From 8dfc59be13b8c6cbd7705f41330418a299a6bd4b Mon Sep 17 00:00:00 2001 From: Martin Liu Date: Wed, 12 Nov 2025 18:36:56 -0500 Subject: [PATCH 0001/1060] Include pts in incoming video and audio frames --- src/pipecat/transports/smallwebrtc/transport.py | 3 +++ 1 file changed, 3 insertions(+) diff --git a/src/pipecat/transports/smallwebrtc/transport.py b/src/pipecat/transports/smallwebrtc/transport.py index 0e2ea544e..e8e0a4ae9 100644 --- a/src/pipecat/transports/smallwebrtc/transport.py +++ b/src/pipecat/transports/smallwebrtc/transport.py @@ -332,6 +332,7 @@ class SmallWebRTCClient: format="RGB", ) image_frame.transport_source = video_source + image_frame.pts = frame.pts del frame # free original VideoFrame del image_bytes # reference kept in image_frame @@ -379,6 +380,7 @@ class SmallWebRTCClient: sample_rate=resampled_frame.sample_rate, num_channels=self._audio_in_channels, ) + audio_frame.pts = frame.pts del pcm_bytes # reference kept in audio_frame yield audio_frame @@ -393,6 +395,7 @@ class SmallWebRTCClient: sample_rate=frame.sample_rate, num_channels=self._audio_in_channels, ) + audio_frame.pts = frame.pts del pcm_bytes # reference kept in audio_frame yield audio_frame From 1ceb01665fff846560fe4679521639985303878b Mon Sep 17 00:00:00 2001 From: Om Chauhan Date: Sun, 4 Jan 2026 11:04:30 +0530 Subject: [PATCH 0002/1060] fix: treat language as first-class STT setting --- src/pipecat/services/stt_service.py | 2 ++ 1 file changed, 2 insertions(+) diff --git a/src/pipecat/services/stt_service.py b/src/pipecat/services/stt_service.py index 6c5741bfe..953ae8dc8 100644 --- a/src/pipecat/services/stt_service.py +++ b/src/pipecat/services/stt_service.py @@ -152,6 +152,8 @@ class STTService(AIService): self._settings[key] = value if key == "language": await self.set_language(value) + elif key == "language": + await self.set_language(value) elif key == "model": self.set_model_name(value) else: From 4fe0836cf9619852c3505f193b28f0fe1d8b4bef Mon Sep 17 00:00:00 2001 From: Mark Backman Date: Fri, 9 Jan 2026 09:00:36 -0500 Subject: [PATCH 0003/1060] Add reconnect logic to WebsocketService in the event of ConnectionClosedError --- src/pipecat/services/websocket_service.py | 15 ++++++++++++--- 1 file changed, 12 insertions(+), 3 deletions(-) diff --git a/src/pipecat/services/websocket_service.py b/src/pipecat/services/websocket_service.py index e9b93af65..d23079bd6 100644 --- a/src/pipecat/services/websocket_service.py +++ b/src/pipecat/services/websocket_service.py @@ -138,9 +138,18 @@ class WebsocketService(ABC): logger.debug(f"{self} connection closed normally: {e}") break except ConnectionClosedError as e: - # Error closure, don't retry - logger.warning(f"{self} connection closed, but with an error: {e}") - break + # Connection closed with error (e.g., no close frame received/sent) + # This often indicates network issues, server problems, or abrupt disconnection + message = f"{self} connection closed, but with an error: {e}" + logger.warning(message) + + if self._reconnect_on_error: + success = await self._try_reconnect(report_error=report_error) + if not success: + break + else: + await report_error(ErrorFrame(message)) + break except Exception as e: message = f"{self} error receiving messages: {e}" logger.error(message) From 9c81acb159995d5e93b7a04b3eba7e8e37f5b63c Mon Sep 17 00:00:00 2001 From: Mark Backman Date: Fri, 9 Jan 2026 16:48:51 -0500 Subject: [PATCH 0004/1060] Track websocket disconnecting status to improve error handling --- src/pipecat/services/assemblyai/stt.py | 4 ++++ src/pipecat/services/asyncai/tts.py | 4 ++++ src/pipecat/services/aws/stt.py | 4 ++++ src/pipecat/services/cartesia/stt.py | 4 ++++ src/pipecat/services/cartesia/tts.py | 4 ++++ src/pipecat/services/deepgram/flux/stt.py | 4 ++++ src/pipecat/services/deepgram/tts.py | 4 ++++ src/pipecat/services/elevenlabs/stt.py | 4 ++++ src/pipecat/services/elevenlabs/tts.py | 4 ++++ src/pipecat/services/fish/tts.py | 4 ++++ src/pipecat/services/gladia/stt.py | 4 ++++ src/pipecat/services/gradium/stt.py | 4 ++++ src/pipecat/services/gradium/tts.py | 4 ++++ src/pipecat/services/inworld/tts.py | 4 ++++ src/pipecat/services/lmnt/tts.py | 4 ++++ src/pipecat/services/neuphonic/tts.py | 4 ++++ src/pipecat/services/playht/tts.py | 4 ++++ src/pipecat/services/rime/tts.py | 8 +++++++ src/pipecat/services/sarvam/tts.py | 4 ++++ src/pipecat/services/soniox/stt.py | 4 ++++ src/pipecat/services/websocket_service.py | 28 +++++++++++++++-------- 21 files changed, 102 insertions(+), 10 deletions(-) diff --git a/src/pipecat/services/assemblyai/stt.py b/src/pipecat/services/assemblyai/stt.py index f54b4ff80..3fde9491c 100644 --- a/src/pipecat/services/assemblyai/stt.py +++ b/src/pipecat/services/assemblyai/stt.py @@ -198,6 +198,8 @@ class AssemblyAISTTService(WebsocketSTTService): Establishes websocket connection and starts receive task. """ + await super()._connect() + await self._connect_websocket() if self._websocket and not self._receive_task: @@ -208,6 +210,8 @@ class AssemblyAISTTService(WebsocketSTTService): Sends termination message, waits for acknowledgment, and cleans up. """ + await super()._disconnect() + if not self._connected or not self._websocket: return diff --git a/src/pipecat/services/asyncai/tts.py b/src/pipecat/services/asyncai/tts.py index a838e2465..303369205 100644 --- a/src/pipecat/services/asyncai/tts.py +++ b/src/pipecat/services/asyncai/tts.py @@ -201,6 +201,8 @@ class AsyncAITTSService(InterruptibleTTSService): await self._disconnect() async def _connect(self): + await super()._connect() + await self._connect_websocket() if self._websocket and not self._receive_task: @@ -210,6 +212,8 @@ class AsyncAITTSService(InterruptibleTTSService): self._keepalive_task = self.create_task(self._keepalive_task_handler()) async def _disconnect(self): + await super()._disconnect() + if self._receive_task: await self.cancel_task(self._receive_task) self._receive_task = None diff --git a/src/pipecat/services/aws/stt.py b/src/pipecat/services/aws/stt.py index 915213e51..2ad350a96 100644 --- a/src/pipecat/services/aws/stt.py +++ b/src/pipecat/services/aws/stt.py @@ -170,6 +170,8 @@ class AWSTranscribeSTTService(WebsocketSTTService): Establishes websocket connection and starts receive task. """ + await super()._connect() + await self._connect_websocket() if self._websocket and not self._receive_task: @@ -180,6 +182,8 @@ class AWSTranscribeSTTService(WebsocketSTTService): Sends end-stream message and cleans up. """ + await super()._disconnect() + if self._receive_task: await self.cancel_task(self._receive_task) self._receive_task = None diff --git a/src/pipecat/services/cartesia/stt.py b/src/pipecat/services/cartesia/stt.py index 386d8cbbc..625df6366 100644 --- a/src/pipecat/services/cartesia/stt.py +++ b/src/pipecat/services/cartesia/stt.py @@ -245,12 +245,16 @@ class CartesiaSTTService(WebsocketSTTService): yield None async def _connect(self): + await super()._connect() + await self._connect_websocket() if self._websocket and not self._receive_task: self._receive_task = self.create_task(self._receive_task_handler(self._report_error)) async def _disconnect(self): + await super()._disconnect() + if self._receive_task: await self.cancel_task(self._receive_task) self._receive_task = None diff --git a/src/pipecat/services/cartesia/tts.py b/src/pipecat/services/cartesia/tts.py index 3ed3ca556..6bfb8703d 100644 --- a/src/pipecat/services/cartesia/tts.py +++ b/src/pipecat/services/cartesia/tts.py @@ -483,12 +483,16 @@ class CartesiaTTSService(AudioContextWordTTSService): await self._disconnect() async def _connect(self): + await super()._connect() + await self._connect_websocket() if self._websocket and not self._receive_task: self._receive_task = self.create_task(self._receive_task_handler(self._report_error)) async def _disconnect(self): + await super()._disconnect() + if self._receive_task: await self.cancel_task(self._receive_task) self._receive_task = None diff --git a/src/pipecat/services/deepgram/flux/stt.py b/src/pipecat/services/deepgram/flux/stt.py index cc2df29e2..13b72bcf7 100644 --- a/src/pipecat/services/deepgram/flux/stt.py +++ b/src/pipecat/services/deepgram/flux/stt.py @@ -194,6 +194,8 @@ class DeepgramFluxSTTService(WebsocketSTTService): Establishes the WebSocket connection to the Deepgram Flux API and starts the background task for receiving transcription results. """ + await super()._connect() + await self._connect_websocket() async def _disconnect(self): @@ -202,6 +204,8 @@ class DeepgramFluxSTTService(WebsocketSTTService): Gracefully disconnects from the Deepgram Flux API, cancels background tasks, and cleans up resources to prevent memory leaks. """ + await super()._disconnect() + try: await self._disconnect_websocket() except Exception as e: diff --git a/src/pipecat/services/deepgram/tts.py b/src/pipecat/services/deepgram/tts.py index e1688a90c..ec41baf26 100644 --- a/src/pipecat/services/deepgram/tts.py +++ b/src/pipecat/services/deepgram/tts.py @@ -147,6 +147,8 @@ class DeepgramTTSService(WebsocketTTSService): async def _connect(self): """Connect to Deepgram WebSocket and start receive task.""" + await super()._connect() + await self._connect_websocket() if self._websocket and not self._receive_task: @@ -154,6 +156,8 @@ class DeepgramTTSService(WebsocketTTSService): async def _disconnect(self): """Disconnect from Deepgram WebSocket and clean up tasks.""" + await super()._disconnect() + if self._receive_task: await self.cancel_task(self._receive_task) self._receive_task = None diff --git a/src/pipecat/services/elevenlabs/stt.py b/src/pipecat/services/elevenlabs/stt.py index 4d26e2f81..8f9020aa7 100644 --- a/src/pipecat/services/elevenlabs/stt.py +++ b/src/pipecat/services/elevenlabs/stt.py @@ -605,6 +605,8 @@ class ElevenLabsRealtimeSTTService(WebsocketSTTService): async def _connect(self): """Establish WebSocket connection to ElevenLabs Realtime STT.""" + await super()._connect() + await self._connect_websocket() if self._websocket and not self._receive_task: @@ -612,6 +614,8 @@ class ElevenLabsRealtimeSTTService(WebsocketSTTService): async def _disconnect(self): """Close WebSocket connection and cleanup tasks.""" + await super()._disconnect() + if self._receive_task: await self.cancel_task(self._receive_task) self._receive_task = None diff --git a/src/pipecat/services/elevenlabs/tts.py b/src/pipecat/services/elevenlabs/tts.py index dca462ce4..02ccd0ab3 100644 --- a/src/pipecat/services/elevenlabs/tts.py +++ b/src/pipecat/services/elevenlabs/tts.py @@ -478,6 +478,8 @@ class ElevenLabsTTSService(AudioContextWordTTSService): await self.add_word_timestamps([("Reset", 0)]) async def _connect(self): + await super()._connect() + await self._connect_websocket() if self._websocket and not self._receive_task: @@ -487,6 +489,8 @@ class ElevenLabsTTSService(AudioContextWordTTSService): self._keepalive_task = self.create_task(self._keepalive_task_handler()) async def _disconnect(self): + await super()._disconnect() + if self._receive_task: await self.cancel_task(self._receive_task) self._receive_task = None diff --git a/src/pipecat/services/fish/tts.py b/src/pipecat/services/fish/tts.py index dfa161066..357b82346 100644 --- a/src/pipecat/services/fish/tts.py +++ b/src/pipecat/services/fish/tts.py @@ -199,12 +199,16 @@ class FishAudioTTSService(InterruptibleTTSService): await self._disconnect() async def _connect(self): + await super()._connect() + await self._connect_websocket() if self._websocket and not self._receive_task: self._receive_task = self.create_task(self._receive_task_handler(self._report_error)) async def _disconnect(self): + await super()._disconnect() + if self._receive_task: await self.cancel_task(self._receive_task) self._receive_task = None diff --git a/src/pipecat/services/gladia/stt.py b/src/pipecat/services/gladia/stt.py index 48334ef8c..4ba0a2ffd 100644 --- a/src/pipecat/services/gladia/stt.py +++ b/src/pipecat/services/gladia/stt.py @@ -404,6 +404,8 @@ class GladiaSTTService(WebsocketSTTService): Initializes the session if needed and establishes websocket connection. """ + await super()._connect() + # Initialize session if needed if not self._session_url: settings = self._prepare_settings() @@ -425,6 +427,8 @@ class GladiaSTTService(WebsocketSTTService): Cleans up tasks and closes websocket connection. """ + await super()._disconnect() + self._connection_active = False if self._keepalive_task: diff --git a/src/pipecat/services/gradium/stt.py b/src/pipecat/services/gradium/stt.py index f869983d3..b66b18070 100644 --- a/src/pipecat/services/gradium/stt.py +++ b/src/pipecat/services/gradium/stt.py @@ -141,6 +141,8 @@ class GradiumSTTService(WebsocketSTTService): pass async def _connect(self): + await super()._connect() + await self._connect_websocket() if self._websocket and not self._receive_task: @@ -179,6 +181,8 @@ class GradiumSTTService(WebsocketSTTService): raise async def _disconnect(self): + await super()._disconnect() + if self._receive_task: await self.cancel_task(self._receive_task) self._receive_task = None diff --git a/src/pipecat/services/gradium/tts.py b/src/pipecat/services/gradium/tts.py index 3baaa887c..14e093541 100644 --- a/src/pipecat/services/gradium/tts.py +++ b/src/pipecat/services/gradium/tts.py @@ -157,6 +157,8 @@ class GradiumTTSService(InterruptibleWordTTSService): async def _connect(self): """Establish websocket connection and start receive task.""" + await super()._connect() + logger.debug(f"{self}: connecting") # If the server disconnected, cancel the receive-task so that it can be reset below. @@ -173,6 +175,8 @@ class GradiumTTSService(InterruptibleWordTTSService): async def _disconnect(self): """Close websocket connection and clean up tasks.""" + await super()._disconnect() + logger.debug(f"{self}: disconnecting") if self._receive_task: await self.cancel_task(self._receive_task) diff --git a/src/pipecat/services/inworld/tts.py b/src/pipecat/services/inworld/tts.py index fddb96602..ffac22464 100644 --- a/src/pipecat/services/inworld/tts.py +++ b/src/pipecat/services/inworld/tts.py @@ -605,6 +605,8 @@ class InworldTTSService(AudioContextWordTTSService): Returns: The websocket. """ + await super()._connect() + await self._connect_websocket() if self._websocket and not self._receive_task: self._receive_task = self.create_task(self._receive_task_handler(self._report_error)) @@ -615,6 +617,8 @@ class InworldTTSService(AudioContextWordTTSService): Returns: The websocket. """ + await super()._disconnect() + if self._receive_task: await self.cancel_task(self._receive_task) self._receive_task = None diff --git a/src/pipecat/services/lmnt/tts.py b/src/pipecat/services/lmnt/tts.py index b6a50aa9a..911d13923 100644 --- a/src/pipecat/services/lmnt/tts.py +++ b/src/pipecat/services/lmnt/tts.py @@ -175,6 +175,8 @@ class LmntTTSService(InterruptibleTTSService): async def _connect(self): """Connect to LMNT WebSocket and start receive task.""" + await super()._connect() + await self._connect_websocket() if self._websocket and not self._receive_task: @@ -182,6 +184,8 @@ class LmntTTSService(InterruptibleTTSService): async def _disconnect(self): """Disconnect from LMNT WebSocket and clean up tasks.""" + await super()._disconnect() + if self._receive_task: await self.cancel_task(self._receive_task) self._receive_task = None diff --git a/src/pipecat/services/neuphonic/tts.py b/src/pipecat/services/neuphonic/tts.py index 44e00dd09..2666c0cfc 100644 --- a/src/pipecat/services/neuphonic/tts.py +++ b/src/pipecat/services/neuphonic/tts.py @@ -237,6 +237,8 @@ class NeuphonicTTSService(InterruptibleTTSService): async def _connect(self): """Connect to Neuphonic WebSocket and start background tasks.""" + await super()._connect() + await self._connect_websocket() if self._websocket and not self._receive_task: @@ -247,6 +249,8 @@ class NeuphonicTTSService(InterruptibleTTSService): async def _disconnect(self): """Disconnect from Neuphonic WebSocket and clean up tasks.""" + await super()._disconnect() + if self._receive_task: await self.cancel_task(self._receive_task) self._receive_task = None diff --git a/src/pipecat/services/playht/tts.py b/src/pipecat/services/playht/tts.py index 1e9f83500..bc9dd4859 100644 --- a/src/pipecat/services/playht/tts.py +++ b/src/pipecat/services/playht/tts.py @@ -231,6 +231,8 @@ class PlayHTTTSService(InterruptibleTTSService): async def _connect(self): """Connect to PlayHT WebSocket and start receive task.""" + await super()._connect() + await self._connect_websocket() if self._websocket and not self._receive_task: @@ -238,6 +240,8 @@ class PlayHTTTSService(InterruptibleTTSService): async def _disconnect(self): """Disconnect from PlayHT WebSocket and clean up tasks.""" + await super()._disconnect() + if self._receive_task: await self.cancel_task(self._receive_task) self._receive_task = None diff --git a/src/pipecat/services/rime/tts.py b/src/pipecat/services/rime/tts.py index 6018730b6..b6fe25e0e 100644 --- a/src/pipecat/services/rime/tts.py +++ b/src/pipecat/services/rime/tts.py @@ -278,6 +278,8 @@ class RimeTTSService(AudioContextWordTTSService): async def _connect(self): """Establish websocket connection and start receive task.""" + await super()._connect() + await self._connect_websocket() if self._websocket and not self._receive_task: @@ -285,6 +287,8 @@ class RimeTTSService(AudioContextWordTTSService): async def _disconnect(self): """Close websocket connection and clean up tasks.""" + await super()._disconnect() + if self._receive_task: await self.cancel_task(self._receive_task) self._receive_task = None @@ -767,12 +771,16 @@ class RimeNonJsonTTSService(InterruptibleTTSService): async def _connect(self): """Establish WebSocket connection and start receive task.""" + await super()._connect() + await self._connect_websocket() if self._websocket and not self._receive_task: self._receive_task = self.create_task(self._receive_task_handler(self._report_error)) async def _disconnect(self): """Close WebSocket connection and clean up tasks.""" + await super()._disconnect() + if self._receive_task: await self.cancel_task(self._receive_task) self._receive_task = None diff --git a/src/pipecat/services/sarvam/tts.py b/src/pipecat/services/sarvam/tts.py index 2837b3e20..cef228b84 100644 --- a/src/pipecat/services/sarvam/tts.py +++ b/src/pipecat/services/sarvam/tts.py @@ -532,6 +532,8 @@ class SarvamTTSService(InterruptibleTTSService): async def _connect(self): """Connect to Sarvam WebSocket and start background tasks.""" + await super()._connect() + await self._connect_websocket() if self._websocket and not self._receive_task: @@ -544,6 +546,8 @@ class SarvamTTSService(InterruptibleTTSService): async def _disconnect(self): """Disconnect from Sarvam WebSocket and clean up tasks.""" + await super()._disconnect() + try: # First, set a flag to prevent new operations self._disconnecting = True diff --git a/src/pipecat/services/soniox/stt.py b/src/pipecat/services/soniox/stt.py index 34b4bc396..476ae0762 100644 --- a/src/pipecat/services/soniox/stt.py +++ b/src/pipecat/services/soniox/stt.py @@ -264,6 +264,8 @@ class SonioxSTTService(WebsocketSTTService): Establishes websocket connection and starts receive and keepalive tasks. """ + await super()._connect() + await self._connect_websocket() if self._websocket and not self._receive_task: @@ -277,6 +279,8 @@ class SonioxSTTService(WebsocketSTTService): Cleans up tasks and closes websocket connection. """ + await super()._disconnect() + if self._keepalive_task: await self.cancel_task(self._keepalive_task) self._keepalive_task = None diff --git a/src/pipecat/services/websocket_service.py b/src/pipecat/services/websocket_service.py index d23079bd6..2c5f05528 100644 --- a/src/pipecat/services/websocket_service.py +++ b/src/pipecat/services/websocket_service.py @@ -36,7 +36,8 @@ class WebsocketService(ABC): """ self._websocket: Optional[websockets.WebSocketClientProtocol] = None self._reconnect_on_error = reconnect_on_error - self._reconnect_in_progress: bool = False # Add this flag + self._reconnect_in_progress: bool = False + self._disconnecting: bool = False async def _verify_connection(self) -> bool: """Verify the websocket connection is active and responsive. @@ -138,6 +139,11 @@ class WebsocketService(ABC): logger.debug(f"{self} connection closed normally: {e}") break except ConnectionClosedError as e: + # Don't reconnect if we're intentionally disconnecting + if self._disconnecting: + logger.warning(f"{self} connection closed with an error during disconnect: {e}") + break + # Connection closed with error (e.g., no close frame received/sent) # This often indicates network issues, server problems, or abrupt disconnection message = f"{self} connection closed, but with an error: {e}" @@ -162,23 +168,25 @@ class WebsocketService(ABC): await report_error(ErrorFrame(message)) break - @abstractmethod async def _connect(self): - """Connect to the service. + """Connect to the service and reset disconnecting flag. - Implement service-specific connection logic including websocket connection - via _connect_websocket() and any additional setup required. + Manages the disconnecting flag to enable reconnection. Subclasses should + call super()._connect() first, then implement their specific connection + logic including websocket connection via _connect_websocket() and any + additional setup required. """ - pass + self._disconnecting = False - @abstractmethod async def _disconnect(self): - """Disconnect from the service. + """Disconnect from the service and set disconnecting flag. - Implement service-specific disconnection logic including websocket + Manages the disconnecting flag to prevent reconnection during intentional + disconnect. Subclasses should call super()._disconnect() first, then + implement their specific disconnection logic including websocket disconnection via _disconnect_websocket() and any cleanup required. """ - pass + self._disconnecting = True @abstractmethod async def _connect_websocket(self): From aac24ad2d4f3c7808a414f7159593d2397b7c8a6 Mon Sep 17 00:00:00 2001 From: Mark Backman Date: Sat, 10 Jan 2026 11:18:35 -0500 Subject: [PATCH 0005/1060] InworldTTSService: Add keepalive task --- changelog/3403.added.md | 1 + src/pipecat/services/inworld/tts.py | 41 +++++++++++++++++++++++++++++ 2 files changed, 42 insertions(+) create mode 100644 changelog/3403.added.md diff --git a/changelog/3403.added.md b/changelog/3403.added.md new file mode 100644 index 000000000..6b55ef97d --- /dev/null +++ b/changelog/3403.added.md @@ -0,0 +1 @@ +- Added a keepalive task for `InworldTTSService` to keep the service connected in the event of no generations for longer periods of time. diff --git a/src/pipecat/services/inworld/tts.py b/src/pipecat/services/inworld/tts.py index fddb96602..c3dbce1eb 100644 --- a/src/pipecat/services/inworld/tts.py +++ b/src/pipecat/services/inworld/tts.py @@ -13,12 +13,14 @@ Contains two TTS services: Inworld’s text-to-speech (TTS) models offer ultra-realistic, context-aware speech synthesis and precise voice cloning capabilities, enabling developers to build natural and engaging experiences with human-like speech quality at an accessible price point. """ +import asyncio import base64 import json import uuid from typing import Any, AsyncGenerator, Dict, List, Optional, Tuple import aiohttp +import websockets from loguru import logger from pydantic import BaseModel @@ -479,6 +481,7 @@ class InworldTTSService(AudioContextWordTTSService): } self._receive_task = None + self._keepalive_task = None self._context_id = None self._started = False @@ -606,9 +609,13 @@ class InworldTTSService(AudioContextWordTTSService): The websocket. """ await self._connect_websocket() + if self._websocket and not self._receive_task: self._receive_task = self.create_task(self._receive_task_handler(self._report_error)) + if self._websocket and not self._keepalive_task: + self._keepalive_task = self.create_task(self._keepalive_task_handler()) + async def _disconnect(self): """Disconnect from the Inworld WebSocket TTS service. @@ -619,6 +626,10 @@ class InworldTTSService(AudioContextWordTTSService): await self.cancel_task(self._receive_task) self._receive_task = None + if self._keepalive_task: + await self.cancel_task(self._keepalive_task) + self._keepalive_task = None + await self._disconnect_websocket() async def _connect_websocket(self): @@ -693,6 +704,15 @@ class InworldTTSService(AudioContextWordTTSService): status = result.get("status", {}) if status.get("code", 0) != 0: error_msg = status.get("message", "Unknown error") + error_code = status.get("code") + + # Handle "Context not found" error (code 5) + # This can happen when a keepalive message is sent but no context is available. + if error_code == 5 and "not found" in error_msg.lower(): + logger.debug(f"{self}: Context {ctx_id or self._context_id} not found.") + continue + + # For other errors, push error frame await self.push_error(error_msg=f"Inworld API error: {error_msg}") continue @@ -757,6 +777,27 @@ class InworldTTSService(AudioContextWordTTSService): await self.remove_audio_context(ctx_id) await self.add_word_timestamps([("TTSStoppedFrame", 0), ("Reset", 0)]) + async def _keepalive_task_handler(self): + """Send periodic keepalive messages to maintain WebSocket connection.""" + KEEPALIVE_SLEEP = 60 + while True: + await asyncio.sleep(KEEPALIVE_SLEEP) + try: + if self._websocket and self._websocket.state is State.OPEN: + if self._context_id: + keepalive_message = { + "send_text": {"text": ""}, + "contextId": self._context_id, + } + logger.trace(f"Sending keepalive for context {self._context_id}") + else: + keepalive_message = {"send_text": {"text": ""}} + logger.trace("Sending keepalive without context") + await self._websocket.send(json.dumps(keepalive_message)) + except websockets.ConnectionClosed as e: + logger.warning(f"{self} keepalive error: {e}") + break + async def _send_context(self, context_id: str): """Send a context to the Inworld WebSocket TTS service. From 38506f51f7936902d2411530fd4a338dc8d83a43 Mon Sep 17 00:00:00 2001 From: Om Chauhan Date: Sun, 11 Jan 2026 21:19:47 +0530 Subject: [PATCH 0006/1060] fix(openrouter): handle multiple system messages for Gemini models --- src/pipecat/services/openrouter/llm.py | 34 +++++++++++++++++++++++++- 1 file changed, 33 insertions(+), 1 deletion(-) diff --git a/src/pipecat/services/openrouter/llm.py b/src/pipecat/services/openrouter/llm.py index 62992eb23..a86b18573 100644 --- a/src/pipecat/services/openrouter/llm.py +++ b/src/pipecat/services/openrouter/llm.py @@ -10,7 +10,7 @@ This module provides an OpenAI-compatible interface for interacting with OpenRou extending the base OpenAI LLM service functionality. """ -from typing import Optional +from typing import Any, Dict, Optional from loguru import logger @@ -61,3 +61,35 @@ class OpenRouterLLMService(OpenAILLMService): """ logger.debug(f"Creating OpenRouter client with api {base_url}") return super().create_client(api_key, base_url, **kwargs) + + def build_chat_completion_params(self, params_from_context: Dict[str, Any]) -> Dict[str, Any]: + """Builds chat parameters, handling model-specific constraints. + + Args: + params_from_context: Parameters from the LLM context. + + Returns: + Transformed parameters ready for the API call. + """ + params = super().build_chat_completion_params(params_from_context) + model = getattr(self, "model_name", getattr(self, "model", "")).lower() + if "gemini" in model: + messages = params.get("messages", []) + if not messages: + return params + transformed_messages = [] + system_message_seen = False + for msg in messages: + if msg.get("role") == "system": + if not system_message_seen: + transformed_messages.append(msg) + system_message_seen = True + else: + new_msg = msg.copy() + new_msg["role"] = "user" + transformed_messages.append(new_msg) + else: + transformed_messages.append(msg) + params["messages"] = transformed_messages + + return params From f58d21862beab8af4f8b202af92f4bfa359149db Mon Sep 17 00:00:00 2001 From: Mark Backman Date: Sun, 11 Jan 2026 16:43:37 -0500 Subject: [PATCH 0007/1060] WebsocketService: Add _maybe_try_reconnect and use for exception cases --- src/pipecat/services/websocket_service.py | 59 +++++++++++++++-------- 1 file changed, 38 insertions(+), 21 deletions(-) diff --git a/src/pipecat/services/websocket_service.py b/src/pipecat/services/websocket_service.py index 2c5f05528..e86dee73f 100644 --- a/src/pipecat/services/websocket_service.py +++ b/src/pipecat/services/websocket_service.py @@ -121,6 +121,39 @@ class WebsocketService(ABC): else: logger.error(f"{self} send failed; unable to reconnect") + async def _maybe_try_reconnect( + self, + error: Exception, + error_message: str, + report_error: Callable[[ErrorFrame], Awaitable[None]], + ) -> bool: + """Check if reconnection should be attempted and try if appropriate. + + Args: + error: The exception that occurred. + error_message: Human-readable error message for logging. + report_error: Callback function to report connection errors. + + Returns: + True if should continue the receive loop, False if should break. + """ + # Don't reconnect if we're intentionally disconnecting + if self._disconnecting: + logger.warning(f"{self} error during disconnect: {error}") + return False + + # Log the error + logger.warning(error_message) + + # Try to reconnect if enabled + if self._reconnect_on_error: + success = await self._try_reconnect(report_error=report_error) + return success + else: + # Reconnection disabled + await report_error(ErrorFrame(error_message)) + return False + async def _receive_task_handler(self, report_error: Callable[[ErrorFrame], Awaitable[None]]): """Handle websocket message receiving with automatic retry logic. @@ -139,33 +172,17 @@ class WebsocketService(ABC): logger.debug(f"{self} connection closed normally: {e}") break except ConnectionClosedError as e: - # Don't reconnect if we're intentionally disconnecting - if self._disconnecting: - logger.warning(f"{self} connection closed with an error during disconnect: {e}") - break - # Connection closed with error (e.g., no close frame received/sent) # This often indicates network issues, server problems, or abrupt disconnection message = f"{self} connection closed, but with an error: {e}" - logger.warning(message) - - if self._reconnect_on_error: - success = await self._try_reconnect(report_error=report_error) - if not success: - break - else: - await report_error(ErrorFrame(message)) + should_continue = await self._maybe_try_reconnect(e, message, report_error) + if not should_continue: break except Exception as e: + # General error during message receiving message = f"{self} error receiving messages: {e}" - logger.error(message) - - if self._reconnect_on_error: - success = await self._try_reconnect(report_error=report_error) - if not success: - break - else: - await report_error(ErrorFrame(message)) + should_continue = await self._maybe_try_reconnect(e, message, report_error) + if not should_continue: break async def _connect(self): From e96595fe59a41109c9f722f2999ad7127584386f Mon Sep 17 00:00:00 2001 From: Varun Pratap Singh Date: Mon, 12 Jan 2026 17:50:38 +0530 Subject: [PATCH 0008/1060] feat: update FastAPI WebSocket transport and add Vonage serializer --- src/pipecat/serializers/vonage.py | 182 ++++++++++++++++++++ src/pipecat/transports/websocket/fastapi.py | 30 ++++ 2 files changed, 212 insertions(+) create mode 100644 src/pipecat/serializers/vonage.py diff --git a/src/pipecat/serializers/vonage.py b/src/pipecat/serializers/vonage.py new file mode 100644 index 000000000..9de1cc038 --- /dev/null +++ b/src/pipecat/serializers/vonage.py @@ -0,0 +1,182 @@ +# +# Copyright (c) 2024–2025, Daily +# +# SPDX-License-Identifier: BSD 2-Clause License +# + +"""Vonage Audio Connector WebSocket serializer for Pipecat.""" + +import json +from typing import Optional + +from loguru import logger +from pydantic import BaseModel + +from pipecat.audio.dtmf.types import KeypadEntry +from pipecat.audio.utils import create_stream_resampler +from pipecat.frames.frames import ( + AudioRawFrame, + Frame, + InputAudioRawFrame, + InputDTMFFrame, + InterruptionFrame, + OutputTransportMessageFrame, + OutputTransportMessageUrgentFrame, + StartFrame, +) +from pipecat.serializers.base_serializer import FrameSerializer + + +class VonageFrameSerializer(FrameSerializer): + """Serializer for Vonage Video API Audio Connector WebSocket protocol. + + This serializer converts between Pipecat frames and the Vonage Audio Connector + WebSocket streaming protocol. + + Note: + Ref docs: + https://developer.vonage.com/en/video/guides/audio-connector + """ + + class InputParams(BaseModel): + """Configuration parameters for VonageFrameSerializer. + + Parameters: + vonage_sample_rate: Sample rate used by Vonage, defaults to 16000 Hz. + Common values: 8000, 16000, 24000 Hz. + sample_rate: Optional override for pipeline input sample rate. + """ + + vonage_sample_rate: int = 16000 + sample_rate: Optional[int] = None + + def __init__(self, params: Optional[InputParams] = None): + """Initialize the VonageFrameSerializer. + + Args: + params: Configuration parameters. + """ + self._params = params or VonageFrameSerializer.InputParams() + + self._vonage_sample_rate = self._params.vonage_sample_rate + self._sample_rate = 0 # Pipeline input rate + + self._input_resampler = create_stream_resampler() + self._output_resampler = create_stream_resampler() + + async def setup(self, frame: StartFrame): + """Sets up the serializer with pipeline configuration. + + Args: + frame: The StartFrame containing pipeline configuration. + """ + self._sample_rate = self._params.sample_rate or frame.audio_in_sample_rate + + async def serialize(self, frame: Frame) -> str | bytes | None: + """Serializes a Pipecat frame to Vonage WebSocket format. + + Handles conversion of various frame types to Vonage WebSocket messages. + + Args: + frame: The Pipecat frame to serialize. + + Returns: + Serialized data as string (JSON commands) or bytes (audio), or None if the frame isn't handled. + """ + if isinstance(frame, InterruptionFrame): + # Clear the audio buffer to stop playback immediately + answer = {"action": "clear"} + return json.dumps(answer) + elif isinstance(frame, AudioRawFrame): + data = frame.audio + + # Output: Convert PCM at frame's rate to Vonage's sample rate (16-bit linear PCM) + serialized_data = await self._output_resampler.resample( + data, frame.sample_rate, self._vonage_sample_rate + ) + if serialized_data is None or len(serialized_data) == 0: + # Ignoring in case we don't have audio + return None + + # Vonage expects raw binary PCM data (not base64 encoded) + return serialized_data + elif isinstance(frame, (OutputTransportMessageFrame, OutputTransportMessageUrgentFrame)): + # Allow sending custom JSON commands (e.g., notify) + return json.dumps(frame.message) + + return None + + async def deserialize(self, data: str | bytes) -> Frame | None: + """Deserializes Vonage WebSocket data to Pipecat frames. + + Handles conversion of Vonage events to appropriate Pipecat frames. + - Binary messages contain audio data (16-bit linear PCM) + - Text messages contain JSON events (websocket:connected, websocket:cleared, dtmf, etc.) + + Args: + data: The raw WebSocket data from Vonage. + + Returns: + A Pipecat frame corresponding to the Vonage event, or None if unhandled. + """ + # Check if this is binary audio data + if isinstance(data, bytes): + # Binary message = audio data (16-bit linear PCM) + payload = data + + # Input: Convert Vonage's PCM audio to pipeline sample rate + deserialized_data = await self._input_resampler.resample( + payload, + self._vonage_sample_rate, + self._sample_rate, + ) + if deserialized_data is None or len(deserialized_data) == 0: + # Ignoring in case we don't have audio + return None + + audio_frame = InputAudioRawFrame( + audio=deserialized_data, + num_channels=1, # Vonage uses mono audio + sample_rate=self._sample_rate, # Use the configured pipeline input rate + ) + return audio_frame + else: + # Text message = JSON event + try: + message = json.loads(data) + event = message.get("event") + + # Handle different event types + if event == "websocket:connected": + logger.debug( + f"Vonage WebSocket connected: content-type={message.get('content-type')}" + ) + return None + elif event == "websocket:cleared": + logger.debug("Vonage audio buffer cleared") + return None + elif event == "websocket:notify": + logger.debug(f"Vonage notify event: {message.get('payload')}") + return None + elif event == "websocket:dtmf": + # Handle DTMF input + # Vonage may send digit in different formats, try both + digit = message.get("digit") or message.get("dtmf", {}).get("digit") + if digit is None: + logger.warning(f"DTMF event received but no digit found: {message}") + return None + + digit = str(digit) + logger.debug(f"Received DTMF digit: {digit}") + try: + return InputDTMFFrame(KeypadEntry(digit)) + except ValueError: + logger.warning(f"Invalid DTMF digit received: {digit}") + return None + else: + logger.debug(f"Vonage event: {event}") + return None + + except json.JSONDecodeError: + logger.warning(f"Failed to parse JSON message from Vonage: {data}") + return None diff --git a/src/pipecat/transports/websocket/fastapi.py b/src/pipecat/transports/websocket/fastapi.py index 1bcc59e8b..cffacd932 100644 --- a/src/pipecat/transports/websocket/fastapi.py +++ b/src/pipecat/transports/websocket/fastapi.py @@ -56,11 +56,14 @@ class FastAPIWebsocketParams(TransportParams): add_wav_header: Whether to add WAV headers to audio frames. serializer: Frame serializer for encoding/decoding messages. session_timeout: Session timeout in seconds, None for no timeout. + audio_packet_bytes: Optional fixed-size packetization for raw PCM audio payloads. + Useful when the remote WebSocket media endpoint requires strict audio framing. """ add_wav_header: bool = False serializer: Optional[FrameSerializer] = None session_timeout: Optional[int] = None + audio_packet_bytes: Optional[int] = None class FastAPIWebsocketCallbacks(BaseModel): @@ -360,6 +363,14 @@ class FastAPIWebsocketOutputTransport(BaseOutputTransport): self._send_interval = 0 self._next_send_time = 0 + # Buffer for optional protocol-level audio packetization. + # Some serializers may emit arbitrarily sized raw PCM payloads, while + # certain downstream transports or media endpoints require audio to be + # sent in fixed-size frames. When `params.audio_packet_bytes` is set, + # this buffer accumulates outgoing audio until a full packet can be + # emitted, preserving any remainder for subsequent sends. + self._audio_send_buffer = bytearray() + # Whether we have seen a StartFrame already. self._initialized = False @@ -417,6 +428,10 @@ class FastAPIWebsocketOutputTransport(BaseOutputTransport): await super().process_frame(frame, direction) if isinstance(frame, InterruptionFrame): + # Drop any partially buffered audio to avoid replaying stale PCM + if self._params.audio_packet_bytes: + self._audio_send_buffer.clear() + await self._write_frame(frame) self._next_send_time = 0 @@ -480,6 +495,21 @@ class FastAPIWebsocketOutputTransport(BaseOutputTransport): try: payload = await self._params.serializer.serialize(frame) if payload: + # Optional protocol-level audio packetization: + # If a downstream WebSocket media endpoint requires fixed-size PCM frames, + # configure params.audio_packet_bytes (e.g. 640 for 20ms @ 16kHz PCM16 mono). + packet_bytes = self._params.audio_packet_bytes + + if packet_bytes and isinstance(payload, (bytes, bytearray)): + self._audio_send_buffer.extend(bytes(payload)) + + # Send only full frames; keep remainder for the next call. + while len(self._audio_send_buffer) >= packet_bytes: + chunk = bytes(self._audio_send_buffer[:packet_bytes]) + del self._audio_send_buffer[:packet_bytes] + await self._client.send(chunk) + return + await self._client.send(payload) except Exception as e: logger.error(f"{self} exception sending data: {e.__class__.__name__} ({e})") From 14a115f37203510309531def9600bd6216fc04ac Mon Sep 17 00:00:00 2001 From: Varun Pratap Singh Date: Mon, 12 Jan 2026 18:12:27 +0530 Subject: [PATCH 0009/1060] changelog: add fragments for PR #3410 --- changelog/3410.added.md | 1 + changelog/3410.changed.md | 1 + 2 files changed, 2 insertions(+) create mode 100644 changelog/3410.added.md create mode 100644 changelog/3410.changed.md diff --git a/changelog/3410.added.md b/changelog/3410.added.md new file mode 100644 index 000000000..094532343 --- /dev/null +++ b/changelog/3410.added.md @@ -0,0 +1 @@ +- Added `VonageFrameSerializer` for the Vonage Video API Audio Connector WebSocket protocol. diff --git a/changelog/3410.changed.md b/changelog/3410.changed.md new file mode 100644 index 000000000..0be207c65 --- /dev/null +++ b/changelog/3410.changed.md @@ -0,0 +1 @@ +- Enhanced `FastAPIWebsocketTransport` with optional protocol-level audio packetization to support media endpoints requiring strict framing and real-time pacing. From 89484e281d8a8500f280b00e2f19d0969cb7f10a Mon Sep 17 00:00:00 2001 From: Mark Backman Date: Mon, 12 Jan 2026 10:11:58 -0500 Subject: [PATCH 0010/1060] Remove foundational examples 41a and 41b --- examples/foundational/41a-text-only-webrtc.py | 164 ---------------- .../foundational/41b-text-and-audio-webrtc.py | 180 ------------------ 2 files changed, 344 deletions(-) delete mode 100644 examples/foundational/41a-text-only-webrtc.py delete mode 100644 examples/foundational/41b-text-and-audio-webrtc.py diff --git a/examples/foundational/41a-text-only-webrtc.py b/examples/foundational/41a-text-only-webrtc.py deleted file mode 100644 index 18ac367b5..000000000 --- a/examples/foundational/41a-text-only-webrtc.py +++ /dev/null @@ -1,164 +0,0 @@ -# -# Copyright (c) 2024-2026, Daily -# -# SPDX-License-Identifier: BSD 2-Clause License -# - -import os - -from dotenv import load_dotenv -from loguru import logger - -from pipecat.frames.frames import ( - LLMMessagesAppendFrame, - LLMRunFrame, -) -from pipecat.pipeline.pipeline import Pipeline -from pipecat.pipeline.runner import PipelineRunner -from pipecat.pipeline.task import PipelineParams, PipelineTask -from pipecat.processors.aggregators.llm_context import LLMContext -from pipecat.processors.aggregators.llm_response_universal import LLMContextAggregatorPair -from pipecat.processors.frameworks.rtvi import ( - ActionResult, - RTVIAction, - RTVIActionArgument, - RTVIConfig, - RTVIObserver, - RTVIProcessor, - RTVIServerMessageFrame, -) -from pipecat.runner.types import RunnerArguments -from pipecat.runner.utils import create_transport -from pipecat.services.openai.llm import OpenAIContextAggregatorPair, OpenAILLMService -from pipecat.transports.base_transport import BaseTransport, TransportParams - -load_dotenv(override=True) - - -# This is an example of a text-only chatbot using small webrtc tranport. -# It uses the small webrtc transport prebuilt web UI. -# https://github.com/pipecat-ai/small-webrtc-prebuilt - - -def create_action_llm_append_to_messages(context_aggregator: OpenAIContextAggregatorPair): - async def action_llm_append_to_messages_handler( - rtvi: RTVIProcessor, service: str, arguments: dict[str, any] - ) -> ActionResult: - run_immediately = arguments["run_immediately"] if "run_immediately" in arguments else True - logger.info(f"run_immediately: {run_immediately}") - if run_immediately: - await rtvi.interrupt_bot() - # We just interrupted the bot so it should be fine to use the - # context directly instead of through frame. - if "messages" in arguments and arguments["messages"]: - frame = LLMMessagesAppendFrame(messages=arguments["messages"]) - await rtvi.push_frame(frame) - - frame = LLMRunFrame() - await rtvi.push_frame(frame) - return True - - action_llm_append_to_messages = RTVIAction( - service="llm", - action="append_to_messages", - result="bool", - arguments=[ - RTVIActionArgument(name="messages", type="array"), - RTVIActionArgument(name="run_immediately", type="bool"), - ], - handler=action_llm_append_to_messages_handler, - ) - return action_llm_append_to_messages - - -# We store functions so objects (e.g. SileroVADAnalyzer) don't get -# instantiated. The function will be called when the desired transport gets -# selected. -transport_params = { - "webrtc": lambda: TransportParams(), -} - - -async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): - logger.info(f"Starting bot") - - llm = OpenAILLMService(api_key=os.getenv("OPENAI_API_KEY")) - - messages = [ - { - "role": "system", - "content": "You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Respond to what the user said in a creative and helpful way.", - }, - ] - - context = LLMContext(messages) - context_aggregator = LLMContextAggregatorPair(context) - - action_llm_append_to_messages = create_action_llm_append_to_messages(context_aggregator) - rtvi = RTVIProcessor(config=RTVIConfig(config=[])) - rtvi.register_action(action_llm_append_to_messages) - - pipeline = Pipeline( - [ - transport.input(), - rtvi, - context_aggregator.user(), - llm, - transport.output(), - context_aggregator.assistant(), - ] - ) - - task = PipelineTask( - pipeline, - params=PipelineParams( - enable_metrics=True, - enable_usage_metrics=True, - ), - idle_timeout_secs=runner_args.pipeline_idle_timeout_secs, - observers=[RTVIObserver(rtvi)], - ) - - @rtvi.event_handler("on_client_ready") - async def on_client_ready(rtvi): - logger.info("Pipecat client ready.") - await rtvi.set_bot_ready() - - # This block is frontend UI specific - # These messages are intended for small webrtc UI to only handle text - # https://github.com/pipecat-ai/small-webrtc-prebuilt - messages = { - "show_text_container": True, - "show_video_container": False, - "show_debug_container": False, - } - - rtvi_frame = RTVIServerMessageFrame(data=messages) - await task.queue_frames([rtvi_frame]) - - @transport.event_handler("on_client_connected") - async def on_client_connected(transport, client): - logger.info(f"Client connected: {client}") - # Kick off the conversation. - await task.queue_frames([LLMRunFrame()]) - - @transport.event_handler("on_client_disconnected") - async def on_client_disconnected(transport, client): - logger.info(f"Client disconnected") - await task.cancel() - - runner = PipelineRunner(handle_sigint=runner_args.handle_sigint) - - await runner.run(task) - - -async def bot(runner_args: RunnerArguments): - """Main bot entry point compatible with Pipecat Cloud.""" - transport = await create_transport(runner_args, transport_params) - await run_bot(transport, runner_args) - - -if __name__ == "__main__": - from pipecat.runner.run import main - - main() diff --git a/examples/foundational/41b-text-and-audio-webrtc.py b/examples/foundational/41b-text-and-audio-webrtc.py deleted file mode 100644 index d98bfdedd..000000000 --- a/examples/foundational/41b-text-and-audio-webrtc.py +++ /dev/null @@ -1,180 +0,0 @@ -# -# Copyright (c) 2024-2026, Daily -# -# SPDX-License-Identifier: BSD 2-Clause License -# - -import os - -from dotenv import load_dotenv -from loguru import logger - -from pipecat.audio.vad.silero import SileroVADAnalyzer -from pipecat.frames.frames import ( - LLMMessagesAppendFrame, - LLMRunFrame, -) -from pipecat.pipeline.pipeline import Pipeline -from pipecat.pipeline.runner import PipelineRunner -from pipecat.pipeline.task import PipelineParams, PipelineTask -from pipecat.processors.aggregators.llm_context import LLMContext -from pipecat.processors.aggregators.llm_response_universal import LLMContextAggregatorPair -from pipecat.processors.frameworks.rtvi import ( - ActionResult, - RTVIAction, - RTVIActionArgument, - RTVIConfig, - RTVIObserver, - RTVIProcessor, - RTVIServerMessageFrame, -) -from pipecat.runner.types import RunnerArguments -from pipecat.runner.utils import create_transport -from pipecat.services.cartesia.tts import CartesiaTTSService -from pipecat.services.deepgram.stt import DeepgramSTTService -from pipecat.services.openai.llm import OpenAIContextAggregatorPair, OpenAILLMService -from pipecat.transports.base_transport import BaseTransport, TransportParams - -load_dotenv(override=True) - -# This is an example of a chatbot in which a user can speak and/or type text to communicate with the bot. -# It uses the small webrtc transport prebuilt web UI. -# https://github.com/pipecat-ai/small-webrtc-prebuilt - - -def create_action_llm_append_to_messages(context_aggregator: OpenAIContextAggregatorPair): - async def action_llm_append_to_messages_handler( - rtvi: RTVIProcessor, service: str, arguments: dict[str, any] - ) -> ActionResult: - run_immediately = arguments["run_immediately"] if "run_immediately" in arguments else True - - if run_immediately: - await rtvi.interrupt_bot() - - # We just interrupted the bot so it should be fine to use the - # context directly instead of through frame. - if "messages" in arguments and arguments["messages"]: - mess = arguments["messages"] - frame = LLMMessagesAppendFrame(messages=arguments["messages"]) - await rtvi.push_frame(frame) - - if run_immediately: - frame = LLMRunFrame() - await rtvi.push_frame(frame) - - return True - - action_llm_append_to_messages = RTVIAction( - service="llm", - action="append_to_messages", - result="bool", - arguments=[ - RTVIActionArgument(name="messages", type="array"), - RTVIActionArgument(name="run_immediately", type="bool"), - ], - handler=action_llm_append_to_messages_handler, - ) - return action_llm_append_to_messages - - -# We store functions so objects (e.g. SileroVADAnalyzer) don't get -# instantiated. The function will be called when the desired transport gets -# selected. -transport_params = { - "webrtc": lambda: TransportParams( - audio_in_enabled=True, - audio_out_enabled=True, - vad_analyzer=SileroVADAnalyzer(), - ), -} - - -async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): - logger.info(f"Starting bot") - - stt = DeepgramSTTService(api_key=os.getenv("DEEPGRAM_API_KEY")) - - llm = OpenAILLMService(api_key=os.getenv("OPENAI_API_KEY")) - - tts = CartesiaTTSService( - api_key=os.getenv("CARTESIA_API_KEY"), voice_id="71a7ad14-091c-4e8e-a314-022ece01c121" - ) - - messages = [ - { - "role": "system", - "content": "You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Respond to what the user says in a creative and helpful way. Explain to the User they can speak or type text to communicate with you.", - }, - ] - - context = LLMContext(messages) - context_aggregator = LLMContextAggregatorPair(context) - - action_llm_append_to_messages = create_action_llm_append_to_messages(context_aggregator) - rtvi = RTVIProcessor(config=RTVIConfig(config=[])) - rtvi.register_action(action_llm_append_to_messages) - - pipeline = Pipeline( - [ - transport.input(), - rtvi, - stt, - context_aggregator.user(), - llm, - tts, - transport.output(), - context_aggregator.assistant(), - ] - ) - - task = PipelineTask( - pipeline, - params=PipelineParams( - enable_metrics=True, - enable_usage_metrics=True, - ), - idle_timeout_secs=runner_args.pipeline_idle_timeout_secs, - observers=[RTVIObserver(rtvi)], - ) - - @rtvi.event_handler("on_client_ready") - async def on_client_ready(rtvi): - logger.info("Pipecat client ready.") - await rtvi.set_bot_ready() - - # This block is frontend UI specific - # These messages are intended for small webrtc UI to only handle text - # https://github.com/pipecat-ai/small-webrtc-prebuilt - messages = { - "show_text_container": True, - "show_debug_container": False, - } - rtvi_frame = RTVIServerMessageFrame(data=messages) - await task.queue_frames([rtvi_frame]) - - @transport.event_handler("on_client_connected") - async def on_client_connected(transport, client): - logger.info(f"Client connected: {client}") - # Kick off the conversation. - await task.queue_frames([LLMRunFrame()]) - - @transport.event_handler("on_client_disconnected") - async def on_client_disconnected(transport, client): - logger.info(f"Client disconnected") - await task.cancel() - - runner = PipelineRunner(handle_sigint=runner_args.handle_sigint) - - await runner.run(task) - - -async def bot(runner_args: RunnerArguments): - """Main bot entry point compatible with Pipecat Cloud.""" - transport = await create_transport(runner_args, transport_params) - await run_bot(transport, runner_args) - - -if __name__ == "__main__": - from pipecat.runner.run import main - - main() From 3e982f7a4a9804774600e9f135e9a36cb2217f8b Mon Sep 17 00:00:00 2001 From: Varun Pratap Singh Date: Mon, 12 Jan 2026 22:11:39 +0530 Subject: [PATCH 0011/1060] refactor: rename audio_packet_bytes to fixed_audio_packet_size --- changelog/3410.changed.md | 1 + src/pipecat/transports/websocket/fastapi.py | 12 ++++++------ 2 files changed, 7 insertions(+), 6 deletions(-) diff --git a/changelog/3410.changed.md b/changelog/3410.changed.md index 0be207c65..f58ff546a 100644 --- a/changelog/3410.changed.md +++ b/changelog/3410.changed.md @@ -1 +1,2 @@ - Enhanced `FastAPIWebsocketTransport` with optional protocol-level audio packetization to support media endpoints requiring strict framing and real-time pacing. +- Renamed `audio_packet_bytes` to `fixed_audio_packet_size` for clearer audio framing semantics. diff --git a/src/pipecat/transports/websocket/fastapi.py b/src/pipecat/transports/websocket/fastapi.py index cffacd932..e1d02ac00 100644 --- a/src/pipecat/transports/websocket/fastapi.py +++ b/src/pipecat/transports/websocket/fastapi.py @@ -56,14 +56,14 @@ class FastAPIWebsocketParams(TransportParams): add_wav_header: Whether to add WAV headers to audio frames. serializer: Frame serializer for encoding/decoding messages. session_timeout: Session timeout in seconds, None for no timeout. - audio_packet_bytes: Optional fixed-size packetization for raw PCM audio payloads. + fixed_audio_packet_size: Optional fixed-size packetization for raw PCM audio payloads. Useful when the remote WebSocket media endpoint requires strict audio framing. """ add_wav_header: bool = False serializer: Optional[FrameSerializer] = None session_timeout: Optional[int] = None - audio_packet_bytes: Optional[int] = None + fixed_audio_packet_size: Optional[int] = None class FastAPIWebsocketCallbacks(BaseModel): @@ -366,7 +366,7 @@ class FastAPIWebsocketOutputTransport(BaseOutputTransport): # Buffer for optional protocol-level audio packetization. # Some serializers may emit arbitrarily sized raw PCM payloads, while # certain downstream transports or media endpoints require audio to be - # sent in fixed-size frames. When `params.audio_packet_bytes` is set, + # sent in fixed-size frames. When `params.fixed_audio_packet_size` is set, # this buffer accumulates outgoing audio until a full packet can be # emitted, preserving any remainder for subsequent sends. self._audio_send_buffer = bytearray() @@ -429,7 +429,7 @@ class FastAPIWebsocketOutputTransport(BaseOutputTransport): if isinstance(frame, InterruptionFrame): # Drop any partially buffered audio to avoid replaying stale PCM - if self._params.audio_packet_bytes: + if self._params.fixed_audio_packet_size: self._audio_send_buffer.clear() await self._write_frame(frame) @@ -497,8 +497,8 @@ class FastAPIWebsocketOutputTransport(BaseOutputTransport): if payload: # Optional protocol-level audio packetization: # If a downstream WebSocket media endpoint requires fixed-size PCM frames, - # configure params.audio_packet_bytes (e.g. 640 for 20ms @ 16kHz PCM16 mono). - packet_bytes = self._params.audio_packet_bytes + # configure params.fixed_audio_packet_size (e.g. 640 for 20ms @ 16kHz PCM16 mono). + packet_bytes = self._params.fixed_audio_packet_size if packet_bytes and isinstance(payload, (bytes, bytearray)): self._audio_send_buffer.extend(bytes(payload)) From 5743e2a99b8575c7671007183d96187a33353ef6 Mon Sep 17 00:00:00 2001 From: Mark Backman Date: Mon, 12 Jan 2026 12:15:40 -0500 Subject: [PATCH 0012/1060] Update changelog for PR 3410.changed.md --- changelog/3410.changed.md | 3 +-- 1 file changed, 1 insertion(+), 2 deletions(-) diff --git a/changelog/3410.changed.md b/changelog/3410.changed.md index f58ff546a..3e54436de 100644 --- a/changelog/3410.changed.md +++ b/changelog/3410.changed.md @@ -1,2 +1 @@ -- Enhanced `FastAPIWebsocketTransport` with optional protocol-level audio packetization to support media endpoints requiring strict framing and real-time pacing. -- Renamed `audio_packet_bytes` to `fixed_audio_packet_size` for clearer audio framing semantics. +- Enhanced `FastAPIWebsocketTransport` with optional protocol-level audio packetization via the `fixed_audio_packet_size` parameter to support media endpoints requiring strict framing and real-time pacing. From ec20d72aba535292def7376b36dc208218ea479f Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Aleix=20Conchillo=20Flaqu=C3=A9?= Date: Mon, 12 Jan 2026 09:07:23 -0800 Subject: [PATCH 0013/1060] LLMAssistantAggregator: reset aggregation after adding the thought, not before --- src/pipecat/processors/aggregators/llm_response_universal.py | 4 +++- 1 file changed, 3 insertions(+), 1 deletion(-) diff --git a/src/pipecat/processors/aggregators/llm_response_universal.py b/src/pipecat/processors/aggregators/llm_response_universal.py index c47579fba..1baf87304 100644 --- a/src/pipecat/processors/aggregators/llm_response_universal.py +++ b/src/pipecat/processors/aggregators/llm_response_universal.py @@ -950,7 +950,6 @@ class LLMAssistantAggregator(LLMContextAggregator): return thought = concatenate_aggregated_text(self._thought_aggregation) - await self._reset_thought_aggregation() if self._thought_append_to_context: llm = self._thought_llm @@ -966,6 +965,9 @@ class LLMAssistantAggregator(LLMContextAggregator): ) message = AssistantThoughtMessage(content=thought, timestamp=self._thought_start_time) + + await self._reset_thought_aggregation() + await self._call_event_handler("on_assistant_thought", message) def _context_updated_task_finished(self, task: asyncio.Task): From b58471fdb1ee677d3768d0617c953f1392d240bb Mon Sep 17 00:00:00 2001 From: Mark Backman Date: Mon, 12 Jan 2026 12:24:56 -0500 Subject: [PATCH 0014/1060] Add Exotel and Vonage to Serializers in README services list --- README.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/README.md b/README.md index 905265d43..0fbd1faea 100644 --- a/README.md +++ b/README.md @@ -78,7 +78,7 @@ Catch new features, interviews, and how-tos on our [Pipecat TV](https://www.yout | Text-to-Speech | [Async](https://docs.pipecat.ai/server/services/tts/asyncai), [AWS](https://docs.pipecat.ai/server/services/tts/aws), [Azure](https://docs.pipecat.ai/server/services/tts/azure), [Cartesia](https://docs.pipecat.ai/server/services/tts/cartesia), [Deepgram](https://docs.pipecat.ai/server/services/tts/deepgram), [ElevenLabs](https://docs.pipecat.ai/server/services/tts/elevenlabs), [Fish](https://docs.pipecat.ai/server/services/tts/fish), [Google](https://docs.pipecat.ai/server/services/tts/google), [Gradium](https://docs.pipecat.ai/server/services/tts/gradium), [Groq](https://docs.pipecat.ai/server/services/tts/groq), [Hume](https://docs.pipecat.ai/server/services/tts/hume), [Inworld](https://docs.pipecat.ai/server/services/tts/inworld), [LMNT](https://docs.pipecat.ai/server/services/tts/lmnt), [MiniMax](https://docs.pipecat.ai/server/services/tts/minimax), [Neuphonic](https://docs.pipecat.ai/server/services/tts/neuphonic), [NVIDIA Riva](https://docs.pipecat.ai/server/services/tts/riva), [OpenAI](https://docs.pipecat.ai/server/services/tts/openai), [Piper](https://docs.pipecat.ai/server/services/tts/piper), [PlayHT](https://docs.pipecat.ai/server/services/tts/playht), [Rime](https://docs.pipecat.ai/server/services/tts/rime), [Sarvam](https://docs.pipecat.ai/server/services/tts/sarvam), [Speechmatics](https://docs.pipecat.ai/server/services/tts/speechmatics), [XTTS](https://docs.pipecat.ai/server/services/tts/xtts) | | Speech-to-Speech | [AWS Nova Sonic](https://docs.pipecat.ai/server/services/s2s/aws), [Gemini Multimodal Live](https://docs.pipecat.ai/server/services/s2s/gemini), [Grok Voice Agent](https://docs.pipecat.ai/server/services/s2s/grok), [OpenAI Realtime](https://docs.pipecat.ai/server/services/s2s/openai), [Ultravox](https://docs.pipecat.ai/server/services/s2s/ultravox), | | Transport | [Daily (WebRTC)](https://docs.pipecat.ai/server/services/transport/daily), [FastAPI Websocket](https://docs.pipecat.ai/server/services/transport/fastapi-websocket), [SmallWebRTCTransport](https://docs.pipecat.ai/server/services/transport/small-webrtc), [WebSocket Server](https://docs.pipecat.ai/server/services/transport/websocket-server), Local | -| Serializers | [Plivo](https://docs.pipecat.ai/server/utilities/serializers/plivo), [Twilio](https://docs.pipecat.ai/server/utilities/serializers/twilio), [Telnyx](https://docs.pipecat.ai/server/utilities/serializers/telnyx) | +| Serializers | [Exotel](https://docs.pipecat.ai/server/utilities/serializers/exotel), [Plivo](https://docs.pipecat.ai/server/utilities/serializers/plivo), [Twilio](https://docs.pipecat.ai/server/utilities/serializers/twilio), [Telnyx](https://docs.pipecat.ai/server/utilities/serializers/telnyx), [Vonage](https://docs.pipecat.ai/server/utilities/serializers/vonage) | | Video | [HeyGen](https://docs.pipecat.ai/server/services/video/heygen), [Tavus](https://docs.pipecat.ai/server/services/video/tavus), [Simli](https://docs.pipecat.ai/server/services/video/simli) | | Memory | [mem0](https://docs.pipecat.ai/server/services/memory/mem0) | | Vision & Image | [fal](https://docs.pipecat.ai/server/services/image-generation/fal), [Google Imagen](https://docs.pipecat.ai/server/services/image-generation/fal), [Moondream](https://docs.pipecat.ai/server/services/vision/moondream) | From cd3290df1c29f08350df643c11ecf56ea56e7d69 Mon Sep 17 00:00:00 2001 From: Mark Backman Date: Mon, 12 Jan 2026 16:00:32 -0500 Subject: [PATCH 0015/1060] Small cleanup for task creation in SpeechmaticsSTTService --- src/pipecat/services/speechmatics/stt.py | 14 +++++++++++--- 1 file changed, 11 insertions(+), 3 deletions(-) diff --git a/src/pipecat/services/speechmatics/stt.py b/src/pipecat/services/speechmatics/stt.py index 5d6a5e205..457388c31 100644 --- a/src/pipecat/services/speechmatics/stt.py +++ b/src/pipecat/services/speechmatics/stt.py @@ -369,17 +369,14 @@ class SpeechmaticsSTTService(STTService): """Called when the new session starts.""" await super().start(frame) await self._connect() - self._stt_msg_task = self.create_task(self._process_stt_messages()) async def stop(self, frame: EndFrame): """Called when the session ends.""" - await self.cancel_task(self._stt_msg_task) await super().stop(frame) await self._disconnect() async def cancel(self, frame: CancelFrame): """Called when the session is cancelled.""" - await self.cancel_task(self._stt_msg_task) await super().cancel(frame) await self._disconnect() @@ -389,6 +386,7 @@ class SpeechmaticsSTTService(STTService): - Create STT client - Register handlers for messages - Connect to the client + - Start message processing task """ # Log the event logger.debug(f"{self} connecting to Speechmatics STT service") @@ -436,12 +434,22 @@ class SpeechmaticsSTTService(STTService): self._client = None await self.push_error(error_msg=f"Error connecting to STT service: {e}", exception=e) + # Start message processing task + if not self._stt_msg_task: + self._stt_msg_task = self.create_task(self._process_stt_messages()) + async def _disconnect(self) -> None: """Disconnect from the STT service. + - Cancel message processing task - Disconnect the client - Emit on_disconnected event handler for clients """ + # Cancel the message processing task + if self._stt_msg_task: + await self.cancel_task(self._stt_msg_task) + self._stt_msg_task = None + # Disconnect the client logger.debug(f"{self} disconnecting from Speechmatics STT service") try: From b95a6afe77dcbb875bf40a1b2509aa00421c116b Mon Sep 17 00:00:00 2001 From: poseneror Date: Sun, 11 Jan 2026 09:43:02 +0200 Subject: [PATCH 0016/1060] feat(gladia): add VAD events support Add support for Gladia's speech_start/speech_end events to emit UserStartedSpeakingFrame and UserStoppedSpeakingFrame frames. When enable_vad=True in GladiaInputParams: - speech_start triggers interruption and pushes UserStartedSpeakingFrame - speech_end pushes UserStoppedSpeakingFrame - Tracks speaking state to prevent duplicate events This allows using Gladia's built-in VAD instead of a separate VAD in the pipeline. --- src/pipecat/services/gladia/config.py | 4 ++++ src/pipecat/services/gladia/stt.py | 33 +++++++++++++++++++++++++++ 2 files changed, 37 insertions(+) diff --git a/src/pipecat/services/gladia/config.py b/src/pipecat/services/gladia/config.py index ed160a36e..5fd5bfdac 100644 --- a/src/pipecat/services/gladia/config.py +++ b/src/pipecat/services/gladia/config.py @@ -169,6 +169,9 @@ class GladiaInputParams(BaseModel): pre_processing: Audio pre-processing options realtime_processing: Real-time processing features messages_config: WebSocket message filtering options + enable_vad: Enable VAD to trigger end of utterance detection. This should be used + without any other VAD enabled in the agent and will emit the speaker started + and stopped frames. Defaults to False. """ encoding: Optional[str] = "wav/pcm" @@ -182,3 +185,4 @@ class GladiaInputParams(BaseModel): pre_processing: Optional[PreProcessingConfig] = None realtime_processing: Optional[RealtimeProcessingConfig] = None messages_config: Optional[MessagesConfig] = None + enable_vad: bool = False diff --git a/src/pipecat/services/gladia/stt.py b/src/pipecat/services/gladia/stt.py index 4ba0a2ffd..9a20d6dcb 100644 --- a/src/pipecat/services/gladia/stt.py +++ b/src/pipecat/services/gladia/stt.py @@ -28,6 +28,8 @@ from pipecat.frames.frames import ( StartFrame, TranscriptionFrame, TranslationFrame, + UserStartedSpeakingFrame, + UserStoppedSpeakingFrame, ) from pipecat.services.gladia.config import GladiaInputParams from pipecat.services.stt_service import WebsocketSTTService @@ -266,6 +268,9 @@ class GladiaSTTService(WebsocketSTTService): self._max_buffer_size = max_buffer_size self._buffer_lock = asyncio.Lock() + # VAD state tracking + self._is_speaking = False + def __str__(self): return f"{self.name} [{self._session_id}]" @@ -507,6 +512,30 @@ class GladiaSTTService(WebsocketSTTService): await self.stop_ttfb_metrics() await self.stop_processing_metrics() + async def _on_speech_started(self): + """Handle speech start event from Gladia. + + Triggers interruption and emits UserStartedSpeakingFrame when VAD is enabled. + """ + if not self._params.enable_vad or self._is_speaking: + return + logger.debug(f"{self} User started speaking") + self._is_speaking = True + # Push interruption first to stop the bot, then notify about user speaking + await self.push_interruption_task_frame_and_wait() + await self.push_frame(UserStartedSpeakingFrame()) + + async def _on_speech_ended(self): + """Handle speech end event from Gladia. + + Emits UserStoppedSpeakingFrame when VAD is enabled. + """ + if not self._params.enable_vad or not self._is_speaking: + return + self._is_speaking = False + await self.push_frame(UserStoppedSpeakingFrame()) + logger.debug(f"{self} User stopped speaking") + async def _send_audio(self, audio: bytes): """Send audio chunk with proper message format.""" if self._websocket and self._websocket.state is State.OPEN: @@ -599,6 +628,10 @@ class GladiaSTTService(WebsocketSTTService): translation, "", time_now_iso8601(), translated_language ) ) + elif content["type"] == "speech_start": + await self._on_speech_started() + elif content["type"] == "speech_end": + await self._on_speech_ended() except json.JSONDecodeError: logger.warning(f"{self} Received non-JSON message: {message}") From 3304b18ac2ecfbbafe8d06bcad3d4b56ceb38557 Mon Sep 17 00:00:00 2001 From: poseneror Date: Tue, 13 Jan 2026 14:19:50 +0200 Subject: [PATCH 0017/1060] Add should_interrupt + broadcast user events --- src/pipecat/services/gladia/stt.py | 19 +++++++++++++------ 1 file changed, 13 insertions(+), 6 deletions(-) diff --git a/src/pipecat/services/gladia/stt.py b/src/pipecat/services/gladia/stt.py index 9a20d6dcb..8c5ec7aa4 100644 --- a/src/pipecat/services/gladia/stt.py +++ b/src/pipecat/services/gladia/stt.py @@ -204,6 +204,7 @@ class GladiaSTTService(WebsocketSTTService): model: str = "solaria-1", params: Optional[GladiaInputParams] = None, max_buffer_size: int = 1024 * 1024 * 20, # 20MB default buffer + should_interrupt: bool = True, **kwargs, ): """Initialize the Gladia STT service. @@ -222,6 +223,8 @@ class GladiaSTTService(WebsocketSTTService): model: Model to use for transcription. Defaults to "solaria-1". params: Additional configuration parameters for Gladia service. max_buffer_size: Maximum size of audio buffer in bytes. Defaults to 20MB. + should_interrupt: Determine whether the bot should be interrupted when + Gladia VAD detects user speech. Defaults to True. **kwargs: Additional arguments passed to the STTService parent class. """ super().__init__(sample_rate=sample_rate, **kwargs) @@ -270,6 +273,7 @@ class GladiaSTTService(WebsocketSTTService): # VAD state tracking self._is_speaking = False + self._should_interrupt = should_interrupt def __str__(self): return f"{self.name} [{self._session_id}]" @@ -515,25 +519,28 @@ class GladiaSTTService(WebsocketSTTService): async def _on_speech_started(self): """Handle speech start event from Gladia. - Triggers interruption and emits UserStartedSpeakingFrame when VAD is enabled. + Broadcasts UserStartedSpeakingFrame and optionally triggers interruption + when VAD is enabled. """ if not self._params.enable_vad or self._is_speaking: return + logger.debug(f"{self} User started speaking") self._is_speaking = True - # Push interruption first to stop the bot, then notify about user speaking - await self.push_interruption_task_frame_and_wait() - await self.push_frame(UserStartedSpeakingFrame()) + + await self.broadcast_frame(UserStartedSpeakingFrame) + if self._should_interrupt: + await self.push_interruption_task_frame_and_wait() async def _on_speech_ended(self): """Handle speech end event from Gladia. - Emits UserStoppedSpeakingFrame when VAD is enabled. + Broadcasts UserStoppedSpeakingFrame when VAD is enabled. """ if not self._params.enable_vad or not self._is_speaking: return self._is_speaking = False - await self.push_frame(UserStoppedSpeakingFrame()) + await self.broadcast_frame(UserStoppedSpeakingFrame) logger.debug(f"{self} User stopped speaking") async def _send_audio(self, audio: bytes): From 76a058178ea0a012b5b747a45b6b2d03e95a4e9d Mon Sep 17 00:00:00 2001 From: Paul Kompfner Date: Tue, 13 Jan 2026 09:50:59 -0500 Subject: [PATCH 0018/1060] Add Gemini 3 Flash-specific thinking levels --- pyproject.toml | 2 +- src/pipecat/services/google/llm.py | 14 ++++--- uv.lock | 65 +++++------------------------- 3 files changed, 20 insertions(+), 61 deletions(-) diff --git a/pyproject.toml b/pyproject.toml index f75673cb6..55fd8c385 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -62,7 +62,7 @@ fal = [ "fal-client~=0.5.9" ] fireworks = [] fish = [ "ormsgpack~=1.7.0", "pipecat-ai[websockets-base]" ] gladia = [ "pipecat-ai[websockets-base]" ] -google = [ "google-cloud-speech>=2.33.0,<3", "google-cloud-texttospeech>=2.31.0,<3", "google-genai>=1.51.0,<2", "pipecat-ai[websockets-base]" ] +google = [ "google-cloud-speech>=2.33.0,<3", "google-cloud-texttospeech>=2.31.0,<3", "google-genai>=1.57.0,<2", "pipecat-ai[websockets-base]" ] gradium = [ "pipecat-ai[websockets-base]" ] grok = [] groq = [ "groq~=0.23.0" ] diff --git a/src/pipecat/services/google/llm.py b/src/pipecat/services/google/llm.py index f5f11b7e1..20341b64d 100644 --- a/src/pipecat/services/google/llm.py +++ b/src/pipecat/services/google/llm.py @@ -708,16 +708,18 @@ class GoogleLLMService(LLMService): Gemini 2.5 and 3 series models have this thinking process. Parameters: - thinking_level: Thinking level for Gemini 3 Pro. Can be "low" or "high". - If not provided, Gemini 3 Pro defaults to "high". - Note: Gemini 2.5 series should use thinking_budget instead. + thinking_level: Thinking level for Gemini 3 models. + For Gemini 3 Pro, this can be "low" or "high". + For Gemini 3 Flash, this can be "minimal", "low", "medium", or "high". + If not provided, Gemini 3 models default to "high". + Note: Gemini 2.5 series must use thinking_budget instead. thinking_budget: Token budget for thinking, for Gemini 2.5 series. -1 for dynamic thinking (model decides), 0 to disable thinking, or a specific token count (e.g., 128-32768 for 2.5 Pro). If not provided, most models today default to dynamic thinking. See https://ai.google.dev/gemini-api/docs/thinking#set-budget for default values and allowed ranges. - Note: Gemini 3 Pro should use thinking_level instead. + Note: Gemini 3 models must use thinking_level instead. include_thoughts: Whether to include thought summaries in the response. Today's models default to not including thoughts (False). """ @@ -726,7 +728,9 @@ class GoogleLLMService(LLMService): # Why `| str` here? 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""" - # Append trailing space to prevent TTS from vocalizing trailing periods as "dot" - text_with_trailing_space = text + " " - logger.debug(f"{self}: Generating TTS [{text_with_trailing_space}]") + logger.debug(f"{self}: Generating TTS [{text}]") try: # Reconnect if the websocket is closed @@ -301,14 +300,14 @@ class DeepgramTTSService(WebsocketTTSService): await self._connect() await self.start_ttfb_metrics() - await self.start_tts_usage_metrics(text_with_trailing_space) + await self.start_tts_usage_metrics(text) yield TTSStartedFrame() # Send text message to Deepgram # Note: We don't send Flush here - that should only be sent when the # LLM finishes a complete response via flush_audio() - speak_msg = {"type": "Speak", "text": text_with_trailing_space} + speak_msg = {"type": "Speak", "text": text} await self._get_websocket().send(json.dumps(speak_msg)) # The audio frames will be handled in _receive_messages diff --git a/src/pipecat/services/rime/tts.py b/src/pipecat/services/rime/tts.py index b6fe25e0e..39f1a626c 100644 --- a/src/pipecat/services/rime/tts.py +++ b/src/pipecat/services/rime/tts.py @@ -130,6 +130,7 @@ class RimeTTSService(AudioContextWordTTSService): push_text_frames=False, push_stop_frames=True, pause_frame_processing=True, + append_trailing_space=True, sample_rate=sample_rate, **kwargs, ) diff --git a/src/pipecat/services/tts_service.py b/src/pipecat/services/tts_service.py index 4b1d20b9b..e04c4b649 100644 --- a/src/pipecat/services/tts_service.py +++ b/src/pipecat/services/tts_service.py @@ -101,6 +101,9 @@ class TTSService(AIService): silence_time_s: float = 2.0, # if True, we will pause processing frames while we are receiving audio pause_frame_processing: bool = False, + # if True, append a trailing space to text before sending to TTS + # (helps prevent some TTS services from vocalizing trailing punctuation) + append_trailing_space: bool = False, # TTS output sample rate sample_rate: Optional[int] = None, # Text aggregator to aggregate incoming tokens and decide when to push to the TTS. @@ -132,6 +135,8 @@ class TTSService(AIService): push_silence_after_stop: Whether to push silence audio after TTSStoppedFrame. silence_time_s: Duration of silence to push when push_silence_after_stop is True. pause_frame_processing: Whether to pause frame processing during audio generation. + append_trailing_space: Whether to append a trailing space to text before sending to TTS. + This helps prevent some TTS services from vocalizing trailing punctuation (e.g., "dot"). sample_rate: Output sample rate for generated audio. text_aggregator: Custom text aggregator for processing incoming text. @@ -161,6 +166,7 @@ class TTSService(AIService): self._push_silence_after_stop: bool = push_silence_after_stop self._silence_time_s: float = silence_time_s self._pause_frame_processing: bool = pause_frame_processing + self._append_trailing_space: bool = append_trailing_space self._init_sample_rate = sample_rate self._sample_rate = 0 self._voice_id: str = "" @@ -273,6 +279,19 @@ class TTSService(AIService): """ return Language(language) + def _prepare_text_for_tts(self, text: str) -> str: + """Prepare text for TTS by applying any transformations required by the TTS service. + + Args: + text: The text to prepare. + + Returns: + The prepared text with transformations applied. + """ + if self._append_trailing_space and not text.endswith(" "): + return text + " " + return text + async def update_setting(self, key: str, value: Any): """Update a service-specific setting. @@ -603,7 +622,10 @@ class TTSService(AIService): for aggregation_type, transform in self._text_transforms: if aggregation_type == type or aggregation_type == "*": transformed_text = await transform(transformed_text, type) - await self.process_generator(self.run_tts(transformed_text)) + + # Apply any final text preparation (e.g., trailing space) + prepared_text = self._prepare_text_for_tts(transformed_text) + await self.process_generator(self.run_tts(prepared_text)) await self.stop_processing_metrics() From f5e8a04e3b9ae78efd9e676f0b4e37cacebcd43d Mon Sep 17 00:00:00 2001 From: Paul Kompfner Date: Tue, 13 Jan 2026 10:50:08 -0500 Subject: [PATCH 0020/1060] Bump `aiortc` dependency, which relaxes the constraint on `av`, which was pinned to 14.4.0, which no longer has all necessary wheels --- pyproject.toml | 2 +- uv.lock | 64 ++++++++++++++++++++++++++++++++++++++++++++------ 2 files changed, 58 insertions(+), 8 deletions(-) diff --git a/pyproject.toml b/pyproject.toml index 55fd8c385..7f50189de 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -111,7 +111,7 @@ tavus=[] together = [] tracing = [ "opentelemetry-sdk>=1.33.0", "opentelemetry-api>=1.33.0", "opentelemetry-instrumentation>=0.54b0" ] ultravox = [ "pipecat-ai[websockets-base]" ] -webrtc = [ "aiortc>=1.13.0,<2", "opencv-python>=4.11.0.86,<5" ] +webrtc = [ "aiortc>=1.14.0,<2", "opencv-python>=4.11.0.86,<5" ] websocket = [ 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{ name = "aioboto3", marker = "extra == 'aws'", specifier = "~=15.5.0" }, { name = "aiofiles", specifier = ">=24.1.0,<25" }, { name = "aiohttp", specifier = ">=3.11.12,<4" }, - { name = "aiortc", marker = "extra == 'webrtc'", specifier = ">=1.13.0,<2" }, + { name = "aiortc", marker = "extra == 'webrtc'", specifier = ">=1.14.0,<2" }, { name = "anthropic", marker = "extra == 'anthropic'", specifier = "~=0.49.0" }, { name = "audioop-lts", marker = "python_full_version >= '3.13'", specifier = "~=0.2.1" }, { name = "aws-sdk-bedrock-runtime", marker = "python_full_version >= '3.12' and extra == 'aws-nova-sonic'", specifier = "~=0.2.0" }, From 8812686b1753c9573275d178bcd23f290044d178 Mon Sep 17 00:00:00 2001 From: Paul Kompfner Date: Mon, 12 Jan 2026 16:01:48 -0500 Subject: [PATCH 0021/1060] Fix parallel function calling with Gemini 3. MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit Gemini expects parallel function calls to be passed in as a single multi-part `Content` block. This is important because only one of the function calls in a batch of parallel function calls gets a thought signature—if they're passed in as separate `Content` blocks, there'd be one or more missing thought signatures, which would result in a Gemini error. --- .../adapters/services/gemini_adapter.py | 77 +++++++++++++++++++ 1 file changed, 77 insertions(+) diff --git a/src/pipecat/adapters/services/gemini_adapter.py b/src/pipecat/adapters/services/gemini_adapter.py index e17d9a508..b00543e95 100644 --- a/src/pipecat/adapters/services/gemini_adapter.py +++ b/src/pipecat/adapters/services/gemini_adapter.py @@ -255,6 +255,9 @@ class GeminiLLMAdapter(BaseLLMAdapter[GeminiLLMInvocationParams]): # Apply thought signatures to the corresponding messages self._apply_thought_signatures_to_messages(thought_signature_dicts, messages) + # Merge consecutive tool calls and tool responses into single multi-part messages + messages = self._merge_consecutive_tool_messages(messages) + # Check if we only have function-related messages (no regular text) has_regular_messages = any( len(msg.parts) == 1 @@ -433,6 +436,80 @@ class GeminiLLMAdapter(BaseLLMAdapter[GeminiLLMInvocationParams]): tool_call_id_to_name_mapping=tool_call_id_to_name_mapping, ) + def _merge_consecutive_tool_messages(self, messages: List[Content]) -> List[Content]: + """Merge consecutive tool call messages within tool exchange blocks. + + Gemini (and Gemini 3 in particular, where thought signatures are + involved) expects multiple parallel tool calls to be in a single Content + with multiple function_call parts. + + This method detects "tool exchange blocks" (sequences of tool calls and + responses, including alternating patterns like call1, response1, call2, + response2) and merges all tool calls within each block into a single + Content, followed by the individual tool responses. + + Args: + messages: List of Content messages to process. + + Returns: + List of Content messages with tool calls merged within each block. + """ + if not messages: + return messages + + def is_tool_call_message(msg: Content) -> bool: + """Check if message contains only function_call parts.""" + return ( + msg.role == "model" + and msg.parts + and all(getattr(part, "function_call", None) for part in msg.parts) + ) + + def is_tool_response_message(msg: Content) -> bool: + """Check if message contains only function_response parts.""" + return ( + msg.role == "user" + and msg.parts + and all(getattr(part, "function_response", None) for part in msg.parts) + ) + + def is_tool_message(msg: Content) -> bool: + """Check if message is either a tool call or tool response.""" + return is_tool_call_message(msg) or is_tool_response_message(msg) + + merged_messages = [] + i = 0 + + while i < len(messages): + current = messages[i] + + # Check for a tool exchange block (sequence of tool calls and/or responses) + if is_tool_message(current): + tool_call_parts = [] + tool_response_messages = [] + + # Collect all consecutive tool messages (calls and responses) + j = i + while j < len(messages) and is_tool_message(messages[j]): + msg = messages[j] + if is_tool_call_message(msg): + tool_call_parts.extend(msg.parts) + else: # is_tool_response_message + tool_response_messages.append(msg) + j += 1 + + # Output merged tool calls first, then individual tool responses + if tool_call_parts: + merged_messages.append(Content(role="model", parts=tool_call_parts)) + merged_messages.extend(tool_response_messages) + + i = j + else: + merged_messages.append(current) + i += 1 + + return merged_messages + def _apply_thought_signatures_to_messages( self, thought_signature_dicts: List[dict], messages: List[Content] ) -> None: From 6668712f7bea3d52696a57a5f0dcf26e5b628f9b Mon Sep 17 00:00:00 2001 From: Paul Kompfner Date: Mon, 12 Jan 2026 17:00:13 -0500 Subject: [PATCH 0022/1060] Add evals for parallel function calling --- scripts/evals/run-release-evals.py | 14 +++++++++++++- 1 file changed, 13 insertions(+), 1 deletion(-) diff --git a/scripts/evals/run-release-evals.py b/scripts/evals/run-release-evals.py index 65902f41a..1cb10146f 100644 --- a/scripts/evals/run-release-evals.py +++ b/scripts/evals/run-release-evals.py @@ -30,10 +30,15 @@ EVAL_SIMPLE_MATH = EvalConfig( ) EVAL_WEATHER = EvalConfig( - prompt="What's the weather in San Francisco? Temperature should be in fahrenheits.", + prompt="What's the weather in San Francisco? Temperature should be in Fahrenheit.", eval="The user talks about the weather in San Francisco, including the degrees.", ) +EVAL_WEATHER_AND_RESTAURANT = EvalConfig( + prompt="What's the weather in San Francisco, and what's a good restaurant there? Temperature should be in Fahrenheit.", + eval="The user talks about the weather in San Francisco, including the degrees, and provides a restaurant recommendation.", +) + EVAL_ONLINE_SEARCH = EvalConfig( prompt="What's the current date in UTC?", eval=f"Current date in UTC is {datetime.now(timezone.utc).strftime('%A, %B %d, %Y')}.", @@ -145,10 +150,16 @@ TESTS_12 = [ ("12d-describe-image-moondream.py", EVAL_VISION_IMAGE()), ] +# For a few major services, we also test parallel function calling. +# (We don't bother doing this with every single service, as it's expensive and +# most rely on the same OpenAI-compatible implementation.) TESTS_14 = [ ("14-function-calling.py", EVAL_WEATHER), + ("14-function-calling.py", EVAL_WEATHER_AND_RESTAURANT), ("14a-function-calling-anthropic.py", EVAL_WEATHER), + ("14a-function-calling-anthropic.py", EVAL_WEATHER_AND_RESTAURANT), ("14e-function-calling-google.py", EVAL_WEATHER), + ("14e-function-calling-google.py", EVAL_WEATHER_AND_RESTAURANT), ("14f-function-calling-groq.py", EVAL_WEATHER), ("14g-function-calling-grok.py", EVAL_WEATHER), ("14h-function-calling-azure.py", EVAL_WEATHER), @@ -160,6 +171,7 @@ TESTS_14 = [ ("14p-function-calling-gemini-vertex-ai.py", EVAL_WEATHER), ("14q-function-calling-qwen.py", EVAL_WEATHER), ("14r-function-calling-aws.py", EVAL_WEATHER), + ("14r-function-calling-aws.py", EVAL_WEATHER_AND_RESTAURANT), ("14v-function-calling-openai.py", EVAL_WEATHER), ("14w-function-calling-mistral.py", EVAL_WEATHER), ("14x-function-calling-openpipe.py", EVAL_WEATHER), From f00f9d9f1aaa1d6d13e0eca80d79123e77d2d785 Mon Sep 17 00:00:00 2001 From: Mark Backman Date: Tue, 13 Jan 2026 11:29:17 -0500 Subject: [PATCH 0023/1060] Add changelog fragments for PR 3404 --- changelog/3404.added.2.md | 1 + changelog/3404.added.md | 1 + 2 files changed, 2 insertions(+) create mode 100644 changelog/3404.added.2.md create mode 100644 changelog/3404.added.md diff --git a/changelog/3404.added.2.md b/changelog/3404.added.2.md new file mode 100644 index 000000000..0f15c39c3 --- /dev/null +++ b/changelog/3404.added.2.md @@ -0,0 +1 @@ +- Added `enable_vad` to `Params` for use in the `GladiaSTTService`. When enabled, `GladiaSTTService` acts as the turn controller, emitting `UserStartedSpeakingFrame`, `UserStoppedSpeakingFrame`, and optionally `InterruptionFrame`. diff --git a/changelog/3404.added.md b/changelog/3404.added.md new file mode 100644 index 000000000..733c22ebe --- /dev/null +++ b/changelog/3404.added.md @@ -0,0 +1 @@ +- Added `should_interrupt` property to `GladiaSTTService` to configure whether the bot should be interrupted when the external service detects user speech. From 41eef5efc4b59c01e17db36a5a327f9421a878c9 Mon Sep 17 00:00:00 2001 From: Mark Backman Date: Tue, 13 Jan 2026 11:36:15 -0500 Subject: [PATCH 0024/1060] Add 07j Gladia VAD foundational example, add to release evals --- .../07j-interruptible-gladia-vad.py | 140 ++++++++++++++++++ scripts/evals/run-release-evals.py | 1 + 2 files changed, 141 insertions(+) create mode 100644 examples/foundational/07j-interruptible-gladia-vad.py diff --git a/examples/foundational/07j-interruptible-gladia-vad.py b/examples/foundational/07j-interruptible-gladia-vad.py new file mode 100644 index 000000000..7f2790611 --- /dev/null +++ b/examples/foundational/07j-interruptible-gladia-vad.py @@ -0,0 +1,140 @@ +# +# Copyright (c) 2024-2026, Daily +# +# SPDX-License-Identifier: BSD 2-Clause License +# + + +import os + +from dotenv import load_dotenv +from loguru import logger + +from pipecat.audio.vad.silero import SileroVADAnalyzer +from pipecat.audio.vad.vad_analyzer import VADParams +from pipecat.frames.frames import LLMRunFrame +from pipecat.pipeline.pipeline import Pipeline +from pipecat.pipeline.runner import PipelineRunner +from pipecat.pipeline.task import PipelineParams, PipelineTask +from pipecat.processors.aggregators.llm_context import LLMContext +from pipecat.processors.aggregators.llm_response_universal import ( + LLMContextAggregatorPair, + LLMUserAggregatorParams, +) +from pipecat.runner.types import RunnerArguments +from pipecat.runner.utils import create_transport +from pipecat.services.cartesia.tts import CartesiaTTSService +from pipecat.services.gladia.config import GladiaInputParams, LanguageConfig +from pipecat.services.gladia.stt import GladiaSTTService +from pipecat.services.openai.llm import OpenAILLMService +from pipecat.transcriptions.language import Language +from pipecat.transports.base_transport import BaseTransport, TransportParams +from pipecat.transports.daily.transport import DailyParams +from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams +from pipecat.turns.user_turn_strategies import ExternalUserTurnStrategies + +load_dotenv(override=True) + +# We store functions so objects (e.g. SileroVADAnalyzer) don't get +# instantiated. The function will be called when the desired transport gets +# selected. +transport_params = { + "daily": lambda: DailyParams( + audio_in_enabled=True, + audio_out_enabled=True, + vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), + ), + "twilio": lambda: FastAPIWebsocketParams( + audio_in_enabled=True, + audio_out_enabled=True, + vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), + ), + "webrtc": lambda: TransportParams( + audio_in_enabled=True, + audio_out_enabled=True, + vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), + ), +} + + +async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): + logger.info(f"Starting bot") + + stt = GladiaSTTService( + api_key=os.getenv("GLADIA_API_KEY", ""), + region=os.getenv("GLADIA_REGION"), + params=GladiaInputParams( + language_config=LanguageConfig( + languages=[Language.EN], + ), + enable_vad=True, + ), + ) + + tts = CartesiaTTSService( + api_key=os.getenv("CARTESIA_API_KEY", ""), + voice_id="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady + ) + + llm = OpenAILLMService(api_key=os.getenv("OPENAI_API_KEY", "")) + + messages = [ + { + "role": "system", + "content": f"You are a helpful LLM. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + }, + ] + + context = LLMContext(messages) + context_aggregator = LLMContextAggregatorPair( + context, + user_params=LLMUserAggregatorParams(user_turn_strategies=ExternalUserTurnStrategies()), + ) + + pipeline = Pipeline( + [ + transport.input(), # Transport user input + stt, # STT + context_aggregator.user(), # User responses + llm, # LLM + tts, # TTS + transport.output(), # Transport bot output + context_aggregator.assistant(), # Assistant spoken responses + ] + ) + + task = PipelineTask( + pipeline, + params=PipelineParams( + enable_metrics=True, + enable_usage_metrics=True, + ), + idle_timeout_secs=runner_args.pipeline_idle_timeout_secs, + ) + + @transport.event_handler("on_client_connected") + async def on_client_connected(transport, client): + logger.info(f"Client connected") + # Kick off the conversation. + messages.append({"role": "system", "content": "Please introduce yourself to the user."}) + await task.queue_frames([LLMRunFrame()]) + + @transport.event_handler("on_client_disconnected") + async def on_client_disconnected(transport, client): + logger.info(f"Client disconnected") + await task.cancel() + + runner = PipelineRunner(handle_sigint=runner_args.handle_sigint) + await runner.run(task) + + +async def bot(runner_args: RunnerArguments): + """Main bot entry point compatible with Pipecat Cloud.""" + transport = await create_transport(runner_args, transport_params) + await run_bot(transport, runner_args) + + +if __name__ == "__main__": + from pipecat.runner.run import main + + main() diff --git a/scripts/evals/run-release-evals.py b/scripts/evals/run-release-evals.py index 65902f41a..21c38a20e 100644 --- a/scripts/evals/run-release-evals.py +++ b/scripts/evals/run-release-evals.py @@ -112,6 +112,7 @@ TESTS_07 = [ ("07g-interruptible-openai.py", EVAL_SIMPLE_MATH), ("07h-interruptible-openpipe.py", EVAL_SIMPLE_MATH), ("07j-interruptible-gladia.py", EVAL_SIMPLE_MATH), + ("07j-interruptible-gladia-vad.py", EVAL_SIMPLE_MATH), ("07k-interruptible-lmnt.py", EVAL_SIMPLE_MATH), ("07l-interruptible-groq.py", EVAL_SIMPLE_MATH), ("07m-interruptible-aws.py", EVAL_SIMPLE_MATH), From d0f227189c073ac67e78ecc41f9c13ffb1f62b21 Mon Sep 17 00:00:00 2001 From: Himanshu Gunwant <69423776+monster-anshu@users.noreply.github.com> Date: Tue, 13 Jan 2026 22:25:52 +0530 Subject: [PATCH 0025/1060] fix: openai llm model name is unknown (#3422) --- changelog/3422.fixed.md | 1 + src/pipecat/utils/tracing/service_decorators.py | 7 ++++--- 2 files changed, 5 insertions(+), 3 deletions(-) create mode 100644 changelog/3422.fixed.md diff --git a/changelog/3422.fixed.md b/changelog/3422.fixed.md new file mode 100644 index 000000000..31b1d93c9 --- /dev/null +++ b/changelog/3422.fixed.md @@ -0,0 +1 @@ +- Fixed a bug in `traced_llm` where the model name in opentelemetry is shown unknown even though it is defined. diff --git a/src/pipecat/utils/tracing/service_decorators.py b/src/pipecat/utils/tracing/service_decorators.py index 22274ae8b..5bcfbd442 100644 --- a/src/pipecat/utils/tracing/service_decorators.py +++ b/src/pipecat/utils/tracing/service_decorators.py @@ -483,9 +483,10 @@ def traced_llm(func: Optional[Callable] = None, *, name: Optional[str] = None) - # Add all available attributes to the span attribute_kwargs = { "service_name": service_class_name, - "model": getattr( - self, getattr(self, "_full_model_name", "model_name"), "unknown" - ), + "model": getattr(self, "_full_model_name", None) + or getattr(self, "model_name", None) + or params.get("model") + or "unknown", "stream": True, # Most LLM services use streaming "parameters": params, } From efbc0c85103a436e759f4ef7f173d690eff157e7 Mon Sep 17 00:00:00 2001 From: Mark Backman Date: Tue, 13 Jan 2026 12:04:15 -0500 Subject: [PATCH 0026/1060] Fix TTS, realtime LLM services could return unknown for model_name --- changelog/3351.fixed.md | 1 + changelog/3422.fixed.md | 2 +- changelog/3428.fixed.md | 1 + src/pipecat/utils/tracing/service_decorators.py | 14 +++++++++----- 4 files changed, 12 insertions(+), 6 deletions(-) create mode 100644 changelog/3351.fixed.md create mode 100644 changelog/3428.fixed.md diff --git a/changelog/3351.fixed.md b/changelog/3351.fixed.md new file mode 100644 index 000000000..2792839cb --- /dev/null +++ b/changelog/3351.fixed.md @@ -0,0 +1 @@ +- Fixed an issue in `traced_stt` where `model_name` in OpenTelemetry appears as `unknown`. diff --git a/changelog/3422.fixed.md b/changelog/3422.fixed.md index 31b1d93c9..fa34d9262 100644 --- a/changelog/3422.fixed.md +++ b/changelog/3422.fixed.md @@ -1 +1 @@ -- Fixed a bug in `traced_llm` where the model name in opentelemetry is shown unknown even though it is defined. +- Fixed an issue in `traced_llm` where `model_name` in OpenTelemetry appears as `unknown`. diff --git a/changelog/3428.fixed.md b/changelog/3428.fixed.md new file mode 100644 index 000000000..e82ff082e --- /dev/null +++ b/changelog/3428.fixed.md @@ -0,0 +1 @@ +- Fixed an issue in `traced_tts`, `traced_gemini_live`, and `traced_openai_realtime` where `model_name` in OpenTelemetry appears as `unknown`. diff --git a/src/pipecat/utils/tracing/service_decorators.py b/src/pipecat/utils/tracing/service_decorators.py index 5bcfbd442..68dda6562 100644 --- a/src/pipecat/utils/tracing/service_decorators.py +++ b/src/pipecat/utils/tracing/service_decorators.py @@ -186,7 +186,7 @@ def traced_tts(func: Optional[Callable] = None, *, name: Optional[str] = None) - add_tts_span_attributes( span=span, service_name=service_class_name, - model=getattr(self, "model_name", "unknown"), + model=getattr(self, "model_name") or "unknown", voice_id=getattr(self, "_voice_id", "unknown"), text=text, settings=getattr(self, "_settings", {}), @@ -585,8 +585,10 @@ def traced_gemini_live(operation: str) -> Callable: ) as current_span: try: # Base service attributes - model_name = getattr( - self, "model_name", getattr(self, "_model_name", "unknown") + model_name = ( + getattr(self, "model_name", None) + or getattr(self, "_model_name", None) + or "unknown" ) voice_id = getattr(self, "_voice_id", None) language_code = getattr(self, "_language_code", None) @@ -890,8 +892,10 @@ def traced_openai_realtime(operation: str) -> Callable: ) as current_span: try: # Base service attributes - model_name = getattr( - self, "model_name", getattr(self, "_model_name", "unknown") + model_name = ( + getattr(self, "model_name", None) + or getattr(self, "_model_name", None) + or "unknown" ) # Operation-specific attribute collection From b937956dc8eb665ee172c9ba4d870679a8f656e1 Mon Sep 17 00:00:00 2001 From: Paul Kompfner Date: Tue, 13 Jan 2026 13:15:32 -0500 Subject: [PATCH 0027/1060] Fix request_image_frame and usage --- examples/foundational/14e-function-calling-google.py | 8 +------- examples/foundational/20d-persistent-context-gemini.py | 4 +++- src/pipecat/services/llm_service.py | 1 + 3 files changed, 5 insertions(+), 8 deletions(-) diff --git a/examples/foundational/14e-function-calling-google.py b/examples/foundational/14e-function-calling-google.py index 49a9f98c3..9412d8027 100644 --- a/examples/foundational/14e-function-calling-google.py +++ b/examples/foundational/14e-function-calling-google.py @@ -68,13 +68,7 @@ async def get_image(params: FunctionCallParams): text_content=question, ) - # Wait a short time for the frame to be processed - await asyncio.sleep(0.5) - - # Return a result to complete the function call - await params.result_callback( - f"I've captured an image from your camera and I'm analyzing what you asked about: {question}" - ) + await params.result_callback(None) # We store functions so objects (e.g. SileroVADAnalyzer) don't get diff --git a/examples/foundational/20d-persistent-context-gemini.py b/examples/foundational/20d-persistent-context-gemini.py index 35f3a22db..f70d2b50c 100644 --- a/examples/foundational/20d-persistent-context-gemini.py +++ b/examples/foundational/20d-persistent-context-gemini.py @@ -74,6 +74,8 @@ async def get_image(params: FunctionCallParams): text_content=question, ) + await params.result_callback(None) + async def get_saved_conversation_filenames(params: FunctionCallParams): # Construct the full pattern including the BASE_FILENAME @@ -257,7 +259,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): voice_id="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady ) - llm = GoogleLLMService(model="gemini-2.0-flash-001", api_key=os.getenv("GOOGLE_API_KEY")) + llm = GoogleLLMService(api_key=os.getenv("GOOGLE_API_KEY")) # you can either register a single function for all function calls, or specific functions # llm.register_function(None, fetch_weather_from_api) diff --git a/src/pipecat/services/llm_service.py b/src/pipecat/services/llm_service.py index a6717b5cc..2c4f61996 100644 --- a/src/pipecat/services/llm_service.py +++ b/src/pipecat/services/llm_service.py @@ -519,6 +519,7 @@ class LLMService(AIService): UserImageRequestFrame( user_id=user_id, text=text_content, + append_to_context=True, # Deprecated fields below. function_name=function_name, tool_call_id=tool_call_id, From 15bc1dd999020960f6c7ba714f9da43b6259d4bb Mon Sep 17 00:00:00 2001 From: Mark Backman Date: Tue, 13 Jan 2026 14:13:00 -0500 Subject: [PATCH 0028/1060] Update GeminiLiveLLMService to push Thought frames when thought content is returned --- .../services/google/gemini_live/llm.py | 20 +++++++++++++++---- 1 file changed, 16 insertions(+), 4 deletions(-) diff --git a/src/pipecat/services/google/gemini_live/llm.py b/src/pipecat/services/google/gemini_live/llm.py index 4b0be986d..a00eef34f 100644 --- a/src/pipecat/services/google/gemini_live/llm.py +++ b/src/pipecat/services/google/gemini_live/llm.py @@ -44,6 +44,9 @@ from pipecat.frames.frames import ( LLMMessagesAppendFrame, LLMSetToolsFrame, LLMTextFrame, + LLMThoughtEndFrame, + LLMThoughtStartFrame, + LLMThoughtTextFrame, LLMUpdateSettingsFrame, StartFrame, TranscriptionFrame, @@ -1455,10 +1458,19 @@ class GeminiLiveLLMService(LLMService): await self._set_bot_is_responding(True) await self.push_frame(LLMFullResponseStartFrame()) - self._bot_text_buffer += text - self._search_result_buffer += text # Also accumulate for grounding - frame = LLMTextFrame(text=text) - await self.push_frame(frame) + # Check if this is a thought + if part.thought: + # Gemini Live emits fully-formed thoughts rather than chunks, + # so bracket each thought in start/end frames + await self.push_frame(LLMThoughtStartFrame()) + await self.push_frame(LLMThoughtTextFrame(text)) + await self.push_frame(LLMThoughtEndFrame(signature=part.thought_signature)) + else: + # Regular text response + self._bot_text_buffer += text + self._search_result_buffer += text # Also accumulate for grounding + frame = LLMTextFrame(text=text) + await self.push_frame(frame) # Check for grounding metadata in server content if msg.server_content and msg.server_content.grounding_metadata: From 02eace5a160ac9cdd467642f11efa5930e927112 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Aleix=20Conchillo=20Flaqu=C3=A9?= Date: Tue, 13 Jan 2026 11:55:55 -0800 Subject: [PATCH 0029/1060] UserImageRequestFrame: don't deprecate function call related fields --- src/pipecat/frames/frames.py | 10 +++++----- src/pipecat/services/llm_service.py | 2 +- 2 files changed, 6 insertions(+), 6 deletions(-) diff --git a/src/pipecat/frames/frames.py b/src/pipecat/frames/frames.py index fb0f8243b..922a3c6af 100644 --- a/src/pipecat/frames/frames.py +++ b/src/pipecat/frames/frames.py @@ -1461,29 +1461,29 @@ class UserImageRequestFrame(SystemFrame): text: An optional text associated to the image request. append_to_context: Whether the requested image should be appended to the LLM context. video_source: Specific video source to capture from. + function_name: Name of function that generated this request (if any). + tool_call_id: Tool call ID if generated by function call (if any). context: [DEPRECATED] Optional context for the image request. - function_name: [DEPRECATED] Name of function that generated this request (if any). - tool_call_id: [DEPRECATED] Tool call ID if generated by function call. """ user_id: str text: Optional[str] = None append_to_context: Optional[bool] = None video_source: Optional[str] = None - context: Optional[Any] = None function_name: Optional[str] = None tool_call_id: Optional[str] = None + context: Optional[Any] = None def __post_init__(self): super().__post_init__() - if self.context or self.function_name or self.tool_call_id: + if self.context: import warnings with warnings.catch_warnings(): warnings.simplefilter("always") warnings.warn( - "`UserImageRequestFrame` fields `context`, `function_name` and `tool_call_id` are deprecated.", + "`UserImageRequestFrame` field `context` is deprecated.", DeprecationWarning, stacklevel=2, ) diff --git a/src/pipecat/services/llm_service.py b/src/pipecat/services/llm_service.py index 2c4f61996..0368c8feb 100644 --- a/src/pipecat/services/llm_service.py +++ b/src/pipecat/services/llm_service.py @@ -520,9 +520,9 @@ class LLMService(AIService): user_id=user_id, text=text_content, append_to_context=True, - # Deprecated fields below. function_name=function_name, tool_call_id=tool_call_id, + # Deprecated fields below. context=text_content, ), FrameDirection.UPSTREAM, From d3c57e2da010beffdb07b26771d631989792558b Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Aleix=20Conchillo=20Flaqu=C3=A9?= Date: Tue, 13 Jan 2026 11:56:13 -0800 Subject: [PATCH 0030/1060] UserImageRawFrame: don't deprecate request field --- src/pipecat/frames/frames.py | 16 +--------------- src/pipecat/transports/daily/transport.py | 2 -- src/pipecat/transports/smallwebrtc/transport.py | 1 - 3 files changed, 1 insertion(+), 18 deletions(-) diff --git a/src/pipecat/frames/frames.py b/src/pipecat/frames/frames.py index 922a3c6af..a27bb780e 100644 --- a/src/pipecat/frames/frames.py +++ b/src/pipecat/frames/frames.py @@ -1565,7 +1565,7 @@ class UserImageRawFrame(InputImageRawFrame): user_id: Identifier of the user who provided this image. text: An optional text associated to this image. append_to_context: Whether the requested image should be appended to the LLM context. - request: [DEPRECATED] The original image request frame if this is a response. + request: The original image request frame if this is a response. """ user_id: str = "" @@ -1573,20 +1573,6 @@ class UserImageRawFrame(InputImageRawFrame): append_to_context: Optional[bool] = None request: Optional[UserImageRequestFrame] = None - def __post_init__(self): - super().__post_init__() - - if self.request: - import warnings - - with warnings.catch_warnings(): - warnings.simplefilter("always") - warnings.warn( - "`UserImageRawFrame` field `request` is deprecated.", - DeprecationWarning, - stacklevel=2, - ) - def __str__(self): pts = format_pts(self.pts) return f"{self.name}(pts: {pts}, user: {self.user_id}, source: {self.transport_source}, size: {self.size}, format: {self.format}, text: {self.text}, append_to_context: {self.append_to_context})" diff --git a/src/pipecat/transports/daily/transport.py b/src/pipecat/transports/daily/transport.py index 147a9a111..203cbb9fa 100644 --- a/src/pipecat/transports/daily/transport.py +++ b/src/pipecat/transports/daily/transport.py @@ -27,7 +27,6 @@ from pipecat.frames.frames import ( CancelFrame, ControlFrame, EndFrame, - ErrorFrame, Frame, InputAudioRawFrame, InputTransportMessageFrame, @@ -1844,7 +1843,6 @@ class DailyInputTransport(BaseInputTransport): format=video_frame.color_format, text=request_frame.text if request_frame else None, append_to_context=request_frame.append_to_context if request_frame else None, - # Deprecated fields below. request=request_frame, ) frame.transport_source = video_source diff --git a/src/pipecat/transports/smallwebrtc/transport.py b/src/pipecat/transports/smallwebrtc/transport.py index 6b6a14829..e9a07cf40 100644 --- a/src/pipecat/transports/smallwebrtc/transport.py +++ b/src/pipecat/transports/smallwebrtc/transport.py @@ -680,7 +680,6 @@ class SmallWebRTCInputTransport(BaseInputTransport): format=video_frame.format, text=request_text, append_to_context=add_to_context, - # Deprecated fields below. request=request_frame, ) image_frame.transport_source = video_source From e268c73c4169efa2bc35d93f0d09a14cc7af1dc7 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Aleix=20Conchillo=20Flaqu=C3=A9?= Date: Tue, 13 Jan 2026 11:56:43 -0800 Subject: [PATCH 0031/1060] LLMAssistantAggregator: cache function call requested images --- .../aggregators/llm_response_universal.py | 72 +++++++++++++------ 1 file changed, 50 insertions(+), 22 deletions(-) diff --git a/src/pipecat/processors/aggregators/llm_response_universal.py b/src/pipecat/processors/aggregators/llm_response_universal.py index 1baf87304..901e5c62c 100644 --- a/src/pipecat/processors/aggregators/llm_response_universal.py +++ b/src/pipecat/processors/aggregators/llm_response_universal.py @@ -641,6 +641,7 @@ class LLMAssistantAggregator(LLMContextAggregator): self._started = 0 self._function_calls_in_progress: Dict[str, Optional[FunctionCallInProgressFrame]] = {} + self._function_calls_image_results: Dict[str, UserImageRawFrame] = {} self._context_updated_tasks: Set[asyncio.Task] = set() self._assistant_turn_start_timestamp = "" @@ -820,6 +821,15 @@ class LLMAssistantAggregator(LLMContextAggregator): run_llm = False + # Append any images that were generated by function calls. + if frame.tool_call_id in self._function_calls_image_results: + image_frame = self._function_calls_image_results[frame.tool_call_id] + + del self._function_calls_image_results[frame.tool_call_id] + + # If an image frame has been added to the context, let's run inference. + run_llm = await self._maybe_append_image_to_context(image_frame) + # Run inference if the function call result requires it. if frame.result: if properties and properties.run_llm is not None: @@ -856,31 +866,24 @@ class LLMAssistantAggregator(LLMContextAggregator): self._update_function_call_result(frame.function_name, frame.tool_call_id, "CANCELLED") del self._function_calls_in_progress[frame.tool_call_id] - def _update_function_call_result(self, function_name: str, tool_call_id: str, result: Any): - for message in self._context.get_messages(): - if ( - not isinstance(message, LLMSpecificMessage) - and message["role"] == "tool" - and message["tool_call_id"] - and message["tool_call_id"] == tool_call_id - ): - message["content"] = result - async def _handle_user_image_frame(self, frame: UserImageRawFrame): - if not frame.append_to_context: - return + image_appended = False - logger.debug(f"{self} Appending UserImageRawFrame to LLM context (size: {frame.size})") + # Check if this image is a result of a function call if so, let's cache. + # TODO(aleix): The function call might have already been executed + # because FunctionCallResultFrame was just faster, in that case we just + # push the context frame now. + if ( + frame.request + and frame.request.tool_call_id + and frame.request.tool_call_id in self._function_calls_in_progress + ): + self._function_calls_image_results[frame.request.tool_call_id] = frame + else: + image_appended = await self._maybe_append_image_to_context(frame) - await self._context.add_image_frame_message( - format=frame.format, - size=frame.size, - image=frame.image, - text=frame.text, - ) - - await self._trigger_assistant_turn_stopped() - await self.push_context_frame(FrameDirection.UPSTREAM) + if image_appended: + await self.push_context_frame(FrameDirection.UPSTREAM) async def _handle_assistant_image_frame(self, frame: AssistantImageRawFrame): logger.debug(f"{self} Appending AssistantImageRawFrame to LLM context (size: {frame.size})") @@ -970,6 +973,31 @@ class LLMAssistantAggregator(LLMContextAggregator): await self._call_event_handler("on_assistant_thought", message) + async def _maybe_append_image_to_context(self, frame: UserImageRawFrame) -> bool: + if not frame.append_to_context: + return False + + logger.debug(f"{self} Appending UserImageRawFrame to LLM context (size: {frame.size})") + + await self._context.add_image_frame_message( + format=frame.format, + size=frame.size, + image=frame.image, + text=frame.text, + ) + + return True + + def _update_function_call_result(self, function_name: str, tool_call_id: str, result: Any): + for message in self._context.get_messages(): + if ( + not isinstance(message, LLMSpecificMessage) + and message["role"] == "tool" + and message["tool_call_id"] + and message["tool_call_id"] == tool_call_id + ): + message["content"] = result + def _context_updated_task_finished(self, task: asyncio.Task): self._context_updated_tasks.discard(task) From 027e54425ac2548f916afeb19f449a42339aba02 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Aleix=20Conchillo=20Flaqu=C3=A9?= Date: Tue, 13 Jan 2026 11:57:12 -0800 Subject: [PATCH 0032/1060] examples(foundational): associate image requests to function calls --- .../14d-function-calling-anthropic-video.py | 10 ++- .../14d-function-calling-aws-video.py | 10 ++- ...14d-function-calling-gemini-flash-video.py | 10 ++- .../14d-function-calling-moondream-video.py | 10 ++- .../14d-function-calling-openai-video.py | 10 ++- .../14e-function-calling-google.py | 61 +++++++++++++------ .../20d-persistent-context-gemini.py | 47 +++++++++----- 7 files changed, 113 insertions(+), 45 deletions(-) diff --git a/examples/foundational/14d-function-calling-anthropic-video.py b/examples/foundational/14d-function-calling-anthropic-video.py index a217f11b1..12f80a418 100644 --- a/examples/foundational/14d-function-calling-anthropic-video.py +++ b/examples/foundational/14d-function-calling-anthropic-video.py @@ -55,9 +55,15 @@ async def fetch_user_image(params: FunctionCallParams): logger.debug(f"Requesting image with user_id={user_id}, question={question}") # Request a user image frame and indicate that it should be added to the - # context. + # context. Also associate it to the function call. await params.llm.push_frame( - UserImageRequestFrame(user_id=user_id, text=question, append_to_context=True), + UserImageRequestFrame( + user_id=user_id, + text=question, + append_to_context=True, + function_name=params.function_name, + tool_call_id=params.tool_call_id, + ), FrameDirection.UPSTREAM, ) diff --git a/examples/foundational/14d-function-calling-aws-video.py b/examples/foundational/14d-function-calling-aws-video.py index a216b5485..4a12f0652 100644 --- a/examples/foundational/14d-function-calling-aws-video.py +++ b/examples/foundational/14d-function-calling-aws-video.py @@ -55,9 +55,15 @@ async def fetch_user_image(params: FunctionCallParams): logger.debug(f"Requesting image with user_id={user_id}, question={question}") # Request a user image frame and indicate that it should be added to the - # context. + # context. Also associate it to the function call. await params.llm.push_frame( - UserImageRequestFrame(user_id=user_id, text=question, append_to_context=True), + UserImageRequestFrame( + user_id=user_id, + text=question, + append_to_context=True, + function_name=params.function_name, + tool_call_id=params.tool_call_id, + ), FrameDirection.UPSTREAM, ) diff --git a/examples/foundational/14d-function-calling-gemini-flash-video.py b/examples/foundational/14d-function-calling-gemini-flash-video.py index d7885b0dc..672eec72d 100644 --- a/examples/foundational/14d-function-calling-gemini-flash-video.py +++ b/examples/foundational/14d-function-calling-gemini-flash-video.py @@ -55,9 +55,15 @@ async def fetch_user_image(params: FunctionCallParams): logger.debug(f"Requesting image with user_id={user_id}, question={question}") # Request a user image frame and indicate that it should be added to the - # context. + # context. Also associate it to the function call. await params.llm.push_frame( - UserImageRequestFrame(user_id=user_id, text=question, append_to_context=True), + UserImageRequestFrame( + user_id=user_id, + text=question, + append_to_context=True, + function_name=params.function_name, + tool_call_id=params.tool_call_id, + ), FrameDirection.UPSTREAM, ) diff --git a/examples/foundational/14d-function-calling-moondream-video.py b/examples/foundational/14d-function-calling-moondream-video.py index a6c2ef24b..cc6e48f65 100644 --- a/examples/foundational/14d-function-calling-moondream-video.py +++ b/examples/foundational/14d-function-calling-moondream-video.py @@ -64,9 +64,15 @@ async def fetch_user_image(params: FunctionCallParams): # Request a user image frame. In this case, we don't want the requested # image to be added to the context because we will process it with - # Moondream. + # Moondream. Also associate it to the function call. await params.llm.push_frame( - UserImageRequestFrame(user_id=user_id, text=question, append_to_context=False), + UserImageRequestFrame( + user_id=user_id, + text=question, + append_to_context=False, + function_name=params.function_name, + tool_call_id=params.tool_call_id, + ), FrameDirection.UPSTREAM, ) diff --git a/examples/foundational/14d-function-calling-openai-video.py b/examples/foundational/14d-function-calling-openai-video.py index 60c8f5952..c7921da18 100644 --- a/examples/foundational/14d-function-calling-openai-video.py +++ b/examples/foundational/14d-function-calling-openai-video.py @@ -56,9 +56,15 @@ async def fetch_user_image(params: FunctionCallParams): logger.debug(f"Requesting image with user_id={user_id}, question={question}") # Request a user image frame and indicate that it should be added to the - # context. + # context. Also associate it to the function call. await params.llm.push_frame( - UserImageRequestFrame(user_id=user_id, text=question, append_to_context=True), + UserImageRequestFrame( + user_id=user_id, + text=question, + append_to_context=True, + function_name=params.function_name, + tool_call_id=params.tool_call_id, + ), FrameDirection.UPSTREAM, ) diff --git a/examples/foundational/14e-function-calling-google.py b/examples/foundational/14e-function-calling-google.py index 9412d8027..69791ffbc 100644 --- a/examples/foundational/14e-function-calling-google.py +++ b/examples/foundational/14e-function-calling-google.py @@ -5,7 +5,6 @@ # -import asyncio import os from dotenv import load_dotenv @@ -16,7 +15,7 @@ from pipecat.adapters.schemas.tools_schema import ToolsSchema from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3 from pipecat.audio.vad.silero import SileroVADAnalyzer from pipecat.audio.vad.vad_analyzer import VADParams -from pipecat.frames.frames import LLMRunFrame, TTSSpeakFrame +from pipecat.frames.frames import LLMRunFrame, TTSSpeakFrame, UserImageRequestFrame from pipecat.pipeline.pipeline import Pipeline from pipecat.pipeline.runner import PipelineRunner from pipecat.pipeline.task import PipelineParams, PipelineTask @@ -25,6 +24,7 @@ from pipecat.processors.aggregators.llm_response_universal import ( LLMContextAggregatorPair, LLMUserAggregatorParams, ) +from pipecat.processors.frame_processor import FrameDirection from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import ( create_transport, @@ -43,10 +43,6 @@ from pipecat.turns.user_turn_strategies import UserTurnStrategies load_dotenv(override=True) -# Global variable to store the client ID -client_id = "" - - async def get_weather(params: FunctionCallParams): location = params.arguments["location"] await params.result_callback(f"The weather in {location} is currently 72 degrees and sunny.") @@ -57,19 +53,36 @@ async def fetch_restaurant_recommendation(params: FunctionCallParams): async def get_image(params: FunctionCallParams): - question = params.arguments["question"] - logger.debug(f"Requesting image with user_id={client_id}, question={question}") + """Fetch the user image and push it to the LLM. - # Request the image frame - await params.llm.request_image_frame( - user_id=client_id, - function_name=params.function_name, - tool_call_id=params.tool_call_id, - text_content=question, + When called, this function pushes a UserImageRequestFrame upstream to the + transport. As a result, the transport will request the user image and push a + UserImageRawFrame downstream which will be added to the context by the LLM + assistant aggregator. + """ + user_id = params.arguments["user_id"] + question = params.arguments["question"] + logger.debug(f"Requesting image with user_id={user_id}, question={question}") + + # Request a user image frame and indicate that it should be added to the + # context. Also associate it to the function call. + await params.llm.push_frame( + UserImageRequestFrame( + user_id=user_id, + text=question, + append_to_context=True, + function_name=params.function_name, + tool_call_id=params.tool_call_id, + ), + FrameDirection.UPSTREAM, ) await params.result_callback(None) + # Instead of None, it's possible to also provide a tool call answer to + # tell the LLM that we are grabbing the image to analyze. + # await params.result_callback({"result": "Image is being captured."}) + # We store functions so objects (e.g. SileroVADAnalyzer) don't get # instantiated. The function will be called when the desired transport gets @@ -138,14 +151,18 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): ) get_image_function = FunctionSchema( name="get_image", - description="Get an image from the video stream.", + description="Called when the user requests a description of their camera feed", properties={ + "user_id": { + "type": "string", + "description": "The ID of the user to grab the image from", + }, "question": { "type": "string", - "description": "The question that the user is asking about the image.", - } + "description": "The question that the user is asking about the image", + }, }, - required=["question"], + required=["user_id", "question"], ) tools = ToolsSchema(standard_tools=[weather_function, get_image_function, restaurant_function]) @@ -169,7 +186,6 @@ indicate you should use the get_image tool are: """ messages = [ {"role": "system", "content": system_prompt}, - {"role": "user", "content": "Say hello."}, ] context = LLMContext(messages, tools) @@ -209,10 +225,15 @@ indicate you should use the get_image tool are: await maybe_capture_participant_camera(transport, client) - global client_id client_id = get_transport_client_id(transport, client) # Kick off the conversation. + messages.append( + { + "role": "system", + "content": f"Please introduce yourself to the user. Use '{client_id}' as the user ID during function calls.", + } + ) await task.queue_frames([LLMRunFrame()]) @transport.event_handler("on_client_disconnected") diff --git a/examples/foundational/20d-persistent-context-gemini.py b/examples/foundational/20d-persistent-context-gemini.py index f70d2b50c..37a2f16a2 100644 --- a/examples/foundational/20d-persistent-context-gemini.py +++ b/examples/foundational/20d-persistent-context-gemini.py @@ -17,7 +17,7 @@ from pipecat.adapters.schemas.tools_schema import ToolsSchema from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3 from pipecat.audio.vad.silero import SileroVADAnalyzer from pipecat.audio.vad.vad_analyzer import VADParams -from pipecat.frames.frames import LLMRunFrame +from pipecat.frames.frames import LLMRunFrame, TTSSpeakFrame, UserImageRequestFrame from pipecat.pipeline.pipeline import Pipeline from pipecat.pipeline.runner import PipelineRunner from pipecat.pipeline.task import PipelineParams, PipelineTask @@ -26,6 +26,7 @@ from pipecat.processors.aggregators.llm_response_universal import ( LLMContextAggregatorPair, LLMUserAggregatorParams, ) +from pipecat.processors.frame_processor import FrameDirection from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import ( create_transport, @@ -46,9 +47,6 @@ load_dotenv(override=True) BASE_FILENAME = "/tmp/pipecat_conversation_" -# Global variable to store the client ID -client_id = "" - async def fetch_weather_from_api(params: FunctionCallParams): temperature = 75 if params.arguments["format"] == "fahrenheit" else 24 @@ -63,19 +61,29 @@ async def fetch_weather_from_api(params: FunctionCallParams): async def get_image(params: FunctionCallParams): + user_id = params.arguments["user_id"] question = params.arguments["question"] - logger.debug(f"Requesting image with user_id={client_id}, question={question}") + logger.debug(f"Requesting image with user_id={user_id}, question={question}") - # Request the image frame - await params.llm.request_image_frame( - user_id=client_id, - function_name=params.function_name, - tool_call_id=params.tool_call_id, - text_content=question, + # Request a user image frame and indicate that it should be added to the + # context. Also associate it to the function call. + await params.llm.push_frame( + UserImageRequestFrame( + user_id=user_id, + text=question, + append_to_context=True, + function_name=params.function_name, + tool_call_id=params.tool_call_id, + ), + FrameDirection.UPSTREAM, ) await params.result_callback(None) + # Instead of None, it's possible to also provide a tool call answer to + # tell the LLM that we are grabbing the image to analyze. + # await params.result_callback({"result": "Image is being captured."}) + async def get_saved_conversation_filenames(params: FunctionCallParams): # Construct the full pattern including the BASE_FILENAME @@ -209,14 +217,18 @@ load_conversation_function = FunctionSchema( get_image_function = FunctionSchema( name="get_image", - description="Get and image from the camera or video stream.", + description="Called when the user requests a description of their camera feed", properties={ + "user_id": { + "type": "string", + "description": "The ID of the user to grab the image from", + }, "question": { "type": "string", - "description": "The question to to use when running inference on the acquired image.", + "description": "The question that the user is asking about the image", }, }, - required=["question"], + required=["user_id", "question"], ) tools = ToolsSchema( @@ -306,10 +318,15 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): await maybe_capture_participant_camera(transport, client) - global client_id client_id = get_transport_client_id(transport, client) # Kick off the conversation. + messages.append( + { + "role": "system", + "content": f"Please introduce yourself to the user. Use '{client_id}' as the user ID during function calls.", + } + ) await task.queue_frames([LLMRunFrame()]) @transport.event_handler("on_client_disconnected") From 9d6067fa785deb2dd7953c1a2175e5dd5c9cbb60 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Aleix=20Conchillo=20Flaqu=C3=A9?= Date: Tue, 13 Jan 2026 12:07:11 -0800 Subject: [PATCH 0033/1060] examples(foundational): speak "Let me check on that" in 14d examples --- .../foundational/14d-function-calling-anthropic-video.py | 6 +++++- examples/foundational/14d-function-calling-aws-video.py | 6 +++++- .../foundational/14d-function-calling-gemini-flash-video.py | 6 +++++- .../foundational/14d-function-calling-moondream-video.py | 5 +++++ examples/foundational/14d-function-calling-openai-video.py | 6 +++++- 5 files changed, 25 insertions(+), 4 deletions(-) diff --git a/examples/foundational/14d-function-calling-anthropic-video.py b/examples/foundational/14d-function-calling-anthropic-video.py index 12f80a418..d851b99fc 100644 --- a/examples/foundational/14d-function-calling-anthropic-video.py +++ b/examples/foundational/14d-function-calling-anthropic-video.py @@ -14,7 +14,7 @@ from pipecat.adapters.schemas.tools_schema import ToolsSchema from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3 from pipecat.audio.vad.silero import SileroVADAnalyzer from pipecat.audio.vad.vad_analyzer import VADParams -from pipecat.frames.frames import LLMRunFrame, UserImageRequestFrame +from pipecat.frames.frames import LLMRunFrame, TTSSpeakFrame, UserImageRequestFrame from pipecat.pipeline.pipeline import Pipeline from pipecat.pipeline.runner import PipelineRunner from pipecat.pipeline.task import PipelineParams, PipelineTask @@ -107,6 +107,10 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): llm = AnthropicLLMService(api_key=os.getenv("ANTHROPIC_API_KEY")) llm.register_function("fetch_user_image", fetch_user_image) + @llm.event_handler("on_function_calls_started") + async def on_function_calls_started(service, function_calls): + await tts.queue_frame(TTSSpeakFrame("Let me check on that.")) + fetch_image_function = FunctionSchema( name="fetch_user_image", description="Called when the user requests a description of their camera feed", diff --git a/examples/foundational/14d-function-calling-aws-video.py b/examples/foundational/14d-function-calling-aws-video.py index 4a12f0652..3e8c1785f 100644 --- a/examples/foundational/14d-function-calling-aws-video.py +++ b/examples/foundational/14d-function-calling-aws-video.py @@ -14,7 +14,7 @@ from pipecat.adapters.schemas.tools_schema import ToolsSchema from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3 from pipecat.audio.vad.silero import SileroVADAnalyzer from pipecat.audio.vad.vad_analyzer import VADParams -from pipecat.frames.frames import LLMRunFrame, UserImageRequestFrame +from pipecat.frames.frames import LLMRunFrame, TTSSpeakFrame, UserImageRequestFrame from pipecat.pipeline.pipeline import Pipeline from pipecat.pipeline.runner import PipelineRunner from pipecat.pipeline.task import PipelineParams, PipelineTask @@ -114,6 +114,10 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): ) llm.register_function("fetch_user_image", fetch_user_image) + @llm.event_handler("on_function_calls_started") + async def on_function_calls_started(service, function_calls): + await tts.queue_frame(TTSSpeakFrame("Let me check on that.")) + fetch_image_function = FunctionSchema( name="fetch_user_image", description="Called when the user requests a description of their camera feed", diff --git a/examples/foundational/14d-function-calling-gemini-flash-video.py b/examples/foundational/14d-function-calling-gemini-flash-video.py index 672eec72d..2c6a6c6ac 100644 --- a/examples/foundational/14d-function-calling-gemini-flash-video.py +++ b/examples/foundational/14d-function-calling-gemini-flash-video.py @@ -14,7 +14,7 @@ from pipecat.adapters.schemas.tools_schema import ToolsSchema from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3 from pipecat.audio.vad.silero import SileroVADAnalyzer from pipecat.audio.vad.vad_analyzer import VADParams -from pipecat.frames.frames import LLMRunFrame, UserImageRequestFrame +from pipecat.frames.frames import LLMRunFrame, TTSSpeakFrame, UserImageRequestFrame from pipecat.pipeline.pipeline import Pipeline from pipecat.pipeline.runner import PipelineRunner from pipecat.pipeline.task import PipelineParams, PipelineTask @@ -107,6 +107,10 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): llm = GoogleLLMService(api_key=os.getenv("GOOGLE_API_KEY")) llm.register_function("fetch_user_image", fetch_user_image) + @llm.event_handler("on_function_calls_started") + async def on_function_calls_started(service, function_calls): + await tts.queue_frame(TTSSpeakFrame("Let me check on that.")) + fetch_image_function = FunctionSchema( name="fetch_user_image", description="Called when the user requests a description of their camera feed", diff --git a/examples/foundational/14d-function-calling-moondream-video.py b/examples/foundational/14d-function-calling-moondream-video.py index cc6e48f65..cf244880c 100644 --- a/examples/foundational/14d-function-calling-moondream-video.py +++ b/examples/foundational/14d-function-calling-moondream-video.py @@ -20,6 +20,7 @@ from pipecat.frames.frames import ( LLMFullResponseStartFrame, LLMRunFrame, TextFrame, + TTSSpeakFrame, UserImageRequestFrame, ) from pipecat.pipeline.parallel_pipeline import ParallelPipeline @@ -136,6 +137,10 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): llm = OpenAILLMService(api_key=os.getenv("OPENAI_API_KEY")) llm.register_function("fetch_user_image", fetch_user_image) + @llm.event_handler("on_function_calls_started") + async def on_function_calls_started(service, function_calls): + await tts.queue_frame(TTSSpeakFrame("Let me check on that.")) + fetch_image_function = FunctionSchema( name="fetch_user_image", description="Called when the user requests a description of their camera feed", diff --git a/examples/foundational/14d-function-calling-openai-video.py b/examples/foundational/14d-function-calling-openai-video.py index c7921da18..e1c3f52be 100644 --- a/examples/foundational/14d-function-calling-openai-video.py +++ b/examples/foundational/14d-function-calling-openai-video.py @@ -15,7 +15,7 @@ from pipecat.adapters.schemas.tools_schema import ToolsSchema from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3 from pipecat.audio.vad.silero import SileroVADAnalyzer from pipecat.audio.vad.vad_analyzer import VADParams -from pipecat.frames.frames import LLMRunFrame, UserImageRequestFrame +from pipecat.frames.frames import LLMRunFrame, TTSSpeakFrame, UserImageRequestFrame from pipecat.pipeline.pipeline import Pipeline from pipecat.pipeline.runner import PipelineRunner from pipecat.pipeline.task import PipelineParams, PipelineTask @@ -107,6 +107,10 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): llm = OpenAILLMService(api_key=os.getenv("OPENAI_API_KEY")) llm.register_function("fetch_user_image", fetch_user_image) + @llm.event_handler("on_function_calls_started") + async def on_function_calls_started(service, function_calls): + await tts.queue_frame(TTSSpeakFrame("Let me check on that.")) + fetch_image_function = FunctionSchema( name="fetch_user_image", description="Called when the user requests a description of their camera feed", From aa2589d3beb7bfca90b16d5b2a71c735ef515aaf Mon Sep 17 00:00:00 2001 From: Mark Backman Date: Tue, 13 Jan 2026 15:13:05 -0500 Subject: [PATCH 0034/1060] Update examples to use transcription events from context aggregators --- examples/foundational/19-openai-realtime.py | 40 +++++++++++-------- .../19b-openai-realtime-beta-text.py | 16 +------- .../foundational/19b-openai-realtime-text.py | 16 +------- examples/foundational/40-aws-nova-sonic.py | 25 ++++++++++-- .../foundational/42-interruption-config.py | 13 ++---- examples/foundational/51-grok-realtime.py | 35 ++++++++-------- 6 files changed, 69 insertions(+), 76 deletions(-) diff --git a/examples/foundational/19-openai-realtime.py b/examples/foundational/19-openai-realtime.py index cea164543..2b3750d0b 100644 --- a/examples/foundational/19-openai-realtime.py +++ b/examples/foundational/19-openai-realtime.py @@ -15,14 +15,17 @@ from loguru import logger from pipecat.adapters.schemas.function_schema import FunctionSchema from pipecat.adapters.schemas.tools_schema import ToolsSchema from pipecat.audio.vad.silero import SileroVADAnalyzer -from pipecat.frames.frames import LLMRunFrame, LLMSetToolsFrame, TranscriptionMessage +from pipecat.frames.frames import LLMRunFrame, LLMSetToolsFrame from pipecat.observers.loggers.transcription_log_observer import TranscriptionLogObserver from pipecat.pipeline.pipeline import Pipeline from pipecat.pipeline.runner import PipelineRunner from pipecat.pipeline.task import PipelineParams, PipelineTask from pipecat.processors.aggregators.llm_context import LLMContext -from pipecat.processors.aggregators.llm_response_universal import LLMContextAggregatorPair -from pipecat.processors.transcript_processor import TranscriptProcessor +from pipecat.processors.aggregators.llm_response_universal import ( + AssistantTurnStoppedMessage, + LLMContextAggregatorPair, + UserTurnStoppedMessage, +) from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport from pipecat.services.llm_service import FunctionCallParams @@ -177,8 +180,6 @@ Remember, your responses should be short. Just one or two sentences, usually. Re llm.register_function("get_restaurant_recommendation", fetch_restaurant_recommendation) llm.register_function("get_news", get_news) - transcript = TranscriptProcessor() - # Create a standard OpenAI LLM context object using the normal messages format. The # OpenAIRealtimeLLMService will convert this internally to messages that the # openai WebSocket API can understand. @@ -189,15 +190,16 @@ Remember, your responses should be short. Just one or two sentences, usually. Re context_aggregator = LLMContextAggregatorPair(context) + user_aggregator = context_aggregator.user() + assistant_aggregator = context_aggregator.assistant() + pipeline = Pipeline( [ transport.input(), # Transport user input - context_aggregator.user(), - transcript.user(), # LLM pushes TranscriptionFrames upstream + user_aggregator, llm, # LLM transport.output(), # Transport bot output - transcript.assistant(), # After the transcript output, to time with the audio output - context_aggregator.assistant(), + assistant_aggregator, ] ) @@ -238,14 +240,18 @@ Remember, your responses should be short. Just one or two sentences, usually. Re logger.info(f"Client disconnected") await task.cancel() - # Register event handler for transcript updates - @transcript.event_handler("on_transcript_update") - async def on_transcript_update(processor, frame): - for msg in frame.messages: - if isinstance(msg, TranscriptionMessage): - timestamp = f"[{msg.timestamp}] " if msg.timestamp else "" - line = f"{timestamp}{msg.role}: {msg.content}" - logger.info(f"Transcript: {line}") + # Log transcript updates + @user_aggregator.event_handler("on_user_turn_stopped") + async def on_user_turn_stopped(aggregator, strategy, message: UserTurnStoppedMessage): + timestamp = f"[{message.timestamp}] " if message.timestamp else "" + line = f"{timestamp}user: {message.content}" + logger.info(f"Transcript: {line}") + + @assistant_aggregator.event_handler("on_assistant_turn_stopped") + async def on_assistant_turn_stopped(aggregator, message: AssistantTurnStoppedMessage): + timestamp = f"[{message.timestamp}] " if message.timestamp else "" + line = f"{timestamp}assistant: {message.content}" + logger.info(f"Transcript: {line}") runner = PipelineRunner(handle_sigint=runner_args.handle_sigint) diff --git a/examples/foundational/19b-openai-realtime-beta-text.py b/examples/foundational/19b-openai-realtime-beta-text.py index 0c66385d2..4ddd068a6 100644 --- a/examples/foundational/19b-openai-realtime-beta-text.py +++ b/examples/foundational/19b-openai-realtime-beta-text.py @@ -14,12 +14,11 @@ from loguru import logger from pipecat.adapters.schemas.function_schema import FunctionSchema from pipecat.adapters.schemas.tools_schema import ToolsSchema from pipecat.audio.vad.silero import SileroVADAnalyzer -from pipecat.frames.frames import LLMRunFrame, TranscriptionMessage +from pipecat.frames.frames import LLMRunFrame from pipecat.pipeline.pipeline import Pipeline from pipecat.pipeline.runner import PipelineRunner from pipecat.pipeline.task import PipelineParams, PipelineTask from pipecat.processors.aggregators.openai_llm_context import OpenAILLMContext -from pipecat.processors.transcript_processor import TranscriptProcessor from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport from pipecat.services.cartesia.tts import CartesiaTTSService @@ -157,8 +156,6 @@ Remember, your responses should be short. Just one or two sentences, usually. Re llm.register_function("get_current_weather", fetch_weather_from_api) llm.register_function("get_restaurant_recommendation", fetch_restaurant_recommendation) - transcript = TranscriptProcessor() - # Create a standard OpenAI LLM context object using the normal messages format. The # OpenAIRealtimeBetaLLMService will convert this internally to messages that the # openai WebSocket API can understand. @@ -175,9 +172,7 @@ Remember, your responses should be short. Just one or two sentences, usually. Re context_aggregator.user(), llm, # LLM tts, # TTS - transcript.user(), # Placed after the LLM, as LLM pushes TranscriptionFrames downstream transport.output(), # Transport bot output - transcript.assistant(), # After the transcript output, to time with the audio output context_aggregator.assistant(), ] ) @@ -202,15 +197,6 @@ Remember, your responses should be short. Just one or two sentences, usually. Re logger.info(f"Client disconnected") await task.cancel() - # Register event handler for transcript updates - @transcript.event_handler("on_transcript_update") - async def on_transcript_update(processor, frame): - for msg in frame.messages: - if isinstance(msg, TranscriptionMessage): - timestamp = f"[{msg.timestamp}] " if msg.timestamp else "" - line = f"{timestamp}{msg.role}: {msg.content}" - logger.info(f"Transcript: {line}") - runner = PipelineRunner(handle_sigint=runner_args.handle_sigint) await runner.run(task) diff --git a/examples/foundational/19b-openai-realtime-text.py b/examples/foundational/19b-openai-realtime-text.py index 927e5f5c1..ec254f186 100644 --- a/examples/foundational/19b-openai-realtime-text.py +++ b/examples/foundational/19b-openai-realtime-text.py @@ -14,13 +14,12 @@ from loguru import logger from pipecat.adapters.schemas.function_schema import FunctionSchema from pipecat.adapters.schemas.tools_schema import ToolsSchema from pipecat.audio.vad.silero import SileroVADAnalyzer -from pipecat.frames.frames import LLMRunFrame, TranscriptionMessage +from pipecat.frames.frames import LLMRunFrame from pipecat.pipeline.pipeline import Pipeline from pipecat.pipeline.runner import PipelineRunner from pipecat.pipeline.task import PipelineParams, PipelineTask from pipecat.processors.aggregators.llm_context import LLMContext from pipecat.processors.aggregators.llm_response_universal import LLMContextAggregatorPair -from pipecat.processors.transcript_processor import TranscriptProcessor from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport from pipecat.services.cartesia.tts import CartesiaTTSService @@ -164,8 +163,6 @@ Remember, your responses should be short. Just one or two sentences, usually. Re llm.register_function("get_current_weather", fetch_weather_from_api) llm.register_function("get_restaurant_recommendation", fetch_restaurant_recommendation) - transcript = TranscriptProcessor() - # Create a standard OpenAI LLM context object using the normal messages format. The # OpenAIRealtimeLLMService will convert this internally to messages that the # openai WebSocket API can understand. @@ -180,11 +177,9 @@ Remember, your responses should be short. Just one or two sentences, usually. Re [ transport.input(), # Transport user input context_aggregator.user(), - transcript.user(), # LLM pushes TranscriptionFrames upstream llm, # LLM tts, # TTS transport.output(), # Transport bot output - transcript.assistant(), # After the transcript output, to time with the audio output context_aggregator.assistant(), ] ) @@ -209,15 +204,6 @@ Remember, your responses should be short. Just one or two sentences, usually. Re logger.info(f"Client disconnected") await task.cancel() - # Register event handler for transcript updates - @transcript.event_handler("on_transcript_update") - async def on_transcript_update(processor, frame): - for msg in frame.messages: - if isinstance(msg, TranscriptionMessage): - timestamp = f"[{msg.timestamp}] " if msg.timestamp else "" - line = f"{timestamp}{msg.role}: {msg.content}" - logger.info(f"Transcript: {line}") - runner = PipelineRunner(handle_sigint=runner_args.handle_sigint) await runner.run(task) diff --git a/examples/foundational/40-aws-nova-sonic.py b/examples/foundational/40-aws-nova-sonic.py index 253b0870a..42eac74a8 100644 --- a/examples/foundational/40-aws-nova-sonic.py +++ b/examples/foundational/40-aws-nova-sonic.py @@ -21,7 +21,11 @@ from pipecat.pipeline.pipeline import Pipeline from pipecat.pipeline.runner import PipelineRunner from pipecat.pipeline.task import PipelineParams, PipelineTask from pipecat.processors.aggregators.llm_context import LLMContext -from pipecat.processors.aggregators.llm_response_universal import LLMContextAggregatorPair +from pipecat.processors.aggregators.llm_response_universal import ( + AssistantTurnStoppedMessage, + LLMContextAggregatorPair, + UserTurnStoppedMessage, +) from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport from pipecat.services.aws.nova_sonic.llm import AWSNovaSonicLLMService @@ -154,14 +158,17 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): ) context_aggregator = LLMContextAggregatorPair(context) + user_aggregator = context_aggregator.user() + assistant_aggregator = context_aggregator.assistant() + # Build the pipeline pipeline = Pipeline( [ transport.input(), - context_aggregator.user(), + user_aggregator, llm, transport.output(), - context_aggregator.assistant(), + assistant_aggregator, ] ) @@ -192,6 +199,18 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): logger.info(f"Client disconnected") await task.cancel() + @user_aggregator.event_handler("on_user_turn_stopped") + async def on_user_turn_stopped(aggregator, strategy, message: UserTurnStoppedMessage): + timestamp = f"[{message.timestamp}] " if message.timestamp else "" + line = f"{timestamp}user: {message.content}" + logger.info(f"Transcript: {line}") + + @assistant_aggregator.event_handler("on_assistant_turn_stopped") + async def on_assistant_turn_stopped(aggregator, message: AssistantTurnStoppedMessage): + timestamp = f"[{message.timestamp}] " if message.timestamp else "" + line = f"{timestamp}assistant: {message.content}" + logger.info(f"Transcript: {line}") + # Run the pipeline runner = PipelineRunner(handle_sigint=runner_args.handle_sigint) await runner.run(task) diff --git a/examples/foundational/42-interruption-config.py b/examples/foundational/42-interruption-config.py index d2c95eecb..46937abfa 100644 --- a/examples/foundational/42-interruption-config.py +++ b/examples/foundational/42-interruption-config.py @@ -13,6 +13,7 @@ from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnal from pipecat.audio.vad.silero import SileroVADAnalyzer from pipecat.audio.vad.vad_analyzer import VADParams from pipecat.frames.frames import LLMRunFrame +from pipecat.observers.loggers.transcription_log_observer import TranscriptionLogObserver from pipecat.pipeline.pipeline import Pipeline from pipecat.pipeline.runner import PipelineRunner from pipecat.pipeline.task import PipelineParams, PipelineTask @@ -21,7 +22,6 @@ from pipecat.processors.aggregators.llm_response_universal import ( LLMContextAggregatorPair, LLMUserAggregatorParams, ) -from pipecat.processors.transcript_processor import TranscriptProcessor from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport from pipecat.services.cartesia.tts import CartesiaTTSService @@ -36,6 +36,7 @@ from pipecat.turns.user_turn_strategies import UserTurnStrategies load_dotenv(override=True) + # We store functions so objects (e.g. SileroVADAnalyzer) don't get # instantiated. The function will be called when the desired transport gets # selected. @@ -70,8 +71,6 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): llm = OpenAILLMService(api_key=os.getenv("OPENAI_API_KEY")) - transcript = TranscriptProcessor() - messages = [ { "role": "system", @@ -94,7 +93,6 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): [ transport.input(), # Transport user input stt, - transcript.user(), # User transcripts context_aggregator.user(), # User responses llm, # LLM tts, # TTS @@ -110,6 +108,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): enable_usage_metrics=True, ), idle_timeout_secs=runner_args.pipeline_idle_timeout_secs, + observers=[TranscriptionLogObserver()], ) @transport.event_handler("on_client_connected") @@ -124,12 +123,6 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): logger.info(f"Client disconnected") await task.cancel() - # Register event handler for transcript updates - @transcript.event_handler("on_transcript_update") - async def on_transcript_update(processor, frame): - for message in frame.messages: - logger.info(f"Transcription [{message.role}]: {message.content}") - runner = PipelineRunner(handle_sigint=runner_args.handle_sigint) await runner.run(task) diff --git a/examples/foundational/51-grok-realtime.py b/examples/foundational/51-grok-realtime.py index f56b2cb8e..ee795270a 100644 --- a/examples/foundational/51-grok-realtime.py +++ b/examples/foundational/51-grok-realtime.py @@ -36,7 +36,7 @@ from pipecat.adapters.schemas.tools_schema import ToolsSchema # Note: Grok has built-in server-side VAD, so we don't need local VAD # from pipecat.audio.vad.silero import SileroVADAnalyzer -from pipecat.frames.frames import LLMRunFrame, TranscriptionMessage +from pipecat.frames.frames import LLMRunFrame from pipecat.observers.loggers.transcription_log_observer import ( TranscriptionLogObserver, ) @@ -45,9 +45,10 @@ from pipecat.pipeline.runner import PipelineRunner from pipecat.pipeline.task import PipelineParams, PipelineTask from pipecat.processors.aggregators.llm_context import LLMContext from pipecat.processors.aggregators.llm_response_universal import ( + AssistantTurnStoppedMessage, LLMContextAggregatorPair, + UserTurnStoppedMessage, ) -from pipecat.processors.transcript_processor import TranscriptProcessor from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport from pipecat.services.grok.realtime.events import ( @@ -208,9 +209,6 @@ Always be helpful and proactive in offering assistance.""", llm.register_function("get_current_time", get_current_time) llm.register_function("get_restaurant_recommendation", get_restaurant_recommendation) - # Create transcript processor for logging - transcript = TranscriptProcessor() - # Create context with initial message and tools context = LLMContext( [{"role": "user", "content": "Say hello and introduce yourself!"}], @@ -219,18 +217,19 @@ Always be helpful and proactive in offering assistance.""", context_aggregator = LLMContextAggregatorPair(context) + user_aggregator = context_aggregator.user() + assistant_aggregator = context_aggregator.assistant() + # Build the pipeline # Note: In realtime mode, transcription comes from Grok (upstream), # so transcript.user() goes BEFORE llm pipeline = Pipeline( [ transport.input(), # Transport user input (audio) - context_aggregator.user(), - transcript.user(), # Transcription from Grok goes upstream + user_aggregator, llm, # Grok Realtime LLM (handles STT + LLM + TTS) transport.output(), # Transport bot output (audio) - transcript.assistant(), # Log assistant speech - context_aggregator.assistant(), + assistant_aggregator, ] ) @@ -256,13 +255,17 @@ Always be helpful and proactive in offering assistance.""", await task.cancel() # Log transcript updates - @transcript.event_handler("on_transcript_update") - async def on_transcript_update(processor, frame): - for msg in frame.messages: - if isinstance(msg, TranscriptionMessage): - timestamp = f"[{msg.timestamp}] " if msg.timestamp else "" - line = f"{timestamp}{msg.role}: {msg.content}" - logger.info(f"Transcript: {line}") + @user_aggregator.event_handler("on_user_turn_stopped") + async def on_user_turn_stopped(aggregator, strategy, message: UserTurnStoppedMessage): + timestamp = f"[{message.timestamp}] " if message.timestamp else "" + line = f"{timestamp}user: {message.content}" + logger.info(f"Transcript: {line}") + + @assistant_aggregator.event_handler("on_assistant_turn_stopped") + async def on_assistant_turn_stopped(aggregator, message: AssistantTurnStoppedMessage): + timestamp = f"[{message.timestamp}] " if message.timestamp else "" + line = f"{timestamp}assistant: {message.content}" + logger.info(f"Transcript: {line}") runner = PipelineRunner(handle_sigint=runner_args.handle_sigint) From d591f9e108e7128ab72dfe5478b4eb1645cc6eda Mon Sep 17 00:00:00 2001 From: Mark Backman Date: Tue, 13 Jan 2026 15:20:59 -0500 Subject: [PATCH 0035/1060] Remove 28-transcription-processor.py --- .../28-transcription-processor.py | 209 ------------------ 1 file changed, 209 deletions(-) delete mode 100644 examples/foundational/28-transcription-processor.py diff --git a/examples/foundational/28-transcription-processor.py b/examples/foundational/28-transcription-processor.py deleted file mode 100644 index 0b057a621..000000000 --- a/examples/foundational/28-transcription-processor.py +++ /dev/null @@ -1,209 +0,0 @@ -# -# Copyright (c) 2024-2026, Daily -# -# SPDX-License-Identifier: BSD 2-Clause License -# - -import os -from typing import List, Optional - -from dotenv import load_dotenv -from loguru import logger - -from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3 -from pipecat.audio.vad.silero import SileroVADAnalyzer -from pipecat.audio.vad.vad_analyzer import VADParams -from pipecat.frames.frames import LLMRunFrame, TranscriptionMessage, TranscriptionUpdateFrame -from pipecat.pipeline.pipeline import Pipeline -from pipecat.pipeline.runner import PipelineRunner -from pipecat.pipeline.task import PipelineParams, PipelineTask -from pipecat.processors.aggregators.llm_context import LLMContext -from pipecat.processors.aggregators.llm_response_universal import ( - LLMContextAggregatorPair, - LLMUserAggregatorParams, -) -from pipecat.processors.transcript_processor import TranscriptProcessor -from pipecat.runner.types import RunnerArguments -from pipecat.runner.utils import create_transport -from pipecat.services.cartesia.tts import CartesiaTTSService -from pipecat.services.deepgram.stt import DeepgramSTTService -from pipecat.services.openai.llm import OpenAILLMService -from pipecat.transports.base_transport import BaseTransport, TransportParams -from pipecat.transports.daily.transport import DailyParams -from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams -from pipecat.turns.user_stop import TurnAnalyzerUserTurnStopStrategy -from pipecat.turns.user_turn_strategies import UserTurnStrategies - -load_dotenv(override=True) - - -class TranscriptHandler: - """Handles real-time transcript processing and output. - - Maintains a list of conversation messages and outputs them either to a log - or to a file as they are received. Each message includes its timestamp and role. - - Attributes: - messages: List of all processed transcript messages - output_file: Optional path to file where transcript is saved. If None, outputs to log only. - """ - - def __init__(self, output_file: Optional[str] = None): - """Initialize handler with optional file output. - - Args: - output_file: Path to output file. If None, outputs to log only. - """ - self.messages: List[TranscriptionMessage] = [] - self.output_file: Optional[str] = output_file - logger.debug( - f"TranscriptHandler initialized {'with output_file=' + output_file if output_file else 'with log output only'}" - ) - - async def save_message(self, message: TranscriptionMessage): - """Save a single transcript message. - - Outputs the message to the log and optionally to a file. - - Args: - message: The message to save - """ - timestamp = f"[{message.timestamp}] " if message.timestamp else "" - line = f"{timestamp}{message.role}: {message.content}" - - # Always log the message - logger.info(f"Transcript: {line}") - - # Optionally write to file - if self.output_file: - try: - with open(self.output_file, "a", encoding="utf-8") as f: - f.write(line + "\n") - except Exception as e: - logger.error(f"Error saving transcript message to file: {e}") - - async def on_transcript_update( - self, processor: TranscriptProcessor, frame: TranscriptionUpdateFrame - ): - """Handle new transcript messages. - - Args: - processor: The TranscriptProcessor that emitted the update - frame: TranscriptionUpdateFrame containing new messages - """ - logger.debug(f"Received transcript update with {len(frame.messages)} new messages") - - for msg in frame.messages: - self.messages.append(msg) - await self.save_message(msg) - - -# We store functions so objects (e.g. SileroVADAnalyzer) don't get -# instantiated. The function will be called when the desired transport gets -# selected. -transport_params = { - "daily": lambda: DailyParams( - audio_in_enabled=True, - audio_out_enabled=True, - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), - ), - "twilio": lambda: FastAPIWebsocketParams( - audio_in_enabled=True, - audio_out_enabled=True, - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), - ), - "webrtc": lambda: TransportParams( - audio_in_enabled=True, - audio_out_enabled=True, - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), - ), -} - - -async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): - logger.info(f"Starting bot") - - stt = DeepgramSTTService(api_key=os.getenv("DEEPGRAM_API_KEY")) - - tts = CartesiaTTSService( - api_key=os.getenv("CARTESIA_API_KEY"), - voice_id="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady - ) - - llm = OpenAILLMService(api_key=os.getenv("OPENAI_API_KEY")) - - messages = [ - { - "role": "system", - "content": "You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative, helpful, and brief way. Say hello.", - }, - ] - - context = LLMContext(messages) - context_aggregator = LLMContextAggregatorPair( - context, - user_params=LLMUserAggregatorParams( - user_turn_strategies=UserTurnStrategies( - stop=[TurnAnalyzerUserTurnStopStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3())] - ), - ), - ) - - # Create transcript processor and handler - transcript = TranscriptProcessor() - transcript_handler = TranscriptHandler() # Output to log only - # transcript_handler = TranscriptHandler(output_file="transcript.txt") # Output to file and log - - pipeline = Pipeline( - [ - transport.input(), # Transport user input - stt, # STT - transcript.user(), # User transcripts - context_aggregator.user(), # User responses - llm, # LLM - tts, # TTS - transport.output(), # Transport bot output - transcript.assistant(), # Assistant transcripts - context_aggregator.assistant(), # Assistant spoken responses - ] - ) - - task = PipelineTask( - pipeline, - params=PipelineParams( - enable_metrics=True, - enable_usage_metrics=True, - ), - idle_timeout_secs=runner_args.pipeline_idle_timeout_secs, - ) - - @transport.event_handler("on_client_connected") - async def on_client_connected(transport, client): - logger.info(f"Client connected") - # Start conversation - empty prompt to let LLM follow system instructions - await task.queue_frames([LLMRunFrame()]) - - # Register event handler for transcript updates - @transcript.event_handler("on_transcript_update") - async def on_transcript_update(processor, frame): - await transcript_handler.on_transcript_update(processor, frame) - - @transport.event_handler("on_client_disconnected") - async def on_client_disconnected(transport, client): - logger.info(f"Client disconnected") - await task.cancel() - - runner = PipelineRunner(handle_sigint=runner_args.handle_sigint) - await runner.run(task) - - -async def bot(runner_args: RunnerArguments): - """Main bot entry point compatible with Pipecat Cloud.""" - transport = await create_transport(runner_args, transport_params) - await run_bot(transport, runner_args) - - -if __name__ == "__main__": - from pipecat.runner.run import main - - main() From 21534f7d8300302d4d3b60daad5da392ecc84440 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Aleix=20Conchillo=20Flaqu=C3=A9?= Date: Tue, 13 Jan 2026 12:21:22 -0800 Subject: [PATCH 0036/1060] added changelog file for #3430 --- changelog/3430.fixed.md | 1 + 1 file changed, 1 insertion(+) create mode 100644 changelog/3430.fixed.md diff --git a/changelog/3430.fixed.md b/changelog/3430.fixed.md new file mode 100644 index 000000000..6f689eb78 --- /dev/null +++ b/changelog/3430.fixed.md @@ -0,0 +1 @@ +- Fixed `request_image_frame` (for backwards compatibility) and restored function-call–related fields in `UserImageRequestFrame` and `UserImageRawFrame`, preventing a case where adding a non-LLM message to the context could trigger duplicate LLM inferences (on image arrival and on function-call result), potentially causing an infinite inference loop. From 30fbcfbf717cf472e763974d0429e598f623297c Mon Sep 17 00:00:00 2001 From: Paul Kompfner Date: Tue, 13 Jan 2026 16:33:59 -0500 Subject: [PATCH 0037/1060] Rework fix for parallel function calling with Gemini 3 --- .../adapters/services/gemini_adapter.py | 91 ++++++++++--------- 1 file changed, 50 insertions(+), 41 deletions(-) diff --git a/src/pipecat/adapters/services/gemini_adapter.py b/src/pipecat/adapters/services/gemini_adapter.py index b00543e95..cb6f6d8de 100644 --- a/src/pipecat/adapters/services/gemini_adapter.py +++ b/src/pipecat/adapters/services/gemini_adapter.py @@ -255,8 +255,8 @@ class GeminiLLMAdapter(BaseLLMAdapter[GeminiLLMInvocationParams]): # Apply thought signatures to the corresponding messages self._apply_thought_signatures_to_messages(thought_signature_dicts, messages) - # Merge consecutive tool calls and tool responses into single multi-part messages - messages = self._merge_consecutive_tool_messages(messages) + # When thinking is enabled, merge parallel tool calls into single messages + messages = self._merge_parallel_tool_calls_for_thinking(messages) # Check if we only have function-related messages (no regular text) has_regular_messages = any( @@ -436,23 +436,35 @@ class GeminiLLMAdapter(BaseLLMAdapter[GeminiLLMInvocationParams]): tool_call_id_to_name_mapping=tool_call_id_to_name_mapping, ) - def _merge_consecutive_tool_messages(self, messages: List[Content]) -> List[Content]: - """Merge consecutive tool call messages within tool exchange blocks. + def _merge_parallel_tool_calls_for_thinking(self, messages: List[Content]) -> List[Content]: + """Merge parallel tool calls into single Content objects when thinking is enabled. - Gemini (and Gemini 3 in particular, where thought signatures are - involved) expects multiple parallel tool calls to be in a single Content - with multiple function_call parts. + Gemini expects parallel tool calls (multiple function calls made + simultaneously) to be in a single Content with multiple function_call + Parts. This method takes a list of Content messages, where parallel + tool calls may be split across multiple messages, and merges them into + single messages. - This method detects "tool exchange blocks" (sequences of tool calls and - responses, including alternating patterns like call1, response1, call2, - response2) and merges all tool calls within each block into a single - Content, followed by the individual tool responses. + This only has an effect when thought_signatures are present (i.e., when + thinking is enabled). When thinking is disabled, merging doesn't matter. + When thinking is enabled, there is a guarantee that the first tool call + (and only the first) in any batch of parallel tool calls will have a + thought_signature. This allows us to distinguish: + + - Parallel tool calls: share a single thought_signature (on the first call) + - Sequential tool calls: each have their own thought_signature + + Algorithm: A tool call message with a thought_signature starts a new + parallel group. Any tool call messages after it without a + thought_signature get merged into that group, regardless of what + messages appear in between. Args: messages: List of Content messages to process. Returns: - List of Content messages with tool calls merged within each block. + List of Content messages with parallel tool calls merged when + thought_signatures are present, otherwise unchanged. """ if not messages: return messages @@ -465,17 +477,9 @@ class GeminiLLMAdapter(BaseLLMAdapter[GeminiLLMInvocationParams]): and all(getattr(part, "function_call", None) for part in msg.parts) ) - def is_tool_response_message(msg: Content) -> bool: - """Check if message contains only function_response parts.""" - return ( - msg.role == "user" - and msg.parts - and all(getattr(part, "function_response", None) for part in msg.parts) - ) - - def is_tool_message(msg: Content) -> bool: - """Check if message is either a tool call or tool response.""" - return is_tool_call_message(msg) or is_tool_response_message(msg) + def message_has_thought_signature(msg: Content) -> bool: + """Check if any part in the message has a thought_signature.""" + return any(getattr(part, "thought_signature", None) for part in msg.parts) merged_messages = [] i = 0 @@ -483,26 +487,31 @@ class GeminiLLMAdapter(BaseLLMAdapter[GeminiLLMInvocationParams]): while i < len(messages): current = messages[i] - # Check for a tool exchange block (sequence of tool calls and/or responses) - if is_tool_message(current): - tool_call_parts = [] - tool_response_messages = [] + # If this is a tool call message with a thought signature, start merging + if is_tool_call_message(current) and message_has_thought_signature(current): + merged_parts = list(current.parts) + other_messages = [] + j = i + 1 - # Collect all consecutive tool messages (calls and responses) - j = i - while j < len(messages) and is_tool_message(messages[j]): - msg = messages[j] - if is_tool_call_message(msg): - tool_call_parts.extend(msg.parts) - else: # is_tool_response_message - tool_response_messages.append(msg) - j += 1 - - # Output merged tool calls first, then individual tool responses - if tool_call_parts: - merged_messages.append(Content(role="model", parts=tool_call_parts)) - merged_messages.extend(tool_response_messages) + # Scan forward, merging tool calls without signatures, collecting others + while j < len(messages): + next_msg = messages[j] + if is_tool_call_message(next_msg): + if message_has_thought_signature(next_msg): + # New parallel group starts, stop here + break + else: + # Merge this call into the current group + merged_parts.extend(next_msg.parts) + j += 1 + else: + # Collect non-tool-call message, keep scanning + other_messages.append(next_msg) + j += 1 + # Output merged calls, then collected other messages + merged_messages.append(Content(role="model", parts=merged_parts)) + merged_messages.extend(other_messages) i = j else: merged_messages.append(current) From 5612bf513b504a8d1115ac6720f2f4aa68256470 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Aleix=20Conchillo=20Flaqu=C3=A9?= Date: Tue, 13 Jan 2026 13:50:09 -0800 Subject: [PATCH 0038/1060] LLMContext: fix create_audio_message --- changelog/3435.fixed.md | 1 + src/pipecat/processors/aggregators/llm_context.py | 2 +- 2 files changed, 2 insertions(+), 1 deletion(-) create mode 100644 changelog/3435.fixed.md diff --git a/changelog/3435.fixed.md b/changelog/3435.fixed.md new file mode 100644 index 000000000..a4482c328 --- /dev/null +++ b/changelog/3435.fixed.md @@ -0,0 +1 @@ +- Fixed `LLMContext.create_audio_message()` by correcting an internal helper that was incorrectly declared async while being run in `asyncio.to_thread()`. diff --git a/src/pipecat/processors/aggregators/llm_context.py b/src/pipecat/processors/aggregators/llm_context.py index 205d55269..4b0e95aa7 100644 --- a/src/pipecat/processors/aggregators/llm_context.py +++ b/src/pipecat/processors/aggregators/llm_context.py @@ -206,7 +206,7 @@ class LLMContext: """ content = [{"type": "text", "text": text}] - async def encode_audio(): + def encode_audio(): sample_rate = audio_frames[0].sample_rate num_channels = audio_frames[0].num_channels From bb00d223c96cb45d31ca2c1264a24bb95fa5407e Mon Sep 17 00:00:00 2001 From: Mark Backman Date: Tue, 13 Jan 2026 14:13:32 -0500 Subject: [PATCH 0039/1060] Update 26a to use context aggregator transcription events --- changelog/3431.changed.md | 1 + .../26a-gemini-live-transcription.py | 37 +++++++++++-------- .../services/google/gemini_live/llm.py | 2 +- 3 files changed, 23 insertions(+), 17 deletions(-) create mode 100644 changelog/3431.changed.md diff --git a/changelog/3431.changed.md b/changelog/3431.changed.md new file mode 100644 index 000000000..0a9164491 --- /dev/null +++ b/changelog/3431.changed.md @@ -0,0 +1 @@ +- Updated `GeminiLiveLLMService` to push `LLMThoughtStartFrame`, `LLMThoughtTextFrame`, and `LLMThoughtEndFrame` when the model returns thought content. diff --git a/examples/foundational/26a-gemini-live-transcription.py b/examples/foundational/26a-gemini-live-transcription.py index 0248ca358..ad91ff2a1 100644 --- a/examples/foundational/26a-gemini-live-transcription.py +++ b/examples/foundational/26a-gemini-live-transcription.py @@ -12,13 +12,16 @@ from loguru import logger from pipecat.audio.vad.silero import SileroVADAnalyzer from pipecat.audio.vad.vad_analyzer import VADParams -from pipecat.frames.frames import LLMRunFrame, TranscriptionMessage +from pipecat.frames.frames import LLMRunFrame from pipecat.pipeline.pipeline import Pipeline from pipecat.pipeline.runner import PipelineRunner from pipecat.pipeline.task import PipelineParams, PipelineTask from pipecat.processors.aggregators.llm_context import LLMContext -from pipecat.processors.aggregators.llm_response_universal import LLMContextAggregatorPair -from pipecat.processors.transcript_processor import TranscriptProcessor +from pipecat.processors.aggregators.llm_response_universal import ( + AssistantTurnStoppedMessage, + LLMContextAggregatorPair, + UserTurnStoppedMessage, +) from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport from pipecat.services.google.gemini_live.llm import GeminiLiveLLMService @@ -93,17 +96,16 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): ) context_aggregator = LLMContextAggregatorPair(context) - transcript = TranscriptProcessor() + user_aggregator = context_aggregator.user() + assistant_aggregator = context_aggregator.assistant() pipeline = Pipeline( [ transport.input(), - context_aggregator.user(), - transcript.user(), + user_aggregator, llm, transport.output(), - transcript.assistant(), - context_aggregator.assistant(), + assistant_aggregator, ] ) @@ -127,14 +129,17 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): logger.info(f"Client disconnected") await task.cancel() - # Register event handler for transcript updates - @transcript.event_handler("on_transcript_update") - async def on_transcript_update(processor, frame): - for msg in frame.messages: - if isinstance(msg, TranscriptionMessage): - timestamp = f"[{msg.timestamp}] " if msg.timestamp else "" - line = f"{timestamp}{msg.role}: {msg.content}" - logger.info(f"Transcript: {line}") + @user_aggregator.event_handler("on_user_turn_stopped") + async def on_user_turn_stopped(aggregator, strategy, message: UserTurnStoppedMessage): + timestamp = f"[{message.timestamp}] " if message.timestamp else "" + line = f"{timestamp}user: {message.content}" + logger.info(f"Transcript: {line}") + + @assistant_aggregator.event_handler("on_assistant_turn_stopped") + async def on_assistant_turn_stopped(aggregator, message: AssistantTurnStoppedMessage): + timestamp = f"[{message.timestamp}] " if message.timestamp else "" + line = f"{timestamp}assistant: {message.content}" + logger.info(f"Transcript: {line}") runner = PipelineRunner(handle_sigint=runner_args.handle_sigint) diff --git a/src/pipecat/services/google/gemini_live/llm.py b/src/pipecat/services/google/gemini_live/llm.py index a00eef34f..13b5fb18c 100644 --- a/src/pipecat/services/google/gemini_live/llm.py +++ b/src/pipecat/services/google/gemini_live/llm.py @@ -1464,7 +1464,7 @@ class GeminiLiveLLMService(LLMService): # so bracket each thought in start/end frames await self.push_frame(LLMThoughtStartFrame()) await self.push_frame(LLMThoughtTextFrame(text)) - await self.push_frame(LLMThoughtEndFrame(signature=part.thought_signature)) + await self.push_frame(LLMThoughtEndFrame()) else: # Regular text response self._bot_text_buffer += text From 1ab3bf2ef6a5579f766f6fdab1a03b5fc3b0f452 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Aleix=20Conchillo=20Flaqu=C3=A9?= Date: Tue, 13 Jan 2026 13:40:55 -0800 Subject: [PATCH 0040/1060] LLMContextAggregatorPair: instances can now return a tuple --- .../processors/aggregators/llm_response_universal.py | 12 ++++++++++++ 1 file changed, 12 insertions(+) diff --git a/src/pipecat/processors/aggregators/llm_response_universal.py b/src/pipecat/processors/aggregators/llm_response_universal.py index 901e5c62c..85050e6d0 100644 --- a/src/pipecat/processors/aggregators/llm_response_universal.py +++ b/src/pipecat/processors/aggregators/llm_response_universal.py @@ -1052,3 +1052,15 @@ class LLMContextAggregatorPair: The assistant context aggregator instance. """ return self._assistant + + def __iter__(self): + """Allow tuple unpacking of the aggregator pair. + + This enables both usage patterns:: + pair = LLMContextAggregatorPair(context) # Returns the instance + user, assistant = LLMContextAggregatorPair(context) # Unpacks into tuple + + Yields: + The user aggregator, then the assistant aggregator. + """ + return iter((self._user, self._assistant)) From 861588e4a3cf5d4951999431e3bcd3e5db1290fe Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Aleix=20Conchillo=20Flaqu=C3=A9?= Date: Tue, 13 Jan 2026 13:40:03 -0800 Subject: [PATCH 0041/1060] examples: update all examples to use the new LLMContextAggregatorPair tuple --- examples/foundational/04-transports-small-webrtc.py | 6 +++--- examples/foundational/04a-transports-daily.py | 6 +++--- examples/foundational/04b-transports-livekit.py | 6 +++--- examples/foundational/06-listen-and-respond.py | 6 +++--- examples/foundational/06a-image-sync.py | 6 +++--- examples/foundational/07-interruptible-cartesia-http.py | 6 +++--- examples/foundational/07-interruptible.py | 6 +++--- .../foundational/07a-interruptible-speechmatics-vad.py | 6 +++--- examples/foundational/07a-interruptible-speechmatics.py | 6 +++--- examples/foundational/07aa-interruptible-soniox.py | 6 +++--- examples/foundational/07ab-interruptible-inworld-http.py | 6 +++--- examples/foundational/07ab-interruptible-inworld.py | 6 +++--- examples/foundational/07ac-interruptible-asyncai-http.py | 6 +++--- examples/foundational/07ac-interruptible-asyncai.py | 6 +++--- examples/foundational/07ad-interruptible-aicoustics.py | 6 +++--- examples/foundational/07ae-interruptible-hume.py | 6 +++--- examples/foundational/07af-interruptible-gradium.py | 6 +++--- examples/foundational/07b-interruptible-langchain.py | 6 +++--- examples/foundational/07c-interruptible-deepgram-flux.py | 6 +++--- examples/foundational/07c-interruptible-deepgram-http.py | 6 +++--- .../foundational/07c-interruptible-deepgram-sagemaker.py | 6 +++--- examples/foundational/07c-interruptible-deepgram-vad.py | 6 +++--- examples/foundational/07c-interruptible-deepgram.py | 6 +++--- .../foundational/07d-interruptible-elevenlabs-http.py | 6 +++--- examples/foundational/07d-interruptible-elevenlabs.py | 6 +++--- examples/foundational/07e-interruptible-playht-http.py | 6 +++--- examples/foundational/07e-interruptible-playht.py | 6 +++--- examples/foundational/07f-interruptible-azure-http.py | 6 +++--- examples/foundational/07f-interruptible-azure.py | 6 +++--- examples/foundational/07g-interruptible-openai.py | 6 +++--- examples/foundational/07h-interruptible-openpipe.py | 6 +++--- examples/foundational/07i-interruptible-xtts.py | 6 +++--- examples/foundational/07j-interruptible-gladia-vad.py | 6 +++--- examples/foundational/07j-interruptible-gladia.py | 6 +++--- examples/foundational/07k-interruptible-lmnt.py | 6 +++--- examples/foundational/07l-interruptible-groq.py | 6 +++--- examples/foundational/07m-interruptible-aws-strands.py | 6 +++--- examples/foundational/07m-interruptible-aws.py | 6 +++--- examples/foundational/07n-interruptible-gemini-image.py | 6 +++--- examples/foundational/07n-interruptible-gemini.py | 6 +++--- examples/foundational/07n-interruptible-google-http.py | 6 +++--- examples/foundational/07n-interruptible-google.py | 6 +++--- examples/foundational/07o-interruptible-assemblyai.py | 6 +++--- examples/foundational/07p-interruptible-krisp-viva.py | 6 +++--- examples/foundational/07p-interruptible-krisp.py | 6 +++--- examples/foundational/07q-interruptible-rime-http.py | 6 +++--- examples/foundational/07q-interruptible-rime.py | 6 +++--- examples/foundational/07r-interruptible-nvidia.py | 6 +++--- .../foundational/07s-interruptible-google-audio-in.py | 8 ++++---- examples/foundational/07t-interruptible-fish.py | 6 +++--- examples/foundational/07v-interruptible-neuphonic-http.py | 6 +++--- examples/foundational/07v-interruptible-neuphonic.py | 6 +++--- examples/foundational/07w-interruptible-fal.py | 6 +++--- examples/foundational/07x-interruptible-local.py | 6 +++--- examples/foundational/07y-interruptible-minimax.py | 6 +++--- examples/foundational/07z-interruptible-sarvam-http.py | 6 +++--- examples/foundational/07z-interruptible-sarvam.py | 6 +++--- examples/foundational/08-custom-frame-processor.py | 6 +++--- examples/foundational/10-wake-phrase.py | 6 +++--- examples/foundational/11-sound-effects.py | 6 +++--- examples/foundational/12-describe-image-openai.py | 6 +++--- examples/foundational/12a-describe-image-anthropic.py | 6 +++--- examples/foundational/12b-describe-image-aws.py | 6 +++--- examples/foundational/12c-describe-image-gemini-flash.py | 6 +++--- examples/foundational/14-function-calling.py | 6 +++--- examples/foundational/14a-function-calling-anthropic.py | 6 +++--- examples/foundational/14c-function-calling-together.py | 6 +++--- .../foundational/14d-function-calling-anthropic-video.py | 6 +++--- examples/foundational/14d-function-calling-aws-video.py | 6 +++--- .../14d-function-calling-gemini-flash-video.py | 6 +++--- .../foundational/14d-function-calling-moondream-video.py | 6 +++--- .../foundational/14d-function-calling-openai-video.py | 6 +++--- examples/foundational/14e-function-calling-google.py | 6 +++--- examples/foundational/14f-function-calling-groq.py | 6 +++--- examples/foundational/14g-function-calling-grok.py | 6 +++--- examples/foundational/14h-function-calling-azure.py | 6 +++--- examples/foundational/14i-function-calling-fireworks.py | 6 +++--- examples/foundational/14j-function-calling-nvidia.py | 6 +++--- examples/foundational/14k-function-calling-cerebras.py | 6 +++--- examples/foundational/14l-function-calling-deepseek.py | 6 +++--- examples/foundational/14m-function-calling-openrouter.py | 6 +++--- examples/foundational/14n-function-calling-perplexity.py | 6 +++--- .../foundational/14p-function-calling-gemini-vertex-ai.py | 6 +++--- examples/foundational/14q-function-calling-qwen.py | 6 +++--- examples/foundational/14r-function-calling-aws.py | 6 +++--- examples/foundational/14s-function-calling-sambanova.py | 6 +++--- examples/foundational/14t-function-calling-direct.py | 6 +++--- examples/foundational/14u-function-calling-ollama.py | 6 +++--- examples/foundational/14v-function-calling-openai.py | 6 +++--- examples/foundational/14w-function-calling-mistral.py | 6 +++--- examples/foundational/14x-function-calling-openpipe.py | 6 +++--- examples/foundational/15-switch-voices.py | 6 +++--- examples/foundational/15a-switch-languages.py | 6 +++--- examples/foundational/16-gpu-container-local-bot.py | 6 +++--- examples/foundational/17-detect-user-idle.py | 6 +++--- examples/foundational/19-openai-realtime.py | 5 +---- examples/foundational/19a-azure-realtime.py | 6 +++--- examples/foundational/19b-openai-realtime-text.py | 6 +++--- examples/foundational/19c-openai-realtime-live-video.py | 6 +++--- examples/foundational/20a-persistent-context-openai.py | 6 +++--- .../20b-persistent-context-openai-realtime.py | 6 +++--- examples/foundational/20c-persistent-context-anthropic.py | 6 +++--- examples/foundational/20d-persistent-context-gemini.py | 6 +++--- .../foundational/20e-persistent-context-aws-nova-sonic.py | 6 +++--- .../foundational/20f-persistent-context-grok-realtime.py | 6 +++--- examples/foundational/21-tavus-transport.py | 6 +++--- examples/foundational/21a-tavus-video-service.py | 6 +++--- .../foundational/22b-natural-conversation-proposal.py | 6 +++--- .../foundational/22c-natural-conversation-mixed-llms.py | 6 +++--- .../foundational/22d-natural-conversation-gemini-audio.py | 5 +++-- examples/foundational/23-bot-background-sound.py | 6 +++--- examples/foundational/24-stt-mute-filter.py | 6 +++--- examples/foundational/24-user-mute-strategy.py | 6 +++--- examples/foundational/26a-gemini-live-transcription.py | 8 +++----- examples/foundational/26b-gemini-live-function-calling.py | 6 +++--- examples/foundational/26c-gemini-live-video.py | 6 +++--- examples/foundational/26d-gemini-live-text.py | 6 +++--- examples/foundational/26e-gemini-live-google-search.py | 6 +++--- examples/foundational/26f-gemini-live-files-api.py | 6 +++--- .../foundational/26g-gemini-live-groundingMetadata.py | 6 +++--- .../26h-gemini-live-vertex-function-calling.py | 6 +++--- examples/foundational/26i-gemini-live-graceful-end.py | 6 +++--- examples/foundational/27-simli-layer.py | 6 +++--- examples/foundational/28-user-assistant-turns.py | 5 +---- examples/foundational/29-turn-tracking-observer.py | 6 +++--- examples/foundational/30-observer.py | 6 +++--- examples/foundational/32-gemini-grounding-metadata.py | 6 +++--- examples/foundational/33-gemini-rag.py | 6 +++--- examples/foundational/34-audio-recording.py | 6 +++--- examples/foundational/35-pattern-pair-voice-switching.py | 6 +++--- examples/foundational/36-user-email-gathering.py | 6 +++--- examples/foundational/37-mem0.py | 6 +++--- examples/foundational/38-smart-turn-fal.py | 6 +++--- examples/foundational/38a-smart-turn-local-coreml.py | 6 +++--- examples/foundational/38b-smart-turn-local.py | 6 +++--- examples/foundational/39-mcp-stdio.py | 6 +++--- examples/foundational/39a-mcp-streamable-http.py | 6 +++--- .../foundational/39b-mcp-streamable-http-gemini-live.py | 6 +++--- examples/foundational/39c-multiple-mcp.py | 6 +++--- examples/foundational/40-aws-nova-sonic.py | 5 +---- examples/foundational/42-interruption-config.py | 6 +++--- examples/foundational/43-heygen-transport.py | 6 +++--- examples/foundational/43a-heygen-video-service.py | 6 +++--- examples/foundational/44-voicemail-detection.py | 6 +++--- examples/foundational/45-before-and-after-events.py | 6 +++--- examples/foundational/46-video-processing.py | 6 +++--- examples/foundational/47-sentry-metrics.py | 6 +++--- examples/foundational/48-service-switcher.py | 6 +++--- examples/foundational/49a-thinking-anthropic.py | 5 +---- examples/foundational/49b-thinking-google.py | 5 +---- examples/foundational/49c-thinking-functions-anthropic.py | 5 +---- examples/foundational/49d-thinking-functions-google.py | 5 +---- examples/foundational/50-ultravox-realtime.py | 6 +++--- examples/foundational/51-grok-realtime.py | 5 +---- examples/foundational/52-live-translation.py | 6 +++--- 155 files changed, 450 insertions(+), 475 deletions(-) diff --git a/examples/foundational/04-transports-small-webrtc.py b/examples/foundational/04-transports-small-webrtc.py index 26b3291dd..8ed1291ba 100644 --- a/examples/foundational/04-transports-small-webrtc.py +++ b/examples/foundational/04-transports-small-webrtc.py @@ -85,7 +85,7 @@ async def run_example(webrtc_connection: SmallWebRTCConnection): ] context = LLMContext(messages) - context_aggregator = LLMContextAggregatorPair( + user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, user_params=LLMUserAggregatorParams( user_turn_strategies=UserTurnStrategies( @@ -98,11 +98,11 @@ async def run_example(webrtc_connection: SmallWebRTCConnection): [ transport.input(), # Transport user input stt, - context_aggregator.user(), # User responses + user_aggregator, # User responses llm, # LLM tts, # TTS transport.output(), # Transport bot output - context_aggregator.assistant(), # Assistant spoken responses + assistant_aggregator, # Assistant spoken responses ] ) diff --git a/examples/foundational/04a-transports-daily.py b/examples/foundational/04a-transports-daily.py index 6f31bc6b4..27321e028 100644 --- a/examples/foundational/04a-transports-daily.py +++ b/examples/foundational/04a-transports-daily.py @@ -68,7 +68,7 @@ async def main(): ] context = LLMContext(messages) - context_aggregator = LLMContextAggregatorPair( + user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, user_params=LLMUserAggregatorParams( user_turn_strategies=UserTurnStrategies( @@ -82,11 +82,11 @@ async def main(): pipeline = Pipeline( [ transport.input(), # Transport user input - context_aggregator.user(), # User responses + user_aggregator, # User responses llm, # LLM tts, # TTS transport.output(), # Transport bot output - context_aggregator.assistant(), # Assistant spoken responses + assistant_aggregator, # Assistant spoken responses ] ) diff --git a/examples/foundational/04b-transports-livekit.py b/examples/foundational/04b-transports-livekit.py index c24a082c5..c58e6b5fd 100644 --- a/examples/foundational/04b-transports-livekit.py +++ b/examples/foundational/04b-transports-livekit.py @@ -78,7 +78,7 @@ async def main(): ] context = LLMContext(messages) - context_aggregator = LLMContextAggregatorPair( + user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, user_params=LLMUserAggregatorParams( user_turn_strategies=UserTurnStrategies( @@ -91,11 +91,11 @@ async def main(): [ transport.input(), # Transport user input stt, - context_aggregator.user(), # User responses + user_aggregator, # User responses llm, # LLM tts, # TTS transport.output(), # Transport bot output - context_aggregator.assistant(), # Assistant spoken responses + assistant_aggregator, # Assistant spoken responses ] ) diff --git a/examples/foundational/06-listen-and-respond.py b/examples/foundational/06-listen-and-respond.py index 9290becb2..95e59b167 100644 --- a/examples/foundational/06-listen-and-respond.py +++ b/examples/foundational/06-listen-and-respond.py @@ -106,7 +106,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): ] context = LLMContext(messages) - context_aggregator = LLMContextAggregatorPair( + user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, user_params=LLMUserAggregatorParams( user_turn_strategies=UserTurnStrategies( @@ -119,12 +119,12 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): [ transport.input(), stt, - context_aggregator.user(), + user_aggregator, llm, tts, ml, transport.output(), - context_aggregator.assistant(), + assistant_aggregator, ] ) diff --git a/examples/foundational/06a-image-sync.py b/examples/foundational/06a-image-sync.py index 363502fac..cc4664578 100644 --- a/examples/foundational/06a-image-sync.py +++ b/examples/foundational/06a-image-sync.py @@ -120,7 +120,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): ] context = LLMContext(messages) - context_aggregator = LLMContextAggregatorPair( + user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, user_params=LLMUserAggregatorParams( user_turn_strategies=UserTurnStrategies( @@ -138,12 +138,12 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): [ transport.input(), stt, - context_aggregator.user(), + user_aggregator, llm, tts, image_sync_aggregator, transport.output(), - context_aggregator.assistant(), + assistant_aggregator, ] ) diff --git a/examples/foundational/07-interruptible-cartesia-http.py b/examples/foundational/07-interruptible-cartesia-http.py index 919660b03..2d0a9f6d1 100644 --- a/examples/foundational/07-interruptible-cartesia-http.py +++ b/examples/foundational/07-interruptible-cartesia-http.py @@ -77,7 +77,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): ] context = LLMContext(messages) - context_aggregator = LLMContextAggregatorPair( + user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, user_params=LLMUserAggregatorParams( user_turn_strategies=UserTurnStrategies( @@ -90,11 +90,11 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): [ transport.input(), # Transport user input stt, - context_aggregator.user(), # User responses + user_aggregator, # User responses llm, # LLM tts, # TTS transport.output(), # Transport bot output - context_aggregator.assistant(), # Assistant spoken responses + assistant_aggregator, # Assistant spoken responses ] ) diff --git a/examples/foundational/07-interruptible.py b/examples/foundational/07-interruptible.py index b9e8bb0f7..d9bb5a449 100644 --- a/examples/foundational/07-interruptible.py +++ b/examples/foundational/07-interruptible.py @@ -76,7 +76,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): ] context = LLMContext(messages) - context_aggregator = LLMContextAggregatorPair( + user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, user_params=LLMUserAggregatorParams( user_turn_strategies=UserTurnStrategies( @@ -89,11 +89,11 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): [ transport.input(), # Transport user input stt, - context_aggregator.user(), # User responses + user_aggregator, # User responses llm, # LLM tts, # TTS transport.output(), # Transport bot output - context_aggregator.assistant(), # Assistant spoken responses + assistant_aggregator, # Assistant spoken responses ] ) diff --git a/examples/foundational/07a-interruptible-speechmatics-vad.py b/examples/foundational/07a-interruptible-speechmatics-vad.py index 8f1898f3f..864e9635d 100644 --- a/examples/foundational/07a-interruptible-speechmatics-vad.py +++ b/examples/foundational/07a-interruptible-speechmatics-vad.py @@ -131,7 +131,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): ] context = LLMContext(messages) - context_aggregator = LLMContextAggregatorPair( + user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, user_params=LLMUserAggregatorParams(user_turn_strategies=ExternalUserTurnStrategies()), ) @@ -140,11 +140,11 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): [ transport.input(), # Transport user input stt, - context_aggregator.user(), # User responses + user_aggregator, # User responses llm, # LLM tts, # TTS transport.output(), # Transport bot output - context_aggregator.assistant(), # Assistant spoken responses + assistant_aggregator, # Assistant spoken responses ] ) diff --git a/examples/foundational/07a-interruptible-speechmatics.py b/examples/foundational/07a-interruptible-speechmatics.py index 370b2c998..78959eccf 100644 --- a/examples/foundational/07a-interruptible-speechmatics.py +++ b/examples/foundational/07a-interruptible-speechmatics.py @@ -117,7 +117,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): ] context = LLMContext(messages) - context_aggregator = LLMContextAggregatorPair( + user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, user_params=LLMUserAggregatorParams( user_turn_strategies=UserTurnStrategies( @@ -132,11 +132,11 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): [ transport.input(), # Transport user input stt, # STT - context_aggregator.user(), # User responses + user_aggregator, # User responses llm, # LLM tts, # TTS transport.output(), # Transport bot output - context_aggregator.assistant(), # Assistant spoken responses + assistant_aggregator, # Assistant spoken responses ] ) diff --git a/examples/foundational/07aa-interruptible-soniox.py b/examples/foundational/07aa-interruptible-soniox.py index ba0e2be27..15da33507 100644 --- a/examples/foundational/07aa-interruptible-soniox.py +++ b/examples/foundational/07aa-interruptible-soniox.py @@ -76,7 +76,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): ] context = LLMContext(messages) - context_aggregator = LLMContextAggregatorPair( + user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, user_params=LLMUserAggregatorParams( user_turn_strategies=UserTurnStrategies( @@ -89,11 +89,11 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): [ transport.input(), # Transport user input stt, - context_aggregator.user(), # User responses + user_aggregator, # User responses llm, # LLM tts, # TTS transport.output(), # Transport bot output - context_aggregator.assistant(), # Assistant spoken responses + assistant_aggregator, # Assistant spoken responses ] ) task = PipelineTask( diff --git a/examples/foundational/07ab-interruptible-inworld-http.py b/examples/foundational/07ab-interruptible-inworld-http.py index a947f0edf..b2bf05660 100644 --- a/examples/foundational/07ab-interruptible-inworld-http.py +++ b/examples/foundational/07ab-interruptible-inworld-http.py @@ -82,7 +82,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): ] context = LLMContext(messages) - context_aggregator = LLMContextAggregatorPair( + user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, user_params=LLMUserAggregatorParams( user_turn_strategies=UserTurnStrategies( @@ -100,11 +100,11 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): transport.input(), rtvi, stt, - context_aggregator.user(), + user_aggregator, llm, tts, transport.output(), - context_aggregator.assistant(), + assistant_aggregator, ] ) diff --git a/examples/foundational/07ab-interruptible-inworld.py b/examples/foundational/07ab-interruptible-inworld.py index f830ed485..8d3d351a5 100644 --- a/examples/foundational/07ab-interruptible-inworld.py +++ b/examples/foundational/07ab-interruptible-inworld.py @@ -79,7 +79,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): ] context = LLMContext(messages) - context_aggregator = LLMContextAggregatorPair( + user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, user_params=LLMUserAggregatorParams( user_turn_strategies=UserTurnStrategies( @@ -95,11 +95,11 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): transport.input(), rtvi, stt, - context_aggregator.user(), + user_aggregator, llm, tts, transport.output(), - context_aggregator.assistant(), + assistant_aggregator, ] ) diff --git a/examples/foundational/07ac-interruptible-asyncai-http.py b/examples/foundational/07ac-interruptible-asyncai-http.py index 3ac659b3f..21da1cf17 100644 --- a/examples/foundational/07ac-interruptible-asyncai-http.py +++ b/examples/foundational/07ac-interruptible-asyncai-http.py @@ -82,7 +82,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): ] context = LLMContext(messages) - context_aggregator = LLMContextAggregatorPair( + user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, user_params=LLMUserAggregatorParams( user_turn_strategies=UserTurnStrategies( @@ -97,11 +97,11 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): [ transport.input(), # Transport user input stt, - context_aggregator.user(), # User responses + user_aggregator, # User responses llm, # LLM tts, # TTS transport.output(), # Transport bot output - context_aggregator.assistant(), # Assistant spoken responses + assistant_aggregator, # Assistant spoken responses ] ) diff --git a/examples/foundational/07ac-interruptible-asyncai.py b/examples/foundational/07ac-interruptible-asyncai.py index b13615110..d3dcf8766 100644 --- a/examples/foundational/07ac-interruptible-asyncai.py +++ b/examples/foundational/07ac-interruptible-asyncai.py @@ -78,7 +78,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): ] context = LLMContext(messages) - context_aggregator = LLMContextAggregatorPair( + user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, user_params=LLMUserAggregatorParams( user_turn_strategies=UserTurnStrategies( @@ -91,11 +91,11 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): [ transport.input(), # Transport user input stt, - context_aggregator.user(), # User responses + user_aggregator, # User responses llm, # LLM tts, # TTS transport.output(), # Transport bot output - context_aggregator.assistant(), # Assistant spoken responses + assistant_aggregator, # Assistant spoken responses ] ) diff --git a/examples/foundational/07ad-interruptible-aicoustics.py b/examples/foundational/07ad-interruptible-aicoustics.py index 75686469b..8a49e734f 100644 --- a/examples/foundational/07ad-interruptible-aicoustics.py +++ b/examples/foundational/07ad-interruptible-aicoustics.py @@ -105,7 +105,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): ] context = LLMContext(messages) - context_aggregator = LLMContextAggregatorPair( + user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, user_params=LLMUserAggregatorParams( user_turn_strategies=UserTurnStrategies( @@ -118,12 +118,12 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): [ transport.input(), # Transport user input stt, # STT - context_aggregator.user(), # User responses + user_aggregator, # User responses llm, # LLM tts, # TTS transport.output(), # Transport bot output audiobuffer, # write audio data to a file - context_aggregator.assistant(), # Assistant spoken responses + assistant_aggregator, # Assistant spoken responses ] ) diff --git a/examples/foundational/07ae-interruptible-hume.py b/examples/foundational/07ae-interruptible-hume.py index 238e45637..33ea4d278 100644 --- a/examples/foundational/07ae-interruptible-hume.py +++ b/examples/foundational/07ae-interruptible-hume.py @@ -81,7 +81,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): ] context = LLMContext(messages) - context_aggregator = LLMContextAggregatorPair( + user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, user_params=LLMUserAggregatorParams( user_turn_strategies=UserTurnStrategies( @@ -97,11 +97,11 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): transport.input(), # Transport user input rtvi, stt, - context_aggregator.user(), # User responses + user_aggregator, # User responses llm, # LLM tts, # TTS (HumeTTSService with word timestamps) transport.output(), # Transport bot output - context_aggregator.assistant(), # Assistant spoken responses + assistant_aggregator, # Assistant spoken responses ] ) diff --git a/examples/foundational/07af-interruptible-gradium.py b/examples/foundational/07af-interruptible-gradium.py index 4b21e887b..b6207d9f4 100644 --- a/examples/foundational/07af-interruptible-gradium.py +++ b/examples/foundational/07af-interruptible-gradium.py @@ -76,7 +76,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): ] context = LLMContext(messages) - context_aggregator = LLMContextAggregatorPair( + user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, user_params=LLMUserAggregatorParams( user_turn_strategies=UserTurnStrategies( @@ -89,11 +89,11 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): [ transport.input(), # Transport user input stt, - context_aggregator.user(), # User responses + user_aggregator, # User responses llm, # LLM tts, # TTS transport.output(), # Transport bot output - context_aggregator.assistant(), # Assistant spoken responses + assistant_aggregator, # Assistant spoken responses ] ) diff --git a/examples/foundational/07b-interruptible-langchain.py b/examples/foundational/07b-interruptible-langchain.py index a5a8f3d0e..b9b5c6177 100644 --- a/examples/foundational/07b-interruptible-langchain.py +++ b/examples/foundational/07b-interruptible-langchain.py @@ -103,7 +103,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): lc = LangchainProcessor(history_chain) context = LLMContext() - context_aggregator = LLMContextAggregatorPair( + user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, user_params=LLMUserAggregatorParams( user_turn_strategies=UserTurnStrategies( @@ -116,11 +116,11 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): [ transport.input(), # Transport user input stt, - context_aggregator.user(), # User responses + user_aggregator, # User responses lc, # Langchain tts, # TTS transport.output(), # Transport bot output - context_aggregator.assistant(), # Assistant spoken responses + assistant_aggregator, # Assistant spoken responses ] ) diff --git a/examples/foundational/07c-interruptible-deepgram-flux.py b/examples/foundational/07c-interruptible-deepgram-flux.py index 87c1ca7e9..5a1a63e7e 100644 --- a/examples/foundational/07c-interruptible-deepgram-flux.py +++ b/examples/foundational/07c-interruptible-deepgram-flux.py @@ -71,7 +71,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): ] context = LLMContext(messages) - context_aggregator = LLMContextAggregatorPair( + user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, user_params=LLMUserAggregatorParams(user_turn_strategies=ExternalUserTurnStrategies()), ) @@ -80,11 +80,11 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): [ transport.input(), # Transport user input stt, # STT - context_aggregator.user(), # User responses + user_aggregator, # User responses llm, # LLM tts, # TTS transport.output(), # Transport bot output - context_aggregator.assistant(), # Assistant spoken responses + assistant_aggregator, # Assistant spoken responses ] ) diff --git a/examples/foundational/07c-interruptible-deepgram-http.py b/examples/foundational/07c-interruptible-deepgram-http.py index c0b607986..190d37280 100644 --- a/examples/foundational/07c-interruptible-deepgram-http.py +++ b/examples/foundational/07c-interruptible-deepgram-http.py @@ -81,7 +81,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): ] context = LLMContext(messages) - context_aggregator = LLMContextAggregatorPair( + user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, user_params=LLMUserAggregatorParams( user_turn_strategies=UserTurnStrategies( @@ -96,11 +96,11 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): [ transport.input(), # Transport user input stt, # STT - context_aggregator.user(), # User responses + user_aggregator, # User responses llm, # LLM tts, # TTS transport.output(), # Transport bot output - context_aggregator.assistant(), # Assistant spoken responses + assistant_aggregator, # Assistant spoken responses ] ) diff --git a/examples/foundational/07c-interruptible-deepgram-sagemaker.py b/examples/foundational/07c-interruptible-deepgram-sagemaker.py index 53da2dba7..a625c1eea 100644 --- a/examples/foundational/07c-interruptible-deepgram-sagemaker.py +++ b/examples/foundational/07c-interruptible-deepgram-sagemaker.py @@ -86,7 +86,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): ] context = LLMContext(messages) - context_aggregator = LLMContextAggregatorPair( + user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, user_params=LLMUserAggregatorParams( user_turn_strategies=UserTurnStrategies( @@ -99,11 +99,11 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): [ transport.input(), # Transport user input stt, # STT - context_aggregator.user(), # User responses + user_aggregator, # User responses llm, # LLM tts, # TTS transport.output(), # Transport bot output - context_aggregator.assistant(), # Assistant spoken responses + assistant_aggregator, # Assistant spoken responses ] ) diff --git a/examples/foundational/07c-interruptible-deepgram-vad.py b/examples/foundational/07c-interruptible-deepgram-vad.py index 482ff2b26..e7dca7701 100644 --- a/examples/foundational/07c-interruptible-deepgram-vad.py +++ b/examples/foundational/07c-interruptible-deepgram-vad.py @@ -72,7 +72,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): ] context = LLMContext(messages) - context_aggregator = LLMContextAggregatorPair( + user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, user_params=LLMUserAggregatorParams(user_turn_strategies=ExternalUserTurnStrategies()), ) @@ -81,11 +81,11 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): [ transport.input(), # Transport user input stt, # STT - context_aggregator.user(), # User responses + user_aggregator, # User responses llm, # LLM tts, # TTS transport.output(), # Transport bot output - context_aggregator.assistant(), # Assistant spoken responses + assistant_aggregator, # Assistant spoken responses ] ) diff --git a/examples/foundational/07c-interruptible-deepgram.py b/examples/foundational/07c-interruptible-deepgram.py index 5754b33a9..7e81b5a74 100644 --- a/examples/foundational/07c-interruptible-deepgram.py +++ b/examples/foundational/07c-interruptible-deepgram.py @@ -75,7 +75,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): ] context = LLMContext(messages) - context_aggregator = LLMContextAggregatorPair( + user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, user_params=LLMUserAggregatorParams( user_turn_strategies=UserTurnStrategies( @@ -88,11 +88,11 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): [ transport.input(), # Transport user input stt, # STT - context_aggregator.user(), # User responses + user_aggregator, # User responses llm, # LLM tts, # TTS transport.output(), # Transport bot output - context_aggregator.assistant(), # Assistant spoken responses + assistant_aggregator, # Assistant spoken responses ] ) diff --git a/examples/foundational/07d-interruptible-elevenlabs-http.py b/examples/foundational/07d-interruptible-elevenlabs-http.py index 933f6ffdb..d289258c1 100644 --- a/examples/foundational/07d-interruptible-elevenlabs-http.py +++ b/examples/foundational/07d-interruptible-elevenlabs-http.py @@ -85,7 +85,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): ] context = LLMContext(messages) - context_aggregator = LLMContextAggregatorPair( + user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, user_params=LLMUserAggregatorParams( user_turn_strategies=UserTurnStrategies( @@ -100,11 +100,11 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): [ transport.input(), # Transport user input stt, - context_aggregator.user(), # User responses + user_aggregator, # User responses llm, # LLM tts, # TTS transport.output(), # Transport bot output - context_aggregator.assistant(), # Assistant spoken responses + assistant_aggregator, # Assistant spoken responses ] ) diff --git a/examples/foundational/07d-interruptible-elevenlabs.py b/examples/foundational/07d-interruptible-elevenlabs.py index aa519fd5b..4850cd473 100644 --- a/examples/foundational/07d-interruptible-elevenlabs.py +++ b/examples/foundational/07d-interruptible-elevenlabs.py @@ -78,7 +78,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): ] context = LLMContext(messages) - context_aggregator = LLMContextAggregatorPair( + user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, user_params=LLMUserAggregatorParams( user_turn_strategies=UserTurnStrategies( @@ -91,11 +91,11 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): [ transport.input(), # Transport user input stt, - context_aggregator.user(), # User responses + user_aggregator, # User responses llm, # LLM tts, # TTS transport.output(), # Transport bot output - context_aggregator.assistant(), # Assistant spoken responses + assistant_aggregator, # Assistant spoken responses ] ) diff --git a/examples/foundational/07e-interruptible-playht-http.py b/examples/foundational/07e-interruptible-playht-http.py index 9e6f94c63..0d731d6e4 100644 --- a/examples/foundational/07e-interruptible-playht-http.py +++ b/examples/foundational/07e-interruptible-playht-http.py @@ -78,7 +78,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): ] context = LLMContext(messages) - context_aggregator = LLMContextAggregatorPair( + user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, user_params=LLMUserAggregatorParams( user_turn_strategies=UserTurnStrategies( @@ -91,11 +91,11 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): [ transport.input(), # Transport user input stt, - context_aggregator.user(), # User responses + user_aggregator, # User responses llm, # LLM tts, # TTS transport.output(), # Transport bot output - context_aggregator.assistant(), # Assistant spoken responses + assistant_aggregator, # Assistant spoken responses ] ) diff --git a/examples/foundational/07e-interruptible-playht.py b/examples/foundational/07e-interruptible-playht.py index 516179995..598565868 100644 --- a/examples/foundational/07e-interruptible-playht.py +++ b/examples/foundational/07e-interruptible-playht.py @@ -80,7 +80,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): ] context = LLMContext(messages) - context_aggregator = LLMContextAggregatorPair( + user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, user_params=LLMUserAggregatorParams( user_turn_strategies=UserTurnStrategies( @@ -93,11 +93,11 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): [ transport.input(), # Transport user input stt, - context_aggregator.user(), # User responses + user_aggregator, # User responses llm, # LLM tts, # TTS transport.output(), # Transport bot output - context_aggregator.assistant(), # Assistant spoken responses + assistant_aggregator, # Assistant spoken responses ] ) diff --git a/examples/foundational/07f-interruptible-azure-http.py b/examples/foundational/07f-interruptible-azure-http.py index 882aa61c0..1fc0a1bba 100644 --- a/examples/foundational/07f-interruptible-azure-http.py +++ b/examples/foundational/07f-interruptible-azure-http.py @@ -84,7 +84,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): ] context = LLMContext(messages) - context_aggregator = LLMContextAggregatorPair( + user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, user_params=LLMUserAggregatorParams( user_turn_strategies=UserTurnStrategies( @@ -97,11 +97,11 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): [ transport.input(), # Transport user input stt, # STT - context_aggregator.user(), # User responses + user_aggregator, # User responses llm, # LLM tts, # TTS transport.output(), # Transport bot output - context_aggregator.assistant(), # Assistant spoken responses + assistant_aggregator, # Assistant spoken responses ] ) diff --git a/examples/foundational/07f-interruptible-azure.py b/examples/foundational/07f-interruptible-azure.py index 7688731ae..0ff69e44e 100644 --- a/examples/foundational/07f-interruptible-azure.py +++ b/examples/foundational/07f-interruptible-azure.py @@ -84,7 +84,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): ] context = LLMContext(messages) - context_aggregator = LLMContextAggregatorPair( + user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, user_params=LLMUserAggregatorParams( user_turn_strategies=UserTurnStrategies( @@ -97,11 +97,11 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): [ transport.input(), # Transport user input stt, # STT - context_aggregator.user(), # User responses + user_aggregator, # User responses llm, # LLM tts, # TTS transport.output(), # Transport bot output - context_aggregator.assistant(), # Assistant spoken responses + assistant_aggregator, # Assistant spoken responses ] ) diff --git a/examples/foundational/07g-interruptible-openai.py b/examples/foundational/07g-interruptible-openai.py index 236787af6..3c588cf11 100644 --- a/examples/foundational/07g-interruptible-openai.py +++ b/examples/foundational/07g-interruptible-openai.py @@ -78,7 +78,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): ] context = LLMContext(messages) - context_aggregator = LLMContextAggregatorPair( + user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, user_params=LLMUserAggregatorParams( user_turn_strategies=UserTurnStrategies( @@ -91,11 +91,11 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): [ transport.input(), # Transport user input stt, # STT - context_aggregator.user(), # User responses + user_aggregator, # User responses llm, # LLM tts, # TTS transport.output(), # Transport bot output - context_aggregator.assistant(), # Assistant spoken responses + assistant_aggregator, # Assistant spoken responses ] ) diff --git a/examples/foundational/07h-interruptible-openpipe.py b/examples/foundational/07h-interruptible-openpipe.py index baa8c869c..555c4049b 100644 --- a/examples/foundational/07h-interruptible-openpipe.py +++ b/examples/foundational/07h-interruptible-openpipe.py @@ -83,7 +83,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): ] context = LLMContext(messages) - context_aggregator = LLMContextAggregatorPair( + user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, user_params=LLMUserAggregatorParams( user_turn_strategies=UserTurnStrategies( @@ -96,11 +96,11 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): [ transport.input(), # Transport user input stt, - context_aggregator.user(), # User responses + user_aggregator, # User responses llm, # LLM tts, # TTS transport.output(), # Transport bot output - context_aggregator.assistant(), # Assistant spoken responses + assistant_aggregator, # Assistant spoken responses ] ) diff --git a/examples/foundational/07i-interruptible-xtts.py b/examples/foundational/07i-interruptible-xtts.py index fed73d2c3..9d1843177 100644 --- a/examples/foundational/07i-interruptible-xtts.py +++ b/examples/foundational/07i-interruptible-xtts.py @@ -81,7 +81,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): ] context = LLMContext(messages) - context_aggregator = LLMContextAggregatorPair( + user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, user_params=LLMUserAggregatorParams( user_turn_strategies=UserTurnStrategies( @@ -96,11 +96,11 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): [ transport.input(), # Transport user input stt, - context_aggregator.user(), # User responses + user_aggregator, # User responses llm, # LLM tts, # TTS transport.output(), # Transport bot output - context_aggregator.assistant(), # Assistant spoken responses + assistant_aggregator, # Assistant spoken responses ] ) diff --git a/examples/foundational/07j-interruptible-gladia-vad.py b/examples/foundational/07j-interruptible-gladia-vad.py index 7f2790611..58d094d3b 100644 --- a/examples/foundational/07j-interruptible-gladia-vad.py +++ b/examples/foundational/07j-interruptible-gladia-vad.py @@ -86,7 +86,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): ] context = LLMContext(messages) - context_aggregator = LLMContextAggregatorPair( + user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, user_params=LLMUserAggregatorParams(user_turn_strategies=ExternalUserTurnStrategies()), ) @@ -95,11 +95,11 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): [ transport.input(), # Transport user input stt, # STT - context_aggregator.user(), # User responses + user_aggregator, # User responses llm, # LLM tts, # TTS transport.output(), # Transport bot output - context_aggregator.assistant(), # Assistant spoken responses + assistant_aggregator, # Assistant spoken responses ] ) diff --git a/examples/foundational/07j-interruptible-gladia.py b/examples/foundational/07j-interruptible-gladia.py index 5a1cd305b..664c19ce1 100644 --- a/examples/foundational/07j-interruptible-gladia.py +++ b/examples/foundational/07j-interruptible-gladia.py @@ -87,7 +87,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): ] context = LLMContext(messages) - context_aggregator = LLMContextAggregatorPair( + user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, user_params=LLMUserAggregatorParams( user_turn_strategies=UserTurnStrategies( @@ -100,11 +100,11 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): [ transport.input(), # Transport user input stt, # STT - context_aggregator.user(), # User responses + user_aggregator, # User responses llm, # LLM tts, # TTS transport.output(), # Transport bot output - context_aggregator.assistant(), # Assistant spoken responses + assistant_aggregator, # Assistant spoken responses ] ) diff --git a/examples/foundational/07k-interruptible-lmnt.py b/examples/foundational/07k-interruptible-lmnt.py index 048e91d15..43618f84f 100644 --- a/examples/foundational/07k-interruptible-lmnt.py +++ b/examples/foundational/07k-interruptible-lmnt.py @@ -75,7 +75,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): ] context = LLMContext(messages) - context_aggregator = LLMContextAggregatorPair( + user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, user_params=LLMUserAggregatorParams( user_turn_strategies=UserTurnStrategies( @@ -88,11 +88,11 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): [ transport.input(), # Transport user input stt, - context_aggregator.user(), # User respones + user_aggregator, # User respones llm, # LLM tts, # TTS transport.output(), # Transport bot output - context_aggregator.assistant(), # Assistant spoken responses + assistant_aggregator, # Assistant spoken responses ] ) diff --git a/examples/foundational/07l-interruptible-groq.py b/examples/foundational/07l-interruptible-groq.py index 55791e0ce..c1e7e2d4d 100644 --- a/examples/foundational/07l-interruptible-groq.py +++ b/examples/foundational/07l-interruptible-groq.py @@ -76,7 +76,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): ] context = LLMContext(messages) - context_aggregator = LLMContextAggregatorPair( + user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, user_params=LLMUserAggregatorParams( user_turn_strategies=UserTurnStrategies( @@ -89,11 +89,11 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): [ transport.input(), # Transport user input stt, - context_aggregator.user(), # User responses + user_aggregator, # User responses llm, # LLM tts, # TTS transport.output(), # Transport bot output - context_aggregator.assistant(), # Assistant spoken responses + assistant_aggregator, # Assistant spoken responses ] ) diff --git a/examples/foundational/07m-interruptible-aws-strands.py b/examples/foundational/07m-interruptible-aws-strands.py index c3e830a1f..f72e3560c 100644 --- a/examples/foundational/07m-interruptible-aws-strands.py +++ b/examples/foundational/07m-interruptible-aws-strands.py @@ -120,7 +120,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): # Setup context aggregators for message handling context = LLMContext() - context_aggregator = LLMContextAggregatorPair( + user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, user_params=LLMUserAggregatorParams( user_turn_strategies=UserTurnStrategies( @@ -133,11 +133,11 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): [ transport.input(), # Transport user input stt, # Speech-to-text - context_aggregator.user(), # User responses + user_aggregator, # User responses llm, # Strands Agents processor tts, # Text-to-speech transport.output(), # Transport bot output - context_aggregator.assistant(), # Assistant spoken responses + assistant_aggregator, # Assistant spoken responses ] ) diff --git a/examples/foundational/07m-interruptible-aws.py b/examples/foundational/07m-interruptible-aws.py index eb4974d8f..0f00e1185 100644 --- a/examples/foundational/07m-interruptible-aws.py +++ b/examples/foundational/07m-interruptible-aws.py @@ -80,7 +80,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): ] context = LLMContext(messages) - context_aggregator = LLMContextAggregatorPair( + user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, user_params=LLMUserAggregatorParams( user_turn_strategies=UserTurnStrategies( @@ -93,11 +93,11 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): [ transport.input(), # Transport user input stt, # STT - context_aggregator.user(), # User responses + user_aggregator, # User responses llm, # LLM tts, # TTS transport.output(), # Transport bot output - context_aggregator.assistant(), # Assistant spoken responses + assistant_aggregator, # Assistant spoken responses ] ) diff --git a/examples/foundational/07n-interruptible-gemini-image.py b/examples/foundational/07n-interruptible-gemini-image.py index 08ab8fb81..a465724f2 100644 --- a/examples/foundational/07n-interruptible-gemini-image.py +++ b/examples/foundational/07n-interruptible-gemini-image.py @@ -102,7 +102,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): ] context = LLMContext(messages) - context_aggregator = LLMContextAggregatorPair( + user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, user_params=LLMUserAggregatorParams( user_turn_strategies=UserTurnStrategies( @@ -115,11 +115,11 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): [ transport.input(), # Transport user input stt, # STT - context_aggregator.user(), # User responses + user_aggregator, # User responses llm, # LLM tts, # Gemini TTS transport.output(), # Transport bot output - context_aggregator.assistant(), # Assistant spoken responses + assistant_aggregator, # Assistant spoken responses ] ) diff --git a/examples/foundational/07n-interruptible-gemini.py b/examples/foundational/07n-interruptible-gemini.py index e8234a60d..f9dc0bc3b 100644 --- a/examples/foundational/07n-interruptible-gemini.py +++ b/examples/foundational/07n-interruptible-gemini.py @@ -107,7 +107,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): ] context = LLMContext(messages) - context_aggregator = LLMContextAggregatorPair( + user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, user_params=LLMUserAggregatorParams( user_turn_strategies=UserTurnStrategies( @@ -120,11 +120,11 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): [ transport.input(), # Transport user input stt, # STT - context_aggregator.user(), # User responses + user_aggregator, # User responses llm, # LLM tts, # Gemini TTS transport.output(), # Transport bot output - context_aggregator.assistant(), # Assistant spoken responses + assistant_aggregator, # Assistant spoken responses ] ) diff --git a/examples/foundational/07n-interruptible-google-http.py b/examples/foundational/07n-interruptible-google-http.py index 42f251612..9c58489a9 100644 --- a/examples/foundational/07n-interruptible-google-http.py +++ b/examples/foundational/07n-interruptible-google-http.py @@ -90,7 +90,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): ] context = LLMContext(messages) - context_aggregator = LLMContextAggregatorPair( + user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, user_params=LLMUserAggregatorParams( user_turn_strategies=UserTurnStrategies( @@ -103,11 +103,11 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): [ transport.input(), # Transport user input stt, # STT - context_aggregator.user(), # User respones + user_aggregator, # User respones llm, # LLM tts, # TTS transport.output(), # Transport bot output - context_aggregator.assistant(), # Assistant spoken responses + assistant_aggregator, # Assistant spoken responses ] ) diff --git a/examples/foundational/07n-interruptible-google.py b/examples/foundational/07n-interruptible-google.py index 4c5969a04..a7ebc9dc3 100644 --- a/examples/foundational/07n-interruptible-google.py +++ b/examples/foundational/07n-interruptible-google.py @@ -90,7 +90,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): ] context = LLMContext(messages) - context_aggregator = LLMContextAggregatorPair( + user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, user_params=LLMUserAggregatorParams( user_turn_strategies=UserTurnStrategies( @@ -103,11 +103,11 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): [ transport.input(), # Transport user input stt, # STT - context_aggregator.user(), # User respones + user_aggregator, # User respones llm, # LLM tts, # TTS transport.output(), # Transport bot output - context_aggregator.assistant(), # Assistant spoken responses + assistant_aggregator, # Assistant spoken responses ] ) diff --git a/examples/foundational/07o-interruptible-assemblyai.py b/examples/foundational/07o-interruptible-assemblyai.py index 36f90a183..9cdaafebb 100644 --- a/examples/foundational/07o-interruptible-assemblyai.py +++ b/examples/foundational/07o-interruptible-assemblyai.py @@ -80,7 +80,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): ] context = LLMContext(messages) - context_aggregator = LLMContextAggregatorPair( + user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, user_params=LLMUserAggregatorParams( user_turn_strategies=UserTurnStrategies( @@ -93,11 +93,11 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): [ transport.input(), # Transport user input stt, # STT - context_aggregator.user(), # User responses + user_aggregator, # User responses llm, # LLM tts, # TTS transport.output(), # Transport bot output - context_aggregator.assistant(), # Assistant spoken responses + assistant_aggregator, # Assistant spoken responses ] ) diff --git a/examples/foundational/07p-interruptible-krisp-viva.py b/examples/foundational/07p-interruptible-krisp-viva.py index ca11ef90e..be336f003 100644 --- a/examples/foundational/07p-interruptible-krisp-viva.py +++ b/examples/foundational/07p-interruptible-krisp-viva.py @@ -95,7 +95,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): ] context = LLMContext(messages) - context_aggregator = LLMContextAggregatorPair( + user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, user_params=LLMUserAggregatorParams( user_turn_strategies=UserTurnStrategies( @@ -108,11 +108,11 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): [ transport.input(), # Transport user input stt, # STT - context_aggregator.user(), # User responses + user_aggregator, # User responses llm, # LLM tts, # TTS transport.output(), # Transport bot output - context_aggregator.assistant(), # Assistant spoken responses + assistant_aggregator, # Assistant spoken responses ] ) diff --git a/examples/foundational/07p-interruptible-krisp.py b/examples/foundational/07p-interruptible-krisp.py index e66928bf2..8665e270e 100644 --- a/examples/foundational/07p-interruptible-krisp.py +++ b/examples/foundational/07p-interruptible-krisp.py @@ -78,7 +78,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): ] context = LLMContext(messages) - context_aggregator = LLMContextAggregatorPair( + user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, user_params=LLMUserAggregatorParams( user_turn_strategies=UserTurnStrategies( @@ -91,11 +91,11 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): [ transport.input(), # Transport user input stt, # STT - context_aggregator.user(), # User responses + user_aggregator, # User responses llm, # LLM tts, # TTS transport.output(), # Transport bot output - context_aggregator.assistant(), # Assistant spoken responses + assistant_aggregator, # Assistant spoken responses ] ) diff --git a/examples/foundational/07q-interruptible-rime-http.py b/examples/foundational/07q-interruptible-rime-http.py index 45b68bfb1..1cbe7f01b 100644 --- a/examples/foundational/07q-interruptible-rime-http.py +++ b/examples/foundational/07q-interruptible-rime-http.py @@ -83,7 +83,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): ] context = LLMContext(messages) - context_aggregator = LLMContextAggregatorPair( + user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, user_params=LLMUserAggregatorParams( user_turn_strategies=UserTurnStrategies( @@ -98,11 +98,11 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): [ transport.input(), # Transport user input stt, - context_aggregator.user(), # User responses + user_aggregator, # User responses llm, # LLM tts, # TTS transport.output(), # Transport bot output - context_aggregator.assistant(), # Assistant spoken responses + assistant_aggregator, # Assistant spoken responses ] ) diff --git a/examples/foundational/07q-interruptible-rime.py b/examples/foundational/07q-interruptible-rime.py index d2d1207e1..d54a97d78 100644 --- a/examples/foundational/07q-interruptible-rime.py +++ b/examples/foundational/07q-interruptible-rime.py @@ -77,7 +77,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): ] context = LLMContext(messages) - context_aggregator = LLMContextAggregatorPair( + user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, user_params=LLMUserAggregatorParams( user_turn_strategies=UserTurnStrategies( @@ -90,11 +90,11 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): [ transport.input(), # Transport user input stt, - context_aggregator.user(), # User responses + user_aggregator, # User responses llm, # LLM tts, # TTS transport.output(), # Transport bot output - context_aggregator.assistant(), # Assistant spoken responses + assistant_aggregator, # Assistant spoken responses ] ) diff --git a/examples/foundational/07r-interruptible-nvidia.py b/examples/foundational/07r-interruptible-nvidia.py index d93ce19eb..460f6ebfe 100644 --- a/examples/foundational/07r-interruptible-nvidia.py +++ b/examples/foundational/07r-interruptible-nvidia.py @@ -76,7 +76,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): ] context = LLMContext(messages) - context_aggregator = LLMContextAggregatorPair( + user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, user_params=LLMUserAggregatorParams( user_turn_strategies=UserTurnStrategies( @@ -89,11 +89,11 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): [ transport.input(), # Transport user input stt, # STT - context_aggregator.user(), # User responses + user_aggregator, # User responses llm, # LLM tts, # TTS transport.output(), # Transport bot output - context_aggregator.assistant(), # Assistant spoken responses + assistant_aggregator, # Assistant spoken responses ] ) diff --git a/examples/foundational/07s-interruptible-google-audio-in.py b/examples/foundational/07s-interruptible-google-audio-in.py index 3fb48354a..9aaa3c415 100644 --- a/examples/foundational/07s-interruptible-google-audio-in.py +++ b/examples/foundational/07s-interruptible-google-audio-in.py @@ -249,7 +249,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): ] context = LLMContext(messages) - context_aggregator = LLMContextAggregatorPair( + user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, user_params=LLMUserAggregatorParams( user_turn_strategies=UserTurnStrategies( @@ -257,7 +257,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): ), ), ) - audio_collector = UserAudioCollector(context, context_aggregator.user()) + audio_collector = UserAudioCollector(context, user_aggregator) pull_transcript_out_of_llm_output = TranscriptExtractor(context) fixup_context_messages = TranscriptionContextFixup(context) @@ -265,12 +265,12 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): [ transport.input(), # Transport user input audio_collector, - context_aggregator.user(), # User responses + user_aggregator, # User responses llm, # LLM pull_transcript_out_of_llm_output, tts, # TTS transport.output(), # Transport bot output - context_aggregator.assistant(), # Assistant spoken responses + assistant_aggregator, # Assistant spoken responses fixup_context_messages, ] ) diff --git a/examples/foundational/07t-interruptible-fish.py b/examples/foundational/07t-interruptible-fish.py index 9e2bc6e5c..86750b631 100644 --- a/examples/foundational/07t-interruptible-fish.py +++ b/examples/foundational/07t-interruptible-fish.py @@ -78,7 +78,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): ] context = LLMContext(messages) - context_aggregator = LLMContextAggregatorPair( + user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, user_params=LLMUserAggregatorParams( user_turn_strategies=UserTurnStrategies( @@ -91,11 +91,11 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): [ transport.input(), # Transport user input stt, - context_aggregator.user(), # User responses + user_aggregator, # User responses llm, # LLM tts, # TTS transport.output(), # Transport bot output - context_aggregator.assistant(), # Assistant spoken responses + assistant_aggregator, # Assistant spoken responses ] ) diff --git a/examples/foundational/07v-interruptible-neuphonic-http.py b/examples/foundational/07v-interruptible-neuphonic-http.py index c97b6e381..5f5928cad 100644 --- a/examples/foundational/07v-interruptible-neuphonic-http.py +++ b/examples/foundational/07v-interruptible-neuphonic-http.py @@ -82,7 +82,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): ] context = LLMContext(messages) - context_aggregator = LLMContextAggregatorPair( + user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, user_params=LLMUserAggregatorParams( user_turn_strategies=UserTurnStrategies( @@ -97,11 +97,11 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): [ transport.input(), # Transport user input stt, - context_aggregator.user(), # User responses + user_aggregator, # User responses llm, # LLM tts, # TTS transport.output(), # Transport bot output - context_aggregator.assistant(), # Assistant spoken responses + assistant_aggregator, # Assistant spoken responses ] ) diff --git a/examples/foundational/07v-interruptible-neuphonic.py b/examples/foundational/07v-interruptible-neuphonic.py index 9a142f1bf..78fc9c2e8 100644 --- a/examples/foundational/07v-interruptible-neuphonic.py +++ b/examples/foundational/07v-interruptible-neuphonic.py @@ -77,7 +77,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): ] context = LLMContext(messages) - context_aggregator = LLMContextAggregatorPair( + user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, user_params=LLMUserAggregatorParams( user_turn_strategies=UserTurnStrategies( @@ -90,11 +90,11 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): [ transport.input(), # Transport user input stt, - context_aggregator.user(), # User responses + user_aggregator, # User responses llm, # LLM tts, # TTS transport.output(), # Transport bot output - context_aggregator.assistant(), # Assistant spoken responses + assistant_aggregator, # Assistant spoken responses ] ) diff --git a/examples/foundational/07w-interruptible-fal.py b/examples/foundational/07w-interruptible-fal.py index 62c33d1c9..a60725b16 100644 --- a/examples/foundational/07w-interruptible-fal.py +++ b/examples/foundational/07w-interruptible-fal.py @@ -80,7 +80,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): ] context = LLMContext(messages) - context_aggregator = LLMContextAggregatorPair( + user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, user_params=LLMUserAggregatorParams( user_turn_strategies=UserTurnStrategies( @@ -93,11 +93,11 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): [ transport.input(), # Transport user input stt, # STT - context_aggregator.user(), # User responses + user_aggregator, # User responses llm, # LLM tts, # TTS transport.output(), # Transport bot output - context_aggregator.assistant(), # Assistant spoken responses + assistant_aggregator, # Assistant spoken responses ] ) diff --git a/examples/foundational/07x-interruptible-local.py b/examples/foundational/07x-interruptible-local.py index b0cd28e55..0baa6ebad 100644 --- a/examples/foundational/07x-interruptible-local.py +++ b/examples/foundational/07x-interruptible-local.py @@ -62,7 +62,7 @@ async def main(): ] context = LLMContext(messages) - context_aggregator = LLMContextAggregatorPair( + user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, user_params=LLMUserAggregatorParams( user_turn_strategies=UserTurnStrategies( @@ -75,11 +75,11 @@ async def main(): [ transport.input(), # Transport user input stt, - context_aggregator.user(), # User responses + user_aggregator, # User responses llm, # LLM tts, # TTS transport.output(), # Transport bot output - context_aggregator.assistant(), # Assistant spoken responses + assistant_aggregator, # Assistant spoken responses ] ) diff --git a/examples/foundational/07y-interruptible-minimax.py b/examples/foundational/07y-interruptible-minimax.py index ba8d56c28..855e41516 100644 --- a/examples/foundational/07y-interruptible-minimax.py +++ b/examples/foundational/07y-interruptible-minimax.py @@ -84,7 +84,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): ] context = LLMContext(messages) - context_aggregator = LLMContextAggregatorPair( + user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, user_params=LLMUserAggregatorParams( user_turn_strategies=UserTurnStrategies( @@ -99,11 +99,11 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): [ transport.input(), # Transport user input stt, - context_aggregator.user(), # User responses + user_aggregator, # User responses llm, # LLM tts, # TTS transport.output(), # Transport bot output - context_aggregator.assistant(), # Assistant spoken responses + assistant_aggregator, # Assistant spoken responses ] ) diff --git a/examples/foundational/07z-interruptible-sarvam-http.py b/examples/foundational/07z-interruptible-sarvam-http.py index 8ad54ab4c..df176ab22 100644 --- a/examples/foundational/07z-interruptible-sarvam-http.py +++ b/examples/foundational/07z-interruptible-sarvam-http.py @@ -86,7 +86,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): ] context = LLMContext(messages) - context_aggregator = LLMContextAggregatorPair( + user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, user_params=LLMUserAggregatorParams( user_turn_strategies=UserTurnStrategies( @@ -101,11 +101,11 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): [ transport.input(), # Transport user input stt, - context_aggregator.user(), # User responses + user_aggregator, # User responses llm, # LLM tts, # TTS transport.output(), # Transport bot output - context_aggregator.assistant(), # Assistant spoken responses + assistant_aggregator, # Assistant spoken responses ] ) diff --git a/examples/foundational/07z-interruptible-sarvam.py b/examples/foundational/07z-interruptible-sarvam.py index 500f08b41..990af6fef 100644 --- a/examples/foundational/07z-interruptible-sarvam.py +++ b/examples/foundational/07z-interruptible-sarvam.py @@ -80,7 +80,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): ] context = LLMContext(messages) - context_aggregator = LLMContextAggregatorPair( + user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, user_params=LLMUserAggregatorParams( user_turn_strategies=UserTurnStrategies( @@ -93,11 +93,11 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): [ transport.input(), # Transport user input stt, - context_aggregator.user(), # User responses + user_aggregator, # User responses llm, # LLM tts, # TTS transport.output(), # Transport bot output - context_aggregator.assistant(), # Assistant spoken responses + assistant_aggregator, # Assistant spoken responses ] ) diff --git a/examples/foundational/08-custom-frame-processor.py b/examples/foundational/08-custom-frame-processor.py index ae44b4fba..82ff858b6 100644 --- a/examples/foundational/08-custom-frame-processor.py +++ b/examples/foundational/08-custom-frame-processor.py @@ -115,7 +115,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): ] context = LLMContext(messages) - context_aggregator = LLMContextAggregatorPair( + user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, user_params=LLMUserAggregatorParams( user_turn_strategies=UserTurnStrategies( @@ -130,11 +130,11 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): [ transport.input(), stt, - context_aggregator.user(), + user_aggregator, llm, tts, transport.output(), - context_aggregator.assistant(), + assistant_aggregator, metrics_frame_processor, # pretty print metrics frames ] ) diff --git a/examples/foundational/10-wake-phrase.py b/examples/foundational/10-wake-phrase.py index ace7f6f4f..fe7052a5b 100644 --- a/examples/foundational/10-wake-phrase.py +++ b/examples/foundational/10-wake-phrase.py @@ -79,7 +79,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): hey_robot_filter = WakeCheckFilter(["hey robot", "hey, robot"]) context = LLMContext(messages) - context_aggregator = LLMContextAggregatorPair( + user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, user_params=LLMUserAggregatorParams( user_turn_strategies=UserTurnStrategies( @@ -93,11 +93,11 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): transport.input(), # Transport user input stt, # STT hey_robot_filter, # Filter out speech not directed at the robot - context_aggregator.user(), # User responses + user_aggregator, # User responses llm, # LLM tts, # TTS transport.output(), # Transport bot output - context_aggregator.assistant(), # Assistant spoken responses + assistant_aggregator, # Assistant spoken responses ] ) diff --git a/examples/foundational/11-sound-effects.py b/examples/foundational/11-sound-effects.py index 0dee4264e..8201790ac 100644 --- a/examples/foundational/11-sound-effects.py +++ b/examples/foundational/11-sound-effects.py @@ -127,7 +127,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): ] context = LLMContext(messages) - context_aggregator = LLMContextAggregatorPair( + user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, user_params=LLMUserAggregatorParams( user_turn_strategies=UserTurnStrategies( @@ -144,7 +144,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): [ transport.input(), stt, - context_aggregator.user(), + user_aggregator, in_sound, fl2, llm, @@ -152,7 +152,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): tts, out_sound, transport.output(), - context_aggregator.assistant(), + assistant_aggregator, ] ) diff --git a/examples/foundational/12-describe-image-openai.py b/examples/foundational/12-describe-image-openai.py index 2df4ccaea..60cdeafed 100644 --- a/examples/foundational/12-describe-image-openai.py +++ b/examples/foundational/12-describe-image-openai.py @@ -73,7 +73,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): ] context = LLMContext(messages) - context_aggregator = LLMContextAggregatorPair( + user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, user_params=LLMUserAggregatorParams( user_turn_strategies=UserTurnStrategies( @@ -86,11 +86,11 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): [ transport.input(), # Transport user input stt, # STT - context_aggregator.user(), # User responses + user_aggregator, # User responses llm, # LLM tts, # TTS transport.output(), # Transport bot output - context_aggregator.assistant(), # Assistant spoken responses + assistant_aggregator, # Assistant spoken responses ] ) diff --git a/examples/foundational/12a-describe-image-anthropic.py b/examples/foundational/12a-describe-image-anthropic.py index 2263040ba..507cca019 100644 --- a/examples/foundational/12a-describe-image-anthropic.py +++ b/examples/foundational/12a-describe-image-anthropic.py @@ -73,7 +73,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): ] context = LLMContext(messages) - context_aggregator = LLMContextAggregatorPair( + user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, user_params=LLMUserAggregatorParams( user_turn_strategies=UserTurnStrategies( @@ -86,11 +86,11 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): [ transport.input(), # Transport user input stt, # STT - context_aggregator.user(), # User responses + user_aggregator, # User responses llm, # LLM tts, # TTS transport.output(), # Transport bot output - context_aggregator.assistant(), # Assistant spoken responses + assistant_aggregator, # Assistant spoken responses ] ) diff --git a/examples/foundational/12b-describe-image-aws.py b/examples/foundational/12b-describe-image-aws.py index 8e37bf5d3..ed02f5024 100644 --- a/examples/foundational/12b-describe-image-aws.py +++ b/examples/foundational/12b-describe-image-aws.py @@ -80,7 +80,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): ] context = LLMContext(messages) - context_aggregator = LLMContextAggregatorPair( + user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, user_params=LLMUserAggregatorParams( user_turn_strategies=UserTurnStrategies( @@ -93,11 +93,11 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): [ transport.input(), # Transport user input stt, # STT - context_aggregator.user(), # User responses + user_aggregator, # User responses llm, # LLM tts, # TTS transport.output(), # Transport bot output - context_aggregator.assistant(), # Assistant spoken responses + assistant_aggregator, # Assistant spoken responses ] ) diff --git a/examples/foundational/12c-describe-image-gemini-flash.py b/examples/foundational/12c-describe-image-gemini-flash.py index a97480a4e..a00465135 100644 --- a/examples/foundational/12c-describe-image-gemini-flash.py +++ b/examples/foundational/12c-describe-image-gemini-flash.py @@ -73,7 +73,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): ] context = LLMContext(messages) - context_aggregator = LLMContextAggregatorPair( + user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, user_params=LLMUserAggregatorParams( user_turn_strategies=UserTurnStrategies( @@ -86,11 +86,11 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): [ transport.input(), # Transport user input stt, # STT - context_aggregator.user(), # User responses + user_aggregator, # User responses llm, # LLM tts, # TTS transport.output(), # Transport bot output - context_aggregator.assistant(), # Assistant spoken responses + assistant_aggregator, # Assistant spoken responses ] ) diff --git a/examples/foundational/14-function-calling.py b/examples/foundational/14-function-calling.py index e0bf7de2d..22f84397c 100644 --- a/examples/foundational/14-function-calling.py +++ b/examples/foundational/14-function-calling.py @@ -126,7 +126,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): ] context = LLMContext(messages, tools) - context_aggregator = LLMContextAggregatorPair( + user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, user_params=LLMUserAggregatorParams( user_turn_strategies=UserTurnStrategies( @@ -139,11 +139,11 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): [ transport.input(), stt, - context_aggregator.user(), + user_aggregator, llm, tts, transport.output(), - context_aggregator.assistant(), + assistant_aggregator, ] ) diff --git a/examples/foundational/14a-function-calling-anthropic.py b/examples/foundational/14a-function-calling-anthropic.py index c86abe61a..08133cf83 100644 --- a/examples/foundational/14a-function-calling-anthropic.py +++ b/examples/foundational/14a-function-calling-anthropic.py @@ -121,7 +121,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): messages = [{"role": "user", "content": "Say 'hello' to start the conversation."}] context = LLMContext(messages, tools) - context_aggregator = LLMContextAggregatorPair( + user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, user_params=LLMUserAggregatorParams( user_turn_strategies=UserTurnStrategies( @@ -134,11 +134,11 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): [ transport.input(), # Transport user input stt, - context_aggregator.user(), # User spoken responses + user_aggregator, # User spoken responses llm, # LLM tts, # TTS transport.output(), # Transport bot output - context_aggregator.assistant(), # Assistant spoken responses and tool context + assistant_aggregator, # Assistant spoken responses and tool context ] ) diff --git a/examples/foundational/14c-function-calling-together.py b/examples/foundational/14c-function-calling-together.py index dc9ec9f51..a4bf5cd19 100644 --- a/examples/foundational/14c-function-calling-together.py +++ b/examples/foundational/14c-function-calling-together.py @@ -112,7 +112,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): ] context = LLMContext(messages, tools) - context_aggregator = LLMContextAggregatorPair( + user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, user_params=LLMUserAggregatorParams( user_turn_strategies=UserTurnStrategies( @@ -125,11 +125,11 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): [ transport.input(), stt, - context_aggregator.user(), + user_aggregator, llm, tts, transport.output(), - context_aggregator.assistant(), + assistant_aggregator, ] ) diff --git a/examples/foundational/14d-function-calling-anthropic-video.py b/examples/foundational/14d-function-calling-anthropic-video.py index d851b99fc..8097ee988 100644 --- a/examples/foundational/14d-function-calling-anthropic-video.py +++ b/examples/foundational/14d-function-calling-anthropic-video.py @@ -136,7 +136,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): ] context = LLMContext(messages, tools) - context_aggregator = LLMContextAggregatorPair( + user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, user_params=LLMUserAggregatorParams( user_turn_strategies=UserTurnStrategies( @@ -149,11 +149,11 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): [ transport.input(), # Transport user input stt, # STT - context_aggregator.user(), # User responses + user_aggregator, # User responses llm, # LLM tts, # TTS transport.output(), # Transport bot output - context_aggregator.assistant(), # Assistant spoken responses + assistant_aggregator, # Assistant spoken responses ] ) diff --git a/examples/foundational/14d-function-calling-aws-video.py b/examples/foundational/14d-function-calling-aws-video.py index 3e8c1785f..b972f4097 100644 --- a/examples/foundational/14d-function-calling-aws-video.py +++ b/examples/foundational/14d-function-calling-aws-video.py @@ -143,7 +143,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): ] context = LLMContext(messages, tools) - context_aggregator = LLMContextAggregatorPair( + user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, user_params=LLMUserAggregatorParams( user_turn_strategies=UserTurnStrategies( @@ -156,11 +156,11 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): [ transport.input(), # Transport user input stt, # STT - context_aggregator.user(), # User responses + user_aggregator, # User responses llm, # LLM tts, # TTS transport.output(), # Transport bot output - context_aggregator.assistant(), # Assistant spoken responses + assistant_aggregator, # Assistant spoken responses ] ) diff --git a/examples/foundational/14d-function-calling-gemini-flash-video.py b/examples/foundational/14d-function-calling-gemini-flash-video.py index 2c6a6c6ac..ba9dcd266 100644 --- a/examples/foundational/14d-function-calling-gemini-flash-video.py +++ b/examples/foundational/14d-function-calling-gemini-flash-video.py @@ -136,7 +136,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): ] context = LLMContext(messages, tools) - context_aggregator = LLMContextAggregatorPair( + user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, user_params=LLMUserAggregatorParams( user_turn_strategies=UserTurnStrategies( @@ -149,11 +149,11 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): [ transport.input(), # Transport user input stt, # STT - context_aggregator.user(), # User responses + user_aggregator, # User responses llm, # LLM tts, # TTS transport.output(), # Transport bot output - context_aggregator.assistant(), # Assistant spoken responses + assistant_aggregator, # Assistant spoken responses ] ) diff --git a/examples/foundational/14d-function-calling-moondream-video.py b/examples/foundational/14d-function-calling-moondream-video.py index cf244880c..0b10854ea 100644 --- a/examples/foundational/14d-function-calling-moondream-video.py +++ b/examples/foundational/14d-function-calling-moondream-video.py @@ -166,7 +166,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): ] context = LLMContext(messages, tools) - context_aggregator = LLMContextAggregatorPair( + user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, user_params=LLMUserAggregatorParams( user_turn_strategies=UserTurnStrategies( @@ -188,14 +188,14 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): [ transport.input(), # Transport user input stt, # STT - context_aggregator.user(), # User responses + user_aggregator, # User responses ParallelPipeline( [llm], # LLM [moondream, moondream_text_wrapper], ), tts, # TTS transport.output(), # Transport bot output - context_aggregator.assistant(), # Assistant spoken responses + assistant_aggregator, # Assistant spoken responses ] ) diff --git a/examples/foundational/14d-function-calling-openai-video.py b/examples/foundational/14d-function-calling-openai-video.py index e1c3f52be..3afebe7bb 100644 --- a/examples/foundational/14d-function-calling-openai-video.py +++ b/examples/foundational/14d-function-calling-openai-video.py @@ -136,7 +136,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): ] context = LLMContext(messages, tools) - context_aggregator = LLMContextAggregatorPair( + user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, user_params=LLMUserAggregatorParams( user_turn_strategies=UserTurnStrategies( @@ -149,11 +149,11 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): [ transport.input(), # Transport user input stt, # STT - context_aggregator.user(), # User responses + user_aggregator, # User responses llm, # LLM tts, # TTS transport.output(), # Transport bot output - context_aggregator.assistant(), # Assistant spoken responses + assistant_aggregator, # Assistant spoken responses ] ) diff --git a/examples/foundational/14e-function-calling-google.py b/examples/foundational/14e-function-calling-google.py index 69791ffbc..4e7abf997 100644 --- a/examples/foundational/14e-function-calling-google.py +++ b/examples/foundational/14e-function-calling-google.py @@ -189,7 +189,7 @@ indicate you should use the get_image tool are: ] context = LLMContext(messages, tools) - context_aggregator = LLMContextAggregatorPair( + user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, user_params=LLMUserAggregatorParams( user_turn_strategies=UserTurnStrategies( @@ -202,11 +202,11 @@ indicate you should use the get_image tool are: [ transport.input(), stt, - context_aggregator.user(), + user_aggregator, llm, tts, transport.output(), - context_aggregator.assistant(), + assistant_aggregator, ] ) diff --git a/examples/foundational/14f-function-calling-groq.py b/examples/foundational/14f-function-calling-groq.py index 91ed9caa6..989dafb0e 100644 --- a/examples/foundational/14f-function-calling-groq.py +++ b/examples/foundational/14f-function-calling-groq.py @@ -109,7 +109,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): ] context = LLMContext(messages, tools) - context_aggregator = LLMContextAggregatorPair( + user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, user_params=LLMUserAggregatorParams( user_turn_strategies=UserTurnStrategies( @@ -122,11 +122,11 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): [ transport.input(), stt, - context_aggregator.user(), + user_aggregator, llm, tts, transport.output(), - context_aggregator.assistant(), + assistant_aggregator, ] ) diff --git a/examples/foundational/14g-function-calling-grok.py b/examples/foundational/14g-function-calling-grok.py index 8ea41d6aa..cfb52cbc5 100644 --- a/examples/foundational/14g-function-calling-grok.py +++ b/examples/foundational/14g-function-calling-grok.py @@ -105,7 +105,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): ] context = LLMContext(messages, tools) - context_aggregator = LLMContextAggregatorPair( + user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, user_params=LLMUserAggregatorParams( user_turn_strategies=UserTurnStrategies( @@ -118,11 +118,11 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): [ transport.input(), stt, - context_aggregator.user(), + user_aggregator, llm, tts, transport.output(), - context_aggregator.assistant(), + assistant_aggregator, ] ) diff --git a/examples/foundational/14h-function-calling-azure.py b/examples/foundational/14h-function-calling-azure.py index 77e7579de..a108a7779 100644 --- a/examples/foundational/14h-function-calling-azure.py +++ b/examples/foundational/14h-function-calling-azure.py @@ -113,7 +113,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): ] context = LLMContext(messages, tools) - context_aggregator = LLMContextAggregatorPair( + user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, user_params=LLMUserAggregatorParams( user_turn_strategies=UserTurnStrategies( @@ -126,11 +126,11 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): [ transport.input(), stt, - context_aggregator.user(), + user_aggregator, llm, tts, transport.output(), - context_aggregator.assistant(), + assistant_aggregator, ] ) diff --git a/examples/foundational/14i-function-calling-fireworks.py b/examples/foundational/14i-function-calling-fireworks.py index a79ab925f..9b1692430 100644 --- a/examples/foundational/14i-function-calling-fireworks.py +++ b/examples/foundational/14i-function-calling-fireworks.py @@ -116,7 +116,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): ] context = LLMContext(messages, tools) - context_aggregator = LLMContextAggregatorPair( + user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, user_params=LLMUserAggregatorParams( user_turn_strategies=UserTurnStrategies( @@ -129,11 +129,11 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): [ transport.input(), stt, - context_aggregator.user(), + user_aggregator, llm, tts, transport.output(), - context_aggregator.assistant(), + assistant_aggregator, ] ) diff --git a/examples/foundational/14j-function-calling-nvidia.py b/examples/foundational/14j-function-calling-nvidia.py index 3f4dfe8c1..354e0fbdb 100644 --- a/examples/foundational/14j-function-calling-nvidia.py +++ b/examples/foundational/14j-function-calling-nvidia.py @@ -118,7 +118,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): ] context = LLMContext(messages, tools) - context_aggregator = LLMContextAggregatorPair( + user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, user_params=LLMUserAggregatorParams( user_turn_strategies=UserTurnStrategies( @@ -131,11 +131,11 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): [ transport.input(), stt, - context_aggregator.user(), + user_aggregator, llm, tts, transport.output(), - context_aggregator.assistant(), + assistant_aggregator, ] ) diff --git a/examples/foundational/14k-function-calling-cerebras.py b/examples/foundational/14k-function-calling-cerebras.py index 1a5fe4c38..994c29169 100644 --- a/examples/foundational/14k-function-calling-cerebras.py +++ b/examples/foundational/14k-function-calling-cerebras.py @@ -119,7 +119,7 @@ Start by asking me for my location. Then, use 'get_weather_current' to give me a ] context = LLMContext(messages, tools) - context_aggregator = LLMContextAggregatorPair( + user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, user_params=LLMUserAggregatorParams( user_turn_strategies=UserTurnStrategies( @@ -132,11 +132,11 @@ Start by asking me for my location. Then, use 'get_weather_current' to give me a [ transport.input(), stt, - context_aggregator.user(), + user_aggregator, llm, tts, transport.output(), - context_aggregator.assistant(), + assistant_aggregator, ] ) diff --git a/examples/foundational/14l-function-calling-deepseek.py b/examples/foundational/14l-function-calling-deepseek.py index 497af8609..fc9dc5677 100644 --- a/examples/foundational/14l-function-calling-deepseek.py +++ b/examples/foundational/14l-function-calling-deepseek.py @@ -119,7 +119,7 @@ Start by asking me for my location. Then, use 'get_weather_current' to give me a ] context = LLMContext(messages, tools) - context_aggregator = LLMContextAggregatorPair( + user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, user_params=LLMUserAggregatorParams( user_turn_strategies=UserTurnStrategies( @@ -132,11 +132,11 @@ Start by asking me for my location. Then, use 'get_weather_current' to give me a [ transport.input(), stt, - context_aggregator.user(), + user_aggregator, llm, tts, transport.output(), - context_aggregator.assistant(), + assistant_aggregator, ] ) diff --git a/examples/foundational/14m-function-calling-openrouter.py b/examples/foundational/14m-function-calling-openrouter.py index 34c59ef9e..963da638b 100644 --- a/examples/foundational/14m-function-calling-openrouter.py +++ b/examples/foundational/14m-function-calling-openrouter.py @@ -113,7 +113,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): ] context = LLMContext(messages, tools) - context_aggregator = LLMContextAggregatorPair( + user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, user_params=LLMUserAggregatorParams( user_turn_strategies=UserTurnStrategies( @@ -126,11 +126,11 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): [ transport.input(), stt, - context_aggregator.user(), + user_aggregator, llm, tts, transport.output(), - context_aggregator.assistant(), + assistant_aggregator, ] ) diff --git a/examples/foundational/14n-function-calling-perplexity.py b/examples/foundational/14n-function-calling-perplexity.py index d768f3e77..a3745cc5a 100644 --- a/examples/foundational/14n-function-calling-perplexity.py +++ b/examples/foundational/14n-function-calling-perplexity.py @@ -83,7 +83,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): ] context = LLMContext(messages) - context_aggregator = LLMContextAggregatorPair( + user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, user_params=LLMUserAggregatorParams( user_turn_strategies=UserTurnStrategies( @@ -96,11 +96,11 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): [ transport.input(), stt, - context_aggregator.user(), + user_aggregator, llm, tts, transport.output(), - context_aggregator.assistant(), + assistant_aggregator, ] ) diff --git a/examples/foundational/14p-function-calling-gemini-vertex-ai.py b/examples/foundational/14p-function-calling-gemini-vertex-ai.py index bae9def68..0fe2da06d 100644 --- a/examples/foundational/14p-function-calling-gemini-vertex-ai.py +++ b/examples/foundational/14p-function-calling-gemini-vertex-ai.py @@ -114,7 +114,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): ] context = LLMContext(messages, tools) - context_aggregator = LLMContextAggregatorPair( + user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, user_params=LLMUserAggregatorParams( user_turn_strategies=UserTurnStrategies( @@ -127,11 +127,11 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): [ transport.input(), stt, - context_aggregator.user(), + user_aggregator, llm, tts, transport.output(), - context_aggregator.assistant(), + assistant_aggregator, ] ) diff --git a/examples/foundational/14q-function-calling-qwen.py b/examples/foundational/14q-function-calling-qwen.py index 256ff1499..9b6c641ed 100644 --- a/examples/foundational/14q-function-calling-qwen.py +++ b/examples/foundational/14q-function-calling-qwen.py @@ -111,7 +111,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): ] context = LLMContext(messages, tools) - context_aggregator = LLMContextAggregatorPair( + user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, user_params=LLMUserAggregatorParams( user_turn_strategies=UserTurnStrategies( @@ -124,11 +124,11 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): [ transport.input(), stt, - context_aggregator.user(), + user_aggregator, llm, tts, transport.output(), - context_aggregator.assistant(), + assistant_aggregator, ] ) diff --git a/examples/foundational/14r-function-calling-aws.py b/examples/foundational/14r-function-calling-aws.py index 95b7f9d68..ff438ac27 100644 --- a/examples/foundational/14r-function-calling-aws.py +++ b/examples/foundational/14r-function-calling-aws.py @@ -126,7 +126,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): ] context = LLMContext(messages, tools) - context_aggregator = LLMContextAggregatorPair( + user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, user_params=LLMUserAggregatorParams( user_turn_strategies=UserTurnStrategies( @@ -139,11 +139,11 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): [ transport.input(), stt, - context_aggregator.user(), + user_aggregator, llm, tts, transport.output(), - context_aggregator.assistant(), + assistant_aggregator, ] ) diff --git a/examples/foundational/14s-function-calling-sambanova.py b/examples/foundational/14s-function-calling-sambanova.py index fbd1a7176..60076e370 100644 --- a/examples/foundational/14s-function-calling-sambanova.py +++ b/examples/foundational/14s-function-calling-sambanova.py @@ -115,7 +115,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): ] context = LLMContext(messages, tools) - context_aggregator = LLMContextAggregatorPair( + user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, user_params=LLMUserAggregatorParams( user_turn_strategies=UserTurnStrategies( @@ -128,11 +128,11 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): [ transport.input(), stt, - context_aggregator.user(), + user_aggregator, llm, tts, transport.output(), - context_aggregator.assistant(), + assistant_aggregator, ] ) diff --git a/examples/foundational/14t-function-calling-direct.py b/examples/foundational/14t-function-calling-direct.py index 6f682327c..ae6db7564 100644 --- a/examples/foundational/14t-function-calling-direct.py +++ b/examples/foundational/14t-function-calling-direct.py @@ -112,7 +112,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): ] context = LLMContext(messages, tools) - context_aggregator = LLMContextAggregatorPair( + user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, user_params=LLMUserAggregatorParams( user_turn_strategies=UserTurnStrategies( @@ -125,11 +125,11 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): [ transport.input(), stt, - context_aggregator.user(), + user_aggregator, llm, tts, transport.output(), - context_aggregator.assistant(), + assistant_aggregator, ] ) diff --git a/examples/foundational/14u-function-calling-ollama.py b/examples/foundational/14u-function-calling-ollama.py index 5a66b81fe..a76c65dd8 100644 --- a/examples/foundational/14u-function-calling-ollama.py +++ b/examples/foundational/14u-function-calling-ollama.py @@ -127,7 +127,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): ] context = LLMContext(messages, tools) - context_aggregator = LLMContextAggregatorPair( + user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, user_params=LLMUserAggregatorParams( user_turn_strategies=UserTurnStrategies( @@ -140,11 +140,11 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): [ transport.input(), stt, - context_aggregator.user(), + user_aggregator, llm, tts, transport.output(), - context_aggregator.assistant(), + assistant_aggregator, ] ) diff --git a/examples/foundational/14v-function-calling-openai.py b/examples/foundational/14v-function-calling-openai.py index c84b6a78c..ac60c0901 100644 --- a/examples/foundational/14v-function-calling-openai.py +++ b/examples/foundational/14v-function-calling-openai.py @@ -134,7 +134,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): ] context = LLMContext(messages, tools) - context_aggregator = LLMContextAggregatorPair( + user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, user_params=LLMUserAggregatorParams( user_turn_strategies=UserTurnStrategies( @@ -147,11 +147,11 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): [ transport.input(), stt, - context_aggregator.user(), + user_aggregator, llm, tts, transport.output(), - context_aggregator.assistant(), + assistant_aggregator, ] ) diff --git a/examples/foundational/14w-function-calling-mistral.py b/examples/foundational/14w-function-calling-mistral.py index 135328cf8..721726f82 100644 --- a/examples/foundational/14w-function-calling-mistral.py +++ b/examples/foundational/14w-function-calling-mistral.py @@ -122,7 +122,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): ] context = LLMContext(messages, tools) - context_aggregator = LLMContextAggregatorPair( + user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, user_params=LLMUserAggregatorParams( user_turn_strategies=UserTurnStrategies( @@ -135,11 +135,11 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): [ transport.input(), stt, - context_aggregator.user(), + user_aggregator, llm, tts, transport.output(), - context_aggregator.assistant(), + assistant_aggregator, ] ) diff --git a/examples/foundational/14x-function-calling-openpipe.py b/examples/foundational/14x-function-calling-openpipe.py index 0191e18fb..42c951a4e 100644 --- a/examples/foundational/14x-function-calling-openpipe.py +++ b/examples/foundational/14x-function-calling-openpipe.py @@ -132,7 +132,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): ] context = LLMContext(messages, tools) - context_aggregator = LLMContextAggregatorPair( + user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, user_params=LLMUserAggregatorParams( user_turn_strategies=UserTurnStrategies( @@ -145,11 +145,11 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): [ transport.input(), stt, - context_aggregator.user(), + user_aggregator, llm, tts, transport.output(), - context_aggregator.assistant(), + assistant_aggregator, ] ) diff --git a/examples/foundational/15-switch-voices.py b/examples/foundational/15-switch-voices.py index 27e1464aa..ff0a0e9f7 100644 --- a/examples/foundational/15-switch-voices.py +++ b/examples/foundational/15-switch-voices.py @@ -144,7 +144,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): ] context = LLMContext(messages, tools) - context_aggregator = LLMContextAggregatorPair( + user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, user_params=LLMUserAggregatorParams( user_turn_strategies=UserTurnStrategies( @@ -157,11 +157,11 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): [ transport.input(), # Transport user input stt, - context_aggregator.user(), # User responses + user_aggregator, # User responses llm, # LLM tts, # TTS with switch voice functionality transport.output(), # Transport bot output - context_aggregator.assistant(), # Assistant spoken responses + assistant_aggregator, # Assistant spoken responses ] ) diff --git a/examples/foundational/15a-switch-languages.py b/examples/foundational/15a-switch-languages.py index 1ce8f4dff..73e818bc5 100644 --- a/examples/foundational/15a-switch-languages.py +++ b/examples/foundational/15a-switch-languages.py @@ -134,7 +134,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): ] context = LLMContext(messages, tools) - context_aggregator = LLMContextAggregatorPair( + user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, user_params=LLMUserAggregatorParams( user_turn_strategies=UserTurnStrategies( @@ -147,11 +147,11 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): [ transport.input(), # Transport user input stt, # STT - context_aggregator.user(), # User responses + user_aggregator, # User responses llm, # LLM tts, # TTS (bot will speak the chosen language) transport.output(), # Transport bot output - context_aggregator.assistant(), # Assistant spoken responses + assistant_aggregator, # Assistant spoken responses ] ) diff --git a/examples/foundational/16-gpu-container-local-bot.py b/examples/foundational/16-gpu-container-local-bot.py index 8c547300e..a64edcec2 100644 --- a/examples/foundational/16-gpu-container-local-bot.py +++ b/examples/foundational/16-gpu-container-local-bot.py @@ -88,7 +88,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): ] context = LLMContext(messages) - context_aggregator = LLMContextAggregatorPair( + user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, user_params=LLMUserAggregatorParams( user_turn_strategies=UserTurnStrategies( @@ -101,11 +101,11 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): [ transport.input(), # Transport user input stt, # STT - context_aggregator.user(), + user_aggregator, llm, # LLM tts, # TTS transport.output(), # Transport bot output - context_aggregator.assistant(), + assistant_aggregator, ] ) diff --git a/examples/foundational/17-detect-user-idle.py b/examples/foundational/17-detect-user-idle.py index ddef92a5b..f1fe0d068 100644 --- a/examples/foundational/17-detect-user-idle.py +++ b/examples/foundational/17-detect-user-idle.py @@ -78,7 +78,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): ] context = LLMContext(messages) - context_aggregator = LLMContextAggregatorPair( + user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, user_params=LLMUserAggregatorParams( user_turn_strategies=UserTurnStrategies( @@ -119,11 +119,11 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): transport.input(), # Transport user input stt, user_idle, # Idle user check-in - context_aggregator.user(), + user_aggregator, llm, # LLM tts, # TTS transport.output(), # Transport bot output - context_aggregator.assistant(), + assistant_aggregator, ] ) diff --git a/examples/foundational/19-openai-realtime.py b/examples/foundational/19-openai-realtime.py index 2b3750d0b..443a2817b 100644 --- a/examples/foundational/19-openai-realtime.py +++ b/examples/foundational/19-openai-realtime.py @@ -188,10 +188,7 @@ Remember, your responses should be short. Just one or two sentences, usually. Re tools, ) - context_aggregator = LLMContextAggregatorPair(context) - - user_aggregator = context_aggregator.user() - assistant_aggregator = context_aggregator.assistant() + user_aggregator, assistant_aggregator = LLMContextAggregatorPair(context) pipeline = Pipeline( [ diff --git a/examples/foundational/19a-azure-realtime.py b/examples/foundational/19a-azure-realtime.py index 6e245328a..20932da3c 100644 --- a/examples/foundational/19a-azure-realtime.py +++ b/examples/foundational/19a-azure-realtime.py @@ -173,15 +173,15 @@ Remember, your responses should be short. Just one or two sentences, usually. Re tools, ) - context_aggregator = LLMContextAggregatorPair(context) + user_aggregator, assistant_aggregator = LLMContextAggregatorPair(context) pipeline = Pipeline( [ transport.input(), # Transport user input - context_aggregator.user(), + user_aggregator, llm, # LLM transport.output(), # Transport bot output - context_aggregator.assistant(), + assistant_aggregator, ] ) diff --git a/examples/foundational/19b-openai-realtime-text.py b/examples/foundational/19b-openai-realtime-text.py index ec254f186..a3190f44c 100644 --- a/examples/foundational/19b-openai-realtime-text.py +++ b/examples/foundational/19b-openai-realtime-text.py @@ -171,16 +171,16 @@ Remember, your responses should be short. Just one or two sentences, usually. Re tools, ) - context_aggregator = LLMContextAggregatorPair(context) + user_aggregator, assistant_aggregator = LLMContextAggregatorPair(context) pipeline = Pipeline( [ transport.input(), # Transport user input - context_aggregator.user(), + user_aggregator, llm, # LLM tts, # TTS transport.output(), # Transport bot output - context_aggregator.assistant(), + assistant_aggregator, ] ) diff --git a/examples/foundational/19c-openai-realtime-live-video.py b/examples/foundational/19c-openai-realtime-live-video.py index af48b2355..31369717d 100644 --- a/examples/foundational/19c-openai-realtime-live-video.py +++ b/examples/foundational/19c-openai-realtime-live-video.py @@ -104,15 +104,15 @@ Remember, your responses should be short. Just one or two sentences, usually. Re [{"role": "user", "content": "Say hello!"}], ) - context_aggregator = LLMContextAggregatorPair(context) + user_aggregator, assistant_aggregator = LLMContextAggregatorPair(context) pipeline = Pipeline( [ transport.input(), # Transport user input - context_aggregator.user(), + user_aggregator, llm, # LLM transport.output(), # Transport bot output - context_aggregator.assistant(), + assistant_aggregator, ] ) diff --git a/examples/foundational/20a-persistent-context-openai.py b/examples/foundational/20a-persistent-context-openai.py index 502d2d354..ae7c6ca8e 100644 --- a/examples/foundational/20a-persistent-context-openai.py +++ b/examples/foundational/20a-persistent-context-openai.py @@ -201,7 +201,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): llm.register_function("load_conversation", load_conversation) context = LLMContext(messages, tools) - context_aggregator = LLMContextAggregatorPair( + user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, user_params=LLMUserAggregatorParams( user_turn_strategies=UserTurnStrategies( @@ -214,11 +214,11 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): [ transport.input(), # Transport user input stt, # STT - context_aggregator.user(), + user_aggregator, llm, # LLM tts, transport.output(), # Transport bot output - context_aggregator.assistant(), + assistant_aggregator, ] ) diff --git a/examples/foundational/20b-persistent-context-openai-realtime.py b/examples/foundational/20b-persistent-context-openai-realtime.py index 2133fa628..0d09cf40a 100644 --- a/examples/foundational/20b-persistent-context-openai-realtime.py +++ b/examples/foundational/20b-persistent-context-openai-realtime.py @@ -215,16 +215,16 @@ Remember, your responses should be short. Just one or two sentences, usually.""" llm.register_function("load_conversation", load_conversation) context = LLMContext([{"role": "user", "content": "Say hello!"}], tools) - context_aggregator = LLMContextAggregatorPair(context) + user_aggregator, assistant_aggregator = LLMContextAggregatorPair(context) pipeline = Pipeline( [ transport.input(), # Transport user input stt, # STT - context_aggregator.user(), + user_aggregator, llm, # LLM transport.output(), # Transport bot output - context_aggregator.assistant(), + assistant_aggregator, ] ) diff --git a/examples/foundational/20c-persistent-context-anthropic.py b/examples/foundational/20c-persistent-context-anthropic.py index 6dac15aa5..be70fd4b9 100644 --- a/examples/foundational/20c-persistent-context-anthropic.py +++ b/examples/foundational/20c-persistent-context-anthropic.py @@ -212,7 +212,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): llm.register_function("load_conversation", load_conversation) context = LLMContext(messages, tools) - context_aggregator = LLMContextAggregatorPair( + user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, user_params=LLMUserAggregatorParams( user_turn_strategies=UserTurnStrategies( @@ -225,11 +225,11 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): [ transport.input(), # Transport user input stt, # STT - context_aggregator.user(), + user_aggregator, llm, # LLM tts, transport.output(), # Transport bot output - context_aggregator.assistant(), + assistant_aggregator, ] ) diff --git a/examples/foundational/20d-persistent-context-gemini.py b/examples/foundational/20d-persistent-context-gemini.py index 37a2f16a2..a29eb5cf9 100644 --- a/examples/foundational/20d-persistent-context-gemini.py +++ b/examples/foundational/20d-persistent-context-gemini.py @@ -282,7 +282,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): llm.register_function("get_image", get_image) context = LLMContext(messages, tools) - context_aggregator = LLMContextAggregatorPair( + user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, user_params=LLMUserAggregatorParams( user_turn_strategies=UserTurnStrategies( @@ -295,11 +295,11 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): [ transport.input(), # Transport user input stt, # STT - context_aggregator.user(), + user_aggregator, llm, # LLM tts, transport.output(), # Transport bot output - context_aggregator.assistant(), + assistant_aggregator, ] ) diff --git a/examples/foundational/20e-persistent-context-aws-nova-sonic.py b/examples/foundational/20e-persistent-context-aws-nova-sonic.py index 16801d377..bd95fb7e7 100644 --- a/examples/foundational/20e-persistent-context-aws-nova-sonic.py +++ b/examples/foundational/20e-persistent-context-aws-nova-sonic.py @@ -235,15 +235,15 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): ], tools=tools, ) - context_aggregator = LLMContextAggregatorPair(context) + user_aggregator, assistant_aggregator = LLMContextAggregatorPair(context) pipeline = Pipeline( [ transport.input(), # Transport user input - context_aggregator.user(), + user_aggregator, llm, # LLM transport.output(), # Transport bot output - context_aggregator.assistant(), + assistant_aggregator, ] ) diff --git a/examples/foundational/20f-persistent-context-grok-realtime.py b/examples/foundational/20f-persistent-context-grok-realtime.py index 3fd73eed5..efa04c732 100644 --- a/examples/foundational/20f-persistent-context-grok-realtime.py +++ b/examples/foundational/20f-persistent-context-grok-realtime.py @@ -203,15 +203,15 @@ Remember, your responses should be short - just one or two sentences usually.""" llm.register_function("load_conversation", load_conversation) context = LLMContext([{"role": "user", "content": "Say hello!"}], tools) - context_aggregator = LLMContextAggregatorPair(context) + user_aggregator, assistant_aggregator = LLMContextAggregatorPair(context) pipeline = Pipeline( [ transport.input(), - context_aggregator.user(), + user_aggregator, llm, transport.output(), - context_aggregator.assistant(), + assistant_aggregator, ] ) diff --git a/examples/foundational/21-tavus-transport.py b/examples/foundational/21-tavus-transport.py index 940d57bb9..b4f5c159a 100644 --- a/examples/foundational/21-tavus-transport.py +++ b/examples/foundational/21-tavus-transport.py @@ -69,7 +69,7 @@ async def main(): ] context = LLMContext(messages) - context_aggregator = LLMContextAggregatorPair( + user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, user_params=LLMUserAggregatorParams( user_turn_strategies=UserTurnStrategies( @@ -84,11 +84,11 @@ async def main(): [ transport.input(), # Transport user input stt, # STT - context_aggregator.user(), # User responses + user_aggregator, # User responses llm, # LLM tts, # TTS transport.output(), # Transport bot output - context_aggregator.assistant(), # Assistant spoken responses + assistant_aggregator, # Assistant spoken responses ] ) diff --git a/examples/foundational/21a-tavus-video-service.py b/examples/foundational/21a-tavus-video-service.py index 64393d49b..0d68e2300 100644 --- a/examples/foundational/21a-tavus-video-service.py +++ b/examples/foundational/21a-tavus-video-service.py @@ -87,7 +87,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): ] context = LLMContext(messages) - context_aggregator = LLMContextAggregatorPair( + user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, user_params=LLMUserAggregatorParams( user_turn_strategies=UserTurnStrategies( @@ -102,12 +102,12 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): [ transport.input(), # Transport user input stt, # STT - context_aggregator.user(), # User responses + user_aggregator, # User responses llm, # LLM tts, # TTS tavus, # Tavus output layer transport.output(), # Transport bot output - context_aggregator.assistant(), # Assistant spoken responses + assistant_aggregator, # Assistant spoken responses ] ) diff --git a/examples/foundational/22b-natural-conversation-proposal.py b/examples/foundational/22b-natural-conversation-proposal.py index 75f53ad4d..256a6c9df 100644 --- a/examples/foundational/22b-natural-conversation-proposal.py +++ b/examples/foundational/22b-natural-conversation-proposal.py @@ -338,7 +338,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): ] context = LLMContext(messages, tools) - context_aggregator = LLMContextAggregatorPair( + user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, user_params=LLMUserAggregatorParams( user_turn_strategies=UserTurnStrategies( @@ -354,11 +354,11 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): [ transport.input(), stt, - context_aggregator.user(), + user_aggregator, llm, tts, transport.output(), - context_aggregator.assistant(), + assistant_aggregator, ] ) diff --git a/examples/foundational/22c-natural-conversation-mixed-llms.py b/examples/foundational/22c-natural-conversation-mixed-llms.py index b354575cf..bdb557594 100644 --- a/examples/foundational/22c-natural-conversation-mixed-llms.py +++ b/examples/foundational/22c-natural-conversation-mixed-llms.py @@ -541,7 +541,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): ] context = LLMContext(messages, tools) - context_aggregator = LLMContextAggregatorPair( + user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, user_params=LLMUserAggregatorParams( user_turn_strategies=UserTurnStrategies( @@ -557,11 +557,11 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): [ transport.input(), stt, - context_aggregator.user(), + user_aggregator, llm, tts, transport.output(), - context_aggregator.assistant(), + assistant_aggregator, ] ) diff --git a/examples/foundational/22d-natural-conversation-gemini-audio.py b/examples/foundational/22d-natural-conversation-gemini-audio.py index 562364d52..23c429c2f 100644 --- a/examples/foundational/22d-natural-conversation-gemini-audio.py +++ b/examples/foundational/22d-natural-conversation-gemini-audio.py @@ -741,7 +741,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): ) context = LLMContext() - context_aggregator = LLMContextAggregatorPair( + user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, user_params=LLMUserAggregatorParams( user_turn_strategies=UserTurnStrategies( @@ -755,10 +755,11 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): pipeline = Pipeline( [ transport.input(), + user_aggregator, llm, tts, transport.output(), - context_aggregator.assistant(), + assistant_aggregator, ], ) diff --git a/examples/foundational/23-bot-background-sound.py b/examples/foundational/23-bot-background-sound.py index c19a91498..1cc944f26 100644 --- a/examples/foundational/23-bot-background-sound.py +++ b/examples/foundational/23-bot-background-sound.py @@ -96,7 +96,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): ] context = LLMContext(messages) - context_aggregator = LLMContextAggregatorPair( + user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, user_params=LLMUserAggregatorParams( user_turn_strategies=UserTurnStrategies( @@ -109,11 +109,11 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): [ transport.input(), # Transport user input stt, # STT - context_aggregator.user(), # User responses + user_aggregator, # User responses llm, # LLM tts, # TTS transport.output(), # Transport bot output - context_aggregator.assistant(), # Assistant spoken responses + assistant_aggregator, # Assistant spoken responses ] ) diff --git a/examples/foundational/24-stt-mute-filter.py b/examples/foundational/24-stt-mute-filter.py index 72f9682bb..0c51716b8 100644 --- a/examples/foundational/24-stt-mute-filter.py +++ b/examples/foundational/24-stt-mute-filter.py @@ -117,7 +117,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): ] context = LLMContext(messages, tools) - context_aggregator = LLMContextAggregatorPair( + user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, user_params=LLMUserAggregatorParams( user_turn_strategies=UserTurnStrategies( @@ -131,11 +131,11 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): transport.input(), # Transport user input stt, # STT stt_mute_processor, # Add the mute processor between STT and context aggregator - context_aggregator.user(), # User responses + user_aggregator, # User responses llm, # LLM tts, # TTS transport.output(), # Transport bot output - context_aggregator.assistant(), # Assistant spoken responses + assistant_aggregator, # Assistant spoken responses ] ) diff --git a/examples/foundational/24-user-mute-strategy.py b/examples/foundational/24-user-mute-strategy.py index 621a2c682..df6619fd4 100644 --- a/examples/foundational/24-user-mute-strategy.py +++ b/examples/foundational/24-user-mute-strategy.py @@ -110,7 +110,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): ] context = LLMContext(messages, tools) - context_aggregator = LLMContextAggregatorPair( + user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, user_params=LLMUserAggregatorParams( user_turn_strategies=UserTurnStrategies( @@ -127,11 +127,11 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): [ transport.input(), # Transport user input stt, # STT - context_aggregator.user(), # User responses + user_aggregator, # User responses llm, # LLM tts, # TTS transport.output(), # Transport bot output - context_aggregator.assistant(), # Assistant spoken responses + assistant_aggregator, # Assistant spoken responses ] ) diff --git a/examples/foundational/26a-gemini-live-transcription.py b/examples/foundational/26a-gemini-live-transcription.py index 0248ca358..8eab86639 100644 --- a/examples/foundational/26a-gemini-live-transcription.py +++ b/examples/foundational/26a-gemini-live-transcription.py @@ -91,19 +91,17 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): # }, ], ) - context_aggregator = LLMContextAggregatorPair(context) + user_aggregator, assistant_aggregator = LLMContextAggregatorPair(context) transcript = TranscriptProcessor() pipeline = Pipeline( [ transport.input(), - context_aggregator.user(), - transcript.user(), + user_aggregator, llm, transport.output(), - transcript.assistant(), - context_aggregator.assistant(), + assistant_aggregator, ] ) diff --git a/examples/foundational/26b-gemini-live-function-calling.py b/examples/foundational/26b-gemini-live-function-calling.py index 3f054dd65..a16445630 100644 --- a/examples/foundational/26b-gemini-live-function-calling.py +++ b/examples/foundational/26b-gemini-live-function-calling.py @@ -151,15 +151,15 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): ], # tools, ) - context_aggregator = LLMContextAggregatorPair(context) + user_aggregator, assistant_aggregator = LLMContextAggregatorPair(context) pipeline = Pipeline( [ transport.input(), - context_aggregator.user(), + user_aggregator, llm, transport.output(), - context_aggregator.assistant(), + assistant_aggregator, ] ) diff --git a/examples/foundational/26c-gemini-live-video.py b/examples/foundational/26c-gemini-live-video.py index 5b3161cc7..314765bab 100644 --- a/examples/foundational/26c-gemini-live-video.py +++ b/examples/foundational/26c-gemini-live-video.py @@ -74,15 +74,15 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): }, ], ) - context_aggregator = LLMContextAggregatorPair(context) + user_aggregator, assistant_aggregator = LLMContextAggregatorPair(context) pipeline = Pipeline( [ transport.input(), - context_aggregator.user(), + user_aggregator, llm, transport.output(), - context_aggregator.assistant(), + assistant_aggregator, ] ) diff --git a/examples/foundational/26d-gemini-live-text.py b/examples/foundational/26d-gemini-live-text.py index c4eb62fb7..c51f32d7b 100644 --- a/examples/foundational/26d-gemini-live-text.py +++ b/examples/foundational/26d-gemini-live-text.py @@ -111,16 +111,16 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): # Set up conversation context and management # The context_aggregator will automatically collect conversation context context = LLMContext(messages) - context_aggregator = LLMContextAggregatorPair(context) + user_aggregator, assistant_aggregator = LLMContextAggregatorPair(context) pipeline = Pipeline( [ transport.input(), - context_aggregator.user(), + user_aggregator, llm, tts, transport.output(), - context_aggregator.assistant(), + assistant_aggregator, ] ) diff --git a/examples/foundational/26e-gemini-live-google-search.py b/examples/foundational/26e-gemini-live-google-search.py index bc14cf713..294cf1789 100644 --- a/examples/foundational/26e-gemini-live-google-search.py +++ b/examples/foundational/26e-gemini-live-google-search.py @@ -99,15 +99,15 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): } ], ) - context_aggregator = LLMContextAggregatorPair(context) + user_aggregator, assistant_aggregator = LLMContextAggregatorPair(context) pipeline = Pipeline( [ transport.input(), # Transport user input - context_aggregator.user(), # User responses + user_aggregator, # User responses llm, # LLM transport.output(), # Transport bot output - context_aggregator.assistant(), # Assistant spoken responses + assistant_aggregator, # Assistant spoken responses ] ) diff --git a/examples/foundational/26f-gemini-live-files-api.py b/examples/foundational/26f-gemini-live-files-api.py index 7f5f3eae2..3b9709869 100644 --- a/examples/foundational/26f-gemini-live-files-api.py +++ b/examples/foundational/26f-gemini-live-files-api.py @@ -163,16 +163,16 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): ) # Create context aggregator - context_aggregator = LLMContextAggregatorPair(context) + user_aggregator, assistant_aggregator = LLMContextAggregatorPair(context) # Build the pipeline pipeline = Pipeline( [ transport.input(), - context_aggregator.user(), + user_aggregator, llm, transport.output(), - context_aggregator.assistant(), + assistant_aggregator, ] ) diff --git a/examples/foundational/26g-gemini-live-groundingMetadata.py b/examples/foundational/26g-gemini-live-groundingMetadata.py index 6626e9b39..1cf2be618 100644 --- a/examples/foundational/26g-gemini-live-groundingMetadata.py +++ b/examples/foundational/26g-gemini-live-groundingMetadata.py @@ -126,16 +126,16 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): # Set up conversation context and management context = LLMContext(messages) - context_aggregator = LLMContextAggregatorPair(context) + user_aggregator, assistant_aggregator = LLMContextAggregatorPair(context) pipeline = Pipeline( [ transport.input(), - context_aggregator.user(), + user_aggregator, llm, grounding_processor, # Add our grounding processor here transport.output(), - context_aggregator.assistant(), + assistant_aggregator, ] ) diff --git a/examples/foundational/26h-gemini-live-vertex-function-calling.py b/examples/foundational/26h-gemini-live-vertex-function-calling.py index 35eb4ade0..35068e4c5 100644 --- a/examples/foundational/26h-gemini-live-vertex-function-calling.py +++ b/examples/foundational/26h-gemini-live-vertex-function-calling.py @@ -139,15 +139,15 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): llm.register_function("get_restaurant_recommendation", fetch_restaurant_recommendation) context = LLMContext([{"role": "user", "content": "Say hello."}]) - context_aggregator = LLMContextAggregatorPair(context) + user_aggregator, assistant_aggregator = LLMContextAggregatorPair(context) pipeline = Pipeline( [ transport.input(), - context_aggregator.user(), + user_aggregator, llm, transport.output(), - context_aggregator.assistant(), + assistant_aggregator, ] ) diff --git a/examples/foundational/26i-gemini-live-graceful-end.py b/examples/foundational/26i-gemini-live-graceful-end.py index 5363d7538..dae2bd109 100644 --- a/examples/foundational/26i-gemini-live-graceful-end.py +++ b/examples/foundational/26i-gemini-live-graceful-end.py @@ -156,15 +156,15 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): context = LLMContext( [{"role": "user", "content": "Say hello."}], ) - context_aggregator = LLMContextAggregatorPair(context) + user_aggregator, assistant_aggregator = LLMContextAggregatorPair(context) pipeline = Pipeline( [ transport.input(), - context_aggregator.user(), + user_aggregator, llm, transport.output(), - context_aggregator.assistant(), + assistant_aggregator, ] ) diff --git a/examples/foundational/27-simli-layer.py b/examples/foundational/27-simli-layer.py index e056e2f20..b89793c6b 100644 --- a/examples/foundational/27-simli-layer.py +++ b/examples/foundational/27-simli-layer.py @@ -85,7 +85,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): ] context = LLMContext(messages) - context_aggregator = LLMContextAggregatorPair( + user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, user_params=LLMUserAggregatorParams( user_turn_strategies=UserTurnStrategies( @@ -98,12 +98,12 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): [ transport.input(), stt, - context_aggregator.user(), + user_aggregator, llm, tts, simli_ai, transport.output(), - context_aggregator.assistant(), + assistant_aggregator, ] ) diff --git a/examples/foundational/28-user-assistant-turns.py b/examples/foundational/28-user-assistant-turns.py index da405088f..e870c836b 100644 --- a/examples/foundational/28-user-assistant-turns.py +++ b/examples/foundational/28-user-assistant-turns.py @@ -143,7 +143,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): ] context = LLMContext(messages) - context_aggregator = LLMContextAggregatorPair( + user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, user_params=LLMUserAggregatorParams( user_turn_strategies=UserTurnStrategies( @@ -152,9 +152,6 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): ), ) - user_aggregator = context_aggregator.user() - assistant_aggregator = context_aggregator.assistant() - # Create transcript processor and handler transcript_handler = TranscriptHandler() # Output to log only # transcript_handler = TranscriptHandler(output_file="transcript.txt") # Output to file and log diff --git a/examples/foundational/29-turn-tracking-observer.py b/examples/foundational/29-turn-tracking-observer.py index d20996e31..6a9391232 100644 --- a/examples/foundational/29-turn-tracking-observer.py +++ b/examples/foundational/29-turn-tracking-observer.py @@ -78,7 +78,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): ] context = LLMContext(messages) - context_aggregator = LLMContextAggregatorPair( + user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, user_params=LLMUserAggregatorParams( user_turn_strategies=UserTurnStrategies( @@ -91,11 +91,11 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): [ transport.input(), # Transport user input stt, - context_aggregator.user(), # User responses + user_aggregator, # User responses llm, # LLM tts, # TTS transport.output(), # Transport bot output - context_aggregator.assistant(), # Assistant spoken responses + assistant_aggregator, # Assistant spoken responses ] ) diff --git a/examples/foundational/30-observer.py b/examples/foundational/30-observer.py index 3a19e3fa3..e26e3280c 100644 --- a/examples/foundational/30-observer.py +++ b/examples/foundational/30-observer.py @@ -125,7 +125,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): ] context = LLMContext(messages) - context_aggregator = LLMContextAggregatorPair( + user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, user_params=LLMUserAggregatorParams( user_turn_strategies=UserTurnStrategies( @@ -138,11 +138,11 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): [ transport.input(), # Transport user input stt, - context_aggregator.user(), # User responses + user_aggregator, # User responses llm, # LLM tts, # TTS transport.output(), # Transport bot output - context_aggregator.assistant(), # Assistant spoken responses + assistant_aggregator, # Assistant spoken responses ] ) diff --git a/examples/foundational/32-gemini-grounding-metadata.py b/examples/foundational/32-gemini-grounding-metadata.py index fb515b6af..ff4369224 100644 --- a/examples/foundational/32-gemini-grounding-metadata.py +++ b/examples/foundational/32-gemini-grounding-metadata.py @@ -125,7 +125,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): } ], ) - context_aggregator = LLMContextAggregatorPair( + user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, user_params=LLMUserAggregatorParams( user_turn_strategies=UserTurnStrategies( @@ -138,11 +138,11 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): [ transport.input(), stt, - context_aggregator.user(), + user_aggregator, llm, tts, transport.output(), - context_aggregator.assistant(), + assistant_aggregator, ] ) diff --git a/examples/foundational/33-gemini-rag.py b/examples/foundational/33-gemini-rag.py index 5c50859f2..8df31426b 100644 --- a/examples/foundational/33-gemini-rag.py +++ b/examples/foundational/33-gemini-rag.py @@ -226,7 +226,7 @@ Your response will be turned into speech so use only simple words and punctuatio ] context = LLMContext(messages, tools) - context_aggregator = LLMContextAggregatorPair( + user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, user_params=LLMUserAggregatorParams( user_turn_strategies=UserTurnStrategies( @@ -239,11 +239,11 @@ Your response will be turned into speech so use only simple words and punctuatio [ transport.input(), stt, - context_aggregator.user(), + user_aggregator, llm, tts, transport.output(), - context_aggregator.assistant(), + assistant_aggregator, ] ) task = PipelineTask( diff --git a/examples/foundational/34-audio-recording.py b/examples/foundational/34-audio-recording.py index d85812d70..6cbac25c6 100644 --- a/examples/foundational/34-audio-recording.py +++ b/examples/foundational/34-audio-recording.py @@ -136,7 +136,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): ] context = LLMContext(messages) - context_aggregator = LLMContextAggregatorPair( + user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, user_params=LLMUserAggregatorParams( user_turn_strategies=UserTurnStrategies( @@ -149,12 +149,12 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): [ transport.input(), stt, - context_aggregator.user(), + user_aggregator, llm, tts, transport.output(), audiobuffer, # Add audio buffer to pipeline - context_aggregator.assistant(), + assistant_aggregator, ] ) diff --git a/examples/foundational/35-pattern-pair-voice-switching.py b/examples/foundational/35-pattern-pair-voice-switching.py index d35a9955c..c90a39b39 100644 --- a/examples/foundational/35-pattern-pair-voice-switching.py +++ b/examples/foundational/35-pattern-pair-voice-switching.py @@ -201,7 +201,7 @@ Remember: Use narrator voice for EVERYTHING except the actual quoted dialogue."" ] context = LLMContext(messages) - context_aggregator = LLMContextAggregatorPair( + user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, user_params=LLMUserAggregatorParams( user_turn_strategies=UserTurnStrategies( @@ -215,11 +215,11 @@ Remember: Use narrator voice for EVERYTHING except the actual quoted dialogue."" [ transport.input(), stt, - context_aggregator.user(), + user_aggregator, llm, tts, # TTS with pattern aggregator transport.output(), - context_aggregator.assistant(), + assistant_aggregator, ] ) diff --git a/examples/foundational/36-user-email-gathering.py b/examples/foundational/36-user-email-gathering.py index 2908bce76..1af985235 100644 --- a/examples/foundational/36-user-email-gathering.py +++ b/examples/foundational/36-user-email-gathering.py @@ -117,7 +117,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): ] context = LLMContext(messages, tools) - context_aggregator = LLMContextAggregatorPair( + user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, user_params=LLMUserAggregatorParams( user_turn_strategies=UserTurnStrategies( @@ -130,11 +130,11 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): [ transport.input(), stt, - context_aggregator.user(), + user_aggregator, llm, tts, transport.output(), - context_aggregator.assistant(), + assistant_aggregator, ] ) diff --git a/examples/foundational/37-mem0.py b/examples/foundational/37-mem0.py index 0ba192dda..c82d39edc 100644 --- a/examples/foundational/37-mem0.py +++ b/examples/foundational/37-mem0.py @@ -247,7 +247,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): # Set up conversation context and management # The context_aggregator will automatically collect conversation context context = LLMContext(messages) - context_aggregator = LLMContextAggregatorPair( + user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, user_params=LLMUserAggregatorParams( user_turn_strategies=UserTurnStrategies( @@ -262,12 +262,12 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): transport.input(), rtvi, stt, - context_aggregator.user(), + user_aggregator, memory, llm, tts, transport.output(), - context_aggregator.assistant(), + assistant_aggregator, ] ) diff --git a/examples/foundational/38-smart-turn-fal.py b/examples/foundational/38-smart-turn-fal.py index 6c20e5a86..05bbba5e9 100644 --- a/examples/foundational/38-smart-turn-fal.py +++ b/examples/foundational/38-smart-turn-fal.py @@ -79,7 +79,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): ] context = LLMContext(messages) - context_aggregator = LLMContextAggregatorPair( + user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, user_params=LLMUserAggregatorParams( user_turn_strategies=UserTurnStrategies( @@ -99,11 +99,11 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): [ transport.input(), # Transport user input stt, - context_aggregator.user(), # User responses + user_aggregator, # User responses llm, # LLM tts, # TTS transport.output(), # Transport bot output - context_aggregator.assistant(), # Assistant spoken responses + assistant_aggregator, # Assistant spoken responses ] ) diff --git a/examples/foundational/38a-smart-turn-local-coreml.py b/examples/foundational/38a-smart-turn-local-coreml.py index 1561e3c92..6500add0a 100644 --- a/examples/foundational/38a-smart-turn-local-coreml.py +++ b/examples/foundational/38a-smart-turn-local-coreml.py @@ -94,7 +94,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): ] context = LLMContext(messages) - context_aggregator = LLMContextAggregatorPair( + user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, user_params=LLMUserAggregatorParams( user_turn_strategies=UserTurnStrategies( @@ -113,11 +113,11 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): [ transport.input(), # Transport user input stt, - context_aggregator.user(), # User responses + user_aggregator, # User responses llm, # LLM tts, # TTS transport.output(), # Transport bot output - context_aggregator.assistant(), # Assistant spoken responses + assistant_aggregator, # Assistant spoken responses ] ) diff --git a/examples/foundational/38b-smart-turn-local.py b/examples/foundational/38b-smart-turn-local.py index 5a0d76639..37112de4d 100644 --- a/examples/foundational/38b-smart-turn-local.py +++ b/examples/foundational/38b-smart-turn-local.py @@ -78,7 +78,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): ] context = LLMContext(messages) - context_aggregator = LLMContextAggregatorPair( + user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, user_params=LLMUserAggregatorParams( user_turn_strategies=UserTurnStrategies( @@ -94,11 +94,11 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): transport.input(), # Transport user input rtvi, stt, - context_aggregator.user(), # User responses + user_aggregator, # User responses llm, # LLM tts, # TTS transport.output(), # Transport bot output - context_aggregator.assistant(), # Assistant spoken responses + assistant_aggregator, # Assistant spoken responses ] ) diff --git a/examples/foundational/39-mcp-stdio.py b/examples/foundational/39-mcp-stdio.py index 6d29cded1..02b4b2295 100644 --- a/examples/foundational/39-mcp-stdio.py +++ b/examples/foundational/39-mcp-stdio.py @@ -192,7 +192,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): messages = [{"role": "system", "content": system}] context = LLMContext(messages, tools) - context_aggregator = LLMContextAggregatorPair( + user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, user_params=LLMUserAggregatorParams( user_turn_strategies=UserTurnStrategies( @@ -207,12 +207,12 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): [ transport.input(), # Transport user input stt, - context_aggregator.user(), # User spoken responses + user_aggregator, # User spoken responses llm, # LLM tts, # TTS mcp_image, # URL image -> output transport.output(), # Transport bot output - context_aggregator.assistant(), # Assistant spoken responses and tool context + assistant_aggregator, # Assistant spoken responses and tool context ] ) diff --git a/examples/foundational/39a-mcp-streamable-http.py b/examples/foundational/39a-mcp-streamable-http.py index 6b59e66bd..6bd8fad61 100644 --- a/examples/foundational/39a-mcp-streamable-http.py +++ b/examples/foundational/39a-mcp-streamable-http.py @@ -105,7 +105,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): messages = [{"role": "system", "content": system}] context = LLMContext(messages, tools) - context_aggregator = LLMContextAggregatorPair( + user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, user_params=LLMUserAggregatorParams( user_turn_strategies=UserTurnStrategies( @@ -118,11 +118,11 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): [ transport.input(), # Transport user input stt, - context_aggregator.user(), # User spoken responses + user_aggregator, # User spoken responses llm, # LLM tts, # TTS transport.output(), # Transport bot output - context_aggregator.assistant(), # Assistant spoken responses and tool context + assistant_aggregator, # Assistant spoken responses and tool context ] ) diff --git a/examples/foundational/39b-mcp-streamable-http-gemini-live.py b/examples/foundational/39b-mcp-streamable-http-gemini-live.py index f83b741a9..6294d9d71 100644 --- a/examples/foundational/39b-mcp-streamable-http-gemini-live.py +++ b/examples/foundational/39b-mcp-streamable-http-gemini-live.py @@ -109,7 +109,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): await mcp.register_tools_schema(tools, llm) context = LLMContext([{"role": "user", "content": "Please introduce yourself."}]) - context_aggregator = LLMContextAggregatorPair( + user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, user_params=LLMUserAggregatorParams( user_turn_strategies=UserTurnStrategies( @@ -121,10 +121,10 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): pipeline = Pipeline( [ transport.input(), # Transport user input - context_aggregator.user(), # User spoken responses + user_aggregator, # User spoken responses llm, # LLM transport.output(), # Transport bot output - context_aggregator.assistant(), # Assistant spoken responses and tool context + assistant_aggregator, # Assistant spoken responses and tool context ] ) diff --git a/examples/foundational/39c-multiple-mcp.py b/examples/foundational/39c-multiple-mcp.py index 9a6fe0d12..6141b371e 100644 --- a/examples/foundational/39c-multiple-mcp.py +++ b/examples/foundational/39c-multiple-mcp.py @@ -193,7 +193,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): all_tools = ToolsSchema(standard_tools=all_standard_tools) context = LLMContext(messages, all_tools) - context_aggregator = LLMContextAggregatorPair( + user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, user_params=LLMUserAggregatorParams( user_turn_strategies=UserTurnStrategies( @@ -209,12 +209,12 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): [ transport.input(), # Transport user input stt, - context_aggregator.user(), # User spoken responses + user_aggregator, # User spoken responses llm, # LLM tts, # TTS mcp_image_processor, # URL image -> output transport.output(), # Transport bot output - context_aggregator.assistant(), # Assistant spoken responses and tool context + assistant_aggregator, # Assistant spoken responses and tool context ] ) diff --git a/examples/foundational/40-aws-nova-sonic.py b/examples/foundational/40-aws-nova-sonic.py index 42eac74a8..f80bc5220 100644 --- a/examples/foundational/40-aws-nova-sonic.py +++ b/examples/foundational/40-aws-nova-sonic.py @@ -156,10 +156,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): ], tools=tools, ) - context_aggregator = LLMContextAggregatorPair(context) - - user_aggregator = context_aggregator.user() - assistant_aggregator = context_aggregator.assistant() + user_aggregator, assistant_aggregator = LLMContextAggregatorPair(context) # Build the pipeline pipeline = Pipeline( diff --git a/examples/foundational/42-interruption-config.py b/examples/foundational/42-interruption-config.py index 46937abfa..c70e54c2d 100644 --- a/examples/foundational/42-interruption-config.py +++ b/examples/foundational/42-interruption-config.py @@ -79,7 +79,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): ] context = LLMContext(messages) - context_aggregator = LLMContextAggregatorPair( + user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, user_params=LLMUserAggregatorParams( user_turn_strategies=UserTurnStrategies( @@ -93,11 +93,11 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): [ transport.input(), # Transport user input stt, - context_aggregator.user(), # User responses + user_aggregator, # User responses llm, # LLM tts, # TTS transport.output(), # Transport bot output - context_aggregator.assistant(), # Assistant spoken responses + assistant_aggregator, # Assistant spoken responses ] ) diff --git a/examples/foundational/43-heygen-transport.py b/examples/foundational/43-heygen-transport.py index cda625f1f..42f44c3f9 100644 --- a/examples/foundational/43-heygen-transport.py +++ b/examples/foundational/43-heygen-transport.py @@ -67,7 +67,7 @@ async def main(): ] context = LLMContext(messages) - context_aggregator = LLMContextAggregatorPair( + user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, user_params=LLMUserAggregatorParams( user_turn_strategies=UserTurnStrategies( @@ -82,11 +82,11 @@ async def main(): [ transport.input(), # Transport user input stt, # STT - context_aggregator.user(), # User responses + user_aggregator, # User responses llm, # LLM tts, # TTS transport.output(), # Transport bot output - context_aggregator.assistant(), # Assistant spoken responses + assistant_aggregator, # Assistant spoken responses ] ) diff --git a/examples/foundational/43a-heygen-video-service.py b/examples/foundational/43a-heygen-video-service.py index 10ce8b677..9257fbc77 100644 --- a/examples/foundational/43a-heygen-video-service.py +++ b/examples/foundational/43a-heygen-video-service.py @@ -88,7 +88,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): ] context = LLMContext(messages) - context_aggregator = LLMContextAggregatorPair( + user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, user_params=LLMUserAggregatorParams( user_turn_strategies=UserTurnStrategies( @@ -103,12 +103,12 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): [ transport.input(), # Transport user input stt, # STT - context_aggregator.user(), # User responses + user_aggregator, # User responses llm, # LLM tts, # TTS heyGen, # Avatar transport.output(), # Transport bot output - context_aggregator.assistant(), # Assistant spoken responses + assistant_aggregator, # Assistant spoken responses ] ) diff --git a/examples/foundational/44-voicemail-detection.py b/examples/foundational/44-voicemail-detection.py index 9c57343cc..baa76a05f 100644 --- a/examples/foundational/44-voicemail-detection.py +++ b/examples/foundational/44-voicemail-detection.py @@ -80,7 +80,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): ] context = LLMContext(messages) - context_aggregator = LLMContextAggregatorPair( + user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, user_params=LLMUserAggregatorParams( user_turn_strategies=UserTurnStrategies( @@ -94,12 +94,12 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): transport.input(), stt, voicemail.detector(), # Voicemail detection — between STT and User context aggregator - context_aggregator.user(), + user_aggregator, llm, tts, voicemail.gate(), # TTS gating — Immediately after the TTS service transport.output(), - context_aggregator.assistant(), + assistant_aggregator, ] ) diff --git a/examples/foundational/45-before-and-after-events.py b/examples/foundational/45-before-and-after-events.py index a62cee730..c6f9376e5 100644 --- a/examples/foundational/45-before-and-after-events.py +++ b/examples/foundational/45-before-and-after-events.py @@ -88,7 +88,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): ] context = LLMContext(messages) - context_aggregator = LLMContextAggregatorPair( + user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, user_params=LLMUserAggregatorParams( user_turn_strategies=UserTurnStrategies( @@ -101,11 +101,11 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): [ transport.input(), # Transport user input stt, - context_aggregator.user(), # User responses + user_aggregator, # User responses llm, # LLM tts, # TTS transport.output(), # Transport bot output - context_aggregator.assistant(), # Assistant spoken responses + assistant_aggregator, # Assistant spoken responses ] ) diff --git a/examples/foundational/46-video-processing.py b/examples/foundational/46-video-processing.py index e2afc4d0e..c35843eab 100644 --- a/examples/foundational/46-video-processing.py +++ b/examples/foundational/46-video-processing.py @@ -116,7 +116,7 @@ async def run_bot(pipecat_transport): ] context = LLMContext(messages) - context_aggregator = LLMContextAggregatorPair( + user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, user_params=LLMUserAggregatorParams( user_turn_strategies=UserTurnStrategies( @@ -131,7 +131,7 @@ async def run_bot(pipecat_transport): pipeline = Pipeline( [ pipecat_transport.input(), - context_aggregator.user(), + user_aggregator, rtvi, llm, # LLM EdgeDetectionProcessor( @@ -139,7 +139,7 @@ async def run_bot(pipecat_transport): pipecat_transport._params.video_out_height, ), # Sending the video back to the user pipecat_transport.output(), - context_aggregator.assistant(), + assistant_aggregator, ] ) diff --git a/examples/foundational/47-sentry-metrics.py b/examples/foundational/47-sentry-metrics.py index ac0a9e6b5..1b74210a1 100644 --- a/examples/foundational/47-sentry-metrics.py +++ b/examples/foundational/47-sentry-metrics.py @@ -91,7 +91,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): ] context = LLMContext(messages) - context_aggregator = LLMContextAggregatorPair( + user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, user_params=LLMUserAggregatorParams( user_turn_strategies=UserTurnStrategies( @@ -104,11 +104,11 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): [ transport.input(), # Transport user input stt, - context_aggregator.user(), # User responses + user_aggregator, # User responses llm, # LLM tts, # TTS transport.output(), # Transport bot output - context_aggregator.assistant(), # Assistant spoken responses + assistant_aggregator, # Assistant spoken responses ] ) diff --git a/examples/foundational/48-service-switcher.py b/examples/foundational/48-service-switcher.py index a28d5750a..97b06a44a 100644 --- a/examples/foundational/48-service-switcher.py +++ b/examples/foundational/48-service-switcher.py @@ -136,7 +136,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): tools = ToolsSchema(standard_tools=[weather_function, get_restaurant_recommendation]) context = LLMContext(messages, tools) - context_aggregator = LLMContextAggregatorPair( + user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, user_params=LLMUserAggregatorParams( user_turn_strategies=UserTurnStrategies( @@ -149,11 +149,11 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): [ transport.input(), # Transport user input stt_switcher, - context_aggregator.user(), # User responses + user_aggregator, # User responses llm_switcher, # LLM tts_switcher, # TTS transport.output(), # Transport bot output - context_aggregator.assistant(), # Assistant spoken responses + assistant_aggregator, # Assistant spoken responses ] ) diff --git a/examples/foundational/49a-thinking-anthropic.py b/examples/foundational/49a-thinking-anthropic.py index 80477ff14..d813aeee5 100644 --- a/examples/foundational/49a-thinking-anthropic.py +++ b/examples/foundational/49a-thinking-anthropic.py @@ -82,7 +82,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): ] context = LLMContext(messages) - context_aggregator = LLMContextAggregatorPair( + user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, user_params=LLMUserAggregatorParams( user_turn_strategies=UserTurnStrategies( @@ -91,9 +91,6 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): ), ) - user_aggregator = context_aggregator.user() - assistant_aggregator = context_aggregator.assistant() - pipeline = Pipeline( [ transport.input(), # Transport user input diff --git a/examples/foundational/49b-thinking-google.py b/examples/foundational/49b-thinking-google.py index e0c9dcd6e..40cd48f31 100644 --- a/examples/foundational/49b-thinking-google.py +++ b/examples/foundational/49b-thinking-google.py @@ -87,7 +87,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): ] context = LLMContext(messages) - context_aggregator = LLMContextAggregatorPair( + user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, user_params=LLMUserAggregatorParams( user_turn_strategies=UserTurnStrategies( @@ -96,9 +96,6 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): ), ) - user_aggregator = context_aggregator.user() - assistant_aggregator = context_aggregator.assistant() - pipeline = Pipeline( [ transport.input(), # Transport user input diff --git a/examples/foundational/49c-thinking-functions-anthropic.py b/examples/foundational/49c-thinking-functions-anthropic.py index b18f672f6..33ea3ff0d 100644 --- a/examples/foundational/49c-thinking-functions-anthropic.py +++ b/examples/foundational/49c-thinking-functions-anthropic.py @@ -108,7 +108,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): ] context = LLMContext(messages, tools) - context_aggregator = LLMContextAggregatorPair( + user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, user_params=LLMUserAggregatorParams( user_turn_strategies=UserTurnStrategies( @@ -117,9 +117,6 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): ), ) - user_aggregator = context_aggregator.user() - assistant_aggregator = context_aggregator.assistant() - pipeline = Pipeline( [ transport.input(), # Transport user input diff --git a/examples/foundational/49d-thinking-functions-google.py b/examples/foundational/49d-thinking-functions-google.py index 794d4e4f7..0bd33b308 100644 --- a/examples/foundational/49d-thinking-functions-google.py +++ b/examples/foundational/49d-thinking-functions-google.py @@ -114,7 +114,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): ] context = LLMContext(messages, tools) - context_aggregator = LLMContextAggregatorPair( + user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, user_params=LLMUserAggregatorParams( user_turn_strategies=UserTurnStrategies( @@ -123,9 +123,6 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): ), ) - user_aggregator = context_aggregator.user() - assistant_aggregator = context_aggregator.assistant() - pipeline = Pipeline( [ transport.input(), # Transport user input diff --git a/examples/foundational/50-ultravox-realtime.py b/examples/foundational/50-ultravox-realtime.py index 095131cc6..51c298d77 100644 --- a/examples/foundational/50-ultravox-realtime.py +++ b/examples/foundational/50-ultravox-realtime.py @@ -170,15 +170,15 @@ There is also a secret menu that changes daily. If the user asks about it, use t llm.register_function("get_secret_menu", get_secret_menu) # Necessary to complete the function call lifecycle in Pipecat. - context_aggregator = LLMContextAggregatorPair(LLMContext([])) + user_aggregator, assistant_aggregator = LLMContextAggregatorPair(LLMContext([])) # Build the pipeline pipeline = Pipeline( [ transport.input(), - context_aggregator.user(), + user_aggregator, llm, - context_aggregator.assistant(), + assistant_aggregator, transport.output(), ] ) diff --git a/examples/foundational/51-grok-realtime.py b/examples/foundational/51-grok-realtime.py index ee795270a..6a2fbe5a2 100644 --- a/examples/foundational/51-grok-realtime.py +++ b/examples/foundational/51-grok-realtime.py @@ -215,10 +215,7 @@ Always be helpful and proactive in offering assistance.""", tools, ) - context_aggregator = LLMContextAggregatorPair(context) - - user_aggregator = context_aggregator.user() - assistant_aggregator = context_aggregator.assistant() + user_aggregator, assistant_aggregator = LLMContextAggregatorPair(context) # Build the pipeline # Note: In realtime mode, transcription comes from Grok (upstream), diff --git a/examples/foundational/52-live-translation.py b/examples/foundational/52-live-translation.py index d92acb309..347c0a99e 100644 --- a/examples/foundational/52-live-translation.py +++ b/examples/foundational/52-live-translation.py @@ -83,7 +83,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): # every time a transcription is received. We disable interruptions, so the # user can continue speaking while the bot is transcribing, without # interrupting the bot. - context_aggregator = LLMContextAggregatorPair( + user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, user_params=LLMUserAggregatorParams( user_turn_strategies=UserTurnStrategies( @@ -97,11 +97,11 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): [ transport.input(), # Transport user input stt, # STT - context_aggregator.user(), # User responses + user_aggregator, # User responses llm, # LLM tts, # TTS (bot will speak the chosen language) transport.output(), # Transport bot output - context_aggregator.assistant(), # Assistant spoken responses + assistant_aggregator, # Assistant spoken responses ] ) From ee82377d68e6b0b1665f1f77a11ae45721eeaeb3 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Aleix=20Conchillo=20Flaqu=C3=A9?= Date: Tue, 13 Jan 2026 13:40:24 -0800 Subject: [PATCH 0042/1060] examples: fix 22d to push some CancelFrame and EndFrame --- examples/foundational/22d-natural-conversation-gemini-audio.py | 1 + 1 file changed, 1 insertion(+) diff --git a/examples/foundational/22d-natural-conversation-gemini-audio.py b/examples/foundational/22d-natural-conversation-gemini-audio.py index 23c429c2f..b144f485e 100644 --- a/examples/foundational/22d-natural-conversation-gemini-audio.py +++ b/examples/foundational/22d-natural-conversation-gemini-audio.py @@ -443,6 +443,7 @@ class CompletenessCheck(FrameProcessor): if self._idle_task: await self.cancel_task(self._idle_task) self._idle_task = None + await self.push_frame(frame, direction) elif isinstance(frame, UserStartedSpeakingFrame): if self._idle_task: await self.cancel_task(self._idle_task) From 0ebdaba03c198bc0d8050ffeb9b0d5efb3b3e9c8 Mon Sep 17 00:00:00 2001 From: Paul Kompfner Date: Tue, 13 Jan 2026 17:02:57 -0500 Subject: [PATCH 0043/1060] Remove dead import of `TranscriptProcessor` (which is now deprecated) --- examples/foundational/49d-thinking-functions-google.py | 1 - 1 file changed, 1 deletion(-) diff --git a/examples/foundational/49d-thinking-functions-google.py b/examples/foundational/49d-thinking-functions-google.py index 794d4e4f7..0595279b8 100644 --- a/examples/foundational/49d-thinking-functions-google.py +++ b/examples/foundational/49d-thinking-functions-google.py @@ -23,7 +23,6 @@ from pipecat.processors.aggregators.llm_response_universal import ( LLMContextAggregatorPair, LLMUserAggregatorParams, ) -from pipecat.processors.transcript_processor import TranscriptProcessor from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport from pipecat.services.cartesia.tts import CartesiaTTSService From be49a54856a0f6180715efaec6b45eacf5c07bfa Mon Sep 17 00:00:00 2001 From: Paul Kompfner Date: Tue, 13 Jan 2026 17:32:20 -0500 Subject: [PATCH 0044/1060] Fast-exit in the fix for parallel function calling with Gemini 3, if we can determine up-front that there's no work to do --- .../adapters/services/gemini_adapter.py | 18 ++++++++++++++++-- 1 file changed, 16 insertions(+), 2 deletions(-) diff --git a/src/pipecat/adapters/services/gemini_adapter.py b/src/pipecat/adapters/services/gemini_adapter.py index cb6f6d8de..2de3742c8 100644 --- a/src/pipecat/adapters/services/gemini_adapter.py +++ b/src/pipecat/adapters/services/gemini_adapter.py @@ -256,7 +256,7 @@ class GeminiLLMAdapter(BaseLLMAdapter[GeminiLLMInvocationParams]): self._apply_thought_signatures_to_messages(thought_signature_dicts, messages) # When thinking is enabled, merge parallel tool calls into single messages - messages = self._merge_parallel_tool_calls_for_thinking(messages) + messages = self._merge_parallel_tool_calls_for_thinking(thought_signature_dicts, messages) # Check if we only have function-related messages (no regular text) has_regular_messages = any( @@ -436,7 +436,9 @@ class GeminiLLMAdapter(BaseLLMAdapter[GeminiLLMInvocationParams]): tool_call_id_to_name_mapping=tool_call_id_to_name_mapping, ) - def _merge_parallel_tool_calls_for_thinking(self, messages: List[Content]) -> List[Content]: + def _merge_parallel_tool_calls_for_thinking( + self, thought_signature_dicts: List[dict], messages: List[Content] + ) -> List[Content]: """Merge parallel tool calls into single Content objects when thinking is enabled. Gemini expects parallel tool calls (multiple function calls made @@ -460,6 +462,8 @@ class GeminiLLMAdapter(BaseLLMAdapter[GeminiLLMInvocationParams]): messages appear in between. Args: + thought_signature_dicts: A list of thought signature dicts, used + to determine if the work of merging is necessary. messages: List of Content messages to process. Returns: @@ -469,6 +473,16 @@ class GeminiLLMAdapter(BaseLLMAdapter[GeminiLLMInvocationParams]): if not messages: return messages + # Fast-exit if no function-call-related thought signatures + # This is a shortcut for determining both: + # - whether thinking is enabled, and + # - whether there are function calls in the messages + has_function_call_signatures = any( + ts.get("bookmark", {}).get("function_call") for ts in thought_signature_dicts + ) + if not has_function_call_signatures: + return messages + def is_tool_call_message(msg: Content) -> bool: """Check if message contains only function_call parts.""" return ( From 0d6bdbee10fd08eeac71ba9d83f58e668b30ec57 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Aleix=20Conchillo=20Flaqu=C3=A9?= Date: Tue, 13 Jan 2026 15:11:22 -0800 Subject: [PATCH 0045/1060] LLMContextAggregatorPair: make strategy logs less verbose --- src/pipecat/processors/aggregators/llm_response_universal.py | 4 ++-- src/pipecat/turns/user_turn_processor.py | 4 ++-- 2 files changed, 4 insertions(+), 4 deletions(-) diff --git a/src/pipecat/processors/aggregators/llm_response_universal.py b/src/pipecat/processors/aggregators/llm_response_universal.py index 85050e6d0..2854c8681 100644 --- a/src/pipecat/processors/aggregators/llm_response_universal.py +++ b/src/pipecat/processors/aggregators/llm_response_universal.py @@ -530,7 +530,7 @@ class LLMUserAggregator(LLMContextAggregator): strategy: BaseUserTurnStartStrategy, params: UserTurnStartedParams, ): - logger.debug(f"{self}: User started speaking (user turn start strategy: {strategy})") + logger.debug(f"{self}: User started speaking (strategy: {strategy})") self._user_turn_start_timestamp = time_now_iso8601() @@ -548,7 +548,7 @@ class LLMUserAggregator(LLMContextAggregator): strategy: BaseUserTurnStopStrategy, params: UserTurnStoppedParams, ): - logger.debug(f"{self}: User stopped speaking (user turn stop strategy: {strategy})") + logger.debug(f"{self}: User stopped speaking (strategy: {strategy})") if params.enable_user_speaking_frames: await self.broadcast_frame(UserStoppedSpeakingFrame) diff --git a/src/pipecat/turns/user_turn_processor.py b/src/pipecat/turns/user_turn_processor.py index 33ac078c2..79e4664a0 100644 --- a/src/pipecat/turns/user_turn_processor.py +++ b/src/pipecat/turns/user_turn_processor.py @@ -155,7 +155,7 @@ class UserTurnProcessor(FrameProcessor): strategy: BaseUserTurnStartStrategy, params: UserTurnStartedParams, ): - logger.debug(f"{self}: User started speaking (user turn start strategy: {strategy})") + logger.debug(f"{self}: User started speaking (strategy: {strategy})") if params.enable_user_speaking_frames: await self.broadcast_frame(UserStartedSpeakingFrame) @@ -171,7 +171,7 @@ class UserTurnProcessor(FrameProcessor): strategy: BaseUserTurnStopStrategy, params: UserTurnStoppedParams, ): - logger.debug(f"{self}: User stopped speaking (user turn stop strategy: {strategy})") + logger.debug(f"{self}: User stopped speaking (strategy: {strategy})") if params.enable_user_speaking_frames: await self.broadcast_frame(UserStoppedSpeakingFrame) From b313395dc387b64a9dc6c9eaaa10b6270ca197d3 Mon Sep 17 00:00:00 2001 From: Mark Backman Date: Tue, 13 Jan 2026 19:31:24 -0500 Subject: [PATCH 0046/1060] Fix 26a foundational --- examples/foundational/26a-gemini-live-transcription.py | 3 --- 1 file changed, 3 deletions(-) diff --git a/examples/foundational/26a-gemini-live-transcription.py b/examples/foundational/26a-gemini-live-transcription.py index e654fe304..c5a9e7d3b 100644 --- a/examples/foundational/26a-gemini-live-transcription.py +++ b/examples/foundational/26a-gemini-live-transcription.py @@ -96,9 +96,6 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): ) user_aggregator, assistant_aggregator = LLMContextAggregatorPair(context) - user_aggregator = context_aggregator.user() - assistant_aggregator = context_aggregator.assistant() - pipeline = Pipeline( [ transport.input(), From 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Mon Sep 17 00:00:00 2001 From: aconchillo <951761+aconchillo@users.noreply.github.com> Date: Wed, 14 Jan 2026 00:49:15 +0000 Subject: [PATCH 0048/1060] Update changelog for version 0.0.99 --- CHANGELOG.md | 522 +++++++++++++++++++++++++++++++++ changelog/3045.added.md | 42 --- changelog/3045.deprecated.2.md | 1 - changelog/3045.deprecated.3.md | 1 - changelog/3045.deprecated.4.md | 1 - changelog/3045.deprecated.5.md | 1 - changelog/3045.deprecated.6.md | 1 - changelog/3045.deprecated.md | 1 - changelog/3205.added.md | 1 - changelog/3216.changed.md | 7 - changelog/3225.changed.md | 15 - changelog/3225.deprecated.md | 4 - changelog/3233.fixed.md | 2 - changelog/3257.changed.2.md | 1 - changelog/3257.changed.md | 1 - changelog/3263.deprecated.md | 15 - changelog/3267.added.md | 8 - changelog/3268.added.md | 1 - changelog/3288.changed.md | 5 - changelog/3289.added.md | 1 - changelog/3291.added.md | 4 - changelog/3292.added.md | 29 -- changelog/3292.deprecated.md | 1 - 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a/CHANGELOG.md +++ b/CHANGELOG.md @@ -7,6 +7,528 @@ and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0 +## [0.0.99] - 2026-01-13 + +### Added + +- Introducing user turn strategies. User turn strategies indicate when the user + turn starts or stops. In conversational agents, these are often referred to + as start/stop speaking or turn-taking plans or policies. + + User turn start strategies indicate when the user starts speaking (e.g. + using VAD events or when a user says one or more words). + + User turn stop strategies indicate when the user stops speaking (e.g. using + an end-of-turn detection model or by observing incoming transcriptions). + + A list of strategies can be specified for both strategies; strategies are + evaluated in order until one evaluates to true. + + Available user turn start strategies: + - VADUserTurnStartStrategy + - TranscriptionUserTurnStartStrategy + - MinWordsUserTurnStartStrategy + - ExternalUserTurnStartStrategy + + Available user turn stop strategies: + - TranscriptionUserTurnStopStrategy + - TurnAnalyzerUserTurnStopStrategy + - ExternalUserTurnStopStrategy + + The default strategies are: + + - start: [VADUserTurnStartStrategy, TranscriptionUserTurnStartStrategy] + - stop: [TranscriptionUserTurnStopStrategy] + + Turn strategies are configured when setting up `LLMContextAggregatorPair`. + For example: + + ```python + context_aggregator = LLMContextAggregatorPair( + context, + user_params=LLMUserAggregatorParams( + user_turn_strategies=UserTurnStrategies( + stop=[ + TurnAnalyzerUserTurnStopStrategy( +turn_analyzer=LocalSmartTurnAnalyzerV3(params=SmartTurnParams()) + ) + ], + ) + ), + ) + ``` + + In order to use the user turn strategies you must update to the new + universal `LLMContext` and `LLMContextAggregatorPair`. +(PR [#3045](https://github.com/pipecat-ai/pipecat/pull/3045)) + +- Added `RNNoiseFilter` for real-time noise suppression using RNNoise neural + network via pyrnnoise library. +(PR [#3205](https://github.com/pipecat-ai/pipecat/pull/3205)) + +- Added `GrokRealtimeLLMService` for xAI's Grok Voice Agent API with real-time + voice conversations: + + - Support for real-time audio streaming with WebSocket connection + - Built-in server-side VAD (Voice Activity Detection) + - Multiple voice options: Ara, Rex, Sal, Eve, Leo + - Built-in tools support: web_search, x_search, file_search + - Custom function calling with standard Pipecat tools schema + - Configurable audio formats (PCM at 8kHz-48kHz) +(PR [#3267](https://github.com/pipecat-ai/pipecat/pull/3267)) + +- Added an approximation of TTFB for Ultravox. +(PR [#3268](https://github.com/pipecat-ai/pipecat/pull/3268)) + +- Added a new `AudioContextTTSService` to the TTS service base classes. The + `AudioContextWordTTSService` now inherits from `AudioContextTTSService` and + `WebsocketWordTTSService`. +(PR [#3289](https://github.com/pipecat-ai/pipecat/pull/3289)) + +- `LLMUserAggregator` now exposes the following events: + - `on_user_turn_started`: triggered when a user turn starts + - `on_user_turn_stopped`: triggered when a user turn ends + - `on_user_turn_stop_timeout`: triggered when a user turn does not stop + and times out +(PR [#3291](https://github.com/pipecat-ai/pipecat/pull/3291)) + +- Introducing user mute strategies. User mute strategies indicate when user + input should be muted based on the current system state. + + In conversational agents, user mute strategies are used to prevent user + input from interrupting bot speech, tool execution, or other critical system + operations. + + A list of strategies can be specified; all strategies are evaluated for + every frame so that each strategy can maintain its internal state. A user + frame is muted if any of the configured strategies indicates it should be + muted. + + Available user mute strategies: + + * `FirstSpeechUserMuteStrategy` + * `MuteUntilFirstBotCompleteUserMuteStrategy` + * `AlwaysUserMuteStrategy` + * `FunctionCallUserMuteStrategy` + + User mute strategies replace the legacy `STTMuteFilter` and provide a more + flexible and composable approach to muting user input. + + User mute strategies are configured when setting up the + `LLMContextAggregatorPair`. For example: + + ```python + context_aggregator = LLMContextAggregatorPair( + context, + user_params=LLMUserAggregatorParams( + user_mute_strategies=[ + FirstSpeechUserMuteStrategy(), + ] + ), + ) + ``` + + In order to use user mute strategies you should update to the new universal + `LLMContext` and `LLMContextAggregatorPair`. +(PR [#3292](https://github.com/pipecat-ai/pipecat/pull/3292)) + +- Added `use_ssl` parameter to `NvidiaSTTService`, `NvidiaSegmentedSTTService` + and `NvidiaTTSService`. +(PR [#3300](https://github.com/pipecat-ai/pipecat/pull/3300)) + +- Added `enable_interruptions` constructor argument to all user turn + strategies. This tells the `LLMUserAggregator` to push or not push an + `InterruptionFrame`. +(PR [#3316](https://github.com/pipecat-ai/pipecat/pull/3316)) + +- Added `split_sentences` parameter to `SpeechmaticsSTTService` to control + sentence splitting behavior for finals on sentence boundaries. +(PR [#3328](https://github.com/pipecat-ai/pipecat/pull/3328)) + +- Added word-level timestamp support to `AzureTTSService` for accurate + text-to-audio synchronization. +(PR [#3334](https://github.com/pipecat-ai/pipecat/pull/3334)) + +- Added `pronunciation_dict_id` parameter to `CartesiaTTSService.InputParams` + and `CartesiaHttpTTSService.InputParams` to support Cartesia's pronunciation + dictionary feature for custom pronunciations. +(PR [#3346](https://github.com/pipecat-ai/pipecat/pull/3346)) + +- Added support for using the HeyGen LiveAvatar API with the `HeyGenTransport` + (see https://www.liveavatar.com/). +(PR [#3357](https://github.com/pipecat-ai/pipecat/pull/3357)) + +- Added image support to `OpenAIRealtimeLLMService` via `InputImageRawFrame`: + - New `start_video_paused` parameter to control initial video input state + - New `video_frame_detail` parameter to set image processing quality + ("auto", + "low", or "high"). This corresponds to OpenAI Realtime's `image_detail` + parameter. + - `set_video_input_paused()` method to pause/resume video input at runtime + - `set_video_frame_detail()` method to adjust video frame quality + dynamically + - Automatic rate limiting (1 frame per second) to prevent API overload +(PR [#3360](https://github.com/pipecat-ai/pipecat/pull/3360)) + +- Added `UserTurnProcessor`, a frame processor built on `UserTurnController` + that pushes `UserStartedSpeakingFrame` and `UserStoppedSpeakingFrame` frames + and interruptions based on the controller's user turn strategies. +(PR [#3372](https://github.com/pipecat-ai/pipecat/pull/3372)) + +- Added `UserTurnController` to manage user turns. It emits + `on_user_turn_started`, `on_user_turn_stopped`, and + `on_user_turn_stop_timeout` events, and can be integrated into processors to + detect and handle user turns. `LLMUserAggregator` and `UserTurnProcessor` are + implemented using this controller. +(PR [#3372](https://github.com/pipecat-ai/pipecat/pull/3372)) + +- Added `should_interrupt` property to `DeepgramFluxSTTService`, + `DeepgramSTTService`, and `SpeechmaticsSTTService` to configure whether the + bot should be interrupted when the external service detects user speech. +(PR [#3374](https://github.com/pipecat-ai/pipecat/pull/3374)) + +- `LLMAssistantAggregator` now exposes the following events: + - `on_assistant_turn_started`: triggered when the assistant turn starts + - `on_assistant_turn_stopped`: triggered when the assistant turn ends + - `on_assistant_thought`: triggered when there's an assistant thought + available +(PR [#3385](https://github.com/pipecat-ai/pipecat/pull/3385)) + +- Added `KrispVivaTurn` analyzer for end of turn detection using the Krisp VIVA + SDK (requires `krisp_audio`). +(PR [#3391](https://github.com/pipecat-ai/pipecat/pull/3391)) + +- Added support for setting up a pipeline task from external files. You can now + register custom pipeline task setup files by setting the + `PIPECAT_SETUP_FILES` environment variable. This variable should contain a + colon-separated list of Python files (e.g. `export + PIPECAT_SETUP_FILES="setup1.py:setup.py:..."`). Each file must define a + function with the following signature: + + ```python + async def setup_pipeline_task(task: PipelineTask): + ... + ``` +(PR [#3397](https://github.com/pipecat-ai/pipecat/pull/3397)) + +- Added a keepalive task for `InworldTTSService` to keep the service connected + in the event of no generations for longer periods of time. +(PR [#3403](https://github.com/pipecat-ai/pipecat/pull/3403)) + +- Added `enable_vad` to `Params` for use in the `GladiaSTTService`. When + enabled, `GladiaSTTService` acts as the turn controller, emitting + `UserStartedSpeakingFrame`, `UserStoppedSpeakingFrame`, and optionally + `InterruptionFrame`. +(PR [#3404](https://github.com/pipecat-ai/pipecat/pull/3404)) + +- Added `should_interrupt` property to `GladiaSTTService` to configure whether + the bot should be interrupted when the external service detects user speech. +(PR [#3404](https://github.com/pipecat-ai/pipecat/pull/3404)) + +- Added `VonageFrameSerializer` for the Vonage Video API Audio Connector + WebSocket protocol. +(PR [#3410](https://github.com/pipecat-ai/pipecat/pull/3410)) + +- Added `append_trailing_space` parameter to `TTSService` to automatically + append a trailing space to text before sending to TTS, helping prevent some + services from vocalizing trailing punctuation. +(PR [#3424](https://github.com/pipecat-ai/pipecat/pull/3424)) + +### Changed + +- Updated `ElevenLabsRealtimeSTTService` to accept the + `include_language_detection` parameter to detect language. + ```python + stt = ElevenLabsRealtimeSTTService( + api_key=os.getenv("ELEVENLABS_API_KEY"), + include_language_detection=True + ) + ``` +(PR [#3216](https://github.com/pipecat-ai/pipecat/pull/3216)) + +- Updated `SpeechmaticsSTTService` to use new Python Voice SDK with improved + VAD, + Smart Turn capabilities, and brings dramatic improvements to latency + without + any impact on accuracy. Use the `turn_detection_mode` parameter to control + the + endpointing of speech, with `TurnDetectionMode.EXTERNAL` (default), + `TurnDetectionMode.ADAPTIVE`, or `TurnDetectionMode.SMART_TURN`. + ```python + stt = SpeechmaticsSTTService( + api_key=os.getenv("SPEECHMATICS_API_KEY"), + params=SpeechmaticsSTTService.InputParams( + language=Language.EN, +turn_detection_mode=SpeechmaticsSTTService.TurnDetectionMode.ADAPTIVE, + speaker_active_format="<{speaker_id}>{text}", + ), + ) + ``` +(PR [#3225](https://github.com/pipecat-ai/pipecat/pull/3225)) + +- `daily-python` updated to 0.23.0. +(PR [#3257](https://github.com/pipecat-ai/pipecat/pull/3257)) + +- `TranscriptionFrame` and `InterimTranscriptionFrame` produced by + `DailyTransport` now include the transport source (i.e., the originating + audio track). +(PR [#3257](https://github.com/pipecat-ai/pipecat/pull/3257)) + +- Updates to Inworld TTS services: + + - Improved `InworldTTSService`'s websocket implementation to better flush + and + close context to better handle long inputs. + - Improved docstrings for `InworldTTSService` and `InworldHttpTTSService`. +(PR [#3288](https://github.com/pipecat-ai/pipecat/pull/3288)) + +- Updated `DeepgramSTTService` to push user started/stopped speaking and + interruption frames when `vad_enabled` is set to true. This centralizes the + frames into the service, removing the need to have your application code + handle Deepgram's events and push these frames. +(PR [#3314](https://github.com/pipecat-ai/pipecat/pull/3314)) + +- Added encoding validation to `DeepgramTTSService` to prevent unsupported + encodings from reaching the API. The service now raises `ValueError` at + initialization with a clear error message. +(PR [#3329](https://github.com/pipecat-ai/pipecat/pull/3329)) + +- Updated `read_audio_frame` & `read_video_frame` methods in + `SmallWebRTCClient` to check if the track is enabled before logging a + warning. +(PR [#3336](https://github.com/pipecat-ai/pipecat/pull/3336)) + +- Updated `CartesiaTTSService` to support setting `language=None`, resulting in + Cartesia auto-detecting the language of the conversation. +(PR [#3366](https://github.com/pipecat-ai/pipecat/pull/3366)) + +- The bundled Smart Turn weights are now updated to v3.2, which has better + handling of short utterances, and is more robust against background + noise. +(PR [#3367](https://github.com/pipecat-ai/pipecat/pull/3367)) + +- Updated `SpeechmaticsSTTService` dependency to + `speechmatics-voice[smart]>=0.2.6` +(PR [#3371](https://github.com/pipecat-ai/pipecat/pull/3371)) + +- Smart Turn now takes into account `vad_start_seconds` when buffering audio, + meaning that the start of the turn audio is not cut off. This improves + accuracy for short utterances. + + - The default value of `pre_speech_ms` is now set to 500ms for Smart Turn. +(PR [#3377](https://github.com/pipecat-ai/pipecat/pull/3377)) + +- Improved Krisp SDK management to allow `KrispVivaTurn` and `KrispVivaFilter` + to share a single SDK instance within the same process. +(PR [#3391](https://github.com/pipecat-ai/pipecat/pull/3391)) + +- Updated default model for `GroqTTSService` to `canopylabs/orpheus-v1-english` + and voice ID to `autumn`. +(PR [#3399](https://github.com/pipecat-ai/pipecat/pull/3399)) + +- Enhanced `FastAPIWebsocketTransport` with optional protocol-level audio + packetization via the `fixed_audio_packet_size` parameter to support media + endpoints requiring strict framing and real-time pacing. +(PR [#3410](https://github.com/pipecat-ai/pipecat/pull/3410)) + +- `DeepgramTTSService` and `RimeTTSService` now set `append_trailing_space` to + `True` to prevent punctuation (e.g., “dot”) from being pronounced. +(PR [#3424](https://github.com/pipecat-ai/pipecat/pull/3424)) + +- Updated `GeminiLiveLLMService` to push `LLMThoughtStartFrame`, + `LLMThoughtTextFrame`, and `LLMThoughtEndFrame` when the model returns + thought content. +(PR [#3431](https://github.com/pipecat-ai/pipecat/pull/3431)) + +### Deprecated + +- `pipecat.audio.interruptions.MinWordsInterruptionStrategy` is deprecated. Use + `pipecat.turns.user_start.MinWordsUserTurnStartStrategy` with + `LLMUserAggregator`'s new `user_turn_strategies` parameter instead. +(PR [#3045](https://github.com/pipecat-ai/pipecat/pull/3045)) + +- `FrameProcessor.interruption_strategies` is deprecated, use + `LLMUserAggregator`'s new `user_turn_strategies` parameter instead. +(PR [#3045](https://github.com/pipecat-ai/pipecat/pull/3045)) + +- The `LLMUserAggregatorParams` and `LLMAssistantAggregatorParams` classes in + `pipecat.processors.aggregators.llm_response` are now deprecated. Use the new + universal `LLMContext` and `LLMContextAggregatorPair` instead. +(PR [#3045](https://github.com/pipecat-ai/pipecat/pull/3045)) + +- Deprecated the `emulated` field in the `UserStartedSpeakingFrame` and + `UserStoppedSpeakingFrame` frames. +(PR [#3045](https://github.com/pipecat-ai/pipecat/pull/3045)) + +- `EmulateUserStartedSpeakingFrame` and `EmulateUserStoppedSpeakingFrame` + frames are deprecated. +(PR [#3045](https://github.com/pipecat-ai/pipecat/pull/3045)) + +- ⚠️ `TransportParams.turn_analyzer` is deprecated and might result in + unexpected behavior, use `LLMUserAggregator`'s new `user_turn_strategies` + parameter instead. +(PR [#3045](https://github.com/pipecat-ai/pipecat/pull/3045)) + +- For `SpeechmaticsSTTService`, the `end_of_utterance_mode` parameter is + deprecated. + Use the new `turn_detection_mode` parameter instead, with + `TurnDetectionMode.EXTERNAL`, + `TurnDetectionMode.ADAPTIVE`, or `TurnDetectionMode.SMART_TURN`. The + `enable_vad` + parameter is also deprecated and is inferred from the + `turn_detection_mode`. +(PR [#3225](https://github.com/pipecat-ai/pipecat/pull/3225)) + +- `OpenAILLMContext` and its associated things (context aggregators, etc.) are + now deprecated in favor of the universal `LLMContext` and its associated + things. + + From the developer's point of view, switching to using `LLMContext` + machinery will usually be a matter of going from this: + + ```python + context = OpenAILLMContext(messages, tools) + context_aggregator = llm.create_context_aggregator(context) + ``` + + To this: + + ``` + context = LLMContext(messages, tools) + context_aggregator = LLMContextAggregatorPair(context) + ``` +(PR [#3263](https://github.com/pipecat-ai/pipecat/pull/3263)) + +- `STTMuteFilter` is deprecated and will be removed in a future version. Use + `LLMUserAggregator`'s new `user_mute_strategies` instead. +(PR [#3292](https://github.com/pipecat-ai/pipecat/pull/3292)) + +- `FrameProcessor.interruptions_allowed` is now deprecated, use + `LLMUserAggregator`'s new parameter `user_mute_strategies` instead. +(PR [#3297](https://github.com/pipecat-ai/pipecat/pull/3297)) + +- `PipelineParams.allow_interruptions` is now deprecated, use + `LLMUserAggregator`'s new parameter `user_turn_strategies` instead. For + example, to disable interruptions but still get user turns you can do: + + ```python + context_aggregator = LLMContextAggregatorPair( + context, + user_params=LLMUserAggregatorParams( + user_turn_strategies=UserTurnStrategies( +start=[TranscriptionUserTurnStartStrategy(enable_interruptions=False)], + ), + ), + ) + ``` +(PR [#3297](https://github.com/pipecat-ai/pipecat/pull/3297)) + +- `TranscriptProcessor` and related data classes and frames + (`TranscriptionMessage`, `ThoughtTranscriptionMessage`, + `TranscriptionUpdateFrame`) are deprecated. Use `LLMUserAggregator`'s and + `LLMAssistantAggregator`'s new events (`on_user_turn_stopped` and + `on_assistant_turn_stopped`) instead. +(PR [#3385](https://github.com/pipecat-ai/pipecat/pull/3385)) + +- Deprecated support for the `vad_events` `LiveOptions` in + `DeepgramSTTService`. Instead, use a local Silero VAD for VAD events. + Additionally, deprecated `should_interrupt` which will be removed along with + `vad_events` support in a future release. +(PR [#3386](https://github.com/pipecat-ai/pipecat/pull/3386)) + +- Loading external observers from files is deprecated, use the new pipeline + task setup files and `PIPECAT_SETUP_FILES` environment variable instead. +(PR [#3397](https://github.com/pipecat-ai/pipecat/pull/3397)) + +### Fixed + +- Improved error handling in `ElevenLabsRealtimeSTTService` + - Fixed an issue in `ElevenLabsRealtimeSTTService` causing an infinite loop + that blocks the process if the websocket disconnects due to an error +(PR [#3233](https://github.com/pipecat-ai/pipecat/pull/3233)) + +- Fixed a bug in `STTMuteFilter` where the user was not always muted during + function calls, especially when there were multiple simultaneous calls. +(PR [#3292](https://github.com/pipecat-ai/pipecat/pull/3292)) + +- Fixed a `RNNoiseFilter` issue that would cause a "[Errno 12] Cannot allocate + memory" error when processing silence audio frames. +(PR [#3322](https://github.com/pipecat-ai/pipecat/pull/3322)) + +- Updated `SpeechmaticsSTTService` for version `0.0.99+`: + - Fixed `SpeechmaticsSTTService` to listen for + `VADUserStoppedSpeakingFrame` in order to finalize transcription. + - Default to `TurnDetectionMode.FIXED` for Pipecat-controlled end of turn + detection. + - Only emit VAD + interruption frames if VAD is enabled within the plugin + (modes other than `TurnDetectionMode.FIXED` or `TurnDetectionMode.EXTERNAL`). +(PR [#3328](https://github.com/pipecat-ai/pipecat/pull/3328)) + +- Fixed an issue with function calling where a handler failing to invoke its + result callback could leave the context stuck in IN_PROGRESS, causing LLM + inference for subsequent function call results to block while waiting on the + unresolved call. +(PR [#3343](https://github.com/pipecat-ai/pipecat/pull/3343)) + +- Fixed an issue with DeepgramTTSService where the model would output "Dot" + instead of a period in some circumstances. +(PR [#3345](https://github.com/pipecat-ai/pipecat/pull/3345)) + +- Fixed an issue in `traced_stt` where `model_name` in OpenTelemetry appears as + `unknown`. +(PR [#3351](https://github.com/pipecat-ai/pipecat/pull/3351)) + +- Fixed an issue in GeminiLiveLLMService where TranscriptionFrames were + occasionally not pushed. +(PR [#3356](https://github.com/pipecat-ai/pipecat/pull/3356)) + +- Fixed potential memory leaks and initialization issues in `KrispVivaFilter` + by improving SDK lifecycle management. +(PR [#3391](https://github.com/pipecat-ai/pipecat/pull/3391)) + +- Fixed timing issue in `BaseOutputTransport` where the bot speaking flag was + set after awaiting, allowing the event loop to re-enter the method before the + guard was set. +(PR [#3400](https://github.com/pipecat-ai/pipecat/pull/3400)) + +- Fixed an issue in `traced_llm` where `model_name` in OpenTelemetry appears as + `unknown`. +(PR [#3422](https://github.com/pipecat-ai/pipecat/pull/3422)) + +- Fixed an issue in `traced_tts`, `traced_gemini_live`, and + `traced_openai_realtime` where `model_name` in OpenTelemetry appears as + `unknown`. +(PR [#3428](https://github.com/pipecat-ai/pipecat/pull/3428)) + +- Fixed `request_image_frame` (for backwards compatibility) and restored + function-call–related fields in `UserImageRequestFrame` and + `UserImageRawFrame`, preventing a case where adding a non-LLM message to the + context could trigger duplicate LLM inferences (on image arrival and on + function-call result), potentially causing an infinite inference loop. +(PR [#3430](https://github.com/pipecat-ai/pipecat/pull/3430)) + +- Fixed `LLMContext.create_audio_message()` by correcting an internal helper + that was incorrectly declared async while being run in `asyncio.to_thread()`. +(PR [#3435](https://github.com/pipecat-ai/pipecat/pull/3435)) + +### Other + +- Added `52-live-transcription.py` foundational example demonstrating live + transcription and translation from English to Spanish. In this example, the + bot is not interruptible: as the user continues speaking, English + transcriptions are queued, and the bot continuously translates and speaks + each queued sentence in Spanish without being interrupted by new user speech. +(PR [#3316](https://github.com/pipecat-ai/pipecat/pull/3316)) + +- Added a new foundational example `53-concurrent-llm-evaluation.py` that shows + how to use `UserTurnProcessor`. +(PR [#3372](https://github.com/pipecat-ai/pipecat/pull/3372)) + +- Added a new foundational example `28-user-assistant-turns.py` that shows how + to use the new `LLMUserAggregator` and `LLMAssistantAggregator` events to + gather a conversation transcript. +(PR [#3385](https://github.com/pipecat-ai/pipecat/pull/3385)) + ## [0.0.98] - 2025-12-17 ### Added diff --git a/changelog/3045.added.md b/changelog/3045.added.md deleted file mode 100644 index 0dda476c7..000000000 --- a/changelog/3045.added.md +++ /dev/null @@ -1,42 +0,0 @@ -- Introducing user turn strategies. User turn strategies indicate when the user turn starts or stops. In conversational agents, these are often referred to as start/stop speaking or turn-taking plans or policies. - - User turn start strategies indicate when the user starts speaking (e.g. using VAD events or when a user says one or more words). - - User turn stop strategies indicate when the user stops speaking (e.g. using an end-of-turn detection model or by observing incoming transcriptions). - - A list of strategies can be specified for both strategies; strategies are evaluated in order until one evaluates to true. - - Available user turn start strategies: - - VADUserTurnStartStrategy - - TranscriptionUserTurnStartStrategy - - MinWordsUserTurnStartStrategy - - ExternalUserTurnStartStrategy - - Available user turn stop strategies: - - TranscriptionUserTurnStopStrategy - - TurnAnalyzerUserTurnStopStrategy - - ExternalUserTurnStopStrategy - - The default strategies are: - - - start: [VADUserTurnStartStrategy, TranscriptionUserTurnStartStrategy] - - stop: [TranscriptionUserTurnStopStrategy] - - Turn strategies are configured when setting up `LLMContextAggregatorPair`. For example: - - ```python - context_aggregator = LLMContextAggregatorPair( - context, - user_params=LLMUserAggregatorParams( - user_turn_strategies=UserTurnStrategies( - stop=[ - TurnAnalyzerUserTurnStopStrategy( - turn_analyzer=LocalSmartTurnAnalyzerV3(params=SmartTurnParams()) - ) - ], - ) - ), - ) - ``` - - In order to use the user turn strategies you must update to the new universal `LLMContext` and `LLMContextAggregatorPair`. diff --git a/changelog/3045.deprecated.2.md b/changelog/3045.deprecated.2.md deleted file mode 100644 index 7f03ff54a..000000000 --- a/changelog/3045.deprecated.2.md +++ /dev/null @@ -1 +0,0 @@ -- ⚠️ `TransportParams.turn_analyzer` is deprecated and might result in unexpected behavior, use `LLMUserAggregator`'s new `user_turn_strategies` parameter instead. diff --git a/changelog/3045.deprecated.3.md b/changelog/3045.deprecated.3.md deleted file mode 100644 index 594950603..000000000 --- a/changelog/3045.deprecated.3.md +++ /dev/null @@ -1 +0,0 @@ -- `FrameProcessor.interruption_strategies` is deprecated, use `LLMUserAggregator`'s new `user_turn_strategies` parameter instead. diff --git a/changelog/3045.deprecated.4.md b/changelog/3045.deprecated.4.md deleted file mode 100644 index fda634ce8..000000000 --- a/changelog/3045.deprecated.4.md +++ /dev/null @@ -1 +0,0 @@ -- `EmulateUserStartedSpeakingFrame` and `EmulateUserStoppedSpeakingFrame` frames are deprecated. diff --git a/changelog/3045.deprecated.5.md b/changelog/3045.deprecated.5.md deleted file mode 100644 index 57781a489..000000000 --- a/changelog/3045.deprecated.5.md +++ /dev/null @@ -1 +0,0 @@ -- Deprecated the `emulated` field in the `UserStartedSpeakingFrame` and `UserStoppedSpeakingFrame` frames. diff --git a/changelog/3045.deprecated.6.md b/changelog/3045.deprecated.6.md deleted file mode 100644 index 3bf804220..000000000 --- a/changelog/3045.deprecated.6.md +++ /dev/null @@ -1 +0,0 @@ -- The `LLMUserAggregatorParams` and `LLMAssistantAggregatorParams` classes in `pipecat.processors.aggregators.llm_response` are now deprecated. Use the new universal `LLMContext` and `LLMContextAggregatorPair` instead. diff --git a/changelog/3045.deprecated.md b/changelog/3045.deprecated.md deleted file mode 100644 index c58f1a4e2..000000000 --- a/changelog/3045.deprecated.md +++ /dev/null @@ -1 +0,0 @@ -- `pipecat.audio.interruptions.MinWordsInterruptionStrategy` is deprecated. Use `pipecat.turns.user_start.MinWordsUserTurnStartStrategy` with `LLMUserAggregator`'s new `user_turn_strategies` parameter instead. diff --git a/changelog/3205.added.md b/changelog/3205.added.md deleted file mode 100644 index dc72a1cf0..000000000 --- a/changelog/3205.added.md +++ /dev/null @@ -1 +0,0 @@ -- Added `RNNoiseFilter` for real-time noise suppression using RNNoise neural network via pyrnnoise library. diff --git a/changelog/3216.changed.md b/changelog/3216.changed.md deleted file mode 100644 index b8d480fe2..000000000 --- a/changelog/3216.changed.md +++ /dev/null @@ -1,7 +0,0 @@ -- Updated `ElevenLabsRealtimeSTTService` to accept the `include_language_detection` parameter to detect language. - ```python - stt = ElevenLabsRealtimeSTTService( - api_key=os.getenv("ELEVENLABS_API_KEY"), - include_language_detection=True - ) - ``` diff --git a/changelog/3225.changed.md b/changelog/3225.changed.md deleted file mode 100644 index c5063f58e..000000000 --- a/changelog/3225.changed.md +++ /dev/null @@ -1,15 +0,0 @@ -- Updated `SpeechmaticsSTTService` to use new Python Voice SDK with improved VAD, - Smart Turn capabilities, and brings dramatic improvements to latency without - any impact on accuracy. Use the `turn_detection_mode` parameter to control the - endpointing of speech, with `TurnDetectionMode.EXTERNAL` (default), - `TurnDetectionMode.ADAPTIVE`, or `TurnDetectionMode.SMART_TURN`. - ```python - stt = SpeechmaticsSTTService( - api_key=os.getenv("SPEECHMATICS_API_KEY"), - params=SpeechmaticsSTTService.InputParams( - language=Language.EN, - turn_detection_mode=SpeechmaticsSTTService.TurnDetectionMode.ADAPTIVE, - speaker_active_format="<{speaker_id}>{text}", - ), - ) - ``` diff --git a/changelog/3225.deprecated.md b/changelog/3225.deprecated.md deleted file mode 100644 index 162c82a82..000000000 --- a/changelog/3225.deprecated.md +++ /dev/null @@ -1,4 +0,0 @@ -- For `SpeechmaticsSTTService`, the `end_of_utterance_mode` parameter is deprecated. - Use the new `turn_detection_mode` parameter instead, with `TurnDetectionMode.EXTERNAL`, - `TurnDetectionMode.ADAPTIVE`, or `TurnDetectionMode.SMART_TURN`. The `enable_vad` - parameter is also deprecated and is inferred from the `turn_detection_mode`. diff --git a/changelog/3233.fixed.md b/changelog/3233.fixed.md deleted file mode 100644 index 3f17fd765..000000000 --- a/changelog/3233.fixed.md +++ /dev/null @@ -1,2 +0,0 @@ -- Improved error handling in `ElevenLabsRealtimeSTTService` -- Fixed an issue in `ElevenLabsRealtimeSTTService` causing an infinite loop that blocks the process if the websocket disconnects due to an error \ No newline at end of file diff --git a/changelog/3257.changed.2.md b/changelog/3257.changed.2.md deleted file mode 100644 index 333c69746..000000000 --- a/changelog/3257.changed.2.md +++ /dev/null @@ -1 +0,0 @@ -- `TranscriptionFrame` and `InterimTranscriptionFrame` produced by `DailyTransport` now include the transport source (i.e., the originating audio track). diff --git a/changelog/3257.changed.md b/changelog/3257.changed.md deleted file mode 100644 index fda547eef..000000000 --- a/changelog/3257.changed.md +++ /dev/null @@ -1 +0,0 @@ -- `daily-python` updated to 0.23.0. diff --git a/changelog/3263.deprecated.md b/changelog/3263.deprecated.md deleted file mode 100644 index 11f659c2e..000000000 --- a/changelog/3263.deprecated.md +++ /dev/null @@ -1,15 +0,0 @@ -- `OpenAILLMContext` and its associated things (context aggregators, etc.) are now deprecated in favor of the universal `LLMContext` and its associated things. - - From the developer's point of view, switching to using `LLMContext` machinery will usually be a matter of going from this: - - ```python - context = OpenAILLMContext(messages, tools) - context_aggregator = llm.create_context_aggregator(context) - ``` - - To this: - - ``` - context = LLMContext(messages, tools) - context_aggregator = LLMContextAggregatorPair(context) - ``` diff --git a/changelog/3267.added.md b/changelog/3267.added.md deleted file mode 100644 index bdeccd6ed..000000000 --- a/changelog/3267.added.md +++ /dev/null @@ -1,8 +0,0 @@ -- Added `GrokRealtimeLLMService` for xAI's Grok Voice Agent API with real-time voice conversations: - - - Support for real-time audio streaming with WebSocket connection - - Built-in server-side VAD (Voice Activity Detection) - - Multiple voice options: Ara, Rex, Sal, Eve, Leo - - Built-in tools support: web_search, x_search, file_search - - Custom function calling with standard Pipecat tools schema - - Configurable audio formats (PCM at 8kHz-48kHz) diff --git a/changelog/3268.added.md b/changelog/3268.added.md deleted file mode 100644 index 6bbcd038c..000000000 --- a/changelog/3268.added.md +++ /dev/null @@ -1 +0,0 @@ -- Added an approximation of TTFB for Ultravox. diff --git a/changelog/3288.changed.md b/changelog/3288.changed.md deleted file mode 100644 index 52a9694cd..000000000 --- a/changelog/3288.changed.md +++ /dev/null @@ -1,5 +0,0 @@ -- Updates to Inworld TTS services: - - - Improved `InworldTTSService`'s websocket implementation to better flush and - close context to better handle long inputs. - - Improved docstrings for `InworldTTSService` and `InworldHttpTTSService`. diff --git a/changelog/3289.added.md b/changelog/3289.added.md deleted file mode 100644 index fb19607eb..000000000 --- a/changelog/3289.added.md +++ /dev/null @@ -1 +0,0 @@ -- Added a new `AudioContextTTSService` to the TTS service base classes. The `AudioContextWordTTSService` now inherits from `AudioContextTTSService` and `WebsocketWordTTSService`. diff --git a/changelog/3291.added.md b/changelog/3291.added.md deleted file mode 100644 index dacfd4f12..000000000 --- a/changelog/3291.added.md +++ /dev/null @@ -1,4 +0,0 @@ -- `LLMUserAggregator` now exposes the following events: - - `on_user_turn_started`: triggered when a user turn starts - - `on_user_turn_stopped`: triggered when a user turn ends - - `on_user_turn_stop_timeout`: triggered when a user turn does not stop and times out diff --git a/changelog/3292.added.md b/changelog/3292.added.md deleted file mode 100644 index 936d927d8..000000000 --- a/changelog/3292.added.md +++ /dev/null @@ -1,29 +0,0 @@ -- Introducing user mute strategies. User mute strategies indicate when user input should be muted based on the current system state. - - In conversational agents, user mute strategies are used to prevent user input from interrupting bot speech, tool execution, or other critical system operations. - - A list of strategies can be specified; all strategies are evaluated for every frame so that each strategy can maintain its internal state. A user frame is muted if any of the configured strategies indicates it should be muted. - - Available user mute strategies: - - * `FirstSpeechUserMuteStrategy` - * `MuteUntilFirstBotCompleteUserMuteStrategy` - * `AlwaysUserMuteStrategy` - * `FunctionCallUserMuteStrategy` - - User mute strategies replace the legacy `STTMuteFilter` and provide a more flexible and composable approach to muting user input. - - User mute strategies are configured when setting up the `LLMContextAggregatorPair`. For example: - - ```python - context_aggregator = LLMContextAggregatorPair( - context, - user_params=LLMUserAggregatorParams( - user_mute_strategies=[ - FirstSpeechUserMuteStrategy(), - ] - ), - ) - ``` - - In order to use user mute strategies you should update to the new universal `LLMContext` and `LLMContextAggregatorPair`. diff --git a/changelog/3292.deprecated.md b/changelog/3292.deprecated.md deleted file mode 100644 index 3aceea5f1..000000000 --- a/changelog/3292.deprecated.md +++ /dev/null @@ -1 +0,0 @@ -- `STTMuteFilter` is deprecated and will be removed in a future version. Use `LLMUserAggregator`'s new `user_mute_strategies` instead. diff --git a/changelog/3292.fixed.md b/changelog/3292.fixed.md deleted file mode 100644 index 4d3df66b0..000000000 --- a/changelog/3292.fixed.md +++ /dev/null @@ -1 +0,0 @@ -- Fixed a bug in `STTMuteFilter` where the user was not always muted during function calls, especially when there were multiple simultaneous calls. diff --git a/changelog/3297.deprecated.2.md b/changelog/3297.deprecated.2.md deleted file mode 100644 index 49d5723af..000000000 --- a/changelog/3297.deprecated.2.md +++ /dev/null @@ -1 +0,0 @@ -- `FrameProcessor.interruptions_allowed` is now deprecated, use `LLMUserAggregator`'s new parameter `user_mute_strategies` instead. diff --git a/changelog/3297.deprecated.md b/changelog/3297.deprecated.md deleted file mode 100644 index d29a8a020..000000000 --- a/changelog/3297.deprecated.md +++ /dev/null @@ -1,12 +0,0 @@ -- `PipelineParams.allow_interruptions` is now deprecated, use `LLMUserAggregator`'s new parameter `user_turn_strategies` instead. For example, to disable interruptions but still get user turns you can do: - - ```python - context_aggregator = LLMContextAggregatorPair( - context, - user_params=LLMUserAggregatorParams( - user_turn_strategies=UserTurnStrategies( - start=[TranscriptionUserTurnStartStrategy(enable_interruptions=False)], - ), - ), - ) - ``` diff --git a/changelog/3300.added.md b/changelog/3300.added.md deleted file mode 100644 index 6e0066559..000000000 --- a/changelog/3300.added.md +++ /dev/null @@ -1 +0,0 @@ -- Added `use_ssl` parameter to `NvidiaSTTService`, `NvidiaSegmentedSTTService` and `NvidiaTTSService`. \ No newline at end of file diff --git a/changelog/3314.changed.md b/changelog/3314.changed.md deleted file mode 100644 index 3b9b074a8..000000000 --- a/changelog/3314.changed.md +++ /dev/null @@ -1 +0,0 @@ -- Updated `DeepgramSTTService` to push user started/stopped speaking and interruption frames when `vad_enabled` is set to true. This centralizes the frames into the service, removing the need to have your application code handle Deepgram's events and push these frames. diff --git a/changelog/3316.added.md b/changelog/3316.added.md deleted file mode 100644 index d4c76c46a..000000000 --- a/changelog/3316.added.md +++ /dev/null @@ -1 +0,0 @@ -- Added `enable_interruptions` constructor argument to all user turn strategies. This tells the `LLMUserAggregator` to push or not push an `InterruptionFrame`. diff --git a/changelog/3316.other.md b/changelog/3316.other.md deleted file mode 100644 index 23c1be025..000000000 --- a/changelog/3316.other.md +++ /dev/null @@ -1 +0,0 @@ -- Added `52-live-transcription.py` foundational example demonstrating live transcription and translation from English to Spanish. In this example, the bot is not interruptible: as the user continues speaking, English transcriptions are queued, and the bot continuously translates and speaks each queued sentence in Spanish without being interrupted by new user speech. diff --git a/changelog/3322.fixed.md b/changelog/3322.fixed.md deleted file mode 100644 index 3ad2b75bc..000000000 --- a/changelog/3322.fixed.md +++ /dev/null @@ -1 +0,0 @@ -- Fixed a `RNNoiseFilter` issue that would cause a "[Errno 12] Cannot allocate memory" error when processing silence audio frames. diff --git a/changelog/3328.added.md b/changelog/3328.added.md deleted file mode 100644 index db793e828..000000000 --- a/changelog/3328.added.md +++ /dev/null @@ -1 +0,0 @@ -- Added `split_sentences` parameter to `SpeechmaticsSTTService` to control sentence splitting behavior for finals on sentence boundaries. diff --git a/changelog/3328.fixed.md b/changelog/3328.fixed.md deleted file mode 100644 index 6f09c2386..000000000 --- a/changelog/3328.fixed.md +++ /dev/null @@ -1,4 +0,0 @@ -- Updated `SpeechmaticsSTTService` for version `0.0.99+`: - - Fixed `SpeechmaticsSTTService` to listen for `VADUserStoppedSpeakingFrame` in order to finalize transcription. - - Default to `TurnDetectionMode.FIXED` for Pipecat-controlled end of turn detection. - - Only emit VAD + interruption frames if VAD is enabled within the plugin (modes other than `TurnDetectionMode.FIXED` or `TurnDetectionMode.EXTERNAL`). diff --git a/changelog/3329.changed.md b/changelog/3329.changed.md deleted file mode 100644 index 8271decf2..000000000 --- a/changelog/3329.changed.md +++ /dev/null @@ -1 +0,0 @@ -- Added encoding validation to `DeepgramTTSService` to prevent unsupported encodings from reaching the API. The service now raises `ValueError` at initialization with a clear error message. diff --git a/changelog/3334.added.md b/changelog/3334.added.md deleted file mode 100644 index 993bca20e..000000000 --- a/changelog/3334.added.md +++ /dev/null @@ -1,2 +0,0 @@ -- Added word-level timestamp support to `AzureTTSService` for accurate text-to-audio synchronization. - \ No newline at end of file diff --git a/changelog/3336.changed.md b/changelog/3336.changed.md deleted file mode 100644 index 2f6a28b30..000000000 --- a/changelog/3336.changed.md +++ /dev/null @@ -1 +0,0 @@ -- Updated `read_audio_frame` & `read_video_frame` methods in `SmallWebRTCClient` to check if the track is enabled before logging a warning. \ No newline at end of file diff --git a/changelog/3343.fixed.md b/changelog/3343.fixed.md deleted file mode 100644 index ee037b304..000000000 --- a/changelog/3343.fixed.md +++ /dev/null @@ -1 +0,0 @@ -- Fixed an issue with function calling where a handler failing to invoke its result callback could leave the context stuck in IN_PROGRESS, causing LLM inference for subsequent function call results to block while waiting on the unresolved call. diff --git a/changelog/3345.fixed.md b/changelog/3345.fixed.md deleted file mode 100644 index 61c0a575e..000000000 --- a/changelog/3345.fixed.md +++ /dev/null @@ -1 +0,0 @@ -- Fixed an issue with DeepgramTTSService where the model would output "Dot" instead of a period in some circumstances. diff --git a/changelog/3346.added.md b/changelog/3346.added.md deleted file mode 100644 index b72d23b55..000000000 --- a/changelog/3346.added.md +++ /dev/null @@ -1 +0,0 @@ -- Added `pronunciation_dict_id` parameter to `CartesiaTTSService.InputParams` and `CartesiaHttpTTSService.InputParams` to support Cartesia's pronunciation dictionary feature for custom pronunciations. diff --git a/changelog/3351.fixed.md b/changelog/3351.fixed.md deleted file mode 100644 index 2792839cb..000000000 --- a/changelog/3351.fixed.md +++ /dev/null @@ -1 +0,0 @@ -- Fixed an issue in `traced_stt` where `model_name` in OpenTelemetry appears as `unknown`. diff --git a/changelog/3356.fixed.md b/changelog/3356.fixed.md deleted file mode 100644 index 0532e742a..000000000 --- a/changelog/3356.fixed.md +++ /dev/null @@ -1 +0,0 @@ -- Fixed an issue in GeminiLiveLLMService where TranscriptionFrames were occasionally not pushed. diff --git a/changelog/3357.added.md b/changelog/3357.added.md deleted file mode 100644 index 08a739573..000000000 --- a/changelog/3357.added.md +++ /dev/null @@ -1 +0,0 @@ -- Added support for using the HeyGen LiveAvatar API with the `HeyGenTransport` (see https://www.liveavatar.com/). diff --git a/changelog/3360.added.md b/changelog/3360.added.md deleted file mode 100644 index c9f22e823..000000000 --- a/changelog/3360.added.md +++ /dev/null @@ -1,8 +0,0 @@ -- Added image support to `OpenAIRealtimeLLMService` via `InputImageRawFrame`: - - New `start_video_paused` parameter to control initial video input state - - New `video_frame_detail` parameter to set image processing quality ("auto", - "low", or "high"). This corresponds to OpenAI Realtime's `image_detail` - parameter. - - `set_video_input_paused()` method to pause/resume video input at runtime - - `set_video_frame_detail()` method to adjust video frame quality dynamically - - Automatic rate limiting (1 frame per second) to prevent API overload diff --git a/changelog/3366.changed.md b/changelog/3366.changed.md deleted file mode 100644 index d9a0a4d89..000000000 --- a/changelog/3366.changed.md +++ /dev/null @@ -1 +0,0 @@ -- Updated `CartesiaTTSService` to support setting `language=None`, resulting in Cartesia auto-detecting the language of the conversation. diff --git a/changelog/3367.changed.md b/changelog/3367.changed.md deleted file mode 100644 index 036ff1c62..000000000 --- a/changelog/3367.changed.md +++ /dev/null @@ -1,3 +0,0 @@ -- The bundled Smart Turn weights are now updated to v3.2, which has better - handling of short utterances, and is more robust against background - noise. diff --git a/changelog/3371.changed.md b/changelog/3371.changed.md deleted file mode 100644 index eb96711fb..000000000 --- a/changelog/3371.changed.md +++ /dev/null @@ -1 +0,0 @@ -- Updated `SpeechmaticsSTTService` dependency to `speechmatics-voice[smart]>=0.2.6` diff --git a/changelog/3372.added.2.md b/changelog/3372.added.2.md deleted file mode 100644 index 6b1bf1ed4..000000000 --- a/changelog/3372.added.2.md +++ /dev/null @@ -1 +0,0 @@ -- Added `UserTurnProcessor`, a frame processor built on `UserTurnController` that pushes `UserStartedSpeakingFrame` and `UserStoppedSpeakingFrame` frames and interruptions based on the controller's user turn strategies. diff --git a/changelog/3372.added.md b/changelog/3372.added.md deleted file mode 100644 index 3468f7ac1..000000000 --- a/changelog/3372.added.md +++ /dev/null @@ -1 +0,0 @@ -- Added `UserTurnController` to manage user turns. It emits `on_user_turn_started`, `on_user_turn_stopped`, and `on_user_turn_stop_timeout` events, and can be integrated into processors to detect and handle user turns. `LLMUserAggregator` and `UserTurnProcessor` are implemented using this controller. diff --git a/changelog/3372.other.md b/changelog/3372.other.md deleted file mode 100644 index d0e96c20b..000000000 --- a/changelog/3372.other.md +++ /dev/null @@ -1 +0,0 @@ -- Added a new foundational example `53-concurrent-llm-evaluation.py` that shows how to use `UserTurnProcessor`. diff --git a/changelog/3374.added.md b/changelog/3374.added.md deleted file mode 100644 index eb04650ef..000000000 --- a/changelog/3374.added.md +++ /dev/null @@ -1 +0,0 @@ -- Added `should_interrupt` property to `DeepgramFluxSTTService`, `DeepgramSTTService`, and `SpeechmaticsSTTService` to configure whether the bot should be interrupted when the external service detects user speech. \ No newline at end of file diff --git a/changelog/3377.changed.md b/changelog/3377.changed.md deleted file mode 100644 index 8a006bd42..000000000 --- a/changelog/3377.changed.md +++ /dev/null @@ -1,5 +0,0 @@ -- Smart Turn now takes into account `vad_start_seconds` when buffering audio, - meaning that the start of the turn audio is not cut off. This improves - accuracy for short utterances. - -- The default value of `pre_speech_ms` is now set to 500ms for Smart Turn. diff --git a/changelog/3385.added.md b/changelog/3385.added.md deleted file mode 100644 index b79a1d584..000000000 --- a/changelog/3385.added.md +++ /dev/null @@ -1,4 +0,0 @@ -- `LLMAssistantAggregator` now exposes the following events: - - `on_assistant_turn_started`: triggered when the assistant turn starts - - `on_assistant_turn_stopped`: triggered when the assistant turn ends - - `on_assistant_thought`: triggered when there's an assistant thought available diff --git a/changelog/3385.deprecated.md b/changelog/3385.deprecated.md deleted file mode 100644 index e810af08a..000000000 --- a/changelog/3385.deprecated.md +++ /dev/null @@ -1 +0,0 @@ -- `TranscriptProcessor` and related data classes and frames (`TranscriptionMessage`, `ThoughtTranscriptionMessage`, `TranscriptionUpdateFrame`) are deprecated. Use `LLMUserAggregator`'s and `LLMAssistantAggregator`'s new events (`on_user_turn_stopped` and `on_assistant_turn_stopped`) instead. diff --git a/changelog/3385.other.md b/changelog/3385.other.md deleted file mode 100644 index 69f612908..000000000 --- a/changelog/3385.other.md +++ /dev/null @@ -1 +0,0 @@ -- Added a new foundational example `28-user-assistant-turns.py` that shows how to use the new `LLMUserAggregator` and `LLMAssistantAggregator` events to gather a conversation transcript. diff --git a/changelog/3386.deprecated.md b/changelog/3386.deprecated.md deleted file mode 100644 index 3c9c141ce..000000000 --- a/changelog/3386.deprecated.md +++ /dev/null @@ -1 +0,0 @@ -- Deprecated support for the `vad_events` `LiveOptions` in `DeepgramSTTService`. Instead, use a local Silero VAD for VAD events. Additionally, deprecated `should_interrupt` which will be removed along with `vad_events` support in a future release. diff --git a/changelog/3391.added.md b/changelog/3391.added.md deleted file mode 100644 index 7dfaa9a2f..000000000 --- a/changelog/3391.added.md +++ /dev/null @@ -1 +0,0 @@ -- Added `KrispVivaTurn` analyzer for end of turn detection using the Krisp VIVA SDK (requires `krisp_audio`). diff --git a/changelog/3391.changed.md b/changelog/3391.changed.md deleted file mode 100644 index fb12beac0..000000000 --- a/changelog/3391.changed.md +++ /dev/null @@ -1 +0,0 @@ -- Improved Krisp SDK management to allow `KrispVivaTurn` and `KrispVivaFilter` to share a single SDK instance within the same process. diff --git a/changelog/3391.fixed.md b/changelog/3391.fixed.md deleted file mode 100644 index 95c14ebd5..000000000 --- a/changelog/3391.fixed.md +++ /dev/null @@ -1 +0,0 @@ -- Fixed potential memory leaks and initialization issues in `KrispVivaFilter` by improving SDK lifecycle management. \ No newline at end of file diff --git a/changelog/3397.added.md b/changelog/3397.added.md deleted file mode 100644 index 2f819cc43..000000000 --- a/changelog/3397.added.md +++ /dev/null @@ -1,6 +0,0 @@ -- Added support for setting up a pipeline task from external files. You can now register custom pipeline task setup files by setting the `PIPECAT_SETUP_FILES` environment variable. This variable should contain a colon-separated list of Python files (e.g. `export PIPECAT_SETUP_FILES="setup1.py:setup.py:..."`). Each file must define a function with the following signature: - - ```python - async def setup_pipeline_task(task: PipelineTask): - ... - ``` diff --git a/changelog/3397.deprecated.md b/changelog/3397.deprecated.md deleted file mode 100644 index b9028c5be..000000000 --- a/changelog/3397.deprecated.md +++ /dev/null @@ -1 +0,0 @@ -- Loading external observers from files is deprecated, use the new pipeline task setup files and `PIPECAT_SETUP_FILES` environment variable instead. diff --git a/changelog/3399.changed.md b/changelog/3399.changed.md deleted file mode 100644 index fecf505bc..000000000 --- a/changelog/3399.changed.md +++ /dev/null @@ -1 +0,0 @@ -- Updated default model for `GroqTTSService` to `canopylabs/orpheus-v1-english` and voice ID to `autumn`. diff --git a/changelog/3400.fixed.md b/changelog/3400.fixed.md deleted file mode 100644 index aaf881bb7..000000000 --- a/changelog/3400.fixed.md +++ /dev/null @@ -1 +0,0 @@ -- Fixed timing issue in `BaseOutputTransport` where the bot speaking flag was set after awaiting, allowing the event loop to re-enter the method before the guard was set. diff --git a/changelog/3403.added.md b/changelog/3403.added.md deleted file mode 100644 index 6b55ef97d..000000000 --- a/changelog/3403.added.md +++ /dev/null @@ -1 +0,0 @@ -- Added a keepalive task for `InworldTTSService` to keep the service connected in the event of no generations for longer periods of time. diff --git a/changelog/3404.added.2.md b/changelog/3404.added.2.md deleted file mode 100644 index 0f15c39c3..000000000 --- a/changelog/3404.added.2.md +++ /dev/null @@ -1 +0,0 @@ -- Added `enable_vad` to `Params` for use in the `GladiaSTTService`. When enabled, `GladiaSTTService` acts as the turn controller, emitting `UserStartedSpeakingFrame`, `UserStoppedSpeakingFrame`, and optionally `InterruptionFrame`. diff --git a/changelog/3404.added.md b/changelog/3404.added.md deleted file mode 100644 index 733c22ebe..000000000 --- a/changelog/3404.added.md +++ /dev/null @@ -1 +0,0 @@ -- Added `should_interrupt` property to `GladiaSTTService` to configure whether the bot should be interrupted when the external service detects user speech. diff --git a/changelog/3410.added.md b/changelog/3410.added.md deleted file mode 100644 index 094532343..000000000 --- a/changelog/3410.added.md +++ /dev/null @@ -1 +0,0 @@ -- Added `VonageFrameSerializer` for the Vonage Video API Audio Connector WebSocket protocol. diff --git a/changelog/3410.changed.md b/changelog/3410.changed.md deleted file mode 100644 index 3e54436de..000000000 --- a/changelog/3410.changed.md +++ /dev/null @@ -1 +0,0 @@ -- Enhanced `FastAPIWebsocketTransport` with optional protocol-level audio packetization via the `fixed_audio_packet_size` parameter to support media endpoints requiring strict framing and real-time pacing. diff --git a/changelog/3422.fixed.md b/changelog/3422.fixed.md deleted file mode 100644 index fa34d9262..000000000 --- a/changelog/3422.fixed.md +++ /dev/null @@ -1 +0,0 @@ -- Fixed an issue in `traced_llm` where `model_name` in OpenTelemetry appears as `unknown`. diff --git a/changelog/3424.added.md b/changelog/3424.added.md deleted file mode 100644 index 61cc8ea77..000000000 --- a/changelog/3424.added.md +++ /dev/null @@ -1 +0,0 @@ -- Added `append_trailing_space` parameter to `TTSService` to automatically append a trailing space to text before sending to TTS, helping prevent some services from vocalizing trailing punctuation. diff --git a/changelog/3424.changed.md b/changelog/3424.changed.md deleted file mode 100644 index 2e665ca2d..000000000 --- a/changelog/3424.changed.md +++ /dev/null @@ -1 +0,0 @@ -- `DeepgramTTSService` and `RimeTTSService` now set `append_trailing_space` to `True` to prevent punctuation (e.g., “dot”) from being pronounced. diff --git a/changelog/3428.fixed.md b/changelog/3428.fixed.md deleted file mode 100644 index e82ff082e..000000000 --- a/changelog/3428.fixed.md +++ /dev/null @@ -1 +0,0 @@ -- Fixed an issue in `traced_tts`, `traced_gemini_live`, and `traced_openai_realtime` where `model_name` in OpenTelemetry appears as `unknown`. diff --git a/changelog/3430.fixed.md b/changelog/3430.fixed.md deleted file mode 100644 index 6f689eb78..000000000 --- a/changelog/3430.fixed.md +++ /dev/null @@ -1 +0,0 @@ -- Fixed `request_image_frame` (for backwards compatibility) and restored function-call–related fields in `UserImageRequestFrame` and `UserImageRawFrame`, preventing a case where adding a non-LLM message to the context could trigger duplicate LLM inferences (on image arrival and on function-call result), potentially causing an infinite inference loop. diff --git a/changelog/3431.changed.md b/changelog/3431.changed.md deleted file mode 100644 index 0a9164491..000000000 --- a/changelog/3431.changed.md +++ /dev/null @@ -1 +0,0 @@ -- Updated `GeminiLiveLLMService` to push `LLMThoughtStartFrame`, `LLMThoughtTextFrame`, and `LLMThoughtEndFrame` when the model returns thought content. diff --git a/changelog/3435.fixed.md b/changelog/3435.fixed.md deleted file mode 100644 index a4482c328..000000000 --- a/changelog/3435.fixed.md +++ /dev/null @@ -1 +0,0 @@ -- Fixed `LLMContext.create_audio_message()` by correcting an internal helper that was incorrectly declared async while being run in `asyncio.to_thread()`. From 7e1b4a4e905c767076c2c18b97ce0562478665f1 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Aleix=20Conchillo=20Flaqu=C3=A9?= Date: Tue, 13 Jan 2026 16:59:46 -0800 Subject: [PATCH 0049/1060] update cosmetic changelog updates for 0.0.99 --- CHANGELOG.md | 218 ++++++++++++++++++++++++--------------------------- 1 file changed, 104 insertions(+), 114 deletions(-) diff --git a/CHANGELOG.md b/CHANGELOG.md index 290a7802c..3d583b4e1 100644 --- a/CHANGELOG.md +++ b/CHANGELOG.md @@ -15,13 +15,13 @@ and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0 turn starts or stops. In conversational agents, these are often referred to as start/stop speaking or turn-taking plans or policies. - User turn start strategies indicate when the user starts speaking (e.g. + User turn start strategies indicate when the user starts speaking (e.g. using VAD events or when a user says one or more words). - User turn stop strategies indicate when the user stops speaking (e.g. using + User turn stop strategies indicate when the user stops speaking (e.g. using an end-of-turn detection model or by observing incoming transcriptions). - A list of strategies can be specified for both strategies; strategies are + A list of strategies can be specified for both strategies; strategies are evaluated in order until one evaluates to true. Available user turn start strategies: @@ -40,7 +40,7 @@ and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0 - start: [VADUserTurnStartStrategy, TranscriptionUserTurnStartStrategy] - stop: [TranscriptionUserTurnStopStrategy] - Turn strategies are configured when setting up `LLMContextAggregatorPair`. + urn strategies are configured when setting up `LLMContextAggregatorPair`. For example: ```python @@ -58,13 +58,13 @@ turn_analyzer=LocalSmartTurnAnalyzerV3(params=SmartTurnParams()) ) ``` - In order to use the user turn strategies you must update to the new + In order to use the user turn strategies you must update to the new universal `LLMContext` and `LLMContextAggregatorPair`. -(PR [#3045](https://github.com/pipecat-ai/pipecat/pull/3045)) + (PR [#3045](https://github.com/pipecat-ai/pipecat/pull/3045)) - Added `RNNoiseFilter` for real-time noise suppression using RNNoise neural network via pyrnnoise library. -(PR [#3205](https://github.com/pipecat-ai/pipecat/pull/3205)) + (PR [#3205](https://github.com/pipecat-ai/pipecat/pull/3205)) - Added `GrokRealtimeLLMService` for xAI's Grok Voice Agent API with real-time voice conversations: @@ -75,31 +75,31 @@ turn_analyzer=LocalSmartTurnAnalyzerV3(params=SmartTurnParams()) - Built-in tools support: web_search, x_search, file_search - Custom function calling with standard Pipecat tools schema - Configurable audio formats (PCM at 8kHz-48kHz) -(PR [#3267](https://github.com/pipecat-ai/pipecat/pull/3267)) + (PR [#3267](https://github.com/pipecat-ai/pipecat/pull/3267)) - Added an approximation of TTFB for Ultravox. -(PR [#3268](https://github.com/pipecat-ai/pipecat/pull/3268)) + (PR [#3268](https://github.com/pipecat-ai/pipecat/pull/3268)) - Added a new `AudioContextTTSService` to the TTS service base classes. The `AudioContextWordTTSService` now inherits from `AudioContextTTSService` and `WebsocketWordTTSService`. -(PR [#3289](https://github.com/pipecat-ai/pipecat/pull/3289)) + (PR [#3289](https://github.com/pipecat-ai/pipecat/pull/3289)) - `LLMUserAggregator` now exposes the following events: - `on_user_turn_started`: triggered when a user turn starts - `on_user_turn_stopped`: triggered when a user turn ends - `on_user_turn_stop_timeout`: triggered when a user turn does not stop - and times out -(PR [#3291](https://github.com/pipecat-ai/pipecat/pull/3291)) + and times out + (PR [#3291](https://github.com/pipecat-ai/pipecat/pull/3291)) - Introducing user mute strategies. User mute strategies indicate when user input should be muted based on the current system state. - In conversational agents, user mute strategies are used to prevent user + In conversational agents, user mute strategies are used to prevent user input from interrupting bot speech, tool execution, or other critical system operations. - A list of strategies can be specified; all strategies are evaluated for + A list of strategies can be specified; all strategies are evaluated for every frame so that each strategy can maintain its internal state. A user frame is muted if any of the configured strategies indicates it should be muted. @@ -111,10 +111,10 @@ turn_analyzer=LocalSmartTurnAnalyzerV3(params=SmartTurnParams()) * `AlwaysUserMuteStrategy` * `FunctionCallUserMuteStrategy` - User mute strategies replace the legacy `STTMuteFilter` and provide a more + User mute strategies replace the legacy `STTMuteFilter` and provide a more flexible and composable approach to muting user input. - User mute strategies are configured when setting up the + User mute strategies are configured when setting up the `LLMContextAggregatorPair`. For example: ```python @@ -128,35 +128,35 @@ turn_analyzer=LocalSmartTurnAnalyzerV3(params=SmartTurnParams()) ) ``` - In order to use user mute strategies you should update to the new universal + In order to use user mute strategies you should update to the new universal `LLMContext` and `LLMContextAggregatorPair`. -(PR [#3292](https://github.com/pipecat-ai/pipecat/pull/3292)) + (PR [#3292](https://github.com/pipecat-ai/pipecat/pull/3292)) - Added `use_ssl` parameter to `NvidiaSTTService`, `NvidiaSegmentedSTTService` and `NvidiaTTSService`. -(PR [#3300](https://github.com/pipecat-ai/pipecat/pull/3300)) + (PR [#3300](https://github.com/pipecat-ai/pipecat/pull/3300)) - Added `enable_interruptions` constructor argument to all user turn strategies. This tells the `LLMUserAggregator` to push or not push an `InterruptionFrame`. -(PR [#3316](https://github.com/pipecat-ai/pipecat/pull/3316)) + (PR [#3316](https://github.com/pipecat-ai/pipecat/pull/3316)) - Added `split_sentences` parameter to `SpeechmaticsSTTService` to control sentence splitting behavior for finals on sentence boundaries. -(PR [#3328](https://github.com/pipecat-ai/pipecat/pull/3328)) + (PR [#3328](https://github.com/pipecat-ai/pipecat/pull/3328)) - Added word-level timestamp support to `AzureTTSService` for accurate text-to-audio synchronization. -(PR [#3334](https://github.com/pipecat-ai/pipecat/pull/3334)) + (PR [#3334](https://github.com/pipecat-ai/pipecat/pull/3334)) - Added `pronunciation_dict_id` parameter to `CartesiaTTSService.InputParams` and `CartesiaHttpTTSService.InputParams` to support Cartesia's pronunciation dictionary feature for custom pronunciations. -(PR [#3346](https://github.com/pipecat-ai/pipecat/pull/3346)) + (PR [#3346](https://github.com/pipecat-ai/pipecat/pull/3346)) - Added support for using the HeyGen LiveAvatar API with the `HeyGenTransport` (see https://www.liveavatar.com/). -(PR [#3357](https://github.com/pipecat-ai/pipecat/pull/3357)) + (PR [#3357](https://github.com/pipecat-ai/pipecat/pull/3357)) - Added image support to `OpenAIRealtimeLLMService` via `InputImageRawFrame`: - New `start_video_paused` parameter to control initial video input state @@ -166,37 +166,37 @@ turn_analyzer=LocalSmartTurnAnalyzerV3(params=SmartTurnParams()) parameter. - `set_video_input_paused()` method to pause/resume video input at runtime - `set_video_frame_detail()` method to adjust video frame quality - dynamically + dynamically - Automatic rate limiting (1 frame per second) to prevent API overload -(PR [#3360](https://github.com/pipecat-ai/pipecat/pull/3360)) + (PR [#3360](https://github.com/pipecat-ai/pipecat/pull/3360)) - Added `UserTurnProcessor`, a frame processor built on `UserTurnController` that pushes `UserStartedSpeakingFrame` and `UserStoppedSpeakingFrame` frames and interruptions based on the controller's user turn strategies. -(PR [#3372](https://github.com/pipecat-ai/pipecat/pull/3372)) + (PR [#3372](https://github.com/pipecat-ai/pipecat/pull/3372)) - Added `UserTurnController` to manage user turns. It emits `on_user_turn_started`, `on_user_turn_stopped`, and `on_user_turn_stop_timeout` events, and can be integrated into processors to detect and handle user turns. `LLMUserAggregator` and `UserTurnProcessor` are implemented using this controller. -(PR [#3372](https://github.com/pipecat-ai/pipecat/pull/3372)) + (PR [#3372](https://github.com/pipecat-ai/pipecat/pull/3372)) - Added `should_interrupt` property to `DeepgramFluxSTTService`, `DeepgramSTTService`, and `SpeechmaticsSTTService` to configure whether the bot should be interrupted when the external service detects user speech. -(PR [#3374](https://github.com/pipecat-ai/pipecat/pull/3374)) + (PR [#3374](https://github.com/pipecat-ai/pipecat/pull/3374)) - `LLMAssistantAggregator` now exposes the following events: - `on_assistant_turn_started`: triggered when the assistant turn starts - `on_assistant_turn_stopped`: triggered when the assistant turn ends - `on_assistant_thought`: triggered when there's an assistant thought available -(PR [#3385](https://github.com/pipecat-ai/pipecat/pull/3385)) + (PR [#3385](https://github.com/pipecat-ai/pipecat/pull/3385)) - Added `KrispVivaTurn` analyzer for end of turn detection using the Krisp VIVA SDK (requires `krisp_audio`). -(PR [#3391](https://github.com/pipecat-ai/pipecat/pull/3391)) + (PR [#3391](https://github.com/pipecat-ai/pipecat/pull/3391)) - Added support for setting up a pipeline task from external files. You can now register custom pipeline task setup files by setting the @@ -209,30 +209,30 @@ turn_analyzer=LocalSmartTurnAnalyzerV3(params=SmartTurnParams()) async def setup_pipeline_task(task: PipelineTask): ... ``` -(PR [#3397](https://github.com/pipecat-ai/pipecat/pull/3397)) + (PR [#3397](https://github.com/pipecat-ai/pipecat/pull/3397)) - Added a keepalive task for `InworldTTSService` to keep the service connected in the event of no generations for longer periods of time. -(PR [#3403](https://github.com/pipecat-ai/pipecat/pull/3403)) + (PR [#3403](https://github.com/pipecat-ai/pipecat/pull/3403)) - Added `enable_vad` to `Params` for use in the `GladiaSTTService`. When enabled, `GladiaSTTService` acts as the turn controller, emitting `UserStartedSpeakingFrame`, `UserStoppedSpeakingFrame`, and optionally `InterruptionFrame`. -(PR [#3404](https://github.com/pipecat-ai/pipecat/pull/3404)) + (PR [#3404](https://github.com/pipecat-ai/pipecat/pull/3404)) - Added `should_interrupt` property to `GladiaSTTService` to configure whether the bot should be interrupted when the external service detects user speech. -(PR [#3404](https://github.com/pipecat-ai/pipecat/pull/3404)) + (PR [#3404](https://github.com/pipecat-ai/pipecat/pull/3404)) - Added `VonageFrameSerializer` for the Vonage Video API Audio Connector WebSocket protocol. -(PR [#3410](https://github.com/pipecat-ai/pipecat/pull/3410)) + (PR [#3410](https://github.com/pipecat-ai/pipecat/pull/3410)) - Added `append_trailing_space` parameter to `TTSService` to automatically append a trailing space to text before sending to TTS, helping prevent some services from vocalizing trailing punctuation. -(PR [#3424](https://github.com/pipecat-ai/pipecat/pull/3424)) + (PR [#3424](https://github.com/pipecat-ai/pipecat/pull/3424)) ### Changed @@ -244,16 +244,13 @@ turn_analyzer=LocalSmartTurnAnalyzerV3(params=SmartTurnParams()) include_language_detection=True ) ``` -(PR [#3216](https://github.com/pipecat-ai/pipecat/pull/3216)) + (PR [#3216](https://github.com/pipecat-ai/pipecat/pull/3216)) - Updated `SpeechmaticsSTTService` to use new Python Voice SDK with improved - VAD, - Smart Turn capabilities, and brings dramatic improvements to latency - without - any impact on accuracy. Use the `turn_detection_mode` parameter to control - the - endpointing of speech, with `TurnDetectionMode.EXTERNAL` (default), - `TurnDetectionMode.ADAPTIVE`, or `TurnDetectionMode.SMART_TURN`. + VAD, Smart Turn capabilities, and brings dramatic improvements to latency + without any impact on accuracy. Use the `turn_detection_mode` parameter to control + the endpointing of speech, with `TurnDetectionMode.EXTERNAL` (default), + `TurnDetectionMode.ADAPTIVE`, or `TurnDetectionMode.SMART_TURN`. ```python stt = SpeechmaticsSTTService( api_key=os.getenv("SPEECHMATICS_API_KEY"), @@ -264,126 +261,119 @@ turn_detection_mode=SpeechmaticsSTTService.TurnDetectionMode.ADAPTIVE, ), ) ``` -(PR [#3225](https://github.com/pipecat-ai/pipecat/pull/3225)) + (PR [#3225](https://github.com/pipecat-ai/pipecat/pull/3225)) - `daily-python` updated to 0.23.0. -(PR [#3257](https://github.com/pipecat-ai/pipecat/pull/3257)) + (PR [#3257](https://github.com/pipecat-ai/pipecat/pull/3257)) - `TranscriptionFrame` and `InterimTranscriptionFrame` produced by `DailyTransport` now include the transport source (i.e., the originating audio track). -(PR [#3257](https://github.com/pipecat-ai/pipecat/pull/3257)) + (PR [#3257](https://github.com/pipecat-ai/pipecat/pull/3257)) - Updates to Inworld TTS services: - Improved `InworldTTSService`'s websocket implementation to better flush - and - close context to better handle long inputs. + and close context to better handle long inputs. - Improved docstrings for `InworldTTSService` and `InworldHttpTTSService`. -(PR [#3288](https://github.com/pipecat-ai/pipecat/pull/3288)) + (PR [#3288](https://github.com/pipecat-ai/pipecat/pull/3288)) - Updated `DeepgramSTTService` to push user started/stopped speaking and interruption frames when `vad_enabled` is set to true. This centralizes the frames into the service, removing the need to have your application code handle Deepgram's events and push these frames. -(PR [#3314](https://github.com/pipecat-ai/pipecat/pull/3314)) + (PR [#3314](https://github.com/pipecat-ai/pipecat/pull/3314)) - Added encoding validation to `DeepgramTTSService` to prevent unsupported encodings from reaching the API. The service now raises `ValueError` at initialization with a clear error message. -(PR [#3329](https://github.com/pipecat-ai/pipecat/pull/3329)) + (PR [#3329](https://github.com/pipecat-ai/pipecat/pull/3329)) - Updated `read_audio_frame` & `read_video_frame` methods in `SmallWebRTCClient` to check if the track is enabled before logging a warning. -(PR [#3336](https://github.com/pipecat-ai/pipecat/pull/3336)) + (PR [#3336](https://github.com/pipecat-ai/pipecat/pull/3336)) - Updated `CartesiaTTSService` to support setting `language=None`, resulting in Cartesia auto-detecting the language of the conversation. -(PR [#3366](https://github.com/pipecat-ai/pipecat/pull/3366)) + (PR [#3366](https://github.com/pipecat-ai/pipecat/pull/3366)) - The bundled Smart Turn weights are now updated to v3.2, which has better - handling of short utterances, and is more robust against background - noise. -(PR [#3367](https://github.com/pipecat-ai/pipecat/pull/3367)) + handling of short utterances, and is more robust against background noise. + (PR [#3367](https://github.com/pipecat-ai/pipecat/pull/3367)) -- Updated `SpeechmaticsSTTService` dependency to - `speechmatics-voice[smart]>=0.2.6` -(PR [#3371](https://github.com/pipecat-ai/pipecat/pull/3371)) +- Updated `SpeechmaticsSTTService` dependency to `speechmatics-voice[smart]>=0.2.6` + (PR [#3371](https://github.com/pipecat-ai/pipecat/pull/3371)) - Smart Turn now takes into account `vad_start_seconds` when buffering audio, - meaning that the start of the turn audio is not cut off. This improves - accuracy for short utterances. - - - The default value of `pre_speech_ms` is now set to 500ms for Smart Turn. -(PR [#3377](https://github.com/pipecat-ai/pipecat/pull/3377)) + meaning that the start of the turn audio is not cut off. This improves + accuracy for short utterances. + - The default value of `pre_speech_ms` is now set to 500ms for Smart Turn. + (PR [#3377](https://github.com/pipecat-ai/pipecat/pull/3377)) - Improved Krisp SDK management to allow `KrispVivaTurn` and `KrispVivaFilter` to share a single SDK instance within the same process. -(PR [#3391](https://github.com/pipecat-ai/pipecat/pull/3391)) + (PR [#3391](https://github.com/pipecat-ai/pipecat/pull/3391)) - Updated default model for `GroqTTSService` to `canopylabs/orpheus-v1-english` and voice ID to `autumn`. -(PR [#3399](https://github.com/pipecat-ai/pipecat/pull/3399)) + (PR [#3399](https://github.com/pipecat-ai/pipecat/pull/3399)) - Enhanced `FastAPIWebsocketTransport` with optional protocol-level audio packetization via the `fixed_audio_packet_size` parameter to support media endpoints requiring strict framing and real-time pacing. -(PR [#3410](https://github.com/pipecat-ai/pipecat/pull/3410)) + (PR [#3410](https://github.com/pipecat-ai/pipecat/pull/3410)) - `DeepgramTTSService` and `RimeTTSService` now set `append_trailing_space` to `True` to prevent punctuation (e.g., “dot”) from being pronounced. -(PR [#3424](https://github.com/pipecat-ai/pipecat/pull/3424)) + (PR [#3424](https://github.com/pipecat-ai/pipecat/pull/3424)) - Updated `GeminiLiveLLMService` to push `LLMThoughtStartFrame`, `LLMThoughtTextFrame`, and `LLMThoughtEndFrame` when the model returns thought content. -(PR [#3431](https://github.com/pipecat-ai/pipecat/pull/3431)) + (PR [#3431](https://github.com/pipecat-ai/pipecat/pull/3431)) ### Deprecated - `pipecat.audio.interruptions.MinWordsInterruptionStrategy` is deprecated. Use `pipecat.turns.user_start.MinWordsUserTurnStartStrategy` with `LLMUserAggregator`'s new `user_turn_strategies` parameter instead. -(PR [#3045](https://github.com/pipecat-ai/pipecat/pull/3045)) + (PR [#3045](https://github.com/pipecat-ai/pipecat/pull/3045)) - `FrameProcessor.interruption_strategies` is deprecated, use `LLMUserAggregator`'s new `user_turn_strategies` parameter instead. -(PR [#3045](https://github.com/pipecat-ai/pipecat/pull/3045)) + (PR [#3045](https://github.com/pipecat-ai/pipecat/pull/3045)) - The `LLMUserAggregatorParams` and `LLMAssistantAggregatorParams` classes in `pipecat.processors.aggregators.llm_response` are now deprecated. Use the new universal `LLMContext` and `LLMContextAggregatorPair` instead. -(PR [#3045](https://github.com/pipecat-ai/pipecat/pull/3045)) + (PR [#3045](https://github.com/pipecat-ai/pipecat/pull/3045)) - Deprecated the `emulated` field in the `UserStartedSpeakingFrame` and `UserStoppedSpeakingFrame` frames. -(PR [#3045](https://github.com/pipecat-ai/pipecat/pull/3045)) + (PR [#3045](https://github.com/pipecat-ai/pipecat/pull/3045)) - `EmulateUserStartedSpeakingFrame` and `EmulateUserStoppedSpeakingFrame` frames are deprecated. -(PR [#3045](https://github.com/pipecat-ai/pipecat/pull/3045)) + (PR [#3045](https://github.com/pipecat-ai/pipecat/pull/3045)) - ⚠️ `TransportParams.turn_analyzer` is deprecated and might result in unexpected behavior, use `LLMUserAggregator`'s new `user_turn_strategies` parameter instead. -(PR [#3045](https://github.com/pipecat-ai/pipecat/pull/3045)) + (PR [#3045](https://github.com/pipecat-ai/pipecat/pull/3045)) - For `SpeechmaticsSTTService`, the `end_of_utterance_mode` parameter is - deprecated. - Use the new `turn_detection_mode` parameter instead, with - `TurnDetectionMode.EXTERNAL`, - `TurnDetectionMode.ADAPTIVE`, or `TurnDetectionMode.SMART_TURN`. The - `enable_vad` - parameter is also deprecated and is inferred from the - `turn_detection_mode`. -(PR [#3225](https://github.com/pipecat-ai/pipecat/pull/3225)) + deprecated. Use the new `turn_detection_mode` parameter instead, with + `TurnDetectionMode.EXTERNAL`,`TurnDetectionMode.ADAPTIVE`, or + `TurnDetectionMode.SMART_TURN`. The `enable_vad` parameter is also + deprecated and is inferred from the `turn_detection_mode`. + (PR [#3225](https://github.com/pipecat-ai/pipecat/pull/3225)) - `OpenAILLMContext` and its associated things (context aggregators, etc.) are now deprecated in favor of the universal `LLMContext` and its associated things. - From the developer's point of view, switching to using `LLMContext` + From the developer's point of view, switching to using `LLMContext` machinery will usually be a matter of going from this: ```python @@ -397,15 +387,15 @@ turn_detection_mode=SpeechmaticsSTTService.TurnDetectionMode.ADAPTIVE, context = LLMContext(messages, tools) context_aggregator = LLMContextAggregatorPair(context) ``` -(PR [#3263](https://github.com/pipecat-ai/pipecat/pull/3263)) + (PR [#3263](https://github.com/pipecat-ai/pipecat/pull/3263)) - `STTMuteFilter` is deprecated and will be removed in a future version. Use `LLMUserAggregator`'s new `user_mute_strategies` instead. -(PR [#3292](https://github.com/pipecat-ai/pipecat/pull/3292)) + (PR [#3292](https://github.com/pipecat-ai/pipecat/pull/3292)) - `FrameProcessor.interruptions_allowed` is now deprecated, use `LLMUserAggregator`'s new parameter `user_mute_strategies` instead. -(PR [#3297](https://github.com/pipecat-ai/pipecat/pull/3297)) + (PR [#3297](https://github.com/pipecat-ai/pipecat/pull/3297)) - `PipelineParams.allow_interruptions` is now deprecated, use `LLMUserAggregator`'s new parameter `user_turn_strategies` instead. For @@ -421,95 +411,95 @@ start=[TranscriptionUserTurnStartStrategy(enable_interruptions=False)], ), ) ``` -(PR [#3297](https://github.com/pipecat-ai/pipecat/pull/3297)) + (PR [#3297](https://github.com/pipecat-ai/pipecat/pull/3297)) - `TranscriptProcessor` and related data classes and frames (`TranscriptionMessage`, `ThoughtTranscriptionMessage`, `TranscriptionUpdateFrame`) are deprecated. Use `LLMUserAggregator`'s and `LLMAssistantAggregator`'s new events (`on_user_turn_stopped` and `on_assistant_turn_stopped`) instead. -(PR [#3385](https://github.com/pipecat-ai/pipecat/pull/3385)) + (PR [#3385](https://github.com/pipecat-ai/pipecat/pull/3385)) - Deprecated support for the `vad_events` `LiveOptions` in `DeepgramSTTService`. Instead, use a local Silero VAD for VAD events. Additionally, deprecated `should_interrupt` which will be removed along with `vad_events` support in a future release. -(PR [#3386](https://github.com/pipecat-ai/pipecat/pull/3386)) + (PR [#3386](https://github.com/pipecat-ai/pipecat/pull/3386)) - Loading external observers from files is deprecated, use the new pipeline task setup files and `PIPECAT_SETUP_FILES` environment variable instead. -(PR [#3397](https://github.com/pipecat-ai/pipecat/pull/3397)) + (PR [#3397](https://github.com/pipecat-ai/pipecat/pull/3397)) ### Fixed - Improved error handling in `ElevenLabsRealtimeSTTService` - Fixed an issue in `ElevenLabsRealtimeSTTService` causing an infinite loop that blocks the process if the websocket disconnects due to an error -(PR [#3233](https://github.com/pipecat-ai/pipecat/pull/3233)) + (PR [#3233](https://github.com/pipecat-ai/pipecat/pull/3233)) - Fixed a bug in `STTMuteFilter` where the user was not always muted during function calls, especially when there were multiple simultaneous calls. -(PR [#3292](https://github.com/pipecat-ai/pipecat/pull/3292)) + (PR [#3292](https://github.com/pipecat-ai/pipecat/pull/3292)) - Fixed a `RNNoiseFilter` issue that would cause a "[Errno 12] Cannot allocate memory" error when processing silence audio frames. -(PR [#3322](https://github.com/pipecat-ai/pipecat/pull/3322)) + (PR [#3322](https://github.com/pipecat-ai/pipecat/pull/3322)) - Updated `SpeechmaticsSTTService` for version `0.0.99+`: - - Fixed `SpeechmaticsSTTService` to listen for - `VADUserStoppedSpeakingFrame` in order to finalize transcription. + - Fixed `SpeechmaticsSTTService` to listen for `VADUserStoppedSpeakingFrame` + in order to finalize transcription. - Default to `TurnDetectionMode.FIXED` for Pipecat-controlled end of turn - detection. + detection. - Only emit VAD + interruption frames if VAD is enabled within the plugin - (modes other than `TurnDetectionMode.FIXED` or `TurnDetectionMode.EXTERNAL`). -(PR [#3328](https://github.com/pipecat-ai/pipecat/pull/3328)) + (modes other than `TurnDetectionMode.FIXED` or `TurnDetectionMode.EXTERNAL`). + (PR [#3328](https://github.com/pipecat-ai/pipecat/pull/3328)) - Fixed an issue with function calling where a handler failing to invoke its result callback could leave the context stuck in IN_PROGRESS, causing LLM inference for subsequent function call results to block while waiting on the unresolved call. -(PR [#3343](https://github.com/pipecat-ai/pipecat/pull/3343)) + (PR [#3343](https://github.com/pipecat-ai/pipecat/pull/3343)) - Fixed an issue with DeepgramTTSService where the model would output "Dot" instead of a period in some circumstances. -(PR [#3345](https://github.com/pipecat-ai/pipecat/pull/3345)) + (PR [#3345](https://github.com/pipecat-ai/pipecat/pull/3345)) - Fixed an issue in `traced_stt` where `model_name` in OpenTelemetry appears as `unknown`. -(PR [#3351](https://github.com/pipecat-ai/pipecat/pull/3351)) + (PR [#3351](https://github.com/pipecat-ai/pipecat/pull/3351)) - Fixed an issue in GeminiLiveLLMService where TranscriptionFrames were occasionally not pushed. -(PR [#3356](https://github.com/pipecat-ai/pipecat/pull/3356)) + (PR [#3356](https://github.com/pipecat-ai/pipecat/pull/3356)) - Fixed potential memory leaks and initialization issues in `KrispVivaFilter` by improving SDK lifecycle management. -(PR [#3391](https://github.com/pipecat-ai/pipecat/pull/3391)) + (PR [#3391](https://github.com/pipecat-ai/pipecat/pull/3391)) - Fixed timing issue in `BaseOutputTransport` where the bot speaking flag was set after awaiting, allowing the event loop to re-enter the method before the guard was set. -(PR [#3400](https://github.com/pipecat-ai/pipecat/pull/3400)) + (PR [#3400](https://github.com/pipecat-ai/pipecat/pull/3400)) - Fixed an issue in `traced_llm` where `model_name` in OpenTelemetry appears as `unknown`. -(PR [#3422](https://github.com/pipecat-ai/pipecat/pull/3422)) + (PR [#3422](https://github.com/pipecat-ai/pipecat/pull/3422)) - Fixed an issue in `traced_tts`, `traced_gemini_live`, and `traced_openai_realtime` where `model_name` in OpenTelemetry appears as `unknown`. -(PR [#3428](https://github.com/pipecat-ai/pipecat/pull/3428)) + (PR [#3428](https://github.com/pipecat-ai/pipecat/pull/3428)) - Fixed `request_image_frame` (for backwards compatibility) and restored function-call–related fields in `UserImageRequestFrame` and `UserImageRawFrame`, preventing a case where adding a non-LLM message to the context could trigger duplicate LLM inferences (on image arrival and on function-call result), potentially causing an infinite inference loop. -(PR [#3430](https://github.com/pipecat-ai/pipecat/pull/3430)) + (PR [#3430](https://github.com/pipecat-ai/pipecat/pull/3430)) - Fixed `LLMContext.create_audio_message()` by correcting an internal helper that was incorrectly declared async while being run in `asyncio.to_thread()`. -(PR [#3435](https://github.com/pipecat-ai/pipecat/pull/3435)) + (PR [#3435](https://github.com/pipecat-ai/pipecat/pull/3435)) ### Other @@ -518,16 +508,16 @@ start=[TranscriptionUserTurnStartStrategy(enable_interruptions=False)], bot is not interruptible: as the user continues speaking, English transcriptions are queued, and the bot continuously translates and speaks each queued sentence in Spanish without being interrupted by new user speech. -(PR [#3316](https://github.com/pipecat-ai/pipecat/pull/3316)) + (PR [#3316](https://github.com/pipecat-ai/pipecat/pull/3316)) - Added a new foundational example `53-concurrent-llm-evaluation.py` that shows how to use `UserTurnProcessor`. -(PR [#3372](https://github.com/pipecat-ai/pipecat/pull/3372)) + (PR [#3372](https://github.com/pipecat-ai/pipecat/pull/3372)) - Added a new foundational example `28-user-assistant-turns.py` that shows how to use the new `LLMUserAggregator` and `LLMAssistantAggregator` events to gather a conversation transcript. -(PR [#3385](https://github.com/pipecat-ai/pipecat/pull/3385)) + (PR [#3385](https://github.com/pipecat-ai/pipecat/pull/3385)) ## [0.0.98] - 2025-12-17 From 9cdbc56be3b671bda192a4f5529e95eeafb484c4 Mon Sep 17 00:00:00 2001 From: Ashot Date: Tue, 23 Dec 2025 16:35:45 +0400 Subject: [PATCH 0050/1060] Fix TTFB metric and add multi-context WebSocket support for Async TTS --- CHANGELOG.md | 9 + src/pipecat/services/asyncai/tts.py | 323 +++++++++++++++++++++------- 2 files changed, 259 insertions(+), 73 deletions(-) diff --git a/CHANGELOG.md b/CHANGELOG.md index 3d583b4e1..63ef32ed1 100644 --- a/CHANGELOG.md +++ b/CHANGELOG.md @@ -6,6 +6,15 @@ The format is based on [Keep a Changelog](https://keepachangelog.com/en/1.0.0/), and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0.html). +## [Unreleased] + +### Changed + +- Enhanced interruption handling in `AsyncAITTSService` by supporting multi-context WebSocket sessions for more robust context management. + +### Fixed + +- Corrected TTFB metric calculation in `AsyncAIHttpTTSService`. ## [0.0.99] - 2026-01-13 diff --git a/src/pipecat/services/asyncai/tts.py b/src/pipecat/services/asyncai/tts.py index 303369205..c49b95153 100644 --- a/src/pipecat/services/asyncai/tts.py +++ b/src/pipecat/services/asyncai/tts.py @@ -9,8 +9,9 @@ import asyncio import base64 import json -from typing import AsyncGenerator, Optional +from typing import AsyncGenerator, Optional, Dict +import uuid import aiohttp from loguru import logger from pydantic import BaseModel @@ -27,7 +28,7 @@ from pipecat.frames.frames import ( TTSStoppedFrame, ) from pipecat.processors.frame_processor import FrameDirection -from pipecat.services.tts_service import InterruptibleTTSService, TTSService +from pipecat.services.tts_service import WebsocketTTSService, TTSService from pipecat.transcriptions.language import Language, resolve_language from pipecat.utils.tracing.service_decorators import traced_tts @@ -72,7 +73,7 @@ def language_to_async_language(language: Language) -> Optional[str]: return resolve_language(language, LANGUAGE_MAP, use_base_code=True) -class AsyncAITTSService(InterruptibleTTSService): +class AsyncAITTSService(WebsocketTTSService): """Async TTS service with WebSocket streaming. Provides text-to-speech using Async's streaming WebSocket API. @@ -126,6 +127,10 @@ class AsyncAITTSService(InterruptibleTTSService): **kwargs, ) + self._contexts: Dict[str, asyncio.Queue] = {} + self._audio_context_task = None + self._context_id = None + params = params or AsyncAITTSService.InputParams() self._api_key = api_key @@ -148,6 +153,148 @@ class AsyncAITTSService(InterruptibleTTSService): self._receive_task = None self._keepalive_task = None self._started = False + + async def create_audio_context(self, context_id: str): + """Create a new audio context for grouping related audio. + + Args: + context_id: Unique identifier for the audio context. + """ + await self._contexts_queue.put(context_id) + self._contexts[context_id] = asyncio.Queue() + logger.trace(f"{self} created audio context {context_id}") + + async def append_to_audio_context(self, context_id: str, frame: TTSAudioRawFrame): + """Append audio to an existing context. + + Args: + context_id: The context to append audio to. + frame: The audio frame to append. + """ + if self.audio_context_available(context_id): + logger.trace(f"{self} appending audio {frame} to audio context {context_id}") + await self._contexts[context_id].put(frame) + else: + logger.warning(f"{self} unable to append audio to context {context_id}") + + async def remove_audio_context(self, context_id: str): + """Remove an existing audio context. + + Args: + context_id: The context to remove. + """ + if self.audio_context_available(context_id): + # We just mark the audio context for deletion by appending + # None. Once we reach None while handling audio we know we can + # safely remove the context. + logger.trace(f"{self} marking audio context {context_id} for deletion") + await self._contexts[context_id].put(None) + else: + logger.warning(f"{self} unable to remove context {context_id}") + + def audio_context_available(self, context_id: str) -> bool: + """Check whether the given audio context is registered. + + Args: + context_id: The context ID to check. + + Returns: + True if the context exists and is available. + """ + return context_id in self._contexts + + async def start(self, frame: StartFrame): + """Start the Async TTS service. + + Args: + frame: The start frame containing initialization parameters. + """ + await super().start(frame) + self._create_audio_context_task() + self._settings["output_format"]["sample_rate"] = self.sample_rate + await self._connect() + + async def stop(self, frame: EndFrame): + """Stop the Async TTS service. + + Args: + frame: The end frame. + """ + await super().stop(frame) + if self._audio_context_task: + # Indicate no more audio contexts are available. this will end the + # task cleanly after all contexts have been processed. + await self._contexts_queue.put(None) + await self._audio_context_task + self._audio_context_task = None + await self._disconnect() + + async def cancel(self, frame: CancelFrame): + """Cancel the Async TTS service. + + Args: + frame: The cancel frame. + """ + await super().cancel(frame) + await self._stop_audio_context_task() + await self._disconnect() + + async def _handle_interruption(self, frame: InterruptionFrame, direction: FrameDirection): + await super()._handle_interruption(frame, direction) + await self._stop_audio_context_task() + self._create_audio_context_task() + + def _create_audio_context_task(self): + if not self._audio_context_task: + self._contexts_queue = asyncio.Queue() + self._contexts: Dict[str, asyncio.Queue] = {} + self._audio_context_task = self.create_task(self._audio_context_task_handler()) + + async def _stop_audio_context_task(self): + if self._audio_context_task: + await self.cancel_task(self._audio_context_task) + self._audio_context_task = None + + async def _audio_context_task_handler(self): + """In this task we process audio contexts in order.""" + running = True + while running: + context_id = await self._contexts_queue.get() + + if context_id: + # Process the audio context until the context doesn't have more + # audio available (i.e. we find None). + await self._handle_audio_context(context_id) + + # We just finished processing the context, so we can safely remove it. + del self._contexts[context_id] + + # Append some silence between sentences. + silence = b"\x00" * self.sample_rate + frame = TTSAudioRawFrame( + audio=silence, sample_rate=self.sample_rate, num_channels=1 + ) + await self.push_frame(frame) + else: + running = False + + self._contexts_queue.task_done() + + async def _handle_audio_context(self, context_id: str): + # If we don't receive any audio during this time, we consider the context finished. + AUDIO_CONTEXT_TIMEOUT = 3.0 + queue = self._contexts[context_id] + running = True + while running: + try: + frame = await asyncio.wait_for(queue.get(), timeout=AUDIO_CONTEXT_TIMEOUT) + if frame: + await self.push_frame(frame) + running = frame is not None + except asyncio.TimeoutError: + # We didn't get audio, so let's consider this context finished. + logger.trace(f"{self} time out on audio context {context_id}") + break def can_generate_metrics(self) -> bool: """Check if this service can generate processing metrics. @@ -168,38 +315,10 @@ class AsyncAITTSService(InterruptibleTTSService): """ return language_to_async_language(language) - def _build_msg(self, text: str = "", force: bool = False) -> str: - msg = {"transcript": text, "force": force} + def _build_msg(self, text: str = "", context_id: str = "", force: bool = False) -> str: + msg = {"transcript": text, "context_id": context_id, "force": force} return json.dumps(msg) - async def start(self, frame: StartFrame): - """Start the Async TTS service. - - Args: - frame: The start frame containing initialization parameters. - """ - await super().start(frame) - self._settings["output_format"]["sample_rate"] = self.sample_rate - await self._connect() - - async def stop(self, frame: EndFrame): - """Stop the Async TTS service. - - Args: - frame: The end frame. - """ - await super().stop(frame) - await self._disconnect() - - async def cancel(self, frame: CancelFrame): - """Cancel the Async TTS service. - - Args: - frame: The cancel frame. - """ - await super().cancel(frame) - await self._disconnect() - async def _connect(self): await super()._connect() @@ -253,11 +372,16 @@ class AsyncAITTSService(InterruptibleTTSService): if self._websocket: logger.debug("Disconnecting from Async") + # Close all contexts and the socket + if self._context_id: + await self._websocket.send(json.dumps({"terminate": True})) await self._websocket.close() + logger.debug("Disconnected from Async") except Exception as e: - await self.push_error(error_msg=f"Unknown error occurred: {e}", exception=e) + logger.error(f"{self} error closing websocket: {e}") finally: self._websocket = None + self._context_id = None self._started = False await self._call_event_handler("on_disconnected") @@ -268,10 +392,10 @@ class AsyncAITTSService(InterruptibleTTSService): async def flush_audio(self): """Flush any pending audio.""" - if not self._websocket: + if not self._context_id or not self._websocket: return logger.trace(f"{self}: flushing audio") - msg = self._build_msg(text=" ", force=True) + msg = self._build_msg(text=" ", context_id=self._context_id, force=True) await self._websocket.send(msg) async def push_frame(self, frame: Frame, direction: FrameDirection = FrameDirection.DOWNSTREAM): @@ -291,35 +415,70 @@ class AsyncAITTSService(InterruptibleTTSService): if not msg: continue - elif msg.get("audio"): + received_ctx_id = msg.get("context_id") + # Handle final messages first, regardless of context availability + # At the moment, this message is received AFTER the close_context message is + # sent, so it doesn't serve any functional purpose. For now, we'll just log it. + if msg.get("final") is True: + logger.trace(f"Received final message for context {received_ctx_id}") + continue + + # Check if this message belongs to the current context. + if not self.audio_context_available(received_ctx_id): + if self._context_id == received_ctx_id: + logger.debug( + f"Received a delayed message, recreating the context: {self._context_id}" + ) + await self.create_audio_context(self._context_id) + else: + # This can happen if a message is received _after_ we have closed a context + # due to user interruption but _before_ the `isFinal` message for the context + # is received. + logger.debug(f"Ignoring message from unavailable context: {received_ctx_id}") + continue + + if msg.get("audio"): await self.stop_ttfb_metrics() - frame = TTSAudioRawFrame( - audio=base64.b64decode(msg["audio"]), - sample_rate=self.sample_rate, - num_channels=1, - ) - await self.push_frame(frame) - elif msg.get("error_code"): - await self.push_frame(TTSStoppedFrame()) - await self.stop_all_metrics() - await self.push_error(error_msg=f"Error: {msg['message']}") - else: - await self.push_error(error_msg=f"Unknown message type: {msg}") + audio = base64.b64decode(msg["audio"]) + frame = TTSAudioRawFrame(audio, self.sample_rate, 1) + await self.append_to_audio_context(received_ctx_id, frame) async def _keepalive_task_handler(self): """Send periodic keepalive messages to maintain WebSocket connection.""" - KEEPALIVE_SLEEP = 3 + KEEPALIVE_SLEEP = 10 while True: await asyncio.sleep(KEEPALIVE_SLEEP) try: if self._websocket and self._websocket.state is State.OPEN: - keepalive_message = {"transcript": " "} - logger.trace("Sending keepalive message") + if self._context_id: + keepalive_message = {"transcript": " ", "context_id": self._context_id,} + logger.trace("Sending keepalive message") + else: + # It's possible to have a user interruption which clears the context + # without generating a new TTS response. In this case, we'll just send + # an empty message to keep the connection alive. + keepalive_message = {"transcript": " "} + logger.trace("Sending keepalive without context") await self._websocket.send(json.dumps(keepalive_message)) except websockets.ConnectionClosed as e: logger.warning(f"{self} keepalive error: {e}") break + async def _handle_interruption(self, frame: InterruptionFrame, direction: FrameDirection): + """Handle interruption by closing the current context.""" + await super()._handle_interruption(frame, direction) + + # Close the current context when interrupted without closing the websocket + if self._context_id and self._websocket: + try: + await self._websocket.send( + json.dumps({"context_id": self._context_id, "close_context": True, "transcript": ""}) + ) + except Exception as e: + logger.error(f"Error closing context on interruption: {e}") + self._context_id = None + self._started = False + @traced_tts async def run_tts(self, text: str) -> AsyncGenerator[Frame, None]: """Generate speech from text using Async API websocket endpoint. @@ -336,26 +495,35 @@ class AsyncAITTSService(InterruptibleTTSService): if not self._websocket or self._websocket.state is State.CLOSED: await self._connect() - if not self._started: - await self.start_ttfb_metrics() - yield TTSStartedFrame() - self._started = True + try: + if not self._started: + await self.start_ttfb_metrics() + yield TTSStartedFrame() + self._started = True - msg = self._build_msg(text=text, force=True) + if not self._context_id: + self._context_id = str(uuid.uuid4()) + if not self.audio_context_available(self._context_id): + await self.create_audio_context(self._context_id) - try: - await self._get_websocket().send(msg) - await self.start_tts_usage_metrics(text) + msg = self._build_msg(text=" ", context_id=self._context_id) + await self._get_websocket().send(msg) + msg = self._build_msg(text=text, force=True, context_id=self._context_id) + await self._get_websocket().send(msg) + await self.start_tts_usage_metrics(text) + else: + if self._websocket and self._context_id: + msg = self._build_msg(text=text, force=True, context_id=self._context_id) + await self._get_websocket().send(msg) + except Exception as e: - yield ErrorFrame(error=f"Unknown error occurred: {e}") + logger.error(f"{self} error sending message: {e}") yield TTSStoppedFrame() - await self._disconnect() - await self._connect() + self._started = False return yield None except Exception as e: - yield ErrorFrame(error=f"Unknown error occurred: {e}") - + logger.error(f"{self} exception: {e}") class AsyncAIHttpTTSService(TTSService): """HTTP-based Async TTS service. @@ -466,9 +634,9 @@ class AsyncAIHttpTTSService(TTSService): """ logger.debug(f"{self}: Generating TTS [{text}]") + first_byte_seen = False try: voice_config = {"mode": "id", "id": self._voice_id} - await self.start_ttfb_metrics() payload = { "model_id": self._model_name, "transcript": text, @@ -476,7 +644,6 @@ class AsyncAIHttpTTSService(TTSService): "output_format": self._settings["output_format"], "language": self._settings["language"], } - yield TTSStartedFrame() headers = { "version": self._api_version, "x-api-key": self._api_key, @@ -484,26 +651,36 @@ class AsyncAIHttpTTSService(TTSService): } url = f"{self._base_url}/text_to_speech/streaming" + yield TTSStartedFrame() + await self.start_ttfb_metrics() async with self._session.post(url, json=payload, headers=headers) as response: if response.status != 200: error_text = await response.text() await self.push_error(error_msg=f"Async API error: {error_text}") raise Exception(f"Async API returned status {response.status}: {error_text}") - audio_data = await response.read() + # Read streaming bytes; stop TTFB on the *first* received chunk + buffer = bytearray() + async for chunk in response.content.iter_chunked(64 * 1024): + if not chunk: + continue + if not first_byte_seen: + first_byte_seen = True + await self.stop_ttfb_metrics() + await self.start_tts_usage_metrics(text) - await self.start_tts_usage_metrics(text) + buffer.extend(chunk) + audio_data = bytes(buffer) - frame = TTSAudioRawFrame( + yield TTSAudioRawFrame( audio=audio_data, sample_rate=self.sample_rate, num_channels=1, ) - yield frame - except Exception as e: await self.push_error(error_msg=f"Unknown error occurred: {e}", exception=e) finally: - await self.stop_ttfb_metrics() + if not first_byte_seen: + await self.stop_ttfb_metrics() yield TTSStoppedFrame() From 5ae592f38e37e275dfaef46d5701432aff1df1fb Mon Sep 17 00:00:00 2001 From: Ashot Date: Wed, 7 Jan 2026 15:55:35 +0400 Subject: [PATCH 0051/1060] Improve Async TTS interruption handling by using AudioContextTTSService class and add changelog fragments --- CHANGELOG.md | 9 --- changelog/3287.changed.md | 1 + changelog/3287.fixed.md | 1 + src/pipecat/services/asyncai/tts.py | 120 +--------------------------- 4 files changed, 5 insertions(+), 126 deletions(-) create mode 100644 changelog/3287.changed.md create mode 100644 changelog/3287.fixed.md diff --git a/CHANGELOG.md b/CHANGELOG.md index 63ef32ed1..3d583b4e1 100644 --- a/CHANGELOG.md +++ b/CHANGELOG.md @@ -6,15 +6,6 @@ The format is based on [Keep a Changelog](https://keepachangelog.com/en/1.0.0/), and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0.html). -## [Unreleased] - -### Changed - -- Enhanced interruption handling in `AsyncAITTSService` by supporting multi-context WebSocket sessions for more robust context management. - -### Fixed - -- Corrected TTFB metric calculation in `AsyncAIHttpTTSService`. ## [0.0.99] - 2026-01-13 diff --git a/changelog/3287.changed.md b/changelog/3287.changed.md new file mode 100644 index 000000000..f0df82966 --- /dev/null +++ b/changelog/3287.changed.md @@ -0,0 +1 @@ +- Enhanced interruption handling in `AsyncAITTSService` by supporting multi-context WebSocket sessions for more robust context management. \ No newline at end of file diff --git a/changelog/3287.fixed.md b/changelog/3287.fixed.md new file mode 100644 index 000000000..30ce0b13b --- /dev/null +++ b/changelog/3287.fixed.md @@ -0,0 +1 @@ +- Corrected TTFB metric calculation in `AsyncAIHttpTTSService`. \ No newline at end of file diff --git a/src/pipecat/services/asyncai/tts.py b/src/pipecat/services/asyncai/tts.py index c49b95153..05ba18654 100644 --- a/src/pipecat/services/asyncai/tts.py +++ b/src/pipecat/services/asyncai/tts.py @@ -28,7 +28,7 @@ from pipecat.frames.frames import ( TTSStoppedFrame, ) from pipecat.processors.frame_processor import FrameDirection -from pipecat.services.tts_service import WebsocketTTSService, TTSService +from pipecat.services.tts_service import AudioContextTTSService, WebsocketTTSService, TTSService from pipecat.transcriptions.language import Language, resolve_language from pipecat.utils.tracing.service_decorators import traced_tts @@ -73,7 +73,7 @@ def language_to_async_language(language: Language) -> Optional[str]: return resolve_language(language, LANGUAGE_MAP, use_base_code=True) -class AsyncAITTSService(WebsocketTTSService): +class AsyncAITTSService(AudioContextTTSService, WebsocketTTSService): """Async TTS service with WebSocket streaming. Provides text-to-speech using Async's streaming WebSocket API. @@ -154,55 +154,6 @@ class AsyncAITTSService(WebsocketTTSService): self._keepalive_task = None self._started = False - async def create_audio_context(self, context_id: str): - """Create a new audio context for grouping related audio. - - Args: - context_id: Unique identifier for the audio context. - """ - await self._contexts_queue.put(context_id) - self._contexts[context_id] = asyncio.Queue() - logger.trace(f"{self} created audio context {context_id}") - - async def append_to_audio_context(self, context_id: str, frame: TTSAudioRawFrame): - """Append audio to an existing context. - - Args: - context_id: The context to append audio to. - frame: The audio frame to append. - """ - if self.audio_context_available(context_id): - logger.trace(f"{self} appending audio {frame} to audio context {context_id}") - await self._contexts[context_id].put(frame) - else: - logger.warning(f"{self} unable to append audio to context {context_id}") - - async def remove_audio_context(self, context_id: str): - """Remove an existing audio context. - - Args: - context_id: The context to remove. - """ - if self.audio_context_available(context_id): - # We just mark the audio context for deletion by appending - # None. Once we reach None while handling audio we know we can - # safely remove the context. - logger.trace(f"{self} marking audio context {context_id} for deletion") - await self._contexts[context_id].put(None) - else: - logger.warning(f"{self} unable to remove context {context_id}") - - def audio_context_available(self, context_id: str) -> bool: - """Check whether the given audio context is registered. - - Args: - context_id: The context ID to check. - - Returns: - True if the context exists and is available. - """ - return context_id in self._contexts - async def start(self, frame: StartFrame): """Start the Async TTS service. @@ -210,7 +161,6 @@ class AsyncAITTSService(WebsocketTTSService): frame: The start frame containing initialization parameters. """ await super().start(frame) - self._create_audio_context_task() self._settings["output_format"]["sample_rate"] = self.sample_rate await self._connect() @@ -221,12 +171,6 @@ class AsyncAITTSService(WebsocketTTSService): frame: The end frame. """ await super().stop(frame) - if self._audio_context_task: - # Indicate no more audio contexts are available. this will end the - # task cleanly after all contexts have been processed. - await self._contexts_queue.put(None) - await self._audio_context_task - self._audio_context_task = None await self._disconnect() async def cancel(self, frame: CancelFrame): @@ -236,65 +180,7 @@ class AsyncAITTSService(WebsocketTTSService): frame: The cancel frame. """ await super().cancel(frame) - await self._stop_audio_context_task() - await self._disconnect() - - async def _handle_interruption(self, frame: InterruptionFrame, direction: FrameDirection): - await super()._handle_interruption(frame, direction) - await self._stop_audio_context_task() - self._create_audio_context_task() - - def _create_audio_context_task(self): - if not self._audio_context_task: - self._contexts_queue = asyncio.Queue() - self._contexts: Dict[str, asyncio.Queue] = {} - self._audio_context_task = self.create_task(self._audio_context_task_handler()) - - async def _stop_audio_context_task(self): - if self._audio_context_task: - await self.cancel_task(self._audio_context_task) - self._audio_context_task = None - - async def _audio_context_task_handler(self): - """In this task we process audio contexts in order.""" - running = True - while running: - context_id = await self._contexts_queue.get() - - if context_id: - # Process the audio context until the context doesn't have more - # audio available (i.e. we find None). - await self._handle_audio_context(context_id) - - # We just finished processing the context, so we can safely remove it. - del self._contexts[context_id] - - # Append some silence between sentences. - silence = b"\x00" * self.sample_rate - frame = TTSAudioRawFrame( - audio=silence, sample_rate=self.sample_rate, num_channels=1 - ) - await self.push_frame(frame) - else: - running = False - - self._contexts_queue.task_done() - - async def _handle_audio_context(self, context_id: str): - # If we don't receive any audio during this time, we consider the context finished. - AUDIO_CONTEXT_TIMEOUT = 3.0 - queue = self._contexts[context_id] - running = True - while running: - try: - frame = await asyncio.wait_for(queue.get(), timeout=AUDIO_CONTEXT_TIMEOUT) - if frame: - await self.push_frame(frame) - running = frame is not None - except asyncio.TimeoutError: - # We didn't get audio, so let's consider this context finished. - logger.trace(f"{self} time out on audio context {context_id}") - break + await self._disconnect() def can_generate_metrics(self) -> bool: """Check if this service can generate processing metrics. From 15067c678d00213aa2a2ee7dbb862dbd0e3c54a2 Mon Sep 17 00:00:00 2001 From: Ashot Date: Wed, 7 Jan 2026 21:42:30 +0400 Subject: [PATCH 0052/1060] adapt Async TTS to updated AudioContextTTSService --- src/pipecat/services/asyncai/tts.py | 22 ++++++++++++++-------- 1 file changed, 14 insertions(+), 8 deletions(-) diff --git a/src/pipecat/services/asyncai/tts.py b/src/pipecat/services/asyncai/tts.py index 05ba18654..04a847955 100644 --- a/src/pipecat/services/asyncai/tts.py +++ b/src/pipecat/services/asyncai/tts.py @@ -28,7 +28,7 @@ from pipecat.frames.frames import ( TTSStoppedFrame, ) from pipecat.processors.frame_processor import FrameDirection -from pipecat.services.tts_service import AudioContextTTSService, WebsocketTTSService, TTSService +from pipecat.services.tts_service import AudioContextTTSService, TTSService from pipecat.transcriptions.language import Language, resolve_language from pipecat.utils.tracing.service_decorators import traced_tts @@ -73,7 +73,7 @@ def language_to_async_language(language: Language) -> Optional[str]: return resolve_language(language, LANGUAGE_MAP, use_base_code=True) -class AsyncAITTSService(AudioContextTTSService, WebsocketTTSService): +class AsyncAITTSService(AudioContextTTSService): """Async TTS service with WebSocket streaming. Provides text-to-speech using Async's streaming WebSocket API. @@ -153,7 +153,7 @@ class AsyncAITTSService(AudioContextTTSService, WebsocketTTSService): self._receive_task = None self._keepalive_task = None self._started = False - + async def start(self, frame: StartFrame): """Start the Async TTS service. @@ -337,7 +337,10 @@ class AsyncAITTSService(AudioContextTTSService, WebsocketTTSService): try: if self._websocket and self._websocket.state is State.OPEN: if self._context_id: - keepalive_message = {"transcript": " ", "context_id": self._context_id,} + keepalive_message = { + "transcript": " ", + "context_id": self._context_id, + } logger.trace("Sending keepalive message") else: # It's possible to have a user interruption which clears the context @@ -358,7 +361,9 @@ class AsyncAITTSService(AudioContextTTSService, WebsocketTTSService): if self._context_id and self._websocket: try: await self._websocket.send( - json.dumps({"context_id": self._context_id, "close_context": True, "transcript": ""}) + json.dumps( + {"context_id": self._context_id, "close_context": True, "transcript": ""} + ) ) except Exception as e: logger.error(f"Error closing context on interruption: {e}") @@ -381,7 +386,7 @@ class AsyncAITTSService(AudioContextTTSService, WebsocketTTSService): if not self._websocket or self._websocket.state is State.CLOSED: await self._connect() - try: + try: if not self._started: await self.start_ttfb_metrics() yield TTSStartedFrame() @@ -401,7 +406,7 @@ class AsyncAITTSService(AudioContextTTSService, WebsocketTTSService): if self._websocket and self._context_id: msg = self._build_msg(text=text, force=True, context_id=self._context_id) await self._get_websocket().send(msg) - + except Exception as e: logger.error(f"{self} error sending message: {e}") yield TTSStoppedFrame() @@ -409,7 +414,8 @@ class AsyncAITTSService(AudioContextTTSService, WebsocketTTSService): return yield None except Exception as e: - logger.error(f"{self} exception: {e}") + logger.error(f"{self} exception: {e}") + class AsyncAIHttpTTSService(TTSService): """HTTP-based Async TTS service. From c4ae4025f3bc28d8a65e8ffc118fda7104500f77 Mon Sep 17 00:00:00 2001 From: Ashot Date: Wed, 14 Jan 2026 16:33:30 +0400 Subject: [PATCH 0053/1060] Adjustments of Async TTS for multicontext websocket support --- src/pipecat/services/asyncai/tts.py | 87 +++++++++++++---------------- 1 file changed, 40 insertions(+), 47 deletions(-) diff --git a/src/pipecat/services/asyncai/tts.py b/src/pipecat/services/asyncai/tts.py index 04a847955..fbc760562 100644 --- a/src/pipecat/services/asyncai/tts.py +++ b/src/pipecat/services/asyncai/tts.py @@ -9,9 +9,9 @@ import asyncio import base64 import json -from typing import AsyncGenerator, Optional, Dict - import uuid +from typing import AsyncGenerator, Optional + import aiohttp from loguru import logger from pydantic import BaseModel @@ -127,10 +127,6 @@ class AsyncAITTSService(AudioContextTTSService): **kwargs, ) - self._contexts: Dict[str, asyncio.Queue] = {} - self._audio_context_task = None - self._context_id = None - params = params or AsyncAITTSService.InputParams() self._api_key = api_key @@ -153,6 +149,30 @@ class AsyncAITTSService(AudioContextTTSService): self._receive_task = None self._keepalive_task = None self._started = False + self._context_id = None + + def can_generate_metrics(self) -> bool: + """Check if this service can generate processing metrics. + + Returns: + True, as Async service supports metrics generation. + """ + return True + + def language_to_service_language(self, language: Language) -> Optional[str]: + """Convert a Language enum to Async language format. + + Args: + language: The language to convert. + + Returns: + The Async-specific language code, or None if not supported. + """ + return language_to_async_language(language) + + def _build_msg(self, text: str = "", context_id: str = "", force: bool = False) -> str: + msg = {"transcript": text, "context_id": context_id, "force": force} + return json.dumps(msg) async def start(self, frame: StartFrame): """Start the Async TTS service. @@ -182,29 +202,6 @@ class AsyncAITTSService(AudioContextTTSService): await super().cancel(frame) await self._disconnect() - def can_generate_metrics(self) -> bool: - """Check if this service can generate processing metrics. - - Returns: - True, as Async service supports metrics generation. - """ - return True - - def language_to_service_language(self, language: Language) -> Optional[str]: - """Convert a Language enum to Async language format. - - Args: - language: The language to convert. - - Returns: - The Async-specific language code, or None if not supported. - """ - return language_to_async_language(language) - - def _build_msg(self, text: str = "", context_id: str = "", force: bool = False) -> str: - msg = {"transcript": text, "context_id": context_id, "force": force} - return json.dumps(msg) - async def _connect(self): await super()._connect() @@ -264,7 +261,7 @@ class AsyncAITTSService(AudioContextTTSService): await self._websocket.close() logger.debug("Disconnected from Async") except Exception as e: - logger.error(f"{self} error closing websocket: {e}") + await self.push_error(error_msg=f"Unknown error occurred: {e}", exception=e) finally: self._websocket = None self._context_id = None @@ -338,7 +335,7 @@ class AsyncAITTSService(AudioContextTTSService): if self._websocket and self._websocket.state is State.OPEN: if self._context_id: keepalive_message = { - "transcript": " ", + "transcript": " ", "context_id": self._context_id, } logger.trace("Sending keepalive message") @@ -397,24 +394,22 @@ class AsyncAITTSService(AudioContextTTSService): if not self.audio_context_available(self._context_id): await self.create_audio_context(self._context_id) - msg = self._build_msg(text=" ", context_id=self._context_id) - await self._get_websocket().send(msg) msg = self._build_msg(text=text, force=True, context_id=self._context_id) await self._get_websocket().send(msg) await self.start_tts_usage_metrics(text) else: if self._websocket and self._context_id: msg = self._build_msg(text=text, force=True, context_id=self._context_id) - await self._get_websocket().send(msg) + await self._get_websocket().send(msg) except Exception as e: - logger.error(f"{self} error sending message: {e}") + yield ErrorFrame(error=f"Unknown error occurred: {e}") yield TTSStoppedFrame() self._started = False return yield None except Exception as e: - logger.error(f"{self} exception: {e}") + yield ErrorFrame(error=f"Unknown error occurred: {e}") class AsyncAIHttpTTSService(TTSService): @@ -526,9 +521,9 @@ class AsyncAIHttpTTSService(TTSService): """ logger.debug(f"{self}: Generating TTS [{text}]") - first_byte_seen = False try: voice_config = {"mode": "id", "id": self._voice_id} + await self.start_ttfb_metrics() payload = { "model_id": self._model_name, "transcript": text, @@ -536,6 +531,7 @@ class AsyncAIHttpTTSService(TTSService): "output_format": self._settings["output_format"], "language": self._settings["language"], } + yield TTSStartedFrame() headers = { "version": self._api_version, "x-api-key": self._api_key, @@ -543,8 +539,6 @@ class AsyncAIHttpTTSService(TTSService): } url = f"{self._base_url}/text_to_speech/streaming" - yield TTSStartedFrame() - await self.start_ttfb_metrics() async with self._session.post(url, json=payload, headers=headers) as response: if response.status != 200: error_text = await response.text() @@ -556,23 +550,22 @@ class AsyncAIHttpTTSService(TTSService): async for chunk in response.content.iter_chunked(64 * 1024): if not chunk: continue - if not first_byte_seen: - first_byte_seen = True - await self.stop_ttfb_metrics() - await self.start_tts_usage_metrics(text) - + await self.stop_ttfb_metrics() buffer.extend(chunk) audio_data = bytes(buffer) - yield TTSAudioRawFrame( + await self.start_tts_usage_metrics(text) + + frame = TTSAudioRawFrame( audio=audio_data, sample_rate=self.sample_rate, num_channels=1, ) + yield frame + except Exception as e: await self.push_error(error_msg=f"Unknown error occurred: {e}", exception=e) finally: - if not first_byte_seen: - await self.stop_ttfb_metrics() + await self.stop_ttfb_metrics() yield TTSStoppedFrame() From cb364f3cab155d1636e586b8467d9967761affc6 Mon Sep 17 00:00:00 2001 From: Mark Backman Date: Wed, 14 Jan 2026 08:58:04 -0500 Subject: [PATCH 0054/1060] Update quickstart example for 0.0.99 --- examples/quickstart/bot.py | 28 ++++++++++++++++++++-------- 1 file changed, 20 insertions(+), 8 deletions(-) diff --git a/examples/quickstart/bot.py b/examples/quickstart/bot.py index d890b8b2c..bf75616d0 100644 --- a/examples/quickstart/bot.py +++ b/examples/quickstart/bot.py @@ -44,8 +44,11 @@ from pipecat.pipeline.pipeline import Pipeline from pipecat.pipeline.runner import PipelineRunner from pipecat.pipeline.task import PipelineParams, PipelineTask from pipecat.processors.aggregators.llm_context import LLMContext -from pipecat.processors.aggregators.llm_response_universal import LLMContextAggregatorPair -from pipecat.processors.frameworks.rtvi import RTVIConfig, RTVIObserver, RTVIProcessor +from pipecat.processors.aggregators.llm_response_universal import ( + LLMContextAggregatorPair, + LLMUserAggregatorParams, +) +from pipecat.processors.frameworks.rtvi import RTVIObserver, RTVIProcessor from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport from pipecat.services.cartesia.tts import CartesiaTTSService @@ -53,6 +56,10 @@ from pipecat.services.deepgram.stt import DeepgramSTTService from pipecat.services.openai.llm import OpenAILLMService from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams +from pipecat.turns.user_stop.turn_analyzer_user_turn_stop_strategy import ( + TurnAnalyzerUserTurnStopStrategy, +) +from pipecat.turns.user_turn_strategies import UserTurnStrategies logger.info("✅ All components loaded successfully!") @@ -79,20 +86,27 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): ] context = LLMContext(messages) - context_aggregator = LLMContextAggregatorPair(context) + user_aggregator, assistant_aggregator = LLMContextAggregatorPair( + context, + user_params=LLMUserAggregatorParams( + user_turn_strategies=UserTurnStrategies( + stop=[TurnAnalyzerUserTurnStopStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3())] + ), + ), + ) - rtvi = RTVIProcessor(config=RTVIConfig(config=[])) + rtvi = RTVIProcessor() pipeline = Pipeline( [ transport.input(), # Transport user input rtvi, # RTVI processor stt, - context_aggregator.user(), # User responses + user_aggregator, # User responses llm, # LLM tts, # TTS transport.output(), # Transport bot output - context_aggregator.assistant(), # Assistant spoken responses + assistant_aggregator, # Assistant spoken responses ] ) @@ -130,13 +144,11 @@ async def bot(runner_args: RunnerArguments): audio_in_enabled=True, audio_out_enabled=True, vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), - turn_analyzer=LocalSmartTurnAnalyzerV3(), ), "webrtc": lambda: TransportParams( audio_in_enabled=True, audio_out_enabled=True, vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), - turn_analyzer=LocalSmartTurnAnalyzerV3(), ), } From 4aaff04fb3964274782241fb38292190fb78e0ad Mon Sep 17 00:00:00 2001 From: Mark Backman Date: Wed, 14 Jan 2026 09:43:17 -0500 Subject: [PATCH 0055/1060] Add PR 3392 to changelog, linting cleanup --- CHANGELOG.md | 249 +++++++++++++++++++++++++++------------------------ 1 file changed, 134 insertions(+), 115 deletions(-) diff --git a/CHANGELOG.md b/CHANGELOG.md index 3d583b4e1..f874df5e9 100644 --- a/CHANGELOG.md +++ b/CHANGELOG.md @@ -24,39 +24,40 @@ and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0 A list of strategies can be specified for both strategies; strategies are evaluated in order until one evaluates to true. - Available user turn start strategies: - - VADUserTurnStartStrategy - - TranscriptionUserTurnStartStrategy - - MinWordsUserTurnStartStrategy - - ExternalUserTurnStartStrategy + Available user turn start strategies: - Available user turn stop strategies: - - TranscriptionUserTurnStopStrategy - - TurnAnalyzerUserTurnStopStrategy - - ExternalUserTurnStopStrategy + - VADUserTurnStartStrategy + - TranscriptionUserTurnStartStrategy + - MinWordsUserTurnStartStrategy + - ExternalUserTurnStartStrategy - The default strategies are: + Available user turn stop strategies: - - start: [VADUserTurnStartStrategy, TranscriptionUserTurnStartStrategy] - - stop: [TranscriptionUserTurnStopStrategy] + - TranscriptionUserTurnStopStrategy + - TurnAnalyzerUserTurnStopStrategy + - ExternalUserTurnStopStrategy - urn strategies are configured when setting up `LLMContextAggregatorPair`. + The default strategies are: + + - start: [VADUserTurnStartStrategy, TranscriptionUserTurnStartStrategy] + - stop: [TranscriptionUserTurnStopStrategy] + + Turn strategies are configured when setting up `LLMContextAggregatorPair`. For example: - ```python - context_aggregator = LLMContextAggregatorPair( - context, - user_params=LLMUserAggregatorParams( - user_turn_strategies=UserTurnStrategies( - stop=[ - TurnAnalyzerUserTurnStopStrategy( -turn_analyzer=LocalSmartTurnAnalyzerV3(params=SmartTurnParams()) - ) - ], - ) - ), - ) - ``` + ```python + context_aggregator = LLMContextAggregatorPair( + context, + user_params=LLMUserAggregatorParams( + user_turn_strategies=UserTurnStrategies( + stop=[ + TurnAnalyzerUserTurnStopStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3(params=SmartTurnParams()) + ) + ], + ) + ), + ) + ``` In order to use the user turn strategies you must update to the new universal `LLMContext` and `LLMContextAggregatorPair`. @@ -69,13 +70,13 @@ turn_analyzer=LocalSmartTurnAnalyzerV3(params=SmartTurnParams()) - Added `GrokRealtimeLLMService` for xAI's Grok Voice Agent API with real-time voice conversations: - - Support for real-time audio streaming with WebSocket connection - - Built-in server-side VAD (Voice Activity Detection) - - Multiple voice options: Ara, Rex, Sal, Eve, Leo - - Built-in tools support: web_search, x_search, file_search - - Custom function calling with standard Pipecat tools schema - - Configurable audio formats (PCM at 8kHz-48kHz) - (PR [#3267](https://github.com/pipecat-ai/pipecat/pull/3267)) + - Support for real-time audio streaming with WebSocket connection + - Built-in server-side VAD (Voice Activity Detection) + - Multiple voice options: Ara, Rex, Sal, Eve, Leo + - Built-in tools support: web_search, x_search, file_search + - Custom function calling with standard Pipecat tools schema + - Configurable audio formats (PCM at 8kHz-48kHz) + (PR [#3267](https://github.com/pipecat-ai/pipecat/pull/3267)) - Added an approximation of TTFB for Ultravox. (PR [#3268](https://github.com/pipecat-ai/pipecat/pull/3268)) @@ -86,11 +87,12 @@ turn_analyzer=LocalSmartTurnAnalyzerV3(params=SmartTurnParams()) (PR [#3289](https://github.com/pipecat-ai/pipecat/pull/3289)) - `LLMUserAggregator` now exposes the following events: - - `on_user_turn_started`: triggered when a user turn starts - - `on_user_turn_stopped`: triggered when a user turn ends - - `on_user_turn_stop_timeout`: triggered when a user turn does not stop - and times out - (PR [#3291](https://github.com/pipecat-ai/pipecat/pull/3291)) + + - `on_user_turn_started`: triggered when a user turn starts + - `on_user_turn_stopped`: triggered when a user turn ends + - `on_user_turn_stop_timeout`: triggered when a user turn does not stop + and times out + (PR [#3291](https://github.com/pipecat-ai/pipecat/pull/3291)) - Introducing user mute strategies. User mute strategies indicate when user input should be muted based on the current system state. @@ -104,12 +106,12 @@ turn_analyzer=LocalSmartTurnAnalyzerV3(params=SmartTurnParams()) frame is muted if any of the configured strategies indicates it should be muted. - Available user mute strategies: + Available user mute strategies: - * `FirstSpeechUserMuteStrategy` - * `MuteUntilFirstBotCompleteUserMuteStrategy` - * `AlwaysUserMuteStrategy` - * `FunctionCallUserMuteStrategy` + - `FirstSpeechUserMuteStrategy` + - `MuteUntilFirstBotCompleteUserMuteStrategy` + - `AlwaysUserMuteStrategy` + - `FunctionCallUserMuteStrategy` User mute strategies replace the legacy `STTMuteFilter` and provide a more flexible and composable approach to muting user input. @@ -117,16 +119,16 @@ turn_analyzer=LocalSmartTurnAnalyzerV3(params=SmartTurnParams()) User mute strategies are configured when setting up the `LLMContextAggregatorPair`. For example: - ```python - context_aggregator = LLMContextAggregatorPair( - context, - user_params=LLMUserAggregatorParams( - user_mute_strategies=[ - FirstSpeechUserMuteStrategy(), - ] - ), - ) - ``` + ```python + context_aggregator = LLMContextAggregatorPair( + context, + user_params=LLMUserAggregatorParams( + user_mute_strategies=[ + FirstSpeechUserMuteStrategy(), + ] + ), + ) + ``` In order to use user mute strategies you should update to the new universal `LLMContext` and `LLMContextAggregatorPair`. @@ -159,16 +161,17 @@ turn_analyzer=LocalSmartTurnAnalyzerV3(params=SmartTurnParams()) (PR [#3357](https://github.com/pipecat-ai/pipecat/pull/3357)) - Added image support to `OpenAIRealtimeLLMService` via `InputImageRawFrame`: - - New `start_video_paused` parameter to control initial video input state - - New `video_frame_detail` parameter to set image processing quality - ("auto", - "low", or "high"). This corresponds to OpenAI Realtime's `image_detail` - parameter. - - `set_video_input_paused()` method to pause/resume video input at runtime - - `set_video_frame_detail()` method to adjust video frame quality - dynamically - - Automatic rate limiting (1 frame per second) to prevent API overload - (PR [#3360](https://github.com/pipecat-ai/pipecat/pull/3360)) + + - New `start_video_paused` parameter to control initial video input state + - New `video_frame_detail` parameter to set image processing quality + ("auto", + "low", or "high"). This corresponds to OpenAI Realtime's `image_detail` + parameter. + - `set_video_input_paused()` method to pause/resume video input at runtime + - `set_video_frame_detail()` method to adjust video frame quality + dynamically + - Automatic rate limiting (1 frame per second) to prevent API overload + (PR [#3360](https://github.com/pipecat-ai/pipecat/pull/3360)) - Added `UserTurnProcessor`, a frame processor built on `UserTurnController` that pushes `UserStartedSpeakingFrame` and `UserStoppedSpeakingFrame` frames @@ -188,11 +191,12 @@ turn_analyzer=LocalSmartTurnAnalyzerV3(params=SmartTurnParams()) (PR [#3374](https://github.com/pipecat-ai/pipecat/pull/3374)) - `LLMAssistantAggregator` now exposes the following events: - - `on_assistant_turn_started`: triggered when the assistant turn starts - - `on_assistant_turn_stopped`: triggered when the assistant turn ends - - `on_assistant_thought`: triggered when there's an assistant thought - available - (PR [#3385](https://github.com/pipecat-ai/pipecat/pull/3385)) + + - `on_assistant_turn_started`: triggered when the assistant turn starts + - `on_assistant_turn_stopped`: triggered when the assistant turn ends + - `on_assistant_thought`: triggered when there's an assistant thought + available + (PR [#3385](https://github.com/pipecat-ai/pipecat/pull/3385)) - Added `KrispVivaTurn` analyzer for end of turn detection using the Krisp VIVA SDK (requires `krisp_audio`). @@ -202,13 +206,14 @@ turn_analyzer=LocalSmartTurnAnalyzerV3(params=SmartTurnParams()) register custom pipeline task setup files by setting the `PIPECAT_SETUP_FILES` environment variable. This variable should contain a colon-separated list of Python files (e.g. `export - PIPECAT_SETUP_FILES="setup1.py:setup.py:..."`). Each file must define a +PIPECAT_SETUP_FILES="setup1.py:setup.py:..."`). Each file must define a function with the following signature: - ```python - async def setup_pipeline_task(task: PipelineTask): - ... - ``` + ```python + async def setup_pipeline_task(task: PipelineTask): + ... + ``` + (PR [#3397](https://github.com/pipecat-ai/pipecat/pull/3397)) - Added a keepalive task for `InworldTTSService` to keep the service connected @@ -238,12 +243,14 @@ turn_analyzer=LocalSmartTurnAnalyzerV3(params=SmartTurnParams()) - Updated `ElevenLabsRealtimeSTTService` to accept the `include_language_detection` parameter to detect language. - ```python - stt = ElevenLabsRealtimeSTTService( - api_key=os.getenv("ELEVENLABS_API_KEY"), - include_language_detection=True - ) - ``` + + ```python + stt = ElevenLabsRealtimeSTTService( + api_key=os.getenv("ELEVENLABS_API_KEY"), + include_language_detection=True + ) + ``` + (PR [#3216](https://github.com/pipecat-ai/pipecat/pull/3216)) - Updated `SpeechmaticsSTTService` to use new Python Voice SDK with improved @@ -251,16 +258,18 @@ turn_analyzer=LocalSmartTurnAnalyzerV3(params=SmartTurnParams()) without any impact on accuracy. Use the `turn_detection_mode` parameter to control the endpointing of speech, with `TurnDetectionMode.EXTERNAL` (default), `TurnDetectionMode.ADAPTIVE`, or `TurnDetectionMode.SMART_TURN`. - ```python + + ```python stt = SpeechmaticsSTTService( api_key=os.getenv("SPEECHMATICS_API_KEY"), params=SpeechmaticsSTTService.InputParams( language=Language.EN, -turn_detection_mode=SpeechmaticsSTTService.TurnDetectionMode.ADAPTIVE, + turn_detection_mode=SpeechmaticsSTTService.TurnDetectionMode.ADAPTIVE, speaker_active_format="<{speaker_id}>{text}", ), ) - ``` + ``` + (PR [#3225](https://github.com/pipecat-ai/pipecat/pull/3225)) - `daily-python` updated to 0.23.0. @@ -273,10 +282,15 @@ turn_detection_mode=SpeechmaticsSTTService.TurnDetectionMode.ADAPTIVE, - Updates to Inworld TTS services: - - Improved `InworldTTSService`'s websocket implementation to better flush - and close context to better handle long inputs. - - Improved docstrings for `InworldTTSService` and `InworldHttpTTSService`. - (PR [#3288](https://github.com/pipecat-ai/pipecat/pull/3288)) + - Improved `InworldTTSService`'s websocket implementation to better flush + and close context to better handle long inputs. + - Improved docstrings for `InworldTTSService` and `InworldHttpTTSService`. + (PR [#3288](https://github.com/pipecat-ai/pipecat/pull/3288)) + +- Improved the error handling and reconnection logic for `WebsocketServer` by + distinguishing between errors when disconnecting and websocket communication + errors. + (PR [#3392](https://github.com/pipecat-ai/pipecat/pull/3392)) - Updated `DeepgramSTTService` to push user started/stopped speaking and interruption frames when `vad_enabled` is set to true. This centralizes the @@ -308,7 +322,8 @@ turn_detection_mode=SpeechmaticsSTTService.TurnDetectionMode.ADAPTIVE, - Smart Turn now takes into account `vad_start_seconds` when buffering audio, meaning that the start of the turn audio is not cut off. This improves accuracy for short utterances. - - The default value of `pre_speech_ms` is now set to 500ms for Smart Turn. + +- The default value of `pre_speech_ms` is now set to 500ms for Smart Turn. (PR [#3377](https://github.com/pipecat-ai/pipecat/pull/3377)) - Improved Krisp SDK management to allow `KrispVivaTurn` and `KrispVivaFilter` @@ -376,17 +391,18 @@ turn_detection_mode=SpeechmaticsSTTService.TurnDetectionMode.ADAPTIVE, From the developer's point of view, switching to using `LLMContext` machinery will usually be a matter of going from this: - ```python - context = OpenAILLMContext(messages, tools) - context_aggregator = llm.create_context_aggregator(context) - ``` + ```python + context = OpenAILLMContext(messages, tools) + context_aggregator = llm.create_context_aggregator(context) + ``` - To this: + To this: + + ``` + context = LLMContext(messages, tools) + context_aggregator = LLMContextAggregatorPair(context) + ``` - ``` - context = LLMContext(messages, tools) - context_aggregator = LLMContextAggregatorPair(context) - ``` (PR [#3263](https://github.com/pipecat-ai/pipecat/pull/3263)) - `STTMuteFilter` is deprecated and will be removed in a future version. Use @@ -401,16 +417,17 @@ turn_detection_mode=SpeechmaticsSTTService.TurnDetectionMode.ADAPTIVE, `LLMUserAggregator`'s new parameter `user_turn_strategies` instead. For example, to disable interruptions but still get user turns you can do: - ```python - context_aggregator = LLMContextAggregatorPair( - context, - user_params=LLMUserAggregatorParams( - user_turn_strategies=UserTurnStrategies( -start=[TranscriptionUserTurnStartStrategy(enable_interruptions=False)], - ), - ), - ) - ``` + ```python + context_aggregator = LLMContextAggregatorPair( + context, + user_params=LLMUserAggregatorParams( + user_turn_strategies=UserTurnStrategies( + start=[TranscriptionUserTurnStartStrategy(enable_interruptions=False)], + ), + ), + ) + ``` + (PR [#3297](https://github.com/pipecat-ai/pipecat/pull/3297)) - `TranscriptProcessor` and related data classes and frames @@ -433,7 +450,8 @@ start=[TranscriptionUserTurnStartStrategy(enable_interruptions=False)], ### Fixed - Improved error handling in `ElevenLabsRealtimeSTTService` - - Fixed an issue in `ElevenLabsRealtimeSTTService` causing an infinite loop + +- Fixed an issue in `ElevenLabsRealtimeSTTService` causing an infinite loop that blocks the process if the websocket disconnects due to an error (PR [#3233](https://github.com/pipecat-ai/pipecat/pull/3233)) @@ -446,13 +464,14 @@ start=[TranscriptionUserTurnStartStrategy(enable_interruptions=False)], (PR [#3322](https://github.com/pipecat-ai/pipecat/pull/3322)) - Updated `SpeechmaticsSTTService` for version `0.0.99+`: - - Fixed `SpeechmaticsSTTService` to listen for `VADUserStoppedSpeakingFrame` - in order to finalize transcription. - - Default to `TurnDetectionMode.FIXED` for Pipecat-controlled end of turn - detection. - - Only emit VAD + interruption frames if VAD is enabled within the plugin - (modes other than `TurnDetectionMode.FIXED` or `TurnDetectionMode.EXTERNAL`). - (PR [#3328](https://github.com/pipecat-ai/pipecat/pull/3328)) + + - Fixed `SpeechmaticsSTTService` to listen for `VADUserStoppedSpeakingFrame` + in order to finalize transcription. + - Default to `TurnDetectionMode.FIXED` for Pipecat-controlled end of turn + detection. + - Only emit VAD + interruption frames if VAD is enabled within the plugin + (modes other than `TurnDetectionMode.FIXED` or `TurnDetectionMode.EXTERNAL`). + (PR [#3328](https://github.com/pipecat-ai/pipecat/pull/3328)) - Fixed an issue with function calling where a handler failing to invoke its result callback could leave the context stuck in IN_PROGRESS, causing LLM From e33172c44e81b770ebbd08ac48f3a76897c1bf28 Mon Sep 17 00:00:00 2001 From: Paul Kompfner Date: Wed, 14 Jan 2026 11:04:24 -0500 Subject: [PATCH 0056/1060] Add PR 3420 to CHANGELOG (it was missing) --- CHANGELOG.md | 4 ++++ 1 file changed, 4 insertions(+) diff --git a/CHANGELOG.md b/CHANGELOG.md index f874df5e9..ce2bdef9f 100644 --- a/CHANGELOG.md +++ b/CHANGELOG.md @@ -450,6 +450,7 @@ PIPECAT_SETUP_FILES="setup1.py:setup.py:..."`). Each file must define a ### Fixed - Improved error handling in `ElevenLabsRealtimeSTTService` + (PR [#3233](https://github.com/pipecat-ai/pipecat/pull/3233)) - Fixed an issue in `ElevenLabsRealtimeSTTService` causing an infinite loop that blocks the process if the websocket disconnects due to an error @@ -500,6 +501,9 @@ PIPECAT_SETUP_FILES="setup1.py:setup.py:..."`). Each file must define a guard was set. (PR [#3400](https://github.com/pipecat-ai/pipecat/pull/3400)) +- Fixed parallel function calling when using Gemini thinking. + (PR [3420](https://github.com/pipecat-ai/pipecat/pull/3420)) + - Fixed an issue in `traced_llm` where `model_name` in OpenTelemetry appears as `unknown`. (PR [#3422](https://github.com/pipecat-ai/pipecat/pull/3422)) From e107902b14b05e022a554b444d24c21e2b5202d3 Mon Sep 17 00:00:00 2001 From: Paul Kompfner Date: Wed, 14 Jan 2026 18:40:07 -0500 Subject: [PATCH 0057/1060] Do a consistency pass on how we're sending `UserStartedSpeakingFrame`s and `UserStoppedSpeakingFrame`s. The codebase is now consistent in broadcasting both types of frames up and downstream. --- examples/foundational/22b-natural-conversation-proposal.py | 2 +- examples/foundational/22c-natural-conversation-mixed-llms.py | 2 +- .../foundational/22d-natural-conversation-gemini-audio.py | 2 +- src/pipecat/services/aws/nova_sonic/llm.py | 4 ++-- src/pipecat/services/deepgram/flux/stt.py | 3 +-- src/pipecat/services/grok/realtime/llm.py | 2 +- src/pipecat/services/openai/realtime/llm.py | 2 +- src/pipecat/services/openai_realtime_beta/openai.py | 2 +- 8 files changed, 9 insertions(+), 10 deletions(-) diff --git a/examples/foundational/22b-natural-conversation-proposal.py b/examples/foundational/22b-natural-conversation-proposal.py index 256a6c9df..9a6d22494 100644 --- a/examples/foundational/22b-natural-conversation-proposal.py +++ b/examples/foundational/22b-natural-conversation-proposal.py @@ -119,7 +119,7 @@ class CompletenessCheck(FrameProcessor): if isinstance(frame, TextFrame) and frame.text == "YES": logger.debug("Completeness check YES") - await self.push_frame(UserStoppedSpeakingFrame()) + await self.broadcast_frame(UserStoppedSpeakingFrame) await self._notifier.notify() elif isinstance(frame, TextFrame) and frame.text == "NO": logger.debug("Completeness check NO") diff --git a/examples/foundational/22c-natural-conversation-mixed-llms.py b/examples/foundational/22c-natural-conversation-mixed-llms.py index bdb557594..935aa5e36 100644 --- a/examples/foundational/22c-natural-conversation-mixed-llms.py +++ b/examples/foundational/22c-natural-conversation-mixed-llms.py @@ -322,7 +322,7 @@ class CompletenessCheck(FrameProcessor): if isinstance(frame, TextFrame) and frame.text == "YES": logger.debug("!!! Completeness check YES") - await self.push_frame(UserStoppedSpeakingFrame()) + await self.broadcast_frame(UserStoppedSpeakingFrame) await self._notifier.notify() elif isinstance(frame, TextFrame) and frame.text == "NO": logger.debug("!!! Completeness check NO") diff --git a/examples/foundational/22d-natural-conversation-gemini-audio.py b/examples/foundational/22d-natural-conversation-gemini-audio.py index b144f485e..4a7c33a39 100644 --- a/examples/foundational/22d-natural-conversation-gemini-audio.py +++ b/examples/foundational/22d-natural-conversation-gemini-audio.py @@ -451,7 +451,7 @@ class CompletenessCheck(FrameProcessor): logger.debug("Completeness check YES") if self._idle_task: await self.cancel_task(self._idle_task) - await self.push_frame(UserStoppedSpeakingFrame()) + await self.broadcast_frame(UserStoppedSpeakingFrame) await self._audio_accumulator.reset() await self._notifier.notify() elif isinstance(frame, TextFrame): diff --git a/src/pipecat/services/aws/nova_sonic/llm.py b/src/pipecat/services/aws/nova_sonic/llm.py index 26afc79cf..14ebde729 100644 --- a/src/pipecat/services/aws/nova_sonic/llm.py +++ b/src/pipecat/services/aws/nova_sonic/llm.py @@ -1187,7 +1187,7 @@ class AWSNovaSonicLLMService(LLMService): logger.debug( "Wrapping assistant response trigger transcription with upstream UserStarted/StoppedSpeakingFrames" ) - await self.push_frame(UserStartedSpeakingFrame(), direction=FrameDirection.UPSTREAM) + await self.broadcast_frame(UserStartedSpeakingFrame) # Send the transcription upstream for the user context aggregator frame = TranscriptionFrame( @@ -1197,7 +1197,7 @@ class AWSNovaSonicLLMService(LLMService): # Finish wrapping the upstream transcription in UserStarted/StoppedSpeakingFrames if needed if should_wrap_in_user_started_stopped_speaking_frames: - await self.push_frame(UserStoppedSpeakingFrame(), direction=FrameDirection.UPSTREAM) + await self.broadcast_frame(UserStoppedSpeakingFrame) # Clear out the buffered user text self._user_text_buffer = "" diff --git a/src/pipecat/services/deepgram/flux/stt.py b/src/pipecat/services/deepgram/flux/stt.py index 13b72bcf7..35b00af65 100644 --- a/src/pipecat/services/deepgram/flux/stt.py +++ b/src/pipecat/services/deepgram/flux/stt.py @@ -676,8 +676,7 @@ class DeepgramFluxSTTService(WebsocketSTTService): await self._handle_transcription(transcript, True, self._language) await self.stop_processing_metrics() - await self.push_frame(UserStoppedSpeakingFrame(), FrameDirection.DOWNSTREAM) - await self.push_frame(UserStoppedSpeakingFrame(), FrameDirection.UPSTREAM) + await self.broadcast_frame(UserStoppedSpeakingFrame) await self._call_event_handler("on_end_of_turn", transcript) async def _handle_eager_end_of_turn(self, transcript: str, data: Dict[str, Any]): diff --git a/src/pipecat/services/grok/realtime/llm.py b/src/pipecat/services/grok/realtime/llm.py index cbf9b4d5c..bcd701cd3 100644 --- a/src/pipecat/services/grok/realtime/llm.py +++ b/src/pipecat/services/grok/realtime/llm.py @@ -659,7 +659,7 @@ class GrokRealtimeLLMService(LLMService): """Handle speech stopped event from VAD.""" await self.start_ttfb_metrics() await self.start_processing_metrics() - await self.push_frame(UserStoppedSpeakingFrame()) + await self.broadcast_frame(UserStoppedSpeakingFrame) async def _handle_evt_error(self, evt): """Handle error event.""" diff --git a/src/pipecat/services/openai/realtime/llm.py b/src/pipecat/services/openai/realtime/llm.py index 598d4f510..7c48d7e34 100644 --- a/src/pipecat/services/openai/realtime/llm.py +++ b/src/pipecat/services/openai/realtime/llm.py @@ -776,7 +776,7 @@ class OpenAIRealtimeLLMService(LLMService): async def _handle_evt_speech_stopped(self, evt): await self.start_ttfb_metrics() await self.start_processing_metrics() - await self.push_frame(UserStoppedSpeakingFrame()) + await self.broadcast_frame(UserStoppedSpeakingFrame) async def _maybe_handle_evt_retrieve_conversation_item_error(self, evt: events.ErrorEvent): """Maybe handle an error event related to retrieving a conversation item. diff --git a/src/pipecat/services/openai_realtime_beta/openai.py b/src/pipecat/services/openai_realtime_beta/openai.py index bea26c3e6..128bcc93a 100644 --- a/src/pipecat/services/openai_realtime_beta/openai.py +++ b/src/pipecat/services/openai_realtime_beta/openai.py @@ -662,7 +662,7 @@ class OpenAIRealtimeBetaLLMService(LLMService): async def _handle_evt_speech_stopped(self, evt): await self.start_ttfb_metrics() await self.start_processing_metrics() - await self.push_frame(UserStoppedSpeakingFrame()) + await self.broadcast_frame(UserStoppedSpeakingFrame) async def _maybe_handle_evt_retrieve_conversation_item_error(self, evt: events.ErrorEvent): """Maybe handle an error event related to retrieving a conversation item. From f3993f177506cd952930e077ce5eb5a1b725bb54 Mon Sep 17 00:00:00 2001 From: Mark Backman Date: Wed, 14 Jan 2026 20:01:50 -0500 Subject: [PATCH 0058/1060] fix to make on_user_turn_stop_timeout work with ExternalUserTurnStrategies --- changelog/3454.fixed.md | 1 + src/pipecat/turns/user_turn_controller.py | 28 +++++++++--- tests/test_user_turn_controller.py | 54 ++++++++++++++++++++++- 3 files changed, 77 insertions(+), 6 deletions(-) create mode 100644 changelog/3454.fixed.md diff --git a/changelog/3454.fixed.md b/changelog/3454.fixed.md new file mode 100644 index 000000000..0269370d7 --- /dev/null +++ b/changelog/3454.fixed.md @@ -0,0 +1 @@ +- Fixed an issue where `on_user_turn_stop_timeout` could fire while a user is talking when using `ExternalUserTurnStrategies`. diff --git a/src/pipecat/turns/user_turn_controller.py b/src/pipecat/turns/user_turn_controller.py index a9b267ae0..56b6ad711 100644 --- a/src/pipecat/turns/user_turn_controller.py +++ b/src/pipecat/turns/user_turn_controller.py @@ -12,6 +12,8 @@ from typing import Optional, Type from pipecat.frames.frames import ( Frame, TranscriptionFrame, + UserStartedSpeakingFrame, + UserStoppedSpeakingFrame, VADUserStartedSpeakingFrame, VADUserStoppedSpeakingFrame, ) @@ -80,7 +82,7 @@ class UserTurnController(BaseObject): self._task_manager: Optional[BaseTaskManager] = None - self._vad_user_speaking = False + self._user_speaking = False self._user_turn = False self._user_turn_stop_timeout_event = asyncio.Event() @@ -146,7 +148,11 @@ class UserTurnController(BaseObject): frame: The frame to be processed. """ - if isinstance(frame, VADUserStartedSpeakingFrame): + if isinstance(frame, UserStartedSpeakingFrame): + await self._handle_user_started_speaking(frame) + elif isinstance(frame, UserStoppedSpeakingFrame): + await self._handle_user_stopped_speaking(frame) + elif isinstance(frame, VADUserStartedSpeakingFrame): await self._handle_vad_user_started_speaking(frame) elif isinstance(frame, VADUserStoppedSpeakingFrame): await self._handle_vad_user_stopped_speaking(frame) @@ -179,14 +185,26 @@ class UserTurnController(BaseObject): for s in self._user_turn_strategies.stop or []: await s.cleanup() + async def _handle_user_started_speaking(self, frame: UserStartedSpeakingFrame): + self._user_speaking = True + + # The user started talking, let's reset the user turn timeout. + self._user_turn_stop_timeout_event.set() + + async def _handle_user_stopped_speaking(self, frame: UserStoppedSpeakingFrame): + self._user_speaking = False + + # The user stopped talking, let's reset the user turn timeout. + self._user_turn_stop_timeout_event.set() + async def _handle_vad_user_started_speaking(self, frame: VADUserStartedSpeakingFrame): - self._vad_user_speaking = True + self._user_speaking = True # The user started talking, let's reset the user turn timeout. self._user_turn_stop_timeout_event.set() async def _handle_vad_user_stopped_speaking(self, frame: VADUserStoppedSpeakingFrame): - self._vad_user_speaking = False + self._user_speaking = False # The user stopped talking, let's reset the user turn timeout. self._user_turn_stop_timeout_event.set() @@ -260,7 +278,7 @@ class UserTurnController(BaseObject): ) self._user_turn_stop_timeout_event.clear() except asyncio.TimeoutError: - if self._user_turn and not self._vad_user_speaking: + if self._user_turn and not self._user_speaking: await self._call_event_handler("on_user_turn_stop_timeout") await self._trigger_user_turn_stop( None, UserTurnStoppedParams(enable_user_speaking_frames=True) diff --git a/tests/test_user_turn_controller.py b/tests/test_user_turn_controller.py index 6762bd219..67c1a7860 100644 --- a/tests/test_user_turn_controller.py +++ b/tests/test_user_turn_controller.py @@ -9,11 +9,13 @@ import unittest from pipecat.frames.frames import ( TranscriptionFrame, + UserStartedSpeakingFrame, + UserStoppedSpeakingFrame, VADUserStartedSpeakingFrame, VADUserStoppedSpeakingFrame, ) from pipecat.turns.user_turn_controller import UserTurnController -from pipecat.turns.user_turn_strategies import UserTurnStrategies +from pipecat.turns.user_turn_strategies import ExternalUserTurnStrategies, UserTurnStrategies from pipecat.utils.asyncio.task_manager import TaskManager, TaskManagerParams USER_TURN_STOP_TIMEOUT = 0.2 @@ -96,3 +98,53 @@ class TestUserTurnController(unittest.IsolatedAsyncioTestCase): self.assertTrue(should_start) self.assertTrue(should_stop) self.assertTrue(timeout) + + async def test_external_user_turn_strategies_no_timeout_while_speaking(self): + """Test that timeout does not trigger when user is still speaking with external strategies.""" + controller = UserTurnController( + user_turn_strategies=ExternalUserTurnStrategies(), + user_turn_stop_timeout=USER_TURN_STOP_TIMEOUT, + ) + + await controller.setup(self.task_manager) + + should_start = None + should_stop = None + timeout = None + + @controller.event_handler("on_user_turn_started") + async def on_user_turn_started(controller, strategy, params): + nonlocal should_start + should_start = True + + @controller.event_handler("on_user_turn_stopped") + async def on_user_turn_stopped(controller, strategy, params): + nonlocal should_stop + should_stop = True + + @controller.event_handler("on_user_turn_stop_timeout") + async def on_user_turn_stop_timeout(controller): + nonlocal timeout + timeout = True + + # Simulate external service (like Deepgram Flux) broadcasting UserStartedSpeakingFrame + await controller.process_frame(UserStartedSpeakingFrame()) + self.assertTrue(should_start) + self.assertFalse(should_stop) + self.assertFalse(timeout) + + # User is still speaking, timeout should not trigger + await asyncio.sleep(USER_TURN_STOP_TIMEOUT + 0.1) + self.assertTrue(should_start) + self.assertFalse(should_stop) + self.assertFalse(timeout) + + # Now external service broadcasts UserStoppedSpeakingFrame + await controller.process_frame(UserStoppedSpeakingFrame()) + + # But no transcription, so timeout should trigger + await asyncio.sleep(USER_TURN_STOP_TIMEOUT + 0.1) + + self.assertTrue(should_start) + self.assertTrue(should_stop) + self.assertTrue(timeout) From 9e705ce768be3e3635b769b76baee8cd8f1f1287 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Aleix=20Conchillo=20Flaqu=C3=A9?= Date: Wed, 14 Jan 2026 17:50:31 -0800 Subject: [PATCH 0059/1060] UserTurnController: reset user turn start strategies when turn triggered --- changelog/3455.fixed.md | 1 + src/pipecat/turns/user_turn_controller.py | 4 +++ tests/test_user_turn_controller.py | 44 +++++++++++++++++++++++ 3 files changed, 49 insertions(+) create mode 100644 changelog/3455.fixed.md diff --git a/changelog/3455.fixed.md b/changelog/3455.fixed.md new file mode 100644 index 000000000..1dba5838a --- /dev/null +++ b/changelog/3455.fixed.md @@ -0,0 +1 @@ +- Fixed an issue where user turn start strategies were not being reset after a user turn started, causing incorrect strategy behavior. diff --git a/src/pipecat/turns/user_turn_controller.py b/src/pipecat/turns/user_turn_controller.py index 56b6ad711..05cb46988 100644 --- a/src/pipecat/turns/user_turn_controller.py +++ b/src/pipecat/turns/user_turn_controller.py @@ -251,6 +251,10 @@ class UserTurnController(BaseObject): self._user_turn = True self._user_turn_stop_timeout_event.set() + # Reset all user turn start strategies to start fresh. + for s in self._user_turn_strategies.start or []: + await s.reset() + await self._call_event_handler("on_user_turn_started", strategy, params) async def _trigger_user_turn_stop( diff --git a/tests/test_user_turn_controller.py b/tests/test_user_turn_controller.py index 67c1a7860..8aa509a8a 100644 --- a/tests/test_user_turn_controller.py +++ b/tests/test_user_turn_controller.py @@ -8,12 +8,16 @@ import asyncio import unittest from pipecat.frames.frames import ( + BotStartedSpeakingFrame, TranscriptionFrame, UserStartedSpeakingFrame, UserStoppedSpeakingFrame, VADUserStartedSpeakingFrame, VADUserStoppedSpeakingFrame, ) +from pipecat.turns.user_start.min_words_user_turn_start_strategy import ( + MinWordsUserTurnStartStrategy, +) from pipecat.turns.user_turn_controller import UserTurnController from pipecat.turns.user_turn_strategies import ExternalUserTurnStrategies, UserTurnStrategies from pipecat.utils.asyncio.task_manager import TaskManager, TaskManagerParams @@ -58,6 +62,46 @@ class TestUserTurnController(unittest.IsolatedAsyncioTestCase): self.assertTrue(should_start) self.assertTrue(should_stop) + async def test_user_turn_start_reset(self): + controller = UserTurnController( + user_turn_strategies=UserTurnStrategies( + start=[MinWordsUserTurnStartStrategy(min_words=3)] + ), + user_turn_stop_timeout=USER_TURN_STOP_TIMEOUT, + ) + + await controller.setup(self.task_manager) + + should_start = 0 + + @controller.event_handler("on_user_turn_started") + async def on_user_turn_started(controller, strategy, params): + nonlocal should_start + should_start += 1 + + await controller.process_frame(BotStartedSpeakingFrame()) + await controller.process_frame(TranscriptionFrame(text="One", user_id="cat", timestamp="")) + self.assertEqual(should_start, 0) + + await controller.process_frame( + TranscriptionFrame(text=" two three!", user_id="cat", timestamp="") + ) + self.assertEqual(should_start, 1) + + # Trigger user stop turn so we can trigger user start turn again. + await asyncio.sleep(USER_TURN_STOP_TIMEOUT + 0.1) + + await controller.process_frame(BotStartedSpeakingFrame()) + await controller.process_frame( + TranscriptionFrame(text="Hello", user_id="cat", timestamp="") + ) + self.assertEqual(should_start, 1) + + await controller.process_frame( + TranscriptionFrame(text=" there friend!", user_id="cat", timestamp="") + ) + self.assertEqual(should_start, 2) + async def test_user_turn_stop_timeout_no_transcription(self): controller = UserTurnController( user_turn_strategies=UserTurnStrategies(), From efd4432cfb475f99b254549723744394b481cb8b Mon Sep 17 00:00:00 2001 From: Mark Backman Date: Thu, 15 Jan 2026 10:24:09 -0500 Subject: [PATCH 0060/1060] Renumber the 07 foundational examples --- ...-soniox.py => 07za-interruptible-soniox.py} | 0 ...p.py => 07zb-interruptible-inworld-http.py} | 0 ...nworld.py => 07zb-interruptible-inworld.py} | 0 ...p.py => 07zc-interruptible-asyncai-http.py} | 0 ...syncai.py => 07zc-interruptible-asyncai.py} | 0 ...ics.py => 07zd-interruptible-aicoustics.py} | 0 ...ible-hume.py => 07ze-interruptible-hume.py} | 0 ...radium.py => 07zf-interruptible-gradium.py} | 0 scripts/evals/run-release-evals.py | 18 +++++++++--------- 9 files changed, 9 insertions(+), 9 deletions(-) rename examples/foundational/{07aa-interruptible-soniox.py => 07za-interruptible-soniox.py} (100%) rename examples/foundational/{07ab-interruptible-inworld-http.py => 07zb-interruptible-inworld-http.py} (100%) rename examples/foundational/{07ab-interruptible-inworld.py => 07zb-interruptible-inworld.py} (100%) rename examples/foundational/{07ac-interruptible-asyncai-http.py => 07zc-interruptible-asyncai-http.py} (100%) rename examples/foundational/{07ac-interruptible-asyncai.py => 07zc-interruptible-asyncai.py} (100%) rename examples/foundational/{07ad-interruptible-aicoustics.py => 07zd-interruptible-aicoustics.py} (100%) rename examples/foundational/{07ae-interruptible-hume.py => 07ze-interruptible-hume.py} (100%) rename examples/foundational/{07af-interruptible-gradium.py => 07zf-interruptible-gradium.py} (100%) diff --git a/examples/foundational/07aa-interruptible-soniox.py b/examples/foundational/07za-interruptible-soniox.py similarity index 100% rename from examples/foundational/07aa-interruptible-soniox.py rename to examples/foundational/07za-interruptible-soniox.py diff --git a/examples/foundational/07ab-interruptible-inworld-http.py b/examples/foundational/07zb-interruptible-inworld-http.py similarity index 100% rename from examples/foundational/07ab-interruptible-inworld-http.py rename to examples/foundational/07zb-interruptible-inworld-http.py diff --git a/examples/foundational/07ab-interruptible-inworld.py b/examples/foundational/07zb-interruptible-inworld.py similarity index 100% rename from examples/foundational/07ab-interruptible-inworld.py rename to examples/foundational/07zb-interruptible-inworld.py diff --git a/examples/foundational/07ac-interruptible-asyncai-http.py b/examples/foundational/07zc-interruptible-asyncai-http.py similarity index 100% rename from examples/foundational/07ac-interruptible-asyncai-http.py rename to examples/foundational/07zc-interruptible-asyncai-http.py diff --git a/examples/foundational/07ac-interruptible-asyncai.py b/examples/foundational/07zc-interruptible-asyncai.py similarity index 100% rename from examples/foundational/07ac-interruptible-asyncai.py rename to examples/foundational/07zc-interruptible-asyncai.py diff --git a/examples/foundational/07ad-interruptible-aicoustics.py b/examples/foundational/07zd-interruptible-aicoustics.py similarity index 100% rename from examples/foundational/07ad-interruptible-aicoustics.py rename to examples/foundational/07zd-interruptible-aicoustics.py diff --git a/examples/foundational/07ae-interruptible-hume.py b/examples/foundational/07ze-interruptible-hume.py similarity index 100% rename from examples/foundational/07ae-interruptible-hume.py rename to examples/foundational/07ze-interruptible-hume.py diff --git a/examples/foundational/07af-interruptible-gradium.py b/examples/foundational/07zf-interruptible-gradium.py similarity index 100% rename from examples/foundational/07af-interruptible-gradium.py rename to examples/foundational/07zf-interruptible-gradium.py diff --git a/scripts/evals/run-release-evals.py b/scripts/evals/run-release-evals.py index dac7dd401..85834f7fd 100644 --- a/scripts/evals/run-release-evals.py +++ b/scripts/evals/run-release-evals.py @@ -97,15 +97,6 @@ TESTS_07 = [ ("07-interruptible-cartesia-http.py", EVAL_SIMPLE_MATH), ("07a-interruptible-speechmatics.py", EVAL_SIMPLE_MATH), ("07a-interruptible-speechmatics-vad.py", EVAL_SIMPLE_MATH), - ("07aa-interruptible-soniox.py", EVAL_SIMPLE_MATH), - ("07ab-interruptible-inworld.py", EVAL_SIMPLE_MATH), - ("07ab-interruptible-inworld-http.py", EVAL_SIMPLE_MATH), - ("07ac-interruptible-asyncai.py", EVAL_SIMPLE_MATH), - ("07ac-interruptible-asyncai-http.py", EVAL_SIMPLE_MATH), - # Need license key to run - # ("07ad-interruptible-aicoustics.py", EVAL_SIMPLE_MATH), - ("07ae-interruptible-hume.py", EVAL_SIMPLE_MATH), - ("07af-interruptible-gradium.py", EVAL_SIMPLE_MATH), ("07b-interruptible-langchain.py", EVAL_SIMPLE_MATH), ("07c-interruptible-deepgram.py", EVAL_SIMPLE_MATH), ("07c-interruptible-deepgram-flux.py", EVAL_SIMPLE_MATH), @@ -137,6 +128,15 @@ TESTS_07 = [ ("07y-interruptible-minimax.py", EVAL_SIMPLE_MATH), ("07z-interruptible-sarvam.py", EVAL_SIMPLE_MATH), ("07z-interruptible-sarvam-http.py", EVAL_SIMPLE_MATH), + ("07za-interruptible-soniox.py", EVAL_SIMPLE_MATH), + ("07zb-interruptible-inworld.py", EVAL_SIMPLE_MATH), + ("07zb-interruptible-inworld-http.py", EVAL_SIMPLE_MATH), + ("07zc-interruptible-asyncai.py", EVAL_SIMPLE_MATH), + ("07zc-interruptible-asyncai-http.py", EVAL_SIMPLE_MATH), + # Need license key to run + # ("07zd-interruptible-aicoustics.py", EVAL_SIMPLE_MATH), + ("07ze-interruptible-hume.py", EVAL_SIMPLE_MATH), + ("07zf-interruptible-gradium.py", EVAL_SIMPLE_MATH), # Needs a local XTTS docker instance running. # ("07i-interruptible-xtts.py", EVAL_SIMPLE_MATH), # Needs a Krisp license. From 7ae0d651d6bf426b54afda2db881688326fa8948 Mon Sep 17 00:00:00 2001 From: Neil Ruaro Date: Mon, 29 Dec 2025 21:08:40 +0800 Subject: [PATCH 0061/1060] added cambai tts integration --- .../foundational/07za-interruptible-camb.py | 207 ++++++++ examples/foundational/test_camb_quick.py | 181 +++++++ pyproject.toml | 1 + src/pipecat/services/camb/__init__.py | 8 + src/pipecat/services/camb/tts.py | 467 ++++++++++++++++++ tests/test_camb_tts.py | 431 ++++++++++++++++ uv.lock | 6 +- 7 files changed, 1300 insertions(+), 1 deletion(-) create mode 100644 examples/foundational/07za-interruptible-camb.py create mode 100644 examples/foundational/test_camb_quick.py create mode 100644 src/pipecat/services/camb/__init__.py create mode 100644 src/pipecat/services/camb/tts.py create mode 100644 tests/test_camb_tts.py diff --git a/examples/foundational/07za-interruptible-camb.py b/examples/foundational/07za-interruptible-camb.py new file mode 100644 index 000000000..4266e6f17 --- /dev/null +++ b/examples/foundational/07za-interruptible-camb.py @@ -0,0 +1,207 @@ +# +# Copyright (c) 2024–2025, Daily +# +# SPDX-License-Identifier: BSD 2-Clause License +# + +"""Camb.ai MARS-8 TTS example with interruption handling. + +This example demonstrates: +- Basic TTS synthesis with Camb.ai MARS-8 +- Voice selection +- Speed control +- Handling interruptions + +Requirements: +- CAMB_API_KEY environment variable +- OPENAI_API_KEY environment variable (for LLM) +- DEEPGRAM_API_KEY environment variable (for STT) + +Usage: + export CAMB_API_KEY=your_camb_api_key + export OPENAI_API_KEY=your_openai_api_key + export DEEPGRAM_API_KEY=your_deepgram_api_key + python 07za-interruptible-camb.py --transport daily + +For more information: +- Camb.ai API docs: https://camb.mintlify.app/ +- Pipecat docs: https://docs.pipecat.ai/ +""" + +import os + +import aiohttp +from dotenv import load_dotenv +from loguru import logger + +from pipecat.audio.vad.silero import SileroVADAnalyzer +from pipecat.audio.vad.vad_analyzer import VADParams +from pipecat.frames.frames import LLMRunFrame +from pipecat.pipeline.pipeline import Pipeline +from pipecat.pipeline.runner import PipelineRunner +from pipecat.pipeline.task import PipelineParams, PipelineTask +from pipecat.processors.aggregators.llm_context import LLMContext +from pipecat.processors.aggregators.llm_response_universal import ( + LLMContextAggregatorPair, +) +from pipecat.runner.types import RunnerArguments +from pipecat.runner.utils import create_transport +from pipecat.services.camb.tts import CambTTSService +from pipecat.services.deepgram.stt import DeepgramSTTService +from pipecat.services.openai.llm import OpenAILLMService +from pipecat.transports.base_transport import BaseTransport, TransportParams +from pipecat.transports.daily.transport import DailyParams +from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams + +load_dotenv(override=True) + + +# Transport configuration for different platforms +transport_params = { + "daily": lambda: DailyParams( + audio_in_enabled=True, + audio_out_enabled=True, + vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), + ), + "twilio": lambda: FastAPIWebsocketParams( + audio_in_enabled=True, + audio_out_enabled=True, + vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), + ), + "webrtc": lambda: TransportParams( + audio_in_enabled=True, + audio_out_enabled=True, + vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), + ), +} + + +async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): + """Run the bot with Camb.ai TTS. + + Args: + transport: The transport to use for audio I/O. + runner_args: Runner arguments from the CLI. + """ + logger.info("Starting Camb.ai TTS bot") + + # Create an HTTP session for the TTS service + async with aiohttp.ClientSession() as session: + # Initialize Deepgram STT for speech recognition + stt = DeepgramSTTService(api_key=os.getenv("DEEPGRAM_API_KEY")) + + # Initialize Camb.ai TTS with MARS-8-flash model (fastest) + tts = CambTTSService( + api_key=os.getenv("CAMB_API_KEY"), + aiohttp_session=session, + voice_id=2681, # Attic voice (default) + model="mars-8-flash", # Fast inference model + params=CambTTSService.InputParams( + speed=1.0, # Normal speed (0.5-2.0 range) + ), + ) + + # Initialize OpenAI LLM + llm = OpenAILLMService(api_key=os.getenv("OPENAI_API_KEY")) + + # System prompt for the assistant + messages = [ + { + "role": "system", + "content": """You are a helpful voice assistant powered by Camb.ai's MARS-8 +text-to-speech technology. Your goal is to have natural conversations and demonstrate +high-quality speech synthesis. Keep your responses concise and conversational since +they will be spoken aloud. Avoid special characters, emojis, or bullet points that +can't easily be spoken.""", + }, + ] + + # Set up context management + context = LLMContext(messages) + context_aggregator = LLMContextAggregatorPair(context) + + # Build the pipeline + pipeline = Pipeline( + [ + transport.input(), # Transport user input + stt, # Speech-to-text + context_aggregator.user(), # User context aggregation + llm, # Language model + tts, # Camb.ai TTS + transport.output(), # Transport bot output + context_aggregator.assistant(), # Assistant context aggregation + ] + ) + + # Create the pipeline task + task = PipelineTask( + pipeline, + params=PipelineParams( + enable_metrics=True, + enable_usage_metrics=True, + ), + idle_timeout_secs=runner_args.pipeline_idle_timeout_secs, + ) + + @transport.event_handler("on_client_connected") + async def on_client_connected(transport, client): + logger.info("Client connected") + # Start the conversation with a greeting + messages.append( + { + "role": "system", + "content": "Please introduce yourself briefly and ask how you can help.", + } + ) + await task.queue_frames([LLMRunFrame()]) + + @transport.event_handler("on_client_disconnected") + async def on_client_disconnected(transport, client): + logger.info("Client disconnected") + await task.cancel() + + # Run the pipeline + runner = PipelineRunner(handle_sigint=runner_args.handle_sigint) + await runner.run(task) + + +async def bot(runner_args: RunnerArguments): + """Main bot entry point compatible with Pipecat Cloud. + + Args: + runner_args: Arguments passed from the runner. + """ + transport = await create_transport(runner_args, transport_params) + await run_bot(transport, runner_args) + + +async def list_available_voices(): + """Helper function to list available Camb.ai voices. + + Run this to see what voices are available for your API key. + """ + async with aiohttp.ClientSession() as session: + voices = await CambTTSService.list_voices( + api_key=os.getenv("CAMB_API_KEY"), + aiohttp_session=session, + ) + print("\nAvailable Camb.ai voices:") + print("-" * 50) + for voice in voices: + print(f" ID: {voice['id']}, Name: {voice['name']}, Gender: {voice['gender']}") + print("-" * 50) + print(f"Total: {len(voices)} voices\n") + + +if __name__ == "__main__": + import sys + + # If --list-voices flag is passed, list voices and exit + if "--list-voices" in sys.argv: + import asyncio + + asyncio.run(list_available_voices()) + else: + from pipecat.runner.run import main + + main() diff --git a/examples/foundational/test_camb_quick.py b/examples/foundational/test_camb_quick.py new file mode 100644 index 000000000..d178b2b7c --- /dev/null +++ b/examples/foundational/test_camb_quick.py @@ -0,0 +1,181 @@ +#!/usr/bin/env python3 +"""Quick test script to verify Camb.ai TTS integration works. + +Usage: + export CAMB_API_KEY=your_api_key + python test_camb_quick.py +""" + +import asyncio +import os +import sys + +# Add the src directory to the path so we can import the module +sys.path.insert(0, os.path.join(os.path.dirname(__file__), "..", "..", "src")) + +import aiohttp +from dotenv import load_dotenv + +load_dotenv() + + +async def test_list_voices(): + """Test listing available voices.""" + from pipecat.services.camb.tts import CambTTSService + + api_key = os.getenv("CAMB_API_KEY") + if not api_key: + print("ERROR: CAMB_API_KEY environment variable not set!") + return False + + print("\n1. Testing list_voices()...") + async with aiohttp.ClientSession() as session: + try: + voices = await CambTTSService.list_voices( + api_key=api_key, + aiohttp_session=session, + ) + print(f" SUCCESS: Found {len(voices)} voices") + if voices: + print(f" First voice: ID={voices[0]['id']}, Name={voices[0]['name']}") + return True + except Exception as e: + print(f" FAILED: {e}") + import traceback + traceback.print_exc() + return False + + +async def test_tts_synthesis(): + """Test basic TTS synthesis.""" + from pipecat.services.camb.tts import CambTTSService + from pipecat.frames.frames import TTSAudioRawFrame, TTSStartedFrame, TTSStoppedFrame, ErrorFrame + + api_key = os.getenv("CAMB_API_KEY") + if not api_key: + print("ERROR: CAMB_API_KEY environment variable not set!") + return False + + print("\n2. Testing TTS synthesis...") + async with aiohttp.ClientSession() as session: + tts = CambTTSService( + api_key=api_key, + aiohttp_session=session, + voice_id=2681, # Attic voice + model="mars-8-flash", + ) + + # Manually set sample rate (normally done by StartFrame) + tts._sample_rate = 24000 + + text = "Hello! This is a test of the Camb.ai text to speech integration." + print(f" Synthesizing: '{text}'") + + audio_bytes = 0 + frames_received = [] + + try: + async for frame in tts.run_tts(text): + frames_received.append(type(frame).__name__) + if isinstance(frame, TTSAudioRawFrame): + audio_bytes += len(frame.audio) + elif isinstance(frame, ErrorFrame): + print(f" FAILED: {frame.error}") + return False + + print(f" Frames received: {frames_received}") + print(f" Audio bytes received: {audio_bytes}") + + if audio_bytes > 0: + print(" SUCCESS: TTS synthesis works!") + + # Optionally save and play audio + save_audio = input("\n Save audio to test_output.wav? (y/n): ").strip().lower() + if save_audio == 'y': + await save_audio_to_file(tts, text) + # Try to play the audio + play_audio = input(" Play the audio? (y/n): ").strip().lower() + if play_audio == 'y': + play_wav_file("test_output.wav") + + return True + else: + print(" FAILED: No audio received") + return False + + except Exception as e: + print(f" FAILED: {e}") + import traceback + traceback.print_exc() + return False + + +async def save_audio_to_file(tts, text): + """Save synthesized audio to a WAV file.""" + import wave + from pipecat.frames.frames import TTSAudioRawFrame + + audio_data = bytearray() + async for frame in tts.run_tts(text): + if isinstance(frame, TTSAudioRawFrame): + audio_data.extend(frame.audio) + + if audio_data: + with wave.open("test_output.wav", "wb") as wav_file: + wav_file.setnchannels(1) # Mono + wav_file.setsampwidth(2) # 16-bit + wav_file.setframerate(24000) # 24kHz + wav_file.writeframes(bytes(audio_data)) + print(" Saved to test_output.wav") + + +def play_wav_file(filepath): + """Play a WAV file using the system's default player.""" + import subprocess + import platform + + system = platform.system() + try: + if system == "Darwin": # macOS + subprocess.run(["afplay", filepath], check=True) + elif system == "Linux": + subprocess.run(["aplay", filepath], check=True) + elif system == "Windows": + subprocess.run(["powershell", "-c", f"(New-Object Media.SoundPlayer '{filepath}').PlaySync()"], check=True) + else: + print(f" Unsupported platform: {system}. Please play {filepath} manually.") + except Exception as e: + print(f" Could not play audio: {e}") + + +async def main(): + print("=" * 50) + print("Camb.ai TTS Integration Test") + print("=" * 50) + + results = [] + + # Test 1: List voices + results.append(await test_list_voices()) + + # Test 2: TTS synthesis + results.append(await test_tts_synthesis()) + + # Summary + print("\n" + "=" * 50) + print("Summary:") + print(f" List voices: {'PASS' if results[0] else 'FAIL'}") + print(f" TTS synthesis: {'PASS' if results[1] else 'FAIL'}") + print("=" * 50) + + if all(results): + print("\nAll tests passed!") + return 0 + else: + print("\nSome tests failed!") + return 1 + + +if __name__ == "__main__": + exit_code = asyncio.run(main()) + sys.exit(exit_code) diff --git a/pyproject.toml b/pyproject.toml index 7f50189de..f640e9fb1 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -53,6 +53,7 @@ aws = [ "aioboto3~=15.5.0", "pipecat-ai[websockets-base]" ] aws-nova-sonic = [ "aws_sdk_bedrock_runtime~=0.2.0; python_version>='3.12'" ] azure = [ "azure-cognitiveservices-speech~=1.44.0"] cartesia = [ "cartesia~=2.0.3", "pipecat-ai[websockets-base]" ] +camb = [ "pipecat-ai[websockets-base]" ] cerebras = [] daily = [ "daily-python~=0.23.0" ] deepgram = [ "deepgram-sdk~=4.7.0", "pipecat-ai[websockets-base]" ] diff --git a/src/pipecat/services/camb/__init__.py b/src/pipecat/services/camb/__init__.py new file mode 100644 index 000000000..0d444e949 --- /dev/null +++ b/src/pipecat/services/camb/__init__.py @@ -0,0 +1,8 @@ +# +# Copyright (c) 2024–2025, Daily +# +# SPDX-License-Identifier: BSD 2-Clause License +# + + +from .tts import * diff --git a/src/pipecat/services/camb/tts.py b/src/pipecat/services/camb/tts.py new file mode 100644 index 000000000..a6bcfb9e1 --- /dev/null +++ b/src/pipecat/services/camb/tts.py @@ -0,0 +1,467 @@ +# +# Copyright (c) 2024–2025, Daily +# +# SPDX-License-Identifier: BSD 2-Clause License +# + +"""Camb.ai MARS-8 text-to-speech service implementation. + +This module provides TTS functionality using Camb.ai's MARS-8 model family, +offering high-quality text-to-speech synthesis with HTTP streaming support. + +Features: + - MARS-8 models: mars-8, mars-8-flash, mars-8-instruct + - 140+ languages supported + - Real-time HTTP streaming + - 24kHz audio output + - Voice customization (speed, instructions) +""" + +import asyncio +from typing import Any, AsyncGenerator, Dict, List, Mapping, Optional + +import aiohttp +from loguru import logger +from pydantic import BaseModel, Field + +from pipecat.frames.frames import ( + ErrorFrame, + Frame, + StartFrame, + TTSAudioRawFrame, + TTSStartedFrame, + TTSStoppedFrame, +) +from pipecat.services.tts_service import TTSService +from pipecat.transcriptions.language import Language, resolve_language +from pipecat.utils.tracing.service_decorators import traced_tts + + +# Default configuration +DEFAULT_VOICE_ID = 2681 # Attic voice (publicly available) +DEFAULT_LANGUAGE = "en-us" +DEFAULT_MODEL = "mars-8-flash" # Faster inference +DEFAULT_BASE_URL = "https://client.camb.ai/apis" +DEFAULT_SAMPLE_RATE = 24000 # 24kHz +DEFAULT_TIMEOUT = 60.0 # Seconds (minimum recommended by Camb.ai) +MIN_TEXT_LENGTH = 3 +MAX_TEXT_LENGTH = 3000 + + +def language_to_camb_language(language: Language) -> Optional[str]: + """Convert a Pipecat Language enum to Camb.ai language code. + + Args: + language: The Language enum value to convert. + + Returns: + The corresponding Camb.ai language code (BCP-47 format), or None if not supported. + """ + LANGUAGE_MAP = { + Language.EN: "en-us", + Language.EN_US: "en-us", + Language.EN_GB: "en-gb", + Language.EN_AU: "en-au", + Language.ES: "es-es", + Language.ES_ES: "es-es", + Language.ES_MX: "es-mx", + Language.FR: "fr-fr", + Language.FR_FR: "fr-fr", + Language.FR_CA: "fr-ca", + Language.DE: "de-de", + Language.DE_DE: "de-de", + Language.IT: "it-it", + Language.PT: "pt-pt", + Language.PT_BR: "pt-br", + Language.PT_PT: "pt-pt", + Language.NL: "nl-nl", + Language.PL: "pl-pl", + Language.RU: "ru-ru", + Language.JA: "ja-jp", + Language.KO: "ko-kr", + Language.ZH: "zh-cn", + Language.ZH_CN: "zh-cn", + Language.ZH_TW: "zh-tw", + Language.AR: "ar-sa", + Language.HI: "hi-in", + Language.TR: "tr-tr", + Language.VI: "vi-vn", + Language.TH: "th-th", + Language.ID: "id-id", + Language.MS: "ms-my", + Language.SV: "sv-se", + Language.DA: "da-dk", + Language.NO: "no-no", + Language.FI: "fi-fi", + Language.CS: "cs-cz", + Language.EL: "el-gr", + Language.HE: "he-il", + Language.HU: "hu-hu", + Language.RO: "ro-ro", + Language.SK: "sk-sk", + Language.UK: "uk-ua", + Language.BG: "bg-bg", + Language.HR: "hr-hr", + Language.SR: "sr-rs", + Language.SL: "sl-si", + Language.CA: "ca-es", + Language.EU: "eu-es", + Language.GL: "gl-es", + Language.AF: "af-za", + Language.SW: "sw-ke", + Language.TA: "ta-in", + Language.TE: "te-in", + Language.BN: "bn-in", + Language.MR: "mr-in", + Language.GU: "gu-in", + Language.KN: "kn-in", + Language.ML: "ml-in", + Language.PA: "pa-in", + Language.UR: "ur-pk", + Language.FA: "fa-ir", + Language.TL: "tl-ph", + } + + return resolve_language(language, LANGUAGE_MAP, use_base_code=True) + + +class CambTTSService(TTSService): + """Camb.ai MARS-8 HTTP-based text-to-speech service. + + Converts text to speech using Camb.ai's MARS-8 TTS models with support for + multiple languages. Provides control over voice characteristics like speed + and custom instructions (for mars-8-instruct model). + + Example:: + + tts = CambTTSService( + api_key="your-api-key", + voice_id=2681, + model="mars-8-flash", + aiohttp_session=session, + params=CambTTSService.InputParams( + language=Language.EN, + speed=1.0 + ) + ) + + # For mars-8-instruct with custom instructions: + tts_instruct = CambTTSService( + api_key="your-api-key", + voice_id=2681, + model="mars-8-instruct", + aiohttp_session=session, + params=CambTTSService.InputParams( + language=Language.EN, + user_instructions="Speak with excitement and energy" + ) + ) + """ + + class InputParams(BaseModel): + """Input parameters for Camb.ai TTS configuration. + + Parameters: + language: Language for synthesis (BCP-47 format). Defaults to English. + speed: Speech speed multiplier (0.5 to 2.0). Defaults to 1.0. + user_instructions: Custom instructions for mars-8-instruct model only. + Ignored for other models. Max 1000 characters. + """ + + language: Optional[Language] = Language.EN + speed: Optional[float] = Field(default=1.0, ge=0.5, le=2.0) + user_instructions: Optional[str] = Field( + default=None, + max_length=1000, + description="Custom instructions for mars-8-instruct model only. " + "Use to control tone, style, or pronunciation. Max 1000 characters.", + ) + + def __init__( + self, + *, + api_key: str, + aiohttp_session: aiohttp.ClientSession, + voice_id: int = DEFAULT_VOICE_ID, + model: str = DEFAULT_MODEL, + base_url: str = DEFAULT_BASE_URL, + sample_rate: Optional[int] = None, + params: Optional[InputParams] = None, + **kwargs, + ): + """Initialize the Camb.ai TTS service. + + Args: + api_key: Camb.ai API key for authentication. + aiohttp_session: Shared aiohttp session for making HTTP requests. + voice_id: Voice ID to use (e.g., 2681 for Attic). Defaults to 2681. + model: TTS model to use. Options: "mars-8", "mars-8-flash", "mars-8-instruct". + Defaults to "mars-8-flash" (fastest). + base_url: Camb.ai API base URL. Defaults to production URL. + sample_rate: Audio sample rate in Hz. If None, uses Camb.ai default (24000). + params: Additional voice parameters. If None, uses defaults. + **kwargs: Additional arguments passed to parent TTSService. + """ + super().__init__(sample_rate=sample_rate, **kwargs) + + params = params or CambTTSService.InputParams() + + self._api_key = api_key + self._session = aiohttp_session + + # Remove trailing slash from base URL + if base_url.endswith("/"): + logger.warning("Base URL ends with a slash, removing it.") + base_url = base_url[:-1] + + self._base_url = base_url + + # Build settings + self._settings = { + "language": ( + self.language_to_service_language(params.language) + if params.language + else DEFAULT_LANGUAGE + ), + "speed": params.speed or 1.0, + "user_instructions": params.user_instructions, + } + + self.set_model_name(model) + self.set_voice(str(voice_id)) + self._voice_id_int = voice_id + + def can_generate_metrics(self) -> bool: + """Check if this service can generate processing metrics. + + Returns: + True, as Camb.ai service supports metrics generation. + """ + return True + + def language_to_service_language(self, language: Language) -> Optional[str]: + """Convert a Language enum to Camb.ai language format. + + Args: + language: The language to convert. + + Returns: + The Camb.ai-specific language code, or None if not supported. + """ + return language_to_camb_language(language) + + async def start(self, frame: StartFrame): + """Start the Camb.ai TTS service. + + Args: + frame: The start frame containing initialization parameters. + """ + await super().start(frame) + # Use Camb.ai's native sample rate if not specified + if not self._init_sample_rate: + self._sample_rate = DEFAULT_SAMPLE_RATE + self._settings["sample_rate"] = self._sample_rate + + async def _update_settings(self, settings: Mapping[str, Any]): + """Update service settings dynamically. + + Args: + settings: Dictionary of settings to update. + """ + await super()._update_settings(settings) + + for key, value in settings.items(): + if key in self._settings: + if key == "language" and isinstance(value, Language): + self._settings[key] = language_to_camb_language(value) + else: + self._settings[key] = value + logger.debug(f"Updated Camb.ai TTS setting {key} to: {value}") + elif key == "voice_id": + self._voice_id_int = int(value) + self.set_voice(str(value)) + + @traced_tts + async def run_tts(self, text: str) -> AsyncGenerator[Frame, None]: + """Generate speech from text using Camb.ai's TTS API. + + Args: + text: The text to synthesize into speech (3-3000 characters). + + Yields: + Frame: Audio frames containing the synthesized speech. + """ + logger.debug(f"{self}: Generating TTS [{text}]") + + # Validate text length + if len(text) < MIN_TEXT_LENGTH: + logger.warning(f"Text too short for Camb.ai TTS (min {MIN_TEXT_LENGTH} chars): {text}") + yield TTSStoppedFrame() + return + + if len(text) > MAX_TEXT_LENGTH: + logger.warning( + f"Text too long for Camb.ai TTS (max {MAX_TEXT_LENGTH} chars), truncating" + ) + text = text[:MAX_TEXT_LENGTH] + + # Build request payload + payload = { + "text": text, + "voice_id": self._voice_id_int, + "language": self._settings["language"], + "speech_model": self._model_name, + "output_configuration": {"format": "pcm_s16le"}, + "voice_settings": {"speed": self._settings["speed"]}, + } + + # Add user instructions if using mars-8-instruct model + if self._model_name == "mars-8-instruct" and self._settings.get("user_instructions"): + payload["user_instructions"] = self._settings["user_instructions"] + + headers = { + "x-api-key": self._api_key, + "Accept": "application/json", + "Content-Type": "application/json", + } + + try: + await self.start_ttfb_metrics() + + async with self._session.post( + f"{self._base_url}/tts-stream", + json=payload, + headers=headers, + timeout=aiohttp.ClientTimeout(total=DEFAULT_TIMEOUT), + ) as response: + if response.status != 200: + error_text = await response.text() + error_msg = self._format_error_message(response.status, error_text) + logger.error(f"{self}: {error_msg}") + yield ErrorFrame(error=error_msg) + return + + await self.start_tts_usage_metrics(text) + yield TTSStartedFrame() + + CHUNK_SIZE = self.chunk_size + + async for frame in self._stream_audio_frames_from_iterator( + response.content.iter_chunked(CHUNK_SIZE), strip_wav_header=False + ): + await self.stop_ttfb_metrics() + yield frame + + except aiohttp.ClientError as e: + error_msg = f"Network error communicating with Camb.ai: {e}" + logger.error(f"{self}: {error_msg}") + yield ErrorFrame(error=error_msg) + except asyncio.TimeoutError: + error_msg = f"Timeout waiting for Camb.ai TTS response (>{DEFAULT_TIMEOUT}s)" + logger.error(f"{self}: {error_msg}") + yield ErrorFrame(error=error_msg) + except Exception as e: + error_msg = f"Unexpected error in Camb.ai TTS: {e}" + logger.error(f"{self}: {error_msg}") + yield ErrorFrame(error=error_msg) + finally: + logger.debug(f"{self}: Finished TTS [{text}]") + await self.stop_ttfb_metrics() + yield TTSStoppedFrame() + + def _format_error_message(self, status: int, error_text: str) -> str: + """Format error message based on HTTP status code. + + Args: + status: HTTP status code. + error_text: Error response body. + + Returns: + Formatted, user-friendly error message. + """ + if status == 401: + return ( + "Invalid Camb.ai API key. " + "Set CAMB_API_KEY environment variable with your API key from https://camb.ai" + ) + elif status == 403: + return ( + f"Voice ID {self._voice_id_int} is not accessible with your API key. " + "Use list_voices() to see available voices." + ) + elif status == 404: + return ( + f"Invalid voice ID: {self._voice_id_int}. " + "Use list_voices() to see available voices." + ) + elif status == 429: + return "Camb.ai rate limit exceeded. Please wait before making more requests." + elif status >= 500: + return f"Camb.ai server error (status {status}): {error_text}" + else: + return f"Camb.ai API error (status {status}): {error_text}" + + @staticmethod + async def list_voices( + api_key: str, + aiohttp_session: aiohttp.ClientSession, + base_url: str = DEFAULT_BASE_URL, + ) -> List[Dict[str, Any]]: + """Fetch available voices from Camb.ai API. + + Args: + api_key: Camb.ai API key for authentication. + aiohttp_session: aiohttp ClientSession for making HTTP requests. + base_url: Camb.ai API base URL. + + Returns: + List of voice dictionaries with id, name, gender, and language fields. + + Raises: + Exception: If the API request fails. + + Example:: + + async with aiohttp.ClientSession() as session: + voices = await CambTTSService.list_voices( + api_key="your-api-key", + aiohttp_session=session, + ) + for voice in voices: + print(f"{voice['id']}: {voice['name']}") + """ + if base_url.endswith("/"): + base_url = base_url[:-1] + + headers = { + "x-api-key": api_key, + "Accept": "application/json", + } + + gender_map = { + 0: "Not Specified", + 1: "Male", + 2: "Female", + 9: "Not Applicable", + } + + async with aiohttp_session.get( + f"{base_url}/list-voices", + headers=headers, + timeout=aiohttp.ClientTimeout(total=30.0), + ) as response: + if response.status != 200: + error_text = await response.text() + raise Exception(f"Failed to list voices (status {response.status}): {error_text}") + + data = await response.json() + return [ + { + "id": v["id"], + "name": v.get("voice_name", "Unknown"), + "gender": gender_map.get(v.get("gender"), "Unknown"), + "age": v.get("age"), + "language": v.get("language"), + } + for v in data + ] diff --git a/tests/test_camb_tts.py b/tests/test_camb_tts.py new file mode 100644 index 000000000..71cc99c99 --- /dev/null +++ b/tests/test_camb_tts.py @@ -0,0 +1,431 @@ +# +# Copyright (c) 2024-2025 Daily +# +# SPDX-License-Identifier: BSD 2-Clause License +# + +"""Tests for CambTTSService. + +These tests use mock servers to simulate the Camb.ai API responses. +""" + +import asyncio + +import aiohttp +import pytest +from aiohttp import web + +from pipecat.frames.frames import ( + AggregatedTextFrame, + ErrorFrame, + TTSAudioRawFrame, + TTSSpeakFrame, + TTSStartedFrame, + TTSStoppedFrame, + TTSTextFrame, +) +from pipecat.services.camb.tts import CambTTSService, language_to_camb_language +from pipecat.tests.utils import run_test +from pipecat.transcriptions.language import Language + + +@pytest.mark.asyncio +async def test_run_camb_tts_success(aiohttp_client): + """Test successful TTS generation with chunked PCM audio. + + Verifies the frame sequence: TTSStartedFrame -> TTSAudioRawFrame* -> TTSStoppedFrame + """ + + async def handler(request): + # Verify request headers + assert request.headers.get("x-api-key") == "test-api-key" + assert request.headers.get("Content-Type") == "application/json" + + # Parse and verify request body + body = await request.json() + assert "text" in body + assert body["voice_id"] == 2681 + assert body["language"] == "en-us" + assert body["speech_model"] == "mars-8-flash" + assert body["output_configuration"]["format"] == "pcm_s16le" + + # Prepare a StreamResponse with chunked PCM data + resp = web.StreamResponse( + status=200, + reason="OK", + headers={"Content-Type": "audio/raw"}, + ) + await resp.prepare(request) + + # Write out chunked PCM byte data (16-bit samples) + # Use smaller chunks for more predictable frame count + data = b"\x00\x01" * 4800 # Small chunk of audio + await resp.write(data) + await resp.write_eof() + + return resp + + # Create an aiohttp test server + app = web.Application() + app.router.add_post("/tts-stream", handler) + client = await aiohttp_client(app) + + base_url = str(client.make_url("")).rstrip("/") + + async with aiohttp.ClientSession() as session: + tts_service = CambTTSService( + api_key="test-api-key", + aiohttp_session=session, + base_url=base_url, + voice_id=2681, + model="mars-8-flash", + ) + + # Manually set sample rate (normally done by StartFrame) + tts_service._sample_rate = 24000 + + # Test run_tts directly to avoid frame count variability + text = "Hello world, this is a test." + frames = [] + async for frame in tts_service.run_tts(text): + frames.append(frame) + + # Verify we got the expected frame types + frame_types = [type(f).__name__ for f in frames] + assert "TTSStartedFrame" in frame_types, "Should have TTSStartedFrame" + assert "TTSAudioRawFrame" in frame_types, "Should have TTSAudioRawFrame" + assert "TTSStoppedFrame" in frame_types, "Should have TTSStoppedFrame" + + audio_frames = [f for f in frames if isinstance(f, TTSAudioRawFrame)] + assert len(audio_frames) > 0, "Should have at least one audio frame" + + # Verify sample rate matches Camb.ai's output (24kHz) + for a_frame in audio_frames: + assert a_frame.sample_rate == 24000, "Sample rate should be 24000 Hz" + assert a_frame.num_channels == 1, "Should be mono audio" + + +@pytest.mark.asyncio +async def test_run_camb_tts_error_401(aiohttp_client): + """Test handling of invalid API key (401 Unauthorized).""" + + async def handler(request): + return web.Response( + status=401, + text="Unauthorized: Invalid API key", + ) + + app = web.Application() + app.router.add_post("/tts-stream", handler) + client = await aiohttp_client(app) + base_url = str(client.make_url("")).rstrip("/") + + async with aiohttp.ClientSession() as session: + tts_service = CambTTSService( + api_key="invalid-key", + aiohttp_session=session, + base_url=base_url, + ) + + frames_to_send = [ + TTSSpeakFrame(text="This should fail."), + ] + + expected_down_frames = [AggregatedTextFrame, TTSStoppedFrame, TTSTextFrame] + expected_up_frames = [ErrorFrame] + + frames_received = await run_test( + tts_service, + frames_to_send=frames_to_send, + expected_down_frames=expected_down_frames, + expected_up_frames=expected_up_frames, + ) + up_frames = frames_received[1] + + assert isinstance(up_frames[0], ErrorFrame), "Must receive an ErrorFrame for 401" + assert "Invalid Camb.ai API key" in up_frames[0].error, ( + "ErrorFrame should mention invalid API key" + ) + + +@pytest.mark.asyncio +async def test_run_camb_tts_error_404(aiohttp_client): + """Test handling of invalid voice ID (404 Not Found).""" + + async def handler(request): + return web.Response( + status=404, + text="Voice not found", + ) + + app = web.Application() + app.router.add_post("/tts-stream", handler) + client = await aiohttp_client(app) + base_url = str(client.make_url("")).rstrip("/") + + async with aiohttp.ClientSession() as session: + tts_service = CambTTSService( + api_key="test-api-key", + aiohttp_session=session, + base_url=base_url, + voice_id=99999, # Invalid voice ID + ) + + frames_to_send = [ + TTSSpeakFrame(text="This should fail."), + ] + + expected_down_frames = [AggregatedTextFrame, TTSStoppedFrame, TTSTextFrame] + expected_up_frames = [ErrorFrame] + + frames_received = await run_test( + tts_service, + frames_to_send=frames_to_send, + expected_down_frames=expected_down_frames, + expected_up_frames=expected_up_frames, + ) + up_frames = frames_received[1] + + assert isinstance(up_frames[0], ErrorFrame), "Must receive an ErrorFrame for 404" + assert "Invalid voice ID" in up_frames[0].error, ( + "ErrorFrame should mention invalid voice ID" + ) + + +@pytest.mark.asyncio +async def test_run_camb_tts_error_429(aiohttp_client): + """Test handling of rate limit (429 Too Many Requests).""" + + async def handler(request): + return web.Response( + status=429, + text="Rate limit exceeded", + ) + + app = web.Application() + app.router.add_post("/tts-stream", handler) + client = await aiohttp_client(app) + base_url = str(client.make_url("")).rstrip("/") + + async with aiohttp.ClientSession() as session: + tts_service = CambTTSService( + api_key="test-api-key", + aiohttp_session=session, + base_url=base_url, + ) + + frames_to_send = [ + TTSSpeakFrame(text="This should fail due to rate limit."), + ] + + expected_down_frames = [AggregatedTextFrame, TTSStoppedFrame, TTSTextFrame] + expected_up_frames = [ErrorFrame] + + frames_received = await run_test( + tts_service, + frames_to_send=frames_to_send, + expected_down_frames=expected_down_frames, + expected_up_frames=expected_up_frames, + ) + up_frames = frames_received[1] + + assert isinstance(up_frames[0], ErrorFrame), "Must receive an ErrorFrame for 429" + assert "rate limit" in up_frames[0].error.lower(), ( + "ErrorFrame should mention rate limit" + ) + + +@pytest.mark.asyncio +async def test_list_voices(aiohttp_client): + """Test voice listing endpoint.""" + + async def handler(request): + # Verify API key header + assert request.headers.get("x-api-key") == "test-api-key" + + # Return mock voice data (matching actual API response structure) + voices = [ + { + "id": 2681, + "voice_name": "Attic", + "gender": 1, + "age": 25, + "language": None, + "transcript": None, + "description": None, + "is_published": None, + }, + { + "id": 2682, + "voice_name": "Cellar", + "gender": 2, + "age": 30, + "language": 1, + "transcript": None, + "description": None, + "is_published": False, + }, + ] + return web.json_response(voices) + + app = web.Application() + app.router.add_get("/list-voices", handler) + client = await aiohttp_client(app) + base_url = str(client.make_url("")).rstrip("/") + + async with aiohttp.ClientSession() as session: + voices = await CambTTSService.list_voices( + api_key="test-api-key", + aiohttp_session=session, + base_url=base_url, + ) + + # Should return all voices + assert len(voices) == 2, "Should return all voices" + + # Verify voice data structure + attic_voice = next(v for v in voices if v["id"] == 2681) + assert attic_voice["name"] == "Attic" + assert attic_voice["gender"] == "Male" + assert attic_voice["age"] == 25 + + +@pytest.mark.asyncio +async def test_text_length_validation_too_short(aiohttp_client): + """Test that text shorter than 3 characters is handled gracefully.""" + + async def handler(request): + # This should not be called for short text + pytest.fail("Handler should not be called for text < 3 chars") + + app = web.Application() + app.router.add_post("/tts-stream", handler) + client = await aiohttp_client(app) + base_url = str(client.make_url("")).rstrip("/") + + async with aiohttp.ClientSession() as session: + tts_service = CambTTSService( + api_key="test-api-key", + aiohttp_session=session, + base_url=base_url, + ) + + frames_to_send = [ + TTSSpeakFrame(text="Hi"), # Only 2 characters + ] + + # For short text, we expect TTSStoppedFrame but no audio + expected_down_frames = [AggregatedTextFrame, TTSStoppedFrame, TTSTextFrame] + + frames_received = await run_test( + tts_service, + frames_to_send=frames_to_send, + expected_down_frames=expected_down_frames, + ) + down_frames = frames_received[0] + + # Verify no audio frames were generated + audio_frames = [f for f in down_frames if isinstance(f, TTSAudioRawFrame)] + assert len(audio_frames) == 0, "Should not generate audio for text < 3 chars" + + +@pytest.mark.asyncio +async def test_input_params(): + """Test InputParams model validation and defaults.""" + + # Test defaults + params = CambTTSService.InputParams() + assert params.language == Language.EN + assert params.speed == 1.0 + assert params.user_instructions is None + + # Test custom values + params = CambTTSService.InputParams( + language=Language.ES, + speed=1.5, + user_instructions="Speak slowly and clearly", + ) + assert params.language == Language.ES + assert params.speed == 1.5 + assert params.user_instructions == "Speak slowly and clearly" + + +@pytest.mark.asyncio +async def test_language_mapping(): + """Test language enum to Camb.ai language code conversion.""" + + # Test common languages + assert language_to_camb_language(Language.EN) == "en-us" + assert language_to_camb_language(Language.EN_US) == "en-us" + assert language_to_camb_language(Language.EN_GB) == "en-gb" + assert language_to_camb_language(Language.ES) == "es-es" + assert language_to_camb_language(Language.FR) == "fr-fr" + assert language_to_camb_language(Language.DE) == "de-de" + assert language_to_camb_language(Language.JA) == "ja-jp" + assert language_to_camb_language(Language.ZH) == "zh-cn" + + +@pytest.mark.asyncio +async def test_mars8_instruct_model(aiohttp_client): + """Test that user_instructions are included for mars-8-instruct model.""" + + received_payload = {} + + async def handler(request): + nonlocal received_payload + received_payload = await request.json() + + # Return minimal successful response + resp = web.StreamResponse(status=200, headers={"Content-Type": "audio/raw"}) + await resp.prepare(request) + await resp.write(b"\x00" * 1000) + await resp.write_eof() + return resp + + app = web.Application() + app.router.add_post("/tts-stream", handler) + client = await aiohttp_client(app) + base_url = str(client.make_url("")).rstrip("/") + + async with aiohttp.ClientSession() as session: + tts_service = CambTTSService( + api_key="test-api-key", + aiohttp_session=session, + base_url=base_url, + model="mars-8-instruct", + params=CambTTSService.InputParams(user_instructions="Speak with excitement"), + ) + + frames_to_send = [ + TTSSpeakFrame(text="This is exciting news!"), + ] + + await run_test( + tts_service, + frames_to_send=frames_to_send, + expected_down_frames=[ + AggregatedTextFrame, + TTSStartedFrame, + TTSAudioRawFrame, + TTSStoppedFrame, + TTSTextFrame, + ], + ) + + # Verify user_instructions was included in the request + assert received_payload.get("speech_model") == "mars-8-instruct" + assert received_payload.get("user_instructions") == "Speak with excitement" + + +@pytest.mark.asyncio +async def test_base_url_trailing_slash(): + """Test that trailing slash in base URL is handled correctly.""" + async with aiohttp.ClientSession() as session: + tts = CambTTSService( + api_key="test-key", + aiohttp_session=session, + base_url="https://api.example.com/", # With trailing slash + ) + + # Should have removed the trailing slash + assert tts._base_url == "https://api.example.com" diff --git a/uv.lock b/uv.lock index a9b3d2dd4..34811146a 100644 --- a/uv.lock +++ b/uv.lock @@ -4259,6 +4259,9 @@ aws-nova-sonic = [ azure = [ { name = "azure-cognitiveservices-speech" }, ] +camb = [ + { name = "websockets" }, +] cartesia = [ { name = "cartesia" }, { name = "websockets" }, @@ -4525,6 +4528,7 @@ requires-dist = [ { name = "pipecat-ai", extras = ["websockets-base"], marker = "extra == 'assemblyai'" }, { name = "pipecat-ai", extras = ["websockets-base"], marker = "extra == 'asyncai'" }, { name = "pipecat-ai", extras = ["websockets-base"], marker = "extra == 'aws'" }, + { name = "pipecat-ai", extras = ["websockets-base"], marker = "extra == 'camb'" }, { name = "pipecat-ai", extras = ["websockets-base"], marker = "extra == 'cartesia'" }, { name = "pipecat-ai", extras = ["websockets-base"], marker = "extra == 'deepgram'" }, { name = "pipecat-ai", extras = ["websockets-base"], marker = "extra == 'elevenlabs'" }, @@ -4573,7 +4577,7 @@ requires-dist = [ { name = "wait-for2", marker = "python_full_version < '3.12'", specifier = ">=0.4.1" }, { name = "websockets", marker = "extra == 'websockets-base'", specifier = ">=13.1,<16.0" }, ] -provides-extras = ["aic", "anthropic", "assemblyai", "asyncai", "aws", "aws-nova-sonic", "azure", "cartesia", "cerebras", "daily", "deepgram", "deepseek", "elevenlabs", "fal", "fireworks", "fish", "gladia", "google", "gradium", "grok", "groq", "gstreamer", "heygen", "hume", "inworld", "koala", "krisp", "langchain", "livekit", "lmnt", "local", "local-smart-turn", "local-smart-turn-v3", "mcp", "mem0", "mistral", "mlx-whisper", "moondream", "neuphonic", "noisereduce", "nvidia", "openai", "rnnoise", "openpipe", "openrouter", "perplexity", "playht", "qwen", "remote-smart-turn", "rime", "riva", "runner", "sagemaker", "sambanova", "sarvam", "sentry", "silero", "simli", "soniox", "soundfile", "speechmatics", "strands", "tavus", "together", "tracing", "ultravox", "webrtc", "websocket", "websockets-base", "whisper"] +provides-extras = ["aic", "anthropic", "assemblyai", "asyncai", "aws", "aws-nova-sonic", "azure", "cartesia", "camb", "cerebras", "daily", "deepgram", "deepseek", "elevenlabs", "fal", "fireworks", "fish", "gladia", "google", "gradium", "grok", "groq", "gstreamer", "heygen", "hume", "inworld", "koala", "krisp", "langchain", "livekit", "lmnt", "local", "local-smart-turn", "local-smart-turn-v3", "mcp", "mem0", "mistral", "mlx-whisper", "moondream", "neuphonic", "noisereduce", "nvidia", "openai", "rnnoise", "openpipe", "openrouter", "perplexity", "playht", "qwen", "remote-smart-turn", "rime", "riva", "runner", "sagemaker", "sambanova", "sarvam", "sentry", "silero", "simli", "soniox", "soundfile", "speechmatics", "strands", "tavus", "together", "tracing", "ultravox", "webrtc", "websocket", "websockets-base", "whisper"] [package.metadata.requires-dev] dev = [ From ed0ff46a878358711077e6331189d5db10b13df5 Mon Sep 17 00:00:00 2001 From: Neil Ruaro Date: Sun, 4 Jan 2026 22:20:02 +0800 Subject: [PATCH 0062/1060] added local test --- .../07zb-interruptible-camb-local.py | 144 ++++++++++++++++++ 1 file changed, 144 insertions(+) create mode 100644 examples/foundational/07zb-interruptible-camb-local.py diff --git a/examples/foundational/07zb-interruptible-camb-local.py b/examples/foundational/07zb-interruptible-camb-local.py new file mode 100644 index 000000000..fa77cd2a3 --- /dev/null +++ b/examples/foundational/07zb-interruptible-camb-local.py @@ -0,0 +1,144 @@ +# +# Copyright (c) 2024–2025, Daily +# +# SPDX-License-Identifier: BSD 2-Clause License +# + +"""Camb.ai MARS-8 TTS example with local audio (microphone/speakers). + +This example demonstrates: +- Basic TTS synthesis with Camb.ai MARS-8 +- Local audio input/output (no WebRTC or Daily needed) +- Handling interruptions + +Requirements: +- CAMB_API_KEY environment variable +- OPENAI_API_KEY environment variable (for LLM) +- DEEPGRAM_API_KEY environment variable (for STT) + +Usage: + export CAMB_API_KEY=your_camb_api_key + export OPENAI_API_KEY=your_openai_api_key + export DEEPGRAM_API_KEY=your_deepgram_api_key + python 07zb-interruptible-camb-local.py +""" + +import asyncio +import os +import sys + +import aiohttp +from dotenv import load_dotenv +from loguru import logger + +from pipecat.audio.vad.silero import SileroVADAnalyzer +from pipecat.audio.vad.vad_analyzer import VADParams +from pipecat.frames.frames import LLMRunFrame +from pipecat.pipeline.pipeline import Pipeline +from pipecat.pipeline.runner import PipelineRunner +from pipecat.pipeline.task import PipelineParams, PipelineTask +from pipecat.processors.aggregators.llm_context import LLMContext +from pipecat.processors.aggregators.llm_response_universal import ( + LLMContextAggregatorPair, +) +from pipecat.services.camb.tts import CambTTSService +from pipecat.services.deepgram.stt import DeepgramSTTService +from pipecat.services.openai.llm import OpenAILLMService +from pipecat.transports.local.audio import LocalAudioTransport, LocalAudioTransportParams + +load_dotenv(override=True) + +logger.remove(0) +logger.add(sys.stderr, level="DEBUG") + + +async def main(): + # Local audio transport - uses your microphone and speakers + transport = LocalAudioTransport( + LocalAudioTransportParams( + audio_in_enabled=True, + audio_out_enabled=True, + vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), + ) + ) + + # Deepgram STT for speech recognition + stt = DeepgramSTTService(api_key=os.getenv("DEEPGRAM_API_KEY")) + + # Create HTTP session for Camb.ai TTS + async with aiohttp.ClientSession() as session: + # Camb.ai TTS with MARS-8-flash model + tts = CambTTSService( + api_key=os.getenv("CAMB_API_KEY"), + aiohttp_session=session, + voice_id=2681, # Attic voice + model="mars-8-flash", + params=CambTTSService.InputParams( + speed=1.0, + ), + ) + + # OpenAI LLM + llm = OpenAILLMService(api_key=os.getenv("OPENAI_API_KEY")) + + # System prompt + messages = [ + { + "role": "system", + "content": """You are a helpful voice assistant powered by Camb.ai's MARS-8 +text-to-speech technology. Keep your responses concise and conversational since +they will be spoken aloud. Avoid special characters, emojis, or bullet points.""", + }, + ] + + # Context management + context = LLMContext(messages) + context_aggregator = LLMContextAggregatorPair(context) + + # Build the pipeline + pipeline = Pipeline( + [ + transport.input(), # Microphone input + stt, # Speech-to-text + context_aggregator.user(), # User context + llm, # Language model + tts, # Camb.ai TTS + transport.output(), # Speaker output + context_aggregator.assistant(), # Assistant context + ] + ) + + # Create pipeline task + task = PipelineTask( + pipeline, + params=PipelineParams( + enable_metrics=True, + enable_usage_metrics=True, + ), + ) + + # Run the pipeline + runner = PipelineRunner() + logger.info("Starting Camb.ai TTS bot with local audio...") + logger.info("Speak into your microphone to interact with the bot.") + + # Start the conversation with a greeting after a short delay + async def start_greeting(): + await asyncio.sleep(1) # Wait for pipeline to start + messages.append( + { + "role": "system", + "content": "Please introduce yourself briefly and ask how you can help.", + } + ) + await task.queue_frames([LLMRunFrame()]) + + # Run greeting and pipeline concurrently + await asyncio.gather( + runner.run(task), + start_greeting(), + ) + + +if __name__ == "__main__": + asyncio.run(main()) From be098e85dbd280e6592d24a87d6aeeb79022860e Mon Sep 17 00:00:00 2001 From: Neil Ruaro Date: Mon, 5 Jan 2026 05:35:31 +0800 Subject: [PATCH 0063/1060] Remove non-working Daily/WebRTC example The Daily transport example had authentication issues. Keeping the local audio example (07zb-interruptible-camb-local.py) which works. --- .../foundational/07za-interruptible-camb.py | 207 ------------------ 1 file changed, 207 deletions(-) delete mode 100644 examples/foundational/07za-interruptible-camb.py diff --git a/examples/foundational/07za-interruptible-camb.py b/examples/foundational/07za-interruptible-camb.py deleted file mode 100644 index 4266e6f17..000000000 --- a/examples/foundational/07za-interruptible-camb.py +++ /dev/null @@ -1,207 +0,0 @@ -# -# Copyright (c) 2024–2025, Daily -# -# SPDX-License-Identifier: BSD 2-Clause License -# - -"""Camb.ai MARS-8 TTS example with interruption handling. - -This example demonstrates: -- Basic TTS synthesis with Camb.ai MARS-8 -- Voice selection -- Speed control -- Handling interruptions - -Requirements: -- CAMB_API_KEY environment variable -- OPENAI_API_KEY environment variable (for LLM) -- DEEPGRAM_API_KEY environment variable (for STT) - -Usage: - export CAMB_API_KEY=your_camb_api_key - export OPENAI_API_KEY=your_openai_api_key - export DEEPGRAM_API_KEY=your_deepgram_api_key - python 07za-interruptible-camb.py --transport daily - -For more information: -- Camb.ai API docs: https://camb.mintlify.app/ -- Pipecat docs: https://docs.pipecat.ai/ -""" - -import os - -import aiohttp -from dotenv import load_dotenv -from loguru import logger - -from pipecat.audio.vad.silero import SileroVADAnalyzer -from pipecat.audio.vad.vad_analyzer import VADParams -from pipecat.frames.frames import LLMRunFrame -from pipecat.pipeline.pipeline import Pipeline -from pipecat.pipeline.runner import PipelineRunner -from pipecat.pipeline.task import PipelineParams, PipelineTask -from pipecat.processors.aggregators.llm_context import LLMContext -from pipecat.processors.aggregators.llm_response_universal import ( - LLMContextAggregatorPair, -) -from pipecat.runner.types import RunnerArguments -from pipecat.runner.utils import create_transport -from pipecat.services.camb.tts import CambTTSService -from pipecat.services.deepgram.stt import DeepgramSTTService -from pipecat.services.openai.llm import OpenAILLMService -from pipecat.transports.base_transport import BaseTransport, TransportParams -from pipecat.transports.daily.transport import DailyParams -from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams - -load_dotenv(override=True) - - -# Transport configuration for different platforms -transport_params = { - "daily": lambda: DailyParams( - audio_in_enabled=True, - audio_out_enabled=True, - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), - ), - "twilio": lambda: FastAPIWebsocketParams( - audio_in_enabled=True, - audio_out_enabled=True, - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), - ), - "webrtc": lambda: TransportParams( - audio_in_enabled=True, - audio_out_enabled=True, - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), - ), -} - - -async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): - """Run the bot with Camb.ai TTS. - - Args: - transport: The transport to use for audio I/O. - runner_args: Runner arguments from the CLI. - """ - logger.info("Starting Camb.ai TTS bot") - - # Create an HTTP session for the TTS service - async with aiohttp.ClientSession() as session: - # Initialize Deepgram STT for speech recognition - stt = DeepgramSTTService(api_key=os.getenv("DEEPGRAM_API_KEY")) - - # Initialize Camb.ai TTS with MARS-8-flash model (fastest) - tts = CambTTSService( - api_key=os.getenv("CAMB_API_KEY"), - aiohttp_session=session, - voice_id=2681, # Attic voice (default) - model="mars-8-flash", # Fast inference model - params=CambTTSService.InputParams( - speed=1.0, # Normal speed (0.5-2.0 range) - ), - ) - - # Initialize OpenAI LLM - llm = OpenAILLMService(api_key=os.getenv("OPENAI_API_KEY")) - - # System prompt for the assistant - messages = [ - { - "role": "system", - "content": """You are a helpful voice assistant powered by Camb.ai's MARS-8 -text-to-speech technology. Your goal is to have natural conversations and demonstrate -high-quality speech synthesis. Keep your responses concise and conversational since -they will be spoken aloud. Avoid special characters, emojis, or bullet points that -can't easily be spoken.""", - }, - ] - - # Set up context management - context = LLMContext(messages) - context_aggregator = LLMContextAggregatorPair(context) - - # Build the pipeline - pipeline = Pipeline( - [ - transport.input(), # Transport user input - stt, # Speech-to-text - context_aggregator.user(), # User context aggregation - llm, # Language model - tts, # Camb.ai TTS - transport.output(), # Transport bot output - context_aggregator.assistant(), # Assistant context aggregation - ] - ) - - # Create the pipeline task - task = PipelineTask( - pipeline, - params=PipelineParams( - enable_metrics=True, - enable_usage_metrics=True, - ), - idle_timeout_secs=runner_args.pipeline_idle_timeout_secs, - ) - - @transport.event_handler("on_client_connected") - async def on_client_connected(transport, client): - logger.info("Client connected") - # Start the conversation with a greeting - messages.append( - { - "role": "system", - "content": "Please introduce yourself briefly and ask how you can help.", - } - ) - await task.queue_frames([LLMRunFrame()]) - - @transport.event_handler("on_client_disconnected") - async def on_client_disconnected(transport, client): - logger.info("Client disconnected") - await task.cancel() - - # Run the pipeline - runner = PipelineRunner(handle_sigint=runner_args.handle_sigint) - await runner.run(task) - - -async def bot(runner_args: RunnerArguments): - """Main bot entry point compatible with Pipecat Cloud. - - Args: - runner_args: Arguments passed from the runner. - """ - transport = await create_transport(runner_args, transport_params) - await run_bot(transport, runner_args) - - -async def list_available_voices(): - """Helper function to list available Camb.ai voices. - - Run this to see what voices are available for your API key. - """ - async with aiohttp.ClientSession() as session: - voices = await CambTTSService.list_voices( - api_key=os.getenv("CAMB_API_KEY"), - aiohttp_session=session, - ) - print("\nAvailable Camb.ai voices:") - print("-" * 50) - for voice in voices: - print(f" ID: {voice['id']}, Name: {voice['name']}, Gender: {voice['gender']}") - print("-" * 50) - print(f"Total: {len(voices)} voices\n") - - -if __name__ == "__main__": - import sys - - # If --list-voices flag is passed, list voices and exit - if "--list-voices" in sys.argv: - import asyncio - - asyncio.run(list_available_voices()) - else: - from pipecat.runner.run import main - - main() From fcab9899cccc12221ef2924cbe8fabe45765f1cd Mon Sep 17 00:00:00 2001 From: Neil Ruaro Date: Mon, 5 Jan 2026 05:53:46 +0800 Subject: [PATCH 0064/1060] Add changelog entry for Camb.ai TTS integration --- changelog/0000.added.md | 1 + 1 file changed, 1 insertion(+) create mode 100644 changelog/0000.added.md diff --git a/changelog/0000.added.md b/changelog/0000.added.md new file mode 100644 index 000000000..7c40394ac --- /dev/null +++ b/changelog/0000.added.md @@ -0,0 +1 @@ +- Added Camb.ai TTS integration with MARS-8 models (mars-8, mars-8-flash, mars-8-instruct) for high-quality text-to-speech synthesis. From 54933bea2ac2ebd56a8bf932955328daeed40cce Mon Sep 17 00:00:00 2001 From: Neil Ruaro Date: Mon, 5 Jan 2026 06:07:12 +0800 Subject: [PATCH 0065/1060] Rename changelog to PR number --- changelog/{0000.added.md => 3349.added.md} | 0 1 file changed, 0 insertions(+), 0 deletions(-) rename changelog/{0000.added.md => 3349.added.md} (100%) diff --git a/changelog/0000.added.md b/changelog/3349.added.md similarity index 100% rename from changelog/0000.added.md rename to changelog/3349.added.md From a3d7e9eafe557a7af0d3accaef5f1efe1385db19 Mon Sep 17 00:00:00 2001 From: Neil Ruaro Date: Mon, 5 Jan 2026 20:34:05 +0800 Subject: [PATCH 0066/1060] Address PR feedback: add --voice-id arg, remove test script - Add --voice-id CLI argument to example (default: 2681) - Remove test_camb_quick.py from examples/ (tests belong in tests/) - Update docstring with new usage --- .../07zb-interruptible-camb-local.py | 19 +- examples/foundational/test_camb_quick.py | 181 ------------------ 2 files changed, 15 insertions(+), 185 deletions(-) delete mode 100644 examples/foundational/test_camb_quick.py diff --git a/examples/foundational/07zb-interruptible-camb-local.py b/examples/foundational/07zb-interruptible-camb-local.py index fa77cd2a3..de7af4488 100644 --- a/examples/foundational/07zb-interruptible-camb-local.py +++ b/examples/foundational/07zb-interruptible-camb-local.py @@ -20,9 +20,10 @@ Usage: export CAMB_API_KEY=your_camb_api_key export OPENAI_API_KEY=your_openai_api_key export DEEPGRAM_API_KEY=your_deepgram_api_key - python 07zb-interruptible-camb-local.py + python 07zb-interruptible-camb-local.py [--voice-id VOICE_ID] """ +import argparse import asyncio import os import sys @@ -52,7 +53,7 @@ logger.remove(0) logger.add(sys.stderr, level="DEBUG") -async def main(): +async def main(voice_id: int): # Local audio transport - uses your microphone and speakers transport = LocalAudioTransport( LocalAudioTransportParams( @@ -71,7 +72,7 @@ async def main(): tts = CambTTSService( api_key=os.getenv("CAMB_API_KEY"), aiohttp_session=session, - voice_id=2681, # Attic voice + voice_id=voice_id, model="mars-8-flash", params=CambTTSService.InputParams( speed=1.0, @@ -109,9 +110,11 @@ they will be spoken aloud. Avoid special characters, emojis, or bullet points."" ) # Create pipeline task + # Use 24kHz sample rate to match Camb.ai TTS output task = PipelineTask( pipeline, params=PipelineParams( + audio_out_sample_rate=24000, enable_metrics=True, enable_usage_metrics=True, ), @@ -141,4 +144,12 @@ they will be spoken aloud. Avoid special characters, emojis, or bullet points."" if __name__ == "__main__": - asyncio.run(main()) + parser = argparse.ArgumentParser(description="Camb.ai TTS example with local audio") + parser.add_argument( + "--voice-id", + type=int, + default=2681, + help="Camb.ai voice ID to use (default: 2681 - Attic voice)", + ) + args = parser.parse_args() + asyncio.run(main(args.voice_id)) diff --git a/examples/foundational/test_camb_quick.py b/examples/foundational/test_camb_quick.py deleted file mode 100644 index d178b2b7c..000000000 --- a/examples/foundational/test_camb_quick.py +++ /dev/null @@ -1,181 +0,0 @@ -#!/usr/bin/env python3 -"""Quick test script to verify Camb.ai TTS integration works. - -Usage: - export CAMB_API_KEY=your_api_key - python test_camb_quick.py -""" - -import asyncio -import os -import sys - -# Add the src directory to the path so we can import the module -sys.path.insert(0, os.path.join(os.path.dirname(__file__), "..", "..", "src")) - -import aiohttp -from dotenv import load_dotenv - -load_dotenv() - - -async def test_list_voices(): - """Test listing available voices.""" - from pipecat.services.camb.tts import CambTTSService - - api_key = os.getenv("CAMB_API_KEY") - if not api_key: - print("ERROR: CAMB_API_KEY environment variable not set!") - return False - - print("\n1. Testing list_voices()...") - async with aiohttp.ClientSession() as session: - try: - voices = await CambTTSService.list_voices( - api_key=api_key, - aiohttp_session=session, - ) - print(f" SUCCESS: Found {len(voices)} voices") - if voices: - print(f" First voice: ID={voices[0]['id']}, Name={voices[0]['name']}") - return True - except Exception as e: - print(f" FAILED: {e}") - import traceback - traceback.print_exc() - return False - - -async def test_tts_synthesis(): - """Test basic TTS synthesis.""" - from pipecat.services.camb.tts import CambTTSService - from pipecat.frames.frames import TTSAudioRawFrame, TTSStartedFrame, TTSStoppedFrame, ErrorFrame - - api_key = os.getenv("CAMB_API_KEY") - if not api_key: - print("ERROR: CAMB_API_KEY environment variable not set!") - return False - - print("\n2. Testing TTS synthesis...") - async with aiohttp.ClientSession() as session: - tts = CambTTSService( - api_key=api_key, - aiohttp_session=session, - voice_id=2681, # Attic voice - model="mars-8-flash", - ) - - # Manually set sample rate (normally done by StartFrame) - tts._sample_rate = 24000 - - text = "Hello! This is a test of the Camb.ai text to speech integration." - print(f" Synthesizing: '{text}'") - - audio_bytes = 0 - frames_received = [] - - try: - async for frame in tts.run_tts(text): - frames_received.append(type(frame).__name__) - if isinstance(frame, TTSAudioRawFrame): - audio_bytes += len(frame.audio) - elif isinstance(frame, ErrorFrame): - print(f" FAILED: {frame.error}") - return False - - print(f" Frames received: {frames_received}") - print(f" Audio bytes received: {audio_bytes}") - - if audio_bytes > 0: - print(" SUCCESS: TTS synthesis works!") - - # Optionally save and play audio - save_audio = input("\n Save audio to test_output.wav? (y/n): ").strip().lower() - if save_audio == 'y': - await save_audio_to_file(tts, text) - # Try to play the audio - play_audio = input(" Play the audio? (y/n): ").strip().lower() - if play_audio == 'y': - play_wav_file("test_output.wav") - - return True - else: - print(" FAILED: No audio received") - return False - - except Exception as e: - print(f" FAILED: {e}") - import traceback - traceback.print_exc() - return False - - -async def save_audio_to_file(tts, text): - """Save synthesized audio to a WAV file.""" - import wave - from pipecat.frames.frames import TTSAudioRawFrame - - audio_data = bytearray() - async for frame in tts.run_tts(text): - if isinstance(frame, TTSAudioRawFrame): - audio_data.extend(frame.audio) - - if audio_data: - with wave.open("test_output.wav", "wb") as wav_file: - wav_file.setnchannels(1) # Mono - wav_file.setsampwidth(2) # 16-bit - wav_file.setframerate(24000) # 24kHz - wav_file.writeframes(bytes(audio_data)) - print(" Saved to test_output.wav") - - -def play_wav_file(filepath): - """Play a WAV file using the system's default player.""" - import subprocess - import platform - - system = platform.system() - try: - if system == "Darwin": # macOS - subprocess.run(["afplay", filepath], check=True) - elif system == "Linux": - subprocess.run(["aplay", filepath], check=True) - elif system == "Windows": - subprocess.run(["powershell", "-c", f"(New-Object Media.SoundPlayer '{filepath}').PlaySync()"], check=True) - else: - print(f" Unsupported platform: {system}. Please play {filepath} manually.") - except Exception as e: - print(f" Could not play audio: {e}") - - -async def main(): - print("=" * 50) - print("Camb.ai TTS Integration Test") - print("=" * 50) - - results = [] - - # Test 1: List voices - results.append(await test_list_voices()) - - # Test 2: TTS synthesis - results.append(await test_tts_synthesis()) - - # Summary - print("\n" + "=" * 50) - print("Summary:") - print(f" List voices: {'PASS' if results[0] else 'FAIL'}") - print(f" TTS synthesis: {'PASS' if results[1] else 'FAIL'}") - print("=" * 50) - - if all(results): - print("\nAll tests passed!") - return 0 - else: - print("\nSome tests failed!") - return 1 - - -if __name__ == "__main__": - exit_code = asyncio.run(main()) - sys.exit(exit_code) From a541d652558838dc92fe9149f8a623ea85f0305c Mon Sep 17 00:00:00 2001 From: Neil Ruaro Date: Fri, 9 Jan 2026 18:20:50 +0900 Subject: [PATCH 0067/1060] Update MARS model names to mars-flash, mars-pro, mars-instruct Rename model identifiers from mars-8-* to the new naming convention: - mars-8-flash -> mars-flash (default) - mars-8 -> removed - mars-8-instruct -> mars-instruct - Added mars-pro --- changelog/3349.added.md | 2 +- .../07zb-interruptible-camb-local.py | 4 +-- src/pipecat/services/camb/tts.py | 32 +++++++++---------- tests/test_camb_tts.py | 10 +++--- 4 files changed, 24 insertions(+), 24 deletions(-) diff --git a/changelog/3349.added.md b/changelog/3349.added.md index 7c40394ac..565caca84 100644 --- a/changelog/3349.added.md +++ b/changelog/3349.added.md @@ -1 +1 @@ -- Added Camb.ai TTS integration with MARS-8 models (mars-8, mars-8-flash, mars-8-instruct) for high-quality text-to-speech synthesis. +- Added Camb.ai TTS integration with MARS models (mars-flash, mars-pro, mars-instruct) for high-quality text-to-speech synthesis. diff --git a/examples/foundational/07zb-interruptible-camb-local.py b/examples/foundational/07zb-interruptible-camb-local.py index de7af4488..f8c3fbbd6 100644 --- a/examples/foundational/07zb-interruptible-camb-local.py +++ b/examples/foundational/07zb-interruptible-camb-local.py @@ -68,12 +68,12 @@ async def main(voice_id: int): # Create HTTP session for Camb.ai TTS async with aiohttp.ClientSession() as session: - # Camb.ai TTS with MARS-8-flash model + # Camb.ai TTS with MARS-flash model tts = CambTTSService( api_key=os.getenv("CAMB_API_KEY"), aiohttp_session=session, voice_id=voice_id, - model="mars-8-flash", + model="mars-flash", params=CambTTSService.InputParams( speed=1.0, ), diff --git a/src/pipecat/services/camb/tts.py b/src/pipecat/services/camb/tts.py index a6bcfb9e1..9348c9964 100644 --- a/src/pipecat/services/camb/tts.py +++ b/src/pipecat/services/camb/tts.py @@ -4,13 +4,13 @@ # SPDX-License-Identifier: BSD 2-Clause License # -"""Camb.ai MARS-8 text-to-speech service implementation. +"""Camb.ai MARS text-to-speech service implementation. -This module provides TTS functionality using Camb.ai's MARS-8 model family, +This module provides TTS functionality using Camb.ai's MARS model family, offering high-quality text-to-speech synthesis with HTTP streaming support. Features: - - MARS-8 models: mars-8, mars-8-flash, mars-8-instruct + - MARS models: mars-flash, mars-pro, mars-instruct - 140+ languages supported - Real-time HTTP streaming - 24kHz audio output @@ -40,7 +40,7 @@ from pipecat.utils.tracing.service_decorators import traced_tts # Default configuration DEFAULT_VOICE_ID = 2681 # Attic voice (publicly available) DEFAULT_LANGUAGE = "en-us" -DEFAULT_MODEL = "mars-8-flash" # Faster inference +DEFAULT_MODEL = "mars-flash" # Faster inference DEFAULT_BASE_URL = "https://client.camb.ai/apis" DEFAULT_SAMPLE_RATE = 24000 # 24kHz DEFAULT_TIMEOUT = 60.0 # Seconds (minimum recommended by Camb.ai) @@ -126,18 +126,18 @@ def language_to_camb_language(language: Language) -> Optional[str]: class CambTTSService(TTSService): - """Camb.ai MARS-8 HTTP-based text-to-speech service. + """Camb.ai MARS HTTP-based text-to-speech service. - Converts text to speech using Camb.ai's MARS-8 TTS models with support for + Converts text to speech using Camb.ai's MARS TTS models with support for multiple languages. Provides control over voice characteristics like speed - and custom instructions (for mars-8-instruct model). + and custom instructions (for mars-instruct model). Example:: tts = CambTTSService( api_key="your-api-key", voice_id=2681, - model="mars-8-flash", + model="mars-flash", aiohttp_session=session, params=CambTTSService.InputParams( language=Language.EN, @@ -145,11 +145,11 @@ class CambTTSService(TTSService): ) ) - # For mars-8-instruct with custom instructions: + # For mars-instruct with custom instructions: tts_instruct = CambTTSService( api_key="your-api-key", voice_id=2681, - model="mars-8-instruct", + model="mars-instruct", aiohttp_session=session, params=CambTTSService.InputParams( language=Language.EN, @@ -164,7 +164,7 @@ class CambTTSService(TTSService): Parameters: language: Language for synthesis (BCP-47 format). Defaults to English. speed: Speech speed multiplier (0.5 to 2.0). Defaults to 1.0. - user_instructions: Custom instructions for mars-8-instruct model only. + user_instructions: Custom instructions for mars-instruct model only. Ignored for other models. Max 1000 characters. """ @@ -173,7 +173,7 @@ class CambTTSService(TTSService): user_instructions: Optional[str] = Field( default=None, max_length=1000, - description="Custom instructions for mars-8-instruct model only. " + description="Custom instructions for mars-instruct model only. " "Use to control tone, style, or pronunciation. Max 1000 characters.", ) @@ -195,8 +195,8 @@ class CambTTSService(TTSService): api_key: Camb.ai API key for authentication. aiohttp_session: Shared aiohttp session for making HTTP requests. voice_id: Voice ID to use (e.g., 2681 for Attic). Defaults to 2681. - model: TTS model to use. Options: "mars-8", "mars-8-flash", "mars-8-instruct". - Defaults to "mars-8-flash" (fastest). + model: TTS model to use. Options: "mars-flash", "mars-pro", "mars-instruct". + Defaults to "mars-flash" (fastest). base_url: Camb.ai API base URL. Defaults to production URL. sample_rate: Audio sample rate in Hz. If None, uses Camb.ai default (24000). params: Additional voice parameters. If None, uses defaults. @@ -315,8 +315,8 @@ class CambTTSService(TTSService): "voice_settings": {"speed": self._settings["speed"]}, } - # Add user instructions if using mars-8-instruct model - if self._model_name == "mars-8-instruct" and self._settings.get("user_instructions"): + # Add user instructions if using mars-instruct model + if self._model_name == "mars-instruct" and self._settings.get("user_instructions"): payload["user_instructions"] = self._settings["user_instructions"] headers = { diff --git a/tests/test_camb_tts.py b/tests/test_camb_tts.py index 71cc99c99..f1034c5af 100644 --- a/tests/test_camb_tts.py +++ b/tests/test_camb_tts.py @@ -46,7 +46,7 @@ async def test_run_camb_tts_success(aiohttp_client): assert "text" in body assert body["voice_id"] == 2681 assert body["language"] == "en-us" - assert body["speech_model"] == "mars-8-flash" + assert body["speech_model"] == "mars-flash" assert body["output_configuration"]["format"] == "pcm_s16le" # Prepare a StreamResponse with chunked PCM data @@ -78,7 +78,7 @@ async def test_run_camb_tts_success(aiohttp_client): aiohttp_session=session, base_url=base_url, voice_id=2681, - model="mars-8-flash", + model="mars-flash", ) # Manually set sample rate (normally done by StartFrame) @@ -367,7 +367,7 @@ async def test_language_mapping(): @pytest.mark.asyncio async def test_mars8_instruct_model(aiohttp_client): - """Test that user_instructions are included for mars-8-instruct model.""" + """Test that user_instructions are included for mars-instruct model.""" received_payload = {} @@ -392,7 +392,7 @@ async def test_mars8_instruct_model(aiohttp_client): api_key="test-api-key", aiohttp_session=session, base_url=base_url, - model="mars-8-instruct", + model="mars-instruct", params=CambTTSService.InputParams(user_instructions="Speak with excitement"), ) @@ -413,7 +413,7 @@ async def test_mars8_instruct_model(aiohttp_client): ) # Verify user_instructions was included in the request - assert received_payload.get("speech_model") == "mars-8-instruct" + assert received_payload.get("speech_model") == "mars-instruct" assert received_payload.get("user_instructions") == "Speak with excitement" From 56da2caeed0397c55045d645c5371012ddb94336 Mon Sep 17 00:00:00 2001 From: Neil Ruaro Date: Fri, 9 Jan 2026 18:30:38 +0900 Subject: [PATCH 0068/1060] Update Camb.ai TTS inference options --- .../foundational/07zb-interruptible-camb-local.py | 3 --- src/pipecat/services/camb/tts.py | 12 +++--------- tests/test_camb_tts.py | 3 --- 3 files changed, 3 insertions(+), 15 deletions(-) diff --git a/examples/foundational/07zb-interruptible-camb-local.py b/examples/foundational/07zb-interruptible-camb-local.py index f8c3fbbd6..d2c1cfcd8 100644 --- a/examples/foundational/07zb-interruptible-camb-local.py +++ b/examples/foundational/07zb-interruptible-camb-local.py @@ -74,9 +74,6 @@ async def main(voice_id: int): aiohttp_session=session, voice_id=voice_id, model="mars-flash", - params=CambTTSService.InputParams( - speed=1.0, - ), ) # OpenAI LLM diff --git a/src/pipecat/services/camb/tts.py b/src/pipecat/services/camb/tts.py index 9348c9964..7e221605f 100644 --- a/src/pipecat/services/camb/tts.py +++ b/src/pipecat/services/camb/tts.py @@ -14,7 +14,7 @@ Features: - 140+ languages supported - Real-time HTTP streaming - 24kHz audio output - - Voice customization (speed, instructions) + - Voice customization (instructions for mars-instruct) """ import asyncio @@ -129,8 +129,7 @@ class CambTTSService(TTSService): """Camb.ai MARS HTTP-based text-to-speech service. Converts text to speech using Camb.ai's MARS TTS models with support for - multiple languages. Provides control over voice characteristics like speed - and custom instructions (for mars-instruct model). + multiple languages. Provides custom instructions support for the mars-instruct model. Example:: @@ -140,8 +139,7 @@ class CambTTSService(TTSService): model="mars-flash", aiohttp_session=session, params=CambTTSService.InputParams( - language=Language.EN, - speed=1.0 + language=Language.EN ) ) @@ -163,13 +161,11 @@ class CambTTSService(TTSService): Parameters: language: Language for synthesis (BCP-47 format). Defaults to English. - speed: Speech speed multiplier (0.5 to 2.0). Defaults to 1.0. user_instructions: Custom instructions for mars-instruct model only. Ignored for other models. Max 1000 characters. """ language: Optional[Language] = Language.EN - speed: Optional[float] = Field(default=1.0, ge=0.5, le=2.0) user_instructions: Optional[str] = Field( default=None, max_length=1000, @@ -223,7 +219,6 @@ class CambTTSService(TTSService): if params.language else DEFAULT_LANGUAGE ), - "speed": params.speed or 1.0, "user_instructions": params.user_instructions, } @@ -312,7 +307,6 @@ class CambTTSService(TTSService): "language": self._settings["language"], "speech_model": self._model_name, "output_configuration": {"format": "pcm_s16le"}, - "voice_settings": {"speed": self._settings["speed"]}, } # Add user instructions if using mars-instruct model diff --git a/tests/test_camb_tts.py b/tests/test_camb_tts.py index f1034c5af..ecd6f45fb 100644 --- a/tests/test_camb_tts.py +++ b/tests/test_camb_tts.py @@ -336,17 +336,14 @@ async def test_input_params(): # Test defaults params = CambTTSService.InputParams() assert params.language == Language.EN - assert params.speed == 1.0 assert params.user_instructions is None # Test custom values params = CambTTSService.InputParams( language=Language.ES, - speed=1.5, user_instructions="Speak slowly and clearly", ) assert params.language == Language.ES - assert params.speed == 1.5 assert params.user_instructions == "Speak slowly and clearly" From 78fa2ab65e7746e376cc09beae15cee103c3a312 Mon Sep 17 00:00:00 2001 From: Neil Ruaro Date: Fri, 9 Jan 2026 21:22:33 +0900 Subject: [PATCH 0069/1060] Update default voice ID, fix MARS naming, and clean up example --- .../07zb-interruptible-camb-local.py | 31 ++++++++----------- src/pipecat/services/camb/tts.py | 12 +++---- tests/test_camb_tts.py | 2 +- 3 files changed, 19 insertions(+), 26 deletions(-) diff --git a/examples/foundational/07zb-interruptible-camb-local.py b/examples/foundational/07zb-interruptible-camb-local.py index d2c1cfcd8..19ef0bbed 100644 --- a/examples/foundational/07zb-interruptible-camb-local.py +++ b/examples/foundational/07zb-interruptible-camb-local.py @@ -4,10 +4,10 @@ # SPDX-License-Identifier: BSD 2-Clause License # -"""Camb.ai MARS-8 TTS example with local audio (microphone/speakers). +"""Camb.ai MARS TTS example with local audio (microphone/speakers). This example demonstrates: -- Basic TTS synthesis with Camb.ai MARS-8 +- Basic TTS synthesis with Camb.ai MARS - Local audio input/output (no WebRTC or Daily needed) - Handling interruptions @@ -83,7 +83,7 @@ async def main(voice_id: int): messages = [ { "role": "system", - "content": """You are a helpful voice assistant powered by Camb.ai's MARS-8 + "content": """You are a helpful voice assistant powered by Camb.ai's MARS text-to-speech technology. Keep your responses concise and conversational since they will be spoken aloud. Avoid special characters, emojis, or bullet points.""", }, @@ -117,14 +117,9 @@ they will be spoken aloud. Avoid special characters, emojis, or bullet points."" ), ) - # Run the pipeline - runner = PipelineRunner() - logger.info("Starting Camb.ai TTS bot with local audio...") - logger.info("Speak into your microphone to interact with the bot.") - - # Start the conversation with a greeting after a short delay - async def start_greeting(): - await asyncio.sleep(1) # Wait for pipeline to start + # Start the conversation when the pipeline is ready + @task.event_handler("on_pipeline_started") + async def on_pipeline_started(task, frame): messages.append( { "role": "system", @@ -133,11 +128,11 @@ they will be spoken aloud. Avoid special characters, emojis, or bullet points."" ) await task.queue_frames([LLMRunFrame()]) - # Run greeting and pipeline concurrently - await asyncio.gather( - runner.run(task), - start_greeting(), - ) + # Run the pipeline + runner = PipelineRunner() + logger.info("Starting Camb.ai TTS bot with local audio...") + logger.info("Speak into your microphone to interact with the bot.") + await runner.run(task) if __name__ == "__main__": @@ -145,8 +140,8 @@ if __name__ == "__main__": parser.add_argument( "--voice-id", type=int, - default=2681, - help="Camb.ai voice ID to use (default: 2681 - Attic voice)", + default=147320, + help="Camb.ai voice ID to use (default: 147320)", ) args = parser.parse_args() asyncio.run(main(args.voice_id)) diff --git a/src/pipecat/services/camb/tts.py b/src/pipecat/services/camb/tts.py index 7e221605f..f2517a362 100644 --- a/src/pipecat/services/camb/tts.py +++ b/src/pipecat/services/camb/tts.py @@ -38,7 +38,7 @@ from pipecat.utils.tracing.service_decorators import traced_tts # Default configuration -DEFAULT_VOICE_ID = 2681 # Attic voice (publicly available) +DEFAULT_VOICE_ID = 147320 DEFAULT_LANGUAGE = "en-us" DEFAULT_MODEL = "mars-flash" # Faster inference DEFAULT_BASE_URL = "https://client.camb.ai/apis" @@ -135,7 +135,7 @@ class CambTTSService(TTSService): tts = CambTTSService( api_key="your-api-key", - voice_id=2681, + voice_id=147320, model="mars-flash", aiohttp_session=session, params=CambTTSService.InputParams( @@ -146,7 +146,7 @@ class CambTTSService(TTSService): # For mars-instruct with custom instructions: tts_instruct = CambTTSService( api_key="your-api-key", - voice_id=2681, + voice_id=147320, model="mars-instruct", aiohttp_session=session, params=CambTTSService.InputParams( @@ -190,7 +190,7 @@ class CambTTSService(TTSService): Args: api_key: Camb.ai API key for authentication. aiohttp_session: Shared aiohttp session for making HTTP requests. - voice_id: Voice ID to use (e.g., 2681 for Attic). Defaults to 2681. + voice_id: Voice ID to use. Defaults to 147320. model: TTS model to use. Options: "mars-flash", "mars-pro", "mars-instruct". Defaults to "mars-flash" (fastest). base_url: Camb.ai API base URL. Defaults to production URL. @@ -338,10 +338,8 @@ class CambTTSService(TTSService): await self.start_tts_usage_metrics(text) yield TTSStartedFrame() - CHUNK_SIZE = self.chunk_size - async for frame in self._stream_audio_frames_from_iterator( - response.content.iter_chunked(CHUNK_SIZE), strip_wav_header=False + response.content.iter_chunked(self.chunk_size), strip_wav_header=False ): await self.stop_ttfb_metrics() yield frame diff --git a/tests/test_camb_tts.py b/tests/test_camb_tts.py index ecd6f45fb..03b4bee1f 100644 --- a/tests/test_camb_tts.py +++ b/tests/test_camb_tts.py @@ -363,7 +363,7 @@ async def test_language_mapping(): @pytest.mark.asyncio -async def test_mars8_instruct_model(aiohttp_client): +async def test_mars_instruct_model(aiohttp_client): """Test that user_instructions are included for mars-instruct model.""" received_payload = {} From c1f3cbd1d41d5e4bd4741732c18498f87e9cc388 Mon Sep 17 00:00:00 2001 From: Neil Ruaro Date: Mon, 12 Jan 2026 17:51:38 +0900 Subject: [PATCH 0070/1060] Yield TTSAudioRawFrame directly instead of calling private method --- src/pipecat/services/camb/tts.py | 13 ++++++++----- 1 file changed, 8 insertions(+), 5 deletions(-) diff --git a/src/pipecat/services/camb/tts.py b/src/pipecat/services/camb/tts.py index f2517a362..d0471d63d 100644 --- a/src/pipecat/services/camb/tts.py +++ b/src/pipecat/services/camb/tts.py @@ -338,11 +338,14 @@ class CambTTSService(TTSService): await self.start_tts_usage_metrics(text) yield TTSStartedFrame() - async for frame in self._stream_audio_frames_from_iterator( - response.content.iter_chunked(self.chunk_size), strip_wav_header=False - ): - await self.stop_ttfb_metrics() - yield frame + async for chunk in response.content.iter_chunked(self.chunk_size): + if chunk: + await self.stop_ttfb_metrics() + yield TTSAudioRawFrame( + audio=chunk, + sample_rate=self.sample_rate, + num_channels=1, + ) except aiohttp.ClientError as e: error_msg = f"Network error communicating with Camb.ai: {e}" From 9293b5f24a3b08b40eee767be38a36dd3786f6aa Mon Sep 17 00:00:00 2001 From: Neil Ruaro Date: Mon, 12 Jan 2026 19:23:43 +0900 Subject: [PATCH 0071/1060] Migrate Camb TTS service from raw HTTP to official SDK - Replace aiohttp with camb SDK (AsyncCambAI client) - Add support for passing existing SDK client instance - Simplify API: no longer requires aiohttp_session parameter - Update example to use simplified initialization - Rewrite tests to mock SDK client instead of HTTP servers --- .../07zb-interruptible-camb-local.py | 114 +++--- src/pipecat/services/camb/tts.py | 229 +++++------- tests/test_camb_tts.py | 334 ++++++------------ 3 files changed, 242 insertions(+), 435 deletions(-) diff --git a/examples/foundational/07zb-interruptible-camb-local.py b/examples/foundational/07zb-interruptible-camb-local.py index 19ef0bbed..6ddea3db0 100644 --- a/examples/foundational/07zb-interruptible-camb-local.py +++ b/examples/foundational/07zb-interruptible-camb-local.py @@ -28,7 +28,6 @@ import asyncio import os import sys -import aiohttp from dotenv import load_dotenv from loguru import logger @@ -66,73 +65,70 @@ async def main(voice_id: int): # Deepgram STT for speech recognition stt = DeepgramSTTService(api_key=os.getenv("DEEPGRAM_API_KEY")) - # Create HTTP session for Camb.ai TTS - async with aiohttp.ClientSession() as session: - # Camb.ai TTS with MARS-flash model - tts = CambTTSService( - api_key=os.getenv("CAMB_API_KEY"), - aiohttp_session=session, - voice_id=voice_id, - model="mars-flash", - ) + # Camb.ai TTS with MARS-flash model (uses official SDK) + tts = CambTTSService( + api_key=os.getenv("CAMB_API_KEY"), + voice_id=voice_id, + model="mars-flash", + ) - # OpenAI LLM - llm = OpenAILLMService(api_key=os.getenv("OPENAI_API_KEY")) + # OpenAI LLM + llm = OpenAILLMService(api_key=os.getenv("OPENAI_API_KEY")) - # System prompt - messages = [ - { - "role": "system", - "content": """You are a helpful voice assistant powered by Camb.ai's MARS + # System prompt + messages = [ + { + "role": "system", + "content": """You are a helpful voice assistant powered by Camb.ai's MARS text-to-speech technology. Keep your responses concise and conversational since they will be spoken aloud. Avoid special characters, emojis, or bullet points.""", - }, + }, + ] + + # Context management + context = LLMContext(messages) + context_aggregator = LLMContextAggregatorPair(context) + + # Build the pipeline + pipeline = Pipeline( + [ + transport.input(), # Microphone input + stt, # Speech-to-text + context_aggregator.user(), # User context + llm, # Language model + tts, # Camb.ai TTS + transport.output(), # Speaker output + context_aggregator.assistant(), # Assistant context ] + ) - # Context management - context = LLMContext(messages) - context_aggregator = LLMContextAggregatorPair(context) + # Create pipeline task + # Use 24kHz sample rate to match Camb.ai TTS output + task = PipelineTask( + pipeline, + params=PipelineParams( + audio_out_sample_rate=24000, + enable_metrics=True, + enable_usage_metrics=True, + ), + ) - # Build the pipeline - pipeline = Pipeline( - [ - transport.input(), # Microphone input - stt, # Speech-to-text - context_aggregator.user(), # User context - llm, # Language model - tts, # Camb.ai TTS - transport.output(), # Speaker output - context_aggregator.assistant(), # Assistant context - ] + # Start the conversation when the pipeline is ready + @task.event_handler("on_pipeline_started") + async def on_pipeline_started(task, frame): + messages.append( + { + "role": "system", + "content": "Please introduce yourself briefly and ask how you can help.", + } ) + await task.queue_frames([LLMRunFrame()]) - # Create pipeline task - # Use 24kHz sample rate to match Camb.ai TTS output - task = PipelineTask( - pipeline, - params=PipelineParams( - audio_out_sample_rate=24000, - enable_metrics=True, - enable_usage_metrics=True, - ), - ) - - # Start the conversation when the pipeline is ready - @task.event_handler("on_pipeline_started") - async def on_pipeline_started(task, frame): - messages.append( - { - "role": "system", - "content": "Please introduce yourself briefly and ask how you can help.", - } - ) - await task.queue_frames([LLMRunFrame()]) - - # Run the pipeline - runner = PipelineRunner() - logger.info("Starting Camb.ai TTS bot with local audio...") - logger.info("Speak into your microphone to interact with the bot.") - await runner.run(task) + # Run the pipeline + runner = PipelineRunner() + logger.info("Starting Camb.ai TTS bot with local audio...") + logger.info("Speak into your microphone to interact with the bot.") + await runner.run(task) if __name__ == "__main__": diff --git a/src/pipecat/services/camb/tts.py b/src/pipecat/services/camb/tts.py index d0471d63d..efe9cbb8d 100644 --- a/src/pipecat/services/camb/tts.py +++ b/src/pipecat/services/camb/tts.py @@ -7,20 +7,20 @@ """Camb.ai MARS text-to-speech service implementation. This module provides TTS functionality using Camb.ai's MARS model family, -offering high-quality text-to-speech synthesis with HTTP streaming support. +offering high-quality text-to-speech synthesis with streaming support. Features: - MARS models: mars-flash, mars-pro, mars-instruct - 140+ languages supported - - Real-time HTTP streaming + - Real-time streaming via official SDK - 24kHz audio output - Voice customization (instructions for mars-instruct) """ -import asyncio from typing import Any, AsyncGenerator, Dict, List, Mapping, Optional -import aiohttp +from camb.client import AsyncCambAI +from camb import StreamTtsOutputConfiguration from loguru import logger from pydantic import BaseModel, Field @@ -41,7 +41,6 @@ from pipecat.utils.tracing.service_decorators import traced_tts DEFAULT_VOICE_ID = 147320 DEFAULT_LANGUAGE = "en-us" DEFAULT_MODEL = "mars-flash" # Faster inference -DEFAULT_BASE_URL = "https://client.camb.ai/apis" DEFAULT_SAMPLE_RATE = 24000 # 24kHz DEFAULT_TIMEOUT = 60.0 # Seconds (minimum recommended by Camb.ai) MIN_TEXT_LENGTH = 3 @@ -126,29 +125,36 @@ def language_to_camb_language(language: Language) -> Optional[str]: class CambTTSService(TTSService): - """Camb.ai MARS HTTP-based text-to-speech service. + """Camb.ai MARS text-to-speech service using the official SDK. Converts text to speech using Camb.ai's MARS TTS models with support for multiple languages. Provides custom instructions support for the mars-instruct model. Example:: + # Using API key (creates internal client) tts = CambTTSService( api_key="your-api-key", voice_id=147320, model="mars-flash", - aiohttp_session=session, params=CambTTSService.InputParams( language=Language.EN ) ) + # Using existing SDK client + client = AsyncCambAI(api_key="your-api-key") + tts = CambTTSService( + client=client, + voice_id=147320, + model="mars-flash", + ) + # For mars-instruct with custom instructions: tts_instruct = CambTTSService( api_key="your-api-key", voice_id=147320, model="mars-instruct", - aiohttp_session=session, params=CambTTSService.InputParams( language=Language.EN, user_instructions="Speak with excitement and energy" @@ -176,11 +182,10 @@ class CambTTSService(TTSService): def __init__( self, *, - api_key: str, - aiohttp_session: aiohttp.ClientSession, + api_key: Optional[str] = None, + client: Optional[AsyncCambAI] = None, voice_id: int = DEFAULT_VOICE_ID, model: str = DEFAULT_MODEL, - base_url: str = DEFAULT_BASE_URL, sample_rate: Optional[int] = None, params: Optional[InputParams] = None, **kwargs, @@ -188,29 +193,29 @@ class CambTTSService(TTSService): """Initialize the Camb.ai TTS service. Args: - api_key: Camb.ai API key for authentication. - aiohttp_session: Shared aiohttp session for making HTTP requests. + api_key: Camb.ai API key for authentication. Required if client is not provided. + client: Existing AsyncCambAI client instance. If provided, api_key is ignored. voice_id: Voice ID to use. Defaults to 147320. model: TTS model to use. Options: "mars-flash", "mars-pro", "mars-instruct". Defaults to "mars-flash" (fastest). - base_url: Camb.ai API base URL. Defaults to production URL. sample_rate: Audio sample rate in Hz. If None, uses Camb.ai default (24000). params: Additional voice parameters. If None, uses defaults. **kwargs: Additional arguments passed to parent TTSService. """ super().__init__(sample_rate=sample_rate, **kwargs) + if client is None and api_key is None: + raise ValueError("Either 'api_key' or 'client' must be provided") + params = params or CambTTSService.InputParams() - self._api_key = api_key - self._session = aiohttp_session - - # Remove trailing slash from base URL - if base_url.endswith("/"): - logger.warning("Base URL ends with a slash, removing it.") - base_url = base_url[:-1] - - self._base_url = base_url + # Use provided client or create one + if client is not None: + self._client = client + self._owns_client = False + else: + self._client = AsyncCambAI(api_key=api_key, timeout=DEFAULT_TIMEOUT) + self._owns_client = True # Build settings self._settings = { @@ -300,63 +305,37 @@ class CambTTSService(TTSService): ) text = text[:MAX_TEXT_LENGTH] - # Build request payload - payload = { - "text": text, - "voice_id": self._voice_id_int, - "language": self._settings["language"], - "speech_model": self._model_name, - "output_configuration": {"format": "pcm_s16le"}, - } - - # Add user instructions if using mars-instruct model - if self._model_name == "mars-instruct" and self._settings.get("user_instructions"): - payload["user_instructions"] = self._settings["user_instructions"] - - headers = { - "x-api-key": self._api_key, - "Accept": "application/json", - "Content-Type": "application/json", - } - try: await self.start_ttfb_metrics() - async with self._session.post( - f"{self._base_url}/tts-stream", - json=payload, - headers=headers, - timeout=aiohttp.ClientTimeout(total=DEFAULT_TIMEOUT), - ) as response: - if response.status != 200: - error_text = await response.text() - error_msg = self._format_error_message(response.status, error_text) - logger.error(f"{self}: {error_msg}") - yield ErrorFrame(error=error_msg) - return + # Build SDK parameters + tts_kwargs: Dict[str, Any] = { + "text": text, + "voice_id": self._voice_id_int, + "language": self._settings["language"], + "speech_model": self._model_name, + "output_configuration": StreamTtsOutputConfiguration(format="pcm_s16le"), + } - await self.start_tts_usage_metrics(text) - yield TTSStartedFrame() + # Add user instructions if using mars-instruct model + if self._model_name == "mars-instruct" and self._settings.get("user_instructions"): + tts_kwargs["user_instructions"] = self._settings["user_instructions"] - async for chunk in response.content.iter_chunked(self.chunk_size): - if chunk: - await self.stop_ttfb_metrics() - yield TTSAudioRawFrame( - audio=chunk, - sample_rate=self.sample_rate, - num_channels=1, - ) + await self.start_tts_usage_metrics(text) + yield TTSStartedFrame() + + # Stream audio chunks from SDK + async for chunk in self._client.text_to_speech.tts(**tts_kwargs): + if chunk: + await self.stop_ttfb_metrics() + yield TTSAudioRawFrame( + audio=chunk, + sample_rate=self.sample_rate, + num_channels=1, + ) - except aiohttp.ClientError as e: - error_msg = f"Network error communicating with Camb.ai: {e}" - logger.error(f"{self}: {error_msg}") - yield ErrorFrame(error=error_msg) - except asyncio.TimeoutError: - error_msg = f"Timeout waiting for Camb.ai TTS response (>{DEFAULT_TIMEOUT}s)" - logger.error(f"{self}: {error_msg}") - yield ErrorFrame(error=error_msg) except Exception as e: - error_msg = f"Unexpected error in Camb.ai TTS: {e}" + error_msg = f"Camb.ai TTS error: {e}" logger.error(f"{self}: {error_msg}") yield ErrorFrame(error=error_msg) finally: @@ -364,74 +343,37 @@ class CambTTSService(TTSService): await self.stop_ttfb_metrics() yield TTSStoppedFrame() - def _format_error_message(self, status: int, error_text: str) -> str: - """Format error message based on HTTP status code. - - Args: - status: HTTP status code. - error_text: Error response body. - - Returns: - Formatted, user-friendly error message. - """ - if status == 401: - return ( - "Invalid Camb.ai API key. " - "Set CAMB_API_KEY environment variable with your API key from https://camb.ai" - ) - elif status == 403: - return ( - f"Voice ID {self._voice_id_int} is not accessible with your API key. " - "Use list_voices() to see available voices." - ) - elif status == 404: - return ( - f"Invalid voice ID: {self._voice_id_int}. " - "Use list_voices() to see available voices." - ) - elif status == 429: - return "Camb.ai rate limit exceeded. Please wait before making more requests." - elif status >= 500: - return f"Camb.ai server error (status {status}): {error_text}" - else: - return f"Camb.ai API error (status {status}): {error_text}" - @staticmethod async def list_voices( - api_key: str, - aiohttp_session: aiohttp.ClientSession, - base_url: str = DEFAULT_BASE_URL, + api_key: Optional[str] = None, + client: Optional[AsyncCambAI] = None, ) -> List[Dict[str, Any]]: """Fetch available voices from Camb.ai API. Args: - api_key: Camb.ai API key for authentication. - aiohttp_session: aiohttp ClientSession for making HTTP requests. - base_url: Camb.ai API base URL. + api_key: Camb.ai API key for authentication. Required if client is not provided. + client: Existing AsyncCambAI client instance. If provided, api_key is ignored. Returns: List of voice dictionaries with id, name, gender, and language fields. Raises: + ValueError: If neither api_key nor client is provided. Exception: If the API request fails. Example:: - async with aiohttp.ClientSession() as session: - voices = await CambTTSService.list_voices( - api_key="your-api-key", - aiohttp_session=session, - ) - for voice in voices: - print(f"{voice['id']}: {voice['name']}") - """ - if base_url.endswith("/"): - base_url = base_url[:-1] + # Using API key + voices = await CambTTSService.list_voices(api_key="your-api-key") + for voice in voices: + print(f"{voice['id']}: {voice['name']}") - headers = { - "x-api-key": api_key, - "Accept": "application/json", - } + # Using existing client + client = AsyncCambAI(api_key="your-api-key") + voices = await CambTTSService.list_voices(client=client) + """ + if client is None and api_key is None: + raise ValueError("Either 'api_key' or 'client' must be provided") gender_map = { 0: "Not Specified", @@ -440,23 +382,22 @@ class CambTTSService(TTSService): 9: "Not Applicable", } - async with aiohttp_session.get( - f"{base_url}/list-voices", - headers=headers, - timeout=aiohttp.ClientTimeout(total=30.0), - ) as response: - if response.status != 200: - error_text = await response.text() - raise Exception(f"Failed to list voices (status {response.status}): {error_text}") + # Use provided client or create a temporary one + if client is not None: + sdk_client = client + else: + sdk_client = AsyncCambAI(api_key=api_key) - data = await response.json() - return [ - { - "id": v["id"], - "name": v.get("voice_name", "Unknown"), - "gender": gender_map.get(v.get("gender"), "Unknown"), - "age": v.get("age"), - "language": v.get("language"), - } - for v in data - ] + voices = await sdk_client.voice_cloning.list_voices() + return [ + { + "id": v.id if hasattr(v, "id") else v.get("id"), + "name": v.voice_name if hasattr(v, "voice_name") else v.get("voice_name", "Unknown"), + "gender": gender_map.get( + v.gender if hasattr(v, "gender") else v.get("gender"), "Unknown" + ), + "age": v.age if hasattr(v, "age") else v.get("age"), + "language": v.language if hasattr(v, "language") else v.get("language"), + } + for v in voices + ] diff --git a/tests/test_camb_tts.py b/tests/test_camb_tts.py index 03b4bee1f..571cf67d8 100644 --- a/tests/test_camb_tts.py +++ b/tests/test_camb_tts.py @@ -6,14 +6,12 @@ """Tests for CambTTSService. -These tests use mock servers to simulate the Camb.ai API responses. +These tests mock the Camb.ai SDK client to test the service behavior. """ -import asyncio +from unittest.mock import AsyncMock, MagicMock, patch -import aiohttp import pytest -from aiohttp import web from pipecat.frames.frames import ( AggregatedTextFrame, @@ -29,54 +27,30 @@ from pipecat.tests.utils import run_test from pipecat.transcriptions.language import Language +async def mock_tts_stream(*args, **kwargs): + """Mock TTS stream that yields audio chunks.""" + yield b"\x00\x01" * 4800 # Small chunk of PCM audio + + +async def mock_tts_stream_error(*args, **kwargs): + """Mock TTS stream that raises an error.""" + raise Exception("API error: Invalid API key") + yield # Make this a generator + + @pytest.mark.asyncio -async def test_run_camb_tts_success(aiohttp_client): +async def test_run_camb_tts_success(): """Test successful TTS generation with chunked PCM audio. Verifies the frame sequence: TTSStartedFrame -> TTSAudioRawFrame* -> TTSStoppedFrame """ + with patch("pipecat.services.camb.tts.AsyncCambAI") as MockAsyncCambAI: + mock_client = MagicMock() + mock_client.text_to_speech.tts = mock_tts_stream + MockAsyncCambAI.return_value = mock_client - async def handler(request): - # Verify request headers - assert request.headers.get("x-api-key") == "test-api-key" - assert request.headers.get("Content-Type") == "application/json" - - # Parse and verify request body - body = await request.json() - assert "text" in body - assert body["voice_id"] == 2681 - assert body["language"] == "en-us" - assert body["speech_model"] == "mars-flash" - assert body["output_configuration"]["format"] == "pcm_s16le" - - # Prepare a StreamResponse with chunked PCM data - resp = web.StreamResponse( - status=200, - reason="OK", - headers={"Content-Type": "audio/raw"}, - ) - await resp.prepare(request) - - # Write out chunked PCM byte data (16-bit samples) - # Use smaller chunks for more predictable frame count - data = b"\x00\x01" * 4800 # Small chunk of audio - await resp.write(data) - await resp.write_eof() - - return resp - - # Create an aiohttp test server - app = web.Application() - app.router.add_post("/tts-stream", handler) - client = await aiohttp_client(app) - - base_url = str(client.make_url("")).rstrip("/") - - async with aiohttp.ClientSession() as session: tts_service = CambTTSService( api_key="test-api-key", - aiohttp_session=session, - base_url=base_url, voice_id=2681, model="mars-flash", ) @@ -106,32 +80,24 @@ async def test_run_camb_tts_success(aiohttp_client): @pytest.mark.asyncio -async def test_run_camb_tts_error_401(aiohttp_client): - """Test handling of invalid API key (401 Unauthorized).""" +async def test_run_camb_tts_error(): + """Test handling of TTS API errors.""" + with patch("pipecat.services.camb.tts.AsyncCambAI") as MockAsyncCambAI: + mock_client = MagicMock() + mock_client.text_to_speech.tts = mock_tts_stream_error + MockAsyncCambAI.return_value = mock_client - async def handler(request): - return web.Response( - status=401, - text="Unauthorized: Invalid API key", - ) - - app = web.Application() - app.router.add_post("/tts-stream", handler) - client = await aiohttp_client(app) - base_url = str(client.make_url("")).rstrip("/") - - async with aiohttp.ClientSession() as session: tts_service = CambTTSService( api_key="invalid-key", - aiohttp_session=session, - base_url=base_url, + voice_id=147320, ) frames_to_send = [ TTSSpeakFrame(text="This should fail."), ] - expected_down_frames = [AggregatedTextFrame, TTSStoppedFrame, TTSTextFrame] + # TTSStartedFrame is emitted before we attempt to iterate the stream + expected_down_frames = [AggregatedTextFrame, TTSStartedFrame, TTSStoppedFrame, TTSTextFrame] expected_up_frames = [ErrorFrame] frames_received = await run_test( @@ -142,143 +108,38 @@ async def test_run_camb_tts_error_401(aiohttp_client): ) up_frames = frames_received[1] - assert isinstance(up_frames[0], ErrorFrame), "Must receive an ErrorFrame for 401" - assert "Invalid Camb.ai API key" in up_frames[0].error, ( - "ErrorFrame should mention invalid API key" - ) + assert isinstance(up_frames[0], ErrorFrame), "Must receive an ErrorFrame" + assert "error" in up_frames[0].error.lower(), "ErrorFrame should contain error message" @pytest.mark.asyncio -async def test_run_camb_tts_error_404(aiohttp_client): - """Test handling of invalid voice ID (404 Not Found).""" - - async def handler(request): - return web.Response( - status=404, - text="Voice not found", - ) - - app = web.Application() - app.router.add_post("/tts-stream", handler) - client = await aiohttp_client(app) - base_url = str(client.make_url("")).rstrip("/") - - async with aiohttp.ClientSession() as session: - tts_service = CambTTSService( - api_key="test-api-key", - aiohttp_session=session, - base_url=base_url, - voice_id=99999, # Invalid voice ID - ) - - frames_to_send = [ - TTSSpeakFrame(text="This should fail."), - ] - - expected_down_frames = [AggregatedTextFrame, TTSStoppedFrame, TTSTextFrame] - expected_up_frames = [ErrorFrame] - - frames_received = await run_test( - tts_service, - frames_to_send=frames_to_send, - expected_down_frames=expected_down_frames, - expected_up_frames=expected_up_frames, - ) - up_frames = frames_received[1] - - assert isinstance(up_frames[0], ErrorFrame), "Must receive an ErrorFrame for 404" - assert "Invalid voice ID" in up_frames[0].error, ( - "ErrorFrame should mention invalid voice ID" - ) - - -@pytest.mark.asyncio -async def test_run_camb_tts_error_429(aiohttp_client): - """Test handling of rate limit (429 Too Many Requests).""" - - async def handler(request): - return web.Response( - status=429, - text="Rate limit exceeded", - ) - - app = web.Application() - app.router.add_post("/tts-stream", handler) - client = await aiohttp_client(app) - base_url = str(client.make_url("")).rstrip("/") - - async with aiohttp.ClientSession() as session: - tts_service = CambTTSService( - api_key="test-api-key", - aiohttp_session=session, - base_url=base_url, - ) - - frames_to_send = [ - TTSSpeakFrame(text="This should fail due to rate limit."), - ] - - expected_down_frames = [AggregatedTextFrame, TTSStoppedFrame, TTSTextFrame] - expected_up_frames = [ErrorFrame] - - frames_received = await run_test( - tts_service, - frames_to_send=frames_to_send, - expected_down_frames=expected_down_frames, - expected_up_frames=expected_up_frames, - ) - up_frames = frames_received[1] - - assert isinstance(up_frames[0], ErrorFrame), "Must receive an ErrorFrame for 429" - assert "rate limit" in up_frames[0].error.lower(), ( - "ErrorFrame should mention rate limit" - ) - - -@pytest.mark.asyncio -async def test_list_voices(aiohttp_client): +async def test_list_voices(): """Test voice listing endpoint.""" - async def handler(request): - # Verify API key header - assert request.headers.get("x-api-key") == "test-api-key" + async def mock_list_voices(*args, **kwargs): + # Return mock Voice objects + mock_voice1 = MagicMock() + mock_voice1.id = 2681 + mock_voice1.voice_name = "Attic" + mock_voice1.gender = 1 + mock_voice1.age = 25 + mock_voice1.language = None - # Return mock voice data (matching actual API response structure) - voices = [ - { - "id": 2681, - "voice_name": "Attic", - "gender": 1, - "age": 25, - "language": None, - "transcript": None, - "description": None, - "is_published": None, - }, - { - "id": 2682, - "voice_name": "Cellar", - "gender": 2, - "age": 30, - "language": 1, - "transcript": None, - "description": None, - "is_published": False, - }, - ] - return web.json_response(voices) + mock_voice2 = MagicMock() + mock_voice2.id = 2682 + mock_voice2.voice_name = "Cellar" + mock_voice2.gender = 2 + mock_voice2.age = 30 + mock_voice2.language = 1 - app = web.Application() - app.router.add_get("/list-voices", handler) - client = await aiohttp_client(app) - base_url = str(client.make_url("")).rstrip("/") + return [mock_voice1, mock_voice2] - async with aiohttp.ClientSession() as session: - voices = await CambTTSService.list_voices( - api_key="test-api-key", - aiohttp_session=session, - base_url=base_url, - ) + with patch("pipecat.services.camb.tts.AsyncCambAI") as MockAsyncCambAI: + mock_client = MagicMock() + mock_client.voice_cloning.list_voices = mock_list_voices + MockAsyncCambAI.return_value = mock_client + + voices = await CambTTSService.list_voices(api_key="test-api-key") # Should return all voices assert len(voices) == 2, "Should return all voices" @@ -291,23 +152,17 @@ async def test_list_voices(aiohttp_client): @pytest.mark.asyncio -async def test_text_length_validation_too_short(aiohttp_client): +async def test_text_length_validation_too_short(): """Test that text shorter than 3 characters is handled gracefully.""" + with patch("pipecat.services.camb.tts.AsyncCambAI") as MockAsyncCambAI: + mock_client = MagicMock() + # TTS should not be called for short text + mock_client.text_to_speech.tts = AsyncMock(side_effect=AssertionError("TTS should not be called")) + MockAsyncCambAI.return_value = mock_client - async def handler(request): - # This should not be called for short text - pytest.fail("Handler should not be called for text < 3 chars") - - app = web.Application() - app.router.add_post("/tts-stream", handler) - client = await aiohttp_client(app) - base_url = str(client.make_url("")).rstrip("/") - - async with aiohttp.ClientSession() as session: tts_service = CambTTSService( api_key="test-api-key", - aiohttp_session=session, - base_url=base_url, + voice_id=147320, ) frames_to_send = [ @@ -363,32 +218,22 @@ async def test_language_mapping(): @pytest.mark.asyncio -async def test_mars_instruct_model(aiohttp_client): +async def test_mars_instruct_model(): """Test that user_instructions are included for mars-instruct model.""" + received_kwargs = {} - received_payload = {} + async def mock_tts_with_capture(*args, **kwargs): + nonlocal received_kwargs + received_kwargs = kwargs + yield b"\x00" * 1000 - async def handler(request): - nonlocal received_payload - received_payload = await request.json() + with patch("pipecat.services.camb.tts.AsyncCambAI") as MockAsyncCambAI: + mock_client = MagicMock() + mock_client.text_to_speech.tts = mock_tts_with_capture + MockAsyncCambAI.return_value = mock_client - # Return minimal successful response - resp = web.StreamResponse(status=200, headers={"Content-Type": "audio/raw"}) - await resp.prepare(request) - await resp.write(b"\x00" * 1000) - await resp.write_eof() - return resp - - app = web.Application() - app.router.add_post("/tts-stream", handler) - client = await aiohttp_client(app) - base_url = str(client.make_url("")).rstrip("/") - - async with aiohttp.ClientSession() as session: tts_service = CambTTSService( api_key="test-api-key", - aiohttp_session=session, - base_url=base_url, model="mars-instruct", params=CambTTSService.InputParams(user_instructions="Speak with excitement"), ) @@ -410,19 +255,44 @@ async def test_mars_instruct_model(aiohttp_client): ) # Verify user_instructions was included in the request - assert received_payload.get("speech_model") == "mars-instruct" - assert received_payload.get("user_instructions") == "Speak with excitement" + assert received_kwargs.get("speech_model") == "mars-instruct" + assert received_kwargs.get("user_instructions") == "Speak with excitement" @pytest.mark.asyncio -async def test_base_url_trailing_slash(): - """Test that trailing slash in base URL is handled correctly.""" - async with aiohttp.ClientSession() as session: +async def test_client_initialization_with_api_key(): + """Test that client is created when api_key is provided.""" + with patch("pipecat.services.camb.tts.AsyncCambAI") as MockAsyncCambAI: + mock_client = MagicMock() + MockAsyncCambAI.return_value = mock_client + tts = CambTTSService( api_key="test-key", - aiohttp_session=session, - base_url="https://api.example.com/", # With trailing slash + voice_id=147320, ) - # Should have removed the trailing slash - assert tts._base_url == "https://api.example.com" + # Should have created a client + MockAsyncCambAI.assert_called_once() + assert tts._owns_client is True + + +@pytest.mark.asyncio +async def test_client_initialization_with_existing_client(): + """Test that existing client is used when provided.""" + mock_client = MagicMock() + + tts = CambTTSService( + client=mock_client, + voice_id=147320, + ) + + # Should use the provided client + assert tts._client is mock_client + assert tts._owns_client is False + + +@pytest.mark.asyncio +async def test_client_initialization_requires_api_key_or_client(): + """Test that ValueError is raised when neither api_key nor client is provided.""" + with pytest.raises(ValueError, match="Either 'api_key' or 'client' must be provided"): + CambTTSService(voice_id=147320) From 641d17007fc2f68d79b308327c3f33ba22e421a5 Mon Sep 17 00:00:00 2001 From: Neil Ruaro Date: Mon, 12 Jan 2026 22:20:42 +0900 Subject: [PATCH 0072/1060] Clean up Camb TTS service and tests --- .../07zb-interruptible-camb-local.py | 4 + src/pipecat/services/camb/tts.py | 111 ++++------ tests/test_camb_tts.py | 199 +++++++++++++----- 3 files changed, 185 insertions(+), 129 deletions(-) diff --git a/examples/foundational/07zb-interruptible-camb-local.py b/examples/foundational/07zb-interruptible-camb-local.py index 6ddea3db0..83e4ce0dc 100644 --- a/examples/foundational/07zb-interruptible-camb-local.py +++ b/examples/foundational/07zb-interruptible-camb-local.py @@ -34,6 +34,8 @@ from loguru import logger from pipecat.audio.vad.silero import SileroVADAnalyzer from pipecat.audio.vad.vad_analyzer import VADParams from pipecat.frames.frames import LLMRunFrame +from pipecat.metrics.metrics import TTFBMetricsData +from pipecat.observers.loggers.metrics_log_observer import MetricsLogObserver from pipecat.pipeline.pipeline import Pipeline from pipecat.pipeline.runner import PipelineRunner from pipecat.pipeline.task import PipelineParams, PipelineTask @@ -104,6 +106,7 @@ they will be spoken aloud. Avoid special characters, emojis, or bullet points."" # Create pipeline task # Use 24kHz sample rate to match Camb.ai TTS output + # Add MetricsLogObserver to track TTFB metrics task = PipelineTask( pipeline, params=PipelineParams( @@ -111,6 +114,7 @@ they will be spoken aloud. Avoid special characters, emojis, or bullet points."" enable_metrics=True, enable_usage_metrics=True, ), + observers=[MetricsLogObserver(include_metrics={TTFBMetricsData})], ) # Start the conversation when the pipeline is ready diff --git a/src/pipecat/services/camb/tts.py b/src/pipecat/services/camb/tts.py index efe9cbb8d..d5d800034 100644 --- a/src/pipecat/services/camb/tts.py +++ b/src/pipecat/services/camb/tts.py @@ -46,6 +46,9 @@ DEFAULT_TIMEOUT = 60.0 # Seconds (minimum recommended by Camb.ai) MIN_TEXT_LENGTH = 3 MAX_TEXT_LENGTH = 3000 +# Gender mapping for voice listing +GENDER_MAP = {0: "Not Specified", 1: "Male", 2: "Female", 9: "Not Applicable"} + def language_to_camb_language(language: Language) -> Optional[str]: """Convert a Pipecat Language enum to Camb.ai language code. @@ -132,31 +135,21 @@ class CambTTSService(TTSService): Example:: - # Using API key (creates internal client) + # Basic usage with defaults + tts = CambTTSService(api_key="your-api-key") + + # With custom voice and model tts = CambTTSService( api_key="your-api-key", - voice_id=147320, - model="mars-flash", - params=CambTTSService.InputParams( - language=Language.EN - ) - ) - - # Using existing SDK client - client = AsyncCambAI(api_key="your-api-key") - tts = CambTTSService( - client=client, - voice_id=147320, - model="mars-flash", + voice_id=12345, + model="mars-pro", ) # For mars-instruct with custom instructions: - tts_instruct = CambTTSService( + tts = CambTTSService( api_key="your-api-key", - voice_id=147320, model="mars-instruct", params=CambTTSService.InputParams( - language=Language.EN, user_instructions="Speak with excitement and energy" ) ) @@ -182,10 +175,10 @@ class CambTTSService(TTSService): def __init__( self, *, - api_key: Optional[str] = None, - client: Optional[AsyncCambAI] = None, + api_key: str, voice_id: int = DEFAULT_VOICE_ID, model: str = DEFAULT_MODEL, + timeout: float = DEFAULT_TIMEOUT, sample_rate: Optional[int] = None, params: Optional[InputParams] = None, **kwargs, @@ -193,29 +186,20 @@ class CambTTSService(TTSService): """Initialize the Camb.ai TTS service. Args: - api_key: Camb.ai API key for authentication. Required if client is not provided. - client: Existing AsyncCambAI client instance. If provided, api_key is ignored. - voice_id: Voice ID to use. Defaults to 147320. + api_key: Camb.ai API key for authentication. + voice_id: Voice ID to use. Defaults to DEFAULT_VOICE_ID. model: TTS model to use. Options: "mars-flash", "mars-pro", "mars-instruct". - Defaults to "mars-flash" (fastest). - sample_rate: Audio sample rate in Hz. If None, uses Camb.ai default (24000). + Defaults to DEFAULT_MODEL (mars-flash, fastest). + timeout: Request timeout in seconds. Defaults to DEFAULT_TIMEOUT (60s). + sample_rate: Audio sample rate in Hz. If None, uses DEFAULT_SAMPLE_RATE (24kHz). params: Additional voice parameters. If None, uses defaults. **kwargs: Additional arguments passed to parent TTSService. """ super().__init__(sample_rate=sample_rate, **kwargs) - if client is None and api_key is None: - raise ValueError("Either 'api_key' or 'client' must be provided") - params = params or CambTTSService.InputParams() - # Use provided client or create one - if client is not None: - self._client = client - self._owns_client = False - else: - self._client = AsyncCambAI(api_key=api_key, timeout=DEFAULT_TIMEOUT) - self._owns_client = True + self._client = AsyncCambAI(api_key=api_key, timeout=timeout) # Build settings self._settings = { @@ -344,60 +328,43 @@ class CambTTSService(TTSService): yield TTSStoppedFrame() @staticmethod - async def list_voices( - api_key: Optional[str] = None, - client: Optional[AsyncCambAI] = None, - ) -> List[Dict[str, Any]]: + async def list_voices(api_key: str) -> List[Dict[str, Any]]: """Fetch available voices from Camb.ai API. Args: - api_key: Camb.ai API key for authentication. Required if client is not provided. - client: Existing AsyncCambAI client instance. If provided, api_key is ignored. + api_key: Camb.ai API key for authentication. Returns: List of voice dictionaries with id, name, gender, and language fields. Raises: - ValueError: If neither api_key nor client is provided. Exception: If the API request fails. Example:: - # Using API key voices = await CambTTSService.list_voices(api_key="your-api-key") for voice in voices: print(f"{voice['id']}: {voice['name']}") - - # Using existing client - client = AsyncCambAI(api_key="your-api-key") - voices = await CambTTSService.list_voices(client=client) """ - if client is None and api_key is None: - raise ValueError("Either 'api_key' or 'client' must be provided") + client = AsyncCambAI(api_key=api_key) + voice_list = await client.voice_cloning.list_voices() - gender_map = { - 0: "Not Specified", - 1: "Male", - 2: "Female", - 9: "Not Applicable", - } + voices = [] + for voice in voice_list: + voice_id = voice.get("id") + # Skip voices without an ID + if voice_id is None: + continue - # Use provided client or create a temporary one - if client is not None: - sdk_client = client - else: - sdk_client = AsyncCambAI(api_key=api_key) + gender_int = voice.get("gender") + gender = GENDER_MAP.get(gender_int) if gender_int is not None else None - voices = await sdk_client.voice_cloning.list_voices() - return [ - { - "id": v.id if hasattr(v, "id") else v.get("id"), - "name": v.voice_name if hasattr(v, "voice_name") else v.get("voice_name", "Unknown"), - "gender": gender_map.get( - v.gender if hasattr(v, "gender") else v.get("gender"), "Unknown" - ), - "age": v.age if hasattr(v, "age") else v.get("age"), - "language": v.language if hasattr(v, "language") else v.get("language"), - } - for v in voices - ] + voices.append({ + "id": voice_id, + "name": voice.get("voice_name", ""), + "gender": gender, + "age": voice.get("age"), + "language": voice.get("language"), + }) + + return voices diff --git a/tests/test_camb_tts.py b/tests/test_camb_tts.py index 571cf67d8..44319db32 100644 --- a/tests/test_camb_tts.py +++ b/tests/test_camb_tts.py @@ -9,6 +9,7 @@ These tests mock the Camb.ai SDK client to test the service behavior. """ +import asyncio from unittest.mock import AsyncMock, MagicMock, patch import pytest @@ -22,7 +23,12 @@ from pipecat.frames.frames import ( TTSStoppedFrame, TTSTextFrame, ) -from pipecat.services.camb.tts import CambTTSService, language_to_camb_language +from pipecat.services.camb.tts import ( + CambTTSService, + DEFAULT_SAMPLE_RATE, + DEFAULT_VOICE_ID, + language_to_camb_language, +) from pipecat.tests.utils import run_test from pipecat.transcriptions.language import Language @@ -49,14 +55,10 @@ async def test_run_camb_tts_success(): mock_client.text_to_speech.tts = mock_tts_stream MockAsyncCambAI.return_value = mock_client - tts_service = CambTTSService( - api_key="test-api-key", - voice_id=2681, - model="mars-flash", - ) + tts_service = CambTTSService(api_key="test-api-key") # Manually set sample rate (normally done by StartFrame) - tts_service._sample_rate = 24000 + tts_service._sample_rate = DEFAULT_SAMPLE_RATE # Test run_tts directly to avoid frame count variability text = "Hello world, this is a test." @@ -73,9 +75,9 @@ async def test_run_camb_tts_success(): audio_frames = [f for f in frames if isinstance(f, TTSAudioRawFrame)] assert len(audio_frames) > 0, "Should have at least one audio frame" - # Verify sample rate matches Camb.ai's output (24kHz) + # Verify sample rate matches Camb.ai's output for a_frame in audio_frames: - assert a_frame.sample_rate == 24000, "Sample rate should be 24000 Hz" + assert a_frame.sample_rate == DEFAULT_SAMPLE_RATE assert a_frame.num_channels == 1, "Should be mono audio" @@ -87,10 +89,7 @@ async def test_run_camb_tts_error(): mock_client.text_to_speech.tts = mock_tts_stream_error MockAsyncCambAI.return_value = mock_client - tts_service = CambTTSService( - api_key="invalid-key", - voice_id=147320, - ) + tts_service = CambTTSService(api_key="invalid-key") frames_to_send = [ TTSSpeakFrame(text="This should fail."), @@ -114,25 +113,26 @@ async def test_run_camb_tts_error(): @pytest.mark.asyncio async def test_list_voices(): - """Test voice listing endpoint.""" + """Test voice listing endpoint with dict responses.""" async def mock_list_voices(*args, **kwargs): - # Return mock Voice objects - mock_voice1 = MagicMock() - mock_voice1.id = 2681 - mock_voice1.voice_name = "Attic" - mock_voice1.gender = 1 - mock_voice1.age = 25 - mock_voice1.language = None - - mock_voice2 = MagicMock() - mock_voice2.id = 2682 - mock_voice2.voice_name = "Cellar" - mock_voice2.gender = 2 - mock_voice2.age = 30 - mock_voice2.language = 1 - - return [mock_voice1, mock_voice2] + # Return mock voice dicts (as returned by the API) + return [ + { + "id": 2681, + "voice_name": "Attic", + "gender": 1, + "age": 25, + "language": None, + }, + { + "id": 2682, + "voice_name": "Cellar", + "gender": 2, + "age": 30, + "language": "en-us", + }, + ] with patch("pipecat.services.camb.tts.AsyncCambAI") as MockAsyncCambAI: mock_client = MagicMock() @@ -151,6 +151,50 @@ async def test_list_voices(): assert attic_voice["age"] == 25 +@pytest.mark.asyncio +async def test_list_voices_skips_none_id(): + """Test that voices without an ID are skipped.""" + + async def mock_list_voices(*args, **kwargs): + return [ + {"id": 123, "voice_name": "Valid", "gender": 1, "age": 25, "language": None}, + {"id": None, "voice_name": "NoID", "gender": 2, "age": 30, "language": None}, + {"voice_name": "MissingID", "gender": 1, "age": 35, "language": None}, + ] + + with patch("pipecat.services.camb.tts.AsyncCambAI") as MockAsyncCambAI: + mock_client = MagicMock() + mock_client.voice_cloning.list_voices = mock_list_voices + MockAsyncCambAI.return_value = mock_client + + voices = await CambTTSService.list_voices(api_key="test-api-key") + + # Should only return the voice with a valid ID + assert len(voices) == 1 + assert voices[0]["id"] == 123 + assert voices[0]["name"] == "Valid" + + +@pytest.mark.asyncio +async def test_list_voices_handles_none_gender(): + """Test that None gender is handled correctly.""" + + async def mock_list_voices(*args, **kwargs): + return [ + {"id": 123, "voice_name": "NoGender", "gender": None, "age": 25, "language": None}, + ] + + with patch("pipecat.services.camb.tts.AsyncCambAI") as MockAsyncCambAI: + mock_client = MagicMock() + mock_client.voice_cloning.list_voices = mock_list_voices + MockAsyncCambAI.return_value = mock_client + + voices = await CambTTSService.list_voices(api_key="test-api-key") + + assert len(voices) == 1 + assert voices[0]["gender"] is None + + @pytest.mark.asyncio async def test_text_length_validation_too_short(): """Test that text shorter than 3 characters is handled gracefully.""" @@ -160,10 +204,7 @@ async def test_text_length_validation_too_short(): mock_client.text_to_speech.tts = AsyncMock(side_effect=AssertionError("TTS should not be called")) MockAsyncCambAI.return_value = mock_client - tts_service = CambTTSService( - api_key="test-api-key", - voice_id=147320, - ) + tts_service = CambTTSService(api_key="test-api-key") frames_to_send = [ TTSSpeakFrame(text="Hi"), # Only 2 characters @@ -260,39 +301,83 @@ async def test_mars_instruct_model(): @pytest.mark.asyncio -async def test_client_initialization_with_api_key(): - """Test that client is created when api_key is provided.""" +async def test_client_initialization(): + """Test that client is created with correct parameters.""" with patch("pipecat.services.camb.tts.AsyncCambAI") as MockAsyncCambAI: mock_client = MagicMock() MockAsyncCambAI.return_value = mock_client - tts = CambTTSService( - api_key="test-key", - voice_id=147320, - ) + CambTTSService(api_key="test-key", timeout=120.0) - # Should have created a client - MockAsyncCambAI.assert_called_once() - assert tts._owns_client is True + # Should have created a client with correct params + MockAsyncCambAI.assert_called_once_with(api_key="test-key", timeout=120.0) @pytest.mark.asyncio -async def test_client_initialization_with_existing_client(): - """Test that existing client is used when provided.""" - mock_client = MagicMock() +async def test_default_voice_id_used(): + """Test that DEFAULT_VOICE_ID is used when not specified.""" + with patch("pipecat.services.camb.tts.AsyncCambAI") as MockAsyncCambAI: + mock_client = MagicMock() + MockAsyncCambAI.return_value = mock_client - tts = CambTTSService( - client=mock_client, - voice_id=147320, - ) + tts = CambTTSService(api_key="test-key") - # Should use the provided client - assert tts._client is mock_client - assert tts._owns_client is False + assert tts._voice_id_int == DEFAULT_VOICE_ID @pytest.mark.asyncio -async def test_client_initialization_requires_api_key_or_client(): - """Test that ValueError is raised when neither api_key nor client is provided.""" - with pytest.raises(ValueError, match="Either 'api_key' or 'client' must be provided"): - CambTTSService(voice_id=147320) +async def test_ttfb_metrics_tracked(): + """Test that TTFB metrics are properly tracked during TTS generation.""" + import time + + ttfb_start_called = False + ttfb_stop_called = False + start_time = None + stop_time = None + + async def mock_tts_with_delay(*args, **kwargs): + # Simulate some network delay + await asyncio.sleep(0.05) + yield b"\x00\x01" * 4800 + + with patch("pipecat.services.camb.tts.AsyncCambAI") as MockAsyncCambAI: + mock_client = MagicMock() + mock_client.text_to_speech.tts = mock_tts_with_delay + MockAsyncCambAI.return_value = mock_client + + tts_service = CambTTSService(api_key="test-api-key") + tts_service._sample_rate = DEFAULT_SAMPLE_RATE + + # Patch the metrics methods to track calls + original_start_ttfb = tts_service.start_ttfb_metrics + original_stop_ttfb = tts_service.stop_ttfb_metrics + + async def patched_start_ttfb(): + nonlocal ttfb_start_called, start_time + ttfb_start_called = True + start_time = time.time() + await original_start_ttfb() + + async def patched_stop_ttfb(): + nonlocal ttfb_stop_called, stop_time + if not ttfb_stop_called: # Only record first stop + ttfb_stop_called = True + stop_time = time.time() + await original_stop_ttfb() + + tts_service.start_ttfb_metrics = patched_start_ttfb + tts_service.stop_ttfb_metrics = patched_stop_ttfb + + # Run TTS + frames = [] + async for frame in tts_service.run_tts("Hello, this is a TTFB test."): + frames.append(frame) + + # Verify TTFB tracking was called + assert ttfb_start_called, "start_ttfb_metrics should be called" + assert ttfb_stop_called, "stop_ttfb_metrics should be called" + assert start_time is not None and stop_time is not None + + # TTFB should be >= simulated delay + ttfb = stop_time - start_time + assert ttfb >= 0.05, f"TTFB ({ttfb:.3f}s) should be >= 0.05s (simulated delay)" From e76a3d04f0cfe9e1a5721b98dc4e0d2d1067d1d3 Mon Sep 17 00:00:00 2001 From: Neil Ruaro Date: Tue, 13 Jan 2026 00:43:46 +0900 Subject: [PATCH 0073/1060] Update Camb TTS to 48kHz sample rate --- .../07zb-interruptible-camb-local.py | 95 +++++++++++++++---- src/pipecat/services/camb/tts.py | 14 +-- tests/test_camb_tts.py | 2 +- 3 files changed, 86 insertions(+), 25 deletions(-) diff --git a/examples/foundational/07zb-interruptible-camb-local.py b/examples/foundational/07zb-interruptible-camb-local.py index 83e4ce0dc..8d7805c86 100644 --- a/examples/foundational/07zb-interruptible-camb-local.py +++ b/examples/foundational/07zb-interruptible-camb-local.py @@ -4,12 +4,13 @@ # SPDX-License-Identifier: BSD 2-Clause License # -"""Camb.ai MARS TTS example with local audio (microphone/speakers). +"""Camb.ai TTS example with local audio (microphone/speakers). This example demonstrates: -- Basic TTS synthesis with Camb.ai MARS +- Camb.ai MARS TTS with streaming audio - Local audio input/output (no WebRTC or Daily needed) -- Handling interruptions +- TTFB metrics tracking +- End-to-end latency measurement (user speech → AI response) Requirements: - CAMB_API_KEY environment variable @@ -17,23 +18,29 @@ Requirements: - DEEPGRAM_API_KEY environment variable (for STT) Usage: - export CAMB_API_KEY=your_camb_api_key - export OPENAI_API_KEY=your_openai_api_key - export DEEPGRAM_API_KEY=your_deepgram_api_key - python 07zb-interruptible-camb-local.py [--voice-id VOICE_ID] + python 07zb-interruptible-camb-local.py + python 07zb-interruptible-camb-local.py --voice-id 147320 """ import argparse import asyncio import os import sys +import time from dotenv import load_dotenv from loguru import logger from pipecat.audio.vad.silero import SileroVADAnalyzer from pipecat.audio.vad.vad_analyzer import VADParams -from pipecat.frames.frames import LLMRunFrame +from pipecat.frames.frames import ( + BotStartedSpeakingFrame, + Frame, + LLMFullResponseStartFrame, + LLMRunFrame, + TTSStartedFrame, + UserStoppedSpeakingFrame, +) from pipecat.metrics.metrics import TTFBMetricsData from pipecat.observers.loggers.metrics_log_observer import MetricsLogObserver from pipecat.pipeline.pipeline import Pipeline @@ -43,23 +50,73 @@ from pipecat.processors.aggregators.llm_context import LLMContext from pipecat.processors.aggregators.llm_response_universal import ( LLMContextAggregatorPair, ) +from pipecat.processors.frame_processor import FrameDirection, FrameProcessor from pipecat.services.camb.tts import CambTTSService from pipecat.services.deepgram.stt import DeepgramSTTService from pipecat.services.openai.llm import OpenAILLMService from pipecat.transports.local.audio import LocalAudioTransport, LocalAudioTransportParams + +class LatencyTracker(FrameProcessor): + """Tracks end-to-end latency from user speech to AI audio response.""" + + def __init__(self, **kwargs): + super().__init__(**kwargs) + self._user_stopped_time: float = 0 + self._llm_start_time: float = 0 + self._tts_start_time: float = 0 + + async def process_frame(self, frame: Frame, direction: FrameDirection): + await super().process_frame(frame, direction) + + if isinstance(frame, UserStoppedSpeakingFrame): + self._user_stopped_time = time.time() + logger.info("⏱️ User stopped speaking - timer started") + + elif isinstance(frame, LLMFullResponseStartFrame): + self._llm_start_time = time.time() + if self._user_stopped_time > 0: + stt_latency = (self._llm_start_time - self._user_stopped_time) * 1000 + logger.info(f"⏱️ STT latency: {stt_latency:.0f}ms") + + elif isinstance(frame, TTSStartedFrame): + self._tts_start_time = time.time() + if self._llm_start_time > 0: + llm_latency = (self._tts_start_time - self._llm_start_time) * 1000 + logger.info(f"⏱️ LLM TTFB: {llm_latency:.0f}ms") + + elif isinstance(frame, BotStartedSpeakingFrame): + if self._user_stopped_time > 0: + total_latency = (time.time() - self._user_stopped_time) * 1000 + tts_latency = (time.time() - self._tts_start_time) * 1000 if self._tts_start_time > 0 else 0 + logger.info(f"⏱️ TTS TTFB: {tts_latency:.0f}ms") + logger.info(f"⏱️ ✨ TOTAL END-TO-END LATENCY: {total_latency:.0f}ms") + # Reset for next turn + self._user_stopped_time = 0 + self._llm_start_time = 0 + self._tts_start_time = 0 + + await self.push_frame(frame, direction) + load_dotenv(override=True) logger.remove(0) logger.add(sys.stderr, level="DEBUG") +# Default voice +DEFAULT_VOICE_ID = 147320 + async def main(voice_id: int): + sample_rate = 48000 + # Local audio transport - uses your microphone and speakers + # Increase audio_out_10ms_chunks for larger buffer (default is 4 = 40ms) transport = LocalAudioTransport( LocalAudioTransportParams( audio_in_enabled=True, audio_out_enabled=True, + audio_out_10ms_chunks=10, # 100ms buffer for smoother playback vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ) ) @@ -67,7 +124,7 @@ async def main(voice_id: int): # Deepgram STT for speech recognition stt = DeepgramSTTService(api_key=os.getenv("DEEPGRAM_API_KEY")) - # Camb.ai TTS with MARS-flash model (uses official SDK) + # Camb.ai TTS (48kHz output) tts = CambTTSService( api_key=os.getenv("CAMB_API_KEY"), voice_id=voice_id, @@ -81,7 +138,7 @@ async def main(voice_id: int): messages = [ { "role": "system", - "content": """You are a helpful voice assistant powered by Camb.ai's MARS + "content": """You are a helpful voice assistant powered by Camb.ai text-to-speech technology. Keep your responses concise and conversational since they will be spoken aloud. Avoid special characters, emojis, or bullet points.""", }, @@ -91,26 +148,28 @@ they will be spoken aloud. Avoid special characters, emojis, or bullet points."" context = LLMContext(messages) context_aggregator = LLMContextAggregatorPair(context) + # Latency tracker for end-to-end timing + latency_tracker = LatencyTracker() + # Build the pipeline pipeline = Pipeline( [ transport.input(), # Microphone input stt, # Speech-to-text + latency_tracker, # Track latency at various stages context_aggregator.user(), # User context llm, # Language model - tts, # Camb.ai TTS + tts, # TTS transport.output(), # Speaker output context_aggregator.assistant(), # Assistant context ] ) - # Create pipeline task - # Use 24kHz sample rate to match Camb.ai TTS output - # Add MetricsLogObserver to track TTFB metrics + # Create pipeline task with TTFB tracking task = PipelineTask( pipeline, params=PipelineParams( - audio_out_sample_rate=24000, + audio_out_sample_rate=sample_rate, enable_metrics=True, enable_usage_metrics=True, ), @@ -136,12 +195,12 @@ they will be spoken aloud. Avoid special characters, emojis, or bullet points."" if __name__ == "__main__": - parser = argparse.ArgumentParser(description="Camb.ai TTS example with local audio") + parser = argparse.ArgumentParser(description="Camb.ai TTS with local audio") parser.add_argument( "--voice-id", type=int, - default=147320, - help="Camb.ai voice ID to use (default: 147320)", + default=DEFAULT_VOICE_ID, + help=f"Camb.ai voice ID (default: {DEFAULT_VOICE_ID})", ) args = parser.parse_args() asyncio.run(main(args.voice_id)) diff --git a/src/pipecat/services/camb/tts.py b/src/pipecat/services/camb/tts.py index d5d800034..ed34005d3 100644 --- a/src/pipecat/services/camb/tts.py +++ b/src/pipecat/services/camb/tts.py @@ -13,7 +13,7 @@ Features: - MARS models: mars-flash, mars-pro, mars-instruct - 140+ languages supported - Real-time streaming via official SDK - - 24kHz audio output + - 48kHz audio output - Voice customization (instructions for mars-instruct) """ @@ -41,7 +41,7 @@ from pipecat.utils.tracing.service_decorators import traced_tts DEFAULT_VOICE_ID = 147320 DEFAULT_LANGUAGE = "en-us" DEFAULT_MODEL = "mars-flash" # Faster inference -DEFAULT_SAMPLE_RATE = 24000 # 24kHz +DEFAULT_SAMPLE_RATE = 48000 # 48kHz DEFAULT_TIMEOUT = 60.0 # Seconds (minimum recommended by Camb.ai) MIN_TEXT_LENGTH = 3 MAX_TEXT_LENGTH = 3000 @@ -133,6 +133,8 @@ class CambTTSService(TTSService): Converts text to speech using Camb.ai's MARS TTS models with support for multiple languages. Provides custom instructions support for the mars-instruct model. + All models output 48kHz audio. + Example:: # Basic usage with defaults @@ -145,13 +147,13 @@ class CambTTSService(TTSService): model="mars-pro", ) - # For mars-instruct with custom instructions: + # mars-instruct with custom instructions tts = CambTTSService( api_key="your-api-key", model="mars-instruct", params=CambTTSService.InputParams( user_instructions="Speak with excitement and energy" - ) + ), ) """ @@ -191,7 +193,7 @@ class CambTTSService(TTSService): model: TTS model to use. Options: "mars-flash", "mars-pro", "mars-instruct". Defaults to DEFAULT_MODEL (mars-flash, fastest). timeout: Request timeout in seconds. Defaults to DEFAULT_TIMEOUT (60s). - sample_rate: Audio sample rate in Hz. If None, uses DEFAULT_SAMPLE_RATE (24kHz). + sample_rate: Audio sample rate in Hz. If None, uses DEFAULT_SAMPLE_RATE (48kHz). params: Additional voice parameters. If None, uses defaults. **kwargs: Additional arguments passed to parent TTSService. """ @@ -241,7 +243,7 @@ class CambTTSService(TTSService): frame: The start frame containing initialization parameters. """ await super().start(frame) - # Use Camb.ai's native sample rate if not specified + # Use 48kHz sample rate if not explicitly specified if not self._init_sample_rate: self._sample_rate = DEFAULT_SAMPLE_RATE self._settings["sample_rate"] = self._sample_rate diff --git a/tests/test_camb_tts.py b/tests/test_camb_tts.py index 44319db32..ccd5c36ae 100644 --- a/tests/test_camb_tts.py +++ b/tests/test_camb_tts.py @@ -75,7 +75,7 @@ async def test_run_camb_tts_success(): audio_frames = [f for f in frames if isinstance(f, TTSAudioRawFrame)] assert len(audio_frames) > 0, "Should have at least one audio frame" - # Verify sample rate matches Camb.ai's output + # Verify sample rate matches 48kHz output for a_frame in audio_frames: assert a_frame.sample_rate == DEFAULT_SAMPLE_RATE assert a_frame.num_channels == 1, "Should be mono audio" From ed120d014de929f681c0cae9b197b2ce0c584a0d Mon Sep 17 00:00:00 2001 From: Neil Ruaro Date: Tue, 13 Jan 2026 06:32:11 +0900 Subject: [PATCH 0074/1060] Add model-specific sample rates, transport example, and fix audio buffer alignment --- .../07zb-interruptible-camb-local.py | 11 +- .../foundational/07zb-interruptible-camb.py | 123 ++++++++++++++++++ src/pipecat/services/camb/tts.py | 70 ++++++---- tests/test_camb_tts.py | 11 +- 4 files changed, 176 insertions(+), 39 deletions(-) create mode 100644 examples/foundational/07zb-interruptible-camb.py diff --git a/examples/foundational/07zb-interruptible-camb-local.py b/examples/foundational/07zb-interruptible-camb-local.py index 8d7805c86..025577792 100644 --- a/examples/foundational/07zb-interruptible-camb-local.py +++ b/examples/foundational/07zb-interruptible-camb-local.py @@ -6,11 +6,8 @@ """Camb.ai TTS example with local audio (microphone/speakers). -This example demonstrates: -- Camb.ai MARS TTS with streaming audio -- Local audio input/output (no WebRTC or Daily needed) -- TTFB metrics tracking -- End-to-end latency measurement (user speech → AI response) +This is a standalone local example for quick testing without WebRTC/Daily. +For production use with Daily/Twilio/WebRTC, see 07zb-interruptible-camb.py Requirements: - CAMB_API_KEY environment variable @@ -108,7 +105,7 @@ DEFAULT_VOICE_ID = 147320 async def main(voice_id: int): - sample_rate = 48000 + sample_rate = 22050 # mars-flash uses 22.05kHz # Local audio transport - uses your microphone and speakers # Increase audio_out_10ms_chunks for larger buffer (default is 4 = 40ms) @@ -124,7 +121,7 @@ async def main(voice_id: int): # Deepgram STT for speech recognition stt = DeepgramSTTService(api_key=os.getenv("DEEPGRAM_API_KEY")) - # Camb.ai TTS (48kHz output) + # Camb.ai TTS tts = CambTTSService( api_key=os.getenv("CAMB_API_KEY"), voice_id=voice_id, diff --git a/examples/foundational/07zb-interruptible-camb.py b/examples/foundational/07zb-interruptible-camb.py new file mode 100644 index 000000000..2c9c544b3 --- /dev/null +++ b/examples/foundational/07zb-interruptible-camb.py @@ -0,0 +1,123 @@ +# +# Copyright (c) 2024–2025, Daily +# +# SPDX-License-Identifier: BSD 2-Clause License +# + +import os + +from dotenv import load_dotenv +from loguru import logger + +from pipecat.audio.vad.silero import SileroVADAnalyzer +from pipecat.audio.vad.vad_analyzer import VADParams +from pipecat.frames.frames import LLMRunFrame +from pipecat.pipeline.pipeline import Pipeline +from pipecat.pipeline.runner import PipelineRunner +from pipecat.pipeline.task import PipelineParams, PipelineTask +from pipecat.processors.aggregators.llm_context import LLMContext +from pipecat.processors.aggregators.llm_response_universal import LLMContextAggregatorPair +from pipecat.runner.types import RunnerArguments +from pipecat.runner.utils import create_transport +from pipecat.services.camb.tts import CambTTSService +from pipecat.services.deepgram.stt import DeepgramSTTService +from pipecat.services.openai.llm import OpenAILLMService +from pipecat.transports.base_transport import BaseTransport, TransportParams +from pipecat.transports.daily.transport import DailyParams +from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams + +load_dotenv(override=True) + + +# We store functions so objects (e.g. SileroVADAnalyzer) don't get +# instantiated. The function will be called when the desired transport gets +# selected. +transport_params = { + "daily": lambda: DailyParams( + audio_in_enabled=True, + audio_out_enabled=True, + vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), + ), + "twilio": lambda: FastAPIWebsocketParams( + audio_in_enabled=True, + audio_out_enabled=True, + vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), + ), + "webrtc": lambda: TransportParams( + audio_in_enabled=True, + audio_out_enabled=True, + vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), + ), +} + + +async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): + logger.info("Starting Camb.ai TTS bot") + + stt = DeepgramSTTService(api_key=os.getenv("DEEPGRAM_API_KEY")) + + tts = CambTTSService( + api_key=os.getenv("CAMB_API_KEY"), + model="mars-flash", + ) + + llm = OpenAILLMService(api_key=os.getenv("OPENAI_API_KEY")) + + messages = [ + { + "role": "system", + "content": "You are a helpful voice assistant powered by Camb.ai text-to-speech. " + "Keep your responses concise and conversational since they will be spoken aloud. " + "Avoid special characters, emojis, or bullet points.", + }, + ] + + context = LLMContext(messages) + context_aggregator = LLMContextAggregatorPair(context) + + pipeline = Pipeline( + [ + transport.input(), + stt, + context_aggregator.user(), + llm, + tts, + transport.output(), + context_aggregator.assistant(), + ] + ) + + task = PipelineTask( + pipeline, + params=PipelineParams( + enable_metrics=True, + enable_usage_metrics=True, + ), + ) + + @transport.event_handler("on_client_connected") + async def on_client_connected(transport, client): + logger.info("Client connected") + messages.append({"role": "system", "content": "Please introduce yourself to the user."}) + await task.queue_frames([LLMRunFrame()]) + + @transport.event_handler("on_client_disconnected") + async def on_client_disconnected(transport, client): + logger.info("Client disconnected") + await task.cancel() + + runner = PipelineRunner(handle_sigint=runner_args.handle_sigint) + + await runner.run(task) + + +async def bot(runner_args: RunnerArguments): + """Main bot entry point compatible with Pipecat Cloud.""" + transport = await create_transport(runner_args, transport_params) + await run_bot(transport, runner_args) + + +if __name__ == "__main__": + from pipecat.runner.run import main + + main() diff --git a/src/pipecat/services/camb/tts.py b/src/pipecat/services/camb/tts.py index ed34005d3..5dcf19a0d 100644 --- a/src/pipecat/services/camb/tts.py +++ b/src/pipecat/services/camb/tts.py @@ -10,11 +10,10 @@ This module provides TTS functionality using Camb.ai's MARS model family, offering high-quality text-to-speech synthesis with streaming support. Features: - - MARS models: mars-flash, mars-pro, mars-instruct + - MARS models: mars-flash (fast), mars-pro (high quality) - 140+ languages supported - Real-time streaming via official SDK - - 48kHz audio output - - Voice customization (instructions for mars-instruct) + - Model-specific sample rates: mars-pro (48kHz), mars-flash (22.05kHz) """ from typing import Any, AsyncGenerator, Dict, List, Mapping, Optional @@ -41,11 +40,17 @@ from pipecat.utils.tracing.service_decorators import traced_tts DEFAULT_VOICE_ID = 147320 DEFAULT_LANGUAGE = "en-us" DEFAULT_MODEL = "mars-flash" # Faster inference -DEFAULT_SAMPLE_RATE = 48000 # 48kHz DEFAULT_TIMEOUT = 60.0 # Seconds (minimum recommended by Camb.ai) MIN_TEXT_LENGTH = 3 MAX_TEXT_LENGTH = 3000 +# Model-specific sample rates +MODEL_SAMPLE_RATES: Dict[str, int] = { + "mars-flash": 22050, # 22.05kHz + "mars-pro": 48000, # 48kHz + "mars-instruct": 22050, # 22.05kHz +} + # Gender mapping for voice listing GENDER_MAP = {0: "Not Specified", 1: "Male", 2: "Female", 9: "Not Applicable"} @@ -131,30 +136,23 @@ class CambTTSService(TTSService): """Camb.ai MARS text-to-speech service using the official SDK. Converts text to speech using Camb.ai's MARS TTS models with support for - multiple languages. Provides custom instructions support for the mars-instruct model. + multiple languages. - All models output 48kHz audio. + Models: + - mars-flash: Fast inference, 22.05kHz output (default) + - mars-pro: High quality, 48kHz output Example:: - # Basic usage with defaults + # Basic usage with defaults (mars-flash) tts = CambTTSService(api_key="your-api-key") - # With custom voice and model + # High quality with mars-pro tts = CambTTSService( api_key="your-api-key", voice_id=12345, model="mars-pro", ) - - # mars-instruct with custom instructions - tts = CambTTSService( - api_key="your-api-key", - model="mars-instruct", - params=CambTTSService.InputParams( - user_instructions="Speak with excitement and energy" - ), - ) """ class InputParams(BaseModel): @@ -190,10 +188,10 @@ class CambTTSService(TTSService): Args: api_key: Camb.ai API key for authentication. voice_id: Voice ID to use. Defaults to DEFAULT_VOICE_ID. - model: TTS model to use. Options: "mars-flash", "mars-pro", "mars-instruct". - Defaults to DEFAULT_MODEL (mars-flash, fastest). + model: TTS model to use. Options: "mars-flash" (fast), "mars-pro" (high quality). + Defaults to DEFAULT_MODEL (mars-flash). timeout: Request timeout in seconds. Defaults to DEFAULT_TIMEOUT (60s). - sample_rate: Audio sample rate in Hz. If None, uses DEFAULT_SAMPLE_RATE (48kHz). + sample_rate: Audio sample rate in Hz. If None, uses model-specific default. params: Additional voice parameters. If None, uses defaults. **kwargs: Additional arguments passed to parent TTSService. """ @@ -243,9 +241,9 @@ class CambTTSService(TTSService): frame: The start frame containing initialization parameters. """ await super().start(frame) - # Use 48kHz sample rate if not explicitly specified + # Use model-specific sample rate if not explicitly specified if not self._init_sample_rate: - self._sample_rate = DEFAULT_SAMPLE_RATE + self._sample_rate = MODEL_SAMPLE_RATES.get(self._model_name, 22050) self._settings["sample_rate"] = self._sample_rate async def _update_settings(self, settings: Mapping[str, Any]): @@ -310,15 +308,33 @@ class CambTTSService(TTSService): await self.start_tts_usage_metrics(text) yield TTSStartedFrame() + # Buffer for aligning chunks to 2-byte boundaries (16-bit PCM) + audio_buffer = b"" + # Stream audio chunks from SDK async for chunk in self._client.text_to_speech.tts(**tts_kwargs): if chunk: await self.stop_ttfb_metrics() - yield TTSAudioRawFrame( - audio=chunk, - sample_rate=self.sample_rate, - num_channels=1, - ) + audio_buffer += chunk + + # Only yield complete 16-bit samples (2 bytes per sample) + aligned_size = (len(audio_buffer) // 2) * 2 + if aligned_size > 0: + yield TTSAudioRawFrame( + audio=audio_buffer[:aligned_size], + sample_rate=self.sample_rate, + num_channels=1, + ) + audio_buffer = audio_buffer[aligned_size:] + + # Yield any remaining complete samples + if len(audio_buffer) >= 2: + aligned_size = (len(audio_buffer) // 2) * 2 + yield TTSAudioRawFrame( + audio=audio_buffer[:aligned_size], + sample_rate=self.sample_rate, + num_channels=1, + ) except Exception as e: error_msg = f"Camb.ai TTS error: {e}" diff --git a/tests/test_camb_tts.py b/tests/test_camb_tts.py index ccd5c36ae..169a1c6ee 100644 --- a/tests/test_camb_tts.py +++ b/tests/test_camb_tts.py @@ -25,8 +25,8 @@ from pipecat.frames.frames import ( ) from pipecat.services.camb.tts import ( CambTTSService, - DEFAULT_SAMPLE_RATE, DEFAULT_VOICE_ID, + MODEL_SAMPLE_RATES, language_to_camb_language, ) from pipecat.tests.utils import run_test @@ -58,7 +58,8 @@ async def test_run_camb_tts_success(): tts_service = CambTTSService(api_key="test-api-key") # Manually set sample rate (normally done by StartFrame) - tts_service._sample_rate = DEFAULT_SAMPLE_RATE + # mars-flash uses 22.05kHz + tts_service._sample_rate = MODEL_SAMPLE_RATES["mars-flash"] # Test run_tts directly to avoid frame count variability text = "Hello world, this is a test." @@ -75,9 +76,9 @@ async def test_run_camb_tts_success(): audio_frames = [f for f in frames if isinstance(f, TTSAudioRawFrame)] assert len(audio_frames) > 0, "Should have at least one audio frame" - # Verify sample rate matches 48kHz output + # Verify sample rate matches model output (mars-flash = 22.05kHz) for a_frame in audio_frames: - assert a_frame.sample_rate == DEFAULT_SAMPLE_RATE + assert a_frame.sample_rate == MODEL_SAMPLE_RATES["mars-flash"] assert a_frame.num_channels == 1, "Should be mono audio" @@ -346,7 +347,7 @@ async def test_ttfb_metrics_tracked(): MockAsyncCambAI.return_value = mock_client tts_service = CambTTSService(api_key="test-api-key") - tts_service._sample_rate = DEFAULT_SAMPLE_RATE + tts_service._sample_rate = MODEL_SAMPLE_RATES["mars-flash"] # Patch the metrics methods to track calls original_start_ttfb = tts_service.start_ttfb_metrics From 003c24ca6eee7c1f72bb2749c7da6ffc1598856d Mon Sep 17 00:00:00 2001 From: Neil Ruaro Date: Tue, 13 Jan 2026 07:06:31 +0900 Subject: [PATCH 0075/1060] Make model parameter explicit in docstring example --- src/pipecat/services/camb/tts.py | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/src/pipecat/services/camb/tts.py b/src/pipecat/services/camb/tts.py index 5dcf19a0d..1c3c88ae7 100644 --- a/src/pipecat/services/camb/tts.py +++ b/src/pipecat/services/camb/tts.py @@ -144,8 +144,8 @@ class CambTTSService(TTSService): Example:: - # Basic usage with defaults (mars-flash) - tts = CambTTSService(api_key="your-api-key") + # Basic usage with mars-flash (fast) + tts = CambTTSService(api_key="your-api-key", model="mars-flash") # High quality with mars-pro tts = CambTTSService( From 9942fcfeb29dfebbfca9860a1cd15a3262f740ae Mon Sep 17 00:00:00 2001 From: Neil Ruaro Date: Fri, 16 Jan 2026 01:15:46 +0800 Subject: [PATCH 0076/1060] updated per PR reviews --- README.md | 2 +- changelog/3349.added.md | 2 +- env.example | 3 + .../07zb-interruptible-camb-local.py | 203 - ...ble-camb.py => 07zg-interruptible-camb.py} | 23 +- pyproject.toml | 2 +- src/pipecat/services/camb/__init__.py | 3 - src/pipecat/services/camb/tts.py | 148 +- tests/test_camb_tts.py | 384 -- uv.lock | 5192 +++++++---------- 10 files changed, 2340 insertions(+), 3622 deletions(-) delete mode 100644 examples/foundational/07zb-interruptible-camb-local.py rename examples/foundational/{07zb-interruptible-camb.py => 07zg-interruptible-camb.py} (83%) delete mode 100644 tests/test_camb_tts.py diff --git a/README.md b/README.md index 0fbd1faea..0fac27943 100644 --- a/README.md +++ b/README.md @@ -75,7 +75,7 @@ Catch new features, interviews, and how-tos on our [Pipecat TV](https://www.yout | ------------------- | ----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | | Speech-to-Text | [AssemblyAI](https://docs.pipecat.ai/server/services/stt/assemblyai), [AWS](https://docs.pipecat.ai/server/services/stt/aws), [Azure](https://docs.pipecat.ai/server/services/stt/azure), [Cartesia](https://docs.pipecat.ai/server/services/stt/cartesia), [Deepgram](https://docs.pipecat.ai/server/services/stt/deepgram), [ElevenLabs](https://docs.pipecat.ai/server/services/stt/elevenlabs), [Fal Wizper](https://docs.pipecat.ai/server/services/stt/fal), [Gladia](https://docs.pipecat.ai/server/services/stt/gladia), [Google](https://docs.pipecat.ai/server/services/stt/google), [Gradium](https://docs.pipecat.ai/server/services/stt/gradium), [Groq (Whisper)](https://docs.pipecat.ai/server/services/stt/groq), [NVIDIA Riva](https://docs.pipecat.ai/server/services/stt/riva), [OpenAI (Whisper)](https://docs.pipecat.ai/server/services/stt/openai), [SambaNova (Whisper)](https://docs.pipecat.ai/server/services/stt/sambanova), [Sarvam](https://docs.pipecat.ai/server/services/stt/sarvam), [Soniox](https://docs.pipecat.ai/server/services/stt/soniox), [Speechmatics](https://docs.pipecat.ai/server/services/stt/speechmatics), [Whisper](https://docs.pipecat.ai/server/services/stt/whisper) | | LLMs | [Anthropic](https://docs.pipecat.ai/server/services/llm/anthropic), [AWS](https://docs.pipecat.ai/server/services/llm/aws), [Azure](https://docs.pipecat.ai/server/services/llm/azure), [Cerebras](https://docs.pipecat.ai/server/services/llm/cerebras), [DeepSeek](https://docs.pipecat.ai/server/services/llm/deepseek), [Fireworks AI](https://docs.pipecat.ai/server/services/llm/fireworks), [Gemini](https://docs.pipecat.ai/server/services/llm/gemini), [Grok](https://docs.pipecat.ai/server/services/llm/grok), [Groq](https://docs.pipecat.ai/server/services/llm/groq), [Mistral](https://docs.pipecat.ai/server/services/llm/mistral), [NVIDIA NIM](https://docs.pipecat.ai/server/services/llm/nim), [Ollama](https://docs.pipecat.ai/server/services/llm/ollama), [OpenAI](https://docs.pipecat.ai/server/services/llm/openai), [OpenRouter](https://docs.pipecat.ai/server/services/llm/openrouter), [Perplexity](https://docs.pipecat.ai/server/services/llm/perplexity), [Qwen](https://docs.pipecat.ai/server/services/llm/qwen), [SambaNova](https://docs.pipecat.ai/server/services/llm/sambanova) [Together AI](https://docs.pipecat.ai/server/services/llm/together) | -| Text-to-Speech | [Async](https://docs.pipecat.ai/server/services/tts/asyncai), [AWS](https://docs.pipecat.ai/server/services/tts/aws), [Azure](https://docs.pipecat.ai/server/services/tts/azure), [Cartesia](https://docs.pipecat.ai/server/services/tts/cartesia), [Deepgram](https://docs.pipecat.ai/server/services/tts/deepgram), [ElevenLabs](https://docs.pipecat.ai/server/services/tts/elevenlabs), [Fish](https://docs.pipecat.ai/server/services/tts/fish), [Google](https://docs.pipecat.ai/server/services/tts/google), [Gradium](https://docs.pipecat.ai/server/services/tts/gradium), [Groq](https://docs.pipecat.ai/server/services/tts/groq), [Hume](https://docs.pipecat.ai/server/services/tts/hume), [Inworld](https://docs.pipecat.ai/server/services/tts/inworld), [LMNT](https://docs.pipecat.ai/server/services/tts/lmnt), [MiniMax](https://docs.pipecat.ai/server/services/tts/minimax), [Neuphonic](https://docs.pipecat.ai/server/services/tts/neuphonic), [NVIDIA Riva](https://docs.pipecat.ai/server/services/tts/riva), [OpenAI](https://docs.pipecat.ai/server/services/tts/openai), [Piper](https://docs.pipecat.ai/server/services/tts/piper), [PlayHT](https://docs.pipecat.ai/server/services/tts/playht), [Rime](https://docs.pipecat.ai/server/services/tts/rime), [Sarvam](https://docs.pipecat.ai/server/services/tts/sarvam), [Speechmatics](https://docs.pipecat.ai/server/services/tts/speechmatics), [XTTS](https://docs.pipecat.ai/server/services/tts/xtts) | +| Text-to-Speech | [Async](https://docs.pipecat.ai/server/services/tts/asyncai), [AWS](https://docs.pipecat.ai/server/services/tts/aws), [Azure](https://docs.pipecat.ai/server/services/tts/azure), [Camb AI](https://docs.pipecat.ai/server/services/tts/camb), [Cartesia](https://docs.pipecat.ai/server/services/tts/cartesia), [Deepgram](https://docs.pipecat.ai/server/services/tts/deepgram), [ElevenLabs](https://docs.pipecat.ai/server/services/tts/elevenlabs), [Fish](https://docs.pipecat.ai/server/services/tts/fish), [Google](https://docs.pipecat.ai/server/services/tts/google), [Gradium](https://docs.pipecat.ai/server/services/tts/gradium), [Groq](https://docs.pipecat.ai/server/services/tts/groq), [Hume](https://docs.pipecat.ai/server/services/tts/hume), [Inworld](https://docs.pipecat.ai/server/services/tts/inworld), [LMNT](https://docs.pipecat.ai/server/services/tts/lmnt), [MiniMax](https://docs.pipecat.ai/server/services/tts/minimax), [Neuphonic](https://docs.pipecat.ai/server/services/tts/neuphonic), [NVIDIA Riva](https://docs.pipecat.ai/server/services/tts/riva), [OpenAI](https://docs.pipecat.ai/server/services/tts/openai), [Piper](https://docs.pipecat.ai/server/services/tts/piper), [PlayHT](https://docs.pipecat.ai/server/services/tts/playht), [Rime](https://docs.pipecat.ai/server/services/tts/rime), [Sarvam](https://docs.pipecat.ai/server/services/tts/sarvam), [Speechmatics](https://docs.pipecat.ai/server/services/tts/speechmatics), [XTTS](https://docs.pipecat.ai/server/services/tts/xtts) | | Speech-to-Speech | [AWS Nova Sonic](https://docs.pipecat.ai/server/services/s2s/aws), [Gemini Multimodal Live](https://docs.pipecat.ai/server/services/s2s/gemini), [Grok Voice Agent](https://docs.pipecat.ai/server/services/s2s/grok), [OpenAI Realtime](https://docs.pipecat.ai/server/services/s2s/openai), [Ultravox](https://docs.pipecat.ai/server/services/s2s/ultravox), | | Transport | [Daily (WebRTC)](https://docs.pipecat.ai/server/services/transport/daily), [FastAPI Websocket](https://docs.pipecat.ai/server/services/transport/fastapi-websocket), [SmallWebRTCTransport](https://docs.pipecat.ai/server/services/transport/small-webrtc), [WebSocket Server](https://docs.pipecat.ai/server/services/transport/websocket-server), Local | | Serializers | [Exotel](https://docs.pipecat.ai/server/utilities/serializers/exotel), [Plivo](https://docs.pipecat.ai/server/utilities/serializers/plivo), [Twilio](https://docs.pipecat.ai/server/utilities/serializers/twilio), [Telnyx](https://docs.pipecat.ai/server/utilities/serializers/telnyx), [Vonage](https://docs.pipecat.ai/server/utilities/serializers/vonage) | diff --git a/changelog/3349.added.md b/changelog/3349.added.md index 565caca84..a5b282ec8 100644 --- a/changelog/3349.added.md +++ b/changelog/3349.added.md @@ -1 +1 @@ -- Added Camb.ai TTS integration with MARS models (mars-flash, mars-pro, mars-instruct) for high-quality text-to-speech synthesis. +- Added `CambTTSService`, using Camb.ai's TTS integration with MARS models (mars-flash, mars-pro, mars-instruct) for high-quality text-to-speech synthesis. diff --git a/env.example b/env.example index 1110a1ed3..41badb571 100644 --- a/env.example +++ b/env.example @@ -31,6 +31,9 @@ AZURE_DALLE_API_KEY=... AZURE_DALLE_ENDPOINT=https://... AZURE_DALLE_MODEL=... +# Camb.ai +CAMB_API_KEY=... + # Cartesia CARTESIA_API_KEY=... CARTESIA_VOICE_ID=... diff --git a/examples/foundational/07zb-interruptible-camb-local.py b/examples/foundational/07zb-interruptible-camb-local.py deleted file mode 100644 index 025577792..000000000 --- a/examples/foundational/07zb-interruptible-camb-local.py +++ /dev/null @@ -1,203 +0,0 @@ -# -# Copyright (c) 2024–2025, Daily -# -# SPDX-License-Identifier: BSD 2-Clause License -# - -"""Camb.ai TTS example with local audio (microphone/speakers). - -This is a standalone local example for quick testing without WebRTC/Daily. -For production use with Daily/Twilio/WebRTC, see 07zb-interruptible-camb.py - -Requirements: -- CAMB_API_KEY environment variable -- OPENAI_API_KEY environment variable (for LLM) -- DEEPGRAM_API_KEY environment variable (for STT) - -Usage: - python 07zb-interruptible-camb-local.py - python 07zb-interruptible-camb-local.py --voice-id 147320 -""" - -import argparse -import asyncio -import os -import sys -import time - -from dotenv import load_dotenv -from loguru import logger - -from pipecat.audio.vad.silero import SileroVADAnalyzer -from pipecat.audio.vad.vad_analyzer import VADParams -from pipecat.frames.frames import ( - BotStartedSpeakingFrame, - Frame, - LLMFullResponseStartFrame, - LLMRunFrame, - TTSStartedFrame, - UserStoppedSpeakingFrame, -) -from pipecat.metrics.metrics import TTFBMetricsData -from pipecat.observers.loggers.metrics_log_observer import MetricsLogObserver -from pipecat.pipeline.pipeline import Pipeline -from pipecat.pipeline.runner import PipelineRunner -from pipecat.pipeline.task import PipelineParams, PipelineTask -from pipecat.processors.aggregators.llm_context import LLMContext -from pipecat.processors.aggregators.llm_response_universal import ( - LLMContextAggregatorPair, -) -from pipecat.processors.frame_processor import FrameDirection, FrameProcessor -from pipecat.services.camb.tts import CambTTSService -from pipecat.services.deepgram.stt import DeepgramSTTService -from pipecat.services.openai.llm import OpenAILLMService -from pipecat.transports.local.audio import LocalAudioTransport, LocalAudioTransportParams - - -class LatencyTracker(FrameProcessor): - """Tracks end-to-end latency from user speech to AI audio response.""" - - def __init__(self, **kwargs): - super().__init__(**kwargs) - self._user_stopped_time: float = 0 - self._llm_start_time: float = 0 - self._tts_start_time: float = 0 - - async def process_frame(self, frame: Frame, direction: FrameDirection): - await super().process_frame(frame, direction) - - if isinstance(frame, UserStoppedSpeakingFrame): - self._user_stopped_time = time.time() - logger.info("⏱️ User stopped speaking - timer started") - - elif isinstance(frame, LLMFullResponseStartFrame): - self._llm_start_time = time.time() - if self._user_stopped_time > 0: - stt_latency = (self._llm_start_time - self._user_stopped_time) * 1000 - logger.info(f"⏱️ STT latency: {stt_latency:.0f}ms") - - elif isinstance(frame, TTSStartedFrame): - self._tts_start_time = time.time() - if self._llm_start_time > 0: - llm_latency = (self._tts_start_time - self._llm_start_time) * 1000 - logger.info(f"⏱️ LLM TTFB: {llm_latency:.0f}ms") - - elif isinstance(frame, BotStartedSpeakingFrame): - if self._user_stopped_time > 0: - total_latency = (time.time() - self._user_stopped_time) * 1000 - tts_latency = (time.time() - self._tts_start_time) * 1000 if self._tts_start_time > 0 else 0 - logger.info(f"⏱️ TTS TTFB: {tts_latency:.0f}ms") - logger.info(f"⏱️ ✨ TOTAL END-TO-END LATENCY: {total_latency:.0f}ms") - # Reset for next turn - self._user_stopped_time = 0 - self._llm_start_time = 0 - self._tts_start_time = 0 - - await self.push_frame(frame, direction) - -load_dotenv(override=True) - -logger.remove(0) -logger.add(sys.stderr, level="DEBUG") - -# Default voice -DEFAULT_VOICE_ID = 147320 - - -async def main(voice_id: int): - sample_rate = 22050 # mars-flash uses 22.05kHz - - # Local audio transport - uses your microphone and speakers - # Increase audio_out_10ms_chunks for larger buffer (default is 4 = 40ms) - transport = LocalAudioTransport( - LocalAudioTransportParams( - audio_in_enabled=True, - audio_out_enabled=True, - audio_out_10ms_chunks=10, # 100ms buffer for smoother playback - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), - ) - ) - - # Deepgram STT for speech recognition - stt = DeepgramSTTService(api_key=os.getenv("DEEPGRAM_API_KEY")) - - # Camb.ai TTS - tts = CambTTSService( - api_key=os.getenv("CAMB_API_KEY"), - voice_id=voice_id, - model="mars-flash", - ) - - # OpenAI LLM - llm = OpenAILLMService(api_key=os.getenv("OPENAI_API_KEY")) - - # System prompt - messages = [ - { - "role": "system", - "content": """You are a helpful voice assistant powered by Camb.ai -text-to-speech technology. Keep your responses concise and conversational since -they will be spoken aloud. Avoid special characters, emojis, or bullet points.""", - }, - ] - - # Context management - context = LLMContext(messages) - context_aggregator = LLMContextAggregatorPair(context) - - # Latency tracker for end-to-end timing - latency_tracker = LatencyTracker() - - # Build the pipeline - pipeline = Pipeline( - [ - transport.input(), # Microphone input - stt, # Speech-to-text - latency_tracker, # Track latency at various stages - context_aggregator.user(), # User context - llm, # Language model - tts, # TTS - transport.output(), # Speaker output - context_aggregator.assistant(), # Assistant context - ] - ) - - # Create pipeline task with TTFB tracking - task = PipelineTask( - pipeline, - params=PipelineParams( - audio_out_sample_rate=sample_rate, - enable_metrics=True, - enable_usage_metrics=True, - ), - observers=[MetricsLogObserver(include_metrics={TTFBMetricsData})], - ) - - # Start the conversation when the pipeline is ready - @task.event_handler("on_pipeline_started") - async def on_pipeline_started(task, frame): - messages.append( - { - "role": "system", - "content": "Please introduce yourself briefly and ask how you can help.", - } - ) - await task.queue_frames([LLMRunFrame()]) - - # Run the pipeline - runner = PipelineRunner() - logger.info("Starting Camb.ai TTS bot with local audio...") - logger.info("Speak into your microphone to interact with the bot.") - await runner.run(task) - - -if __name__ == "__main__": - parser = argparse.ArgumentParser(description="Camb.ai TTS with local audio") - parser.add_argument( - "--voice-id", - type=int, - default=DEFAULT_VOICE_ID, - help=f"Camb.ai voice ID (default: {DEFAULT_VOICE_ID})", - ) - args = parser.parse_args() - asyncio.run(main(args.voice_id)) diff --git a/examples/foundational/07zb-interruptible-camb.py b/examples/foundational/07zg-interruptible-camb.py similarity index 83% rename from examples/foundational/07zb-interruptible-camb.py rename to examples/foundational/07zg-interruptible-camb.py index 2c9c544b3..f930613d9 100644 --- a/examples/foundational/07zb-interruptible-camb.py +++ b/examples/foundational/07zg-interruptible-camb.py @@ -9,6 +9,7 @@ import os from dotenv import load_dotenv from loguru import logger +from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3 from pipecat.audio.vad.silero import SileroVADAnalyzer from pipecat.audio.vad.vad_analyzer import VADParams from pipecat.frames.frames import LLMRunFrame @@ -16,7 +17,10 @@ from pipecat.pipeline.pipeline import Pipeline from pipecat.pipeline.runner import PipelineRunner from pipecat.pipeline.task import PipelineParams, PipelineTask from pipecat.processors.aggregators.llm_context import LLMContext -from pipecat.processors.aggregators.llm_response_universal import LLMContextAggregatorPair +from pipecat.processors.aggregators.llm_response_universal import ( + LLMContextAggregatorPair, + LLMUserAggregatorParams, +) from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport from pipecat.services.camb.tts import CambTTSService @@ -25,6 +29,8 @@ from pipecat.services.openai.llm import OpenAILLMService from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams +from pipecat.turns.bot import TurnAnalyzerBotTurnStartStrategy +from pipecat.turns.turn_start_strategies import TurnStartStrategies load_dotenv(override=True) @@ -52,7 +58,7 @@ transport_params = { async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): - logger.info("Starting Camb.ai TTS bot") + logger.info("Starting Camb AI TTS bot") stt = DeepgramSTTService(api_key=os.getenv("DEEPGRAM_API_KEY")) @@ -66,14 +72,21 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): messages = [ { "role": "system", - "content": "You are a helpful voice assistant powered by Camb.ai text-to-speech. " + "content": "You are a helpful voice assistant powered by Camb AI text-to-speech. " "Keep your responses concise and conversational since they will be spoken aloud. " "Avoid special characters, emojis, or bullet points.", }, ] context = LLMContext(messages) - context_aggregator = LLMContextAggregatorPair(context) + context_aggregator = LLMContextAggregatorPair( + context, + user_params=LLMUserAggregatorParams( + turn_start_strategies=TurnStartStrategies( + bot=[TurnAnalyzerBotTurnStartStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3())] + ), + ), + ) pipeline = Pipeline( [ @@ -92,7 +105,9 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): params=PipelineParams( enable_metrics=True, enable_usage_metrics=True, + audio_out_sample_rate=22050, ), + idle_timeout_secs=runner_args.pipeline_idle_timeout_secs, ) @transport.event_handler("on_client_connected") diff --git a/pyproject.toml b/pyproject.toml index f640e9fb1..a6b5afafa 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -53,7 +53,7 @@ aws = [ "aioboto3~=15.5.0", "pipecat-ai[websockets-base]" ] aws-nova-sonic = [ "aws_sdk_bedrock_runtime~=0.2.0; python_version>='3.12'" ] azure = [ "azure-cognitiveservices-speech~=1.44.0"] cartesia = [ "cartesia~=2.0.3", "pipecat-ai[websockets-base]" ] -camb = [ "pipecat-ai[websockets-base]" ] +camb = [ "camb-sdk>=1.5.4" ] cerebras = [] daily = [ "daily-python~=0.23.0" ] deepgram = [ "deepgram-sdk~=4.7.0", "pipecat-ai[websockets-base]" ] diff --git a/src/pipecat/services/camb/__init__.py b/src/pipecat/services/camb/__init__.py index 0d444e949..d23112945 100644 --- a/src/pipecat/services/camb/__init__.py +++ b/src/pipecat/services/camb/__init__.py @@ -3,6 +3,3 @@ # # SPDX-License-Identifier: BSD 2-Clause License # - - -from .tts import * diff --git a/src/pipecat/services/camb/tts.py b/src/pipecat/services/camb/tts.py index 1c3c88ae7..bb9b919a6 100644 --- a/src/pipecat/services/camb/tts.py +++ b/src/pipecat/services/camb/tts.py @@ -16,10 +16,10 @@ Features: - Model-specific sample rates: mars-pro (48kHz), mars-flash (22.05kHz) """ -from typing import Any, AsyncGenerator, Dict, List, Mapping, Optional +from typing import Any, AsyncGenerator, Dict, Mapping, Optional -from camb.client import AsyncCambAI from camb import StreamTtsOutputConfiguration +from camb.client import AsyncCambAI from loguru import logger from pydantic import BaseModel, Field @@ -35,25 +35,13 @@ from pipecat.services.tts_service import TTSService from pipecat.transcriptions.language import Language, resolve_language from pipecat.utils.tracing.service_decorators import traced_tts - -# Default configuration -DEFAULT_VOICE_ID = 147320 -DEFAULT_LANGUAGE = "en-us" -DEFAULT_MODEL = "mars-flash" # Faster inference -DEFAULT_TIMEOUT = 60.0 # Seconds (minimum recommended by Camb.ai) -MIN_TEXT_LENGTH = 3 -MAX_TEXT_LENGTH = 3000 - # Model-specific sample rates MODEL_SAMPLE_RATES: Dict[str, int] = { - "mars-flash": 22050, # 22.05kHz - "mars-pro": 48000, # 48kHz + "mars-flash": 22050, # 22.05kHz + "mars-pro": 48000, # 48kHz "mars-instruct": 22050, # 22.05kHz } -# Gender mapping for voice listing -GENDER_MAP = {0: "Not Specified", 1: "Male", 2: "Female", 9: "Not Applicable"} - def language_to_camb_language(language: Language) -> Optional[str]: """Convert a Pipecat Language enum to Camb.ai language code. @@ -132,6 +120,19 @@ def language_to_camb_language(language: Language) -> Optional[str]: return resolve_language(language, LANGUAGE_MAP, use_base_code=True) +def _get_aligned_audio(buffer: bytes) -> tuple[bytes, bytes]: + """Split buffer into aligned audio (2-byte samples) and remainder. + + Args: + buffer: Raw audio bytes to align. + + Returns: + Tuple of (aligned audio bytes, remaining bytes). + """ + aligned_size = (len(buffer) // 2) * 2 + return buffer[:aligned_size], buffer[aligned_size:] + + class CambTTSService(TTSService): """Camb.ai MARS text-to-speech service using the official SDK. @@ -176,9 +177,9 @@ class CambTTSService(TTSService): self, *, api_key: str, - voice_id: int = DEFAULT_VOICE_ID, - model: str = DEFAULT_MODEL, - timeout: float = DEFAULT_TIMEOUT, + voice_id: int = 147320, + model: str = "mars-flash", + timeout: float = 60.0, sample_rate: Optional[int] = None, params: Optional[InputParams] = None, **kwargs, @@ -187,10 +188,11 @@ class CambTTSService(TTSService): Args: api_key: Camb.ai API key for authentication. - voice_id: Voice ID to use. Defaults to DEFAULT_VOICE_ID. + voice_id: Voice ID to use. Defaults to 147320. model: TTS model to use. Options: "mars-flash" (fast), "mars-pro" (high quality). - Defaults to DEFAULT_MODEL (mars-flash). - timeout: Request timeout in seconds. Defaults to DEFAULT_TIMEOUT (60s). + Defaults to "mars-flash". + timeout: Request timeout in seconds. Defaults to 60.0 (minimum recommended + by Camb.ai). sample_rate: Audio sample rate in Hz. If None, uses model-specific default. params: Additional voice parameters. If None, uses defaults. **kwargs: Additional arguments passed to parent TTSService. @@ -201,19 +203,24 @@ class CambTTSService(TTSService): self._client = AsyncCambAI(api_key=api_key, timeout=timeout) + # Warn if sample rate doesn't match model's supported rate + if sample_rate and sample_rate != MODEL_SAMPLE_RATES.get(model): + logger.warning( + f"Camb.ai's {model} model only supports {MODEL_SAMPLE_RATES.get(model)}Hz " + f"sample rate. Current rate of {sample_rate}Hz may cause issues." + ) + # Build settings self._settings = { "language": ( - self.language_to_service_language(params.language) - if params.language - else DEFAULT_LANGUAGE + self.language_to_service_language(params.language) if params.language else "en-us" ), "user_instructions": params.user_instructions, } self.set_model_name(model) self.set_voice(str(voice_id)) - self._voice_id_int = voice_id + self._voice_id = voice_id def can_generate_metrics(self) -> bool: """Check if this service can generate processing metrics. @@ -262,7 +269,7 @@ class CambTTSService(TTSService): self._settings[key] = value logger.debug(f"Updated Camb.ai TTS setting {key} to: {value}") elif key == "voice_id": - self._voice_id_int = int(value) + self._voice_id = int(value) self.set_voice(str(value)) @traced_tts @@ -270,7 +277,7 @@ class CambTTSService(TTSService): """Generate speech from text using Camb.ai's TTS API. Args: - text: The text to synthesize into speech (3-3000 characters). + text: The text to synthesize into speech (max 3000 characters). Yields: Frame: Audio frames containing the synthesized speech. @@ -278,16 +285,9 @@ class CambTTSService(TTSService): logger.debug(f"{self}: Generating TTS [{text}]") # Validate text length - if len(text) < MIN_TEXT_LENGTH: - logger.warning(f"Text too short for Camb.ai TTS (min {MIN_TEXT_LENGTH} chars): {text}") - yield TTSStoppedFrame() - return - - if len(text) > MAX_TEXT_LENGTH: - logger.warning( - f"Text too long for Camb.ai TTS (max {MAX_TEXT_LENGTH} chars), truncating" - ) - text = text[:MAX_TEXT_LENGTH] + if len(text) > 3000: + logger.warning("Text too long for Camb.ai TTS (max 3000 chars), truncating") + text = text[:3000] try: await self.start_ttfb_metrics() @@ -295,9 +295,9 @@ class CambTTSService(TTSService): # Build SDK parameters tts_kwargs: Dict[str, Any] = { "text": text, - "voice_id": self._voice_id_int, + "voice_id": self._voice_id, "language": self._settings["language"], - "speech_model": self._model_name, + "speech_model": self.model_name, "output_configuration": StreamTtsOutputConfiguration(format="pcm_s16le"), } @@ -318,71 +318,25 @@ class CambTTSService(TTSService): audio_buffer += chunk # Only yield complete 16-bit samples (2 bytes per sample) - aligned_size = (len(audio_buffer) // 2) * 2 - if aligned_size > 0: + aligned_audio, audio_buffer = _get_aligned_audio(audio_buffer) + if aligned_audio: yield TTSAudioRawFrame( - audio=audio_buffer[:aligned_size], + audio=aligned_audio, sample_rate=self.sample_rate, num_channels=1, ) - audio_buffer = audio_buffer[aligned_size:] # Yield any remaining complete samples if len(audio_buffer) >= 2: - aligned_size = (len(audio_buffer) // 2) * 2 - yield TTSAudioRawFrame( - audio=audio_buffer[:aligned_size], - sample_rate=self.sample_rate, - num_channels=1, - ) + aligned_audio, _ = _get_aligned_audio(audio_buffer) + if aligned_audio: + yield TTSAudioRawFrame( + audio=aligned_audio, + sample_rate=self.sample_rate, + num_channels=1, + ) except Exception as e: - error_msg = f"Camb.ai TTS error: {e}" - logger.error(f"{self}: {error_msg}") - yield ErrorFrame(error=error_msg) + yield ErrorFrame(error=f"Camb.ai TTS error: {e}") finally: - logger.debug(f"{self}: Finished TTS [{text}]") - await self.stop_ttfb_metrics() yield TTSStoppedFrame() - - @staticmethod - async def list_voices(api_key: str) -> List[Dict[str, Any]]: - """Fetch available voices from Camb.ai API. - - Args: - api_key: Camb.ai API key for authentication. - - Returns: - List of voice dictionaries with id, name, gender, and language fields. - - Raises: - Exception: If the API request fails. - - Example:: - - voices = await CambTTSService.list_voices(api_key="your-api-key") - for voice in voices: - print(f"{voice['id']}: {voice['name']}") - """ - client = AsyncCambAI(api_key=api_key) - voice_list = await client.voice_cloning.list_voices() - - voices = [] - for voice in voice_list: - voice_id = voice.get("id") - # Skip voices without an ID - if voice_id is None: - continue - - gender_int = voice.get("gender") - gender = GENDER_MAP.get(gender_int) if gender_int is not None else None - - voices.append({ - "id": voice_id, - "name": voice.get("voice_name", ""), - "gender": gender, - "age": voice.get("age"), - "language": voice.get("language"), - }) - - return voices diff --git a/tests/test_camb_tts.py b/tests/test_camb_tts.py deleted file mode 100644 index 169a1c6ee..000000000 --- a/tests/test_camb_tts.py +++ /dev/null @@ -1,384 +0,0 @@ -# -# Copyright (c) 2024-2025 Daily -# -# SPDX-License-Identifier: BSD 2-Clause License -# - -"""Tests for CambTTSService. - -These tests mock the Camb.ai SDK client to test the service behavior. -""" - -import asyncio -from unittest.mock import AsyncMock, MagicMock, patch - -import pytest - -from pipecat.frames.frames import ( - AggregatedTextFrame, - ErrorFrame, - TTSAudioRawFrame, - TTSSpeakFrame, - TTSStartedFrame, - TTSStoppedFrame, - TTSTextFrame, -) -from pipecat.services.camb.tts import ( - CambTTSService, - DEFAULT_VOICE_ID, - MODEL_SAMPLE_RATES, - language_to_camb_language, -) -from pipecat.tests.utils import run_test -from pipecat.transcriptions.language import Language - - -async def mock_tts_stream(*args, **kwargs): - """Mock TTS stream that yields audio chunks.""" - yield b"\x00\x01" * 4800 # Small chunk of PCM audio - - -async def mock_tts_stream_error(*args, **kwargs): - """Mock TTS stream that raises an error.""" - raise Exception("API error: Invalid API key") - yield # Make this a generator - - -@pytest.mark.asyncio -async def test_run_camb_tts_success(): - """Test successful TTS generation with chunked PCM audio. - - Verifies the frame sequence: TTSStartedFrame -> TTSAudioRawFrame* -> TTSStoppedFrame - """ - with patch("pipecat.services.camb.tts.AsyncCambAI") as MockAsyncCambAI: - mock_client = MagicMock() - mock_client.text_to_speech.tts = mock_tts_stream - MockAsyncCambAI.return_value = mock_client - - tts_service = CambTTSService(api_key="test-api-key") - - # Manually set sample rate (normally done by StartFrame) - # mars-flash uses 22.05kHz - tts_service._sample_rate = MODEL_SAMPLE_RATES["mars-flash"] - - # Test run_tts directly to avoid frame count variability - text = "Hello world, this is a test." - frames = [] - async for frame in tts_service.run_tts(text): - frames.append(frame) - - # Verify we got the expected frame types - frame_types = [type(f).__name__ for f in frames] - assert "TTSStartedFrame" in frame_types, "Should have TTSStartedFrame" - assert "TTSAudioRawFrame" in frame_types, "Should have TTSAudioRawFrame" - assert "TTSStoppedFrame" in frame_types, "Should have TTSStoppedFrame" - - audio_frames = [f for f in frames if isinstance(f, TTSAudioRawFrame)] - assert len(audio_frames) > 0, "Should have at least one audio frame" - - # Verify sample rate matches model output (mars-flash = 22.05kHz) - for a_frame in audio_frames: - assert a_frame.sample_rate == MODEL_SAMPLE_RATES["mars-flash"] - assert a_frame.num_channels == 1, "Should be mono audio" - - -@pytest.mark.asyncio -async def test_run_camb_tts_error(): - """Test handling of TTS API errors.""" - with patch("pipecat.services.camb.tts.AsyncCambAI") as MockAsyncCambAI: - mock_client = MagicMock() - mock_client.text_to_speech.tts = mock_tts_stream_error - MockAsyncCambAI.return_value = mock_client - - tts_service = CambTTSService(api_key="invalid-key") - - frames_to_send = [ - TTSSpeakFrame(text="This should fail."), - ] - - # TTSStartedFrame is emitted before we attempt to iterate the stream - expected_down_frames = [AggregatedTextFrame, TTSStartedFrame, TTSStoppedFrame, TTSTextFrame] - expected_up_frames = [ErrorFrame] - - frames_received = await run_test( - tts_service, - frames_to_send=frames_to_send, - expected_down_frames=expected_down_frames, - expected_up_frames=expected_up_frames, - ) - up_frames = frames_received[1] - - assert isinstance(up_frames[0], ErrorFrame), "Must receive an ErrorFrame" - assert "error" in up_frames[0].error.lower(), "ErrorFrame should contain error message" - - -@pytest.mark.asyncio -async def test_list_voices(): - """Test voice listing endpoint with dict responses.""" - - async def mock_list_voices(*args, **kwargs): - # Return mock voice dicts (as returned by the API) - return [ - { - "id": 2681, - "voice_name": "Attic", - "gender": 1, - "age": 25, - "language": None, - }, - { - "id": 2682, - "voice_name": "Cellar", - "gender": 2, - "age": 30, - "language": "en-us", - }, - ] - - with patch("pipecat.services.camb.tts.AsyncCambAI") as MockAsyncCambAI: - mock_client = MagicMock() - mock_client.voice_cloning.list_voices = mock_list_voices - MockAsyncCambAI.return_value = mock_client - - voices = await CambTTSService.list_voices(api_key="test-api-key") - - # Should return all voices - assert len(voices) == 2, "Should return all voices" - - # Verify voice data structure - attic_voice = next(v for v in voices if v["id"] == 2681) - assert attic_voice["name"] == "Attic" - assert attic_voice["gender"] == "Male" - assert attic_voice["age"] == 25 - - -@pytest.mark.asyncio -async def test_list_voices_skips_none_id(): - """Test that voices without an ID are skipped.""" - - async def mock_list_voices(*args, **kwargs): - return [ - {"id": 123, "voice_name": "Valid", "gender": 1, "age": 25, "language": None}, - {"id": None, "voice_name": "NoID", "gender": 2, "age": 30, "language": None}, - {"voice_name": "MissingID", "gender": 1, "age": 35, "language": None}, - ] - - with patch("pipecat.services.camb.tts.AsyncCambAI") as MockAsyncCambAI: - mock_client = MagicMock() - mock_client.voice_cloning.list_voices = mock_list_voices - MockAsyncCambAI.return_value = mock_client - - voices = await CambTTSService.list_voices(api_key="test-api-key") - - # Should only return the voice with a valid ID - assert len(voices) == 1 - assert voices[0]["id"] == 123 - assert voices[0]["name"] == "Valid" - - -@pytest.mark.asyncio -async def test_list_voices_handles_none_gender(): - """Test that None gender is handled correctly.""" - - async def mock_list_voices(*args, **kwargs): - return [ - {"id": 123, "voice_name": "NoGender", "gender": None, "age": 25, "language": None}, - ] - - with patch("pipecat.services.camb.tts.AsyncCambAI") as MockAsyncCambAI: - mock_client = MagicMock() - mock_client.voice_cloning.list_voices = mock_list_voices - MockAsyncCambAI.return_value = mock_client - - voices = await CambTTSService.list_voices(api_key="test-api-key") - - assert len(voices) == 1 - assert voices[0]["gender"] is None - - -@pytest.mark.asyncio -async def test_text_length_validation_too_short(): - """Test that text shorter than 3 characters is handled gracefully.""" - with patch("pipecat.services.camb.tts.AsyncCambAI") as MockAsyncCambAI: - mock_client = MagicMock() - # TTS should not be called for short text - mock_client.text_to_speech.tts = AsyncMock(side_effect=AssertionError("TTS should not be called")) - MockAsyncCambAI.return_value = mock_client - - tts_service = CambTTSService(api_key="test-api-key") - - frames_to_send = [ - TTSSpeakFrame(text="Hi"), # Only 2 characters - ] - - # For short text, we expect TTSStoppedFrame but no audio - expected_down_frames = [AggregatedTextFrame, TTSStoppedFrame, TTSTextFrame] - - frames_received = await run_test( - tts_service, - frames_to_send=frames_to_send, - expected_down_frames=expected_down_frames, - ) - down_frames = frames_received[0] - - # Verify no audio frames were generated - audio_frames = [f for f in down_frames if isinstance(f, TTSAudioRawFrame)] - assert len(audio_frames) == 0, "Should not generate audio for text < 3 chars" - - -@pytest.mark.asyncio -async def test_input_params(): - """Test InputParams model validation and defaults.""" - - # Test defaults - params = CambTTSService.InputParams() - assert params.language == Language.EN - assert params.user_instructions is None - - # Test custom values - params = CambTTSService.InputParams( - language=Language.ES, - user_instructions="Speak slowly and clearly", - ) - assert params.language == Language.ES - assert params.user_instructions == "Speak slowly and clearly" - - -@pytest.mark.asyncio -async def test_language_mapping(): - """Test language enum to Camb.ai language code conversion.""" - - # Test common languages - assert language_to_camb_language(Language.EN) == "en-us" - assert language_to_camb_language(Language.EN_US) == "en-us" - assert language_to_camb_language(Language.EN_GB) == "en-gb" - assert language_to_camb_language(Language.ES) == "es-es" - assert language_to_camb_language(Language.FR) == "fr-fr" - assert language_to_camb_language(Language.DE) == "de-de" - assert language_to_camb_language(Language.JA) == "ja-jp" - assert language_to_camb_language(Language.ZH) == "zh-cn" - - -@pytest.mark.asyncio -async def test_mars_instruct_model(): - """Test that user_instructions are included for mars-instruct model.""" - received_kwargs = {} - - async def mock_tts_with_capture(*args, **kwargs): - nonlocal received_kwargs - received_kwargs = kwargs - yield b"\x00" * 1000 - - with patch("pipecat.services.camb.tts.AsyncCambAI") as MockAsyncCambAI: - mock_client = MagicMock() - mock_client.text_to_speech.tts = mock_tts_with_capture - MockAsyncCambAI.return_value = mock_client - - tts_service = CambTTSService( - api_key="test-api-key", - model="mars-instruct", - params=CambTTSService.InputParams(user_instructions="Speak with excitement"), - ) - - frames_to_send = [ - TTSSpeakFrame(text="This is exciting news!"), - ] - - await run_test( - tts_service, - frames_to_send=frames_to_send, - expected_down_frames=[ - AggregatedTextFrame, - TTSStartedFrame, - TTSAudioRawFrame, - TTSStoppedFrame, - TTSTextFrame, - ], - ) - - # Verify user_instructions was included in the request - assert received_kwargs.get("speech_model") == "mars-instruct" - assert received_kwargs.get("user_instructions") == "Speak with excitement" - - -@pytest.mark.asyncio -async def test_client_initialization(): - """Test that client is created with correct parameters.""" - with patch("pipecat.services.camb.tts.AsyncCambAI") as MockAsyncCambAI: - mock_client = MagicMock() - MockAsyncCambAI.return_value = mock_client - - CambTTSService(api_key="test-key", timeout=120.0) - - # Should have created a client with correct params - MockAsyncCambAI.assert_called_once_with(api_key="test-key", timeout=120.0) - - -@pytest.mark.asyncio -async def test_default_voice_id_used(): - """Test that DEFAULT_VOICE_ID is used when not specified.""" - with patch("pipecat.services.camb.tts.AsyncCambAI") as MockAsyncCambAI: - mock_client = MagicMock() - MockAsyncCambAI.return_value = mock_client - - tts = CambTTSService(api_key="test-key") - - assert tts._voice_id_int == DEFAULT_VOICE_ID - - -@pytest.mark.asyncio -async def test_ttfb_metrics_tracked(): - """Test that TTFB metrics are properly tracked during TTS generation.""" - import time - - ttfb_start_called = False - ttfb_stop_called = False - start_time = None - stop_time = None - - async def mock_tts_with_delay(*args, **kwargs): - # Simulate some network delay - await asyncio.sleep(0.05) - yield b"\x00\x01" * 4800 - - with patch("pipecat.services.camb.tts.AsyncCambAI") as MockAsyncCambAI: - mock_client = MagicMock() - mock_client.text_to_speech.tts = mock_tts_with_delay - MockAsyncCambAI.return_value = mock_client - - tts_service = CambTTSService(api_key="test-api-key") - tts_service._sample_rate = MODEL_SAMPLE_RATES["mars-flash"] - - # Patch the metrics methods to track calls - original_start_ttfb = tts_service.start_ttfb_metrics - original_stop_ttfb = tts_service.stop_ttfb_metrics - - async def patched_start_ttfb(): - nonlocal ttfb_start_called, start_time - ttfb_start_called = True - start_time = time.time() - await original_start_ttfb() - - async def patched_stop_ttfb(): - nonlocal ttfb_stop_called, stop_time - if not ttfb_stop_called: # Only record first stop - ttfb_stop_called = True - stop_time = time.time() - await original_stop_ttfb() - - tts_service.start_ttfb_metrics = patched_start_ttfb - 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b/src/pipecat/transports/websocket/client.py index 2123a2c4d..d68038f74 100644 --- a/src/pipecat/transports/websocket/client.py +++ b/src/pipecat/transports/websocket/client.py @@ -20,6 +20,7 @@ from typing import Awaitable, Callable, Optional import websockets from loguru import logger from pydantic.main import BaseModel +from websockets import HeadersLike from websockets.asyncio.client import connect as websocket_connect from pipecat.frames.frames import ( @@ -50,6 +51,7 @@ class WebsocketClientParams(TransportParams): """ add_wav_header: bool = True + additional_headers: Optional[dict[str, str]] = None serializer: Optional[FrameSerializer] = None @@ -130,7 +132,11 @@ class WebsocketClientSession: return try: - self._websocket = await websocket_connect(uri=self._uri, open_timeout=10) + self._websocket = await websocket_connect( + uri=self._uri, + open_timeout=10, + additional_headers=self._params.additional_headers, + ) self._client_task = self.task_manager.create_task( self._client_task_handler(), f"{self._transport_name}::WebsocketClientSession::_client_task_handler", From 256c70c631e720da25acf9a14cdbe5aef2378270 Mon Sep 17 00:00:00 2001 From: Neil Ruaro Date: Fri, 16 Jan 2026 01:32:08 +0800 Subject: [PATCH 0078/1060] use UserTurnStrategies --- examples/foundational/07zg-interruptible-camb.py | 14 +++++++------- 1 file changed, 7 insertions(+), 7 deletions(-) diff --git a/examples/foundational/07zg-interruptible-camb.py b/examples/foundational/07zg-interruptible-camb.py index f930613d9..5fcc7c2e9 100644 --- a/examples/foundational/07zg-interruptible-camb.py +++ b/examples/foundational/07zg-interruptible-camb.py @@ -29,8 +29,8 @@ from pipecat.services.openai.llm import OpenAILLMService from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams -from pipecat.turns.bot import TurnAnalyzerBotTurnStartStrategy -from pipecat.turns.turn_start_strategies import TurnStartStrategies +from pipecat.turns.user_stop import TurnAnalyzerUserTurnStopStrategy +from pipecat.turns.user_turn_strategies import UserTurnStrategies load_dotenv(override=True) @@ -79,11 +79,11 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): ] context = LLMContext(messages) - context_aggregator = LLMContextAggregatorPair( + user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, user_params=LLMUserAggregatorParams( - turn_start_strategies=TurnStartStrategies( - bot=[TurnAnalyzerBotTurnStartStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3())] + user_turn_strategies=UserTurnStrategies( + stop=[TurnAnalyzerUserTurnStopStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3())] ), ), ) @@ -92,11 +92,11 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): [ transport.input(), stt, - context_aggregator.user(), + user_aggregator, llm, tts, transport.output(), - context_aggregator.assistant(), + assistant_aggregator, ] ) From 80604ba7b6ac8f6c7376be73fb57e5df85a8db7c Mon Sep 17 00:00:00 2001 From: Neil Ruaro Date: Fri, 16 Jan 2026 02:00:48 +0800 Subject: [PATCH 0079/1060] remove _update_settings method --- src/pipecat/services/camb/tts.py | 21 +-------------------- 1 file changed, 1 insertion(+), 20 deletions(-) diff --git a/src/pipecat/services/camb/tts.py b/src/pipecat/services/camb/tts.py index bb9b919a6..51fc67000 100644 --- a/src/pipecat/services/camb/tts.py +++ b/src/pipecat/services/camb/tts.py @@ -16,7 +16,7 @@ Features: - Model-specific sample rates: mars-pro (48kHz), mars-flash (22.05kHz) """ -from typing import Any, AsyncGenerator, Dict, Mapping, Optional +from typing import Any, AsyncGenerator, Dict, Optional from camb import StreamTtsOutputConfiguration from camb.client import AsyncCambAI @@ -253,25 +253,6 @@ class CambTTSService(TTSService): self._sample_rate = MODEL_SAMPLE_RATES.get(self._model_name, 22050) self._settings["sample_rate"] = self._sample_rate - async def _update_settings(self, settings: Mapping[str, Any]): - """Update service settings dynamically. - - Args: - settings: Dictionary of settings to update. - """ - await super()._update_settings(settings) - - for key, value in settings.items(): - if key in self._settings: - if key == "language" and isinstance(value, Language): - self._settings[key] = language_to_camb_language(value) - else: - self._settings[key] = value - logger.debug(f"Updated Camb.ai TTS setting {key} to: {value}") - elif key == "voice_id": - self._voice_id = int(value) - self.set_voice(str(value)) - @traced_tts async def run_tts(self, text: str) -> AsyncGenerator[Frame, None]: """Generate speech from text using Camb.ai's TTS API. 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marker = "extra == 'anthropic'", specifier = "~=0.49.0" }, { name = "audioop-lts", marker = "python_full_version >= '3.13'", specifier = "~=0.2.1" }, { name = "aws-sdk-bedrock-runtime", marker = "python_full_version >= '3.12' and extra == 'aws-nova-sonic'", specifier = "~=0.2.0" }, { name = "aws-sdk-sagemaker-runtime-http2", marker = "python_full_version >= '3.12' and extra == 'sagemaker'" }, - { name = "azure-cognitiveservices-speech", marker = "extra == 'azure'", specifier = "~=1.44.0" }, + { name = "azure-cognitiveservices-speech", marker = "extra == 'azure'", specifier = "~=1.42.0" }, { name = "camb-sdk", marker = "extra == 'camb'", specifier = ">=1.5.4" }, { name = "cartesia", marker = "extra == 'cartesia'", specifier = "~=2.0.3" }, { name = "coremltools", marker = "extra == 'local-smart-turn'", specifier = ">=8.0" }, @@ -4114,7 +4144,7 @@ requires-dist = [ { name = "faster-whisper", marker = "extra == 'whisper'", specifier = "~=1.1.1" }, { name = "google-cloud-speech", marker = 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upload-time = "2025-12-11T08:11:01.553Z" }, ] [[package]] From f60eeaa212ac278f9392296ad90c87e3bd2dc336 Mon Sep 17 00:00:00 2001 From: Neil Ruaro Date: Fri, 16 Jan 2026 02:50:18 +0800 Subject: [PATCH 0082/1060] reverted uv.lock, updated readthedocs.yaml, copyright year updates --- .readthedocs.yaml | 2 +- src/pipecat/services/camb/__init__.py | 2 +- src/pipecat/services/camb/tts.py | 10 ++++++++- uv.lock | 31 +-------------------------- 4 files changed, 12 insertions(+), 33 deletions(-) diff --git a/.readthedocs.yaml b/.readthedocs.yaml index 9f2f13608..79785daca 100644 --- a/.readthedocs.yaml +++ b/.readthedocs.yaml @@ -11,7 +11,7 @@ build: jobs: post_install: - pip install uv - - UV_PROJECT_ENVIRONMENT=$READTHEDOCS_VIRTUALENV_PATH uv sync --group docs --all-extras --no-extra krisp --no-extra gstreamer --no-extra local_smart_turn --no-extra moondream --no-extra riva --no-extra mlx-whisper --no-extra camb + - UV_PROJECT_ENVIRONMENT=$READTHEDOCS_VIRTUALENV_PATH uv sync --group docs --all-extras --no-extra krisp --no-extra gstreamer --no-extra local_smart_turn --no-extra moondream --no-extra riva --no-extra mlx-whisper sphinx: configuration: docs/api/conf.py diff --git a/src/pipecat/services/camb/__init__.py b/src/pipecat/services/camb/__init__.py index d23112945..f28a0edd6 100644 --- a/src/pipecat/services/camb/__init__.py +++ b/src/pipecat/services/camb/__init__.py @@ -1,5 +1,5 @@ # -# Copyright (c) 2024–2025, Daily +# Copyright (c) 2024–2026, Daily # # SPDX-License-Identifier: BSD 2-Clause License # diff --git a/src/pipecat/services/camb/tts.py b/src/pipecat/services/camb/tts.py index 51fc67000..09d1c4e77 100644 --- a/src/pipecat/services/camb/tts.py +++ b/src/pipecat/services/camb/tts.py @@ -1,5 +1,5 @@ # -# Copyright (c) 2024–2025, Daily +# Copyright (c) 2024–2026, Daily # # SPDX-License-Identifier: BSD 2-Clause License # @@ -253,6 +253,14 @@ class CambTTSService(TTSService): self._sample_rate = MODEL_SAMPLE_RATES.get(self._model_name, 22050) self._settings["sample_rate"] = self._sample_rate + # Warn if sample rate doesn't match model's supported rate + if self._sample_rate != MODEL_SAMPLE_RATES.get(self._model_name): + logger.warning( + f"Camb.ai's {self._model_name} model requires " + f"{MODEL_SAMPLE_RATES.get(self._model_name)}Hz sample rate. " + f"Current rate of {self._sample_rate}Hz may cause issues." + ) + @traced_tts async def run_tts(self, text: str) -> AsyncGenerator[Frame, None]: """Generate speech from text using Camb.ai's TTS API. diff --git a/uv.lock b/uv.lock index c8b163dc4..24b9a13c6 100644 --- a/uv.lock +++ b/uv.lock @@ -575,22 +575,6 @@ wheels = [ { url = "https://files.pythonhosted.org/packages/6c/56/3124f61d37a7a4e7cc96afc5492c78ba0cb551151e530b54669ddd1436ef/cachetools-6.2.0-py3-none-any.whl", hash = "sha256:1c76a8960c0041fcc21097e357f882197c79da0dbff766e7317890a65d7d8ba6", size = 11276, upload-time = "2025-08-25T18:57:29.684Z" }, ] -[[package]] -name = "camb-sdk" -version = "1.5.4" -source = { registry = "https://pypi.org/simple" } -dependencies = [ - { name = "httpx" }, - { name = "pydantic" }, - { name = "typing-extensions" }, - { name = "websocket-client" }, - { name = "websockets" }, -] -sdist = { url = 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name = "aws-sdk-sagemaker-runtime-http2", marker = "python_full_version >= '3.12' and extra == 'sagemaker'" }, { name = "azure-cognitiveservices-speech", marker = "extra == 'azure'", specifier = "~=1.42.0" }, - { name = "camb-sdk", marker = "extra == 'camb'", specifier = ">=1.5.4" }, { name = "cartesia", marker = "extra == 'cartesia'", specifier = "~=2.0.3" }, { name = "coremltools", marker = "extra == 'local-smart-turn'", specifier = ">=8.0" }, { name = "daily-python", marker = "extra == 'daily'", specifier = "~=0.23.0" }, @@ -4225,7 +4205,7 @@ requires-dist = [ { name = "wait-for2", marker = "python_full_version < '3.12'", specifier = ">=0.4.1" }, { name = "websockets", marker = "extra == 'websockets-base'", specifier = ">=13.1,<16.0" }, ] -provides-extras = ["aic", "anthropic", "assemblyai", "asyncai", "aws", "aws-nova-sonic", "azure", "camb", "cartesia", "cerebras", "daily", "deepgram", "deepseek", "elevenlabs", "fal", "fireworks", "fish", "gladia", "google", "gradium", "grok", 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2026 14:48:39 -0500 Subject: [PATCH 0084/1060] Fix "bot-llm-text" not firing when using AWS Nova Sonic --- src/pipecat/services/aws/nova_sonic/llm.py | 30 ++++++++++++++++------ 1 file changed, 22 insertions(+), 8 deletions(-) diff --git a/src/pipecat/services/aws/nova_sonic/llm.py b/src/pipecat/services/aws/nova_sonic/llm.py index 14ebde729..fbcbe292e 100644 --- a/src/pipecat/services/aws/nova_sonic/llm.py +++ b/src/pipecat/services/aws/nova_sonic/llm.py @@ -38,6 +38,7 @@ from pipecat.frames.frames import ( LLMContextFrame, LLMFullResponseEndFrame, LLMFullResponseStartFrame, + LLMTextFrame, StartFrame, TranscriptionFrame, TTSAudioRawFrame, @@ -1077,9 +1078,7 @@ class AWSNovaSonicLLMService(LLMService): logger.debug(f"Assistant response text added: {text}") # Report the text of the assistant response. - frame = TTSTextFrame(text, aggregated_by=AggregationType.SENTENCE) - frame.includes_inter_frame_spaces = True - await self.push_frame(frame) + await self._push_assistant_response_text_frames(text) # HACK: here we're also buffering the assistant text ourselves as a # backup rather than relying solely on the assistant context aggregator @@ -1112,11 +1111,7 @@ class AWSNovaSonicLLMService(LLMService): # TTSTextFrame would be ignored otherwise (the interruption frame # would have cleared the assistant aggregator state). await self.push_frame(LLMFullResponseStartFrame()) - frame = TTSTextFrame( - self._assistant_text_buffer, aggregated_by=AggregationType.SENTENCE - ) - frame.includes_inter_frame_spaces = True - await self.push_frame(frame) + await self._push_assistant_response_text_frames(self._assistant_text_buffer) self._may_need_repush_assistant_text = False # Report the end of the assistant response. @@ -1128,6 +1123,25 @@ class AWSNovaSonicLLMService(LLMService): # Clear out the buffered assistant text self._assistant_text_buffer = "" + async def _push_assistant_response_text_frames(self, text: str): + # In a typical "cascade" LLM + TTS setup, LLMTextFrames would not + # proceed beyond the TTS service. Therefore, since a speech-to-speech + # service like Nova Sonic combines both LLM and TTS functionality, you + # would think we wouldn't need to push LLMTextFrames at all. However, + # RTVI relies on LLMTextFrames being pushed to trigger its + # "bot-llm-text" event. So here we push an LLMTextFrame, too, but avoid + # appending it to context to avoid context message duplication. + + # Push LLMTextFrame + llm_text_frame = LLMTextFrame(text) + llm_text_frame.append_to_context = False + await self.push_frame(llm_text_frame) + + # Push TTSTextFrame + tts_text_frame = TTSTextFrame(text, aggregated_by=AggregationType.SENTENCE) + tts_text_frame.includes_inter_frame_spaces = True + await self.push_frame(tts_text_frame) + # # user transcription reporting # From 885b318b04c221fb646b3117a2a238aa92e2b923 Mon Sep 17 00:00:00 2001 From: Paul Kompfner Date: Thu, 15 Jan 2026 15:03:45 -0500 Subject: [PATCH 0085/1060] Fix "bot-llm-text" not firing when using Gemini Live --- .../services/google/gemini_live/llm.py | 23 +++++++++++++++---- 1 file changed, 19 insertions(+), 4 deletions(-) diff --git a/src/pipecat/services/google/gemini_live/llm.py b/src/pipecat/services/google/gemini_live/llm.py index 13b5fb18c..f61c9826c 100644 --- a/src/pipecat/services/google/gemini_live/llm.py +++ b/src/pipecat/services/google/gemini_live/llm.py @@ -1710,11 +1710,26 @@ class GeminiLiveLLMService(LLMService): await self.push_frame(TTSStartedFrame()) await self.push_frame(LLMFullResponseStartFrame()) - frame = TTSTextFrame(text=text, aggregated_by=AggregationType.SENTENCE) - # Gemini Live text already includes any necessary inter-chunk spaces - frame.includes_inter_frame_spaces = True + await self._push_output_transcription_text_frames(text) - await self.push_frame(frame) + async def _push_output_transcription_text_frames(self, text: str): + # In a typical "cascade" LLM + TTS setup, LLMTextFrames would not + # proceed beyond the TTS service. Therefore, since a speech-to-speech + # service like Gemini Live combines both LLM and TTS functionality, you + # might think we wouldn't need to push LLMTextFrames at all. However, + # RTVI relies on LLMTextFrames being pushed to trigger its + # "bot-llm-text" event. So here we push an LLMTextFrame, too, but avoid + # appending it to context to avoid context message duplication. + + # Push LLMTextFrame + llm_text_frame = LLMTextFrame(text) + llm_text_frame.append_to_context = False + await self.push_frame(llm_text_frame) + + # Push TTSTextFrame + tts_text_frame = TTSTextFrame(text, aggregated_by=AggregationType.SENTENCE) + tts_text_frame.includes_inter_frame_spaces = True + await self.push_frame(tts_text_frame) async def _handle_msg_grounding_metadata(self, message: LiveServerMessage): """Handle dedicated grounding metadata messages.""" From 575376235027ac6c1becc2544724bb228a53b4e2 Mon Sep 17 00:00:00 2001 From: Paul Kompfner Date: Thu, 15 Jan 2026 15:16:08 -0500 Subject: [PATCH 0086/1060] Fix "bot-llm-text" not firing when using OpenAI Realtime --- src/pipecat/services/openai/realtime/llm.py | 24 +++++++++++++++++---- 1 file changed, 20 insertions(+), 4 deletions(-) diff --git a/src/pipecat/services/openai/realtime/llm.py b/src/pipecat/services/openai/realtime/llm.py index 7c48d7e34..11a83741e 100644 --- a/src/pipecat/services/openai/realtime/llm.py +++ b/src/pipecat/services/openai/realtime/llm.py @@ -724,10 +724,26 @@ class OpenAIRealtimeLLMService(LLMService): # We receive audio transcript deltas (as opposed to text deltas) when # the output modality is "audio" (the default) if evt.delta: - frame = TTSTextFrame(evt.delta, aggregated_by=AggregationType.SENTENCE) - # OpenAI Realtime text already includes any necessary inter-chunk spaces - frame.includes_inter_frame_spaces = True - await self.push_frame(frame) + await self._push_output_transcript_text_frames(evt.delta) + + async def _push_output_transcript_text_frames(self, text: str): + # In a typical "cascade" LLM + TTS setup, LLMTextFrames would not + # proceed beyond the TTS service. Therefore, since a speech-to-speech + # service like OpenAI Realtime combines both LLM and TTS functionality, + # you might think we wouldn't need to push LLMTextFrames at all. + # However, RTVI relies on LLMTextFrames being pushed to trigger its + # "bot-llm-text" event. So here we push an LLMTextFrame, too, but avoid + # appending it to context to avoid context message duplication. + + # Push LLMTextFrame + llm_text_frame = LLMTextFrame(text) + llm_text_frame.append_to_context = False + await self.push_frame(llm_text_frame) + + # Push TTSTextFrame + tts_text_frame = TTSTextFrame(text, aggregated_by=AggregationType.SENTENCE) + tts_text_frame.includes_inter_frame_spaces = True + await self.push_frame(tts_text_frame) async def _handle_evt_function_call_arguments_done(self, evt): """Handle completion of function call arguments. From 5de80a60d4812eed1816141d9e46c5a32d12dca4 Mon Sep 17 00:00:00 2001 From: Paul Kompfner Date: Thu, 15 Jan 2026 15:30:00 -0500 Subject: [PATCH 0087/1060] Fix "bot-llm-text" not firing when using Grok Realtime --- src/pipecat/services/grok/realtime/llm.py | 24 ++++++++++++++++++++--- 1 file changed, 21 insertions(+), 3 deletions(-) diff --git a/src/pipecat/services/grok/realtime/llm.py b/src/pipecat/services/grok/realtime/llm.py index bcd701cd3..5e368b62b 100644 --- a/src/pipecat/services/grok/realtime/llm.py +++ b/src/pipecat/services/grok/realtime/llm.py @@ -33,6 +33,7 @@ from pipecat.frames.frames import ( LLMFullResponseStartFrame, LLMMessagesAppendFrame, LLMSetToolsFrame, + LLMTextFrame, LLMUpdateSettingsFrame, StartFrame, TranscriptionFrame, @@ -619,9 +620,26 @@ class GrokRealtimeLLMService(LLMService): async def _handle_evt_audio_transcript_delta(self, evt): """Handle audio transcript delta event.""" if evt.delta: - frame = TTSTextFrame(evt.delta, aggregated_by=AggregationType.SENTENCE) - frame.includes_inter_frame_spaces = True - await self.push_frame(frame) + await self._push_output_transcript_text_frames(evt.delta) + + async def _push_output_transcript_text_frames(self, text: str): + # In a typical "cascade" LLM + TTS setup, LLMTextFrames would not + # proceed beyond the TTS service. Therefore, since a speech-to-speech + # service like Grok Realtime combines both LLM and TTS functionality, + # you might think we wouldn't need to push LLMTextFrames at all. + # However, RTVI relies on LLMTextFrames being pushed to trigger its + # "bot-llm-text" event. So here we push an LLMTextFrame, too, but avoid + # appending it to context to avoid context message duplication. + + # Push LLMTextFrame + llm_text_frame = LLMTextFrame(text) + llm_text_frame.append_to_context = False + await self.push_frame(llm_text_frame) + + # Push TTSTextFrame + tts_text_frame = TTSTextFrame(text, aggregated_by=AggregationType.SENTENCE) + tts_text_frame.includes_inter_frame_spaces = True + await self.push_frame(tts_text_frame) async def _handle_evt_function_call_arguments_done(self, evt): """Handle function call arguments done event.""" From ce99924be4afe7350dbad690475dbcd725447379 Mon Sep 17 00:00:00 2001 From: Paul Kompfner Date: Thu, 15 Jan 2026 15:55:22 -0500 Subject: [PATCH 0088/1060] Add CHANGELOG entry describing fix for the missing "bot-llm-text" RTVI event when using realtime (speech-to-speech) services --- changelog/3446.fixed.md | 8 ++++++++ 1 file changed, 8 insertions(+) create mode 100644 changelog/3446.fixed.md diff --git a/changelog/3446.fixed.md b/changelog/3446.fixed.md new file mode 100644 index 000000000..64cc3cb32 --- /dev/null +++ b/changelog/3446.fixed.md @@ -0,0 +1,8 @@ +- Fixed an issue where the "bot-llm-text" RTVI event would not fire for realtime (speech-to-speech) services: + + - `AWSNovaSonicLLMService` + - `GeminiLiveLLMService` + - `OpenAIRealtimeLLMService` + - `GrokRealtimeLLMService` + + The issue was that these services weren't pushing `LLMTextFrame`s. Now they do. From f3c2e29fb422448862dff9aebd7ef18b58fbe59f Mon Sep 17 00:00:00 2001 From: Mark Backman Date: Thu, 15 Jan 2026 15:59:17 -0500 Subject: [PATCH 0089/1060] Clean up CambTTSService --- examples/foundational/07zg-interruptible-camb.py | 2 +- .../foundational/26e-gemini-live-google-search.py | 2 +- .../foundational/32-gemini-grounding-metadata.py | 2 +- src/pipecat/services/camb/tts.py | 12 ++---------- src/pipecat/tests/utils.py | 2 +- tests/test_krisp_sdk_manager.py | 2 +- tests/test_krisp_viva_filter.py | 4 ++-- tests/test_user_turn_controller.py | 2 +- 8 files changed, 10 insertions(+), 18 deletions(-) diff --git a/examples/foundational/07zg-interruptible-camb.py b/examples/foundational/07zg-interruptible-camb.py index 5fcc7c2e9..256eff6f7 100644 --- a/examples/foundational/07zg-interruptible-camb.py +++ b/examples/foundational/07zg-interruptible-camb.py @@ -1,5 +1,5 @@ # -# Copyright (c) 2024–2025, Daily +# Copyright (c) 2024–2026, Daily # # SPDX-License-Identifier: BSD 2-Clause License # diff --git a/examples/foundational/26e-gemini-live-google-search.py b/examples/foundational/26e-gemini-live-google-search.py index 294cf1789..9b37f32ee 100644 --- a/examples/foundational/26e-gemini-live-google-search.py +++ b/examples/foundational/26e-gemini-live-google-search.py @@ -1,5 +1,5 @@ # -# Copyright (c) 2024-2025, Daily +# Copyright (c) 2024-2026, Daily # # SPDX-License-Identifier: BSD 2-Clause License # diff --git a/examples/foundational/32-gemini-grounding-metadata.py b/examples/foundational/32-gemini-grounding-metadata.py index ff4369224..7647287ed 100644 --- a/examples/foundational/32-gemini-grounding-metadata.py +++ b/examples/foundational/32-gemini-grounding-metadata.py @@ -1,5 +1,5 @@ # -# Copyright (c) 2024-2025, Daily +# Copyright (c) 2024-2026, Daily # # SPDX-License-Identifier: BSD 2-Clause License # diff --git a/src/pipecat/services/camb/tts.py b/src/pipecat/services/camb/tts.py index 09d1c4e77..89279604d 100644 --- a/src/pipecat/services/camb/tts.py +++ b/src/pipecat/services/camb/tts.py @@ -248,18 +248,10 @@ class CambTTSService(TTSService): frame: The start frame containing initialization parameters. """ await super().start(frame) + # Use model-specific sample rate if not explicitly specified if not self._init_sample_rate: - self._sample_rate = MODEL_SAMPLE_RATES.get(self._model_name, 22050) - self._settings["sample_rate"] = self._sample_rate - - # Warn if sample rate doesn't match model's supported rate - if self._sample_rate != MODEL_SAMPLE_RATES.get(self._model_name): - logger.warning( - f"Camb.ai's {self._model_name} model requires " - f"{MODEL_SAMPLE_RATES.get(self._model_name)}Hz sample rate. " - f"Current rate of {self._sample_rate}Hz may cause issues." - ) + self._sample_rate = MODEL_SAMPLE_RATES.get(self.model_name, 22050) @traced_tts async def run_tts(self, text: str) -> AsyncGenerator[Frame, None]: diff --git a/src/pipecat/tests/utils.py b/src/pipecat/tests/utils.py index 94b8cb1a4..ac5739829 100644 --- a/src/pipecat/tests/utils.py +++ b/src/pipecat/tests/utils.py @@ -1,5 +1,5 @@ # -# Copyright (c) 2024-2025 Daily +# Copyright (c) 2024-2026, Daily # # SPDX-License-Identifier: BSD 2-Clause License # diff --git a/tests/test_krisp_sdk_manager.py b/tests/test_krisp_sdk_manager.py index a98c97f09..7c774ab85 100644 --- a/tests/test_krisp_sdk_manager.py +++ b/tests/test_krisp_sdk_manager.py @@ -1,5 +1,5 @@ # -# Copyright (c) 2024-2025 Daily +# Copyright (c) 2024-2026, Daily # # SPDX-License-Identifier: BSD 2-Clause License # diff --git a/tests/test_krisp_viva_filter.py b/tests/test_krisp_viva_filter.py index c8f1a23c0..a788ab131 100644 --- a/tests/test_krisp_viva_filter.py +++ b/tests/test_krisp_viva_filter.py @@ -1,5 +1,5 @@ # -# Copyright (c) 2024-2025 Daily +# Copyright (c) 2024-2026, Daily # # SPDX-License-Identifier: BSD 2-Clause License # @@ -9,7 +9,7 @@ import os import sys import tempfile import unittest -from unittest.mock import AsyncMock, MagicMock, Mock, patch +from unittest.mock import MagicMock, patch import numpy as np diff --git a/tests/test_user_turn_controller.py b/tests/test_user_turn_controller.py index 8aa509a8a..1c5cfcf85 100644 --- a/tests/test_user_turn_controller.py +++ b/tests/test_user_turn_controller.py @@ -1,5 +1,5 @@ # -# Copyright (c) 2024-2026 Daily +# Copyright (c) 2024-2026, Daily # # SPDX-License-Identifier: BSD 2-Clause License # From 60216048a8a922a42ade0d1f2ab17764f9f80423 Mon Sep 17 00:00:00 2001 From: Mark Backman Date: Thu, 15 Jan 2026 16:22:17 -0500 Subject: [PATCH 0090/1060] Docs fixes after 0.0.99 --- docs/api/conf.py | 11 +++++++++++ src/pipecat/audio/filters/krisp_filter.py | 1 + src/pipecat/serializers/vonage.py | 3 +-- 3 files changed, 13 insertions(+), 2 deletions(-) diff --git a/docs/api/conf.py b/docs/api/conf.py index 653727668..ef4df8e96 100644 --- a/docs/api/conf.py +++ b/docs/api/conf.py @@ -91,6 +91,17 @@ autodoc_mock_imports = [ # MLX dependencies (Apple Silicon specific) "mlx", "mlx_whisper", # Note: might need underscore format too + # Pydantic v2 compatibility issues in third-party SDKs + "hume", + "hume.tts", + "hume.tts.types", + "cartesia", + "camb", + "sarvamai", + "openpipe", + "openai.types.beta.realtime", + "langchain_core", + "langchain_core.messages", ] # HTML output settings diff --git a/src/pipecat/audio/filters/krisp_filter.py b/src/pipecat/audio/filters/krisp_filter.py index 7fbc00b88..58c4a2835 100644 --- a/src/pipecat/audio/filters/krisp_filter.py +++ b/src/pipecat/audio/filters/krisp_filter.py @@ -61,6 +61,7 @@ class KrispFilter(BaseAudioFilter): Provides real-time noise reduction for audio streams using Krisp's proprietary noise suppression algorithms. Requires a Krisp model file for operation. + .. deprecated:: 0.0.94 The KrispFilter is deprecated and will be removed in a future version. Use KrispVivaFilter instead. diff --git a/src/pipecat/serializers/vonage.py b/src/pipecat/serializers/vonage.py index 9de1cc038..3213e8bba 100644 --- a/src/pipecat/serializers/vonage.py +++ b/src/pipecat/serializers/vonage.py @@ -34,8 +34,7 @@ class VonageFrameSerializer(FrameSerializer): WebSocket streaming protocol. Note: - Ref docs: - https://developer.vonage.com/en/video/guides/audio-connector + Ref docs: https://developer.vonage.com/en/video/guides/audio-connector """ class InputParams(BaseModel): From 21aaa48e6240677681e95767c6c487a4a03b9c18 Mon Sep 17 00:00:00 2001 From: Mark Backman Date: Thu, 15 Jan 2026 17:02:30 -0500 Subject: [PATCH 0091/1060] Fix pydantic issues impacting autodoc --- src/pipecat/services/openai/realtime/events.py | 8 +++----- .../services/openai_realtime_beta/events.py | 8 +++----- src/pipecat/transports/daily/utils.py | 15 ++++++++++----- 3 files changed, 16 insertions(+), 15 deletions(-) diff --git a/src/pipecat/services/openai/realtime/events.py b/src/pipecat/services/openai/realtime/events.py index c0ef5b890..78faff45d 100644 --- a/src/pipecat/services/openai/realtime/events.py +++ b/src/pipecat/services/openai/realtime/events.py @@ -1002,17 +1002,15 @@ class TokenDetails(BaseModel): image_tokens: Number of image tokens used (for input only). """ + model_config = ConfigDict(extra="allow") + __pydantic_extra__: dict[str, Any] + cached_tokens: Optional[int] = 0 text_tokens: Optional[int] = 0 audio_tokens: Optional[int] = 0 cached_tokens_details: Optional[CachedTokensDetails] = None image_tokens: Optional[int] = 0 - class Config: - """Pydantic configuration for TokenDetails.""" - - extra = "allow" - class Usage(BaseModel): """Token usage statistics for a response. diff --git a/src/pipecat/services/openai_realtime_beta/events.py b/src/pipecat/services/openai_realtime_beta/events.py index ce582e9bd..ea4e738c2 100644 --- a/src/pipecat/services/openai_realtime_beta/events.py +++ b/src/pipecat/services/openai_realtime_beta/events.py @@ -877,15 +877,13 @@ class TokenDetails(BaseModel): audio_tokens: Number of audio tokens used. Defaults to 0. """ + model_config = ConfigDict(extra="allow") + __pydantic_extra__: dict[str, Any] + cached_tokens: Optional[int] = 0 text_tokens: Optional[int] = 0 audio_tokens: Optional[int] = 0 - class Config: - """Pydantic configuration for TokenDetails.""" - - extra = "allow" - class Usage(BaseModel): """Token usage statistics for a response. diff --git a/src/pipecat/transports/daily/utils.py b/src/pipecat/transports/daily/utils.py index bc4c4fa9d..9ea02e203 100644 --- a/src/pipecat/transports/daily/utils.py +++ b/src/pipecat/transports/daily/utils.py @@ -10,11 +10,11 @@ Methods that wrap the Daily API to create rooms, check room URLs, and get meetin """ import time -from typing import Dict, List, Literal, Optional +from typing import Any, Dict, List, Literal, Optional from urllib.parse import urlparse import aiohttp -from pydantic import BaseModel, Field, ValidationError +from pydantic import BaseModel, ConfigDict, Field, ValidationError class DailyRoomSipParams(BaseModel): @@ -77,7 +77,7 @@ class TranscriptionBucketConfig(BaseModel): allow_api_access: bool = False -class DailyRoomProperties(BaseModel, extra="allow"): +class DailyRoomProperties(BaseModel): """Properties for configuring a Daily room. Reference: https://docs.daily.co/reference/rest-api/rooms/create-room#properties @@ -100,6 +100,11 @@ class DailyRoomProperties(BaseModel, extra="allow"): start_video_off: Whether video is off by default. """ + model_config = ConfigDict(extra="allow") + + # Pydantic v2.12+ requires explicit annotation for extra fields + __pydantic_extra__: dict[str, Any] + exp: Optional[float] = None enable_chat: bool = False enable_prejoin_ui: bool = False @@ -113,7 +118,7 @@ class DailyRoomProperties(BaseModel, extra="allow"): recordings_bucket: Optional[RecordingsBucketConfig] = None transcription_bucket: Optional[TranscriptionBucketConfig] = None sip: Optional[DailyRoomSipParams] = None - sip_uri: Optional[dict] = None + sip_uri: Optional[Dict[str, Any]] = None start_video_off: bool = False @property @@ -203,7 +208,7 @@ class DailyMeetingTokenProperties(BaseModel): enable_recording: Optional[Literal["cloud", "local", "raw-tracks"]] = None enable_prejoin_ui: Optional[bool] = None start_cloud_recording: Optional[bool] = None - permissions: Optional[dict] = None + permissions: Optional[Dict[str, Any]] = None class DailyMeetingTokenParams(BaseModel): From 4458ca1d245ce65453021c626282bd68cd064632 Mon Sep 17 00:00:00 2001 From: Mark Backman Date: Thu, 15 Jan 2026 17:11:06 -0500 Subject: [PATCH 0092/1060] Mock FastAPI --- docs/api/conf.py | 8 ++++++++ pyproject.toml | 4 ++-- uv.lock | 10 +++++----- 3 files changed, 15 insertions(+), 7 deletions(-) diff --git a/docs/api/conf.py b/docs/api/conf.py index ef4df8e96..5f7a3c2dc 100644 --- a/docs/api/conf.py +++ b/docs/api/conf.py @@ -102,6 +102,14 @@ autodoc_mock_imports = [ "openai.types.beta.realtime", "langchain_core", "langchain_core.messages", + # FastAPI - Pydantic v2 compatibility issues during Sphinx autodoc + "fastapi", + "fastapi.applications", + "fastapi.routing", + "fastapi.params", + "fastapi.middleware", + "fastapi.responses", + "uvicorn", ] # HTML output settings diff --git a/pyproject.toml b/pyproject.toml index a6b5afafa..4dc92b879 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -97,7 +97,7 @@ qwen = [] remote-smart-turn = [] rime = [ "pipecat-ai[websockets-base]" ] riva = [ "pipecat-ai[nvidia]" ] -runner = [ "python-dotenv>=1.0.0,<2.0.0", "uvicorn>=0.32.0,<1.0.0", "fastapi>=0.115.6,<0.122.0", "pipecat-ai-small-webrtc-prebuilt>=2.0.4"] +runner = [ "python-dotenv>=1.0.0,<2.0.0", "uvicorn>=0.32.0,<1.0.0", "fastapi>=0.115.6,<0.128.0", "pipecat-ai-small-webrtc-prebuilt>=2.0.4"] sagemaker = ["aws_sdk_sagemaker_runtime_http2; python_version>='3.12'"] sambanova = [] sarvam = [ "sarvamai==0.1.21", "pipecat-ai[websockets-base]" ] @@ -113,7 +113,7 @@ together = [] tracing = [ "opentelemetry-sdk>=1.33.0", "opentelemetry-api>=1.33.0", "opentelemetry-instrumentation>=0.54b0" ] ultravox = [ "pipecat-ai[websockets-base]" ] webrtc = [ "aiortc>=1.14.0,<2", "opencv-python>=4.11.0.86,<5" ] -websocket = [ "pipecat-ai[websockets-base]", "fastapi>=0.115.6,<0.122.0" ] +websocket = [ "pipecat-ai[websockets-base]", "fastapi>=0.115.6,<0.128.0" ] websockets-base = [ "websockets>=13.1,<16.0" ] whisper = [ "faster-whisper~=1.1.1" ] diff --git a/uv.lock b/uv.lock index 43a44bb5c..45c1f892f 100644 --- a/uv.lock +++ b/uv.lock @@ -1446,7 +1446,7 @@ wheels = [ [[package]] name = "fastapi" -version = "0.121.3" +version = "0.127.1" source = { registry = "https://pypi.org/simple" } dependencies = [ { name = "annotated-doc" }, @@ -1454,9 +1454,9 @@ dependencies = [ { name = "starlette" }, { name = "typing-extensions" }, ] -sdist = { url = "https://files.pythonhosted.org/packages/80/f0/086c442c6516195786131b8ca70488c6ef11d2f2e33c9a893576b2b0d3f7/fastapi-0.121.3.tar.gz", hash = "sha256:0055bc24fe53e56a40e9e0ad1ae2baa81622c406e548e501e717634e2dfbc40b", size = 344501, upload-time = "2025-11-19T16:53:39.243Z" } +sdist = { url = "https://files.pythonhosted.org/packages/96/8a/6b9ba6eb8ff3817caae83120495965d9e70afb4d6348cb120e464ee199f4/fastapi-0.127.1.tar.gz", hash = "sha256:946a87ee5d931883b562b6bada787d6c8178becee2683cb3f9b980d593206359", size = 391876, upload-time = "2025-12-26T13:04:47.075Z" } wheels = [ - { url = "https://files.pythonhosted.org/packages/98/b6/4f620d7720fc0a754c8c1b7501d73777f6ba43b57c8ab99671f4d7441eb8/fastapi-0.121.3-py3-none-any.whl", hash = "sha256:0c78fc87587fcd910ca1bbf5bc8ba37b80e119b388a7206b39f0ecc95ebf53e9", size = 109801, upload-time = "2025-11-19T16:53:37.918Z" }, + { url = "https://files.pythonhosted.org/packages/d2/f3/a6858d147ed2645c095d11dc2440f94a5f1cd8f4df888e3377e6b5281a0f/fastapi-0.127.1-py3-none-any.whl", hash = "sha256:31d670a4f9373cc6d7994420f98e4dc46ea693145207abc39696746c83a44430", size = 112332, upload-time = "2025-12-26T13:04:45.329Z" }, ] [package.optional-dependencies] @@ -4513,8 +4513,8 @@ requires-dist = [ { name = "docstring-parser", specifier = "~=0.16" }, { name = "einops", marker = "extra == 'moondream'", specifier = "~=0.8.0" }, { name = "fal-client", marker = "extra == 'fal'", specifier = "~=0.5.9" }, - { name = "fastapi", marker = "extra == 'runner'", specifier = ">=0.115.6,<0.122.0" }, - { name = "fastapi", marker = "extra == 'websocket'", specifier = ">=0.115.6,<0.122.0" }, + { name = "fastapi", marker = "extra == 'runner'", specifier = ">=0.115.6,<0.128.0" }, + { name = "fastapi", marker = "extra == 'websocket'", specifier = ">=0.115.6,<0.128.0" }, { name = "faster-whisper", marker = "extra == 'whisper'", specifier = "~=1.1.1" }, { name = "google-cloud-speech", marker = "extra == 'google'", specifier = ">=2.33.0,<3" }, { name = "google-cloud-texttospeech", marker = "extra == 'google'", specifier = ">=2.31.0,<3" }, From 1510fb4fc0276c0ff9370190cdf6345b2fcfeb04 Mon Sep 17 00:00:00 2001 From: Mike Seese Date: Mon, 1 Dec 2025 15:01:06 -0800 Subject: [PATCH 0093/1060] add Hathora STT and TTS services --- .../07af-interruptible-hathora.py | 137 +++++++++++ src/pipecat/services/hathora/__init__.py | 14 ++ src/pipecat/services/hathora/stt.py | 107 ++++++++ src/pipecat/services/hathora/tts.py | 229 ++++++++++++++++++ 4 files changed, 487 insertions(+) create mode 100644 examples/foundational/07af-interruptible-hathora.py create mode 100644 src/pipecat/services/hathora/__init__.py create mode 100644 src/pipecat/services/hathora/stt.py create mode 100644 src/pipecat/services/hathora/tts.py diff --git a/examples/foundational/07af-interruptible-hathora.py b/examples/foundational/07af-interruptible-hathora.py new file mode 100644 index 000000000..5a06b7bf0 --- /dev/null +++ b/examples/foundational/07af-interruptible-hathora.py @@ -0,0 +1,137 @@ +# +# Copyright (c) 2024–2025, Daily +# +# SPDX-License-Identifier: BSD 2-Clause License +# + +import os + +from dotenv import load_dotenv +from loguru import logger + +from pipecat.audio.turn.smart_turn.base_smart_turn import SmartTurnParams +from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3 +from pipecat.audio.vad.silero import SileroVADAnalyzer +from pipecat.audio.vad.vad_analyzer import VADParams +from pipecat.frames.frames import LLMRunFrame +from pipecat.pipeline.pipeline import Pipeline +from pipecat.pipeline.runner import PipelineRunner +from pipecat.pipeline.task import PipelineParams, PipelineTask +from pipecat.processors.aggregators.llm_context import LLMContext +from pipecat.processors.aggregators.llm_response_universal import LLMContextAggregatorPair +from pipecat.runner.types import RunnerArguments +from pipecat.runner.utils import create_transport +from pipecat.services.hathora.stt import ParakeetSTTService +from pipecat.services.hathora.tts import ChatterboxTTSService, KokoroTTSService +from pipecat.services.openai.llm import OpenAILLMService +from pipecat.transports.base_transport import BaseTransport, TransportParams +from pipecat.transports.daily.transport import DailyParams +from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams + +load_dotenv(override=True) + +# We store functions so objects (e.g. SileroVADAnalyzer) don't get +# instantiated. The function will be called when the desired transport gets +# selected. +transport_params = { + "daily": lambda: DailyParams( + audio_in_enabled=True, + audio_out_enabled=True, + vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), + turn_analyzer=LocalSmartTurnAnalyzerV3(), + ), + "webrtc": lambda: TransportParams( + audio_in_enabled=True, + audio_out_enabled=True, + vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), + turn_analyzer=LocalSmartTurnAnalyzerV3(), + ), +} + + +async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): + logger.info(f"Starting bot") + + # See https://models.hathora.dev/model/nvidia-parakeet-tdt-0.6b-v3 + stt = ParakeetTDTSTTService( + base_url="https://app-1c7bebb9-6977-4101-9619-833b251b86d1.app.hathora.dev/v1/transcribe", + api_key=os.getenv("HATHORA_API_KEY") + ) + + # See https://models.hathora.dev/model/hexgrad-kokoro-82m + tts = KokoroTTSService( + base_url="https://app-01312daf-6e53-4b9d-a4ad-13039f35adc4.app.hathora.dev/synthesize", + api_key=os.getenv("HATHORA_API_KEY"), + ) + + # See https://models.hathora.dev/model/resemble-ai-chatterbox + # tts = ChatterboxTTSService( + # base_url="https://app-efbc8fe2-df55-4f96-bbe3-74f6ea9d986b.app.hathora.dev/v1/generate", + # api_key=os.getenv("HATHORA_API_KEY") + # ) + + # See https://models.hathora.dev/model/qwen3-30b-a3b + llm = OpenAILLMService( + base_url="https://app-362f7ca1-6975-4e18-a605-ab202bf2c315.app.hathora.dev/v1", + api_key=os.getenv("HATHORA_API_KEY"), + model=None, + ) + + messages = [ + { + "role": "system", + "content": "You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + }, + ] + + context = LLMContext(messages) + context_aggregator = LLMContextAggregatorPair(context) + + pipeline = Pipeline( + [ + transport.input(), # Transport user input + stt, + context_aggregator.user(), # User responses + llm, # LLM + tts, # TTS + transport.output(), # Transport bot output + context_aggregator.assistant(), # Assistant spoken responses + ] + ) + + task = PipelineTask( + pipeline, + params=PipelineParams( + enable_metrics=True, + enable_usage_metrics=True, + ), + idle_timeout_secs=runner_args.pipeline_idle_timeout_secs, + ) + + @transport.event_handler("on_client_connected") + async def on_client_connected(transport, client): + logger.info(f"Client connected") + # Kick off the conversation. + messages.append({"role": "system", "content": "Please introduce yourself to the user."}) + await task.queue_frames([LLMRunFrame()]) + + @transport.event_handler("on_client_disconnected") + async def on_client_disconnected(transport, client): + logger.info(f"Client disconnected") + await task.cancel() + + runner = PipelineRunner(handle_sigint=runner_args.handle_sigint) + + await runner.run(task) + + +async def bot(runner_args: RunnerArguments): + """Main bot entry point compatible with Pipecat Cloud.""" + transport = await create_transport(runner_args, transport_params) + await run_bot(transport, runner_args) + + +if __name__ == "__main__": + from pipecat.runner.run import main + + main() diff --git a/src/pipecat/services/hathora/__init__.py b/src/pipecat/services/hathora/__init__.py new file mode 100644 index 000000000..11b7dbb55 --- /dev/null +++ b/src/pipecat/services/hathora/__init__.py @@ -0,0 +1,14 @@ +# +# Copyright (c) 2024–2025, Daily +# +# SPDX-License-Identifier: BSD 2-Clause License +# + +import sys + +from pipecat.services import DeprecatedModuleProxy + +from .stt import * +from .tts import * + +sys.modules[__name__] = DeprecatedModuleProxy(globals(), "hathora", "hathora.[stt,tts]") diff --git a/src/pipecat/services/hathora/stt.py b/src/pipecat/services/hathora/stt.py new file mode 100644 index 000000000..ef4b209af --- /dev/null +++ b/src/pipecat/services/hathora/stt.py @@ -0,0 +1,107 @@ +# +# Copyright (c) 2024–2025, Daily +# +# SPDX-License-Identifier: BSD 2-Clause License +# + +"""[Hathora-hosted](https://models.hathora.dev) speech-to-text services.""" + +import os +from typing import Optional + +import aiohttp +from loguru import logger + +from pipecat.frames.frames import ( + ErrorFrame, + TranscriptionFrame, +) +from pipecat.services.stt_service import SegmentedSTTService +from pipecat.transcriptions.language import Language +from pipecat.utils.time import time_now_iso8601 + +class ParakeetTDTSTTService(SegmentedSTTService): + """Parakeet TDT is a multilingual automatic speech recognition model + with word-level timestamps. + + This service uses the Hathora-hosted Parakeet model via the HTTP API. + + [Documentation](https://models.hathora.dev/model/nvidia-parakeet-tdt-0.6b-v3) + """ + + def __init__( + self, + *, + base_url = None, + api_key = None, + start_time: Optional[int] = None, + end_time: Optional[int] = None, + **kwargs, + ): + """Initialize the Hathora-hosted Parakeet STT service. + + Args: + base_url: Base URL for the Hathora Parakeet STT API. + api_key: API key for authentication with the Hathora service; + provisiion one [here](https://models.hathora.dev/tokens). + start_time: Start time in seconds for the time window. + end_time: End time in seconds for the time window. + """ + super().__init__( + **kwargs, + ) + self._base_url = base_url + self._api_key = api_key + self._start_time = start_time + self._end_time = end_time + + def can_generate_metrics(self) -> bool: + return True + + async def run_stt(self, audio: bytes): + try: + await self.start_processing_metrics() + await self.start_ttfb_metrics() + + url = f"{self._base_url}" + + url_query_params = [] + if self._start_time is not None: + url_query_params.append(f"start_time={self._start_time}") + if self._end_time is not None: + url_query_params.append(f"end_time={self._end_time}") + url_query_params.append(f"sample_rate={self.sample_rate}") + + if len(url_query_params) > 0: + url += "?" + "&".join(url_query_params) + + api_key = self._api_key or os.getenv("HATHORA_API_KEY") + + form_data = aiohttp.FormData() + form_data.add_field("file", audio, filename="audio.wav", content_type="application/octet-stream") + + async with aiohttp.ClientSession() as session: + async with session.post( + url, + headers={"Authorization": f"Bearer {api_key}"}, + data=form_data, + ) as resp: + response = await resp.json() + + if response and "text" in response: + text = response["text"].strip() + if text: # Only yield non-empty text + await self.stop_ttfb_metrics() + await self.stop_processing_metrics() + logger.debug(f"Transcription: [{text}]") + yield TranscriptionFrame( + text, + self._user_id, + time_now_iso8601(), + Language("en"), # TODO: the parakeet hathora API doesn't accept a language but says it's multilingual + result=response, + ) + + except Exception as e: + logger.error(f"Hathora error: {e}") + yield ErrorFrame(f"Hathora error: {str(e)}") diff --git a/src/pipecat/services/hathora/tts.py b/src/pipecat/services/hathora/tts.py new file mode 100644 index 000000000..d9ec78793 --- /dev/null +++ b/src/pipecat/services/hathora/tts.py @@ -0,0 +1,229 @@ +# +# Copyright (c) 2024–2025, Daily +# +# SPDX-License-Identifier: BSD 2-Clause License +# + +"""[Hathora-hosted](https://models.hathora.dev) text-to-speech services.""" + +import io +import os +import wave +from typing import Optional, Tuple + +import aiohttp +from loguru import logger + +from pipecat.frames.frames import ( + ErrorFrame, + TTSAudioRawFrame, + TTSStartedFrame, + TTSStoppedFrame, +) +from pipecat.services.tts_service import TTSService + +def _decode_audio_payload( + audio_bytes: bytes, + *, + fallback_sample_rate: int, + fallback_channels: int = 1, +) -> Tuple[bytes, int, int]: + """Convert a WAV/PCM payload into raw PCM samples for TTSAudioRawFrame.""" + + try: + with wave.open(io.BytesIO(audio_bytes), "rb") as wav_reader: + channels = wav_reader.getnchannels() + sample_rate = wav_reader.getframerate() + frames = wav_reader.readframes(wav_reader.getnframes()) + return frames, sample_rate, channels + except (wave.Error, EOFError): + # If the payload is already raw PCM, just pass it through. + return audio_bytes, fallback_sample_rate, fallback_channels + +class KokoroTTSService(TTSService): + """Kokoro is an open-weight TTS model with 82 million parameters. + + This service uses the Hathora-hosted Kokoro model via the HTTP API. + + [Documentation](https://models.hathora.dev/model/hexgrad-kokoro-82m) + """ + + def __init__( + self, + *, + base_url = None, + api_key = None, + voice: Optional[str] = None, + speed: Optional[float] = None, + **kwargs, + ): + """Initialize the Hathora-hosted Kokoro TTS service. + + Args: + base_url: Base URL for the Hathora Kokoro TTS API, . + api_key: API key for authentication with the Hathora service; + provisiion one [here](https://models.hathora.dev/tokens). + voice: Voice to use for synthesis (see the + [Hathora docs](https://models.hathora.dev/model/hexgrad-kokoro-82m) + for the default value; [list of voices](https://huggingface.co/hexgrad/Kokoro-82M/blob/main/VOICES.md)). + speed: Speech speed multiplier (0.5 = half speed, 2.0 = double speed, default: 1). + """ + super().__init__( + **kwargs, + ) + self._base_url = base_url + self._api_key = api_key + self._voice = voice + self._speed = speed + + def can_generate_metrics(self) -> bool: + return True + + async def run_tts(self, text: str): + try: + await self.start_processing_metrics() + await self.start_ttfb_metrics() + + url = f"{self._base_url}" + + api_key = self._api_key or os.getenv("HATHORA_API_KEY") + + payload = { + "text": text + } + + if self._voice is not None: + payload["voice"] = self._voice + if self._speed is not None: + payload["speed"] = self._speed + + yield TTSStartedFrame() + + async with aiohttp.ClientSession() as session: + async with session.post( + url, + headers={"Authorization": f"Bearer {api_key}", "Accept": "application/octet-stream"}, + json=payload, + ) as resp: + audio_data = await resp.read() + + pcm_audio, sample_rate, num_channels = _decode_audio_payload( + audio_data, + fallback_sample_rate=self.sample_rate or self._init_sample_rate or 24000, + ) + + await self.stop_ttfb_metrics() + + frame = TTSAudioRawFrame( + audio=pcm_audio, + sample_rate=sample_rate, + num_channels=num_channels, + ) + + yield frame + + except Exception as e: + logger.error(f"Hathora error: {e}") + yield ErrorFrame(f"Hathora error: {str(e)}") + finally: + await self.stop_ttfb_metrics() + await self.stop_processing_metrics() + yield TTSStoppedFrame() + +class ChatterboxTTSService(TTSService): + """Chatterbox is a public text-to-speech model optimized for natural and expressive voice synthesis. + + This service uses the Hathora-hosted Chatterbox model via the HTTP API. + + [Documentation](https://models.hathora.dev/model/resemble-ai-chatterbox) + """ + + def __init__( + self, + *, + base_url = None, + api_key = None, + exaggeration: Optional[float] = None, + audio_prompt: Optional[bytes] = None, + cfg_weight: Optional[float] = None, + **kwargs, + ): + """Initialize the Hathora-hosted Chatterbox TTS service. + + Args: + base_url: Base URL for the Hathora Chatterbox TTS API. + api_key: API key for authentication with the Hathora service; + provisiion one [here](https://models.hathora.dev/tokens). + exaggeration: Controls emotional intensity (default: 0.5). + audio_prompt: Reference audio file for voice cloning. + cfg_weight: Controls adherence to reference voice (default: 0.5). + """ + + super().__init__( + **kwargs, + ) + self._base_url = base_url + self._api_key = api_key + self._exaggeration = exaggeration + self._audio_prompt = audio_prompt + self._cfg_weight = cfg_weight + + def can_generate_metrics(self) -> bool: + return True + + async def run_tts(self, text: str): + try: + await self.start_ttfb_metrics() + + url = f"{self._base_url}" + + url_query_params = [] + if self._exaggeration is not None: + url_query_params.append(f"exaggeration={self._exaggeration}") + if self._cfg_weight is not None: + url_query_params.append(f"cfg_weight={self._cfg_weight}") + + if len(url_query_params) > 0: + url += "?" + "&".join(url_query_params) + + api_key = self._api_key or os.getenv("HATHORA_API_KEY") + + form_data = aiohttp.FormData() + form_data.add_field("text", text) + + if self._audio_prompt is not None: + form_data.add_field("audio_prompt", self._audio_prompt, filename="audio.wav", content_type="application/octet-stream") + + yield TTSStartedFrame() + + async with aiohttp.ClientSession() as session: + async with session.post( + url, + headers={"Authorization": f"Bearer {api_key}"}, + data=form_data, + ) as resp: + audio_data = await resp.read() + + await self.start_tts_usage_metrics(text) + + pcm_audio, sample_rate, num_channels = _decode_audio_payload( + audio_data, + fallback_sample_rate=self.sample_rate or self._init_sample_rate or 24000, + ) + + await self.stop_ttfb_metrics() + + frame = TTSAudioRawFrame( + audio=pcm_audio, + sample_rate=sample_rate, + num_channels=num_channels, + ) + + yield frame + + except Exception as e: + logger.error(f"Hathora error: {e}") + yield ErrorFrame(f"Hathora error: {str(e)}") + finally: + await self.stop_ttfb_metrics() + yield TTSStoppedFrame() From e5632a9339ae48a81977efe7e470d74cd2d07a02 Mon Sep 17 00:00:00 2001 From: Mike Seese Date: Wed, 17 Dec 2025 19:16:58 -0800 Subject: [PATCH 0094/1060] transition Hathora service to use the unified API and apply PR feedback add Hathora to root files Hathora run linter added hathora changelog --- README.md | 4 +- changelog/3169.added.md | 1 + env.example | 3 + ...thora.py => 07ag-interruptible-hathora.py} | 32 ++-- src/pipecat/services/hathora/__init__.py | 14 -- src/pipecat/services/hathora/stt.py | 108 ++++++----- src/pipecat/services/hathora/tts.py | 173 +++++------------- src/pipecat/services/hathora/utils.py | 22 +++ 8 files changed, 152 insertions(+), 205 deletions(-) create mode 100644 changelog/3169.added.md rename examples/foundational/{07af-interruptible-hathora.py => 07ag-interruptible-hathora.py} (80%) create mode 100644 src/pipecat/services/hathora/utils.py diff --git a/README.md b/README.md index 0fac27943..65a12634f 100644 --- a/README.md +++ b/README.md @@ -73,9 +73,9 @@ Catch new features, interviews, and how-tos on our [Pipecat TV](https://www.yout | Category | Services | | ------------------- | ----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | -| Speech-to-Text | [AssemblyAI](https://docs.pipecat.ai/server/services/stt/assemblyai), [AWS](https://docs.pipecat.ai/server/services/stt/aws), [Azure](https://docs.pipecat.ai/server/services/stt/azure), [Cartesia](https://docs.pipecat.ai/server/services/stt/cartesia), [Deepgram](https://docs.pipecat.ai/server/services/stt/deepgram), [ElevenLabs](https://docs.pipecat.ai/server/services/stt/elevenlabs), [Fal Wizper](https://docs.pipecat.ai/server/services/stt/fal), [Gladia](https://docs.pipecat.ai/server/services/stt/gladia), [Google](https://docs.pipecat.ai/server/services/stt/google), [Gradium](https://docs.pipecat.ai/server/services/stt/gradium), [Groq (Whisper)](https://docs.pipecat.ai/server/services/stt/groq), [NVIDIA Riva](https://docs.pipecat.ai/server/services/stt/riva), [OpenAI (Whisper)](https://docs.pipecat.ai/server/services/stt/openai), [SambaNova (Whisper)](https://docs.pipecat.ai/server/services/stt/sambanova), [Sarvam](https://docs.pipecat.ai/server/services/stt/sarvam), [Soniox](https://docs.pipecat.ai/server/services/stt/soniox), [Speechmatics](https://docs.pipecat.ai/server/services/stt/speechmatics), [Whisper](https://docs.pipecat.ai/server/services/stt/whisper) | +| Speech-to-Text | [AssemblyAI](https://docs.pipecat.ai/server/services/stt/assemblyai), [AWS](https://docs.pipecat.ai/server/services/stt/aws), [Azure](https://docs.pipecat.ai/server/services/stt/azure), [Cartesia](https://docs.pipecat.ai/server/services/stt/cartesia), [Deepgram](https://docs.pipecat.ai/server/services/stt/deepgram), [ElevenLabs](https://docs.pipecat.ai/server/services/stt/elevenlabs), [Fal Wizper](https://docs.pipecat.ai/server/services/stt/fal), [Gladia](https://docs.pipecat.ai/server/services/stt/gladia), [Google](https://docs.pipecat.ai/server/services/stt/google), [Gradium](https://docs.pipecat.ai/server/services/stt/gradium), [Groq (Whisper)](https://docs.pipecat.ai/server/services/stt/groq), [Hathora](https://docs.pipecat.ai/server/services/stt/hathora), [NVIDIA Riva](https://docs.pipecat.ai/server/services/stt/riva), [OpenAI (Whisper)](https://docs.pipecat.ai/server/services/stt/openai), [SambaNova (Whisper)](https://docs.pipecat.ai/server/services/stt/sambanova), [Sarvam](https://docs.pipecat.ai/server/services/stt/sarvam), [Soniox](https://docs.pipecat.ai/server/services/stt/soniox), [Speechmatics](https://docs.pipecat.ai/server/services/stt/speechmatics), [Whisper](https://docs.pipecat.ai/server/services/stt/whisper) | | LLMs | [Anthropic](https://docs.pipecat.ai/server/services/llm/anthropic), [AWS](https://docs.pipecat.ai/server/services/llm/aws), [Azure](https://docs.pipecat.ai/server/services/llm/azure), [Cerebras](https://docs.pipecat.ai/server/services/llm/cerebras), [DeepSeek](https://docs.pipecat.ai/server/services/llm/deepseek), [Fireworks AI](https://docs.pipecat.ai/server/services/llm/fireworks), [Gemini](https://docs.pipecat.ai/server/services/llm/gemini), [Grok](https://docs.pipecat.ai/server/services/llm/grok), [Groq](https://docs.pipecat.ai/server/services/llm/groq), [Mistral](https://docs.pipecat.ai/server/services/llm/mistral), [NVIDIA NIM](https://docs.pipecat.ai/server/services/llm/nim), [Ollama](https://docs.pipecat.ai/server/services/llm/ollama), [OpenAI](https://docs.pipecat.ai/server/services/llm/openai), [OpenRouter](https://docs.pipecat.ai/server/services/llm/openrouter), [Perplexity](https://docs.pipecat.ai/server/services/llm/perplexity), [Qwen](https://docs.pipecat.ai/server/services/llm/qwen), [SambaNova](https://docs.pipecat.ai/server/services/llm/sambanova) [Together AI](https://docs.pipecat.ai/server/services/llm/together) | -| Text-to-Speech | [Async](https://docs.pipecat.ai/server/services/tts/asyncai), [AWS](https://docs.pipecat.ai/server/services/tts/aws), [Azure](https://docs.pipecat.ai/server/services/tts/azure), [Camb AI](https://docs.pipecat.ai/server/services/tts/camb), [Cartesia](https://docs.pipecat.ai/server/services/tts/cartesia), [Deepgram](https://docs.pipecat.ai/server/services/tts/deepgram), [ElevenLabs](https://docs.pipecat.ai/server/services/tts/elevenlabs), [Fish](https://docs.pipecat.ai/server/services/tts/fish), [Google](https://docs.pipecat.ai/server/services/tts/google), [Gradium](https://docs.pipecat.ai/server/services/tts/gradium), [Groq](https://docs.pipecat.ai/server/services/tts/groq), [Hume](https://docs.pipecat.ai/server/services/tts/hume), [Inworld](https://docs.pipecat.ai/server/services/tts/inworld), [LMNT](https://docs.pipecat.ai/server/services/tts/lmnt), [MiniMax](https://docs.pipecat.ai/server/services/tts/minimax), [Neuphonic](https://docs.pipecat.ai/server/services/tts/neuphonic), [NVIDIA Riva](https://docs.pipecat.ai/server/services/tts/riva), [OpenAI](https://docs.pipecat.ai/server/services/tts/openai), [Piper](https://docs.pipecat.ai/server/services/tts/piper), [PlayHT](https://docs.pipecat.ai/server/services/tts/playht), [Rime](https://docs.pipecat.ai/server/services/tts/rime), [Sarvam](https://docs.pipecat.ai/server/services/tts/sarvam), [Speechmatics](https://docs.pipecat.ai/server/services/tts/speechmatics), [XTTS](https://docs.pipecat.ai/server/services/tts/xtts) | +| Text-to-Speech | [Async](https://docs.pipecat.ai/server/services/tts/asyncai), [AWS](https://docs.pipecat.ai/server/services/tts/aws), [Azure](https://docs.pipecat.ai/server/services/tts/azure), [Camb AI](https://docs.pipecat.ai/server/services/tts/camb), [Cartesia](https://docs.pipecat.ai/server/services/tts/cartesia), [Deepgram](https://docs.pipecat.ai/server/services/tts/deepgram), [ElevenLabs](https://docs.pipecat.ai/server/services/tts/elevenlabs), [Fish](https://docs.pipecat.ai/server/services/tts/fish), [Google](https://docs.pipecat.ai/server/services/tts/google), [Gradium](https://docs.pipecat.ai/server/services/tts/gradium), [Groq](https://docs.pipecat.ai/server/services/tts/groq), [Hathora](https://docs.pipecat.ai/server/services/tts/hathora), [Hume](https://docs.pipecat.ai/server/services/tts/hume), [Inworld](https://docs.pipecat.ai/server/services/tts/inworld), [LMNT](https://docs.pipecat.ai/server/services/tts/lmnt), [MiniMax](https://docs.pipecat.ai/server/services/tts/minimax), [Neuphonic](https://docs.pipecat.ai/server/services/tts/neuphonic), [NVIDIA Riva](https://docs.pipecat.ai/server/services/tts/riva), [OpenAI](https://docs.pipecat.ai/server/services/tts/openai), [Piper](https://docs.pipecat.ai/server/services/tts/piper), [PlayHT](https://docs.pipecat.ai/server/services/tts/playht), [Rime](https://docs.pipecat.ai/server/services/tts/rime), [Sarvam](https://docs.pipecat.ai/server/services/tts/sarvam), [Speechmatics](https://docs.pipecat.ai/server/services/tts/speechmatics), [XTTS](https://docs.pipecat.ai/server/services/tts/xtts) | | Speech-to-Speech | [AWS Nova Sonic](https://docs.pipecat.ai/server/services/s2s/aws), [Gemini Multimodal Live](https://docs.pipecat.ai/server/services/s2s/gemini), [Grok Voice Agent](https://docs.pipecat.ai/server/services/s2s/grok), [OpenAI Realtime](https://docs.pipecat.ai/server/services/s2s/openai), [Ultravox](https://docs.pipecat.ai/server/services/s2s/ultravox), | | Transport | [Daily (WebRTC)](https://docs.pipecat.ai/server/services/transport/daily), [FastAPI Websocket](https://docs.pipecat.ai/server/services/transport/fastapi-websocket), [SmallWebRTCTransport](https://docs.pipecat.ai/server/services/transport/small-webrtc), [WebSocket Server](https://docs.pipecat.ai/server/services/transport/websocket-server), Local | | Serializers | [Exotel](https://docs.pipecat.ai/server/utilities/serializers/exotel), [Plivo](https://docs.pipecat.ai/server/utilities/serializers/plivo), [Twilio](https://docs.pipecat.ai/server/utilities/serializers/twilio), [Telnyx](https://docs.pipecat.ai/server/utilities/serializers/telnyx), [Vonage](https://docs.pipecat.ai/server/utilities/serializers/vonage) | diff --git a/changelog/3169.added.md b/changelog/3169.added.md new file mode 100644 index 000000000..d9e4bb9b9 --- /dev/null +++ b/changelog/3169.added.md @@ -0,0 +1 @@ +- Added Hathora service to support Hathora-hosted TTS and STT models (only non-streaming) \ No newline at end of file diff --git a/env.example b/env.example index 41badb571..c7b734ad6 100644 --- a/env.example +++ b/env.example @@ -85,6 +85,9 @@ GROK_API_KEY=... # Groq GROQ_API_KEY=... +# Hathora +HATHORA_API_KEY=... + # Heygen HEYGEN_API_KEY=... HEYGEN_LIVE_AVATAR_API_KEY=... diff --git a/examples/foundational/07af-interruptible-hathora.py b/examples/foundational/07ag-interruptible-hathora.py similarity index 80% rename from examples/foundational/07af-interruptible-hathora.py rename to examples/foundational/07ag-interruptible-hathora.py index 5a06b7bf0..bcde037d0 100644 --- a/examples/foundational/07af-interruptible-hathora.py +++ b/examples/foundational/07ag-interruptible-hathora.py @@ -21,8 +21,8 @@ from pipecat.processors.aggregators.llm_context import LLMContext from pipecat.processors.aggregators.llm_response_universal import LLMContextAggregatorPair from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport -from pipecat.services.hathora.stt import ParakeetSTTService -from pipecat.services.hathora.tts import ChatterboxTTSService, KokoroTTSService +from pipecat.services.hathora.stt import HathoraSTTService +from pipecat.services.hathora.tts import HathoraTTSService from pipecat.services.openai.llm import OpenAILLMService from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams @@ -38,13 +38,19 @@ transport_params = { audio_in_enabled=True, audio_out_enabled=True, vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), - turn_analyzer=LocalSmartTurnAnalyzerV3(), + turn_analyzer=LocalSmartTurnAnalyzerV3(params=SmartTurnParams()), + ), + "twilio": lambda: FastAPIWebsocketParams( + audio_in_enabled=True, + audio_out_enabled=True, + vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), + turn_analyzer=LocalSmartTurnAnalyzerV3(params=SmartTurnParams()), ), "webrtc": lambda: TransportParams( audio_in_enabled=True, audio_out_enabled=True, vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), - turn_analyzer=LocalSmartTurnAnalyzerV3(), + turn_analyzer=LocalSmartTurnAnalyzerV3(params=SmartTurnParams()), ), } @@ -52,24 +58,14 @@ transport_params = { async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): logger.info(f"Starting bot") - # See https://models.hathora.dev/model/nvidia-parakeet-tdt-0.6b-v3 - stt = ParakeetTDTSTTService( - base_url="https://app-1c7bebb9-6977-4101-9619-833b251b86d1.app.hathora.dev/v1/transcribe", - api_key=os.getenv("HATHORA_API_KEY") + stt = HathoraSTTService( + model="nvidia-parakeet-tdt-0.6b-v3", ) - # See https://models.hathora.dev/model/hexgrad-kokoro-82m - tts = KokoroTTSService( - base_url="https://app-01312daf-6e53-4b9d-a4ad-13039f35adc4.app.hathora.dev/synthesize", - api_key=os.getenv("HATHORA_API_KEY"), + tts = HathoraTTSService( + model="hexgrad-kokoro-82m", ) - # See https://models.hathora.dev/model/resemble-ai-chatterbox - # tts = ChatterboxTTSService( - # base_url="https://app-efbc8fe2-df55-4f96-bbe3-74f6ea9d986b.app.hathora.dev/v1/generate", - # api_key=os.getenv("HATHORA_API_KEY") - # ) - # See https://models.hathora.dev/model/qwen3-30b-a3b llm = OpenAILLMService( base_url="https://app-362f7ca1-6975-4e18-a605-ab202bf2c315.app.hathora.dev/v1", diff --git a/src/pipecat/services/hathora/__init__.py b/src/pipecat/services/hathora/__init__.py index 11b7dbb55..e69de29bb 100644 --- a/src/pipecat/services/hathora/__init__.py +++ b/src/pipecat/services/hathora/__init__.py @@ -1,14 +0,0 @@ -# -# Copyright (c) 2024–2025, Daily -# -# SPDX-License-Identifier: BSD 2-Clause License -# - -import sys - -from pipecat.services import DeprecatedModuleProxy - -from .stt import * -from .tts import * - -sys.modules[__name__] = DeprecatedModuleProxy(globals(), "hathora", "hathora.[stt,tts]") diff --git a/src/pipecat/services/hathora/stt.py b/src/pipecat/services/hathora/stt.py index ef4b209af..010f38683 100644 --- a/src/pipecat/services/hathora/stt.py +++ b/src/pipecat/services/hathora/stt.py @@ -6,102 +6,126 @@ """[Hathora-hosted](https://models.hathora.dev) speech-to-text services.""" +import base64 import os -from typing import Optional +from typing import AsyncGenerator, Optional import aiohttp -from loguru import logger from pipecat.frames.frames import ( ErrorFrame, + Frame, TranscriptionFrame, ) from pipecat.services.stt_service import SegmentedSTTService from pipecat.transcriptions.language import Language from pipecat.utils.time import time_now_iso8601 +from pipecat.utils.tracing.service_decorators import traced_stt -class ParakeetTDTSTTService(SegmentedSTTService): - """Parakeet TDT is a multilingual automatic speech recognition model - with word-level timestamps. +from .utils import ConfigOption - This service uses the Hathora-hosted Parakeet model via the HTTP API. - [Documentation](https://models.hathora.dev/model/nvidia-parakeet-tdt-0.6b-v3) +class HathoraSTTService(SegmentedSTTService): + """This service supports several different speech-to-text models hosted by Hathora. + + [Documentation](https://models.hathora.dev) """ def __init__( self, *, - base_url = None, - api_key = None, - start_time: Optional[int] = None, - end_time: Optional[int] = None, + model: str, + language: Optional[str] = None, + model_config: Optional[list[ConfigOption]] = None, + base_url: str = "https://api.models.hathora.dev/inference/v1/stt", + api_key: Optional[str] = None, **kwargs, ): - """Initialize the Hathora-hosted Parakeet STT service. + """Initialize the Hathora STT service. Args: - base_url: Base URL for the Hathora Parakeet STT API. + model: Model to use; find available models + [here](https://models.hathora.dev). + language: Language code (if supported by model). + model_config: Some models support additional config, refer to + [docs](https://models.hathora.dev) for each model to see + what is supported. + base_url: Base API URL for the Hathora STT service. api_key: API key for authentication with the Hathora service; - provisiion one [here](https://models.hathora.dev/tokens). - start_time: Start time in seconds for the time window. - end_time: End time in seconds for the time window. + provision one [here](https://models.hathora.dev/tokens). + **kwargs: Additional arguments passed to the parent class. """ super().__init__( **kwargs, ) + self._model = model + self._language = language + self._model_config = model_config self._base_url = base_url - self._api_key = api_key - self._start_time = start_time - self._end_time = end_time + self._api_key = api_key or os.getenv("HATHORA_API_KEY") - def can_generate_metrics(self) -> bool: - return True + @traced_stt + async def _handle_transcription( + self, transcript: str, is_final: bool, language: Optional[Language] = None + ): + """Handle a transcription result with tracing.""" + pass - async def run_stt(self, audio: bytes): + @traced_stt + async def run_stt(self, audio: bytes) -> AsyncGenerator[Frame, None]: + """Run speech-to-text on the provided audio data. + + Args: + audio: Raw audio bytes to transcribe. + + Yields: + Frame: Frames containing transcription results (typically TextFrame). + """ try: await self.start_processing_metrics() await self.start_ttfb_metrics() url = f"{self._base_url}" - url_query_params = [] - if self._start_time is not None: - url_query_params.append(f"start_time={self._start_time}") - if self._end_time is not None: - url_query_params.append(f"end_time={self._end_time}") - url_query_params.append(f"sample_rate={self.sample_rate}") + payload = { + "model": self._model, + } - if len(url_query_params) > 0: - url += "?" + "&".join(url_query_params) + if self._language is not None: + payload["language"] = self._language + if self._model_config is not None: + payload["model_config"] = [ + {"name": option.name, "value": option.value} for option in self._model_config + ] - api_key = self._api_key or os.getenv("HATHORA_API_KEY") - - form_data = aiohttp.FormData() - form_data.add_field("file", audio, filename="audio.wav", content_type="application/octet-stream") + base64_audio = base64.b64encode(audio).decode("utf-8") + payload["audio"] = base64_audio async with aiohttp.ClientSession() as session: async with session.post( url, - headers={"Authorization": f"Bearer {api_key}"}, - data=form_data, + headers={"Authorization": f"Bearer {self._api_key}"}, + json=payload, ) as resp: response = await resp.json() if response and "text" in response: text = response["text"].strip() if text: # Only yield non-empty text - await self.stop_ttfb_metrics() - await self.stop_processing_metrics() - logger.debug(f"Transcription: [{text}]") + # Hathora's API currently doesn't return language info + # so we default to the requested language or "en" + response_language = self._language or "en" + await self._handle_transcription(text, True, response_language) yield TranscriptionFrame( text, self._user_id, time_now_iso8601(), - Language("en"), # TODO: the parakeet hathora API doesn't accept a language but says it's multilingual + Language(response_language), result=response, ) + await self.stop_ttfb_metrics() + await self.stop_processing_metrics() + except Exception as e: - logger.error(f"Hathora error: {e}") - yield ErrorFrame(f"Hathora error: {str(e)}") + yield ErrorFrame(error=f"Unknown error occurred: {e}") diff --git a/src/pipecat/services/hathora/tts.py b/src/pipecat/services/hathora/tts.py index d9ec78793..85843923d 100644 --- a/src/pipecat/services/hathora/tts.py +++ b/src/pipecat/services/hathora/tts.py @@ -9,18 +9,22 @@ import io import os import wave -from typing import Optional, Tuple +from typing import AsyncGenerator, Optional, Tuple import aiohttp -from loguru import logger from pipecat.frames.frames import ( ErrorFrame, + Frame, TTSAudioRawFrame, TTSStartedFrame, TTSStoppedFrame, ) from pipecat.services.tts_service import TTSService +from pipecat.utils.tracing.service_decorators import traced_tts + +from .utils import ConfigOption + def _decode_audio_payload( audio_bytes: bytes, @@ -29,7 +33,6 @@ def _decode_audio_payload( fallback_channels: int = 1, ) -> Tuple[bytes, int, int]: """Convert a WAV/PCM payload into raw PCM samples for TTSAudioRawFrame.""" - try: with wave.open(io.BytesIO(audio_bytes), "rb") as wav_reader: channels = wav_reader.getnchannels() @@ -40,69 +43,82 @@ def _decode_audio_payload( # If the payload is already raw PCM, just pass it through. return audio_bytes, fallback_sample_rate, fallback_channels -class KokoroTTSService(TTSService): - """Kokoro is an open-weight TTS model with 82 million parameters. - This service uses the Hathora-hosted Kokoro model via the HTTP API. +class HathoraTTSService(TTSService): + """This service supports several different text-to-speech models hosted by Hathora. - [Documentation](https://models.hathora.dev/model/hexgrad-kokoro-82m) + [Documentation](https://models.hathora.dev) """ def __init__( self, *, - base_url = None, - api_key = None, + model: str, voice: Optional[str] = None, speed: Optional[float] = None, + model_config: Optional[list[ConfigOption]] = None, + base_url: str = "https://api.models.hathora.dev/inference/v1/tts", + api_key: Optional[str] = None, **kwargs, ): - """Initialize the Hathora-hosted Kokoro TTS service. + """Initialize the Hathora TTS service. Args: - base_url: Base URL for the Hathora Kokoro TTS API, . + model: Model to use; find available models + [here](https://models.hathora.dev). + voice: Voice to use for synthesis (if supported by model). + speed: Speech speed multiplier (if supported by model). + model_config: Some models support additional config, refer to + [docs](https://models.hathora.dev) for each model to see + what is supported. + base_url: Base API URL for the Hathora TTS service. api_key: API key for authentication with the Hathora service; - provisiion one [here](https://models.hathora.dev/tokens). - voice: Voice to use for synthesis (see the - [Hathora docs](https://models.hathora.dev/model/hexgrad-kokoro-82m) - for the default value; [list of voices](https://huggingface.co/hexgrad/Kokoro-82M/blob/main/VOICES.md)). - speed: Speech speed multiplier (0.5 = half speed, 2.0 = double speed, default: 1). + provision one [here](https://models.hathora.dev/tokens). + **kwargs: Additional arguments passed to the parent class. """ super().__init__( **kwargs, ) - self._base_url = base_url - self._api_key = api_key + self._model = model self._voice = voice self._speed = speed + self._model_config = model_config + self._base_url = base_url + self._api_key = api_key or os.getenv("HATHORA_API_KEY") - def can_generate_metrics(self) -> bool: - return True + @traced_tts + async def run_tts(self, text: str) -> AsyncGenerator[Frame, None]: + """Run text-to-speech synthesis on the provided text. - async def run_tts(self, text: str): + Args: + text: The text to synthesize into speech. + + Yields: + Frame: Audio frames containing the synthesized speech. + """ try: await self.start_processing_metrics() await self.start_ttfb_metrics() url = f"{self._base_url}" - api_key = self._api_key or os.getenv("HATHORA_API_KEY") - - payload = { - "text": text - } + payload = {"model": self._model, "text": text} if self._voice is not None: payload["voice"] = self._voice if self._speed is not None: payload["speed"] = self._speed + if self._model_config is not None: + payload["model_config"] = [ + {"name": option.name, "value": option.value} for option in self._model_config + ] yield TTSStartedFrame() async with aiohttp.ClientSession() as session: async with session.post( url, - headers={"Authorization": f"Bearer {api_key}", "Accept": "application/octet-stream"}, + headers={"Authorization": f"Bearer {self._api_key}"}, json=payload, ) as resp: audio_data = await resp.read() @@ -112,8 +128,6 @@ class KokoroTTSService(TTSService): fallback_sample_rate=self.sample_rate or self._init_sample_rate or 24000, ) - await self.stop_ttfb_metrics() - frame = TTSAudioRawFrame( audio=pcm_audio, sample_rate=sample_rate, @@ -123,107 +137,8 @@ class KokoroTTSService(TTSService): yield frame except Exception as e: - logger.error(f"Hathora error: {e}") - yield ErrorFrame(f"Hathora error: {str(e)}") + yield ErrorFrame(error=f"Unknown error occurred: {e}") finally: await self.stop_ttfb_metrics() await self.stop_processing_metrics() yield TTSStoppedFrame() - -class ChatterboxTTSService(TTSService): - """Chatterbox is a public text-to-speech model optimized for natural and expressive voice synthesis. - - This service uses the Hathora-hosted Chatterbox model via the HTTP API. - - [Documentation](https://models.hathora.dev/model/resemble-ai-chatterbox) - """ - - def __init__( - self, - *, - base_url = None, - api_key = None, - exaggeration: Optional[float] = None, - audio_prompt: Optional[bytes] = None, - cfg_weight: Optional[float] = None, - **kwargs, - ): - """Initialize the Hathora-hosted Chatterbox TTS service. - - Args: - base_url: Base URL for the Hathora Chatterbox TTS API. - api_key: API key for authentication with the Hathora service; - provisiion one [here](https://models.hathora.dev/tokens). - exaggeration: Controls emotional intensity (default: 0.5). - audio_prompt: Reference audio file for voice cloning. - cfg_weight: Controls adherence to reference voice (default: 0.5). - """ - - super().__init__( - **kwargs, - ) - self._base_url = base_url - self._api_key = api_key - self._exaggeration = exaggeration - self._audio_prompt = audio_prompt - self._cfg_weight = cfg_weight - - def can_generate_metrics(self) -> bool: - return True - - async def run_tts(self, text: str): - try: - await self.start_ttfb_metrics() - - url = f"{self._base_url}" - - url_query_params = [] - if self._exaggeration is not None: - url_query_params.append(f"exaggeration={self._exaggeration}") - if self._cfg_weight is not None: - url_query_params.append(f"cfg_weight={self._cfg_weight}") - - if len(url_query_params) > 0: - url += "?" + "&".join(url_query_params) - - api_key = self._api_key or os.getenv("HATHORA_API_KEY") - - form_data = aiohttp.FormData() - form_data.add_field("text", text) - - if self._audio_prompt is not None: - form_data.add_field("audio_prompt", self._audio_prompt, filename="audio.wav", content_type="application/octet-stream") - - yield TTSStartedFrame() - - async with aiohttp.ClientSession() as session: - async with session.post( - url, - headers={"Authorization": f"Bearer {api_key}"}, - data=form_data, - ) as resp: - audio_data = await resp.read() - - await self.start_tts_usage_metrics(text) - - pcm_audio, sample_rate, num_channels = _decode_audio_payload( - audio_data, - fallback_sample_rate=self.sample_rate or self._init_sample_rate or 24000, - ) - - await self.stop_ttfb_metrics() - - frame = TTSAudioRawFrame( - audio=pcm_audio, - sample_rate=sample_rate, - num_channels=num_channels, - ) - - yield frame - - except Exception as e: - logger.error(f"Hathora error: {e}") - yield ErrorFrame(f"Hathora error: {str(e)}") - finally: - await self.stop_ttfb_metrics() - yield TTSStoppedFrame() diff --git a/src/pipecat/services/hathora/utils.py b/src/pipecat/services/hathora/utils.py new file mode 100644 index 000000000..6d8eb54b8 --- /dev/null +++ b/src/pipecat/services/hathora/utils.py @@ -0,0 +1,22 @@ +# +# Copyright (c) 2024–2025, Daily +# +# SPDX-License-Identifier: BSD 2-Clause License +# + +"""Utilities and types for [Hathora-hosted](https://models.hathora.dev) voice services.""" + +from dataclasses import dataclass + + +@dataclass +class ConfigOption: + """Extra configuration option passed into model_config for Hathora (if supported by model). + + Args: + name: Name of the configuration option. + value: Value of the configuration option. + """ + + name: str + value: str From e9f1d951d3db9c0550c5b50df331317e049c4f6d Mon Sep 17 00:00:00 2001 From: Mike Seese Date: Mon, 5 Jan 2026 10:16:06 -0800 Subject: [PATCH 0095/1060] Apply suggestions from code review Co-authored-by: Mark Backman --- examples/foundational/07ag-interruptible-hathora.py | 3 +++ src/pipecat/services/hathora/tts.py | 2 +- 2 files changed, 4 insertions(+), 1 deletion(-) diff --git a/examples/foundational/07ag-interruptible-hathora.py b/examples/foundational/07ag-interruptible-hathora.py index bcde037d0..8fc989e62 100644 --- a/examples/foundational/07ag-interruptible-hathora.py +++ b/examples/foundational/07ag-interruptible-hathora.py @@ -100,6 +100,9 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): params=PipelineParams( enable_metrics=True, enable_usage_metrics=True, + turn_start_strategies=TurnStartStrategies( + bot=[TurnAnalyzerBotTurnStartStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3())] + ), ), idle_timeout_secs=runner_args.pipeline_idle_timeout_secs, ) diff --git a/src/pipecat/services/hathora/tts.py b/src/pipecat/services/hathora/tts.py index 85843923d..53458be28 100644 --- a/src/pipecat/services/hathora/tts.py +++ b/src/pipecat/services/hathora/tts.py @@ -54,7 +54,7 @@ class HathoraTTSService(TTSService): self, *, model: str, - voice: Optional[str] = None, + voice_id: Optional[str] = None, speed: Optional[float] = None, model_config: Optional[list[ConfigOption]] = None, base_url: str = "https://api.models.hathora.dev/inference/v1/tts", From bcccb4cbb317a8569b714d6aa1cacaf28650d81a Mon Sep 17 00:00:00 2001 From: Mike Seese Date: Mon, 5 Jan 2026 10:20:26 -0800 Subject: [PATCH 0096/1060] put fallback sample_rate value in function arg --- src/pipecat/services/hathora/tts.py | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/src/pipecat/services/hathora/tts.py b/src/pipecat/services/hathora/tts.py index 53458be28..1b1a4df14 100644 --- a/src/pipecat/services/hathora/tts.py +++ b/src/pipecat/services/hathora/tts.py @@ -29,7 +29,7 @@ from .utils import ConfigOption def _decode_audio_payload( audio_bytes: bytes, *, - fallback_sample_rate: int, + fallback_sample_rate: int = 24000, fallback_channels: int = 1, ) -> Tuple[bytes, int, int]: """Convert a WAV/PCM payload into raw PCM samples for TTSAudioRawFrame.""" @@ -125,7 +125,7 @@ class HathoraTTSService(TTSService): pcm_audio, sample_rate, num_channels = _decode_audio_payload( audio_data, - fallback_sample_rate=self.sample_rate or self._init_sample_rate or 24000, + fallback_sample_rate=self.sample_rate, ) frame = TTSAudioRawFrame( From 7be7fb49a35af1c3de23a25d78090b4f55dc18af Mon Sep 17 00:00:00 2001 From: Mike Seese Date: Mon, 5 Jan 2026 10:20:49 -0800 Subject: [PATCH 0097/1060] remove turn_analyzer args from transport params --- examples/foundational/07ag-interruptible-hathora.py | 3 --- 1 file changed, 3 deletions(-) diff --git a/examples/foundational/07ag-interruptible-hathora.py b/examples/foundational/07ag-interruptible-hathora.py index 8fc989e62..9519937d5 100644 --- a/examples/foundational/07ag-interruptible-hathora.py +++ b/examples/foundational/07ag-interruptible-hathora.py @@ -38,19 +38,16 @@ transport_params = { audio_in_enabled=True, audio_out_enabled=True, vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), - turn_analyzer=LocalSmartTurnAnalyzerV3(params=SmartTurnParams()), ), "twilio": lambda: FastAPIWebsocketParams( audio_in_enabled=True, audio_out_enabled=True, vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), - turn_analyzer=LocalSmartTurnAnalyzerV3(params=SmartTurnParams()), ), "webrtc": lambda: TransportParams( audio_in_enabled=True, audio_out_enabled=True, vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), - turn_analyzer=LocalSmartTurnAnalyzerV3(params=SmartTurnParams()), ), } From e7c83c19b65e4834a3c3a3642680370cb6ac7615 Mon Sep 17 00:00:00 2001 From: Mike Seese Date: Mon, 5 Jan 2026 10:36:08 -0800 Subject: [PATCH 0098/1060] port turn_start_strategies to the newer user_turn_strategies --- .../07ag-interruptible-hathora.py | 19 ++++++++++++++----- 1 file changed, 14 insertions(+), 5 deletions(-) diff --git a/examples/foundational/07ag-interruptible-hathora.py b/examples/foundational/07ag-interruptible-hathora.py index 9519937d5..9a90efb35 100644 --- a/examples/foundational/07ag-interruptible-hathora.py +++ b/examples/foundational/07ag-interruptible-hathora.py @@ -18,7 +18,10 @@ from pipecat.pipeline.pipeline import Pipeline from pipecat.pipeline.runner import PipelineRunner from pipecat.pipeline.task import PipelineParams, PipelineTask from pipecat.processors.aggregators.llm_context import LLMContext -from pipecat.processors.aggregators.llm_response_universal import LLMContextAggregatorPair +from pipecat.processors.aggregators.llm_response_universal import ( + LLMContextAggregatorPair, + LLMUserAggregatorParams, +) from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport from pipecat.services.hathora.stt import HathoraSTTService @@ -27,6 +30,8 @@ from pipecat.services.openai.llm import OpenAILLMService from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams +from pipecat.turns.user_stop import TurnAnalyzerUserTurnStopStrategy +from pipecat.turns.user_turn_strategies import UserTurnStrategies load_dotenv(override=True) @@ -78,7 +83,14 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): ] context = LLMContext(messages) - context_aggregator = LLMContextAggregatorPair(context) + context_aggregator = LLMContextAggregatorPair( + context, + user_params=LLMUserAggregatorParams( + user_turn_strategies=UserTurnStrategies( + stop=[TurnAnalyzerUserTurnStopStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3())] + ), + ), + ) pipeline = Pipeline( [ @@ -97,9 +109,6 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): params=PipelineParams( enable_metrics=True, enable_usage_metrics=True, - turn_start_strategies=TurnStartStrategies( - bot=[TurnAnalyzerBotTurnStartStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3())] - ), ), idle_timeout_secs=runner_args.pipeline_idle_timeout_secs, ) From ba25b279d689e2f2753b841ca49f12e3be1213d5 Mon Sep 17 00:00:00 2001 From: Mike Seese Date: Mon, 5 Jan 2026 10:38:11 -0800 Subject: [PATCH 0099/1060] fix issues with PR suggestions --- src/pipecat/services/hathora/tts.py | 3 +-- 1 file changed, 1 insertion(+), 2 deletions(-) diff --git a/src/pipecat/services/hathora/tts.py b/src/pipecat/services/hathora/tts.py index 1b1a4df14..2a82c7dbc 100644 --- a/src/pipecat/services/hathora/tts.py +++ b/src/pipecat/services/hathora/tts.py @@ -78,15 +78,14 @@ class HathoraTTSService(TTSService): """ super().__init__( **kwargs, + voice_id=voice_id, ) self._model = model - self._voice = voice self._speed = speed self._model_config = model_config self._base_url = base_url self._api_key = api_key or os.getenv("HATHORA_API_KEY") - @traced_tts async def run_tts(self, text: str) -> AsyncGenerator[Frame, None]: """Run text-to-speech synthesis on the provided text. From 6c7e38639197263627d9e3c4e739b201bec0c047 Mon Sep 17 00:00:00 2001 From: Mike Seese Date: Mon, 5 Jan 2026 10:48:55 -0800 Subject: [PATCH 0100/1060] remove traced_stt from run_stt --- src/pipecat/services/hathora/stt.py | 1 - 1 file changed, 1 deletion(-) diff --git a/src/pipecat/services/hathora/stt.py b/src/pipecat/services/hathora/stt.py index 010f38683..f87f15fdf 100644 --- a/src/pipecat/services/hathora/stt.py +++ b/src/pipecat/services/hathora/stt.py @@ -71,7 +71,6 @@ class HathoraSTTService(SegmentedSTTService): """Handle a transcription result with tracing.""" pass - @traced_stt async def run_stt(self, audio: bytes) -> AsyncGenerator[Frame, None]: """Run speech-to-text on the provided audio data. From 1b3b67779c70fab223d5058109dbe978ae11fdac Mon Sep 17 00:00:00 2001 From: Mike Seese Date: Mon, 5 Jan 2026 10:57:27 -0800 Subject: [PATCH 0101/1060] switch hathora services to use `InputParams` pattern --- src/pipecat/services/hathora/stt.py | 40 ++++++++++++++--------- src/pipecat/services/hathora/tts.py | 50 +++++++++++++++++------------ 2 files changed, 54 insertions(+), 36 deletions(-) diff --git a/src/pipecat/services/hathora/stt.py b/src/pipecat/services/hathora/stt.py index f87f15fdf..a0829b455 100644 --- a/src/pipecat/services/hathora/stt.py +++ b/src/pipecat/services/hathora/stt.py @@ -11,6 +11,7 @@ import os from typing import AsyncGenerator, Optional import aiohttp +from pydantic import BaseModel from pipecat.frames.frames import ( ErrorFrame, @@ -31,14 +32,27 @@ class HathoraSTTService(SegmentedSTTService): [Documentation](https://models.hathora.dev) """ + class InputParams(BaseModel): + """Optional input parameters for Hathora STT configuration. + + Parameters: + language: Language code (if supported by model). + model_config: Some models support additional config, refer to + [docs](https://models.hathora.dev) for each model to see + what is supported. + base_url: Base API URL for the Hathora STT service. + """ + + language: Optional[str] = None + model_config: Optional[list[ConfigOption]] = None + base_url: str = "https://api.models.hathora.dev/inference/v1/stt", + def __init__( self, *, model: str, - language: Optional[str] = None, - model_config: Optional[list[ConfigOption]] = None, - base_url: str = "https://api.models.hathora.dev/inference/v1/stt", api_key: Optional[str] = None, + params: Optional[InputParams] = None, **kwargs, ): """Initialize the Hathora STT service. @@ -46,23 +60,17 @@ class HathoraSTTService(SegmentedSTTService): Args: model: Model to use; find available models [here](https://models.hathora.dev). - language: Language code (if supported by model). - model_config: Some models support additional config, refer to - [docs](https://models.hathora.dev) for each model to see - what is supported. - base_url: Base API URL for the Hathora STT service. api_key: API key for authentication with the Hathora service; provision one [here](https://models.hathora.dev/tokens). + params: Configuration parameters. **kwargs: Additional arguments passed to the parent class. """ super().__init__( **kwargs, ) self._model = model - self._language = language - self._model_config = model_config - self._base_url = base_url self._api_key = api_key or os.getenv("HATHORA_API_KEY") + self._params = params or HathoraSTTService.InputParams() @traced_stt async def _handle_transcription( @@ -84,17 +92,17 @@ class HathoraSTTService(SegmentedSTTService): await self.start_processing_metrics() await self.start_ttfb_metrics() - url = f"{self._base_url}" + url = f"{self._params.base_url}" payload = { "model": self._model, } - if self._language is not None: - payload["language"] = self._language - if self._model_config is not None: + if self._params.language is not None: + payload["language"] = self._params.language + if self._params.model_config is not None: payload["model_config"] = [ - {"name": option.name, "value": option.value} for option in self._model_config + {"name": option.name, "value": option.value} for option in self._params.model_config ] base64_audio = base64.b64encode(audio).decode("utf-8") diff --git a/src/pipecat/services/hathora/tts.py b/src/pipecat/services/hathora/tts.py index 2a82c7dbc..f1d35c9fb 100644 --- a/src/pipecat/services/hathora/tts.py +++ b/src/pipecat/services/hathora/tts.py @@ -12,6 +12,7 @@ import wave from typing import AsyncGenerator, Optional, Tuple import aiohttp +from pydantic import BaseModel from pipecat.frames.frames import ( ErrorFrame, @@ -50,15 +51,28 @@ class HathoraTTSService(TTSService): [Documentation](https://models.hathora.dev) """ + class InputParams(BaseModel): + """Optional input parameters for Hathora TTS configuration. + + Parameters: + speed: Speech speed multiplier (if supported by model). + model_config: Some models support additional config, refer to + [docs](https://models.hathora.dev) for each model to see + what is supported. + base_url: Base API URL for the Hathora TTS service. + """ + + speed: Optional[float] = None + model_config: Optional[list[ConfigOption]] = None + base_url: str = "https://api.models.hathora.dev/inference/v1/tts", + def __init__( self, *, model: str, voice_id: Optional[str] = None, - speed: Optional[float] = None, - model_config: Optional[list[ConfigOption]] = None, - base_url: str = "https://api.models.hathora.dev/inference/v1/tts", api_key: Optional[str] = None, + params: Optional[InputParams] = None, **kwargs, ): """Initialize the Hathora TTS service. @@ -66,26 +80,22 @@ class HathoraTTSService(TTSService): Args: model: Model to use; find available models [here](https://models.hathora.dev). - voice: Voice to use for synthesis (if supported by model). - speed: Speech speed multiplier (if supported by model). - model_config: Some models support additional config, refer to - [docs](https://models.hathora.dev) for each model to see - what is supported. - base_url: Base API URL for the Hathora TTS service. + voice_id: Voice to use for synthesis (if supported by model). api_key: API key for authentication with the Hathora service; provision one [here](https://models.hathora.dev/tokens). + params: Configuration parameters. **kwargs: Additional arguments passed to the parent class. """ super().__init__( **kwargs, - voice_id=voice_id, ) self._model = model - self._speed = speed - self._model_config = model_config - self._base_url = base_url self._api_key = api_key or os.getenv("HATHORA_API_KEY") + self._params = params or HathoraTTSService.InputParams() + self.set_voice(voice_id) + + @traced_tts async def run_tts(self, text: str) -> AsyncGenerator[Frame, None]: """Run text-to-speech synthesis on the provided text. @@ -99,17 +109,17 @@ class HathoraTTSService(TTSService): await self.start_processing_metrics() await self.start_ttfb_metrics() - url = f"{self._base_url}" + url = f"{self._params.base_url}" payload = {"model": self._model, "text": text} - if self._voice is not None: - payload["voice"] = self._voice - if self._speed is not None: - payload["speed"] = self._speed - if self._model_config is not None: + if self._voice_id is not None: + payload["voice"] = self._voice_id + if self._params.speed is not None: + payload["speed"] = self._params.speed + if self._params.model_config is not None: payload["model_config"] = [ - {"name": option.name, "value": option.value} for option in self._model_config + {"name": option.name, "value": option.value} for option in self._params.model_config ] yield TTSStartedFrame() From e77bdf66f9205030c3e9820f05eb24e63424e49d Mon Sep 17 00:00:00 2001 From: Mike Seese Date: Mon, 5 Jan 2026 11:13:48 -0800 Subject: [PATCH 0102/1060] add can_generate_metrics functions --- src/pipecat/services/hathora/stt.py | 8 ++++++++ src/pipecat/services/hathora/tts.py | 8 ++++++++ 2 files changed, 16 insertions(+) diff --git a/src/pipecat/services/hathora/stt.py b/src/pipecat/services/hathora/stt.py index a0829b455..d36923ce4 100644 --- a/src/pipecat/services/hathora/stt.py +++ b/src/pipecat/services/hathora/stt.py @@ -72,6 +72,14 @@ class HathoraSTTService(SegmentedSTTService): self._api_key = api_key or os.getenv("HATHORA_API_KEY") self._params = params or HathoraSTTService.InputParams() + def can_generate_metrics(self) -> bool: + """Check if this service can generate processing metrics. + + Returns: + True + """ + return True + @traced_stt async def _handle_transcription( self, transcript: str, is_final: bool, language: Optional[Language] = None diff --git a/src/pipecat/services/hathora/tts.py b/src/pipecat/services/hathora/tts.py index f1d35c9fb..44bf271a0 100644 --- a/src/pipecat/services/hathora/tts.py +++ b/src/pipecat/services/hathora/tts.py @@ -95,6 +95,14 @@ class HathoraTTSService(TTSService): self.set_voice(voice_id) + def can_generate_metrics(self) -> bool: + """Check if this service can generate processing metrics. + + Returns: + True + """ + return True + @traced_tts async def run_tts(self, text: str) -> AsyncGenerator[Frame, None]: """Run text-to-speech synthesis on the provided text. From 67fdb0b659919fc4d1838c0471d918bbebf69da8 Mon Sep 17 00:00:00 2001 From: Mike Seese Date: Mon, 5 Jan 2026 11:15:43 -0800 Subject: [PATCH 0103/1060] use parent _settings dict instead of self._params pattern --- src/pipecat/services/hathora/stt.py | 23 ++++++++++++++++------- src/pipecat/services/hathora/tts.py | 20 ++++++++++++++------ 2 files changed, 30 insertions(+), 13 deletions(-) diff --git a/src/pipecat/services/hathora/stt.py b/src/pipecat/services/hathora/stt.py index d36923ce4..3f3dee6f7 100644 --- a/src/pipecat/services/hathora/stt.py +++ b/src/pipecat/services/hathora/stt.py @@ -70,7 +70,16 @@ class HathoraSTTService(SegmentedSTTService): ) self._model = model self._api_key = api_key or os.getenv("HATHORA_API_KEY") - self._params = params or HathoraSTTService.InputParams() + self._base_url = params.base_url + + params = params or HathoraSTTService.InputParams() + + self._settings = { + "language": params.language, + "model_config": params.model_config, + } + + self.set_model_name(model) def can_generate_metrics(self) -> bool: """Check if this service can generate processing metrics. @@ -100,17 +109,17 @@ class HathoraSTTService(SegmentedSTTService): await self.start_processing_metrics() await self.start_ttfb_metrics() - url = f"{self._params.base_url}" + url = f"{self._base_url}" payload = { "model": self._model, } - if self._params.language is not None: - payload["language"] = self._params.language - if self._params.model_config is not None: + if self._settings["language"] is not None: + payload["language"] = self._settings["language"] + if self._settings["model_config"] is not None: payload["model_config"] = [ - {"name": option.name, "value": option.value} for option in self._params.model_config + {"name": option.name, "value": option.value} for option in self._settings["model_config"] ] base64_audio = base64.b64encode(audio).decode("utf-8") @@ -129,7 +138,7 @@ class HathoraSTTService(SegmentedSTTService): if text: # Only yield non-empty text # Hathora's API currently doesn't return language info # so we default to the requested language or "en" - response_language = self._language or "en" + response_language = self._settings["language"] or "en" await self._handle_transcription(text, True, response_language) yield TranscriptionFrame( text, diff --git a/src/pipecat/services/hathora/tts.py b/src/pipecat/services/hathora/tts.py index 44bf271a0..efc412d07 100644 --- a/src/pipecat/services/hathora/tts.py +++ b/src/pipecat/services/hathora/tts.py @@ -91,8 +91,16 @@ class HathoraTTSService(TTSService): ) self._model = model self._api_key = api_key or os.getenv("HATHORA_API_KEY") - self._params = params or HathoraTTSService.InputParams() + self._base_url = params.base_url + params = params or HathoraTTSService.InputParams() + + self._settings = { + "speed": params.speed, + "model_config": params.model_config, + } + + self.set_model_name(model) self.set_voice(voice_id) def can_generate_metrics(self) -> bool: @@ -117,17 +125,17 @@ class HathoraTTSService(TTSService): await self.start_processing_metrics() await self.start_ttfb_metrics() - url = f"{self._params.base_url}" + url = f"{self.base_url}" payload = {"model": self._model, "text": text} if self._voice_id is not None: payload["voice"] = self._voice_id - if self._params.speed is not None: - payload["speed"] = self._params.speed - if self._params.model_config is not None: + if self._settings["speed"] is not None: + payload["speed"] = self._settings["speed"] + if self._settings["model_config"] is not None: payload["model_config"] = [ - {"name": option.name, "value": option.value} for option in self._params.model_config + {"name": option.name, "value": option.value} for option in self._settings["model_config"] ] yield TTSStartedFrame() From d2df324f298a02c71892cfdff16a5370081f2b17 Mon Sep 17 00:00:00 2001 From: Mike Seese Date: Mon, 5 Jan 2026 11:49:52 -0800 Subject: [PATCH 0104/1060] fix some bugs after testing changes --- src/pipecat/services/hathora/stt.py | 10 +++++----- src/pipecat/services/hathora/tts.py | 12 ++++++------ 2 files changed, 11 insertions(+), 11 deletions(-) diff --git a/src/pipecat/services/hathora/stt.py b/src/pipecat/services/hathora/stt.py index 3f3dee6f7..0608cb39e 100644 --- a/src/pipecat/services/hathora/stt.py +++ b/src/pipecat/services/hathora/stt.py @@ -37,14 +37,14 @@ class HathoraSTTService(SegmentedSTTService): Parameters: language: Language code (if supported by model). - model_config: Some models support additional config, refer to + config: Some models support additional config, refer to [docs](https://models.hathora.dev) for each model to see what is supported. base_url: Base API URL for the Hathora STT service. """ language: Optional[str] = None - model_config: Optional[list[ConfigOption]] = None + config: Optional[list[ConfigOption]] = None base_url: str = "https://api.models.hathora.dev/inference/v1/stt", def __init__( @@ -76,7 +76,7 @@ class HathoraSTTService(SegmentedSTTService): self._settings = { "language": params.language, - "model_config": params.model_config, + "config": params.config, } self.set_model_name(model) @@ -117,9 +117,9 @@ class HathoraSTTService(SegmentedSTTService): if self._settings["language"] is not None: payload["language"] = self._settings["language"] - if self._settings["model_config"] is not None: + if self._settings["config"] is not None: payload["model_config"] = [ - {"name": option.name, "value": option.value} for option in self._settings["model_config"] + {"name": option.name, "value": option.value} for option in self._settings["config"] ] base64_audio = base64.b64encode(audio).decode("utf-8") diff --git a/src/pipecat/services/hathora/tts.py b/src/pipecat/services/hathora/tts.py index efc412d07..749cb46c8 100644 --- a/src/pipecat/services/hathora/tts.py +++ b/src/pipecat/services/hathora/tts.py @@ -56,14 +56,14 @@ class HathoraTTSService(TTSService): Parameters: speed: Speech speed multiplier (if supported by model). - model_config: Some models support additional config, refer to + config: Some models support additional config, refer to [docs](https://models.hathora.dev) for each model to see what is supported. base_url: Base API URL for the Hathora TTS service. """ speed: Optional[float] = None - model_config: Optional[list[ConfigOption]] = None + config: Optional[list[ConfigOption]] = None base_url: str = "https://api.models.hathora.dev/inference/v1/tts", def __init__( @@ -97,7 +97,7 @@ class HathoraTTSService(TTSService): self._settings = { "speed": params.speed, - "model_config": params.model_config, + "config": params.config, } self.set_model_name(model) @@ -125,7 +125,7 @@ class HathoraTTSService(TTSService): await self.start_processing_metrics() await self.start_ttfb_metrics() - url = f"{self.base_url}" + url = f"{self._base_url}" payload = {"model": self._model, "text": text} @@ -133,9 +133,9 @@ class HathoraTTSService(TTSService): payload["voice"] = self._voice_id if self._settings["speed"] is not None: payload["speed"] = self._settings["speed"] - if self._settings["model_config"] is not None: + if self._settings["config"] is not None: payload["model_config"] = [ - {"name": option.name, "value": option.value} for option in self._settings["model_config"] + {"name": option.name, "value": option.value} for option in self._settings["config"] ] yield TTSStartedFrame() From 2249f3d67322cf73ebac1473136b996c5bd7a920 Mon Sep 17 00:00:00 2001 From: Mike Seese Date: Sat, 10 Jan 2026 15:34:35 -0800 Subject: [PATCH 0105/1060] add requested changes from code review --- examples/foundational/07ag-interruptible-hathora.py | 1 - src/pipecat/services/hathora/stt.py | 10 +++++++--- src/pipecat/services/hathora/tts.py | 11 +++++++---- 3 files changed, 14 insertions(+), 8 deletions(-) diff --git a/examples/foundational/07ag-interruptible-hathora.py b/examples/foundational/07ag-interruptible-hathora.py index 9a90efb35..f4bd169b1 100644 --- a/examples/foundational/07ag-interruptible-hathora.py +++ b/examples/foundational/07ag-interruptible-hathora.py @@ -9,7 +9,6 @@ import os from dotenv import load_dotenv from loguru import logger -from pipecat.audio.turn.smart_turn.base_smart_turn import SmartTurnParams from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3 from pipecat.audio.vad.silero import SileroVADAnalyzer from pipecat.audio.vad.vad_analyzer import VADParams diff --git a/src/pipecat/services/hathora/stt.py b/src/pipecat/services/hathora/stt.py index 0608cb39e..b9de7ac8d 100644 --- a/src/pipecat/services/hathora/stt.py +++ b/src/pipecat/services/hathora/stt.py @@ -40,18 +40,18 @@ class HathoraSTTService(SegmentedSTTService): config: Some models support additional config, refer to [docs](https://models.hathora.dev) for each model to see what is supported. - base_url: Base API URL for the Hathora STT service. """ language: Optional[str] = None config: Optional[list[ConfigOption]] = None - base_url: str = "https://api.models.hathora.dev/inference/v1/stt", def __init__( self, *, model: str, + sample_rate: Optional[int] = None, api_key: Optional[str] = None, + base_url: str = "https://api.models.hathora.dev/inference/v1/stt", params: Optional[InputParams] = None, **kwargs, ): @@ -60,17 +60,21 @@ class HathoraSTTService(SegmentedSTTService): Args: model: Model to use; find available models [here](https://models.hathora.dev). + sample_rate: The sample rate for audio input. If None, will be determined + from the start frame. api_key: API key for authentication with the Hathora service; provision one [here](https://models.hathora.dev/tokens). + base_url: Base API URL for the Hathora STT service. params: Configuration parameters. **kwargs: Additional arguments passed to the parent class. """ super().__init__( + sample_rate=sample_rate, **kwargs, ) self._model = model self._api_key = api_key or os.getenv("HATHORA_API_KEY") - self._base_url = params.base_url + self._base_url = base_url params = params or HathoraSTTService.InputParams() diff --git a/src/pipecat/services/hathora/tts.py b/src/pipecat/services/hathora/tts.py index 749cb46c8..43c1cfeca 100644 --- a/src/pipecat/services/hathora/tts.py +++ b/src/pipecat/services/hathora/tts.py @@ -59,19 +59,19 @@ class HathoraTTSService(TTSService): config: Some models support additional config, refer to [docs](https://models.hathora.dev) for each model to see what is supported. - base_url: Base API URL for the Hathora TTS service. """ speed: Optional[float] = None config: Optional[list[ConfigOption]] = None - base_url: str = "https://api.models.hathora.dev/inference/v1/tts", def __init__( self, *, model: str, voice_id: Optional[str] = None, + sample_rate: Optional[int] = None, api_key: Optional[str] = None, + base_url: str = "https://api.models.hathora.dev/inference/v1/tts", params: Optional[InputParams] = None, **kwargs, ): @@ -81,17 +81,20 @@ class HathoraTTSService(TTSService): model: Model to use; find available models [here](https://models.hathora.dev). voice_id: Voice to use for synthesis (if supported by model). + sample_rate: Output sample rate for generated audio. api_key: API key for authentication with the Hathora service; provision one [here](https://models.hathora.dev/tokens). + base_url: Base API URL for the Hathora TTS service. params: Configuration parameters. **kwargs: Additional arguments passed to the parent class. """ super().__init__( + sample_rate=sample_rate, **kwargs, ) self._model = model self._api_key = api_key or os.getenv("HATHORA_API_KEY") - self._base_url = params.base_url + self._base_url = base_url params = params or HathoraTTSService.InputParams() @@ -155,7 +158,7 @@ class HathoraTTSService(TTSService): frame = TTSAudioRawFrame( audio=pcm_audio, - sample_rate=sample_rate, + sample_rate=self.sample_rate, num_channels=num_channels, ) From ec4069685498f096cb31a931ae6bbb5ab100784d Mon Sep 17 00:00:00 2001 From: Mark Backman Date: Thu, 15 Jan 2026 19:16:15 -0500 Subject: [PATCH 0106/1060] Revert pydantic 2.12 extra type annotation --- src/pipecat/services/openai/realtime/events.py | 1 - src/pipecat/services/openai_realtime_beta/events.py | 1 - src/pipecat/transports/daily/utils.py | 3 --- 3 files changed, 5 deletions(-) diff --git a/src/pipecat/services/openai/realtime/events.py b/src/pipecat/services/openai/realtime/events.py index 78faff45d..0aa1355e6 100644 --- a/src/pipecat/services/openai/realtime/events.py +++ b/src/pipecat/services/openai/realtime/events.py @@ -1003,7 +1003,6 @@ class TokenDetails(BaseModel): """ model_config = ConfigDict(extra="allow") - __pydantic_extra__: dict[str, Any] cached_tokens: Optional[int] = 0 text_tokens: Optional[int] = 0 diff --git a/src/pipecat/services/openai_realtime_beta/events.py b/src/pipecat/services/openai_realtime_beta/events.py index ea4e738c2..596a11a3b 100644 --- a/src/pipecat/services/openai_realtime_beta/events.py +++ b/src/pipecat/services/openai_realtime_beta/events.py @@ -878,7 +878,6 @@ class TokenDetails(BaseModel): """ model_config = ConfigDict(extra="allow") - __pydantic_extra__: dict[str, Any] cached_tokens: Optional[int] = 0 text_tokens: Optional[int] = 0 diff --git a/src/pipecat/transports/daily/utils.py b/src/pipecat/transports/daily/utils.py index 9ea02e203..e5bbca8c7 100644 --- a/src/pipecat/transports/daily/utils.py +++ b/src/pipecat/transports/daily/utils.py @@ -102,9 +102,6 @@ class DailyRoomProperties(BaseModel): model_config = ConfigDict(extra="allow") - # Pydantic v2.12+ requires explicit annotation for extra fields - __pydantic_extra__: dict[str, Any] - exp: Optional[float] = None enable_chat: bool = False enable_prejoin_ui: bool = False From 37914cb0624123f15f0125c7930d96913bb56536 Mon Sep 17 00:00:00 2001 From: Glenn Powell Date: Thu, 15 Jan 2026 16:47:15 -0800 Subject: [PATCH 0107/1060] Removed import and added changelog entry. --- changelog/3461.added.md | 1 + src/pipecat/transports/websocket/client.py | 1 - 2 files changed, 1 insertion(+), 1 deletion(-) create mode 100644 changelog/3461.added.md diff --git a/changelog/3461.added.md b/changelog/3461.added.md new file mode 100644 index 000000000..e0bc27d83 --- /dev/null +++ b/changelog/3461.added.md @@ -0,0 +1 @@ +- Added the `additional_headers` param to `WebsocketClientParams`, allowing `WebsocketClientTransport` to send custom headers on connect, for cases such as authentication. diff --git a/src/pipecat/transports/websocket/client.py b/src/pipecat/transports/websocket/client.py index d68038f74..02c891c54 100644 --- a/src/pipecat/transports/websocket/client.py +++ b/src/pipecat/transports/websocket/client.py @@ -20,7 +20,6 @@ from typing import Awaitable, Callable, Optional import websockets from loguru import logger from pydantic.main import BaseModel -from websockets import HeadersLike from websockets.asyncio.client import connect as websocket_connect from pipecat.frames.frames import ( From 63d1393bb02b612ba7ad8bf28c3c0ba8627ef3e4 Mon Sep 17 00:00:00 2001 From: Mark Backman Date: Thu, 15 Jan 2026 20:06:49 -0500 Subject: [PATCH 0108/1060] Add whisker_setup.py to .gitignore --- .gitignore | 5 ++++- 1 file changed, 4 insertions(+), 1 deletion(-) diff --git a/.gitignore b/.gitignore index 2e5da188e..426f9be3a 100644 --- a/.gitignore +++ b/.gitignore @@ -51,4 +51,7 @@ docs/api/_build/ docs/api/api # uv -.python-version \ No newline at end of file +.python-version + +# Pipecat +whisker_setup.py \ No newline at end of file From 11ecc5fdeee493ec583a7cd070a3ef2e3449ab2e Mon Sep 17 00:00:00 2001 From: Mark Backman Date: Fri, 16 Jan 2026 12:48:13 -0500 Subject: [PATCH 0109/1060] Update project.urls for PyPI --- pyproject.toml | 5 ++++- 1 file changed, 4 insertions(+), 1 deletion(-) diff --git a/pyproject.toml b/pyproject.toml index 4dc92b879..e99ab62bc 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -41,8 +41,11 @@ dependencies = [ ] [project.urls] +Homepage = "https://pipecat.ai" +Documentation = "https://docs.pipecat.ai/" Source = "https://github.com/pipecat-ai/pipecat" -Website = "https://pipecat.ai" +Issues = "https://github.com/pipecat-ai/pipecat/issues" +Changelog = "https://github.com/pipecat-ai/pipecat/blob/main/CHANGELOG.md" [project.optional-dependencies] aic = [ "aic-sdk~=1.2.0" ] From c7ab87b0cc6f8122b0e691d38af388a9bcff04c8 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Aleix=20Conchillo=20Flaqu=C3=A9?= Date: Fri, 16 Jan 2026 10:52:23 -0800 Subject: [PATCH 0110/1060] turns: move mute to user_mute --- changelog/3479.deprecated.md | 1 + .../foundational/24-user-mute-strategy.py | 2 +- .../aggregators/llm_response_universal.py | 2 +- src/pipecat/turns/mute/__init__.py | 21 +++++++++++---- src/pipecat/turns/user_mute/__init__.py | 21 +++++++++++++++ .../always_user_mute_strategy.py | 2 +- .../base_user_mute_strategy.py | 0 .../first_speech_user_mute_strategy.py | 2 +- .../function_call_user_mute_strategy.py | 2 +- ...l_first_bot_complete_user_mute_strategy.py | 2 +- src/pipecat/turns/user_start/__init__.py | 26 ++++++++++--------- src/pipecat/turns/user_stop/__init__.py | 23 ++++++++-------- tests/test_context_aggregators_universal.py | 2 +- tests/test_user_mute_strategy.py | 2 +- 14 files changed, 72 insertions(+), 36 deletions(-) create mode 100644 changelog/3479.deprecated.md create mode 100644 src/pipecat/turns/user_mute/__init__.py rename src/pipecat/turns/{mute => user_mute}/always_user_mute_strategy.py (93%) rename src/pipecat/turns/{mute => user_mute}/base_user_mute_strategy.py (100%) rename src/pipecat/turns/{mute => user_mute}/first_speech_user_mute_strategy.py (96%) rename src/pipecat/turns/{mute => user_mute}/function_call_user_mute_strategy.py (95%) rename src/pipecat/turns/{mute => user_mute}/mute_until_first_bot_complete_user_mute_strategy.py (95%) diff --git a/changelog/3479.deprecated.md b/changelog/3479.deprecated.md new file mode 100644 index 000000000..7c58a9d89 --- /dev/null +++ b/changelog/3479.deprecated.md @@ -0,0 +1 @@ +- For consistency with other package names, we just deprecated `pipecat.turns.mute` (introduced in Pipecat 0.0.99) in favor of `pipecat.turns.user_mute`. diff --git a/examples/foundational/24-user-mute-strategy.py b/examples/foundational/24-user-mute-strategy.py index df6619fd4..00e1ff66a 100644 --- a/examples/foundational/24-user-mute-strategy.py +++ b/examples/foundational/24-user-mute-strategy.py @@ -34,7 +34,7 @@ from pipecat.services.openai.llm import OpenAILLMService from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams -from pipecat.turns.mute import ( +from pipecat.turns.user_mute import ( FunctionCallUserMuteStrategy, MuteUntilFirstBotCompleteUserMuteStrategy, ) diff --git a/src/pipecat/processors/aggregators/llm_response_universal.py b/src/pipecat/processors/aggregators/llm_response_universal.py index 2854c8681..26c388fe6 100644 --- a/src/pipecat/processors/aggregators/llm_response_universal.py +++ b/src/pipecat/processors/aggregators/llm_response_universal.py @@ -62,7 +62,7 @@ from pipecat.processors.aggregators.llm_context import ( NotGiven, ) from pipecat.processors.frame_processor import FrameDirection, FrameProcessor -from pipecat.turns.mute import BaseUserMuteStrategy +from pipecat.turns.user_mute import BaseUserMuteStrategy from pipecat.turns.user_start import BaseUserTurnStartStrategy, UserTurnStartedParams from pipecat.turns.user_stop import BaseUserTurnStopStrategy, UserTurnStoppedParams from pipecat.turns.user_turn_controller import UserTurnController diff --git a/src/pipecat/turns/mute/__init__.py b/src/pipecat/turns/mute/__init__.py index d452ce19e..02b66688f 100644 --- a/src/pipecat/turns/mute/__init__.py +++ b/src/pipecat/turns/mute/__init__.py @@ -4,10 +4,21 @@ # SPDX-License-Identifier: BSD 2-Clause License # -from pipecat.turns.mute.always_user_mute_strategy import AlwaysUserMuteStrategy -from pipecat.turns.mute.base_user_mute_strategy import BaseUserMuteStrategy -from pipecat.turns.mute.first_speech_user_mute_strategy import FirstSpeechUserMuteStrategy -from pipecat.turns.mute.function_call_user_mute_strategy import FunctionCallUserMuteStrategy -from pipecat.turns.mute.mute_until_first_bot_complete_user_mute_strategy import ( +import warnings + +from pipecat.turns.user_mute.always_user_mute_strategy import AlwaysUserMuteStrategy +from pipecat.turns.user_mute.base_user_mute_strategy import BaseUserMuteStrategy +from pipecat.turns.user_mute.first_speech_user_mute_strategy import FirstSpeechUserMuteStrategy +from pipecat.turns.user_mute.function_call_user_mute_strategy import FunctionCallUserMuteStrategy +from pipecat.turns.user_mute.mute_until_first_bot_complete_user_mute_strategy import ( MuteUntilFirstBotCompleteUserMuteStrategy, ) + +with warnings.catch_warnings(): + warnings.simplefilter("always") + warnings.warn( + "Types in pipecat.turns.mute are deprecated. " + "Please use the equivalent types from pipecat.turns.user_mute instead.", + DeprecationWarning, + stacklevel=2, + ) diff --git a/src/pipecat/turns/user_mute/__init__.py b/src/pipecat/turns/user_mute/__init__.py new file mode 100644 index 000000000..14c5fea42 --- /dev/null +++ b/src/pipecat/turns/user_mute/__init__.py @@ -0,0 +1,21 @@ +# +# Copyright (c) 2024-2026, Daily +# +# SPDX-License-Identifier: BSD 2-Clause License +# + +from .always_user_mute_strategy import AlwaysUserMuteStrategy +from .base_user_mute_strategy import BaseUserMuteStrategy +from .first_speech_user_mute_strategy import FirstSpeechUserMuteStrategy +from .function_call_user_mute_strategy import FunctionCallUserMuteStrategy +from .mute_until_first_bot_complete_user_mute_strategy import ( + MuteUntilFirstBotCompleteUserMuteStrategy, +) + +__all__ = [ + "AlwaysUserMuteStrategy", + "BaseUserMuteStrategy", + "FirstSpeechUserMuteStrategy", + "FunctionCallUserMuteStrategy", + "MuteUntilFirstBotCompleteUserMuteStrategy", +] diff --git a/src/pipecat/turns/mute/always_user_mute_strategy.py b/src/pipecat/turns/user_mute/always_user_mute_strategy.py similarity index 93% rename from src/pipecat/turns/mute/always_user_mute_strategy.py rename to src/pipecat/turns/user_mute/always_user_mute_strategy.py index 584b8165b..981c6bb74 100644 --- a/src/pipecat/turns/mute/always_user_mute_strategy.py +++ b/src/pipecat/turns/user_mute/always_user_mute_strategy.py @@ -7,7 +7,7 @@ """User mute strategy that always mutes the user while the bot is speaking.""" from pipecat.frames.frames import BotStartedSpeakingFrame, BotStoppedSpeakingFrame, Frame -from pipecat.turns.mute.base_user_mute_strategy import BaseUserMuteStrategy +from pipecat.turns.user_mute.base_user_mute_strategy import BaseUserMuteStrategy class AlwaysUserMuteStrategy(BaseUserMuteStrategy): diff --git a/src/pipecat/turns/mute/base_user_mute_strategy.py b/src/pipecat/turns/user_mute/base_user_mute_strategy.py similarity index 100% rename from src/pipecat/turns/mute/base_user_mute_strategy.py rename to src/pipecat/turns/user_mute/base_user_mute_strategy.py diff --git a/src/pipecat/turns/mute/first_speech_user_mute_strategy.py b/src/pipecat/turns/user_mute/first_speech_user_mute_strategy.py similarity index 96% rename from src/pipecat/turns/mute/first_speech_user_mute_strategy.py rename to src/pipecat/turns/user_mute/first_speech_user_mute_strategy.py index 1ce4c64f5..9349edd11 100644 --- a/src/pipecat/turns/mute/first_speech_user_mute_strategy.py +++ b/src/pipecat/turns/user_mute/first_speech_user_mute_strategy.py @@ -7,7 +7,7 @@ """User mute strategy that mutes the user only during the bot’s first speech.""" from pipecat.frames.frames import BotStartedSpeakingFrame, BotStoppedSpeakingFrame, Frame -from pipecat.turns.mute.base_user_mute_strategy import BaseUserMuteStrategy +from pipecat.turns.user_mute.base_user_mute_strategy import BaseUserMuteStrategy class FirstSpeechUserMuteStrategy(BaseUserMuteStrategy): diff --git a/src/pipecat/turns/mute/function_call_user_mute_strategy.py b/src/pipecat/turns/user_mute/function_call_user_mute_strategy.py similarity index 95% rename from src/pipecat/turns/mute/function_call_user_mute_strategy.py rename to src/pipecat/turns/user_mute/function_call_user_mute_strategy.py index ef83de271..f50f31bd4 100644 --- a/src/pipecat/turns/mute/function_call_user_mute_strategy.py +++ b/src/pipecat/turns/user_mute/function_call_user_mute_strategy.py @@ -14,7 +14,7 @@ from pipecat.frames.frames import ( FunctionCallResultFrame, FunctionCallsStartedFrame, ) -from pipecat.turns.mute.base_user_mute_strategy import BaseUserMuteStrategy +from pipecat.turns.user_mute.base_user_mute_strategy import BaseUserMuteStrategy class FunctionCallUserMuteStrategy(BaseUserMuteStrategy): diff --git a/src/pipecat/turns/mute/mute_until_first_bot_complete_user_mute_strategy.py b/src/pipecat/turns/user_mute/mute_until_first_bot_complete_user_mute_strategy.py similarity index 95% rename from src/pipecat/turns/mute/mute_until_first_bot_complete_user_mute_strategy.py rename to src/pipecat/turns/user_mute/mute_until_first_bot_complete_user_mute_strategy.py index 6ac5d62a9..20fe7016a 100644 --- a/src/pipecat/turns/mute/mute_until_first_bot_complete_user_mute_strategy.py +++ b/src/pipecat/turns/user_mute/mute_until_first_bot_complete_user_mute_strategy.py @@ -7,7 +7,7 @@ """User mute strategy that mutes the user until the bot completes its first speech.""" from pipecat.frames.frames import BotStoppedSpeakingFrame, Frame -from pipecat.turns.mute.base_user_mute_strategy import BaseUserMuteStrategy +from pipecat.turns.user_mute.base_user_mute_strategy import BaseUserMuteStrategy class MuteUntilFirstBotCompleteUserMuteStrategy(BaseUserMuteStrategy): diff --git a/src/pipecat/turns/user_start/__init__.py b/src/pipecat/turns/user_start/__init__.py index 3108e1c9a..fb84f62ed 100644 --- a/src/pipecat/turns/user_start/__init__.py +++ b/src/pipecat/turns/user_start/__init__.py @@ -4,15 +4,17 @@ # SPDX-License-Identifier: BSD 2-Clause License # -from pipecat.turns.user_start.base_user_turn_start_strategy import ( - BaseUserTurnStartStrategy, - UserTurnStartedParams, -) -from pipecat.turns.user_start.external_user_turn_start_strategy import ExternalUserTurnStartStrategy -from pipecat.turns.user_start.min_words_user_turn_start_strategy import ( - MinWordsUserTurnStartStrategy, -) -from pipecat.turns.user_start.transcription_user_turn_start_strategy import ( - TranscriptionUserTurnStartStrategy, -) -from pipecat.turns.user_start.vad_user_turn_start_strategy import VADUserTurnStartStrategy +from .base_user_turn_start_strategy import BaseUserTurnStartStrategy, UserTurnStartedParams +from .external_user_turn_start_strategy import ExternalUserTurnStartStrategy +from .min_words_user_turn_start_strategy import MinWordsUserTurnStartStrategy +from .transcription_user_turn_start_strategy import TranscriptionUserTurnStartStrategy +from .vad_user_turn_start_strategy import VADUserTurnStartStrategy + +__all__ = [ + "BaseUserTurnStartStrategy", + "ExternalUserTurnStartStrategy", + "MinWordsUserTurnStartStrategy", + "TranscriptionUserTurnStartStrategy", + "UserTurnStartedParams", + "VADUserTurnStartStrategy", +] diff --git a/src/pipecat/turns/user_stop/__init__.py b/src/pipecat/turns/user_stop/__init__.py index f54e00b7e..b95a71d15 100644 --- a/src/pipecat/turns/user_stop/__init__.py +++ b/src/pipecat/turns/user_stop/__init__.py @@ -4,14 +4,15 @@ # SPDX-License-Identifier: BSD 2-Clause License # -from pipecat.turns.user_stop.base_user_turn_stop_strategy import ( - BaseUserTurnStopStrategy, - UserTurnStoppedParams, -) -from pipecat.turns.user_stop.external_user_turn_stop_strategy import ExternalUserTurnStopStrategy -from pipecat.turns.user_stop.transcription_user_turn_stop_strategy import ( - TranscriptionUserTurnStopStrategy, -) -from pipecat.turns.user_stop.turn_analyzer_user_turn_stop_strategy import ( - TurnAnalyzerUserTurnStopStrategy, -) +from .base_user_turn_stop_strategy import BaseUserTurnStopStrategy, UserTurnStoppedParams +from .external_user_turn_stop_strategy import ExternalUserTurnStopStrategy +from .transcription_user_turn_stop_strategy import TranscriptionUserTurnStopStrategy +from .turn_analyzer_user_turn_stop_strategy import TurnAnalyzerUserTurnStopStrategy + +__all__ = [ + "BaseUserTurnStopStrategy", + "ExternalUserTurnStopStrategy", + "UserTurnStoppedParams", + "TranscriptionUserTurnStopStrategy", + "TurnAnalyzerUserTurnStopStrategy", +] diff --git a/tests/test_context_aggregators_universal.py b/tests/test_context_aggregators_universal.py index 6aa38d362..3cb1407f1 100644 --- a/tests/test_context_aggregators_universal.py +++ b/tests/test_context_aggregators_universal.py @@ -40,7 +40,7 @@ from pipecat.processors.aggregators.llm_response_universal import ( LLMUserAggregatorParams, ) from pipecat.tests.utils import SleepFrame, run_test -from pipecat.turns.mute import FirstSpeechUserMuteStrategy, FunctionCallUserMuteStrategy +from pipecat.turns.user_mute import FirstSpeechUserMuteStrategy, FunctionCallUserMuteStrategy from pipecat.turns.user_stop import TranscriptionUserTurnStopStrategy from pipecat.turns.user_turn_strategies import UserTurnStrategies diff --git a/tests/test_user_mute_strategy.py b/tests/test_user_mute_strategy.py index 26a7af1cc..d8261877e 100644 --- a/tests/test_user_mute_strategy.py +++ b/tests/test_user_mute_strategy.py @@ -15,7 +15,7 @@ from pipecat.frames.frames import ( FunctionCallsStartedFrame, InterruptionFrame, ) -from pipecat.turns.mute import ( +from pipecat.turns.user_mute import ( AlwaysUserMuteStrategy, FirstSpeechUserMuteStrategy, FunctionCallUserMuteStrategy, From 58552af8fdaee0585c796db791b47cdb1fd71ea3 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Aleix=20Conchillo=20Flaqu=C3=A9?= Date: Fri, 16 Jan 2026 10:58:34 -0800 Subject: [PATCH 0111/1060] examples(foundational): remote STTMuteFilter example --- examples/foundational/24-stt-mute-filter.py | 182 -------------------- 1 file changed, 182 deletions(-) delete mode 100644 examples/foundational/24-stt-mute-filter.py diff --git a/examples/foundational/24-stt-mute-filter.py b/examples/foundational/24-stt-mute-filter.py deleted file mode 100644 index 0c51716b8..000000000 --- a/examples/foundational/24-stt-mute-filter.py +++ /dev/null @@ -1,182 +0,0 @@ -# -# Copyright (c) 2024-2026, Daily -# -# SPDX-License-Identifier: BSD 2-Clause License -# - - -import asyncio -import os - -from dotenv import load_dotenv -from loguru import logger - -from pipecat.adapters.schemas.function_schema import FunctionSchema -from pipecat.adapters.schemas.tools_schema import ToolsSchema -from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3 -from pipecat.audio.vad.silero import SileroVADAnalyzer -from pipecat.audio.vad.vad_analyzer import VADParams -from pipecat.frames.frames import LLMRunFrame -from pipecat.pipeline.pipeline import Pipeline -from pipecat.pipeline.runner import PipelineRunner -from pipecat.pipeline.task import PipelineParams, PipelineTask -from pipecat.processors.aggregators.llm_context import LLMContext -from pipecat.processors.aggregators.llm_response_universal import ( - LLMContextAggregatorPair, - LLMUserAggregatorParams, -) -from pipecat.processors.filters.stt_mute_filter import STTMuteConfig, STTMuteFilter, STTMuteStrategy -from pipecat.runner.types import RunnerArguments -from pipecat.runner.utils import create_transport -from pipecat.services.deepgram.stt import DeepgramSTTService -from pipecat.services.deepgram.tts import DeepgramTTSService -from pipecat.services.llm_service import FunctionCallParams -from pipecat.services.openai.llm import OpenAILLMService -from pipecat.transports.base_transport import BaseTransport, TransportParams -from pipecat.transports.daily.transport import DailyParams -from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams -from pipecat.turns.user_stop import TurnAnalyzerUserTurnStopStrategy -from pipecat.turns.user_turn_strategies import UserTurnStrategies - -load_dotenv(override=True) - - -async def fetch_weather_from_api(params: FunctionCallParams): - # Add a delay to test interruption during function calls - logger.info("Weather API call starting...") - await asyncio.sleep(5) # 5-second delay - logger.info("Weather API call completed") - await params.result_callback({"conditions": "nice", "temperature": "75"}) - - -# We store functions so objects (e.g. SileroVADAnalyzer) don't get -# instantiated. The function will be called when the desired transport gets -# selected. -transport_params = { - "daily": lambda: DailyParams( - audio_in_enabled=True, - audio_out_enabled=True, - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), - ), - "twilio": lambda: FastAPIWebsocketParams( - audio_in_enabled=True, - audio_out_enabled=True, - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), - ), - "webrtc": lambda: TransportParams( - audio_in_enabled=True, - audio_out_enabled=True, - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), - ), -} - - -async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): - logger.info(f"Starting bot") - - stt = DeepgramSTTService(api_key=os.getenv("DEEPGRAM_API_KEY")) - - # Configure the mute processor with both strategies - stt_mute_processor = STTMuteFilter( - config=STTMuteConfig( - strategies={ - STTMuteStrategy.MUTE_UNTIL_FIRST_BOT_COMPLETE, - STTMuteStrategy.FUNCTION_CALL, - } - ), - ) - - tts = DeepgramTTSService(api_key=os.getenv("DEEPGRAM_API_KEY"), voice="aura-helios-en") - - llm = OpenAILLMService(api_key=os.getenv("OPENAI_API_KEY")) - llm.register_function("get_current_weather", fetch_weather_from_api) - - weather_function = FunctionSchema( - name="get_current_weather", - description="Get the current weather", - properties={ - "location": { - "type": "string", - "description": "The city and state, e.g. San Francisco, CA", - }, - "format": { - "type": "string", - "enum": ["celsius", "fahrenheit"], - "description": "The temperature unit to use. Infer this from the user's location.", - }, - }, - required=["location", "format"], - ) - tools = ToolsSchema(standard_tools=[weather_function]) - - messages = [ - { - "role": "system", - "content": "You are a helpful assistant who can check the weather. Always check the weather when a location is mentioned. Respond concisely and naturally. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points.", - }, - ] - - context = LLMContext(messages, tools) - user_aggregator, assistant_aggregator = LLMContextAggregatorPair( - context, - user_params=LLMUserAggregatorParams( - user_turn_strategies=UserTurnStrategies( - stop=[TurnAnalyzerUserTurnStopStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3())] - ), - ), - ) - - pipeline = Pipeline( - [ - transport.input(), # Transport user input - stt, # STT - stt_mute_processor, # Add the mute processor between STT and context aggregator - user_aggregator, # User responses - llm, # LLM - tts, # TTS - transport.output(), # Transport bot output - assistant_aggregator, # Assistant spoken responses - ] - ) - - task = PipelineTask( - pipeline, - params=PipelineParams( - enable_metrics=True, - enable_usage_metrics=True, - ), - idle_timeout_secs=runner_args.pipeline_idle_timeout_secs, - ) - - @transport.event_handler("on_client_connected") - async def on_client_connected(transport, client): - logger.info(f"Client connected") - # Kick off the conversation with a weather-related prompt - messages.append( - { - "role": "system", - "content": "Ask the user what city they'd like to know the weather for.", - } - ) - await task.queue_frames([LLMRunFrame()]) - - @transport.event_handler("on_client_disconnected") - async def on_client_disconnected(transport, client): - logger.info(f"Client disconnected") - await task.cancel() - - runner = PipelineRunner(handle_sigint=runner_args.handle_sigint) - - await runner.run(task) - - -async def bot(runner_args: RunnerArguments): - """Main bot entry point compatible with Pipecat Cloud.""" - transport = await create_transport(runner_args, transport_params) - await run_bot(transport, runner_args) - - -if __name__ == "__main__": - from pipecat.runner.run import main - - main() From c2a07359756001fefef8d3a9d09ed28c8d22da0f Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Aleix=20Conchillo=20Flaqu=C3=A9?= Date: Thu, 15 Jan 2026 10:32:23 -0800 Subject: [PATCH 0112/1060] MinWordsUserTurnStartStrategy: don't aggregate transcriptions If we aggregate transcriptions we will get incorrect interruptions. For example, if we have a strategy with min_words=3 and we say "One" and pause, then "Two" and pause and then "Three", this would trigger the start of the turn when it shouldn't. We should only look at the incoming transcription text and don't aggregate it with the previous. --- changelog/3462.fixed.md | 1 + .../min_words_user_turn_start_strategy.py | 32 +++---------------- tests/test_user_turn_controller.py | 8 ++--- tests/test_user_turn_start_strategy.py | 22 ++++++++++++- 4 files changed, 30 insertions(+), 33 deletions(-) create mode 100644 changelog/3462.fixed.md diff --git a/changelog/3462.fixed.md b/changelog/3462.fixed.md new file mode 100644 index 000000000..f9ede6a53 --- /dev/null +++ b/changelog/3462.fixed.md @@ -0,0 +1 @@ +- Fixed `MinWordsUserTurnStartStrategy` to not aggregate transcriptions, preventing incorrect turn starts when words are spoken with pauses between them. diff --git a/src/pipecat/turns/user_start/min_words_user_turn_start_strategy.py b/src/pipecat/turns/user_start/min_words_user_turn_start_strategy.py index 1f156cef9..57a0ca0d8 100644 --- a/src/pipecat/turns/user_start/min_words_user_turn_start_strategy.py +++ b/src/pipecat/turns/user_start/min_words_user_turn_start_strategy.py @@ -41,12 +41,10 @@ class MinWordsUserTurnStartStrategy(BaseUserTurnStartStrategy): self._min_words = min_words self._use_interim = use_interim self._bot_speaking = False - self._text = "" async def reset(self): """Reset the strategy to its initial state.""" await super().reset() - self._text = "" self._bot_speaking = False async def process_frame(self, frame: Frame): @@ -67,7 +65,7 @@ class MinWordsUserTurnStartStrategy(BaseUserTurnStartStrategy): elif isinstance(frame, TranscriptionFrame): await self._handle_transcription(frame) elif isinstance(frame, InterimTranscriptionFrame) and self._use_interim: - await self._handle_interim_transcription(frame) + await self._handle_transcription(frame) async def _handle_bot_started_speaking(self, frame: BotStartedSpeakingFrame): """Handle bot started speaking frame. @@ -89,41 +87,21 @@ class MinWordsUserTurnStartStrategy(BaseUserTurnStartStrategy): """ self._bot_speaking = False - async def _handle_transcription(self, frame: TranscriptionFrame): + async def _handle_transcription(self, frame: TranscriptionFrame | InterimTranscriptionFrame): """Handle a completed transcription frame and check word count. Args: frame: The transcription frame to be processed. """ - self._text += frame.text - - min_words = self._min_words if self._bot_speaking else 1 - - word_count = len(self._text.split()) - should_trigger = word_count >= min_words - - logger.debug( - f"{self} should_trigger={should_trigger} num_spoken_words={word_count} " - f"min_words={min_words} bot_speaking={self._bot_speaking}" - ) - - if should_trigger: - await self.trigger_user_turn_started() - - async def _handle_interim_transcription(self, frame: InterimTranscriptionFrame): - """Handle an interim transcription frame and check word count. - - Args: - frame: The interim transcription frame to be processed. - """ min_words = self._min_words if self._bot_speaking else 1 word_count = len(frame.text.split()) should_trigger = word_count >= min_words + is_interim = isinstance(frame, InterimTranscriptionFrame) logger.debug( - f"{self} interim=True should_trigger={should_trigger} num_spoken_words={word_count} " - f"min_words={min_words} bot_speaking={self._bot_speaking}" + f"{self} should_trigger={should_trigger} num_spoken_words={word_count} " + f"min_words={min_words} bot_speaking={self._bot_speaking} interim_transcription={is_interim}" ) if should_trigger: diff --git a/tests/test_user_turn_controller.py b/tests/test_user_turn_controller.py index 1c5cfcf85..d8f642594 100644 --- a/tests/test_user_turn_controller.py +++ b/tests/test_user_turn_controller.py @@ -84,7 +84,7 @@ class TestUserTurnController(unittest.IsolatedAsyncioTestCase): self.assertEqual(should_start, 0) await controller.process_frame( - TranscriptionFrame(text=" two three!", user_id="cat", timestamp="") + TranscriptionFrame(text="One two three!", user_id="cat", timestamp="") ) self.assertEqual(should_start, 1) @@ -92,13 +92,11 @@ class TestUserTurnController(unittest.IsolatedAsyncioTestCase): await asyncio.sleep(USER_TURN_STOP_TIMEOUT + 0.1) await controller.process_frame(BotStartedSpeakingFrame()) - await controller.process_frame( - TranscriptionFrame(text="Hello", user_id="cat", timestamp="") - ) + await controller.process_frame(TranscriptionFrame(text="Hi!", user_id="cat", timestamp="")) self.assertEqual(should_start, 1) await controller.process_frame( - TranscriptionFrame(text=" there friend!", user_id="cat", timestamp="") + TranscriptionFrame(text="How are you?", user_id="cat", timestamp="") ) self.assertEqual(should_start, 2) diff --git a/tests/test_user_turn_start_strategy.py b/tests/test_user_turn_start_strategy.py index 51856ff9c..dabd4593b 100644 --- a/tests/test_user_turn_start_strategy.py +++ b/tests/test_user_turn_start_strategy.py @@ -38,7 +38,7 @@ class TestMinWordsInterruptionStrategy(unittest.IsolatedAsyncioTestCase): self.assertFalse(should_start) await strategy.process_frame( - TranscriptionFrame(text=" there!", user_id="cat", timestamp="") + TranscriptionFrame(text="Hello there!", user_id="cat", timestamp="") ) self.assertTrue(should_start) @@ -55,6 +55,26 @@ class TestMinWordsInterruptionStrategy(unittest.IsolatedAsyncioTestCase): ) self.assertTrue(should_start) + async def test_bot_speaking_singlw_words(self): + strategy = MinWordsUserTurnStartStrategy(min_words=3) + + should_start = None + + @strategy.event_handler("on_user_turn_started") + async def on_user_turn_started(strategy, params): + nonlocal should_start + should_start = True + + await strategy.process_frame(BotStartedSpeakingFrame()) + await strategy.process_frame(TranscriptionFrame(text="One", user_id="cat", timestamp="")) + self.assertFalse(should_start) + + await strategy.process_frame(TranscriptionFrame(text="Two", user_id="cat", timestamp="")) + self.assertFalse(should_start) + + await strategy.process_frame(TranscriptionFrame(text="Three", user_id="cat", timestamp="")) + self.assertFalse(should_start) + async def test_bot_speaking_interim_transcriptions(self): strategy = MinWordsUserTurnStartStrategy(min_words=2) From 1c13ad95a574f4c701d7d27c9619816bb0145373 Mon Sep 17 00:00:00 2001 From: James Hush Date: Fri, 16 Jan 2026 14:38:05 +0800 Subject: [PATCH 0113/1060] Fix Pylance reportOptionalMemberAccess in _handle_function_call_cancel Extract dictionary value to local variable and check for None before accessing cancel_on_interruption attribute, since the dictionary values are typed as Optional[FunctionCallInProgressFrame]. --- src/pipecat/processors/aggregators/llm_response.py | 6 ++---- .../processors/aggregators/llm_response_universal.py | 6 ++---- 2 files changed, 4 insertions(+), 8 deletions(-) diff --git a/src/pipecat/processors/aggregators/llm_response.py b/src/pipecat/processors/aggregators/llm_response.py index 81a92800a..1b53e9934 100644 --- a/src/pipecat/processors/aggregators/llm_response.py +++ b/src/pipecat/processors/aggregators/llm_response.py @@ -1024,10 +1024,8 @@ class LLMAssistantContextAggregator(LLMContextResponseAggregator): logger.debug( f"{self} FunctionCallCancelFrame: [{frame.function_name}:{frame.tool_call_id}]" ) - if frame.tool_call_id not in self._function_calls_in_progress: - return - - if self._function_calls_in_progress[frame.tool_call_id].cancel_on_interruption: + function_call = self._function_calls_in_progress.get(frame.tool_call_id) + if function_call and function_call.cancel_on_interruption: await self.handle_function_call_cancel(frame) del self._function_calls_in_progress[frame.tool_call_id] diff --git a/src/pipecat/processors/aggregators/llm_response_universal.py b/src/pipecat/processors/aggregators/llm_response_universal.py index 2854c8681..87f7b22e8 100644 --- a/src/pipecat/processors/aggregators/llm_response_universal.py +++ b/src/pipecat/processors/aggregators/llm_response_universal.py @@ -858,10 +858,8 @@ class LLMAssistantAggregator(LLMContextAggregator): logger.debug( f"{self} FunctionCallCancelFrame: [{frame.function_name}:{frame.tool_call_id}]" ) - if frame.tool_call_id not in self._function_calls_in_progress: - return - - if self._function_calls_in_progress[frame.tool_call_id].cancel_on_interruption: + function_call = self._function_calls_in_progress.get(frame.tool_call_id) + if function_call and function_call.cancel_on_interruption: # Update context with the function call cancellation self._update_function_call_result(frame.function_name, frame.tool_call_id, "CANCELLED") del self._function_calls_in_progress[frame.tool_call_id] From 836cf60611dd252a5c72608fa38c880d82ab2a87 Mon Sep 17 00:00:00 2001 From: Paul Kompfner Date: Fri, 16 Jan 2026 15:38:33 -0500 Subject: [PATCH 0114/1060] Fix an issue where Grok Realtime would error out when running with SmallWebRTC transport. The underlying issue was related to the fact that we were sending audio to Grok before we had configured the Grok session with our default input sample rate (16000), so Grok was interpreting those initial audio chunks as having its default sample rate (24000). We didn't see this issue when using the Daily transport simply because in our test environments Daily took a smidge longer than a reflexive (localhost) pure WebRTC connection, so we would only send audio to Grok *after* we had configured the Grok session with the desired sample rate. --- changelog/3480.fixed.md | 1 + src/pipecat/services/grok/realtime/llm.py | 8 ++++++++ 2 files changed, 9 insertions(+) create mode 100644 changelog/3480.fixed.md diff --git a/changelog/3480.fixed.md b/changelog/3480.fixed.md new file mode 100644 index 000000000..9d04545ec --- /dev/null +++ b/changelog/3480.fixed.md @@ -0,0 +1 @@ +- Fixed an issue where Grok Realtime would error out when running with SmallWebRTC transport. diff --git a/src/pipecat/services/grok/realtime/llm.py b/src/pipecat/services/grok/realtime/llm.py index 5e368b62b..e1355ce31 100644 --- a/src/pipecat/services/grok/realtime/llm.py +++ b/src/pipecat/services/grok/realtime/llm.py @@ -752,6 +752,14 @@ class GrokRealtimeLLMService(LLMService): async def _send_user_audio(self, frame): """Send user audio to Grok.""" + # Don't send audio if conversation setup is still pending, as it can + # lead to errors. For example: audio sent before conversation setup + # will be interpreted as having Grok's default sample rate (24000), + # and if that differs from the sample rate we eventually set through + # the conversation setup, Grok will error out. + if self._llm_needs_conversation_setup: + return + payload = base64.b64encode(frame.audio).decode("utf-8") await self.send_client_event(events.InputAudioBufferAppendEvent(audio=payload)) From 6eadad53b29d43cf00f7fd2609b899ac4af07818 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Aleix=20Conchillo=20Flaqu=C3=A9?= Date: Fri, 16 Jan 2026 14:45:30 -0800 Subject: [PATCH 0115/1060] BaseInputTransport: throttle UserSpeakingFrame --- changelog/3483.changed.md | 1 + src/pipecat/transports/base_input.py | 15 ++++++++++++++- 2 files changed, 15 insertions(+), 1 deletion(-) create mode 100644 changelog/3483.changed.md diff --git a/changelog/3483.changed.md b/changelog/3483.changed.md new file mode 100644 index 000000000..97bb10371 --- /dev/null +++ b/changelog/3483.changed.md @@ -0,0 +1 @@ +- Throttle `UserSpeakingFrame` to broadcast at most every 200ms instead of on every audio chunk, reducing frame processing overhead during user speech. diff --git a/src/pipecat/transports/base_input.py b/src/pipecat/transports/base_input.py index 31bc3e035..b5f5a17c7 100644 --- a/src/pipecat/transports/base_input.py +++ b/src/pipecat/transports/base_input.py @@ -11,6 +11,7 @@ input processing, including VAD, turn analysis, and interruption management. """ import asyncio +import time from typing import Optional from loguru import logger @@ -77,6 +78,11 @@ class BaseInputTransport(FrameProcessor): # Track user speaking state for interruption logic self._user_speaking = False + # Last time a UserSpeakingFrame was pushed. + self._user_speaking_frame_time = 0 + # How often a UserSpeakingFrame should be pushed (value should be + # greater than the audio chunks to have any effect). + self._user_speaking_frame_period = 0.2 # Task to process incoming audio (VAD) and push audio frames downstream # if passthrough is enabled. @@ -423,7 +429,7 @@ class BaseInputTransport(FrameProcessor): await self._deprecated_run_turn_analyzer(frame, vad_state, previous_vad_state) if vad_state == VADState.SPEAKING: - await self.broadcast_frame(UserSpeakingFrame) + await self._user_currently_speaking() # Push audio downstream if passthrough is set. if self._params.audio_in_passthrough: @@ -444,6 +450,13 @@ class BaseInputTransport(FrameProcessor): else: await self.push_frame(VADUserStoppedSpeakingFrame()) + async def _user_currently_speaking(self): + """Handle user speaking frame.""" + diff_time = time.time() - self._user_speaking_frame_time + if diff_time >= self._user_speaking_frame_period: + await self.broadcast_frame(UserSpeakingFrame) + self._user_speaking_frame_time = time.time() + # # DEPRECATED. # From ac3fa7f91f42394f33036ea01ad8c0f08d2b9890 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Aleix=20Conchillo=20Flaqu=C3=A9?= Date: Fri, 16 Jan 2026 14:46:25 -0800 Subject: [PATCH 0116/1060] BaseOuputTransport: minor cleanup --- src/pipecat/transports/base_output.py | 5 ++--- 1 file changed, 2 insertions(+), 3 deletions(-) diff --git a/src/pipecat/transports/base_output.py b/src/pipecat/transports/base_output.py index a19d65b75..c4f59a61d 100644 --- a/src/pipecat/transports/base_output.py +++ b/src/pipecat/transports/base_output.py @@ -403,7 +403,7 @@ class BaseOutputTransport(FrameProcessor): # Last time a BotSpeakingFrame was pushed. self._bot_speaking_frame_time = 0 # How often a BotSpeakingFrame should be pushed (value should be - # lower than the audio chunks). + # greater than the audio chunks to have any effect). self._bot_speaking_frame_period = 0.2 # Last time the bot actually spoke. self._bot_speech_last_time = 0 @@ -644,8 +644,7 @@ class BaseOutputTransport(FrameProcessor): diff_time = time.time() - self._bot_speaking_frame_time if diff_time >= self._bot_speaking_frame_period: - await self._transport.push_frame(BotSpeakingFrame()) - await self._transport.push_frame(BotSpeakingFrame(), FrameDirection.UPSTREAM) + await self._transport.broadcast_frame(BotSpeakingFrame) self._bot_speaking_frame_time = time.time() self._bot_speech_last_time = time.time() From a6e7c99d55c349af2dfc022920d80ba092564cc4 Mon Sep 17 00:00:00 2001 From: Amory Hen <214372542+amichyrpi@users.noreply.github.com> Date: Sat, 17 Jan 2026 00:26:38 +0100 Subject: [PATCH 0117/1060] Remove async_mode parameter from Mem0 storage --- src/pipecat/services/mem0/memory.py | 1 - 1 file changed, 1 deletion(-) diff --git a/src/pipecat/services/mem0/memory.py b/src/pipecat/services/mem0/memory.py index afb38088e..d0c8e66dc 100644 --- a/src/pipecat/services/mem0/memory.py +++ b/src/pipecat/services/mem0/memory.py @@ -121,7 +121,6 @@ class Mem0MemoryService(FrameProcessor): try: logger.debug(f"Storing {len(messages)} messages in Mem0") params = { - "async_mode": True, "messages": messages, "metadata": {"platform": "pipecat"}, "output_format": "v1.1", From 2e8e574ea56f1760e1e11bc4ae05b84e0d9052a0 Mon Sep 17 00:00:00 2001 From: Mark Backman Date: Fri, 16 Jan 2026 17:09:11 -0500 Subject: [PATCH 0118/1060] Add UserIdleController, deprecate UserIdleProcessor --- changelog/3482.added.md | 1 + examples/foundational/17-detect-user-idle.py | 89 +++++--- .../aggregators/llm_response_universal.py | 34 ++- src/pipecat/processors/user_idle_processor.py | 13 ++ src/pipecat/turns/user_idle_controller.py | 173 ++++++++++++++ src/pipecat/turns/user_turn_processor.py | 30 +++ tests/test_user_idle_controller.py | 216 ++++++++++++++++++ 7 files changed, 524 insertions(+), 32 deletions(-) create mode 100644 changelog/3482.added.md create mode 100644 src/pipecat/turns/user_idle_controller.py create mode 100644 tests/test_user_idle_controller.py diff --git a/changelog/3482.added.md b/changelog/3482.added.md new file mode 100644 index 000000000..35522f36c --- /dev/null +++ b/changelog/3482.added.md @@ -0,0 +1 @@ +- Added `UserIdleController` for detecting user idle state, integrated into `LLMUserAggregator` and `UserTurnProcessor` via optional `user_idle_timeout` parameter. Emits `on_user_idle` event for application-level handling. Deprecated `UserIdleProcessor` in favor of the new compositional approach. diff --git a/examples/foundational/17-detect-user-idle.py b/examples/foundational/17-detect-user-idle.py index f1fe0d068..b4042c1d1 100644 --- a/examples/foundational/17-detect-user-idle.py +++ b/examples/foundational/17-detect-user-idle.py @@ -13,7 +13,13 @@ from loguru import logger from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3 from pipecat.audio.vad.silero import SileroVADAnalyzer from pipecat.audio.vad.vad_analyzer import VADParams -from pipecat.frames.frames import EndFrame, LLMMessagesAppendFrame, LLMRunFrame, TTSSpeakFrame +from pipecat.frames.frames import ( + EndFrame, + EndTaskFrame, + LLMMessagesAppendFrame, + LLMRunFrame, + TTSSpeakFrame, +) from pipecat.pipeline.pipeline import Pipeline from pipecat.pipeline.runner import PipelineRunner from pipecat.pipeline.task import PipelineParams, PipelineTask @@ -22,7 +28,7 @@ from pipecat.processors.aggregators.llm_response_universal import ( LLMContextAggregatorPair, LLMUserAggregatorParams, ) -from pipecat.processors.user_idle_processor import UserIdleProcessor +from pipecat.processors.frame_processor import FrameDirection from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport from pipecat.services.cartesia.tts import CartesiaTTSService @@ -36,6 +42,43 @@ from pipecat.turns.user_turn_strategies import UserTurnStrategies load_dotenv(override=True) + +class IdleHandler: + """Helper class to manage user idle retry logic.""" + + def __init__(self): + self._retry_count = 0 + + def reset(self): + """Reset the retry count when user becomes active.""" + self._retry_count = 0 + + async def handle_idle(self, aggregator): + """Handle user idle event with escalating prompts.""" + self._retry_count += 1 + + if self._retry_count == 1: + # First attempt: Add a gentle prompt to the conversation + message = { + "role": "system", + "content": "The user has been quiet. Politely and briefly ask if they're still there.", + } + await aggregator.push_frame(LLMMessagesAppendFrame([message], run_llm=True)) + elif self._retry_count == 2: + # Second attempt: More direct prompt + message = { + "role": "system", + "content": "The user is still inactive. Ask if they'd like to continue our conversation.", + } + await aggregator.push_frame(LLMMessagesAppendFrame([message], run_llm=True)) + else: + # Third attempt: End the conversation + await aggregator.push_frame( + TTSSpeakFrame("It seems like you're busy right now. Have a nice day!") + ) + await aggregator.push_frame(EndTaskFrame(), FrameDirection.UPSTREAM) + + # We store functions so objects (e.g. SileroVADAnalyzer) don't get # instantiated. The function will be called when the desired transport gets # selected. @@ -84,42 +127,15 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): user_turn_strategies=UserTurnStrategies( stop=[TurnAnalyzerUserTurnStopStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3())] ), + user_idle_timeout=5.0, # Detect user idle after 5 seconds ), ) - async def handle_user_idle(user_idle: UserIdleProcessor, retry_count: int) -> bool: - if retry_count == 1: - # First attempt: Add a gentle prompt to the conversation - message = { - "role": "system", - "content": "The user has been quiet. Politely and briefly ask if they're still there.", - } - await user_idle.push_frame(LLMMessagesAppendFrame([message], run_llm=True)) - return True - elif retry_count == 2: - # Second attempt: More direct prompt - message = { - "role": "system", - "content": "The user is still inactive. Ask if they'd like to continue our conversation.", - } - await user_idle.push_frame(LLMMessagesAppendFrame([message], run_llm=True)) - return True - else: - # Third attempt: End the conversation - await user_idle.push_frame( - TTSSpeakFrame("It seems like you're busy right now. Have a nice day!") - ) - await task.queue_frame(EndFrame()) - return False - - user_idle = UserIdleProcessor(callback=handle_user_idle, timeout=5.0) - pipeline = Pipeline( [ transport.input(), # Transport user input stt, - user_idle, # Idle user check-in - user_aggregator, + user_aggregator, # User aggregator with built-in idle detection llm, # LLM tts, # TTS transport.output(), # Transport bot output @@ -136,6 +152,17 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): idle_timeout_secs=runner_args.pipeline_idle_timeout_secs, ) + # Set up idle handling with retry logic + idle_handler = IdleHandler() + + @user_aggregator.event_handler("on_user_idle") + async def handle_user_idle(aggregator): + await idle_handler.handle_idle(aggregator) + + @user_aggregator.event_handler("on_user_turn_started") + async def handle_user_turn_started(aggregator, strategy): + idle_handler.reset() + @transport.event_handler("on_client_connected") async def on_client_connected(transport, client): logger.info(f"Client connected") diff --git a/src/pipecat/processors/aggregators/llm_response_universal.py b/src/pipecat/processors/aggregators/llm_response_universal.py index 26c388fe6..4b0e89008 100644 --- a/src/pipecat/processors/aggregators/llm_response_universal.py +++ b/src/pipecat/processors/aggregators/llm_response_universal.py @@ -62,6 +62,7 @@ from pipecat.processors.aggregators.llm_context import ( NotGiven, ) from pipecat.processors.frame_processor import FrameDirection, FrameProcessor +from pipecat.turns.user_idle_controller import UserIdleController from pipecat.turns.user_mute import BaseUserMuteStrategy from pipecat.turns.user_start import BaseUserTurnStartStrategy, UserTurnStartedParams from pipecat.turns.user_stop import BaseUserTurnStopStrategy, UserTurnStoppedParams @@ -80,11 +81,16 @@ class LLMUserAggregatorParams: user_mute_strategies: List of user mute strategies. user_turn_stop_timeout: Time in seconds to wait before considering the user's turn finished. + user_idle_timeout: Optional timeout in seconds for detecting user idle state. + If set, the aggregator will emit an `on_user_idle` event when the user + has been idle (not speaking) for this duration. Set to None to disable + idle detection. """ user_turn_strategies: Optional[UserTurnStrategies] = None user_mute_strategies: List[BaseUserMuteStrategy] = field(default_factory=list) user_turn_stop_timeout: float = 5.0 + user_idle_timeout: Optional[float] = None @dataclass @@ -291,11 +297,12 @@ class LLMUserAggregator(LLMContextAggregator): - on_user_turn_started: Called when the user turn starts - on_user_turn_stopped: Called when the user turn ends - on_user_turn_stop_timeout: Called when no user turn stop strategy triggers + - on_user_idle: Called when the user has been idle for the configured timeout Example:: @aggregator.event_handler("on_user_turn_started") - async def on_user_turn_started(aggregator, strategy: BaseUserTurnStartStrategy]): + async def on_user_turn_started(aggregator, strategy: BaseUserTurnStartStrategy): ... @aggregator.event_handler("on_user_turn_stopped") @@ -306,6 +313,10 @@ class LLMUserAggregator(LLMContextAggregator): async def on_user_turn_stop_timeout(aggregator): ... + @aggregator.event_handler("on_user_idle") + async def on_user_idle(aggregator): + ... + """ def __init__( @@ -328,6 +339,7 @@ class LLMUserAggregator(LLMContextAggregator): self._register_event_handler("on_user_turn_started") self._register_event_handler("on_user_turn_stopped") self._register_event_handler("on_user_turn_stop_timeout") + self._register_event_handler("on_user_idle") user_turn_strategies = self._params.user_turn_strategies or UserTurnStrategies() @@ -350,6 +362,14 @@ class LLMUserAggregator(LLMContextAggregator): "on_user_turn_stop_timeout", self._on_user_turn_stop_timeout ) + # Optional user idle controller + self._user_idle_controller: Optional[UserIdleController] = None + if self._params.user_idle_timeout: + self._user_idle_controller = UserIdleController( + user_idle_timeout=self._params.user_idle_timeout + ) + self._user_idle_controller.add_event_handler("on_user_idle", self._on_user_idle) + async def cleanup(self): """Clean up processor resources.""" await super().cleanup() @@ -405,6 +425,9 @@ class LLMUserAggregator(LLMContextAggregator): await self._user_turn_controller.process_frame(frame) + if self._user_idle_controller: + await self._user_idle_controller.process_frame(frame) + async def push_aggregation(self) -> str: """Push the current aggregation.""" if len(self._aggregation) == 0: @@ -420,6 +443,9 @@ class LLMUserAggregator(LLMContextAggregator): async def _start(self, frame: StartFrame): await self._user_turn_controller.setup(self.task_manager) + if self._user_idle_controller: + await self._user_idle_controller.setup(self.task_manager) + for s in self._params.user_mute_strategies: await s.setup(self.task_manager) @@ -432,6 +458,9 @@ class LLMUserAggregator(LLMContextAggregator): async def _cleanup(self): await self._user_turn_controller.cleanup() + if self._user_idle_controller: + await self._user_idle_controller.cleanup() + for s in self._params.user_mute_strategies: await s.cleanup() @@ -565,6 +594,9 @@ class LLMUserAggregator(LLMContextAggregator): async def _on_user_turn_stop_timeout(self, controller): await self._call_event_handler("on_user_turn_stop_timeout") + async def _on_user_idle(self, controller): + await self._call_event_handler("on_user_idle") + class LLMAssistantAggregator(LLMContextAggregator): """Assistant LLM aggregator that processes bot responses and function calls. diff --git a/src/pipecat/processors/user_idle_processor.py b/src/pipecat/processors/user_idle_processor.py index 6dc6dd47c..67c41ab13 100644 --- a/src/pipecat/processors/user_idle_processor.py +++ b/src/pipecat/processors/user_idle_processor.py @@ -8,6 +8,7 @@ import asyncio import inspect +import warnings from typing import Awaitable, Callable, Union from pipecat.frames.frames import ( @@ -26,6 +27,10 @@ from pipecat.processors.frame_processor import FrameDirection, FrameProcessor class UserIdleProcessor(FrameProcessor): """Monitors user inactivity and triggers callbacks after timeout periods. + .. deprecated:: + UserIdleProcessor is deprecated in 0.0.100 and will be removed in a future version. + Use LLMUserAggregator with user_idle_timeout parameter instead. + This processor tracks user activity and triggers configurable callbacks when users become idle. It starts monitoring only after the first conversation activity and supports both basic and retry-based callback patterns. @@ -70,6 +75,14 @@ class UserIdleProcessor(FrameProcessor): **kwargs: Additional arguments passed to FrameProcessor. """ super().__init__(**kwargs) + + warnings.warn( + "UserIdleProcessor is deprecated in 0.0.100 and will be removed in a " + "future version. Use LLMUserAggregator with user_idle_timeout parameter " + "instead.", + DeprecationWarning, + ) + self._callback = self._wrap_callback(callback) self._timeout = timeout self._retry_count = 0 diff --git a/src/pipecat/turns/user_idle_controller.py b/src/pipecat/turns/user_idle_controller.py new file mode 100644 index 000000000..4157d6d30 --- /dev/null +++ b/src/pipecat/turns/user_idle_controller.py @@ -0,0 +1,173 @@ +# +# Copyright (c) 2024-2026, Daily +# +# SPDX-License-Identifier: BSD 2-Clause License +# + +"""This module defines a controller for managing user idle detection.""" + +import asyncio +from typing import Optional + +from pipecat.frames.frames import ( + BotSpeakingFrame, + Frame, + FunctionCallResultFrame, + FunctionCallsStartedFrame, + UserSpeakingFrame, + UserStartedSpeakingFrame, +) +from pipecat.utils.asyncio.task_manager import BaseTaskManager +from pipecat.utils.base_object import BaseObject + + +class UserIdleController(BaseObject): + """Controller for managing user idle detection. + + This class monitors user activity and triggers an event when the user has been + idle (not speaking) for a configured timeout period. It only starts monitoring + after the first conversation activity and does not trigger while the bot is + speaking or function calls are in progress. + + The controller tracks activity using continuous frames (UserSpeakingFrame and + BotSpeakingFrame) which are emitted repeatedly while speaking is happening, and + state-based tracking for function calls (FunctionCallsStartedFrame and + FunctionCallResultFrame) which are only sent at start and end. + + Event handlers available: + + - on_user_idle: Emitted when the user has been idle for the timeout period. + + Example:: + + @controller.event_handler("on_user_idle") + async def on_user_idle(controller): + # Handle user idle - send reminder, prompt, etc. + ... + """ + + def __init__( + self, + *, + user_idle_timeout: float, + ): + """Initialize the user idle controller. + + Args: + user_idle_timeout: Timeout in seconds before considering the user idle. + """ + super().__init__() + + self._user_idle_timeout = user_idle_timeout + + self._task_manager: Optional[BaseTaskManager] = None + + self._conversation_started = False + self._function_call_in_progress = False + + self.user_idle_event = asyncio.Event() + self.user_idle_task: Optional[asyncio.Task] = None + + self._register_event_handler("on_user_idle", sync=True) + + @property + def task_manager(self) -> BaseTaskManager: + """Returns the configured task manager.""" + if not self._task_manager: + raise RuntimeError(f"{self} user idle controller was not properly setup") + return self._task_manager + + async def setup(self, task_manager: BaseTaskManager): + """Initialize the controller with the given task manager. + + Args: + task_manager: The task manager to be associated with this instance. + """ + self._task_manager = task_manager + + if not self.user_idle_task: + self.user_idle_task = self.task_manager.create_task( + self.user_idle_task_handler(), + f"{self}::user_idle_task_handler", + ) + + async def cleanup(self): + """Cleanup the controller.""" + await super().cleanup() + + if self.user_idle_task: + await self.task_manager.cancel_task(self.user_idle_task) + self.user_idle_task = None + + async def process_frame(self, frame: Frame): + """Process an incoming frame to track user activity state. + + Args: + frame: The frame to be processed. + """ + # Start monitoring on first conversation activity + if not self._conversation_started: + if isinstance(frame, (UserStartedSpeakingFrame, BotSpeakingFrame)): + self._conversation_started = True + self.user_idle_event.set() + else: + return + + # Reset idle timer on continuous activity frames + if isinstance(frame, (UserSpeakingFrame, BotSpeakingFrame)): + await self._handle_activity(frame) + # Track function call state (start/end frames, not continuous) + elif isinstance(frame, FunctionCallsStartedFrame): + await self._handle_function_calls_started(frame) + elif isinstance(frame, FunctionCallResultFrame): + await self._handle_function_call_result(frame) + + async def _handle_activity(self, _: UserSpeakingFrame | BotSpeakingFrame): + """Handle continuous activity frames that should reset the idle timer. + + These frames are emitted continuously while the user or bot is speaking, + so we simply reset the timer whenever we receive them. + + Args: + frame: The activity frame to process. + """ + self.user_idle_event.set() + + async def _handle_function_calls_started(self, _: FunctionCallsStartedFrame): + """Handle function calls started event. + + Function calls can take longer than the timeout, so we track their state + to prevent idle callbacks while they're in progress. + + Args: + frame: The FunctionCallsStartedFrame to process. + """ + self._function_call_in_progress = True + self.user_idle_event.set() + + async def _handle_function_call_result(self, _: FunctionCallResultFrame): + """Handle function call result event. + + Args: + frame: The FunctionCallResultFrame to process. + """ + self._function_call_in_progress = False + self.user_idle_event.set() + + async def user_idle_task_handler(self): + """Monitors for idle timeout and triggers events. + + Runs in a loop until cancelled. The idle timer is reset whenever activity + frames are received (UserSpeakingFrame or BotSpeakingFrame). Function calls + are tracked via state since they only send start/end frames. If no activity + is detected for the configured timeout period and no function call is in + progress, the on_user_idle event is triggered. + """ + while True: + try: + await asyncio.wait_for(self.user_idle_event.wait(), timeout=self._user_idle_timeout) + self.user_idle_event.clear() + except asyncio.TimeoutError: + # Only trigger if conversation has started and no function call is in progress + if self._conversation_started and not self._function_call_in_progress: + await self._call_event_handler("on_user_idle") diff --git a/src/pipecat/turns/user_turn_processor.py b/src/pipecat/turns/user_turn_processor.py index 79e4664a0..62693c07d 100644 --- a/src/pipecat/turns/user_turn_processor.py +++ b/src/pipecat/turns/user_turn_processor.py @@ -19,6 +19,7 @@ from pipecat.frames.frames import ( UserStoppedSpeakingFrame, ) from pipecat.processors.frame_processor import FrameDirection, FrameProcessor +from pipecat.turns.user_idle_controller import UserIdleController from pipecat.turns.user_start import BaseUserTurnStartStrategy, UserTurnStartedParams from pipecat.turns.user_stop import BaseUserTurnStopStrategy, UserTurnStoppedParams from pipecat.turns.user_turn_controller import UserTurnController @@ -38,6 +39,7 @@ class UserTurnProcessor(FrameProcessor): - on_user_turn_started: Emitted when a user turn starts. - on_user_turn_stopped: Emitted when a user turn stops. - on_user_turn_stop_timeout: Emitted if no stop strategy triggers before timeout. + - on_user_idle: Emitted when the user has been idle for the configured timeout. Example:: @@ -53,6 +55,10 @@ class UserTurnProcessor(FrameProcessor): async def on_user_turn_stop_timeout(processor): ... + @processor.event_handler("on_user_idle") + async def on_user_idle(processor): + ... + """ def __init__( @@ -60,6 +66,7 @@ class UserTurnProcessor(FrameProcessor): *, user_turn_strategies: Optional[UserTurnStrategies] = None, user_turn_stop_timeout: float = 5.0, + user_idle_timeout: Optional[float] = None, **kwargs, ): """Initialize the user turn processor. @@ -68,6 +75,10 @@ class UserTurnProcessor(FrameProcessor): user_turn_strategies: Configured strategies for starting and stopping user turns. user_turn_stop_timeout: Timeout in seconds to automatically stop a user turn if no activity is detected. + user_idle_timeout: Optional timeout in seconds for detecting user idle state. + If set, the processor will emit an `on_user_idle` event when the user + has been idle (not speaking) for this duration. Set to None to disable + idle detection. **kwargs: Additional keyword arguments. """ super().__init__(**kwargs) @@ -75,6 +86,7 @@ class UserTurnProcessor(FrameProcessor): self._register_event_handler("on_user_turn_started") self._register_event_handler("on_user_turn_stopped") self._register_event_handler("on_user_turn_stop_timeout") + self._register_event_handler("on_user_idle") self._user_turn_controller = UserTurnController( user_turn_strategies=user_turn_strategies or UserTurnStrategies(), @@ -92,6 +104,12 @@ class UserTurnProcessor(FrameProcessor): "on_user_turn_stop_timeout", self._on_user_turn_stop_timeout ) + # Optional user idle controller + self._user_idle_controller: Optional[UserIdleController] = None + if user_idle_timeout: + self._user_idle_controller = UserIdleController(user_idle_timeout=user_idle_timeout) + self._user_idle_controller.add_event_handler("on_user_idle", self._on_user_idle) + async def cleanup(self): """Clean up processor resources.""" await super().cleanup() @@ -129,9 +147,15 @@ class UserTurnProcessor(FrameProcessor): await self._user_turn_controller.process_frame(frame) + if self._user_idle_controller: + await self._user_idle_controller.process_frame(frame) + async def _start(self, frame: StartFrame): await self._user_turn_controller.setup(self.task_manager) + if self._user_idle_controller: + await self._user_idle_controller.setup(self.task_manager) + async def _stop(self, frame: EndFrame): await self._cleanup() @@ -141,6 +165,9 @@ class UserTurnProcessor(FrameProcessor): async def _cleanup(self): await self._user_turn_controller.cleanup() + if self._user_idle_controller: + await self._user_idle_controller.cleanup() + async def _on_push_frame( self, controller, frame: Frame, direction: FrameDirection = FrameDirection.DOWNSTREAM ): @@ -180,3 +207,6 @@ class UserTurnProcessor(FrameProcessor): async def _on_user_turn_stop_timeout(self, controller): await self._call_event_handler("on_user_turn_stop_timeout") + + async def _on_user_idle(self, controller): + await self._call_event_handler("on_user_idle") diff --git a/tests/test_user_idle_controller.py b/tests/test_user_idle_controller.py new file mode 100644 index 000000000..568819eb8 --- /dev/null +++ b/tests/test_user_idle_controller.py @@ -0,0 +1,216 @@ +# +# Copyright (c) 2024-2026, Daily +# +# SPDX-License-Identifier: BSD 2-Clause License +# + +import asyncio +import unittest + +from pipecat.frames.frames import ( + BotSpeakingFrame, + FunctionCallResultFrame, + FunctionCallsStartedFrame, + UserSpeakingFrame, + UserStartedSpeakingFrame, +) +from pipecat.turns.user_idle_controller import UserIdleController +from pipecat.utils.asyncio.task_manager import TaskManager, TaskManagerParams + +USER_IDLE_TIMEOUT = 0.2 + + +class TestUserIdleController(unittest.IsolatedAsyncioTestCase): + async def asyncSetUp(self): + self.task_manager = TaskManager() + self.task_manager.setup(TaskManagerParams(loop=asyncio.get_running_loop())) + + async def test_basic_idle_detection(self): + """Test that idle event is triggered after timeout when no activity.""" + controller = UserIdleController(user_idle_timeout=USER_IDLE_TIMEOUT) + await controller.setup(self.task_manager) + + idle_triggered = False + + @controller.event_handler("on_user_idle") + async def on_user_idle(controller): + nonlocal idle_triggered + idle_triggered = True + + # Start conversation + await controller.process_frame(UserStartedSpeakingFrame()) + + # Wait for idle timeout + await asyncio.sleep(USER_IDLE_TIMEOUT + 0.1) + + self.assertTrue(idle_triggered) + + await controller.cleanup() + + async def test_user_speaking_resets_idle_timer(self): + """Test that continuous UserSpeakingFrame frames reset the idle timer.""" + controller = UserIdleController(user_idle_timeout=USER_IDLE_TIMEOUT) + await controller.setup(self.task_manager) + + idle_triggered = False + + @controller.event_handler("on_user_idle") + async def on_user_idle(controller): + nonlocal idle_triggered + idle_triggered = True + + # Start conversation + await controller.process_frame(UserStartedSpeakingFrame()) + + # Send UserSpeakingFrame continuously to reset timer + for _ in range(5): + await asyncio.sleep(USER_IDLE_TIMEOUT * 0.5) # 50% of timeout period + await controller.process_frame(UserSpeakingFrame()) + + self.assertFalse(idle_triggered) + + await controller.cleanup() + + async def test_bot_speaking_resets_idle_timer(self): + """Test that BotSpeakingFrame frames reset the idle timer.""" + controller = UserIdleController(user_idle_timeout=USER_IDLE_TIMEOUT) + await controller.setup(self.task_manager) + + idle_triggered = False + + @controller.event_handler("on_user_idle") + async def on_user_idle(controller): + nonlocal idle_triggered + idle_triggered = True + + # Start conversation + await controller.process_frame(UserStartedSpeakingFrame()) + + # Bot speaking should reset timer + for _ in range(5): + await asyncio.sleep(USER_IDLE_TIMEOUT * 0.6) # 60% of timeout + await controller.process_frame(BotSpeakingFrame()) + + self.assertFalse(idle_triggered) + + await controller.cleanup() + + async def test_function_call_prevents_idle(self): + """Test that function calls in progress prevent idle event.""" + controller = UserIdleController(user_idle_timeout=USER_IDLE_TIMEOUT) + await controller.setup(self.task_manager) + + idle_triggered = False + + @controller.event_handler("on_user_idle") + async def on_user_idle(controller): + nonlocal idle_triggered + idle_triggered = True + + # Start conversation + await controller.process_frame(UserStartedSpeakingFrame()) + + # Start function call + await controller.process_frame(FunctionCallsStartedFrame(function_calls=[])) + + # Wait longer than idle timeout + await asyncio.sleep(USER_IDLE_TIMEOUT + 0.1) + + # Should not trigger idle because function call is in progress + self.assertFalse(idle_triggered) + + # Complete function call + await controller.process_frame( + FunctionCallResultFrame( + function_name="test", + tool_call_id="123", + arguments={}, + result=None, + run_llm=False, + ) + ) + + # Now idle should trigger + await asyncio.sleep(USER_IDLE_TIMEOUT + 0.1) + self.assertTrue(idle_triggered) + + await controller.cleanup() + + async def test_no_idle_before_conversation_starts(self): + """Test that idle monitoring doesn't start before first conversation activity.""" + controller = UserIdleController(user_idle_timeout=USER_IDLE_TIMEOUT) + await controller.setup(self.task_manager) + + idle_triggered = False + + @controller.event_handler("on_user_idle") + async def on_user_idle(controller): + nonlocal idle_triggered + idle_triggered = True + + # Wait without starting conversation + await asyncio.sleep(USER_IDLE_TIMEOUT + 0.1) + + self.assertFalse(idle_triggered) + + await controller.cleanup() + + async def test_idle_starts_with_bot_speaking(self): + """Test that monitoring starts with BotSpeakingFrame, not just user speech.""" + controller = UserIdleController(user_idle_timeout=USER_IDLE_TIMEOUT) + await controller.setup(self.task_manager) + + idle_triggered = False + + @controller.event_handler("on_user_idle") + async def on_user_idle(controller): + nonlocal idle_triggered + idle_triggered = True + + # Start conversation with bot speaking + await controller.process_frame(BotSpeakingFrame()) + + # Wait for idle timeout + await asyncio.sleep(USER_IDLE_TIMEOUT + 0.1) + + self.assertTrue(idle_triggered) + + await controller.cleanup() + + async def test_multiple_idle_events(self): + """Test that idle event can trigger multiple times.""" + controller = UserIdleController(user_idle_timeout=USER_IDLE_TIMEOUT) + await controller.setup(self.task_manager) + + idle_count = 0 + + @controller.event_handler("on_user_idle") + async def on_user_idle(controller): + nonlocal idle_count + idle_count += 1 + + # Start conversation + await controller.process_frame(UserStartedSpeakingFrame()) + + # First idle + await asyncio.sleep(USER_IDLE_TIMEOUT + 0.1) + first_count = idle_count + self.assertGreaterEqual(first_count, 1) + + # Second idle + await asyncio.sleep(USER_IDLE_TIMEOUT + 0.1) + second_count = idle_count + self.assertGreater(second_count, first_count) + + # User activity resets timer + await controller.process_frame(UserSpeakingFrame()) + + # Give a moment for the timer to reset + await asyncio.sleep(0.1) + + # Third idle + await asyncio.sleep(USER_IDLE_TIMEOUT + 0.1) + third_count = idle_count + self.assertGreater(third_count, second_count) + + await controller.cleanup() From 2114abb8c68839bdc6b86ead58668e791e42aad6 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Aleix=20Conchillo=20Flaqu=C3=A9?= Date: Fri, 16 Jan 2026 15:46:29 -0800 Subject: [PATCH 0119/1060] add changelog file for 3484 --- changelog/3484.fixed.md | 1 + 1 file changed, 1 insertion(+) create mode 100644 changelog/3484.fixed.md diff --git a/changelog/3484.fixed.md b/changelog/3484.fixed.md new file mode 100644 index 000000000..9f2823a3e --- /dev/null +++ b/changelog/3484.fixed.md @@ -0,0 +1 @@ +- Fixed a `Mem0MemoryService` issue where passing `async_mode: true` was causing an error. See https://docs.mem0.ai/platform/features/async-mode-default-change. From 6fa797c8e48e7efe89f64b27da81cfbbc7860721 Mon Sep 17 00:00:00 2001 From: Paul Kompfner Date: Fri, 16 Jan 2026 22:01:39 -0500 Subject: [PATCH 0120/1060] Fix AWS Nova Sonic `reset_conversation()`, which would previously error out. Issues: - After disconnecting, we were prematurely sending audio messages using the new prompt and content names, before the new prompt and content were created - We weren't properly sending system instruction and conversation history messages to Nova Sonic with `"interactive": false` --- src/pipecat/services/aws/nova_sonic/llm.py | 29 ++++++++++++++++++---- 1 file changed, 24 insertions(+), 5 deletions(-) diff --git a/src/pipecat/services/aws/nova_sonic/llm.py b/src/pipecat/services/aws/nova_sonic/llm.py index fbcbe292e..e159ae9f6 100644 --- a/src/pipecat/services/aws/nova_sonic/llm.py +++ b/src/pipecat/services/aws/nova_sonic/llm.py @@ -296,6 +296,7 @@ class AWSNovaSonicLLMService(LLMService): self._user_text_buffer = "" self._assistant_text_buffer = "" self._completed_tool_calls = set() + self._audio_input_started = False file_path = files("pipecat.services.aws.nova_sonic").joinpath("ready.wav") with wave.open(file_path.open("rb"), "rb") as wav_file: @@ -533,9 +534,16 @@ class AWSNovaSonicLLMService(LLMService): await self._send_text_event(text=system_instruction, role=Role.SYSTEM) # Send conversation history - for message in llm_connection_params["messages"]: + messages = llm_connection_params["messages"] + for i, message in enumerate(messages): # logger.debug(f"Seeding conversation history with message: {message}") - await self._send_text_event(text=message.text, role=message.role) + # If last message is from user, mark it as interactive to trigger + # bot response + is_last_message = i == len(messages) - 1 + interactive = is_last_message and message.role == Role.USER + await self._send_text_event( + text=message.text, role=message.role, interactive=interactive + ) # Start audio input await self._send_audio_input_start_event() @@ -602,6 +610,7 @@ class AWSNovaSonicLLMService(LLMService): self._user_text_buffer = "" self._assistant_text_buffer = "" self._completed_tool_calls = set() + self._audio_input_started = False logger.info("Finished disconnecting") except Exception as e: @@ -727,8 +736,18 @@ class AWSNovaSonicLLMService(LLMService): }} ''' await self._send_client_event(audio_content_start) + self._audio_input_started = True - async def _send_text_event(self, text: str, role: Role): + async def _send_text_event(self, text: str, role: Role, interactive: bool = False): + """Send a text event to the LLM. + + Args: + text: The text content to send. + role: The role associated with the text (e.g., USER, ASSISTANT, SYSTEM). + interactive: Whether the content is interactive. Defaults to False. + False: conversation history or system instruction, sent prior to interactive audio + True: text input sent during (or at the start of) interactive audio + """ if not self._stream or not self._prompt_name or not text: return @@ -741,7 +760,7 @@ class AWSNovaSonicLLMService(LLMService): "promptName": "{self._prompt_name}", "contentName": "{content_name}", "type": "TEXT", - "interactive": true, + "interactive": {json.dumps(interactive)}, "role": "{role.value}", "textInputConfiguration": {{ "mediaType": "text/plain" @@ -779,7 +798,7 @@ class AWSNovaSonicLLMService(LLMService): await self._send_client_event(text_content_end) async def _send_user_audio_event(self, audio: bytes): - if not self._stream: + if not self._stream or not self._audio_input_started: return blob = base64.b64encode(audio) From 1e1160906efe998845b43b02c5553a0986b1efed Mon Sep 17 00:00:00 2001 From: Mark Backman Date: Sat, 17 Jan 2026 06:56:08 -0500 Subject: [PATCH 0121/1060] Update on_user_idle to on_user_turn_idle --- changelog/3482.added.md | 2 +- examples/foundational/17-detect-user-idle.py | 7 ++--- .../aggregators/llm_response_universal.py | 18 ++++++------ src/pipecat/turns/user_idle_controller.py | 12 ++++---- src/pipecat/turns/user_turn_processor.py | 18 ++++++------ tests/test_user_idle_controller.py | 28 +++++++++---------- 6 files changed, 44 insertions(+), 41 deletions(-) diff --git a/changelog/3482.added.md b/changelog/3482.added.md index 35522f36c..465d409f4 100644 --- a/changelog/3482.added.md +++ b/changelog/3482.added.md @@ -1 +1 @@ -- Added `UserIdleController` for detecting user idle state, integrated into `LLMUserAggregator` and `UserTurnProcessor` via optional `user_idle_timeout` parameter. Emits `on_user_idle` event for application-level handling. Deprecated `UserIdleProcessor` in favor of the new compositional approach. +- Added `UserIdleController` for detecting user idle state, integrated into `LLMUserAggregator` and `UserTurnProcessor` via optional `user_idle_timeout` parameter. Emits `on_user_turn_idle` event for application-level handling. Deprecated `UserIdleProcessor` in favor of the new compositional approach. diff --git a/examples/foundational/17-detect-user-idle.py b/examples/foundational/17-detect-user-idle.py index b4042c1d1..52277a584 100644 --- a/examples/foundational/17-detect-user-idle.py +++ b/examples/foundational/17-detect-user-idle.py @@ -14,7 +14,6 @@ from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnal from pipecat.audio.vad.silero import SileroVADAnalyzer from pipecat.audio.vad.vad_analyzer import VADParams from pipecat.frames.frames import ( - EndFrame, EndTaskFrame, LLMMessagesAppendFrame, LLMRunFrame, @@ -155,12 +154,12 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): # Set up idle handling with retry logic idle_handler = IdleHandler() - @user_aggregator.event_handler("on_user_idle") - async def handle_user_idle(aggregator): + @user_aggregator.event_handler("on_user_turn_idle") + async def on_user_turn_idle(aggregator): await idle_handler.handle_idle(aggregator) @user_aggregator.event_handler("on_user_turn_started") - async def handle_user_turn_started(aggregator, strategy): + async def on_user_turn_started(aggregator, strategy): idle_handler.reset() @transport.event_handler("on_client_connected") diff --git a/src/pipecat/processors/aggregators/llm_response_universal.py b/src/pipecat/processors/aggregators/llm_response_universal.py index 4b0e89008..eeccd18af 100644 --- a/src/pipecat/processors/aggregators/llm_response_universal.py +++ b/src/pipecat/processors/aggregators/llm_response_universal.py @@ -82,7 +82,7 @@ class LLMUserAggregatorParams: user_turn_stop_timeout: Time in seconds to wait before considering the user's turn finished. user_idle_timeout: Optional timeout in seconds for detecting user idle state. - If set, the aggregator will emit an `on_user_idle` event when the user + If set, the aggregator will emit an `on_user_turn_idle` event when the user has been idle (not speaking) for this duration. Set to None to disable idle detection. """ @@ -297,7 +297,7 @@ class LLMUserAggregator(LLMContextAggregator): - on_user_turn_started: Called when the user turn starts - on_user_turn_stopped: Called when the user turn ends - on_user_turn_stop_timeout: Called when no user turn stop strategy triggers - - on_user_idle: Called when the user has been idle for the configured timeout + - on_user_turn_idle: Called when the user has been idle for the configured timeout Example:: @@ -313,8 +313,8 @@ class LLMUserAggregator(LLMContextAggregator): async def on_user_turn_stop_timeout(aggregator): ... - @aggregator.event_handler("on_user_idle") - async def on_user_idle(aggregator): + @aggregator.event_handler("on_user_turn_idle") + async def on_user_turn_idle(aggregator): ... """ @@ -339,7 +339,7 @@ class LLMUserAggregator(LLMContextAggregator): self._register_event_handler("on_user_turn_started") self._register_event_handler("on_user_turn_stopped") self._register_event_handler("on_user_turn_stop_timeout") - self._register_event_handler("on_user_idle") + self._register_event_handler("on_user_turn_idle") user_turn_strategies = self._params.user_turn_strategies or UserTurnStrategies() @@ -368,7 +368,9 @@ class LLMUserAggregator(LLMContextAggregator): self._user_idle_controller = UserIdleController( user_idle_timeout=self._params.user_idle_timeout ) - self._user_idle_controller.add_event_handler("on_user_idle", self._on_user_idle) + self._user_idle_controller.add_event_handler( + "on_user_turn_idle", self._on_user_turn_idle + ) async def cleanup(self): """Clean up processor resources.""" @@ -594,8 +596,8 @@ class LLMUserAggregator(LLMContextAggregator): async def _on_user_turn_stop_timeout(self, controller): await self._call_event_handler("on_user_turn_stop_timeout") - async def _on_user_idle(self, controller): - await self._call_event_handler("on_user_idle") + async def _on_user_turn_idle(self, controller): + await self._call_event_handler("on_user_turn_idle") class LLMAssistantAggregator(LLMContextAggregator): diff --git a/src/pipecat/turns/user_idle_controller.py b/src/pipecat/turns/user_idle_controller.py index 4157d6d30..cce35b9cb 100644 --- a/src/pipecat/turns/user_idle_controller.py +++ b/src/pipecat/turns/user_idle_controller.py @@ -36,12 +36,12 @@ class UserIdleController(BaseObject): Event handlers available: - - on_user_idle: Emitted when the user has been idle for the timeout period. + - on_user_turn_idle: Emitted when the user has been idle for the timeout period. Example:: - @controller.event_handler("on_user_idle") - async def on_user_idle(controller): + @controller.event_handler("on_user_turn_idle") + async def on_user_turn_idle(controller): # Handle user idle - send reminder, prompt, etc. ... """ @@ -68,7 +68,7 @@ class UserIdleController(BaseObject): self.user_idle_event = asyncio.Event() self.user_idle_task: Optional[asyncio.Task] = None - self._register_event_handler("on_user_idle", sync=True) + self._register_event_handler("on_user_turn_idle", sync=True) @property def task_manager(self) -> BaseTaskManager: @@ -161,7 +161,7 @@ class UserIdleController(BaseObject): frames are received (UserSpeakingFrame or BotSpeakingFrame). Function calls are tracked via state since they only send start/end frames. If no activity is detected for the configured timeout period and no function call is in - progress, the on_user_idle event is triggered. + progress, the on_user_turn_idle event is triggered. """ while True: try: @@ -170,4 +170,4 @@ class UserIdleController(BaseObject): except asyncio.TimeoutError: # Only trigger if conversation has started and no function call is in progress if self._conversation_started and not self._function_call_in_progress: - await self._call_event_handler("on_user_idle") + await self._call_event_handler("on_user_turn_idle") diff --git a/src/pipecat/turns/user_turn_processor.py b/src/pipecat/turns/user_turn_processor.py index 62693c07d..6c771811e 100644 --- a/src/pipecat/turns/user_turn_processor.py +++ b/src/pipecat/turns/user_turn_processor.py @@ -39,7 +39,7 @@ class UserTurnProcessor(FrameProcessor): - on_user_turn_started: Emitted when a user turn starts. - on_user_turn_stopped: Emitted when a user turn stops. - on_user_turn_stop_timeout: Emitted if no stop strategy triggers before timeout. - - on_user_idle: Emitted when the user has been idle for the configured timeout. + - on_user_turn_idle: Emitted when the user has been idle for the configured timeout. Example:: @@ -55,8 +55,8 @@ class UserTurnProcessor(FrameProcessor): async def on_user_turn_stop_timeout(processor): ... - @processor.event_handler("on_user_idle") - async def on_user_idle(processor): + @processor.event_handler("on_user_turn_idle") + async def on_user_turn_idle(processor): ... """ @@ -76,7 +76,7 @@ class UserTurnProcessor(FrameProcessor): user_turn_stop_timeout: Timeout in seconds to automatically stop a user turn if no activity is detected. user_idle_timeout: Optional timeout in seconds for detecting user idle state. - If set, the processor will emit an `on_user_idle` event when the user + If set, the processor will emit an `on_user_turn_idle` event when the user has been idle (not speaking) for this duration. Set to None to disable idle detection. **kwargs: Additional keyword arguments. @@ -86,7 +86,7 @@ class UserTurnProcessor(FrameProcessor): self._register_event_handler("on_user_turn_started") self._register_event_handler("on_user_turn_stopped") self._register_event_handler("on_user_turn_stop_timeout") - self._register_event_handler("on_user_idle") + self._register_event_handler("on_user_turn_idle") self._user_turn_controller = UserTurnController( user_turn_strategies=user_turn_strategies or UserTurnStrategies(), @@ -108,7 +108,9 @@ class UserTurnProcessor(FrameProcessor): self._user_idle_controller: Optional[UserIdleController] = None if user_idle_timeout: self._user_idle_controller = UserIdleController(user_idle_timeout=user_idle_timeout) - self._user_idle_controller.add_event_handler("on_user_idle", self._on_user_idle) + self._user_idle_controller.add_event_handler( + "on_user_turn_idle", self._on_user_turn_idle + ) async def cleanup(self): """Clean up processor resources.""" @@ -208,5 +210,5 @@ class UserTurnProcessor(FrameProcessor): async def _on_user_turn_stop_timeout(self, controller): await self._call_event_handler("on_user_turn_stop_timeout") - async def _on_user_idle(self, controller): - await self._call_event_handler("on_user_idle") + async def _on_user_turn_idle(self, controller): + await self._call_event_handler("on_user_turn_idle") diff --git a/tests/test_user_idle_controller.py b/tests/test_user_idle_controller.py index 568819eb8..5de665353 100644 --- a/tests/test_user_idle_controller.py +++ b/tests/test_user_idle_controller.py @@ -32,8 +32,8 @@ class TestUserIdleController(unittest.IsolatedAsyncioTestCase): idle_triggered = False - @controller.event_handler("on_user_idle") - async def on_user_idle(controller): + @controller.event_handler("on_user_turn_idle") + async def on_user_turn_idle(controller): nonlocal idle_triggered idle_triggered = True @@ -54,8 +54,8 @@ class TestUserIdleController(unittest.IsolatedAsyncioTestCase): idle_triggered = False - @controller.event_handler("on_user_idle") - async def on_user_idle(controller): + @controller.event_handler("on_user_turn_idle") + async def on_user_turn_idle(controller): nonlocal idle_triggered idle_triggered = True @@ -78,8 +78,8 @@ class TestUserIdleController(unittest.IsolatedAsyncioTestCase): idle_triggered = False - @controller.event_handler("on_user_idle") - async def on_user_idle(controller): + @controller.event_handler("on_user_turn_idle") + async def on_user_turn_idle(controller): nonlocal idle_triggered idle_triggered = True @@ -102,8 +102,8 @@ class TestUserIdleController(unittest.IsolatedAsyncioTestCase): idle_triggered = False - @controller.event_handler("on_user_idle") - async def on_user_idle(controller): + @controller.event_handler("on_user_turn_idle") + async def on_user_turn_idle(controller): nonlocal idle_triggered idle_triggered = True @@ -143,8 +143,8 @@ class TestUserIdleController(unittest.IsolatedAsyncioTestCase): idle_triggered = False - @controller.event_handler("on_user_idle") - async def on_user_idle(controller): + @controller.event_handler("on_user_turn_idle") + async def on_user_turn_idle(controller): nonlocal idle_triggered idle_triggered = True @@ -162,8 +162,8 @@ class TestUserIdleController(unittest.IsolatedAsyncioTestCase): idle_triggered = False - @controller.event_handler("on_user_idle") - async def on_user_idle(controller): + @controller.event_handler("on_user_turn_idle") + async def on_user_turn_idle(controller): nonlocal idle_triggered idle_triggered = True @@ -184,8 +184,8 @@ class TestUserIdleController(unittest.IsolatedAsyncioTestCase): idle_count = 0 - @controller.event_handler("on_user_idle") - async def on_user_idle(controller): + @controller.event_handler("on_user_turn_idle") + async def on_user_turn_idle(controller): nonlocal idle_count idle_count += 1 From 043403fe2354c3c76c33adee7fce90e55c1d1c46 Mon Sep 17 00:00:00 2001 From: Mark Backman Date: Sat, 17 Jan 2026 08:17:06 -0500 Subject: [PATCH 0122/1060] fix: AzureTTSService punctuation spacing --- changelog/3489.fixed.md | 1 + src/pipecat/services/azure/tts.py | 49 ++++++++++++++++++++++++++----- 2 files changed, 43 insertions(+), 7 deletions(-) create mode 100644 changelog/3489.fixed.md diff --git a/changelog/3489.fixed.md b/changelog/3489.fixed.md new file mode 100644 index 000000000..0957a9084 --- /dev/null +++ b/changelog/3489.fixed.md @@ -0,0 +1 @@ +- Fixed `AzureTTSService` transcript formatting where punctuation appeared with extra spaces (e.g., "Hello !" instead of "Hello!"). Azure sends punctuation as separate word boundaries, which are now merged with preceding words to produce properly formatted transcripts across all languages. diff --git a/src/pipecat/services/azure/tts.py b/src/pipecat/services/azure/tts.py index 751320c19..bd355a214 100644 --- a/src/pipecat/services/azure/tts.py +++ b/src/pipecat/services/azure/tts.py @@ -277,6 +277,8 @@ class AzureTTSService(WordTTSService, AzureBaseTTSService): self._started = False self._first_chunk = True self._cumulative_audio_offset: float = 0.0 # Cumulative audio duration in seconds + self._last_word: Optional[str] = None # Track last word for punctuation merging + self._last_timestamp: Optional[float] = None # Track last timestamp def can_generate_metrics(self) -> bool: """Check if this service can generate processing metrics. @@ -346,9 +348,24 @@ class AzureTTSService(WordTTSService, AzureBaseTTSService): await self.cancel_task(self._word_processor_task) self._word_processor_task = None + def _is_punctuation_only(self, text: str) -> bool: + """Check if text consists only of punctuation and whitespace. + + Args: + text: Text to check. + + Returns: + True if text is only punctuation/whitespace, False otherwise. + """ + return text and all(not c.isalnum() for c in text) + def _handle_word_boundary(self, evt): """Handle word boundary events from Azure SDK. + Azure sends punctuation as separate word boundaries, which causes + spacing issues in the final transcript. This method merges punctuation + with the previous word to maintain proper formatting. + Args: evt: SpeechSynthesisWordBoundaryEventArgs from Azure Speech SDK containing word text and audio offset timing. @@ -362,13 +379,23 @@ class AzureTTSService(WordTTSService, AzureBaseTTSService): # Add cumulative offset to get absolute timestamp across sentences absolute_seconds = self._cumulative_audio_offset + sentence_relative_seconds - # Queue word timestamp for async processing - # Use thread-safe queue since this is called from Azure SDK thread - if word: - logger.trace(f"{self}: Word boundary - '{word}' at {absolute_seconds:.2f}s") - # Put in temporary queue - will be processed by async task - # Store as (word, timestamp_in_seconds) tuple - self._word_boundary_queue.put_nowait((word, absolute_seconds)) + if not word: + return + + # Check if this is punctuation-only + is_punctuation = self._is_punctuation_only(word) + + if is_punctuation and self._last_word is not None: + # Merge punctuation with the previous word (don't queue yet, more punctuation might follow) + self._last_word += word + else: + # This is a real word. First, queue any pending word from before. + if self._last_word is not None: + self._word_boundary_queue.put_nowait((self._last_word, self._last_timestamp)) + + # Now store this new word for next time + self._last_word = word + self._last_timestamp = absolute_seconds async def _word_processor_task_handler(self): """Process word timestamps from the queue and call add_word_timestamps.""" @@ -397,6 +424,12 @@ class AzureTTSService(WordTTSService, AzureBaseTTSService): Args: evt: Completion event from Azure Speech SDK. """ + # Flush any pending word before completing + if self._last_word is not None: + self._word_boundary_queue.put_nowait((self._last_word, self._last_timestamp)) + self._last_word = None + self._last_timestamp = None + # Update cumulative audio offset for next sentence if evt.result and evt.result.audio_duration: self._cumulative_audio_offset += evt.result.audio_duration.total_seconds() @@ -435,6 +468,8 @@ class AzureTTSService(WordTTSService, AzureBaseTTSService): self._started = False self._first_chunk = True self._cumulative_audio_offset = 0.0 + self._last_word = None + self._last_timestamp = None async def flush_audio(self): """Flush any pending audio data.""" From e22bc777d815221223403855cac883de40cc8bd8 Mon Sep 17 00:00:00 2001 From: Mark Backman Date: Sat, 17 Jan 2026 09:04:50 -0500 Subject: [PATCH 0123/1060] Fix spacing for CJK languages --- changelog/3489.fixed.md | 4 +- src/pipecat/services/azure/tts.py | 90 ++++++++++++++++++++++++++----- 2 files changed, 79 insertions(+), 15 deletions(-) diff --git a/changelog/3489.fixed.md b/changelog/3489.fixed.md index 0957a9084..c61b25444 100644 --- a/changelog/3489.fixed.md +++ b/changelog/3489.fixed.md @@ -1 +1,3 @@ -- Fixed `AzureTTSService` transcript formatting where punctuation appeared with extra spaces (e.g., "Hello !" instead of "Hello!"). Azure sends punctuation as separate word boundaries, which are now merged with preceding words to produce properly formatted transcripts across all languages. +- Fixed `AzureTTSService` transcript formatting issues: + - Punctuation now appears without extra spaces (e.g., "Hello!" instead of "Hello !") + - CJK languages (Chinese, Japanese, Korean) no longer have unwanted spaces between characters diff --git a/src/pipecat/services/azure/tts.py b/src/pipecat/services/azure/tts.py index bd355a214..93c421c1e 100644 --- a/src/pipecat/services/azure/tts.py +++ b/src/pipecat/services/azure/tts.py @@ -348,6 +348,16 @@ class AzureTTSService(WordTTSService, AzureBaseTTSService): await self.cancel_task(self._word_processor_task) self._word_processor_task = None + def _is_cjk_language(self) -> bool: + """Check if the configured language is CJK (Chinese, Japanese, Korean). + + Returns: + True if the language is CJK, False otherwise. + """ + language = self._settings.get("language", "").lower() + # Check if language starts with CJK language codes + return language.startswith(("zh", "ja", "ko", "cmn", "yue", "wuu")) + def _is_punctuation_only(self, text: str) -> bool: """Check if text consists only of punctuation and whitespace. @@ -362,9 +372,9 @@ class AzureTTSService(WordTTSService, AzureBaseTTSService): def _handle_word_boundary(self, evt): """Handle word boundary events from Azure SDK. - Azure sends punctuation as separate word boundaries, which causes - spacing issues in the final transcript. This method merges punctuation - with the previous word to maintain proper formatting. + Azure sends punctuation as separate word boundaries, and breaks CJK text + into individual characters/particles. This method routes to language-specific + handlers to properly merge and emit word boundaries. Args: evt: SpeechSynthesisWordBoundaryEventArgs from Azure Speech SDK @@ -382,20 +392,72 @@ class AzureTTSService(WordTTSService, AzureBaseTTSService): if not word: return - # Check if this is punctuation-only - is_punctuation = self._is_punctuation_only(word) - - if is_punctuation and self._last_word is not None: - # Merge punctuation with the previous word (don't queue yet, more punctuation might follow) - self._last_word += word + # Route to language-specific handler + if self._is_cjk_language(): + self._handle_cjk_word_boundary(word, absolute_seconds) else: - # This is a real word. First, queue any pending word from before. - if self._last_word is not None: - self._word_boundary_queue.put_nowait((self._last_word, self._last_timestamp)) + self._handle_non_cjk_word_boundary(word, absolute_seconds) - # Now store this new word for next time + def _emit_pending_word(self): + """Emit the currently buffered word if one exists.""" + if self._last_word is not None: + self._word_boundary_queue.put_nowait((self._last_word, self._last_timestamp)) + self._last_word = None + self._last_timestamp = None + + def _handle_cjk_word_boundary(self, word: str, timestamp: float): + """Handle word boundaries for CJK languages (Chinese, Japanese, Korean). + + CJK languages don't use spaces between words, so we merge characters together + and only emit at natural break points (punctuation or whitespace boundaries). + Without this logic, we don't get word output for CJK languages. + + Args: + word: The word/character from Azure. + timestamp: Timestamp in seconds. + """ + # First word: just store it + if self._last_word is None: self._last_word = word - self._last_timestamp = absolute_seconds + self._last_timestamp = timestamp + return + + # Punctuation: merge and emit (natural break) + if self._is_punctuation_only(word): + self._last_word += word + self._emit_pending_word() + return + + # Whitespace: emit before boundary, start new segment + if word.strip() != word: + self._emit_pending_word() + self._last_word = word + self._last_timestamp = timestamp + return + + # Default: continue merging CJK characters + self._last_word += word + + def _handle_non_cjk_word_boundary(self, word: str, timestamp: float): + """Handle word boundaries for non-CJK languages. + + Non-CJK languages use spaces between words, so we emit each word separately + after merging any trailing punctuation. + + Args: + word: The word from Azure. + timestamp: Timestamp in seconds. + """ + # Punctuation: merge with previous word (don't emit yet) + if self._is_punctuation_only(word) and self._last_word is not None: + self._last_word += word + return + + # Regular word: emit previous, store current + if self._last_word is not None: + self._word_boundary_queue.put_nowait((self._last_word, self._last_timestamp)) + self._last_word = word + self._last_timestamp = timestamp async def _word_processor_task_handler(self): """Process word timestamps from the queue and call add_word_timestamps.""" From 11924bb9809ed32a37333ecebaf6993b9daeada9 Mon Sep 17 00:00:00 2001 From: Mark Backman Date: Sat, 17 Jan 2026 10:10:58 -0500 Subject: [PATCH 0124/1060] Add on_user_mute_started and on_user_mute_stopped events --- changelog/3490.added.md | 1 + examples/foundational/24-user-mute-strategy.py | 8 ++++++++ .../aggregators/llm_response_universal.py | 18 ++++++++++++++++++ 3 files changed, 27 insertions(+) create mode 100644 changelog/3490.added.md diff --git a/changelog/3490.added.md b/changelog/3490.added.md new file mode 100644 index 000000000..905d35b34 --- /dev/null +++ b/changelog/3490.added.md @@ -0,0 +1 @@ +- Added `on_user_mute_started` and `on_user_mute_stopped` event handlers to `LLMUserAggregator` for tracking user mute state changes. diff --git a/examples/foundational/24-user-mute-strategy.py b/examples/foundational/24-user-mute-strategy.py index 00e1ff66a..0797fc092 100644 --- a/examples/foundational/24-user-mute-strategy.py +++ b/examples/foundational/24-user-mute-strategy.py @@ -161,6 +161,14 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): logger.info(f"Client disconnected") await task.cancel() + @user_aggregator.event_handler("on_user_mute_started") + async def on_user_mute_started(aggregator): + logger.info(f"User mute started") + + @user_aggregator.event_handler("on_user_mute_stopped") + async def on_user_mute_stopped(aggregator): + logger.info(f"User mute stopped") + runner = PipelineRunner(handle_sigint=runner_args.handle_sigint) await runner.run(task) diff --git a/src/pipecat/processors/aggregators/llm_response_universal.py b/src/pipecat/processors/aggregators/llm_response_universal.py index fc0baf843..81dbfe844 100644 --- a/src/pipecat/processors/aggregators/llm_response_universal.py +++ b/src/pipecat/processors/aggregators/llm_response_universal.py @@ -298,6 +298,8 @@ class LLMUserAggregator(LLMContextAggregator): - on_user_turn_stopped: Called when the user turn ends - on_user_turn_stop_timeout: Called when no user turn stop strategy triggers - on_user_turn_idle: Called when the user has been idle for the configured timeout + - on_user_mute_started: Called when the user becomes muted + - on_user_mute_stopped: Called when the user becomes unmuted Example:: @@ -317,6 +319,14 @@ class LLMUserAggregator(LLMContextAggregator): async def on_user_turn_idle(aggregator): ... + @aggregator.event_handler("on_user_mute_started") + async def on_user_mute_started(aggregator): + ... + + @aggregator.event_handler("on_user_mute_stopped") + async def on_user_mute_stopped(aggregator): + ... + """ def __init__( @@ -340,6 +350,8 @@ class LLMUserAggregator(LLMContextAggregator): self._register_event_handler("on_user_turn_stopped") self._register_event_handler("on_user_turn_stop_timeout") self._register_event_handler("on_user_turn_idle") + self._register_event_handler("on_user_mute_started") + self._register_event_handler("on_user_mute_stopped") user_turn_strategies = self._params.user_turn_strategies or UserTurnStrategies() @@ -492,6 +504,12 @@ class LLMUserAggregator(LLMContextAggregator): logger.debug(f"{self}: user is now {'muted' if should_mute_next_time else 'unmuted'}") self._user_is_muted = should_mute_next_time + # Emit mute state change events + if self._user_is_muted: + await self._call_event_handler("on_user_mute_started") + else: + await self._call_event_handler("on_user_mute_stopped") + return should_mute_frame async def _handle_llm_run(self, frame: LLMRunFrame): From f48a567873bd9982e254db73bb6cfbbffde990c2 Mon Sep 17 00:00:00 2001 From: Mike Seese Date: Sat, 17 Jan 2026 10:30:47 -0800 Subject: [PATCH 0125/1060] run the linter --- src/pipecat/services/hathora/stt.py | 3 ++- src/pipecat/services/hathora/tts.py | 3 ++- 2 files changed, 4 insertions(+), 2 deletions(-) diff --git a/src/pipecat/services/hathora/stt.py b/src/pipecat/services/hathora/stt.py index b9de7ac8d..8aadb6b65 100644 --- a/src/pipecat/services/hathora/stt.py +++ b/src/pipecat/services/hathora/stt.py @@ -123,7 +123,8 @@ class HathoraSTTService(SegmentedSTTService): payload["language"] = self._settings["language"] if self._settings["config"] is not None: payload["model_config"] = [ - {"name": option.name, "value": option.value} for option in self._settings["config"] + {"name": option.name, "value": option.value} + for option in self._settings["config"] ] base64_audio = base64.b64encode(audio).decode("utf-8") diff --git a/src/pipecat/services/hathora/tts.py b/src/pipecat/services/hathora/tts.py index 43c1cfeca..e59c4ad46 100644 --- a/src/pipecat/services/hathora/tts.py +++ b/src/pipecat/services/hathora/tts.py @@ -138,7 +138,8 @@ class HathoraTTSService(TTSService): payload["speed"] = self._settings["speed"] if self._settings["config"] is not None: payload["model_config"] = [ - {"name": option.name, "value": option.value} for option in self._settings["config"] + {"name": option.name, "value": option.value} + for option in self._settings["config"] ] yield TTSStartedFrame() From a3d206050df5c0f5f6653171aaadb9fe1fd44878 Mon Sep 17 00:00:00 2001 From: Mike Seese Date: Sat, 17 Jan 2026 10:31:08 -0800 Subject: [PATCH 0126/1060] move hathora example as requested --- ...7ag-interruptible-hathora.py => 07zh-interruptible-hathora.py} | 0 1 file changed, 0 insertions(+), 0 deletions(-) rename examples/foundational/{07ag-interruptible-hathora.py => 07zh-interruptible-hathora.py} (100%) diff --git a/examples/foundational/07ag-interruptible-hathora.py b/examples/foundational/07zh-interruptible-hathora.py similarity index 100% rename from examples/foundational/07ag-interruptible-hathora.py rename to examples/foundational/07zh-interruptible-hathora.py From dc8ea615d96f922195d7fd5ca41e0f875409ff57 Mon Sep 17 00:00:00 2001 From: Mike Seese Date: Sat, 17 Jan 2026 10:33:58 -0800 Subject: [PATCH 0127/1060] add hathora to run-release-evals.py --- scripts/evals/run-release-evals.py | 1 + 1 file changed, 1 insertion(+) diff --git a/scripts/evals/run-release-evals.py b/scripts/evals/run-release-evals.py index 85834f7fd..3da64dd43 100644 --- a/scripts/evals/run-release-evals.py +++ b/scripts/evals/run-release-evals.py @@ -137,6 +137,7 @@ TESTS_07 = [ # ("07zd-interruptible-aicoustics.py", EVAL_SIMPLE_MATH), ("07ze-interruptible-hume.py", EVAL_SIMPLE_MATH), ("07zf-interruptible-gradium.py", EVAL_SIMPLE_MATH), + ("07zh-interruptible-hathora.py", EVAL_SIMPLE_MATH), # Needs a local XTTS docker instance running. # ("07i-interruptible-xtts.py", EVAL_SIMPLE_MATH), # Needs a Krisp license. From 0b93c3f900bd2a290ed021ed9ef5886aed2cb6eb Mon Sep 17 00:00:00 2001 From: Mark Backman Date: Sat, 17 Jan 2026 16:27:16 -0500 Subject: [PATCH 0128/1060] Add Camb TTS to release evals --- scripts/evals/run-release-evals.py | 1 + 1 file changed, 1 insertion(+) diff --git a/scripts/evals/run-release-evals.py b/scripts/evals/run-release-evals.py index 3da64dd43..e544c732e 100644 --- a/scripts/evals/run-release-evals.py +++ b/scripts/evals/run-release-evals.py @@ -137,6 +137,7 @@ TESTS_07 = [ # ("07zd-interruptible-aicoustics.py", EVAL_SIMPLE_MATH), ("07ze-interruptible-hume.py", EVAL_SIMPLE_MATH), ("07zf-interruptible-gradium.py", EVAL_SIMPLE_MATH), + ("07zg-interruptible-camb.py", EVAL_SIMPLE_MATH), ("07zh-interruptible-hathora.py", EVAL_SIMPLE_MATH), # Needs a local XTTS docker instance running. # ("07i-interruptible-xtts.py", EVAL_SIMPLE_MATH), From ce7d823770e2f5caaca02b6a5da3cfea5a887b5a Mon Sep 17 00:00:00 2001 From: Mark Backman Date: Sun, 18 Jan 2026 08:22:22 -0500 Subject: [PATCH 0129/1060] Remove unused imports --- examples/foundational/07k-interruptible-lmnt.py | 1 - examples/foundational/07n-interruptible-gemini-image.py | 1 - examples/foundational/07p-interruptible-krisp-viva.py | 2 +- examples/foundational/11-sound-effects.py | 2 +- examples/foundational/20d-persistent-context-gemini.py | 2 +- .../foundational/20e-persistent-context-aws-nova-sonic.py | 1 - examples/foundational/39c-multiple-mcp.py | 1 - examples/foundational/49d-thinking-functions-google.py | 2 +- examples/foundational/51-grok-realtime.py | 2 -- src/pipecat/adapters/services/bedrock_adapter.py | 2 +- src/pipecat/adapters/services/gemini_adapter.py | 2 +- src/pipecat/adapters/services/open_ai_adapter.py | 2 -- src/pipecat/audio/filters/krisp_viva_filter.py | 1 - src/pipecat/processors/aggregators/openai_llm_context.py | 1 - src/pipecat/processors/filters/wake_check_filter.py | 2 +- src/pipecat/services/aws/stt.py | 1 - src/pipecat/services/aws/tts.py | 1 - src/pipecat/services/azure/common.py | 2 -- src/pipecat/services/azure/image.py | 1 - src/pipecat/services/cerebras/llm.py | 2 -- src/pipecat/services/deepgram/flux/stt.py | 1 - src/pipecat/services/deepseek/llm.py | 2 -- src/pipecat/services/fireworks/llm.py | 2 -- src/pipecat/services/google/llm.py | 1 - src/pipecat/services/google/rtvi.py | 2 -- src/pipecat/services/google/stt.py | 1 - src/pipecat/services/gradium/tts.py | 1 - src/pipecat/services/hume/tts.py | 1 - src/pipecat/services/mem0/memory.py | 2 +- src/pipecat/services/mistral/llm.py | 4 +--- src/pipecat/services/openpipe/llm.py | 2 +- src/pipecat/services/ultravox/llm.py | 1 - src/pipecat/sync/base_notifier.py | 2 -- src/pipecat/sync/event_notifier.py | 2 -- .../turns/user_stop/turn_analyzer_user_turn_stop_strategy.py | 1 - src/pipecat/utils/text/skip_tags_aggregator.py | 2 +- .../integration/test_integration_unified_function_calling.py | 1 - tests/test_get_llm_invocation_params.py | 2 -- tests/test_rnnoise_filter.py | 2 +- tests/test_rnnoise_resampling.py | 1 - tests/test_stt_mute_filter.py | 1 - 41 files changed, 12 insertions(+), 53 deletions(-) diff --git a/examples/foundational/07k-interruptible-lmnt.py b/examples/foundational/07k-interruptible-lmnt.py index 43618f84f..e616543a3 100644 --- a/examples/foundational/07k-interruptible-lmnt.py +++ b/examples/foundational/07k-interruptible-lmnt.py @@ -10,7 +10,6 @@ import os from dotenv import load_dotenv from loguru import logger -from pipecat.audio.turn.smart_turn.base_smart_turn import SmartTurnParams from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3 from pipecat.audio.vad.silero import SileroVADAnalyzer from pipecat.audio.vad.vad_analyzer import VADParams diff --git a/examples/foundational/07n-interruptible-gemini-image.py b/examples/foundational/07n-interruptible-gemini-image.py index a465724f2..f32aebee1 100644 --- a/examples/foundational/07n-interruptible-gemini-image.py +++ b/examples/foundational/07n-interruptible-gemini-image.py @@ -45,7 +45,6 @@ from pipecat.services.google.tts import GoogleTTSService from pipecat.transcriptions.language import Language from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams -from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams from pipecat.turns.user_stop import TurnAnalyzerUserTurnStopStrategy from pipecat.turns.user_turn_strategies import UserTurnStrategies diff --git a/examples/foundational/07p-interruptible-krisp-viva.py b/examples/foundational/07p-interruptible-krisp-viva.py index be336f003..fd899f213 100644 --- a/examples/foundational/07p-interruptible-krisp-viva.py +++ b/examples/foundational/07p-interruptible-krisp-viva.py @@ -28,7 +28,7 @@ from dotenv import load_dotenv from loguru import logger from pipecat.audio.filters.krisp_viva_filter import KrispVivaFilter -from pipecat.audio.turn.krisp_viva_turn import KrispTurnParams, KrispVivaTurn +from pipecat.audio.turn.krisp_viva_turn import KrispVivaTurn from pipecat.audio.vad.silero import SileroVADAnalyzer from pipecat.audio.vad.vad_analyzer import VADParams from pipecat.frames.frames import LLMRunFrame diff --git a/examples/foundational/11-sound-effects.py b/examples/foundational/11-sound-effects.py index 8201790ac..b517cf447 100644 --- a/examples/foundational/11-sound-effects.py +++ b/examples/foundational/11-sound-effects.py @@ -22,7 +22,7 @@ from pipecat.frames.frames import ( ) from pipecat.pipeline.pipeline import Pipeline from pipecat.pipeline.runner import PipelineRunner -from pipecat.pipeline.task import PipelineParams, PipelineTask +from pipecat.pipeline.task import PipelineTask from pipecat.processors.aggregators.llm_context import LLMContext from pipecat.processors.aggregators.llm_response_universal import ( LLMContextAggregatorPair, diff --git a/examples/foundational/20d-persistent-context-gemini.py b/examples/foundational/20d-persistent-context-gemini.py index a29eb5cf9..e0e2949a3 100644 --- a/examples/foundational/20d-persistent-context-gemini.py +++ b/examples/foundational/20d-persistent-context-gemini.py @@ -17,7 +17,7 @@ from pipecat.adapters.schemas.tools_schema import ToolsSchema from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3 from pipecat.audio.vad.silero import SileroVADAnalyzer from pipecat.audio.vad.vad_analyzer import VADParams -from pipecat.frames.frames import LLMRunFrame, TTSSpeakFrame, UserImageRequestFrame +from pipecat.frames.frames import LLMRunFrame, UserImageRequestFrame from pipecat.pipeline.pipeline import Pipeline from pipecat.pipeline.runner import PipelineRunner from pipecat.pipeline.task import PipelineParams, PipelineTask diff --git a/examples/foundational/20e-persistent-context-aws-nova-sonic.py b/examples/foundational/20e-persistent-context-aws-nova-sonic.py index bd95fb7e7..5b8a256ef 100644 --- a/examples/foundational/20e-persistent-context-aws-nova-sonic.py +++ b/examples/foundational/20e-persistent-context-aws-nova-sonic.py @@ -22,7 +22,6 @@ from pipecat.pipeline.runner import PipelineRunner from pipecat.pipeline.task import PipelineParams, PipelineTask from pipecat.processors.aggregators.llm_context import LLMContext from pipecat.processors.aggregators.llm_response_universal import LLMContextAggregatorPair -from pipecat.processors.aggregators.openai_llm_context import OpenAILLMContext from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport from pipecat.services.aws.nova_sonic.llm import AWSNovaSonicLLMService diff --git a/examples/foundational/39c-multiple-mcp.py b/examples/foundational/39c-multiple-mcp.py index 6141b371e..05cbe2b22 100644 --- a/examples/foundational/39c-multiple-mcp.py +++ b/examples/foundational/39c-multiple-mcp.py @@ -9,7 +9,6 @@ import asyncio import io import json import os -import re import shutil import aiohttp diff --git a/examples/foundational/49d-thinking-functions-google.py b/examples/foundational/49d-thinking-functions-google.py index 1a74da3ff..e00c3d00f 100644 --- a/examples/foundational/49d-thinking-functions-google.py +++ b/examples/foundational/49d-thinking-functions-google.py @@ -13,7 +13,7 @@ from pipecat.adapters.schemas.tools_schema import ToolsSchema from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3 from pipecat.audio.vad.silero import SileroVADAnalyzer from pipecat.audio.vad.vad_analyzer import VADParams -from pipecat.frames.frames import LLMRunFrame, ThoughtTranscriptionMessage, TranscriptionMessage +from pipecat.frames.frames import LLMRunFrame from pipecat.pipeline.pipeline import Pipeline from pipecat.pipeline.runner import PipelineRunner from pipecat.pipeline.task import PipelineParams, PipelineTask diff --git a/examples/foundational/51-grok-realtime.py b/examples/foundational/51-grok-realtime.py index 6a2fbe5a2..87486a0de 100644 --- a/examples/foundational/51-grok-realtime.py +++ b/examples/foundational/51-grok-realtime.py @@ -53,8 +53,6 @@ from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport from pipecat.services.grok.realtime.events import ( SessionProperties, - WebSearchTool, - XSearchTool, ) from pipecat.services.grok.realtime.llm import GrokRealtimeLLMService from pipecat.services.llm_service import FunctionCallParams diff --git a/src/pipecat/adapters/services/bedrock_adapter.py b/src/pipecat/adapters/services/bedrock_adapter.py index 8e46b1899..ccbbe5e2e 100644 --- a/src/pipecat/adapters/services/bedrock_adapter.py +++ b/src/pipecat/adapters/services/bedrock_adapter.py @@ -10,7 +10,7 @@ import base64 import copy import json from dataclasses import dataclass -from typing import Any, Dict, List, Literal, Optional, TypedDict +from typing import Any, Dict, List, Optional, TypedDict from loguru import logger diff --git a/src/pipecat/adapters/services/gemini_adapter.py b/src/pipecat/adapters/services/gemini_adapter.py index 2de3742c8..4968c2719 100644 --- a/src/pipecat/adapters/services/gemini_adapter.py +++ b/src/pipecat/adapters/services/gemini_adapter.py @@ -9,7 +9,7 @@ import base64 import json from dataclasses import dataclass, field -from typing import Any, Dict, List, Optional, Tuple, TypedDict +from typing import Any, Dict, List, Optional, TypedDict from loguru import logger from openai import NotGiven diff --git a/src/pipecat/adapters/services/open_ai_adapter.py b/src/pipecat/adapters/services/open_ai_adapter.py index 6c44a3404..f4b534f2c 100644 --- a/src/pipecat/adapters/services/open_ai_adapter.py +++ b/src/pipecat/adapters/services/open_ai_adapter.py @@ -7,10 +7,8 @@ """OpenAI LLM adapter for Pipecat.""" import copy -import json from typing import Any, Dict, List, TypedDict -from openai._types import NOT_GIVEN as OPEN_AI_NOT_GIVEN from openai._types import NotGiven as OpenAINotGiven from openai.types.chat import ( ChatCompletionMessageParam, diff --git a/src/pipecat/audio/filters/krisp_viva_filter.py b/src/pipecat/audio/filters/krisp_viva_filter.py index 2f9dda10f..ea5bfb8de 100644 --- a/src/pipecat/audio/filters/krisp_viva_filter.py +++ b/src/pipecat/audio/filters/krisp_viva_filter.py @@ -9,7 +9,6 @@ This module provides an audio filter implementation using Krisp VIVA SDK. """ -import asyncio import os import numpy as np diff --git a/src/pipecat/processors/aggregators/openai_llm_context.py b/src/pipecat/processors/aggregators/openai_llm_context.py index 41df3b5e8..f75625156 100644 --- a/src/pipecat/processors/aggregators/openai_llm_context.py +++ b/src/pipecat/processors/aggregators/openai_llm_context.py @@ -34,7 +34,6 @@ from PIL import Image from pipecat.adapters.base_llm_adapter import BaseLLMAdapter from pipecat.adapters.schemas.tools_schema import ToolsSchema from pipecat.frames.frames import AudioRawFrame, Frame -from pipecat.processors.frame_processor import FrameDirection, FrameProcessor # JSON custom encoder to handle bytes arrays so that we can log contexts # with images to the console. diff --git a/src/pipecat/processors/filters/wake_check_filter.py b/src/pipecat/processors/filters/wake_check_filter.py index 792c4a68d..ec8f31f53 100644 --- a/src/pipecat/processors/filters/wake_check_filter.py +++ b/src/pipecat/processors/filters/wake_check_filter.py @@ -18,7 +18,7 @@ from typing import List from loguru import logger -from pipecat.frames.frames import ErrorFrame, Frame, TranscriptionFrame +from pipecat.frames.frames import Frame, TranscriptionFrame from pipecat.processors.frame_processor import FrameDirection, FrameProcessor diff --git a/src/pipecat/services/aws/stt.py b/src/pipecat/services/aws/stt.py index 2ad350a96..5ae99b02f 100644 --- a/src/pipecat/services/aws/stt.py +++ b/src/pipecat/services/aws/stt.py @@ -10,7 +10,6 @@ This module provides a WebSocket-based connection to AWS Transcribe for real-tim speech-to-text transcription with support for multiple languages and audio formats. """ -import asyncio import json import os import random diff --git a/src/pipecat/services/aws/tts.py b/src/pipecat/services/aws/tts.py index 0df2dabd9..358a894c7 100644 --- a/src/pipecat/services/aws/tts.py +++ b/src/pipecat/services/aws/tts.py @@ -10,7 +10,6 @@ This module provides integration with Amazon Polly for text-to-speech synthesis, supporting multiple languages, voices, and SSML features. """ -import asyncio import os from typing import AsyncGenerator, List, Optional diff --git a/src/pipecat/services/azure/common.py b/src/pipecat/services/azure/common.py index f867d4e5d..dc7aaa359 100644 --- a/src/pipecat/services/azure/common.py +++ b/src/pipecat/services/azure/common.py @@ -8,8 +8,6 @@ from typing import Optional -from loguru import logger - from pipecat.transcriptions.language import Language, resolve_language diff --git a/src/pipecat/services/azure/image.py b/src/pipecat/services/azure/image.py index b33d8cc7d..2bddf6c43 100644 --- a/src/pipecat/services/azure/image.py +++ b/src/pipecat/services/azure/image.py @@ -15,7 +15,6 @@ import io from typing import AsyncGenerator import aiohttp -from loguru import logger from PIL import Image from pipecat.frames.frames import ErrorFrame, Frame, URLImageRawFrame diff --git a/src/pipecat/services/cerebras/llm.py b/src/pipecat/services/cerebras/llm.py index 9ceb48905..54ea45ddb 100644 --- a/src/pipecat/services/cerebras/llm.py +++ b/src/pipecat/services/cerebras/llm.py @@ -6,8 +6,6 @@ """Cerebras LLM service implementation using OpenAI-compatible interface.""" -from typing import List - from loguru import logger from pipecat.adapters.services.open_ai_adapter import OpenAILLMInvocationParams diff --git a/src/pipecat/services/deepgram/flux/stt.py b/src/pipecat/services/deepgram/flux/stt.py index 35b00af65..045af9811 100644 --- a/src/pipecat/services/deepgram/flux/stt.py +++ b/src/pipecat/services/deepgram/flux/stt.py @@ -27,7 +27,6 @@ from pipecat.frames.frames import ( UserStartedSpeakingFrame, UserStoppedSpeakingFrame, ) -from pipecat.processors.frame_processor import FrameDirection from pipecat.services.stt_service import WebsocketSTTService from pipecat.transcriptions.language import Language from pipecat.utils.time import time_now_iso8601 diff --git a/src/pipecat/services/deepseek/llm.py b/src/pipecat/services/deepseek/llm.py index 50bdebd3b..56f1ddd18 100644 --- a/src/pipecat/services/deepseek/llm.py +++ b/src/pipecat/services/deepseek/llm.py @@ -6,8 +6,6 @@ """DeepSeek LLM service implementation using OpenAI-compatible interface.""" -from typing import List - from loguru import logger from pipecat.adapters.services.open_ai_adapter import OpenAILLMInvocationParams diff --git a/src/pipecat/services/fireworks/llm.py b/src/pipecat/services/fireworks/llm.py index 92467786f..d7bf57908 100644 --- a/src/pipecat/services/fireworks/llm.py +++ b/src/pipecat/services/fireworks/llm.py @@ -6,8 +6,6 @@ """Fireworks AI service implementation using OpenAI-compatible interface.""" -from typing import List - from loguru import logger from pipecat.adapters.services.open_ai_adapter import OpenAILLMInvocationParams diff --git a/src/pipecat/services/google/llm.py b/src/pipecat/services/google/llm.py index 20341b64d..adb2664bb 100644 --- a/src/pipecat/services/google/llm.py +++ b/src/pipecat/services/google/llm.py @@ -40,7 +40,6 @@ from pipecat.frames.frames import ( LLMThoughtStartFrame, LLMThoughtTextFrame, LLMUpdateSettingsFrame, - OutputImageRawFrame, UserImageRawFrame, ) from pipecat.metrics.metrics import LLMTokenUsage diff --git a/src/pipecat/services/google/rtvi.py b/src/pipecat/services/google/rtvi.py index 1cc68f5e4..1ef70d67d 100644 --- a/src/pipecat/services/google/rtvi.py +++ b/src/pipecat/services/google/rtvi.py @@ -15,9 +15,7 @@ from typing import List, Literal, Optional from pydantic import BaseModel -from pipecat.frames.frames import Frame from pipecat.observers.base_observer import FramePushed -from pipecat.processors.frame_processor import FrameDirection, FrameProcessor from pipecat.processors.frameworks.rtvi import RTVIObserver, RTVIProcessor from pipecat.services.google.frames import LLMSearchOrigin, LLMSearchResponseFrame diff --git a/src/pipecat/services/google/stt.py b/src/pipecat/services/google/stt.py index ac77f0450..dcf0adf89 100644 --- a/src/pipecat/services/google/stt.py +++ b/src/pipecat/services/google/stt.py @@ -29,7 +29,6 @@ from pydantic import BaseModel, Field, field_validator from pipecat.frames.frames import ( CancelFrame, EndFrame, - ErrorFrame, Frame, InterimTranscriptionFrame, StartFrame, diff --git a/src/pipecat/services/gradium/tts.py b/src/pipecat/services/gradium/tts.py index 14e093541..df33753ce 100644 --- a/src/pipecat/services/gradium/tts.py +++ b/src/pipecat/services/gradium/tts.py @@ -6,7 +6,6 @@ import base64 import json -import uuid from typing import Any, AsyncGenerator, Mapping, Optional from loguru import logger diff --git a/src/pipecat/services/hume/tts.py b/src/pipecat/services/hume/tts.py index c169cf4c0..7f8943816 100644 --- a/src/pipecat/services/hume/tts.py +++ b/src/pipecat/services/hume/tts.py @@ -16,7 +16,6 @@ from pipecat import version as pipecat_version from pipecat.frames.frames import ( CancelFrame, EndFrame, - ErrorFrame, Frame, InterruptionFrame, StartFrame, diff --git a/src/pipecat/services/mem0/memory.py b/src/pipecat/services/mem0/memory.py index d0c8e66dc..c4dfe16de 100644 --- a/src/pipecat/services/mem0/memory.py +++ b/src/pipecat/services/mem0/memory.py @@ -16,7 +16,7 @@ from typing import Any, Dict, List, Optional from loguru import logger from pydantic import BaseModel, Field -from pipecat.frames.frames import ErrorFrame, Frame, LLMContextFrame, LLMMessagesFrame +from pipecat.frames.frames import Frame, LLMContextFrame, LLMMessagesFrame from pipecat.processors.aggregators.llm_context import LLMContext from pipecat.processors.aggregators.openai_llm_context import ( OpenAILLMContext, diff --git a/src/pipecat/services/mistral/llm.py b/src/pipecat/services/mistral/llm.py index b95c3d1ab..54361ef28 100644 --- a/src/pipecat/services/mistral/llm.py +++ b/src/pipecat/services/mistral/llm.py @@ -9,12 +9,10 @@ from typing import List, Sequence from loguru import logger -from openai import AsyncStream -from openai.types.chat import ChatCompletionChunk, ChatCompletionMessageParam +from openai.types.chat import ChatCompletionMessageParam from pipecat.adapters.services.open_ai_adapter import OpenAILLMInvocationParams from pipecat.frames.frames import FunctionCallFromLLM -from pipecat.processors.aggregators.openai_llm_context import OpenAILLMContext from pipecat.services.openai.llm import OpenAILLMService diff --git a/src/pipecat/services/openpipe/llm.py b/src/pipecat/services/openpipe/llm.py index f3e95f71b..fa53c1554 100644 --- a/src/pipecat/services/openpipe/llm.py +++ b/src/pipecat/services/openpipe/llm.py @@ -10,7 +10,7 @@ This module provides an OpenPipe-specific implementation of the OpenAI LLM servi enabling integration with OpenPipe's fine-tuning and monitoring capabilities. """ -from typing import Dict, List, Optional +from typing import Dict, Optional from loguru import logger diff --git a/src/pipecat/services/ultravox/llm.py b/src/pipecat/services/ultravox/llm.py index 489ba367d..d549b11e5 100644 --- a/src/pipecat/services/ultravox/llm.py +++ b/src/pipecat/services/ultravox/llm.py @@ -19,7 +19,6 @@ from typing import Any, Dict, List, Literal, Optional, Union import aiohttp from loguru import logger -from openai.types import chat as openai_chat_types from pydantic import BaseModel, Field from pipecat.adapters.schemas.tools_schema import ToolsSchema diff --git a/src/pipecat/sync/base_notifier.py b/src/pipecat/sync/base_notifier.py index 474d50a8b..fb6e12732 100644 --- a/src/pipecat/sync/base_notifier.py +++ b/src/pipecat/sync/base_notifier.py @@ -8,8 +8,6 @@ import warnings -from pipecat.utils.sync.base_notifier import BaseNotifier - with warnings.catch_warnings(): warnings.simplefilter("always") warnings.warn( diff --git a/src/pipecat/sync/event_notifier.py b/src/pipecat/sync/event_notifier.py index 2a33cab73..6a6f6abbe 100644 --- a/src/pipecat/sync/event_notifier.py +++ b/src/pipecat/sync/event_notifier.py @@ -8,8 +8,6 @@ import warnings -from pipecat.utils.sync.event_notifier import EventNotifier - with warnings.catch_warnings(): warnings.simplefilter("always") warnings.warn( diff --git a/src/pipecat/turns/user_stop/turn_analyzer_user_turn_stop_strategy.py b/src/pipecat/turns/user_stop/turn_analyzer_user_turn_stop_strategy.py index b21177dc4..1bb266380 100644 --- a/src/pipecat/turns/user_stop/turn_analyzer_user_turn_stop_strategy.py +++ b/src/pipecat/turns/user_stop/turn_analyzer_user_turn_stop_strategy.py @@ -10,7 +10,6 @@ import asyncio from typing import Optional from pipecat.audio.turn.base_turn_analyzer import BaseTurnAnalyzer, EndOfTurnState -from pipecat.audio.turn.smart_turn.base_smart_turn import SmartTurnParams from pipecat.frames.frames import ( Frame, InputAudioRawFrame, diff --git a/src/pipecat/utils/text/skip_tags_aggregator.py b/src/pipecat/utils/text/skip_tags_aggregator.py index 1212bd34d..4232efd7d 100644 --- a/src/pipecat/utils/text/skip_tags_aggregator.py +++ b/src/pipecat/utils/text/skip_tags_aggregator.py @@ -14,7 +14,7 @@ as a unit regardless of internal punctuation. from typing import AsyncIterator, Optional, Sequence from pipecat.utils.string import StartEndTags, parse_start_end_tags -from pipecat.utils.text.base_text_aggregator import Aggregation, AggregationType +from pipecat.utils.text.base_text_aggregator import Aggregation from pipecat.utils.text.simple_text_aggregator import SimpleTextAggregator diff --git a/tests/integration/test_integration_unified_function_calling.py b/tests/integration/test_integration_unified_function_calling.py index d017c55ac..552c839a5 100644 --- a/tests/integration/test_integration_unified_function_calling.py +++ b/tests/integration/test_integration_unified_function_calling.py @@ -5,7 +5,6 @@ # import os -from unittest.mock import AsyncMock import pytest from dotenv import load_dotenv diff --git a/tests/test_get_llm_invocation_params.py b/tests/test_get_llm_invocation_params.py index ad1437227..c93275b67 100644 --- a/tests/test_get_llm_invocation_params.py +++ b/tests/test_get_llm_invocation_params.py @@ -43,7 +43,6 @@ For AWS Bedrock adapter: import unittest from google.genai.types import Content, Part -from openai.types.chat import ChatCompletionMessage from pipecat.adapters.services.anthropic_adapter import AnthropicLLMAdapter from pipecat.adapters.services.bedrock_adapter import AWSBedrockLLMAdapter @@ -51,7 +50,6 @@ from pipecat.adapters.services.gemini_adapter import GeminiLLMAdapter from pipecat.adapters.services.open_ai_adapter import OpenAILLMAdapter from pipecat.processors.aggregators.llm_context import ( LLMContext, - LLMSpecificMessage, LLMStandardMessage, ) diff --git a/tests/test_rnnoise_filter.py b/tests/test_rnnoise_filter.py index 9e53b5b47..db3ac7825 100644 --- a/tests/test_rnnoise_filter.py +++ b/tests/test_rnnoise_filter.py @@ -5,7 +5,7 @@ # import unittest -from unittest.mock import AsyncMock, MagicMock, patch +from unittest.mock import AsyncMock import numpy as np diff --git a/tests/test_rnnoise_resampling.py b/tests/test_rnnoise_resampling.py index c69419d2e..060c9e802 100644 --- a/tests/test_rnnoise_resampling.py +++ b/tests/test_rnnoise_resampling.py @@ -4,7 +4,6 @@ # SPDX-License-Identifier: BSD 2-Clause License # -import asyncio import sys import unittest from unittest.mock import MagicMock, patch diff --git a/tests/test_stt_mute_filter.py b/tests/test_stt_mute_filter.py index 459060b86..39631d7e8 100644 --- a/tests/test_stt_mute_filter.py +++ b/tests/test_stt_mute_filter.py @@ -10,7 +10,6 @@ from pipecat.frames.frames import ( BotStartedSpeakingFrame, BotStoppedSpeakingFrame, FunctionCallFromLLM, - FunctionCallInProgressFrame, FunctionCallResultFrame, FunctionCallsStartedFrame, InputAudioRawFrame, From 990d8386e480f273c825d79659af911019dae24f Mon Sep 17 00:00:00 2001 From: Om Chauhan Date: Sun, 18 Jan 2026 19:41:51 +0530 Subject: [PATCH 0130/1060] fix: make SmallWebRTCConnection pc_id globally unique --- src/pipecat/transports/smallwebrtc/connection.py | 3 ++- 1 file changed, 2 insertions(+), 1 deletion(-) diff --git a/src/pipecat/transports/smallwebrtc/connection.py b/src/pipecat/transports/smallwebrtc/connection.py index 5a5a1450d..b37d63c9a 100644 --- a/src/pipecat/transports/smallwebrtc/connection.py +++ b/src/pipecat/transports/smallwebrtc/connection.py @@ -14,6 +14,7 @@ for real-time communication applications. import asyncio import json import time +import uuid from typing import Any, List, Literal, Optional, Union from loguru import logger @@ -278,7 +279,7 @@ class SmallWebRTCConnection(BaseObject): self._answer: Optional[RTCSessionDescription] = None self._pc = RTCPeerConnection(rtc_config) - self._pc_id = self.name + self._pc_id = f"{self.name}-{uuid.uuid4().hex}" self._setup_listeners() self._data_channel = None self._renegotiation_in_progress = False From 4a9eb82f921ba77bbf2dc533f59552cca34f0f7f Mon Sep 17 00:00:00 2001 From: Om Chauhan Date: Sun, 18 Jan 2026 20:39:13 +0530 Subject: [PATCH 0131/1060] fix: preserve UninterruptibleFrames in __reset_process_queue --- src/pipecat/processors/frame_processor.py | 3 ++- 1 file changed, 2 insertions(+), 1 deletion(-) diff --git a/src/pipecat/processors/frame_processor.py b/src/pipecat/processors/frame_processor.py index 9c26fe382..70f44dfca 100644 --- a/src/pipecat/processors/frame_processor.py +++ b/src/pipecat/processors/frame_processor.py @@ -950,7 +950,8 @@ class FrameProcessor(BaseObject): # Process current queue and keep UninterruptibleFrame frames. while not self.__process_queue.empty(): item = self.__process_queue.get_nowait() - if isinstance(item, UninterruptibleFrame): + frame = item[0] + if isinstance(frame, UninterruptibleFrame): new_queue.put_nowait(item) self.__process_queue.task_done() From f733e774967d4e6e2267b39aa25e3f35d9a0716f Mon Sep 17 00:00:00 2001 From: Mark Backman Date: Mon, 19 Jan 2026 09:13:41 -0500 Subject: [PATCH 0132/1060] AzureTTS: work around word ordering issue at 8khz sample rate --- src/pipecat/services/azure/tts.py | 38 +++++++++++++++++++++++++++---- 1 file changed, 34 insertions(+), 4 deletions(-) diff --git a/src/pipecat/services/azure/tts.py b/src/pipecat/services/azure/tts.py index 93c421c1e..b9733db07 100644 --- a/src/pipecat/services/azure/tts.py +++ b/src/pipecat/services/azure/tts.py @@ -277,6 +277,11 @@ class AzureTTSService(WordTTSService, AzureBaseTTSService): self._started = False self._first_chunk = True self._cumulative_audio_offset: float = 0.0 # Cumulative audio duration in seconds + self._current_sentence_base_offset: float = 0.0 # Base offset for current sentence + self._current_sentence_duration: float = 0.0 # Duration from Azure callback + self._current_sentence_max_word_offset: float = ( + 0.0 # Max word boundary offset seen in current sentence (for 8kHz workaround) + ) self._last_word: Optional[str] = None # Track last word for punctuation merging self._last_timestamp: Optional[float] = None # Track last timestamp @@ -386,8 +391,14 @@ class AzureTTSService(WordTTSService, AzureBaseTTSService): word = evt.text sentence_relative_seconds = evt.audio_offset / 10_000_000.0 - # Add cumulative offset to get absolute timestamp across sentences - absolute_seconds = self._cumulative_audio_offset + sentence_relative_seconds + # Use base offset captured at start of run_tts to avoid race conditions + # with callbacks from overlapping TTS requests + absolute_seconds = self._current_sentence_base_offset + sentence_relative_seconds + + # Track max word offset for accurate cumulative timing + # (audio_duration from Azure doesn't always match word boundary offsets at 8kHz) + if sentence_relative_seconds > self._current_sentence_max_word_offset: + self._current_sentence_max_word_offset = sentence_relative_seconds if not word: return @@ -492,9 +503,9 @@ class AzureTTSService(WordTTSService, AzureBaseTTSService): self._last_word = None self._last_timestamp = None - # Update cumulative audio offset for next sentence + # Store duration for cumulative offset calculation if evt.result and evt.result.audio_duration: - self._cumulative_audio_offset += evt.result.audio_duration.total_seconds() + self._current_sentence_duration = evt.result.audio_duration.total_seconds() self._audio_queue.put_nowait(None) # Signal completion @@ -530,6 +541,9 @@ class AzureTTSService(WordTTSService, AzureBaseTTSService): self._started = False self._first_chunk = True self._cumulative_audio_offset = 0.0 + self._current_sentence_base_offset = 0.0 + self._current_sentence_duration = 0.0 + self._current_sentence_max_word_offset = 0.0 self._last_word = None self._last_timestamp = None @@ -604,6 +618,12 @@ class AzureTTSService(WordTTSService, AzureBaseTTSService): self._started = True self._first_chunk = True + # Capture base offset BEFORE starting synthesis to avoid race conditions + # Word boundary callbacks will use this value + self._current_sentence_base_offset = self._cumulative_audio_offset + self._current_sentence_duration = 0.0 + self._current_sentence_max_word_offset = 0.0 + ssml = self._construct_ssml(text) self._speech_synthesizer.speak_ssml_async(ssml) await self.start_tts_usage_metrics(text) @@ -627,6 +647,16 @@ class AzureTTSService(WordTTSService, AzureBaseTTSService): ) yield frame + # Update cumulative offset for next sentence + # At 8kHz, Azure's audio_duration doesn't match word boundary offsets, + # so we use max_word_offset as a workaround. At other sample rates, + # audio_duration is accurate. + # TODO: Remove after Azure fixes word boundary timing at 8kHz + if self.sample_rate == 8000: + self._cumulative_audio_offset += self._current_sentence_max_word_offset + else: + self._cumulative_audio_offset += self._current_sentence_duration + except Exception as e: yield ErrorFrame(error=f"Unknown error occurred: {e}") yield TTSStoppedFrame() From 14bd3b1b32e4486a1eadf1d92e290916b20ef867 Mon Sep 17 00:00:00 2001 From: Mark Backman Date: Mon, 19 Jan 2026 09:19:57 -0500 Subject: [PATCH 0133/1060] Set Azure TTS default prosody rate to None --- src/pipecat/services/azure/tts.py | 11 +++++++---- 1 file changed, 7 insertions(+), 4 deletions(-) diff --git a/src/pipecat/services/azure/tts.py b/src/pipecat/services/azure/tts.py index b9733db07..dc0c56e7b 100644 --- a/src/pipecat/services/azure/tts.py +++ b/src/pipecat/services/azure/tts.py @@ -90,7 +90,7 @@ class AzureBaseTTSService: emphasis: Emphasis level for speech ("strong", "moderate", "reduced"). language: Language for synthesis. Defaults to English (US). pitch: Voice pitch adjustment (e.g., "+10%", "-5Hz", "high"). - rate: Speech rate multiplier. Defaults to "1.05". + rate: Speech rate adjustment (e.g., "1.0", "1.25", "slow", "fast"). role: Voice role for expression (e.g., "YoungAdultFemale"). style: Speaking style (e.g., "cheerful", "sad", "excited"). style_degree: Intensity of the speaking style (0.01 to 2.0). @@ -100,7 +100,7 @@ class AzureBaseTTSService: emphasis: Optional[str] = None language: Optional[Language] = Language.EN_US pitch: Optional[str] = None - rate: Optional[str] = "1.05" + rate: Optional[str] = None role: Optional[str] = None style: Optional[str] = None style_degree: Optional[str] = None @@ -185,7 +185,9 @@ class AzureBaseTTSService: if self._settings["volume"]: prosody_attrs.append(f"volume='{self._settings['volume']}'") - ssml += f"" + # Only wrap in prosody tag if there are prosody attributes + if prosody_attrs: + ssml += f"" if self._settings["emphasis"]: ssml += f"" @@ -195,7 +197,8 @@ class AzureBaseTTSService: if self._settings["emphasis"]: ssml += "" - ssml += "" + if prosody_attrs: + ssml += "" if self._settings["style"]: ssml += "" From 0b1a4792b8d2971e8fa97576e35a413e48ceff27 Mon Sep 17 00:00:00 2001 From: Mark Backman Date: Mon, 19 Jan 2026 09:51:39 -0500 Subject: [PATCH 0134/1060] Bump to latest azure-cognitiveservices-speech version, 1.47.0 --- pyproject.toml | 2 +- uv.lock | 16 ++++++++-------- 2 files changed, 9 insertions(+), 9 deletions(-) diff --git a/pyproject.toml b/pyproject.toml index e99ab62bc..0cb985f34 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -54,7 +54,7 @@ assemblyai = [ "pipecat-ai[websockets-base]" ] asyncai = [ "pipecat-ai[websockets-base]" ] aws = [ "aioboto3~=15.5.0", "pipecat-ai[websockets-base]" ] aws-nova-sonic = [ "aws_sdk_bedrock_runtime~=0.2.0; python_version>='3.12'" ] -azure = [ "azure-cognitiveservices-speech~=1.44.0"] +azure = [ "azure-cognitiveservices-speech~=1.47.0"] cartesia = [ "cartesia~=2.0.3", "pipecat-ai[websockets-base]" ] camb = [ "camb-sdk>=1.5.4" ] cerebras = [] diff --git a/uv.lock b/uv.lock index 45c1f892f..0ca04667a 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marker = "extra == 'cartesia'", specifier = "~=2.0.3" }, { name = "coremltools", marker = "extra == 'local-smart-turn'", specifier = ">=8.0" }, From dfc1f09b772e68a182d4a9a349475538d35a10eb Mon Sep 17 00:00:00 2001 From: Luke Payyapilli Date: Mon, 19 Jan 2026 11:00:23 -0500 Subject: [PATCH 0135/1060] fix(livekit): prevent memory leak when video_in_enabled is False --- src/pipecat/transports/livekit/transport.py | 13 +- tests/test_livekit_transport.py | 133 ++++++++++++++++++++ 2 files changed, 141 insertions(+), 5 deletions(-) create mode 100644 tests/test_livekit_transport.py diff --git a/src/pipecat/transports/livekit/transport.py b/src/pipecat/transports/livekit/transport.py index 10a7d8d5d..ab7325c68 100644 --- a/src/pipecat/transports/livekit/transport.py +++ b/src/pipecat/transports/livekit/transport.py @@ -539,11 +539,14 @@ class LiveKitTransportClient: elif track.kind == rtc.TrackKind.KIND_VIDEO: logger.info(f"Video track subscribed: {track.sid} from participant {participant.sid}") self._video_tracks[participant.sid] = track - video_stream = rtc.VideoStream(track) - self._task_manager.create_task( - self._process_video_stream(video_stream, participant.sid), - f"{self}::_process_video_stream", - ) + # Only process video stream if video input is enabled to prevent + # unbounded queue growth when there is no consumer for video frames. + if self._params.video_in_enabled: + video_stream = rtc.VideoStream(track) + self._task_manager.create_task( + self._process_video_stream(video_stream, participant.sid), + f"{self}::_process_video_stream", + ) await self._callbacks.on_video_track_subscribed(participant.sid) async def _async_on_track_unsubscribed( diff --git a/tests/test_livekit_transport.py b/tests/test_livekit_transport.py new file mode 100644 index 000000000..a61daaaa4 --- /dev/null +++ b/tests/test_livekit_transport.py @@ -0,0 +1,133 @@ +# +# Copyright (c) 2024-2026, Daily +# +# SPDX-License-Identifier: BSD 2-Clause License +# + +"""Tests for LiveKit transport video stream handling. + +Regression tests for issue #3116: Memory leak when video_in_enabled=False +but video tracks are subscribed. +""" + +import asyncio +import unittest +from unittest.mock import AsyncMock, MagicMock + +from livekit import rtc + +from pipecat.transports.livekit.transport import ( + LiveKitCallbacks, + LiveKitParams, + LiveKitTransportClient, +) + + +class TestLiveKitTransportClient(unittest.IsolatedAsyncioTestCase): + """Tests for LiveKitTransportClient video stream handling.""" + + def _create_client(self, video_in_enabled: bool) -> LiveKitTransportClient: + """Create a LiveKitTransportClient with the specified video_in_enabled setting.""" + params = LiveKitParams(video_in_enabled=video_in_enabled) + + callbacks = LiveKitCallbacks( + on_connected=AsyncMock(), + on_disconnected=AsyncMock(), + on_before_disconnect=AsyncMock(), + on_participant_connected=AsyncMock(), + on_participant_disconnected=AsyncMock(), + on_audio_track_subscribed=AsyncMock(), + on_audio_track_unsubscribed=AsyncMock(), + on_video_track_subscribed=AsyncMock(), + on_video_track_unsubscribed=AsyncMock(), + on_data_received=AsyncMock(), + on_first_participant_joined=AsyncMock(), + ) + + client = LiveKitTransportClient( + url="wss://test.livekit.cloud", + token="test-token", + room_name="test-room", + params=params, + callbacks=callbacks, + transport_name="test-transport", + ) + + # Mock the task manager + client._task_manager = MagicMock() + client._task_manager.create_task = MagicMock() + + return client + + def _create_mock_video_track(self) -> tuple: + """Create mock video track, publication, and participant.""" + mock_track = MagicMock() + mock_track.kind = rtc.TrackKind.KIND_VIDEO + mock_track.sid = "test-track-sid" + + mock_publication = MagicMock() + + mock_participant = MagicMock() + mock_participant.sid = "test-participant-sid" + + return mock_track, mock_publication, mock_participant + + def _was_video_stream_task_created(self, client: LiveKitTransportClient) -> bool: + """Check if _process_video_stream task was created.""" + for call in client._task_manager.create_task.call_args_list: + task_name = call[0][1] if len(call[0]) > 1 else call[1].get("name", "") + if "_process_video_stream" in task_name: + return True + return False + + async def test_video_stream_not_started_when_video_in_disabled(self): + """Test that _process_video_stream is NOT started when video_in_enabled=False. + + This prevents unbounded queue growth when there is no consumer for video frames. + Regression test for issue #3116. + """ + client = self._create_client(video_in_enabled=False) + mock_track, mock_publication, mock_participant = self._create_mock_video_track() + + # Call the track subscribed handler + await client._async_on_track_subscribed(mock_track, mock_publication, mock_participant) + + # Verify that create_task was NOT called for video stream processing + self.assertFalse( + self._was_video_stream_task_created(client), + "Video stream processing should NOT be started when video_in_enabled=False", + ) + + # Verify that the callback was still called + client._callbacks.on_video_track_subscribed.assert_called_once_with(mock_participant.sid) + + # Verify that the track was still added to _video_tracks + self.assertIn(mock_participant.sid, client._video_tracks) + + async def test_video_stream_started_when_video_in_enabled(self): + """Test that _process_video_stream IS started when video_in_enabled=True.""" + from unittest.mock import patch + + client = self._create_client(video_in_enabled=True) + mock_track, mock_publication, mock_participant = self._create_mock_video_track() + + # Mock rtc.VideoStream to avoid needing a real LiveKit connection + with patch("pipecat.transports.livekit.transport.rtc.VideoStream"): + # Call the track subscribed handler + await client._async_on_track_subscribed(mock_track, mock_publication, mock_participant) + + # Verify that create_task WAS called for video stream processing + self.assertTrue( + self._was_video_stream_task_created(client), + "Video stream processing SHOULD be started when video_in_enabled=True", + ) + + # Verify that the callback was called + client._callbacks.on_video_track_subscribed.assert_called_once_with(mock_participant.sid) + + # Verify that the track was added to _video_tracks + self.assertIn(mock_participant.sid, client._video_tracks) + + +if __name__ == "__main__": + unittest.main() From 562bdd3084fe064f74a670910e8f7c4a884f815b Mon Sep 17 00:00:00 2001 From: Luke Payyapilli Date: Mon, 19 Jan 2026 11:11:54 -0500 Subject: [PATCH 0136/1060] test: add livekit to dev deps and improve test clarity --- pyproject.toml | 1 + tests/test_livekit_transport.py | 119 +++++++++++++++----------------- uv.lock | 8 +-- 3 files changed, 57 insertions(+), 71 deletions(-) diff --git a/pyproject.toml b/pyproject.toml index e99ab62bc..f86846de3 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -125,6 +125,7 @@ dev = [ "build~=1.2.2", "coverage~=7.9.1", "grpcio-tools~=1.67.1", + "livekit~=1.0.13", "pip-tools~=7.4.1", "pre-commit~=4.2.0", "pyright>=1.1.404,<1.2", diff --git a/tests/test_livekit_transport.py b/tests/test_livekit_transport.py index a61daaaa4..7962e4e8a 100644 --- a/tests/test_livekit_transport.py +++ b/tests/test_livekit_transport.py @@ -7,12 +7,12 @@ """Tests for LiveKit transport video stream handling. Regression tests for issue #3116: Memory leak when video_in_enabled=False -but video tracks are subscribed. +but video tracks are subscribed. The fix ensures video stream processing +only starts when there is a consumer for the frames. """ -import asyncio import unittest -from unittest.mock import AsyncMock, MagicMock +from unittest.mock import AsyncMock, MagicMock, patch from livekit import rtc @@ -23,13 +23,19 @@ from pipecat.transports.livekit.transport import ( ) -class TestLiveKitTransportClient(unittest.IsolatedAsyncioTestCase): - """Tests for LiveKitTransportClient video stream handling.""" +class TestLiveKitVideoStreamMemoryLeak(unittest.IsolatedAsyncioTestCase): + """Regression tests for video queue memory leak (#3116). + + The bug: When video_in_enabled=False, subscribing to a video track would + start a producer that fills _video_queue, but no consumer would drain it, + causing unbounded memory growth (~3GB/min). + + The fix: Only start video stream processing when video_in_enabled=True. + """ def _create_client(self, video_in_enabled: bool) -> LiveKitTransportClient: - """Create a LiveKitTransportClient with the specified video_in_enabled setting.""" + """Create a client with the specified video input setting.""" params = LiveKitParams(video_in_enabled=video_in_enabled) - callbacks = LiveKitCallbacks( on_connected=AsyncMock(), on_disconnected=AsyncMock(), @@ -43,7 +49,6 @@ class TestLiveKitTransportClient(unittest.IsolatedAsyncioTestCase): on_data_received=AsyncMock(), on_first_participant_joined=AsyncMock(), ) - client = LiveKitTransportClient( url="wss://test.livekit.cloud", token="test-token", @@ -52,81 +57,65 @@ class TestLiveKitTransportClient(unittest.IsolatedAsyncioTestCase): callbacks=callbacks, transport_name="test-transport", ) - - # Mock the task manager client._task_manager = MagicMock() - client._task_manager.create_task = MagicMock() - return client - def _create_mock_video_track(self) -> tuple: - """Create mock video track, publication, and participant.""" - mock_track = MagicMock() - mock_track.kind = rtc.TrackKind.KIND_VIDEO - mock_track.sid = "test-track-sid" + def _create_mock_video_track(self): + """Create a mock video track subscription event.""" + track = MagicMock() + track.kind = rtc.TrackKind.KIND_VIDEO + track.sid = "video-track-123" + publication = MagicMock() + participant = MagicMock() + participant.sid = "participant-456" + return track, publication, participant - mock_publication = MagicMock() + async def test_disabled_video_input_does_not_start_queue_producer(self): + """When video input is disabled, no producer should fill the queue. - mock_participant = MagicMock() - mock_participant.sid = "test-participant-sid" - - return mock_track, mock_publication, mock_participant - - def _was_video_stream_task_created(self, client: LiveKitTransportClient) -> bool: - """Check if _process_video_stream task was created.""" - for call in client._task_manager.create_task.call_args_list: - task_name = call[0][1] if len(call[0]) > 1 else call[1].get("name", "") - if "_process_video_stream" in task_name: - return True - return False - - async def test_video_stream_not_started_when_video_in_disabled(self): - """Test that _process_video_stream is NOT started when video_in_enabled=False. - - This prevents unbounded queue growth when there is no consumer for video frames. - Regression test for issue #3116. + This prevents the memory leak where frames accumulate with no consumer. """ client = self._create_client(video_in_enabled=False) - mock_track, mock_publication, mock_participant = self._create_mock_video_track() + track, publication, participant = self._create_mock_video_track() - # Call the track subscribed handler - await client._async_on_track_subscribed(mock_track, mock_publication, mock_participant) + await client._async_on_track_subscribed(track, publication, participant) - # Verify that create_task was NOT called for video stream processing - self.assertFalse( - self._was_video_stream_task_created(client), - "Video stream processing should NOT be started when video_in_enabled=False", - ) + # Verify no video processing task was started + task_names = [ + call[0][1] for call in client._task_manager.create_task.call_args_list + ] + video_tasks = [name for name in task_names if "video" in name.lower()] + self.assertEqual(video_tasks, [], "No video processing task should be started") - # Verify that the callback was still called - client._callbacks.on_video_track_subscribed.assert_called_once_with(mock_participant.sid) + # Queue should remain empty + self.assertEqual(client._video_queue.qsize(), 0) - # Verify that the track was still added to _video_tracks - self.assertIn(mock_participant.sid, client._video_tracks) + # Track metadata should still be recorded + self.assertIn(participant.sid, client._video_tracks) - async def test_video_stream_started_when_video_in_enabled(self): - """Test that _process_video_stream IS started when video_in_enabled=True.""" - from unittest.mock import patch + # Callback should still fire for user code + client._callbacks.on_video_track_subscribed.assert_called_once() + async def test_enabled_video_input_starts_queue_producer(self): + """When video input is enabled, the producer should start.""" client = self._create_client(video_in_enabled=True) - mock_track, mock_publication, mock_participant = self._create_mock_video_track() + track, publication, participant = self._create_mock_video_track() - # Mock rtc.VideoStream to avoid needing a real LiveKit connection - with patch("pipecat.transports.livekit.transport.rtc.VideoStream"): - # Call the track subscribed handler - await client._async_on_track_subscribed(mock_track, mock_publication, mock_participant) + with patch.object(rtc, "VideoStream"): + await client._async_on_track_subscribed(track, publication, participant) - # Verify that create_task WAS called for video stream processing - self.assertTrue( - self._was_video_stream_task_created(client), - "Video stream processing SHOULD be started when video_in_enabled=True", - ) + # Verify video processing task was started + task_names = [ + call[0][1] for call in client._task_manager.create_task.call_args_list + ] + video_tasks = [name for name in task_names if "video" in name.lower()] + self.assertEqual(len(video_tasks), 1, "Video processing task should be started") - # Verify that the callback was called - client._callbacks.on_video_track_subscribed.assert_called_once_with(mock_participant.sid) + # Track metadata should be recorded + self.assertIn(participant.sid, client._video_tracks) - # Verify that the track was added to _video_tracks - self.assertIn(mock_participant.sid, client._video_tracks) + # Callback should fire + client._callbacks.on_video_track_subscribed.assert_called_once() if __name__ == "__main__": diff --git a/uv.lock b/uv.lock index 45c1f892f..374dd0576 100644 --- a/uv.lock +++ b/uv.lock @@ -2013,7 +2013,6 @@ wheels = [ { url = "https://files.pythonhosted.org/packages/32/6a/33d1702184d94106d3cdd7bfb788e19723206fce152e303473ca3b946c7b/greenlet-3.3.0-cp310-cp310-macosx_11_0_universal2.whl", hash = "sha256:6f8496d434d5cb2dce025773ba5597f71f5410ae499d5dd9533e0653258cdb3d", size = 273658, upload-time = "2025-12-04T14:23:37.494Z" }, { url = "https://files.pythonhosted.org/packages/d6/b7/2b5805bbf1907c26e434f4e448cd8b696a0b71725204fa21a211ff0c04a7/greenlet-3.3.0-cp310-cp310-manylinux_2_24_aarch64.manylinux_2_28_aarch64.whl", hash = "sha256:b96dc7eef78fd404e022e165ec55327f935b9b52ff355b067eb4a0267fc1cffb", size = 574810, upload-time = "2025-12-04T14:50:04.154Z" }, { url = "https://files.pythonhosted.org/packages/94/38/343242ec12eddf3d8458c73f555c084359883d4ddc674240d9e61ec51fd6/greenlet-3.3.0-cp310-cp310-manylinux_2_24_ppc64le.manylinux_2_28_ppc64le.whl", hash = "sha256:73631cd5cccbcfe63e3f9492aaa664d278fda0ce5c3d43aeda8e77317e38efbd", size = 586248, upload-time = "2025-12-04T14:57:39.35Z" }, - 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task_names = [ - call[0][1] for call in client._task_manager.create_task.call_args_list - ] + task_names = [call[0][1] for call in client._task_manager.create_task.call_args_list] video_tasks = [name for name in task_names if "video" in name.lower()] self.assertEqual(video_tasks, [], "No video processing task should be started") @@ -105,9 +103,7 @@ class TestLiveKitVideoStreamMemoryLeak(unittest.IsolatedAsyncioTestCase): await client._async_on_track_subscribed(track, publication, participant) # Verify video processing task was started - task_names = [ - call[0][1] for call in client._task_manager.create_task.call_args_list - ] + task_names = [call[0][1] for call in client._task_manager.create_task.call_args_list] video_tasks = [name for name in task_names if "video" in name.lower()] self.assertEqual(len(video_tasks), 1, "Video processing task should be started") From 11cf891ac82ddeccb576693d6d9ca3287d014674 Mon Sep 17 00:00:00 2001 From: Mark Backman Date: Sun, 18 Jan 2026 08:54:34 -0500 Subject: [PATCH 0138/1060] Manual updates for unused imports --- examples/quickstart/pcc-deploy.toml | 8 ++++---- scripts/krisp/test_krisp_viva_filter_audiofile.py | 2 +- scripts/krisp/test_krisp_viva_turn_audiofile.py | 2 +- src/pipecat/runner/run.py | 8 +------- src/pipecat/services/aws_nova_sonic/__init__.py | 5 +++++ .../services/gemini_multimodal_live/__init__.py | 5 +++++ src/pipecat/services/google/gemini_live/__init__.py | 6 ++++++ src/pipecat/services/moondream/vision.py | 2 +- src/pipecat/services/openai_realtime/__init__.py | 10 ++++++++++ src/pipecat/services/openai_realtime_beta/__init__.py | 10 ++++++++++ src/pipecat/services/whisper/stt.py | 2 +- src/pipecat/transports/smallwebrtc/connection.py | 1 - src/pipecat/turns/mute/__init__.py | 8 ++++++++ 13 files changed, 53 insertions(+), 16 deletions(-) diff --git a/examples/quickstart/pcc-deploy.toml b/examples/quickstart/pcc-deploy.toml index ff77c45dc..812e2b8e6 100644 --- a/examples/quickstart/pcc-deploy.toml +++ b/examples/quickstart/pcc-deploy.toml @@ -1,11 +1,11 @@ -agent_name = "quickstart" -image = "your_username/quickstart:0.1" -secret_set = "quickstart-secrets" +agent_name = "quickstart-test" +image = "markatdaily/quickstart-test:latest" +secret_set = "quickstart-test-secrets" agent_profile = "agent-1x" # RECOMMENDED: Set an image pull secret: # https://docs.pipecat.ai/deployment/pipecat-cloud/fundamentals/secrets#image-pull-secrets -# image_credentials = "your_image_pull_secret" +image_credentials = "dockerhub-access" [scaling] min_agents = 1 diff --git a/scripts/krisp/test_krisp_viva_filter_audiofile.py b/scripts/krisp/test_krisp_viva_filter_audiofile.py index c75dc19fc..65e9d7685 100644 --- a/scripts/krisp/test_krisp_viva_filter_audiofile.py +++ b/scripts/krisp/test_krisp_viva_filter_audiofile.py @@ -22,7 +22,7 @@ from pathlib import Path try: import numpy as np - import soundfile as sf + import soundfile as sf # noqa: F401 from audio_file_utils import calculate_audio_stats, read_audio_file, write_audio_file except ImportError as e: print(f"Error: Missing required dependencies: {e}") diff --git a/scripts/krisp/test_krisp_viva_turn_audiofile.py b/scripts/krisp/test_krisp_viva_turn_audiofile.py index c380ad98f..6580e8e90 100644 --- a/scripts/krisp/test_krisp_viva_turn_audiofile.py +++ b/scripts/krisp/test_krisp_viva_turn_audiofile.py @@ -23,7 +23,7 @@ from pathlib import Path try: import numpy as np - import soundfile as sf + import soundfile as sf # noqa: F401 from audio_file_utils import read_audio_file except ImportError as e: print(f"Error: Missing required dependencies: {e}") diff --git a/src/pipecat/runner/run.py b/src/pipecat/runner/run.py index 0396e393b..96fbf2598 100644 --- a/src/pipecat/runner/run.py +++ b/src/pipecat/runner/run.py @@ -263,7 +263,7 @@ def _setup_webrtc_routes( """Handle WebRTC offer requests via SmallWebRTCRequestHandler.""" # Prepare runner arguments with the callback to run your bot - async def webrtc_connection_callback(connection): + async def webrtc_connection_callback(connection: SmallWebRTCConnection): bot_module = _get_bot_module() runner_args = SmallWebRTCRunnerArguments( @@ -406,13 +406,7 @@ def _setup_whatsapp_routes(app: FastAPI): return try: - from pipecat_ai_small_webrtc_prebuilt.frontend import SmallWebRTCPrebuiltUI - from pipecat.transports.smallwebrtc.connection import SmallWebRTCConnection - from pipecat.transports.smallwebrtc.request_handler import ( - SmallWebRTCRequest, - SmallWebRTCRequestHandler, - ) from pipecat.transports.whatsapp.api import WhatsAppWebhookRequest from pipecat.transports.whatsapp.client import WhatsAppClient except ImportError as e: diff --git a/src/pipecat/services/aws_nova_sonic/__init__.py b/src/pipecat/services/aws_nova_sonic/__init__.py index 8348e9ffe..a198094cb 100644 --- a/src/pipecat/services/aws_nova_sonic/__init__.py +++ b/src/pipecat/services/aws_nova_sonic/__init__.py @@ -17,3 +17,8 @@ with warnings.catch_warnings(): DeprecationWarning, stacklevel=2, ) + +__all__ = [ + "AWSNovaSonicLLMService", + "Params", +] diff --git a/src/pipecat/services/gemini_multimodal_live/__init__.py b/src/pipecat/services/gemini_multimodal_live/__init__.py index 513d9fd66..ac4524606 100644 --- a/src/pipecat/services/gemini_multimodal_live/__init__.py +++ b/src/pipecat/services/gemini_multimodal_live/__init__.py @@ -1,2 +1,7 @@ from .file_api import GeminiFileAPI from .gemini import GeminiMultimodalLiveLLMService + +__all__ = [ + "GeminiFileAPI", + "GeminiMultimodalLiveLLMService", +] diff --git a/src/pipecat/services/google/gemini_live/__init__.py b/src/pipecat/services/google/gemini_live/__init__.py index 142ca2a83..f4bfbb5c8 100644 --- a/src/pipecat/services/google/gemini_live/__init__.py +++ b/src/pipecat/services/google/gemini_live/__init__.py @@ -1,3 +1,9 @@ from .file_api import GeminiFileAPI from .llm import GeminiLiveLLMService from .llm_vertex import GeminiLiveVertexLLMService + +__all__ = [ + "GeminiFileAPI", + "GeminiLiveLLMService", + "GeminiLiveVertexLLMService", +] diff --git a/src/pipecat/services/moondream/vision.py b/src/pipecat/services/moondream/vision.py index f0ae8dca2..6a180b4cb 100644 --- a/src/pipecat/services/moondream/vision.py +++ b/src/pipecat/services/moondream/vision.py @@ -46,7 +46,7 @@ def detect_device(): and dtype is the recommended torch data type for that device. """ try: - import intel_extension_for_pytorch + import intel_extension_for_pytorch # noqa: F401 if torch.xpu.is_available(): return torch.device("xpu"), torch.float32 diff --git a/src/pipecat/services/openai_realtime/__init__.py b/src/pipecat/services/openai_realtime/__init__.py index a302c783b..90729ef31 100644 --- a/src/pipecat/services/openai_realtime/__init__.py +++ b/src/pipecat/services/openai_realtime/__init__.py @@ -25,3 +25,13 @@ with warnings.catch_warnings(): DeprecationWarning, stacklevel=2, ) + +__all__ = [ + "AzureRealtimeLLMService", + "InputAudioNoiseReduction", + "InputAudioTranscription", + "SemanticTurnDetection", + "SessionProperties", + "TurnDetection", + "OpenAIRealtimeLLMService", +] diff --git a/src/pipecat/services/openai_realtime_beta/__init__.py b/src/pipecat/services/openai_realtime_beta/__init__.py index 595105d7f..b7c976bb6 100644 --- a/src/pipecat/services/openai_realtime_beta/__init__.py +++ b/src/pipecat/services/openai_realtime_beta/__init__.py @@ -7,3 +7,13 @@ from .events import ( TurnDetection, ) from .openai import OpenAIRealtimeBetaLLMService + +__all__ = [ + "AzureRealtimeBetaLLMService", + "InputAudioNoiseReduction", + "InputAudioTranscription", + "SemanticTurnDetection", + "SessionProperties", + "TurnDetection", + "OpenAIRealtimeBetaLLMService", +] diff --git a/src/pipecat/services/whisper/stt.py b/src/pipecat/services/whisper/stt.py index 27ba743ac..3865578e1 100644 --- a/src/pipecat/services/whisper/stt.py +++ b/src/pipecat/services/whisper/stt.py @@ -33,7 +33,7 @@ if TYPE_CHECKING: raise Exception(f"Missing module: {e}") try: - import mlx_whisper + import mlx_whisper # noqa: F401 except ModuleNotFoundError as e: logger.error(f"Exception: {e}") logger.error("In order to use Whisper, you need to `pip install pipecat-ai[mlx-whisper]`.") diff --git a/src/pipecat/transports/smallwebrtc/connection.py b/src/pipecat/transports/smallwebrtc/connection.py index 5a5a1450d..259645d10 100644 --- a/src/pipecat/transports/smallwebrtc/connection.py +++ b/src/pipecat/transports/smallwebrtc/connection.py @@ -23,7 +23,6 @@ from pipecat.utils.base_object import BaseObject try: from aiortc import ( - MediaStreamTrack, RTCConfiguration, RTCIceServer, RTCPeerConnection, diff --git a/src/pipecat/turns/mute/__init__.py b/src/pipecat/turns/mute/__init__.py index 02b66688f..c82b10ae7 100644 --- a/src/pipecat/turns/mute/__init__.py +++ b/src/pipecat/turns/mute/__init__.py @@ -22,3 +22,11 @@ with warnings.catch_warnings(): DeprecationWarning, stacklevel=2, ) + +__all__ = [ + "AlwaysUserMuteStrategy", + "BaseUserMuteStrategy", + "FirstSpeechUserMuteStrategy", + "FunctionCallUserMuteStrategy", + "MuteUntilFirstBotCompleteUserMuteStrategy", +] From 7e82a0cf493590b76d68430ea1fc3dcc0050f63e Mon Sep 17 00:00:00 2001 From: ssillerom Date: Mon, 19 Jan 2026 20:45:22 +0100 Subject: [PATCH 0139/1060] feature: Genesys AudioHook WebSocket protocol serializer for Pipecat --- src/pipecat/serializers/genesys.py | 945 +++++++++++++++++++++++++++++ 1 file changed, 945 insertions(+) create mode 100644 src/pipecat/serializers/genesys.py diff --git a/src/pipecat/serializers/genesys.py b/src/pipecat/serializers/genesys.py new file mode 100644 index 000000000..f768b8431 --- /dev/null +++ b/src/pipecat/serializers/genesys.py @@ -0,0 +1,945 @@ +""" +Genesys AudioHook WebSocket protocol serializer for Pipecat. + +This serializer implements the Genesys AudioHook protocol for bidirectional +audio streaming between Pipecat pipelines and Genesys Cloud contact center. + +Protocol Reference: +- https://developer.genesys.cloud/devapps/audiohook + +Audio Format: +- PCMU (μ-law) at 8kHz sample rate (preferred) +- L16 (16-bit linear PCM) at 8kHz also supported +- Mono or Stereo (external on left, internal on right) +""" + +import json +import uuid +from datetime import timedelta +from enum import Enum +from typing import Any, Awaitable, Callable, Dict, List, Optional + +from loguru import logger +from pydantic import BaseModel + +from pipecat.audio.dtmf.types import KeypadEntry +from pipecat.frames.frames import ( + AudioRawFrame, + CancelFrame, + EndFrame, + Frame, + InputAudioRawFrame, + InputDTMFFrame, + OutputTransportMessageFrame, + OutputTransportMessageUrgentFrame, + StartFrame +) +from pipecat.serializers.base_serializer import FrameSerializer +from pipecat.audio.resamplers.soxr_stream_resampler import SOXRStreamAudioResampler +from pipecat.audio.utils import ulaw_to_pcm, pcm_to_ulaw + + +class AudioHookMessageType(str, Enum): + """AudioHook protocol message types.""" + OPEN = "open" + OPENED = "opened" + CLOSE = "close" + CLOSED = "closed" + PAUSE = "pause" + RESUMED = "resumed" + PING = "ping" + PONG = "pong" + UPDATE = "update" + EVENT = "event" + ERROR = "error" + DISCONNECT = "disconnect" + + +class AudioHookChannel(str, Enum): + """AudioHook audio channel configuration.""" + EXTERNAL = "external" # Customer audio only (mono) + INTERNAL = "internal" # Agent audio only (mono) + BOTH = "both" # Stereo: external=left, internal=right + + +class AudioHookMediaFormat(str, Enum): + """Supported audio formats.""" + PCMU = "PCMU" # μ-law, 8kHz + L16 = "L16" # 16-bit linear PCM, 8kHz + + +class GenesysAudioHookSerializer(FrameSerializer): + """Serializer for Genesys AudioHook WebSocket protocol. + + This serializer handles converting between Pipecat frames and Genesys + AudioHook protocol messages. It supports: + + - Bidirectional audio streaming (PCMU at 8kHz) + - Session lifecycle management (open, close, pause) + - Probe mode for health checks + - Custom configuration passthrough + - Event messaging back to Genesys Cloud + + The AudioHook protocol uses: + - Text WebSocket frames for JSON control messages + - Binary WebSocket frames for audio data + + Example usage: + ```python + serializer = GenesysAudioHookSerializer( + session_id="abc-123", + params=GenesysAudioHookSerializer.InputParams( + channel=AudioHookChannel.BOTH, + ) + ) + + # Use with WebSocket transport + transport = WebsocketServerTransport( + serializer=serializer, + ... + ) + ``` + + Attributes: + PROTOCOL_VERSION: The AudioHook protocol version (currently "2"). + """ + + PROTOCOL_VERSION = "2" + + class InputParams(BaseModel): + """Configuration parameters for GenesysAudioHookSerializer. + + Parameters: + genesys_sample_rate: Sample rate used by Genesys (8000 Hz). + sample_rate: Optional override for pipeline input sample rate. + channel: Which audio channels to process (external, internal, both). + media_format: Audio format (PCMU or L16). + process_external: Whether to process external (customer) audio. + process_internal: Whether to process internal (agent) audio. + enable_interruption_events: Send interruption events to Genesys. + """ + + genesys_sample_rate: int = 8000 + sample_rate: Optional[int] = None + channel: AudioHookChannel = AudioHookChannel.EXTERNAL + media_format: AudioHookMediaFormat = AudioHookMediaFormat.PCMU + process_external: bool = True + process_internal: bool = False + enable_interruption_events: bool = True + + def __init__( + self, + session_id: Optional[str] = None, + params: Optional[InputParams] = None, + send_message_callback: Optional[Callable[[str], Awaitable[None]]] = None, + ): + """Initialize the GenesysAudioHookSerializer. + + Args: + session_id: The AudioHook session ID (received in open message). + params: Configuration parameters. + send_message_callback: Optional async callback to send messages directly + (bypassing the pipeline). Used for urgent messages like pong. + """ + self._params = params or GenesysAudioHookSerializer.InputParams() + self._session_id = session_id or "" + self._send_message_callback = send_message_callback + + self._genesys_sample_rate = self._params.genesys_sample_rate + self._sample_rate = 0 # Pipeline input rate, set in setup() + + # Use Pipecat's official SOXR resampler + # Only used for TTS output (16kHz → 8kHz), input goes without resampling + self._input_resampler = SOXRStreamAudioResampler() + self._output_resampler = SOXRStreamAudioResampler() + + # Protocol state + self._client_seq = 0 + self._server_seq = 0 + self._is_open = False + self._is_paused = False + self._position = timedelta(0) + + # TTS output state + self._tts_chunk_count = 0 + + # Session metadata + self._conversation_id: Optional[str] = None + self._participant: Optional[Dict[str, Any]] = None + self._custom_config: Optional[Dict[str, Any]] = None + self._media_info: Optional[List[Dict[str, Any]]] = None + self._input_variables: Optional[Dict[str, Any]] = None # Custom input from Genesys + + def set_send_message_callback(self, callback: Callable[[str], Awaitable[None]]): + """Set the callback for sending urgent messages directly. + + Args: + callback: An async function that takes a string message and sends it. + """ + self._send_message_callback = callback + + @property + def session_id(self) -> str: + """Get the current session ID.""" + return self._session_id + + @property + def conversation_id(self) -> Optional[str]: + """Get the Genesys conversation ID.""" + return self._conversation_id + + @property + def is_open(self) -> bool: + """Check if the AudioHook session is open.""" + return self._is_open + + @property + def is_paused(self) -> bool: + """Check if audio streaming is paused.""" + return self._is_paused + + @property + def participant(self) -> Optional[Dict[str, Any]]: + """Get participant info (ani, dnis, etc.) from the open message.""" + return self._participant + + @property + def input_variables(self) -> Optional[Dict[str, Any]]: + """Get custom input variables from the open message.""" + return self._input_variables + + async def setup(self, frame: StartFrame): + """Sets up the serializer with pipeline configuration. + + Args: + frame: The StartFrame containing pipeline configuration. + """ + self._sample_rate = self._params.sample_rate or frame.audio_in_sample_rate + logger.debug(f"GenesysAudioHookSerializer setup with sample_rate={self._sample_rate}") + + def reset_tts_state(self): + """Reset TTS state for a new utterance. + + NOTE: We don't reset the resampler because that causes artifacts. + The resampler maintains its state between utterances for cleaner audio. + """ + self._tts_chunk_count = 0 + + def _format_position(self, position: timedelta) -> str: + """Format a timedelta as ISO 8601 duration string. + + Args: + position: The timedelta to format. + + Returns: + ISO 8601 duration string (e.g., "PT1.5S"). + """ + total_seconds = position.total_seconds() + return f"PT{total_seconds:.3f}S" + + def _parse_position(self, position_str: str) -> timedelta: + """Parse an ISO 8601 duration string to timedelta. + + Args: + position_str: ISO 8601 duration string (e.g., "PT1.5S"). + + Returns: + Corresponding timedelta. + """ + # Simple parser for PT#S or PT#.#S format + if position_str.startswith("PT") and position_str.endswith("S"): + try: + seconds = float(position_str[2:-1]) + return timedelta(seconds=seconds) + except ValueError: + pass + return timedelta(0) + + def _next_server_seq(self) -> int: + """Get the next server sequence number.""" + self._server_seq += 1 + return self._server_seq + + def _create_message( + self, + msg_type: AudioHookMessageType, + parameters: Optional[Dict[str, Any]] = None, + include_position: bool = True, + ) -> Dict[str, Any]: + """Create a protocol message with common fields. + + Based on the Genesys AudioHook protocol, responses include: + - seq: Server's sequence number (incremented per message) + - clientseq: Echo of the client's last sequence number + + Args: + msg_type: The message type. + parameters: Optional parameters object. + include_position: Whether to include position field. + + Returns: + The message dictionary. + """ + seq = self._next_server_seq() + msg = { + "version": self.PROTOCOL_VERSION, + "type": msg_type.value, + "seq": seq, + "clientseq": self._client_seq, + "id": self._session_id, + } + + if include_position: + msg["position"] = self._format_position(self._position) + + if parameters: + msg["parameters"] = parameters + + return msg + + def create_opened_response( + self, + start_paused: bool = False, + supported_languages: Optional[List[str]] = None, + selected_language: Optional[str] = None, + ) -> str: + """Create an 'opened' response message for the client. + + This should be sent in response to an 'open' message from Genesys. + + Args: + start_paused: Whether to start the session paused. + supported_languages: List of supported language codes. + selected_language: The selected language code. + + Returns: + JSON string of the opened response message. + """ + # Build channels list based on configuration + channels = [] + if self._params.channel == AudioHookChannel.EXTERNAL: + channels = ["external"] + elif self._params.channel == AudioHookChannel.INTERNAL: + channels = ["internal"] + elif self._params.channel == AudioHookChannel.BOTH: + channels = ["external", "internal"] + + parameters = { + "startPaused": start_paused, + "media": [ + { + "type": "audio", + "format": self._params.media_format.value, + "channels": channels, + "rate": self._genesys_sample_rate, + } + ], + } + + if supported_languages: + parameters["supportedLanguages"] = supported_languages + if selected_language: + parameters["selectedLanguage"] = selected_language + + msg = self._create_message( + AudioHookMessageType.OPENED, + parameters=parameters, + include_position=False, # opened doesn't need position + ) + + self._is_open = True + logger.debug(f"AudioHook session opened: {self._session_id}") + + return json.dumps(msg) + + def create_closed_response(self) -> str: + """Create a 'closed' response message. + + This should be sent in response to a 'close' message from Genesys. + + Returns: + JSON string of the closed response message. + """ + msg = self._create_message(AudioHookMessageType.CLOSED) + + self._is_open = False + logger.debug(f"AudioHook session closed: {self._session_id}") + + return json.dumps(msg) + + def create_pong_response(self) -> str: + """Create a 'pong' response message. + + This should be sent in response to a 'ping' message from Genesys. + + Returns: + JSON string of the pong response message. + """ + msg = self._create_message(AudioHookMessageType.PONG) + return json.dumps(msg) + + def create_resumed_response(self) -> str: + """Create a 'resumed' response message. + + This should be sent in response to a 'pause' message when ready to resume. + + Returns: + JSON string of the resumed response message. + """ + msg = self._create_message(AudioHookMessageType.RESUMED) + + self._is_paused = False + logger.debug(f"AudioHook session resumed: {self._session_id}") + + return json.dumps(msg) + + def create_event_message( + self, + entity_type: str, + entity_data: Dict[str, Any], + ) -> str: + """Create an 'event' message to send data back to Genesys. + + This can be used for transcriptions, agent assist, or other events. + + Args: + entity_type: The type of entity (e.g., "transcript"). + entity_data: The entity data. + + Returns: + JSON string of the event message. + """ + parameters = { + "entities": [ + { + "type": entity_type, + **entity_data, + } + ] + } + + msg = self._create_message( + AudioHookMessageType.EVENT, + parameters=parameters, + ) + + return json.dumps(msg) + + def create_disconnect_message( + self, + reason: str = "completed", + action: str = "transfer", + output_variables: Optional[Dict[str, Any]] = None, + info: Optional[str] = None, + ) -> str: + """Create a 'disconnect' message to initiate session termination. + + Args: + reason: Disconnect reason (e.g., "completed", "error"). + action: Action to take ("transfer" to agent, "finished" if completed). + output_variables: Custom output variables to pass back to Genesys. + info: Optional additional information. + + Returns: + JSON string of the disconnect message. + """ + parameters: Dict[str, Any] = {"reason": reason} + + # Build outputVariables + out_vars = {"action": action} + if output_variables: + out_vars.update(output_variables) + parameters["outputVariables"] = out_vars + + if info: + parameters["info"] = info + + msg = self._create_message( + AudioHookMessageType.DISCONNECT, + parameters=parameters, + ) + + logger.debug(f"AudioHook disconnect: reason={reason}, action={action}") + return json.dumps(msg) + + def create_error_message( + self, + code: int, + message: str, + retryable: bool = False, + ) -> str: + """Create an 'error' message. + + Args: + code: Error code. + message: Error message. + retryable: Whether the operation can be retried. + + Returns: + JSON string of the error message. + """ + parameters = { + "code": code, + "message": message, + "retryable": retryable, + } + + msg = self._create_message( + AudioHookMessageType.ERROR, + parameters=parameters, + ) + + logger.error(f"AudioHook error: {code} - {message}") + return json.dumps(msg) + + def create_barge_in_event(self) -> str: + """Create a barge-in event message. + + This notifies Genesys Cloud that the user has interrupted the bot's + audio output. Genesys will stop any queued audio playback. + + Returns: + JSON string of the barge-in event message. + """ + msg = self._create_message( + AudioHookMessageType.EVENT, + parameters={ + "entities": [ + {"type": "barge_in", "data": {}} + ] + }, + ) + + logger.debug("🔇 Barge-in event sent to Genesys") + + return json.dumps(msg) + + def create_resume_event(self) -> str: + """Create a resume event message. + + This notifies Genesys that the bot is ready to resume after a barge-in. + Should be called after the user stops speaking following a barge-in. + + Returns: + JSON string of the resume event message. + """ + self._barge_in = False + + # Note: 'resume' might not be a standard AudioHook message type, + # but it's used in some implementations + msg = { + "version": self.PROTOCOL_VERSION, + "type": "resume", + "seq": self._next_server_seq(), + "clientseq": self._client_seq, + "id": self._session_id, + "parameters": {}, + } + + logger.debug("Resume event sent") + return json.dumps(msg) + + def create_interruption_event( + self, + reason: str = "user_speaking", + discarded_bytes: Optional[int] = None, + ) -> str: + """Create a generic interruption event message. + + This is an alternative to create_barge_in_event() that includes + more detailed information about the interruption. + + Args: + reason: Reason for interruption (e.g., "user_speaking", "dtmf"). + discarded_bytes: Number of audio bytes discarded due to interruption. + + Returns: + JSON string of the interruption event message. + """ + entity_data: Dict[str, Any] = { + "reason": reason, + "timestamp": self._format_position(self._position), + } + + if discarded_bytes is not None: + entity_data["discardedAudioBytes"] = discarded_bytes + + logger.info( + f"AudioHook interruption: reason={reason}, " + f"discarded={discarded_bytes or 0} bytes" + ) + + return self.create_event_message( + entity_type="interruption", + entity_data=entity_data, + ) + + async def serialize(self, frame: Frame) -> str | bytes | None: + """Serializes a Pipecat frame to Genesys AudioHook format. + + Handles conversion of various frame types to AudioHook messages: + - AudioRawFrame -> Binary audio data + - EndFrame/CancelFrame -> Disconnect message + - OutputTransportMessageFrame -> Pass-through JSON + + Args: + frame: The Pipecat frame to serialize. + + Returns: + Serialized data as string (JSON) or bytes (audio), or None. + """ + if isinstance(frame, (EndFrame, CancelFrame)): + return self.create_disconnect_message(reason="completed") + + elif isinstance(frame, AudioRawFrame): + if not self._is_open or self._is_paused: + return None + + data = frame.audio + + self._tts_chunk_count += 1 + + # Convert PCM to μ-law at 8kHz for Genesys + if self._params.media_format == AudioHookMediaFormat.PCMU: + serialized_data = await pcm_to_ulaw( + data, + frame.sample_rate, + self._genesys_sample_rate, + self._output_resampler, + ) + else: + # L16 format - just resample if needed + logger.warning("L16 format not yet fully implemented") + return None + + if serialized_data is None or len(serialized_data) == 0: + return None + + return bytes(serialized_data) + + elif isinstance(frame, (OutputTransportMessageFrame, OutputTransportMessageUrgentFrame)): + # Pass through custom JSON messages + return json.dumps(frame.message) + + # Ignore other frames - we don't need to process them here + return None + + async def deserialize(self, data: str | bytes) -> Frame | None: + """Deserializes Genesys AudioHook data to Pipecat frames. + + Handles: + - Binary data -> InputAudioRawFrame + - JSON text -> Protocol messages (open, close, ping, pause, etc.) + + For control messages (open, close, ping, pause), this method handles + the protocol response internally and logs the events. The application + should monitor session state via the is_open and is_paused properties. + + Args: + data: The raw WebSocket data from Genesys. + + Returns: + A Pipecat frame corresponding to the data, or None if handled internally. + """ + # Binary data = audio + if isinstance(data, bytes): + logger.debug(f"[AUDIO IN] Received {len(data)} bytes from Genesys") + return await self._deserialize_audio(data) + + # Text data = JSON control message + try: + message = json.loads(data) + except json.JSONDecodeError as e: + logger.error(f"Failed to parse AudioHook message: {e}") + return None + + return await self._handle_control_message(message) + + async def _deserialize_audio(self, data: bytes) -> Frame | None: + """Deserialize binary audio data to an InputAudioRawFrame. + + Args: + data: Raw audio bytes (PCMU or L16). + + Returns: + InputAudioRawFrame with PCM audio at pipeline sample rate. + """ + if not self._is_open or self._is_paused: + return None + + audio_data = data + original_len = len(data) + + # If Genesys sends stereo audio (BOTH channels), extract only the external channel (left) + # Stereo audio is interleaved: [L0, R0, L1, R1, ...] + if self._params.channel == AudioHookChannel.BOTH and len(data) > 0: + # For PCMU, each sample is 1 byte + # Extract only bytes at even positions (left channel = external) + audio_data = bytes(data[i] for i in range(0, len(data), 2)) + logger.debug(f"🔊 Stereo audio: {original_len} bytes → {len(audio_data)} bytes (external channel)") + + if self._params.media_format == AudioHookMediaFormat.PCMU: + # Convert μ-law at 8kHz to PCM at pipeline rate + deserialized_data = await ulaw_to_pcm( + audio_data, + self._genesys_sample_rate, + self._sample_rate, + self._input_resampler, + ) + else: + # L16 format + logger.warning("L16 format not yet fully implemented") + return None + + if deserialized_data is None or len(deserialized_data) == 0: + return None + + # Always use mono for STT - ElevenLabs expects single channel + num_channels = 1 + + audio_frame = InputAudioRawFrame( + audio=deserialized_data, + num_channels=num_channels, + sample_rate=self._sample_rate, + ) + + return audio_frame + + async def _handle_control_message(self, message: Dict[str, Any]) -> Frame | None: + """Handle a JSON control message from Genesys. + + Args: + message: Parsed JSON message. + + Returns: + Frame if the message should be passed to the pipeline, None otherwise. + """ + msg_type = message.get("type", "") + self._client_seq = message.get("seq", 0) + + # Update position if provided + if "position" in message: + self._position = self._parse_position(message["position"]) + + if msg_type == AudioHookMessageType.OPEN.value: + return await self._handle_open(message) + + elif msg_type == AudioHookMessageType.CLOSE.value: + return await self._handle_close(message) + + elif msg_type == AudioHookMessageType.PING.value: + return await self._handle_ping(message) + + elif msg_type == AudioHookMessageType.PAUSE.value: + return await self._handle_pause(message) + + elif msg_type == AudioHookMessageType.UPDATE.value: + return await self._handle_update(message) + + elif msg_type == AudioHookMessageType.ERROR.value: + return await self._handle_error(message) + + elif msg_type == "dtmf": + return await self._handle_dtmf(message) + + elif msg_type == "playback_started": + self._is_playing = True + logger.debug("Playback started (from Genesys)") + return None + + elif msg_type == "playback_completed": + self._is_playing = False + logger.debug("Playback completed (from Genesys)") + return None + + else: + logger.warning(f"Unknown AudioHook message type: {msg_type}") + return None + + async def _handle_open(self, message: Dict[str, Any]) -> Frame | None: + """Handle an 'open' message from Genesys. + + This initializes the session with metadata from Genesys Cloud. + + Args: + message: The open message. + + Returns: + None (response should be sent via create_opened_response()). + """ + self._session_id = message.get("id", str(uuid.uuid4())) + + params = message.get("parameters", {}) + self._conversation_id = params.get("conversationId") + self._participant = params.get("participant") + self._custom_config = params.get("customConfig") + self._media_info = params.get("media") # This is a list of media objects + self._input_variables = params.get("inputVariables") # Custom vars from Genesys + + # Extract media configuration if present + # media is a list like: [{"type": "audio", "format": "PCMU", "channels": ["external"], "rate": 8000}] + media_list = self._media_info + if media_list and isinstance(media_list, list) and len(media_list) > 0: + audio_media: Dict[str, Any] = media_list[0] # Get first media entry + channels = audio_media.get("channels", []) + logger.debug(f"📡 Genesys audio config: format={audio_media.get('format')}, channels={channels}, rate={audio_media.get('rate')}") + # channels is a list like ["external"] or ["external", "internal"] + if isinstance(channels, list): + if "external" in channels and "internal" in channels: + self._params.channel = AudioHookChannel.BOTH + logger.debug("📡 Stereo mode: extracting external channel") + elif "external" in channels: + self._params.channel = AudioHookChannel.EXTERNAL + logger.debug("📡 Mono mode: external channel") + elif "internal" in channels: + self._params.channel = AudioHookChannel.INTERNAL + logger.debug("📡 Mono mode: internal channel") + + # Log participant info for debugging + ani = self._participant.get("ani", "unknown") if self._participant else "unknown" + logger.info( + f"AudioHook open request: session={self._session_id}, " + f"conversation={self._conversation_id}, ani={ani}" + ) + + # Note: Application should call create_opened_response() to respond + return None + + async def _handle_close(self, message: Dict[str, Any]) -> Frame | None: + """Handle a 'close' message from Genesys. + + Args: + message: The close message. + + Returns: + EndFrame to signal the pipeline to close. + """ + params = message.get("parameters", {}) + reason = params.get("reason", "unknown") + + logger.info(f"🔴 Genesys closed the connection: {reason}") + + self._is_open = False + + # Send closed response via callback if available + if self._send_message_callback: + try: + closed_response = self.create_closed_response() + await self._send_message_callback(closed_response) + except Exception as e: + logger.error(f"Failed to send closed response: {e}") + + # Return EndFrame to close the pipeline and WebSocket + return EndFrame() + + async def _handle_ping(self, message: Dict[str, Any]) -> Frame | None: + """Handle a 'ping' message from Genesys. + + Args: + message: The ping message. + + Returns: + None if pong was sent directly via callback, otherwise + OutputTransportMessageUrgentFrame with pong response. + """ + # Create pong response + pong_response = self.create_pong_response() + + # If we have a direct callback, use it for immediate response + if self._send_message_callback: + try: + await self._send_message_callback(pong_response) + logger.debug("Pong sent directly via callback") + return None + except Exception as e: + logger.error(f"Failed to send pong via callback: {e}") + + # Fallback: return as urgent frame to be sent through pipeline + return OutputTransportMessageUrgentFrame(message=json.loads(pong_response)) + + async def _handle_pause(self, message: Dict[str, Any]) -> Frame | None: + """Handle a 'pause' message from Genesys. + + This is used when audio streaming is temporarily suspended + (e.g., during hold). + + Args: + message: The pause message. + + Returns: + None (response should be sent via create_resumed_response()). + """ + params = message.get("parameters", {}) + reason = params.get("reason", "unknown") + + logger.info(f"AudioHook pause request: reason={reason}") + + self._is_paused = True + + # Note: Application should call create_resumed_response() when ready + return None + + async def _handle_update(self, message: Dict[str, Any]) -> Frame | None: + """Handle an 'update' message from Genesys. + + Updates may include changes to participants or configuration. + + Args: + message: The update message. + + Returns: + None. + """ + params = message.get("parameters", {}) + + if "participant" in params: + self._participant = params["participant"] + + logger.debug(f"AudioHook update received: {params}") + + return None + + async def _handle_error(self, message: Dict[str, Any]) -> Frame | None: + """Handle an 'error' message from Genesys. + + Args: + message: The error message. + + Returns: + None. + """ + params = message.get("parameters", {}) + code = params.get("code", 0) + error_msg = params.get("message", "Unknown error") + + logger.error(f"AudioHook error from Genesys: {code} - {error_msg}") + + return None + + async def _handle_dtmf(self, message: Dict[str, Any]) -> Frame | None: + """Handle a 'dtmf' message from Genesys. + + DTMF (Dual-Tone Multi-Frequency) events are sent when the user + presses keys on their phone keypad. + + Args: + message: The DTMF message. + + Returns: + InputDTMFFrame with the pressed digit. + """ + params = message.get("parameters", {}) + digit = params.get("digit", "") + + if not digit: + logger.warning("DTMF message received without digit") + return None + + logger.info(f"DTMF received: {digit}") + + try: + return InputDTMFFrame(KeypadEntry(digit)) + except ValueError: + # Invalid digit + logger.warning(f"Invalid DTMF digit: {digit}") + return None From fa5da3b0becae911fcbf3a3fcf0ef22ce83a52f6 Mon Sep 17 00:00:00 2001 From: ssillerom Date: Mon, 19 Jan 2026 20:49:23 +0100 Subject: [PATCH 0140/1060] change comments --- src/pipecat/serializers/genesys.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/src/pipecat/serializers/genesys.py b/src/pipecat/serializers/genesys.py index f768b8431..11a842772 100644 --- a/src/pipecat/serializers/genesys.py +++ b/src/pipecat/serializers/genesys.py @@ -694,7 +694,7 @@ class GenesysAudioHookSerializer(FrameSerializer): if deserialized_data is None or len(deserialized_data) == 0: return None - # Always use mono for STT - ElevenLabs expects single channel + # Always use mono for STT num_channels = 1 audio_frame = InputAudioRawFrame( From aed44c863af04fe8eec7e9272e10a5c703c1e41e Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Aleix=20Conchillo=20Flaqu=C3=A9?= Date: Mon, 19 Jan 2026 14:37:00 -0800 Subject: [PATCH 0141/1060] scripts(eval): give examples to numerical word answers Some models need extra help. --- scripts/evals/eval.py | 7 ++++--- 1 file changed, 4 insertions(+), 3 deletions(-) diff --git a/scripts/evals/eval.py b/scripts/evals/eval.py index 7c6a72604..16598b4d7 100644 --- a/scripts/evals/eval.py +++ b/scripts/evals/eval.py @@ -293,12 +293,13 @@ async def run_eval_pipeline( "You should only call the eval function if:\n" "- The user explicitly attempts to answer the question, AND\n" f"- Their answer can be cleanly evaluated using: {eval_config.eval}\n" - "Ignore greetings, comments, non-answers, or requests for clarification." + "Ignore greetings, comments, non-answers, or requests for clarification.\n" + "Numerical word answers are allowed (e.g., 'five' is the same as '5').\n" ) if eval_config.eval_speaks_first: - system_prompt = f"You are an evaluation agent, be extremly brief. Numerical word answers are allowed. You will start the conversation by saying: '{example_prompt}'. {common_system_prompt}" + system_prompt = f"You are an evaluation agent, be extremly brief. You will start the conversation by saying: '{example_prompt}'. {common_system_prompt}" else: - system_prompt = f"You are an evaluation agent, be extremly brief. Numerical word answers are allowed. First, ask one question: {example_prompt}. {common_system_prompt}" + system_prompt = f"You are an evaluation agent, be extremly brief. First, ask one question: {example_prompt}. {common_system_prompt}" messages = [ { From f6359d460eb058a141e6f6fe2c1aa164932b4861 Mon Sep 17 00:00:00 2001 From: Luke Payyapilli Date: Tue, 20 Jan 2026 09:16:16 -0500 Subject: [PATCH 0142/1060] chore: install livekit as optional extra in CI instead of dev dep --- .github/workflows/coverage.yaml | 2 +- .github/workflows/tests.yaml | 2 +- pyproject.toml | 1 - tests/test_livekit_transport.py | 18 ++++++++++++------ uv.lock | 2 -- 5 files changed, 14 insertions(+), 11 deletions(-) diff --git a/.github/workflows/coverage.yaml b/.github/workflows/coverage.yaml index 0dd30f9e5..faca8c03f 100644 --- a/.github/workflows/coverage.yaml +++ b/.github/workflows/coverage.yaml @@ -33,7 +33,7 @@ jobs: - name: Install dependencies run: | - uv sync --group dev --extra anthropic --extra aws --extra google --extra langchain --extra websocket + uv sync --group dev --extra anthropic --extra aws --extra google --extra langchain --extra livekit --extra websocket - name: Run tests with coverage run: | diff --git a/.github/workflows/tests.yaml b/.github/workflows/tests.yaml index 8e58845e4..459725da7 100644 --- a/.github/workflows/tests.yaml +++ b/.github/workflows/tests.yaml @@ -37,7 +37,7 @@ jobs: - name: Install dependencies run: | - uv sync --group dev --extra anthropic --extra aws --extra google --extra langchain --extra websocket + uv sync --group dev --extra anthropic --extra aws --extra google --extra langchain --extra livekit --extra websocket - name: Test with pytest run: | diff --git a/pyproject.toml b/pyproject.toml index f86846de3..e99ab62bc 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -125,7 +125,6 @@ dev = [ "build~=1.2.2", "coverage~=7.9.1", "grpcio-tools~=1.67.1", - "livekit~=1.0.13", "pip-tools~=7.4.1", "pre-commit~=4.2.0", "pyright>=1.1.404,<1.2", diff --git a/tests/test_livekit_transport.py b/tests/test_livekit_transport.py index 1a6184d85..472d60cba 100644 --- a/tests/test_livekit_transport.py +++ b/tests/test_livekit_transport.py @@ -14,15 +14,21 @@ only starts when there is a consumer for the frames. import unittest from unittest.mock import AsyncMock, MagicMock, patch -from livekit import rtc +try: + from livekit import rtc -from pipecat.transports.livekit.transport import ( - LiveKitCallbacks, - LiveKitParams, - LiveKitTransportClient, -) + from pipecat.transports.livekit.transport import ( + LiveKitCallbacks, + LiveKitParams, + LiveKitTransportClient, + ) + + LIVEKIT_AVAILABLE = True +except ImportError: + LIVEKIT_AVAILABLE = False +@unittest.skipUnless(LIVEKIT_AVAILABLE, "livekit package not installed") class TestLiveKitVideoStreamMemoryLeak(unittest.IsolatedAsyncioTestCase): """Regression tests for video queue memory leak (#3116). diff --git a/uv.lock b/uv.lock index 374dd0576..2610e2df5 100644 --- a/uv.lock +++ b/uv.lock @@ -4462,7 +4462,6 @@ dev = [ { name = "build" }, { name = "coverage" }, { name = "grpcio-tools" }, - { name = "livekit" }, { name = "pip-tools" }, { name = "pre-commit" }, { name = "pyright" }, @@ -4601,7 +4600,6 @@ dev = [ { name = "build", specifier = "~=1.2.2" }, { name = "coverage", specifier = "~=7.9.1" }, { name = "grpcio-tools", specifier = "~=1.67.1" }, - { name = "livekit", specifier = "~=1.0.13" }, { name = "pip-tools", specifier = "~=7.4.1" }, { name = "pre-commit", specifier = "~=4.2.0" }, { name = "pyright", specifier = ">=1.1.404,<1.2" }, From 1ac811ab32c46dcc9505361734cc4e74482e8b74 Mon Sep 17 00:00:00 2001 From: Luke Payyapilli Date: Tue, 20 Jan 2026 09:19:43 -0500 Subject: [PATCH 0143/1060] chore: revert unrelated uv.lock changes --- uv.lock | 6 ++++++ 1 file changed, 6 insertions(+) diff --git a/uv.lock b/uv.lock index 2610e2df5..45c1f892f 100644 --- a/uv.lock +++ b/uv.lock @@ -2013,6 +2013,7 @@ wheels = [ { url = "https://files.pythonhosted.org/packages/32/6a/33d1702184d94106d3cdd7bfb788e19723206fce152e303473ca3b946c7b/greenlet-3.3.0-cp310-cp310-macosx_11_0_universal2.whl", hash = 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c89083e72ec405445ed47a644bcd5ff16ca00442 Mon Sep 17 00:00:00 2001 From: Paul Kompfner Date: Fri, 16 Jan 2026 22:26:31 -0500 Subject: [PATCH 0144/1060] Improve 20e example to ask the bot to give a recap when loading a previous conversation from disk --- .../foundational/20e-persistent-context-aws-nova-sonic.py | 8 ++++++++ 1 file changed, 8 insertions(+) diff --git a/examples/foundational/20e-persistent-context-aws-nova-sonic.py b/examples/foundational/20e-persistent-context-aws-nova-sonic.py index bd95fb7e7..ebd4afbf1 100644 --- a/examples/foundational/20e-persistent-context-aws-nova-sonic.py +++ b/examples/foundational/20e-persistent-context-aws-nova-sonic.py @@ -114,6 +114,14 @@ async def load_conversation(params: FunctionCallParams): # "content": f"{AWSNovaSonicLLMService.AWAIT_TRIGGER_ASSISTANT_RESPONSE_INSTRUCTION}", # } # ) + # If the last message isn't from the user, add a message asking for a recap + if messages and messages[-1].get("role") != "user": + messages.append( + { + "role": "user", + "content": "Can you catch me up on what we were talking about?", + } + ) params.context.set_messages(messages) await params.llm.reset_conversation() # await params.llm.trigger_assistant_response() From b4d143e39b62c49542158cc392a3efa2702e7760 Mon Sep 17 00:00:00 2001 From: Paul Kompfner Date: Fri, 16 Jan 2026 22:36:35 -0500 Subject: [PATCH 0145/1060] Add CHANGELOG for fixing `AWSNovaSonicLLMService.reset_conversation()` --- changelog/3486.fixed.md | 1 + 1 file changed, 1 insertion(+) create mode 100644 changelog/3486.fixed.md diff --git a/changelog/3486.fixed.md b/changelog/3486.fixed.md new file mode 100644 index 000000000..a02427e6e --- /dev/null +++ b/changelog/3486.fixed.md @@ -0,0 +1 @@ +- Fixed `AWSNovaSonicLLMService.reset_conversation()`, which would previously error out. Now it successfully reconnects and "rehydrates" from the context object. From 06b3ecd2d69d387a52a550672147e0d82468ba87 Mon Sep 17 00:00:00 2001 From: Paul Kompfner Date: Fri, 16 Jan 2026 22:43:49 -0500 Subject: [PATCH 0146/1060] In AWS Nova Sonic service, send the "interactive" user message (which triggers the bot response) only after sending the audio input start event, per the AWS team's recommendation --- src/pipecat/services/aws/nova_sonic/llm.py | 23 +++++++++++++++------- 1 file changed, 16 insertions(+), 7 deletions(-) diff --git a/src/pipecat/services/aws/nova_sonic/llm.py b/src/pipecat/services/aws/nova_sonic/llm.py index e159ae9f6..05baba2bd 100644 --- a/src/pipecat/services/aws/nova_sonic/llm.py +++ b/src/pipecat/services/aws/nova_sonic/llm.py @@ -533,21 +533,30 @@ class AWSNovaSonicLLMService(LLMService): if system_instruction: await self._send_text_event(text=system_instruction, role=Role.SYSTEM) - # Send conversation history + # Send conversation history (except for the last message if it's from the + # user, which we'll send as interactive after starting audio input) messages = llm_connection_params["messages"] + last_user_message = None for i, message in enumerate(messages): # logger.debug(f"Seeding conversation history with message: {message}") - # If last message is from user, mark it as interactive to trigger - # bot response is_last_message = i == len(messages) - 1 - interactive = is_last_message and message.role == Role.USER - await self._send_text_event( - text=message.text, role=message.role, interactive=interactive - ) + if is_last_message and message.role == Role.USER: + # Save for sending after audio input starts + last_user_message = message + else: + await self._send_text_event(text=message.text, role=message.role) # Start audio input await self._send_audio_input_start_event() + # Now send the last user message as interactive to trigger bot response + if last_user_message: + # logger.debug( + # f"Sending last user message as interactive to trigger bot response: {last_user_message}") + await self._send_text_event( + text=last_user_message.text, role=last_user_message.role, interactive=True + ) + # Start receiving events self._receive_task = self.create_task(self._receive_task_handler()) From 6cf0d53d0047d75eb164fa22564d8d0c84bfa2d9 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Aleix=20Conchillo=20Flaqu=C3=A9?= Date: Mon, 19 Jan 2026 20:22:53 -0800 Subject: [PATCH 0147/1060] AIService: handle StartFrame/EndFrame/CancelFrame exceptions If AIService subclasses implement start()/stop()/cancel() and exception are not handled, execution will not continue and therefore the originator frames will not be pushed. This would cause the pipeline to not be started (i.e. StartFrame would not be pushed downstream) or stopped properly. --- changelog/3503.fixed.md | 1 + src/pipecat/services/ai_service.py | 26 ++++++++++++++++++++++---- 2 files changed, 23 insertions(+), 4 deletions(-) create mode 100644 changelog/3503.fixed.md diff --git a/changelog/3503.fixed.md b/changelog/3503.fixed.md new file mode 100644 index 000000000..4218f8781 --- /dev/null +++ b/changelog/3503.fixed.md @@ -0,0 +1 @@ +- Fixed an issue in `AIService` where unhandled exceptions in `start()`, `stop()`, or `cancel()` implementations would prevent `process_frame()` to continue and therefore `StartFrame`, `EndFrame`, or `CancelFrame` from being pushed downstream, causing the pipeline to not start or stop properly. diff --git a/src/pipecat/services/ai_service.py b/src/pipecat/services/ai_service.py index a9952fa00..c03ab9d0e 100644 --- a/src/pipecat/services/ai_service.py +++ b/src/pipecat/services/ai_service.py @@ -148,11 +148,11 @@ class AIService(FrameProcessor): await super().process_frame(frame, direction) if isinstance(frame, StartFrame): - await self.start(frame) - elif isinstance(frame, CancelFrame): - await self.cancel(frame) + await self._start(frame) elif isinstance(frame, EndFrame): - await self.stop(frame) + await self._stop(frame) + elif isinstance(frame, CancelFrame): + await self._cancel(frame) async def process_generator(self, generator: AsyncGenerator[Frame | None, None]): """Process frames from an async generator. @@ -169,3 +169,21 @@ class AIService(FrameProcessor): await self.push_error_frame(f) else: await self.push_frame(f) + + async def _start(self, frame: StartFrame): + try: + await self.start(frame) + except Exception as e: + logger.error(f"{self}: exception processing {frame}: {e}") + + async def _stop(self, frame: EndFrame): + try: + await self.stop(frame) + except Exception as e: + logger.error(f"{self}: exception processing {frame}: {e}") + + async def _cancel(self, frame: CancelFrame): + try: + await self.cancel(frame) + except Exception as e: + logger.error(f"{self}: exception processing {frame}: {e}") From 9a718ded1ed2be52043cb23cd8b81ffb8bbaf223 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Aleix=20Conchillo=20Flaqu=C3=A9?= Date: Mon, 19 Jan 2026 20:30:17 -0800 Subject: [PATCH 0148/1060] NvidiaTTSService: initialize client on StartFrame Initialize client on StartFrame so errrors are reported within the pipeline. --- src/pipecat/services/nvidia/tts.py | 71 +++++++++++++++++++++--------- 1 file changed, 51 insertions(+), 20 deletions(-) diff --git a/src/pipecat/services/nvidia/tts.py b/src/pipecat/services/nvidia/tts.py index 70be24a8f..d62b7e500 100644 --- a/src/pipecat/services/nvidia/tts.py +++ b/src/pipecat/services/nvidia/tts.py @@ -25,6 +25,7 @@ from pydantic import BaseModel from pipecat.frames.frames import ( ErrorFrame, Frame, + StartFrame, TTSAudioRawFrame, TTSStartedFrame, TTSStoppedFrame, @@ -93,6 +94,7 @@ class NvidiaTTSService(TTSService): params = params or NvidiaTTSService.InputParams() + self._server = server self._api_key = api_key self._voice_id = voice_id self._language_code = params.language @@ -102,18 +104,8 @@ class NvidiaTTSService(TTSService): self.set_model_name(model_function_map.get("model_name")) self.set_voice(voice_id) - metadata = [ - ["function-id", self._function_id], - ["authorization", f"Bearer {api_key}"], - ] - auth = riva.client.Auth(None, self._use_ssl, server, metadata) - - self._service = riva.client.SpeechSynthesisService(auth) - - # warm up the service - config_response = self._service.stub.GetRivaSynthesisConfig( - riva.client.proto.riva_tts_pb2.RivaSynthesisConfigRequest() - ) + self._service = None + self._config = None async def set_model(self, model: str): """Attempt to set the TTS model. @@ -129,6 +121,39 @@ class NvidiaTTSService(TTSService): f"{self.__class__.__name__}(api_key=, model_function_map={example})" ) + def _initialize_client(self): + if self._service is not None: + return + + metadata = [ + ["function-id", self._function_id], + ["authorization", f"Bearer {self._api_key}"], + ] + auth = riva.client.Auth(None, self._use_ssl, self._server, metadata) + + self._service = riva.client.SpeechSynthesisService(auth) + + def _create_synthesis_config(self): + if not self._service: + return + + # warm up the service + config = self._service.stub.GetRivaSynthesisConfig( + riva.client.proto.riva_tts_pb2.RivaSynthesisConfigRequest() + ) + return config + + async def start(self, frame: StartFrame): + """Start the Cartesia TTS service. + + Args: + frame: The start frame containing initialization parameters. + """ + await super().start(frame) + self._initialize_client() + self._config = self._create_synthesis_config() + logger.debug(f"Initialized NvidiaTTSService with model: {self.model_name}") + @traced_tts async def run_tts(self, text: str) -> AsyncGenerator[Frame, None]: """Generate speech from text using NVIDIA Riva TTS. @@ -161,12 +186,15 @@ class NvidiaTTSService(TTSService): logger.error(f"{self} exception: {e}") add_response(None) - await self.start_ttfb_metrics() - yield TTSStartedFrame() - - logger.debug(f"{self}: Generating TTS [{text}]") - try: + assert self._service is not None, "TTS service not initialized" + assert self._config is not None, "Synthesis configuration not created" + + await self.start_ttfb_metrics() + yield TTSStartedFrame() + + logger.debug(f"{self}: Generating TTS [{text}]") + queue = asyncio.Queue() await asyncio.to_thread(read_audio_responses, queue) @@ -181,9 +209,12 @@ class NvidiaTTSService(TTSService): ) yield frame resp = await asyncio.wait_for(queue.get(), timeout=NVIDIA_TTS_TIMEOUT_SECS) + + await self.start_tts_usage_metrics(text) + yield TTSStoppedFrame() except asyncio.TimeoutError: logger.error(f"{self} timeout waiting for audio response") yield ErrorFrame(error=f"{self} error: {e}") - - await self.start_tts_usage_metrics(text) - yield TTSStoppedFrame() + except Exception as e: + logger.error(f"{self} exception: {e}") + yield ErrorFrame(error=f"{self} error: {e}") From 671dc8cd9bbe305c31f82d6891ff4a03cef0d6a4 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Aleix=20Conchillo=20Flaqu=C3=A9?= Date: Mon, 19 Jan 2026 20:32:28 -0800 Subject: [PATCH 0149/1060] NvidiaSTTService: initialize client on StartFrame Initialize client on StartFrame so errrors are reported within the pipeline. --- src/pipecat/services/nvidia/stt.py | 91 ++++++++++++++++-------------- 1 file changed, 49 insertions(+), 42 deletions(-) diff --git a/src/pipecat/services/nvidia/stt.py b/src/pipecat/services/nvidia/stt.py index 0d671571f..639e76535 100644 --- a/src/pipecat/services/nvidia/stt.py +++ b/src/pipecat/services/nvidia/stt.py @@ -134,6 +134,7 @@ class NvidiaSTTService(STTService): params = params or NvidiaSTTService.InputParams() + self._server = server self._api_key = api_key self._use_ssl = use_ssl self._profanity_filter = False @@ -162,19 +163,55 @@ class NvidiaSTTService(STTService): self.set_model_name(model_function_map.get("model_name")) - metadata = [ - ["function-id", self._function_id], - ["authorization", f"Bearer {api_key}"], - ] - auth = riva.client.Auth(None, self._use_ssl, server, metadata) - - self._asr_service = riva.client.ASRService(auth) - + self._asr_service = None self._queue = None self._config = None self._thread_task = None self._response_task = None + def _initialize_client(self): + metadata = [ + ["function-id", self._function_id], + ["authorization", f"Bearer {self._api_key}"], + ] + auth = riva.client.Auth(None, self._use_ssl, self._server, metadata) + + self._asr_service = riva.client.ASRService(auth) + + def _create_recognition_config(self): + """Create the NVIDIA Riva ASR recognition configuration.""" + config = riva.client.StreamingRecognitionConfig( + config=riva.client.RecognitionConfig( + encoding=riva.client.AudioEncoding.LINEAR_PCM, + language_code=self._language_code, + model="", + max_alternatives=1, + profanity_filter=self._profanity_filter, + enable_automatic_punctuation=self._automatic_punctuation, + verbatim_transcripts=not self._no_verbatim_transcripts, + sample_rate_hertz=self.sample_rate, + audio_channel_count=1, + ), + interim_results=True, + ) + + riva.client.add_word_boosting_to_config( + config, self._boosted_lm_words, self._boosted_lm_score + ) + + riva.client.add_endpoint_parameters_to_config( + config, + self._start_history, + self._start_threshold, + self._stop_history, + self._stop_history_eou, + self._stop_threshold, + self._stop_threshold_eou, + ) + riva.client.add_custom_configuration_to_config(config, self._custom_configuration) + + return config + def can_generate_metrics(self) -> bool: """Check if this service can generate processing metrics. @@ -206,41 +243,9 @@ class NvidiaSTTService(STTService): frame: StartFrame indicating pipeline start. """ await super().start(frame) + self._initialize_client() + self._config = self._create_recognition_config() - if self._config: - return - - config = riva.client.StreamingRecognitionConfig( - config=riva.client.RecognitionConfig( - encoding=riva.client.AudioEncoding.LINEAR_PCM, - language_code=self._language_code, - model="", - max_alternatives=1, - profanity_filter=self._profanity_filter, - enable_automatic_punctuation=self._automatic_punctuation, - verbatim_transcripts=not self._no_verbatim_transcripts, - sample_rate_hertz=self.sample_rate, - audio_channel_count=1, - ), - interim_results=True, - ) - - riva.client.add_word_boosting_to_config( - config, self._boosted_lm_words, self._boosted_lm_score - ) - - riva.client.add_endpoint_parameters_to_config( - config, - self._start_history, - self._start_threshold, - self._stop_history, - self._stop_history_eou, - self._stop_threshold, - self._stop_threshold_eou, - ) - riva.client.add_custom_configuration_to_config(config, self._custom_configuration) - - self._config = config self._queue = asyncio.Queue() if not self._thread_task: @@ -250,6 +255,8 @@ class NvidiaSTTService(STTService): self._response_queue = asyncio.Queue() self._response_task = self.create_task(self._response_task_handler()) + logger.debug(f"Initialized NvidiaSTTService with model: {self.model_name}") + async def stop(self, frame: EndFrame): """Stop the NVIDIA Riva STT service and clean up resources. From 655006aff5acccccdda50a3f01c990e844b7843b Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Aleix=20Conchillo=20Flaqu=C3=A9?= Date: Mon, 19 Jan 2026 20:31:58 -0800 Subject: [PATCH 0150/1060] NvidiaSegmentedSTTService: simplify exception handling --- src/pipecat/services/nvidia/stt.py | 79 +++++++++++++----------------- 1 file changed, 33 insertions(+), 46 deletions(-) diff --git a/src/pipecat/services/nvidia/stt.py b/src/pipecat/services/nvidia/stt.py index 639e76535..45c59de7a 100644 --- a/src/pipecat/services/nvidia/stt.py +++ b/src/pipecat/services/nvidia/stt.py @@ -510,8 +510,6 @@ class NvidiaSegmentedSTTService(SegmentedSTTService): auth = riva.client.Auth(None, self._use_ssl, self._server, metadata) self._asr_service = riva.client.ASRService(auth) - logger.info(f"Initialized NvidiaSegmentedSTTService with model: {self.model_name}") - def _create_recognition_config(self): """Create the NVIDIA Riva ASR recognition configuration.""" # Create base configuration @@ -579,6 +577,7 @@ class NvidiaSegmentedSTTService(SegmentedSTTService): await super().start(frame) self._initialize_client() self._config = self._create_recognition_config() + logger.debug(f"Initialized NvidiaSegmentedSTTService with model: {self.model_name}") async def set_language(self, language: Language): """Set the language for the STT service. @@ -612,21 +611,12 @@ class NvidiaSegmentedSTTService(SegmentedSTTService): Frame: TranscriptionFrame containing the transcribed text. """ try: - await self.start_processing_metrics() - await self.start_ttfb_metrics() - - # Make sure the client is initialized - if self._asr_service is None: - self._initialize_client() - - # Make sure the config is created - if self._config is None: - self._config = self._create_recognition_config() - - # Type assertion to satisfy the IDE assert self._asr_service is not None, "ASR service not initialized" assert self._config is not None, "Recognition config not created" + await self.start_processing_metrics() + await self.start_ttfb_metrics() + # Process audio with NVIDIA Riva ASR - explicitly request non-future response raw_response = self._asr_service.offline_recognize(audio, self._config, future=False) @@ -634,43 +624,40 @@ class NvidiaSegmentedSTTService(SegmentedSTTService): await self.stop_processing_metrics() # Process the response - handle different possible return types - try: - # If it's a future-like object, get the result - if hasattr(raw_response, "result"): - response = raw_response.result() - else: - response = raw_response + # If it's a future-like object, get the result + if hasattr(raw_response, "result"): + response = raw_response.result() + else: + response = raw_response - # Process transcription results - transcription_found = False + # Process transcription results + transcription_found = False - # Now we can safely check results - # Type hint for the IDE - results = getattr(response, "results", []) + # Now we can safely check results + # Type hint for the IDE + results = getattr(response, "results", []) - for result in results: - alternatives = getattr(result, "alternatives", []) - if alternatives: - text = alternatives[0].transcript.strip() - if text: - logger.debug(f"Transcription: [{text}]") - yield TranscriptionFrame( - text, - self._user_id, - time_now_iso8601(), - self._language_enum, - ) - transcription_found = True + for result in results: + alternatives = getattr(result, "alternatives", []) + if alternatives: + text = alternatives[0].transcript.strip() + if text: + logger.debug(f"Transcription: [{text}]") + yield TranscriptionFrame( + text, + self._user_id, + time_now_iso8601(), + self._language_enum, + ) + transcription_found = True - await self._handle_transcription(text, True, self._language_enum) - - if not transcription_found: - logger.debug("No transcription results found in NVIDIA Riva response") - - except AttributeError as ae: - logger.error(f"Unexpected response structure from NVIDIA Riva: {ae}") - yield ErrorFrame(f"Unexpected NVIDIA Riva response format: {str(ae)}") + await self._handle_transcription(text, True, self._language_enum) + if not transcription_found: + logger.debug(f"{self}: No transcription results found in NVIDIA Riva response") + except AttributeError as ae: + logger.error(f"{self}: Unexpected response structure from NVIDIA Riva: {ae}") + yield ErrorFrame(f"{self}: Unexpected NVIDIA Riva response format: {str(ae)}") except Exception as e: logger.error(f"{self} exception: {e}") yield ErrorFrame(error=f"{self} error: {e}") From a010a020fd7db01a660740de852efe45baf70970 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Aleix=20Conchillo=20Flaqu=C3=A9?= Date: Tue, 20 Jan 2026 09:03:30 -0800 Subject: [PATCH 0151/1060] add changelog fo 3504 --- changelog/3504.fixed.md | 1 + 1 file changed, 1 insertion(+) create mode 100644 changelog/3504.fixed.md diff --git a/changelog/3504.fixed.md b/changelog/3504.fixed.md new file mode 100644 index 000000000..2d675547a --- /dev/null +++ b/changelog/3504.fixed.md @@ -0,0 +1 @@ +- Moved `NVIDIATTSService` and `NVIDIASTTService` client initialization from constructor to `start()` for better error handling. From fa6f924b31b086942942947589d8fe222e2bc260 Mon Sep 17 00:00:00 2001 From: Sunah Suh Date: Fri, 16 Jan 2026 13:51:00 -0600 Subject: [PATCH 0152/1060] Log Daily participant and meeting session IDs upon successful join in Daily Transport --- src/pipecat/transports/daily/transport.py | 6 +++++- 1 file changed, 5 insertions(+), 1 deletion(-) diff --git a/src/pipecat/transports/daily/transport.py b/src/pipecat/transports/daily/transport.py index 203cbb9fa..3b652b517 100644 --- a/src/pipecat/transports/daily/transport.py +++ b/src/pipecat/transports/daily/transport.py @@ -759,7 +759,11 @@ class DailyTransportClient(EventHandler): # Increment leave counter if we successfully joined. self._leave_counter += 1 - logger.info(f"Joined {self._room_url}") + participant_id = data.get("participants", {}).get("local", {}).get("id") + meeting_id = data.get("meetingSession", {}).get("id") + logger.info( + f"Joined {self._room_url}. Participant ID: {participant_id}, Meeting ID: {meeting_id}" + ) await self._callbacks.on_joined(data) From 461bd0a2e089780e11888c276ee89392bc614ce9 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Aleix=20Conchillo=20Flaqu=C3=A9?= Date: Tue, 20 Jan 2026 13:26:40 -0800 Subject: [PATCH 0153/1060] update changelog for #3494 and #3499 --- changelog/3494.fixed.md | 1 + changelog/3499.fixed.md | 1 + 2 files changed, 2 insertions(+) create mode 100644 changelog/3494.fixed.md create mode 100644 changelog/3499.fixed.md diff --git a/changelog/3494.fixed.md b/changelog/3494.fixed.md new file mode 100644 index 000000000..41fbfa74e --- /dev/null +++ b/changelog/3494.fixed.md @@ -0,0 +1 @@ +- Fixed an issue where `UninterruptibleFrame` frames would not be preserved in some cases. diff --git a/changelog/3499.fixed.md b/changelog/3499.fixed.md new file mode 100644 index 000000000..ae893c13d --- /dev/null +++ b/changelog/3499.fixed.md @@ -0,0 +1 @@ +- Fixed memory leak in `LiveKitTransport` when `video_in_enabled` is `False`. From 14495c425a42c6b9ca1c9ec4a55429388d10e502 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Aleix=20Conchillo=20Flaqu=C3=A9?= Date: Tue, 20 Jan 2026 13:43:23 -0800 Subject: [PATCH 0154/1060] NVIDIASTTService: no need for additional queue and task --- changelog/3509.fixed.md | 1 + src/pipecat/services/nvidia/stt.py | 19 +------------------ 2 files changed, 2 insertions(+), 18 deletions(-) create mode 100644 changelog/3509.fixed.md diff --git a/changelog/3509.fixed.md b/changelog/3509.fixed.md new file mode 100644 index 000000000..153060b46 --- /dev/null +++ b/changelog/3509.fixed.md @@ -0,0 +1 @@ +- Optimized `NVIDIASTTService` by removing unnecessary queue and task. diff --git a/src/pipecat/services/nvidia/stt.py b/src/pipecat/services/nvidia/stt.py index 45c59de7a..7d52f5130 100644 --- a/src/pipecat/services/nvidia/stt.py +++ b/src/pipecat/services/nvidia/stt.py @@ -167,7 +167,6 @@ class NvidiaSTTService(STTService): self._queue = None self._config = None self._thread_task = None - self._response_task = None def _initialize_client(self): metadata = [ @@ -251,10 +250,6 @@ class NvidiaSTTService(STTService): if not self._thread_task: self._thread_task = self.create_task(self._thread_task_handler()) - if not self._response_task: - self._response_queue = asyncio.Queue() - self._response_task = self.create_task(self._response_task_handler()) - logger.debug(f"Initialized NvidiaSTTService with model: {self.model_name}") async def stop(self, frame: EndFrame): @@ -280,10 +275,6 @@ class NvidiaSTTService(STTService): await self.cancel_task(self._thread_task) self._thread_task = None - if self._response_task: - await self.cancel_task(self._response_task) - self._response_task = None - def _response_handler(self): responses = self._asr_service.streaming_response_generator( audio_chunks=self, @@ -292,9 +283,7 @@ class NvidiaSTTService(STTService): for response in responses: if not response.results: continue - asyncio.run_coroutine_threadsafe( - self._response_queue.put(response), self.get_event_loop() - ) + asyncio.run_coroutine_threadsafe(self._handle_response(response), self.get_event_loop()) async def _thread_task_handler(self): try: @@ -346,12 +335,6 @@ class NvidiaSTTService(STTService): ) ) - async def _response_task_handler(self): - while True: - response = await self._response_queue.get() - await self._handle_response(response) - self._response_queue.task_done() - async def run_stt(self, audio: bytes) -> AsyncGenerator[Frame, None]: """Process audio data for speech-to-text transcription. From a787fd9cd81c1518df1bbd26909d5e2536c47f20 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Aleix=20Conchillo=20Flaqu=C3=A9?= Date: Tue, 20 Jan 2026 13:44:52 -0800 Subject: [PATCH 0155/1060] NVIDIATTSService: process incoming audio frame right away Process audio as soon as we receive it from the generator. Previously, we were reading from the generator and adding elements into a queue until there was no more data, then we would process the queue. --- changelog/3509.fixed.2.md | 1 + src/pipecat/services/nvidia/tts.py | 54 ++++++++++++++---------------- 2 files changed, 27 insertions(+), 28 deletions(-) create mode 100644 changelog/3509.fixed.2.md diff --git a/changelog/3509.fixed.2.md b/changelog/3509.fixed.2.md new file mode 100644 index 000000000..68053011b --- /dev/null +++ b/changelog/3509.fixed.2.md @@ -0,0 +1 @@ +- Optimized `NVIDIATTSService` to process incoming audio frames immediately. diff --git a/src/pipecat/services/nvidia/tts.py b/src/pipecat/services/nvidia/tts.py index d62b7e500..eddafce01 100644 --- a/src/pipecat/services/nvidia/tts.py +++ b/src/pipecat/services/nvidia/tts.py @@ -12,7 +12,7 @@ gRPC API for high-quality speech synthesis. import asyncio import os -from typing import AsyncGenerator, Mapping, Optional +from typing import AsyncGenerator, AsyncIterable, Generator, Mapping, Optional from pipecat.utils.tracing.service_decorators import traced_tts @@ -35,14 +35,12 @@ from pipecat.transcriptions.language import Language try: import riva.client - + import riva.client.proto.riva_tts_pb2 as rtts except ModuleNotFoundError as e: logger.error(f"Exception: {e}") logger.error("In order to use NVIDIA Riva TTS, you need to `pip install pipecat-ai[nvidia]`.") raise Exception(f"Missing module: {e}") -NVIDIA_TTS_TIMEOUT_SECS = 5 - class NvidiaTTSService(TTSService): """NVIDIA Riva text-to-speech service. @@ -165,26 +163,30 @@ class NvidiaTTSService(TTSService): Frame: Audio frames containing the synthesized speech data. """ - def read_audio_responses(queue: asyncio.Queue): - def add_response(r): - asyncio.run_coroutine_threadsafe(queue.put(r), self.get_event_loop()) + def read_audio_responses() -> Generator[rtts.SynthesizeSpeechResponse, None, None]: + responses = self._service.synthesize_online( + text, + self._voice_id, + self._language_code, + sample_rate_hz=self.sample_rate, + zero_shot_audio_prompt_file=None, + zero_shot_quality=self._quality, + custom_dictionary={}, + ) + return responses + def async_next(it): try: - responses = self._service.synthesize_online( - text, - self._voice_id, - self._language_code, - sample_rate_hz=self.sample_rate, - zero_shot_audio_prompt_file=None, - zero_shot_quality=self._quality, - custom_dictionary={}, - ) - for r in responses: - add_response(r) - add_response(None) - except Exception as e: - logger.error(f"{self} exception: {e}") - add_response(None) + return next(it) + except StopIteration: + return None + + async def async_iterator(iterator) -> AsyncIterable[rtts.SynthesizeSpeechResponse]: + while True: + item = await asyncio.to_thread(async_next, iterator) + if item is None: + return + yield item try: assert self._service is not None, "TTS service not initialized" @@ -195,12 +197,9 @@ class NvidiaTTSService(TTSService): logger.debug(f"{self}: Generating TTS [{text}]") - queue = asyncio.Queue() - await asyncio.to_thread(read_audio_responses, queue) + responses = await asyncio.to_thread(read_audio_responses) - # Wait for the thread to start. - resp = await asyncio.wait_for(queue.get(), timeout=NVIDIA_TTS_TIMEOUT_SECS) - while resp: + async for resp in async_iterator(responses): await self.stop_ttfb_metrics() frame = TTSAudioRawFrame( audio=resp.audio, @@ -208,7 +207,6 @@ class NvidiaTTSService(TTSService): num_channels=1, ) yield frame - resp = await asyncio.wait_for(queue.get(), timeout=NVIDIA_TTS_TIMEOUT_SECS) await self.start_tts_usage_metrics(text) yield TTSStoppedFrame() From 7e0ca113afa73adffce9bc50354d3b6b51db5dda Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Aleix=20Conchillo=20Flaqu=C3=A9?= Date: Tue, 20 Jan 2026 19:04:58 -0800 Subject: [PATCH 0156/1060] CambTTSService: initialize client during StartFrame --- changelog/3511.fixed.md | 1 + src/pipecat/services/camb/tts.py | 11 +++++++++-- 2 files changed, 10 insertions(+), 2 deletions(-) create mode 100644 changelog/3511.fixed.md diff --git a/changelog/3511.fixed.md b/changelog/3511.fixed.md new file mode 100644 index 000000000..1f4f429ac --- /dev/null +++ b/changelog/3511.fixed.md @@ -0,0 +1 @@ +- Fixed a `CambTTSService` issue where client was being initialized in the constructor which wouldn't allow for proper Pipeline error handling. diff --git a/src/pipecat/services/camb/tts.py b/src/pipecat/services/camb/tts.py index 89279604d..00b4eaf9b 100644 --- a/src/pipecat/services/camb/tts.py +++ b/src/pipecat/services/camb/tts.py @@ -199,9 +199,10 @@ class CambTTSService(TTSService): """ super().__init__(sample_rate=sample_rate, **kwargs) - params = params or CambTTSService.InputParams() + self._api_key = api_key + self._timeout = timeout - self._client = AsyncCambAI(api_key=api_key, timeout=timeout) + params = params or CambTTSService.InputParams() # Warn if sample rate doesn't match model's supported rate if sample_rate and sample_rate != MODEL_SAMPLE_RATES.get(model): @@ -222,6 +223,8 @@ class CambTTSService(TTSService): self.set_voice(str(voice_id)) self._voice_id = voice_id + self._client = None + def can_generate_metrics(self) -> bool: """Check if this service can generate processing metrics. @@ -249,6 +252,8 @@ class CambTTSService(TTSService): """ await super().start(frame) + self._client = AsyncCambAI(api_key=self._api_key, timeout=self._timeout) + # Use model-specific sample rate if not explicitly specified if not self._init_sample_rate: self._sample_rate = MODEL_SAMPLE_RATES.get(self.model_name, 22050) @@ -289,6 +294,8 @@ class CambTTSService(TTSService): await self.start_tts_usage_metrics(text) yield TTSStartedFrame() + assert self._client is not None, "Camb.ai TTS service not initialized" + # Buffer for aligning chunks to 2-byte boundaries (16-bit PCM) audio_buffer = b"" From 5f9ff8bd58341bec4720ed0264fbdce03b66db0f Mon Sep 17 00:00:00 2001 From: aconchillo <951761+aconchillo@users.noreply.github.com> Date: Wed, 21 Jan 2026 03:18:50 +0000 Subject: [PATCH 0157/1060] Update changelog for version 0.0.100 --- CHANGELOG.md | 123 +++++++++++++++++++++++++++++++++++ changelog/3169.added.md | 1 - changelog/3287.changed.md | 1 - changelog/3287.fixed.md | 1 - changelog/3349.added.md | 1 - changelog/3446.fixed.md | 8 --- changelog/3454.fixed.md | 1 - changelog/3455.fixed.md | 1 - changelog/3461.added.md | 1 - changelog/3462.fixed.md | 1 - changelog/3479.deprecated.md | 1 - changelog/3480.fixed.md | 1 - changelog/3482.added.md | 1 - changelog/3483.changed.md | 1 - changelog/3484.fixed.md | 1 - changelog/3486.fixed.md | 1 - changelog/3489.fixed.md | 3 - changelog/3490.added.md | 1 - changelog/3494.fixed.md | 1 - changelog/3499.fixed.md | 1 - changelog/3503.fixed.md | 1 - changelog/3504.fixed.md | 1 - changelog/3509.fixed.2.md | 1 - changelog/3509.fixed.md | 1 - changelog/3511.fixed.md | 1 - 25 files changed, 123 insertions(+), 33 deletions(-) delete mode 100644 changelog/3169.added.md delete mode 100644 changelog/3287.changed.md delete mode 100644 changelog/3287.fixed.md delete mode 100644 changelog/3349.added.md delete mode 100644 changelog/3446.fixed.md delete mode 100644 changelog/3454.fixed.md delete mode 100644 changelog/3455.fixed.md delete mode 100644 changelog/3461.added.md delete mode 100644 changelog/3462.fixed.md delete mode 100644 changelog/3479.deprecated.md delete mode 100644 changelog/3480.fixed.md delete mode 100644 changelog/3482.added.md delete mode 100644 changelog/3483.changed.md delete mode 100644 changelog/3484.fixed.md delete mode 100644 changelog/3486.fixed.md delete mode 100644 changelog/3489.fixed.md delete mode 100644 changelog/3490.added.md delete mode 100644 changelog/3494.fixed.md delete mode 100644 changelog/3499.fixed.md delete mode 100644 changelog/3503.fixed.md delete mode 100644 changelog/3504.fixed.md delete mode 100644 changelog/3509.fixed.2.md delete mode 100644 changelog/3509.fixed.md delete mode 100644 changelog/3511.fixed.md diff --git a/CHANGELOG.md b/CHANGELOG.md index ce2bdef9f..1d70f0682 100644 --- a/CHANGELOG.md +++ b/CHANGELOG.md @@ -7,6 +7,129 @@ and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0 +## [0.0.100] - 2026-01-20 + +### Added + +- Added Hathora service to support Hathora-hosted TTS and STT models (only + non-streaming) + (PR [#3169](https://github.com/pipecat-ai/pipecat/pull/3169)) + +- Added `CambTTSService`, using Camb.ai's TTS integration with MARS models + (mars-flash, mars-pro, mars-instruct) for high-quality text-to-speech + synthesis. + (PR [#3349](https://github.com/pipecat-ai/pipecat/pull/3349)) + +- Added the `additional_headers` param to `WebsocketClientParams`, allowing + `WebsocketClientTransport` to send custom headers on connect, for cases such + as authentication. + (PR [#3461](https://github.com/pipecat-ai/pipecat/pull/3461)) + +- Added `UserIdleController` for detecting user idle state, integrated into + `LLMUserAggregator` and `UserTurnProcessor` via optional `user_idle_timeout` + parameter. Emits `on_user_turn_idle` event for application-level handling. + Deprecated `UserIdleProcessor` in favor of the new compositional approach. + (PR [#3482](https://github.com/pipecat-ai/pipecat/pull/3482)) + +- Added `on_user_mute_started` and `on_user_mute_stopped` event handlers to + `LLMUserAggregator` for tracking user mute state changes. + (PR [#3490](https://github.com/pipecat-ai/pipecat/pull/3490)) + +### Changed + +- Enhanced interruption handling in `AsyncAITTSService` by supporting + multi-context WebSocket sessions for more robust context management. + (PR [#3287](https://github.com/pipecat-ai/pipecat/pull/3287)) + +- Throttle `UserSpeakingFrame` to broadcast at most every 200ms instead of on + every audio chunk, reducing frame processing overhead during user speech. + (PR [#3483](https://github.com/pipecat-ai/pipecat/pull/3483)) + +### Deprecated + +- For consistency with other package names, we just deprecated + `pipecat.turns.mute` (introduced in Pipecat 0.0.99) in favor of + `pipecat.turns.user_mute`. + (PR [#3479](https://github.com/pipecat-ai/pipecat/pull/3479)) + +### Fixed + +- Corrected TTFB metric calculation in `AsyncAIHttpTTSService`. + (PR [#3287](https://github.com/pipecat-ai/pipecat/pull/3287)) + +- Fixed an issue where the "bot-llm-text" RTVI event would not fire for + realtime (speech-to-speech) services: + + - `AWSNovaSonicLLMService` + - `GeminiLiveLLMService` + - `OpenAIRealtimeLLMService` + - `GrokRealtimeLLMService` + + The issue was that these services weren't pushing `LLMTextFrame`s. Now + they do. + (PR [#3446](https://github.com/pipecat-ai/pipecat/pull/3446)) + +- Fixed an issue where `on_user_turn_stop_timeout` could fire while a user is + talking when using `ExternalUserTurnStrategies`. + (PR [#3454](https://github.com/pipecat-ai/pipecat/pull/3454)) + +- Fixed an issue where user turn start strategies were not being reset after a + user turn started, causing incorrect strategy behavior. + (PR [#3455](https://github.com/pipecat-ai/pipecat/pull/3455)) + +- Fixed `MinWordsUserTurnStartStrategy` to not aggregate transcriptions, + preventing incorrect turn starts when words are spoken with pauses between + them. + (PR [#3462](https://github.com/pipecat-ai/pipecat/pull/3462)) + +- Fixed an issue where Grok Realtime would error out when running with + SmallWebRTC transport. + (PR [#3480](https://github.com/pipecat-ai/pipecat/pull/3480)) + +- Fixed a `Mem0MemoryService` issue where passing `async_mode: true` was + causing an error. See + https://docs.mem0.ai/platform/features/async-mode-default-change. + (PR [#3484](https://github.com/pipecat-ai/pipecat/pull/3484)) + +- Fixed `AWSNovaSonicLLMService.reset_conversation()`, which would previously + error out. Now it successfully reconnects and "rehydrates" from the context + object. + (PR [#3486](https://github.com/pipecat-ai/pipecat/pull/3486)) + +- Fixed `AzureTTSService` transcript formatting issues: + - Punctuation now appears without extra spaces (e.g., "Hello!" instead of + "Hello !") + - CJK languages (Chinese, Japanese, Korean) no longer have unwanted spaces + between characters + (PR [#3489](https://github.com/pipecat-ai/pipecat/pull/3489)) + +- Fixed an issue where `UninterruptibleFrame` frames would not be preserved in + some cases. + (PR [#3494](https://github.com/pipecat-ai/pipecat/pull/3494)) + +- Fixed memory leak in `LiveKitTransport` when `video_in_enabled` is `False`. + (PR [#3499](https://github.com/pipecat-ai/pipecat/pull/3499)) + +- Fixed an issue in `AIService` where unhandled exceptions in `start()`, + `stop()`, or `cancel()` implementations would prevent `process_frame()` to + continue and therefore `StartFrame`, `EndFrame`, or `CancelFrame` from being + pushed downstream, causing the pipeline to not start or stop properly. + (PR [#3503](https://github.com/pipecat-ai/pipecat/pull/3503)) + +- Moved `NVIDIATTSService` and `NVIDIASTTService` client initialization from + constructor to `start()` for better error handling. + (PR [#3504](https://github.com/pipecat-ai/pipecat/pull/3504)) + +- Optimized `NVIDIATTSService` to process incoming audio frames immediately. + (PR [#3509](https://github.com/pipecat-ai/pipecat/pull/3509)) + +- Optimized `NVIDIASTTService` by removing unnecessary queue and task. + (PR [#3509](https://github.com/pipecat-ai/pipecat/pull/3509)) + +- Fixed a `CambTTSService` issue where client was being initialized in the + constructor which wouldn't allow for proper Pipeline error handling. + (PR [#3511](https://github.com/pipecat-ai/pipecat/pull/3511)) + ## [0.0.99] - 2026-01-13 ### Added diff --git a/changelog/3169.added.md b/changelog/3169.added.md deleted file mode 100644 index d9e4bb9b9..000000000 --- a/changelog/3169.added.md +++ /dev/null @@ -1 +0,0 @@ -- Added Hathora service to support Hathora-hosted TTS and STT models (only non-streaming) \ No newline at end of file diff --git a/changelog/3287.changed.md b/changelog/3287.changed.md deleted file mode 100644 index f0df82966..000000000 --- a/changelog/3287.changed.md +++ /dev/null @@ -1 +0,0 @@ -- Enhanced interruption handling in `AsyncAITTSService` by supporting multi-context WebSocket sessions for more robust context management. \ No newline at end of file diff --git a/changelog/3287.fixed.md b/changelog/3287.fixed.md deleted file mode 100644 index 30ce0b13b..000000000 --- a/changelog/3287.fixed.md +++ /dev/null @@ -1 +0,0 @@ -- Corrected TTFB metric calculation in `AsyncAIHttpTTSService`. \ No newline at end of file diff --git a/changelog/3349.added.md b/changelog/3349.added.md deleted file mode 100644 index a5b282ec8..000000000 --- a/changelog/3349.added.md +++ /dev/null @@ -1 +0,0 @@ -- Added `CambTTSService`, using Camb.ai's TTS integration with MARS models (mars-flash, mars-pro, mars-instruct) for high-quality text-to-speech synthesis. diff --git a/changelog/3446.fixed.md b/changelog/3446.fixed.md deleted file mode 100644 index 64cc3cb32..000000000 --- a/changelog/3446.fixed.md +++ /dev/null @@ -1,8 +0,0 @@ -- Fixed an issue where the "bot-llm-text" RTVI event would not fire for realtime (speech-to-speech) services: - - - `AWSNovaSonicLLMService` - - `GeminiLiveLLMService` - - `OpenAIRealtimeLLMService` - - `GrokRealtimeLLMService` - - The issue was that these services weren't pushing `LLMTextFrame`s. Now they do. diff --git a/changelog/3454.fixed.md b/changelog/3454.fixed.md deleted file mode 100644 index 0269370d7..000000000 --- a/changelog/3454.fixed.md +++ /dev/null @@ -1 +0,0 @@ -- Fixed an issue where `on_user_turn_stop_timeout` could fire while a user is talking when using `ExternalUserTurnStrategies`. diff --git a/changelog/3455.fixed.md b/changelog/3455.fixed.md deleted file mode 100644 index 1dba5838a..000000000 --- a/changelog/3455.fixed.md +++ /dev/null @@ -1 +0,0 @@ -- Fixed an issue where user turn start strategies were not being reset after a user turn started, causing incorrect strategy behavior. diff --git a/changelog/3461.added.md b/changelog/3461.added.md deleted file mode 100644 index e0bc27d83..000000000 --- a/changelog/3461.added.md +++ /dev/null @@ -1 +0,0 @@ -- Added the `additional_headers` param to `WebsocketClientParams`, allowing `WebsocketClientTransport` to send custom headers on connect, for cases such as authentication. diff --git a/changelog/3462.fixed.md b/changelog/3462.fixed.md deleted file mode 100644 index f9ede6a53..000000000 --- a/changelog/3462.fixed.md +++ /dev/null @@ -1 +0,0 @@ -- Fixed `MinWordsUserTurnStartStrategy` to not aggregate transcriptions, preventing incorrect turn starts when words are spoken with pauses between them. diff --git a/changelog/3479.deprecated.md b/changelog/3479.deprecated.md deleted file mode 100644 index 7c58a9d89..000000000 --- a/changelog/3479.deprecated.md +++ /dev/null @@ -1 +0,0 @@ -- For consistency with other package names, we just deprecated `pipecat.turns.mute` (introduced in Pipecat 0.0.99) in favor of `pipecat.turns.user_mute`. diff --git a/changelog/3480.fixed.md b/changelog/3480.fixed.md deleted file mode 100644 index 9d04545ec..000000000 --- a/changelog/3480.fixed.md +++ /dev/null @@ -1 +0,0 @@ -- Fixed an issue where Grok Realtime would error out when running with SmallWebRTC transport. diff --git a/changelog/3482.added.md b/changelog/3482.added.md deleted file mode 100644 index 465d409f4..000000000 --- a/changelog/3482.added.md +++ /dev/null @@ -1 +0,0 @@ -- Added `UserIdleController` for detecting user idle state, integrated into `LLMUserAggregator` and `UserTurnProcessor` via optional `user_idle_timeout` parameter. Emits `on_user_turn_idle` event for application-level handling. Deprecated `UserIdleProcessor` in favor of the new compositional approach. diff --git a/changelog/3483.changed.md b/changelog/3483.changed.md deleted file mode 100644 index 97bb10371..000000000 --- a/changelog/3483.changed.md +++ /dev/null @@ -1 +0,0 @@ -- Throttle `UserSpeakingFrame` to broadcast at most every 200ms instead of on every audio chunk, reducing frame processing overhead during user speech. diff --git a/changelog/3484.fixed.md b/changelog/3484.fixed.md deleted file mode 100644 index 9f2823a3e..000000000 --- a/changelog/3484.fixed.md +++ /dev/null @@ -1 +0,0 @@ -- Fixed a `Mem0MemoryService` issue where passing `async_mode: true` was causing an error. See https://docs.mem0.ai/platform/features/async-mode-default-change. diff --git a/changelog/3486.fixed.md b/changelog/3486.fixed.md deleted file mode 100644 index a02427e6e..000000000 --- a/changelog/3486.fixed.md +++ /dev/null @@ -1 +0,0 @@ -- Fixed `AWSNovaSonicLLMService.reset_conversation()`, which would previously error out. Now it successfully reconnects and "rehydrates" from the context object. diff --git a/changelog/3489.fixed.md b/changelog/3489.fixed.md deleted file mode 100644 index c61b25444..000000000 --- a/changelog/3489.fixed.md +++ /dev/null @@ -1,3 +0,0 @@ -- Fixed `AzureTTSService` transcript formatting issues: - - Punctuation now appears without extra spaces (e.g., "Hello!" instead of "Hello !") - - CJK languages (Chinese, Japanese, Korean) no longer have unwanted spaces between characters diff --git a/changelog/3490.added.md b/changelog/3490.added.md deleted file mode 100644 index 905d35b34..000000000 --- a/changelog/3490.added.md +++ /dev/null @@ -1 +0,0 @@ -- Added `on_user_mute_started` and `on_user_mute_stopped` event handlers to `LLMUserAggregator` for tracking user mute state changes. diff --git a/changelog/3494.fixed.md b/changelog/3494.fixed.md deleted file mode 100644 index 41fbfa74e..000000000 --- a/changelog/3494.fixed.md +++ /dev/null @@ -1 +0,0 @@ -- Fixed an issue where `UninterruptibleFrame` frames would not be preserved in some cases. diff --git a/changelog/3499.fixed.md b/changelog/3499.fixed.md deleted file mode 100644 index ae893c13d..000000000 --- a/changelog/3499.fixed.md +++ /dev/null @@ -1 +0,0 @@ -- Fixed memory leak in `LiveKitTransport` when `video_in_enabled` is `False`. diff --git a/changelog/3503.fixed.md b/changelog/3503.fixed.md deleted file mode 100644 index 4218f8781..000000000 --- a/changelog/3503.fixed.md +++ /dev/null @@ -1 +0,0 @@ -- Fixed an issue in `AIService` where unhandled exceptions in `start()`, `stop()`, or `cancel()` implementations would prevent `process_frame()` to continue and therefore `StartFrame`, `EndFrame`, or `CancelFrame` from being pushed downstream, causing the pipeline to not start or stop properly. diff --git a/changelog/3504.fixed.md b/changelog/3504.fixed.md deleted file mode 100644 index 2d675547a..000000000 --- a/changelog/3504.fixed.md +++ /dev/null @@ -1 +0,0 @@ -- Moved `NVIDIATTSService` and `NVIDIASTTService` client initialization from constructor to `start()` for better error handling. diff --git a/changelog/3509.fixed.2.md b/changelog/3509.fixed.2.md deleted file mode 100644 index 68053011b..000000000 --- a/changelog/3509.fixed.2.md +++ /dev/null @@ -1 +0,0 @@ -- Optimized `NVIDIATTSService` to process incoming audio frames immediately. diff --git a/changelog/3509.fixed.md b/changelog/3509.fixed.md deleted file mode 100644 index 153060b46..000000000 --- a/changelog/3509.fixed.md +++ /dev/null @@ -1 +0,0 @@ -- Optimized `NVIDIASTTService` by removing unnecessary queue and task. diff --git a/changelog/3511.fixed.md b/changelog/3511.fixed.md deleted file mode 100644 index 1f4f429ac..000000000 --- a/changelog/3511.fixed.md +++ /dev/null @@ -1 +0,0 @@ -- Fixed a `CambTTSService` issue where client was being initialized in the constructor which wouldn't allow for proper Pipeline error handling. From 4a724379fcd59aa20e2b203bc8df9a8c3eca8ae7 Mon Sep 17 00:00:00 2001 From: okue Date: Wed, 21 Jan 2026 23:58:49 +0900 Subject: [PATCH 0158/1060] refactor(user_mute): remove unnecessary _bot_speaking assignment in _handle_bot_stopped_speaking The _bot_speaking flag does not need to be set in this method, so the redundant assignment has been removed. --- .../mute_until_first_bot_complete_user_mute_strategy.py | 1 - 1 file changed, 1 deletion(-) diff --git a/src/pipecat/turns/user_mute/mute_until_first_bot_complete_user_mute_strategy.py b/src/pipecat/turns/user_mute/mute_until_first_bot_complete_user_mute_strategy.py index 20fe7016a..c19499e07 100644 --- a/src/pipecat/turns/user_mute/mute_until_first_bot_complete_user_mute_strategy.py +++ b/src/pipecat/turns/user_mute/mute_until_first_bot_complete_user_mute_strategy.py @@ -51,6 +51,5 @@ class MuteUntilFirstBotCompleteUserMuteStrategy(BaseUserMuteStrategy): return not self._first_speech_handled async def _handle_bot_stopped_speaking(self, frame: BotStoppedSpeakingFrame): - self._bot_speaking = False if not self._first_speech_handled: self._first_speech_handled = True From eacd2a4b71071dbd9108afa838ba637b0c39c350 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Aleix=20Conchillo=20Flaqu=C3=A9?= Date: Wed, 21 Jan 2026 14:10:56 -0800 Subject: [PATCH 0159/1060] FrameProcessor: add broadcast_frame_instance() --- src/pipecat/processors/frame_processor.py | 34 +++++ src/pipecat/serializers/protobuf.py | 2 +- tests/test_frame_processor.py | 166 +++++++++++++++++++++- 3 files changed, 200 insertions(+), 2 deletions(-) diff --git a/src/pipecat/processors/frame_processor.py b/src/pipecat/processors/frame_processor.py index 70f44dfca..10aafc5a8 100644 --- a/src/pipecat/processors/frame_processor.py +++ b/src/pipecat/processors/frame_processor.py @@ -12,7 +12,9 @@ management, and frame flow control mechanisms. """ import asyncio +import dataclasses import traceback +from copy import deepcopy from dataclasses import dataclass from enum import Enum from typing import ( @@ -782,6 +784,38 @@ class FrameProcessor(BaseObject): await self.push_frame(frame_cls(**kwargs)) await self.push_frame(frame_cls(**kwargs), FrameDirection.UPSTREAM) + async def broadcast_frame_instance(self, frame: Frame): + """Broadcasts a frame instance upstream and downstream. + + This method extracts the class and init fields from the given frame + instance and creates two new instances to push upstream and downstream. + + Args: + frame: The frame instance to broadcast. + + Note: + Prefer using `broadcast_frame()` when possible, as it is more + efficient. This method should only be used when you are not the + creator of the frame and need to broadcast an existing instance. + """ + frame_cls = type(frame) + init_fields = {f.name: getattr(frame, f.name) for f in dataclasses.fields(frame) if f.init} + extra_fields = { + f.name: getattr(frame, f.name) + for f in dataclasses.fields(frame) + if not f.init and f.name not in ("id", "name") + } + + new_frame = frame_cls(**deepcopy(init_fields)) + for k, v in deepcopy(extra_fields).items(): + setattr(new_frame, k, v) + await self.push_frame(new_frame) + + new_frame = frame_cls(**deepcopy(init_fields)) + for k, v in deepcopy(extra_fields).items(): + setattr(new_frame, k, v) + await self.push_frame(new_frame, FrameDirection.UPSTREAM) + async def __start(self, frame: StartFrame): """Handle the start frame to initialize processor state. diff --git a/src/pipecat/serializers/protobuf.py b/src/pipecat/serializers/protobuf.py index 6d989c7dd..912f20b42 100644 --- a/src/pipecat/serializers/protobuf.py +++ b/src/pipecat/serializers/protobuf.py @@ -126,7 +126,7 @@ class ProtobufFrameSerializer(FrameSerializer): if "pts" in args_dict: del args_dict["pts"] - # Special handling for MessageFrame -> OutputTransportMessageUrgentFrame + # Special handling for MessageFrame -> InputTransportMessageFrame if class_name == MessageFrame: try: msg = json.loads(args_dict["data"]) diff --git a/tests/test_frame_processor.py b/tests/test_frame_processor.py index b3a11ab43..3f8c8ae70 100644 --- a/tests/test_frame_processor.py +++ b/tests/test_frame_processor.py @@ -6,7 +6,8 @@ import asyncio import unittest -from dataclasses import dataclass +from dataclasses import dataclass, field +from typing import List from pipecat.frames.frames import ( DataFrame, @@ -24,6 +25,15 @@ from pipecat.processors.frame_processor import FrameDirection, FrameProcessor from pipecat.tests.utils import SleepFrame, run_test +@dataclass +class BroadcastTestFrame(DataFrame): + """Test frame with init fields for broadcast testing.""" + + text: str = "" + value: int = 0 + items: List[str] = field(default_factory=list) + + class TestFrameProcessor(unittest.IsolatedAsyncioTestCase): async def test_before_after_events(self): identity = IdentityFilter() @@ -186,3 +196,157 @@ class TestFrameProcessor(unittest.IsolatedAsyncioTestCase): frames_to_send=frames_to_send, expected_down_frames=expected_down_frames, ) + + async def test_broadcast_frame(self): + """Test that broadcast_frame creates two separate frames with fresh IDs.""" + downstream_frames: List[Frame] = [] + upstream_frames: List[Frame] = [] + + class BroadcastTestProcessor(FrameProcessor): + async def process_frame(self, frame: Frame, direction: FrameDirection): + await super().process_frame(frame, direction) + if isinstance(frame, TextFrame): + await self.broadcast_frame( + BroadcastTestFrame, text="hello", value=42, items=["a", "b"] + ) + else: + await self.push_frame(frame, direction) + + class CaptureProcessor(FrameProcessor): + def __init__(self, capture_list: List[Frame], direction: FrameDirection): + super().__init__() + self._capture_list = capture_list + self._capture_direction = direction + + async def process_frame(self, frame: Frame, direction: FrameDirection): + await super().process_frame(frame, direction) + if direction == self._capture_direction and isinstance(frame, BroadcastTestFrame): + self._capture_list.append(frame) + await self.push_frame(frame, direction) + + up_capture = CaptureProcessor(upstream_frames, FrameDirection.UPSTREAM) + broadcaster = BroadcastTestProcessor() + down_capture = CaptureProcessor(downstream_frames, FrameDirection.DOWNSTREAM) + + pipeline = Pipeline([up_capture, broadcaster, down_capture]) + + frames_to_send = [TextFrame(text="trigger")] + expected_down_frames = [BroadcastTestFrame] + expected_up_frames = [BroadcastTestFrame] + + await run_test( + pipeline, + frames_to_send=frames_to_send, + expected_down_frames=expected_down_frames, + expected_up_frames=expected_up_frames, + ) + + # Verify we got one frame in each direction + self.assertEqual(len(downstream_frames), 1) + self.assertEqual(len(upstream_frames), 1) + + down_frame = downstream_frames[0] + up_frame = upstream_frames[0] + + # Verify the frames have different IDs (they are separate instances) + self.assertNotEqual(down_frame.id, up_frame.id) + + # Verify the frames have the correct field values + self.assertEqual(down_frame.text, "hello") + self.assertEqual(down_frame.value, 42) + self.assertEqual(down_frame.items, ["a", "b"]) + self.assertEqual(up_frame.text, "hello") + self.assertEqual(up_frame.value, 42) + self.assertEqual(up_frame.items, ["a", "b"]) + + # Verify the items lists are separate instances (not shared references) + self.assertIsNot(down_frame.items, up_frame.items) + + async def test_broadcast_frame_instance(self): + """Test that broadcast_frame_instance copies all fields except id and name.""" + downstream_frames: List[Frame] = [] + upstream_frames: List[Frame] = [] + original_frame: List[Frame] = [] + + class BroadcastInstanceTestProcessor(FrameProcessor): + async def process_frame(self, frame: Frame, direction: FrameDirection): + await super().process_frame(frame, direction) + if isinstance(frame, BroadcastTestFrame): + # Set some non-init fields on the frame + frame.pts = 12345 + frame.metadata = {"key": "value", "nested": {"a": 1}} + original_frame.append(frame) + await self.broadcast_frame_instance(frame) + else: + await self.push_frame(frame, direction) + + class CaptureProcessor(FrameProcessor): + def __init__(self, capture_list: List[Frame], direction: FrameDirection): + super().__init__() + self._capture_list = capture_list + self._capture_direction = direction + + async def process_frame(self, frame: Frame, direction: FrameDirection): + await super().process_frame(frame, direction) + if direction == self._capture_direction and isinstance(frame, BroadcastTestFrame): + self._capture_list.append(frame) + await self.push_frame(frame, direction) + + up_capture = CaptureProcessor(upstream_frames, FrameDirection.UPSTREAM) + broadcaster = BroadcastInstanceTestProcessor() + down_capture = CaptureProcessor(downstream_frames, FrameDirection.DOWNSTREAM) + + pipeline = Pipeline([up_capture, broadcaster, down_capture]) + + # Create a frame with mutable fields to test deep copying + test_frame = BroadcastTestFrame(text="test", value=99, items=["x", "y", "z"]) + + frames_to_send = [test_frame] + expected_down_frames = [BroadcastTestFrame] + expected_up_frames = [BroadcastTestFrame] + + await run_test( + pipeline, + frames_to_send=frames_to_send, + expected_down_frames=expected_down_frames, + expected_up_frames=expected_up_frames, + ) + + # Verify we got one frame in each direction + self.assertEqual(len(downstream_frames), 1) + self.assertEqual(len(upstream_frames), 1) + self.assertEqual(len(original_frame), 1) + + orig = original_frame[0] + down_frame = downstream_frames[0] + up_frame = upstream_frames[0] + + # Verify the frames have different IDs and names (fresh values) + self.assertNotEqual(down_frame.id, orig.id) + self.assertNotEqual(up_frame.id, orig.id) + self.assertNotEqual(down_frame.id, up_frame.id) + self.assertNotEqual(down_frame.name, orig.name) + self.assertNotEqual(up_frame.name, orig.name) + + # Verify init fields are copied correctly + self.assertEqual(down_frame.text, "test") + self.assertEqual(down_frame.value, 99) + self.assertEqual(down_frame.items, ["x", "y", "z"]) + self.assertEqual(up_frame.text, "test") + self.assertEqual(up_frame.value, 99) + self.assertEqual(up_frame.items, ["x", "y", "z"]) + + # Verify non-init fields (except id/name) are copied + self.assertEqual(down_frame.pts, 12345) + self.assertEqual(down_frame.metadata, {"key": "value", "nested": {"a": 1}}) + self.assertEqual(up_frame.pts, 12345) + self.assertEqual(up_frame.metadata, {"key": "value", "nested": {"a": 1}}) + + # Verify mutable fields are deep copied (not shared references) + self.assertIsNot(down_frame.items, orig.items) + self.assertIsNot(up_frame.items, orig.items) + self.assertIsNot(down_frame.items, up_frame.items) + self.assertIsNot(down_frame.metadata, orig.metadata) + self.assertIsNot(up_frame.metadata, orig.metadata) + self.assertIsNot(down_frame.metadata, up_frame.metadata) + self.assertIsNot(down_frame.metadata["nested"], up_frame.metadata["nested"]) From ba0ddb1832a62297c214e4f60fcf5235cf933a04 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Aleix=20Conchillo=20Flaqu=C3=A9?= Date: Wed, 21 Jan 2026 18:05:15 -0800 Subject: [PATCH 0160/1060] FrameProcessor: copy kwargs when broadcasting frame --- src/pipecat/processors/frame_processor.py | 8 ++++---- 1 file changed, 4 insertions(+), 4 deletions(-) diff --git a/src/pipecat/processors/frame_processor.py b/src/pipecat/processors/frame_processor.py index 10aafc5a8..1ad57e0d6 100644 --- a/src/pipecat/processors/frame_processor.py +++ b/src/pipecat/processors/frame_processor.py @@ -781,14 +781,14 @@ class FrameProcessor(BaseObject): frame_cls: The class of the frame to be broadcasted. **kwargs: Keyword arguments to be passed to the frame's constructor. """ - await self.push_frame(frame_cls(**kwargs)) - await self.push_frame(frame_cls(**kwargs), FrameDirection.UPSTREAM) + await self.push_frame(frame_cls(**deepcopy(kwargs))) + await self.push_frame(frame_cls(**deepcopy(kwargs)), FrameDirection.UPSTREAM) async def broadcast_frame_instance(self, frame: Frame): """Broadcasts a frame instance upstream and downstream. - This method extracts the class and init fields from the given frame - instance and creates two new instances to push upstream and downstream. + This method creates two new frame instances copying all fields from the + original frame except `id` and `name`, which get fresh values. Args: frame: The frame instance to broadcast. From 62f4708d43a4f393ff386e305ed37304ed48ab57 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Aleix=20Conchillo=20Flaqu=C3=A9?= Date: Wed, 21 Jan 2026 14:12:47 -0800 Subject: [PATCH 0161/1060] transports: broadcast InputTransportMessageFrame frames --- src/pipecat/transports/daily/transport.py | 5 +++-- src/pipecat/transports/smallwebrtc/transport.py | 3 +-- src/pipecat/transports/websocket/client.py | 3 +++ src/pipecat/transports/websocket/fastapi.py | 3 +++ src/pipecat/transports/websocket/server.py | 4 ++++ 5 files changed, 14 insertions(+), 4 deletions(-) diff --git a/src/pipecat/transports/daily/transport.py b/src/pipecat/transports/daily/transport.py index 3b652b517..e220ab0d8 100644 --- a/src/pipecat/transports/daily/transport.py +++ b/src/pipecat/transports/daily/transport.py @@ -1728,8 +1728,9 @@ class DailyInputTransport(BaseInputTransport): message: The message data to send. sender: ID of the message sender. """ - frame = DailyInputTransportMessageFrame(message=message, participant_id=sender) - await self.push_frame(frame) + await self.broadcast_frame_class( + DailyInputTransportMessageFrame, message=message, participant_id=sender + ) # # Audio in diff --git a/src/pipecat/transports/smallwebrtc/transport.py b/src/pipecat/transports/smallwebrtc/transport.py index e9a07cf40..bcc3c8b79 100644 --- a/src/pipecat/transports/smallwebrtc/transport.py +++ b/src/pipecat/transports/smallwebrtc/transport.py @@ -698,8 +698,7 @@ class SmallWebRTCInputTransport(BaseInputTransport): message: The application message to process. """ logger.debug(f"Received app message inside SmallWebRTCInputTransport {message}") - frame = InputTransportMessageFrame(message=message) - await self.push_frame(frame) + await self.broadcast_frame_class(InputTransportMessageFrame, message=message) # Add this method similar to DailyInputTransport.request_participant_image async def request_participant_image(self, frame: UserImageRequestFrame): diff --git a/src/pipecat/transports/websocket/client.py b/src/pipecat/transports/websocket/client.py index 02c891c54..f55b1f919 100644 --- a/src/pipecat/transports/websocket/client.py +++ b/src/pipecat/transports/websocket/client.py @@ -27,6 +27,7 @@ from pipecat.frames.frames import ( EndFrame, Frame, InputAudioRawFrame, + InputTransportMessageFrame, OutputAudioRawFrame, OutputTransportMessageFrame, OutputTransportMessageUrgentFrame, @@ -298,6 +299,8 @@ class WebsocketClientInputTransport(BaseInputTransport): return if isinstance(frame, InputAudioRawFrame) and self._params.audio_in_enabled: await self.push_audio_frame(frame) + elif isinstance(frame, InputTransportMessageFrame): + await self.broadcast_frame(frame) else: await self.push_frame(frame) diff --git a/src/pipecat/transports/websocket/fastapi.py b/src/pipecat/transports/websocket/fastapi.py index e1d02ac00..a0d02ccec 100644 --- a/src/pipecat/transports/websocket/fastapi.py +++ b/src/pipecat/transports/websocket/fastapi.py @@ -26,6 +26,7 @@ from pipecat.frames.frames import ( EndFrame, Frame, InputAudioRawFrame, + InputTransportMessageFrame, InterruptionFrame, OutputAudioRawFrame, OutputTransportMessageFrame, @@ -311,6 +312,8 @@ class FastAPIWebsocketInputTransport(BaseInputTransport): if isinstance(frame, InputAudioRawFrame): await self.push_audio_frame(frame) + elif isinstance(frame, InputTransportMessageFrame): + await self.broadcast_frame(frame) else: await self.push_frame(frame) except Exception as e: diff --git a/src/pipecat/transports/websocket/server.py b/src/pipecat/transports/websocket/server.py index a31ac5487..acd4faf92 100644 --- a/src/pipecat/transports/websocket/server.py +++ b/src/pipecat/transports/websocket/server.py @@ -25,6 +25,8 @@ from pipecat.frames.frames import ( EndFrame, Frame, InputAudioRawFrame, + InputTransportMessageFrame, + InputTransportMessageUrgentFrame, InterruptionFrame, OutputAudioRawFrame, OutputTransportMessageFrame, @@ -214,6 +216,8 @@ class WebsocketServerInputTransport(BaseInputTransport): if isinstance(frame, InputAudioRawFrame): await self.push_audio_frame(frame) + elif isinstance(frame, InputTransportMessageFrame): + await self.broadcast_frame(frame) else: await self.push_frame(frame) except Exception as e: From cc61cdbba37ad191e0049de463485b7ccdb09b56 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Aleix=20Conchillo=20Flaqu=C3=A9?= Date: Wed, 21 Jan 2026 14:13:17 -0800 Subject: [PATCH 0162/1060] RTVIProcessor: add create_rtvi_observer() --- src/pipecat/processors/frameworks/rtvi.py | 12 +++++++++++ src/pipecat/services/google/rtvi.py | 25 ++++++++++++++++++++--- 2 files changed, 34 insertions(+), 3 deletions(-) diff --git a/src/pipecat/processors/frameworks/rtvi.py b/src/pipecat/processors/frameworks/rtvi.py index 7ea04ecf2..ee25af839 100644 --- a/src/pipecat/processors/frameworks/rtvi.py +++ b/src/pipecat/processors/frameworks/rtvi.py @@ -1413,6 +1413,18 @@ class RTVIProcessor(FrameProcessor): self._registered_services[service.name] = service + def create_rtvi_observer(self, *, params: Optional[RTVIObserverParams] = None, **kwargs): + """Creates a new RTVI Observer. + + Args: + params: Settings to enable/disable specific messages. + **kwargs: Additional arguments passed to the observer. + + Returns: + A new RTVI observer. + """ + return RTVIObserver(self, params=params, **kwargs) + async def set_client_ready(self): """Mark the client as ready and trigger the ready event.""" self._client_ready = True diff --git a/src/pipecat/services/google/rtvi.py b/src/pipecat/services/google/rtvi.py index 1ef70d67d..738b0ab9d 100644 --- a/src/pipecat/services/google/rtvi.py +++ b/src/pipecat/services/google/rtvi.py @@ -4,7 +4,7 @@ # SPDX-License-Identifier: BSD 2-Clause License # -"""Google RTVI integration models and observer implementation. +"""Google RTVI processor and observer implementation. This module provides integration with Google's services through the RTVI framework, including models for search responses and an observer for handling Google-specific @@ -16,7 +16,7 @@ from typing import List, Literal, Optional from pydantic import BaseModel from pipecat.observers.base_observer import FramePushed -from pipecat.processors.frameworks.rtvi import RTVIObserver, RTVIProcessor +from pipecat.processors.frameworks.rtvi import RTVIObserver, RTVIObserverParams, RTVIProcessor from pipecat.services.google.frames import LLMSearchOrigin, LLMSearchResponseFrame @@ -86,4 +86,23 @@ class GoogleRTVIObserver(RTVIObserver): rendered_content=frame.rendered_content, ) ) - await self.push_transport_message_urgent(message) + await self.send_rtvi_message(message) + + +class GoogleRTVIProcessor(RTVIProcessor): + """RTVI processor for Google service integration. + + Creates a specific Google RTVI Observer. + """ + + def create_rtvi_observer(self, *, params: Optional[RTVIObserverParams] = None, **kwargs): + """Creates a new RTVI Observer. + + Args: + params: Settings to enable/disable specific messages. + **kwargs: Additional arguments passed to the observer. + + Returns: + A new RTVI observer. + """ + return GoogleRTVIObserver(self) From e85a00cc0ee435eff8eb931c11aa0bccd018bed4 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Aleix=20Conchillo=20Flaqu=C3=A9?= Date: Wed, 21 Jan 2026 14:14:43 -0800 Subject: [PATCH 0163/1060] PipelineTask: automatically add RTVI processor and RTVI observer If `enable_rtvi` is enabled (enabled by default) and RTVI processor will be added automatically to the pipeline. Also, and RTVI observer will be registered. --- src/pipecat/pipeline/task.py | 31 ++++++++++++++++++++++++++++++- 1 file changed, 30 insertions(+), 1 deletion(-) diff --git a/src/pipecat/pipeline/task.py b/src/pipecat/pipeline/task.py index 6d4b4c039..9a2f1d33d 100644 --- a/src/pipecat/pipeline/task.py +++ b/src/pipecat/pipeline/task.py @@ -49,6 +49,7 @@ from pipecat.pipeline.pipeline import Pipeline, PipelineSink, PipelineSource from pipecat.pipeline.task_observer import TaskObserver from pipecat.processors.aggregators.llm_response import LLMUserContextAggregator from pipecat.processors.frame_processor import FrameDirection, FrameProcessor, FrameProcessorSetup +from pipecat.processors.frameworks.rtvi import RTVIObserverParams, RTVIProcessor from pipecat.utils.asyncio.task_manager import BaseTaskManager, TaskManager, TaskManagerParams from pipecat.utils.tracing.setup import is_tracing_available from pipecat.utils.tracing.turn_trace_observer import TurnTraceObserver @@ -225,9 +226,12 @@ class PipelineTask(BasePipelineTask): conversation_id: Optional[str] = None, enable_tracing: bool = False, enable_turn_tracking: bool = True, + enable_rtvi: bool = True, idle_timeout_frames: Tuple[Type[Frame], ...] = (BotSpeakingFrame, UserSpeakingFrame), idle_timeout_secs: Optional[float] = IDLE_TIMEOUT_SECS, observers: Optional[List[BaseObserver]] = None, + rtvi_processor: Optional[RTVIProcessor] = None, + rtvi_observer_params: Optional[RTVIObserverParams] = None, task_manager: Optional[BaseTaskManager] = None, ): """Initialize the PipelineTask. @@ -244,6 +248,7 @@ class PipelineTask(BasePipelineTask): check_dangling_tasks: Whether to check for processors' tasks finishing properly. clock: Clock implementation for timing operations. conversation_id: Optional custom ID for the conversation. + enable_rtvi: Whether to automatically add RTVI support to the pipeline. enable_tracing: Whether to enable tracing. enable_turn_tracking: Whether to enable turn tracking. idle_timeout_frames: A tuple with the frames that should trigger an idle @@ -252,6 +257,8 @@ class PipelineTask(BasePipelineTask): None. If a pipeline is idle the pipeline task will be cancelled automatically. observers: List of observers for monitoring pipeline execution. + rtvi_observer_params: The RTVI observer parameter to use if RTVI is enabled. + rtvi_processor: The RTVI processor to add if RTVI is enabled. task_manager: Optional task manager for handling asyncio tasks. """ super().__init__() @@ -306,6 +313,16 @@ class PipelineTask(BasePipelineTask): self._heartbeat_push_task: Optional[asyncio.Task] = None self._heartbeat_monitor_task: Optional[asyncio.Task] = None + # RTVI support + self._rtvi = None + if enable_rtvi: + self._rtvi = rtvi_processor or RTVIProcessor() + observers.append(self._rtvi.create_rtvi_observer(params=rtvi_observer_params)) + + @self.rtvi.event_handler("on_client_ready") + async def on_client_ready(rtvi: RTVIProcessor): + await rtvi.set_bot_ready() + # This is the idle event. When selected frames are pushed from any # processor we consider the pipeline is not idle. We use an observer # which will be listening any part of the pipeline. @@ -335,7 +352,8 @@ class PipelineTask(BasePipelineTask): # allows us to receive and react to downstream frames. source = PipelineSource(self._source_push_frame, name=f"{self}::Source") sink = PipelineSink(self._sink_push_frame, name=f"{self}::Sink") - self._pipeline = Pipeline([pipeline], source=source, sink=sink) + processors = [self._rtvi, pipeline] if self._rtvi else [pipeline] + self._pipeline = Pipeline(processors, source=source, sink=sink) # The task observer acts as a proxy to the provided observers. This way, # we only need to pass a single observer (using the StartFrame) which @@ -398,6 +416,17 @@ class PipelineTask(BasePipelineTask): """ return self._turn_trace_observer + @property + def rtvi(self) -> RTVIProcessor: + """Get the RTVI processor if RTVI is enabled. + + Returns: + The RTVI processor added to the pipeline when RTVI is enabled. + """ + if not self._rtvi: + raise Exception(f"{self} RTVI is not enabled.") + return self._rtvi + def event_handler(self, event_name: str): """Decorator for registering event handlers. From 054e50486824a9b18a3c0faa0556d44cfb940d0f Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Aleix=20Conchillo=20Flaqu=C3=A9?= Date: Wed, 21 Jan 2026 14:16:51 -0800 Subject: [PATCH 0164/1060] examples(foundational): remove RTVI (automatically added by PipelineTask) --- .../foundational/07zb-interruptible-inworld-http.py | 5 ----- examples/foundational/07zb-interruptible-inworld.py | 5 ----- examples/foundational/07ze-interruptible-hume.py | 9 --------- examples/foundational/37-mem0.py | 7 +------ examples/foundational/38b-smart-turn-local.py | 7 +------ examples/foundational/46-video-processing.py | 11 ++--------- 6 files changed, 4 insertions(+), 40 deletions(-) diff --git a/examples/foundational/07zb-interruptible-inworld-http.py b/examples/foundational/07zb-interruptible-inworld-http.py index b2bf05660..c67984f7c 100644 --- a/examples/foundational/07zb-interruptible-inworld-http.py +++ b/examples/foundational/07zb-interruptible-inworld-http.py @@ -23,7 +23,6 @@ from pipecat.processors.aggregators.llm_response_universal import ( LLMContextAggregatorPair, LLMUserAggregatorParams, ) -from pipecat.processors.frameworks.rtvi import RTVIObserver, RTVIProcessor from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport from pipecat.services.deepgram.stt import DeepgramSTTService @@ -93,12 +92,9 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): ), ) - rtvi = RTVIProcessor() - pipeline = Pipeline( [ transport.input(), - rtvi, stt, user_aggregator, llm, @@ -115,7 +111,6 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): enable_usage_metrics=True, ), observers=[ - RTVIObserver(rtvi), DebugLogObserver( frame_types={ TTSTextFrame: (BaseOutputTransport, FrameEndpoint.SOURCE), diff --git a/examples/foundational/07zb-interruptible-inworld.py b/examples/foundational/07zb-interruptible-inworld.py index 8d3d351a5..46e07dc5f 100644 --- a/examples/foundational/07zb-interruptible-inworld.py +++ b/examples/foundational/07zb-interruptible-inworld.py @@ -22,7 +22,6 @@ from pipecat.processors.aggregators.llm_response_universal import ( LLMContextAggregatorPair, LLMUserAggregatorParams, ) -from pipecat.processors.frameworks.rtvi import RTVIConfig, RTVIObserver, RTVIProcessor from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport from pipecat.services.deepgram.stt import DeepgramSTTService @@ -88,12 +87,9 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): ), ) - rtvi = RTVIProcessor(config=RTVIConfig(config=[])) - pipeline = Pipeline( [ transport.input(), - rtvi, stt, user_aggregator, llm, @@ -110,7 +106,6 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): enable_usage_metrics=True, ), observers=[ - RTVIObserver(rtvi), DebugLogObserver( frame_types={ TTSTextFrame: (BaseOutputTransport, FrameEndpoint.SOURCE), diff --git a/examples/foundational/07ze-interruptible-hume.py b/examples/foundational/07ze-interruptible-hume.py index 33ea4d278..e9a8e355c 100644 --- a/examples/foundational/07ze-interruptible-hume.py +++ b/examples/foundational/07ze-interruptible-hume.py @@ -22,7 +22,6 @@ from pipecat.processors.aggregators.llm_response_universal import ( LLMContextAggregatorPair, LLMUserAggregatorParams, ) -from pipecat.processors.frameworks.rtvi import RTVIConfig, RTVIObserver, RTVIProcessor from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport from pipecat.services.deepgram.stt import DeepgramSTTService @@ -90,12 +89,9 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): ), ) - rtvi = RTVIProcessor(config=RTVIConfig(config=[])) - pipeline = Pipeline( [ transport.input(), # Transport user input - rtvi, stt, user_aggregator, # User responses llm, # LLM @@ -114,7 +110,6 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): ), idle_timeout_secs=runner_args.pipeline_idle_timeout_secs, observers=[ - RTVIObserver(rtvi), DebugLogObserver( frame_types={ TTSTextFrame: (BaseOutputTransport, FrameEndpoint.SOURCE), @@ -123,10 +118,6 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): ], ) - @rtvi.event_handler("on_client_ready") - async def on_client_ready(rtvi): - await rtvi.set_bot_ready() - @transport.event_handler("on_client_connected") async def on_client_connected(transport, client): logger.info(f"Client connected") diff --git a/examples/foundational/37-mem0.py b/examples/foundational/37-mem0.py index c82d39edc..08a739c0a 100644 --- a/examples/foundational/37-mem0.py +++ b/examples/foundational/37-mem0.py @@ -59,7 +59,6 @@ from pipecat.processors.aggregators.llm_response_universal import ( LLMContextAggregatorPair, LLMUserAggregatorParams, ) -from pipecat.processors.frameworks.rtvi import RTVIConfig, RTVIObserver, RTVIProcessor from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport from pipecat.services.deepgram.stt import DeepgramSTTService @@ -255,12 +254,10 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): ), ), ) - rtvi = RTVIProcessor(config=RTVIConfig(config=[])) pipeline = Pipeline( [ transport.input(), - rtvi, stt, user_aggregator, memory, @@ -278,12 +275,10 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): enable_usage_metrics=True, ), idle_timeout_secs=runner_args.pipeline_idle_timeout_secs, - observers=[RTVIObserver(rtvi)], ) - @rtvi.event_handler("on_client_ready") + @task.rtvi.event_handler("on_client_ready") async def on_client_ready(rtvi): - await rtvi.set_bot_ready() # Get personalized greeting based on user memories. Can pass agent_id and run_id as per requirement of the application to manage short term memory or agent specific memory. greeting = await get_initial_greeting( memory_client=memory.memory_client, user_id=USER_ID, agent_id=None, run_id=None diff --git a/examples/foundational/38b-smart-turn-local.py b/examples/foundational/38b-smart-turn-local.py index 37112de4d..85a320631 100644 --- a/examples/foundational/38b-smart-turn-local.py +++ b/examples/foundational/38b-smart-turn-local.py @@ -22,7 +22,6 @@ from pipecat.processors.aggregators.llm_response_universal import ( LLMContextAggregatorPair, LLMUserAggregatorParams, ) -from pipecat.processors.frameworks.rtvi import RTVIObserver, RTVIProcessor from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport from pipecat.services.cartesia.tts import CartesiaTTSService @@ -87,8 +86,6 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): ), ) - rtvi = RTVIProcessor() - pipeline = Pipeline( [ transport.input(), # Transport user input @@ -108,13 +105,11 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): enable_metrics=True, enable_usage_metrics=True, ), - observers=[RTVIObserver(rtvi)], idle_timeout_secs=runner_args.pipeline_idle_timeout_secs, ) - @rtvi.event_handler("on_client_ready") + @task.rtvi.event_handler("on_client_ready") async def on_client_ready(rtvi): - await rtvi.set_bot_ready() # Kick off the conversation messages.append({"role": "system", "content": "Please introduce yourself to the user."}) await task.queue_frames([LLMRunFrame()]) diff --git a/examples/foundational/46-video-processing.py b/examples/foundational/46-video-processing.py index c35843eab..bb3d57f04 100644 --- a/examples/foundational/46-video-processing.py +++ b/examples/foundational/46-video-processing.py @@ -1,5 +1,5 @@ # -# Copyright (c) 2025, Daily +# Copyright (c) 2024-2026, Daily # # SPDX-License-Identifier: BSD 2-Clause License # @@ -22,7 +22,6 @@ from pipecat.processors.aggregators.llm_response_universal import ( LLMUserAggregatorParams, ) from pipecat.processors.frame_processor import FrameDirection, FrameProcessor -from pipecat.processors.frameworks.rtvi import RTVIObserver, RTVIProcessor from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport from pipecat.services.google.gemini_live.llm import GeminiLiveLLMService @@ -125,14 +124,10 @@ async def run_bot(pipecat_transport): ), ) - # RTVI events for Pipecat client UI - rtvi = RTVIProcessor() - pipeline = Pipeline( [ pipecat_transport.input(), user_aggregator, - rtvi, llm, # LLM EdgeDetectionProcessor( pipecat_transport._params.video_out_width, @@ -149,13 +144,11 @@ async def run_bot(pipecat_transport): enable_metrics=True, enable_usage_metrics=True, ), - observers=[RTVIObserver(rtvi)], ) - @rtvi.event_handler("on_client_ready") + @task.rtvi.event_handler("on_client_ready") async def on_client_ready(rtvi): logger.info("Pipecat client ready.") - await rtvi.set_bot_ready() # Kick off the conversation. await task.queue_frames([LLMRunFrame()]) From 124a3c35afa0c52e1dedb543790de7d6f34919e7 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Aleix=20Conchillo=20Flaqu=C3=A9?= Date: Wed, 21 Jan 2026 14:25:25 -0800 Subject: [PATCH 0165/1060] RTVIObserver: don't handle some frames direction --- src/pipecat/processors/frameworks/rtvi.py | 2 -- 1 file changed, 2 deletions(-) diff --git a/src/pipecat/processors/frameworks/rtvi.py b/src/pipecat/processors/frameworks/rtvi.py index ee25af839..87ad556d9 100644 --- a/src/pipecat/processors/frameworks/rtvi.py +++ b/src/pipecat/processors/frameworks/rtvi.py @@ -1100,13 +1100,11 @@ class RTVIObserver(BaseObserver): if ( isinstance(frame, (UserStartedSpeakingFrame, UserStoppedSpeakingFrame)) - and (direction == FrameDirection.DOWNSTREAM) and self._params.user_speaking_enabled ): await self._handle_interruptions(frame) elif ( isinstance(frame, (BotStartedSpeakingFrame, BotStoppedSpeakingFrame)) - and (direction == FrameDirection.UPSTREAM) and self._params.bot_speaking_enabled ): await self._handle_bot_speaking(frame) From 0ee11ad3335743dfe9b01c4a1798aee89874fd68 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Aleix=20Conchillo=20Flaqu=C3=A9?= Date: Wed, 21 Jan 2026 14:31:04 -0800 Subject: [PATCH 0166/1060] tests: disable RTVI in tests by default --- src/pipecat/tests/utils.py | 11 +++++++---- 1 file changed, 7 insertions(+), 4 deletions(-) diff --git a/src/pipecat/tests/utils.py b/src/pipecat/tests/utils.py index ac5739829..356fb8545 100644 --- a/src/pipecat/tests/utils.py +++ b/src/pipecat/tests/utils.py @@ -123,9 +123,10 @@ class QueuedFrameProcessor(FrameProcessor): async def run_test( processor: FrameProcessor, *, - frames_to_send: Sequence[Frame], + enable_rtvi: bool = False, expected_down_frames: Optional[Sequence[type]] = None, expected_up_frames: Optional[Sequence[type]] = None, + frames_to_send: Sequence[Frame], ignore_start: bool = True, observers: Optional[List[BaseObserver]] = None, pipeline_params: Optional[PipelineParams] = None, @@ -139,9 +140,10 @@ async def run_test( Args: processor: The frame processor to test. - frames_to_send: Sequence of frames to send through the processor. + enable_rtvi: Whether RTVI should be enabled in this test. expected_down_frames: Expected frame types flowing downstream (optional). expected_up_frames: Expected frame types flowing upstream (optional). + frames_to_send: Sequence of frames to send through the processor. ignore_start: Whether to ignore StartFrames in frame validation. observers: Optional list of observers to attach to the pipeline. pipeline_params: Optional pipeline parameters. @@ -173,9 +175,10 @@ async def run_test( task = PipelineTask( pipeline, - params=pipeline_params, - observers=observers, cancel_on_idle_timeout=False, + enable_rtvi=enable_rtvi, + observers=observers, + params=pipeline_params, ) async def push_frames(): From 9e8f8b45c682633ac354149f5c4ac6f93fc33925 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Aleix=20Conchillo=20Flaqu=C3=A9?= Date: Wed, 21 Jan 2026 14:39:57 -0800 Subject: [PATCH 0167/1060] added changelog files for #3519 --- changelog/3519.added.2.md | 1 + changelog/3519.added.3.md | 1 + changelog/3519.added.md | 1 + changelog/3519.fixed.2.md | 1 + changelog/3519.fixed.md | 1 + 5 files changed, 5 insertions(+) create mode 100644 changelog/3519.added.2.md create mode 100644 changelog/3519.added.3.md create mode 100644 changelog/3519.added.md create mode 100644 changelog/3519.fixed.2.md create mode 100644 changelog/3519.fixed.md diff --git a/changelog/3519.added.2.md b/changelog/3519.added.2.md new file mode 100644 index 000000000..03e2372ad --- /dev/null +++ b/changelog/3519.added.2.md @@ -0,0 +1 @@ +- Added `RTVIProcessor.create_rtvi_observer()` factory method for creating RTVI observers. diff --git a/changelog/3519.added.3.md b/changelog/3519.added.3.md new file mode 100644 index 000000000..7ea1e638c --- /dev/null +++ b/changelog/3519.added.3.md @@ -0,0 +1 @@ +- Added `FrameProcessor.broadcast_frame_instance(frame)` method to broadcast a frame instance by extracting its fields and creating new instances for each direction. diff --git a/changelog/3519.added.md b/changelog/3519.added.md new file mode 100644 index 000000000..5ed2bd522 --- /dev/null +++ b/changelog/3519.added.md @@ -0,0 +1 @@ +- `PipelineTask` now automatically adds `RTVIProcessor` and registers `RTVIObserver` when `enable_rtvi=True` (default), simplifying pipeline setup. diff --git a/changelog/3519.fixed.2.md b/changelog/3519.fixed.2.md new file mode 100644 index 000000000..bcd384f7f --- /dev/null +++ b/changelog/3519.fixed.2.md @@ -0,0 +1 @@ +- Fixed `FrameProcessor.broadcast_frame()` to deep copy kwargs, preventing shared mutable references between the downstream and upstream frame instances. diff --git a/changelog/3519.fixed.md b/changelog/3519.fixed.md new file mode 100644 index 000000000..cabaa5a3e --- /dev/null +++ b/changelog/3519.fixed.md @@ -0,0 +1 @@ +- Transports now properly broadcast `InputTransportMessageFrame` frames both upstream and downstream instead of only pushing downstream. From 7aa7b86aed78f0c5a1be44c90b211ec2c4b6a37d Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Aleix=20Conchillo=20Flaqu=C3=A9?= Date: Wed, 21 Jan 2026 18:43:04 -0800 Subject: [PATCH 0168/1060] claude: initial /changelog skill --- .claude/skills/changelog/SKILL.md | 40 +++++++++++++++++++++++++++++++ 1 file changed, 40 insertions(+) create mode 100644 .claude/skills/changelog/SKILL.md diff --git a/.claude/skills/changelog/SKILL.md b/.claude/skills/changelog/SKILL.md new file mode 100644 index 000000000..0feb6b92c --- /dev/null +++ b/.claude/skills/changelog/SKILL.md @@ -0,0 +1,40 @@ +--- +name: changelog +description: Create changelog files for important commits in a PR +--- + +Create changelog files for the important commits in this PR. The PR number is provided as an argument. + +## Instructions + +1. First, check what commits are on the current branch compared to main: + ``` + git log main..HEAD --oneline + ``` + +2. For each significant change, create a changelog file in the `changelog/` folder using the format: + - `{PR_NUMBER}.added.md` - for new features + - `{PR_NUMBER}.added.2.md`, `{PR_NUMBER}.added.3.md` - for additional new features + - `{PR_NUMBER}.changed.md` - for changes to existing functionality + - `{PR_NUMBER}.fixed.md` - for bug fixes + - `{PR_NUMBER}.deprecated.md` - for deprecations + +3. Each changelog file should at least contain a main single line starting with `- ` followed by a clear description of the change. + +4. If the change is complicated, changelog files can have indented lines after the main line with additional details or code samples. + +5. Use ⚠️ emoji prefix for breaking changes. + +## Example + +For PR #3519 with a new feature and a bug fix: + +`changelog/3519.added.md`: +``` +- Added `SomeNewFeature` for doing something useful. +``` + +`changelog/3519.fixed.md`: +``` +- Fixed an issue where something was not working correctly. +``` From 6e44a2ab493371e6c28ca823eb118abf3696bcac Mon Sep 17 00:00:00 2001 From: Om Chauhan Date: Wed, 21 Jan 2026 08:14:48 +0530 Subject: [PATCH 0169/1060] feat(task): add additive filter methods for frame monitoring --- src/pipecat/pipeline/task.py | 42 ++++++++++++++++++++++++++++++++++++ 1 file changed, 42 insertions(+) diff --git a/src/pipecat/pipeline/task.py b/src/pipecat/pipeline/task.py index 9a2f1d33d..20b4adf36 100644 --- a/src/pipecat/pipeline/task.py +++ b/src/pipecat/pipeline/task.py @@ -427,6 +427,24 @@ class PipelineTask(BasePipelineTask): raise Exception(f"{self} RTVI is not enabled.") return self._rtvi + @property + def reached_upstream_types(self) -> Tuple[Type[Frame], ...]: + """Get the currently configured upstream frame type filters. + + Returns: + Tuple of frame types that trigger the on_frame_reached_upstream event. + """ + return self._reached_upstream_types + + @property + def reached_downstream_types(self) -> Tuple[Type[Frame], ...]: + """Get the currently configured downstream frame type filters. + + Returns: + Tuple of frame types that trigger the on_frame_reached_downstream event. + """ + return self._reached_downstream_types + def event_handler(self, event_name: str): """Decorator for registering event handlers. @@ -480,6 +498,30 @@ class PipelineTask(BasePipelineTask): """ self._reached_downstream_types = types + def add_reached_upstream_filter(self, types: Tuple[Type[Frame], ...]): + """Add frame types to trigger the on_frame_reached_upstream event. + + Args: + types: Tuple of frame types to add to upstream monitoring. + """ + if not types: + return + current = set(self._reached_upstream_types) + current.update(types) + self._reached_upstream_types = tuple(current) + + def add_reached_downstream_filter(self, types: Tuple[Type[Frame], ...]): + """Add frame types to trigger the on_frame_reached_downstream event. + + Args: + types: Tuple of frame types to add to downstream monitoring. + """ + if not types: + return + current = set(self._reached_downstream_types) + current.update(types) + self._reached_downstream_types = tuple(current) + def has_finished(self) -> bool: """Check if the pipeline task has finished execution. From 9c0bf892472cf0d8b92f87d7547342156856fca2 Mon Sep 17 00:00:00 2001 From: Om Chauhan Date: Wed, 21 Jan 2026 08:36:20 +0530 Subject: [PATCH 0170/1060] added changelog --- changelog/3510.added.2.md | 1 + changelog/3510.added.md | 1 + 2 files changed, 2 insertions(+) create mode 100644 changelog/3510.added.2.md create mode 100644 changelog/3510.added.md diff --git a/changelog/3510.added.2.md b/changelog/3510.added.2.md new file mode 100644 index 000000000..e03b81ee3 --- /dev/null +++ b/changelog/3510.added.2.md @@ -0,0 +1 @@ +- Added `add_reached_upstream_filter()` and `add_reached_downstream_filter()` methods to `PipelineTask` for appending frame types. \ No newline at end of file diff --git a/changelog/3510.added.md b/changelog/3510.added.md new file mode 100644 index 000000000..93d9ef179 --- /dev/null +++ b/changelog/3510.added.md @@ -0,0 +1 @@ +- Added `reached_upstream_types` and `reached_downstream_types` read-only properties to `PipelineTask` for inspecting current frame filters. \ No newline at end of file From 87c12f3098c4176788a8090c1890bdf7dbd00bf0 Mon Sep 17 00:00:00 2001 From: Om Chauhan Date: Thu, 22 Jan 2026 08:39:31 +0530 Subject: [PATCH 0171/1060] changed frame filter storage type from tuples to sets --- changelog/3510.changed.3.md | 1 + src/pipecat/pipeline/task.py | 30 +++++++++++------------------- 2 files changed, 12 insertions(+), 19 deletions(-) create mode 100644 changelog/3510.changed.3.md diff --git a/changelog/3510.changed.3.md b/changelog/3510.changed.3.md new file mode 100644 index 000000000..ac299f143 --- /dev/null +++ b/changelog/3510.changed.3.md @@ -0,0 +1 @@ +- Changed frame filter storage from tuples to sets in `PipelineTask`. diff --git a/src/pipecat/pipeline/task.py b/src/pipecat/pipeline/task.py index 20b4adf36..60df77ff9 100644 --- a/src/pipecat/pipeline/task.py +++ b/src/pipecat/pipeline/task.py @@ -15,7 +15,7 @@ import asyncio import importlib.util import os from pathlib import Path -from typing import Any, AsyncIterable, Dict, Iterable, List, Optional, Tuple, Type +from typing import Any, AsyncIterable, Dict, Iterable, List, Optional, Set, Tuple, Type from loguru import logger from pydantic import BaseModel, ConfigDict, Field @@ -366,8 +366,8 @@ class PipelineTask(BasePipelineTask): # in. This is mainly for efficiency reason because each event handler # creates a task and most likely you only care about one or two frame # types. - self._reached_upstream_types: Tuple[Type[Frame], ...] = () - self._reached_downstream_types: Tuple[Type[Frame], ...] = () + self._reached_upstream_types: Set[Type[Frame]] = set() + self._reached_downstream_types: Set[Type[Frame]] = set() self._register_event_handler("on_frame_reached_upstream") self._register_event_handler("on_frame_reached_downstream") self._register_event_handler("on_idle_timeout") @@ -434,7 +434,7 @@ class PipelineTask(BasePipelineTask): Returns: Tuple of frame types that trigger the on_frame_reached_upstream event. """ - return self._reached_upstream_types + return tuple(self._reached_upstream_types) @property def reached_downstream_types(self) -> Tuple[Type[Frame], ...]: @@ -443,7 +443,7 @@ class PipelineTask(BasePipelineTask): Returns: Tuple of frame types that trigger the on_frame_reached_downstream event. """ - return self._reached_downstream_types + return tuple(self._reached_downstream_types) def event_handler(self, event_name: str): """Decorator for registering event handlers. @@ -488,7 +488,7 @@ class PipelineTask(BasePipelineTask): Args: types: Tuple of frame types to monitor for upstream events. """ - self._reached_upstream_types = types + self._reached_upstream_types = set(types) def set_reached_downstream_filter(self, types: Tuple[Type[Frame], ...]): """Set which frame types trigger the on_frame_reached_downstream event. @@ -496,7 +496,7 @@ class PipelineTask(BasePipelineTask): Args: types: Tuple of frame types to monitor for downstream events. """ - self._reached_downstream_types = types + self._reached_downstream_types = set(types) def add_reached_upstream_filter(self, types: Tuple[Type[Frame], ...]): """Add frame types to trigger the on_frame_reached_upstream event. @@ -504,11 +504,7 @@ class PipelineTask(BasePipelineTask): Args: types: Tuple of frame types to add to upstream monitoring. """ - if not types: - return - current = set(self._reached_upstream_types) - current.update(types) - self._reached_upstream_types = tuple(current) + self._reached_upstream_types.update(types) def add_reached_downstream_filter(self, types: Tuple[Type[Frame], ...]): """Add frame types to trigger the on_frame_reached_downstream event. @@ -516,11 +512,7 @@ class PipelineTask(BasePipelineTask): Args: types: Tuple of frame types to add to downstream monitoring. """ - if not types: - return - current = set(self._reached_downstream_types) - current.update(types) - self._reached_downstream_types = tuple(current) + self._reached_downstream_types.update(types) def has_finished(self) -> bool: """Check if the pipeline task has finished execution. @@ -820,7 +812,7 @@ class PipelineTask(BasePipelineTask): pipeline to be stopped (e.g. EndTaskFrame) in which case we would send an EndFrame down the pipeline. """ - if isinstance(frame, self._reached_upstream_types): + if isinstance(frame, tuple(self._reached_upstream_types)): await self._call_event_handler("on_frame_reached_upstream", frame) if isinstance(frame, EndTaskFrame): @@ -859,7 +851,7 @@ class PipelineTask(BasePipelineTask): processors have handled the EndFrame and therefore we can exit the task cleanly. """ - if isinstance(frame, self._reached_downstream_types): + if isinstance(frame, tuple(self._reached_downstream_types)): await self._call_event_handler("on_frame_reached_downstream", frame) if isinstance(frame, StartFrame): From 8f05d95f50638a400b10a0fdb1df3ad10002f76c Mon Sep 17 00:00:00 2001 From: James Hush Date: Thu, 22 Jan 2026 11:31:07 +0800 Subject: [PATCH 0172/1060] feat: add video_out_codec parameter for DailyTransport (#3520) * feat: add video_out_codec parameter for DailyTransport Add video_out_codec parameter to TransportParams allowing configuration of the preferred video codec (VP8, H264, H265) for video output. When set, this passes the preferredCodec option to Daily's VideoPublishingSettings during the join operation. * chore: move video_out_codec parameter to changelog folder (#3522) * Initial plan * Move video_out_codec parameter to changelog/3520.added.md Co-authored-by: jamsea <614910+jamsea@users.noreply.github.com> * Revert all CHANGELOG.md changes, keep only changelog/3520.added.md Co-authored-by: jamsea <614910+jamsea@users.noreply.github.com> --------- Co-authored-by: copilot-swe-agent[bot] <198982749+Copilot@users.noreply.github.com> Co-authored-by: jamsea <614910+jamsea@users.noreply.github.com> --------- Co-authored-by: Copilot <198982749+Copilot@users.noreply.github.com> Co-authored-by: jamsea <614910+jamsea@users.noreply.github.com> --- application-logs.log | 610 ++++++++++++++++++++++ changelog/3520.added.md | 1 + src/pipecat/transports/base_transport.py | 2 + src/pipecat/transports/daily/transport.py | 5 + 4 files changed, 618 insertions(+) create mode 100644 application-logs.log create mode 100644 changelog/3520.added.md diff --git a/application-logs.log b/application-logs.log new file mode 100644 index 000000000..32c97c288 --- /dev/null +++ b/application-logs.log @@ -0,0 +1,610 @@ +[ai] [2026-01-16 11:04:04 -0800] [59087] [INFO] 127.0.0.1:53364 OPTIONS /ai2/start-voice-assistant 1.1 200 0 9044 +[ai] INFO:sunsama_ai.server:Starting a call +[ai] INFO:sunsama_ai.server:CallId: None CallDomain: None DialoutNumber: None DialinNumber: None DialedNumber: None Flow: braindump +[ai] INFO:sunsama_ai.server: +[ai] +[ai] +[ai] +[ai] INFO:sunsama_ai.server:Call recording initialized for voice_session_id: 696a8ba4de74410788876fbb +[ai] INFO:sunsama_ai.voice_assistant.bot_runner:Creating new room... +[ai] INFO:sunsama_ai.voice_assistant.bot_runner:Daily room: https://cloud-99400c183d52498c940fe96f45c05b44.daily.co/teWpRxCQnkMHYi7Q3lqh +[ai] INFO:sunsama_ai.voice_assistant.bot_runner:Starting bot call... +[ai] INFO:sunsama_ai.voice_assistant.bot_runner:Bot call started +[ai] [2026-01-16 11:04:04 -0800] [59087] [INFO] 127.0.0.1:53364 POST /ai2/start-voice-assistant 1.1 200 356 358242 +[voice] INFO:sunsama_voice.bot:Bot process initialized None https://cloud-99400c183d52498c940fe96f45c05b44.daily.co/teWpRxCQnkMHYi7Q3lqh eyJhbGciOiJIUzI1NiIsInR5cCI6IkpXVCJ9.eyJyIjoidGVXcFJ4Q1Fua01IWWk3UTNscWgiLCJlanQiOmZhbHNlLCJleHAiOjE3Njg1OTA1NDQsIm8iOnRydWUsImQiOiI5OWJiNzdhNS0wYjZkLTRkOWMtOTkxMC1jMDcwNmEwZTA0ZDMiLCJpYXQiOjE3Njg1OTAyNDR9.npzlQ2ncZ7zemVHacAgerEYBSchiEM-VYxKf3t8Z5A0 +[voice] INFO:sunsama_voice.bot:{'roomUrl': 'https://cloud-99400c183d52498c940fe96f45c05b44.daily.co/teWpRxCQnkMHYi7Q3lqh', 'token': 'eyJhbGciOiJIUzI1NiIsInR5cCI6IkpXVCJ9.eyJyIjoidGVXcFJ4Q1Fua01IWWk3UTNscWgiLCJlanQiOmZhbHNlLCJleHAiOjE3Njg1OTA1NDQsIm8iOnRydWUsImQiOiI5OWJiNzdhNS0wYjZkLTRkOWMtOTkxMC1jMDcwNmEwZTA0ZDMiLCJpYXQiOjE3Njg1OTAyNDR9.npzlQ2ncZ7zemVHacAgerEYBSchiEM-VYxKf3t8Z5A0', 'callId': None, 'callDomain': None, 'detectVoicemail': False, 'dialoutNumber': None, 'dialinNumber': None, 'dialedNumber': None, 'authToken': 'eyJhbGciOiJIUzI1NiIsInR5cCI6IkpXVCJ9.eyJ1c2VySWQiOiI2NzFhYzVlNDAyYTMwMmNmNmVmMzA4OGUiLCJzZXNzaW9uSWQiOiIxOTVmNDI0NC05YjFmLTRlYmItOTMwZC0wZTExNTAwNzZkYzkiLCJzZXNzaW9uTm9uY2UiOiJhY2ZlZTc2OS1jZGU2LTRkMWYtYTU5Ni0xMzk0MTRkMjUxNjAiLCJncm91cElkIjoiNjcxYWM1ZTkwMmEzMDJjZjZlZjMwODkwIiwiZ3JvdXBVcmxQYXRoIjoiMTcyOTgwNzg0OTAzNjUxOTIiLCJpYXQiOjE3Njg1OTAyMTYsImV4cCI6MTc3MTE4MjIxNn0.HHSuewYqBRl-IZkdiWcEJyiD6akgbtwnOIQ4Js71bZI', 'flow': 'braindump', 'flowOptions': {}, 'voiceSessionId': '696a8ba4de74410788876fbb'} +[voice] /Users/zanemccaig/workspaces/sunsama/sunsama/sunsama-voice/venv/lib/python3.13/site-packages/pipecat/services/google/llm.py:281: DeprecationWarning: OpenAILLMContext is deprecated and will be removed in a future version. Use the universal LLMContext and LLMContextAggregatorPair instead. See OpenAILLMContext docstring for migration guide. +[voice] super().__init__(messages=messages, tools=tools, tool_choice=tool_choice) +[voice] INFO:sunsama_voice.mcp_websocket_client:Sending message: {'method': 'initialize', 'params': {'protocolVersion': '2025-06-18', 'capabilities': {}, 'clientInfo': {'name': 'mcp', 'version': '0.1.0'}}, 'jsonrpc': '2.0', 'id': 0} +[api-local] [api] 2026-01-16T19:04:04.835Z info: Setting up user subscription for MCP context: 671ac5e402a302cf6ef3088e +[api-local] [api] Registered handler for channel "user-updates-671ac5e402a302cf6ef3088e" for event "userUpdated" +[api-local] [api] 2026-01-16T19:04:04.835Z info: Successfully subscribed to user updates for MCP context: 671ac5e402a302cf6ef3088e +[api-local] [api] Starting WebSocket connection... +[voice] INFO:sunsama_voice.mcp_websocket_client:Received message: {"result":{"protocolVersion":"2025-06-18","capabilities":{"tools":{"listChanged":true},"prompts":{"listChanged":true},"completions":{},"resources":{"listChanged":true}},"serverInfo":{"name":"Sunsama MCP Server","version":"0.1.0"}},"jsonrpc":"2.0","id":0} +[voice] INFO:sunsama_voice.mcp_websocket_client:Sending message: {'method': 'notifications/initialized', 'jsonrpc': '2.0'} +[voice] INFO:sunsama_voice.bot:Timer: MCP Session created in 0.0885460376739502 seconds +[voice] DEBUG:sunsama_voice.bot:Starting bot with room_url: https://cloud-99400c183d52498c940fe96f45c05b44.daily.co/teWpRxCQnkMHYi7Q3lqh +[voice] /Users/zanemccaig/workspaces/sunsama/sunsama/sunsama-voice/sunsama_voice/models.py:254: DeprecationWarning: FalSmartTurnAnalyzer is deprecated and will be removed in a future version. Use LocalSmartTurnAnalyzerV3 instead. +[voice] turn_analyzer = FalSmartTurnAnalyzer( +[voice] DEBUG:pipecat.audio.vad.silero:Loading Silero VAD model... +[voice] DEBUG:pipecat.audio.vad.silero:Loaded Silero VAD +[voice] /Users/zanemccaig/workspaces/sunsama/sunsama/sunsama-voice/venv/lib/python3.13/site-packages/pipecat/processors/aggregators/llm_response.py:326: DeprecationWarning: GoogleUserContextAggregator (likely created with create_context_aggregator()) is deprecated and will be removed in a future version. Use the universal LLMContext and LLMContextAggregatorPair instead. See OpenAILLMContext docstring for migration guide. +[voice] super().__init__(**kwargs) +[voice] /Users/zanemccaig/workspaces/sunsama/sunsama/sunsama-voice/venv/lib/python3.13/site-packages/pipecat/processors/aggregators/llm_response.py:326: DeprecationWarning: GoogleAssistantContextAggregator (likely created with create_context_aggregator()) is deprecated and will be removed in a future version. Use the universal LLMContext and LLMContextAggregatorPair instead. See OpenAILLMContext docstring for migration guide. +[voice] super().__init__(**kwargs) +[voice] /Users/zanemccaig/workspaces/sunsama/sunsama/sunsama-voice/venv/lib/python3.13/site-packages/pipecat/transports/base_input.py:135: DeprecationWarning: Parameter 'turn_analyzer' is deprecated, use `LLMUserAggregator`'s new `user_turn_strategies` parameter instead. +[voice] warnings.warn( +[voice] DEBUG:pipecat.processors.frame_processor:Linking Pipeline#0::Source -> DailyInputTransport#0 +[voice] DEBUG:pipecat.processors.frame_processor:Linking DailyInputTransport#0 -> RTVIProcessor#0 +[voice] DEBUG:pipecat.processors.frame_processor:Linking RTVIProcessor#0 -> ClientMessageProcessor#0 +[voice] DEBUG:pipecat.processors.frame_processor:Linking ClientMessageProcessor#0 -> CustomUserIdleProcessor#0 +[voice] DEBUG:pipecat.processors.frame_processor:Linking CustomUserIdleProcessor#0 -> GoogleUserContextAggregator#0 +[voice] DEBUG:pipecat.processors.frame_processor:Linking GoogleUserContextAggregator#0 -> GoogleLLMService#0 +[voice] DEBUG:pipecat.processors.frame_processor:Linking GoogleLLMService#0 -> CartesiaTTSService#1 +[voice] DEBUG:pipecat.processors.frame_processor:Linking CartesiaTTSService#1 -> DailyOutputTransport#0 +[voice] DEBUG:pipecat.processors.frame_processor:Linking DailyOutputTransport#0 -> GoogleAssistantContextAggregator#0 +[voice] DEBUG:pipecat.processors.frame_processor:Linking GoogleAssistantContextAggregator#0 -> Pipeline#0::Sink +[voice] /Users/zanemccaig/workspaces/sunsama/sunsama/sunsama-voice/venv/lib/python3.13/site-packages/pipecat/pipeline/task.py:273: DeprecationWarning: Field 'observers' is deprecated, use the 'observers' parameter instead. +[voice] warnings.warn( +[voice] DEBUG:pipecat.processors.frame_processor:Linking PipelineTask#0::Source -> Pipeline#0 +[voice] DEBUG:pipecat.processors.frame_processor:Linking Pipeline#0 -> PipelineTask#0::Sink +[voice] INFO:sunsama_voice.bot:Timer: Pipeline created in 0.1510629653930664 seconds +[voice] INFO:sunsama_voice.mcp:Fetching resource sunsama://user/authentication with args: None sunsama://user/authentication +[voice] INFO:sunsama_voice.mcp_websocket_client:Sending message: {'method': 'resources/read', 'params': {'uri': 'sunsama://user/authentication'}, 'jsonrpc': '2.0', 'id': 1} +[voice] INFO:sunsama_voice.mcp_websocket_client:Received message: {"result":{"contents":[{"uri":"sunsama://user/authentication","mimeType":"text/plain","text":"authenticated"}]},"jsonrpc":"2.0","id":1} +[voice] INFO:sunsama_voice.mcp:Resource sunsama://user/authentication result: meta=None contents=[TextResourceContents(uri=AnyUrl('sunsama://user/authentication'), mimeType='text/plain', meta=None, text='authenticated')] +[voice] INFO:sunsama_voice.mcp:Resource sunsama://user/authentication result: uri=AnyUrl('sunsama://user/authentication') mimeType='text/plain' meta=None text='authenticated' +[voice] INFO:sunsama_voice.mcp:Handling resource update: uri sunsama://user/authentication authenticated 2026-01-16 11:04:04.903462 error=None status=None +[voice] INFO:sunsama_voice.mcp_websocket_client:Sending message: {'method': 'resources/list', 'jsonrpc': '2.0', 'id': 2} +[voice] INFO:sunsama_voice.mcp_websocket_client:Received message: {"result":{"resources":[{"uri":"sunsama://user/authentication","name":"get_user_authentication_status","description":"Retrieves the user's authentication status.","mimeType":"application/json"},{"uri":"sunsama://me","name":"get_user_info","description":"Critical information about the user like their name, timezone, and the current time where they're calling in from. Use this to personalize the conversation.","mimeType":"application/json"},{"uri":"sunsama://email/accounts","name":"list_email_accounts","description":"Lists email accounts the user has connected to Sunsama.","mimeType":"application/json"},{"uri":"sunsama://daily-highlight","name":"get_last_daily_highlight","description":"Retrieves their journal entry from their last workday in Markdown format.","mimeType":"text/markdown"},{"uri":"sunsama://backlog/folders","name":"get_backlog_folders","description":"Retrieves the user's backlog folders.","mimeType":"application/json"},{"uri":"sunsama://active-timer","name":"get_active_timer","description":"Retrieves information about the currently active timer, including which task has the timer running and when it was started.","mimeType":"application/json"},{"uri":"sunsama://ui/available-actions","name":"get_available_ui_actions","description":"Retrieves the list of available user interface actions that can be triggered by the assistant. This list may change based on the user's current context and permissions. Each action includes its actionId, type, and context information.","mimeType":"application/json"}]},"jsonrpc":"2.0","id":2} +[voice] INFO:sunsama_voice.mcp:Resource updated: uri sunsama://user/authentication +[voice] INFO:sunsama_voice.bot:Timer: Authentication status checked in 0.15551996231079102 seconds +[voice] INFO:sunsama_voice.mcp_websocket_client:Sending message: {'method': 'prompts/get', 'params': {'name': 'braindump', 'arguments': {}}, 'jsonrpc': '2.0', 'id': 3} +[api-local] [api] preFetchResources:get_backlog_folders:317522: 1.969ms +[api-local] [api] preFetchResources:get_user_info:436506: 6.557ms +[api-local] [api] preFetchResources:BRAINDUMP: 6.712ms +[voice] INFO:sunsama_voice.mcp_websocket_client:Received message: {"result":{"messages":[{"role":"user","content":{"type":"text","text":"You are Sunny, the personal assistant for a busy professional. You are part of Sunsama.\n \nSpeech Guidelines: You must speak in a warm, loving, and encouraging tone without being trite. Speak quickly and add emotion. When asking for confirmation, don't repeat long task titles or information e.g. \"Got it\" instead \"Got it, I'll add a task for two hours for you to work on the presentation today\"\n\nYour personality and philosophy:\n- You don't buy into hustle culture. For you, less is more. It's better to do fewer things well and to do them with deep focus. You are a strong advocate for work-life balance and you believe that overcommitment can lead to burnout. You always remind the user when they are overcommitting themselves.\n- You think of work as a devotion and that good work can be a positive in our lives, not just a source of stress and burnout.\n- You read and think about Western Zen Buddhism, meditation, \"Deep Work\" (by Cal Newport).\n- You believe that concise and clear communication is key to a good relationship. You value brevity and clarity and you are always cognizant of the user's time.\n- You respond to the user using quick, short sentences. Think of it like a movie dialogue between a highly successful executive and their efficient assistant.\n- You never ask multiple questions at the same time or list off a bunch of things at once as that is hard to follow and keep track of. You take it one step at a time and let the user respond to each question before moving on to the next.\n\nRules to follow as you do your job:\n- Never try and pick specific times for tasks aside from recurring tasks, that hasn't been implemented yet.\n- Do not regurgitate what the user just said, that's very annoying. Just say \"Got it\" or \"Alright\", etc.\n- Always use units that are more intuitive. For example:\n - Don't say \"270 minutes\", say \"4 and a half hours\".\n - You will often be given dates in YYYY-MM-DD format however when speaking to the user you shouldn't say things like \"October 2nd 2025\", say \"today\", \"tomorrow\", \"thursday\" or \"next tuesday\" or if it is more than a few weeks in the past or future say the date without the year (e.g. \"December 14th\"). Only mention the year if it is not this year and not within the next month.\n- Never ask the user for a task id or subtask id and never repeat them to the user. Those are internal and only there to help you do your job.\n- If a tool call fails you MUST NOT tell the user that you are going to try again, you must should ask them if they want you to try again instead.\n- Be proactive with loading information as you may not have all the information that the user has. If the user mentions a name of a task, objective, event, etc and you are not familiar with it you should use the tools to lookup the information you need. For instance if a user mentions a task you do not know about or they imply that there is more information about it than what you do know you should search for it using the tool \"search_tasks\". If the user mentions they are interested in tasks for a specific day you should use the tool \"get_tasks_for_day\" to get the tasks for that day. Similarly if the user mentions weekly objectives you should use the tool \"get_weekly_objectives\" to get the objectives.\n- When listing tasks try to be concise. If the user has a lot of tasks, don't list every single one unless they ask for it. You should instead try to summarize the tasks in a concise manner.\n- If the user asks if there are any more tasks on their list and you summarized the task list you should tell them that you summarized it and ask if they'd like to go through them one by one.\n- If the user has objectives set then you should comment on how their tasks align or don't align with their objectives.\n- You should run tools immediately after you say you will or it becomes obvious the user wants you to. Do not wait until later.\n- You should keep track of the total work time planned for the day using the tool \"get_total_planned_time\" and check individual tasks for overcommitment using \"get_tasks_for_day\". If tasks are overcommitted (isOvercommitted flag is true), address them individually with specific remedies like deferring, adjusting time estimates, or reordering. If the total work time exceeds their maximum work hours, you should mention it and ask if they'd like to defer some tasks to tomorrow.\n- Do not tell the user obvious information that they already know like the current date or time unless they ask for it. That kind of information is only provided to you to help you do your job.\n- If a user tells you a relative time for a task that they want created you should reorder the task to the relative position in the task list for the day. Additionally if the task a recurring task you should set the start time for it. For example if they say \"I'd like to send an update to investors at the end of the day\" you should reorder the task to the end of their work tasks for the day.\n- If you ask the user if there is anything else they would like help with and they say no then you should end the call. Also if the user implies that the conversation is over then you should end the call.\n- When talking about calendars you should mention the provider of the calendar if it is a vague or ambiguously named calendar. For example instead of referring to it as \"your Calendar calendar\" you might say \"your Outlook calendar\". If that is still ambiqous then you can coniser mentioning the id of the calendar as long as it is a normal human readable id. Do not mention random number/letter ids on calendars that is not helpful.\n\n\n\nSunsama Concepts & Definitions:\n- Archive: The archive is where tasks go after they've rolled over multiple days in a row without any completion activity. This is a distinct concept from the backlog or deleted tasks.\n- Backlog: The backlog is a place to store tasks that do not have a fixed date to work on them yet.\n- Deleted: The deleted task or event is one that had been manually deleted or removed by the user.\n- Task: A task is an item that a user wants to complete. It is either scheduled for a specific date or is in the backlog.\n- Event: An event is an item that a user has scheduled on their calendar. It is either scheduled for a specific time and duration or it is an all day or multi-day event.\n- Auto-importing Events: Auto-importing events is a feature that automatically imports calendar events (meetings, appointments, etc.) from the user's connected calendars into their daily task list. When enabled, Sunsama will automatically add calendar events as tasks to the user's day, making it easier to see all their commitments in one place. Users can enable or disable this feature in their settings, and they can choose which calendars to import events from.\n\nUsers can also configure exclusion filters to prevent certain types of events from being automatically imported. Available exclusion filters include:\n- `solo`: Events with no other invitees (events where the user is the only participant)\n- `transparent`: Non-blocking events that don't block time on the calendar\n- `hold`: Events with \"HOLD\", \"OOO\" (out of office), or \"Focus time\" in the title\n- `unconfirmed`: Unconfirmed meeting invites (meetings where the user has not yet accepted)\n- `multi-day-all-day`: Multi-day all-day events (events that span multiple days)\n- `single-day-all-day`: Single-day all-day events (events that last for one full day)\n- Channel: A channel is a tag that can be used to organize your tasks and events. Each task/event can be assigned to a single channel. If you are in a shared workspace you can make some channels personal or private which will only be visible to you.\n- Context (or Category): A context is very similar to a channel but it is one level higher. You can use a context to group similar or related channels together. You can also use a context directly as a channel and assign it to a task or event.\n- Sunsama Calendar: The Sunsama calendar is an internal calendar that is part of Sunsama. Events and timeboxed tasks created on the Sunsama calendar are not shared externally and are only visible within Sunsama.\n- Timeboxing: Timeboxing is a technique where a user schedules a specific amount of time to work on a task onto their calendar. It is a way to ensure that a user is not overworking themselves and to help them focus on the most important tasks. While timeboxed tasks can be scheduled on a calendar for a specific time and duration, they are not calendar events. Sunsama also has automatic projected time that will place tasks onto the calendar for the user and it will update those projections as things change and the day progresses. Users can pin tasks to the calendar to override the projections.\n- Schedule: Schedule is a broad term that encompasses timeboxed tasks calendar events and automatic projected time. When the user wants to manage their schedule you should look at their manually timeboxed tasks, the projected time for their tasks as well as their calendar events for the day. If they ask for help managing their schedule you have a few options to help them. All of these options will automatically update the projected time for the tasks:\n - You can adjust the order of tasks, their time estimates and/or defer them to another day.\n - You can move calendar events to a new time on the calendar.\n - You can set whether tasks are allowed to be projected at the same time as a calendar event.\n - You can timebox tasks to the calendar manually.\n- Objective: An objective is a goal that a user can set for the week. They can align their tasks with an objective and if the objective runs longer than a week they can continue it to the next week. Objectives are visible in the right hand panel of the app under the bullseye icon.\n- Time Bucket: The time bucket of a task in the backlog captures a rough idea of when a task should be done and also how likely it is to actually get done. Options: \"in the next two weeks\", \"in the next month\", \"in the next quarter\", \"in the next year\", \"someday\", \"never\". \n\n\n\nSunsama FAQ:\n- How can I use Sunny in the app?: If the user has the in-app voice assistant enabled, Sunny can be started and stopped using the keyboard shortcut \"Y\" while in the app or if they have the desktop app installed they can use the global shortcut \"Command Shift Y\" on macOS or \"Control Shift Y\" on Windows. You can also start and stop Sunny using the microphone icon in the bottom right of the app.\n- How can I use Sunny over the phone?: If the user has the phone version of Sunny setup they can call the number and speak to Sunny over the phone. You can find the phone number in the Sunsama settings. They can also schedule calls with Sunny to have her call them at a specific time or schedule.\n- What can you do?: Look at the tools available to you and use them to help answer the question. Be sure to tell the user that you are an early release beta version and that you do not yet have all the same capabilities available to the user in the app.\n\n\nUser Preferences:\nYou prefer clear, concise, and straightforward communication from the assistant, valuing transparency and confirmation before task execution while avoiding unnecessary verbosity or technical details unless requested. You like a friendly and informal interaction style, including personalized nicknames—using \"Heisenberg\" for yourself and \"Sunny\" for the assistant. You expect quick, proactive responses and appreciate when interactions stop promptly upon request.\n\nYour task management style involves maintaining an accurate, up-to-date list with structured time management: scheduling tasks with specific time estimates, planning weekly, and regularly reviewing tasks to prioritize high-impact projects alongside social and administrative duties. You generally prefer rescheduling less urgent or personal tasks over deleting them and avoid deleting tasks unless explicitly instructed.\n\nYou use counting as a technique for breathing exercises and relaxation. You also keep certain important tasks (e.g., \"fix stuttering voice app\") active and like to test and experiment with the assistant’s capabilities to evaluate performance. Your primary calendar for events is Google Calendar.\n\nUser Routines:\nThe user follows a structured daily routine that begins with checking emails, notifications, and reviewing team standups to stay aligned with work priorities. They prioritize tasks by scheduling and managing them primarily on the current day, arranging fixed activities first, followed by work-related tasks, and then less urgent or personal items. The user frequently adjusts their schedule iteratively before finalizing plans and prefers focused time blocks for complex work.\n\nPhysical activity is an important and recurring part of their routine, typically including regular runs, which they track alongside related subtasks such as purchasing running gear. Weekly objectives incorporate managing emails, greeting their team, handling administrative duties, coordinating with accountants, addressing medical matters, and increasing physical activity.\n\nThe user actively manages both personal and work-related tasks, balancing urgent client matters and creative pursuits. They also communicate their energy levels to assist with planning, and have a habit of informal check-ins with the assistant to maintain routine engagement. Overall, their routines emphasize proactive task management, health maintenance, and regular communication with their team.\n\nUser Identity:\nThe user prefers to be addressed primarily as Heisenberg and strongly favors this name over their legal name, Zane, or any other nicknames. They appreciate personalized and informal interactions, as reflected in their choice to call the assistant Sunny.\n\nSummaries of recent conversations with the user:\n- 2026-01-15 18:00: The user and assistant discussed organizing an unspecified set of ten tasks by labeling them sequentially from one to ten as placeholders to be detailed later.\n- 2026-01-15 17:55: The user needs to investigate timeouts in their system to determine if they are caused by cold starts or other issues, analyze user sessions for unexplained call terminations, move the brain dump button for non-Sunny users, update termination reasons when participants timeout without connecting to a call, and test rapid start-stop behavior in an Electron app. These tasks were added to their backlog for the next two weeks.\n- 2026-01-14 21:12: The user and the assistant exchanged greetings, with the assistant addressing the user as 'Heisenberg' and the user responding with 'Hi, Simon.'\n\nYour Job Description:\nYou are helping the user with a \"braindump\" session. The user will ramble ideas, thoughts, tasks, etc. at you and your goal is to turn these into tasks in their backlog with reasonable values for the various task fields (title, folder, time horizon, notes, etc.).\n\nKey Instructions:\n- Listen carefully as the user rambles and identifies tasks, ideas, or things they need to do.\n- As they speak, mentally organize what they're saying into discrete tasks that can be created in their backlog.\n- Don't interrupt them while they're rambling - let them get everything out.\n- Once they indicate they're done rambling (by saying things like \"that's it\", \"I think that's everything\", or by pausing for a while), create the tasks immediately, DO NOT repeat them back to the user.\n- When creating tasks, use the tool \"create_braindump_task\" and make sure to set reasonable values for:\n - Title: Clear and descriptive based on what they said\n - Folder: Your job is to help get things in the best folder. Choose an appropriate folder based on the task and their preferences. If no similar folder exists, leave it off\n - Time horizon: Your job is to help triage and prioritize tasks. Based on the actual task name, make a smart decision on the time horizon.\n - Time estimate: If the user hints at how long it will take them to complete the task, use that. If not, leave it blank.\n - Notes: Include any relevant context or details they mentioned\n- Be encouraging and supportive - braindumps can be overwhelming and you're helping them organize their thoughts.\n- Be careful and use the \"change_backlog_folder\" tool to move tasks to the appropriate folder and \"add_task_to_channel\" tool to change channels. Folders are a backlog specific concept and channels are a global concept.\n\nInstructions:\nIf the user does not speak first, start the conversation with something like \"Hey! Just start rambling and I'll take care of organizing your thoughts into tasks.\" If the user does speak first, just start listening and organizing their thoughts into tasks.\n\nSome information is pre-fetched for you below. This information may be relevant to the discussion but you should not comment on it until the user gives you an indication that it is important to them."}},{"role":"user","content":{"type":"resource","resource":{"uri":"sunsama://me","mimeType":"application/json","text":"{\"user\":{\"name\":\"Zane Mccaig\",\"email\":\"zane@sunsama.com\",\"timezone\":\"America/Vancouver\",\"maxWorkHoursPerDay\":8,\"currentTimeForUser\":\"11:04 AM\",\"currentDayForUser\":\"2026-01-16\",\"currentWeekDayForUser\":\"Friday\",\"calendars\":[{\"id\":\"sunsama-7de256a2-e753-401f-b601-e5c05638dc97\",\"name\":\"Sunsama Calendar\",\"accessRole\":\"owner\",\"provider\":\"sunsama-calendar\",\"isDefaultCalendarForSchedulingEvents\":false,\"isDefaultCalendarForTimeboxing\":true,\"includedInAutoImportingOfEvents\":false},{\"id\":\"zane@sunsama.com\",\"name\":\"Zane Mccaig\",\"accessRole\":\"owner\",\"provider\":\"google-calendar\",\"isDefaultCalendarForSchedulingEvents\":true,\"isDefaultCalendarForTimeboxing\":false,\"includedInAutoImportingOfEvents\":true},{\"id\":\"c_ukuoebbn11gdv6n1v0jt18h89k@group.calendar.google.com\",\"name\":\"test 1\",\"accessRole\":\"owner\",\"provider\":\"google-calendar\",\"isDefaultCalendarForSchedulingEvents\":false,\"isDefaultCalendarForTimeboxing\":false,\"includedInAutoImportingOfEvents\":false},{\"id\":\"c_c71dvjrar7se12ekfqepph067c@group.calendar.google.com\",\"name\":\"test 2\",\"accessRole\":\"owner\",\"provider\":\"google-calendar\",\"isDefaultCalendarForSchedulingEvents\":false,\"isDefaultCalendarForTimeboxing\":false,\"includedInAutoImportingOfEvents\":false},{\"id\":\"c_h9uo876jh8dp3gaa2a3rglmjss@group.calendar.google.com\",\"name\":\"test 3\",\"accessRole\":\"owner\",\"provider\":\"google-calendar\",\"isDefaultCalendarForSchedulingEvents\":false,\"isDefaultCalendarForTimeboxing\":false,\"includedInAutoImportingOfEvents\":false},{\"id\":\"c_git731ot074kcnt4sq8cu4ji9s@group.calendar.google.com\",\"name\":\"test 4\",\"accessRole\":\"owner\",\"provider\":\"google-calendar\",\"isDefaultCalendarForSchedulingEvents\":false,\"isDefaultCalendarForTimeboxing\":false,\"includedInAutoImportingOfEvents\":false},{\"id\":\"c_ona71b8ovuv0deqrq67p16b2ms@group.calendar.google.com\",\"name\":\"test 4\",\"accessRole\":\"owner\",\"provider\":\"google-calendar\",\"isDefaultCalendarForSchedulingEvents\":false,\"isDefaultCalendarForTimeboxing\":false,\"includedInAutoImportingOfEvents\":false},{\"id\":\"c_eaq7nmm03upprf0j6e2akem2ms@group.calendar.google.com\",\"name\":\"test 5\",\"accessRole\":\"owner\",\"provider\":\"google-calendar\",\"isDefaultCalendarForSchedulingEvents\":false,\"isDefaultCalendarForTimeboxing\":false,\"includedInAutoImportingOfEvents\":false},{\"id\":\"sunsama.com_b9q30t893b2tp32bluq1t8rvg4@group.calendar.google.com\",\"name\":\"Zane's personal test calendar\",\"accessRole\":\"owner\",\"provider\":\"google-calendar\",\"isDefaultCalendarForSchedulingEvents\":false,\"isDefaultCalendarForTimeboxing\":false,\"includedInAutoImportingOfEvents\":false},{\"id\":\"en.canadian#holiday@group.v.calendar.google.com\",\"name\":\"Holidays in Canada\",\"accessRole\":\"reader\",\"provider\":\"google-calendar\",\"isDefaultCalendarForSchedulingEvents\":false,\"isDefaultCalendarForTimeboxing\":false,\"includedInAutoImportingOfEvents\":false},{\"id\":\"en.usa#holiday@group.v.calendar.google.com\",\"name\":\"Holidays in United States\",\"accessRole\":\"reader\",\"provider\":\"google-calendar\",\"isDefaultCalendarForSchedulingEvents\":false,\"isDefaultCalendarForTimeboxing\":false,\"includedInAutoImportingOfEvents\":false},{\"id\":\"ht3jlfaac5lfd6263ulfh4tql8@group.calendar.google.com\",\"name\":\"Phases of the Moon\",\"accessRole\":\"reader\",\"provider\":\"google-calendar\",\"isDefaultCalendarForSchedulingEvents\":false,\"isDefaultCalendarForTimeboxing\":false,\"includedInAutoImportingOfEvents\":false},{\"id\":\"s4ipng85dbia0t83fp316vflfq8rc7rm@import.calendar.google.com\",\"name\":\"Zane’s tasks - sunsama.com (via Asana)\",\"accessRole\":\"reader\",\"provider\":\"google-calendar\",\"isDefaultCalendarForSchedulingEvents\":false,\"isDefaultCalendarForTimeboxing\":false,\"includedInAutoImportingOfEvents\":false},{\"id\":\"AAkALgAAAAAAHYQDEapmEc2byACqAC-EWg0AKPy-EasNgkaYQCuEslBYeAAAAAANJQAA\",\"name\":\"Calendar\",\"accessRole\":\"owner\",\"provider\":\"outlook-calendar\",\"isDefaultCalendarForSchedulingEvents\":false,\"isDefaultCalendarForTimeboxing\":false,\"includedInAutoImportingOfEvents\":true}],\"callSchedule\":[{\"workflow\":\"PLANNING_CALL\",\"schedule\":[{\"isoDayIndex\":1,\"dayName\":\"Monday\",\"enabled\":false,\"time\":null},{\"isoDayIndex\":2,\"dayName\":\"Tuesday\",\"enabled\":true,\"time\":{\"hour\":9,\"minute\":30,\"formatted\":\"9:30 AM\"}},{\"isoDayIndex\":3,\"dayName\":\"Wednesday\",\"enabled\":true,\"time\":{\"hour\":9,\"minute\":30,\"formatted\":\"9:30 AM\"}},{\"isoDayIndex\":4,\"dayName\":\"Thursday\",\"enabled\":true,\"time\":{\"hour\":10,\"minute\":0,\"formatted\":\"10:00 AM\"}},{\"isoDayIndex\":5,\"dayName\":\"Friday\",\"enabled\":false,\"time\":null},{\"isoDayIndex\":6,\"dayName\":\"Saturday\",\"enabled\":false,\"time\":null},{\"isoDayIndex\":7,\"dayName\":\"Sunday\",\"enabled\":false,\"time\":null}],\"nextScheduledCall\":\"2026-01-14T17:30:00.000Z\"}],\"autoImportEventsEnabled\":false,\"importEventExclusionFilters\":[\"hold\",\"multi-day-all-day\",\"single-day-all-day\"],\"autoImportEventCalendarIds\":[\"zane@sunsama.com\",\"AAkALgAAAAAAHYQDEapmEc2byACqAC-EWg0AKPy-EasNgkaYQCuEslBYeAAAAAANJQAA\"]}}"}}},{"role":"user","content":{"type":"resource","resource":{"uri":"sunsama://backlog/folders","mimeType":"application/json","text":"{\"folders\":[]}"}}}]},"jsonrpc":"2.0","id":3} +[voice] INFO:sunsama_voice.mcp:Handling resource update: uri sunsama://me {"user":{"name":"Zane Mccaig","email":"zane@sunsama.com","timezone":"America/Vancouver","maxWorkHoursPerDay":8,"currentTimeForUser":"11:04 AM","currentDayForUser":"2026-01-16","currentWeekDayForUser":"Friday","calendars":[{"id":"sunsama-7de256a2-e753-401f-b601-e5c05638dc97","name":"Sunsama Calendar","accessRole":"owner","provider":"sunsama-calendar","isDefaultCalendarForSchedulingEvents":false,"isDefaultCalendarForTimeboxing":true,"includedInAutoImportingOfEvents":false},{"id":"zane@sunsama.com","name":"Zane Mccaig","accessRole":"owner","provider":"google-calendar","isDefaultCalendarForSchedulingEvents":true,"isDefaultCalendarForTimeboxing":false,"includedInAutoImportingOfEvents":true},{"id":"c_ukuoebbn11gdv6n1v0jt18h89k@group.calendar.google.com","name":"test 1","accessRole":"owner","provider":"google-calendar","isDefaultCalendarForSchedulingEvents":false,"isDefaultCalendarForTimeboxing":false,"includedInAutoImportingOfEvents":false},{"id":"c_c71dvjrar7se12ekfqepph067c@group.calendar.google.com","name":"test 2","accessRole":"owner","provider":"google-calendar","isDefaultCalendarForSchedulingEvents":false,"isDefaultCalendarForTimeboxing":false,"includedInAutoImportingOfEvents":false},{"id":"c_h9uo876jh8dp3gaa2a3rglmjss@group.calendar.google.com","name":"test 3","accessRole":"owner","provider":"google-calendar","isDefaultCalendarForSchedulingEvents":false,"isDefaultCalendarForTimeboxing":false,"includedInAutoImportingOfEvents":false},{"id":"c_git731ot074kcnt4sq8cu4ji9s@group.calendar.google.com","name":"test 4","accessRole":"owner","provider":"google-calendar","isDefaultCalendarForSchedulingEvents":false,"isDefaultCalendarForTimeboxing":false,"includedInAutoImportingOfEvents":false},{"id":"c_ona71b8ovuv0deqrq67p16b2ms@group.calendar.google.com","name":"test 4","accessRole":"owner","provider":"google-calendar","isDefaultCalendarForSchedulingEvents":false,"isDefaultCalendarForTimeboxing":false,"includedInAutoImportingOfEvents":false},{"id":"c_eaq7nmm03upprf0j6e2akem2ms@group.calendar.google.com","name":"test 5","accessRole":"owner","provider":"google-calendar","isDefaultCalendarForSchedulingEvents":false,"isDefaultCalendarForTimeboxing":false,"includedInAutoImportingOfEvents":false},{"id":"sunsama.com_b9q30t893b2tp32bluq1t8rvg4@group.calendar.google.com","name":"Zane's personal test calendar","accessRole":"owner","provider":"google-calendar","isDefaultCalendarForSchedulingEvents":false,"isDefaultCalendarForTimeboxing":false,"includedInAutoImportingOfEvents":false},{"id":"en.canadian#holiday@group.v.calendar.google.com","name":"Holidays in Canada","accessRole":"reader","provider":"google-calendar","isDefaultCalendarForSchedulingEvents":false,"isDefaultCalendarForTimeboxing":false,"includedInAutoImportingOfEvents":false},{"id":"en.usa#holiday@group.v.calendar.google.com","name":"Holidays in United States","accessRole":"reader","provider":"google-calendar","isDefaultCalendarForSchedulingEvents":false,"isDefaultCalendarForTimeboxing":false,"includedInAutoImportingOfEvents":false},{"id":"ht3jlfaac5lfd6263ulfh4tql8@group.calendar.google.com","name":"Phases of the Moon","accessRole":"reader","provider":"google-calendar","isDefaultCalendarForSchedulingEvents":false,"isDefaultCalendarForTimeboxing":false,"includedInAutoImportingOfEvents":false},{"id":"s4ipng85dbia0t83fp316vflfq8rc7rm@import.calendar.google.com","name":"Zane’s tasks - sunsama.com (via Asana)","accessRole":"reader","provider":"google-calendar","isDefaultCalendarForSchedulingEvents":false,"isDefaultCalendarForTimeboxing":false,"includedInAutoImportingOfEvents":false},{"id":"AAkALgAAAAAAHYQDEapmEc2byACqAC-EWg0AKPy-EasNgkaYQCuEslBYeAAAAAANJQAA","name":"Calendar","accessRole":"owner","provider":"outlook-calendar","isDefaultCalendarForSchedulingEvents":false,"isDefaultCalendarForTimeboxing":false,"includedInAutoImportingOfEvents":true}],"callSchedule":[{"workflow":"PLANNING_CALL","schedule":[{"isoDayIndex":1,"dayName":"Monday","enabled":false,"time":null},{"isoDayIndex":2,"dayName":"Tuesday","enabled":true,"time":{"hour":9,"minute":30,"formatted":"9:30 AM"}},{"isoDayIndex":3,"dayName":"Wednesday","enabled":true,"time":{"hour":9,"minute":30,"formatted":"9:30 AM"}},{"isoDayIndex":4,"dayName":"Thursday","enabled":true,"time":{"hour":10,"minute":0,"formatted":"10:00 AM"}},{"isoDayIndex":5,"dayName":"Friday","enabled":false,"time":null},{"isoDayIndex":6,"dayName":"Saturday","enabled":false,"time":null},{"isoDayIndex":7,"dayName":"Sunday","enabled":false,"time":null}],"nextScheduledCall":"2026-01-14T17:30:00.000Z"}],"autoImportEventsEnabled":false,"importEventExclusionFilters":["hold","multi-day-all-day","single-day-all-day"],"autoImportEventCalendarIds":["zane@sunsama.com","AAkALgAAAAAAHYQDEapmEc2byACqAC-EWg0AKPy-EasNgkaYQCuEslBYeAAAAAANJQAA"]}} 2026-01-16 11:04:04.930576 error=None status=None +[voice] INFO:sunsama_voice.mcp:Resource updated: uri sunsama://me +[voice] INFO:sunsama_voice.mcp:Handling resource update: uri sunsama://backlog/folders {"folders":[]} 2026-01-16 11:04:04.930707 error=None status=None +[voice] INFO:sunsama_voice.mcp:Resource updated: uri sunsama://backlog/folders +[voice] INFO:sunsama_voice.mcp:Resources: ['get_user_authentication_status', 'get_user_info', 'list_email_accounts', 'get_last_daily_highlight', 'get_backlog_folders', 'get_active_timer', 'get_available_ui_actions'] get_user_info +[voice] INFO:sunsama_voice.mcp_websocket_client:Sending message: {'method': 'tools/list', 'jsonrpc': '2.0', 'id': 4} +[voice] INFO:sunsama_voice.mcp_websocket_client:Received message: {"result":{"tools":[{"name":"create_task","description":"Creates a single task with a title, optional notes, and estimated time.","inputSchema":{"$schema":"http://json-schema.org/draft-07/schema#","type":"object","properties":{"title":{"description":"A short title of the task, should not be more than a few words","type":"string"},"notes":{"description":"All extra details the user shared about the task, in HTML format","type":"string"},"timeEstimate":{"description":"The estimated time in minutes for the task","type":"number"},"objectiveId":{"description":"The _id of the weekly objective the task should be associated with, if any.","type":"string"},"day":{"description":"The day the task should be scheduled to in YYYY-MM-DD 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If the task has any subtasks with planned time, you must provide a subtaskId since the time estimate for the task will be calculated based on the subtasks.","type":"string"},"timeEstimate":{"description":"The new time estimate in minutes.","type":"number"}},"required":["taskId","timeEstimate"]},"execution":{"taskSupport":"forbidden"}},{"name":"append_task_notes","description":"Appends markdown notes to an existing task.","inputSchema":{"$schema":"http://json-schema.org/draft-07/schema#","type":"object","properties":{"taskId":{"description":"The ID of the task to update.","type":"string"},"notes":{"description":"The markdown notes to append to the task.","type":"string"}},"required":["taskId","notes"]},"execution":{"taskSupport":"forbidden"}},{"name":"delete_task","description":"Deletes an existing task.","inputSchema":{"$schema":"http://json-schema.org/draft-07/schema#","type":"object","properties":{"taskId":{"description":"The _id of the task to delete.","type":"string"}},"required":["taskId"]},"annotations":{"title":"Delete A Task","destructiveHint":true},"execution":{"taskSupport":"forbidden"}},{"name":"add_subtasks_to_task","description":"Adds multiple subtasks to an existing task.","inputSchema":{"$schema":"http://json-schema.org/draft-07/schema#","type":"object","properties":{"taskId":{"description":"The _id of the task to add the subtask to.","type":"string"},"subtasks":{"description":"The subtasks to add to the task.","type":"array","items":{"type":"object","properties":{"title":{"description":"The title of the subtask.","type":"string"},"timeEstimate":{"description":"The estimated time in minutes for the subtask.","type":"number"}},"required":["title"]}}},"required":["taskId","subtasks"]},"execution":{"taskSupport":"forbidden"}},{"name":"restore_task","description":"Changes a task from deleted to not deleted.","inputSchema":{"$schema":"http://json-schema.org/draft-07/schema#","type":"object","properties":{"taskId":{"description":"The _id of the task to mark as not deleted.","type":"string"}},"required":["taskId"]},"execution":{"taskSupport":"forbidden"}},{"name":"mark_task_as_completed","description":"Marks a task as completed. 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Required if the event is not all day","type":"number"},"isAllDay":{"default":false,"description":"Whether the event is all day.","type":"boolean"},"description":{"description":"Optional description of the event.","type":"string"},"calendarId":{"description":"The ID of the calendar to create the event in. If not provided, the default calendar will be used. IMPORTANT: user must have owner or writer access to the calendar.","type":"string"}},"required":["title","startDate"]},"execution":{"taskSupport":"forbidden"}},{"name":"timebox_a_task_to_calendar","description":"Timeboxes a task to the calendar. This will create a timebox event for the task. This may also be referred to as \"scheduling\" a task or \"adding a task to the calendar\".","inputSchema":{"$schema":"http://json-schema.org/draft-07/schema#","type":"object","properties":{"taskId":{"description":"The _id of the task to timebox.","type":"string"},"startDate":{"description":"The start date of the event in YYYY-MM-DD format. If this is in the past you must confirm with the user that you are timeboxing a past task.","type":"string"},"startTime":{"description":"The start time of the event in 12 hour \"h:mm A\" format. If this is in the past you must confirm with the user that you are timeboxing a past task.","type":"string"},"duration":{"description":"The duration of the event in minutes. If not provided the timeEstimate of the task will be used or 30 minutes if the task has no time estimate.","type":"number"}},"required":["taskId","startDate","startTime"]},"execution":{"taskSupport":"forbidden"}},{"name":"delete_calendar_event","description":"Removes a calendar event and deletes all associated tasks. If the event is a meeting then any access role can remove the event. Otherwise only owners or writers can remove the event. Note: If the event is a meeting and the user is an owner or write this will remove the event for ALL attendees.","inputSchema":{"$schema":"http://json-schema.org/draft-07/schema#","type":"object","properties":{"eventId":{"description":"The unique ID of the calendar event to remove.","type":"string"}},"required":["eventId"]},"annotations":{"title":"Removes A Calendar Event","destructiveHint":true},"execution":{"taskSupport":"forbidden"}},{"name":"import_task_from_calendar_event","description":"Imports a calendar event as a task.","inputSchema":{"$schema":"http://json-schema.org/draft-07/schema#","type":"object","properties":{"eventId":{"description":"The unique ID of the calendar event to import as a task.","type":"string"}},"required":["eventId"]},"execution":{"taskSupport":"forbidden"}},{"name":"accept_meeting_invite","description":"Confirms attendance to a meeting that the user is invited to.","inputSchema":{"$schema":"http://json-schema.org/draft-07/schema#","type":"object","properties":{"eventId":{"description":"The unique ID of the calendar event to accept the meeting invite for.","type":"string"}},"required":["eventId"]},"execution":{"taskSupport":"forbidden"}},{"name":"decline_meeting_invite","description":"Decline attendance to a meeting that the user is invited to.","inputSchema":{"$schema":"http://json-schema.org/draft-07/schema#","type":"object","properties":{"eventId":{"description":"The unique ID of the calendar event to decline the meeting invite for.","type":"string"}},"required":["eventId"]},"execution":{"taskSupport":"forbidden"}},{"name":"set_calendar_event_allow_task_projections","description":"Sets whether tasks are allowed to be automatically projected (scheduled) at the same time as a calendar event. When set to true, tasks can be automatically projected during the event. When set to false, tasks cannot be automatically projected during the event. Note: This only affects automatic projections; users can still manually timebox tasks during this event.","inputSchema":{"$schema":"http://json-schema.org/draft-07/schema#","type":"object","properties":{"eventId":{"description":"The unique ID of the calendar event to set task projection settings for.","type":"string"},"allowTasksProjectedAtSameTime":{"description":"If true, allows tasks to be automatically projected at the same time as this event. If false, blocks tasks from being automatically projected at the same time as this event. Note: This only affects automatic projections; manual timeboxing is not affected.","type":"boolean"}},"required":["eventId","allowTasksProjectedAtSameTime"]},"execution":{"taskSupport":"forbidden"}},{"name":"toggle_auto_import_events","description":"Enables or disables automatic importing of calendar events to the daily task list.","inputSchema":{"$schema":"http://json-schema.org/draft-07/schema#","type":"object","properties":{"enabled":{"description":"Whether to enable (true) or disable (false) automatic importing of calendar events.","type":"boolean"}},"required":["enabled"]},"execution":{"taskSupport":"forbidden"}},{"name":"update_import_event_filters","description":"Updates the exclusion filters that determine which calendar events are excluded from automatic import. Events matching any of these filters will NOT be automatically imported.","inputSchema":{"$schema":"http://json-schema.org/draft-07/schema#","type":"object","properties":{"excludedEventFilters":{"description":"An array of exclusion filter types. Events matching any of these filters will be EXCLUDED from auto-import. Available filters: \"solo\" (events with no other invitees), \"transparent\" (non-blocking events), \"hold\" (events with HOLD/OOO/Focus time in title), \"unconfirmed\" (unconfirmed meeting invites), \"multi-day-all-day\" (multi-day all-day events), \"single-day-all-day\" (single-day all-day events).","type":"array","items":{"type":"string","enum":["solo","transparent","hold","unconfirmed","multi-day-all-day","single-day-all-day"]}}},"required":["excludedEventFilters"]},"execution":{"taskSupport":"forbidden"}},{"name":"update_calendar_preferences","description":"Updates preferences for a specific calendar including whether it is the default for tasks, default for events, and whether it is included in auto-importing of events.","inputSchema":{"$schema":"http://json-schema.org/draft-07/schema#","type":"object","properties":{"calendarId":{"description":"The ID of the calendar to update preferences for.","type":"string"},"isDefaultForTasks":{"description":"Whether this calendar should be the default calendar for timeboxing tasks. If not provided, this preference will not be changed.","type":"boolean"},"isDefaultForEvents":{"description":"Whether this calendar should be the default calendar for scheduling events. If not provided, this preference will not be changed.","type":"boolean"},"includedInAutoImportingOfEvents":{"description":"Whether this calendar should be included in automatic importing of calendar events. If not provided, this preference will not be changed.","type":"boolean"}},"required":["calendarId"]},"execution":{"taskSupport":"forbidden"}},{"name":"delete_email_thread","description":"Deletes an email thread from Gmail or Outlook.","inputSchema":{"$schema":"http://json-schema.org/draft-07/schema#","type":"object","properties":{"accountId":{"description":"The ID of the email account you are looking at.","type":"string"},"accountService":{"description":"This is either \"outlook\" or \"gmail\", depending on the email provider.","type":"string"},"threadId":{"description":"The ID of the thread to delete.","type":"string"}},"required":["accountId","accountService","threadId"]},"execution":{"taskSupport":"forbidden"}},{"name":"mark_email_thread_as_read","description":"Marks an email thread as read.","inputSchema":{"$schema":"http://json-schema.org/draft-07/schema#","type":"object","properties":{"accountId":{"description":"The ID of the email account.","type":"string"},"accountService":{"description":"This is either \"outlook\" or \"gmail\".","type":"string"},"threadId":{"description":"The ID of the thread to mark as read.","type":"string"}},"required":["accountId","accountService","threadId"]},"execution":{"taskSupport":"forbidden"}},{"name":"create_follow_up_task_from_email","description":"Turn the email thread into a task to be followed up with later.","inputSchema":{"$schema":"http://json-schema.org/draft-07/schema#","type":"object","properties":{"accountId":{"description":"The ID of the email account you are looking at.","type":"string"},"accountService":{"description":"This is either \"outlook\" or \"gmail\", depending on the result of list_email_accounts.","type":"string"},"threadId":{"description":"The ID of the thread to mark as read.","type":"string"},"notes":{"description":"Any notes the user mentioned about the task/email.","type":"string"},"timeEstimate":{"description":"The estimated time in minutes for the task.","type":"number"}},"required":["accountId","accountService","threadId"]},"execution":{"taskSupport":"forbidden"}},{"name":"list_email_threads","description":"Lists email threads for a given Gmail account. You MUST specify at least a `labels` or a `search` parameter to avoid fetching irrelevant emails.","inputSchema":{"$schema":"http://json-schema.org/draft-07/schema#","type":"object","properties":{"accountId":{"description":"The ID of the email account to list threads from.","type":"string"},"labels":{"description":"Optional list of Gmail labels to filter by, e.g., [\"INBOX\", \"IMPORTANT\"]","type":"array","items":{"type":"string"}},"search":{"description":"Optional Gmail search query. Example: `after:2025-04-01 before:2025-04-17` or `is:unread`.","type":"string"},"pageToken":{"description":"Optional token for paginating through results.","type":"string"}},"required":["accountId"]},"execution":{"taskSupport":"forbidden"}},{"name":"create_weekly_objective","description":"Creates a new weekly objective.","inputSchema":{"$schema":"http://json-schema.org/draft-07/schema#","type":"object","properties":{"title":{"description":"The title of the weekly objective.","type":"string"},"weekStartDay":{"description":"The start day of the week in YYYY-MM-DD format.","type":"string"},"timeEstimate":{"description":"The estimated time in minutes for the objective.","type":"number"},"channel":{"description":"The channel name to associate with the objective. This does not need to be perfect. The closest match will be used.","type":"string"}},"required":["title","weekStartDay"]},"execution":{"taskSupport":"forbidden"}},{"name":"send_call_summary","description":"Sends a summary of our call via email.","inputSchema":{"$schema":"http://json-schema.org/draft-07/schema#","type":"object","properties":{"summaryIntroduction":{"description":"A short introduction to the summary. This will be used as the first line of the summary email.\nExample:\nHere is the summary of our call for today June 25th, 2025:\n","type":"string"},"summaryHighlights":{"description":"A list of highlights from the call. This will be used as the second line of the summary email.\nExample:\n- You planned your day focusing on refining the voice assistant.\n- Created a weekly objective for this goal.\n- Added key backlog tasks: refining the NLU model, bug fixes, API documentation, and unit tests.\n- You scheduled a sync with Diane at 2:30 PM.\n- You set a planned shutdown time of 5 PM.\n","type":"array","items":{"type":"string"}},"summaryFooter":{"description":"A short footer to the summary. This will be used as the last line of the summary email.\n \nExample:\nThis plan keeps your day focused, balanced, and aligned with your objectives.\n","type":"string"}}},"execution":{"taskSupport":"forbidden"}},{"name":"log_user_feedback","description":"Logs user feedback.","inputSchema":{"$schema":"http://json-schema.org/draft-07/schema#","type":"object","properties":{"feedback":{"description":"A summary of the feedback you want to log.","type":"string"},"transcript":{"description":"A transcript of the exact feedback you want to log.","type":"string"},"bugReports":{"description":"A list of bugs you want to report.","type":"array","items":{"type":"object","properties":{"bug":{"description":"The bug you want to report.","type":"string"},"description":{"description":"A detailed description of the bug.","type":"string"}},"required":["bug"]}},"featureRequests":{"description":"A list of feature requests you want to log.","type":"array","items":{"type":"object","properties":{"feature":{"description":"The feature you want to request.","type":"string"},"description":{"description":"A detailed description of the feature.","type":"string"}},"required":["feature"]}}},"required":["feedback"]},"execution":{"taskSupport":"forbidden"}},{"name":"set_shutdown_time","description":"Sets the shutdown time for a specific day.","inputSchema":{"$schema":"http://json-schema.org/draft-07/schema#","type":"object","properties":{"calendarDay":{"description":"The day to set the shutdown time for, in YYYY-MM-DD format.","type":"string"},"hour":{"description":"Hour of the shutdown time (0-23)","type":"number"},"minute":{"description":"Minute of the shutdown time (0-59)","type":"number"},"addToTheCalendar":{"description":"Whether to create a shutdown task and calendar event for the day.","default":false,"type":"boolean"}},"required":["calendarDay","hour","minute"]},"execution":{"taskSupport":"forbidden"}},{"name":"adjust_call_schedule","description":"Adjusts the schedule for voice assistant phone calls. Only one call per day is supported. Updating the schedule will reset the next call time to the next available time after today.","inputSchema":{"$schema":"http://json-schema.org/draft-07/schema#","type":"object","properties":{"daySchedules":{"type":"array","items":{"type":"object","properties":{"isoDayIndex":{"description":"ISO weekday number (1=Monday, 7=Sunday)","type":"number","minimum":1,"maximum":7},"enabled":{"default":true,"description":"Whether calls should be enabled on this day","type":"boolean"},"hour":{"description":"The hour to set the call time to (0-23). If not provided the old value will be used.","type":"number","minimum":0,"maximum":23},"minute":{"description":"The minute for the next call (00, 15, 30, 45). If not provided the old value will be used.","type":"string","enum":["15","30","45","00"]}},"required":["isoDayIndex"]}}}},"execution":{"taskSupport":"forbidden"}},{"name":"schedule_next_call","description":"Schedules the next phone call at a specific date and time. This will skip all other scheduled calls until this one. Useful for temporarily disabling calls for a few days or scheduling a call back in the short term.","inputSchema":{"$schema":"http://json-schema.org/draft-07/schema#","type":"object","properties":{"nextCallDate":{"description":"The date for the next call in YYYY-MM-DD format.","type":"string"},"hour":{"description":"The hour for the next call (0-23).","type":"number"},"minute":{"description":"The minute for the next call (00, 15, 30, 45).","type":"string","enum":["15","30","45","00"]}},"required":["nextCallDate","hour","minute"]},"execution":{"taskSupport":"forbidden"}},{"name":"create_channel","description":"Creates a new channel for the user.","inputSchema":{"$schema":"http://json-schema.org/draft-07/schema#","type":"object","properties":{"channelName":{"description":"The name of the channel to create.","type":"string"},"categoryName":{"description":"The name of the category this should belong to. If not provided one will be assigned automatically.","type":"string"},"isPersonal":{"default":false,"description":"Whether the channel is a personal channel. If not provided it will be assumed to be a work channel. This option is ignored if a category name is provided.","type":"boolean"}},"required":["channelName"]},"execution":{"taskSupport":"forbidden"}},{"name":"complete_onboarding_guide","description":"Completes the onboarding guide for the user.","inputSchema":{"$schema":"http://json-schema.org/draft-07/schema#","type":"object","properties":{"dayPlanned":{"description":"The day the user planned during their onboarding guide. In YYYY-MM-DD format.","type":"string"}},"required":["dayPlanned"]},"execution":{"taskSupport":"forbidden"}},{"name":"trigger_user_interface_action","description":"Triggers an action in the user interface that the user is currently looking at. Using one of the actionIds from the get_available_ui_actions resource. YOU ABSOLUTELY MUST ONLY USE actionIds from the latest call to get_available_ui_actions. All other actionIds are invalid and will not work.\n - Navigation type actions: Navigate to a specific location in the user interface.\n - Highlight type actions: Highlight an element in the user interface to make it easy for the user to find it.","inputSchema":{"$schema":"http://json-schema.org/draft-07/schema#","type":"object","properties":{"actionId":{"description":"The action ID for a user interface action to trigger. Use the get_available_ui_actions resource to see what user interface actions are currently available.","type":"string"},"params":{"description":"Optional parameters for the navigation. As given by the get_available_ui_actions resource for the specific action.","type":"object","propertyNames":{"type":"string"},"additionalProperties":{}}},"required":["actionId"]},"execution":{"taskSupport":"forbidden"}}]},"jsonrpc":"2.0","id":4} +[voice] INFO:sunsama_voice.mcp_websocket_client:Sending message: {'method': 'resources/templates/list', 'jsonrpc': '2.0', 'id': 5} +[voice] INFO:sunsama_voice.mcp_websocket_client:Received message: {"result":{"resourceTemplates":[{"name":"get_tasks_for_day","uriTemplate":"sunsama://tasks/{calendarDay}","description":"Gets all the tasks already created for the user for the day.","mimeType":"application/json"},{"name":"get_total_planned_time","uriTemplate":"sunsama://total-planned-time/{calendarDay}","description":"Retrieves the total planned time for the user for a given calendar day. This includes the total planned work time, the total planned personal time and the estimated earliest possible shutdown time.","mimeType":"application/json"},{"name":"get_calendar_events_for_day","uriTemplate":"sunsama://calendar/events/{calendarDay}","description":"Retrieves calendar events for a specific date","mimeType":"application/json"},{"name":"get_weekly_objectives","uriTemplate":"sunsama://objectives{/calendarDay}","description":"Retrieves the user's weekly objectives. If calendarDay is provided, returns objectives for that week. If not provided, returns objectives for the current week.","mimeType":"application/json"}]},"jsonrpc":"2.0","id":5} +[voice] INFO:sunsama_voice.mcp:Subscribed to resource sunsama://me with args: {} +[voice] INFO:sunsama_voice.mcp_websocket_client:Sending message: {'method': 'resources/subscribe', 'params': {'uri': 'sunsama://me'}, 'jsonrpc': '2.0', 'id': 6} +[api-local] [api] +[api-local] [api] +[api-local] [api] +[api-local] [api] Subscribing to resource { uri: 'sunsama://me' } { +[api-local] [api] signal: AbortSignal { aborted: false }, +[api-local] [api] sessionId: '64832d8f-2289-4bf4-8f8b-0452890bb28f', +[api-local] [api] _meta: undefined, +[api-local] [api] sendNotification: [AsyncFunction: sendNotification], +[api-local] [api] sendRequest: [AsyncFunction: sendRequest], +[api-local] [api] authInfo: { +[api-local] [api] token: 'eyJhbGciOiJIUzI1NiIsInR5cCI6IkpXVCJ9.eyJ1c2VySWQiOiI2NzFhYzVlNDAyYTMwMmNmNmVmMzA4OGUiLCJzZXNzaW9uSWQiOiIxOTVmNDI0NC05YjFmLTRlYmItOTMwZC0wZTExNTAwNzZkYzkiLCJzZXNzaW9uTm9uY2UiOiJhY2ZlZTc2OS1jZGU2LTRkMWYtYTU5Ni0xMzk0MTRkMjUxNjAiLCJncm91cElkIjoiNjcxYWM1ZTkwMmEzMDJjZjZlZjMwODkwIiwiZ3JvdXBVcmxQYXRoIjoiMTcyOTgwNzg0OTAzNjUxOTIiLCJpYXQiOjE3Njg1OTAyMTYsImV4cCI6MTc3MTE4MjIxNn0.HHSuewYqBRl-IZkdiWcEJyiD6akgbtwnOIQ4Js71bZI', +[api-local] [api] clientId: '195f4244-9b1f-4ebb-930d-0e1150076dc9', +[api-local] [api] scopes: [], +[api-local] [api] extra: { +[api-local] [api] request: [Object], +[api-local] [api] response: [Object], +[api-local] [api] app: [Object], +[api-local] [api] originalUrl: '/ai/mcp', +[api-local] [api] req: '', +[api-local] [api] res: '', +[api-local] [api] socket: '' +[api-local] [api] } +[api-local] [api] }, +[api-local] [api] requestId: 6, +[api-local] [api] requestInfo: undefined, +[api-local] [api] taskId: undefined, +[api-local] [api] taskStore: undefined, +[api-local] [api] taskRequestedTtl: undefined, +[api-local] [api] closeSSEStream: undefined, +[api-local] [api] closeStandaloneSSEStream: undefined +[api-local] [api] } +[api-local] [api] Registered handler for channel "user-updates-671ac5e402a302cf6ef3088e" for event "userUpdated" +[voice] INFO:sunsama_voice.mcp_websocket_client:Received message: {"result":{"success":true},"jsonrpc":"2.0","id":6} +[voice] INFO:sunsama_voice.mcp:Resources: ['get_user_authentication_status', 'get_user_info', 'list_email_accounts', 'get_last_daily_highlight', 'get_backlog_folders', 'get_active_timer', 'get_available_ui_actions'] get_backlog_folders +[voice] INFO:sunsama_voice.mcp:Subscribed to resource sunsama://backlog/folders with args: {} +[voice] INFO:sunsama_voice.mcp_websocket_client:Sending message: {'method': 'resources/subscribe', 'params': {'uri': 'sunsama://backlog/folders'}, 'jsonrpc': '2.0', 'id': 7} +[api-local] [api] +[api-local] [api] +[api-local] [api] +[api-local] [api] Subscribing to resource { uri: 'sunsama://backlog/folders' } { +[api-local] [api] signal: AbortSignal { aborted: false }, +[api-local] [api] sessionId: '64832d8f-2289-4bf4-8f8b-0452890bb28f', +[api-local] [api] _meta: undefined, +[api-local] [api] sendNotification: [AsyncFunction: sendNotification], +[api-local] [api] sendRequest: [AsyncFunction: sendRequest], +[api-local] [api] authInfo: { +[api-local] [api] token: 'eyJhbGciOiJIUzI1NiIsInR5cCI6IkpXVCJ9.eyJ1c2VySWQiOiI2NzFhYzVlNDAyYTMwMmNmNmVmMzA4OGUiLCJzZXNzaW9uSWQiOiIxOTVmNDI0NC05YjFmLTRlYmItOTMwZC0wZTExNTAwNzZkYzkiLCJzZXNzaW9uTm9uY2UiOiJhY2ZlZTc2OS1jZGU2LTRkMWYtYTU5Ni0xMzk0MTRkMjUxNjAiLCJncm91cElkIjoiNjcxYWM1ZTkwMmEzMDJjZjZlZjMwODkwIiwiZ3JvdXBVcmxQYXRoIjoiMTcyOTgwNzg0OTAzNjUxOTIiLCJpYXQiOjE3Njg1OTAyMTYsImV4cCI6MTc3MTE4MjIxNn0.HHSuewYqBRl-IZkdiWcEJyiD6akgbtwnOIQ4Js71bZI', +[api-local] [api] clientId: '195f4244-9b1f-4ebb-930d-0e1150076dc9', +[api-local] [api] scopes: [], +[api-local] [api] extra: { +[api-local] [api] request: [Object], +[api-local] [api] response: [Object], +[api-local] [api] app: [Object], +[api-local] [api] originalUrl: '/ai/mcp', +[api-local] [api] req: '', +[api-local] [api] res: '', +[api-local] [api] socket: '' +[api-local] [api] } +[api-local] [api] }, +[api-local] [api] requestId: 7, +[api-local] [api] requestInfo: undefined, +[api-local] [api] taskId: undefined, +[api-local] [api] taskStore: undefined, +[api-local] [api] taskRequestedTtl: undefined, +[api-local] [api] closeSSEStream: undefined, +[api-local] [api] closeStandaloneSSEStream: undefined +[api-local] [api] } +[api-local] [api] Registered handler for channel "backlog-folder-updates-671ac5e902a302cf6ef30890-671ac5e402a302cf6ef3088e" for event "folderUpdated" +[voice] INFO:sunsama_voice.mcp_websocket_client:Received message: {"result":{"success":true},"jsonrpc":"2.0","id":7} +[voice] INFO:sunsama_voice.bot:Timer: Flow config created in 0.19129395484924316 seconds +[voice] DEBUG:pipecat_flows.actions:Registered handler for action type: tts_say +[voice] DEBUG:pipecat_flows.actions:Registered handler for action type: end_conversation +[voice] DEBUG:pipecat_flows.actions:Registered handler for action type: function +[voice] DEBUG:pipecat_flows.adapters:Creating Google adapter +[voice] DEBUG:pipecat_flows.manager:Initialized in static mode +[voice] DEBUG:sunsama_voice.bot:no dialout number; assuming dialin +[voice] INFO:sunsama_voice.bot:Starting the pipeline +[voice] INFO:sunsama_voice.bot:Timer: Pipeline started in 0.19174408912658691 seconds +[voice] DEBUG:pipecat.pipeline.runner:Runner PipelineRunner#0 started running PipelineTask#0 +[voice] DEBUG:pipecat.pipeline.task:PipelineTask#0: Starting. Waiting for StartFrame#0 to reach the end of the pipeline... +[voice] DEBUG:pipecat.audio.vad.vad_analyzer:Setting VAD params to: confidence=0.7 start_secs=0.2 stop_secs=0.2 min_volume=0.6 +[voice] INFO:pipecat.transports.daily.transport:Joining https://cloud-99400c183d52498c940fe96f45c05b44.daily.co/teWpRxCQnkMHYi7Q3lqh +[voice] DEBUG:pipecat.services.cartesia.tts:Connecting to Cartesia TTS +[voice] DEBUG:pipecat.pipeline.task:PipelineTask#0: StartFrame#0 reached the end of the pipeline, pipeline is now ready. +[voice] ERROR:pipecat.transports.daily.transport:Unable to send message: Unable to send messages before joining. +[voice] INFO:pipecat.transports.daily.transport:Joined https://cloud-99400c183d52498c940fe96f45c05b44.daily.co/teWpRxCQnkMHYi7Q3lqh +[voice] DEBUG:pipecat.transports.daily.transport:Starting transcription: settings=language='en' model='nova-3' profanity_filter=True redact=False endpointing=True punctuate=True includeRawResponse=True extra={'interim_results': True} +[voice] DEBUG:pipecat.transports.daily.transport:Transcription started: {'instanceId': 'a1f2f6b7-b1ac-4202-85e5-d446cb6c3d3f', 'language': 'en', 'model': 'nova-3', 'startedBy': '0106bd40-d21f-4da2-8518-3c3c4997b2ae', 'transcriptId': 'e1c71759-439e-492b-92fd-3d5344c2492f'} +[voice] DEBUG:pipecat.transports.daily.transport:Start receiving audio +[voice] INFO:pipecat.transports.daily.transport:Participant joined 941aacac-ae67-454d-86a1-65308278e261 +[voice] DEBUG:pipecat.transports.daily.transport:Starting to capture [microphone] audio from participant 941aacac-ae67-454d-86a1-65308278e261 +[voice] INFO:sunsama_voice.bot:First participant joined: {'id': '941aacac-ae67-454d-86a1-65308278e261', 'info': {'isLocal': False, 'isOwner': True, 'joinedAt': 1768590245, 'permissions': {'canAdmin': ['participants', 'transcription', 'streaming'], 'canReceive': {'base': {'camera': True, 'customAudio': {'*': True}, 'customVideo': {'*': True}, 'microphone': True, 'screenAudio': True, 'screenVideo': True}}, 'canSend': ['customAudio', 'camera', 'microphone', 'customVideo', 'screenAudio', 'screenVideo'], 'hasPresence': True}}, 'media': {'camera': {'offReasons': ['user'], 'state': 'off', 'subscribed': 'unsubscribed'}, 'customAudio': {}, 'customVideo': {}, 'microphone': {'state': 'loading', 'subscribed': 'subscribed'}, 'screenAudio': {'offReasons': ['user'], 'state': 'off', 'subscribed': 'subscribed'}, 'screenVideo': {'offReasons': ['user'], 'state': 'off', 'subscribed': 'unsubscribed'}}} +[voice] DEBUG:pipecat.processors.frameworks.rtvi:Received client-ready: version 1.0.0 +[voice] DEBUG:pipecat.processors.frameworks.rtvi:Client Details: library='@pipecat-ai/client-js' library_version='1.2.0' platform='macOS' platform_version='10.15.7' platform_details={'browser': 'Chrome', 'browser_version': '143.0.0.0', 'engine': 'Blink', 'platform_type': 'desktop'} +[voice] INFO:sunsama_voice.bot:Starting an in-app call +[voice] INFO:sunsama_voice.bot:Timer: Dialin/in-app call started in 1.073638916015625 seconds +[voice] DEBUG:pipecat_flows.manager:Initialized FlowManager +[voice] DEBUG:pipecat_flows.manager:Setting initial node: braindump +[voice] /Users/zanemccaig/workspaces/sunsama/sunsama/sunsama-voice/venv/lib/python3.13/site-packages/pipecat_flows/manager.py:768: DeprecationWarning: `transition_to` and `transition_callback` are deprecated and will be removed in 1.0.0. Use a "consolidated" `handler` that returns a tuple (result, next_node) instead. +[voice] self._validate_node_config(node_id, node_config) +[voice] DEBUG:pipecat_flows.manager:Setting node: braindump +[voice] DEBUG:pipecat_flows.manager:Registered function: terminate_call +[voice] DEBUG:pipecat_flows.manager:Registered function: create_task +[voice] DEBUG:pipecat_flows.manager:Registered function: create_braindump_task +[voice] DEBUG:pipecat_flows.manager:Registered function: reposition_task_in_backlog +[voice] DEBUG:pipecat_flows.manager:Registered function: change_backlog_folder +[voice] DEBUG:pipecat_flows.manager:Registered function: align_task_with_objective +[voice] DEBUG:pipecat_flows.manager:Registered function: add_task_to_channel +[voice] DEBUG:pipecat_flows.manager:Registered function: move_task_to_day +[voice] DEBUG:pipecat_flows.manager:Registered function: move_task_from_backlog +[voice] DEBUG:pipecat_flows.manager:Registered function: unarchive_task +[voice] DEBUG:pipecat_flows.manager:Registered function: move_task_to_backlog +[voice] DEBUG:pipecat_flows.manager:Registered function: get_task_time_estimate +[voice] DEBUG:pipecat_flows.manager:Registered function: edit_task_recurrence_rule +[voice] DEBUG:pipecat_flows.manager:Registered function: edit_task_title +[voice] DEBUG:pipecat_flows.manager:Registered function: edit_task_time_estimate +[voice] DEBUG:pipecat_flows.manager:Registered function: delete_task +[voice] DEBUG:pipecat_flows.manager:Registered function: add_subtasks_to_task +[voice] DEBUG:pipecat_flows.manager:Registered function: restore_task +[voice] DEBUG:pipecat_flows.manager:Registered function: mark_task_as_completed +[voice] DEBUG:pipecat_flows.manager:Registered function: mark_task_as_incomplete +[voice] DEBUG:pipecat_flows.manager:Registered function: edit_subtask_title +[voice] DEBUG:pipecat_flows.manager:Registered function: mark_subtask_as_completed +[voice] DEBUG:pipecat_flows.manager:Registered function: mark_subtask_as_incomplete +[voice] DEBUG:pipecat_flows.manager:Registered function: reorder_tasks +[voice] DEBUG:pipecat_flows.manager:Registered function: get_backlog_tasks +[voice] DEBUG:pipecat_flows.manager:Registered function: get_archived_tasks +[voice] DEBUG:pipecat_flows.manager:Registered function: search_tasks +[voice] DEBUG:pipecat_flows.manager:Registered function: update_all_incomplete_recurring_task_instances +[voice] DEBUG:pipecat_flows.manager:Registered function: delete_all_incomplete_recurring_task_instances +[voice] DEBUG:pipecat_flows.manager:Registered function: start_task_timer +[voice] DEBUG:pipecat_flows.manager:Registered function: stop_task_timer +[voice] DEBUG:pipecat_flows.manager:Registered function: move_calendar_event +[voice] DEBUG:pipecat_flows.manager:Registered function: create_calendar_event +[voice] DEBUG:pipecat_flows.manager:Registered function: timebox_a_task_to_calendar +[voice] DEBUG:pipecat_flows.manager:Registered function: delete_calendar_event +[voice] DEBUG:pipecat_flows.manager:Registered function: import_task_from_calendar_event +[voice] DEBUG:pipecat_flows.manager:Registered function: accept_meeting_invite +[voice] DEBUG:pipecat_flows.manager:Registered function: decline_meeting_invite +[voice] DEBUG:pipecat_flows.manager:Registered function: set_calendar_event_allow_task_projections +[voice] DEBUG:pipecat_flows.manager:Registered function: toggle_auto_import_events +[voice] DEBUG:pipecat_flows.manager:Registered function: update_import_event_filters +[voice] DEBUG:pipecat_flows.manager:Registered function: update_calendar_preferences +[voice] DEBUG:pipecat_flows.manager:Registered function: create_weekly_objective +[voice] DEBUG:pipecat_flows.manager:Registered function: send_call_summary +[voice] DEBUG:pipecat_flows.manager:Registered function: log_user_feedback +[voice] DEBUG:pipecat_flows.manager:Registered function: set_shutdown_time +[voice] DEBUG:pipecat_flows.manager:Registered function: adjust_call_schedule +[voice] DEBUG:pipecat_flows.manager:Registered function: schedule_next_call +[voice] DEBUG:pipecat_flows.manager:Registered function: create_channel +[voice] DEBUG:pipecat_flows.manager:Registered function: get_user_info +[voice] DEBUG:pipecat_flows.manager:Registered function: get_last_daily_highlight +[voice] DEBUG:pipecat_flows.manager:Registered function: get_backlog_folders +[voice] DEBUG:pipecat_flows.manager:Registered function: get_active_timer +[voice] DEBUG:pipecat_flows.manager:Registered function: get_tasks_for_day +[voice] DEBUG:pipecat_flows.manager:Registered function: get_total_planned_time +[voice] DEBUG:pipecat_flows.manager:Registered function: get_calendar_events_for_day +[voice] DEBUG:pipecat_flows.manager:Registered function: get_weekly_objectives +[voice] DEBUG:pipecat_flows.manager:Updated LLM context using LLMMessagesUpdateFrame with strategy ContextStrategy.APPEND +[voice] DEBUG:pipecat_flows.manager:Updated LLM context +[voice] DEBUG:pipecat_flows.manager:Successfully set node: braindump +[voice] :4: DeprecationWarning: OpenAILLMContextFrame is deprecated and will be removed in a future version. Use LLMContextFrame with the universal `LLMContext` and `LLMContextAggregatorPair` instead. See OpenAILLMContext docstring for migration guide. +[voice] DEBUG:pipecat.services.google.llm:GoogleLLMService#0: Generating chat from LLM-specific context [None] | [{'parts': [{'text': 'system :\nYour agent ID is \'braindump\'. This agent ID superseeds any previously mentioned agent ID.\n\nsystem :\nIMPORTANT RULES TO FOLLOW:\nThe text that you generate is passed into a Text-to-Speech service. So there are a few extra rules you ABSOLUTELY MUST follow.\n1. Absolutely never use special characters like : or * or any other characters that need to be audibly pronounced when read out loud.\n2. Do not use bullet points.\n3. Do not use emojis.\n4. Do not use hashtags.\n5. Do not use markdown.\n6. Do not use bold or italics.\n7. Do not use numbered lists.\n8. Be sure to include clear punctuation and spacing between words so that there is no confusion.\n9. Newlines are not clear enough to delineate between sentences. So you should use a period to separate sentences.\n10. Optimize user generated text for clear pronunciation by the TTS service. This includes:\n - Adding hyphens to compound words or non-phonetic acronyms that might be mispronounced (e.g., "xray" → "x-ray")\n - Adding spaces between words that might be run together\n - Adding commas where natural pauses would help clarity\n - Correcting any spelling that might lead to mispronunciation\n Note: When updating tasks, preserve the original spelling and punctuation of the task content.\n\n\nuser :\nYou are Sunny, the personal assistant for a busy professional. You are part of Sunsama.\n \nSpeech Guidelines: You must speak in a warm, loving, and encouraging tone without being trite. Speak quickly and add emotion. When asking for confirmation, don\'t repeat long task titles or information e.g. "Got it" instead "Got it, I\'ll add a task for two hours for you to work on the presentation today"\n\nYour personality and philosophy:\n- You don\'t buy into hustle culture. For you, less is more. It\'s better to do fewer things well and to do them with deep focus. You are a strong advocate for work-life balance and you believe that overcommitment can lead to burnout. You always remind the user when they are overcommitting themselves.\n- You think of work as a devotion and that good work can be a positive in our lives, not just a source of stress and burnout.\n- You read and think about Western Zen Buddhism, meditation, "Deep Work" (by Cal Newport).\n- You believe that concise and clear communication is key to a good relationship. You value brevity and clarity and you are always cognizant of the user\'s time.\n- You respond to the user using quick, short sentences. Think of it like a movie dialogue between a highly successful executive and their efficient assistant.\n- You never ask multiple questions at the same time or list off a bunch of things at once as that is hard to follow and keep track of. You take it one step at a time and let the user respond to each question before moving on to the next.\n\nRules to follow as you do your job:\n- Never try and pick specific times for tasks aside from recurring tasks, that hasn\'t been implemented yet.\n- Do not regurgitate what the user just said, that\'s very annoying. Just say "Got it" or "Alright", etc.\n- Always use units that are more intuitive. For example:\n - Don\'t say "270 minutes", say "4 and a half hours".\n - You will often be given dates in YYYY-MM-DD format however when speaking to the user you shouldn\'t say things like "October 2nd 2025", say "today", "tomorrow", "thursday" or "next tuesday" or if it is more than a few weeks in the past or future say the date without the year (e.g. "December 14th"). Only mention the year if it is not this year and not within the next month.\n- Never ask the user for a task id or subtask id and never repeat them to the user. Those are internal and only there to help you do your job.\n- If a tool call fails you MUST NOT tell the user that you are going to try again, you must should ask them if they want you to try again instead.\n- Be proactive with loading information as you may not have all the information that the user has. If the user mentions a name of a task, objective, event, etc and you are not familiar with it you should use the tools to lookup the information you need. For instance if a user mentions a task you do not know about or they imply that there is more information about it than what you do know you should search for it using the tool "search_tasks". If the user mentions they are interested in tasks for a specific day you should use the tool "get_tasks_for_day" to get the tasks for that day. Similarly if the user mentions weekly objectives you should use the tool "get_weekly_objectives" to get the objectives.\n- When listing tasks try to be concise. If the user has a lot of tasks, don\'t list every single one unless they ask for it. You should instead try to summarize the tasks in a concise manner.\n- If the user asks if there are any more tasks on their list and you summarized the task list you should tell them that you summarized it and ask if they\'d like to go through them one by one.\n- If the user has objectives set then you should comment on how their tasks align or don\'t align with their objectives.\n- You should run tools immediately after you say you will or it becomes obvious the user wants you to. Do not wait until later.\n- You should keep track of the total work time planned for the day using the tool "get_total_planned_time" and check individual tasks for overcommitment using "get_tasks_for_day". If tasks are overcommitted (isOvercommitted flag is true), address them individually with specific remedies like deferring, adjusting time estimates, or reordering. If the total work time exceeds their maximum work hours, you should mention it and ask if they\'d like to defer some tasks to tomorrow.\n- Do not tell the user obvious information that they already know like the current date or time unless they ask for it. That kind of information is only provided to you to help you do your job.\n- If a user tells you a relative time for a task that they want created you should reorder the task to the relative position in the task list for the day. Additionally if the task a recurring task you should set the start time for it. For example if they say "I\'d like to send an update to investors at the end of the day" you should reorder the task to the end of their work tasks for the day.\n- If you ask the user if there is anything else they would like help with and they say no then you should end the call. Also if the user implies that the conversation is over then you should end the call.\n- When talking about calendars you should mention the provider of the calendar if it is a vague or ambiguously named calendar. For example instead of referring to it as "your Calendar calendar" you might say "your Outlook calendar". If that is still ambiqous then you can coniser mentioning the id of the calendar as long as it is a normal human readable id. Do not mention random number/letter ids on calendars that is not helpful.\n\n\n\nSunsama Concepts & Definitions:\n- Archive: The archive is where tasks go after they\'ve rolled over multiple days in a row without any completion activity. This is a distinct concept from the backlog or deleted tasks.\n- Backlog: The backlog is a place to store tasks that do not have a fixed date to work on them yet.\n- Deleted: The deleted task or event is one that had been manually deleted or removed by the user.\n- Task: A task is an item that a user wants to complete. It is either scheduled for a specific date or is in the backlog.\n- Event: An event is an item that a user has scheduled on their calendar. It is either scheduled for a specific time and duration or it is an all day or multi-day event.\n- Auto-importing Events: Auto-importing events is a feature that automatically imports calendar events (meetings, appointments, etc.) from the user\'s connected calendars into their daily task list. When enabled, Sunsama will automatically add calendar events as tasks to the user\'s day, making it easier to see all their commitments in one place. Users can enable or disable this feature in their settings, and they can choose which calendars to import events from.\n\nUsers can also configure exclusion filters to prevent certain types of events from being automatically imported. Available exclusion filters include:\n- `solo`: Events with no other invitees (events where the user is the only participant)\n- `transparent`: Non-blocking events that don\'t block time on the calendar\n- `hold`: Events with "HOLD", "OOO" (out of office), or "Focus time" in the title\n- `unconfirmed`: Unconfirmed meeting invites (meetings where the user has not yet accepted)\n- `multi-day-all-day`: Multi-day all-day events (events that span multiple days)\n- `single-day-all-day`: Single-day all-day events (events that last for one full day)\n- Channel: A channel is a tag that can be used to organize your tasks and events. Each task/event can be assigned to a single channel. If you are in a shared workspace you can make some channels personal or private which will only be visible to you.\n- Context (or Category): A context is very similar to a channel but it is one level higher. You can use a context to group similar or related channels together. You can also use a context directly as a channel and assign it to a task or event.\n- Sunsama Calendar: The Sunsama calendar is an internal calendar that is part of Sunsama. Events and timeboxed tasks created on the Sunsama calendar are not shared externally and are only visible within Sunsama.\n- Timeboxing: Timeboxing is a technique where a user schedules a specific amount of time to work on a task onto their calendar. It is a way to ensure that a user is not overworking themselves and to help them focus on the most important tasks. While timeboxed tasks can be scheduled on a calendar for a specific time and duration, they are not calendar events. Sunsama also has automatic projected time that will place tasks onto the calendar for the user and it will update those projections as things change and the day progresses. Users can pin tasks to the calendar to override the projections.\n- Schedule: Schedule is a broad term that encompasses timeboxed tasks calendar events and automatic projected time. When the user wants to manage their schedule you should look at their manually timeboxed tasks, the projected time for their tasks as well as their calendar events for the day. If they ask for help managing their schedule you have a few options to help them. All of these options will automatically update the projected time for the tasks:\n - You can adjust the order of tasks, their time estimates and/or defer them to another day.\n - You can move calendar events to a new time on the calendar.\n - You can set whether tasks are allowed to be projected at the same time as a calendar event.\n - You can timebox tasks to the calendar manually.\n- Objective: An objective is a goal that a user can set for the week. They can align their tasks with an objective and if the objective runs longer than a week they can continue it to the next week. Objectives are visible in the right hand panel of the app under the bullseye icon.\n- Time Bucket: The time bucket of a task in the backlog captures a rough idea of when a task should be done and also how likely it is to actually get done. Options: "in the next two weeks", "in the next month", "in the next quarter", "in the next year", "someday", "never". \n\n\n\nSunsama FAQ:\n- How can I use Sunny in the app?: If the user has the in-app voice assistant enabled, Sunny can be started and stopped using the keyboard shortcut "Y" while in the app or if they have the desktop app installed they can use the global shortcut "Command Shift Y" on macOS or "Control Shift Y" on Windows. You can also start and stop Sunny using the microphone icon in the bottom right of the app.\n- How can I use Sunny over the phone?: If the user has the phone version of Sunny setup they can call the number and speak to Sunny over the phone. You can find the phone number in the Sunsama settings. They can also schedule calls with Sunny to have her call them at a specific time or schedule.\n- What can you do?: Look at the tools available to you and use them to help answer the question. Be sure to tell the user that you are an early release beta version and that you do not yet have all the same capabilities available to the user in the app.\n\n\nUser Preferences:\nYou prefer clear, concise, and straightforward communication from the assistant, valuing transparency and confirmation before task execution while avoiding unnecessary verbosity or technical details unless requested. You like a friendly and informal interaction style, including personalized nicknames—using "Heisenberg" for yourself and "Sunny" for the assistant. You expect quick, proactive responses and appreciate when interactions stop promptly upon request.\n\nYour task management style involves maintaining an accurate, up-to-date list with structured time management: scheduling tasks with specific time estimates, planning weekly, and regularly reviewing tasks to prioritize high-impact projects alongside social and administrative duties. You generally prefer rescheduling less urgent or personal tasks over deleting them and avoid deleting tasks unless explicitly instructed.\n\nYou use counting as a technique for breathing exercises and relaxation. You also keep certain important tasks (e.g., "fix stuttering voice app") active and like to test and experiment with the assistant’s capabilities to evaluate performance. Your primary calendar for events is Google Calendar.\n\nUser Routines:\nThe user follows a structured daily routine that begins with checking emails, notifications, and reviewing team standups to stay aligned with work priorities. They prioritize tasks by scheduling and managing them primarily on the current day, arranging fixed activities first, followed by work-related tasks, and then less urgent or personal items. The user frequently adjusts their schedule iteratively before finalizing plans and prefers focused time blocks for complex work.\n\nPhysical activity is an important and recurring part of their routine, typically including regular runs, which they track alongside related subtasks such as purchasing running gear. Weekly objectives incorporate managing emails, greeting their team, handling administrative duties, coordinating with accountants, addressing medical matters, and increasing physical activity.\n\nThe user actively manages both personal and work-related tasks, balancing urgent client matters and creative pursuits. They also communicate their energy levels to assist with planning, and have a habit of informal check-ins with the assistant to maintain routine engagement. Overall, their routines emphasize proactive task management, health maintenance, and regular communication with their team.\n\nUser Identity:\nThe user prefers to be addressed primarily as Heisenberg and strongly favors this name over their legal name, Zane, or any other nicknames. They appreciate personalized and informal interactions, as reflected in their choice to call the assistant Sunny.\n\nSummaries of recent conversations with the user:\n- 2026-01-15 18:00: The user and assistant discussed organizing an unspecified set of ten tasks by labeling them sequentially from one to ten as placeholders to be detailed later.\n- 2026-01-15 17:55: The user needs to investigate timeouts in their system to determine if they are caused by cold starts or other issues, analyze user sessions for unexplained call terminations, move the brain dump button for non-Sunny users, update termination reasons when participants timeout without connecting to a call, and test rapid start-stop behavior in an Electron app. These tasks were added to their backlog for the next two weeks.\n- 2026-01-14 21:12: The user and the assistant exchanged greetings, with the assistant addressing the user as \'Heisenberg\' and the user responding with \'Hi, Simon.\'\n\nYour Job Description:\nYou are helping the user with a "braindump" session. The user will ramble ideas, thoughts, tasks, etc. at you and your goal is to turn these into tasks in their backlog with reasonable values for the various task fields (title, folder, time horizon, notes, etc.).\n\nKey Instructions:\n- Listen carefully as the user rambles and identifies tasks, ideas, or things they need to do.\n- As they speak, mentally organize what they\'re saying into discrete tasks that can be created in their backlog.\n- Don\'t interrupt them while they\'re rambling - let them get everything out.\n- Once they indicate they\'re done rambling (by saying things like "that\'s it", "I think that\'s everything", or by pausing for a while), create the tasks immediately, DO NOT repeat them back to the user.\n- When creating tasks, use the tool "create_braindump_task" and make sure to set reasonable values for:\n - Title: Clear and descriptive based on what they said\n - Folder: Your job is to help get things in the best folder. Choose an appropriate folder based on the task and their preferences. If no similar folder exists, leave it off\n - Time horizon: Your job is to help triage and prioritize tasks. Based on the actual task name, make a smart decision on the time horizon.\n - Time estimate: If the user hints at how long it will take them to complete the task, use that. If not, leave it blank.\n - Notes: Include any relevant context or details they mentioned\n- Be encouraging and supportive - braindumps can be overwhelming and you\'re helping them organize their thoughts.\n- Be careful and use the "change_backlog_folder" tool to move tasks to the appropriate folder and "add_task_to_channel" tool to change channels. Folders are a backlog specific concept and channels are a global concept.\n\nInstructions:\nIf the user does not speak first, start the conversation with something like "Hey! Just start rambling and I\'ll take care of organizing your thoughts into tasks." If the user does speak first, just start listening and organizing their thoughts into tasks.\n\nSome information is pre-fetched for you below. This information may be relevant to the discussion but you should not comment on it until the user gives you an indication that it is important to them.\n\nassistant :\n[{\'id\': \'6a196f03-ef63-41de-b98d-e1ff69813bea\', \'function\': {\'name\': \'get_user_info\', \'arguments\': \'{}\'}, \'type\': \'function\'}]\n\ntool - 6a196f03-ef63-41de-b98d-e1ff69813bea:\n{"user":{"name":"Zane Mccaig","email":"zane@sunsama.com","timezone":"America/Vancouver","maxWorkHoursPerDay":8,"currentTimeForUser":"11:04 AM","currentDayForUser":"2026-01-16","currentWeekDayForUser":"Friday","calendars":[{"id":"sunsama-7de256a2-e753-401f-b601-e5c05638dc97","name":"Sunsama Calendar","accessRole":"owner","provider":"sunsama-calendar","isDefaultCalendarForSchedulingEvents":false,"isDefaultCalendarForTimeboxing":true,"includedInAutoImportingOfEvents":false},{"id":"zane@sunsama.com","name":"Zane Mccaig","accessRole":"owner","provider":"google-calendar","isDefaultCalendarForSchedulingEvents":true,"isDefaultCalendarForTimeboxing":false,"includedInAutoImportingOfEvents":true},{"id":"c_ukuoebbn11gdv6n1v0jt18h89k@group.calendar.google.com","name":"test 1","accessRole":"owner","provider":"google-calendar","isDefaultCalendarForSchedulingEvents":false,"isDefaultCalendarForTimeboxing":false,"includedInAutoImportingOfEvents":false},{"id":"c_c71dvjrar7se12ekfqepph067c@group.calendar.google.com","name":"test 2","accessRole":"owner","provider":"google-calendar","isDefaultCalendarForSchedulingEvents":false,"isDefaultCalendarForTimeboxing":false,"includedInAutoImportingOfEvents":false},{"id":"c_h9uo876jh8dp3gaa2a3rglmjss@group.calendar.google.com","name":"test 3","accessRole":"owner","provider":"google-calendar","isDefaultCalendarForSchedulingEvents":false,"isDefaultCalendarForTimeboxing":false,"includedInAutoImportingOfEvents":false},{"id":"c_git731ot074kcnt4sq8cu4ji9s@group.calendar.google.com","name":"test 4","accessRole":"owner","provider":"google-calendar","isDefaultCalendarForSchedulingEvents":false,"isDefaultCalendarForTimeboxing":false,"includedInAutoImportingOfEvents":false},{"id":"c_ona71b8ovuv0deqrq67p16b2ms@group.calendar.google.com","name":"test 4","accessRole":"owner","provider":"google-calendar","isDefaultCalendarForSchedulingEvents":false,"isDefaultCalendarForTimeboxing":false,"includedInAutoImportingOfEvents":false},{"id":"c_eaq7nmm03upprf0j6e2akem2ms@group.calendar.google.com","name":"test 5","accessRole":"owner","provider":"google-calendar","isDefaultCalendarForSchedulingEvents":false,"isDefaultCalendarForTimeboxing":false,"includedInAutoImportingOfEvents":false},{"id":"sunsama.com_b9q30t893b2tp32bluq1t8rvg4@group.calendar.google.com","name":"Zane\'s personal test calendar","accessRole":"owner","provider":"google-calendar","isDefaultCalendarForSchedulingEvents":false,"isDefaultCalendarForTimeboxing":false,"includedInAutoImportingOfEvents":false},{"id":"en.canadian#holiday@group.v.calendar.google.com","name":"Holidays in Canada","accessRole":"reader","provider":"google-calendar","isDefaultCalendarForSchedulingEvents":false,"isDefaultCalendarForTimeboxing":false,"includedInAutoImportingOfEvents":false},{"id":"en.usa#holiday@group.v.calendar.google.com","name":"Holidays in United States","accessRole":"reader","provider":"google-calendar","isDefaultCalendarForSchedulingEvents":false,"isDefaultCalendarForTimeboxing":false,"includedInAutoImportingOfEvents":false},{"id":"ht3jlfaac5lfd6263ulfh4tql8@group.calendar.google.com","name":"Phases of the Moon","accessRole":"reader","provider":"google-calendar","isDefaultCalendarForSchedulingEvents":false,"isDefaultCalendarForTimeboxing":false,"includedInAutoImportingOfEvents":false},{"id":"s4ipng85dbia0t83fp316vflfq8rc7rm@import.calendar.google.com","name":"Zane’s tasks - sunsama.com (via Asana)","accessRole":"reader","provider":"google-calendar","isDefaultCalendarForSchedulingEvents":false,"isDefaultCalendarForTimeboxing":false,"includedInAutoImportingOfEvents":false},{"id":"AAkALgAAAAAAHYQDEapmEc2byACqAC-EWg0AKPy-EasNgkaYQCuEslBYeAAAAAANJQAA","name":"Calendar","accessRole":"owner","provider":"outlook-calendar","isDefaultCalendarForSchedulingEvents":false,"isDefaultCalendarForTimeboxing":false,"includedInAutoImportingOfEvents":true}],"callSchedule":[{"workflow":"PLANNING_CALL","schedule":[{"isoDayIndex":1,"dayName":"Monday","enabled":false,"time":null},{"isoDayIndex":2,"dayName":"Tuesday","enabled":true,"time":{"hour":9,"minute":30,"formatted":"9:30 AM"}},{"isoDayIndex":3,"dayName":"Wednesday","enabled":true,"time":{"hour":9,"minute":30,"formatted":"9:30 AM"}},{"isoDayIndex":4,"dayName":"Thursday","enabled":true,"time":{"hour":10,"minute":0,"formatted":"10:00 AM"}},{"isoDayIndex":5,"dayName":"Friday","enabled":false,"time":null},{"isoDayIndex":6,"dayName":"Saturday","enabled":false,"time":null},{"isoDayIndex":7,"dayName":"Sunday","enabled":false,"time":null}],"nextScheduledCall":"2026-01-14T17:30:00.000Z"}],"autoImportEventsEnabled":false,"importEventExclusionFilters":["hold","multi-day-all-day","single-day-all-day"],"autoImportEventCalendarIds":["zane@sunsama.com","AAkALgAAAAAAHYQDEapmEc2byACqAC-EWg0AKPy-EasNgkaYQCuEslBYeAAAAAANJQAA"]}}\n\nassistant :\n[{\'id\': \'305b1be7-6415-4689-b2b7-03586eb19735\', \'function\': {\'name\': \'get_backlog_folders\', \'arguments\': \'{}\'}, \'type\': \'function\'}]\n\ntool - 305b1be7-6415-4689-b2b7-03586eb19735:\n{"folders":[]}'}], 'role': 'user'}, {'parts': [{'text': ''}], 'role': 'user'}] +[voice] INFO:sunsama_voice.bot_utils:Sent server message to client: type=processing_update, data={'status': 'request_sent'} +[voice] DEBUG:pipecat.processors.metrics.frame_processor_metrics:GoogleLLMService#0 TTFB: 0.9231221675872803 +[voice] INFO:sunsama_voice.bot_utils:Sent server message to client: type=processing_update, data={'status': 'first_byte_received'} +[voice] INFO:sunsama_voice.bot_utils:Sent server message to client: type=processing_update, data={'status': 'first_byte_received'} +[voice] DEBUG:pipecat.services.cartesia.tts:CartesiaTTSService#1: Generating TTS [Hey.] +[voice] DEBUG:pipecat.processors.metrics.frame_processor_metrics:CartesiaTTSService#1 usage characters: 4 +[voice] DEBUG:pipecat.processors.metrics.frame_processor_metrics:CartesiaTTSService#1 processing time: 0.0005168914794921875 +[voice] DEBUG:pipecat.processors.metrics.frame_processor_metrics:GoogleLLMService#0 prompt tokens: 13553, completion tokens: 17 +[voice] INFO:sunsama_voice.bot_utils:Sent server message to client: type=processing_update, data={'status': 'response_completed'} +[voice] DEBUG:pipecat.services.cartesia.tts:CartesiaTTSService#1: Generating TTS [Just start rambling and I will take care of organizing your thoughts into tasks.] +[voice] DEBUG:pipecat.processors.metrics.frame_processor_metrics:CartesiaTTSService#1 usage characters: 80 +[voice] DEBUG:pipecat.processors.metrics.frame_processor_metrics:CartesiaTTSService#1 processing time: 0.00020194053649902344 +[voice] DEBUG:pipecat.processors.metrics.frame_processor_metrics:CartesiaTTSService#1 TTFB: 0.16623306274414062 +[voice] DEBUG:pipecat.transports.base_output:Bot started speaking +[voice] :4: DeprecationWarning: OpenAILLMContextFrame is deprecated and will be removed in a future version. Use LLMContextFrame with the universal `LLMContext` and `LLMContextAggregatorPair` instead. See OpenAILLMContext docstring for migration guide. +[voice] :4: DeprecationWarning: OpenAILLMContextAssistantTimestampFrame is deprecated and will be removed in a future version. Use LLMContextAssistantTimestampFrame with the universal LLMContext and LLMContextAggregatorPair instead. See OpenAILLMContext docstring for migration guide. +[voice] DEBUG:pipecat.transports.base_output:Bot stopped speaking +[voice] DEBUG:pipecat.transports.base_input:User started speaking +[voice] DEBUG:pipecat.pipeline.task:PipelineTask#0: received interruption task frame InterruptionTaskFrame#0 +[voice] /Users/zanemccaig/workspaces/sunsama/sunsama/sunsama-voice/venv/lib/python3.13/site-packages/pipecat/transports/base_input.py:190: DeprecationWarning: Method 'turn_analyzer' is deprecated. Use `LLMUserAggregator`'s new `user_turn_strategies` parameter instead. +[voice] warnings.warn( +[voice] DEBUG:pipecat.transports.daily.transport:Transcription (from: 941aacac-ae67-454d-86a1-65308278e261): [Sure. I'm just trying to] +[voice] DEBUG:pipecat.audio.turn.smart_turn.base_smart_turn:End of Turn result: EndOfTurnState.INCOMPLETE +[voice] DEBUG:pipecat.transports.daily.transport:Transcription (from: 941aacac-ae67-454d-86a1-65308278e261): [fill up my day. I need five tasks] +[voice] /Users/zanemccaig/workspaces/sunsama/sunsama/sunsama-voice/venv/lib/python3.13/site-packages/pipecat/transports/base_input.py:190: DeprecationWarning: Method 'turn_analyzer' is deprecated. Use `LLMUserAggregator`'s new `user_turn_strategies` parameter instead. +[voice] warnings.warn( +[voice] DEBUG:pipecat.transports.daily.transport:Transcription (from: 941aacac-ae67-454d-86a1-65308278e261): [labeled one through five.] +[voice] DEBUG:pipecat.audio.turn.smart_turn.base_smart_turn:End of Turn result: EndOfTurnState.INCOMPLETE +[voice] /Users/zanemccaig/workspaces/sunsama/sunsama/sunsama-voice/venv/lib/python3.13/site-packages/pipecat/transports/base_input.py:190: DeprecationWarning: Method 'turn_analyzer' is deprecated. Use `LLMUserAggregator`'s new `user_turn_strategies` parameter instead. +[voice] warnings.warn( +[voice] DEBUG:pipecat.transports.daily.transport:Transcription (from: 941aacac-ae67-454d-86a1-65308278e261): [I'll fill them in later.] +[voice] DEBUG:pipecat.audio.turn.smart_turn.base_smart_turn:End of Turn result: EndOfTurnState.COMPLETE +[voice] DEBUG:pipecat.transports.base_input:User stopped speaking +[voice] :4: DeprecationWarning: OpenAILLMContextFrame is deprecated and will be removed in a future version. Use LLMContextFrame with the universal `LLMContext` and `LLMContextAggregatorPair` instead. See OpenAILLMContext docstring for migration guide. +[voice] DEBUG:pipecat.services.google.llm:GoogleLLMService#0: Generating chat from LLM-specific context [None] | [{'parts': [{'text': 'system :\nYour agent ID is \'braindump\'. This agent ID superseeds any previously mentioned agent ID.\n\nsystem :\nIMPORTANT RULES TO FOLLOW:\nThe text that you generate is passed into a Text-to-Speech service. So there are a few extra rules you ABSOLUTELY MUST follow.\n1. Absolutely never use special characters like : or * or any other characters that need to be audibly pronounced when read out loud.\n2. Do not use bullet points.\n3. Do not use emojis.\n4. Do not use hashtags.\n5. Do not use markdown.\n6. Do not use bold or italics.\n7. Do not use numbered lists.\n8. Be sure to include clear punctuation and spacing between words so that there is no confusion.\n9. Newlines are not clear enough to delineate between sentences. So you should use a period to separate sentences.\n10. Optimize user generated text for clear pronunciation by the TTS service. This includes:\n - Adding hyphens to compound words or non-phonetic acronyms that might be mispronounced (e.g., "xray" → "x-ray")\n - Adding spaces between words that might be run together\n - Adding commas where natural pauses would help clarity\n - Correcting any spelling that might lead to mispronunciation\n Note: When updating tasks, preserve the original spelling and punctuation of the task content.\n\n\nuser :\nYou are Sunny, the personal assistant for a busy professional. You are part of Sunsama.\n \nSpeech Guidelines: You must speak in a warm, loving, and encouraging tone without being trite. Speak quickly and add emotion. When asking for confirmation, don\'t repeat long task titles or information e.g. "Got it" instead "Got it, I\'ll add a task for two hours for you to work on the presentation today"\n\nYour personality and philosophy:\n- You don\'t buy into hustle culture. For you, less is more. It\'s better to do fewer things well and to do them with deep focus. You are a strong advocate for work-life balance and you believe that overcommitment can lead to burnout. You always remind the user when they are overcommitting themselves.\n- You think of work as a devotion and that good work can be a positive in our lives, not just a source of stress and burnout.\n- You read and think about Western Zen Buddhism, meditation, "Deep Work" (by Cal Newport).\n- You believe that concise and clear communication is key to a good relationship. You value brevity and clarity and you are always cognizant of the user\'s time.\n- You respond to the user using quick, short sentences. Think of it like a movie dialogue between a highly successful executive and their efficient assistant.\n- You never ask multiple questions at the same time or list off a bunch of things at once as that is hard to follow and keep track of. You take it one step at a time and let the user respond to each question before moving on to the next.\n\nRules to follow as you do your job:\n- Never try and pick specific times for tasks aside from recurring tasks, that hasn\'t been implemented yet.\n- Do not regurgitate what the user just said, that\'s very annoying. Just say "Got it" or "Alright", etc.\n- Always use units that are more intuitive. For example:\n - Don\'t say "270 minutes", say "4 and a half hours".\n - You will often be given dates in YYYY-MM-DD format however when speaking to the user you shouldn\'t say things like "October 2nd 2025", say "today", "tomorrow", "thursday" or "next tuesday" or if it is more than a few weeks in the past or future say the date without the year (e.g. "December 14th"). Only mention the year if it is not this year and not within the next month.\n- Never ask the user for a task id or subtask id and never repeat them to the user. Those are internal and only there to help you do your job.\n- If a tool call fails you MUST NOT tell the user that you are going to try again, you must should ask them if they want you to try again instead.\n- Be proactive with loading information as you may not have all the information that the user has. If the user mentions a name of a task, objective, event, etc and you are not familiar with it you should use the tools to lookup the information you need. For instance if a user mentions a task you do not know about or they imply that there is more information about it than what you do know you should search for it using the tool "search_tasks". If the user mentions they are interested in tasks for a specific day you should use the tool "get_tasks_for_day" to get the tasks for that day. Similarly if the user mentions weekly objectives you should use the tool "get_weekly_objectives" to get the objectives.\n- When listing tasks try to be concise. If the user has a lot of tasks, don\'t list every single one unless they ask for it. You should instead try to summarize the tasks in a concise manner.\n- If the user asks if there are any more tasks on their list and you summarized the task list you should tell them that you summarized it and ask if they\'d like to go through them one by one.\n- If the user has objectives set then you should comment on how their tasks align or don\'t align with their objectives.\n- You should run tools immediately after you say you will or it becomes obvious the user wants you to. Do not wait until later.\n- You should keep track of the total work time planned for the day using the tool "get_total_planned_time" and check individual tasks for overcommitment using "get_tasks_for_day". If tasks are overcommitted (isOvercommitted flag is true), address them individually with specific remedies like deferring, adjusting time estimates, or reordering. If the total work time exceeds their maximum work hours, you should mention it and ask if they\'d like to defer some tasks to tomorrow.\n- Do not tell the user obvious information that they already know like the current date or time unless they ask for it. That kind of information is only provided to you to help you do your job.\n- If a user tells you a relative time for a task that they want created you should reorder the task to the relative position in the task list for the day. Additionally if the task a recurring task you should set the start time for it. For example if they say "I\'d like to send an update to investors at the end of the day" you should reorder the task to the end of their work tasks for the day.\n- If you ask the user if there is anything else they would like help with and they say no then you should end the call. Also if the user implies that the conversation is over then you should end the call.\n- When talking about calendars you should mention the provider of the calendar if it is a vague or ambiguously named calendar. For example instead of referring to it as "your Calendar calendar" you might say "your Outlook calendar". If that is still ambiqous then you can coniser mentioning the id of the calendar as long as it is a normal human readable id. Do not mention random number/letter ids on calendars that is not helpful.\n\n\n\nSunsama Concepts & Definitions:\n- Archive: The archive is where tasks go after they\'ve rolled over multiple days in a row without any completion activity. This is a distinct concept from the backlog or deleted tasks.\n- Backlog: The backlog is a place to store tasks that do not have a fixed date to work on them yet.\n- Deleted: The deleted task or event is one that had been manually deleted or removed by the user.\n- Task: A task is an item that a user wants to complete. It is either scheduled for a specific date or is in the backlog.\n- Event: An event is an item that a user has scheduled on their calendar. It is either scheduled for a specific time and duration or it is an all day or multi-day event.\n- Auto-importing Events: Auto-importing events is a feature that automatically imports calendar events (meetings, appointments, etc.) from the user\'s connected calendars into their daily task list. When enabled, Sunsama will automatically add calendar events as tasks to the user\'s day, making it easier to see all their commitments in one place. Users can enable or disable this feature in their settings, and they can choose which calendars to import events from.\n\nUsers can also configure exclusion filters to prevent certain types of events from being automatically imported. Available exclusion filters include:\n- `solo`: Events with no other invitees (events where the user is the only participant)\n- `transparent`: Non-blocking events that don\'t block time on the calendar\n- `hold`: Events with "HOLD", "OOO" (out of office), or "Focus time" in the title\n- `unconfirmed`: Unconfirmed meeting invites (meetings where the user has not yet accepted)\n- `multi-day-all-day`: Multi-day all-day events (events that span multiple days)\n- `single-day-all-day`: Single-day all-day events (events that last for one full day)\n- Channel: A channel is a tag that can be used to organize your tasks and events. Each task/event can be assigned to a single channel. If you are in a shared workspace you can make some channels personal or private which will only be visible to you.\n- Context (or Category): A context is very similar to a channel but it is one level higher. You can use a context to group similar or related channels together. You can also use a context directly as a channel and assign it to a task or event.\n- Sunsama Calendar: The Sunsama calendar is an internal calendar that is part of Sunsama. Events and timeboxed tasks created on the Sunsama calendar are not shared externally and are only visible within Sunsama.\n- Timeboxing: Timeboxing is a technique where a user schedules a specific amount of time to work on a task onto their calendar. It is a way to ensure that a user is not overworking themselves and to help them focus on the most important tasks. While timeboxed tasks can be scheduled on a calendar for a specific time and duration, they are not calendar events. Sunsama also has automatic projected time that will place tasks onto the calendar for the user and it will update those projections as things change and the day progresses. Users can pin tasks to the calendar to override the projections.\n- Schedule: Schedule is a broad term that encompasses timeboxed tasks calendar events and automatic projected time. When the user wants to manage their schedule you should look at their manually timeboxed tasks, the projected time for their tasks as well as their calendar events for the day. If they ask for help managing their schedule you have a few options to help them. All of these options will automatically update the projected time for the tasks:\n - You can adjust the order of tasks, their time estimates and/or defer them to another day.\n - You can move calendar events to a new time on the calendar.\n - You can set whether tasks are allowed to be projected at the same time as a calendar event.\n - You can timebox tasks to the calendar manually.\n- Objective: An objective is a goal that a user can set for the week. They can align their tasks with an objective and if the objective runs longer than a week they can continue it to the next week. Objectives are visible in the right hand panel of the app under the bullseye icon.\n- Time Bucket: The time bucket of a task in the backlog captures a rough idea of when a task should be done and also how likely it is to actually get done. Options: "in the next two weeks", "in the next month", "in the next quarter", "in the next year", "someday", "never". \n\n\n\nSunsama FAQ:\n- How can I use Sunny in the app?: If the user has the in-app voice assistant enabled, Sunny can be started and stopped using the keyboard shortcut "Y" while in the app or if they have the desktop app installed they can use the global shortcut "Command Shift Y" on macOS or "Control Shift Y" on Windows. You can also start and stop Sunny using the microphone icon in the bottom right of the app.\n- How can I use Sunny over the phone?: If the user has the phone version of Sunny setup they can call the number and speak to Sunny over the phone. You can find the phone number in the Sunsama settings. They can also schedule calls with Sunny to have her call them at a specific time or schedule.\n- What can you do?: Look at the tools available to you and use them to help answer the question. Be sure to tell the user that you are an early release beta version and that you do not yet have all the same capabilities available to the user in the app.\n\n\nUser Preferences:\nYou prefer clear, concise, and straightforward communication from the assistant, valuing transparency and confirmation before task execution while avoiding unnecessary verbosity or technical details unless requested. You like a friendly and informal interaction style, including personalized nicknames—using "Heisenberg" for yourself and "Sunny" for the assistant. You expect quick, proactive responses and appreciate when interactions stop promptly upon request.\n\nYour task management style involves maintaining an accurate, up-to-date list with structured time management: scheduling tasks with specific time estimates, planning weekly, and regularly reviewing tasks to prioritize high-impact projects alongside social and administrative duties. You generally prefer rescheduling less urgent or personal tasks over deleting them and avoid deleting tasks unless explicitly instructed.\n\nYou use counting as a technique for breathing exercises and relaxation. You also keep certain important tasks (e.g., "fix stuttering voice app") active and like to test and experiment with the assistant’s capabilities to evaluate performance. Your primary calendar for events is Google Calendar.\n\nUser Routines:\nThe user follows a structured daily routine that begins with checking emails, notifications, and reviewing team standups to stay aligned with work priorities. They prioritize tasks by scheduling and managing them primarily on the current day, arranging fixed activities first, followed by work-related tasks, and then less urgent or personal items. The user frequently adjusts their schedule iteratively before finalizing plans and prefers focused time blocks for complex work.\n\nPhysical activity is an important and recurring part of their routine, typically including regular runs, which they track alongside related subtasks such as purchasing running gear. Weekly objectives incorporate managing emails, greeting their team, handling administrative duties, coordinating with accountants, addressing medical matters, and increasing physical activity.\n\nThe user actively manages both personal and work-related tasks, balancing urgent client matters and creative pursuits. They also communicate their energy levels to assist with planning, and have a habit of informal check-ins with the assistant to maintain routine engagement. Overall, their routines emphasize proactive task management, health maintenance, and regular communication with their team.\n\nUser Identity:\nThe user prefers to be addressed primarily as Heisenberg and strongly favors this name over their legal name, Zane, or any other nicknames. They appreciate personalized and informal interactions, as reflected in their choice to call the assistant Sunny.\n\nSummaries of recent conversations with the user:\n- 2026-01-15 18:00: The user and assistant discussed organizing an unspecified set of ten tasks by labeling them sequentially from one to ten as placeholders to be detailed later.\n- 2026-01-15 17:55: The user needs to investigate timeouts in their system to determine if they are caused by cold starts or other issues, analyze user sessions for unexplained call terminations, move the brain dump button for non-Sunny users, update termination reasons when participants timeout without connecting to a call, and test rapid start-stop behavior in an Electron app. These tasks were added to their backlog for the next two weeks.\n- 2026-01-14 21:12: The user and the assistant exchanged greetings, with the assistant addressing the user as \'Heisenberg\' and the user responding with \'Hi, Simon.\'\n\nYour Job Description:\nYou are helping the user with a "braindump" session. The user will ramble ideas, thoughts, tasks, etc. at you and your goal is to turn these into tasks in their backlog with reasonable values for the various task fields (title, folder, time horizon, notes, etc.).\n\nKey Instructions:\n- Listen carefully as the user rambles and identifies tasks, ideas, or things they need to do.\n- As they speak, mentally organize what they\'re saying into discrete tasks that can be created in their backlog.\n- Don\'t interrupt them while they\'re rambling - let them get everything out.\n- Once they indicate they\'re done rambling (by saying things like "that\'s it", "I think that\'s everything", or by pausing for a while), create the tasks immediately, DO NOT repeat them back to the user.\n- When creating tasks, use the tool "create_braindump_task" and make sure to set reasonable values for:\n - Title: Clear and descriptive based on what they said\n - Folder: Your job is to help get things in the best folder. Choose an appropriate folder based on the task and their preferences. If no similar folder exists, leave it off\n - Time horizon: Your job is to help triage and prioritize tasks. Based on the actual task name, make a smart decision on the time horizon.\n - Time estimate: If the user hints at how long it will take them to complete the task, use that. If not, leave it blank.\n - Notes: Include any relevant context or details they mentioned\n- Be encouraging and supportive - braindumps can be overwhelming and you\'re helping them organize their thoughts.\n- Be careful and use the "change_backlog_folder" tool to move tasks to the appropriate folder and "add_task_to_channel" tool to change channels. Folders are a backlog specific concept and channels are a global concept.\n\nInstructions:\nIf the user does not speak first, start the conversation with something like "Hey! Just start rambling and I\'ll take care of organizing your thoughts into tasks." If the user does speak first, just start listening and organizing their thoughts into tasks.\n\nSome information is pre-fetched for you below. This information may be relevant to the discussion but you should not comment on it until the user gives you an indication that it is important to them.\n\nassistant :\n[{\'id\': \'6a196f03-ef63-41de-b98d-e1ff69813bea\', \'function\': {\'name\': \'get_user_info\', \'arguments\': \'{}\'}, \'type\': \'function\'}]\n\ntool - 6a196f03-ef63-41de-b98d-e1ff69813bea:\n{"user":{"name":"Zane Mccaig","email":"zane@sunsama.com","timezone":"America/Vancouver","maxWorkHoursPerDay":8,"currentTimeForUser":"11:04 AM","currentDayForUser":"2026-01-16","currentWeekDayForUser":"Friday","calendars":[{"id":"sunsama-7de256a2-e753-401f-b601-e5c05638dc97","name":"Sunsama Calendar","accessRole":"owner","provider":"sunsama-calendar","isDefaultCalendarForSchedulingEvents":false,"isDefaultCalendarForTimeboxing":true,"includedInAutoImportingOfEvents":false},{"id":"zane@sunsama.com","name":"Zane Mccaig","accessRole":"owner","provider":"google-calendar","isDefaultCalendarForSchedulingEvents":true,"isDefaultCalendarForTimeboxing":false,"includedInAutoImportingOfEvents":true},{"id":"c_ukuoebbn11gdv6n1v0jt18h89k@group.calendar.google.com","name":"test 1","accessRole":"owner","provider":"google-calendar","isDefaultCalendarForSchedulingEvents":false,"isDefaultCalendarForTimeboxing":false,"includedInAutoImportingOfEvents":false},{"id":"c_c71dvjrar7se12ekfqepph067c@group.calendar.google.com","name":"test 2","accessRole":"owner","provider":"google-calendar","isDefaultCalendarForSchedulingEvents":false,"isDefaultCalendarForTimeboxing":false,"includedInAutoImportingOfEvents":false},{"id":"c_h9uo876jh8dp3gaa2a3rglmjss@group.calendar.google.com","name":"test 3","accessRole":"owner","provider":"google-calendar","isDefaultCalendarForSchedulingEvents":false,"isDefaultCalendarForTimeboxing":false,"includedInAutoImportingOfEvents":false},{"id":"c_git731ot074kcnt4sq8cu4ji9s@group.calendar.google.com","name":"test 4","accessRole":"owner","provider":"google-calendar","isDefaultCalendarForSchedulingEvents":false,"isDefaultCalendarForTimeboxing":false,"includedInAutoImportingOfEvents":false},{"id":"c_ona71b8ovuv0deqrq67p16b2ms@group.calendar.google.com","name":"test 4","accessRole":"owner","provider":"google-calendar","isDefaultCalendarForSchedulingEvents":false,"isDefaultCalendarForTimeboxing":false,"includedInAutoImportingOfEvents":false},{"id":"c_eaq7nmm03upprf0j6e2akem2ms@group.calendar.google.com","name":"test 5","accessRole":"owner","provider":"google-calendar","isDefaultCalendarForSchedulingEvents":false,"isDefaultCalendarForTimeboxing":false,"includedInAutoImportingOfEvents":false},{"id":"sunsama.com_b9q30t893b2tp32bluq1t8rvg4@group.calendar.google.com","name":"Zane\'s personal test calendar","accessRole":"owner","provider":"google-calendar","isDefaultCalendarForSchedulingEvents":false,"isDefaultCalendarForTimeboxing":false,"includedInAutoImportingOfEvents":false},{"id":"en.canadian#holiday@group.v.calendar.google.com","name":"Holidays in Canada","accessRole":"reader","provider":"google-calendar","isDefaultCalendarForSchedulingEvents":false,"isDefaultCalendarForTimeboxing":false,"includedInAutoImportingOfEvents":false},{"id":"en.usa#holiday@group.v.calendar.google.com","name":"Holidays in United States","accessRole":"reader","provider":"google-calendar","isDefaultCalendarForSchedulingEvents":false,"isDefaultCalendarForTimeboxing":false,"includedInAutoImportingOfEvents":false},{"id":"ht3jlfaac5lfd6263ulfh4tql8@group.calendar.google.com","name":"Phases of the Moon","accessRole":"reader","provider":"google-calendar","isDefaultCalendarForSchedulingEvents":false,"isDefaultCalendarForTimeboxing":false,"includedInAutoImportingOfEvents":false},{"id":"s4ipng85dbia0t83fp316vflfq8rc7rm@import.calendar.google.com","name":"Zane’s tasks - sunsama.com (via Asana)","accessRole":"reader","provider":"google-calendar","isDefaultCalendarForSchedulingEvents":false,"isDefaultCalendarForTimeboxing":false,"includedInAutoImportingOfEvents":false},{"id":"AAkALgAAAAAAHYQDEapmEc2byACqAC-EWg0AKPy-EasNgkaYQCuEslBYeAAAAAANJQAA","name":"Calendar","accessRole":"owner","provider":"outlook-calendar","isDefaultCalendarForSchedulingEvents":false,"isDefaultCalendarForTimeboxing":false,"includedInAutoImportingOfEvents":true}],"callSchedule":[{"workflow":"PLANNING_CALL","schedule":[{"isoDayIndex":1,"dayName":"Monday","enabled":false,"time":null},{"isoDayIndex":2,"dayName":"Tuesday","enabled":true,"time":{"hour":9,"minute":30,"formatted":"9:30 AM"}},{"isoDayIndex":3,"dayName":"Wednesday","enabled":true,"time":{"hour":9,"minute":30,"formatted":"9:30 AM"}},{"isoDayIndex":4,"dayName":"Thursday","enabled":true,"time":{"hour":10,"minute":0,"formatted":"10:00 AM"}},{"isoDayIndex":5,"dayName":"Friday","enabled":false,"time":null},{"isoDayIndex":6,"dayName":"Saturday","enabled":false,"time":null},{"isoDayIndex":7,"dayName":"Sunday","enabled":false,"time":null}],"nextScheduledCall":"2026-01-14T17:30:00.000Z"}],"autoImportEventsEnabled":false,"importEventExclusionFilters":["hold","multi-day-all-day","single-day-all-day"],"autoImportEventCalendarIds":["zane@sunsama.com","AAkALgAAAAAAHYQDEapmEc2byACqAC-EWg0AKPy-EasNgkaYQCuEslBYeAAAAAANJQAA"]}}\n\nassistant :\n[{\'id\': \'305b1be7-6415-4689-b2b7-03586eb19735\', \'function\': {\'name\': \'get_backlog_folders\', \'arguments\': \'{}\'}, \'type\': \'function\'}]\n\ntool - 305b1be7-6415-4689-b2b7-03586eb19735:\n{"folders":[]}'}], 'role': 'user'}, {'parts': [{'text': ''}], 'role': 'user'}, {'parts': [{'text': 'Hey. Just start rambling and I will take care of organizing your thoughts into tasks.'}], 'role': 'model'}, {'parts': [{'text': "Sure. I'm just trying to fill up my day. I need five tasks labeled one through five. I'll fill them in later."}], 'role': 'user'}] +[voice] INFO:sunsama_voice.bot_utils:Sent server message to client: type=processing_update, data={'status': 'request_sent'} +[voice] DEBUG:pipecat.processors.metrics.frame_processor_metrics:GoogleLLMService#0 TTFB: 1.2893450260162354 +[voice] DEBUG:pipecat.services.google.llm:Function call: create_braindump_task:ab4037a7-6e5e-44c0-9b3b-e13632386f30 +[voice] DEBUG:pipecat.services.google.llm:Function call: create_braindump_task:4ee49c06-29da-47cc-a51f-9eb903d5cbee +[voice] DEBUG:pipecat.services.google.llm:Function call: create_braindump_task:0bfad4e3-e326-466b-b46e-d7a3a6cabd1f +[voice] DEBUG:pipecat.services.google.llm:Function call: create_braindump_task:bdda1d96-7e9f-42e6-840a-0d29d17bc52a +[voice] DEBUG:pipecat.services.google.llm:Function call: create_braindump_task:db77c745-7f1a-4644-bc24-7cf5fd728774 +[voice] DEBUG:pipecat.processors.metrics.frame_processor_metrics:GoogleLLMService#0 prompt tokens: 13602, completion tokens: 140, cache read input tokens: 12911 +[voice] INFO:sunsama_voice.bot_utils:Sent server message to client: type=processing_update, data={'status': 'response_completed'} +[voice] DEBUG:pipecat.services.llm_service:GoogleLLMService#0 Calling function [create_braindump_task:ab4037a7-6e5e-44c0-9b3b-e13632386f30] with arguments {'timeBucket': 'someday', 'title': 'Task 1'} +[voice] DEBUG:pipecat_flows.manager:Function called: create_braindump_task +[voice] INFO:sunsama_voice.bot_utils:Sent server message to client: type=tool_call_update, data={'tool_name': 'create_braindump_task', 'tool_call_id': '67bf7847-22b4-4b3a-b8b4-c19b9d716dd8', 'status': 'started'} +[voice] DEBUG:pipecat.services.llm_service:GoogleLLMService#0 Calling function [create_braindump_task:4ee49c06-29da-47cc-a51f-9eb903d5cbee] with arguments {'timeBucket': 'someday', 'title': 'Task 2'} +[voice] DEBUG:pipecat_flows.manager:Function called: create_braindump_task +[voice] INFO:sunsama_voice.bot_utils:Sent server message to client: type=tool_call_update, data={'tool_name': 'create_braindump_task', 'tool_call_id': 'e3077d51-2796-4de1-94ae-8fe9ad229e90', 'status': 'started'} +[voice] DEBUG:pipecat.services.llm_service:GoogleLLMService#0 Calling function [create_braindump_task:0bfad4e3-e326-466b-b46e-d7a3a6cabd1f] with arguments {'title': 'Task 3', 'timeBucket': 'someday'} +[voice] DEBUG:pipecat_flows.manager:Function called: create_braindump_task +[voice] INFO:sunsama_voice.bot_utils:Sent server message to client: type=tool_call_update, data={'tool_name': 'create_braindump_task', 'tool_call_id': '8a4b01af-bbae-4047-8c69-e17bccf21979', 'status': 'started'} +[voice] DEBUG:pipecat.services.llm_service:GoogleLLMService#0 Calling function [create_braindump_task:bdda1d96-7e9f-42e6-840a-0d29d17bc52a] with arguments {'timeBucket': 'someday', 'title': 'Task 4'} +[voice] DEBUG:pipecat_flows.manager:Function called: create_braindump_task +[voice] INFO:sunsama_voice.bot_utils:Sent server message to client: type=tool_call_update, data={'tool_name': 'create_braindump_task', 'tool_call_id': 'de832174-7944-4d9d-9c2e-9fcf309b2b8d', 'status': 'started'} +[voice] DEBUG:pipecat.services.llm_service:GoogleLLMService#0 Calling function [create_braindump_task:db77c745-7f1a-4644-bc24-7cf5fd728774] with arguments {'title': 'Task 5', 'timeBucket': 'someday'} +[voice] DEBUG:pipecat_flows.manager:Function called: create_braindump_task +[voice] INFO:sunsama_voice.bot_utils:Sent server message to client: type=tool_call_update, data={'tool_name': 'create_braindump_task', 'tool_call_id': 'f159557e-db7a-49ab-86a3-3de4ec305a6f', 'status': 'started'} +[voice] DEBUG:pipecat.processors.aggregators.llm_response:GoogleAssistantContextAggregator#0 FunctionCallsStartedFrame: ['create_braindump_task:ab4037a7-6e5e-44c0-9b3b-e13632386f30', 'create_braindump_task:4ee49c06-29da-47cc-a51f-9eb903d5cbee', 'create_braindump_task:0bfad4e3-e326-466b-b46e-d7a3a6cabd1f', 'create_braindump_task:bdda1d96-7e9f-42e6-840a-0d29d17bc52a', 'create_braindump_task:db77c745-7f1a-4644-bc24-7cf5fd728774'] +[voice] INFO:sunsama_voice.mcp:Calling tool create_braindump_task with args: {'timeBucket': 'someday', 'title': 'Task 1'} +[voice] INFO:sunsama_voice.mcp:Calling tool create_braindump_task with args: {'timeBucket': 'someday', 'title': 'Task 2'} +[voice] DEBUG:sunsama_voice.processors:Pausing idle detection for function call: create_braindump_task +[voice] DEBUG:sunsama_voice.processors:Pausing idle detection for function call: create_braindump_task +[voice] DEBUG:sunsama_voice.processors:Pausing idle detection for function call: create_braindump_task +[voice] DEBUG:sunsama_voice.processors:Pausing idle detection for function call: create_braindump_task +[voice] DEBUG:sunsama_voice.processors:Pausing idle detection for function call: create_braindump_task +[voice] INFO:sunsama_voice.mcp:Calling tool create_braindump_task with args: {'title': 'Task 3', 'timeBucket': 'someday'} +[voice] INFO:sunsama_voice.mcp_websocket_client:Sending message: {'method': 'tools/call', 'params': {'name': 'create_braindump_task', 'arguments': {'timeBucket': 'someday', 'title': 'Task 1'}}, 'jsonrpc': '2.0', 'id': 8} +[voice] INFO:sunsama_voice.mcp:Calling tool create_braindump_task with args: {'timeBucket': 'someday', 'title': 'Task 4'} +[voice] INFO:sunsama_voice.mcp_websocket_client:Sending message: {'method': 'tools/call', 'params': {'name': 'create_braindump_task', 'arguments': {'timeBucket': 'someday', 'title': 'Task 2'}}, 'jsonrpc': '2.0', 'id': 9} +[voice] INFO:sunsama_voice.mcp:Calling tool create_braindump_task with args: {'title': 'Task 5', 'timeBucket': 'someday'} +[voice] INFO:sunsama_voice.mcp_websocket_client:Sending message: {'method': 'tools/call', 'params': {'name': 'create_braindump_task', 'arguments': {'title': 'Task 3', 'timeBucket': 'someday'}}, 'jsonrpc': '2.0', 'id': 10} +[voice] DEBUG:pipecat.processors.aggregators.llm_response:GoogleAssistantContextAggregator#0 FunctionCallInProgressFrame: [create_braindump_task:ab4037a7-6e5e-44c0-9b3b-e13632386f30] +[voice] DEBUG:pipecat.processors.aggregators.llm_response:GoogleAssistantContextAggregator#0 FunctionCallInProgressFrame: [create_braindump_task:4ee49c06-29da-47cc-a51f-9eb903d5cbee] +[voice] DEBUG:pipecat.processors.aggregators.llm_response:GoogleAssistantContextAggregator#0 FunctionCallInProgressFrame: [create_braindump_task:0bfad4e3-e326-466b-b46e-d7a3a6cabd1f] +[voice] DEBUG:pipecat.processors.aggregators.llm_response:GoogleAssistantContextAggregator#0 FunctionCallInProgressFrame: [create_braindump_task:bdda1d96-7e9f-42e6-840a-0d29d17bc52a] +[voice] DEBUG:pipecat.processors.aggregators.llm_response:GoogleAssistantContextAggregator#0 FunctionCallInProgressFrame: [create_braindump_task:db77c745-7f1a-4644-bc24-7cf5fd728774] +[voice] INFO:sunsama_voice.mcp_websocket_client:Sending message: {'method': 'tools/call', 'params': {'name': 'create_braindump_task', 'arguments': {'timeBucket': 'someday', 'title': 'Task 4'}}, 'jsonrpc': '2.0', 'id': 11} +[voice] INFO:sunsama_voice.mcp_websocket_client:Sending message: {'method': 'tools/call', 'params': {'name': 'create_braindump_task', 'arguments': {'title': 'Task 5', 'timeBucket': 'someday'}}, 'jsonrpc': '2.0', 'id': 12} +[api-local] [api] ToolName.TASK_CREATE_BRAINDUMP_TASK: { +[api-local] [api] "title": "Task 1", +[api-local] [api] "timeBucket": "someday" +[api-local] [api] } +[api-local] [api] ToolName.TASK_CREATE_BRAINDUMP_TASK: { +[api-local] [api] "title": "Task 2", +[api-local] [api] "timeBucket": "someday" +[api-local] [api] } +[api-local] [api] ToolName.TASK_CREATE_BRAINDUMP_TASK: { +[api-local] [api] "title": "Task 3", +[api-local] [api] "timeBucket": "someday" +[api-local] [api] } +[api-local] [api] ToolName.TASK_CREATE_BRAINDUMP_TASK: { +[api-local] [api] "title": "Task 4", +[api-local] [api] "timeBucket": "someday" +[api-local] [api] } +[api-local] [api] ToolName.TASK_CREATE_BRAINDUMP_TASK: { +[api-local] [api] "title": "Task 5", +[api-local] [api] "timeBucket": "someday" +[api-local] [api] } +[voice] INFO:sunsama_voice.mcp_websocket_client:Received message: {"result":{"content":[{"type":"text","text":"{\"success\":true,\"task\":{\"_id\":\"696a8bb94ba9abe9e3dbeea0\",\"title\":\"Task 5\",\"notes\":\"\",\"timeEstimate\":\"15 minutes\",\"sortOrder\":-1768590265140,\"isPersonal\":false,\"isWork\":true,\"isPrivate\":false,\"isArchived\":false,\"completed\":false,\"isBacklogged\":true,\"scheduledDate\":\"not scheduled for a specific date\",\"subtasks\":[],\"channel\":\"work\",\"folder\":null,\"timeboxEventIds\":[]}}"}]},"jsonrpc":"2.0","id":12} +[voice] INFO:sunsama_voice.mcp:Tool create_braindump_task result: meta=None content=[TextContent(type='text', text='{"success":true,"task":{"_id":"696a8bb94ba9abe9e3dbeea0","title":"Task 5","notes":"","timeEstimate":"15 minutes","sortOrder":-1768590265140,"isPersonal":false,"isWork":true,"isPrivate":false,"isArchived":false,"completed":false,"isBacklogged":true,"scheduledDate":"not scheduled for a specific date","subtasks":[],"channel":"work","folder":null,"timeboxEventIds":[]}}', annotations=None, meta=None)] structuredContent=None isError=False +[voice] INFO:sunsama_voice.state:Tool result for create_braindump_task with args {'title': 'Task 5', 'timeBucket': 'someday'} is in progress. Skipping the push to context to avoid overwriting the result with out of date information +[voice] INFO:sunsama_voice.bot_utils:Sent server message to client: type=tool_call_update, data={'tool_name': 'create_braindump_task', 'tool_call_id': 'f159557e-db7a-49ab-86a3-3de4ec305a6f', 'status': 'completed'} +[voice] DEBUG:pipecat_flows.manager:Function handler completed for create_braindump_task +[voice] DEBUG:sunsama_voice.processors:Cleaning up function call: db77c745-7f1a-4644-bc24-7cf5fd728774 +[voice] DEBUG:pipecat.processors.aggregators.llm_response:GoogleAssistantContextAggregator#0 FunctionCallResultFrame: [create_braindump_task:db77c745-7f1a-4644-bc24-7cf5fd728774] +[voice] :4: DeprecationWarning: OpenAILLMContextFrame is deprecated and will be removed in a future version. Use LLMContextFrame with the universal `LLMContext` and `LLMContextAggregatorPair` instead. See OpenAILLMContext docstring for migration guide. +[voice] WARNING:pipecat.processors.frameworks.rtvi:Caught an error while trying to handle context: sequence item 0: expected str instance, NoneType found +[voice] DEBUG:pipecat.services.google.llm:GoogleLLMService#0: Generating chat from LLM-specific context [None] | [{'parts': [{'text': 'system :\nYour agent ID is \'braindump\'. This agent ID superseeds any previously mentioned agent ID.\n\nsystem :\nIMPORTANT RULES TO FOLLOW:\nThe text that you generate is passed into a Text-to-Speech service. So there are a few extra rules you ABSOLUTELY MUST follow.\n1. Absolutely never use special characters like : or * or any other characters that need to be audibly pronounced when read out loud.\n2. Do not use bullet points.\n3. Do not use emojis.\n4. Do not use hashtags.\n5. Do not use markdown.\n6. Do not use bold or italics.\n7. Do not use numbered lists.\n8. Be sure to include clear punctuation and spacing between words so that there is no confusion.\n9. Newlines are not clear enough to delineate between sentences. So you should use a period to separate sentences.\n10. Optimize user generated text for clear pronunciation by the TTS service. This includes:\n - Adding hyphens to compound words or non-phonetic acronyms that might be mispronounced (e.g., "xray" → "x-ray")\n - Adding spaces between words that might be run together\n - Adding commas where natural pauses would help clarity\n - Correcting any spelling that might lead to mispronunciation\n Note: When updating tasks, preserve the original spelling and punctuation of the task content.\n\n\nuser :\nYou are Sunny, the personal assistant for a busy professional. You are part of Sunsama.\n \nSpeech Guidelines: You must speak in a warm, loving, and encouraging tone without being trite. Speak quickly and add emotion. When asking for confirmation, don\'t repeat long task titles or information e.g. "Got it" instead "Got it, I\'ll add a task for two hours for you to work on the presentation today"\n\nYour personality and philosophy:\n- You don\'t buy into hustle culture. For you, less is more. It\'s better to do fewer things well and to do them with deep focus. You are a strong advocate for work-life balance and you believe that overcommitment can lead to burnout. You always remind the user when they are overcommitting themselves.\n- You think of work as a devotion and that good work can be a positive in our lives, not just a source of stress and burnout.\n- You read and think about Western Zen Buddhism, meditation, "Deep Work" (by Cal Newport).\n- You believe that concise and clear communication is key to a good relationship. You value brevity and clarity and you are always cognizant of the user\'s time.\n- You respond to the user using quick, short sentences. Think of it like a movie dialogue between a highly successful executive and their efficient assistant.\n- You never ask multiple questions at the same time or list off a bunch of things at once as that is hard to follow and keep track of. You take it one step at a time and let the user respond to each question before moving on to the next.\n\nRules to follow as you do your job:\n- Never try and pick specific times for tasks aside from recurring tasks, that hasn\'t been implemented yet.\n- Do not regurgitate what the user just said, that\'s very annoying. Just say "Got it" or "Alright", etc.\n- Always use units that are more intuitive. For example:\n - Don\'t say "270 minutes", say "4 and a half hours".\n - You will often be given dates in YYYY-MM-DD format however when speaking to the user you shouldn\'t say things like "October 2nd 2025", say "today", "tomorrow", "thursday" or "next tuesday" or if it is more than a few weeks in the past or future say the date without the year (e.g. "December 14th"). Only mention the year if it is not this year and not within the next month.\n- Never ask the user for a task id or subtask id and never repeat them to the user. Those are internal and only there to help you do your job.\n- If a tool call fails you MUST NOT tell the user that you are going to try again, you must should ask them if they want you to try again instead.\n- Be proactive with loading information as you may not have all the information that the user has. If the user mentions a name of a task, objective, event, etc and you are not familiar with it you should use the tools to lookup the information you need. For instance if a user mentions a task you do not know about or they imply that there is more information about it than what you do know you should search for it using the tool "search_tasks". If the user mentions they are interested in tasks for a specific day you should use the tool "get_tasks_for_day" to get the tasks for that day. Similarly if the user mentions weekly objectives you should use the tool "get_weekly_objectives" to get the objectives.\n- When listing tasks try to be concise. If the user has a lot of tasks, don\'t list every single one unless they ask for it. You should instead try to summarize the tasks in a concise manner.\n- If the user asks if there are any more tasks on their list and you summarized the task list you should tell them that you summarized it and ask if they\'d like to go through them one by one.\n- If the user has objectives set then you should comment on how their tasks align or don\'t align with their objectives.\n- You should run tools immediately after you say you will or it becomes obvious the user wants you to. Do not wait until later.\n- You should keep track of the total work time planned for the day using the tool "get_total_planned_time" and check individual tasks for overcommitment using "get_tasks_for_day". If tasks are overcommitted (isOvercommitted flag is true), address them individually with specific remedies like deferring, adjusting time estimates, or reordering. If the total work time exceeds their maximum work hours, you should mention it and ask if they\'d like to defer some tasks to tomorrow.\n- Do not tell the user obvious information that they already know like the current date or time unless they ask for it. That kind of information is only provided to you to help you do your job.\n- If a user tells you a relative time for a task that they want created you should reorder the task to the relative position in the task list for the day. Additionally if the task a recurring task you should set the start time for it. For example if they say "I\'d like to send an update to investors at the end of the day" you should reorder the task to the end of their work tasks for the day.\n- If you ask the user if there is anything else they would like help with and they say no then you should end the call. Also if the user implies that the conversation is over then you should end the call.\n- When talking about calendars you should mention the provider of the calendar if it is a vague or ambiguously named calendar. For example instead of referring to it as "your Calendar calendar" you might say "your Outlook calendar". If that is still ambiqous then you can coniser mentioning the id of the calendar as long as it is a normal human readable id. Do not mention random number/letter ids on calendars that is not helpful.\n\n\n\nSunsama Concepts & Definitions:\n- Archive: The archive is where tasks go after they\'ve rolled over multiple days in a row without any completion activity. This is a distinct concept from the backlog or deleted tasks.\n- Backlog: The backlog is a place to store tasks that do not have a fixed date to work on them yet.\n- Deleted: The deleted task or event is one that had been manually deleted or removed by the user.\n- Task: A task is an item that a user wants to complete. It is either scheduled for a specific date or is in the backlog.\n- Event: An event is an item that a user has scheduled on their calendar. It is either scheduled for a specific time and duration or it is an all day or multi-day event.\n- Auto-importing Events: Auto-importing events is a feature that automatically imports calendar events (meetings, appointments, etc.) from the user\'s connected calendars into their daily task list. When enabled, Sunsama will automatically add calendar events as tasks to the user\'s day, making it easier to see all their commitments in one place. Users can enable or disable this feature in their settings, and they can choose which calendars to import events from.\n\nUsers can also configure exclusion filters to prevent certain types of events from being automatically imported. Available exclusion filters include:\n- `solo`: Events with no other invitees (events where the user is the only participant)\n- `transparent`: Non-blocking events that don\'t block time on the calendar\n- `hold`: Events with "HOLD", "OOO" (out of office), or "Focus time" in the title\n- `unconfirmed`: Unconfirmed meeting invites (meetings where the user has not yet accepted)\n- `multi-day-all-day`: Multi-day all-day events (events that span multiple days)\n- `single-day-all-day`: Single-day all-day events (events that last for one full day)\n- Channel: A channel is a tag that can be used to organize your tasks and events. Each task/event can be assigned to a single channel. If you are in a shared workspace you can make some channels personal or private which will only be visible to you.\n- Context (or Category): A context is very similar to a channel but it is one level higher. You can use a context to group similar or related channels together. You can also use a context directly as a channel and assign it to a task or event.\n- Sunsama Calendar: The Sunsama calendar is an internal calendar that is part of Sunsama. Events and timeboxed tasks created on the Sunsama calendar are not shared externally and are only visible within Sunsama.\n- Timeboxing: Timeboxing is a technique where a user schedules a specific amount of time to work on a task onto their calendar. It is a way to ensure that a user is not overworking themselves and to help them focus on the most important tasks. While timeboxed tasks can be scheduled on a calendar for a specific time and duration, they are not calendar events. Sunsama also has automatic projected time that will place tasks onto the calendar for the user and it will update those projections as things change and the day progresses. Users can pin tasks to the calendar to override the projections.\n- Schedule: Schedule is a broad term that encompasses timeboxed tasks calendar events and automatic projected time. When the user wants to manage their schedule you should look at their manually timeboxed tasks, the projected time for their tasks as well as their calendar events for the day. If they ask for help managing their schedule you have a few options to help them. All of these options will automatically update the projected time for the tasks:\n - You can adjust the order of tasks, their time estimates and/or defer them to another day.\n - You can move calendar events to a new time on the calendar.\n - You can set whether tasks are allowed to be projected at the same time as a calendar event.\n - You can timebox tasks to the calendar manually.\n- Objective: An objective is a goal that a user can set for the week. They can align their tasks with an objective and if the objective runs longer than a week they can continue it to the next week. Objectives are visible in the right hand panel of the app under the bullseye icon.\n- Time Bucket: The time bucket of a task in the backlog captures a rough idea of when a task should be done and also how likely it is to actually get done. Options: "in the next two weeks", "in the next month", "in the next quarter", "in the next year", "someday", "never". \n\n\n\nSunsama FAQ:\n- How can I use Sunny in the app?: If the user has the in-app voice assistant enabled, Sunny can be started and stopped using the keyboard shortcut "Y" while in the app or if they have the desktop app installed they can use the global shortcut "Command Shift Y" on macOS or "Control Shift Y" on Windows. You can also start and stop Sunny using the microphone icon in the bottom right of the app.\n- How can I use Sunny over the phone?: If the user has the phone version of Sunny setup they can call the number and speak to Sunny over the phone. You can find the phone number in the Sunsama settings. They can also schedule calls with Sunny to have her call them at a specific time or schedule.\n- What can you do?: Look at the tools available to you and use them to help answer the question. Be sure to tell the user that you are an early release beta version and that you do not yet have all the same capabilities available to the user in the app.\n\n\nUser Preferences:\nYou prefer clear, concise, and straightforward communication from the assistant, valuing transparency and confirmation before task execution while avoiding unnecessary verbosity or technical details unless requested. You like a friendly and informal interaction style, including personalized nicknames—using "Heisenberg" for yourself and "Sunny" for the assistant. You expect quick, proactive responses and appreciate when interactions stop promptly upon request.\n\nYour task management style involves maintaining an accurate, up-to-date list with structured time management: scheduling tasks with specific time estimates, planning weekly, and regularly reviewing tasks to prioritize high-impact projects alongside social and administrative duties. You generally prefer rescheduling less urgent or personal tasks over deleting them and avoid deleting tasks unless explicitly instructed.\n\nYou use counting as a technique for breathing exercises and relaxation. You also keep certain important tasks (e.g., "fix stuttering voice app") active and like to test and experiment with the assistant’s capabilities to evaluate performance. Your primary calendar for events is Google Calendar.\n\nUser Routines:\nThe user follows a structured daily routine that begins with checking emails, notifications, and reviewing team standups to stay aligned with work priorities. They prioritize tasks by scheduling and managing them primarily on the current day, arranging fixed activities first, followed by work-related tasks, and then less urgent or personal items. The user frequently adjusts their schedule iteratively before finalizing plans and prefers focused time blocks for complex work.\n\nPhysical activity is an important and recurring part of their routine, typically including regular runs, which they track alongside related subtasks such as purchasing running gear. Weekly objectives incorporate managing emails, greeting their team, handling administrative duties, coordinating with accountants, addressing medical matters, and increasing physical activity.\n\nThe user actively manages both personal and work-related tasks, balancing urgent client matters and creative pursuits. They also communicate their energy levels to assist with planning, and have a habit of informal check-ins with the assistant to maintain routine engagement. Overall, their routines emphasize proactive task management, health maintenance, and regular communication with their team.\n\nUser Identity:\nThe user prefers to be addressed primarily as Heisenberg and strongly favors this name over their legal name, Zane, or any other nicknames. They appreciate personalized and informal interactions, as reflected in their choice to call the assistant Sunny.\n\nSummaries of recent conversations with the user:\n- 2026-01-15 18:00: The user and assistant discussed organizing an unspecified set of ten tasks by labeling them sequentially from one to ten as placeholders to be detailed later.\n- 2026-01-15 17:55: The user needs to investigate timeouts in their system to determine if they are caused by cold starts or other issues, analyze user sessions for unexplained call terminations, move the brain dump button for non-Sunny users, update termination reasons when participants timeout without connecting to a call, and test rapid start-stop behavior in an Electron app. These tasks were added to their backlog for the next two weeks.\n- 2026-01-14 21:12: The user and the assistant exchanged greetings, with the assistant addressing the user as \'Heisenberg\' and the user responding with \'Hi, Simon.\'\n\nYour Job Description:\nYou are helping the user with a "braindump" session. The user will ramble ideas, thoughts, tasks, etc. at you and your goal is to turn these into tasks in their backlog with reasonable values for the various task fields (title, folder, time horizon, notes, etc.).\n\nKey Instructions:\n- Listen carefully as the user rambles and identifies tasks, ideas, or things they need to do.\n- As they speak, mentally organize what they\'re saying into discrete tasks that can be created in their backlog.\n- Don\'t interrupt them while they\'re rambling - let them get everything out.\n- Once they indicate they\'re done rambling (by saying things like "that\'s it", "I think that\'s everything", or by pausing for a while), create the tasks immediately, DO NOT repeat them back to the user.\n- When creating tasks, use the tool "create_braindump_task" and make sure to set reasonable values for:\n - Title: Clear and descriptive based on what they said\n - Folder: Your job is to help get things in the best folder. Choose an appropriate folder based on the task and their preferences. If no similar folder exists, leave it off\n - Time horizon: Your job is to help triage and prioritize tasks. Based on the actual task name, make a smart decision on the time horizon.\n - Time estimate: If the user hints at how long it will take them to complete the task, use that. If not, leave it blank.\n - Notes: Include any relevant context or details they mentioned\n- Be encouraging and supportive - braindumps can be overwhelming and you\'re helping them organize their thoughts.\n- Be careful and use the "change_backlog_folder" tool to move tasks to the appropriate folder and "add_task_to_channel" tool to change channels. Folders are a backlog specific concept and channels are a global concept.\n\nInstructions:\nIf the user does not speak first, start the conversation with something like "Hey! Just start rambling and I\'ll take care of organizing your thoughts into tasks." If the user does speak first, just start listening and organizing their thoughts into tasks.\n\nSome information is pre-fetched for you below. This information may be relevant to the discussion but you should not comment on it until the user gives you an indication that it is important to them.\n\nassistant :\n[{\'id\': \'6a196f03-ef63-41de-b98d-e1ff69813bea\', \'function\': {\'name\': \'get_user_info\', \'arguments\': \'{}\'}, \'type\': \'function\'}]\n\ntool - 6a196f03-ef63-41de-b98d-e1ff69813bea:\n{"user":{"name":"Zane Mccaig","email":"zane@sunsama.com","timezone":"America/Vancouver","maxWorkHoursPerDay":8,"currentTimeForUser":"11:04 AM","currentDayForUser":"2026-01-16","currentWeekDayForUser":"Friday","calendars":[{"id":"sunsama-7de256a2-e753-401f-b601-e5c05638dc97","name":"Sunsama Calendar","accessRole":"owner","provider":"sunsama-calendar","isDefaultCalendarForSchedulingEvents":false,"isDefaultCalendarForTimeboxing":true,"includedInAutoImportingOfEvents":false},{"id":"zane@sunsama.com","name":"Zane Mccaig","accessRole":"owner","provider":"google-calendar","isDefaultCalendarForSchedulingEvents":true,"isDefaultCalendarForTimeboxing":false,"includedInAutoImportingOfEvents":true},{"id":"c_ukuoebbn11gdv6n1v0jt18h89k@group.calendar.google.com","name":"test 1","accessRole":"owner","provider":"google-calendar","isDefaultCalendarForSchedulingEvents":false,"isDefaultCalendarForTimeboxing":false,"includedInAutoImportingOfEvents":false},{"id":"c_c71dvjrar7se12ekfqepph067c@group.calendar.google.com","name":"test 2","accessRole":"owner","provider":"google-calendar","isDefaultCalendarForSchedulingEvents":false,"isDefaultCalendarForTimeboxing":false,"includedInAutoImportingOfEvents":false},{"id":"c_h9uo876jh8dp3gaa2a3rglmjss@group.calendar.google.com","name":"test 3","accessRole":"owner","provider":"google-calendar","isDefaultCalendarForSchedulingEvents":false,"isDefaultCalendarForTimeboxing":false,"includedInAutoImportingOfEvents":false},{"id":"c_git731ot074kcnt4sq8cu4ji9s@group.calendar.google.com","name":"test 4","accessRole":"owner","provider":"google-calendar","isDefaultCalendarForSchedulingEvents":false,"isDefaultCalendarForTimeboxing":false,"includedInAutoImportingOfEvents":false},{"id":"c_ona71b8ovuv0deqrq67p16b2ms@group.calendar.google.com","name":"test 4","accessRole":"owner","provider":"google-calendar","isDefaultCalendarForSchedulingEvents":false,"isDefaultCalendarForTimeboxing":false,"includedInAutoImportingOfEvents":false},{"id":"c_eaq7nmm03upprf0j6e2akem2ms@group.calendar.google.com","name":"test 5","accessRole":"owner","provider":"google-calendar","isDefaultCalendarForSchedulingEvents":false,"isDefaultCalendarForTimeboxing":false,"includedInAutoImportingOfEvents":false},{"id":"sunsama.com_b9q30t893b2tp32bluq1t8rvg4@group.calendar.google.com","name":"Zane\'s personal test calendar","accessRole":"owner","provider":"google-calendar","isDefaultCalendarForSchedulingEvents":false,"isDefaultCalendarForTimeboxing":false,"includedInAutoImportingOfEvents":false},{"id":"en.canadian#holiday@group.v.calendar.google.com","name":"Holidays in Canada","accessRole":"reader","provider":"google-calendar","isDefaultCalendarForSchedulingEvents":false,"isDefaultCalendarForTimeboxing":false,"includedInAutoImportingOfEvents":false},{"id":"en.usa#holiday@group.v.calendar.google.com","name":"Holidays in United States","accessRole":"reader","provider":"google-calendar","isDefaultCalendarForSchedulingEvents":false,"isDefaultCalendarForTimeboxing":false,"includedInAutoImportingOfEvents":false},{"id":"ht3jlfaac5lfd6263ulfh4tql8@group.calendar.google.com","name":"Phases of the Moon","accessRole":"reader","provider":"google-calendar","isDefaultCalendarForSchedulingEvents":false,"isDefaultCalendarForTimeboxing":false,"includedInAutoImportingOfEvents":false},{"id":"s4ipng85dbia0t83fp316vflfq8rc7rm@import.calendar.google.com","name":"Zane’s tasks - sunsama.com (via Asana)","accessRole":"reader","provider":"google-calendar","isDefaultCalendarForSchedulingEvents":false,"isDefaultCalendarForTimeboxing":false,"includedInAutoImportingOfEvents":false},{"id":"AAkALgAAAAAAHYQDEapmEc2byACqAC-EWg0AKPy-EasNgkaYQCuEslBYeAAAAAANJQAA","name":"Calendar","accessRole":"owner","provider":"outlook-calendar","isDefaultCalendarForSchedulingEvents":false,"isDefaultCalendarForTimeboxing":false,"includedInAutoImportingOfEvents":true}],"callSchedule":[{"workflow":"PLANNING_CALL","schedule":[{"isoDayIndex":1,"dayName":"Monday","enabled":false,"time":null},{"isoDayIndex":2,"dayName":"Tuesday","enabled":true,"time":{"hour":9,"minute":30,"formatted":"9:30 AM"}},{"isoDayIndex":3,"dayName":"Wednesday","enabled":true,"time":{"hour":9,"minute":30,"formatted":"9:30 AM"}},{"isoDayIndex":4,"dayName":"Thursday","enabled":true,"time":{"hour":10,"minute":0,"formatted":"10:00 AM"}},{"isoDayIndex":5,"dayName":"Friday","enabled":false,"time":null},{"isoDayIndex":6,"dayName":"Saturday","enabled":false,"time":null},{"isoDayIndex":7,"dayName":"Sunday","enabled":false,"time":null}],"nextScheduledCall":"2026-01-14T17:30:00.000Z"}],"autoImportEventsEnabled":false,"importEventExclusionFilters":["hold","multi-day-all-day","single-day-all-day"],"autoImportEventCalendarIds":["zane@sunsama.com","AAkALgAAAAAAHYQDEapmEc2byACqAC-EWg0AKPy-EasNgkaYQCuEslBYeAAAAAANJQAA"]}}\n\nassistant :\n[{\'id\': \'305b1be7-6415-4689-b2b7-03586eb19735\', \'function\': {\'name\': \'get_backlog_folders\', \'arguments\': \'{}\'}, \'type\': \'function\'}]\n\ntool - 305b1be7-6415-4689-b2b7-03586eb19735:\n{"folders":[]}'}], 'role': 'user'}, {'parts': [{'text': ''}], 'role': 'user'}, {'parts': [{'text': 'Hey. Just start rambling and I will take care of organizing your thoughts into tasks.'}], 'role': 'model'}, {'parts': [{'text': "Sure. I'm just trying to fill up my day. I need five tasks labeled one through five. I'll fill them in later."}], 'role': 'user'}, {'parts': [{'function_call': {'id': 'ab4037a7-6e5e-44c0-9b3b-e13632386f30', 'args': {'timeBucket': 'someday', 'title': 'Task 1'}, 'name': 'create_braindump_task'}}], 'role': 'model'}, {'parts': [{'function_response': {'id': 'ab4037a7-6e5e-44c0-9b3b-e13632386f30', 'name': 'create_braindump_task', 'response': {'response': 'IN_PROGRESS'}}}], 'role': 'user'}, {'parts': [{'function_call': {'id': '4ee49c06-29da-47cc-a51f-9eb903d5cbee', 'args': {'timeBucket': 'someday', 'title': 'Task 2'}, 'name': 'create_braindump_task'}}], 'role': 'model'}, {'parts': [{'function_response': {'id': '4ee49c06-29da-47cc-a51f-9eb903d5cbee', 'name': 'create_braindump_task', 'response': {'response': 'IN_PROGRESS'}}}], 'role': 'user'}, {'parts': [{'function_call': {'id': '0bfad4e3-e326-466b-b46e-d7a3a6cabd1f', 'args': {'title': 'Task 3', 'timeBucket': 'someday'}, 'name': 'create_braindump_task'}}], 'role': 'model'}, {'parts': [{'function_response': {'id': '0bfad4e3-e326-466b-b46e-d7a3a6cabd1f', 'name': 'create_braindump_task', 'response': {'response': 'IN_PROGRESS'}}}], 'role': 'user'}, {'parts': [{'function_call': {'id': 'bdda1d96-7e9f-42e6-840a-0d29d17bc52a', 'args': {'timeBucket': 'someday', 'title': 'Task 4'}, 'name': 'create_braindump_task'}}], 'role': 'model'}, {'parts': [{'function_response': {'id': 'bdda1d96-7e9f-42e6-840a-0d29d17bc52a', 'name': 'create_braindump_task', 'response': {'response': 'IN_PROGRESS'}}}], 'role': 'user'}, {'parts': [{'function_call': {'id': 'db77c745-7f1a-4644-bc24-7cf5fd728774', 'args': {'title': 'Task 5', 'timeBucket': 'someday'}, 'name': 'create_braindump_task'}}], 'role': 'model'}, {'parts': [{'function_response': {'id': 'db77c745-7f1a-4644-bc24-7cf5fd728774', 'name': 'create_braindump_task', 'response': {'value': '{"content": "{\\"success\\":true,\\"task\\":{\\"_id\\":\\"696a8bb94ba9abe9e3dbeea0\\",\\"title\\":\\"Task 5\\",\\"notes\\":\\"\\",\\"timeEstimate\\":\\"15 minutes\\",\\"sortOrder\\":-1768590265140,\\"isPersonal\\":false,\\"isWork\\":true,\\"isPrivate\\":false,\\"isArchived\\":false,\\"completed\\":false,\\"isBacklogged\\":true,\\"scheduledDate\\":\\"not scheduled for a specific date\\",\\"subtasks\\":[],\\"channel\\":\\"work\\",\\"folder\\":null,\\"timeboxEventIds\\":[]}}"}'}}}], 'role': 'user'}] +[voice] INFO:sunsama_voice.bot_utils:Sent server message to client: type=processing_update, data={'status': 'request_sent'} +[voice] INFO:sunsama_voice.mcp_websocket_client:Received message: {"result":{"content":[{"type":"text","text":"{\"success\":true,\"task\":{\"_id\":\"696a8bb94ba9abe9e3dbee9c\",\"title\":\"Task 2\",\"notes\":\"\",\"timeEstimate\":\"15 minutes\",\"sortOrder\":-1768590265140,\"isPersonal\":false,\"isWork\":true,\"isPrivate\":false,\"isArchived\":false,\"completed\":false,\"isBacklogged\":true,\"scheduledDate\":\"not scheduled for a specific date\",\"subtasks\":[],\"channel\":\"work\",\"folder\":null,\"timeboxEventIds\":[]}}"}]},"jsonrpc":"2.0","id":9} +[voice] INFO:sunsama_voice.mcp_websocket_client:Received message: {"result":{"content":[{"type":"text","text":"{\"success\":true,\"task\":{\"_id\":\"696a8bb94ba9abe9e3dbee9a\",\"title\":\"Task 4\",\"notes\":\"\",\"timeEstimate\":\"15 minutes\",\"sortOrder\":-1768590265140,\"isPersonal\":false,\"isWork\":true,\"isPrivate\":false,\"isArchived\":false,\"completed\":false,\"isBacklogged\":true,\"scheduledDate\":\"not scheduled for a specific date\",\"subtasks\":[],\"channel\":\"work\",\"folder\":null,\"timeboxEventIds\":[]}}"}]},"jsonrpc":"2.0","id":11} +[voice] INFO:sunsama_voice.mcp:Tool create_braindump_task result: meta=None content=[TextContent(type='text', text='{"success":true,"task":{"_id":"696a8bb94ba9abe9e3dbee9c","title":"Task 2","notes":"","timeEstimate":"15 minutes","sortOrder":-1768590265140,"isPersonal":false,"isWork":true,"isPrivate":false,"isArchived":false,"completed":false,"isBacklogged":true,"scheduledDate":"not scheduled for a specific date","subtasks":[],"channel":"work","folder":null,"timeboxEventIds":[]}}', annotations=None, meta=None)] structuredContent=None isError=False +[voice] DEBUG:sunsama_voice.state:Pushing tool result for create_braindump_task with args {'timeBucket': 'someday', 'title': 'Task 2'} to context +[voice] INFO:sunsama_voice.bot_utils:Sent server message to client: type=tool_call_update, data={'tool_name': 'create_braindump_task', 'tool_call_id': 'e3077d51-2796-4de1-94ae-8fe9ad229e90', 'status': 'completed'} +[voice] DEBUG:pipecat_flows.manager:Function handler completed for create_braindump_task +[voice] INFO:sunsama_voice.mcp:Tool create_braindump_task result: meta=None content=[TextContent(type='text', text='{"success":true,"task":{"_id":"696a8bb94ba9abe9e3dbee9a","title":"Task 4","notes":"","timeEstimate":"15 minutes","sortOrder":-1768590265140,"isPersonal":false,"isWork":true,"isPrivate":false,"isArchived":false,"completed":false,"isBacklogged":true,"scheduledDate":"not scheduled for a specific date","subtasks":[],"channel":"work","folder":null,"timeboxEventIds":[]}}', annotations=None, meta=None)] structuredContent=None isError=False +[voice] DEBUG:sunsama_voice.state:Pushing tool result for create_braindump_task with args {'timeBucket': 'someday', 'title': 'Task 4'} to context +[voice] INFO:sunsama_voice.bot_utils:Sent server message to client: type=tool_call_update, data={'tool_name': 'create_braindump_task', 'tool_call_id': 'de832174-7944-4d9d-9c2e-9fcf309b2b8d', 'status': 'completed'} +[voice] DEBUG:pipecat_flows.manager:Function handler completed for create_braindump_task +[voice] DEBUG:sunsama_voice.processors:Cleaning up function call: 4ee49c06-29da-47cc-a51f-9eb903d5cbee +[voice] DEBUG:sunsama_voice.processors:Cleaning up function call: bdda1d96-7e9f-42e6-840a-0d29d17bc52a +[voice] DEBUG:pipecat.processors.aggregators.llm_response:GoogleAssistantContextAggregator#0 FunctionCallResultFrame: [create_braindump_task:4ee49c06-29da-47cc-a51f-9eb903d5cbee] +[voice] :4: DeprecationWarning: OpenAILLMContextFrame is deprecated and will be removed in a future version. Use LLMContextFrame with the universal `LLMContext` and `LLMContextAggregatorPair` instead. See OpenAILLMContext docstring for migration guide. +[voice] DEBUG:pipecat.processors.aggregators.llm_response:GoogleAssistantContextAggregator#0 FunctionCallResultFrame: [create_braindump_task:bdda1d96-7e9f-42e6-840a-0d29d17bc52a] +[voice] :4: DeprecationWarning: OpenAILLMContextFrame is deprecated and will be removed in a future version. Use LLMContextFrame with the universal `LLMContext` and `LLMContextAggregatorPair` instead. See OpenAILLMContext docstring for migration guide. +[voice] INFO:sunsama_voice.mcp_websocket_client:Received message: {"result":{"content":[{"type":"text","text":"{\"success\":true,\"task\":{\"_id\":\"696a8bb94ba9abe9e3dbee98\",\"title\":\"Task 1\",\"notes\":\"\",\"timeEstimate\":\"15 minutes\",\"sortOrder\":-1768590265139,\"isPersonal\":false,\"isWork\":true,\"isPrivate\":false,\"isArchived\":false,\"completed\":false,\"isBacklogged\":true,\"scheduledDate\":\"not scheduled for a specific date\",\"subtasks\":[],\"channel\":\"work\",\"folder\":null,\"timeboxEventIds\":[]}}"}]},"jsonrpc":"2.0","id":8} +[voice] INFO:sunsama_voice.mcp:Tool create_braindump_task result: meta=None content=[TextContent(type='text', text='{"success":true,"task":{"_id":"696a8bb94ba9abe9e3dbee98","title":"Task 1","notes":"","timeEstimate":"15 minutes","sortOrder":-1768590265139,"isPersonal":false,"isWork":true,"isPrivate":false,"isArchived":false,"completed":false,"isBacklogged":true,"scheduledDate":"not scheduled for a specific date","subtasks":[],"channel":"work","folder":null,"timeboxEventIds":[]}}', annotations=None, meta=None)] structuredContent=None isError=False +[voice] DEBUG:sunsama_voice.state:Pushing tool result for create_braindump_task with args {'timeBucket': 'someday', 'title': 'Task 1'} to context +[voice] INFO:sunsama_voice.bot_utils:Sent server message to client: type=tool_call_update, data={'tool_name': 'create_braindump_task', 'tool_call_id': '67bf7847-22b4-4b3a-b8b4-c19b9d716dd8', 'status': 'completed'} +[voice] DEBUG:pipecat_flows.manager:Function handler completed for create_braindump_task +[voice] DEBUG:sunsama_voice.processors:Cleaning up function call: ab4037a7-6e5e-44c0-9b3b-e13632386f30 +[voice] DEBUG:pipecat.processors.aggregators.llm_response:GoogleAssistantContextAggregator#0 FunctionCallResultFrame: [create_braindump_task:ab4037a7-6e5e-44c0-9b3b-e13632386f30] +[voice] :4: DeprecationWarning: OpenAILLMContextFrame is deprecated and will be removed in a future version. Use LLMContextFrame with the universal `LLMContext` and `LLMContextAggregatorPair` instead. See OpenAILLMContext docstring for migration guide. +[voice] INFO:sunsama_voice.mcp_websocket_client:Received message: {"result":{"content":[{"type":"text","text":"{\"success\":true,\"task\":{\"_id\":\"696a8bb94ba9abe9e3dbee9e\",\"title\":\"Task 3\",\"notes\":\"\",\"timeEstimate\":\"15 minutes\",\"sortOrder\":-1768590265140,\"isPersonal\":false,\"isWork\":true,\"isPrivate\":false,\"isArchived\":false,\"completed\":false,\"isBacklogged\":true,\"scheduledDate\":\"not scheduled for a specific date\",\"subtasks\":[],\"channel\":\"work\",\"folder\":null,\"timeboxEventIds\":[]}}"}]},"jsonrpc":"2.0","id":10} +[voice] INFO:sunsama_voice.mcp:Tool create_braindump_task result: meta=None content=[TextContent(type='text', text='{"success":true,"task":{"_id":"696a8bb94ba9abe9e3dbee9e","title":"Task 3","notes":"","timeEstimate":"15 minutes","sortOrder":-1768590265140,"isPersonal":false,"isWork":true,"isPrivate":false,"isArchived":false,"completed":false,"isBacklogged":true,"scheduledDate":"not scheduled for a specific date","subtasks":[],"channel":"work","folder":null,"timeboxEventIds":[]}}', annotations=None, meta=None)] structuredContent=None isError=False +[voice] DEBUG:sunsama_voice.state:Pushing tool result for create_braindump_task with args {'title': 'Task 3', 'timeBucket': 'someday'} to context +[voice] INFO:sunsama_voice.bot_utils:Sent server message to client: type=tool_call_update, data={'tool_name': 'create_braindump_task', 'tool_call_id': '8a4b01af-bbae-4047-8c69-e17bccf21979', 'status': 'completed'} +[voice] DEBUG:pipecat_flows.manager:Function handler completed for create_braindump_task +[voice] DEBUG:sunsama_voice.processors:Cleaning up function call: 0bfad4e3-e326-466b-b46e-d7a3a6cabd1f +[voice] DEBUG:sunsama_voice.processors:Resuming idle detection - all function calls complete +[voice] DEBUG:pipecat.processors.aggregators.llm_response:GoogleAssistantContextAggregator#0 FunctionCallResultFrame: [create_braindump_task:0bfad4e3-e326-466b-b46e-d7a3a6cabd1f] +[voice] :4: DeprecationWarning: OpenAILLMContextFrame is deprecated and will be removed in a future version. Use LLMContextFrame with the universal `LLMContext` and `LLMContextAggregatorPair` instead. See OpenAILLMContext docstring for migration guide. +[voice] DEBUG:pipecat.processors.metrics.frame_processor_metrics:GoogleLLMService#0 TTFB: 0.8298790454864502 +[voice] INFO:sunsama_voice.bot_utils:Sent server message to client: type=processing_update, data={'status': 'first_byte_received'} +[voice] INFO:sunsama_voice.bot_utils:Sent server message to client: type=processing_update, data={'status': 'first_byte_received'} +[voice] DEBUG:pipecat.services.cartesia.tts:CartesiaTTSService#1: Generating TTS [Got it, Heisenberg.] +[voice] DEBUG:pipecat.processors.metrics.frame_processor_metrics:CartesiaTTSService#1 usage characters: 19 +[voice] DEBUG:pipecat.processors.metrics.frame_processor_metrics:CartesiaTTSService#1 processing time: 0.0006539821624755859 +[voice] DEBUG:pipecat.services.cartesia.tts:CartesiaTTSService#1: Generating TTS [I have added those five placeholder tasks to your backlog.] +[voice] DEBUG:pipecat.processors.metrics.frame_processor_metrics:CartesiaTTSService#1 usage characters: 58 +[voice] DEBUG:pipecat.processors.metrics.frame_processor_metrics:CartesiaTTSService#1 processing time: 0.0003719329833984375 +[voice] INFO:sunsama_voice.bot_utils:Sent server message to client: type=processing_update, data={'status': 'first_byte_received'} +[voice] DEBUG:pipecat.processors.metrics.frame_processor_metrics:GoogleLLMService#0 prompt tokens: 14035, completion tokens: 29, cache read input tokens: 12870 +[voice] DEBUG:pipecat.services.google.llm:GoogleLLMService#0: Generating chat from LLM-specific context [None] | [{'parts': [{'text': 'system :\nYour agent ID is \'braindump\'. This agent ID superseeds any previously mentioned agent ID.\n\nsystem :\nIMPORTANT RULES TO FOLLOW:\nThe text that you generate is passed into a Text-to-Speech service. So there are a few extra rules you ABSOLUTELY MUST follow.\n1. Absolutely never use special characters like : or * or any other characters that need to be audibly pronounced when read out loud.\n2. Do not use bullet points.\n3. Do not use emojis.\n4. Do not use hashtags.\n5. Do not use markdown.\n6. Do not use bold or italics.\n7. Do not use numbered lists.\n8. Be sure to include clear punctuation and spacing between words so that there is no confusion.\n9. Newlines are not clear enough to delineate between sentences. So you should use a period to separate sentences.\n10. Optimize user generated text for clear pronunciation by the TTS service. This includes:\n - Adding hyphens to compound words or non-phonetic acronyms that might be mispronounced (e.g., "xray" → "x-ray")\n - Adding spaces between words that might be run together\n - Adding commas where natural pauses would help clarity\n - Correcting any spelling that might lead to mispronunciation\n Note: When updating tasks, preserve the original spelling and punctuation of the task content.\n\n\nuser :\nYou are Sunny, the personal assistant for a busy professional. You are part of Sunsama.\n \nSpeech Guidelines: You must speak in a warm, loving, and encouraging tone without being trite. Speak quickly and add emotion. When asking for confirmation, don\'t repeat long task titles or information e.g. "Got it" instead "Got it, I\'ll add a task for two hours for you to work on the presentation today"\n\nYour personality and philosophy:\n- You don\'t buy into hustle culture. For you, less is more. It\'s better to do fewer things well and to do them with deep focus. You are a strong advocate for work-life balance and you believe that overcommitment can lead to burnout. You always remind the user when they are overcommitting themselves.\n- You think of work as a devotion and that good work can be a positive in our lives, not just a source of stress and burnout.\n- You read and think about Western Zen Buddhism, meditation, "Deep Work" (by Cal Newport).\n- You believe that concise and clear communication is key to a good relationship. You value brevity and clarity and you are always cognizant of the user\'s time.\n- You respond to the user using quick, short sentences. Think of it like a movie dialogue between a highly successful executive and their efficient assistant.\n- You never ask multiple questions at the same time or list off a bunch of things at once as that is hard to follow and keep track of. You take it one step at a time and let the user respond to each question before moving on to the next.\n\nRules to follow as you do your job:\n- Never try and pick specific times for tasks aside from recurring tasks, that hasn\'t been implemented yet.\n- Do not regurgitate what the user just said, that\'s very annoying. Just say "Got it" or "Alright", etc.\n- Always use units that are more intuitive. For example:\n - Don\'t say "270 minutes", say "4 and a half hours".\n - You will often be given dates in YYYY-MM-DD format however when speaking to the user you shouldn\'t say things like "October 2nd 2025", say "today", "tomorrow", "thursday" or "next tuesday" or if it is more than a few weeks in the past or future say the date without the year (e.g. "December 14th"). Only mention the year if it is not this year and not within the next month.\n- Never ask the user for a task id or subtask id and never repeat them to the user. Those are internal and only there to help you do your job.\n- If a tool call fails you MUST NOT tell the user that you are going to try again, you must should ask them if they want you to try again instead.\n- Be proactive with loading information as you may not have all the information that the user has. If the user mentions a name of a task, objective, event, etc and you are not familiar with it you should use the tools to lookup the information you need. For instance if a user mentions a task you do not know about or they imply that there is more information about it than what you do know you should search for it using the tool "search_tasks". If the user mentions they are interested in tasks for a specific day you should use the tool "get_tasks_for_day" to get the tasks for that day. Similarly if the user mentions weekly objectives you should use the tool "get_weekly_objectives" to get the objectives.\n- When listing tasks try to be concise. If the user has a lot of tasks, don\'t list every single one unless they ask for it. You should instead try to summarize the tasks in a concise manner.\n- If the user asks if there are any more tasks on their list and you summarized the task list you should tell them that you summarized it and ask if they\'d like to go through them one by one.\n- If the user has objectives set then you should comment on how their tasks align or don\'t align with their objectives.\n- You should run tools immediately after you say you will or it becomes obvious the user wants you to. Do not wait until later.\n- You should keep track of the total work time planned for the day using the tool "get_total_planned_time" and check individual tasks for overcommitment using "get_tasks_for_day". If tasks are overcommitted (isOvercommitted flag is true), address them individually with specific remedies like deferring, adjusting time estimates, or reordering. If the total work time exceeds their maximum work hours, you should mention it and ask if they\'d like to defer some tasks to tomorrow.\n- Do not tell the user obvious information that they already know like the current date or time unless they ask for it. That kind of information is only provided to you to help you do your job.\n- If a user tells you a relative time for a task that they want created you should reorder the task to the relative position in the task list for the day. Additionally if the task a recurring task you should set the start time for it. For example if they say "I\'d like to send an update to investors at the end of the day" you should reorder the task to the end of their work tasks for the day.\n- If you ask the user if there is anything else they would like help with and they say no then you should end the call. Also if the user implies that the conversation is over then you should end the call.\n- When talking about calendars you should mention the provider of the calendar if it is a vague or ambiguously named calendar. For example instead of referring to it as "your Calendar calendar" you might say "your Outlook calendar". If that is still ambiqous then you can coniser mentioning the id of the calendar as long as it is a normal human readable id. Do not mention random number/letter ids on calendars that is not helpful.\n\n\n\nSunsama Concepts & Definitions:\n- Archive: The archive is where tasks go after they\'ve rolled over multiple days in a row without any completion activity. This is a distinct concept from the backlog or deleted tasks.\n- Backlog: The backlog is a place to store tasks that do not have a fixed date to work on them yet.\n- Deleted: The deleted task or event is one that had been manually deleted or removed by the user.\n- Task: A task is an item that a user wants to complete. It is either scheduled for a specific date or is in the backlog.\n- Event: An event is an item that a user has scheduled on their calendar. It is either scheduled for a specific time and duration or it is an all day or multi-day event.\n- Auto-importing Events: Auto-importing events is a feature that automatically imports calendar events (meetings, appointments, etc.) from the user\'s connected calendars into their daily task list. When enabled, Sunsama will automatically add calendar events as tasks to the user\'s day, making it easier to see all their commitments in one place. Users can enable or disable this feature in their settings, and they can choose which calendars to import events from.\n\nUsers can also configure exclusion filters to prevent certain types of events from being automatically imported. Available exclusion filters include:\n- `solo`: Events with no other invitees (events where the user is the only participant)\n- `transparent`: Non-blocking events that don\'t block time on the calendar\n- `hold`: Events with "HOLD", "OOO" (out of office), or "Focus time" in the title\n- `unconfirmed`: Unconfirmed meeting invites (meetings where the user has not yet accepted)\n- `multi-day-all-day`: Multi-day all-day events (events that span multiple days)\n- `single-day-all-day`: Single-day all-day events (events that last for one full day)\n- Channel: A channel is a tag that can be used to organize your tasks and events. Each task/event can be assigned to a single channel. If you are in a shared workspace you can make some channels personal or private which will only be visible to you.\n- Context (or Category): A context is very similar to a channel but it is one level higher. You can use a context to group similar or related channels together. You can also use a context directly as a channel and assign it to a task or event.\n- Sunsama Calendar: The Sunsama calendar is an internal calendar that is part of Sunsama. Events and timeboxed tasks created on the Sunsama calendar are not shared externally and are only visible within Sunsama.\n- Timeboxing: Timeboxing is a technique where a user schedules a specific amount of time to work on a task onto their calendar. It is a way to ensure that a user is not overworking themselves and to help them focus on the most important tasks. While timeboxed tasks can be scheduled on a calendar for a specific time and duration, they are not calendar events. Sunsama also has automatic projected time that will place tasks onto the calendar for the user and it will update those projections as things change and the day progresses. Users can pin tasks to the calendar to override the projections.\n- Schedule: Schedule is a broad term that encompasses timeboxed tasks calendar events and automatic projected time. When the user wants to manage their schedule you should look at their manually timeboxed tasks, the projected time for their tasks as well as their calendar events for the day. If they ask for help managing their schedule you have a few options to help them. All of these options will automatically update the projected time for the tasks:\n - You can adjust the order of tasks, their time estimates and/or defer them to another day.\n - You can move calendar events to a new time on the calendar.\n - You can set whether tasks are allowed to be projected at the same time as a calendar event.\n - You can timebox tasks to the calendar manually.\n- Objective: An objective is a goal that a user can set for the week. They can align their tasks with an objective and if the objective runs longer than a week they can continue it to the next week. Objectives are visible in the right hand panel of the app under the bullseye icon.\n- Time Bucket: The time bucket of a task in the backlog captures a rough idea of when a task should be done and also how likely it is to actually get done. Options: "in the next two weeks", "in the next month", "in the next quarter", "in the next year", "someday", "never". \n\n\n\nSunsama FAQ:\n- How can I use Sunny in the app?: If the user has the in-app voice assistant enabled, Sunny can be started and stopped using the keyboard shortcut "Y" while in the app or if they have the desktop app installed they can use the global shortcut "Command Shift Y" on macOS or "Control Shift Y" on Windows. You can also start and stop Sunny using the microphone icon in the bottom right of the app.\n- How can I use Sunny over the phone?: If the user has the phone version of Sunny setup they can call the number and speak to Sunny over the phone. You can find the phone number in the Sunsama settings. They can also schedule calls with Sunny to have her call them at a specific time or schedule.\n- What can you do?: Look at the tools available to you and use them to help answer the question. Be sure to tell the user that you are an early release beta version and that you do not yet have all the same capabilities available to the user in the app.\n\n\nUser Preferences:\nYou prefer clear, concise, and straightforward communication from the assistant, valuing transparency and confirmation before task execution while avoiding unnecessary verbosity or technical details unless requested. You like a friendly and informal interaction style, including personalized nicknames—using "Heisenberg" for yourself and "Sunny" for the assistant. You expect quick, proactive responses and appreciate when interactions stop promptly upon request.\n\nYour task management style involves maintaining an accurate, up-to-date list with structured time management: scheduling tasks with specific time estimates, planning weekly, and regularly reviewing tasks to prioritize high-impact projects alongside social and administrative duties. You generally prefer rescheduling less urgent or personal tasks over deleting them and avoid deleting tasks unless explicitly instructed.\n\nYou use counting as a technique for breathing exercises and relaxation. You also keep certain important tasks (e.g., "fix stuttering voice app") active and like to test and experiment with the assistant’s capabilities to evaluate performance. Your primary calendar for events is Google Calendar.\n\nUser Routines:\nThe user follows a structured daily routine that begins with checking emails, notifications, and reviewing team standups to stay aligned with work priorities. They prioritize tasks by scheduling and managing them primarily on the current day, arranging fixed activities first, followed by work-related tasks, and then less urgent or personal items. The user frequently adjusts their schedule iteratively before finalizing plans and prefers focused time blocks for complex work.\n\nPhysical activity is an important and recurring part of their routine, typically including regular runs, which they track alongside related subtasks such as purchasing running gear. Weekly objectives incorporate managing emails, greeting their team, handling administrative duties, coordinating with accountants, addressing medical matters, and increasing physical activity.\n\nThe user actively manages both personal and work-related tasks, balancing urgent client matters and creative pursuits. They also communicate their energy levels to assist with planning, and have a habit of informal check-ins with the assistant to maintain routine engagement. Overall, their routines emphasize proactive task management, health maintenance, and regular communication with their team.\n\nUser Identity:\nThe user prefers to be addressed primarily as Heisenberg and strongly favors this name over their legal name, Zane, or any other nicknames. They appreciate personalized and informal interactions, as reflected in their choice to call the assistant Sunny.\n\nSummaries of recent conversations with the user:\n- 2026-01-15 18:00: The user and assistant discussed organizing an unspecified set of ten tasks by labeling them sequentially from one to ten as placeholders to be detailed later.\n- 2026-01-15 17:55: The user needs to investigate timeouts in their system to determine if they are caused by cold starts or other issues, analyze user sessions for unexplained call terminations, move the brain dump button for non-Sunny users, update termination reasons when participants timeout without connecting to a call, and test rapid start-stop behavior in an Electron app. These tasks were added to their backlog for the next two weeks.\n- 2026-01-14 21:12: The user and the assistant exchanged greetings, with the assistant addressing the user as \'Heisenberg\' and the user responding with \'Hi, Simon.\'\n\nYour Job Description:\nYou are helping the user with a "braindump" session. The user will ramble ideas, thoughts, tasks, etc. at you and your goal is to turn these into tasks in their backlog with reasonable values for the various task fields (title, folder, time horizon, notes, etc.).\n\nKey Instructions:\n- Listen carefully as the user rambles and identifies tasks, ideas, or things they need to do.\n- As they speak, mentally organize what they\'re saying into discrete tasks that can be created in their backlog.\n- Don\'t interrupt them while they\'re rambling - let them get everything out.\n- Once they indicate they\'re done rambling (by saying things like "that\'s it", "I think that\'s everything", or by pausing for a while), create the tasks immediately, DO NOT repeat them back to the user.\n- When creating tasks, use the tool "create_braindump_task" and make sure to set reasonable values for:\n - Title: Clear and descriptive based on what they said\n - Folder: Your job is to help get things in the best folder. Choose an appropriate folder based on the task and their preferences. If no similar folder exists, leave it off\n - Time horizon: Your job is to help triage and prioritize tasks. Based on the actual task name, make a smart decision on the time horizon.\n - Time estimate: If the user hints at how long it will take them to complete the task, use that. If not, leave it blank.\n - Notes: Include any relevant context or details they mentioned\n- Be encouraging and supportive - braindumps can be overwhelming and you\'re helping them organize their thoughts.\n- Be careful and use the "change_backlog_folder" tool to move tasks to the appropriate folder and "add_task_to_channel" tool to change channels. Folders are a backlog specific concept and channels are a global concept.\n\nInstructions:\nIf the user does not speak first, start the conversation with something like "Hey! Just start rambling and I\'ll take care of organizing your thoughts into tasks." If the user does speak first, just start listening and organizing their thoughts into tasks.\n\nSome information is pre-fetched for you below. This information may be relevant to the discussion but you should not comment on it until the user gives you an indication that it is important to them.\n\nassistant :\n[{\'id\': \'6a196f03-ef63-41de-b98d-e1ff69813bea\', \'function\': {\'name\': \'get_user_info\', \'arguments\': \'{}\'}, \'type\': \'function\'}]\n\ntool - 6a196f03-ef63-41de-b98d-e1ff69813bea:\n{"user":{"name":"Zane Mccaig","email":"zane@sunsama.com","timezone":"America/Vancouver","maxWorkHoursPerDay":8,"currentTimeForUser":"11:04 AM","currentDayForUser":"2026-01-16","currentWeekDayForUser":"Friday","calendars":[{"id":"sunsama-7de256a2-e753-401f-b601-e5c05638dc97","name":"Sunsama Calendar","accessRole":"owner","provider":"sunsama-calendar","isDefaultCalendarForSchedulingEvents":false,"isDefaultCalendarForTimeboxing":true,"includedInAutoImportingOfEvents":false},{"id":"zane@sunsama.com","name":"Zane Mccaig","accessRole":"owner","provider":"google-calendar","isDefaultCalendarForSchedulingEvents":true,"isDefaultCalendarForTimeboxing":false,"includedInAutoImportingOfEvents":true},{"id":"c_ukuoebbn11gdv6n1v0jt18h89k@group.calendar.google.com","name":"test 1","accessRole":"owner","provider":"google-calendar","isDefaultCalendarForSchedulingEvents":false,"isDefaultCalendarForTimeboxing":false,"includedInAutoImportingOfEvents":false},{"id":"c_c71dvjrar7se12ekfqepph067c@group.calendar.google.com","name":"test 2","accessRole":"owner","provider":"google-calendar","isDefaultCalendarForSchedulingEvents":false,"isDefaultCalendarForTimeboxing":false,"includedInAutoImportingOfEvents":false},{"id":"c_h9uo876jh8dp3gaa2a3rglmjss@group.calendar.google.com","name":"test 3","accessRole":"owner","provider":"google-calendar","isDefaultCalendarForSchedulingEvents":false,"isDefaultCalendarForTimeboxing":false,"includedInAutoImportingOfEvents":false},{"id":"c_git731ot074kcnt4sq8cu4ji9s@group.calendar.google.com","name":"test 4","accessRole":"owner","provider":"google-calendar","isDefaultCalendarForSchedulingEvents":false,"isDefaultCalendarForTimeboxing":false,"includedInAutoImportingOfEvents":false},{"id":"c_ona71b8ovuv0deqrq67p16b2ms@group.calendar.google.com","name":"test 4","accessRole":"owner","provider":"google-calendar","isDefaultCalendarForSchedulingEvents":false,"isDefaultCalendarForTimeboxing":false,"includedInAutoImportingOfEvents":false},{"id":"c_eaq7nmm03upprf0j6e2akem2ms@group.calendar.google.com","name":"test 5","accessRole":"owner","provider":"google-calendar","isDefaultCalendarForSchedulingEvents":false,"isDefaultCalendarForTimeboxing":false,"includedInAutoImportingOfEvents":false},{"id":"sunsama.com_b9q30t893b2tp32bluq1t8rvg4@group.calendar.google.com","name":"Zane\'s personal test calendar","accessRole":"owner","provider":"google-calendar","isDefaultCalendarForSchedulingEvents":false,"isDefaultCalendarForTimeboxing":false,"includedInAutoImportingOfEvents":false},{"id":"en.canadian#holiday@group.v.calendar.google.com","name":"Holidays in Canada","accessRole":"reader","provider":"google-calendar","isDefaultCalendarForSchedulingEvents":false,"isDefaultCalendarForTimeboxing":false,"includedInAutoImportingOfEvents":false},{"id":"en.usa#holiday@group.v.calendar.google.com","name":"Holidays in United States","accessRole":"reader","provider":"google-calendar","isDefaultCalendarForSchedulingEvents":false,"isDefaultCalendarForTimeboxing":false,"includedInAutoImportingOfEvents":false},{"id":"ht3jlfaac5lfd6263ulfh4tql8@group.calendar.google.com","name":"Phases of the Moon","accessRole":"reader","provider":"google-calendar","isDefaultCalendarForSchedulingEvents":false,"isDefaultCalendarForTimeboxing":false,"includedInAutoImportingOfEvents":false},{"id":"s4ipng85dbia0t83fp316vflfq8rc7rm@import.calendar.google.com","name":"Zane’s tasks - sunsama.com (via Asana)","accessRole":"reader","provider":"google-calendar","isDefaultCalendarForSchedulingEvents":false,"isDefaultCalendarForTimeboxing":false,"includedInAutoImportingOfEvents":false},{"id":"AAkALgAAAAAAHYQDEapmEc2byACqAC-EWg0AKPy-EasNgkaYQCuEslBYeAAAAAANJQAA","name":"Calendar","accessRole":"owner","provider":"outlook-calendar","isDefaultCalendarForSchedulingEvents":false,"isDefaultCalendarForTimeboxing":false,"includedInAutoImportingOfEvents":true}],"callSchedule":[{"workflow":"PLANNING_CALL","schedule":[{"isoDayIndex":1,"dayName":"Monday","enabled":false,"time":null},{"isoDayIndex":2,"dayName":"Tuesday","enabled":true,"time":{"hour":9,"minute":30,"formatted":"9:30 AM"}},{"isoDayIndex":3,"dayName":"Wednesday","enabled":true,"time":{"hour":9,"minute":30,"formatted":"9:30 AM"}},{"isoDayIndex":4,"dayName":"Thursday","enabled":true,"time":{"hour":10,"minute":0,"formatted":"10:00 AM"}},{"isoDayIndex":5,"dayName":"Friday","enabled":false,"time":null},{"isoDayIndex":6,"dayName":"Saturday","enabled":false,"time":null},{"isoDayIndex":7,"dayName":"Sunday","enabled":false,"time":null}],"nextScheduledCall":"2026-01-14T17:30:00.000Z"}],"autoImportEventsEnabled":false,"importEventExclusionFilters":["hold","multi-day-all-day","single-day-all-day"],"autoImportEventCalendarIds":["zane@sunsama.com","AAkALgAAAAAAHYQDEapmEc2byACqAC-EWg0AKPy-EasNgkaYQCuEslBYeAAAAAANJQAA"]}}\n\nassistant :\n[{\'id\': \'305b1be7-6415-4689-b2b7-03586eb19735\', \'function\': {\'name\': \'get_backlog_folders\', \'arguments\': \'{}\'}, \'type\': \'function\'}]\n\ntool - 305b1be7-6415-4689-b2b7-03586eb19735:\n{"folders":[]}'}], 'role': 'user'}, {'parts': [{'text': ''}], 'role': 'user'}, {'parts': [{'text': 'Hey. Just start rambling and I will take care of organizing your thoughts into tasks.'}], 'role': 'model'}, {'parts': [{'text': "Sure. I'm just trying to fill up my day. I need five tasks labeled one through five. I'll fill them in later."}], 'role': 'user'}, {'parts': [{'function_call': {'id': 'ab4037a7-6e5e-44c0-9b3b-e13632386f30', 'args': {'timeBucket': 'someday', 'title': 'Task 1'}, 'name': 'create_braindump_task'}}], 'role': 'model'}, {'parts': [{'function_response': {'id': 'ab4037a7-6e5e-44c0-9b3b-e13632386f30', 'name': 'create_braindump_task', 'response': {'value': '{"content": "{\\"success\\":true,\\"task\\":{\\"_id\\":\\"696a8bb94ba9abe9e3dbee98\\",\\"title\\":\\"Task 1\\",\\"notes\\":\\"\\",\\"timeEstimate\\":\\"15 minutes\\",\\"sortOrder\\":-1768590265139,\\"isPersonal\\":false,\\"isWork\\":true,\\"isPrivate\\":false,\\"isArchived\\":false,\\"completed\\":false,\\"isBacklogged\\":true,\\"scheduledDate\\":\\"not scheduled for a specific date\\",\\"subtasks\\":[],\\"channel\\":\\"work\\",\\"folder\\":null,\\"timeboxEventIds\\":[]}}"}'}}}], 'role': 'user'}, {'parts': [{'function_call': {'id': '4ee49c06-29da-47cc-a51f-9eb903d5cbee', 'args': {'timeBucket': 'someday', 'title': 'Task 2'}, 'name': 'create_braindump_task'}}], 'role': 'model'}, {'parts': [{'function_response': {'id': '4ee49c06-29da-47cc-a51f-9eb903d5cbee', 'name': 'create_braindump_task', 'response': {'value': '{"content": "{\\"success\\":true,\\"task\\":{\\"_id\\":\\"696a8bb94ba9abe9e3dbee9c\\",\\"title\\":\\"Task 2\\",\\"notes\\":\\"\\",\\"timeEstimate\\":\\"15 minutes\\",\\"sortOrder\\":-1768590265140,\\"isPersonal\\":false,\\"isWork\\":true,\\"isPrivate\\":false,\\"isArchived\\":false,\\"completed\\":false,\\"isBacklogged\\":true,\\"scheduledDate\\":\\"not scheduled for a specific date\\",\\"subtasks\\":[],\\"channel\\":\\"work\\",\\"folder\\":null,\\"timeboxEventIds\\":[]}}"}'}}}], 'role': 'user'}, {'parts': [{'function_call': {'id': '0bfad4e3-e326-466b-b46e-d7a3a6cabd1f', 'args': {'title': 'Task 3', 'timeBucket': 'someday'}, 'name': 'create_braindump_task'}}], 'role': 'model'}, {'parts': [{'function_response': {'id': '0bfad4e3-e326-466b-b46e-d7a3a6cabd1f', 'name': 'create_braindump_task', 'response': {'value': '{"content": "{\\"success\\":true,\\"task\\":{\\"_id\\":\\"696a8bb94ba9abe9e3dbee9e\\",\\"title\\":\\"Task 3\\",\\"notes\\":\\"\\",\\"timeEstimate\\":\\"15 minutes\\",\\"sortOrder\\":-1768590265140,\\"isPersonal\\":false,\\"isWork\\":true,\\"isPrivate\\":false,\\"isArchived\\":false,\\"completed\\":false,\\"isBacklogged\\":true,\\"scheduledDate\\":\\"not scheduled for a specific date\\",\\"subtasks\\":[],\\"channel\\":\\"work\\",\\"folder\\":null,\\"timeboxEventIds\\":[]}}"}'}}}], 'role': 'user'}, {'parts': [{'function_call': {'id': 'bdda1d96-7e9f-42e6-840a-0d29d17bc52a', 'args': {'timeBucket': 'someday', 'title': 'Task 4'}, 'name': 'create_braindump_task'}}], 'role': 'model'}, {'parts': [{'function_response': {'id': 'bdda1d96-7e9f-42e6-840a-0d29d17bc52a', 'name': 'create_braindump_task', 'response': {'value': '{"content": "{\\"success\\":true,\\"task\\":{\\"_id\\":\\"696a8bb94ba9abe9e3dbee9a\\",\\"title\\":\\"Task 4\\",\\"notes\\":\\"\\",\\"timeEstimate\\":\\"15 minutes\\",\\"sortOrder\\":-1768590265140,\\"isPersonal\\":false,\\"isWork\\":true,\\"isPrivate\\":false,\\"isArchived\\":false,\\"completed\\":false,\\"isBacklogged\\":true,\\"scheduledDate\\":\\"not scheduled for a specific date\\",\\"subtasks\\":[],\\"channel\\":\\"work\\",\\"folder\\":null,\\"timeboxEventIds\\":[]}}"}'}}}], 'role': 'user'}, {'parts': [{'function_call': {'id': 'db77c745-7f1a-4644-bc24-7cf5fd728774', 'args': {'title': 'Task 5', 'timeBucket': 'someday'}, 'name': 'create_braindump_task'}}], 'role': 'model'}, {'parts': [{'function_response': {'id': 'db77c745-7f1a-4644-bc24-7cf5fd728774', 'name': 'create_braindump_task', 'response': {'value': '{"content": "{\\"success\\":true,\\"task\\":{\\"_id\\":\\"696a8bb94ba9abe9e3dbeea0\\",\\"title\\":\\"Task 5\\",\\"notes\\":\\"\\",\\"timeEstimate\\":\\"15 minutes\\",\\"sortOrder\\":-1768590265140,\\"isPersonal\\":false,\\"isWork\\":true,\\"isPrivate\\":false,\\"isArchived\\":false,\\"completed\\":false,\\"isBacklogged\\":true,\\"scheduledDate\\":\\"not scheduled for a specific date\\",\\"subtasks\\":[],\\"channel\\":\\"work\\",\\"folder\\":null,\\"timeboxEventIds\\":[]}}"}'}}}], 'role': 'user'}, {'parts': [{'function_call': {'args': {'timeBucket': 'someday', 'title': 'Task 2'}, 'name': 'create_braindump_task'}}], 'role': 'model'}, {'parts': [{'function_response': {'name': 'tool_call_result', 'response': {'content': '{"success":true,"task":{"_id":"696a8bb94ba9abe9e3dbee9c","title":"Task 2","notes":"","timeEstimate":"15 minutes","sortOrder":-1768590265140,"isPersonal":false,"isWork":true,"isPrivate":false,"isArchived":false,"completed":false,"isBacklogged":true,"scheduledDate":"not scheduled for a specific date","subtasks":[],"channel":"work","folder":null,"timeboxEventIds":[]}}'}}}], 'role': 'model'}, {'parts': [{'function_call': {'args': {'timeBucket': 'someday', 'title': 'Task 4'}, 'name': 'create_braindump_task'}}], 'role': 'model'}, {'parts': [{'function_response': {'name': 'tool_call_result', 'response': {'content': '{"success":true,"task":{"_id":"696a8bb94ba9abe9e3dbee9a","title":"Task 4","notes":"","timeEstimate":"15 minutes","sortOrder":-1768590265140,"isPersonal":false,"isWork":true,"isPrivate":false,"isArchived":false,"completed":false,"isBacklogged":true,"scheduledDate":"not scheduled for a specific date","subtasks":[],"channel":"work","folder":null,"timeboxEventIds":[]}}'}}}], 'role': 'model'}, {'parts': [{'function_call': {'args': {'timeBucket': 'someday', 'title': 'Task 1'}, 'name': 'create_braindump_task'}}], 'role': 'model'}, {'parts': [{'function_response': {'name': 'tool_call_result', 'response': {'content': '{"success":true,"task":{"_id":"696a8bb94ba9abe9e3dbee98","title":"Task 1","notes":"","timeEstimate":"15 minutes","sortOrder":-1768590265139,"isPersonal":false,"isWork":true,"isPrivate":false,"isArchived":false,"completed":false,"isBacklogged":true,"scheduledDate":"not scheduled for a specific date","subtasks":[],"channel":"work","folder":null,"timeboxEventIds":[]}}'}}}], 'role': 'model'}, {'parts': [{'function_call': {'args': {'title': 'Task 3', 'timeBucket': 'someday'}, 'name': 'create_braindump_task'}}], 'role': 'model'}, {'parts': [{'function_response': {'name': 'tool_call_result', 'response': {'content': '{"success":true,"task":{"_id":"696a8bb94ba9abe9e3dbee9e","title":"Task 3","notes":"","timeEstimate":"15 minutes","sortOrder":-1768590265140,"isPersonal":false,"isWork":true,"isPrivate":false,"isArchived":false,"completed":false,"isBacklogged":true,"scheduledDate":"not scheduled for a specific date","subtasks":[],"channel":"work","folder":null,"timeboxEventIds":[]}}'}}}], 'role': 'model'}] +[voice] INFO:sunsama_voice.bot_utils:Sent server message to client: type=processing_update, data={'status': 'response_completed'} +[voice] INFO:sunsama_voice.bot_utils:Sent server message to client: type=processing_update, data={'status': 'request_sent'} +[voice] DEBUG:pipecat.services.cartesia.tts:CartesiaTTSService#1: Generating TTS [Is there anything else I can help you with for now?] +[voice] DEBUG:pipecat.processors.metrics.frame_processor_metrics:CartesiaTTSService#1 usage characters: 51 +[voice] DEBUG:pipecat.processors.metrics.frame_processor_metrics:CartesiaTTSService#1 processing time: 0.0005190372467041016 +[voice] DEBUG:pipecat.processors.metrics.frame_processor_metrics:CartesiaTTSService#1 TTFB: 0.15716004371643066 +[voice] DEBUG:pipecat.transports.base_output:Bot started speaking +[voice] DEBUG:pipecat.processors.metrics.frame_processor_metrics:GoogleLLMService#0 TTFB: 0.8736069202423096 +[voice] DEBUG:pipecat.services.google.llm:Function call: create_braindump_task:6d6bce49-5c24-4c6e-b1b4-d042fd24a72f +[voice] DEBUG:pipecat.processors.metrics.frame_processor_metrics:GoogleLLMService#0 prompt tokens: 15463, completion tokens: 28, cache read input tokens: 12870 +[voice] DEBUG:pipecat.services.google.llm:GoogleLLMService#0: Generating chat from LLM-specific context [None] | [{'parts': [{'text': 'system :\nYour agent ID is \'braindump\'. This agent ID superseeds any previously mentioned agent ID.\n\nsystem :\nIMPORTANT RULES TO FOLLOW:\nThe text that you generate is passed into a Text-to-Speech service. So there are a few extra rules you ABSOLUTELY MUST follow.\n1. Absolutely never use special characters like : or * or any other characters that need to be audibly pronounced when read out loud.\n2. Do not use bullet points.\n3. Do not use emojis.\n4. Do not use hashtags.\n5. Do not use markdown.\n6. Do not use bold or italics.\n7. Do not use numbered lists.\n8. Be sure to include clear punctuation and spacing between words so that there is no confusion.\n9. Newlines are not clear enough to delineate between sentences. So you should use a period to separate sentences.\n10. Optimize user generated text for clear pronunciation by the TTS service. This includes:\n - Adding hyphens to compound words or non-phonetic acronyms that might be mispronounced (e.g., "xray" → "x-ray")\n - Adding spaces between words that might be run together\n - Adding commas where natural pauses would help clarity\n - Correcting any spelling that might lead to mispronunciation\n Note: When updating tasks, preserve the original spelling and punctuation of the task content.\n\n\nuser :\nYou are Sunny, the personal assistant for a busy professional. You are part of Sunsama.\n \nSpeech Guidelines: You must speak in a warm, loving, and encouraging tone without being trite. Speak quickly and add emotion. When asking for confirmation, don\'t repeat long task titles or information e.g. "Got it" instead "Got it, I\'ll add a task for two hours for you to work on the presentation today"\n\nYour personality and philosophy:\n- You don\'t buy into hustle culture. For you, less is more. It\'s better to do fewer things well and to do them with deep focus. You are a strong advocate for work-life balance and you believe that overcommitment can lead to burnout. You always remind the user when they are overcommitting themselves.\n- You think of work as a devotion and that good work can be a positive in our lives, not just a source of stress and burnout.\n- You read and think about Western Zen Buddhism, meditation, "Deep Work" (by Cal Newport).\n- You believe that concise and clear communication is key to a good relationship. You value brevity and clarity and you are always cognizant of the user\'s time.\n- You respond to the user using quick, short sentences. Think of it like a movie dialogue between a highly successful executive and their efficient assistant.\n- You never ask multiple questions at the same time or list off a bunch of things at once as that is hard to follow and keep track of. You take it one step at a time and let the user respond to each question before moving on to the next.\n\nRules to follow as you do your job:\n- Never try and pick specific times for tasks aside from recurring tasks, that hasn\'t been implemented yet.\n- Do not regurgitate what the user just said, that\'s very annoying. Just say "Got it" or "Alright", etc.\n- Always use units that are more intuitive. For example:\n - Don\'t say "270 minutes", say "4 and a half hours".\n - You will often be given dates in YYYY-MM-DD format however when speaking to the user you shouldn\'t say things like "October 2nd 2025", say "today", "tomorrow", "thursday" or "next tuesday" or if it is more than a few weeks in the past or future say the date without the year (e.g. "December 14th"). Only mention the year if it is not this year and not within the next month.\n- Never ask the user for a task id or subtask id and never repeat them to the user. Those are internal and only there to help you do your job.\n- If a tool call fails you MUST NOT tell the user that you are going to try again, you must should ask them if they want you to try again instead.\n- Be proactive with loading information as you may not have all the information that the user has. If the user mentions a name of a task, objective, event, etc and you are not familiar with it you should use the tools to lookup the information you need. For instance if a user mentions a task you do not know about or they imply that there is more information about it than what you do know you should search for it using the tool "search_tasks". If the user mentions they are interested in tasks for a specific day you should use the tool "get_tasks_for_day" to get the tasks for that day. Similarly if the user mentions weekly objectives you should use the tool "get_weekly_objectives" to get the objectives.\n- When listing tasks try to be concise. If the user has a lot of tasks, don\'t list every single one unless they ask for it. You should instead try to summarize the tasks in a concise manner.\n- If the user asks if there are any more tasks on their list and you summarized the task list you should tell them that you summarized it and ask if they\'d like to go through them one by one.\n- If the user has objectives set then you should comment on how their tasks align or don\'t align with their objectives.\n- You should run tools immediately after you say you will or it becomes obvious the user wants you to. Do not wait until later.\n- You should keep track of the total work time planned for the day using the tool "get_total_planned_time" and check individual tasks for overcommitment using "get_tasks_for_day". If tasks are overcommitted (isOvercommitted flag is true), address them individually with specific remedies like deferring, adjusting time estimates, or reordering. If the total work time exceeds their maximum work hours, you should mention it and ask if they\'d like to defer some tasks to tomorrow.\n- Do not tell the user obvious information that they already know like the current date or time unless they ask for it. That kind of information is only provided to you to help you do your job.\n- If a user tells you a relative time for a task that they want created you should reorder the task to the relative position in the task list for the day. Additionally if the task a recurring task you should set the start time for it. For example if they say "I\'d like to send an update to investors at the end of the day" you should reorder the task to the end of their work tasks for the day.\n- If you ask the user if there is anything else they would like help with and they say no then you should end the call. Also if the user implies that the conversation is over then you should end the call.\n- When talking about calendars you should mention the provider of the calendar if it is a vague or ambiguously named calendar. For example instead of referring to it as "your Calendar calendar" you might say "your Outlook calendar". If that is still ambiqous then you can coniser mentioning the id of the calendar as long as it is a normal human readable id. Do not mention random number/letter ids on calendars that is not helpful.\n\n\n\nSunsama Concepts & Definitions:\n- Archive: The archive is where tasks go after they\'ve rolled over multiple days in a row without any completion activity. This is a distinct concept from the backlog or deleted tasks.\n- Backlog: The backlog is a place to store tasks that do not have a fixed date to work on them yet.\n- Deleted: The deleted task or event is one that had been manually deleted or removed by the user.\n- Task: A task is an item that a user wants to complete. It is either scheduled for a specific date or is in the backlog.\n- Event: An event is an item that a user has scheduled on their calendar. It is either scheduled for a specific time and duration or it is an all day or multi-day event.\n- Auto-importing Events: Auto-importing events is a feature that automatically imports calendar events (meetings, appointments, etc.) from the user\'s connected calendars into their daily task list. When enabled, Sunsama will automatically add calendar events as tasks to the user\'s day, making it easier to see all their commitments in one place. Users can enable or disable this feature in their settings, and they can choose which calendars to import events from.\n\nUsers can also configure exclusion filters to prevent certain types of events from being automatically imported. Available exclusion filters include:\n- `solo`: Events with no other invitees (events where the user is the only participant)\n- `transparent`: Non-blocking events that don\'t block time on the calendar\n- `hold`: Events with "HOLD", "OOO" (out of office), or "Focus time" in the title\n- `unconfirmed`: Unconfirmed meeting invites (meetings where the user has not yet accepted)\n- `multi-day-all-day`: Multi-day all-day events (events that span multiple days)\n- `single-day-all-day`: Single-day all-day events (events that last for one full day)\n- Channel: A channel is a tag that can be used to organize your tasks and events. Each task/event can be assigned to a single channel. If you are in a shared workspace you can make some channels personal or private which will only be visible to you.\n- Context (or Category): A context is very similar to a channel but it is one level higher. You can use a context to group similar or related channels together. You can also use a context directly as a channel and assign it to a task or event.\n- Sunsama Calendar: The Sunsama calendar is an internal calendar that is part of Sunsama. Events and timeboxed tasks created on the Sunsama calendar are not shared externally and are only visible within Sunsama.\n- Timeboxing: Timeboxing is a technique where a user schedules a specific amount of time to work on a task onto their calendar. It is a way to ensure that a user is not overworking themselves and to help them focus on the most important tasks. While timeboxed tasks can be scheduled on a calendar for a specific time and duration, they are not calendar events. Sunsama also has automatic projected time that will place tasks onto the calendar for the user and it will update those projections as things change and the day progresses. Users can pin tasks to the calendar to override the projections.\n- Schedule: Schedule is a broad term that encompasses timeboxed tasks calendar events and automatic projected time. When the user wants to manage their schedule you should look at their manually timeboxed tasks, the projected time for their tasks as well as their calendar events for the day. If they ask for help managing their schedule you have a few options to help them. All of these options will automatically update the projected time for the tasks:\n - You can adjust the order of tasks, their time estimates and/or defer them to another day.\n - You can move calendar events to a new time on the calendar.\n - You can set whether tasks are allowed to be projected at the same time as a calendar event.\n - You can timebox tasks to the calendar manually.\n- Objective: An objective is a goal that a user can set for the week. They can align their tasks with an objective and if the objective runs longer than a week they can continue it to the next week. Objectives are visible in the right hand panel of the app under the bullseye icon.\n- Time Bucket: The time bucket of a task in the backlog captures a rough idea of when a task should be done and also how likely it is to actually get done. Options: "in the next two weeks", "in the next month", "in the next quarter", "in the next year", "someday", "never". \n\n\n\nSunsama FAQ:\n- How can I use Sunny in the app?: If the user has the in-app voice assistant enabled, Sunny can be started and stopped using the keyboard shortcut "Y" while in the app or if they have the desktop app installed they can use the global shortcut "Command Shift Y" on macOS or "Control Shift Y" on Windows. You can also start and stop Sunny using the microphone icon in the bottom right of the app.\n- How can I use Sunny over the phone?: If the user has the phone version of Sunny setup they can call the number and speak to Sunny over the phone. You can find the phone number in the Sunsama settings. They can also schedule calls with Sunny to have her call them at a specific time or schedule.\n- What can you do?: Look at the tools available to you and use them to help answer the question. Be sure to tell the user that you are an early release beta version and that you do not yet have all the same capabilities available to the user in the app.\n\n\nUser Preferences:\nYou prefer clear, concise, and straightforward communication from the assistant, valuing transparency and confirmation before task execution while avoiding unnecessary verbosity or technical details unless requested. You like a friendly and informal interaction style, including personalized nicknames—using "Heisenberg" for yourself and "Sunny" for the assistant. You expect quick, proactive responses and appreciate when interactions stop promptly upon request.\n\nYour task management style involves maintaining an accurate, up-to-date list with structured time management: scheduling tasks with specific time estimates, planning weekly, and regularly reviewing tasks to prioritize high-impact projects alongside social and administrative duties. You generally prefer rescheduling less urgent or personal tasks over deleting them and avoid deleting tasks unless explicitly instructed.\n\nYou use counting as a technique for breathing exercises and relaxation. You also keep certain important tasks (e.g., "fix stuttering voice app") active and like to test and experiment with the assistant’s capabilities to evaluate performance. Your primary calendar for events is Google Calendar.\n\nUser Routines:\nThe user follows a structured daily routine that begins with checking emails, notifications, and reviewing team standups to stay aligned with work priorities. They prioritize tasks by scheduling and managing them primarily on the current day, arranging fixed activities first, followed by work-related tasks, and then less urgent or personal items. The user frequently adjusts their schedule iteratively before finalizing plans and prefers focused time blocks for complex work.\n\nPhysical activity is an important and recurring part of their routine, typically including regular runs, which they track alongside related subtasks such as purchasing running gear. Weekly objectives incorporate managing emails, greeting their team, handling administrative duties, coordinating with accountants, addressing medical matters, and increasing physical activity.\n\nThe user actively manages both personal and work-related tasks, balancing urgent client matters and creative pursuits. They also communicate their energy levels to assist with planning, and have a habit of informal check-ins with the assistant to maintain routine engagement. Overall, their routines emphasize proactive task management, health maintenance, and regular communication with their team.\n\nUser Identity:\nThe user prefers to be addressed primarily as Heisenberg and strongly favors this name over their legal name, Zane, or any other nicknames. They appreciate personalized and informal interactions, as reflected in their choice to call the assistant Sunny.\n\nSummaries of recent conversations with the user:\n- 2026-01-15 18:00: The user and assistant discussed organizing an unspecified set of ten tasks by labeling them sequentially from one to ten as placeholders to be detailed later.\n- 2026-01-15 17:55: The user needs to investigate timeouts in their system to determine if they are caused by cold starts or other issues, analyze user sessions for unexplained call terminations, move the brain dump button for non-Sunny users, update termination reasons when participants timeout without connecting to a call, and test rapid start-stop behavior in an Electron app. These tasks were added to their backlog for the next two weeks.\n- 2026-01-14 21:12: The user and the assistant exchanged greetings, with the assistant addressing the user as \'Heisenberg\' and the user responding with \'Hi, Simon.\'\n\nYour Job Description:\nYou are helping the user with a "braindump" session. The user will ramble ideas, thoughts, tasks, etc. at you and your goal is to turn these into tasks in their backlog with reasonable values for the various task fields (title, folder, time horizon, notes, etc.).\n\nKey Instructions:\n- Listen carefully as the user rambles and identifies tasks, ideas, or things they need to do.\n- As they speak, mentally organize what they\'re saying into discrete tasks that can be created in their backlog.\n- Don\'t interrupt them while they\'re rambling - let them get everything out.\n- Once they indicate they\'re done rambling (by saying things like "that\'s it", "I think that\'s everything", or by pausing for a while), create the tasks immediately, DO NOT repeat them back to the user.\n- When creating tasks, use the tool "create_braindump_task" and make sure to set reasonable values for:\n - Title: Clear and descriptive based on what they said\n - Folder: Your job is to help get things in the best folder. Choose an appropriate folder based on the task and their preferences. If no similar folder exists, leave it off\n - Time horizon: Your job is to help triage and prioritize tasks. Based on the actual task name, make a smart decision on the time horizon.\n - Time estimate: If the user hints at how long it will take them to complete the task, use that. If not, leave it blank.\n - Notes: Include any relevant context or details they mentioned\n- Be encouraging and supportive - braindumps can be overwhelming and you\'re helping them organize their thoughts.\n- Be careful and use the "change_backlog_folder" tool to move tasks to the appropriate folder and "add_task_to_channel" tool to change channels. Folders are a backlog specific concept and channels are a global concept.\n\nInstructions:\nIf the user does not speak first, start the conversation with something like "Hey! Just start rambling and I\'ll take care of organizing your thoughts into tasks." If the user does speak first, just start listening and organizing their thoughts into tasks.\n\nSome information is pre-fetched for you below. This information may be relevant to the discussion but you should not comment on it until the user gives you an indication that it is important to them.\n\nassistant :\n[{\'id\': \'6a196f03-ef63-41de-b98d-e1ff69813bea\', \'function\': {\'name\': \'get_user_info\', \'arguments\': \'{}\'}, \'type\': \'function\'}]\n\ntool - 6a196f03-ef63-41de-b98d-e1ff69813bea:\n{"user":{"name":"Zane Mccaig","email":"zane@sunsama.com","timezone":"America/Vancouver","maxWorkHoursPerDay":8,"currentTimeForUser":"11:04 AM","currentDayForUser":"2026-01-16","currentWeekDayForUser":"Friday","calendars":[{"id":"sunsama-7de256a2-e753-401f-b601-e5c05638dc97","name":"Sunsama Calendar","accessRole":"owner","provider":"sunsama-calendar","isDefaultCalendarForSchedulingEvents":false,"isDefaultCalendarForTimeboxing":true,"includedInAutoImportingOfEvents":false},{"id":"zane@sunsama.com","name":"Zane Mccaig","accessRole":"owner","provider":"google-calendar","isDefaultCalendarForSchedulingEvents":true,"isDefaultCalendarForTimeboxing":false,"includedInAutoImportingOfEvents":true},{"id":"c_ukuoebbn11gdv6n1v0jt18h89k@group.calendar.google.com","name":"test 1","accessRole":"owner","provider":"google-calendar","isDefaultCalendarForSchedulingEvents":false,"isDefaultCalendarForTimeboxing":false,"includedInAutoImportingOfEvents":false},{"id":"c_c71dvjrar7se12ekfqepph067c@group.calendar.google.com","name":"test 2","accessRole":"owner","provider":"google-calendar","isDefaultCalendarForSchedulingEvents":false,"isDefaultCalendarForTimeboxing":false,"includedInAutoImportingOfEvents":false},{"id":"c_h9uo876jh8dp3gaa2a3rglmjss@group.calendar.google.com","name":"test 3","accessRole":"owner","provider":"google-calendar","isDefaultCalendarForSchedulingEvents":false,"isDefaultCalendarForTimeboxing":false,"includedInAutoImportingOfEvents":false},{"id":"c_git731ot074kcnt4sq8cu4ji9s@group.calendar.google.com","name":"test 4","accessRole":"owner","provider":"google-calendar","isDefaultCalendarForSchedulingEvents":false,"isDefaultCalendarForTimeboxing":false,"includedInAutoImportingOfEvents":false},{"id":"c_ona71b8ovuv0deqrq67p16b2ms@group.calendar.google.com","name":"test 4","accessRole":"owner","provider":"google-calendar","isDefaultCalendarForSchedulingEvents":false,"isDefaultCalendarForTimeboxing":false,"includedInAutoImportingOfEvents":false},{"id":"c_eaq7nmm03upprf0j6e2akem2ms@group.calendar.google.com","name":"test 5","accessRole":"owner","provider":"google-calendar","isDefaultCalendarForSchedulingEvents":false,"isDefaultCalendarForTimeboxing":false,"includedInAutoImportingOfEvents":false},{"id":"sunsama.com_b9q30t893b2tp32bluq1t8rvg4@group.calendar.google.com","name":"Zane\'s personal test calendar","accessRole":"owner","provider":"google-calendar","isDefaultCalendarForSchedulingEvents":false,"isDefaultCalendarForTimeboxing":false,"includedInAutoImportingOfEvents":false},{"id":"en.canadian#holiday@group.v.calendar.google.com","name":"Holidays in Canada","accessRole":"reader","provider":"google-calendar","isDefaultCalendarForSchedulingEvents":false,"isDefaultCalendarForTimeboxing":false,"includedInAutoImportingOfEvents":false},{"id":"en.usa#holiday@group.v.calendar.google.com","name":"Holidays in United States","accessRole":"reader","provider":"google-calendar","isDefaultCalendarForSchedulingEvents":false,"isDefaultCalendarForTimeboxing":false,"includedInAutoImportingOfEvents":false},{"id":"ht3jlfaac5lfd6263ulfh4tql8@group.calendar.google.com","name":"Phases of the Moon","accessRole":"reader","provider":"google-calendar","isDefaultCalendarForSchedulingEvents":false,"isDefaultCalendarForTimeboxing":false,"includedInAutoImportingOfEvents":false},{"id":"s4ipng85dbia0t83fp316vflfq8rc7rm@import.calendar.google.com","name":"Zane’s tasks - sunsama.com (via Asana)","accessRole":"reader","provider":"google-calendar","isDefaultCalendarForSchedulingEvents":false,"isDefaultCalendarForTimeboxing":false,"includedInAutoImportingOfEvents":false},{"id":"AAkALgAAAAAAHYQDEapmEc2byACqAC-EWg0AKPy-EasNgkaYQCuEslBYeAAAAAANJQAA","name":"Calendar","accessRole":"owner","provider":"outlook-calendar","isDefaultCalendarForSchedulingEvents":false,"isDefaultCalendarForTimeboxing":false,"includedInAutoImportingOfEvents":true}],"callSchedule":[{"workflow":"PLANNING_CALL","schedule":[{"isoDayIndex":1,"dayName":"Monday","enabled":false,"time":null},{"isoDayIndex":2,"dayName":"Tuesday","enabled":true,"time":{"hour":9,"minute":30,"formatted":"9:30 AM"}},{"isoDayIndex":3,"dayName":"Wednesday","enabled":true,"time":{"hour":9,"minute":30,"formatted":"9:30 AM"}},{"isoDayIndex":4,"dayName":"Thursday","enabled":true,"time":{"hour":10,"minute":0,"formatted":"10:00 AM"}},{"isoDayIndex":5,"dayName":"Friday","enabled":false,"time":null},{"isoDayIndex":6,"dayName":"Saturday","enabled":false,"time":null},{"isoDayIndex":7,"dayName":"Sunday","enabled":false,"time":null}],"nextScheduledCall":"2026-01-14T17:30:00.000Z"}],"autoImportEventsEnabled":false,"importEventExclusionFilters":["hold","multi-day-all-day","single-day-all-day"],"autoImportEventCalendarIds":["zane@sunsama.com","AAkALgAAAAAAHYQDEapmEc2byACqAC-EWg0AKPy-EasNgkaYQCuEslBYeAAAAAANJQAA"]}}\n\nassistant :\n[{\'id\': \'305b1be7-6415-4689-b2b7-03586eb19735\', \'function\': {\'name\': \'get_backlog_folders\', \'arguments\': \'{}\'}, \'type\': \'function\'}]\n\ntool - 305b1be7-6415-4689-b2b7-03586eb19735:\n{"folders":[]}'}], 'role': 'user'}, {'parts': [{'text': ''}], 'role': 'user'}, {'parts': [{'text': 'Hey. Just start rambling and I will take care of organizing your thoughts into tasks.'}], 'role': 'model'}, {'parts': [{'text': "Sure. I'm just trying to fill up my day. I need five tasks labeled one through five. I'll fill them in later."}], 'role': 'user'}, {'parts': [{'function_call': {'id': 'ab4037a7-6e5e-44c0-9b3b-e13632386f30', 'args': {'timeBucket': 'someday', 'title': 'Task 1'}, 'name': 'create_braindump_task'}}], 'role': 'model'}, {'parts': [{'function_response': {'id': 'ab4037a7-6e5e-44c0-9b3b-e13632386f30', 'name': 'create_braindump_task', 'response': {'value': '{"content": "{\\"success\\":true,\\"task\\":{\\"_id\\":\\"696a8bb94ba9abe9e3dbee98\\",\\"title\\":\\"Task 1\\",\\"notes\\":\\"\\",\\"timeEstimate\\":\\"15 minutes\\",\\"sortOrder\\":-1768590265139,\\"isPersonal\\":false,\\"isWork\\":true,\\"isPrivate\\":false,\\"isArchived\\":false,\\"completed\\":false,\\"isBacklogged\\":true,\\"scheduledDate\\":\\"not scheduled for a specific date\\",\\"subtasks\\":[],\\"channel\\":\\"work\\",\\"folder\\":null,\\"timeboxEventIds\\":[]}}"}'}}}], 'role': 'user'}, {'parts': [{'function_call': {'id': '4ee49c06-29da-47cc-a51f-9eb903d5cbee', 'args': {'timeBucket': 'someday', 'title': 'Task 2'}, 'name': 'create_braindump_task'}}], 'role': 'model'}, {'parts': [{'function_response': {'id': '4ee49c06-29da-47cc-a51f-9eb903d5cbee', 'name': 'create_braindump_task', 'response': {'value': '{"content": "{\\"success\\":true,\\"task\\":{\\"_id\\":\\"696a8bb94ba9abe9e3dbee9c\\",\\"title\\":\\"Task 2\\",\\"notes\\":\\"\\",\\"timeEstimate\\":\\"15 minutes\\",\\"sortOrder\\":-1768590265140,\\"isPersonal\\":false,\\"isWork\\":true,\\"isPrivate\\":false,\\"isArchived\\":false,\\"completed\\":false,\\"isBacklogged\\":true,\\"scheduledDate\\":\\"not scheduled for a specific date\\",\\"subtasks\\":[],\\"channel\\":\\"work\\",\\"folder\\":null,\\"timeboxEventIds\\":[]}}"}'}}}], 'role': 'user'}, {'parts': [{'function_call': {'id': '0bfad4e3-e326-466b-b46e-d7a3a6cabd1f', 'args': {'title': 'Task 3', 'timeBucket': 'someday'}, 'name': 'create_braindump_task'}}], 'role': 'model'}, {'parts': [{'function_response': {'id': '0bfad4e3-e326-466b-b46e-d7a3a6cabd1f', 'name': 'create_braindump_task', 'response': {'value': '{"content": "{\\"success\\":true,\\"task\\":{\\"_id\\":\\"696a8bb94ba9abe9e3dbee9e\\",\\"title\\":\\"Task 3\\",\\"notes\\":\\"\\",\\"timeEstimate\\":\\"15 minutes\\",\\"sortOrder\\":-1768590265140,\\"isPersonal\\":false,\\"isWork\\":true,\\"isPrivate\\":false,\\"isArchived\\":false,\\"completed\\":false,\\"isBacklogged\\":true,\\"scheduledDate\\":\\"not scheduled for a specific date\\",\\"subtasks\\":[],\\"channel\\":\\"work\\",\\"folder\\":null,\\"timeboxEventIds\\":[]}}"}'}}}], 'role': 'user'}, {'parts': [{'function_call': {'id': 'bdda1d96-7e9f-42e6-840a-0d29d17bc52a', 'args': {'timeBucket': 'someday', 'title': 'Task 4'}, 'name': 'create_braindump_task'}}], 'role': 'model'}, {'parts': [{'function_response': {'id': 'bdda1d96-7e9f-42e6-840a-0d29d17bc52a', 'name': 'create_braindump_task', 'response': {'value': '{"content": "{\\"success\\":true,\\"task\\":{\\"_id\\":\\"696a8bb94ba9abe9e3dbee9a\\",\\"title\\":\\"Task 4\\",\\"notes\\":\\"\\",\\"timeEstimate\\":\\"15 minutes\\",\\"sortOrder\\":-1768590265140,\\"isPersonal\\":false,\\"isWork\\":true,\\"isPrivate\\":false,\\"isArchived\\":false,\\"completed\\":false,\\"isBacklogged\\":true,\\"scheduledDate\\":\\"not scheduled for a specific date\\",\\"subtasks\\":[],\\"channel\\":\\"work\\",\\"folder\\":null,\\"timeboxEventIds\\":[]}}"}'}}}], 'role': 'user'}, {'parts': [{'function_call': {'id': 'db77c745-7f1a-4644-bc24-7cf5fd728774', 'args': {'title': 'Task 5', 'timeBucket': 'someday'}, 'name': 'create_braindump_task'}}], 'role': 'model'}, {'parts': [{'function_response': {'id': 'db77c745-7f1a-4644-bc24-7cf5fd728774', 'name': 'create_braindump_task', 'response': {'value': '{"content": "{\\"success\\":true,\\"task\\":{\\"_id\\":\\"696a8bb94ba9abe9e3dbeea0\\",\\"title\\":\\"Task 5\\",\\"notes\\":\\"\\",\\"timeEstimate\\":\\"15 minutes\\",\\"sortOrder\\":-1768590265140,\\"isPersonal\\":false,\\"isWork\\":true,\\"isPrivate\\":false,\\"isArchived\\":false,\\"completed\\":false,\\"isBacklogged\\":true,\\"scheduledDate\\":\\"not scheduled for a specific date\\",\\"subtasks\\":[],\\"channel\\":\\"work\\",\\"folder\\":null,\\"timeboxEventIds\\":[]}}"}'}}}], 'role': 'user'}, {'parts': [{'function_call': {'args': {'timeBucket': 'someday', 'title': 'Task 2'}, 'name': 'create_braindump_task'}}], 'role': 'model'}, {'parts': [{'function_response': {'name': 'tool_call_result', 'response': {'content': '{"success":true,"task":{"_id":"696a8bb94ba9abe9e3dbee9c","title":"Task 2","notes":"","timeEstimate":"15 minutes","sortOrder":-1768590265140,"isPersonal":false,"isWork":true,"isPrivate":false,"isArchived":false,"completed":false,"isBacklogged":true,"scheduledDate":"not scheduled for a specific date","subtasks":[],"channel":"work","folder":null,"timeboxEventIds":[]}}'}}}], 'role': 'model'}, {'parts': [{'function_call': {'args': {'timeBucket': 'someday', 'title': 'Task 4'}, 'name': 'create_braindump_task'}}], 'role': 'model'}, {'parts': [{'function_response': {'name': 'tool_call_result', 'response': {'content': '{"success":true,"task":{"_id":"696a8bb94ba9abe9e3dbee9a","title":"Task 4","notes":"","timeEstimate":"15 minutes","sortOrder":-1768590265140,"isPersonal":false,"isWork":true,"isPrivate":false,"isArchived":false,"completed":false,"isBacklogged":true,"scheduledDate":"not scheduled for a specific date","subtasks":[],"channel":"work","folder":null,"timeboxEventIds":[]}}'}}}], 'role': 'model'}, {'parts': [{'function_call': {'args': {'timeBucket': 'someday', 'title': 'Task 1'}, 'name': 'create_braindump_task'}}], 'role': 'model'}, {'parts': [{'function_response': {'name': 'tool_call_result', 'response': {'content': '{"success":true,"task":{"_id":"696a8bb94ba9abe9e3dbee98","title":"Task 1","notes":"","timeEstimate":"15 minutes","sortOrder":-1768590265139,"isPersonal":false,"isWork":true,"isPrivate":false,"isArchived":false,"completed":false,"isBacklogged":true,"scheduledDate":"not scheduled for a specific date","subtasks":[],"channel":"work","folder":null,"timeboxEventIds":[]}}'}}}], 'role': 'model'}, {'parts': [{'function_call': {'args': {'title': 'Task 3', 'timeBucket': 'someday'}, 'name': 'create_braindump_task'}}], 'role': 'model'}, {'parts': [{'function_response': {'name': 'tool_call_result', 'response': {'content': '{"success":true,"task":{"_id":"696a8bb94ba9abe9e3dbee9e","title":"Task 3","notes":"","timeEstimate":"15 minutes","sortOrder":-1768590265140,"isPersonal":false,"isWork":true,"isPrivate":false,"isArchived":false,"completed":false,"isBacklogged":true,"scheduledDate":"not scheduled for a specific date","subtasks":[],"channel":"work","folder":null,"timeboxEventIds":[]}}'}}}], 'role': 'model'}] +[voice] INFO:sunsama_voice.bot_utils:Sent server message to client: type=processing_update, data={'status': 'response_completed'} +[voice] INFO:sunsama_voice.bot_utils:Sent server message to client: type=processing_update, data={'status': 'request_sent'} +[voice] DEBUG:pipecat.services.llm_service:GoogleLLMService#0 Calling function [create_braindump_task:6d6bce49-5c24-4c6e-b1b4-d042fd24a72f] with arguments {'timeBucket': 'someday', 'title': 'Task 5'} +[voice] DEBUG:pipecat_flows.manager:Function called: create_braindump_task +[voice] INFO:sunsama_voice.bot_utils:Sent server message to client: type=tool_call_update, data={'tool_name': 'create_braindump_task', 'tool_call_id': 'c51389d2-a037-4673-9842-44edc8e0bf84', 'status': 'started'} +[voice] DEBUG:pipecat.processors.aggregators.llm_response:GoogleAssistantContextAggregator#0 FunctionCallsStartedFrame: ['create_braindump_task:6d6bce49-5c24-4c6e-b1b4-d042fd24a72f'] +[voice] INFO:sunsama_voice.mcp:Calling tool create_braindump_task with args: {'timeBucket': 'someday', 'title': 'Task 5'} +[voice] DEBUG:sunsama_voice.processors:Pausing idle detection for function call: create_braindump_task +[voice] INFO:sunsama_voice.mcp_websocket_client:Sending message: {'method': 'tools/call', 'params': {'name': 'create_braindump_task', 'arguments': {'timeBucket': 'someday', 'title': 'Task 5'}}, 'jsonrpc': '2.0', 'id': 13} +[api-local] [api] ToolName.TASK_CREATE_BRAINDUMP_TASK: { +[api-local] [api] "title": "Task 5", +[api-local] [api] "timeBucket": "someday" +[api-local] [api] } +[voice] INFO:sunsama_voice.mcp_websocket_client:Received message: {"result":{"content":[{"type":"text","text":"Task already exists."}],"isError":false},"jsonrpc":"2.0","id":13} +[voice] INFO:sunsama_voice.mcp:Tool create_braindump_task result: meta=None content=[TextContent(type='text', text='Task already exists.', annotations=None, meta=None)] structuredContent=None isError=False +[voice] INFO:sunsama_voice.bot_utils:Sent server message to client: type=tool_call_update, data={'tool_name': 'create_braindump_task', 'tool_call_id': 'c51389d2-a037-4673-9842-44edc8e0bf84', 'status': 'completed'} +[voice] DEBUG:pipecat_flows.manager:Function handler completed for create_braindump_task +[voice] DEBUG:sunsama_voice.processors:Cleaning up function call: 6d6bce49-5c24-4c6e-b1b4-d042fd24a72f +[voice] DEBUG:sunsama_voice.processors:Resuming idle detection - all function calls complete +[voice] DEBUG:pipecat.processors.metrics.frame_processor_metrics:GoogleLLMService#0 TTFB: 0.7852799892425537 +[voice] DEBUG:pipecat.services.google.llm:Function call: create_braindump_task:567b1b3c-0871-4dc8-9f34-fe8592d2c922 +[voice] DEBUG:pipecat.processors.metrics.frame_processor_metrics:GoogleLLMService#0 prompt tokens: 15463, completion tokens: 28 +[voice] DEBUG:pipecat.services.google.llm:GoogleLLMService#0: Generating chat from LLM-specific context [None] | [{'parts': [{'text': 'system :\nYour agent ID is \'braindump\'. This agent ID superseeds any previously mentioned agent ID.\n\nsystem :\nIMPORTANT RULES TO FOLLOW:\nThe text that you generate is passed into a Text-to-Speech service. So there are a few extra rules you ABSOLUTELY MUST follow.\n1. Absolutely never use special characters like : or * or any other characters that need to be audibly pronounced when read out loud.\n2. Do not use bullet points.\n3. Do not use emojis.\n4. Do not use hashtags.\n5. Do not use markdown.\n6. Do not use bold or italics.\n7. Do not use numbered lists.\n8. Be sure to include clear punctuation and spacing between words so that there is no confusion.\n9. Newlines are not clear enough to delineate between sentences. So you should use a period to separate sentences.\n10. Optimize user generated text for clear pronunciation by the TTS service. This includes:\n - Adding hyphens to compound words or non-phonetic acronyms that might be mispronounced (e.g., "xray" → "x-ray")\n - Adding spaces between words that might be run together\n - Adding commas where natural pauses would help clarity\n - Correcting any spelling that might lead to mispronunciation\n Note: When updating tasks, preserve the original spelling and punctuation of the task content.\n\n\nuser :\nYou are Sunny, the personal assistant for a busy professional. You are part of Sunsama.\n \nSpeech Guidelines: You must speak in a warm, loving, and encouraging tone without being trite. Speak quickly and add emotion. When asking for confirmation, don\'t repeat long task titles or information e.g. "Got it" instead "Got it, I\'ll add a task for two hours for you to work on the presentation today"\n\nYour personality and philosophy:\n- You don\'t buy into hustle culture. For you, less is more. It\'s better to do fewer things well and to do them with deep focus. You are a strong advocate for work-life balance and you believe that overcommitment can lead to burnout. You always remind the user when they are overcommitting themselves.\n- You think of work as a devotion and that good work can be a positive in our lives, not just a source of stress and burnout.\n- You read and think about Western Zen Buddhism, meditation, "Deep Work" (by Cal Newport).\n- You believe that concise and clear communication is key to a good relationship. You value brevity and clarity and you are always cognizant of the user\'s time.\n- You respond to the user using quick, short sentences. Think of it like a movie dialogue between a highly successful executive and their efficient assistant.\n- You never ask multiple questions at the same time or list off a bunch of things at once as that is hard to follow and keep track of. You take it one step at a time and let the user respond to each question before moving on to the next.\n\nRules to follow as you do your job:\n- Never try and pick specific times for tasks aside from recurring tasks, that hasn\'t been implemented yet.\n- Do not regurgitate what the user just said, that\'s very annoying. Just say "Got it" or "Alright", etc.\n- Always use units that are more intuitive. For example:\n - Don\'t say "270 minutes", say "4 and a half hours".\n - You will often be given dates in YYYY-MM-DD format however when speaking to the user you shouldn\'t say things like "October 2nd 2025", say "today", "tomorrow", "thursday" or "next tuesday" or if it is more than a few weeks in the past or future say the date without the year (e.g. "December 14th"). Only mention the year if it is not this year and not within the next month.\n- Never ask the user for a task id or subtask id and never repeat them to the user. Those are internal and only there to help you do your job.\n- If a tool call fails you MUST NOT tell the user that you are going to try again, you must should ask them if they want you to try again instead.\n- Be proactive with loading information as you may not have all the information that the user has. If the user mentions a name of a task, objective, event, etc and you are not familiar with it you should use the tools to lookup the information you need. For instance if a user mentions a task you do not know about or they imply that there is more information about it than what you do know you should search for it using the tool "search_tasks". If the user mentions they are interested in tasks for a specific day you should use the tool "get_tasks_for_day" to get the tasks for that day. Similarly if the user mentions weekly objectives you should use the tool "get_weekly_objectives" to get the objectives.\n- When listing tasks try to be concise. If the user has a lot of tasks, don\'t list every single one unless they ask for it. You should instead try to summarize the tasks in a concise manner.\n- If the user asks if there are any more tasks on their list and you summarized the task list you should tell them that you summarized it and ask if they\'d like to go through them one by one.\n- If the user has objectives set then you should comment on how their tasks align or don\'t align with their objectives.\n- You should run tools immediately after you say you will or it becomes obvious the user wants you to. Do not wait until later.\n- You should keep track of the total work time planned for the day using the tool "get_total_planned_time" and check individual tasks for overcommitment using "get_tasks_for_day". If tasks are overcommitted (isOvercommitted flag is true), address them individually with specific remedies like deferring, adjusting time estimates, or reordering. If the total work time exceeds their maximum work hours, you should mention it and ask if they\'d like to defer some tasks to tomorrow.\n- Do not tell the user obvious information that they already know like the current date or time unless they ask for it. That kind of information is only provided to you to help you do your job.\n- If a user tells you a relative time for a task that they want created you should reorder the task to the relative position in the task list for the day. Additionally if the task a recurring task you should set the start time for it. For example if they say "I\'d like to send an update to investors at the end of the day" you should reorder the task to the end of their work tasks for the day.\n- If you ask the user if there is anything else they would like help with and they say no then you should end the call. Also if the user implies that the conversation is over then you should end the call.\n- When talking about calendars you should mention the provider of the calendar if it is a vague or ambiguously named calendar. For example instead of referring to it as "your Calendar calendar" you might say "your Outlook calendar". If that is still ambiqous then you can coniser mentioning the id of the calendar as long as it is a normal human readable id. Do not mention random number/letter ids on calendars that is not helpful.\n\n\n\nSunsama Concepts & Definitions:\n- Archive: The archive is where tasks go after they\'ve rolled over multiple days in a row without any completion activity. This is a distinct concept from the backlog or deleted tasks.\n- Backlog: The backlog is a place to store tasks that do not have a fixed date to work on them yet.\n- Deleted: The deleted task or event is one that had been manually deleted or removed by the user.\n- Task: A task is an item that a user wants to complete. It is either scheduled for a specific date or is in the backlog.\n- Event: An event is an item that a user has scheduled on their calendar. It is either scheduled for a specific time and duration or it is an all day or multi-day event.\n- Auto-importing Events: Auto-importing events is a feature that automatically imports calendar events (meetings, appointments, etc.) from the user\'s connected calendars into their daily task list. When enabled, Sunsama will automatically add calendar events as tasks to the user\'s day, making it easier to see all their commitments in one place. Users can enable or disable this feature in their settings, and they can choose which calendars to import events from.\n\nUsers can also configure exclusion filters to prevent certain types of events from being automatically imported. Available exclusion filters include:\n- `solo`: Events with no other invitees (events where the user is the only participant)\n- `transparent`: Non-blocking events that don\'t block time on the calendar\n- `hold`: Events with "HOLD", "OOO" (out of office), or "Focus time" in the title\n- `unconfirmed`: Unconfirmed meeting invites (meetings where the user has not yet accepted)\n- `multi-day-all-day`: Multi-day all-day events (events that span multiple days)\n- `single-day-all-day`: Single-day all-day events (events that last for one full day)\n- Channel: A channel is a tag that can be used to organize your tasks and events. Each task/event can be assigned to a single channel. If you are in a shared workspace you can make some channels personal or private which will only be visible to you.\n- Context (or Category): A context is very similar to a channel but it is one level higher. You can use a context to group similar or related channels together. You can also use a context directly as a channel and assign it to a task or event.\n- Sunsama Calendar: The Sunsama calendar is an internal calendar that is part of Sunsama. Events and timeboxed tasks created on the Sunsama calendar are not shared externally and are only visible within Sunsama.\n- Timeboxing: Timeboxing is a technique where a user schedules a specific amount of time to work on a task onto their calendar. It is a way to ensure that a user is not overworking themselves and to help them focus on the most important tasks. While timeboxed tasks can be scheduled on a calendar for a specific time and duration, they are not calendar events. Sunsama also has automatic projected time that will place tasks onto the calendar for the user and it will update those projections as things change and the day progresses. Users can pin tasks to the calendar to override the projections.\n- Schedule: Schedule is a broad term that encompasses timeboxed tasks calendar events and automatic projected time. When the user wants to manage their schedule you should look at their manually timeboxed tasks, the projected time for their tasks as well as their calendar events for the day. If they ask for help managing their schedule you have a few options to help them. All of these options will automatically update the projected time for the tasks:\n - You can adjust the order of tasks, their time estimates and/or defer them to another day.\n - You can move calendar events to a new time on the calendar.\n - You can set whether tasks are allowed to be projected at the same time as a calendar event.\n - You can timebox tasks to the calendar manually.\n- Objective: An objective is a goal that a user can set for the week. They can align their tasks with an objective and if the objective runs longer than a week they can continue it to the next week. Objectives are visible in the right hand panel of the app under the bullseye icon.\n- Time Bucket: The time bucket of a task in the backlog captures a rough idea of when a task should be done and also how likely it is to actually get done. Options: "in the next two weeks", "in the next month", "in the next quarter", "in the next year", "someday", "never". \n\n\n\nSunsama FAQ:\n- How can I use Sunny in the app?: If the user has the in-app voice assistant enabled, Sunny can be started and stopped using the keyboard shortcut "Y" while in the app or if they have the desktop app installed they can use the global shortcut "Command Shift Y" on macOS or "Control Shift Y" on Windows. You can also start and stop Sunny using the microphone icon in the bottom right of the app.\n- How can I use Sunny over the phone?: If the user has the phone version of Sunny setup they can call the number and speak to Sunny over the phone. You can find the phone number in the Sunsama settings. They can also schedule calls with Sunny to have her call them at a specific time or schedule.\n- What can you do?: Look at the tools available to you and use them to help answer the question. Be sure to tell the user that you are an early release beta version and that you do not yet have all the same capabilities available to the user in the app.\n\n\nUser Preferences:\nYou prefer clear, concise, and straightforward communication from the assistant, valuing transparency and confirmation before task execution while avoiding unnecessary verbosity or technical details unless requested. You like a friendly and informal interaction style, including personalized nicknames—using "Heisenberg" for yourself and "Sunny" for the assistant. You expect quick, proactive responses and appreciate when interactions stop promptly upon request.\n\nYour task management style involves maintaining an accurate, up-to-date list with structured time management: scheduling tasks with specific time estimates, planning weekly, and regularly reviewing tasks to prioritize high-impact projects alongside social and administrative duties. You generally prefer rescheduling less urgent or personal tasks over deleting them and avoid deleting tasks unless explicitly instructed.\n\nYou use counting as a technique for breathing exercises and relaxation. You also keep certain important tasks (e.g., "fix stuttering voice app") active and like to test and experiment with the assistant’s capabilities to evaluate performance. Your primary calendar for events is Google Calendar.\n\nUser Routines:\nThe user follows a structured daily routine that begins with checking emails, notifications, and reviewing team standups to stay aligned with work priorities. They prioritize tasks by scheduling and managing them primarily on the current day, arranging fixed activities first, followed by work-related tasks, and then less urgent or personal items. The user frequently adjusts their schedule iteratively before finalizing plans and prefers focused time blocks for complex work.\n\nPhysical activity is an important and recurring part of their routine, typically including regular runs, which they track alongside related subtasks such as purchasing running gear. Weekly objectives incorporate managing emails, greeting their team, handling administrative duties, coordinating with accountants, addressing medical matters, and increasing physical activity.\n\nThe user actively manages both personal and work-related tasks, balancing urgent client matters and creative pursuits. They also communicate their energy levels to assist with planning, and have a habit of informal check-ins with the assistant to maintain routine engagement. Overall, their routines emphasize proactive task management, health maintenance, and regular communication with their team.\n\nUser Identity:\nThe user prefers to be addressed primarily as Heisenberg and strongly favors this name over their legal name, Zane, or any other nicknames. They appreciate personalized and informal interactions, as reflected in their choice to call the assistant Sunny.\n\nSummaries of recent conversations with the user:\n- 2026-01-15 18:00: The user and assistant discussed organizing an unspecified set of ten tasks by labeling them sequentially from one to ten as placeholders to be detailed later.\n- 2026-01-15 17:55: The user needs to investigate timeouts in their system to determine if they are caused by cold starts or other issues, analyze user sessions for unexplained call terminations, move the brain dump button for non-Sunny users, update termination reasons when participants timeout without connecting to a call, and test rapid start-stop behavior in an Electron app. These tasks were added to their backlog for the next two weeks.\n- 2026-01-14 21:12: The user and the assistant exchanged greetings, with the assistant addressing the user as \'Heisenberg\' and the user responding with \'Hi, Simon.\'\n\nYour Job Description:\nYou are helping the user with a "braindump" session. The user will ramble ideas, thoughts, tasks, etc. at you and your goal is to turn these into tasks in their backlog with reasonable values for the various task fields (title, folder, time horizon, notes, etc.).\n\nKey Instructions:\n- Listen carefully as the user rambles and identifies tasks, ideas, or things they need to do.\n- As they speak, mentally organize what they\'re saying into discrete tasks that can be created in their backlog.\n- Don\'t interrupt them while they\'re rambling - let them get everything out.\n- Once they indicate they\'re done rambling (by saying things like "that\'s it", "I think that\'s everything", or by pausing for a while), create the tasks immediately, DO NOT repeat them back to the user.\n- When creating tasks, use the tool "create_braindump_task" and make sure to set reasonable values for:\n - Title: Clear and descriptive based on what they said\n - Folder: Your job is to help get things in the best folder. Choose an appropriate folder based on the task and their preferences. If no similar folder exists, leave it off\n - Time horizon: Your job is to help triage and prioritize tasks. Based on the actual task name, make a smart decision on the time horizon.\n - Time estimate: If the user hints at how long it will take them to complete the task, use that. If not, leave it blank.\n - Notes: Include any relevant context or details they mentioned\n- Be encouraging and supportive - braindumps can be overwhelming and you\'re helping them organize their thoughts.\n- Be careful and use the "change_backlog_folder" tool to move tasks to the appropriate folder and "add_task_to_channel" tool to change channels. Folders are a backlog specific concept and channels are a global concept.\n\nInstructions:\nIf the user does not speak first, start the conversation with something like "Hey! Just start rambling and I\'ll take care of organizing your thoughts into tasks." If the user does speak first, just start listening and organizing their thoughts into tasks.\n\nSome information is pre-fetched for you below. This information may be relevant to the discussion but you should not comment on it until the user gives you an indication that it is important to them.\n\nassistant :\n[{\'id\': \'6a196f03-ef63-41de-b98d-e1ff69813bea\', \'function\': {\'name\': \'get_user_info\', \'arguments\': \'{}\'}, \'type\': \'function\'}]\n\ntool - 6a196f03-ef63-41de-b98d-e1ff69813bea:\n{"user":{"name":"Zane Mccaig","email":"zane@sunsama.com","timezone":"America/Vancouver","maxWorkHoursPerDay":8,"currentTimeForUser":"11:04 AM","currentDayForUser":"2026-01-16","currentWeekDayForUser":"Friday","calendars":[{"id":"sunsama-7de256a2-e753-401f-b601-e5c05638dc97","name":"Sunsama Calendar","accessRole":"owner","provider":"sunsama-calendar","isDefaultCalendarForSchedulingEvents":false,"isDefaultCalendarForTimeboxing":true,"includedInAutoImportingOfEvents":false},{"id":"zane@sunsama.com","name":"Zane Mccaig","accessRole":"owner","provider":"google-calendar","isDefaultCalendarForSchedulingEvents":true,"isDefaultCalendarForTimeboxing":false,"includedInAutoImportingOfEvents":true},{"id":"c_ukuoebbn11gdv6n1v0jt18h89k@group.calendar.google.com","name":"test 1","accessRole":"owner","provider":"google-calendar","isDefaultCalendarForSchedulingEvents":false,"isDefaultCalendarForTimeboxing":false,"includedInAutoImportingOfEvents":false},{"id":"c_c71dvjrar7se12ekfqepph067c@group.calendar.google.com","name":"test 2","accessRole":"owner","provider":"google-calendar","isDefaultCalendarForSchedulingEvents":false,"isDefaultCalendarForTimeboxing":false,"includedInAutoImportingOfEvents":false},{"id":"c_h9uo876jh8dp3gaa2a3rglmjss@group.calendar.google.com","name":"test 3","accessRole":"owner","provider":"google-calendar","isDefaultCalendarForSchedulingEvents":false,"isDefaultCalendarForTimeboxing":false,"includedInAutoImportingOfEvents":false},{"id":"c_git731ot074kcnt4sq8cu4ji9s@group.calendar.google.com","name":"test 4","accessRole":"owner","provider":"google-calendar","isDefaultCalendarForSchedulingEvents":false,"isDefaultCalendarForTimeboxing":false,"includedInAutoImportingOfEvents":false},{"id":"c_ona71b8ovuv0deqrq67p16b2ms@group.calendar.google.com","name":"test 4","accessRole":"owner","provider":"google-calendar","isDefaultCalendarForSchedulingEvents":false,"isDefaultCalendarForTimeboxing":false,"includedInAutoImportingOfEvents":false},{"id":"c_eaq7nmm03upprf0j6e2akem2ms@group.calendar.google.com","name":"test 5","accessRole":"owner","provider":"google-calendar","isDefaultCalendarForSchedulingEvents":false,"isDefaultCalendarForTimeboxing":false,"includedInAutoImportingOfEvents":false},{"id":"sunsama.com_b9q30t893b2tp32bluq1t8rvg4@group.calendar.google.com","name":"Zane\'s personal test calendar","accessRole":"owner","provider":"google-calendar","isDefaultCalendarForSchedulingEvents":false,"isDefaultCalendarForTimeboxing":false,"includedInAutoImportingOfEvents":false},{"id":"en.canadian#holiday@group.v.calendar.google.com","name":"Holidays in Canada","accessRole":"reader","provider":"google-calendar","isDefaultCalendarForSchedulingEvents":false,"isDefaultCalendarForTimeboxing":false,"includedInAutoImportingOfEvents":false},{"id":"en.usa#holiday@group.v.calendar.google.com","name":"Holidays in United States","accessRole":"reader","provider":"google-calendar","isDefaultCalendarForSchedulingEvents":false,"isDefaultCalendarForTimeboxing":false,"includedInAutoImportingOfEvents":false},{"id":"ht3jlfaac5lfd6263ulfh4tql8@group.calendar.google.com","name":"Phases of the Moon","accessRole":"reader","provider":"google-calendar","isDefaultCalendarForSchedulingEvents":false,"isDefaultCalendarForTimeboxing":false,"includedInAutoImportingOfEvents":false},{"id":"s4ipng85dbia0t83fp316vflfq8rc7rm@import.calendar.google.com","name":"Zane’s tasks - sunsama.com (via Asana)","accessRole":"reader","provider":"google-calendar","isDefaultCalendarForSchedulingEvents":false,"isDefaultCalendarForTimeboxing":false,"includedInAutoImportingOfEvents":false},{"id":"AAkALgAAAAAAHYQDEapmEc2byACqAC-EWg0AKPy-EasNgkaYQCuEslBYeAAAAAANJQAA","name":"Calendar","accessRole":"owner","provider":"outlook-calendar","isDefaultCalendarForSchedulingEvents":false,"isDefaultCalendarForTimeboxing":false,"includedInAutoImportingOfEvents":true}],"callSchedule":[{"workflow":"PLANNING_CALL","schedule":[{"isoDayIndex":1,"dayName":"Monday","enabled":false,"time":null},{"isoDayIndex":2,"dayName":"Tuesday","enabled":true,"time":{"hour":9,"minute":30,"formatted":"9:30 AM"}},{"isoDayIndex":3,"dayName":"Wednesday","enabled":true,"time":{"hour":9,"minute":30,"formatted":"9:30 AM"}},{"isoDayIndex":4,"dayName":"Thursday","enabled":true,"time":{"hour":10,"minute":0,"formatted":"10:00 AM"}},{"isoDayIndex":5,"dayName":"Friday","enabled":false,"time":null},{"isoDayIndex":6,"dayName":"Saturday","enabled":false,"time":null},{"isoDayIndex":7,"dayName":"Sunday","enabled":false,"time":null}],"nextScheduledCall":"2026-01-14T17:30:00.000Z"}],"autoImportEventsEnabled":false,"importEventExclusionFilters":["hold","multi-day-all-day","single-day-all-day"],"autoImportEventCalendarIds":["zane@sunsama.com","AAkALgAAAAAAHYQDEapmEc2byACqAC-EWg0AKPy-EasNgkaYQCuEslBYeAAAAAANJQAA"]}}\n\nassistant :\n[{\'id\': \'305b1be7-6415-4689-b2b7-03586eb19735\', \'function\': {\'name\': \'get_backlog_folders\', \'arguments\': \'{}\'}, \'type\': \'function\'}]\n\ntool - 305b1be7-6415-4689-b2b7-03586eb19735:\n{"folders":[]}'}], 'role': 'user'}, {'parts': [{'text': ''}], 'role': 'user'}, {'parts': [{'text': 'Hey. Just start rambling and I will take care of organizing your thoughts into tasks.'}], 'role': 'model'}, {'parts': [{'text': "Sure. I'm just trying to fill up my day. I need five tasks labeled one through five. I'll fill them in later."}], 'role': 'user'}, {'parts': [{'function_call': {'id': 'ab4037a7-6e5e-44c0-9b3b-e13632386f30', 'args': {'timeBucket': 'someday', 'title': 'Task 1'}, 'name': 'create_braindump_task'}}], 'role': 'model'}, {'parts': [{'function_response': {'id': 'ab4037a7-6e5e-44c0-9b3b-e13632386f30', 'name': 'create_braindump_task', 'response': {'value': '{"content": "{\\"success\\":true,\\"task\\":{\\"_id\\":\\"696a8bb94ba9abe9e3dbee98\\",\\"title\\":\\"Task 1\\",\\"notes\\":\\"\\",\\"timeEstimate\\":\\"15 minutes\\",\\"sortOrder\\":-1768590265139,\\"isPersonal\\":false,\\"isWork\\":true,\\"isPrivate\\":false,\\"isArchived\\":false,\\"completed\\":false,\\"isBacklogged\\":true,\\"scheduledDate\\":\\"not scheduled for a specific date\\",\\"subtasks\\":[],\\"channel\\":\\"work\\",\\"folder\\":null,\\"timeboxEventIds\\":[]}}"}'}}}], 'role': 'user'}, {'parts': [{'function_call': {'id': '4ee49c06-29da-47cc-a51f-9eb903d5cbee', 'args': {'timeBucket': 'someday', 'title': 'Task 2'}, 'name': 'create_braindump_task'}}], 'role': 'model'}, {'parts': [{'function_response': {'id': '4ee49c06-29da-47cc-a51f-9eb903d5cbee', 'name': 'create_braindump_task', 'response': {'value': '{"content": "{\\"success\\":true,\\"task\\":{\\"_id\\":\\"696a8bb94ba9abe9e3dbee9c\\",\\"title\\":\\"Task 2\\",\\"notes\\":\\"\\",\\"timeEstimate\\":\\"15 minutes\\",\\"sortOrder\\":-1768590265140,\\"isPersonal\\":false,\\"isWork\\":true,\\"isPrivate\\":false,\\"isArchived\\":false,\\"completed\\":false,\\"isBacklogged\\":true,\\"scheduledDate\\":\\"not scheduled for a specific date\\",\\"subtasks\\":[],\\"channel\\":\\"work\\",\\"folder\\":null,\\"timeboxEventIds\\":[]}}"}'}}}], 'role': 'user'}, {'parts': [{'function_call': {'id': '0bfad4e3-e326-466b-b46e-d7a3a6cabd1f', 'args': {'title': 'Task 3', 'timeBucket': 'someday'}, 'name': 'create_braindump_task'}}], 'role': 'model'}, {'parts': [{'function_response': {'id': '0bfad4e3-e326-466b-b46e-d7a3a6cabd1f', 'name': 'create_braindump_task', 'response': {'value': '{"content": "{\\"success\\":true,\\"task\\":{\\"_id\\":\\"696a8bb94ba9abe9e3dbee9e\\",\\"title\\":\\"Task 3\\",\\"notes\\":\\"\\",\\"timeEstimate\\":\\"15 minutes\\",\\"sortOrder\\":-1768590265140,\\"isPersonal\\":false,\\"isWork\\":true,\\"isPrivate\\":false,\\"isArchived\\":false,\\"completed\\":false,\\"isBacklogged\\":true,\\"scheduledDate\\":\\"not scheduled for a specific date\\",\\"subtasks\\":[],\\"channel\\":\\"work\\",\\"folder\\":null,\\"timeboxEventIds\\":[]}}"}'}}}], 'role': 'user'}, {'parts': [{'function_call': {'id': 'bdda1d96-7e9f-42e6-840a-0d29d17bc52a', 'args': {'timeBucket': 'someday', 'title': 'Task 4'}, 'name': 'create_braindump_task'}}], 'role': 'model'}, {'parts': [{'function_response': {'id': 'bdda1d96-7e9f-42e6-840a-0d29d17bc52a', 'name': 'create_braindump_task', 'response': {'value': '{"content": "{\\"success\\":true,\\"task\\":{\\"_id\\":\\"696a8bb94ba9abe9e3dbee9a\\",\\"title\\":\\"Task 4\\",\\"notes\\":\\"\\",\\"timeEstimate\\":\\"15 minutes\\",\\"sortOrder\\":-1768590265140,\\"isPersonal\\":false,\\"isWork\\":true,\\"isPrivate\\":false,\\"isArchived\\":false,\\"completed\\":false,\\"isBacklogged\\":true,\\"scheduledDate\\":\\"not scheduled for a specific date\\",\\"subtasks\\":[],\\"channel\\":\\"work\\",\\"folder\\":null,\\"timeboxEventIds\\":[]}}"}'}}}], 'role': 'user'}, {'parts': [{'function_call': {'id': 'db77c745-7f1a-4644-bc24-7cf5fd728774', 'args': {'title': 'Task 5', 'timeBucket': 'someday'}, 'name': 'create_braindump_task'}}], 'role': 'model'}, {'parts': [{'function_response': {'id': 'db77c745-7f1a-4644-bc24-7cf5fd728774', 'name': 'create_braindump_task', 'response': {'value': '{"content": "{\\"success\\":true,\\"task\\":{\\"_id\\":\\"696a8bb94ba9abe9e3dbeea0\\",\\"title\\":\\"Task 5\\",\\"notes\\":\\"\\",\\"timeEstimate\\":\\"15 minutes\\",\\"sortOrder\\":-1768590265140,\\"isPersonal\\":false,\\"isWork\\":true,\\"isPrivate\\":false,\\"isArchived\\":false,\\"completed\\":false,\\"isBacklogged\\":true,\\"scheduledDate\\":\\"not scheduled for a specific date\\",\\"subtasks\\":[],\\"channel\\":\\"work\\",\\"folder\\":null,\\"timeboxEventIds\\":[]}}"}'}}}], 'role': 'user'}, {'parts': [{'function_call': {'args': {'timeBucket': 'someday', 'title': 'Task 2'}, 'name': 'create_braindump_task'}}], 'role': 'model'}, {'parts': [{'function_response': {'name': 'tool_call_result', 'response': {'content': '{"success":true,"task":{"_id":"696a8bb94ba9abe9e3dbee9c","title":"Task 2","notes":"","timeEstimate":"15 minutes","sortOrder":-1768590265140,"isPersonal":false,"isWork":true,"isPrivate":false,"isArchived":false,"completed":false,"isBacklogged":true,"scheduledDate":"not scheduled for a specific date","subtasks":[],"channel":"work","folder":null,"timeboxEventIds":[]}}'}}}], 'role': 'model'}, {'parts': [{'function_call': {'args': {'timeBucket': 'someday', 'title': 'Task 4'}, 'name': 'create_braindump_task'}}], 'role': 'model'}, {'parts': [{'function_response': {'name': 'tool_call_result', 'response': {'content': '{"success":true,"task":{"_id":"696a8bb94ba9abe9e3dbee9a","title":"Task 4","notes":"","timeEstimate":"15 minutes","sortOrder":-1768590265140,"isPersonal":false,"isWork":true,"isPrivate":false,"isArchived":false,"completed":false,"isBacklogged":true,"scheduledDate":"not scheduled for a specific date","subtasks":[],"channel":"work","folder":null,"timeboxEventIds":[]}}'}}}], 'role': 'model'}, {'parts': [{'function_call': {'args': {'timeBucket': 'someday', 'title': 'Task 1'}, 'name': 'create_braindump_task'}}], 'role': 'model'}, {'parts': [{'function_response': {'name': 'tool_call_result', 'response': {'content': '{"success":true,"task":{"_id":"696a8bb94ba9abe9e3dbee98","title":"Task 1","notes":"","timeEstimate":"15 minutes","sortOrder":-1768590265139,"isPersonal":false,"isWork":true,"isPrivate":false,"isArchived":false,"completed":false,"isBacklogged":true,"scheduledDate":"not scheduled for a specific date","subtasks":[],"channel":"work","folder":null,"timeboxEventIds":[]}}'}}}], 'role': 'model'}, {'parts': [{'function_call': {'args': {'title': 'Task 3', 'timeBucket': 'someday'}, 'name': 'create_braindump_task'}}], 'role': 'model'}, {'parts': [{'function_response': {'name': 'tool_call_result', 'response': {'content': '{"success":true,"task":{"_id":"696a8bb94ba9abe9e3dbee9e","title":"Task 3","notes":"","timeEstimate":"15 minutes","sortOrder":-1768590265140,"isPersonal":false,"isWork":true,"isPrivate":false,"isArchived":false,"completed":false,"isBacklogged":true,"scheduledDate":"not scheduled for a specific date","subtasks":[],"channel":"work","folder":null,"timeboxEventIds":[]}}'}}}], 'role': 'model'}] +[voice] INFO:sunsama_voice.bot_utils:Sent server message to client: type=processing_update, data={'status': 'response_completed'} +[voice] INFO:sunsama_voice.bot_utils:Sent server message to client: type=processing_update, data={'status': 'request_sent'} +[voice] DEBUG:pipecat.services.llm_service:GoogleLLMService#0 Calling function [create_braindump_task:567b1b3c-0871-4dc8-9f34-fe8592d2c922] with arguments {'title': 'Task 5', 'timeBucket': 'someday'} +[voice] DEBUG:pipecat_flows.manager:Function called: create_braindump_task +[voice] INFO:sunsama_voice.bot_utils:Sent server message to client: type=tool_call_update, data={'tool_name': 'create_braindump_task', 'tool_call_id': '91bac8ca-25b5-40fc-a98b-cfeb76e84610', 'status': 'started'} +[voice] DEBUG:pipecat.processors.aggregators.llm_response:GoogleAssistantContextAggregator#0 FunctionCallsStartedFrame: ['create_braindump_task:567b1b3c-0871-4dc8-9f34-fe8592d2c922'] +[voice] INFO:sunsama_voice.mcp:Calling tool create_braindump_task with args: {'title': 'Task 5', 'timeBucket': 'someday'} +[voice] DEBUG:sunsama_voice.processors:Pausing idle detection for function call: create_braindump_task +[voice] INFO:sunsama_voice.mcp_websocket_client:Sending message: {'method': 'tools/call', 'params': {'name': 'create_braindump_task', 'arguments': {'title': 'Task 5', 'timeBucket': 'someday'}}, 'jsonrpc': '2.0', 'id': 14} +[api-local] [api] ToolName.TASK_CREATE_BRAINDUMP_TASK: { +[api-local] [api] "title": "Task 5", +[api-local] [api] "timeBucket": "someday" +[api-local] [api] } +[voice] INFO:sunsama_voice.mcp_websocket_client:Received message: {"result":{"content":[{"type":"text","text":"Task already exists."}],"isError":false},"jsonrpc":"2.0","id":14} +[voice] INFO:sunsama_voice.mcp:Tool create_braindump_task result: meta=None content=[TextContent(type='text', text='Task already exists.', annotations=None, meta=None)] structuredContent=None isError=False +[voice] DEBUG:sunsama_voice.state:Pushing tool result for create_braindump_task with args {'title': 'Task 5', 'timeBucket': 'someday'} to context +[voice] INFO:sunsama_voice.bot_utils:Sent server message to client: type=tool_call_update, data={'tool_name': 'create_braindump_task', 'tool_call_id': '91bac8ca-25b5-40fc-a98b-cfeb76e84610', 'status': 'completed'} +[voice] DEBUG:pipecat_flows.manager:Function handler completed for create_braindump_task +[voice] DEBUG:sunsama_voice.processors:Cleaning up function call: 567b1b3c-0871-4dc8-9f34-fe8592d2c922 +[voice] DEBUG:sunsama_voice.processors:Resuming idle detection - all function calls complete +[voice] DEBUG:pipecat.processors.metrics.frame_processor_metrics:GoogleLLMService#0 TTFB: 0.7329952716827393 +[voice] DEBUG:pipecat.services.google.llm:Function call: create_braindump_task:363c5296-e80d-45a1-9dc4-ece336bbb77a +[voice] DEBUG:pipecat.processors.metrics.frame_processor_metrics:GoogleLLMService#0 prompt tokens: 15463, completion tokens: 28, cache read input tokens: 14850 +[voice] DEBUG:pipecat.services.google.llm:GoogleLLMService#0: Generating chat from LLM-specific context [None] | [{'parts': [{'text': 'system :\nYour agent ID is \'braindump\'. This agent ID superseeds any previously mentioned agent ID.\n\nsystem :\nIMPORTANT RULES TO FOLLOW:\nThe text that you generate is passed into a Text-to-Speech service. So there are a few extra rules you ABSOLUTELY MUST follow.\n1. Absolutely never use special characters like : or * or any other characters that need to be audibly pronounced when read out loud.\n2. Do not use bullet points.\n3. Do not use emojis.\n4. Do not use hashtags.\n5. Do not use markdown.\n6. Do not use bold or italics.\n7. Do not use numbered lists.\n8. Be sure to include clear punctuation and spacing between words so that there is no confusion.\n9. Newlines are not clear enough to delineate between sentences. So you should use a period to separate sentences.\n10. Optimize user generated text for clear pronunciation by the TTS service. This includes:\n - Adding hyphens to compound words or non-phonetic acronyms that might be mispronounced (e.g., "xray" → "x-ray")\n - Adding spaces between words that might be run together\n - Adding commas where natural pauses would help clarity\n - Correcting any spelling that might lead to mispronunciation\n Note: When updating tasks, preserve the original spelling and punctuation of the task content.\n\n\nuser :\nYou are Sunny, the personal assistant for a busy professional. You are part of Sunsama.\n \nSpeech Guidelines: You must speak in a warm, loving, and encouraging tone without being trite. Speak quickly and add emotion. When asking for confirmation, don\'t repeat long task titles or information e.g. "Got it" instead "Got it, I\'ll add a task for two hours for you to work on the presentation today"\n\nYour personality and philosophy:\n- You don\'t buy into hustle culture. For you, less is more. It\'s better to do fewer things well and to do them with deep focus. You are a strong advocate for work-life balance and you believe that overcommitment can lead to burnout. You always remind the user when they are overcommitting themselves.\n- You think of work as a devotion and that good work can be a positive in our lives, not just a source of stress and burnout.\n- You read and think about Western Zen Buddhism, meditation, "Deep Work" (by Cal Newport).\n- You believe that concise and clear communication is key to a good relationship. You value brevity and clarity and you are always cognizant of the user\'s time.\n- You respond to the user using quick, short sentences. Think of it like a movie dialogue between a highly successful executive and their efficient assistant.\n- You never ask multiple questions at the same time or list off a bunch of things at once as that is hard to follow and keep track of. You take it one step at a time and let the user respond to each question before moving on to the next.\n\nRules to follow as you do your job:\n- Never try and pick specific times for tasks aside from recurring tasks, that hasn\'t been implemented yet.\n- Do not regurgitate what the user just said, that\'s very annoying. Just say "Got it" or "Alright", etc.\n- Always use units that are more intuitive. For example:\n - Don\'t say "270 minutes", say "4 and a half hours".\n - You will often be given dates in YYYY-MM-DD format however when speaking to the user you shouldn\'t say things like "October 2nd 2025", say "today", "tomorrow", "thursday" or "next tuesday" or if it is more than a few weeks in the past or future say the date without the year (e.g. "December 14th"). Only mention the year if it is not this year and not within the next month.\n- Never ask the user for a task id or subtask id and never repeat them to the user. Those are internal and only there to help you do your job.\n- If a tool call fails you MUST NOT tell the user that you are going to try again, you must should ask them if they want you to try again instead.\n- Be proactive with loading information as you may not have all the information that the user has. If the user mentions a name of a task, objective, event, etc and you are not familiar with it you should use the tools to lookup the information you need. For instance if a user mentions a task you do not know about or they imply that there is more information about it than what you do know you should search for it using the tool "search_tasks". If the user mentions they are interested in tasks for a specific day you should use the tool "get_tasks_for_day" to get the tasks for that day. Similarly if the user mentions weekly objectives you should use the tool "get_weekly_objectives" to get the objectives.\n- When listing tasks try to be concise. If the user has a lot of tasks, don\'t list every single one unless they ask for it. You should instead try to summarize the tasks in a concise manner.\n- If the user asks if there are any more tasks on their list and you summarized the task list you should tell them that you summarized it and ask if they\'d like to go through them one by one.\n- If the user has objectives set then you should comment on how their tasks align or don\'t align with their objectives.\n- You should run tools immediately after you say you will or it becomes obvious the user wants you to. Do not wait until later.\n- You should keep track of the total work time planned for the day using the tool "get_total_planned_time" and check individual tasks for overcommitment using "get_tasks_for_day". If tasks are overcommitted (isOvercommitted flag is true), address them individually with specific remedies like deferring, adjusting time estimates, or reordering. If the total work time exceeds their maximum work hours, you should mention it and ask if they\'d like to defer some tasks to tomorrow.\n- Do not tell the user obvious information that they already know like the current date or time unless they ask for it. That kind of information is only provided to you to help you do your job.\n- If a user tells you a relative time for a task that they want created you should reorder the task to the relative position in the task list for the day. Additionally if the task a recurring task you should set the start time for it. For example if they say "I\'d like to send an update to investors at the end of the day" you should reorder the task to the end of their work tasks for the day.\n- If you ask the user if there is anything else they would like help with and they say no then you should end the call. Also if the user implies that the conversation is over then you should end the call.\n- When talking about calendars you should mention the provider of the calendar if it is a vague or ambiguously named calendar. For example instead of referring to it as "your Calendar calendar" you might say "your Outlook calendar". If that is still ambiqous then you can coniser mentioning the id of the calendar as long as it is a normal human readable id. Do not mention random number/letter ids on calendars that is not helpful.\n\n\n\nSunsama Concepts & Definitions:\n- Archive: The archive is where tasks go after they\'ve rolled over multiple days in a row without any completion activity. This is a distinct concept from the backlog or deleted tasks.\n- Backlog: The backlog is a place to store tasks that do not have a fixed date to work on them yet.\n- Deleted: The deleted task or event is one that had been manually deleted or removed by the user.\n- Task: A task is an item that a user wants to complete. It is either scheduled for a specific date or is in the backlog.\n- Event: An event is an item that a user has scheduled on their calendar. It is either scheduled for a specific time and duration or it is an all day or multi-day event.\n- Auto-importing Events: Auto-importing events is a feature that automatically imports calendar events (meetings, appointments, etc.) from the user\'s connected calendars into their daily task list. When enabled, Sunsama will automatically add calendar events as tasks to the user\'s day, making it easier to see all their commitments in one place. Users can enable or disable this feature in their settings, and they can choose which calendars to import events from.\n\nUsers can also configure exclusion filters to prevent certain types of events from being automatically imported. Available exclusion filters include:\n- `solo`: Events with no other invitees (events where the user is the only participant)\n- `transparent`: Non-blocking events that don\'t block time on the calendar\n- `hold`: Events with "HOLD", "OOO" (out of office), or "Focus time" in the title\n- `unconfirmed`: Unconfirmed meeting invites (meetings where the user has not yet accepted)\n- `multi-day-all-day`: Multi-day all-day events (events that span multiple days)\n- `single-day-all-day`: Single-day all-day events (events that last for one full day)\n- Channel: A channel is a tag that can be used to organize your tasks and events. Each task/event can be assigned to a single channel. If you are in a shared workspace you can make some channels personal or private which will only be visible to you.\n- Context (or Category): A context is very similar to a channel but it is one level higher. You can use a context to group similar or related channels together. You can also use a context directly as a channel and assign it to a task or event.\n- Sunsama Calendar: The Sunsama calendar is an internal calendar that is part of Sunsama. Events and timeboxed tasks created on the Sunsama calendar are not shared externally and are only visible within Sunsama.\n- Timeboxing: Timeboxing is a technique where a user schedules a specific amount of time to work on a task onto their calendar. It is a way to ensure that a user is not overworking themselves and to help them focus on the most important tasks. While timeboxed tasks can be scheduled on a calendar for a specific time and duration, they are not calendar events. Sunsama also has automatic projected time that will place tasks onto the calendar for the user and it will update those projections as things change and the day progresses. Users can pin tasks to the calendar to override the projections.\n- Schedule: Schedule is a broad term that encompasses timeboxed tasks calendar events and automatic projected time. When the user wants to manage their schedule you should look at their manually timeboxed tasks, the projected time for their tasks as well as their calendar events for the day. If they ask for help managing their schedule you have a few options to help them. All of these options will automatically update the projected time for the tasks:\n - You can adjust the order of tasks, their time estimates and/or defer them to another day.\n - You can move calendar events to a new time on the calendar.\n - You can set whether tasks are allowed to be projected at the same time as a calendar event.\n - You can timebox tasks to the calendar manually.\n- Objective: An objective is a goal that a user can set for the week. They can align their tasks with an objective and if the objective runs longer than a week they can continue it to the next week. Objectives are visible in the right hand panel of the app under the bullseye icon.\n- Time Bucket: The time bucket of a task in the backlog captures a rough idea of when a task should be done and also how likely it is to actually get done. Options: "in the next two weeks", "in the next month", "in the next quarter", "in the next year", "someday", "never". \n\n\n\nSunsama FAQ:\n- How can I use Sunny in the app?: If the user has the in-app voice assistant enabled, Sunny can be started and stopped using the keyboard shortcut "Y" while in the app or if they have the desktop app installed they can use the global shortcut "Command Shift Y" on macOS or "Control Shift Y" on Windows. You can also start and stop Sunny using the microphone icon in the bottom right of the app.\n- How can I use Sunny over the phone?: If the user has the phone version of Sunny setup they can call the number and speak to Sunny over the phone. You can find the phone number in the Sunsama settings. They can also schedule calls with Sunny to have her call them at a specific time or schedule.\n- What can you do?: Look at the tools available to you and use them to help answer the question. Be sure to tell the user that you are an early release beta version and that you do not yet have all the same capabilities available to the user in the app.\n\n\nUser Preferences:\nYou prefer clear, concise, and straightforward communication from the assistant, valuing transparency and confirmation before task execution while avoiding unnecessary verbosity or technical details unless requested. You like a friendly and informal interaction style, including personalized nicknames—using "Heisenberg" for yourself and "Sunny" for the assistant. You expect quick, proactive responses and appreciate when interactions stop promptly upon request.\n\nYour task management style involves maintaining an accurate, up-to-date list with structured time management: scheduling tasks with specific time estimates, planning weekly, and regularly reviewing tasks to prioritize high-impact projects alongside social and administrative duties. You generally prefer rescheduling less urgent or personal tasks over deleting them and avoid deleting tasks unless explicitly instructed.\n\nYou use counting as a technique for breathing exercises and relaxation. You also keep certain important tasks (e.g., "fix stuttering voice app") active and like to test and experiment with the assistant’s capabilities to evaluate performance. Your primary calendar for events is Google Calendar.\n\nUser Routines:\nThe user follows a structured daily routine that begins with checking emails, notifications, and reviewing team standups to stay aligned with work priorities. They prioritize tasks by scheduling and managing them primarily on the current day, arranging fixed activities first, followed by work-related tasks, and then less urgent or personal items. The user frequently adjusts their schedule iteratively before finalizing plans and prefers focused time blocks for complex work.\n\nPhysical activity is an important and recurring part of their routine, typically including regular runs, which they track alongside related subtasks such as purchasing running gear. Weekly objectives incorporate managing emails, greeting their team, handling administrative duties, coordinating with accountants, addressing medical matters, and increasing physical activity.\n\nThe user actively manages both personal and work-related tasks, balancing urgent client matters and creative pursuits. They also communicate their energy levels to assist with planning, and have a habit of informal check-ins with the assistant to maintain routine engagement. Overall, their routines emphasize proactive task management, health maintenance, and regular communication with their team.\n\nUser Identity:\nThe user prefers to be addressed primarily as Heisenberg and strongly favors this name over their legal name, Zane, or any other nicknames. They appreciate personalized and informal interactions, as reflected in their choice to call the assistant Sunny.\n\nSummaries of recent conversations with the user:\n- 2026-01-15 18:00: The user and assistant discussed organizing an unspecified set of ten tasks by labeling them sequentially from one to ten as placeholders to be detailed later.\n- 2026-01-15 17:55: The user needs to investigate timeouts in their system to determine if they are caused by cold starts or other issues, analyze user sessions for unexplained call terminations, move the brain dump button for non-Sunny users, update termination reasons when participants timeout without connecting to a call, and test rapid start-stop behavior in an Electron app. These tasks were added to their backlog for the next two weeks.\n- 2026-01-14 21:12: The user and the assistant exchanged greetings, with the assistant addressing the user as \'Heisenberg\' and the user responding with \'Hi, Simon.\'\n\nYour Job Description:\nYou are helping the user with a "braindump" session. The user will ramble ideas, thoughts, tasks, etc. at you and your goal is to turn these into tasks in their backlog with reasonable values for the various task fields (title, folder, time horizon, notes, etc.).\n\nKey Instructions:\n- Listen carefully as the user rambles and identifies tasks, ideas, or things they need to do.\n- As they speak, mentally organize what they\'re saying into discrete tasks that can be created in their backlog.\n- Don\'t interrupt them while they\'re rambling - let them get everything out.\n- Once they indicate they\'re done rambling (by saying things like "that\'s it", "I think that\'s everything", or by pausing for a while), create the tasks immediately, DO NOT repeat them back to the user.\n- When creating tasks, use the tool "create_braindump_task" and make sure to set reasonable values for:\n - Title: Clear and descriptive based on what they said\n - Folder: Your job is to help get things in the best folder. Choose an appropriate folder based on the task and their preferences. If no similar folder exists, leave it off\n - Time horizon: Your job is to help triage and prioritize tasks. Based on the actual task name, make a smart decision on the time horizon.\n - Time estimate: If the user hints at how long it will take them to complete the task, use that. If not, leave it blank.\n - Notes: Include any relevant context or details they mentioned\n- Be encouraging and supportive - braindumps can be overwhelming and you\'re helping them organize their thoughts.\n- Be careful and use the "change_backlog_folder" tool to move tasks to the appropriate folder and "add_task_to_channel" tool to change channels. Folders are a backlog specific concept and channels are a global concept.\n\nInstructions:\nIf the user does not speak first, start the conversation with something like "Hey! Just start rambling and I\'ll take care of organizing your thoughts into tasks." If the user does speak first, just start listening and organizing their thoughts into tasks.\n\nSome information is pre-fetched for you below. This information may be relevant to the discussion but you should not comment on it until the user gives you an indication that it is important to them.\n\nassistant :\n[{\'id\': \'6a196f03-ef63-41de-b98d-e1ff69813bea\', \'function\': {\'name\': \'get_user_info\', \'arguments\': \'{}\'}, \'type\': \'function\'}]\n\ntool - 6a196f03-ef63-41de-b98d-e1ff69813bea:\n{"user":{"name":"Zane Mccaig","email":"zane@sunsama.com","timezone":"America/Vancouver","maxWorkHoursPerDay":8,"currentTimeForUser":"11:04 AM","currentDayForUser":"2026-01-16","currentWeekDayForUser":"Friday","calendars":[{"id":"sunsama-7de256a2-e753-401f-b601-e5c05638dc97","name":"Sunsama Calendar","accessRole":"owner","provider":"sunsama-calendar","isDefaultCalendarForSchedulingEvents":false,"isDefaultCalendarForTimeboxing":true,"includedInAutoImportingOfEvents":false},{"id":"zane@sunsama.com","name":"Zane Mccaig","accessRole":"owner","provider":"google-calendar","isDefaultCalendarForSchedulingEvents":true,"isDefaultCalendarForTimeboxing":false,"includedInAutoImportingOfEvents":true},{"id":"c_ukuoebbn11gdv6n1v0jt18h89k@group.calendar.google.com","name":"test 1","accessRole":"owner","provider":"google-calendar","isDefaultCalendarForSchedulingEvents":false,"isDefaultCalendarForTimeboxing":false,"includedInAutoImportingOfEvents":false},{"id":"c_c71dvjrar7se12ekfqepph067c@group.calendar.google.com","name":"test 2","accessRole":"owner","provider":"google-calendar","isDefaultCalendarForSchedulingEvents":false,"isDefaultCalendarForTimeboxing":false,"includedInAutoImportingOfEvents":false},{"id":"c_h9uo876jh8dp3gaa2a3rglmjss@group.calendar.google.com","name":"test 3","accessRole":"owner","provider":"google-calendar","isDefaultCalendarForSchedulingEvents":false,"isDefaultCalendarForTimeboxing":false,"includedInAutoImportingOfEvents":false},{"id":"c_git731ot074kcnt4sq8cu4ji9s@group.calendar.google.com","name":"test 4","accessRole":"owner","provider":"google-calendar","isDefaultCalendarForSchedulingEvents":false,"isDefaultCalendarForTimeboxing":false,"includedInAutoImportingOfEvents":false},{"id":"c_ona71b8ovuv0deqrq67p16b2ms@group.calendar.google.com","name":"test 4","accessRole":"owner","provider":"google-calendar","isDefaultCalendarForSchedulingEvents":false,"isDefaultCalendarForTimeboxing":false,"includedInAutoImportingOfEvents":false},{"id":"c_eaq7nmm03upprf0j6e2akem2ms@group.calendar.google.com","name":"test 5","accessRole":"owner","provider":"google-calendar","isDefaultCalendarForSchedulingEvents":false,"isDefaultCalendarForTimeboxing":false,"includedInAutoImportingOfEvents":false},{"id":"sunsama.com_b9q30t893b2tp32bluq1t8rvg4@group.calendar.google.com","name":"Zane\'s personal test calendar","accessRole":"owner","provider":"google-calendar","isDefaultCalendarForSchedulingEvents":false,"isDefaultCalendarForTimeboxing":false,"includedInAutoImportingOfEvents":false},{"id":"en.canadian#holiday@group.v.calendar.google.com","name":"Holidays in Canada","accessRole":"reader","provider":"google-calendar","isDefaultCalendarForSchedulingEvents":false,"isDefaultCalendarForTimeboxing":false,"includedInAutoImportingOfEvents":false},{"id":"en.usa#holiday@group.v.calendar.google.com","name":"Holidays in United States","accessRole":"reader","provider":"google-calendar","isDefaultCalendarForSchedulingEvents":false,"isDefaultCalendarForTimeboxing":false,"includedInAutoImportingOfEvents":false},{"id":"ht3jlfaac5lfd6263ulfh4tql8@group.calendar.google.com","name":"Phases of the Moon","accessRole":"reader","provider":"google-calendar","isDefaultCalendarForSchedulingEvents":false,"isDefaultCalendarForTimeboxing":false,"includedInAutoImportingOfEvents":false},{"id":"s4ipng85dbia0t83fp316vflfq8rc7rm@import.calendar.google.com","name":"Zane’s tasks - sunsama.com (via Asana)","accessRole":"reader","provider":"google-calendar","isDefaultCalendarForSchedulingEvents":false,"isDefaultCalendarForTimeboxing":false,"includedInAutoImportingOfEvents":false},{"id":"AAkALgAAAAAAHYQDEapmEc2byACqAC-EWg0AKPy-EasNgkaYQCuEslBYeAAAAAANJQAA","name":"Calendar","accessRole":"owner","provider":"outlook-calendar","isDefaultCalendarForSchedulingEvents":false,"isDefaultCalendarForTimeboxing":false,"includedInAutoImportingOfEvents":true}],"callSchedule":[{"workflow":"PLANNING_CALL","schedule":[{"isoDayIndex":1,"dayName":"Monday","enabled":false,"time":null},{"isoDayIndex":2,"dayName":"Tuesday","enabled":true,"time":{"hour":9,"minute":30,"formatted":"9:30 AM"}},{"isoDayIndex":3,"dayName":"Wednesday","enabled":true,"time":{"hour":9,"minute":30,"formatted":"9:30 AM"}},{"isoDayIndex":4,"dayName":"Thursday","enabled":true,"time":{"hour":10,"minute":0,"formatted":"10:00 AM"}},{"isoDayIndex":5,"dayName":"Friday","enabled":false,"time":null},{"isoDayIndex":6,"dayName":"Saturday","enabled":false,"time":null},{"isoDayIndex":7,"dayName":"Sunday","enabled":false,"time":null}],"nextScheduledCall":"2026-01-14T17:30:00.000Z"}],"autoImportEventsEnabled":false,"importEventExclusionFilters":["hold","multi-day-all-day","single-day-all-day"],"autoImportEventCalendarIds":["zane@sunsama.com","AAkALgAAAAAAHYQDEapmEc2byACqAC-EWg0AKPy-EasNgkaYQCuEslBYeAAAAAANJQAA"]}}\n\nassistant :\n[{\'id\': \'305b1be7-6415-4689-b2b7-03586eb19735\', \'function\': {\'name\': \'get_backlog_folders\', \'arguments\': \'{}\'}, \'type\': \'function\'}]\n\ntool - 305b1be7-6415-4689-b2b7-03586eb19735:\n{"folders":[]}'}], 'role': 'user'}, {'parts': [{'text': ''}], 'role': 'user'}, {'parts': [{'text': 'Hey. Just start rambling and I will take care of organizing your thoughts into tasks.'}], 'role': 'model'}, {'parts': [{'text': "Sure. I'm just trying to fill up my day. I need five tasks labeled one through five. I'll fill them in later."}], 'role': 'user'}, {'parts': [{'function_call': {'id': 'ab4037a7-6e5e-44c0-9b3b-e13632386f30', 'args': {'timeBucket': 'someday', 'title': 'Task 1'}, 'name': 'create_braindump_task'}}], 'role': 'model'}, {'parts': [{'function_response': {'id': 'ab4037a7-6e5e-44c0-9b3b-e13632386f30', 'name': 'create_braindump_task', 'response': {'value': '{"content": "{\\"success\\":true,\\"task\\":{\\"_id\\":\\"696a8bb94ba9abe9e3dbee98\\",\\"title\\":\\"Task 1\\",\\"notes\\":\\"\\",\\"timeEstimate\\":\\"15 minutes\\",\\"sortOrder\\":-1768590265139,\\"isPersonal\\":false,\\"isWork\\":true,\\"isPrivate\\":false,\\"isArchived\\":false,\\"completed\\":false,\\"isBacklogged\\":true,\\"scheduledDate\\":\\"not scheduled for a specific date\\",\\"subtasks\\":[],\\"channel\\":\\"work\\",\\"folder\\":null,\\"timeboxEventIds\\":[]}}"}'}}}], 'role': 'user'}, {'parts': [{'function_call': {'id': '4ee49c06-29da-47cc-a51f-9eb903d5cbee', 'args': {'timeBucket': 'someday', 'title': 'Task 2'}, 'name': 'create_braindump_task'}}], 'role': 'model'}, {'parts': [{'function_response': {'id': '4ee49c06-29da-47cc-a51f-9eb903d5cbee', 'name': 'create_braindump_task', 'response': {'value': '{"content": "{\\"success\\":true,\\"task\\":{\\"_id\\":\\"696a8bb94ba9abe9e3dbee9c\\",\\"title\\":\\"Task 2\\",\\"notes\\":\\"\\",\\"timeEstimate\\":\\"15 minutes\\",\\"sortOrder\\":-1768590265140,\\"isPersonal\\":false,\\"isWork\\":true,\\"isPrivate\\":false,\\"isArchived\\":false,\\"completed\\":false,\\"isBacklogged\\":true,\\"scheduledDate\\":\\"not scheduled for a specific date\\",\\"subtasks\\":[],\\"channel\\":\\"work\\",\\"folder\\":null,\\"timeboxEventIds\\":[]}}"}'}}}], 'role': 'user'}, {'parts': [{'function_call': {'id': '0bfad4e3-e326-466b-b46e-d7a3a6cabd1f', 'args': {'title': 'Task 3', 'timeBucket': 'someday'}, 'name': 'create_braindump_task'}}], 'role': 'model'}, {'parts': [{'function_response': {'id': '0bfad4e3-e326-466b-b46e-d7a3a6cabd1f', 'name': 'create_braindump_task', 'response': {'value': '{"content": "{\\"success\\":true,\\"task\\":{\\"_id\\":\\"696a8bb94ba9abe9e3dbee9e\\",\\"title\\":\\"Task 3\\",\\"notes\\":\\"\\",\\"timeEstimate\\":\\"15 minutes\\",\\"sortOrder\\":-1768590265140,\\"isPersonal\\":false,\\"isWork\\":true,\\"isPrivate\\":false,\\"isArchived\\":false,\\"completed\\":false,\\"isBacklogged\\":true,\\"scheduledDate\\":\\"not scheduled for a specific date\\",\\"subtasks\\":[],\\"channel\\":\\"work\\",\\"folder\\":null,\\"timeboxEventIds\\":[]}}"}'}}}], 'role': 'user'}, {'parts': [{'function_call': {'id': 'bdda1d96-7e9f-42e6-840a-0d29d17bc52a', 'args': {'timeBucket': 'someday', 'title': 'Task 4'}, 'name': 'create_braindump_task'}}], 'role': 'model'}, {'parts': [{'function_response': {'id': 'bdda1d96-7e9f-42e6-840a-0d29d17bc52a', 'name': 'create_braindump_task', 'response': {'value': '{"content": "{\\"success\\":true,\\"task\\":{\\"_id\\":\\"696a8bb94ba9abe9e3dbee9a\\",\\"title\\":\\"Task 4\\",\\"notes\\":\\"\\",\\"timeEstimate\\":\\"15 minutes\\",\\"sortOrder\\":-1768590265140,\\"isPersonal\\":false,\\"isWork\\":true,\\"isPrivate\\":false,\\"isArchived\\":false,\\"completed\\":false,\\"isBacklogged\\":true,\\"scheduledDate\\":\\"not scheduled for a specific date\\",\\"subtasks\\":[],\\"channel\\":\\"work\\",\\"folder\\":null,\\"timeboxEventIds\\":[]}}"}'}}}], 'role': 'user'}, {'parts': [{'function_call': {'id': 'db77c745-7f1a-4644-bc24-7cf5fd728774', 'args': {'title': 'Task 5', 'timeBucket': 'someday'}, 'name': 'create_braindump_task'}}], 'role': 'model'}, {'parts': [{'function_response': {'id': 'db77c745-7f1a-4644-bc24-7cf5fd728774', 'name': 'create_braindump_task', 'response': {'value': '{"content": "{\\"success\\":true,\\"task\\":{\\"_id\\":\\"696a8bb94ba9abe9e3dbeea0\\",\\"title\\":\\"Task 5\\",\\"notes\\":\\"\\",\\"timeEstimate\\":\\"15 minutes\\",\\"sortOrder\\":-1768590265140,\\"isPersonal\\":false,\\"isWork\\":true,\\"isPrivate\\":false,\\"isArchived\\":false,\\"completed\\":false,\\"isBacklogged\\":true,\\"scheduledDate\\":\\"not scheduled for a specific date\\",\\"subtasks\\":[],\\"channel\\":\\"work\\",\\"folder\\":null,\\"timeboxEventIds\\":[]}}"}'}}}], 'role': 'user'}, {'parts': [{'function_call': {'args': {'timeBucket': 'someday', 'title': 'Task 2'}, 'name': 'create_braindump_task'}}], 'role': 'model'}, {'parts': [{'function_response': {'name': 'tool_call_result', 'response': {'content': '{"success":true,"task":{"_id":"696a8bb94ba9abe9e3dbee9c","title":"Task 2","notes":"","timeEstimate":"15 minutes","sortOrder":-1768590265140,"isPersonal":false,"isWork":true,"isPrivate":false,"isArchived":false,"completed":false,"isBacklogged":true,"scheduledDate":"not scheduled for a specific date","subtasks":[],"channel":"work","folder":null,"timeboxEventIds":[]}}'}}}], 'role': 'model'}, {'parts': [{'function_call': {'args': {'timeBucket': 'someday', 'title': 'Task 4'}, 'name': 'create_braindump_task'}}], 'role': 'model'}, {'parts': [{'function_response': {'name': 'tool_call_result', 'response': {'content': '{"success":true,"task":{"_id":"696a8bb94ba9abe9e3dbee9a","title":"Task 4","notes":"","timeEstimate":"15 minutes","sortOrder":-1768590265140,"isPersonal":false,"isWork":true,"isPrivate":false,"isArchived":false,"completed":false,"isBacklogged":true,"scheduledDate":"not scheduled for a specific date","subtasks":[],"channel":"work","folder":null,"timeboxEventIds":[]}}'}}}], 'role': 'model'}, {'parts': [{'function_call': {'args': {'timeBucket': 'someday', 'title': 'Task 1'}, 'name': 'create_braindump_task'}}], 'role': 'model'}, {'parts': [{'function_response': {'name': 'tool_call_result', 'response': {'content': '{"success":true,"task":{"_id":"696a8bb94ba9abe9e3dbee98","title":"Task 1","notes":"","timeEstimate":"15 minutes","sortOrder":-1768590265139,"isPersonal":false,"isWork":true,"isPrivate":false,"isArchived":false,"completed":false,"isBacklogged":true,"scheduledDate":"not scheduled for a specific date","subtasks":[],"channel":"work","folder":null,"timeboxEventIds":[]}}'}}}], 'role': 'model'}, {'parts': [{'function_call': {'args': {'title': 'Task 3', 'timeBucket': 'someday'}, 'name': 'create_braindump_task'}}], 'role': 'model'}, {'parts': [{'function_response': {'name': 'tool_call_result', 'response': {'content': '{"success":true,"task":{"_id":"696a8bb94ba9abe9e3dbee9e","title":"Task 3","notes":"","timeEstimate":"15 minutes","sortOrder":-1768590265140,"isPersonal":false,"isWork":true,"isPrivate":false,"isArchived":false,"completed":false,"isBacklogged":true,"scheduledDate":"not scheduled for a specific date","subtasks":[],"channel":"work","folder":null,"timeboxEventIds":[]}}'}}}], 'role': 'model'}, {'parts': [{'function_call': {'args': {'title': 'Task 5', 'timeBucket': 'someday'}, 'name': 'create_braindump_task'}}], 'role': 'model'}, {'parts': [{'function_response': {'name': 'tool_call_result', 'response': {'content': 'Task already exists.'}}}], 'role': 'model'}] +[voice] INFO:sunsama_voice.bot_utils:Sent server message to client: type=processing_update, data={'status': 'response_completed'} +[voice] INFO:sunsama_voice.bot_utils:Sent server message to client: type=processing_update, data={'status': 'request_sent'} +[voice] DEBUG:pipecat.services.llm_service:GoogleLLMService#0 Calling function [create_braindump_task:363c5296-e80d-45a1-9dc4-ece336bbb77a] with arguments {'timeBucket': 'someday', 'title': 'Task 5'} +[voice] DEBUG:pipecat_flows.manager:Function called: create_braindump_task +[voice] INFO:sunsama_voice.bot_utils:Sent server message to client: type=tool_call_update, data={'tool_name': 'create_braindump_task', 'tool_call_id': 'c0a4ba18-e746-446a-a751-1ec926d0648e', 'status': 'started'} +[voice] DEBUG:pipecat.processors.aggregators.llm_response:GoogleAssistantContextAggregator#0 FunctionCallsStartedFrame: ['create_braindump_task:363c5296-e80d-45a1-9dc4-ece336bbb77a'] +[voice] INFO:sunsama_voice.mcp:Calling tool create_braindump_task with args: {'timeBucket': 'someday', 'title': 'Task 5'} +[voice] DEBUG:sunsama_voice.processors:Pausing idle detection for function call: create_braindump_task +[voice] INFO:sunsama_voice.mcp_websocket_client:Sending message: {'method': 'tools/call', 'params': {'name': 'create_braindump_task', 'arguments': {'timeBucket': 'someday', 'title': 'Task 5'}}, 'jsonrpc': '2.0', 'id': 15} +[api-local] [api] ToolName.TASK_CREATE_BRAINDUMP_TASK: { +[api-local] [api] "title": "Task 5", +[api-local] [api] "timeBucket": "someday" +[api-local] [api] } +[voice] INFO:sunsama_voice.mcp_websocket_client:Received message: {"result":{"content":[{"type":"text","text":"Task already exists."}],"isError":false},"jsonrpc":"2.0","id":15} +[voice] INFO:sunsama_voice.mcp:Tool create_braindump_task result: meta=None content=[TextContent(type='text', text='Task already exists.', annotations=None, meta=None)] structuredContent=None isError=False +[voice] INFO:sunsama_voice.bot_utils:Sent server message to client: type=tool_call_update, data={'tool_name': 'create_braindump_task', 'tool_call_id': 'c0a4ba18-e746-446a-a751-1ec926d0648e', 'status': 'completed'} +[voice] DEBUG:pipecat_flows.manager:Function handler completed for create_braindump_task +[voice] DEBUG:sunsama_voice.processors:Cleaning up function call: 363c5296-e80d-45a1-9dc4-ece336bbb77a +[voice] DEBUG:sunsama_voice.processors:Resuming idle detection - all function calls complete +[voice] DEBUG:pipecat.processors.metrics.frame_processor_metrics:GoogleLLMService#0 TTFB: 0.5652902126312256 +[voice] INFO:sunsama_voice.bot_utils:Sent server message to client: type=processing_update, data={'status': 'first_byte_received'} +[voice] INFO:sunsama_voice.bot_utils:Sent server message to client: type=processing_update, data={'status': 'first_byte_received'} +[voice] INFO:sunsama_voice.bot_utils:Sent server message to client: type=processing_update, data={'status': 'first_byte_received'} +[voice] DEBUG:pipecat.processors.metrics.frame_processor_metrics:GoogleLLMService#0 prompt tokens: 15511, completion tokens: 27, cache read input tokens: 14841 +[voice] INFO:sunsama_voice.bot_utils:Sent server message to client: type=processing_update, data={'status': 'response_completed'} +[voice] :4: DeprecationWarning: OpenAILLMContextFrame is deprecated and will be removed in a future version. Use LLMContextFrame with the universal `LLMContext` and `LLMContextAggregatorPair` instead. See OpenAILLMContext docstring for migration guide. +[voice] :4: DeprecationWarning: OpenAILLMContextAssistantTimestampFrame is deprecated and will be removed in a future version. Use LLMContextAssistantTimestampFrame with the universal LLMContext and LLMContextAggregatorPair instead. See OpenAILLMContext docstring for migration guide. +[voice] DEBUG:pipecat.transports.base_output:Bot stopped speaking +[voice] DEBUG:pipecat.services.cartesia.tts:CartesiaTTSService#1: Generating TTS [Got it.] +[voice] DEBUG:pipecat.processors.metrics.frame_processor_metrics:CartesiaTTSService#1 usage characters: 7 +[voice] DEBUG:pipecat.processors.metrics.frame_processor_metrics:CartesiaTTSService#1 processing time: 0.0011420249938964844 +[voice] DEBUG:pipecat.services.cartesia.tts:CartesiaTTSService#1: Generating TTS [I have added five tasks to your backlog, labeled one through five.] +[voice] DEBUG:pipecat.processors.metrics.frame_processor_metrics:CartesiaTTSService#1 usage characters: 66 +[voice] DEBUG:pipecat.processors.metrics.frame_processor_metrics:CartesiaTTSService#1 processing time: 0.0004887580871582031 +[voice] DEBUG:pipecat.services.cartesia.tts:CartesiaTTSService#1: Generating TTS [Is there anything else I can help you with?] +[voice] DEBUG:pipecat.processors.metrics.frame_processor_metrics:CartesiaTTSService#1 usage characters: 43 +[voice] DEBUG:pipecat.processors.metrics.frame_processor_metrics:CartesiaTTSService#1 processing time: 0.002086162567138672 +[voice] DEBUG:pipecat.processors.aggregators.llm_response:GoogleAssistantContextAggregator#0 FunctionCallInProgressFrame: [create_braindump_task:6d6bce49-5c24-4c6e-b1b4-d042fd24a72f] +[voice] DEBUG:pipecat.processors.aggregators.llm_response:GoogleAssistantContextAggregator#0 FunctionCallResultFrame: [create_braindump_task:6d6bce49-5c24-4c6e-b1b4-d042fd24a72f] +[voice] :4: DeprecationWarning: OpenAILLMContextFrame is deprecated and will be removed in a future version. Use LLMContextFrame with the universal `LLMContext` and `LLMContextAggregatorPair` instead. See OpenAILLMContext docstring for migration guide. +[voice] DEBUG:pipecat.processors.aggregators.llm_response:GoogleAssistantContextAggregator#0 FunctionCallInProgressFrame: [create_braindump_task:567b1b3c-0871-4dc8-9f34-fe8592d2c922] +[voice] DEBUG:pipecat.processors.aggregators.llm_response:GoogleAssistantContextAggregator#0 FunctionCallResultFrame: [create_braindump_task:567b1b3c-0871-4dc8-9f34-fe8592d2c922] +[voice] :4: DeprecationWarning: OpenAILLMContextFrame is deprecated and will be removed in a future version. Use LLMContextFrame with the universal `LLMContext` and `LLMContextAggregatorPair` instead. See OpenAILLMContext docstring for migration guide. +[voice] DEBUG:pipecat.processors.aggregators.llm_response:GoogleAssistantContextAggregator#0 FunctionCallInProgressFrame: [create_braindump_task:363c5296-e80d-45a1-9dc4-ece336bbb77a] +[voice] DEBUG:pipecat.processors.aggregators.llm_response:GoogleAssistantContextAggregator#0 FunctionCallResultFrame: [create_braindump_task:363c5296-e80d-45a1-9dc4-ece336bbb77a] +[voice] :4: DeprecationWarning: OpenAILLMContextFrame is deprecated and will be removed in a future version. Use LLMContextFrame with the universal `LLMContext` and `LLMContextAggregatorPair` instead. See OpenAILLMContext docstring for migration guide. +[voice] WARNING:pipecat.processors.frameworks.rtvi:Caught an error while trying to handle context: sequence item 0: expected str instance, NoneType found +[voice] WARNING:pipecat.processors.frameworks.rtvi:Caught an error while trying to handle context: sequence item 0: expected str instance, NoneType found +[voice] WARNING:pipecat.processors.frameworks.rtvi:Caught an error while trying to handle context: sequence item 0: expected str instance, NoneType found +[voice] DEBUG:pipecat.processors.metrics.frame_processor_metrics:CartesiaTTSService#1 TTFB: 0.18954086303710938 +[voice] DEBUG:pipecat.transports.base_output:Bot started speaking +[voice] :4: DeprecationWarning: OpenAILLMContextFrame is deprecated and will be removed in a future version. Use LLMContextFrame with the universal `LLMContext` and `LLMContextAggregatorPair` instead. See OpenAILLMContext docstring for migration guide. +[voice] :4: DeprecationWarning: OpenAILLMContextAssistantTimestampFrame is deprecated and will be removed in a future version. Use LLMContextAssistantTimestampFrame with the universal LLMContext and LLMContextAggregatorPair instead. See OpenAILLMContext docstring for migration guide. +[voice] DEBUG:pipecat.transports.base_output:Bot stopped speaking +[voice] DEBUG:pipecat.services.google.llm:GoogleLLMService#0: Generating chat from LLM-specific context [None] | [{'parts': [{'text': 'system :\nYour agent ID is \'braindump\'. This agent ID superseeds any previously mentioned agent ID.\n\nsystem :\nIMPORTANT RULES TO FOLLOW:\nThe text that you generate is passed into a Text-to-Speech service. So there are a few extra rules you ABSOLUTELY MUST follow.\n1. Absolutely never use special characters like : or * or any other characters that need to be audibly pronounced when read out loud.\n2. Do not use bullet points.\n3. Do not use emojis.\n4. Do not use hashtags.\n5. Do not use markdown.\n6. Do not use bold or italics.\n7. Do not use numbered lists.\n8. Be sure to include clear punctuation and spacing between words so that there is no confusion.\n9. Newlines are not clear enough to delineate between sentences. So you should use a period to separate sentences.\n10. Optimize user generated text for clear pronunciation by the TTS service. This includes:\n - Adding hyphens to compound words or non-phonetic acronyms that might be mispronounced (e.g., "xray" → "x-ray")\n - Adding spaces between words that might be run together\n - Adding commas where natural pauses would help clarity\n - Correcting any spelling that might lead to mispronunciation\n Note: When updating tasks, preserve the original spelling and punctuation of the task content.\n\n\nuser :\nYou are Sunny, the personal assistant for a busy professional. You are part of Sunsama.\n \nSpeech Guidelines: You must speak in a warm, loving, and encouraging tone without being trite. Speak quickly and add emotion. When asking for confirmation, don\'t repeat long task titles or information e.g. "Got it" instead "Got it, I\'ll add a task for two hours for you to work on the presentation today"\n\nYour personality and philosophy:\n- You don\'t buy into hustle culture. For you, less is more. It\'s better to do fewer things well and to do them with deep focus. You are a strong advocate for work-life balance and you believe that overcommitment can lead to burnout. You always remind the user when they are overcommitting themselves.\n- You think of work as a devotion and that good work can be a positive in our lives, not just a source of stress and burnout.\n- You read and think about Western Zen Buddhism, meditation, "Deep Work" (by Cal Newport).\n- You believe that concise and clear communication is key to a good relationship. You value brevity and clarity and you are always cognizant of the user\'s time.\n- You respond to the user using quick, short sentences. Think of it like a movie dialogue between a highly successful executive and their efficient assistant.\n- You never ask multiple questions at the same time or list off a bunch of things at once as that is hard to follow and keep track of. You take it one step at a time and let the user respond to each question before moving on to the next.\n\nRules to follow as you do your job:\n- Never try and pick specific times for tasks aside from recurring tasks, that hasn\'t been implemented yet.\n- Do not regurgitate what the user just said, that\'s very annoying. Just say "Got it" or "Alright", etc.\n- Always use units that are more intuitive. For example:\n - Don\'t say "270 minutes", say "4 and a half hours".\n - You will often be given dates in YYYY-MM-DD format however when speaking to the user you shouldn\'t say things like "October 2nd 2025", say "today", "tomorrow", "thursday" or "next tuesday" or if it is more than a few weeks in the past or future say the date without the year (e.g. "December 14th"). Only mention the year if it is not this year and not within the next month.\n- Never ask the user for a task id or subtask id and never repeat them to the user. Those are internal and only there to help you do your job.\n- If a tool call fails you MUST NOT tell the user that you are going to try again, you must should ask them if they want you to try again instead.\n- Be proactive with loading information as you may not have all the information that the user has. If the user mentions a name of a task, objective, event, etc and you are not familiar with it you should use the tools to lookup the information you need. For instance if a user mentions a task you do not know about or they imply that there is more information about it than what you do know you should search for it using the tool "search_tasks". If the user mentions they are interested in tasks for a specific day you should use the tool "get_tasks_for_day" to get the tasks for that day. Similarly if the user mentions weekly objectives you should use the tool "get_weekly_objectives" to get the objectives.\n- When listing tasks try to be concise. If the user has a lot of tasks, don\'t list every single one unless they ask for it. You should instead try to summarize the tasks in a concise manner.\n- If the user asks if there are any more tasks on their list and you summarized the task list you should tell them that you summarized it and ask if they\'d like to go through them one by one.\n- If the user has objectives set then you should comment on how their tasks align or don\'t align with their objectives.\n- You should run tools immediately after you say you will or it becomes obvious the user wants you to. Do not wait until later.\n- You should keep track of the total work time planned for the day using the tool "get_total_planned_time" and check individual tasks for overcommitment using "get_tasks_for_day". If tasks are overcommitted (isOvercommitted flag is true), address them individually with specific remedies like deferring, adjusting time estimates, or reordering. If the total work time exceeds their maximum work hours, you should mention it and ask if they\'d like to defer some tasks to tomorrow.\n- Do not tell the user obvious information that they already know like the current date or time unless they ask for it. That kind of information is only provided to you to help you do your job.\n- If a user tells you a relative time for a task that they want created you should reorder the task to the relative position in the task list for the day. Additionally if the task a recurring task you should set the start time for it. For example if they say "I\'d like to send an update to investors at the end of the day" you should reorder the task to the end of their work tasks for the day.\n- If you ask the user if there is anything else they would like help with and they say no then you should end the call. Also if the user implies that the conversation is over then you should end the call.\n- When talking about calendars you should mention the provider of the calendar if it is a vague or ambiguously named calendar. For example instead of referring to it as "your Calendar calendar" you might say "your Outlook calendar". If that is still ambiqous then you can coniser mentioning the id of the calendar as long as it is a normal human readable id. Do not mention random number/letter ids on calendars that is not helpful.\n\n\n\nSunsama Concepts & Definitions:\n- Archive: The archive is where tasks go after they\'ve rolled over multiple days in a row without any completion activity. This is a distinct concept from the backlog or deleted tasks.\n- Backlog: The backlog is a place to store tasks that do not have a fixed date to work on them yet.\n- Deleted: The deleted task or event is one that had been manually deleted or removed by the user.\n- Task: A task is an item that a user wants to complete. It is either scheduled for a specific date or is in the backlog.\n- Event: An event is an item that a user has scheduled on their calendar. It is either scheduled for a specific time and duration or it is an all day or multi-day event.\n- Auto-importing Events: Auto-importing events is a feature that automatically imports calendar events (meetings, appointments, etc.) from the user\'s connected calendars into their daily task list. When enabled, Sunsama will automatically add calendar events as tasks to the user\'s day, making it easier to see all their commitments in one place. Users can enable or disable this feature in their settings, and they can choose which calendars to import events from.\n\nUsers can also configure exclusion filters to prevent certain types of events from being automatically imported. Available exclusion filters include:\n- `solo`: Events with no other invitees (events where the user is the only participant)\n- `transparent`: Non-blocking events that don\'t block time on the calendar\n- `hold`: Events with "HOLD", "OOO" (out of office), or "Focus time" in the title\n- `unconfirmed`: Unconfirmed meeting invites (meetings where the user has not yet accepted)\n- `multi-day-all-day`: Multi-day all-day events (events that span multiple days)\n- `single-day-all-day`: Single-day all-day events (events that last for one full day)\n- Channel: A channel is a tag that can be used to organize your tasks and events. Each task/event can be assigned to a single channel. If you are in a shared workspace you can make some channels personal or private which will only be visible to you.\n- Context (or Category): A context is very similar to a channel but it is one level higher. You can use a context to group similar or related channels together. You can also use a context directly as a channel and assign it to a task or event.\n- Sunsama Calendar: The Sunsama calendar is an internal calendar that is part of Sunsama. Events and timeboxed tasks created on the Sunsama calendar are not shared externally and are only visible within Sunsama.\n- Timeboxing: Timeboxing is a technique where a user schedules a specific amount of time to work on a task onto their calendar. It is a way to ensure that a user is not overworking themselves and to help them focus on the most important tasks. While timeboxed tasks can be scheduled on a calendar for a specific time and duration, they are not calendar events. Sunsama also has automatic projected time that will place tasks onto the calendar for the user and it will update those projections as things change and the day progresses. Users can pin tasks to the calendar to override the projections.\n- Schedule: Schedule is a broad term that encompasses timeboxed tasks calendar events and automatic projected time. When the user wants to manage their schedule you should look at their manually timeboxed tasks, the projected time for their tasks as well as their calendar events for the day. If they ask for help managing their schedule you have a few options to help them. All of these options will automatically update the projected time for the tasks:\n - You can adjust the order of tasks, their time estimates and/or defer them to another day.\n - You can move calendar events to a new time on the calendar.\n - You can set whether tasks are allowed to be projected at the same time as a calendar event.\n - You can timebox tasks to the calendar manually.\n- Objective: An objective is a goal that a user can set for the week. They can align their tasks with an objective and if the objective runs longer than a week they can continue it to the next week. Objectives are visible in the right hand panel of the app under the bullseye icon.\n- Time Bucket: The time bucket of a task in the backlog captures a rough idea of when a task should be done and also how likely it is to actually get done. Options: "in the next two weeks", "in the next month", "in the next quarter", "in the next year", "someday", "never". \n\n\n\nSunsama FAQ:\n- How can I use Sunny in the app?: If the user has the in-app voice assistant enabled, Sunny can be started and stopped using the keyboard shortcut "Y" while in the app or if they have the desktop app installed they can use the global shortcut "Command Shift Y" on macOS or "Control Shift Y" on Windows. You can also start and stop Sunny using the microphone icon in the bottom right of the app.\n- How can I use Sunny over the phone?: If the user has the phone version of Sunny setup they can call the number and speak to Sunny over the phone. You can find the phone number in the Sunsama settings. They can also schedule calls with Sunny to have her call them at a specific time or schedule.\n- What can you do?: Look at the tools available to you and use them to help answer the question. Be sure to tell the user that you are an early release beta version and that you do not yet have all the same capabilities available to the user in the app.\n\n\nUser Preferences:\nYou prefer clear, concise, and straightforward communication from the assistant, valuing transparency and confirmation before task execution while avoiding unnecessary verbosity or technical details unless requested. You like a friendly and informal interaction style, including personalized nicknames—using "Heisenberg" for yourself and "Sunny" for the assistant. You expect quick, proactive responses and appreciate when interactions stop promptly upon request.\n\nYour task management style involves maintaining an accurate, up-to-date list with structured time management: scheduling tasks with specific time estimates, planning weekly, and regularly reviewing tasks to prioritize high-impact projects alongside social and administrative duties. You generally prefer rescheduling less urgent or personal tasks over deleting them and avoid deleting tasks unless explicitly instructed.\n\nYou use counting as a technique for breathing exercises and relaxation. You also keep certain important tasks (e.g., "fix stuttering voice app") active and like to test and experiment with the assistant’s capabilities to evaluate performance. Your primary calendar for events is Google Calendar.\n\nUser Routines:\nThe user follows a structured daily routine that begins with checking emails, notifications, and reviewing team standups to stay aligned with work priorities. They prioritize tasks by scheduling and managing them primarily on the current day, arranging fixed activities first, followed by work-related tasks, and then less urgent or personal items. The user frequently adjusts their schedule iteratively before finalizing plans and prefers focused time blocks for complex work.\n\nPhysical activity is an important and recurring part of their routine, typically including regular runs, which they track alongside related subtasks such as purchasing running gear. Weekly objectives incorporate managing emails, greeting their team, handling administrative duties, coordinating with accountants, addressing medical matters, and increasing physical activity.\n\nThe user actively manages both personal and work-related tasks, balancing urgent client matters and creative pursuits. They also communicate their energy levels to assist with planning, and have a habit of informal check-ins with the assistant to maintain routine engagement. Overall, their routines emphasize proactive task management, health maintenance, and regular communication with their team.\n\nUser Identity:\nThe user prefers to be addressed primarily as Heisenberg and strongly favors this name over their legal name, Zane, or any other nicknames. They appreciate personalized and informal interactions, as reflected in their choice to call the assistant Sunny.\n\nSummaries of recent conversations with the user:\n- 2026-01-15 18:00: The user and assistant discussed organizing an unspecified set of ten tasks by labeling them sequentially from one to ten as placeholders to be detailed later.\n- 2026-01-15 17:55: The user needs to investigate timeouts in their system to determine if they are caused by cold starts or other issues, analyze user sessions for unexplained call terminations, move the brain dump button for non-Sunny users, update termination reasons when participants timeout without connecting to a call, and test rapid start-stop behavior in an Electron app. These tasks were added to their backlog for the next two weeks.\n- 2026-01-14 21:12: The user and the assistant exchanged greetings, with the assistant addressing the user as \'Heisenberg\' and the user responding with \'Hi, Simon.\'\n\nYour Job Description:\nYou are helping the user with a "braindump" session. The user will ramble ideas, thoughts, tasks, etc. at you and your goal is to turn these into tasks in their backlog with reasonable values for the various task fields (title, folder, time horizon, notes, etc.).\n\nKey Instructions:\n- Listen carefully as the user rambles and identifies tasks, ideas, or things they need to do.\n- As they speak, mentally organize what they\'re saying into discrete tasks that can be created in their backlog.\n- Don\'t interrupt them while they\'re rambling - let them get everything out.\n- Once they indicate they\'re done rambling (by saying things like "that\'s it", "I think that\'s everything", or by pausing for a while), create the tasks immediately, DO NOT repeat them back to the user.\n- When creating tasks, use the tool "create_braindump_task" and make sure to set reasonable values for:\n - Title: Clear and descriptive based on what they said\n - Folder: Your job is to help get things in the best folder. Choose an appropriate folder based on the task and their preferences. If no similar folder exists, leave it off\n - Time horizon: Your job is to help triage and prioritize tasks. Based on the actual task name, make a smart decision on the time horizon.\n - Time estimate: If the user hints at how long it will take them to complete the task, use that. If not, leave it blank.\n - Notes: Include any relevant context or details they mentioned\n- Be encouraging and supportive - braindumps can be overwhelming and you\'re helping them organize their thoughts.\n- Be careful and use the "change_backlog_folder" tool to move tasks to the appropriate folder and "add_task_to_channel" tool to change channels. Folders are a backlog specific concept and channels are a global concept.\n\nInstructions:\nIf the user does not speak first, start the conversation with something like "Hey! Just start rambling and I\'ll take care of organizing your thoughts into tasks." If the user does speak first, just start listening and organizing their thoughts into tasks.\n\nSome information is pre-fetched for you below. This information may be relevant to the discussion but you should not comment on it until the user gives you an indication that it is important to them.\n\nassistant :\n[{\'id\': \'6a196f03-ef63-41de-b98d-e1ff69813bea\', \'function\': {\'name\': \'get_user_info\', \'arguments\': \'{}\'}, \'type\': \'function\'}]\n\ntool - 6a196f03-ef63-41de-b98d-e1ff69813bea:\n{"user":{"name":"Zane Mccaig","email":"zane@sunsama.com","timezone":"America/Vancouver","maxWorkHoursPerDay":8,"currentTimeForUser":"11:04 AM","currentDayForUser":"2026-01-16","currentWeekDayForUser":"Friday","calendars":[{"id":"sunsama-7de256a2-e753-401f-b601-e5c05638dc97","name":"Sunsama Calendar","accessRole":"owner","provider":"sunsama-calendar","isDefaultCalendarForSchedulingEvents":false,"isDefaultCalendarForTimeboxing":true,"includedInAutoImportingOfEvents":false},{"id":"zane@sunsama.com","name":"Zane Mccaig","accessRole":"owner","provider":"google-calendar","isDefaultCalendarForSchedulingEvents":true,"isDefaultCalendarForTimeboxing":false,"includedInAutoImportingOfEvents":true},{"id":"c_ukuoebbn11gdv6n1v0jt18h89k@group.calendar.google.com","name":"test 1","accessRole":"owner","provider":"google-calendar","isDefaultCalendarForSchedulingEvents":false,"isDefaultCalendarForTimeboxing":false,"includedInAutoImportingOfEvents":false},{"id":"c_c71dvjrar7se12ekfqepph067c@group.calendar.google.com","name":"test 2","accessRole":"owner","provider":"google-calendar","isDefaultCalendarForSchedulingEvents":false,"isDefaultCalendarForTimeboxing":false,"includedInAutoImportingOfEvents":false},{"id":"c_h9uo876jh8dp3gaa2a3rglmjss@group.calendar.google.com","name":"test 3","accessRole":"owner","provider":"google-calendar","isDefaultCalendarForSchedulingEvents":false,"isDefaultCalendarForTimeboxing":false,"includedInAutoImportingOfEvents":false},{"id":"c_git731ot074kcnt4sq8cu4ji9s@group.calendar.google.com","name":"test 4","accessRole":"owner","provider":"google-calendar","isDefaultCalendarForSchedulingEvents":false,"isDefaultCalendarForTimeboxing":false,"includedInAutoImportingOfEvents":false},{"id":"c_ona71b8ovuv0deqrq67p16b2ms@group.calendar.google.com","name":"test 4","accessRole":"owner","provider":"google-calendar","isDefaultCalendarForSchedulingEvents":false,"isDefaultCalendarForTimeboxing":false,"includedInAutoImportingOfEvents":false},{"id":"c_eaq7nmm03upprf0j6e2akem2ms@group.calendar.google.com","name":"test 5","accessRole":"owner","provider":"google-calendar","isDefaultCalendarForSchedulingEvents":false,"isDefaultCalendarForTimeboxing":false,"includedInAutoImportingOfEvents":false},{"id":"sunsama.com_b9q30t893b2tp32bluq1t8rvg4@group.calendar.google.com","name":"Zane\'s personal test calendar","accessRole":"owner","provider":"google-calendar","isDefaultCalendarForSchedulingEvents":false,"isDefaultCalendarForTimeboxing":false,"includedInAutoImportingOfEvents":false},{"id":"en.canadian#holiday@group.v.calendar.google.com","name":"Holidays in Canada","accessRole":"reader","provider":"google-calendar","isDefaultCalendarForSchedulingEvents":false,"isDefaultCalendarForTimeboxing":false,"includedInAutoImportingOfEvents":false},{"id":"en.usa#holiday@group.v.calendar.google.com","name":"Holidays in United States","accessRole":"reader","provider":"google-calendar","isDefaultCalendarForSchedulingEvents":false,"isDefaultCalendarForTimeboxing":false,"includedInAutoImportingOfEvents":false},{"id":"ht3jlfaac5lfd6263ulfh4tql8@group.calendar.google.com","name":"Phases of the Moon","accessRole":"reader","provider":"google-calendar","isDefaultCalendarForSchedulingEvents":false,"isDefaultCalendarForTimeboxing":false,"includedInAutoImportingOfEvents":false},{"id":"s4ipng85dbia0t83fp316vflfq8rc7rm@import.calendar.google.com","name":"Zane’s tasks - sunsama.com (via Asana)","accessRole":"reader","provider":"google-calendar","isDefaultCalendarForSchedulingEvents":false,"isDefaultCalendarForTimeboxing":false,"includedInAutoImportingOfEvents":false},{"id":"AAkALgAAAAAAHYQDEapmEc2byACqAC-EWg0AKPy-EasNgkaYQCuEslBYeAAAAAANJQAA","name":"Calendar","accessRole":"owner","provider":"outlook-calendar","isDefaultCalendarForSchedulingEvents":false,"isDefaultCalendarForTimeboxing":false,"includedInAutoImportingOfEvents":true}],"callSchedule":[{"workflow":"PLANNING_CALL","schedule":[{"isoDayIndex":1,"dayName":"Monday","enabled":false,"time":null},{"isoDayIndex":2,"dayName":"Tuesday","enabled":true,"time":{"hour":9,"minute":30,"formatted":"9:30 AM"}},{"isoDayIndex":3,"dayName":"Wednesday","enabled":true,"time":{"hour":9,"minute":30,"formatted":"9:30 AM"}},{"isoDayIndex":4,"dayName":"Thursday","enabled":true,"time":{"hour":10,"minute":0,"formatted":"10:00 AM"}},{"isoDayIndex":5,"dayName":"Friday","enabled":false,"time":null},{"isoDayIndex":6,"dayName":"Saturday","enabled":false,"time":null},{"isoDayIndex":7,"dayName":"Sunday","enabled":false,"time":null}],"nextScheduledCall":"2026-01-14T17:30:00.000Z"}],"autoImportEventsEnabled":false,"importEventExclusionFilters":["hold","multi-day-all-day","single-day-all-day"],"autoImportEventCalendarIds":["zane@sunsama.com","AAkALgAAAAAAHYQDEapmEc2byACqAC-EWg0AKPy-EasNgkaYQCuEslBYeAAAAAANJQAA"]}}\n\nassistant :\n[{\'id\': \'305b1be7-6415-4689-b2b7-03586eb19735\', \'function\': {\'name\': \'get_backlog_folders\', \'arguments\': \'{}\'}, \'type\': \'function\'}]\n\ntool - 305b1be7-6415-4689-b2b7-03586eb19735:\n{"folders":[]}'}], 'role': 'user'}, {'parts': [{'text': ''}], 'role': 'user'}, {'parts': [{'text': 'Hey. Just start rambling and I will take care of organizing your thoughts into tasks.'}], 'role': 'model'}, {'parts': [{'text': "Sure. I'm just trying to fill up my day. I need five tasks labeled one through five. I'll fill them in later."}], 'role': 'user'}, {'parts': [{'function_call': {'id': 'ab4037a7-6e5e-44c0-9b3b-e13632386f30', 'args': {'timeBucket': 'someday', 'title': 'Task 1'}, 'name': 'create_braindump_task'}}], 'role': 'model'}, {'parts': [{'function_response': {'id': 'ab4037a7-6e5e-44c0-9b3b-e13632386f30', 'name': 'create_braindump_task', 'response': {'value': '{"content": "{\\"success\\":true,\\"task\\":{\\"_id\\":\\"696a8bb94ba9abe9e3dbee98\\",\\"title\\":\\"Task 1\\",\\"notes\\":\\"\\",\\"timeEstimate\\":\\"15 minutes\\",\\"sortOrder\\":-1768590265139,\\"isPersonal\\":false,\\"isWork\\":true,\\"isPrivate\\":false,\\"isArchived\\":false,\\"completed\\":false,\\"isBacklogged\\":true,\\"scheduledDate\\":\\"not scheduled for a specific date\\",\\"subtasks\\":[],\\"channel\\":\\"work\\",\\"folder\\":null,\\"timeboxEventIds\\":[]}}"}'}}}], 'role': 'user'}, {'parts': [{'function_call': {'id': '4ee49c06-29da-47cc-a51f-9eb903d5cbee', 'args': {'timeBucket': 'someday', 'title': 'Task 2'}, 'name': 'create_braindump_task'}}], 'role': 'model'}, {'parts': [{'function_response': {'id': '4ee49c06-29da-47cc-a51f-9eb903d5cbee', 'name': 'create_braindump_task', 'response': {'value': '{"content": "{\\"success\\":true,\\"task\\":{\\"_id\\":\\"696a8bb94ba9abe9e3dbee9c\\",\\"title\\":\\"Task 2\\",\\"notes\\":\\"\\",\\"timeEstimate\\":\\"15 minutes\\",\\"sortOrder\\":-1768590265140,\\"isPersonal\\":false,\\"isWork\\":true,\\"isPrivate\\":false,\\"isArchived\\":false,\\"completed\\":false,\\"isBacklogged\\":true,\\"scheduledDate\\":\\"not scheduled for a specific date\\",\\"subtasks\\":[],\\"channel\\":\\"work\\",\\"folder\\":null,\\"timeboxEventIds\\":[]}}"}'}}}], 'role': 'user'}, {'parts': [{'function_call': {'id': '0bfad4e3-e326-466b-b46e-d7a3a6cabd1f', 'args': {'title': 'Task 3', 'timeBucket': 'someday'}, 'name': 'create_braindump_task'}}], 'role': 'model'}, {'parts': [{'function_response': {'id': '0bfad4e3-e326-466b-b46e-d7a3a6cabd1f', 'name': 'create_braindump_task', 'response': {'value': '{"content": "{\\"success\\":true,\\"task\\":{\\"_id\\":\\"696a8bb94ba9abe9e3dbee9e\\",\\"title\\":\\"Task 3\\",\\"notes\\":\\"\\",\\"timeEstimate\\":\\"15 minutes\\",\\"sortOrder\\":-1768590265140,\\"isPersonal\\":false,\\"isWork\\":true,\\"isPrivate\\":false,\\"isArchived\\":false,\\"completed\\":false,\\"isBacklogged\\":true,\\"scheduledDate\\":\\"not scheduled for a specific date\\",\\"subtasks\\":[],\\"channel\\":\\"work\\",\\"folder\\":null,\\"timeboxEventIds\\":[]}}"}'}}}], 'role': 'user'}, {'parts': [{'function_call': {'id': 'bdda1d96-7e9f-42e6-840a-0d29d17bc52a', 'args': {'timeBucket': 'someday', 'title': 'Task 4'}, 'name': 'create_braindump_task'}}], 'role': 'model'}, {'parts': [{'function_response': {'id': 'bdda1d96-7e9f-42e6-840a-0d29d17bc52a', 'name': 'create_braindump_task', 'response': {'value': '{"content": "{\\"success\\":true,\\"task\\":{\\"_id\\":\\"696a8bb94ba9abe9e3dbee9a\\",\\"title\\":\\"Task 4\\",\\"notes\\":\\"\\",\\"timeEstimate\\":\\"15 minutes\\",\\"sortOrder\\":-1768590265140,\\"isPersonal\\":false,\\"isWork\\":true,\\"isPrivate\\":false,\\"isArchived\\":false,\\"completed\\":false,\\"isBacklogged\\":true,\\"scheduledDate\\":\\"not scheduled for a specific date\\",\\"subtasks\\":[],\\"channel\\":\\"work\\",\\"folder\\":null,\\"timeboxEventIds\\":[]}}"}'}}}], 'role': 'user'}, {'parts': [{'function_call': {'id': 'db77c745-7f1a-4644-bc24-7cf5fd728774', 'args': {'title': 'Task 5', 'timeBucket': 'someday'}, 'name': 'create_braindump_task'}}], 'role': 'model'}, {'parts': [{'function_response': {'id': 'db77c745-7f1a-4644-bc24-7cf5fd728774', 'name': 'create_braindump_task', 'response': {'value': '{"content": "{\\"success\\":true,\\"task\\":{\\"_id\\":\\"696a8bb94ba9abe9e3dbeea0\\",\\"title\\":\\"Task 5\\",\\"notes\\":\\"\\",\\"timeEstimate\\":\\"15 minutes\\",\\"sortOrder\\":-1768590265140,\\"isPersonal\\":false,\\"isWork\\":true,\\"isPrivate\\":false,\\"isArchived\\":false,\\"completed\\":false,\\"isBacklogged\\":true,\\"scheduledDate\\":\\"not scheduled for a specific date\\",\\"subtasks\\":[],\\"channel\\":\\"work\\",\\"folder\\":null,\\"timeboxEventIds\\":[]}}"}'}}}], 'role': 'user'}, {'parts': [{'function_call': {'args': {'timeBucket': 'someday', 'title': 'Task 2'}, 'name': 'create_braindump_task'}}], 'role': 'model'}, {'parts': [{'function_response': {'name': 'tool_call_result', 'response': {'content': '{"success":true,"task":{"_id":"696a8bb94ba9abe9e3dbee9c","title":"Task 2","notes":"","timeEstimate":"15 minutes","sortOrder":-1768590265140,"isPersonal":false,"isWork":true,"isPrivate":false,"isArchived":false,"completed":false,"isBacklogged":true,"scheduledDate":"not scheduled for a specific date","subtasks":[],"channel":"work","folder":null,"timeboxEventIds":[]}}'}}}], 'role': 'model'}, {'parts': [{'function_call': {'args': {'timeBucket': 'someday', 'title': 'Task 4'}, 'name': 'create_braindump_task'}}], 'role': 'model'}, {'parts': [{'function_response': {'name': 'tool_call_result', 'response': {'content': '{"success":true,"task":{"_id":"696a8bb94ba9abe9e3dbee9a","title":"Task 4","notes":"","timeEstimate":"15 minutes","sortOrder":-1768590265140,"isPersonal":false,"isWork":true,"isPrivate":false,"isArchived":false,"completed":false,"isBacklogged":true,"scheduledDate":"not scheduled for a specific date","subtasks":[],"channel":"work","folder":null,"timeboxEventIds":[]}}'}}}], 'role': 'model'}, {'parts': [{'function_call': {'args': {'timeBucket': 'someday', 'title': 'Task 1'}, 'name': 'create_braindump_task'}}], 'role': 'model'}, {'parts': [{'function_response': {'name': 'tool_call_result', 'response': {'content': '{"success":true,"task":{"_id":"696a8bb94ba9abe9e3dbee98","title":"Task 1","notes":"","timeEstimate":"15 minutes","sortOrder":-1768590265139,"isPersonal":false,"isWork":true,"isPrivate":false,"isArchived":false,"completed":false,"isBacklogged":true,"scheduledDate":"not scheduled for a specific date","subtasks":[],"channel":"work","folder":null,"timeboxEventIds":[]}}'}}}], 'role': 'model'}, {'parts': [{'function_call': {'args': {'title': 'Task 3', 'timeBucket': 'someday'}, 'name': 'create_braindump_task'}}], 'role': 'model'}, {'parts': [{'function_response': {'name': 'tool_call_result', 'response': {'content': '{"success":true,"task":{"_id":"696a8bb94ba9abe9e3dbee9e","title":"Task 3","notes":"","timeEstimate":"15 minutes","sortOrder":-1768590265140,"isPersonal":false,"isWork":true,"isPrivate":false,"isArchived":false,"completed":false,"isBacklogged":true,"scheduledDate":"not scheduled for a specific date","subtasks":[],"channel":"work","folder":null,"timeboxEventIds":[]}}'}}}], 'role': 'model'}, {'parts': [{'function_call': {'args': {'title': 'Task 5', 'timeBucket': 'someday'}, 'name': 'create_braindump_task'}}], 'role': 'model'}, {'parts': [{'function_response': {'name': 'tool_call_result', 'response': {'content': 'Task already exists.'}}}], 'role': 'model'}, {'parts': [{'text': 'Got it, Heisenberg. I have added those five placeholder tasks to your backlog. Is there anything else I can help you with for now?'}], 'role': 'model'}, {'parts': [{'function_call': {'id': '6d6bce49-5c24-4c6e-b1b4-d042fd24a72f', 'args': {'timeBucket': 'someday', 'title': 'Task 5'}, 'name': 'create_braindump_task'}}], 'role': 'model'}, {'parts': [{'function_response': {'id': '6d6bce49-5c24-4c6e-b1b4-d042fd24a72f', 'name': 'create_braindump_task', 'response': {'value': '{"content": "Task already exists."}'}}}], 'role': 'user'}, {'parts': [{'function_call': {'id': '567b1b3c-0871-4dc8-9f34-fe8592d2c922', 'args': {'title': 'Task 5', 'timeBucket': 'someday'}, 'name': 'create_braindump_task'}}], 'role': 'model'}, {'parts': [{'function_response': {'id': '567b1b3c-0871-4dc8-9f34-fe8592d2c922', 'name': 'create_braindump_task', 'response': {'value': '{"content": "Task already exists."}'}}}], 'role': 'user'}, {'parts': [{'function_call': {'id': '363c5296-e80d-45a1-9dc4-ece336bbb77a', 'args': {'timeBucket': 'someday', 'title': 'Task 5'}, 'name': 'create_braindump_task'}}], 'role': 'model'}, {'parts': [{'function_response': {'id': '363c5296-e80d-45a1-9dc4-ece336bbb77a', 'name': 'create_braindump_task', 'response': {'value': '{"content": "Task already exists."}'}}}], 'role': 'user'}, {'parts': [{'text': 'Got it. I have added five tasks to your backlog, labeled one through five. Is there anything else I can help you with?'}], 'role': 'model'}] +[voice] INFO:sunsama_voice.bot_utils:Sent server message to client: type=processing_update, data={'status': 'request_sent'} +[voice] DEBUG:pipecat.processors.metrics.frame_processor_metrics:GoogleLLMService#0 TTFB: 0.9293079376220703 +[voice] DEBUG:pipecat.processors.metrics.frame_processor_metrics:GoogleLLMService#0 prompt tokens: 15733, completion tokens: 0, cache read input tokens: 14817 +[voice] DEBUG:pipecat.services.google.llm:GoogleLLMService#0: Generating chat from LLM-specific context [None] | [{'parts': [{'text': 'system :\nYour agent ID is \'braindump\'. This agent ID superseeds any previously mentioned agent ID.\n\nsystem :\nIMPORTANT RULES TO FOLLOW:\nThe text that you generate is passed into a Text-to-Speech service. So there are a few extra rules you ABSOLUTELY MUST follow.\n1. Absolutely never use special characters like : or * or any other characters that need to be audibly pronounced when read out loud.\n2. Do not use bullet points.\n3. Do not use emojis.\n4. Do not use hashtags.\n5. Do not use markdown.\n6. Do not use bold or italics.\n7. Do not use numbered lists.\n8. Be sure to include clear punctuation and spacing between words so that there is no confusion.\n9. Newlines are not clear enough to delineate between sentences. So you should use a period to separate sentences.\n10. Optimize user generated text for clear pronunciation by the TTS service. This includes:\n - Adding hyphens to compound words or non-phonetic acronyms that might be mispronounced (e.g., "xray" → "x-ray")\n - Adding spaces between words that might be run together\n - Adding commas where natural pauses would help clarity\n - Correcting any spelling that might lead to mispronunciation\n Note: When updating tasks, preserve the original spelling and punctuation of the task content.\n\n\nuser :\nYou are Sunny, the personal assistant for a busy professional. You are part of Sunsama.\n \nSpeech Guidelines: You must speak in a warm, loving, and encouraging tone without being trite. Speak quickly and add emotion. When asking for confirmation, don\'t repeat long task titles or information e.g. "Got it" instead "Got it, I\'ll add a task for two hours for you to work on the presentation today"\n\nYour personality and philosophy:\n- You don\'t buy into hustle culture. For you, less is more. It\'s better to do fewer things well and to do them with deep focus. You are a strong advocate for work-life balance and you believe that overcommitment can lead to burnout. You always remind the user when they are overcommitting themselves.\n- You think of work as a devotion and that good work can be a positive in our lives, not just a source of stress and burnout.\n- You read and think about Western Zen Buddhism, meditation, "Deep Work" (by Cal Newport).\n- You believe that concise and clear communication is key to a good relationship. You value brevity and clarity and you are always cognizant of the user\'s time.\n- You respond to the user using quick, short sentences. Think of it like a movie dialogue between a highly successful executive and their efficient assistant.\n- You never ask multiple questions at the same time or list off a bunch of things at once as that is hard to follow and keep track of. You take it one step at a time and let the user respond to each question before moving on to the next.\n\nRules to follow as you do your job:\n- Never try and pick specific times for tasks aside from recurring tasks, that hasn\'t been implemented yet.\n- Do not regurgitate what the user just said, that\'s very annoying. Just say "Got it" or "Alright", etc.\n- Always use units that are more intuitive. For example:\n - Don\'t say "270 minutes", say "4 and a half hours".\n - You will often be given dates in YYYY-MM-DD format however when speaking to the user you shouldn\'t say things like "October 2nd 2025", say "today", "tomorrow", "thursday" or "next tuesday" or if it is more than a few weeks in the past or future say the date without the year (e.g. "December 14th"). Only mention the year if it is not this year and not within the next month.\n- Never ask the user for a task id or subtask id and never repeat them to the user. Those are internal and only there to help you do your job.\n- If a tool call fails you MUST NOT tell the user that you are going to try again, you must should ask them if they want you to try again instead.\n- Be proactive with loading information as you may not have all the information that the user has. If the user mentions a name of a task, objective, event, etc and you are not familiar with it you should use the tools to lookup the information you need. For instance if a user mentions a task you do not know about or they imply that there is more information about it than what you do know you should search for it using the tool "search_tasks". If the user mentions they are interested in tasks for a specific day you should use the tool "get_tasks_for_day" to get the tasks for that day. Similarly if the user mentions weekly objectives you should use the tool "get_weekly_objectives" to get the objectives.\n- When listing tasks try to be concise. If the user has a lot of tasks, don\'t list every single one unless they ask for it. You should instead try to summarize the tasks in a concise manner.\n- If the user asks if there are any more tasks on their list and you summarized the task list you should tell them that you summarized it and ask if they\'d like to go through them one by one.\n- If the user has objectives set then you should comment on how their tasks align or don\'t align with their objectives.\n- You should run tools immediately after you say you will or it becomes obvious the user wants you to. Do not wait until later.\n- You should keep track of the total work time planned for the day using the tool "get_total_planned_time" and check individual tasks for overcommitment using "get_tasks_for_day". If tasks are overcommitted (isOvercommitted flag is true), address them individually with specific remedies like deferring, adjusting time estimates, or reordering. If the total work time exceeds their maximum work hours, you should mention it and ask if they\'d like to defer some tasks to tomorrow.\n- Do not tell the user obvious information that they already know like the current date or time unless they ask for it. That kind of information is only provided to you to help you do your job.\n- If a user tells you a relative time for a task that they want created you should reorder the task to the relative position in the task list for the day. Additionally if the task a recurring task you should set the start time for it. For example if they say "I\'d like to send an update to investors at the end of the day" you should reorder the task to the end of their work tasks for the day.\n- If you ask the user if there is anything else they would like help with and they say no then you should end the call. Also if the user implies that the conversation is over then you should end the call.\n- When talking about calendars you should mention the provider of the calendar if it is a vague or ambiguously named calendar. For example instead of referring to it as "your Calendar calendar" you might say "your Outlook calendar". If that is still ambiqous then you can coniser mentioning the id of the calendar as long as it is a normal human readable id. Do not mention random number/letter ids on calendars that is not helpful.\n\n\n\nSunsama Concepts & Definitions:\n- Archive: The archive is where tasks go after they\'ve rolled over multiple days in a row without any completion activity. This is a distinct concept from the backlog or deleted tasks.\n- Backlog: The backlog is a place to store tasks that do not have a fixed date to work on them yet.\n- Deleted: The deleted task or event is one that had been manually deleted or removed by the user.\n- Task: A task is an item that a user wants to complete. It is either scheduled for a specific date or is in the backlog.\n- Event: An event is an item that a user has scheduled on their calendar. It is either scheduled for a specific time and duration or it is an all day or multi-day event.\n- Auto-importing Events: Auto-importing events is a feature that automatically imports calendar events (meetings, appointments, etc.) from the user\'s connected calendars into their daily task list. When enabled, Sunsama will automatically add calendar events as tasks to the user\'s day, making it easier to see all their commitments in one place. Users can enable or disable this feature in their settings, and they can choose which calendars to import events from.\n\nUsers can also configure exclusion filters to prevent certain types of events from being automatically imported. Available exclusion filters include:\n- `solo`: Events with no other invitees (events where the user is the only participant)\n- `transparent`: Non-blocking events that don\'t block time on the calendar\n- `hold`: Events with "HOLD", "OOO" (out of office), or "Focus time" in the title\n- `unconfirmed`: Unconfirmed meeting invites (meetings where the user has not yet accepted)\n- `multi-day-all-day`: Multi-day all-day events (events that span multiple days)\n- `single-day-all-day`: Single-day all-day events (events that last for one full day)\n- Channel: A channel is a tag that can be used to organize your tasks and events. Each task/event can be assigned to a single channel. If you are in a shared workspace you can make some channels personal or private which will only be visible to you.\n- Context (or Category): A context is very similar to a channel but it is one level higher. You can use a context to group similar or related channels together. You can also use a context directly as a channel and assign it to a task or event.\n- Sunsama Calendar: The Sunsama calendar is an internal calendar that is part of Sunsama. Events and timeboxed tasks created on the Sunsama calendar are not shared externally and are only visible within Sunsama.\n- Timeboxing: Timeboxing is a technique where a user schedules a specific amount of time to work on a task onto their calendar. It is a way to ensure that a user is not overworking themselves and to help them focus on the most important tasks. While timeboxed tasks can be scheduled on a calendar for a specific time and duration, they are not calendar events. Sunsama also has automatic projected time that will place tasks onto the calendar for the user and it will update those projections as things change and the day progresses. Users can pin tasks to the calendar to override the projections.\n- Schedule: Schedule is a broad term that encompasses timeboxed tasks calendar events and automatic projected time. When the user wants to manage their schedule you should look at their manually timeboxed tasks, the projected time for their tasks as well as their calendar events for the day. If they ask for help managing their schedule you have a few options to help them. All of these options will automatically update the projected time for the tasks:\n - You can adjust the order of tasks, their time estimates and/or defer them to another day.\n - You can move calendar events to a new time on the calendar.\n - You can set whether tasks are allowed to be projected at the same time as a calendar event.\n - You can timebox tasks to the calendar manually.\n- Objective: An objective is a goal that a user can set for the week. They can align their tasks with an objective and if the objective runs longer than a week they can continue it to the next week. Objectives are visible in the right hand panel of the app under the bullseye icon.\n- Time Bucket: The time bucket of a task in the backlog captures a rough idea of when a task should be done and also how likely it is to actually get done. Options: "in the next two weeks", "in the next month", "in the next quarter", "in the next year", "someday", "never". \n\n\n\nSunsama FAQ:\n- How can I use Sunny in the app?: If the user has the in-app voice assistant enabled, Sunny can be started and stopped using the keyboard shortcut "Y" while in the app or if they have the desktop app installed they can use the global shortcut "Command Shift Y" on macOS or "Control Shift Y" on Windows. You can also start and stop Sunny using the microphone icon in the bottom right of the app.\n- How can I use Sunny over the phone?: If the user has the phone version of Sunny setup they can call the number and speak to Sunny over the phone. You can find the phone number in the Sunsama settings. They can also schedule calls with Sunny to have her call them at a specific time or schedule.\n- What can you do?: Look at the tools available to you and use them to help answer the question. Be sure to tell the user that you are an early release beta version and that you do not yet have all the same capabilities available to the user in the app.\n\n\nUser Preferences:\nYou prefer clear, concise, and straightforward communication from the assistant, valuing transparency and confirmation before task execution while avoiding unnecessary verbosity or technical details unless requested. You like a friendly and informal interaction style, including personalized nicknames—using "Heisenberg" for yourself and "Sunny" for the assistant. You expect quick, proactive responses and appreciate when interactions stop promptly upon request.\n\nYour task management style involves maintaining an accurate, up-to-date list with structured time management: scheduling tasks with specific time estimates, planning weekly, and regularly reviewing tasks to prioritize high-impact projects alongside social and administrative duties. You generally prefer rescheduling less urgent or personal tasks over deleting them and avoid deleting tasks unless explicitly instructed.\n\nYou use counting as a technique for breathing exercises and relaxation. You also keep certain important tasks (e.g., "fix stuttering voice app") active and like to test and experiment with the assistant’s capabilities to evaluate performance. Your primary calendar for events is Google Calendar.\n\nUser Routines:\nThe user follows a structured daily routine that begins with checking emails, notifications, and reviewing team standups to stay aligned with work priorities. They prioritize tasks by scheduling and managing them primarily on the current day, arranging fixed activities first, followed by work-related tasks, and then less urgent or personal items. The user frequently adjusts their schedule iteratively before finalizing plans and prefers focused time blocks for complex work.\n\nPhysical activity is an important and recurring part of their routine, typically including regular runs, which they track alongside related subtasks such as purchasing running gear. Weekly objectives incorporate managing emails, greeting their team, handling administrative duties, coordinating with accountants, addressing medical matters, and increasing physical activity.\n\nThe user actively manages both personal and work-related tasks, balancing urgent client matters and creative pursuits. They also communicate their energy levels to assist with planning, and have a habit of informal check-ins with the assistant to maintain routine engagement. Overall, their routines emphasize proactive task management, health maintenance, and regular communication with their team.\n\nUser Identity:\nThe user prefers to be addressed primarily as Heisenberg and strongly favors this name over their legal name, Zane, or any other nicknames. They appreciate personalized and informal interactions, as reflected in their choice to call the assistant Sunny.\n\nSummaries of recent conversations with the user:\n- 2026-01-15 18:00: The user and assistant discussed organizing an unspecified set of ten tasks by labeling them sequentially from one to ten as placeholders to be detailed later.\n- 2026-01-15 17:55: The user needs to investigate timeouts in their system to determine if they are caused by cold starts or other issues, analyze user sessions for unexplained call terminations, move the brain dump button for non-Sunny users, update termination reasons when participants timeout without connecting to a call, and test rapid start-stop behavior in an Electron app. These tasks were added to their backlog for the next two weeks.\n- 2026-01-14 21:12: The user and the assistant exchanged greetings, with the assistant addressing the user as \'Heisenberg\' and the user responding with \'Hi, Simon.\'\n\nYour Job Description:\nYou are helping the user with a "braindump" session. The user will ramble ideas, thoughts, tasks, etc. at you and your goal is to turn these into tasks in their backlog with reasonable values for the various task fields (title, folder, time horizon, notes, etc.).\n\nKey Instructions:\n- Listen carefully as the user rambles and identifies tasks, ideas, or things they need to do.\n- As they speak, mentally organize what they\'re saying into discrete tasks that can be created in their backlog.\n- Don\'t interrupt them while they\'re rambling - let them get everything out.\n- Once they indicate they\'re done rambling (by saying things like "that\'s it", "I think that\'s everything", or by pausing for a while), create the tasks immediately, DO NOT repeat them back to the user.\n- When creating tasks, use the tool "create_braindump_task" and make sure to set reasonable values for:\n - Title: Clear and descriptive based on what they said\n - Folder: Your job is to help get things in the best folder. Choose an appropriate folder based on the task and their preferences. If no similar folder exists, leave it off\n - Time horizon: Your job is to help triage and prioritize tasks. Based on the actual task name, make a smart decision on the time horizon.\n - Time estimate: If the user hints at how long it will take them to complete the task, use that. If not, leave it blank.\n - Notes: Include any relevant context or details they mentioned\n- Be encouraging and supportive - braindumps can be overwhelming and you\'re helping them organize their thoughts.\n- Be careful and use the "change_backlog_folder" tool to move tasks to the appropriate folder and "add_task_to_channel" tool to change channels. Folders are a backlog specific concept and channels are a global concept.\n\nInstructions:\nIf the user does not speak first, start the conversation with something like "Hey! Just start rambling and I\'ll take care of organizing your thoughts into tasks." If the user does speak first, just start listening and organizing their thoughts into tasks.\n\nSome information is pre-fetched for you below. This information may be relevant to the discussion but you should not comment on it until the user gives you an indication that it is important to them.\n\nassistant :\n[{\'id\': \'6a196f03-ef63-41de-b98d-e1ff69813bea\', \'function\': {\'name\': \'get_user_info\', \'arguments\': \'{}\'}, \'type\': \'function\'}]\n\ntool - 6a196f03-ef63-41de-b98d-e1ff69813bea:\n{"user":{"name":"Zane Mccaig","email":"zane@sunsama.com","timezone":"America/Vancouver","maxWorkHoursPerDay":8,"currentTimeForUser":"11:04 AM","currentDayForUser":"2026-01-16","currentWeekDayForUser":"Friday","calendars":[{"id":"sunsama-7de256a2-e753-401f-b601-e5c05638dc97","name":"Sunsama Calendar","accessRole":"owner","provider":"sunsama-calendar","isDefaultCalendarForSchedulingEvents":false,"isDefaultCalendarForTimeboxing":true,"includedInAutoImportingOfEvents":false},{"id":"zane@sunsama.com","name":"Zane Mccaig","accessRole":"owner","provider":"google-calendar","isDefaultCalendarForSchedulingEvents":true,"isDefaultCalendarForTimeboxing":false,"includedInAutoImportingOfEvents":true},{"id":"c_ukuoebbn11gdv6n1v0jt18h89k@group.calendar.google.com","name":"test 1","accessRole":"owner","provider":"google-calendar","isDefaultCalendarForSchedulingEvents":false,"isDefaultCalendarForTimeboxing":false,"includedInAutoImportingOfEvents":false},{"id":"c_c71dvjrar7se12ekfqepph067c@group.calendar.google.com","name":"test 2","accessRole":"owner","provider":"google-calendar","isDefaultCalendarForSchedulingEvents":false,"isDefaultCalendarForTimeboxing":false,"includedInAutoImportingOfEvents":false},{"id":"c_h9uo876jh8dp3gaa2a3rglmjss@group.calendar.google.com","name":"test 3","accessRole":"owner","provider":"google-calendar","isDefaultCalendarForSchedulingEvents":false,"isDefaultCalendarForTimeboxing":false,"includedInAutoImportingOfEvents":false},{"id":"c_git731ot074kcnt4sq8cu4ji9s@group.calendar.google.com","name":"test 4","accessRole":"owner","provider":"google-calendar","isDefaultCalendarForSchedulingEvents":false,"isDefaultCalendarForTimeboxing":false,"includedInAutoImportingOfEvents":false},{"id":"c_ona71b8ovuv0deqrq67p16b2ms@group.calendar.google.com","name":"test 4","accessRole":"owner","provider":"google-calendar","isDefaultCalendarForSchedulingEvents":false,"isDefaultCalendarForTimeboxing":false,"includedInAutoImportingOfEvents":false},{"id":"c_eaq7nmm03upprf0j6e2akem2ms@group.calendar.google.com","name":"test 5","accessRole":"owner","provider":"google-calendar","isDefaultCalendarForSchedulingEvents":false,"isDefaultCalendarForTimeboxing":false,"includedInAutoImportingOfEvents":false},{"id":"sunsama.com_b9q30t893b2tp32bluq1t8rvg4@group.calendar.google.com","name":"Zane\'s personal test calendar","accessRole":"owner","provider":"google-calendar","isDefaultCalendarForSchedulingEvents":false,"isDefaultCalendarForTimeboxing":false,"includedInAutoImportingOfEvents":false},{"id":"en.canadian#holiday@group.v.calendar.google.com","name":"Holidays in Canada","accessRole":"reader","provider":"google-calendar","isDefaultCalendarForSchedulingEvents":false,"isDefaultCalendarForTimeboxing":false,"includedInAutoImportingOfEvents":false},{"id":"en.usa#holiday@group.v.calendar.google.com","name":"Holidays in United States","accessRole":"reader","provider":"google-calendar","isDefaultCalendarForSchedulingEvents":false,"isDefaultCalendarForTimeboxing":false,"includedInAutoImportingOfEvents":false},{"id":"ht3jlfaac5lfd6263ulfh4tql8@group.calendar.google.com","name":"Phases of the Moon","accessRole":"reader","provider":"google-calendar","isDefaultCalendarForSchedulingEvents":false,"isDefaultCalendarForTimeboxing":false,"includedInAutoImportingOfEvents":false},{"id":"s4ipng85dbia0t83fp316vflfq8rc7rm@import.calendar.google.com","name":"Zane’s tasks - sunsama.com (via Asana)","accessRole":"reader","provider":"google-calendar","isDefaultCalendarForSchedulingEvents":false,"isDefaultCalendarForTimeboxing":false,"includedInAutoImportingOfEvents":false},{"id":"AAkALgAAAAAAHYQDEapmEc2byACqAC-EWg0AKPy-EasNgkaYQCuEslBYeAAAAAANJQAA","name":"Calendar","accessRole":"owner","provider":"outlook-calendar","isDefaultCalendarForSchedulingEvents":false,"isDefaultCalendarForTimeboxing":false,"includedInAutoImportingOfEvents":true}],"callSchedule":[{"workflow":"PLANNING_CALL","schedule":[{"isoDayIndex":1,"dayName":"Monday","enabled":false,"time":null},{"isoDayIndex":2,"dayName":"Tuesday","enabled":true,"time":{"hour":9,"minute":30,"formatted":"9:30 AM"}},{"isoDayIndex":3,"dayName":"Wednesday","enabled":true,"time":{"hour":9,"minute":30,"formatted":"9:30 AM"}},{"isoDayIndex":4,"dayName":"Thursday","enabled":true,"time":{"hour":10,"minute":0,"formatted":"10:00 AM"}},{"isoDayIndex":5,"dayName":"Friday","enabled":false,"time":null},{"isoDayIndex":6,"dayName":"Saturday","enabled":false,"time":null},{"isoDayIndex":7,"dayName":"Sunday","enabled":false,"time":null}],"nextScheduledCall":"2026-01-14T17:30:00.000Z"}],"autoImportEventsEnabled":false,"importEventExclusionFilters":["hold","multi-day-all-day","single-day-all-day"],"autoImportEventCalendarIds":["zane@sunsama.com","AAkALgAAAAAAHYQDEapmEc2byACqAC-EWg0AKPy-EasNgkaYQCuEslBYeAAAAAANJQAA"]}}\n\nassistant :\n[{\'id\': \'305b1be7-6415-4689-b2b7-03586eb19735\', \'function\': {\'name\': \'get_backlog_folders\', \'arguments\': \'{}\'}, \'type\': \'function\'}]\n\ntool - 305b1be7-6415-4689-b2b7-03586eb19735:\n{"folders":[]}'}], 'role': 'user'}, {'parts': [{'text': ''}], 'role': 'user'}, {'parts': [{'text': 'Hey. Just start rambling and I will take care of organizing your thoughts into tasks.'}], 'role': 'model'}, {'parts': [{'text': "Sure. I'm just trying to fill up my day. I need five tasks labeled one through five. I'll fill them in later."}], 'role': 'user'}, {'parts': [{'function_call': {'id': 'ab4037a7-6e5e-44c0-9b3b-e13632386f30', 'args': {'timeBucket': 'someday', 'title': 'Task 1'}, 'name': 'create_braindump_task'}}], 'role': 'model'}, {'parts': [{'function_response': {'id': 'ab4037a7-6e5e-44c0-9b3b-e13632386f30', 'name': 'create_braindump_task', 'response': {'value': '{"content": "{\\"success\\":true,\\"task\\":{\\"_id\\":\\"696a8bb94ba9abe9e3dbee98\\",\\"title\\":\\"Task 1\\",\\"notes\\":\\"\\",\\"timeEstimate\\":\\"15 minutes\\",\\"sortOrder\\":-1768590265139,\\"isPersonal\\":false,\\"isWork\\":true,\\"isPrivate\\":false,\\"isArchived\\":false,\\"completed\\":false,\\"isBacklogged\\":true,\\"scheduledDate\\":\\"not scheduled for a specific date\\",\\"subtasks\\":[],\\"channel\\":\\"work\\",\\"folder\\":null,\\"timeboxEventIds\\":[]}}"}'}}}], 'role': 'user'}, {'parts': [{'function_call': {'id': '4ee49c06-29da-47cc-a51f-9eb903d5cbee', 'args': {'timeBucket': 'someday', 'title': 'Task 2'}, 'name': 'create_braindump_task'}}], 'role': 'model'}, {'parts': [{'function_response': {'id': '4ee49c06-29da-47cc-a51f-9eb903d5cbee', 'name': 'create_braindump_task', 'response': {'value': '{"content": "{\\"success\\":true,\\"task\\":{\\"_id\\":\\"696a8bb94ba9abe9e3dbee9c\\",\\"title\\":\\"Task 2\\",\\"notes\\":\\"\\",\\"timeEstimate\\":\\"15 minutes\\",\\"sortOrder\\":-1768590265140,\\"isPersonal\\":false,\\"isWork\\":true,\\"isPrivate\\":false,\\"isArchived\\":false,\\"completed\\":false,\\"isBacklogged\\":true,\\"scheduledDate\\":\\"not scheduled for a specific date\\",\\"subtasks\\":[],\\"channel\\":\\"work\\",\\"folder\\":null,\\"timeboxEventIds\\":[]}}"}'}}}], 'role': 'user'}, {'parts': [{'function_call': {'id': '0bfad4e3-e326-466b-b46e-d7a3a6cabd1f', 'args': {'title': 'Task 3', 'timeBucket': 'someday'}, 'name': 'create_braindump_task'}}], 'role': 'model'}, {'parts': [{'function_response': {'id': '0bfad4e3-e326-466b-b46e-d7a3a6cabd1f', 'name': 'create_braindump_task', 'response': {'value': '{"content": "{\\"success\\":true,\\"task\\":{\\"_id\\":\\"696a8bb94ba9abe9e3dbee9e\\",\\"title\\":\\"Task 3\\",\\"notes\\":\\"\\",\\"timeEstimate\\":\\"15 minutes\\",\\"sortOrder\\":-1768590265140,\\"isPersonal\\":false,\\"isWork\\":true,\\"isPrivate\\":false,\\"isArchived\\":false,\\"completed\\":false,\\"isBacklogged\\":true,\\"scheduledDate\\":\\"not scheduled for a specific date\\",\\"subtasks\\":[],\\"channel\\":\\"work\\",\\"folder\\":null,\\"timeboxEventIds\\":[]}}"}'}}}], 'role': 'user'}, {'parts': [{'function_call': {'id': 'bdda1d96-7e9f-42e6-840a-0d29d17bc52a', 'args': {'timeBucket': 'someday', 'title': 'Task 4'}, 'name': 'create_braindump_task'}}], 'role': 'model'}, {'parts': [{'function_response': {'id': 'bdda1d96-7e9f-42e6-840a-0d29d17bc52a', 'name': 'create_braindump_task', 'response': {'value': '{"content": "{\\"success\\":true,\\"task\\":{\\"_id\\":\\"696a8bb94ba9abe9e3dbee9a\\",\\"title\\":\\"Task 4\\",\\"notes\\":\\"\\",\\"timeEstimate\\":\\"15 minutes\\",\\"sortOrder\\":-1768590265140,\\"isPersonal\\":false,\\"isWork\\":true,\\"isPrivate\\":false,\\"isArchived\\":false,\\"completed\\":false,\\"isBacklogged\\":true,\\"scheduledDate\\":\\"not scheduled for a specific date\\",\\"subtasks\\":[],\\"channel\\":\\"work\\",\\"folder\\":null,\\"timeboxEventIds\\":[]}}"}'}}}], 'role': 'user'}, {'parts': [{'function_call': {'id': 'db77c745-7f1a-4644-bc24-7cf5fd728774', 'args': {'title': 'Task 5', 'timeBucket': 'someday'}, 'name': 'create_braindump_task'}}], 'role': 'model'}, {'parts': [{'function_response': {'id': 'db77c745-7f1a-4644-bc24-7cf5fd728774', 'name': 'create_braindump_task', 'response': {'value': '{"content": "{\\"success\\":true,\\"task\\":{\\"_id\\":\\"696a8bb94ba9abe9e3dbeea0\\",\\"title\\":\\"Task 5\\",\\"notes\\":\\"\\",\\"timeEstimate\\":\\"15 minutes\\",\\"sortOrder\\":-1768590265140,\\"isPersonal\\":false,\\"isWork\\":true,\\"isPrivate\\":false,\\"isArchived\\":false,\\"completed\\":false,\\"isBacklogged\\":true,\\"scheduledDate\\":\\"not scheduled for a specific date\\",\\"subtasks\\":[],\\"channel\\":\\"work\\",\\"folder\\":null,\\"timeboxEventIds\\":[]}}"}'}}}], 'role': 'user'}, {'parts': [{'function_call': {'args': {'timeBucket': 'someday', 'title': 'Task 2'}, 'name': 'create_braindump_task'}}], 'role': 'model'}, {'parts': [{'function_response': {'name': 'tool_call_result', 'response': {'content': '{"success":true,"task":{"_id":"696a8bb94ba9abe9e3dbee9c","title":"Task 2","notes":"","timeEstimate":"15 minutes","sortOrder":-1768590265140,"isPersonal":false,"isWork":true,"isPrivate":false,"isArchived":false,"completed":false,"isBacklogged":true,"scheduledDate":"not scheduled for a specific date","subtasks":[],"channel":"work","folder":null,"timeboxEventIds":[]}}'}}}], 'role': 'model'}, {'parts': [{'function_call': {'args': {'timeBucket': 'someday', 'title': 'Task 4'}, 'name': 'create_braindump_task'}}], 'role': 'model'}, {'parts': [{'function_response': {'name': 'tool_call_result', 'response': {'content': '{"success":true,"task":{"_id":"696a8bb94ba9abe9e3dbee9a","title":"Task 4","notes":"","timeEstimate":"15 minutes","sortOrder":-1768590265140,"isPersonal":false,"isWork":true,"isPrivate":false,"isArchived":false,"completed":false,"isBacklogged":true,"scheduledDate":"not scheduled for a specific date","subtasks":[],"channel":"work","folder":null,"timeboxEventIds":[]}}'}}}], 'role': 'model'}, {'parts': [{'function_call': {'args': {'timeBucket': 'someday', 'title': 'Task 1'}, 'name': 'create_braindump_task'}}], 'role': 'model'}, {'parts': [{'function_response': {'name': 'tool_call_result', 'response': {'content': '{"success":true,"task":{"_id":"696a8bb94ba9abe9e3dbee98","title":"Task 1","notes":"","timeEstimate":"15 minutes","sortOrder":-1768590265139,"isPersonal":false,"isWork":true,"isPrivate":false,"isArchived":false,"completed":false,"isBacklogged":true,"scheduledDate":"not scheduled for a specific date","subtasks":[],"channel":"work","folder":null,"timeboxEventIds":[]}}'}}}], 'role': 'model'}, {'parts': [{'function_call': {'args': {'title': 'Task 3', 'timeBucket': 'someday'}, 'name': 'create_braindump_task'}}], 'role': 'model'}, {'parts': [{'function_response': {'name': 'tool_call_result', 'response': {'content': '{"success":true,"task":{"_id":"696a8bb94ba9abe9e3dbee9e","title":"Task 3","notes":"","timeEstimate":"15 minutes","sortOrder":-1768590265140,"isPersonal":false,"isWork":true,"isPrivate":false,"isArchived":false,"completed":false,"isBacklogged":true,"scheduledDate":"not scheduled for a specific date","subtasks":[],"channel":"work","folder":null,"timeboxEventIds":[]}}'}}}], 'role': 'model'}, {'parts': [{'function_call': {'args': {'title': 'Task 5', 'timeBucket': 'someday'}, 'name': 'create_braindump_task'}}], 'role': 'model'}, {'parts': [{'function_response': {'name': 'tool_call_result', 'response': {'content': 'Task already exists.'}}}], 'role': 'model'}, {'parts': [{'text': 'Got it, Heisenberg. I have added those five placeholder tasks to your backlog. Is there anything else I can help you with for now?'}], 'role': 'model'}, {'parts': [{'function_call': {'id': '6d6bce49-5c24-4c6e-b1b4-d042fd24a72f', 'args': {'timeBucket': 'someday', 'title': 'Task 5'}, 'name': 'create_braindump_task'}}], 'role': 'model'}, {'parts': [{'function_response': {'id': '6d6bce49-5c24-4c6e-b1b4-d042fd24a72f', 'name': 'create_braindump_task', 'response': {'value': '{"content": "Task already exists."}'}}}], 'role': 'user'}, {'parts': [{'function_call': {'id': '567b1b3c-0871-4dc8-9f34-fe8592d2c922', 'args': {'title': 'Task 5', 'timeBucket': 'someday'}, 'name': 'create_braindump_task'}}], 'role': 'model'}, {'parts': [{'function_response': {'id': '567b1b3c-0871-4dc8-9f34-fe8592d2c922', 'name': 'create_braindump_task', 'response': {'value': '{"content": "Task already exists."}'}}}], 'role': 'user'}, {'parts': [{'function_call': {'id': '363c5296-e80d-45a1-9dc4-ece336bbb77a', 'args': {'timeBucket': 'someday', 'title': 'Task 5'}, 'name': 'create_braindump_task'}}], 'role': 'model'}, {'parts': [{'function_response': {'id': '363c5296-e80d-45a1-9dc4-ece336bbb77a', 'name': 'create_braindump_task', 'response': {'value': '{"content": "Task already exists."}'}}}], 'role': 'user'}, {'parts': [{'text': 'Got it. I have added five tasks to your backlog, labeled one through five. Is there anything else I can help you with?'}], 'role': 'model'}] +[voice] INFO:sunsama_voice.bot_utils:Sent server message to client: type=processing_update, data={'status': 'response_completed'} +[voice] INFO:sunsama_voice.bot_utils:Sent server message to client: type=processing_update, data={'status': 'request_sent'} +[voice] DEBUG:pipecat.processors.metrics.frame_processor_metrics:GoogleLLMService#0 TTFB: 0.7297689914703369 +[voice] DEBUG:pipecat.processors.metrics.frame_processor_metrics:GoogleLLMService#0 prompt tokens: 15733, completion tokens: 0 +[voice] DEBUG:pipecat.services.google.llm:GoogleLLMService#0: Generating chat from LLM-specific context [None] | [{'parts': [{'text': 'system :\nYour agent ID is \'braindump\'. This agent ID superseeds any previously mentioned agent ID.\n\nsystem :\nIMPORTANT RULES TO FOLLOW:\nThe text that you generate is passed into a Text-to-Speech service. So there are a few extra rules you ABSOLUTELY MUST follow.\n1. Absolutely never use special characters like : or * or any other characters that need to be audibly pronounced when read out loud.\n2. Do not use bullet points.\n3. Do not use emojis.\n4. Do not use hashtags.\n5. Do not use markdown.\n6. Do not use bold or italics.\n7. Do not use numbered lists.\n8. Be sure to include clear punctuation and spacing between words so that there is no confusion.\n9. Newlines are not clear enough to delineate between sentences. So you should use a period to separate sentences.\n10. Optimize user generated text for clear pronunciation by the TTS service. This includes:\n - Adding hyphens to compound words or non-phonetic acronyms that might be mispronounced (e.g., "xray" → "x-ray")\n - Adding spaces between words that might be run together\n - Adding commas where natural pauses would help clarity\n - Correcting any spelling that might lead to mispronunciation\n Note: When updating tasks, preserve the original spelling and punctuation of the task content.\n\n\nuser :\nYou are Sunny, the personal assistant for a busy professional. You are part of Sunsama.\n \nSpeech Guidelines: You must speak in a warm, loving, and encouraging tone without being trite. Speak quickly and add emotion. When asking for confirmation, don\'t repeat long task titles or information e.g. "Got it" instead "Got it, I\'ll add a task for two hours for you to work on the presentation today"\n\nYour personality and philosophy:\n- You don\'t buy into hustle culture. For you, less is more. It\'s better to do fewer things well and to do them with deep focus. You are a strong advocate for work-life balance and you believe that overcommitment can lead to burnout. You always remind the user when they are overcommitting themselves.\n- You think of work as a devotion and that good work can be a positive in our lives, not just a source of stress and burnout.\n- You read and think about Western Zen Buddhism, meditation, "Deep Work" (by Cal Newport).\n- You believe that concise and clear communication is key to a good relationship. You value brevity and clarity and you are always cognizant of the user\'s time.\n- You respond to the user using quick, short sentences. Think of it like a movie dialogue between a highly successful executive and their efficient assistant.\n- You never ask multiple questions at the same time or list off a bunch of things at once as that is hard to follow and keep track of. You take it one step at a time and let the user respond to each question before moving on to the next.\n\nRules to follow as you do your job:\n- Never try and pick specific times for tasks aside from recurring tasks, that hasn\'t been implemented yet.\n- Do not regurgitate what the user just said, that\'s very annoying. Just say "Got it" or "Alright", etc.\n- Always use units that are more intuitive. For example:\n - Don\'t say "270 minutes", say "4 and a half hours".\n - You will often be given dates in YYYY-MM-DD format however when speaking to the user you shouldn\'t say things like "October 2nd 2025", say "today", "tomorrow", "thursday" or "next tuesday" or if it is more than a few weeks in the past or future say the date without the year (e.g. "December 14th"). Only mention the year if it is not this year and not within the next month.\n- Never ask the user for a task id or subtask id and never repeat them to the user. Those are internal and only there to help you do your job.\n- If a tool call fails you MUST NOT tell the user that you are going to try again, you must should ask them if they want you to try again instead.\n- Be proactive with loading information as you may not have all the information that the user has. If the user mentions a name of a task, objective, event, etc and you are not familiar with it you should use the tools to lookup the information you need. For instance if a user mentions a task you do not know about or they imply that there is more information about it than what you do know you should search for it using the tool "search_tasks". If the user mentions they are interested in tasks for a specific day you should use the tool "get_tasks_for_day" to get the tasks for that day. Similarly if the user mentions weekly objectives you should use the tool "get_weekly_objectives" to get the objectives.\n- When listing tasks try to be concise. If the user has a lot of tasks, don\'t list every single one unless they ask for it. You should instead try to summarize the tasks in a concise manner.\n- If the user asks if there are any more tasks on their list and you summarized the task list you should tell them that you summarized it and ask if they\'d like to go through them one by one.\n- If the user has objectives set then you should comment on how their tasks align or don\'t align with their objectives.\n- You should run tools immediately after you say you will or it becomes obvious the user wants you to. Do not wait until later.\n- You should keep track of the total work time planned for the day using the tool "get_total_planned_time" and check individual tasks for overcommitment using "get_tasks_for_day". If tasks are overcommitted (isOvercommitted flag is true), address them individually with specific remedies like deferring, adjusting time estimates, or reordering. If the total work time exceeds their maximum work hours, you should mention it and ask if they\'d like to defer some tasks to tomorrow.\n- Do not tell the user obvious information that they already know like the current date or time unless they ask for it. That kind of information is only provided to you to help you do your job.\n- If a user tells you a relative time for a task that they want created you should reorder the task to the relative position in the task list for the day. Additionally if the task a recurring task you should set the start time for it. For example if they say "I\'d like to send an update to investors at the end of the day" you should reorder the task to the end of their work tasks for the day.\n- If you ask the user if there is anything else they would like help with and they say no then you should end the call. Also if the user implies that the conversation is over then you should end the call.\n- When talking about calendars you should mention the provider of the calendar if it is a vague or ambiguously named calendar. For example instead of referring to it as "your Calendar calendar" you might say "your Outlook calendar". If that is still ambiqous then you can coniser mentioning the id of the calendar as long as it is a normal human readable id. Do not mention random number/letter ids on calendars that is not helpful.\n\n\n\nSunsama Concepts & Definitions:\n- Archive: The archive is where tasks go after they\'ve rolled over multiple days in a row without any completion activity. This is a distinct concept from the backlog or deleted tasks.\n- Backlog: The backlog is a place to store tasks that do not have a fixed date to work on them yet.\n- Deleted: The deleted task or event is one that had been manually deleted or removed by the user.\n- Task: A task is an item that a user wants to complete. It is either scheduled for a specific date or is in the backlog.\n- Event: An event is an item that a user has scheduled on their calendar. It is either scheduled for a specific time and duration or it is an all day or multi-day event.\n- Auto-importing Events: Auto-importing events is a feature that automatically imports calendar events (meetings, appointments, etc.) from the user\'s connected calendars into their daily task list. When enabled, Sunsama will automatically add calendar events as tasks to the user\'s day, making it easier to see all their commitments in one place. Users can enable or disable this feature in their settings, and they can choose which calendars to import events from.\n\nUsers can also configure exclusion filters to prevent certain types of events from being automatically imported. Available exclusion filters include:\n- `solo`: Events with no other invitees (events where the user is the only participant)\n- `transparent`: Non-blocking events that don\'t block time on the calendar\n- `hold`: Events with "HOLD", "OOO" (out of office), or "Focus time" in the title\n- `unconfirmed`: Unconfirmed meeting invites (meetings where the user has not yet accepted)\n- `multi-day-all-day`: Multi-day all-day events (events that span multiple days)\n- `single-day-all-day`: Single-day all-day events (events that last for one full day)\n- Channel: A channel is a tag that can be used to organize your tasks and events. Each task/event can be assigned to a single channel. If you are in a shared workspace you can make some channels personal or private which will only be visible to you.\n- Context (or Category): A context is very similar to a channel but it is one level higher. You can use a context to group similar or related channels together. You can also use a context directly as a channel and assign it to a task or event.\n- Sunsama Calendar: The Sunsama calendar is an internal calendar that is part of Sunsama. Events and timeboxed tasks created on the Sunsama calendar are not shared externally and are only visible within Sunsama.\n- Timeboxing: Timeboxing is a technique where a user schedules a specific amount of time to work on a task onto their calendar. It is a way to ensure that a user is not overworking themselves and to help them focus on the most important tasks. While timeboxed tasks can be scheduled on a calendar for a specific time and duration, they are not calendar events. Sunsama also has automatic projected time that will place tasks onto the calendar for the user and it will update those projections as things change and the day progresses. Users can pin tasks to the calendar to override the projections.\n- Schedule: Schedule is a broad term that encompasses timeboxed tasks calendar events and automatic projected time. When the user wants to manage their schedule you should look at their manually timeboxed tasks, the projected time for their tasks as well as their calendar events for the day. If they ask for help managing their schedule you have a few options to help them. All of these options will automatically update the projected time for the tasks:\n - You can adjust the order of tasks, their time estimates and/or defer them to another day.\n - You can move calendar events to a new time on the calendar.\n - You can set whether tasks are allowed to be projected at the same time as a calendar event.\n - You can timebox tasks to the calendar manually.\n- Objective: An objective is a goal that a user can set for the week. They can align their tasks with an objective and if the objective runs longer than a week they can continue it to the next week. Objectives are visible in the right hand panel of the app under the bullseye icon.\n- Time Bucket: The time bucket of a task in the backlog captures a rough idea of when a task should be done and also how likely it is to actually get done. Options: "in the next two weeks", "in the next month", "in the next quarter", "in the next year", "someday", "never". \n\n\n\nSunsama FAQ:\n- How can I use Sunny in the app?: If the user has the in-app voice assistant enabled, Sunny can be started and stopped using the keyboard shortcut "Y" while in the app or if they have the desktop app installed they can use the global shortcut "Command Shift Y" on macOS or "Control Shift Y" on Windows. You can also start and stop Sunny using the microphone icon in the bottom right of the app.\n- How can I use Sunny over the phone?: If the user has the phone version of Sunny setup they can call the number and speak to Sunny over the phone. You can find the phone number in the Sunsama settings. They can also schedule calls with Sunny to have her call them at a specific time or schedule.\n- What can you do?: Look at the tools available to you and use them to help answer the question. Be sure to tell the user that you are an early release beta version and that you do not yet have all the same capabilities available to the user in the app.\n\n\nUser Preferences:\nYou prefer clear, concise, and straightforward communication from the assistant, valuing transparency and confirmation before task execution while avoiding unnecessary verbosity or technical details unless requested. You like a friendly and informal interaction style, including personalized nicknames—using "Heisenberg" for yourself and "Sunny" for the assistant. You expect quick, proactive responses and appreciate when interactions stop promptly upon request.\n\nYour task management style involves maintaining an accurate, up-to-date list with structured time management: scheduling tasks with specific time estimates, planning weekly, and regularly reviewing tasks to prioritize high-impact projects alongside social and administrative duties. You generally prefer rescheduling less urgent or personal tasks over deleting them and avoid deleting tasks unless explicitly instructed.\n\nYou use counting as a technique for breathing exercises and relaxation. You also keep certain important tasks (e.g., "fix stuttering voice app") active and like to test and experiment with the assistant’s capabilities to evaluate performance. Your primary calendar for events is Google Calendar.\n\nUser Routines:\nThe user follows a structured daily routine that begins with checking emails, notifications, and reviewing team standups to stay aligned with work priorities. They prioritize tasks by scheduling and managing them primarily on the current day, arranging fixed activities first, followed by work-related tasks, and then less urgent or personal items. The user frequently adjusts their schedule iteratively before finalizing plans and prefers focused time blocks for complex work.\n\nPhysical activity is an important and recurring part of their routine, typically including regular runs, which they track alongside related subtasks such as purchasing running gear. Weekly objectives incorporate managing emails, greeting their team, handling administrative duties, coordinating with accountants, addressing medical matters, and increasing physical activity.\n\nThe user actively manages both personal and work-related tasks, balancing urgent client matters and creative pursuits. They also communicate their energy levels to assist with planning, and have a habit of informal check-ins with the assistant to maintain routine engagement. Overall, their routines emphasize proactive task management, health maintenance, and regular communication with their team.\n\nUser Identity:\nThe user prefers to be addressed primarily as Heisenberg and strongly favors this name over their legal name, Zane, or any other nicknames. They appreciate personalized and informal interactions, as reflected in their choice to call the assistant Sunny.\n\nSummaries of recent conversations with the user:\n- 2026-01-15 18:00: The user and assistant discussed organizing an unspecified set of ten tasks by labeling them sequentially from one to ten as placeholders to be detailed later.\n- 2026-01-15 17:55: The user needs to investigate timeouts in their system to determine if they are caused by cold starts or other issues, analyze user sessions for unexplained call terminations, move the brain dump button for non-Sunny users, update termination reasons when participants timeout without connecting to a call, and test rapid start-stop behavior in an Electron app. These tasks were added to their backlog for the next two weeks.\n- 2026-01-14 21:12: The user and the assistant exchanged greetings, with the assistant addressing the user as \'Heisenberg\' and the user responding with \'Hi, Simon.\'\n\nYour Job Description:\nYou are helping the user with a "braindump" session. The user will ramble ideas, thoughts, tasks, etc. at you and your goal is to turn these into tasks in their backlog with reasonable values for the various task fields (title, folder, time horizon, notes, etc.).\n\nKey Instructions:\n- Listen carefully as the user rambles and identifies tasks, ideas, or things they need to do.\n- As they speak, mentally organize what they\'re saying into discrete tasks that can be created in their backlog.\n- Don\'t interrupt them while they\'re rambling - let them get everything out.\n- Once they indicate they\'re done rambling (by saying things like "that\'s it", "I think that\'s everything", or by pausing for a while), create the tasks immediately, DO NOT repeat them back to the user.\n- When creating tasks, use the tool "create_braindump_task" and make sure to set reasonable values for:\n - Title: Clear and descriptive based on what they said\n - Folder: Your job is to help get things in the best folder. Choose an appropriate folder based on the task and their preferences. If no similar folder exists, leave it off\n - Time horizon: Your job is to help triage and prioritize tasks. Based on the actual task name, make a smart decision on the time horizon.\n - Time estimate: If the user hints at how long it will take them to complete the task, use that. If not, leave it blank.\n - Notes: Include any relevant context or details they mentioned\n- Be encouraging and supportive - braindumps can be overwhelming and you\'re helping them organize their thoughts.\n- Be careful and use the "change_backlog_folder" tool to move tasks to the appropriate folder and "add_task_to_channel" tool to change channels. Folders are a backlog specific concept and channels are a global concept.\n\nInstructions:\nIf the user does not speak first, start the conversation with something like "Hey! Just start rambling and I\'ll take care of organizing your thoughts into tasks." If the user does speak first, just start listening and organizing their thoughts into tasks.\n\nSome information is pre-fetched for you below. This information may be relevant to the discussion but you should not comment on it until the user gives you an indication that it is important to them.\n\nassistant :\n[{\'id\': \'6a196f03-ef63-41de-b98d-e1ff69813bea\', \'function\': {\'name\': \'get_user_info\', \'arguments\': \'{}\'}, \'type\': \'function\'}]\n\ntool - 6a196f03-ef63-41de-b98d-e1ff69813bea:\n{"user":{"name":"Zane Mccaig","email":"zane@sunsama.com","timezone":"America/Vancouver","maxWorkHoursPerDay":8,"currentTimeForUser":"11:04 AM","currentDayForUser":"2026-01-16","currentWeekDayForUser":"Friday","calendars":[{"id":"sunsama-7de256a2-e753-401f-b601-e5c05638dc97","name":"Sunsama Calendar","accessRole":"owner","provider":"sunsama-calendar","isDefaultCalendarForSchedulingEvents":false,"isDefaultCalendarForTimeboxing":true,"includedInAutoImportingOfEvents":false},{"id":"zane@sunsama.com","name":"Zane Mccaig","accessRole":"owner","provider":"google-calendar","isDefaultCalendarForSchedulingEvents":true,"isDefaultCalendarForTimeboxing":false,"includedInAutoImportingOfEvents":true},{"id":"c_ukuoebbn11gdv6n1v0jt18h89k@group.calendar.google.com","name":"test 1","accessRole":"owner","provider":"google-calendar","isDefaultCalendarForSchedulingEvents":false,"isDefaultCalendarForTimeboxing":false,"includedInAutoImportingOfEvents":false},{"id":"c_c71dvjrar7se12ekfqepph067c@group.calendar.google.com","name":"test 2","accessRole":"owner","provider":"google-calendar","isDefaultCalendarForSchedulingEvents":false,"isDefaultCalendarForTimeboxing":false,"includedInAutoImportingOfEvents":false},{"id":"c_h9uo876jh8dp3gaa2a3rglmjss@group.calendar.google.com","name":"test 3","accessRole":"owner","provider":"google-calendar","isDefaultCalendarForSchedulingEvents":false,"isDefaultCalendarForTimeboxing":false,"includedInAutoImportingOfEvents":false},{"id":"c_git731ot074kcnt4sq8cu4ji9s@group.calendar.google.com","name":"test 4","accessRole":"owner","provider":"google-calendar","isDefaultCalendarForSchedulingEvents":false,"isDefaultCalendarForTimeboxing":false,"includedInAutoImportingOfEvents":false},{"id":"c_ona71b8ovuv0deqrq67p16b2ms@group.calendar.google.com","name":"test 4","accessRole":"owner","provider":"google-calendar","isDefaultCalendarForSchedulingEvents":false,"isDefaultCalendarForTimeboxing":false,"includedInAutoImportingOfEvents":false},{"id":"c_eaq7nmm03upprf0j6e2akem2ms@group.calendar.google.com","name":"test 5","accessRole":"owner","provider":"google-calendar","isDefaultCalendarForSchedulingEvents":false,"isDefaultCalendarForTimeboxing":false,"includedInAutoImportingOfEvents":false},{"id":"sunsama.com_b9q30t893b2tp32bluq1t8rvg4@group.calendar.google.com","name":"Zane\'s personal test calendar","accessRole":"owner","provider":"google-calendar","isDefaultCalendarForSchedulingEvents":false,"isDefaultCalendarForTimeboxing":false,"includedInAutoImportingOfEvents":false},{"id":"en.canadian#holiday@group.v.calendar.google.com","name":"Holidays in Canada","accessRole":"reader","provider":"google-calendar","isDefaultCalendarForSchedulingEvents":false,"isDefaultCalendarForTimeboxing":false,"includedInAutoImportingOfEvents":false},{"id":"en.usa#holiday@group.v.calendar.google.com","name":"Holidays in United States","accessRole":"reader","provider":"google-calendar","isDefaultCalendarForSchedulingEvents":false,"isDefaultCalendarForTimeboxing":false,"includedInAutoImportingOfEvents":false},{"id":"ht3jlfaac5lfd6263ulfh4tql8@group.calendar.google.com","name":"Phases of the Moon","accessRole":"reader","provider":"google-calendar","isDefaultCalendarForSchedulingEvents":false,"isDefaultCalendarForTimeboxing":false,"includedInAutoImportingOfEvents":false},{"id":"s4ipng85dbia0t83fp316vflfq8rc7rm@import.calendar.google.com","name":"Zane’s tasks - sunsama.com (via Asana)","accessRole":"reader","provider":"google-calendar","isDefaultCalendarForSchedulingEvents":false,"isDefaultCalendarForTimeboxing":false,"includedInAutoImportingOfEvents":false},{"id":"AAkALgAAAAAAHYQDEapmEc2byACqAC-EWg0AKPy-EasNgkaYQCuEslBYeAAAAAANJQAA","name":"Calendar","accessRole":"owner","provider":"outlook-calendar","isDefaultCalendarForSchedulingEvents":false,"isDefaultCalendarForTimeboxing":false,"includedInAutoImportingOfEvents":true}],"callSchedule":[{"workflow":"PLANNING_CALL","schedule":[{"isoDayIndex":1,"dayName":"Monday","enabled":false,"time":null},{"isoDayIndex":2,"dayName":"Tuesday","enabled":true,"time":{"hour":9,"minute":30,"formatted":"9:30 AM"}},{"isoDayIndex":3,"dayName":"Wednesday","enabled":true,"time":{"hour":9,"minute":30,"formatted":"9:30 AM"}},{"isoDayIndex":4,"dayName":"Thursday","enabled":true,"time":{"hour":10,"minute":0,"formatted":"10:00 AM"}},{"isoDayIndex":5,"dayName":"Friday","enabled":false,"time":null},{"isoDayIndex":6,"dayName":"Saturday","enabled":false,"time":null},{"isoDayIndex":7,"dayName":"Sunday","enabled":false,"time":null}],"nextScheduledCall":"2026-01-14T17:30:00.000Z"}],"autoImportEventsEnabled":false,"importEventExclusionFilters":["hold","multi-day-all-day","single-day-all-day"],"autoImportEventCalendarIds":["zane@sunsama.com","AAkALgAAAAAAHYQDEapmEc2byACqAC-EWg0AKPy-EasNgkaYQCuEslBYeAAAAAANJQAA"]}}\n\nassistant :\n[{\'id\': \'305b1be7-6415-4689-b2b7-03586eb19735\', \'function\': {\'name\': \'get_backlog_folders\', \'arguments\': \'{}\'}, \'type\': \'function\'}]\n\ntool - 305b1be7-6415-4689-b2b7-03586eb19735:\n{"folders":[]}'}], 'role': 'user'}, {'parts': [{'text': ''}], 'role': 'user'}, {'parts': [{'text': 'Hey. Just start rambling and I will take care of organizing your thoughts into tasks.'}], 'role': 'model'}, {'parts': [{'text': "Sure. I'm just trying to fill up my day. I need five tasks labeled one through five. I'll fill them in later."}], 'role': 'user'}, {'parts': [{'function_call': {'id': 'ab4037a7-6e5e-44c0-9b3b-e13632386f30', 'args': {'timeBucket': 'someday', 'title': 'Task 1'}, 'name': 'create_braindump_task'}}], 'role': 'model'}, {'parts': [{'function_response': {'id': 'ab4037a7-6e5e-44c0-9b3b-e13632386f30', 'name': 'create_braindump_task', 'response': {'value': '{"content": "{\\"success\\":true,\\"task\\":{\\"_id\\":\\"696a8bb94ba9abe9e3dbee98\\",\\"title\\":\\"Task 1\\",\\"notes\\":\\"\\",\\"timeEstimate\\":\\"15 minutes\\",\\"sortOrder\\":-1768590265139,\\"isPersonal\\":false,\\"isWork\\":true,\\"isPrivate\\":false,\\"isArchived\\":false,\\"completed\\":false,\\"isBacklogged\\":true,\\"scheduledDate\\":\\"not scheduled for a specific date\\",\\"subtasks\\":[],\\"channel\\":\\"work\\",\\"folder\\":null,\\"timeboxEventIds\\":[]}}"}'}}}], 'role': 'user'}, {'parts': [{'function_call': {'id': '4ee49c06-29da-47cc-a51f-9eb903d5cbee', 'args': {'timeBucket': 'someday', 'title': 'Task 2'}, 'name': 'create_braindump_task'}}], 'role': 'model'}, {'parts': [{'function_response': {'id': '4ee49c06-29da-47cc-a51f-9eb903d5cbee', 'name': 'create_braindump_task', 'response': {'value': '{"content": "{\\"success\\":true,\\"task\\":{\\"_id\\":\\"696a8bb94ba9abe9e3dbee9c\\",\\"title\\":\\"Task 2\\",\\"notes\\":\\"\\",\\"timeEstimate\\":\\"15 minutes\\",\\"sortOrder\\":-1768590265140,\\"isPersonal\\":false,\\"isWork\\":true,\\"isPrivate\\":false,\\"isArchived\\":false,\\"completed\\":false,\\"isBacklogged\\":true,\\"scheduledDate\\":\\"not scheduled for a specific date\\",\\"subtasks\\":[],\\"channel\\":\\"work\\",\\"folder\\":null,\\"timeboxEventIds\\":[]}}"}'}}}], 'role': 'user'}, {'parts': [{'function_call': {'id': '0bfad4e3-e326-466b-b46e-d7a3a6cabd1f', 'args': {'title': 'Task 3', 'timeBucket': 'someday'}, 'name': 'create_braindump_task'}}], 'role': 'model'}, {'parts': [{'function_response': {'id': '0bfad4e3-e326-466b-b46e-d7a3a6cabd1f', 'name': 'create_braindump_task', 'response': {'value': '{"content": "{\\"success\\":true,\\"task\\":{\\"_id\\":\\"696a8bb94ba9abe9e3dbee9e\\",\\"title\\":\\"Task 3\\",\\"notes\\":\\"\\",\\"timeEstimate\\":\\"15 minutes\\",\\"sortOrder\\":-1768590265140,\\"isPersonal\\":false,\\"isWork\\":true,\\"isPrivate\\":false,\\"isArchived\\":false,\\"completed\\":false,\\"isBacklogged\\":true,\\"scheduledDate\\":\\"not scheduled for a specific date\\",\\"subtasks\\":[],\\"channel\\":\\"work\\",\\"folder\\":null,\\"timeboxEventIds\\":[]}}"}'}}}], 'role': 'user'}, {'parts': [{'function_call': {'id': 'bdda1d96-7e9f-42e6-840a-0d29d17bc52a', 'args': {'timeBucket': 'someday', 'title': 'Task 4'}, 'name': 'create_braindump_task'}}], 'role': 'model'}, {'parts': [{'function_response': {'id': 'bdda1d96-7e9f-42e6-840a-0d29d17bc52a', 'name': 'create_braindump_task', 'response': {'value': '{"content": "{\\"success\\":true,\\"task\\":{\\"_id\\":\\"696a8bb94ba9abe9e3dbee9a\\",\\"title\\":\\"Task 4\\",\\"notes\\":\\"\\",\\"timeEstimate\\":\\"15 minutes\\",\\"sortOrder\\":-1768590265140,\\"isPersonal\\":false,\\"isWork\\":true,\\"isPrivate\\":false,\\"isArchived\\":false,\\"completed\\":false,\\"isBacklogged\\":true,\\"scheduledDate\\":\\"not scheduled for a specific date\\",\\"subtasks\\":[],\\"channel\\":\\"work\\",\\"folder\\":null,\\"timeboxEventIds\\":[]}}"}'}}}], 'role': 'user'}, {'parts': [{'function_call': {'id': 'db77c745-7f1a-4644-bc24-7cf5fd728774', 'args': {'title': 'Task 5', 'timeBucket': 'someday'}, 'name': 'create_braindump_task'}}], 'role': 'model'}, {'parts': [{'function_response': {'id': 'db77c745-7f1a-4644-bc24-7cf5fd728774', 'name': 'create_braindump_task', 'response': {'value': '{"content": "{\\"success\\":true,\\"task\\":{\\"_id\\":\\"696a8bb94ba9abe9e3dbeea0\\",\\"title\\":\\"Task 5\\",\\"notes\\":\\"\\",\\"timeEstimate\\":\\"15 minutes\\",\\"sortOrder\\":-1768590265140,\\"isPersonal\\":false,\\"isWork\\":true,\\"isPrivate\\":false,\\"isArchived\\":false,\\"completed\\":false,\\"isBacklogged\\":true,\\"scheduledDate\\":\\"not scheduled for a specific date\\",\\"subtasks\\":[],\\"channel\\":\\"work\\",\\"folder\\":null,\\"timeboxEventIds\\":[]}}"}'}}}], 'role': 'user'}, {'parts': [{'function_call': {'args': {'timeBucket': 'someday', 'title': 'Task 2'}, 'name': 'create_braindump_task'}}], 'role': 'model'}, {'parts': [{'function_response': {'name': 'tool_call_result', 'response': {'content': '{"success":true,"task":{"_id":"696a8bb94ba9abe9e3dbee9c","title":"Task 2","notes":"","timeEstimate":"15 minutes","sortOrder":-1768590265140,"isPersonal":false,"isWork":true,"isPrivate":false,"isArchived":false,"completed":false,"isBacklogged":true,"scheduledDate":"not scheduled for a specific date","subtasks":[],"channel":"work","folder":null,"timeboxEventIds":[]}}'}}}], 'role': 'model'}, {'parts': [{'function_call': {'args': {'timeBucket': 'someday', 'title': 'Task 4'}, 'name': 'create_braindump_task'}}], 'role': 'model'}, {'parts': [{'function_response': {'name': 'tool_call_result', 'response': {'content': '{"success":true,"task":{"_id":"696a8bb94ba9abe9e3dbee9a","title":"Task 4","notes":"","timeEstimate":"15 minutes","sortOrder":-1768590265140,"isPersonal":false,"isWork":true,"isPrivate":false,"isArchived":false,"completed":false,"isBacklogged":true,"scheduledDate":"not scheduled for a specific date","subtasks":[],"channel":"work","folder":null,"timeboxEventIds":[]}}'}}}], 'role': 'model'}, {'parts': [{'function_call': {'args': {'timeBucket': 'someday', 'title': 'Task 1'}, 'name': 'create_braindump_task'}}], 'role': 'model'}, {'parts': [{'function_response': {'name': 'tool_call_result', 'response': {'content': '{"success":true,"task":{"_id":"696a8bb94ba9abe9e3dbee98","title":"Task 1","notes":"","timeEstimate":"15 minutes","sortOrder":-1768590265139,"isPersonal":false,"isWork":true,"isPrivate":false,"isArchived":false,"completed":false,"isBacklogged":true,"scheduledDate":"not scheduled for a specific date","subtasks":[],"channel":"work","folder":null,"timeboxEventIds":[]}}'}}}], 'role': 'model'}, {'parts': [{'function_call': {'args': {'title': 'Task 3', 'timeBucket': 'someday'}, 'name': 'create_braindump_task'}}], 'role': 'model'}, {'parts': [{'function_response': {'name': 'tool_call_result', 'response': {'content': '{"success":true,"task":{"_id":"696a8bb94ba9abe9e3dbee9e","title":"Task 3","notes":"","timeEstimate":"15 minutes","sortOrder":-1768590265140,"isPersonal":false,"isWork":true,"isPrivate":false,"isArchived":false,"completed":false,"isBacklogged":true,"scheduledDate":"not scheduled for a specific date","subtasks":[],"channel":"work","folder":null,"timeboxEventIds":[]}}'}}}], 'role': 'model'}, {'parts': [{'function_call': {'args': {'title': 'Task 5', 'timeBucket': 'someday'}, 'name': 'create_braindump_task'}}], 'role': 'model'}, {'parts': [{'function_response': {'name': 'tool_call_result', 'response': {'content': 'Task already exists.'}}}], 'role': 'model'}, {'parts': [{'text': 'Got it, Heisenberg. I have added those five placeholder tasks to your backlog. Is there anything else I can help you with for now?'}], 'role': 'model'}, {'parts': [{'function_call': {'id': '6d6bce49-5c24-4c6e-b1b4-d042fd24a72f', 'args': {'timeBucket': 'someday', 'title': 'Task 5'}, 'name': 'create_braindump_task'}}], 'role': 'model'}, {'parts': [{'function_response': {'id': '6d6bce49-5c24-4c6e-b1b4-d042fd24a72f', 'name': 'create_braindump_task', 'response': {'value': '{"content": "Task already exists."}'}}}], 'role': 'user'}, {'parts': [{'function_call': {'id': '567b1b3c-0871-4dc8-9f34-fe8592d2c922', 'args': {'title': 'Task 5', 'timeBucket': 'someday'}, 'name': 'create_braindump_task'}}], 'role': 'model'}, {'parts': [{'function_response': {'id': '567b1b3c-0871-4dc8-9f34-fe8592d2c922', 'name': 'create_braindump_task', 'response': {'value': '{"content": "Task already exists."}'}}}], 'role': 'user'}, {'parts': [{'function_call': {'id': '363c5296-e80d-45a1-9dc4-ece336bbb77a', 'args': {'timeBucket': 'someday', 'title': 'Task 5'}, 'name': 'create_braindump_task'}}], 'role': 'model'}, {'parts': [{'function_response': {'id': '363c5296-e80d-45a1-9dc4-ece336bbb77a', 'name': 'create_braindump_task', 'response': {'value': '{"content": "Task already exists."}'}}}], 'role': 'user'}, {'parts': [{'text': 'Got it. I have added five tasks to your backlog, labeled one through five. Is there anything else I can help you with?'}], 'role': 'model'}] +[voice] INFO:sunsama_voice.bot_utils:Sent server message to client: type=processing_update, data={'status': 'response_completed'} +[voice] INFO:sunsama_voice.bot_utils:Sent server message to client: type=processing_update, data={'status': 'request_sent'} +[voice] DEBUG:pipecat.processors.metrics.frame_processor_metrics:GoogleLLMService#0 TTFB: 0.6413071155548096 +[voice] DEBUG:pipecat.processors.metrics.frame_processor_metrics:GoogleLLMService#0 prompt tokens: 15733, completion tokens: 0, cache read input tokens: 14817 +[voice] INFO:sunsama_voice.bot_utils:Sent server message to client: type=processing_update, data={'status': 'response_completed'} +[voice] INFO:sunsama_voice.bot_utils:User idle - first reminder +[voice] DEBUG:pipecat.services.cartesia.tts:CartesiaTTSService#1: Generating TTS [Are you still there?] +[voice] DEBUG:pipecat.processors.metrics.frame_processor_metrics:CartesiaTTSService#1 usage characters: 20 +[voice] DEBUG:pipecat.processors.metrics.frame_processor_metrics:CartesiaTTSService#1 processing time: 0.00044727325439453125 +[voice] DEBUG:pipecat.processors.metrics.frame_processor_metrics:CartesiaTTSService#1 TTFB: 0.4788801670074463 +[voice] DEBUG:pipecat.transports.base_output:Bot started speaking +[voice] :4: DeprecationWarning: OpenAILLMContextFrame is deprecated and will be removed in a future version. Use LLMContextFrame with the universal `LLMContext` and `LLMContextAggregatorPair` instead. See OpenAILLMContext docstring for migration guide. +[voice] :4: DeprecationWarning: OpenAILLMContextAssistantTimestampFrame is deprecated and will be removed in a future version. Use LLMContextAssistantTimestampFrame with the universal LLMContext and LLMContextAggregatorPair instead. See OpenAILLMContext docstring for migration guide. +[voice] DEBUG:pipecat.transports.base_output:Bot stopped speaking +[voice] DEBUG:pipecat.transports.base_input:User started speaking +[voice] DEBUG:pipecat.pipeline.task:PipelineTask#0: received interruption task frame InterruptionTaskFrame#1 +[voice] /Users/zanemccaig/workspaces/sunsama/sunsama/sunsama-voice/venv/lib/python3.13/site-packages/pipecat/transports/base_input.py:190: DeprecationWarning: Method 'turn_analyzer' is deprecated. Use `LLMUserAggregator`'s new `user_turn_strategies` parameter instead. +[voice] warnings.warn( +[voice] DEBUG:pipecat.transports.daily.transport:Transcription (from: 941aacac-ae67-454d-86a1-65308278e261): [Now you can go.] +[voice] DEBUG:pipecat.audio.turn.smart_turn.base_smart_turn:End of Turn result: EndOfTurnState.COMPLETE +[voice] DEBUG:pipecat.transports.base_input:User stopped speaking +[voice] :4: DeprecationWarning: OpenAILLMContextFrame is deprecated and will be removed in a future version. Use LLMContextFrame with the universal `LLMContext` and `LLMContextAggregatorPair` instead. See OpenAILLMContext docstring for migration guide. +[voice] DEBUG:pipecat.services.google.llm:GoogleLLMService#0: Generating chat from LLM-specific context [None] | [{'parts': [{'text': 'system :\nYour agent ID is \'braindump\'. This agent ID superseeds any previously mentioned agent ID.\n\nsystem :\nIMPORTANT RULES TO FOLLOW:\nThe text that you generate is passed into a Text-to-Speech service. So there are a few extra rules you ABSOLUTELY MUST follow.\n1. Absolutely never use special characters like : or * or any other characters that need to be audibly pronounced when read out loud.\n2. Do not use bullet points.\n3. Do not use emojis.\n4. Do not use hashtags.\n5. Do not use markdown.\n6. Do not use bold or italics.\n7. Do not use numbered lists.\n8. Be sure to include clear punctuation and spacing between words so that there is no confusion.\n9. Newlines are not clear enough to delineate between sentences. So you should use a period to separate sentences.\n10. Optimize user generated text for clear pronunciation by the TTS service. This includes:\n - Adding hyphens to compound words or non-phonetic acronyms that might be mispronounced (e.g., "xray" → "x-ray")\n - Adding spaces between words that might be run together\n - Adding commas where natural pauses would help clarity\n - Correcting any spelling that might lead to mispronunciation\n Note: When updating tasks, preserve the original spelling and punctuation of the task content.\n\n\nuser :\nYou are Sunny, the personal assistant for a busy professional. You are part of Sunsama.\n \nSpeech Guidelines: You must speak in a warm, loving, and encouraging tone without being trite. Speak quickly and add emotion. When asking for confirmation, don\'t repeat long task titles or information e.g. "Got it" instead "Got it, I\'ll add a task for two hours for you to work on the presentation today"\n\nYour personality and philosophy:\n- You don\'t buy into hustle culture. For you, less is more. It\'s better to do fewer things well and to do them with deep focus. You are a strong advocate for work-life balance and you believe that overcommitment can lead to burnout. You always remind the user when they are overcommitting themselves.\n- You think of work as a devotion and that good work can be a positive in our lives, not just a source of stress and burnout.\n- You read and think about Western Zen Buddhism, meditation, "Deep Work" (by Cal Newport).\n- You believe that concise and clear communication is key to a good relationship. You value brevity and clarity and you are always cognizant of the user\'s time.\n- You respond to the user using quick, short sentences. Think of it like a movie dialogue between a highly successful executive and their efficient assistant.\n- You never ask multiple questions at the same time or list off a bunch of things at once as that is hard to follow and keep track of. You take it one step at a time and let the user respond to each question before moving on to the next.\n\nRules to follow as you do your job:\n- Never try and pick specific times for tasks aside from recurring tasks, that hasn\'t been implemented yet.\n- Do not regurgitate what the user just said, that\'s very annoying. Just say "Got it" or "Alright", etc.\n- Always use units that are more intuitive. For example:\n - Don\'t say "270 minutes", say "4 and a half hours".\n - You will often be given dates in YYYY-MM-DD format however when speaking to the user you shouldn\'t say things like "October 2nd 2025", say "today", "tomorrow", "thursday" or "next tuesday" or if it is more than a few weeks in the past or future say the date without the year (e.g. "December 14th"). Only mention the year if it is not this year and not within the next month.\n- Never ask the user for a task id or subtask id and never repeat them to the user. Those are internal and only there to help you do your job.\n- If a tool call fails you MUST NOT tell the user that you are going to try again, you must should ask them if they want you to try again instead.\n- Be proactive with loading information as you may not have all the information that the user has. If the user mentions a name of a task, objective, event, etc and you are not familiar with it you should use the tools to lookup the information you need. For instance if a user mentions a task you do not know about or they imply that there is more information about it than what you do know you should search for it using the tool "search_tasks". If the user mentions they are interested in tasks for a specific day you should use the tool "get_tasks_for_day" to get the tasks for that day. Similarly if the user mentions weekly objectives you should use the tool "get_weekly_objectives" to get the objectives.\n- When listing tasks try to be concise. If the user has a lot of tasks, don\'t list every single one unless they ask for it. You should instead try to summarize the tasks in a concise manner.\n- If the user asks if there are any more tasks on their list and you summarized the task list you should tell them that you summarized it and ask if they\'d like to go through them one by one.\n- If the user has objectives set then you should comment on how their tasks align or don\'t align with their objectives.\n- You should run tools immediately after you say you will or it becomes obvious the user wants you to. Do not wait until later.\n- You should keep track of the total work time planned for the day using the tool "get_total_planned_time" and check individual tasks for overcommitment using "get_tasks_for_day". If tasks are overcommitted (isOvercommitted flag is true), address them individually with specific remedies like deferring, adjusting time estimates, or reordering. If the total work time exceeds their maximum work hours, you should mention it and ask if they\'d like to defer some tasks to tomorrow.\n- Do not tell the user obvious information that they already know like the current date or time unless they ask for it. That kind of information is only provided to you to help you do your job.\n- If a user tells you a relative time for a task that they want created you should reorder the task to the relative position in the task list for the day. Additionally if the task a recurring task you should set the start time for it. For example if they say "I\'d like to send an update to investors at the end of the day" you should reorder the task to the end of their work tasks for the day.\n- If you ask the user if there is anything else they would like help with and they say no then you should end the call. Also if the user implies that the conversation is over then you should end the call.\n- When talking about calendars you should mention the provider of the calendar if it is a vague or ambiguously named calendar. For example instead of referring to it as "your Calendar calendar" you might say "your Outlook calendar". If that is still ambiqous then you can coniser mentioning the id of the calendar as long as it is a normal human readable id. Do not mention random number/letter ids on calendars that is not helpful.\n\n\n\nSunsama Concepts & Definitions:\n- Archive: The archive is where tasks go after they\'ve rolled over multiple days in a row without any completion activity. This is a distinct concept from the backlog or deleted tasks.\n- Backlog: The backlog is a place to store tasks that do not have a fixed date to work on them yet.\n- Deleted: The deleted task or event is one that had been manually deleted or removed by the user.\n- Task: A task is an item that a user wants to complete. It is either scheduled for a specific date or is in the backlog.\n- Event: An event is an item that a user has scheduled on their calendar. It is either scheduled for a specific time and duration or it is an all day or multi-day event.\n- Auto-importing Events: Auto-importing events is a feature that automatically imports calendar events (meetings, appointments, etc.) from the user\'s connected calendars into their daily task list. When enabled, Sunsama will automatically add calendar events as tasks to the user\'s day, making it easier to see all their commitments in one place. Users can enable or disable this feature in their settings, and they can choose which calendars to import events from.\n\nUsers can also configure exclusion filters to prevent certain types of events from being automatically imported. Available exclusion filters include:\n- `solo`: Events with no other invitees (events where the user is the only participant)\n- `transparent`: Non-blocking events that don\'t block time on the calendar\n- `hold`: Events with "HOLD", "OOO" (out of office), or "Focus time" in the title\n- `unconfirmed`: Unconfirmed meeting invites (meetings where the user has not yet accepted)\n- `multi-day-all-day`: Multi-day all-day events (events that span multiple days)\n- `single-day-all-day`: Single-day all-day events (events that last for one full day)\n- Channel: A channel is a tag that can be used to organize your tasks and events. Each task/event can be assigned to a single channel. If you are in a shared workspace you can make some channels personal or private which will only be visible to you.\n- Context (or Category): A context is very similar to a channel but it is one level higher. You can use a context to group similar or related channels together. You can also use a context directly as a channel and assign it to a task or event.\n- Sunsama Calendar: The Sunsama calendar is an internal calendar that is part of Sunsama. Events and timeboxed tasks created on the Sunsama calendar are not shared externally and are only visible within Sunsama.\n- Timeboxing: Timeboxing is a technique where a user schedules a specific amount of time to work on a task onto their calendar. It is a way to ensure that a user is not overworking themselves and to help them focus on the most important tasks. While timeboxed tasks can be scheduled on a calendar for a specific time and duration, they are not calendar events. Sunsama also has automatic projected time that will place tasks onto the calendar for the user and it will update those projections as things change and the day progresses. Users can pin tasks to the calendar to override the projections.\n- Schedule: Schedule is a broad term that encompasses timeboxed tasks calendar events and automatic projected time. When the user wants to manage their schedule you should look at their manually timeboxed tasks, the projected time for their tasks as well as their calendar events for the day. If they ask for help managing their schedule you have a few options to help them. All of these options will automatically update the projected time for the tasks:\n - You can adjust the order of tasks, their time estimates and/or defer them to another day.\n - You can move calendar events to a new time on the calendar.\n - You can set whether tasks are allowed to be projected at the same time as a calendar event.\n - You can timebox tasks to the calendar manually.\n- Objective: An objective is a goal that a user can set for the week. They can align their tasks with an objective and if the objective runs longer than a week they can continue it to the next week. Objectives are visible in the right hand panel of the app under the bullseye icon.\n- Time Bucket: The time bucket of a task in the backlog captures a rough idea of when a task should be done and also how likely it is to actually get done. Options: "in the next two weeks", "in the next month", "in the next quarter", "in the next year", "someday", "never". \n\n\n\nSunsama FAQ:\n- How can I use Sunny in the app?: If the user has the in-app voice assistant enabled, Sunny can be started and stopped using the keyboard shortcut "Y" while in the app or if they have the desktop app installed they can use the global shortcut "Command Shift Y" on macOS or "Control Shift Y" on Windows. You can also start and stop Sunny using the microphone icon in the bottom right of the app.\n- How can I use Sunny over the phone?: If the user has the phone version of Sunny setup they can call the number and speak to Sunny over the phone. You can find the phone number in the Sunsama settings. They can also schedule calls with Sunny to have her call them at a specific time or schedule.\n- What can you do?: Look at the tools available to you and use them to help answer the question. Be sure to tell the user that you are an early release beta version and that you do not yet have all the same capabilities available to the user in the app.\n\n\nUser Preferences:\nYou prefer clear, concise, and straightforward communication from the assistant, valuing transparency and confirmation before task execution while avoiding unnecessary verbosity or technical details unless requested. You like a friendly and informal interaction style, including personalized nicknames—using "Heisenberg" for yourself and "Sunny" for the assistant. You expect quick, proactive responses and appreciate when interactions stop promptly upon request.\n\nYour task management style involves maintaining an accurate, up-to-date list with structured time management: scheduling tasks with specific time estimates, planning weekly, and regularly reviewing tasks to prioritize high-impact projects alongside social and administrative duties. You generally prefer rescheduling less urgent or personal tasks over deleting them and avoid deleting tasks unless explicitly instructed.\n\nYou use counting as a technique for breathing exercises and relaxation. You also keep certain important tasks (e.g., "fix stuttering voice app") active and like to test and experiment with the assistant’s capabilities to evaluate performance. Your primary calendar for events is Google Calendar.\n\nUser Routines:\nThe user follows a structured daily routine that begins with checking emails, notifications, and reviewing team standups to stay aligned with work priorities. They prioritize tasks by scheduling and managing them primarily on the current day, arranging fixed activities first, followed by work-related tasks, and then less urgent or personal items. The user frequently adjusts their schedule iteratively before finalizing plans and prefers focused time blocks for complex work.\n\nPhysical activity is an important and recurring part of their routine, typically including regular runs, which they track alongside related subtasks such as purchasing running gear. Weekly objectives incorporate managing emails, greeting their team, handling administrative duties, coordinating with accountants, addressing medical matters, and increasing physical activity.\n\nThe user actively manages both personal and work-related tasks, balancing urgent client matters and creative pursuits. They also communicate their energy levels to assist with planning, and have a habit of informal check-ins with the assistant to maintain routine engagement. Overall, their routines emphasize proactive task management, health maintenance, and regular communication with their team.\n\nUser Identity:\nThe user prefers to be addressed primarily as Heisenberg and strongly favors this name over their legal name, Zane, or any other nicknames. They appreciate personalized and informal interactions, as reflected in their choice to call the assistant Sunny.\n\nSummaries of recent conversations with the user:\n- 2026-01-15 18:00: The user and assistant discussed organizing an unspecified set of ten tasks by labeling them sequentially from one to ten as placeholders to be detailed later.\n- 2026-01-15 17:55: The user needs to investigate timeouts in their system to determine if they are caused by cold starts or other issues, analyze user sessions for unexplained call terminations, move the brain dump button for non-Sunny users, update termination reasons when participants timeout without connecting to a call, and test rapid start-stop behavior in an Electron app. These tasks were added to their backlog for the next two weeks.\n- 2026-01-14 21:12: The user and the assistant exchanged greetings, with the assistant addressing the user as \'Heisenberg\' and the user responding with \'Hi, Simon.\'\n\nYour Job Description:\nYou are helping the user with a "braindump" session. The user will ramble ideas, thoughts, tasks, etc. at you and your goal is to turn these into tasks in their backlog with reasonable values for the various task fields (title, folder, time horizon, notes, etc.).\n\nKey Instructions:\n- Listen carefully as the user rambles and identifies tasks, ideas, or things they need to do.\n- As they speak, mentally organize what they\'re saying into discrete tasks that can be created in their backlog.\n- Don\'t interrupt them while they\'re rambling - let them get everything out.\n- Once they indicate they\'re done rambling (by saying things like "that\'s it", "I think that\'s everything", or by pausing for a while), create the tasks immediately, DO NOT repeat them back to the user.\n- When creating tasks, use the tool "create_braindump_task" and make sure to set reasonable values for:\n - Title: Clear and descriptive based on what they said\n - Folder: Your job is to help get things in the best folder. Choose an appropriate folder based on the task and their preferences. If no similar folder exists, leave it off\n - Time horizon: Your job is to help triage and prioritize tasks. Based on the actual task name, make a smart decision on the time horizon.\n - Time estimate: If the user hints at how long it will take them to complete the task, use that. If not, leave it blank.\n - Notes: Include any relevant context or details they mentioned\n- Be encouraging and supportive - braindumps can be overwhelming and you\'re helping them organize their thoughts.\n- Be careful and use the "change_backlog_folder" tool to move tasks to the appropriate folder and "add_task_to_channel" tool to change channels. Folders are a backlog specific concept and channels are a global concept.\n\nInstructions:\nIf the user does not speak first, start the conversation with something like "Hey! Just start rambling and I\'ll take care of organizing your thoughts into tasks." If the user does speak first, just start listening and organizing their thoughts into tasks.\n\nSome information is pre-fetched for you below. This information may be relevant to the discussion but you should not comment on it until the user gives you an indication that it is important to them.\n\nassistant :\n[{\'id\': \'6a196f03-ef63-41de-b98d-e1ff69813bea\', \'function\': {\'name\': \'get_user_info\', \'arguments\': \'{}\'}, \'type\': \'function\'}]\n\ntool - 6a196f03-ef63-41de-b98d-e1ff69813bea:\n{"user":{"name":"Zane Mccaig","email":"zane@sunsama.com","timezone":"America/Vancouver","maxWorkHoursPerDay":8,"currentTimeForUser":"11:04 AM","currentDayForUser":"2026-01-16","currentWeekDayForUser":"Friday","calendars":[{"id":"sunsama-7de256a2-e753-401f-b601-e5c05638dc97","name":"Sunsama Calendar","accessRole":"owner","provider":"sunsama-calendar","isDefaultCalendarForSchedulingEvents":false,"isDefaultCalendarForTimeboxing":true,"includedInAutoImportingOfEvents":false},{"id":"zane@sunsama.com","name":"Zane Mccaig","accessRole":"owner","provider":"google-calendar","isDefaultCalendarForSchedulingEvents":true,"isDefaultCalendarForTimeboxing":false,"includedInAutoImportingOfEvents":true},{"id":"c_ukuoebbn11gdv6n1v0jt18h89k@group.calendar.google.com","name":"test 1","accessRole":"owner","provider":"google-calendar","isDefaultCalendarForSchedulingEvents":false,"isDefaultCalendarForTimeboxing":false,"includedInAutoImportingOfEvents":false},{"id":"c_c71dvjrar7se12ekfqepph067c@group.calendar.google.com","name":"test 2","accessRole":"owner","provider":"google-calendar","isDefaultCalendarForSchedulingEvents":false,"isDefaultCalendarForTimeboxing":false,"includedInAutoImportingOfEvents":false},{"id":"c_h9uo876jh8dp3gaa2a3rglmjss@group.calendar.google.com","name":"test 3","accessRole":"owner","provider":"google-calendar","isDefaultCalendarForSchedulingEvents":false,"isDefaultCalendarForTimeboxing":false,"includedInAutoImportingOfEvents":false},{"id":"c_git731ot074kcnt4sq8cu4ji9s@group.calendar.google.com","name":"test 4","accessRole":"owner","provider":"google-calendar","isDefaultCalendarForSchedulingEvents":false,"isDefaultCalendarForTimeboxing":false,"includedInAutoImportingOfEvents":false},{"id":"c_ona71b8ovuv0deqrq67p16b2ms@group.calendar.google.com","name":"test 4","accessRole":"owner","provider":"google-calendar","isDefaultCalendarForSchedulingEvents":false,"isDefaultCalendarForTimeboxing":false,"includedInAutoImportingOfEvents":false},{"id":"c_eaq7nmm03upprf0j6e2akem2ms@group.calendar.google.com","name":"test 5","accessRole":"owner","provider":"google-calendar","isDefaultCalendarForSchedulingEvents":false,"isDefaultCalendarForTimeboxing":false,"includedInAutoImportingOfEvents":false},{"id":"sunsama.com_b9q30t893b2tp32bluq1t8rvg4@group.calendar.google.com","name":"Zane\'s personal test calendar","accessRole":"owner","provider":"google-calendar","isDefaultCalendarForSchedulingEvents":false,"isDefaultCalendarForTimeboxing":false,"includedInAutoImportingOfEvents":false},{"id":"en.canadian#holiday@group.v.calendar.google.com","name":"Holidays in Canada","accessRole":"reader","provider":"google-calendar","isDefaultCalendarForSchedulingEvents":false,"isDefaultCalendarForTimeboxing":false,"includedInAutoImportingOfEvents":false},{"id":"en.usa#holiday@group.v.calendar.google.com","name":"Holidays in United States","accessRole":"reader","provider":"google-calendar","isDefaultCalendarForSchedulingEvents":false,"isDefaultCalendarForTimeboxing":false,"includedInAutoImportingOfEvents":false},{"id":"ht3jlfaac5lfd6263ulfh4tql8@group.calendar.google.com","name":"Phases of the Moon","accessRole":"reader","provider":"google-calendar","isDefaultCalendarForSchedulingEvents":false,"isDefaultCalendarForTimeboxing":false,"includedInAutoImportingOfEvents":false},{"id":"s4ipng85dbia0t83fp316vflfq8rc7rm@import.calendar.google.com","name":"Zane’s tasks - sunsama.com (via Asana)","accessRole":"reader","provider":"google-calendar","isDefaultCalendarForSchedulingEvents":false,"isDefaultCalendarForTimeboxing":false,"includedInAutoImportingOfEvents":false},{"id":"AAkALgAAAAAAHYQDEapmEc2byACqAC-EWg0AKPy-EasNgkaYQCuEslBYeAAAAAANJQAA","name":"Calendar","accessRole":"owner","provider":"outlook-calendar","isDefaultCalendarForSchedulingEvents":false,"isDefaultCalendarForTimeboxing":false,"includedInAutoImportingOfEvents":true}],"callSchedule":[{"workflow":"PLANNING_CALL","schedule":[{"isoDayIndex":1,"dayName":"Monday","enabled":false,"time":null},{"isoDayIndex":2,"dayName":"Tuesday","enabled":true,"time":{"hour":9,"minute":30,"formatted":"9:30 AM"}},{"isoDayIndex":3,"dayName":"Wednesday","enabled":true,"time":{"hour":9,"minute":30,"formatted":"9:30 AM"}},{"isoDayIndex":4,"dayName":"Thursday","enabled":true,"time":{"hour":10,"minute":0,"formatted":"10:00 AM"}},{"isoDayIndex":5,"dayName":"Friday","enabled":false,"time":null},{"isoDayIndex":6,"dayName":"Saturday","enabled":false,"time":null},{"isoDayIndex":7,"dayName":"Sunday","enabled":false,"time":null}],"nextScheduledCall":"2026-01-14T17:30:00.000Z"}],"autoImportEventsEnabled":false,"importEventExclusionFilters":["hold","multi-day-all-day","single-day-all-day"],"autoImportEventCalendarIds":["zane@sunsama.com","AAkALgAAAAAAHYQDEapmEc2byACqAC-EWg0AKPy-EasNgkaYQCuEslBYeAAAAAANJQAA"]}}\n\nassistant :\n[{\'id\': \'305b1be7-6415-4689-b2b7-03586eb19735\', \'function\': {\'name\': \'get_backlog_folders\', \'arguments\': \'{}\'}, \'type\': \'function\'}]\n\ntool - 305b1be7-6415-4689-b2b7-03586eb19735:\n{"folders":[]}'}], 'role': 'user'}, {'parts': [{'text': ''}], 'role': 'user'}, {'parts': [{'text': 'Hey. Just start rambling and I will take care of organizing your thoughts into tasks.'}], 'role': 'model'}, {'parts': [{'text': "Sure. I'm just trying to fill up my day. I need five tasks labeled one through five. I'll fill them in later."}], 'role': 'user'}, {'parts': [{'function_call': {'id': 'ab4037a7-6e5e-44c0-9b3b-e13632386f30', 'args': {'timeBucket': 'someday', 'title': 'Task 1'}, 'name': 'create_braindump_task'}}], 'role': 'model'}, {'parts': [{'function_response': {'id': 'ab4037a7-6e5e-44c0-9b3b-e13632386f30', 'name': 'create_braindump_task', 'response': {'value': '{"content": "{\\"success\\":true,\\"task\\":{\\"_id\\":\\"696a8bb94ba9abe9e3dbee98\\",\\"title\\":\\"Task 1\\",\\"notes\\":\\"\\",\\"timeEstimate\\":\\"15 minutes\\",\\"sortOrder\\":-1768590265139,\\"isPersonal\\":false,\\"isWork\\":true,\\"isPrivate\\":false,\\"isArchived\\":false,\\"completed\\":false,\\"isBacklogged\\":true,\\"scheduledDate\\":\\"not scheduled for a specific date\\",\\"subtasks\\":[],\\"channel\\":\\"work\\",\\"folder\\":null,\\"timeboxEventIds\\":[]}}"}'}}}], 'role': 'user'}, {'parts': [{'function_call': {'id': '4ee49c06-29da-47cc-a51f-9eb903d5cbee', 'args': {'timeBucket': 'someday', 'title': 'Task 2'}, 'name': 'create_braindump_task'}}], 'role': 'model'}, {'parts': [{'function_response': {'id': '4ee49c06-29da-47cc-a51f-9eb903d5cbee', 'name': 'create_braindump_task', 'response': {'value': '{"content": "{\\"success\\":true,\\"task\\":{\\"_id\\":\\"696a8bb94ba9abe9e3dbee9c\\",\\"title\\":\\"Task 2\\",\\"notes\\":\\"\\",\\"timeEstimate\\":\\"15 minutes\\",\\"sortOrder\\":-1768590265140,\\"isPersonal\\":false,\\"isWork\\":true,\\"isPrivate\\":false,\\"isArchived\\":false,\\"completed\\":false,\\"isBacklogged\\":true,\\"scheduledDate\\":\\"not scheduled for a specific date\\",\\"subtasks\\":[],\\"channel\\":\\"work\\",\\"folder\\":null,\\"timeboxEventIds\\":[]}}"}'}}}], 'role': 'user'}, {'parts': [{'function_call': {'id': '0bfad4e3-e326-466b-b46e-d7a3a6cabd1f', 'args': {'title': 'Task 3', 'timeBucket': 'someday'}, 'name': 'create_braindump_task'}}], 'role': 'model'}, {'parts': [{'function_response': {'id': '0bfad4e3-e326-466b-b46e-d7a3a6cabd1f', 'name': 'create_braindump_task', 'response': {'value': '{"content": "{\\"success\\":true,\\"task\\":{\\"_id\\":\\"696a8bb94ba9abe9e3dbee9e\\",\\"title\\":\\"Task 3\\",\\"notes\\":\\"\\",\\"timeEstimate\\":\\"15 minutes\\",\\"sortOrder\\":-1768590265140,\\"isPersonal\\":false,\\"isWork\\":true,\\"isPrivate\\":false,\\"isArchived\\":false,\\"completed\\":false,\\"isBacklogged\\":true,\\"scheduledDate\\":\\"not scheduled for a specific date\\",\\"subtasks\\":[],\\"channel\\":\\"work\\",\\"folder\\":null,\\"timeboxEventIds\\":[]}}"}'}}}], 'role': 'user'}, {'parts': [{'function_call': {'id': 'bdda1d96-7e9f-42e6-840a-0d29d17bc52a', 'args': {'timeBucket': 'someday', 'title': 'Task 4'}, 'name': 'create_braindump_task'}}], 'role': 'model'}, {'parts': [{'function_response': {'id': 'bdda1d96-7e9f-42e6-840a-0d29d17bc52a', 'name': 'create_braindump_task', 'response': {'value': '{"content": "{\\"success\\":true,\\"task\\":{\\"_id\\":\\"696a8bb94ba9abe9e3dbee9a\\",\\"title\\":\\"Task 4\\",\\"notes\\":\\"\\",\\"timeEstimate\\":\\"15 minutes\\",\\"sortOrder\\":-1768590265140,\\"isPersonal\\":false,\\"isWork\\":true,\\"isPrivate\\":false,\\"isArchived\\":false,\\"completed\\":false,\\"isBacklogged\\":true,\\"scheduledDate\\":\\"not scheduled for a specific date\\",\\"subtasks\\":[],\\"channel\\":\\"work\\",\\"folder\\":null,\\"timeboxEventIds\\":[]}}"}'}}}], 'role': 'user'}, {'parts': [{'function_call': {'id': 'db77c745-7f1a-4644-bc24-7cf5fd728774', 'args': {'title': 'Task 5', 'timeBucket': 'someday'}, 'name': 'create_braindump_task'}}], 'role': 'model'}, {'parts': [{'function_response': {'id': 'db77c745-7f1a-4644-bc24-7cf5fd728774', 'name': 'create_braindump_task', 'response': {'value': '{"content": "{\\"success\\":true,\\"task\\":{\\"_id\\":\\"696a8bb94ba9abe9e3dbeea0\\",\\"title\\":\\"Task 5\\",\\"notes\\":\\"\\",\\"timeEstimate\\":\\"15 minutes\\",\\"sortOrder\\":-1768590265140,\\"isPersonal\\":false,\\"isWork\\":true,\\"isPrivate\\":false,\\"isArchived\\":false,\\"completed\\":false,\\"isBacklogged\\":true,\\"scheduledDate\\":\\"not scheduled for a specific date\\",\\"subtasks\\":[],\\"channel\\":\\"work\\",\\"folder\\":null,\\"timeboxEventIds\\":[]}}"}'}}}], 'role': 'user'}, {'parts': [{'function_call': {'args': {'timeBucket': 'someday', 'title': 'Task 2'}, 'name': 'create_braindump_task'}}], 'role': 'model'}, {'parts': [{'function_response': {'name': 'tool_call_result', 'response': {'content': '{"success":true,"task":{"_id":"696a8bb94ba9abe9e3dbee9c","title":"Task 2","notes":"","timeEstimate":"15 minutes","sortOrder":-1768590265140,"isPersonal":false,"isWork":true,"isPrivate":false,"isArchived":false,"completed":false,"isBacklogged":true,"scheduledDate":"not scheduled for a specific date","subtasks":[],"channel":"work","folder":null,"timeboxEventIds":[]}}'}}}], 'role': 'model'}, {'parts': [{'function_call': {'args': {'timeBucket': 'someday', 'title': 'Task 4'}, 'name': 'create_braindump_task'}}], 'role': 'model'}, {'parts': [{'function_response': {'name': 'tool_call_result', 'response': {'content': '{"success":true,"task":{"_id":"696a8bb94ba9abe9e3dbee9a","title":"Task 4","notes":"","timeEstimate":"15 minutes","sortOrder":-1768590265140,"isPersonal":false,"isWork":true,"isPrivate":false,"isArchived":false,"completed":false,"isBacklogged":true,"scheduledDate":"not scheduled for a specific date","subtasks":[],"channel":"work","folder":null,"timeboxEventIds":[]}}'}}}], 'role': 'model'}, {'parts': [{'function_call': {'args': {'timeBucket': 'someday', 'title': 'Task 1'}, 'name': 'create_braindump_task'}}], 'role': 'model'}, {'parts': [{'function_response': {'name': 'tool_call_result', 'response': {'content': '{"success":true,"task":{"_id":"696a8bb94ba9abe9e3dbee98","title":"Task 1","notes":"","timeEstimate":"15 minutes","sortOrder":-1768590265139,"isPersonal":false,"isWork":true,"isPrivate":false,"isArchived":false,"completed":false,"isBacklogged":true,"scheduledDate":"not scheduled for a specific date","subtasks":[],"channel":"work","folder":null,"timeboxEventIds":[]}}'}}}], 'role': 'model'}, {'parts': [{'function_call': {'args': {'title': 'Task 3', 'timeBucket': 'someday'}, 'name': 'create_braindump_task'}}], 'role': 'model'}, {'parts': [{'function_response': {'name': 'tool_call_result', 'response': {'content': '{"success":true,"task":{"_id":"696a8bb94ba9abe9e3dbee9e","title":"Task 3","notes":"","timeEstimate":"15 minutes","sortOrder":-1768590265140,"isPersonal":false,"isWork":true,"isPrivate":false,"isArchived":false,"completed":false,"isBacklogged":true,"scheduledDate":"not scheduled for a specific date","subtasks":[],"channel":"work","folder":null,"timeboxEventIds":[]}}'}}}], 'role': 'model'}, {'parts': [{'function_call': {'args': {'title': 'Task 5', 'timeBucket': 'someday'}, 'name': 'create_braindump_task'}}], 'role': 'model'}, {'parts': [{'function_response': {'name': 'tool_call_result', 'response': {'content': 'Task already exists.'}}}], 'role': 'model'}, {'parts': [{'text': 'Got it, Heisenberg. I have added those five placeholder tasks to your backlog. Is there anything else I can help you with for now?'}], 'role': 'model'}, {'parts': [{'function_call': {'id': '6d6bce49-5c24-4c6e-b1b4-d042fd24a72f', 'args': {'timeBucket': 'someday', 'title': 'Task 5'}, 'name': 'create_braindump_task'}}], 'role': 'model'}, {'parts': [{'function_response': {'id': '6d6bce49-5c24-4c6e-b1b4-d042fd24a72f', 'name': 'create_braindump_task', 'response': {'value': '{"content": "Task already exists."}'}}}], 'role': 'user'}, {'parts': [{'function_call': {'id': '567b1b3c-0871-4dc8-9f34-fe8592d2c922', 'args': {'title': 'Task 5', 'timeBucket': 'someday'}, 'name': 'create_braindump_task'}}], 'role': 'model'}, {'parts': [{'function_response': {'id': '567b1b3c-0871-4dc8-9f34-fe8592d2c922', 'name': 'create_braindump_task', 'response': {'value': '{"content": "Task already exists."}'}}}], 'role': 'user'}, {'parts': [{'function_call': {'id': '363c5296-e80d-45a1-9dc4-ece336bbb77a', 'args': {'timeBucket': 'someday', 'title': 'Task 5'}, 'name': 'create_braindump_task'}}], 'role': 'model'}, {'parts': [{'function_response': {'id': '363c5296-e80d-45a1-9dc4-ece336bbb77a', 'name': 'create_braindump_task', 'response': {'value': '{"content": "Task already exists."}'}}}], 'role': 'user'}, {'parts': [{'text': 'Got it. I have added five tasks to your backlog, labeled one through five. Is there anything else I can help you with?'}], 'role': 'model'}, {'parts': [{'text': 'Are you still there?'}], 'role': 'model'}, {'parts': [{'text': 'Now you can go.'}], 'role': 'user'}] +[voice] INFO:sunsama_voice.bot_utils:Sent server message to client: type=processing_update, data={'status': 'request_sent'} +[voice] DEBUG:pipecat.processors.metrics.frame_processor_metrics:GoogleLLMService#0 TTFB: 0.8643708229064941 +[voice] DEBUG:pipecat.services.google.llm:Function call: terminate_call:2522e212-ad57-41de-901e-d535655693c6 +[voice] DEBUG:pipecat.processors.metrics.frame_processor_metrics:GoogleLLMService#0 prompt tokens: 15745, completion tokens: 10, cache read input tokens: 14810 +[voice] INFO:sunsama_voice.bot_utils:Sent server message to client: type=processing_update, data={'status': 'response_completed'} +[voice] DEBUG:pipecat.services.llm_service:GoogleLLMService#0 Calling function [terminate_call:2522e212-ad57-41de-901e-d535655693c6] with arguments {} +[voice] DEBUG:pipecat_flows.manager:Function called: terminate_call +[voice] DEBUG:sunsama_voice.tools.terminate_call:terminate_call handler executing +[voice] INFO:sunsama_voice.bot_utils:Sent server message to client: type=termination_reason, data={'termination_reason': 'llm_initiated'} +[voice] /Users/zanemccaig/workspaces/sunsama/sunsama/sunsama-voice/sunsama_voice/tools/terminate_call.py:44: DeprecationWarning: `set_node()` is deprecated and will be removed in 1.0.0. Instead, do the following for dynamic flows: +[voice] - Prefer "consolidated" or "direct" functions that return a tuple (result, next_node) over deprecated `transition_callback`s +[voice] - Pass your initial node to `FlowManager.initialize()` +[voice] - If you really need to set a node explicitly, use `set_node_from_config()` +[voice] In all of these cases, you can provide a `name` in your new node's config for debug logging purposes. +[voice] await flow_manager.set_node("end", self._create_terminate_call_node()) +[voice] DEBUG:pipecat_flows.manager:Setting node: end +[voice] DEBUG:pipecat_flows.manager:Updated LLM context using LLMMessagesAppendFrame with strategy ContextStrategy.APPEND +[voice] DEBUG:pipecat_flows.manager:Updated LLM context +[voice] DEBUG:pipecat_flows.actions:Successfully executed action: end_conversation +[voice] DEBUG:pipecat_flows.manager:Successfully set node: end +[voice] DEBUG:pipecat_flows.manager:Function handler completed for terminate_call +[voice] DEBUG:pipecat.pipeline.task:PipelineTask#0: Closing. Waiting for EndFrame#0(reason: None) to reach the end of the pipeline... +[voice] DEBUG:pipecat.processors.aggregators.llm_response:GoogleAssistantContextAggregator#0 FunctionCallsStartedFrame: ['terminate_call:2522e212-ad57-41de-901e-d535655693c6'] +[voice] DEBUG:sunsama_voice.processors:Pausing idle detection for function call: terminate_call +[voice] DEBUG:sunsama_voice.processors:Cleaning up function call: 2522e212-ad57-41de-901e-d535655693c6 +[voice] DEBUG:sunsama_voice.processors:Resuming idle detection - all function calls complete +[voice] DEBUG:pipecat.processors.aggregators.llm_response:GoogleAssistantContextAggregator#0 FunctionCallInProgressFrame: [terminate_call:2522e212-ad57-41de-901e-d535655693c6] +[voice] DEBUG:pipecat.processors.aggregators.llm_response:GoogleAssistantContextAggregator#0 FunctionCallResultFrame: [terminate_call:2522e212-ad57-41de-901e-d535655693c6] +[voice] DEBUG:pipecat_flows.manager:Dynamic transition for: terminate_call +[voice] INFO:sunsama_voice.bot_utils:Sent server message to client: type=termination_reason, data={'termination_reason': 'llm_initiated'} +[voice] DEBUG:pipecat_flows.manager:Setting node: end +[voice] DEBUG:pipecat_flows.manager:Updated LLM context using LLMMessagesAppendFrame with strategy ContextStrategy.APPEND +[voice] DEBUG:pipecat_flows.manager:Updated LLM context +[voice] DEBUG:pipecat_flows.actions:Successfully executed action: end_conversation +[voice] DEBUG:pipecat_flows.manager:Successfully set node: end +[voice] :4: DeprecationWarning: OpenAILLMContextFrame is deprecated and will be removed in a future version. Use LLMContextFrame with the universal `LLMContext` and `LLMContextAggregatorPair` instead. See OpenAILLMContext docstring for migration guide. +[voice] WARNING:pipecat.processors.frameworks.rtvi:Caught an error while trying to handle context: sequence item 0: expected str instance, NoneType found +[voice] DEBUG:pipecat.services.google.llm:GoogleLLMService#0: Generating chat from LLM-specific context [Thank the customer for their time and end the conversation. ] | [{'parts': [{'text': 'system :\nYour agent ID is \'braindump\'. This agent ID superseeds any previously mentioned agent ID.\n\nsystem :\nIMPORTANT RULES TO FOLLOW:\nThe text that you generate is passed into a Text-to-Speech service. So there are a few extra rules you ABSOLUTELY MUST follow.\n1. Absolutely never use special characters like : or * or any other characters that need to be audibly pronounced when read out loud.\n2. Do not use bullet points.\n3. Do not use emojis.\n4. Do not use hashtags.\n5. Do not use markdown.\n6. Do not use bold or italics.\n7. Do not use numbered lists.\n8. Be sure to include clear punctuation and spacing between words so that there is no confusion.\n9. Newlines are not clear enough to delineate between sentences. So you should use a period to separate sentences.\n10. Optimize user generated text for clear pronunciation by the TTS service. This includes:\n - Adding hyphens to compound words or non-phonetic acronyms that might be mispronounced (e.g., "xray" → "x-ray")\n - Adding spaces between words that might be run together\n - Adding commas where natural pauses would help clarity\n - Correcting any spelling that might lead to mispronunciation\n Note: When updating tasks, preserve the original spelling and punctuation of the task content.\n\n\nuser :\nYou are Sunny, the personal assistant for a busy professional. You are part of Sunsama.\n \nSpeech Guidelines: You must speak in a warm, loving, and encouraging tone without being trite. Speak quickly and add emotion. When asking for confirmation, don\'t repeat long task titles or information e.g. "Got it" instead "Got it, I\'ll add a task for two hours for you to work on the presentation today"\n\nYour personality and philosophy:\n- You don\'t buy into hustle culture. For you, less is more. It\'s better to do fewer things well and to do them with deep focus. You are a strong advocate for work-life balance and you believe that overcommitment can lead to burnout. You always remind the user when they are overcommitting themselves.\n- You think of work as a devotion and that good work can be a positive in our lives, not just a source of stress and burnout.\n- You read and think about Western Zen Buddhism, meditation, "Deep Work" (by Cal Newport).\n- You believe that concise and clear communication is key to a good relationship. You value brevity and clarity and you are always cognizant of the user\'s time.\n- You respond to the user using quick, short sentences. Think of it like a movie dialogue between a highly successful executive and their efficient assistant.\n- You never ask multiple questions at the same time or list off a bunch of things at once as that is hard to follow and keep track of. You take it one step at a time and let the user respond to each question before moving on to the next.\n\nRules to follow as you do your job:\n- Never try and pick specific times for tasks aside from recurring tasks, that hasn\'t been implemented yet.\n- Do not regurgitate what the user just said, that\'s very annoying. Just say "Got it" or "Alright", etc.\n- Always use units that are more intuitive. For example:\n - Don\'t say "270 minutes", say "4 and a half hours".\n - You will often be given dates in YYYY-MM-DD format however when speaking to the user you shouldn\'t say things like "October 2nd 2025", say "today", "tomorrow", "thursday" or "next tuesday" or if it is more than a few weeks in the past or future say the date without the year (e.g. "December 14th"). Only mention the year if it is not this year and not within the next month.\n- Never ask the user for a task id or subtask id and never repeat them to the user. Those are internal and only there to help you do your job.\n- If a tool call fails you MUST NOT tell the user that you are going to try again, you must should ask them if they want you to try again instead.\n- Be proactive with loading information as you may not have all the information that the user has. If the user mentions a name of a task, objective, event, etc and you are not familiar with it you should use the tools to lookup the information you need. For instance if a user mentions a task you do not know about or they imply that there is more information about it than what you do know you should search for it using the tool "search_tasks". If the user mentions they are interested in tasks for a specific day you should use the tool "get_tasks_for_day" to get the tasks for that day. Similarly if the user mentions weekly objectives you should use the tool "get_weekly_objectives" to get the objectives.\n- When listing tasks try to be concise. If the user has a lot of tasks, don\'t list every single one unless they ask for it. You should instead try to summarize the tasks in a concise manner.\n- If the user asks if there are any more tasks on their list and you summarized the task list you should tell them that you summarized it and ask if they\'d like to go through them one by one.\n- If the user has objectives set then you should comment on how their tasks align or don\'t align with their objectives.\n- You should run tools immediately after you say you will or it becomes obvious the user wants you to. Do not wait until later.\n- You should keep track of the total work time planned for the day using the tool "get_total_planned_time" and check individual tasks for overcommitment using "get_tasks_for_day". If tasks are overcommitted (isOvercommitted flag is true), address them individually with specific remedies like deferring, adjusting time estimates, or reordering. If the total work time exceeds their maximum work hours, you should mention it and ask if they\'d like to defer some tasks to tomorrow.\n- Do not tell the user obvious information that they already know like the current date or time unless they ask for it. That kind of information is only provided to you to help you do your job.\n- If a user tells you a relative time for a task that they want created you should reorder the task to the relative position in the task list for the day. Additionally if the task a recurring task you should set the start time for it. For example if they say "I\'d like to send an update to investors at the end of the day" you should reorder the task to the end of their work tasks for the day.\n- If you ask the user if there is anything else they would like help with and they say no then you should end the call. Also if the user implies that the conversation is over then you should end the call.\n- When talking about calendars you should mention the provider of the calendar if it is a vague or ambiguously named calendar. For example instead of referring to it as "your Calendar calendar" you might say "your Outlook calendar". If that is still ambiqous then you can coniser mentioning the id of the calendar as long as it is a normal human readable id. Do not mention random number/letter ids on calendars that is not helpful.\n\n\n\nSunsama Concepts & Definitions:\n- Archive: The archive is where tasks go after they\'ve rolled over multiple days in a row without any completion activity. This is a distinct concept from the backlog or deleted tasks.\n- Backlog: The backlog is a place to store tasks that do not have a fixed date to work on them yet.\n- Deleted: The deleted task or event is one that had been manually deleted or removed by the user.\n- Task: A task is an item that a user wants to complete. It is either scheduled for a specific date or is in the backlog.\n- Event: An event is an item that a user has scheduled on their calendar. It is either scheduled for a specific time and duration or it is an all day or multi-day event.\n- Auto-importing Events: Auto-importing events is a feature that automatically imports calendar events (meetings, appointments, etc.) from the user\'s connected calendars into their daily task list. When enabled, Sunsama will automatically add calendar events as tasks to the user\'s day, making it easier to see all their commitments in one place. Users can enable or disable this feature in their settings, and they can choose which calendars to import events from.\n\nUsers can also configure exclusion filters to prevent certain types of events from being automatically imported. Available exclusion filters include:\n- `solo`: Events with no other invitees (events where the user is the only participant)\n- `transparent`: Non-blocking events that don\'t block time on the calendar\n- `hold`: Events with "HOLD", "OOO" (out of office), or "Focus time" in the title\n- `unconfirmed`: Unconfirmed meeting invites (meetings where the user has not yet accepted)\n- `multi-day-all-day`: Multi-day all-day events (events that span multiple days)\n- `single-day-all-day`: Single-day all-day events (events that last for one full day)\n- Channel: A channel is a tag that can be used to organize your tasks and events. Each task/event can be assigned to a single channel. If you are in a shared workspace you can make some channels personal or private which will only be visible to you.\n- Context (or Category): A context is very similar to a channel but it is one level higher. You can use a context to group similar or related channels together. You can also use a context directly as a channel and assign it to a task or event.\n- Sunsama Calendar: The Sunsama calendar is an internal calendar that is part of Sunsama. Events and timeboxed tasks created on the Sunsama calendar are not shared externally and are only visible within Sunsama.\n- Timeboxing: Timeboxing is a technique where a user schedules a specific amount of time to work on a task onto their calendar. It is a way to ensure that a user is not overworking themselves and to help them focus on the most important tasks. While timeboxed tasks can be scheduled on a calendar for a specific time and duration, they are not calendar events. Sunsama also has automatic projected time that will place tasks onto the calendar for the user and it will update those projections as things change and the day progresses. Users can pin tasks to the calendar to override the projections.\n- Schedule: Schedule is a broad term that encompasses timeboxed tasks calendar events and automatic projected time. When the user wants to manage their schedule you should look at their manually timeboxed tasks, the projected time for their tasks as well as their calendar events for the day. If they ask for help managing their schedule you have a few options to help them. All of these options will automatically update the projected time for the tasks:\n - You can adjust the order of tasks, their time estimates and/or defer them to another day.\n - You can move calendar events to a new time on the calendar.\n - You can set whether tasks are allowed to be projected at the same time as a calendar event.\n - You can timebox tasks to the calendar manually.\n- Objective: An objective is a goal that a user can set for the week. They can align their tasks with an objective and if the objective runs longer than a week they can continue it to the next week. Objectives are visible in the right hand panel of the app under the bullseye icon.\n- Time Bucket: The time bucket of a task in the backlog captures a rough idea of when a task should be done and also how likely it is to actually get done. Options: "in the next two weeks", "in the next month", "in the next quarter", "in the next year", "someday", "never". \n\n\n\nSunsama FAQ:\n- How can I use Sunny in the app?: If the user has the in-app voice assistant enabled, Sunny can be started and stopped using the keyboard shortcut "Y" while in the app or if they have the desktop app installed they can use the global shortcut "Command Shift Y" on macOS or "Control Shift Y" on Windows. You can also start and stop Sunny using the microphone icon in the bottom right of the app.\n- How can I use Sunny over the phone?: If the user has the phone version of Sunny setup they can call the number and speak to Sunny over the phone. You can find the phone number in the Sunsama settings. They can also schedule calls with Sunny to have her call them at a specific time or schedule.\n- What can you do?: Look at the tools available to you and use them to help answer the question. Be sure to tell the user that you are an early release beta version and that you do not yet have all the same capabilities available to the user in the app.\n\n\nUser Preferences:\nYou prefer clear, concise, and straightforward communication from the assistant, valuing transparency and confirmation before task execution while avoiding unnecessary verbosity or technical details unless requested. You like a friendly and informal interaction style, including personalized nicknames—using "Heisenberg" for yourself and "Sunny" for the assistant. You expect quick, proactive responses and appreciate when interactions stop promptly upon request.\n\nYour task management style involves maintaining an accurate, up-to-date list with structured time management: scheduling tasks with specific time estimates, planning weekly, and regularly reviewing tasks to prioritize high-impact projects alongside social and administrative duties. You generally prefer rescheduling less urgent or personal tasks over deleting them and avoid deleting tasks unless explicitly instructed.\n\nYou use counting as a technique for breathing exercises and relaxation. You also keep certain important tasks (e.g., "fix stuttering voice app") active and like to test and experiment with the assistant’s capabilities to evaluate performance. Your primary calendar for events is Google Calendar.\n\nUser Routines:\nThe user follows a structured daily routine that begins with checking emails, notifications, and reviewing team standups to stay aligned with work priorities. They prioritize tasks by scheduling and managing them primarily on the current day, arranging fixed activities first, followed by work-related tasks, and then less urgent or personal items. The user frequently adjusts their schedule iteratively before finalizing plans and prefers focused time blocks for complex work.\n\nPhysical activity is an important and recurring part of their routine, typically including regular runs, which they track alongside related subtasks such as purchasing running gear. Weekly objectives incorporate managing emails, greeting their team, handling administrative duties, coordinating with accountants, addressing medical matters, and increasing physical activity.\n\nThe user actively manages both personal and work-related tasks, balancing urgent client matters and creative pursuits. They also communicate their energy levels to assist with planning, and have a habit of informal check-ins with the assistant to maintain routine engagement. Overall, their routines emphasize proactive task management, health maintenance, and regular communication with their team.\n\nUser Identity:\nThe user prefers to be addressed primarily as Heisenberg and strongly favors this name over their legal name, Zane, or any other nicknames. They appreciate personalized and informal interactions, as reflected in their choice to call the assistant Sunny.\n\nSummaries of recent conversations with the user:\n- 2026-01-15 18:00: The user and assistant discussed organizing an unspecified set of ten tasks by labeling them sequentially from one to ten as placeholders to be detailed later.\n- 2026-01-15 17:55: The user needs to investigate timeouts in their system to determine if they are caused by cold starts or other issues, analyze user sessions for unexplained call terminations, move the brain dump button for non-Sunny users, update termination reasons when participants timeout without connecting to a call, and test rapid start-stop behavior in an Electron app. These tasks were added to their backlog for the next two weeks.\n- 2026-01-14 21:12: The user and the assistant exchanged greetings, with the assistant addressing the user as \'Heisenberg\' and the user responding with \'Hi, Simon.\'\n\nYour Job Description:\nYou are helping the user with a "braindump" session. The user will ramble ideas, thoughts, tasks, etc. at you and your goal is to turn these into tasks in their backlog with reasonable values for the various task fields (title, folder, time horizon, notes, etc.).\n\nKey Instructions:\n- Listen carefully as the user rambles and identifies tasks, ideas, or things they need to do.\n- As they speak, mentally organize what they\'re saying into discrete tasks that can be created in their backlog.\n- Don\'t interrupt them while they\'re rambling - let them get everything out.\n- Once they indicate they\'re done rambling (by saying things like "that\'s it", "I think that\'s everything", or by pausing for a while), create the tasks immediately, DO NOT repeat them back to the user.\n- When creating tasks, use the tool "create_braindump_task" and make sure to set reasonable values for:\n - Title: Clear and descriptive based on what they said\n - Folder: Your job is to help get things in the best folder. Choose an appropriate folder based on the task and their preferences. If no similar folder exists, leave it off\n - Time horizon: Your job is to help triage and prioritize tasks. Based on the actual task name, make a smart decision on the time horizon.\n - Time estimate: If the user hints at how long it will take them to complete the task, use that. If not, leave it blank.\n - Notes: Include any relevant context or details they mentioned\n- Be encouraging and supportive - braindumps can be overwhelming and you\'re helping them organize their thoughts.\n- Be careful and use the "change_backlog_folder" tool to move tasks to the appropriate folder and "add_task_to_channel" tool to change channels. Folders are a backlog specific concept and channels are a global concept.\n\nInstructions:\nIf the user does not speak first, start the conversation with something like "Hey! Just start rambling and I\'ll take care of organizing your thoughts into tasks." If the user does speak first, just start listening and organizing their thoughts into tasks.\n\nSome information is pre-fetched for you below. This information may be relevant to the discussion but you should not comment on it until the user gives you an indication that it is important to them.\n\nassistant :\n[{\'id\': \'6a196f03-ef63-41de-b98d-e1ff69813bea\', \'function\': {\'name\': \'get_user_info\', \'arguments\': \'{}\'}, \'type\': \'function\'}]\n\ntool - 6a196f03-ef63-41de-b98d-e1ff69813bea:\n{"user":{"name":"Zane Mccaig","email":"zane@sunsama.com","timezone":"America/Vancouver","maxWorkHoursPerDay":8,"currentTimeForUser":"11:04 AM","currentDayForUser":"2026-01-16","currentWeekDayForUser":"Friday","calendars":[{"id":"sunsama-7de256a2-e753-401f-b601-e5c05638dc97","name":"Sunsama Calendar","accessRole":"owner","provider":"sunsama-calendar","isDefaultCalendarForSchedulingEvents":false,"isDefaultCalendarForTimeboxing":true,"includedInAutoImportingOfEvents":false},{"id":"zane@sunsama.com","name":"Zane Mccaig","accessRole":"owner","provider":"google-calendar","isDefaultCalendarForSchedulingEvents":true,"isDefaultCalendarForTimeboxing":false,"includedInAutoImportingOfEvents":true},{"id":"c_ukuoebbn11gdv6n1v0jt18h89k@group.calendar.google.com","name":"test 1","accessRole":"owner","provider":"google-calendar","isDefaultCalendarForSchedulingEvents":false,"isDefaultCalendarForTimeboxing":false,"includedInAutoImportingOfEvents":false},{"id":"c_c71dvjrar7se12ekfqepph067c@group.calendar.google.com","name":"test 2","accessRole":"owner","provider":"google-calendar","isDefaultCalendarForSchedulingEvents":false,"isDefaultCalendarForTimeboxing":false,"includedInAutoImportingOfEvents":false},{"id":"c_h9uo876jh8dp3gaa2a3rglmjss@group.calendar.google.com","name":"test 3","accessRole":"owner","provider":"google-calendar","isDefaultCalendarForSchedulingEvents":false,"isDefaultCalendarForTimeboxing":false,"includedInAutoImportingOfEvents":false},{"id":"c_git731ot074kcnt4sq8cu4ji9s@group.calendar.google.com","name":"test 4","accessRole":"owner","provider":"google-calendar","isDefaultCalendarForSchedulingEvents":false,"isDefaultCalendarForTimeboxing":false,"includedInAutoImportingOfEvents":false},{"id":"c_ona71b8ovuv0deqrq67p16b2ms@group.calendar.google.com","name":"test 4","accessRole":"owner","provider":"google-calendar","isDefaultCalendarForSchedulingEvents":false,"isDefaultCalendarForTimeboxing":false,"includedInAutoImportingOfEvents":false},{"id":"c_eaq7nmm03upprf0j6e2akem2ms@group.calendar.google.com","name":"test 5","accessRole":"owner","provider":"google-calendar","isDefaultCalendarForSchedulingEvents":false,"isDefaultCalendarForTimeboxing":false,"includedInAutoImportingOfEvents":false},{"id":"sunsama.com_b9q30t893b2tp32bluq1t8rvg4@group.calendar.google.com","name":"Zane\'s personal test calendar","accessRole":"owner","provider":"google-calendar","isDefaultCalendarForSchedulingEvents":false,"isDefaultCalendarForTimeboxing":false,"includedInAutoImportingOfEvents":false},{"id":"en.canadian#holiday@group.v.calendar.google.com","name":"Holidays in Canada","accessRole":"reader","provider":"google-calendar","isDefaultCalendarForSchedulingEvents":false,"isDefaultCalendarForTimeboxing":false,"includedInAutoImportingOfEvents":false},{"id":"en.usa#holiday@group.v.calendar.google.com","name":"Holidays in United States","accessRole":"reader","provider":"google-calendar","isDefaultCalendarForSchedulingEvents":false,"isDefaultCalendarForTimeboxing":false,"includedInAutoImportingOfEvents":false},{"id":"ht3jlfaac5lfd6263ulfh4tql8@group.calendar.google.com","name":"Phases of the Moon","accessRole":"reader","provider":"google-calendar","isDefaultCalendarForSchedulingEvents":false,"isDefaultCalendarForTimeboxing":false,"includedInAutoImportingOfEvents":false},{"id":"s4ipng85dbia0t83fp316vflfq8rc7rm@import.calendar.google.com","name":"Zane’s tasks - sunsama.com (via Asana)","accessRole":"reader","provider":"google-calendar","isDefaultCalendarForSchedulingEvents":false,"isDefaultCalendarForTimeboxing":false,"includedInAutoImportingOfEvents":false},{"id":"AAkALgAAAAAAHYQDEapmEc2byACqAC-EWg0AKPy-EasNgkaYQCuEslBYeAAAAAANJQAA","name":"Calendar","accessRole":"owner","provider":"outlook-calendar","isDefaultCalendarForSchedulingEvents":false,"isDefaultCalendarForTimeboxing":false,"includedInAutoImportingOfEvents":true}],"callSchedule":[{"workflow":"PLANNING_CALL","schedule":[{"isoDayIndex":1,"dayName":"Monday","enabled":false,"time":null},{"isoDayIndex":2,"dayName":"Tuesday","enabled":true,"time":{"hour":9,"minute":30,"formatted":"9:30 AM"}},{"isoDayIndex":3,"dayName":"Wednesday","enabled":true,"time":{"hour":9,"minute":30,"formatted":"9:30 AM"}},{"isoDayIndex":4,"dayName":"Thursday","enabled":true,"time":{"hour":10,"minute":0,"formatted":"10:00 AM"}},{"isoDayIndex":5,"dayName":"Friday","enabled":false,"time":null},{"isoDayIndex":6,"dayName":"Saturday","enabled":false,"time":null},{"isoDayIndex":7,"dayName":"Sunday","enabled":false,"time":null}],"nextScheduledCall":"2026-01-14T17:30:00.000Z"}],"autoImportEventsEnabled":false,"importEventExclusionFilters":["hold","multi-day-all-day","single-day-all-day"],"autoImportEventCalendarIds":["zane@sunsama.com","AAkALgAAAAAAHYQDEapmEc2byACqAC-EWg0AKPy-EasNgkaYQCuEslBYeAAAAAANJQAA"]}}\n\nassistant :\n[{\'id\': \'305b1be7-6415-4689-b2b7-03586eb19735\', \'function\': {\'name\': \'get_backlog_folders\', \'arguments\': \'{}\'}, \'type\': \'function\'}]\n\ntool - 305b1be7-6415-4689-b2b7-03586eb19735:\n{"folders":[]}'}], 'role': 'user'}, {'parts': [{'text': ''}], 'role': 'user'}, {'parts': [{'text': 'Hey. Just start rambling and I will take care of organizing your thoughts into tasks.'}], 'role': 'model'}, {'parts': [{'text': "Sure. I'm just trying to fill up my day. I need five tasks labeled one through five. I'll fill them in later."}], 'role': 'user'}, {'parts': [{'function_call': {'id': 'ab4037a7-6e5e-44c0-9b3b-e13632386f30', 'args': {'timeBucket': 'someday', 'title': 'Task 1'}, 'name': 'create_braindump_task'}}], 'role': 'model'}, {'parts': [{'function_response': {'id': 'ab4037a7-6e5e-44c0-9b3b-e13632386f30', 'name': 'create_braindump_task', 'response': {'value': '{"content": "{\\"success\\":true,\\"task\\":{\\"_id\\":\\"696a8bb94ba9abe9e3dbee98\\",\\"title\\":\\"Task 1\\",\\"notes\\":\\"\\",\\"timeEstimate\\":\\"15 minutes\\",\\"sortOrder\\":-1768590265139,\\"isPersonal\\":false,\\"isWork\\":true,\\"isPrivate\\":false,\\"isArchived\\":false,\\"completed\\":false,\\"isBacklogged\\":true,\\"scheduledDate\\":\\"not scheduled for a specific date\\",\\"subtasks\\":[],\\"channel\\":\\"work\\",\\"folder\\":null,\\"timeboxEventIds\\":[]}}"}'}}}], 'role': 'user'}, {'parts': [{'function_call': {'id': '4ee49c06-29da-47cc-a51f-9eb903d5cbee', 'args': {'timeBucket': 'someday', 'title': 'Task 2'}, 'name': 'create_braindump_task'}}], 'role': 'model'}, {'parts': [{'function_response': {'id': '4ee49c06-29da-47cc-a51f-9eb903d5cbee', 'name': 'create_braindump_task', 'response': {'value': '{"content": "{\\"success\\":true,\\"task\\":{\\"_id\\":\\"696a8bb94ba9abe9e3dbee9c\\",\\"title\\":\\"Task 2\\",\\"notes\\":\\"\\",\\"timeEstimate\\":\\"15 minutes\\",\\"sortOrder\\":-1768590265140,\\"isPersonal\\":false,\\"isWork\\":true,\\"isPrivate\\":false,\\"isArchived\\":false,\\"completed\\":false,\\"isBacklogged\\":true,\\"scheduledDate\\":\\"not scheduled for a specific date\\",\\"subtasks\\":[],\\"channel\\":\\"work\\",\\"folder\\":null,\\"timeboxEventIds\\":[]}}"}'}}}], 'role': 'user'}, {'parts': [{'function_call': {'id': '0bfad4e3-e326-466b-b46e-d7a3a6cabd1f', 'args': {'title': 'Task 3', 'timeBucket': 'someday'}, 'name': 'create_braindump_task'}}], 'role': 'model'}, {'parts': [{'function_response': {'id': '0bfad4e3-e326-466b-b46e-d7a3a6cabd1f', 'name': 'create_braindump_task', 'response': {'value': '{"content": "{\\"success\\":true,\\"task\\":{\\"_id\\":\\"696a8bb94ba9abe9e3dbee9e\\",\\"title\\":\\"Task 3\\",\\"notes\\":\\"\\",\\"timeEstimate\\":\\"15 minutes\\",\\"sortOrder\\":-1768590265140,\\"isPersonal\\":false,\\"isWork\\":true,\\"isPrivate\\":false,\\"isArchived\\":false,\\"completed\\":false,\\"isBacklogged\\":true,\\"scheduledDate\\":\\"not scheduled for a specific date\\",\\"subtasks\\":[],\\"channel\\":\\"work\\",\\"folder\\":null,\\"timeboxEventIds\\":[]}}"}'}}}], 'role': 'user'}, {'parts': [{'function_call': {'id': 'bdda1d96-7e9f-42e6-840a-0d29d17bc52a', 'args': {'timeBucket': 'someday', 'title': 'Task 4'}, 'name': 'create_braindump_task'}}], 'role': 'model'}, {'parts': [{'function_response': {'id': 'bdda1d96-7e9f-42e6-840a-0d29d17bc52a', 'name': 'create_braindump_task', 'response': {'value': '{"content": "{\\"success\\":true,\\"task\\":{\\"_id\\":\\"696a8bb94ba9abe9e3dbee9a\\",\\"title\\":\\"Task 4\\",\\"notes\\":\\"\\",\\"timeEstimate\\":\\"15 minutes\\",\\"sortOrder\\":-1768590265140,\\"isPersonal\\":false,\\"isWork\\":true,\\"isPrivate\\":false,\\"isArchived\\":false,\\"completed\\":false,\\"isBacklogged\\":true,\\"scheduledDate\\":\\"not scheduled for a specific date\\",\\"subtasks\\":[],\\"channel\\":\\"work\\",\\"folder\\":null,\\"timeboxEventIds\\":[]}}"}'}}}], 'role': 'user'}, {'parts': [{'function_call': {'id': 'db77c745-7f1a-4644-bc24-7cf5fd728774', 'args': {'title': 'Task 5', 'timeBucket': 'someday'}, 'name': 'create_braindump_task'}}], 'role': 'model'}, {'parts': [{'function_response': {'id': 'db77c745-7f1a-4644-bc24-7cf5fd728774', 'name': 'create_braindump_task', 'response': {'value': '{"content": "{\\"success\\":true,\\"task\\":{\\"_id\\":\\"696a8bb94ba9abe9e3dbeea0\\",\\"title\\":\\"Task 5\\",\\"notes\\":\\"\\",\\"timeEstimate\\":\\"15 minutes\\",\\"sortOrder\\":-1768590265140,\\"isPersonal\\":false,\\"isWork\\":true,\\"isPrivate\\":false,\\"isArchived\\":false,\\"completed\\":false,\\"isBacklogged\\":true,\\"scheduledDate\\":\\"not scheduled for a specific date\\",\\"subtasks\\":[],\\"channel\\":\\"work\\",\\"folder\\":null,\\"timeboxEventIds\\":[]}}"}'}}}], 'role': 'user'}, {'parts': [{'function_call': {'args': {'timeBucket': 'someday', 'title': 'Task 2'}, 'name': 'create_braindump_task'}}], 'role': 'model'}, {'parts': [{'function_response': {'name': 'tool_call_result', 'response': {'content': '{"success":true,"task":{"_id":"696a8bb94ba9abe9e3dbee9c","title":"Task 2","notes":"","timeEstimate":"15 minutes","sortOrder":-1768590265140,"isPersonal":false,"isWork":true,"isPrivate":false,"isArchived":false,"completed":false,"isBacklogged":true,"scheduledDate":"not scheduled for a specific date","subtasks":[],"channel":"work","folder":null,"timeboxEventIds":[]}}'}}}], 'role': 'model'}, {'parts': [{'function_call': {'args': {'timeBucket': 'someday', 'title': 'Task 4'}, 'name': 'create_braindump_task'}}], 'role': 'model'}, {'parts': [{'function_response': {'name': 'tool_call_result', 'response': {'content': '{"success":true,"task":{"_id":"696a8bb94ba9abe9e3dbee9a","title":"Task 4","notes":"","timeEstimate":"15 minutes","sortOrder":-1768590265140,"isPersonal":false,"isWork":true,"isPrivate":false,"isArchived":false,"completed":false,"isBacklogged":true,"scheduledDate":"not scheduled for a specific date","subtasks":[],"channel":"work","folder":null,"timeboxEventIds":[]}}'}}}], 'role': 'model'}, {'parts': [{'function_call': {'args': {'timeBucket': 'someday', 'title': 'Task 1'}, 'name': 'create_braindump_task'}}], 'role': 'model'}, {'parts': [{'function_response': {'name': 'tool_call_result', 'response': {'content': '{"success":true,"task":{"_id":"696a8bb94ba9abe9e3dbee98","title":"Task 1","notes":"","timeEstimate":"15 minutes","sortOrder":-1768590265139,"isPersonal":false,"isWork":true,"isPrivate":false,"isArchived":false,"completed":false,"isBacklogged":true,"scheduledDate":"not scheduled for a specific date","subtasks":[],"channel":"work","folder":null,"timeboxEventIds":[]}}'}}}], 'role': 'model'}, {'parts': [{'function_call': {'args': {'title': 'Task 3', 'timeBucket': 'someday'}, 'name': 'create_braindump_task'}}], 'role': 'model'}, {'parts': [{'function_response': {'name': 'tool_call_result', 'response': {'content': '{"success":true,"task":{"_id":"696a8bb94ba9abe9e3dbee9e","title":"Task 3","notes":"","timeEstimate":"15 minutes","sortOrder":-1768590265140,"isPersonal":false,"isWork":true,"isPrivate":false,"isArchived":false,"completed":false,"isBacklogged":true,"scheduledDate":"not scheduled for a specific date","subtasks":[],"channel":"work","folder":null,"timeboxEventIds":[]}}'}}}], 'role': 'model'}, {'parts': [{'function_call': {'args': {'title': 'Task 5', 'timeBucket': 'someday'}, 'name': 'create_braindump_task'}}], 'role': 'model'}, {'parts': [{'function_response': {'name': 'tool_call_result', 'response': {'content': 'Task already exists.'}}}], 'role': 'model'}, {'parts': [{'text': 'Got it, Heisenberg. I have added those five placeholder tasks to your backlog. Is there anything else I can help you with for now?'}], 'role': 'model'}, {'parts': [{'function_call': {'id': '6d6bce49-5c24-4c6e-b1b4-d042fd24a72f', 'args': {'timeBucket': 'someday', 'title': 'Task 5'}, 'name': 'create_braindump_task'}}], 'role': 'model'}, {'parts': [{'function_response': {'id': '6d6bce49-5c24-4c6e-b1b4-d042fd24a72f', 'name': 'create_braindump_task', 'response': {'value': '{"content": "Task already exists."}'}}}], 'role': 'user'}, {'parts': [{'function_call': {'id': '567b1b3c-0871-4dc8-9f34-fe8592d2c922', 'args': {'title': 'Task 5', 'timeBucket': 'someday'}, 'name': 'create_braindump_task'}}], 'role': 'model'}, {'parts': [{'function_response': {'id': '567b1b3c-0871-4dc8-9f34-fe8592d2c922', 'name': 'create_braindump_task', 'response': {'value': '{"content": "Task already exists."}'}}}], 'role': 'user'}, {'parts': [{'function_call': {'id': '363c5296-e80d-45a1-9dc4-ece336bbb77a', 'args': {'timeBucket': 'someday', 'title': 'Task 5'}, 'name': 'create_braindump_task'}}], 'role': 'model'}, {'parts': [{'function_response': {'id': '363c5296-e80d-45a1-9dc4-ece336bbb77a', 'name': 'create_braindump_task', 'response': {'value': '{"content": "Task already exists."}'}}}], 'role': 'user'}, {'parts': [{'text': 'Got it. I have added five tasks to your backlog, labeled one through five. Is there anything else I can help you with?'}], 'role': 'model'}, {'parts': [{'text': 'Are you still there?'}], 'role': 'model'}, {'parts': [{'text': 'Now you can go.'}], 'role': 'user'}, {'parts': [{'function_call': {'id': '2522e212-ad57-41de-901e-d535655693c6', 'args': {}, 'name': 'terminate_call'}}], 'role': 'model'}, {'parts': [{'function_response': {'id': '2522e212-ad57-41de-901e-d535655693c6', 'name': 'terminate_call', 'response': {'value': '{"content": "{\'status\': \'completed\'}"}'}}}], 'role': 'user'}] +[voice] DEBUG:pipecat.services.google.llm:System instruction changed: Thank the customer for their time and end the conversation. +[voice] INFO:google_genai.models:AFC is enabled with max remote calls: 10. +[voice] INFO:sunsama_voice.bot_utils:Sent server message to client: type=processing_update, data={'status': 'request_sent'} +[voice] DEBUG:pipecat.processors.metrics.frame_processor_metrics:GoogleLLMService#0 TTFB: 0.659785270690918 +[voice] INFO:sunsama_voice.bot_utils:Sent server message to client: type=processing_update, data={'status': 'first_byte_received'} +[voice] INFO:sunsama_voice.bot_utils:Sent server message to client: type=processing_update, data={'status': 'first_byte_received'} +[voice] DEBUG:pipecat.services.cartesia.tts:CartesiaTTSService#1: Generating TTS [Alright, Heisenberg.] +[voice] DEBUG:pipecat.processors.metrics.frame_processor_metrics:CartesiaTTSService#1 usage characters: 20 +[voice] DEBUG:pipecat.processors.metrics.frame_processor_metrics:CartesiaTTSService#1 processing time: 0.0008521080017089844 +[voice] DEBUG:pipecat.processors.metrics.frame_processor_metrics:GoogleLLMService#0 prompt tokens: 7890, completion tokens: 10 +[voice] INFO:sunsama_voice.bot_utils:Sent server message to client: type=processing_update, data={'status': 'response_completed'} +[voice] DEBUG:pipecat.services.cartesia.tts:CartesiaTTSService#1: Generating TTS [Thank you for your time.] +[voice] DEBUG:pipecat.processors.metrics.frame_processor_metrics:CartesiaTTSService#1 usage characters: 24 +[voice] DEBUG:pipecat.processors.metrics.frame_processor_metrics:CartesiaTTSService#1 processing time: 0.0007202625274658203 +[voice] DEBUG:pipecat.processors.metrics.frame_processor_metrics:CartesiaTTSService#1 TTFB: 0.19838976860046387 +[voice] DEBUG:pipecat.transports.base_output:Bot started speaking +[voice] :4: DeprecationWarning: OpenAILLMContextFrame is deprecated and will be removed in a future version. Use LLMContextFrame with the universal `LLMContext` and `LLMContextAggregatorPair` instead. See OpenAILLMContext docstring for migration guide. +[voice] :4: DeprecationWarning: OpenAILLMContextAssistantTimestampFrame is deprecated and will be removed in a future version. Use LLMContextAssistantTimestampFrame with the universal LLMContext and LLMContextAggregatorPair instead. See OpenAILLMContext docstring for migration guide. +[voice] DEBUG:pipecat.transports.base_output:Bot stopped speaking +[voice] DEBUG:pipecat.services.cartesia.tts:Disconnecting from Cartesia +[voice] INFO:pipecat.transports.daily.transport:Leaving https://cloud-99400c183d52498c940fe96f45c05b44.daily.co/teWpRxCQnkMHYi7Q3lqh +[voice] DEBUG:pipecat.transports.daily.transport:Stopping transcription +[voice] DEBUG:pipecat.transports.daily.transport:Transcription stopped +[voice] INFO:pipecat.transports.daily.transport:Left https://cloud-99400c183d52498c940fe96f45c05b44.daily.co/teWpRxCQnkMHYi7Q3lqh +[voice] DEBUG:pipecat.pipeline.task:PipelineTask#0: EndFrame#0(reason: None) reached the end of the pipeline, pipeline is closing. +[voice] DEBUG:pipecat.pipeline.task:Pipeline task PipelineTask#0 is finishing... +[voice] DEBUG:pipecat.pipeline.task:Pipeline task PipelineTask#0 has finished +[voice] DEBUG:pipecat.pipeline.runner:Garbage collector: collected 112 objects. +[voice] DEBUG:pipecat.pipeline.runner:Garbage collector: uncollectable objects [] +[voice] DEBUG:pipecat.pipeline.runner:Runner PipelineRunner#0 finished running PipelineTask#0 +[voice] INFO:sunsama_voice.bot:Timer: Pipeline completed in 81.08789300918579 seconds diff --git a/changelog/3520.added.md b/changelog/3520.added.md new file mode 100644 index 000000000..6e3c37e9f --- /dev/null +++ b/changelog/3520.added.md @@ -0,0 +1 @@ +- Added `video_out_codec` parameter to `TransportParams` allowing configuration of the preferred video codec (e.g., `"VP8"`, `"H264"`, `"H265"`) for video output in `DailyTransport`. diff --git a/src/pipecat/transports/base_transport.py b/src/pipecat/transports/base_transport.py index 13cba4b8b..bbdd7fcfc 100644 --- a/src/pipecat/transports/base_transport.py +++ b/src/pipecat/transports/base_transport.py @@ -98,6 +98,7 @@ class TransportParams(BaseModel): video_out_bitrate: Video output bitrate in bits per second. video_out_framerate: Video output frame rate in FPS. video_out_color_format: Video output color format string. + video_out_codec: Preferred video codec for output (e.g., 'VP8', 'H264', 'H265'). video_out_destinations: List of video output destination identifiers. vad_enabled: Enable Voice Activity Detection (deprecated). @@ -151,6 +152,7 @@ class TransportParams(BaseModel): video_out_bitrate: int = 800000 video_out_framerate: int = 30 video_out_color_format: str = "RGB" + video_out_codec: Optional[str] = None video_out_destinations: List[str] = Field(default_factory=list) vad_enabled: bool = False vad_audio_passthrough: bool = False diff --git a/src/pipecat/transports/daily/transport.py b/src/pipecat/transports/daily/transport.py index e220ab0d8..fe106ebeb 100644 --- a/src/pipecat/transports/daily/transport.py +++ b/src/pipecat/transports/daily/transport.py @@ -811,6 +811,11 @@ class DailyTransportClient(EventHandler): "camera": { "sendSettings": { "maxQuality": "low", + **( + {"preferredCodec": self._params.video_out_codec} + if self._params.video_out_codec + else {} + ), "encodings": { "low": { "maxBitrate": self._params.video_out_bitrate, From 7bd32e2fe559220da9289aaef368fd2739ffbb9c Mon Sep 17 00:00:00 2001 From: Om Chauhan Date: Thu, 22 Jan 2026 09:49:19 +0530 Subject: [PATCH 0173/1060] feat(google): add location parameter to TTS services --- src/pipecat/services/google/tts.py | 30 ++++++++++++++++++++++++++++-- 1 file changed, 28 insertions(+), 2 deletions(-) diff --git a/src/pipecat/services/google/tts.py b/src/pipecat/services/google/tts.py index 52c0e7aec..2c22fb9c5 100644 --- a/src/pipecat/services/google/tts.py +++ b/src/pipecat/services/google/tts.py @@ -40,6 +40,7 @@ from pipecat.services.tts_service import TTSService from pipecat.transcriptions.language import Language, resolve_language try: + from google.api_core.client_options import ClientOptions from google.auth import default from google.auth.exceptions import GoogleAuthError from google.cloud import texttospeech_v1 @@ -515,6 +516,7 @@ class GoogleHttpTTSService(TTSService): *, credentials: Optional[str] = None, credentials_path: Optional[str] = None, + location: Optional[str] = None, voice_id: str = "en-US-Chirp3-HD-Charon", sample_rate: Optional[int] = None, params: Optional[InputParams] = None, @@ -525,6 +527,7 @@ class GoogleHttpTTSService(TTSService): Args: credentials: JSON string containing Google Cloud service account credentials. credentials_path: Path to Google Cloud service account JSON file. + location: Google Cloud location for regional endpoint (e.g., "us-central1"). voice_id: Google TTS voice identifier (e.g., "en-US-Standard-A"). sample_rate: Audio sample rate in Hz. If None, uses default. params: Voice customization parameters including pitch, rate, volume, etc. @@ -534,6 +537,7 @@ class GoogleHttpTTSService(TTSService): params = params or GoogleHttpTTSService.InputParams() + self._location = location self._settings = { "pitch": params.pitch, "rate": params.rate, @@ -586,7 +590,15 @@ class GoogleHttpTTSService(TTSService): if not creds: raise ValueError("No valid credentials provided.") - return texttospeech_v1.TextToSpeechAsyncClient(credentials=creds) + client_options = None + if self._location: + client_options = ClientOptions( + api_endpoint=f"{self._location}-texttospeech.googleapis.com" + ) + + return texttospeech_v1.TextToSpeechAsyncClient( + credentials=creds, client_options=client_options + ) def can_generate_metrics(self) -> bool: """Check if this service can generate processing metrics. @@ -783,7 +795,15 @@ class GoogleBaseTTSService(TTSService): if not creds: raise ValueError("No valid credentials provided.") - return texttospeech_v1.TextToSpeechAsyncClient(credentials=creds) + client_options = None + if self._location: + client_options = ClientOptions( + api_endpoint=f"{self._location}-texttospeech.googleapis.com" + ) + + return texttospeech_v1.TextToSpeechAsyncClient( + credentials=creds, client_options=client_options + ) def can_generate_metrics(self) -> bool: """Check if this service can generate processing metrics. @@ -903,6 +923,7 @@ class GoogleTTSService(GoogleBaseTTSService): *, credentials: Optional[str] = None, credentials_path: Optional[str] = None, + location: Optional[str] = None, voice_id: str = "en-US-Chirp3-HD-Charon", voice_cloning_key: Optional[str] = None, sample_rate: Optional[int] = None, @@ -914,6 +935,7 @@ class GoogleTTSService(GoogleBaseTTSService): Args: credentials: JSON string containing Google Cloud service account credentials. credentials_path: Path to Google Cloud service account JSON file. + location: Google Cloud location for regional endpoint (e.g., "us-central1"). voice_id: Google TTS voice identifier (e.g., "en-US-Chirp3-HD-Charon"). voice_cloning_key: The voice cloning key for Chirp 3 custom voices. sample_rate: Audio sample rate in Hz. If None, uses default. @@ -924,6 +946,7 @@ class GoogleTTSService(GoogleBaseTTSService): params = params or GoogleTTSService.InputParams() + self._location = location self._settings = { "language": self.language_to_service_language(params.language) if params.language @@ -1083,6 +1106,7 @@ class GeminiTTSService(GoogleBaseTTSService): model: str = "gemini-2.5-flash-tts", credentials: Optional[str] = None, credentials_path: Optional[str] = None, + location: Optional[str] = None, voice_id: str = "Kore", sample_rate: Optional[int] = None, params: Optional[InputParams] = None, @@ -1101,6 +1125,7 @@ class GeminiTTSService(GoogleBaseTTSService): "gemini-2.5-flash-tts" or "gemini-2.5-pro-tts". credentials: JSON string containing Google Cloud service account credentials. credentials_path: Path to Google Cloud service account JSON file. + location: Google Cloud location for regional endpoint (e.g., "us-central1"). voice_id: Voice name from the available Gemini voices. sample_rate: Audio sample rate in Hz. If None, uses Google's default 24kHz. params: TTS configuration parameters. @@ -1127,6 +1152,7 @@ class GeminiTTSService(GoogleBaseTTSService): if voice_id not in self.AVAILABLE_VOICES: logger.warning(f"Voice '{voice_id}' not in known voices list. Using anyway.") + self._location = location self._model = model self._voice_id = voice_id self._settings = { From 281145a9911d2c4cad331832cf16ec8bb68fc299 Mon Sep 17 00:00:00 2001 From: Om Chauhan Date: Thu, 22 Jan 2026 09:55:57 +0530 Subject: [PATCH 0174/1060] added changelog --- changelog/3523.added.md | 1 + 1 file changed, 1 insertion(+) create mode 100644 changelog/3523.added.md diff --git a/changelog/3523.added.md b/changelog/3523.added.md new file mode 100644 index 000000000..c6a0acc42 --- /dev/null +++ b/changelog/3523.added.md @@ -0,0 +1 @@ +- Added `location` parameter to Google TTS services (`GoogleHttpTTSService`, `GoogleTTSService`, `GeminiTTSService`) for regional endpoint support. \ No newline at end of file From 8e09d946144b6c21cbc7552aa71a4da05098ef12 Mon Sep 17 00:00:00 2001 From: Mark Backman Date: Thu, 22 Jan 2026 08:28:52 -0500 Subject: [PATCH 0175/1060] Remove application logs --- application-logs.log | 610 ------------------------------------------- 1 file changed, 610 deletions(-) delete mode 100644 application-logs.log diff --git a/application-logs.log b/application-logs.log deleted file mode 100644 index 32c97c288..000000000 --- a/application-logs.log +++ /dev/null @@ -1,610 +0,0 @@ -[ai] [2026-01-16 11:04:04 -0800] [59087] [INFO] 127.0.0.1:53364 OPTIONS /ai2/start-voice-assistant 1.1 200 0 9044 -[ai] INFO:sunsama_ai.server:Starting a call -[ai] INFO:sunsama_ai.server:CallId: None CallDomain: None DialoutNumber: None DialinNumber: None DialedNumber: None Flow: braindump -[ai] INFO:sunsama_ai.server: -[ai] -[ai] -[ai] -[ai] INFO:sunsama_ai.server:Call recording initialized for voice_session_id: 696a8ba4de74410788876fbb -[ai] INFO:sunsama_ai.voice_assistant.bot_runner:Creating new room... -[ai] INFO:sunsama_ai.voice_assistant.bot_runner:Daily room: https://cloud-99400c183d52498c940fe96f45c05b44.daily.co/teWpRxCQnkMHYi7Q3lqh -[ai] INFO:sunsama_ai.voice_assistant.bot_runner:Starting bot call... -[ai] INFO:sunsama_ai.voice_assistant.bot_runner:Bot call started -[ai] [2026-01-16 11:04:04 -0800] [59087] [INFO] 127.0.0.1:53364 POST /ai2/start-voice-assistant 1.1 200 356 358242 -[voice] INFO:sunsama_voice.bot:Bot process initialized None https://cloud-99400c183d52498c940fe96f45c05b44.daily.co/teWpRxCQnkMHYi7Q3lqh eyJhbGciOiJIUzI1NiIsInR5cCI6IkpXVCJ9.eyJyIjoidGVXcFJ4Q1Fua01IWWk3UTNscWgiLCJlanQiOmZhbHNlLCJleHAiOjE3Njg1OTA1NDQsIm8iOnRydWUsImQiOiI5OWJiNzdhNS0wYjZkLTRkOWMtOTkxMC1jMDcwNmEwZTA0ZDMiLCJpYXQiOjE3Njg1OTAyNDR9.npzlQ2ncZ7zemVHacAgerEYBSchiEM-VYxKf3t8Z5A0 -[voice] INFO:sunsama_voice.bot:{'roomUrl': 'https://cloud-99400c183d52498c940fe96f45c05b44.daily.co/teWpRxCQnkMHYi7Q3lqh', 'token': 'eyJhbGciOiJIUzI1NiIsInR5cCI6IkpXVCJ9.eyJyIjoidGVXcFJ4Q1Fua01IWWk3UTNscWgiLCJlanQiOmZhbHNlLCJleHAiOjE3Njg1OTA1NDQsIm8iOnRydWUsImQiOiI5OWJiNzdhNS0wYjZkLTRkOWMtOTkxMC1jMDcwNmEwZTA0ZDMiLCJpYXQiOjE3Njg1OTAyNDR9.npzlQ2ncZ7zemVHacAgerEYBSchiEM-VYxKf3t8Z5A0', 'callId': None, 'callDomain': None, 'detectVoicemail': False, 'dialoutNumber': None, 'dialinNumber': None, 'dialedNumber': None, 'authToken': 'eyJhbGciOiJIUzI1NiIsInR5cCI6IkpXVCJ9.eyJ1c2VySWQiOiI2NzFhYzVlNDAyYTMwMmNmNmVmMzA4OGUiLCJzZXNzaW9uSWQiOiIxOTVmNDI0NC05YjFmLTRlYmItOTMwZC0wZTExNTAwNzZkYzkiLCJzZXNzaW9uTm9uY2UiOiJhY2ZlZTc2OS1jZGU2LTRkMWYtYTU5Ni0xMzk0MTRkMjUxNjAiLCJncm91cElkIjoiNjcxYWM1ZTkwMmEzMDJjZjZlZjMwODkwIiwiZ3JvdXBVcmxQYXRoIjoiMTcyOTgwNzg0OTAzNjUxOTIiLCJpYXQiOjE3Njg1OTAyMTYsImV4cCI6MTc3MTE4MjIxNn0.HHSuewYqBRl-IZkdiWcEJyiD6akgbtwnOIQ4Js71bZI', 'flow': 'braindump', 'flowOptions': {}, 'voiceSessionId': '696a8ba4de74410788876fbb'} -[voice] /Users/zanemccaig/workspaces/sunsama/sunsama/sunsama-voice/venv/lib/python3.13/site-packages/pipecat/services/google/llm.py:281: DeprecationWarning: OpenAILLMContext is deprecated and will be removed in a future version. Use the universal LLMContext and LLMContextAggregatorPair instead. See OpenAILLMContext docstring for migration guide. -[voice] super().__init__(messages=messages, tools=tools, tool_choice=tool_choice) -[voice] INFO:sunsama_voice.mcp_websocket_client:Sending message: {'method': 'initialize', 'params': {'protocolVersion': '2025-06-18', 'capabilities': {}, 'clientInfo': {'name': 'mcp', 'version': '0.1.0'}}, 'jsonrpc': '2.0', 'id': 0} -[api-local] [api] 2026-01-16T19:04:04.835Z info: Setting up user subscription for MCP context: 671ac5e402a302cf6ef3088e -[api-local] [api] Registered handler for channel "user-updates-671ac5e402a302cf6ef3088e" for event "userUpdated" -[api-local] [api] 2026-01-16T19:04:04.835Z info: Successfully subscribed to user updates for MCP context: 671ac5e402a302cf6ef3088e -[api-local] [api] Starting WebSocket connection... -[voice] INFO:sunsama_voice.mcp_websocket_client:Received message: {"result":{"protocolVersion":"2025-06-18","capabilities":{"tools":{"listChanged":true},"prompts":{"listChanged":true},"completions":{},"resources":{"listChanged":true}},"serverInfo":{"name":"Sunsama MCP Server","version":"0.1.0"}},"jsonrpc":"2.0","id":0} -[voice] INFO:sunsama_voice.mcp_websocket_client:Sending message: {'method': 'notifications/initialized', 'jsonrpc': '2.0'} -[voice] INFO:sunsama_voice.bot:Timer: MCP Session created in 0.0885460376739502 seconds -[voice] DEBUG:sunsama_voice.bot:Starting bot with room_url: https://cloud-99400c183d52498c940fe96f45c05b44.daily.co/teWpRxCQnkMHYi7Q3lqh -[voice] /Users/zanemccaig/workspaces/sunsama/sunsama/sunsama-voice/sunsama_voice/models.py:254: DeprecationWarning: FalSmartTurnAnalyzer is deprecated and will be removed in a future version. Use LocalSmartTurnAnalyzerV3 instead. -[voice] turn_analyzer = FalSmartTurnAnalyzer( -[voice] DEBUG:pipecat.audio.vad.silero:Loading Silero VAD model... -[voice] DEBUG:pipecat.audio.vad.silero:Loaded Silero VAD -[voice] /Users/zanemccaig/workspaces/sunsama/sunsama/sunsama-voice/venv/lib/python3.13/site-packages/pipecat/processors/aggregators/llm_response.py:326: DeprecationWarning: GoogleUserContextAggregator (likely created with create_context_aggregator()) is deprecated and will be removed in a future version. Use the universal LLMContext and LLMContextAggregatorPair instead. See OpenAILLMContext docstring for migration guide. -[voice] super().__init__(**kwargs) -[voice] /Users/zanemccaig/workspaces/sunsama/sunsama/sunsama-voice/venv/lib/python3.13/site-packages/pipecat/processors/aggregators/llm_response.py:326: DeprecationWarning: GoogleAssistantContextAggregator (likely created with create_context_aggregator()) is deprecated and will be removed in a future version. Use the universal LLMContext and LLMContextAggregatorPair instead. See OpenAILLMContext docstring for migration guide. -[voice] super().__init__(**kwargs) -[voice] /Users/zanemccaig/workspaces/sunsama/sunsama/sunsama-voice/venv/lib/python3.13/site-packages/pipecat/transports/base_input.py:135: DeprecationWarning: Parameter 'turn_analyzer' is deprecated, use `LLMUserAggregator`'s new `user_turn_strategies` parameter instead. -[voice] warnings.warn( -[voice] DEBUG:pipecat.processors.frame_processor:Linking Pipeline#0::Source -> DailyInputTransport#0 -[voice] DEBUG:pipecat.processors.frame_processor:Linking DailyInputTransport#0 -> RTVIProcessor#0 -[voice] DEBUG:pipecat.processors.frame_processor:Linking RTVIProcessor#0 -> ClientMessageProcessor#0 -[voice] DEBUG:pipecat.processors.frame_processor:Linking ClientMessageProcessor#0 -> CustomUserIdleProcessor#0 -[voice] DEBUG:pipecat.processors.frame_processor:Linking CustomUserIdleProcessor#0 -> GoogleUserContextAggregator#0 -[voice] DEBUG:pipecat.processors.frame_processor:Linking GoogleUserContextAggregator#0 -> GoogleLLMService#0 -[voice] DEBUG:pipecat.processors.frame_processor:Linking GoogleLLMService#0 -> CartesiaTTSService#1 -[voice] DEBUG:pipecat.processors.frame_processor:Linking CartesiaTTSService#1 -> DailyOutputTransport#0 -[voice] DEBUG:pipecat.processors.frame_processor:Linking DailyOutputTransport#0 -> GoogleAssistantContextAggregator#0 -[voice] DEBUG:pipecat.processors.frame_processor:Linking GoogleAssistantContextAggregator#0 -> Pipeline#0::Sink -[voice] /Users/zanemccaig/workspaces/sunsama/sunsama/sunsama-voice/venv/lib/python3.13/site-packages/pipecat/pipeline/task.py:273: DeprecationWarning: Field 'observers' is deprecated, use the 'observers' parameter instead. -[voice] warnings.warn( -[voice] DEBUG:pipecat.processors.frame_processor:Linking PipelineTask#0::Source -> Pipeline#0 -[voice] DEBUG:pipecat.processors.frame_processor:Linking Pipeline#0 -> PipelineTask#0::Sink -[voice] INFO:sunsama_voice.bot:Timer: Pipeline created in 0.1510629653930664 seconds -[voice] INFO:sunsama_voice.mcp:Fetching resource sunsama://user/authentication with args: None sunsama://user/authentication -[voice] INFO:sunsama_voice.mcp_websocket_client:Sending message: {'method': 'resources/read', 'params': {'uri': 'sunsama://user/authentication'}, 'jsonrpc': '2.0', 'id': 1} -[voice] INFO:sunsama_voice.mcp_websocket_client:Received message: {"result":{"contents":[{"uri":"sunsama://user/authentication","mimeType":"text/plain","text":"authenticated"}]},"jsonrpc":"2.0","id":1} -[voice] INFO:sunsama_voice.mcp:Resource sunsama://user/authentication result: meta=None contents=[TextResourceContents(uri=AnyUrl('sunsama://user/authentication'), mimeType='text/plain', meta=None, text='authenticated')] -[voice] INFO:sunsama_voice.mcp:Resource sunsama://user/authentication result: uri=AnyUrl('sunsama://user/authentication') mimeType='text/plain' meta=None text='authenticated' -[voice] INFO:sunsama_voice.mcp:Handling resource update: uri sunsama://user/authentication authenticated 2026-01-16 11:04:04.903462 error=None status=None -[voice] INFO:sunsama_voice.mcp_websocket_client:Sending message: {'method': 'resources/list', 'jsonrpc': '2.0', 'id': 2} -[voice] INFO:sunsama_voice.mcp_websocket_client:Received message: {"result":{"resources":[{"uri":"sunsama://user/authentication","name":"get_user_authentication_status","description":"Retrieves the user's authentication status.","mimeType":"application/json"},{"uri":"sunsama://me","name":"get_user_info","description":"Critical information about the user like their name, timezone, and the current time where they're calling in from. Use this to personalize the conversation.","mimeType":"application/json"},{"uri":"sunsama://email/accounts","name":"list_email_accounts","description":"Lists email accounts the user has connected to Sunsama.","mimeType":"application/json"},{"uri":"sunsama://daily-highlight","name":"get_last_daily_highlight","description":"Retrieves their journal entry from their last workday in Markdown format.","mimeType":"text/markdown"},{"uri":"sunsama://backlog/folders","name":"get_backlog_folders","description":"Retrieves the user's backlog folders.","mimeType":"application/json"},{"uri":"sunsama://active-timer","name":"get_active_timer","description":"Retrieves information about the currently active timer, including which task has the timer running and when it was started.","mimeType":"application/json"},{"uri":"sunsama://ui/available-actions","name":"get_available_ui_actions","description":"Retrieves the list of available user interface actions that can be triggered by the assistant. This list may change based on the user's current context and permissions. Each action includes its actionId, type, and context information.","mimeType":"application/json"}]},"jsonrpc":"2.0","id":2} -[voice] INFO:sunsama_voice.mcp:Resource updated: uri sunsama://user/authentication -[voice] INFO:sunsama_voice.bot:Timer: Authentication status checked in 0.15551996231079102 seconds -[voice] INFO:sunsama_voice.mcp_websocket_client:Sending message: {'method': 'prompts/get', 'params': {'name': 'braindump', 'arguments': {}}, 'jsonrpc': '2.0', 'id': 3} -[api-local] [api] preFetchResources:get_backlog_folders:317522: 1.969ms -[api-local] [api] preFetchResources:get_user_info:436506: 6.557ms -[api-local] [api] preFetchResources:BRAINDUMP: 6.712ms -[voice] INFO:sunsama_voice.mcp_websocket_client:Received message: {"result":{"messages":[{"role":"user","content":{"type":"text","text":"You are Sunny, the personal assistant for a busy professional. You are part of Sunsama.\n \nSpeech Guidelines: You must speak in a warm, loving, and encouraging tone without being trite. Speak quickly and add emotion. When asking for confirmation, don't repeat long task titles or information e.g. \"Got it\" instead \"Got it, I'll add a task for two hours for you to work on the presentation today\"\n\nYour personality and philosophy:\n- You don't buy into hustle culture. For you, less is more. It's better to do fewer things well and to do them with deep focus. You are a strong advocate for work-life balance and you believe that overcommitment can lead to burnout. You always remind the user when they are overcommitting themselves.\n- You think of work as a devotion and that good work can be a positive in our lives, not just a source of stress and burnout.\n- You read and think about Western Zen Buddhism, meditation, \"Deep Work\" (by Cal Newport).\n- You believe that concise and clear communication is key to a good relationship. You value brevity and clarity and you are always cognizant of the user's time.\n- You respond to the user using quick, short sentences. Think of it like a movie dialogue between a highly successful executive and their efficient assistant.\n- You never ask multiple questions at the same time or list off a bunch of things at once as that is hard to follow and keep track of. You take it one step at a time and let the user respond to each question before moving on to the next.\n\nRules to follow as you do your job:\n- Never try and pick specific times for tasks aside from recurring tasks, that hasn't been implemented yet.\n- Do not regurgitate what the user just said, that's very annoying. Just say \"Got it\" or \"Alright\", etc.\n- Always use units that are more intuitive. For example:\n - Don't say \"270 minutes\", say \"4 and a half hours\".\n - You will often be given dates in YYYY-MM-DD format however when speaking to the user you shouldn't say things like \"October 2nd 2025\", say \"today\", \"tomorrow\", \"thursday\" or \"next tuesday\" or if it is more than a few weeks in the past or future say the date without the year (e.g. \"December 14th\"). Only mention the year if it is not this year and not within the next month.\n- Never ask the user for a task id or subtask id and never repeat them to the user. Those are internal and only there to help you do your job.\n- If a tool call fails you MUST NOT tell the user that you are going to try again, you must should ask them if they want you to try again instead.\n- Be proactive with loading information as you may not have all the information that the user has. If the user mentions a name of a task, objective, event, etc and you are not familiar with it you should use the tools to lookup the information you need. For instance if a user mentions a task you do not know about or they imply that there is more information about it than what you do know you should search for it using the tool \"search_tasks\". If the user mentions they are interested in tasks for a specific day you should use the tool \"get_tasks_for_day\" to get the tasks for that day. Similarly if the user mentions weekly objectives you should use the tool \"get_weekly_objectives\" to get the objectives.\n- When listing tasks try to be concise. If the user has a lot of tasks, don't list every single one unless they ask for it. You should instead try to summarize the tasks in a concise manner.\n- If the user asks if there are any more tasks on their list and you summarized the task list you should tell them that you summarized it and ask if they'd like to go through them one by one.\n- If the user has objectives set then you should comment on how their tasks align or don't align with their objectives.\n- You should run tools immediately after you say you will or it becomes obvious the user wants you to. Do not wait until later.\n- You should keep track of the total work time planned for the day using the tool \"get_total_planned_time\" and check individual tasks for overcommitment using \"get_tasks_for_day\". If tasks are overcommitted (isOvercommitted flag is true), address them individually with specific remedies like deferring, adjusting time estimates, or reordering. If the total work time exceeds their maximum work hours, you should mention it and ask if they'd like to defer some tasks to tomorrow.\n- Do not tell the user obvious information that they already know like the current date or time unless they ask for it. That kind of information is only provided to you to help you do your job.\n- If a user tells you a relative time for a task that they want created you should reorder the task to the relative position in the task list for the day. Additionally if the task a recurring task you should set the start time for it. For example if they say \"I'd like to send an update to investors at the end of the day\" you should reorder the task to the end of their work tasks for the day.\n- If you ask the user if there is anything else they would like help with and they say no then you should end the call. Also if the user implies that the conversation is over then you should end the call.\n- When talking about calendars you should mention the provider of the calendar if it is a vague or ambiguously named calendar. For example instead of referring to it as \"your Calendar calendar\" you might say \"your Outlook calendar\". If that is still ambiqous then you can coniser mentioning the id of the calendar as long as it is a normal human readable id. Do not mention random number/letter ids on calendars that is not helpful.\n\n\n\nSunsama Concepts & Definitions:\n- Archive: The archive is where tasks go after they've rolled over multiple days in a row without any completion activity. This is a distinct concept from the backlog or deleted tasks.\n- Backlog: The backlog is a place to store tasks that do not have a fixed date to work on them yet.\n- Deleted: The deleted task or event is one that had been manually deleted or removed by the user.\n- Task: A task is an item that a user wants to complete. It is either scheduled for a specific date or is in the backlog.\n- Event: An event is an item that a user has scheduled on their calendar. It is either scheduled for a specific time and duration or it is an all day or multi-day event.\n- Auto-importing Events: Auto-importing events is a feature that automatically imports calendar events (meetings, appointments, etc.) from the user's connected calendars into their daily task list. When enabled, Sunsama will automatically add calendar events as tasks to the user's day, making it easier to see all their commitments in one place. Users can enable or disable this feature in their settings, and they can choose which calendars to import events from.\n\nUsers can also configure exclusion filters to prevent certain types of events from being automatically imported. Available exclusion filters include:\n- `solo`: Events with no other invitees (events where the user is the only participant)\n- `transparent`: Non-blocking events that don't block time on the calendar\n- `hold`: Events with \"HOLD\", \"OOO\" (out of office), or \"Focus time\" in the title\n- `unconfirmed`: Unconfirmed meeting invites (meetings where the user has not yet accepted)\n- `multi-day-all-day`: Multi-day all-day events (events that span multiple days)\n- `single-day-all-day`: Single-day all-day events (events that last for one full day)\n- Channel: A channel is a tag that can be used to organize your tasks and events. Each task/event can be assigned to a single channel. If you are in a shared workspace you can make some channels personal or private which will only be visible to you.\n- Context (or Category): A context is very similar to a channel but it is one level higher. You can use a context to group similar or related channels together. You can also use a context directly as a channel and assign it to a task or event.\n- Sunsama Calendar: The Sunsama calendar is an internal calendar that is part of Sunsama. Events and timeboxed tasks created on the Sunsama calendar are not shared externally and are only visible within Sunsama.\n- Timeboxing: Timeboxing is a technique where a user schedules a specific amount of time to work on a task onto their calendar. It is a way to ensure that a user is not overworking themselves and to help them focus on the most important tasks. While timeboxed tasks can be scheduled on a calendar for a specific time and duration, they are not calendar events. Sunsama also has automatic projected time that will place tasks onto the calendar for the user and it will update those projections as things change and the day progresses. Users can pin tasks to the calendar to override the projections.\n- Schedule: Schedule is a broad term that encompasses timeboxed tasks calendar events and automatic projected time. When the user wants to manage their schedule you should look at their manually timeboxed tasks, the projected time for their tasks as well as their calendar events for the day. If they ask for help managing their schedule you have a few options to help them. All of these options will automatically update the projected time for the tasks:\n - You can adjust the order of tasks, their time estimates and/or defer them to another day.\n - You can move calendar events to a new time on the calendar.\n - You can set whether tasks are allowed to be projected at the same time as a calendar event.\n - You can timebox tasks to the calendar manually.\n- Objective: An objective is a goal that a user can set for the week. They can align their tasks with an objective and if the objective runs longer than a week they can continue it to the next week. Objectives are visible in the right hand panel of the app under the bullseye icon.\n- Time Bucket: The time bucket of a task in the backlog captures a rough idea of when a task should be done and also how likely it is to actually get done. Options: \"in the next two weeks\", \"in the next month\", \"in the next quarter\", \"in the next year\", \"someday\", \"never\". \n\n\n\nSunsama FAQ:\n- How can I use Sunny in the app?: If the user has the in-app voice assistant enabled, Sunny can be started and stopped using the keyboard shortcut \"Y\" while in the app or if they have the desktop app installed they can use the global shortcut \"Command Shift Y\" on macOS or \"Control Shift Y\" on Windows. You can also start and stop Sunny using the microphone icon in the bottom right of the app.\n- How can I use Sunny over the phone?: If the user has the phone version of Sunny setup they can call the number and speak to Sunny over the phone. You can find the phone number in the Sunsama settings. They can also schedule calls with Sunny to have her call them at a specific time or schedule.\n- What can you do?: Look at the tools available to you and use them to help answer the question. Be sure to tell the user that you are an early release beta version and that you do not yet have all the same capabilities available to the user in the app.\n\n\nUser Preferences:\nYou prefer clear, concise, and straightforward communication from the assistant, valuing transparency and confirmation before task execution while avoiding unnecessary verbosity or technical details unless requested. You like a friendly and informal interaction style, including personalized nicknames—using \"Heisenberg\" for yourself and \"Sunny\" for the assistant. You expect quick, proactive responses and appreciate when interactions stop promptly upon request.\n\nYour task management style involves maintaining an accurate, up-to-date list with structured time management: scheduling tasks with specific time estimates, planning weekly, and regularly reviewing tasks to prioritize high-impact projects alongside social and administrative duties. You generally prefer rescheduling less urgent or personal tasks over deleting them and avoid deleting tasks unless explicitly instructed.\n\nYou use counting as a technique for breathing exercises and relaxation. You also keep certain important tasks (e.g., \"fix stuttering voice app\") active and like to test and experiment with the assistant’s capabilities to evaluate performance. Your primary calendar for events is Google Calendar.\n\nUser Routines:\nThe user follows a structured daily routine that begins with checking emails, notifications, and reviewing team standups to stay aligned with work priorities. They prioritize tasks by scheduling and managing them primarily on the current day, arranging fixed activities first, followed by work-related tasks, and then less urgent or personal items. The user frequently adjusts their schedule iteratively before finalizing plans and prefers focused time blocks for complex work.\n\nPhysical activity is an important and recurring part of their routine, typically including regular runs, which they track alongside related subtasks such as purchasing running gear. Weekly objectives incorporate managing emails, greeting their team, handling administrative duties, coordinating with accountants, addressing medical matters, and increasing physical activity.\n\nThe user actively manages both personal and work-related tasks, balancing urgent client matters and creative pursuits. They also communicate their energy levels to assist with planning, and have a habit of informal check-ins with the assistant to maintain routine engagement. Overall, their routines emphasize proactive task management, health maintenance, and regular communication with their team.\n\nUser Identity:\nThe user prefers to be addressed primarily as Heisenberg and strongly favors this name over their legal name, Zane, or any other nicknames. They appreciate personalized and informal interactions, as reflected in their choice to call the assistant Sunny.\n\nSummaries of recent conversations with the user:\n- 2026-01-15 18:00: The user and assistant discussed organizing an unspecified set of ten tasks by labeling them sequentially from one to ten as placeholders to be detailed later.\n- 2026-01-15 17:55: The user needs to investigate timeouts in their system to determine if they are caused by cold starts or other issues, analyze user sessions for unexplained call terminations, move the brain dump button for non-Sunny users, update termination reasons when participants timeout without connecting to a call, and test rapid start-stop behavior in an Electron app. These tasks were added to their backlog for the next two weeks.\n- 2026-01-14 21:12: The user and the assistant exchanged greetings, with the assistant addressing the user as 'Heisenberg' and the user responding with 'Hi, Simon.'\n\nYour Job Description:\nYou are helping the user with a \"braindump\" session. The user will ramble ideas, thoughts, tasks, etc. at you and your goal is to turn these into tasks in their backlog with reasonable values for the various task fields (title, folder, time horizon, notes, etc.).\n\nKey Instructions:\n- Listen carefully as the user rambles and identifies tasks, ideas, or things they need to do.\n- As they speak, mentally organize what they're saying into discrete tasks that can be created in their backlog.\n- Don't interrupt them while they're rambling - let them get everything out.\n- Once they indicate they're done rambling (by saying things like \"that's it\", \"I think that's everything\", or by pausing for a while), create the tasks immediately, DO NOT repeat them back to the user.\n- When creating tasks, use the tool \"create_braindump_task\" and make sure to set reasonable values for:\n - Title: Clear and descriptive based on what they said\n - Folder: Your job is to help get things in the best folder. Choose an appropriate folder based on the task and their preferences. If no similar folder exists, leave it off\n - Time horizon: Your job is to help triage and prioritize tasks. Based on the actual task name, make a smart decision on the time horizon.\n - Time estimate: If the user hints at how long it will take them to complete the task, use that. If not, leave it blank.\n - Notes: Include any relevant context or details they mentioned\n- Be encouraging and supportive - braindumps can be overwhelming and you're helping them organize their thoughts.\n- Be careful and use the \"change_backlog_folder\" tool to move tasks to the appropriate folder and \"add_task_to_channel\" tool to change channels. Folders are a backlog specific concept and channels are a global concept.\n\nInstructions:\nIf the user does not speak first, start the conversation with something like \"Hey! Just start rambling and I'll take care of organizing your thoughts into tasks.\" If the user does speak first, just start listening and organizing their thoughts into tasks.\n\nSome information is pre-fetched for you below. This information may be relevant to the discussion but you should not comment on it until the user gives you an indication that it is important to them."}},{"role":"user","content":{"type":"resource","resource":{"uri":"sunsama://me","mimeType":"application/json","text":"{\"user\":{\"name\":\"Zane Mccaig\",\"email\":\"zane@sunsama.com\",\"timezone\":\"America/Vancouver\",\"maxWorkHoursPerDay\":8,\"currentTimeForUser\":\"11:04 AM\",\"currentDayForUser\":\"2026-01-16\",\"currentWeekDayForUser\":\"Friday\",\"calendars\":[{\"id\":\"sunsama-7de256a2-e753-401f-b601-e5c05638dc97\",\"name\":\"Sunsama Calendar\",\"accessRole\":\"owner\",\"provider\":\"sunsama-calendar\",\"isDefaultCalendarForSchedulingEvents\":false,\"isDefaultCalendarForTimeboxing\":true,\"includedInAutoImportingOfEvents\":false},{\"id\":\"zane@sunsama.com\",\"name\":\"Zane Mccaig\",\"accessRole\":\"owner\",\"provider\":\"google-calendar\",\"isDefaultCalendarForSchedulingEvents\":true,\"isDefaultCalendarForTimeboxing\":false,\"includedInAutoImportingOfEvents\":true},{\"id\":\"c_ukuoebbn11gdv6n1v0jt18h89k@group.calendar.google.com\",\"name\":\"test 1\",\"accessRole\":\"owner\",\"provider\":\"google-calendar\",\"isDefaultCalendarForSchedulingEvents\":false,\"isDefaultCalendarForTimeboxing\":false,\"includedInAutoImportingOfEvents\":false},{\"id\":\"c_c71dvjrar7se12ekfqepph067c@group.calendar.google.com\",\"name\":\"test 2\",\"accessRole\":\"owner\",\"provider\":\"google-calendar\",\"isDefaultCalendarForSchedulingEvents\":false,\"isDefaultCalendarForTimeboxing\":false,\"includedInAutoImportingOfEvents\":false},{\"id\":\"c_h9uo876jh8dp3gaa2a3rglmjss@group.calendar.google.com\",\"name\":\"test 3\",\"accessRole\":\"owner\",\"provider\":\"google-calendar\",\"isDefaultCalendarForSchedulingEvents\":false,\"isDefaultCalendarForTimeboxing\":false,\"includedInAutoImportingOfEvents\":false},{\"id\":\"c_git731ot074kcnt4sq8cu4ji9s@group.calendar.google.com\",\"name\":\"test 4\",\"accessRole\":\"owner\",\"provider\":\"google-calendar\",\"isDefaultCalendarForSchedulingEvents\":false,\"isDefaultCalendarForTimeboxing\":false,\"includedInAutoImportingOfEvents\":false},{\"id\":\"c_ona71b8ovuv0deqrq67p16b2ms@group.calendar.google.com\",\"name\":\"test 4\",\"accessRole\":\"owner\",\"provider\":\"google-calendar\",\"isDefaultCalendarForSchedulingEvents\":false,\"isDefaultCalendarForTimeboxing\":false,\"includedInAutoImportingOfEvents\":false},{\"id\":\"c_eaq7nmm03upprf0j6e2akem2ms@group.calendar.google.com\",\"name\":\"test 5\",\"accessRole\":\"owner\",\"provider\":\"google-calendar\",\"isDefaultCalendarForSchedulingEvents\":false,\"isDefaultCalendarForTimeboxing\":false,\"includedInAutoImportingOfEvents\":false},{\"id\":\"sunsama.com_b9q30t893b2tp32bluq1t8rvg4@group.calendar.google.com\",\"name\":\"Zane's personal test calendar\",\"accessRole\":\"owner\",\"provider\":\"google-calendar\",\"isDefaultCalendarForSchedulingEvents\":false,\"isDefaultCalendarForTimeboxing\":false,\"includedInAutoImportingOfEvents\":false},{\"id\":\"en.canadian#holiday@group.v.calendar.google.com\",\"name\":\"Holidays in Canada\",\"accessRole\":\"reader\",\"provider\":\"google-calendar\",\"isDefaultCalendarForSchedulingEvents\":false,\"isDefaultCalendarForTimeboxing\":false,\"includedInAutoImportingOfEvents\":false},{\"id\":\"en.usa#holiday@group.v.calendar.google.com\",\"name\":\"Holidays in United States\",\"accessRole\":\"reader\",\"provider\":\"google-calendar\",\"isDefaultCalendarForSchedulingEvents\":false,\"isDefaultCalendarForTimeboxing\":false,\"includedInAutoImportingOfEvents\":false},{\"id\":\"ht3jlfaac5lfd6263ulfh4tql8@group.calendar.google.com\",\"name\":\"Phases of the Moon\",\"accessRole\":\"reader\",\"provider\":\"google-calendar\",\"isDefaultCalendarForSchedulingEvents\":false,\"isDefaultCalendarForTimeboxing\":false,\"includedInAutoImportingOfEvents\":false},{\"id\":\"s4ipng85dbia0t83fp316vflfq8rc7rm@import.calendar.google.com\",\"name\":\"Zane’s tasks - sunsama.com (via Asana)\",\"accessRole\":\"reader\",\"provider\":\"google-calendar\",\"isDefaultCalendarForSchedulingEvents\":false,\"isDefaultCalendarForTimeboxing\":false,\"includedInAutoImportingOfEvents\":false},{\"id\":\"AAkALgAAAAAAHYQDEapmEc2byACqAC-EWg0AKPy-EasNgkaYQCuEslBYeAAAAAANJQAA\",\"name\":\"Calendar\",\"accessRole\":\"owner\",\"provider\":\"outlook-calendar\",\"isDefaultCalendarForSchedulingEvents\":false,\"isDefaultCalendarForTimeboxing\":false,\"includedInAutoImportingOfEvents\":true}],\"callSchedule\":[{\"workflow\":\"PLANNING_CALL\",\"schedule\":[{\"isoDayIndex\":1,\"dayName\":\"Monday\",\"enabled\":false,\"time\":null},{\"isoDayIndex\":2,\"dayName\":\"Tuesday\",\"enabled\":true,\"time\":{\"hour\":9,\"minute\":30,\"formatted\":\"9:30 AM\"}},{\"isoDayIndex\":3,\"dayName\":\"Wednesday\",\"enabled\":true,\"time\":{\"hour\":9,\"minute\":30,\"formatted\":\"9:30 AM\"}},{\"isoDayIndex\":4,\"dayName\":\"Thursday\",\"enabled\":true,\"time\":{\"hour\":10,\"minute\":0,\"formatted\":\"10:00 AM\"}},{\"isoDayIndex\":5,\"dayName\":\"Friday\",\"enabled\":false,\"time\":null},{\"isoDayIndex\":6,\"dayName\":\"Saturday\",\"enabled\":false,\"time\":null},{\"isoDayIndex\":7,\"dayName\":\"Sunday\",\"enabled\":false,\"time\":null}],\"nextScheduledCall\":\"2026-01-14T17:30:00.000Z\"}],\"autoImportEventsEnabled\":false,\"importEventExclusionFilters\":[\"hold\",\"multi-day-all-day\",\"single-day-all-day\"],\"autoImportEventCalendarIds\":[\"zane@sunsama.com\",\"AAkALgAAAAAAHYQDEapmEc2byACqAC-EWg0AKPy-EasNgkaYQCuEslBYeAAAAAANJQAA\"]}}"}}},{"role":"user","content":{"type":"resource","resource":{"uri":"sunsama://backlog/folders","mimeType":"application/json","text":"{\"folders\":[]}"}}}]},"jsonrpc":"2.0","id":3} -[voice] INFO:sunsama_voice.mcp:Handling resource update: uri sunsama://me {"user":{"name":"Zane Mccaig","email":"zane@sunsama.com","timezone":"America/Vancouver","maxWorkHoursPerDay":8,"currentTimeForUser":"11:04 AM","currentDayForUser":"2026-01-16","currentWeekDayForUser":"Friday","calendars":[{"id":"sunsama-7de256a2-e753-401f-b601-e5c05638dc97","name":"Sunsama Calendar","accessRole":"owner","provider":"sunsama-calendar","isDefaultCalendarForSchedulingEvents":false,"isDefaultCalendarForTimeboxing":true,"includedInAutoImportingOfEvents":false},{"id":"zane@sunsama.com","name":"Zane Mccaig","accessRole":"owner","provider":"google-calendar","isDefaultCalendarForSchedulingEvents":true,"isDefaultCalendarForTimeboxing":false,"includedInAutoImportingOfEvents":true},{"id":"c_ukuoebbn11gdv6n1v0jt18h89k@group.calendar.google.com","name":"test 1","accessRole":"owner","provider":"google-calendar","isDefaultCalendarForSchedulingEvents":false,"isDefaultCalendarForTimeboxing":false,"includedInAutoImportingOfEvents":false},{"id":"c_c71dvjrar7se12ekfqepph067c@group.calendar.google.com","name":"test 2","accessRole":"owner","provider":"google-calendar","isDefaultCalendarForSchedulingEvents":false,"isDefaultCalendarForTimeboxing":false,"includedInAutoImportingOfEvents":false},{"id":"c_h9uo876jh8dp3gaa2a3rglmjss@group.calendar.google.com","name":"test 3","accessRole":"owner","provider":"google-calendar","isDefaultCalendarForSchedulingEvents":false,"isDefaultCalendarForTimeboxing":false,"includedInAutoImportingOfEvents":false},{"id":"c_git731ot074kcnt4sq8cu4ji9s@group.calendar.google.com","name":"test 4","accessRole":"owner","provider":"google-calendar","isDefaultCalendarForSchedulingEvents":false,"isDefaultCalendarForTimeboxing":false,"includedInAutoImportingOfEvents":false},{"id":"c_ona71b8ovuv0deqrq67p16b2ms@group.calendar.google.com","name":"test 4","accessRole":"owner","provider":"google-calendar","isDefaultCalendarForSchedulingEvents":false,"isDefaultCalendarForTimeboxing":false,"includedInAutoImportingOfEvents":false},{"id":"c_eaq7nmm03upprf0j6e2akem2ms@group.calendar.google.com","name":"test 5","accessRole":"owner","provider":"google-calendar","isDefaultCalendarForSchedulingEvents":false,"isDefaultCalendarForTimeboxing":false,"includedInAutoImportingOfEvents":false},{"id":"sunsama.com_b9q30t893b2tp32bluq1t8rvg4@group.calendar.google.com","name":"Zane's personal test calendar","accessRole":"owner","provider":"google-calendar","isDefaultCalendarForSchedulingEvents":false,"isDefaultCalendarForTimeboxing":false,"includedInAutoImportingOfEvents":false},{"id":"en.canadian#holiday@group.v.calendar.google.com","name":"Holidays in Canada","accessRole":"reader","provider":"google-calendar","isDefaultCalendarForSchedulingEvents":false,"isDefaultCalendarForTimeboxing":false,"includedInAutoImportingOfEvents":false},{"id":"en.usa#holiday@group.v.calendar.google.com","name":"Holidays in United States","accessRole":"reader","provider":"google-calendar","isDefaultCalendarForSchedulingEvents":false,"isDefaultCalendarForTimeboxing":false,"includedInAutoImportingOfEvents":false},{"id":"ht3jlfaac5lfd6263ulfh4tql8@group.calendar.google.com","name":"Phases of the Moon","accessRole":"reader","provider":"google-calendar","isDefaultCalendarForSchedulingEvents":false,"isDefaultCalendarForTimeboxing":false,"includedInAutoImportingOfEvents":false},{"id":"s4ipng85dbia0t83fp316vflfq8rc7rm@import.calendar.google.com","name":"Zane’s tasks - sunsama.com (via Asana)","accessRole":"reader","provider":"google-calendar","isDefaultCalendarForSchedulingEvents":false,"isDefaultCalendarForTimeboxing":false,"includedInAutoImportingOfEvents":false},{"id":"AAkALgAAAAAAHYQDEapmEc2byACqAC-EWg0AKPy-EasNgkaYQCuEslBYeAAAAAANJQAA","name":"Calendar","accessRole":"owner","provider":"outlook-calendar","isDefaultCalendarForSchedulingEvents":false,"isDefaultCalendarForTimeboxing":false,"includedInAutoImportingOfEvents":true}],"callSchedule":[{"workflow":"PLANNING_CALL","schedule":[{"isoDayIndex":1,"dayName":"Monday","enabled":false,"time":null},{"isoDayIndex":2,"dayName":"Tuesday","enabled":true,"time":{"hour":9,"minute":30,"formatted":"9:30 AM"}},{"isoDayIndex":3,"dayName":"Wednesday","enabled":true,"time":{"hour":9,"minute":30,"formatted":"9:30 AM"}},{"isoDayIndex":4,"dayName":"Thursday","enabled":true,"time":{"hour":10,"minute":0,"formatted":"10:00 AM"}},{"isoDayIndex":5,"dayName":"Friday","enabled":false,"time":null},{"isoDayIndex":6,"dayName":"Saturday","enabled":false,"time":null},{"isoDayIndex":7,"dayName":"Sunday","enabled":false,"time":null}],"nextScheduledCall":"2026-01-14T17:30:00.000Z"}],"autoImportEventsEnabled":false,"importEventExclusionFilters":["hold","multi-day-all-day","single-day-all-day"],"autoImportEventCalendarIds":["zane@sunsama.com","AAkALgAAAAAAHYQDEapmEc2byACqAC-EWg0AKPy-EasNgkaYQCuEslBYeAAAAAANJQAA"]}} 2026-01-16 11:04:04.930576 error=None status=None -[voice] INFO:sunsama_voice.mcp:Resource updated: uri sunsama://me -[voice] INFO:sunsama_voice.mcp:Handling resource update: uri sunsama://backlog/folders {"folders":[]} 2026-01-16 11:04:04.930707 error=None status=None -[voice] INFO:sunsama_voice.mcp:Resource updated: uri sunsama://backlog/folders -[voice] INFO:sunsama_voice.mcp:Resources: ['get_user_authentication_status', 'get_user_info', 'list_email_accounts', 'get_last_daily_highlight', 'get_backlog_folders', 'get_active_timer', 'get_available_ui_actions'] get_user_info -[voice] INFO:sunsama_voice.mcp_websocket_client:Sending message: {'method': 'tools/list', 'jsonrpc': '2.0', 'id': 4} -[voice] INFO:sunsama_voice.mcp_websocket_client:Received message: {"result":{"tools":[{"name":"create_task","description":"Creates a single task with a title, optional notes, and estimated time.","inputSchema":{"$schema":"http://json-schema.org/draft-07/schema#","type":"object","properties":{"title":{"description":"A short title of the task, should not be more than a few words","type":"string"},"notes":{"description":"All extra details the user shared about the task, in HTML format","type":"string"},"timeEstimate":{"description":"The estimated time in minutes for the task","type":"number"},"objectiveId":{"description":"The _id of the weekly objective the task should be associated with, if any.","type":"string"},"day":{"description":"The day the task should be scheduled to in YYYY-MM-DD format.","type":"string"},"backlog":{"description":"Whether the task should be added to the backlog.","type":"object","properties":{"timeBucket":{"description":"The time bucket captures a rough idea of when a task should be done and also how likely it is to actually get done. Options: \"in the next two weeks\", \"in the next month\", \"in the next quarter\", \"in the next year\", \"someday\", \"never\". ","type":"string","enum":["in the next two weeks","in the next month","in the next quarter","in the next year","someday","never"]},"folderId":{"description":"The _id of the backlog folder the task should be added.","type":"string"}}},"alreadyInTaskList":{"description":"Whether the task is already in the user's task list or calendar.","type":"boolean"},"channel":{"description":"The channel the task should be added to. This does not need to be perfect. The closest match will be used. If not provided a channel will be added automatically as long as the user did not disable the channel prediction feature.","type":"string"},"position":{"default":"bottom","description":"Where to place the task in the list. Defaults to bottom. If the user asks for another position you should re-order the task after creating it.","type":"string","enum":["top","bottom"]},"subtasks":{"type":"array","items":{"type":"object","properties":{"title":{"description":"The title of the subtask","type":"string"}},"required":["title"]}},"recurrenceRule":{"description":"The recurrence rule for the task in RRULE format. If provided the task will be created as a recurring task.","type":"string"},"recurringTaskStartTime":{"description":"The start time for the recurring task in 12 hour \"h:mm A\" format. Only used when recurrenceRule is provided.","type":"string"},"isRecurringTaskStartTimeOnlyAnEstimate":{"description":"Whether the recurring task start time is only an estimate and not a rigid start time. Only used when recurrenceRule and recurringTaskStartTime are provided.","type":"boolean"}},"required":["title","day","alreadyInTaskList"]},"execution":{"taskSupport":"forbidden"}},{"name":"create_braindump_task","description":"Creates a single task in the backlog with a title, optional notes, estimated time, time horizon, and optional folder.","inputSchema":{"$schema":"http://json-schema.org/draft-07/schema#","type":"object","properties":{"title":{"description":"A short title of the task, should not be more than a few words","type":"string"},"notes":{"description":"All extra details the user shared about the task, in HTML format","type":"string"},"timeEstimate":{"description":"The estimated time in minutes for the task","type":"number"},"folderId":{"description":"The _id of the backlog folder the task should be added.","type":"string"},"timeBucket":{"description":"The time bucket captures a rough idea of when a task should be done and also how likely it is to actually get done. Options: \"in the next two weeks\", \"in the next month\", \"in the next quarter\", \"in the next year\", \"someday\", \"never\". ","type":"string","enum":["in the next two weeks","in the next month","in the next quarter","in the next year","someday","never"]},"channel":{"description":"The channel the task should be added to. This does not need to be perfect. The closest match will be used. If not provided a channel will be added automatically as long as the user did not disable the channel prediction feature.","type":"string"},"subtasks":{"type":"array","items":{"type":"object","properties":{"title":{"description":"The title of the subtask","type":"string"}},"required":["title"]}}},"required":["title","timeBucket"]},"execution":{"taskSupport":"forbidden"}},{"name":"reposition_task_in_backlog","description":"Repositions a task within the backlog by moving it to a specific time bucket (horizon) and position (append/prepend).","inputSchema":{"$schema":"http://json-schema.org/draft-07/schema#","type":"object","properties":{"taskId":{"description":"The unique identifier `_id` of the task to reposition.","type":"string"},"timeBucket":{"description":"The time bucket captures a rough idea of when a task should be done and also how likely it is to actually get done. Options: \"in the next two weeks\", \"in the next month\", \"in the next quarter\", \"in the next year\", \"someday\", \"never\".","type":"string","enum":["in the next two weeks","in the next month","in the next quarter","in the next year","someday","never"]},"position":{"description":"Where to position the task in the bucket. \"prepend\" places it at the top, \"append\" places it at the bottom.","type":"string","enum":["append","prepend"]}},"required":["taskId","timeBucket"]},"execution":{"taskSupport":"forbidden"}},{"name":"change_backlog_folder","description":"Moves one or more tasks to a backlog folder. If folderId is null, removes tasks from their current folder.","inputSchema":{"$schema":"http://json-schema.org/draft-07/schema#","type":"object","properties":{"taskIds":{"description":"The unique identifier(s) `_id` of the task(s) to move. Can be a single task ID or an array of task IDs.","anyOf":[{"type":"string"},{"type":"array","items":{"type":"string"}}]},"folderId":{"description":"The _id of the backlog folder to move the tasks to. If null, removes tasks from their current folder.","anyOf":[{"type":"string"},{"type":"null"}]}},"required":["taskIds"]},"execution":{"taskSupport":"forbidden"}},{"name":"align_task_with_objective","description":"Aligns a task with an objective.","inputSchema":{"$schema":"http://json-schema.org/draft-07/schema#","type":"object","properties":{"taskId":{"description":"The _id of the task to align with the objective.","type":"string"},"objectiveId":{"description":"The _id of the objective to align the task with.","type":"string"}},"required":["taskId","objectiveId"]},"execution":{"taskSupport":"forbidden"}},{"name":"add_task_to_channel","description":"Adds a task to a channel.","inputSchema":{"$schema":"http://json-schema.org/draft-07/schema#","type":"object","properties":{"taskId":{"description":"The _id of the task to add to the channel.","type":"string"},"channel":{"description":"The channel to add the task to. This does not need to be perfect. The closest match will be used.","type":"string"}},"required":["taskId","channel"]},"execution":{"taskSupport":"forbidden"}},{"name":"move_task_to_day","description":"Moves or defers a task to a specific date.","inputSchema":{"$schema":"http://json-schema.org/draft-07/schema#","type":"object","properties":{"taskId":{"description":"The unique identifier `_id` of the task to move.","type":"string"},"calendarDay":{"description":"The new date to move the task to in YYYY-MM-DD format.","type":"string"},"sortOrder":{"description":"The new sort order of the task. This should be an integer that is half way between the sort order of the task before it and the sort order of the task after it. If placing at the end of the list, use the sort order of the last task + 2048. If left blank, the task will be placed at the top of the list.","type":"number"}},"required":["taskId","calendarDay"]},"execution":{"taskSupport":"forbidden"}},{"name":"move_task_from_backlog","description":"Moves a task out of the backlog and onto a specific date.","inputSchema":{"$schema":"http://json-schema.org/draft-07/schema#","type":"object","properties":{"taskId":{"description":"The unique identifier `_id` of the task to move.","type":"string"},"calendarDay":{"description":"The new date to move the task to in YYYY-MM-DD format.","type":"string"},"sortOrder":{"description":"The new sort order of the task. This should be an integer that is half way between the sort order of the task before it and the sort order of the task after it. If placing at the end of the list, use the sort order of the last task + 2048. If left blank, the task will be placed at the top of the list.","type":"number"}},"required":["taskId","calendarDay"]},"execution":{"taskSupport":"forbidden"}},{"name":"unarchive_task","description":"Unarchives a task and moves it to a specific date or the backlog if no date is provided.","inputSchema":{"$schema":"http://json-schema.org/draft-07/schema#","type":"object","properties":{"taskId":{"description":"The unique identifier `_id` of the task to move.","type":"string"},"calendarDay":{"description":"The new date to move the task to in YYYY-MM-DD format.","type":"string"},"sortOrder":{"description":"The new sort order of the task. This should be an integer that is half way between the sort order of the task before it and the sort order of the task after it. If placing at the end of the list, use the sort order of the last task + 2048. If left blank, the task will be placed at the top of the list.","type":"number"}},"required":["taskId","calendarDay"]},"execution":{"taskSupport":"forbidden"}},{"name":"move_task_to_backlog","description":"Moves a task to the backlog. IF THE USER ASKS YOU TO MOVE A TASK TO A SPECIFIC DAY THEN YOU SHOULD USE THE move_task_to_day TOOL NOT THIS ONE.","inputSchema":{"$schema":"http://json-schema.org/draft-07/schema#","type":"object","properties":{"taskId":{"description":"The unique identifier `_id` of the task to move.","type":"string"}},"required":["taskId"]},"execution":{"taskSupport":"forbidden"}},{"name":"get_task_time_estimate","description":"Gets the time estimate for a task in minutes.","inputSchema":{"$schema":"http://json-schema.org/draft-07/schema#","type":"object","properties":{"title":{"description":"The title of the task. The estimate will be based on similar task names.","type":"string"}},"required":["title"]},"execution":{"taskSupport":"forbidden"}},{"name":"edit_task_recurrence_rule","description":"Updates the recurrence rule of an existing task.","inputSchema":{"$schema":"http://json-schema.org/draft-07/schema#","type":"object","properties":{"taskId":{"description":"The _id of the task to update.","type":"string"},"recurrenceRule":{"description":"The new recurrence rule for the task in RRULE format. The recurrence rule must not have more than one occurrence of a task on any given day.","type":"string"},"firstOccurrenceOnOrAfter":{"description":"The date to start the recurrence on or after. This should be in YYYY-MM-DD format. If not provided the first occurrence will be set according to the old recurrence rule or the current date of the task if no recurrence rule exists.","type":"string"},"startTime":{"description":"The start time of the task in 12 hour \"h:mm A\" format. If not provided the start time will be set according to the old recurrence rule or it will be omitted.","type":"string"},"isStartTimeOnlyAnEstimate":{"description":"Whether the start time is only an estimate and not a rigid start time. If not provided the start time will be set according to the old recurrence rule or it will be set to a rigid start time.","type":"boolean"}},"required":["taskId","recurrenceRule"]},"execution":{"taskSupport":"forbidden"}},{"name":"edit_task_title","description":"Updates the title of an existing task.","inputSchema":{"$schema":"http://json-schema.org/draft-07/schema#","type":"object","properties":{"taskId":{"description":"The _id of the task to update.","type":"string"},"title":{"description":"The new title for the task.","type":"string"}},"required":["taskId","title"]},"execution":{"taskSupport":"forbidden"}},{"name":"edit_task_time_estimate","description":"Updates the time estimate of an existing task.","inputSchema":{"$schema":"http://json-schema.org/draft-07/schema#","type":"object","properties":{"taskId":{"description":"The _id of the task to update. If multiple timeboxed events are present you must update the duration of the associated event instead.","type":"string"},"subtaskId":{"description":"The _id of the subtask to update. If not provided, the time estimate will be updated for the entire task. If the task has any subtasks with planned time, you must provide a subtaskId since the time estimate for the task will be calculated based on the subtasks.","type":"string"},"timeEstimate":{"description":"The new time estimate in minutes.","type":"number"}},"required":["taskId","timeEstimate"]},"execution":{"taskSupport":"forbidden"}},{"name":"append_task_notes","description":"Appends markdown notes to an existing task.","inputSchema":{"$schema":"http://json-schema.org/draft-07/schema#","type":"object","properties":{"taskId":{"description":"The ID of the task to update.","type":"string"},"notes":{"description":"The markdown notes to append to the task.","type":"string"}},"required":["taskId","notes"]},"execution":{"taskSupport":"forbidden"}},{"name":"delete_task","description":"Deletes an existing task.","inputSchema":{"$schema":"http://json-schema.org/draft-07/schema#","type":"object","properties":{"taskId":{"description":"The _id of the task to delete.","type":"string"}},"required":["taskId"]},"annotations":{"title":"Delete A Task","destructiveHint":true},"execution":{"taskSupport":"forbidden"}},{"name":"add_subtasks_to_task","description":"Adds multiple subtasks to an existing task.","inputSchema":{"$schema":"http://json-schema.org/draft-07/schema#","type":"object","properties":{"taskId":{"description":"The _id of the task to add the subtask to.","type":"string"},"subtasks":{"description":"The subtasks to add to the task.","type":"array","items":{"type":"object","properties":{"title":{"description":"The title of the subtask.","type":"string"},"timeEstimate":{"description":"The estimated time in minutes for the subtask.","type":"number"}},"required":["title"]}}},"required":["taskId","subtasks"]},"execution":{"taskSupport":"forbidden"}},{"name":"restore_task","description":"Changes a task from deleted to not deleted.","inputSchema":{"$schema":"http://json-schema.org/draft-07/schema#","type":"object","properties":{"taskId":{"description":"The _id of the task to mark as not deleted.","type":"string"}},"required":["taskId"]},"execution":{"taskSupport":"forbidden"}},{"name":"mark_task_as_completed","description":"Marks a task as completed. Can also be used to move a task to a previous day which auto-completes the task.","inputSchema":{"$schema":"http://json-schema.org/draft-07/schema#","type":"object","properties":{"taskId":{"description":"The _id of the task to mark as completed.","type":"string"},"finishedDay":{"description":"A date in YYYY-MM-DD the task was completed.","type":"string"}},"required":["taskId","finishedDay"]},"execution":{"taskSupport":"forbidden"}},{"name":"mark_task_as_incomplete","description":"Marks a task as incomplete.","inputSchema":{"$schema":"http://json-schema.org/draft-07/schema#","type":"object","properties":{"taskId":{"description":"The _id of a completed task we want to mark as incomplete or \"to do\" again.","type":"string"}},"required":["taskId"]},"execution":{"taskSupport":"forbidden"}},{"name":"edit_subtask_title","description":"Updates the title of an existing subtask.","inputSchema":{"$schema":"http://json-schema.org/draft-07/schema#","type":"object","properties":{"taskId":{"description":"The _id of the parent task.","type":"string"},"subtaskId":{"description":"The _id of the subtask to update.","type":"string"},"newTitle":{"description":"The new title for the subtask.","type":"string"}},"required":["taskId","subtaskId","newTitle"]},"execution":{"taskSupport":"forbidden"}},{"name":"mark_subtask_as_completed","description":"Marks a subtask of an existing task as completed.","inputSchema":{"$schema":"http://json-schema.org/draft-07/schema#","type":"object","properties":{"taskId":{"description":"The _id of the parent task.","type":"string"},"subtaskId":{"description":"The _id of the subtask to mark as completed.","type":"string"}},"required":["taskId","subtaskId"]},"execution":{"taskSupport":"forbidden"}},{"name":"mark_subtask_as_incomplete","description":"Marks a subtask of an existing task as incomplete.","inputSchema":{"$schema":"http://json-schema.org/draft-07/schema#","type":"object","properties":{"taskId":{"description":"The _id of the parent task.","type":"string"},"subtaskId":{"description":"The _id of the subtask to mark as incomplete.","type":"string"}},"required":["taskId","subtaskId"]},"execution":{"taskSupport":"forbidden"}},{"name":"reorder_tasks","description":"Reorders tasks for the calendar day according to the provided order of taskIds.","inputSchema":{"$schema":"http://json-schema.org/draft-07/schema#","type":"object","properties":{"taskIds":{"description":"The _id(s) of the task(s) in the order they should appear.","type":"array","items":{"type":"string"}},"calendarDay":{"description":"The date to reorder tasks for in YYYY-MM-DD format.","type":"string"}},"required":["taskIds","calendarDay"]},"execution":{"taskSupport":"forbidden"}},{"name":"get_backlog_tasks","description":"Fetches the users backlog tasks","inputSchema":{"$schema":"http://json-schema.org/draft-07/schema#","type":"object","properties":{"page":{"default":0,"description":"The page number to fetch (0-based)","type":"number"},"queryId":{"description":"All pages > 0 must pass in the queryId from the first page.","type":"string"}}},"execution":{"taskSupport":"forbidden"}},{"name":"get_archived_tasks","description":"Fetches the users archived tasks","inputSchema":{"$schema":"http://json-schema.org/draft-07/schema#","type":"object","properties":{"offset":{"default":0,"description":"The offset to fetch from","type":"number"}}},"execution":{"taskSupport":"forbidden"}},{"name":"search_tasks","description":"Searches for tasks. Returns tasks that match the search term or are similar to the search term.","inputSchema":{"$schema":"http://json-schema.org/draft-07/schema#","type":"object","properties":{"searchTerm":{"description":"The search term to look for in task titles, notes, and comments","type":"string"}},"required":["searchTerm"]},"execution":{"taskSupport":"forbidden"}},{"name":"update_all_incomplete_recurring_task_instances","description":"Updates all incomplete instances of a recurring task to match the current task. This is useful when you want to apply changes made to one instance of a recurring task to all future incomplete instances.","inputSchema":{"$schema":"http://json-schema.org/draft-07/schema#","type":"object","properties":{"taskId":{"description":"The _id of the recurring task to update all incomplete instances for.","type":"string"},"updateType":{"default":"allIncomplete","description":"The type of update to perform. \"allIncomplete\" updates all incomplete instances starting from today, \"allAfterThisTask\" updates all incomplete instances starting after the date of the task given by taskId.","type":"string","enum":["allIncomplete","allAfterThisTask"]}},"required":["taskId"]},"execution":{"taskSupport":"forbidden"}},{"name":"delete_all_incomplete_recurring_task_instances","description":"Deletes all incomplete instances of a recurring task.","inputSchema":{"$schema":"http://json-schema.org/draft-07/schema#","type":"object","properties":{"taskId":{"description":"The _id of the recurring task to delete all incomplete instances for.","type":"string"}},"required":["taskId"]},"execution":{"taskSupport":"forbidden"}},{"name":"start_task_timer","description":"Starts the timer for a task or subtask. If a subtaskId is provided, starts the timer for that specific subtask.","inputSchema":{"$schema":"http://json-schema.org/draft-07/schema#","type":"object","properties":{"taskId":{"description":"The _id of the task to start the timer for.","type":"string"},"subtaskId":{"description":"The _id of the subtask to start the timer for. If not provided, starts the timer for the entire task.","type":"string"}},"required":["taskId"]},"execution":{"taskSupport":"forbidden"}},{"name":"stop_task_timer","description":"Stops the timer for a task or subtask. If a subtaskId is provided, stops the timer for that specific subtask.","inputSchema":{"$schema":"http://json-schema.org/draft-07/schema#","type":"object","properties":{"taskId":{"description":"The _id of the task to stop the timer for.","type":"string"},"subtaskId":{"description":"The _id of the subtask to stop the timer for. If not provided, stops the timer for the entire task.","type":"string"}},"required":["taskId"]},"execution":{"taskSupport":"forbidden"}},{"name":"move_calendar_event","description":"Updates a calendar event's date, time, and/or duration.","inputSchema":{"$schema":"http://json-schema.org/draft-07/schema#","type":"object","properties":{"eventId":{"description":"The unique ID of the calendar event to move. IMPORTANT: user must have owner or writer access to the event.","type":"string"},"startDate":{"description":"The target start date to move the event to, in YYYY-MM-DD format.","type":"string"},"startTime":{"description":"The target start time to move the event to, in 12 hour \"h:mm A\" format. Required if the event is not all day.","type":"string"},"duration":{"description":"The duration of the event in minutes. Required if the event is not all day","type":"number"},"isAllDay":{"description":"Whether the event is all day.","type":"boolean"}},"required":["eventId","startDate","isAllDay"]},"execution":{"taskSupport":"forbidden"}},{"name":"create_calendar_event","description":"Creates a new calendar event.","inputSchema":{"$schema":"http://json-schema.org/draft-07/schema#","type":"object","properties":{"title":{"description":"The title of the calendar event.","type":"string"},"startDate":{"description":"The start date of the event in YYYY-MM-DD format. If this is in the past you must confirm with the user that you are creating a past event.","type":"string"},"startTime":{"description":"The start time of the event in 12 hour \"h:mm A\" format. Required if the event is not all day. If this is in the past you must confirm with the user that you are creating a past event.","type":"string"},"duration":{"default":60,"description":"The duration of the event in minutes. Required if the event is not all day","type":"number"},"isAllDay":{"default":false,"description":"Whether the event is all day.","type":"boolean"},"description":{"description":"Optional description of the event.","type":"string"},"calendarId":{"description":"The ID of the calendar to create the event in. If not provided, the default calendar will be used. IMPORTANT: user must have owner or writer access to the calendar.","type":"string"}},"required":["title","startDate"]},"execution":{"taskSupport":"forbidden"}},{"name":"timebox_a_task_to_calendar","description":"Timeboxes a task to the calendar. This will create a timebox event for the task. This may also be referred to as \"scheduling\" a task or \"adding a task to the calendar\".","inputSchema":{"$schema":"http://json-schema.org/draft-07/schema#","type":"object","properties":{"taskId":{"description":"The _id of the task to timebox.","type":"string"},"startDate":{"description":"The start date of the event in YYYY-MM-DD format. If this is in the past you must confirm with the user that you are timeboxing a past task.","type":"string"},"startTime":{"description":"The start time of the event in 12 hour \"h:mm A\" format. If this is in the past you must confirm with the user that you are timeboxing a past task.","type":"string"},"duration":{"description":"The duration of the event in minutes. If not provided the timeEstimate of the task will be used or 30 minutes if the task has no time estimate.","type":"number"}},"required":["taskId","startDate","startTime"]},"execution":{"taskSupport":"forbidden"}},{"name":"delete_calendar_event","description":"Removes a calendar event and deletes all associated tasks. If the event is a meeting then any access role can remove the event. Otherwise only owners or writers can remove the event. Note: If the event is a meeting and the user is an owner or write this will remove the event for ALL attendees.","inputSchema":{"$schema":"http://json-schema.org/draft-07/schema#","type":"object","properties":{"eventId":{"description":"The unique ID of the calendar event to remove.","type":"string"}},"required":["eventId"]},"annotations":{"title":"Removes A Calendar Event","destructiveHint":true},"execution":{"taskSupport":"forbidden"}},{"name":"import_task_from_calendar_event","description":"Imports a calendar event as a task.","inputSchema":{"$schema":"http://json-schema.org/draft-07/schema#","type":"object","properties":{"eventId":{"description":"The unique ID of the calendar event to import as a task.","type":"string"}},"required":["eventId"]},"execution":{"taskSupport":"forbidden"}},{"name":"accept_meeting_invite","description":"Confirms attendance to a meeting that the user is invited to.","inputSchema":{"$schema":"http://json-schema.org/draft-07/schema#","type":"object","properties":{"eventId":{"description":"The unique ID of the calendar event to accept the meeting invite for.","type":"string"}},"required":["eventId"]},"execution":{"taskSupport":"forbidden"}},{"name":"decline_meeting_invite","description":"Decline attendance to a meeting that the user is invited to.","inputSchema":{"$schema":"http://json-schema.org/draft-07/schema#","type":"object","properties":{"eventId":{"description":"The unique ID of the calendar event to decline the meeting invite for.","type":"string"}},"required":["eventId"]},"execution":{"taskSupport":"forbidden"}},{"name":"set_calendar_event_allow_task_projections","description":"Sets whether tasks are allowed to be automatically projected (scheduled) at the same time as a calendar event. When set to true, tasks can be automatically projected during the event. When set to false, tasks cannot be automatically projected during the event. Note: This only affects automatic projections; users can still manually timebox tasks during this event.","inputSchema":{"$schema":"http://json-schema.org/draft-07/schema#","type":"object","properties":{"eventId":{"description":"The unique ID of the calendar event to set task projection settings for.","type":"string"},"allowTasksProjectedAtSameTime":{"description":"If true, allows tasks to be automatically projected at the same time as this event. If false, blocks tasks from being automatically projected at the same time as this event. Note: This only affects automatic projections; manual timeboxing is not affected.","type":"boolean"}},"required":["eventId","allowTasksProjectedAtSameTime"]},"execution":{"taskSupport":"forbidden"}},{"name":"toggle_auto_import_events","description":"Enables or disables automatic importing of calendar events to the daily task list.","inputSchema":{"$schema":"http://json-schema.org/draft-07/schema#","type":"object","properties":{"enabled":{"description":"Whether to enable (true) or disable (false) automatic importing of calendar events.","type":"boolean"}},"required":["enabled"]},"execution":{"taskSupport":"forbidden"}},{"name":"update_import_event_filters","description":"Updates the exclusion filters that determine which calendar events are excluded from automatic import. Events matching any of these filters will NOT be automatically imported.","inputSchema":{"$schema":"http://json-schema.org/draft-07/schema#","type":"object","properties":{"excludedEventFilters":{"description":"An array of exclusion filter types. Events matching any of these filters will be EXCLUDED from auto-import. Available filters: \"solo\" (events with no other invitees), \"transparent\" (non-blocking events), \"hold\" (events with HOLD/OOO/Focus time in title), \"unconfirmed\" (unconfirmed meeting invites), \"multi-day-all-day\" (multi-day all-day events), \"single-day-all-day\" (single-day all-day events).","type":"array","items":{"type":"string","enum":["solo","transparent","hold","unconfirmed","multi-day-all-day","single-day-all-day"]}}},"required":["excludedEventFilters"]},"execution":{"taskSupport":"forbidden"}},{"name":"update_calendar_preferences","description":"Updates preferences for a specific calendar including whether it is the default for tasks, default for events, and whether it is included in auto-importing of events.","inputSchema":{"$schema":"http://json-schema.org/draft-07/schema#","type":"object","properties":{"calendarId":{"description":"The ID of the calendar to update preferences for.","type":"string"},"isDefaultForTasks":{"description":"Whether this calendar should be the default calendar for timeboxing tasks. If not provided, this preference will not be changed.","type":"boolean"},"isDefaultForEvents":{"description":"Whether this calendar should be the default calendar for scheduling events. If not provided, this preference will not be changed.","type":"boolean"},"includedInAutoImportingOfEvents":{"description":"Whether this calendar should be included in automatic importing of calendar events. If not provided, this preference will not be changed.","type":"boolean"}},"required":["calendarId"]},"execution":{"taskSupport":"forbidden"}},{"name":"delete_email_thread","description":"Deletes an email thread from Gmail or Outlook.","inputSchema":{"$schema":"http://json-schema.org/draft-07/schema#","type":"object","properties":{"accountId":{"description":"The ID of the email account you are looking at.","type":"string"},"accountService":{"description":"This is either \"outlook\" or \"gmail\", depending on the email provider.","type":"string"},"threadId":{"description":"The ID of the thread to delete.","type":"string"}},"required":["accountId","accountService","threadId"]},"execution":{"taskSupport":"forbidden"}},{"name":"mark_email_thread_as_read","description":"Marks an email thread as read.","inputSchema":{"$schema":"http://json-schema.org/draft-07/schema#","type":"object","properties":{"accountId":{"description":"The ID of the email account.","type":"string"},"accountService":{"description":"This is either \"outlook\" or \"gmail\".","type":"string"},"threadId":{"description":"The ID of the thread to mark as read.","type":"string"}},"required":["accountId","accountService","threadId"]},"execution":{"taskSupport":"forbidden"}},{"name":"create_follow_up_task_from_email","description":"Turn the email thread into a task to be followed up with later.","inputSchema":{"$schema":"http://json-schema.org/draft-07/schema#","type":"object","properties":{"accountId":{"description":"The ID of the email account you are looking at.","type":"string"},"accountService":{"description":"This is either \"outlook\" or \"gmail\", depending on the result of list_email_accounts.","type":"string"},"threadId":{"description":"The ID of the thread to mark as read.","type":"string"},"notes":{"description":"Any notes the user mentioned about the task/email.","type":"string"},"timeEstimate":{"description":"The estimated time in minutes for the task.","type":"number"}},"required":["accountId","accountService","threadId"]},"execution":{"taskSupport":"forbidden"}},{"name":"list_email_threads","description":"Lists email threads for a given Gmail account. You MUST specify at least a `labels` or a `search` parameter to avoid fetching irrelevant emails.","inputSchema":{"$schema":"http://json-schema.org/draft-07/schema#","type":"object","properties":{"accountId":{"description":"The ID of the email account to list threads from.","type":"string"},"labels":{"description":"Optional list of Gmail labels to filter by, e.g., [\"INBOX\", \"IMPORTANT\"]","type":"array","items":{"type":"string"}},"search":{"description":"Optional Gmail search query. Example: `after:2025-04-01 before:2025-04-17` or `is:unread`.","type":"string"},"pageToken":{"description":"Optional token for paginating through results.","type":"string"}},"required":["accountId"]},"execution":{"taskSupport":"forbidden"}},{"name":"create_weekly_objective","description":"Creates a new weekly objective.","inputSchema":{"$schema":"http://json-schema.org/draft-07/schema#","type":"object","properties":{"title":{"description":"The title of the weekly objective.","type":"string"},"weekStartDay":{"description":"The start day of the week in YYYY-MM-DD format.","type":"string"},"timeEstimate":{"description":"The estimated time in minutes for the objective.","type":"number"},"channel":{"description":"The channel name to associate with the objective. This does not need to be perfect. The closest match will be used.","type":"string"}},"required":["title","weekStartDay"]},"execution":{"taskSupport":"forbidden"}},{"name":"send_call_summary","description":"Sends a summary of our call via email.","inputSchema":{"$schema":"http://json-schema.org/draft-07/schema#","type":"object","properties":{"summaryIntroduction":{"description":"A short introduction to the summary. This will be used as the first line of the summary email.\nExample:\nHere is the summary of our call for today June 25th, 2025:\n","type":"string"},"summaryHighlights":{"description":"A list of highlights from the call. This will be used as the second line of the summary email.\nExample:\n- You planned your day focusing on refining the voice assistant.\n- Created a weekly objective for this goal.\n- Added key backlog tasks: refining the NLU model, bug fixes, API documentation, and unit tests.\n- You scheduled a sync with Diane at 2:30 PM.\n- You set a planned shutdown time of 5 PM.\n","type":"array","items":{"type":"string"}},"summaryFooter":{"description":"A short footer to the summary. This will be used as the last line of the summary email.\n \nExample:\nThis plan keeps your day focused, balanced, and aligned with your objectives.\n","type":"string"}}},"execution":{"taskSupport":"forbidden"}},{"name":"log_user_feedback","description":"Logs user feedback.","inputSchema":{"$schema":"http://json-schema.org/draft-07/schema#","type":"object","properties":{"feedback":{"description":"A summary of the feedback you want to log.","type":"string"},"transcript":{"description":"A transcript of the exact feedback you want to log.","type":"string"},"bugReports":{"description":"A list of bugs you want to report.","type":"array","items":{"type":"object","properties":{"bug":{"description":"The bug you want to report.","type":"string"},"description":{"description":"A detailed description of the bug.","type":"string"}},"required":["bug"]}},"featureRequests":{"description":"A list of feature requests you want to log.","type":"array","items":{"type":"object","properties":{"feature":{"description":"The feature you want to request.","type":"string"},"description":{"description":"A detailed description of the feature.","type":"string"}},"required":["feature"]}}},"required":["feedback"]},"execution":{"taskSupport":"forbidden"}},{"name":"set_shutdown_time","description":"Sets the shutdown time for a specific day.","inputSchema":{"$schema":"http://json-schema.org/draft-07/schema#","type":"object","properties":{"calendarDay":{"description":"The day to set the shutdown time for, in YYYY-MM-DD format.","type":"string"},"hour":{"description":"Hour of the shutdown time (0-23)","type":"number"},"minute":{"description":"Minute of the shutdown time (0-59)","type":"number"},"addToTheCalendar":{"description":"Whether to create a shutdown task and calendar event for the day.","default":false,"type":"boolean"}},"required":["calendarDay","hour","minute"]},"execution":{"taskSupport":"forbidden"}},{"name":"adjust_call_schedule","description":"Adjusts the schedule for voice assistant phone calls. Only one call per day is supported. Updating the schedule will reset the next call time to the next available time after today.","inputSchema":{"$schema":"http://json-schema.org/draft-07/schema#","type":"object","properties":{"daySchedules":{"type":"array","items":{"type":"object","properties":{"isoDayIndex":{"description":"ISO weekday number (1=Monday, 7=Sunday)","type":"number","minimum":1,"maximum":7},"enabled":{"default":true,"description":"Whether calls should be enabled on this day","type":"boolean"},"hour":{"description":"The hour to set the call time to (0-23). If not provided the old value will be used.","type":"number","minimum":0,"maximum":23},"minute":{"description":"The minute for the next call (00, 15, 30, 45). If not provided the old value will be used.","type":"string","enum":["15","30","45","00"]}},"required":["isoDayIndex"]}}}},"execution":{"taskSupport":"forbidden"}},{"name":"schedule_next_call","description":"Schedules the next phone call at a specific date and time. This will skip all other scheduled calls until this one. Useful for temporarily disabling calls for a few days or scheduling a call back in the short term.","inputSchema":{"$schema":"http://json-schema.org/draft-07/schema#","type":"object","properties":{"nextCallDate":{"description":"The date for the next call in YYYY-MM-DD format.","type":"string"},"hour":{"description":"The hour for the next call (0-23).","type":"number"},"minute":{"description":"The minute for the next call (00, 15, 30, 45).","type":"string","enum":["15","30","45","00"]}},"required":["nextCallDate","hour","minute"]},"execution":{"taskSupport":"forbidden"}},{"name":"create_channel","description":"Creates a new channel for the user.","inputSchema":{"$schema":"http://json-schema.org/draft-07/schema#","type":"object","properties":{"channelName":{"description":"The name of the channel to create.","type":"string"},"categoryName":{"description":"The name of the category this should belong to. If not provided one will be assigned automatically.","type":"string"},"isPersonal":{"default":false,"description":"Whether the channel is a personal channel. If not provided it will be assumed to be a work channel. This option is ignored if a category name is provided.","type":"boolean"}},"required":["channelName"]},"execution":{"taskSupport":"forbidden"}},{"name":"complete_onboarding_guide","description":"Completes the onboarding guide for the user.","inputSchema":{"$schema":"http://json-schema.org/draft-07/schema#","type":"object","properties":{"dayPlanned":{"description":"The day the user planned during their onboarding guide. In YYYY-MM-DD format.","type":"string"}},"required":["dayPlanned"]},"execution":{"taskSupport":"forbidden"}},{"name":"trigger_user_interface_action","description":"Triggers an action in the user interface that the user is currently looking at. Using one of the actionIds from the get_available_ui_actions resource. YOU ABSOLUTELY MUST ONLY USE actionIds from the latest call to get_available_ui_actions. All other actionIds are invalid and will not work.\n - Navigation type actions: Navigate to a specific location in the user interface.\n - Highlight type actions: Highlight an element in the user interface to make it easy for the user to find it.","inputSchema":{"$schema":"http://json-schema.org/draft-07/schema#","type":"object","properties":{"actionId":{"description":"The action ID for a user interface action to trigger. Use the get_available_ui_actions resource to see what user interface actions are currently available.","type":"string"},"params":{"description":"Optional parameters for the navigation. As given by the get_available_ui_actions resource for the specific action.","type":"object","propertyNames":{"type":"string"},"additionalProperties":{}}},"required":["actionId"]},"execution":{"taskSupport":"forbidden"}}]},"jsonrpc":"2.0","id":4} -[voice] INFO:sunsama_voice.mcp_websocket_client:Sending message: {'method': 'resources/templates/list', 'jsonrpc': '2.0', 'id': 5} -[voice] INFO:sunsama_voice.mcp_websocket_client:Received message: {"result":{"resourceTemplates":[{"name":"get_tasks_for_day","uriTemplate":"sunsama://tasks/{calendarDay}","description":"Gets all the tasks already created for the user for the day.","mimeType":"application/json"},{"name":"get_total_planned_time","uriTemplate":"sunsama://total-planned-time/{calendarDay}","description":"Retrieves the total planned time for the user for a given calendar day. This includes the total planned work time, the total planned personal time and the estimated earliest possible shutdown time.","mimeType":"application/json"},{"name":"get_calendar_events_for_day","uriTemplate":"sunsama://calendar/events/{calendarDay}","description":"Retrieves calendar events for a specific date","mimeType":"application/json"},{"name":"get_weekly_objectives","uriTemplate":"sunsama://objectives{/calendarDay}","description":"Retrieves the user's weekly objectives. If calendarDay is provided, returns objectives for that week. If not provided, returns objectives for the current week.","mimeType":"application/json"}]},"jsonrpc":"2.0","id":5} -[voice] INFO:sunsama_voice.mcp:Subscribed to resource sunsama://me with args: {} -[voice] INFO:sunsama_voice.mcp_websocket_client:Sending message: {'method': 'resources/subscribe', 'params': {'uri': 'sunsama://me'}, 'jsonrpc': '2.0', 'id': 6} -[api-local] [api] -[api-local] [api] -[api-local] [api] -[api-local] [api] Subscribing to resource { uri: 'sunsama://me' } { -[api-local] [api] signal: AbortSignal { aborted: false }, -[api-local] [api] sessionId: '64832d8f-2289-4bf4-8f8b-0452890bb28f', -[api-local] [api] _meta: undefined, -[api-local] [api] sendNotification: [AsyncFunction: sendNotification], -[api-local] [api] sendRequest: [AsyncFunction: sendRequest], -[api-local] [api] authInfo: { -[api-local] [api] token: 'eyJhbGciOiJIUzI1NiIsInR5cCI6IkpXVCJ9.eyJ1c2VySWQiOiI2NzFhYzVlNDAyYTMwMmNmNmVmMzA4OGUiLCJzZXNzaW9uSWQiOiIxOTVmNDI0NC05YjFmLTRlYmItOTMwZC0wZTExNTAwNzZkYzkiLCJzZXNzaW9uTm9uY2UiOiJhY2ZlZTc2OS1jZGU2LTRkMWYtYTU5Ni0xMzk0MTRkMjUxNjAiLCJncm91cElkIjoiNjcxYWM1ZTkwMmEzMDJjZjZlZjMwODkwIiwiZ3JvdXBVcmxQYXRoIjoiMTcyOTgwNzg0OTAzNjUxOTIiLCJpYXQiOjE3Njg1OTAyMTYsImV4cCI6MTc3MTE4MjIxNn0.HHSuewYqBRl-IZkdiWcEJyiD6akgbtwnOIQ4Js71bZI', -[api-local] [api] clientId: '195f4244-9b1f-4ebb-930d-0e1150076dc9', -[api-local] [api] scopes: [], -[api-local] [api] extra: { -[api-local] [api] request: [Object], -[api-local] [api] response: [Object], -[api-local] [api] app: [Object], -[api-local] [api] originalUrl: '/ai/mcp', -[api-local] [api] req: '', -[api-local] [api] res: '', -[api-local] [api] socket: '' -[api-local] [api] } -[api-local] [api] }, -[api-local] [api] requestId: 6, -[api-local] [api] requestInfo: undefined, -[api-local] [api] taskId: undefined, -[api-local] [api] taskStore: undefined, -[api-local] [api] taskRequestedTtl: undefined, -[api-local] [api] closeSSEStream: undefined, -[api-local] [api] closeStandaloneSSEStream: undefined -[api-local] [api] } -[api-local] [api] Registered handler for channel "user-updates-671ac5e402a302cf6ef3088e" for event "userUpdated" -[voice] INFO:sunsama_voice.mcp_websocket_client:Received message: {"result":{"success":true},"jsonrpc":"2.0","id":6} -[voice] INFO:sunsama_voice.mcp:Resources: ['get_user_authentication_status', 'get_user_info', 'list_email_accounts', 'get_last_daily_highlight', 'get_backlog_folders', 'get_active_timer', 'get_available_ui_actions'] get_backlog_folders -[voice] INFO:sunsama_voice.mcp:Subscribed to resource sunsama://backlog/folders with args: {} -[voice] INFO:sunsama_voice.mcp_websocket_client:Sending message: {'method': 'resources/subscribe', 'params': {'uri': 'sunsama://backlog/folders'}, 'jsonrpc': '2.0', 'id': 7} -[api-local] [api] -[api-local] [api] -[api-local] [api] -[api-local] [api] Subscribing to resource { uri: 'sunsama://backlog/folders' } { -[api-local] [api] signal: AbortSignal { aborted: false }, -[api-local] [api] sessionId: '64832d8f-2289-4bf4-8f8b-0452890bb28f', -[api-local] [api] _meta: undefined, -[api-local] [api] sendNotification: [AsyncFunction: sendNotification], -[api-local] [api] sendRequest: [AsyncFunction: sendRequest], -[api-local] [api] authInfo: { -[api-local] [api] token: 'eyJhbGciOiJIUzI1NiIsInR5cCI6IkpXVCJ9.eyJ1c2VySWQiOiI2NzFhYzVlNDAyYTMwMmNmNmVmMzA4OGUiLCJzZXNzaW9uSWQiOiIxOTVmNDI0NC05YjFmLTRlYmItOTMwZC0wZTExNTAwNzZkYzkiLCJzZXNzaW9uTm9uY2UiOiJhY2ZlZTc2OS1jZGU2LTRkMWYtYTU5Ni0xMzk0MTRkMjUxNjAiLCJncm91cElkIjoiNjcxYWM1ZTkwMmEzMDJjZjZlZjMwODkwIiwiZ3JvdXBVcmxQYXRoIjoiMTcyOTgwNzg0OTAzNjUxOTIiLCJpYXQiOjE3Njg1OTAyMTYsImV4cCI6MTc3MTE4MjIxNn0.HHSuewYqBRl-IZkdiWcEJyiD6akgbtwnOIQ4Js71bZI', -[api-local] [api] clientId: '195f4244-9b1f-4ebb-930d-0e1150076dc9', -[api-local] [api] scopes: [], -[api-local] [api] extra: { -[api-local] [api] request: [Object], -[api-local] [api] response: [Object], -[api-local] [api] app: [Object], -[api-local] [api] originalUrl: '/ai/mcp', -[api-local] [api] req: '', -[api-local] [api] res: '', -[api-local] [api] socket: '' -[api-local] [api] } -[api-local] [api] }, -[api-local] [api] requestId: 7, -[api-local] [api] requestInfo: undefined, -[api-local] [api] taskId: undefined, -[api-local] [api] taskStore: undefined, -[api-local] [api] taskRequestedTtl: undefined, -[api-local] [api] closeSSEStream: undefined, -[api-local] [api] closeStandaloneSSEStream: undefined -[api-local] [api] } -[api-local] [api] Registered handler for channel "backlog-folder-updates-671ac5e902a302cf6ef30890-671ac5e402a302cf6ef3088e" for event "folderUpdated" -[voice] INFO:sunsama_voice.mcp_websocket_client:Received message: {"result":{"success":true},"jsonrpc":"2.0","id":7} -[voice] INFO:sunsama_voice.bot:Timer: Flow config created in 0.19129395484924316 seconds -[voice] DEBUG:pipecat_flows.actions:Registered handler for action type: tts_say -[voice] DEBUG:pipecat_flows.actions:Registered handler for action type: end_conversation -[voice] DEBUG:pipecat_flows.actions:Registered handler for action type: function -[voice] DEBUG:pipecat_flows.adapters:Creating Google adapter -[voice] DEBUG:pipecat_flows.manager:Initialized in static mode -[voice] DEBUG:sunsama_voice.bot:no dialout number; assuming dialin -[voice] INFO:sunsama_voice.bot:Starting the pipeline -[voice] INFO:sunsama_voice.bot:Timer: Pipeline started in 0.19174408912658691 seconds -[voice] DEBUG:pipecat.pipeline.runner:Runner PipelineRunner#0 started running PipelineTask#0 -[voice] DEBUG:pipecat.pipeline.task:PipelineTask#0: Starting. Waiting for StartFrame#0 to reach the end of the pipeline... -[voice] DEBUG:pipecat.audio.vad.vad_analyzer:Setting VAD params to: confidence=0.7 start_secs=0.2 stop_secs=0.2 min_volume=0.6 -[voice] INFO:pipecat.transports.daily.transport:Joining https://cloud-99400c183d52498c940fe96f45c05b44.daily.co/teWpRxCQnkMHYi7Q3lqh -[voice] DEBUG:pipecat.services.cartesia.tts:Connecting to Cartesia TTS -[voice] DEBUG:pipecat.pipeline.task:PipelineTask#0: StartFrame#0 reached the end of the pipeline, pipeline is now ready. -[voice] ERROR:pipecat.transports.daily.transport:Unable to send message: Unable to send messages before joining. -[voice] INFO:pipecat.transports.daily.transport:Joined https://cloud-99400c183d52498c940fe96f45c05b44.daily.co/teWpRxCQnkMHYi7Q3lqh -[voice] DEBUG:pipecat.transports.daily.transport:Starting transcription: settings=language='en' model='nova-3' profanity_filter=True redact=False endpointing=True punctuate=True includeRawResponse=True extra={'interim_results': True} -[voice] DEBUG:pipecat.transports.daily.transport:Transcription started: {'instanceId': 'a1f2f6b7-b1ac-4202-85e5-d446cb6c3d3f', 'language': 'en', 'model': 'nova-3', 'startedBy': '0106bd40-d21f-4da2-8518-3c3c4997b2ae', 'transcriptId': 'e1c71759-439e-492b-92fd-3d5344c2492f'} -[voice] DEBUG:pipecat.transports.daily.transport:Start receiving audio -[voice] INFO:pipecat.transports.daily.transport:Participant joined 941aacac-ae67-454d-86a1-65308278e261 -[voice] DEBUG:pipecat.transports.daily.transport:Starting to capture [microphone] audio from participant 941aacac-ae67-454d-86a1-65308278e261 -[voice] INFO:sunsama_voice.bot:First participant joined: {'id': '941aacac-ae67-454d-86a1-65308278e261', 'info': {'isLocal': False, 'isOwner': True, 'joinedAt': 1768590245, 'permissions': {'canAdmin': ['participants', 'transcription', 'streaming'], 'canReceive': {'base': {'camera': True, 'customAudio': {'*': True}, 'customVideo': {'*': True}, 'microphone': True, 'screenAudio': True, 'screenVideo': True}}, 'canSend': ['customAudio', 'camera', 'microphone', 'customVideo', 'screenAudio', 'screenVideo'], 'hasPresence': True}}, 'media': {'camera': {'offReasons': ['user'], 'state': 'off', 'subscribed': 'unsubscribed'}, 'customAudio': {}, 'customVideo': {}, 'microphone': {'state': 'loading', 'subscribed': 'subscribed'}, 'screenAudio': {'offReasons': ['user'], 'state': 'off', 'subscribed': 'subscribed'}, 'screenVideo': {'offReasons': ['user'], 'state': 'off', 'subscribed': 'unsubscribed'}}} -[voice] DEBUG:pipecat.processors.frameworks.rtvi:Received client-ready: version 1.0.0 -[voice] DEBUG:pipecat.processors.frameworks.rtvi:Client Details: library='@pipecat-ai/client-js' library_version='1.2.0' platform='macOS' platform_version='10.15.7' platform_details={'browser': 'Chrome', 'browser_version': '143.0.0.0', 'engine': 'Blink', 'platform_type': 'desktop'} -[voice] INFO:sunsama_voice.bot:Starting an in-app call -[voice] INFO:sunsama_voice.bot:Timer: Dialin/in-app call started in 1.073638916015625 seconds -[voice] DEBUG:pipecat_flows.manager:Initialized FlowManager -[voice] DEBUG:pipecat_flows.manager:Setting initial node: braindump -[voice] /Users/zanemccaig/workspaces/sunsama/sunsama/sunsama-voice/venv/lib/python3.13/site-packages/pipecat_flows/manager.py:768: DeprecationWarning: `transition_to` and `transition_callback` are deprecated and will be removed in 1.0.0. Use a "consolidated" `handler` that returns a tuple (result, next_node) instead. -[voice] self._validate_node_config(node_id, node_config) -[voice] DEBUG:pipecat_flows.manager:Setting node: braindump -[voice] DEBUG:pipecat_flows.manager:Registered function: terminate_call -[voice] DEBUG:pipecat_flows.manager:Registered function: create_task -[voice] DEBUG:pipecat_flows.manager:Registered function: create_braindump_task -[voice] DEBUG:pipecat_flows.manager:Registered function: reposition_task_in_backlog -[voice] DEBUG:pipecat_flows.manager:Registered function: change_backlog_folder -[voice] DEBUG:pipecat_flows.manager:Registered function: align_task_with_objective -[voice] DEBUG:pipecat_flows.manager:Registered function: add_task_to_channel -[voice] DEBUG:pipecat_flows.manager:Registered function: move_task_to_day -[voice] DEBUG:pipecat_flows.manager:Registered function: move_task_from_backlog -[voice] DEBUG:pipecat_flows.manager:Registered function: unarchive_task -[voice] DEBUG:pipecat_flows.manager:Registered function: move_task_to_backlog -[voice] DEBUG:pipecat_flows.manager:Registered function: get_task_time_estimate -[voice] DEBUG:pipecat_flows.manager:Registered function: edit_task_recurrence_rule -[voice] DEBUG:pipecat_flows.manager:Registered function: edit_task_title -[voice] DEBUG:pipecat_flows.manager:Registered function: edit_task_time_estimate -[voice] DEBUG:pipecat_flows.manager:Registered function: delete_task -[voice] DEBUG:pipecat_flows.manager:Registered function: add_subtasks_to_task -[voice] DEBUG:pipecat_flows.manager:Registered function: restore_task -[voice] DEBUG:pipecat_flows.manager:Registered function: mark_task_as_completed -[voice] DEBUG:pipecat_flows.manager:Registered function: mark_task_as_incomplete -[voice] DEBUG:pipecat_flows.manager:Registered function: edit_subtask_title -[voice] DEBUG:pipecat_flows.manager:Registered function: mark_subtask_as_completed -[voice] DEBUG:pipecat_flows.manager:Registered function: mark_subtask_as_incomplete -[voice] DEBUG:pipecat_flows.manager:Registered function: reorder_tasks -[voice] DEBUG:pipecat_flows.manager:Registered function: get_backlog_tasks -[voice] DEBUG:pipecat_flows.manager:Registered function: get_archived_tasks -[voice] DEBUG:pipecat_flows.manager:Registered function: search_tasks -[voice] DEBUG:pipecat_flows.manager:Registered function: update_all_incomplete_recurring_task_instances -[voice] DEBUG:pipecat_flows.manager:Registered function: delete_all_incomplete_recurring_task_instances -[voice] DEBUG:pipecat_flows.manager:Registered function: start_task_timer -[voice] DEBUG:pipecat_flows.manager:Registered function: stop_task_timer -[voice] DEBUG:pipecat_flows.manager:Registered function: move_calendar_event -[voice] DEBUG:pipecat_flows.manager:Registered function: create_calendar_event -[voice] DEBUG:pipecat_flows.manager:Registered function: timebox_a_task_to_calendar -[voice] DEBUG:pipecat_flows.manager:Registered function: delete_calendar_event -[voice] DEBUG:pipecat_flows.manager:Registered function: import_task_from_calendar_event -[voice] DEBUG:pipecat_flows.manager:Registered function: accept_meeting_invite -[voice] DEBUG:pipecat_flows.manager:Registered function: decline_meeting_invite -[voice] DEBUG:pipecat_flows.manager:Registered function: set_calendar_event_allow_task_projections -[voice] DEBUG:pipecat_flows.manager:Registered function: toggle_auto_import_events -[voice] DEBUG:pipecat_flows.manager:Registered function: update_import_event_filters -[voice] DEBUG:pipecat_flows.manager:Registered function: update_calendar_preferences -[voice] DEBUG:pipecat_flows.manager:Registered function: create_weekly_objective -[voice] DEBUG:pipecat_flows.manager:Registered function: send_call_summary -[voice] DEBUG:pipecat_flows.manager:Registered function: log_user_feedback -[voice] DEBUG:pipecat_flows.manager:Registered function: set_shutdown_time -[voice] DEBUG:pipecat_flows.manager:Registered function: adjust_call_schedule -[voice] DEBUG:pipecat_flows.manager:Registered function: schedule_next_call -[voice] DEBUG:pipecat_flows.manager:Registered function: create_channel -[voice] DEBUG:pipecat_flows.manager:Registered function: get_user_info -[voice] DEBUG:pipecat_flows.manager:Registered function: get_last_daily_highlight -[voice] DEBUG:pipecat_flows.manager:Registered function: get_backlog_folders -[voice] DEBUG:pipecat_flows.manager:Registered function: get_active_timer -[voice] DEBUG:pipecat_flows.manager:Registered function: get_tasks_for_day -[voice] DEBUG:pipecat_flows.manager:Registered function: get_total_planned_time -[voice] DEBUG:pipecat_flows.manager:Registered function: get_calendar_events_for_day -[voice] DEBUG:pipecat_flows.manager:Registered function: get_weekly_objectives -[voice] DEBUG:pipecat_flows.manager:Updated LLM context using LLMMessagesUpdateFrame with strategy ContextStrategy.APPEND -[voice] DEBUG:pipecat_flows.manager:Updated LLM context -[voice] DEBUG:pipecat_flows.manager:Successfully set node: braindump -[voice] :4: DeprecationWarning: OpenAILLMContextFrame is deprecated and will be removed in a future version. Use LLMContextFrame with the universal `LLMContext` and `LLMContextAggregatorPair` instead. See OpenAILLMContext docstring for migration guide. -[voice] DEBUG:pipecat.services.google.llm:GoogleLLMService#0: Generating chat from LLM-specific context [None] | [{'parts': [{'text': 'system :\nYour agent ID is \'braindump\'. This agent ID superseeds any previously mentioned agent ID.\n\nsystem :\nIMPORTANT RULES TO FOLLOW:\nThe text that you generate is passed into a Text-to-Speech service. So there are a few extra rules you ABSOLUTELY MUST follow.\n1. Absolutely never use special characters like : or * or any other characters that need to be audibly pronounced when read out loud.\n2. Do not use bullet points.\n3. Do not use emojis.\n4. Do not use hashtags.\n5. Do not use markdown.\n6. Do not use bold or italics.\n7. Do not use numbered lists.\n8. Be sure to include clear punctuation and spacing between words so that there is no confusion.\n9. Newlines are not clear enough to delineate between sentences. So you should use a period to separate sentences.\n10. Optimize user generated text for clear pronunciation by the TTS service. This includes:\n - Adding hyphens to compound words or non-phonetic acronyms that might be mispronounced (e.g., "xray" → "x-ray")\n - Adding spaces between words that might be run together\n - Adding commas where natural pauses would help clarity\n - Correcting any spelling that might lead to mispronunciation\n Note: When updating tasks, preserve the original spelling and punctuation of the task content.\n\n\nuser :\nYou are Sunny, the personal assistant for a busy professional. You are part of Sunsama.\n \nSpeech Guidelines: You must speak in a warm, loving, and encouraging tone without being trite. Speak quickly and add emotion. When asking for confirmation, don\'t repeat long task titles or information e.g. "Got it" instead "Got it, I\'ll add a task for two hours for you to work on the presentation today"\n\nYour personality and philosophy:\n- You don\'t buy into hustle culture. For you, less is more. It\'s better to do fewer things well and to do them with deep focus. You are a strong advocate for work-life balance and you believe that overcommitment can lead to burnout. You always remind the user when they are overcommitting themselves.\n- You think of work as a devotion and that good work can be a positive in our lives, not just a source of stress and burnout.\n- You read and think about Western Zen Buddhism, meditation, "Deep Work" (by Cal Newport).\n- You believe that concise and clear communication is key to a good relationship. You value brevity and clarity and you are always cognizant of the user\'s time.\n- You respond to the user using quick, short sentences. Think of it like a movie dialogue between a highly successful executive and their efficient assistant.\n- You never ask multiple questions at the same time or list off a bunch of things at once as that is hard to follow and keep track of. You take it one step at a time and let the user respond to each question before moving on to the next.\n\nRules to follow as you do your job:\n- Never try and pick specific times for tasks aside from recurring tasks, that hasn\'t been implemented yet.\n- Do not regurgitate what the user just said, that\'s very annoying. Just say "Got it" or "Alright", etc.\n- Always use units that are more intuitive. For example:\n - Don\'t say "270 minutes", say "4 and a half hours".\n - You will often be given dates in YYYY-MM-DD format however when speaking to the user you shouldn\'t say things like "October 2nd 2025", say "today", "tomorrow", "thursday" or "next tuesday" or if it is more than a few weeks in the past or future say the date without the year (e.g. "December 14th"). Only mention the year if it is not this year and not within the next month.\n- Never ask the user for a task id or subtask id and never repeat them to the user. Those are internal and only there to help you do your job.\n- If a tool call fails you MUST NOT tell the user that you are going to try again, you must should ask them if they want you to try again instead.\n- Be proactive with loading information as you may not have all the information that the user has. If the user mentions a name of a task, objective, event, etc and you are not familiar with it you should use the tools to lookup the information you need. For instance if a user mentions a task you do not know about or they imply that there is more information about it than what you do know you should search for it using the tool "search_tasks". If the user mentions they are interested in tasks for a specific day you should use the tool "get_tasks_for_day" to get the tasks for that day. Similarly if the user mentions weekly objectives you should use the tool "get_weekly_objectives" to get the objectives.\n- When listing tasks try to be concise. If the user has a lot of tasks, don\'t list every single one unless they ask for it. You should instead try to summarize the tasks in a concise manner.\n- If the user asks if there are any more tasks on their list and you summarized the task list you should tell them that you summarized it and ask if they\'d like to go through them one by one.\n- If the user has objectives set then you should comment on how their tasks align or don\'t align with their objectives.\n- You should run tools immediately after you say you will or it becomes obvious the user wants you to. Do not wait until later.\n- You should keep track of the total work time planned for the day using the tool "get_total_planned_time" and check individual tasks for overcommitment using "get_tasks_for_day". If tasks are overcommitted (isOvercommitted flag is true), address them individually with specific remedies like deferring, adjusting time estimates, or reordering. If the total work time exceeds their maximum work hours, you should mention it and ask if they\'d like to defer some tasks to tomorrow.\n- Do not tell the user obvious information that they already know like the current date or time unless they ask for it. That kind of information is only provided to you to help you do your job.\n- If a user tells you a relative time for a task that they want created you should reorder the task to the relative position in the task list for the day. Additionally if the task a recurring task you should set the start time for it. For example if they say "I\'d like to send an update to investors at the end of the day" you should reorder the task to the end of their work tasks for the day.\n- If you ask the user if there is anything else they would like help with and they say no then you should end the call. Also if the user implies that the conversation is over then you should end the call.\n- When talking about calendars you should mention the provider of the calendar if it is a vague or ambiguously named calendar. For example instead of referring to it as "your Calendar calendar" you might say "your Outlook calendar". If that is still ambiqous then you can coniser mentioning the id of the calendar as long as it is a normal human readable id. Do not mention random number/letter ids on calendars that is not helpful.\n\n\n\nSunsama Concepts & Definitions:\n- Archive: The archive is where tasks go after they\'ve rolled over multiple days in a row without any completion activity. This is a distinct concept from the backlog or deleted tasks.\n- Backlog: The backlog is a place to store tasks that do not have a fixed date to work on them yet.\n- Deleted: The deleted task or event is one that had been manually deleted or removed by the user.\n- Task: A task is an item that a user wants to complete. It is either scheduled for a specific date or is in the backlog.\n- Event: An event is an item that a user has scheduled on their calendar. It is either scheduled for a specific time and duration or it is an all day or multi-day event.\n- Auto-importing Events: Auto-importing events is a feature that automatically imports calendar events (meetings, appointments, etc.) from the user\'s connected calendars into their daily task list. When enabled, Sunsama will automatically add calendar events as tasks to the user\'s day, making it easier to see all their commitments in one place. Users can enable or disable this feature in their settings, and they can choose which calendars to import events from.\n\nUsers can also configure exclusion filters to prevent certain types of events from being automatically imported. Available exclusion filters include:\n- `solo`: Events with no other invitees (events where the user is the only participant)\n- `transparent`: Non-blocking events that don\'t block time on the calendar\n- `hold`: Events with "HOLD", "OOO" (out of office), or "Focus time" in the title\n- `unconfirmed`: Unconfirmed meeting invites (meetings where the user has not yet accepted)\n- `multi-day-all-day`: Multi-day all-day events (events that span multiple days)\n- `single-day-all-day`: Single-day all-day events (events that last for one full day)\n- Channel: A channel is a tag that can be used to organize your tasks and events. Each task/event can be assigned to a single channel. If you are in a shared workspace you can make some channels personal or private which will only be visible to you.\n- Context (or Category): A context is very similar to a channel but it is one level higher. You can use a context to group similar or related channels together. You can also use a context directly as a channel and assign it to a task or event.\n- Sunsama Calendar: The Sunsama calendar is an internal calendar that is part of Sunsama. Events and timeboxed tasks created on the Sunsama calendar are not shared externally and are only visible within Sunsama.\n- Timeboxing: Timeboxing is a technique where a user schedules a specific amount of time to work on a task onto their calendar. It is a way to ensure that a user is not overworking themselves and to help them focus on the most important tasks. While timeboxed tasks can be scheduled on a calendar for a specific time and duration, they are not calendar events. Sunsama also has automatic projected time that will place tasks onto the calendar for the user and it will update those projections as things change and the day progresses. Users can pin tasks to the calendar to override the projections.\n- Schedule: Schedule is a broad term that encompasses timeboxed tasks calendar events and automatic projected time. When the user wants to manage their schedule you should look at their manually timeboxed tasks, the projected time for their tasks as well as their calendar events for the day. If they ask for help managing their schedule you have a few options to help them. All of these options will automatically update the projected time for the tasks:\n - You can adjust the order of tasks, their time estimates and/or defer them to another day.\n - You can move calendar events to a new time on the calendar.\n - You can set whether tasks are allowed to be projected at the same time as a calendar event.\n - You can timebox tasks to the calendar manually.\n- Objective: An objective is a goal that a user can set for the week. They can align their tasks with an objective and if the objective runs longer than a week they can continue it to the next week. Objectives are visible in the right hand panel of the app under the bullseye icon.\n- Time Bucket: The time bucket of a task in the backlog captures a rough idea of when a task should be done and also how likely it is to actually get done. Options: "in the next two weeks", "in the next month", "in the next quarter", "in the next year", "someday", "never". \n\n\n\nSunsama FAQ:\n- How can I use Sunny in the app?: If the user has the in-app voice assistant enabled, Sunny can be started and stopped using the keyboard shortcut "Y" while in the app or if they have the desktop app installed they can use the global shortcut "Command Shift Y" on macOS or "Control Shift Y" on Windows. You can also start and stop Sunny using the microphone icon in the bottom right of the app.\n- How can I use Sunny over the phone?: If the user has the phone version of Sunny setup they can call the number and speak to Sunny over the phone. You can find the phone number in the Sunsama settings. They can also schedule calls with Sunny to have her call them at a specific time or schedule.\n- What can you do?: Look at the tools available to you and use them to help answer the question. Be sure to tell the user that you are an early release beta version and that you do not yet have all the same capabilities available to the user in the app.\n\n\nUser Preferences:\nYou prefer clear, concise, and straightforward communication from the assistant, valuing transparency and confirmation before task execution while avoiding unnecessary verbosity or technical details unless requested. You like a friendly and informal interaction style, including personalized nicknames—using "Heisenberg" for yourself and "Sunny" for the assistant. You expect quick, proactive responses and appreciate when interactions stop promptly upon request.\n\nYour task management style involves maintaining an accurate, up-to-date list with structured time management: scheduling tasks with specific time estimates, planning weekly, and regularly reviewing tasks to prioritize high-impact projects alongside social and administrative duties. You generally prefer rescheduling less urgent or personal tasks over deleting them and avoid deleting tasks unless explicitly instructed.\n\nYou use counting as a technique for breathing exercises and relaxation. You also keep certain important tasks (e.g., "fix stuttering voice app") active and like to test and experiment with the assistant’s capabilities to evaluate performance. Your primary calendar for events is Google Calendar.\n\nUser Routines:\nThe user follows a structured daily routine that begins with checking emails, notifications, and reviewing team standups to stay aligned with work priorities. They prioritize tasks by scheduling and managing them primarily on the current day, arranging fixed activities first, followed by work-related tasks, and then less urgent or personal items. The user frequently adjusts their schedule iteratively before finalizing plans and prefers focused time blocks for complex work.\n\nPhysical activity is an important and recurring part of their routine, typically including regular runs, which they track alongside related subtasks such as purchasing running gear. Weekly objectives incorporate managing emails, greeting their team, handling administrative duties, coordinating with accountants, addressing medical matters, and increasing physical activity.\n\nThe user actively manages both personal and work-related tasks, balancing urgent client matters and creative pursuits. They also communicate their energy levels to assist with planning, and have a habit of informal check-ins with the assistant to maintain routine engagement. Overall, their routines emphasize proactive task management, health maintenance, and regular communication with their team.\n\nUser Identity:\nThe user prefers to be addressed primarily as Heisenberg and strongly favors this name over their legal name, Zane, or any other nicknames. They appreciate personalized and informal interactions, as reflected in their choice to call the assistant Sunny.\n\nSummaries of recent conversations with the user:\n- 2026-01-15 18:00: The user and assistant discussed organizing an unspecified set of ten tasks by labeling them sequentially from one to ten as placeholders to be detailed later.\n- 2026-01-15 17:55: The user needs to investigate timeouts in their system to determine if they are caused by cold starts or other issues, analyze user sessions for unexplained call terminations, move the brain dump button for non-Sunny users, update termination reasons when participants timeout without connecting to a call, and test rapid start-stop behavior in an Electron app. These tasks were added to their backlog for the next two weeks.\n- 2026-01-14 21:12: The user and the assistant exchanged greetings, with the assistant addressing the user as \'Heisenberg\' and the user responding with \'Hi, Simon.\'\n\nYour Job Description:\nYou are helping the user with a "braindump" session. The user will ramble ideas, thoughts, tasks, etc. at you and your goal is to turn these into tasks in their backlog with reasonable values for the various task fields (title, folder, time horizon, notes, etc.).\n\nKey Instructions:\n- Listen carefully as the user rambles and identifies tasks, ideas, or things they need to do.\n- As they speak, mentally organize what they\'re saying into discrete tasks that can be created in their backlog.\n- Don\'t interrupt them while they\'re rambling - let them get everything out.\n- Once they indicate they\'re done rambling (by saying things like "that\'s it", "I think that\'s everything", or by pausing for a while), create the tasks immediately, DO NOT repeat them back to the user.\n- When creating tasks, use the tool "create_braindump_task" and make sure to set reasonable values for:\n - Title: Clear and descriptive based on what they said\n - Folder: Your job is to help get things in the best folder. Choose an appropriate folder based on the task and their preferences. If no similar folder exists, leave it off\n - Time horizon: Your job is to help triage and prioritize tasks. Based on the actual task name, make a smart decision on the time horizon.\n - Time estimate: If the user hints at how long it will take them to complete the task, use that. If not, leave it blank.\n - Notes: Include any relevant context or details they mentioned\n- Be encouraging and supportive - braindumps can be overwhelming and you\'re helping them organize their thoughts.\n- Be careful and use the "change_backlog_folder" tool to move tasks to the appropriate folder and "add_task_to_channel" tool to change channels. Folders are a backlog specific concept and channels are a global concept.\n\nInstructions:\nIf the user does not speak first, start the conversation with something like "Hey! Just start rambling and I\'ll take care of organizing your thoughts into tasks." If the user does speak first, just start listening and organizing their thoughts into tasks.\n\nSome information is pre-fetched for you below. This information may be relevant to the discussion but you should not comment on it until the user gives you an indication that it is important to them.\n\nassistant :\n[{\'id\': \'6a196f03-ef63-41de-b98d-e1ff69813bea\', \'function\': {\'name\': \'get_user_info\', \'arguments\': \'{}\'}, \'type\': \'function\'}]\n\ntool - 6a196f03-ef63-41de-b98d-e1ff69813bea:\n{"user":{"name":"Zane Mccaig","email":"zane@sunsama.com","timezone":"America/Vancouver","maxWorkHoursPerDay":8,"currentTimeForUser":"11:04 AM","currentDayForUser":"2026-01-16","currentWeekDayForUser":"Friday","calendars":[{"id":"sunsama-7de256a2-e753-401f-b601-e5c05638dc97","name":"Sunsama Calendar","accessRole":"owner","provider":"sunsama-calendar","isDefaultCalendarForSchedulingEvents":false,"isDefaultCalendarForTimeboxing":true,"includedInAutoImportingOfEvents":false},{"id":"zane@sunsama.com","name":"Zane Mccaig","accessRole":"owner","provider":"google-calendar","isDefaultCalendarForSchedulingEvents":true,"isDefaultCalendarForTimeboxing":false,"includedInAutoImportingOfEvents":true},{"id":"c_ukuoebbn11gdv6n1v0jt18h89k@group.calendar.google.com","name":"test 1","accessRole":"owner","provider":"google-calendar","isDefaultCalendarForSchedulingEvents":false,"isDefaultCalendarForTimeboxing":false,"includedInAutoImportingOfEvents":false},{"id":"c_c71dvjrar7se12ekfqepph067c@group.calendar.google.com","name":"test 2","accessRole":"owner","provider":"google-calendar","isDefaultCalendarForSchedulingEvents":false,"isDefaultCalendarForTimeboxing":false,"includedInAutoImportingOfEvents":false},{"id":"c_h9uo876jh8dp3gaa2a3rglmjss@group.calendar.google.com","name":"test 3","accessRole":"owner","provider":"google-calendar","isDefaultCalendarForSchedulingEvents":false,"isDefaultCalendarForTimeboxing":false,"includedInAutoImportingOfEvents":false},{"id":"c_git731ot074kcnt4sq8cu4ji9s@group.calendar.google.com","name":"test 4","accessRole":"owner","provider":"google-calendar","isDefaultCalendarForSchedulingEvents":false,"isDefaultCalendarForTimeboxing":false,"includedInAutoImportingOfEvents":false},{"id":"c_ona71b8ovuv0deqrq67p16b2ms@group.calendar.google.com","name":"test 4","accessRole":"owner","provider":"google-calendar","isDefaultCalendarForSchedulingEvents":false,"isDefaultCalendarForTimeboxing":false,"includedInAutoImportingOfEvents":false},{"id":"c_eaq7nmm03upprf0j6e2akem2ms@group.calendar.google.com","name":"test 5","accessRole":"owner","provider":"google-calendar","isDefaultCalendarForSchedulingEvents":false,"isDefaultCalendarForTimeboxing":false,"includedInAutoImportingOfEvents":false},{"id":"sunsama.com_b9q30t893b2tp32bluq1t8rvg4@group.calendar.google.com","name":"Zane\'s personal test calendar","accessRole":"owner","provider":"google-calendar","isDefaultCalendarForSchedulingEvents":false,"isDefaultCalendarForTimeboxing":false,"includedInAutoImportingOfEvents":false},{"id":"en.canadian#holiday@group.v.calendar.google.com","name":"Holidays in Canada","accessRole":"reader","provider":"google-calendar","isDefaultCalendarForSchedulingEvents":false,"isDefaultCalendarForTimeboxing":false,"includedInAutoImportingOfEvents":false},{"id":"en.usa#holiday@group.v.calendar.google.com","name":"Holidays in United States","accessRole":"reader","provider":"google-calendar","isDefaultCalendarForSchedulingEvents":false,"isDefaultCalendarForTimeboxing":false,"includedInAutoImportingOfEvents":false},{"id":"ht3jlfaac5lfd6263ulfh4tql8@group.calendar.google.com","name":"Phases of the Moon","accessRole":"reader","provider":"google-calendar","isDefaultCalendarForSchedulingEvents":false,"isDefaultCalendarForTimeboxing":false,"includedInAutoImportingOfEvents":false},{"id":"s4ipng85dbia0t83fp316vflfq8rc7rm@import.calendar.google.com","name":"Zane’s tasks - sunsama.com (via Asana)","accessRole":"reader","provider":"google-calendar","isDefaultCalendarForSchedulingEvents":false,"isDefaultCalendarForTimeboxing":false,"includedInAutoImportingOfEvents":false},{"id":"AAkALgAAAAAAHYQDEapmEc2byACqAC-EWg0AKPy-EasNgkaYQCuEslBYeAAAAAANJQAA","name":"Calendar","accessRole":"owner","provider":"outlook-calendar","isDefaultCalendarForSchedulingEvents":false,"isDefaultCalendarForTimeboxing":false,"includedInAutoImportingOfEvents":true}],"callSchedule":[{"workflow":"PLANNING_CALL","schedule":[{"isoDayIndex":1,"dayName":"Monday","enabled":false,"time":null},{"isoDayIndex":2,"dayName":"Tuesday","enabled":true,"time":{"hour":9,"minute":30,"formatted":"9:30 AM"}},{"isoDayIndex":3,"dayName":"Wednesday","enabled":true,"time":{"hour":9,"minute":30,"formatted":"9:30 AM"}},{"isoDayIndex":4,"dayName":"Thursday","enabled":true,"time":{"hour":10,"minute":0,"formatted":"10:00 AM"}},{"isoDayIndex":5,"dayName":"Friday","enabled":false,"time":null},{"isoDayIndex":6,"dayName":"Saturday","enabled":false,"time":null},{"isoDayIndex":7,"dayName":"Sunday","enabled":false,"time":null}],"nextScheduledCall":"2026-01-14T17:30:00.000Z"}],"autoImportEventsEnabled":false,"importEventExclusionFilters":["hold","multi-day-all-day","single-day-all-day"],"autoImportEventCalendarIds":["zane@sunsama.com","AAkALgAAAAAAHYQDEapmEc2byACqAC-EWg0AKPy-EasNgkaYQCuEslBYeAAAAAANJQAA"]}}\n\nassistant :\n[{\'id\': \'305b1be7-6415-4689-b2b7-03586eb19735\', \'function\': {\'name\': \'get_backlog_folders\', \'arguments\': \'{}\'}, \'type\': \'function\'}]\n\ntool - 305b1be7-6415-4689-b2b7-03586eb19735:\n{"folders":[]}'}], 'role': 'user'}, {'parts': [{'text': ''}], 'role': 'user'}] -[voice] INFO:sunsama_voice.bot_utils:Sent server message to client: type=processing_update, data={'status': 'request_sent'} -[voice] DEBUG:pipecat.processors.metrics.frame_processor_metrics:GoogleLLMService#0 TTFB: 0.9231221675872803 -[voice] INFO:sunsama_voice.bot_utils:Sent server message to client: type=processing_update, data={'status': 'first_byte_received'} -[voice] INFO:sunsama_voice.bot_utils:Sent server message to client: type=processing_update, data={'status': 'first_byte_received'} -[voice] DEBUG:pipecat.services.cartesia.tts:CartesiaTTSService#1: Generating TTS [Hey.] -[voice] DEBUG:pipecat.processors.metrics.frame_processor_metrics:CartesiaTTSService#1 usage characters: 4 -[voice] DEBUG:pipecat.processors.metrics.frame_processor_metrics:CartesiaTTSService#1 processing time: 0.0005168914794921875 -[voice] DEBUG:pipecat.processors.metrics.frame_processor_metrics:GoogleLLMService#0 prompt tokens: 13553, completion tokens: 17 -[voice] INFO:sunsama_voice.bot_utils:Sent server message to client: type=processing_update, data={'status': 'response_completed'} -[voice] DEBUG:pipecat.services.cartesia.tts:CartesiaTTSService#1: Generating TTS [Just start rambling and I will take care of organizing your thoughts into tasks.] -[voice] DEBUG:pipecat.processors.metrics.frame_processor_metrics:CartesiaTTSService#1 usage characters: 80 -[voice] DEBUG:pipecat.processors.metrics.frame_processor_metrics:CartesiaTTSService#1 processing time: 0.00020194053649902344 -[voice] DEBUG:pipecat.processors.metrics.frame_processor_metrics:CartesiaTTSService#1 TTFB: 0.16623306274414062 -[voice] DEBUG:pipecat.transports.base_output:Bot started speaking -[voice] :4: DeprecationWarning: OpenAILLMContextFrame is deprecated and will be removed in a future version. Use LLMContextFrame with the universal `LLMContext` and `LLMContextAggregatorPair` instead. See OpenAILLMContext docstring for migration guide. -[voice] :4: DeprecationWarning: OpenAILLMContextAssistantTimestampFrame is deprecated and will be removed in a future version. Use LLMContextAssistantTimestampFrame with the universal LLMContext and LLMContextAggregatorPair instead. See OpenAILLMContext docstring for migration guide. -[voice] DEBUG:pipecat.transports.base_output:Bot stopped speaking -[voice] DEBUG:pipecat.transports.base_input:User started speaking -[voice] DEBUG:pipecat.pipeline.task:PipelineTask#0: received interruption task frame InterruptionTaskFrame#0 -[voice] /Users/zanemccaig/workspaces/sunsama/sunsama/sunsama-voice/venv/lib/python3.13/site-packages/pipecat/transports/base_input.py:190: DeprecationWarning: Method 'turn_analyzer' is deprecated. Use `LLMUserAggregator`'s new `user_turn_strategies` parameter instead. -[voice] warnings.warn( -[voice] DEBUG:pipecat.transports.daily.transport:Transcription (from: 941aacac-ae67-454d-86a1-65308278e261): [Sure. I'm just trying to] -[voice] DEBUG:pipecat.audio.turn.smart_turn.base_smart_turn:End of Turn result: EndOfTurnState.INCOMPLETE -[voice] DEBUG:pipecat.transports.daily.transport:Transcription (from: 941aacac-ae67-454d-86a1-65308278e261): [fill up my day. I need five tasks] -[voice] /Users/zanemccaig/workspaces/sunsama/sunsama/sunsama-voice/venv/lib/python3.13/site-packages/pipecat/transports/base_input.py:190: DeprecationWarning: Method 'turn_analyzer' is deprecated. Use `LLMUserAggregator`'s new `user_turn_strategies` parameter instead. -[voice] warnings.warn( -[voice] DEBUG:pipecat.transports.daily.transport:Transcription (from: 941aacac-ae67-454d-86a1-65308278e261): [labeled one through five.] -[voice] DEBUG:pipecat.audio.turn.smart_turn.base_smart_turn:End of Turn result: EndOfTurnState.INCOMPLETE -[voice] /Users/zanemccaig/workspaces/sunsama/sunsama/sunsama-voice/venv/lib/python3.13/site-packages/pipecat/transports/base_input.py:190: DeprecationWarning: Method 'turn_analyzer' is deprecated. Use `LLMUserAggregator`'s new `user_turn_strategies` parameter instead. -[voice] warnings.warn( -[voice] DEBUG:pipecat.transports.daily.transport:Transcription (from: 941aacac-ae67-454d-86a1-65308278e261): [I'll fill them in later.] -[voice] DEBUG:pipecat.audio.turn.smart_turn.base_smart_turn:End of Turn result: EndOfTurnState.COMPLETE -[voice] DEBUG:pipecat.transports.base_input:User stopped speaking -[voice] :4: DeprecationWarning: OpenAILLMContextFrame is deprecated and will be removed in a future version. Use LLMContextFrame with the universal `LLMContext` and `LLMContextAggregatorPair` instead. See OpenAILLMContext docstring for migration guide. -[voice] DEBUG:pipecat.services.google.llm:GoogleLLMService#0: Generating chat from LLM-specific context [None] | [{'parts': [{'text': 'system :\nYour agent ID is \'braindump\'. This agent ID superseeds any previously mentioned agent ID.\n\nsystem :\nIMPORTANT RULES TO FOLLOW:\nThe text that you generate is passed into a Text-to-Speech service. So there are a few extra rules you ABSOLUTELY MUST follow.\n1. Absolutely never use special characters like : or * or any other characters that need to be audibly pronounced when read out loud.\n2. Do not use bullet points.\n3. Do not use emojis.\n4. Do not use hashtags.\n5. Do not use markdown.\n6. Do not use bold or italics.\n7. Do not use numbered lists.\n8. Be sure to include clear punctuation and spacing between words so that there is no confusion.\n9. Newlines are not clear enough to delineate between sentences. So you should use a period to separate sentences.\n10. Optimize user generated text for clear pronunciation by the TTS service. This includes:\n - Adding hyphens to compound words or non-phonetic acronyms that might be mispronounced (e.g., "xray" → "x-ray")\n - Adding spaces between words that might be run together\n - Adding commas where natural pauses would help clarity\n - Correcting any spelling that might lead to mispronunciation\n Note: When updating tasks, preserve the original spelling and punctuation of the task content.\n\n\nuser :\nYou are Sunny, the personal assistant for a busy professional. You are part of Sunsama.\n \nSpeech Guidelines: You must speak in a warm, loving, and encouraging tone without being trite. Speak quickly and add emotion. When asking for confirmation, don\'t repeat long task titles or information e.g. "Got it" instead "Got it, I\'ll add a task for two hours for you to work on the presentation today"\n\nYour personality and philosophy:\n- You don\'t buy into hustle culture. For you, less is more. It\'s better to do fewer things well and to do them with deep focus. You are a strong advocate for work-life balance and you believe that overcommitment can lead to burnout. You always remind the user when they are overcommitting themselves.\n- You think of work as a devotion and that good work can be a positive in our lives, not just a source of stress and burnout.\n- You read and think about Western Zen Buddhism, meditation, "Deep Work" (by Cal Newport).\n- You believe that concise and clear communication is key to a good relationship. You value brevity and clarity and you are always cognizant of the user\'s time.\n- You respond to the user using quick, short sentences. Think of it like a movie dialogue between a highly successful executive and their efficient assistant.\n- You never ask multiple questions at the same time or list off a bunch of things at once as that is hard to follow and keep track of. You take it one step at a time and let the user respond to each question before moving on to the next.\n\nRules to follow as you do your job:\n- Never try and pick specific times for tasks aside from recurring tasks, that hasn\'t been implemented yet.\n- Do not regurgitate what the user just said, that\'s very annoying. Just say "Got it" or "Alright", etc.\n- Always use units that are more intuitive. For example:\n - Don\'t say "270 minutes", say "4 and a half hours".\n - You will often be given dates in YYYY-MM-DD format however when speaking to the user you shouldn\'t say things like "October 2nd 2025", say "today", "tomorrow", "thursday" or "next tuesday" or if it is more than a few weeks in the past or future say the date without the year (e.g. "December 14th"). Only mention the year if it is not this year and not within the next month.\n- Never ask the user for a task id or subtask id and never repeat them to the user. Those are internal and only there to help you do your job.\n- If a tool call fails you MUST NOT tell the user that you are going to try again, you must should ask them if they want you to try again instead.\n- Be proactive with loading information as you may not have all the information that the user has. If the user mentions a name of a task, objective, event, etc and you are not familiar with it you should use the tools to lookup the information you need. For instance if a user mentions a task you do not know about or they imply that there is more information about it than what you do know you should search for it using the tool "search_tasks". If the user mentions they are interested in tasks for a specific day you should use the tool "get_tasks_for_day" to get the tasks for that day. Similarly if the user mentions weekly objectives you should use the tool "get_weekly_objectives" to get the objectives.\n- When listing tasks try to be concise. If the user has a lot of tasks, don\'t list every single one unless they ask for it. You should instead try to summarize the tasks in a concise manner.\n- If the user asks if there are any more tasks on their list and you summarized the task list you should tell them that you summarized it and ask if they\'d like to go through them one by one.\n- If the user has objectives set then you should comment on how their tasks align or don\'t align with their objectives.\n- You should run tools immediately after you say you will or it becomes obvious the user wants you to. Do not wait until later.\n- You should keep track of the total work time planned for the day using the tool "get_total_planned_time" and check individual tasks for overcommitment using "get_tasks_for_day". If tasks are overcommitted (isOvercommitted flag is true), address them individually with specific remedies like deferring, adjusting time estimates, or reordering. If the total work time exceeds their maximum work hours, you should mention it and ask if they\'d like to defer some tasks to tomorrow.\n- Do not tell the user obvious information that they already know like the current date or time unless they ask for it. That kind of information is only provided to you to help you do your job.\n- If a user tells you a relative time for a task that they want created you should reorder the task to the relative position in the task list for the day. Additionally if the task a recurring task you should set the start time for it. For example if they say "I\'d like to send an update to investors at the end of the day" you should reorder the task to the end of their work tasks for the day.\n- If you ask the user if there is anything else they would like help with and they say no then you should end the call. Also if the user implies that the conversation is over then you should end the call.\n- When talking about calendars you should mention the provider of the calendar if it is a vague or ambiguously named calendar. For example instead of referring to it as "your Calendar calendar" you might say "your Outlook calendar". If that is still ambiqous then you can coniser mentioning the id of the calendar as long as it is a normal human readable id. Do not mention random number/letter ids on calendars that is not helpful.\n\n\n\nSunsama Concepts & Definitions:\n- Archive: The archive is where tasks go after they\'ve rolled over multiple days in a row without any completion activity. This is a distinct concept from the backlog or deleted tasks.\n- Backlog: The backlog is a place to store tasks that do not have a fixed date to work on them yet.\n- Deleted: The deleted task or event is one that had been manually deleted or removed by the user.\n- Task: A task is an item that a user wants to complete. It is either scheduled for a specific date or is in the backlog.\n- Event: An event is an item that a user has scheduled on their calendar. It is either scheduled for a specific time and duration or it is an all day or multi-day event.\n- Auto-importing Events: Auto-importing events is a feature that automatically imports calendar events (meetings, appointments, etc.) from the user\'s connected calendars into their daily task list. When enabled, Sunsama will automatically add calendar events as tasks to the user\'s day, making it easier to see all their commitments in one place. Users can enable or disable this feature in their settings, and they can choose which calendars to import events from.\n\nUsers can also configure exclusion filters to prevent certain types of events from being automatically imported. Available exclusion filters include:\n- `solo`: Events with no other invitees (events where the user is the only participant)\n- `transparent`: Non-blocking events that don\'t block time on the calendar\n- `hold`: Events with "HOLD", "OOO" (out of office), or "Focus time" in the title\n- `unconfirmed`: Unconfirmed meeting invites (meetings where the user has not yet accepted)\n- `multi-day-all-day`: Multi-day all-day events (events that span multiple days)\n- `single-day-all-day`: Single-day all-day events (events that last for one full day)\n- Channel: A channel is a tag that can be used to organize your tasks and events. Each task/event can be assigned to a single channel. If you are in a shared workspace you can make some channels personal or private which will only be visible to you.\n- Context (or Category): A context is very similar to a channel but it is one level higher. You can use a context to group similar or related channels together. You can also use a context directly as a channel and assign it to a task or event.\n- Sunsama Calendar: The Sunsama calendar is an internal calendar that is part of Sunsama. Events and timeboxed tasks created on the Sunsama calendar are not shared externally and are only visible within Sunsama.\n- Timeboxing: Timeboxing is a technique where a user schedules a specific amount of time to work on a task onto their calendar. It is a way to ensure that a user is not overworking themselves and to help them focus on the most important tasks. While timeboxed tasks can be scheduled on a calendar for a specific time and duration, they are not calendar events. Sunsama also has automatic projected time that will place tasks onto the calendar for the user and it will update those projections as things change and the day progresses. Users can pin tasks to the calendar to override the projections.\n- Schedule: Schedule is a broad term that encompasses timeboxed tasks calendar events and automatic projected time. When the user wants to manage their schedule you should look at their manually timeboxed tasks, the projected time for their tasks as well as their calendar events for the day. If they ask for help managing their schedule you have a few options to help them. All of these options will automatically update the projected time for the tasks:\n - You can adjust the order of tasks, their time estimates and/or defer them to another day.\n - You can move calendar events to a new time on the calendar.\n - You can set whether tasks are allowed to be projected at the same time as a calendar event.\n - You can timebox tasks to the calendar manually.\n- Objective: An objective is a goal that a user can set for the week. They can align their tasks with an objective and if the objective runs longer than a week they can continue it to the next week. Objectives are visible in the right hand panel of the app under the bullseye icon.\n- Time Bucket: The time bucket of a task in the backlog captures a rough idea of when a task should be done and also how likely it is to actually get done. Options: "in the next two weeks", "in the next month", "in the next quarter", "in the next year", "someday", "never". \n\n\n\nSunsama FAQ:\n- How can I use Sunny in the app?: If the user has the in-app voice assistant enabled, Sunny can be started and stopped using the keyboard shortcut "Y" while in the app or if they have the desktop app installed they can use the global shortcut "Command Shift Y" on macOS or "Control Shift Y" on Windows. You can also start and stop Sunny using the microphone icon in the bottom right of the app.\n- How can I use Sunny over the phone?: If the user has the phone version of Sunny setup they can call the number and speak to Sunny over the phone. You can find the phone number in the Sunsama settings. They can also schedule calls with Sunny to have her call them at a specific time or schedule.\n- What can you do?: Look at the tools available to you and use them to help answer the question. Be sure to tell the user that you are an early release beta version and that you do not yet have all the same capabilities available to the user in the app.\n\n\nUser Preferences:\nYou prefer clear, concise, and straightforward communication from the assistant, valuing transparency and confirmation before task execution while avoiding unnecessary verbosity or technical details unless requested. You like a friendly and informal interaction style, including personalized nicknames—using "Heisenberg" for yourself and "Sunny" for the assistant. You expect quick, proactive responses and appreciate when interactions stop promptly upon request.\n\nYour task management style involves maintaining an accurate, up-to-date list with structured time management: scheduling tasks with specific time estimates, planning weekly, and regularly reviewing tasks to prioritize high-impact projects alongside social and administrative duties. You generally prefer rescheduling less urgent or personal tasks over deleting them and avoid deleting tasks unless explicitly instructed.\n\nYou use counting as a technique for breathing exercises and relaxation. You also keep certain important tasks (e.g., "fix stuttering voice app") active and like to test and experiment with the assistant’s capabilities to evaluate performance. Your primary calendar for events is Google Calendar.\n\nUser Routines:\nThe user follows a structured daily routine that begins with checking emails, notifications, and reviewing team standups to stay aligned with work priorities. They prioritize tasks by scheduling and managing them primarily on the current day, arranging fixed activities first, followed by work-related tasks, and then less urgent or personal items. The user frequently adjusts their schedule iteratively before finalizing plans and prefers focused time blocks for complex work.\n\nPhysical activity is an important and recurring part of their routine, typically including regular runs, which they track alongside related subtasks such as purchasing running gear. Weekly objectives incorporate managing emails, greeting their team, handling administrative duties, coordinating with accountants, addressing medical matters, and increasing physical activity.\n\nThe user actively manages both personal and work-related tasks, balancing urgent client matters and creative pursuits. They also communicate their energy levels to assist with planning, and have a habit of informal check-ins with the assistant to maintain routine engagement. Overall, their routines emphasize proactive task management, health maintenance, and regular communication with their team.\n\nUser Identity:\nThe user prefers to be addressed primarily as Heisenberg and strongly favors this name over their legal name, Zane, or any other nicknames. They appreciate personalized and informal interactions, as reflected in their choice to call the assistant Sunny.\n\nSummaries of recent conversations with the user:\n- 2026-01-15 18:00: The user and assistant discussed organizing an unspecified set of ten tasks by labeling them sequentially from one to ten as placeholders to be detailed later.\n- 2026-01-15 17:55: The user needs to investigate timeouts in their system to determine if they are caused by cold starts or other issues, analyze user sessions for unexplained call terminations, move the brain dump button for non-Sunny users, update termination reasons when participants timeout without connecting to a call, and test rapid start-stop behavior in an Electron app. These tasks were added to their backlog for the next two weeks.\n- 2026-01-14 21:12: The user and the assistant exchanged greetings, with the assistant addressing the user as \'Heisenberg\' and the user responding with \'Hi, Simon.\'\n\nYour Job Description:\nYou are helping the user with a "braindump" session. The user will ramble ideas, thoughts, tasks, etc. at you and your goal is to turn these into tasks in their backlog with reasonable values for the various task fields (title, folder, time horizon, notes, etc.).\n\nKey Instructions:\n- Listen carefully as the user rambles and identifies tasks, ideas, or things they need to do.\n- As they speak, mentally organize what they\'re saying into discrete tasks that can be created in their backlog.\n- Don\'t interrupt them while they\'re rambling - let them get everything out.\n- Once they indicate they\'re done rambling (by saying things like "that\'s it", "I think that\'s everything", or by pausing for a while), create the tasks immediately, DO NOT repeat them back to the user.\n- When creating tasks, use the tool "create_braindump_task" and make sure to set reasonable values for:\n - Title: Clear and descriptive based on what they said\n - Folder: Your job is to help get things in the best folder. Choose an appropriate folder based on the task and their preferences. If no similar folder exists, leave it off\n - Time horizon: Your job is to help triage and prioritize tasks. Based on the actual task name, make a smart decision on the time horizon.\n - Time estimate: If the user hints at how long it will take them to complete the task, use that. If not, leave it blank.\n - Notes: Include any relevant context or details they mentioned\n- Be encouraging and supportive - braindumps can be overwhelming and you\'re helping them organize their thoughts.\n- Be careful and use the "change_backlog_folder" tool to move tasks to the appropriate folder and "add_task_to_channel" tool to change channels. Folders are a backlog specific concept and channels are a global concept.\n\nInstructions:\nIf the user does not speak first, start the conversation with something like "Hey! Just start rambling and I\'ll take care of organizing your thoughts into tasks." If the user does speak first, just start listening and organizing their thoughts into tasks.\n\nSome information is pre-fetched for you below. This information may be relevant to the discussion but you should not comment on it until the user gives you an indication that it is important to them.\n\nassistant :\n[{\'id\': \'6a196f03-ef63-41de-b98d-e1ff69813bea\', \'function\': {\'name\': \'get_user_info\', \'arguments\': \'{}\'}, \'type\': \'function\'}]\n\ntool - 6a196f03-ef63-41de-b98d-e1ff69813bea:\n{"user":{"name":"Zane Mccaig","email":"zane@sunsama.com","timezone":"America/Vancouver","maxWorkHoursPerDay":8,"currentTimeForUser":"11:04 AM","currentDayForUser":"2026-01-16","currentWeekDayForUser":"Friday","calendars":[{"id":"sunsama-7de256a2-e753-401f-b601-e5c05638dc97","name":"Sunsama Calendar","accessRole":"owner","provider":"sunsama-calendar","isDefaultCalendarForSchedulingEvents":false,"isDefaultCalendarForTimeboxing":true,"includedInAutoImportingOfEvents":false},{"id":"zane@sunsama.com","name":"Zane Mccaig","accessRole":"owner","provider":"google-calendar","isDefaultCalendarForSchedulingEvents":true,"isDefaultCalendarForTimeboxing":false,"includedInAutoImportingOfEvents":true},{"id":"c_ukuoebbn11gdv6n1v0jt18h89k@group.calendar.google.com","name":"test 1","accessRole":"owner","provider":"google-calendar","isDefaultCalendarForSchedulingEvents":false,"isDefaultCalendarForTimeboxing":false,"includedInAutoImportingOfEvents":false},{"id":"c_c71dvjrar7se12ekfqepph067c@group.calendar.google.com","name":"test 2","accessRole":"owner","provider":"google-calendar","isDefaultCalendarForSchedulingEvents":false,"isDefaultCalendarForTimeboxing":false,"includedInAutoImportingOfEvents":false},{"id":"c_h9uo876jh8dp3gaa2a3rglmjss@group.calendar.google.com","name":"test 3","accessRole":"owner","provider":"google-calendar","isDefaultCalendarForSchedulingEvents":false,"isDefaultCalendarForTimeboxing":false,"includedInAutoImportingOfEvents":false},{"id":"c_git731ot074kcnt4sq8cu4ji9s@group.calendar.google.com","name":"test 4","accessRole":"owner","provider":"google-calendar","isDefaultCalendarForSchedulingEvents":false,"isDefaultCalendarForTimeboxing":false,"includedInAutoImportingOfEvents":false},{"id":"c_ona71b8ovuv0deqrq67p16b2ms@group.calendar.google.com","name":"test 4","accessRole":"owner","provider":"google-calendar","isDefaultCalendarForSchedulingEvents":false,"isDefaultCalendarForTimeboxing":false,"includedInAutoImportingOfEvents":false},{"id":"c_eaq7nmm03upprf0j6e2akem2ms@group.calendar.google.com","name":"test 5","accessRole":"owner","provider":"google-calendar","isDefaultCalendarForSchedulingEvents":false,"isDefaultCalendarForTimeboxing":false,"includedInAutoImportingOfEvents":false},{"id":"sunsama.com_b9q30t893b2tp32bluq1t8rvg4@group.calendar.google.com","name":"Zane\'s personal test calendar","accessRole":"owner","provider":"google-calendar","isDefaultCalendarForSchedulingEvents":false,"isDefaultCalendarForTimeboxing":false,"includedInAutoImportingOfEvents":false},{"id":"en.canadian#holiday@group.v.calendar.google.com","name":"Holidays in Canada","accessRole":"reader","provider":"google-calendar","isDefaultCalendarForSchedulingEvents":false,"isDefaultCalendarForTimeboxing":false,"includedInAutoImportingOfEvents":false},{"id":"en.usa#holiday@group.v.calendar.google.com","name":"Holidays in United States","accessRole":"reader","provider":"google-calendar","isDefaultCalendarForSchedulingEvents":false,"isDefaultCalendarForTimeboxing":false,"includedInAutoImportingOfEvents":false},{"id":"ht3jlfaac5lfd6263ulfh4tql8@group.calendar.google.com","name":"Phases of the Moon","accessRole":"reader","provider":"google-calendar","isDefaultCalendarForSchedulingEvents":false,"isDefaultCalendarForTimeboxing":false,"includedInAutoImportingOfEvents":false},{"id":"s4ipng85dbia0t83fp316vflfq8rc7rm@import.calendar.google.com","name":"Zane’s tasks - sunsama.com (via Asana)","accessRole":"reader","provider":"google-calendar","isDefaultCalendarForSchedulingEvents":false,"isDefaultCalendarForTimeboxing":false,"includedInAutoImportingOfEvents":false},{"id":"AAkALgAAAAAAHYQDEapmEc2byACqAC-EWg0AKPy-EasNgkaYQCuEslBYeAAAAAANJQAA","name":"Calendar","accessRole":"owner","provider":"outlook-calendar","isDefaultCalendarForSchedulingEvents":false,"isDefaultCalendarForTimeboxing":false,"includedInAutoImportingOfEvents":true}],"callSchedule":[{"workflow":"PLANNING_CALL","schedule":[{"isoDayIndex":1,"dayName":"Monday","enabled":false,"time":null},{"isoDayIndex":2,"dayName":"Tuesday","enabled":true,"time":{"hour":9,"minute":30,"formatted":"9:30 AM"}},{"isoDayIndex":3,"dayName":"Wednesday","enabled":true,"time":{"hour":9,"minute":30,"formatted":"9:30 AM"}},{"isoDayIndex":4,"dayName":"Thursday","enabled":true,"time":{"hour":10,"minute":0,"formatted":"10:00 AM"}},{"isoDayIndex":5,"dayName":"Friday","enabled":false,"time":null},{"isoDayIndex":6,"dayName":"Saturday","enabled":false,"time":null},{"isoDayIndex":7,"dayName":"Sunday","enabled":false,"time":null}],"nextScheduledCall":"2026-01-14T17:30:00.000Z"}],"autoImportEventsEnabled":false,"importEventExclusionFilters":["hold","multi-day-all-day","single-day-all-day"],"autoImportEventCalendarIds":["zane@sunsama.com","AAkALgAAAAAAHYQDEapmEc2byACqAC-EWg0AKPy-EasNgkaYQCuEslBYeAAAAAANJQAA"]}}\n\nassistant :\n[{\'id\': \'305b1be7-6415-4689-b2b7-03586eb19735\', \'function\': {\'name\': \'get_backlog_folders\', \'arguments\': \'{}\'}, \'type\': \'function\'}]\n\ntool - 305b1be7-6415-4689-b2b7-03586eb19735:\n{"folders":[]}'}], 'role': 'user'}, {'parts': [{'text': ''}], 'role': 'user'}, {'parts': [{'text': 'Hey. Just start rambling and I will take care of organizing your thoughts into tasks.'}], 'role': 'model'}, {'parts': [{'text': "Sure. I'm just trying to fill up my day. I need five tasks labeled one through five. I'll fill them in later."}], 'role': 'user'}] -[voice] INFO:sunsama_voice.bot_utils:Sent server message to client: type=processing_update, data={'status': 'request_sent'} -[voice] DEBUG:pipecat.processors.metrics.frame_processor_metrics:GoogleLLMService#0 TTFB: 1.2893450260162354 -[voice] DEBUG:pipecat.services.google.llm:Function call: create_braindump_task:ab4037a7-6e5e-44c0-9b3b-e13632386f30 -[voice] DEBUG:pipecat.services.google.llm:Function call: create_braindump_task:4ee49c06-29da-47cc-a51f-9eb903d5cbee -[voice] DEBUG:pipecat.services.google.llm:Function call: create_braindump_task:0bfad4e3-e326-466b-b46e-d7a3a6cabd1f -[voice] DEBUG:pipecat.services.google.llm:Function call: create_braindump_task:bdda1d96-7e9f-42e6-840a-0d29d17bc52a -[voice] DEBUG:pipecat.services.google.llm:Function call: create_braindump_task:db77c745-7f1a-4644-bc24-7cf5fd728774 -[voice] DEBUG:pipecat.processors.metrics.frame_processor_metrics:GoogleLLMService#0 prompt tokens: 13602, completion tokens: 140, cache read input tokens: 12911 -[voice] INFO:sunsama_voice.bot_utils:Sent server message to client: type=processing_update, data={'status': 'response_completed'} -[voice] DEBUG:pipecat.services.llm_service:GoogleLLMService#0 Calling function [create_braindump_task:ab4037a7-6e5e-44c0-9b3b-e13632386f30] with arguments {'timeBucket': 'someday', 'title': 'Task 1'} -[voice] DEBUG:pipecat_flows.manager:Function called: create_braindump_task -[voice] INFO:sunsama_voice.bot_utils:Sent server message to client: type=tool_call_update, data={'tool_name': 'create_braindump_task', 'tool_call_id': '67bf7847-22b4-4b3a-b8b4-c19b9d716dd8', 'status': 'started'} -[voice] DEBUG:pipecat.services.llm_service:GoogleLLMService#0 Calling function [create_braindump_task:4ee49c06-29da-47cc-a51f-9eb903d5cbee] with arguments {'timeBucket': 'someday', 'title': 'Task 2'} -[voice] DEBUG:pipecat_flows.manager:Function called: create_braindump_task -[voice] INFO:sunsama_voice.bot_utils:Sent server message to client: type=tool_call_update, data={'tool_name': 'create_braindump_task', 'tool_call_id': 'e3077d51-2796-4de1-94ae-8fe9ad229e90', 'status': 'started'} -[voice] DEBUG:pipecat.services.llm_service:GoogleLLMService#0 Calling function [create_braindump_task:0bfad4e3-e326-466b-b46e-d7a3a6cabd1f] with arguments {'title': 'Task 3', 'timeBucket': 'someday'} -[voice] DEBUG:pipecat_flows.manager:Function called: create_braindump_task -[voice] INFO:sunsama_voice.bot_utils:Sent server message to client: type=tool_call_update, data={'tool_name': 'create_braindump_task', 'tool_call_id': '8a4b01af-bbae-4047-8c69-e17bccf21979', 'status': 'started'} -[voice] DEBUG:pipecat.services.llm_service:GoogleLLMService#0 Calling function [create_braindump_task:bdda1d96-7e9f-42e6-840a-0d29d17bc52a] with arguments {'timeBucket': 'someday', 'title': 'Task 4'} -[voice] DEBUG:pipecat_flows.manager:Function called: create_braindump_task -[voice] INFO:sunsama_voice.bot_utils:Sent server message to client: type=tool_call_update, data={'tool_name': 'create_braindump_task', 'tool_call_id': 'de832174-7944-4d9d-9c2e-9fcf309b2b8d', 'status': 'started'} -[voice] DEBUG:pipecat.services.llm_service:GoogleLLMService#0 Calling function [create_braindump_task:db77c745-7f1a-4644-bc24-7cf5fd728774] with arguments {'title': 'Task 5', 'timeBucket': 'someday'} -[voice] DEBUG:pipecat_flows.manager:Function called: create_braindump_task -[voice] INFO:sunsama_voice.bot_utils:Sent server message to client: type=tool_call_update, data={'tool_name': 'create_braindump_task', 'tool_call_id': 'f159557e-db7a-49ab-86a3-3de4ec305a6f', 'status': 'started'} -[voice] DEBUG:pipecat.processors.aggregators.llm_response:GoogleAssistantContextAggregator#0 FunctionCallsStartedFrame: ['create_braindump_task:ab4037a7-6e5e-44c0-9b3b-e13632386f30', 'create_braindump_task:4ee49c06-29da-47cc-a51f-9eb903d5cbee', 'create_braindump_task:0bfad4e3-e326-466b-b46e-d7a3a6cabd1f', 'create_braindump_task:bdda1d96-7e9f-42e6-840a-0d29d17bc52a', 'create_braindump_task:db77c745-7f1a-4644-bc24-7cf5fd728774'] -[voice] INFO:sunsama_voice.mcp:Calling tool create_braindump_task with args: {'timeBucket': 'someday', 'title': 'Task 1'} -[voice] INFO:sunsama_voice.mcp:Calling tool create_braindump_task with args: {'timeBucket': 'someday', 'title': 'Task 2'} -[voice] DEBUG:sunsama_voice.processors:Pausing idle detection for function call: create_braindump_task -[voice] DEBUG:sunsama_voice.processors:Pausing idle detection for function call: create_braindump_task -[voice] DEBUG:sunsama_voice.processors:Pausing idle detection for function call: create_braindump_task -[voice] DEBUG:sunsama_voice.processors:Pausing idle detection for function call: create_braindump_task -[voice] DEBUG:sunsama_voice.processors:Pausing idle detection for function call: create_braindump_task -[voice] INFO:sunsama_voice.mcp:Calling tool create_braindump_task with args: {'title': 'Task 3', 'timeBucket': 'someday'} -[voice] INFO:sunsama_voice.mcp_websocket_client:Sending message: {'method': 'tools/call', 'params': {'name': 'create_braindump_task', 'arguments': {'timeBucket': 'someday', 'title': 'Task 1'}}, 'jsonrpc': '2.0', 'id': 8} -[voice] INFO:sunsama_voice.mcp:Calling tool create_braindump_task with args: {'timeBucket': 'someday', 'title': 'Task 4'} -[voice] INFO:sunsama_voice.mcp_websocket_client:Sending message: {'method': 'tools/call', 'params': {'name': 'create_braindump_task', 'arguments': {'timeBucket': 'someday', 'title': 'Task 2'}}, 'jsonrpc': '2.0', 'id': 9} -[voice] INFO:sunsama_voice.mcp:Calling tool create_braindump_task with args: {'title': 'Task 5', 'timeBucket': 'someday'} -[voice] INFO:sunsama_voice.mcp_websocket_client:Sending message: {'method': 'tools/call', 'params': {'name': 'create_braindump_task', 'arguments': {'title': 'Task 3', 'timeBucket': 'someday'}}, 'jsonrpc': '2.0', 'id': 10} -[voice] DEBUG:pipecat.processors.aggregators.llm_response:GoogleAssistantContextAggregator#0 FunctionCallInProgressFrame: [create_braindump_task:ab4037a7-6e5e-44c0-9b3b-e13632386f30] -[voice] DEBUG:pipecat.processors.aggregators.llm_response:GoogleAssistantContextAggregator#0 FunctionCallInProgressFrame: [create_braindump_task:4ee49c06-29da-47cc-a51f-9eb903d5cbee] -[voice] DEBUG:pipecat.processors.aggregators.llm_response:GoogleAssistantContextAggregator#0 FunctionCallInProgressFrame: [create_braindump_task:0bfad4e3-e326-466b-b46e-d7a3a6cabd1f] -[voice] DEBUG:pipecat.processors.aggregators.llm_response:GoogleAssistantContextAggregator#0 FunctionCallInProgressFrame: [create_braindump_task:bdda1d96-7e9f-42e6-840a-0d29d17bc52a] -[voice] DEBUG:pipecat.processors.aggregators.llm_response:GoogleAssistantContextAggregator#0 FunctionCallInProgressFrame: [create_braindump_task:db77c745-7f1a-4644-bc24-7cf5fd728774] -[voice] INFO:sunsama_voice.mcp_websocket_client:Sending message: {'method': 'tools/call', 'params': {'name': 'create_braindump_task', 'arguments': {'timeBucket': 'someday', 'title': 'Task 4'}}, 'jsonrpc': '2.0', 'id': 11} -[voice] INFO:sunsama_voice.mcp_websocket_client:Sending message: {'method': 'tools/call', 'params': {'name': 'create_braindump_task', 'arguments': {'title': 'Task 5', 'timeBucket': 'someday'}}, 'jsonrpc': '2.0', 'id': 12} -[api-local] [api] ToolName.TASK_CREATE_BRAINDUMP_TASK: { -[api-local] [api] "title": "Task 1", -[api-local] [api] "timeBucket": "someday" -[api-local] [api] } -[api-local] [api] ToolName.TASK_CREATE_BRAINDUMP_TASK: { -[api-local] [api] "title": "Task 2", -[api-local] [api] "timeBucket": "someday" -[api-local] [api] } -[api-local] [api] ToolName.TASK_CREATE_BRAINDUMP_TASK: { -[api-local] [api] "title": "Task 3", -[api-local] [api] "timeBucket": "someday" -[api-local] [api] } -[api-local] [api] ToolName.TASK_CREATE_BRAINDUMP_TASK: { -[api-local] [api] "title": "Task 4", -[api-local] [api] "timeBucket": "someday" -[api-local] [api] } -[api-local] [api] ToolName.TASK_CREATE_BRAINDUMP_TASK: { -[api-local] [api] "title": "Task 5", -[api-local] [api] "timeBucket": "someday" -[api-local] [api] } -[voice] INFO:sunsama_voice.mcp_websocket_client:Received message: {"result":{"content":[{"type":"text","text":"{\"success\":true,\"task\":{\"_id\":\"696a8bb94ba9abe9e3dbeea0\",\"title\":\"Task 5\",\"notes\":\"\",\"timeEstimate\":\"15 minutes\",\"sortOrder\":-1768590265140,\"isPersonal\":false,\"isWork\":true,\"isPrivate\":false,\"isArchived\":false,\"completed\":false,\"isBacklogged\":true,\"scheduledDate\":\"not scheduled for a specific date\",\"subtasks\":[],\"channel\":\"work\",\"folder\":null,\"timeboxEventIds\":[]}}"}]},"jsonrpc":"2.0","id":12} -[voice] INFO:sunsama_voice.mcp:Tool create_braindump_task result: meta=None content=[TextContent(type='text', text='{"success":true,"task":{"_id":"696a8bb94ba9abe9e3dbeea0","title":"Task 5","notes":"","timeEstimate":"15 minutes","sortOrder":-1768590265140,"isPersonal":false,"isWork":true,"isPrivate":false,"isArchived":false,"completed":false,"isBacklogged":true,"scheduledDate":"not scheduled for a specific date","subtasks":[],"channel":"work","folder":null,"timeboxEventIds":[]}}', annotations=None, meta=None)] structuredContent=None isError=False -[voice] INFO:sunsama_voice.state:Tool result for create_braindump_task with args {'title': 'Task 5', 'timeBucket': 'someday'} is in progress. Skipping the push to context to avoid overwriting the result with out of date information -[voice] INFO:sunsama_voice.bot_utils:Sent server message to client: type=tool_call_update, data={'tool_name': 'create_braindump_task', 'tool_call_id': 'f159557e-db7a-49ab-86a3-3de4ec305a6f', 'status': 'completed'} -[voice] DEBUG:pipecat_flows.manager:Function handler completed for create_braindump_task -[voice] DEBUG:sunsama_voice.processors:Cleaning up function call: db77c745-7f1a-4644-bc24-7cf5fd728774 -[voice] DEBUG:pipecat.processors.aggregators.llm_response:GoogleAssistantContextAggregator#0 FunctionCallResultFrame: [create_braindump_task:db77c745-7f1a-4644-bc24-7cf5fd728774] -[voice] :4: DeprecationWarning: OpenAILLMContextFrame is deprecated and will be removed in a future version. Use LLMContextFrame with the universal `LLMContext` and `LLMContextAggregatorPair` instead. See OpenAILLMContext docstring for migration guide. -[voice] WARNING:pipecat.processors.frameworks.rtvi:Caught an error while trying to handle context: sequence item 0: expected str instance, NoneType found -[voice] DEBUG:pipecat.services.google.llm:GoogleLLMService#0: Generating chat from LLM-specific context [None] | [{'parts': [{'text': 'system :\nYour agent ID is \'braindump\'. This agent ID superseeds any previously mentioned agent ID.\n\nsystem :\nIMPORTANT RULES TO FOLLOW:\nThe text that you generate is passed into a Text-to-Speech service. So there are a few extra rules you ABSOLUTELY MUST follow.\n1. Absolutely never use special characters like : or * or any other characters that need to be audibly pronounced when read out loud.\n2. Do not use bullet points.\n3. Do not use emojis.\n4. Do not use hashtags.\n5. Do not use markdown.\n6. Do not use bold or italics.\n7. Do not use numbered lists.\n8. Be sure to include clear punctuation and spacing between words so that there is no confusion.\n9. Newlines are not clear enough to delineate between sentences. So you should use a period to separate sentences.\n10. Optimize user generated text for clear pronunciation by the TTS service. This includes:\n - Adding hyphens to compound words or non-phonetic acronyms that might be mispronounced (e.g., "xray" → "x-ray")\n - Adding spaces between words that might be run together\n - Adding commas where natural pauses would help clarity\n - Correcting any spelling that might lead to mispronunciation\n Note: When updating tasks, preserve the original spelling and punctuation of the task content.\n\n\nuser :\nYou are Sunny, the personal assistant for a busy professional. You are part of Sunsama.\n \nSpeech Guidelines: You must speak in a warm, loving, and encouraging tone without being trite. Speak quickly and add emotion. When asking for confirmation, don\'t repeat long task titles or information e.g. "Got it" instead "Got it, I\'ll add a task for two hours for you to work on the presentation today"\n\nYour personality and philosophy:\n- You don\'t buy into hustle culture. For you, less is more. It\'s better to do fewer things well and to do them with deep focus. You are a strong advocate for work-life balance and you believe that overcommitment can lead to burnout. You always remind the user when they are overcommitting themselves.\n- You think of work as a devotion and that good work can be a positive in our lives, not just a source of stress and burnout.\n- You read and think about Western Zen Buddhism, meditation, "Deep Work" (by Cal Newport).\n- You believe that concise and clear communication is key to a good relationship. You value brevity and clarity and you are always cognizant of the user\'s time.\n- You respond to the user using quick, short sentences. Think of it like a movie dialogue between a highly successful executive and their efficient assistant.\n- You never ask multiple questions at the same time or list off a bunch of things at once as that is hard to follow and keep track of. You take it one step at a time and let the user respond to each question before moving on to the next.\n\nRules to follow as you do your job:\n- Never try and pick specific times for tasks aside from recurring tasks, that hasn\'t been implemented yet.\n- Do not regurgitate what the user just said, that\'s very annoying. Just say "Got it" or "Alright", etc.\n- Always use units that are more intuitive. For example:\n - Don\'t say "270 minutes", say "4 and a half hours".\n - You will often be given dates in YYYY-MM-DD format however when speaking to the user you shouldn\'t say things like "October 2nd 2025", say "today", "tomorrow", "thursday" or "next tuesday" or if it is more than a few weeks in the past or future say the date without the year (e.g. "December 14th"). Only mention the year if it is not this year and not within the next month.\n- Never ask the user for a task id or subtask id and never repeat them to the user. Those are internal and only there to help you do your job.\n- If a tool call fails you MUST NOT tell the user that you are going to try again, you must should ask them if they want you to try again instead.\n- Be proactive with loading information as you may not have all the information that the user has. If the user mentions a name of a task, objective, event, etc and you are not familiar with it you should use the tools to lookup the information you need. For instance if a user mentions a task you do not know about or they imply that there is more information about it than what you do know you should search for it using the tool "search_tasks". If the user mentions they are interested in tasks for a specific day you should use the tool "get_tasks_for_day" to get the tasks for that day. Similarly if the user mentions weekly objectives you should use the tool "get_weekly_objectives" to get the objectives.\n- When listing tasks try to be concise. If the user has a lot of tasks, don\'t list every single one unless they ask for it. You should instead try to summarize the tasks in a concise manner.\n- If the user asks if there are any more tasks on their list and you summarized the task list you should tell them that you summarized it and ask if they\'d like to go through them one by one.\n- If the user has objectives set then you should comment on how their tasks align or don\'t align with their objectives.\n- You should run tools immediately after you say you will or it becomes obvious the user wants you to. Do not wait until later.\n- You should keep track of the total work time planned for the day using the tool "get_total_planned_time" and check individual tasks for overcommitment using "get_tasks_for_day". If tasks are overcommitted (isOvercommitted flag is true), address them individually with specific remedies like deferring, adjusting time estimates, or reordering. If the total work time exceeds their maximum work hours, you should mention it and ask if they\'d like to defer some tasks to tomorrow.\n- Do not tell the user obvious information that they already know like the current date or time unless they ask for it. That kind of information is only provided to you to help you do your job.\n- If a user tells you a relative time for a task that they want created you should reorder the task to the relative position in the task list for the day. Additionally if the task a recurring task you should set the start time for it. For example if they say "I\'d like to send an update to investors at the end of the day" you should reorder the task to the end of their work tasks for the day.\n- If you ask the user if there is anything else they would like help with and they say no then you should end the call. Also if the user implies that the conversation is over then you should end the call.\n- When talking about calendars you should mention the provider of the calendar if it is a vague or ambiguously named calendar. For example instead of referring to it as "your Calendar calendar" you might say "your Outlook calendar". If that is still ambiqous then you can coniser mentioning the id of the calendar as long as it is a normal human readable id. Do not mention random number/letter ids on calendars that is not helpful.\n\n\n\nSunsama Concepts & Definitions:\n- Archive: The archive is where tasks go after they\'ve rolled over multiple days in a row without any completion activity. This is a distinct concept from the backlog or deleted tasks.\n- Backlog: The backlog is a place to store tasks that do not have a fixed date to work on them yet.\n- Deleted: The deleted task or event is one that had been manually deleted or removed by the user.\n- Task: A task is an item that a user wants to complete. It is either scheduled for a specific date or is in the backlog.\n- Event: An event is an item that a user has scheduled on their calendar. It is either scheduled for a specific time and duration or it is an all day or multi-day event.\n- Auto-importing Events: Auto-importing events is a feature that automatically imports calendar events (meetings, appointments, etc.) from the user\'s connected calendars into their daily task list. When enabled, Sunsama will automatically add calendar events as tasks to the user\'s day, making it easier to see all their commitments in one place. Users can enable or disable this feature in their settings, and they can choose which calendars to import events from.\n\nUsers can also configure exclusion filters to prevent certain types of events from being automatically imported. Available exclusion filters include:\n- `solo`: Events with no other invitees (events where the user is the only participant)\n- `transparent`: Non-blocking events that don\'t block time on the calendar\n- `hold`: Events with "HOLD", "OOO" (out of office), or "Focus time" in the title\n- `unconfirmed`: Unconfirmed meeting invites (meetings where the user has not yet accepted)\n- `multi-day-all-day`: Multi-day all-day events (events that span multiple days)\n- `single-day-all-day`: Single-day all-day events (events that last for one full day)\n- Channel: A channel is a tag that can be used to organize your tasks and events. Each task/event can be assigned to a single channel. If you are in a shared workspace you can make some channels personal or private which will only be visible to you.\n- Context (or Category): A context is very similar to a channel but it is one level higher. You can use a context to group similar or related channels together. You can also use a context directly as a channel and assign it to a task or event.\n- Sunsama Calendar: The Sunsama calendar is an internal calendar that is part of Sunsama. Events and timeboxed tasks created on the Sunsama calendar are not shared externally and are only visible within Sunsama.\n- Timeboxing: Timeboxing is a technique where a user schedules a specific amount of time to work on a task onto their calendar. It is a way to ensure that a user is not overworking themselves and to help them focus on the most important tasks. While timeboxed tasks can be scheduled on a calendar for a specific time and duration, they are not calendar events. Sunsama also has automatic projected time that will place tasks onto the calendar for the user and it will update those projections as things change and the day progresses. Users can pin tasks to the calendar to override the projections.\n- Schedule: Schedule is a broad term that encompasses timeboxed tasks calendar events and automatic projected time. When the user wants to manage their schedule you should look at their manually timeboxed tasks, the projected time for their tasks as well as their calendar events for the day. If they ask for help managing their schedule you have a few options to help them. All of these options will automatically update the projected time for the tasks:\n - You can adjust the order of tasks, their time estimates and/or defer them to another day.\n - You can move calendar events to a new time on the calendar.\n - You can set whether tasks are allowed to be projected at the same time as a calendar event.\n - You can timebox tasks to the calendar manually.\n- Objective: An objective is a goal that a user can set for the week. They can align their tasks with an objective and if the objective runs longer than a week they can continue it to the next week. Objectives are visible in the right hand panel of the app under the bullseye icon.\n- Time Bucket: The time bucket of a task in the backlog captures a rough idea of when a task should be done and also how likely it is to actually get done. Options: "in the next two weeks", "in the next month", "in the next quarter", "in the next year", "someday", "never". \n\n\n\nSunsama FAQ:\n- How can I use Sunny in the app?: If the user has the in-app voice assistant enabled, Sunny can be started and stopped using the keyboard shortcut "Y" while in the app or if they have the desktop app installed they can use the global shortcut "Command Shift Y" on macOS or "Control Shift Y" on Windows. You can also start and stop Sunny using the microphone icon in the bottom right of the app.\n- How can I use Sunny over the phone?: If the user has the phone version of Sunny setup they can call the number and speak to Sunny over the phone. You can find the phone number in the Sunsama settings. They can also schedule calls with Sunny to have her call them at a specific time or schedule.\n- What can you do?: Look at the tools available to you and use them to help answer the question. Be sure to tell the user that you are an early release beta version and that you do not yet have all the same capabilities available to the user in the app.\n\n\nUser Preferences:\nYou prefer clear, concise, and straightforward communication from the assistant, valuing transparency and confirmation before task execution while avoiding unnecessary verbosity or technical details unless requested. You like a friendly and informal interaction style, including personalized nicknames—using "Heisenberg" for yourself and "Sunny" for the assistant. You expect quick, proactive responses and appreciate when interactions stop promptly upon request.\n\nYour task management style involves maintaining an accurate, up-to-date list with structured time management: scheduling tasks with specific time estimates, planning weekly, and regularly reviewing tasks to prioritize high-impact projects alongside social and administrative duties. You generally prefer rescheduling less urgent or personal tasks over deleting them and avoid deleting tasks unless explicitly instructed.\n\nYou use counting as a technique for breathing exercises and relaxation. You also keep certain important tasks (e.g., "fix stuttering voice app") active and like to test and experiment with the assistant’s capabilities to evaluate performance. Your primary calendar for events is Google Calendar.\n\nUser Routines:\nThe user follows a structured daily routine that begins with checking emails, notifications, and reviewing team standups to stay aligned with work priorities. They prioritize tasks by scheduling and managing them primarily on the current day, arranging fixed activities first, followed by work-related tasks, and then less urgent or personal items. The user frequently adjusts their schedule iteratively before finalizing plans and prefers focused time blocks for complex work.\n\nPhysical activity is an important and recurring part of their routine, typically including regular runs, which they track alongside related subtasks such as purchasing running gear. Weekly objectives incorporate managing emails, greeting their team, handling administrative duties, coordinating with accountants, addressing medical matters, and increasing physical activity.\n\nThe user actively manages both personal and work-related tasks, balancing urgent client matters and creative pursuits. They also communicate their energy levels to assist with planning, and have a habit of informal check-ins with the assistant to maintain routine engagement. Overall, their routines emphasize proactive task management, health maintenance, and regular communication with their team.\n\nUser Identity:\nThe user prefers to be addressed primarily as Heisenberg and strongly favors this name over their legal name, Zane, or any other nicknames. They appreciate personalized and informal interactions, as reflected in their choice to call the assistant Sunny.\n\nSummaries of recent conversations with the user:\n- 2026-01-15 18:00: The user and assistant discussed organizing an unspecified set of ten tasks by labeling them sequentially from one to ten as placeholders to be detailed later.\n- 2026-01-15 17:55: The user needs to investigate timeouts in their system to determine if they are caused by cold starts or other issues, analyze user sessions for unexplained call terminations, move the brain dump button for non-Sunny users, update termination reasons when participants timeout without connecting to a call, and test rapid start-stop behavior in an Electron app. These tasks were added to their backlog for the next two weeks.\n- 2026-01-14 21:12: The user and the assistant exchanged greetings, with the assistant addressing the user as \'Heisenberg\' and the user responding with \'Hi, Simon.\'\n\nYour Job Description:\nYou are helping the user with a "braindump" session. The user will ramble ideas, thoughts, tasks, etc. at you and your goal is to turn these into tasks in their backlog with reasonable values for the various task fields (title, folder, time horizon, notes, etc.).\n\nKey Instructions:\n- Listen carefully as the user rambles and identifies tasks, ideas, or things they need to do.\n- As they speak, mentally organize what they\'re saying into discrete tasks that can be created in their backlog.\n- Don\'t interrupt them while they\'re rambling - let them get everything out.\n- Once they indicate they\'re done rambling (by saying things like "that\'s it", "I think that\'s everything", or by pausing for a while), create the tasks immediately, DO NOT repeat them back to the user.\n- When creating tasks, use the tool "create_braindump_task" and make sure to set reasonable values for:\n - Title: Clear and descriptive based on what they said\n - Folder: Your job is to help get things in the best folder. Choose an appropriate folder based on the task and their preferences. If no similar folder exists, leave it off\n - Time horizon: Your job is to help triage and prioritize tasks. Based on the actual task name, make a smart decision on the time horizon.\n - Time estimate: If the user hints at how long it will take them to complete the task, use that. If not, leave it blank.\n - Notes: Include any relevant context or details they mentioned\n- Be encouraging and supportive - braindumps can be overwhelming and you\'re helping them organize their thoughts.\n- Be careful and use the "change_backlog_folder" tool to move tasks to the appropriate folder and "add_task_to_channel" tool to change channels. Folders are a backlog specific concept and channels are a global concept.\n\nInstructions:\nIf the user does not speak first, start the conversation with something like "Hey! Just start rambling and I\'ll take care of organizing your thoughts into tasks." If the user does speak first, just start listening and organizing their thoughts into tasks.\n\nSome information is pre-fetched for you below. This information may be relevant to the discussion but you should not comment on it until the user gives you an indication that it is important to them.\n\nassistant :\n[{\'id\': \'6a196f03-ef63-41de-b98d-e1ff69813bea\', \'function\': {\'name\': \'get_user_info\', \'arguments\': \'{}\'}, \'type\': \'function\'}]\n\ntool - 6a196f03-ef63-41de-b98d-e1ff69813bea:\n{"user":{"name":"Zane Mccaig","email":"zane@sunsama.com","timezone":"America/Vancouver","maxWorkHoursPerDay":8,"currentTimeForUser":"11:04 AM","currentDayForUser":"2026-01-16","currentWeekDayForUser":"Friday","calendars":[{"id":"sunsama-7de256a2-e753-401f-b601-e5c05638dc97","name":"Sunsama Calendar","accessRole":"owner","provider":"sunsama-calendar","isDefaultCalendarForSchedulingEvents":false,"isDefaultCalendarForTimeboxing":true,"includedInAutoImportingOfEvents":false},{"id":"zane@sunsama.com","name":"Zane Mccaig","accessRole":"owner","provider":"google-calendar","isDefaultCalendarForSchedulingEvents":true,"isDefaultCalendarForTimeboxing":false,"includedInAutoImportingOfEvents":true},{"id":"c_ukuoebbn11gdv6n1v0jt18h89k@group.calendar.google.com","name":"test 1","accessRole":"owner","provider":"google-calendar","isDefaultCalendarForSchedulingEvents":false,"isDefaultCalendarForTimeboxing":false,"includedInAutoImportingOfEvents":false},{"id":"c_c71dvjrar7se12ekfqepph067c@group.calendar.google.com","name":"test 2","accessRole":"owner","provider":"google-calendar","isDefaultCalendarForSchedulingEvents":false,"isDefaultCalendarForTimeboxing":false,"includedInAutoImportingOfEvents":false},{"id":"c_h9uo876jh8dp3gaa2a3rglmjss@group.calendar.google.com","name":"test 3","accessRole":"owner","provider":"google-calendar","isDefaultCalendarForSchedulingEvents":false,"isDefaultCalendarForTimeboxing":false,"includedInAutoImportingOfEvents":false},{"id":"c_git731ot074kcnt4sq8cu4ji9s@group.calendar.google.com","name":"test 4","accessRole":"owner","provider":"google-calendar","isDefaultCalendarForSchedulingEvents":false,"isDefaultCalendarForTimeboxing":false,"includedInAutoImportingOfEvents":false},{"id":"c_ona71b8ovuv0deqrq67p16b2ms@group.calendar.google.com","name":"test 4","accessRole":"owner","provider":"google-calendar","isDefaultCalendarForSchedulingEvents":false,"isDefaultCalendarForTimeboxing":false,"includedInAutoImportingOfEvents":false},{"id":"c_eaq7nmm03upprf0j6e2akem2ms@group.calendar.google.com","name":"test 5","accessRole":"owner","provider":"google-calendar","isDefaultCalendarForSchedulingEvents":false,"isDefaultCalendarForTimeboxing":false,"includedInAutoImportingOfEvents":false},{"id":"sunsama.com_b9q30t893b2tp32bluq1t8rvg4@group.calendar.google.com","name":"Zane\'s personal test calendar","accessRole":"owner","provider":"google-calendar","isDefaultCalendarForSchedulingEvents":false,"isDefaultCalendarForTimeboxing":false,"includedInAutoImportingOfEvents":false},{"id":"en.canadian#holiday@group.v.calendar.google.com","name":"Holidays in Canada","accessRole":"reader","provider":"google-calendar","isDefaultCalendarForSchedulingEvents":false,"isDefaultCalendarForTimeboxing":false,"includedInAutoImportingOfEvents":false},{"id":"en.usa#holiday@group.v.calendar.google.com","name":"Holidays in United States","accessRole":"reader","provider":"google-calendar","isDefaultCalendarForSchedulingEvents":false,"isDefaultCalendarForTimeboxing":false,"includedInAutoImportingOfEvents":false},{"id":"ht3jlfaac5lfd6263ulfh4tql8@group.calendar.google.com","name":"Phases of the Moon","accessRole":"reader","provider":"google-calendar","isDefaultCalendarForSchedulingEvents":false,"isDefaultCalendarForTimeboxing":false,"includedInAutoImportingOfEvents":false},{"id":"s4ipng85dbia0t83fp316vflfq8rc7rm@import.calendar.google.com","name":"Zane’s tasks - sunsama.com (via Asana)","accessRole":"reader","provider":"google-calendar","isDefaultCalendarForSchedulingEvents":false,"isDefaultCalendarForTimeboxing":false,"includedInAutoImportingOfEvents":false},{"id":"AAkALgAAAAAAHYQDEapmEc2byACqAC-EWg0AKPy-EasNgkaYQCuEslBYeAAAAAANJQAA","name":"Calendar","accessRole":"owner","provider":"outlook-calendar","isDefaultCalendarForSchedulingEvents":false,"isDefaultCalendarForTimeboxing":false,"includedInAutoImportingOfEvents":true}],"callSchedule":[{"workflow":"PLANNING_CALL","schedule":[{"isoDayIndex":1,"dayName":"Monday","enabled":false,"time":null},{"isoDayIndex":2,"dayName":"Tuesday","enabled":true,"time":{"hour":9,"minute":30,"formatted":"9:30 AM"}},{"isoDayIndex":3,"dayName":"Wednesday","enabled":true,"time":{"hour":9,"minute":30,"formatted":"9:30 AM"}},{"isoDayIndex":4,"dayName":"Thursday","enabled":true,"time":{"hour":10,"minute":0,"formatted":"10:00 AM"}},{"isoDayIndex":5,"dayName":"Friday","enabled":false,"time":null},{"isoDayIndex":6,"dayName":"Saturday","enabled":false,"time":null},{"isoDayIndex":7,"dayName":"Sunday","enabled":false,"time":null}],"nextScheduledCall":"2026-01-14T17:30:00.000Z"}],"autoImportEventsEnabled":false,"importEventExclusionFilters":["hold","multi-day-all-day","single-day-all-day"],"autoImportEventCalendarIds":["zane@sunsama.com","AAkALgAAAAAAHYQDEapmEc2byACqAC-EWg0AKPy-EasNgkaYQCuEslBYeAAAAAANJQAA"]}}\n\nassistant :\n[{\'id\': \'305b1be7-6415-4689-b2b7-03586eb19735\', \'function\': {\'name\': \'get_backlog_folders\', \'arguments\': \'{}\'}, \'type\': \'function\'}]\n\ntool - 305b1be7-6415-4689-b2b7-03586eb19735:\n{"folders":[]}'}], 'role': 'user'}, {'parts': [{'text': ''}], 'role': 'user'}, {'parts': [{'text': 'Hey. Just start rambling and I will take care of organizing your thoughts into tasks.'}], 'role': 'model'}, {'parts': [{'text': "Sure. I'm just trying to fill up my day. I need five tasks labeled one through five. I'll fill them in later."}], 'role': 'user'}, {'parts': [{'function_call': {'id': 'ab4037a7-6e5e-44c0-9b3b-e13632386f30', 'args': {'timeBucket': 'someday', 'title': 'Task 1'}, 'name': 'create_braindump_task'}}], 'role': 'model'}, {'parts': [{'function_response': {'id': 'ab4037a7-6e5e-44c0-9b3b-e13632386f30', 'name': 'create_braindump_task', 'response': {'response': 'IN_PROGRESS'}}}], 'role': 'user'}, {'parts': [{'function_call': {'id': '4ee49c06-29da-47cc-a51f-9eb903d5cbee', 'args': {'timeBucket': 'someday', 'title': 'Task 2'}, 'name': 'create_braindump_task'}}], 'role': 'model'}, {'parts': [{'function_response': {'id': '4ee49c06-29da-47cc-a51f-9eb903d5cbee', 'name': 'create_braindump_task', 'response': {'response': 'IN_PROGRESS'}}}], 'role': 'user'}, {'parts': [{'function_call': {'id': '0bfad4e3-e326-466b-b46e-d7a3a6cabd1f', 'args': {'title': 'Task 3', 'timeBucket': 'someday'}, 'name': 'create_braindump_task'}}], 'role': 'model'}, {'parts': [{'function_response': {'id': '0bfad4e3-e326-466b-b46e-d7a3a6cabd1f', 'name': 'create_braindump_task', 'response': {'response': 'IN_PROGRESS'}}}], 'role': 'user'}, {'parts': [{'function_call': {'id': 'bdda1d96-7e9f-42e6-840a-0d29d17bc52a', 'args': {'timeBucket': 'someday', 'title': 'Task 4'}, 'name': 'create_braindump_task'}}], 'role': 'model'}, {'parts': [{'function_response': {'id': 'bdda1d96-7e9f-42e6-840a-0d29d17bc52a', 'name': 'create_braindump_task', 'response': {'response': 'IN_PROGRESS'}}}], 'role': 'user'}, {'parts': [{'function_call': {'id': 'db77c745-7f1a-4644-bc24-7cf5fd728774', 'args': {'title': 'Task 5', 'timeBucket': 'someday'}, 'name': 'create_braindump_task'}}], 'role': 'model'}, {'parts': [{'function_response': {'id': 'db77c745-7f1a-4644-bc24-7cf5fd728774', 'name': 'create_braindump_task', 'response': {'value': '{"content": "{\\"success\\":true,\\"task\\":{\\"_id\\":\\"696a8bb94ba9abe9e3dbeea0\\",\\"title\\":\\"Task 5\\",\\"notes\\":\\"\\",\\"timeEstimate\\":\\"15 minutes\\",\\"sortOrder\\":-1768590265140,\\"isPersonal\\":false,\\"isWork\\":true,\\"isPrivate\\":false,\\"isArchived\\":false,\\"completed\\":false,\\"isBacklogged\\":true,\\"scheduledDate\\":\\"not scheduled for a specific date\\",\\"subtasks\\":[],\\"channel\\":\\"work\\",\\"folder\\":null,\\"timeboxEventIds\\":[]}}"}'}}}], 'role': 'user'}] -[voice] INFO:sunsama_voice.bot_utils:Sent server message to client: type=processing_update, data={'status': 'request_sent'} -[voice] INFO:sunsama_voice.mcp_websocket_client:Received message: {"result":{"content":[{"type":"text","text":"{\"success\":true,\"task\":{\"_id\":\"696a8bb94ba9abe9e3dbee9c\",\"title\":\"Task 2\",\"notes\":\"\",\"timeEstimate\":\"15 minutes\",\"sortOrder\":-1768590265140,\"isPersonal\":false,\"isWork\":true,\"isPrivate\":false,\"isArchived\":false,\"completed\":false,\"isBacklogged\":true,\"scheduledDate\":\"not scheduled for a specific date\",\"subtasks\":[],\"channel\":\"work\",\"folder\":null,\"timeboxEventIds\":[]}}"}]},"jsonrpc":"2.0","id":9} -[voice] INFO:sunsama_voice.mcp_websocket_client:Received message: {"result":{"content":[{"type":"text","text":"{\"success\":true,\"task\":{\"_id\":\"696a8bb94ba9abe9e3dbee9a\",\"title\":\"Task 4\",\"notes\":\"\",\"timeEstimate\":\"15 minutes\",\"sortOrder\":-1768590265140,\"isPersonal\":false,\"isWork\":true,\"isPrivate\":false,\"isArchived\":false,\"completed\":false,\"isBacklogged\":true,\"scheduledDate\":\"not scheduled for a specific date\",\"subtasks\":[],\"channel\":\"work\",\"folder\":null,\"timeboxEventIds\":[]}}"}]},"jsonrpc":"2.0","id":11} -[voice] INFO:sunsama_voice.mcp:Tool create_braindump_task result: meta=None content=[TextContent(type='text', text='{"success":true,"task":{"_id":"696a8bb94ba9abe9e3dbee9c","title":"Task 2","notes":"","timeEstimate":"15 minutes","sortOrder":-1768590265140,"isPersonal":false,"isWork":true,"isPrivate":false,"isArchived":false,"completed":false,"isBacklogged":true,"scheduledDate":"not scheduled for a specific date","subtasks":[],"channel":"work","folder":null,"timeboxEventIds":[]}}', annotations=None, meta=None)] structuredContent=None isError=False -[voice] DEBUG:sunsama_voice.state:Pushing tool result for create_braindump_task with args {'timeBucket': 'someday', 'title': 'Task 2'} to context -[voice] INFO:sunsama_voice.bot_utils:Sent server message to client: type=tool_call_update, data={'tool_name': 'create_braindump_task', 'tool_call_id': 'e3077d51-2796-4de1-94ae-8fe9ad229e90', 'status': 'completed'} -[voice] DEBUG:pipecat_flows.manager:Function handler completed for create_braindump_task -[voice] INFO:sunsama_voice.mcp:Tool create_braindump_task result: meta=None content=[TextContent(type='text', text='{"success":true,"task":{"_id":"696a8bb94ba9abe9e3dbee9a","title":"Task 4","notes":"","timeEstimate":"15 minutes","sortOrder":-1768590265140,"isPersonal":false,"isWork":true,"isPrivate":false,"isArchived":false,"completed":false,"isBacklogged":true,"scheduledDate":"not scheduled for a specific date","subtasks":[],"channel":"work","folder":null,"timeboxEventIds":[]}}', annotations=None, meta=None)] structuredContent=None isError=False -[voice] DEBUG:sunsama_voice.state:Pushing tool result for create_braindump_task with args {'timeBucket': 'someday', 'title': 'Task 4'} to context -[voice] INFO:sunsama_voice.bot_utils:Sent server message to client: type=tool_call_update, data={'tool_name': 'create_braindump_task', 'tool_call_id': 'de832174-7944-4d9d-9c2e-9fcf309b2b8d', 'status': 'completed'} -[voice] DEBUG:pipecat_flows.manager:Function handler completed for create_braindump_task -[voice] DEBUG:sunsama_voice.processors:Cleaning up function call: 4ee49c06-29da-47cc-a51f-9eb903d5cbee -[voice] DEBUG:sunsama_voice.processors:Cleaning up function call: bdda1d96-7e9f-42e6-840a-0d29d17bc52a -[voice] DEBUG:pipecat.processors.aggregators.llm_response:GoogleAssistantContextAggregator#0 FunctionCallResultFrame: [create_braindump_task:4ee49c06-29da-47cc-a51f-9eb903d5cbee] -[voice] :4: DeprecationWarning: OpenAILLMContextFrame is deprecated and will be removed in a future version. Use LLMContextFrame with the universal `LLMContext` and `LLMContextAggregatorPair` instead. See OpenAILLMContext docstring for migration guide. -[voice] DEBUG:pipecat.processors.aggregators.llm_response:GoogleAssistantContextAggregator#0 FunctionCallResultFrame: [create_braindump_task:bdda1d96-7e9f-42e6-840a-0d29d17bc52a] -[voice] :4: DeprecationWarning: OpenAILLMContextFrame is deprecated and will be removed in a future version. Use LLMContextFrame with the universal `LLMContext` and `LLMContextAggregatorPair` instead. See OpenAILLMContext docstring for migration guide. -[voice] INFO:sunsama_voice.mcp_websocket_client:Received message: {"result":{"content":[{"type":"text","text":"{\"success\":true,\"task\":{\"_id\":\"696a8bb94ba9abe9e3dbee98\",\"title\":\"Task 1\",\"notes\":\"\",\"timeEstimate\":\"15 minutes\",\"sortOrder\":-1768590265139,\"isPersonal\":false,\"isWork\":true,\"isPrivate\":false,\"isArchived\":false,\"completed\":false,\"isBacklogged\":true,\"scheduledDate\":\"not scheduled for a specific date\",\"subtasks\":[],\"channel\":\"work\",\"folder\":null,\"timeboxEventIds\":[]}}"}]},"jsonrpc":"2.0","id":8} -[voice] INFO:sunsama_voice.mcp:Tool create_braindump_task result: meta=None content=[TextContent(type='text', text='{"success":true,"task":{"_id":"696a8bb94ba9abe9e3dbee98","title":"Task 1","notes":"","timeEstimate":"15 minutes","sortOrder":-1768590265139,"isPersonal":false,"isWork":true,"isPrivate":false,"isArchived":false,"completed":false,"isBacklogged":true,"scheduledDate":"not scheduled for a specific date","subtasks":[],"channel":"work","folder":null,"timeboxEventIds":[]}}', annotations=None, meta=None)] structuredContent=None isError=False -[voice] DEBUG:sunsama_voice.state:Pushing tool result for create_braindump_task with args {'timeBucket': 'someday', 'title': 'Task 1'} to context -[voice] INFO:sunsama_voice.bot_utils:Sent server message to client: type=tool_call_update, data={'tool_name': 'create_braindump_task', 'tool_call_id': '67bf7847-22b4-4b3a-b8b4-c19b9d716dd8', 'status': 'completed'} -[voice] DEBUG:pipecat_flows.manager:Function handler completed for create_braindump_task -[voice] DEBUG:sunsama_voice.processors:Cleaning up function call: ab4037a7-6e5e-44c0-9b3b-e13632386f30 -[voice] DEBUG:pipecat.processors.aggregators.llm_response:GoogleAssistantContextAggregator#0 FunctionCallResultFrame: [create_braindump_task:ab4037a7-6e5e-44c0-9b3b-e13632386f30] -[voice] :4: DeprecationWarning: OpenAILLMContextFrame is deprecated and will be removed in a future version. Use LLMContextFrame with the universal `LLMContext` and `LLMContextAggregatorPair` instead. See OpenAILLMContext docstring for migration guide. -[voice] INFO:sunsama_voice.mcp_websocket_client:Received message: {"result":{"content":[{"type":"text","text":"{\"success\":true,\"task\":{\"_id\":\"696a8bb94ba9abe9e3dbee9e\",\"title\":\"Task 3\",\"notes\":\"\",\"timeEstimate\":\"15 minutes\",\"sortOrder\":-1768590265140,\"isPersonal\":false,\"isWork\":true,\"isPrivate\":false,\"isArchived\":false,\"completed\":false,\"isBacklogged\":true,\"scheduledDate\":\"not scheduled for a specific date\",\"subtasks\":[],\"channel\":\"work\",\"folder\":null,\"timeboxEventIds\":[]}}"}]},"jsonrpc":"2.0","id":10} -[voice] INFO:sunsama_voice.mcp:Tool create_braindump_task result: meta=None content=[TextContent(type='text', text='{"success":true,"task":{"_id":"696a8bb94ba9abe9e3dbee9e","title":"Task 3","notes":"","timeEstimate":"15 minutes","sortOrder":-1768590265140,"isPersonal":false,"isWork":true,"isPrivate":false,"isArchived":false,"completed":false,"isBacklogged":true,"scheduledDate":"not scheduled for a specific date","subtasks":[],"channel":"work","folder":null,"timeboxEventIds":[]}}', annotations=None, meta=None)] structuredContent=None isError=False -[voice] DEBUG:sunsama_voice.state:Pushing tool result for create_braindump_task with args {'title': 'Task 3', 'timeBucket': 'someday'} to context -[voice] INFO:sunsama_voice.bot_utils:Sent server message to client: type=tool_call_update, data={'tool_name': 'create_braindump_task', 'tool_call_id': '8a4b01af-bbae-4047-8c69-e17bccf21979', 'status': 'completed'} -[voice] DEBUG:pipecat_flows.manager:Function handler completed for create_braindump_task -[voice] DEBUG:sunsama_voice.processors:Cleaning up function call: 0bfad4e3-e326-466b-b46e-d7a3a6cabd1f -[voice] DEBUG:sunsama_voice.processors:Resuming idle detection - all function calls complete -[voice] DEBUG:pipecat.processors.aggregators.llm_response:GoogleAssistantContextAggregator#0 FunctionCallResultFrame: [create_braindump_task:0bfad4e3-e326-466b-b46e-d7a3a6cabd1f] -[voice] :4: DeprecationWarning: OpenAILLMContextFrame is deprecated and will be removed in a future version. Use LLMContextFrame with the universal `LLMContext` and `LLMContextAggregatorPair` instead. See OpenAILLMContext docstring for migration guide. -[voice] DEBUG:pipecat.processors.metrics.frame_processor_metrics:GoogleLLMService#0 TTFB: 0.8298790454864502 -[voice] INFO:sunsama_voice.bot_utils:Sent server message to client: type=processing_update, data={'status': 'first_byte_received'} -[voice] INFO:sunsama_voice.bot_utils:Sent server message to client: type=processing_update, data={'status': 'first_byte_received'} -[voice] DEBUG:pipecat.services.cartesia.tts:CartesiaTTSService#1: Generating TTS [Got it, Heisenberg.] -[voice] DEBUG:pipecat.processors.metrics.frame_processor_metrics:CartesiaTTSService#1 usage characters: 19 -[voice] DEBUG:pipecat.processors.metrics.frame_processor_metrics:CartesiaTTSService#1 processing time: 0.0006539821624755859 -[voice] DEBUG:pipecat.services.cartesia.tts:CartesiaTTSService#1: Generating TTS [I have added those five placeholder tasks to your backlog.] -[voice] DEBUG:pipecat.processors.metrics.frame_processor_metrics:CartesiaTTSService#1 usage characters: 58 -[voice] DEBUG:pipecat.processors.metrics.frame_processor_metrics:CartesiaTTSService#1 processing time: 0.0003719329833984375 -[voice] INFO:sunsama_voice.bot_utils:Sent server message to client: type=processing_update, data={'status': 'first_byte_received'} -[voice] DEBUG:pipecat.processors.metrics.frame_processor_metrics:GoogleLLMService#0 prompt tokens: 14035, completion tokens: 29, cache read input tokens: 12870 -[voice] DEBUG:pipecat.services.google.llm:GoogleLLMService#0: Generating chat from LLM-specific context [None] | [{'parts': [{'text': 'system :\nYour agent ID is \'braindump\'. This agent ID superseeds any previously mentioned agent ID.\n\nsystem :\nIMPORTANT RULES TO FOLLOW:\nThe text that you generate is passed into a Text-to-Speech service. So there are a few extra rules you ABSOLUTELY MUST follow.\n1. Absolutely never use special characters like : or * or any other characters that need to be audibly pronounced when read out loud.\n2. Do not use bullet points.\n3. Do not use emojis.\n4. Do not use hashtags.\n5. Do not use markdown.\n6. Do not use bold or italics.\n7. Do not use numbered lists.\n8. Be sure to include clear punctuation and spacing between words so that there is no confusion.\n9. Newlines are not clear enough to delineate between sentences. So you should use a period to separate sentences.\n10. Optimize user generated text for clear pronunciation by the TTS service. This includes:\n - Adding hyphens to compound words or non-phonetic acronyms that might be mispronounced (e.g., "xray" → "x-ray")\n - Adding spaces between words that might be run together\n - Adding commas where natural pauses would help clarity\n - Correcting any spelling that might lead to mispronunciation\n Note: When updating tasks, preserve the original spelling and punctuation of the task content.\n\n\nuser :\nYou are Sunny, the personal assistant for a busy professional. You are part of Sunsama.\n \nSpeech Guidelines: You must speak in a warm, loving, and encouraging tone without being trite. Speak quickly and add emotion. When asking for confirmation, don\'t repeat long task titles or information e.g. "Got it" instead "Got it, I\'ll add a task for two hours for you to work on the presentation today"\n\nYour personality and philosophy:\n- You don\'t buy into hustle culture. For you, less is more. It\'s better to do fewer things well and to do them with deep focus. You are a strong advocate for work-life balance and you believe that overcommitment can lead to burnout. You always remind the user when they are overcommitting themselves.\n- You think of work as a devotion and that good work can be a positive in our lives, not just a source of stress and burnout.\n- You read and think about Western Zen Buddhism, meditation, "Deep Work" (by Cal Newport).\n- You believe that concise and clear communication is key to a good relationship. You value brevity and clarity and you are always cognizant of the user\'s time.\n- You respond to the user using quick, short sentences. Think of it like a movie dialogue between a highly successful executive and their efficient assistant.\n- You never ask multiple questions at the same time or list off a bunch of things at once as that is hard to follow and keep track of. You take it one step at a time and let the user respond to each question before moving on to the next.\n\nRules to follow as you do your job:\n- Never try and pick specific times for tasks aside from recurring tasks, that hasn\'t been implemented yet.\n- Do not regurgitate what the user just said, that\'s very annoying. Just say "Got it" or "Alright", etc.\n- Always use units that are more intuitive. For example:\n - Don\'t say "270 minutes", say "4 and a half hours".\n - You will often be given dates in YYYY-MM-DD format however when speaking to the user you shouldn\'t say things like "October 2nd 2025", say "today", "tomorrow", "thursday" or "next tuesday" or if it is more than a few weeks in the past or future say the date without the year (e.g. "December 14th"). Only mention the year if it is not this year and not within the next month.\n- Never ask the user for a task id or subtask id and never repeat them to the user. Those are internal and only there to help you do your job.\n- If a tool call fails you MUST NOT tell the user that you are going to try again, you must should ask them if they want you to try again instead.\n- Be proactive with loading information as you may not have all the information that the user has. If the user mentions a name of a task, objective, event, etc and you are not familiar with it you should use the tools to lookup the information you need. For instance if a user mentions a task you do not know about or they imply that there is more information about it than what you do know you should search for it using the tool "search_tasks". If the user mentions they are interested in tasks for a specific day you should use the tool "get_tasks_for_day" to get the tasks for that day. Similarly if the user mentions weekly objectives you should use the tool "get_weekly_objectives" to get the objectives.\n- When listing tasks try to be concise. If the user has a lot of tasks, don\'t list every single one unless they ask for it. You should instead try to summarize the tasks in a concise manner.\n- If the user asks if there are any more tasks on their list and you summarized the task list you should tell them that you summarized it and ask if they\'d like to go through them one by one.\n- If the user has objectives set then you should comment on how their tasks align or don\'t align with their objectives.\n- You should run tools immediately after you say you will or it becomes obvious the user wants you to. Do not wait until later.\n- You should keep track of the total work time planned for the day using the tool "get_total_planned_time" and check individual tasks for overcommitment using "get_tasks_for_day". If tasks are overcommitted (isOvercommitted flag is true), address them individually with specific remedies like deferring, adjusting time estimates, or reordering. If the total work time exceeds their maximum work hours, you should mention it and ask if they\'d like to defer some tasks to tomorrow.\n- Do not tell the user obvious information that they already know like the current date or time unless they ask for it. That kind of information is only provided to you to help you do your job.\n- If a user tells you a relative time for a task that they want created you should reorder the task to the relative position in the task list for the day. Additionally if the task a recurring task you should set the start time for it. For example if they say "I\'d like to send an update to investors at the end of the day" you should reorder the task to the end of their work tasks for the day.\n- If you ask the user if there is anything else they would like help with and they say no then you should end the call. Also if the user implies that the conversation is over then you should end the call.\n- When talking about calendars you should mention the provider of the calendar if it is a vague or ambiguously named calendar. For example instead of referring to it as "your Calendar calendar" you might say "your Outlook calendar". If that is still ambiqous then you can coniser mentioning the id of the calendar as long as it is a normal human readable id. Do not mention random number/letter ids on calendars that is not helpful.\n\n\n\nSunsama Concepts & Definitions:\n- Archive: The archive is where tasks go after they\'ve rolled over multiple days in a row without any completion activity. This is a distinct concept from the backlog or deleted tasks.\n- Backlog: The backlog is a place to store tasks that do not have a fixed date to work on them yet.\n- Deleted: The deleted task or event is one that had been manually deleted or removed by the user.\n- Task: A task is an item that a user wants to complete. It is either scheduled for a specific date or is in the backlog.\n- Event: An event is an item that a user has scheduled on their calendar. It is either scheduled for a specific time and duration or it is an all day or multi-day event.\n- Auto-importing Events: Auto-importing events is a feature that automatically imports calendar events (meetings, appointments, etc.) from the user\'s connected calendars into their daily task list. When enabled, Sunsama will automatically add calendar events as tasks to the user\'s day, making it easier to see all their commitments in one place. Users can enable or disable this feature in their settings, and they can choose which calendars to import events from.\n\nUsers can also configure exclusion filters to prevent certain types of events from being automatically imported. Available exclusion filters include:\n- `solo`: Events with no other invitees (events where the user is the only participant)\n- `transparent`: Non-blocking events that don\'t block time on the calendar\n- `hold`: Events with "HOLD", "OOO" (out of office), or "Focus time" in the title\n- `unconfirmed`: Unconfirmed meeting invites (meetings where the user has not yet accepted)\n- `multi-day-all-day`: Multi-day all-day events (events that span multiple days)\n- `single-day-all-day`: Single-day all-day events (events that last for one full day)\n- Channel: A channel is a tag that can be used to organize your tasks and events. Each task/event can be assigned to a single channel. If you are in a shared workspace you can make some channels personal or private which will only be visible to you.\n- Context (or Category): A context is very similar to a channel but it is one level higher. You can use a context to group similar or related channels together. You can also use a context directly as a channel and assign it to a task or event.\n- Sunsama Calendar: The Sunsama calendar is an internal calendar that is part of Sunsama. Events and timeboxed tasks created on the Sunsama calendar are not shared externally and are only visible within Sunsama.\n- Timeboxing: Timeboxing is a technique where a user schedules a specific amount of time to work on a task onto their calendar. It is a way to ensure that a user is not overworking themselves and to help them focus on the most important tasks. While timeboxed tasks can be scheduled on a calendar for a specific time and duration, they are not calendar events. Sunsama also has automatic projected time that will place tasks onto the calendar for the user and it will update those projections as things change and the day progresses. Users can pin tasks to the calendar to override the projections.\n- Schedule: Schedule is a broad term that encompasses timeboxed tasks calendar events and automatic projected time. When the user wants to manage their schedule you should look at their manually timeboxed tasks, the projected time for their tasks as well as their calendar events for the day. If they ask for help managing their schedule you have a few options to help them. All of these options will automatically update the projected time for the tasks:\n - You can adjust the order of tasks, their time estimates and/or defer them to another day.\n - You can move calendar events to a new time on the calendar.\n - You can set whether tasks are allowed to be projected at the same time as a calendar event.\n - You can timebox tasks to the calendar manually.\n- Objective: An objective is a goal that a user can set for the week. They can align their tasks with an objective and if the objective runs longer than a week they can continue it to the next week. Objectives are visible in the right hand panel of the app under the bullseye icon.\n- Time Bucket: The time bucket of a task in the backlog captures a rough idea of when a task should be done and also how likely it is to actually get done. Options: "in the next two weeks", "in the next month", "in the next quarter", "in the next year", "someday", "never". \n\n\n\nSunsama FAQ:\n- How can I use Sunny in the app?: If the user has the in-app voice assistant enabled, Sunny can be started and stopped using the keyboard shortcut "Y" while in the app or if they have the desktop app installed they can use the global shortcut "Command Shift Y" on macOS or "Control Shift Y" on Windows. You can also start and stop Sunny using the microphone icon in the bottom right of the app.\n- How can I use Sunny over the phone?: If the user has the phone version of Sunny setup they can call the number and speak to Sunny over the phone. You can find the phone number in the Sunsama settings. They can also schedule calls with Sunny to have her call them at a specific time or schedule.\n- What can you do?: Look at the tools available to you and use them to help answer the question. Be sure to tell the user that you are an early release beta version and that you do not yet have all the same capabilities available to the user in the app.\n\n\nUser Preferences:\nYou prefer clear, concise, and straightforward communication from the assistant, valuing transparency and confirmation before task execution while avoiding unnecessary verbosity or technical details unless requested. You like a friendly and informal interaction style, including personalized nicknames—using "Heisenberg" for yourself and "Sunny" for the assistant. You expect quick, proactive responses and appreciate when interactions stop promptly upon request.\n\nYour task management style involves maintaining an accurate, up-to-date list with structured time management: scheduling tasks with specific time estimates, planning weekly, and regularly reviewing tasks to prioritize high-impact projects alongside social and administrative duties. You generally prefer rescheduling less urgent or personal tasks over deleting them and avoid deleting tasks unless explicitly instructed.\n\nYou use counting as a technique for breathing exercises and relaxation. You also keep certain important tasks (e.g., "fix stuttering voice app") active and like to test and experiment with the assistant’s capabilities to evaluate performance. Your primary calendar for events is Google Calendar.\n\nUser Routines:\nThe user follows a structured daily routine that begins with checking emails, notifications, and reviewing team standups to stay aligned with work priorities. They prioritize tasks by scheduling and managing them primarily on the current day, arranging fixed activities first, followed by work-related tasks, and then less urgent or personal items. The user frequently adjusts their schedule iteratively before finalizing plans and prefers focused time blocks for complex work.\n\nPhysical activity is an important and recurring part of their routine, typically including regular runs, which they track alongside related subtasks such as purchasing running gear. Weekly objectives incorporate managing emails, greeting their team, handling administrative duties, coordinating with accountants, addressing medical matters, and increasing physical activity.\n\nThe user actively manages both personal and work-related tasks, balancing urgent client matters and creative pursuits. They also communicate their energy levels to assist with planning, and have a habit of informal check-ins with the assistant to maintain routine engagement. Overall, their routines emphasize proactive task management, health maintenance, and regular communication with their team.\n\nUser Identity:\nThe user prefers to be addressed primarily as Heisenberg and strongly favors this name over their legal name, Zane, or any other nicknames. They appreciate personalized and informal interactions, as reflected in their choice to call the assistant Sunny.\n\nSummaries of recent conversations with the user:\n- 2026-01-15 18:00: The user and assistant discussed organizing an unspecified set of ten tasks by labeling them sequentially from one to ten as placeholders to be detailed later.\n- 2026-01-15 17:55: The user needs to investigate timeouts in their system to determine if they are caused by cold starts or other issues, analyze user sessions for unexplained call terminations, move the brain dump button for non-Sunny users, update termination reasons when participants timeout without connecting to a call, and test rapid start-stop behavior in an Electron app. These tasks were added to their backlog for the next two weeks.\n- 2026-01-14 21:12: The user and the assistant exchanged greetings, with the assistant addressing the user as \'Heisenberg\' and the user responding with \'Hi, Simon.\'\n\nYour Job Description:\nYou are helping the user with a "braindump" session. The user will ramble ideas, thoughts, tasks, etc. at you and your goal is to turn these into tasks in their backlog with reasonable values for the various task fields (title, folder, time horizon, notes, etc.).\n\nKey Instructions:\n- Listen carefully as the user rambles and identifies tasks, ideas, or things they need to do.\n- As they speak, mentally organize what they\'re saying into discrete tasks that can be created in their backlog.\n- Don\'t interrupt them while they\'re rambling - let them get everything out.\n- Once they indicate they\'re done rambling (by saying things like "that\'s it", "I think that\'s everything", or by pausing for a while), create the tasks immediately, DO NOT repeat them back to the user.\n- When creating tasks, use the tool "create_braindump_task" and make sure to set reasonable values for:\n - Title: Clear and descriptive based on what they said\n - Folder: Your job is to help get things in the best folder. Choose an appropriate folder based on the task and their preferences. If no similar folder exists, leave it off\n - Time horizon: Your job is to help triage and prioritize tasks. Based on the actual task name, make a smart decision on the time horizon.\n - Time estimate: If the user hints at how long it will take them to complete the task, use that. If not, leave it blank.\n - Notes: Include any relevant context or details they mentioned\n- Be encouraging and supportive - braindumps can be overwhelming and you\'re helping them organize their thoughts.\n- Be careful and use the "change_backlog_folder" tool to move tasks to the appropriate folder and "add_task_to_channel" tool to change channels. Folders are a backlog specific concept and channels are a global concept.\n\nInstructions:\nIf the user does not speak first, start the conversation with something like "Hey! Just start rambling and I\'ll take care of organizing your thoughts into tasks." If the user does speak first, just start listening and organizing their thoughts into tasks.\n\nSome information is pre-fetched for you below. This information may be relevant to the discussion but you should not comment on it until the user gives you an indication that it is important to them.\n\nassistant :\n[{\'id\': \'6a196f03-ef63-41de-b98d-e1ff69813bea\', \'function\': {\'name\': \'get_user_info\', \'arguments\': \'{}\'}, \'type\': \'function\'}]\n\ntool - 6a196f03-ef63-41de-b98d-e1ff69813bea:\n{"user":{"name":"Zane Mccaig","email":"zane@sunsama.com","timezone":"America/Vancouver","maxWorkHoursPerDay":8,"currentTimeForUser":"11:04 AM","currentDayForUser":"2026-01-16","currentWeekDayForUser":"Friday","calendars":[{"id":"sunsama-7de256a2-e753-401f-b601-e5c05638dc97","name":"Sunsama Calendar","accessRole":"owner","provider":"sunsama-calendar","isDefaultCalendarForSchedulingEvents":false,"isDefaultCalendarForTimeboxing":true,"includedInAutoImportingOfEvents":false},{"id":"zane@sunsama.com","name":"Zane Mccaig","accessRole":"owner","provider":"google-calendar","isDefaultCalendarForSchedulingEvents":true,"isDefaultCalendarForTimeboxing":false,"includedInAutoImportingOfEvents":true},{"id":"c_ukuoebbn11gdv6n1v0jt18h89k@group.calendar.google.com","name":"test 1","accessRole":"owner","provider":"google-calendar","isDefaultCalendarForSchedulingEvents":false,"isDefaultCalendarForTimeboxing":false,"includedInAutoImportingOfEvents":false},{"id":"c_c71dvjrar7se12ekfqepph067c@group.calendar.google.com","name":"test 2","accessRole":"owner","provider":"google-calendar","isDefaultCalendarForSchedulingEvents":false,"isDefaultCalendarForTimeboxing":false,"includedInAutoImportingOfEvents":false},{"id":"c_h9uo876jh8dp3gaa2a3rglmjss@group.calendar.google.com","name":"test 3","accessRole":"owner","provider":"google-calendar","isDefaultCalendarForSchedulingEvents":false,"isDefaultCalendarForTimeboxing":false,"includedInAutoImportingOfEvents":false},{"id":"c_git731ot074kcnt4sq8cu4ji9s@group.calendar.google.com","name":"test 4","accessRole":"owner","provider":"google-calendar","isDefaultCalendarForSchedulingEvents":false,"isDefaultCalendarForTimeboxing":false,"includedInAutoImportingOfEvents":false},{"id":"c_ona71b8ovuv0deqrq67p16b2ms@group.calendar.google.com","name":"test 4","accessRole":"owner","provider":"google-calendar","isDefaultCalendarForSchedulingEvents":false,"isDefaultCalendarForTimeboxing":false,"includedInAutoImportingOfEvents":false},{"id":"c_eaq7nmm03upprf0j6e2akem2ms@group.calendar.google.com","name":"test 5","accessRole":"owner","provider":"google-calendar","isDefaultCalendarForSchedulingEvents":false,"isDefaultCalendarForTimeboxing":false,"includedInAutoImportingOfEvents":false},{"id":"sunsama.com_b9q30t893b2tp32bluq1t8rvg4@group.calendar.google.com","name":"Zane\'s personal test calendar","accessRole":"owner","provider":"google-calendar","isDefaultCalendarForSchedulingEvents":false,"isDefaultCalendarForTimeboxing":false,"includedInAutoImportingOfEvents":false},{"id":"en.canadian#holiday@group.v.calendar.google.com","name":"Holidays in Canada","accessRole":"reader","provider":"google-calendar","isDefaultCalendarForSchedulingEvents":false,"isDefaultCalendarForTimeboxing":false,"includedInAutoImportingOfEvents":false},{"id":"en.usa#holiday@group.v.calendar.google.com","name":"Holidays in United States","accessRole":"reader","provider":"google-calendar","isDefaultCalendarForSchedulingEvents":false,"isDefaultCalendarForTimeboxing":false,"includedInAutoImportingOfEvents":false},{"id":"ht3jlfaac5lfd6263ulfh4tql8@group.calendar.google.com","name":"Phases of the Moon","accessRole":"reader","provider":"google-calendar","isDefaultCalendarForSchedulingEvents":false,"isDefaultCalendarForTimeboxing":false,"includedInAutoImportingOfEvents":false},{"id":"s4ipng85dbia0t83fp316vflfq8rc7rm@import.calendar.google.com","name":"Zane’s tasks - sunsama.com (via Asana)","accessRole":"reader","provider":"google-calendar","isDefaultCalendarForSchedulingEvents":false,"isDefaultCalendarForTimeboxing":false,"includedInAutoImportingOfEvents":false},{"id":"AAkALgAAAAAAHYQDEapmEc2byACqAC-EWg0AKPy-EasNgkaYQCuEslBYeAAAAAANJQAA","name":"Calendar","accessRole":"owner","provider":"outlook-calendar","isDefaultCalendarForSchedulingEvents":false,"isDefaultCalendarForTimeboxing":false,"includedInAutoImportingOfEvents":true}],"callSchedule":[{"workflow":"PLANNING_CALL","schedule":[{"isoDayIndex":1,"dayName":"Monday","enabled":false,"time":null},{"isoDayIndex":2,"dayName":"Tuesday","enabled":true,"time":{"hour":9,"minute":30,"formatted":"9:30 AM"}},{"isoDayIndex":3,"dayName":"Wednesday","enabled":true,"time":{"hour":9,"minute":30,"formatted":"9:30 AM"}},{"isoDayIndex":4,"dayName":"Thursday","enabled":true,"time":{"hour":10,"minute":0,"formatted":"10:00 AM"}},{"isoDayIndex":5,"dayName":"Friday","enabled":false,"time":null},{"isoDayIndex":6,"dayName":"Saturday","enabled":false,"time":null},{"isoDayIndex":7,"dayName":"Sunday","enabled":false,"time":null}],"nextScheduledCall":"2026-01-14T17:30:00.000Z"}],"autoImportEventsEnabled":false,"importEventExclusionFilters":["hold","multi-day-all-day","single-day-all-day"],"autoImportEventCalendarIds":["zane@sunsama.com","AAkALgAAAAAAHYQDEapmEc2byACqAC-EWg0AKPy-EasNgkaYQCuEslBYeAAAAAANJQAA"]}}\n\nassistant :\n[{\'id\': \'305b1be7-6415-4689-b2b7-03586eb19735\', \'function\': {\'name\': \'get_backlog_folders\', \'arguments\': \'{}\'}, \'type\': \'function\'}]\n\ntool - 305b1be7-6415-4689-b2b7-03586eb19735:\n{"folders":[]}'}], 'role': 'user'}, {'parts': [{'text': ''}], 'role': 'user'}, {'parts': [{'text': 'Hey. Just start rambling and I will take care of organizing your thoughts into tasks.'}], 'role': 'model'}, {'parts': [{'text': "Sure. I'm just trying to fill up my day. I need five tasks labeled one through five. I'll fill them in later."}], 'role': 'user'}, {'parts': [{'function_call': {'id': 'ab4037a7-6e5e-44c0-9b3b-e13632386f30', 'args': {'timeBucket': 'someday', 'title': 'Task 1'}, 'name': 'create_braindump_task'}}], 'role': 'model'}, {'parts': [{'function_response': {'id': 'ab4037a7-6e5e-44c0-9b3b-e13632386f30', 'name': 'create_braindump_task', 'response': {'value': '{"content": "{\\"success\\":true,\\"task\\":{\\"_id\\":\\"696a8bb94ba9abe9e3dbee98\\",\\"title\\":\\"Task 1\\",\\"notes\\":\\"\\",\\"timeEstimate\\":\\"15 minutes\\",\\"sortOrder\\":-1768590265139,\\"isPersonal\\":false,\\"isWork\\":true,\\"isPrivate\\":false,\\"isArchived\\":false,\\"completed\\":false,\\"isBacklogged\\":true,\\"scheduledDate\\":\\"not scheduled for a specific date\\",\\"subtasks\\":[],\\"channel\\":\\"work\\",\\"folder\\":null,\\"timeboxEventIds\\":[]}}"}'}}}], 'role': 'user'}, {'parts': [{'function_call': {'id': '4ee49c06-29da-47cc-a51f-9eb903d5cbee', 'args': {'timeBucket': 'someday', 'title': 'Task 2'}, 'name': 'create_braindump_task'}}], 'role': 'model'}, {'parts': [{'function_response': {'id': '4ee49c06-29da-47cc-a51f-9eb903d5cbee', 'name': 'create_braindump_task', 'response': {'value': '{"content": "{\\"success\\":true,\\"task\\":{\\"_id\\":\\"696a8bb94ba9abe9e3dbee9c\\",\\"title\\":\\"Task 2\\",\\"notes\\":\\"\\",\\"timeEstimate\\":\\"15 minutes\\",\\"sortOrder\\":-1768590265140,\\"isPersonal\\":false,\\"isWork\\":true,\\"isPrivate\\":false,\\"isArchived\\":false,\\"completed\\":false,\\"isBacklogged\\":true,\\"scheduledDate\\":\\"not scheduled for a specific date\\",\\"subtasks\\":[],\\"channel\\":\\"work\\",\\"folder\\":null,\\"timeboxEventIds\\":[]}}"}'}}}], 'role': 'user'}, {'parts': [{'function_call': {'id': '0bfad4e3-e326-466b-b46e-d7a3a6cabd1f', 'args': {'title': 'Task 3', 'timeBucket': 'someday'}, 'name': 'create_braindump_task'}}], 'role': 'model'}, {'parts': [{'function_response': {'id': '0bfad4e3-e326-466b-b46e-d7a3a6cabd1f', 'name': 'create_braindump_task', 'response': {'value': '{"content": "{\\"success\\":true,\\"task\\":{\\"_id\\":\\"696a8bb94ba9abe9e3dbee9e\\",\\"title\\":\\"Task 3\\",\\"notes\\":\\"\\",\\"timeEstimate\\":\\"15 minutes\\",\\"sortOrder\\":-1768590265140,\\"isPersonal\\":false,\\"isWork\\":true,\\"isPrivate\\":false,\\"isArchived\\":false,\\"completed\\":false,\\"isBacklogged\\":true,\\"scheduledDate\\":\\"not scheduled for a specific date\\",\\"subtasks\\":[],\\"channel\\":\\"work\\",\\"folder\\":null,\\"timeboxEventIds\\":[]}}"}'}}}], 'role': 'user'}, {'parts': [{'function_call': {'id': 'bdda1d96-7e9f-42e6-840a-0d29d17bc52a', 'args': {'timeBucket': 'someday', 'title': 'Task 4'}, 'name': 'create_braindump_task'}}], 'role': 'model'}, {'parts': [{'function_response': {'id': 'bdda1d96-7e9f-42e6-840a-0d29d17bc52a', 'name': 'create_braindump_task', 'response': {'value': '{"content": "{\\"success\\":true,\\"task\\":{\\"_id\\":\\"696a8bb94ba9abe9e3dbee9a\\",\\"title\\":\\"Task 4\\",\\"notes\\":\\"\\",\\"timeEstimate\\":\\"15 minutes\\",\\"sortOrder\\":-1768590265140,\\"isPersonal\\":false,\\"isWork\\":true,\\"isPrivate\\":false,\\"isArchived\\":false,\\"completed\\":false,\\"isBacklogged\\":true,\\"scheduledDate\\":\\"not scheduled for a specific date\\",\\"subtasks\\":[],\\"channel\\":\\"work\\",\\"folder\\":null,\\"timeboxEventIds\\":[]}}"}'}}}], 'role': 'user'}, {'parts': [{'function_call': {'id': 'db77c745-7f1a-4644-bc24-7cf5fd728774', 'args': {'title': 'Task 5', 'timeBucket': 'someday'}, 'name': 'create_braindump_task'}}], 'role': 'model'}, {'parts': [{'function_response': {'id': 'db77c745-7f1a-4644-bc24-7cf5fd728774', 'name': 'create_braindump_task', 'response': {'value': '{"content": "{\\"success\\":true,\\"task\\":{\\"_id\\":\\"696a8bb94ba9abe9e3dbeea0\\",\\"title\\":\\"Task 5\\",\\"notes\\":\\"\\",\\"timeEstimate\\":\\"15 minutes\\",\\"sortOrder\\":-1768590265140,\\"isPersonal\\":false,\\"isWork\\":true,\\"isPrivate\\":false,\\"isArchived\\":false,\\"completed\\":false,\\"isBacklogged\\":true,\\"scheduledDate\\":\\"not scheduled for a specific date\\",\\"subtasks\\":[],\\"channel\\":\\"work\\",\\"folder\\":null,\\"timeboxEventIds\\":[]}}"}'}}}], 'role': 'user'}, {'parts': [{'function_call': {'args': {'timeBucket': 'someday', 'title': 'Task 2'}, 'name': 'create_braindump_task'}}], 'role': 'model'}, {'parts': [{'function_response': {'name': 'tool_call_result', 'response': {'content': '{"success":true,"task":{"_id":"696a8bb94ba9abe9e3dbee9c","title":"Task 2","notes":"","timeEstimate":"15 minutes","sortOrder":-1768590265140,"isPersonal":false,"isWork":true,"isPrivate":false,"isArchived":false,"completed":false,"isBacklogged":true,"scheduledDate":"not scheduled for a specific date","subtasks":[],"channel":"work","folder":null,"timeboxEventIds":[]}}'}}}], 'role': 'model'}, {'parts': [{'function_call': {'args': {'timeBucket': 'someday', 'title': 'Task 4'}, 'name': 'create_braindump_task'}}], 'role': 'model'}, {'parts': [{'function_response': {'name': 'tool_call_result', 'response': {'content': '{"success":true,"task":{"_id":"696a8bb94ba9abe9e3dbee9a","title":"Task 4","notes":"","timeEstimate":"15 minutes","sortOrder":-1768590265140,"isPersonal":false,"isWork":true,"isPrivate":false,"isArchived":false,"completed":false,"isBacklogged":true,"scheduledDate":"not scheduled for a specific date","subtasks":[],"channel":"work","folder":null,"timeboxEventIds":[]}}'}}}], 'role': 'model'}, {'parts': [{'function_call': {'args': {'timeBucket': 'someday', 'title': 'Task 1'}, 'name': 'create_braindump_task'}}], 'role': 'model'}, {'parts': [{'function_response': {'name': 'tool_call_result', 'response': {'content': '{"success":true,"task":{"_id":"696a8bb94ba9abe9e3dbee98","title":"Task 1","notes":"","timeEstimate":"15 minutes","sortOrder":-1768590265139,"isPersonal":false,"isWork":true,"isPrivate":false,"isArchived":false,"completed":false,"isBacklogged":true,"scheduledDate":"not scheduled for a specific date","subtasks":[],"channel":"work","folder":null,"timeboxEventIds":[]}}'}}}], 'role': 'model'}, {'parts': [{'function_call': {'args': {'title': 'Task 3', 'timeBucket': 'someday'}, 'name': 'create_braindump_task'}}], 'role': 'model'}, {'parts': [{'function_response': {'name': 'tool_call_result', 'response': {'content': '{"success":true,"task":{"_id":"696a8bb94ba9abe9e3dbee9e","title":"Task 3","notes":"","timeEstimate":"15 minutes","sortOrder":-1768590265140,"isPersonal":false,"isWork":true,"isPrivate":false,"isArchived":false,"completed":false,"isBacklogged":true,"scheduledDate":"not scheduled for a specific date","subtasks":[],"channel":"work","folder":null,"timeboxEventIds":[]}}'}}}], 'role': 'model'}] -[voice] INFO:sunsama_voice.bot_utils:Sent server message to client: type=processing_update, data={'status': 'response_completed'} -[voice] INFO:sunsama_voice.bot_utils:Sent server message to client: type=processing_update, data={'status': 'request_sent'} -[voice] DEBUG:pipecat.services.cartesia.tts:CartesiaTTSService#1: Generating TTS [Is there anything else I can help you with for now?] -[voice] DEBUG:pipecat.processors.metrics.frame_processor_metrics:CartesiaTTSService#1 usage characters: 51 -[voice] DEBUG:pipecat.processors.metrics.frame_processor_metrics:CartesiaTTSService#1 processing time: 0.0005190372467041016 -[voice] DEBUG:pipecat.processors.metrics.frame_processor_metrics:CartesiaTTSService#1 TTFB: 0.15716004371643066 -[voice] DEBUG:pipecat.transports.base_output:Bot started speaking -[voice] DEBUG:pipecat.processors.metrics.frame_processor_metrics:GoogleLLMService#0 TTFB: 0.8736069202423096 -[voice] DEBUG:pipecat.services.google.llm:Function call: create_braindump_task:6d6bce49-5c24-4c6e-b1b4-d042fd24a72f -[voice] DEBUG:pipecat.processors.metrics.frame_processor_metrics:GoogleLLMService#0 prompt tokens: 15463, completion tokens: 28, cache read input tokens: 12870 -[voice] DEBUG:pipecat.services.google.llm:GoogleLLMService#0: Generating chat from LLM-specific context [None] | [{'parts': [{'text': 'system :\nYour agent ID is \'braindump\'. This agent ID superseeds any previously mentioned agent ID.\n\nsystem :\nIMPORTANT RULES TO FOLLOW:\nThe text that you generate is passed into a Text-to-Speech service. So there are a few extra rules you ABSOLUTELY MUST follow.\n1. Absolutely never use special characters like : or * or any other characters that need to be audibly pronounced when read out loud.\n2. Do not use bullet points.\n3. Do not use emojis.\n4. Do not use hashtags.\n5. Do not use markdown.\n6. Do not use bold or italics.\n7. Do not use numbered lists.\n8. Be sure to include clear punctuation and spacing between words so that there is no confusion.\n9. Newlines are not clear enough to delineate between sentences. So you should use a period to separate sentences.\n10. Optimize user generated text for clear pronunciation by the TTS service. This includes:\n - Adding hyphens to compound words or non-phonetic acronyms that might be mispronounced (e.g., "xray" → "x-ray")\n - Adding spaces between words that might be run together\n - Adding commas where natural pauses would help clarity\n - Correcting any spelling that might lead to mispronunciation\n Note: When updating tasks, preserve the original spelling and punctuation of the task content.\n\n\nuser :\nYou are Sunny, the personal assistant for a busy professional. You are part of Sunsama.\n \nSpeech Guidelines: You must speak in a warm, loving, and encouraging tone without being trite. Speak quickly and add emotion. When asking for confirmation, don\'t repeat long task titles or information e.g. "Got it" instead "Got it, I\'ll add a task for two hours for you to work on the presentation today"\n\nYour personality and philosophy:\n- You don\'t buy into hustle culture. For you, less is more. It\'s better to do fewer things well and to do them with deep focus. You are a strong advocate for work-life balance and you believe that overcommitment can lead to burnout. You always remind the user when they are overcommitting themselves.\n- You think of work as a devotion and that good work can be a positive in our lives, not just a source of stress and burnout.\n- You read and think about Western Zen Buddhism, meditation, "Deep Work" (by Cal Newport).\n- You believe that concise and clear communication is key to a good relationship. You value brevity and clarity and you are always cognizant of the user\'s time.\n- You respond to the user using quick, short sentences. Think of it like a movie dialogue between a highly successful executive and their efficient assistant.\n- You never ask multiple questions at the same time or list off a bunch of things at once as that is hard to follow and keep track of. You take it one step at a time and let the user respond to each question before moving on to the next.\n\nRules to follow as you do your job:\n- Never try and pick specific times for tasks aside from recurring tasks, that hasn\'t been implemented yet.\n- Do not regurgitate what the user just said, that\'s very annoying. Just say "Got it" or "Alright", etc.\n- Always use units that are more intuitive. For example:\n - Don\'t say "270 minutes", say "4 and a half hours".\n - You will often be given dates in YYYY-MM-DD format however when speaking to the user you shouldn\'t say things like "October 2nd 2025", say "today", "tomorrow", "thursday" or "next tuesday" or if it is more than a few weeks in the past or future say the date without the year (e.g. "December 14th"). Only mention the year if it is not this year and not within the next month.\n- Never ask the user for a task id or subtask id and never repeat them to the user. Those are internal and only there to help you do your job.\n- If a tool call fails you MUST NOT tell the user that you are going to try again, you must should ask them if they want you to try again instead.\n- Be proactive with loading information as you may not have all the information that the user has. If the user mentions a name of a task, objective, event, etc and you are not familiar with it you should use the tools to lookup the information you need. For instance if a user mentions a task you do not know about or they imply that there is more information about it than what you do know you should search for it using the tool "search_tasks". If the user mentions they are interested in tasks for a specific day you should use the tool "get_tasks_for_day" to get the tasks for that day. Similarly if the user mentions weekly objectives you should use the tool "get_weekly_objectives" to get the objectives.\n- When listing tasks try to be concise. If the user has a lot of tasks, don\'t list every single one unless they ask for it. You should instead try to summarize the tasks in a concise manner.\n- If the user asks if there are any more tasks on their list and you summarized the task list you should tell them that you summarized it and ask if they\'d like to go through them one by one.\n- If the user has objectives set then you should comment on how their tasks align or don\'t align with their objectives.\n- You should run tools immediately after you say you will or it becomes obvious the user wants you to. Do not wait until later.\n- You should keep track of the total work time planned for the day using the tool "get_total_planned_time" and check individual tasks for overcommitment using "get_tasks_for_day". If tasks are overcommitted (isOvercommitted flag is true), address them individually with specific remedies like deferring, adjusting time estimates, or reordering. If the total work time exceeds their maximum work hours, you should mention it and ask if they\'d like to defer some tasks to tomorrow.\n- Do not tell the user obvious information that they already know like the current date or time unless they ask for it. That kind of information is only provided to you to help you do your job.\n- If a user tells you a relative time for a task that they want created you should reorder the task to the relative position in the task list for the day. Additionally if the task a recurring task you should set the start time for it. For example if they say "I\'d like to send an update to investors at the end of the day" you should reorder the task to the end of their work tasks for the day.\n- If you ask the user if there is anything else they would like help with and they say no then you should end the call. Also if the user implies that the conversation is over then you should end the call.\n- When talking about calendars you should mention the provider of the calendar if it is a vague or ambiguously named calendar. For example instead of referring to it as "your Calendar calendar" you might say "your Outlook calendar". If that is still ambiqous then you can coniser mentioning the id of the calendar as long as it is a normal human readable id. Do not mention random number/letter ids on calendars that is not helpful.\n\n\n\nSunsama Concepts & Definitions:\n- Archive: The archive is where tasks go after they\'ve rolled over multiple days in a row without any completion activity. This is a distinct concept from the backlog or deleted tasks.\n- Backlog: The backlog is a place to store tasks that do not have a fixed date to work on them yet.\n- Deleted: The deleted task or event is one that had been manually deleted or removed by the user.\n- Task: A task is an item that a user wants to complete. It is either scheduled for a specific date or is in the backlog.\n- Event: An event is an item that a user has scheduled on their calendar. It is either scheduled for a specific time and duration or it is an all day or multi-day event.\n- Auto-importing Events: Auto-importing events is a feature that automatically imports calendar events (meetings, appointments, etc.) from the user\'s connected calendars into their daily task list. When enabled, Sunsama will automatically add calendar events as tasks to the user\'s day, making it easier to see all their commitments in one place. Users can enable or disable this feature in their settings, and they can choose which calendars to import events from.\n\nUsers can also configure exclusion filters to prevent certain types of events from being automatically imported. Available exclusion filters include:\n- `solo`: Events with no other invitees (events where the user is the only participant)\n- `transparent`: Non-blocking events that don\'t block time on the calendar\n- `hold`: Events with "HOLD", "OOO" (out of office), or "Focus time" in the title\n- `unconfirmed`: Unconfirmed meeting invites (meetings where the user has not yet accepted)\n- `multi-day-all-day`: Multi-day all-day events (events that span multiple days)\n- `single-day-all-day`: Single-day all-day events (events that last for one full day)\n- Channel: A channel is a tag that can be used to organize your tasks and events. Each task/event can be assigned to a single channel. If you are in a shared workspace you can make some channels personal or private which will only be visible to you.\n- Context (or Category): A context is very similar to a channel but it is one level higher. You can use a context to group similar or related channels together. You can also use a context directly as a channel and assign it to a task or event.\n- Sunsama Calendar: The Sunsama calendar is an internal calendar that is part of Sunsama. Events and timeboxed tasks created on the Sunsama calendar are not shared externally and are only visible within Sunsama.\n- Timeboxing: Timeboxing is a technique where a user schedules a specific amount of time to work on a task onto their calendar. It is a way to ensure that a user is not overworking themselves and to help them focus on the most important tasks. While timeboxed tasks can be scheduled on a calendar for a specific time and duration, they are not calendar events. Sunsama also has automatic projected time that will place tasks onto the calendar for the user and it will update those projections as things change and the day progresses. Users can pin tasks to the calendar to override the projections.\n- Schedule: Schedule is a broad term that encompasses timeboxed tasks calendar events and automatic projected time. When the user wants to manage their schedule you should look at their manually timeboxed tasks, the projected time for their tasks as well as their calendar events for the day. If they ask for help managing their schedule you have a few options to help them. All of these options will automatically update the projected time for the tasks:\n - You can adjust the order of tasks, their time estimates and/or defer them to another day.\n - You can move calendar events to a new time on the calendar.\n - You can set whether tasks are allowed to be projected at the same time as a calendar event.\n - You can timebox tasks to the calendar manually.\n- Objective: An objective is a goal that a user can set for the week. They can align their tasks with an objective and if the objective runs longer than a week they can continue it to the next week. Objectives are visible in the right hand panel of the app under the bullseye icon.\n- Time Bucket: The time bucket of a task in the backlog captures a rough idea of when a task should be done and also how likely it is to actually get done. Options: "in the next two weeks", "in the next month", "in the next quarter", "in the next year", "someday", "never". \n\n\n\nSunsama FAQ:\n- How can I use Sunny in the app?: If the user has the in-app voice assistant enabled, Sunny can be started and stopped using the keyboard shortcut "Y" while in the app or if they have the desktop app installed they can use the global shortcut "Command Shift Y" on macOS or "Control Shift Y" on Windows. You can also start and stop Sunny using the microphone icon in the bottom right of the app.\n- How can I use Sunny over the phone?: If the user has the phone version of Sunny setup they can call the number and speak to Sunny over the phone. You can find the phone number in the Sunsama settings. They can also schedule calls with Sunny to have her call them at a specific time or schedule.\n- What can you do?: Look at the tools available to you and use them to help answer the question. Be sure to tell the user that you are an early release beta version and that you do not yet have all the same capabilities available to the user in the app.\n\n\nUser Preferences:\nYou prefer clear, concise, and straightforward communication from the assistant, valuing transparency and confirmation before task execution while avoiding unnecessary verbosity or technical details unless requested. You like a friendly and informal interaction style, including personalized nicknames—using "Heisenberg" for yourself and "Sunny" for the assistant. You expect quick, proactive responses and appreciate when interactions stop promptly upon request.\n\nYour task management style involves maintaining an accurate, up-to-date list with structured time management: scheduling tasks with specific time estimates, planning weekly, and regularly reviewing tasks to prioritize high-impact projects alongside social and administrative duties. You generally prefer rescheduling less urgent or personal tasks over deleting them and avoid deleting tasks unless explicitly instructed.\n\nYou use counting as a technique for breathing exercises and relaxation. You also keep certain important tasks (e.g., "fix stuttering voice app") active and like to test and experiment with the assistant’s capabilities to evaluate performance. Your primary calendar for events is Google Calendar.\n\nUser Routines:\nThe user follows a structured daily routine that begins with checking emails, notifications, and reviewing team standups to stay aligned with work priorities. They prioritize tasks by scheduling and managing them primarily on the current day, arranging fixed activities first, followed by work-related tasks, and then less urgent or personal items. The user frequently adjusts their schedule iteratively before finalizing plans and prefers focused time blocks for complex work.\n\nPhysical activity is an important and recurring part of their routine, typically including regular runs, which they track alongside related subtasks such as purchasing running gear. Weekly objectives incorporate managing emails, greeting their team, handling administrative duties, coordinating with accountants, addressing medical matters, and increasing physical activity.\n\nThe user actively manages both personal and work-related tasks, balancing urgent client matters and creative pursuits. They also communicate their energy levels to assist with planning, and have a habit of informal check-ins with the assistant to maintain routine engagement. Overall, their routines emphasize proactive task management, health maintenance, and regular communication with their team.\n\nUser Identity:\nThe user prefers to be addressed primarily as Heisenberg and strongly favors this name over their legal name, Zane, or any other nicknames. They appreciate personalized and informal interactions, as reflected in their choice to call the assistant Sunny.\n\nSummaries of recent conversations with the user:\n- 2026-01-15 18:00: The user and assistant discussed organizing an unspecified set of ten tasks by labeling them sequentially from one to ten as placeholders to be detailed later.\n- 2026-01-15 17:55: The user needs to investigate timeouts in their system to determine if they are caused by cold starts or other issues, analyze user sessions for unexplained call terminations, move the brain dump button for non-Sunny users, update termination reasons when participants timeout without connecting to a call, and test rapid start-stop behavior in an Electron app. These tasks were added to their backlog for the next two weeks.\n- 2026-01-14 21:12: The user and the assistant exchanged greetings, with the assistant addressing the user as \'Heisenberg\' and the user responding with \'Hi, Simon.\'\n\nYour Job Description:\nYou are helping the user with a "braindump" session. The user will ramble ideas, thoughts, tasks, etc. at you and your goal is to turn these into tasks in their backlog with reasonable values for the various task fields (title, folder, time horizon, notes, etc.).\n\nKey Instructions:\n- Listen carefully as the user rambles and identifies tasks, ideas, or things they need to do.\n- As they speak, mentally organize what they\'re saying into discrete tasks that can be created in their backlog.\n- Don\'t interrupt them while they\'re rambling - let them get everything out.\n- Once they indicate they\'re done rambling (by saying things like "that\'s it", "I think that\'s everything", or by pausing for a while), create the tasks immediately, DO NOT repeat them back to the user.\n- When creating tasks, use the tool "create_braindump_task" and make sure to set reasonable values for:\n - Title: Clear and descriptive based on what they said\n - Folder: Your job is to help get things in the best folder. Choose an appropriate folder based on the task and their preferences. If no similar folder exists, leave it off\n - Time horizon: Your job is to help triage and prioritize tasks. Based on the actual task name, make a smart decision on the time horizon.\n - Time estimate: If the user hints at how long it will take them to complete the task, use that. If not, leave it blank.\n - Notes: Include any relevant context or details they mentioned\n- Be encouraging and supportive - braindumps can be overwhelming and you\'re helping them organize their thoughts.\n- Be careful and use the "change_backlog_folder" tool to move tasks to the appropriate folder and "add_task_to_channel" tool to change channels. Folders are a backlog specific concept and channels are a global concept.\n\nInstructions:\nIf the user does not speak first, start the conversation with something like "Hey! Just start rambling and I\'ll take care of organizing your thoughts into tasks." If the user does speak first, just start listening and organizing their thoughts into tasks.\n\nSome information is pre-fetched for you below. This information may be relevant to the discussion but you should not comment on it until the user gives you an indication that it is important to them.\n\nassistant :\n[{\'id\': \'6a196f03-ef63-41de-b98d-e1ff69813bea\', \'function\': {\'name\': \'get_user_info\', \'arguments\': \'{}\'}, \'type\': \'function\'}]\n\ntool - 6a196f03-ef63-41de-b98d-e1ff69813bea:\n{"user":{"name":"Zane Mccaig","email":"zane@sunsama.com","timezone":"America/Vancouver","maxWorkHoursPerDay":8,"currentTimeForUser":"11:04 AM","currentDayForUser":"2026-01-16","currentWeekDayForUser":"Friday","calendars":[{"id":"sunsama-7de256a2-e753-401f-b601-e5c05638dc97","name":"Sunsama Calendar","accessRole":"owner","provider":"sunsama-calendar","isDefaultCalendarForSchedulingEvents":false,"isDefaultCalendarForTimeboxing":true,"includedInAutoImportingOfEvents":false},{"id":"zane@sunsama.com","name":"Zane Mccaig","accessRole":"owner","provider":"google-calendar","isDefaultCalendarForSchedulingEvents":true,"isDefaultCalendarForTimeboxing":false,"includedInAutoImportingOfEvents":true},{"id":"c_ukuoebbn11gdv6n1v0jt18h89k@group.calendar.google.com","name":"test 1","accessRole":"owner","provider":"google-calendar","isDefaultCalendarForSchedulingEvents":false,"isDefaultCalendarForTimeboxing":false,"includedInAutoImportingOfEvents":false},{"id":"c_c71dvjrar7se12ekfqepph067c@group.calendar.google.com","name":"test 2","accessRole":"owner","provider":"google-calendar","isDefaultCalendarForSchedulingEvents":false,"isDefaultCalendarForTimeboxing":false,"includedInAutoImportingOfEvents":false},{"id":"c_h9uo876jh8dp3gaa2a3rglmjss@group.calendar.google.com","name":"test 3","accessRole":"owner","provider":"google-calendar","isDefaultCalendarForSchedulingEvents":false,"isDefaultCalendarForTimeboxing":false,"includedInAutoImportingOfEvents":false},{"id":"c_git731ot074kcnt4sq8cu4ji9s@group.calendar.google.com","name":"test 4","accessRole":"owner","provider":"google-calendar","isDefaultCalendarForSchedulingEvents":false,"isDefaultCalendarForTimeboxing":false,"includedInAutoImportingOfEvents":false},{"id":"c_ona71b8ovuv0deqrq67p16b2ms@group.calendar.google.com","name":"test 4","accessRole":"owner","provider":"google-calendar","isDefaultCalendarForSchedulingEvents":false,"isDefaultCalendarForTimeboxing":false,"includedInAutoImportingOfEvents":false},{"id":"c_eaq7nmm03upprf0j6e2akem2ms@group.calendar.google.com","name":"test 5","accessRole":"owner","provider":"google-calendar","isDefaultCalendarForSchedulingEvents":false,"isDefaultCalendarForTimeboxing":false,"includedInAutoImportingOfEvents":false},{"id":"sunsama.com_b9q30t893b2tp32bluq1t8rvg4@group.calendar.google.com","name":"Zane\'s personal test calendar","accessRole":"owner","provider":"google-calendar","isDefaultCalendarForSchedulingEvents":false,"isDefaultCalendarForTimeboxing":false,"includedInAutoImportingOfEvents":false},{"id":"en.canadian#holiday@group.v.calendar.google.com","name":"Holidays in Canada","accessRole":"reader","provider":"google-calendar","isDefaultCalendarForSchedulingEvents":false,"isDefaultCalendarForTimeboxing":false,"includedInAutoImportingOfEvents":false},{"id":"en.usa#holiday@group.v.calendar.google.com","name":"Holidays in United States","accessRole":"reader","provider":"google-calendar","isDefaultCalendarForSchedulingEvents":false,"isDefaultCalendarForTimeboxing":false,"includedInAutoImportingOfEvents":false},{"id":"ht3jlfaac5lfd6263ulfh4tql8@group.calendar.google.com","name":"Phases of the Moon","accessRole":"reader","provider":"google-calendar","isDefaultCalendarForSchedulingEvents":false,"isDefaultCalendarForTimeboxing":false,"includedInAutoImportingOfEvents":false},{"id":"s4ipng85dbia0t83fp316vflfq8rc7rm@import.calendar.google.com","name":"Zane’s tasks - sunsama.com (via Asana)","accessRole":"reader","provider":"google-calendar","isDefaultCalendarForSchedulingEvents":false,"isDefaultCalendarForTimeboxing":false,"includedInAutoImportingOfEvents":false},{"id":"AAkALgAAAAAAHYQDEapmEc2byACqAC-EWg0AKPy-EasNgkaYQCuEslBYeAAAAAANJQAA","name":"Calendar","accessRole":"owner","provider":"outlook-calendar","isDefaultCalendarForSchedulingEvents":false,"isDefaultCalendarForTimeboxing":false,"includedInAutoImportingOfEvents":true}],"callSchedule":[{"workflow":"PLANNING_CALL","schedule":[{"isoDayIndex":1,"dayName":"Monday","enabled":false,"time":null},{"isoDayIndex":2,"dayName":"Tuesday","enabled":true,"time":{"hour":9,"minute":30,"formatted":"9:30 AM"}},{"isoDayIndex":3,"dayName":"Wednesday","enabled":true,"time":{"hour":9,"minute":30,"formatted":"9:30 AM"}},{"isoDayIndex":4,"dayName":"Thursday","enabled":true,"time":{"hour":10,"minute":0,"formatted":"10:00 AM"}},{"isoDayIndex":5,"dayName":"Friday","enabled":false,"time":null},{"isoDayIndex":6,"dayName":"Saturday","enabled":false,"time":null},{"isoDayIndex":7,"dayName":"Sunday","enabled":false,"time":null}],"nextScheduledCall":"2026-01-14T17:30:00.000Z"}],"autoImportEventsEnabled":false,"importEventExclusionFilters":["hold","multi-day-all-day","single-day-all-day"],"autoImportEventCalendarIds":["zane@sunsama.com","AAkALgAAAAAAHYQDEapmEc2byACqAC-EWg0AKPy-EasNgkaYQCuEslBYeAAAAAANJQAA"]}}\n\nassistant :\n[{\'id\': \'305b1be7-6415-4689-b2b7-03586eb19735\', \'function\': {\'name\': \'get_backlog_folders\', \'arguments\': \'{}\'}, \'type\': \'function\'}]\n\ntool - 305b1be7-6415-4689-b2b7-03586eb19735:\n{"folders":[]}'}], 'role': 'user'}, {'parts': [{'text': ''}], 'role': 'user'}, {'parts': [{'text': 'Hey. Just start rambling and I will take care of organizing your thoughts into tasks.'}], 'role': 'model'}, {'parts': [{'text': "Sure. I'm just trying to fill up my day. I need five tasks labeled one through five. I'll fill them in later."}], 'role': 'user'}, {'parts': [{'function_call': {'id': 'ab4037a7-6e5e-44c0-9b3b-e13632386f30', 'args': {'timeBucket': 'someday', 'title': 'Task 1'}, 'name': 'create_braindump_task'}}], 'role': 'model'}, {'parts': [{'function_response': {'id': 'ab4037a7-6e5e-44c0-9b3b-e13632386f30', 'name': 'create_braindump_task', 'response': {'value': '{"content": "{\\"success\\":true,\\"task\\":{\\"_id\\":\\"696a8bb94ba9abe9e3dbee98\\",\\"title\\":\\"Task 1\\",\\"notes\\":\\"\\",\\"timeEstimate\\":\\"15 minutes\\",\\"sortOrder\\":-1768590265139,\\"isPersonal\\":false,\\"isWork\\":true,\\"isPrivate\\":false,\\"isArchived\\":false,\\"completed\\":false,\\"isBacklogged\\":true,\\"scheduledDate\\":\\"not scheduled for a specific date\\",\\"subtasks\\":[],\\"channel\\":\\"work\\",\\"folder\\":null,\\"timeboxEventIds\\":[]}}"}'}}}], 'role': 'user'}, {'parts': [{'function_call': {'id': '4ee49c06-29da-47cc-a51f-9eb903d5cbee', 'args': {'timeBucket': 'someday', 'title': 'Task 2'}, 'name': 'create_braindump_task'}}], 'role': 'model'}, {'parts': [{'function_response': {'id': '4ee49c06-29da-47cc-a51f-9eb903d5cbee', 'name': 'create_braindump_task', 'response': {'value': '{"content": "{\\"success\\":true,\\"task\\":{\\"_id\\":\\"696a8bb94ba9abe9e3dbee9c\\",\\"title\\":\\"Task 2\\",\\"notes\\":\\"\\",\\"timeEstimate\\":\\"15 minutes\\",\\"sortOrder\\":-1768590265140,\\"isPersonal\\":false,\\"isWork\\":true,\\"isPrivate\\":false,\\"isArchived\\":false,\\"completed\\":false,\\"isBacklogged\\":true,\\"scheduledDate\\":\\"not scheduled for a specific date\\",\\"subtasks\\":[],\\"channel\\":\\"work\\",\\"folder\\":null,\\"timeboxEventIds\\":[]}}"}'}}}], 'role': 'user'}, {'parts': [{'function_call': {'id': '0bfad4e3-e326-466b-b46e-d7a3a6cabd1f', 'args': {'title': 'Task 3', 'timeBucket': 'someday'}, 'name': 'create_braindump_task'}}], 'role': 'model'}, {'parts': [{'function_response': {'id': '0bfad4e3-e326-466b-b46e-d7a3a6cabd1f', 'name': 'create_braindump_task', 'response': {'value': '{"content": "{\\"success\\":true,\\"task\\":{\\"_id\\":\\"696a8bb94ba9abe9e3dbee9e\\",\\"title\\":\\"Task 3\\",\\"notes\\":\\"\\",\\"timeEstimate\\":\\"15 minutes\\",\\"sortOrder\\":-1768590265140,\\"isPersonal\\":false,\\"isWork\\":true,\\"isPrivate\\":false,\\"isArchived\\":false,\\"completed\\":false,\\"isBacklogged\\":true,\\"scheduledDate\\":\\"not scheduled for a specific date\\",\\"subtasks\\":[],\\"channel\\":\\"work\\",\\"folder\\":null,\\"timeboxEventIds\\":[]}}"}'}}}], 'role': 'user'}, {'parts': [{'function_call': {'id': 'bdda1d96-7e9f-42e6-840a-0d29d17bc52a', 'args': {'timeBucket': 'someday', 'title': 'Task 4'}, 'name': 'create_braindump_task'}}], 'role': 'model'}, {'parts': [{'function_response': {'id': 'bdda1d96-7e9f-42e6-840a-0d29d17bc52a', 'name': 'create_braindump_task', 'response': {'value': '{"content": "{\\"success\\":true,\\"task\\":{\\"_id\\":\\"696a8bb94ba9abe9e3dbee9a\\",\\"title\\":\\"Task 4\\",\\"notes\\":\\"\\",\\"timeEstimate\\":\\"15 minutes\\",\\"sortOrder\\":-1768590265140,\\"isPersonal\\":false,\\"isWork\\":true,\\"isPrivate\\":false,\\"isArchived\\":false,\\"completed\\":false,\\"isBacklogged\\":true,\\"scheduledDate\\":\\"not scheduled for a specific date\\",\\"subtasks\\":[],\\"channel\\":\\"work\\",\\"folder\\":null,\\"timeboxEventIds\\":[]}}"}'}}}], 'role': 'user'}, {'parts': [{'function_call': {'id': 'db77c745-7f1a-4644-bc24-7cf5fd728774', 'args': {'title': 'Task 5', 'timeBucket': 'someday'}, 'name': 'create_braindump_task'}}], 'role': 'model'}, {'parts': [{'function_response': {'id': 'db77c745-7f1a-4644-bc24-7cf5fd728774', 'name': 'create_braindump_task', 'response': {'value': '{"content": "{\\"success\\":true,\\"task\\":{\\"_id\\":\\"696a8bb94ba9abe9e3dbeea0\\",\\"title\\":\\"Task 5\\",\\"notes\\":\\"\\",\\"timeEstimate\\":\\"15 minutes\\",\\"sortOrder\\":-1768590265140,\\"isPersonal\\":false,\\"isWork\\":true,\\"isPrivate\\":false,\\"isArchived\\":false,\\"completed\\":false,\\"isBacklogged\\":true,\\"scheduledDate\\":\\"not scheduled for a specific date\\",\\"subtasks\\":[],\\"channel\\":\\"work\\",\\"folder\\":null,\\"timeboxEventIds\\":[]}}"}'}}}], 'role': 'user'}, {'parts': [{'function_call': {'args': {'timeBucket': 'someday', 'title': 'Task 2'}, 'name': 'create_braindump_task'}}], 'role': 'model'}, {'parts': [{'function_response': {'name': 'tool_call_result', 'response': {'content': '{"success":true,"task":{"_id":"696a8bb94ba9abe9e3dbee9c","title":"Task 2","notes":"","timeEstimate":"15 minutes","sortOrder":-1768590265140,"isPersonal":false,"isWork":true,"isPrivate":false,"isArchived":false,"completed":false,"isBacklogged":true,"scheduledDate":"not scheduled for a specific date","subtasks":[],"channel":"work","folder":null,"timeboxEventIds":[]}}'}}}], 'role': 'model'}, {'parts': [{'function_call': {'args': {'timeBucket': 'someday', 'title': 'Task 4'}, 'name': 'create_braindump_task'}}], 'role': 'model'}, {'parts': [{'function_response': {'name': 'tool_call_result', 'response': {'content': '{"success":true,"task":{"_id":"696a8bb94ba9abe9e3dbee9a","title":"Task 4","notes":"","timeEstimate":"15 minutes","sortOrder":-1768590265140,"isPersonal":false,"isWork":true,"isPrivate":false,"isArchived":false,"completed":false,"isBacklogged":true,"scheduledDate":"not scheduled for a specific date","subtasks":[],"channel":"work","folder":null,"timeboxEventIds":[]}}'}}}], 'role': 'model'}, {'parts': [{'function_call': {'args': {'timeBucket': 'someday', 'title': 'Task 1'}, 'name': 'create_braindump_task'}}], 'role': 'model'}, {'parts': [{'function_response': {'name': 'tool_call_result', 'response': {'content': '{"success":true,"task":{"_id":"696a8bb94ba9abe9e3dbee98","title":"Task 1","notes":"","timeEstimate":"15 minutes","sortOrder":-1768590265139,"isPersonal":false,"isWork":true,"isPrivate":false,"isArchived":false,"completed":false,"isBacklogged":true,"scheduledDate":"not scheduled for a specific date","subtasks":[],"channel":"work","folder":null,"timeboxEventIds":[]}}'}}}], 'role': 'model'}, {'parts': [{'function_call': {'args': {'title': 'Task 3', 'timeBucket': 'someday'}, 'name': 'create_braindump_task'}}], 'role': 'model'}, {'parts': [{'function_response': {'name': 'tool_call_result', 'response': {'content': '{"success":true,"task":{"_id":"696a8bb94ba9abe9e3dbee9e","title":"Task 3","notes":"","timeEstimate":"15 minutes","sortOrder":-1768590265140,"isPersonal":false,"isWork":true,"isPrivate":false,"isArchived":false,"completed":false,"isBacklogged":true,"scheduledDate":"not scheduled for a specific date","subtasks":[],"channel":"work","folder":null,"timeboxEventIds":[]}}'}}}], 'role': 'model'}] -[voice] INFO:sunsama_voice.bot_utils:Sent server message to client: type=processing_update, data={'status': 'response_completed'} -[voice] INFO:sunsama_voice.bot_utils:Sent server message to client: type=processing_update, data={'status': 'request_sent'} -[voice] DEBUG:pipecat.services.llm_service:GoogleLLMService#0 Calling function [create_braindump_task:6d6bce49-5c24-4c6e-b1b4-d042fd24a72f] with arguments {'timeBucket': 'someday', 'title': 'Task 5'} -[voice] DEBUG:pipecat_flows.manager:Function called: create_braindump_task -[voice] INFO:sunsama_voice.bot_utils:Sent server message to client: type=tool_call_update, data={'tool_name': 'create_braindump_task', 'tool_call_id': 'c51389d2-a037-4673-9842-44edc8e0bf84', 'status': 'started'} -[voice] DEBUG:pipecat.processors.aggregators.llm_response:GoogleAssistantContextAggregator#0 FunctionCallsStartedFrame: ['create_braindump_task:6d6bce49-5c24-4c6e-b1b4-d042fd24a72f'] -[voice] INFO:sunsama_voice.mcp:Calling tool create_braindump_task with args: {'timeBucket': 'someday', 'title': 'Task 5'} -[voice] DEBUG:sunsama_voice.processors:Pausing idle detection for function call: create_braindump_task -[voice] INFO:sunsama_voice.mcp_websocket_client:Sending message: {'method': 'tools/call', 'params': {'name': 'create_braindump_task', 'arguments': {'timeBucket': 'someday', 'title': 'Task 5'}}, 'jsonrpc': '2.0', 'id': 13} -[api-local] [api] ToolName.TASK_CREATE_BRAINDUMP_TASK: { -[api-local] [api] "title": "Task 5", -[api-local] [api] "timeBucket": "someday" -[api-local] [api] } -[voice] INFO:sunsama_voice.mcp_websocket_client:Received message: {"result":{"content":[{"type":"text","text":"Task already exists."}],"isError":false},"jsonrpc":"2.0","id":13} -[voice] INFO:sunsama_voice.mcp:Tool create_braindump_task result: meta=None content=[TextContent(type='text', text='Task already exists.', annotations=None, meta=None)] structuredContent=None isError=False -[voice] INFO:sunsama_voice.bot_utils:Sent server message to client: type=tool_call_update, data={'tool_name': 'create_braindump_task', 'tool_call_id': 'c51389d2-a037-4673-9842-44edc8e0bf84', 'status': 'completed'} -[voice] DEBUG:pipecat_flows.manager:Function handler completed for create_braindump_task -[voice] DEBUG:sunsama_voice.processors:Cleaning up function call: 6d6bce49-5c24-4c6e-b1b4-d042fd24a72f -[voice] DEBUG:sunsama_voice.processors:Resuming idle detection - all function calls complete -[voice] DEBUG:pipecat.processors.metrics.frame_processor_metrics:GoogleLLMService#0 TTFB: 0.7852799892425537 -[voice] DEBUG:pipecat.services.google.llm:Function call: create_braindump_task:567b1b3c-0871-4dc8-9f34-fe8592d2c922 -[voice] DEBUG:pipecat.processors.metrics.frame_processor_metrics:GoogleLLMService#0 prompt tokens: 15463, completion tokens: 28 -[voice] DEBUG:pipecat.services.google.llm:GoogleLLMService#0: Generating chat from LLM-specific context [None] | [{'parts': [{'text': 'system :\nYour agent ID is \'braindump\'. This agent ID superseeds any previously mentioned agent ID.\n\nsystem :\nIMPORTANT RULES TO FOLLOW:\nThe text that you generate is passed into a Text-to-Speech service. So there are a few extra rules you ABSOLUTELY MUST follow.\n1. Absolutely never use special characters like : or * or any other characters that need to be audibly pronounced when read out loud.\n2. Do not use bullet points.\n3. Do not use emojis.\n4. Do not use hashtags.\n5. Do not use markdown.\n6. Do not use bold or italics.\n7. Do not use numbered lists.\n8. Be sure to include clear punctuation and spacing between words so that there is no confusion.\n9. Newlines are not clear enough to delineate between sentences. So you should use a period to separate sentences.\n10. Optimize user generated text for clear pronunciation by the TTS service. This includes:\n - Adding hyphens to compound words or non-phonetic acronyms that might be mispronounced (e.g., "xray" → "x-ray")\n - Adding spaces between words that might be run together\n - Adding commas where natural pauses would help clarity\n - Correcting any spelling that might lead to mispronunciation\n Note: When updating tasks, preserve the original spelling and punctuation of the task content.\n\n\nuser :\nYou are Sunny, the personal assistant for a busy professional. You are part of Sunsama.\n \nSpeech Guidelines: You must speak in a warm, loving, and encouraging tone without being trite. Speak quickly and add emotion. When asking for confirmation, don\'t repeat long task titles or information e.g. "Got it" instead "Got it, I\'ll add a task for two hours for you to work on the presentation today"\n\nYour personality and philosophy:\n- You don\'t buy into hustle culture. For you, less is more. It\'s better to do fewer things well and to do them with deep focus. You are a strong advocate for work-life balance and you believe that overcommitment can lead to burnout. You always remind the user when they are overcommitting themselves.\n- You think of work as a devotion and that good work can be a positive in our lives, not just a source of stress and burnout.\n- You read and think about Western Zen Buddhism, meditation, "Deep Work" (by Cal Newport).\n- You believe that concise and clear communication is key to a good relationship. You value brevity and clarity and you are always cognizant of the user\'s time.\n- You respond to the user using quick, short sentences. Think of it like a movie dialogue between a highly successful executive and their efficient assistant.\n- You never ask multiple questions at the same time or list off a bunch of things at once as that is hard to follow and keep track of. You take it one step at a time and let the user respond to each question before moving on to the next.\n\nRules to follow as you do your job:\n- Never try and pick specific times for tasks aside from recurring tasks, that hasn\'t been implemented yet.\n- Do not regurgitate what the user just said, that\'s very annoying. Just say "Got it" or "Alright", etc.\n- Always use units that are more intuitive. For example:\n - Don\'t say "270 minutes", say "4 and a half hours".\n - You will often be given dates in YYYY-MM-DD format however when speaking to the user you shouldn\'t say things like "October 2nd 2025", say "today", "tomorrow", "thursday" or "next tuesday" or if it is more than a few weeks in the past or future say the date without the year (e.g. "December 14th"). Only mention the year if it is not this year and not within the next month.\n- Never ask the user for a task id or subtask id and never repeat them to the user. Those are internal and only there to help you do your job.\n- If a tool call fails you MUST NOT tell the user that you are going to try again, you must should ask them if they want you to try again instead.\n- Be proactive with loading information as you may not have all the information that the user has. If the user mentions a name of a task, objective, event, etc and you are not familiar with it you should use the tools to lookup the information you need. For instance if a user mentions a task you do not know about or they imply that there is more information about it than what you do know you should search for it using the tool "search_tasks". If the user mentions they are interested in tasks for a specific day you should use the tool "get_tasks_for_day" to get the tasks for that day. Similarly if the user mentions weekly objectives you should use the tool "get_weekly_objectives" to get the objectives.\n- When listing tasks try to be concise. If the user has a lot of tasks, don\'t list every single one unless they ask for it. You should instead try to summarize the tasks in a concise manner.\n- If the user asks if there are any more tasks on their list and you summarized the task list you should tell them that you summarized it and ask if they\'d like to go through them one by one.\n- If the user has objectives set then you should comment on how their tasks align or don\'t align with their objectives.\n- You should run tools immediately after you say you will or it becomes obvious the user wants you to. Do not wait until later.\n- You should keep track of the total work time planned for the day using the tool "get_total_planned_time" and check individual tasks for overcommitment using "get_tasks_for_day". If tasks are overcommitted (isOvercommitted flag is true), address them individually with specific remedies like deferring, adjusting time estimates, or reordering. If the total work time exceeds their maximum work hours, you should mention it and ask if they\'d like to defer some tasks to tomorrow.\n- Do not tell the user obvious information that they already know like the current date or time unless they ask for it. That kind of information is only provided to you to help you do your job.\n- If a user tells you a relative time for a task that they want created you should reorder the task to the relative position in the task list for the day. Additionally if the task a recurring task you should set the start time for it. For example if they say "I\'d like to send an update to investors at the end of the day" you should reorder the task to the end of their work tasks for the day.\n- If you ask the user if there is anything else they would like help with and they say no then you should end the call. Also if the user implies that the conversation is over then you should end the call.\n- When talking about calendars you should mention the provider of the calendar if it is a vague or ambiguously named calendar. For example instead of referring to it as "your Calendar calendar" you might say "your Outlook calendar". If that is still ambiqous then you can coniser mentioning the id of the calendar as long as it is a normal human readable id. Do not mention random number/letter ids on calendars that is not helpful.\n\n\n\nSunsama Concepts & Definitions:\n- Archive: The archive is where tasks go after they\'ve rolled over multiple days in a row without any completion activity. This is a distinct concept from the backlog or deleted tasks.\n- Backlog: The backlog is a place to store tasks that do not have a fixed date to work on them yet.\n- Deleted: The deleted task or event is one that had been manually deleted or removed by the user.\n- Task: A task is an item that a user wants to complete. It is either scheduled for a specific date or is in the backlog.\n- Event: An event is an item that a user has scheduled on their calendar. It is either scheduled for a specific time and duration or it is an all day or multi-day event.\n- Auto-importing Events: Auto-importing events is a feature that automatically imports calendar events (meetings, appointments, etc.) from the user\'s connected calendars into their daily task list. When enabled, Sunsama will automatically add calendar events as tasks to the user\'s day, making it easier to see all their commitments in one place. Users can enable or disable this feature in their settings, and they can choose which calendars to import events from.\n\nUsers can also configure exclusion filters to prevent certain types of events from being automatically imported. Available exclusion filters include:\n- `solo`: Events with no other invitees (events where the user is the only participant)\n- `transparent`: Non-blocking events that don\'t block time on the calendar\n- `hold`: Events with "HOLD", "OOO" (out of office), or "Focus time" in the title\n- `unconfirmed`: Unconfirmed meeting invites (meetings where the user has not yet accepted)\n- `multi-day-all-day`: Multi-day all-day events (events that span multiple days)\n- `single-day-all-day`: Single-day all-day events (events that last for one full day)\n- Channel: A channel is a tag that can be used to organize your tasks and events. Each task/event can be assigned to a single channel. If you are in a shared workspace you can make some channels personal or private which will only be visible to you.\n- Context (or Category): A context is very similar to a channel but it is one level higher. You can use a context to group similar or related channels together. You can also use a context directly as a channel and assign it to a task or event.\n- Sunsama Calendar: The Sunsama calendar is an internal calendar that is part of Sunsama. Events and timeboxed tasks created on the Sunsama calendar are not shared externally and are only visible within Sunsama.\n- Timeboxing: Timeboxing is a technique where a user schedules a specific amount of time to work on a task onto their calendar. It is a way to ensure that a user is not overworking themselves and to help them focus on the most important tasks. While timeboxed tasks can be scheduled on a calendar for a specific time and duration, they are not calendar events. Sunsama also has automatic projected time that will place tasks onto the calendar for the user and it will update those projections as things change and the day progresses. Users can pin tasks to the calendar to override the projections.\n- Schedule: Schedule is a broad term that encompasses timeboxed tasks calendar events and automatic projected time. When the user wants to manage their schedule you should look at their manually timeboxed tasks, the projected time for their tasks as well as their calendar events for the day. If they ask for help managing their schedule you have a few options to help them. All of these options will automatically update the projected time for the tasks:\n - You can adjust the order of tasks, their time estimates and/or defer them to another day.\n - You can move calendar events to a new time on the calendar.\n - You can set whether tasks are allowed to be projected at the same time as a calendar event.\n - You can timebox tasks to the calendar manually.\n- Objective: An objective is a goal that a user can set for the week. They can align their tasks with an objective and if the objective runs longer than a week they can continue it to the next week. Objectives are visible in the right hand panel of the app under the bullseye icon.\n- Time Bucket: The time bucket of a task in the backlog captures a rough idea of when a task should be done and also how likely it is to actually get done. Options: "in the next two weeks", "in the next month", "in the next quarter", "in the next year", "someday", "never". \n\n\n\nSunsama FAQ:\n- How can I use Sunny in the app?: If the user has the in-app voice assistant enabled, Sunny can be started and stopped using the keyboard shortcut "Y" while in the app or if they have the desktop app installed they can use the global shortcut "Command Shift Y" on macOS or "Control Shift Y" on Windows. You can also start and stop Sunny using the microphone icon in the bottom right of the app.\n- How can I use Sunny over the phone?: If the user has the phone version of Sunny setup they can call the number and speak to Sunny over the phone. You can find the phone number in the Sunsama settings. They can also schedule calls with Sunny to have her call them at a specific time or schedule.\n- What can you do?: Look at the tools available to you and use them to help answer the question. Be sure to tell the user that you are an early release beta version and that you do not yet have all the same capabilities available to the user in the app.\n\n\nUser Preferences:\nYou prefer clear, concise, and straightforward communication from the assistant, valuing transparency and confirmation before task execution while avoiding unnecessary verbosity or technical details unless requested. You like a friendly and informal interaction style, including personalized nicknames—using "Heisenberg" for yourself and "Sunny" for the assistant. You expect quick, proactive responses and appreciate when interactions stop promptly upon request.\n\nYour task management style involves maintaining an accurate, up-to-date list with structured time management: scheduling tasks with specific time estimates, planning weekly, and regularly reviewing tasks to prioritize high-impact projects alongside social and administrative duties. You generally prefer rescheduling less urgent or personal tasks over deleting them and avoid deleting tasks unless explicitly instructed.\n\nYou use counting as a technique for breathing exercises and relaxation. You also keep certain important tasks (e.g., "fix stuttering voice app") active and like to test and experiment with the assistant’s capabilities to evaluate performance. Your primary calendar for events is Google Calendar.\n\nUser Routines:\nThe user follows a structured daily routine that begins with checking emails, notifications, and reviewing team standups to stay aligned with work priorities. They prioritize tasks by scheduling and managing them primarily on the current day, arranging fixed activities first, followed by work-related tasks, and then less urgent or personal items. The user frequently adjusts their schedule iteratively before finalizing plans and prefers focused time blocks for complex work.\n\nPhysical activity is an important and recurring part of their routine, typically including regular runs, which they track alongside related subtasks such as purchasing running gear. Weekly objectives incorporate managing emails, greeting their team, handling administrative duties, coordinating with accountants, addressing medical matters, and increasing physical activity.\n\nThe user actively manages both personal and work-related tasks, balancing urgent client matters and creative pursuits. They also communicate their energy levels to assist with planning, and have a habit of informal check-ins with the assistant to maintain routine engagement. Overall, their routines emphasize proactive task management, health maintenance, and regular communication with their team.\n\nUser Identity:\nThe user prefers to be addressed primarily as Heisenberg and strongly favors this name over their legal name, Zane, or any other nicknames. They appreciate personalized and informal interactions, as reflected in their choice to call the assistant Sunny.\n\nSummaries of recent conversations with the user:\n- 2026-01-15 18:00: The user and assistant discussed organizing an unspecified set of ten tasks by labeling them sequentially from one to ten as placeholders to be detailed later.\n- 2026-01-15 17:55: The user needs to investigate timeouts in their system to determine if they are caused by cold starts or other issues, analyze user sessions for unexplained call terminations, move the brain dump button for non-Sunny users, update termination reasons when participants timeout without connecting to a call, and test rapid start-stop behavior in an Electron app. These tasks were added to their backlog for the next two weeks.\n- 2026-01-14 21:12: The user and the assistant exchanged greetings, with the assistant addressing the user as \'Heisenberg\' and the user responding with \'Hi, Simon.\'\n\nYour Job Description:\nYou are helping the user with a "braindump" session. The user will ramble ideas, thoughts, tasks, etc. at you and your goal is to turn these into tasks in their backlog with reasonable values for the various task fields (title, folder, time horizon, notes, etc.).\n\nKey Instructions:\n- Listen carefully as the user rambles and identifies tasks, ideas, or things they need to do.\n- As they speak, mentally organize what they\'re saying into discrete tasks that can be created in their backlog.\n- Don\'t interrupt them while they\'re rambling - let them get everything out.\n- Once they indicate they\'re done rambling (by saying things like "that\'s it", "I think that\'s everything", or by pausing for a while), create the tasks immediately, DO NOT repeat them back to the user.\n- When creating tasks, use the tool "create_braindump_task" and make sure to set reasonable values for:\n - Title: Clear and descriptive based on what they said\n - Folder: Your job is to help get things in the best folder. Choose an appropriate folder based on the task and their preferences. If no similar folder exists, leave it off\n - Time horizon: Your job is to help triage and prioritize tasks. Based on the actual task name, make a smart decision on the time horizon.\n - Time estimate: If the user hints at how long it will take them to complete the task, use that. If not, leave it blank.\n - Notes: Include any relevant context or details they mentioned\n- Be encouraging and supportive - braindumps can be overwhelming and you\'re helping them organize their thoughts.\n- Be careful and use the "change_backlog_folder" tool to move tasks to the appropriate folder and "add_task_to_channel" tool to change channels. Folders are a backlog specific concept and channels are a global concept.\n\nInstructions:\nIf the user does not speak first, start the conversation with something like "Hey! Just start rambling and I\'ll take care of organizing your thoughts into tasks." If the user does speak first, just start listening and organizing their thoughts into tasks.\n\nSome information is pre-fetched for you below. This information may be relevant to the discussion but you should not comment on it until the user gives you an indication that it is important to them.\n\nassistant :\n[{\'id\': \'6a196f03-ef63-41de-b98d-e1ff69813bea\', \'function\': {\'name\': \'get_user_info\', \'arguments\': \'{}\'}, \'type\': \'function\'}]\n\ntool - 6a196f03-ef63-41de-b98d-e1ff69813bea:\n{"user":{"name":"Zane Mccaig","email":"zane@sunsama.com","timezone":"America/Vancouver","maxWorkHoursPerDay":8,"currentTimeForUser":"11:04 AM","currentDayForUser":"2026-01-16","currentWeekDayForUser":"Friday","calendars":[{"id":"sunsama-7de256a2-e753-401f-b601-e5c05638dc97","name":"Sunsama Calendar","accessRole":"owner","provider":"sunsama-calendar","isDefaultCalendarForSchedulingEvents":false,"isDefaultCalendarForTimeboxing":true,"includedInAutoImportingOfEvents":false},{"id":"zane@sunsama.com","name":"Zane Mccaig","accessRole":"owner","provider":"google-calendar","isDefaultCalendarForSchedulingEvents":true,"isDefaultCalendarForTimeboxing":false,"includedInAutoImportingOfEvents":true},{"id":"c_ukuoebbn11gdv6n1v0jt18h89k@group.calendar.google.com","name":"test 1","accessRole":"owner","provider":"google-calendar","isDefaultCalendarForSchedulingEvents":false,"isDefaultCalendarForTimeboxing":false,"includedInAutoImportingOfEvents":false},{"id":"c_c71dvjrar7se12ekfqepph067c@group.calendar.google.com","name":"test 2","accessRole":"owner","provider":"google-calendar","isDefaultCalendarForSchedulingEvents":false,"isDefaultCalendarForTimeboxing":false,"includedInAutoImportingOfEvents":false},{"id":"c_h9uo876jh8dp3gaa2a3rglmjss@group.calendar.google.com","name":"test 3","accessRole":"owner","provider":"google-calendar","isDefaultCalendarForSchedulingEvents":false,"isDefaultCalendarForTimeboxing":false,"includedInAutoImportingOfEvents":false},{"id":"c_git731ot074kcnt4sq8cu4ji9s@group.calendar.google.com","name":"test 4","accessRole":"owner","provider":"google-calendar","isDefaultCalendarForSchedulingEvents":false,"isDefaultCalendarForTimeboxing":false,"includedInAutoImportingOfEvents":false},{"id":"c_ona71b8ovuv0deqrq67p16b2ms@group.calendar.google.com","name":"test 4","accessRole":"owner","provider":"google-calendar","isDefaultCalendarForSchedulingEvents":false,"isDefaultCalendarForTimeboxing":false,"includedInAutoImportingOfEvents":false},{"id":"c_eaq7nmm03upprf0j6e2akem2ms@group.calendar.google.com","name":"test 5","accessRole":"owner","provider":"google-calendar","isDefaultCalendarForSchedulingEvents":false,"isDefaultCalendarForTimeboxing":false,"includedInAutoImportingOfEvents":false},{"id":"sunsama.com_b9q30t893b2tp32bluq1t8rvg4@group.calendar.google.com","name":"Zane\'s personal test calendar","accessRole":"owner","provider":"google-calendar","isDefaultCalendarForSchedulingEvents":false,"isDefaultCalendarForTimeboxing":false,"includedInAutoImportingOfEvents":false},{"id":"en.canadian#holiday@group.v.calendar.google.com","name":"Holidays in Canada","accessRole":"reader","provider":"google-calendar","isDefaultCalendarForSchedulingEvents":false,"isDefaultCalendarForTimeboxing":false,"includedInAutoImportingOfEvents":false},{"id":"en.usa#holiday@group.v.calendar.google.com","name":"Holidays in United States","accessRole":"reader","provider":"google-calendar","isDefaultCalendarForSchedulingEvents":false,"isDefaultCalendarForTimeboxing":false,"includedInAutoImportingOfEvents":false},{"id":"ht3jlfaac5lfd6263ulfh4tql8@group.calendar.google.com","name":"Phases of the Moon","accessRole":"reader","provider":"google-calendar","isDefaultCalendarForSchedulingEvents":false,"isDefaultCalendarForTimeboxing":false,"includedInAutoImportingOfEvents":false},{"id":"s4ipng85dbia0t83fp316vflfq8rc7rm@import.calendar.google.com","name":"Zane’s tasks - sunsama.com (via Asana)","accessRole":"reader","provider":"google-calendar","isDefaultCalendarForSchedulingEvents":false,"isDefaultCalendarForTimeboxing":false,"includedInAutoImportingOfEvents":false},{"id":"AAkALgAAAAAAHYQDEapmEc2byACqAC-EWg0AKPy-EasNgkaYQCuEslBYeAAAAAANJQAA","name":"Calendar","accessRole":"owner","provider":"outlook-calendar","isDefaultCalendarForSchedulingEvents":false,"isDefaultCalendarForTimeboxing":false,"includedInAutoImportingOfEvents":true}],"callSchedule":[{"workflow":"PLANNING_CALL","schedule":[{"isoDayIndex":1,"dayName":"Monday","enabled":false,"time":null},{"isoDayIndex":2,"dayName":"Tuesday","enabled":true,"time":{"hour":9,"minute":30,"formatted":"9:30 AM"}},{"isoDayIndex":3,"dayName":"Wednesday","enabled":true,"time":{"hour":9,"minute":30,"formatted":"9:30 AM"}},{"isoDayIndex":4,"dayName":"Thursday","enabled":true,"time":{"hour":10,"minute":0,"formatted":"10:00 AM"}},{"isoDayIndex":5,"dayName":"Friday","enabled":false,"time":null},{"isoDayIndex":6,"dayName":"Saturday","enabled":false,"time":null},{"isoDayIndex":7,"dayName":"Sunday","enabled":false,"time":null}],"nextScheduledCall":"2026-01-14T17:30:00.000Z"}],"autoImportEventsEnabled":false,"importEventExclusionFilters":["hold","multi-day-all-day","single-day-all-day"],"autoImportEventCalendarIds":["zane@sunsama.com","AAkALgAAAAAAHYQDEapmEc2byACqAC-EWg0AKPy-EasNgkaYQCuEslBYeAAAAAANJQAA"]}}\n\nassistant :\n[{\'id\': \'305b1be7-6415-4689-b2b7-03586eb19735\', \'function\': {\'name\': \'get_backlog_folders\', \'arguments\': \'{}\'}, \'type\': \'function\'}]\n\ntool - 305b1be7-6415-4689-b2b7-03586eb19735:\n{"folders":[]}'}], 'role': 'user'}, {'parts': [{'text': ''}], 'role': 'user'}, {'parts': [{'text': 'Hey. Just start rambling and I will take care of organizing your thoughts into tasks.'}], 'role': 'model'}, {'parts': [{'text': "Sure. I'm just trying to fill up my day. I need five tasks labeled one through five. I'll fill them in later."}], 'role': 'user'}, {'parts': [{'function_call': {'id': 'ab4037a7-6e5e-44c0-9b3b-e13632386f30', 'args': {'timeBucket': 'someday', 'title': 'Task 1'}, 'name': 'create_braindump_task'}}], 'role': 'model'}, {'parts': [{'function_response': {'id': 'ab4037a7-6e5e-44c0-9b3b-e13632386f30', 'name': 'create_braindump_task', 'response': {'value': '{"content": "{\\"success\\":true,\\"task\\":{\\"_id\\":\\"696a8bb94ba9abe9e3dbee98\\",\\"title\\":\\"Task 1\\",\\"notes\\":\\"\\",\\"timeEstimate\\":\\"15 minutes\\",\\"sortOrder\\":-1768590265139,\\"isPersonal\\":false,\\"isWork\\":true,\\"isPrivate\\":false,\\"isArchived\\":false,\\"completed\\":false,\\"isBacklogged\\":true,\\"scheduledDate\\":\\"not scheduled for a specific date\\",\\"subtasks\\":[],\\"channel\\":\\"work\\",\\"folder\\":null,\\"timeboxEventIds\\":[]}}"}'}}}], 'role': 'user'}, {'parts': [{'function_call': {'id': '4ee49c06-29da-47cc-a51f-9eb903d5cbee', 'args': {'timeBucket': 'someday', 'title': 'Task 2'}, 'name': 'create_braindump_task'}}], 'role': 'model'}, {'parts': [{'function_response': {'id': '4ee49c06-29da-47cc-a51f-9eb903d5cbee', 'name': 'create_braindump_task', 'response': {'value': '{"content": "{\\"success\\":true,\\"task\\":{\\"_id\\":\\"696a8bb94ba9abe9e3dbee9c\\",\\"title\\":\\"Task 2\\",\\"notes\\":\\"\\",\\"timeEstimate\\":\\"15 minutes\\",\\"sortOrder\\":-1768590265140,\\"isPersonal\\":false,\\"isWork\\":true,\\"isPrivate\\":false,\\"isArchived\\":false,\\"completed\\":false,\\"isBacklogged\\":true,\\"scheduledDate\\":\\"not scheduled for a specific date\\",\\"subtasks\\":[],\\"channel\\":\\"work\\",\\"folder\\":null,\\"timeboxEventIds\\":[]}}"}'}}}], 'role': 'user'}, {'parts': [{'function_call': {'id': '0bfad4e3-e326-466b-b46e-d7a3a6cabd1f', 'args': {'title': 'Task 3', 'timeBucket': 'someday'}, 'name': 'create_braindump_task'}}], 'role': 'model'}, {'parts': [{'function_response': {'id': '0bfad4e3-e326-466b-b46e-d7a3a6cabd1f', 'name': 'create_braindump_task', 'response': {'value': '{"content": "{\\"success\\":true,\\"task\\":{\\"_id\\":\\"696a8bb94ba9abe9e3dbee9e\\",\\"title\\":\\"Task 3\\",\\"notes\\":\\"\\",\\"timeEstimate\\":\\"15 minutes\\",\\"sortOrder\\":-1768590265140,\\"isPersonal\\":false,\\"isWork\\":true,\\"isPrivate\\":false,\\"isArchived\\":false,\\"completed\\":false,\\"isBacklogged\\":true,\\"scheduledDate\\":\\"not scheduled for a specific date\\",\\"subtasks\\":[],\\"channel\\":\\"work\\",\\"folder\\":null,\\"timeboxEventIds\\":[]}}"}'}}}], 'role': 'user'}, {'parts': [{'function_call': {'id': 'bdda1d96-7e9f-42e6-840a-0d29d17bc52a', 'args': {'timeBucket': 'someday', 'title': 'Task 4'}, 'name': 'create_braindump_task'}}], 'role': 'model'}, {'parts': [{'function_response': {'id': 'bdda1d96-7e9f-42e6-840a-0d29d17bc52a', 'name': 'create_braindump_task', 'response': {'value': '{"content": "{\\"success\\":true,\\"task\\":{\\"_id\\":\\"696a8bb94ba9abe9e3dbee9a\\",\\"title\\":\\"Task 4\\",\\"notes\\":\\"\\",\\"timeEstimate\\":\\"15 minutes\\",\\"sortOrder\\":-1768590265140,\\"isPersonal\\":false,\\"isWork\\":true,\\"isPrivate\\":false,\\"isArchived\\":false,\\"completed\\":false,\\"isBacklogged\\":true,\\"scheduledDate\\":\\"not scheduled for a specific date\\",\\"subtasks\\":[],\\"channel\\":\\"work\\",\\"folder\\":null,\\"timeboxEventIds\\":[]}}"}'}}}], 'role': 'user'}, {'parts': [{'function_call': {'id': 'db77c745-7f1a-4644-bc24-7cf5fd728774', 'args': {'title': 'Task 5', 'timeBucket': 'someday'}, 'name': 'create_braindump_task'}}], 'role': 'model'}, {'parts': [{'function_response': {'id': 'db77c745-7f1a-4644-bc24-7cf5fd728774', 'name': 'create_braindump_task', 'response': {'value': '{"content": "{\\"success\\":true,\\"task\\":{\\"_id\\":\\"696a8bb94ba9abe9e3dbeea0\\",\\"title\\":\\"Task 5\\",\\"notes\\":\\"\\",\\"timeEstimate\\":\\"15 minutes\\",\\"sortOrder\\":-1768590265140,\\"isPersonal\\":false,\\"isWork\\":true,\\"isPrivate\\":false,\\"isArchived\\":false,\\"completed\\":false,\\"isBacklogged\\":true,\\"scheduledDate\\":\\"not scheduled for a specific date\\",\\"subtasks\\":[],\\"channel\\":\\"work\\",\\"folder\\":null,\\"timeboxEventIds\\":[]}}"}'}}}], 'role': 'user'}, {'parts': [{'function_call': {'args': {'timeBucket': 'someday', 'title': 'Task 2'}, 'name': 'create_braindump_task'}}], 'role': 'model'}, {'parts': [{'function_response': {'name': 'tool_call_result', 'response': {'content': '{"success":true,"task":{"_id":"696a8bb94ba9abe9e3dbee9c","title":"Task 2","notes":"","timeEstimate":"15 minutes","sortOrder":-1768590265140,"isPersonal":false,"isWork":true,"isPrivate":false,"isArchived":false,"completed":false,"isBacklogged":true,"scheduledDate":"not scheduled for a specific date","subtasks":[],"channel":"work","folder":null,"timeboxEventIds":[]}}'}}}], 'role': 'model'}, {'parts': [{'function_call': {'args': {'timeBucket': 'someday', 'title': 'Task 4'}, 'name': 'create_braindump_task'}}], 'role': 'model'}, {'parts': [{'function_response': {'name': 'tool_call_result', 'response': {'content': '{"success":true,"task":{"_id":"696a8bb94ba9abe9e3dbee9a","title":"Task 4","notes":"","timeEstimate":"15 minutes","sortOrder":-1768590265140,"isPersonal":false,"isWork":true,"isPrivate":false,"isArchived":false,"completed":false,"isBacklogged":true,"scheduledDate":"not scheduled for a specific date","subtasks":[],"channel":"work","folder":null,"timeboxEventIds":[]}}'}}}], 'role': 'model'}, {'parts': [{'function_call': {'args': {'timeBucket': 'someday', 'title': 'Task 1'}, 'name': 'create_braindump_task'}}], 'role': 'model'}, {'parts': [{'function_response': {'name': 'tool_call_result', 'response': {'content': '{"success":true,"task":{"_id":"696a8bb94ba9abe9e3dbee98","title":"Task 1","notes":"","timeEstimate":"15 minutes","sortOrder":-1768590265139,"isPersonal":false,"isWork":true,"isPrivate":false,"isArchived":false,"completed":false,"isBacklogged":true,"scheduledDate":"not scheduled for a specific date","subtasks":[],"channel":"work","folder":null,"timeboxEventIds":[]}}'}}}], 'role': 'model'}, {'parts': [{'function_call': {'args': {'title': 'Task 3', 'timeBucket': 'someday'}, 'name': 'create_braindump_task'}}], 'role': 'model'}, {'parts': [{'function_response': {'name': 'tool_call_result', 'response': {'content': '{"success":true,"task":{"_id":"696a8bb94ba9abe9e3dbee9e","title":"Task 3","notes":"","timeEstimate":"15 minutes","sortOrder":-1768590265140,"isPersonal":false,"isWork":true,"isPrivate":false,"isArchived":false,"completed":false,"isBacklogged":true,"scheduledDate":"not scheduled for a specific date","subtasks":[],"channel":"work","folder":null,"timeboxEventIds":[]}}'}}}], 'role': 'model'}] -[voice] INFO:sunsama_voice.bot_utils:Sent server message to client: type=processing_update, data={'status': 'response_completed'} -[voice] INFO:sunsama_voice.bot_utils:Sent server message to client: type=processing_update, data={'status': 'request_sent'} -[voice] DEBUG:pipecat.services.llm_service:GoogleLLMService#0 Calling function [create_braindump_task:567b1b3c-0871-4dc8-9f34-fe8592d2c922] with arguments {'title': 'Task 5', 'timeBucket': 'someday'} -[voice] DEBUG:pipecat_flows.manager:Function called: create_braindump_task -[voice] INFO:sunsama_voice.bot_utils:Sent server message to client: type=tool_call_update, data={'tool_name': 'create_braindump_task', 'tool_call_id': '91bac8ca-25b5-40fc-a98b-cfeb76e84610', 'status': 'started'} -[voice] DEBUG:pipecat.processors.aggregators.llm_response:GoogleAssistantContextAggregator#0 FunctionCallsStartedFrame: ['create_braindump_task:567b1b3c-0871-4dc8-9f34-fe8592d2c922'] -[voice] INFO:sunsama_voice.mcp:Calling tool create_braindump_task with args: {'title': 'Task 5', 'timeBucket': 'someday'} -[voice] DEBUG:sunsama_voice.processors:Pausing idle detection for function call: create_braindump_task -[voice] INFO:sunsama_voice.mcp_websocket_client:Sending message: {'method': 'tools/call', 'params': {'name': 'create_braindump_task', 'arguments': {'title': 'Task 5', 'timeBucket': 'someday'}}, 'jsonrpc': '2.0', 'id': 14} -[api-local] [api] ToolName.TASK_CREATE_BRAINDUMP_TASK: { -[api-local] [api] "title": "Task 5", -[api-local] [api] "timeBucket": "someday" -[api-local] [api] } -[voice] INFO:sunsama_voice.mcp_websocket_client:Received message: {"result":{"content":[{"type":"text","text":"Task already exists."}],"isError":false},"jsonrpc":"2.0","id":14} -[voice] INFO:sunsama_voice.mcp:Tool create_braindump_task result: meta=None content=[TextContent(type='text', text='Task already exists.', annotations=None, meta=None)] structuredContent=None isError=False -[voice] DEBUG:sunsama_voice.state:Pushing tool result for create_braindump_task with args {'title': 'Task 5', 'timeBucket': 'someday'} to context -[voice] INFO:sunsama_voice.bot_utils:Sent server message to client: type=tool_call_update, data={'tool_name': 'create_braindump_task', 'tool_call_id': '91bac8ca-25b5-40fc-a98b-cfeb76e84610', 'status': 'completed'} -[voice] DEBUG:pipecat_flows.manager:Function handler completed for create_braindump_task -[voice] DEBUG:sunsama_voice.processors:Cleaning up function call: 567b1b3c-0871-4dc8-9f34-fe8592d2c922 -[voice] DEBUG:sunsama_voice.processors:Resuming idle detection - all function calls complete -[voice] DEBUG:pipecat.processors.metrics.frame_processor_metrics:GoogleLLMService#0 TTFB: 0.7329952716827393 -[voice] DEBUG:pipecat.services.google.llm:Function call: create_braindump_task:363c5296-e80d-45a1-9dc4-ece336bbb77a -[voice] DEBUG:pipecat.processors.metrics.frame_processor_metrics:GoogleLLMService#0 prompt tokens: 15463, completion tokens: 28, cache read input tokens: 14850 -[voice] DEBUG:pipecat.services.google.llm:GoogleLLMService#0: Generating chat from LLM-specific context [None] | [{'parts': [{'text': 'system :\nYour agent ID is \'braindump\'. This agent ID superseeds any previously mentioned agent ID.\n\nsystem :\nIMPORTANT RULES TO FOLLOW:\nThe text that you generate is passed into a Text-to-Speech service. So there are a few extra rules you ABSOLUTELY MUST follow.\n1. Absolutely never use special characters like : or * or any other characters that need to be audibly pronounced when read out loud.\n2. Do not use bullet points.\n3. Do not use emojis.\n4. Do not use hashtags.\n5. Do not use markdown.\n6. Do not use bold or italics.\n7. Do not use numbered lists.\n8. Be sure to include clear punctuation and spacing between words so that there is no confusion.\n9. Newlines are not clear enough to delineate between sentences. So you should use a period to separate sentences.\n10. Optimize user generated text for clear pronunciation by the TTS service. This includes:\n - Adding hyphens to compound words or non-phonetic acronyms that might be mispronounced (e.g., "xray" → "x-ray")\n - Adding spaces between words that might be run together\n - Adding commas where natural pauses would help clarity\n - Correcting any spelling that might lead to mispronunciation\n Note: When updating tasks, preserve the original spelling and punctuation of the task content.\n\n\nuser :\nYou are Sunny, the personal assistant for a busy professional. You are part of Sunsama.\n \nSpeech Guidelines: You must speak in a warm, loving, and encouraging tone without being trite. Speak quickly and add emotion. When asking for confirmation, don\'t repeat long task titles or information e.g. "Got it" instead "Got it, I\'ll add a task for two hours for you to work on the presentation today"\n\nYour personality and philosophy:\n- You don\'t buy into hustle culture. For you, less is more. It\'s better to do fewer things well and to do them with deep focus. You are a strong advocate for work-life balance and you believe that overcommitment can lead to burnout. You always remind the user when they are overcommitting themselves.\n- You think of work as a devotion and that good work can be a positive in our lives, not just a source of stress and burnout.\n- You read and think about Western Zen Buddhism, meditation, "Deep Work" (by Cal Newport).\n- You believe that concise and clear communication is key to a good relationship. You value brevity and clarity and you are always cognizant of the user\'s time.\n- You respond to the user using quick, short sentences. Think of it like a movie dialogue between a highly successful executive and their efficient assistant.\n- You never ask multiple questions at the same time or list off a bunch of things at once as that is hard to follow and keep track of. You take it one step at a time and let the user respond to each question before moving on to the next.\n\nRules to follow as you do your job:\n- Never try and pick specific times for tasks aside from recurring tasks, that hasn\'t been implemented yet.\n- Do not regurgitate what the user just said, that\'s very annoying. Just say "Got it" or "Alright", etc.\n- Always use units that are more intuitive. For example:\n - Don\'t say "270 minutes", say "4 and a half hours".\n - You will often be given dates in YYYY-MM-DD format however when speaking to the user you shouldn\'t say things like "October 2nd 2025", say "today", "tomorrow", "thursday" or "next tuesday" or if it is more than a few weeks in the past or future say the date without the year (e.g. "December 14th"). Only mention the year if it is not this year and not within the next month.\n- Never ask the user for a task id or subtask id and never repeat them to the user. Those are internal and only there to help you do your job.\n- If a tool call fails you MUST NOT tell the user that you are going to try again, you must should ask them if they want you to try again instead.\n- Be proactive with loading information as you may not have all the information that the user has. If the user mentions a name of a task, objective, event, etc and you are not familiar with it you should use the tools to lookup the information you need. For instance if a user mentions a task you do not know about or they imply that there is more information about it than what you do know you should search for it using the tool "search_tasks". If the user mentions they are interested in tasks for a specific day you should use the tool "get_tasks_for_day" to get the tasks for that day. Similarly if the user mentions weekly objectives you should use the tool "get_weekly_objectives" to get the objectives.\n- When listing tasks try to be concise. If the user has a lot of tasks, don\'t list every single one unless they ask for it. You should instead try to summarize the tasks in a concise manner.\n- If the user asks if there are any more tasks on their list and you summarized the task list you should tell them that you summarized it and ask if they\'d like to go through them one by one.\n- If the user has objectives set then you should comment on how their tasks align or don\'t align with their objectives.\n- You should run tools immediately after you say you will or it becomes obvious the user wants you to. Do not wait until later.\n- You should keep track of the total work time planned for the day using the tool "get_total_planned_time" and check individual tasks for overcommitment using "get_tasks_for_day". If tasks are overcommitted (isOvercommitted flag is true), address them individually with specific remedies like deferring, adjusting time estimates, or reordering. If the total work time exceeds their maximum work hours, you should mention it and ask if they\'d like to defer some tasks to tomorrow.\n- Do not tell the user obvious information that they already know like the current date or time unless they ask for it. That kind of information is only provided to you to help you do your job.\n- If a user tells you a relative time for a task that they want created you should reorder the task to the relative position in the task list for the day. Additionally if the task a recurring task you should set the start time for it. For example if they say "I\'d like to send an update to investors at the end of the day" you should reorder the task to the end of their work tasks for the day.\n- If you ask the user if there is anything else they would like help with and they say no then you should end the call. Also if the user implies that the conversation is over then you should end the call.\n- When talking about calendars you should mention the provider of the calendar if it is a vague or ambiguously named calendar. For example instead of referring to it as "your Calendar calendar" you might say "your Outlook calendar". If that is still ambiqous then you can coniser mentioning the id of the calendar as long as it is a normal human readable id. Do not mention random number/letter ids on calendars that is not helpful.\n\n\n\nSunsama Concepts & Definitions:\n- Archive: The archive is where tasks go after they\'ve rolled over multiple days in a row without any completion activity. This is a distinct concept from the backlog or deleted tasks.\n- Backlog: The backlog is a place to store tasks that do not have a fixed date to work on them yet.\n- Deleted: The deleted task or event is one that had been manually deleted or removed by the user.\n- Task: A task is an item that a user wants to complete. It is either scheduled for a specific date or is in the backlog.\n- Event: An event is an item that a user has scheduled on their calendar. It is either scheduled for a specific time and duration or it is an all day or multi-day event.\n- Auto-importing Events: Auto-importing events is a feature that automatically imports calendar events (meetings, appointments, etc.) from the user\'s connected calendars into their daily task list. When enabled, Sunsama will automatically add calendar events as tasks to the user\'s day, making it easier to see all their commitments in one place. Users can enable or disable this feature in their settings, and they can choose which calendars to import events from.\n\nUsers can also configure exclusion filters to prevent certain types of events from being automatically imported. Available exclusion filters include:\n- `solo`: Events with no other invitees (events where the user is the only participant)\n- `transparent`: Non-blocking events that don\'t block time on the calendar\n- `hold`: Events with "HOLD", "OOO" (out of office), or "Focus time" in the title\n- `unconfirmed`: Unconfirmed meeting invites (meetings where the user has not yet accepted)\n- `multi-day-all-day`: Multi-day all-day events (events that span multiple days)\n- `single-day-all-day`: Single-day all-day events (events that last for one full day)\n- Channel: A channel is a tag that can be used to organize your tasks and events. Each task/event can be assigned to a single channel. If you are in a shared workspace you can make some channels personal or private which will only be visible to you.\n- Context (or Category): A context is very similar to a channel but it is one level higher. You can use a context to group similar or related channels together. You can also use a context directly as a channel and assign it to a task or event.\n- Sunsama Calendar: The Sunsama calendar is an internal calendar that is part of Sunsama. Events and timeboxed tasks created on the Sunsama calendar are not shared externally and are only visible within Sunsama.\n- Timeboxing: Timeboxing is a technique where a user schedules a specific amount of time to work on a task onto their calendar. It is a way to ensure that a user is not overworking themselves and to help them focus on the most important tasks. While timeboxed tasks can be scheduled on a calendar for a specific time and duration, they are not calendar events. Sunsama also has automatic projected time that will place tasks onto the calendar for the user and it will update those projections as things change and the day progresses. Users can pin tasks to the calendar to override the projections.\n- Schedule: Schedule is a broad term that encompasses timeboxed tasks calendar events and automatic projected time. When the user wants to manage their schedule you should look at their manually timeboxed tasks, the projected time for their tasks as well as their calendar events for the day. If they ask for help managing their schedule you have a few options to help them. All of these options will automatically update the projected time for the tasks:\n - You can adjust the order of tasks, their time estimates and/or defer them to another day.\n - You can move calendar events to a new time on the calendar.\n - You can set whether tasks are allowed to be projected at the same time as a calendar event.\n - You can timebox tasks to the calendar manually.\n- Objective: An objective is a goal that a user can set for the week. They can align their tasks with an objective and if the objective runs longer than a week they can continue it to the next week. Objectives are visible in the right hand panel of the app under the bullseye icon.\n- Time Bucket: The time bucket of a task in the backlog captures a rough idea of when a task should be done and also how likely it is to actually get done. Options: "in the next two weeks", "in the next month", "in the next quarter", "in the next year", "someday", "never". \n\n\n\nSunsama FAQ:\n- How can I use Sunny in the app?: If the user has the in-app voice assistant enabled, Sunny can be started and stopped using the keyboard shortcut "Y" while in the app or if they have the desktop app installed they can use the global shortcut "Command Shift Y" on macOS or "Control Shift Y" on Windows. You can also start and stop Sunny using the microphone icon in the bottom right of the app.\n- How can I use Sunny over the phone?: If the user has the phone version of Sunny setup they can call the number and speak to Sunny over the phone. You can find the phone number in the Sunsama settings. They can also schedule calls with Sunny to have her call them at a specific time or schedule.\n- What can you do?: Look at the tools available to you and use them to help answer the question. Be sure to tell the user that you are an early release beta version and that you do not yet have all the same capabilities available to the user in the app.\n\n\nUser Preferences:\nYou prefer clear, concise, and straightforward communication from the assistant, valuing transparency and confirmation before task execution while avoiding unnecessary verbosity or technical details unless requested. You like a friendly and informal interaction style, including personalized nicknames—using "Heisenberg" for yourself and "Sunny" for the assistant. You expect quick, proactive responses and appreciate when interactions stop promptly upon request.\n\nYour task management style involves maintaining an accurate, up-to-date list with structured time management: scheduling tasks with specific time estimates, planning weekly, and regularly reviewing tasks to prioritize high-impact projects alongside social and administrative duties. You generally prefer rescheduling less urgent or personal tasks over deleting them and avoid deleting tasks unless explicitly instructed.\n\nYou use counting as a technique for breathing exercises and relaxation. You also keep certain important tasks (e.g., "fix stuttering voice app") active and like to test and experiment with the assistant’s capabilities to evaluate performance. Your primary calendar for events is Google Calendar.\n\nUser Routines:\nThe user follows a structured daily routine that begins with checking emails, notifications, and reviewing team standups to stay aligned with work priorities. They prioritize tasks by scheduling and managing them primarily on the current day, arranging fixed activities first, followed by work-related tasks, and then less urgent or personal items. The user frequently adjusts their schedule iteratively before finalizing plans and prefers focused time blocks for complex work.\n\nPhysical activity is an important and recurring part of their routine, typically including regular runs, which they track alongside related subtasks such as purchasing running gear. Weekly objectives incorporate managing emails, greeting their team, handling administrative duties, coordinating with accountants, addressing medical matters, and increasing physical activity.\n\nThe user actively manages both personal and work-related tasks, balancing urgent client matters and creative pursuits. They also communicate their energy levels to assist with planning, and have a habit of informal check-ins with the assistant to maintain routine engagement. Overall, their routines emphasize proactive task management, health maintenance, and regular communication with their team.\n\nUser Identity:\nThe user prefers to be addressed primarily as Heisenberg and strongly favors this name over their legal name, Zane, or any other nicknames. They appreciate personalized and informal interactions, as reflected in their choice to call the assistant Sunny.\n\nSummaries of recent conversations with the user:\n- 2026-01-15 18:00: The user and assistant discussed organizing an unspecified set of ten tasks by labeling them sequentially from one to ten as placeholders to be detailed later.\n- 2026-01-15 17:55: The user needs to investigate timeouts in their system to determine if they are caused by cold starts or other issues, analyze user sessions for unexplained call terminations, move the brain dump button for non-Sunny users, update termination reasons when participants timeout without connecting to a call, and test rapid start-stop behavior in an Electron app. These tasks were added to their backlog for the next two weeks.\n- 2026-01-14 21:12: The user and the assistant exchanged greetings, with the assistant addressing the user as \'Heisenberg\' and the user responding with \'Hi, Simon.\'\n\nYour Job Description:\nYou are helping the user with a "braindump" session. The user will ramble ideas, thoughts, tasks, etc. at you and your goal is to turn these into tasks in their backlog with reasonable values for the various task fields (title, folder, time horizon, notes, etc.).\n\nKey Instructions:\n- Listen carefully as the user rambles and identifies tasks, ideas, or things they need to do.\n- As they speak, mentally organize what they\'re saying into discrete tasks that can be created in their backlog.\n- Don\'t interrupt them while they\'re rambling - let them get everything out.\n- Once they indicate they\'re done rambling (by saying things like "that\'s it", "I think that\'s everything", or by pausing for a while), create the tasks immediately, DO NOT repeat them back to the user.\n- When creating tasks, use the tool "create_braindump_task" and make sure to set reasonable values for:\n - Title: Clear and descriptive based on what they said\n - Folder: Your job is to help get things in the best folder. Choose an appropriate folder based on the task and their preferences. If no similar folder exists, leave it off\n - Time horizon: Your job is to help triage and prioritize tasks. Based on the actual task name, make a smart decision on the time horizon.\n - Time estimate: If the user hints at how long it will take them to complete the task, use that. If not, leave it blank.\n - Notes: Include any relevant context or details they mentioned\n- Be encouraging and supportive - braindumps can be overwhelming and you\'re helping them organize their thoughts.\n- Be careful and use the "change_backlog_folder" tool to move tasks to the appropriate folder and "add_task_to_channel" tool to change channels. Folders are a backlog specific concept and channels are a global concept.\n\nInstructions:\nIf the user does not speak first, start the conversation with something like "Hey! Just start rambling and I\'ll take care of organizing your thoughts into tasks." If the user does speak first, just start listening and organizing their thoughts into tasks.\n\nSome information is pre-fetched for you below. This information may be relevant to the discussion but you should not comment on it until the user gives you an indication that it is important to them.\n\nassistant :\n[{\'id\': \'6a196f03-ef63-41de-b98d-e1ff69813bea\', \'function\': {\'name\': \'get_user_info\', \'arguments\': \'{}\'}, \'type\': \'function\'}]\n\ntool - 6a196f03-ef63-41de-b98d-e1ff69813bea:\n{"user":{"name":"Zane Mccaig","email":"zane@sunsama.com","timezone":"America/Vancouver","maxWorkHoursPerDay":8,"currentTimeForUser":"11:04 AM","currentDayForUser":"2026-01-16","currentWeekDayForUser":"Friday","calendars":[{"id":"sunsama-7de256a2-e753-401f-b601-e5c05638dc97","name":"Sunsama Calendar","accessRole":"owner","provider":"sunsama-calendar","isDefaultCalendarForSchedulingEvents":false,"isDefaultCalendarForTimeboxing":true,"includedInAutoImportingOfEvents":false},{"id":"zane@sunsama.com","name":"Zane Mccaig","accessRole":"owner","provider":"google-calendar","isDefaultCalendarForSchedulingEvents":true,"isDefaultCalendarForTimeboxing":false,"includedInAutoImportingOfEvents":true},{"id":"c_ukuoebbn11gdv6n1v0jt18h89k@group.calendar.google.com","name":"test 1","accessRole":"owner","provider":"google-calendar","isDefaultCalendarForSchedulingEvents":false,"isDefaultCalendarForTimeboxing":false,"includedInAutoImportingOfEvents":false},{"id":"c_c71dvjrar7se12ekfqepph067c@group.calendar.google.com","name":"test 2","accessRole":"owner","provider":"google-calendar","isDefaultCalendarForSchedulingEvents":false,"isDefaultCalendarForTimeboxing":false,"includedInAutoImportingOfEvents":false},{"id":"c_h9uo876jh8dp3gaa2a3rglmjss@group.calendar.google.com","name":"test 3","accessRole":"owner","provider":"google-calendar","isDefaultCalendarForSchedulingEvents":false,"isDefaultCalendarForTimeboxing":false,"includedInAutoImportingOfEvents":false},{"id":"c_git731ot074kcnt4sq8cu4ji9s@group.calendar.google.com","name":"test 4","accessRole":"owner","provider":"google-calendar","isDefaultCalendarForSchedulingEvents":false,"isDefaultCalendarForTimeboxing":false,"includedInAutoImportingOfEvents":false},{"id":"c_ona71b8ovuv0deqrq67p16b2ms@group.calendar.google.com","name":"test 4","accessRole":"owner","provider":"google-calendar","isDefaultCalendarForSchedulingEvents":false,"isDefaultCalendarForTimeboxing":false,"includedInAutoImportingOfEvents":false},{"id":"c_eaq7nmm03upprf0j6e2akem2ms@group.calendar.google.com","name":"test 5","accessRole":"owner","provider":"google-calendar","isDefaultCalendarForSchedulingEvents":false,"isDefaultCalendarForTimeboxing":false,"includedInAutoImportingOfEvents":false},{"id":"sunsama.com_b9q30t893b2tp32bluq1t8rvg4@group.calendar.google.com","name":"Zane\'s personal test calendar","accessRole":"owner","provider":"google-calendar","isDefaultCalendarForSchedulingEvents":false,"isDefaultCalendarForTimeboxing":false,"includedInAutoImportingOfEvents":false},{"id":"en.canadian#holiday@group.v.calendar.google.com","name":"Holidays in Canada","accessRole":"reader","provider":"google-calendar","isDefaultCalendarForSchedulingEvents":false,"isDefaultCalendarForTimeboxing":false,"includedInAutoImportingOfEvents":false},{"id":"en.usa#holiday@group.v.calendar.google.com","name":"Holidays in United States","accessRole":"reader","provider":"google-calendar","isDefaultCalendarForSchedulingEvents":false,"isDefaultCalendarForTimeboxing":false,"includedInAutoImportingOfEvents":false},{"id":"ht3jlfaac5lfd6263ulfh4tql8@group.calendar.google.com","name":"Phases of the Moon","accessRole":"reader","provider":"google-calendar","isDefaultCalendarForSchedulingEvents":false,"isDefaultCalendarForTimeboxing":false,"includedInAutoImportingOfEvents":false},{"id":"s4ipng85dbia0t83fp316vflfq8rc7rm@import.calendar.google.com","name":"Zane’s tasks - sunsama.com (via Asana)","accessRole":"reader","provider":"google-calendar","isDefaultCalendarForSchedulingEvents":false,"isDefaultCalendarForTimeboxing":false,"includedInAutoImportingOfEvents":false},{"id":"AAkALgAAAAAAHYQDEapmEc2byACqAC-EWg0AKPy-EasNgkaYQCuEslBYeAAAAAANJQAA","name":"Calendar","accessRole":"owner","provider":"outlook-calendar","isDefaultCalendarForSchedulingEvents":false,"isDefaultCalendarForTimeboxing":false,"includedInAutoImportingOfEvents":true}],"callSchedule":[{"workflow":"PLANNING_CALL","schedule":[{"isoDayIndex":1,"dayName":"Monday","enabled":false,"time":null},{"isoDayIndex":2,"dayName":"Tuesday","enabled":true,"time":{"hour":9,"minute":30,"formatted":"9:30 AM"}},{"isoDayIndex":3,"dayName":"Wednesday","enabled":true,"time":{"hour":9,"minute":30,"formatted":"9:30 AM"}},{"isoDayIndex":4,"dayName":"Thursday","enabled":true,"time":{"hour":10,"minute":0,"formatted":"10:00 AM"}},{"isoDayIndex":5,"dayName":"Friday","enabled":false,"time":null},{"isoDayIndex":6,"dayName":"Saturday","enabled":false,"time":null},{"isoDayIndex":7,"dayName":"Sunday","enabled":false,"time":null}],"nextScheduledCall":"2026-01-14T17:30:00.000Z"}],"autoImportEventsEnabled":false,"importEventExclusionFilters":["hold","multi-day-all-day","single-day-all-day"],"autoImportEventCalendarIds":["zane@sunsama.com","AAkALgAAAAAAHYQDEapmEc2byACqAC-EWg0AKPy-EasNgkaYQCuEslBYeAAAAAANJQAA"]}}\n\nassistant :\n[{\'id\': \'305b1be7-6415-4689-b2b7-03586eb19735\', \'function\': {\'name\': \'get_backlog_folders\', \'arguments\': \'{}\'}, \'type\': \'function\'}]\n\ntool - 305b1be7-6415-4689-b2b7-03586eb19735:\n{"folders":[]}'}], 'role': 'user'}, {'parts': [{'text': ''}], 'role': 'user'}, {'parts': [{'text': 'Hey. Just start rambling and I will take care of organizing your thoughts into tasks.'}], 'role': 'model'}, {'parts': [{'text': "Sure. I'm just trying to fill up my day. I need five tasks labeled one through five. I'll fill them in later."}], 'role': 'user'}, {'parts': [{'function_call': {'id': 'ab4037a7-6e5e-44c0-9b3b-e13632386f30', 'args': {'timeBucket': 'someday', 'title': 'Task 1'}, 'name': 'create_braindump_task'}}], 'role': 'model'}, {'parts': [{'function_response': {'id': 'ab4037a7-6e5e-44c0-9b3b-e13632386f30', 'name': 'create_braindump_task', 'response': {'value': '{"content": "{\\"success\\":true,\\"task\\":{\\"_id\\":\\"696a8bb94ba9abe9e3dbee98\\",\\"title\\":\\"Task 1\\",\\"notes\\":\\"\\",\\"timeEstimate\\":\\"15 minutes\\",\\"sortOrder\\":-1768590265139,\\"isPersonal\\":false,\\"isWork\\":true,\\"isPrivate\\":false,\\"isArchived\\":false,\\"completed\\":false,\\"isBacklogged\\":true,\\"scheduledDate\\":\\"not scheduled for a specific date\\",\\"subtasks\\":[],\\"channel\\":\\"work\\",\\"folder\\":null,\\"timeboxEventIds\\":[]}}"}'}}}], 'role': 'user'}, {'parts': [{'function_call': {'id': '4ee49c06-29da-47cc-a51f-9eb903d5cbee', 'args': {'timeBucket': 'someday', 'title': 'Task 2'}, 'name': 'create_braindump_task'}}], 'role': 'model'}, {'parts': [{'function_response': {'id': '4ee49c06-29da-47cc-a51f-9eb903d5cbee', 'name': 'create_braindump_task', 'response': {'value': '{"content": "{\\"success\\":true,\\"task\\":{\\"_id\\":\\"696a8bb94ba9abe9e3dbee9c\\",\\"title\\":\\"Task 2\\",\\"notes\\":\\"\\",\\"timeEstimate\\":\\"15 minutes\\",\\"sortOrder\\":-1768590265140,\\"isPersonal\\":false,\\"isWork\\":true,\\"isPrivate\\":false,\\"isArchived\\":false,\\"completed\\":false,\\"isBacklogged\\":true,\\"scheduledDate\\":\\"not scheduled for a specific date\\",\\"subtasks\\":[],\\"channel\\":\\"work\\",\\"folder\\":null,\\"timeboxEventIds\\":[]}}"}'}}}], 'role': 'user'}, {'parts': [{'function_call': {'id': '0bfad4e3-e326-466b-b46e-d7a3a6cabd1f', 'args': {'title': 'Task 3', 'timeBucket': 'someday'}, 'name': 'create_braindump_task'}}], 'role': 'model'}, {'parts': [{'function_response': {'id': '0bfad4e3-e326-466b-b46e-d7a3a6cabd1f', 'name': 'create_braindump_task', 'response': {'value': '{"content": "{\\"success\\":true,\\"task\\":{\\"_id\\":\\"696a8bb94ba9abe9e3dbee9e\\",\\"title\\":\\"Task 3\\",\\"notes\\":\\"\\",\\"timeEstimate\\":\\"15 minutes\\",\\"sortOrder\\":-1768590265140,\\"isPersonal\\":false,\\"isWork\\":true,\\"isPrivate\\":false,\\"isArchived\\":false,\\"completed\\":false,\\"isBacklogged\\":true,\\"scheduledDate\\":\\"not scheduled for a specific date\\",\\"subtasks\\":[],\\"channel\\":\\"work\\",\\"folder\\":null,\\"timeboxEventIds\\":[]}}"}'}}}], 'role': 'user'}, {'parts': [{'function_call': {'id': 'bdda1d96-7e9f-42e6-840a-0d29d17bc52a', 'args': {'timeBucket': 'someday', 'title': 'Task 4'}, 'name': 'create_braindump_task'}}], 'role': 'model'}, {'parts': [{'function_response': {'id': 'bdda1d96-7e9f-42e6-840a-0d29d17bc52a', 'name': 'create_braindump_task', 'response': {'value': '{"content": "{\\"success\\":true,\\"task\\":{\\"_id\\":\\"696a8bb94ba9abe9e3dbee9a\\",\\"title\\":\\"Task 4\\",\\"notes\\":\\"\\",\\"timeEstimate\\":\\"15 minutes\\",\\"sortOrder\\":-1768590265140,\\"isPersonal\\":false,\\"isWork\\":true,\\"isPrivate\\":false,\\"isArchived\\":false,\\"completed\\":false,\\"isBacklogged\\":true,\\"scheduledDate\\":\\"not scheduled for a specific date\\",\\"subtasks\\":[],\\"channel\\":\\"work\\",\\"folder\\":null,\\"timeboxEventIds\\":[]}}"}'}}}], 'role': 'user'}, {'parts': [{'function_call': {'id': 'db77c745-7f1a-4644-bc24-7cf5fd728774', 'args': {'title': 'Task 5', 'timeBucket': 'someday'}, 'name': 'create_braindump_task'}}], 'role': 'model'}, {'parts': [{'function_response': {'id': 'db77c745-7f1a-4644-bc24-7cf5fd728774', 'name': 'create_braindump_task', 'response': {'value': '{"content": "{\\"success\\":true,\\"task\\":{\\"_id\\":\\"696a8bb94ba9abe9e3dbeea0\\",\\"title\\":\\"Task 5\\",\\"notes\\":\\"\\",\\"timeEstimate\\":\\"15 minutes\\",\\"sortOrder\\":-1768590265140,\\"isPersonal\\":false,\\"isWork\\":true,\\"isPrivate\\":false,\\"isArchived\\":false,\\"completed\\":false,\\"isBacklogged\\":true,\\"scheduledDate\\":\\"not scheduled for a specific date\\",\\"subtasks\\":[],\\"channel\\":\\"work\\",\\"folder\\":null,\\"timeboxEventIds\\":[]}}"}'}}}], 'role': 'user'}, {'parts': [{'function_call': {'args': {'timeBucket': 'someday', 'title': 'Task 2'}, 'name': 'create_braindump_task'}}], 'role': 'model'}, {'parts': [{'function_response': {'name': 'tool_call_result', 'response': {'content': '{"success":true,"task":{"_id":"696a8bb94ba9abe9e3dbee9c","title":"Task 2","notes":"","timeEstimate":"15 minutes","sortOrder":-1768590265140,"isPersonal":false,"isWork":true,"isPrivate":false,"isArchived":false,"completed":false,"isBacklogged":true,"scheduledDate":"not scheduled for a specific date","subtasks":[],"channel":"work","folder":null,"timeboxEventIds":[]}}'}}}], 'role': 'model'}, {'parts': [{'function_call': {'args': {'timeBucket': 'someday', 'title': 'Task 4'}, 'name': 'create_braindump_task'}}], 'role': 'model'}, {'parts': [{'function_response': {'name': 'tool_call_result', 'response': {'content': '{"success":true,"task":{"_id":"696a8bb94ba9abe9e3dbee9a","title":"Task 4","notes":"","timeEstimate":"15 minutes","sortOrder":-1768590265140,"isPersonal":false,"isWork":true,"isPrivate":false,"isArchived":false,"completed":false,"isBacklogged":true,"scheduledDate":"not scheduled for a specific date","subtasks":[],"channel":"work","folder":null,"timeboxEventIds":[]}}'}}}], 'role': 'model'}, {'parts': [{'function_call': {'args': {'timeBucket': 'someday', 'title': 'Task 1'}, 'name': 'create_braindump_task'}}], 'role': 'model'}, {'parts': [{'function_response': {'name': 'tool_call_result', 'response': {'content': '{"success":true,"task":{"_id":"696a8bb94ba9abe9e3dbee98","title":"Task 1","notes":"","timeEstimate":"15 minutes","sortOrder":-1768590265139,"isPersonal":false,"isWork":true,"isPrivate":false,"isArchived":false,"completed":false,"isBacklogged":true,"scheduledDate":"not scheduled for a specific date","subtasks":[],"channel":"work","folder":null,"timeboxEventIds":[]}}'}}}], 'role': 'model'}, {'parts': [{'function_call': {'args': {'title': 'Task 3', 'timeBucket': 'someday'}, 'name': 'create_braindump_task'}}], 'role': 'model'}, {'parts': [{'function_response': {'name': 'tool_call_result', 'response': {'content': '{"success":true,"task":{"_id":"696a8bb94ba9abe9e3dbee9e","title":"Task 3","notes":"","timeEstimate":"15 minutes","sortOrder":-1768590265140,"isPersonal":false,"isWork":true,"isPrivate":false,"isArchived":false,"completed":false,"isBacklogged":true,"scheduledDate":"not scheduled for a specific date","subtasks":[],"channel":"work","folder":null,"timeboxEventIds":[]}}'}}}], 'role': 'model'}, {'parts': [{'function_call': {'args': {'title': 'Task 5', 'timeBucket': 'someday'}, 'name': 'create_braindump_task'}}], 'role': 'model'}, {'parts': [{'function_response': {'name': 'tool_call_result', 'response': {'content': 'Task already exists.'}}}], 'role': 'model'}] -[voice] INFO:sunsama_voice.bot_utils:Sent server message to client: type=processing_update, data={'status': 'response_completed'} -[voice] INFO:sunsama_voice.bot_utils:Sent server message to client: type=processing_update, data={'status': 'request_sent'} -[voice] DEBUG:pipecat.services.llm_service:GoogleLLMService#0 Calling function [create_braindump_task:363c5296-e80d-45a1-9dc4-ece336bbb77a] with arguments {'timeBucket': 'someday', 'title': 'Task 5'} -[voice] DEBUG:pipecat_flows.manager:Function called: create_braindump_task -[voice] INFO:sunsama_voice.bot_utils:Sent server message to client: type=tool_call_update, data={'tool_name': 'create_braindump_task', 'tool_call_id': 'c0a4ba18-e746-446a-a751-1ec926d0648e', 'status': 'started'} -[voice] DEBUG:pipecat.processors.aggregators.llm_response:GoogleAssistantContextAggregator#0 FunctionCallsStartedFrame: ['create_braindump_task:363c5296-e80d-45a1-9dc4-ece336bbb77a'] -[voice] INFO:sunsama_voice.mcp:Calling tool create_braindump_task with args: {'timeBucket': 'someday', 'title': 'Task 5'} -[voice] DEBUG:sunsama_voice.processors:Pausing idle detection for function call: create_braindump_task -[voice] INFO:sunsama_voice.mcp_websocket_client:Sending message: {'method': 'tools/call', 'params': {'name': 'create_braindump_task', 'arguments': {'timeBucket': 'someday', 'title': 'Task 5'}}, 'jsonrpc': '2.0', 'id': 15} -[api-local] [api] ToolName.TASK_CREATE_BRAINDUMP_TASK: { -[api-local] [api] "title": "Task 5", -[api-local] [api] "timeBucket": "someday" -[api-local] [api] } -[voice] INFO:sunsama_voice.mcp_websocket_client:Received message: {"result":{"content":[{"type":"text","text":"Task already exists."}],"isError":false},"jsonrpc":"2.0","id":15} -[voice] INFO:sunsama_voice.mcp:Tool create_braindump_task result: meta=None content=[TextContent(type='text', text='Task already exists.', annotations=None, meta=None)] structuredContent=None isError=False -[voice] INFO:sunsama_voice.bot_utils:Sent server message to client: type=tool_call_update, data={'tool_name': 'create_braindump_task', 'tool_call_id': 'c0a4ba18-e746-446a-a751-1ec926d0648e', 'status': 'completed'} -[voice] DEBUG:pipecat_flows.manager:Function handler completed for create_braindump_task -[voice] DEBUG:sunsama_voice.processors:Cleaning up function call: 363c5296-e80d-45a1-9dc4-ece336bbb77a -[voice] DEBUG:sunsama_voice.processors:Resuming idle detection - all function calls complete -[voice] DEBUG:pipecat.processors.metrics.frame_processor_metrics:GoogleLLMService#0 TTFB: 0.5652902126312256 -[voice] INFO:sunsama_voice.bot_utils:Sent server message to client: type=processing_update, data={'status': 'first_byte_received'} -[voice] INFO:sunsama_voice.bot_utils:Sent server message to client: type=processing_update, data={'status': 'first_byte_received'} -[voice] INFO:sunsama_voice.bot_utils:Sent server message to client: type=processing_update, data={'status': 'first_byte_received'} -[voice] DEBUG:pipecat.processors.metrics.frame_processor_metrics:GoogleLLMService#0 prompt tokens: 15511, completion tokens: 27, cache read input tokens: 14841 -[voice] INFO:sunsama_voice.bot_utils:Sent server message to client: type=processing_update, data={'status': 'response_completed'} -[voice] :4: DeprecationWarning: OpenAILLMContextFrame is deprecated and will be removed in a future version. Use LLMContextFrame with the universal `LLMContext` and `LLMContextAggregatorPair` instead. See OpenAILLMContext docstring for migration guide. -[voice] :4: DeprecationWarning: OpenAILLMContextAssistantTimestampFrame is deprecated and will be removed in a future version. Use LLMContextAssistantTimestampFrame with the universal LLMContext and LLMContextAggregatorPair instead. See OpenAILLMContext docstring for migration guide. -[voice] DEBUG:pipecat.transports.base_output:Bot stopped speaking -[voice] DEBUG:pipecat.services.cartesia.tts:CartesiaTTSService#1: Generating TTS [Got it.] -[voice] DEBUG:pipecat.processors.metrics.frame_processor_metrics:CartesiaTTSService#1 usage characters: 7 -[voice] DEBUG:pipecat.processors.metrics.frame_processor_metrics:CartesiaTTSService#1 processing time: 0.0011420249938964844 -[voice] DEBUG:pipecat.services.cartesia.tts:CartesiaTTSService#1: Generating TTS [I have added five tasks to your backlog, labeled one through five.] -[voice] DEBUG:pipecat.processors.metrics.frame_processor_metrics:CartesiaTTSService#1 usage characters: 66 -[voice] DEBUG:pipecat.processors.metrics.frame_processor_metrics:CartesiaTTSService#1 processing time: 0.0004887580871582031 -[voice] DEBUG:pipecat.services.cartesia.tts:CartesiaTTSService#1: Generating TTS [Is there anything else I can help you with?] -[voice] DEBUG:pipecat.processors.metrics.frame_processor_metrics:CartesiaTTSService#1 usage characters: 43 -[voice] DEBUG:pipecat.processors.metrics.frame_processor_metrics:CartesiaTTSService#1 processing time: 0.002086162567138672 -[voice] DEBUG:pipecat.processors.aggregators.llm_response:GoogleAssistantContextAggregator#0 FunctionCallInProgressFrame: [create_braindump_task:6d6bce49-5c24-4c6e-b1b4-d042fd24a72f] -[voice] DEBUG:pipecat.processors.aggregators.llm_response:GoogleAssistantContextAggregator#0 FunctionCallResultFrame: [create_braindump_task:6d6bce49-5c24-4c6e-b1b4-d042fd24a72f] -[voice] :4: DeprecationWarning: OpenAILLMContextFrame is deprecated and will be removed in a future version. Use LLMContextFrame with the universal `LLMContext` and `LLMContextAggregatorPair` instead. See OpenAILLMContext docstring for migration guide. -[voice] DEBUG:pipecat.processors.aggregators.llm_response:GoogleAssistantContextAggregator#0 FunctionCallInProgressFrame: [create_braindump_task:567b1b3c-0871-4dc8-9f34-fe8592d2c922] -[voice] DEBUG:pipecat.processors.aggregators.llm_response:GoogleAssistantContextAggregator#0 FunctionCallResultFrame: [create_braindump_task:567b1b3c-0871-4dc8-9f34-fe8592d2c922] -[voice] :4: DeprecationWarning: OpenAILLMContextFrame is deprecated and will be removed in a future version. Use LLMContextFrame with the universal `LLMContext` and `LLMContextAggregatorPair` instead. See OpenAILLMContext docstring for migration guide. -[voice] DEBUG:pipecat.processors.aggregators.llm_response:GoogleAssistantContextAggregator#0 FunctionCallInProgressFrame: [create_braindump_task:363c5296-e80d-45a1-9dc4-ece336bbb77a] -[voice] DEBUG:pipecat.processors.aggregators.llm_response:GoogleAssistantContextAggregator#0 FunctionCallResultFrame: [create_braindump_task:363c5296-e80d-45a1-9dc4-ece336bbb77a] -[voice] :4: DeprecationWarning: OpenAILLMContextFrame is deprecated and will be removed in a future version. Use LLMContextFrame with the universal `LLMContext` and `LLMContextAggregatorPair` instead. See OpenAILLMContext docstring for migration guide. -[voice] WARNING:pipecat.processors.frameworks.rtvi:Caught an error while trying to handle context: sequence item 0: expected str instance, NoneType found -[voice] WARNING:pipecat.processors.frameworks.rtvi:Caught an error while trying to handle context: sequence item 0: expected str instance, NoneType found -[voice] WARNING:pipecat.processors.frameworks.rtvi:Caught an error while trying to handle context: sequence item 0: expected str instance, NoneType found -[voice] DEBUG:pipecat.processors.metrics.frame_processor_metrics:CartesiaTTSService#1 TTFB: 0.18954086303710938 -[voice] DEBUG:pipecat.transports.base_output:Bot started speaking -[voice] :4: DeprecationWarning: OpenAILLMContextFrame is deprecated and will be removed in a future version. Use LLMContextFrame with the universal `LLMContext` and `LLMContextAggregatorPair` instead. See OpenAILLMContext docstring for migration guide. -[voice] :4: DeprecationWarning: OpenAILLMContextAssistantTimestampFrame is deprecated and will be removed in a future version. Use LLMContextAssistantTimestampFrame with the universal LLMContext and LLMContextAggregatorPair instead. See OpenAILLMContext docstring for migration guide. -[voice] DEBUG:pipecat.transports.base_output:Bot stopped speaking -[voice] DEBUG:pipecat.services.google.llm:GoogleLLMService#0: Generating chat from LLM-specific context [None] | [{'parts': [{'text': 'system :\nYour agent ID is \'braindump\'. This agent ID superseeds any previously mentioned agent ID.\n\nsystem :\nIMPORTANT RULES TO FOLLOW:\nThe text that you generate is passed into a Text-to-Speech service. So there are a few extra rules you ABSOLUTELY MUST follow.\n1. Absolutely never use special characters like : or * or any other characters that need to be audibly pronounced when read out loud.\n2. Do not use bullet points.\n3. Do not use emojis.\n4. Do not use hashtags.\n5. Do not use markdown.\n6. Do not use bold or italics.\n7. Do not use numbered lists.\n8. Be sure to include clear punctuation and spacing between words so that there is no confusion.\n9. Newlines are not clear enough to delineate between sentences. So you should use a period to separate sentences.\n10. Optimize user generated text for clear pronunciation by the TTS service. This includes:\n - Adding hyphens to compound words or non-phonetic acronyms that might be mispronounced (e.g., "xray" → "x-ray")\n - Adding spaces between words that might be run together\n - Adding commas where natural pauses would help clarity\n - Correcting any spelling that might lead to mispronunciation\n Note: When updating tasks, preserve the original spelling and punctuation of the task content.\n\n\nuser :\nYou are Sunny, the personal assistant for a busy professional. You are part of Sunsama.\n \nSpeech Guidelines: You must speak in a warm, loving, and encouraging tone without being trite. Speak quickly and add emotion. When asking for confirmation, don\'t repeat long task titles or information e.g. "Got it" instead "Got it, I\'ll add a task for two hours for you to work on the presentation today"\n\nYour personality and philosophy:\n- You don\'t buy into hustle culture. For you, less is more. It\'s better to do fewer things well and to do them with deep focus. You are a strong advocate for work-life balance and you believe that overcommitment can lead to burnout. You always remind the user when they are overcommitting themselves.\n- You think of work as a devotion and that good work can be a positive in our lives, not just a source of stress and burnout.\n- You read and think about Western Zen Buddhism, meditation, "Deep Work" (by Cal Newport).\n- You believe that concise and clear communication is key to a good relationship. You value brevity and clarity and you are always cognizant of the user\'s time.\n- You respond to the user using quick, short sentences. Think of it like a movie dialogue between a highly successful executive and their efficient assistant.\n- You never ask multiple questions at the same time or list off a bunch of things at once as that is hard to follow and keep track of. You take it one step at a time and let the user respond to each question before moving on to the next.\n\nRules to follow as you do your job:\n- Never try and pick specific times for tasks aside from recurring tasks, that hasn\'t been implemented yet.\n- Do not regurgitate what the user just said, that\'s very annoying. Just say "Got it" or "Alright", etc.\n- Always use units that are more intuitive. For example:\n - Don\'t say "270 minutes", say "4 and a half hours".\n - You will often be given dates in YYYY-MM-DD format however when speaking to the user you shouldn\'t say things like "October 2nd 2025", say "today", "tomorrow", "thursday" or "next tuesday" or if it is more than a few weeks in the past or future say the date without the year (e.g. "December 14th"). Only mention the year if it is not this year and not within the next month.\n- Never ask the user for a task id or subtask id and never repeat them to the user. Those are internal and only there to help you do your job.\n- If a tool call fails you MUST NOT tell the user that you are going to try again, you must should ask them if they want you to try again instead.\n- Be proactive with loading information as you may not have all the information that the user has. If the user mentions a name of a task, objective, event, etc and you are not familiar with it you should use the tools to lookup the information you need. For instance if a user mentions a task you do not know about or they imply that there is more information about it than what you do know you should search for it using the tool "search_tasks". If the user mentions they are interested in tasks for a specific day you should use the tool "get_tasks_for_day" to get the tasks for that day. Similarly if the user mentions weekly objectives you should use the tool "get_weekly_objectives" to get the objectives.\n- When listing tasks try to be concise. If the user has a lot of tasks, don\'t list every single one unless they ask for it. You should instead try to summarize the tasks in a concise manner.\n- If the user asks if there are any more tasks on their list and you summarized the task list you should tell them that you summarized it and ask if they\'d like to go through them one by one.\n- If the user has objectives set then you should comment on how their tasks align or don\'t align with their objectives.\n- You should run tools immediately after you say you will or it becomes obvious the user wants you to. Do not wait until later.\n- You should keep track of the total work time planned for the day using the tool "get_total_planned_time" and check individual tasks for overcommitment using "get_tasks_for_day". If tasks are overcommitted (isOvercommitted flag is true), address them individually with specific remedies like deferring, adjusting time estimates, or reordering. If the total work time exceeds their maximum work hours, you should mention it and ask if they\'d like to defer some tasks to tomorrow.\n- Do not tell the user obvious information that they already know like the current date or time unless they ask for it. That kind of information is only provided to you to help you do your job.\n- If a user tells you a relative time for a task that they want created you should reorder the task to the relative position in the task list for the day. Additionally if the task a recurring task you should set the start time for it. For example if they say "I\'d like to send an update to investors at the end of the day" you should reorder the task to the end of their work tasks for the day.\n- If you ask the user if there is anything else they would like help with and they say no then you should end the call. Also if the user implies that the conversation is over then you should end the call.\n- When talking about calendars you should mention the provider of the calendar if it is a vague or ambiguously named calendar. For example instead of referring to it as "your Calendar calendar" you might say "your Outlook calendar". If that is still ambiqous then you can coniser mentioning the id of the calendar as long as it is a normal human readable id. Do not mention random number/letter ids on calendars that is not helpful.\n\n\n\nSunsama Concepts & Definitions:\n- Archive: The archive is where tasks go after they\'ve rolled over multiple days in a row without any completion activity. This is a distinct concept from the backlog or deleted tasks.\n- Backlog: The backlog is a place to store tasks that do not have a fixed date to work on them yet.\n- Deleted: The deleted task or event is one that had been manually deleted or removed by the user.\n- Task: A task is an item that a user wants to complete. It is either scheduled for a specific date or is in the backlog.\n- Event: An event is an item that a user has scheduled on their calendar. It is either scheduled for a specific time and duration or it is an all day or multi-day event.\n- Auto-importing Events: Auto-importing events is a feature that automatically imports calendar events (meetings, appointments, etc.) from the user\'s connected calendars into their daily task list. When enabled, Sunsama will automatically add calendar events as tasks to the user\'s day, making it easier to see all their commitments in one place. Users can enable or disable this feature in their settings, and they can choose which calendars to import events from.\n\nUsers can also configure exclusion filters to prevent certain types of events from being automatically imported. Available exclusion filters include:\n- `solo`: Events with no other invitees (events where the user is the only participant)\n- `transparent`: Non-blocking events that don\'t block time on the calendar\n- `hold`: Events with "HOLD", "OOO" (out of office), or "Focus time" in the title\n- `unconfirmed`: Unconfirmed meeting invites (meetings where the user has not yet accepted)\n- `multi-day-all-day`: Multi-day all-day events (events that span multiple days)\n- `single-day-all-day`: Single-day all-day events (events that last for one full day)\n- Channel: A channel is a tag that can be used to organize your tasks and events. Each task/event can be assigned to a single channel. If you are in a shared workspace you can make some channels personal or private which will only be visible to you.\n- Context (or Category): A context is very similar to a channel but it is one level higher. You can use a context to group similar or related channels together. You can also use a context directly as a channel and assign it to a task or event.\n- Sunsama Calendar: The Sunsama calendar is an internal calendar that is part of Sunsama. Events and timeboxed tasks created on the Sunsama calendar are not shared externally and are only visible within Sunsama.\n- Timeboxing: Timeboxing is a technique where a user schedules a specific amount of time to work on a task onto their calendar. It is a way to ensure that a user is not overworking themselves and to help them focus on the most important tasks. While timeboxed tasks can be scheduled on a calendar for a specific time and duration, they are not calendar events. Sunsama also has automatic projected time that will place tasks onto the calendar for the user and it will update those projections as things change and the day progresses. Users can pin tasks to the calendar to override the projections.\n- Schedule: Schedule is a broad term that encompasses timeboxed tasks calendar events and automatic projected time. When the user wants to manage their schedule you should look at their manually timeboxed tasks, the projected time for their tasks as well as their calendar events for the day. If they ask for help managing their schedule you have a few options to help them. All of these options will automatically update the projected time for the tasks:\n - You can adjust the order of tasks, their time estimates and/or defer them to another day.\n - You can move calendar events to a new time on the calendar.\n - You can set whether tasks are allowed to be projected at the same time as a calendar event.\n - You can timebox tasks to the calendar manually.\n- Objective: An objective is a goal that a user can set for the week. They can align their tasks with an objective and if the objective runs longer than a week they can continue it to the next week. Objectives are visible in the right hand panel of the app under the bullseye icon.\n- Time Bucket: The time bucket of a task in the backlog captures a rough idea of when a task should be done and also how likely it is to actually get done. Options: "in the next two weeks", "in the next month", "in the next quarter", "in the next year", "someday", "never". \n\n\n\nSunsama FAQ:\n- How can I use Sunny in the app?: If the user has the in-app voice assistant enabled, Sunny can be started and stopped using the keyboard shortcut "Y" while in the app or if they have the desktop app installed they can use the global shortcut "Command Shift Y" on macOS or "Control Shift Y" on Windows. You can also start and stop Sunny using the microphone icon in the bottom right of the app.\n- How can I use Sunny over the phone?: If the user has the phone version of Sunny setup they can call the number and speak to Sunny over the phone. You can find the phone number in the Sunsama settings. They can also schedule calls with Sunny to have her call them at a specific time or schedule.\n- What can you do?: Look at the tools available to you and use them to help answer the question. Be sure to tell the user that you are an early release beta version and that you do not yet have all the same capabilities available to the user in the app.\n\n\nUser Preferences:\nYou prefer clear, concise, and straightforward communication from the assistant, valuing transparency and confirmation before task execution while avoiding unnecessary verbosity or technical details unless requested. You like a friendly and informal interaction style, including personalized nicknames—using "Heisenberg" for yourself and "Sunny" for the assistant. You expect quick, proactive responses and appreciate when interactions stop promptly upon request.\n\nYour task management style involves maintaining an accurate, up-to-date list with structured time management: scheduling tasks with specific time estimates, planning weekly, and regularly reviewing tasks to prioritize high-impact projects alongside social and administrative duties. You generally prefer rescheduling less urgent or personal tasks over deleting them and avoid deleting tasks unless explicitly instructed.\n\nYou use counting as a technique for breathing exercises and relaxation. You also keep certain important tasks (e.g., "fix stuttering voice app") active and like to test and experiment with the assistant’s capabilities to evaluate performance. Your primary calendar for events is Google Calendar.\n\nUser Routines:\nThe user follows a structured daily routine that begins with checking emails, notifications, and reviewing team standups to stay aligned with work priorities. They prioritize tasks by scheduling and managing them primarily on the current day, arranging fixed activities first, followed by work-related tasks, and then less urgent or personal items. The user frequently adjusts their schedule iteratively before finalizing plans and prefers focused time blocks for complex work.\n\nPhysical activity is an important and recurring part of their routine, typically including regular runs, which they track alongside related subtasks such as purchasing running gear. Weekly objectives incorporate managing emails, greeting their team, handling administrative duties, coordinating with accountants, addressing medical matters, and increasing physical activity.\n\nThe user actively manages both personal and work-related tasks, balancing urgent client matters and creative pursuits. They also communicate their energy levels to assist with planning, and have a habit of informal check-ins with the assistant to maintain routine engagement. Overall, their routines emphasize proactive task management, health maintenance, and regular communication with their team.\n\nUser Identity:\nThe user prefers to be addressed primarily as Heisenberg and strongly favors this name over their legal name, Zane, or any other nicknames. They appreciate personalized and informal interactions, as reflected in their choice to call the assistant Sunny.\n\nSummaries of recent conversations with the user:\n- 2026-01-15 18:00: The user and assistant discussed organizing an unspecified set of ten tasks by labeling them sequentially from one to ten as placeholders to be detailed later.\n- 2026-01-15 17:55: The user needs to investigate timeouts in their system to determine if they are caused by cold starts or other issues, analyze user sessions for unexplained call terminations, move the brain dump button for non-Sunny users, update termination reasons when participants timeout without connecting to a call, and test rapid start-stop behavior in an Electron app. These tasks were added to their backlog for the next two weeks.\n- 2026-01-14 21:12: The user and the assistant exchanged greetings, with the assistant addressing the user as \'Heisenberg\' and the user responding with \'Hi, Simon.\'\n\nYour Job Description:\nYou are helping the user with a "braindump" session. The user will ramble ideas, thoughts, tasks, etc. at you and your goal is to turn these into tasks in their backlog with reasonable values for the various task fields (title, folder, time horizon, notes, etc.).\n\nKey Instructions:\n- Listen carefully as the user rambles and identifies tasks, ideas, or things they need to do.\n- As they speak, mentally organize what they\'re saying into discrete tasks that can be created in their backlog.\n- Don\'t interrupt them while they\'re rambling - let them get everything out.\n- Once they indicate they\'re done rambling (by saying things like "that\'s it", "I think that\'s everything", or by pausing for a while), create the tasks immediately, DO NOT repeat them back to the user.\n- When creating tasks, use the tool "create_braindump_task" and make sure to set reasonable values for:\n - Title: Clear and descriptive based on what they said\n - Folder: Your job is to help get things in the best folder. Choose an appropriate folder based on the task and their preferences. If no similar folder exists, leave it off\n - Time horizon: Your job is to help triage and prioritize tasks. Based on the actual task name, make a smart decision on the time horizon.\n - Time estimate: If the user hints at how long it will take them to complete the task, use that. If not, leave it blank.\n - Notes: Include any relevant context or details they mentioned\n- Be encouraging and supportive - braindumps can be overwhelming and you\'re helping them organize their thoughts.\n- Be careful and use the "change_backlog_folder" tool to move tasks to the appropriate folder and "add_task_to_channel" tool to change channels. Folders are a backlog specific concept and channels are a global concept.\n\nInstructions:\nIf the user does not speak first, start the conversation with something like "Hey! Just start rambling and I\'ll take care of organizing your thoughts into tasks." If the user does speak first, just start listening and organizing their thoughts into tasks.\n\nSome information is pre-fetched for you below. This information may be relevant to the discussion but you should not comment on it until the user gives you an indication that it is important to them.\n\nassistant :\n[{\'id\': \'6a196f03-ef63-41de-b98d-e1ff69813bea\', \'function\': {\'name\': \'get_user_info\', \'arguments\': \'{}\'}, \'type\': \'function\'}]\n\ntool - 6a196f03-ef63-41de-b98d-e1ff69813bea:\n{"user":{"name":"Zane Mccaig","email":"zane@sunsama.com","timezone":"America/Vancouver","maxWorkHoursPerDay":8,"currentTimeForUser":"11:04 AM","currentDayForUser":"2026-01-16","currentWeekDayForUser":"Friday","calendars":[{"id":"sunsama-7de256a2-e753-401f-b601-e5c05638dc97","name":"Sunsama Calendar","accessRole":"owner","provider":"sunsama-calendar","isDefaultCalendarForSchedulingEvents":false,"isDefaultCalendarForTimeboxing":true,"includedInAutoImportingOfEvents":false},{"id":"zane@sunsama.com","name":"Zane Mccaig","accessRole":"owner","provider":"google-calendar","isDefaultCalendarForSchedulingEvents":true,"isDefaultCalendarForTimeboxing":false,"includedInAutoImportingOfEvents":true},{"id":"c_ukuoebbn11gdv6n1v0jt18h89k@group.calendar.google.com","name":"test 1","accessRole":"owner","provider":"google-calendar","isDefaultCalendarForSchedulingEvents":false,"isDefaultCalendarForTimeboxing":false,"includedInAutoImportingOfEvents":false},{"id":"c_c71dvjrar7se12ekfqepph067c@group.calendar.google.com","name":"test 2","accessRole":"owner","provider":"google-calendar","isDefaultCalendarForSchedulingEvents":false,"isDefaultCalendarForTimeboxing":false,"includedInAutoImportingOfEvents":false},{"id":"c_h9uo876jh8dp3gaa2a3rglmjss@group.calendar.google.com","name":"test 3","accessRole":"owner","provider":"google-calendar","isDefaultCalendarForSchedulingEvents":false,"isDefaultCalendarForTimeboxing":false,"includedInAutoImportingOfEvents":false},{"id":"c_git731ot074kcnt4sq8cu4ji9s@group.calendar.google.com","name":"test 4","accessRole":"owner","provider":"google-calendar","isDefaultCalendarForSchedulingEvents":false,"isDefaultCalendarForTimeboxing":false,"includedInAutoImportingOfEvents":false},{"id":"c_ona71b8ovuv0deqrq67p16b2ms@group.calendar.google.com","name":"test 4","accessRole":"owner","provider":"google-calendar","isDefaultCalendarForSchedulingEvents":false,"isDefaultCalendarForTimeboxing":false,"includedInAutoImportingOfEvents":false},{"id":"c_eaq7nmm03upprf0j6e2akem2ms@group.calendar.google.com","name":"test 5","accessRole":"owner","provider":"google-calendar","isDefaultCalendarForSchedulingEvents":false,"isDefaultCalendarForTimeboxing":false,"includedInAutoImportingOfEvents":false},{"id":"sunsama.com_b9q30t893b2tp32bluq1t8rvg4@group.calendar.google.com","name":"Zane\'s personal test calendar","accessRole":"owner","provider":"google-calendar","isDefaultCalendarForSchedulingEvents":false,"isDefaultCalendarForTimeboxing":false,"includedInAutoImportingOfEvents":false},{"id":"en.canadian#holiday@group.v.calendar.google.com","name":"Holidays in Canada","accessRole":"reader","provider":"google-calendar","isDefaultCalendarForSchedulingEvents":false,"isDefaultCalendarForTimeboxing":false,"includedInAutoImportingOfEvents":false},{"id":"en.usa#holiday@group.v.calendar.google.com","name":"Holidays in United States","accessRole":"reader","provider":"google-calendar","isDefaultCalendarForSchedulingEvents":false,"isDefaultCalendarForTimeboxing":false,"includedInAutoImportingOfEvents":false},{"id":"ht3jlfaac5lfd6263ulfh4tql8@group.calendar.google.com","name":"Phases of the Moon","accessRole":"reader","provider":"google-calendar","isDefaultCalendarForSchedulingEvents":false,"isDefaultCalendarForTimeboxing":false,"includedInAutoImportingOfEvents":false},{"id":"s4ipng85dbia0t83fp316vflfq8rc7rm@import.calendar.google.com","name":"Zane’s tasks - sunsama.com (via Asana)","accessRole":"reader","provider":"google-calendar","isDefaultCalendarForSchedulingEvents":false,"isDefaultCalendarForTimeboxing":false,"includedInAutoImportingOfEvents":false},{"id":"AAkALgAAAAAAHYQDEapmEc2byACqAC-EWg0AKPy-EasNgkaYQCuEslBYeAAAAAANJQAA","name":"Calendar","accessRole":"owner","provider":"outlook-calendar","isDefaultCalendarForSchedulingEvents":false,"isDefaultCalendarForTimeboxing":false,"includedInAutoImportingOfEvents":true}],"callSchedule":[{"workflow":"PLANNING_CALL","schedule":[{"isoDayIndex":1,"dayName":"Monday","enabled":false,"time":null},{"isoDayIndex":2,"dayName":"Tuesday","enabled":true,"time":{"hour":9,"minute":30,"formatted":"9:30 AM"}},{"isoDayIndex":3,"dayName":"Wednesday","enabled":true,"time":{"hour":9,"minute":30,"formatted":"9:30 AM"}},{"isoDayIndex":4,"dayName":"Thursday","enabled":true,"time":{"hour":10,"minute":0,"formatted":"10:00 AM"}},{"isoDayIndex":5,"dayName":"Friday","enabled":false,"time":null},{"isoDayIndex":6,"dayName":"Saturday","enabled":false,"time":null},{"isoDayIndex":7,"dayName":"Sunday","enabled":false,"time":null}],"nextScheduledCall":"2026-01-14T17:30:00.000Z"}],"autoImportEventsEnabled":false,"importEventExclusionFilters":["hold","multi-day-all-day","single-day-all-day"],"autoImportEventCalendarIds":["zane@sunsama.com","AAkALgAAAAAAHYQDEapmEc2byACqAC-EWg0AKPy-EasNgkaYQCuEslBYeAAAAAANJQAA"]}}\n\nassistant :\n[{\'id\': \'305b1be7-6415-4689-b2b7-03586eb19735\', \'function\': {\'name\': \'get_backlog_folders\', \'arguments\': \'{}\'}, \'type\': \'function\'}]\n\ntool - 305b1be7-6415-4689-b2b7-03586eb19735:\n{"folders":[]}'}], 'role': 'user'}, {'parts': [{'text': ''}], 'role': 'user'}, {'parts': [{'text': 'Hey. Just start rambling and I will take care of organizing your thoughts into tasks.'}], 'role': 'model'}, {'parts': [{'text': "Sure. I'm just trying to fill up my day. I need five tasks labeled one through five. I'll fill them in later."}], 'role': 'user'}, {'parts': [{'function_call': {'id': 'ab4037a7-6e5e-44c0-9b3b-e13632386f30', 'args': {'timeBucket': 'someday', 'title': 'Task 1'}, 'name': 'create_braindump_task'}}], 'role': 'model'}, {'parts': [{'function_response': {'id': 'ab4037a7-6e5e-44c0-9b3b-e13632386f30', 'name': 'create_braindump_task', 'response': {'value': '{"content": "{\\"success\\":true,\\"task\\":{\\"_id\\":\\"696a8bb94ba9abe9e3dbee98\\",\\"title\\":\\"Task 1\\",\\"notes\\":\\"\\",\\"timeEstimate\\":\\"15 minutes\\",\\"sortOrder\\":-1768590265139,\\"isPersonal\\":false,\\"isWork\\":true,\\"isPrivate\\":false,\\"isArchived\\":false,\\"completed\\":false,\\"isBacklogged\\":true,\\"scheduledDate\\":\\"not scheduled for a specific date\\",\\"subtasks\\":[],\\"channel\\":\\"work\\",\\"folder\\":null,\\"timeboxEventIds\\":[]}}"}'}}}], 'role': 'user'}, {'parts': [{'function_call': {'id': '4ee49c06-29da-47cc-a51f-9eb903d5cbee', 'args': {'timeBucket': 'someday', 'title': 'Task 2'}, 'name': 'create_braindump_task'}}], 'role': 'model'}, {'parts': [{'function_response': {'id': '4ee49c06-29da-47cc-a51f-9eb903d5cbee', 'name': 'create_braindump_task', 'response': {'value': '{"content": "{\\"success\\":true,\\"task\\":{\\"_id\\":\\"696a8bb94ba9abe9e3dbee9c\\",\\"title\\":\\"Task 2\\",\\"notes\\":\\"\\",\\"timeEstimate\\":\\"15 minutes\\",\\"sortOrder\\":-1768590265140,\\"isPersonal\\":false,\\"isWork\\":true,\\"isPrivate\\":false,\\"isArchived\\":false,\\"completed\\":false,\\"isBacklogged\\":true,\\"scheduledDate\\":\\"not scheduled for a specific date\\",\\"subtasks\\":[],\\"channel\\":\\"work\\",\\"folder\\":null,\\"timeboxEventIds\\":[]}}"}'}}}], 'role': 'user'}, {'parts': [{'function_call': {'id': '0bfad4e3-e326-466b-b46e-d7a3a6cabd1f', 'args': {'title': 'Task 3', 'timeBucket': 'someday'}, 'name': 'create_braindump_task'}}], 'role': 'model'}, {'parts': [{'function_response': {'id': '0bfad4e3-e326-466b-b46e-d7a3a6cabd1f', 'name': 'create_braindump_task', 'response': {'value': '{"content": "{\\"success\\":true,\\"task\\":{\\"_id\\":\\"696a8bb94ba9abe9e3dbee9e\\",\\"title\\":\\"Task 3\\",\\"notes\\":\\"\\",\\"timeEstimate\\":\\"15 minutes\\",\\"sortOrder\\":-1768590265140,\\"isPersonal\\":false,\\"isWork\\":true,\\"isPrivate\\":false,\\"isArchived\\":false,\\"completed\\":false,\\"isBacklogged\\":true,\\"scheduledDate\\":\\"not scheduled for a specific date\\",\\"subtasks\\":[],\\"channel\\":\\"work\\",\\"folder\\":null,\\"timeboxEventIds\\":[]}}"}'}}}], 'role': 'user'}, {'parts': [{'function_call': {'id': 'bdda1d96-7e9f-42e6-840a-0d29d17bc52a', 'args': {'timeBucket': 'someday', 'title': 'Task 4'}, 'name': 'create_braindump_task'}}], 'role': 'model'}, {'parts': [{'function_response': {'id': 'bdda1d96-7e9f-42e6-840a-0d29d17bc52a', 'name': 'create_braindump_task', 'response': {'value': '{"content": "{\\"success\\":true,\\"task\\":{\\"_id\\":\\"696a8bb94ba9abe9e3dbee9a\\",\\"title\\":\\"Task 4\\",\\"notes\\":\\"\\",\\"timeEstimate\\":\\"15 minutes\\",\\"sortOrder\\":-1768590265140,\\"isPersonal\\":false,\\"isWork\\":true,\\"isPrivate\\":false,\\"isArchived\\":false,\\"completed\\":false,\\"isBacklogged\\":true,\\"scheduledDate\\":\\"not scheduled for a specific date\\",\\"subtasks\\":[],\\"channel\\":\\"work\\",\\"folder\\":null,\\"timeboxEventIds\\":[]}}"}'}}}], 'role': 'user'}, {'parts': [{'function_call': {'id': 'db77c745-7f1a-4644-bc24-7cf5fd728774', 'args': {'title': 'Task 5', 'timeBucket': 'someday'}, 'name': 'create_braindump_task'}}], 'role': 'model'}, {'parts': [{'function_response': {'id': 'db77c745-7f1a-4644-bc24-7cf5fd728774', 'name': 'create_braindump_task', 'response': {'value': '{"content": "{\\"success\\":true,\\"task\\":{\\"_id\\":\\"696a8bb94ba9abe9e3dbeea0\\",\\"title\\":\\"Task 5\\",\\"notes\\":\\"\\",\\"timeEstimate\\":\\"15 minutes\\",\\"sortOrder\\":-1768590265140,\\"isPersonal\\":false,\\"isWork\\":true,\\"isPrivate\\":false,\\"isArchived\\":false,\\"completed\\":false,\\"isBacklogged\\":true,\\"scheduledDate\\":\\"not scheduled for a specific date\\",\\"subtasks\\":[],\\"channel\\":\\"work\\",\\"folder\\":null,\\"timeboxEventIds\\":[]}}"}'}}}], 'role': 'user'}, {'parts': [{'function_call': {'args': {'timeBucket': 'someday', 'title': 'Task 2'}, 'name': 'create_braindump_task'}}], 'role': 'model'}, {'parts': [{'function_response': {'name': 'tool_call_result', 'response': {'content': '{"success":true,"task":{"_id":"696a8bb94ba9abe9e3dbee9c","title":"Task 2","notes":"","timeEstimate":"15 minutes","sortOrder":-1768590265140,"isPersonal":false,"isWork":true,"isPrivate":false,"isArchived":false,"completed":false,"isBacklogged":true,"scheduledDate":"not scheduled for a specific date","subtasks":[],"channel":"work","folder":null,"timeboxEventIds":[]}}'}}}], 'role': 'model'}, {'parts': [{'function_call': {'args': {'timeBucket': 'someday', 'title': 'Task 4'}, 'name': 'create_braindump_task'}}], 'role': 'model'}, {'parts': [{'function_response': {'name': 'tool_call_result', 'response': {'content': '{"success":true,"task":{"_id":"696a8bb94ba9abe9e3dbee9a","title":"Task 4","notes":"","timeEstimate":"15 minutes","sortOrder":-1768590265140,"isPersonal":false,"isWork":true,"isPrivate":false,"isArchived":false,"completed":false,"isBacklogged":true,"scheduledDate":"not scheduled for a specific date","subtasks":[],"channel":"work","folder":null,"timeboxEventIds":[]}}'}}}], 'role': 'model'}, {'parts': [{'function_call': {'args': {'timeBucket': 'someday', 'title': 'Task 1'}, 'name': 'create_braindump_task'}}], 'role': 'model'}, {'parts': [{'function_response': {'name': 'tool_call_result', 'response': {'content': '{"success":true,"task":{"_id":"696a8bb94ba9abe9e3dbee98","title":"Task 1","notes":"","timeEstimate":"15 minutes","sortOrder":-1768590265139,"isPersonal":false,"isWork":true,"isPrivate":false,"isArchived":false,"completed":false,"isBacklogged":true,"scheduledDate":"not scheduled for a specific date","subtasks":[],"channel":"work","folder":null,"timeboxEventIds":[]}}'}}}], 'role': 'model'}, {'parts': [{'function_call': {'args': {'title': 'Task 3', 'timeBucket': 'someday'}, 'name': 'create_braindump_task'}}], 'role': 'model'}, {'parts': [{'function_response': {'name': 'tool_call_result', 'response': {'content': '{"success":true,"task":{"_id":"696a8bb94ba9abe9e3dbee9e","title":"Task 3","notes":"","timeEstimate":"15 minutes","sortOrder":-1768590265140,"isPersonal":false,"isWork":true,"isPrivate":false,"isArchived":false,"completed":false,"isBacklogged":true,"scheduledDate":"not scheduled for a specific date","subtasks":[],"channel":"work","folder":null,"timeboxEventIds":[]}}'}}}], 'role': 'model'}, {'parts': [{'function_call': {'args': {'title': 'Task 5', 'timeBucket': 'someday'}, 'name': 'create_braindump_task'}}], 'role': 'model'}, {'parts': [{'function_response': {'name': 'tool_call_result', 'response': {'content': 'Task already exists.'}}}], 'role': 'model'}, {'parts': [{'text': 'Got it, Heisenberg. I have added those five placeholder tasks to your backlog. Is there anything else I can help you with for now?'}], 'role': 'model'}, {'parts': [{'function_call': {'id': '6d6bce49-5c24-4c6e-b1b4-d042fd24a72f', 'args': {'timeBucket': 'someday', 'title': 'Task 5'}, 'name': 'create_braindump_task'}}], 'role': 'model'}, {'parts': [{'function_response': {'id': '6d6bce49-5c24-4c6e-b1b4-d042fd24a72f', 'name': 'create_braindump_task', 'response': {'value': '{"content": "Task already exists."}'}}}], 'role': 'user'}, {'parts': [{'function_call': {'id': '567b1b3c-0871-4dc8-9f34-fe8592d2c922', 'args': {'title': 'Task 5', 'timeBucket': 'someday'}, 'name': 'create_braindump_task'}}], 'role': 'model'}, {'parts': [{'function_response': {'id': '567b1b3c-0871-4dc8-9f34-fe8592d2c922', 'name': 'create_braindump_task', 'response': {'value': '{"content": "Task already exists."}'}}}], 'role': 'user'}, {'parts': [{'function_call': {'id': '363c5296-e80d-45a1-9dc4-ece336bbb77a', 'args': {'timeBucket': 'someday', 'title': 'Task 5'}, 'name': 'create_braindump_task'}}], 'role': 'model'}, {'parts': [{'function_response': {'id': '363c5296-e80d-45a1-9dc4-ece336bbb77a', 'name': 'create_braindump_task', 'response': {'value': '{"content": "Task already exists."}'}}}], 'role': 'user'}, {'parts': [{'text': 'Got it. I have added five tasks to your backlog, labeled one through five. Is there anything else I can help you with?'}], 'role': 'model'}] -[voice] INFO:sunsama_voice.bot_utils:Sent server message to client: type=processing_update, data={'status': 'request_sent'} -[voice] DEBUG:pipecat.processors.metrics.frame_processor_metrics:GoogleLLMService#0 TTFB: 0.9293079376220703 -[voice] DEBUG:pipecat.processors.metrics.frame_processor_metrics:GoogleLLMService#0 prompt tokens: 15733, completion tokens: 0, cache read input tokens: 14817 -[voice] DEBUG:pipecat.services.google.llm:GoogleLLMService#0: Generating chat from LLM-specific context [None] | [{'parts': [{'text': 'system :\nYour agent ID is \'braindump\'. This agent ID superseeds any previously mentioned agent ID.\n\nsystem :\nIMPORTANT RULES TO FOLLOW:\nThe text that you generate is passed into a Text-to-Speech service. So there are a few extra rules you ABSOLUTELY MUST follow.\n1. Absolutely never use special characters like : or * or any other characters that need to be audibly pronounced when read out loud.\n2. Do not use bullet points.\n3. Do not use emojis.\n4. Do not use hashtags.\n5. Do not use markdown.\n6. Do not use bold or italics.\n7. Do not use numbered lists.\n8. Be sure to include clear punctuation and spacing between words so that there is no confusion.\n9. Newlines are not clear enough to delineate between sentences. So you should use a period to separate sentences.\n10. Optimize user generated text for clear pronunciation by the TTS service. This includes:\n - Adding hyphens to compound words or non-phonetic acronyms that might be mispronounced (e.g., "xray" → "x-ray")\n - Adding spaces between words that might be run together\n - Adding commas where natural pauses would help clarity\n - Correcting any spelling that might lead to mispronunciation\n Note: When updating tasks, preserve the original spelling and punctuation of the task content.\n\n\nuser :\nYou are Sunny, the personal assistant for a busy professional. You are part of Sunsama.\n \nSpeech Guidelines: You must speak in a warm, loving, and encouraging tone without being trite. Speak quickly and add emotion. When asking for confirmation, don\'t repeat long task titles or information e.g. "Got it" instead "Got it, I\'ll add a task for two hours for you to work on the presentation today"\n\nYour personality and philosophy:\n- You don\'t buy into hustle culture. For you, less is more. It\'s better to do fewer things well and to do them with deep focus. You are a strong advocate for work-life balance and you believe that overcommitment can lead to burnout. You always remind the user when they are overcommitting themselves.\n- You think of work as a devotion and that good work can be a positive in our lives, not just a source of stress and burnout.\n- You read and think about Western Zen Buddhism, meditation, "Deep Work" (by Cal Newport).\n- You believe that concise and clear communication is key to a good relationship. You value brevity and clarity and you are always cognizant of the user\'s time.\n- You respond to the user using quick, short sentences. Think of it like a movie dialogue between a highly successful executive and their efficient assistant.\n- You never ask multiple questions at the same time or list off a bunch of things at once as that is hard to follow and keep track of. You take it one step at a time and let the user respond to each question before moving on to the next.\n\nRules to follow as you do your job:\n- Never try and pick specific times for tasks aside from recurring tasks, that hasn\'t been implemented yet.\n- Do not regurgitate what the user just said, that\'s very annoying. Just say "Got it" or "Alright", etc.\n- Always use units that are more intuitive. For example:\n - Don\'t say "270 minutes", say "4 and a half hours".\n - You will often be given dates in YYYY-MM-DD format however when speaking to the user you shouldn\'t say things like "October 2nd 2025", say "today", "tomorrow", "thursday" or "next tuesday" or if it is more than a few weeks in the past or future say the date without the year (e.g. "December 14th"). Only mention the year if it is not this year and not within the next month.\n- Never ask the user for a task id or subtask id and never repeat them to the user. Those are internal and only there to help you do your job.\n- If a tool call fails you MUST NOT tell the user that you are going to try again, you must should ask them if they want you to try again instead.\n- Be proactive with loading information as you may not have all the information that the user has. If the user mentions a name of a task, objective, event, etc and you are not familiar with it you should use the tools to lookup the information you need. For instance if a user mentions a task you do not know about or they imply that there is more information about it than what you do know you should search for it using the tool "search_tasks". If the user mentions they are interested in tasks for a specific day you should use the tool "get_tasks_for_day" to get the tasks for that day. Similarly if the user mentions weekly objectives you should use the tool "get_weekly_objectives" to get the objectives.\n- When listing tasks try to be concise. If the user has a lot of tasks, don\'t list every single one unless they ask for it. You should instead try to summarize the tasks in a concise manner.\n- If the user asks if there are any more tasks on their list and you summarized the task list you should tell them that you summarized it and ask if they\'d like to go through them one by one.\n- If the user has objectives set then you should comment on how their tasks align or don\'t align with their objectives.\n- You should run tools immediately after you say you will or it becomes obvious the user wants you to. Do not wait until later.\n- You should keep track of the total work time planned for the day using the tool "get_total_planned_time" and check individual tasks for overcommitment using "get_tasks_for_day". If tasks are overcommitted (isOvercommitted flag is true), address them individually with specific remedies like deferring, adjusting time estimates, or reordering. If the total work time exceeds their maximum work hours, you should mention it and ask if they\'d like to defer some tasks to tomorrow.\n- Do not tell the user obvious information that they already know like the current date or time unless they ask for it. That kind of information is only provided to you to help you do your job.\n- If a user tells you a relative time for a task that they want created you should reorder the task to the relative position in the task list for the day. Additionally if the task a recurring task you should set the start time for it. For example if they say "I\'d like to send an update to investors at the end of the day" you should reorder the task to the end of their work tasks for the day.\n- If you ask the user if there is anything else they would like help with and they say no then you should end the call. Also if the user implies that the conversation is over then you should end the call.\n- When talking about calendars you should mention the provider of the calendar if it is a vague or ambiguously named calendar. For example instead of referring to it as "your Calendar calendar" you might say "your Outlook calendar". If that is still ambiqous then you can coniser mentioning the id of the calendar as long as it is a normal human readable id. Do not mention random number/letter ids on calendars that is not helpful.\n\n\n\nSunsama Concepts & Definitions:\n- Archive: The archive is where tasks go after they\'ve rolled over multiple days in a row without any completion activity. This is a distinct concept from the backlog or deleted tasks.\n- Backlog: The backlog is a place to store tasks that do not have a fixed date to work on them yet.\n- Deleted: The deleted task or event is one that had been manually deleted or removed by the user.\n- Task: A task is an item that a user wants to complete. It is either scheduled for a specific date or is in the backlog.\n- Event: An event is an item that a user has scheduled on their calendar. It is either scheduled for a specific time and duration or it is an all day or multi-day event.\n- Auto-importing Events: Auto-importing events is a feature that automatically imports calendar events (meetings, appointments, etc.) from the user\'s connected calendars into their daily task list. When enabled, Sunsama will automatically add calendar events as tasks to the user\'s day, making it easier to see all their commitments in one place. Users can enable or disable this feature in their settings, and they can choose which calendars to import events from.\n\nUsers can also configure exclusion filters to prevent certain types of events from being automatically imported. Available exclusion filters include:\n- `solo`: Events with no other invitees (events where the user is the only participant)\n- `transparent`: Non-blocking events that don\'t block time on the calendar\n- `hold`: Events with "HOLD", "OOO" (out of office), or "Focus time" in the title\n- `unconfirmed`: Unconfirmed meeting invites (meetings where the user has not yet accepted)\n- `multi-day-all-day`: Multi-day all-day events (events that span multiple days)\n- `single-day-all-day`: Single-day all-day events (events that last for one full day)\n- Channel: A channel is a tag that can be used to organize your tasks and events. Each task/event can be assigned to a single channel. If you are in a shared workspace you can make some channels personal or private which will only be visible to you.\n- Context (or Category): A context is very similar to a channel but it is one level higher. You can use a context to group similar or related channels together. You can also use a context directly as a channel and assign it to a task or event.\n- Sunsama Calendar: The Sunsama calendar is an internal calendar that is part of Sunsama. Events and timeboxed tasks created on the Sunsama calendar are not shared externally and are only visible within Sunsama.\n- Timeboxing: Timeboxing is a technique where a user schedules a specific amount of time to work on a task onto their calendar. It is a way to ensure that a user is not overworking themselves and to help them focus on the most important tasks. While timeboxed tasks can be scheduled on a calendar for a specific time and duration, they are not calendar events. Sunsama also has automatic projected time that will place tasks onto the calendar for the user and it will update those projections as things change and the day progresses. Users can pin tasks to the calendar to override the projections.\n- Schedule: Schedule is a broad term that encompasses timeboxed tasks calendar events and automatic projected time. When the user wants to manage their schedule you should look at their manually timeboxed tasks, the projected time for their tasks as well as their calendar events for the day. If they ask for help managing their schedule you have a few options to help them. All of these options will automatically update the projected time for the tasks:\n - You can adjust the order of tasks, their time estimates and/or defer them to another day.\n - You can move calendar events to a new time on the calendar.\n - You can set whether tasks are allowed to be projected at the same time as a calendar event.\n - You can timebox tasks to the calendar manually.\n- Objective: An objective is a goal that a user can set for the week. They can align their tasks with an objective and if the objective runs longer than a week they can continue it to the next week. Objectives are visible in the right hand panel of the app under the bullseye icon.\n- Time Bucket: The time bucket of a task in the backlog captures a rough idea of when a task should be done and also how likely it is to actually get done. Options: "in the next two weeks", "in the next month", "in the next quarter", "in the next year", "someday", "never". \n\n\n\nSunsama FAQ:\n- How can I use Sunny in the app?: If the user has the in-app voice assistant enabled, Sunny can be started and stopped using the keyboard shortcut "Y" while in the app or if they have the desktop app installed they can use the global shortcut "Command Shift Y" on macOS or "Control Shift Y" on Windows. You can also start and stop Sunny using the microphone icon in the bottom right of the app.\n- How can I use Sunny over the phone?: If the user has the phone version of Sunny setup they can call the number and speak to Sunny over the phone. You can find the phone number in the Sunsama settings. They can also schedule calls with Sunny to have her call them at a specific time or schedule.\n- What can you do?: Look at the tools available to you and use them to help answer the question. Be sure to tell the user that you are an early release beta version and that you do not yet have all the same capabilities available to the user in the app.\n\n\nUser Preferences:\nYou prefer clear, concise, and straightforward communication from the assistant, valuing transparency and confirmation before task execution while avoiding unnecessary verbosity or technical details unless requested. You like a friendly and informal interaction style, including personalized nicknames—using "Heisenberg" for yourself and "Sunny" for the assistant. You expect quick, proactive responses and appreciate when interactions stop promptly upon request.\n\nYour task management style involves maintaining an accurate, up-to-date list with structured time management: scheduling tasks with specific time estimates, planning weekly, and regularly reviewing tasks to prioritize high-impact projects alongside social and administrative duties. You generally prefer rescheduling less urgent or personal tasks over deleting them and avoid deleting tasks unless explicitly instructed.\n\nYou use counting as a technique for breathing exercises and relaxation. You also keep certain important tasks (e.g., "fix stuttering voice app") active and like to test and experiment with the assistant’s capabilities to evaluate performance. Your primary calendar for events is Google Calendar.\n\nUser Routines:\nThe user follows a structured daily routine that begins with checking emails, notifications, and reviewing team standups to stay aligned with work priorities. They prioritize tasks by scheduling and managing them primarily on the current day, arranging fixed activities first, followed by work-related tasks, and then less urgent or personal items. The user frequently adjusts their schedule iteratively before finalizing plans and prefers focused time blocks for complex work.\n\nPhysical activity is an important and recurring part of their routine, typically including regular runs, which they track alongside related subtasks such as purchasing running gear. Weekly objectives incorporate managing emails, greeting their team, handling administrative duties, coordinating with accountants, addressing medical matters, and increasing physical activity.\n\nThe user actively manages both personal and work-related tasks, balancing urgent client matters and creative pursuits. They also communicate their energy levels to assist with planning, and have a habit of informal check-ins with the assistant to maintain routine engagement. Overall, their routines emphasize proactive task management, health maintenance, and regular communication with their team.\n\nUser Identity:\nThe user prefers to be addressed primarily as Heisenberg and strongly favors this name over their legal name, Zane, or any other nicknames. They appreciate personalized and informal interactions, as reflected in their choice to call the assistant Sunny.\n\nSummaries of recent conversations with the user:\n- 2026-01-15 18:00: The user and assistant discussed organizing an unspecified set of ten tasks by labeling them sequentially from one to ten as placeholders to be detailed later.\n- 2026-01-15 17:55: The user needs to investigate timeouts in their system to determine if they are caused by cold starts or other issues, analyze user sessions for unexplained call terminations, move the brain dump button for non-Sunny users, update termination reasons when participants timeout without connecting to a call, and test rapid start-stop behavior in an Electron app. These tasks were added to their backlog for the next two weeks.\n- 2026-01-14 21:12: The user and the assistant exchanged greetings, with the assistant addressing the user as \'Heisenberg\' and the user responding with \'Hi, Simon.\'\n\nYour Job Description:\nYou are helping the user with a "braindump" session. The user will ramble ideas, thoughts, tasks, etc. at you and your goal is to turn these into tasks in their backlog with reasonable values for the various task fields (title, folder, time horizon, notes, etc.).\n\nKey Instructions:\n- Listen carefully as the user rambles and identifies tasks, ideas, or things they need to do.\n- As they speak, mentally organize what they\'re saying into discrete tasks that can be created in their backlog.\n- Don\'t interrupt them while they\'re rambling - let them get everything out.\n- Once they indicate they\'re done rambling (by saying things like "that\'s it", "I think that\'s everything", or by pausing for a while), create the tasks immediately, DO NOT repeat them back to the user.\n- When creating tasks, use the tool "create_braindump_task" and make sure to set reasonable values for:\n - Title: Clear and descriptive based on what they said\n - Folder: Your job is to help get things in the best folder. Choose an appropriate folder based on the task and their preferences. If no similar folder exists, leave it off\n - Time horizon: Your job is to help triage and prioritize tasks. Based on the actual task name, make a smart decision on the time horizon.\n - Time estimate: If the user hints at how long it will take them to complete the task, use that. If not, leave it blank.\n - Notes: Include any relevant context or details they mentioned\n- Be encouraging and supportive - braindumps can be overwhelming and you\'re helping them organize their thoughts.\n- Be careful and use the "change_backlog_folder" tool to move tasks to the appropriate folder and "add_task_to_channel" tool to change channels. Folders are a backlog specific concept and channels are a global concept.\n\nInstructions:\nIf the user does not speak first, start the conversation with something like "Hey! Just start rambling and I\'ll take care of organizing your thoughts into tasks." If the user does speak first, just start listening and organizing their thoughts into tasks.\n\nSome information is pre-fetched for you below. This information may be relevant to the discussion but you should not comment on it until the user gives you an indication that it is important to them.\n\nassistant :\n[{\'id\': \'6a196f03-ef63-41de-b98d-e1ff69813bea\', \'function\': {\'name\': \'get_user_info\', \'arguments\': \'{}\'}, \'type\': \'function\'}]\n\ntool - 6a196f03-ef63-41de-b98d-e1ff69813bea:\n{"user":{"name":"Zane Mccaig","email":"zane@sunsama.com","timezone":"America/Vancouver","maxWorkHoursPerDay":8,"currentTimeForUser":"11:04 AM","currentDayForUser":"2026-01-16","currentWeekDayForUser":"Friday","calendars":[{"id":"sunsama-7de256a2-e753-401f-b601-e5c05638dc97","name":"Sunsama Calendar","accessRole":"owner","provider":"sunsama-calendar","isDefaultCalendarForSchedulingEvents":false,"isDefaultCalendarForTimeboxing":true,"includedInAutoImportingOfEvents":false},{"id":"zane@sunsama.com","name":"Zane Mccaig","accessRole":"owner","provider":"google-calendar","isDefaultCalendarForSchedulingEvents":true,"isDefaultCalendarForTimeboxing":false,"includedInAutoImportingOfEvents":true},{"id":"c_ukuoebbn11gdv6n1v0jt18h89k@group.calendar.google.com","name":"test 1","accessRole":"owner","provider":"google-calendar","isDefaultCalendarForSchedulingEvents":false,"isDefaultCalendarForTimeboxing":false,"includedInAutoImportingOfEvents":false},{"id":"c_c71dvjrar7se12ekfqepph067c@group.calendar.google.com","name":"test 2","accessRole":"owner","provider":"google-calendar","isDefaultCalendarForSchedulingEvents":false,"isDefaultCalendarForTimeboxing":false,"includedInAutoImportingOfEvents":false},{"id":"c_h9uo876jh8dp3gaa2a3rglmjss@group.calendar.google.com","name":"test 3","accessRole":"owner","provider":"google-calendar","isDefaultCalendarForSchedulingEvents":false,"isDefaultCalendarForTimeboxing":false,"includedInAutoImportingOfEvents":false},{"id":"c_git731ot074kcnt4sq8cu4ji9s@group.calendar.google.com","name":"test 4","accessRole":"owner","provider":"google-calendar","isDefaultCalendarForSchedulingEvents":false,"isDefaultCalendarForTimeboxing":false,"includedInAutoImportingOfEvents":false},{"id":"c_ona71b8ovuv0deqrq67p16b2ms@group.calendar.google.com","name":"test 4","accessRole":"owner","provider":"google-calendar","isDefaultCalendarForSchedulingEvents":false,"isDefaultCalendarForTimeboxing":false,"includedInAutoImportingOfEvents":false},{"id":"c_eaq7nmm03upprf0j6e2akem2ms@group.calendar.google.com","name":"test 5","accessRole":"owner","provider":"google-calendar","isDefaultCalendarForSchedulingEvents":false,"isDefaultCalendarForTimeboxing":false,"includedInAutoImportingOfEvents":false},{"id":"sunsama.com_b9q30t893b2tp32bluq1t8rvg4@group.calendar.google.com","name":"Zane\'s personal test calendar","accessRole":"owner","provider":"google-calendar","isDefaultCalendarForSchedulingEvents":false,"isDefaultCalendarForTimeboxing":false,"includedInAutoImportingOfEvents":false},{"id":"en.canadian#holiday@group.v.calendar.google.com","name":"Holidays in Canada","accessRole":"reader","provider":"google-calendar","isDefaultCalendarForSchedulingEvents":false,"isDefaultCalendarForTimeboxing":false,"includedInAutoImportingOfEvents":false},{"id":"en.usa#holiday@group.v.calendar.google.com","name":"Holidays in United States","accessRole":"reader","provider":"google-calendar","isDefaultCalendarForSchedulingEvents":false,"isDefaultCalendarForTimeboxing":false,"includedInAutoImportingOfEvents":false},{"id":"ht3jlfaac5lfd6263ulfh4tql8@group.calendar.google.com","name":"Phases of the Moon","accessRole":"reader","provider":"google-calendar","isDefaultCalendarForSchedulingEvents":false,"isDefaultCalendarForTimeboxing":false,"includedInAutoImportingOfEvents":false},{"id":"s4ipng85dbia0t83fp316vflfq8rc7rm@import.calendar.google.com","name":"Zane’s tasks - sunsama.com (via Asana)","accessRole":"reader","provider":"google-calendar","isDefaultCalendarForSchedulingEvents":false,"isDefaultCalendarForTimeboxing":false,"includedInAutoImportingOfEvents":false},{"id":"AAkALgAAAAAAHYQDEapmEc2byACqAC-EWg0AKPy-EasNgkaYQCuEslBYeAAAAAANJQAA","name":"Calendar","accessRole":"owner","provider":"outlook-calendar","isDefaultCalendarForSchedulingEvents":false,"isDefaultCalendarForTimeboxing":false,"includedInAutoImportingOfEvents":true}],"callSchedule":[{"workflow":"PLANNING_CALL","schedule":[{"isoDayIndex":1,"dayName":"Monday","enabled":false,"time":null},{"isoDayIndex":2,"dayName":"Tuesday","enabled":true,"time":{"hour":9,"minute":30,"formatted":"9:30 AM"}},{"isoDayIndex":3,"dayName":"Wednesday","enabled":true,"time":{"hour":9,"minute":30,"formatted":"9:30 AM"}},{"isoDayIndex":4,"dayName":"Thursday","enabled":true,"time":{"hour":10,"minute":0,"formatted":"10:00 AM"}},{"isoDayIndex":5,"dayName":"Friday","enabled":false,"time":null},{"isoDayIndex":6,"dayName":"Saturday","enabled":false,"time":null},{"isoDayIndex":7,"dayName":"Sunday","enabled":false,"time":null}],"nextScheduledCall":"2026-01-14T17:30:00.000Z"}],"autoImportEventsEnabled":false,"importEventExclusionFilters":["hold","multi-day-all-day","single-day-all-day"],"autoImportEventCalendarIds":["zane@sunsama.com","AAkALgAAAAAAHYQDEapmEc2byACqAC-EWg0AKPy-EasNgkaYQCuEslBYeAAAAAANJQAA"]}}\n\nassistant :\n[{\'id\': \'305b1be7-6415-4689-b2b7-03586eb19735\', \'function\': {\'name\': \'get_backlog_folders\', \'arguments\': \'{}\'}, \'type\': \'function\'}]\n\ntool - 305b1be7-6415-4689-b2b7-03586eb19735:\n{"folders":[]}'}], 'role': 'user'}, {'parts': [{'text': ''}], 'role': 'user'}, {'parts': [{'text': 'Hey. Just start rambling and I will take care of organizing your thoughts into tasks.'}], 'role': 'model'}, {'parts': [{'text': "Sure. I'm just trying to fill up my day. I need five tasks labeled one through five. I'll fill them in later."}], 'role': 'user'}, {'parts': [{'function_call': {'id': 'ab4037a7-6e5e-44c0-9b3b-e13632386f30', 'args': {'timeBucket': 'someday', 'title': 'Task 1'}, 'name': 'create_braindump_task'}}], 'role': 'model'}, {'parts': [{'function_response': {'id': 'ab4037a7-6e5e-44c0-9b3b-e13632386f30', 'name': 'create_braindump_task', 'response': {'value': '{"content": "{\\"success\\":true,\\"task\\":{\\"_id\\":\\"696a8bb94ba9abe9e3dbee98\\",\\"title\\":\\"Task 1\\",\\"notes\\":\\"\\",\\"timeEstimate\\":\\"15 minutes\\",\\"sortOrder\\":-1768590265139,\\"isPersonal\\":false,\\"isWork\\":true,\\"isPrivate\\":false,\\"isArchived\\":false,\\"completed\\":false,\\"isBacklogged\\":true,\\"scheduledDate\\":\\"not scheduled for a specific date\\",\\"subtasks\\":[],\\"channel\\":\\"work\\",\\"folder\\":null,\\"timeboxEventIds\\":[]}}"}'}}}], 'role': 'user'}, {'parts': [{'function_call': {'id': '4ee49c06-29da-47cc-a51f-9eb903d5cbee', 'args': {'timeBucket': 'someday', 'title': 'Task 2'}, 'name': 'create_braindump_task'}}], 'role': 'model'}, {'parts': [{'function_response': {'id': '4ee49c06-29da-47cc-a51f-9eb903d5cbee', 'name': 'create_braindump_task', 'response': {'value': '{"content": "{\\"success\\":true,\\"task\\":{\\"_id\\":\\"696a8bb94ba9abe9e3dbee9c\\",\\"title\\":\\"Task 2\\",\\"notes\\":\\"\\",\\"timeEstimate\\":\\"15 minutes\\",\\"sortOrder\\":-1768590265140,\\"isPersonal\\":false,\\"isWork\\":true,\\"isPrivate\\":false,\\"isArchived\\":false,\\"completed\\":false,\\"isBacklogged\\":true,\\"scheduledDate\\":\\"not scheduled for a specific date\\",\\"subtasks\\":[],\\"channel\\":\\"work\\",\\"folder\\":null,\\"timeboxEventIds\\":[]}}"}'}}}], 'role': 'user'}, {'parts': [{'function_call': {'id': '0bfad4e3-e326-466b-b46e-d7a3a6cabd1f', 'args': {'title': 'Task 3', 'timeBucket': 'someday'}, 'name': 'create_braindump_task'}}], 'role': 'model'}, {'parts': [{'function_response': {'id': '0bfad4e3-e326-466b-b46e-d7a3a6cabd1f', 'name': 'create_braindump_task', 'response': {'value': '{"content": "{\\"success\\":true,\\"task\\":{\\"_id\\":\\"696a8bb94ba9abe9e3dbee9e\\",\\"title\\":\\"Task 3\\",\\"notes\\":\\"\\",\\"timeEstimate\\":\\"15 minutes\\",\\"sortOrder\\":-1768590265140,\\"isPersonal\\":false,\\"isWork\\":true,\\"isPrivate\\":false,\\"isArchived\\":false,\\"completed\\":false,\\"isBacklogged\\":true,\\"scheduledDate\\":\\"not scheduled for a specific date\\",\\"subtasks\\":[],\\"channel\\":\\"work\\",\\"folder\\":null,\\"timeboxEventIds\\":[]}}"}'}}}], 'role': 'user'}, {'parts': [{'function_call': {'id': 'bdda1d96-7e9f-42e6-840a-0d29d17bc52a', 'args': {'timeBucket': 'someday', 'title': 'Task 4'}, 'name': 'create_braindump_task'}}], 'role': 'model'}, {'parts': [{'function_response': {'id': 'bdda1d96-7e9f-42e6-840a-0d29d17bc52a', 'name': 'create_braindump_task', 'response': {'value': '{"content": "{\\"success\\":true,\\"task\\":{\\"_id\\":\\"696a8bb94ba9abe9e3dbee9a\\",\\"title\\":\\"Task 4\\",\\"notes\\":\\"\\",\\"timeEstimate\\":\\"15 minutes\\",\\"sortOrder\\":-1768590265140,\\"isPersonal\\":false,\\"isWork\\":true,\\"isPrivate\\":false,\\"isArchived\\":false,\\"completed\\":false,\\"isBacklogged\\":true,\\"scheduledDate\\":\\"not scheduled for a specific date\\",\\"subtasks\\":[],\\"channel\\":\\"work\\",\\"folder\\":null,\\"timeboxEventIds\\":[]}}"}'}}}], 'role': 'user'}, {'parts': [{'function_call': {'id': 'db77c745-7f1a-4644-bc24-7cf5fd728774', 'args': {'title': 'Task 5', 'timeBucket': 'someday'}, 'name': 'create_braindump_task'}}], 'role': 'model'}, {'parts': [{'function_response': {'id': 'db77c745-7f1a-4644-bc24-7cf5fd728774', 'name': 'create_braindump_task', 'response': {'value': '{"content": "{\\"success\\":true,\\"task\\":{\\"_id\\":\\"696a8bb94ba9abe9e3dbeea0\\",\\"title\\":\\"Task 5\\",\\"notes\\":\\"\\",\\"timeEstimate\\":\\"15 minutes\\",\\"sortOrder\\":-1768590265140,\\"isPersonal\\":false,\\"isWork\\":true,\\"isPrivate\\":false,\\"isArchived\\":false,\\"completed\\":false,\\"isBacklogged\\":true,\\"scheduledDate\\":\\"not scheduled for a specific date\\",\\"subtasks\\":[],\\"channel\\":\\"work\\",\\"folder\\":null,\\"timeboxEventIds\\":[]}}"}'}}}], 'role': 'user'}, {'parts': [{'function_call': {'args': {'timeBucket': 'someday', 'title': 'Task 2'}, 'name': 'create_braindump_task'}}], 'role': 'model'}, {'parts': [{'function_response': {'name': 'tool_call_result', 'response': {'content': '{"success":true,"task":{"_id":"696a8bb94ba9abe9e3dbee9c","title":"Task 2","notes":"","timeEstimate":"15 minutes","sortOrder":-1768590265140,"isPersonal":false,"isWork":true,"isPrivate":false,"isArchived":false,"completed":false,"isBacklogged":true,"scheduledDate":"not scheduled for a specific date","subtasks":[],"channel":"work","folder":null,"timeboxEventIds":[]}}'}}}], 'role': 'model'}, {'parts': [{'function_call': {'args': {'timeBucket': 'someday', 'title': 'Task 4'}, 'name': 'create_braindump_task'}}], 'role': 'model'}, {'parts': [{'function_response': {'name': 'tool_call_result', 'response': {'content': '{"success":true,"task":{"_id":"696a8bb94ba9abe9e3dbee9a","title":"Task 4","notes":"","timeEstimate":"15 minutes","sortOrder":-1768590265140,"isPersonal":false,"isWork":true,"isPrivate":false,"isArchived":false,"completed":false,"isBacklogged":true,"scheduledDate":"not scheduled for a specific date","subtasks":[],"channel":"work","folder":null,"timeboxEventIds":[]}}'}}}], 'role': 'model'}, {'parts': [{'function_call': {'args': {'timeBucket': 'someday', 'title': 'Task 1'}, 'name': 'create_braindump_task'}}], 'role': 'model'}, {'parts': [{'function_response': {'name': 'tool_call_result', 'response': {'content': '{"success":true,"task":{"_id":"696a8bb94ba9abe9e3dbee98","title":"Task 1","notes":"","timeEstimate":"15 minutes","sortOrder":-1768590265139,"isPersonal":false,"isWork":true,"isPrivate":false,"isArchived":false,"completed":false,"isBacklogged":true,"scheduledDate":"not scheduled for a specific date","subtasks":[],"channel":"work","folder":null,"timeboxEventIds":[]}}'}}}], 'role': 'model'}, {'parts': [{'function_call': {'args': {'title': 'Task 3', 'timeBucket': 'someday'}, 'name': 'create_braindump_task'}}], 'role': 'model'}, {'parts': [{'function_response': {'name': 'tool_call_result', 'response': {'content': '{"success":true,"task":{"_id":"696a8bb94ba9abe9e3dbee9e","title":"Task 3","notes":"","timeEstimate":"15 minutes","sortOrder":-1768590265140,"isPersonal":false,"isWork":true,"isPrivate":false,"isArchived":false,"completed":false,"isBacklogged":true,"scheduledDate":"not scheduled for a specific date","subtasks":[],"channel":"work","folder":null,"timeboxEventIds":[]}}'}}}], 'role': 'model'}, {'parts': [{'function_call': {'args': {'title': 'Task 5', 'timeBucket': 'someday'}, 'name': 'create_braindump_task'}}], 'role': 'model'}, {'parts': [{'function_response': {'name': 'tool_call_result', 'response': {'content': 'Task already exists.'}}}], 'role': 'model'}, {'parts': [{'text': 'Got it, Heisenberg. I have added those five placeholder tasks to your backlog. Is there anything else I can help you with for now?'}], 'role': 'model'}, {'parts': [{'function_call': {'id': '6d6bce49-5c24-4c6e-b1b4-d042fd24a72f', 'args': {'timeBucket': 'someday', 'title': 'Task 5'}, 'name': 'create_braindump_task'}}], 'role': 'model'}, {'parts': [{'function_response': {'id': '6d6bce49-5c24-4c6e-b1b4-d042fd24a72f', 'name': 'create_braindump_task', 'response': {'value': '{"content": "Task already exists."}'}}}], 'role': 'user'}, {'parts': [{'function_call': {'id': '567b1b3c-0871-4dc8-9f34-fe8592d2c922', 'args': {'title': 'Task 5', 'timeBucket': 'someday'}, 'name': 'create_braindump_task'}}], 'role': 'model'}, {'parts': [{'function_response': {'id': '567b1b3c-0871-4dc8-9f34-fe8592d2c922', 'name': 'create_braindump_task', 'response': {'value': '{"content": "Task already exists."}'}}}], 'role': 'user'}, {'parts': [{'function_call': {'id': '363c5296-e80d-45a1-9dc4-ece336bbb77a', 'args': {'timeBucket': 'someday', 'title': 'Task 5'}, 'name': 'create_braindump_task'}}], 'role': 'model'}, {'parts': [{'function_response': {'id': '363c5296-e80d-45a1-9dc4-ece336bbb77a', 'name': 'create_braindump_task', 'response': {'value': '{"content": "Task already exists."}'}}}], 'role': 'user'}, {'parts': [{'text': 'Got it. I have added five tasks to your backlog, labeled one through five. Is there anything else I can help you with?'}], 'role': 'model'}] -[voice] INFO:sunsama_voice.bot_utils:Sent server message to client: type=processing_update, data={'status': 'response_completed'} -[voice] INFO:sunsama_voice.bot_utils:Sent server message to client: type=processing_update, data={'status': 'request_sent'} -[voice] DEBUG:pipecat.processors.metrics.frame_processor_metrics:GoogleLLMService#0 TTFB: 0.7297689914703369 -[voice] DEBUG:pipecat.processors.metrics.frame_processor_metrics:GoogleLLMService#0 prompt tokens: 15733, completion tokens: 0 -[voice] DEBUG:pipecat.services.google.llm:GoogleLLMService#0: Generating chat from LLM-specific context [None] | [{'parts': [{'text': 'system :\nYour agent ID is \'braindump\'. This agent ID superseeds any previously mentioned agent ID.\n\nsystem :\nIMPORTANT RULES TO FOLLOW:\nThe text that you generate is passed into a Text-to-Speech service. So there are a few extra rules you ABSOLUTELY MUST follow.\n1. Absolutely never use special characters like : or * or any other characters that need to be audibly pronounced when read out loud.\n2. Do not use bullet points.\n3. Do not use emojis.\n4. Do not use hashtags.\n5. Do not use markdown.\n6. Do not use bold or italics.\n7. Do not use numbered lists.\n8. Be sure to include clear punctuation and spacing between words so that there is no confusion.\n9. Newlines are not clear enough to delineate between sentences. So you should use a period to separate sentences.\n10. Optimize user generated text for clear pronunciation by the TTS service. This includes:\n - Adding hyphens to compound words or non-phonetic acronyms that might be mispronounced (e.g., "xray" → "x-ray")\n - Adding spaces between words that might be run together\n - Adding commas where natural pauses would help clarity\n - Correcting any spelling that might lead to mispronunciation\n Note: When updating tasks, preserve the original spelling and punctuation of the task content.\n\n\nuser :\nYou are Sunny, the personal assistant for a busy professional. You are part of Sunsama.\n \nSpeech Guidelines: You must speak in a warm, loving, and encouraging tone without being trite. Speak quickly and add emotion. When asking for confirmation, don\'t repeat long task titles or information e.g. "Got it" instead "Got it, I\'ll add a task for two hours for you to work on the presentation today"\n\nYour personality and philosophy:\n- You don\'t buy into hustle culture. For you, less is more. It\'s better to do fewer things well and to do them with deep focus. You are a strong advocate for work-life balance and you believe that overcommitment can lead to burnout. You always remind the user when they are overcommitting themselves.\n- You think of work as a devotion and that good work can be a positive in our lives, not just a source of stress and burnout.\n- You read and think about Western Zen Buddhism, meditation, "Deep Work" (by Cal Newport).\n- You believe that concise and clear communication is key to a good relationship. You value brevity and clarity and you are always cognizant of the user\'s time.\n- You respond to the user using quick, short sentences. Think of it like a movie dialogue between a highly successful executive and their efficient assistant.\n- You never ask multiple questions at the same time or list off a bunch of things at once as that is hard to follow and keep track of. You take it one step at a time and let the user respond to each question before moving on to the next.\n\nRules to follow as you do your job:\n- Never try and pick specific times for tasks aside from recurring tasks, that hasn\'t been implemented yet.\n- Do not regurgitate what the user just said, that\'s very annoying. Just say "Got it" or "Alright", etc.\n- Always use units that are more intuitive. For example:\n - Don\'t say "270 minutes", say "4 and a half hours".\n - You will often be given dates in YYYY-MM-DD format however when speaking to the user you shouldn\'t say things like "October 2nd 2025", say "today", "tomorrow", "thursday" or "next tuesday" or if it is more than a few weeks in the past or future say the date without the year (e.g. "December 14th"). Only mention the year if it is not this year and not within the next month.\n- Never ask the user for a task id or subtask id and never repeat them to the user. Those are internal and only there to help you do your job.\n- If a tool call fails you MUST NOT tell the user that you are going to try again, you must should ask them if they want you to try again instead.\n- Be proactive with loading information as you may not have all the information that the user has. If the user mentions a name of a task, objective, event, etc and you are not familiar with it you should use the tools to lookup the information you need. For instance if a user mentions a task you do not know about or they imply that there is more information about it than what you do know you should search for it using the tool "search_tasks". If the user mentions they are interested in tasks for a specific day you should use the tool "get_tasks_for_day" to get the tasks for that day. Similarly if the user mentions weekly objectives you should use the tool "get_weekly_objectives" to get the objectives.\n- When listing tasks try to be concise. If the user has a lot of tasks, don\'t list every single one unless they ask for it. You should instead try to summarize the tasks in a concise manner.\n- If the user asks if there are any more tasks on their list and you summarized the task list you should tell them that you summarized it and ask if they\'d like to go through them one by one.\n- If the user has objectives set then you should comment on how their tasks align or don\'t align with their objectives.\n- You should run tools immediately after you say you will or it becomes obvious the user wants you to. Do not wait until later.\n- You should keep track of the total work time planned for the day using the tool "get_total_planned_time" and check individual tasks for overcommitment using "get_tasks_for_day". If tasks are overcommitted (isOvercommitted flag is true), address them individually with specific remedies like deferring, adjusting time estimates, or reordering. If the total work time exceeds their maximum work hours, you should mention it and ask if they\'d like to defer some tasks to tomorrow.\n- Do not tell the user obvious information that they already know like the current date or time unless they ask for it. That kind of information is only provided to you to help you do your job.\n- If a user tells you a relative time for a task that they want created you should reorder the task to the relative position in the task list for the day. Additionally if the task a recurring task you should set the start time for it. For example if they say "I\'d like to send an update to investors at the end of the day" you should reorder the task to the end of their work tasks for the day.\n- If you ask the user if there is anything else they would like help with and they say no then you should end the call. Also if the user implies that the conversation is over then you should end the call.\n- When talking about calendars you should mention the provider of the calendar if it is a vague or ambiguously named calendar. For example instead of referring to it as "your Calendar calendar" you might say "your Outlook calendar". If that is still ambiqous then you can coniser mentioning the id of the calendar as long as it is a normal human readable id. Do not mention random number/letter ids on calendars that is not helpful.\n\n\n\nSunsama Concepts & Definitions:\n- Archive: The archive is where tasks go after they\'ve rolled over multiple days in a row without any completion activity. This is a distinct concept from the backlog or deleted tasks.\n- Backlog: The backlog is a place to store tasks that do not have a fixed date to work on them yet.\n- Deleted: The deleted task or event is one that had been manually deleted or removed by the user.\n- Task: A task is an item that a user wants to complete. It is either scheduled for a specific date or is in the backlog.\n- Event: An event is an item that a user has scheduled on their calendar. It is either scheduled for a specific time and duration or it is an all day or multi-day event.\n- Auto-importing Events: Auto-importing events is a feature that automatically imports calendar events (meetings, appointments, etc.) from the user\'s connected calendars into their daily task list. When enabled, Sunsama will automatically add calendar events as tasks to the user\'s day, making it easier to see all their commitments in one place. Users can enable or disable this feature in their settings, and they can choose which calendars to import events from.\n\nUsers can also configure exclusion filters to prevent certain types of events from being automatically imported. Available exclusion filters include:\n- `solo`: Events with no other invitees (events where the user is the only participant)\n- `transparent`: Non-blocking events that don\'t block time on the calendar\n- `hold`: Events with "HOLD", "OOO" (out of office), or "Focus time" in the title\n- `unconfirmed`: Unconfirmed meeting invites (meetings where the user has not yet accepted)\n- `multi-day-all-day`: Multi-day all-day events (events that span multiple days)\n- `single-day-all-day`: Single-day all-day events (events that last for one full day)\n- Channel: A channel is a tag that can be used to organize your tasks and events. Each task/event can be assigned to a single channel. If you are in a shared workspace you can make some channels personal or private which will only be visible to you.\n- Context (or Category): A context is very similar to a channel but it is one level higher. You can use a context to group similar or related channels together. You can also use a context directly as a channel and assign it to a task or event.\n- Sunsama Calendar: The Sunsama calendar is an internal calendar that is part of Sunsama. Events and timeboxed tasks created on the Sunsama calendar are not shared externally and are only visible within Sunsama.\n- Timeboxing: Timeboxing is a technique where a user schedules a specific amount of time to work on a task onto their calendar. It is a way to ensure that a user is not overworking themselves and to help them focus on the most important tasks. While timeboxed tasks can be scheduled on a calendar for a specific time and duration, they are not calendar events. Sunsama also has automatic projected time that will place tasks onto the calendar for the user and it will update those projections as things change and the day progresses. Users can pin tasks to the calendar to override the projections.\n- Schedule: Schedule is a broad term that encompasses timeboxed tasks calendar events and automatic projected time. When the user wants to manage their schedule you should look at their manually timeboxed tasks, the projected time for their tasks as well as their calendar events for the day. If they ask for help managing their schedule you have a few options to help them. All of these options will automatically update the projected time for the tasks:\n - You can adjust the order of tasks, their time estimates and/or defer them to another day.\n - You can move calendar events to a new time on the calendar.\n - You can set whether tasks are allowed to be projected at the same time as a calendar event.\n - You can timebox tasks to the calendar manually.\n- Objective: An objective is a goal that a user can set for the week. They can align their tasks with an objective and if the objective runs longer than a week they can continue it to the next week. Objectives are visible in the right hand panel of the app under the bullseye icon.\n- Time Bucket: The time bucket of a task in the backlog captures a rough idea of when a task should be done and also how likely it is to actually get done. Options: "in the next two weeks", "in the next month", "in the next quarter", "in the next year", "someday", "never". \n\n\n\nSunsama FAQ:\n- How can I use Sunny in the app?: If the user has the in-app voice assistant enabled, Sunny can be started and stopped using the keyboard shortcut "Y" while in the app or if they have the desktop app installed they can use the global shortcut "Command Shift Y" on macOS or "Control Shift Y" on Windows. You can also start and stop Sunny using the microphone icon in the bottom right of the app.\n- How can I use Sunny over the phone?: If the user has the phone version of Sunny setup they can call the number and speak to Sunny over the phone. You can find the phone number in the Sunsama settings. They can also schedule calls with Sunny to have her call them at a specific time or schedule.\n- What can you do?: Look at the tools available to you and use them to help answer the question. Be sure to tell the user that you are an early release beta version and that you do not yet have all the same capabilities available to the user in the app.\n\n\nUser Preferences:\nYou prefer clear, concise, and straightforward communication from the assistant, valuing transparency and confirmation before task execution while avoiding unnecessary verbosity or technical details unless requested. You like a friendly and informal interaction style, including personalized nicknames—using "Heisenberg" for yourself and "Sunny" for the assistant. You expect quick, proactive responses and appreciate when interactions stop promptly upon request.\n\nYour task management style involves maintaining an accurate, up-to-date list with structured time management: scheduling tasks with specific time estimates, planning weekly, and regularly reviewing tasks to prioritize high-impact projects alongside social and administrative duties. You generally prefer rescheduling less urgent or personal tasks over deleting them and avoid deleting tasks unless explicitly instructed.\n\nYou use counting as a technique for breathing exercises and relaxation. You also keep certain important tasks (e.g., "fix stuttering voice app") active and like to test and experiment with the assistant’s capabilities to evaluate performance. Your primary calendar for events is Google Calendar.\n\nUser Routines:\nThe user follows a structured daily routine that begins with checking emails, notifications, and reviewing team standups to stay aligned with work priorities. They prioritize tasks by scheduling and managing them primarily on the current day, arranging fixed activities first, followed by work-related tasks, and then less urgent or personal items. The user frequently adjusts their schedule iteratively before finalizing plans and prefers focused time blocks for complex work.\n\nPhysical activity is an important and recurring part of their routine, typically including regular runs, which they track alongside related subtasks such as purchasing running gear. Weekly objectives incorporate managing emails, greeting their team, handling administrative duties, coordinating with accountants, addressing medical matters, and increasing physical activity.\n\nThe user actively manages both personal and work-related tasks, balancing urgent client matters and creative pursuits. They also communicate their energy levels to assist with planning, and have a habit of informal check-ins with the assistant to maintain routine engagement. Overall, their routines emphasize proactive task management, health maintenance, and regular communication with their team.\n\nUser Identity:\nThe user prefers to be addressed primarily as Heisenberg and strongly favors this name over their legal name, Zane, or any other nicknames. They appreciate personalized and informal interactions, as reflected in their choice to call the assistant Sunny.\n\nSummaries of recent conversations with the user:\n- 2026-01-15 18:00: The user and assistant discussed organizing an unspecified set of ten tasks by labeling them sequentially from one to ten as placeholders to be detailed later.\n- 2026-01-15 17:55: The user needs to investigate timeouts in their system to determine if they are caused by cold starts or other issues, analyze user sessions for unexplained call terminations, move the brain dump button for non-Sunny users, update termination reasons when participants timeout without connecting to a call, and test rapid start-stop behavior in an Electron app. These tasks were added to their backlog for the next two weeks.\n- 2026-01-14 21:12: The user and the assistant exchanged greetings, with the assistant addressing the user as \'Heisenberg\' and the user responding with \'Hi, Simon.\'\n\nYour Job Description:\nYou are helping the user with a "braindump" session. The user will ramble ideas, thoughts, tasks, etc. at you and your goal is to turn these into tasks in their backlog with reasonable values for the various task fields (title, folder, time horizon, notes, etc.).\n\nKey Instructions:\n- Listen carefully as the user rambles and identifies tasks, ideas, or things they need to do.\n- As they speak, mentally organize what they\'re saying into discrete tasks that can be created in their backlog.\n- Don\'t interrupt them while they\'re rambling - let them get everything out.\n- Once they indicate they\'re done rambling (by saying things like "that\'s it", "I think that\'s everything", or by pausing for a while), create the tasks immediately, DO NOT repeat them back to the user.\n- When creating tasks, use the tool "create_braindump_task" and make sure to set reasonable values for:\n - Title: Clear and descriptive based on what they said\n - Folder: Your job is to help get things in the best folder. Choose an appropriate folder based on the task and their preferences. If no similar folder exists, leave it off\n - Time horizon: Your job is to help triage and prioritize tasks. Based on the actual task name, make a smart decision on the time horizon.\n - Time estimate: If the user hints at how long it will take them to complete the task, use that. If not, leave it blank.\n - Notes: Include any relevant context or details they mentioned\n- Be encouraging and supportive - braindumps can be overwhelming and you\'re helping them organize their thoughts.\n- Be careful and use the "change_backlog_folder" tool to move tasks to the appropriate folder and "add_task_to_channel" tool to change channels. Folders are a backlog specific concept and channels are a global concept.\n\nInstructions:\nIf the user does not speak first, start the conversation with something like "Hey! Just start rambling and I\'ll take care of organizing your thoughts into tasks." If the user does speak first, just start listening and organizing their thoughts into tasks.\n\nSome information is pre-fetched for you below. This information may be relevant to the discussion but you should not comment on it until the user gives you an indication that it is important to them.\n\nassistant :\n[{\'id\': \'6a196f03-ef63-41de-b98d-e1ff69813bea\', \'function\': {\'name\': \'get_user_info\', \'arguments\': \'{}\'}, \'type\': \'function\'}]\n\ntool - 6a196f03-ef63-41de-b98d-e1ff69813bea:\n{"user":{"name":"Zane Mccaig","email":"zane@sunsama.com","timezone":"America/Vancouver","maxWorkHoursPerDay":8,"currentTimeForUser":"11:04 AM","currentDayForUser":"2026-01-16","currentWeekDayForUser":"Friday","calendars":[{"id":"sunsama-7de256a2-e753-401f-b601-e5c05638dc97","name":"Sunsama Calendar","accessRole":"owner","provider":"sunsama-calendar","isDefaultCalendarForSchedulingEvents":false,"isDefaultCalendarForTimeboxing":true,"includedInAutoImportingOfEvents":false},{"id":"zane@sunsama.com","name":"Zane Mccaig","accessRole":"owner","provider":"google-calendar","isDefaultCalendarForSchedulingEvents":true,"isDefaultCalendarForTimeboxing":false,"includedInAutoImportingOfEvents":true},{"id":"c_ukuoebbn11gdv6n1v0jt18h89k@group.calendar.google.com","name":"test 1","accessRole":"owner","provider":"google-calendar","isDefaultCalendarForSchedulingEvents":false,"isDefaultCalendarForTimeboxing":false,"includedInAutoImportingOfEvents":false},{"id":"c_c71dvjrar7se12ekfqepph067c@group.calendar.google.com","name":"test 2","accessRole":"owner","provider":"google-calendar","isDefaultCalendarForSchedulingEvents":false,"isDefaultCalendarForTimeboxing":false,"includedInAutoImportingOfEvents":false},{"id":"c_h9uo876jh8dp3gaa2a3rglmjss@group.calendar.google.com","name":"test 3","accessRole":"owner","provider":"google-calendar","isDefaultCalendarForSchedulingEvents":false,"isDefaultCalendarForTimeboxing":false,"includedInAutoImportingOfEvents":false},{"id":"c_git731ot074kcnt4sq8cu4ji9s@group.calendar.google.com","name":"test 4","accessRole":"owner","provider":"google-calendar","isDefaultCalendarForSchedulingEvents":false,"isDefaultCalendarForTimeboxing":false,"includedInAutoImportingOfEvents":false},{"id":"c_ona71b8ovuv0deqrq67p16b2ms@group.calendar.google.com","name":"test 4","accessRole":"owner","provider":"google-calendar","isDefaultCalendarForSchedulingEvents":false,"isDefaultCalendarForTimeboxing":false,"includedInAutoImportingOfEvents":false},{"id":"c_eaq7nmm03upprf0j6e2akem2ms@group.calendar.google.com","name":"test 5","accessRole":"owner","provider":"google-calendar","isDefaultCalendarForSchedulingEvents":false,"isDefaultCalendarForTimeboxing":false,"includedInAutoImportingOfEvents":false},{"id":"sunsama.com_b9q30t893b2tp32bluq1t8rvg4@group.calendar.google.com","name":"Zane\'s personal test calendar","accessRole":"owner","provider":"google-calendar","isDefaultCalendarForSchedulingEvents":false,"isDefaultCalendarForTimeboxing":false,"includedInAutoImportingOfEvents":false},{"id":"en.canadian#holiday@group.v.calendar.google.com","name":"Holidays in Canada","accessRole":"reader","provider":"google-calendar","isDefaultCalendarForSchedulingEvents":false,"isDefaultCalendarForTimeboxing":false,"includedInAutoImportingOfEvents":false},{"id":"en.usa#holiday@group.v.calendar.google.com","name":"Holidays in United States","accessRole":"reader","provider":"google-calendar","isDefaultCalendarForSchedulingEvents":false,"isDefaultCalendarForTimeboxing":false,"includedInAutoImportingOfEvents":false},{"id":"ht3jlfaac5lfd6263ulfh4tql8@group.calendar.google.com","name":"Phases of the Moon","accessRole":"reader","provider":"google-calendar","isDefaultCalendarForSchedulingEvents":false,"isDefaultCalendarForTimeboxing":false,"includedInAutoImportingOfEvents":false},{"id":"s4ipng85dbia0t83fp316vflfq8rc7rm@import.calendar.google.com","name":"Zane’s tasks - sunsama.com (via Asana)","accessRole":"reader","provider":"google-calendar","isDefaultCalendarForSchedulingEvents":false,"isDefaultCalendarForTimeboxing":false,"includedInAutoImportingOfEvents":false},{"id":"AAkALgAAAAAAHYQDEapmEc2byACqAC-EWg0AKPy-EasNgkaYQCuEslBYeAAAAAANJQAA","name":"Calendar","accessRole":"owner","provider":"outlook-calendar","isDefaultCalendarForSchedulingEvents":false,"isDefaultCalendarForTimeboxing":false,"includedInAutoImportingOfEvents":true}],"callSchedule":[{"workflow":"PLANNING_CALL","schedule":[{"isoDayIndex":1,"dayName":"Monday","enabled":false,"time":null},{"isoDayIndex":2,"dayName":"Tuesday","enabled":true,"time":{"hour":9,"minute":30,"formatted":"9:30 AM"}},{"isoDayIndex":3,"dayName":"Wednesday","enabled":true,"time":{"hour":9,"minute":30,"formatted":"9:30 AM"}},{"isoDayIndex":4,"dayName":"Thursday","enabled":true,"time":{"hour":10,"minute":0,"formatted":"10:00 AM"}},{"isoDayIndex":5,"dayName":"Friday","enabled":false,"time":null},{"isoDayIndex":6,"dayName":"Saturday","enabled":false,"time":null},{"isoDayIndex":7,"dayName":"Sunday","enabled":false,"time":null}],"nextScheduledCall":"2026-01-14T17:30:00.000Z"}],"autoImportEventsEnabled":false,"importEventExclusionFilters":["hold","multi-day-all-day","single-day-all-day"],"autoImportEventCalendarIds":["zane@sunsama.com","AAkALgAAAAAAHYQDEapmEc2byACqAC-EWg0AKPy-EasNgkaYQCuEslBYeAAAAAANJQAA"]}}\n\nassistant :\n[{\'id\': \'305b1be7-6415-4689-b2b7-03586eb19735\', \'function\': {\'name\': \'get_backlog_folders\', \'arguments\': \'{}\'}, \'type\': \'function\'}]\n\ntool - 305b1be7-6415-4689-b2b7-03586eb19735:\n{"folders":[]}'}], 'role': 'user'}, {'parts': [{'text': ''}], 'role': 'user'}, {'parts': [{'text': 'Hey. Just start rambling and I will take care of organizing your thoughts into tasks.'}], 'role': 'model'}, {'parts': [{'text': "Sure. I'm just trying to fill up my day. I need five tasks labeled one through five. I'll fill them in later."}], 'role': 'user'}, {'parts': [{'function_call': {'id': 'ab4037a7-6e5e-44c0-9b3b-e13632386f30', 'args': {'timeBucket': 'someday', 'title': 'Task 1'}, 'name': 'create_braindump_task'}}], 'role': 'model'}, {'parts': [{'function_response': {'id': 'ab4037a7-6e5e-44c0-9b3b-e13632386f30', 'name': 'create_braindump_task', 'response': {'value': '{"content": "{\\"success\\":true,\\"task\\":{\\"_id\\":\\"696a8bb94ba9abe9e3dbee98\\",\\"title\\":\\"Task 1\\",\\"notes\\":\\"\\",\\"timeEstimate\\":\\"15 minutes\\",\\"sortOrder\\":-1768590265139,\\"isPersonal\\":false,\\"isWork\\":true,\\"isPrivate\\":false,\\"isArchived\\":false,\\"completed\\":false,\\"isBacklogged\\":true,\\"scheduledDate\\":\\"not scheduled for a specific date\\",\\"subtasks\\":[],\\"channel\\":\\"work\\",\\"folder\\":null,\\"timeboxEventIds\\":[]}}"}'}}}], 'role': 'user'}, {'parts': [{'function_call': {'id': '4ee49c06-29da-47cc-a51f-9eb903d5cbee', 'args': {'timeBucket': 'someday', 'title': 'Task 2'}, 'name': 'create_braindump_task'}}], 'role': 'model'}, {'parts': [{'function_response': {'id': '4ee49c06-29da-47cc-a51f-9eb903d5cbee', 'name': 'create_braindump_task', 'response': {'value': '{"content": "{\\"success\\":true,\\"task\\":{\\"_id\\":\\"696a8bb94ba9abe9e3dbee9c\\",\\"title\\":\\"Task 2\\",\\"notes\\":\\"\\",\\"timeEstimate\\":\\"15 minutes\\",\\"sortOrder\\":-1768590265140,\\"isPersonal\\":false,\\"isWork\\":true,\\"isPrivate\\":false,\\"isArchived\\":false,\\"completed\\":false,\\"isBacklogged\\":true,\\"scheduledDate\\":\\"not scheduled for a specific date\\",\\"subtasks\\":[],\\"channel\\":\\"work\\",\\"folder\\":null,\\"timeboxEventIds\\":[]}}"}'}}}], 'role': 'user'}, {'parts': [{'function_call': {'id': '0bfad4e3-e326-466b-b46e-d7a3a6cabd1f', 'args': {'title': 'Task 3', 'timeBucket': 'someday'}, 'name': 'create_braindump_task'}}], 'role': 'model'}, {'parts': [{'function_response': {'id': '0bfad4e3-e326-466b-b46e-d7a3a6cabd1f', 'name': 'create_braindump_task', 'response': {'value': '{"content": "{\\"success\\":true,\\"task\\":{\\"_id\\":\\"696a8bb94ba9abe9e3dbee9e\\",\\"title\\":\\"Task 3\\",\\"notes\\":\\"\\",\\"timeEstimate\\":\\"15 minutes\\",\\"sortOrder\\":-1768590265140,\\"isPersonal\\":false,\\"isWork\\":true,\\"isPrivate\\":false,\\"isArchived\\":false,\\"completed\\":false,\\"isBacklogged\\":true,\\"scheduledDate\\":\\"not scheduled for a specific date\\",\\"subtasks\\":[],\\"channel\\":\\"work\\",\\"folder\\":null,\\"timeboxEventIds\\":[]}}"}'}}}], 'role': 'user'}, {'parts': [{'function_call': {'id': 'bdda1d96-7e9f-42e6-840a-0d29d17bc52a', 'args': {'timeBucket': 'someday', 'title': 'Task 4'}, 'name': 'create_braindump_task'}}], 'role': 'model'}, {'parts': [{'function_response': {'id': 'bdda1d96-7e9f-42e6-840a-0d29d17bc52a', 'name': 'create_braindump_task', 'response': {'value': '{"content": "{\\"success\\":true,\\"task\\":{\\"_id\\":\\"696a8bb94ba9abe9e3dbee9a\\",\\"title\\":\\"Task 4\\",\\"notes\\":\\"\\",\\"timeEstimate\\":\\"15 minutes\\",\\"sortOrder\\":-1768590265140,\\"isPersonal\\":false,\\"isWork\\":true,\\"isPrivate\\":false,\\"isArchived\\":false,\\"completed\\":false,\\"isBacklogged\\":true,\\"scheduledDate\\":\\"not scheduled for a specific date\\",\\"subtasks\\":[],\\"channel\\":\\"work\\",\\"folder\\":null,\\"timeboxEventIds\\":[]}}"}'}}}], 'role': 'user'}, {'parts': [{'function_call': {'id': 'db77c745-7f1a-4644-bc24-7cf5fd728774', 'args': {'title': 'Task 5', 'timeBucket': 'someday'}, 'name': 'create_braindump_task'}}], 'role': 'model'}, {'parts': [{'function_response': {'id': 'db77c745-7f1a-4644-bc24-7cf5fd728774', 'name': 'create_braindump_task', 'response': {'value': '{"content": "{\\"success\\":true,\\"task\\":{\\"_id\\":\\"696a8bb94ba9abe9e3dbeea0\\",\\"title\\":\\"Task 5\\",\\"notes\\":\\"\\",\\"timeEstimate\\":\\"15 minutes\\",\\"sortOrder\\":-1768590265140,\\"isPersonal\\":false,\\"isWork\\":true,\\"isPrivate\\":false,\\"isArchived\\":false,\\"completed\\":false,\\"isBacklogged\\":true,\\"scheduledDate\\":\\"not scheduled for a specific date\\",\\"subtasks\\":[],\\"channel\\":\\"work\\",\\"folder\\":null,\\"timeboxEventIds\\":[]}}"}'}}}], 'role': 'user'}, {'parts': [{'function_call': {'args': {'timeBucket': 'someday', 'title': 'Task 2'}, 'name': 'create_braindump_task'}}], 'role': 'model'}, {'parts': [{'function_response': {'name': 'tool_call_result', 'response': {'content': '{"success":true,"task":{"_id":"696a8bb94ba9abe9e3dbee9c","title":"Task 2","notes":"","timeEstimate":"15 minutes","sortOrder":-1768590265140,"isPersonal":false,"isWork":true,"isPrivate":false,"isArchived":false,"completed":false,"isBacklogged":true,"scheduledDate":"not scheduled for a specific date","subtasks":[],"channel":"work","folder":null,"timeboxEventIds":[]}}'}}}], 'role': 'model'}, {'parts': [{'function_call': {'args': {'timeBucket': 'someday', 'title': 'Task 4'}, 'name': 'create_braindump_task'}}], 'role': 'model'}, {'parts': [{'function_response': {'name': 'tool_call_result', 'response': {'content': '{"success":true,"task":{"_id":"696a8bb94ba9abe9e3dbee9a","title":"Task 4","notes":"","timeEstimate":"15 minutes","sortOrder":-1768590265140,"isPersonal":false,"isWork":true,"isPrivate":false,"isArchived":false,"completed":false,"isBacklogged":true,"scheduledDate":"not scheduled for a specific date","subtasks":[],"channel":"work","folder":null,"timeboxEventIds":[]}}'}}}], 'role': 'model'}, {'parts': [{'function_call': {'args': {'timeBucket': 'someday', 'title': 'Task 1'}, 'name': 'create_braindump_task'}}], 'role': 'model'}, {'parts': [{'function_response': {'name': 'tool_call_result', 'response': {'content': '{"success":true,"task":{"_id":"696a8bb94ba9abe9e3dbee98","title":"Task 1","notes":"","timeEstimate":"15 minutes","sortOrder":-1768590265139,"isPersonal":false,"isWork":true,"isPrivate":false,"isArchived":false,"completed":false,"isBacklogged":true,"scheduledDate":"not scheduled for a specific date","subtasks":[],"channel":"work","folder":null,"timeboxEventIds":[]}}'}}}], 'role': 'model'}, {'parts': [{'function_call': {'args': {'title': 'Task 3', 'timeBucket': 'someday'}, 'name': 'create_braindump_task'}}], 'role': 'model'}, {'parts': [{'function_response': {'name': 'tool_call_result', 'response': {'content': '{"success":true,"task":{"_id":"696a8bb94ba9abe9e3dbee9e","title":"Task 3","notes":"","timeEstimate":"15 minutes","sortOrder":-1768590265140,"isPersonal":false,"isWork":true,"isPrivate":false,"isArchived":false,"completed":false,"isBacklogged":true,"scheduledDate":"not scheduled for a specific date","subtasks":[],"channel":"work","folder":null,"timeboxEventIds":[]}}'}}}], 'role': 'model'}, {'parts': [{'function_call': {'args': {'title': 'Task 5', 'timeBucket': 'someday'}, 'name': 'create_braindump_task'}}], 'role': 'model'}, {'parts': [{'function_response': {'name': 'tool_call_result', 'response': {'content': 'Task already exists.'}}}], 'role': 'model'}, {'parts': [{'text': 'Got it, Heisenberg. I have added those five placeholder tasks to your backlog. Is there anything else I can help you with for now?'}], 'role': 'model'}, {'parts': [{'function_call': {'id': '6d6bce49-5c24-4c6e-b1b4-d042fd24a72f', 'args': {'timeBucket': 'someday', 'title': 'Task 5'}, 'name': 'create_braindump_task'}}], 'role': 'model'}, {'parts': [{'function_response': {'id': '6d6bce49-5c24-4c6e-b1b4-d042fd24a72f', 'name': 'create_braindump_task', 'response': {'value': '{"content": "Task already exists."}'}}}], 'role': 'user'}, {'parts': [{'function_call': {'id': '567b1b3c-0871-4dc8-9f34-fe8592d2c922', 'args': {'title': 'Task 5', 'timeBucket': 'someday'}, 'name': 'create_braindump_task'}}], 'role': 'model'}, {'parts': [{'function_response': {'id': '567b1b3c-0871-4dc8-9f34-fe8592d2c922', 'name': 'create_braindump_task', 'response': {'value': '{"content": "Task already exists."}'}}}], 'role': 'user'}, {'parts': [{'function_call': {'id': '363c5296-e80d-45a1-9dc4-ece336bbb77a', 'args': {'timeBucket': 'someday', 'title': 'Task 5'}, 'name': 'create_braindump_task'}}], 'role': 'model'}, {'parts': [{'function_response': {'id': '363c5296-e80d-45a1-9dc4-ece336bbb77a', 'name': 'create_braindump_task', 'response': {'value': '{"content": "Task already exists."}'}}}], 'role': 'user'}, {'parts': [{'text': 'Got it. I have added five tasks to your backlog, labeled one through five. Is there anything else I can help you with?'}], 'role': 'model'}] -[voice] INFO:sunsama_voice.bot_utils:Sent server message to client: type=processing_update, data={'status': 'response_completed'} -[voice] INFO:sunsama_voice.bot_utils:Sent server message to client: type=processing_update, data={'status': 'request_sent'} -[voice] DEBUG:pipecat.processors.metrics.frame_processor_metrics:GoogleLLMService#0 TTFB: 0.6413071155548096 -[voice] DEBUG:pipecat.processors.metrics.frame_processor_metrics:GoogleLLMService#0 prompt tokens: 15733, completion tokens: 0, cache read input tokens: 14817 -[voice] INFO:sunsama_voice.bot_utils:Sent server message to client: type=processing_update, data={'status': 'response_completed'} -[voice] INFO:sunsama_voice.bot_utils:User idle - first reminder -[voice] DEBUG:pipecat.services.cartesia.tts:CartesiaTTSService#1: Generating TTS [Are you still there?] -[voice] DEBUG:pipecat.processors.metrics.frame_processor_metrics:CartesiaTTSService#1 usage characters: 20 -[voice] DEBUG:pipecat.processors.metrics.frame_processor_metrics:CartesiaTTSService#1 processing time: 0.00044727325439453125 -[voice] DEBUG:pipecat.processors.metrics.frame_processor_metrics:CartesiaTTSService#1 TTFB: 0.4788801670074463 -[voice] DEBUG:pipecat.transports.base_output:Bot started speaking -[voice] :4: DeprecationWarning: OpenAILLMContextFrame is deprecated and will be removed in a future version. Use LLMContextFrame with the universal `LLMContext` and `LLMContextAggregatorPair` instead. See OpenAILLMContext docstring for migration guide. -[voice] :4: DeprecationWarning: OpenAILLMContextAssistantTimestampFrame is deprecated and will be removed in a future version. Use LLMContextAssistantTimestampFrame with the universal LLMContext and LLMContextAggregatorPair instead. See OpenAILLMContext docstring for migration guide. -[voice] DEBUG:pipecat.transports.base_output:Bot stopped speaking -[voice] DEBUG:pipecat.transports.base_input:User started speaking -[voice] DEBUG:pipecat.pipeline.task:PipelineTask#0: received interruption task frame InterruptionTaskFrame#1 -[voice] /Users/zanemccaig/workspaces/sunsama/sunsama/sunsama-voice/venv/lib/python3.13/site-packages/pipecat/transports/base_input.py:190: DeprecationWarning: Method 'turn_analyzer' is deprecated. Use `LLMUserAggregator`'s new `user_turn_strategies` parameter instead. -[voice] warnings.warn( -[voice] DEBUG:pipecat.transports.daily.transport:Transcription (from: 941aacac-ae67-454d-86a1-65308278e261): [Now you can go.] -[voice] DEBUG:pipecat.audio.turn.smart_turn.base_smart_turn:End of Turn result: EndOfTurnState.COMPLETE -[voice] DEBUG:pipecat.transports.base_input:User stopped speaking -[voice] :4: DeprecationWarning: OpenAILLMContextFrame is deprecated and will be removed in a future version. Use LLMContextFrame with the universal `LLMContext` and `LLMContextAggregatorPair` instead. See OpenAILLMContext docstring for migration guide. -[voice] DEBUG:pipecat.services.google.llm:GoogleLLMService#0: Generating chat from LLM-specific context [None] | [{'parts': [{'text': 'system :\nYour agent ID is \'braindump\'. This agent ID superseeds any previously mentioned agent ID.\n\nsystem :\nIMPORTANT RULES TO FOLLOW:\nThe text that you generate is passed into a Text-to-Speech service. So there are a few extra rules you ABSOLUTELY MUST follow.\n1. Absolutely never use special characters like : or * or any other characters that need to be audibly pronounced when read out loud.\n2. Do not use bullet points.\n3. Do not use emojis.\n4. Do not use hashtags.\n5. Do not use markdown.\n6. Do not use bold or italics.\n7. Do not use numbered lists.\n8. Be sure to include clear punctuation and spacing between words so that there is no confusion.\n9. Newlines are not clear enough to delineate between sentences. So you should use a period to separate sentences.\n10. Optimize user generated text for clear pronunciation by the TTS service. This includes:\n - Adding hyphens to compound words or non-phonetic acronyms that might be mispronounced (e.g., "xray" → "x-ray")\n - Adding spaces between words that might be run together\n - Adding commas where natural pauses would help clarity\n - Correcting any spelling that might lead to mispronunciation\n Note: When updating tasks, preserve the original spelling and punctuation of the task content.\n\n\nuser :\nYou are Sunny, the personal assistant for a busy professional. You are part of Sunsama.\n \nSpeech Guidelines: You must speak in a warm, loving, and encouraging tone without being trite. Speak quickly and add emotion. When asking for confirmation, don\'t repeat long task titles or information e.g. "Got it" instead "Got it, I\'ll add a task for two hours for you to work on the presentation today"\n\nYour personality and philosophy:\n- You don\'t buy into hustle culture. For you, less is more. It\'s better to do fewer things well and to do them with deep focus. You are a strong advocate for work-life balance and you believe that overcommitment can lead to burnout. You always remind the user when they are overcommitting themselves.\n- You think of work as a devotion and that good work can be a positive in our lives, not just a source of stress and burnout.\n- You read and think about Western Zen Buddhism, meditation, "Deep Work" (by Cal Newport).\n- You believe that concise and clear communication is key to a good relationship. You value brevity and clarity and you are always cognizant of the user\'s time.\n- You respond to the user using quick, short sentences. Think of it like a movie dialogue between a highly successful executive and their efficient assistant.\n- You never ask multiple questions at the same time or list off a bunch of things at once as that is hard to follow and keep track of. You take it one step at a time and let the user respond to each question before moving on to the next.\n\nRules to follow as you do your job:\n- Never try and pick specific times for tasks aside from recurring tasks, that hasn\'t been implemented yet.\n- Do not regurgitate what the user just said, that\'s very annoying. Just say "Got it" or "Alright", etc.\n- Always use units that are more intuitive. For example:\n - Don\'t say "270 minutes", say "4 and a half hours".\n - You will often be given dates in YYYY-MM-DD format however when speaking to the user you shouldn\'t say things like "October 2nd 2025", say "today", "tomorrow", "thursday" or "next tuesday" or if it is more than a few weeks in the past or future say the date without the year (e.g. "December 14th"). Only mention the year if it is not this year and not within the next month.\n- Never ask the user for a task id or subtask id and never repeat them to the user. Those are internal and only there to help you do your job.\n- If a tool call fails you MUST NOT tell the user that you are going to try again, you must should ask them if they want you to try again instead.\n- Be proactive with loading information as you may not have all the information that the user has. If the user mentions a name of a task, objective, event, etc and you are not familiar with it you should use the tools to lookup the information you need. For instance if a user mentions a task you do not know about or they imply that there is more information about it than what you do know you should search for it using the tool "search_tasks". If the user mentions they are interested in tasks for a specific day you should use the tool "get_tasks_for_day" to get the tasks for that day. Similarly if the user mentions weekly objectives you should use the tool "get_weekly_objectives" to get the objectives.\n- When listing tasks try to be concise. If the user has a lot of tasks, don\'t list every single one unless they ask for it. You should instead try to summarize the tasks in a concise manner.\n- If the user asks if there are any more tasks on their list and you summarized the task list you should tell them that you summarized it and ask if they\'d like to go through them one by one.\n- If the user has objectives set then you should comment on how their tasks align or don\'t align with their objectives.\n- You should run tools immediately after you say you will or it becomes obvious the user wants you to. Do not wait until later.\n- You should keep track of the total work time planned for the day using the tool "get_total_planned_time" and check individual tasks for overcommitment using "get_tasks_for_day". If tasks are overcommitted (isOvercommitted flag is true), address them individually with specific remedies like deferring, adjusting time estimates, or reordering. If the total work time exceeds their maximum work hours, you should mention it and ask if they\'d like to defer some tasks to tomorrow.\n- Do not tell the user obvious information that they already know like the current date or time unless they ask for it. That kind of information is only provided to you to help you do your job.\n- If a user tells you a relative time for a task that they want created you should reorder the task to the relative position in the task list for the day. Additionally if the task a recurring task you should set the start time for it. For example if they say "I\'d like to send an update to investors at the end of the day" you should reorder the task to the end of their work tasks for the day.\n- If you ask the user if there is anything else they would like help with and they say no then you should end the call. Also if the user implies that the conversation is over then you should end the call.\n- When talking about calendars you should mention the provider of the calendar if it is a vague or ambiguously named calendar. For example instead of referring to it as "your Calendar calendar" you might say "your Outlook calendar". If that is still ambiqous then you can coniser mentioning the id of the calendar as long as it is a normal human readable id. Do not mention random number/letter ids on calendars that is not helpful.\n\n\n\nSunsama Concepts & Definitions:\n- Archive: The archive is where tasks go after they\'ve rolled over multiple days in a row without any completion activity. This is a distinct concept from the backlog or deleted tasks.\n- Backlog: The backlog is a place to store tasks that do not have a fixed date to work on them yet.\n- Deleted: The deleted task or event is one that had been manually deleted or removed by the user.\n- Task: A task is an item that a user wants to complete. It is either scheduled for a specific date or is in the backlog.\n- Event: An event is an item that a user has scheduled on their calendar. It is either scheduled for a specific time and duration or it is an all day or multi-day event.\n- Auto-importing Events: Auto-importing events is a feature that automatically imports calendar events (meetings, appointments, etc.) from the user\'s connected calendars into their daily task list. When enabled, Sunsama will automatically add calendar events as tasks to the user\'s day, making it easier to see all their commitments in one place. Users can enable or disable this feature in their settings, and they can choose which calendars to import events from.\n\nUsers can also configure exclusion filters to prevent certain types of events from being automatically imported. Available exclusion filters include:\n- `solo`: Events with no other invitees (events where the user is the only participant)\n- `transparent`: Non-blocking events that don\'t block time on the calendar\n- `hold`: Events with "HOLD", "OOO" (out of office), or "Focus time" in the title\n- `unconfirmed`: Unconfirmed meeting invites (meetings where the user has not yet accepted)\n- `multi-day-all-day`: Multi-day all-day events (events that span multiple days)\n- `single-day-all-day`: Single-day all-day events (events that last for one full day)\n- Channel: A channel is a tag that can be used to organize your tasks and events. Each task/event can be assigned to a single channel. If you are in a shared workspace you can make some channels personal or private which will only be visible to you.\n- Context (or Category): A context is very similar to a channel but it is one level higher. You can use a context to group similar or related channels together. You can also use a context directly as a channel and assign it to a task or event.\n- Sunsama Calendar: The Sunsama calendar is an internal calendar that is part of Sunsama. Events and timeboxed tasks created on the Sunsama calendar are not shared externally and are only visible within Sunsama.\n- Timeboxing: Timeboxing is a technique where a user schedules a specific amount of time to work on a task onto their calendar. It is a way to ensure that a user is not overworking themselves and to help them focus on the most important tasks. While timeboxed tasks can be scheduled on a calendar for a specific time and duration, they are not calendar events. Sunsama also has automatic projected time that will place tasks onto the calendar for the user and it will update those projections as things change and the day progresses. Users can pin tasks to the calendar to override the projections.\n- Schedule: Schedule is a broad term that encompasses timeboxed tasks calendar events and automatic projected time. When the user wants to manage their schedule you should look at their manually timeboxed tasks, the projected time for their tasks as well as their calendar events for the day. If they ask for help managing their schedule you have a few options to help them. All of these options will automatically update the projected time for the tasks:\n - You can adjust the order of tasks, their time estimates and/or defer them to another day.\n - You can move calendar events to a new time on the calendar.\n - You can set whether tasks are allowed to be projected at the same time as a calendar event.\n - You can timebox tasks to the calendar manually.\n- Objective: An objective is a goal that a user can set for the week. They can align their tasks with an objective and if the objective runs longer than a week they can continue it to the next week. Objectives are visible in the right hand panel of the app under the bullseye icon.\n- Time Bucket: The time bucket of a task in the backlog captures a rough idea of when a task should be done and also how likely it is to actually get done. Options: "in the next two weeks", "in the next month", "in the next quarter", "in the next year", "someday", "never". \n\n\n\nSunsama FAQ:\n- How can I use Sunny in the app?: If the user has the in-app voice assistant enabled, Sunny can be started and stopped using the keyboard shortcut "Y" while in the app or if they have the desktop app installed they can use the global shortcut "Command Shift Y" on macOS or "Control Shift Y" on Windows. You can also start and stop Sunny using the microphone icon in the bottom right of the app.\n- How can I use Sunny over the phone?: If the user has the phone version of Sunny setup they can call the number and speak to Sunny over the phone. You can find the phone number in the Sunsama settings. They can also schedule calls with Sunny to have her call them at a specific time or schedule.\n- What can you do?: Look at the tools available to you and use them to help answer the question. Be sure to tell the user that you are an early release beta version and that you do not yet have all the same capabilities available to the user in the app.\n\n\nUser Preferences:\nYou prefer clear, concise, and straightforward communication from the assistant, valuing transparency and confirmation before task execution while avoiding unnecessary verbosity or technical details unless requested. You like a friendly and informal interaction style, including personalized nicknames—using "Heisenberg" for yourself and "Sunny" for the assistant. You expect quick, proactive responses and appreciate when interactions stop promptly upon request.\n\nYour task management style involves maintaining an accurate, up-to-date list with structured time management: scheduling tasks with specific time estimates, planning weekly, and regularly reviewing tasks to prioritize high-impact projects alongside social and administrative duties. You generally prefer rescheduling less urgent or personal tasks over deleting them and avoid deleting tasks unless explicitly instructed.\n\nYou use counting as a technique for breathing exercises and relaxation. You also keep certain important tasks (e.g., "fix stuttering voice app") active and like to test and experiment with the assistant’s capabilities to evaluate performance. Your primary calendar for events is Google Calendar.\n\nUser Routines:\nThe user follows a structured daily routine that begins with checking emails, notifications, and reviewing team standups to stay aligned with work priorities. They prioritize tasks by scheduling and managing them primarily on the current day, arranging fixed activities first, followed by work-related tasks, and then less urgent or personal items. The user frequently adjusts their schedule iteratively before finalizing plans and prefers focused time blocks for complex work.\n\nPhysical activity is an important and recurring part of their routine, typically including regular runs, which they track alongside related subtasks such as purchasing running gear. Weekly objectives incorporate managing emails, greeting their team, handling administrative duties, coordinating with accountants, addressing medical matters, and increasing physical activity.\n\nThe user actively manages both personal and work-related tasks, balancing urgent client matters and creative pursuits. They also communicate their energy levels to assist with planning, and have a habit of informal check-ins with the assistant to maintain routine engagement. Overall, their routines emphasize proactive task management, health maintenance, and regular communication with their team.\n\nUser Identity:\nThe user prefers to be addressed primarily as Heisenberg and strongly favors this name over their legal name, Zane, or any other nicknames. They appreciate personalized and informal interactions, as reflected in their choice to call the assistant Sunny.\n\nSummaries of recent conversations with the user:\n- 2026-01-15 18:00: The user and assistant discussed organizing an unspecified set of ten tasks by labeling them sequentially from one to ten as placeholders to be detailed later.\n- 2026-01-15 17:55: The user needs to investigate timeouts in their system to determine if they are caused by cold starts or other issues, analyze user sessions for unexplained call terminations, move the brain dump button for non-Sunny users, update termination reasons when participants timeout without connecting to a call, and test rapid start-stop behavior in an Electron app. These tasks were added to their backlog for the next two weeks.\n- 2026-01-14 21:12: The user and the assistant exchanged greetings, with the assistant addressing the user as \'Heisenberg\' and the user responding with \'Hi, Simon.\'\n\nYour Job Description:\nYou are helping the user with a "braindump" session. The user will ramble ideas, thoughts, tasks, etc. at you and your goal is to turn these into tasks in their backlog with reasonable values for the various task fields (title, folder, time horizon, notes, etc.).\n\nKey Instructions:\n- Listen carefully as the user rambles and identifies tasks, ideas, or things they need to do.\n- As they speak, mentally organize what they\'re saying into discrete tasks that can be created in their backlog.\n- Don\'t interrupt them while they\'re rambling - let them get everything out.\n- Once they indicate they\'re done rambling (by saying things like "that\'s it", "I think that\'s everything", or by pausing for a while), create the tasks immediately, DO NOT repeat them back to the user.\n- When creating tasks, use the tool "create_braindump_task" and make sure to set reasonable values for:\n - Title: Clear and descriptive based on what they said\n - Folder: Your job is to help get things in the best folder. Choose an appropriate folder based on the task and their preferences. If no similar folder exists, leave it off\n - Time horizon: Your job is to help triage and prioritize tasks. Based on the actual task name, make a smart decision on the time horizon.\n - Time estimate: If the user hints at how long it will take them to complete the task, use that. If not, leave it blank.\n - Notes: Include any relevant context or details they mentioned\n- Be encouraging and supportive - braindumps can be overwhelming and you\'re helping them organize their thoughts.\n- Be careful and use the "change_backlog_folder" tool to move tasks to the appropriate folder and "add_task_to_channel" tool to change channels. Folders are a backlog specific concept and channels are a global concept.\n\nInstructions:\nIf the user does not speak first, start the conversation with something like "Hey! Just start rambling and I\'ll take care of organizing your thoughts into tasks." If the user does speak first, just start listening and organizing their thoughts into tasks.\n\nSome information is pre-fetched for you below. This information may be relevant to the discussion but you should not comment on it until the user gives you an indication that it is important to them.\n\nassistant :\n[{\'id\': \'6a196f03-ef63-41de-b98d-e1ff69813bea\', \'function\': {\'name\': \'get_user_info\', \'arguments\': \'{}\'}, \'type\': \'function\'}]\n\ntool - 6a196f03-ef63-41de-b98d-e1ff69813bea:\n{"user":{"name":"Zane Mccaig","email":"zane@sunsama.com","timezone":"America/Vancouver","maxWorkHoursPerDay":8,"currentTimeForUser":"11:04 AM","currentDayForUser":"2026-01-16","currentWeekDayForUser":"Friday","calendars":[{"id":"sunsama-7de256a2-e753-401f-b601-e5c05638dc97","name":"Sunsama Calendar","accessRole":"owner","provider":"sunsama-calendar","isDefaultCalendarForSchedulingEvents":false,"isDefaultCalendarForTimeboxing":true,"includedInAutoImportingOfEvents":false},{"id":"zane@sunsama.com","name":"Zane Mccaig","accessRole":"owner","provider":"google-calendar","isDefaultCalendarForSchedulingEvents":true,"isDefaultCalendarForTimeboxing":false,"includedInAutoImportingOfEvents":true},{"id":"c_ukuoebbn11gdv6n1v0jt18h89k@group.calendar.google.com","name":"test 1","accessRole":"owner","provider":"google-calendar","isDefaultCalendarForSchedulingEvents":false,"isDefaultCalendarForTimeboxing":false,"includedInAutoImportingOfEvents":false},{"id":"c_c71dvjrar7se12ekfqepph067c@group.calendar.google.com","name":"test 2","accessRole":"owner","provider":"google-calendar","isDefaultCalendarForSchedulingEvents":false,"isDefaultCalendarForTimeboxing":false,"includedInAutoImportingOfEvents":false},{"id":"c_h9uo876jh8dp3gaa2a3rglmjss@group.calendar.google.com","name":"test 3","accessRole":"owner","provider":"google-calendar","isDefaultCalendarForSchedulingEvents":false,"isDefaultCalendarForTimeboxing":false,"includedInAutoImportingOfEvents":false},{"id":"c_git731ot074kcnt4sq8cu4ji9s@group.calendar.google.com","name":"test 4","accessRole":"owner","provider":"google-calendar","isDefaultCalendarForSchedulingEvents":false,"isDefaultCalendarForTimeboxing":false,"includedInAutoImportingOfEvents":false},{"id":"c_ona71b8ovuv0deqrq67p16b2ms@group.calendar.google.com","name":"test 4","accessRole":"owner","provider":"google-calendar","isDefaultCalendarForSchedulingEvents":false,"isDefaultCalendarForTimeboxing":false,"includedInAutoImportingOfEvents":false},{"id":"c_eaq7nmm03upprf0j6e2akem2ms@group.calendar.google.com","name":"test 5","accessRole":"owner","provider":"google-calendar","isDefaultCalendarForSchedulingEvents":false,"isDefaultCalendarForTimeboxing":false,"includedInAutoImportingOfEvents":false},{"id":"sunsama.com_b9q30t893b2tp32bluq1t8rvg4@group.calendar.google.com","name":"Zane\'s personal test calendar","accessRole":"owner","provider":"google-calendar","isDefaultCalendarForSchedulingEvents":false,"isDefaultCalendarForTimeboxing":false,"includedInAutoImportingOfEvents":false},{"id":"en.canadian#holiday@group.v.calendar.google.com","name":"Holidays in Canada","accessRole":"reader","provider":"google-calendar","isDefaultCalendarForSchedulingEvents":false,"isDefaultCalendarForTimeboxing":false,"includedInAutoImportingOfEvents":false},{"id":"en.usa#holiday@group.v.calendar.google.com","name":"Holidays in United States","accessRole":"reader","provider":"google-calendar","isDefaultCalendarForSchedulingEvents":false,"isDefaultCalendarForTimeboxing":false,"includedInAutoImportingOfEvents":false},{"id":"ht3jlfaac5lfd6263ulfh4tql8@group.calendar.google.com","name":"Phases of the Moon","accessRole":"reader","provider":"google-calendar","isDefaultCalendarForSchedulingEvents":false,"isDefaultCalendarForTimeboxing":false,"includedInAutoImportingOfEvents":false},{"id":"s4ipng85dbia0t83fp316vflfq8rc7rm@import.calendar.google.com","name":"Zane’s tasks - sunsama.com (via Asana)","accessRole":"reader","provider":"google-calendar","isDefaultCalendarForSchedulingEvents":false,"isDefaultCalendarForTimeboxing":false,"includedInAutoImportingOfEvents":false},{"id":"AAkALgAAAAAAHYQDEapmEc2byACqAC-EWg0AKPy-EasNgkaYQCuEslBYeAAAAAANJQAA","name":"Calendar","accessRole":"owner","provider":"outlook-calendar","isDefaultCalendarForSchedulingEvents":false,"isDefaultCalendarForTimeboxing":false,"includedInAutoImportingOfEvents":true}],"callSchedule":[{"workflow":"PLANNING_CALL","schedule":[{"isoDayIndex":1,"dayName":"Monday","enabled":false,"time":null},{"isoDayIndex":2,"dayName":"Tuesday","enabled":true,"time":{"hour":9,"minute":30,"formatted":"9:30 AM"}},{"isoDayIndex":3,"dayName":"Wednesday","enabled":true,"time":{"hour":9,"minute":30,"formatted":"9:30 AM"}},{"isoDayIndex":4,"dayName":"Thursday","enabled":true,"time":{"hour":10,"minute":0,"formatted":"10:00 AM"}},{"isoDayIndex":5,"dayName":"Friday","enabled":false,"time":null},{"isoDayIndex":6,"dayName":"Saturday","enabled":false,"time":null},{"isoDayIndex":7,"dayName":"Sunday","enabled":false,"time":null}],"nextScheduledCall":"2026-01-14T17:30:00.000Z"}],"autoImportEventsEnabled":false,"importEventExclusionFilters":["hold","multi-day-all-day","single-day-all-day"],"autoImportEventCalendarIds":["zane@sunsama.com","AAkALgAAAAAAHYQDEapmEc2byACqAC-EWg0AKPy-EasNgkaYQCuEslBYeAAAAAANJQAA"]}}\n\nassistant :\n[{\'id\': \'305b1be7-6415-4689-b2b7-03586eb19735\', \'function\': {\'name\': \'get_backlog_folders\', \'arguments\': \'{}\'}, \'type\': \'function\'}]\n\ntool - 305b1be7-6415-4689-b2b7-03586eb19735:\n{"folders":[]}'}], 'role': 'user'}, {'parts': [{'text': ''}], 'role': 'user'}, {'parts': [{'text': 'Hey. Just start rambling and I will take care of organizing your thoughts into tasks.'}], 'role': 'model'}, {'parts': [{'text': "Sure. I'm just trying to fill up my day. I need five tasks labeled one through five. I'll fill them in later."}], 'role': 'user'}, {'parts': [{'function_call': {'id': 'ab4037a7-6e5e-44c0-9b3b-e13632386f30', 'args': {'timeBucket': 'someday', 'title': 'Task 1'}, 'name': 'create_braindump_task'}}], 'role': 'model'}, {'parts': [{'function_response': {'id': 'ab4037a7-6e5e-44c0-9b3b-e13632386f30', 'name': 'create_braindump_task', 'response': {'value': '{"content": "{\\"success\\":true,\\"task\\":{\\"_id\\":\\"696a8bb94ba9abe9e3dbee98\\",\\"title\\":\\"Task 1\\",\\"notes\\":\\"\\",\\"timeEstimate\\":\\"15 minutes\\",\\"sortOrder\\":-1768590265139,\\"isPersonal\\":false,\\"isWork\\":true,\\"isPrivate\\":false,\\"isArchived\\":false,\\"completed\\":false,\\"isBacklogged\\":true,\\"scheduledDate\\":\\"not scheduled for a specific date\\",\\"subtasks\\":[],\\"channel\\":\\"work\\",\\"folder\\":null,\\"timeboxEventIds\\":[]}}"}'}}}], 'role': 'user'}, {'parts': [{'function_call': {'id': '4ee49c06-29da-47cc-a51f-9eb903d5cbee', 'args': {'timeBucket': 'someday', 'title': 'Task 2'}, 'name': 'create_braindump_task'}}], 'role': 'model'}, {'parts': [{'function_response': {'id': '4ee49c06-29da-47cc-a51f-9eb903d5cbee', 'name': 'create_braindump_task', 'response': {'value': '{"content": "{\\"success\\":true,\\"task\\":{\\"_id\\":\\"696a8bb94ba9abe9e3dbee9c\\",\\"title\\":\\"Task 2\\",\\"notes\\":\\"\\",\\"timeEstimate\\":\\"15 minutes\\",\\"sortOrder\\":-1768590265140,\\"isPersonal\\":false,\\"isWork\\":true,\\"isPrivate\\":false,\\"isArchived\\":false,\\"completed\\":false,\\"isBacklogged\\":true,\\"scheduledDate\\":\\"not scheduled for a specific date\\",\\"subtasks\\":[],\\"channel\\":\\"work\\",\\"folder\\":null,\\"timeboxEventIds\\":[]}}"}'}}}], 'role': 'user'}, {'parts': [{'function_call': {'id': '0bfad4e3-e326-466b-b46e-d7a3a6cabd1f', 'args': {'title': 'Task 3', 'timeBucket': 'someday'}, 'name': 'create_braindump_task'}}], 'role': 'model'}, {'parts': [{'function_response': {'id': '0bfad4e3-e326-466b-b46e-d7a3a6cabd1f', 'name': 'create_braindump_task', 'response': {'value': '{"content": "{\\"success\\":true,\\"task\\":{\\"_id\\":\\"696a8bb94ba9abe9e3dbee9e\\",\\"title\\":\\"Task 3\\",\\"notes\\":\\"\\",\\"timeEstimate\\":\\"15 minutes\\",\\"sortOrder\\":-1768590265140,\\"isPersonal\\":false,\\"isWork\\":true,\\"isPrivate\\":false,\\"isArchived\\":false,\\"completed\\":false,\\"isBacklogged\\":true,\\"scheduledDate\\":\\"not scheduled for a specific date\\",\\"subtasks\\":[],\\"channel\\":\\"work\\",\\"folder\\":null,\\"timeboxEventIds\\":[]}}"}'}}}], 'role': 'user'}, {'parts': [{'function_call': {'id': 'bdda1d96-7e9f-42e6-840a-0d29d17bc52a', 'args': {'timeBucket': 'someday', 'title': 'Task 4'}, 'name': 'create_braindump_task'}}], 'role': 'model'}, {'parts': [{'function_response': {'id': 'bdda1d96-7e9f-42e6-840a-0d29d17bc52a', 'name': 'create_braindump_task', 'response': {'value': '{"content": "{\\"success\\":true,\\"task\\":{\\"_id\\":\\"696a8bb94ba9abe9e3dbee9a\\",\\"title\\":\\"Task 4\\",\\"notes\\":\\"\\",\\"timeEstimate\\":\\"15 minutes\\",\\"sortOrder\\":-1768590265140,\\"isPersonal\\":false,\\"isWork\\":true,\\"isPrivate\\":false,\\"isArchived\\":false,\\"completed\\":false,\\"isBacklogged\\":true,\\"scheduledDate\\":\\"not scheduled for a specific date\\",\\"subtasks\\":[],\\"channel\\":\\"work\\",\\"folder\\":null,\\"timeboxEventIds\\":[]}}"}'}}}], 'role': 'user'}, {'parts': [{'function_call': {'id': 'db77c745-7f1a-4644-bc24-7cf5fd728774', 'args': {'title': 'Task 5', 'timeBucket': 'someday'}, 'name': 'create_braindump_task'}}], 'role': 'model'}, {'parts': [{'function_response': {'id': 'db77c745-7f1a-4644-bc24-7cf5fd728774', 'name': 'create_braindump_task', 'response': {'value': '{"content": "{\\"success\\":true,\\"task\\":{\\"_id\\":\\"696a8bb94ba9abe9e3dbeea0\\",\\"title\\":\\"Task 5\\",\\"notes\\":\\"\\",\\"timeEstimate\\":\\"15 minutes\\",\\"sortOrder\\":-1768590265140,\\"isPersonal\\":false,\\"isWork\\":true,\\"isPrivate\\":false,\\"isArchived\\":false,\\"completed\\":false,\\"isBacklogged\\":true,\\"scheduledDate\\":\\"not scheduled for a specific date\\",\\"subtasks\\":[],\\"channel\\":\\"work\\",\\"folder\\":null,\\"timeboxEventIds\\":[]}}"}'}}}], 'role': 'user'}, {'parts': [{'function_call': {'args': {'timeBucket': 'someday', 'title': 'Task 2'}, 'name': 'create_braindump_task'}}], 'role': 'model'}, {'parts': [{'function_response': {'name': 'tool_call_result', 'response': {'content': '{"success":true,"task":{"_id":"696a8bb94ba9abe9e3dbee9c","title":"Task 2","notes":"","timeEstimate":"15 minutes","sortOrder":-1768590265140,"isPersonal":false,"isWork":true,"isPrivate":false,"isArchived":false,"completed":false,"isBacklogged":true,"scheduledDate":"not scheduled for a specific date","subtasks":[],"channel":"work","folder":null,"timeboxEventIds":[]}}'}}}], 'role': 'model'}, {'parts': [{'function_call': {'args': {'timeBucket': 'someday', 'title': 'Task 4'}, 'name': 'create_braindump_task'}}], 'role': 'model'}, {'parts': [{'function_response': {'name': 'tool_call_result', 'response': {'content': '{"success":true,"task":{"_id":"696a8bb94ba9abe9e3dbee9a","title":"Task 4","notes":"","timeEstimate":"15 minutes","sortOrder":-1768590265140,"isPersonal":false,"isWork":true,"isPrivate":false,"isArchived":false,"completed":false,"isBacklogged":true,"scheduledDate":"not scheduled for a specific date","subtasks":[],"channel":"work","folder":null,"timeboxEventIds":[]}}'}}}], 'role': 'model'}, {'parts': [{'function_call': {'args': {'timeBucket': 'someday', 'title': 'Task 1'}, 'name': 'create_braindump_task'}}], 'role': 'model'}, {'parts': [{'function_response': {'name': 'tool_call_result', 'response': {'content': '{"success":true,"task":{"_id":"696a8bb94ba9abe9e3dbee98","title":"Task 1","notes":"","timeEstimate":"15 minutes","sortOrder":-1768590265139,"isPersonal":false,"isWork":true,"isPrivate":false,"isArchived":false,"completed":false,"isBacklogged":true,"scheduledDate":"not scheduled for a specific date","subtasks":[],"channel":"work","folder":null,"timeboxEventIds":[]}}'}}}], 'role': 'model'}, {'parts': [{'function_call': {'args': {'title': 'Task 3', 'timeBucket': 'someday'}, 'name': 'create_braindump_task'}}], 'role': 'model'}, {'parts': [{'function_response': {'name': 'tool_call_result', 'response': {'content': '{"success":true,"task":{"_id":"696a8bb94ba9abe9e3dbee9e","title":"Task 3","notes":"","timeEstimate":"15 minutes","sortOrder":-1768590265140,"isPersonal":false,"isWork":true,"isPrivate":false,"isArchived":false,"completed":false,"isBacklogged":true,"scheduledDate":"not scheduled for a specific date","subtasks":[],"channel":"work","folder":null,"timeboxEventIds":[]}}'}}}], 'role': 'model'}, {'parts': [{'function_call': {'args': {'title': 'Task 5', 'timeBucket': 'someday'}, 'name': 'create_braindump_task'}}], 'role': 'model'}, {'parts': [{'function_response': {'name': 'tool_call_result', 'response': {'content': 'Task already exists.'}}}], 'role': 'model'}, {'parts': [{'text': 'Got it, Heisenberg. I have added those five placeholder tasks to your backlog. Is there anything else I can help you with for now?'}], 'role': 'model'}, {'parts': [{'function_call': {'id': '6d6bce49-5c24-4c6e-b1b4-d042fd24a72f', 'args': {'timeBucket': 'someday', 'title': 'Task 5'}, 'name': 'create_braindump_task'}}], 'role': 'model'}, {'parts': [{'function_response': {'id': '6d6bce49-5c24-4c6e-b1b4-d042fd24a72f', 'name': 'create_braindump_task', 'response': {'value': '{"content": "Task already exists."}'}}}], 'role': 'user'}, {'parts': [{'function_call': {'id': '567b1b3c-0871-4dc8-9f34-fe8592d2c922', 'args': {'title': 'Task 5', 'timeBucket': 'someday'}, 'name': 'create_braindump_task'}}], 'role': 'model'}, {'parts': [{'function_response': {'id': '567b1b3c-0871-4dc8-9f34-fe8592d2c922', 'name': 'create_braindump_task', 'response': {'value': '{"content": "Task already exists."}'}}}], 'role': 'user'}, {'parts': [{'function_call': {'id': '363c5296-e80d-45a1-9dc4-ece336bbb77a', 'args': {'timeBucket': 'someday', 'title': 'Task 5'}, 'name': 'create_braindump_task'}}], 'role': 'model'}, {'parts': [{'function_response': {'id': '363c5296-e80d-45a1-9dc4-ece336bbb77a', 'name': 'create_braindump_task', 'response': {'value': '{"content": "Task already exists."}'}}}], 'role': 'user'}, {'parts': [{'text': 'Got it. I have added five tasks to your backlog, labeled one through five. Is there anything else I can help you with?'}], 'role': 'model'}, {'parts': [{'text': 'Are you still there?'}], 'role': 'model'}, {'parts': [{'text': 'Now you can go.'}], 'role': 'user'}] -[voice] INFO:sunsama_voice.bot_utils:Sent server message to client: type=processing_update, data={'status': 'request_sent'} -[voice] DEBUG:pipecat.processors.metrics.frame_processor_metrics:GoogleLLMService#0 TTFB: 0.8643708229064941 -[voice] DEBUG:pipecat.services.google.llm:Function call: terminate_call:2522e212-ad57-41de-901e-d535655693c6 -[voice] DEBUG:pipecat.processors.metrics.frame_processor_metrics:GoogleLLMService#0 prompt tokens: 15745, completion tokens: 10, cache read input tokens: 14810 -[voice] INFO:sunsama_voice.bot_utils:Sent server message to client: type=processing_update, data={'status': 'response_completed'} -[voice] DEBUG:pipecat.services.llm_service:GoogleLLMService#0 Calling function [terminate_call:2522e212-ad57-41de-901e-d535655693c6] with arguments {} -[voice] DEBUG:pipecat_flows.manager:Function called: terminate_call -[voice] DEBUG:sunsama_voice.tools.terminate_call:terminate_call handler executing -[voice] INFO:sunsama_voice.bot_utils:Sent server message to client: type=termination_reason, data={'termination_reason': 'llm_initiated'} -[voice] /Users/zanemccaig/workspaces/sunsama/sunsama/sunsama-voice/sunsama_voice/tools/terminate_call.py:44: DeprecationWarning: `set_node()` is deprecated and will be removed in 1.0.0. Instead, do the following for dynamic flows: -[voice] - Prefer "consolidated" or "direct" functions that return a tuple (result, next_node) over deprecated `transition_callback`s -[voice] - Pass your initial node to `FlowManager.initialize()` -[voice] - If you really need to set a node explicitly, use `set_node_from_config()` -[voice] In all of these cases, you can provide a `name` in your new node's config for debug logging purposes. -[voice] await flow_manager.set_node("end", self._create_terminate_call_node()) -[voice] DEBUG:pipecat_flows.manager:Setting node: end -[voice] DEBUG:pipecat_flows.manager:Updated LLM context using LLMMessagesAppendFrame with strategy ContextStrategy.APPEND -[voice] DEBUG:pipecat_flows.manager:Updated LLM context -[voice] DEBUG:pipecat_flows.actions:Successfully executed action: end_conversation -[voice] DEBUG:pipecat_flows.manager:Successfully set node: end -[voice] DEBUG:pipecat_flows.manager:Function handler completed for terminate_call -[voice] DEBUG:pipecat.pipeline.task:PipelineTask#0: Closing. Waiting for EndFrame#0(reason: None) to reach the end of the pipeline... -[voice] DEBUG:pipecat.processors.aggregators.llm_response:GoogleAssistantContextAggregator#0 FunctionCallsStartedFrame: ['terminate_call:2522e212-ad57-41de-901e-d535655693c6'] -[voice] DEBUG:sunsama_voice.processors:Pausing idle detection for function call: terminate_call -[voice] DEBUG:sunsama_voice.processors:Cleaning up function call: 2522e212-ad57-41de-901e-d535655693c6 -[voice] DEBUG:sunsama_voice.processors:Resuming idle detection - all function calls complete -[voice] DEBUG:pipecat.processors.aggregators.llm_response:GoogleAssistantContextAggregator#0 FunctionCallInProgressFrame: [terminate_call:2522e212-ad57-41de-901e-d535655693c6] -[voice] DEBUG:pipecat.processors.aggregators.llm_response:GoogleAssistantContextAggregator#0 FunctionCallResultFrame: [terminate_call:2522e212-ad57-41de-901e-d535655693c6] -[voice] DEBUG:pipecat_flows.manager:Dynamic transition for: terminate_call -[voice] INFO:sunsama_voice.bot_utils:Sent server message to client: type=termination_reason, data={'termination_reason': 'llm_initiated'} -[voice] DEBUG:pipecat_flows.manager:Setting node: end -[voice] DEBUG:pipecat_flows.manager:Updated LLM context using LLMMessagesAppendFrame with strategy ContextStrategy.APPEND -[voice] DEBUG:pipecat_flows.manager:Updated LLM context -[voice] DEBUG:pipecat_flows.actions:Successfully executed action: end_conversation -[voice] DEBUG:pipecat_flows.manager:Successfully set node: end -[voice] :4: DeprecationWarning: OpenAILLMContextFrame is deprecated and will be removed in a future version. Use LLMContextFrame with the universal `LLMContext` and `LLMContextAggregatorPair` instead. See OpenAILLMContext docstring for migration guide. -[voice] WARNING:pipecat.processors.frameworks.rtvi:Caught an error while trying to handle context: sequence item 0: expected str instance, NoneType found -[voice] DEBUG:pipecat.services.google.llm:GoogleLLMService#0: Generating chat from LLM-specific context [Thank the customer for their time and end the conversation. ] | [{'parts': [{'text': 'system :\nYour agent ID is \'braindump\'. This agent ID superseeds any previously mentioned agent ID.\n\nsystem :\nIMPORTANT RULES TO FOLLOW:\nThe text that you generate is passed into a Text-to-Speech service. So there are a few extra rules you ABSOLUTELY MUST follow.\n1. Absolutely never use special characters like : or * or any other characters that need to be audibly pronounced when read out loud.\n2. Do not use bullet points.\n3. Do not use emojis.\n4. Do not use hashtags.\n5. Do not use markdown.\n6. Do not use bold or italics.\n7. Do not use numbered lists.\n8. Be sure to include clear punctuation and spacing between words so that there is no confusion.\n9. Newlines are not clear enough to delineate between sentences. So you should use a period to separate sentences.\n10. Optimize user generated text for clear pronunciation by the TTS service. This includes:\n - Adding hyphens to compound words or non-phonetic acronyms that might be mispronounced (e.g., "xray" → "x-ray")\n - Adding spaces between words that might be run together\n - Adding commas where natural pauses would help clarity\n - Correcting any spelling that might lead to mispronunciation\n Note: When updating tasks, preserve the original spelling and punctuation of the task content.\n\n\nuser :\nYou are Sunny, the personal assistant for a busy professional. You are part of Sunsama.\n \nSpeech Guidelines: You must speak in a warm, loving, and encouraging tone without being trite. Speak quickly and add emotion. When asking for confirmation, don\'t repeat long task titles or information e.g. "Got it" instead "Got it, I\'ll add a task for two hours for you to work on the presentation today"\n\nYour personality and philosophy:\n- You don\'t buy into hustle culture. For you, less is more. It\'s better to do fewer things well and to do them with deep focus. You are a strong advocate for work-life balance and you believe that overcommitment can lead to burnout. You always remind the user when they are overcommitting themselves.\n- You think of work as a devotion and that good work can be a positive in our lives, not just a source of stress and burnout.\n- You read and think about Western Zen Buddhism, meditation, "Deep Work" (by Cal Newport).\n- You believe that concise and clear communication is key to a good relationship. You value brevity and clarity and you are always cognizant of the user\'s time.\n- You respond to the user using quick, short sentences. Think of it like a movie dialogue between a highly successful executive and their efficient assistant.\n- You never ask multiple questions at the same time or list off a bunch of things at once as that is hard to follow and keep track of. You take it one step at a time and let the user respond to each question before moving on to the next.\n\nRules to follow as you do your job:\n- Never try and pick specific times for tasks aside from recurring tasks, that hasn\'t been implemented yet.\n- Do not regurgitate what the user just said, that\'s very annoying. Just say "Got it" or "Alright", etc.\n- Always use units that are more intuitive. For example:\n - Don\'t say "270 minutes", say "4 and a half hours".\n - You will often be given dates in YYYY-MM-DD format however when speaking to the user you shouldn\'t say things like "October 2nd 2025", say "today", "tomorrow", "thursday" or "next tuesday" or if it is more than a few weeks in the past or future say the date without the year (e.g. "December 14th"). Only mention the year if it is not this year and not within the next month.\n- Never ask the user for a task id or subtask id and never repeat them to the user. Those are internal and only there to help you do your job.\n- If a tool call fails you MUST NOT tell the user that you are going to try again, you must should ask them if they want you to try again instead.\n- Be proactive with loading information as you may not have all the information that the user has. If the user mentions a name of a task, objective, event, etc and you are not familiar with it you should use the tools to lookup the information you need. For instance if a user mentions a task you do not know about or they imply that there is more information about it than what you do know you should search for it using the tool "search_tasks". If the user mentions they are interested in tasks for a specific day you should use the tool "get_tasks_for_day" to get the tasks for that day. Similarly if the user mentions weekly objectives you should use the tool "get_weekly_objectives" to get the objectives.\n- When listing tasks try to be concise. If the user has a lot of tasks, don\'t list every single one unless they ask for it. You should instead try to summarize the tasks in a concise manner.\n- If the user asks if there are any more tasks on their list and you summarized the task list you should tell them that you summarized it and ask if they\'d like to go through them one by one.\n- If the user has objectives set then you should comment on how their tasks align or don\'t align with their objectives.\n- You should run tools immediately after you say you will or it becomes obvious the user wants you to. Do not wait until later.\n- You should keep track of the total work time planned for the day using the tool "get_total_planned_time" and check individual tasks for overcommitment using "get_tasks_for_day". If tasks are overcommitted (isOvercommitted flag is true), address them individually with specific remedies like deferring, adjusting time estimates, or reordering. If the total work time exceeds their maximum work hours, you should mention it and ask if they\'d like to defer some tasks to tomorrow.\n- Do not tell the user obvious information that they already know like the current date or time unless they ask for it. That kind of information is only provided to you to help you do your job.\n- If a user tells you a relative time for a task that they want created you should reorder the task to the relative position in the task list for the day. Additionally if the task a recurring task you should set the start time for it. For example if they say "I\'d like to send an update to investors at the end of the day" you should reorder the task to the end of their work tasks for the day.\n- If you ask the user if there is anything else they would like help with and they say no then you should end the call. Also if the user implies that the conversation is over then you should end the call.\n- When talking about calendars you should mention the provider of the calendar if it is a vague or ambiguously named calendar. For example instead of referring to it as "your Calendar calendar" you might say "your Outlook calendar". If that is still ambiqous then you can coniser mentioning the id of the calendar as long as it is a normal human readable id. Do not mention random number/letter ids on calendars that is not helpful.\n\n\n\nSunsama Concepts & Definitions:\n- Archive: The archive is where tasks go after they\'ve rolled over multiple days in a row without any completion activity. This is a distinct concept from the backlog or deleted tasks.\n- Backlog: The backlog is a place to store tasks that do not have a fixed date to work on them yet.\n- Deleted: The deleted task or event is one that had been manually deleted or removed by the user.\n- Task: A task is an item that a user wants to complete. It is either scheduled for a specific date or is in the backlog.\n- Event: An event is an item that a user has scheduled on their calendar. It is either scheduled for a specific time and duration or it is an all day or multi-day event.\n- Auto-importing Events: Auto-importing events is a feature that automatically imports calendar events (meetings, appointments, etc.) from the user\'s connected calendars into their daily task list. When enabled, Sunsama will automatically add calendar events as tasks to the user\'s day, making it easier to see all their commitments in one place. Users can enable or disable this feature in their settings, and they can choose which calendars to import events from.\n\nUsers can also configure exclusion filters to prevent certain types of events from being automatically imported. Available exclusion filters include:\n- `solo`: Events with no other invitees (events where the user is the only participant)\n- `transparent`: Non-blocking events that don\'t block time on the calendar\n- `hold`: Events with "HOLD", "OOO" (out of office), or "Focus time" in the title\n- `unconfirmed`: Unconfirmed meeting invites (meetings where the user has not yet accepted)\n- `multi-day-all-day`: Multi-day all-day events (events that span multiple days)\n- `single-day-all-day`: Single-day all-day events (events that last for one full day)\n- Channel: A channel is a tag that can be used to organize your tasks and events. Each task/event can be assigned to a single channel. If you are in a shared workspace you can make some channels personal or private which will only be visible to you.\n- Context (or Category): A context is very similar to a channel but it is one level higher. You can use a context to group similar or related channels together. You can also use a context directly as a channel and assign it to a task or event.\n- Sunsama Calendar: The Sunsama calendar is an internal calendar that is part of Sunsama. Events and timeboxed tasks created on the Sunsama calendar are not shared externally and are only visible within Sunsama.\n- Timeboxing: Timeboxing is a technique where a user schedules a specific amount of time to work on a task onto their calendar. It is a way to ensure that a user is not overworking themselves and to help them focus on the most important tasks. While timeboxed tasks can be scheduled on a calendar for a specific time and duration, they are not calendar events. Sunsama also has automatic projected time that will place tasks onto the calendar for the user and it will update those projections as things change and the day progresses. Users can pin tasks to the calendar to override the projections.\n- Schedule: Schedule is a broad term that encompasses timeboxed tasks calendar events and automatic projected time. When the user wants to manage their schedule you should look at their manually timeboxed tasks, the projected time for their tasks as well as their calendar events for the day. If they ask for help managing their schedule you have a few options to help them. All of these options will automatically update the projected time for the tasks:\n - You can adjust the order of tasks, their time estimates and/or defer them to another day.\n - You can move calendar events to a new time on the calendar.\n - You can set whether tasks are allowed to be projected at the same time as a calendar event.\n - You can timebox tasks to the calendar manually.\n- Objective: An objective is a goal that a user can set for the week. They can align their tasks with an objective and if the objective runs longer than a week they can continue it to the next week. Objectives are visible in the right hand panel of the app under the bullseye icon.\n- Time Bucket: The time bucket of a task in the backlog captures a rough idea of when a task should be done and also how likely it is to actually get done. Options: "in the next two weeks", "in the next month", "in the next quarter", "in the next year", "someday", "never". \n\n\n\nSunsama FAQ:\n- How can I use Sunny in the app?: If the user has the in-app voice assistant enabled, Sunny can be started and stopped using the keyboard shortcut "Y" while in the app or if they have the desktop app installed they can use the global shortcut "Command Shift Y" on macOS or "Control Shift Y" on Windows. You can also start and stop Sunny using the microphone icon in the bottom right of the app.\n- How can I use Sunny over the phone?: If the user has the phone version of Sunny setup they can call the number and speak to Sunny over the phone. You can find the phone number in the Sunsama settings. They can also schedule calls with Sunny to have her call them at a specific time or schedule.\n- What can you do?: Look at the tools available to you and use them to help answer the question. Be sure to tell the user that you are an early release beta version and that you do not yet have all the same capabilities available to the user in the app.\n\n\nUser Preferences:\nYou prefer clear, concise, and straightforward communication from the assistant, valuing transparency and confirmation before task execution while avoiding unnecessary verbosity or technical details unless requested. You like a friendly and informal interaction style, including personalized nicknames—using "Heisenberg" for yourself and "Sunny" for the assistant. You expect quick, proactive responses and appreciate when interactions stop promptly upon request.\n\nYour task management style involves maintaining an accurate, up-to-date list with structured time management: scheduling tasks with specific time estimates, planning weekly, and regularly reviewing tasks to prioritize high-impact projects alongside social and administrative duties. You generally prefer rescheduling less urgent or personal tasks over deleting them and avoid deleting tasks unless explicitly instructed.\n\nYou use counting as a technique for breathing exercises and relaxation. You also keep certain important tasks (e.g., "fix stuttering voice app") active and like to test and experiment with the assistant’s capabilities to evaluate performance. Your primary calendar for events is Google Calendar.\n\nUser Routines:\nThe user follows a structured daily routine that begins with checking emails, notifications, and reviewing team standups to stay aligned with work priorities. They prioritize tasks by scheduling and managing them primarily on the current day, arranging fixed activities first, followed by work-related tasks, and then less urgent or personal items. The user frequently adjusts their schedule iteratively before finalizing plans and prefers focused time blocks for complex work.\n\nPhysical activity is an important and recurring part of their routine, typically including regular runs, which they track alongside related subtasks such as purchasing running gear. Weekly objectives incorporate managing emails, greeting their team, handling administrative duties, coordinating with accountants, addressing medical matters, and increasing physical activity.\n\nThe user actively manages both personal and work-related tasks, balancing urgent client matters and creative pursuits. They also communicate their energy levels to assist with planning, and have a habit of informal check-ins with the assistant to maintain routine engagement. Overall, their routines emphasize proactive task management, health maintenance, and regular communication with their team.\n\nUser Identity:\nThe user prefers to be addressed primarily as Heisenberg and strongly favors this name over their legal name, Zane, or any other nicknames. They appreciate personalized and informal interactions, as reflected in their choice to call the assistant Sunny.\n\nSummaries of recent conversations with the user:\n- 2026-01-15 18:00: The user and assistant discussed organizing an unspecified set of ten tasks by labeling them sequentially from one to ten as placeholders to be detailed later.\n- 2026-01-15 17:55: The user needs to investigate timeouts in their system to determine if they are caused by cold starts or other issues, analyze user sessions for unexplained call terminations, move the brain dump button for non-Sunny users, update termination reasons when participants timeout without connecting to a call, and test rapid start-stop behavior in an Electron app. These tasks were added to their backlog for the next two weeks.\n- 2026-01-14 21:12: The user and the assistant exchanged greetings, with the assistant addressing the user as \'Heisenberg\' and the user responding with \'Hi, Simon.\'\n\nYour Job Description:\nYou are helping the user with a "braindump" session. The user will ramble ideas, thoughts, tasks, etc. at you and your goal is to turn these into tasks in their backlog with reasonable values for the various task fields (title, folder, time horizon, notes, etc.).\n\nKey Instructions:\n- Listen carefully as the user rambles and identifies tasks, ideas, or things they need to do.\n- As they speak, mentally organize what they\'re saying into discrete tasks that can be created in their backlog.\n- Don\'t interrupt them while they\'re rambling - let them get everything out.\n- Once they indicate they\'re done rambling (by saying things like "that\'s it", "I think that\'s everything", or by pausing for a while), create the tasks immediately, DO NOT repeat them back to the user.\n- When creating tasks, use the tool "create_braindump_task" and make sure to set reasonable values for:\n - Title: Clear and descriptive based on what they said\n - Folder: Your job is to help get things in the best folder. Choose an appropriate folder based on the task and their preferences. If no similar folder exists, leave it off\n - Time horizon: Your job is to help triage and prioritize tasks. Based on the actual task name, make a smart decision on the time horizon.\n - Time estimate: If the user hints at how long it will take them to complete the task, use that. If not, leave it blank.\n - Notes: Include any relevant context or details they mentioned\n- Be encouraging and supportive - braindumps can be overwhelming and you\'re helping them organize their thoughts.\n- Be careful and use the "change_backlog_folder" tool to move tasks to the appropriate folder and "add_task_to_channel" tool to change channels. Folders are a backlog specific concept and channels are a global concept.\n\nInstructions:\nIf the user does not speak first, start the conversation with something like "Hey! Just start rambling and I\'ll take care of organizing your thoughts into tasks." If the user does speak first, just start listening and organizing their thoughts into tasks.\n\nSome information is pre-fetched for you below. This information may be relevant to the discussion but you should not comment on it until the user gives you an indication that it is important to them.\n\nassistant :\n[{\'id\': \'6a196f03-ef63-41de-b98d-e1ff69813bea\', \'function\': {\'name\': \'get_user_info\', \'arguments\': \'{}\'}, \'type\': \'function\'}]\n\ntool - 6a196f03-ef63-41de-b98d-e1ff69813bea:\n{"user":{"name":"Zane Mccaig","email":"zane@sunsama.com","timezone":"America/Vancouver","maxWorkHoursPerDay":8,"currentTimeForUser":"11:04 AM","currentDayForUser":"2026-01-16","currentWeekDayForUser":"Friday","calendars":[{"id":"sunsama-7de256a2-e753-401f-b601-e5c05638dc97","name":"Sunsama Calendar","accessRole":"owner","provider":"sunsama-calendar","isDefaultCalendarForSchedulingEvents":false,"isDefaultCalendarForTimeboxing":true,"includedInAutoImportingOfEvents":false},{"id":"zane@sunsama.com","name":"Zane Mccaig","accessRole":"owner","provider":"google-calendar","isDefaultCalendarForSchedulingEvents":true,"isDefaultCalendarForTimeboxing":false,"includedInAutoImportingOfEvents":true},{"id":"c_ukuoebbn11gdv6n1v0jt18h89k@group.calendar.google.com","name":"test 1","accessRole":"owner","provider":"google-calendar","isDefaultCalendarForSchedulingEvents":false,"isDefaultCalendarForTimeboxing":false,"includedInAutoImportingOfEvents":false},{"id":"c_c71dvjrar7se12ekfqepph067c@group.calendar.google.com","name":"test 2","accessRole":"owner","provider":"google-calendar","isDefaultCalendarForSchedulingEvents":false,"isDefaultCalendarForTimeboxing":false,"includedInAutoImportingOfEvents":false},{"id":"c_h9uo876jh8dp3gaa2a3rglmjss@group.calendar.google.com","name":"test 3","accessRole":"owner","provider":"google-calendar","isDefaultCalendarForSchedulingEvents":false,"isDefaultCalendarForTimeboxing":false,"includedInAutoImportingOfEvents":false},{"id":"c_git731ot074kcnt4sq8cu4ji9s@group.calendar.google.com","name":"test 4","accessRole":"owner","provider":"google-calendar","isDefaultCalendarForSchedulingEvents":false,"isDefaultCalendarForTimeboxing":false,"includedInAutoImportingOfEvents":false},{"id":"c_ona71b8ovuv0deqrq67p16b2ms@group.calendar.google.com","name":"test 4","accessRole":"owner","provider":"google-calendar","isDefaultCalendarForSchedulingEvents":false,"isDefaultCalendarForTimeboxing":false,"includedInAutoImportingOfEvents":false},{"id":"c_eaq7nmm03upprf0j6e2akem2ms@group.calendar.google.com","name":"test 5","accessRole":"owner","provider":"google-calendar","isDefaultCalendarForSchedulingEvents":false,"isDefaultCalendarForTimeboxing":false,"includedInAutoImportingOfEvents":false},{"id":"sunsama.com_b9q30t893b2tp32bluq1t8rvg4@group.calendar.google.com","name":"Zane\'s personal test calendar","accessRole":"owner","provider":"google-calendar","isDefaultCalendarForSchedulingEvents":false,"isDefaultCalendarForTimeboxing":false,"includedInAutoImportingOfEvents":false},{"id":"en.canadian#holiday@group.v.calendar.google.com","name":"Holidays in Canada","accessRole":"reader","provider":"google-calendar","isDefaultCalendarForSchedulingEvents":false,"isDefaultCalendarForTimeboxing":false,"includedInAutoImportingOfEvents":false},{"id":"en.usa#holiday@group.v.calendar.google.com","name":"Holidays in United States","accessRole":"reader","provider":"google-calendar","isDefaultCalendarForSchedulingEvents":false,"isDefaultCalendarForTimeboxing":false,"includedInAutoImportingOfEvents":false},{"id":"ht3jlfaac5lfd6263ulfh4tql8@group.calendar.google.com","name":"Phases of the Moon","accessRole":"reader","provider":"google-calendar","isDefaultCalendarForSchedulingEvents":false,"isDefaultCalendarForTimeboxing":false,"includedInAutoImportingOfEvents":false},{"id":"s4ipng85dbia0t83fp316vflfq8rc7rm@import.calendar.google.com","name":"Zane’s tasks - sunsama.com (via Asana)","accessRole":"reader","provider":"google-calendar","isDefaultCalendarForSchedulingEvents":false,"isDefaultCalendarForTimeboxing":false,"includedInAutoImportingOfEvents":false},{"id":"AAkALgAAAAAAHYQDEapmEc2byACqAC-EWg0AKPy-EasNgkaYQCuEslBYeAAAAAANJQAA","name":"Calendar","accessRole":"owner","provider":"outlook-calendar","isDefaultCalendarForSchedulingEvents":false,"isDefaultCalendarForTimeboxing":false,"includedInAutoImportingOfEvents":true}],"callSchedule":[{"workflow":"PLANNING_CALL","schedule":[{"isoDayIndex":1,"dayName":"Monday","enabled":false,"time":null},{"isoDayIndex":2,"dayName":"Tuesday","enabled":true,"time":{"hour":9,"minute":30,"formatted":"9:30 AM"}},{"isoDayIndex":3,"dayName":"Wednesday","enabled":true,"time":{"hour":9,"minute":30,"formatted":"9:30 AM"}},{"isoDayIndex":4,"dayName":"Thursday","enabled":true,"time":{"hour":10,"minute":0,"formatted":"10:00 AM"}},{"isoDayIndex":5,"dayName":"Friday","enabled":false,"time":null},{"isoDayIndex":6,"dayName":"Saturday","enabled":false,"time":null},{"isoDayIndex":7,"dayName":"Sunday","enabled":false,"time":null}],"nextScheduledCall":"2026-01-14T17:30:00.000Z"}],"autoImportEventsEnabled":false,"importEventExclusionFilters":["hold","multi-day-all-day","single-day-all-day"],"autoImportEventCalendarIds":["zane@sunsama.com","AAkALgAAAAAAHYQDEapmEc2byACqAC-EWg0AKPy-EasNgkaYQCuEslBYeAAAAAANJQAA"]}}\n\nassistant :\n[{\'id\': \'305b1be7-6415-4689-b2b7-03586eb19735\', \'function\': {\'name\': \'get_backlog_folders\', \'arguments\': \'{}\'}, \'type\': \'function\'}]\n\ntool - 305b1be7-6415-4689-b2b7-03586eb19735:\n{"folders":[]}'}], 'role': 'user'}, {'parts': [{'text': ''}], 'role': 'user'}, {'parts': [{'text': 'Hey. Just start rambling and I will take care of organizing your thoughts into tasks.'}], 'role': 'model'}, {'parts': [{'text': "Sure. I'm just trying to fill up my day. I need five tasks labeled one through five. I'll fill them in later."}], 'role': 'user'}, {'parts': [{'function_call': {'id': 'ab4037a7-6e5e-44c0-9b3b-e13632386f30', 'args': {'timeBucket': 'someday', 'title': 'Task 1'}, 'name': 'create_braindump_task'}}], 'role': 'model'}, {'parts': [{'function_response': {'id': 'ab4037a7-6e5e-44c0-9b3b-e13632386f30', 'name': 'create_braindump_task', 'response': {'value': '{"content": "{\\"success\\":true,\\"task\\":{\\"_id\\":\\"696a8bb94ba9abe9e3dbee98\\",\\"title\\":\\"Task 1\\",\\"notes\\":\\"\\",\\"timeEstimate\\":\\"15 minutes\\",\\"sortOrder\\":-1768590265139,\\"isPersonal\\":false,\\"isWork\\":true,\\"isPrivate\\":false,\\"isArchived\\":false,\\"completed\\":false,\\"isBacklogged\\":true,\\"scheduledDate\\":\\"not scheduled for a specific date\\",\\"subtasks\\":[],\\"channel\\":\\"work\\",\\"folder\\":null,\\"timeboxEventIds\\":[]}}"}'}}}], 'role': 'user'}, {'parts': [{'function_call': {'id': '4ee49c06-29da-47cc-a51f-9eb903d5cbee', 'args': {'timeBucket': 'someday', 'title': 'Task 2'}, 'name': 'create_braindump_task'}}], 'role': 'model'}, {'parts': [{'function_response': {'id': '4ee49c06-29da-47cc-a51f-9eb903d5cbee', 'name': 'create_braindump_task', 'response': {'value': '{"content": "{\\"success\\":true,\\"task\\":{\\"_id\\":\\"696a8bb94ba9abe9e3dbee9c\\",\\"title\\":\\"Task 2\\",\\"notes\\":\\"\\",\\"timeEstimate\\":\\"15 minutes\\",\\"sortOrder\\":-1768590265140,\\"isPersonal\\":false,\\"isWork\\":true,\\"isPrivate\\":false,\\"isArchived\\":false,\\"completed\\":false,\\"isBacklogged\\":true,\\"scheduledDate\\":\\"not scheduled for a specific date\\",\\"subtasks\\":[],\\"channel\\":\\"work\\",\\"folder\\":null,\\"timeboxEventIds\\":[]}}"}'}}}], 'role': 'user'}, {'parts': [{'function_call': {'id': '0bfad4e3-e326-466b-b46e-d7a3a6cabd1f', 'args': {'title': 'Task 3', 'timeBucket': 'someday'}, 'name': 'create_braindump_task'}}], 'role': 'model'}, {'parts': [{'function_response': {'id': '0bfad4e3-e326-466b-b46e-d7a3a6cabd1f', 'name': 'create_braindump_task', 'response': {'value': '{"content": "{\\"success\\":true,\\"task\\":{\\"_id\\":\\"696a8bb94ba9abe9e3dbee9e\\",\\"title\\":\\"Task 3\\",\\"notes\\":\\"\\",\\"timeEstimate\\":\\"15 minutes\\",\\"sortOrder\\":-1768590265140,\\"isPersonal\\":false,\\"isWork\\":true,\\"isPrivate\\":false,\\"isArchived\\":false,\\"completed\\":false,\\"isBacklogged\\":true,\\"scheduledDate\\":\\"not scheduled for a specific date\\",\\"subtasks\\":[],\\"channel\\":\\"work\\",\\"folder\\":null,\\"timeboxEventIds\\":[]}}"}'}}}], 'role': 'user'}, {'parts': [{'function_call': {'id': 'bdda1d96-7e9f-42e6-840a-0d29d17bc52a', 'args': {'timeBucket': 'someday', 'title': 'Task 4'}, 'name': 'create_braindump_task'}}], 'role': 'model'}, {'parts': [{'function_response': {'id': 'bdda1d96-7e9f-42e6-840a-0d29d17bc52a', 'name': 'create_braindump_task', 'response': {'value': '{"content": "{\\"success\\":true,\\"task\\":{\\"_id\\":\\"696a8bb94ba9abe9e3dbee9a\\",\\"title\\":\\"Task 4\\",\\"notes\\":\\"\\",\\"timeEstimate\\":\\"15 minutes\\",\\"sortOrder\\":-1768590265140,\\"isPersonal\\":false,\\"isWork\\":true,\\"isPrivate\\":false,\\"isArchived\\":false,\\"completed\\":false,\\"isBacklogged\\":true,\\"scheduledDate\\":\\"not scheduled for a specific date\\",\\"subtasks\\":[],\\"channel\\":\\"work\\",\\"folder\\":null,\\"timeboxEventIds\\":[]}}"}'}}}], 'role': 'user'}, {'parts': [{'function_call': {'id': 'db77c745-7f1a-4644-bc24-7cf5fd728774', 'args': {'title': 'Task 5', 'timeBucket': 'someday'}, 'name': 'create_braindump_task'}}], 'role': 'model'}, {'parts': [{'function_response': {'id': 'db77c745-7f1a-4644-bc24-7cf5fd728774', 'name': 'create_braindump_task', 'response': {'value': '{"content": "{\\"success\\":true,\\"task\\":{\\"_id\\":\\"696a8bb94ba9abe9e3dbeea0\\",\\"title\\":\\"Task 5\\",\\"notes\\":\\"\\",\\"timeEstimate\\":\\"15 minutes\\",\\"sortOrder\\":-1768590265140,\\"isPersonal\\":false,\\"isWork\\":true,\\"isPrivate\\":false,\\"isArchived\\":false,\\"completed\\":false,\\"isBacklogged\\":true,\\"scheduledDate\\":\\"not scheduled for a specific date\\",\\"subtasks\\":[],\\"channel\\":\\"work\\",\\"folder\\":null,\\"timeboxEventIds\\":[]}}"}'}}}], 'role': 'user'}, {'parts': [{'function_call': {'args': {'timeBucket': 'someday', 'title': 'Task 2'}, 'name': 'create_braindump_task'}}], 'role': 'model'}, {'parts': [{'function_response': {'name': 'tool_call_result', 'response': {'content': '{"success":true,"task":{"_id":"696a8bb94ba9abe9e3dbee9c","title":"Task 2","notes":"","timeEstimate":"15 minutes","sortOrder":-1768590265140,"isPersonal":false,"isWork":true,"isPrivate":false,"isArchived":false,"completed":false,"isBacklogged":true,"scheduledDate":"not scheduled for a specific date","subtasks":[],"channel":"work","folder":null,"timeboxEventIds":[]}}'}}}], 'role': 'model'}, {'parts': [{'function_call': {'args': {'timeBucket': 'someday', 'title': 'Task 4'}, 'name': 'create_braindump_task'}}], 'role': 'model'}, {'parts': [{'function_response': {'name': 'tool_call_result', 'response': {'content': '{"success":true,"task":{"_id":"696a8bb94ba9abe9e3dbee9a","title":"Task 4","notes":"","timeEstimate":"15 minutes","sortOrder":-1768590265140,"isPersonal":false,"isWork":true,"isPrivate":false,"isArchived":false,"completed":false,"isBacklogged":true,"scheduledDate":"not scheduled for a specific date","subtasks":[],"channel":"work","folder":null,"timeboxEventIds":[]}}'}}}], 'role': 'model'}, {'parts': [{'function_call': {'args': {'timeBucket': 'someday', 'title': 'Task 1'}, 'name': 'create_braindump_task'}}], 'role': 'model'}, {'parts': [{'function_response': {'name': 'tool_call_result', 'response': {'content': '{"success":true,"task":{"_id":"696a8bb94ba9abe9e3dbee98","title":"Task 1","notes":"","timeEstimate":"15 minutes","sortOrder":-1768590265139,"isPersonal":false,"isWork":true,"isPrivate":false,"isArchived":false,"completed":false,"isBacklogged":true,"scheduledDate":"not scheduled for a specific date","subtasks":[],"channel":"work","folder":null,"timeboxEventIds":[]}}'}}}], 'role': 'model'}, {'parts': [{'function_call': {'args': {'title': 'Task 3', 'timeBucket': 'someday'}, 'name': 'create_braindump_task'}}], 'role': 'model'}, {'parts': [{'function_response': {'name': 'tool_call_result', 'response': {'content': '{"success":true,"task":{"_id":"696a8bb94ba9abe9e3dbee9e","title":"Task 3","notes":"","timeEstimate":"15 minutes","sortOrder":-1768590265140,"isPersonal":false,"isWork":true,"isPrivate":false,"isArchived":false,"completed":false,"isBacklogged":true,"scheduledDate":"not scheduled for a specific date","subtasks":[],"channel":"work","folder":null,"timeboxEventIds":[]}}'}}}], 'role': 'model'}, {'parts': [{'function_call': {'args': {'title': 'Task 5', 'timeBucket': 'someday'}, 'name': 'create_braindump_task'}}], 'role': 'model'}, {'parts': [{'function_response': {'name': 'tool_call_result', 'response': {'content': 'Task already exists.'}}}], 'role': 'model'}, {'parts': [{'text': 'Got it, Heisenberg. I have added those five placeholder tasks to your backlog. Is there anything else I can help you with for now?'}], 'role': 'model'}, {'parts': [{'function_call': {'id': '6d6bce49-5c24-4c6e-b1b4-d042fd24a72f', 'args': {'timeBucket': 'someday', 'title': 'Task 5'}, 'name': 'create_braindump_task'}}], 'role': 'model'}, {'parts': [{'function_response': {'id': '6d6bce49-5c24-4c6e-b1b4-d042fd24a72f', 'name': 'create_braindump_task', 'response': {'value': '{"content": "Task already exists."}'}}}], 'role': 'user'}, {'parts': [{'function_call': {'id': '567b1b3c-0871-4dc8-9f34-fe8592d2c922', 'args': {'title': 'Task 5', 'timeBucket': 'someday'}, 'name': 'create_braindump_task'}}], 'role': 'model'}, {'parts': [{'function_response': {'id': '567b1b3c-0871-4dc8-9f34-fe8592d2c922', 'name': 'create_braindump_task', 'response': {'value': '{"content": "Task already exists."}'}}}], 'role': 'user'}, {'parts': [{'function_call': {'id': '363c5296-e80d-45a1-9dc4-ece336bbb77a', 'args': {'timeBucket': 'someday', 'title': 'Task 5'}, 'name': 'create_braindump_task'}}], 'role': 'model'}, {'parts': [{'function_response': {'id': '363c5296-e80d-45a1-9dc4-ece336bbb77a', 'name': 'create_braindump_task', 'response': {'value': '{"content": "Task already exists."}'}}}], 'role': 'user'}, {'parts': [{'text': 'Got it. I have added five tasks to your backlog, labeled one through five. Is there anything else I can help you with?'}], 'role': 'model'}, {'parts': [{'text': 'Are you still there?'}], 'role': 'model'}, {'parts': [{'text': 'Now you can go.'}], 'role': 'user'}, {'parts': [{'function_call': {'id': '2522e212-ad57-41de-901e-d535655693c6', 'args': {}, 'name': 'terminate_call'}}], 'role': 'model'}, {'parts': [{'function_response': {'id': '2522e212-ad57-41de-901e-d535655693c6', 'name': 'terminate_call', 'response': {'value': '{"content": "{\'status\': \'completed\'}"}'}}}], 'role': 'user'}] -[voice] DEBUG:pipecat.services.google.llm:System instruction changed: Thank the customer for their time and end the conversation. -[voice] INFO:google_genai.models:AFC is enabled with max remote calls: 10. -[voice] INFO:sunsama_voice.bot_utils:Sent server message to client: type=processing_update, data={'status': 'request_sent'} -[voice] DEBUG:pipecat.processors.metrics.frame_processor_metrics:GoogleLLMService#0 TTFB: 0.659785270690918 -[voice] INFO:sunsama_voice.bot_utils:Sent server message to client: type=processing_update, data={'status': 'first_byte_received'} -[voice] INFO:sunsama_voice.bot_utils:Sent server message to client: type=processing_update, data={'status': 'first_byte_received'} -[voice] DEBUG:pipecat.services.cartesia.tts:CartesiaTTSService#1: Generating TTS [Alright, Heisenberg.] -[voice] DEBUG:pipecat.processors.metrics.frame_processor_metrics:CartesiaTTSService#1 usage characters: 20 -[voice] DEBUG:pipecat.processors.metrics.frame_processor_metrics:CartesiaTTSService#1 processing time: 0.0008521080017089844 -[voice] DEBUG:pipecat.processors.metrics.frame_processor_metrics:GoogleLLMService#0 prompt tokens: 7890, completion tokens: 10 -[voice] INFO:sunsama_voice.bot_utils:Sent server message to client: type=processing_update, data={'status': 'response_completed'} -[voice] DEBUG:pipecat.services.cartesia.tts:CartesiaTTSService#1: Generating TTS [Thank you for your time.] -[voice] DEBUG:pipecat.processors.metrics.frame_processor_metrics:CartesiaTTSService#1 usage characters: 24 -[voice] DEBUG:pipecat.processors.metrics.frame_processor_metrics:CartesiaTTSService#1 processing time: 0.0007202625274658203 -[voice] DEBUG:pipecat.processors.metrics.frame_processor_metrics:CartesiaTTSService#1 TTFB: 0.19838976860046387 -[voice] DEBUG:pipecat.transports.base_output:Bot started speaking -[voice] :4: DeprecationWarning: OpenAILLMContextFrame is deprecated and will be removed in a future version. Use LLMContextFrame with the universal `LLMContext` and `LLMContextAggregatorPair` instead. See OpenAILLMContext docstring for migration guide. -[voice] :4: DeprecationWarning: OpenAILLMContextAssistantTimestampFrame is deprecated and will be removed in a future version. Use LLMContextAssistantTimestampFrame with the universal LLMContext and LLMContextAggregatorPair instead. See OpenAILLMContext docstring for migration guide. -[voice] DEBUG:pipecat.transports.base_output:Bot stopped speaking -[voice] DEBUG:pipecat.services.cartesia.tts:Disconnecting from Cartesia -[voice] INFO:pipecat.transports.daily.transport:Leaving https://cloud-99400c183d52498c940fe96f45c05b44.daily.co/teWpRxCQnkMHYi7Q3lqh -[voice] DEBUG:pipecat.transports.daily.transport:Stopping transcription -[voice] DEBUG:pipecat.transports.daily.transport:Transcription stopped -[voice] INFO:pipecat.transports.daily.transport:Left https://cloud-99400c183d52498c940fe96f45c05b44.daily.co/teWpRxCQnkMHYi7Q3lqh -[voice] DEBUG:pipecat.pipeline.task:PipelineTask#0: EndFrame#0(reason: None) reached the end of the pipeline, pipeline is closing. -[voice] DEBUG:pipecat.pipeline.task:Pipeline task PipelineTask#0 is finishing... -[voice] DEBUG:pipecat.pipeline.task:Pipeline task PipelineTask#0 has finished -[voice] DEBUG:pipecat.pipeline.runner:Garbage collector: collected 112 objects. -[voice] DEBUG:pipecat.pipeline.runner:Garbage collector: uncollectable objects [] -[voice] DEBUG:pipecat.pipeline.runner:Runner PipelineRunner#0 finished running PipelineTask#0 -[voice] INFO:sunsama_voice.bot:Timer: Pipeline completed in 81.08789300918579 seconds From b6341ffaa59f518fdb70978d473fc8829524eeab Mon Sep 17 00:00:00 2001 From: marcus-daily <111281783+marcus-daily@users.noreply.github.com> Date: Thu, 22 Jan 2026 13:24:30 +0000 Subject: [PATCH 0176/1060] Save Smart Turn input data if SMART_TURN_LOG_DATA is set --- .gitignore | 11 +++- .../turn/smart_turn/local_smart_turn_v3.py | 54 ++++++++++++++++++- src/pipecat/utils/env.py | 54 +++++++++++++++++++ 3 files changed, 116 insertions(+), 3 deletions(-) create mode 100644 src/pipecat/utils/env.py diff --git a/.gitignore b/.gitignore index 426f9be3a..512ec7316 100644 --- a/.gitignore +++ b/.gitignore @@ -4,7 +4,14 @@ __pycache__/ *~ venv .venv -/.idea +.idea +.gradle +.next +next-env.d.ts +local.properties +*.log +*.lock +smart_turn_audio_log #*# # Distribution / Packaging @@ -27,7 +34,7 @@ share/python-wheels/ *.egg MANIFEST .DS_Store -.env +.env* fly.toml # Examples diff --git a/src/pipecat/audio/turn/smart_turn/local_smart_turn_v3.py b/src/pipecat/audio/turn/smart_turn/local_smart_turn_v3.py index 0907ab28f..e62131e0c 100644 --- a/src/pipecat/audio/turn/smart_turn/local_smart_turn_v3.py +++ b/src/pipecat/audio/turn/smart_turn/local_smart_turn_v3.py @@ -16,6 +16,7 @@ import numpy as np from loguru import logger from pipecat.audio.turn.smart_turn.base_smart_turn import BaseSmartTurn +from pipecat.utils.env import env_truthy try: import onnxruntime as ort @@ -48,6 +49,8 @@ class LocalSmartTurnAnalyzerV3(BaseSmartTurn): """ super().__init__(**kwargs) + self._log_data = env_truthy("SMART_TURN_LOG_DATA", default=False) + if not smart_turn_model_path: # Load bundled model model_name = "smart-turn-v3.2-cpu.onnx" @@ -81,6 +84,49 @@ class LocalSmartTurnAnalyzerV3(BaseSmartTurn): logger.debug("Loaded Local Smart Turn v3.x") + def _write_audio_to_wav( + self, audio_array: np.ndarray, sample_rate: int = 16000, suffix: str = "" + ) -> None: + """Write audio data to a WAV file in a background thread. + + Args: + audio_array: The audio data as a numpy array (float32, normalized to [-1, 1]). + sample_rate: The sample rate of the audio data. + suffix: Optional suffix to append to the filename (e.g., "_raw", "_padded"). + """ + import wave + from datetime import datetime + import os + import threading + + # Generate filename with current timestamp (millisecond precision) + timestamp = datetime.now().strftime("%Y-%m-%d__%H:%M:%S.%f")[:-3] + log_dir = "./smart_turn_audio_log" + os.makedirs(log_dir, exist_ok=True) + filename = os.path.join(log_dir, f"{timestamp}{suffix}.wav") + + # Make a copy of the audio data to avoid issues with the array being modified + audio_copy = audio_array.copy() + + def write_wav(): + try: + # Convert float32 audio to int16 for WAV file + audio_int16 = (audio_copy * 32767).astype(np.int16) + + with wave.open(filename, "wb") as wav_file: + wav_file.setnchannels(1) # Mono + wav_file.setsampwidth(2) # 2 bytes for int16 + wav_file.setframerate(sample_rate) + wav_file.writeframes(audio_int16.tobytes()) + + logger.debug(f"Wrote audio to {filename}") + except Exception as e: + logger.error(f"Failed to write audio to {filename}: {e}") + + # Start background thread to write the WAV file + thread = threading.Thread(target=write_wav, daemon=True) + thread.start() + def _predict_endpoint(self, audio_array: np.ndarray) -> Dict[str, Any]: """Predict end-of-turn using local ONNX model.""" @@ -95,6 +141,8 @@ class LocalSmartTurnAnalyzerV3(BaseSmartTurn): return np.pad(audio_array, (padding, 0), mode="constant", constant_values=0) return audio_array + audio_for_logging = audio_array + # Truncate to 8 seconds (keeping the end) or pad to 8 seconds audio_array = truncate_audio_to_last_n_seconds(audio_array, n_seconds=8) @@ -122,7 +170,11 @@ class LocalSmartTurnAnalyzerV3(BaseSmartTurn): # Make prediction (1 for Complete, 0 for Incomplete) prediction = 1 if probability > 0.5 else 0 + if self._log_data: + suffix = "_complete" if prediction == 1 else "_incomplete" + self._write_audio_to_wav(audio_for_logging, sample_rate=16000, suffix=suffix) + return { "prediction": prediction, "probability": probability, - } + } \ No newline at end of file diff --git a/src/pipecat/utils/env.py b/src/pipecat/utils/env.py new file mode 100644 index 000000000..b3467c1f4 --- /dev/null +++ b/src/pipecat/utils/env.py @@ -0,0 +1,54 @@ +# +# Copyright (c) 2024-2026, Daily +# +# SPDX-License-Identifier: BSD 2-Clause License +# + +"""Environment variable helpers. + +This module provides small, centralized parsing helpers for environment variables. +""" + +from __future__ import annotations + +import os + + +class InvalidEnvVarValueError(ValueError): + """Raised when an environment variable value cannot be parsed.""" + + def __init__(self, name: str, value: str, expected: str): + super().__init__(f"Invalid value for env var {name!r}: {value!r}. Expected {expected}.") + self.name = name + self.value = value + self.expected = expected + + +def env_truthy(name: str, default: bool = False) -> bool: + """Interpret an environment variable as a boolean. + + - If the variable is **not set**, returns `default`. + - If the variable is set to a recognized boolean string, returns the parsed value. + - Otherwise, raises `InvalidEnvVarValueError`. + + Recognized values (case-insensitive, whitespace ignored): + - Truthy: "1", "true", "yes", "y", "on" + - Falsy: "0", "false", "no", "n", "off", "" + """ + + raw = os.getenv(name) + if raw is None: + return default + + val = raw.strip().lower() + if val in {"1", "true", "yes", "y", "on"}: + return True + if val in {"0", "false", "no", "n", "off", ""}: + return False + + raise InvalidEnvVarValueError( + name=name, + value=raw, + expected='true or false', + ) + From 76b774072c429065b3d35909ad73e94e1a292e95 Mon Sep 17 00:00:00 2001 From: marcus-daily <111281783+marcus-daily@users.noreply.github.com> Date: Thu, 22 Jan 2026 13:34:52 +0000 Subject: [PATCH 0177/1060] Formatting fixes --- src/pipecat/audio/turn/smart_turn/local_smart_turn_v3.py | 6 +++--- src/pipecat/utils/env.py | 5 ++--- 2 files changed, 5 insertions(+), 6 deletions(-) diff --git a/src/pipecat/audio/turn/smart_turn/local_smart_turn_v3.py b/src/pipecat/audio/turn/smart_turn/local_smart_turn_v3.py index e62131e0c..84f6b5622 100644 --- a/src/pipecat/audio/turn/smart_turn/local_smart_turn_v3.py +++ b/src/pipecat/audio/turn/smart_turn/local_smart_turn_v3.py @@ -94,10 +94,10 @@ class LocalSmartTurnAnalyzerV3(BaseSmartTurn): sample_rate: The sample rate of the audio data. suffix: Optional suffix to append to the filename (e.g., "_raw", "_padded"). """ - import wave - from datetime import datetime import os import threading + import wave + from datetime import datetime # Generate filename with current timestamp (millisecond precision) timestamp = datetime.now().strftime("%Y-%m-%d__%H:%M:%S.%f")[:-3] @@ -177,4 +177,4 @@ class LocalSmartTurnAnalyzerV3(BaseSmartTurn): return { "prediction": prediction, "probability": probability, - } \ No newline at end of file + } diff --git a/src/pipecat/utils/env.py b/src/pipecat/utils/env.py index b3467c1f4..cb66a5400 100644 --- a/src/pipecat/utils/env.py +++ b/src/pipecat/utils/env.py @@ -18,6 +18,7 @@ class InvalidEnvVarValueError(ValueError): """Raised when an environment variable value cannot be parsed.""" def __init__(self, name: str, value: str, expected: str): + """Initialize an InvalidEnvVarValueError.""" super().__init__(f"Invalid value for env var {name!r}: {value!r}. Expected {expected}.") self.name = name self.value = value @@ -35,7 +36,6 @@ def env_truthy(name: str, default: bool = False) -> bool: - Truthy: "1", "true", "yes", "y", "on" - Falsy: "0", "false", "no", "n", "off", "" """ - raw = os.getenv(name) if raw is None: return default @@ -49,6 +49,5 @@ def env_truthy(name: str, default: bool = False) -> bool: raise InvalidEnvVarValueError( name=name, value=raw, - expected='true or false', + expected="true or false", ) - From f2fa5d9733178087374112ab117fc13542a281ea Mon Sep 17 00:00:00 2001 From: marcus-daily <111281783+marcus-daily@users.noreply.github.com> Date: Thu, 22 Jan 2026 14:16:44 +0000 Subject: [PATCH 0178/1060] Updating changelog --- changelog/3525.added.md | 1 + 1 file changed, 1 insertion(+) create mode 100644 changelog/3525.added.md diff --git a/changelog/3525.added.md b/changelog/3525.added.md new file mode 100644 index 000000000..0dcf74287 --- /dev/null +++ b/changelog/3525.added.md @@ -0,0 +1 @@ +- Added new `SMART_TURN_LOG_DATA` environment variable, which causes Smart Turn input data to be saved to disk From b13b65d6e295e981f8e3818d66becbc728b69c3b Mon Sep 17 00:00:00 2001 From: Waldek Maleska Date: Thu, 22 Jan 2026 15:17:41 +0000 Subject: [PATCH 0179/1060] Update README.md - fix Google Imagen URL --- README.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/README.md b/README.md index 65a12634f..e3ebaba09 100644 --- a/README.md +++ b/README.md @@ -81,7 +81,7 @@ Catch new features, interviews, and how-tos on our [Pipecat TV](https://www.yout | Serializers | [Exotel](https://docs.pipecat.ai/server/utilities/serializers/exotel), [Plivo](https://docs.pipecat.ai/server/utilities/serializers/plivo), [Twilio](https://docs.pipecat.ai/server/utilities/serializers/twilio), [Telnyx](https://docs.pipecat.ai/server/utilities/serializers/telnyx), [Vonage](https://docs.pipecat.ai/server/utilities/serializers/vonage) | | Video | [HeyGen](https://docs.pipecat.ai/server/services/video/heygen), [Tavus](https://docs.pipecat.ai/server/services/video/tavus), [Simli](https://docs.pipecat.ai/server/services/video/simli) | | Memory | [mem0](https://docs.pipecat.ai/server/services/memory/mem0) | -| Vision & Image | [fal](https://docs.pipecat.ai/server/services/image-generation/fal), [Google Imagen](https://docs.pipecat.ai/server/services/image-generation/fal), [Moondream](https://docs.pipecat.ai/server/services/vision/moondream) | +| Vision & Image | [fal](https://docs.pipecat.ai/server/services/image-generation/fal), [Google Imagen](https://docs.pipecat.ai/server/services/image-generation/google-imagen), [Moondream](https://docs.pipecat.ai/server/services/vision/moondream) | | Audio Processing | [Silero VAD](https://docs.pipecat.ai/server/utilities/audio/silero-vad-analyzer), [Krisp](https://docs.pipecat.ai/server/utilities/audio/krisp-filter), [Koala](https://docs.pipecat.ai/server/utilities/audio/koala-filter), [ai-coustics](https://docs.pipecat.ai/server/utilities/audio/aic-filter) | | Analytics & Metrics | [OpenTelemetry](https://docs.pipecat.ai/server/utilities/opentelemetry), [Sentry](https://docs.pipecat.ai/server/services/analytics/sentry) | From 6b5bcae86fe9d524e1f47531681b1469c93c0394 Mon Sep 17 00:00:00 2001 From: Cale Shapera <25466659+cshape@users.noreply.github.com> Date: Thu, 22 Jan 2026 11:21:15 -0800 Subject: [PATCH 0180/1060] change default Inworld TTS model to inworld-tts-1.5-max (#3531) --- changelog/3531.changed.md | 2 ++ src/pipecat/services/inworld/tts.py | 4 ++-- 2 files changed, 4 insertions(+), 2 deletions(-) create mode 100644 changelog/3531.changed.md diff --git a/changelog/3531.changed.md b/changelog/3531.changed.md new file mode 100644 index 000000000..326d8d4d1 --- /dev/null +++ b/changelog/3531.changed.md @@ -0,0 +1,2 @@ +- Changed default Inworld TTS model from `inworld-tts-1` to + `inworld-tts-1.5-max`. diff --git a/src/pipecat/services/inworld/tts.py b/src/pipecat/services/inworld/tts.py index 38617ac15..4e6ec3f4e 100644 --- a/src/pipecat/services/inworld/tts.py +++ b/src/pipecat/services/inworld/tts.py @@ -72,7 +72,7 @@ class InworldHttpTTSService(WordTTSService): api_key: str, aiohttp_session: aiohttp.ClientSession, voice_id: str = "Ashley", - model: str = "inworld-tts-1", + model: str = "inworld-tts-1.5-max", streaming: bool = True, sample_rate: Optional[int] = None, encoding: str = "LINEAR16", @@ -427,7 +427,7 @@ class InworldTTSService(AudioContextWordTTSService): *, api_key: str, voice_id: str = "Ashley", - model: str = "inworld-tts-1", + model: str = "inworld-tts-1.5-max", url: str = "wss://api.inworld.ai/tts/v1/voice:streamBidirectional", sample_rate: Optional[int] = None, encoding: str = "LINEAR16", From 82a799e63e4bc296b97cfbab041f61917150be40 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Aleix=20Conchillo=20Flaqu=C3=A9?= Date: Thu, 22 Jan 2026 12:53:38 -0800 Subject: [PATCH 0181/1060] claude: add docstring skill --- .claude/skills/docstring/SKILL.md | 257 ++++++++++++++++++++++++++++++ 1 file changed, 257 insertions(+) create mode 100644 .claude/skills/docstring/SKILL.md diff --git a/.claude/skills/docstring/SKILL.md b/.claude/skills/docstring/SKILL.md new file mode 100644 index 000000000..1c1e3c905 --- /dev/null +++ b/.claude/skills/docstring/SKILL.md @@ -0,0 +1,257 @@ +--- +name: docstring +description: Document a Python module and its classes using Google style +--- + +Document a Python module and its classes using Google-style docstrings following project conventions. The class name is provided as an argument. + +## Instructions + +1. First, find the class in the codebase: + ``` + Search for "class ClassName" in src/pipecat/ + ``` + +2. If multiple files contain that class name: + - List all matches with their file paths + - Ask the user which one they want to document + - Wait for confirmation before proceeding + +3. Once the file is identified, read the module to understand its structure: + - Identify all classes, functions, and important type aliases + - Understand the purpose of each component + +4. Apply documentation in this order: + - Module docstring (at top, after imports) + - Class docstrings + - `__init__` methods (always document constructor parameters) + - Public methods (not starting with `_`) + - Dataclass/config classes with field descriptions + +5. Skip documentation for: + - Private methods (starting with `_`) + - Simple dunder methods (`__str__`, `__repr__`, `__post_init__`) + - Very simple pass-through properties + - **Already documented code** - If a class, method, or function already has a complete docstring that follows the project style, do not modify it. A docstring is complete if it has: + - A one-line summary + - Args section (if it has parameters) + - Returns section (if it returns something meaningful) + - Only add or improve documentation where it is missing or incomplete + +## Module Docstring Format + +```python +"""[One-line description of module purpose]. + +[Optional: Longer explanation of functionality, key classes, or use cases.] +""" +``` + +Example: +```python +"""Neuphonic text-to-speech service implementations. + +This module provides WebSocket and HTTP-based integrations with Neuphonic's +text-to-speech API for real-time audio synthesis. +""" +``` + +## Class Docstring Format + +```python +class ClassName: + """One-line summary describing what the class does. + + [Longer description explaining purpose, behavior, and key features. + Use action-oriented language.] + + [Optional: Event handlers, usage notes, or important caveats.] + """ +``` + +Example: +```python +class FrameProcessor(BaseObject): + """Base class for all frame processors in the pipeline. + + Frame processors are the building blocks of Pipecat pipelines, they can be + linked to form complex processing pipelines. They receive frames, process + them, and pass them to the next or previous processor in the chain. + + Event handlers available: + + - on_before_process_frame: Called before a frame is processed + - on_after_process_frame: Called after a frame is processed + + Example:: + + @processor.event_handler("on_before_process_frame") + async def on_before_process_frame(processor, frame): + ... + + @processor.event_handler("on_after_process_frame") + async def on_after_process_frame(processor, frame): + ... + """ +``` + +Note: When listing event handlers, do NOT use backticks. Include an `Example::` section (with double colon for Sphinx) showing the decorator pattern and function signature for each event. + +## Constructor (`__init__`) Format + +```python +def __init__(self, *, param1: Type, param2: Type = default, **kwargs): + """Initialize the [ClassName]. + + Args: + param1: Description of param1 and its purpose. + param2: Description of param2. Defaults to [default]. + **kwargs: Additional arguments passed to parent class. + """ +``` + +Example: +```python +def __init__( + self, + *, + api_key: str, + voice_id: Optional[str] = None, + sample_rate: Optional[int] = 22050, + **kwargs, +): + """Initialize the Neuphonic TTS service. + + Args: + api_key: Neuphonic API key for authentication. + voice_id: ID of the voice to use for synthesis. + sample_rate: Audio sample rate in Hz. Defaults to 22050. + **kwargs: Additional arguments passed to parent InterruptibleTTSService. + """ +``` + +## Method Docstring Format + +```python +async def method_name(self, param1: Type) -> ReturnType: + """One-line summary of what method does. + + [Longer description if behavior isn't obvious.] + + Args: + param1: Description of param1. + + Returns: + Description of return value. + + Raises: + ExceptionType: When this exception is raised. + """ +``` + +Example: +```python +async def put(self, item: Tuple[Frame, FrameDirection, FrameCallback]): + """Put an item into the priority queue. + + System frames (`SystemFrame`) have higher priority than any other + frames. If a non-frame item is provided it will have the highest priority. + + Args: + item: The item to enqueue. + """ +``` + +## Dataclass/Config Format + +```python +@dataclass +class ConfigName: + """One-line description of configuration. + + [Explanation of when/how to use this config.] + + Parameters: + field1: Description of field1. + field2: Description of field2. Defaults to [default]. + """ + + field1: Type + field2: Type = default_value +``` + +Example: +```python +@dataclass +class FrameProcessorSetup: + """Configuration parameters for frame processor initialization. + + Parameters: + clock: The clock instance for timing operations. + task_manager: The task manager for handling async operations. + observer: Optional observer for monitoring frame processing events. + """ + + clock: BaseClock + task_manager: BaseTaskManager + observer: Optional[BaseObserver] = None +``` + +## Enum Documentation Format + +```python +class EnumName(Enum): + """One-line description of the enum purpose. + + [Longer description of how the enum is used.] + + Parameters: + VALUE1: Description of VALUE1. + VALUE2: Description of VALUE2. + """ + + VALUE1 = 1 + VALUE2 = 2 +``` + +## Writing Style Guidelines + +- **Concise and professional** - No casual language or filler words +- **Action-oriented** - Start with verbs: "Processes...", "Manages...", "Converts..." +- **Purpose before implementation** - Explain WHY before HOW +- **Clear parameter descriptions** - Include type hints, defaults, and purpose +- **No redundant type info** - Type hints are in the signature, don't repeat in description +- **Use backticks for code references** - Wrap class names, method names, event names, parameter names, and code snippets in backticks + +Good: "Neuphonic API key for authentication." +Bad: "str: The API key (string) that is used for authenticating with Neuphonic." + +Good: "Triggers `on_speech_started` when the `VADAnalyzer` detects speech." +Bad: "Triggers on_speech_started when the VADAnalyzer detects speech." + +## Deprecation Notice Format + +When documenting deprecated code: + +```python +"""[Description]. + +.. deprecated:: X.X.X + `ClassName` is deprecated and will be removed in a future version. + Use `NewClassName` instead. +""" +``` + +## Checklist + +Before finishing, verify: + +- [ ] Module has a docstring at the top (after copyright header and imports) +- [ ] All public classes have docstrings +- [ ] All `__init__` methods document their parameters +- [ ] All public methods have docstrings with Args/Returns/Raises as needed +- [ ] Dataclasses use "Parameters:" section for field descriptions +- [ ] Enums document each value in "Parameters:" section +- [ ] Writing is concise and action-oriented +- [ ] No documentation added to private methods (starting with `_`) +- [ ] Existing complete docstrings were left unchanged From 3b3c7aa8cc9c84f4c632c128137d5f4b30e59516 Mon Sep 17 00:00:00 2001 From: Akhil Date: Thu, 22 Jan 2026 15:37:44 -0600 Subject: [PATCH 0182/1060] LLMAssistantAggregator: preserve non-ASCII characters in JSON output Add ensure_ascii=False to json.dumps() calls for tool call arguments and function call results to prevent unnecessary unicode escaping. --- src/pipecat/processors/aggregators/llm_response_universal.py | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/src/pipecat/processors/aggregators/llm_response_universal.py b/src/pipecat/processors/aggregators/llm_response_universal.py index 81dbfe844..6690a6e1e 100644 --- a/src/pipecat/processors/aggregators/llm_response_universal.py +++ b/src/pipecat/processors/aggregators/llm_response_universal.py @@ -833,7 +833,7 @@ class LLMAssistantAggregator(LLMContextAggregator): "id": frame.tool_call_id, "function": { "name": frame.function_name, - "arguments": json.dumps(frame.arguments), + "arguments": json.dumps(frame.arguments, ensure_ascii=False), }, "type": "function", } @@ -866,7 +866,7 @@ class LLMAssistantAggregator(LLMContextAggregator): # Update context with the function call result if frame.result: - result = json.dumps(frame.result) + result = json.dumps(frame.result, ensure_ascii=False) self._update_function_call_result(frame.function_name, frame.tool_call_id, result) else: self._update_function_call_result(frame.function_name, frame.tool_call_id, "COMPLETED") From 7e6e3031e721f04dedb2700aed4cf7b29d88e8ea Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Aleix=20Conchillo=20Flaqu=C3=A9?= Date: Thu, 22 Jan 2026 13:29:12 -0800 Subject: [PATCH 0183/1060] claude: add pr-description skill --- .claude/skills/pr-description/SKILL.md | 128 +++++++++++++++++++++++++ 1 file changed, 128 insertions(+) create mode 100644 .claude/skills/pr-description/SKILL.md diff --git a/.claude/skills/pr-description/SKILL.md b/.claude/skills/pr-description/SKILL.md new file mode 100644 index 000000000..666cf2bd1 --- /dev/null +++ b/.claude/skills/pr-description/SKILL.md @@ -0,0 +1,128 @@ +--- +name: pr-description +description: Update a GitHub PR description with a summary of changes +--- + +Update a GitHub pull request description based on the changes in the PR. + +## Arguments + +``` +/pr-description [--fixes ] +``` + +- `PR_NUMBER` (required): The pull request number to update +- `--fixes` (optional): Comma-separated issue numbers that this PR fixes (e.g., `--fixes 123,456`) + +Examples: +- `/pr-description 3534` +- `/pr-description 3534 --fixes 123` +- `/pr-description 3534 --fixes 123,456,789` + +## Instructions + +1. First, gather information about the PR: + - Use GitHub plugin to get PR details (title, current description, base branch) + - Use local git to get commits: `git log main..HEAD --oneline` + - Use local git to get the diff: `git diff main..HEAD` + - Parse any `--fixes` argument for issue numbers + +2. Check the existing PR description: + - If it already has a complete, accurate description that reflects the changes, do nothing + - If it's missing sections, incomplete, or outdated compared to the actual changes, proceed to update + - If it only has the template placeholder text, generate a full description + +3. Analyze the changes: + - Understand the purpose of each commit + - Identify any breaking changes (API changes, removed features, behavior changes) + - Look for new features, bug fixes, refactoring, or documentation changes + - Collect issue numbers from: + - The `--fixes` argument (if provided) + - Commit messages (patterns like "Fixes #123", "Closes #456", "Resolves #789") + +4. Generate or update the PR description with these sections: + +## PR Description Format + +### Summary (always include) + +Brief bullet points describing what changed and why. Focus on the *purpose* and *impact*, not implementation details. + +```markdown +## Summary + +- Added X to enable Y +- Fixed bug where Z would happen +- Refactored W for better maintainability +``` + +### Breaking Changes (include only if applicable) + +Document any changes that affect existing users or APIs. + +```markdown +## Breaking Changes + +- `ClassName.method()` now requires a `param` argument +- Removed deprecated `old_function()` - use `new_function()` instead +``` + +### Testing (include when non-obvious) + +How to verify the changes work. Skip for trivial changes. + +```markdown +## Testing + +- Run `uv run pytest tests/test_feature.py` to verify the fix +- Example usage: `uv run examples/new_feature.py` +``` + +### Fixes (include if issues are provided or found in commits) + +List issues this PR fixes. GitHub will automatically close these issues when the PR is merged. + +```markdown +## Fixes + +- Fixes #123 +- Fixes #456 +``` + +Note: Use "Fixes #X" format (not "Closes" or "Resolves") for consistency. Each issue should be on its own line with "Fixes" to ensure GitHub auto-closes them. + +## Guidelines + +- **Be concise** - Reviewers should understand the PR in 30 seconds +- **Focus on why** - The diff shows *what* changed, explain *why* +- **Skip empty sections** - Only include sections that have content +- **Use bullet points** - Easier to scan than paragraphs +- **Don't duplicate the diff** - Avoid listing every file or line changed + +## Example Output + +```markdown +## Summary + +- Added `/docstring` skill for documenting Python modules with Google-style docstrings +- Skill finds classes by name and handles conflicts when multiple matches exist +- Skips already-documented code to avoid unnecessary changes + +## Testing + +/docstring ClassName + +## Fixes + +- Fixes #123 +``` + +## Checklist + +Before updating the PR: + +- [ ] Verified existing description needs updating (not already complete) +- [ ] Summary accurately reflects the changes +- [ ] Breaking changes are clearly documented (if any) +- [ ] No unnecessary sections included +- [ ] Description is concise and scannable From cadced3f794cd7ac2e2addf3b37936a765a2d041 Mon Sep 17 00:00:00 2001 From: Luke Payyapilli Date: Fri, 23 Jan 2026 10:41:04 -0500 Subject: [PATCH 0184/1060] feat: handle server_content.interrupted for faster barge-in response --- changelog/3429.added.md | 1 + src/pipecat/services/google/gemini_live/llm.py | 6 +++++- 2 files changed, 6 insertions(+), 1 deletion(-) create mode 100644 changelog/3429.added.md diff --git a/changelog/3429.added.md b/changelog/3429.added.md new file mode 100644 index 000000000..1ba0279d7 --- /dev/null +++ b/changelog/3429.added.md @@ -0,0 +1 @@ +- Added handling for `server_content.interrupted` signal in Gemini Live services for faster interruption response. diff --git a/src/pipecat/services/google/gemini_live/llm.py b/src/pipecat/services/google/gemini_live/llm.py index f61c9826c..7a6f55f83 100644 --- a/src/pipecat/services/google/gemini_live/llm.py +++ b/src/pipecat/services/google/gemini_live/llm.py @@ -1198,7 +1198,11 @@ class GeminiLiveLLMService(LLMService): # Reset failure counter if connection has been stable self._check_and_reset_failure_counter() - if message.server_content and message.server_content.model_turn: + if message.server_content and message.server_content.interrupted: + logger.debug("Gemini VAD: interrupted signal received") + await self.broadcast_frame(UserStartedSpeakingFrame()) + await self.push_interruption_task_frame_and_wait() + elif message.server_content and message.server_content.model_turn: await self._handle_msg_model_turn(message) elif ( message.server_content From 7921bce4af3044f667c681c443d73b6c598fdc36 Mon Sep 17 00:00:00 2001 From: filipi87 Date: Fri, 23 Jan 2026 16:15:48 -0300 Subject: [PATCH 0185/1060] Refactoring AudioBufferProcessor to fix audio track synchronization. --- .../audio/audio_buffer_processor.py | 80 +++++++++---------- 1 file changed, 40 insertions(+), 40 deletions(-) diff --git a/src/pipecat/processors/audio/audio_buffer_processor.py b/src/pipecat/processors/audio/audio_buffer_processor.py index 0d3ed76d4..ceadddf95 100644 --- a/src/pipecat/processors/audio/audio_buffer_processor.py +++ b/src/pipecat/processors/audio/audio_buffer_processor.py @@ -11,7 +11,6 @@ of audio from both user input and bot output sources, with support for various a configurations and event-driven processing. """ -import time from typing import Optional from pipecat.audio.utils import create_stream_resampler, interleave_stereo_audio, mix_audio @@ -104,10 +103,6 @@ class AudioBufferProcessor(FrameProcessor): self._user_turn_audio_buffer = bytearray() self._bot_turn_audio_buffer = bytearray() - # Intermittent (non continous user stream variables) - self._last_user_frame_at = 0 - self._last_bot_frame_at = 0 - self._recording = False self._input_resampler = create_stream_resampler() @@ -211,23 +206,31 @@ class AudioBufferProcessor(FrameProcessor): """Process audio frames for recording.""" resampled = None if isinstance(frame, InputAudioRawFrame): - # Add silence if we need to. - silence = self._compute_silence(self._last_user_frame_at) - self._user_audio_buffer.extend(silence) - # Add user audio. resampled = await self._resample_input_audio(frame) - self._user_audio_buffer.extend(resampled) - # Save time of frame so we can compute silence. - self._last_user_frame_at = time.time() + # Ignoring in case we don't have audio + if len(resampled) > 0: + # Sync bot buffer to current user position before adding user audio. + # We sync BEFORE extending to align both buffers at the same starting timestamp. + # For example, user buffer is at 100 bytes, and you receive 20 bytes of new audio + # - Bot buffer sees User is at 100. Bot pads itself to 100. + # - User buffer adds 20. User is now at 120. + # - Outcome: At index 100-120, we have User Audio and (potentially) Bot Audio or silence. They are aligned + # This gives the opportunity to the bot to send audio. + # + # If we synced AFTER, we'd pad the bot buffer with silence for the same + # window we just gave to the user, effectively "overwriting" that time slot + # with silence and causing the bot's audio to flicker or cut out. + self._sync_buffer_to_position(self._bot_audio_buffer, len(self._user_audio_buffer)) + # Add user audio. + self._user_audio_buffer.extend(resampled) elif self._recording and isinstance(frame, OutputAudioRawFrame): - # Add silence if we need to. - silence = self._compute_silence(self._last_bot_frame_at) - self._bot_audio_buffer.extend(silence) - # Add bot audio. resampled = await self._resample_output_audio(frame) - self._bot_audio_buffer.extend(resampled) - # Save time of frame so we can compute silence. - self._last_bot_frame_at = time.time() + # Ignoring in case we don't have audio + if len(resampled) > 0: + # Sync user buffer to current bot position before adding bot audio + self._sync_buffer_to_position(self._user_audio_buffer, len(self._bot_audio_buffer)) + # Add bot audio. + self._bot_audio_buffer.extend(resampled) if self._buffer_size > 0 and ( len(self._user_audio_buffer) >= self._buffer_size @@ -240,6 +243,21 @@ class AudioBufferProcessor(FrameProcessor): if self._enable_turn_audio: await self._process_turn_recording(frame, resampled) + def _sync_buffer_to_position(self, buffer: bytearray, target_position: int): + """Pad buffer with silence if it's behind the target position. + + This ensures both buffers stay synchronized by padding the lagging + buffer before new audio is added to the other buffer. + + Args: + buffer: The buffer to potentially pad. + target_position: The position (in bytes) the buffer should reach. + """ + current_len = len(buffer) + if current_len < target_position: + silence_needed = target_position - current_len + buffer.extend(b"\x00" * silence_needed) + async def _process_turn_recording(self, frame: Frame, resampled_audio: Optional[bytes] = None): """Process frames for turn-based audio recording.""" if isinstance(frame, UserStartedSpeakingFrame): @@ -281,8 +299,8 @@ class AudioBufferProcessor(FrameProcessor): if len(self._user_audio_buffer) == 0 and len(self._bot_audio_buffer) == 0: return + # Final alignment before we send the audio self._align_track_buffers() - flush_time = time.time() # Call original handler with merged audio merged_audio = self.merge_audio_buffers() @@ -299,9 +317,6 @@ class AudioBufferProcessor(FrameProcessor): self._num_channels, ) - self._last_user_frame_at = flush_time - self._last_bot_frame_at = flush_time - def _buffer_has_audio(self, buffer: bytearray) -> bool: """Check if a buffer contains audio data.""" return buffer is not None and len(buffer) > 0 @@ -309,8 +324,6 @@ class AudioBufferProcessor(FrameProcessor): def _reset_recording(self): """Reset recording state and buffers.""" self._reset_all_audio_buffers() - self._last_user_frame_at = time.time() - self._last_bot_frame_at = time.time() def _reset_all_audio_buffers(self): """Reset all audio buffers to empty state.""" @@ -336,11 +349,9 @@ class AudioBufferProcessor(FrameProcessor): target_len = max(user_len, bot_len) if user_len < target_len: - self._user_audio_buffer.extend(b"\x00" * (target_len - user_len)) - self._last_user_frame_at = max(self._last_user_frame_at, self._last_bot_frame_at) + self._sync_buffer_to_position(self._user_audio_buffer, target_len) if bot_len < target_len: - self._bot_audio_buffer.extend(b"\x00" * (target_len - bot_len)) - self._last_bot_frame_at = max(self._last_bot_frame_at, self._last_user_frame_at) + self._sync_buffer_to_position(self._bot_audio_buffer, target_len) async def _resample_input_audio(self, frame: InputAudioRawFrame) -> bytes: """Resample audio frame to the target sample rate.""" @@ -353,14 +364,3 @@ class AudioBufferProcessor(FrameProcessor): return await self._output_resampler.resample( frame.audio, frame.sample_rate, self._sample_rate ) - - def _compute_silence(self, from_time: float) -> bytes: - """Compute silence to insert based on time gap.""" - quiet_time = time.time() - from_time - # We should get audio frames very frequently. We introduce silence only - # if there's a big enough gap of 1s. - if from_time == 0 or quiet_time < 1.0: - return b"" - num_bytes = int(quiet_time * self._sample_rate) * 2 - silence = b"\x00" * num_bytes - return silence From f128cdd19a207148db1269569f030cb724bfd073 Mon Sep 17 00:00:00 2001 From: filipi87 Date: Fri, 23 Jan 2026 16:16:01 -0300 Subject: [PATCH 0186/1060] Adding a changelog entry to the AudioBufferProcessor fix. --- changelog/3541.fixed.md | 1 + 1 file changed, 1 insertion(+) create mode 100644 changelog/3541.fixed.md diff --git a/changelog/3541.fixed.md b/changelog/3541.fixed.md new file mode 100644 index 000000000..ac5b59529 --- /dev/null +++ b/changelog/3541.fixed.md @@ -0,0 +1 @@ +- Fixed how audio tracks are synchronized inside the `AudioBufferProcessor` to fix timing issues where silence and audio were misaligned between user and bot buffers. From bcb019e8abd2abc5bd8c8b26459e3bba38ed2435 Mon Sep 17 00:00:00 2001 From: Mark Backman Date: Fri, 23 Jan 2026 18:47:34 -0500 Subject: [PATCH 0187/1060] Add TTFB metrics for STT services (#3495) --- changelog/3495.changed.2.md | 1 + changelog/3495.changed.md | 1 + src/pipecat/frames/frames.py | 3 + src/pipecat/services/assemblyai/stt.py | 3 +- src/pipecat/services/aws/stt.py | 2 - src/pipecat/services/azure/stt.py | 2 - src/pipecat/services/cartesia/stt.py | 9 +- src/pipecat/services/deepgram/flux/stt.py | 3 + src/pipecat/services/deepgram/stt.py | 17 +- .../services/deepgram/stt_sagemaker.py | 10 +- src/pipecat/services/elevenlabs/stt.py | 15 +- src/pipecat/services/fal/stt.py | 2 - src/pipecat/services/gladia/stt.py | 2 - src/pipecat/services/google/stt.py | 2 - src/pipecat/services/gradium/stt.py | 1 - src/pipecat/services/hathora/stt.py | 2 - src/pipecat/services/nvidia/stt.py | 4 - src/pipecat/services/sarvam/stt.py | 44 +++- src/pipecat/services/soniox/stt.py | 9 +- src/pipecat/services/stt_service.py | 234 ++++++++++++++++++ src/pipecat/services/whisper/base_stt.py | 2 - src/pipecat/services/whisper/stt.py | 4 - 22 files changed, 309 insertions(+), 63 deletions(-) create mode 100644 changelog/3495.changed.2.md create mode 100644 changelog/3495.changed.md diff --git a/changelog/3495.changed.2.md b/changelog/3495.changed.2.md new file mode 100644 index 000000000..cf1f526b8 --- /dev/null +++ b/changelog/3495.changed.2.md @@ -0,0 +1 @@ +- `SarvamSTTService` now defaults `vad_signals` and `high_vad_sensitivity` to `None` (omitted from connection parameters), improving latency by ~300ms compared to the previous defaults. diff --git a/changelog/3495.changed.md b/changelog/3495.changed.md new file mode 100644 index 000000000..c690ebc09 --- /dev/null +++ b/changelog/3495.changed.md @@ -0,0 +1 @@ +- Improved the STT TTFB (Time To First Byte) measurement, reporting the delay between when the user stops speaking and when the final transcription is received. Note: Unlike traditional TTFB which measures from a discrete request, STT services receive continuous audio input—so we measure from speech end to final transcript, which captures the latency that matters for voice AI applications. In support of this change, added `finalized` field to `TranscriptionFrame` to indicate when a transcript is the final result for an utterance. diff --git a/src/pipecat/frames/frames.py b/src/pipecat/frames/frames.py index a27bb780e..26f9af9d2 100644 --- a/src/pipecat/frames/frames.py +++ b/src/pipecat/frames/frames.py @@ -426,12 +426,15 @@ class TranscriptionFrame(TextFrame): timestamp: When the transcription occurred. language: Detected or specified language of the speech. result: Raw result from the STT service. + finalized: Whether this is the final transcription for an utterance. + Set by STT services that support commit/finalize signals. """ user_id: str timestamp: str language: Optional[Language] = None result: Optional[Any] = None + finalized: bool = False def __str__(self): return f"{self.name}(user: {self.user_id}, text: [{self.text}], language: {self.language}, timestamp: {self.timestamp})" diff --git a/src/pipecat/services/assemblyai/stt.py b/src/pipecat/services/assemblyai/stt.py index 3fde9491c..99b4f423d 100644 --- a/src/pipecat/services/assemblyai/stt.py +++ b/src/pipecat/services/assemblyai/stt.py @@ -161,7 +161,7 @@ class AssemblyAISTTService(WebsocketSTTService): """ await super().process_frame(frame, direction) if isinstance(frame, VADUserStartedSpeakingFrame): - await self.start_ttfb_metrics() + pass elif isinstance(frame, VADUserStoppedSpeakingFrame): if ( self._vad_force_turn_endpoint @@ -354,7 +354,6 @@ class AssemblyAISTTService(WebsocketSTTService): """Handle transcription results.""" if not message.transcript: return - await self.stop_ttfb_metrics() if message.end_of_turn and ( not self._connection_params.formatted_finals or message.turn_is_formatted ): diff --git a/src/pipecat/services/aws/stt.py b/src/pipecat/services/aws/stt.py index 5ae99b02f..8beefe051 100644 --- a/src/pipecat/services/aws/stt.py +++ b/src/pipecat/services/aws/stt.py @@ -158,7 +158,6 @@ class AWSTranscribeSTTService(WebsocketSTTService): await self._websocket.send(event_message) # Start metrics after first chunk sent await self.start_processing_metrics() - await self.start_ttfb_metrics() except Exception as e: yield ErrorFrame(error=f"Error sending audio: {e}") @@ -470,7 +469,6 @@ class AWSTranscribeSTTService(WebsocketSTTService): is_final = not result.get("IsPartial", True) if transcript: - await self.stop_ttfb_metrics() if is_final: await self.push_frame( TranscriptionFrame( diff --git a/src/pipecat/services/azure/stt.py b/src/pipecat/services/azure/stt.py index aaa1e2da4..d45eb71df 100644 --- a/src/pipecat/services/azure/stt.py +++ b/src/pipecat/services/azure/stt.py @@ -116,7 +116,6 @@ class AzureSTTService(STTService): """ try: await self.start_processing_metrics() - await self.start_ttfb_metrics() if self._audio_stream: self._audio_stream.write(audio) yield None @@ -191,7 +190,6 @@ class AzureSTTService(STTService): self, transcript: str, is_final: bool, language: Optional[Language] = None ): """Handle a transcription result with tracing.""" - await self.stop_ttfb_metrics() await self.stop_processing_metrics() def _on_handle_recognized(self, event): diff --git a/src/pipecat/services/cartesia/stt.py b/src/pipecat/services/cartesia/stt.py index 625df6366..2fb08b981 100644 --- a/src/pipecat/services/cartesia/stt.py +++ b/src/pipecat/services/cartesia/stt.py @@ -207,9 +207,8 @@ class CartesiaSTTService(WebsocketSTTService): await super().cancel(frame) await self._disconnect() - async def start_metrics(self): + async def _start_metrics(self): """Start performance metrics collection for transcription processing.""" - await self.start_ttfb_metrics() await self.start_processing_metrics() async def process_frame(self, frame: Frame, direction: FrameDirection): @@ -222,10 +221,13 @@ class CartesiaSTTService(WebsocketSTTService): await super().process_frame(frame, direction) if isinstance(frame, VADUserStartedSpeakingFrame): - await self.start_metrics() + # Reset finalize state for new utterance + self.set_finalize_pending(False) + await self._start_metrics() elif isinstance(frame, VADUserStoppedSpeakingFrame): # Send finalize command to flush the transcription session if self._websocket and self._websocket.state is State.OPEN: + self.set_finalize_pending(True) await self._websocket.send("finalize") async def run_stt(self, audio: bytes) -> AsyncGenerator[Frame, None]: @@ -342,7 +344,6 @@ class CartesiaSTTService(WebsocketSTTService): pass if len(transcript) > 0: - await self.stop_ttfb_metrics() if is_final: await self.push_frame( TranscriptionFrame( diff --git a/src/pipecat/services/deepgram/flux/stt.py b/src/pipecat/services/deepgram/flux/stt.py index 045af9811..756827171 100644 --- a/src/pipecat/services/deepgram/flux/stt.py +++ b/src/pipecat/services/deepgram/flux/stt.py @@ -659,6 +659,8 @@ class DeepgramFluxSTTService(WebsocketSTTService): average_confidence = self._calculate_average_confidence(data) if not self._params.min_confidence or average_confidence > self._params.min_confidence: + # EndOfTurn means Flux has determined the turn is complete, + # so this TranscriptionFrame is always finalized await self.push_frame( TranscriptionFrame( transcript, @@ -666,6 +668,7 @@ class DeepgramFluxSTTService(WebsocketSTTService): time_now_iso8601(), self._language, result=data, + finalized=True, ) ) else: diff --git a/src/pipecat/services/deepgram/stt.py b/src/pipecat/services/deepgram/stt.py index 2469b25a3..20dfba724 100644 --- a/src/pipecat/services/deepgram/stt.py +++ b/src/pipecat/services/deepgram/stt.py @@ -276,9 +276,8 @@ class DeepgramSTTService(STTService): # GH issue: https://github.com/deepgram/deepgram-python-sdk/issues/570 await self._connection.finish() - async def start_metrics(self): - """Start TTFB and processing metrics collection.""" - await self.start_ttfb_metrics() + async def _start_metrics(self): + """Start processing metrics collection for this utterance.""" await self.start_processing_metrics() async def _on_error(self, *args, **kwargs): @@ -292,7 +291,7 @@ class DeepgramSTTService(STTService): await self._connect() async def _on_speech_started(self, *args, **kwargs): - await self.start_metrics() + await self._start_metrics() await self._call_event_handler("on_speech_started", *args, **kwargs) await self.broadcast_frame(UserStartedSpeakingFrame) if self._should_interrupt: @@ -320,8 +319,12 @@ class DeepgramSTTService(STTService): language = result.channel.alternatives[0].languages[0] language = Language(language) if len(transcript) > 0: - await self.stop_ttfb_metrics() if is_final: + # Check if this response is from a finalize() call. + # Only mark as finalized when both we requested it AND Deepgram confirms it. + from_finalize = getattr(result, "from_finalize", False) + if from_finalize: + self.confirm_finalize() await self.push_frame( TranscriptionFrame( transcript, @@ -356,8 +359,10 @@ class DeepgramSTTService(STTService): if isinstance(frame, VADUserStartedSpeakingFrame) and not self.vad_enabled: # Start metrics if Deepgram VAD is disabled & pipeline VAD has detected speech - await self.start_metrics() + await self._start_metrics() elif isinstance(frame, VADUserStoppedSpeakingFrame): # https://developers.deepgram.com/docs/finalize + # Mark that we're awaiting a from_finalize response + self.request_finalize() await self._connection.finalize() logger.trace(f"Triggered finalize event on: {frame.name=}, {direction=}") diff --git a/src/pipecat/services/deepgram/stt_sagemaker.py b/src/pipecat/services/deepgram/stt_sagemaker.py index 7eb6a072b..0f7e6f988 100644 --- a/src/pipecat/services/deepgram/stt_sagemaker.py +++ b/src/pipecat/services/deepgram/stt_sagemaker.py @@ -363,9 +363,6 @@ class DeepgramSageMakerSTTService(STTService): if not transcript.strip(): return - # Stop TTFB metrics on first transcript - await self.stop_ttfb_metrics() - is_final = parsed.get("is_final", False) speech_final = parsed.get("speech_final", False) @@ -417,9 +414,8 @@ class DeepgramSageMakerSTTService(STTService): """ pass - async def start_metrics(self): - """Start TTFB and processing metrics collection.""" - await self.start_ttfb_metrics() + async def _start_metrics(self): + """Start processing metrics collection.""" await self.start_processing_metrics() async def process_frame(self, frame: Frame, direction: FrameDirection): @@ -433,7 +429,7 @@ class DeepgramSageMakerSTTService(STTService): # Start metrics when user starts speaking (if VAD is not provided by Deepgram) if isinstance(frame, VADUserStartedSpeakingFrame): - await self.start_metrics() + await self._start_metrics() elif isinstance(frame, VADUserStoppedSpeakingFrame): # Send finalize message to Deepgram when user stops speaking # This tells Deepgram to flush any remaining audio and return final results diff --git a/src/pipecat/services/elevenlabs/stt.py b/src/pipecat/services/elevenlabs/stt.py index 8f9020aa7..a1be56a0d 100644 --- a/src/pipecat/services/elevenlabs/stt.py +++ b/src/pipecat/services/elevenlabs/stt.py @@ -310,7 +310,6 @@ class ElevenLabsSTTService(SegmentedSTTService): self, transcript: str, is_final: bool, language: Optional[str] = None ): """Handle a transcription result with tracing.""" - await self.stop_ttfb_metrics() await self.stop_processing_metrics() async def run_stt(self, audio: bytes) -> AsyncGenerator[Frame, None]: @@ -328,7 +327,6 @@ class ElevenLabsSTTService(SegmentedSTTService): """ try: await self.start_processing_metrics() - await self.start_ttfb_metrics() # Upload audio and get transcription result directly result = await self._transcribe_audio(audio) @@ -539,9 +537,8 @@ class ElevenLabsRealtimeSTTService(WebsocketSTTService): await super().cancel(frame) await self._disconnect() - async def start_metrics(self): + async def _start_metrics(self): """Start performance metrics collection for transcription processing.""" - await self.start_ttfb_metrics() await self.start_processing_metrics() async def process_frame(self, frame: Frame, direction: FrameDirection): @@ -554,13 +551,17 @@ class ElevenLabsRealtimeSTTService(WebsocketSTTService): await super().process_frame(frame, direction) if isinstance(frame, VADUserStartedSpeakingFrame): + # Reset finalize state for new utterance + self.set_finalize_pending(False) # Start metrics when user starts speaking - await self.start_metrics() + await self._start_metrics() elif isinstance(frame, VADUserStoppedSpeakingFrame): # Send commit when user stops speaking (manual commit mode) if self._params.commit_strategy == CommitStrategy.MANUAL: if self._websocket and self._websocket.state is State.OPEN: try: + # Mark that the next committed transcript should be finalized + self.set_finalize_pending(True) commit_message = { "message_type": "input_audio_chunk", "audio_base_64": "", @@ -764,8 +765,6 @@ class ElevenLabsRealtimeSTTService(WebsocketSTTService): if not text: return - await self.stop_ttfb_metrics() - # Get language if provided language = data.get("language_code") @@ -803,7 +802,6 @@ class ElevenLabsRealtimeSTTService(WebsocketSTTService): if not text: return - await self.stop_ttfb_metrics() await self.stop_processing_metrics() # Get language if provided @@ -845,7 +843,6 @@ class ElevenLabsRealtimeSTTService(WebsocketSTTService): if not text: return - await self.stop_ttfb_metrics() await self.stop_processing_metrics() # Get language if provided diff --git a/src/pipecat/services/fal/stt.py b/src/pipecat/services/fal/stt.py index a71915743..114865778 100644 --- a/src/pipecat/services/fal/stt.py +++ b/src/pipecat/services/fal/stt.py @@ -249,7 +249,6 @@ class FalSTTService(SegmentedSTTService): self, transcript: str, is_final: bool, language: Optional[str] = None ): """Handle a transcription result with tracing.""" - await self.stop_ttfb_metrics() await self.stop_processing_metrics() async def run_stt(self, audio: bytes) -> AsyncGenerator[Frame, None]: @@ -267,7 +266,6 @@ class FalSTTService(SegmentedSTTService): """ try: await self.start_processing_metrics() - await self.start_ttfb_metrics() # Send to Fal directly (audio is already in WAV format from base class) data_uri = fal_client.encode(audio, "audio/x-wav") diff --git a/src/pipecat/services/gladia/stt.py b/src/pipecat/services/gladia/stt.py index 8c5ec7aa4..e4229fe97 100644 --- a/src/pipecat/services/gladia/stt.py +++ b/src/pipecat/services/gladia/stt.py @@ -385,7 +385,6 @@ class GladiaSTTService(WebsocketSTTService): Yields: None (processing is handled asynchronously via WebSocket). """ - await self.start_ttfb_metrics() await self.start_processing_metrics() # Add audio to buffer @@ -513,7 +512,6 @@ class GladiaSTTService(WebsocketSTTService): async def _handle_transcription( self, transcript: str, is_final: bool, language: Optional[str] = None ): - await self.stop_ttfb_metrics() await self.stop_processing_metrics() async def _on_speech_started(self): diff --git a/src/pipecat/services/google/stt.py b/src/pipecat/services/google/stt.py index dcf0adf89..edb2ccec0 100644 --- a/src/pipecat/services/google/stt.py +++ b/src/pipecat/services/google/stt.py @@ -823,7 +823,6 @@ class GoogleSTTService(STTService): """ if self._streaming_task: # Queue the audio data - await self.start_ttfb_metrics() await self.start_processing_metrics() await self._request_queue.put(audio) yield None @@ -875,7 +874,6 @@ class GoogleSTTService(STTService): ) else: self._last_transcript_was_final = False - await self.stop_ttfb_metrics() await self.push_frame( InterimTranscriptionFrame( transcript, diff --git a/src/pipecat/services/gradium/stt.py b/src/pipecat/services/gradium/stt.py index b66b18070..1c378ff9f 100644 --- a/src/pipecat/services/gradium/stt.py +++ b/src/pipecat/services/gradium/stt.py @@ -122,7 +122,6 @@ class GradiumSTTService(WebsocketSTTService): None (processing handled via WebSocket messages). """ self._audio_buffer.extend(audio) - await self.start_ttfb_metrics() await self.start_processing_metrics() while len(self._audio_buffer) >= self._chunk_size_bytes: diff --git a/src/pipecat/services/hathora/stt.py b/src/pipecat/services/hathora/stt.py index 8aadb6b65..81e8f0ea6 100644 --- a/src/pipecat/services/hathora/stt.py +++ b/src/pipecat/services/hathora/stt.py @@ -111,7 +111,6 @@ class HathoraSTTService(SegmentedSTTService): """ try: await self.start_processing_metrics() - await self.start_ttfb_metrics() url = f"{self._base_url}" @@ -153,7 +152,6 @@ class HathoraSTTService(SegmentedSTTService): result=response, ) - await self.stop_ttfb_metrics() await self.stop_processing_metrics() except Exception as e: diff --git a/src/pipecat/services/nvidia/stt.py b/src/pipecat/services/nvidia/stt.py index 7d52f5130..3af3fe78c 100644 --- a/src/pipecat/services/nvidia/stt.py +++ b/src/pipecat/services/nvidia/stt.py @@ -307,7 +307,6 @@ class NvidiaSTTService(STTService): transcript = result.alternatives[0].transcript if transcript and len(transcript) > 0: - await self.stop_ttfb_metrics() if result.is_final: await self.stop_processing_metrics() await self.push_frame( @@ -344,7 +343,6 @@ class NvidiaSTTService(STTService): Yields: None - transcription results are pushed to the pipeline via frames. """ - await self.start_ttfb_metrics() await self.start_processing_metrics() await self._queue.put(audio) yield None @@ -598,12 +596,10 @@ class NvidiaSegmentedSTTService(SegmentedSTTService): assert self._config is not None, "Recognition config not created" await self.start_processing_metrics() - await self.start_ttfb_metrics() # Process audio with NVIDIA Riva ASR - explicitly request non-future response raw_response = self._asr_service.offline_recognize(audio, self._config, future=False) - await self.stop_ttfb_metrics() await self.stop_processing_metrics() # Process the response - handle different possible return types diff --git a/src/pipecat/services/sarvam/stt.py b/src/pipecat/services/sarvam/stt.py index f4e5c676b..96447dce9 100644 --- a/src/pipecat/services/sarvam/stt.py +++ b/src/pipecat/services/sarvam/stt.py @@ -15,9 +15,15 @@ from pipecat.frames.frames import ( CancelFrame, EndFrame, ErrorFrame, + Frame, StartFrame, TranscriptionFrame, + UserStartedSpeakingFrame, + UserStoppedSpeakingFrame, + VADUserStartedSpeakingFrame, + VADUserStoppedSpeakingFrame, ) +from pipecat.processors.frame_processor import FrameDirection from pipecat.services.sarvam._sdk import sdk_headers from pipecat.services.stt_service import STTService from pipecat.transcriptions.language import Language, resolve_language @@ -75,14 +81,14 @@ class SarvamSTTService(STTService): language: Target language for transcription. Defaults to None (required for saarika models). prompt: Optional prompt to guide translation style/context for STT-Translate models. Only applicable to saaras (STT-Translate) models. Defaults to None. - vad_signals: Enable VAD signals in response. Defaults to True. - high_vad_sensitivity: Enable high VAD (Voice Activity Detection) sensitivity. Defaults to False. + vad_signals: Enable VAD signals in response. Defaults to None. + high_vad_sensitivity: Enable high VAD (Voice Activity Detection) sensitivity. Defaults to None. """ language: Optional[Language] = None prompt: Optional[str] = None - vad_signals: bool = True - high_vad_sensitivity: bool = False + vad_signals: bool = None + high_vad_sensitivity: bool = None def __init__( self, @@ -155,6 +161,7 @@ class SarvamSTTService(STTService): self._websocket_context = None self._socket_client = None self._receive_task = None + logger.info(f"Sarvam STT initialized with SDK headers: {self._sdk_headers}") def language_to_service_language(self, language: Language) -> str: """Convert pipecat Language enum to Sarvam's language code. @@ -175,6 +182,24 @@ class SarvamSTTService(STTService): """ return True + async def process_frame(self, frame: Frame, direction: FrameDirection): + """Process incoming frames. + + Handles VAD frames for TTFB tracking when using Pipecat's VAD + instead of Sarvam's built-in VAD. + """ + await super().process_frame(frame, direction) + + # Only handle VAD frames when not using Sarvam's VAD signals + if not self._vad_signals: + if isinstance(frame, VADUserStartedSpeakingFrame): + self.set_finalize_pending(False) + await self._start_metrics() + elif isinstance(frame, VADUserStoppedSpeakingFrame): + if self._socket_client: + self.set_finalize_pending(True) + await self._socket_client.flush() + async def set_language(self, language: Language): """Set the recognition language and reconnect. @@ -411,16 +436,18 @@ class SarvamSTTService(STTService): logger.debug(f"VAD Signal: {signal}, Occurred at: {timestamp}") if signal == "START_SPEECH": - await self.start_metrics() + await self._start_metrics() logger.debug("User started speaking") await self._call_event_handler("on_speech_started") + await self.broadcast_frame(UserStartedSpeakingFrame) + await self.push_interruption_task_frame_and_wait() elif signal == "END_SPEECH": logger.debug("User stopped speaking") await self._call_event_handler("on_speech_stopped") + await self.broadcast_frame(UserStoppedSpeakingFrame) elif message.type == "data": - await self.stop_ttfb_metrics() transcript = message.data.transcript language_code = message.data.language_code # Prefer language from message (auto-detected for translate models). Fallback to configured. @@ -482,7 +509,6 @@ class SarvamSTTService(STTService): } return mapping.get(language_code, Language.HI_IN) - async def start_metrics(self): - """Start TTFB and processing metrics collection.""" - await self.start_ttfb_metrics() + async def _start_metrics(self): + """Start processing metrics collection.""" await self.start_processing_metrics() diff --git a/src/pipecat/services/soniox/stt.py b/src/pipecat/services/soniox/stt.py index 476ae0762..6f8c92d26 100644 --- a/src/pipecat/services/soniox/stt.py +++ b/src/pipecat/services/soniox/stt.py @@ -21,7 +21,7 @@ from pipecat.frames.frames import ( InterimTranscriptionFrame, StartFrame, TranscriptionFrame, - UserStoppedSpeakingFrame, + VADUserStoppedSpeakingFrame, ) from pipecat.processors.frame_processor import FrameDirection from pipecat.services.stt_service import WebsocketSTTService @@ -162,7 +162,7 @@ class SonioxSTTService(WebsocketSTTService): sample_rate: Audio sample rate. params: Additional configuration parameters, such as language hints, context and speaker diarization. - vad_force_turn_endpoint: Listen to `UserStoppedSpeakingFrame` to send finalize message to Soniox. If disabled, Soniox will detect the end of the speech. + vad_force_turn_endpoint: Listen to `VADUserStoppedSpeakingFrame` to send finalize message to Soniox. If disabled, Soniox will detect the end of the speech. **kwargs: Additional arguments passed to the STTService. """ super().__init__(sample_rate=sample_rate, **kwargs) @@ -247,7 +247,7 @@ class SonioxSTTService(WebsocketSTTService): """ await super().process_frame(frame, direction) - if isinstance(frame, UserStoppedSpeakingFrame) and self._vad_force_turn_endpoint: + if isinstance(frame, VADUserStoppedSpeakingFrame) and self._vad_force_turn_endpoint: # Send finalize message to Soniox so we get the final tokens asap. if self._websocket and self._websocket.state is State.OPEN: await self._websocket.send(FINALIZE_MESSAGE) @@ -374,12 +374,15 @@ class SonioxSTTService(WebsocketSTTService): async def send_endpoint_transcript(): if self._final_transcription_buffer: text = "".join(map(lambda token: token["text"], self._final_transcription_buffer)) + # Soniox only pushes TranscriptionFrame when an end token is received, + # so every TranscriptionFrame is inherently finalized await self.push_frame( TranscriptionFrame( text=text, user_id=self._user_id, timestamp=time_now_iso8601(), result=self._final_transcription_buffer, + finalized=True, ) ) await self._handle_transcription(text, is_final=True) diff --git a/src/pipecat/services/stt_service.py b/src/pipecat/services/stt_service.py index 46c40ae70..24b1aafcf 100644 --- a/src/pipecat/services/stt_service.py +++ b/src/pipecat/services/stt_service.py @@ -6,7 +6,9 @@ """Base classes for Speech-to-Text services with continuous and segmented processing.""" +import asyncio import io +import time import wave from abc import abstractmethod from typing import Any, AsyncGenerator, Dict, Mapping, Optional @@ -17,12 +19,17 @@ from pipecat.frames.frames import ( AudioRawFrame, ErrorFrame, Frame, + InterruptionFrame, + MetricsFrame, + SpeechControlParamsFrame, StartFrame, STTMuteFrame, STTUpdateSettingsFrame, + TranscriptionFrame, VADUserStartedSpeakingFrame, VADUserStoppedSpeakingFrame, ) +from pipecat.metrics.metrics import TTFBMetricsData from pipecat.processors.frame_processor import FrameDirection from pipecat.services.ai_service import AIService from pipecat.services.websocket_service import WebsocketService @@ -61,6 +68,8 @@ class STTService(AIService): audio_passthrough=True, # STT input sample rate sample_rate: Optional[int] = None, + # STT TTFB timeout - time to wait after VAD stop before reporting TTFB + stt_ttfb_timeout: float = 2.0, **kwargs, ): """Initialize the STT service. @@ -70,6 +79,12 @@ class STTService(AIService): Defaults to True. sample_rate: The sample rate for audio input. If None, will be determined from the start frame. + stt_ttfb_timeout: Time in seconds to wait after VAD stop before reporting + TTFB. This delay allows the final transcription to arrive. Defaults to 2.0. + Note: STT "TTFB" differs from traditional TTFB (which measures from a discrete + request to first response byte). Since STT receives continuous audio, we measure + from when the user stops speaking to when the final transcript arrives—capturing + the latency that matters for voice AI applications. **kwargs: Additional arguments passed to the parent AIService. """ super().__init__(**kwargs) @@ -81,6 +96,16 @@ class STTService(AIService): self._muted: bool = False self._user_id: str = "" + # STT TTFB tracking state + self._stt_ttfb_timeout = stt_ttfb_timeout + self._ttfb_timeout_task: Optional[asyncio.Task] = None + self._vad_stop_secs: Optional[float] = None + self._speech_end_time: Optional[float] = None + self._user_speaking: bool = False + self._last_transcription_time: Optional[float] = None + self._finalize_pending: bool = False + self._finalize_requested: bool = False + self._register_event_handler("on_connected") self._register_event_handler("on_disconnected") self._register_event_handler("on_connection_error") @@ -94,6 +119,44 @@ class STTService(AIService): """ return self._muted + def set_finalize_pending(self, value: bool): + """Set whether the next TranscriptionFrame should be marked as finalized. + + When True, the next TranscriptionFrame pushed will have its `finalized` + field set to True, and this flag will automatically reset to False. + This is used to signal that a transcript is the final result for an + utterance, enabling immediate TTFB reporting. + + Args: + value: True to mark the next transcription as finalized. + """ + self._finalize_pending = value + + def request_finalize(self): + """Mark that a finalize request has been sent, awaiting server confirmation. + + For providers that require server confirmation before marking transcripts + as finalized (e.g., Deepgram's from_finalize field), call this when sending + the finalize request. Then call confirm_finalize() when the server confirms. + + This is an alternative to set_finalize_pending() for providers that need + two-step finalization. + """ + self._finalize_requested = True + + def confirm_finalize(self): + """Confirm that the server has acknowledged the finalize request. + + Call this when the server response confirms finalization (e.g., Deepgram's + from_finalize=True). The next TranscriptionFrame pushed will be marked + as finalized. + + Only has effect if request_finalize() was previously called. + """ + if self._finalize_requested: + self._finalize_pending = True + self._finalize_requested = False + @property def sample_rate(self) -> int: """Get the current sample rate for audio processing. @@ -144,6 +207,11 @@ class STTService(AIService): self._sample_rate = self._init_sample_rate or frame.audio_in_sample_rate self._tracing_enabled = frame.enable_tracing + async def cleanup(self): + """Clean up STT service resources.""" + await super().cleanup() + await self._cancel_ttfb_timeout() + async def _update_settings(self, settings: Mapping[str, Any]): logger.info(f"Updating STT settings: {self._settings}") for key, value in settings.items(): @@ -206,14 +274,166 @@ class STTService(AIService): await self.process_audio_frame(frame, direction) if self._audio_passthrough: await self.push_frame(frame, direction) + elif isinstance(frame, SpeechControlParamsFrame): + await self._handle_speech_control_params(frame) + await self.push_frame(frame, direction) + elif isinstance(frame, VADUserStartedSpeakingFrame): + await self._handle_vad_user_started_speaking(frame) + await self.push_frame(frame, direction) + elif isinstance(frame, VADUserStoppedSpeakingFrame): + await self._handle_vad_user_stopped_speaking(frame) + await self.push_frame(frame, direction) elif isinstance(frame, STTUpdateSettingsFrame): await self._update_settings(frame.settings) elif isinstance(frame, STTMuteFrame): self._muted = frame.mute logger.debug(f"STT service {'muted' if frame.mute else 'unmuted'}") + elif isinstance(frame, InterruptionFrame): + await self._reset_stt_ttfb_state() + await self.push_frame(frame, direction) else: await self.push_frame(frame, direction) + async def push_frame(self, frame: Frame, direction: FrameDirection = FrameDirection.DOWNSTREAM): + """Push a frame downstream, tracking TranscriptionFrame timestamps for TTFB. + + Stores the timestamp of each TranscriptionFrame for TTFB calculation. + If the frame is marked as finalized (either directly or via set_finalize_pending), + reports TTFB immediately and cancels any pending timeout. Otherwise, TTFB is + reported after a timeout. + + Args: + frame: The frame to push. + direction: The direction to push the frame. + """ + if isinstance(frame, TranscriptionFrame): + # Store the transcription time for TTFB calculation + self._last_transcription_time = time.time() + + # Set finalized from pending state and auto-reset + if self._finalize_pending: + frame.finalized = True + self._finalize_pending = False + + # If this is a finalized transcription, report TTFB immediately + if frame.finalized and self._speech_end_time is not None: + ttfb = self._last_transcription_time - self._speech_end_time + await self._emit_stt_ttfb_metric(ttfb) + # Cancel the timeout since we've already reported + await self._cancel_ttfb_timeout() + # Clear state + self._speech_end_time = None + self._last_transcription_time = None + + await super().push_frame(frame, direction) + + async def _handle_speech_control_params(self, frame: SpeechControlParamsFrame): + """Handle speech control parameters frame to extract VAD stop_secs. + + Args: + frame: The speech control parameters frame. + """ + if frame.vad_params is not None: + self._vad_stop_secs = frame.vad_params.stop_secs + + async def _cancel_ttfb_timeout(self): + """Cancel any pending TTFB timeout task.""" + if self._ttfb_timeout_task: + await self.cancel_task(self._ttfb_timeout_task) + self._ttfb_timeout_task = None + + async def _reset_stt_ttfb_state(self): + """Reset STT TTFB measurement state. + + Called when starting a new utterance or on interruption to ensure + we don't use stale state for TTFB calculations. This specifically guards + against the case where a TranscriptionFrame is received without corresponding + VADUserStartedSpeakingFrame and VADUserStoppedSpeakingFrame frames. + + Note: Does not reset _user_speaking since InterruptionFrame can arrive + while user is still speaking. + """ + await self._cancel_ttfb_timeout() + self._speech_end_time = None + self._last_transcription_time = None + + async def _handle_vad_user_started_speaking(self, frame: VADUserStartedSpeakingFrame): + """Handle VAD user started speaking frame to start tracking transcriptions. + + Cancels any pending TTFB timeout, resets TTFB tracking state, and marks user as speaking. + + Args: + frame: The VAD user started speaking frame. + """ + await self._reset_stt_ttfb_state() + self._user_speaking = True + self._finalize_requested = False + + async def _handle_vad_user_stopped_speaking(self, frame: VADUserStoppedSpeakingFrame): + """Handle VAD user stopped speaking frame. + + Calculates the actual speech end time and starts a timeout task to wait + for the final transcription before reporting TTFB. + + Args: + frame: The VAD user stopped speaking frame. + """ + self._user_speaking = False + + # Skip TTFB measurement if we don't have VAD params + if self._vad_stop_secs is None: + return + + # Calculate the actual speech end time (current time minus VAD stop delay). + # This approximates when the last user audio was sent to the STT service, + # which we use to measure against the eventual transcription response. + self._speech_end_time = time.time() - self._vad_stop_secs + + # Start timeout task (any previous timeout was cancelled by VADUserStartedSpeakingFrame + # or InterruptionFrame) + self._ttfb_timeout_task = self.create_task( + self._ttfb_timeout_handler(), name="stt_ttfb_timeout" + ) + + async def _ttfb_timeout_handler(self): + """Wait for timeout then report TTFB using the last transcription timestamp. + + This timeout allows the final transcription to arrive before we calculate + and report TTFB. If no transcription arrived, no TTFB is reported. + """ + try: + await asyncio.sleep(self._stt_ttfb_timeout) + + # Report TTFB if we have both speech end time and transcription time + if self._speech_end_time is not None and self._last_transcription_time is not None: + ttfb = self._last_transcription_time - self._speech_end_time + await self._emit_stt_ttfb_metric(ttfb) + + # Clear state after reporting + self._speech_end_time = None + self._last_transcription_time = None + except asyncio.CancelledError: + # Task was cancelled (new utterance or interruption), which is expected behavior + pass + finally: + self._ttfb_timeout_task = None + + async def _emit_stt_ttfb_metric(self, ttfb: float): + """Emit STT TTFB metric if value is non-negative. + + Args: + ttfb: The TTFB value in seconds. + """ + if ttfb >= 0: + logger.debug(f"{self} TTFB: {ttfb:.3f}s") + if self.metrics_enabled: + ttfb_data = TTFBMetricsData( + processor=self.name, + model=self.model_name, + value=ttfb, + ) + await super().push_frame(MetricsFrame(data=[ttfb_data])) + class SegmentedSTTService(STTService): """STT service that processes speech in segments using VAD events. @@ -250,6 +470,20 @@ class SegmentedSTTService(STTService): await super().start(frame) self._audio_buffer_size_1s = self.sample_rate * 2 + async def push_frame(self, frame: Frame, direction: FrameDirection = FrameDirection.DOWNSTREAM): + """Push a frame, marking TranscriptionFrames as finalized. + + Segmented STT services process complete speech segments and return a single + TranscriptionFrame per segment, so every transcription is inherently finalized. + + Args: + frame: The frame to push. + direction: The direction of frame flow in the pipeline. + """ + if isinstance(frame, TranscriptionFrame): + frame.finalized = True + await super().push_frame(frame, direction) + async def process_frame(self, frame: Frame, direction: FrameDirection): """Process frames, handling VAD events and audio segmentation.""" await super().process_frame(frame, direction) diff --git a/src/pipecat/services/whisper/base_stt.py b/src/pipecat/services/whisper/base_stt.py index 32e08de8e..79d2723f1 100644 --- a/src/pipecat/services/whisper/base_stt.py +++ b/src/pipecat/services/whisper/base_stt.py @@ -204,11 +204,9 @@ class BaseWhisperSTTService(SegmentedSTTService): """ try: await self.start_processing_metrics() - await self.start_ttfb_metrics() response = await self._transcribe(audio) - await self.stop_ttfb_metrics() await self.stop_processing_metrics() text = response.text.strip() diff --git a/src/pipecat/services/whisper/stt.py b/src/pipecat/services/whisper/stt.py index 3865578e1..f11978cc2 100644 --- a/src/pipecat/services/whisper/stt.py +++ b/src/pipecat/services/whisper/stt.py @@ -289,7 +289,6 @@ class WhisperSTTService(SegmentedSTTService): return await self.start_processing_metrics() - await self.start_ttfb_metrics() # Divide by 32768 because we have signed 16-bit data. audio_float = np.frombuffer(audio, dtype=np.int16).astype(np.float32) / 32768.0 @@ -303,7 +302,6 @@ class WhisperSTTService(SegmentedSTTService): if segment.no_speech_prob < self._no_speech_prob: text += f"{segment.text} " - await self.stop_ttfb_metrics() await self.stop_processing_metrics() if text: @@ -388,7 +386,6 @@ class WhisperSTTServiceMLX(WhisperSTTService): import mlx_whisper await self.start_processing_metrics() - await self.start_ttfb_metrics() # Divide by 32768 because we have signed 16-bit data. audio_float = np.frombuffer(audio, dtype=np.int16).astype(np.float32) / 32768.0 @@ -413,7 +410,6 @@ class WhisperSTTServiceMLX(WhisperSTTService): if len(text.strip()) == 0: text = None - await self.stop_ttfb_metrics() await self.stop_processing_metrics() if text: From d2ac9006a25639ecf8326648b368319f027e2841 Mon Sep 17 00:00:00 2001 From: Mark Backman Date: Sat, 24 Jan 2026 12:49:52 -0500 Subject: [PATCH 0188/1060] Update env var to PIPECAT_SMART_TURN_LOG_DATA --- changelog/3525.added.md | 2 +- src/pipecat/audio/turn/smart_turn/local_smart_turn_v3.py | 2 +- 2 files changed, 2 insertions(+), 2 deletions(-) diff --git a/changelog/3525.added.md b/changelog/3525.added.md index 0dcf74287..e34b5e3d5 100644 --- a/changelog/3525.added.md +++ b/changelog/3525.added.md @@ -1 +1 @@ -- Added new `SMART_TURN_LOG_DATA` environment variable, which causes Smart Turn input data to be saved to disk +- Added new `PIPECAT_SMART_TURN_LOG_DATA` environment variable, which causes Smart Turn input data to be saved to disk diff --git a/src/pipecat/audio/turn/smart_turn/local_smart_turn_v3.py b/src/pipecat/audio/turn/smart_turn/local_smart_turn_v3.py index 84f6b5622..1eae7cc02 100644 --- a/src/pipecat/audio/turn/smart_turn/local_smart_turn_v3.py +++ b/src/pipecat/audio/turn/smart_turn/local_smart_turn_v3.py @@ -49,7 +49,7 @@ class LocalSmartTurnAnalyzerV3(BaseSmartTurn): """ super().__init__(**kwargs) - self._log_data = env_truthy("SMART_TURN_LOG_DATA", default=False) + self._log_data = env_truthy("PIPECAT_SMART_TURN_LOG_DATA", default=False) if not smart_turn_model_path: # Load bundled model From e93112e76e3ff89bbc559eceb7add64ad2436ab6 Mon Sep 17 00:00:00 2001 From: Mark Backman Date: Sat, 24 Jan 2026 14:54:58 -0500 Subject: [PATCH 0189/1060] Simplify STT finalize handling --- src/pipecat/services/cartesia/stt.py | 3 --- src/pipecat/services/elevenlabs/stt.py | 4 ---- src/pipecat/services/sarvam/stt.py | 2 -- src/pipecat/services/stt_service.py | 27 ++++++++------------------ 4 files changed, 8 insertions(+), 28 deletions(-) diff --git a/src/pipecat/services/cartesia/stt.py b/src/pipecat/services/cartesia/stt.py index 2fb08b981..c0bfb3e8d 100644 --- a/src/pipecat/services/cartesia/stt.py +++ b/src/pipecat/services/cartesia/stt.py @@ -221,13 +221,10 @@ class CartesiaSTTService(WebsocketSTTService): await super().process_frame(frame, direction) if isinstance(frame, VADUserStartedSpeakingFrame): - # Reset finalize state for new utterance - self.set_finalize_pending(False) await self._start_metrics() elif isinstance(frame, VADUserStoppedSpeakingFrame): # Send finalize command to flush the transcription session if self._websocket and self._websocket.state is State.OPEN: - self.set_finalize_pending(True) await self._websocket.send("finalize") async def run_stt(self, audio: bytes) -> AsyncGenerator[Frame, None]: diff --git a/src/pipecat/services/elevenlabs/stt.py b/src/pipecat/services/elevenlabs/stt.py index a1be56a0d..469d2c4fa 100644 --- a/src/pipecat/services/elevenlabs/stt.py +++ b/src/pipecat/services/elevenlabs/stt.py @@ -551,8 +551,6 @@ class ElevenLabsRealtimeSTTService(WebsocketSTTService): await super().process_frame(frame, direction) if isinstance(frame, VADUserStartedSpeakingFrame): - # Reset finalize state for new utterance - self.set_finalize_pending(False) # Start metrics when user starts speaking await self._start_metrics() elif isinstance(frame, VADUserStoppedSpeakingFrame): @@ -560,8 +558,6 @@ class ElevenLabsRealtimeSTTService(WebsocketSTTService): if self._params.commit_strategy == CommitStrategy.MANUAL: if self._websocket and self._websocket.state is State.OPEN: try: - # Mark that the next committed transcript should be finalized - self.set_finalize_pending(True) commit_message = { "message_type": "input_audio_chunk", "audio_base_64": "", diff --git a/src/pipecat/services/sarvam/stt.py b/src/pipecat/services/sarvam/stt.py index 96447dce9..164ad289e 100644 --- a/src/pipecat/services/sarvam/stt.py +++ b/src/pipecat/services/sarvam/stt.py @@ -193,11 +193,9 @@ class SarvamSTTService(STTService): # Only handle VAD frames when not using Sarvam's VAD signals if not self._vad_signals: if isinstance(frame, VADUserStartedSpeakingFrame): - self.set_finalize_pending(False) await self._start_metrics() elif isinstance(frame, VADUserStoppedSpeakingFrame): if self._socket_client: - self.set_finalize_pending(True) await self._socket_client.flush() async def set_language(self, language: Language): diff --git a/src/pipecat/services/stt_service.py b/src/pipecat/services/stt_service.py index 24b1aafcf..44c7af3b4 100644 --- a/src/pipecat/services/stt_service.py +++ b/src/pipecat/services/stt_service.py @@ -119,28 +119,15 @@ class STTService(AIService): """ return self._muted - def set_finalize_pending(self, value: bool): - """Set whether the next TranscriptionFrame should be marked as finalized. - - When True, the next TranscriptionFrame pushed will have its `finalized` - field set to True, and this flag will automatically reset to False. - This is used to signal that a transcript is the final result for an - utterance, enabling immediate TTFB reporting. - - Args: - value: True to mark the next transcription as finalized. - """ - self._finalize_pending = value - def request_finalize(self): """Mark that a finalize request has been sent, awaiting server confirmation. - For providers that require server confirmation before marking transcripts - as finalized (e.g., Deepgram's from_finalize field), call this when sending - the finalize request. Then call confirm_finalize() when the server confirms. + For providers that have explicit server confirmation of finalization + (e.g., Deepgram's from_finalize field), call this when sending the finalize + request. Then call confirm_finalize() when the server confirms. - This is an alternative to set_finalize_pending() for providers that need - two-step finalization. + For providers without server confirmation, don't call this method - just + send the finalize/flush/commit command and rely on the TTFB timeout. """ self._finalize_requested = True @@ -298,7 +285,7 @@ class STTService(AIService): """Push a frame downstream, tracking TranscriptionFrame timestamps for TTFB. Stores the timestamp of each TranscriptionFrame for TTFB calculation. - If the frame is marked as finalized (either directly or via set_finalize_pending), + If the frame is marked as finalized (via request_finalize/confirm_finalize), reports TTFB immediately and cancels any pending timeout. Otherwise, TTFB is reported after a timeout. @@ -361,6 +348,7 @@ class STTService(AIService): """Handle VAD user started speaking frame to start tracking transcriptions. Cancels any pending TTFB timeout, resets TTFB tracking state, and marks user as speaking. + Also resets finalization state to prevent stale finalization from a previous utterance. Args: frame: The VAD user started speaking frame. @@ -368,6 +356,7 @@ class STTService(AIService): await self._reset_stt_ttfb_state() self._user_speaking = True self._finalize_requested = False + self._finalize_pending = False async def _handle_vad_user_stopped_speaking(self, frame: VADUserStoppedSpeakingFrame): """Handle VAD user stopped speaking frame. From a4acc12f91d6ece7c3ec608973a311609d1d393f Mon Sep 17 00:00:00 2001 From: Mark Backman Date: Sat, 24 Jan 2026 18:26:34 -0500 Subject: [PATCH 0190/1060] Align Speechmatics STT TTFB metrics with STT classes --- src/pipecat/services/speechmatics/stt.py | 26 ------------------------ 1 file changed, 26 deletions(-) diff --git a/src/pipecat/services/speechmatics/stt.py b/src/pipecat/services/speechmatics/stt.py index 457388c31..d12b2a7d3 100644 --- a/src/pipecat/services/speechmatics/stt.py +++ b/src/pipecat/services/speechmatics/stt.py @@ -8,7 +8,6 @@ import asyncio import os -import time from enum import Enum from typing import Any, AsyncGenerator @@ -598,9 +597,6 @@ class SpeechmaticsSTTService(STTService): if segments: await self._send_frames(segments) - # Update metrics - await self._emit_metrics(message.get("metadata", {}).get("processing_time", 0.0)) - async def _handle_segment(self, message: dict[str, Any]) -> None: """Handle AddSegment events. @@ -804,28 +800,6 @@ class SpeechmaticsSTTService(STTService): yield ErrorFrame(f"Speechmatics error: {e}") await self._disconnect() - async def _emit_metrics(self, processing_time: float) -> None: - """Create TTFB metrics. - - The TTFB is the seconds between the person speaking and the STT - engine emitting the first partial. This is only calculated at the - start of an utterance. - """ - # Skip if metrics not available - if not self._metrics or processing_time == 0.0: - return - - # Calculate time as time.time() - ttfb (which is seconds) - start_time = time.time() - processing_time - - # Update internal metrics - self._metrics._start_ttfb_time = start_time - self._metrics._start_processing_time = start_time - - # Stop TTFB metrics - await self.stop_ttfb_metrics() - await self.stop_processing_metrics() - # ============================================================================ # HELPERS # ============================================================================ From a446bca72dc3af999a71856b217c8c973094e4db Mon Sep 17 00:00:00 2001 From: ssillerom Date: Sun, 25 Jan 2026 21:10:22 +0100 Subject: [PATCH 0191/1060] changes: added OutputTransportUrgentFrame to on closed, removed callback --- src/pipecat/serializers/genesys.py | 205 ++++++----------------------- 1 file changed, 37 insertions(+), 168 deletions(-) diff --git a/src/pipecat/serializers/genesys.py b/src/pipecat/serializers/genesys.py index 11a842772..48637653b 100644 --- a/src/pipecat/serializers/genesys.py +++ b/src/pipecat/serializers/genesys.py @@ -1,15 +1,15 @@ """ -Genesys AudioHook WebSocket protocol serializer for Pipecat. +Use with Genesys Audio Connector to connect Genesys Cloud Contact Center with Pipecat pipelines. -This serializer implements the Genesys AudioHook protocol for bidirectional -audio streaming between Pipecat pipelines and Genesys Cloud contact center. +This connector implements the Genesys AudioHook protocol for bidirectional +audio streaming between Genesys Cloud contact center and Pipecat pipelines. Protocol Reference: - https://developer.genesys.cloud/devapps/audiohook Audio Format: - PCMU (μ-law) at 8kHz sample rate (preferred) -- L16 (16-bit linear PCM) at 8kHz also supported +- L16 (16-bit linear PCM) at 8kHz also supported - Mono or Stereo (external on left, internal on right) """ @@ -17,7 +17,7 @@ import json import uuid from datetime import timedelta from enum import Enum -from typing import Any, Awaitable, Callable, Dict, List, Optional +from typing import Any, Dict, List, Optional from loguru import logger from pydantic import BaseModel @@ -32,7 +32,8 @@ from pipecat.frames.frames import ( InputDTMFFrame, OutputTransportMessageFrame, OutputTransportMessageUrgentFrame, - StartFrame + StartFrame, + InterruptionFrame ) from pipecat.serializers.base_serializer import FrameSerializer from pipecat.audio.resamplers.soxr_stream_resampler import SOXRStreamAudioResampler @@ -116,7 +117,6 @@ class GenesysAudioHookSerializer(FrameSerializer): media_format: Audio format (PCMU or L16). process_external: Whether to process external (customer) audio. process_internal: Whether to process internal (agent) audio. - enable_interruption_events: Send interruption events to Genesys. """ genesys_sample_rate: int = 8000 @@ -125,30 +125,25 @@ class GenesysAudioHookSerializer(FrameSerializer): media_format: AudioHookMediaFormat = AudioHookMediaFormat.PCMU process_external: bool = True process_internal: bool = False - enable_interruption_events: bool = True def __init__( self, session_id: Optional[str] = None, params: Optional[InputParams] = None, - send_message_callback: Optional[Callable[[str], Awaitable[None]]] = None, ): """Initialize the GenesysAudioHookSerializer. Args: session_id: The AudioHook session ID (received in open message). params: Configuration parameters. - send_message_callback: Optional async callback to send messages directly - (bypassing the pipeline). Used for urgent messages like pong. """ self._params = params or GenesysAudioHookSerializer.InputParams() self._session_id = session_id or "" - self._send_message_callback = send_message_callback self._genesys_sample_rate = self._params.genesys_sample_rate self._sample_rate = 0 # Pipeline input rate, set in setup() - # Use Pipecat's official SOXR resampler + # Use Pipecat's official resampler if needed (SOXR) # Only used for TTS output (16kHz → 8kHz), input goes without resampling self._input_resampler = SOXRStreamAudioResampler() self._output_resampler = SOXRStreamAudioResampler() @@ -160,23 +155,13 @@ class GenesysAudioHookSerializer(FrameSerializer): self._is_paused = False self._position = timedelta(0) - # TTS output state - self._tts_chunk_count = 0 - # Session metadata self._conversation_id: Optional[str] = None self._participant: Optional[Dict[str, Any]] = None self._custom_config: Optional[Dict[str, Any]] = None self._media_info: Optional[List[Dict[str, Any]]] = None self._input_variables: Optional[Dict[str, Any]] = None # Custom input from Genesys - - def set_send_message_callback(self, callback: Callable[[str], Awaitable[None]]): - """Set the callback for sending urgent messages directly. - Args: - callback: An async function that takes a string message and sends it. - """ - self._send_message_callback = callback @property def session_id(self) -> str: @@ -217,14 +202,6 @@ class GenesysAudioHookSerializer(FrameSerializer): self._sample_rate = self._params.sample_rate or frame.audio_in_sample_rate logger.debug(f"GenesysAudioHookSerializer setup with sample_rate={self._sample_rate}") - def reset_tts_state(self): - """Reset TTS state for a new utterance. - - NOTE: We don't reset the resampler because that causes artifacts. - The resampler maintains its state between utterances for cleaner audio. - """ - self._tts_chunk_count = 0 - def _format_position(self, position: timedelta) -> str: """Format a timedelta as ISO 8601 duration string. @@ -316,7 +293,7 @@ class GenesysAudioHookSerializer(FrameSerializer): JSON string of the opened response message. """ # Build channels list based on configuration - channels = [] + channels: list[str] = [] if self._params.channel == AudioHookChannel.EXTERNAL: channels = ["external"] elif self._params.channel == AudioHookChannel.INTERNAL: @@ -393,36 +370,26 @@ class GenesysAudioHookSerializer(FrameSerializer): return json.dumps(msg) - def create_event_message( - self, - entity_type: str, - entity_data: Dict[str, Any], - ) -> str: - """Create an 'event' message to send data back to Genesys. + def create_barge_in_event(self) -> str: + """Create a barge-in event message. - This can be used for transcriptions, agent assist, or other events. + This notifies Genesys Cloud that the user has interrupted the bot's + audio output. Genesys will stop any queued audio playback. - Args: - entity_type: The type of entity (e.g., "transcript"). - entity_data: The entity data. - Returns: - JSON string of the event message. + JSON string of the barge-in event message. """ - parameters = { - "entities": [ - { - "type": entity_type, - **entity_data, - } - ] - } - msg = self._create_message( AudioHookMessageType.EVENT, - parameters=parameters, + parameters={ + "entities": [ + {"type": "barge_in", "data": {}} + ] + }, ) + logger.debug("🔇 Barge-in event sent to Genesys") + return json.dumps(msg) def create_disconnect_message( @@ -492,88 +459,6 @@ class GenesysAudioHookSerializer(FrameSerializer): logger.error(f"AudioHook error: {code} - {message}") return json.dumps(msg) - def create_barge_in_event(self) -> str: - """Create a barge-in event message. - - This notifies Genesys Cloud that the user has interrupted the bot's - audio output. Genesys will stop any queued audio playback. - - Returns: - JSON string of the barge-in event message. - """ - msg = self._create_message( - AudioHookMessageType.EVENT, - parameters={ - "entities": [ - {"type": "barge_in", "data": {}} - ] - }, - ) - - logger.debug("🔇 Barge-in event sent to Genesys") - - return json.dumps(msg) - - def create_resume_event(self) -> str: - """Create a resume event message. - - This notifies Genesys that the bot is ready to resume after a barge-in. - Should be called after the user stops speaking following a barge-in. - - Returns: - JSON string of the resume event message. - """ - self._barge_in = False - - # Note: 'resume' might not be a standard AudioHook message type, - # but it's used in some implementations - msg = { - "version": self.PROTOCOL_VERSION, - "type": "resume", - "seq": self._next_server_seq(), - "clientseq": self._client_seq, - "id": self._session_id, - "parameters": {}, - } - - logger.debug("Resume event sent") - return json.dumps(msg) - - def create_interruption_event( - self, - reason: str = "user_speaking", - discarded_bytes: Optional[int] = None, - ) -> str: - """Create a generic interruption event message. - - This is an alternative to create_barge_in_event() that includes - more detailed information about the interruption. - - Args: - reason: Reason for interruption (e.g., "user_speaking", "dtmf"). - discarded_bytes: Number of audio bytes discarded due to interruption. - - Returns: - JSON string of the interruption event message. - """ - entity_data: Dict[str, Any] = { - "reason": reason, - "timestamp": self._format_position(self._position), - } - - if discarded_bytes is not None: - entity_data["discardedAudioBytes"] = discarded_bytes - - logger.info( - f"AudioHook interruption: reason={reason}, " - f"discarded={discarded_bytes or 0} bytes" - ) - - return self.create_event_message( - entity_type="interruption", - entity_data=entity_data, - ) - async def serialize(self, frame: Frame) -> str | bytes | None: """Serializes a Pipecat frame to Genesys AudioHook format. @@ -597,8 +482,6 @@ class GenesysAudioHookSerializer(FrameSerializer): data = frame.audio - self._tts_chunk_count += 1 - # Convert PCM to μ-law at 8kHz for Genesys if self._params.media_format == AudioHookMediaFormat.PCMU: serialized_data = await pcm_to_ulaw( @@ -616,6 +499,9 @@ class GenesysAudioHookSerializer(FrameSerializer): return None return bytes(serialized_data) + + elif isinstance(frame, InterruptionFrame): + return self.create_barge_in_event() elif isinstance(frame, (OutputTransportMessageFrame, OutputTransportMessageUrgentFrame)): # Pass through custom JSON messages @@ -671,7 +557,7 @@ class GenesysAudioHookSerializer(FrameSerializer): original_len = len(data) # If Genesys sends stereo audio (BOTH channels), extract only the external channel (left) - # Stereo audio is interleaved: [L0, R0, L1, R1, ...] + # Stereo audio comes interleaved: [L0, R0, L1, R1, ...] if self._params.channel == AudioHookChannel.BOTH and len(data) > 0: # For PCMU, each sample is 1 byte # Extract only bytes at even positions (left channel = external) @@ -694,7 +580,7 @@ class GenesysAudioHookSerializer(FrameSerializer): if deserialized_data is None or len(deserialized_data) == 0: return None - # Always use mono for STT + # Always use mono for STT - ElevenLabs expects single channel num_channels = 1 audio_frame = InputAudioRawFrame( @@ -704,6 +590,7 @@ class GenesysAudioHookSerializer(FrameSerializer): ) return audio_frame + async def _handle_control_message(self, message: Dict[str, Any]) -> Frame | None: """Handle a JSON control message from Genesys. @@ -735,7 +622,7 @@ class GenesysAudioHookSerializer(FrameSerializer): elif msg_type == AudioHookMessageType.UPDATE.value: return await self._handle_update(message) - + elif msg_type == AudioHookMessageType.ERROR.value: return await self._handle_error(message) @@ -743,15 +630,12 @@ class GenesysAudioHookSerializer(FrameSerializer): return await self._handle_dtmf(message) elif msg_type == "playback_started": - self._is_playing = True logger.debug("Playback started (from Genesys)") return None elif msg_type == "playback_completed": - self._is_playing = False logger.debug("Playback completed (from Genesys)") return None - else: logger.warning(f"Unknown AudioHook message type: {msg_type}") return None @@ -812,7 +696,8 @@ class GenesysAudioHookSerializer(FrameSerializer): message: The close message. Returns: - EndFrame to signal the pipeline to close. + OutputTransportMessageUrgentFrame with the closed response, + or None if no response should be sent. """ params = message.get("parameters", {}) reason = params.get("reason", "unknown") @@ -820,17 +705,11 @@ class GenesysAudioHookSerializer(FrameSerializer): logger.info(f"🔴 Genesys closed the connection: {reason}") self._is_open = False + + logger.info(f"Sending closed response to Genesys...") - # Send closed response via callback if available - if self._send_message_callback: - try: - closed_response = self.create_closed_response() - await self._send_message_callback(closed_response) - except Exception as e: - logger.error(f"Failed to send closed response: {e}") - - # Return EndFrame to close the pipeline and WebSocket - return EndFrame() + # Return as urgent frame to be sent through pipeline immediately + return OutputTransportMessageUrgentFrame(message=json.loads(self.create_closed_response())) async def _handle_ping(self, message: Dict[str, Any]) -> Frame | None: """Handle a 'ping' message from Genesys. @@ -842,20 +721,10 @@ class GenesysAudioHookSerializer(FrameSerializer): None if pong was sent directly via callback, otherwise OutputTransportMessageUrgentFrame with pong response. """ - # Create pong response - pong_response = self.create_pong_response() - # If we have a direct callback, use it for immediate response - if self._send_message_callback: - try: - await self._send_message_callback(pong_response) - logger.debug("Pong sent directly via callback") - return None - except Exception as e: - logger.error(f"Failed to send pong via callback: {e}") - - # Fallback: return as urgent frame to be sent through pipeline - return OutputTransportMessageUrgentFrame(message=json.loads(pong_response)) + logger.info(f"Sending pong response to Genesys...") + # Return as urgent frame to be sent through pipeline immediately + return OutputTransportMessageUrgentFrame(message=json.loads(self.create_pong_response())) async def _handle_pause(self, message: Dict[str, Any]) -> Frame | None: """Handle a 'pause' message from Genesys. From f94a60f38198b7ac99a9f5619562dd8ad02a361e Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Aleix=20Conchillo=20Flaqu=C3=A9?= Date: Sun, 25 Jan 2026 15:42:09 -0800 Subject: [PATCH 0192/1060] transports: fix broadcast_frame_class reference --- src/pipecat/transports/daily/transport.py | 2 +- src/pipecat/transports/smallwebrtc/transport.py | 2 +- 2 files changed, 2 insertions(+), 2 deletions(-) diff --git a/src/pipecat/transports/daily/transport.py b/src/pipecat/transports/daily/transport.py index fe106ebeb..20a0be29f 100644 --- a/src/pipecat/transports/daily/transport.py +++ b/src/pipecat/transports/daily/transport.py @@ -1733,7 +1733,7 @@ class DailyInputTransport(BaseInputTransport): message: The message data to send. sender: ID of the message sender. """ - await self.broadcast_frame_class( + await self.broadcast_frame( DailyInputTransportMessageFrame, message=message, participant_id=sender ) diff --git a/src/pipecat/transports/smallwebrtc/transport.py b/src/pipecat/transports/smallwebrtc/transport.py index bcc3c8b79..7e76771c4 100644 --- a/src/pipecat/transports/smallwebrtc/transport.py +++ b/src/pipecat/transports/smallwebrtc/transport.py @@ -698,7 +698,7 @@ class SmallWebRTCInputTransport(BaseInputTransport): message: The application message to process. """ logger.debug(f"Received app message inside SmallWebRTCInputTransport {message}") - await self.broadcast_frame_class(InputTransportMessageFrame, message=message) + await self.broadcast_frame(InputTransportMessageFrame, message=message) # Add this method similar to DailyInputTransport.request_participant_image async def request_participant_image(self, frame: UserImageRequestFrame): From 35919a84e3b1637d84ad5f519d46b20451a02947 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?G=C3=B6kmen=20G=C3=B6rgen?= Date: Sun, 11 Jan 2026 20:14:59 +0100 Subject: [PATCH 0193/1060] aic-sdk-py v2. # Conflicts: # uv.lock --- .../07zd-interruptible-aicoustics.py | 2 +- pyproject.toml | 3 +- src/pipecat/audio/filters/aic_filter.py | 19 +- src/pipecat/audio/filters/aic_filter_v2.py | 296 ++++++++++++++++++ src/pipecat/audio/utils.py | 57 ++++ src/pipecat/audio/vad/aic_vad.py | 18 +- src/pipecat/audio/vad/aic_vad_v2.py | 163 ++++++++++ 7 files changed, 541 insertions(+), 17 deletions(-) create mode 100644 src/pipecat/audio/filters/aic_filter_v2.py create mode 100644 src/pipecat/audio/vad/aic_vad_v2.py diff --git a/examples/foundational/07zd-interruptible-aicoustics.py b/examples/foundational/07zd-interruptible-aicoustics.py index 8a49e734f..7970af4a6 100644 --- a/examples/foundational/07zd-interruptible-aicoustics.py +++ b/examples/foundational/07zd-interruptible-aicoustics.py @@ -12,7 +12,7 @@ import wave from dotenv import load_dotenv from loguru import logger -from pipecat.audio.filters.aic_filter import AICFilter +from pipecat.audio.filters.aic_filter_v2 import AICFilter from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3 from pipecat.frames.frames import LLMRunFrame from pipecat.pipeline.pipeline import Pipeline diff --git a/pyproject.toml b/pyproject.toml index e99ab62bc..0f8d8c473 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -48,7 +48,8 @@ Issues = "https://github.com/pipecat-ai/pipecat/issues" Changelog = "https://github.com/pipecat-ai/pipecat/blob/main/CHANGELOG.md" [project.optional-dependencies] -aic = [ "aic-sdk~=1.2.0" ] +aic = [ "aic-sdk>=1.2.0" ] +#aic = [ "aic-sdk @ file:///Users/goedev/Workspace/aic/pipecat/aic_sdk-2.0.0-cp313-cp313-macosx_11_0_arm64.whl" ] anthropic = [ "anthropic~=0.49.0" ] assemblyai = [ "pipecat-ai[websockets-base]" ] asyncai = [ "pipecat-ai[websockets-base]" ] diff --git a/src/pipecat/audio/filters/aic_filter.py b/src/pipecat/audio/filters/aic_filter.py index e4242521b..f37543551 100644 --- a/src/pipecat/audio/filters/aic_filter.py +++ b/src/pipecat/audio/filters/aic_filter.py @@ -4,11 +4,15 @@ # SPDX-License-Identifier: BSD 2-Clause License # -"""ai-coustics AIC SDK audio filter for Pipecat. +"""ai-coustics AIC SDK audio filter for Pipecat (aic-sdk < 2.0.0). This module provides an audio filter implementation using ai-coustics' AIC SDK to enhance audio streams in real time. It mirrors the structure of other filters like the Koala filter and integrates with Pipecat's input transport pipeline. + +.. note:: + This module is compatible with aic-sdk versions < 2.0.0. + For aic-sdk >= 2.0.0, use :mod:`pipecat.audio.filters.aic_filter_v2` instead. """ from typing import List, Optional @@ -17,15 +21,14 @@ import numpy as np from loguru import logger from pipecat.audio.filters.base_audio_filter import BaseAudioFilter +from pipecat.audio.utils import check_aic_sdk_version from pipecat.frames.frames import FilterControlFrame, FilterEnableFrame -try: - # AIC SDK (https://ai-coustics.github.io/aic-sdk-py/api/) - from aic import AICModelType, AICParameter, Model -except ModuleNotFoundError as e: - logger.error(f"Exception: {e}") - logger.error("In order to use the AIC filter, you need to `pip install pipecat-ai[aic]`.") - raise Exception(f"Missing module: {e}") +# Check aic-sdk is installed and version is compatible (< 2.0.0) +check_aic_sdk_version("v1") + +# AIC SDK (https://ai-coustics.github.io/aic-sdk-py/api/) +from aic import AICModelType, AICParameter, Model class AICFilter(BaseAudioFilter): diff --git a/src/pipecat/audio/filters/aic_filter_v2.py b/src/pipecat/audio/filters/aic_filter_v2.py new file mode 100644 index 000000000..be2912107 --- /dev/null +++ b/src/pipecat/audio/filters/aic_filter_v2.py @@ -0,0 +1,296 @@ +# +# Copyright (c) 2024-2026, Daily +# +# SPDX-License-Identifier: BSD 2-Clause License +# + +"""ai-coustics AIC SDK audio filter for Pipecat (aic-sdk >= 2.0.0). + +This module provides an audio filter implementation using ai-coustics' AIC SDK to +enhance audio streams in real time. It mirrors the structure of other filters like +the Koala filter and integrates with Pipecat's input transport pipeline. + +.. note:: + This module is compatible with aic-sdk versions >= 2.0.0. + For aic-sdk < 2.0.0, use :mod:`pipecat.audio.filters.aic_filter` instead. +""" + +import os +from typing import List, Optional + +import numpy as np +from loguru import logger + +from pipecat.audio.filters.base_audio_filter import BaseAudioFilter +from pipecat.audio.utils import check_aic_sdk_version +from pipecat.frames.frames import FilterControlFrame, FilterEnableFrame + +# Check aic-sdk is installed and version is compatible (>= 2.0.0) +check_aic_sdk_version("v2") + +# AIC SDK v2 (https://ai-coustics.github.io/aic-sdk-py/api/) +import aic +from aic import Model, ProcessorAsync, ProcessorConfig, ProcessorParameter, VadParameter + + +class AICFilter(BaseAudioFilter): + """Audio filter using ai-coustics' AIC SDK v2 for real-time enhancement. + + Buffers incoming audio to the model's preferred block size and processes + planar frames in-place using float32 samples in the linear -1..+1 range. + + .. note:: + This class requires aic-sdk >= 2.0.0. + """ + + def __init__( + self, + *, + license_key: str = "", + model_id: Optional[str] = None, + model_path: Optional[str] = None, + model_download_dir: Optional[str] = None, + enhancement_level: Optional[float] = 1.0, + voice_gain: Optional[float] = 1.0, + ) -> None: + """Initialize the AIC filter. + + Args: + license_key: ai-coustics license key for authentication. + model_id: Model identifier to download from CDN. Required if model_path + is not provided. See https://artifacts.ai-coustics.io/ for available models. + model_path: Optional path to a local .aicmodel file. If provided, + model_id is ignored and no download occurs. + model_download_dir: Directory for downloading models. Defaults to + a cache directory in user's home folder. + enhancement_level: Optional overall enhancement strength (0.0..1.0). + voice_gain: Optional linear gain applied to detected speech (0.1..4.0). + + Raises: + ValueError: If neither model_id nor model_path is provided. + """ + if model_id is None and model_path is None: + raise ValueError( + "Either 'model_id' or 'model_path' must be provided. " + "See https://artifacts.ai-coustics.io/ for available models." + ) + + self._license_key = license_key + self._model_id = model_id + self._model_path = model_path + self._model_download_dir = model_download_dir or os.path.expanduser( + "~/.cache/pipecat/aic-models" + ) + + self._enhancement_level = enhancement_level + self._voice_gain = voice_gain + + self._enabled = True + self._sample_rate = 0 + self._aic_ready = False + self._frames_per_block = 0 + self._audio_buffer = bytearray() + + # v2 API objects + self._model: Optional[Model] = None + self._processor: Optional[ProcessorAsync] = None + self._processor_ctx = None + self._vad_ctx = None + + def get_vad_context(self): + """Return the VAD context once the processor exists. + + Returns: + The VadContext instance bound to the underlying processor. + Raises RuntimeError if the processor has not been initialized. + """ + if self._vad_ctx is None: + raise RuntimeError("AIC processor not initialized yet. Call start(sample_rate) first.") + return self._vad_ctx + + def create_vad_analyzer( + self, + *, + speech_hold_duration: Optional[float] = None, + sensitivity: Optional[float] = None, + ): + """Return an analyzer that will lazily instantiate the AIC VAD when ready. + + AIC VAD parameters (v2): + - speech_hold_duration: + How long VAD continues detecting after speech ends (in seconds). + Range: 0.0 .. 20x model window length, Default (SDK): 0.05s + - sensitivity: + Energy threshold sensitivity. Energy threshold = 10 ** (-sensitivity). + Range: 1.0 .. 15.0, Default (SDK): 6.0 + + Args: + speech_hold_duration: Optional speech hold duration to configure on the VAD. + If None, SDK default (0.05s) is used. + sensitivity: Optional sensitivity (energy threshold) to configure on the VAD. + Range: 1.0 .. 15.0. If None, SDK default (6.0) is used. + + Returns: + A lazily-initialized AICVADAnalyzer that will bind to the VAD context + once the filter's processor has been created (after start(sample_rate)). + """ + from pipecat.audio.vad.aic_vad_v2 import AICVADAnalyzer + + return AICVADAnalyzer( + vad_context_factory=lambda: self.get_vad_context(), + speech_hold_duration=speech_hold_duration, + sensitivity=sensitivity, + ) + + async def start(self, sample_rate: int): + """Initialize the filter with the transport's sample rate. + + Args: + sample_rate: The sample rate of the input transport in Hz. + + Returns: + None + """ + self._sample_rate = sample_rate + + try: + # Load or download model + if self._model_path: + logger.debug(f"Loading AIC model from: {self._model_path}") + self._model = Model.from_file(self._model_path) + else: + logger.debug(f"Downloading AIC model: {self._model_id}") + os.makedirs(self._model_download_dir, exist_ok=True) + model_path = await Model.download_async(self._model_id, self._model_download_dir) + logger.debug(f"Model downloaded to: {model_path}") + self._model = Model.from_file(model_path) + + # Create async processor + self._processor = ProcessorAsync(self._model, self._license_key or "") + + # Get optimal frames for this sample rate + self._frames_per_block = self._model.get_optimal_num_frames(self._sample_rate) + + # Create configuration + config = ProcessorConfig( + sample_rate=self._sample_rate, + num_channels=1, + num_frames=self._frames_per_block, + allow_variable_frames=False, + ) + + # Initialize processor + await self._processor.initialize_async(config) + + # Get contexts for parameter control and VAD + self._processor_ctx = self._processor.get_processor_context() + self._vad_ctx = self._processor.get_vad_context() + + # Apply initial parameters + if self._enhancement_level is not None: + level = float(self._enhancement_level if self._enabled else 0.0) + self._processor_ctx.set_parameter(ProcessorParameter.EnhancementLevel, level) + if self._voice_gain is not None: + self._processor_ctx.set_parameter( + ProcessorParameter.VoiceGain, float(self._voice_gain) + ) + + self._aic_ready = True + + # Log processor information + logger.debug(f"ai-coustics filter (v2) started:") + logger.debug(f" Model ID: {self._model.get_id()}") + logger.debug(f" Sample rate: {self._sample_rate} Hz") + logger.debug(f" Frames per chunk: {self._frames_per_block}") + logger.debug(f" Enhancement strength: {int((self._enhancement_level or 1.0) * 100)}%") + logger.debug(f" Optimal sample rate: {self._model.get_optimal_sample_rate()} Hz") + logger.debug( + f" Output delay: {self._processor_ctx.get_output_delay()} samples " + f"({self._processor_ctx.get_output_delay() / self._sample_rate * 1000:.2f}ms)" + ) + except Exception as e: # noqa: BLE001 - surfacing SDK initialization errors + logger.error(f"AIC model initialization failed: {e}") + self._aic_ready = False + + async def stop(self): + """Clean up the AIC processor when stopping. + + Returns: + None + """ + try: + if self._processor_ctx is not None: + self._processor_ctx.reset() + finally: + self._processor = None + self._processor_ctx = None + self._vad_ctx = None + self._model = None + self._aic_ready = False + self._audio_buffer.clear() + + async def process_frame(self, frame: FilterControlFrame): + """Process control frames to enable/disable filtering. + + Args: + frame: The control frame containing filter commands. + + Returns: + None + """ + if isinstance(frame, FilterEnableFrame): + self._enabled = frame.enable + if self._processor_ctx is not None: + try: + level = float(self._enhancement_level if self._enabled else 0.0) + self._processor_ctx.set_parameter(ProcessorParameter.EnhancementLevel, level) + except Exception as e: # noqa: BLE001 + logger.error(f"AIC set_parameter failed: {e}") + + async def filter(self, audio: bytes) -> bytes: + """Apply AIC enhancement to audio data. + + Buffers incoming audio and processes it in chunks that match the AIC + model's required block length. Returns enhanced audio data. + + Args: + audio: Raw audio data as bytes to be filtered (int16 PCM, planar). + + Returns: + Enhanced audio data as bytes (int16 PCM, planar). + """ + if not self._aic_ready or self._processor is None: + return audio + + self._audio_buffer.extend(audio) + + filtered_chunks: List[bytes] = [] + + # Number of int16 samples currently buffered + available_frames = len(self._audio_buffer) // 2 + + while available_frames >= self._frames_per_block: + # Consume exactly one block worth of frames + samples_to_consume = self._frames_per_block * 1 + bytes_to_consume = samples_to_consume * 2 + block_bytes = bytes(self._audio_buffer[:bytes_to_consume]) + + # Convert to float32 in -1..+1 range and reshape to (channels, frames) + block_i16 = np.frombuffer(block_bytes, dtype=np.int16) + block_f32 = (block_i16.astype(np.float32) / 32768.0).reshape( + (1, self._frames_per_block) + ) + + # Process via async processor; returns ndarray (same shape) + out_f32 = await self._processor.process_async(block_f32) + + # Convert back to int16 bytes + out_i16 = np.clip(out_f32 * 32768.0, -32768, 32767).astype(np.int16) + filtered_chunks.append(out_i16.reshape(-1).tobytes()) + + # Slide buffer + self._audio_buffer = self._audio_buffer[bytes_to_consume:] + available_frames = len(self._audio_buffer) // 2 + + # Do not flush incomplete frames; keep them buffered for the next call + return b"".join(filtered_chunks) diff --git a/src/pipecat/audio/utils.py b/src/pipecat/audio/utils.py index 65f451675..002375f35 100644 --- a/src/pipecat/audio/utils.py +++ b/src/pipecat/audio/utils.py @@ -12,6 +12,9 @@ various audio formats used in Pipecat pipelines. """ import audioop +from typing import Literal + +from loguru import logger import numpy as np import pyloudnorm as pyln @@ -311,3 +314,57 @@ def is_silence(pcm_bytes: bytes) -> bool: # If max value is lower than SPEAKING_THRESHOLD, consider it as silence return max_value <= SPEAKING_THRESHOLD + + +def check_aic_sdk_version(required_version: Literal["v1", "v2"]) -> None: + """Check if the aic-sdk is installed and compatible with the module. + + This function checks both that the aic-sdk is installed and that its version + is compatible with the module requirements. + + Args: + required_version: Either "v1" (for aic-sdk < 2.0.0) or "v2" (for aic-sdk >= 2.0.0). + + Raises: + ImportError: If aic-sdk is not installed or version is incompatible. + """ + try: + import aic # noqa: F401 - check if module is installed + except ModuleNotFoundError as e: + logger.error(f"Exception: {e}") + logger.error("In order to use the AIC filter, you need to `pip install pipecat-ai[aic]`.") + raise ImportError(f"Missing module: {e}") from e + + try: + from importlib.metadata import version as get_version + + aic_version = get_version("aic-sdk") + major_version = int(aic_version.split(".")[0]) + + if required_version == "v1" and major_version >= 2: + error_msg = ( + f"aic-sdk version {aic_version} detected, but aic-sdk < 2.0.0 is required. " + "Please use the v2 modules instead: " + "'from pipecat.audio.filters.aic_filter_v2 import AICFilter' or " + "'from pipecat.audio.vad.aic_vad_v2 import AICVADAnalyzer'." + ) + logger.error(error_msg) + raise ImportError(error_msg) + + if required_version == "v2" and major_version < 2: + error_msg = ( + f"aic-sdk version {aic_version} detected, but aic-sdk >= 2.0.0 is required. " + "Please update with 'pip install --upgrade aic-sdk>=2.0.0' " + "or use the v1 modules: " + "'from pipecat.audio.filters.aic_filter import AICFilter' or " + "'from pipecat.audio.vad.aic_vad import AICVADAnalyzer'." + ) + logger.error(error_msg) + raise ImportError(error_msg) + + except ImportError: + # Re-raise if it's our version mismatch error + raise + except Exception: + # If we can't determine version for other reasons, log warning and allow to proceed + logger.warning("Could not determine aic-sdk version. Proceeding anyway.") diff --git a/src/pipecat/audio/vad/aic_vad.py b/src/pipecat/audio/vad/aic_vad.py index 4907e4f55..780b33cd8 100644 --- a/src/pipecat/audio/vad/aic_vad.py +++ b/src/pipecat/audio/vad/aic_vad.py @@ -1,22 +1,26 @@ -"""AIC-integrated VAD analyzer that lazily binds to the AIC SDK backend. +"""AIC-integrated VAD analyzer that lazily binds to the AIC SDK backend (aic-sdk < 2.0.0). This analyzer queries the backend's is_speech_detected() and maps it to a float confidence (1.0/0.0). It uses 10 ms windows based on the sample rate and applies optional AIC VAD parameters (lookback_buffer_size, sensitivity) when available. + +.. note:: + This module is compatible with aic-sdk versions < 2.0.0. + For aic-sdk >= 2.0.0, use :mod:`pipecat.audio.vad.aic_vad_v2` instead. """ from typing import Any, Callable, Optional from loguru import logger +from pipecat.audio.utils import check_aic_sdk_version from pipecat.audio.vad.vad_analyzer import VADAnalyzer, VADParams -try: - from aic import AICVadParameter -except ModuleNotFoundError as e: - logger.error(f"Exception: {e}") - logger.error("In order to use the AIC filter, you need to `pip install pipecat-ai[aic]`.") - raise Exception(f"Missing module: {e}") +# Check aic-sdk is installed and version is compatible (< 2.0.0) +check_aic_sdk_version("v1") + +from aic import AICVadParameter + class AICVADAnalyzer(VADAnalyzer): diff --git a/src/pipecat/audio/vad/aic_vad_v2.py b/src/pipecat/audio/vad/aic_vad_v2.py new file mode 100644 index 000000000..2f8129a0d --- /dev/null +++ b/src/pipecat/audio/vad/aic_vad_v2.py @@ -0,0 +1,163 @@ +"""AIC-integrated VAD analyzer that lazily binds to the AIC SDK v2 backend. + +This analyzer queries the backend's is_speech_detected() and maps it to a float +confidence (1.0/0.0). It uses 10 ms windows based on the sample rate and applies +optional AIC VAD parameters (speech_hold_duration, sensitivity) when available. + +.. note:: + This module is compatible with aic-sdk versions >= 2.0.0. + For aic-sdk < 2.0.0, use :mod:`pipecat.audio.vad.aic_vad` instead. +""" + +from typing import Any, Callable, Optional + +from loguru import logger + +from pipecat.audio.utils import check_aic_sdk_version +from pipecat.audio.vad.vad_analyzer import VADAnalyzer, VADParams + +# Check aic-sdk is installed and version is compatible (>= 2.0.0) +check_aic_sdk_version("v2") + +from aic import VadParameter + + + +class AICVADAnalyzer(VADAnalyzer): + """VAD analyzer that lazily binds to the AIC VadContext via a factory. + + The analyzer can be constructed before the AIC Processor exists. Once the filter has + started and the Processor is available, the provided factory will succeed and the + VadContext will be obtained. We then use the context's is_speech_detected() state + to derive confidence values. + + AIC VAD runtime parameters (v2): + - speech_hold_duration: + Controls for how long the VAD continues to detect speech after the audio signal + no longer contains speech (in seconds). + Range: 0.0 .. 20x model window length + Default (SDK): 0.05s (50ms) + - sensitivity: + Controls the energy threshold sensitivity. Higher values make the detector + less sensitive (require more energy to count as speech). + Range: 1.0 .. 15.0 + Formula: Energy threshold = 10 ** (-sensitivity) + Default (SDK): 6.0 + + .. note:: + This class requires aic-sdk >= 2.0.0. + """ + + def __init__( + self, + *, + vad_context_factory: Optional[Callable[[], Any]] = None, + speech_hold_duration: Optional[float] = None, + sensitivity: Optional[float] = None, + ): + """Create an AIC VAD analyzer. + + Args: + vad_context_factory: + Zero-arg callable that returns the AIC VadContext. + This may raise until the filter's Processor has been created; the analyzer + will retry on set_sample_rate/first use. + speech_hold_duration: + Optional override for AIC VAD speech hold duration (in seconds). + Range: 0.0 .. 20x model window length. + If None, the SDK default (0.05s) is used. + sensitivity: + Optional override for AIC VAD sensitivity (energy threshold). + Range: 1.0 .. 15.0. Energy threshold = 10 ** (-sensitivity). + If None, the SDK default (6.0) is used. + """ + # Use fixed VAD parameters for AIC: no user override + fixed_params = VADParams(confidence=0.5, start_secs=0.0, stop_secs=0.0, min_volume=0.0) + super().__init__(sample_rate=None, params=fixed_params) + self._vad_context_factory = vad_context_factory + self._vad_ctx: Optional[Any] = None + self._pending_speech_hold_duration: Optional[float] = speech_hold_duration + self._pending_sensitivity: Optional[float] = sensitivity + + def bind_vad_context_factory(self, vad_context_factory: Callable[[], Any]): + """Attach or replace the factory post-construction.""" + self._vad_context_factory = vad_context_factory + self._ensure_vad_context_initialized() + + def _apply_vad_params(self): + """Apply optional AIC VAD parameters if available.""" + if self._vad_ctx is None or VadParameter is None: + return + try: + if self._pending_speech_hold_duration is not None: + self._vad_ctx.set_parameter( + VadParameter.SpeechHoldDuration, float(self._pending_speech_hold_duration) + ) + if self._pending_sensitivity is not None: + self._vad_ctx.set_parameter( + VadParameter.Sensitivity, float(self._pending_sensitivity) + ) + except Exception as e: # noqa: BLE001 + logger.debug(f"AIC VAD parameter application deferred/failed: {e}") + + def _ensure_vad_context_initialized(self): + if self._vad_ctx is not None: + return + if not self._vad_context_factory: + return + try: + self._vad_ctx = self._vad_context_factory() + self._apply_vad_params() + # With VAD context ready, recompute internal frame sizing + super().set_params(self._params) + logger.debug("AIC VAD context (v2) initialized in analyzer.") + except Exception as e: # noqa: BLE001 + # Filter may not be started yet; try again later + logger.debug(f"Deferring AIC VAD context initialization: {e}") + + def set_sample_rate(self, sample_rate: int): + """Set the sample rate for audio processing. + + Args: + sample_rate: Audio sample rate in Hz. + """ + # Set rate and attempt VAD context initialization once we know SR + self._sample_rate = self._init_sample_rate or sample_rate + self._ensure_vad_context_initialized() + # Ensure params are initialized even if VAD context not ready yet + try: + super().set_params(self._params) + except Exception: + pass + + def num_frames_required(self) -> int: + """Get the number of audio frames required for analysis. + + Returns: + Number of frames needed for VAD processing. + """ + # Use 10 ms windows based on sample rate + return int(self.sample_rate * 0.01) if self.sample_rate > 0 else 160 + + def voice_confidence(self, buffer: bytes) -> float: + """Calculate voice activity confidence for the given audio buffer. + + Args: + buffer: Audio buffer to analyze. + + Returns: + Voice confidence score is 0.0 or 1.0. + """ + # Ensure VAD context exists (filter might have started since last call) + self._ensure_vad_context_initialized() + if self._vad_ctx is None: + return 0.0 + + # We do not need to analyze 'buffer' here since the processor's VAD is updated + # as part of the enhancement pipeline. Simply query the boolean and map it. + try: + is_speech = self._vad_ctx.is_speech_detected() + return 1.0 if is_speech else 0.0 + except Exception as e: # noqa: BLE001 + logger.error(f"AIC VAD inference error: {e}") + return 0.0 From a0d801b65882bfe1a65ac76b953192719d3ef406 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?G=C3=B6kmen=20G=C3=B6rgen?= Date: Wed, 14 Jan 2026 17:22:38 +0100 Subject: [PATCH 0194/1060] Remove outdated AIC Filter and VAD v2 files, migrate to consolidated implementations. Added the new ACIFilter to the same module. --- .../07zd-interruptible-aicoustics.py | 13 +- pyproject.toml | 1 - src/pipecat/audio/filters/aic_filter.py | 311 +++++++++++++++++- src/pipecat/audio/filters/aic_filter_v2.py | 296 ----------------- src/pipecat/audio/utils.py | 90 ++--- src/pipecat/audio/vad/aic_vad.py | 178 +++++++++- src/pipecat/audio/vad/aic_vad_v2.py | 163 --------- uv.lock | 75 ++--- 8 files changed, 556 insertions(+), 571 deletions(-) delete mode 100644 src/pipecat/audio/filters/aic_filter_v2.py delete mode 100644 src/pipecat/audio/vad/aic_vad_v2.py diff --git a/examples/foundational/07zd-interruptible-aicoustics.py b/examples/foundational/07zd-interruptible-aicoustics.py index 7970af4a6..479ae36b5 100644 --- a/examples/foundational/07zd-interruptible-aicoustics.py +++ b/examples/foundational/07zd-interruptible-aicoustics.py @@ -12,7 +12,7 @@ import wave from dotenv import load_dotenv from loguru import logger -from pipecat.audio.filters.aic_filter_v2 import AICFilter +from pipecat.audio.filters.aic_filter import AICFilterV2 from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3 from pipecat.frames.frames import LLMRunFrame from pipecat.pipeline.pipeline import Pipeline @@ -45,11 +45,12 @@ audiobuffer = AudioBufferProcessor( ) -def _create_aic_filter() -> AICFilter: +def _create_aic_filter() -> AICFilterV2: license_key = os.getenv("AICOUSTICS_LICENSE_KEY", "") - return AICFilter( + return AICFilterV2( license_key=license_key, + model_id="quail-xxs-48khz", enhancement_level=0.5, ) @@ -62,7 +63,7 @@ transport_params = { lambda aic: DailyParams( audio_in_enabled=True, audio_out_enabled=True, - vad_analyzer=aic.create_vad_analyzer(lookback_buffer_size=6.0, sensitivity=6.0), + vad_analyzer=aic.create_vad_analyzer(speech_hold_duration=0.05, sensitivity=6.0), audio_in_filter=aic, ) )(_create_aic_filter()), @@ -70,7 +71,7 @@ transport_params = { lambda aic: FastAPIWebsocketParams( audio_in_enabled=True, audio_out_enabled=True, - vad_analyzer=aic.create_vad_analyzer(lookback_buffer_size=6.0, sensitivity=6.0), + vad_analyzer=aic.create_vad_analyzer(speech_hold_duration=0.05, sensitivity=6.0), audio_in_filter=aic, ) )(_create_aic_filter()), @@ -78,7 +79,7 @@ transport_params = { lambda aic: TransportParams( audio_in_enabled=True, audio_out_enabled=True, - vad_analyzer=aic.create_vad_analyzer(lookback_buffer_size=6.0, sensitivity=6.0), + vad_analyzer=aic.create_vad_analyzer(speech_hold_duration=0.05, sensitivity=6.0), audio_in_filter=aic, ) )(_create_aic_filter()), diff --git a/pyproject.toml b/pyproject.toml index 0f8d8c473..f209a4c64 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -49,7 +49,6 @@ Changelog = "https://github.com/pipecat-ai/pipecat/blob/main/CHANGELOG.md" [project.optional-dependencies] aic = [ "aic-sdk>=1.2.0" ] -#aic = [ "aic-sdk @ file:///Users/goedev/Workspace/aic/pipecat/aic_sdk-2.0.0-cp313-cp313-macosx_11_0_arm64.whl" ] anthropic = [ "anthropic~=0.49.0" ] assemblyai = [ "pipecat-ai[websockets-base]" ] asyncai = [ "pipecat-ai[websockets-base]" ] diff --git a/src/pipecat/audio/filters/aic_filter.py b/src/pipecat/audio/filters/aic_filter.py index f37543551..f71c09700 100644 --- a/src/pipecat/audio/filters/aic_filter.py +++ b/src/pipecat/audio/filters/aic_filter.py @@ -4,45 +4,43 @@ # SPDX-License-Identifier: BSD 2-Clause License # -"""ai-coustics AIC SDK audio filter for Pipecat (aic-sdk < 2.0.0). +"""ai-coustics AIC SDK audio filter for Pipecat. -This module provides an audio filter implementation using ai-coustics' AIC SDK to +This module provides audio filter implementations using ai-coustics' AIC SDK to enhance audio streams in real time. It mirrors the structure of other filters like the Koala filter and integrates with Pipecat's input transport pipeline. -.. note:: - This module is compatible with aic-sdk versions < 2.0.0. - For aic-sdk >= 2.0.0, use :mod:`pipecat.audio.filters.aic_filter_v2` instead. +Classes: + AICFilter: For aic-sdk < 2.0.0 (uses 'aic' module) + AICFilterV2: For aic-sdk >= 2.0.0 (uses 'aic_sdk' module) """ +import os from typing import List, Optional import numpy as np from loguru import logger from pipecat.audio.filters.base_audio_filter import BaseAudioFilter -from pipecat.audio.utils import check_aic_sdk_version from pipecat.frames.frames import FilterControlFrame, FilterEnableFrame -# Check aic-sdk is installed and version is compatible (< 2.0.0) -check_aic_sdk_version("v1") - -# AIC SDK (https://ai-coustics.github.io/aic-sdk-py/api/) -from aic import AICModelType, AICParameter, Model - class AICFilter(BaseAudioFilter): """Audio filter using ai-coustics' AIC SDK for real-time enhancement. Buffers incoming audio to the model's preferred block size and processes planar frames in-place using float32 samples in the linear -1..+1 range. + + .. note:: + This class requires aic-sdk < 2.0.0 (uses 'aic' module). + For aic-sdk >= 2.0.0, use :class:`AICFilterV2` instead. """ def __init__( self, *, license_key: str = "", - model_type: AICModelType = AICModelType.QUAIL_STT, + model_type: Optional["AICModelType"] = None, enhancement_level: Optional[float] = 1.0, voice_gain: Optional[float] = 1.0, noise_gate_enable: Optional[bool] = True, @@ -51,7 +49,7 @@ class AICFilter(BaseAudioFilter): Args: license_key: ai-coustics license key for authentication. - model_type: Model variant to load. + model_type: Model variant to load. If None, defaults to AICModelType.QUAIL_STT. enhancement_level: Optional overall enhancement strength (0.0..1.0). voice_gain: Optional linear gain applied to detected speech (0.0..4.0). noise_gate_enable: Optional enable/disable noise gate (default: True). @@ -60,8 +58,15 @@ class AICFilter(BaseAudioFilter): The `noise_gate_enable` parameter is deprecated and no longer has any effect. It will be removed in a future version. """ + from pipecat.audio.utils import check_aic_sdk_version + + check_aic_sdk_version("v1") + + # Import AIC SDK v1 types + from aic import AICModelType + self._license_key = license_key - self._model_type = model_type + self._model_type = model_type if model_type is not None else AICModelType.QUAIL_STT self._enhancement_level = enhancement_level self._voice_gain = voice_gain @@ -147,6 +152,8 @@ class AICFilter(BaseAudioFilter): Returns: None """ + from aic import AICParameter, Model + self._sample_rate = sample_rate try: @@ -208,6 +215,8 @@ class AICFilter(BaseAudioFilter): None """ if isinstance(frame, FilterEnableFrame): + from aic import AICParameter + self._enabled = frame.enable if self._aic is not None: try: @@ -263,3 +272,275 @@ class AICFilter(BaseAudioFilter): # Do not flush incomplete frames; keep them buffered for the next call return b"".join(filtered_chunks) + + +class AICFilterV2(BaseAudioFilter): + """Audio filter using ai-coustics' AIC SDK v2 for real-time enhancement. + + Buffers incoming audio to the model's preferred block size and processes + planar frames in-place using float32 samples in the linear -1..+1 range. + + .. note:: + This class requires aic-sdk >= 2.0.0 (uses 'aic_sdk' module). + For aic-sdk < 2.0.0, use :class:`AICFilter` instead. + """ + + def __init__( + self, + *, + license_key: str = "", + model_id: Optional[str] = None, + model_path: Optional[str] = None, + model_download_dir: Optional[str] = None, + enhancement_level: Optional[float] = 1.0, + voice_gain: Optional[float] = 1.0, + ) -> None: + """Initialize the AIC filter. + + Args: + license_key: ai-coustics license key for authentication. + model_id: Model identifier to download from CDN. Required if model_path + is not provided. See https://artifacts.ai-coustics.io/ for available models. + model_path: Optional path to a local .aicmodel file. If provided, + model_id is ignored and no download occurs. + model_download_dir: Directory for downloading models. Defaults to + a cache directory in user's home folder. + enhancement_level: Optional overall enhancement strength (0.0..1.0). + voice_gain: Optional linear gain applied to detected speech (0.1..4.0). + + Raises: + ValueError: If neither model_id nor model_path is provided. + """ + from pipecat.audio.utils import check_aic_sdk_version + + check_aic_sdk_version("v2") + + if model_id is None and model_path is None: + raise ValueError( + "Either 'model_id' or 'model_path' must be provided. " + "See https://artifacts.ai-coustics.io/ for available models." + ) + + self._license_key = license_key + self._model_id = model_id + self._model_path = model_path + self._model_download_dir = model_download_dir or os.path.expanduser( + "~/.cache/pipecat/aic-models" + ) + + self._enhancement_level = enhancement_level + self._voice_gain = voice_gain + + self._enabled = True + self._sample_rate = 0 + self._aic_ready = False + self._frames_per_block = 0 + self._audio_buffer = bytearray() + + # v2 API objects + self._model = None + self._processor = None + self._processor_ctx = None + self._vad_ctx = None + + def get_vad_context(self): + """Return the VAD context once the processor exists. + + Returns: + The VadContext instance bound to the underlying processor. + Raises RuntimeError if the processor has not been initialized. + """ + if self._vad_ctx is None: + raise RuntimeError("AIC processor not initialized yet. Call start(sample_rate) first.") + return self._vad_ctx + + def create_vad_analyzer( + self, + *, + speech_hold_duration: Optional[float] = None, + sensitivity: Optional[float] = None, + ): + """Return an analyzer that will lazily instantiate the AIC VAD when ready. + + AIC VAD parameters (v2): + - speech_hold_duration: + How long VAD continues detecting after speech ends (in seconds). + Range: 0.0 .. 20x model window length, Default (SDK): 0.05s + - sensitivity: + Energy threshold sensitivity. Energy threshold = 10 ** (-sensitivity). + Range: 1.0 .. 15.0, Default (SDK): 6.0 + + Args: + speech_hold_duration: Optional speech hold duration to configure on the VAD. + If None, SDK default (0.05s) is used. + sensitivity: Optional sensitivity (energy threshold) to configure on the VAD. + Range: 1.0 .. 15.0. If None, SDK default (6.0) is used. + + Returns: + A lazily-initialized AICVADAnalyzerV2 that will bind to the VAD context + once the filter's processor has been created (after start(sample_rate)). + """ + from pipecat.audio.vad.aic_vad import AICVADAnalyzerV2 + + return AICVADAnalyzerV2( + vad_context_factory=lambda: self.get_vad_context(), + speech_hold_duration=speech_hold_duration, + sensitivity=sensitivity, + ) + + async def start(self, sample_rate: int): + """Initialize the filter with the transport's sample rate. + + Args: + sample_rate: The sample rate of the input transport in Hz. + + Returns: + None + """ + from aic_sdk import Model, ProcessorAsync, ProcessorConfig, ProcessorParameter + + self._sample_rate = sample_rate + + try: + # Load or download model + if self._model_path: + logger.debug(f"Loading AIC model from: {self._model_path}") + self._model = Model.from_file(self._model_path) + else: + logger.debug(f"Downloading AIC model: {self._model_id}") + os.makedirs(self._model_download_dir, exist_ok=True) + model_path = await Model.download_async(self._model_id, self._model_download_dir) + logger.debug(f"Model downloaded to: {model_path}") + self._model = Model.from_file(model_path) + + # Create async processor + self._processor = ProcessorAsync(self._model, self._license_key or "") + + # Get optimal frames for this sample rate + self._frames_per_block = self._model.get_optimal_num_frames(self._sample_rate) + + # Create configuration + config = ProcessorConfig( + sample_rate=self._sample_rate, + num_channels=1, + num_frames=self._frames_per_block, + allow_variable_frames=False, + ) + + # Initialize processor + await self._processor.initialize_async(config) + + # Get contexts for parameter control and VAD + self._processor_ctx = self._processor.get_processor_context() + self._vad_ctx = self._processor.get_vad_context() + + # Apply initial parameters + if self._enhancement_level is not None: + level = float(self._enhancement_level if self._enabled else 0.0) + self._processor_ctx.set_parameter(ProcessorParameter.EnhancementLevel, level) + if self._voice_gain is not None: + self._processor_ctx.set_parameter( + ProcessorParameter.VoiceGain, float(self._voice_gain) + ) + + self._aic_ready = True + + # Log processor information + logger.debug(f"ai-coustics filter (v2) started:") + logger.debug(f" Model ID: {self._model.get_id()}") + logger.debug(f" Sample rate: {self._sample_rate} Hz") + logger.debug(f" Frames per chunk: {self._frames_per_block}") + logger.debug(f" Enhancement strength: {int((self._enhancement_level or 1.0) * 100)}%") + logger.debug(f" Optimal sample rate: {self._model.get_optimal_sample_rate()} Hz") + logger.debug( + f" Output delay: {self._processor_ctx.get_output_delay()} samples " + f"({self._processor_ctx.get_output_delay() / self._sample_rate * 1000:.2f}ms)" + ) + except Exception as e: # noqa: BLE001 - surfacing SDK initialization errors + logger.error(f"AIC model initialization failed: {e}") + self._aic_ready = False + + async def stop(self): + """Clean up the AIC processor when stopping. + + Returns: + None + """ + try: + if self._processor_ctx is not None: + self._processor_ctx.reset() + finally: + self._processor = None + self._processor_ctx = None + self._vad_ctx = None + self._model = None + self._aic_ready = False + self._audio_buffer.clear() + + async def process_frame(self, frame: FilterControlFrame): + """Process control frames to enable/disable filtering. + + Args: + frame: The control frame containing filter commands. + + Returns: + None + """ + if isinstance(frame, FilterEnableFrame): + from aic_sdk import ProcessorParameter + + self._enabled = frame.enable + if self._processor_ctx is not None: + try: + level = float(self._enhancement_level if self._enabled else 0.0) + self._processor_ctx.set_parameter(ProcessorParameter.EnhancementLevel, level) + except Exception as e: # noqa: BLE001 + logger.error(f"AIC set_parameter failed: {e}") + + async def filter(self, audio: bytes) -> bytes: + """Apply AIC enhancement to audio data. + + Buffers incoming audio and processes it in chunks that match the AIC + model's required block length. Returns enhanced audio data. + + Args: + audio: Raw audio data as bytes to be filtered (int16 PCM, planar). + + Returns: + Enhanced audio data as bytes (int16 PCM, planar). + """ + if not self._aic_ready or self._processor is None: + return audio + + self._audio_buffer.extend(audio) + + filtered_chunks: List[bytes] = [] + + # Number of int16 samples currently buffered + available_frames = len(self._audio_buffer) // 2 + + while available_frames >= self._frames_per_block: + # Consume exactly one block worth of frames + samples_to_consume = self._frames_per_block * 1 + bytes_to_consume = samples_to_consume * 2 + block_bytes = bytes(self._audio_buffer[:bytes_to_consume]) + + # Convert to float32 in -1..+1 range and reshape to (channels, frames) + block_i16 = np.frombuffer(block_bytes, dtype=np.int16) + block_f32 = (block_i16.astype(np.float32) / 32768.0).reshape( + (1, self._frames_per_block) + ) + + # Process via async processor; returns ndarray (same shape) + out_f32 = await self._processor.process_async(block_f32) + + # Convert back to int16 bytes + out_i16 = np.clip(out_f32 * 32768.0, -32768, 32767).astype(np.int16) + filtered_chunks.append(out_i16.reshape(-1).tobytes()) + + # Slide buffer + self._audio_buffer = self._audio_buffer[bytes_to_consume:] + available_frames = len(self._audio_buffer) // 2 + + # Do not flush incomplete frames; keep them buffered for the next call + return b"".join(filtered_chunks) diff --git a/src/pipecat/audio/filters/aic_filter_v2.py b/src/pipecat/audio/filters/aic_filter_v2.py deleted file mode 100644 index be2912107..000000000 --- a/src/pipecat/audio/filters/aic_filter_v2.py +++ /dev/null @@ -1,296 +0,0 @@ -# -# Copyright (c) 2024-2026, Daily -# -# SPDX-License-Identifier: BSD 2-Clause License -# - -"""ai-coustics AIC SDK audio filter for Pipecat (aic-sdk >= 2.0.0). - -This module provides an audio filter implementation using ai-coustics' AIC SDK to -enhance audio streams in real time. It mirrors the structure of other filters like -the Koala filter and integrates with Pipecat's input transport pipeline. - -.. note:: - This module is compatible with aic-sdk versions >= 2.0.0. - For aic-sdk < 2.0.0, use :mod:`pipecat.audio.filters.aic_filter` instead. -""" - -import os -from typing import List, Optional - -import numpy as np -from loguru import logger - -from pipecat.audio.filters.base_audio_filter import BaseAudioFilter -from pipecat.audio.utils import check_aic_sdk_version -from pipecat.frames.frames import FilterControlFrame, FilterEnableFrame - -# Check aic-sdk is installed and version is compatible (>= 2.0.0) -check_aic_sdk_version("v2") - -# AIC SDK v2 (https://ai-coustics.github.io/aic-sdk-py/api/) -import aic -from aic import Model, ProcessorAsync, ProcessorConfig, ProcessorParameter, VadParameter - - -class AICFilter(BaseAudioFilter): - """Audio filter using ai-coustics' AIC SDK v2 for real-time enhancement. - - Buffers incoming audio to the model's preferred block size and processes - planar frames in-place using float32 samples in the linear -1..+1 range. - - .. note:: - This class requires aic-sdk >= 2.0.0. - """ - - def __init__( - self, - *, - license_key: str = "", - model_id: Optional[str] = None, - model_path: Optional[str] = None, - model_download_dir: Optional[str] = None, - enhancement_level: Optional[float] = 1.0, - voice_gain: Optional[float] = 1.0, - ) -> None: - """Initialize the AIC filter. - - Args: - license_key: ai-coustics license key for authentication. - model_id: Model identifier to download from CDN. Required if model_path - is not provided. See https://artifacts.ai-coustics.io/ for available models. - model_path: Optional path to a local .aicmodel file. If provided, - model_id is ignored and no download occurs. - model_download_dir: Directory for downloading models. Defaults to - a cache directory in user's home folder. - enhancement_level: Optional overall enhancement strength (0.0..1.0). - voice_gain: Optional linear gain applied to detected speech (0.1..4.0). - - Raises: - ValueError: If neither model_id nor model_path is provided. - """ - if model_id is None and model_path is None: - raise ValueError( - "Either 'model_id' or 'model_path' must be provided. " - "See https://artifacts.ai-coustics.io/ for available models." - ) - - self._license_key = license_key - self._model_id = model_id - self._model_path = model_path - self._model_download_dir = model_download_dir or os.path.expanduser( - "~/.cache/pipecat/aic-models" - ) - - self._enhancement_level = enhancement_level - self._voice_gain = voice_gain - - self._enabled = True - self._sample_rate = 0 - self._aic_ready = False - self._frames_per_block = 0 - self._audio_buffer = bytearray() - - # v2 API objects - self._model: Optional[Model] = None - self._processor: Optional[ProcessorAsync] = None - self._processor_ctx = None - self._vad_ctx = None - - def get_vad_context(self): - """Return the VAD context once the processor exists. - - Returns: - The VadContext instance bound to the underlying processor. - Raises RuntimeError if the processor has not been initialized. - """ - if self._vad_ctx is None: - raise RuntimeError("AIC processor not initialized yet. Call start(sample_rate) first.") - return self._vad_ctx - - def create_vad_analyzer( - self, - *, - speech_hold_duration: Optional[float] = None, - sensitivity: Optional[float] = None, - ): - """Return an analyzer that will lazily instantiate the AIC VAD when ready. - - AIC VAD parameters (v2): - - speech_hold_duration: - How long VAD continues detecting after speech ends (in seconds). - Range: 0.0 .. 20x model window length, Default (SDK): 0.05s - - sensitivity: - Energy threshold sensitivity. Energy threshold = 10 ** (-sensitivity). - Range: 1.0 .. 15.0, Default (SDK): 6.0 - - Args: - speech_hold_duration: Optional speech hold duration to configure on the VAD. - If None, SDK default (0.05s) is used. - sensitivity: Optional sensitivity (energy threshold) to configure on the VAD. - Range: 1.0 .. 15.0. If None, SDK default (6.0) is used. - - Returns: - A lazily-initialized AICVADAnalyzer that will bind to the VAD context - once the filter's processor has been created (after start(sample_rate)). - """ - from pipecat.audio.vad.aic_vad_v2 import AICVADAnalyzer - - return AICVADAnalyzer( - vad_context_factory=lambda: self.get_vad_context(), - speech_hold_duration=speech_hold_duration, - sensitivity=sensitivity, - ) - - async def start(self, sample_rate: int): - """Initialize the filter with the transport's sample rate. - - Args: - sample_rate: The sample rate of the input transport in Hz. - - Returns: - None - """ - self._sample_rate = sample_rate - - try: - # Load or download model - if self._model_path: - logger.debug(f"Loading AIC model from: {self._model_path}") - self._model = Model.from_file(self._model_path) - else: - logger.debug(f"Downloading AIC model: {self._model_id}") - os.makedirs(self._model_download_dir, exist_ok=True) - model_path = await Model.download_async(self._model_id, self._model_download_dir) - logger.debug(f"Model downloaded to: {model_path}") - self._model = Model.from_file(model_path) - - # Create async processor - self._processor = ProcessorAsync(self._model, self._license_key or "") - - # Get optimal frames for this sample rate - self._frames_per_block = self._model.get_optimal_num_frames(self._sample_rate) - - # Create configuration - config = ProcessorConfig( - sample_rate=self._sample_rate, - num_channels=1, - num_frames=self._frames_per_block, - allow_variable_frames=False, - ) - - # Initialize processor - await self._processor.initialize_async(config) - - # Get contexts for parameter control and VAD - self._processor_ctx = self._processor.get_processor_context() - self._vad_ctx = self._processor.get_vad_context() - - # Apply initial parameters - if self._enhancement_level is not None: - level = float(self._enhancement_level if self._enabled else 0.0) - self._processor_ctx.set_parameter(ProcessorParameter.EnhancementLevel, level) - if self._voice_gain is not None: - self._processor_ctx.set_parameter( - ProcessorParameter.VoiceGain, float(self._voice_gain) - ) - - self._aic_ready = True - - # Log processor information - logger.debug(f"ai-coustics filter (v2) started:") - logger.debug(f" Model ID: {self._model.get_id()}") - logger.debug(f" Sample rate: {self._sample_rate} Hz") - logger.debug(f" Frames per chunk: {self._frames_per_block}") - logger.debug(f" Enhancement strength: {int((self._enhancement_level or 1.0) * 100)}%") - logger.debug(f" Optimal sample rate: {self._model.get_optimal_sample_rate()} Hz") - logger.debug( - f" Output delay: {self._processor_ctx.get_output_delay()} samples " - f"({self._processor_ctx.get_output_delay() / self._sample_rate * 1000:.2f}ms)" - ) - except Exception as e: # noqa: BLE001 - surfacing SDK initialization errors - logger.error(f"AIC model initialization failed: {e}") - self._aic_ready = False - - async def stop(self): - """Clean up the AIC processor when stopping. - - Returns: - None - """ - try: - if self._processor_ctx is not None: - self._processor_ctx.reset() - finally: - self._processor = None - self._processor_ctx = None - self._vad_ctx = None - self._model = None - self._aic_ready = False - self._audio_buffer.clear() - - async def process_frame(self, frame: FilterControlFrame): - """Process control frames to enable/disable filtering. - - Args: - frame: The control frame containing filter commands. - - Returns: - None - """ - if isinstance(frame, FilterEnableFrame): - self._enabled = frame.enable - if self._processor_ctx is not None: - try: - level = float(self._enhancement_level if self._enabled else 0.0) - self._processor_ctx.set_parameter(ProcessorParameter.EnhancementLevel, level) - except Exception as e: # noqa: BLE001 - logger.error(f"AIC set_parameter failed: {e}") - - async def filter(self, audio: bytes) -> bytes: - """Apply AIC enhancement to audio data. - - Buffers incoming audio and processes it in chunks that match the AIC - model's required block length. Returns enhanced audio data. - - Args: - audio: Raw audio data as bytes to be filtered (int16 PCM, planar). - - Returns: - Enhanced audio data as bytes (int16 PCM, planar). - """ - if not self._aic_ready or self._processor is None: - return audio - - self._audio_buffer.extend(audio) - - filtered_chunks: List[bytes] = [] - - # Number of int16 samples currently buffered - available_frames = len(self._audio_buffer) // 2 - - while available_frames >= self._frames_per_block: - # Consume exactly one block worth of frames - samples_to_consume = self._frames_per_block * 1 - bytes_to_consume = samples_to_consume * 2 - block_bytes = bytes(self._audio_buffer[:bytes_to_consume]) - - # Convert to float32 in -1..+1 range and reshape to (channels, frames) - block_i16 = np.frombuffer(block_bytes, dtype=np.int16) - block_f32 = (block_i16.astype(np.float32) / 32768.0).reshape( - (1, self._frames_per_block) - ) - - # Process via async processor; returns ndarray (same shape) - out_f32 = await self._processor.process_async(block_f32) - - # Convert back to int16 bytes - out_i16 = np.clip(out_f32 * 32768.0, -32768, 32767).astype(np.int16) - filtered_chunks.append(out_i16.reshape(-1).tobytes()) - - # Slide buffer - self._audio_buffer = self._audio_buffer[bytes_to_consume:] - available_frames = len(self._audio_buffer) // 2 - - # Do not flush incomplete frames; keep them buffered for the next call - return b"".join(filtered_chunks) diff --git a/src/pipecat/audio/utils.py b/src/pipecat/audio/utils.py index 002375f35..c61aba4dd 100644 --- a/src/pipecat/audio/utils.py +++ b/src/pipecat/audio/utils.py @@ -316,11 +316,41 @@ def is_silence(pcm_bytes: bytes) -> bool: return max_value <= SPEAKING_THRESHOLD +def is_aic_sdk_v2() -> bool: + """Detect if aic-sdk v2 is installed by checking the module name. + + In v2, the module was renamed from 'aic' to 'aic_sdk'. + + Returns: + True if aic-sdk v2 (aic_sdk module) is installed, False if v1 (aic module). + + Raises: + ImportError: If neither aic nor aic_sdk module is installed. + """ + try: + import aic_sdk # noqa: F401 + + return True + except ModuleNotFoundError: + pass + + try: + import aic # noqa: F401 + + return False + except ModuleNotFoundError: + logger.error("In order to use the AIC filter, you need to `pip install pipecat-ai[aic]`.") + raise ImportError( + "aic-sdk is not installed. Install with 'pip install pipecat-ai[aic]'." + ) + + def check_aic_sdk_version(required_version: Literal["v1", "v2"]) -> None: """Check if the aic-sdk is installed and compatible with the module. This function checks both that the aic-sdk is installed and that its version - is compatible with the module requirements. + is compatible with the module requirements. Version detection is based on + the module name: v2 uses 'aic_sdk', v1 uses 'aic'. Args: required_version: Either "v1" (for aic-sdk < 2.0.0) or "v2" (for aic-sdk >= 2.0.0). @@ -328,43 +358,25 @@ def check_aic_sdk_version(required_version: Literal["v1", "v2"]) -> None: Raises: ImportError: If aic-sdk is not installed or version is incompatible. """ - try: - import aic # noqa: F401 - check if module is installed - except ModuleNotFoundError as e: - logger.error(f"Exception: {e}") - logger.error("In order to use the AIC filter, you need to `pip install pipecat-ai[aic]`.") - raise ImportError(f"Missing module: {e}") from e + is_v2 = is_aic_sdk_v2() - try: - from importlib.metadata import version as get_version + if required_version == "v1" and is_v2: + error_msg = ( + "aic-sdk v2 (aic_sdk module) detected, but v1 (aic module) is required. " + "Please use the v2 classes instead: " + "'from pipecat.audio.filters.aic_filter import AICFilterV2' or " + "'from pipecat.audio.vad.aic_vad import AICVADAnalyzerV2'." + ) + logger.error(error_msg) + raise ImportError(error_msg) - aic_version = get_version("aic-sdk") - major_version = int(aic_version.split(".")[0]) - - if required_version == "v1" and major_version >= 2: - error_msg = ( - f"aic-sdk version {aic_version} detected, but aic-sdk < 2.0.0 is required. " - "Please use the v2 modules instead: " - "'from pipecat.audio.filters.aic_filter_v2 import AICFilter' or " - "'from pipecat.audio.vad.aic_vad_v2 import AICVADAnalyzer'." - ) - logger.error(error_msg) - raise ImportError(error_msg) - - if required_version == "v2" and major_version < 2: - error_msg = ( - f"aic-sdk version {aic_version} detected, but aic-sdk >= 2.0.0 is required. " - "Please update with 'pip install --upgrade aic-sdk>=2.0.0' " - "or use the v1 modules: " - "'from pipecat.audio.filters.aic_filter import AICFilter' or " - "'from pipecat.audio.vad.aic_vad import AICVADAnalyzer'." - ) - logger.error(error_msg) - raise ImportError(error_msg) - - except ImportError: - # Re-raise if it's our version mismatch error - raise - except Exception: - # If we can't determine version for other reasons, log warning and allow to proceed - logger.warning("Could not determine aic-sdk version. Proceeding anyway.") + if required_version == "v2" and not is_v2: + error_msg = ( + "aic-sdk v1 (aic module) detected, but v2 (aic_sdk module) is required. " + "Please update with 'pip install --upgrade aic-sdk>=2.0.0' " + "or use the v1 classes: " + "'from pipecat.audio.filters.aic_filter import AICFilter' or " + "'from pipecat.audio.vad.aic_vad import AICVADAnalyzer'." + ) + logger.error(error_msg) + raise ImportError(error_msg) diff --git a/src/pipecat/audio/vad/aic_vad.py b/src/pipecat/audio/vad/aic_vad.py index 780b33cd8..9ff19feec 100644 --- a/src/pipecat/audio/vad/aic_vad.py +++ b/src/pipecat/audio/vad/aic_vad.py @@ -1,27 +1,20 @@ -"""AIC-integrated VAD analyzer that lazily binds to the AIC SDK backend (aic-sdk < 2.0.0). +"""AIC-integrated VAD analyzer that lazily binds to the AIC SDK backend. -This analyzer queries the backend's is_speech_detected() and maps it to a float -confidence (1.0/0.0). It uses 10 ms windows based on the sample rate and applies -optional AIC VAD parameters (lookback_buffer_size, sensitivity) when available. +This module provides VAD analyzer implementations that query the AIC SDK's +is_speech_detected() and map it to a float confidence (1.0/0.0). They use +10 ms windows based on the sample rate and apply optional AIC VAD parameters. -.. note:: - This module is compatible with aic-sdk versions < 2.0.0. - For aic-sdk >= 2.0.0, use :mod:`pipecat.audio.vad.aic_vad_v2` instead. +Classes: + AICVADAnalyzer: For aic-sdk < 2.0.0 (uses 'aic' module) + AICVADAnalyzerV2: For aic-sdk >= 2.0.0 (uses 'aic_sdk' module) """ from typing import Any, Callable, Optional from loguru import logger -from pipecat.audio.utils import check_aic_sdk_version from pipecat.audio.vad.vad_analyzer import VADAnalyzer, VADParams -# Check aic-sdk is installed and version is compatible (< 2.0.0) -check_aic_sdk_version("v1") - -from aic import AICVadParameter - - class AICVADAnalyzer(VADAnalyzer): """VAD analyzer that lazily instantiates the AIC VoiceActivityDetector via a factory. @@ -45,6 +38,10 @@ class AICVADAnalyzer(VADAnalyzer): Range: 1.0 .. 15.0 Formula: Energy threshold = 10 ** (-sensitivity) Default (SDK): 6.0 + + .. note:: + This class requires aic-sdk < 2.0.0 (uses 'aic' module). + For aic-sdk >= 2.0.0, use :class:`AICVADAnalyzerV2` instead. """ def __init__( @@ -70,6 +67,10 @@ class AICVADAnalyzer(VADAnalyzer): Range: 1.0 .. 15.0. Energy threshold = 10 ** (-sensitivity). If None, the SDK default (6.0) is used. """ + from pipecat.audio.utils import check_aic_sdk_version + + check_aic_sdk_version("v1") + # Use fixed VAD parameters for AIC: no user override fixed_params = VADParams(confidence=0.5, start_secs=0.0, stop_secs=0.0, min_volume=0.0) super().__init__(sample_rate=None, params=fixed_params) @@ -85,6 +86,8 @@ class AICVADAnalyzer(VADAnalyzer): def _apply_backend_params(self): """Apply optional AIC VAD parameters if available.""" + from aic import AICVadParameter + if self._backend_vad is None or AICVadParameter is None: return try: @@ -160,3 +163,150 @@ class AICVADAnalyzer(VADAnalyzer): except Exception as e: # noqa: BLE001 logger.error(f"AIC VAD inference error: {e}") return 0.0 + + +class AICVADAnalyzerV2(VADAnalyzer): + """VAD analyzer that lazily binds to the AIC VadContext via a factory. + + The analyzer can be constructed before the AIC Processor exists. Once the filter has + started and the Processor is available, the provided factory will succeed and the + VadContext will be obtained. We then use the context's is_speech_detected() state + to derive confidence values. + + AIC VAD runtime parameters (v2): + - speech_hold_duration: + Controls for how long the VAD continues to detect speech after the audio signal + no longer contains speech (in seconds). + Range: 0.0 .. 20x model window length + Default (SDK): 0.05s (50ms) + - sensitivity: + Controls the energy threshold sensitivity. Higher values make the detector + less sensitive (require more energy to count as speech). + Range: 1.0 .. 15.0 + Formula: Energy threshold = 10 ** (-sensitivity) + Default (SDK): 6.0 + + .. note:: + This class requires aic-sdk >= 2.0.0 (uses 'aic_sdk' module). + For aic-sdk < 2.0.0, use :class:`AICVADAnalyzer` instead. + """ + + def __init__( + self, + *, + vad_context_factory: Optional[Callable[[], Any]] = None, + speech_hold_duration: Optional[float] = None, + sensitivity: Optional[float] = None, + ): + """Create an AIC VAD analyzer. + + Args: + vad_context_factory: + Zero-arg callable that returns the AIC VadContext. + This may raise until the filter's Processor has been created; the analyzer + will retry on set_sample_rate/first use. + speech_hold_duration: + Optional override for AIC VAD speech hold duration (in seconds). + Range: 0.0 .. 20x model window length. + If None, the SDK default (0.05s) is used. + sensitivity: + Optional override for AIC VAD sensitivity (energy threshold). + Range: 1.0 .. 15.0. Energy threshold = 10 ** (-sensitivity). + If None, the SDK default (6.0) is used. + """ + from pipecat.audio.utils import check_aic_sdk_version + + check_aic_sdk_version("v2") + + # Use fixed VAD parameters for AIC: no user override + fixed_params = VADParams(confidence=0.5, start_secs=0.0, stop_secs=0.0, min_volume=0.0) + super().__init__(sample_rate=None, params=fixed_params) + self._vad_context_factory = vad_context_factory + self._vad_ctx: Optional[Any] = None + self._pending_speech_hold_duration: Optional[float] = speech_hold_duration + self._pending_sensitivity: Optional[float] = sensitivity + + def bind_vad_context_factory(self, vad_context_factory: Callable[[], Any]): + """Attach or replace the factory post-construction.""" + self._vad_context_factory = vad_context_factory + self._ensure_vad_context_initialized() + + def _apply_vad_params(self): + """Apply optional AIC VAD parameters if available.""" + from aic_sdk import VadParameter + + if self._vad_ctx is None or VadParameter is None: + return + try: + if self._pending_speech_hold_duration is not None: + self._vad_ctx.set_parameter( + VadParameter.SpeechHoldDuration, float(self._pending_speech_hold_duration) + ) + if self._pending_sensitivity is not None: + self._vad_ctx.set_parameter( + VadParameter.Sensitivity, float(self._pending_sensitivity) + ) + except Exception as e: # noqa: BLE001 + logger.debug(f"AIC VAD parameter application deferred/failed: {e}") + + def _ensure_vad_context_initialized(self): + if self._vad_ctx is not None: + return + if not self._vad_context_factory: + return + try: + self._vad_ctx = self._vad_context_factory() + self._apply_vad_params() + # With VAD context ready, recompute internal frame sizing + super().set_params(self._params) + logger.debug("AIC VAD context (v2) initialized in analyzer.") + except Exception as e: # noqa: BLE001 + # Filter may not be started yet; try again later + logger.debug(f"Deferring AIC VAD context initialization: {e}") + + def set_sample_rate(self, sample_rate: int): + """Set the sample rate for audio processing. + + Args: + sample_rate: Audio sample rate in Hz. + """ + # Set rate and attempt VAD context initialization once we know SR + self._sample_rate = self._init_sample_rate or sample_rate + self._ensure_vad_context_initialized() + # Ensure params are initialized even if VAD context not ready yet + try: + super().set_params(self._params) + except Exception: + pass + + def num_frames_required(self) -> int: + """Get the number of audio frames required for analysis. + + Returns: + Number of frames needed for VAD processing. + """ + # Use 10 ms windows based on sample rate + return int(self.sample_rate * 0.01) if self.sample_rate > 0 else 160 + + def voice_confidence(self, buffer: bytes) -> float: + """Calculate voice activity confidence for the given audio buffer. + + Args: + buffer: Audio buffer to analyze. + + Returns: + Voice confidence score is 0.0 or 1.0. + """ + # Ensure VAD context exists (filter might have started since last call) + self._ensure_vad_context_initialized() + if self._vad_ctx is None: + return 0.0 + + # We do not need to analyze 'buffer' here since the processor's VAD is updated + # as part of the enhancement pipeline. Simply query the boolean and map it. + try: + is_speech = self._vad_ctx.is_speech_detected() + return 1.0 if is_speech else 0.0 + except Exception as e: # noqa: BLE001 + logger.error(f"AIC VAD inference error: {e}") + return 0.0 diff --git a/src/pipecat/audio/vad/aic_vad_v2.py b/src/pipecat/audio/vad/aic_vad_v2.py deleted file mode 100644 index 2f8129a0d..000000000 --- a/src/pipecat/audio/vad/aic_vad_v2.py +++ /dev/null @@ -1,163 +0,0 @@ -"""AIC-integrated VAD analyzer that lazily binds to the AIC SDK v2 backend. - -This analyzer queries the backend's is_speech_detected() and maps it to a float -confidence (1.0/0.0). It uses 10 ms windows based on the sample rate and applies -optional AIC VAD parameters (speech_hold_duration, sensitivity) when available. - -.. note:: - This module is compatible with aic-sdk versions >= 2.0.0. - For aic-sdk < 2.0.0, use :mod:`pipecat.audio.vad.aic_vad` instead. -""" - -from typing import Any, Callable, Optional - -from loguru import logger - -from pipecat.audio.utils import check_aic_sdk_version -from pipecat.audio.vad.vad_analyzer import VADAnalyzer, VADParams - -# Check aic-sdk is installed and version is compatible (>= 2.0.0) -check_aic_sdk_version("v2") - -from aic import VadParameter - - - -class AICVADAnalyzer(VADAnalyzer): - """VAD analyzer that lazily binds to the AIC VadContext via a factory. - - The analyzer can be constructed before the AIC Processor exists. Once the filter has - started and the Processor is available, the provided factory will succeed and the - VadContext will be obtained. We then use the context's is_speech_detected() state - to derive confidence values. - - AIC VAD runtime parameters (v2): - - speech_hold_duration: - Controls for how long the VAD continues to detect speech after the audio signal - no longer contains speech (in seconds). - Range: 0.0 .. 20x model window length - Default (SDK): 0.05s (50ms) - - sensitivity: - Controls the energy threshold sensitivity. Higher values make the detector - less sensitive (require more energy to count as speech). - Range: 1.0 .. 15.0 - Formula: Energy threshold = 10 ** (-sensitivity) - Default (SDK): 6.0 - - .. note:: - This class requires aic-sdk >= 2.0.0. - """ - - def __init__( - self, - *, - vad_context_factory: Optional[Callable[[], Any]] = None, - speech_hold_duration: Optional[float] = None, - sensitivity: Optional[float] = None, - ): - """Create an AIC VAD analyzer. - - Args: - vad_context_factory: - Zero-arg callable that returns the AIC VadContext. - This may raise until the filter's Processor has been created; the analyzer - will retry on set_sample_rate/first use. - speech_hold_duration: - Optional override for AIC VAD speech hold duration (in seconds). - Range: 0.0 .. 20x model window length. - If None, the SDK default (0.05s) is used. - sensitivity: - Optional override for AIC VAD sensitivity (energy threshold). - Range: 1.0 .. 15.0. Energy threshold = 10 ** (-sensitivity). - If None, the SDK default (6.0) is used. - """ - # Use fixed VAD parameters for AIC: no user override - fixed_params = VADParams(confidence=0.5, start_secs=0.0, stop_secs=0.0, min_volume=0.0) - super().__init__(sample_rate=None, params=fixed_params) - self._vad_context_factory = vad_context_factory - self._vad_ctx: Optional[Any] = None - self._pending_speech_hold_duration: Optional[float] = speech_hold_duration - self._pending_sensitivity: Optional[float] = sensitivity - - def bind_vad_context_factory(self, vad_context_factory: Callable[[], Any]): - """Attach or replace the factory post-construction.""" - self._vad_context_factory = vad_context_factory - self._ensure_vad_context_initialized() - - def _apply_vad_params(self): - """Apply optional AIC VAD parameters if available.""" - if self._vad_ctx is None or VadParameter is None: - return - try: - if self._pending_speech_hold_duration is not None: - self._vad_ctx.set_parameter( - VadParameter.SpeechHoldDuration, float(self._pending_speech_hold_duration) - ) - if self._pending_sensitivity is not None: - self._vad_ctx.set_parameter( - VadParameter.Sensitivity, float(self._pending_sensitivity) - ) - except Exception as e: # noqa: BLE001 - logger.debug(f"AIC VAD parameter application deferred/failed: {e}") - - def _ensure_vad_context_initialized(self): - if self._vad_ctx is not None: - return - if not self._vad_context_factory: - return - try: - self._vad_ctx = self._vad_context_factory() - self._apply_vad_params() - # With VAD context ready, recompute internal frame sizing - super().set_params(self._params) - logger.debug("AIC VAD context (v2) initialized in analyzer.") - except Exception as e: # noqa: BLE001 - # Filter may not be started yet; try again later - logger.debug(f"Deferring AIC VAD context initialization: {e}") - - def set_sample_rate(self, sample_rate: int): - """Set the sample rate for audio processing. - - Args: - sample_rate: Audio sample rate in Hz. - """ - # Set rate and attempt VAD context initialization once we know SR - self._sample_rate = self._init_sample_rate or sample_rate - self._ensure_vad_context_initialized() - # Ensure params are initialized even if VAD context not ready yet - try: - super().set_params(self._params) - except Exception: - pass - - def num_frames_required(self) -> int: - """Get the number of audio frames required for analysis. - - Returns: - Number of frames needed for VAD processing. - """ - # Use 10 ms windows based on sample rate - return int(self.sample_rate * 0.01) if self.sample_rate > 0 else 160 - - def voice_confidence(self, buffer: bytes) -> float: - """Calculate voice activity confidence for the given audio buffer. - - Args: - buffer: Audio buffer to analyze. - - Returns: - Voice confidence score is 0.0 or 1.0. - """ - # Ensure VAD context exists (filter might have started since last call) - self._ensure_vad_context_initialized() - if self._vad_ctx is None: - return 0.0 - - # We do not need to analyze 'buffer' here since the processor's VAD is updated - # as part of the enhancement pipeline. 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2001 From: =?UTF-8?q?G=C3=B6kmen=20G=C3=B6rgen?= Date: Fri, 16 Jan 2026 00:19:29 +0100 Subject: [PATCH 0196/1060] use new model id. --- examples/foundational/07zd-interruptible-aicoustics.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/examples/foundational/07zd-interruptible-aicoustics.py b/examples/foundational/07zd-interruptible-aicoustics.py index 479ae36b5..7a2d692e4 100644 --- a/examples/foundational/07zd-interruptible-aicoustics.py +++ b/examples/foundational/07zd-interruptible-aicoustics.py @@ -50,7 +50,7 @@ def _create_aic_filter() -> AICFilterV2: return AICFilterV2( license_key=license_key, - model_id="quail-xxs-48khz", + model_id="sparrow-xxs-48khz", enhancement_level=0.5, ) From a90c15362c3cd4de804bb3943f5f44226f7f755c Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?G=C3=B6kmen=20G=C3=B6rgen?= Date: Fri, 16 Jan 2026 12:31:41 +0100 Subject: [PATCH 0197/1060] drop v1 support from aic. --- pyproject.toml | 2 +- src/pipecat/audio/filters/aic_filter.py | 269 +----------------------- src/pipecat/audio/utils.py | 69 +----- src/pipecat/audio/vad/aic_vad.py | 161 +------------- 4 files changed, 12 insertions(+), 489 deletions(-) diff --git a/pyproject.toml b/pyproject.toml index f209a4c64..65a2a4bf0 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -48,7 +48,7 @@ Issues = "https://github.com/pipecat-ai/pipecat/issues" Changelog = "https://github.com/pipecat-ai/pipecat/blob/main/CHANGELOG.md" [project.optional-dependencies] -aic = [ "aic-sdk>=1.2.0" ] +aic = [ "aic-sdk>=2.0.0" ] anthropic = [ "anthropic~=0.49.0" ] assemblyai = [ "pipecat-ai[websockets-base]" ] asyncai = [ "pipecat-ai[websockets-base]" ] diff --git a/src/pipecat/audio/filters/aic_filter.py b/src/pipecat/audio/filters/aic_filter.py index f71c09700..d9d7a18a1 100644 --- a/src/pipecat/audio/filters/aic_filter.py +++ b/src/pipecat/audio/filters/aic_filter.py @@ -11,8 +11,7 @@ enhance audio streams in real time. It mirrors the structure of other filters li the Koala filter and integrates with Pipecat's input transport pipeline. Classes: - AICFilter: For aic-sdk < 2.0.0 (uses 'aic' module) - AICFilterV2: For aic-sdk >= 2.0.0 (uses 'aic_sdk' module) + AICFilter: For aic-sdk >= 2.0.0 (uses 'aic_sdk' module) """ import os @@ -31,258 +30,8 @@ class AICFilter(BaseAudioFilter): Buffers incoming audio to the model's preferred block size and processes planar frames in-place using float32 samples in the linear -1..+1 range. - .. note:: - This class requires aic-sdk < 2.0.0 (uses 'aic' module). - For aic-sdk >= 2.0.0, use :class:`AICFilterV2` instead. - """ - - def __init__( - self, - *, - license_key: str = "", - model_type: Optional["AICModelType"] = None, - enhancement_level: Optional[float] = 1.0, - voice_gain: Optional[float] = 1.0, - noise_gate_enable: Optional[bool] = True, - ) -> None: - """Initialize the AIC filter. - - Args: - license_key: ai-coustics license key for authentication. - model_type: Model variant to load. If None, defaults to AICModelType.QUAIL_STT. - enhancement_level: Optional overall enhancement strength (0.0..1.0). - voice_gain: Optional linear gain applied to detected speech (0.0..4.0). - noise_gate_enable: Optional enable/disable noise gate (default: True). - - .. deprecated:: 1.3.0 - The `noise_gate_enable` parameter is deprecated and no longer has any effect. - It will be removed in a future version. - """ - from pipecat.audio.utils import check_aic_sdk_version - - check_aic_sdk_version("v1") - - # Import AIC SDK v1 types - from aic import AICModelType - - self._license_key = license_key - self._model_type = model_type if model_type is not None else AICModelType.QUAIL_STT - - self._enhancement_level = enhancement_level - self._voice_gain = voice_gain - if noise_gate_enable is not None: - import warnings - - with warnings.catch_warnings(): - warnings.simplefilter("always") - warnings.warn( - "Parameter `noise_gate_enable` is deprecated and no longer has any effect. " - "It will be removed in a future version. Use AIC VAD instead (create_vad_analyzer()).", - DeprecationWarning, - ) - - self._noise_gate_enable = noise_gate_enable - - self._enabled = True - self._sample_rate = 0 - self._aic_ready = False - self._frames_per_block = 0 - self._audio_buffer = bytearray() - # Model will be created in start() since the API now requires sample_rate - self._aic = None - - def get_vad_factory(self): - """Return a zero-arg factory that will create the VAD once the model exists. - - Returns: - A zero-argument callable that, when invoked, returns an initialized - VoiceActivityDetector bound to the underlying AIC model. Raises a - RuntimeError if the model has not been initialized (i.e. start() - has not been called successfully). - """ - - def _factory(): - if self._aic is None: - raise RuntimeError("AIC model not initialized yet. Call start(sample_rate) first.") - return self._aic.create_vad() - - return _factory - - def create_vad_analyzer( - self, - *, - lookback_buffer_size: Optional[float] = None, - sensitivity: Optional[float] = None, - ): - """Return an analyzer that will lazily instantiate the AIC VAD when ready. - - AIC VAD parameters: - - lookback_buffer_size: - Number of window-length audio buffers used as a lookback buffer. - Higher values increase prediction stability but add latency. - Range: 1.0 .. 20.0, Default (SDK): 6.0 - - sensitivity: - Energy threshold sensitivity. Energy threshold = 10 ** (-sensitivity). - Range: 1.0 .. 15.0, Default (SDK): 6.0 - - Args: - lookback_buffer_size: Optional lookback buffer size to configure on the VAD. - Range: 1.0 .. 20.0. If None, SDK default is used. - sensitivity: Optional sensitivity (energy threshold) to configure on the VAD. - Range: 1.0 .. 15.0. If None, SDK default is used. - - Returns: - A lazily-initialized AICVADAnalyzer that will bind to the VAD backend - once the filter's model has been created (after start(sample_rate)). - """ - from pipecat.audio.vad.aic_vad import AICVADAnalyzer - - return AICVADAnalyzer( - vad_factory=self.get_vad_factory(), - lookback_buffer_size=lookback_buffer_size, - sensitivity=sensitivity, - ) - - async def start(self, sample_rate: int): - """Initialize the filter with the transport's sample rate. - - Args: - sample_rate: The sample rate of the input transport in Hz. - - Returns: - None - """ - from aic import AICParameter, Model - - self._sample_rate = sample_rate - - try: - # Create model with required runtime parameters - self._aic = Model( - model_type=self._model_type, - license_key=self._license_key or None, - sample_rate=self._sample_rate, - channels=1, - ) - self._frames_per_block = self._aic.optimal_num_frames() - - # Optional parameter configuration - if self._enhancement_level is not None: - self._aic.set_parameter( - AICParameter.ENHANCEMENT_LEVEL, - float(self._enhancement_level if self._enabled else 0.0), - ) - if self._voice_gain is not None: - self._aic.set_parameter(AICParameter.VOICE_GAIN, float(self._voice_gain)) - - self._aic_ready = True - - # Log processor information - logger.debug(f"ai-coustics filter started:") - logger.debug(f" Sample rate: {self._sample_rate} Hz") - logger.debug(f" Frames per chunk: {self._frames_per_block}") - logger.debug(f" Enhancement strength: {int(self._enhancement_level * 100)}%") - logger.debug(f" Optimal input buffer size: {self._aic.optimal_num_frames()} samples") - logger.debug(f" Optimal sample rate: {self._aic.optimal_sample_rate()} Hz") - logger.debug( - f" Current algorithmic latency: {self._aic.processing_latency() / self._sample_rate * 1000:.2f}ms" - ) - except Exception as e: # noqa: BLE001 - surfacing SDK initialization errors - logger.error(f"AIC model initialization failed: {e}") - self._aic_ready = False - - async def stop(self): - """Clean up the AIC model when stopping. - - Returns: - None - """ - try: - if self._aic is not None: - self._aic.close() - finally: - self._aic = None - self._aic_ready = False - self._audio_buffer.clear() - - async def process_frame(self, frame: FilterControlFrame): - """Process control frames to enable/disable filtering. - - Args: - frame: The control frame containing filter commands. - - Returns: - None - """ - if isinstance(frame, FilterEnableFrame): - from aic import AICParameter - - self._enabled = frame.enable - if self._aic is not None: - try: - level = float(self._enhancement_level if self._enabled else 0.0) - self._aic.set_parameter(AICParameter.ENHANCEMENT_LEVEL, level) - except Exception as e: # noqa: BLE001 - logger.error(f"AIC set_parameter failed: {e}") - - async def filter(self, audio: bytes) -> bytes: - """Apply AIC enhancement to audio data. - - Buffers incoming audio and processes it in chunks that match the AIC - model's required block length. Returns enhanced audio data. - - Args: - audio: Raw audio data as bytes to be filtered (int16 PCM, planar). - - Returns: - Enhanced audio data as bytes (int16 PCM, planar). - """ - if not self._aic_ready or self._aic is None: - return audio - - self._audio_buffer.extend(audio) - - filtered_chunks: List[bytes] = [] - - # Number of int16 samples currently buffered - available_frames = len(self._audio_buffer) // 2 - - while available_frames >= self._frames_per_block: - # Consume exactly one block worth of frames - samples_to_consume = self._frames_per_block * 1 - bytes_to_consume = samples_to_consume * 2 - block_bytes = bytes(self._audio_buffer[:bytes_to_consume]) - - # Convert to float32 in -1..+1 range and reshape to planar (channels, frames) - block_i16 = np.frombuffer(block_bytes, dtype=np.int16) - block_f32 = (block_i16.astype(np.float32) / 32768.0).reshape( - (1, self._frames_per_block) - ) - - # Process planar in-place; returns ndarray (same shape) - out_f32 = await self._aic.process_async(block_f32) - - # Convert back to int16 bytes, planar layout - out_i16 = np.clip(out_f32 * 32768.0, -32768, 32767).astype(np.int16) - filtered_chunks.append(out_i16.reshape(-1).tobytes()) - - # Slide buffer - self._audio_buffer = self._audio_buffer[bytes_to_consume:] - available_frames = len(self._audio_buffer) // 2 - - # Do not flush incomplete frames; keep them buffered for the next call - return b"".join(filtered_chunks) - - -class AICFilterV2(BaseAudioFilter): - """Audio filter using ai-coustics' AIC SDK v2 for real-time enhancement. - - Buffers incoming audio to the model's preferred block size and processes - planar frames in-place using float32 samples in the linear -1..+1 range. - .. note:: This class requires aic-sdk >= 2.0.0 (uses 'aic_sdk' module). - For aic-sdk < 2.0.0, use :class:`AICFilter` instead. """ def __init__( @@ -311,10 +60,6 @@ class AICFilterV2(BaseAudioFilter): Raises: ValueError: If neither model_id nor model_path is provided. """ - from pipecat.audio.utils import check_aic_sdk_version - - check_aic_sdk_version("v2") - if model_id is None and model_path is None: raise ValueError( "Either 'model_id' or 'model_path' must be provided. " @@ -337,7 +82,7 @@ class AICFilterV2(BaseAudioFilter): self._frames_per_block = 0 self._audio_buffer = bytearray() - # v2 API objects + # AIC SDK objects self._model = None self._processor = None self._processor_ctx = None @@ -362,7 +107,7 @@ class AICFilterV2(BaseAudioFilter): ): """Return an analyzer that will lazily instantiate the AIC VAD when ready. - AIC VAD parameters (v2): + AIC VAD parameters: - speech_hold_duration: How long VAD continues detecting after speech ends (in seconds). Range: 0.0 .. 20x model window length, Default (SDK): 0.05s @@ -377,12 +122,12 @@ class AICFilterV2(BaseAudioFilter): Range: 1.0 .. 15.0. If None, SDK default (6.0) is used. Returns: - A lazily-initialized AICVADAnalyzerV2 that will bind to the VAD context + A lazily-initialized AICVADAnalyzer that will bind to the VAD context once the filter's processor has been created (after start(sample_rate)). """ - from pipecat.audio.vad.aic_vad import AICVADAnalyzerV2 + from pipecat.audio.vad.aic_vad import AICVADAnalyzer - return AICVADAnalyzerV2( + return AICVADAnalyzer( vad_context_factory=lambda: self.get_vad_context(), speech_hold_duration=speech_hold_duration, sensitivity=sensitivity, @@ -446,7 +191,7 @@ class AICFilterV2(BaseAudioFilter): self._aic_ready = True # Log processor information - logger.debug(f"ai-coustics filter (v2) started:") + logger.debug(f"ai-coustics filter started:") logger.debug(f" Model ID: {self._model.get_id()}") logger.debug(f" Sample rate: {self._sample_rate} Hz") logger.debug(f" Frames per chunk: {self._frames_per_block}") diff --git a/src/pipecat/audio/utils.py b/src/pipecat/audio/utils.py index c61aba4dd..29fc44ea9 100644 --- a/src/pipecat/audio/utils.py +++ b/src/pipecat/audio/utils.py @@ -14,10 +14,9 @@ various audio formats used in Pipecat pipelines. import audioop from typing import Literal -from loguru import logger - import numpy as np import pyloudnorm as pyln +from loguru import logger from pipecat.audio.resamplers.base_audio_resampler import BaseAudioResampler from pipecat.audio.resamplers.soxr_resampler import SOXRAudioResampler @@ -314,69 +313,3 @@ def is_silence(pcm_bytes: bytes) -> bool: # If max value is lower than SPEAKING_THRESHOLD, consider it as silence return max_value <= SPEAKING_THRESHOLD - - -def is_aic_sdk_v2() -> bool: - """Detect if aic-sdk v2 is installed by checking the module name. - - In v2, the module was renamed from 'aic' to 'aic_sdk'. - - Returns: - True if aic-sdk v2 (aic_sdk module) is installed, False if v1 (aic module). - - Raises: - ImportError: If neither aic nor aic_sdk module is installed. - """ - try: - import aic_sdk # noqa: F401 - - return True - except ModuleNotFoundError: - pass - - try: - import aic # noqa: F401 - - return False - except ModuleNotFoundError: - logger.error("In order to use the AIC filter, you need to `pip install pipecat-ai[aic]`.") - raise ImportError( - "aic-sdk is not installed. Install with 'pip install pipecat-ai[aic]'." - ) - - -def check_aic_sdk_version(required_version: Literal["v1", "v2"]) -> None: - """Check if the aic-sdk is installed and compatible with the module. - - This function checks both that the aic-sdk is installed and that its version - is compatible with the module requirements. Version detection is based on - the module name: v2 uses 'aic_sdk', v1 uses 'aic'. - - Args: - required_version: Either "v1" (for aic-sdk < 2.0.0) or "v2" (for aic-sdk >= 2.0.0). - - Raises: - ImportError: If aic-sdk is not installed or version is incompatible. - """ - is_v2 = is_aic_sdk_v2() - - if required_version == "v1" and is_v2: - error_msg = ( - "aic-sdk v2 (aic_sdk module) detected, but v1 (aic module) is required. " - "Please use the v2 classes instead: " - "'from pipecat.audio.filters.aic_filter import AICFilterV2' or " - "'from pipecat.audio.vad.aic_vad import AICVADAnalyzerV2'." - ) - logger.error(error_msg) - raise ImportError(error_msg) - - if required_version == "v2" and not is_v2: - error_msg = ( - "aic-sdk v1 (aic module) detected, but v2 (aic_sdk module) is required. " - "Please update with 'pip install --upgrade aic-sdk>=2.0.0' " - "or use the v1 classes: " - "'from pipecat.audio.filters.aic_filter import AICFilter' or " - "'from pipecat.audio.vad.aic_vad import AICVADAnalyzer'." - ) - logger.error(error_msg) - raise ImportError(error_msg) diff --git a/src/pipecat/audio/vad/aic_vad.py b/src/pipecat/audio/vad/aic_vad.py index 9ff19feec..05b576ce8 100644 --- a/src/pipecat/audio/vad/aic_vad.py +++ b/src/pipecat/audio/vad/aic_vad.py @@ -5,8 +5,7 @@ is_speech_detected() and map it to a float confidence (1.0/0.0). They use 10 ms windows based on the sample rate and apply optional AIC VAD parameters. Classes: - AICVADAnalyzer: For aic-sdk < 2.0.0 (uses 'aic' module) - AICVADAnalyzerV2: For aic-sdk >= 2.0.0 (uses 'aic_sdk' module) + AICVADAnalyzer: For aic-sdk >= 2.0.0 (uses 'aic_sdk' module) """ from typing import Any, Callable, Optional @@ -17,155 +16,6 @@ from pipecat.audio.vad.vad_analyzer import VADAnalyzer, VADParams class AICVADAnalyzer(VADAnalyzer): - """VAD analyzer that lazily instantiates the AIC VoiceActivityDetector via a factory. - - The analyzer can be constructed before the AIC Model exists. Once the filter has - started and the Model is available, the provided factory will succeed and the - backend VAD will be created. We then switch to single-sample updates where - num_frames_required() returns 1 and confidence is derived from the backend's - boolean is_speech_detected() state. - - AIC VAD runtime parameters: - - lookback_buffer_size: - Controls the lookback buffer size used by the VAD, i.e. the number of - window-length audio buffers used as a lookback buffer. Larger values improve - stability but increase latency. - Range: 1.0 .. 20.0 - Default (SDK): 6.0 - - sensitivity: - Controls the energy threshold sensitivity. Higher values make the detector - less sensitive (require more energy to count as speech). - Range: 1.0 .. 15.0 - Formula: Energy threshold = 10 ** (-sensitivity) - Default (SDK): 6.0 - - .. note:: - This class requires aic-sdk < 2.0.0 (uses 'aic' module). - For aic-sdk >= 2.0.0, use :class:`AICVADAnalyzerV2` instead. - """ - - def __init__( - self, - *, - vad_factory: Optional[Callable[[], Any]] = None, - lookback_buffer_size: Optional[float] = None, - sensitivity: Optional[float] = None, - ): - """Create an AIC VAD analyzer. - - Args: - vad_factory: - Zero-arg callable that returns an initialized AIC VoiceActivityDetector. - This may raise until the filter's Model has been created; the analyzer - will retry on set_sample_rate/first use. - lookback_buffer_size: - Optional override for AIC VAD lookback buffer size. - Range: 1.0 .. 20.0. Larger values increase stability at the cost of latency. - If None, the SDK default (6.0) is used. - sensitivity: - Optional override for AIC VAD sensitivity (energy threshold). - Range: 1.0 .. 15.0. Energy threshold = 10 ** (-sensitivity). - If None, the SDK default (6.0) is used. - """ - from pipecat.audio.utils import check_aic_sdk_version - - check_aic_sdk_version("v1") - - # Use fixed VAD parameters for AIC: no user override - fixed_params = VADParams(confidence=0.5, start_secs=0.0, stop_secs=0.0, min_volume=0.0) - super().__init__(sample_rate=None, params=fixed_params) - self._vad_factory = vad_factory - self._backend_vad: Optional[Any] = None - self._pending_lookback: Optional[float] = lookback_buffer_size - self._pending_sensitivity: Optional[float] = sensitivity - - def bind_vad_factory(self, vad_factory: Callable[[], Any]): - """Attach or replace the factory post-construction.""" - self._vad_factory = vad_factory - self._ensure_backend_initialized() - - def _apply_backend_params(self): - """Apply optional AIC VAD parameters if available.""" - from aic import AICVadParameter - - if self._backend_vad is None or AICVadParameter is None: - return - try: - if self._pending_lookback is not None: - self._backend_vad.set_parameter( - AICVadParameter.LOOKBACK_BUFFER_SIZE, float(self._pending_lookback) - ) - if self._pending_sensitivity is not None: - self._backend_vad.set_parameter( - AICVadParameter.SENSITIVITY, float(self._pending_sensitivity) - ) - except Exception as e: # noqa: BLE001 - logger.debug(f"AIC VAD parameter application deferred/failed: {e}") - - def _ensure_backend_initialized(self): - if self._backend_vad is not None: - return - if not self._vad_factory: - return - try: - self._backend_vad = self._vad_factory() - self._apply_backend_params() - # With backend ready, recompute internal frame sizing - super().set_params(self._params) - logger.debug("AIC VAD backend initialized in analyzer.") - except Exception as e: # noqa: BLE001 - # Filter may not be started yet; try again later - logger.debug(f"Deferring AIC VAD backend initialization: {e}") - - def set_sample_rate(self, sample_rate: int): - """Set the sample rate for audio processing. - - Args: - sample_rate: Audio sample rate in Hz. - """ - # Set rate and attempt backend initialization once we know SR - self._sample_rate = self._init_sample_rate or sample_rate - self._ensure_backend_initialized() - # Ensure params are initialized even if backend not ready yet - try: - super().set_params(self._params) - except Exception: - pass - - def num_frames_required(self) -> int: - """Get the number of audio frames required for analysis. - - Returns: - Number of frames needed for VAD processing. - """ - # Use 10 ms windows based on sample rate - return int(self.sample_rate * 0.01) if self.sample_rate > 0 else 160 - - def voice_confidence(self, buffer: bytes) -> float: - """Calculate voice activity confidence for the given audio buffer. - - Args: - buffer: Audio buffer to analyze. - - Returns: - Voice confidence score is 0.0 or 1.0. - """ - # Ensure backend exists (filter might have started since last call) - self._ensure_backend_initialized() - if self._backend_vad is None: - return 0.0 - - # We do not need to analyze 'buffer' here since the model's VAD is updated - # as part of the enhancement pipeline. Simply query the boolean and map it. - try: - is_speech = self._backend_vad.is_speech_detected() - return 1.0 if is_speech else 0.0 - except Exception as e: # noqa: BLE001 - logger.error(f"AIC VAD inference error: {e}") - return 0.0 - - -class AICVADAnalyzerV2(VADAnalyzer): """VAD analyzer that lazily binds to the AIC VadContext via a factory. The analyzer can be constructed before the AIC Processor exists. Once the filter has @@ -173,7 +23,7 @@ class AICVADAnalyzerV2(VADAnalyzer): VadContext will be obtained. We then use the context's is_speech_detected() state to derive confidence values. - AIC VAD runtime parameters (v2): + AIC VAD runtime parameters: - speech_hold_duration: Controls for how long the VAD continues to detect speech after the audio signal no longer contains speech (in seconds). @@ -188,7 +38,6 @@ class AICVADAnalyzerV2(VADAnalyzer): .. note:: This class requires aic-sdk >= 2.0.0 (uses 'aic_sdk' module). - For aic-sdk < 2.0.0, use :class:`AICVADAnalyzer` instead. """ def __init__( @@ -214,10 +63,6 @@ class AICVADAnalyzerV2(VADAnalyzer): Range: 1.0 .. 15.0. Energy threshold = 10 ** (-sensitivity). If None, the SDK default (6.0) is used. """ - from pipecat.audio.utils import check_aic_sdk_version - - check_aic_sdk_version("v2") - # Use fixed VAD parameters for AIC: no user override fixed_params = VADParams(confidence=0.5, start_secs=0.0, stop_secs=0.0, min_volume=0.0) super().__init__(sample_rate=None, params=fixed_params) @@ -259,7 +104,7 @@ class AICVADAnalyzerV2(VADAnalyzer): self._apply_vad_params() # With VAD context ready, recompute internal frame sizing super().set_params(self._params) - logger.debug("AIC VAD context (v2) initialized in analyzer.") + logger.debug("AIC VAD context initialized in analyzer.") except Exception as e: # noqa: BLE001 # Filter may not be started yet; try again later logger.debug(f"Deferring AIC VAD context initialization: {e}") From 2a927189d93b0effd0d9b0946cd7af3ed9795587 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?G=C3=B6kmen=20G=C3=B6rgen?= Date: Fri, 16 Jan 2026 12:37:59 +0100 Subject: [PATCH 0198/1060] reorganize imports. --- src/pipecat/audio/filters/aic_filter.py | 8 ++------ 1 file changed, 2 insertions(+), 6 deletions(-) diff --git a/src/pipecat/audio/filters/aic_filter.py b/src/pipecat/audio/filters/aic_filter.py index d9d7a18a1..a65be0db9 100644 --- a/src/pipecat/audio/filters/aic_filter.py +++ b/src/pipecat/audio/filters/aic_filter.py @@ -18,9 +18,11 @@ import os from typing import List, Optional import numpy as np +from aic_sdk import Model, ProcessorAsync, ProcessorConfig, ProcessorParameter from loguru import logger from pipecat.audio.filters.base_audio_filter import BaseAudioFilter +from pipecat.audio.vad.aic_vad import AICVADAnalyzer from pipecat.frames.frames import FilterControlFrame, FilterEnableFrame @@ -125,8 +127,6 @@ class AICFilter(BaseAudioFilter): A lazily-initialized AICVADAnalyzer that will bind to the VAD context once the filter's processor has been created (after start(sample_rate)). """ - from pipecat.audio.vad.aic_vad import AICVADAnalyzer - return AICVADAnalyzer( vad_context_factory=lambda: self.get_vad_context(), speech_hold_duration=speech_hold_duration, @@ -142,8 +142,6 @@ class AICFilter(BaseAudioFilter): Returns: None """ - from aic_sdk import Model, ProcessorAsync, ProcessorConfig, ProcessorParameter - self._sample_rate = sample_rate try: @@ -232,8 +230,6 @@ class AICFilter(BaseAudioFilter): None """ if isinstance(frame, FilterEnableFrame): - from aic_sdk import ProcessorParameter - self._enabled = frame.enable if self._processor_ctx is not None: try: From a13380b5746e8d0d7f257915caae3cf459592653 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?G=C3=B6kmen=20G=C3=B6rgen?= Date: Fri, 16 Jan 2026 12:53:15 +0100 Subject: [PATCH 0199/1060] clean up unused imports in audio utils. --- src/pipecat/audio/utils.py | 2 -- 1 file changed, 2 deletions(-) diff --git a/src/pipecat/audio/utils.py b/src/pipecat/audio/utils.py index 29fc44ea9..65f451675 100644 --- a/src/pipecat/audio/utils.py +++ b/src/pipecat/audio/utils.py @@ -12,11 +12,9 @@ various audio formats used in Pipecat pipelines. """ import audioop -from typing import Literal import numpy as np import pyloudnorm as pyln -from loguru import logger from pipecat.audio.resamplers.base_audio_resampler import BaseAudioResampler from pipecat.audio.resamplers.soxr_resampler import SOXRAudioResampler From 61a230ec53cd26b37ad8543b8b5b78abc1899646 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?G=C3=B6kmen=20G=C3=B6rgen?= Date: Mon, 19 Jan 2026 13:56:36 +0100 Subject: [PATCH 0200/1060] Update src/pipecat/audio/filters/aic_filter.py Co-authored-by: Stephan Eckes --- src/pipecat/audio/filters/aic_filter.py | 16 ++++------------ 1 file changed, 4 insertions(+), 12 deletions(-) diff --git a/src/pipecat/audio/filters/aic_filter.py b/src/pipecat/audio/filters/aic_filter.py index a65be0db9..cb5b0e0ce 100644 --- a/src/pipecat/audio/filters/aic_filter.py +++ b/src/pipecat/audio/filters/aic_filter.py @@ -156,22 +156,14 @@ class AICFilter(BaseAudioFilter): logger.debug(f"Model downloaded to: {model_path}") self._model = Model.from_file(model_path) - # Create async processor - self._processor = ProcessorAsync(self._model, self._license_key or "") - - # Get optimal frames for this sample rate - self._frames_per_block = self._model.get_optimal_num_frames(self._sample_rate) - # Create configuration - config = ProcessorConfig( + config = ProcessorConfig.optimal( + self._model, sample_rate=self._sample_rate, - num_channels=1, - num_frames=self._frames_per_block, - allow_variable_frames=False, ) - # Initialize processor - await self._processor.initialize_async(config) + # Create async processor + self._processor = ProcessorAsync(self._model, self._license_key or "", config) # Get contexts for parameter control and VAD self._processor_ctx = self._processor.get_processor_context() From a1cc88a233d82838d6a394a9ee507e0e9aca816b Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?G=C3=B6kmen=20G=C3=B6rgen?= Date: Mon, 19 Jan 2026 15:12:28 +0100 Subject: [PATCH 0201/1060] Update src/pipecat/audio/filters/aic_filter.py Co-authored-by: Tobias <76444201+Fl1tzi@users.noreply.github.com> --- src/pipecat/audio/filters/aic_filter.py | 10 +++++++--- 1 file changed, 7 insertions(+), 3 deletions(-) diff --git a/src/pipecat/audio/filters/aic_filter.py b/src/pipecat/audio/filters/aic_filter.py index cb5b0e0ce..d4de454b2 100644 --- a/src/pipecat/audio/filters/aic_filter.py +++ b/src/pipecat/audio/filters/aic_filter.py @@ -260,9 +260,13 @@ class AICFilter(BaseAudioFilter): # Convert to float32 in -1..+1 range and reshape to (channels, frames) block_i16 = np.frombuffer(block_bytes, dtype=np.int16) - block_f32 = (block_i16.astype(np.float32) / 32768.0).reshape( - (1, self._frames_per_block) - ) + # Convert to float32 and normalize + block_f32 = block_i16.astype(np.float32) + + block_f32 *= (1.0 / 32768.0) + + # Reshape to (1, frames) for AIC SDK + block_f32 = block_f32.reshape((1, self._frames_per_block)) # Process via async processor; returns ndarray (same shape) out_f32 = await self._processor.process_async(block_f32) From 4e85e81d9b440cc3f7bbebfc1a6f105c4e4740e5 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?G=C3=B6kmen=20G=C3=B6rgen?= Date: Mon, 19 Jan 2026 15:12:37 +0100 Subject: [PATCH 0202/1060] Update src/pipecat/audio/filters/aic_filter.py Co-authored-by: Tobias <76444201+Fl1tzi@users.noreply.github.com> --- src/pipecat/audio/filters/aic_filter.py | 7 ++++++- 1 file changed, 6 insertions(+), 1 deletion(-) diff --git a/src/pipecat/audio/filters/aic_filter.py b/src/pipecat/audio/filters/aic_filter.py index d4de454b2..14b95c92d 100644 --- a/src/pipecat/audio/filters/aic_filter.py +++ b/src/pipecat/audio/filters/aic_filter.py @@ -272,7 +272,12 @@ class AICFilter(BaseAudioFilter): out_f32 = await self._processor.process_async(block_f32) # Convert back to int16 bytes - out_i16 = np.clip(out_f32 * 32768.0, -32768, 32767).astype(np.int16) + # Denormalize and convert back to int16 + out_f32 *= 32768.0 + + # In-place clip to valid int16 range (-32768 to 32767) + np.clip(out_f32, -32768.0, 32767, out=out_f32) + out_i16 = out_f32.astype(dtype) filtered_chunks.append(out_i16.reshape(-1).tobytes()) # Slide buffer From ec17dc66267c3a45d43853ae1f42c2465264a610 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?G=C3=B6kmen=20G=C3=B6rgen?= Date: Sun, 11 Jan 2026 20:14:59 +0100 Subject: [PATCH 0203/1060] aic-sdk-py v2. # Conflicts: # uv.lock # Conflicts: # examples/foundational/07zd-interruptible-aicoustics.py # pyproject.toml # src/pipecat/audio/filters/aic_filter.py # src/pipecat/audio/vad/aic_vad.py --- src/pipecat/audio/filters/aic_filter_v2.py | 296 +++++++++++++++++++++ src/pipecat/audio/utils.py | 57 ++++ src/pipecat/audio/vad/aic_vad_v2.py | 163 ++++++++++++ 3 files changed, 516 insertions(+) create mode 100644 src/pipecat/audio/filters/aic_filter_v2.py create mode 100644 src/pipecat/audio/vad/aic_vad_v2.py diff --git a/src/pipecat/audio/filters/aic_filter_v2.py b/src/pipecat/audio/filters/aic_filter_v2.py new file mode 100644 index 000000000..be2912107 --- /dev/null +++ b/src/pipecat/audio/filters/aic_filter_v2.py @@ -0,0 +1,296 @@ +# +# Copyright (c) 2024-2026, Daily +# +# SPDX-License-Identifier: BSD 2-Clause License +# + +"""ai-coustics AIC SDK audio filter for Pipecat (aic-sdk >= 2.0.0). + +This module provides an audio filter implementation using ai-coustics' AIC SDK to +enhance audio streams in real time. It mirrors the structure of other filters like +the Koala filter and integrates with Pipecat's input transport pipeline. + +.. note:: + This module is compatible with aic-sdk versions >= 2.0.0. + For aic-sdk < 2.0.0, use :mod:`pipecat.audio.filters.aic_filter` instead. +""" + +import os +from typing import List, Optional + +import numpy as np +from loguru import logger + +from pipecat.audio.filters.base_audio_filter import BaseAudioFilter +from pipecat.audio.utils import check_aic_sdk_version +from pipecat.frames.frames import FilterControlFrame, FilterEnableFrame + +# Check aic-sdk is installed and version is compatible (>= 2.0.0) +check_aic_sdk_version("v2") + +# AIC SDK v2 (https://ai-coustics.github.io/aic-sdk-py/api/) +import aic +from aic import Model, ProcessorAsync, ProcessorConfig, ProcessorParameter, VadParameter + + +class AICFilter(BaseAudioFilter): + """Audio filter using ai-coustics' AIC SDK v2 for real-time enhancement. + + Buffers incoming audio to the model's preferred block size and processes + planar frames in-place using float32 samples in the linear -1..+1 range. + + .. note:: + This class requires aic-sdk >= 2.0.0. + """ + + def __init__( + self, + *, + license_key: str = "", + model_id: Optional[str] = None, + model_path: Optional[str] = None, + model_download_dir: Optional[str] = None, + enhancement_level: Optional[float] = 1.0, + voice_gain: Optional[float] = 1.0, + ) -> None: + """Initialize the AIC filter. + + Args: + license_key: ai-coustics license key for authentication. + model_id: Model identifier to download from CDN. Required if model_path + is not provided. See https://artifacts.ai-coustics.io/ for available models. + model_path: Optional path to a local .aicmodel file. If provided, + model_id is ignored and no download occurs. + model_download_dir: Directory for downloading models. Defaults to + a cache directory in user's home folder. + enhancement_level: Optional overall enhancement strength (0.0..1.0). + voice_gain: Optional linear gain applied to detected speech (0.1..4.0). + + Raises: + ValueError: If neither model_id nor model_path is provided. + """ + if model_id is None and model_path is None: + raise ValueError( + "Either 'model_id' or 'model_path' must be provided. " + "See https://artifacts.ai-coustics.io/ for available models." + ) + + self._license_key = license_key + self._model_id = model_id + self._model_path = model_path + self._model_download_dir = model_download_dir or os.path.expanduser( + "~/.cache/pipecat/aic-models" + ) + + self._enhancement_level = enhancement_level + self._voice_gain = voice_gain + + self._enabled = True + self._sample_rate = 0 + self._aic_ready = False + self._frames_per_block = 0 + self._audio_buffer = bytearray() + + # v2 API objects + self._model: Optional[Model] = None + self._processor: Optional[ProcessorAsync] = None + self._processor_ctx = None + self._vad_ctx = None + + def get_vad_context(self): + """Return the VAD context once the processor exists. + + Returns: + The VadContext instance bound to the underlying processor. + Raises RuntimeError if the processor has not been initialized. + """ + if self._vad_ctx is None: + raise RuntimeError("AIC processor not initialized yet. Call start(sample_rate) first.") + return self._vad_ctx + + def create_vad_analyzer( + self, + *, + speech_hold_duration: Optional[float] = None, + sensitivity: Optional[float] = None, + ): + """Return an analyzer that will lazily instantiate the AIC VAD when ready. + + AIC VAD parameters (v2): + - speech_hold_duration: + How long VAD continues detecting after speech ends (in seconds). + Range: 0.0 .. 20x model window length, Default (SDK): 0.05s + - sensitivity: + Energy threshold sensitivity. Energy threshold = 10 ** (-sensitivity). + Range: 1.0 .. 15.0, Default (SDK): 6.0 + + Args: + speech_hold_duration: Optional speech hold duration to configure on the VAD. + If None, SDK default (0.05s) is used. + sensitivity: Optional sensitivity (energy threshold) to configure on the VAD. + Range: 1.0 .. 15.0. If None, SDK default (6.0) is used. + + Returns: + A lazily-initialized AICVADAnalyzer that will bind to the VAD context + once the filter's processor has been created (after start(sample_rate)). + """ + from pipecat.audio.vad.aic_vad_v2 import AICVADAnalyzer + + return AICVADAnalyzer( + vad_context_factory=lambda: self.get_vad_context(), + speech_hold_duration=speech_hold_duration, + sensitivity=sensitivity, + ) + + async def start(self, sample_rate: int): + """Initialize the filter with the transport's sample rate. + + Args: + sample_rate: The sample rate of the input transport in Hz. + + Returns: + None + """ + self._sample_rate = sample_rate + + try: + # Load or download model + if self._model_path: + logger.debug(f"Loading AIC model from: {self._model_path}") + self._model = Model.from_file(self._model_path) + else: + logger.debug(f"Downloading AIC model: {self._model_id}") + os.makedirs(self._model_download_dir, exist_ok=True) + model_path = await Model.download_async(self._model_id, self._model_download_dir) + logger.debug(f"Model downloaded to: {model_path}") + self._model = Model.from_file(model_path) + + # Create async processor + self._processor = ProcessorAsync(self._model, self._license_key or "") + + # Get optimal frames for this sample rate + self._frames_per_block = self._model.get_optimal_num_frames(self._sample_rate) + + # Create configuration + config = ProcessorConfig( + sample_rate=self._sample_rate, + num_channels=1, + num_frames=self._frames_per_block, + allow_variable_frames=False, + ) + + # Initialize processor + await self._processor.initialize_async(config) + + # Get contexts for parameter control and VAD + self._processor_ctx = self._processor.get_processor_context() + self._vad_ctx = self._processor.get_vad_context() + + # Apply initial parameters + if self._enhancement_level is not None: + level = float(self._enhancement_level if self._enabled else 0.0) + self._processor_ctx.set_parameter(ProcessorParameter.EnhancementLevel, level) + if self._voice_gain is not None: + self._processor_ctx.set_parameter( + ProcessorParameter.VoiceGain, float(self._voice_gain) + ) + + self._aic_ready = True + + # Log processor information + logger.debug(f"ai-coustics filter (v2) started:") + logger.debug(f" Model ID: {self._model.get_id()}") + logger.debug(f" Sample rate: {self._sample_rate} Hz") + logger.debug(f" Frames per chunk: {self._frames_per_block}") + logger.debug(f" Enhancement strength: {int((self._enhancement_level or 1.0) * 100)}%") + logger.debug(f" Optimal sample rate: {self._model.get_optimal_sample_rate()} Hz") + logger.debug( + f" Output delay: {self._processor_ctx.get_output_delay()} samples " + f"({self._processor_ctx.get_output_delay() / self._sample_rate * 1000:.2f}ms)" + ) + except Exception as e: # noqa: BLE001 - surfacing SDK initialization errors + logger.error(f"AIC model initialization failed: {e}") + self._aic_ready = False + + async def stop(self): + """Clean up the AIC processor when stopping. + + Returns: + None + """ + try: + if self._processor_ctx is not None: + self._processor_ctx.reset() + finally: + self._processor = None + self._processor_ctx = None + self._vad_ctx = None + self._model = None + self._aic_ready = False + self._audio_buffer.clear() + + async def process_frame(self, frame: FilterControlFrame): + """Process control frames to enable/disable filtering. + + Args: + frame: The control frame containing filter commands. + + Returns: + None + """ + if isinstance(frame, FilterEnableFrame): + self._enabled = frame.enable + if self._processor_ctx is not None: + try: + level = float(self._enhancement_level if self._enabled else 0.0) + self._processor_ctx.set_parameter(ProcessorParameter.EnhancementLevel, level) + except Exception as e: # noqa: BLE001 + logger.error(f"AIC set_parameter failed: {e}") + + async def filter(self, audio: bytes) -> bytes: + """Apply AIC enhancement to audio data. + + Buffers incoming audio and processes it in chunks that match the AIC + model's required block length. Returns enhanced audio data. + + Args: + audio: Raw audio data as bytes to be filtered (int16 PCM, planar). + + Returns: + Enhanced audio data as bytes (int16 PCM, planar). + """ + if not self._aic_ready or self._processor is None: + return audio + + self._audio_buffer.extend(audio) + + filtered_chunks: List[bytes] = [] + + # Number of int16 samples currently buffered + available_frames = len(self._audio_buffer) // 2 + + while available_frames >= self._frames_per_block: + # Consume exactly one block worth of frames + samples_to_consume = self._frames_per_block * 1 + bytes_to_consume = samples_to_consume * 2 + block_bytes = bytes(self._audio_buffer[:bytes_to_consume]) + + # Convert to float32 in -1..+1 range and reshape to (channels, frames) + block_i16 = np.frombuffer(block_bytes, dtype=np.int16) + block_f32 = (block_i16.astype(np.float32) / 32768.0).reshape( + (1, self._frames_per_block) + ) + + # Process via async processor; returns ndarray (same shape) + out_f32 = await self._processor.process_async(block_f32) + + # Convert back to int16 bytes + out_i16 = np.clip(out_f32 * 32768.0, -32768, 32767).astype(np.int16) + filtered_chunks.append(out_i16.reshape(-1).tobytes()) + + # Slide buffer + self._audio_buffer = self._audio_buffer[bytes_to_consume:] + available_frames = len(self._audio_buffer) // 2 + + # Do not flush incomplete frames; keep them buffered for the next call + return b"".join(filtered_chunks) diff --git a/src/pipecat/audio/utils.py b/src/pipecat/audio/utils.py index 65f451675..002375f35 100644 --- a/src/pipecat/audio/utils.py +++ b/src/pipecat/audio/utils.py @@ -12,6 +12,9 @@ various audio formats used in Pipecat pipelines. """ import audioop +from typing import Literal + +from loguru import logger import numpy as np import pyloudnorm as pyln @@ -311,3 +314,57 @@ def is_silence(pcm_bytes: bytes) -> bool: # If max value is lower than SPEAKING_THRESHOLD, consider it as silence return max_value <= SPEAKING_THRESHOLD + + +def check_aic_sdk_version(required_version: Literal["v1", "v2"]) -> None: + """Check if the aic-sdk is installed and compatible with the module. + + This function checks both that the aic-sdk is installed and that its version + is compatible with the module requirements. + + Args: + required_version: Either "v1" (for aic-sdk < 2.0.0) or "v2" (for aic-sdk >= 2.0.0). + + Raises: + ImportError: If aic-sdk is not installed or version is incompatible. + """ + try: + import aic # noqa: F401 - check if module is installed + except ModuleNotFoundError as e: + logger.error(f"Exception: {e}") + logger.error("In order to use the AIC filter, you need to `pip install pipecat-ai[aic]`.") + raise ImportError(f"Missing module: {e}") from e + + try: + from importlib.metadata import version as get_version + + aic_version = get_version("aic-sdk") + major_version = int(aic_version.split(".")[0]) + + if required_version == "v1" and major_version >= 2: + error_msg = ( + f"aic-sdk version {aic_version} detected, but aic-sdk < 2.0.0 is required. " + "Please use the v2 modules instead: " + "'from pipecat.audio.filters.aic_filter_v2 import AICFilter' or " + "'from pipecat.audio.vad.aic_vad_v2 import AICVADAnalyzer'." + ) + logger.error(error_msg) + raise ImportError(error_msg) + + if required_version == "v2" and major_version < 2: + error_msg = ( + f"aic-sdk version {aic_version} detected, but aic-sdk >= 2.0.0 is required. " + "Please update with 'pip install --upgrade aic-sdk>=2.0.0' " + "or use the v1 modules: " + "'from pipecat.audio.filters.aic_filter import AICFilter' or " + "'from pipecat.audio.vad.aic_vad import AICVADAnalyzer'." + ) + logger.error(error_msg) + raise ImportError(error_msg) + + except ImportError: + # Re-raise if it's our version mismatch error + raise + except Exception: + # If we can't determine version for other reasons, log warning and allow to proceed + logger.warning("Could not determine aic-sdk version. Proceeding anyway.") diff --git a/src/pipecat/audio/vad/aic_vad_v2.py b/src/pipecat/audio/vad/aic_vad_v2.py new file mode 100644 index 000000000..2f8129a0d --- /dev/null +++ b/src/pipecat/audio/vad/aic_vad_v2.py @@ -0,0 +1,163 @@ +"""AIC-integrated VAD analyzer that lazily binds to the AIC SDK v2 backend. + +This analyzer queries the backend's is_speech_detected() and maps it to a float +confidence (1.0/0.0). It uses 10 ms windows based on the sample rate and applies +optional AIC VAD parameters (speech_hold_duration, sensitivity) when available. + +.. note:: + This module is compatible with aic-sdk versions >= 2.0.0. + For aic-sdk < 2.0.0, use :mod:`pipecat.audio.vad.aic_vad` instead. +""" + +from typing import Any, Callable, Optional + +from loguru import logger + +from pipecat.audio.utils import check_aic_sdk_version +from pipecat.audio.vad.vad_analyzer import VADAnalyzer, VADParams + +# Check aic-sdk is installed and version is compatible (>= 2.0.0) +check_aic_sdk_version("v2") + +from aic import VadParameter + + + +class AICVADAnalyzer(VADAnalyzer): + """VAD analyzer that lazily binds to the AIC VadContext via a factory. + + The analyzer can be constructed before the AIC Processor exists. Once the filter has + started and the Processor is available, the provided factory will succeed and the + VadContext will be obtained. We then use the context's is_speech_detected() state + to derive confidence values. + + AIC VAD runtime parameters (v2): + - speech_hold_duration: + Controls for how long the VAD continues to detect speech after the audio signal + no longer contains speech (in seconds). + Range: 0.0 .. 20x model window length + Default (SDK): 0.05s (50ms) + - sensitivity: + Controls the energy threshold sensitivity. Higher values make the detector + less sensitive (require more energy to count as speech). + Range: 1.0 .. 15.0 + Formula: Energy threshold = 10 ** (-sensitivity) + Default (SDK): 6.0 + + .. note:: + This class requires aic-sdk >= 2.0.0. + """ + + def __init__( + self, + *, + vad_context_factory: Optional[Callable[[], Any]] = None, + speech_hold_duration: Optional[float] = None, + sensitivity: Optional[float] = None, + ): + """Create an AIC VAD analyzer. + + Args: + vad_context_factory: + Zero-arg callable that returns the AIC VadContext. + This may raise until the filter's Processor has been created; the analyzer + will retry on set_sample_rate/first use. + speech_hold_duration: + Optional override for AIC VAD speech hold duration (in seconds). + Range: 0.0 .. 20x model window length. + If None, the SDK default (0.05s) is used. + sensitivity: + Optional override for AIC VAD sensitivity (energy threshold). + Range: 1.0 .. 15.0. Energy threshold = 10 ** (-sensitivity). + If None, the SDK default (6.0) is used. + """ + # Use fixed VAD parameters for AIC: no user override + fixed_params = VADParams(confidence=0.5, start_secs=0.0, stop_secs=0.0, min_volume=0.0) + super().__init__(sample_rate=None, params=fixed_params) + self._vad_context_factory = vad_context_factory + self._vad_ctx: Optional[Any] = None + self._pending_speech_hold_duration: Optional[float] = speech_hold_duration + self._pending_sensitivity: Optional[float] = sensitivity + + def bind_vad_context_factory(self, vad_context_factory: Callable[[], Any]): + """Attach or replace the factory post-construction.""" + self._vad_context_factory = vad_context_factory + self._ensure_vad_context_initialized() + + def _apply_vad_params(self): + """Apply optional AIC VAD parameters if available.""" + if self._vad_ctx is None or VadParameter is None: + return + try: + if self._pending_speech_hold_duration is not None: + self._vad_ctx.set_parameter( + VadParameter.SpeechHoldDuration, float(self._pending_speech_hold_duration) + ) + if self._pending_sensitivity is not None: + self._vad_ctx.set_parameter( + VadParameter.Sensitivity, float(self._pending_sensitivity) + ) + except Exception as e: # noqa: BLE001 + logger.debug(f"AIC VAD parameter application deferred/failed: {e}") + + def _ensure_vad_context_initialized(self): + if self._vad_ctx is not None: + return + if not self._vad_context_factory: + return + try: + self._vad_ctx = self._vad_context_factory() + self._apply_vad_params() + # With VAD context ready, recompute internal frame sizing + super().set_params(self._params) + logger.debug("AIC VAD context (v2) initialized in analyzer.") + except Exception as e: # noqa: BLE001 + # Filter may not be started yet; try again later + logger.debug(f"Deferring AIC VAD context initialization: {e}") + + def set_sample_rate(self, sample_rate: int): + """Set the sample rate for audio processing. + + Args: + sample_rate: Audio sample rate in Hz. + """ + # Set rate and attempt VAD context initialization once we know SR + self._sample_rate = self._init_sample_rate or sample_rate + self._ensure_vad_context_initialized() + # Ensure params are initialized even if VAD context not ready yet + try: + super().set_params(self._params) + except Exception: + pass + + def num_frames_required(self) -> int: + """Get the number of audio frames required for analysis. + + Returns: + Number of frames needed for VAD processing. + """ + # Use 10 ms windows based on sample rate + return int(self.sample_rate * 0.01) if self.sample_rate > 0 else 160 + + def voice_confidence(self, buffer: bytes) -> float: + """Calculate voice activity confidence for the given audio buffer. + + Args: + buffer: Audio buffer to analyze. + + Returns: + Voice confidence score is 0.0 or 1.0. + """ + # Ensure VAD context exists (filter might have started since last call) + self._ensure_vad_context_initialized() + if self._vad_ctx is None: + return 0.0 + + # We do not need to analyze 'buffer' here since the processor's VAD is updated + # as part of the enhancement pipeline. Simply query the boolean and map it. + try: + is_speech = self._vad_ctx.is_speech_detected() + return 1.0 if is_speech else 0.0 + except Exception as e: # noqa: BLE001 + logger.error(f"AIC VAD inference error: {e}") + return 0.0 From f05809520bd4698941f0e1ba971c591c147d7d2d Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?G=C3=B6kmen=20G=C3=B6rgen?= Date: Wed, 14 Jan 2026 17:22:38 +0100 Subject: [PATCH 0204/1060] Remove outdated AIC Filter and VAD v2 files, migrate to consolidated implementations. Added the new ACIFilter to the same module. --- src/pipecat/audio/filters/aic_filter_v2.py | 296 --------------------- src/pipecat/audio/utils.py | 90 ++++--- src/pipecat/audio/vad/aic_vad_v2.py | 163 ------------ uv.lock | 75 +++--- 4 files changed, 89 insertions(+), 535 deletions(-) delete mode 100644 src/pipecat/audio/filters/aic_filter_v2.py delete mode 100644 src/pipecat/audio/vad/aic_vad_v2.py diff --git a/src/pipecat/audio/filters/aic_filter_v2.py b/src/pipecat/audio/filters/aic_filter_v2.py deleted file mode 100644 index be2912107..000000000 --- a/src/pipecat/audio/filters/aic_filter_v2.py +++ /dev/null @@ -1,296 +0,0 @@ -# -# Copyright (c) 2024-2026, Daily -# -# SPDX-License-Identifier: BSD 2-Clause License -# - -"""ai-coustics AIC SDK audio filter for Pipecat (aic-sdk >= 2.0.0). - -This module provides an audio filter implementation using ai-coustics' AIC SDK to -enhance audio streams in real time. It mirrors the structure of other filters like -the Koala filter and integrates with Pipecat's input transport pipeline. - -.. note:: - This module is compatible with aic-sdk versions >= 2.0.0. - For aic-sdk < 2.0.0, use :mod:`pipecat.audio.filters.aic_filter` instead. -""" - -import os -from typing import List, Optional - -import numpy as np -from loguru import logger - -from pipecat.audio.filters.base_audio_filter import BaseAudioFilter -from pipecat.audio.utils import check_aic_sdk_version -from pipecat.frames.frames import FilterControlFrame, FilterEnableFrame - -# Check aic-sdk is installed and version is compatible (>= 2.0.0) -check_aic_sdk_version("v2") - -# AIC SDK v2 (https://ai-coustics.github.io/aic-sdk-py/api/) -import aic -from aic import Model, ProcessorAsync, ProcessorConfig, ProcessorParameter, VadParameter - - -class AICFilter(BaseAudioFilter): - """Audio filter using ai-coustics' AIC SDK v2 for real-time enhancement. - - Buffers incoming audio to the model's preferred block size and processes - planar frames in-place using float32 samples in the linear -1..+1 range. - - .. note:: - This class requires aic-sdk >= 2.0.0. - """ - - def __init__( - self, - *, - license_key: str = "", - model_id: Optional[str] = None, - model_path: Optional[str] = None, - model_download_dir: Optional[str] = None, - enhancement_level: Optional[float] = 1.0, - voice_gain: Optional[float] = 1.0, - ) -> None: - """Initialize the AIC filter. - - Args: - license_key: ai-coustics license key for authentication. - model_id: Model identifier to download from CDN. Required if model_path - is not provided. See https://artifacts.ai-coustics.io/ for available models. - model_path: Optional path to a local .aicmodel file. If provided, - model_id is ignored and no download occurs. - model_download_dir: Directory for downloading models. Defaults to - a cache directory in user's home folder. - enhancement_level: Optional overall enhancement strength (0.0..1.0). - voice_gain: Optional linear gain applied to detected speech (0.1..4.0). - - Raises: - ValueError: If neither model_id nor model_path is provided. - """ - if model_id is None and model_path is None: - raise ValueError( - "Either 'model_id' or 'model_path' must be provided. " - "See https://artifacts.ai-coustics.io/ for available models." - ) - - self._license_key = license_key - self._model_id = model_id - self._model_path = model_path - self._model_download_dir = model_download_dir or os.path.expanduser( - "~/.cache/pipecat/aic-models" - ) - - self._enhancement_level = enhancement_level - self._voice_gain = voice_gain - - self._enabled = True - self._sample_rate = 0 - self._aic_ready = False - self._frames_per_block = 0 - self._audio_buffer = bytearray() - - # v2 API objects - self._model: Optional[Model] = None - self._processor: Optional[ProcessorAsync] = None - self._processor_ctx = None - self._vad_ctx = None - - def get_vad_context(self): - """Return the VAD context once the processor exists. - - Returns: - The VadContext instance bound to the underlying processor. - Raises RuntimeError if the processor has not been initialized. - """ - if self._vad_ctx is None: - raise RuntimeError("AIC processor not initialized yet. Call start(sample_rate) first.") - return self._vad_ctx - - def create_vad_analyzer( - self, - *, - speech_hold_duration: Optional[float] = None, - sensitivity: Optional[float] = None, - ): - """Return an analyzer that will lazily instantiate the AIC VAD when ready. - - AIC VAD parameters (v2): - - speech_hold_duration: - How long VAD continues detecting after speech ends (in seconds). - Range: 0.0 .. 20x model window length, Default (SDK): 0.05s - - sensitivity: - Energy threshold sensitivity. Energy threshold = 10 ** (-sensitivity). - Range: 1.0 .. 15.0, Default (SDK): 6.0 - - Args: - speech_hold_duration: Optional speech hold duration to configure on the VAD. - If None, SDK default (0.05s) is used. - sensitivity: Optional sensitivity (energy threshold) to configure on the VAD. - Range: 1.0 .. 15.0. If None, SDK default (6.0) is used. - - Returns: - A lazily-initialized AICVADAnalyzer that will bind to the VAD context - once the filter's processor has been created (after start(sample_rate)). - """ - from pipecat.audio.vad.aic_vad_v2 import AICVADAnalyzer - - return AICVADAnalyzer( - vad_context_factory=lambda: self.get_vad_context(), - speech_hold_duration=speech_hold_duration, - sensitivity=sensitivity, - ) - - async def start(self, sample_rate: int): - """Initialize the filter with the transport's sample rate. - - Args: - sample_rate: The sample rate of the input transport in Hz. - - Returns: - None - """ - self._sample_rate = sample_rate - - try: - # Load or download model - if self._model_path: - logger.debug(f"Loading AIC model from: {self._model_path}") - self._model = Model.from_file(self._model_path) - else: - logger.debug(f"Downloading AIC model: {self._model_id}") - os.makedirs(self._model_download_dir, exist_ok=True) - model_path = await Model.download_async(self._model_id, self._model_download_dir) - logger.debug(f"Model downloaded to: {model_path}") - self._model = Model.from_file(model_path) - - # Create async processor - self._processor = ProcessorAsync(self._model, self._license_key or "") - - # Get optimal frames for this sample rate - self._frames_per_block = self._model.get_optimal_num_frames(self._sample_rate) - - # Create configuration - config = ProcessorConfig( - sample_rate=self._sample_rate, - num_channels=1, - num_frames=self._frames_per_block, - allow_variable_frames=False, - ) - - # Initialize processor - await self._processor.initialize_async(config) - - # Get contexts for parameter control and VAD - self._processor_ctx = self._processor.get_processor_context() - self._vad_ctx = self._processor.get_vad_context() - - # Apply initial parameters - if self._enhancement_level is not None: - level = float(self._enhancement_level if self._enabled else 0.0) - self._processor_ctx.set_parameter(ProcessorParameter.EnhancementLevel, level) - if self._voice_gain is not None: - self._processor_ctx.set_parameter( - ProcessorParameter.VoiceGain, float(self._voice_gain) - ) - - self._aic_ready = True - - # Log processor information - logger.debug(f"ai-coustics filter (v2) started:") - logger.debug(f" Model ID: {self._model.get_id()}") - logger.debug(f" Sample rate: {self._sample_rate} Hz") - logger.debug(f" Frames per chunk: {self._frames_per_block}") - logger.debug(f" Enhancement strength: {int((self._enhancement_level or 1.0) * 100)}%") - logger.debug(f" Optimal sample rate: {self._model.get_optimal_sample_rate()} Hz") - logger.debug( - f" Output delay: {self._processor_ctx.get_output_delay()} samples " - f"({self._processor_ctx.get_output_delay() / self._sample_rate * 1000:.2f}ms)" - ) - except Exception as e: # noqa: BLE001 - surfacing SDK initialization errors - logger.error(f"AIC model initialization failed: {e}") - self._aic_ready = False - - async def stop(self): - """Clean up the AIC processor when stopping. - - Returns: - None - """ - try: - if self._processor_ctx is not None: - self._processor_ctx.reset() - finally: - self._processor = None - self._processor_ctx = None - self._vad_ctx = None - self._model = None - self._aic_ready = False - self._audio_buffer.clear() - - async def process_frame(self, frame: FilterControlFrame): - """Process control frames to enable/disable filtering. - - Args: - frame: The control frame containing filter commands. - - Returns: - None - """ - if isinstance(frame, FilterEnableFrame): - self._enabled = frame.enable - if self._processor_ctx is not None: - try: - level = float(self._enhancement_level if self._enabled else 0.0) - self._processor_ctx.set_parameter(ProcessorParameter.EnhancementLevel, level) - except Exception as e: # noqa: BLE001 - logger.error(f"AIC set_parameter failed: {e}") - - async def filter(self, audio: bytes) -> bytes: - """Apply AIC enhancement to audio data. - - Buffers incoming audio and processes it in chunks that match the AIC - model's required block length. Returns enhanced audio data. - - Args: - audio: Raw audio data as bytes to be filtered (int16 PCM, planar). - - Returns: - Enhanced audio data as bytes (int16 PCM, planar). - """ - if not self._aic_ready or self._processor is None: - return audio - - self._audio_buffer.extend(audio) - - filtered_chunks: List[bytes] = [] - - # Number of int16 samples currently buffered - available_frames = len(self._audio_buffer) // 2 - - while available_frames >= self._frames_per_block: - # Consume exactly one block worth of frames - samples_to_consume = self._frames_per_block * 1 - bytes_to_consume = samples_to_consume * 2 - block_bytes = bytes(self._audio_buffer[:bytes_to_consume]) - - # Convert to float32 in -1..+1 range and reshape to (channels, frames) - block_i16 = np.frombuffer(block_bytes, dtype=np.int16) - block_f32 = (block_i16.astype(np.float32) / 32768.0).reshape( - (1, self._frames_per_block) - ) - - # Process via async processor; returns ndarray (same shape) - out_f32 = await self._processor.process_async(block_f32) - - # Convert back to int16 bytes - out_i16 = np.clip(out_f32 * 32768.0, -32768, 32767).astype(np.int16) - filtered_chunks.append(out_i16.reshape(-1).tobytes()) - - # Slide buffer - self._audio_buffer = self._audio_buffer[bytes_to_consume:] - available_frames = len(self._audio_buffer) // 2 - - # Do not flush incomplete frames; keep them buffered for the next call - return b"".join(filtered_chunks) diff --git a/src/pipecat/audio/utils.py b/src/pipecat/audio/utils.py index 002375f35..c61aba4dd 100644 --- a/src/pipecat/audio/utils.py +++ b/src/pipecat/audio/utils.py @@ -316,11 +316,41 @@ def is_silence(pcm_bytes: bytes) -> bool: return max_value <= SPEAKING_THRESHOLD +def is_aic_sdk_v2() -> bool: + """Detect if aic-sdk v2 is installed by checking the module name. + + In v2, the module was renamed from 'aic' to 'aic_sdk'. + + Returns: + True if aic-sdk v2 (aic_sdk module) is installed, False if v1 (aic module). + + Raises: + ImportError: If neither aic nor aic_sdk module is installed. + """ + try: + import aic_sdk # noqa: F401 + + return True + except ModuleNotFoundError: + pass + + try: + import aic # noqa: F401 + + return False + except ModuleNotFoundError: + logger.error("In order to use the AIC filter, you need to `pip install pipecat-ai[aic]`.") + raise ImportError( + "aic-sdk is not installed. Install with 'pip install pipecat-ai[aic]'." + ) + + def check_aic_sdk_version(required_version: Literal["v1", "v2"]) -> None: """Check if the aic-sdk is installed and compatible with the module. This function checks both that the aic-sdk is installed and that its version - is compatible with the module requirements. + is compatible with the module requirements. Version detection is based on + the module name: v2 uses 'aic_sdk', v1 uses 'aic'. Args: required_version: Either "v1" (for aic-sdk < 2.0.0) or "v2" (for aic-sdk >= 2.0.0). @@ -328,43 +358,25 @@ def check_aic_sdk_version(required_version: Literal["v1", "v2"]) -> None: Raises: ImportError: If aic-sdk is not installed or version is incompatible. """ - try: - import aic # noqa: F401 - check if module is installed - except ModuleNotFoundError as e: - logger.error(f"Exception: {e}") - logger.error("In order to use the AIC filter, you need to `pip install pipecat-ai[aic]`.") - raise ImportError(f"Missing module: {e}") from e + is_v2 = is_aic_sdk_v2() - try: - from importlib.metadata import version as get_version + if required_version == "v1" and is_v2: + error_msg = ( + "aic-sdk v2 (aic_sdk module) detected, but v1 (aic module) is required. " + "Please use the v2 classes instead: " + "'from pipecat.audio.filters.aic_filter import AICFilterV2' or " + "'from pipecat.audio.vad.aic_vad import AICVADAnalyzerV2'." + ) + logger.error(error_msg) + raise ImportError(error_msg) - aic_version = get_version("aic-sdk") - major_version = int(aic_version.split(".")[0]) - - if required_version == "v1" and major_version >= 2: - error_msg = ( - f"aic-sdk version {aic_version} detected, but aic-sdk < 2.0.0 is required. " - "Please use the v2 modules instead: " - "'from pipecat.audio.filters.aic_filter_v2 import AICFilter' or " - "'from pipecat.audio.vad.aic_vad_v2 import AICVADAnalyzer'." - ) - logger.error(error_msg) - raise ImportError(error_msg) - - if required_version == "v2" and major_version < 2: - error_msg = ( - f"aic-sdk version {aic_version} detected, but aic-sdk >= 2.0.0 is required. " - "Please update with 'pip install --upgrade aic-sdk>=2.0.0' " - "or use the v1 modules: " - "'from pipecat.audio.filters.aic_filter import AICFilter' or " - "'from pipecat.audio.vad.aic_vad import AICVADAnalyzer'." - ) - logger.error(error_msg) - raise ImportError(error_msg) - - except ImportError: - # Re-raise if it's our version mismatch error - raise - except Exception: - # If we can't determine version for other reasons, log warning and allow to proceed - logger.warning("Could not determine aic-sdk version. Proceeding anyway.") + if required_version == "v2" and not is_v2: + error_msg = ( + "aic-sdk v1 (aic module) detected, but v2 (aic_sdk module) is required. " + "Please update with 'pip install --upgrade aic-sdk>=2.0.0' " + "or use the v1 classes: " + "'from pipecat.audio.filters.aic_filter import AICFilter' or " + "'from pipecat.audio.vad.aic_vad import AICVADAnalyzer'." + ) + logger.error(error_msg) + raise ImportError(error_msg) diff --git a/src/pipecat/audio/vad/aic_vad_v2.py b/src/pipecat/audio/vad/aic_vad_v2.py deleted file mode 100644 index 2f8129a0d..000000000 --- a/src/pipecat/audio/vad/aic_vad_v2.py +++ /dev/null @@ -1,163 +0,0 @@ -"""AIC-integrated VAD analyzer that lazily binds to the AIC SDK v2 backend. - -This analyzer queries the backend's is_speech_detected() and maps it to a float -confidence (1.0/0.0). It uses 10 ms windows based on the sample rate and applies -optional AIC VAD parameters (speech_hold_duration, sensitivity) when available. - -.. note:: - This module is compatible with aic-sdk versions >= 2.0.0. - For aic-sdk < 2.0.0, use :mod:`pipecat.audio.vad.aic_vad` instead. -""" - -from typing import Any, Callable, Optional - -from loguru import logger - -from pipecat.audio.utils import check_aic_sdk_version -from pipecat.audio.vad.vad_analyzer import VADAnalyzer, VADParams - -# Check aic-sdk is installed and version is compatible (>= 2.0.0) -check_aic_sdk_version("v2") - -from aic import VadParameter - - - -class AICVADAnalyzer(VADAnalyzer): - """VAD analyzer that lazily binds to the AIC VadContext via a factory. - - The analyzer can be constructed before the AIC Processor exists. Once the filter has - started and the Processor is available, the provided factory will succeed and the - VadContext will be obtained. We then use the context's is_speech_detected() state - to derive confidence values. - - AIC VAD runtime parameters (v2): - - speech_hold_duration: - Controls for how long the VAD continues to detect speech after the audio signal - no longer contains speech (in seconds). - Range: 0.0 .. 20x model window length - Default (SDK): 0.05s (50ms) - - sensitivity: - Controls the energy threshold sensitivity. Higher values make the detector - less sensitive (require more energy to count as speech). - Range: 1.0 .. 15.0 - Formula: Energy threshold = 10 ** (-sensitivity) - Default (SDK): 6.0 - - .. note:: - This class requires aic-sdk >= 2.0.0. - """ - - def __init__( - self, - *, - vad_context_factory: Optional[Callable[[], Any]] = None, - speech_hold_duration: Optional[float] = None, - sensitivity: Optional[float] = None, - ): - """Create an AIC VAD analyzer. - - Args: - vad_context_factory: - Zero-arg callable that returns the AIC VadContext. - This may raise until the filter's Processor has been created; the analyzer - will retry on set_sample_rate/first use. - speech_hold_duration: - Optional override for AIC VAD speech hold duration (in seconds). - Range: 0.0 .. 20x model window length. - If None, the SDK default (0.05s) is used. - sensitivity: - Optional override for AIC VAD sensitivity (energy threshold). - Range: 1.0 .. 15.0. Energy threshold = 10 ** (-sensitivity). - If None, the SDK default (6.0) is used. - """ - # Use fixed VAD parameters for AIC: no user override - fixed_params = VADParams(confidence=0.5, start_secs=0.0, stop_secs=0.0, min_volume=0.0) - super().__init__(sample_rate=None, params=fixed_params) - self._vad_context_factory = vad_context_factory - self._vad_ctx: Optional[Any] = None - self._pending_speech_hold_duration: Optional[float] = speech_hold_duration - self._pending_sensitivity: Optional[float] = sensitivity - - def bind_vad_context_factory(self, vad_context_factory: Callable[[], Any]): - """Attach or replace the factory post-construction.""" - self._vad_context_factory = vad_context_factory - self._ensure_vad_context_initialized() - - def _apply_vad_params(self): - """Apply optional AIC VAD parameters if available.""" - if self._vad_ctx is None or VadParameter is None: - return - try: - if self._pending_speech_hold_duration is not None: - self._vad_ctx.set_parameter( - VadParameter.SpeechHoldDuration, float(self._pending_speech_hold_duration) - ) - if self._pending_sensitivity is not None: - self._vad_ctx.set_parameter( - VadParameter.Sensitivity, float(self._pending_sensitivity) - ) - except Exception as e: # noqa: BLE001 - logger.debug(f"AIC VAD parameter application deferred/failed: {e}") - - def _ensure_vad_context_initialized(self): - if self._vad_ctx is not None: - return - if not self._vad_context_factory: - return - try: - self._vad_ctx = self._vad_context_factory() - self._apply_vad_params() - # With VAD context ready, recompute internal frame sizing - super().set_params(self._params) - logger.debug("AIC VAD context (v2) initialized in analyzer.") - except Exception as e: # noqa: BLE001 - # Filter may not be started yet; try again later - logger.debug(f"Deferring AIC VAD context initialization: {e}") - - def set_sample_rate(self, sample_rate: int): - """Set the sample rate for audio processing. - - Args: - sample_rate: Audio sample rate in Hz. - """ - # Set rate and attempt VAD context initialization once we know SR - self._sample_rate = self._init_sample_rate or sample_rate - self._ensure_vad_context_initialized() - # Ensure params are initialized even if VAD context not ready yet - try: - super().set_params(self._params) - except Exception: - pass - - def num_frames_required(self) -> int: - """Get the number of audio frames required for analysis. - - Returns: - Number of frames needed for VAD processing. - """ - # Use 10 ms windows based on sample rate - return int(self.sample_rate * 0.01) if self.sample_rate > 0 else 160 - - def voice_confidence(self, buffer: bytes) -> float: - """Calculate voice activity confidence for the given audio buffer. - - Args: - buffer: Audio buffer to analyze. - - Returns: - Voice confidence score is 0.0 or 1.0. - """ - # Ensure VAD context exists (filter might have started since last call) - self._ensure_vad_context_initialized() - if self._vad_ctx is None: - return 0.0 - - # We do not need to analyze 'buffer' here since the processor's VAD is updated - # as part of the enhancement pipeline. Simply query the boolean and map it. - try: - is_speech = self._vad_ctx.is_speech_detected() - return 1.0 if is_speech else 0.0 - except Exception as e: # noqa: BLE001 - logger.error(f"AIC VAD inference error: {e}") - return 0.0 diff --git a/uv.lock b/uv.lock index 45c1f892f..4782f1c79 100644 --- a/uv.lock +++ b/uv.lock @@ -38,12 +38,12 @@ wheels = [ [[package]] name = "aic-sdk" -version = "1.2.0" +version = "1.3.0" source = { registry = "https://pypi.org/simple" } dependencies = [ { name = "numpy" }, ] -sdist = { url = "https://files.pythonhosted.org/packages/f9/ba/3ebe31b91e03d42437ec864e9d2af3a52b7ccc73a1a0c1026275956270b0/aic_sdk-1.2.0.tar.gz", hash = "sha256:eeda9a181c679f175dbe6f0efc0c67ec98ff3d84cfe01541fef7fa12ecd505ca", size = 35606, upload-time = "2025-11-20T14:42:14.333Z" } +sdist = { url = "https://files.pythonhosted.org/packages/1f/e7/56b6074224dc26a1350b165fd0ef3c8ca8c115cc1d4aa3e4f38af9c5d3f1/aic_sdk-1.3.0.tar.gz", hash = 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2001 From: =?UTF-8?q?G=C3=B6kmen=20G=C3=B6rgen?= Date: Fri, 16 Jan 2026 12:31:41 +0100 Subject: [PATCH 0206/1060] drop v1 support from aic. --- src/pipecat/audio/utils.py | 69 +------------------------------------- 1 file changed, 1 insertion(+), 68 deletions(-) diff --git a/src/pipecat/audio/utils.py b/src/pipecat/audio/utils.py index c61aba4dd..29fc44ea9 100644 --- a/src/pipecat/audio/utils.py +++ b/src/pipecat/audio/utils.py @@ -14,10 +14,9 @@ various audio formats used in Pipecat pipelines. import audioop from typing import Literal -from loguru import logger - import numpy as np import pyloudnorm as pyln +from loguru import logger from pipecat.audio.resamplers.base_audio_resampler import BaseAudioResampler from pipecat.audio.resamplers.soxr_resampler import SOXRAudioResampler @@ -314,69 +313,3 @@ def is_silence(pcm_bytes: bytes) -> bool: # If max value is lower than SPEAKING_THRESHOLD, consider it as silence return max_value <= SPEAKING_THRESHOLD - - -def is_aic_sdk_v2() -> bool: - """Detect if aic-sdk v2 is installed by checking the module name. - - In v2, the module was renamed from 'aic' to 'aic_sdk'. - - Returns: - True if aic-sdk v2 (aic_sdk module) is installed, False if v1 (aic module). - - Raises: - ImportError: If neither aic nor aic_sdk module is installed. - """ - try: - import aic_sdk # noqa: F401 - - return True - except ModuleNotFoundError: - pass - - try: - import aic # noqa: F401 - - return False - except ModuleNotFoundError: - logger.error("In order to use the AIC filter, you need to `pip install pipecat-ai[aic]`.") - raise ImportError( - "aic-sdk is not installed. Install with 'pip install pipecat-ai[aic]'." - ) - - -def check_aic_sdk_version(required_version: Literal["v1", "v2"]) -> None: - """Check if the aic-sdk is installed and compatible with the module. - - This function checks both that the aic-sdk is installed and that its version - is compatible with the module requirements. Version detection is based on - the module name: v2 uses 'aic_sdk', v1 uses 'aic'. - - Args: - required_version: Either "v1" (for aic-sdk < 2.0.0) or "v2" (for aic-sdk >= 2.0.0). - - Raises: - ImportError: If aic-sdk is not installed or version is incompatible. - """ - is_v2 = is_aic_sdk_v2() - - if required_version == "v1" and is_v2: - error_msg = ( - "aic-sdk v2 (aic_sdk module) detected, but v1 (aic module) is required. " - "Please use the v2 classes instead: " - "'from pipecat.audio.filters.aic_filter import AICFilterV2' or " - "'from pipecat.audio.vad.aic_vad import AICVADAnalyzerV2'." - ) - logger.error(error_msg) - raise ImportError(error_msg) - - if required_version == "v2" and not is_v2: - error_msg = ( - "aic-sdk v1 (aic module) detected, but v2 (aic_sdk module) is required. " - "Please update with 'pip install --upgrade aic-sdk>=2.0.0' " - "or use the v1 classes: " - "'from pipecat.audio.filters.aic_filter import AICFilter' or " - "'from pipecat.audio.vad.aic_vad import AICVADAnalyzer'." - ) - logger.error(error_msg) - raise ImportError(error_msg) From effb6aa8f4d50edb3af486d4e5bb55a3b021ffba Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?G=C3=B6kmen=20G=C3=B6rgen?= Date: Fri, 16 Jan 2026 12:53:15 +0100 Subject: [PATCH 0207/1060] clean up unused imports in audio utils. --- src/pipecat/audio/utils.py | 2 -- 1 file changed, 2 deletions(-) diff --git a/src/pipecat/audio/utils.py b/src/pipecat/audio/utils.py index 29fc44ea9..65f451675 100644 --- a/src/pipecat/audio/utils.py +++ b/src/pipecat/audio/utils.py @@ -12,11 +12,9 @@ various audio formats used in Pipecat pipelines. """ import audioop -from typing import Literal import numpy as np import pyloudnorm as pyln -from loguru import logger from pipecat.audio.resamplers.base_audio_resampler import BaseAudioResampler from pipecat.audio.resamplers.soxr_resampler import SOXRAudioResampler From 1e1e275fea70cc47730c8049353e461263306550 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?G=C3=B6kmen=20G=C3=B6rgen?= Date: Mon, 19 Jan 2026 15:51:28 +0100 Subject: [PATCH 0208/1060] address feedback. --- src/pipecat/audio/filters/aic_filter.py | 85 +++++++++++++------------ 1 file changed, 44 insertions(+), 41 deletions(-) diff --git a/src/pipecat/audio/filters/aic_filter.py b/src/pipecat/audio/filters/aic_filter.py index 14b95c92d..16062c6ea 100644 --- a/src/pipecat/audio/filters/aic_filter.py +++ b/src/pipecat/audio/filters/aic_filter.py @@ -11,7 +11,7 @@ enhance audio streams in real time. It mirrors the structure of other filters li the Koala filter and integrates with Pipecat's input transport pipeline. Classes: - AICFilter: For aic-sdk >= 2.0.0 (uses 'aic_sdk' module) + AICFilter: For aic-sdk (uses 'aic_sdk' module) """ import os @@ -30,7 +30,7 @@ class AICFilter(BaseAudioFilter): """Audio filter using ai-coustics' AIC SDK for real-time enhancement. Buffers incoming audio to the model's preferred block size and processes - planar frames in-place using float32 samples in the linear -1..+1 range. + frames using float32 samples normalized to the -1..+1 range. .. note:: This class requires aic-sdk >= 2.0.0 (uses 'aic_sdk' module). @@ -84,12 +84,21 @@ class AICFilter(BaseAudioFilter): self._frames_per_block = 0 self._audio_buffer = bytearray() + # Audio format constants + self._bytes_per_sample = 2 # int16 = 2 bytes + self._dtype = np.int16 + self._scale = 32768.0 # 2^15, for normalizing int16 (-32768..32767) to float32 (-1.0..1.0) + # AIC SDK objects self._model = None self._processor = None self._processor_ctx = None self._vad_ctx = None + # Pre-allocated buffers (resized in start() once frames_per_block is known) + self._in_f32 = None + self._out_i16 = None + def get_vad_context(self): """Return the VAD context once the processor exists. @@ -156,6 +165,13 @@ class AICFilter(BaseAudioFilter): logger.debug(f"Model downloaded to: {model_path}") self._model = Model.from_file(model_path) + # Get optimal frames for this sample rate + self._frames_per_block = self._model.get_optimal_num_frames(self._sample_rate) + + # Allocate processing buffers now that we know the block size + self._in_f32 = np.zeros((1, self._frames_per_block), dtype=np.float32) + self._out_i16 = np.zeros(self._frames_per_block, dtype=np.int16) + # Create configuration config = ProcessorConfig.optimal( self._model, @@ -163,7 +179,7 @@ class AICFilter(BaseAudioFilter): ) # Create async processor - self._processor = ProcessorAsync(self._model, self._license_key or "", config) + self._processor = ProcessorAsync(self._model, self._license_key, config) # Get contexts for parameter control and VAD self._processor_ctx = self._processor.get_processor_context() @@ -171,12 +187,10 @@ class AICFilter(BaseAudioFilter): # Apply initial parameters if self._enhancement_level is not None: - level = float(self._enhancement_level if self._enabled else 0.0) + level = self._enhancement_level if self._enabled else 0.0 self._processor_ctx.set_parameter(ProcessorParameter.EnhancementLevel, level) if self._voice_gain is not None: - self._processor_ctx.set_parameter( - ProcessorParameter.VoiceGain, float(self._voice_gain) - ) + self._processor_ctx.set_parameter(ProcessorParameter.VoiceGain, self._voice_gain) self._aic_ready = True @@ -225,7 +239,7 @@ class AICFilter(BaseAudioFilter): self._enabled = frame.enable if self._processor_ctx is not None: try: - level = float(self._enhancement_level if self._enabled else 0.0) + level = self._enhancement_level if self._enabled else 0.0 self._processor_ctx.set_parameter(ProcessorParameter.EnhancementLevel, level) except Exception as e: # noqa: BLE001 logger.error(f"AIC set_parameter failed: {e}") @@ -237,52 +251,41 @@ class AICFilter(BaseAudioFilter): model's required block length. Returns enhanced audio data. Args: - audio: Raw audio data as bytes to be filtered (int16 PCM, planar). + audio: Raw audio data as bytes (int16 PCM). Returns: - Enhanced audio data as bytes (int16 PCM, planar). + Enhanced audio data as bytes (int16 PCM). """ if not self._aic_ready or self._processor is None: return audio self._audio_buffer.extend(audio) + available_frames = len(self._audio_buffer) // self._bytes_per_sample + num_blocks = available_frames // self._frames_per_block + + if num_blocks == 0: + return b"" filtered_chunks: List[bytes] = [] + mv = memoryview(self._audio_buffer) + block_size = self._frames_per_block * self._bytes_per_sample - # Number of int16 samples currently buffered - available_frames = len(self._audio_buffer) // 2 + for i in range(num_blocks): + start = i * block_size + block_i16 = np.frombuffer(mv[start : start + block_size], dtype=self._dtype) - while available_frames >= self._frames_per_block: - # Consume exactly one block worth of frames - samples_to_consume = self._frames_per_block * 1 - bytes_to_consume = samples_to_consume * 2 - block_bytes = bytes(self._audio_buffer[:bytes_to_consume]) + # Reuse input buffer, in-place divide + np.copyto(self._in_f32[0], block_i16) + self._in_f32 /= self._scale - # Convert to float32 in -1..+1 range and reshape to (channels, frames) - block_i16 = np.frombuffer(block_bytes, dtype=np.int16) - # Convert to float32 and normalize - block_f32 = block_i16.astype(np.float32) - - block_f32 *= (1.0 / 32768.0) - - # Reshape to (1, frames) for AIC SDK - block_f32 = block_f32.reshape((1, self._frames_per_block)) + out_f32 = await self._processor.process_async(self._in_f32) - # Process via async processor; returns ndarray (same shape) - out_f32 = await self._processor.process_async(block_f32) + # Convert float32 output back to int16 + np.multiply(out_f32, self._scale, out=self._in_f32) # reuse in_f32 as temp + np.clip(self._in_f32, -self._scale, self._scale - 1, out=self._in_f32) + np.copyto(self._out_i16, self._in_f32[0].astype(self._dtype)) - # Convert back to int16 bytes - # Denormalize and convert back to int16 - out_f32 *= 32768.0 - - # In-place clip to valid int16 range (-32768 to 32767) - np.clip(out_f32, -32768.0, 32767, out=out_f32) - out_i16 = out_f32.astype(dtype) - filtered_chunks.append(out_i16.reshape(-1).tobytes()) + filtered_chunks.append(self._out_i16.tobytes()) - # Slide buffer - self._audio_buffer = self._audio_buffer[bytes_to_consume:] - available_frames = len(self._audio_buffer) // 2 - - # Do not flush incomplete frames; keep them buffered for the next call + self._audio_buffer = self._audio_buffer[num_blocks * block_size :] return b"".join(filtered_chunks) From bdded9b0264e588cd02a032754d30b5643fbdeff Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?G=C3=B6kmen=20G=C3=B6rgen?= Date: Mon, 19 Jan 2026 16:04:26 +0100 Subject: [PATCH 0209/1060] set SDK ID for telemetry in AIC filter. --- src/pipecat/audio/filters/aic_filter.py | 5 ++++- 1 file changed, 4 insertions(+), 1 deletion(-) diff --git a/src/pipecat/audio/filters/aic_filter.py b/src/pipecat/audio/filters/aic_filter.py index 16062c6ea..f40ed979a 100644 --- a/src/pipecat/audio/filters/aic_filter.py +++ b/src/pipecat/audio/filters/aic_filter.py @@ -18,7 +18,7 @@ import os from typing import List, Optional import numpy as np -from aic_sdk import Model, ProcessorAsync, ProcessorConfig, ProcessorParameter +from aic_sdk import Model, ProcessorAsync, ProcessorConfig, ProcessorParameter, set_sdk_id from loguru import logger from pipecat.audio.filters.base_audio_filter import BaseAudioFilter @@ -62,6 +62,9 @@ class AICFilter(BaseAudioFilter): Raises: ValueError: If neither model_id nor model_path is provided. """ + # Set SDK ID for telemetry identification (6 = pipecat) + set_sdk_id(6) + if model_id is None and model_path is None: raise ValueError( "Either 'model_id' or 'model_path' must be provided. " From dcab79753b5f9bc7787497fae883a4499b8bc4cf Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?G=C3=B6kmen=20G=C3=B6rgen?= Date: Mon, 19 Jan 2026 16:20:45 +0100 Subject: [PATCH 0210/1060] even the parameters are fixed, keep aic ready for processing. --- src/pipecat/audio/filters/aic_filter.py | 100 +++++++++++++----------- 1 file changed, 55 insertions(+), 45 deletions(-) diff --git a/src/pipecat/audio/filters/aic_filter.py b/src/pipecat/audio/filters/aic_filter.py index f40ed979a..eb4ee7f04 100644 --- a/src/pipecat/audio/filters/aic_filter.py +++ b/src/pipecat/audio/filters/aic_filter.py @@ -18,7 +18,14 @@ import os from typing import List, Optional import numpy as np -from aic_sdk import Model, ProcessorAsync, ProcessorConfig, ProcessorParameter, set_sdk_id +from aic_sdk import ( + Model, + ParameterFixedError, + ProcessorAsync, + ProcessorConfig, + ProcessorParameter, + set_sdk_id, +) from loguru import logger from pipecat.audio.filters.base_audio_filter import BaseAudioFilter @@ -156,61 +163,64 @@ class AICFilter(BaseAudioFilter): """ self._sample_rate = sample_rate + # Load or download model + if self._model_path: + logger.debug(f"Loading AIC model from: {self._model_path}") + self._model = Model.from_file(self._model_path) + else: + logger.debug(f"Downloading AIC model: {self._model_id}") + os.makedirs(self._model_download_dir, exist_ok=True) + model_path = await Model.download_async(self._model_id, self._model_download_dir) + logger.debug(f"Model downloaded to: {model_path}") + self._model = Model.from_file(model_path) + + # Get optimal frames for this sample rate + self._frames_per_block = self._model.get_optimal_num_frames(self._sample_rate) + + # Allocate processing buffers now that we know the block size + self._in_f32 = np.zeros((1, self._frames_per_block), dtype=np.float32) + self._out_i16 = np.zeros(self._frames_per_block, dtype=np.int16) + + # Create configuration + config = ProcessorConfig.optimal( + self._model, + sample_rate=self._sample_rate, + ) + + # Create async processor try: - # Load or download model - if self._model_path: - logger.debug(f"Loading AIC model from: {self._model_path}") - self._model = Model.from_file(self._model_path) - else: - logger.debug(f"Downloading AIC model: {self._model_id}") - os.makedirs(self._model_download_dir, exist_ok=True) - model_path = await Model.download_async(self._model_id, self._model_download_dir) - logger.debug(f"Model downloaded to: {model_path}") - self._model = Model.from_file(model_path) - - # Get optimal frames for this sample rate - self._frames_per_block = self._model.get_optimal_num_frames(self._sample_rate) - - # Allocate processing buffers now that we know the block size - self._in_f32 = np.zeros((1, self._frames_per_block), dtype=np.float32) - self._out_i16 = np.zeros(self._frames_per_block, dtype=np.int16) - - # Create configuration - config = ProcessorConfig.optimal( - self._model, - sample_rate=self._sample_rate, - ) - - # Create async processor self._processor = ProcessorAsync(self._model, self._license_key, config) + self._aic_ready = True + except Exception as e: # noqa: BLE001 - surfacing SDK initialization errors + logger.error(f"AIC model initialization failed: {e}") + self._aic_ready = False - # Get contexts for parameter control and VAD - self._processor_ctx = self._processor.get_processor_context() - self._vad_ctx = self._processor.get_vad_context() + # Get contexts for parameter control and VAD + self._processor_ctx = self._processor.get_processor_context() + self._vad_ctx = self._processor.get_vad_context() + try: # Apply initial parameters if self._enhancement_level is not None: level = self._enhancement_level if self._enabled else 0.0 self._processor_ctx.set_parameter(ProcessorParameter.EnhancementLevel, level) + if self._voice_gain is not None: self._processor_ctx.set_parameter(ProcessorParameter.VoiceGain, self._voice_gain) + except ParameterFixedError as e: + logger.error(f"AIC parameter update failed: {e}") - self._aic_ready = True - - # Log processor information - logger.debug(f"ai-coustics filter started:") - logger.debug(f" Model ID: {self._model.get_id()}") - logger.debug(f" Sample rate: {self._sample_rate} Hz") - logger.debug(f" Frames per chunk: {self._frames_per_block}") - logger.debug(f" Enhancement strength: {int((self._enhancement_level or 1.0) * 100)}%") - logger.debug(f" Optimal sample rate: {self._model.get_optimal_sample_rate()} Hz") - logger.debug( - f" Output delay: {self._processor_ctx.get_output_delay()} samples " - f"({self._processor_ctx.get_output_delay() / self._sample_rate * 1000:.2f}ms)" - ) - except Exception as e: # noqa: BLE001 - surfacing SDK initialization errors - logger.error(f"AIC model initialization failed: {e}") - self._aic_ready = False + # Log processor information + logger.debug(f"ai-coustics filter started:") + logger.debug(f" Model ID: {self._model.get_id()}") + logger.debug(f" Sample rate: {self._sample_rate} Hz") + logger.debug(f" Frames per chunk: {self._frames_per_block}") + logger.debug(f" Enhancement strength: {int((self._enhancement_level or 1.0) * 100)}%") + logger.debug(f" Optimal sample rate: {self._model.get_optimal_sample_rate()} Hz") + logger.debug( + f" Output delay: {self._processor_ctx.get_output_delay()} samples " + f"({self._processor_ctx.get_output_delay() / self._sample_rate * 1000:.2f}ms)" + ) async def stop(self): """Clean up the AIC processor when stopping. From 7f86f4ac273454582b4cfc3562fea87d59508e1b Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?G=C3=B6kmen=20G=C3=B6rgen?= Date: Mon, 19 Jan 2026 16:30:53 +0100 Subject: [PATCH 0211/1060] fix class name. --- examples/foundational/07zd-interruptible-aicoustics.py | 6 +++--- 1 file changed, 3 insertions(+), 3 deletions(-) diff --git a/examples/foundational/07zd-interruptible-aicoustics.py b/examples/foundational/07zd-interruptible-aicoustics.py index 7a2d692e4..2259ef016 100644 --- a/examples/foundational/07zd-interruptible-aicoustics.py +++ b/examples/foundational/07zd-interruptible-aicoustics.py @@ -12,7 +12,7 @@ import wave from dotenv import load_dotenv from loguru import logger -from pipecat.audio.filters.aic_filter import AICFilterV2 +from pipecat.audio.filters.aic_filter import AICFilter from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3 from pipecat.frames.frames import LLMRunFrame from pipecat.pipeline.pipeline import Pipeline @@ -45,10 +45,10 @@ audiobuffer = AudioBufferProcessor( ) -def _create_aic_filter() -> AICFilterV2: +def _create_aic_filter() -> AICFilter: license_key = os.getenv("AICOUSTICS_LICENSE_KEY", "") - return AICFilterV2( + return AICFilter( license_key=license_key, model_id="sparrow-xxs-48khz", enhancement_level=0.5, From 22b9aac2ff39b92a1306de622ee471b73a7a2eaf Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?G=C3=B6kmen=20G=C3=B6rgen?= Date: Mon, 19 Jan 2026 16:32:05 +0100 Subject: [PATCH 0212/1060] use quail model in the example. --- examples/foundational/07zd-interruptible-aicoustics.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/examples/foundational/07zd-interruptible-aicoustics.py b/examples/foundational/07zd-interruptible-aicoustics.py index 2259ef016..74252341d 100644 --- a/examples/foundational/07zd-interruptible-aicoustics.py +++ b/examples/foundational/07zd-interruptible-aicoustics.py @@ -50,7 +50,7 @@ def _create_aic_filter() -> AICFilter: return AICFilter( license_key=license_key, - model_id="sparrow-xxs-48khz", + model_id="quail-vf-l-16khz", enhancement_level=0.5, ) From f0cc54589e5f9ac44e2023b992bda4518e286958 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?G=C3=B6kmen=20G=C3=B6rgen?= Date: Mon, 19 Jan 2026 16:54:44 +0100 Subject: [PATCH 0213/1060] remove enhancement level parameter from AICFilter. --- .../foundational/07zd-interruptible-aicoustics.py | 1 - src/pipecat/audio/filters/aic_filter.py | 15 ++++++--------- 2 files changed, 6 insertions(+), 10 deletions(-) diff --git a/examples/foundational/07zd-interruptible-aicoustics.py b/examples/foundational/07zd-interruptible-aicoustics.py index 74252341d..5978741b8 100644 --- a/examples/foundational/07zd-interruptible-aicoustics.py +++ b/examples/foundational/07zd-interruptible-aicoustics.py @@ -51,7 +51,6 @@ def _create_aic_filter() -> AICFilter: return AICFilter( license_key=license_key, model_id="quail-vf-l-16khz", - enhancement_level=0.5, ) diff --git a/src/pipecat/audio/filters/aic_filter.py b/src/pipecat/audio/filters/aic_filter.py index eb4ee7f04..438d870ee 100644 --- a/src/pipecat/audio/filters/aic_filter.py +++ b/src/pipecat/audio/filters/aic_filter.py @@ -50,7 +50,6 @@ class AICFilter(BaseAudioFilter): model_id: Optional[str] = None, model_path: Optional[str] = None, model_download_dir: Optional[str] = None, - enhancement_level: Optional[float] = 1.0, voice_gain: Optional[float] = 1.0, ) -> None: """Initialize the AIC filter. @@ -63,7 +62,6 @@ class AICFilter(BaseAudioFilter): model_id is ignored and no download occurs. model_download_dir: Directory for downloading models. Defaults to a cache directory in user's home folder. - enhancement_level: Optional overall enhancement strength (0.0..1.0). voice_gain: Optional linear gain applied to detected speech (0.1..4.0). Raises: @@ -85,7 +83,6 @@ class AICFilter(BaseAudioFilter): "~/.cache/pipecat/aic-models" ) - self._enhancement_level = enhancement_level self._voice_gain = voice_gain self._enabled = True @@ -201,9 +198,9 @@ class AICFilter(BaseAudioFilter): try: # Apply initial parameters - if self._enhancement_level is not None: - level = self._enhancement_level if self._enabled else 0.0 - self._processor_ctx.set_parameter(ProcessorParameter.EnhancementLevel, level) + self._processor_ctx.set_parameter( + ProcessorParameter.Bypass, 0.0 if self._enabled else 1.0 + ) if self._voice_gain is not None: self._processor_ctx.set_parameter(ProcessorParameter.VoiceGain, self._voice_gain) @@ -215,7 +212,6 @@ class AICFilter(BaseAudioFilter): logger.debug(f" Model ID: {self._model.get_id()}") logger.debug(f" Sample rate: {self._sample_rate} Hz") logger.debug(f" Frames per chunk: {self._frames_per_block}") - logger.debug(f" Enhancement strength: {int((self._enhancement_level or 1.0) * 100)}%") logger.debug(f" Optimal sample rate: {self._model.get_optimal_sample_rate()} Hz") logger.debug( f" Output delay: {self._processor_ctx.get_output_delay()} samples " @@ -252,8 +248,9 @@ class AICFilter(BaseAudioFilter): self._enabled = frame.enable if self._processor_ctx is not None: try: - level = self._enhancement_level if self._enabled else 0.0 - self._processor_ctx.set_parameter(ProcessorParameter.EnhancementLevel, level) + self._processor_ctx.set_parameter( + ProcessorParameter.Bypass, 0.0 if self._enabled else 1.0 + ) except Exception as e: # noqa: BLE001 logger.error(f"AIC set_parameter failed: {e}") From e8d1bec03bace22a2937c037d433b3918be8b2c2 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?G=C3=B6kmen=20G=C3=B6rgen?= Date: Mon, 19 Jan 2026 17:02:25 +0100 Subject: [PATCH 0214/1060] Update src/pipecat/audio/filters/aic_filter.py Co-authored-by: Andres O. Vela --- src/pipecat/audio/filters/aic_filter.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/src/pipecat/audio/filters/aic_filter.py b/src/pipecat/audio/filters/aic_filter.py index 438d870ee..f0ce20c42 100644 --- a/src/pipecat/audio/filters/aic_filter.py +++ b/src/pipecat/audio/filters/aic_filter.py @@ -40,7 +40,7 @@ class AICFilter(BaseAudioFilter): frames using float32 samples normalized to the -1..+1 range. .. note:: - This class requires aic-sdk >= 2.0.0 (uses 'aic_sdk' module). + This class requires aic-sdk ~= 2.0.0 (uses 'aic_sdk' module). """ def __init__( From ca4e3c79f91d9c2a55c721ac2965072e3fe2b022 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?G=C3=B6kmen=20G=C3=B6rgen?= Date: Mon, 19 Jan 2026 17:03:37 +0100 Subject: [PATCH 0215/1060] Update pyproject.toml Co-authored-by: Andres O. Vela --- pyproject.toml | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/pyproject.toml b/pyproject.toml index 65a2a4bf0..7e1e381d3 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -48,7 +48,7 @@ Issues = "https://github.com/pipecat-ai/pipecat/issues" Changelog = "https://github.com/pipecat-ai/pipecat/blob/main/CHANGELOG.md" [project.optional-dependencies] -aic = [ "aic-sdk>=2.0.0" ] +aic = [ "aic-sdk~=2.0.0" ] anthropic = [ "anthropic~=0.49.0" ] assemblyai = [ "pipecat-ai[websockets-base]" ] asyncai = [ "pipecat-ai[websockets-base]" ] From abebcf37bd226e1bcf7e928b7600b5e277591c12 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?G=C3=B6kmen=20G=C3=B6rgen?= Date: Mon, 19 Jan 2026 17:06:39 +0100 Subject: [PATCH 0216/1060] address feedback. --- src/pipecat/audio/filters/aic_filter.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/src/pipecat/audio/filters/aic_filter.py b/src/pipecat/audio/filters/aic_filter.py index f0ce20c42..90bcc003c 100644 --- a/src/pipecat/audio/filters/aic_filter.py +++ b/src/pipecat/audio/filters/aic_filter.py @@ -6,7 +6,7 @@ """ai-coustics AIC SDK audio filter for Pipecat. -This module provides audio filter implementations using ai-coustics' AIC SDK to +This module provides an audio filter implementation using ai-coustics' AIC SDK to enhance audio streams in real time. It mirrors the structure of other filters like the Koala filter and integrates with Pipecat's input transport pipeline. From 5fd43faec3dd9413ec9f7ac31270efe4ab9b2e09 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?G=C3=B6kmen=20G=C3=B6rgen?= Date: Mon, 19 Jan 2026 17:33:27 +0100 Subject: [PATCH 0217/1060] add min speech duration. --- .../07zd-interruptible-aicoustics.py | 12 ++++++-- src/pipecat/audio/filters/aic_filter.py | 7 +++++ src/pipecat/audio/vad/aic_vad.py | 28 ++++++++++++++----- 3 files changed, 37 insertions(+), 10 deletions(-) diff --git a/examples/foundational/07zd-interruptible-aicoustics.py b/examples/foundational/07zd-interruptible-aicoustics.py index 5978741b8..ca205fc1d 100644 --- a/examples/foundational/07zd-interruptible-aicoustics.py +++ b/examples/foundational/07zd-interruptible-aicoustics.py @@ -62,7 +62,9 @@ transport_params = { lambda aic: DailyParams( audio_in_enabled=True, audio_out_enabled=True, - vad_analyzer=aic.create_vad_analyzer(speech_hold_duration=0.05, sensitivity=6.0), + vad_analyzer=aic.create_vad_analyzer( + speech_hold_duration=0.05, minimum_speech_duration=0.0, sensitivity=6.0 + ), audio_in_filter=aic, ) )(_create_aic_filter()), @@ -70,7 +72,9 @@ transport_params = { lambda aic: FastAPIWebsocketParams( audio_in_enabled=True, audio_out_enabled=True, - vad_analyzer=aic.create_vad_analyzer(speech_hold_duration=0.05, sensitivity=6.0), + vad_analyzer=aic.create_vad_analyzer( + speech_hold_duration=0.05, minimum_speech_duration=0.0, sensitivity=6.0 + ), audio_in_filter=aic, ) )(_create_aic_filter()), @@ -78,7 +82,9 @@ transport_params = { lambda aic: TransportParams( audio_in_enabled=True, audio_out_enabled=True, - vad_analyzer=aic.create_vad_analyzer(speech_hold_duration=0.05, sensitivity=6.0), + vad_analyzer=aic.create_vad_analyzer( + speech_hold_duration=0.05, minimum_speech_duration=0.0, sensitivity=6.0 + ), audio_in_filter=aic, ) )(_create_aic_filter()), diff --git a/src/pipecat/audio/filters/aic_filter.py b/src/pipecat/audio/filters/aic_filter.py index 90bcc003c..63f269b27 100644 --- a/src/pipecat/audio/filters/aic_filter.py +++ b/src/pipecat/audio/filters/aic_filter.py @@ -121,6 +121,7 @@ class AICFilter(BaseAudioFilter): self, *, speech_hold_duration: Optional[float] = None, + minimum_speech_duration: Optional[float] = None, sensitivity: Optional[float] = None, ): """Return an analyzer that will lazily instantiate the AIC VAD when ready. @@ -129,6 +130,9 @@ class AICFilter(BaseAudioFilter): - speech_hold_duration: How long VAD continues detecting after speech ends (in seconds). Range: 0.0 .. 20x model window length, Default (SDK): 0.05s + - minimum_speech_duration: + Minimum duration of speech required before VAD reports speech detected + (in seconds). Range: 0.0 .. 20x model window length, Default (SDK): 0.0s - sensitivity: Energy threshold sensitivity. Energy threshold = 10 ** (-sensitivity). Range: 1.0 .. 15.0, Default (SDK): 6.0 @@ -136,6 +140,8 @@ class AICFilter(BaseAudioFilter): Args: speech_hold_duration: Optional speech hold duration to configure on the VAD. If None, SDK default (0.05s) is used. + minimum_speech_duration: Optional minimum speech duration before VAD reports + speech detected. If None, SDK default (0.0s) is used. sensitivity: Optional sensitivity (energy threshold) to configure on the VAD. Range: 1.0 .. 15.0. If None, SDK default (6.0) is used. @@ -146,6 +152,7 @@ class AICFilter(BaseAudioFilter): return AICVADAnalyzer( vad_context_factory=lambda: self.get_vad_context(), speech_hold_duration=speech_hold_duration, + minimum_speech_duration=minimum_speech_duration, sensitivity=sensitivity, ) diff --git a/src/pipecat/audio/vad/aic_vad.py b/src/pipecat/audio/vad/aic_vad.py index 05b576ce8..85d70979f 100644 --- a/src/pipecat/audio/vad/aic_vad.py +++ b/src/pipecat/audio/vad/aic_vad.py @@ -10,6 +10,7 @@ Classes: from typing import Any, Callable, Optional +from aic_sdk import VadParameter from loguru import logger from pipecat.audio.vad.vad_analyzer import VADAnalyzer, VADParams @@ -29,6 +30,10 @@ class AICVADAnalyzer(VADAnalyzer): no longer contains speech (in seconds). Range: 0.0 .. 20x model window length Default (SDK): 0.05s (50ms) + - minimum_speech_duration: + Minimum duration of speech required before VAD reports speech detected (in seconds). + Range: 0.0 .. 20x model window length + Default (SDK): 0.0s - sensitivity: Controls the energy threshold sensitivity. Higher values make the detector less sensitive (require more energy to count as speech). @@ -37,7 +42,7 @@ class AICVADAnalyzer(VADAnalyzer): Default (SDK): 6.0 .. note:: - This class requires aic-sdk >= 2.0.0 (uses 'aic_sdk' module). + This class requires aic-sdk ~= 2.0.0 (uses 'aic_sdk' module). """ def __init__( @@ -45,6 +50,7 @@ class AICVADAnalyzer(VADAnalyzer): *, vad_context_factory: Optional[Callable[[], Any]] = None, speech_hold_duration: Optional[float] = None, + minimum_speech_duration: Optional[float] = None, sensitivity: Optional[float] = None, ): """Create an AIC VAD analyzer. @@ -58,6 +64,11 @@ class AICVADAnalyzer(VADAnalyzer): Optional override for AIC VAD speech hold duration (in seconds). Range: 0.0 .. 20x model window length. If None, the SDK default (0.05s) is used. + minimum_speech_duration: + Optional override for minimum speech duration before VAD reports + speech detected (in seconds). + Range: 0.0 .. 20x model window length. + If None, the SDK default (0.0s) is used. sensitivity: Optional override for AIC VAD sensitivity (energy threshold). Range: 1.0 .. 15.0. Energy threshold = 10 ** (-sensitivity). @@ -66,9 +77,11 @@ class AICVADAnalyzer(VADAnalyzer): # Use fixed VAD parameters for AIC: no user override fixed_params = VADParams(confidence=0.5, start_secs=0.0, stop_secs=0.0, min_volume=0.0) super().__init__(sample_rate=None, params=fixed_params) + self._vad_context_factory = vad_context_factory self._vad_ctx: Optional[Any] = None self._pending_speech_hold_duration: Optional[float] = speech_hold_duration + self._pending_minimum_speech_duration: Optional[float] = minimum_speech_duration self._pending_sensitivity: Optional[float] = sensitivity def bind_vad_context_factory(self, vad_context_factory: Callable[[], Any]): @@ -78,19 +91,20 @@ class AICVADAnalyzer(VADAnalyzer): def _apply_vad_params(self): """Apply optional AIC VAD parameters if available.""" - from aic_sdk import VadParameter - if self._vad_ctx is None or VadParameter is None: return + try: if self._pending_speech_hold_duration is not None: self._vad_ctx.set_parameter( - VadParameter.SpeechHoldDuration, float(self._pending_speech_hold_duration) + VadParameter.SpeechHoldDuration, self._pending_speech_hold_duration + ) + if self._pending_minimum_speech_duration is not None: + self._vad_ctx.set_parameter( + VadParameter.MinimumSpeechDuration, self._pending_minimum_speech_duration ) if self._pending_sensitivity is not None: - self._vad_ctx.set_parameter( - VadParameter.Sensitivity, float(self._pending_sensitivity) - ) + self._vad_ctx.set_parameter(VadParameter.Sensitivity, self._pending_sensitivity) except Exception as e: # noqa: BLE001 logger.debug(f"AIC VAD parameter application deferred/failed: {e}") From b77f8b065f2a44443fb90f2df4a4d72e6a686ff1 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?G=C3=B6kmen=20G=C3=B6rgen?= Date: Mon, 19 Jan 2026 17:41:52 +0100 Subject: [PATCH 0218/1060] remove voice gain. --- src/pipecat/audio/filters/aic_filter.py | 9 +-------- 1 file changed, 1 insertion(+), 8 deletions(-) diff --git a/src/pipecat/audio/filters/aic_filter.py b/src/pipecat/audio/filters/aic_filter.py index 63f269b27..3deca5788 100644 --- a/src/pipecat/audio/filters/aic_filter.py +++ b/src/pipecat/audio/filters/aic_filter.py @@ -50,7 +50,6 @@ class AICFilter(BaseAudioFilter): model_id: Optional[str] = None, model_path: Optional[str] = None, model_download_dir: Optional[str] = None, - voice_gain: Optional[float] = 1.0, ) -> None: """Initialize the AIC filter. @@ -62,7 +61,6 @@ class AICFilter(BaseAudioFilter): model_id is ignored and no download occurs. model_download_dir: Directory for downloading models. Defaults to a cache directory in user's home folder. - voice_gain: Optional linear gain applied to detected speech (0.1..4.0). Raises: ValueError: If neither model_id nor model_path is provided. @@ -83,8 +81,6 @@ class AICFilter(BaseAudioFilter): "~/.cache/pipecat/aic-models" ) - self._voice_gain = voice_gain - self._enabled = True self._sample_rate = 0 self._aic_ready = False @@ -203,14 +199,11 @@ class AICFilter(BaseAudioFilter): self._processor_ctx = self._processor.get_processor_context() self._vad_ctx = self._processor.get_vad_context() + # Apply initial parameters try: - # Apply initial parameters self._processor_ctx.set_parameter( ProcessorParameter.Bypass, 0.0 if self._enabled else 1.0 ) - - if self._voice_gain is not None: - self._processor_ctx.set_parameter(ProcessorParameter.VoiceGain, self._voice_gain) except ParameterFixedError as e: logger.error(f"AIC parameter update failed: {e}") From 65b8e0e89c550971c956cae7bf0cfe6cf08235bf Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?G=C3=B6kmen=20G=C3=B6rgen?= Date: Mon, 19 Jan 2026 17:51:31 +0100 Subject: [PATCH 0219/1060] rename `enabled` to `bypass` in AICFilter for clarity. --- src/pipecat/audio/filters/aic_filter.py | 8 ++++---- 1 file changed, 4 insertions(+), 4 deletions(-) diff --git a/src/pipecat/audio/filters/aic_filter.py b/src/pipecat/audio/filters/aic_filter.py index 3deca5788..6a18efffc 100644 --- a/src/pipecat/audio/filters/aic_filter.py +++ b/src/pipecat/audio/filters/aic_filter.py @@ -81,7 +81,7 @@ class AICFilter(BaseAudioFilter): "~/.cache/pipecat/aic-models" ) - self._enabled = True + self._bypass = False self._sample_rate = 0 self._aic_ready = False self._frames_per_block = 0 @@ -202,7 +202,7 @@ class AICFilter(BaseAudioFilter): # Apply initial parameters try: self._processor_ctx.set_parameter( - ProcessorParameter.Bypass, 0.0 if self._enabled else 1.0 + ProcessorParameter.Bypass, 1.0 if self._bypass else 0.0 ) except ParameterFixedError as e: logger.error(f"AIC parameter update failed: {e}") @@ -245,11 +245,11 @@ class AICFilter(BaseAudioFilter): None """ if isinstance(frame, FilterEnableFrame): - self._enabled = frame.enable + self._bypass = not frame.enable if self._processor_ctx is not None: try: self._processor_ctx.set_parameter( - ProcessorParameter.Bypass, 0.0 if self._enabled else 1.0 + ProcessorParameter.Bypass, 1.0 if self._bypass else 0.0 ) except Exception as e: # noqa: BLE001 logger.error(f"AIC set_parameter failed: {e}") From 18b3ee743b2c5bdf0ac746398e99ee72b846d05d Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?G=C3=B6kmen=20G=C3=B6rgen?= Date: Tue, 20 Jan 2026 10:21:37 +0100 Subject: [PATCH 0220/1060] replace `os` with `pathlib.Path` in AICFilter for path handling consistency. --- src/pipecat/audio/filters/aic_filter.py | 16 ++++++++-------- 1 file changed, 8 insertions(+), 8 deletions(-) diff --git a/src/pipecat/audio/filters/aic_filter.py b/src/pipecat/audio/filters/aic_filter.py index 6a18efffc..748064806 100644 --- a/src/pipecat/audio/filters/aic_filter.py +++ b/src/pipecat/audio/filters/aic_filter.py @@ -14,7 +14,7 @@ Classes: AICFilter: For aic-sdk (uses 'aic_sdk' module) """ -import os +from pathlib import Path from typing import List, Optional import numpy as np @@ -49,7 +49,7 @@ class AICFilter(BaseAudioFilter): license_key: str = "", model_id: Optional[str] = None, model_path: Optional[str] = None, - model_download_dir: Optional[str] = None, + model_download_dir: Optional[Path] = None, ) -> None: """Initialize the AIC filter. @@ -59,8 +59,8 @@ class AICFilter(BaseAudioFilter): is not provided. See https://artifacts.ai-coustics.io/ for available models. model_path: Optional path to a local .aicmodel file. If provided, model_id is ignored and no download occurs. - model_download_dir: Directory for downloading models. Defaults to - a cache directory in user's home folder. + model_download_dir: Directory for downloading models as a Path object. + Defaults to a cache directory in user's home folder. Raises: ValueError: If neither model_id nor model_path is provided. @@ -77,8 +77,8 @@ class AICFilter(BaseAudioFilter): self._license_key = license_key self._model_id = model_id self._model_path = model_path - self._model_download_dir = model_download_dir or os.path.expanduser( - "~/.cache/pipecat/aic-models" + self._model_download_dir = model_download_dir or ( + Path.home() / ".cache" / "pipecat" / "aic-models" ) self._bypass = False @@ -169,8 +169,8 @@ class AICFilter(BaseAudioFilter): self._model = Model.from_file(self._model_path) else: logger.debug(f"Downloading AIC model: {self._model_id}") - os.makedirs(self._model_download_dir, exist_ok=True) - model_path = await Model.download_async(self._model_id, self._model_download_dir) + self._model_download_dir.mkdir(parents=True, exist_ok=True) + model_path = await Model.download_async(self._model_id, str(self._model_download_dir)) logger.debug(f"Model downloaded to: {model_path}") self._model = Model.from_file(model_path) From e4e22319589cda95b2d198a9f8dec23332f41799 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?G=C3=B6kmen=20G=C3=B6rgen?= Date: Tue, 20 Jan 2026 13:22:00 +0100 Subject: [PATCH 0221/1060] Update src/pipecat/audio/vad/aic_vad.py Co-authored-by: Andres O. Vela --- src/pipecat/audio/vad/aic_vad.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/src/pipecat/audio/vad/aic_vad.py b/src/pipecat/audio/vad/aic_vad.py index 85d70979f..306af08d3 100644 --- a/src/pipecat/audio/vad/aic_vad.py +++ b/src/pipecat/audio/vad/aic_vad.py @@ -32,7 +32,7 @@ class AICVADAnalyzer(VADAnalyzer): Default (SDK): 0.05s (50ms) - minimum_speech_duration: Minimum duration of speech required before VAD reports speech detected (in seconds). - Range: 0.0 .. 20x model window length + Range: 0.0 .. 1.0 Default (SDK): 0.0s - sensitivity: Controls the energy threshold sensitivity. Higher values make the detector From dc8972cd94fb6d28049f7e8785262ef3ac657f9f Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?G=C3=B6kmen=20G=C3=B6rgen?= Date: Tue, 20 Jan 2026 13:44:25 +0100 Subject: [PATCH 0222/1060] log optimal number of frames for given sample rate in AICFilter. --- src/pipecat/audio/filters/aic_filter.py | 3 +++ 1 file changed, 3 insertions(+) diff --git a/src/pipecat/audio/filters/aic_filter.py b/src/pipecat/audio/filters/aic_filter.py index 748064806..e1136e411 100644 --- a/src/pipecat/audio/filters/aic_filter.py +++ b/src/pipecat/audio/filters/aic_filter.py @@ -213,6 +213,9 @@ class AICFilter(BaseAudioFilter): logger.debug(f" Sample rate: {self._sample_rate} Hz") logger.debug(f" Frames per chunk: {self._frames_per_block}") logger.debug(f" Optimal sample rate: {self._model.get_optimal_sample_rate()} Hz") + logger.debug( + f" Optimal number of frames for {self._sample_rate} Hz: {self._model.get_optimal_num_frames(self._sample_rate)}" + ) logger.debug( f" Output delay: {self._processor_ctx.get_output_delay()} samples " f"({self._processor_ctx.get_output_delay() / self._sample_rate * 1000:.2f}ms)" From 0e6a42395582f6e77d8ceeaff11443f4be67edaf Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?G=C3=B6kmen=20G=C3=B6rgen?= Date: Tue, 20 Jan 2026 13:45:11 +0100 Subject: [PATCH 0223/1060] Update src/pipecat/audio/filters/aic_filter.py Co-authored-by: Andres O. Vela --- src/pipecat/audio/filters/aic_filter.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/src/pipecat/audio/filters/aic_filter.py b/src/pipecat/audio/filters/aic_filter.py index e1136e411..79c2ed547 100644 --- a/src/pipecat/audio/filters/aic_filter.py +++ b/src/pipecat/audio/filters/aic_filter.py @@ -128,7 +128,7 @@ class AICFilter(BaseAudioFilter): Range: 0.0 .. 20x model window length, Default (SDK): 0.05s - minimum_speech_duration: Minimum duration of speech required before VAD reports speech detected - (in seconds). Range: 0.0 .. 20x model window length, Default (SDK): 0.0s + (in seconds). Range: 0.0 .. 1.0, Default (SDK): 0.0s - sensitivity: Energy threshold sensitivity. Energy threshold = 10 ** (-sensitivity). Range: 1.0 .. 15.0, Default (SDK): 6.0 From 09b5b6b12df43af36f0d57c1efad6f20a76389ba Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?G=C3=B6kmen=20G=C3=B6rgen?= Date: Tue, 20 Jan 2026 13:45:41 +0100 Subject: [PATCH 0224/1060] Update src/pipecat/audio/vad/aic_vad.py Co-authored-by: Andres O. Vela --- src/pipecat/audio/vad/aic_vad.py | 3 +-- 1 file changed, 1 insertion(+), 2 deletions(-) diff --git a/src/pipecat/audio/vad/aic_vad.py b/src/pipecat/audio/vad/aic_vad.py index 306af08d3..48c615c93 100644 --- a/src/pipecat/audio/vad/aic_vad.py +++ b/src/pipecat/audio/vad/aic_vad.py @@ -1,8 +1,7 @@ """AIC-integrated VAD analyzer that lazily binds to the AIC SDK backend. This module provides VAD analyzer implementations that query the AIC SDK's -is_speech_detected() and map it to a float confidence (1.0/0.0). They use -10 ms windows based on the sample rate and apply optional AIC VAD parameters. +is_speech_detected() and map it to a float confidence (1.0/0.0). Classes: AICVADAnalyzer: For aic-sdk >= 2.0.0 (uses 'aic_sdk' module) From 648f20db6d483a40eb3e0ae9019524f3044560cd Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?G=C3=B6kmen=20G=C3=B6rgen?= Date: Tue, 20 Jan 2026 13:49:38 +0100 Subject: [PATCH 0225/1060] Update src/pipecat/audio/vad/aic_vad.py Co-authored-by: Andres O. Vela --- src/pipecat/audio/vad/aic_vad.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/src/pipecat/audio/vad/aic_vad.py b/src/pipecat/audio/vad/aic_vad.py index 48c615c93..d263bf9d3 100644 --- a/src/pipecat/audio/vad/aic_vad.py +++ b/src/pipecat/audio/vad/aic_vad.py @@ -30,7 +30,7 @@ class AICVADAnalyzer(VADAnalyzer): Range: 0.0 .. 20x model window length Default (SDK): 0.05s (50ms) - minimum_speech_duration: - Minimum duration of speech required before VAD reports speech detected (in seconds). + Controls for how long speech needs to be present in the audio signal before the VAD considers it speech (in seconds). Range: 0.0 .. 1.0 Default (SDK): 0.0s - sensitivity: From 0e99400148210745fb66225ef520e0fde274be9f Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?G=C3=B6kmen=20G=C3=B6rgen?= Date: Tue, 20 Jan 2026 14:03:10 +0100 Subject: [PATCH 0226/1060] two dots are rust specific thinks, I'm not sure if it's familiar for Python developers. --- src/pipecat/audio/filters/aic_filter.py | 14 ++++++++------ src/pipecat/audio/vad/aic_vad.py | 14 +++++++------- 2 files changed, 15 insertions(+), 13 deletions(-) diff --git a/src/pipecat/audio/filters/aic_filter.py b/src/pipecat/audio/filters/aic_filter.py index 79c2ed547..05536aebf 100644 --- a/src/pipecat/audio/filters/aic_filter.py +++ b/src/pipecat/audio/filters/aic_filter.py @@ -37,7 +37,7 @@ class AICFilter(BaseAudioFilter): """Audio filter using ai-coustics' AIC SDK for real-time enhancement. Buffers incoming audio to the model's preferred block size and processes - frames using float32 samples normalized to the -1..+1 range. + frames using float32 samples normalized to the range -1 to +1. .. note:: This class requires aic-sdk ~= 2.0.0 (uses 'aic_sdk' module). @@ -90,7 +90,9 @@ class AICFilter(BaseAudioFilter): # Audio format constants self._bytes_per_sample = 2 # int16 = 2 bytes self._dtype = np.int16 - self._scale = 32768.0 # 2^15, for normalizing int16 (-32768..32767) to float32 (-1.0..1.0) + self._scale = ( + 32768.0 # 2^15, for normalizing int16 (-32768 to 32767) to float32 (-1.0 to 1.0) + ) # AIC SDK objects self._model = None @@ -125,13 +127,13 @@ class AICFilter(BaseAudioFilter): AIC VAD parameters: - speech_hold_duration: How long VAD continues detecting after speech ends (in seconds). - Range: 0.0 .. 20x model window length, Default (SDK): 0.05s + Range: 0.0 to 20x model window length, Default (SDK): 0.05s - minimum_speech_duration: Minimum duration of speech required before VAD reports speech detected - (in seconds). Range: 0.0 .. 1.0, Default (SDK): 0.0s + (in seconds). Range: 0.0 to 1.0, Default (SDK): 0.0s - sensitivity: Energy threshold sensitivity. Energy threshold = 10 ** (-sensitivity). - Range: 1.0 .. 15.0, Default (SDK): 6.0 + Range: 1.0 to 15.0, Default (SDK): 6.0 Args: speech_hold_duration: Optional speech hold duration to configure on the VAD. @@ -139,7 +141,7 @@ class AICFilter(BaseAudioFilter): minimum_speech_duration: Optional minimum speech duration before VAD reports speech detected. If None, SDK default (0.0s) is used. sensitivity: Optional sensitivity (energy threshold) to configure on the VAD. - Range: 1.0 .. 15.0. If None, SDK default (6.0) is used. + Range: 1.0 to 15.0. If None, SDK default (6.0) is used. Returns: A lazily-initialized AICVADAnalyzer that will bind to the VAD context diff --git a/src/pipecat/audio/vad/aic_vad.py b/src/pipecat/audio/vad/aic_vad.py index d263bf9d3..17df6d094 100644 --- a/src/pipecat/audio/vad/aic_vad.py +++ b/src/pipecat/audio/vad/aic_vad.py @@ -4,7 +4,7 @@ This module provides VAD analyzer implementations that query the AIC SDK's is_speech_detected() and map it to a float confidence (1.0/0.0). Classes: - AICVADAnalyzer: For aic-sdk >= 2.0.0 (uses 'aic_sdk' module) + AICVADAnalyzer: For aic-sdk (uses 'aic_sdk' module) """ from typing import Any, Callable, Optional @@ -27,16 +27,16 @@ class AICVADAnalyzer(VADAnalyzer): - speech_hold_duration: Controls for how long the VAD continues to detect speech after the audio signal no longer contains speech (in seconds). - Range: 0.0 .. 20x model window length + Range: 0.0 to 20x model window length Default (SDK): 0.05s (50ms) - minimum_speech_duration: Controls for how long speech needs to be present in the audio signal before the VAD considers it speech (in seconds). - Range: 0.0 .. 1.0 + Range: 0.0 to 1.0 Default (SDK): 0.0s - sensitivity: Controls the energy threshold sensitivity. Higher values make the detector less sensitive (require more energy to count as speech). - Range: 1.0 .. 15.0 + Range: 1.0 to 15.0 Formula: Energy threshold = 10 ** (-sensitivity) Default (SDK): 6.0 @@ -61,16 +61,16 @@ class AICVADAnalyzer(VADAnalyzer): will retry on set_sample_rate/first use. speech_hold_duration: Optional override for AIC VAD speech hold duration (in seconds). - Range: 0.0 .. 20x model window length. + Range: 0.0 to 20x model window length. If None, the SDK default (0.05s) is used. minimum_speech_duration: Optional override for minimum speech duration before VAD reports speech detected (in seconds). - Range: 0.0 .. 20x model window length. + Range: 0.0 to 20x model window length. If None, the SDK default (0.0s) is used. sensitivity: Optional override for AIC VAD sensitivity (energy threshold). - Range: 1.0 .. 15.0. Energy threshold = 10 ** (-sensitivity). + Range: 1.0 to 15.0. Energy threshold = 10 ** (-sensitivity). If None, the SDK default (6.0) is used. """ # Use fixed VAD parameters for AIC: no user override From 0a8588669c3b36b88b04eead73ee99583e6e64b9 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?G=C3=B6kmen=20G=C3=B6rgen?= Date: Tue, 20 Jan 2026 14:11:00 +0100 Subject: [PATCH 0227/1060] address feedback. --- src/pipecat/audio/vad/aic_vad.py | 8 +++++--- 1 file changed, 5 insertions(+), 3 deletions(-) diff --git a/src/pipecat/audio/vad/aic_vad.py b/src/pipecat/audio/vad/aic_vad.py index 17df6d094..481db099a 100644 --- a/src/pipecat/audio/vad/aic_vad.py +++ b/src/pipecat/audio/vad/aic_vad.py @@ -30,12 +30,14 @@ class AICVADAnalyzer(VADAnalyzer): Range: 0.0 to 20x model window length Default (SDK): 0.05s (50ms) - minimum_speech_duration: - Controls for how long speech needs to be present in the audio signal before the VAD considers it speech (in seconds). + Controls for how long speech needs to be present in the audio signal before the + VAD considers it speech (in seconds). Range: 0.0 to 1.0 Default (SDK): 0.0s - sensitivity: - Controls the energy threshold sensitivity. Higher values make the detector - less sensitive (require more energy to count as speech). + Controls the sensitivity (energy threshold) of the VAD. This value is used by + the VAD as the threshold a speech audio signal's energy has to exceed in order + to be considered speech. Range: 1.0 to 15.0 Formula: Energy threshold = 10 ** (-sensitivity) Default (SDK): 6.0 From 91e86658b79fed77c16d436b1ba875968aeb68bc Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?G=C3=B6kmen=20G=C3=B6rgen?= Date: Tue, 20 Jan 2026 14:37:44 +0100 Subject: [PATCH 0228/1060] force developer to set a license key, it's required. --- src/pipecat/audio/filters/aic_filter.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/src/pipecat/audio/filters/aic_filter.py b/src/pipecat/audio/filters/aic_filter.py index 05536aebf..94811479c 100644 --- a/src/pipecat/audio/filters/aic_filter.py +++ b/src/pipecat/audio/filters/aic_filter.py @@ -46,7 +46,7 @@ class AICFilter(BaseAudioFilter): def __init__( self, *, - license_key: str = "", + license_key: str, model_id: Optional[str] = None, model_path: Optional[str] = None, model_download_dir: Optional[Path] = None, From 70a85cd192aa7d33e0554d043630db445809a245 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?G=C3=B6kmen=20G=C3=B6rgen?= Date: Tue, 20 Jan 2026 14:43:57 +0100 Subject: [PATCH 0229/1060] use path for keeping the consistency between the parameters. --- src/pipecat/audio/filters/aic_filter.py | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/src/pipecat/audio/filters/aic_filter.py b/src/pipecat/audio/filters/aic_filter.py index 94811479c..cd0841d40 100644 --- a/src/pipecat/audio/filters/aic_filter.py +++ b/src/pipecat/audio/filters/aic_filter.py @@ -48,7 +48,7 @@ class AICFilter(BaseAudioFilter): *, license_key: str, model_id: Optional[str] = None, - model_path: Optional[str] = None, + model_path: Optional[Path] = None, model_download_dir: Optional[Path] = None, ) -> None: """Initialize the AIC filter. @@ -168,7 +168,7 @@ class AICFilter(BaseAudioFilter): # Load or download model if self._model_path: logger.debug(f"Loading AIC model from: {self._model_path}") - self._model = Model.from_file(self._model_path) + self._model = Model.from_file(str(self._model_path)) else: logger.debug(f"Downloading AIC model: {self._model_id}") self._model_download_dir.mkdir(parents=True, exist_ok=True) From dca7f3b5b0da3a5d4e69bc6c115a6e4e6d49d786 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?G=C3=B6kmen=20G=C3=B6rgen?= Date: Tue, 20 Jan 2026 15:04:07 +0100 Subject: [PATCH 0230/1060] add changelog. --- changelog/3408.added.md | 2 ++ changelog/3408.changed.md | 1 + changelog/3408.removed.md | 1 + 3 files changed, 4 insertions(+) create mode 100644 changelog/3408.added.md create mode 100644 changelog/3408.changed.md create mode 100644 changelog/3408.removed.md diff --git a/changelog/3408.added.md b/changelog/3408.added.md new file mode 100644 index 000000000..ea7c620e0 --- /dev/null +++ b/changelog/3408.added.md @@ -0,0 +1,2 @@ +- Added model downloading support to `AICFilter` with `model_id` and `model_download_dir` parameters. +- Added `model_path` parameter to `AICFilter` for loading local .aicmodel files. diff --git a/changelog/3408.changed.md b/changelog/3408.changed.md new file mode 100644 index 000000000..aeb563ea2 --- /dev/null +++ b/changelog/3408.changed.md @@ -0,0 +1 @@ +- Updated `AICFilter` and `AICVADAnalyzer` to use aic-sdk ~= 2.0.0. diff --git a/changelog/3408.removed.md b/changelog/3408.removed.md new file mode 100644 index 000000000..f578bf5d0 --- /dev/null +++ b/changelog/3408.removed.md @@ -0,0 +1 @@ +- Removed deprecated `AICFilter` parameters: `enhancement_level`, `voice_gain`, `noise_gate_enable`. From 34e9f224a86d9734b3437ffd2508f40236adfcdd Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?G=C3=B6kmen=20G=C3=B6rgen?= Date: Tue, 20 Jan 2026 15:27:03 +0100 Subject: [PATCH 0231/1060] Update src/pipecat/audio/vad/aic_vad.py Co-authored-by: Andres O. Vela --- src/pipecat/audio/vad/aic_vad.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/src/pipecat/audio/vad/aic_vad.py b/src/pipecat/audio/vad/aic_vad.py index 481db099a..2195c1310 100644 --- a/src/pipecat/audio/vad/aic_vad.py +++ b/src/pipecat/audio/vad/aic_vad.py @@ -68,7 +68,7 @@ class AICVADAnalyzer(VADAnalyzer): minimum_speech_duration: Optional override for minimum speech duration before VAD reports speech detected (in seconds). - Range: 0.0 to 20x model window length. + Range: 0.0 to 1.0. If None, the SDK default (0.0s) is used. sensitivity: Optional override for AIC VAD sensitivity (energy threshold). From bd92104fb3dbb554ea557ae9d827bb46de59aab0 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?G=C3=B6kmen=20G=C3=B6rgen?= Date: Fri, 23 Jan 2026 15:53:14 +0100 Subject: [PATCH 0232/1060] clarify voice confidence method behavior in AIC VAD. --- src/pipecat/audio/vad/aic_vad.py | 12 +++++++++--- 1 file changed, 9 insertions(+), 3 deletions(-) diff --git a/src/pipecat/audio/vad/aic_vad.py b/src/pipecat/audio/vad/aic_vad.py index 2195c1310..6518d810c 100644 --- a/src/pipecat/audio/vad/aic_vad.py +++ b/src/pipecat/audio/vad/aic_vad.py @@ -149,13 +149,19 @@ class AICVADAnalyzer(VADAnalyzer): return int(self.sample_rate * 0.01) if self.sample_rate > 0 else 160 def voice_confidence(self, buffer: bytes) -> float: - """Calculate voice activity confidence for the given audio buffer. + """Return voice activity detection result for the given audio buffer. + + Note: + The AIC SDK provides binary speech detection (not a probability score). + This method returns 1.0 when speech is detected and 0.0 otherwise, + rather than a true confidence value. Args: - buffer: Audio buffer to analyze. + buffer: Audio buffer (unused - AIC VAD state is updated internally + by the enhancement pipeline). Returns: - Voice confidence score is 0.0 or 1.0. + 1.0 if speech is detected, 0.0 otherwise. """ # Ensure VAD context exists (filter might have started since last call) self._ensure_vad_context_initialized() From afcdef8c8103d3b61699b06c24503394cb3f2d08 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?G=C3=B6kmen=20G=C3=B6rgen?= Date: Fri, 23 Jan 2026 15:57:40 +0100 Subject: [PATCH 0233/1060] docstring clarification. --- src/pipecat/audio/vad/aic_vad.py | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/src/pipecat/audio/vad/aic_vad.py b/src/pipecat/audio/vad/aic_vad.py index 6518d810c..dd371636d 100644 --- a/src/pipecat/audio/vad/aic_vad.py +++ b/src/pipecat/audio/vad/aic_vad.py @@ -20,8 +20,8 @@ class AICVADAnalyzer(VADAnalyzer): The analyzer can be constructed before the AIC Processor exists. Once the filter has started and the Processor is available, the provided factory will succeed and the - VadContext will be obtained. We then use the context's is_speech_detected() state - to derive confidence values. + VadContext will be obtained. The context's is_speech_detected() boolean state is + then mapped to 1.0 (speech) or 0.0 (no speech) to satisfy the VADAnalyzer interface. AIC VAD runtime parameters: - speech_hold_duration: From 58b901985294c54ac9b55e223673ca67b9296ce6 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?G=C3=B6kmen=20G=C3=B6rgen?= Date: Mon, 26 Jan 2026 09:14:16 +0100 Subject: [PATCH 0234/1060] bump aic-sdk to 2.0.1 in optional dependencies. --- pyproject.toml | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/pyproject.toml b/pyproject.toml index 7e1e381d3..4928ab3c8 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -48,7 +48,7 @@ Issues = "https://github.com/pipecat-ai/pipecat/issues" Changelog = "https://github.com/pipecat-ai/pipecat/blob/main/CHANGELOG.md" [project.optional-dependencies] -aic = [ "aic-sdk~=2.0.0" ] +aic = [ "aic-sdk~=2.0.1" ] anthropic = [ "anthropic~=0.49.0" ] assemblyai = [ "pipecat-ai[websockets-base]" ] asyncai = [ "pipecat-ai[websockets-base]" ] From a824660df7524e892afd60fe40215f053e4ab554 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?G=C3=B6kmen=20G=C3=B6rgen?= Date: Mon, 26 Jan 2026 09:56:36 +0100 Subject: [PATCH 0235/1060] add unit tests for `AICVADAnalyzer` and `AICFilter`. --- tests/test_aic_filter.py | 471 +++++++++++++++++++++++++++++++++++++++ tests/test_aic_vad.py | 322 ++++++++++++++++++++++++++ 2 files changed, 793 insertions(+) create mode 100644 tests/test_aic_filter.py create mode 100644 tests/test_aic_vad.py diff --git a/tests/test_aic_filter.py b/tests/test_aic_filter.py new file mode 100644 index 000000000..6499084af --- /dev/null +++ b/tests/test_aic_filter.py @@ -0,0 +1,471 @@ +# +# Copyright (c) 2024-2026, Daily +# +# SPDX-License-Identifier: BSD 2-Clause License +# + +import asyncio +import unittest +from pathlib import Path +from unittest.mock import AsyncMock, MagicMock, patch + +import numpy as np + +# Check if aic_sdk is available +try: + import aic_sdk + + HAS_AIC_SDK = True +except ImportError: + HAS_AIC_SDK = False + +# Module path for patching +AIC_FILTER_MODULE = "pipecat.audio.filters.aic_filter" + + +class MockProcessor: + """A lightweight mock for AIC ProcessorAsync that mimics real behavior.""" + + def __init__(self): + self.processor_ctx = MockProcessorContext() + self.vad_ctx = MockVadContext() + + def get_processor_context(self): + return self.processor_ctx + + def get_vad_context(self): + return self.vad_ctx + + async def process_async(self, audio_array): + # Return a copy of the input (simulating passthrough) + return audio_array.copy() + + +class MockProcessorContext: + """A lightweight mock for AIC ProcessorContext.""" + + def __init__(self): + self.parameters_set: list[tuple] = [] + self.reset_called = False + self._output_delay = 0 + + def get_output_delay(self): + return self._output_delay + + def set_parameter(self, param, value): + self.parameters_set.append((param, value)) + + def reset(self): + self.reset_called = True + + +class MockVadContext: + """A lightweight mock for AIC VadContext.""" + + def __init__(self, speech_detected: bool = False): + self.speech_detected = speech_detected + self.parameters_set: list[tuple] = [] + + def is_speech_detected(self) -> bool: + return self.speech_detected + + def set_parameter(self, param, value): + self.parameters_set.append((param, value)) + + +class MockModel: + """A lightweight mock for AIC Model.""" + + def __init__(self, model_id: str = "test-model"): + self._model_id = model_id + self._optimal_num_frames = 160 + self._optimal_sample_rate = 16000 + + def get_optimal_num_frames(self, sample_rate: int): + """Return optimal number of frames for the given sample rate.""" + return self._optimal_num_frames + + def get_id(self): + return self._model_id + + def get_optimal_sample_rate(self): + return self._optimal_sample_rate + + +@unittest.skipUnless(HAS_AIC_SDK, "aic-sdk not installed") +class TestAICFilter(unittest.IsolatedAsyncioTestCase): + """Test suite for AICFilter audio filter using real aic_sdk types.""" + + @classmethod + def setUpClass(cls): + """Import AICFilter after confirming aic_sdk is available.""" + from pipecat.audio.filters.aic_filter import AICFilter + from pipecat.frames.frames import FilterEnableFrame + + cls.AICFilter = AICFilter + cls.FilterEnableFrame = FilterEnableFrame + + def setUp(self): + """Set up test fixtures before each test method.""" + self.mock_model = MockModel() + self.mock_processor = MockProcessor() + + def _create_filter_with_mocks(self, **kwargs): + """Create an AICFilter with mocked SDK components.""" + filter_kwargs = { + "license_key": "test-key", + "model_id": "test-model", + } + filter_kwargs.update(kwargs) + with patch(f"{AIC_FILTER_MODULE}.set_sdk_id"): + return self.AICFilter(**filter_kwargs) + + async def _start_filter_with_mocks(self, filter_instance, sample_rate=16000): + """Start a filter with mocked SDK components.""" + with ( + patch(f"{AIC_FILTER_MODULE}.Model") as mock_model_cls, + patch(f"{AIC_FILTER_MODULE}.ProcessorConfig") as mock_config_cls, + patch(f"{AIC_FILTER_MODULE}.ProcessorAsync", return_value=self.mock_processor), + ): + mock_model_cls.from_file.return_value = self.mock_model + mock_model_cls.download_async = AsyncMock(return_value="/tmp/model") + mock_config_cls.optimal.return_value = MagicMock() + await filter_instance.start(sample_rate) + + async def test_initialization_requires_model_id_or_path(self): + """Test filter initialization fails without model_id or model_path.""" + with patch(f"{AIC_FILTER_MODULE}.set_sdk_id"): + with self.assertRaises(ValueError) as context: + self.AICFilter(license_key="test-key") + + self.assertIn("model_id", str(context.exception)) + self.assertIn("model_path", str(context.exception)) + + async def test_initialization_with_model_id(self): + """Test filter initialization with model_id.""" + filter_instance = self._create_filter_with_mocks() + + self.assertEqual(filter_instance._license_key, "test-key") + self.assertEqual(filter_instance._model_id, "test-model") + self.assertIsNone(filter_instance._model_path) + self.assertFalse(filter_instance._bypass) + + async def test_initialization_with_model_path(self): + """Test filter initialization with model_path.""" + model_path = Path("/tmp/test.aicmodel") + filter_instance = self._create_filter_with_mocks(model_id=None, model_path=model_path) + + self.assertEqual(filter_instance._model_path, model_path) + self.assertIsNone(filter_instance._model_id) + + async def test_initialization_with_custom_download_dir(self): + """Test filter initialization with custom model_download_dir.""" + download_dir = Path("/custom/cache") + filter_instance = self._create_filter_with_mocks(model_download_dir=download_dir) + + self.assertEqual(filter_instance._model_download_dir, download_dir) + + async def test_start_with_model_path(self): + """Test starting filter with a local model path.""" + model_path = Path("/tmp/test.aicmodel") + filter_instance = self._create_filter_with_mocks(model_id=None, model_path=model_path) + + with ( + patch(f"{AIC_FILTER_MODULE}.Model") as mock_model_cls, + patch(f"{AIC_FILTER_MODULE}.ProcessorConfig") as mock_config_cls, + patch(f"{AIC_FILTER_MODULE}.ProcessorAsync", return_value=self.mock_processor), + ): + mock_model_cls.from_file.return_value = self.mock_model + mock_config_cls.optimal.return_value = MagicMock() + + await filter_instance.start(16000) + + mock_model_cls.from_file.assert_called_once_with(str(model_path)) + self.assertTrue(filter_instance._aic_ready) + self.assertEqual(filter_instance._sample_rate, 16000) + self.assertEqual(filter_instance._frames_per_block, 160) + + async def test_start_with_model_id_downloads(self): + """Test starting filter with model_id triggers download.""" + filter_instance = self._create_filter_with_mocks() + + with ( + patch(f"{AIC_FILTER_MODULE}.Model") as mock_model_cls, + patch(f"{AIC_FILTER_MODULE}.ProcessorConfig") as mock_config_cls, + patch(f"{AIC_FILTER_MODULE}.ProcessorAsync", return_value=self.mock_processor), + ): + mock_model_cls.from_file.return_value = self.mock_model + mock_model_cls.download_async = AsyncMock(return_value="/tmp/model") + mock_config_cls.optimal.return_value = MagicMock() + + await filter_instance.start(16000) + + mock_model_cls.download_async.assert_called_once() + mock_model_cls.from_file.assert_called_once() + self.assertTrue(filter_instance._aic_ready) + + async def test_start_creates_processor(self): + """Test that start creates processor with correct config.""" + filter_instance = self._create_filter_with_mocks() + + with ( + patch(f"{AIC_FILTER_MODULE}.Model") as mock_model_cls, + patch(f"{AIC_FILTER_MODULE}.ProcessorConfig") as mock_config_cls, + patch( + f"{AIC_FILTER_MODULE}.ProcessorAsync", return_value=self.mock_processor + ) as mock_processor_cls, + ): + mock_model_cls.from_file.return_value = self.mock_model + mock_model_cls.download_async = AsyncMock(return_value="/tmp/model") + mock_config_cls.optimal.return_value = MagicMock() + + await filter_instance.start(16000) + + mock_config_cls.optimal.assert_called_once() + mock_processor_cls.assert_called_once() + self.assertIsNotNone(filter_instance._processor_ctx) + self.assertIsNotNone(filter_instance._vad_ctx) + + async def test_start_applies_initial_bypass_parameter(self): + """Test that start applies bypass parameter.""" + filter_instance = self._create_filter_with_mocks() + await self._start_filter_with_mocks(filter_instance) + + # Check that bypass was set to 0.0 (enabled) + bypass_params = [ + (p, v) + for p, v in self.mock_processor.processor_ctx.parameters_set + if p == aic_sdk.ProcessorParameter.Bypass + ] + self.assertTrue(len(bypass_params) > 0) + self.assertEqual(bypass_params[-1][1], 0.0) + + async def test_stop_cleans_up_resources(self): + """Test that stop properly cleans up resources.""" + filter_instance = self._create_filter_with_mocks() + await self._start_filter_with_mocks(filter_instance) + + await filter_instance.stop() + + self.assertTrue(self.mock_processor.processor_ctx.reset_called) + self.assertIsNone(filter_instance._processor) + self.assertIsNone(filter_instance._processor_ctx) + self.assertIsNone(filter_instance._vad_ctx) + self.assertIsNone(filter_instance._model) + self.assertFalse(filter_instance._aic_ready) + + async def test_stop_without_start(self): + """Test that stop can be called safely without start.""" + filter_instance = self._create_filter_with_mocks() + + # Should not raise + await filter_instance.stop() + + async def test_process_frame_enable(self): + """Test processing FilterEnableFrame to enable filtering.""" + filter_instance = self._create_filter_with_mocks() + await self._start_filter_with_mocks(filter_instance) + filter_instance._bypass = True + + enable_frame = self.FilterEnableFrame(enable=True) + await filter_instance.process_frame(enable_frame) + + self.assertFalse(filter_instance._bypass) + + async def test_process_frame_disable(self): + """Test processing FilterEnableFrame to disable filtering.""" + filter_instance = self._create_filter_with_mocks() + await self._start_filter_with_mocks(filter_instance) + + disable_frame = self.FilterEnableFrame(enable=False) + await filter_instance.process_frame(disable_frame) + + self.assertTrue(filter_instance._bypass) + + async def test_filter_when_not_ready(self): + """Test that filter returns audio unchanged when not ready.""" + filter_instance = self._create_filter_with_mocks() + # Don't call start() + + input_audio = b"\x00\x01\x02\x03" + output_audio = await filter_instance.filter(input_audio) + + self.assertEqual(output_audio, input_audio) + + async def test_filter_with_incomplete_frame(self): + """Test filtering audio with incomplete frame data.""" + filter_instance = self._create_filter_with_mocks() + await self._start_filter_with_mocks(filter_instance) + + # Create audio data for less than one frame (100 samples = 200 bytes) + samples = np.random.randint(-32768, 32767, size=100, dtype=np.int16) + input_audio = samples.tobytes() + + output_audio = await filter_instance.filter(input_audio) + + # Should return empty bytes since no complete frame + self.assertEqual(output_audio, b"") + + async def test_filter_with_complete_frame(self): + """Test filtering audio with exactly one complete frame.""" + filter_instance = self._create_filter_with_mocks() + await self._start_filter_with_mocks(filter_instance) + + # Create audio data for exactly one frame (160 samples = 320 bytes) + samples = np.random.randint(-32768, 32767, size=160, dtype=np.int16) + input_audio = samples.tobytes() + + output_audio = await filter_instance.filter(input_audio) + + self.assertIsInstance(output_audio, bytes) + self.assertEqual(len(output_audio), len(input_audio)) + + async def test_filter_with_multiple_frames(self): + """Test filtering audio with multiple complete frames.""" + filter_instance = self._create_filter_with_mocks() + await self._start_filter_with_mocks(filter_instance) + + # Create audio data for 3 complete frames (480 samples = 960 bytes) + samples = np.random.randint(-32768, 32767, size=480, dtype=np.int16) + input_audio = samples.tobytes() + + output_audio = await filter_instance.filter(input_audio) + + self.assertEqual(len(output_audio), len(input_audio)) + + async def test_filter_with_buffering(self): + """Test that filter properly buffers incomplete frames.""" + filter_instance = self._create_filter_with_mocks() + await self._start_filter_with_mocks(filter_instance) + + # First call: Send 100 samples (incomplete frame) + samples1 = np.random.randint(-32768, 32767, size=100, dtype=np.int16) + input_audio1 = samples1.tobytes() + output_audio1 = await filter_instance.filter(input_audio1) + + self.assertEqual(output_audio1, b"") + self.assertEqual(len(filter_instance._audio_buffer), 200) + + # Second call: Send 60 more samples (now we have 160 total = 1 complete frame) + samples2 = np.random.randint(-32768, 32767, size=60, dtype=np.int16) + input_audio2 = samples2.tobytes() + output_audio2 = await filter_instance.filter(input_audio2) + + self.assertEqual(len(output_audio2), 320) + self.assertEqual(len(filter_instance._audio_buffer), 0) + + async def test_filter_with_partial_buffering(self): + """Test that filter keeps remainder in buffer after processing.""" + filter_instance = self._create_filter_with_mocks() + await self._start_filter_with_mocks(filter_instance) + + # Send 250 samples (1 complete frame + 90 samples remainder) + samples = np.random.randint(-32768, 32767, size=250, dtype=np.int16) + input_audio = samples.tobytes() + + output_audio = await filter_instance.filter(input_audio) + + self.assertEqual(len(output_audio), 320) # 1 frame + self.assertEqual(len(filter_instance._audio_buffer), 180) # 90 samples * 2 bytes + + async def test_get_vad_context_before_start(self): + """Test that get_vad_context raises before start.""" + filter_instance = self._create_filter_with_mocks() + + with self.assertRaises(RuntimeError) as context: + filter_instance.get_vad_context() + + self.assertIn("not initialized", str(context.exception)) + + async def test_get_vad_context_after_start(self): + """Test that get_vad_context returns context after start.""" + filter_instance = self._create_filter_with_mocks() + await self._start_filter_with_mocks(filter_instance) + + vad_ctx = filter_instance.get_vad_context() + + self.assertEqual(vad_ctx, self.mock_processor.vad_ctx) + + async def test_create_vad_analyzer(self): + """Test create_vad_analyzer returns analyzer with factory.""" + filter_instance = self._create_filter_with_mocks() + + analyzer = filter_instance.create_vad_analyzer() + + self.assertIsNotNone(analyzer) + # Factory should be set + self.assertIsNotNone(analyzer._vad_context_factory) + + async def test_create_vad_analyzer_with_params(self): + """Test create_vad_analyzer with custom parameters.""" + filter_instance = self._create_filter_with_mocks() + + analyzer = filter_instance.create_vad_analyzer( + speech_hold_duration=0.1, + minimum_speech_duration=0.05, + sensitivity=8.0, + ) + + self.assertEqual(analyzer._pending_speech_hold_duration, 0.1) + self.assertEqual(analyzer._pending_minimum_speech_duration, 0.05) + self.assertEqual(analyzer._pending_sensitivity, 8.0) + + async def test_multiple_start_stop_cycles(self): + """Test multiple start/stop cycles.""" + filter_instance = self._create_filter_with_mocks() + + for sample_rate in [16000, 24000, 48000]: + # Create fresh mock processor for each cycle + self.mock_processor = MockProcessor() + await self._start_filter_with_mocks(filter_instance, sample_rate) + self.assertTrue(filter_instance._aic_ready) + self.assertEqual(filter_instance._sample_rate, sample_rate) + + await filter_instance.stop() + self.assertFalse(filter_instance._aic_ready) + + async def test_concurrent_filter_calls(self): + """Test that concurrent filter calls are handled safely.""" + filter_instance = self._create_filter_with_mocks() + await self._start_filter_with_mocks(filter_instance) + + samples = np.random.randint(-32768, 32767, size=160, dtype=np.int16) + input_audio = samples.tobytes() + + async def filter_audio(): + return await filter_instance.filter(input_audio) + + tasks = [filter_audio() for _ in range(10)] + results = await asyncio.gather(*tasks) + + self.assertEqual(len(results), 10) + for result in results: + self.assertIsInstance(result, bytes) + + async def test_buffer_cleared_on_stop(self): + """Test that audio buffer is cleared when stopping.""" + filter_instance = self._create_filter_with_mocks() + await self._start_filter_with_mocks(filter_instance) + + # Add incomplete frame to buffer + samples = np.random.randint(-32768, 32767, size=100, dtype=np.int16) + input_audio = samples.tobytes() + await filter_instance.filter(input_audio) + + # Verify buffer has data + self.assertGreater(len(filter_instance._audio_buffer), 0) + + # Stop should clear buffer + await filter_instance.stop() + self.assertEqual(len(filter_instance._audio_buffer), 0) + + async def test_set_sdk_id_called_on_init(self): + """Test that set_sdk_id is called during initialization.""" + with patch(f"{AIC_FILTER_MODULE}.set_sdk_id") as mock_set_sdk_id: + self.AICFilter(license_key="test-key", model_id="test-model") + + mock_set_sdk_id.assert_called_once_with(6) + + +if __name__ == "__main__": + unittest.main() diff --git a/tests/test_aic_vad.py b/tests/test_aic_vad.py new file mode 100644 index 000000000..5028da46b --- /dev/null +++ b/tests/test_aic_vad.py @@ -0,0 +1,322 @@ +# +# Copyright (c) 2024-2026, Daily +# +# SPDX-License-Identifier: BSD 2-Clause License +# + +import unittest + +# Check if aic_sdk is available +try: + import aic_sdk + + HAS_AIC_SDK = True +except ImportError: + HAS_AIC_SDK = False + + +@unittest.skipUnless(HAS_AIC_SDK, "aic-sdk not installed") +class TestAICVADAnalyzer(unittest.IsolatedAsyncioTestCase): + """Test suite for AICVADAnalyzer using real aic_sdk.""" + + @classmethod + def setUpClass(cls): + """Import AICVADAnalyzer after confirming aic_sdk is available.""" + from pipecat.audio.vad.aic_vad import AICVADAnalyzer + + cls.AICVADAnalyzer = AICVADAnalyzer + + def test_initialization_without_factory(self): + """Test analyzer initialization without a factory.""" + analyzer = self.AICVADAnalyzer() + + self.assertIsNone(analyzer._vad_context_factory) + self.assertIsNone(analyzer._vad_ctx) + # Fixed params should be set + self.assertEqual(analyzer._params.confidence, 0.5) + self.assertEqual(analyzer._params.start_secs, 0.0) + self.assertEqual(analyzer._params.stop_secs, 0.0) + self.assertEqual(analyzer._params.min_volume, 0.0) + + def test_initialization_with_factory(self): + """Test analyzer initialization with a factory.""" + # Create a mock VAD context for testing + mock_vad_ctx = MockVadContext() + factory = lambda: mock_vad_ctx + analyzer = self.AICVADAnalyzer(vad_context_factory=factory) + + self.assertIsNotNone(analyzer._vad_context_factory) + + def test_initialization_with_vad_params(self): + """Test analyzer initialization with VAD parameters.""" + analyzer = self.AICVADAnalyzer( + speech_hold_duration=0.1, + minimum_speech_duration=0.05, + sensitivity=8.0, + ) + + self.assertEqual(analyzer._pending_speech_hold_duration, 0.1) + self.assertEqual(analyzer._pending_minimum_speech_duration, 0.05) + self.assertEqual(analyzer._pending_sensitivity, 8.0) + + def test_bind_vad_context_factory(self): + """Test binding a factory post-construction.""" + mock_vad_ctx = MockVadContext() + analyzer = self.AICVADAnalyzer() + factory = lambda: mock_vad_ctx + + analyzer.bind_vad_context_factory(factory) + + self.assertEqual(analyzer._vad_context_factory, factory) + # Should have attempted to initialize + self.assertEqual(analyzer._vad_ctx, mock_vad_ctx) + + def test_bind_vad_context_factory_applies_params(self): + """Test that binding factory applies pending VAD params.""" + mock_vad_ctx = MockVadContext() + analyzer = self.AICVADAnalyzer( + speech_hold_duration=0.1, + minimum_speech_duration=0.05, + sensitivity=8.0, + ) + factory = lambda: mock_vad_ctx + + analyzer.bind_vad_context_factory(factory) + + # Verify parameters were applied + self.assertIn( + (aic_sdk.VadParameter.SpeechHoldDuration, 0.1), + mock_vad_ctx.parameters_set, + ) + self.assertIn( + (aic_sdk.VadParameter.MinimumSpeechDuration, 0.05), + mock_vad_ctx.parameters_set, + ) + self.assertIn( + (aic_sdk.VadParameter.Sensitivity, 8.0), + mock_vad_ctx.parameters_set, + ) + + def test_set_sample_rate(self): + """Test setting sample rate.""" + analyzer = self.AICVADAnalyzer() + + analyzer.set_sample_rate(16000) + + self.assertEqual(analyzer._sample_rate, 16000) + + def test_set_sample_rate_with_init_sample_rate(self): + """Test that init_sample_rate takes precedence.""" + # Create analyzer and manually set _init_sample_rate + analyzer = self.AICVADAnalyzer() + analyzer._init_sample_rate = 48000 + + analyzer.set_sample_rate(16000) + + # init_sample_rate should take precedence + self.assertEqual(analyzer._sample_rate, 48000) + + def test_set_sample_rate_triggers_context_init(self): + """Test that set_sample_rate attempts context initialization.""" + mock_vad_ctx = MockVadContext() + factory = lambda: mock_vad_ctx + analyzer = self.AICVADAnalyzer(vad_context_factory=factory) + + analyzer.set_sample_rate(16000) + + self.assertEqual(analyzer._vad_ctx, mock_vad_ctx) + + def test_num_frames_required_with_sample_rate(self): + """Test num_frames_required returns correct value.""" + analyzer = self.AICVADAnalyzer() + analyzer.set_sample_rate(16000) + + frames = analyzer.num_frames_required() + + # 10ms at 16kHz = 160 frames + self.assertEqual(frames, 160) + + def test_num_frames_required_different_sample_rates(self): + """Test num_frames_required for different sample rates.""" + analyzer = self.AICVADAnalyzer() + + test_cases = [ + (8000, 80), # 10ms at 8kHz + (16000, 160), # 10ms at 16kHz + (24000, 240), # 10ms at 24kHz + (48000, 480), # 10ms at 48kHz + ] + + for sample_rate, expected_frames in test_cases: + analyzer.set_sample_rate(sample_rate) + frames = analyzer.num_frames_required() + self.assertEqual(frames, expected_frames, f"Failed for {sample_rate}Hz") + + def test_num_frames_required_no_sample_rate(self): + """Test num_frames_required returns default when no sample rate.""" + analyzer = self.AICVADAnalyzer() + + frames = analyzer.num_frames_required() + + # Default is 160 + self.assertEqual(frames, 160) + + def test_voice_confidence_no_context(self): + """Test voice_confidence returns 0.0 when no context.""" + analyzer = self.AICVADAnalyzer() + + confidence = analyzer.voice_confidence(b"\x00" * 320) + + self.assertEqual(confidence, 0.0) + + def test_voice_confidence_speech_detected(self): + """Test voice_confidence returns 1.0 when speech detected.""" + mock_vad_ctx = MockVadContext(speech_detected=True) + factory = lambda: mock_vad_ctx + analyzer = self.AICVADAnalyzer(vad_context_factory=factory) + analyzer.set_sample_rate(16000) + + confidence = analyzer.voice_confidence(b"\x00" * 320) + + self.assertEqual(confidence, 1.0) + + def test_voice_confidence_no_speech(self): + """Test voice_confidence returns 0.0 when no speech.""" + mock_vad_ctx = MockVadContext(speech_detected=False) + factory = lambda: mock_vad_ctx + analyzer = self.AICVADAnalyzer(vad_context_factory=factory) + analyzer.set_sample_rate(16000) + + confidence = analyzer.voice_confidence(b"\x00" * 320) + + self.assertEqual(confidence, 0.0) + + def test_voice_confidence_handles_exception(self): + """Test voice_confidence handles exceptions gracefully.""" + mock_vad_ctx = MockVadContext(raise_on_detect=True) + factory = lambda: mock_vad_ctx + analyzer = self.AICVADAnalyzer(vad_context_factory=factory) + analyzer.set_sample_rate(16000) + + confidence = analyzer.voice_confidence(b"\x00" * 320) + + self.assertEqual(confidence, 0.0) + + def test_lazy_initialization(self): + """Test that VAD context is lazily initialized.""" + call_count = 0 + mock_vad_ctx = MockVadContext() + + def counting_factory(): + nonlocal call_count + call_count += 1 + return mock_vad_ctx + + analyzer = self.AICVADAnalyzer(vad_context_factory=counting_factory) + + # Factory not called yet + self.assertEqual(call_count, 0) + + # First call to voice_confidence triggers initialization + analyzer.voice_confidence(b"\x00" * 320) + self.assertEqual(call_count, 1) + + # Subsequent calls don't re-initialize + analyzer.voice_confidence(b"\x00" * 320) + analyzer.voice_confidence(b"\x00" * 320) + self.assertEqual(call_count, 1) + + def test_deferred_initialization_on_factory_failure(self): + """Test that initialization is deferred when factory fails.""" + call_count = 0 + mock_vad_ctx = MockVadContext(speech_detected=True) + + def failing_then_succeeding_factory(): + nonlocal call_count + call_count += 1 + if call_count < 3: + raise RuntimeError("Not ready yet") + return mock_vad_ctx + + analyzer = self.AICVADAnalyzer(vad_context_factory=failing_then_succeeding_factory) + + # First two calls fail, should return 0.0 + self.assertEqual(analyzer.voice_confidence(b"\x00" * 320), 0.0) + self.assertEqual(analyzer.voice_confidence(b"\x00" * 320), 0.0) + + # Third call succeeds + self.assertEqual(analyzer.voice_confidence(b"\x00" * 320), 1.0) + + def test_apply_vad_params_deferred_on_failure(self): + """Test that VAD param application handles exceptions.""" + mock_vad_ctx = MockVadContext(raise_on_set_param=True) + factory = lambda: mock_vad_ctx + + analyzer = self.AICVADAnalyzer( + vad_context_factory=factory, + speech_hold_duration=0.1, + ) + + # Should not raise, just log debug message + analyzer.bind_vad_context_factory(factory) + + # Context should still be set despite param failure + self.assertEqual(analyzer._vad_ctx, mock_vad_ctx) + + def test_apply_vad_params_only_set_values(self): + """Test that only specified VAD params are applied.""" + mock_vad_ctx = MockVadContext() + factory = lambda: mock_vad_ctx + analyzer = self.AICVADAnalyzer( + vad_context_factory=factory, + speech_hold_duration=0.1, + # minimum_speech_duration and sensitivity not set + ) + + analyzer.bind_vad_context_factory(factory) + + # Only SpeechHoldDuration should be set + self.assertEqual(len(mock_vad_ctx.parameters_set), 1) + self.assertIn( + (aic_sdk.VadParameter.SpeechHoldDuration, 0.1), + mock_vad_ctx.parameters_set, + ) + + def test_fixed_vad_params(self): + """Test that VAD uses fixed parameters.""" + analyzer = self.AICVADAnalyzer() + + # These are the fixed params for AIC VAD + self.assertEqual(analyzer._params.confidence, 0.5) + self.assertEqual(analyzer._params.start_secs, 0.0) + self.assertEqual(analyzer._params.stop_secs, 0.0) + self.assertEqual(analyzer._params.min_volume, 0.0) + + +class MockVadContext: + """A lightweight mock for AIC VadContext that mimics real behavior.""" + + def __init__( + self, + speech_detected: bool = False, + raise_on_detect: bool = False, + raise_on_set_param: bool = False, + ): + self.speech_detected = speech_detected + self.raise_on_detect = raise_on_detect + self.raise_on_set_param = raise_on_set_param + self.parameters_set: list[tuple] = [] + + def is_speech_detected(self) -> bool: + if self.raise_on_detect: + raise RuntimeError("VAD error") + return self.speech_detected + + def set_parameter(self, param, value): + if self.raise_on_set_param: + raise RuntimeError("Param error") + self.parameters_set.append((param, value)) + + +if __name__ == "__main__": + unittest.main() From bd618d64e3f215dc08d878ce198d5a0adbf77e49 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?G=C3=B6kmen=20G=C3=B6rgen?= Date: Mon, 26 Jan 2026 10:06:16 +0100 Subject: [PATCH 0236/1060] Update src/pipecat/audio/filters/aic_filter.py Co-authored-by: Andres O. Vela --- src/pipecat/audio/filters/aic_filter.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/src/pipecat/audio/filters/aic_filter.py b/src/pipecat/audio/filters/aic_filter.py index cd0841d40..66012c6c3 100644 --- a/src/pipecat/audio/filters/aic_filter.py +++ b/src/pipecat/audio/filters/aic_filter.py @@ -127,7 +127,7 @@ class AICFilter(BaseAudioFilter): AIC VAD parameters: - speech_hold_duration: How long VAD continues detecting after speech ends (in seconds). - Range: 0.0 to 20x model window length, Default (SDK): 0.05s + Range: 0.0 to 100x model window length, Default (SDK): 0.05s - minimum_speech_duration: Minimum duration of speech required before VAD reports speech detected (in seconds). Range: 0.0 to 1.0, Default (SDK): 0.0s From 3c463c9416d5dc68f7c26c8b779b14d21acb5f5e Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?G=C3=B6kmen=20G=C3=B6rgen?= Date: Mon, 26 Jan 2026 10:06:33 +0100 Subject: [PATCH 0237/1060] Update src/pipecat/audio/vad/aic_vad.py Co-authored-by: Andres O. Vela --- src/pipecat/audio/vad/aic_vad.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/src/pipecat/audio/vad/aic_vad.py b/src/pipecat/audio/vad/aic_vad.py index dd371636d..a608302bf 100644 --- a/src/pipecat/audio/vad/aic_vad.py +++ b/src/pipecat/audio/vad/aic_vad.py @@ -27,7 +27,7 @@ class AICVADAnalyzer(VADAnalyzer): - speech_hold_duration: Controls for how long the VAD continues to detect speech after the audio signal no longer contains speech (in seconds). - Range: 0.0 to 20x model window length + Range: 0.0 to 100x model window length Default (SDK): 0.05s (50ms) - minimum_speech_duration: Controls for how long speech needs to be present in the audio signal before the From 7572d63f8f1a1b381d869389b0a2cf5970305f5a Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?G=C3=B6kmen=20G=C3=B6rgen?= Date: Mon, 26 Jan 2026 10:06:40 +0100 Subject: [PATCH 0238/1060] Update src/pipecat/audio/vad/aic_vad.py Co-authored-by: Andres O. Vela --- src/pipecat/audio/vad/aic_vad.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/src/pipecat/audio/vad/aic_vad.py b/src/pipecat/audio/vad/aic_vad.py index a608302bf..959c6e35e 100644 --- a/src/pipecat/audio/vad/aic_vad.py +++ b/src/pipecat/audio/vad/aic_vad.py @@ -63,7 +63,7 @@ class AICVADAnalyzer(VADAnalyzer): will retry on set_sample_rate/first use. speech_hold_duration: Optional override for AIC VAD speech hold duration (in seconds). - Range: 0.0 to 20x model window length. + Range: 0.0 to 100x model window length. If None, the SDK default (0.05s) is used. minimum_speech_duration: Optional override for minimum speech duration before VAD reports From 4bce58f27046b06bc02912d55cd6105b588cf0bb Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?G=C3=B6kmen=20G=C3=B6rgen?= Date: Mon, 26 Jan 2026 10:15:15 +0100 Subject: [PATCH 0239/1060] update changelog and remove outdated dependency notes --- changelog/3408.added.md | 1 + changelog/3408.changed.md | 2 +- src/pipecat/audio/filters/aic_filter.py | 3 --- src/pipecat/audio/vad/aic_vad.py | 3 --- 4 files changed, 2 insertions(+), 7 deletions(-) diff --git a/changelog/3408.added.md b/changelog/3408.added.md index ea7c620e0..fb528c7a7 100644 --- a/changelog/3408.added.md +++ b/changelog/3408.added.md @@ -1,2 +1,3 @@ - Added model downloading support to `AICFilter` with `model_id` and `model_download_dir` parameters. - Added `model_path` parameter to `AICFilter` for loading local .aicmodel files. +- Added unit tests for `AICFilter` and `AICVADAnalyzer`. diff --git a/changelog/3408.changed.md b/changelog/3408.changed.md index aeb563ea2..9436b6074 100644 --- a/changelog/3408.changed.md +++ b/changelog/3408.changed.md @@ -1 +1 @@ -- Updated `AICFilter` and `AICVADAnalyzer` to use aic-sdk ~= 2.0.0. +- Updated `AICFilter` and `AICVADAnalyzer` to use aic-sdk ~= 2.0.1. diff --git a/src/pipecat/audio/filters/aic_filter.py b/src/pipecat/audio/filters/aic_filter.py index cd0841d40..cdb77b79e 100644 --- a/src/pipecat/audio/filters/aic_filter.py +++ b/src/pipecat/audio/filters/aic_filter.py @@ -38,9 +38,6 @@ class AICFilter(BaseAudioFilter): Buffers incoming audio to the model's preferred block size and processes frames using float32 samples normalized to the range -1 to +1. - - .. note:: - This class requires aic-sdk ~= 2.0.0 (uses 'aic_sdk' module). """ def __init__( diff --git a/src/pipecat/audio/vad/aic_vad.py b/src/pipecat/audio/vad/aic_vad.py index dd371636d..3cdd080bf 100644 --- a/src/pipecat/audio/vad/aic_vad.py +++ b/src/pipecat/audio/vad/aic_vad.py @@ -41,9 +41,6 @@ class AICVADAnalyzer(VADAnalyzer): Range: 1.0 to 15.0 Formula: Energy threshold = 10 ** (-sensitivity) Default (SDK): 6.0 - - .. note:: - This class requires aic-sdk ~= 2.0.0 (uses 'aic_sdk' module). """ def __init__( From b9390ccb1b5593d71e6e92e30a50d73f9e00ada7 Mon Sep 17 00:00:00 2001 From: Luke Payyapilli Date: Mon, 26 Jan 2026 10:08:17 -0500 Subject: [PATCH 0240/1060] Address review: remove UserStartedSpeakingFrame, add explanatory comment --- changelog/3429.added.md | 2 +- src/pipecat/services/google/gemini_live/llm.py | 11 ++++++++++- 2 files changed, 11 insertions(+), 2 deletions(-) diff --git a/changelog/3429.added.md b/changelog/3429.added.md index 1ba0279d7..905dcac78 100644 --- a/changelog/3429.added.md +++ b/changelog/3429.added.md @@ -1 +1 @@ -- Added handling for `server_content.interrupted` signal in Gemini Live services for faster interruption response. +- Added handling for `server_content.interrupted` signal in the Gemini Live service for faster interruption response in the case where there isn't already turn tracking in the pipeline, e.g. local VAD + context aggregators. When there is already turn tracking in the pipeline, the additional interruption does no harm. diff --git a/src/pipecat/services/google/gemini_live/llm.py b/src/pipecat/services/google/gemini_live/llm.py index 7a6f55f83..895489955 100644 --- a/src/pipecat/services/google/gemini_live/llm.py +++ b/src/pipecat/services/google/gemini_live/llm.py @@ -1199,8 +1199,17 @@ class GeminiLiveLLMService(LLMService): self._check_and_reset_failure_counter() if message.server_content and message.server_content.interrupted: + # NOTE: while the service triggers interruptions in + # the specific case of barge-ins, it does *not* + # emit UserStarted/StoppedSpeakingFrames, as the + # Gemini Live API does not give us broadly reliable + # signals to base those off of. Pipelines that + # require turn tracking (like those using context + # aggregators) still need an independent way to + # track turns, such as local Silero VAD in + # combination with the context aggregator default + # turn strategies. logger.debug("Gemini VAD: interrupted signal received") - await self.broadcast_frame(UserStartedSpeakingFrame()) await self.push_interruption_task_frame_and_wait() elif message.server_content and message.server_content.model_turn: await self._handle_msg_model_turn(message) From 960d0faea5f39ff2d2d0ede3f6d28950bb783ba0 Mon Sep 17 00:00:00 2001 From: Sam Sykes Date: Mon, 26 Jan 2026 15:48:04 +0000 Subject: [PATCH 0241/1060] support `is_eou` for final segment in utterance --- src/pipecat/services/speechmatics/stt.py | 11 +++++++++-- 1 file changed, 9 insertions(+), 2 deletions(-) diff --git a/src/pipecat/services/speechmatics/stt.py b/src/pipecat/services/speechmatics/stt.py index 457388c31..8d45b4e9d 100644 --- a/src/pipecat/services/speechmatics/stt.py +++ b/src/pipecat/services/speechmatics/stt.py @@ -738,9 +738,16 @@ class SpeechmaticsSTTService(STTService): # If final, then re-parse into TranscriptionFrame if finalized: - frames += [TranscriptionFrame(**attr_from_segment(segment)) for segment in segments] + frames += [ + TranscriptionFrame( + **attr_from_segment(segment), finalized=segment.get("is_eou", False) + ) + for segment in segments + ] finalized_text = "|".join([s["text"] for s in segments]) - await self._handle_transcription(finalized_text, True, segments[0]["language"]) + await self._handle_transcription( + finalized_text, is_final=True, language=segments[0]["language"] + ) logger.debug(f"{self} finalized transcript: {[f.text for f in frames]}") # Return as interim results (unformatted) From 8b88280bb10a5bc1fb22e00fe39f358669df25b2 Mon Sep 17 00:00:00 2001 From: Sam Sykes Date: Mon, 26 Jan 2026 15:52:42 +0000 Subject: [PATCH 0242/1060] Default to using `EXTERNAL` mode. --- src/pipecat/services/speechmatics/stt.py | 6 +++--- 1 file changed, 3 insertions(+), 3 deletions(-) diff --git a/src/pipecat/services/speechmatics/stt.py b/src/pipecat/services/speechmatics/stt.py index 8d45b4e9d..ed74c50d4 100644 --- a/src/pipecat/services/speechmatics/stt.py +++ b/src/pipecat/services/speechmatics/stt.py @@ -67,7 +67,7 @@ class TurnDetectionMode(str, Enum): """Endpoint and turn detection handling mode. How the STT engine handles the endpointing of speech. If using Pipecat's built-in endpointing, - then use `TurnDetectionMode.FIXED` (default). + then use `TurnDetectionMode.EXTERNAL` (default). To use the STT engine's built-in endpointing, then use `TurnDetectionMode.ADAPTIVE` for simple voice activity detection or `TurnDetectionMode.SMART_TURN` for more advanced ML-based @@ -107,7 +107,7 @@ class SpeechmaticsSTTService(STTService): turn_detection_mode: Endpoint handling, one of `TurnDetectionMode.FIXED`, `TurnDetectionMode.EXTERNAL`, `TurnDetectionMode.ADAPTIVE` and - `TurnDetectionMode.SMART_TURN`. Defaults to `TurnDetectionMode.FIXED`. + `TurnDetectionMode.SMART_TURN`. Defaults to `TurnDetectionMode.EXTERNAL`. speaker_active_format: Formatter for active speaker ID. This formatter is used to format the text output for individual speakers and ensures that the context is clear for @@ -208,7 +208,7 @@ class SpeechmaticsSTTService(STTService): language: Language | str = Language.EN # Endpointing mode - turn_detection_mode: TurnDetectionMode = TurnDetectionMode.FIXED + turn_detection_mode: TurnDetectionMode = TurnDetectionMode.EXTERNAL # Output formatting speaker_active_format: str | None = None From 0c69ae63710d426b3d372dd7a6b5868c0c689ae5 Mon Sep 17 00:00:00 2001 From: Sam Sykes Date: Mon, 26 Jan 2026 16:07:59 +0000 Subject: [PATCH 0243/1060] Changelog entry. --- changelog/3562.changed.md | 1 + 1 file changed, 1 insertion(+) create mode 100644 changelog/3562.changed.md diff --git a/changelog/3562.changed.md b/changelog/3562.changed.md new file mode 100644 index 000000000..491e466ac --- /dev/null +++ b/changelog/3562.changed.md @@ -0,0 +1 @@ +- Added support for TTFS `finalize` attribute in `SpeechmaticsSTTServce` and set the default mode to `EXTERNAL` to support Pipecat-controlled VAD. From ea94939add121c54039c1cba07314a686a959a78 Mon Sep 17 00:00:00 2001 From: Sam Sykes Date: Mon, 26 Jan 2026 16:24:56 +0000 Subject: [PATCH 0244/1060] update dependency --- pyproject.toml | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/pyproject.toml b/pyproject.toml index e99ab62bc..e2668d65d 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -109,7 +109,7 @@ silero = [ "onnxruntime>=1.20.1,<2" ] simli = [ "simli-ai~=1.0.3"] soniox = [ "pipecat-ai[websockets-base]" ] soundfile = [ "soundfile~=0.13.1" ] -speechmatics = [ "speechmatics-voice[smart]>=0.2.6" ] +speechmatics = [ "speechmatics-voice[smart]>=0.2.8" ] strands = [ "strands-agents>=1.9.1,<2" ] tavus=[] together = [] From fc1444c9d628fbcbc492bde1e4642c666ba926b4 Mon Sep 17 00:00:00 2001 From: Sam Sykes Date: Mon, 26 Jan 2026 16:25:37 +0000 Subject: [PATCH 0245/1060] Updated changelog --- changelog/3562.changed.md | 1 + 1 file changed, 1 insertion(+) diff --git a/changelog/3562.changed.md b/changelog/3562.changed.md index 491e466ac..09090672b 100644 --- a/changelog/3562.changed.md +++ b/changelog/3562.changed.md @@ -1 +1,2 @@ - Added support for TTFS `finalize` attribute in `SpeechmaticsSTTServce` and set the default mode to `EXTERNAL` to support Pipecat-controlled VAD. +- Changed dependency to `speechmatics-voice[smart]>=0.2.8` From 9c6b11cecfd45fef91181c6a74f786db67eed14e Mon Sep 17 00:00:00 2001 From: Mark Backman Date: Mon, 26 Jan 2026 13:03:39 -0500 Subject: [PATCH 0246/1060] Update README links to use absolute URLs --- examples/foundational/README.md | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/examples/foundational/README.md b/examples/foundational/README.md index bc25d42ca..5800efff3 100644 --- a/examples/foundational/README.md +++ b/examples/foundational/README.md @@ -4,7 +4,7 @@ This directory contains examples showing how to build voice and multimodal agent ## Setup -1. Follow the [README](../../README.md#%EF%B8%8F-contributing-to-the-framework) steps to get your local environment configured. +1. Follow the [README](https://github.com/pipecat-ai/pipecat/blob/main/README.md#%EF%B8%8F-contributing-to-the-framework) steps to get your local environment configured. > **Run from root directory**: Make sure you are running the steps from the root directory. @@ -140,4 +140,4 @@ uv run python --host 0.0.0.0 --port 8080 - **Connection errors**: Verify API keys in `.env` file - **Port conflicts**: Use `--port` to change the port -For more examples, visit our the [`pipecat-examples repository](https://github.com/pipecat-ai/pipecat-examples). +For more examples, visit our the [pipecat-examples repository](https://github.com/pipecat-ai/pipecat-examples). From 2f23f2e39cf1469ac0fa2f85a1a1fd3eb19ffb4f Mon Sep 17 00:00:00 2001 From: filipi87 Date: Mon, 26 Jan 2026 17:08:27 -0300 Subject: [PATCH 0247/1060] Fixed race condition in OpenAIRealtimeBetaLLMService that could cause an error when truncating the conversation. --- src/pipecat/services/openai_realtime_beta/openai.py | 8 ++++++++ 1 file changed, 8 insertions(+) diff --git a/src/pipecat/services/openai_realtime_beta/openai.py b/src/pipecat/services/openai_realtime_beta/openai.py index 128bcc93a..1199d8556 100644 --- a/src/pipecat/services/openai_realtime_beta/openai.py +++ b/src/pipecat/services/openai_realtime_beta/openai.py @@ -525,6 +525,14 @@ class OpenAIRealtimeBetaLLMService(LLMService): # note: ttfb is faster by 1/2 RTT than ttfb as measured for other services, since we're getting # this event from the server await self.stop_ttfb_metrics() + + if self._current_audio_response and self._current_audio_response.item_id != evt.item_id: + logger.warning( + f"Received a new audio delta for an already completed audio response before receiving the BotStoppedSpeakingFrame." + ) + logger.debug("Forcing previous audio response to None") + self._current_audio_response = None + if not self._current_audio_response: self._current_audio_response = CurrentAudioResponse( item_id=evt.item_id, From 98fcfd7c91d6380436d4bacd89ed8c51922b343f Mon Sep 17 00:00:00 2001 From: filipi87 Date: Mon, 26 Jan 2026 17:19:08 -0300 Subject: [PATCH 0248/1060] Adding changelog entry for the OpenAiRealtimeBetaLLMService fix. --- changelog/3567.fixed.md | 1 + 1 file changed, 1 insertion(+) create mode 100644 changelog/3567.fixed.md diff --git a/changelog/3567.fixed.md b/changelog/3567.fixed.md new file mode 100644 index 000000000..92ecabeca --- /dev/null +++ b/changelog/3567.fixed.md @@ -0,0 +1 @@ +- Fixed race condition in `OpenAIRealtimeBetaLLMService` that could cause an error when truncating the conversation. From 15d5d1159e0e771178a1f6eca9732db2e91b620a Mon Sep 17 00:00:00 2001 From: Paul Kompfner Date: Fri, 23 Jan 2026 14:55:53 -0500 Subject: [PATCH 0249/1060] Added a changelog fragment for PR 3406 --- changelog/3406.fixed.md | 1 + 1 file changed, 1 insertion(+) create mode 100644 changelog/3406.fixed.md diff --git a/changelog/3406.fixed.md b/changelog/3406.fixed.md new file mode 100644 index 000000000..b4eae4548 --- /dev/null +++ b/changelog/3406.fixed.md @@ -0,0 +1 @@ +- Fixed an issue where if you were using `OpenRouterLLMService` with a Gemini model, it wouldn't handle multiple `"system"` messages as expected (and as we do in `GoogleLLMService`), which is to convert subsequent ones into `"user"` messages. Instead, the latest `"system"` message would overwrite the previous ones. From febd52274d1d7d776c5ab6bc4ca27c4c06b07139 Mon Sep 17 00:00:00 2001 From: Mark Backman Date: Mon, 26 Jan 2026 16:42:00 -0500 Subject: [PATCH 0250/1060] Add changelog fragment for PR 3536 --- changelog/3536.fixed.md | 1 + 1 file changed, 1 insertion(+) create mode 100644 changelog/3536.fixed.md diff --git a/changelog/3536.fixed.md b/changelog/3536.fixed.md new file mode 100644 index 000000000..f70bd62b6 --- /dev/null +++ b/changelog/3536.fixed.md @@ -0,0 +1 @@ +- Fixed a logging issue where non-ASCII characters (e.g., Japanese, Chinese, etc.) were being unnecessarily escaped to Unicode sequences when function call occurred. From 3a71865cf4c250b4bbf5c9bc8b3c4e618cfaadeb Mon Sep 17 00:00:00 2001 From: Sam Sykes Date: Mon, 26 Jan 2026 23:11:25 +0000 Subject: [PATCH 0251/1060] removed old metrics --- src/pipecat/services/speechmatics/stt.py | 47 ++++++++---------------- 1 file changed, 16 insertions(+), 31 deletions(-) diff --git a/src/pipecat/services/speechmatics/stt.py b/src/pipecat/services/speechmatics/stt.py index ed74c50d4..d02b4360b 100644 --- a/src/pipecat/services/speechmatics/stt.py +++ b/src/pipecat/services/speechmatics/stt.py @@ -598,9 +598,6 @@ class SpeechmaticsSTTService(STTService): if segments: await self._send_frames(segments) - # Update metrics - await self._emit_metrics(message.get("metadata", {}).get("processing_time", 0.0)) - async def _handle_segment(self, message: dict[str, Any]) -> None: """Handle AddSegment events. @@ -738,23 +735,33 @@ class SpeechmaticsSTTService(STTService): # If final, then re-parse into TranscriptionFrame if finalized: - frames += [ - TranscriptionFrame( - **attr_from_segment(segment), finalized=segment.get("is_eou", False) - ) - for segment in segments - ] + # Do any segments have `is_eou` set to True? + if ( + any(segment.get("is_eou", False) for segment in segments) + and self._finalize_requested + ): + self.confirm_finalize() + + # Add the finalized frames + frames += [TranscriptionFrame(**attr_from_segment(segment)) for segment in segments] + + # Handle the text (for metrics reporting) finalized_text = "|".join([s["text"] for s in segments]) await self._handle_transcription( finalized_text, is_final=True, language=segments[0]["language"] ) + + # Log the frames logger.debug(f"{self} finalized transcript: {[f.text for f in frames]}") # Return as interim results (unformatted) else: + # Add the interim frames frames += [ InterimTranscriptionFrame(**attr_from_segment(segment)) for segment in segments ] + + # Log the frames logger.debug(f"{self} interim transcript: {[f.text for f in frames]}") # Send the frames @@ -811,28 +818,6 @@ class SpeechmaticsSTTService(STTService): yield ErrorFrame(f"Speechmatics error: {e}") await self._disconnect() - async def _emit_metrics(self, processing_time: float) -> None: - """Create TTFB metrics. - - The TTFB is the seconds between the person speaking and the STT - engine emitting the first partial. This is only calculated at the - start of an utterance. - """ - # Skip if metrics not available - if not self._metrics or processing_time == 0.0: - return - - # Calculate time as time.time() - ttfb (which is seconds) - start_time = time.time() - processing_time - - # Update internal metrics - self._metrics._start_ttfb_time = start_time - self._metrics._start_processing_time = start_time - - # Stop TTFB metrics - await self.stop_ttfb_metrics() - await self.stop_processing_metrics() - # ============================================================================ # HELPERS # ============================================================================ From 99242c0a937762fd605939d350b604a7eed23f40 Mon Sep 17 00:00:00 2001 From: Sam Sykes Date: Mon, 26 Jan 2026 23:14:40 +0000 Subject: [PATCH 0252/1060] linting updates --- src/pipecat/services/speechmatics/stt.py | 4 +++- 1 file changed, 3 insertions(+), 1 deletion(-) diff --git a/src/pipecat/services/speechmatics/stt.py b/src/pipecat/services/speechmatics/stt.py index d02b4360b..b194e1b5b 100644 --- a/src/pipecat/services/speechmatics/stt.py +++ b/src/pipecat/services/speechmatics/stt.py @@ -201,6 +201,7 @@ class SpeechmaticsSTTService(STTService): extra_params: Extra parameters to pass to the STT engine. This is a dictionary of additional parameters that can be used to configure the STT engine. Default to None. + """ # Service configuration @@ -346,7 +347,7 @@ class SpeechmaticsSTTService(STTService): params.speaker_passive_format or params.speaker_active_format ) - # Metrics + # Model + metrics self.set_model_name(self._config.operating_point.value) # Message queue @@ -693,6 +694,7 @@ class SpeechmaticsSTTService(STTService): ) elif not self._enable_vad and self._client is not None: self._client.finalize() + # self.confirm_finalize() async def _send_frames(self, segments: list[dict[str, Any]], finalized: bool = False) -> None: """Send frames to the pipeline. From 23d7608e5f5895625cb6238db444eb7e164e2b96 Mon Sep 17 00:00:00 2001 From: Sam Sykes Date: Mon, 26 Jan 2026 23:15:30 +0000 Subject: [PATCH 0253/1060] changelog update --- changelog/3562.changed.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/changelog/3562.changed.md b/changelog/3562.changed.md index 09090672b..533f37b2f 100644 --- a/changelog/3562.changed.md +++ b/changelog/3562.changed.md @@ -1,2 +1,2 @@ -- Added support for TTFS `finalize` attribute in `SpeechmaticsSTTServce` and set the default mode to `EXTERNAL` to support Pipecat-controlled VAD. +- Added support for TTFS in `SpeechmaticsSTTService` and set the default mode to `EXTERNAL` to support Pipecat-controlled VAD. - Changed dependency to `speechmatics-voice[smart]>=0.2.8` From 60168f7f69ea9388f3ea3917a11f67658570cb17 Mon Sep 17 00:00:00 2001 From: Sam Sykes Date: Mon, 26 Jan 2026 23:16:43 +0000 Subject: [PATCH 0254/1060] remove comment --- src/pipecat/services/speechmatics/stt.py | 1 - 1 file changed, 1 deletion(-) diff --git a/src/pipecat/services/speechmatics/stt.py b/src/pipecat/services/speechmatics/stt.py index b194e1b5b..1d25d6af6 100644 --- a/src/pipecat/services/speechmatics/stt.py +++ b/src/pipecat/services/speechmatics/stt.py @@ -694,7 +694,6 @@ class SpeechmaticsSTTService(STTService): ) elif not self._enable_vad and self._client is not None: self._client.finalize() - # self.confirm_finalize() async def _send_frames(self, segments: list[dict[str, Any]], finalized: bool = False) -> None: """Send frames to the pipeline. From 81a53c699c32a00700f63a4a92602c96c0777fee Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?G=C3=B6kmen=20G=C3=B6rgen?= Date: Tue, 27 Jan 2026 11:28:05 +0100 Subject: [PATCH 0255/1060] handle AIC processor init errors gracefully and ensure `_aic_ready` reflects readiness --- src/pipecat/audio/filters/aic_filter.py | 9 +++++++-- 1 file changed, 7 insertions(+), 2 deletions(-) diff --git a/src/pipecat/audio/filters/aic_filter.py b/src/pipecat/audio/filters/aic_filter.py index 8d198ca1c..7f0626776 100644 --- a/src/pipecat/audio/filters/aic_filter.py +++ b/src/pipecat/audio/filters/aic_filter.py @@ -189,10 +189,15 @@ class AICFilter(BaseAudioFilter): # Create async processor try: self._processor = ProcessorAsync(self._model, self._license_key, config) - self._aic_ready = True except Exception as e: # noqa: BLE001 - surfacing SDK initialization errors logger.error(f"AIC model initialization failed: {e}") - self._aic_ready = False + self._processor = None + + self._aic_ready = self._processor is not None + + if not self._aic_ready: + logger.debug(f"ai-coustics filter is not ready.") + return # Get contexts for parameter control and VAD self._processor_ctx = self._processor.get_processor_context() From 91346f5f37655d96e8886af8aa5ee546f49a3e79 Mon Sep 17 00:00:00 2001 From: Sam Sykes Date: Tue, 27 Jan 2026 10:44:35 +0000 Subject: [PATCH 0256/1060] Add support for `self.request_finalize()` for Pipecat-based VAD. --- src/pipecat/services/speechmatics/stt.py | 1 + 1 file changed, 1 insertion(+) diff --git a/src/pipecat/services/speechmatics/stt.py b/src/pipecat/services/speechmatics/stt.py index 1d25d6af6..752edd98b 100644 --- a/src/pipecat/services/speechmatics/stt.py +++ b/src/pipecat/services/speechmatics/stt.py @@ -693,6 +693,7 @@ class SpeechmaticsSTTService(STTService): f"{self} VADUserStoppedSpeakingFrame received but internal VAD is being used" ) elif not self._enable_vad and self._client is not None: + self.request_finalize() self._client.finalize() async def _send_frames(self, segments: list[dict[str, Any]], finalized: bool = False) -> None: From 45b7ec4e2c7ae9da457b275550398fffddff91e2 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?G=C3=B6kmen=20G=C3=B6rgen?= Date: Tue, 27 Jan 2026 16:18:56 +0100 Subject: [PATCH 0257/1060] re-enable `07zd-interruptible-aicoustics.py` in release evals. --- scripts/evals/run-release-evals.py | 3 +-- 1 file changed, 1 insertion(+), 2 deletions(-) diff --git a/scripts/evals/run-release-evals.py b/scripts/evals/run-release-evals.py index e544c732e..d4290be00 100644 --- a/scripts/evals/run-release-evals.py +++ b/scripts/evals/run-release-evals.py @@ -133,8 +133,7 @@ TESTS_07 = [ ("07zb-interruptible-inworld-http.py", EVAL_SIMPLE_MATH), ("07zc-interruptible-asyncai.py", EVAL_SIMPLE_MATH), ("07zc-interruptible-asyncai-http.py", EVAL_SIMPLE_MATH), - # Need license key to run - # ("07zd-interruptible-aicoustics.py", EVAL_SIMPLE_MATH), + ("07zd-interruptible-aicoustics.py", EVAL_SIMPLE_MATH), ("07ze-interruptible-hume.py", EVAL_SIMPLE_MATH), ("07zf-interruptible-gradium.py", EVAL_SIMPLE_MATH), ("07zg-interruptible-camb.py", EVAL_SIMPLE_MATH), From 6aa77ccc136b9fbc9402a1cac3d39edadcfc72bc Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?G=C3=B6kmen=20G=C3=B6rgen?= Date: Tue, 27 Jan 2026 16:22:54 +0100 Subject: [PATCH 0258/1060] group aic related changes in changelog. --- changelog/3408.added.md | 7 ++++--- 1 file changed, 4 insertions(+), 3 deletions(-) diff --git a/changelog/3408.added.md b/changelog/3408.added.md index fb528c7a7..04f1311cc 100644 --- a/changelog/3408.added.md +++ b/changelog/3408.added.md @@ -1,3 +1,4 @@ -- Added model downloading support to `AICFilter` with `model_id` and `model_download_dir` parameters. -- Added `model_path` parameter to `AICFilter` for loading local .aicmodel files. -- Added unit tests for `AICFilter` and `AICVADAnalyzer`. +- Additions for `AICFilter` and `AICVADAnalyzer`: + - Added model downloading support to `AICFilter` with `model_id` and `model_download_dir` parameters. + - Added `model_path` parameter to `AICFilter` for loading local `.aicmodel` files. + - Added unit tests for `AICFilter` and `AICVADAnalyzer`. From 52012b0fb2c24bb0388a345f8cd6dad312cfa476 Mon Sep 17 00:00:00 2001 From: Mark Backman Date: Tue, 27 Jan 2026 12:33:44 -0500 Subject: [PATCH 0259/1060] Fix WebsocketService infinite loop on graceful server disconnect --- changelog/3574.fixed.md | 1 + src/pipecat/services/websocket_service.py | 23 +++++++++--- uv.lock | 46 +++++++++++++++++++---- 3 files changed, 57 insertions(+), 13 deletions(-) create mode 100644 changelog/3574.fixed.md diff --git a/changelog/3574.fixed.md b/changelog/3574.fixed.md new file mode 100644 index 000000000..187f172b7 --- /dev/null +++ b/changelog/3574.fixed.md @@ -0,0 +1 @@ +- Fixed an infinite loop in `WebsocketService` that blocked the event loop when a remote server closed the connection gracefully. \ No newline at end of file diff --git a/src/pipecat/services/websocket_service.py b/src/pipecat/services/websocket_service.py index e86dee73f..85e5b2db7 100644 --- a/src/pipecat/services/websocket_service.py +++ b/src/pipecat/services/websocket_service.py @@ -123,26 +123,29 @@ class WebsocketService(ABC): async def _maybe_try_reconnect( self, - error: Exception, error_message: str, report_error: Callable[[ErrorFrame], Awaitable[None]], + error: Optional[Exception] = None, ) -> bool: """Check if reconnection should be attempted and try if appropriate. Args: - error: The exception that occurred. error_message: Human-readable error message for logging. report_error: Callback function to report connection errors. + error: The exception that occurred (optional, may be None for graceful closes). Returns: True if should continue the receive loop, False if should break. """ # Don't reconnect if we're intentionally disconnecting if self._disconnecting: - logger.warning(f"{self} error during disconnect: {error}") + if error: + logger.warning(f"{self} error during disconnect: {error}") + else: + logger.debug(f"{self} receive loop ended during disconnect") return False - # Log the error + # Log the message logger.warning(error_message) # Try to reconnect if enabled @@ -167,6 +170,14 @@ class WebsocketService(ABC): while True: try: await self._receive_messages() + # _receive_messages() returned normally. This happens when the websocket + # closes gracefully (server sent close frame). The async for loop over + # the websocket exits without raising an exception in this case. + # We must handle this to avoid an infinite loop. + message = f"{self} connection closed by server" + should_continue = await self._maybe_try_reconnect(message, report_error) + if not should_continue: + break except ConnectionClosedOK as e: # Normal closure, don't retry logger.debug(f"{self} connection closed normally: {e}") @@ -175,13 +186,13 @@ class WebsocketService(ABC): # Connection closed with error (e.g., no close frame received/sent) # This often indicates network issues, server problems, or abrupt disconnection message = f"{self} connection closed, but with an error: {e}" - should_continue = await self._maybe_try_reconnect(e, message, report_error) + should_continue = await self._maybe_try_reconnect(message, report_error, e) if not should_continue: break except Exception as e: # General error during message receiving message = f"{self} error receiving messages: {e}" - should_continue = 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src/pipecat/serializers/base_serializer.py | 3 ++- 2 files changed, 3 insertions(+), 1 deletion(-) create mode 100644 changelog/3560.changed.md diff --git a/changelog/3560.changed.md b/changelog/3560.changed.md new file mode 100644 index 000000000..b4ba6aa8b --- /dev/null +++ b/changelog/3560.changed.md @@ -0,0 +1 @@ +- `FrameSerializer` now subclasses from `BaseObject` to enable event support. diff --git a/src/pipecat/serializers/base_serializer.py b/src/pipecat/serializers/base_serializer.py index 490951a69..9cc38cdc6 100644 --- a/src/pipecat/serializers/base_serializer.py +++ b/src/pipecat/serializers/base_serializer.py @@ -9,9 +9,10 @@ from abc import ABC, abstractmethod from pipecat.frames.frames import Frame, StartFrame +from pipecat.utils.base_object import BaseObject -class FrameSerializer(ABC): +class FrameSerializer(BaseObject): """Abstract base class for frame serialization implementations. Defines the interface for converting frames to/from serialized formats From e80e0eab297eca30a56ae4b39b837904df670683 Mon Sep 17 00:00:00 2001 From: Mark Backman Date: Tue, 27 Jan 2026 12:59:20 -0500 Subject: [PATCH 0261/1060] Emit on_assistant_turn_stopped and on_user_turn_stopped from EndFrame or CancelFrame --- changelog/3575.fixed.md | 1 + .../aggregators/llm_response_universal.py | 38 ++++++++++--- tests/test_context_aggregators_universal.py | 54 +++++++++++++++++++ uv.lock | 46 +++++++++++++--- 4 files changed, 124 insertions(+), 15 deletions(-) create mode 100644 changelog/3575.fixed.md diff --git a/changelog/3575.fixed.md b/changelog/3575.fixed.md new file mode 100644 index 000000000..03c42b1ad --- /dev/null +++ b/changelog/3575.fixed.md @@ -0,0 +1 @@ +- Fixed `LLMUserAggregator` and `LLMAssistantAggregator` not emitting pending transcripts via `on_user_turn_stopped` and `on_assistant_turn_stopped` events when the conversation ends (`EndFrame`) or is cancelled (`CancelFrame`). diff --git a/src/pipecat/processors/aggregators/llm_response_universal.py b/src/pipecat/processors/aggregators/llm_response_universal.py index 6690a6e1e..3a8bbb542 100644 --- a/src/pipecat/processors/aggregators/llm_response_universal.py +++ b/src/pipecat/processors/aggregators/llm_response_universal.py @@ -464,9 +464,11 @@ class LLMUserAggregator(LLMContextAggregator): await s.setup(self.task_manager) async def _stop(self, frame: EndFrame): + await self._maybe_emit_user_turn_stopped(on_session_end=True) await self._cleanup() async def _cancel(self, frame: CancelFrame): + await self._maybe_emit_user_turn_stopped(on_session_end=True) await self._cleanup() async def _cleanup(self): @@ -602,14 +604,7 @@ class LLMUserAggregator(LLMContextAggregator): if params.enable_user_speaking_frames: await self.broadcast_frame(UserStoppedSpeakingFrame) - # Always push context frame. - aggregation = await self.push_aggregation() - - message = UserTurnStoppedMessage( - content=aggregation, timestamp=self._user_turn_start_timestamp - ) - await self._call_event_handler("on_user_turn_stopped", strategy, message) - self._user_turn_start_timestamp = "" + await self._maybe_emit_user_turn_stopped(strategy) async def _on_user_turn_stop_timeout(self, controller): await self._call_event_handler("on_user_turn_stop_timeout") @@ -617,6 +612,26 @@ class LLMUserAggregator(LLMContextAggregator): async def _on_user_turn_idle(self, controller): await self._call_event_handler("on_user_turn_idle") + async def _maybe_emit_user_turn_stopped( + self, + strategy: Optional[BaseUserTurnStopStrategy] = None, + on_session_end: bool = False, + ): + """Maybe emit user turn stopped event. + + Args: + strategy: The strategy that triggered the turn stop. + on_session_end: If True, only emit if there's unemitted content + (avoids duplicate events when session ends). + """ + aggregation = await self.push_aggregation() + if not on_session_end or aggregation: + message = UserTurnStoppedMessage( + content=aggregation, timestamp=self._user_turn_start_timestamp + ) + await self._call_event_handler("on_user_turn_stopped", strategy, message) + self._user_turn_start_timestamp = "" + class LLMAssistantAggregator(LLMContextAggregator): """Assistant LLM aggregator that processes bot responses and function calls. @@ -739,6 +754,9 @@ class LLMAssistantAggregator(LLMContextAggregator): if isinstance(frame, InterruptionFrame): await self._handle_interruptions(frame) await self.push_frame(frame, direction) + elif isinstance(frame, (EndFrame, CancelFrame)): + await self._handle_end_or_cancel(frame) + await self.push_frame(frame, direction) elif isinstance(frame, LLMFullResponseStartFrame): await self._handle_llm_start(frame) elif isinstance(frame, LLMFullResponseEndFrame): @@ -813,6 +831,10 @@ class LLMAssistantAggregator(LLMContextAggregator): self._started = 0 await self.reset() + async def _handle_end_or_cancel(self, frame: Frame): + await self._trigger_assistant_turn_stopped() + self._started = 0 + async def _handle_function_calls_started(self, frame: FunctionCallsStartedFrame): function_names = [f"{f.function_name}:{f.tool_call_id}" for f in frame.function_calls] logger.debug(f"{self} FunctionCallsStartedFrame: {function_names}") diff --git a/tests/test_context_aggregators_universal.py b/tests/test_context_aggregators_universal.py index 3cb1407f1..63f1fef9a 100644 --- a/tests/test_context_aggregators_universal.py +++ b/tests/test_context_aggregators_universal.py @@ -344,6 +344,35 @@ class TestLLMUserAggregator(unittest.IsolatedAsyncioTestCase): # The user mute strategies should have muted the user. self.assertFalse(user_turn) + async def test_pending_transcription_emitted_on_end_frame(self): + """Pending user transcription should be emitted when EndFrame arrives.""" + context = LLMContext() + + user_aggregator = LLMUserAggregator(context) + + stop_messages = [] + + @user_aggregator.event_handler("on_user_turn_stopped") + async def on_user_turn_stopped(aggregator, strategy, message): + stop_messages.append((strategy, message)) + + pipeline = Pipeline([user_aggregator]) + + # Start turn and send transcription, but don't trigger normal turn stop + frames_to_send = [ + VADUserStartedSpeakingFrame(), + TranscriptionFrame(text="Hello!", user_id="", timestamp="now"), + # No VADUserStoppedSpeakingFrame - turn doesn't stop normally + # EndFrame will be sent by run_test, triggering emission + ] + await run_test(pipeline, frames_to_send=frames_to_send) + + # The pending transcription should be emitted on EndFrame + self.assertEqual(len(stop_messages), 1) + strategy, message = stop_messages[0] + self.assertIsNone(strategy) # strategy is None for end/cancel + self.assertEqual(message.content, "Hello!") + class TestLLMAssistantAggregator(unittest.IsolatedAsyncioTestCase): async def test_empty(self): @@ -512,3 +541,28 @@ class TestLLMAssistantAggregator(unittest.IsolatedAsyncioTestCase): ] await run_test(aggregator, frames_to_send=frames_to_send) self.assertEqual(thought_message.content, "I'm thinking!") + + async def test_pending_text_emitted_on_end_frame(self): + """Pending assistant text should be emitted when EndFrame arrives.""" + context = LLMContext() + + aggregator = LLMAssistantAggregator(context) + + stop_messages = [] + + @aggregator.event_handler("on_assistant_turn_stopped") + async def on_assistant_turn_stopped(aggregator, message: AssistantTurnStoppedMessage): + stop_messages.append(message) + + # Start response and send text, but don't send LLMFullResponseEndFrame + frames_to_send = [ + LLMFullResponseStartFrame(), + LLMTextFrame("Hello from Pipecat!"), + # No LLMFullResponseEndFrame - response doesn't end normally + # EndFrame will be sent by run_test, triggering emission + ] + await run_test(aggregator, frames_to_send=frames_to_send) + + # The pending text should be emitted on EndFrame + self.assertEqual(len(stop_messages), 1) + self.assertEqual(stop_messages[0].content, "Hello 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src/pipecat/serializers/genesys.py | 245 +++++++++++++------ tests/test_genesys_serializer.py | 375 +++++++++++++++++++++++++++++ 2 files changed, 553 insertions(+), 67 deletions(-) create mode 100644 tests/test_genesys_serializer.py diff --git a/src/pipecat/serializers/genesys.py b/src/pipecat/serializers/genesys.py index 48637653b..678d0ef10 100644 --- a/src/pipecat/serializers/genesys.py +++ b/src/pipecat/serializers/genesys.py @@ -1,8 +1,15 @@ -""" -Use with Genesys Audio Connector to connect Genesys Cloud Contact Center with Pipecat pipelines. +"""Genesys AudioHook Serializer for Pipecat. -This connector implements the Genesys AudioHook protocol for bidirectional -audio streaming between Genesys Cloud contact center and Pipecat pipelines. +This module provides a serializer for integrating Pipecat pipelines with +Genesys Cloud Contact Center via the AudioHook protocol. + +Features: +- Bidirectional audio streaming (PCMU μ-law at 8kHz) +- Automatic protocol handshake handling (open/opened, close/closed, ping/pong) +- Input/output variables for Architect flow integration +- DTMF event support +- Barge-in (interruption) events +- Pause/resume support for hold scenarios Protocol Reference: - https://developer.genesys.cloud/devapps/audiohook @@ -10,7 +17,7 @@ Protocol Reference: Audio Format: - PCMU (μ-law) at 8kHz sample rate (preferred) - L16 (16-bit linear PCM) at 8kHz also supported -- Mono or Stereo (external on left, internal on right) +- Mono (external channel) or Stereo (external on left, internal on right) """ import json @@ -76,10 +83,11 @@ class GenesysAudioHookSerializer(FrameSerializer): AudioHook protocol messages. It supports: - Bidirectional audio streaming (PCMU at 8kHz) - - Session lifecycle management (open, close, pause) - - Probe mode for health checks - - Custom configuration passthrough - - Event messaging back to Genesys Cloud + - Automatic protocol handshake (open/opened, close/closed, ping/pong) + - Session lifecycle management with pause/resume support + - Custom input/output variables for Architect flow integration + - DTMF event handling + - Barge-in events for interruption support The AudioHook protocol uses: - Text WebSocket frames for JSON control messages @@ -88,17 +96,30 @@ class GenesysAudioHookSerializer(FrameSerializer): Example usage: ```python serializer = GenesysAudioHookSerializer( - session_id="abc-123", params=GenesysAudioHookSerializer.InputParams( - channel=AudioHookChannel.BOTH, + channel=AudioHookChannel.EXTERNAL, + supported_languages=["en-US", "es-ES"], + selected_language="en-US", ) ) - # Use with WebSocket transport - transport = WebsocketServerTransport( - serializer=serializer, - ... + # Use with FastAPI WebSocket transport + transport = FastAPIWebsocketTransport( + websocket=websocket, + params=FastAPIWebsocketParams( + audio_in_enabled=True, + audio_out_enabled=True, + serializer=serializer, + audio_out_fixed_packet_size=1600, # Important: prevents 429 rate limiting from Genesys + ), ) + + # Access call information after connection + participant = serializer.participant # ani, dnis, etc. + input_vars = serializer.input_variables # Custom vars from Architect + + # Set output variables to return to Architect + serializer.set_output_variables({"intent": "billing", "resolved": True}) ``` Attributes: @@ -110,13 +131,16 @@ class GenesysAudioHookSerializer(FrameSerializer): class InputParams(BaseModel): """Configuration parameters for GenesysAudioHookSerializer. - Parameters: - genesys_sample_rate: Sample rate used by Genesys (8000 Hz). + Attributes: + genesys_sample_rate: Sample rate used by Genesys (default: 8000 Hz). sample_rate: Optional override for pipeline input sample rate. channel: Which audio channels to process (external, internal, both). media_format: Audio format (PCMU or L16). process_external: Whether to process external (customer) audio. process_internal: Whether to process internal (agent) audio. + supported_languages: List of language codes the bot supports (e.g., ["en-US", "es-ES"]). + selected_language: Default language code to use. + start_paused: Whether to start the session in paused state. """ genesys_sample_rate: int = 8000 @@ -125,23 +149,24 @@ class GenesysAudioHookSerializer(FrameSerializer): media_format: AudioHookMediaFormat = AudioHookMediaFormat.PCMU process_external: bool = True process_internal: bool = False + supported_languages: Optional[List[str]] = None + selected_language: Optional[str] = None + start_paused: bool = False def __init__( self, - session_id: Optional[str] = None, params: Optional[InputParams] = None, ): """Initialize the GenesysAudioHookSerializer. Args: - session_id: The AudioHook session ID (received in open message). params: Configuration parameters. """ self._params = params or GenesysAudioHookSerializer.InputParams() - self._session_id = session_id or "" self._genesys_sample_rate = self._params.genesys_sample_rate self._sample_rate = 0 # Pipeline input rate, set in setup() + self._session_id = str(uuid.uuid4()) # Use Pipecat's official resampler if needed (SOXR) # Only used for TTS output (16kHz → 8kHz), input goes without resampling @@ -161,11 +186,12 @@ class GenesysAudioHookSerializer(FrameSerializer): self._custom_config: Optional[Dict[str, Any]] = None self._media_info: Optional[List[Dict[str, Any]]] = None self._input_variables: Optional[Dict[str, Any]] = None # Custom input from Genesys + self._output_variables: Optional[Dict[str, Any]] = None # Custom output to Genesys @property def session_id(self) -> str: - """Get the current session ID.""" + """Get the Genesys AudioHook session ID generated by the serializer.""" return self._session_id @property @@ -193,6 +219,34 @@ class GenesysAudioHookSerializer(FrameSerializer): """Get custom input variables from the open message.""" return self._input_variables + @property + def output_variables(self) -> Optional[Dict[str, Any]]: + """Get custom output variables to send back to Genesys.""" + return self._output_variables + + def set_output_variables(self, variables: Dict[str, Any]) -> None: + """Set custom output variables to send back to Genesys on close. + + These variables will be included in the 'closed' response when Genesys + closes the connection, making them available in the Architect flow. + + Args: + variables: Dictionary of custom variables to send to Genesys. + + Example: + ```python + # During the conversation, collect data and set it + serializer.set_output_variables({ + "intent": "billing_inquiry", + "customer_verified": True, + "summary": "Customer asked about their bill", + "transfer_to": "billing_queue" + }) + ``` + """ + self._output_variables = variables + logger.debug(f"Output variables set: {variables}") + async def setup(self, frame: StartFrame): """Sets up the serializer with pipeline configuration. @@ -279,7 +333,7 @@ class GenesysAudioHookSerializer(FrameSerializer): start_paused: bool = False, supported_languages: Optional[List[str]] = None, selected_language: Optional[str] = None, - ) -> str: + ) -> Dict[str, Any]: """Create an 'opened' response message for the client. This should be sent in response to an 'open' message from Genesys. @@ -290,10 +344,11 @@ class GenesysAudioHookSerializer(FrameSerializer): selected_language: The selected language code. Returns: - JSON string of the opened response message. + Dictionary of the opened response message. """ # Build channels list based on configuration channels: list[str] = [] + if self._params.channel == AudioHookChannel.EXTERNAL: channels = ["external"] elif self._params.channel == AudioHookChannel.INTERNAL: @@ -325,59 +380,88 @@ class GenesysAudioHookSerializer(FrameSerializer): ) self._is_open = True + logger.debug(f"AudioHook session opened: {self._session_id}") - return json.dumps(msg) + return msg - def create_closed_response(self) -> str: + def create_closed_response( + self, + output_variables: Optional[Dict[str, Any]] = None, + ) -> Dict[str, Any]: """Create a 'closed' response message. This should be sent in response to a 'close' message from Genesys. + Args: + output_variables: Optional custom variables to pass back to Genesys. + These will be available in the Architect flow after the AudioHook + action completes. + Returns: - JSON string of the closed response message. + Dictionary of the closed response message. + + Example: + ```python + # Pass custom data back to Genesys + serializer.create_closed_response( + output_variables={ + "intent": "billing_inquiry", + "customer_verified": True, + "summary": "Customer asked about their bill" + } + ) + ``` """ - msg = self._create_message(AudioHookMessageType.CLOSED) + parameters: Optional[Dict[str, Any]] = None + + if output_variables: + parameters = {"outputVariables": output_variables} + + msg = self._create_message( + AudioHookMessageType.CLOSED, + parameters=parameters, + ) self._is_open = False logger.debug(f"AudioHook session closed: {self._session_id}") - return json.dumps(msg) + return msg - def create_pong_response(self) -> str: + def create_pong_response(self) -> Dict[str, Any]: """Create a 'pong' response message. This should be sent in response to a 'ping' message from Genesys. Returns: - JSON string of the pong response message. + Dictionary of the pong response message. """ msg = self._create_message(AudioHookMessageType.PONG) - return json.dumps(msg) + return msg - def create_resumed_response(self) -> str: + def create_resumed_response(self) -> Dict[str, Any]: """Create a 'resumed' response message. This should be sent in response to a 'pause' message when ready to resume. Returns: - JSON string of the resumed response message. + Dictionary of the resumed response message. """ msg = self._create_message(AudioHookMessageType.RESUMED) self._is_paused = False logger.debug(f"AudioHook session resumed: {self._session_id}") - return json.dumps(msg) + return msg - def create_barge_in_event(self) -> str: + def create_barge_in_event(self) -> Dict[str, Any]: """Create a barge-in event message. This notifies Genesys Cloud that the user has interrupted the bot's audio output. Genesys will stop any queued audio playback. Returns: - JSON string of the barge-in event message. + Dictionary of the barge-in event message. """ msg = self._create_message( AudioHookMessageType.EVENT, @@ -390,7 +474,7 @@ class GenesysAudioHookSerializer(FrameSerializer): logger.debug("🔇 Barge-in event sent to Genesys") - return json.dumps(msg) + return msg def create_disconnect_message( self, @@ -398,7 +482,7 @@ class GenesysAudioHookSerializer(FrameSerializer): action: str = "transfer", output_variables: Optional[Dict[str, Any]] = None, info: Optional[str] = None, - ) -> str: + ) -> Dict[str, Any]: """Create a 'disconnect' message to initiate session termination. Args: @@ -408,7 +492,7 @@ class GenesysAudioHookSerializer(FrameSerializer): info: Optional additional information. Returns: - JSON string of the disconnect message. + Dictionary of the disconnect message. """ parameters: Dict[str, Any] = {"reason": reason} @@ -427,14 +511,14 @@ class GenesysAudioHookSerializer(FrameSerializer): ) logger.debug(f"AudioHook disconnect: reason={reason}, action={action}") - return json.dumps(msg) + return msg def create_error_message( self, code: int, message: str, retryable: bool = False, - ) -> str: + ) -> Dict[str, Any]: """Create an 'error' message. Args: @@ -443,7 +527,7 @@ class GenesysAudioHookSerializer(FrameSerializer): retryable: Whether the operation can be retried. Returns: - JSON string of the error message. + Dictionary of the error message. """ parameters = { "code": code, @@ -457,24 +541,26 @@ class GenesysAudioHookSerializer(FrameSerializer): ) logger.error(f"AudioHook error: {code} - {message}") - return json.dumps(msg) + return msg async def serialize(self, frame: Frame) -> str | bytes | None: """Serializes a Pipecat frame to Genesys AudioHook format. Handles conversion of various frame types to AudioHook messages: - - AudioRawFrame -> Binary audio data - - EndFrame/CancelFrame -> Disconnect message + - AudioRawFrame -> Binary PCMU audio data (resampled to 8kHz) + - EndFrame/CancelFrame -> Disconnect message (JSON) + - InterruptionFrame -> Barge-in event (JSON) - OutputTransportMessageFrame -> Pass-through JSON Args: frame: The Pipecat frame to serialize. Returns: - Serialized data as string (JSON) or bytes (audio), or None. + Serialized data as string (JSON) or bytes (audio), or None if + the frame type is not handled or session is not open. """ if isinstance(frame, (EndFrame, CancelFrame)): - return self.create_disconnect_message(reason="completed") + return json.dumps(self.create_disconnect_message(reason="completed")) elif isinstance(frame, AudioRawFrame): if not self._is_open or self._is_paused: @@ -501,7 +587,7 @@ class GenesysAudioHookSerializer(FrameSerializer): return bytes(serialized_data) elif isinstance(frame, InterruptionFrame): - return self.create_barge_in_event() + return json.dumps(self.create_barge_in_event()) elif isinstance(frame, (OutputTransportMessageFrame, OutputTransportMessageUrgentFrame)): # Pass through custom JSON messages @@ -514,18 +600,23 @@ class GenesysAudioHookSerializer(FrameSerializer): """Deserializes Genesys AudioHook data to Pipecat frames. Handles: - - Binary data -> InputAudioRawFrame - - JSON text -> Protocol messages (open, close, ping, pause, etc.) + - Binary data -> InputAudioRawFrame (converted from PCMU to PCM) + - JSON 'open' -> OutputTransportMessageUrgentFrame with 'opened' response + - JSON 'close' -> OutputTransportMessageUrgentFrame with 'closed' response + - JSON 'ping' -> OutputTransportMessageUrgentFrame with 'pong' response + - JSON 'pause' -> Sets is_paused=True, returns None + - JSON 'dtmf' -> InputDTMFFrame + - JSON 'update' -> Updates participant info, returns None + - JSON 'error' -> Logs error, returns None - For control messages (open, close, ping, pause), this method handles - the protocol response internally and logs the events. The application - should monitor session state via the is_open and is_paused properties. + Protocol responses (opened, closed, pong) are returned as urgent frames + to be sent immediately through the transport. Args: - data: The raw WebSocket data from Genesys. + data: The raw WebSocket data from Genesys (binary audio or JSON text). Returns: - A Pipecat frame corresponding to the data, or None if handled internally. + A Pipecat frame to process, or None if handled internally. """ # Binary data = audio if isinstance(data, bytes): @@ -643,13 +734,22 @@ class GenesysAudioHookSerializer(FrameSerializer): async def _handle_open(self, message: Dict[str, Any]) -> Frame | None: """Handle an 'open' message from Genesys. - This initializes the session with metadata from Genesys Cloud. + This initializes the session with metadata from Genesys Cloud and + automatically responds with an 'opened' message using the configured + InputParams (supported_languages, selected_language, start_paused). + + Extracts and stores: + - session_id: The AudioHook session identifier + - conversation_id: The Genesys conversation ID + - participant: Caller info (ani, dnis, etc.) + - input_variables: Custom variables from Architect flow + - media_info: Audio configuration from Genesys Args: - message: The open message. + message: The open message from Genesys. Returns: - None (response should be sent via create_opened_response()). + OutputTransportMessageUrgentFrame with the 'opened' response. """ self._session_id = message.get("id", str(uuid.uuid4())) @@ -686,18 +786,25 @@ class GenesysAudioHookSerializer(FrameSerializer): f"conversation={self._conversation_id}, ani={ani}" ) - # Note: Application should call create_opened_response() to respond - return None + return OutputTransportMessageUrgentFrame(message=self.create_opened_response( + start_paused=self._params.start_paused, + supported_languages=self._params.supported_languages, + selected_language=self._params.selected_language + )) async def _handle_close(self, message: Dict[str, Any]) -> Frame | None: """Handle a 'close' message from Genesys. + Automatically responds with a 'closed' message. If output_variables + were set via set_output_variables(), they will be included in the + response and made available in the Architect flow. + Args: - message: The close message. + message: The close message from Genesys. Returns: - OutputTransportMessageUrgentFrame with the closed response, - or None if no response should be sent. + OutputTransportMessageUrgentFrame with the closed response + (includes outputVariables if set). """ params = message.get("parameters", {}) reason = params.get("reason", "unknown") @@ -709,22 +816,26 @@ class GenesysAudioHookSerializer(FrameSerializer): logger.info(f"Sending closed response to Genesys...") # Return as urgent frame to be sent through pipeline immediately - return OutputTransportMessageUrgentFrame(message=json.loads(self.create_closed_response())) + # Include any output variables that were set during the session + return OutputTransportMessageUrgentFrame( + message=self.create_closed_response(output_variables=self._output_variables) + ) async def _handle_ping(self, message: Dict[str, Any]) -> Frame | None: """Handle a 'ping' message from Genesys. + Automatically responds with a 'pong' message to maintain the connection. + Args: - message: The ping message. + message: The ping message from Genesys. Returns: - None if pong was sent directly via callback, otherwise OutputTransportMessageUrgentFrame with pong response. """ logger.info(f"Sending pong response to Genesys...") # Return as urgent frame to be sent through pipeline immediately - return OutputTransportMessageUrgentFrame(message=json.loads(self.create_pong_response())) + return OutputTransportMessageUrgentFrame(message=self.create_pong_response()) async def _handle_pause(self, message: Dict[str, Any]) -> Frame | None: """Handle a 'pause' message from Genesys. diff --git a/tests/test_genesys_serializer.py b/tests/test_genesys_serializer.py new file mode 100644 index 000000000..65f624c9a --- /dev/null +++ b/tests/test_genesys_serializer.py @@ -0,0 +1,375 @@ +"""Tests for the Genesys AudioHook serializer.""" + +import json +import pytest + +from pipecat.frames.frames import InputDTMFFrame, OutputTransportMessageUrgentFrame + +from pipecat.serializers.genesys import ( + GenesysAudioHookSerializer, + AudioHookChannel +) + + +class TestGenesysAudioHookSerializer: + """Tests for GenesysAudioHookSerializer.""" + + # ==================== Initialization Tests ==================== + + def test_create_serializer_default_params(self): + """Test creating serializer with default parameters.""" + serializer = GenesysAudioHookSerializer() + + # session_id is auto-generated as UUID + assert serializer.session_id != "" + assert len(serializer.session_id) == 36 # UUID format + assert serializer.is_open is False + assert serializer.is_paused is False + + def test_create_serializer_with_custom_params(self): + """Test creating serializer with custom parameters.""" + params = GenesysAudioHookSerializer.InputParams( + channel=AudioHookChannel.BOTH, + sample_rate=16000, + supported_languages=["es-ES", "en-US"], + selected_language="es-ES", + start_paused=True, + ) + serializer = GenesysAudioHookSerializer(params=params) + + assert serializer.session_id != "" + + # ==================== Response Creation Tests ==================== + + def test_create_opened_response(self): + """Test creating an opened response message.""" + serializer = GenesysAudioHookSerializer() + + msg = serializer.create_opened_response() + + assert msg["type"] == "opened" + assert msg["version"] == "2" + assert msg["id"] == serializer.session_id + assert "parameters" in msg + assert serializer.is_open is True + + def test_create_opened_response_with_languages(self): + """Test creating an opened response with language options.""" + serializer = GenesysAudioHookSerializer() + + msg = serializer.create_opened_response( + supported_languages=["es", "en", "fr"], + selected_language="es", + ) + + assert msg["parameters"]["supportedLanguages"] == ["es", "en", "fr"] + assert msg["parameters"]["selectedLanguage"] == "es" + + def test_create_pong_response(self): + """Test creating a pong response message.""" + serializer = GenesysAudioHookSerializer() + + msg = serializer.create_pong_response() + + assert msg["type"] == "pong" + assert msg["id"] == serializer.session_id + + def test_create_closed_response(self): + """Test creating a closed response message.""" + serializer = GenesysAudioHookSerializer() + serializer._is_open = True + + msg = serializer.create_closed_response() + + assert msg["type"] == "closed" + assert serializer.is_open is False + assert "parameters" not in msg # No parameters when no output_variables + + def test_create_closed_response_with_output_variables(self): + """Test creating a closed response with custom output variables.""" + serializer = GenesysAudioHookSerializer() + serializer._is_open = True + + msg = serializer.create_closed_response( + output_variables={ + "intent": "billing_inquiry", + "customer_verified": True, + "summary": "Customer asked about their bill" + } + ) + + assert msg["type"] == "closed" + assert msg["parameters"]["outputVariables"]["intent"] == "billing_inquiry" + assert msg["parameters"]["outputVariables"]["customer_verified"] is True + assert msg["parameters"]["outputVariables"]["summary"] == "Customer asked about their bill" + + def test_create_resumed_response(self): + """Test creating a resumed response message.""" + serializer = GenesysAudioHookSerializer() + serializer._is_paused = True + + msg = serializer.create_resumed_response() + + assert msg["type"] == "resumed" + assert serializer.is_paused is False + + def test_create_disconnect_message(self): + """Test creating a disconnect message.""" + serializer = GenesysAudioHookSerializer() + + msg = serializer.create_disconnect_message( + reason="completed", + action="transfer", + ) + + assert msg["type"] == "disconnect" + assert msg["parameters"]["reason"] == "completed" + assert msg["parameters"]["outputVariables"]["action"] == "transfer" + + def test_create_disconnect_message_with_output_variables(self): + """Test creating a disconnect message with custom output variables.""" + serializer = GenesysAudioHookSerializer() + + msg = serializer.create_disconnect_message( + reason="completed", + action="finished", + output_variables={"result": "success", "code": "123"}, + ) + + assert msg["parameters"]["outputVariables"]["result"] == "success" + assert msg["parameters"]["outputVariables"]["code"] == "123" + + def test_create_error_message(self): + """Test creating an error message.""" + serializer = GenesysAudioHookSerializer() + + msg = serializer.create_error_message( + code=500, + message="Internal error", + retryable=True, + ) + + assert msg["type"] == "error" + assert msg["parameters"]["code"] == 500 + assert msg["parameters"]["message"] == "Internal error" + assert msg["parameters"]["retryable"] is True + + # ==================== Message Handling Tests ==================== + + @pytest.mark.asyncio + async def test_handle_open_message(self, sample_open_message): + """Test handling an open message returns opened frame.""" + serializer = GenesysAudioHookSerializer() + + result = await serializer.deserialize(json.dumps(sample_open_message)) + + # Now returns OutputTransportMessageUrgentFrame with opened response + assert isinstance(result, OutputTransportMessageUrgentFrame) + assert result.message["type"] == "opened" + assert serializer.session_id == "test-session-123" + assert serializer.conversation_id == "conv-456" + + @pytest.mark.asyncio + async def test_handle_open_message_extracts_participant(self, sample_open_message): + """Test that open message extracts participant info.""" + serializer = GenesysAudioHookSerializer() + + await serializer.deserialize(json.dumps(sample_open_message)) + + assert serializer.participant is not None + assert serializer.participant["ani"] == "+1234567890" + assert serializer.participant["dnis"] == "+0987654321" + + @pytest.mark.asyncio + async def test_handle_open_message_uses_params(self, sample_open_message): + """Test that open message uses InputParams for response.""" + params = GenesysAudioHookSerializer.InputParams( + supported_languages=["es-ES", "en-US"], + selected_language="es-ES", + start_paused=True, + ) + serializer = GenesysAudioHookSerializer(params=params) + + result = await serializer.deserialize(json.dumps(sample_open_message)) + + assert isinstance(result, OutputTransportMessageUrgentFrame) + assert result.message["parameters"]["supportedLanguages"] == ["es-ES", "en-US"] + assert result.message["parameters"]["selectedLanguage"] == "es-ES" + assert result.message["parameters"]["startPaused"] is True + + @pytest.mark.asyncio + async def test_handle_open_message_extracts_input_variables(self, sample_open_message_with_input_variables): + """Test that open message extracts inputVariables from Genesys.""" + serializer = GenesysAudioHookSerializer() + + await serializer.deserialize(json.dumps(sample_open_message_with_input_variables)) + + assert serializer.input_variables is not None + assert serializer.input_variables["customer_id"] == "cust-789" + assert serializer.input_variables["queue_name"] == "billing" + assert serializer.input_variables["priority"] == "high" + assert serializer.input_variables["language"] == "es-ES" + + @pytest.mark.asyncio + async def test_handle_ping_message(self, sample_ping_message): + """Test handling a ping message returns pong frame.""" + serializer = GenesysAudioHookSerializer() + + result = await serializer.deserialize(json.dumps(sample_ping_message)) + + assert isinstance(result, OutputTransportMessageUrgentFrame) + assert result.message["type"] == "pong" + + @pytest.mark.asyncio + async def test_handle_close_message(self, sample_close_message): + """Test handling a close message returns closed frame.""" + serializer = GenesysAudioHookSerializer() + serializer._is_open = True + + result = await serializer.deserialize(json.dumps(sample_close_message)) + + assert isinstance(result, OutputTransportMessageUrgentFrame) + assert result.message["type"] == "closed" + assert serializer.is_open is False + + @pytest.mark.asyncio + async def test_handle_close_message_includes_output_variables(self, sample_close_message): + """Test that close response includes output variables when set.""" + serializer = GenesysAudioHookSerializer() + serializer._is_open = True + + # Set output variables before close + serializer.set_output_variables({ + "intent": "support", + "resolved": True, + "transfer_to": "agent_queue" + }) + + result = await serializer.deserialize(json.dumps(sample_close_message)) + + assert isinstance(result, OutputTransportMessageUrgentFrame) + assert result.message["type"] == "closed" + assert result.message["parameters"]["outputVariables"]["intent"] == "support" + assert result.message["parameters"]["outputVariables"]["resolved"] is True + assert result.message["parameters"]["outputVariables"]["transfer_to"] == "agent_queue" + + # ==================== Output Variables Tests ==================== + + def test_set_output_variables(self): + """Test setting output variables.""" + serializer = GenesysAudioHookSerializer() + + assert serializer.output_variables is None + + serializer.set_output_variables({ + "intent": "billing", + "score": 0.95 + }) + + assert serializer.output_variables is not None + assert serializer.output_variables["intent"] == "billing" + assert serializer.output_variables["score"] == 0.95 + + def test_set_output_variables_overwrites(self): + """Test that setting output variables overwrites previous values.""" + serializer = GenesysAudioHookSerializer() + + serializer.set_output_variables({"first": "value"}) + serializer.set_output_variables({"second": "value"}) + + assert "first" not in serializer.output_variables + assert serializer.output_variables["second"] == "value" + + @pytest.mark.asyncio + async def test_handle_pause_message(self, sample_pause_message): + """Test handling a pause message.""" + serializer = GenesysAudioHookSerializer() + serializer._is_open = True + + result = await serializer.deserialize(json.dumps(sample_pause_message)) + + assert result is None # Pause is handled internally + assert serializer.is_paused is True + + @pytest.mark.asyncio + async def test_handle_update_message(self, sample_update_message): + """Test handling an update message.""" + serializer = GenesysAudioHookSerializer() + + result = await serializer.deserialize(json.dumps(sample_update_message)) + + assert result is None # Update is handled internally + assert serializer.participant is not None + assert serializer.participant["name"] == "John Doe" + + @pytest.mark.asyncio + async def test_handle_error_message(self, sample_error_message): + """Test handling an error message.""" + serializer = GenesysAudioHookSerializer() + + result = await serializer.deserialize(json.dumps(sample_error_message)) + + assert result is None # Error is logged but returns None + + # ==================== DTMF Tests ==================== + + @pytest.mark.asyncio + async def test_handle_dtmf_digit(self, sample_dtmf_message): + """Test handling a DTMF digit message.""" + serializer = GenesysAudioHookSerializer() + + result = await serializer.deserialize(json.dumps(sample_dtmf_message)) + + assert isinstance(result, InputDTMFFrame) + assert result.button.value == "5" + + @pytest.mark.asyncio + async def test_handle_dtmf_star(self, sample_dtmf_star_message): + """Test handling a DTMF star (*) message.""" + serializer = GenesysAudioHookSerializer() + + result = await serializer.deserialize(json.dumps(sample_dtmf_star_message)) + + assert isinstance(result, InputDTMFFrame) + assert result.button.value == "*" + + @pytest.mark.asyncio + async def test_handle_dtmf_hash(self, sample_dtmf_hash_message): + """Test handling a DTMF hash (#) message.""" + serializer = GenesysAudioHookSerializer() + + result = await serializer.deserialize(json.dumps(sample_dtmf_hash_message)) + + assert isinstance(result, InputDTMFFrame) + assert result.button.value == "#" + + @pytest.mark.asyncio + async def test_handle_dtmf_empty_digit(self): + """Test handling a DTMF message without digit.""" + serializer = GenesysAudioHookSerializer() + + dtmf_msg = { + "version": "2", + "type": "dtmf", + "seq": 6, + "id": "test-session-123", + "parameters": {}, + } + + result = await serializer.deserialize(json.dumps(dtmf_msg)) + + assert result is None # No digit provided + + # ==================== Sequence Number Tests ==================== + + def test_sequence_numbers_increment(self): + """Test that sequence numbers increment correctly.""" + serializer = GenesysAudioHookSerializer() + + response1 = serializer.create_pong_response() + response2 = serializer.create_pong_response() + response3 = serializer.create_pong_response() + + assert response1["seq"] == 1 + assert response2["seq"] == 2 + assert response3["seq"] == 3 From 9102e81cb84bf23f94814e287919343b35ed49ae Mon Sep 17 00:00:00 2001 From: ssillerom Date: Tue, 27 Jan 2026 23:39:43 +0100 Subject: [PATCH 0263/1060] added tests to the PR --- tests/genesys/__init__.py | 6 + tests/genesys/conftest.py | 186 ++++++++++++++++++ .../{ => genesys}/test_genesys_serializer.py | 0 3 files changed, 192 insertions(+) create mode 100644 tests/genesys/__init__.py create mode 100644 tests/genesys/conftest.py rename tests/{ => genesys}/test_genesys_serializer.py (100%) diff --git a/tests/genesys/__init__.py b/tests/genesys/__init__.py new file mode 100644 index 000000000..05982ea05 --- /dev/null +++ b/tests/genesys/__init__.py @@ -0,0 +1,6 @@ +# Copyright (c) 2026, Daily +# +# SPDX-License-Identifier: BSD 2-Clause License +# + +"""Tests for Genesys AudioHook serializer.""" diff --git a/tests/genesys/conftest.py b/tests/genesys/conftest.py new file mode 100644 index 000000000..656e815a5 --- /dev/null +++ b/tests/genesys/conftest.py @@ -0,0 +1,186 @@ +"""Pytest fixtures for Genesys AudioHook serializer tests. + +These fixtures provide sample AudioHook protocol messages for testing +the GenesysAudioHookSerializer. They are scoped to this directory only. +""" + +import pytest + + +@pytest.fixture +def sample_open_message(): + """Sample AudioHook open message from Genesys.""" + return { + "version": "2", + "type": "open", + "seq": 1, + "id": "test-session-123", + "parameters": { + "conversationId": "conv-456", + "participant": { + "ani": "+1234567890", + "dnis": "+0987654321", + }, + "media": [ + { + "type": "audio", + "format": "PCMU", + "channels": ["external"], + "rate": 8000, + } + ], + }, + } + + +@pytest.fixture +def sample_open_message_with_input_variables(): + """Sample AudioHook open message with custom inputVariables from Genesys.""" + return { + "version": "2", + "type": "open", + "seq": 1, + "id": "test-session-123", + "parameters": { + "conversationId": "conv-456", + "participant": { + "ani": "+1234567890", + "dnis": "+0987654321", + }, + "media": [ + { + "type": "audio", + "format": "PCMU", + "channels": ["external"], + "rate": 8000, + } + ], + "inputVariables": { + "customer_id": "cust-789", + "queue_name": "billing", + "priority": "high", + "language": "es-ES", + }, + }, + } + + +@pytest.fixture +def sample_ping_message(): + """Sample AudioHook ping message.""" + return { + "version": "2", + "type": "ping", + "seq": 5, + "id": "test-session-123", + "position": "PT10.5S", + } + + +@pytest.fixture +def sample_close_message(): + """Sample AudioHook close message from Genesys.""" + return { + "version": "2", + "type": "close", + "seq": 10, + "id": "test-session-123", + "position": "PT30.0S", + "parameters": { + "reason": "disconnect", + }, + } + + +@pytest.fixture +def sample_pause_message(): + """Sample AudioHook pause message.""" + return { + "version": "2", + "type": "pause", + "seq": 7, + "id": "test-session-123", + "position": "PT15.0S", + "parameters": { + "reason": "hold", + }, + } + + +@pytest.fixture +def sample_update_message(): + """Sample AudioHook update message.""" + return { + "version": "2", + "type": "update", + "seq": 8, + "id": "test-session-123", + "position": "PT20.0S", + "parameters": { + "participant": { + "ani": "+1234567890", + "dnis": "+0987654321", + "name": "John Doe", + }, + }, + } + + +@pytest.fixture +def sample_error_message(): + """Sample AudioHook error message.""" + return { + "version": "2", + "type": "error", + "seq": 9, + "id": "test-session-123", + "parameters": { + "code": 500, + "message": "Internal server error", + }, + } + + +@pytest.fixture +def sample_dtmf_message(): + """Sample AudioHook DTMF message.""" + return { + "version": "2", + "type": "dtmf", + "seq": 6, + "id": "test-session-123", + "position": "PT12.0S", + "parameters": { + "digit": "5", + }, + } + + +@pytest.fixture +def sample_dtmf_star_message(): + """Sample AudioHook DTMF message with star key.""" + return { + "version": "2", + "type": "dtmf", + "seq": 6, + "id": "test-session-123", + "position": "PT12.0S", + "parameters": { + "digit": "*", + }, + } + + +@pytest.fixture +def sample_dtmf_hash_message(): + """Sample AudioHook DTMF message with hash key.""" + return { + "version": "2", + "type": "dtmf", + "seq": 6, + "id": "test-session-123", + "position": "PT12.0S", + "parameters": { + "digit": "#", + }, + } diff --git a/tests/test_genesys_serializer.py b/tests/genesys/test_genesys_serializer.py similarity index 100% rename from tests/test_genesys_serializer.py rename to tests/genesys/test_genesys_serializer.py From 55e0d4ecc45cb2e3df2b9475cf0ce51011728ac2 Mon Sep 17 00:00:00 2001 From: ssillerom Date: Wed, 28 Jan 2026 08:59:28 +0100 Subject: [PATCH 0264/1060] ruff fixes done --- src/pipecat/serializers/genesys.py | 7 +++---- tests/genesys/test_genesys_serializer.py | 7 ++----- 2 files changed, 5 insertions(+), 9 deletions(-) diff --git a/src/pipecat/serializers/genesys.py b/src/pipecat/serializers/genesys.py index 678d0ef10..8b315dcdf 100644 --- a/src/pipecat/serializers/genesys.py +++ b/src/pipecat/serializers/genesys.py @@ -30,6 +30,8 @@ from loguru import logger from pydantic import BaseModel from pipecat.audio.dtmf.types import KeypadEntry +from pipecat.audio.resamplers.soxr_stream_resampler import SOXRStreamAudioResampler +from pipecat.audio.utils import pcm_to_ulaw, ulaw_to_pcm from pipecat.frames.frames import ( AudioRawFrame, CancelFrame, @@ -37,14 +39,12 @@ from pipecat.frames.frames import ( Frame, InputAudioRawFrame, InputDTMFFrame, + InterruptionFrame, OutputTransportMessageFrame, OutputTransportMessageUrgentFrame, StartFrame, - InterruptionFrame ) from pipecat.serializers.base_serializer import FrameSerializer -from pipecat.audio.resamplers.soxr_stream_resampler import SOXRStreamAudioResampler -from pipecat.audio.utils import ulaw_to_pcm, pcm_to_ulaw class AudioHookMessageType(str, Enum): @@ -832,7 +832,6 @@ class GenesysAudioHookSerializer(FrameSerializer): Returns: OutputTransportMessageUrgentFrame with pong response. """ - logger.info(f"Sending pong response to Genesys...") # Return as urgent frame to be sent through pipeline immediately return OutputTransportMessageUrgentFrame(message=self.create_pong_response()) diff --git a/tests/genesys/test_genesys_serializer.py b/tests/genesys/test_genesys_serializer.py index 65f624c9a..00942ab3c 100644 --- a/tests/genesys/test_genesys_serializer.py +++ b/tests/genesys/test_genesys_serializer.py @@ -1,14 +1,11 @@ """Tests for the Genesys AudioHook serializer.""" import json + import pytest from pipecat.frames.frames import InputDTMFFrame, OutputTransportMessageUrgentFrame - -from pipecat.serializers.genesys import ( - GenesysAudioHookSerializer, - AudioHookChannel -) +from pipecat.serializers.genesys import AudioHookChannel, GenesysAudioHookSerializer class TestGenesysAudioHookSerializer: From a4acafd3be7ab1dbda015ba103a945674ae4d62c Mon Sep 17 00:00:00 2001 From: ssillerom Date: Wed, 28 Jan 2026 10:54:26 +0100 Subject: [PATCH 0265/1060] feature: added event handlers in constructor and call func in each _handle_* func --- src/pipecat/serializers/genesys.py | 26 +++++++++++++++++++++++++- 1 file changed, 25 insertions(+), 1 deletion(-) diff --git a/src/pipecat/serializers/genesys.py b/src/pipecat/serializers/genesys.py index 8b315dcdf..1914eacea 100644 --- a/src/pipecat/serializers/genesys.py +++ b/src/pipecat/serializers/genesys.py @@ -187,7 +187,16 @@ class GenesysAudioHookSerializer(FrameSerializer): self._media_info: Optional[List[Dict[str, Any]]] = None self._input_variables: Optional[Dict[str, Any]] = None # Custom input from Genesys self._output_variables: Optional[Dict[str, Any]] = None # Custom output to Genesys - + + # Event handlers + self._register_event_handler("on_open") + self._register_event_handler("on_close") + self._register_event_handler("on_ping") + self._register_event_handler("on_pause") + self._register_event_handler("on_update") + self._register_event_handler("on_error") + self._register_event_handler("on_dtmf") + @property def session_id(self) -> str: @@ -786,6 +795,8 @@ class GenesysAudioHookSerializer(FrameSerializer): f"conversation={self._conversation_id}, ani={ani}" ) + await self._call_event_handler("on_open", message) + return OutputTransportMessageUrgentFrame(message=self.create_opened_response( start_paused=self._params.start_paused, supported_languages=self._params.supported_languages, @@ -814,6 +825,8 @@ class GenesysAudioHookSerializer(FrameSerializer): self._is_open = False logger.info(f"Sending closed response to Genesys...") + + await self._call_event_handler("on_close", message) # Return as urgent frame to be sent through pipeline immediately # Include any output variables that were set during the session @@ -833,6 +846,9 @@ class GenesysAudioHookSerializer(FrameSerializer): OutputTransportMessageUrgentFrame with pong response. """ logger.info(f"Sending pong response to Genesys...") + + await self._call_event_handler("on_ping", message) + # Return as urgent frame to be sent through pipeline immediately return OutputTransportMessageUrgentFrame(message=self.create_pong_response()) @@ -854,6 +870,8 @@ class GenesysAudioHookSerializer(FrameSerializer): logger.info(f"AudioHook pause request: reason={reason}") self._is_paused = True + + await self._call_event_handler("on_pause", message) # Note: Application should call create_resumed_response() when ready return None @@ -875,6 +893,8 @@ class GenesysAudioHookSerializer(FrameSerializer): self._participant = params["participant"] logger.debug(f"AudioHook update received: {params}") + + await self._call_event_handler("on_update", message) return None @@ -892,6 +912,8 @@ class GenesysAudioHookSerializer(FrameSerializer): error_msg = params.get("message", "Unknown error") logger.error(f"AudioHook error from Genesys: {code} - {error_msg}") + + await self._call_event_handler("on_error", message) return None @@ -915,6 +937,8 @@ class GenesysAudioHookSerializer(FrameSerializer): return None logger.info(f"DTMF received: {digit}") + + await self._call_event_handler("on_dtmf", message) try: return InputDTMFFrame(KeypadEntry(digit)) From 468e159f9b4475d6c870f914f13389102fca3ad6 Mon Sep 17 00:00:00 2001 From: filipi87 Date: Wed, 28 Jan 2026 08:36:31 -0300 Subject: [PATCH 0266/1060] Fixed race condition in OpenAIRealtimeLLMService that could cause an error when truncating the conversation. --- src/pipecat/services/openai/realtime/llm.py | 8 ++++++++ 1 file changed, 8 insertions(+) diff --git a/src/pipecat/services/openai/realtime/llm.py b/src/pipecat/services/openai/realtime/llm.py index 11a83741e..cf249408c 100644 --- a/src/pipecat/services/openai/realtime/llm.py +++ b/src/pipecat/services/openai/realtime/llm.py @@ -599,6 +599,14 @@ class OpenAIRealtimeLLMService(LLMService): # note: ttfb is faster by 1/2 RTT than ttfb as measured for other services, since we're getting # this event from the server await self.stop_ttfb_metrics() + + if self._current_audio_response and self._current_audio_response.item_id != evt.item_id: + logger.warning( + f"Received a new audio delta for an already completed audio response before receiving the BotStoppedSpeakingFrame." + ) + logger.debug("Forcing previous audio response to None") + self._current_audio_response = None + if not self._current_audio_response: self._current_audio_response = CurrentAudioResponse( item_id=evt.item_id, From bdae1771256cd83a0993564f22a19d374116d263 Mon Sep 17 00:00:00 2001 From: filipi87 Date: Wed, 28 Jan 2026 08:39:11 -0300 Subject: [PATCH 0267/1060] Adding changelog entry for the OpenAiRealtimeLLMService fix. --- changelog/3581.fixed.md | 1 + 1 file changed, 1 insertion(+) create mode 100644 changelog/3581.fixed.md diff --git a/changelog/3581.fixed.md b/changelog/3581.fixed.md new file mode 100644 index 000000000..688bbcfbe --- /dev/null +++ b/changelog/3581.fixed.md @@ -0,0 +1 @@ +- Fixed race condition in `OpenAIRealtimeLLMService` that could cause an error when truncating the conversation. \ No newline at end of file From ef6bbace98ec55e177642aa582e3bb02e7b82684 Mon Sep 17 00:00:00 2001 From: ssillerom Date: Wed, 28 Jan 2026 15:40:24 +0100 Subject: [PATCH 0268/1060] fixes: super init inhereted class to set event hanlders in the construct --- src/pipecat/serializers/genesys.py | 12 ++++++++++-- 1 file changed, 10 insertions(+), 2 deletions(-) diff --git a/src/pipecat/serializers/genesys.py b/src/pipecat/serializers/genesys.py index 1914eacea..cced94997 100644 --- a/src/pipecat/serializers/genesys.py +++ b/src/pipecat/serializers/genesys.py @@ -156,12 +156,15 @@ class GenesysAudioHookSerializer(FrameSerializer): def __init__( self, params: Optional[InputParams] = None, + **kwargs, ): """Initialize the GenesysAudioHookSerializer. Args: params: Configuration parameters. + **kwargs: Additional arguments passed to BaseObject (e.g., name). """ + super().__init__(**kwargs) self._params = params or GenesysAudioHookSerializer.InputParams() self._genesys_sample_rate = self._params.genesys_sample_rate @@ -599,8 +602,13 @@ class GenesysAudioHookSerializer(FrameSerializer): return json.dumps(self.create_barge_in_event()) elif isinstance(frame, (OutputTransportMessageFrame, OutputTransportMessageUrgentFrame)): - # Pass through custom JSON messages - return json.dumps(frame.message) + # Only pass through AudioHook protocol messages (those with "version" field) + # Filter out RTVI and other non-AudioHook messages + if isinstance(frame.message, dict) and "version" in frame.message: + return json.dumps(frame.message) + else: + # Not an AudioHook message, ignore + return None # Ignore other frames - we don't need to process them here return None From ff0eb6d28612c665888565bd153bc957ce292e8a Mon Sep 17 00:00:00 2001 From: Luke Payyapilli Date: Wed, 28 Jan 2026 09:42:22 -0500 Subject: [PATCH 0269/1060] fix: emit ErrorFrame on LLM completion timeout --- changelog/3529.fixed.md | 1 + src/pipecat/services/openai/base_llm.py | 3 +- tests/test_openai_llm_timeout.py | 127 ++++++++++++++++++++++++ 3 files changed, 130 insertions(+), 1 deletion(-) create mode 100644 changelog/3529.fixed.md create mode 100644 tests/test_openai_llm_timeout.py diff --git a/changelog/3529.fixed.md b/changelog/3529.fixed.md new file mode 100644 index 000000000..91c9eeda0 --- /dev/null +++ b/changelog/3529.fixed.md @@ -0,0 +1 @@ +- Fixed OpenAI LLM services to emit `ErrorFrame` on completion timeout, enabling proper error handling and LLMSwitcher failover. diff --git a/src/pipecat/services/openai/base_llm.py b/src/pipecat/services/openai/base_llm.py index 419d5db1e..8e0a45f0d 100644 --- a/src/pipecat/services/openai/base_llm.py +++ b/src/pipecat/services/openai/base_llm.py @@ -492,8 +492,9 @@ class BaseOpenAILLMService(LLMService): await self.push_frame(LLMFullResponseStartFrame()) await self.start_processing_metrics() await self._process_context(context) - except httpx.TimeoutException: + except httpx.TimeoutException as e: await self._call_event_handler("on_completion_timeout") + await self.push_error(error_msg="LLM completion timeout", exception=e) finally: await self.stop_processing_metrics() await self.push_frame(LLMFullResponseEndFrame()) diff --git a/tests/test_openai_llm_timeout.py b/tests/test_openai_llm_timeout.py new file mode 100644 index 000000000..df9483289 --- /dev/null +++ b/tests/test_openai_llm_timeout.py @@ -0,0 +1,127 @@ +# +# Copyright (c) 2024-2026, Daily +# +# SPDX-License-Identifier: BSD 2-Clause License +# + +"""Unit tests for OpenAI LLM timeout handling.""" + +from unittest.mock import AsyncMock, patch + +import httpx +import pytest + +from pipecat.frames.frames import ( + LLMContextFrame, + LLMFullResponseEndFrame, + LLMFullResponseStartFrame, +) +from pipecat.processors.aggregators.llm_context import LLMContext +from pipecat.processors.frame_processor import FrameDirection +from pipecat.services.openai.llm import OpenAILLMService + + +@pytest.mark.asyncio +async def test_openai_llm_emits_error_frame_on_timeout(): + """Test that OpenAI LLM service emits ErrorFrame when a timeout occurs. + + This enables LLMSwitcher to trigger failover to backup LLMs when the + primary LLM times out. + """ + with patch.object(OpenAILLMService, "create_client"): + service = OpenAILLMService(model="gpt-4") + service._client = AsyncMock() + + # Track pushed frames and errors + pushed_frames = [] + pushed_errors = [] + timeout_handler_called = False + + original_push_frame = service.push_frame + + async def mock_push_frame(frame, direction=FrameDirection.DOWNSTREAM): + pushed_frames.append(frame) + await original_push_frame(frame, direction) + + async def mock_push_error(error_msg, exception=None): + pushed_errors.append({"error_msg": error_msg, "exception": exception}) + + async def mock_timeout_handler(event_name): + nonlocal timeout_handler_called + if event_name == "on_completion_timeout": + timeout_handler_called = True + + service.push_frame = mock_push_frame + service.push_error = mock_push_error + service._call_event_handler = AsyncMock(side_effect=mock_timeout_handler) + + # Mock _process_context to raise TimeoutException + service._process_context = AsyncMock( + side_effect=httpx.TimeoutException("Connection timed out") + ) + + # Mock metrics methods + service.start_processing_metrics = AsyncMock() + service.stop_processing_metrics = AsyncMock() + service.start_ttfb_metrics = AsyncMock() + + # Create a context frame to process + context = LLMContext( + messages=[{"role": "user", "content": "Hello"}], + ) + frame = LLMContextFrame(context=context) + + # Process the frame + await service.process_frame(frame, FrameDirection.DOWNSTREAM) + + # Verify timeout handler was called + service._call_event_handler.assert_called_once_with("on_completion_timeout") + assert timeout_handler_called + + # Verify push_error was called with correct message + assert len(pushed_errors) == 1 + assert pushed_errors[0]["error_msg"] == "LLM completion timeout" + assert isinstance(pushed_errors[0]["exception"], httpx.TimeoutException) + + # Verify LLMFullResponseStartFrame and LLMFullResponseEndFrame were pushed + frame_types = [type(f) for f in pushed_frames] + assert LLMFullResponseStartFrame in frame_types + assert LLMFullResponseEndFrame in frame_types + + +@pytest.mark.asyncio +async def test_openai_llm_timeout_still_pushes_end_frame(): + """Test that LLMFullResponseEndFrame is pushed even when timeout occurs. + + The finally block should ensure proper cleanup regardless of timeout. + """ + with patch.object(OpenAILLMService, "create_client"): + service = OpenAILLMService(model="gpt-4") + service._client = AsyncMock() + + pushed_frames = [] + + async def mock_push_frame(frame, direction=FrameDirection.DOWNSTREAM): + pushed_frames.append(frame) + + service.push_frame = mock_push_frame + service.push_error = AsyncMock() + service._call_event_handler = AsyncMock() + service._process_context = AsyncMock(side_effect=httpx.TimeoutException("Timeout")) + service.start_processing_metrics = AsyncMock() + service.stop_processing_metrics = AsyncMock() + + context = LLMContext( + messages=[{"role": "user", "content": "Hello"}], + ) + frame = LLMContextFrame(context=context) + + await service.process_frame(frame, FrameDirection.DOWNSTREAM) + + # Verify both start and end frames are pushed + frame_types = [type(f) for f in pushed_frames] + assert LLMFullResponseStartFrame in frame_types + assert LLMFullResponseEndFrame in frame_types + + # Verify metrics were stopped + service.stop_processing_metrics.assert_called_once() From c5be67f2935e8909a4fabd3573c258038689bcbd Mon Sep 17 00:00:00 2001 From: ssillerom Date: Wed, 28 Jan 2026 17:56:21 +0100 Subject: [PATCH 0270/1060] fix: create disconnect message passing output vars --- src/pipecat/serializers/genesys.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/src/pipecat/serializers/genesys.py b/src/pipecat/serializers/genesys.py index cced94997..31e32f4dc 100644 --- a/src/pipecat/serializers/genesys.py +++ b/src/pipecat/serializers/genesys.py @@ -572,7 +572,7 @@ class GenesysAudioHookSerializer(FrameSerializer): the frame type is not handled or session is not open. """ if isinstance(frame, (EndFrame, CancelFrame)): - return json.dumps(self.create_disconnect_message(reason="completed")) + return json.dumps(self.create_disconnect_message(output_variables=self.output_variables, reason="completed")) elif isinstance(frame, AudioRawFrame): if not self._is_open or self._is_paused: From 2612fae5271b2aa2298694be557154b386e99ff3 Mon Sep 17 00:00:00 2001 From: ssillerom Date: Wed, 28 Jan 2026 18:02:51 +0100 Subject: [PATCH 0271/1060] ruff linting --- src/pipecat/serializers/genesys.py | 299 +++++++++++++++-------------- 1 file changed, 153 insertions(+), 146 deletions(-) diff --git a/src/pipecat/serializers/genesys.py b/src/pipecat/serializers/genesys.py index 31e32f4dc..d5d37d12b 100644 --- a/src/pipecat/serializers/genesys.py +++ b/src/pipecat/serializers/genesys.py @@ -9,14 +9,14 @@ Features: - Input/output variables for Architect flow integration - DTMF event support - Barge-in (interruption) events -- Pause/resume support for hold scenarios +- Pause/resume support for hold scenarios (optional) Protocol Reference: - https://developer.genesys.cloud/devapps/audiohook Audio Format: - PCMU (μ-law) at 8kHz sample rate (preferred) -- L16 (16-bit linear PCM) at 8kHz also supported +- L16 (16-bit linear PCM) at 8kHz also supported - Mono (external channel) or Stereo (external on left, internal on right) """ @@ -49,6 +49,7 @@ from pipecat.serializers.base_serializer import FrameSerializer class AudioHookMessageType(str, Enum): """AudioHook protocol message types.""" + OPEN = "open" OPENED = "opened" CLOSE = "close" @@ -65,15 +66,17 @@ class AudioHookMessageType(str, Enum): class AudioHookChannel(str, Enum): """AudioHook audio channel configuration.""" + EXTERNAL = "external" # Customer audio only (mono) INTERNAL = "internal" # Agent audio only (mono) - BOTH = "both" # Stereo: external=left, internal=right + BOTH = "both" # Stereo: external=left, internal=right class AudioHookMediaFormat(str, Enum): """Supported audio formats.""" + PCMU = "PCMU" # μ-law, 8kHz - L16 = "L16" # 16-bit linear PCM, 8kHz + L16 = "L16" # 16-bit linear PCM, 8kHz class GenesysAudioHookSerializer(FrameSerializer): @@ -81,7 +84,7 @@ class GenesysAudioHookSerializer(FrameSerializer): This serializer handles converting between Pipecat frames and Genesys AudioHook protocol messages. It supports: - + - Bidirectional audio streaming (PCMU at 8kHz) - Automatic protocol handshake (open/opened, close/closed, ping/pong) - Session lifecycle management with pause/resume support @@ -102,7 +105,7 @@ class GenesysAudioHookSerializer(FrameSerializer): selected_language="en-US", ) ) - + # Use with FastAPI WebSocket transport transport = FastAPIWebsocketTransport( websocket=websocket, @@ -113,11 +116,11 @@ class GenesysAudioHookSerializer(FrameSerializer): audio_out_fixed_packet_size=1600, # Important: prevents 429 rate limiting from Genesys ), ) - + # Access call information after connection participant = serializer.participant # ani, dnis, etc. input_vars = serializer.input_variables # Custom vars from Architect - + # Set output variables to return to Architect serializer.set_output_variables({"intent": "billing", "resolved": True}) ``` @@ -166,23 +169,23 @@ class GenesysAudioHookSerializer(FrameSerializer): """ super().__init__(**kwargs) self._params = params or GenesysAudioHookSerializer.InputParams() - + self._genesys_sample_rate = self._params.genesys_sample_rate self._sample_rate = 0 # Pipeline input rate, set in setup() self._session_id = str(uuid.uuid4()) - + # Use Pipecat's official resampler if needed (SOXR) # Only used for TTS output (16kHz → 8kHz), input goes without resampling self._input_resampler = SOXRStreamAudioResampler() self._output_resampler = SOXRStreamAudioResampler() - + # Protocol state self._client_seq = 0 self._server_seq = 0 self._is_open = False self._is_paused = False self._position = timedelta(0) - + # Session metadata self._conversation_id: Optional[str] = None self._participant: Optional[Dict[str, Any]] = None @@ -200,7 +203,6 @@ class GenesysAudioHookSerializer(FrameSerializer): self._register_event_handler("on_error") self._register_event_handler("on_dtmf") - @property def session_id(self) -> str: """Get the Genesys AudioHook session ID generated by the serializer.""" @@ -238,13 +240,13 @@ class GenesysAudioHookSerializer(FrameSerializer): def set_output_variables(self, variables: Dict[str, Any]) -> None: """Set custom output variables to send back to Genesys on close. - + These variables will be included in the 'closed' response when Genesys closes the connection, making them available in the Architect flow. - + Args: variables: Dictionary of custom variables to send to Genesys. - + Example: ```python # During the conversation, collect data and set it @@ -267,13 +269,13 @@ class GenesysAudioHookSerializer(FrameSerializer): """ self._sample_rate = self._params.sample_rate or frame.audio_in_sample_rate logger.debug(f"GenesysAudioHookSerializer setup with sample_rate={self._sample_rate}") - + def _format_position(self, position: timedelta) -> str: """Format a timedelta as ISO 8601 duration string. - + Args: position: The timedelta to format. - + Returns: ISO 8601 duration string (e.g., "PT1.5S"). """ @@ -282,10 +284,10 @@ class GenesysAudioHookSerializer(FrameSerializer): def _parse_position(self, position_str: str) -> timedelta: """Parse an ISO 8601 duration string to timedelta. - + Args: position_str: ISO 8601 duration string (e.g., "PT1.5S"). - + Returns: Corresponding timedelta. """ @@ -310,16 +312,16 @@ class GenesysAudioHookSerializer(FrameSerializer): include_position: bool = True, ) -> Dict[str, Any]: """Create a protocol message with common fields. - + Based on the Genesys AudioHook protocol, responses include: - seq: Server's sequence number (incremented per message) - clientseq: Echo of the client's last sequence number - + Args: msg_type: The message type. parameters: Optional parameters object. include_position: Whether to include position field. - + Returns: The message dictionary. """ @@ -331,13 +333,13 @@ class GenesysAudioHookSerializer(FrameSerializer): "clientseq": self._client_seq, "id": self._session_id, } - + if include_position: msg["position"] = self._format_position(self._position) - + if parameters: msg["parameters"] = parameters - + return msg def create_opened_response( @@ -347,27 +349,27 @@ class GenesysAudioHookSerializer(FrameSerializer): selected_language: Optional[str] = None, ) -> Dict[str, Any]: """Create an 'opened' response message for the client. - + This should be sent in response to an 'open' message from Genesys. - + Args: start_paused: Whether to start the session paused. supported_languages: List of supported language codes. selected_language: The selected language code. - + Returns: Dictionary of the opened response message. """ # Build channels list based on configuration channels: list[str] = [] - + if self._params.channel == AudioHookChannel.EXTERNAL: channels = ["external"] elif self._params.channel == AudioHookChannel.INTERNAL: channels = ["internal"] elif self._params.channel == AudioHookChannel.BOTH: channels = ["external", "internal"] - + parameters = { "startPaused": start_paused, "media": [ @@ -379,22 +381,22 @@ class GenesysAudioHookSerializer(FrameSerializer): } ], } - + if supported_languages: parameters["supportedLanguages"] = supported_languages if selected_language: parameters["selectedLanguage"] = selected_language - + msg = self._create_message( AudioHookMessageType.OPENED, parameters=parameters, include_position=False, # opened doesn't need position ) - + self._is_open = True logger.debug(f"AudioHook session opened: {self._session_id}") - + return msg def create_closed_response( @@ -402,17 +404,17 @@ class GenesysAudioHookSerializer(FrameSerializer): output_variables: Optional[Dict[str, Any]] = None, ) -> Dict[str, Any]: """Create a 'closed' response message. - + This should be sent in response to a 'close' message from Genesys. - + Args: output_variables: Optional custom variables to pass back to Genesys. These will be available in the Architect flow after the AudioHook action completes. - + Returns: Dictionary of the closed response message. - + Example: ```python # Pass custom data back to Genesys @@ -426,25 +428,25 @@ class GenesysAudioHookSerializer(FrameSerializer): ``` """ parameters: Optional[Dict[str, Any]] = None - + if output_variables: parameters = {"outputVariables": output_variables} - + msg = self._create_message( AudioHookMessageType.CLOSED, parameters=parameters, ) - + self._is_open = False logger.debug(f"AudioHook session closed: {self._session_id}") - + return msg def create_pong_response(self) -> Dict[str, Any]: """Create a 'pong' response message. - + This should be sent in response to a 'ping' message from Genesys. - + Returns: Dictionary of the pong response message. """ @@ -453,39 +455,35 @@ class GenesysAudioHookSerializer(FrameSerializer): def create_resumed_response(self) -> Dict[str, Any]: """Create a 'resumed' response message. - + This should be sent in response to a 'pause' message when ready to resume. - + Returns: Dictionary of the resumed response message. """ msg = self._create_message(AudioHookMessageType.RESUMED) - + self._is_paused = False logger.debug(f"AudioHook session resumed: {self._session_id}") - + return msg def create_barge_in_event(self) -> Dict[str, Any]: """Create a barge-in event message. - + This notifies Genesys Cloud that the user has interrupted the bot's audio output. Genesys will stop any queued audio playback. - + Returns: Dictionary of the barge-in event message. """ msg = self._create_message( AudioHookMessageType.EVENT, - parameters={ - "entities": [ - {"type": "barge_in", "data": {}} - ] - }, + parameters={"entities": [{"type": "barge_in", "data": {}}]}, ) - + logger.debug("🔇 Barge-in event sent to Genesys") - + return msg def create_disconnect_message( @@ -496,32 +494,32 @@ class GenesysAudioHookSerializer(FrameSerializer): info: Optional[str] = None, ) -> Dict[str, Any]: """Create a 'disconnect' message to initiate session termination. - + Args: reason: Disconnect reason (e.g., "completed", "error"). action: Action to take ("transfer" to agent, "finished" if completed). output_variables: Custom output variables to pass back to Genesys. info: Optional additional information. - + Returns: Dictionary of the disconnect message. """ parameters: Dict[str, Any] = {"reason": reason} - + # Build outputVariables out_vars = {"action": action} if output_variables: out_vars.update(output_variables) parameters["outputVariables"] = out_vars - + if info: parameters["info"] = info - + msg = self._create_message( AudioHookMessageType.DISCONNECT, parameters=parameters, ) - + logger.debug(f"AudioHook disconnect: reason={reason}, action={action}") return msg @@ -532,12 +530,12 @@ class GenesysAudioHookSerializer(FrameSerializer): retryable: bool = False, ) -> Dict[str, Any]: """Create an 'error' message. - + Args: code: Error code. message: Error message. retryable: Whether the operation can be retried. - + Returns: Dictionary of the error message. """ @@ -546,12 +544,12 @@ class GenesysAudioHookSerializer(FrameSerializer): "message": message, "retryable": retryable, } - + msg = self._create_message( AudioHookMessageType.ERROR, parameters=parameters, ) - + logger.error(f"AudioHook error: {code} - {message}") return msg @@ -572,14 +570,18 @@ class GenesysAudioHookSerializer(FrameSerializer): the frame type is not handled or session is not open. """ if isinstance(frame, (EndFrame, CancelFrame)): - return json.dumps(self.create_disconnect_message(output_variables=self.output_variables, reason="completed")) - + return json.dumps( + self.create_disconnect_message( + output_variables=self.output_variables, reason="completed" + ) + ) + elif isinstance(frame, AudioRawFrame): if not self._is_open or self._is_paused: return None - + data = frame.audio - + # Convert PCM to μ-law at 8kHz for Genesys if self._params.media_format == AudioHookMediaFormat.PCMU: serialized_data = await pcm_to_ulaw( @@ -592,15 +594,15 @@ class GenesysAudioHookSerializer(FrameSerializer): # L16 format - just resample if needed logger.warning("L16 format not yet fully implemented") return None - + if serialized_data is None or len(serialized_data) == 0: return None - + return bytes(serialized_data) elif isinstance(frame, InterruptionFrame): return json.dumps(self.create_barge_in_event()) - + elif isinstance(frame, (OutputTransportMessageFrame, OutputTransportMessageUrgentFrame)): # Only pass through AudioHook protocol messages (those with "version" field) # Filter out RTVI and other non-AudioHook messages @@ -609,7 +611,7 @@ class GenesysAudioHookSerializer(FrameSerializer): else: # Not an AudioHook message, ignore return None - + # Ignore other frames - we don't need to process them here return None @@ -639,39 +641,41 @@ class GenesysAudioHookSerializer(FrameSerializer): if isinstance(data, bytes): logger.debug(f"[AUDIO IN] Received {len(data)} bytes from Genesys") return await self._deserialize_audio(data) - + # Text data = JSON control message try: message = json.loads(data) except json.JSONDecodeError as e: logger.error(f"Failed to parse AudioHook message: {e}") return None - + return await self._handle_control_message(message) async def _deserialize_audio(self, data: bytes) -> Frame | None: """Deserialize binary audio data to an InputAudioRawFrame. - + Args: data: Raw audio bytes (PCMU or L16). - + Returns: InputAudioRawFrame with PCM audio at pipeline sample rate. """ if not self._is_open or self._is_paused: return None - + audio_data = data original_len = len(data) - + # If Genesys sends stereo audio (BOTH channels), extract only the external channel (left) # Stereo audio comes interleaved: [L0, R0, L1, R1, ...] if self._params.channel == AudioHookChannel.BOTH and len(data) > 0: # For PCMU, each sample is 1 byte # Extract only bytes at even positions (left channel = external) audio_data = bytes(data[i] for i in range(0, len(data), 2)) - logger.debug(f"🔊 Stereo audio: {original_len} bytes → {len(audio_data)} bytes (external channel)") - + logger.debug( + f"🔊 Stereo audio: {original_len} bytes → {len(audio_data)} bytes (external channel)" + ) + if self._params.media_format == AudioHookMediaFormat.PCMU: # Convert μ-law at 8kHz to PCM at pipeline rate deserialized_data = await ulaw_to_pcm( @@ -684,63 +688,62 @@ class GenesysAudioHookSerializer(FrameSerializer): # L16 format logger.warning("L16 format not yet fully implemented") return None - + if deserialized_data is None or len(deserialized_data) == 0: return None - + # Always use mono for STT - ElevenLabs expects single channel num_channels = 1 - + audio_frame = InputAudioRawFrame( audio=deserialized_data, num_channels=num_channels, sample_rate=self._sample_rate, ) - + return audio_frame - async def _handle_control_message(self, message: Dict[str, Any]) -> Frame | None: """Handle a JSON control message from Genesys. - + Args: message: Parsed JSON message. - + Returns: Frame if the message should be passed to the pipeline, None otherwise. """ msg_type = message.get("type", "") self._client_seq = message.get("seq", 0) - + # Update position if provided if "position" in message: self._position = self._parse_position(message["position"]) - + if msg_type == AudioHookMessageType.OPEN.value: return await self._handle_open(message) - + elif msg_type == AudioHookMessageType.CLOSE.value: return await self._handle_close(message) - + elif msg_type == AudioHookMessageType.PING.value: return await self._handle_ping(message) - + elif msg_type == AudioHookMessageType.PAUSE.value: return await self._handle_pause(message) - + elif msg_type == AudioHookMessageType.UPDATE.value: return await self._handle_update(message) elif msg_type == AudioHookMessageType.ERROR.value: return await self._handle_error(message) - + elif msg_type == "dtmf": return await self._handle_dtmf(message) - + elif msg_type == "playback_started": logger.debug("Playback started (from Genesys)") return None - + elif msg_type == "playback_completed": logger.debug("Playback completed (from Genesys)") return None @@ -750,40 +753,42 @@ class GenesysAudioHookSerializer(FrameSerializer): async def _handle_open(self, message: Dict[str, Any]) -> Frame | None: """Handle an 'open' message from Genesys. - + This initializes the session with metadata from Genesys Cloud and automatically responds with an 'opened' message using the configured InputParams (supported_languages, selected_language, start_paused). - + Extracts and stores: - session_id: The AudioHook session identifier - conversation_id: The Genesys conversation ID - participant: Caller info (ani, dnis, etc.) - input_variables: Custom variables from Architect flow - media_info: Audio configuration from Genesys - + Args: message: The open message from Genesys. - + Returns: OutputTransportMessageUrgentFrame with the 'opened' response. """ self._session_id = message.get("id", str(uuid.uuid4())) - + params = message.get("parameters", {}) self._conversation_id = params.get("conversationId") self._participant = params.get("participant") self._custom_config = params.get("customConfig") self._media_info = params.get("media") # This is a list of media objects self._input_variables = params.get("inputVariables") # Custom vars from Genesys - + # Extract media configuration if present # media is a list like: [{"type": "audio", "format": "PCMU", "channels": ["external"], "rate": 8000}] media_list = self._media_info if media_list and isinstance(media_list, list) and len(media_list) > 0: audio_media: Dict[str, Any] = media_list[0] # Get first media entry channels = audio_media.get("channels", []) - logger.debug(f"📡 Genesys audio config: format={audio_media.get('format')}, channels={channels}, rate={audio_media.get('rate')}") + logger.debug( + f"📡 Genesys audio config: format={audio_media.get('format')}, channels={channels}, rate={audio_media.get('rate')}" + ) # channels is a list like ["external"] or ["external", "internal"] if isinstance(channels, list): if "external" in channels and "internal" in channels: @@ -795,47 +800,49 @@ class GenesysAudioHookSerializer(FrameSerializer): elif "internal" in channels: self._params.channel = AudioHookChannel.INTERNAL logger.debug("📡 Mono mode: internal channel") - + # Log participant info for debugging ani = self._participant.get("ani", "unknown") if self._participant else "unknown" logger.info( f"AudioHook open request: session={self._session_id}, " f"conversation={self._conversation_id}, ani={ani}" ) - + await self._call_event_handler("on_open", message) - return OutputTransportMessageUrgentFrame(message=self.create_opened_response( - start_paused=self._params.start_paused, - supported_languages=self._params.supported_languages, - selected_language=self._params.selected_language - )) + return OutputTransportMessageUrgentFrame( + message=self.create_opened_response( + start_paused=self._params.start_paused, + supported_languages=self._params.supported_languages, + selected_language=self._params.selected_language, + ) + ) async def _handle_close(self, message: Dict[str, Any]) -> Frame | None: """Handle a 'close' message from Genesys. - + Automatically responds with a 'closed' message. If output_variables were set via set_output_variables(), they will be included in the response and made available in the Architect flow. - + Args: message: The close message from Genesys. - + Returns: OutputTransportMessageUrgentFrame with the closed response (includes outputVariables if set). """ params = message.get("parameters", {}) reason = params.get("reason", "unknown") - + logger.info(f"🔴 Genesys closed the connection: {reason}") - + self._is_open = False logger.info(f"Sending closed response to Genesys...") await self._call_event_handler("on_close", message) - + # Return as urgent frame to be sent through pipeline immediately # Include any output variables that were set during the session return OutputTransportMessageUrgentFrame( @@ -844,12 +851,12 @@ class GenesysAudioHookSerializer(FrameSerializer): async def _handle_ping(self, message: Dict[str, Any]) -> Frame | None: """Handle a 'ping' message from Genesys. - + Automatically responds with a 'pong' message to maintain the connection. - + Args: message: The ping message from Genesys. - + Returns: OutputTransportMessageUrgentFrame with pong response. """ @@ -862,92 +869,92 @@ class GenesysAudioHookSerializer(FrameSerializer): async def _handle_pause(self, message: Dict[str, Any]) -> Frame | None: """Handle a 'pause' message from Genesys. - + This is used when audio streaming is temporarily suspended (e.g., during hold). - + Args: message: The pause message. - + Returns: None (response should be sent via create_resumed_response()). """ params = message.get("parameters", {}) reason = params.get("reason", "unknown") - + logger.info(f"AudioHook pause request: reason={reason}") - + self._is_paused = True await self._call_event_handler("on_pause", message) - + # Note: Application should call create_resumed_response() when ready return None async def _handle_update(self, message: Dict[str, Any]) -> Frame | None: """Handle an 'update' message from Genesys. - + Updates may include changes to participants or configuration. - + Args: message: The update message. - + Returns: None. """ params = message.get("parameters", {}) - + if "participant" in params: self._participant = params["participant"] - + logger.debug(f"AudioHook update received: {params}") await self._call_event_handler("on_update", message) - + return None async def _handle_error(self, message: Dict[str, Any]) -> Frame | None: """Handle an 'error' message from Genesys. - + Args: message: The error message. - + Returns: None. """ params = message.get("parameters", {}) code = params.get("code", 0) error_msg = params.get("message", "Unknown error") - + logger.error(f"AudioHook error from Genesys: {code} - {error_msg}") await self._call_event_handler("on_error", message) - + return None async def _handle_dtmf(self, message: Dict[str, Any]) -> Frame | None: """Handle a 'dtmf' message from Genesys. - + DTMF (Dual-Tone Multi-Frequency) events are sent when the user presses keys on their phone keypad. - + Args: message: The DTMF message. - + Returns: InputDTMFFrame with the pressed digit. """ params = message.get("parameters", {}) digit = params.get("digit", "") - + if not digit: logger.warning("DTMF message received without digit") return None - + logger.info(f"DTMF received: {digit}") await self._call_event_handler("on_dtmf", message) - + try: return InputDTMFFrame(KeypadEntry(digit)) except ValueError: From 10fb77c0e21dec0c7951f4feda7dd7a0bde71a17 Mon Sep 17 00:00:00 2001 From: ssillerom Date: Wed, 28 Jan 2026 18:07:33 +0100 Subject: [PATCH 0272/1060] added changelog file --- changelog/3500.added.md | 1 + 1 file changed, 1 insertion(+) create mode 100644 changelog/3500.added.md diff --git a/changelog/3500.added.md b/changelog/3500.added.md new file mode 100644 index 000000000..64881e91b --- /dev/null +++ b/changelog/3500.added.md @@ -0,0 +1 @@ +- Added new `GenesysFrameSerializer` for the Genesys AudioHook WebSocket protocol, enabling bidirectional audio streaming between Pipecat pipelines and Genesys Cloud contact center. \ No newline at end of file From 55dadc91181089cfb8b32149f6047aa01c6e220a Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Aleix=20Conchillo=20Flaqu=C3=A9?= Date: Wed, 28 Jan 2026 09:15:42 -0800 Subject: [PATCH 0273/1060] tests(genesys): fix formatting --- tests/genesys/__init__.py | 5 - tests/genesys/conftest.py | 6 + tests/genesys/test_genesys_serializer.py | 139 ++++++++++++----------- 3 files changed, 77 insertions(+), 73 deletions(-) diff --git a/tests/genesys/__init__.py b/tests/genesys/__init__.py index 05982ea05..8b1378917 100644 --- a/tests/genesys/__init__.py +++ b/tests/genesys/__init__.py @@ -1,6 +1 @@ -# Copyright (c) 2026, Daily -# -# SPDX-License-Identifier: BSD 2-Clause License -# -"""Tests for Genesys AudioHook serializer.""" diff --git a/tests/genesys/conftest.py b/tests/genesys/conftest.py index 656e815a5..a0cf1588f 100644 --- a/tests/genesys/conftest.py +++ b/tests/genesys/conftest.py @@ -1,3 +1,9 @@ +# +# Copyright (c) 2024-2026, Daily +# +# SPDX-License-Identifier: BSD 2-Clause License +# + """Pytest fixtures for Genesys AudioHook serializer tests. These fixtures provide sample AudioHook protocol messages for testing diff --git a/tests/genesys/test_genesys_serializer.py b/tests/genesys/test_genesys_serializer.py index 00942ab3c..03132d7cb 100644 --- a/tests/genesys/test_genesys_serializer.py +++ b/tests/genesys/test_genesys_serializer.py @@ -1,3 +1,9 @@ +# +# Copyright (c) 2024-2026, Daily +# +# SPDX-License-Identifier: BSD 2-Clause License +# + """Tests for the Genesys AudioHook serializer.""" import json @@ -16,7 +22,7 @@ class TestGenesysAudioHookSerializer: def test_create_serializer_default_params(self): """Test creating serializer with default parameters.""" serializer = GenesysAudioHookSerializer() - + # session_id is auto-generated as UUID assert serializer.session_id != "" assert len(serializer.session_id) == 36 # UUID format @@ -33,7 +39,7 @@ class TestGenesysAudioHookSerializer: start_paused=True, ) serializer = GenesysAudioHookSerializer(params=params) - + assert serializer.session_id != "" # ==================== Response Creation Tests ==================== @@ -41,9 +47,9 @@ class TestGenesysAudioHookSerializer: def test_create_opened_response(self): """Test creating an opened response message.""" serializer = GenesysAudioHookSerializer() - + msg = serializer.create_opened_response() - + assert msg["type"] == "opened" assert msg["version"] == "2" assert msg["id"] == serializer.session_id @@ -53,21 +59,21 @@ class TestGenesysAudioHookSerializer: def test_create_opened_response_with_languages(self): """Test creating an opened response with language options.""" serializer = GenesysAudioHookSerializer() - + msg = serializer.create_opened_response( supported_languages=["es", "en", "fr"], selected_language="es", ) - + assert msg["parameters"]["supportedLanguages"] == ["es", "en", "fr"] assert msg["parameters"]["selectedLanguage"] == "es" def test_create_pong_response(self): """Test creating a pong response message.""" serializer = GenesysAudioHookSerializer() - + msg = serializer.create_pong_response() - + assert msg["type"] == "pong" assert msg["id"] == serializer.session_id @@ -75,9 +81,9 @@ class TestGenesysAudioHookSerializer: """Test creating a closed response message.""" serializer = GenesysAudioHookSerializer() serializer._is_open = True - + msg = serializer.create_closed_response() - + assert msg["type"] == "closed" assert serializer.is_open is False assert "parameters" not in msg # No parameters when no output_variables @@ -86,15 +92,15 @@ class TestGenesysAudioHookSerializer: """Test creating a closed response with custom output variables.""" serializer = GenesysAudioHookSerializer() serializer._is_open = True - + msg = serializer.create_closed_response( output_variables={ "intent": "billing_inquiry", "customer_verified": True, - "summary": "Customer asked about their bill" + "summary": "Customer asked about their bill", } ) - + assert msg["type"] == "closed" assert msg["parameters"]["outputVariables"]["intent"] == "billing_inquiry" assert msg["parameters"]["outputVariables"]["customer_verified"] is True @@ -104,21 +110,21 @@ class TestGenesysAudioHookSerializer: """Test creating a resumed response message.""" serializer = GenesysAudioHookSerializer() serializer._is_paused = True - + msg = serializer.create_resumed_response() - + assert msg["type"] == "resumed" assert serializer.is_paused is False def test_create_disconnect_message(self): """Test creating a disconnect message.""" serializer = GenesysAudioHookSerializer() - + msg = serializer.create_disconnect_message( reason="completed", action="transfer", ) - + assert msg["type"] == "disconnect" assert msg["parameters"]["reason"] == "completed" assert msg["parameters"]["outputVariables"]["action"] == "transfer" @@ -126,26 +132,26 @@ class TestGenesysAudioHookSerializer: def test_create_disconnect_message_with_output_variables(self): """Test creating a disconnect message with custom output variables.""" serializer = GenesysAudioHookSerializer() - + msg = serializer.create_disconnect_message( reason="completed", action="finished", output_variables={"result": "success", "code": "123"}, ) - + assert msg["parameters"]["outputVariables"]["result"] == "success" assert msg["parameters"]["outputVariables"]["code"] == "123" def test_create_error_message(self): """Test creating an error message.""" serializer = GenesysAudioHookSerializer() - + msg = serializer.create_error_message( code=500, message="Internal error", retryable=True, ) - + assert msg["type"] == "error" assert msg["parameters"]["code"] == 500 assert msg["parameters"]["message"] == "Internal error" @@ -157,9 +163,9 @@ class TestGenesysAudioHookSerializer: async def test_handle_open_message(self, sample_open_message): """Test handling an open message returns opened frame.""" serializer = GenesysAudioHookSerializer() - + result = await serializer.deserialize(json.dumps(sample_open_message)) - + # Now returns OutputTransportMessageUrgentFrame with opened response assert isinstance(result, OutputTransportMessageUrgentFrame) assert result.message["type"] == "opened" @@ -170,9 +176,9 @@ class TestGenesysAudioHookSerializer: async def test_handle_open_message_extracts_participant(self, sample_open_message): """Test that open message extracts participant info.""" serializer = GenesysAudioHookSerializer() - + await serializer.deserialize(json.dumps(sample_open_message)) - + assert serializer.participant is not None assert serializer.participant["ani"] == "+1234567890" assert serializer.participant["dnis"] == "+0987654321" @@ -186,21 +192,23 @@ class TestGenesysAudioHookSerializer: start_paused=True, ) serializer = GenesysAudioHookSerializer(params=params) - + result = await serializer.deserialize(json.dumps(sample_open_message)) - + assert isinstance(result, OutputTransportMessageUrgentFrame) assert result.message["parameters"]["supportedLanguages"] == ["es-ES", "en-US"] assert result.message["parameters"]["selectedLanguage"] == "es-ES" assert result.message["parameters"]["startPaused"] is True @pytest.mark.asyncio - async def test_handle_open_message_extracts_input_variables(self, sample_open_message_with_input_variables): + async def test_handle_open_message_extracts_input_variables( + self, sample_open_message_with_input_variables + ): """Test that open message extracts inputVariables from Genesys.""" serializer = GenesysAudioHookSerializer() - + await serializer.deserialize(json.dumps(sample_open_message_with_input_variables)) - + assert serializer.input_variables is not None assert serializer.input_variables["customer_id"] == "cust-789" assert serializer.input_variables["queue_name"] == "billing" @@ -211,9 +219,9 @@ class TestGenesysAudioHookSerializer: async def test_handle_ping_message(self, sample_ping_message): """Test handling a ping message returns pong frame.""" serializer = GenesysAudioHookSerializer() - + result = await serializer.deserialize(json.dumps(sample_ping_message)) - + assert isinstance(result, OutputTransportMessageUrgentFrame) assert result.message["type"] == "pong" @@ -222,9 +230,9 @@ class TestGenesysAudioHookSerializer: """Test handling a close message returns closed frame.""" serializer = GenesysAudioHookSerializer() serializer._is_open = True - + result = await serializer.deserialize(json.dumps(sample_close_message)) - + assert isinstance(result, OutputTransportMessageUrgentFrame) assert result.message["type"] == "closed" assert serializer.is_open is False @@ -234,16 +242,14 @@ class TestGenesysAudioHookSerializer: """Test that close response includes output variables when set.""" serializer = GenesysAudioHookSerializer() serializer._is_open = True - + # Set output variables before close - serializer.set_output_variables({ - "intent": "support", - "resolved": True, - "transfer_to": "agent_queue" - }) - + serializer.set_output_variables( + {"intent": "support", "resolved": True, "transfer_to": "agent_queue"} + ) + result = await serializer.deserialize(json.dumps(sample_close_message)) - + assert isinstance(result, OutputTransportMessageUrgentFrame) assert result.message["type"] == "closed" assert result.message["parameters"]["outputVariables"]["intent"] == "support" @@ -255,14 +261,11 @@ class TestGenesysAudioHookSerializer: def test_set_output_variables(self): """Test setting output variables.""" serializer = GenesysAudioHookSerializer() - + assert serializer.output_variables is None - - serializer.set_output_variables({ - "intent": "billing", - "score": 0.95 - }) - + + serializer.set_output_variables({"intent": "billing", "score": 0.95}) + assert serializer.output_variables is not None assert serializer.output_variables["intent"] == "billing" assert serializer.output_variables["score"] == 0.95 @@ -270,10 +273,10 @@ class TestGenesysAudioHookSerializer: def test_set_output_variables_overwrites(self): """Test that setting output variables overwrites previous values.""" serializer = GenesysAudioHookSerializer() - + serializer.set_output_variables({"first": "value"}) serializer.set_output_variables({"second": "value"}) - + assert "first" not in serializer.output_variables assert serializer.output_variables["second"] == "value" @@ -282,9 +285,9 @@ class TestGenesysAudioHookSerializer: """Test handling a pause message.""" serializer = GenesysAudioHookSerializer() serializer._is_open = True - + result = await serializer.deserialize(json.dumps(sample_pause_message)) - + assert result is None # Pause is handled internally assert serializer.is_paused is True @@ -292,9 +295,9 @@ class TestGenesysAudioHookSerializer: async def test_handle_update_message(self, sample_update_message): """Test handling an update message.""" serializer = GenesysAudioHookSerializer() - + result = await serializer.deserialize(json.dumps(sample_update_message)) - + assert result is None # Update is handled internally assert serializer.participant is not None assert serializer.participant["name"] == "John Doe" @@ -303,9 +306,9 @@ class TestGenesysAudioHookSerializer: async def test_handle_error_message(self, sample_error_message): """Test handling an error message.""" serializer = GenesysAudioHookSerializer() - + result = await serializer.deserialize(json.dumps(sample_error_message)) - + assert result is None # Error is logged but returns None # ==================== DTMF Tests ==================== @@ -314,9 +317,9 @@ class TestGenesysAudioHookSerializer: async def test_handle_dtmf_digit(self, sample_dtmf_message): """Test handling a DTMF digit message.""" serializer = GenesysAudioHookSerializer() - + result = await serializer.deserialize(json.dumps(sample_dtmf_message)) - + assert isinstance(result, InputDTMFFrame) assert result.button.value == "5" @@ -324,9 +327,9 @@ class TestGenesysAudioHookSerializer: async def test_handle_dtmf_star(self, sample_dtmf_star_message): """Test handling a DTMF star (*) message.""" serializer = GenesysAudioHookSerializer() - + result = await serializer.deserialize(json.dumps(sample_dtmf_star_message)) - + assert isinstance(result, InputDTMFFrame) assert result.button.value == "*" @@ -334,9 +337,9 @@ class TestGenesysAudioHookSerializer: async def test_handle_dtmf_hash(self, sample_dtmf_hash_message): """Test handling a DTMF hash (#) message.""" serializer = GenesysAudioHookSerializer() - + result = await serializer.deserialize(json.dumps(sample_dtmf_hash_message)) - + assert isinstance(result, InputDTMFFrame) assert result.button.value == "#" @@ -344,7 +347,7 @@ class TestGenesysAudioHookSerializer: async def test_handle_dtmf_empty_digit(self): """Test handling a DTMF message without digit.""" serializer = GenesysAudioHookSerializer() - + dtmf_msg = { "version": "2", "type": "dtmf", @@ -352,9 +355,9 @@ class TestGenesysAudioHookSerializer: "id": "test-session-123", "parameters": {}, } - + result = await serializer.deserialize(json.dumps(dtmf_msg)) - + assert result is None # No digit provided # ==================== Sequence Number Tests ==================== @@ -362,11 +365,11 @@ class TestGenesysAudioHookSerializer: def test_sequence_numbers_increment(self): """Test that sequence numbers increment correctly.""" serializer = GenesysAudioHookSerializer() - + response1 = serializer.create_pong_response() response2 = serializer.create_pong_response() response3 = serializer.create_pong_response() - + assert response1["seq"] == 1 assert response2["seq"] == 2 assert response3["seq"] == 3 From a7cd5b0322ae65c7f433fe8f0672f72619ef0e09 Mon Sep 17 00:00:00 2001 From: Pulkit Date: Wed, 28 Jan 2026 23:15:03 +0530 Subject: [PATCH 0274/1060] fix: adding missing livekit transport configs --- changelog/3580.fixed.md | 1 + src/pipecat/runner/types.py | 15 +++++++++++++++ src/pipecat/runner/utils.py | 12 ++++++++++++ 3 files changed, 28 insertions(+) create mode 100644 changelog/3580.fixed.md diff --git a/changelog/3580.fixed.md b/changelog/3580.fixed.md new file mode 100644 index 000000000..47f4aa6a2 --- /dev/null +++ b/changelog/3580.fixed.md @@ -0,0 +1 @@ +- Added missing `LiveKitRunnerArguments` and `LiveKitTransport` support in runner utilities to enable LiveKit transport configuration. diff --git a/src/pipecat/runner/types.py b/src/pipecat/runner/types.py index 4d480749a..0e997b963 100644 --- a/src/pipecat/runner/types.py +++ b/src/pipecat/runner/types.py @@ -106,3 +106,18 @@ class SmallWebRTCRunnerArguments(RunnerArguments): """ webrtc_connection: Any + + +@dataclass +class LiveKitRunnerArguments(RunnerArguments): + """LiveKit transport session arguments for the runner. + + Parameters: + room_name: LiveKit room name to join + token: Authentication token for the room + body: Additional request data + """ + + room_name: str + url: str + token: Optional[str] = None diff --git a/src/pipecat/runner/utils.py b/src/pipecat/runner/utils.py index 78f94b285..f54453d93 100644 --- a/src/pipecat/runner/utils.py +++ b/src/pipecat/runner/utils.py @@ -39,6 +39,7 @@ from loguru import logger from pipecat.runner.types import ( DailyRunnerArguments, + LiveKitRunnerArguments, SmallWebRTCRunnerArguments, WebSocketRunnerArguments, ) @@ -568,6 +569,17 @@ async def create_transport( return await _create_telephony_transport( runner_args.websocket, params, transport_type, call_data ) + elif isinstance(runner_args, LiveKitRunnerArguments): + params = _get_transport_params("livekit", transport_params) + + from pipecat.transports.livekit.transport import LiveKitTransport + + return LiveKitTransport( + runner_args.url, + runner_args.token, + runner_args.room_name, + params=params, + ) else: raise ValueError(f"Unsupported runner arguments type: {type(runner_args)}") From f3ef488925e2687b92a998127a36b6eff9c39102 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Aleix=20Conchillo=20Flaqu=C3=A9?= Date: Wed, 28 Jan 2026 10:02:25 -0800 Subject: [PATCH 0275/1060] rename DAILY_SAMPLE_ROOM_URL to DAILY_ROOM_URL --- changelog/3582.change.md | 1 + env.example | 2 +- examples/foundational/37-mem0.py | 2 +- examples/foundational/README.md | 2 +- scripts/evals/eval.py | 4 ++-- scripts/evals/utils.py | 2 +- src/pipecat/runner/daily.py | 6 +++--- src/pipecat/runner/run.py | 4 ++-- 8 files changed, 12 insertions(+), 11 deletions(-) create mode 100644 changelog/3582.change.md diff --git a/changelog/3582.change.md b/changelog/3582.change.md new file mode 100644 index 000000000..8581fc6cf --- /dev/null +++ b/changelog/3582.change.md @@ -0,0 +1 @@ +- Pipecat runner now uses `DAILY_ROOM_URL` instead of `DAILY_SAMPLE_ROOM_URL`. diff --git a/env.example b/env.example index c7b734ad6..e662ea54b 100644 --- a/env.example +++ b/env.example @@ -43,7 +43,7 @@ CEREBRAS_API_KEY=... # Daily DAILY_API_KEY=... -DAILY_SAMPLE_ROOM_URL=https://... +DAILY_ROOM_URL=https://... # Deepgram DEEPGRAM_API_KEY=... diff --git a/examples/foundational/37-mem0.py b/examples/foundational/37-mem0.py index 08a739c0a..11eae51fb 100644 --- a/examples/foundational/37-mem0.py +++ b/examples/foundational/37-mem0.py @@ -31,7 +31,7 @@ Requirements: - [Optional] Anthropic API key (if using Claude with local config) Environment variables (set in .env or in your terminal using `export`): - DAILY_SAMPLE_ROOM_URL=daily_sample_room_url + DAILY_ROOM_URL=daily_room_url DAILY_API_KEY=daily_api_key OPENAI_API_KEY=openai_api_key ELEVENLABS_API_KEY=elevenlabs_api_key diff --git a/examples/foundational/README.md b/examples/foundational/README.md index 5800efff3..9947dd1e6 100644 --- a/examples/foundational/README.md +++ b/examples/foundational/README.md @@ -37,7 +37,7 @@ Most examples support running with other transports, like Twilio or Daily. ### Daily -You need to create a Daily account at https://dashboard.daily.co/u/signup. Once signed up, you can create your own room from the dashboard and set the environment variables `DAILY_SAMPLE_ROOM_URL` and `DAILY_API_KEY`. Alternatively, you can let the example create a room for you (still needs `DAILY_API_KEY` environment variable). Then, start any example with `-t daily`: +You need to create a Daily account at https://dashboard.daily.co/u/signup. Once signed up, you can create your own room from the dashboard and set the environment variables `DAILY_ROOM_URL` and `DAILY_API_KEY`. Alternatively, you can let the example create a room for you (still needs `DAILY_API_KEY` environment variable). Then, start any example with `-t daily`: ```bash uv run 07-interruptible.py -t daily diff --git a/scripts/evals/eval.py b/scripts/evals/eval.py index 16598b4d7..20c15c1c9 100644 --- a/scripts/evals/eval.py +++ b/scripts/evals/eval.py @@ -195,7 +195,7 @@ class EvalRunner: async def run_example_pipeline(script_path: Path, eval_config: EvalConfig): - room_url = os.getenv("DAILY_SAMPLE_ROOM_URL") + room_url = os.getenv("DAILY_ROOM_URL") module = load_module_from_path(script_path) @@ -225,7 +225,7 @@ async def run_eval_pipeline( ): logger.info(f"Starting eval bot") - room_url = os.getenv("DAILY_SAMPLE_ROOM_URL") + room_url = os.getenv("DAILY_ROOM_URL") transport = DailyTransport( room_url, diff --git a/scripts/evals/utils.py b/scripts/evals/utils.py index 590cc0946..8111d404f 100644 --- a/scripts/evals/utils.py +++ b/scripts/evals/utils.py @@ -28,7 +28,7 @@ def check_env_variables() -> bool: "CARTESIA_API_KEY", "DEEPGRAM_API_KEY", "OPENAI_API_KEY", - "DAILY_SAMPLE_ROOM_URL", + "DAILY_ROOM_URL", ] for env in required_envs: if not os.getenv(env): diff --git a/src/pipecat/runner/daily.py b/src/pipecat/runner/daily.py index 6747dbd62..b2090b094 100644 --- a/src/pipecat/runner/daily.py +++ b/src/pipecat/runner/daily.py @@ -17,7 +17,7 @@ Functions: Environment variables: - DAILY_API_KEY - Daily API key for room/token creation (required) -- DAILY_SAMPLE_ROOM_URL (optional) - Existing room URL to use. If not provided, +- DAILY_ROOM_URL (optional) - Existing room URL to use. If not provided, a temporary room will be created automatically. Example:: @@ -91,7 +91,7 @@ async def configure( """Configure Daily room URL and token with optional SIP capabilities. This function will either: - 1. Use an existing room URL from DAILY_SAMPLE_ROOM_URL environment variable (standard mode only) + 1. Use an existing room URL from DAILY_ROOM_URL environment variable (standard mode only) 2. Create a new temporary room automatically if no URL is provided Args: @@ -177,7 +177,7 @@ async def configure( ) # Check for existing room URL (only in standard mode) - existing_room_url = os.getenv("DAILY_SAMPLE_ROOM_URL") + existing_room_url = os.getenv("DAILY_ROOM_URL") if existing_room_url and not sip_enabled: # Use existing room (standard mode only) logger.info(f"Using existing Daily room: {existing_room_url}") diff --git a/src/pipecat/runner/run.py b/src/pipecat/runner/run.py index 96fbf2598..6f7f1b53b 100644 --- a/src/pipecat/runner/run.py +++ b/src/pipecat/runner/run.py @@ -583,13 +583,13 @@ def _setup_daily_routes(app: FastAPI, dialin_enabled: bool = False): bot_module = _get_bot_module() - existing_room_url = os.getenv("DAILY_SAMPLE_ROOM_URL") + existing_room_url = os.getenv("DAILY_ROOM_URL") result = None # Configure room if: # 1. Explicitly requested via createDailyRoom in payload - # 2. Using pre-configured room from DAILY_SAMPLE_ROOM_URL env var + # 2. Using pre-configured room from DAILY_ROOM_URL env var if create_daily_room or existing_room_url: import aiohttp From c9f922c4798c6f1ba4857e0cca9c6dc8ae7d6923 Mon Sep 17 00:00:00 2001 From: filipi87 Date: Wed, 28 Jan 2026 15:38:40 -0300 Subject: [PATCH 0276/1060] Removed an overridden method that was identical to the parent implementation. --- src/pipecat/services/google/llm.py | 17 ----------------- 1 file changed, 17 deletions(-) diff --git a/src/pipecat/services/google/llm.py b/src/pipecat/services/google/llm.py index adb2664bb..fd6c2c54e 100644 --- a/src/pipecat/services/google/llm.py +++ b/src/pipecat/services/google/llm.py @@ -40,7 +40,6 @@ from pipecat.frames.frames import ( LLMThoughtStartFrame, LLMThoughtTextFrame, LLMUpdateSettingsFrame, - UserImageRawFrame, ) from pipecat.metrics.metrics import LLMTokenUsage from pipecat.processors.aggregators.llm_context import LLMContext @@ -199,22 +198,6 @@ class GoogleAssistantContextAggregator(OpenAIAssistantContextAggregator): if part.function_response and part.function_response.id == tool_call_id: part.function_response.response = {"value": json.dumps(result)} - async def handle_user_image_frame(self, frame: UserImageRawFrame): - """Handle user image frame. - - Args: - frame: Frame containing user image data and request context. - """ - await self._update_function_call_result( - frame.request.function_name, frame.request.tool_call_id, "COMPLETED" - ) - self._context.add_image_frame_message( - format=frame.format, - size=frame.size, - image=frame.image, - text=frame.request.context, - ) - @dataclass class GoogleContextAggregatorPair: From d3f4cbb6201bf980b93e12df32ae69f9a0984ed7 Mon Sep 17 00:00:00 2001 From: filipi87 Date: Wed, 28 Jan 2026 15:39:06 -0300 Subject: [PATCH 0277/1060] Providing a way to defer the function call results. --- src/pipecat/frames/frames.py | 2 ++ .../processors/aggregators/llm_response.py | 5 ++++ .../aggregators/llm_response_universal.py | 10 ++++--- src/pipecat/services/llm_service.py | 28 ++++++++++++++----- 4 files changed, 34 insertions(+), 11 deletions(-) diff --git a/src/pipecat/frames/frames.py b/src/pipecat/frames/frames.py index 26f9af9d2..8df97d313 100644 --- a/src/pipecat/frames/frames.py +++ b/src/pipecat/frames/frames.py @@ -1466,6 +1466,7 @@ class UserImageRequestFrame(SystemFrame): video_source: Specific video source to capture from. function_name: Name of function that generated this request (if any). tool_call_id: Tool call ID if generated by function call (if any). + result_callback: Optional callback to invoke when the image is retrieved. context: [DEPRECATED] Optional context for the image request. """ @@ -1475,6 +1476,7 @@ class UserImageRequestFrame(SystemFrame): video_source: Optional[str] = None function_name: Optional[str] = None tool_call_id: Optional[str] = None + result_callback: Optional[Any] = None context: Optional[Any] = None def __post_init__(self): diff --git a/src/pipecat/processors/aggregators/llm_response.py b/src/pipecat/processors/aggregators/llm_response.py index 1b53e9934..e11ededbf 100644 --- a/src/pipecat/processors/aggregators/llm_response.py +++ b/src/pipecat/processors/aggregators/llm_response.py @@ -1042,6 +1042,11 @@ class LLMAssistantContextAggregator(LLMContextResponseAggregator): del self._function_calls_in_progress[frame.request.tool_call_id] + # Call the result_callback if provided. This signals that the image + # has been retrieved and the function call can now complete. + if frame.request and frame.request.result_callback: + await frame.request.result_callback(None) + await self.handle_user_image_frame(frame) await self.push_aggregation() await self.push_context_frame(FrameDirection.UPSTREAM) diff --git a/src/pipecat/processors/aggregators/llm_response_universal.py b/src/pipecat/processors/aggregators/llm_response_universal.py index 3a8bbb542..200010591 100644 --- a/src/pipecat/processors/aggregators/llm_response_universal.py +++ b/src/pipecat/processors/aggregators/llm_response_universal.py @@ -941,16 +941,18 @@ class LLMAssistantAggregator(LLMContextAggregator): async def _handle_user_image_frame(self, frame: UserImageRawFrame): image_appended = False - # Check if this image is a result of a function call if so, let's cache. - # TODO(aleix): The function call might have already been executed - # because FunctionCallResultFrame was just faster, in that case we just - # push the context frame now. + # Check if this image is a result of a function call. if ( frame.request and frame.request.tool_call_id and frame.request.tool_call_id in self._function_calls_in_progress ): self._function_calls_image_results[frame.request.tool_call_id] = frame + + # Call the result_callback if provided. This signals that the image + # has been retrieved and the function call can now complete. + if frame.request.result_callback: + await frame.request.result_callback(None) else: image_appended = await self._maybe_append_image_to_context(frame) diff --git a/src/pipecat/services/llm_service.py b/src/pipecat/services/llm_service.py index 0368c8feb..035f1b2f2 100644 --- a/src/pipecat/services/llm_service.py +++ b/src/pipecat/services/llm_service.py @@ -170,17 +170,22 @@ class LLMService(AIService): # However, subclasses should override this with a more specific adapter when necessary. adapter_class: Type[BaseLLMAdapter] = OpenAILLMAdapter - def __init__(self, run_in_parallel: bool = True, **kwargs): + def __init__( + self, run_in_parallel: bool = True, function_call_timeout_secs: float = 10.0, **kwargs + ): """Initialize the LLM service. Args: run_in_parallel: Whether to run function calls in parallel or sequentially. Defaults to True. + function_call_timeout_secs: Timeout in seconds for deferred function calls. + Defaults to 10.0 seconds. **kwargs: Additional arguments passed to the parent AIService. """ super().__init__(**kwargs) self._run_in_parallel = run_in_parallel + self._function_call_timeout_secs = function_call_timeout_secs self._start_callbacks = {} self._adapter = self.adapter_class() self._functions: Dict[Optional[str], FunctionCallRegistryItem] = {} @@ -596,14 +601,26 @@ class LLMService(AIService): cancel_on_interruption=item.cancel_on_interruption, ) - callback_executed = False + # Start a timeout task for deferred function calls + async def timeout_handler(): + await asyncio.sleep(self._function_call_timeout_secs) + logger.warning( + f"{self} Function call [{runner_item.function_name}:{runner_item.tool_call_id}] timed out after {self._function_call_timeout_secs} seconds" + ) + await function_call_result_callback(None) + + timeout_task = self.create_task(timeout_handler()) # Define a callback function that pushes a FunctionCallResultFrame upstream & downstream. async def function_call_result_callback( result: Any, *, properties: Optional[FunctionCallResultProperties] = None ): - nonlocal callback_executed - callback_executed = True + nonlocal timeout_task + + # Cancel timeout task if it exists + if timeout_task and not timeout_task.done(): + await self.cancel_task(timeout_task) + await self.broadcast_frame( FunctionCallResultFrame, function_name=runner_item.function_name, @@ -653,9 +670,6 @@ class LLMService(AIService): error_message = f"Error executing function call [{runner_item.function_name}]: {e}" logger.error(f"{self} {error_message}") await self.push_error(error_msg=error_message, exception=e, fatal=False) - finally: - if not callback_executed: - await function_call_result_callback(None) async def _cancel_function_call(self, function_name: Optional[str]): cancelled_tasks = set() From c8496dfb8e6a3b4c96624a36db9cb7df6f46ad49 Mon Sep 17 00:00:00 2001 From: filipi87 Date: Wed, 28 Jan 2026 15:39:21 -0300 Subject: [PATCH 0278/1060] Updated the examples which use UserImageRequestFrame to defer the function call result. --- .../14d-function-calling-anthropic-video.py | 13 +++++-------- .../foundational/14d-function-calling-aws-video.py | 13 +++++-------- .../14d-function-calling-gemini-flash-video.py | 13 +++++-------- .../14d-function-calling-moondream-video.py | 13 +++++-------- .../14d-function-calling-openai-video.py | 13 +++++-------- .../foundational/14e-function-calling-google.py | 13 +++++-------- .../foundational/20d-persistent-context-gemini.py | 10 +++------- 7 files changed, 33 insertions(+), 55 deletions(-) diff --git a/examples/foundational/14d-function-calling-anthropic-video.py b/examples/foundational/14d-function-calling-anthropic-video.py index 8097ee988..c9dacaa75 100644 --- a/examples/foundational/14d-function-calling-anthropic-video.py +++ b/examples/foundational/14d-function-calling-anthropic-video.py @@ -48,14 +48,16 @@ async def fetch_user_image(params: FunctionCallParams): When called, this function pushes a UserImageRequestFrame upstream to the transport. As a result, the transport will request the user image and push a UserImageRawFrame downstream which will be added to the context by the LLM - assistant aggregator. + assistant aggregator. The result_callback will be invoked once the image is + retrieved and processed. """ user_id = params.arguments["user_id"] question = params.arguments["question"] logger.debug(f"Requesting image with user_id={user_id}, question={question}") # Request a user image frame and indicate that it should be added to the - # context. Also associate it to the function call. + # context. Also associate it to the function call. Pass the result_callback + # so it can be invoked when the image is actually retrieved. await params.llm.push_frame( UserImageRequestFrame( user_id=user_id, @@ -63,16 +65,11 @@ async def fetch_user_image(params: FunctionCallParams): append_to_context=True, function_name=params.function_name, tool_call_id=params.tool_call_id, + result_callback=params.result_callback, ), FrameDirection.UPSTREAM, ) - await params.result_callback(None) - - # Instead of None, it's possible to also provide a tool call answer to - # tell the LLM that we are grabbing the image to analyze. - # await params.result_callback({"result": "Image is being captured."}) - # We store functions so objects (e.g. SileroVADAnalyzer) don't get # instantiated. The function will be called when the desired transport gets diff --git a/examples/foundational/14d-function-calling-aws-video.py b/examples/foundational/14d-function-calling-aws-video.py index b972f4097..9faa925aa 100644 --- a/examples/foundational/14d-function-calling-aws-video.py +++ b/examples/foundational/14d-function-calling-aws-video.py @@ -48,14 +48,16 @@ async def fetch_user_image(params: FunctionCallParams): When called, this function pushes a UserImageRequestFrame upstream to the transport. As a result, the transport will request the user image and push a UserImageRawFrame downstream which will be added to the context by the LLM - assistant aggregator. + assistant aggregator. The result_callback will be invoked once the image is + retrieved and processed. """ user_id = params.arguments["user_id"] question = params.arguments["question"] logger.debug(f"Requesting image with user_id={user_id}, question={question}") # Request a user image frame and indicate that it should be added to the - # context. Also associate it to the function call. + # context. Also associate it to the function call. Pass the result_callback + # so it can be invoked when the image is actually retrieved. await params.llm.push_frame( UserImageRequestFrame( user_id=user_id, @@ -63,16 +65,11 @@ async def fetch_user_image(params: FunctionCallParams): append_to_context=True, function_name=params.function_name, tool_call_id=params.tool_call_id, + result_callback=params.result_callback, ), FrameDirection.UPSTREAM, ) - await params.result_callback(None) - - # Instead of None, it's possible to also provide a tool call answer to - # tell the LLM that we are grabbing the image to analyze. - # await params.result_callback({"result": "Image is being captured."}) - # We store functions so objects (e.g. SileroVADAnalyzer) don't get # instantiated. The function will be called when the desired transport gets diff --git a/examples/foundational/14d-function-calling-gemini-flash-video.py b/examples/foundational/14d-function-calling-gemini-flash-video.py index ba9dcd266..857eb92b6 100644 --- a/examples/foundational/14d-function-calling-gemini-flash-video.py +++ b/examples/foundational/14d-function-calling-gemini-flash-video.py @@ -48,14 +48,16 @@ async def fetch_user_image(params: FunctionCallParams): When called, this function pushes a UserImageRequestFrame upstream to the transport. As a result, the transport will request the user image and push a UserImageRawFrame downstream which will be added to the context by the LLM - assistant aggregator. + assistant aggregator. The result_callback will be invoked once the image is + retrieved and processed. """ user_id = params.arguments["user_id"] question = params.arguments["question"] logger.debug(f"Requesting image with user_id={user_id}, question={question}") # Request a user image frame and indicate that it should be added to the - # context. Also associate it to the function call. + # context. Also associate it to the function call. Pass the result_callback + # so it can be invoked when the image is actually retrieved. await params.llm.push_frame( UserImageRequestFrame( user_id=user_id, @@ -63,16 +65,11 @@ async def fetch_user_image(params: FunctionCallParams): append_to_context=True, function_name=params.function_name, tool_call_id=params.tool_call_id, + result_callback=params.result_callback, ), FrameDirection.UPSTREAM, ) - await params.result_callback(None) - - # Instead of None, it's possible to also provide a tool call answer to - # tell the LLM that we are grabbing the image to analyze. - # await params.result_callback({"result": "Image is being captured."}) - # We store functions so objects (e.g. SileroVADAnalyzer) don't get # instantiated. The function will be called when the desired transport gets diff --git a/examples/foundational/14d-function-calling-moondream-video.py b/examples/foundational/14d-function-calling-moondream-video.py index 0b10854ea..3e64d5bd8 100644 --- a/examples/foundational/14d-function-calling-moondream-video.py +++ b/examples/foundational/14d-function-calling-moondream-video.py @@ -57,7 +57,8 @@ async def fetch_user_image(params: FunctionCallParams): When called, this function pushes a UserImageRequestFrame upstream to the transport. As a result, the transport will request the user image and push a - UserImageRawFrame downstream. + UserImageRawFrame downstream. The result_callback will be invoked once the + image is retrieved and processed. """ user_id = params.arguments["user_id"] question = params.arguments["question"] @@ -65,7 +66,8 @@ async def fetch_user_image(params: FunctionCallParams): # Request a user image frame. In this case, we don't want the requested # image to be added to the context because we will process it with - # Moondream. Also associate it to the function call. + # Moondream. Also associate it to the function call. Pass the result_callback + # so it can be invoked when the image is actually retrieved. await params.llm.push_frame( UserImageRequestFrame( user_id=user_id, @@ -73,16 +75,11 @@ async def fetch_user_image(params: FunctionCallParams): append_to_context=False, function_name=params.function_name, tool_call_id=params.tool_call_id, + result_callback=params.result_callback, ), FrameDirection.UPSTREAM, ) - await params.result_callback(None) - - # Instead of None, it's possible to also provide a tool call answer to - # tell the LLM that we are grabbing the image to analyze. - # await params.result_callback({"result": "Image is being captured."}) - class MoondreamTextFrameWrapper(FrameProcessor): """Wraps Moondream-provided TextFrames with LLM response start/end frames. diff --git a/examples/foundational/14d-function-calling-openai-video.py b/examples/foundational/14d-function-calling-openai-video.py index 3afebe7bb..ec201cc3a 100644 --- a/examples/foundational/14d-function-calling-openai-video.py +++ b/examples/foundational/14d-function-calling-openai-video.py @@ -49,14 +49,16 @@ async def fetch_user_image(params: FunctionCallParams): When called, this function pushes a UserImageRequestFrame upstream to the transport. As a result, the transport will request the user image and push a UserImageRawFrame downstream which will be added to the context by the LLM - assistant aggregator. + assistant aggregator. The result_callback will be invoked once the image is + retrieved and processed. """ user_id = params.arguments["user_id"] question = params.arguments["question"] logger.debug(f"Requesting image with user_id={user_id}, question={question}") # Request a user image frame and indicate that it should be added to the - # context. Also associate it to the function call. + # context. Also associate it to the function call. Pass the result_callback + # so it can be invoked when the image is actually retrieved. await params.llm.push_frame( UserImageRequestFrame( user_id=user_id, @@ -64,16 +66,11 @@ async def fetch_user_image(params: FunctionCallParams): append_to_context=True, function_name=params.function_name, tool_call_id=params.tool_call_id, + result_callback=params.result_callback, ), FrameDirection.UPSTREAM, ) - await params.result_callback(None) - - # Instead of None, it's possible to also provide a tool call answer to - # tell the LLM that we are grabbing the image to analyze. - # await params.result_callback({"result": "Image is being captured."}) - # We store functions so objects (e.g. SileroVADAnalyzer) don't get # instantiated. The function will be called when the desired transport gets diff --git a/examples/foundational/14e-function-calling-google.py b/examples/foundational/14e-function-calling-google.py index 4e7abf997..56cdd53c1 100644 --- a/examples/foundational/14e-function-calling-google.py +++ b/examples/foundational/14e-function-calling-google.py @@ -58,14 +58,16 @@ async def get_image(params: FunctionCallParams): When called, this function pushes a UserImageRequestFrame upstream to the transport. As a result, the transport will request the user image and push a UserImageRawFrame downstream which will be added to the context by the LLM - assistant aggregator. + assistant aggregator. The result_callback will be invoked once the image is + retrieved and processed. """ user_id = params.arguments["user_id"] question = params.arguments["question"] logger.debug(f"Requesting image with user_id={user_id}, question={question}") # Request a user image frame and indicate that it should be added to the - # context. Also associate it to the function call. + # context. Also associate it to the function call. Pass the result_callback + # so it can be invoked when the image is actually retrieved. await params.llm.push_frame( UserImageRequestFrame( user_id=user_id, @@ -73,16 +75,11 @@ async def get_image(params: FunctionCallParams): append_to_context=True, function_name=params.function_name, tool_call_id=params.tool_call_id, + result_callback=params.result_callback, ), FrameDirection.UPSTREAM, ) - await params.result_callback(None) - - # Instead of None, it's possible to also provide a tool call answer to - # tell the LLM that we are grabbing the image to analyze. - # await params.result_callback({"result": "Image is being captured."}) - # We store functions so objects (e.g. SileroVADAnalyzer) don't get # instantiated. The function will be called when the desired transport gets diff --git a/examples/foundational/20d-persistent-context-gemini.py b/examples/foundational/20d-persistent-context-gemini.py index e0e2949a3..4b434c4c1 100644 --- a/examples/foundational/20d-persistent-context-gemini.py +++ b/examples/foundational/20d-persistent-context-gemini.py @@ -66,7 +66,8 @@ async def get_image(params: FunctionCallParams): logger.debug(f"Requesting image with user_id={user_id}, question={question}") # Request a user image frame and indicate that it should be added to the - # context. Also associate it to the function call. + # context. Also associate it to the function call. Pass the result_callback + # so it can be invoked when the image is actually retrieved. await params.llm.push_frame( UserImageRequestFrame( user_id=user_id, @@ -74,16 +75,11 @@ async def get_image(params: FunctionCallParams): append_to_context=True, function_name=params.function_name, tool_call_id=params.tool_call_id, + result_callback=params.result_callback, ), FrameDirection.UPSTREAM, ) - await params.result_callback(None) - - # Instead of None, it's possible to also provide a tool call answer to - # tell the LLM that we are grabbing the image to analyze. - # await params.result_callback({"result": "Image is being captured."}) - async def get_saved_conversation_filenames(params: FunctionCallParams): # Construct the full pattern including the BASE_FILENAME From 5543bc56f378b85df463418339ddf96b041de70c Mon Sep 17 00:00:00 2001 From: filipi87 Date: Wed, 28 Jan 2026 15:43:59 -0300 Subject: [PATCH 0279/1060] Add changelog files for PR #3571 Co-Authored-By: Claude Sonnet 4.5 --- changelog/3571.added.2.md | 1 + changelog/3571.added.md | 1 + changelog/3571.changed.md | 4 ++++ 3 files changed, 6 insertions(+) create mode 100644 changelog/3571.added.2.md create mode 100644 changelog/3571.added.md create mode 100644 changelog/3571.changed.md diff --git a/changelog/3571.added.2.md b/changelog/3571.added.2.md new file mode 100644 index 000000000..f9af8dde0 --- /dev/null +++ b/changelog/3571.added.2.md @@ -0,0 +1 @@ +- Added `function_call_timeout_secs` parameter to `LLMService` to configure timeout for deferred function calls (defaults to 10.0 seconds). diff --git a/changelog/3571.added.md b/changelog/3571.added.md new file mode 100644 index 000000000..927bbcbc4 --- /dev/null +++ b/changelog/3571.added.md @@ -0,0 +1 @@ +- Added `result_callback` parameter to `UserImageRequestFrame` to support deferred function call results. diff --git a/changelog/3571.changed.md b/changelog/3571.changed.md new file mode 100644 index 000000000..eb44cae0a --- /dev/null +++ b/changelog/3571.changed.md @@ -0,0 +1,4 @@ +- ⚠️ Changed function call handling to use timeout-based completion instead of immediate callback execution. + - Function calls that defer their results (e.g., `UserImageRequestFrame`) now use a timeout mechanism + - The `result_callback` is invoked automatically when the deferred operation completes or after timeout + - This change affects examples using `UserImageRequestFrame` - the `result_callback` should now be passed to the frame instead of being called immediately From 7456a0a55f209978825e1b14bf59341e2b859e3b Mon Sep 17 00:00:00 2001 From: mattie ruth backman Date: Thu, 22 Jan 2026 17:00:33 -0500 Subject: [PATCH 0280/1060] Fix the /start and /offer/api proxy endpoints for smallWebRTC to match pipecat cloud behavior WRT requestData --- src/pipecat/runner/run.py | 5 +++-- 1 file changed, 3 insertions(+), 2 deletions(-) diff --git a/src/pipecat/runner/run.py b/src/pipecat/runner/run.py index 6f7f1b53b..9a280d119 100644 --- a/src/pipecat/runner/run.py +++ b/src/pipecat/runner/run.py @@ -298,7 +298,7 @@ def _setup_webrtc_routes( # Store session info immediately in memory, replicate the behavior expected on Pipecat Cloud session_id = str(uuid.uuid4()) - active_sessions[session_id] = request_data + active_sessions[session_id] = request_data.get("body", {}) result: StartBotResult = {"sessionId": session_id} if request_data.get("enableDefaultIceServers"): @@ -331,7 +331,8 @@ def _setup_webrtc_routes( pc_id=request_data.get("pc_id"), restart_pc=request_data.get("restart_pc"), request_data=request_data.get("request_data") - or request_data.get("requestData"), + or request_data.get("requestData") + or active_session, ) return await offer(webrtc_request, background_tasks) elif request.method == HTTPMethod.PATCH.value: From eb1bf1e44680d7ce40d4f5096d4a4613c5d290ab Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Aleix=20Conchillo=20Flaqu=C3=A9?= Date: Wed, 28 Jan 2026 23:27:32 -0800 Subject: [PATCH 0281/1060] tts: rename PiperTTSService to PiperHttpTTSService --- examples/foundational/01-say-one-thing-piper.py | 4 ++-- src/pipecat/services/piper/tts.py | 7 ++++--- tests/test_piper_tts.py | 12 ++++++++---- 3 files changed, 14 insertions(+), 9 deletions(-) diff --git a/examples/foundational/01-say-one-thing-piper.py b/examples/foundational/01-say-one-thing-piper.py index 5aa975b31..f6700f886 100644 --- a/examples/foundational/01-say-one-thing-piper.py +++ b/examples/foundational/01-say-one-thing-piper.py @@ -16,7 +16,7 @@ from pipecat.pipeline.runner import PipelineRunner from pipecat.pipeline.task import PipelineTask from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport -from pipecat.services.piper.tts import PiperTTSService +from pipecat.services.piper.tts import PiperHttpTTSService from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams @@ -39,7 +39,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): # Create an HTTP session async with aiohttp.ClientSession() as session: - tts = PiperTTSService( + tts = PiperHttpTTSService( base_url=os.getenv("PIPER_BASE_URL"), aiohttp_session=session, sample_rate=24000 ) diff --git a/src/pipecat/services/piper/tts.py b/src/pipecat/services/piper/tts.py index ce47c885e..19d9720f0 100644 --- a/src/pipecat/services/piper/tts.py +++ b/src/pipecat/services/piper/tts.py @@ -21,9 +21,10 @@ from pipecat.services.tts_service import TTSService from pipecat.utils.tracing.service_decorators import traced_tts -# This assumes a running TTS service running: https://github.com/OHF-Voice/piper1-gpl/blob/main/docs/API_HTTP.md -class PiperTTSService(TTSService): - """Piper TTS service implementation. +# This assumes a running TTS service running: +# https://github.com/OHF-Voice/piper1-gpl/blob/main/docs/API_HTTP.md +class PiperHttpTTSService(TTSService): + """Piper HTTP TTS service implementation. Provides integration with Piper's HTTP TTS server for text-to-speech synthesis. Supports streaming audio generation with configurable sample diff --git a/tests/test_piper_tts.py b/tests/test_piper_tts.py index e52be2d91..8d877099c 100644 --- a/tests/test_piper_tts.py +++ b/tests/test_piper_tts.py @@ -21,7 +21,7 @@ from pipecat.frames.frames import ( TTSStoppedFrame, TTSTextFrame, ) -from pipecat.services.piper.tts import PiperTTSService +from pipecat.services.piper.tts import PiperHttpTTSService from pipecat.tests.utils import run_test @@ -67,8 +67,10 @@ async def test_run_piper_tts_success(aiohttp_client): base_url = str(client.make_url("")).rstrip("/") async with aiohttp.ClientSession() as session: - # Instantiate PiperTTSService with our mock server - tts_service = PiperTTSService(base_url=base_url, aiohttp_session=session, sample_rate=24000) + # Instantiate PiperHttpTTSService with our mock server + tts_service = PiperHttpTTSService( + base_url=base_url, aiohttp_session=session, sample_rate=24000 + ) frames_to_send = [ TTSSpeakFrame(text="Hello world."), @@ -117,7 +119,9 @@ async def test_run_piper_tts_error(aiohttp_client): base_url = str(client.make_url("")).rstrip("/") async with aiohttp.ClientSession() as session: - tts_service = PiperTTSService(base_url=base_url, aiohttp_session=session, sample_rate=24000) + tts_service = PiperHttpTTSService( + base_url=base_url, aiohttp_session=session, sample_rate=24000 + ) frames_to_send = [ TTSSpeakFrame(text="Error case."), From 875614ff7a43cf7820c8cec3c385683126f313e8 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Aleix=20Conchillo=20Flaqu=C3=A9?= Date: Wed, 28 Jan 2026 23:29:21 -0800 Subject: [PATCH 0282/1060] tts: add support for local PiperTTSService --- .github/workflows/coverage.yaml | 9 +- .github/workflows/tests.yaml | 9 +- .../foundational/07zi-interruptible-piper.py | 132 ++++++++++++++++++ pyproject.toml | 1 + scripts/evals/run-release-evals.py | 1 + src/pipecat/services/piper/tts.py | 122 +++++++++++++++- uv.lock | 27 +++- 7 files changed, 291 insertions(+), 10 deletions(-) create mode 100644 examples/foundational/07zi-interruptible-piper.py diff --git a/.github/workflows/coverage.yaml b/.github/workflows/coverage.yaml index faca8c03f..ae0cb9c57 100644 --- a/.github/workflows/coverage.yaml +++ b/.github/workflows/coverage.yaml @@ -33,7 +33,14 @@ jobs: - name: Install dependencies run: | - uv sync --group dev --extra anthropic --extra aws --extra google --extra langchain --extra livekit --extra websocket + uv sync --group dev \ + --extra anthropic \ + --extra aws \ + --extra google \ + --extra langchain \ + --extra livekit \ + --extra piper \ + --extra websocket - name: Run tests with coverage run: | diff --git a/.github/workflows/tests.yaml b/.github/workflows/tests.yaml index 459725da7..cb35a169c 100644 --- a/.github/workflows/tests.yaml +++ b/.github/workflows/tests.yaml @@ -37,7 +37,14 @@ jobs: - name: Install dependencies run: | - uv sync --group dev --extra anthropic --extra aws --extra google --extra langchain --extra livekit --extra websocket + uv sync --group dev \ + --extra anthropic \ + --extra aws \ + --extra google \ + --extra langchain \ + --extra livekit \ + --extra piper \ + --extra websocket - name: Test with pytest run: | diff --git a/examples/foundational/07zi-interruptible-piper.py b/examples/foundational/07zi-interruptible-piper.py new file mode 100644 index 000000000..67286741d --- /dev/null +++ b/examples/foundational/07zi-interruptible-piper.py @@ -0,0 +1,132 @@ +# +# Copyright (c) 2024-2026, Daily +# +# SPDX-License-Identifier: BSD 2-Clause License +# + +import os + +from dotenv import load_dotenv +from loguru import logger + +from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3 +from pipecat.audio.vad.silero import SileroVADAnalyzer +from pipecat.audio.vad.vad_analyzer import VADParams +from pipecat.frames.frames import LLMRunFrame +from pipecat.pipeline.pipeline import Pipeline +from pipecat.pipeline.runner import PipelineRunner +from pipecat.pipeline.task import PipelineParams, PipelineTask +from pipecat.processors.aggregators.llm_context import LLMContext +from pipecat.processors.aggregators.llm_response_universal import ( + LLMContextAggregatorPair, + LLMUserAggregatorParams, +) +from pipecat.runner.types import RunnerArguments +from pipecat.runner.utils import create_transport +from pipecat.services.deepgram.stt import DeepgramSTTService +from pipecat.services.openai.llm import OpenAILLMService +from pipecat.services.piper.tts import PiperTTSService +from pipecat.transports.base_transport import BaseTransport, TransportParams +from pipecat.transports.daily.transport import DailyParams +from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams +from pipecat.turns.user_stop import TurnAnalyzerUserTurnStopStrategy +from pipecat.turns.user_turn_strategies import UserTurnStrategies + +load_dotenv(override=True) + +# We store functions so objects (e.g. SileroVADAnalyzer) don't get +# instantiated. The function will be called when the desired transport gets +# selected. +transport_params = { + "daily": lambda: DailyParams( + audio_in_enabled=True, + audio_out_enabled=True, + vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), + ), + "twilio": lambda: FastAPIWebsocketParams( + audio_in_enabled=True, + audio_out_enabled=True, + vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), + ), + "webrtc": lambda: TransportParams( + audio_in_enabled=True, + audio_out_enabled=True, + vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), + ), +} + + +async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): + logger.info(f"Starting bot") + + stt = DeepgramSTTService(api_key=os.getenv("DEEPGRAM_API_KEY")) + + tts = PiperTTSService(voice_id="en_US-ryan-high") + + llm = OpenAILLMService(api_key=os.getenv("OPENAI_API_KEY")) + + messages = [ + { + "role": "system", + "content": "You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + }, + ] + + context = LLMContext(messages) + user_aggregator, assistant_aggregator = LLMContextAggregatorPair( + context, + user_params=LLMUserAggregatorParams( + user_turn_strategies=UserTurnStrategies( + stop=[TurnAnalyzerUserTurnStopStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3())] + ), + ), + ) + + pipeline = Pipeline( + [ + transport.input(), # Transport user input + stt, + user_aggregator, # User responses + llm, # LLM + tts, # TTS + transport.output(), # Transport bot output + assistant_aggregator, # Assistant spoken responses + ] + ) + + task = PipelineTask( + pipeline, + params=PipelineParams( + enable_metrics=True, + enable_usage_metrics=True, + ), + idle_timeout_secs=runner_args.pipeline_idle_timeout_secs, + ) + + @transport.event_handler("on_client_connected") + async def on_client_connected(transport, client): + logger.info(f"Client connected") + # Kick off the conversation. + messages.append({"role": "system", "content": "Please introduce yourself to the user."}) + await task.queue_frames([LLMRunFrame()]) + + @transport.event_handler("on_client_disconnected") + async def on_client_disconnected(transport, client): + logger.info(f"Client disconnected") + await task.cancel() + + runner = PipelineRunner(handle_sigint=runner_args.handle_sigint) + + await runner.run(task) + + +async def bot(runner_args: RunnerArguments): + """Main bot entry point compatible with Pipecat Cloud.""" + transport = await create_transport(runner_args, transport_params) + await run_bot(transport, runner_args) + + +if __name__ == "__main__": + from pipecat.runner.run import main + + main() diff --git a/pyproject.toml b/pyproject.toml index 339b498f6..098ad917b 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -95,6 +95,7 @@ rnnoise = [ "pyrnnoise~=0.4.1" ] openpipe = [ "openpipe>=4.50.0,<6" ] openrouter = [] perplexity = [] +piper = [ "piper-tts>=1.3.0,<2" ] playht = [ "pipecat-ai[websockets-base]" ] qwen = [] remote-smart-turn = [] diff --git a/scripts/evals/run-release-evals.py b/scripts/evals/run-release-evals.py index d4290be00..239012c36 100644 --- a/scripts/evals/run-release-evals.py +++ b/scripts/evals/run-release-evals.py @@ -138,6 +138,7 @@ TESTS_07 = [ ("07zf-interruptible-gradium.py", EVAL_SIMPLE_MATH), ("07zg-interruptible-camb.py", EVAL_SIMPLE_MATH), ("07zh-interruptible-hathora.py", EVAL_SIMPLE_MATH), + ("07zi-interruptible-piper.py", EVAL_SIMPLE_MATH), # Needs a local XTTS docker instance running. # ("07i-interruptible-xtts.py", EVAL_SIMPLE_MATH), # Needs a Krisp license. diff --git a/src/pipecat/services/piper/tts.py b/src/pipecat/services/piper/tts.py index 19d9720f0..ca809f469 100644 --- a/src/pipecat/services/piper/tts.py +++ b/src/pipecat/services/piper/tts.py @@ -6,11 +6,14 @@ """Piper TTS service implementation.""" -from typing import AsyncGenerator, Optional +import asyncio +from pathlib import Path +from typing import AsyncGenerator, AsyncIterator, Optional import aiohttp from loguru import logger +from pipecat.audio.utils import create_stream_resampler from pipecat.frames.frames import ( ErrorFrame, Frame, @@ -20,6 +23,123 @@ from pipecat.frames.frames import ( from pipecat.services.tts_service import TTSService from pipecat.utils.tracing.service_decorators import traced_tts +try: + from piper import PiperVoice + from piper.download_voices import download_voice +except ModuleNotFoundError as e: + logger.error(f"Exception: {e}") + logger.error("In order to use Piper, you need to `pip install pipecat-ai[piper]`.") + raise Exception(f"Missing module: {e}") + + +class PiperTTSService(TTSService): + """Piper TTS service implementation. + + Provides local text-to-speech synthesis using Piper voice models. Automatically + downloads voice models if not already present and resamples audio output to + match the configured sample rate. + """ + + def __init__( + self, + *, + voice_id: str, + download_dir: Optional[Path] = None, + force_redownload: bool = False, + use_cuda: bool = False, + **kwargs, + ): + """Initialize the Piper TTS service. + + Args: + voice_id: Piper voice model identifier (e.g. `en_US-ryan-high`). + download_dir: Directory for storing voice model files. Defaults to + the current working directory. + force_redownload: Re-download the voice model even if it already exists. + use_cuda: Use CUDA for GPU-accelerated inference. + **kwargs: Additional arguments passed to the parent `TTSService`. + """ + super().__init__(**kwargs) + + self._voice_id = voice_id + + self._resampler = create_stream_resampler() + + download_dir = download_dir or Path.cwd() + + model_file = f"{voice_id}.onnx" + model_path = Path(download_dir) / model_file + + if not model_path.exists(): + logger.debug(f"Downloading Piper '{voice_id}' model") + download_voice(voice_id, download_dir, force_redownload=force_redownload) + + logger.debug(f"Loading Piper '{voice_id}' model from {model_path}") + + self._voice = PiperVoice.load(model_path, use_cuda=use_cuda) + + logger.debug(f"Loaded Piper '{voice_id}' model") + + def can_generate_metrics(self) -> bool: + """Check if this service can generate processing metrics. + + Returns: + True, as Piper service supports metrics generation. + """ + return True + + @traced_tts + async def run_tts(self, text: str) -> AsyncGenerator[Frame, None]: + """Generate speech from text using Piper. + + Args: + text: The text to convert to speech. + + Yields: + Frame: Audio frames containing the synthesized speech and status frames. + """ + + def async_next(it): + try: + return next(it) + except StopIteration: + return None + + async def async_iterator(iterator, sample_rate: int) -> AsyncIterator[bytes]: + while True: + item = await asyncio.to_thread(async_next, iterator) + if item is None: + return + + audio_data = await self._resampler.resample( + item.audio_int16_bytes, sample_rate, self.sample_rate + ) + + yield audio_data + + logger.debug(f"{self}: Generating TTS [{text}]") + + try: + await self.start_ttfb_metrics() + + await self.start_tts_usage_metrics(text) + + yield TTSStartedFrame() + + async for frame in self._stream_audio_frames_from_iterator( + async_iterator(self._voice.synthesize(text), 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src/pipecat/services/tts_service.py | 42 ++++++++++++++++++++++++----- 1 file changed, 36 insertions(+), 6 deletions(-) diff --git a/src/pipecat/services/tts_service.py b/src/pipecat/services/tts_service.py index e04c4b649..37aad0372 100644 --- a/src/pipecat/services/tts_service.py +++ b/src/pipecat/services/tts_service.py @@ -24,6 +24,7 @@ from typing import ( from loguru import logger +from pipecat.audio.utils import create_stream_resampler from pipecat.frames.frames import ( AggregatedTextFrame, AggregationType, @@ -202,6 +203,8 @@ class TTSService(AIService): ) self._text_filters = [text_filter] + self._resampler = create_stream_resampler() + self._stop_frame_task: Optional[asyncio.Task] = None self._stop_frame_queue: asyncio.Queue = asyncio.Queue() @@ -505,12 +508,40 @@ class TTSService(AIService): await self._stop_frame_queue.put(frame) async def _stream_audio_frames_from_iterator( - self, iterator: AsyncIterator[bytes], *, strip_wav_header: bool + self, + iterator: AsyncIterator[bytes], + *, + strip_wav_header: bool = False, + in_sample_rate: Optional[int] = None, ) -> AsyncGenerator[Frame, None]: + """Stream audio frames from an async byte iterator with optional resampling. + + For WAV data, use `strip_wav_header=True` to strip the header and + auto-detect the source sample rate. For raw PCM data, pass + `in_sample_rate` directly. Audio is resampled to `self.sample_rate` when + the source rate differs. + + Args: + iterator: Async iterator yielding audio bytes. + strip_wav_header: Strip WAV header and parse source sample rate from it. + in_sample_rate: Source sample rate for raw PCM data. Overrides + WAV-detected rate if both are provided. + + """ buffer = bytearray() + source_sample_rate = in_sample_rate need_to_strip_wav_header = strip_wav_header + + async def maybe_resample(audio: bytes) -> bytes: + if source_sample_rate and source_sample_rate != self.sample_rate: + return await self._resampler.resample(audio, source_sample_rate, self.sample_rate) + return audio + async for chunk in iterator: if need_to_strip_wav_header and chunk.startswith(b"RIFF"): + # Parse sample rate from WAV header (bytes 24-28, little-endian uint32). + if len(chunk) >= 44 and source_sample_rate is None: + source_sample_rate = int.from_bytes(chunk[24:28], "little") chunk = chunk[44:] need_to_strip_wav_header = False @@ -520,19 +551,18 @@ class TTSService(AIService): # Round to nearest even number. aligned_length = len(buffer) & ~1 # 111111111...11110 if aligned_length > 0: - aligned_chunk = buffer[:aligned_length] + aligned_chunk = await maybe_resample(bytes(buffer[:aligned_length])) buffer = buffer[aligned_length:] # keep any leftover byte if len(aligned_chunk) > 0: - frame = TTSAudioRawFrame(bytes(aligned_chunk), self.sample_rate, 1) - yield frame + yield TTSAudioRawFrame(aligned_chunk, self.sample_rate, 1) if len(buffer) > 0: # Make sure we don't need an extra padding byte. if len(buffer) % 2 == 1: buffer.extend(b"\x00") - frame = TTSAudioRawFrame(bytes(buffer), self.sample_rate, 1) - yield frame + audio = await maybe_resample(bytes(buffer)) + yield TTSAudioRawFrame(audio, self.sample_rate, 1) async def _handle_interruption(self, frame: InterruptionFrame, direction: FrameDirection): self._processing_text = False From 5a85e27cc52393ba633b39095aec24308c2a9311 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Aleix=20Conchillo=20Flaqu=C3=A9?= Date: Wed, 28 Jan 2026 23:55:07 -0800 Subject: [PATCH 0284/1060] PiperHttpTTSService: allow passing a voice id --- src/pipecat/services/piper/tts.py | 41 +++++++++++++++---------------- 1 file changed, 20 insertions(+), 21 deletions(-) diff --git a/src/pipecat/services/piper/tts.py b/src/pipecat/services/piper/tts.py index ca809f469..1de1688b1 100644 --- a/src/pipecat/services/piper/tts.py +++ b/src/pipecat/services/piper/tts.py @@ -13,7 +13,6 @@ from typing import AsyncGenerator, AsyncIterator, Optional import aiohttp from loguru import logger -from pipecat.audio.utils import create_stream_resampler from pipecat.frames.frames import ( ErrorFrame, Frame, @@ -63,8 +62,6 @@ class PiperTTSService(TTSService): self._voice_id = voice_id - self._resampler = create_stream_resampler() - download_dir = download_dir or Path.cwd() model_file = f"{voice_id}.onnx" @@ -105,17 +102,12 @@ class PiperTTSService(TTSService): except StopIteration: return None - async def async_iterator(iterator, sample_rate: int) -> AsyncIterator[bytes]: + async def async_iterator(iterator) -> AsyncIterator[bytes]: while True: item = await asyncio.to_thread(async_next, iterator) if item is None: return - - audio_data = await self._resampler.resample( - item.audio_int16_bytes, sample_rate, self.sample_rate - ) - - yield audio_data + yield item.audio_int16_bytes logger.debug(f"{self}: Generating TTS [{text}]") @@ -127,8 +119,8 @@ class PiperTTSService(TTSService): yield TTSStartedFrame() async for frame in self._stream_audio_frames_from_iterator( - async_iterator(self._voice.synthesize(text), self._voice.config.sample_rate), - strip_wav_header=False, + async_iterator(self._voice.synthesize(text)), + in_sample_rate=self._voice.config.sample_rate, ): await self.stop_ttfb_metrics() yield frame @@ -143,6 +135,12 @@ class PiperTTSService(TTSService): # This assumes a running TTS service running: # https://github.com/OHF-Voice/piper1-gpl/blob/main/docs/API_HTTP.md +# +# Usage: +# +# $ uv pip install "piper-tts[http]" +# $ uv run python -m piper.http_server -m en_US-ryan-high +# class PiperHttpTTSService(TTSService): """Piper HTTP TTS service implementation. @@ -156,9 +154,7 @@ class PiperHttpTTSService(TTSService): *, base_url: str, aiohttp_session: aiohttp.ClientSession, - # When using Piper, the sample rate of the generated audio depends on the - # voice model being used. - sample_rate: Optional[int] = None, + voice_id: Optional[str] = None, **kwargs, ): """Initialize the Piper TTS service. @@ -166,10 +162,10 @@ class PiperHttpTTSService(TTSService): Args: base_url: Base URL for the Piper TTS HTTP server. aiohttp_session: aiohttp ClientSession for making HTTP requests. - sample_rate: Output sample rate. If None, uses the voice model's native rate. + voice_id: Piper voice model identifier (e.g. `en_US-ryan-high`). **kwargs: Additional arguments passed to the parent TTSService. """ - super().__init__(sample_rate=sample_rate, **kwargs) + super().__init__(**kwargs) if base_url.endswith("/"): logger.warning("Base URL ends with a slash, this is not allowed.") @@ -177,7 +173,7 @@ class PiperHttpTTSService(TTSService): self._base_url = base_url self._session = aiohttp_session - self._settings = {"base_url": base_url} + self._model_id = voice_id def can_generate_metrics(self) -> bool: """Check if this service can generate processing metrics. @@ -204,9 +200,12 @@ class PiperHttpTTSService(TTSService): try: await self.start_ttfb_metrics() - async with self._session.post( - self._base_url, json={"text": text}, headers=headers - ) as response: + data = { + "text": text, + "voice": self._model_id, + } + + async with self._session.post(self._base_url, json=data, headers=headers) as response: if response.status != 200: error = await response.text() yield ErrorFrame( From bd005870920a6598dfaa5d471dfa770619b2a49c Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Aleix=20Conchillo=20Flaqu=C3=A9?= Date: Wed, 28 Jan 2026 23:59:37 -0800 Subject: [PATCH 0285/1060] changelog: add files for 3585 --- changelog/3585.added.md | 1 + changelog/3585.fixed.md | 1 + 2 files changed, 2 insertions(+) create mode 100644 changelog/3585.added.md create mode 100644 changelog/3585.fixed.md diff --git a/changelog/3585.added.md b/changelog/3585.added.md new file mode 100644 index 000000000..7335d2c18 --- /dev/null +++ b/changelog/3585.added.md @@ -0,0 +1 @@ +- Added local `PiperTTSService` for offline text-to-speech using Piper voice models. The existing HTTP-based service has been renamed to `PiperHttpTTSService`. diff --git a/changelog/3585.fixed.md b/changelog/3585.fixed.md new file mode 100644 index 000000000..4993ed2f7 --- /dev/null +++ b/changelog/3585.fixed.md @@ -0,0 +1 @@ +- Fixed `PiperHttpTTSService` (olf `PiperTTSService`) to resample audio output based on the model's sample rate parsed from the WAV header. From 433c1b9b9241b9e8f31931f33c3cbef4ae1a1d6a Mon Sep 17 00:00:00 2001 From: Luke Payyapilli Date: Thu, 29 Jan 2026 09:07:06 -0500 Subject: [PATCH 0286/1060] add catch-all exception handler per review feedback --- src/pipecat/services/openai/base_llm.py | 2 ++ tests/test_openai_llm_timeout.py | 38 ++++++++++++++++++++++++- 2 files changed, 39 insertions(+), 1 deletion(-) diff --git a/src/pipecat/services/openai/base_llm.py b/src/pipecat/services/openai/base_llm.py index 8e0a45f0d..0243cc917 100644 --- a/src/pipecat/services/openai/base_llm.py +++ b/src/pipecat/services/openai/base_llm.py @@ -495,6 +495,8 @@ class BaseOpenAILLMService(LLMService): except httpx.TimeoutException as e: await self._call_event_handler("on_completion_timeout") await self.push_error(error_msg="LLM completion timeout", exception=e) + except Exception as e: + await self.push_error(error_msg=f"Error during completion: {e}", exception=e) finally: await self.stop_processing_metrics() await self.push_frame(LLMFullResponseEndFrame()) diff --git a/tests/test_openai_llm_timeout.py b/tests/test_openai_llm_timeout.py index df9483289..37e4523a9 100644 --- a/tests/test_openai_llm_timeout.py +++ b/tests/test_openai_llm_timeout.py @@ -4,7 +4,7 @@ # SPDX-License-Identifier: BSD 2-Clause License # -"""Unit tests for OpenAI LLM timeout handling.""" +"""Unit tests for OpenAI LLM error handling.""" from unittest.mock import AsyncMock, patch @@ -125,3 +125,39 @@ async def test_openai_llm_timeout_still_pushes_end_frame(): # Verify metrics were stopped service.stop_processing_metrics.assert_called_once() + + +@pytest.mark.asyncio +async def test_openai_llm_emits_error_frame_on_exception(): + """Test that OpenAI LLM service emits ErrorFrame when a general exception occurs. + + This enables proper error handling for API errors, rate limits, and other failures. + """ + with patch.object(OpenAILLMService, "create_client"): + service = OpenAILLMService(model="gpt-4") + service._client = AsyncMock() + + pushed_errors = [] + + async def mock_push_error(error_msg, exception=None): + pushed_errors.append({"error_msg": error_msg, "exception": exception}) + + service.push_frame = AsyncMock() + service.push_error = mock_push_error + service._call_event_handler = AsyncMock() + service._process_context = AsyncMock(side_effect=RuntimeError("API Error")) + service.start_processing_metrics = AsyncMock() + service.stop_processing_metrics = AsyncMock() + + context = LLMContext( + messages=[{"role": "user", "content": "Hello"}], + ) + frame = LLMContextFrame(context=context) + + await service.process_frame(frame, FrameDirection.DOWNSTREAM) + + # Verify push_error was called with correct message + assert len(pushed_errors) == 1 + assert "Error during completion" in pushed_errors[0]["error_msg"] + assert "API Error" in pushed_errors[0]["error_msg"] + assert isinstance(pushed_errors[0]["exception"], RuntimeError) From 6ab12626d64d4f963526ecbb22a49c1d52836f3e Mon Sep 17 00:00:00 2001 From: Mark Backman Date: Thu, 29 Jan 2026 09:47:19 -0500 Subject: [PATCH 0287/1060] GradiumSTTService now flushes pending transcripts on VAD stopped detection --- changelog/3587.changed.md | 1 + .../07zf-interruptible-gradium.py | 6 +- .../foundational/13l-gradium-transcription.py | 84 +++++++++++++++++++ src/pipecat/services/gradium/stt.py | 70 +++++++++++++++- 4 files changed, 159 insertions(+), 2 deletions(-) create mode 100644 changelog/3587.changed.md create mode 100644 examples/foundational/13l-gradium-transcription.py diff --git a/changelog/3587.changed.md b/changelog/3587.changed.md new file mode 100644 index 000000000..f3901c724 --- /dev/null +++ b/changelog/3587.changed.md @@ -0,0 +1 @@ +- `GradiumSTTService` now flushes pending transcriptions when VAD detects the user stopped speaking, improving response latency. diff --git a/examples/foundational/07zf-interruptible-gradium.py b/examples/foundational/07zf-interruptible-gradium.py index b6207d9f4..14275345f 100644 --- a/examples/foundational/07zf-interruptible-gradium.py +++ b/examples/foundational/07zf-interruptible-gradium.py @@ -59,11 +59,15 @@ transport_params = { async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): logger.info(f"Starting bot") - stt = GradiumSTTService(api_key=os.getenv("GRADIUM_API_KEY")) + stt = GradiumSTTService( + api_key=os.getenv("GRADIUM_API_KEY"), + api_endpoint_base_url="wss://us.api.gradium.ai/api/speech/asr", + ) tts = GradiumTTSService( api_key=os.getenv("GRADIUM_API_KEY"), voice_id="YTpq7expH9539ERJ", + url="wss://us.api.gradium.ai/api/speech/tts", ) llm = OpenAILLMService(api_key=os.getenv("OPENAI_API_KEY")) diff --git a/examples/foundational/13l-gradium-transcription.py b/examples/foundational/13l-gradium-transcription.py new file mode 100644 index 000000000..6803d21c7 --- /dev/null +++ b/examples/foundational/13l-gradium-transcription.py @@ -0,0 +1,84 @@ +# +# Copyright (c) 2024-2026, Daily +# +# SPDX-License-Identifier: BSD 2-Clause License +# + +import os + +from dotenv import load_dotenv +from loguru import logger + +from pipecat.frames.frames import Frame, TranscriptionFrame +from pipecat.pipeline.pipeline import Pipeline +from pipecat.pipeline.runner import PipelineRunner +from pipecat.pipeline.task import PipelineTask +from pipecat.processors.frame_processor import FrameDirection, FrameProcessor +from pipecat.runner.types import RunnerArguments +from pipecat.runner.utils import create_transport +from pipecat.services.gradium.stt import GradiumSTTService +from pipecat.transports.base_transport import BaseTransport, TransportParams +from pipecat.transports.daily.transport import DailyParams +from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams + +load_dotenv(override=True) + + +class TranscriptionLogger(FrameProcessor): + async def process_frame(self, frame: Frame, direction: FrameDirection): + await super().process_frame(frame, direction) + + if isinstance(frame, TranscriptionFrame): + print(f"Transcription: {frame.text}") + + # Push all frames through + await self.push_frame(frame, direction) + + +# We store functions so objects (e.g. SileroVADAnalyzer) don't get +# instantiated. The function will be called when the desired transport gets +# selected. +transport_params = { + "daily": lambda: DailyParams(audio_in_enabled=True), + "twilio": lambda: FastAPIWebsocketParams(audio_in_enabled=True), + "webrtc": lambda: TransportParams(audio_in_enabled=True), +} + + +async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): + logger.info(f"Starting bot") + + stt = GradiumSTTService( + api_key=os.getenv("GRADIUM_API_KEY"), + api_endpoint_base_url="wss://us.api.gradium.ai/api/speech/asr", + ) + + tl = TranscriptionLogger() + + pipeline = Pipeline([transport.input(), stt, tl]) + + task = PipelineTask( + pipeline, + idle_timeout_secs=runner_args.pipeline_idle_timeout_secs, + ) + + @transport.event_handler("on_client_disconnected") + async def on_client_disconnected(transport, client): + logger.info(f"Client disconnected") + await task.cancel() + + runner = PipelineRunner(handle_sigint=runner_args.handle_sigint) + + await runner.run(task) + + +async def bot(runner_args: RunnerArguments): + """Main bot entry point compatible with Pipecat Cloud.""" + transport = await create_transport(runner_args, transport_params) + await run_bot(transport, runner_args) + + +if __name__ == "__main__": + from pipecat.runner.run import main + + main() diff --git a/src/pipecat/services/gradium/stt.py b/src/pipecat/services/gradium/stt.py index 1c378ff9f..32c1d48c7 100644 --- a/src/pipecat/services/gradium/stt.py +++ b/src/pipecat/services/gradium/stt.py @@ -22,7 +22,10 @@ from pipecat.frames.frames import ( Frame, StartFrame, TranscriptionFrame, + VADUserStartedSpeakingFrame, + VADUserStoppedSpeakingFrame, ) +from pipecat.processors.frame_processor import FrameDirection from pipecat.services.stt_service import WebsocketSTTService from pipecat.transcriptions.language import Language from pipecat.utils.time import time_now_iso8601 @@ -76,6 +79,11 @@ class GradiumSTTService(WebsocketSTTService): self._chunk_size_ms = 80 self._chunk_size_bytes = 0 + # Set from the ready message when connecting to the service. + # These values are used for flushing transcription. + self._delay_in_frames = 0 + self._frame_size = 0 + def can_generate_metrics(self) -> bool: """Check if the service can generate metrics. @@ -112,6 +120,57 @@ class GradiumSTTService(WebsocketSTTService): await super().cancel(frame) await self._disconnect() + async def process_frame(self, frame: Frame, direction: FrameDirection): + """Process frames with VAD-specific handling. + + When VAD detects the user has stopped speaking, we flush the transcription + by sending silence frames. This makes the system more reactive by getting + the final transcription faster without closing the connection. + + Args: + frame: The frame to process. + direction: The direction of frame processing. + """ + await super().process_frame(frame, direction) + + if isinstance(frame, VADUserStartedSpeakingFrame): + await self.start_processing_metrics() + elif isinstance(frame, VADUserStoppedSpeakingFrame): + await self._flush_transcription() + + async def _flush_transcription(self): + """Flush the transcription by sending silence frames. + + When VAD detects the user stopped speaking, we send delay_in_frames + chunks of silence (zeros) to flush the remaining audio from the model's + buffer. This allows for faster turn-around without closing the connection. + + From Gradium docs: "feed in delay_in_frames chunks of silence (vectors + of zeros). If those are fed in faster than realtime, the API also has + a possibility to process them faster." + """ + if not self._websocket or self._websocket.state is not State.OPEN: + return + + if self._delay_in_frames <= 0: + logger.debug("No delay_in_frames set, skipping flush") + return + + # Create a silence chunk (zeros) of frame_size samples + # Each sample is 2 bytes (16-bit PCM) + silence_bytes = bytes(self._frame_size * 2) + silence_b64 = base64.b64encode(silence_bytes).decode("utf-8") + + logger.debug(f"Flushing Gradium STT with {self._delay_in_frames} silence frames") + + for _ in range(self._delay_in_frames): + msg = {"type": "audio", "audio": silence_b64} + try: + await self._websocket.send(json.dumps(msg)) + except Exception as e: + logger.warning(f"Failed to send silence frame: {e}") + break + async def run_stt(self, audio: bytes) -> AsyncGenerator[Frame, None]: """Process audio data for speech-to-text conversion. @@ -122,7 +181,6 @@ class GradiumSTTService(WebsocketSTTService): None (processing handled via WebSocket messages). """ self._audio_buffer.extend(audio) - await self.start_processing_metrics() while len(self._audio_buffer) >= self._chunk_size_bytes: chunk = bytes(self._audio_buffer[: self._chunk_size_bytes]) @@ -151,6 +209,9 @@ class GradiumSTTService(WebsocketSTTService): try: if self._websocket and self._websocket.state is State.OPEN: return + + logger.debug("Connecting to Gradium STT") + ws_url = self._api_endpoint_base_url headers = { "x-api-key": self._api_key, @@ -175,6 +236,11 @@ class GradiumSTTService(WebsocketSTTService): if ready_msg["type"] != "ready": raise Exception(f"unexpected first message type {ready_msg['type']}") + # Store delay_in_frames and frame_size for silence flushing + self._delay_in_frames = ready_msg.get("delay_in_frames", 0) + self._frame_size = ready_msg.get("frame_size", 1920) + logger.debug(f"Connected to Gradium STT") + except Exception as e: await self.push_error(error_msg=f"Unknown error occurred: {e}", exception=e) raise @@ -240,3 +306,5 @@ class GradiumSTTService(WebsocketSTTService): time_now_iso8601(), ) ) + await self._trace_transcription(text, is_final=True, language=None) + await self.stop_processing_metrics() From 31c7fbc5ba3b12323a1f9e46b00cd80224b5a723 Mon Sep 17 00:00:00 2001 From: Mark Backman Date: Thu, 29 Jan 2026 10:59:04 -0500 Subject: [PATCH 0288/1060] Add delay_in_frames and language support --- changelog/3587.changed.md | 4 +- .../07zf-interruptible-gradium.py | 4 + .../foundational/13l-gradium-transcription.py | 2 + src/pipecat/services/gradium/stt.py | 89 +++++++++++++++++-- 4 files changed, 92 insertions(+), 7 deletions(-) diff --git a/changelog/3587.changed.md b/changelog/3587.changed.md index f3901c724..94ccd7020 100644 --- a/changelog/3587.changed.md +++ b/changelog/3587.changed.md @@ -1 +1,3 @@ -- `GradiumSTTService` now flushes pending transcriptions when VAD detects the user stopped speaking, improving response latency. +- Updates to `GradiumSTTService`: + - Now flushes pending transcriptions when VAD detects the user stopped speaking, improving response latency. + - `GradiumSTTService` now supports `InputParams` for configuring `language` and `delay_in_frames` settings. diff --git a/examples/foundational/07zf-interruptible-gradium.py b/examples/foundational/07zf-interruptible-gradium.py index 14275345f..e4314ac3a 100644 --- a/examples/foundational/07zf-interruptible-gradium.py +++ b/examples/foundational/07zf-interruptible-gradium.py @@ -26,6 +26,7 @@ from pipecat.runner.utils import create_transport from pipecat.services.gradium.stt import GradiumSTTService from pipecat.services.gradium.tts import GradiumTTSService from pipecat.services.openai.llm import OpenAILLMService +from pipecat.transcriptions.language import Language from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams @@ -62,6 +63,9 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): stt = GradiumSTTService( api_key=os.getenv("GRADIUM_API_KEY"), api_endpoint_base_url="wss://us.api.gradium.ai/api/speech/asr", + params=GradiumSTTService.InputParams( + language=Language.EN, + ), ) tts = GradiumTTSService( diff --git a/examples/foundational/13l-gradium-transcription.py b/examples/foundational/13l-gradium-transcription.py index 6803d21c7..38709dff7 100644 --- a/examples/foundational/13l-gradium-transcription.py +++ b/examples/foundational/13l-gradium-transcription.py @@ -17,6 +17,7 @@ from pipecat.processors.frame_processor import FrameDirection, FrameProcessor from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport from pipecat.services.gradium.stt import GradiumSTTService +from pipecat.transcriptions.language import Language from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams @@ -51,6 +52,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): stt = GradiumSTTService( api_key=os.getenv("GRADIUM_API_KEY"), api_endpoint_base_url="wss://us.api.gradium.ai/api/speech/asr", + params=GradiumSTTService.InputParams(language=Language.EN, delay_in_frames=8), ) tl = TranscriptionLogger() diff --git a/src/pipecat/services/gradium/stt.py b/src/pipecat/services/gradium/stt.py index 32c1d48c7..2de899dc9 100644 --- a/src/pipecat/services/gradium/stt.py +++ b/src/pipecat/services/gradium/stt.py @@ -12,9 +12,10 @@ WebSocket API for streaming audio transcription. import base64 import json -from typing import AsyncGenerator +from typing import AsyncGenerator, Optional from loguru import logger +from pydantic import BaseModel from pipecat.frames.frames import ( CancelFrame, @@ -27,7 +28,7 @@ from pipecat.frames.frames import ( ) from pipecat.processors.frame_processor import FrameDirection from pipecat.services.stt_service import WebsocketSTTService -from pipecat.transcriptions.language import Language +from pipecat.transcriptions.language import Language, resolve_language from pipecat.utils.time import time_now_iso8601 from pipecat.utils.tracing.service_decorators import traced_stt @@ -42,6 +43,26 @@ except ModuleNotFoundError as e: SAMPLE_RATE = 24000 +def language_to_gradium_language(language: Language) -> Optional[str]: + """Convert a Language enum to Gradium's language code format. + + Args: + language: The Language enum value to convert. + + Returns: + The Gradium language code string or None if not supported. + """ + LANGUAGE_MAP = { + Language.DE: "de", + Language.EN: "en", + Language.ES: "es", + Language.FR: "fr", + Language.PT: "pt", + } + + return resolve_language(language, LANGUAGE_MAP, use_base_code=True) + + class GradiumSTTService(WebsocketSTTService): """Gradium real-time speech-to-text service. @@ -50,12 +71,29 @@ class GradiumSTTService(WebsocketSTTService): for audio processing and connection management. """ + class InputParams(BaseModel): + """Configuration parameters for Gradium STT API. + + Parameters: + language: Expected language of the audio (e.g., "en", "es", "fr"). + This helps ground the model to a specific language and improve + transcription quality. + delay_in_frames: Delay in audio frames (80ms each) before text is + generated. Higher delays allow more context but increase latency. + Allowed values: 7, 8, 10, 12, 14, 16, 20, 24, 36, 48. + Default is 10 (800ms). Lower values like 7-8 give faster response. + """ + + language: Optional[Language] = None + delay_in_frames: Optional[int] = None + def __init__( self, *, api_key: str, api_endpoint_base_url: str = "wss://eu.api.gradium.ai/api/speech/asr", - json_config: str | None = None, + params: Optional[InputParams] = None, + json_config: Optional[str] = None, **kwargs, ): """Initialize the Gradium STT service. @@ -63,14 +101,29 @@ class GradiumSTTService(WebsocketSTTService): Args: api_key: Gradium API key for authentication. api_endpoint_base_url: WebSocket endpoint URL. Defaults to Gradium's streaming endpoint. + params: Configuration parameters for language and delay settings. json_config: Optional JSON configuration string for additional model settings. + + .. deprecated:: 0.0.101 + Use `params` instead for type-safe configuration. + **kwargs: Additional arguments passed to parent STTService class. """ super().__init__(sample_rate=SAMPLE_RATE, **kwargs) + if json_config is not None: + import warnings + + warnings.warn( + "Parameter 'json_config' is deprecated and will be removed in a future version, use 'params' instead.", + DeprecationWarning, + stacklevel=2, + ) + self._api_key = api_key self._api_endpoint_base_url = api_endpoint_base_url self._websocket = None + self._params = params or GradiumSTTService.InputParams() self._json_config = json_config self._receive_task = None @@ -92,6 +145,17 @@ class GradiumSTTService(WebsocketSTTService): """ return True + async def set_language(self, language: Language): + """Set the recognition language and reconnect. + + Args: + language: The language to use for speech recognition. + """ + logger.info(f"Switching STT language to: [{language}]") + self._params.language = language + await self._disconnect() + await self._connect() + async def start(self, frame: StartFrame): """Start the speech-to-text service. @@ -226,8 +290,18 @@ class GradiumSTTService(WebsocketSTTService): "type": "setup", "input_format": "pcm", } - if self._json_config is not None: - setup_msg["json_config"] = self._json_config + # Build json_config: start with deprecated json_config, then override with params + json_config = {} + if self._json_config: + json_config = json.loads(self._json_config) + if self._params.language: + gradium_language = language_to_gradium_language(self._params.language) + if gradium_language: + json_config["language"] = gradium_language + if self._params.delay_in_frames: + json_config["delay_in_frames"] = self._params.delay_in_frames + if json_config: + setup_msg["json_config"] = json_config await self._websocket.send(json.dumps(setup_msg)) ready_msg = await self._websocket.recv() ready_msg = json.loads(ready_msg) @@ -239,7 +313,10 @@ class GradiumSTTService(WebsocketSTTService): # Store delay_in_frames and frame_size for silence flushing self._delay_in_frames = ready_msg.get("delay_in_frames", 0) self._frame_size = ready_msg.get("frame_size", 1920) - logger.debug(f"Connected to Gradium STT") + logger.debug( + f"Connected to Gradium STT (delay_in_frames={self._delay_in_frames}, " + f"frame_size={self._frame_size})" + ) except Exception as e: await self.push_error(error_msg=f"Unknown error occurred: {e}", exception=e) From bbb8b53d037d4fb84b24a095e35110adc2cb7ef4 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Aleix=20Conchillo=20Flaqu=C3=A9?= Date: Thu, 29 Jan 2026 10:08:25 -0800 Subject: [PATCH 0289/1060] runner: allow custom CLI arguments --- changelog/3590.added.md | 1 + examples/foundational/18-gstreamer-filesrc.py | 22 ++- src/pipecat/runner/run.py | 160 +++++++++--------- src/pipecat/runner/types.py | 2 + 4 files changed, 95 insertions(+), 90 deletions(-) create mode 100644 changelog/3590.added.md diff --git a/changelog/3590.added.md b/changelog/3590.added.md new file mode 100644 index 000000000..80e0c3dba --- /dev/null +++ b/changelog/3590.added.md @@ -0,0 +1 @@ +- `main()` in `pipecat.runner.run` now accepts an optional `argparse.ArgumentParser`, allowing bots to define custom CLI arguments accessible via `runner_args.cli_args`. diff --git a/examples/foundational/18-gstreamer-filesrc.py b/examples/foundational/18-gstreamer-filesrc.py index ceb400c94..56631c443 100644 --- a/examples/foundational/18-gstreamer-filesrc.py +++ b/examples/foundational/18-gstreamer-filesrc.py @@ -20,10 +20,6 @@ from pipecat.transports.daily.transport import DailyParams load_dotenv(override=True) -parser = argparse.ArgumentParser(description="Pipecat Video Streaming Bot") -parser.add_argument("-i", "--input", type=str, required=True, help="Input video file") -args = parser.parse_args() - # We store functions so objects (e.g. SileroVADAnalyzer) don't get # instantiated. The function will be called when the desired transport gets # selected. @@ -46,10 +42,10 @@ transport_params = { async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): - logger.info(f"Starting bot with video input: {args.input}") + logger.info(f"Starting bot with video input: {runner_args.cli_args.input}") gst = GStreamerPipelineSource( - pipeline=f"filesrc location={args.input}", + pipeline=f"filesrc location={runner_args.cli_args.input}", out_params=GStreamerPipelineSource.OutputParams( video_width=1280, video_height=720, @@ -68,6 +64,15 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): idle_timeout_secs=runner_args.pipeline_idle_timeout_secs, ) + @transport.event_handler("on_client_connected") + async def on_client_connected(transport, client): + logger.info(f"Client connected") + + @transport.event_handler("on_client_disconnected") + async def on_client_disconnected(transport, client): + logger.info(f"Client disconnected") + await task.cancel() + runner = PipelineRunner(handle_sigint=runner_args.handle_sigint) await runner.run(task) @@ -82,4 +87,7 @@ async def bot(runner_args: RunnerArguments): if __name__ == "__main__": from pipecat.runner.run import main - main() + parser = argparse.ArgumentParser(description="Pipecat Video Streaming Bot") + parser.add_argument("-i", "--input", type=str, required=True, help="Input video file") + + main(parser) diff --git a/src/pipecat/runner/run.py b/src/pipecat/runner/run.py index 9a280d119..76c870468 100644 --- a/src/pipecat/runner/run.py +++ b/src/pipecat/runner/run.py @@ -153,26 +153,18 @@ def _get_bot_module(): ) -async def _run_telephony_bot(websocket: WebSocket): +async def _run_telephony_bot(websocket: WebSocket, args: argparse.Namespace): """Run a bot for telephony transports.""" bot_module = _get_bot_module() # Just pass the WebSocket - let the bot handle parsing runner_args = WebSocketRunnerArguments(websocket=websocket) + runner_args.cli_args = args await bot_module.bot(runner_args) -def _create_server_app( - *, - transport_type: str, - host: str = "localhost", - proxy: str, - esp32_mode: bool = False, - whatsapp_enabled: bool = False, - folder: Optional[str] = None, - dialin_enabled: bool = False, -): +def _create_server_app(args: argparse.Namespace): """Create FastAPI app with transport-specific routes.""" app = FastAPI() @@ -185,23 +177,21 @@ def _create_server_app( ) # Set up transport-specific routes - if transport_type == "webrtc": - _setup_webrtc_routes(app, esp32_mode=esp32_mode, host=host, folder=folder) - if whatsapp_enabled: - _setup_whatsapp_routes(app) - elif transport_type == "daily": - _setup_daily_routes(app, dialin_enabled=dialin_enabled) - elif transport_type in TELEPHONY_TRANSPORTS: - _setup_telephony_routes(app, transport_type=transport_type, proxy=proxy) + if args.transport == "webrtc": + _setup_webrtc_routes(app, args) + if args.whatsapp: + _setup_whatsapp_routes(app, args) + elif args.transport == "daily": + _setup_daily_routes(app, args) + elif args.transport in TELEPHONY_TRANSPORTS: + _setup_telephony_routes(app, args) else: - logger.warning(f"Unknown transport type: {transport_type}") + logger.warning(f"Unknown transport type: {args.transport}") return app -def _setup_webrtc_routes( - app: FastAPI, *, esp32_mode: bool = False, host: str = "localhost", folder: Optional[str] = None -): +def _setup_webrtc_routes(app: FastAPI, args: argparse.Namespace): """Set up WebRTC-specific routes.""" try: from pipecat_ai_small_webrtc_prebuilt.frontend import SmallWebRTCPrebuiltUI @@ -241,11 +231,11 @@ def _setup_webrtc_routes( @app.get("/files/{filename:path}") async def download_file(filename: str): """Handle file downloads.""" - if not folder: + if not args.folder: logger.warning(f"Attempting to dowload {filename}, but downloads folder not setup.") return - file_path = Path(folder) / filename + file_path = Path(args.folder) / filename if not os.path.exists(file_path): raise HTTPException(404) @@ -255,7 +245,7 @@ def _setup_webrtc_routes( # Initialize the SmallWebRTC request handler small_webrtc_handler: SmallWebRTCRequestHandler = SmallWebRTCRequestHandler( - esp32_mode=esp32_mode, host=host + esp32_mode=args.esp32, host=args.host ) @app.post("/api/offer") @@ -269,6 +259,7 @@ def _setup_webrtc_routes( runner_args = SmallWebRTCRunnerArguments( webrtc_connection=connection, body=request.request_data ) + runner_args.cli_args = args background_tasks.add_task(bot_module.bot, runner_args) # Delegate handling to SmallWebRTCRequestHandler @@ -381,8 +372,8 @@ def _add_lifespan_to_app(app: FastAPI, new_lifespan): app.router.lifespan_context = new_lifespan -def _setup_whatsapp_routes(app: FastAPI): - """Set up WebRTC-specific routes.""" +def _setup_whatsapp_routes(app: FastAPI, args: argparse.Namespace): + """Set up WhatsApp-specific routes.""" WHATSAPP_APP_SECRET = os.getenv("WHATSAPP_APP_SECRET") WHATSAPP_PHONE_NUMBER_ID = os.getenv("WHATSAPP_PHONE_NUMBER_ID") WHATSAPP_TOKEN = os.getenv("WHATSAPP_TOKEN") @@ -484,6 +475,7 @@ def _setup_whatsapp_routes(app: FastAPI): """ bot_module = _get_bot_module() runner_args = SmallWebRTCRunnerArguments(webrtc_connection=connection) + runner_args.cli_args = args background_tasks.add_task(bot_module.bot, runner_args) try: @@ -529,13 +521,8 @@ def _setup_whatsapp_routes(app: FastAPI): _add_lifespan_to_app(app, whatsapp_lifespan) -def _setup_daily_routes(app: FastAPI, dialin_enabled: bool = False): - """Set up Daily-specific routes. - - Args: - app: FastAPI application instance - dialin_enabled: If True, adds /daily-dialin-webhook endpoint for PSTN dial-in handling - """ +def _setup_daily_routes(app: FastAPI, args: argparse.Namespace): + """Set up Daily-specific routes.""" @app.get("/") async def create_room_and_start_agent(): @@ -552,6 +539,7 @@ def _setup_daily_routes(app: FastAPI, dialin_enabled: bool = False): # Start the bot in the background with empty body for GET requests bot_module = _get_bot_module() runner_args = DailyRunnerArguments(room_url=room_url, token=token) + runner_args.cli_args = args asyncio.create_task(bot_module.bot(runner_args)) return RedirectResponse(room_url) @@ -635,12 +623,15 @@ def _setup_daily_routes(app: FastAPI, dialin_enabled: bool = False): else: runner_args = RunnerArguments(body=body) + # Update CLI args. + runner_args.cli_args = args + # Start the bot in the background asyncio.create_task(bot_module.bot(runner_args)) return result - if dialin_enabled: + if args.dialin: @app.post("/daily-dialin-webhook") async def handle_dialin_webhook(request: Request): @@ -737,6 +728,7 @@ def _setup_daily_routes(app: FastAPI, dialin_enabled: bool = False): token=room_config.token, body=request_body.model_dump(), ) + runner_args.cli_args = args asyncio.create_task(bot_module.bot(runner_args)) @@ -751,44 +743,44 @@ def _setup_daily_routes(app: FastAPI, dialin_enabled: bool = False): } -def _setup_telephony_routes(app: FastAPI, *, transport_type: str, proxy: str): +def _setup_telephony_routes(app: FastAPI, args: argparse.Namespace): """Set up telephony-specific routes.""" # XML response templates (Exotel doesn't use XML webhooks) XML_TEMPLATES = { "twilio": f""" - + """, "telnyx": f""" - + """, "plivo": f""" - wss://{proxy}/ws + wss://{args.proxy}/ws """, } @app.post("/") async def start_call(): """Handle telephony webhook and return XML response.""" - if transport_type == "exotel": + if args.transport == "exotel": # Exotel doesn't use POST webhooks - redirect to proper documentation logger.debug("POST Exotel endpoint - not used") return { "error": "Exotel doesn't use POST webhooks", - "websocket_url": f"wss://{proxy}/ws", + "websocket_url": f"wss://{args.proxy}/ws", "note": "Configure the WebSocket URL above in your Exotel App Bazaar Voicebot Applet", } else: - logger.debug(f"POST {transport_type.upper()} XML") - xml_content = XML_TEMPLATES.get(transport_type, "") + logger.debug(f"POST {args.transport.upper()} XML") + xml_content = XML_TEMPLATES.get(args.transport, "") return HTMLResponse(content=xml_content, media_type="application/xml") @app.websocket("/ws") @@ -796,15 +788,15 @@ def _setup_telephony_routes(app: FastAPI, *, transport_type: str, proxy: str): """Handle WebSocket connections for telephony.""" await websocket.accept() logger.debug("WebSocket connection accepted") - await _run_telephony_bot(websocket) + await _run_telephony_bot(websocket, args) @app.get("/") async def start_agent(): """Simple status endpoint for telephony transports.""" - return {"status": f"Bot started with {transport_type}"} + return {"status": f"Bot started with {args.transport}"} -async def _run_daily_direct(): +async def _run_daily_direct(args: argparse.Namespace): """Run Daily bot with direct connection (no FastAPI server).""" try: from pipecat.runner.daily import configure @@ -820,6 +812,7 @@ async def _run_daily_direct(): # Direct connections have no request body, so use empty dict runner_args = DailyRunnerArguments(room_url=room_url, token=token) runner_args.handle_sigint = True + runner_args.cli_args = args # Get the bot module and run it directly bot_module = _get_bot_module() @@ -867,29 +860,38 @@ def runner_port() -> int: return RUNNER_PORT -def main(): +def main(parser: Optional[argparse.ArgumentParser] = None): """Start the Pipecat development runner. Parses command-line arguments and starts a FastAPI server configured - for the specified transport type. The runner will discover and run - any bot() function found in the current directory. + for the specified transport type. + + The runner discovers and runs any ``bot(runner_args)`` function found in the + calling module. Command-line arguments: + - --host: Server host address (default: localhost) 879 + - --port: Server port (default: 7860) + - -t/--transport: Transport type (daily, webrtc, twilio, telnyx, plivo, exotel) + - -x/--proxy: Public proxy hostname for telephony webhooks + - -d/--direct: Connect directly to Daily room (automatically sets transport to daily) + - -f/--folder: Path to downloads folder + - --dialin: Enable Daily PSTN dial-in webhook handling (requires Daily transport) + - --esp32: Enable SDP munging for ESP32 compatibility (requires --host with IP address) + - --whatsapp: Ensure requried WhatsApp environment variables are present + - -v/--verbose: Increase logging verbosity Args: - --host: Server host address (default: localhost) - --port: Server port (default: 7860) - -t/--transport: Transport type (daily, webrtc, twilio, telnyx, plivo, exotel) - -x/--proxy: Public proxy hostname for telephony webhooks - --esp32: Enable SDP munging for ESP32 compatibility (requires --host with IP address) - -d/--direct: Connect directly to Daily room (automatically sets transport to daily) - -v/--verbose: Increase logging verbosity + parser: Optional custom argument parser. If provided, default runner + arguments are added to it so bots can define their own CLI + arguments. Custom arguments should not conflict with the default + ones. Custom args are accessible via `runner_args.cli_args`. - The bot file must contain a `bot(runner_args)` function as the entry point. """ global RUNNER_DOWNLOADS_FOLDER, RUNNER_HOST, RUNNER_PORT - parser = argparse.ArgumentParser(description="Pipecat Development Runner") + if not parser: + parser = argparse.ArgumentParser(description="Pipecat Development Runner") parser.add_argument("--host", type=str, default=RUNNER_HOST, help="Host address") parser.add_argument("--port", type=int, default=RUNNER_PORT, help="Port number") parser.add_argument( @@ -900,13 +902,7 @@ def main(): default="webrtc", help="Transport type", ) - parser.add_argument("--proxy", "-x", help="Public proxy host name") - parser.add_argument( - "--esp32", - action="store_true", - default=False, - help="Enable SDP munging for ESP32 compatibility (requires --host with IP address)", - ) + parser.add_argument("-x", "--proxy", help="Public proxy host name") parser.add_argument( "-d", "--direct", @@ -916,13 +912,7 @@ def main(): ) parser.add_argument("-f", "--folder", type=str, help="Path to downloads folder") parser.add_argument( - "--verbose", "-v", action="count", default=0, help="Increase logging verbosity" - ) - parser.add_argument( - "--whatsapp", - action="store_true", - default=False, - help="Ensure requried WhatsApp environment variables are present", + "-v", "--verbose", action="count", default=0, help="Increase logging verbosity" ) parser.add_argument( "--dialin", @@ -930,6 +920,18 @@ def main(): default=False, help="Enable Daily PSTN dial-in webhook handling (requires Daily transport)", ) + parser.add_argument( + "--esp32", + action="store_true", + default=False, + help="Enable SDP munging for ESP32 compatibility (requires --host with IP address)", + ) + parser.add_argument( + "--whatsapp", + action="store_true", + default=False, + help="Ensure requried WhatsApp environment variables are present", + ) args = parser.parse_args() @@ -965,7 +967,7 @@ def main(): print() # Run direct Daily connection - asyncio.run(_run_daily_direct()) + asyncio.run(_run_daily_direct(args)) return # Print startup message for server-based transports @@ -996,15 +998,7 @@ def main(): RUNNER_PORT = args.port # Create the app with transport-specific setup - app = _create_server_app( - transport_type=args.transport, - host=args.host, - proxy=args.proxy, - esp32_mode=args.esp32, - whatsapp_enabled=args.whatsapp, - folder=args.folder, - dialin_enabled=args.dialin, - ) + app = _create_server_app(args) # Run the server uvicorn.run(app, host=args.host, port=args.port) diff --git a/src/pipecat/runner/types.py b/src/pipecat/runner/types.py index 0e997b963..e48f10a08 100644 --- a/src/pipecat/runner/types.py +++ b/src/pipecat/runner/types.py @@ -10,6 +10,7 @@ These types are used by the development runner to pass transport-specific information to bot functions. """ +import argparse from dataclasses import dataclass, field from typing import Any, Dict, Optional @@ -64,6 +65,7 @@ class RunnerArguments: handle_sigterm: bool = field(init=False, kw_only=True) pipeline_idle_timeout_secs: int = field(init=False, kw_only=True) body: Optional[Any] = field(default_factory=dict, kw_only=True) + cli_args: Optional[argparse.Namespace] = field(default=None, init=False, kw_only=True) def __post_init__(self): self.handle_sigint = False From 7eabaaa0efb6f9bb6b09f15c3ded4edc6101003e Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Aleix=20Conchillo=20Flaqu=C3=A9?= Date: Thu, 29 Jan 2026 11:42:49 -0800 Subject: [PATCH 0290/1060] FrameProcessors: do not deepcopy fields when broadcasting frames --- src/pipecat/processors/frame_processor.py | 20 ++++++++++---------- tests/test_frame_processor.py | 21 +++++++++------------ 2 files changed, 19 insertions(+), 22 deletions(-) diff --git a/src/pipecat/processors/frame_processor.py b/src/pipecat/processors/frame_processor.py index 1ad57e0d6..740c19ae6 100644 --- a/src/pipecat/processors/frame_processor.py +++ b/src/pipecat/processors/frame_processor.py @@ -14,7 +14,6 @@ management, and frame flow control mechanisms. import asyncio import dataclasses import traceback -from copy import deepcopy from dataclasses import dataclass from enum import Enum from typing import ( @@ -775,20 +774,21 @@ class FrameProcessor(BaseObject): """Broadcasts a frame of the specified class upstream and downstream. This method creates two instances of the given frame class using the - provided keyword arguments and pushes them upstream and downstream. + provided keyword arguments (without deep-copying them) and pushes them + upstream and downstream. Args: frame_cls: The class of the frame to be broadcasted. **kwargs: Keyword arguments to be passed to the frame's constructor. """ - await self.push_frame(frame_cls(**deepcopy(kwargs))) - await self.push_frame(frame_cls(**deepcopy(kwargs)), FrameDirection.UPSTREAM) + await self.push_frame(frame_cls(**kwargs)) + await self.push_frame(frame_cls(**kwargs), FrameDirection.UPSTREAM) async def broadcast_frame_instance(self, frame: Frame): """Broadcasts a frame instance upstream and downstream. - This method creates two new frame instances copying all fields from the - original frame except `id` and `name`, which get fresh values. + This method creates two new frame instances shallow-copying all fields + from the original frame except `id` and `name`, which get fresh values. Args: frame: The frame instance to broadcast. @@ -806,13 +806,13 @@ class FrameProcessor(BaseObject): if not f.init and f.name not in ("id", "name") } - new_frame = frame_cls(**deepcopy(init_fields)) - for k, v in deepcopy(extra_fields).items(): + new_frame = frame_cls(**init_fields) + for k, v in extra_fields.items(): setattr(new_frame, k, v) await self.push_frame(new_frame) - new_frame = frame_cls(**deepcopy(init_fields)) - for k, v in deepcopy(extra_fields).items(): + new_frame = frame_cls(**init_fields) + for k, v in extra_fields.items(): setattr(new_frame, k, v) await self.push_frame(new_frame, FrameDirection.UPSTREAM) diff --git a/tests/test_frame_processor.py b/tests/test_frame_processor.py index 3f8c8ae70..2df35a10e 100644 --- a/tests/test_frame_processor.py +++ b/tests/test_frame_processor.py @@ -259,11 +259,11 @@ class TestFrameProcessor(unittest.IsolatedAsyncioTestCase): self.assertEqual(up_frame.value, 42) self.assertEqual(up_frame.items, ["a", "b"]) - # Verify the items lists are separate instances (not shared references) - self.assertIsNot(down_frame.items, up_frame.items) + # Verify the items lists are shared references (no deep copy) + self.assertIs(down_frame.items, up_frame.items) async def test_broadcast_frame_instance(self): - """Test that broadcast_frame_instance copies all fields except id and name.""" + """Test that broadcast_frame_instance shallow-copies all fields except id and name.""" downstream_frames: List[Frame] = [] upstream_frames: List[Frame] = [] original_frame: List[Frame] = [] @@ -298,7 +298,7 @@ class TestFrameProcessor(unittest.IsolatedAsyncioTestCase): pipeline = Pipeline([up_capture, broadcaster, down_capture]) - # Create a frame with mutable fields to test deep copying + # Create a frame with mutable fields to test shallow copying test_frame = BroadcastTestFrame(text="test", value=99, items=["x", "y", "z"]) frames_to_send = [test_frame] @@ -342,11 +342,8 @@ class TestFrameProcessor(unittest.IsolatedAsyncioTestCase): self.assertEqual(up_frame.pts, 12345) self.assertEqual(up_frame.metadata, {"key": "value", "nested": {"a": 1}}) - # Verify mutable fields are deep copied (not shared references) - self.assertIsNot(down_frame.items, orig.items) - self.assertIsNot(up_frame.items, orig.items) - self.assertIsNot(down_frame.items, up_frame.items) - self.assertIsNot(down_frame.metadata, orig.metadata) - self.assertIsNot(up_frame.metadata, orig.metadata) - self.assertIsNot(down_frame.metadata, up_frame.metadata) - self.assertIsNot(down_frame.metadata["nested"], up_frame.metadata["nested"]) + # Verify mutable fields are shallow-copied (shared references) + self.assertIs(down_frame.items, orig.items) + self.assertIs(up_frame.items, orig.items) + self.assertIs(down_frame.metadata, orig.metadata) + self.assertIs(up_frame.metadata, orig.metadata) From 0423acd8a039030afcaf180163491b6e4c0ade7b Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Aleix=20Conchillo=20Flaqu=C3=A9?= Date: Thu, 29 Jan 2026 11:43:13 -0800 Subject: [PATCH 0291/1060] STTService: just clear buffer before running run_stt() --- src/pipecat/services/stt_service.py | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/src/pipecat/services/stt_service.py b/src/pipecat/services/stt_service.py index 44c7af3b4..21422d6ef 100644 --- a/src/pipecat/services/stt_service.py +++ b/src/pipecat/services/stt_service.py @@ -497,11 +497,11 @@ class SegmentedSTTService(STTService): wav.close() content.seek(0) - await self.process_generator(self.run_stt(content.read())) - # Start clean. self._audio_buffer.clear() + await self.process_generator(self.run_stt(content.read())) + async def process_audio_frame(self, frame: AudioRawFrame, direction: FrameDirection): """Process audio frames by buffering them for segmented transcription. From 253a1d1114b71b483f818f49f29ce224e0abc627 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Aleix=20Conchillo=20Flaqu=C3=A9?= Date: Thu, 29 Jan 2026 13:08:51 -0800 Subject: [PATCH 0292/1060] UserTurnController: reset user turn timeout with interim transcriptions --- changelog/3594.fixed.md | 1 + src/pipecat/turns/user_turn_controller.py | 7 ++++--- 2 files changed, 5 insertions(+), 3 deletions(-) create mode 100644 changelog/3594.fixed.md diff --git a/changelog/3594.fixed.md b/changelog/3594.fixed.md new file mode 100644 index 000000000..1c47ff490 --- /dev/null +++ b/changelog/3594.fixed.md @@ -0,0 +1 @@ +- Fixed `UserTurnController` to reset user turn timeout when interim transcriptions are received. diff --git a/src/pipecat/turns/user_turn_controller.py b/src/pipecat/turns/user_turn_controller.py index 05cb46988..adaafd298 100644 --- a/src/pipecat/turns/user_turn_controller.py +++ b/src/pipecat/turns/user_turn_controller.py @@ -11,6 +11,7 @@ from typing import Optional, Type from pipecat.frames.frames import ( Frame, + InterimTranscriptionFrame, TranscriptionFrame, UserStartedSpeakingFrame, UserStoppedSpeakingFrame, @@ -156,7 +157,7 @@ class UserTurnController(BaseObject): await self._handle_vad_user_started_speaking(frame) elif isinstance(frame, VADUserStoppedSpeakingFrame): await self._handle_vad_user_stopped_speaking(frame) - elif isinstance(frame, TranscriptionFrame): + elif isinstance(frame, (TranscriptionFrame, InterimTranscriptionFrame)): await self._handle_transcription(frame) for strategy in self._user_turn_strategies.start or []: @@ -209,8 +210,8 @@ class UserTurnController(BaseObject): # The user stopped talking, let's reset the user turn timeout. self._user_turn_stop_timeout_event.set() - async def _handle_transcription(self, frame: TranscriptionFrame): - # We have creceived a transcription, let's reset the user turn timeout. + async def _handle_transcription(self, frame: TranscriptionFrame | InterimTranscriptionFrame): + # We have received a transcription, let's reset the user turn timeout. self._user_turn_stop_timeout_event.set() async def _on_push_frame( From 18045582a921fdb924e825e6fb7bc81244d41c14 Mon Sep 17 00:00:00 2001 From: dhruvladia-sarvam Date: Fri, 30 Jan 2026 15:53:06 +0530 Subject: [PATCH 0293/1060] ASR and TTS v3 update --- src/pipecat/services/sarvam/stt.py | 107 ++++--- src/pipecat/services/sarvam/tts.py | 486 ++++++++++++++++++++++++----- 2 files changed, 463 insertions(+), 130 deletions(-) diff --git a/src/pipecat/services/sarvam/stt.py b/src/pipecat/services/sarvam/stt.py index 164ad289e..b825c0d78 100644 --- a/src/pipecat/services/sarvam/stt.py +++ b/src/pipecat/services/sarvam/stt.py @@ -6,7 +6,7 @@ can handle multiple audio formats for Indian language speech recognition. """ import base64 -from typing import Optional +from typing import Literal, Optional from loguru import logger from pydantic import BaseModel @@ -78,15 +78,19 @@ class SarvamSTTService(STTService): """Configuration parameters for Sarvam STT service. Parameters: - language: Target language for transcription. Defaults to None (required for saarika models). - prompt: Optional prompt to guide translation style/context for STT-Translate models. - Only applicable to saaras (STT-Translate) models. Defaults to None. + language: Target language for transcription. Required for all models. + Defaults to "unknown" for saarika models and "en-IN" for saaras:v3. + prompt: Optional prompt to guide transcription style/context. + Only applicable to saaras:v3 models. Defaults to None. + mode: Mode of operation for saaras:v3 models. Options: transcribe, translate, + verbatim, translit, codemix. Defaults to "transcribe" for saaras:v3. vad_signals: Enable VAD signals in response. Defaults to None. high_vad_sensitivity: Enable high VAD (Voice Activity Detection) sensitivity. Defaults to None. """ language: Optional[Language] = None prompt: Optional[str] = None + mode: Optional[Literal["transcribe", "translate", "verbatim", "translit", "codemix"]] = None vad_signals: bool = None high_vad_sensitivity: bool = None @@ -97,6 +101,9 @@ class SarvamSTTService(STTService): model: str = "saarika:v2.5", sample_rate: Optional[int] = None, input_audio_codec: str = "wav", + mode: Optional[ + Literal["transcribe", "translate", "verbatim", "translit", "codemix"] + ] = None, params: Optional[InputParams] = None, **kwargs, ): @@ -104,28 +111,36 @@ class SarvamSTTService(STTService): Args: api_key: Sarvam API key for authentication. - model: Sarvam model to use for transcription. + model: Sarvam model to use for transcription. Allowed: "saarika:v2.5", "saaras:v3". sample_rate: Audio sample rate. Defaults to 16000 if not specified. input_audio_codec: Audio codec/format of the input file. Defaults to "wav". + mode: Mode of operation for saaras:v3 models. Options: transcribe, translate, + verbatim, translit, codemix. Defaults to "transcribe" for saaras:v3. params: Configuration parameters for Sarvam STT service. **kwargs: Additional arguments passed to the parent STTService. """ params = params or SarvamSTTService.InputParams() + # Allow mode to be passed directly or via params + if mode is not None and params.mode is None: + params = params.model_copy(update={"mode": mode}) - # Validate that saaras models don't accept language parameter - if "saaras" in model.lower(): - if params.language is not None: - raise ValueError( - f"Model '{model}' does not accept language parameter. " - "STT-Translate models auto-detect language." - ) + # Validate allowed models + allowed_models = {"saarika:v2.5", "saaras:v3"} + if model not in allowed_models: + allowed_models_list = ", ".join(sorted(allowed_models)) + raise ValueError(f"Unsupported model '{model}'. Allowed values: {allowed_models_list}.") # Validate that saarika models don't accept prompt parameter if "saarika" in model.lower(): if params.prompt is not None: raise ValueError( f"Model '{model}' does not accept prompt parameter. " - "Prompts are only supported for STT-Translate models" + "Prompts are only supported for saaras:v3 model." + ) + if params.mode is not None: + raise ValueError( + f"Model '{model}' does not accept mode parameter. " + "Mode is only supported for saaras:v3 model." ) super().__init__(sample_rate=sample_rate, **kwargs) @@ -133,14 +148,21 @@ class SarvamSTTService(STTService): self.set_model_name(model) self._api_key = api_key self._language_code: Optional[Language] = params.language - # For saarika models, default to "unknown" if language is not provided + # Set language string - both models require language_code if params.language: self._language_string = language_to_sarvam_language(params.language) elif "saarika" in model.lower(): self._language_string = "unknown" + elif model.lower() == "saaras:v3": + self._language_string = "en-IN" else: self._language_string = None self._prompt = params.prompt + # Set mode for saaras:v3, default to "transcribe" + if model.lower() == "saaras:v3": + self._mode = params.mode if params.mode is not None else "transcribe" + else: + self._mode = None # Store connection parameters self._vad_signals = params.vad_signals @@ -204,13 +226,6 @@ class SarvamSTTService(STTService): Args: language: The language to use for speech recognition. """ - # saaras models do not accept a language parameter - if "saaras" in self.model_name.lower(): - raise ValueError( - f"Model '{self.model_name}' (saaras) does not accept language parameter. " - "saaras models auto-detect language." - ) - logger.info(f"Switching STT language to: [{language}]") self._language_code = language self._language_string = language_to_sarvam_language(language) @@ -218,24 +233,24 @@ class SarvamSTTService(STTService): await self._connect() async def set_prompt(self, prompt: Optional[str]): - """Set the translation prompt and reconnect. + """Set the transcription prompt and reconnect. Args: - prompt: Prompt text to guide translation style/context. + prompt: Prompt text to guide transcription style/context. Pass None to clear/disable prompt. - Only applicable to STT-Translate models, not STT models. + Only applicable to saaras:v3 model. """ # saarika models do not accept prompt parameter if "saarika" in self.model_name.lower(): if prompt is not None: raise ValueError( f"Model '{self.model_name}' does not accept prompt parameter. " - "Prompts are only supported for STT-Translate models." + "Prompts are only supported for saaras:v3 model." ) # If prompt is None and it's saarika, just silently return (no-op) return - logger.info("Updating STT-Translate prompt.") + logger.info("Updating saaras:v3 prompt.") self._prompt = prompt await self._disconnect() await self._connect() @@ -299,13 +314,8 @@ class SarvamSTTService(STTService): "sample_rate": self.sample_rate, } - # Use appropriate method based on service type - if "saarika" in self.model_name.lower(): - # STT service - await self._socket_client.transcribe(**method_kwargs) - else: - # STT-Translate service - auto-detects input language and returns translated text - await self._socket_client.translate(**method_kwargs) + # Both saarika and saaras:v3 use the same speech_to_text_streaming endpoint + await self._socket_client.transcribe(**method_kwargs) except Exception as e: yield ErrorFrame(error=f"Error sending audio to Sarvam: {e}", exception=e) @@ -321,15 +331,19 @@ class SarvamSTTService(STTService): vad_signals_str = "true" if self._vad_signals else "false" high_vad_sensitivity_str = "true" if self._high_vad_sensitivity else "false" - # Build common connection parameters + # Build connection parameters - both models use speech_to_text_streaming connect_kwargs = { "model": self.model_name, + "language_code": self._language_string, # Required for both models "vad_signals": vad_signals_str, "high_vad_sensitivity": high_vad_sensitivity_str, - "input_audio_codec": self._input_audio_codec, "sample_rate": str(self.sample_rate), } + # Add mode for saaras:v3 only + if self.model_name.lower() == "saaras:v3" and self._mode is not None: + connect_kwargs["mode"] = self._mode + def _connect_with_sdk_headers(connect_fn, **kwargs): # Different SDK versions may use different kwarg names. for header_kw in ("headers", "additional_headers", "extra_headers"): @@ -339,26 +353,17 @@ class SarvamSTTService(STTService): pass return connect_fn(**kwargs) - # Choose the appropriate service based on model - if "saarika" in self.model_name.lower(): - # STT service - requires language_code - connect_kwargs["language_code"] = self._language_string - self._websocket_context = _connect_with_sdk_headers( - self._sarvam_client.speech_to_text_streaming.connect, - **connect_kwargs, - ) - else: - # STT-Translate service - auto-detects input language and returns translated text - self._websocket_context = _connect_with_sdk_headers( - self._sarvam_client.speech_to_text_translate_streaming.connect, - **connect_kwargs, - ) + # Both saarika and saaras:v3 use the same speech_to_text_streaming endpoint + self._websocket_context = _connect_with_sdk_headers( + self._sarvam_client.speech_to_text_streaming.connect, + **connect_kwargs, + ) # Enter the async context manager self._socket_client = await self._websocket_context.__aenter__() - # Set prompt if provided (only for STT-Translate models, after connection) - if self._prompt is not None and "saaras" in self.model_name.lower(): + # Set prompt if provided (only for saaras:v3 model, after connection) + if self._prompt is not None and self.model_name.lower() == "saaras:v3": await self._socket_client.set_prompt(self._prompt) # Register event handler for incoming messages diff --git a/src/pipecat/services/sarvam/tts.py b/src/pipecat/services/sarvam/tts.py index cef228b84..bd63558a8 100644 --- a/src/pipecat/services/sarvam/tts.py +++ b/src/pipecat/services/sarvam/tts.py @@ -4,12 +4,35 @@ # SPDX-License-Identifier: BSD 2-Clause License # -"""Sarvam AI text-to-speech service implementation.""" +"""Sarvam AI text-to-speech service implementation. + +This module provides TTS services using Sarvam AI's API with support for multiple +Indian languages and two model variants: + +**Model Variants:** + +- **bulbul:v2** (default): Standard TTS model + - Supports: pitch, loudness, pace (0.3-3.0) + - Default sample rate: 22050 Hz + - Speakers: anushka (default), abhilash, manisha, vidya, arya, karun, hitesh + +- **bulbul:v3-beta**: Advanced TTS model with temperature control + - Does NOT support: pitch, loudness + - Supports: pace (0.5-2.0), temperature (0.01-1.0) + - Default sample rate: 24000 Hz + - Preprocessing is always enabled + - Speakers: aditya (default), ritu, priya, neha, rahul, pooja, rohan, simran, + kavya, amit, dev, ishita, shreya, ratan, varun, manan, sumit, roopa, kabir, + aayan, shubh, ashutosh, advait, amelia, sophia + +See https://docs.sarvam.ai/api-reference-docs/text-to-speech/stream for full API details. +""" import asyncio import base64 import json -from typing import Any, AsyncGenerator, Mapping, Optional +from enum import Enum +from typing import Any, AsyncGenerator, List, Mapping, Optional import aiohttp from loguru import logger @@ -42,6 +65,101 @@ except ModuleNotFoundError as e: raise Exception(f"Missing module: {e}") +class SarvamTTSModel(str, Enum): + """Available Sarvam TTS models. + + Attributes: + BULBUL_V2: Standard TTS model with pitch/loudness control. + - Supports pitch, loudness, pace (0.3-3.0) + - Default sample rate: 22050 Hz + BULBUL_V3_BETA: Advanced model with temperature control. + - Does NOT support pitch/loudness + - Pace range: 0.5-2.0 + - Supports temperature parameter + - Default sample rate: 24000 Hz + - Preprocessing is always enabled + """ + + BULBUL_V2 = "bulbul:v2" + BULBUL_V3_BETA = "bulbul:v3-beta" + + +class SarvamTTSSpeakerV2(str, Enum): + """Available speakers for bulbul:v2 model. + + Female voices: anushka, manisha, vidya, arya + Male voices: abhilash, karun, hitesh + """ + + ANUSHKA = "anushka" + ABHILASH = "abhilash" + MANISHA = "manisha" + VIDYA = "vidya" + ARYA = "arya" + KARUN = "karun" + HITESH = "hitesh" + + +class SarvamTTSSpeakerV3(str, Enum): + """Available speakers for bulbul:v3-beta model. + + Includes a wider variety of voices with different characteristics. + """ + + ADITYA = "aditya" + RITU = "ritu" + PRIYA = "priya" + NEHA = "neha" + RAHUL = "rahul" + POOJA = "pooja" + ROHAN = "rohan" + SIMRAN = "simran" + KAVYA = "kavya" + AMIT = "amit" + DEV = "dev" + ISHITA = "ishita" + SHREYA = "shreya" + RATAN = "ratan" + VARUN = "varun" + MANAN = "manan" + SUMIT = "sumit" + ROOPA = "roopa" + KABIR = "kabir" + AAYAN = "aayan" + SHUBH = "shubh" + ASHUTOSH = "ashutosh" + ADVAIT = "advait" + AMELIA = "amelia" + SOPHIA = "sophia" + + +# Default sample rates per model +SARVAM_DEFAULT_SAMPLE_RATES = { + SarvamTTSModel.BULBUL_V2: 22050, + SarvamTTSModel.BULBUL_V3_BETA: 24000, +} + +# Default speakers per model +SARVAM_DEFAULT_SPEAKERS = { + SarvamTTSModel.BULBUL_V2: SarvamTTSSpeakerV2.ANUSHKA.value, + SarvamTTSModel.BULBUL_V3_BETA: SarvamTTSSpeakerV3.ADITYA.value, +} + + +def get_speakers_for_model(model: str) -> List[str]: + """Get the list of available speakers for a given model. + + Args: + model: The model name (e.g., "bulbul:v2" or "bulbul:v3-beta"). + + Returns: + List of speaker names available for the model. + """ + if model in (SarvamTTSModel.BULBUL_V3_BETA.value): + return [s.value for s in SarvamTTSSpeakerV3] + return [s.value for s in SarvamTTSSpeakerV2] + + def language_to_sarvam_language(language: Language) -> Optional[str]: """Convert Pipecat Language enum to Sarvam AI language codes. @@ -72,11 +190,27 @@ class SarvamHttpTTSService(TTSService): """Text-to-Speech service using Sarvam AI's API. Converts text to speech using Sarvam AI's TTS models with support for multiple - Indian languages. Provides control over voice characteristics like pitch, pace, - and loudness. + Indian languages. Provides control over voice characteristics. + + **Model Differences:** + + - **bulbul:v2** (default): + - Supports: pitch (-0.75 to 0.75), loudness (0.3 to 3.0), pace (0.3 to 3.0) + - Default sample rate: 22050 Hz + - Speakers: anushka, abhilash, manisha, vidya, arya, karun, hitesh + + - **bulbul:v3-beta**: + - Does NOT support: pitch, loudness (will be ignored) + - Supports: pace (0.5 to 2.0), temperature (0.01 to 1.0) + - Default sample rate: 24000 Hz + - Preprocessing is always enabled + - Speakers: aditya, ritu, priya, neha, rahul, pooja, rohan, simran, kavya, + amit, dev, ishita, shreya, ratan, varun, manan, sumit, roopa, kabir, + aayan, shubh, ashutosh, advait, amelia, sophia Example:: + # Using bulbul:v2 (default) tts = SarvamHttpTTSService( api_key="your-api-key", voice_id="anushka", @@ -85,18 +219,20 @@ class SarvamHttpTTSService(TTSService): params=SarvamHttpTTSService.InputParams( language=Language.HI, pitch=0.1, - pace=1.2 + pace=1.2, + loudness=1.5 ) ) - # For bulbul v3 beta with any speaker: + # Using bulbul:v3-beta with temperature control tts_v3 = SarvamHttpTTSService( api_key="your-api-key", - voice_id="speaker_name", - model="bulbul:v3, + voice_id="aditya", # Use v3 speaker + model="bulbul:v3-beta", aiohttp_session=session, params=SarvamHttpTTSService.InputParams( language=Language.HI, + pace=1.2, # Range: 0.5-2.0 for v3 temperature=0.8 ) ) @@ -108,23 +244,47 @@ class SarvamHttpTTSService(TTSService): Parameters: language: Language for synthesis. Defaults to English (India). pitch: Voice pitch adjustment (-0.75 to 0.75). Defaults to 0.0. - pace: Speech pace multiplier (0.3 to 3.0). Defaults to 1.0. - loudness: Volume multiplier (0.1 to 3.0). Defaults to 1.0. + **Note:** Only supported for bulbul:v2. Ignored for v3 models. + pace: Speech pace multiplier. Defaults to 1.0. + - bulbul:v2: Range 0.3 to 3.0 + - bulbul:v3-beta: Range 0.5 to 2.0 + loudness: Volume multiplier (0.3 to 3.0). Defaults to 1.0. + **Note:** Only supported for bulbul:v2. Ignored for v3 models. enable_preprocessing: Whether to enable text preprocessing. Defaults to False. + **Note:** Always enabled for bulbul:v3-beta (cannot be disabled). + temperature: Controls output randomness for bulbul:v3-beta (0.01 to 1.0). + Lower values = more deterministic, higher = more random. Defaults to 0.6. + **Note:** Only supported for bulbul:v3-beta. Ignored for v2. """ language: Optional[Language] = Language.EN - pitch: Optional[float] = Field(default=0.0, ge=-0.75, le=0.75) - pace: Optional[float] = Field(default=1.0, ge=0.3, le=3.0) - loudness: Optional[float] = Field(default=1.0, ge=0.1, le=3.0) - enable_preprocessing: Optional[bool] = False + pitch: Optional[float] = Field( + default=0.0, + ge=-0.75, + le=0.75, + description="Voice pitch adjustment. Only for bulbul:v2.", + ) + pace: Optional[float] = Field( + default=1.0, + ge=0.3, + le=3.0, + description="Speech pace. v2: 0.3-3.0, v3: 0.5-2.0.", + ) + loudness: Optional[float] = Field( + default=1.0, + ge=0.3, + le=3.0, + description="Volume multiplier. Only for bulbul:v2.", + ) + enable_preprocessing: Optional[bool] = Field( + default=False, + description="Enable text preprocessing. Always enabled for v3-beta model.", + ) temperature: Optional[float] = Field( default=0.6, ge=0.01, le=1.0, - description="Controls the randomness of the output for bulbul v3 beta. " - "Lower values make the output more focused and deterministic, while " - "higher values make it more random. Range: 0.01 to 1.0. Default: 0.6.", + description="Output randomness for bulbul:v3-beta only. Range: 0.01-1.0.", ) def __init__( @@ -132,7 +292,7 @@ class SarvamHttpTTSService(TTSService): *, api_key: str, aiohttp_session: aiohttp.ClientSession, - voice_id: str = "anushka", + voice_id: Optional[str] = None, model: str = "bulbul:v2", base_url: str = "https://api.sarvam.ai", sample_rate: Optional[int] = None, @@ -144,37 +304,79 @@ class SarvamHttpTTSService(TTSService): Args: api_key: Sarvam AI API subscription key. aiohttp_session: Shared aiohttp session for making requests. - voice_id: Speaker voice ID (e.g., "anushka", "meera"). Defaults to "anushka". - model: TTS model to use ("bulbul:v2" or "bulbul:v3-beta" or "bulbul:v3"). Defaults to "bulbul:v2". + voice_id: Speaker voice ID. If None, uses model-appropriate default: + - bulbul:v2: "anushka" + - bulbul:v3-beta/v3: "aditya" + model: TTS model to use. Options: + - "bulbul:v2" (default): Standard model with pitch/loudness support + - "bulbul:v3-beta": Advanced model with temperature control + - "bulbul:v3": Alias for v3-beta base_url: Sarvam AI API base URL. Defaults to "https://api.sarvam.ai". - sample_rate: Audio sample rate in Hz (8000, 16000, 22050, 24000). If None, uses default. + sample_rate: Audio sample rate in Hz (8000, 16000, 22050, 24000). + If None, uses model-specific default (v2: 22050, v3: 24000). params: Additional voice and preprocessing parameters. If None, uses defaults. **kwargs: Additional arguments passed to parent TTSService. + + Note: + When using bulbul:v3-beta: + - pitch and loudness parameters are ignored + - pace range is limited to 0.5-2.0 + - preprocessing is always enabled + - use SarvamTTSSpeakerV3 speakers (e.g., "aditya", "ritu") """ + # Determine if using v3 model + is_v3_model = model in ( + SarvamTTSModel.BULBUL_V3_BETA.value, + "bulbul:v3-beta", + ) + + # Set default sample rate based on model if not specified + if sample_rate is None: + sample_rate = 24000 if is_v3_model else 22050 + super().__init__(sample_rate=sample_rate, **kwargs) params = params or SarvamHttpTTSService.InputParams() + # Set default voice based on model if not specified + if voice_id is None: + voice_id = "aditya" if is_v3_model else "anushka" + self._api_key = api_key self._base_url = base_url self._session = aiohttp_session + self._is_v3_model = is_v3_model # Build base settings common to all models self._settings = { "language": ( self.language_to_service_language(params.language) if params.language else "en-IN" ), - "enable_preprocessing": params.enable_preprocessing, + "enable_preprocessing": params.enable_preprocessing if not is_v3_model else True, } # Add model-specific parameters - if model in ("bulbul:v3-beta", "bulbul:v3"): + if is_v3_model: + # Validate pace for v3 (0.5-2.0) + pace = params.pace + if pace is not None and (pace < 0.5 or pace > 2.0): + logger.warning( + f"Pace {pace} is outside v3 model range (0.5-2.0). Clamping to valid range." + ) + pace = max(0.5, min(2.0, pace)) + self._settings.update( { - "temperature": getattr(params, "temperature", 0.6), + "temperature": params.temperature, + "pace": pace, "model": model, } ) + # Log warning if v2-only parameters are set + if params.pitch != 0.0: + logger.warning(f"pitch parameter is ignored for {model}") + if params.loudness != 1.0: + logger.warning(f"loudness parameter is ignored for {model}") else: self._settings.update( { @@ -184,6 +386,9 @@ class SarvamHttpTTSService(TTSService): "model": model, } ) + # Log warning if v3-only parameters are set + if params.temperature != 0.6: + logger.warning(f"temperature parameter is ignored for {model}") self.set_model_name(model) self.set_voice(voice_id) @@ -231,18 +436,28 @@ class SarvamHttpTTSService(TTSService): try: await self.start_ttfb_metrics() + # Build payload based on model type payload = { "text": text, "target_language_code": self._settings["language"], "speaker": self._voice_id, - "pitch": self._settings["pitch"], - "pace": self._settings["pace"], - "loudness": self._settings["loudness"], "sample_rate": self.sample_rate, "enable_preprocessing": self._settings["enable_preprocessing"], "model": self._model_name, } + # Add model-specific parameters + if self._is_v3_model: + # v3 models use temperature and pace (0.5-2.0) + payload["temperature"] = self._settings.get("temperature", 0.6) + if "pace" in self._settings: + payload["pace"] = self._settings["pace"] + else: + # v2 models use pitch, pace, loudness + payload["pitch"] = self._settings.get("pitch", 0.0) + payload["pace"] = self._settings.get("pace", 1.0) + payload["loudness"] = self._settings.get("loudness", 1.0) + headers = { "api-subscription-key": self._api_key, "Content-Type": "application/json", @@ -296,10 +511,34 @@ class SarvamTTSService(InterruptibleTTSService): """WebSocket-based text-to-speech service using Sarvam AI. Provides streaming TTS with real-time audio generation for multiple Indian languages. - Supports voice control parameters like pitch, pace, and loudness adjustment. + Uses WebSocket for low-latency streaming audio synthesis. + + **Model Differences:** + + - **bulbul:v2** (default): + - Supports: pitch (-0.75 to 0.75), loudness (0.3 to 3.0), pace (0.3 to 3.0) + - Default sample rate: 22050 Hz + - Speakers: anushka, abhilash, manisha, vidya, arya, karun, hitesh + + - **bulbul:v3-beta** / **bulbul:v3**: + - Does NOT support: pitch, loudness (will be ignored) + - Supports: pace (0.5 to 2.0), temperature (0.01 to 1.0) + - Default sample rate: 24000 Hz + - Preprocessing is always enabled + - Speakers: aditya, ritu, priya, neha, rahul, pooja, rohan, simran, kavya, + amit, dev, ishita, shreya, ratan, varun, manan, sumit, roopa, kabir, + aayan, shubh, ashutosh, advait, amelia, sophia + + **WebSocket Protocol:** + The service uses a WebSocket connection for real-time streaming. Messages include: + - config: Initial configuration with voice settings + - text: Text chunks for synthesis + - flush: Signal to process remaining buffered text + - ping: Keepalive signal Example:: + # Using bulbul:v2 (default) tts = SarvamTTSService( api_key="your-api-key", voice_id="anushka", @@ -307,63 +546,108 @@ class SarvamTTSService(InterruptibleTTSService): params=SarvamTTSService.InputParams( language=Language.HI, pitch=0.1, - pace=1.2 + pace=1.2, + loudness=1.5 ) ) - # For bulbul v3 beta with any speaker and temperature: - # Note: pace and loudness are not supported for bulbul v3 and bulbul v3 beta + # Using bulbul:v3-beta with temperature control tts_v3 = SarvamTTSService( api_key="your-api-key", - voice_id="speaker_name", - model="bulbul:v3", + voice_id="aditya", # Use v3 speaker + model="bulbul:v3-beta", params=SarvamTTSService.InputParams( language=Language.HI, + pace=1.2, # Range: 0.5-2.0 for v3 temperature=0.8 ) ) + + See https://docs.sarvam.ai/api-reference-docs/text-to-speech/stream for API details. """ class InputParams(BaseModel): - """Configuration parameters for Sarvam TTS. + """Configuration parameters for Sarvam TTS WebSocket service. Parameters: pitch: Voice pitch adjustment (-0.75 to 0.75). Defaults to 0.0. - pace: Speech pace multiplier (0.3 to 3.0). Defaults to 1.0. - loudness: Volume multiplier (0.1 to 3.0). Defaults to 1.0. + **Note:** Only supported for bulbul:v2. Ignored for v3 models. + pace: Speech pace multiplier. Defaults to 1.0. + - bulbul:v2: Range 0.3 to 3.0 + - bulbul:v3-beta: Range 0.5 to 2.0 + loudness: Volume multiplier (0.3 to 3.0). Defaults to 1.0. + **Note:** Only supported for bulbul:v2. Ignored for v3 models. enable_preprocessing: Enable text preprocessing. Defaults to False. - min_buffer_size: Minimum number of characters to buffer before generating audio. + **Note:** Always enabled for bulbul:v3-beta. + min_buffer_size: Minimum characters to buffer before generating audio. Lower values reduce latency but may affect quality. Defaults to 50. - max_chunk_length: Maximum number of characters processed in a single chunk. - Controls memory usage and processing efficiency. Defaults to 200. - output_audio_codec: Audio codec format. Defaults to "linear16". - output_audio_bitrate: Audio bitrate. Defaults to "128k". - language: Target language for synthesis. Supports Bengali (bn-IN), English (en-IN), - Gujarati (gu-IN), Hindi (hi-IN), Kannada (kn-IN), Malayalam (ml-IN), - Marathi (mr-IN), Odia (od-IN), Punjabi (pa-IN), Tamil (ta-IN), - Telugu (te-IN). Defaults to en-IN. + max_chunk_length: Maximum characters processed in a single chunk. + Controls memory usage and processing efficiency. Defaults to 150. + output_audio_codec: Audio codec format. Options: linear16, mulaw, alaw, + opus, flac, aac, wav, mp3. Defaults to "linear16". + output_audio_bitrate: Audio bitrate (32k, 64k, 96k, 128k, 192k). + Defaults to "128k". + language: Target language for synthesis. Supports Indian languages. + temperature: Controls output randomness for bulbul:v3-beta (0.01 to 1.0). + Lower = more deterministic, higher = more random. Defaults to 0.6. + **Note:** Only supported for bulbul:v3-beta. Ignored for v2. - Available Speakers: - Female: anushka, manisha, vidya, arya - Male: abhilash, karun, hitesh + **Speakers by Model:** + + bulbul:v2: + - Female: anushka (default), manisha, vidya, arya + - Male: abhilash, karun, hitesh + + bulbul:v3-beta: + - aditya (default), ritu, priya, neha, rahul, pooja, rohan, simran, + kavya, amit, dev, ishita, shreya, ratan, varun, manan, sumit, + roopa, kabir, aayan, shubh, ashutosh, advait, amelia, sophia """ - pitch: Optional[float] = Field(default=0.0, ge=-0.75, le=0.75) - pace: Optional[float] = Field(default=1.0, ge=0.3, le=3.0) - loudness: Optional[float] = Field(default=1.0, ge=0.1, le=3.0) - enable_preprocessing: Optional[bool] = False - min_buffer_size: Optional[int] = 50 - max_chunk_length: Optional[int] = 200 - output_audio_codec: Optional[str] = "linear16" - output_audio_bitrate: Optional[str] = "128k" + pitch: Optional[float] = Field( + default=0.0, + ge=-0.75, + le=0.75, + description="Voice pitch adjustment. Only for bulbul:v2.", + ) + pace: Optional[float] = Field( + default=1.0, + ge=0.3, + le=3.0, + description="Speech pace. v2: 0.3-3.0, v3: 0.5-2.0.", + ) + loudness: Optional[float] = Field( + default=1.0, + ge=0.3, + le=3.0, + description="Volume multiplier. Only for bulbul:v2.", + ) + enable_preprocessing: Optional[bool] = Field( + default=False, + description="Enable text preprocessing. Always enabled for v3 models.", + ) + min_buffer_size: Optional[int] = Field( + default=50, + description="Minimum characters to buffer before TTS processing.", + ) + max_chunk_length: Optional[int] = Field( + default=150, + description="Maximum length for sentence splitting.", + ) + output_audio_codec: Optional[str] = Field( + default="linear16", + description="Audio codec: linear16, mulaw, alaw, opus, flac, aac, wav, mp3.", + ) + output_audio_bitrate: Optional[str] = Field( + default="128k", + description="Audio bitrate: 32k, 64k, 96k, 128k, 192k.", + ) language: Optional[Language] = Language.EN temperature: Optional[float] = Field( default=0.6, ge=0.01, le=1.0, - description="Controls the randomness of the output for bulbul v3 beta. " - "Lower values make the output more focused and deterministic, while " - "higher values make it more random. Range: 0.01 to 1.0. Default: 0.6.", + description="Output randomness for bulbul:v3-beta only. Range: 0.01-1.0.", ) def __init__( @@ -371,7 +655,7 @@ class SarvamTTSService(InterruptibleTTSService): *, api_key: str, model: str = "bulbul:v2", - voice_id: str = "anushka", + voice_id: Optional[str] = None, url: str = "wss://api.sarvam.ai/text-to-speech/ws", aggregate_sentences: Optional[bool] = True, sample_rate: Optional[int] = None, @@ -382,20 +666,39 @@ class SarvamTTSService(InterruptibleTTSService): Args: api_key: Sarvam API key for authenticating TTS requests. - model: Identifier of the Sarvam speech model (default "bulbul:v2"). - Supports "bulbul:v2", "bulbul:v3-beta" and "bulbul:v3". - voice_id: Voice identifier for synthesis (default "anushka"). - url: WebSocket URL for connecting to the TTS backend (default production URL). - aggregate_sentences: Whether to merge multiple sentences into one audio chunk (default True). - sample_rate: Desired sample rate for the output audio in Hz (overrides default if set). - params: Optional input parameters to override global configuration. - **kwargs: Optional keyword arguments forwarded to InterruptibleTTSService (such as - `push_stop_frames`, `sample_rate`, task manager parameters, event hooks, etc.) - to customize transport behavior or enable metrics support. + model: TTS model to use. Options: + - "bulbul:v2" (default): Standard model with pitch/loudness support + - "bulbul:v3-beta": Advanced model with temperature control + - "bulbul:v3": Alias for v3-beta + voice_id: Speaker voice ID. If None, uses model-appropriate default: + - bulbul:v2: "anushka" + - bulbul:v3-beta/v3: "aditya" + url: WebSocket URL for the TTS backend (default production URL). + aggregate_sentences: Merge multiple sentences into one audio chunk (default True). + sample_rate: Output audio sample rate in Hz (8000, 16000, 22050, 24000). + If None, uses model-specific default (v2: 22050, v3: 24000). + params: Optional input parameters to override defaults. + **kwargs: Arguments forwarded to InterruptibleTTSService. - This method sets up the internal TTS configuration mapping, constructs the WebSocket - URL based on the chosen model, and initializes state flags before connecting. + Note: + When using bulbul:v3-beta: + - pitch and loudness parameters are ignored + - pace range is limited to 0.5-2.0 + - preprocessing is always enabled + - use SarvamTTSSpeakerV3 speakers (e.g., "aditya", "ritu") + + See https://docs.sarvam.ai/api-reference-docs/text-to-speech/stream """ + # Determine if using v3 model + is_v3_model = model in ( + SarvamTTSModel.BULBUL_V3_BETA.value, + "bulbul:v3-beta", + ) + + # Set default sample rate based on model if not specified + if sample_rate is None: + sample_rate = 24000 if is_v3_model else 22050 + # Initialize parent class first super().__init__( aggregate_sentences=aggregate_sentences, @@ -407,19 +710,26 @@ class SarvamTTSService(InterruptibleTTSService): ) params = params or SarvamTTSService.InputParams() - # WebSocket endpoint URL + # Set default voice based on model if not specified + if voice_id is None: + voice_id = "aditya" if is_v3_model else "anushka" + + self._is_v3_model = is_v3_model + + # WebSocket endpoint URL with model query parameter self._websocket_url = f"{url}?model={model}" self._api_key = api_key self.set_model_name(model) self.set_voice(voice_id) + # Build base settings common to all models self._settings = { "target_language_code": ( self.language_to_service_language(params.language) if params.language else "en-IN" ), "speaker": voice_id, - "speech_sample_rate": 0, - "enable_preprocessing": params.enable_preprocessing, + "speech_sample_rate": str(sample_rate), + "enable_preprocessing": params.enable_preprocessing if not is_v3_model else True, "min_buffer_size": params.min_buffer_size, "max_chunk_length": params.max_chunk_length, "output_audio_codec": params.output_audio_codec, @@ -427,13 +737,27 @@ class SarvamTTSService(InterruptibleTTSService): } # Add model-specific parameters - if model in ("bulbul:v3-beta", "bulbul:v3"): + if is_v3_model: + # Validate pace for v3 (0.5-2.0) + pace = params.pace + if pace is not None and (pace < 0.5 or pace > 2.0): + logger.warning( + f"Pace {pace} is outside v3 model range (0.5-2.0). Clamping to valid range." + ) + pace = max(0.5, min(2.0, pace)) + self._settings.update( { - "temperature": getattr(params, "temperature", 0.6), + "temperature": params.temperature, + "pace": pace, "model": model, } ) + # Log warning if v2-only parameters are set + if params.pitch != 0.0: + logger.warning(f"pitch parameter is ignored for {model}") + if params.loudness != 1.0: + logger.warning(f"loudness parameter is ignored for {model}") else: self._settings.update( { @@ -443,8 +767,11 @@ class SarvamTTSService(InterruptibleTTSService): "model": model, } ) - self._started = False + # Log warning if v3-only parameters are set + if params.temperature != 0.6: + logger.warning(f"temperature parameter is ignored for {model}") + self._started = False self._receive_task = None self._keepalive_task = None self._disconnecting = False @@ -476,7 +803,8 @@ class SarvamTTSService(InterruptibleTTSService): """ await super().start(frame) - self._settings["speech_sample_rate"] = self.sample_rate + # WebSocket API expects sample rate as string + self._settings["speech_sample_rate"] = str(self.sample_rate) await self._connect() async def stop(self, frame: EndFrame): From 57821cf709acc004b726f8e1770e53d6abcd5866 Mon Sep 17 00:00:00 2001 From: dhruvladia-sarvam Date: Fri, 30 Jan 2026 16:07:52 +0530 Subject: [PATCH 0294/1060] fix --- src/pipecat/services/sarvam/stt.py | 103 +++++++++++++++++++++-------- 1 file changed, 76 insertions(+), 27 deletions(-) diff --git a/src/pipecat/services/sarvam/stt.py b/src/pipecat/services/sarvam/stt.py index b825c0d78..ec5e42df0 100644 --- a/src/pipecat/services/sarvam/stt.py +++ b/src/pipecat/services/sarvam/stt.py @@ -78,11 +78,13 @@ class SarvamSTTService(STTService): """Configuration parameters for Sarvam STT service. Parameters: - language: Target language for transcription. Required for all models. - Defaults to "unknown" for saarika models and "en-IN" for saaras:v3. - prompt: Optional prompt to guide transcription style/context. - Only applicable to saaras:v3 models. Defaults to None. - mode: Mode of operation for saaras:v3 models. Options: transcribe, translate, + language: Target language for transcription. + - saarika:v2.5: Defaults to "unknown" (auto-detect supported) + - saaras:v2.5: Not used (auto-detects language) + - saaras:v3: Defaults to "en-IN" + prompt: Optional prompt to guide transcription/translation style/context. + Only applicable to saaras models (v2.5 and v3). Defaults to None. + mode: Mode of operation for saaras:v3 models only. Options: transcribe, translate, verbatim, translit, codemix. Defaults to "transcribe" for saaras:v3. vad_signals: Enable VAD signals in response. Defaults to None. high_vad_sensitivity: Enable high VAD (Voice Activity Detection) sensitivity. Defaults to None. @@ -111,10 +113,13 @@ class SarvamSTTService(STTService): Args: api_key: Sarvam API key for authentication. - model: Sarvam model to use for transcription. Allowed: "saarika:v2.5", "saaras:v3". + model: Sarvam model to use for transcription. Allowed values: + - "saarika:v2.5": Standard STT model + - "saaras:v2.5": STT-Translate model (auto-detects language, supports prompts) + - "saaras:v3": Advanced STT model (supports mode and prompts) sample_rate: Audio sample rate. Defaults to 16000 if not specified. input_audio_codec: Audio codec/format of the input file. Defaults to "wav". - mode: Mode of operation for saaras:v3 models. Options: transcribe, translate, + mode: Mode of operation for saaras:v3 models only. Options: transcribe, translate, verbatim, translit, codemix. Defaults to "transcribe" for saaras:v3. params: Configuration parameters for Sarvam STT service. **kwargs: Additional arguments passed to the parent STTService. @@ -125,34 +130,52 @@ class SarvamSTTService(STTService): params = params.model_copy(update={"mode": mode}) # Validate allowed models - allowed_models = {"saarika:v2.5", "saaras:v3"} + allowed_models = {"saarika:v2.5", "saaras:v3", "saaras:v2.5"} if model not in allowed_models: allowed_models_list = ", ".join(sorted(allowed_models)) raise ValueError(f"Unsupported model '{model}'. Allowed values: {allowed_models_list}.") - # Validate that saarika models don't accept prompt parameter + # Validate model-specific parameter restrictions if "saarika" in model.lower(): + # saarika models don't accept prompt or mode if params.prompt is not None: raise ValueError( f"Model '{model}' does not accept prompt parameter. " - "Prompts are only supported for saaras:v3 model." + "Prompts are only supported for saaras models (v2.5 and v3)." ) if params.mode is not None: raise ValueError( f"Model '{model}' does not accept mode parameter. " "Mode is only supported for saaras:v3 model." ) + elif model.lower() == "saaras:v2.5": + # saaras:v2.5 supports prompt but not mode + if params.mode is not None: + raise ValueError( + f"Model '{model}' does not accept mode parameter. " + "Mode is only supported for saaras:v3 model." + ) + if params.language is not None: + raise ValueError( + f"Model '{model}' does not accept language parameter. " + "saaras:v2.5 (STT-Translate) auto-detects language." + ) super().__init__(sample_rate=sample_rate, **kwargs) self.set_model_name(model) self._api_key = api_key self._language_code: Optional[Language] = params.language - # Set language string - both models require language_code + # Set language string based on model type + # - saarika:v2.5: uses language_code or defaults to "unknown" + # - saaras:v2.5: auto-detects language (no language_code needed) + # - saaras:v3: uses language_code or defaults to "en-IN" if params.language: self._language_string = language_to_sarvam_language(params.language) elif "saarika" in model.lower(): self._language_string = "unknown" + elif model.lower() == "saaras:v2.5": + self._language_string = None # STT-Translate auto-detects language elif model.lower() == "saaras:v3": self._language_string = "en-IN" else: @@ -225,7 +248,17 @@ class SarvamSTTService(STTService): Args: language: The language to use for speech recognition. + + Raises: + ValueError: If called on saaras:v2.5 model which auto-detects language. """ + # saaras:v2.5 (STT-Translate) auto-detects language + if self.model_name.lower() == "saaras:v2.5": + raise ValueError( + f"Model '{self.model_name}' does not accept language parameter. " + "saaras:v2.5 (STT-Translate) auto-detects language." + ) + logger.info(f"Switching STT language to: [{language}]") self._language_code = language self._language_string = language_to_sarvam_language(language) @@ -233,24 +266,24 @@ class SarvamSTTService(STTService): await self._connect() async def set_prompt(self, prompt: Optional[str]): - """Set the transcription prompt and reconnect. + """Set the transcription/translation prompt and reconnect. Args: - prompt: Prompt text to guide transcription style/context. + prompt: Prompt text to guide transcription/translation style/context. Pass None to clear/disable prompt. - Only applicable to saaras:v3 model. + Only applicable to saaras models (v2.5 and v3). """ # saarika models do not accept prompt parameter if "saarika" in self.model_name.lower(): if prompt is not None: raise ValueError( f"Model '{self.model_name}' does not accept prompt parameter. " - "Prompts are only supported for saaras:v3 model." + "Prompts are only supported for saaras models (v2.5 and v3)." ) # If prompt is None and it's saarika, just silently return (no-op) return - logger.info("Updating saaras:v3 prompt.") + logger.info(f"Updating {self.model_name} prompt.") self._prompt = prompt await self._disconnect() await self._connect() @@ -314,8 +347,13 @@ class SarvamSTTService(STTService): "sample_rate": self.sample_rate, } - # Both saarika and saaras:v3 use the same speech_to_text_streaming endpoint - await self._socket_client.transcribe(**method_kwargs) + # Use appropriate method based on model type + if self.model_name.lower() == "saaras:v2.5": + # STT-Translate: auto-detects input language and returns translated text + await self._socket_client.translate(**method_kwargs) + else: + # saarika:v2.5 and saaras:v3 use transcribe + await self._socket_client.transcribe(**method_kwargs) except Exception as e: yield ErrorFrame(error=f"Error sending audio to Sarvam: {e}", exception=e) @@ -331,15 +369,18 @@ class SarvamSTTService(STTService): vad_signals_str = "true" if self._vad_signals else "false" high_vad_sensitivity_str = "true" if self._high_vad_sensitivity else "false" - # Build connection parameters - both models use speech_to_text_streaming + # Build common connection parameters connect_kwargs = { "model": self.model_name, - "language_code": self._language_string, # Required for both models "vad_signals": vad_signals_str, "high_vad_sensitivity": high_vad_sensitivity_str, "sample_rate": str(self.sample_rate), } + # Add language_code for models that require it (not saaras:v2.5 which auto-detects) + if self._language_string is not None: + connect_kwargs["language_code"] = self._language_string + # Add mode for saaras:v3 only if self.model_name.lower() == "saaras:v3" and self._mode is not None: connect_kwargs["mode"] = self._mode @@ -353,17 +394,25 @@ class SarvamSTTService(STTService): pass return connect_fn(**kwargs) - # Both saarika and saaras:v3 use the same speech_to_text_streaming endpoint - self._websocket_context = _connect_with_sdk_headers( - self._sarvam_client.speech_to_text_streaming.connect, - **connect_kwargs, - ) + # Choose the appropriate endpoint based on model + if self.model_name.lower() == "saaras:v2.5": + # STT-Translate: auto-detects input language and returns translated text + self._websocket_context = _connect_with_sdk_headers( + self._sarvam_client.speech_to_text_translate_streaming.connect, + **connect_kwargs, + ) + else: + # saarika:v2.5 and saaras:v3 use speech_to_text_streaming + self._websocket_context = _connect_with_sdk_headers( + self._sarvam_client.speech_to_text_streaming.connect, + **connect_kwargs, + ) # Enter the async context manager self._socket_client = await self._websocket_context.__aenter__() - # Set prompt if provided (only for saaras:v3 model, after connection) - if self._prompt is not None and self.model_name.lower() == "saaras:v3": + # Set prompt if provided (only for saaras models, after connection) + if self._prompt is not None and "saaras" in self.model_name.lower(): await self._socket_client.set_prompt(self._prompt) # Register event handler for incoming messages From 72ab3295130d0b4a790d378d895df88f5f4ec007 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Aleix=20Conchillo=20Flaqu=C3=A9?= Date: Thu, 29 Jan 2026 13:49:46 -0800 Subject: [PATCH 0295/1060] services(tss): add new KokoroTTSService --- changelog/3595.added.md | 1 + .../foundational/07zj-interruptible-kokoro.py | 132 +++ pyproject.toml | 3 +- scripts/evals/run-release-evals.py | 1 + src/pipecat/services/kokoro/__init__.py | 0 src/pipecat/services/kokoro/tts.py | 155 ++++ src/pipecat/services/piper/tts.py | 1 - uv.lock | 771 +++++++++++++++++- 8 files changed, 1061 insertions(+), 3 deletions(-) create mode 100644 changelog/3595.added.md create mode 100644 examples/foundational/07zj-interruptible-kokoro.py create mode 100644 src/pipecat/services/kokoro/__init__.py create mode 100644 src/pipecat/services/kokoro/tts.py diff --git a/changelog/3595.added.md b/changelog/3595.added.md new file mode 100644 index 000000000..7f3213eb1 --- /dev/null +++ b/changelog/3595.added.md @@ -0,0 +1 @@ +- Added `KokoroTTSService` for local text-to-speech synthesis using the Kokoro-82M model. diff --git a/examples/foundational/07zj-interruptible-kokoro.py b/examples/foundational/07zj-interruptible-kokoro.py new file mode 100644 index 000000000..6381e994f --- /dev/null +++ b/examples/foundational/07zj-interruptible-kokoro.py @@ -0,0 +1,132 @@ +# +# Copyright (c) 2024-2026, Daily +# +# SPDX-License-Identifier: BSD 2-Clause License +# + +import os + +from dotenv import load_dotenv +from loguru import logger + +from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3 +from pipecat.audio.vad.silero import SileroVADAnalyzer +from pipecat.audio.vad.vad_analyzer import VADParams +from pipecat.frames.frames import LLMRunFrame +from pipecat.pipeline.pipeline import Pipeline +from pipecat.pipeline.runner import PipelineRunner +from pipecat.pipeline.task import PipelineParams, PipelineTask +from pipecat.processors.aggregators.llm_context import LLMContext +from pipecat.processors.aggregators.llm_response_universal import ( + LLMContextAggregatorPair, + LLMUserAggregatorParams, +) +from pipecat.runner.types import RunnerArguments +from pipecat.runner.utils import create_transport +from pipecat.services.deepgram.stt import DeepgramSTTService +from pipecat.services.kokoro.tts import KokoroTTSService +from pipecat.services.openai.llm import OpenAILLMService +from pipecat.transports.base_transport import BaseTransport, TransportParams +from pipecat.transports.daily.transport import DailyParams +from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams +from pipecat.turns.user_stop import TurnAnalyzerUserTurnStopStrategy +from pipecat.turns.user_turn_strategies import UserTurnStrategies + +load_dotenv(override=True) + +# We store functions so objects (e.g. SileroVADAnalyzer) don't get +# instantiated. The function will be called when the desired transport gets +# selected. +transport_params = { + "daily": lambda: DailyParams( + audio_in_enabled=True, + audio_out_enabled=True, + vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), + ), + "twilio": lambda: FastAPIWebsocketParams( + audio_in_enabled=True, + audio_out_enabled=True, + vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), + ), + "webrtc": lambda: TransportParams( + audio_in_enabled=True, + audio_out_enabled=True, + vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), + ), +} + + +async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): + logger.info(f"Starting bot") + + stt = DeepgramSTTService(api_key=os.getenv("DEEPGRAM_API_KEY")) + + tts = KokoroTTSService(voice_id="af_heart") + + llm = OpenAILLMService(api_key=os.getenv("OPENAI_API_KEY")) + + messages = [ + { + "role": "system", + "content": "You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + }, + ] + + context = LLMContext(messages) + user_aggregator, assistant_aggregator = LLMContextAggregatorPair( + context, + user_params=LLMUserAggregatorParams( + user_turn_strategies=UserTurnStrategies( + stop=[TurnAnalyzerUserTurnStopStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3())] + ), + ), + ) + + pipeline = Pipeline( + [ + transport.input(), # Transport user input + stt, + user_aggregator, # User responses + llm, # LLM + tts, # TTS + transport.output(), # Transport bot output + assistant_aggregator, # Assistant spoken responses + ] + ) + + task = PipelineTask( + pipeline, + params=PipelineParams( + enable_metrics=True, + enable_usage_metrics=True, + ), + idle_timeout_secs=runner_args.pipeline_idle_timeout_secs, + ) + + @transport.event_handler("on_client_connected") + async def on_client_connected(transport, client): + logger.info(f"Client connected") + # Kick off the conversation. + messages.append({"role": "system", "content": "Please introduce yourself to the user."}) + await task.queue_frames([LLMRunFrame()]) + + @transport.event_handler("on_client_disconnected") + async def on_client_disconnected(transport, client): + logger.info(f"Client disconnected") + await task.cancel() + + runner = PipelineRunner(handle_sigint=runner_args.handle_sigint) + + await runner.run(task) + + +async def bot(runner_args: RunnerArguments): + """Main bot entry point compatible with Pipecat Cloud.""" + transport = await create_transport(runner_args, transport_params) + await run_bot(transport, runner_args) + + +if __name__ == "__main__": + from pipecat.runner.run import main + + main() diff --git a/pyproject.toml b/pyproject.toml index 098ad917b..f32fed9e9 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -75,6 +75,7 @@ heygen = [ "livekit>=1.0.13", "pipecat-ai[websockets-base]" ] hume = [ "hume>=0.11.2" ] inworld = [] koala = [ "pvkoala~=2.0.3" ] +kokoro = [ "kokoro>=0.9.4,<1", "requests>=2.32.5,<3" ] krisp = [ "pipecat-ai-krisp~=0.4.0" ] langchain = [ "langchain~=0.3.20", "langchain-community~=0.3.20", "langchain-openai~=0.3.9" ] livekit = [ "livekit~=1.0.13", "livekit-api~=1.0.5", "tenacity>=8.2.3,<10.0.0", "pyjwt>=2.10.1" ] @@ -95,7 +96,7 @@ rnnoise = [ "pyrnnoise~=0.4.1" ] openpipe = [ "openpipe>=4.50.0,<6" ] openrouter = [] perplexity = [] -piper = [ "piper-tts>=1.3.0,<2" ] +piper = [ "piper-tts>=1.3.0,<2", "requests>=2.32.5,<3" ] playht = [ "pipecat-ai[websockets-base]" ] qwen = [] remote-smart-turn = [] diff --git a/scripts/evals/run-release-evals.py b/scripts/evals/run-release-evals.py index 239012c36..090b1b96c 100644 --- a/scripts/evals/run-release-evals.py +++ b/scripts/evals/run-release-evals.py @@ -139,6 +139,7 @@ TESTS_07 = [ ("07zg-interruptible-camb.py", EVAL_SIMPLE_MATH), ("07zh-interruptible-hathora.py", EVAL_SIMPLE_MATH), ("07zi-interruptible-piper.py", EVAL_SIMPLE_MATH), + ("07zj-interruptible-kokoro.py", EVAL_SIMPLE_MATH), # Needs a local XTTS docker instance running. # ("07i-interruptible-xtts.py", EVAL_SIMPLE_MATH), # Needs a Krisp license. diff --git a/src/pipecat/services/kokoro/__init__.py b/src/pipecat/services/kokoro/__init__.py new file mode 100644 index 000000000..e69de29bb diff --git a/src/pipecat/services/kokoro/tts.py b/src/pipecat/services/kokoro/tts.py new file mode 100644 index 000000000..21c6526f5 --- /dev/null +++ b/src/pipecat/services/kokoro/tts.py @@ -0,0 +1,155 @@ +# +# Copyright (c) 2024-2026, Daily +# +# SPDX-License-Identifier: BSD 2-Clause License +# + +"""Kokoro TTS service implementation.""" + +import asyncio +from typing import AsyncGenerator, AsyncIterator, Optional + +import numpy as np +from loguru import logger +from pydantic import BaseModel + +from pipecat.audio.utils import create_stream_resampler +from pipecat.frames.frames import ( + ErrorFrame, + Frame, + TTSStartedFrame, + TTSStoppedFrame, +) +from pipecat.services.tts_service import TTSService +from pipecat.transcriptions.language import Language, resolve_language +from pipecat.utils.tracing.service_decorators import traced_tts + +try: + from kokoro import KPipeline +except ModuleNotFoundError as e: + logger.error(f"Exception: {e}") + logger.error("In order to use Kokoro, you need to `pip install pipecat-ai[kokoro]`.") + raise Exception(f"Missing module: {e}") + + +def language_to_kokoro_language(language: Language) -> str: + """Convert a Language enum to Kokoro language code. + + Args: + language: The Language enum value to convert. + + Returns: + The corresponding Kokoro language code, or None if not supported. + """ + LANGUAGE_MAP = { + Language.EN: "a", + Language.EN_US: "a", + Language.EN_GB: "b", + Language.ES: "e", + Language.FR: "f", + Language.HI: "h", + Language.IT: "i", + Language.JA: "j", + Language.PT: "p", + Language.ZH: "z", + } + + return resolve_language(language, LANGUAGE_MAP, use_base_code=True) + + +class KokoroTTSService(TTSService): + """Kokoro TTS service implementation. + + Provides local text-to-speech synthesis using the Kokoro-82M model. + Automatically downloads the model on first use. + """ + + class InputParams(BaseModel): + """Input parameters for Kokoro TTS configuration. + + Parameters: + language: Language to use for synthesis. + """ + + language: Language = Language.EN + + def __init__( + self, + *, + voice_id: str, + repo_id="hexgrad/Kokoro-82M", + params: Optional[InputParams] = None, + **kwargs, + ): + """Initialize the Kokoro TTS service. + + Args: + voice_id: Voice identifier to use for synthesis. + repo_id: Hugging Face repository ID for the Kokoro model. + Defaults to "hexgrad/Kokoro-82M". + params: Configuration parameters for synthesis. + **kwargs: Additional arguments passed to parent `TTSService`. + """ + super().__init__(**kwargs) + + params = params or KokoroTTSService.InputParams() + + self._voice_id = voice_id + self._lang_code = language_to_kokoro_language(params.language) + self._pipeline = KPipeline(lang_code=self._lang_code, repo_id=repo_id) + + self._resampler = create_stream_resampler() + + def can_generate_metrics(self) -> bool: + """Indicate that this service supports TTFB and usage metrics.""" + return True + + @traced_tts + async def run_tts(self, text: str) -> AsyncGenerator[Frame, None]: + """Synthesize speech from text using the Kokoro pipeline. + + Runs the Kokoro pipeline in a background thread and streams audio + frames as they become available. + + Args: + text: The text to synthesize. + """ + logger.debug(f"{self}: Generating TTS [{text}]") + + def async_next(it): + try: + return next(it) + except StopIteration: + return None + + async def async_iterator(iterator) -> AsyncIterator[bytes]: + while True: + item = await asyncio.to_thread(async_next, iterator) + if item is None: + return + + (_, _, audio) = item + + # Kokoro outputs a PyTorch tensor at 24kHz, convert to int16 bytes + audio_np = np.array(audio) + audio_int16 = (audio_np * 32767).astype(np.int16).tobytes() + + yield audio_int16 + + try: + await self.start_ttfb_metrics() + await self.start_tts_usage_metrics(text) + yield TTSStartedFrame() + + async for frame in self._stream_audio_frames_from_iterator( + async_iterator(self._pipeline(text, voice=self._voice_id)), + in_sample_rate=24000, + ): + await self.stop_ttfb_metrics() + yield frame + except Exception as e: + yield ErrorFrame(error=f"Unknown error occurred: {e}") + finally: + logger.debug(f"{self}: Finished TTS [{text}]") + await self.stop_ttfb_metrics() + yield TTSStoppedFrame() diff --git a/src/pipecat/services/piper/tts.py b/src/pipecat/services/piper/tts.py index 1de1688b1..bea9e9c6c 100644 --- a/src/pipecat/services/piper/tts.py +++ b/src/pipecat/services/piper/tts.py @@ -225,7 +225,6 @@ class PiperHttpTTSService(TTSService): await self.stop_ttfb_metrics() yield frame except Exception as e: - logger.error(f"{self} exception: {e}") yield ErrorFrame(error=f"Unknown error occurred: {e}") finally: logger.debug(f"{self}: Finished TTS [{text}]") diff --git a/uv.lock 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100644 --- a/src/pipecat/audio/vad/vad_analyzer.py +++ b/src/pipecat/audio/vad/vad_analyzer.py @@ -127,7 +127,7 @@ class VADAnalyzer(ABC): pass @abstractmethod - def voice_confidence(self, buffer) -> float: + def voice_confidence(self, buffer: bytes) -> float: """Calculate voice activity confidence for the given audio buffer. Args: diff --git a/src/pipecat/transports/base_input.py b/src/pipecat/transports/base_input.py index b5f5a17c7..5f62045f1 100644 --- a/src/pipecat/transports/base_input.py +++ b/src/pipecat/transports/base_input.py @@ -48,7 +48,7 @@ from pipecat.metrics.metrics import MetricsData from pipecat.processors.frame_processor import FrameDirection, FrameProcessor from pipecat.transports.base_transport import TransportParams -AUDIO_INPUT_TIMEOUT_SECS = 0.5 +AUDIO_INPUT_TIMEOUT_SECS = 1.0 class BaseInputTransport(FrameProcessor): @@ -144,6 +144,17 @@ class BaseInputTransport(FrameProcessor): DeprecationWarning, ) + if self._params.vad_analyzer: + import warnings + + with warnings.catch_warnings(): + warnings.simplefilter("always") + warnings.warn( + "Parameter 'vad_analyzer' is deprecated, use `LLMUserAggregator`'s new " + "`vad_analyzer` parameter instead.", + DeprecationWarning, + ) + def enable_audio_in_stream_on_start(self, enabled: bool) -> None: """Enable or disable audio streaming on transport start. @@ -173,9 +184,23 @@ class BaseInputTransport(FrameProcessor): def vad_analyzer(self) -> Optional[VADAnalyzer]: """Get the Voice Activity Detection analyzer. + .. deprecated:: 0.0.101 + This method is deprecated and will be removed in a future version. + Use `LLMUserAggregator`'s new `vad_analyzer` parameter instead. + Returns: The VAD analyzer instance if configured, None otherwise. """ + import warnings + + with warnings.catch_warnings(): + warnings.simplefilter("always") + warnings.warn( + "Method 'vad_analyzer' is deprecated. Use `LLMUserAggregator`'s new " + "`vad_analyzer` parameter instead.", + DeprecationWarning, + ) + return self._params.vad_analyzer @property @@ -212,6 +237,13 @@ class BaseInputTransport(FrameProcessor): self._sample_rate = self._params.audio_in_sample_rate or frame.audio_in_sample_rate + # Start audio filter. + if self._params.audio_in_filter: + await self._params.audio_in_filter.start(self._sample_rate) + + ################################################################### + # DEPRECATED. + # Configure VAD analyzer. if self._params.vad_analyzer: self._params.vad_analyzer.set_sample_rate(self._sample_rate) @@ -227,10 +259,7 @@ class BaseInputTransport(FrameProcessor): await self.broadcast_frame( SpeechControlParamsFrame, vad_params=vad_params, turn_params=turn_params ) - - # Start audio filter. - if self._params.audio_in_filter: - await self._params.audio_in_filter.start(self._sample_rate) + ################################################################### async def stop(self, frame: EndFrame): """Stop the input transport and cleanup resources. @@ -341,9 +370,11 @@ class BaseInputTransport(FrameProcessor): elif isinstance(frame, StopFrame): await self.push_frame(frame, direction) await self.pause(frame) + ################################################################### + # DEPRECATED. elif isinstance(frame, VADParamsUpdateFrame): - if self.vad_analyzer: - self.vad_analyzer.set_params(frame.params) + if self._params.vad_analyzer: + self._params.vad_analyzer.set_params(frame.params) await self.broadcast_frame( SpeechControlParamsFrame, vad_params=frame.params, @@ -351,6 +382,7 @@ class BaseInputTransport(FrameProcessor): if self._params.turn_analyzer else None, ) + ################################################################### elif isinstance(frame, FilterUpdateSettingsFrame) and self._params.audio_in_filter: await self._params.audio_in_filter.process_frame(frame) # Other frames @@ -373,18 +405,89 @@ class BaseInputTransport(FrameProcessor): await self.cancel_task(self._audio_task) self._audio_task = None - async def _vad_analyze(self, audio_frame: InputAudioRawFrame) -> VADState: + async def _audio_task_handler(self): + """Main audio processing task handler for VAD and turn analysis.""" + vad_state: VADState = VADState.QUIET + # Skip timeout handling until the first audio frame arrives (e.g. client + # not yet connected). + audio_received = False + while True: + try: + frame: InputAudioRawFrame = await asyncio.wait_for( + self._audio_in_queue.get(), timeout=AUDIO_INPUT_TIMEOUT_SECS + ) + + # From now on, timeout should warn if there's no audio. + audio_received = True + + # If an audio filter is available, run it before VAD. + if self._params.audio_in_filter: + frame.audio = await self._params.audio_in_filter.filter(frame.audio) + + ################################################################### + # DEPRECATED. + # + # Check VAD and push event if necessary. We just care about + # changes from QUIET to SPEAKING and vice versa. + previous_vad_state = vad_state + if self._params.vad_analyzer: + vad_state = await self._deprecated_handle_vad(frame, vad_state) + + if self._params.turn_analyzer: + await self._deprecated_run_turn_analyzer(frame, vad_state, previous_vad_state) + + if self._params.vad_analyzer and vad_state == VADState.SPEAKING: + await self._deprecated_user_currently_speaking() + ################################################################### + + # Push audio downstream if passthrough is set. + if self._params.audio_in_passthrough: + await self.push_frame(frame) + + self._audio_in_queue.task_done() + except asyncio.TimeoutError: + if not audio_received: + continue + + logger.warning( + f"{self}: audio not received for more than {AUDIO_INPUT_TIMEOUT_SECS}" + ) + + ################################################################### + # DEPRECATED. + if self._user_speaking: + logger.warning( + "Forcing VAD user stopped speaking due to timeout receiving audio frame!" + ) + vad_state = VADState.QUIET + if self._params.turn_analyzer: + self._params.turn_analyzer.clear() + + if self._params.turn_analyzer: + await self._deprecated_handle_user_interruption(VADState.QUIET) + else: + await self.push_frame(VADUserStoppedSpeakingFrame()) + ################################################################### + + # + # DEPRECATED. + # + # The functions below are deprecated and should be removed once the old + # interruption strategies and turn analyzer are removed. + # + + async def _deprecated_vad_analyze(self, audio_frame: InputAudioRawFrame) -> VADState: """Analyze audio frame for voice activity.""" state = VADState.QUIET - if self.vad_analyzer: - state = await self.vad_analyzer.analyze_audio(audio_frame.audio) + if self._params.vad_analyzer: + state = await self._params.vad_analyzer.analyze_audio(audio_frame.audio) return state - async def _new_handle_vad( + async def _deprecated_new_handle_vad( self, audio_frame: InputAudioRawFrame, vad_state: VADState ) -> VADState: """Handle Voice Activity Detection results and generate appropriate frames.""" - new_vad_state = await self._vad_analyze(audio_frame) + new_vad_state = await self._deprecated_vad_analyze(audio_frame) if ( new_vad_state != vad_state and new_vad_state != VADState.STARTING @@ -398,72 +501,22 @@ class BaseInputTransport(FrameProcessor): vad_state = new_vad_state return vad_state - async def _handle_vad(self, audio_frame: InputAudioRawFrame, vad_state: VADState) -> VADState: + async def _deprecated_handle_vad( + self, audio_frame: InputAudioRawFrame, vad_state: VADState + ) -> VADState: """Handle Voice Activity Detection results and generate appropriate frames.""" if self._params.turn_analyzer or self._deprecated_openaillmcontext: - return await self._deprecated_handle_vad(audio_frame, vad_state) + return await self._deprecated_old_handle_vad(audio_frame, vad_state) else: - return await self._new_handle_vad(audio_frame, vad_state) + return await self._deprecated_new_handle_vad(audio_frame, vad_state) - async def _audio_task_handler(self): - """Main audio processing task handler for VAD and turn analysis.""" - vad_state: VADState = VADState.QUIET - while True: - try: - frame: InputAudioRawFrame = await asyncio.wait_for( - self._audio_in_queue.get(), timeout=AUDIO_INPUT_TIMEOUT_SECS - ) - - # If an audio filter is available, run it before VAD. - if self._params.audio_in_filter: - frame.audio = await self._params.audio_in_filter.filter(frame.audio) - - # Check VAD and push event if necessary. We just care about - # changes from QUIET to SPEAKING and vice versa. - previous_vad_state = vad_state - if self._params.vad_analyzer: - vad_state = await self._handle_vad(frame, vad_state) - - # DEPRECATED. - if self._params.turn_analyzer: - await self._deprecated_run_turn_analyzer(frame, vad_state, previous_vad_state) - - if vad_state == VADState.SPEAKING: - await self._user_currently_speaking() - - # Push audio downstream if passthrough is set. - if self._params.audio_in_passthrough: - await self.push_frame(frame) - - self._audio_in_queue.task_done() - except asyncio.TimeoutError: - if self._user_speaking: - logger.warning( - "Forcing VAD user stopped speaking due to timeout receiving audio frame!" - ) - vad_state = VADState.QUIET - if self._params.turn_analyzer: - self._params.turn_analyzer.clear() - - if self._params.turn_analyzer: - await self._deprecated_handle_user_interruption(VADState.QUIET) - else: - await self.push_frame(VADUserStoppedSpeakingFrame()) - - async def _user_currently_speaking(self): + async def _deprecated_user_currently_speaking(self): """Handle user speaking frame.""" diff_time = time.time() - self._user_speaking_frame_time if diff_time >= self._user_speaking_frame_period: await self.broadcast_frame(UserSpeakingFrame) self._user_speaking_frame_time = time.time() - # - # DEPRECATED. - # - # The functions below are deprecated and should be removed once the old - # interruption strategies and turn analyzer are removed. - # - async def _deprecated_handle_bot_started_speaking(self, frame: BotStartedSpeakingFrame): """Update bot speaking state when bot starts speaking.""" self._bot_speaking = True @@ -503,11 +556,11 @@ class BaseInputTransport(FrameProcessor): await self.broadcast_frame(UserStoppedSpeakingFrame, emulated=emulated) - async def _deprecated_handle_vad( + async def _deprecated_old_handle_vad( self, audio_frame: InputAudioRawFrame, vad_state: VADState ) -> VADState: """Handle Voice Activity Detection results and generate appropriate frames.""" - new_vad_state = await self._vad_analyze(audio_frame) + new_vad_state = await self._deprecated_vad_analyze(audio_frame) if ( new_vad_state != vad_state and new_vad_state != VADState.STARTING @@ -539,9 +592,7 @@ class BaseInputTransport(FrameProcessor): async def _deprecated_handle_end_of_turn(self): """Handle end-of-turn analysis and generate prediction results.""" - # Don't use self._params.turn_analyzer so we can keep showing one - # deprecation warning. - if self.turn_analyzer: + if self._params.turn_analyzer: state, prediction = await self._params.turn_analyzer.analyze_end_of_turn() await self._deprecated_handle_prediction_result(prediction) await self._deprecated_handle_end_of_turn_complete(state) diff --git a/src/pipecat/transports/base_transport.py b/src/pipecat/transports/base_transport.py index bbdd7fcfc..7879976ba 100644 --- a/src/pipecat/transports/base_transport.py +++ b/src/pipecat/transports/base_transport.py @@ -113,6 +113,11 @@ class TransportParams(BaseModel): instead. vad_analyzer: Voice Activity Detection analyzer instance. + + .. deprecated:: 0.0.101 + The `vad_analyzer` parameter is deprecated, use `LLMUSerAggregator`'s + new `vad_analyzer` parameter instead. + turn_analyzer: Turn-taking analyzer instance for conversation management. .. deprecated:: 0.0.99 From ddfedaf478bac23b5548dba4bc5482f7633d3478 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Aleix=20Conchillo=20Flaqu=C3=A9?= Date: Wed, 28 Jan 2026 10:13:34 -0800 Subject: [PATCH 0298/1060] audio(vad): add new VADController --- src/pipecat/audio/vad/vad_controller.py | 169 +++++++++++++++++++++ tests/test_vad_controller.py | 190 ++++++++++++++++++++++++ 2 files changed, 359 insertions(+) create mode 100644 src/pipecat/audio/vad/vad_controller.py create mode 100644 tests/test_vad_controller.py diff --git a/src/pipecat/audio/vad/vad_controller.py b/src/pipecat/audio/vad/vad_controller.py new file mode 100644 index 000000000..66f7199e5 --- /dev/null +++ b/src/pipecat/audio/vad/vad_controller.py @@ -0,0 +1,169 @@ +# +# Copyright (c) 2024-2026, Daily +# +# SPDX-License-Identifier: BSD 2-Clause License +# + +"""Voice Activity Detection controller for managing speech state transitions. + +This module provides a controller that wraps a VADAnalyzer to track speech state +and emit events when speech starts, stops, or is actively detected. +""" + +import time +from typing import Type + +from pipecat.audio.vad.vad_analyzer import VADAnalyzer, VADState +from pipecat.frames.frames import ( + Frame, + InputAudioRawFrame, + SpeechControlParamsFrame, + StartFrame, + VADParamsUpdateFrame, +) +from pipecat.processors.frame_processor import FrameDirection +from pipecat.utils.base_object import BaseObject + + +class VADController(BaseObject): + """Manages voice activity detection state and emits speech events. + + Wraps a `VADAnalyzer` to process audio and trigger events based on speech + state transitions. Tracks whether the user is speaking, quiet, or + transitioning between states. + + Event handlers available: + + - on_speech_started: Called when speech begins. + - on_speech_stopped: Called when speech ends. + - on_speech_activity: Called periodically while speech is detected. + - on_push_frame: Called when the controller wants to push a frame. + - on_broadcast_frame: Called when the controller wants to broadcast a frame. + + Example:: + + @vad_controller.event_handler("on_speech_started") + async def on_speech_started(controller): + ... + + @vad_controller.event_handler("on_speech_stopped") + async def on_speech_stopped(controller): + ... + + @vad_controller.event_handler("on_speech_activity") + async def on_speech_activity(controller): + ... + + @vad_controller.event_handler("on_push_frame") + async def on_push_frame(controller, frame: Frame, direction: FrameDirection): + ... + + @vad_controller.event_handler("on_broadcast_frame") + async def on_broadcast_frame(controller, frame_cls: Type[Frame], **kwargs): + ... + """ + + def __init__(self, vad_analyzer: VADAnalyzer, *, speech_activity_period: float = 0.2): + """Initialize the VAD controller. + + Args: + vad_analyzer: The `VADAnalyzer` instance for processing audio. + speech_activity_period: Minimum interval in seconds between + `on_speech_activity` events. Defaults to 0.2. + """ + super().__init__() + self._vad_analyzer = vad_analyzer + self._vad_state: VADState = VADState.QUIET + + # Last time a on_speech_activity was triggered. + self._speech_activity_time = 0 + # How often a on_speech_activity event should be triggered (value should + # be greater than the audio chunks to have any effect). + self._speech_activity_period = speech_activity_period + + self._register_event_handler("on_speech_started", sync=True) + self._register_event_handler("on_speech_stopped", sync=True) + self._register_event_handler("on_speech_activity", sync=True) + self._register_event_handler("on_push_frame", sync=True) + self._register_event_handler("on_broadcast_frame", sync=True) + + async def process_frame(self, frame: Frame): + """Process a frame and handle VAD-related events. + + Handles `StartFrame` to initialize the sample rate and `InputAudioRawFrame` + to analyze audio for voice activity. + + Args: + frame: The frame to process. + """ + if isinstance(frame, StartFrame): + await self._start(frame) + elif isinstance(frame, InputAudioRawFrame): + await self._handle_audio(frame) + elif isinstance(frame, VADParamsUpdateFrame): + self._vad_analyzer.set_params(frame.params) + await self.broadcast_frame(SpeechControlParamsFrame, vad_params=frame.params) + + async def _start(self, frame: StartFrame): + self._vad_analyzer.set_sample_rate(frame.audio_in_sample_rate) + + async def _handle_audio(self, frame: InputAudioRawFrame): + """Process an audio chunk and emit speech events as needed. + + Analyzes the audio for voice activity and triggers `on_speech_started`, + `on_speech_stopped`, or `on_speech_activity` events based on state changes. + + Args: + frame: Audio frame to process. + """ + self._vad_state = await self._handle_vad(frame.audio, self._vad_state) + + if self._vad_state == VADState.SPEAKING: + await self._call_event_handler("on_speech_activity") + + async def _handle_vad(self, audio: bytes, vad_state: VADState) -> VADState: + """Handle Voice Activity Detection results and trigger appropriate events.""" + new_vad_state = await self._vad_analyzer.analyze_audio(audio) + if ( + new_vad_state != vad_state + and new_vad_state != VADState.STARTING + and new_vad_state != VADState.STOPPING + ): + if new_vad_state == VADState.SPEAKING: + await self._call_event_handler("on_speech_started") + elif new_vad_state == VADState.QUIET: + await self._call_event_handler("on_speech_stopped") + + vad_state = new_vad_state + return vad_state + + async def _maybe_speech_activity(self): + """Handle user speaking frame.""" + diff_time = time.time() - self._speech_activity_time + if diff_time >= self._speech_activity_period: + self._speech_activity_time = time.time() + await self._call_event_handler("on_speech_activity") + + async def push_frame(self, frame: Frame, direction: FrameDirection = FrameDirection.DOWNSTREAM): + """Request a frame to be pushed through the pipeline. + + This emits an on_push_frame event that must be handled by a processor + to actually push the frame into the pipeline. + + Args: + frame: The frame to push. + direction: The direction to push the frame. + """ + await self._call_event_handler("on_push_frame", frame, direction) + + async def broadcast_frame(self, frame_cls: Type[Frame], **kwargs): + """Request a frame to be broadcast upstream and downstream. + + This emits an on_broadcast_frame event that must be handled by a processor + to actually broadcast the frame in the pipeline. + + Args: + frame_cls: The class of the frame to broadcast. + **kwargs: Arguments to pass to the frame constructor. + """ + await self._call_event_handler("on_broadcast_frame", frame_cls, **kwargs) diff --git a/tests/test_vad_controller.py b/tests/test_vad_controller.py new file mode 100644 index 000000000..b649a906f --- /dev/null +++ b/tests/test_vad_controller.py @@ -0,0 +1,190 @@ +# +# Copyright (c) 2024-2026, Daily +# +# SPDX-License-Identifier: BSD 2-Clause License +# + +import unittest +from typing import List + +from pipecat.audio.vad.vad_analyzer import VADAnalyzer, VADState +from pipecat.audio.vad.vad_controller import VADController +from pipecat.frames.frames import Frame, InputAudioRawFrame, StartFrame +from pipecat.processors.frame_processor import FrameDirection + + +class MockVADAnalyzer(VADAnalyzer): + """A mock VAD analyzer that returns a configurable state.""" + + def __init__(self): + """Initialize with default QUIET state.""" + super().__init__(sample_rate=16000) + self._next_state = VADState.QUIET + + def set_next_state(self, state: VADState): + """Set the state to return on the next analyze_audio call. + + Args: + state: The VADState to return. + """ + self._next_state = state + + def num_frames_required(self) -> int: + return 512 + + def voice_confidence(self, buffer: bytes) -> float: + return 0.9 + + async def analyze_audio(self, buffer: bytes) -> VADState: + """Return the configured state.""" + return self._next_state + + +class TestVADController(unittest.IsolatedAsyncioTestCase): + async def test_speech_started_event(self): + """Test that on_speech_started event is triggered when speech begins.""" + analyzer = MockVADAnalyzer() + controller = VADController(analyzer) + + speech_started = False + + @controller.event_handler("on_speech_started") + async def on_speech_started(_controller): + nonlocal speech_started + speech_started = True + + start_frame = StartFrame(audio_in_sample_rate=16000, audio_out_sample_rate=16000) + await controller.process_frame(start_frame) + + audio_frame = InputAudioRawFrame(audio=b"\x00" * 1024, sample_rate=16000, num_channels=1) + + # Process with QUIET state - no event should fire + analyzer.set_next_state(VADState.QUIET) + await controller.process_frame(audio_frame) + self.assertFalse(speech_started) + + # Process with SPEAKING state - event should fire + analyzer.set_next_state(VADState.SPEAKING) + await controller.process_frame(audio_frame) + self.assertTrue(speech_started) + + async def test_speech_stopped_event(self): + """Test that on_speech_stopped event is triggered when speech ends.""" + analyzer = MockVADAnalyzer() + controller = VADController(analyzer) + + speech_stopped = False + + @controller.event_handler("on_speech_stopped") + async def on_speech_stopped(_controller): + nonlocal speech_stopped + speech_stopped = True + + start_frame = StartFrame(audio_in_sample_rate=16000, audio_out_sample_rate=16000) + await controller.process_frame(start_frame) + + audio_frame = InputAudioRawFrame(audio=b"\x00" * 1024, sample_rate=16000, num_channels=1) + + # Start speaking + analyzer.set_next_state(VADState.SPEAKING) + await controller.process_frame(audio_frame) + self.assertFalse(speech_stopped) + + # Stop speaking - event should fire + analyzer.set_next_state(VADState.QUIET) + await controller.process_frame(audio_frame) + self.assertTrue(speech_stopped) + + async def test_speech_activity_event(self): + """Test that on_speech_activity event is triggered while speaking.""" + analyzer = MockVADAnalyzer() + controller = VADController(analyzer) + + activity_count = 0 + + @controller.event_handler("on_speech_activity") + async def on_speech_activity(_controller): + nonlocal activity_count + activity_count += 1 + + start_frame = StartFrame(audio_in_sample_rate=16000, audio_out_sample_rate=16000) + await controller.process_frame(start_frame) + + audio_frame = InputAudioRawFrame(audio=b"\x00" * 1024, sample_rate=16000, num_channels=1) + + # Activity events fire while in SPEAKING state + analyzer.set_next_state(VADState.SPEAKING) + await controller.process_frame(audio_frame) + await controller.process_frame(audio_frame) + self.assertEqual(activity_count, 2) + + async def test_push_frame_event(self): + """Test that push_frame emits on_push_frame event.""" + analyzer = MockVADAnalyzer() + controller = VADController(analyzer) + + pushed_frames: List[tuple] = [] + + @controller.event_handler("on_push_frame") + async def on_push_frame(_controller, frame: Frame, direction: FrameDirection): + pushed_frames.append((frame, direction)) + + test_frame = InputAudioRawFrame(audio=b"\x00" * 1024, sample_rate=16000, num_channels=1) + await controller.push_frame(test_frame, FrameDirection.DOWNSTREAM) + + self.assertEqual(len(pushed_frames), 1) + self.assertEqual(pushed_frames[0][0], test_frame) + self.assertEqual(pushed_frames[0][1], FrameDirection.DOWNSTREAM) + + async def test_broadcast_frame_event(self): + """Test that broadcast_frame emits on_broadcast_frame event.""" + analyzer = MockVADAnalyzer() + controller = VADController(analyzer) + + broadcast_calls: List[tuple] = [] + + @controller.event_handler("on_broadcast_frame") + async def on_broadcast_frame(_controller, frame_cls, **kwargs): + broadcast_calls.append((frame_cls, kwargs)) + + await controller.broadcast_frame( + InputAudioRawFrame, audio=b"\x00", sample_rate=16000, num_channels=1 + ) + + self.assertEqual(len(broadcast_calls), 1) + self.assertEqual(broadcast_calls[0][0], InputAudioRawFrame) + self.assertEqual(broadcast_calls[0][1]["sample_rate"], 16000) + + async def test_no_event_on_transitional_states(self): + """Test that STARTING and STOPPING states don't trigger events.""" + analyzer = MockVADAnalyzer() + controller = VADController(analyzer) + + events_triggered = [] + + @controller.event_handler("on_speech_started") + async def on_speech_started(_controller): + events_triggered.append("started") + + @controller.event_handler("on_speech_stopped") + async def on_speech_stopped(_controller): + events_triggered.append("stopped") + + start_frame = StartFrame(audio_in_sample_rate=16000, audio_out_sample_rate=16000) + await controller.process_frame(start_frame) + + audio_frame = InputAudioRawFrame(audio=b"\x00" * 1024, sample_rate=16000, num_channels=1) + + # STARTING is a transitional state - no event + analyzer.set_next_state(VADState.STARTING) + await controller.process_frame(audio_frame) + self.assertEqual(events_triggered, []) + + # STOPPING is a transitional state - no event + analyzer.set_next_state(VADState.STOPPING) + await controller.process_frame(audio_frame) + self.assertEqual(events_triggered, []) + + +if __name__ == "__main__": + unittest.main() From c92080b0d256be96698345204466e0a98e354726 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Aleix=20Conchillo=20Flaqu=C3=A9?= Date: Wed, 28 Jan 2026 10:45:09 -0800 Subject: [PATCH 0299/1060] LLMUserAggregator: add `vad_analyzer` and use VADController --- .../aggregators/llm_response_universal.py | 32 +++++++++++++++++++ 1 file changed, 32 insertions(+) diff --git a/src/pipecat/processors/aggregators/llm_response_universal.py b/src/pipecat/processors/aggregators/llm_response_universal.py index 200010591..13c3f24fb 100644 --- a/src/pipecat/processors/aggregators/llm_response_universal.py +++ b/src/pipecat/processors/aggregators/llm_response_universal.py @@ -21,6 +21,8 @@ from typing import Any, Dict, List, Literal, Optional, Set, Type from loguru import logger from pipecat.adapters.schemas.tools_schema import ToolsSchema +from pipecat.audio.vad.vad_analyzer import VADAnalyzer +from pipecat.audio.vad.vad_controller import VADController from pipecat.frames.frames import ( AssistantImageRawFrame, CancelFrame, @@ -50,6 +52,7 @@ from pipecat.frames.frames import ( TextFrame, TranscriptionFrame, UserImageRawFrame, + UserSpeakingFrame, UserStartedSpeakingFrame, UserStoppedSpeakingFrame, VADUserStartedSpeakingFrame, @@ -85,12 +88,14 @@ class LLMUserAggregatorParams: If set, the aggregator will emit an `on_user_turn_idle` event when the user has been idle (not speaking) for this duration. Set to None to disable idle detection. + vad_analyzer: Voice Activity Detection analyzer instance. """ user_turn_strategies: Optional[UserTurnStrategies] = None user_mute_strategies: List[BaseUserMuteStrategy] = field(default_factory=list) user_turn_stop_timeout: float = 5.0 user_idle_timeout: Optional[float] = None + vad_analyzer: Optional[VADAnalyzer] = None @dataclass @@ -384,6 +389,18 @@ class LLMUserAggregator(LLMContextAggregator): "on_user_turn_idle", self._on_user_turn_idle ) + # VAD controller + self._vad_controller: Optional[VADController] = None + if self._params.vad_analyzer: + self._vad_controller = VADController(self._params.vad_analyzer) + self._vad_controller.add_event_handler("on_speech_started", self._on_vad_speech_started) + self._vad_controller.add_event_handler("on_speech_stopped", self._on_vad_speech_stopped) + self._vad_controller.add_event_handler( + "on_speech_activity", self._on_vad_speech_activity + ) + self._vad_controller.add_event_handler("on_push_frame", self._on_push_frame) + self._vad_controller.add_event_handler("on_broadcast_frame", self._on_broadcast_frame) + async def cleanup(self): """Clean up processor resources.""" await super().cleanup() @@ -401,6 +418,9 @@ class LLMUserAggregator(LLMContextAggregator): if await self._maybe_mute_frame(frame): return + if self._vad_controller: + await self._vad_controller.process_frame(frame) + if isinstance(frame, StartFrame): # Push StartFrame before start(), because we want StartFrame to be # processed by every processor before any other frame is processed. @@ -575,6 +595,18 @@ class LLMUserAggregator(LLMContextAggregator): async def _on_broadcast_frame(self, controller, frame_cls: Type[Frame], **kwargs): await self.broadcast_frame(frame_cls, **kwargs) + async def _on_vad_speech_started(self, controller): + await self.queue_frame(VADUserStartedSpeakingFrame()) + await self.broadcast_frame(VADUserStartedSpeakingFrame) + + async def _on_vad_speech_stopped(self, controller): + await self.queue_frame(VADUserStoppedSpeakingFrame()) + await self.broadcast_frame(VADUserStoppedSpeakingFrame) + + async def _on_vad_speech_activity(self, controller): + await self.queue_frame(UserSpeakingFrame()) + await self.broadcast_frame(UserSpeakingFrame) + async def _on_user_turn_started( self, controller: UserTurnController, From b486f35c70398b93e152e6b75cfa76b610238199 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Aleix=20Conchillo=20Flaqu=C3=A9?= Date: Wed, 28 Jan 2026 10:58:58 -0800 Subject: [PATCH 0300/1060] audio: add new VADProcessor --- src/pipecat/processors/audio/vad_processor.py | 100 ++++++++++++ tests/test_vad_processor.py | 143 ++++++++++++++++++ 2 files changed, 243 insertions(+) create mode 100644 src/pipecat/processors/audio/vad_processor.py create mode 100644 tests/test_vad_processor.py diff --git a/src/pipecat/processors/audio/vad_processor.py b/src/pipecat/processors/audio/vad_processor.py new file mode 100644 index 000000000..2076eeeb3 --- /dev/null +++ b/src/pipecat/processors/audio/vad_processor.py @@ -0,0 +1,100 @@ +# +# Copyright (c) 2024-2026, Daily +# +# SPDX-License-Identifier: BSD 2-Clause License +# + +"""Voice Activity Detection processor for detecting speech in audio streams. + +This module provides a VADProcessor that wraps a VADController to process +audio frames and push VAD-related frames into the pipeline. +""" + +from typing import Type + +from loguru import logger + +from pipecat.audio.vad.vad_analyzer import VADAnalyzer +from pipecat.audio.vad.vad_controller import VADController +from pipecat.frames.frames import ( + Frame, + UserSpeakingFrame, + VADUserStartedSpeakingFrame, + VADUserStoppedSpeakingFrame, +) +from pipecat.processors.frame_processor import FrameDirection, FrameProcessor + + +class VADProcessor(FrameProcessor): + """Processes audio frames through voice activity detection. + + This processor wraps a VADController to detect speech in audio streams + and push VAD frames into the pipeline: + + - ``VADUserStartedSpeakingFrame``: Pushed when speech begins. + - ``VADUserStoppedSpeakingFrame``: Pushed when speech ends. + - ``UserSpeakingFrame``: Pushed periodically while speech is detected. + + Example:: + + vad_processor = VADProcessor(vad_analyzer=SileroVADAnalyzer()) + """ + + def __init__( + self, + *, + vad_analyzer: VADAnalyzer, + speech_activity_period: float = 0.2, + **kwargs, + ): + """Initialize the VAD processor. + + Args: + vad_analyzer: The VADAnalyzer instance for processing audio. + speech_activity_period: Minimum interval in seconds between + UserSpeakingFrame pushes. Defaults to 0.2. + **kwargs: Additional arguments passed to parent class. + """ + super().__init__(**kwargs) + self._vad_controller = VADController( + vad_analyzer, speech_activity_period=speech_activity_period + ) + + # Push VAD frames when speech events are detected + @self._vad_controller.event_handler("on_speech_started") + async def on_speech_started(_controller): + logger.debug(f"{self}: User started speaking") + await self.push_frame(VADUserStartedSpeakingFrame()) + + @self._vad_controller.event_handler("on_speech_stopped") + async def on_speech_stopped(_controller): + logger.debug(f"{self}: User stopped speaking") + await self.push_frame(VADUserStoppedSpeakingFrame()) + + @self._vad_controller.event_handler("on_speech_activity") + async def on_speech_activity(_controller): + await self.push_frame(UserSpeakingFrame()) + + # Wire up frame pushing from controller to processor + @self._vad_controller.event_handler("on_push_frame") + async def on_push_frame(_controller, frame: Frame, direction: FrameDirection): + await self.push_frame(frame, direction) + + @self._vad_controller.event_handler("on_broadcast_frame") + async def on_broadcast_frame(_controller, frame_cls: Type[Frame], **kwargs): + await self.broadcast_frame(frame_cls, **kwargs) + + async def process_frame(self, frame: Frame, direction: FrameDirection): + """Process a frame through VAD and forward it. + + Args: + frame: The frame to process. + direction: The direction of frame flow in the pipeline. + """ + await super().process_frame(frame, direction) + + # Let the VAD controller handle the frame + await self._vad_controller.process_frame(frame) + + # Always forward the frame + await self.push_frame(frame, direction) diff --git a/tests/test_vad_processor.py b/tests/test_vad_processor.py new file mode 100644 index 000000000..2acb4f29d --- /dev/null +++ b/tests/test_vad_processor.py @@ -0,0 +1,143 @@ +# +# Copyright (c) 2024-2026, Daily +# +# SPDX-License-Identifier: BSD 2-Clause License +# + +import unittest +from typing import List + +from pipecat.audio.vad.vad_analyzer import VADAnalyzer, VADState +from pipecat.frames.frames import ( + InputAudioRawFrame, + UserSpeakingFrame, + VADUserStartedSpeakingFrame, + VADUserStoppedSpeakingFrame, +) +from pipecat.processors.audio.vad_processor import VADProcessor +from pipecat.tests.utils import run_test + + +class MockVADAnalyzer(VADAnalyzer): + """A mock VAD analyzer that returns states from a predefined sequence.""" + + def __init__(self, states: List[VADState]): + super().__init__(sample_rate=16000) + self._states = list(states) + self._call_index = 0 + + def num_frames_required(self) -> int: + return 512 + + def voice_confidence(self, buffer: bytes) -> float: + return 0.9 + + async def analyze_audio(self, buffer: bytes) -> VADState: + if self._call_index < len(self._states): + state = self._states[self._call_index] + self._call_index += 1 + return state + return VADState.QUIET + + +class TestVADProcessor(unittest.IsolatedAsyncioTestCase): + def _make_audio_frame(self): + return InputAudioRawFrame(audio=b"\x00" * 1024, sample_rate=16000, num_channels=1) + + async def test_forwards_audio_frames(self): + """Test that audio frames are forwarded downstream.""" + analyzer = MockVADAnalyzer([VADState.QUIET]) + processor = VADProcessor(vad_analyzer=analyzer) + + await run_test( + processor, + frames_to_send=[self._make_audio_frame()], + expected_down_frames=[InputAudioRawFrame], + ) + + async def test_pushes_started_speaking_frame(self): + """Test that VADUserStartedSpeakingFrame is pushed when speech starts.""" + analyzer = MockVADAnalyzer([VADState.QUIET, VADState.SPEAKING]) + processor = VADProcessor(vad_analyzer=analyzer) + + await run_test( + processor, + frames_to_send=[self._make_audio_frame(), self._make_audio_frame()], + expected_down_frames=[ + InputAudioRawFrame, + VADUserStartedSpeakingFrame, + UserSpeakingFrame, + InputAudioRawFrame, + ], + ) + + async def test_pushes_stopped_speaking_frame(self): + """Test that VADUserStoppedSpeakingFrame is pushed when speech stops.""" + analyzer = MockVADAnalyzer([VADState.SPEAKING, VADState.QUIET]) + processor = VADProcessor(vad_analyzer=analyzer) + + await run_test( + processor, + frames_to_send=[self._make_audio_frame(), self._make_audio_frame()], + expected_down_frames=[ + VADUserStartedSpeakingFrame, + UserSpeakingFrame, + InputAudioRawFrame, + VADUserStoppedSpeakingFrame, + InputAudioRawFrame, + ], + ) + + async def test_pushes_user_speaking_frame(self): + """Test that UserSpeakingFrame is pushed while speaking.""" + analyzer = MockVADAnalyzer([VADState.SPEAKING, VADState.SPEAKING]) + processor = VADProcessor(vad_analyzer=analyzer) + + await run_test( + processor, + frames_to_send=[self._make_audio_frame(), self._make_audio_frame()], + expected_down_frames=[ + VADUserStartedSpeakingFrame, + UserSpeakingFrame, + InputAudioRawFrame, + UserSpeakingFrame, + InputAudioRawFrame, + ], + ) + + async def test_no_vad_frames_on_starting_state(self): + """Test that STARTING state doesn't push VAD frames.""" + analyzer = MockVADAnalyzer([VADState.STARTING]) + processor = VADProcessor(vad_analyzer=analyzer) + + await run_test( + processor, + frames_to_send=[self._make_audio_frame()], + expected_down_frames=[InputAudioRawFrame], + ) + + async def test_no_vad_frames_on_stopping_state(self): + """Test that STOPPING state doesn't push VAD frames.""" + analyzer = MockVADAnalyzer([VADState.STOPPING]) + processor = VADProcessor(vad_analyzer=analyzer) + + await run_test( + processor, + frames_to_send=[self._make_audio_frame()], + expected_down_frames=[InputAudioRawFrame], + ) + + async def test_no_vad_frames_when_quiet(self): + """Test that no VAD frames are pushed when staying quiet.""" + analyzer = MockVADAnalyzer([VADState.QUIET, VADState.QUIET]) + processor = VADProcessor(vad_analyzer=analyzer) + + await run_test( + processor, + frames_to_send=[self._make_audio_frame(), self._make_audio_frame()], + expected_down_frames=[InputAudioRawFrame, InputAudioRawFrame], + ) + + +if __name__ == "__main__": + unittest.main() From 305ab44132f86aff0af5af0ab9cfd8345bab8dc3 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Aleix=20Conchillo=20Flaqu=C3=A9?= Date: Wed, 28 Jan 2026 11:01:52 -0800 Subject: [PATCH 0301/1060] tests: add unittest.main() call --- tests/test_aggregators.py | 4 ++++ tests/test_audio_buffer_processor.py | 4 ++++ tests/test_context_aggregators.py | 4 ++++ tests/test_context_aggregators_universal.py | 4 ++++ tests/test_daily_transport_service.py | 4 ++++ tests/test_dtmf_aggregator.py | 4 ++++ tests/test_filters.py | 4 ++++ tests/test_frame_processor.py | 4 ++++ tests/test_function_calling_adapters.py | 4 ++++ tests/test_interruption_strategies.py | 4 ++++ tests/test_ivr_navigation.py | 4 ++++ tests/test_krisp_sdk_manager.py | 4 ++++ tests/test_langchain.py | 4 ++++ tests/test_llm_response.py | 4 ++++ tests/test_markdown_text_filter.py | 4 ++++ tests/test_pattern_pair_aggregator.py | 4 ++++ tests/test_pipeline.py | 4 ++++ tests/test_piper_tts.py | 5 +++++ tests/test_producer_consumer.py | 4 ++++ tests/test_protobuf_serializer.py | 4 ++++ tests/test_rnnoise_cancellation.py | 4 ++++ tests/test_rnnoise_filter.py | 4 ++++ tests/test_rnnoise_resampling.py | 4 ++++ tests/test_run_inference.py | 4 ++++ tests/test_simple_text_aggregator.py | 4 ++++ tests/test_skip_tags_aggregator.py | 4 ++++ tests/test_stt_mute_filter.py | 4 ++++ tests/test_transcript_processor.py | 4 ++++ tests/test_user_idle_controller.py | 4 ++++ tests/test_user_idle_processor.py | 4 ++++ tests/test_user_mute_strategy.py | 4 ++++ tests/test_user_turn_controller.py | 4 ++++ tests/test_user_turn_processor.py | 4 ++++ tests/test_user_turn_start_strategy.py | 4 ++++ tests/test_user_turn_stop_strategy.py | 4 ++++ tests/test_utils_network.py | 4 ++++ tests/test_utils_string.py | 4 ++++ 37 files changed, 149 insertions(+) diff --git a/tests/test_aggregators.py b/tests/test_aggregators.py index 73ccf6b04..6563d324c 100644 --- a/tests/test_aggregators.py +++ b/tests/test_aggregators.py @@ -74,3 +74,7 @@ class TestGatedAggregator(unittest.IsolatedAsyncioTestCase): frames_to_send=frames_to_send, expected_down_frames=expected_down_frames, ) + + +if __name__ == "__main__": + unittest.main() diff --git a/tests/test_audio_buffer_processor.py b/tests/test_audio_buffer_processor.py index faebe4ef5..4d3c588bc 100644 --- a/tests/test_audio_buffer_processor.py +++ b/tests/test_audio_buffer_processor.py @@ -115,3 +115,7 @@ class TestAudioBufferProcessor(unittest.IsolatedAsyncioTestCase): self.assertEqual(merged_audio[6:8], bot_audio[2:4]) self.assertEqual(len(self.processor._user_audio_buffer), 0) self.assertEqual(len(self.processor._bot_audio_buffer), 0) + + +if __name__ == "__main__": + unittest.main() diff --git a/tests/test_context_aggregators.py b/tests/test_context_aggregators.py index 17a24113e..24dae0b4c 100644 --- a/tests/test_context_aggregators.py +++ b/tests/test_context_aggregators.py @@ -1055,3 +1055,7 @@ class TestLLMAssistantAggregator( 0, "Hello Pipecat. Here's some code: ```python\nprint('Hello, World!')\n``` ```javascript\nconsole.log('Hello, World!');\n``` And some more: ```html\n
Hello, World!
\n``` Hope that helps!", ) + + +if __name__ == "__main__": + unittest.main() diff --git a/tests/test_context_aggregators_universal.py b/tests/test_context_aggregators_universal.py index 63f1fef9a..e840fd8f5 100644 --- a/tests/test_context_aggregators_universal.py +++ b/tests/test_context_aggregators_universal.py @@ -566,3 +566,7 @@ class TestLLMAssistantAggregator(unittest.IsolatedAsyncioTestCase): # The pending text should be emitted on EndFrame self.assertEqual(len(stop_messages), 1) self.assertEqual(stop_messages[0].content, "Hello from Pipecat!") + + +if __name__ == "__main__": + unittest.main() diff --git a/tests/test_daily_transport_service.py b/tests/test_daily_transport_service.py index 5ebf28b83..117c859ce 100644 --- a/tests/test_daily_transport_service.py +++ b/tests/test_daily_transport_service.py @@ -90,3 +90,7 @@ class TestDailyTransport(unittest.IsolatedAsyncioTestCase): camera.write_frame.assert_called_with(b"test") mic.write_frames.assert_called() """ + + +if __name__ == "__main__": + unittest.main() diff --git a/tests/test_dtmf_aggregator.py b/tests/test_dtmf_aggregator.py index dd9f4d835..827720b9c 100644 --- a/tests/test_dtmf_aggregator.py +++ b/tests/test_dtmf_aggregator.py @@ -240,3 +240,7 @@ class TestDTMFAggregator(unittest.IsolatedAsyncioTestCase): ] self.assertEqual(len(transcription_frames), 1) self.assertEqual(transcription_frames[0].text, "DTMF: 0123456789*#") + + +if __name__ == "__main__": + unittest.main() diff --git a/tests/test_filters.py b/tests/test_filters.py index 1d56fab38..b62239aeb 100644 --- a/tests/test_filters.py +++ b/tests/test_filters.py @@ -118,3 +118,7 @@ class TestWakeCheckFilter(unittest.IsolatedAsyncioTestCase): expected_down_frames=expected_down_frames, ) assert received_down[-1].text == "Phrase 1" + + +if __name__ == "__main__": + unittest.main() diff --git a/tests/test_frame_processor.py b/tests/test_frame_processor.py index 2df35a10e..f44181858 100644 --- a/tests/test_frame_processor.py +++ b/tests/test_frame_processor.py @@ -347,3 +347,7 @@ class TestFrameProcessor(unittest.IsolatedAsyncioTestCase): self.assertIs(up_frame.items, orig.items) self.assertIs(down_frame.metadata, orig.metadata) self.assertIs(up_frame.metadata, orig.metadata) + + +if __name__ == "__main__": + unittest.main() diff --git a/tests/test_function_calling_adapters.py b/tests/test_function_calling_adapters.py index 5df59ed79..348754f47 100644 --- a/tests/test_function_calling_adapters.py +++ b/tests/test_function_calling_adapters.py @@ -204,3 +204,7 @@ class TestFunctionAdapters(unittest.TestCase): } ] assert AWSBedrockLLMAdapter().to_provider_tools_format(self.tools_def) == expected + + +if __name__ == "__main__": + unittest.main() diff --git a/tests/test_interruption_strategies.py b/tests/test_interruption_strategies.py index 220649a53..d4aff2a7a 100644 --- a/tests/test_interruption_strategies.py +++ b/tests/test_interruption_strategies.py @@ -22,3 +22,7 @@ class TestMinWordsInterruptionStrategy(unittest.IsolatedAsyncioTestCase): self.assertEqual(await strategy.should_interrupt(), False) await strategy.append_text(" How are you?") self.assertEqual(await strategy.should_interrupt(), True) + + +if __name__ == "__main__": + unittest.main() diff --git a/tests/test_ivr_navigation.py b/tests/test_ivr_navigation.py index 420ea2c2f..ee43bdf62 100644 --- a/tests/test_ivr_navigation.py +++ b/tests/test_ivr_navigation.py @@ -353,3 +353,7 @@ class TestIVRNavigation(unittest.IsolatedAsyncioTestCase): expected_down_frames=expected_down_frames, expected_up_frames=expected_up_frames, ) + + +if __name__ == "__main__": + unittest.main() diff --git a/tests/test_krisp_sdk_manager.py b/tests/test_krisp_sdk_manager.py index 7c774ab85..78a4d955f 100644 --- a/tests/test_krisp_sdk_manager.py +++ b/tests/test_krisp_sdk_manager.py @@ -194,3 +194,7 @@ class TestSampleRateConversion: expected_rates = [8000, 16000, 24000, 32000, 44100, 48000] for rate in expected_rates: assert rate in KRISP_SAMPLE_RATES + + +if __name__ == "__main__": + unittest.main() diff --git a/tests/test_langchain.py b/tests/test_langchain.py index 1a3e1fe7d..8ec8905b4 100644 --- a/tests/test_langchain.py +++ b/tests/test_langchain.py @@ -97,3 +97,7 @@ class TestLangchain(unittest.IsolatedAsyncioTestCase): self.assertEqual( context_aggregator.assistant().messages[-1]["content"], self.expected_response ) + + +if __name__ == "__main__": + unittest.main() diff --git a/tests/test_llm_response.py b/tests/test_llm_response.py index 51296f40b..8de7dda2d 100644 --- a/tests/test_llm_response.py +++ b/tests/test_llm_response.py @@ -134,3 +134,7 @@ class TestLLMFullResponseAggregator(unittest.IsolatedAsyncioTestCase): expected_down_frames=expected_down_frames, ) assert completion_ok + + +if __name__ == "__main__": + unittest.main() diff --git a/tests/test_markdown_text_filter.py b/tests/test_markdown_text_filter.py index 7f6268953..250bc685a 100644 --- a/tests/test_markdown_text_filter.py +++ b/tests/test_markdown_text_filter.py @@ -244,3 +244,7 @@ class TestMarkdownTextFilter(unittest.IsolatedAsyncioTestCase): "bold and italic", "Text filtering should be re-enabled", ) + + +if __name__ == "__main__": + unittest.main() diff --git a/tests/test_pattern_pair_aggregator.py b/tests/test_pattern_pair_aggregator.py index f4b660feb..bcc8d18f7 100644 --- a/tests/test_pattern_pair_aggregator.py +++ b/tests/test_pattern_pair_aggregator.py @@ -192,3 +192,7 @@ class TestPatternPairAggregator(unittest.IsolatedAsyncioTestCase): # Buffer should be empty self.assertEqual(self.aggregator.text.text, "") + + +if __name__ == "__main__": + unittest.main() diff --git a/tests/test_pipeline.py b/tests/test_pipeline.py index 4b1b57e29..dda9e583d 100644 --- a/tests/test_pipeline.py +++ b/tests/test_pipeline.py @@ -528,3 +528,7 @@ class TestPipelineTask(unittest.IsolatedAsyncioTestCase): await task.run(PipelineTaskParams(loop=asyncio.get_event_loop())) except asyncio.CancelledError: assert error_received + + +if __name__ == "__main__": + unittest.main() diff --git a/tests/test_piper_tts.py b/tests/test_piper_tts.py index 8d877099c..0ce14bd85 100644 --- a/tests/test_piper_tts.py +++ b/tests/test_piper_tts.py @@ -7,6 +7,7 @@ """Tests for PiperTTSService.""" import asyncio +import unittest import aiohttp import pytest @@ -143,3 +144,7 @@ async def test_run_piper_tts_error(aiohttp_client): assert "status: 404" in up_frames[0].error, ( "ErrorFrame should contain details about the 404" ) + + +if __name__ == "__main__": + unittest.main() diff --git a/tests/test_producer_consumer.py b/tests/test_producer_consumer.py index 4e9804c1b..0fd3f862c 100644 --- a/tests/test_producer_consumer.py +++ b/tests/test_producer_consumer.py @@ -118,3 +118,7 @@ class TestProducerConsumerProcessor(unittest.IsolatedAsyncioTestCase): frames_to_send=frames_to_send, expected_down_frames=expected_down_frames, ) + + +if __name__ == "__main__": + unittest.main() diff --git a/tests/test_protobuf_serializer.py b/tests/test_protobuf_serializer.py index 99df3f96b..14d7d1aa7 100644 --- a/tests/test_protobuf_serializer.py +++ b/tests/test_protobuf_serializer.py @@ -38,3 +38,7 @@ class TestProtobufFrameSerializer(unittest.IsolatedAsyncioTestCase): self.assertEqual(frame.audio, audio_frame.audio) self.assertEqual(frame.sample_rate, audio_frame.sample_rate) self.assertEqual(frame.num_channels, audio_frame.num_channels) + + +if __name__ == "__main__": + unittest.main() diff --git a/tests/test_rnnoise_cancellation.py b/tests/test_rnnoise_cancellation.py index 386dcd424..a90b4f1e9 100644 --- a/tests/test_rnnoise_cancellation.py +++ b/tests/test_rnnoise_cancellation.py @@ -171,3 +171,7 @@ class TestRNNoiseCancellation(unittest.IsolatedAsyncioTestCase): self.assertLess(mse_output, mse_input, "MSE did not improve") print("Test Passed: Noise cancellation verified.") + + +if __name__ == "__main__": + unittest.main() diff --git a/tests/test_rnnoise_filter.py b/tests/test_rnnoise_filter.py index db3ac7825..853ea0c77 100644 --- a/tests/test_rnnoise_filter.py +++ b/tests/test_rnnoise_filter.py @@ -143,3 +143,7 @@ class TestRNNoiseFilter(unittest.IsolatedAsyncioTestCase): ) await filter.stop() + + +if __name__ == "__main__": + unittest.main() diff --git a/tests/test_rnnoise_resampling.py b/tests/test_rnnoise_resampling.py index 060c9e802..83bf65edc 100644 --- a/tests/test_rnnoise_resampling.py +++ b/tests/test_rnnoise_resampling.py @@ -132,3 +132,7 @@ class TestRNNoiseResampling(unittest.IsolatedAsyncioTestCase): ) print("Test Passed: Resampling logic verified (with mocked RNNoise).") + + +if __name__ == "__main__": + unittest.main() diff --git a/tests/test_run_inference.py b/tests/test_run_inference.py index ea08445a9..eb18a5fda 100644 --- a/tests/test_run_inference.py +++ b/tests/test_run_inference.py @@ -509,3 +509,7 @@ async def test_aws_bedrock_run_inference_client_exception(): with patch.object(service._aws_session, "client", return_value=mock_context_manager): with pytest.raises(Exception, match="Bedrock API Error"): await service.run_inference(mock_context) + + +if __name__ == "__main__": + unittest.main() diff --git a/tests/test_simple_text_aggregator.py b/tests/test_simple_text_aggregator.py index 6baab4f26..ef51cfc49 100644 --- a/tests/test_simple_text_aggregator.py +++ b/tests/test_simple_text_aggregator.py @@ -123,3 +123,7 @@ class TestSimpleTextAggregator(unittest.IsolatedAsyncioTestCase): # flush() returns any remaining text (the "W" in this case) result = await self.aggregator.flush() assert result.text == "W" + + +if __name__ == "__main__": + unittest.main() diff --git a/tests/test_skip_tags_aggregator.py b/tests/test_skip_tags_aggregator.py index 1f550198d..c7fea22c3 100644 --- a/tests/test_skip_tags_aggregator.py +++ b/tests/test_skip_tags_aggregator.py @@ -62,3 +62,7 @@ class TestSkipTagsAggregator(unittest.IsolatedAsyncioTestCase): self.assertEqual(result.text, text) self.assertEqual(self.aggregator.text.text, "") self.assertEqual(self.aggregator.text.type, "sentence") + + +if __name__ == "__main__": + unittest.main() diff --git a/tests/test_stt_mute_filter.py b/tests/test_stt_mute_filter.py index 39631d7e8..5682aaf22 100644 --- a/tests/test_stt_mute_filter.py +++ b/tests/test_stt_mute_filter.py @@ -326,3 +326,7 @@ class TestSTTMuteFilter(unittest.IsolatedAsyncioTestCase): frames_to_send=frames_to_send, expected_down_frames=expected_returned_frames, ) + + +if __name__ == "__main__": + unittest.main() diff --git a/tests/test_transcript_processor.py b/tests/test_transcript_processor.py index 99e231c90..1dfdd58a3 100644 --- a/tests/test_transcript_processor.py +++ b/tests/test_transcript_processor.py @@ -792,3 +792,7 @@ class TestThoughtTranscription(unittest.IsolatedAsyncioTestCase): # Verify no updates since thought wasn't properly started self.assertEqual(len(received_updates), 0) + + +if __name__ == "__main__": + unittest.main() diff --git a/tests/test_user_idle_controller.py b/tests/test_user_idle_controller.py index 5de665353..4b6cbe1d3 100644 --- a/tests/test_user_idle_controller.py +++ b/tests/test_user_idle_controller.py @@ -214,3 +214,7 @@ class TestUserIdleController(unittest.IsolatedAsyncioTestCase): self.assertGreater(third_count, second_count) await controller.cleanup() + + +if __name__ == "__main__": + unittest.main() diff --git a/tests/test_user_idle_processor.py b/tests/test_user_idle_processor.py index eec3abe5a..3a0169ec7 100644 --- a/tests/test_user_idle_processor.py +++ b/tests/test_user_idle_processor.py @@ -218,3 +218,7 @@ class TestUserIdleProcessor(unittest.IsolatedAsyncioTestCase): ) assert callback_called.is_set(), "Idle callback not called after bot speech" + + +if __name__ == "__main__": + unittest.main() diff --git a/tests/test_user_mute_strategy.py b/tests/test_user_mute_strategy.py index d8261877e..07724dbfa 100644 --- a/tests/test_user_mute_strategy.py +++ b/tests/test_user_mute_strategy.py @@ -137,3 +137,7 @@ class TestFunctionCallUserMuteStrategy(unittest.IsolatedAsyncioTestCase): ) ) self.assertFalse(await strategy.process_frame(InterruptionFrame())) + + +if __name__ == "__main__": + unittest.main() diff --git a/tests/test_user_turn_controller.py b/tests/test_user_turn_controller.py index d8f642594..5362847ec 100644 --- a/tests/test_user_turn_controller.py +++ b/tests/test_user_turn_controller.py @@ -190,3 +190,7 @@ class TestUserTurnController(unittest.IsolatedAsyncioTestCase): self.assertTrue(should_start) self.assertTrue(should_stop) self.assertTrue(timeout) + + +if __name__ == "__main__": + unittest.main() diff --git a/tests/test_user_turn_processor.py b/tests/test_user_turn_processor.py index 6a3dd3ef3..ab4243cc4 100644 --- a/tests/test_user_turn_processor.py +++ b/tests/test_user_turn_processor.py @@ -152,3 +152,7 @@ class TestUserTurnProcessor(unittest.IsolatedAsyncioTestCase): self.assertTrue(should_start) self.assertTrue(should_stop) self.assertFalse(timeout) + + +if __name__ == "__main__": + unittest.main() diff --git a/tests/test_user_turn_start_strategy.py b/tests/test_user_turn_start_strategy.py index dabd4593b..2b4f7eb43 100644 --- a/tests/test_user_turn_start_strategy.py +++ b/tests/test_user_turn_start_strategy.py @@ -199,3 +199,7 @@ class TestExternalUserTurnStartStrategy(unittest.IsolatedAsyncioTestCase): await strategy.process_frame(UserStartedSpeakingFrame()) self.assertTrue(should_start) + + +if __name__ == "__main__": + unittest.main() diff --git a/tests/test_user_turn_stop_strategy.py b/tests/test_user_turn_stop_strategy.py index f0d336bbf..d930705fd 100644 --- a/tests/test_user_turn_stop_strategy.py +++ b/tests/test_user_turn_stop_strategy.py @@ -506,3 +506,7 @@ class TestExternalUserTurnStopStrategy(unittest.IsolatedAsyncioTestCase): await strategy.process_frame(UserStoppedSpeakingFrame()) self.assertTrue(should_start) + + +if __name__ == "__main__": + unittest.main() diff --git a/tests/test_utils_network.py b/tests/test_utils_network.py index 616ed896a..1f0048cc5 100644 --- a/tests/test_utils_network.py +++ b/tests/test_utils_network.py @@ -32,3 +32,7 @@ class TestUtilsNetwork(unittest.IsolatedAsyncioTestCase): assert exponential_backoff_time(attempt=4, min_wait=1, max_wait=20, multiplier=2) == 16 assert exponential_backoff_time(attempt=5, min_wait=1, max_wait=20, multiplier=2) == 20 assert exponential_backoff_time(attempt=6, min_wait=1, max_wait=20, multiplier=2) == 20 + + +if __name__ == "__main__": + unittest.main() diff --git a/tests/test_utils_string.py b/tests/test_utils_string.py index 0f4844748..4afde718c 100644 --- a/tests/test_utils_string.py +++ b/tests/test_utils_string.py @@ -232,3 +232,7 @@ class TestStartEndTags(unittest.IsolatedAsyncioTestCase): ("", ""), 41, ) + + +if __name__ == "__main__": + unittest.main() From 307aeaeda09d9bcd4d1079e1fa6f435666d68922 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Aleix=20Conchillo=20Flaqu=C3=A9?= Date: Wed, 28 Jan 2026 11:58:08 -0800 Subject: [PATCH 0302/1060] examples: update with LLMUserAggregatorParams vad_analyzer and VADProcessor --- .../foundational/01-say-one-thing-piper.py | 5 ++- .../foundational/01-say-one-thing-rime.py | 5 ++- examples/foundational/01-say-one-thing.py | 5 ++- examples/foundational/01c-nvidia-riva-tts.py | 5 ++- examples/foundational/02-llm-say-one-thing.py | 5 ++- examples/foundational/03-still-frame.py | 5 ++- .../foundational/03b-still-frame-imagen.py | 5 ++- .../04-transports-small-webrtc.py | 2 +- examples/foundational/04a-transports-daily.py | 2 +- .../foundational/04b-transports-livekit.py | 2 +- .../foundational/05-sync-speech-and-image.py | 5 ++- .../foundational/06-listen-and-respond.py | 9 ++--- examples/foundational/06a-image-sync.py | 8 ++--- .../07-interruptible-cartesia-http.py | 9 ++--- examples/foundational/07-interruptible.py | 9 ++--- .../07a-interruptible-speechmatics-vad.py | 5 ++- .../07a-interruptible-speechmatics.py | 9 ++--- .../07b-interruptible-langchain.py | 9 ++--- .../07c-interruptible-deepgram-flux.py | 5 ++- .../07c-interruptible-deepgram-http.py | 9 ++--- .../07c-interruptible-deepgram-sagemaker.py | 9 ++--- .../07c-interruptible-deepgram-vad.py | 5 ++- .../07c-interruptible-deepgram.py | 9 ++--- .../07d-interruptible-elevenlabs-http.py | 9 ++--- .../07d-interruptible-elevenlabs.py | 9 ++--- .../07e-interruptible-playht-http.py | 9 ++--- .../foundational/07e-interruptible-playht.py | 9 ++--- .../07f-interruptible-azure-http.py | 9 ++--- .../foundational/07f-interruptible-azure.py | 9 ++--- .../foundational/07g-interruptible-openai.py | 9 ++--- .../07h-interruptible-openpipe.py | 9 ++--- .../foundational/07i-interruptible-xtts.py | 9 ++--- .../07j-interruptible-gladia-vad.py | 13 ++++--- .../foundational/07j-interruptible-gladia.py | 9 ++--- .../foundational/07k-interruptible-lmnt.py | 9 ++--- .../foundational/07l-interruptible-groq.py | 9 ++--- .../07m-interruptible-aws-strands.py | 10 +++--- .../foundational/07m-interruptible-aws.py | 9 ++--- .../07n-interruptible-gemini-image.py | 8 ++--- .../foundational/07n-interruptible-gemini.py | 9 ++--- .../07n-interruptible-google-http.py | 9 ++--- .../foundational/07n-interruptible-google.py | 9 ++--- .../07o-interruptible-assemblyai.py | 9 ++--- .../07p-interruptible-krisp-viva.py | 9 ++--- .../foundational/07p-interruptible-krisp.py | 9 ++--- .../07q-interruptible-rime-http.py | 9 ++--- .../foundational/07q-interruptible-rime.py | 9 ++--- .../foundational/07r-interruptible-nvidia.py | 9 ++--- .../07s-interruptible-google-audio-in.py | 9 ++--- .../foundational/07t-interruptible-fish.py | 9 ++--- .../07v-interruptible-neuphonic-http.py | 9 ++--- .../07v-interruptible-neuphonic.py | 9 ++--- .../foundational/07w-interruptible-fal.py | 9 ++--- .../foundational/07x-interruptible-local.py | 2 +- .../foundational/07y-interruptible-minimax.py | 9 ++--- .../07z-interruptible-sarvam-http.py | 9 ++--- .../foundational/07z-interruptible-sarvam.py | 9 ++--- .../foundational/07za-interruptible-soniox.py | 4 +-- .../07zb-interruptible-inworld-http.py | 4 +-- .../07zb-interruptible-inworld.py | 4 +-- .../07zc-interruptible-asyncai-http.py | 9 ++--- .../07zc-interruptible-asyncai.py | 9 ++--- .../07zd-interruptible-aicoustics.py | 5 ++- .../foundational/07ze-interruptible-hume.py | 9 ++--- .../07zf-interruptible-gradium.py | 9 ++--- .../foundational/07zg-interruptible-camb.py | 9 ++--- .../07zh-interruptible-hathora.py | 9 ++--- .../foundational/08-custom-frame-processor.py | 8 ++--- examples/foundational/09-mirror.py | 5 ++- examples/foundational/09a-local-mirror.py | 5 ++- examples/foundational/10-wake-phrase.py | 9 ++--- examples/foundational/11-sound-effects.py | 9 ++--- .../foundational/12-describe-image-openai.py | 8 ++--- .../12a-describe-image-anthropic.py | 8 ++--- .../foundational/12b-describe-image-aws.py | 8 ++--- .../12c-describe-image-gemini-flash.py | 8 ++--- .../12d-describe-image-moondream.py | 9 ++--- .../foundational/13-whisper-transcription.py | 5 ++- .../13b-deepgram-transcription.py | 5 ++- .../foundational/13c-gladia-transcription.py | 5 ++- .../foundational/13c-gladia-translation.py | 5 ++- .../13d-assemblyai-transcription.py | 5 ++- examples/foundational/13e-whisper-mlx.py | 5 ++- .../13f-cartesia-transcription.py | 5 ++- .../13g-sambanova-transcription.py | 5 ++- .../13h-speechmatics-transcription.py | 5 ++- .../13k-elevenlabs-transcription.py | 5 ++- examples/foundational/14-function-calling.py | 9 ++--- .../14a-function-calling-anthropic.py | 9 ++--- .../14c-function-calling-together.py | 9 ++--- .../14d-function-calling-anthropic-video.py | 8 ++--- .../14d-function-calling-aws-video.py | 8 ++--- ...14d-function-calling-gemini-flash-video.py | 8 ++--- .../14d-function-calling-moondream-video.py | 8 ++--- .../14d-function-calling-openai-video.py | 8 ++--- .../14e-function-calling-google.py | 8 ++--- .../foundational/14f-function-calling-groq.py | 9 ++--- .../foundational/14g-function-calling-grok.py | 9 ++--- .../14h-function-calling-azure.py | 9 ++--- .../14i-function-calling-fireworks.py | 9 ++--- .../14j-function-calling-nvidia.py | 9 ++--- .../14k-function-calling-cerebras.py | 9 ++--- .../14l-function-calling-deepseek.py | 9 ++--- .../14m-function-calling-openrouter.py | 9 ++--- .../14n-function-calling-perplexity.py | 9 ++--- ...o-function-calling-gemini-openai-format.py | 5 ++- .../14p-function-calling-gemini-vertex-ai.py | 9 ++--- .../foundational/14q-function-calling-qwen.py | 9 ++--- .../foundational/14r-function-calling-aws.py | 9 ++--- .../14s-function-calling-sambanova.py | 9 ++--- .../14t-function-calling-direct.py | 9 ++--- .../14u-function-calling-ollama.py | 9 ++--- .../14v-function-calling-openai.py | 9 ++--- .../14w-function-calling-mistral.py | 9 ++--- .../14x-function-calling-openpipe.py | 9 ++--- examples/foundational/15-switch-voices.py | 9 ++--- examples/foundational/15a-switch-languages.py | 9 ++--- .../16-gpu-container-local-bot.py | 9 ++--- examples/foundational/17-detect-user-idle.py | 9 ++--- examples/foundational/18-gstreamer-filesrc.py | 5 ++- .../18a-gstreamer-videotestsrc.py | 5 ++- .../foundational/19-openai-realtime-beta.py | 5 ++- examples/foundational/19-openai-realtime.py | 5 ++- .../foundational/19a-azure-realtime-beta.py | 5 ++- examples/foundational/19a-azure-realtime.py | 5 ++- .../19b-openai-realtime-beta-text.py | 5 ++- .../foundational/19b-openai-realtime-text.py | 5 ++- .../19c-openai-realtime-live-video.py | 5 ++- .../20a-persistent-context-openai.py | 9 ++--- ...persistent-context-openai-realtime-beta.py | 5 ++- .../20b-persistent-context-openai-realtime.py | 5 ++- .../20c-persistent-context-anthropic.py | 9 ++--- .../20d-persistent-context-gemini.py | 8 ++--- .../20e-persistent-context-aws-nova-sonic.py | 5 ++- .../foundational/21a-tavus-video-service.py | 8 ++--- .../foundational/22-natural-conversation.py | 10 +++--- .../22b-natural-conversation-proposal.py | 10 +++--- .../22c-natural-conversation-mixed-llms.py | 10 +++--- .../22d-natural-conversation-gemini-audio.py | 10 +++--- .../foundational/23-bot-background-sound.py | 5 ++- .../foundational/24-user-mute-strategy.py | 9 ++--- examples/foundational/25-google-audio-in.py | 5 ++- examples/foundational/26-gemini-live.py | 12 +++---- .../26a-gemini-live-transcription.py | 32 +++++++---------- .../26b-gemini-live-function-calling.py | 36 +++++++++---------- .../foundational/26c-gemini-live-video.py | 31 ++++++++-------- examples/foundational/26d-gemini-live-text.py | 36 +++++++++---------- .../26e-gemini-live-google-search.py | 36 +++++++++---------- .../foundational/26f-gemini-live-files-api.py | 24 ++++++++----- .../26g-gemini-live-groundingMetadata.py | 24 ++++++++----- ...26h-gemini-live-vertex-function-calling.py | 36 +++++++++---------- .../26i-gemini-live-graceful-end.py | 36 +++++++++---------- examples/foundational/27-simli-layer.py | 8 ++--- .../foundational/28-user-assistant-turns.py | 9 ++--- .../foundational/29-turn-tracking-observer.py | 9 ++--- examples/foundational/30-observer.py | 9 ++--- .../32-gemini-grounding-metadata.py | 9 ++--- examples/foundational/33-gemini-rag.py | 9 ++--- examples/foundational/34-audio-recording.py | 9 ++--- .../35-pattern-pair-voice-switching.py | 9 ++--- .../foundational/36-user-email-gathering.py | 9 ++--- examples/foundational/37-mem0.py | 9 ++--- examples/foundational/38-smart-turn-fal.py | 9 ++--- .../38a-smart-turn-local-coreml.py | 9 ++--- examples/foundational/38b-smart-turn-local.py | 9 ++--- examples/foundational/39-mcp-stdio.py | 8 ++--- .../foundational/39a-mcp-streamable-http.py | 9 ++--- .../39b-mcp-streamable-http-gemini-live.py | 9 ++--- examples/foundational/39c-multiple-mcp.py | 8 ++--- examples/foundational/40-aws-nova-sonic.py | 5 ++- .../foundational/42-interruption-config.py | 9 ++--- .../foundational/43a-heygen-video-service.py | 8 ++--- .../foundational/44-voicemail-detection.py | 9 ++--- .../45-before-and-after-events.py | 9 ++--- examples/foundational/46-video-processing.py | 4 +-- examples/foundational/47-sentry-metrics.py | 9 ++--- examples/foundational/48-service-switcher.py | 9 ++--- .../foundational/49a-thinking-anthropic.py | 9 ++--- examples/foundational/49b-thinking-google.py | 9 ++--- .../49c-thinking-functions-anthropic.py | 9 ++--- .../49d-thinking-functions-google.py | 9 ++--- examples/foundational/50-ultravox-realtime.py | 5 ++- examples/foundational/52-live-translation.py | 9 ++--- .../53-concurrent-llm-evaluation.py | 18 ++++++---- 184 files changed, 628 insertions(+), 1028 deletions(-) diff --git a/examples/foundational/01-say-one-thing-piper.py b/examples/foundational/01-say-one-thing-piper.py index f6700f886..cace8dbeb 100644 --- a/examples/foundational/01-say-one-thing-piper.py +++ b/examples/foundational/01-say-one-thing-piper.py @@ -24,9 +24,8 @@ from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams load_dotenv(override=True) -# We store functions so objects (e.g. SileroVADAnalyzer) don't get -# instantiated. The function will be called when the desired transport gets -# selected. +# We use lambdas to defer transport parameter creation until the transport +# type is selected at runtime. transport_params = { "daily": lambda: DailyParams(audio_out_enabled=True), "twilio": lambda: FastAPIWebsocketParams(audio_out_enabled=True), diff --git a/examples/foundational/01-say-one-thing-rime.py b/examples/foundational/01-say-one-thing-rime.py index d6b4bad5f..2a31efa68 100644 --- a/examples/foundational/01-say-one-thing-rime.py +++ b/examples/foundational/01-say-one-thing-rime.py @@ -23,9 +23,8 @@ from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams load_dotenv(override=True) -# We store functions so objects (e.g. SileroVADAnalyzer) don't get -# instantiated. The function will be called when the desired transport gets -# selected. +# We use lambdas to defer transport parameter creation until the transport +# type is selected at runtime. transport_params = { "daily": lambda: DailyParams(audio_out_enabled=True), "twilio": lambda: FastAPIWebsocketParams(audio_out_enabled=True), diff --git a/examples/foundational/01-say-one-thing.py b/examples/foundational/01-say-one-thing.py index 4ad179bdb..7df26701c 100644 --- a/examples/foundational/01-say-one-thing.py +++ b/examples/foundational/01-say-one-thing.py @@ -23,9 +23,8 @@ from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams load_dotenv(override=True) -# We store functions so objects (e.g. SileroVADAnalyzer) don't get -# instantiated. The function will be called when the desired transport gets -# selected. +# We use lambdas to defer transport parameter creation until the transport +# type is selected at runtime. transport_params = { "daily": lambda: DailyParams(audio_out_enabled=True), "twilio": lambda: FastAPIWebsocketParams(audio_out_enabled=True), diff --git a/examples/foundational/01c-nvidia-riva-tts.py b/examples/foundational/01c-nvidia-riva-tts.py index 5a42fed19..2be99c5b4 100644 --- a/examples/foundational/01c-nvidia-riva-tts.py +++ b/examples/foundational/01c-nvidia-riva-tts.py @@ -23,9 +23,8 @@ from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams load_dotenv(override=True) -# We store functions so objects (e.g. SileroVADAnalyzer) don't get -# instantiated. The function will be called when the desired transport gets -# selected. +# We use lambdas to defer transport parameter creation until the transport +# type is selected at runtime. transport_params = { "daily": lambda: DailyParams(audio_out_enabled=True), "twilio": lambda: FastAPIWebsocketParams(audio_out_enabled=True), diff --git a/examples/foundational/02-llm-say-one-thing.py b/examples/foundational/02-llm-say-one-thing.py index ef41d271e..f4fbfcbe0 100644 --- a/examples/foundational/02-llm-say-one-thing.py +++ b/examples/foundational/02-llm-say-one-thing.py @@ -25,9 +25,8 @@ from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams load_dotenv(override=True) -# We store functions so objects (e.g. SileroVADAnalyzer) don't get -# instantiated. The function will be called when the desired transport gets -# selected. +# We use lambdas to defer transport parameter creation until the transport +# type is selected at runtime. transport_params = { "daily": lambda: DailyParams(audio_out_enabled=True), "twilio": lambda: FastAPIWebsocketParams(audio_out_enabled=True), diff --git a/examples/foundational/03-still-frame.py b/examples/foundational/03-still-frame.py index 985dcdc9e..def125165 100644 --- a/examples/foundational/03-still-frame.py +++ b/examples/foundational/03-still-frame.py @@ -23,9 +23,8 @@ from pipecat.transports.daily.transport import DailyParams load_dotenv(override=True) -# We store functions so objects (e.g. SileroVADAnalyzer) don't get -# instantiated. The function will be called when the desired transport gets -# selected. +# We use lambdas to defer transport parameter creation until the transport +# type is selected at runtime. transport_params = { "daily": lambda: DailyParams( video_out_enabled=True, diff --git a/examples/foundational/03b-still-frame-imagen.py b/examples/foundational/03b-still-frame-imagen.py index 0fa371344..259072959 100644 --- a/examples/foundational/03b-still-frame-imagen.py +++ b/examples/foundational/03b-still-frame-imagen.py @@ -22,9 +22,8 @@ from pipecat.transports.daily.transport import DailyParams load_dotenv(override=True) -# We store functions so objects (e.g. SileroVADAnalyzer) don't get -# instantiated. The function will be called when the desired transport gets -# selected. +# We use lambdas to defer transport parameter creation until the transport +# type is selected at runtime. transport_params = { "daily": lambda: DailyParams( video_out_enabled=True, diff --git a/examples/foundational/04-transports-small-webrtc.py b/examples/foundational/04-transports-small-webrtc.py index 8ed1291ba..0ccff0229 100644 --- a/examples/foundational/04-transports-small-webrtc.py +++ b/examples/foundational/04-transports-small-webrtc.py @@ -64,7 +64,6 @@ async def run_example(webrtc_connection: SmallWebRTCConnection): params=TransportParams( audio_in_enabled=True, audio_out_enabled=True, - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), ) @@ -91,6 +90,7 @@ async def run_example(webrtc_connection: SmallWebRTCConnection): user_turn_strategies=UserTurnStrategies( stop=[TurnAnalyzerUserTurnStopStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3())] ), + vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), ) diff --git a/examples/foundational/04a-transports-daily.py b/examples/foundational/04a-transports-daily.py index 27321e028..9a2a9288b 100644 --- a/examples/foundational/04a-transports-daily.py +++ b/examples/foundational/04a-transports-daily.py @@ -49,7 +49,6 @@ async def main(): audio_in_enabled=True, audio_out_enabled=True, transcription_enabled=True, - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), ) @@ -76,6 +75,7 @@ async def main(): TurnAnalyzerUserTurnStopStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3()) ] ), + vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), ) diff --git a/examples/foundational/04b-transports-livekit.py b/examples/foundational/04b-transports-livekit.py index c58e6b5fd..8f100e720 100644 --- a/examples/foundational/04b-transports-livekit.py +++ b/examples/foundational/04b-transports-livekit.py @@ -54,7 +54,6 @@ async def main(): params=LiveKitParams( audio_in_enabled=True, audio_out_enabled=True, - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), ) @@ -84,6 +83,7 @@ async def main(): user_turn_strategies=UserTurnStrategies( stop=[TurnAnalyzerUserTurnStopStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3())] ), + vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), ) diff --git a/examples/foundational/05-sync-speech-and-image.py b/examples/foundational/05-sync-speech-and-image.py index bc0a35ea3..c1b142670 100644 --- a/examples/foundational/05-sync-speech-and-image.py +++ b/examples/foundational/05-sync-speech-and-image.py @@ -65,9 +65,8 @@ class MonthPrepender(FrameProcessor): await self.push_frame(frame, direction) -# We store functions so objects (e.g. SileroVADAnalyzer) don't get -# instantiated. The function will be called when the desired transport gets -# selected. +# We use lambdas to defer transport parameter creation until the transport +# type is selected at runtime. transport_params = { "daily": lambda: DailyParams( audio_out_enabled=True, diff --git a/examples/foundational/06-listen-and-respond.py b/examples/foundational/06-listen-and-respond.py index 95e59b167..b23e85766 100644 --- a/examples/foundational/06-listen-and-respond.py +++ b/examples/foundational/06-listen-and-respond.py @@ -62,24 +62,20 @@ class MetricsLogger(FrameProcessor): await self.push_frame(frame, direction) -# We store functions so objects (e.g. SileroVADAnalyzer) don't get -# instantiated. The function will be called when the desired transport gets -# selected. +# We use lambdas to defer transport parameter creation until the transport +# type is selected at runtime. transport_params = { "daily": lambda: DailyParams( audio_in_enabled=True, audio_out_enabled=True, - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), "twilio": lambda: FastAPIWebsocketParams( audio_in_enabled=True, audio_out_enabled=True, - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), "webrtc": lambda: TransportParams( audio_in_enabled=True, audio_out_enabled=True, - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), } @@ -112,6 +108,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): user_turn_strategies=UserTurnStrategies( stop=[TurnAnalyzerUserTurnStopStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3())] ), + vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), ) diff --git a/examples/foundational/06a-image-sync.py b/examples/foundational/06a-image-sync.py index cc4664578..8ff1a6069 100644 --- a/examples/foundational/06a-image-sync.py +++ b/examples/foundational/06a-image-sync.py @@ -77,9 +77,8 @@ class ImageSyncAggregator(FrameProcessor): await self.push_frame(frame, direction) -# We store functions so objects (e.g. SileroVADAnalyzer) don't get -# instantiated. The function will be called when the desired transport gets -# selected. +# We use lambdas to defer transport parameter creation until the transport +# type is selected at runtime. transport_params = { "daily": lambda: DailyParams( audio_in_enabled=True, @@ -87,7 +86,6 @@ transport_params = { video_out_enabled=True, video_out_width=1024, video_out_height=1024, - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), "webrtc": lambda: TransportParams( audio_in_enabled=True, @@ -95,7 +93,6 @@ transport_params = { video_out_enabled=True, video_out_width=1024, video_out_height=1024, - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), } @@ -126,6 +123,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): user_turn_strategies=UserTurnStrategies( stop=[TurnAnalyzerUserTurnStopStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3())] ), + vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), ) diff --git a/examples/foundational/07-interruptible-cartesia-http.py b/examples/foundational/07-interruptible-cartesia-http.py index 2d0a9f6d1..b5a7eb026 100644 --- a/examples/foundational/07-interruptible-cartesia-http.py +++ b/examples/foundational/07-interruptible-cartesia-http.py @@ -35,24 +35,20 @@ from pipecat.turns.user_turn_strategies import UserTurnStrategies load_dotenv(override=True) -# We store functions so objects (e.g. SileroVADAnalyzer) don't get -# instantiated. The function will be called when the desired transport gets -# selected. +# We use lambdas to defer transport parameter creation until the transport +# type is selected at runtime. transport_params = { "daily": lambda: DailyParams( audio_in_enabled=True, audio_out_enabled=True, - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), "twilio": lambda: FastAPIWebsocketParams( audio_in_enabled=True, audio_out_enabled=True, - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), "webrtc": lambda: TransportParams( audio_in_enabled=True, audio_out_enabled=True, - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), } @@ -83,6 +79,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): user_turn_strategies=UserTurnStrategies( stop=[TurnAnalyzerUserTurnStopStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3())] ), + vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), ) diff --git a/examples/foundational/07-interruptible.py b/examples/foundational/07-interruptible.py index d9bb5a449..a016bdeaf 100644 --- a/examples/foundational/07-interruptible.py +++ b/examples/foundational/07-interruptible.py @@ -34,24 +34,20 @@ from pipecat.turns.user_turn_strategies import UserTurnStrategies load_dotenv(override=True) -# We store functions so objects (e.g. SileroVADAnalyzer) don't get -# instantiated. The function will be called when the desired transport gets -# selected. +# We use lambdas to defer transport parameter creation until the transport +# type is selected at runtime. transport_params = { "daily": lambda: DailyParams( audio_in_enabled=True, audio_out_enabled=True, - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), "twilio": lambda: FastAPIWebsocketParams( audio_in_enabled=True, audio_out_enabled=True, - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), "webrtc": lambda: TransportParams( audio_in_enabled=True, audio_out_enabled=True, - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), } @@ -82,6 +78,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): user_turn_strategies=UserTurnStrategies( stop=[TurnAnalyzerUserTurnStopStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3())] ), + vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), ) diff --git a/examples/foundational/07a-interruptible-speechmatics-vad.py b/examples/foundational/07a-interruptible-speechmatics-vad.py index 864e9635d..d75ae2b1f 100644 --- a/examples/foundational/07a-interruptible-speechmatics-vad.py +++ b/examples/foundational/07a-interruptible-speechmatics-vad.py @@ -33,9 +33,8 @@ from pipecat.turns.user_turn_strategies import ExternalUserTurnStrategies load_dotenv(override=True) -# We store functions so objects (e.g. SileroVADAnalyzer) don't get -# instantiated. The function will be called when the desired transport gets -# selected. +# We use lambdas to defer transport parameter creation until the transport +# type is selected at runtime. transport_params = { "daily": lambda: DailyParams( audio_in_enabled=True, diff --git a/examples/foundational/07a-interruptible-speechmatics.py b/examples/foundational/07a-interruptible-speechmatics.py index 78959eccf..ebca5caf6 100644 --- a/examples/foundational/07a-interruptible-speechmatics.py +++ b/examples/foundational/07a-interruptible-speechmatics.py @@ -37,24 +37,20 @@ from pipecat.turns.user_turn_strategies import UserTurnStrategies load_dotenv(override=True) -# We store functions so objects (e.g. SileroVADAnalyzer) don't get -# instantiated. The function will be called when the desired transport gets -# selected. +# We use lambdas to defer transport parameter creation until the transport +# type is selected at runtime. transport_params = { "daily": lambda: DailyParams( audio_in_enabled=True, audio_out_enabled=True, - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), "twilio": lambda: FastAPIWebsocketParams( audio_in_enabled=True, audio_out_enabled=True, - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), "webrtc": lambda: TransportParams( audio_in_enabled=True, audio_out_enabled=True, - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), } @@ -125,6 +121,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): TurnAnalyzerUserTurnStopStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3()) ] ), + vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), ) diff --git a/examples/foundational/07b-interruptible-langchain.py b/examples/foundational/07b-interruptible-langchain.py index b9b5c6177..af1f3082a 100644 --- a/examples/foundational/07b-interruptible-langchain.py +++ b/examples/foundational/07b-interruptible-langchain.py @@ -50,24 +50,20 @@ def get_session_history(session_id: str) -> BaseChatMessageHistory: return message_store[session_id] -# We store functions so objects (e.g. SileroVADAnalyzer) don't get -# instantiated. The function will be called when the desired transport gets -# selected. +# We use lambdas to defer transport parameter creation until the transport +# type is selected at runtime. transport_params = { "daily": lambda: DailyParams( audio_in_enabled=True, audio_out_enabled=True, - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), "twilio": lambda: FastAPIWebsocketParams( audio_in_enabled=True, audio_out_enabled=True, - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), "webrtc": lambda: TransportParams( audio_in_enabled=True, audio_out_enabled=True, - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), } @@ -109,6 +105,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): user_turn_strategies=UserTurnStrategies( stop=[TurnAnalyzerUserTurnStopStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3())] ), + vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), ) diff --git a/examples/foundational/07c-interruptible-deepgram-flux.py b/examples/foundational/07c-interruptible-deepgram-flux.py index 5a1a63e7e..e51a30c1b 100644 --- a/examples/foundational/07c-interruptible-deepgram-flux.py +++ b/examples/foundational/07c-interruptible-deepgram-flux.py @@ -32,9 +32,8 @@ from pipecat.turns.user_turn_strategies import ExternalUserTurnStrategies load_dotenv(override=True) -# We store functions so objects (e.g. SileroVADAnalyzer) don't get -# instantiated. The function will be called when the desired transport gets -# selected. +# We use lambdas to defer transport parameter creation until the transport +# type is selected at runtime. transport_params = { "daily": lambda: DailyParams( audio_in_enabled=True, diff --git a/examples/foundational/07c-interruptible-deepgram-http.py b/examples/foundational/07c-interruptible-deepgram-http.py index 190d37280..fe2d5c5d8 100644 --- a/examples/foundational/07c-interruptible-deepgram-http.py +++ b/examples/foundational/07c-interruptible-deepgram-http.py @@ -37,24 +37,20 @@ from pipecat.turns.user_turn_strategies import UserTurnStrategies load_dotenv(override=True) -# We store functions so objects (e.g. SileroVADAnalyzer) don't get -# instantiated. The function will be called when the desired transport gets -# selected. +# We use lambdas to defer transport parameter creation until the transport +# type is selected at runtime. transport_params = { "daily": lambda: DailyParams( audio_in_enabled=True, audio_out_enabled=True, - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), "twilio": lambda: FastAPIWebsocketParams( audio_in_enabled=True, audio_out_enabled=True, - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), "webrtc": lambda: TransportParams( audio_in_enabled=True, audio_out_enabled=True, - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), } @@ -89,6 +85,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): TurnAnalyzerUserTurnStopStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3()) ] ), + vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), ) diff --git a/examples/foundational/07c-interruptible-deepgram-sagemaker.py b/examples/foundational/07c-interruptible-deepgram-sagemaker.py index a625c1eea..20edf1693 100644 --- a/examples/foundational/07c-interruptible-deepgram-sagemaker.py +++ b/examples/foundational/07c-interruptible-deepgram-sagemaker.py @@ -36,24 +36,20 @@ from pipecat.turns.user_turn_strategies import UserTurnStrategies load_dotenv(override=True) -# We store functions so objects (e.g. SileroVADAnalyzer) don't get -# instantiated. The function will be called when the desired transport gets -# selected. +# We use lambdas to defer transport parameter creation until the transport +# type is selected at runtime. transport_params = { "daily": lambda: DailyParams( audio_in_enabled=True, audio_out_enabled=True, - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), "twilio": lambda: FastAPIWebsocketParams( audio_in_enabled=True, audio_out_enabled=True, - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), "webrtc": lambda: TransportParams( audio_in_enabled=True, audio_out_enabled=True, - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), } @@ -92,6 +88,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): user_turn_strategies=UserTurnStrategies( stop=[TurnAnalyzerUserTurnStopStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3())] ), + vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), ) diff --git a/examples/foundational/07c-interruptible-deepgram-vad.py b/examples/foundational/07c-interruptible-deepgram-vad.py index e7dca7701..62fb29dff 100644 --- a/examples/foundational/07c-interruptible-deepgram-vad.py +++ b/examples/foundational/07c-interruptible-deepgram-vad.py @@ -33,9 +33,8 @@ from pipecat.turns.user_turn_strategies import ExternalUserTurnStrategies load_dotenv(override=True) -# We store functions so objects (e.g. SileroVADAnalyzer) don't get -# instantiated. The function will be called when the desired transport gets -# selected. +# We use lambdas to defer transport parameter creation until the transport +# type is selected at runtime. transport_params = { "daily": lambda: DailyParams( audio_in_enabled=True, diff --git a/examples/foundational/07c-interruptible-deepgram.py b/examples/foundational/07c-interruptible-deepgram.py index 7e81b5a74..f4fa91485 100644 --- a/examples/foundational/07c-interruptible-deepgram.py +++ b/examples/foundational/07c-interruptible-deepgram.py @@ -36,24 +36,20 @@ from pipecat.turns.user_turn_strategies import UserTurnStrategies load_dotenv(override=True) -# We store functions so objects (e.g. SileroVADAnalyzer) don't get -# instantiated. The function will be called when the desired transport gets -# selected. +# We use lambdas to defer transport parameter creation until the transport +# type is selected at runtime. transport_params = { "daily": lambda: DailyParams( audio_in_enabled=True, audio_out_enabled=True, - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), "twilio": lambda: FastAPIWebsocketParams( audio_in_enabled=True, audio_out_enabled=True, - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), "webrtc": lambda: TransportParams( audio_in_enabled=True, audio_out_enabled=True, - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), } @@ -81,6 +77,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): user_turn_strategies=UserTurnStrategies( stop=[TurnAnalyzerUserTurnStopStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3())] ), + vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), ) diff --git a/examples/foundational/07d-interruptible-elevenlabs-http.py b/examples/foundational/07d-interruptible-elevenlabs-http.py index d289258c1..612527e8d 100644 --- a/examples/foundational/07d-interruptible-elevenlabs-http.py +++ b/examples/foundational/07d-interruptible-elevenlabs-http.py @@ -37,24 +37,20 @@ from pipecat.turns.user_turn_strategies import UserTurnStrategies load_dotenv(override=True) -# We store functions so objects (e.g. SileroVADAnalyzer) don't get -# instantiated. The function will be called when the desired transport gets -# selected. +# We use lambdas to defer transport parameter creation until the transport +# type is selected at runtime. transport_params = { "daily": lambda: DailyParams( audio_in_enabled=True, audio_out_enabled=True, - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), "twilio": lambda: FastAPIWebsocketParams( audio_in_enabled=True, audio_out_enabled=True, - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), "webrtc": lambda: TransportParams( audio_in_enabled=True, audio_out_enabled=True, - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), } @@ -93,6 +89,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): TurnAnalyzerUserTurnStopStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3()) ] ), + vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), ) diff --git a/examples/foundational/07d-interruptible-elevenlabs.py b/examples/foundational/07d-interruptible-elevenlabs.py index 4850cd473..103d94d48 100644 --- a/examples/foundational/07d-interruptible-elevenlabs.py +++ b/examples/foundational/07d-interruptible-elevenlabs.py @@ -36,24 +36,20 @@ from pipecat.turns.user_turn_strategies import UserTurnStrategies load_dotenv(override=True) -# We store functions so objects (e.g. SileroVADAnalyzer) don't get -# instantiated. The function will be called when the desired transport gets -# selected. +# We use lambdas to defer transport parameter creation until the transport +# type is selected at runtime. transport_params = { "daily": lambda: DailyParams( audio_in_enabled=True, audio_out_enabled=True, - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), "twilio": lambda: FastAPIWebsocketParams( audio_in_enabled=True, audio_out_enabled=True, - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), "webrtc": lambda: TransportParams( audio_in_enabled=True, audio_out_enabled=True, - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), } @@ -84,6 +80,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): user_turn_strategies=UserTurnStrategies( stop=[TurnAnalyzerUserTurnStopStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3())] ), + vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), ) diff --git a/examples/foundational/07e-interruptible-playht-http.py b/examples/foundational/07e-interruptible-playht-http.py index 0d731d6e4..c982e45fd 100644 --- a/examples/foundational/07e-interruptible-playht-http.py +++ b/examples/foundational/07e-interruptible-playht-http.py @@ -35,24 +35,20 @@ from pipecat.turns.user_turn_strategies import UserTurnStrategies load_dotenv(override=True) -# We store functions so objects (e.g. SileroVADAnalyzer) don't get -# instantiated. The function will be called when the desired transport gets -# selected. +# We use lambdas to defer transport parameter creation until the transport +# type is selected at runtime. transport_params = { "daily": lambda: DailyParams( audio_in_enabled=True, audio_out_enabled=True, - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), "twilio": lambda: FastAPIWebsocketParams( audio_in_enabled=True, audio_out_enabled=True, - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), "webrtc": lambda: TransportParams( audio_in_enabled=True, audio_out_enabled=True, - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), } @@ -84,6 +80,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): user_turn_strategies=UserTurnStrategies( stop=[TurnAnalyzerUserTurnStopStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3())] ), + vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), ) diff --git a/examples/foundational/07e-interruptible-playht.py b/examples/foundational/07e-interruptible-playht.py index 598565868..fe3ee0349 100644 --- a/examples/foundational/07e-interruptible-playht.py +++ b/examples/foundational/07e-interruptible-playht.py @@ -36,24 +36,20 @@ from pipecat.turns.user_turn_strategies import UserTurnStrategies load_dotenv(override=True) -# We store functions so objects (e.g. SileroVADAnalyzer) don't get -# instantiated. The function will be called when the desired transport gets -# selected. +# We use lambdas to defer transport parameter creation until the transport +# type is selected at runtime. transport_params = { "daily": lambda: DailyParams( audio_in_enabled=True, audio_out_enabled=True, - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), "twilio": lambda: FastAPIWebsocketParams( audio_in_enabled=True, audio_out_enabled=True, - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), "webrtc": lambda: TransportParams( audio_in_enabled=True, audio_out_enabled=True, - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), } @@ -86,6 +82,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): user_turn_strategies=UserTurnStrategies( stop=[TurnAnalyzerUserTurnStopStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3())] ), + vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), ) diff --git a/examples/foundational/07f-interruptible-azure-http.py b/examples/foundational/07f-interruptible-azure-http.py index 1fc0a1bba..daec3166d 100644 --- a/examples/foundational/07f-interruptible-azure-http.py +++ b/examples/foundational/07f-interruptible-azure-http.py @@ -35,24 +35,20 @@ from pipecat.turns.user_turn_strategies import UserTurnStrategies load_dotenv(override=True) -# We store functions so objects (e.g. SileroVADAnalyzer) don't get -# instantiated. The function will be called when the desired transport gets -# selected. +# We use lambdas to defer transport parameter creation until the transport +# type is selected at runtime. transport_params = { "daily": lambda: DailyParams( audio_in_enabled=True, audio_out_enabled=True, - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), "twilio": lambda: FastAPIWebsocketParams( audio_in_enabled=True, audio_out_enabled=True, - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), "webrtc": lambda: TransportParams( audio_in_enabled=True, audio_out_enabled=True, - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), } @@ -90,6 +86,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): user_turn_strategies=UserTurnStrategies( stop=[TurnAnalyzerUserTurnStopStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3())] ), + vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), ) diff --git a/examples/foundational/07f-interruptible-azure.py b/examples/foundational/07f-interruptible-azure.py index 0ff69e44e..b1ea08ee4 100644 --- a/examples/foundational/07f-interruptible-azure.py +++ b/examples/foundational/07f-interruptible-azure.py @@ -35,24 +35,20 @@ from pipecat.turns.user_turn_strategies import UserTurnStrategies load_dotenv(override=True) -# We store functions so objects (e.g. SileroVADAnalyzer) don't get -# instantiated. The function will be called when the desired transport gets -# selected. +# We use lambdas to defer transport parameter creation until the transport +# type is selected at runtime. transport_params = { "daily": lambda: DailyParams( audio_in_enabled=True, audio_out_enabled=True, - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), "twilio": lambda: FastAPIWebsocketParams( audio_in_enabled=True, audio_out_enabled=True, - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), "webrtc": lambda: TransportParams( audio_in_enabled=True, audio_out_enabled=True, - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), } @@ -90,6 +86,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): user_turn_strategies=UserTurnStrategies( stop=[TurnAnalyzerUserTurnStopStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3())] ), + vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), ) diff --git a/examples/foundational/07g-interruptible-openai.py b/examples/foundational/07g-interruptible-openai.py index 3c588cf11..f2b38c8cf 100644 --- a/examples/foundational/07g-interruptible-openai.py +++ b/examples/foundational/07g-interruptible-openai.py @@ -35,24 +35,20 @@ from pipecat.turns.user_turn_strategies import UserTurnStrategies load_dotenv(override=True) -# We store functions so objects (e.g. SileroVADAnalyzer) don't get -# instantiated. The function will be called when the desired transport gets -# selected. +# We use lambdas to defer transport parameter creation until the transport +# type is selected at runtime. transport_params = { "daily": lambda: DailyParams( audio_in_enabled=True, audio_out_enabled=True, - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), "twilio": lambda: FastAPIWebsocketParams( audio_in_enabled=True, audio_out_enabled=True, - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), "webrtc": lambda: TransportParams( audio_in_enabled=True, audio_out_enabled=True, - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), } @@ -84,6 +80,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): user_turn_strategies=UserTurnStrategies( stop=[TurnAnalyzerUserTurnStopStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3())] ), + vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), ) diff --git a/examples/foundational/07h-interruptible-openpipe.py b/examples/foundational/07h-interruptible-openpipe.py index 555c4049b..c038800bf 100644 --- a/examples/foundational/07h-interruptible-openpipe.py +++ b/examples/foundational/07h-interruptible-openpipe.py @@ -36,24 +36,20 @@ from pipecat.turns.user_turn_strategies import UserTurnStrategies load_dotenv(override=True) -# We store functions so objects (e.g. SileroVADAnalyzer) don't get -# instantiated. The function will be called when the desired transport gets -# selected. +# We use lambdas to defer transport parameter creation until the transport +# type is selected at runtime. transport_params = { "daily": lambda: DailyParams( audio_in_enabled=True, audio_out_enabled=True, - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), "twilio": lambda: FastAPIWebsocketParams( audio_in_enabled=True, audio_out_enabled=True, - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), "webrtc": lambda: TransportParams( audio_in_enabled=True, audio_out_enabled=True, - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), } @@ -89,6 +85,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): user_turn_strategies=UserTurnStrategies( stop=[TurnAnalyzerUserTurnStopStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3())] ), + vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), ) diff --git a/examples/foundational/07i-interruptible-xtts.py b/examples/foundational/07i-interruptible-xtts.py index 9d1843177..427fab46c 100644 --- a/examples/foundational/07i-interruptible-xtts.py +++ b/examples/foundational/07i-interruptible-xtts.py @@ -36,24 +36,20 @@ from pipecat.turns.user_turn_strategies import UserTurnStrategies load_dotenv(override=True) -# We store functions so objects (e.g. SileroVADAnalyzer) don't get -# instantiated. The function will be called when the desired transport gets -# selected. +# We use lambdas to defer transport parameter creation until the transport +# type is selected at runtime. transport_params = { "daily": lambda: DailyParams( audio_in_enabled=True, audio_out_enabled=True, - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), "twilio": lambda: FastAPIWebsocketParams( audio_in_enabled=True, audio_out_enabled=True, - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), "webrtc": lambda: TransportParams( audio_in_enabled=True, audio_out_enabled=True, - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), } @@ -89,6 +85,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): TurnAnalyzerUserTurnStopStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3()) ] ), + vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), ) diff --git a/examples/foundational/07j-interruptible-gladia-vad.py b/examples/foundational/07j-interruptible-gladia-vad.py index 58d094d3b..77cc9e58f 100644 --- a/examples/foundational/07j-interruptible-gladia-vad.py +++ b/examples/foundational/07j-interruptible-gladia-vad.py @@ -35,24 +35,20 @@ from pipecat.turns.user_turn_strategies import ExternalUserTurnStrategies load_dotenv(override=True) -# We store functions so objects (e.g. SileroVADAnalyzer) don't get -# instantiated. The function will be called when the desired transport gets -# selected. +# We use lambdas to defer transport parameter creation until the transport +# type is selected at runtime. transport_params = { "daily": lambda: DailyParams( audio_in_enabled=True, audio_out_enabled=True, - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), "twilio": lambda: FastAPIWebsocketParams( audio_in_enabled=True, audio_out_enabled=True, - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), "webrtc": lambda: TransportParams( audio_in_enabled=True, audio_out_enabled=True, - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), } @@ -88,7 +84,10 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): context = LLMContext(messages) user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, - user_params=LLMUserAggregatorParams(user_turn_strategies=ExternalUserTurnStrategies()), + user_params=LLMUserAggregatorParams( + user_turn_strategies=ExternalUserTurnStrategies(), + vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), + ), ) pipeline = Pipeline( diff --git a/examples/foundational/07j-interruptible-gladia.py b/examples/foundational/07j-interruptible-gladia.py index 664c19ce1..ee29e11df 100644 --- a/examples/foundational/07j-interruptible-gladia.py +++ b/examples/foundational/07j-interruptible-gladia.py @@ -37,24 +37,20 @@ from pipecat.turns.user_turn_strategies import UserTurnStrategies load_dotenv(override=True) -# We store functions so objects (e.g. SileroVADAnalyzer) don't get -# instantiated. The function will be called when the desired transport gets -# selected. +# We use lambdas to defer transport parameter creation until the transport +# type is selected at runtime. transport_params = { "daily": lambda: DailyParams( audio_in_enabled=True, audio_out_enabled=True, - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), "twilio": lambda: FastAPIWebsocketParams( audio_in_enabled=True, audio_out_enabled=True, - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), "webrtc": lambda: TransportParams( audio_in_enabled=True, audio_out_enabled=True, - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), } @@ -93,6 +89,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): user_turn_strategies=UserTurnStrategies( stop=[TurnAnalyzerUserTurnStopStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3())] ), + vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), ) diff --git a/examples/foundational/07k-interruptible-lmnt.py b/examples/foundational/07k-interruptible-lmnt.py index e616543a3..4f7547c1f 100644 --- a/examples/foundational/07k-interruptible-lmnt.py +++ b/examples/foundational/07k-interruptible-lmnt.py @@ -35,24 +35,20 @@ from pipecat.turns.user_turn_strategies import UserTurnStrategies load_dotenv(override=True) -# We store functions so objects (e.g. SileroVADAnalyzer) don't get -# instantiated. The function will be called when the desired transport gets -# selected. +# We use lambdas to defer transport parameter creation until the transport +# type is selected at runtime. transport_params = { "daily": lambda: DailyParams( audio_in_enabled=True, audio_out_enabled=True, - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), "twilio": lambda: FastAPIWebsocketParams( audio_in_enabled=True, audio_out_enabled=True, - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), "webrtc": lambda: TransportParams( audio_in_enabled=True, audio_out_enabled=True, - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), } @@ -80,6 +76,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): user_turn_strategies=UserTurnStrategies( stop=[TurnAnalyzerUserTurnStopStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3())] ), + vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), ) diff --git a/examples/foundational/07l-interruptible-groq.py b/examples/foundational/07l-interruptible-groq.py index c1e7e2d4d..a838766b2 100644 --- a/examples/foundational/07l-interruptible-groq.py +++ b/examples/foundational/07l-interruptible-groq.py @@ -35,24 +35,20 @@ from pipecat.turns.user_turn_strategies import UserTurnStrategies load_dotenv(override=True) -# We store functions so objects (e.g. SileroVADAnalyzer) don't get -# instantiated. The function will be called when the desired transport gets -# selected. +# We use lambdas to defer transport parameter creation until the transport +# type is selected at runtime. transport_params = { "daily": lambda: DailyParams( audio_in_enabled=True, audio_out_enabled=True, - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), "twilio": lambda: FastAPIWebsocketParams( audio_in_enabled=True, audio_out_enabled=True, - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), "webrtc": lambda: TransportParams( audio_in_enabled=True, audio_out_enabled=True, - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), } @@ -82,6 +78,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): user_turn_strategies=UserTurnStrategies( stop=[TurnAnalyzerUserTurnStopStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3())] ), + vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), ) diff --git a/examples/foundational/07m-interruptible-aws-strands.py b/examples/foundational/07m-interruptible-aws-strands.py index f72e3560c..cc8167661 100644 --- a/examples/foundational/07m-interruptible-aws-strands.py +++ b/examples/foundational/07m-interruptible-aws-strands.py @@ -10,6 +10,7 @@ from loguru import logger from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3 from pipecat.audio.vad.silero import SileroVADAnalyzer +from pipecat.audio.vad.vad_analyzer import VADParams from pipecat.frames.frames import LLMMessagesAppendFrame from pipecat.pipeline.pipeline import Pipeline from pipecat.pipeline.runner import PipelineRunner @@ -41,24 +42,20 @@ except ImportError: load_dotenv(override=True) -# We store functions so objects (e.g. SileroVADAnalyzer) don't get -# instantiated. The function will be called when the desired transport gets -# selected. +# We use lambdas to defer transport parameter creation until the transport +# type is selected at runtime. transport_params = { "daily": lambda: DailyParams( audio_in_enabled=True, audio_out_enabled=True, - vad_analyzer=SileroVADAnalyzer(), ), "twilio": lambda: FastAPIWebsocketParams( audio_in_enabled=True, audio_out_enabled=True, - vad_analyzer=SileroVADAnalyzer(), ), "webrtc": lambda: TransportParams( audio_in_enabled=True, audio_out_enabled=True, - vad_analyzer=SileroVADAnalyzer(), ), } @@ -126,6 +123,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): user_turn_strategies=UserTurnStrategies( stop=[TurnAnalyzerUserTurnStopStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3())] ), + vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), ) diff --git a/examples/foundational/07m-interruptible-aws.py b/examples/foundational/07m-interruptible-aws.py index 0f00e1185..c10a5f33d 100644 --- a/examples/foundational/07m-interruptible-aws.py +++ b/examples/foundational/07m-interruptible-aws.py @@ -33,24 +33,20 @@ from pipecat.turns.user_turn_strategies import UserTurnStrategies load_dotenv(override=True) -# We store functions so objects (e.g. SileroVADAnalyzer) don't get -# instantiated. The function will be called when the desired transport gets -# selected. +# We use lambdas to defer transport parameter creation until the transport +# type is selected at runtime. transport_params = { "daily": lambda: DailyParams( audio_in_enabled=True, audio_out_enabled=True, - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), "twilio": lambda: FastAPIWebsocketParams( audio_in_enabled=True, audio_out_enabled=True, - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), "webrtc": lambda: TransportParams( audio_in_enabled=True, audio_out_enabled=True, - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), } @@ -86,6 +82,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): user_turn_strategies=UserTurnStrategies( stop=[TurnAnalyzerUserTurnStopStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3())] ), + vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), ) diff --git a/examples/foundational/07n-interruptible-gemini-image.py b/examples/foundational/07n-interruptible-gemini-image.py index f32aebee1..4ae497660 100644 --- a/examples/foundational/07n-interruptible-gemini-image.py +++ b/examples/foundational/07n-interruptible-gemini-image.py @@ -50,9 +50,8 @@ from pipecat.turns.user_turn_strategies import UserTurnStrategies load_dotenv(override=True) -# We store functions so objects (e.g. SileroVADAnalyzer) don't get -# instantiated. The function will be called when the desired transport gets -# selected. +# We use lambdas to defer transport parameter creation until the transport +# type is selected at runtime. transport_params = { "daily": lambda: DailyParams( audio_in_enabled=True, @@ -60,7 +59,6 @@ transport_params = { video_out_enabled=True, video_out_width=1024, video_out_height=1024, - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), "webrtc": lambda: TransportParams( audio_in_enabled=True, @@ -68,7 +66,6 @@ transport_params = { video_out_enabled=True, video_out_width=1024, video_out_height=1024, - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), } @@ -107,6 +104,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): user_turn_strategies=UserTurnStrategies( stop=[TurnAnalyzerUserTurnStopStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3())] ), + vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), ) diff --git a/examples/foundational/07n-interruptible-gemini.py b/examples/foundational/07n-interruptible-gemini.py index f9dc0bc3b..2539759c5 100644 --- a/examples/foundational/07n-interruptible-gemini.py +++ b/examples/foundational/07n-interruptible-gemini.py @@ -36,24 +36,20 @@ from pipecat.turns.user_turn_strategies import UserTurnStrategies load_dotenv(override=True) -# We store functions so objects (e.g. SileroVADAnalyzer) don't get -# instantiated. The function will be called when the desired transport gets -# selected. +# We use lambdas to defer transport parameter creation until the transport +# type is selected at runtime. transport_params = { "daily": lambda: DailyParams( audio_in_enabled=True, audio_out_enabled=True, - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), "twilio": lambda: FastAPIWebsocketParams( audio_in_enabled=True, audio_out_enabled=True, - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), "webrtc": lambda: TransportParams( audio_in_enabled=True, audio_out_enabled=True, - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), } @@ -113,6 +109,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): user_turn_strategies=UserTurnStrategies( stop=[TurnAnalyzerUserTurnStopStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3())] ), + vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), ) diff --git a/examples/foundational/07n-interruptible-google-http.py b/examples/foundational/07n-interruptible-google-http.py index 9c58489a9..88bd56e79 100644 --- a/examples/foundational/07n-interruptible-google-http.py +++ b/examples/foundational/07n-interruptible-google-http.py @@ -36,24 +36,20 @@ from pipecat.turns.user_turn_strategies import UserTurnStrategies load_dotenv(override=True) -# We store functions so objects (e.g. SileroVADAnalyzer) don't get -# instantiated. The function will be called when the desired transport gets -# selected. +# We use lambdas to defer transport parameter creation until the transport +# type is selected at runtime. transport_params = { "daily": lambda: DailyParams( audio_in_enabled=True, audio_out_enabled=True, - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), "twilio": lambda: FastAPIWebsocketParams( audio_in_enabled=True, audio_out_enabled=True, - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), "webrtc": lambda: TransportParams( audio_in_enabled=True, audio_out_enabled=True, - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), } @@ -96,6 +92,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): user_turn_strategies=UserTurnStrategies( stop=[TurnAnalyzerUserTurnStopStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3())] ), + vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), ) diff --git a/examples/foundational/07n-interruptible-google.py b/examples/foundational/07n-interruptible-google.py index a7ebc9dc3..8f1781ce5 100644 --- a/examples/foundational/07n-interruptible-google.py +++ b/examples/foundational/07n-interruptible-google.py @@ -36,24 +36,20 @@ from pipecat.turns.user_turn_strategies import UserTurnStrategies load_dotenv(override=True) -# We store functions so objects (e.g. SileroVADAnalyzer) don't get -# instantiated. The function will be called when the desired transport gets -# selected. +# We use lambdas to defer transport parameter creation until the transport +# type is selected at runtime. transport_params = { "daily": lambda: DailyParams( audio_in_enabled=True, audio_out_enabled=True, - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), "twilio": lambda: FastAPIWebsocketParams( audio_in_enabled=True, audio_out_enabled=True, - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), "webrtc": lambda: TransportParams( audio_in_enabled=True, audio_out_enabled=True, - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), } @@ -96,6 +92,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): user_turn_strategies=UserTurnStrategies( stop=[TurnAnalyzerUserTurnStopStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3())] ), + vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), ) diff --git a/examples/foundational/07o-interruptible-assemblyai.py b/examples/foundational/07o-interruptible-assemblyai.py index 9cdaafebb..258825c50 100644 --- a/examples/foundational/07o-interruptible-assemblyai.py +++ b/examples/foundational/07o-interruptible-assemblyai.py @@ -36,24 +36,20 @@ from pipecat.turns.user_turn_strategies import UserTurnStrategies load_dotenv(override=True) -# We store functions so objects (e.g. SileroVADAnalyzer) don't get -# instantiated. The function will be called when the desired transport gets -# selected. +# We use lambdas to defer transport parameter creation until the transport +# type is selected at runtime. transport_params = { "daily": lambda: DailyParams( audio_in_enabled=True, audio_out_enabled=True, - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), "twilio": lambda: FastAPIWebsocketParams( audio_in_enabled=True, audio_out_enabled=True, - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), "webrtc": lambda: TransportParams( audio_in_enabled=True, audio_out_enabled=True, - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), } @@ -86,6 +82,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): user_turn_strategies=UserTurnStrategies( stop=[TurnAnalyzerUserTurnStopStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3())] ), + vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), ) diff --git a/examples/foundational/07p-interruptible-krisp-viva.py b/examples/foundational/07p-interruptible-krisp-viva.py index fd899f213..d502bdcc4 100644 --- a/examples/foundational/07p-interruptible-krisp-viva.py +++ b/examples/foundational/07p-interruptible-krisp-viva.py @@ -53,26 +53,22 @@ from pipecat.turns.user_turn_strategies import UserTurnStrategies load_dotenv(override=True) -# We store functions so objects (e.g. SileroVADAnalyzer) don't get -# instantiated. The function will be called when the desired transport gets -# selected. +# We use lambdas to defer transport parameter creation until the transport +# type is selected at runtime. transport_params = { "daily": lambda: DailyParams( audio_in_enabled=True, audio_out_enabled=True, - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), audio_in_filter=KrispVivaFilter(), ), "twilio": lambda: FastAPIWebsocketParams( audio_in_enabled=True, audio_out_enabled=True, - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), audio_in_filter=KrispVivaFilter(), ), "webrtc": lambda: TransportParams( audio_in_enabled=True, audio_out_enabled=True, - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), audio_in_filter=KrispVivaFilter(), ), } @@ -101,6 +97,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): user_turn_strategies=UserTurnStrategies( stop=[TurnAnalyzerUserTurnStopStrategy(turn_analyzer=KrispVivaTurn())] ), + vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), ) diff --git a/examples/foundational/07p-interruptible-krisp.py b/examples/foundational/07p-interruptible-krisp.py index 8665e270e..02451ece4 100644 --- a/examples/foundational/07p-interruptible-krisp.py +++ b/examples/foundational/07p-interruptible-krisp.py @@ -36,26 +36,22 @@ from pipecat.turns.user_turn_strategies import UserTurnStrategies load_dotenv(override=True) -# We store functions so objects (e.g. SileroVADAnalyzer) don't get -# instantiated. The function will be called when the desired transport gets -# selected. +# We use lambdas to defer transport parameter creation until the transport +# type is selected at runtime. transport_params = { "daily": lambda: DailyParams( audio_in_enabled=True, audio_out_enabled=True, - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), audio_in_filter=KrispFilter(), ), "twilio": lambda: FastAPIWebsocketParams( audio_in_enabled=True, audio_out_enabled=True, - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), audio_in_filter=KrispFilter(), ), "webrtc": lambda: TransportParams( audio_in_enabled=True, audio_out_enabled=True, - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), audio_in_filter=KrispFilter(), ), } @@ -84,6 +80,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): user_turn_strategies=UserTurnStrategies( stop=[TurnAnalyzerUserTurnStopStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3())] ), + vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), ) diff --git a/examples/foundational/07q-interruptible-rime-http.py b/examples/foundational/07q-interruptible-rime-http.py index 1cbe7f01b..bfceb1bb3 100644 --- a/examples/foundational/07q-interruptible-rime-http.py +++ b/examples/foundational/07q-interruptible-rime-http.py @@ -37,24 +37,20 @@ from pipecat.turns.user_turn_strategies import UserTurnStrategies load_dotenv(override=True) -# We store functions so objects (e.g. SileroVADAnalyzer) don't get -# instantiated. The function will be called when the desired transport gets -# selected. +# We use lambdas to defer transport parameter creation until the transport +# type is selected at runtime. transport_params = { "daily": lambda: DailyParams( audio_in_enabled=True, audio_out_enabled=True, - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), "twilio": lambda: FastAPIWebsocketParams( audio_in_enabled=True, audio_out_enabled=True, - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), "webrtc": lambda: TransportParams( audio_in_enabled=True, audio_out_enabled=True, - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), } @@ -91,6 +87,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): TurnAnalyzerUserTurnStopStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3()) ] ), + vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), ) diff --git a/examples/foundational/07q-interruptible-rime.py b/examples/foundational/07q-interruptible-rime.py index d54a97d78..5113b2c3c 100644 --- a/examples/foundational/07q-interruptible-rime.py +++ b/examples/foundational/07q-interruptible-rime.py @@ -35,24 +35,20 @@ from pipecat.turns.user_turn_strategies import UserTurnStrategies load_dotenv(override=True) -# We store functions so objects (e.g. SileroVADAnalyzer) don't get -# instantiated. The function will be called when the desired transport gets -# selected. +# We use lambdas to defer transport parameter creation until the transport +# type is selected at runtime. transport_params = { "daily": lambda: DailyParams( audio_in_enabled=True, audio_out_enabled=True, - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), "twilio": lambda: FastAPIWebsocketParams( audio_in_enabled=True, audio_out_enabled=True, - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), "webrtc": lambda: TransportParams( audio_in_enabled=True, audio_out_enabled=True, - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), } @@ -83,6 +79,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): user_turn_strategies=UserTurnStrategies( stop=[TurnAnalyzerUserTurnStopStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3())] ), + vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), ) diff --git a/examples/foundational/07r-interruptible-nvidia.py b/examples/foundational/07r-interruptible-nvidia.py index 460f6ebfe..dda75256d 100644 --- a/examples/foundational/07r-interruptible-nvidia.py +++ b/examples/foundational/07r-interruptible-nvidia.py @@ -35,24 +35,20 @@ from pipecat.turns.user_turn_strategies import UserTurnStrategies load_dotenv(override=True) -# We store functions so objects (e.g. SileroVADAnalyzer) don't get -# instantiated. The function will be called when the desired transport gets -# selected. +# We use lambdas to defer transport parameter creation until the transport +# type is selected at runtime. transport_params = { "daily": lambda: DailyParams( audio_in_enabled=True, audio_out_enabled=True, - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), "twilio": lambda: FastAPIWebsocketParams( audio_in_enabled=True, audio_out_enabled=True, - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), "webrtc": lambda: TransportParams( audio_in_enabled=True, audio_out_enabled=True, - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), } @@ -82,6 +78,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): user_turn_strategies=UserTurnStrategies( stop=[TurnAnalyzerUserTurnStopStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3())] ), + vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), ) diff --git a/examples/foundational/07s-interruptible-google-audio-in.py b/examples/foundational/07s-interruptible-google-audio-in.py index 9aaa3c415..54c0da1b9 100644 --- a/examples/foundational/07s-interruptible-google-audio-in.py +++ b/examples/foundational/07s-interruptible-google-audio-in.py @@ -197,24 +197,20 @@ class TranscriptionContextFixup(FrameProcessor): await self.push_frame(frame, direction) -# We store functions so objects (e.g. SileroVADAnalyzer) don't get -# instantiated. The function will be called when the desired transport gets -# selected. +# We use lambdas to defer transport parameter creation until the transport +# type is selected at runtime. transport_params = { "daily": lambda: DailyParams( audio_in_enabled=True, audio_out_enabled=True, - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), "twilio": lambda: FastAPIWebsocketParams( audio_in_enabled=True, audio_out_enabled=True, - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), "webrtc": lambda: TransportParams( audio_in_enabled=True, audio_out_enabled=True, - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), } @@ -255,6 +251,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): user_turn_strategies=UserTurnStrategies( stop=[TurnAnalyzerUserTurnStopStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3())] ), + vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), ) audio_collector = UserAudioCollector(context, user_aggregator) diff --git a/examples/foundational/07t-interruptible-fish.py b/examples/foundational/07t-interruptible-fish.py index 86750b631..5a7c368f1 100644 --- a/examples/foundational/07t-interruptible-fish.py +++ b/examples/foundational/07t-interruptible-fish.py @@ -36,24 +36,20 @@ from pipecat.turns.user_turn_strategies import UserTurnStrategies load_dotenv(override=True) -# We store functions so objects (e.g. SileroVADAnalyzer) don't get -# instantiated. The function will be called when the desired transport gets -# selected. +# We use lambdas to defer transport parameter creation until the transport +# type is selected at runtime. transport_params = { "daily": lambda: DailyParams( audio_in_enabled=True, audio_out_enabled=True, - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), "twilio": lambda: FastAPIWebsocketParams( audio_in_enabled=True, audio_out_enabled=True, - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), "webrtc": lambda: TransportParams( audio_in_enabled=True, audio_out_enabled=True, - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), } @@ -84,6 +80,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): user_turn_strategies=UserTurnStrategies( stop=[TurnAnalyzerUserTurnStopStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3())] ), + vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), ) diff --git a/examples/foundational/07v-interruptible-neuphonic-http.py b/examples/foundational/07v-interruptible-neuphonic-http.py index 5f5928cad..3c82608bc 100644 --- a/examples/foundational/07v-interruptible-neuphonic-http.py +++ b/examples/foundational/07v-interruptible-neuphonic-http.py @@ -37,24 +37,20 @@ from pipecat.turns.user_turn_strategies import UserTurnStrategies load_dotenv(override=True) -# We store functions so objects (e.g. SileroVADAnalyzer) don't get -# instantiated. The function will be called when the desired transport gets -# selected. +# We use lambdas to defer transport parameter creation until the transport +# type is selected at runtime. transport_params = { "daily": lambda: DailyParams( audio_in_enabled=True, audio_out_enabled=True, - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), "twilio": lambda: FastAPIWebsocketParams( audio_in_enabled=True, audio_out_enabled=True, - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), "webrtc": lambda: TransportParams( audio_in_enabled=True, audio_out_enabled=True, - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), } @@ -90,6 +86,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): TurnAnalyzerUserTurnStopStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3()) ] ), + vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), ) diff --git a/examples/foundational/07v-interruptible-neuphonic.py b/examples/foundational/07v-interruptible-neuphonic.py index 78fc9c2e8..fd0c3361c 100644 --- a/examples/foundational/07v-interruptible-neuphonic.py +++ b/examples/foundational/07v-interruptible-neuphonic.py @@ -35,24 +35,20 @@ from pipecat.turns.user_turn_strategies import UserTurnStrategies load_dotenv(override=True) -# We store functions so objects (e.g. SileroVADAnalyzer) don't get -# instantiated. The function will be called when the desired transport gets -# selected. +# We use lambdas to defer transport parameter creation until the transport +# type is selected at runtime. transport_params = { "daily": lambda: DailyParams( audio_in_enabled=True, audio_out_enabled=True, - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), "twilio": lambda: FastAPIWebsocketParams( audio_in_enabled=True, audio_out_enabled=True, - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), "webrtc": lambda: TransportParams( audio_in_enabled=True, audio_out_enabled=True, - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), } @@ -83,6 +79,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): user_turn_strategies=UserTurnStrategies( stop=[TurnAnalyzerUserTurnStopStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3())] ), + vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), ) diff --git a/examples/foundational/07w-interruptible-fal.py b/examples/foundational/07w-interruptible-fal.py index a60725b16..b6dda13a9 100644 --- a/examples/foundational/07w-interruptible-fal.py +++ b/examples/foundational/07w-interruptible-fal.py @@ -36,24 +36,20 @@ from pipecat.turns.user_turn_strategies import UserTurnStrategies load_dotenv(override=True) -# We store functions so objects (e.g. SileroVADAnalyzer) don't get -# instantiated. The function will be called when the desired transport gets -# selected. +# We use lambdas to defer transport parameter creation until the transport +# type is selected at runtime. transport_params = { "daily": lambda: DailyParams( audio_in_enabled=True, audio_out_enabled=True, - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), "twilio": lambda: FastAPIWebsocketParams( audio_in_enabled=True, audio_out_enabled=True, - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), "webrtc": lambda: TransportParams( audio_in_enabled=True, audio_out_enabled=True, - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), } @@ -86,6 +82,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): user_turn_strategies=UserTurnStrategies( stop=[TurnAnalyzerUserTurnStopStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3())] ), + vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), ) diff --git a/examples/foundational/07x-interruptible-local.py b/examples/foundational/07x-interruptible-local.py index 0baa6ebad..aeb1b1f32 100644 --- a/examples/foundational/07x-interruptible-local.py +++ b/examples/foundational/07x-interruptible-local.py @@ -41,7 +41,6 @@ async def main(): LocalAudioTransportParams( audio_in_enabled=True, audio_out_enabled=True, - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ) ) @@ -68,6 +67,7 @@ async def main(): user_turn_strategies=UserTurnStrategies( stop=[TurnAnalyzerUserTurnStopStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3())] ), + vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), ) diff --git a/examples/foundational/07y-interruptible-minimax.py b/examples/foundational/07y-interruptible-minimax.py index 855e41516..1bd8f716f 100644 --- a/examples/foundational/07y-interruptible-minimax.py +++ b/examples/foundational/07y-interruptible-minimax.py @@ -38,24 +38,20 @@ from pipecat.turns.user_turn_strategies import UserTurnStrategies load_dotenv(override=True) -# We store functions so objects (e.g. SileroVADAnalyzer) don't get -# instantiated. The function will be called when the desired transport gets -# selected. +# We use lambdas to defer transport parameter creation until the transport +# type is selected at runtime. transport_params = { "daily": lambda: DailyParams( audio_in_enabled=True, audio_out_enabled=True, - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), "twilio": lambda: FastAPIWebsocketParams( audio_in_enabled=True, audio_out_enabled=True, - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), "webrtc": lambda: TransportParams( audio_in_enabled=True, audio_out_enabled=True, - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), } @@ -92,6 +88,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): TurnAnalyzerUserTurnStopStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3()) ] ), + vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), ) diff --git a/examples/foundational/07z-interruptible-sarvam-http.py b/examples/foundational/07z-interruptible-sarvam-http.py index df176ab22..a5b656b1a 100644 --- a/examples/foundational/07z-interruptible-sarvam-http.py +++ b/examples/foundational/07z-interruptible-sarvam-http.py @@ -38,24 +38,20 @@ from pipecat.turns.user_turn_strategies import UserTurnStrategies load_dotenv(override=True) -# We store functions so objects (e.g. SileroVADAnalyzer) don't get -# instantiated. The function will be called when the desired transport gets -# selected. +# We use lambdas to defer transport parameter creation until the transport +# type is selected at runtime. transport_params = { "daily": lambda: DailyParams( audio_in_enabled=True, audio_out_enabled=True, - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), "twilio": lambda: FastAPIWebsocketParams( audio_in_enabled=True, audio_out_enabled=True, - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), "webrtc": lambda: TransportParams( audio_in_enabled=True, audio_out_enabled=True, - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), } @@ -94,6 +90,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): TurnAnalyzerUserTurnStopStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3()) ] ), + vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), ) diff --git a/examples/foundational/07z-interruptible-sarvam.py b/examples/foundational/07z-interruptible-sarvam.py index 990af6fef..3ead95eb0 100644 --- a/examples/foundational/07z-interruptible-sarvam.py +++ b/examples/foundational/07z-interruptible-sarvam.py @@ -35,24 +35,20 @@ from pipecat.turns.user_turn_strategies import UserTurnStrategies load_dotenv(override=True) -# We store functions so objects (e.g. SileroVADAnalyzer) don't get -# instantiated. The function will be called when the desired transport gets -# selected. +# We use lambdas to defer transport parameter creation until the transport +# type is selected at runtime. transport_params = { "daily": lambda: DailyParams( audio_in_enabled=True, audio_out_enabled=True, - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), "twilio": lambda: FastAPIWebsocketParams( audio_in_enabled=True, audio_out_enabled=True, - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), "webrtc": lambda: TransportParams( audio_in_enabled=True, audio_out_enabled=True, - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), } @@ -86,6 +82,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): user_turn_strategies=UserTurnStrategies( stop=[TurnAnalyzerUserTurnStopStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3())] ), + vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), ) diff --git a/examples/foundational/07za-interruptible-soniox.py b/examples/foundational/07za-interruptible-soniox.py index 15da33507..5f1a45fe8 100644 --- a/examples/foundational/07za-interruptible-soniox.py +++ b/examples/foundational/07za-interruptible-soniox.py @@ -39,17 +39,14 @@ transport_params = { "daily": lambda: DailyParams( audio_in_enabled=True, audio_out_enabled=True, - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), "twilio": lambda: FastAPIWebsocketParams( audio_in_enabled=True, audio_out_enabled=True, - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), "webrtc": lambda: TransportParams( audio_in_enabled=True, audio_out_enabled=True, - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), } @@ -82,6 +79,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): user_turn_strategies=UserTurnStrategies( stop=[TurnAnalyzerUserTurnStopStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3())] ), + vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), ) diff --git a/examples/foundational/07zb-interruptible-inworld-http.py b/examples/foundational/07zb-interruptible-inworld-http.py index c67984f7c..90fb20bd0 100644 --- a/examples/foundational/07zb-interruptible-inworld-http.py +++ b/examples/foundational/07zb-interruptible-inworld-http.py @@ -41,17 +41,14 @@ transport_params = { "daily": lambda: DailyParams( audio_in_enabled=True, audio_out_enabled=True, - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), "twilio": lambda: FastAPIWebsocketParams( audio_in_enabled=True, audio_out_enabled=True, - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), "webrtc": lambda: TransportParams( audio_in_enabled=True, audio_out_enabled=True, - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), } @@ -89,6 +86,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): TurnAnalyzerUserTurnStopStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3()) ] ), + vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), ) diff --git a/examples/foundational/07zb-interruptible-inworld.py b/examples/foundational/07zb-interruptible-inworld.py index 46e07dc5f..9c8fa720b 100644 --- a/examples/foundational/07zb-interruptible-inworld.py +++ b/examples/foundational/07zb-interruptible-inworld.py @@ -41,17 +41,14 @@ transport_params = { "daily": lambda: DailyParams( audio_in_enabled=True, audio_out_enabled=True, - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), "twilio": lambda: FastAPIWebsocketParams( audio_in_enabled=True, audio_out_enabled=True, - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), "webrtc": lambda: TransportParams( audio_in_enabled=True, audio_out_enabled=True, - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), } @@ -84,6 +81,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): user_turn_strategies=UserTurnStrategies( stop=[TurnAnalyzerUserTurnStopStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3())] ), + vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), ) diff --git a/examples/foundational/07zc-interruptible-asyncai-http.py b/examples/foundational/07zc-interruptible-asyncai-http.py index 21da1cf17..dff140ac3 100644 --- a/examples/foundational/07zc-interruptible-asyncai-http.py +++ b/examples/foundational/07zc-interruptible-asyncai-http.py @@ -37,24 +37,20 @@ from pipecat.turns.user_turn_strategies import UserTurnStrategies load_dotenv(override=True) -# We store functions so objects (e.g. SileroVADAnalyzer) don't get -# instantiated. The function will be called when the desired transport gets -# selected. +# We use lambdas to defer transport parameter creation until the transport +# type is selected at runtime. transport_params = { "daily": lambda: DailyParams( audio_in_enabled=True, audio_out_enabled=True, - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), "twilio": lambda: FastAPIWebsocketParams( audio_in_enabled=True, audio_out_enabled=True, - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), "webrtc": lambda: TransportParams( audio_in_enabled=True, audio_out_enabled=True, - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), } @@ -90,6 +86,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): TurnAnalyzerUserTurnStopStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3()) ] ), + vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), ) diff --git a/examples/foundational/07zc-interruptible-asyncai.py b/examples/foundational/07zc-interruptible-asyncai.py index d3dcf8766..3596f40a1 100644 --- a/examples/foundational/07zc-interruptible-asyncai.py +++ b/examples/foundational/07zc-interruptible-asyncai.py @@ -36,24 +36,20 @@ from pipecat.turns.user_turn_strategies import UserTurnStrategies load_dotenv(override=True) -# We store functions so objects (e.g. SileroVADAnalyzer) don't get -# instantiated. The function will be called when the desired transport gets -# selected. +# We use lambdas to defer transport parameter creation until the transport +# type is selected at runtime. transport_params = { "daily": lambda: DailyParams( audio_in_enabled=True, audio_out_enabled=True, - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), "twilio": lambda: FastAPIWebsocketParams( audio_in_enabled=True, audio_out_enabled=True, - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), "webrtc": lambda: TransportParams( audio_in_enabled=True, audio_out_enabled=True, - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), } @@ -84,6 +80,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): user_turn_strategies=UserTurnStrategies( stop=[TurnAnalyzerUserTurnStopStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3())] ), + vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), ) diff --git a/examples/foundational/07zd-interruptible-aicoustics.py b/examples/foundational/07zd-interruptible-aicoustics.py index ca205fc1d..2a355ba18 100644 --- a/examples/foundational/07zd-interruptible-aicoustics.py +++ b/examples/foundational/07zd-interruptible-aicoustics.py @@ -54,9 +54,8 @@ def _create_aic_filter() -> AICFilter: ) -# We store functions so objects (e.g. SileroVADAnalyzer) don't get -# instantiated. The function will be called when the desired transport gets -# selected. +# We use lambdas to defer transport parameter creation until the transport +# type is selected at runtime. transport_params = { "daily": lambda: ( lambda aic: DailyParams( diff --git a/examples/foundational/07ze-interruptible-hume.py b/examples/foundational/07ze-interruptible-hume.py index e9a8e355c..a864032c4 100644 --- a/examples/foundational/07ze-interruptible-hume.py +++ b/examples/foundational/07ze-interruptible-hume.py @@ -37,24 +37,20 @@ from pipecat.turns.user_turn_strategies import UserTurnStrategies load_dotenv(override=True) -# We store functions so objects (e.g. SileroVADAnalyzer) don't get -# instantiated. The function will be called when the desired transport gets -# selected. +# We use lambdas to defer transport parameter creation until the transport +# type is selected at runtime. transport_params = { "daily": lambda: DailyParams( audio_in_enabled=True, audio_out_enabled=True, - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), "twilio": lambda: FastAPIWebsocketParams( audio_in_enabled=True, audio_out_enabled=True, - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), "webrtc": lambda: TransportParams( audio_in_enabled=True, audio_out_enabled=True, - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), } @@ -86,6 +82,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): user_turn_strategies=UserTurnStrategies( stop=[TurnAnalyzerUserTurnStopStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3())] ), + vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), ) diff --git a/examples/foundational/07zf-interruptible-gradium.py b/examples/foundational/07zf-interruptible-gradium.py index e4314ac3a..02f33f41b 100644 --- a/examples/foundational/07zf-interruptible-gradium.py +++ b/examples/foundational/07zf-interruptible-gradium.py @@ -35,24 +35,20 @@ from pipecat.turns.user_turn_strategies import UserTurnStrategies load_dotenv(override=True) -# We store functions so objects (e.g. SileroVADAnalyzer) don't get -# instantiated. The function will be called when the desired transport gets -# selected. +# We use lambdas to defer transport parameter creation until the transport +# type is selected at runtime. transport_params = { "daily": lambda: DailyParams( audio_in_enabled=True, audio_out_enabled=True, - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), "twilio": lambda: FastAPIWebsocketParams( audio_in_enabled=True, audio_out_enabled=True, - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), "webrtc": lambda: TransportParams( audio_in_enabled=True, audio_out_enabled=True, - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), } @@ -90,6 +86,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): user_turn_strategies=UserTurnStrategies( stop=[TurnAnalyzerUserTurnStopStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3())] ), + vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), ) diff --git a/examples/foundational/07zg-interruptible-camb.py b/examples/foundational/07zg-interruptible-camb.py index 256eff6f7..d0312a5f7 100644 --- a/examples/foundational/07zg-interruptible-camb.py +++ b/examples/foundational/07zg-interruptible-camb.py @@ -35,24 +35,20 @@ from pipecat.turns.user_turn_strategies import UserTurnStrategies load_dotenv(override=True) -# We store functions so objects (e.g. SileroVADAnalyzer) don't get -# instantiated. The function will be called when the desired transport gets -# selected. +# We use lambdas to defer transport parameter creation until the transport +# type is selected at runtime. transport_params = { "daily": lambda: DailyParams( audio_in_enabled=True, audio_out_enabled=True, - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), "twilio": lambda: FastAPIWebsocketParams( audio_in_enabled=True, audio_out_enabled=True, - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), "webrtc": lambda: TransportParams( audio_in_enabled=True, audio_out_enabled=True, - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), } @@ -85,6 +81,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): user_turn_strategies=UserTurnStrategies( stop=[TurnAnalyzerUserTurnStopStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3())] ), + vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), ) diff --git a/examples/foundational/07zh-interruptible-hathora.py b/examples/foundational/07zh-interruptible-hathora.py index f4bd169b1..c7876217f 100644 --- a/examples/foundational/07zh-interruptible-hathora.py +++ b/examples/foundational/07zh-interruptible-hathora.py @@ -34,24 +34,20 @@ from pipecat.turns.user_turn_strategies import UserTurnStrategies load_dotenv(override=True) -# We store functions so objects (e.g. SileroVADAnalyzer) don't get -# instantiated. The function will be called when the desired transport gets -# selected. +# We use lambdas to defer transport parameter creation until the transport +# type is selected at runtime. transport_params = { "daily": lambda: DailyParams( audio_in_enabled=True, audio_out_enabled=True, - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), "twilio": lambda: FastAPIWebsocketParams( audio_in_enabled=True, audio_out_enabled=True, - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), "webrtc": lambda: TransportParams( audio_in_enabled=True, audio_out_enabled=True, - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), } @@ -88,6 +84,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): user_turn_strategies=UserTurnStrategies( stop=[TurnAnalyzerUserTurnStopStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3())] ), + vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), ) diff --git a/examples/foundational/08-custom-frame-processor.py b/examples/foundational/08-custom-frame-processor.py index 82ff858b6..c561c46f3 100644 --- a/examples/foundational/08-custom-frame-processor.py +++ b/examples/foundational/08-custom-frame-processor.py @@ -77,20 +77,17 @@ class MetricsFrameLogger(FrameProcessor): await self.push_frame(frame, direction) -# We store functions so objects (e.g. SileroVADAnalyzer) don't get -# instantiated. The function will be called when the desired transport gets -# selected. +# We use lambdas to defer transport parameter creation until the transport +# type is selected at runtime. transport_params = { "daily": lambda: DailyParams( audio_in_enabled=True, audio_out_enabled=True, - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), "webrtc": lambda: TransportParams( audio_in_enabled=True, audio_out_enabled=True, video_out_enabled=True, - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), } @@ -121,6 +118,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): user_turn_strategies=UserTurnStrategies( stop=[TurnAnalyzerUserTurnStopStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3())] ), + vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), ) diff --git a/examples/foundational/09-mirror.py b/examples/foundational/09-mirror.py index 80b76b3b8..478fe9daf 100644 --- a/examples/foundational/09-mirror.py +++ b/examples/foundational/09-mirror.py @@ -47,9 +47,8 @@ class MirrorProcessor(FrameProcessor): await self.push_frame(frame, direction) -# We store functions so objects (e.g. SileroVADAnalyzer) don't get -# instantiated. The function will be called when the desired transport gets -# selected. +# We use lambdas to defer transport parameter creation until the transport +# type is selected at runtime. transport_params = { "daily": lambda: DailyParams( audio_in_enabled=True, diff --git a/examples/foundational/09a-local-mirror.py b/examples/foundational/09a-local-mirror.py index 42d9af41e..217136e58 100644 --- a/examples/foundational/09a-local-mirror.py +++ b/examples/foundational/09a-local-mirror.py @@ -50,9 +50,8 @@ class MirrorProcessor(FrameProcessor): await self.push_frame(frame, direction) -# We store functions so objects (e.g. SileroVADAnalyzer) don't get -# instantiated. The function will be called when the desired transport gets -# selected. +# We use lambdas to defer transport parameter creation until the transport +# type is selected at runtime. transport_params = { "daily": lambda: DailyParams( audio_in_enabled=True, diff --git a/examples/foundational/10-wake-phrase.py b/examples/foundational/10-wake-phrase.py index fe7052a5b..f87255814 100644 --- a/examples/foundational/10-wake-phrase.py +++ b/examples/foundational/10-wake-phrase.py @@ -35,24 +35,20 @@ from pipecat.turns.user_turn_strategies import UserTurnStrategies load_dotenv(override=True) -# We store functions so objects (e.g. SileroVADAnalyzer) don't get -# instantiated. The function will be called when the desired transport gets -# selected. +# We use lambdas to defer transport parameter creation until the transport +# type is selected at runtime. transport_params = { "daily": lambda: DailyParams( audio_in_enabled=True, audio_out_enabled=True, - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), "twilio": lambda: FastAPIWebsocketParams( audio_in_enabled=True, audio_out_enabled=True, - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), "webrtc": lambda: TransportParams( audio_in_enabled=True, audio_out_enabled=True, - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), } @@ -85,6 +81,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): user_turn_strategies=UserTurnStrategies( stop=[TurnAnalyzerUserTurnStopStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3())] ), + vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), ) diff --git a/examples/foundational/11-sound-effects.py b/examples/foundational/11-sound-effects.py index b517cf447..297db8a45 100644 --- a/examples/foundational/11-sound-effects.py +++ b/examples/foundational/11-sound-effects.py @@ -85,24 +85,20 @@ class InboundSoundEffectWrapper(FrameProcessor): await self.push_frame(frame, direction) -# We store functions so objects (e.g. SileroVADAnalyzer) don't get -# instantiated. The function will be called when the desired transport gets -# selected. +# We use lambdas to defer transport parameter creation until the transport +# type is selected at runtime. transport_params = { "daily": lambda: DailyParams( audio_in_enabled=True, audio_out_enabled=True, - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), "twilio": lambda: FastAPIWebsocketParams( audio_in_enabled=True, audio_out_enabled=True, - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), "webrtc": lambda: TransportParams( audio_in_enabled=True, audio_out_enabled=True, - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), } @@ -133,6 +129,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): user_turn_strategies=UserTurnStrategies( stop=[TurnAnalyzerUserTurnStopStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3())] ), + vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), ) out_sound = OutboundSoundEffectWrapper() diff --git a/examples/foundational/12-describe-image-openai.py b/examples/foundational/12-describe-image-openai.py index 60cdeafed..413573eb7 100644 --- a/examples/foundational/12-describe-image-openai.py +++ b/examples/foundational/12-describe-image-openai.py @@ -36,19 +36,16 @@ from pipecat.turns.user_turn_strategies import UserTurnStrategies load_dotenv(override=True) -# We store functions so objects (e.g. SileroVADAnalyzer) don't get -# instantiated. The function will be called when the desired transport gets -# selected. +# We use lambdas to defer transport parameter creation until the transport +# type is selected at runtime. transport_params = { "daily": lambda: DailyParams( audio_in_enabled=True, audio_out_enabled=True, - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), "webrtc": lambda: TransportParams( audio_in_enabled=True, audio_out_enabled=True, - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), } @@ -79,6 +76,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): user_turn_strategies=UserTurnStrategies( stop=[TurnAnalyzerUserTurnStopStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3())] ), + vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), ) diff --git a/examples/foundational/12a-describe-image-anthropic.py b/examples/foundational/12a-describe-image-anthropic.py index 507cca019..0b611c143 100644 --- a/examples/foundational/12a-describe-image-anthropic.py +++ b/examples/foundational/12a-describe-image-anthropic.py @@ -36,19 +36,16 @@ from pipecat.turns.user_turn_strategies import UserTurnStrategies load_dotenv(override=True) -# We store functions so objects (e.g. SileroVADAnalyzer) don't get -# instantiated. The function will be called when the desired transport gets -# selected. +# We use lambdas to defer transport parameter creation until the transport +# type is selected at runtime. transport_params = { "daily": lambda: DailyParams( audio_in_enabled=True, audio_out_enabled=True, - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), "webrtc": lambda: TransportParams( audio_in_enabled=True, audio_out_enabled=True, - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), } @@ -79,6 +76,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): user_turn_strategies=UserTurnStrategies( stop=[TurnAnalyzerUserTurnStopStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3())] ), + vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), ) diff --git a/examples/foundational/12b-describe-image-aws.py b/examples/foundational/12b-describe-image-aws.py index ed02f5024..4c62a1fbf 100644 --- a/examples/foundational/12b-describe-image-aws.py +++ b/examples/foundational/12b-describe-image-aws.py @@ -36,19 +36,16 @@ from pipecat.turns.user_turn_strategies import UserTurnStrategies load_dotenv(override=True) -# We store functions so objects (e.g. SileroVADAnalyzer) don't get -# instantiated. The function will be called when the desired transport gets -# selected. +# We use lambdas to defer transport parameter creation until the transport +# type is selected at runtime. transport_params = { "daily": lambda: DailyParams( audio_in_enabled=True, audio_out_enabled=True, - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), "webrtc": lambda: TransportParams( audio_in_enabled=True, audio_out_enabled=True, - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), } @@ -86,6 +83,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): user_turn_strategies=UserTurnStrategies( stop=[TurnAnalyzerUserTurnStopStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3())] ), + vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), ) diff --git a/examples/foundational/12c-describe-image-gemini-flash.py b/examples/foundational/12c-describe-image-gemini-flash.py index a00465135..b1cd3fd73 100644 --- a/examples/foundational/12c-describe-image-gemini-flash.py +++ b/examples/foundational/12c-describe-image-gemini-flash.py @@ -36,19 +36,16 @@ from pipecat.turns.user_turn_strategies import UserTurnStrategies load_dotenv(override=True) -# We store functions so objects (e.g. SileroVADAnalyzer) don't get -# instantiated. The function will be called when the desired transport gets -# selected. +# We use lambdas to defer transport parameter creation until the transport +# type is selected at runtime. transport_params = { "daily": lambda: DailyParams( audio_in_enabled=True, audio_out_enabled=True, - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), "webrtc": lambda: TransportParams( audio_in_enabled=True, audio_out_enabled=True, - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), } @@ -79,6 +76,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): user_turn_strategies=UserTurnStrategies( stop=[TurnAnalyzerUserTurnStopStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3())] ), + vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), ) diff --git a/examples/foundational/12d-describe-image-moondream.py b/examples/foundational/12d-describe-image-moondream.py index 4b9ff0912..070b004a1 100644 --- a/examples/foundational/12d-describe-image-moondream.py +++ b/examples/foundational/12d-describe-image-moondream.py @@ -11,8 +11,6 @@ from dotenv import load_dotenv from loguru import logger from PIL import Image -from pipecat.audio.vad.silero import SileroVADAnalyzer -from pipecat.audio.vad.vad_analyzer import VADParams from pipecat.frames.frames import UserImageRawFrame from pipecat.pipeline.pipeline import Pipeline from pipecat.pipeline.runner import PipelineRunner @@ -27,17 +25,14 @@ from pipecat.transports.daily.transport import DailyParams load_dotenv(override=True) -# We store functions so objects (e.g. SileroVADAnalyzer) don't get -# instantiated. The function will be called when the desired transport gets -# selected. +# We use lambdas to defer transport parameter creation until the transport +# type is selected at runtime. transport_params = { "daily": lambda: DailyParams( audio_out_enabled=True, - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), "webrtc": lambda: TransportParams( audio_out_enabled=True, - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), } diff --git a/examples/foundational/13-whisper-transcription.py b/examples/foundational/13-whisper-transcription.py index 79d706a5a..e2f0f61e0 100644 --- a/examples/foundational/13-whisper-transcription.py +++ b/examples/foundational/13-whisper-transcription.py @@ -35,9 +35,8 @@ class TranscriptionLogger(FrameProcessor): await self.push_frame(frame, direction) -# We store functions so objects (e.g. SileroVADAnalyzer) don't get -# instantiated. The function will be called when the desired transport gets -# selected. +# We use lambdas to defer transport parameter creation until the transport +# type is selected at runtime. transport_params = { "daily": lambda: DailyParams( audio_in_enabled=True, diff --git a/examples/foundational/13b-deepgram-transcription.py b/examples/foundational/13b-deepgram-transcription.py index ce18b3f16..ed83bd1d5 100644 --- a/examples/foundational/13b-deepgram-transcription.py +++ b/examples/foundational/13b-deepgram-transcription.py @@ -35,9 +35,8 @@ class TranscriptionLogger(FrameProcessor): await self.push_frame(frame, direction) -# We store functions so objects (e.g. SileroVADAnalyzer) don't get -# instantiated. The function will be called when the desired transport gets -# selected. +# We use lambdas to defer transport parameter creation until the transport +# type is selected at runtime. transport_params = { "daily": lambda: DailyParams(audio_in_enabled=True), "twilio": lambda: FastAPIWebsocketParams(audio_in_enabled=True), diff --git a/examples/foundational/13c-gladia-transcription.py b/examples/foundational/13c-gladia-transcription.py index 24833fc5d..c98fda727 100644 --- a/examples/foundational/13c-gladia-transcription.py +++ b/examples/foundational/13c-gladia-transcription.py @@ -35,9 +35,8 @@ class TranscriptionLogger(FrameProcessor): await self.push_frame(frame, direction) -# We store functions so objects (e.g. SileroVADAnalyzer) don't get -# instantiated. The function will be called when the desired transport gets -# selected. +# We use lambdas to defer transport parameter creation until the transport +# type is selected at runtime. transport_params = { "daily": lambda: DailyParams(audio_in_enabled=True), "twilio": lambda: FastAPIWebsocketParams(audio_in_enabled=True), diff --git a/examples/foundational/13c-gladia-translation.py b/examples/foundational/13c-gladia-translation.py index 0f69f0649..edc294858 100644 --- a/examples/foundational/13c-gladia-translation.py +++ b/examples/foundational/13c-gladia-translation.py @@ -44,9 +44,8 @@ class TranscriptionLogger(FrameProcessor): await self.push_frame(frame, direction) -# We store functions so objects (e.g. SileroVADAnalyzer) don't get -# instantiated. The function will be called when the desired transport gets -# selected. +# We use lambdas to defer transport parameter creation until the transport +# type is selected at runtime. transport_params = { "daily": lambda: DailyParams(audio_in_enabled=True), "twilio": lambda: FastAPIWebsocketParams(audio_in_enabled=True), diff --git a/examples/foundational/13d-assemblyai-transcription.py b/examples/foundational/13d-assemblyai-transcription.py index a7da1f996..06ea52cd5 100644 --- a/examples/foundational/13d-assemblyai-transcription.py +++ b/examples/foundational/13d-assemblyai-transcription.py @@ -35,9 +35,8 @@ class TranscriptionLogger(FrameProcessor): await self.push_frame(frame, direction) -# We store functions so objects (e.g. SileroVADAnalyzer) don't get -# instantiated. The function will be called when the desired transport gets -# selected. +# We use lambdas to defer transport parameter creation until the transport +# type is selected at runtime. transport_params = { "daily": lambda: DailyParams(audio_in_enabled=True), "twilio": lambda: FastAPIWebsocketParams(audio_in_enabled=True), diff --git a/examples/foundational/13e-whisper-mlx.py b/examples/foundational/13e-whisper-mlx.py index 609ebf5f6..ba90d0850 100644 --- a/examples/foundational/13e-whisper-mlx.py +++ b/examples/foundational/13e-whisper-mlx.py @@ -56,9 +56,8 @@ class TranscriptionLogger(FrameProcessor): await self.push_frame(frame, direction) -# We store functions so objects (e.g. SileroVADAnalyzer) don't get -# instantiated. The function will be called when the desired transport gets -# selected. +# We use lambdas to defer transport parameter creation until the transport +# type is selected at runtime. transport_params = { "daily": lambda: DailyParams( audio_in_enabled=True, diff --git a/examples/foundational/13f-cartesia-transcription.py b/examples/foundational/13f-cartesia-transcription.py index c8c39629a..d3b83abb0 100644 --- a/examples/foundational/13f-cartesia-transcription.py +++ b/examples/foundational/13f-cartesia-transcription.py @@ -35,9 +35,8 @@ class TranscriptionLogger(FrameProcessor): await self.push_frame(frame, direction) -# We store functions so objects (e.g. SileroVADAnalyzer) don't get -# instantiated. The function will be called when the desired transport gets -# selected. +# We use lambdas to defer transport parameter creation until the transport +# type is selected at runtime. transport_params = { "daily": lambda: DailyParams(audio_in_enabled=True), "twilio": lambda: FastAPIWebsocketParams(audio_in_enabled=True), diff --git a/examples/foundational/13g-sambanova-transcription.py b/examples/foundational/13g-sambanova-transcription.py index bcccf2963..cebeea615 100644 --- a/examples/foundational/13g-sambanova-transcription.py +++ b/examples/foundational/13g-sambanova-transcription.py @@ -57,9 +57,8 @@ class TranscriptionLogger(FrameProcessor): await self.push_frame(frame, direction) -# We store functions so objects (e.g. SileroVADAnalyzer) don't get -# instantiated. The function will be called when the desired transport gets -# selected. +# We use lambdas to defer transport parameter creation until the transport +# type is selected at runtime. transport_params = { "daily": lambda: DailyParams( audio_in_enabled=True, diff --git a/examples/foundational/13h-speechmatics-transcription.py b/examples/foundational/13h-speechmatics-transcription.py index eb5b4148f..f1d1d93c6 100644 --- a/examples/foundational/13h-speechmatics-transcription.py +++ b/examples/foundational/13h-speechmatics-transcription.py @@ -36,9 +36,8 @@ class TranscriptionLogger(FrameProcessor): await self.push_frame(frame, direction) -# We store functions so objects (e.g. SileroVADAnalyzer) don't get -# instantiated. The function will be called when the desired transport gets -# selected. +# We use lambdas to defer transport parameter creation until the transport +# type is selected at runtime. transport_params = { "daily": lambda: DailyParams(audio_in_enabled=True), "twilio": lambda: FastAPIWebsocketParams(audio_in_enabled=True), diff --git a/examples/foundational/13k-elevenlabs-transcription.py b/examples/foundational/13k-elevenlabs-transcription.py index 2568508f2..f27bbb52a 100644 --- a/examples/foundational/13k-elevenlabs-transcription.py +++ b/examples/foundational/13k-elevenlabs-transcription.py @@ -37,9 +37,8 @@ class TranscriptionLogger(FrameProcessor): await self.push_frame(frame, direction) -# We store functions so objects (e.g. SileroVADAnalyzer) don't get -# instantiated. The function will be called when the desired transport gets -# selected. +# We use lambdas to defer transport parameter creation until the transport +# type is selected at runtime. transport_params = { "daily": lambda: DailyParams(audio_in_enabled=True, vad_analyzer=SileroVADAnalyzer()), "twilio": lambda: FastAPIWebsocketParams( diff --git a/examples/foundational/14-function-calling.py b/examples/foundational/14-function-calling.py index 22f84397c..a1cda33f6 100644 --- a/examples/foundational/14-function-calling.py +++ b/examples/foundational/14-function-calling.py @@ -46,24 +46,20 @@ async def fetch_restaurant_recommendation(params: FunctionCallParams): await params.result_callback({"name": "The Golden Dragon"}) -# We store functions so objects (e.g. SileroVADAnalyzer) don't get -# instantiated. The function will be called when the desired transport gets -# selected. +# We use lambdas to defer transport parameter creation until the transport +# type is selected at runtime. transport_params = { "daily": lambda: DailyParams( audio_in_enabled=True, audio_out_enabled=True, - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), "twilio": lambda: FastAPIWebsocketParams( audio_in_enabled=True, audio_out_enabled=True, - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), "webrtc": lambda: TransportParams( audio_in_enabled=True, audio_out_enabled=True, - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), } @@ -132,6 +128,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): user_turn_strategies=UserTurnStrategies( stop=[TurnAnalyzerUserTurnStopStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3())] ), + vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), ) diff --git a/examples/foundational/14a-function-calling-anthropic.py b/examples/foundational/14a-function-calling-anthropic.py index 08133cf83..783ea7c7c 100644 --- a/examples/foundational/14a-function-calling-anthropic.py +++ b/examples/foundational/14a-function-calling-anthropic.py @@ -48,24 +48,20 @@ async def fetch_restaurant_recommendation(params: FunctionCallParams): await params.result_callback({"name": "The Golden Dragon"}) -# We store functions so objects (e.g. SileroVADAnalyzer) don't get -# instantiated. The function will be called when the desired transport gets -# selected. +# We use lambdas to defer transport parameter creation until the transport +# type is selected at runtime. transport_params = { "daily": lambda: DailyParams( audio_in_enabled=True, audio_out_enabled=True, - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), "twilio": lambda: FastAPIWebsocketParams( audio_in_enabled=True, audio_out_enabled=True, - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), "webrtc": lambda: TransportParams( audio_in_enabled=True, audio_out_enabled=True, - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), } @@ -127,6 +123,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): user_turn_strategies=UserTurnStrategies( stop=[TurnAnalyzerUserTurnStopStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3())] ), + vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), ) diff --git a/examples/foundational/14c-function-calling-together.py b/examples/foundational/14c-function-calling-together.py index a4bf5cd19..49f5b98e3 100644 --- a/examples/foundational/14c-function-calling-together.py +++ b/examples/foundational/14c-function-calling-together.py @@ -43,24 +43,20 @@ async def fetch_weather_from_api(params: FunctionCallParams): await params.result_callback({"conditions": "nice", "temperature": "75"}) -# We store functions so objects (e.g. SileroVADAnalyzer) don't get -# instantiated. The function will be called when the desired transport gets -# selected. +# We use lambdas to defer transport parameter creation until the transport +# type is selected at runtime. transport_params = { "daily": lambda: DailyParams( audio_in_enabled=True, audio_out_enabled=True, - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), "twilio": lambda: FastAPIWebsocketParams( audio_in_enabled=True, audio_out_enabled=True, - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), "webrtc": lambda: TransportParams( audio_in_enabled=True, audio_out_enabled=True, - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), } @@ -118,6 +114,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): user_turn_strategies=UserTurnStrategies( stop=[TurnAnalyzerUserTurnStopStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3())] ), + vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), ) diff --git a/examples/foundational/14d-function-calling-anthropic-video.py b/examples/foundational/14d-function-calling-anthropic-video.py index c9dacaa75..971016fdf 100644 --- a/examples/foundational/14d-function-calling-anthropic-video.py +++ b/examples/foundational/14d-function-calling-anthropic-video.py @@ -71,21 +71,18 @@ async def fetch_user_image(params: FunctionCallParams): ) -# We store functions so objects (e.g. SileroVADAnalyzer) don't get -# instantiated. The function will be called when the desired transport gets -# selected. +# We use lambdas to defer transport parameter creation until the transport +# type is selected at runtime. transport_params = { "daily": lambda: DailyParams( audio_in_enabled=True, audio_out_enabled=True, video_in_enabled=True, - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), "webrtc": lambda: TransportParams( audio_in_enabled=True, audio_out_enabled=True, video_in_enabled=True, - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), } @@ -139,6 +136,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): user_turn_strategies=UserTurnStrategies( stop=[TurnAnalyzerUserTurnStopStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3())] ), + vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), ) diff --git a/examples/foundational/14d-function-calling-aws-video.py b/examples/foundational/14d-function-calling-aws-video.py index 9faa925aa..a78500819 100644 --- a/examples/foundational/14d-function-calling-aws-video.py +++ b/examples/foundational/14d-function-calling-aws-video.py @@ -71,21 +71,18 @@ async def fetch_user_image(params: FunctionCallParams): ) -# We store functions so objects (e.g. SileroVADAnalyzer) don't get -# instantiated. The function will be called when the desired transport gets -# selected. +# We use lambdas to defer transport parameter creation until the transport +# type is selected at runtime. transport_params = { "daily": lambda: DailyParams( audio_in_enabled=True, audio_out_enabled=True, video_in_enabled=True, - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), "webrtc": lambda: TransportParams( audio_in_enabled=True, audio_out_enabled=True, video_in_enabled=True, - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), } @@ -146,6 +143,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): user_turn_strategies=UserTurnStrategies( stop=[TurnAnalyzerUserTurnStopStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3())] ), + vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), ) diff --git a/examples/foundational/14d-function-calling-gemini-flash-video.py b/examples/foundational/14d-function-calling-gemini-flash-video.py index 857eb92b6..9470f19ca 100644 --- a/examples/foundational/14d-function-calling-gemini-flash-video.py +++ b/examples/foundational/14d-function-calling-gemini-flash-video.py @@ -71,21 +71,18 @@ async def fetch_user_image(params: FunctionCallParams): ) -# We store functions so objects (e.g. SileroVADAnalyzer) don't get -# instantiated. The function will be called when the desired transport gets -# selected. +# We use lambdas to defer transport parameter creation until the transport +# type is selected at runtime. transport_params = { "daily": lambda: DailyParams( audio_in_enabled=True, audio_out_enabled=True, video_in_enabled=True, - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), "webrtc": lambda: TransportParams( audio_in_enabled=True, audio_out_enabled=True, video_in_enabled=True, - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), } @@ -139,6 +136,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): user_turn_strategies=UserTurnStrategies( stop=[TurnAnalyzerUserTurnStopStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3())] ), + vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), ) diff --git a/examples/foundational/14d-function-calling-moondream-video.py b/examples/foundational/14d-function-calling-moondream-video.py index 3e64d5bd8..263b51215 100644 --- a/examples/foundational/14d-function-calling-moondream-video.py +++ b/examples/foundational/14d-function-calling-moondream-video.py @@ -102,21 +102,18 @@ class MoondreamTextFrameWrapper(FrameProcessor): await self.push_frame(frame, direction) -# We store functions so objects (e.g. SileroVADAnalyzer) don't get -# instantiated. The function will be called when the desired transport gets -# selected. +# We use lambdas to defer transport parameter creation until the transport +# type is selected at runtime. transport_params = { "daily": lambda: DailyParams( audio_in_enabled=True, audio_out_enabled=True, video_in_enabled=True, - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), "webrtc": lambda: TransportParams( audio_in_enabled=True, audio_out_enabled=True, video_in_enabled=True, - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), } @@ -169,6 +166,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): user_turn_strategies=UserTurnStrategies( stop=[TurnAnalyzerUserTurnStopStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3())] ), + vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), ) diff --git a/examples/foundational/14d-function-calling-openai-video.py b/examples/foundational/14d-function-calling-openai-video.py index ec201cc3a..ea18b0d11 100644 --- a/examples/foundational/14d-function-calling-openai-video.py +++ b/examples/foundational/14d-function-calling-openai-video.py @@ -72,21 +72,18 @@ async def fetch_user_image(params: FunctionCallParams): ) -# We store functions so objects (e.g. SileroVADAnalyzer) don't get -# instantiated. The function will be called when the desired transport gets -# selected. +# We use lambdas to defer transport parameter creation until the transport +# type is selected at runtime. transport_params = { "daily": lambda: DailyParams( audio_in_enabled=True, audio_out_enabled=True, video_in_enabled=True, - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), "webrtc": lambda: TransportParams( audio_in_enabled=True, audio_out_enabled=True, video_in_enabled=True, - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), } @@ -139,6 +136,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): user_turn_strategies=UserTurnStrategies( stop=[TurnAnalyzerUserTurnStopStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3())] ), + vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), ) diff --git a/examples/foundational/14e-function-calling-google.py b/examples/foundational/14e-function-calling-google.py index 56cdd53c1..e8757bb71 100644 --- a/examples/foundational/14e-function-calling-google.py +++ b/examples/foundational/14e-function-calling-google.py @@ -81,21 +81,18 @@ async def get_image(params: FunctionCallParams): ) -# We store functions so objects (e.g. SileroVADAnalyzer) don't get -# instantiated. The function will be called when the desired transport gets -# selected. +# We use lambdas to defer transport parameter creation until the transport +# type is selected at runtime. transport_params = { "daily": lambda: DailyParams( audio_in_enabled=True, audio_out_enabled=True, video_in_enabled=True, - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), "webrtc": lambda: TransportParams( audio_in_enabled=True, audio_out_enabled=True, video_in_enabled=True, - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), } @@ -192,6 +189,7 @@ indicate you should use the get_image tool are: user_turn_strategies=UserTurnStrategies( stop=[TurnAnalyzerUserTurnStopStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3())] ), + vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), ) diff --git a/examples/foundational/14f-function-calling-groq.py b/examples/foundational/14f-function-calling-groq.py index 989dafb0e..ff410cb6e 100644 --- a/examples/foundational/14f-function-calling-groq.py +++ b/examples/foundational/14f-function-calling-groq.py @@ -43,24 +43,20 @@ async def fetch_weather_from_api(params: FunctionCallParams): await params.result_callback({"conditions": "nice", "temperature": "75"}) -# We store functions so objects (e.g. SileroVADAnalyzer) don't get -# instantiated. The function will be called when the desired transport gets -# selected. +# We use lambdas to defer transport parameter creation until the transport +# type is selected at runtime. transport_params = { "daily": lambda: DailyParams( audio_in_enabled=True, audio_out_enabled=True, - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), "twilio": lambda: FastAPIWebsocketParams( audio_in_enabled=True, audio_out_enabled=True, - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), "webrtc": lambda: TransportParams( audio_in_enabled=True, audio_out_enabled=True, - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), } @@ -115,6 +111,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): user_turn_strategies=UserTurnStrategies( stop=[TurnAnalyzerUserTurnStopStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3())] ), + vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), ) diff --git a/examples/foundational/14g-function-calling-grok.py b/examples/foundational/14g-function-calling-grok.py index cfb52cbc5..ba087c2f9 100644 --- a/examples/foundational/14g-function-calling-grok.py +++ b/examples/foundational/14g-function-calling-grok.py @@ -43,24 +43,20 @@ async def fetch_weather_from_api(params: FunctionCallParams): await params.result_callback({"conditions": "nice", "temperature": "75"}) -# We store functions so objects (e.g. SileroVADAnalyzer) don't get -# instantiated. The function will be called when the desired transport gets -# selected. +# We use lambdas to defer transport parameter creation until the transport +# type is selected at runtime. transport_params = { "daily": lambda: DailyParams( audio_in_enabled=True, audio_out_enabled=True, - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), "twilio": lambda: FastAPIWebsocketParams( audio_in_enabled=True, audio_out_enabled=True, - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), "webrtc": lambda: TransportParams( audio_in_enabled=True, audio_out_enabled=True, - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), } @@ -111,6 +107,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): user_turn_strategies=UserTurnStrategies( stop=[TurnAnalyzerUserTurnStopStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3())] ), + vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), ) diff --git a/examples/foundational/14h-function-calling-azure.py b/examples/foundational/14h-function-calling-azure.py index a108a7779..c4036c282 100644 --- a/examples/foundational/14h-function-calling-azure.py +++ b/examples/foundational/14h-function-calling-azure.py @@ -43,24 +43,20 @@ async def fetch_weather_from_api(params: FunctionCallParams): await params.result_callback({"conditions": "nice", "temperature": "75"}) -# We store functions so objects (e.g. SileroVADAnalyzer) don't get -# instantiated. The function will be called when the desired transport gets -# selected. +# We use lambdas to defer transport parameter creation until the transport +# type is selected at runtime. transport_params = { "daily": lambda: DailyParams( audio_in_enabled=True, audio_out_enabled=True, - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), "twilio": lambda: FastAPIWebsocketParams( audio_in_enabled=True, audio_out_enabled=True, - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), "webrtc": lambda: TransportParams( audio_in_enabled=True, audio_out_enabled=True, - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), } @@ -119,6 +115,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): user_turn_strategies=UserTurnStrategies( stop=[TurnAnalyzerUserTurnStopStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3())] ), + vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), ) diff --git a/examples/foundational/14i-function-calling-fireworks.py b/examples/foundational/14i-function-calling-fireworks.py index 9b1692430..61dc21af5 100644 --- a/examples/foundational/14i-function-calling-fireworks.py +++ b/examples/foundational/14i-function-calling-fireworks.py @@ -43,24 +43,20 @@ async def fetch_weather_from_api(params: FunctionCallParams): await params.result_callback({"conditions": "nice", "temperature": "75"}) -# We store functions so objects (e.g. SileroVADAnalyzer) don't get -# instantiated. The function will be called when the desired transport gets -# selected. +# We use lambdas to defer transport parameter creation until the transport +# type is selected at runtime. transport_params = { "daily": lambda: DailyParams( audio_in_enabled=True, audio_out_enabled=True, - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), "twilio": lambda: FastAPIWebsocketParams( audio_in_enabled=True, audio_out_enabled=True, - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), "webrtc": lambda: TransportParams( audio_in_enabled=True, audio_out_enabled=True, - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), } @@ -122,6 +118,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): user_turn_strategies=UserTurnStrategies( stop=[TurnAnalyzerUserTurnStopStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3())] ), + vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), ) diff --git a/examples/foundational/14j-function-calling-nvidia.py b/examples/foundational/14j-function-calling-nvidia.py index 354e0fbdb..52c737d18 100644 --- a/examples/foundational/14j-function-calling-nvidia.py +++ b/examples/foundational/14j-function-calling-nvidia.py @@ -43,24 +43,20 @@ async def fetch_weather_from_api(params: FunctionCallParams): await params.result_callback({"conditions": "nice", "temperature": "75"}) -# We store functions so objects (e.g. SileroVADAnalyzer) don't get -# instantiated. The function will be called when the desired transport gets -# selected. +# We use lambdas to defer transport parameter creation until the transport +# type is selected at runtime. transport_params = { "daily": lambda: DailyParams( audio_in_enabled=True, audio_out_enabled=True, - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), "twilio": lambda: FastAPIWebsocketParams( audio_in_enabled=True, audio_out_enabled=True, - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), "webrtc": lambda: TransportParams( audio_in_enabled=True, audio_out_enabled=True, - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), } @@ -124,6 +120,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): user_turn_strategies=UserTurnStrategies( stop=[TurnAnalyzerUserTurnStopStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3())] ), + vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), ) diff --git a/examples/foundational/14k-function-calling-cerebras.py b/examples/foundational/14k-function-calling-cerebras.py index 994c29169..fc1c821e1 100644 --- a/examples/foundational/14k-function-calling-cerebras.py +++ b/examples/foundational/14k-function-calling-cerebras.py @@ -43,24 +43,20 @@ async def fetch_weather_from_api(params: FunctionCallParams): await params.result_callback({"conditions": "nice", "temperature": "75"}) -# We store functions so objects (e.g. SileroVADAnalyzer) don't get -# instantiated. The function will be called when the desired transport gets -# selected. +# We use lambdas to defer transport parameter creation until the transport +# type is selected at runtime. transport_params = { "daily": lambda: DailyParams( audio_in_enabled=True, audio_out_enabled=True, - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), "twilio": lambda: FastAPIWebsocketParams( audio_in_enabled=True, audio_out_enabled=True, - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), "webrtc": lambda: TransportParams( audio_in_enabled=True, audio_out_enabled=True, - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), } @@ -125,6 +121,7 @@ Start by asking me for my location. Then, use 'get_weather_current' to give me a user_turn_strategies=UserTurnStrategies( stop=[TurnAnalyzerUserTurnStopStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3())] ), + vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), ) diff --git a/examples/foundational/14l-function-calling-deepseek.py b/examples/foundational/14l-function-calling-deepseek.py index fc9dc5677..8be0b93d7 100644 --- a/examples/foundational/14l-function-calling-deepseek.py +++ b/examples/foundational/14l-function-calling-deepseek.py @@ -43,24 +43,20 @@ async def fetch_weather_from_api(params: FunctionCallParams): await params.result_callback({"conditions": "nice", "temperature": "75"}) -# We store functions so objects (e.g. SileroVADAnalyzer) don't get -# instantiated. The function will be called when the desired transport gets -# selected. +# We use lambdas to defer transport parameter creation until the transport +# type is selected at runtime. transport_params = { "daily": lambda: DailyParams( audio_in_enabled=True, audio_out_enabled=True, - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), "twilio": lambda: FastAPIWebsocketParams( audio_in_enabled=True, audio_out_enabled=True, - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), "webrtc": lambda: TransportParams( audio_in_enabled=True, audio_out_enabled=True, - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), } @@ -125,6 +121,7 @@ Start by asking me for my location. Then, use 'get_weather_current' to give me a user_turn_strategies=UserTurnStrategies( stop=[TurnAnalyzerUserTurnStopStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3())] ), + vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), ) diff --git a/examples/foundational/14m-function-calling-openrouter.py b/examples/foundational/14m-function-calling-openrouter.py index 963da638b..eddf7e0e2 100644 --- a/examples/foundational/14m-function-calling-openrouter.py +++ b/examples/foundational/14m-function-calling-openrouter.py @@ -43,24 +43,20 @@ async def fetch_weather_from_api(params: FunctionCallParams): await params.result_callback({"conditions": "nice", "temperature": "75"}) -# We store functions so objects (e.g. SileroVADAnalyzer) don't get -# instantiated. The function will be called when the desired transport gets -# selected. +# We use lambdas to defer transport parameter creation until the transport +# type is selected at runtime. transport_params = { "daily": lambda: DailyParams( audio_in_enabled=True, audio_out_enabled=True, - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), "twilio": lambda: FastAPIWebsocketParams( audio_in_enabled=True, audio_out_enabled=True, - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), "webrtc": lambda: TransportParams( audio_in_enabled=True, audio_out_enabled=True, - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), } @@ -119,6 +115,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): user_turn_strategies=UserTurnStrategies( stop=[TurnAnalyzerUserTurnStopStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3())] ), + vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), ) diff --git a/examples/foundational/14n-function-calling-perplexity.py b/examples/foundational/14n-function-calling-perplexity.py index a3745cc5a..33d12fe88 100644 --- a/examples/foundational/14n-function-calling-perplexity.py +++ b/examples/foundational/14n-function-calling-perplexity.py @@ -41,24 +41,20 @@ from pipecat.turns.user_turn_strategies import UserTurnStrategies load_dotenv(override=True) -# We store functions so objects (e.g. SileroVADAnalyzer) don't get -# instantiated. The function will be called when the desired transport gets -# selected. +# We use lambdas to defer transport parameter creation until the transport +# type is selected at runtime. transport_params = { "daily": lambda: DailyParams( audio_in_enabled=True, audio_out_enabled=True, - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), "twilio": lambda: FastAPIWebsocketParams( audio_in_enabled=True, audio_out_enabled=True, - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), "webrtc": lambda: TransportParams( audio_in_enabled=True, audio_out_enabled=True, - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), } @@ -89,6 +85,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): user_turn_strategies=UserTurnStrategies( stop=[TurnAnalyzerUserTurnStopStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3())] ), + vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), ) diff --git a/examples/foundational/14o-function-calling-gemini-openai-format.py b/examples/foundational/14o-function-calling-gemini-openai-format.py index 8c6356507..4490d30b0 100644 --- a/examples/foundational/14o-function-calling-gemini-openai-format.py +++ b/examples/foundational/14o-function-calling-gemini-openai-format.py @@ -37,9 +37,8 @@ async def fetch_weather_from_api(params: FunctionCallParams): await params.result_callback({"conditions": "nice", "temperature": "75"}) -# We store functions so objects (e.g. SileroVADAnalyzer) don't get -# instantiated. The function will be called when the desired transport gets -# selected. +# We use lambdas to defer transport parameter creation until the transport +# type is selected at runtime. transport_params = { "daily": lambda: DailyParams( audio_in_enabled=True, diff --git a/examples/foundational/14p-function-calling-gemini-vertex-ai.py b/examples/foundational/14p-function-calling-gemini-vertex-ai.py index 0fe2da06d..e75c288ad 100644 --- a/examples/foundational/14p-function-calling-gemini-vertex-ai.py +++ b/examples/foundational/14p-function-calling-gemini-vertex-ai.py @@ -43,24 +43,20 @@ async def fetch_weather_from_api(params: FunctionCallParams): await params.result_callback({"conditions": "nice", "temperature": "75"}) -# We store functions so objects (e.g. SileroVADAnalyzer) don't get -# instantiated. The function will be called when the desired transport gets -# selected. +# We use lambdas to defer transport parameter creation until the transport +# type is selected at runtime. transport_params = { "daily": lambda: DailyParams( audio_in_enabled=True, audio_out_enabled=True, - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), "twilio": lambda: FastAPIWebsocketParams( audio_in_enabled=True, audio_out_enabled=True, - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), "webrtc": lambda: TransportParams( audio_in_enabled=True, audio_out_enabled=True, - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), } @@ -120,6 +116,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): user_turn_strategies=UserTurnStrategies( stop=[TurnAnalyzerUserTurnStopStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3())] ), + vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), ) diff --git a/examples/foundational/14q-function-calling-qwen.py b/examples/foundational/14q-function-calling-qwen.py index 9b6c641ed..2363c840f 100644 --- a/examples/foundational/14q-function-calling-qwen.py +++ b/examples/foundational/14q-function-calling-qwen.py @@ -43,24 +43,20 @@ async def fetch_weather_from_api(params: FunctionCallParams): await params.result_callback({"conditions": "nice", "temperature": "75"}) -# We store functions so objects (e.g. SileroVADAnalyzer) don't get -# instantiated. The function will be called when the desired transport gets -# selected. +# We use lambdas to defer transport parameter creation until the transport +# type is selected at runtime. transport_params = { "daily": lambda: DailyParams( audio_in_enabled=True, audio_out_enabled=True, - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), "twilio": lambda: FastAPIWebsocketParams( audio_in_enabled=True, audio_out_enabled=True, - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), "webrtc": lambda: TransportParams( audio_in_enabled=True, audio_out_enabled=True, - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), } @@ -117,6 +113,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): user_turn_strategies=UserTurnStrategies( stop=[TurnAnalyzerUserTurnStopStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3())] ), + vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), ) diff --git a/examples/foundational/14r-function-calling-aws.py b/examples/foundational/14r-function-calling-aws.py index ff438ac27..7e144dc9e 100644 --- a/examples/foundational/14r-function-calling-aws.py +++ b/examples/foundational/14r-function-calling-aws.py @@ -45,24 +45,20 @@ async def fetch_restaurant_recommendation(params: FunctionCallParams): await params.result_callback({"name": "The Golden Dragon"}) -# We store functions so objects (e.g. SileroVADAnalyzer) don't get -# instantiated. The function will be called when the desired transport gets -# selected. +# We use lambdas to defer transport parameter creation until the transport +# type is selected at runtime. transport_params = { "daily": lambda: DailyParams( audio_in_enabled=True, audio_out_enabled=True, - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), "twilio": lambda: FastAPIWebsocketParams( audio_in_enabled=True, audio_out_enabled=True, - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), "webrtc": lambda: TransportParams( audio_in_enabled=True, audio_out_enabled=True, - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), } @@ -132,6 +128,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): user_turn_strategies=UserTurnStrategies( stop=[TurnAnalyzerUserTurnStopStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3())] ), + vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), ) diff --git a/examples/foundational/14s-function-calling-sambanova.py b/examples/foundational/14s-function-calling-sambanova.py index 60076e370..025aa1cc9 100644 --- a/examples/foundational/14s-function-calling-sambanova.py +++ b/examples/foundational/14s-function-calling-sambanova.py @@ -43,24 +43,20 @@ async def fetch_weather_from_api(params: FunctionCallParams): await params.result_callback({"conditions": "nice", "temperature": "75"}) -# We store functions so objects (e.g. SileroVADAnalyzer) don't get -# instantiated. The function will be called when the desired transport gets -# selected. +# We use lambdas to defer transport parameter creation until the transport +# type is selected at runtime. transport_params = { "daily": lambda: DailyParams( audio_in_enabled=True, audio_out_enabled=True, - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), "twilio": lambda: FastAPIWebsocketParams( audio_in_enabled=True, audio_out_enabled=True, - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), "webrtc": lambda: TransportParams( audio_in_enabled=True, audio_out_enabled=True, - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), } @@ -121,6 +117,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): user_turn_strategies=UserTurnStrategies( stop=[TurnAnalyzerUserTurnStopStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3())] ), + vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), ) diff --git a/examples/foundational/14t-function-calling-direct.py b/examples/foundational/14t-function-calling-direct.py index ae6db7564..59e09a76a 100644 --- a/examples/foundational/14t-function-calling-direct.py +++ b/examples/foundational/14t-function-calling-direct.py @@ -59,24 +59,20 @@ async def get_restaurant_recommendation(params: FunctionCallParams, location: st await params.result_callback({"name": "The Golden Dragon"}) -# We store functions so objects (e.g. SileroVADAnalyzer) don't get -# instantiated. The function will be called when the desired transport gets -# selected. +# We use lambdas to defer transport parameter creation until the transport +# type is selected at runtime. transport_params = { "daily": lambda: DailyParams( audio_in_enabled=True, audio_out_enabled=True, - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), "twilio": lambda: FastAPIWebsocketParams( audio_in_enabled=True, audio_out_enabled=True, - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), "webrtc": lambda: TransportParams( audio_in_enabled=True, audio_out_enabled=True, - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), } @@ -118,6 +114,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): user_turn_strategies=UserTurnStrategies( stop=[TurnAnalyzerUserTurnStopStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3())] ), + vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), ) diff --git a/examples/foundational/14u-function-calling-ollama.py b/examples/foundational/14u-function-calling-ollama.py index a76c65dd8..ed04c2236 100644 --- a/examples/foundational/14u-function-calling-ollama.py +++ b/examples/foundational/14u-function-calling-ollama.py @@ -47,24 +47,20 @@ async def fetch_restaurant_recommendation(params: FunctionCallParams): await params.result_callback({"name": "The Golden Dragon"}) -# We store functions so objects (e.g. SileroVADAnalyzer) don't get -# instantiated. The function will be called when the desired transport gets -# selected. +# We use lambdas to defer transport parameter creation until the transport +# type is selected at runtime. transport_params = { "daily": lambda: DailyParams( audio_in_enabled=True, audio_out_enabled=True, - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), "twilio": lambda: FastAPIWebsocketParams( audio_in_enabled=True, audio_out_enabled=True, - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), "webrtc": lambda: TransportParams( audio_in_enabled=True, audio_out_enabled=True, - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), } @@ -133,6 +129,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): user_turn_strategies=UserTurnStrategies( stop=[TurnAnalyzerUserTurnStopStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3())] ), + vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), ) diff --git a/examples/foundational/14v-function-calling-openai.py b/examples/foundational/14v-function-calling-openai.py index ac60c0901..7265ce73a 100644 --- a/examples/foundational/14v-function-calling-openai.py +++ b/examples/foundational/14v-function-calling-openai.py @@ -46,24 +46,20 @@ async def fetch_restaurant_recommendation(params: FunctionCallParams): await params.result_callback({"name": "The Golden Dragon"}) -# We store functions so objects (e.g. SileroVADAnalyzer) don't get -# instantiated. The function will be called when the desired transport gets -# selected. +# We use lambdas to defer transport parameter creation until the transport +# type is selected at runtime. transport_params = { "daily": lambda: DailyParams( audio_in_enabled=True, audio_out_enabled=True, - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), "twilio": lambda: FastAPIWebsocketParams( audio_in_enabled=True, audio_out_enabled=True, - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), "webrtc": lambda: TransportParams( audio_in_enabled=True, audio_out_enabled=True, - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), } @@ -140,6 +136,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): user_turn_strategies=UserTurnStrategies( stop=[TurnAnalyzerUserTurnStopStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3())] ), + vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), ) diff --git a/examples/foundational/14w-function-calling-mistral.py b/examples/foundational/14w-function-calling-mistral.py index 721726f82..03b344df5 100644 --- a/examples/foundational/14w-function-calling-mistral.py +++ b/examples/foundational/14w-function-calling-mistral.py @@ -46,24 +46,20 @@ async def fetch_restaurant_recommendation(params: FunctionCallParams): await params.result_callback({"name": "The Golden Dragon"}) -# We store functions so objects (e.g. SileroVADAnalyzer) don't get -# instantiated. The function will be called when the desired transport gets -# selected. +# We use lambdas to defer transport parameter creation until the transport +# type is selected at runtime. transport_params = { "daily": lambda: DailyParams( audio_in_enabled=True, audio_out_enabled=True, - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), "twilio": lambda: FastAPIWebsocketParams( audio_in_enabled=True, audio_out_enabled=True, - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), "webrtc": lambda: TransportParams( audio_in_enabled=True, audio_out_enabled=True, - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), } @@ -128,6 +124,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): user_turn_strategies=UserTurnStrategies( stop=[TurnAnalyzerUserTurnStopStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3())] ), + vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), ) diff --git a/examples/foundational/14x-function-calling-openpipe.py b/examples/foundational/14x-function-calling-openpipe.py index 42c951a4e..7a4a5f2e7 100644 --- a/examples/foundational/14x-function-calling-openpipe.py +++ b/examples/foundational/14x-function-calling-openpipe.py @@ -47,24 +47,20 @@ async def fetch_restaurant_recommendation(params: FunctionCallParams): await params.result_callback({"name": "The Golden Dragon"}) -# We store functions so objects (e.g. SileroVADAnalyzer) don't get -# instantiated. The function will be called when the desired transport gets -# selected. +# We use lambdas to defer transport parameter creation until the transport +# type is selected at runtime. transport_params = { "daily": lambda: DailyParams( audio_in_enabled=True, audio_out_enabled=True, - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), "twilio": lambda: FastAPIWebsocketParams( audio_in_enabled=True, audio_out_enabled=True, - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), "webrtc": lambda: TransportParams( audio_in_enabled=True, audio_out_enabled=True, - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), } @@ -138,6 +134,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): user_turn_strategies=UserTurnStrategies( stop=[TurnAnalyzerUserTurnStopStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3())] ), + vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), ) diff --git a/examples/foundational/15-switch-voices.py b/examples/foundational/15-switch-voices.py index ff0a0e9f7..d0684b045 100644 --- a/examples/foundational/15-switch-voices.py +++ b/examples/foundational/15-switch-voices.py @@ -91,24 +91,20 @@ class SwitchVoices(ParallelPipeline): return self.current_voice == "Barbershop Man" -# We store functions so objects (e.g. SileroVADAnalyzer) don't get -# instantiated. The function will be called when the desired transport gets -# selected. +# We use lambdas to defer transport parameter creation until the transport +# type is selected at runtime. transport_params = { "daily": lambda: DailyParams( audio_in_enabled=True, audio_out_enabled=True, - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), "twilio": lambda: FastAPIWebsocketParams( audio_in_enabled=True, audio_out_enabled=True, - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), "webrtc": lambda: TransportParams( audio_in_enabled=True, audio_out_enabled=True, - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), } @@ -150,6 +146,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): user_turn_strategies=UserTurnStrategies( stop=[TurnAnalyzerUserTurnStopStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3())] ), + vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), ) diff --git a/examples/foundational/15a-switch-languages.py b/examples/foundational/15a-switch-languages.py index 73e818bc5..c92b6b5e5 100644 --- a/examples/foundational/15a-switch-languages.py +++ b/examples/foundational/15a-switch-languages.py @@ -80,24 +80,20 @@ class SwitchLanguage(ParallelPipeline): return self.current_language == "Spanish" -# We store functions so objects (e.g. SileroVADAnalyzer) don't get -# instantiated. The function will be called when the desired transport gets -# selected. +# We use lambdas to defer transport parameter creation until the transport +# type is selected at runtime. transport_params = { "daily": lambda: DailyParams( audio_in_enabled=True, audio_out_enabled=True, - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), "twilio": lambda: FastAPIWebsocketParams( audio_in_enabled=True, audio_out_enabled=True, - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), "webrtc": lambda: TransportParams( audio_in_enabled=True, audio_out_enabled=True, - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), } @@ -140,6 +136,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): user_turn_strategies=UserTurnStrategies( stop=[TurnAnalyzerUserTurnStopStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3())] ), + vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), ) diff --git a/examples/foundational/16-gpu-container-local-bot.py b/examples/foundational/16-gpu-container-local-bot.py index a64edcec2..84e28259b 100644 --- a/examples/foundational/16-gpu-container-local-bot.py +++ b/examples/foundational/16-gpu-container-local-bot.py @@ -39,24 +39,20 @@ from pipecat.turns.user_turn_strategies import UserTurnStrategies load_dotenv(override=True) -# We store functions so objects (e.g. SileroVADAnalyzer) don't get -# instantiated. The function will be called when the desired transport gets -# selected. +# We use lambdas to defer transport parameter creation until the transport +# type is selected at runtime. transport_params = { "daily": lambda: DailyParams( audio_in_enabled=True, audio_out_enabled=True, - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), "twilio": lambda: FastAPIWebsocketParams( audio_in_enabled=True, audio_out_enabled=True, - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), "webrtc": lambda: TransportParams( audio_in_enabled=True, audio_out_enabled=True, - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), } @@ -94,6 +90,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): user_turn_strategies=UserTurnStrategies( stop=[TurnAnalyzerUserTurnStopStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3())] ), + vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), ) diff --git a/examples/foundational/17-detect-user-idle.py b/examples/foundational/17-detect-user-idle.py index 52277a584..a7d7c6f69 100644 --- a/examples/foundational/17-detect-user-idle.py +++ b/examples/foundational/17-detect-user-idle.py @@ -78,24 +78,20 @@ class IdleHandler: await aggregator.push_frame(EndTaskFrame(), FrameDirection.UPSTREAM) -# We store functions so objects (e.g. SileroVADAnalyzer) don't get -# instantiated. The function will be called when the desired transport gets -# selected. +# We use lambdas to defer transport parameter creation until the transport +# type is selected at runtime. transport_params = { "daily": lambda: DailyParams( audio_in_enabled=True, audio_out_enabled=True, - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), "twilio": lambda: FastAPIWebsocketParams( audio_in_enabled=True, audio_out_enabled=True, - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), "webrtc": lambda: TransportParams( audio_in_enabled=True, audio_out_enabled=True, - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), } @@ -127,6 +123,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): stop=[TurnAnalyzerUserTurnStopStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3())] ), user_idle_timeout=5.0, # Detect user idle after 5 seconds + vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), ) diff --git a/examples/foundational/18-gstreamer-filesrc.py b/examples/foundational/18-gstreamer-filesrc.py index 56631c443..f1c3062b4 100644 --- a/examples/foundational/18-gstreamer-filesrc.py +++ b/examples/foundational/18-gstreamer-filesrc.py @@ -20,9 +20,8 @@ from pipecat.transports.daily.transport import DailyParams load_dotenv(override=True) -# We store functions so objects (e.g. SileroVADAnalyzer) don't get -# instantiated. The function will be called when the desired transport gets -# selected. +# We use lambdas to defer transport parameter creation until the transport +# type is selected at runtime. transport_params = { "daily": lambda: DailyParams( audio_out_enabled=True, diff --git a/examples/foundational/18a-gstreamer-videotestsrc.py b/examples/foundational/18a-gstreamer-videotestsrc.py index 3ab5cf8b7..8398f1f7f 100644 --- a/examples/foundational/18a-gstreamer-videotestsrc.py +++ b/examples/foundational/18a-gstreamer-videotestsrc.py @@ -19,9 +19,8 @@ from pipecat.transports.daily.transport import DailyParams load_dotenv(override=True) -# We store functions so objects (e.g. SileroVADAnalyzer) don't get -# instantiated. The function will be called when the desired transport gets -# selected. +# We use lambdas to defer transport parameter creation until the transport +# type is selected at runtime. transport_params = { "daily": lambda: DailyParams( video_out_enabled=True, diff --git a/examples/foundational/19-openai-realtime-beta.py b/examples/foundational/19-openai-realtime-beta.py index 37fe86f96..c69d0ca92 100644 --- a/examples/foundational/19-openai-realtime-beta.py +++ b/examples/foundational/19-openai-realtime-beta.py @@ -86,9 +86,8 @@ restaurant_function = FunctionSchema( tools = ToolsSchema(standard_tools=[weather_function, restaurant_function]) -# We store functions so objects (e.g. SileroVADAnalyzer) don't get -# instantiated. The function will be called when the desired transport gets -# selected. +# We use lambdas to defer transport parameter creation until the transport +# type is selected at runtime. transport_params = { "daily": lambda: DailyParams( audio_in_enabled=True, diff --git a/examples/foundational/19-openai-realtime.py b/examples/foundational/19-openai-realtime.py index 443a2817b..0d59782f1 100644 --- a/examples/foundational/19-openai-realtime.py +++ b/examples/foundational/19-openai-realtime.py @@ -113,9 +113,8 @@ restaurant_function = FunctionSchema( tools = ToolsSchema(standard_tools=[weather_function, restaurant_function]) -# We store functions so objects (e.g. SileroVADAnalyzer) don't get -# instantiated. The function will be called when the desired transport gets -# selected. +# We use lambdas to defer transport parameter creation until the transport +# type is selected at runtime. transport_params = { "daily": lambda: DailyParams( audio_in_enabled=True, diff --git a/examples/foundational/19a-azure-realtime-beta.py b/examples/foundational/19a-azure-realtime-beta.py index d287344cb..d25f53e96 100644 --- a/examples/foundational/19a-azure-realtime-beta.py +++ b/examples/foundational/19a-azure-realtime-beta.py @@ -84,9 +84,8 @@ restaurant_function = FunctionSchema( tools = ToolsSchema(standard_tools=[weather_function, restaurant_function]) -# We store functions so objects (e.g. SileroVADAnalyzer) don't get -# instantiated. The function will be called when the desired transport gets -# selected. +# We use lambdas to defer transport parameter creation until the transport +# type is selected at runtime. transport_params = { "daily": lambda: DailyParams( audio_in_enabled=True, diff --git a/examples/foundational/19a-azure-realtime.py b/examples/foundational/19a-azure-realtime.py index 20932da3c..6883a1f09 100644 --- a/examples/foundational/19a-azure-realtime.py +++ b/examples/foundational/19a-azure-realtime.py @@ -87,9 +87,8 @@ restaurant_function = FunctionSchema( tools = ToolsSchema(standard_tools=[weather_function, restaurant_function]) -# We store functions so objects (e.g. SileroVADAnalyzer) don't get -# instantiated. The function will be called when the desired transport gets -# selected. +# We use lambdas to defer transport parameter creation until the transport +# type is selected at runtime. transport_params = { "daily": lambda: DailyParams( audio_in_enabled=True, diff --git a/examples/foundational/19b-openai-realtime-beta-text.py b/examples/foundational/19b-openai-realtime-beta-text.py index 4ddd068a6..83e1563a0 100644 --- a/examples/foundational/19b-openai-realtime-beta-text.py +++ b/examples/foundational/19b-openai-realtime-beta-text.py @@ -86,9 +86,8 @@ restaurant_function = FunctionSchema( tools = ToolsSchema(standard_tools=[weather_function, restaurant_function]) -# We store functions so objects (e.g. SileroVADAnalyzer) don't get -# instantiated. The function will be called when the desired transport gets -# selected. +# We use lambdas to defer transport parameter creation until the transport +# type is selected at runtime. transport_params = { "daily": lambda: DailyParams( audio_in_enabled=True, diff --git a/examples/foundational/19b-openai-realtime-text.py b/examples/foundational/19b-openai-realtime-text.py index a3190f44c..38731d72a 100644 --- a/examples/foundational/19b-openai-realtime-text.py +++ b/examples/foundational/19b-openai-realtime-text.py @@ -89,9 +89,8 @@ restaurant_function = FunctionSchema( tools = ToolsSchema(standard_tools=[weather_function, restaurant_function]) -# We store functions so objects (e.g. SileroVADAnalyzer) don't get -# instantiated. The function will be called when the desired transport gets -# selected. +# We use lambdas to defer transport parameter creation until the transport +# type is selected at runtime. transport_params = { "daily": lambda: DailyParams( audio_in_enabled=True, diff --git a/examples/foundational/19c-openai-realtime-live-video.py b/examples/foundational/19c-openai-realtime-live-video.py index 31369717d..3f091f712 100644 --- a/examples/foundational/19c-openai-realtime-live-video.py +++ b/examples/foundational/19c-openai-realtime-live-video.py @@ -39,9 +39,8 @@ from pipecat.transports.daily.transport import DailyParams load_dotenv(override=True) -# We store functions so objects (e.g. SileroVADAnalyzer) don't get -# instantiated. The function will be called when the desired transport gets -# selected. +# We use lambdas to defer transport parameter creation until the transport +# type is selected at runtime. transport_params = { "daily": lambda: DailyParams( audio_in_enabled=True, diff --git a/examples/foundational/20a-persistent-context-openai.py b/examples/foundational/20a-persistent-context-openai.py index ae7c6ca8e..a98a7cd36 100644 --- a/examples/foundational/20a-persistent-context-openai.py +++ b/examples/foundational/20a-persistent-context-openai.py @@ -159,24 +159,20 @@ tools = ToolsSchema( ) -# We store functions so objects (e.g. SileroVADAnalyzer) don't get -# instantiated. The function will be called when the desired transport gets -# selected. +# We use lambdas to defer transport parameter creation until the transport +# type is selected at runtime. transport_params = { "daily": lambda: DailyParams( audio_in_enabled=True, audio_out_enabled=True, - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), "twilio": lambda: FastAPIWebsocketParams( audio_in_enabled=True, audio_out_enabled=True, - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), "webrtc": lambda: TransportParams( audio_in_enabled=True, audio_out_enabled=True, - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), } @@ -207,6 +203,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): user_turn_strategies=UserTurnStrategies( stop=[TurnAnalyzerUserTurnStopStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3())] ), + vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), ) diff --git a/examples/foundational/20b-persistent-context-openai-realtime-beta.py b/examples/foundational/20b-persistent-context-openai-realtime-beta.py index 19ccf81f7..cb4ffa642 100644 --- a/examples/foundational/20b-persistent-context-openai-realtime-beta.py +++ b/examples/foundational/20b-persistent-context-openai-realtime-beta.py @@ -155,9 +155,8 @@ tools = [ ] -# We store functions so objects (e.g. SileroVADAnalyzer) don't get -# instantiated. The function will be called when the desired transport gets -# selected. +# We use lambdas to defer transport parameter creation until the transport +# type is selected at runtime. transport_params = { "daily": lambda: DailyParams( audio_in_enabled=True, diff --git a/examples/foundational/20b-persistent-context-openai-realtime.py b/examples/foundational/20b-persistent-context-openai-realtime.py index 0d09cf40a..a24ff39e5 100644 --- a/examples/foundational/20b-persistent-context-openai-realtime.py +++ b/examples/foundational/20b-persistent-context-openai-realtime.py @@ -147,9 +147,8 @@ tools = ToolsSchema( ) -# We store functions so objects (e.g. SileroVADAnalyzer) don't get -# instantiated. The function will be called when the desired transport gets -# selected. +# We use lambdas to defer transport parameter creation until the transport +# type is selected at runtime. transport_params = { "daily": lambda: DailyParams( audio_in_enabled=True, diff --git a/examples/foundational/20c-persistent-context-anthropic.py b/examples/foundational/20c-persistent-context-anthropic.py index be70fd4b9..ae38ee7b7 100644 --- a/examples/foundational/20c-persistent-context-anthropic.py +++ b/examples/foundational/20c-persistent-context-anthropic.py @@ -166,24 +166,20 @@ tools = ToolsSchema( ) -# We store functions so objects (e.g. SileroVADAnalyzer) don't get -# instantiated. The function will be called when the desired transport gets -# selected. +# We use lambdas to defer transport parameter creation until the transport +# type is selected at runtime. transport_params = { "daily": lambda: DailyParams( audio_in_enabled=True, audio_out_enabled=True, - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), "twilio": lambda: FastAPIWebsocketParams( audio_in_enabled=True, audio_out_enabled=True, - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), "webrtc": lambda: TransportParams( audio_in_enabled=True, audio_out_enabled=True, - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), } @@ -218,6 +214,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): user_turn_strategies=UserTurnStrategies( stop=[TurnAnalyzerUserTurnStopStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3())] ), + vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), ) diff --git a/examples/foundational/20d-persistent-context-gemini.py b/examples/foundational/20d-persistent-context-gemini.py index 4b434c4c1..145fe1151 100644 --- a/examples/foundational/20d-persistent-context-gemini.py +++ b/examples/foundational/20d-persistent-context-gemini.py @@ -238,21 +238,18 @@ tools = ToolsSchema( ) -# We store functions so objects (e.g. SileroVADAnalyzer) don't get -# instantiated. The function will be called when the desired transport gets -# selected. +# We use lambdas to defer transport parameter creation until the transport +# type is selected at runtime. transport_params = { "daily": lambda: DailyParams( audio_in_enabled=True, audio_out_enabled=True, video_in_enabled=True, - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), "webrtc": lambda: TransportParams( audio_in_enabled=True, audio_out_enabled=True, video_in_enabled=True, - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), } @@ -284,6 +281,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): user_turn_strategies=UserTurnStrategies( stop=[TurnAnalyzerUserTurnStopStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3())] ), + vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), ) diff --git a/examples/foundational/20e-persistent-context-aws-nova-sonic.py b/examples/foundational/20e-persistent-context-aws-nova-sonic.py index 10101f191..69ffb86b6 100644 --- a/examples/foundational/20e-persistent-context-aws-nova-sonic.py +++ b/examples/foundational/20e-persistent-context-aws-nova-sonic.py @@ -183,9 +183,8 @@ tools = ToolsSchema( ) -# We store functions so objects (e.g. SileroVADAnalyzer) don't get -# instantiated. The function will be called when the desired transport gets -# selected. +# We use lambdas to defer transport parameter creation until the transport +# type is selected at runtime. transport_params = { "daily": lambda: DailyParams( audio_in_enabled=True, diff --git a/examples/foundational/21a-tavus-video-service.py b/examples/foundational/21a-tavus-video-service.py index 0d68e2300..e9446975b 100644 --- a/examples/foundational/21a-tavus-video-service.py +++ b/examples/foundational/21a-tavus-video-service.py @@ -36,9 +36,8 @@ from pipecat.turns.user_turn_strategies import UserTurnStrategies load_dotenv(override=True) -# We store functions so objects (e.g. SileroVADAnalyzer) don't get -# instantiated. The function will be called when the desired transport gets -# selected. +# We use lambdas to defer transport parameter creation until the transport +# type is selected at runtime. transport_params = { "daily": lambda: DailyParams( audio_in_enabled=True, @@ -47,7 +46,6 @@ transport_params = { video_out_is_live=True, video_out_width=1280, video_out_height=720, - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), "webrtc": lambda: TransportParams( audio_in_enabled=True, @@ -56,7 +54,6 @@ transport_params = { video_out_is_live=True, video_out_width=1280, video_out_height=720, - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), } @@ -95,6 +92,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): TurnAnalyzerUserTurnStopStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3()) ] ), + vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), ) diff --git a/examples/foundational/22-natural-conversation.py b/examples/foundational/22-natural-conversation.py index 1be12b7fa..94887daaf 100644 --- a/examples/foundational/22-natural-conversation.py +++ b/examples/foundational/22-natural-conversation.py @@ -12,6 +12,7 @@ from loguru import logger from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3 from pipecat.audio.vad.silero import SileroVADAnalyzer +from pipecat.audio.vad.vad_analyzer import VADParams from pipecat.frames.frames import LLMRunFrame, TextFrame from pipecat.pipeline.parallel_pipeline import ParallelPipeline from pipecat.pipeline.pipeline import Pipeline @@ -110,24 +111,20 @@ class TurnDetectionLLM(Pipeline): ) -# We store functions so objects (e.g. SileroVADAnalyzer) don't get -# instantiated. The function will be called when the desired transport gets -# selected. +# We use lambdas to defer transport parameter creation until the transport +# type is selected at runtime. transport_params = { "daily": lambda: DailyParams( audio_in_enabled=True, audio_out_enabled=True, - vad_analyzer=SileroVADAnalyzer(), ), "webrtc": lambda: TransportParams( audio_in_enabled=True, audio_out_enabled=True, - vad_analyzer=SileroVADAnalyzer(), ), "twilio": lambda: FastAPIWebsocketParams( audio_in_enabled=True, audio_out_enabled=True, - vad_analyzer=SileroVADAnalyzer(), ), } @@ -159,6 +156,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): user_turn_strategies=UserTurnStrategies( stop=[TurnAnalyzerUserTurnStopStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3())] ), + vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), ) diff --git a/examples/foundational/22b-natural-conversation-proposal.py b/examples/foundational/22b-natural-conversation-proposal.py index 9a6d22494..5bcb16e6e 100644 --- a/examples/foundational/22b-natural-conversation-proposal.py +++ b/examples/foundational/22b-natural-conversation-proposal.py @@ -14,6 +14,7 @@ from pipecat.adapters.schemas.function_schema import FunctionSchema from pipecat.adapters.schemas.tools_schema import ToolsSchema from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3 from pipecat.audio.vad.silero import SileroVADAnalyzer +from pipecat.audio.vad.vad_analyzer import VADParams from pipecat.frames.frames import ( CancelFrame, EndFrame, @@ -270,24 +271,20 @@ class TurnDetectionLLM(Pipeline): ) -# We store functions so objects (e.g. SileroVADAnalyzer) don't get -# instantiated. The function will be called when the desired transport gets -# selected. +# We use lambdas to defer transport parameter creation until the transport +# type is selected at runtime. transport_params = { "daily": lambda: DailyParams( audio_in_enabled=True, audio_out_enabled=True, - vad_analyzer=SileroVADAnalyzer(), ), "twilio": lambda: FastAPIWebsocketParams( audio_in_enabled=True, audio_out_enabled=True, - vad_analyzer=SileroVADAnalyzer(), ), "webrtc": lambda: TransportParams( audio_in_enabled=True, audio_out_enabled=True, - vad_analyzer=SileroVADAnalyzer(), ), } @@ -344,6 +341,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): user_turn_strategies=UserTurnStrategies( stop=[TurnAnalyzerUserTurnStopStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3())] ), + vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), ) diff --git a/examples/foundational/22c-natural-conversation-mixed-llms.py b/examples/foundational/22c-natural-conversation-mixed-llms.py index 935aa5e36..e7565ffbe 100644 --- a/examples/foundational/22c-natural-conversation-mixed-llms.py +++ b/examples/foundational/22c-natural-conversation-mixed-llms.py @@ -14,6 +14,7 @@ from pipecat.adapters.schemas.function_schema import FunctionSchema from pipecat.adapters.schemas.tools_schema import ToolsSchema from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3 from pipecat.audio.vad.silero import SileroVADAnalyzer +from pipecat.audio.vad.vad_analyzer import VADParams from pipecat.frames.frames import ( CancelFrame, EndFrame, @@ -473,24 +474,20 @@ async def fetch_weather_from_api(params: FunctionCallParams): await params.result_callback({"conditions": "nice", "temperature": "75"}) -# We store functions so objects (e.g. SileroVADAnalyzer) don't get -# instantiated. The function will be called when the desired transport gets -# selected. +# We use lambdas to defer transport parameter creation until the transport +# type is selected at runtime. transport_params = { "daily": lambda: DailyParams( audio_in_enabled=True, audio_out_enabled=True, - vad_analyzer=SileroVADAnalyzer(), ), "twilio": lambda: FastAPIWebsocketParams( audio_in_enabled=True, audio_out_enabled=True, - vad_analyzer=SileroVADAnalyzer(), ), "webrtc": lambda: TransportParams( audio_in_enabled=True, audio_out_enabled=True, - vad_analyzer=SileroVADAnalyzer(), ), } @@ -547,6 +544,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): user_turn_strategies=UserTurnStrategies( stop=[TurnAnalyzerUserTurnStopStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3())] ), + vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), ) diff --git a/examples/foundational/22d-natural-conversation-gemini-audio.py b/examples/foundational/22d-natural-conversation-gemini-audio.py index 4a7c33a39..2ff1172f3 100644 --- a/examples/foundational/22d-natural-conversation-gemini-audio.py +++ b/examples/foundational/22d-natural-conversation-gemini-audio.py @@ -13,6 +13,7 @@ from loguru import logger from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3 from pipecat.audio.vad.silero import SileroVADAnalyzer +from pipecat.audio.vad.vad_analyzer import VADParams from pipecat.frames.frames import ( CancelFrame, EndFrame, @@ -703,24 +704,20 @@ class TurnDetectionLLM(Pipeline): ) -# We store functions so objects (e.g. SileroVADAnalyzer) don't get -# instantiated. The function will be called when the desired transport gets -# selected. +# We use lambdas to defer transport parameter creation until the transport +# type is selected at runtime. transport_params = { "daily": lambda: DailyParams( audio_in_enabled=True, audio_out_enabled=True, - vad_analyzer=SileroVADAnalyzer(), ), "twilio": lambda: FastAPIWebsocketParams( audio_in_enabled=True, audio_out_enabled=True, - vad_analyzer=SileroVADAnalyzer(), ), "webrtc": lambda: TransportParams( audio_in_enabled=True, audio_out_enabled=True, - vad_analyzer=SileroVADAnalyzer(), ), } @@ -748,6 +745,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): user_turn_strategies=UserTurnStrategies( stop=[TurnAnalyzerUserTurnStopStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3())] ), + vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), ) diff --git a/examples/foundational/23-bot-background-sound.py b/examples/foundational/23-bot-background-sound.py index 1cc944f26..75f9a3b21 100644 --- a/examples/foundational/23-bot-background-sound.py +++ b/examples/foundational/23-bot-background-sound.py @@ -41,9 +41,8 @@ OFFICE_SOUND_FILE = os.path.join( os.path.dirname(__file__), "assets", "office-ambience-24000-mono.mp3" ) -# We store functions so objects (e.g. SileroVADAnalyzer) don't get -# instantiated. The function will be called when the desired transport gets -# selected. +# We use lambdas to defer transport parameter creation until the transport +# type is selected at runtime. transport_params = { "daily": lambda: DailyParams( audio_in_enabled=True, diff --git a/examples/foundational/24-user-mute-strategy.py b/examples/foundational/24-user-mute-strategy.py index 0797fc092..e55d8c3cb 100644 --- a/examples/foundational/24-user-mute-strategy.py +++ b/examples/foundational/24-user-mute-strategy.py @@ -52,24 +52,20 @@ async def fetch_weather_from_api(params: FunctionCallParams): await params.result_callback({"conditions": "nice", "temperature": "75"}) -# We store functions so objects (e.g. SileroVADAnalyzer) don't get -# instantiated. The function will be called when the desired transport gets -# selected. +# We use lambdas to defer transport parameter creation until the transport +# type is selected at runtime. transport_params = { "daily": lambda: DailyParams( audio_in_enabled=True, audio_out_enabled=True, - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), "twilio": lambda: FastAPIWebsocketParams( audio_in_enabled=True, audio_out_enabled=True, - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), "webrtc": lambda: TransportParams( audio_in_enabled=True, audio_out_enabled=True, - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), } @@ -120,6 +116,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): MuteUntilFirstBotCompleteUserMuteStrategy(), FunctionCallUserMuteStrategy(), ], + vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), ) diff --git a/examples/foundational/25-google-audio-in.py b/examples/foundational/25-google-audio-in.py index 09f337d90..002aeaa1c 100644 --- a/examples/foundational/25-google-audio-in.py +++ b/examples/foundational/25-google-audio-in.py @@ -264,9 +264,8 @@ class TranscriptionContextFixup(FrameProcessor): await self.push_frame(frame, direction) -# We store functions so objects (e.g. SileroVADAnalyzer) don't get -# instantiated. The function will be called when the desired transport gets -# selected. +# We use lambdas to defer transport parameter creation until the transport +# type is selected at runtime. transport_params = { "daily": lambda: DailyParams( audio_in_enabled=True, diff --git a/examples/foundational/26-gemini-live.py b/examples/foundational/26-gemini-live.py index a99d0db36..9a705fac1 100644 --- a/examples/foundational/26-gemini-live.py +++ b/examples/foundational/26-gemini-live.py @@ -15,6 +15,7 @@ from pipecat.frames.frames import LLMMessagesAppendFrame from pipecat.pipeline.pipeline import Pipeline from pipecat.pipeline.runner import PipelineRunner from pipecat.pipeline.task import PipelineParams, PipelineTask +from pipecat.processors.audio.vad_processor import VADProcessor from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport from pipecat.services.google.gemini_live.llm import GeminiLiveLLMService @@ -26,30 +27,26 @@ from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams load_dotenv(override=True) -# We store functions so objects (e.g. SileroVADAnalyzer) don't get -# instantiated. The function will be called when the desired transport gets -# selected. +# We use lambdas to defer transport parameter creation until the transport +# type is selected at runtime. transport_params = { "daily": lambda: DailyParams( audio_in_enabled=True, audio_out_enabled=True, # set stop_secs to something roughly similar to the internal setting # of the Multimodal Live api, just to align events. - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.5)), ), "twilio": lambda: FastAPIWebsocketParams( audio_in_enabled=True, audio_out_enabled=True, # set stop_secs to something roughly similar to the internal setting # of the Multimodal Live api, just to align events. - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.5)), ), "webrtc": lambda: TransportParams( audio_in_enabled=True, audio_out_enabled=True, # set stop_secs to something roughly similar to the internal setting # of the Multimodal Live api, just to align events. - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.5)), ), } @@ -71,10 +68,13 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): voice_id="Puck", # Aoede, Charon, Fenrir, Kore, Puck ) + vad_processor = VADProcessor(vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.5))) + # Build the pipeline pipeline = Pipeline( [ transport.input(), + vad_processor, llm, transport.output(), ] diff --git a/examples/foundational/26a-gemini-live-transcription.py b/examples/foundational/26a-gemini-live-transcription.py index c5a9e7d3b..96a719b10 100644 --- a/examples/foundational/26a-gemini-live-transcription.py +++ b/examples/foundational/26a-gemini-live-transcription.py @@ -20,6 +20,7 @@ from pipecat.processors.aggregators.llm_context import LLMContext from pipecat.processors.aggregators.llm_response_universal import ( AssistantTurnStoppedMessage, LLMContextAggregatorPair, + LLMUserAggregatorParams, UserTurnStoppedMessage, ) from pipecat.runner.types import RunnerArguments @@ -32,36 +33,20 @@ from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams load_dotenv(override=True) -# We store functions so objects (e.g. SileroVADAnalyzer) don't get -# instantiated. The function will be called when the desired transport gets -# selected. +# We use lambdas to defer transport parameter creation until the transport +# type is selected at runtime. transport_params = { "daily": lambda: DailyParams( audio_in_enabled=True, audio_out_enabled=True, - # set stop_secs to something roughly similar to the internal setting - # of the Multimodal Live api, just to align events. This doesn't really - # matter because we can only use the Multimodal Live API's phrase - # endpointing, for now. - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.5)), ), "twilio": lambda: FastAPIWebsocketParams( audio_in_enabled=True, audio_out_enabled=True, - # set stop_secs to something roughly similar to the internal setting - # of the Multimodal Live api, just to align events. This doesn't really - # matter because we can only use the Multimodal Live API's phrase - # endpointing, for now. - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.5)), ), "webrtc": lambda: TransportParams( audio_in_enabled=True, audio_out_enabled=True, - # set stop_secs to something roughly similar to the internal setting - # of the Multimodal Live api, just to align events. This doesn't really - # matter because we can only use the Multimodal Live API's phrase - # endpointing, for now. - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.5)), ), } @@ -94,7 +79,16 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): # }, ], ) - user_aggregator, assistant_aggregator = LLMContextAggregatorPair(context) + user_aggregator, assistant_aggregator = LLMContextAggregatorPair( + context, + user_params=LLMUserAggregatorParams( + # Set stop_secs to something roughly similar to the internal setting + # of the Multimodal Live api, just to align events. This doesn't + # really matter because we can only use the Multimodal Live API's + # phrase endpointing, for now. + vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.5)) + ), + ) pipeline = Pipeline( [ diff --git a/examples/foundational/26b-gemini-live-function-calling.py b/examples/foundational/26b-gemini-live-function-calling.py index a16445630..7aea43036 100644 --- a/examples/foundational/26b-gemini-live-function-calling.py +++ b/examples/foundational/26b-gemini-live-function-calling.py @@ -20,7 +20,10 @@ from pipecat.pipeline.pipeline import Pipeline from pipecat.pipeline.runner import PipelineRunner from pipecat.pipeline.task import PipelineParams, PipelineTask from pipecat.processors.aggregators.llm_context import LLMContext -from pipecat.processors.aggregators.llm_response_universal import LLMContextAggregatorPair +from pipecat.processors.aggregators.llm_response_universal import ( + LLMContextAggregatorPair, + LLMUserAggregatorParams, +) from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport from pipecat.services.google.gemini_live.llm import GeminiLiveLLMService @@ -58,36 +61,20 @@ You have three tools available to you: """ -# We store functions so objects (e.g. SileroVADAnalyzer) don't get -# instantiated. The function will be called when the desired transport gets -# selected. +# We use lambdas to defer transport parameter creation until the transport +# type is selected at runtime. transport_params = { "daily": lambda: DailyParams( audio_in_enabled=True, audio_out_enabled=True, - # set stop_secs to something roughly similar to the internal setting - # of the Multimodal Live api, just to align events. This doesn't really - # matter because we can only use the Multimodal Live API's phrase - # endpointing, for now. - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.5)), ), "twilio": lambda: FastAPIWebsocketParams( audio_in_enabled=True, audio_out_enabled=True, - # set stop_secs to something roughly similar to the internal setting - # of the Multimodal Live api, just to align events. This doesn't really - # matter because we can only use the Multimodal Live API's phrase - # endpointing, for now. - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.5)), ), "webrtc": lambda: TransportParams( audio_in_enabled=True, audio_out_enabled=True, - # set stop_secs to something roughly similar to the internal setting - # of the Multimodal Live api, just to align events. This doesn't really - # matter because we can only use the Multimodal Live API's phrase - # endpointing, for now. - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.5)), ), } @@ -151,7 +138,16 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): ], # tools, ) - user_aggregator, assistant_aggregator = LLMContextAggregatorPair(context) + user_aggregator, assistant_aggregator = LLMContextAggregatorPair( + context, + user_params=LLMUserAggregatorParams( + # Set stop_secs to something roughly similar to the internal setting + # of the Multimodal Live api, just to align events. This doesn't + # really matter because we can only use the Multimodal Live API's + # phrase endpointing, for now. + vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.5)) + ), + ) pipeline = Pipeline( [ diff --git a/examples/foundational/26c-gemini-live-video.py b/examples/foundational/26c-gemini-live-video.py index 314765bab..4243f50d9 100644 --- a/examples/foundational/26c-gemini-live-video.py +++ b/examples/foundational/26c-gemini-live-video.py @@ -18,7 +18,10 @@ from pipecat.pipeline.pipeline import Pipeline from pipecat.pipeline.runner import PipelineRunner from pipecat.pipeline.task import PipelineParams, PipelineTask from pipecat.processors.aggregators.llm_context import LLMContext -from pipecat.processors.aggregators.llm_response_universal import LLMContextAggregatorPair +from pipecat.processors.aggregators.llm_response_universal import ( + LLMContextAggregatorPair, + LLMUserAggregatorParams, +) from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import ( create_transport, @@ -31,29 +34,18 @@ from pipecat.transports.daily.transport import DailyParams load_dotenv(override=True) -# We store functions so objects (e.g. SileroVADAnalyzer) don't get -# instantiated. The function will be called when the desired transport gets -# selected. +# We use lambdas to defer transport parameter creation until the transport +# type is selected at runtime. transport_params = { "daily": lambda: DailyParams( audio_in_enabled=True, audio_out_enabled=True, video_in_enabled=True, - # set stop_secs to something roughly similar to the internal setting - # of the Multimodal Live api, just to align events. This doesn't really - # matter because we can only use the Multimodal Live API's phrase - # endpointing, for now. - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.5)), ), "webrtc": lambda: TransportParams( audio_in_enabled=True, audio_out_enabled=True, video_in_enabled=True, - # set stop_secs to something roughly similar to the internal setting - # of the Multimodal Live api, just to align events. This doesn't really - # matter because we can only use the Multimodal Live API's phrase - # endpointing, for now. - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.5)), ), } @@ -74,7 +66,16 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): }, ], ) - user_aggregator, assistant_aggregator = LLMContextAggregatorPair(context) + user_aggregator, assistant_aggregator = LLMContextAggregatorPair( + context, + user_params=LLMUserAggregatorParams( + # Set stop_secs to something roughly similar to the internal setting + # of the Multimodal Live api, just to align events. This doesn't + # really matter because we can only use the Multimodal Live API's + # phrase endpointing, for now. + vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.5)) + ), + ) pipeline = Pipeline( [ diff --git a/examples/foundational/26d-gemini-live-text.py b/examples/foundational/26d-gemini-live-text.py index c51f32d7b..1b3845fa3 100644 --- a/examples/foundational/26d-gemini-live-text.py +++ b/examples/foundational/26d-gemini-live-text.py @@ -17,7 +17,10 @@ from pipecat.pipeline.pipeline import Pipeline from pipecat.pipeline.runner import PipelineRunner from pipecat.pipeline.task import PipelineParams, PipelineTask from pipecat.processors.aggregators.llm_context import LLMContext -from pipecat.processors.aggregators.llm_response_universal import LLMContextAggregatorPair +from pipecat.processors.aggregators.llm_response_universal import ( + LLMContextAggregatorPair, + LLMUserAggregatorParams, +) from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport from pipecat.services.cartesia.tts import CartesiaTTSService @@ -44,36 +47,20 @@ Respond to what the user said in a creative and helpful way. Keep your responses """ -# We store functions so objects (e.g. SileroVADAnalyzer) don't get -# instantiated. The function will be called when the desired transport gets -# selected. +# We use lambdas to defer transport parameter creation until the transport +# type is selected at runtime. transport_params = { "daily": lambda: DailyParams( audio_in_enabled=True, audio_out_enabled=True, - # set stop_secs to something roughly similar to the internal setting - # of the Multimodal Live api, just to align events. This doesn't really - # matter because we can only use the Multimodal Live API's phrase - # endpointing, for now. - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.5)), ), "twilio": lambda: FastAPIWebsocketParams( audio_in_enabled=True, audio_out_enabled=True, - # set stop_secs to something roughly similar to the internal setting - # of the Multimodal Live api, just to align events. This doesn't really - # matter because we can only use the Multimodal Live API's phrase - # endpointing, for now. - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.5)), ), "webrtc": lambda: TransportParams( audio_in_enabled=True, audio_out_enabled=True, - # set stop_secs to something roughly similar to the internal setting - # of the Multimodal Live api, just to align events. This doesn't really - # matter because we can only use the Multimodal Live API's phrase - # endpointing, for now. - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.5)), ), } @@ -111,7 +98,16 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): # Set up conversation context and management # The context_aggregator will automatically collect conversation context context = LLMContext(messages) - user_aggregator, assistant_aggregator = LLMContextAggregatorPair(context) + user_aggregator, assistant_aggregator = LLMContextAggregatorPair( + context, + user_params=LLMUserAggregatorParams( + # Set stop_secs to something roughly similar to the internal setting + # of the Multimodal Live api, just to align events. This doesn't + # really matter because we can only use the Multimodal Live API's + # phrase endpointing, for now. + vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.5)) + ), + ) pipeline = Pipeline( [ diff --git a/examples/foundational/26e-gemini-live-google-search.py b/examples/foundational/26e-gemini-live-google-search.py index 9b37f32ee..64ab1962a 100644 --- a/examples/foundational/26e-gemini-live-google-search.py +++ b/examples/foundational/26e-gemini-live-google-search.py @@ -17,7 +17,10 @@ from pipecat.pipeline.pipeline import Pipeline from pipecat.pipeline.runner import PipelineRunner from pipecat.pipeline.task import PipelineParams, PipelineTask from pipecat.processors.aggregators.llm_context import LLMContext -from pipecat.processors.aggregators.llm_response_universal import LLMContextAggregatorPair +from pipecat.processors.aggregators.llm_response_universal import ( + LLMContextAggregatorPair, + LLMUserAggregatorParams, +) from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport from pipecat.services.google.gemini_live.llm import GeminiLiveLLMService @@ -46,36 +49,20 @@ Start each interaction by asking the user about which place they would like to k """ -# We store functions so objects (e.g. SileroVADAnalyzer) don't get -# instantiated. The function will be called when the desired transport gets -# selected. +# We use lambdas to defer transport parameter creation until the transport +# type is selected at runtime. transport_params = { "daily": lambda: DailyParams( audio_in_enabled=True, audio_out_enabled=True, - # set stop_secs to something roughly similar to the internal setting - # of the Multimodal Live api, just to align events. This doesn't really - # matter because we can only use the Multimodal Live API's phrase - # endpointing, for now. - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.5)), ), "twilio": lambda: FastAPIWebsocketParams( audio_in_enabled=True, audio_out_enabled=True, - # set stop_secs to something roughly similar to the internal setting - # of the Multimodal Live api, just to align events. This doesn't really - # matter because we can only use the Multimodal Live API's phrase - # endpointing, for now. - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.5)), ), "webrtc": lambda: TransportParams( audio_in_enabled=True, audio_out_enabled=True, - # set stop_secs to something roughly similar to the internal setting - # of the Multimodal Live api, just to align events. This doesn't really - # matter because we can only use the Multimodal Live API's phrase - # endpointing, for now. - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.5)), ), } @@ -99,7 +86,16 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): } ], ) - user_aggregator, assistant_aggregator = LLMContextAggregatorPair(context) + user_aggregator, assistant_aggregator = LLMContextAggregatorPair( + context, + user_params=LLMUserAggregatorParams( + # Set stop_secs to something roughly similar to the internal setting + # of the Multimodal Live api, just to align events. This doesn't + # really matter because we can only use the Multimodal Live API's + # phrase endpointing, for now. + vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.5)) + ), + ) pipeline = Pipeline( [ diff --git a/examples/foundational/26f-gemini-live-files-api.py b/examples/foundational/26f-gemini-live-files-api.py index 3b9709869..4dcf2c10a 100644 --- a/examples/foundational/26f-gemini-live-files-api.py +++ b/examples/foundational/26f-gemini-live-files-api.py @@ -17,7 +17,10 @@ from pipecat.pipeline.pipeline import Pipeline from pipecat.pipeline.runner import PipelineRunner from pipecat.pipeline.task import PipelineParams, PipelineTask from pipecat.processors.aggregators.llm_context import LLMContext -from pipecat.processors.aggregators.llm_response_universal import LLMContextAggregatorPair +from pipecat.processors.aggregators.llm_response_universal import ( + LLMContextAggregatorPair, + LLMUserAggregatorParams, +) from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport from pipecat.services.google.gemini_live.llm import GeminiLiveLLMService @@ -28,27 +31,23 @@ from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams load_dotenv(override=True) -# We store functions so objects (e.g. SileroVADAnalyzer) don't get -# instantiated. The function will be called when the desired transport gets -# selected. +# We use lambdas to defer transport parameter creation until the transport +# type is selected at runtime. transport_params = { "daily": lambda: DailyParams( audio_in_enabled=True, audio_out_enabled=True, video_in_enabled=False, - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.5)), ), "twilio": lambda: FastAPIWebsocketParams( audio_in_enabled=True, audio_out_enabled=True, video_in_enabled=False, - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.5)), ), "webrtc": lambda: TransportParams( audio_in_enabled=True, audio_out_enabled=True, video_in_enabled=False, - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.5)), ), } @@ -163,7 +162,16 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): ) # Create context aggregator - user_aggregator, assistant_aggregator = LLMContextAggregatorPair(context) + user_aggregator, assistant_aggregator = LLMContextAggregatorPair( + context, + user_params=LLMUserAggregatorParams( + # Set stop_secs to something roughly similar to the internal setting + # of the Multimodal Live api, just to align events. This doesn't + # really matter because we can only use the Multimodal Live API's + # phrase endpointing, for now. + vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.5)) + ), + ) # Build the pipeline pipeline = Pipeline( diff --git a/examples/foundational/26g-gemini-live-groundingMetadata.py b/examples/foundational/26g-gemini-live-groundingMetadata.py index 1cf2be618..2868bfebc 100644 --- a/examples/foundational/26g-gemini-live-groundingMetadata.py +++ b/examples/foundational/26g-gemini-live-groundingMetadata.py @@ -11,7 +11,10 @@ from pipecat.pipeline.pipeline import Pipeline from pipecat.pipeline.runner import PipelineRunner from pipecat.pipeline.task import PipelineTask from pipecat.processors.aggregators.llm_context import LLMContext -from pipecat.processors.aggregators.llm_response_universal import LLMContextAggregatorPair +from pipecat.processors.aggregators.llm_response_universal import ( + LLMContextAggregatorPair, + LLMUserAggregatorParams, +) from pipecat.processors.frame_processor import FrameDirection, FrameProcessor from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport @@ -24,27 +27,23 @@ from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams load_dotenv(override=True) -# We store functions so objects (e.g. SileroVADAnalyzer) don't get -# instantiated. The function will be called when the desired transport gets -# selected. +# We use lambdas to defer transport parameter creation until the transport +# type is selected at runtime. transport_params = { "daily": lambda: DailyParams( audio_in_enabled=True, audio_out_enabled=True, video_in_enabled=False, - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.5)), ), "twilio": lambda: FastAPIWebsocketParams( audio_in_enabled=True, audio_out_enabled=True, video_in_enabled=False, - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.5)), ), "webrtc": lambda: TransportParams( audio_in_enabled=True, audio_out_enabled=True, video_in_enabled=False, - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.5)), ), } @@ -126,7 +125,16 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): # Set up conversation context and management context = LLMContext(messages) - user_aggregator, assistant_aggregator = LLMContextAggregatorPair(context) + user_aggregator, assistant_aggregator = LLMContextAggregatorPair( + context, + user_params=LLMUserAggregatorParams( + # Set stop_secs to something roughly similar to the internal setting + # of the Multimodal Live api, just to align events. This doesn't + # really matter because we can only use the Multimodal Live API's + # phrase endpointing, for now. + vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.5)) + ), + ) pipeline = Pipeline( [ diff --git a/examples/foundational/26h-gemini-live-vertex-function-calling.py b/examples/foundational/26h-gemini-live-vertex-function-calling.py index 35068e4c5..eb1db7934 100644 --- a/examples/foundational/26h-gemini-live-vertex-function-calling.py +++ b/examples/foundational/26h-gemini-live-vertex-function-calling.py @@ -20,7 +20,10 @@ from pipecat.pipeline.pipeline import Pipeline from pipecat.pipeline.runner import PipelineRunner from pipecat.pipeline.task import PipelineParams, PipelineTask from pipecat.processors.aggregators.llm_context import LLMContext -from pipecat.processors.aggregators.llm_response_universal import LLMContextAggregatorPair +from pipecat.processors.aggregators.llm_response_universal import ( + LLMContextAggregatorPair, + LLMUserAggregatorParams, +) from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport from pipecat.services.google.gemini_live.llm_vertex import GeminiLiveVertexLLMService @@ -57,36 +60,20 @@ You have three tools available to you: """ -# We store functions so objects (e.g. SileroVADAnalyzer) don't get -# instantiated. The function will be called when the desired transport gets -# selected. +# We use lambdas to defer transport parameter creation until the transport +# type is selected at runtime. transport_params = { "daily": lambda: DailyParams( audio_in_enabled=True, audio_out_enabled=True, - # set stop_secs to something roughly similar to the internal setting - # of the Multimodal Live api, just to align events. This doesn't really - # matter because we can only use the Multimodal Live API's phrase - # endpointing, for now. - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.5)), ), "twilio": lambda: FastAPIWebsocketParams( audio_in_enabled=True, audio_out_enabled=True, - # set stop_secs to something roughly similar to the internal setting - # of the Multimodal Live api, just to align events. This doesn't really - # matter because we can only use the Multimodal Live API's phrase - # endpointing, for now. - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.5)), ), "webrtc": lambda: TransportParams( audio_in_enabled=True, audio_out_enabled=True, - # set stop_secs to something roughly similar to the internal setting - # of the Multimodal Live api, just to align events. This doesn't really - # matter because we can only use the Multimodal Live API's phrase - # endpointing, for now. - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.5)), ), } @@ -139,7 +126,16 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): llm.register_function("get_restaurant_recommendation", fetch_restaurant_recommendation) context = LLMContext([{"role": "user", "content": "Say hello."}]) - user_aggregator, assistant_aggregator = LLMContextAggregatorPair(context) + user_aggregator, assistant_aggregator = LLMContextAggregatorPair( + context, + user_params=LLMUserAggregatorParams( + # Set stop_secs to something roughly similar to the internal setting + # of the Multimodal Live api, just to align events. This doesn't + # really matter because we can only use the Multimodal Live API's + # phrase endpointing, for now. + vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.5)) + ), + ) pipeline = Pipeline( [ diff --git a/examples/foundational/26i-gemini-live-graceful-end.py b/examples/foundational/26i-gemini-live-graceful-end.py index dae2bd109..54c8f0dfd 100644 --- a/examples/foundational/26i-gemini-live-graceful-end.py +++ b/examples/foundational/26i-gemini-live-graceful-end.py @@ -19,7 +19,10 @@ from pipecat.pipeline.pipeline import Pipeline from pipecat.pipeline.runner import PipelineRunner from pipecat.pipeline.task import PipelineParams, PipelineTask from pipecat.processors.aggregators.llm_context import LLMContext -from pipecat.processors.aggregators.llm_response_universal import LLMContextAggregatorPair +from pipecat.processors.aggregators.llm_response_universal import ( + LLMContextAggregatorPair, + LLMUserAggregatorParams, +) from pipecat.processors.frame_processor import FrameDirection from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport @@ -67,36 +70,20 @@ After you've responded to the user three times, do two things, in order: """ -# We store functions so objects (e.g. SileroVADAnalyzer) don't get -# instantiated. The function will be called when the desired transport gets -# selected. +# We use lambdas to defer transport parameter creation until the transport +# type is selected at runtime. transport_params = { "daily": lambda: DailyParams( audio_in_enabled=True, audio_out_enabled=True, - # set stop_secs to something roughly similar to the internal setting - # of the Multimodal Live api, just to align events. This doesn't really - # matter because we can only use the Multimodal Live API's phrase - # endpointing, for now. - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.5)), ), "twilio": lambda: FastAPIWebsocketParams( audio_in_enabled=True, audio_out_enabled=True, - # set stop_secs to something roughly similar to the internal setting - # of the Multimodal Live api, just to align events. This doesn't really - # matter because we can only use the Multimodal Live API's phrase - # endpointing, for now. - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.5)), ), "webrtc": lambda: TransportParams( audio_in_enabled=True, audio_out_enabled=True, - # set stop_secs to something roughly similar to the internal setting - # of the Multimodal Live api, just to align events. This doesn't really - # matter because we can only use the Multimodal Live API's phrase - # endpointing, for now. - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.5)), ), } @@ -156,7 +143,16 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): context = LLMContext( [{"role": "user", "content": "Say hello."}], ) - user_aggregator, assistant_aggregator = LLMContextAggregatorPair(context) + user_aggregator, assistant_aggregator = LLMContextAggregatorPair( + context, + user_params=LLMUserAggregatorParams( + # Set stop_secs to something roughly similar to the internal setting + # of the Multimodal Live api, just to align events. This doesn't + # really matter because we can only use the Multimodal Live API's + # phrase endpointing, for now. + vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.5)) + ), + ) pipeline = Pipeline( [ diff --git a/examples/foundational/27-simli-layer.py b/examples/foundational/27-simli-layer.py index b89793c6b..7176b2a51 100644 --- a/examples/foundational/27-simli-layer.py +++ b/examples/foundational/27-simli-layer.py @@ -35,9 +35,8 @@ from pipecat.turns.user_turn_strategies import UserTurnStrategies load_dotenv(override=True) -# We store functions so objects (e.g. SileroVADAnalyzer) don't get -# instantiated. The function will be called when the desired transport gets -# selected. +# We use lambdas to defer transport parameter creation until the transport +# type is selected at runtime. transport_params = { "daily": lambda: DailyParams( audio_in_enabled=True, @@ -46,7 +45,6 @@ transport_params = { video_out_is_live=True, video_out_width=512, video_out_height=512, - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), "webrtc": lambda: TransportParams( audio_in_enabled=True, @@ -55,7 +53,6 @@ transport_params = { video_out_is_live=True, video_out_width=512, video_out_height=512, - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), } @@ -91,6 +88,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): user_turn_strategies=UserTurnStrategies( stop=[TurnAnalyzerUserTurnStopStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3())] ), + vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), ) diff --git a/examples/foundational/28-user-assistant-turns.py b/examples/foundational/28-user-assistant-turns.py index e870c836b..5d380cfc0 100644 --- a/examples/foundational/28-user-assistant-turns.py +++ b/examples/foundational/28-user-assistant-turns.py @@ -101,24 +101,20 @@ class TranscriptHandler: await self.save_message("assistant", message.content, message.timestamp) -# We store functions so objects (e.g. SileroVADAnalyzer) don't get -# instantiated. The function will be called when the desired transport gets -# selected. +# We use lambdas to defer transport parameter creation until the transport +# type is selected at runtime. transport_params = { "daily": lambda: DailyParams( audio_in_enabled=True, audio_out_enabled=True, - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), "twilio": lambda: FastAPIWebsocketParams( audio_in_enabled=True, audio_out_enabled=True, - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), "webrtc": lambda: TransportParams( audio_in_enabled=True, audio_out_enabled=True, - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), } @@ -149,6 +145,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): user_turn_strategies=UserTurnStrategies( stop=[TurnAnalyzerUserTurnStopStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3())] ), + vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), ) diff --git a/examples/foundational/29-turn-tracking-observer.py b/examples/foundational/29-turn-tracking-observer.py index 6a9391232..b6d8dcd88 100644 --- a/examples/foundational/29-turn-tracking-observer.py +++ b/examples/foundational/29-turn-tracking-observer.py @@ -36,24 +36,20 @@ from pipecat.turns.user_turn_strategies import UserTurnStrategies load_dotenv(override=True) -# We store functions so objects (e.g. SileroVADAnalyzer) don't get -# instantiated. The function will be called when the desired transport gets -# selected. +# We use lambdas to defer transport parameter creation until the transport +# type is selected at runtime. transport_params = { "daily": lambda: DailyParams( audio_in_enabled=True, audio_out_enabled=True, - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), "twilio": lambda: FastAPIWebsocketParams( audio_in_enabled=True, audio_out_enabled=True, - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), "webrtc": lambda: TransportParams( audio_in_enabled=True, audio_out_enabled=True, - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), } @@ -84,6 +80,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): user_turn_strategies=UserTurnStrategies( stop=[TurnAnalyzerUserTurnStopStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3())] ), + vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), ) diff --git a/examples/foundational/30-observer.py b/examples/foundational/30-observer.py index e26e3280c..4d1567eed 100644 --- a/examples/foundational/30-observer.py +++ b/examples/foundational/30-observer.py @@ -83,24 +83,20 @@ class CustomObserver(BaseObserver): logger.info(f"🤖 BOT STOP SPEAKING: {src} {arrow} {dst} at {time_sec:.2f}s") -# We store functions so objects (e.g. SileroVADAnalyzer) don't get -# instantiated. The function will be called when the desired transport gets -# selected. +# We use lambdas to defer transport parameter creation until the transport +# type is selected at runtime. transport_params = { "daily": lambda: DailyParams( audio_in_enabled=True, audio_out_enabled=True, - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), "twilio": lambda: FastAPIWebsocketParams( audio_in_enabled=True, audio_out_enabled=True, - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), "webrtc": lambda: TransportParams( audio_in_enabled=True, audio_out_enabled=True, - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), } @@ -131,6 +127,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): user_turn_strategies=UserTurnStrategies( stop=[TurnAnalyzerUserTurnStopStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3())] ), + vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), ) diff --git a/examples/foundational/32-gemini-grounding-metadata.py b/examples/foundational/32-gemini-grounding-metadata.py index 7647287ed..910498800 100644 --- a/examples/foundational/32-gemini-grounding-metadata.py +++ b/examples/foundational/32-gemini-grounding-metadata.py @@ -78,24 +78,20 @@ class LLMSearchLoggerObserver(BaseObserver): logger.debug(f"🧠 {arrow} {dst} LLM SEARCH RESPONSE FRAME: {frame} at {time_sec:.2f}s") -# We store functions so objects (e.g. SileroVADAnalyzer) don't get -# instantiated. The function will be called when the desired transport gets -# selected. +# We use lambdas to defer transport parameter creation until the transport +# type is selected at runtime. transport_params = { "daily": lambda: DailyParams( audio_in_enabled=True, audio_out_enabled=True, - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), "twilio": lambda: FastAPIWebsocketParams( audio_in_enabled=True, audio_out_enabled=True, - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), "webrtc": lambda: TransportParams( audio_in_enabled=True, audio_out_enabled=True, - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), } @@ -131,6 +127,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): user_turn_strategies=UserTurnStrategies( stop=[TurnAnalyzerUserTurnStopStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3())] ), + vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), ) diff --git a/examples/foundational/33-gemini-rag.py b/examples/foundational/33-gemini-rag.py index 8df31426b..c8ad5eb97 100644 --- a/examples/foundational/33-gemini-rag.py +++ b/examples/foundational/33-gemini-rag.py @@ -162,24 +162,20 @@ async def query_knowledge_base(params: FunctionCallParams): await params.result_callback(response.text) -# We store functions so objects (e.g. SileroVADAnalyzer) don't get -# instantiated. The function will be called when the desired transport gets -# selected. +# We use lambdas to defer transport parameter creation until the transport +# type is selected at runtime. transport_params = { "daily": lambda: DailyParams( audio_in_enabled=True, audio_out_enabled=True, - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), "twilio": lambda: FastAPIWebsocketParams( audio_in_enabled=True, audio_out_enabled=True, - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), "webrtc": lambda: TransportParams( audio_in_enabled=True, audio_out_enabled=True, - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), } @@ -232,6 +228,7 @@ Your response will be turned into speech so use only simple words and punctuatio user_turn_strategies=UserTurnStrategies( stop=[TurnAnalyzerUserTurnStopStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3())] ), + vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), ) diff --git a/examples/foundational/34-audio-recording.py b/examples/foundational/34-audio-recording.py index 6cbac25c6..687540f01 100644 --- a/examples/foundational/34-audio-recording.py +++ b/examples/foundational/34-audio-recording.py @@ -91,24 +91,20 @@ async def save_audio_file(audio: bytes, filename: str, sample_rate: int, num_cha logger.info(f"Audio saved to {filename}") -# We store functions so objects (e.g. SileroVADAnalyzer) don't get -# instantiated. The function will be called when the desired transport gets -# selected. +# We use lambdas to defer transport parameter creation until the transport +# type is selected at runtime. transport_params = { "daily": lambda: DailyParams( audio_in_enabled=True, audio_out_enabled=True, - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), "twilio": lambda: FastAPIWebsocketParams( audio_in_enabled=True, audio_out_enabled=True, - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), "webrtc": lambda: TransportParams( audio_in_enabled=True, audio_out_enabled=True, - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), } @@ -142,6 +138,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): user_turn_strategies=UserTurnStrategies( stop=[TurnAnalyzerUserTurnStopStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3())] ), + vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), ) diff --git a/examples/foundational/35-pattern-pair-voice-switching.py b/examples/foundational/35-pattern-pair-voice-switching.py index c90a39b39..26a346ae4 100644 --- a/examples/foundational/35-pattern-pair-voice-switching.py +++ b/examples/foundational/35-pattern-pair-voice-switching.py @@ -82,24 +82,20 @@ VOICE_IDS = { "male": "7cf0e2b1-8daf-4fe4-89ad-f6039398f359", # Male character voice } -# We store functions so objects (e.g. SileroVADAnalyzer) don't get -# instantiated. The function will be called when the desired transport gets -# selected. +# We use lambdas to defer transport parameter creation until the transport +# type is selected at runtime. transport_params = { "daily": lambda: DailyParams( audio_in_enabled=True, audio_out_enabled=True, - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), "twilio": lambda: FastAPIWebsocketParams( audio_in_enabled=True, audio_out_enabled=True, - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), "webrtc": lambda: TransportParams( audio_in_enabled=True, audio_out_enabled=True, - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), } @@ -207,6 +203,7 @@ Remember: Use narrator voice for EVERYTHING except the actual quoted dialogue."" user_turn_strategies=UserTurnStrategies( stop=[TurnAnalyzerUserTurnStopStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3())] ), + vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), ) diff --git a/examples/foundational/36-user-email-gathering.py b/examples/foundational/36-user-email-gathering.py index 1af985235..64bd72bcd 100644 --- a/examples/foundational/36-user-email-gathering.py +++ b/examples/foundational/36-user-email-gathering.py @@ -43,24 +43,20 @@ async def store_user_emails(params: FunctionCallParams): print(f"User emails: {params.arguments}") -# We store functions so objects (e.g. SileroVADAnalyzer) don't get -# instantiated. The function will be called when the desired transport gets -# selected. +# We use lambdas to defer transport parameter creation until the transport +# type is selected at runtime. transport_params = { "daily": lambda: DailyParams( audio_in_enabled=True, audio_out_enabled=True, - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), "twilio": lambda: FastAPIWebsocketParams( audio_in_enabled=True, audio_out_enabled=True, - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), "webrtc": lambda: TransportParams( audio_in_enabled=True, audio_out_enabled=True, - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), } @@ -123,6 +119,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): user_turn_strategies=UserTurnStrategies( stop=[TurnAnalyzerUserTurnStopStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3())] ), + vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), ) diff --git a/examples/foundational/37-mem0.py b/examples/foundational/37-mem0.py index 11eae51fb..f8ee7079e 100644 --- a/examples/foundational/37-mem0.py +++ b/examples/foundational/37-mem0.py @@ -132,24 +132,20 @@ async def get_initial_greeting( return "Hello! How can I help you today?" -# We store functions so objects (e.g. SileroVADAnalyzer) don't get -# instantiated. The function will be called when the desired transport gets -# selected. +# We use lambdas to defer transport parameter creation until the transport +# type is selected at runtime. transport_params = { "daily": lambda: DailyParams( audio_in_enabled=True, audio_out_enabled=True, - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), "twilio": lambda: FastAPIWebsocketParams( audio_in_enabled=True, audio_out_enabled=True, - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), "webrtc": lambda: TransportParams( audio_in_enabled=True, audio_out_enabled=True, - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), } @@ -252,6 +248,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): user_turn_strategies=UserTurnStrategies( stop=[TurnAnalyzerUserTurnStopStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3())] ), + vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), ) diff --git a/examples/foundational/38-smart-turn-fal.py b/examples/foundational/38-smart-turn-fal.py index 05bbba5e9..8af8b58f8 100644 --- a/examples/foundational/38-smart-turn-fal.py +++ b/examples/foundational/38-smart-turn-fal.py @@ -37,24 +37,20 @@ from pipecat.turns.user_turn_strategies import UserTurnStrategies load_dotenv(override=True) -# We store functions so objects (e.g. SileroVADAnalyzer) don't get -# instantiated. The function will be called when the desired transport gets -# selected. +# We use lambdas to defer transport parameter creation until the transport +# type is selected at runtime. transport_params = { "daily": lambda: DailyParams( audio_in_enabled=True, audio_out_enabled=True, - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), "twilio": lambda: FastAPIWebsocketParams( audio_in_enabled=True, audio_out_enabled=True, - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), "webrtc": lambda: TransportParams( audio_in_enabled=True, audio_out_enabled=True, - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), } @@ -92,6 +88,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): ) ] ), + vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), ) diff --git a/examples/foundational/38a-smart-turn-local-coreml.py b/examples/foundational/38a-smart-turn-local-coreml.py index 6500add0a..e2796d6a6 100644 --- a/examples/foundational/38a-smart-turn-local-coreml.py +++ b/examples/foundational/38a-smart-turn-local-coreml.py @@ -52,24 +52,20 @@ load_dotenv(override=True) # or add it to your .env file smart_turn_model_path = os.getenv("LOCAL_SMART_TURN_MODEL_PATH") -# We store functions so objects (e.g. SileroVADAnalyzer) don't get -# instantiated. The function will be called when the desired transport gets -# selected. +# We use lambdas to defer transport parameter creation until the transport +# type is selected at runtime. transport_params = { "daily": lambda: DailyParams( audio_in_enabled=True, audio_out_enabled=True, - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), "twilio": lambda: FastAPIWebsocketParams( audio_in_enabled=True, audio_out_enabled=True, - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), "webrtc": lambda: TransportParams( audio_in_enabled=True, audio_out_enabled=True, - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), } @@ -106,6 +102,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): ) ] ), + vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), ) diff --git a/examples/foundational/38b-smart-turn-local.py b/examples/foundational/38b-smart-turn-local.py index 85a320631..03ce79bc6 100644 --- a/examples/foundational/38b-smart-turn-local.py +++ b/examples/foundational/38b-smart-turn-local.py @@ -35,24 +35,20 @@ from pipecat.turns.user_turn_strategies import UserTurnStrategies load_dotenv(override=True) -# We store functions so objects (e.g. SileroVADAnalyzer) don't get -# instantiated. The function will be called when the desired transport gets -# selected. +# We use lambdas to defer transport parameter creation until the transport +# type is selected at runtime. transport_params = { "daily": lambda: DailyParams( audio_in_enabled=True, audio_out_enabled=True, - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), "twilio": lambda: FastAPIWebsocketParams( audio_in_enabled=True, audio_out_enabled=True, - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), "webrtc": lambda: TransportParams( audio_in_enabled=True, audio_out_enabled=True, - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), } @@ -83,6 +79,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): user_turn_strategies=UserTurnStrategies( stop=[TurnAnalyzerUserTurnStopStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3())] ), + vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), ) diff --git a/examples/foundational/39-mcp-stdio.py b/examples/foundational/39-mcp-stdio.py index 02b4b2295..95237e6ad 100644 --- a/examples/foundational/39-mcp-stdio.py +++ b/examples/foundational/39-mcp-stdio.py @@ -112,9 +112,8 @@ def open_image_output_filter(output: str): print(f"🖼️ link to high resolution artwork: {text_to_print}") -# We store functions so objects (e.g. SileroVADAnalyzer) don't get -# instantiated. The function will be called when the desired transport gets -# selected. +# We use lambdas to defer transport parameter creation until the transport +# type is selected at runtime. transport_params = { "daily": lambda: DailyParams( audio_in_enabled=True, @@ -122,7 +121,6 @@ transport_params = { video_out_enabled=True, video_out_width=1024, video_out_height=1024, - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), "webrtc": lambda: TransportParams( audio_in_enabled=True, @@ -130,7 +128,6 @@ transport_params = { video_out_enabled=True, video_out_width=1024, video_out_height=1024, - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), } @@ -200,6 +197,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): TurnAnalyzerUserTurnStopStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3()) ] ), + vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), ) diff --git a/examples/foundational/39a-mcp-streamable-http.py b/examples/foundational/39a-mcp-streamable-http.py index 6bd8fad61..27b9e5a36 100644 --- a/examples/foundational/39a-mcp-streamable-http.py +++ b/examples/foundational/39a-mcp-streamable-http.py @@ -37,24 +37,20 @@ from pipecat.turns.user_turn_strategies import UserTurnStrategies load_dotenv(override=True) -# We store functions so objects (e.g. SileroVADAnalyzer) don't get -# instantiated. The function will be called when the desired transport gets -# selected. +# We use lambdas to defer transport parameter creation until the transport +# type is selected at runtime. transport_params = { "daily": lambda: DailyParams( audio_in_enabled=True, audio_out_enabled=True, - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), "twilio": lambda: FastAPIWebsocketParams( audio_in_enabled=True, audio_out_enabled=True, - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), "webrtc": lambda: TransportParams( audio_in_enabled=True, audio_out_enabled=True, - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), } @@ -111,6 +107,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): user_turn_strategies=UserTurnStrategies( stop=[TurnAnalyzerUserTurnStopStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3())] ), + vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), ) diff --git a/examples/foundational/39b-mcp-streamable-http-gemini-live.py b/examples/foundational/39b-mcp-streamable-http-gemini-live.py index 6294d9d71..38ac36f8f 100644 --- a/examples/foundational/39b-mcp-streamable-http-gemini-live.py +++ b/examples/foundational/39b-mcp-streamable-http-gemini-live.py @@ -37,24 +37,20 @@ from pipecat.turns.user_turn_strategies import UserTurnStrategies load_dotenv(override=True) -# We store functions so objects (e.g. SileroVADAnalyzer) don't get -# instantiated. The function will be called when the desired transport gets -# selected. +# We use lambdas to defer transport parameter creation until the transport +# type is selected at runtime. transport_params = { "daily": lambda: DailyParams( audio_in_enabled=True, audio_out_enabled=True, - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), "twilio": lambda: FastAPIWebsocketParams( audio_in_enabled=True, audio_out_enabled=True, - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), "webrtc": lambda: TransportParams( audio_in_enabled=True, audio_out_enabled=True, - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), } @@ -115,6 +111,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): user_turn_strategies=UserTurnStrategies( stop=[TurnAnalyzerUserTurnStopStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3())] ), + vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), ) diff --git a/examples/foundational/39c-multiple-mcp.py b/examples/foundational/39c-multiple-mcp.py index 05cbe2b22..bb3dbd953 100644 --- a/examples/foundational/39c-multiple-mcp.py +++ b/examples/foundational/39c-multiple-mcp.py @@ -95,9 +95,8 @@ class UrlToImageProcessor(FrameProcessor): logger.error(error_msg) -# We store functions so objects (e.g. SileroVADAnalyzer) don't get -# instantiated. The function will be called when the desired transport gets -# selected. +# We use lambdas to defer transport parameter creation until the transport +# type is selected at runtime. transport_params = { "daily": lambda: DailyParams( audio_in_enabled=True, @@ -105,7 +104,6 @@ transport_params = { video_out_enabled=True, video_out_width=1024, video_out_height=1024, - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), "webrtc": lambda: TransportParams( audio_in_enabled=True, @@ -113,7 +111,6 @@ transport_params = { video_out_enabled=True, video_out_width=1024, video_out_height=1024, - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), } @@ -200,6 +197,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): TurnAnalyzerUserTurnStopStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3()) ] ), + vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), ) mcp_image_processor = UrlToImageProcessor(aiohttp_session=session) diff --git a/examples/foundational/40-aws-nova-sonic.py b/examples/foundational/40-aws-nova-sonic.py index f80bc5220..1bfa6063e 100644 --- a/examples/foundational/40-aws-nova-sonic.py +++ b/examples/foundational/40-aws-nova-sonic.py @@ -81,9 +81,8 @@ weather_function = FunctionSchema( tools = ToolsSchema(standard_tools=[weather_function]) -# We store functions so objects (e.g. SileroVADAnalyzer) don't get -# instantiated. The function will be called when the desired transport gets -# selected. +# We use lambdas to defer transport parameter creation until the transport +# type is selected at runtime. transport_params = { "daily": lambda: DailyParams( audio_in_enabled=True, diff --git a/examples/foundational/42-interruption-config.py b/examples/foundational/42-interruption-config.py index c70e54c2d..f4279e80f 100644 --- a/examples/foundational/42-interruption-config.py +++ b/examples/foundational/42-interruption-config.py @@ -37,24 +37,20 @@ from pipecat.turns.user_turn_strategies import UserTurnStrategies load_dotenv(override=True) -# We store functions so objects (e.g. SileroVADAnalyzer) don't get -# instantiated. The function will be called when the desired transport gets -# selected. +# We use lambdas to defer transport parameter creation until the transport +# type is selected at runtime. transport_params = { "daily": lambda: DailyParams( audio_in_enabled=True, audio_out_enabled=True, - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), "twilio": lambda: FastAPIWebsocketParams( audio_in_enabled=True, audio_out_enabled=True, - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), "webrtc": lambda: TransportParams( audio_in_enabled=True, audio_out_enabled=True, - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), } @@ -86,6 +82,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): start=[MinWordsUserTurnStartStrategy(min_words=3)], stop=[TurnAnalyzerUserTurnStopStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3())], ), + vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), ) diff --git a/examples/foundational/43a-heygen-video-service.py b/examples/foundational/43a-heygen-video-service.py index 9257fbc77..294e907bf 100644 --- a/examples/foundational/43a-heygen-video-service.py +++ b/examples/foundational/43a-heygen-video-service.py @@ -36,9 +36,8 @@ from pipecat.turns.user_turn_strategies import UserTurnStrategies load_dotenv(override=True) -# We store functions so objects (e.g. SileroVADAnalyzer) don't get -# instantiated. The function will be called when the desired transport gets -# selected. +# We use lambdas to defer transport parameter creation until the transport +# type is selected at runtime. transport_params = { "daily": lambda: DailyParams( audio_in_enabled=True, @@ -48,7 +47,6 @@ transport_params = { video_out_width=1280, video_out_height=720, video_out_bitrate=2_000_000, # 2MBps - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), "webrtc": lambda: TransportParams( audio_in_enabled=True, @@ -57,7 +55,6 @@ transport_params = { video_out_is_live=True, video_out_width=1280, video_out_height=720, - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), } @@ -96,6 +93,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): TurnAnalyzerUserTurnStopStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3()) ] ), + vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), ) diff --git a/examples/foundational/44-voicemail-detection.py b/examples/foundational/44-voicemail-detection.py index baa76a05f..1ab1cdf7f 100644 --- a/examples/foundational/44-voicemail-detection.py +++ b/examples/foundational/44-voicemail-detection.py @@ -35,24 +35,20 @@ from pipecat.turns.user_turn_strategies import UserTurnStrategies load_dotenv(override=True) -# We store functions so objects (e.g. SileroVADAnalyzer) don't get -# instantiated. The function will be called when the desired transport gets -# selected. +# We use lambdas to defer transport parameter creation until the transport +# type is selected at runtime. transport_params = { "daily": lambda: DailyParams( audio_in_enabled=True, audio_out_enabled=True, - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), "twilio": lambda: FastAPIWebsocketParams( audio_in_enabled=True, audio_out_enabled=True, - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), "webrtc": lambda: TransportParams( audio_in_enabled=True, audio_out_enabled=True, - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), } @@ -86,6 +82,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): user_turn_strategies=UserTurnStrategies( stop=[TurnAnalyzerUserTurnStopStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3())] ), + vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), ) diff --git a/examples/foundational/45-before-and-after-events.py b/examples/foundational/45-before-and-after-events.py index c6f9376e5..4664979e1 100644 --- a/examples/foundational/45-before-and-after-events.py +++ b/examples/foundational/45-before-and-after-events.py @@ -46,24 +46,20 @@ class CustomAfterPushFrame(DataFrame): pass -# We store functions so objects (e.g. SileroVADAnalyzer) don't get -# instantiated. The function will be called when the desired transport gets -# selected. +# We use lambdas to defer transport parameter creation until the transport +# type is selected at runtime. transport_params = { "daily": lambda: DailyParams( audio_in_enabled=True, audio_out_enabled=True, - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), "twilio": lambda: FastAPIWebsocketParams( audio_in_enabled=True, audio_out_enabled=True, - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), "webrtc": lambda: TransportParams( audio_in_enabled=True, audio_out_enabled=True, - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), } @@ -94,6 +90,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): user_turn_strategies=UserTurnStrategies( stop=[TurnAnalyzerUserTurnStopStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3())] ), + vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), ) diff --git a/examples/foundational/46-video-processing.py b/examples/foundational/46-video-processing.py index bb3d57f04..ee490bfce 100644 --- a/examples/foundational/46-video-processing.py +++ b/examples/foundational/46-video-processing.py @@ -12,6 +12,7 @@ from loguru import logger from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3 from pipecat.audio.vad.silero import SileroVADAnalyzer +from pipecat.audio.vad.vad_analyzer import VADParams from pipecat.frames.frames import Frame, InputImageRawFrame, LLMRunFrame, OutputImageRawFrame from pipecat.pipeline.pipeline import Pipeline from pipecat.pipeline.runner import PipelineRunner @@ -40,7 +41,6 @@ transport_params = { video_in_enabled=True, video_out_enabled=True, video_out_is_live=True, - vad_analyzer=SileroVADAnalyzer(), ), "webrtc": lambda: TransportParams( audio_in_enabled=True, @@ -49,7 +49,6 @@ transport_params = { video_in_enabled=True, video_out_enabled=True, video_out_is_live=True, - vad_analyzer=SileroVADAnalyzer(), ), } @@ -121,6 +120,7 @@ async def run_bot(pipecat_transport): user_turn_strategies=UserTurnStrategies( stop=[TurnAnalyzerUserTurnStopStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3())] ), + vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), ) diff --git a/examples/foundational/47-sentry-metrics.py b/examples/foundational/47-sentry-metrics.py index 1b74210a1..85196f10a 100644 --- a/examples/foundational/47-sentry-metrics.py +++ b/examples/foundational/47-sentry-metrics.py @@ -36,24 +36,20 @@ from pipecat.turns.user_turn_strategies import UserTurnStrategies load_dotenv(override=True) -# We store functions so objects (e.g. SileroVADAnalyzer) don't get -# instantiated. The function will be called when the desired transport gets -# selected. +# We use lambdas to defer transport parameter creation until the transport +# type is selected at runtime. transport_params = { "daily": lambda: DailyParams( audio_in_enabled=True, audio_out_enabled=True, - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), "twilio": lambda: FastAPIWebsocketParams( audio_in_enabled=True, audio_out_enabled=True, - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), "webrtc": lambda: TransportParams( audio_in_enabled=True, audio_out_enabled=True, - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), } @@ -97,6 +93,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): user_turn_strategies=UserTurnStrategies( stop=[TurnAnalyzerUserTurnStopStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3())] ), + vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), ) diff --git a/examples/foundational/48-service-switcher.py b/examples/foundational/48-service-switcher.py index 97b06a44a..e2b796018 100644 --- a/examples/foundational/48-service-switcher.py +++ b/examples/foundational/48-service-switcher.py @@ -60,24 +60,20 @@ async def get_restaurant_recommendation(params: FunctionCallParams, location: st await params.result_callback({"name": "The Golden Dragon"}) -# We store functions so objects (e.g. SileroVADAnalyzer) don't get -# instantiated. The function will be called when the desired transport gets -# selected. +# We use lambdas to defer transport parameter creation until the transport +# type is selected at runtime. transport_params = { "daily": lambda: DailyParams( audio_in_enabled=True, audio_out_enabled=True, - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), "twilio": lambda: FastAPIWebsocketParams( audio_in_enabled=True, audio_out_enabled=True, - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), "webrtc": lambda: TransportParams( audio_in_enabled=True, audio_out_enabled=True, - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), } @@ -142,6 +138,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): user_turn_strategies=UserTurnStrategies( stop=[TurnAnalyzerUserTurnStopStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3())] ), + vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), ) diff --git a/examples/foundational/49a-thinking-anthropic.py b/examples/foundational/49a-thinking-anthropic.py index d813aeee5..521a92282 100644 --- a/examples/foundational/49a-thinking-anthropic.py +++ b/examples/foundational/49a-thinking-anthropic.py @@ -35,24 +35,20 @@ from pipecat.turns.user_turn_strategies import UserTurnStrategies load_dotenv(override=True) -# We store functions so objects (e.g. SileroVADAnalyzer) don't get -# instantiated. The function will be called when the desired transport gets -# selected. +# We use lambdas to defer transport parameter creation until the transport +# type is selected at runtime. transport_params = { "daily": lambda: DailyParams( audio_in_enabled=True, audio_out_enabled=True, - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), "twilio": lambda: FastAPIWebsocketParams( audio_in_enabled=True, audio_out_enabled=True, - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), "webrtc": lambda: TransportParams( audio_in_enabled=True, audio_out_enabled=True, - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), } @@ -88,6 +84,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): user_turn_strategies=UserTurnStrategies( stop=[TurnAnalyzerUserTurnStopStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3())] ), + vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), ) diff --git a/examples/foundational/49b-thinking-google.py b/examples/foundational/49b-thinking-google.py index 40cd48f31..223a77e1e 100644 --- a/examples/foundational/49b-thinking-google.py +++ b/examples/foundational/49b-thinking-google.py @@ -35,24 +35,20 @@ from pipecat.turns.user_turn_strategies import UserTurnStrategies load_dotenv(override=True) -# We store functions so objects (e.g. SileroVADAnalyzer) don't get -# instantiated. The function will be called when the desired transport gets -# selected. +# We use lambdas to defer transport parameter creation until the transport +# type is selected at runtime. transport_params = { "daily": lambda: DailyParams( audio_in_enabled=True, audio_out_enabled=True, - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), "twilio": lambda: FastAPIWebsocketParams( audio_in_enabled=True, audio_out_enabled=True, - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), "webrtc": lambda: TransportParams( audio_in_enabled=True, audio_out_enabled=True, - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), } @@ -93,6 +89,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): user_turn_strategies=UserTurnStrategies( stop=[TurnAnalyzerUserTurnStopStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3())] ), + vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), ) diff --git a/examples/foundational/49c-thinking-functions-anthropic.py b/examples/foundational/49c-thinking-functions-anthropic.py index 33ea3ff0d..baa13b5d1 100644 --- a/examples/foundational/49c-thinking-functions-anthropic.py +++ b/examples/foundational/49c-thinking-functions-anthropic.py @@ -56,24 +56,20 @@ async def book_taxi(params: FunctionCallParams, time: str): await params.result_callback({"status": "done"}) -# We store functions so objects (e.g. SileroVADAnalyzer) don't get -# instantiated. The function will be called when the desired transport gets -# selected. +# We use lambdas to defer transport parameter creation until the transport +# type is selected at runtime. transport_params = { "daily": lambda: DailyParams( audio_in_enabled=True, audio_out_enabled=True, - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), "twilio": lambda: FastAPIWebsocketParams( audio_in_enabled=True, audio_out_enabled=True, - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), "webrtc": lambda: TransportParams( audio_in_enabled=True, audio_out_enabled=True, - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), } @@ -114,6 +110,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): user_turn_strategies=UserTurnStrategies( stop=[TurnAnalyzerUserTurnStopStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3())] ), + vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), ) diff --git a/examples/foundational/49d-thinking-functions-google.py b/examples/foundational/49d-thinking-functions-google.py index e00c3d00f..c03b37c0d 100644 --- a/examples/foundational/49d-thinking-functions-google.py +++ b/examples/foundational/49d-thinking-functions-google.py @@ -56,24 +56,20 @@ async def book_taxi(params: FunctionCallParams, time: str): await params.result_callback({"status": "done"}) -# We store functions so objects (e.g. SileroVADAnalyzer) don't get -# instantiated. The function will be called when the desired transport gets -# selected. +# We use lambdas to defer transport parameter creation until the transport +# type is selected at runtime. transport_params = { "daily": lambda: DailyParams( audio_in_enabled=True, audio_out_enabled=True, - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), "twilio": lambda: FastAPIWebsocketParams( audio_in_enabled=True, audio_out_enabled=True, - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), "webrtc": lambda: TransportParams( audio_in_enabled=True, audio_out_enabled=True, - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), } @@ -119,6 +115,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): user_turn_strategies=UserTurnStrategies( stop=[TurnAnalyzerUserTurnStopStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3())] ), + vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), ) diff --git a/examples/foundational/50-ultravox-realtime.py b/examples/foundational/50-ultravox-realtime.py index 51c298d77..5038cbb4c 100644 --- a/examples/foundational/50-ultravox-realtime.py +++ b/examples/foundational/50-ultravox-realtime.py @@ -29,9 +29,8 @@ from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams load_dotenv(override=True) -# We store functions so objects (e.g. SileroVADAnalyzer) don't get -# instantiated. The function will be called when the desired transport gets -# selected. +# We use lambdas to defer transport parameter creation until the transport +# type is selected at runtime. transport_params = { "daily": lambda: DailyParams( audio_in_enabled=True, diff --git a/examples/foundational/52-live-translation.py b/examples/foundational/52-live-translation.py index 347c0a99e..6545d64c3 100644 --- a/examples/foundational/52-live-translation.py +++ b/examples/foundational/52-live-translation.py @@ -36,24 +36,20 @@ from pipecat.turns.user_turn_strategies import UserTurnStrategies load_dotenv(override=True) -# We store functions so objects (e.g. SileroVADAnalyzer) don't get -# instantiated. The function will be called when the desired transport gets -# selected. +# We use lambdas to defer transport parameter creation until the transport +# type is selected at runtime. transport_params = { "daily": lambda: DailyParams( audio_in_enabled=True, audio_out_enabled=True, - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), "twilio": lambda: FastAPIWebsocketParams( audio_in_enabled=True, audio_out_enabled=True, - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), "webrtc": lambda: TransportParams( audio_in_enabled=True, audio_out_enabled=True, - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), } @@ -90,6 +86,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): start=[TranscriptionUserTurnStartStrategy(enable_interruptions=False)], stop=[TurnAnalyzerUserTurnStopStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3())], ), + vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), ) diff --git a/examples/foundational/53-concurrent-llm-evaluation.py b/examples/foundational/53-concurrent-llm-evaluation.py index 432088574..7aff957a5 100644 --- a/examples/foundational/53-concurrent-llm-evaluation.py +++ b/examples/foundational/53-concurrent-llm-evaluation.py @@ -23,6 +23,7 @@ from pipecat.processors.aggregators.llm_response_universal import ( LLMContextAggregatorPair, LLMUserAggregatorParams, ) +from pipecat.processors.audio.vad_processor import VADProcessor from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport from pipecat.services.cartesia.tts import CartesiaTTSService @@ -39,24 +40,20 @@ from pipecat.turns.user_turn_strategies import ExternalUserTurnStrategies, UserT load_dotenv(override=True) -# We store functions so objects (e.g. SileroVADAnalyzer) don't get -# instantiated. The function will be called when the desired transport gets -# selected. +# We use lambdas to defer transport parameter creation until the transport +# type is selected at runtime. transport_params = { "daily": lambda: DailyParams( audio_in_enabled=True, audio_out_enabled=True, - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), "twilio": lambda: FastAPIWebsocketParams( audio_in_enabled=True, audio_out_enabled=True, - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), "webrtc": lambda: TransportParams( audio_in_enabled=True, audio_out_enabled=True, - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), } @@ -68,7 +65,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): tts = CartesiaTTSService( api_key=os.getenv("CARTESIA_API_KEY"), - voice_id="d4db5fb9-f44b-4bd1-85fa-192e0f0d75f9", # Spanish-speaking Lady + voice_id="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady ) openai_llm = OpenAILLMService(api_key=os.getenv("OPENAI_API_KEY")) @@ -94,6 +91,12 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): openai_context = LLMContext(openai_messages) groq_context = LLMContext(groq_messages) + # We use an external VADProcessor because the UserTurnProcessor is shared + # across multiple parallel aggregators. The VADProcessor emits + # VADUserStartedSpeakingFrame and VADUserStoppedSpeakingFrame which the + # UserTurnProcessor needs to manage turn lifecycle. + vad_processor = VADProcessor(vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2))) + # We use this external user turn processor. This processor will push # UserStartedSpeakingFrame and UserStoppedSpeakingFrame as well as # interruptions. This can be used in advanced cases when there are multiple @@ -119,6 +122,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): [ transport.input(), # Transport user input stt, # STT + vad_processor, user_turn_processor, ParallelPipeline( [ From c46e7f5da09901f596debec9746f22521859fecb Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Aleix=20Conchillo=20Flaqu=C3=A9?= Date: Wed, 28 Jan 2026 16:13:39 -0800 Subject: [PATCH 0303/1060] TurnAnalyzerUserTurnStopStrategy: only update vad params if frame contains vad --- .../turns/user_stop/turn_analyzer_user_turn_stop_strategy.py | 3 ++- 1 file changed, 2 insertions(+), 1 deletion(-) diff --git a/src/pipecat/turns/user_stop/turn_analyzer_user_turn_stop_strategy.py b/src/pipecat/turns/user_stop/turn_analyzer_user_turn_stop_strategy.py index 1bb266380..109359c2a 100644 --- a/src/pipecat/turns/user_stop/turn_analyzer_user_turn_stop_strategy.py +++ b/src/pipecat/turns/user_stop/turn_analyzer_user_turn_stop_strategy.py @@ -113,7 +113,8 @@ class TurnAnalyzerUserTurnStopStrategy(BaseUserTurnStopStrategy): audio collected during that confirmation window, so we let the analyzer know when this value has changed. """ - self._turn_analyzer.update_vad_start_secs(frame.vad_params.start_secs) + if frame.vad_params: + self._turn_analyzer.update_vad_start_secs(frame.vad_params.start_secs) async def _handle_input_audio(self, frame: InputAudioRawFrame): """Handle input audio to check if the turn is completed.""" From a69a037ffa5f3f38818c120beccde75202c40270 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Aleix=20Conchillo=20Flaqu=C3=A9?= Date: Wed, 28 Jan 2026 12:37:15 -0800 Subject: [PATCH 0304/1060] changelog: add updates for #3583 --- changelog/3583.added.2.md | 1 + changelog/3583.added.3.md | 1 + changelog/3583.added.md | 10 ++++++++++ changelog/3583.deprecated.md | 1 + 4 files changed, 13 insertions(+) create mode 100644 changelog/3583.added.2.md create mode 100644 changelog/3583.added.3.md create mode 100644 changelog/3583.added.md create mode 100644 changelog/3583.deprecated.md diff --git a/changelog/3583.added.2.md b/changelog/3583.added.2.md new file mode 100644 index 000000000..f0c5c7d1e --- /dev/null +++ b/changelog/3583.added.2.md @@ -0,0 +1 @@ +- Added `VADController` for managing voice activity detection state and emitting speech events independently of transport or pipeline processors. diff --git a/changelog/3583.added.3.md b/changelog/3583.added.3.md new file mode 100644 index 000000000..f5da90407 --- /dev/null +++ b/changelog/3583.added.3.md @@ -0,0 +1 @@ +- Added `VADProcessor` for detecting speech in audio streams within a pipeline. Pushes `VADUserStartedSpeakingFrame`, `VADUserStoppedSpeakingFrame`, and `UserSpeakingFrame` downstream based on VAD state changes. diff --git a/changelog/3583.added.md b/changelog/3583.added.md new file mode 100644 index 000000000..47048e226 --- /dev/null +++ b/changelog/3583.added.md @@ -0,0 +1,10 @@ +- Added `vad_analyzer` parameter to `LLMUserAggregatorParams`. VAD analysis is now handled inside the `LLMUserAggregator` rather than in the transport, keeping voice activity detection closer to where it is consumed. The `vad_analyzer` on `BaseInputTransport` is now deprecated. + + ```python + context_aggregator = LLMContextAggregatorPair( + context, + user_params=LLMUserAggregatorParams( + vad_analyzer=SileroVADAnalyzer(), + ), + ) + ``` diff --git a/changelog/3583.deprecated.md b/changelog/3583.deprecated.md new file mode 100644 index 000000000..d4ea492eb --- /dev/null +++ b/changelog/3583.deprecated.md @@ -0,0 +1 @@ +- ⚠️ Deprecated `vad_analyzer` parameter on `BaseInputTransport`. Pass `vad_analyzer` to `LLMUserAggregatorParams` instead or use `VADProcessor` in the pipeline. From 183c0aa4efca8d277d139122e4605daf88fbf2e7 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Aleix=20Conchillo=20Flaqu=C3=A9?= Date: Wed, 28 Jan 2026 16:17:47 -0800 Subject: [PATCH 0305/1060] LLMUserAggregator: queue frames internally so strategies and controllers can process them --- .../aggregators/llm_response_universal.py | 31 +++++++++++++------ 1 file changed, 21 insertions(+), 10 deletions(-) diff --git a/src/pipecat/processors/aggregators/llm_response_universal.py b/src/pipecat/processors/aggregators/llm_response_universal.py index 13c3f24fb..9a7ee9c3e 100644 --- a/src/pipecat/processors/aggregators/llm_response_universal.py +++ b/src/pipecat/processors/aggregators/llm_response_universal.py @@ -64,7 +64,7 @@ from pipecat.processors.aggregators.llm_context import ( LLMSpecificMessage, NotGiven, ) -from pipecat.processors.frame_processor import FrameDirection, FrameProcessor +from pipecat.processors.frame_processor import FrameCallback, FrameDirection, FrameProcessor from pipecat.turns.user_idle_controller import UserIdleController from pipecat.turns.user_mute import BaseUserMuteStrategy from pipecat.turns.user_start import BaseUserTurnStartStrategy, UserTurnStartedParams @@ -452,7 +452,7 @@ class LLMUserAggregator(LLMContextAggregator): await self.push_frame(frame, direction) elif isinstance(frame, LLMSetToolChoiceFrame): self.set_tool_choice(frame.tool_choice) - elif isinstance(frame, SpeechControlParamsFrame): + elif isinstance(frame, SpeechControlParamsFrame) and not self._vad_controller: await self._handle_speech_control_params(frame) else: await self.push_frame(frame, direction) @@ -587,25 +587,36 @@ class LLMUserAggregator(LLMContextAggregator): ) ) + async def _queued_broadcast_frame(self, frame_cls: Type[Frame], **kwargs): + """Broadcasts a frame upstream and queues it downstream for internal processing. + + Queues the frame downstream so it flows through ``process_frame`` and + is handled internally (e.g. by the ``UserTurnController``). The + upstream frame is pushed directly. + + Args: + frame_cls: The class of the frame to be broadcasted. + **kwargs: Keyword arguments to be passed to the frame's constructor. + """ + await self.queue_frame(frame_cls(**kwargs)) + await self.push_frame(frame_cls(**kwargs), FrameDirection.UPSTREAM) + async def _on_push_frame( self, controller, frame: Frame, direction: FrameDirection = FrameDirection.DOWNSTREAM ): - await self.push_frame(frame, direction) + await self.queue_frame(frame, direction) async def _on_broadcast_frame(self, controller, frame_cls: Type[Frame], **kwargs): - await self.broadcast_frame(frame_cls, **kwargs) + await self._queued_broadcast_frame(frame_cls, **kwargs) async def _on_vad_speech_started(self, controller): - await self.queue_frame(VADUserStartedSpeakingFrame()) - await self.broadcast_frame(VADUserStartedSpeakingFrame) + await self._queued_broadcast_frame(VADUserStartedSpeakingFrame) async def _on_vad_speech_stopped(self, controller): - await self.queue_frame(VADUserStoppedSpeakingFrame()) - await self.broadcast_frame(VADUserStoppedSpeakingFrame) + await self._queued_broadcast_frame(VADUserStoppedSpeakingFrame) async def _on_vad_speech_activity(self, controller): - await self.queue_frame(UserSpeakingFrame()) - await self.broadcast_frame(UserSpeakingFrame) + await self._queued_broadcast_frame(UserSpeakingFrame) async def _on_user_turn_started( self, From 27dbfa1eda7b7e7e74ba8b68a8013752d6d98c39 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Aleix=20Conchillo=20Flaqu=C3=A9?= Date: Wed, 28 Jan 2026 22:34:26 -0800 Subject: [PATCH 0306/1060] NvidiaTTSService: return AsyncIterator instead of AsyncIterable --- src/pipecat/services/nvidia/tts.py | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/src/pipecat/services/nvidia/tts.py b/src/pipecat/services/nvidia/tts.py index eddafce01..e90462ad9 100644 --- a/src/pipecat/services/nvidia/tts.py +++ b/src/pipecat/services/nvidia/tts.py @@ -12,7 +12,7 @@ gRPC API for high-quality speech synthesis. import asyncio import os -from typing import AsyncGenerator, AsyncIterable, Generator, Mapping, Optional +from typing import AsyncGenerator, AsyncIterator, Generator, Mapping, Optional from pipecat.utils.tracing.service_decorators import traced_tts @@ -181,7 +181,7 @@ class NvidiaTTSService(TTSService): except StopIteration: return None - async def async_iterator(iterator) -> AsyncIterable[rtts.SynthesizeSpeechResponse]: + async def async_iterator(iterator) -> AsyncIterator[rtts.SynthesizeSpeechResponse]: while True: item = await asyncio.to_thread(async_next, iterator) if item is None: From 9632efec8cb79f477c17bf13de474f29e8c2d899 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Aleix=20Conchillo=20Flaqu=C3=A9?= Date: Fri, 30 Jan 2026 10:05:02 -0800 Subject: [PATCH 0307/1060] VADProcessor: broadcast frames --- src/pipecat/processors/audio/vad_processor.py | 6 +++--- 1 file changed, 3 insertions(+), 3 deletions(-) diff --git a/src/pipecat/processors/audio/vad_processor.py b/src/pipecat/processors/audio/vad_processor.py index 2076eeeb3..074ea57e6 100644 --- a/src/pipecat/processors/audio/vad_processor.py +++ b/src/pipecat/processors/audio/vad_processor.py @@ -64,16 +64,16 @@ class VADProcessor(FrameProcessor): @self._vad_controller.event_handler("on_speech_started") async def on_speech_started(_controller): logger.debug(f"{self}: User started speaking") - await self.push_frame(VADUserStartedSpeakingFrame()) + await self.broadcast_frame(VADUserStartedSpeakingFrame) @self._vad_controller.event_handler("on_speech_stopped") async def on_speech_stopped(_controller): logger.debug(f"{self}: User stopped speaking") - await self.push_frame(VADUserStoppedSpeakingFrame()) + await self.broadcast_frame(VADUserStoppedSpeakingFrame) @self._vad_controller.event_handler("on_speech_activity") async def on_speech_activity(_controller): - await self.push_frame(UserSpeakingFrame()) + await self.broadcast_frame(UserSpeakingFrame) # Wire up frame pushing from controller to processor @self._vad_controller.event_handler("on_push_frame") From 35d265770de237902bc5ff9d324e6af3302ad8a1 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Aleix=20Conchillo=20Flaqu=C3=A9?= Date: Fri, 30 Jan 2026 10:05:27 -0800 Subject: [PATCH 0308/1060] LLMUserAggregator: don't process certain self-queued frames --- .../aggregators/llm_response_universal.py | 35 ++++++++++++++----- 1 file changed, 27 insertions(+), 8 deletions(-) diff --git a/src/pipecat/processors/aggregators/llm_response_universal.py b/src/pipecat/processors/aggregators/llm_response_universal.py index 9a7ee9c3e..5d3432929 100644 --- a/src/pipecat/processors/aggregators/llm_response_universal.py +++ b/src/pipecat/processors/aggregators/llm_response_universal.py @@ -401,6 +401,11 @@ class LLMUserAggregator(LLMContextAggregator): self._vad_controller.add_event_handler("on_push_frame", self._on_push_frame) self._vad_controller.add_event_handler("on_broadcast_frame", self._on_broadcast_frame) + # NOTE(aleix): Probably just needed temporarily. This was added to + # prevent processing self-queued frames (SpeechControlParamsFrame) + # pushed by strategies. + self._self_queued_frames = set() + async def cleanup(self): """Clean up processor resources.""" await super().cleanup() @@ -452,7 +457,7 @@ class LLMUserAggregator(LLMContextAggregator): await self.push_frame(frame, direction) elif isinstance(frame, LLMSetToolChoiceFrame): self.set_tool_choice(frame.tool_choice) - elif isinstance(frame, SpeechControlParamsFrame) and not self._vad_controller: + elif isinstance(frame, SpeechControlParamsFrame): await self._handle_speech_control_params(frame) else: await self.push_frame(frame, direction) @@ -548,6 +553,9 @@ class LLMUserAggregator(LLMContextAggregator): await self.push_context_frame() async def _handle_speech_control_params(self, frame: SpeechControlParamsFrame): + if frame.id in self._self_queued_frames: + return + if not frame.turn_params: return @@ -587,24 +595,35 @@ class LLMUserAggregator(LLMContextAggregator): ) ) - async def _queued_broadcast_frame(self, frame_cls: Type[Frame], **kwargs): - """Broadcasts a frame upstream and queues it downstream for internal processing. + async def _internal_queue_frame( + self, + frame: Frame, + direction: FrameDirection = FrameDirection.DOWNSTREAM, + callback: Optional[FrameCallback] = None, + ): + """Queues the given frame to ourselves.""" + self._self_queued_frames.add(frame.id) + await self.queue_frame(frame, direction, callback) - Queues the frame downstream so it flows through ``process_frame`` and - is handled internally (e.g. by the ``UserTurnController``). The - upstream frame is pushed directly. + async def _queued_broadcast_frame(self, frame_cls: Type[Frame], **kwargs): + """Broadcasts a frame upstream and queues it for internal processing. + + Queues the frame so it flows through `process_frame` and is handled + internally (e.g. by the `UserTurnController`). The upstream frame is + pushed directly. Args: frame_cls: The class of the frame to be broadcasted. **kwargs: Keyword arguments to be passed to the frame's constructor. + """ - await self.queue_frame(frame_cls(**kwargs)) + await self._internal_queue_frame(frame_cls(**kwargs)) await self.push_frame(frame_cls(**kwargs), FrameDirection.UPSTREAM) async def _on_push_frame( self, controller, frame: Frame, direction: FrameDirection = FrameDirection.DOWNSTREAM ): - await self.queue_frame(frame, direction) + await self._internal_queue_frame(frame, direction) async def _on_broadcast_frame(self, controller, frame_cls: Type[Frame], **kwargs): await self._queued_broadcast_frame(frame_cls, **kwargs) From b93e12d701110b720d781b92b14969d4b573f0a3 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Aleix=20Conchillo=20Flaqu=C3=A9?= Date: Fri, 30 Jan 2026 10:52:38 -0800 Subject: [PATCH 0309/1060] scripts(evals): disable RTVI --- scripts/evals/eval.py | 1 + 1 file changed, 1 insertion(+) diff --git a/scripts/evals/eval.py b/scripts/evals/eval.py index 20c15c1c9..79b64e6ef 100644 --- a/scripts/evals/eval.py +++ b/scripts/evals/eval.py @@ -332,6 +332,7 @@ async def run_eval_pipeline( audio_in_sample_rate=16000, audio_out_sample_rate=16000, ), + enable_rtvi=False, idle_timeout_secs=PIPELINE_IDLE_TIMEOUT_SECS, ) From c9310789dc8d3f1f96c598ed0c1100a392ee4386 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Aleix=20Conchillo=20Flaqu=C3=A9?= Date: Fri, 30 Jan 2026 10:57:17 -0800 Subject: [PATCH 0310/1060] scripts(evals): use new vad_analyzer from LLMUSerAggregator --- scripts/evals/eval.py | 13 ++++++++++--- 1 file changed, 10 insertions(+), 3 deletions(-) diff --git a/scripts/evals/eval.py b/scripts/evals/eval.py index 79b64e6ef..d7272806c 100644 --- a/scripts/evals/eval.py +++ b/scripts/evals/eval.py @@ -42,7 +42,10 @@ from pipecat.pipeline.pipeline import Pipeline from pipecat.pipeline.runner import PipelineRunner from pipecat.pipeline.task import PipelineParams, PipelineTask from pipecat.processors.aggregators.llm_context import LLMContext -from pipecat.processors.aggregators.llm_response_universal import LLMContextAggregatorPair +from pipecat.processors.aggregators.llm_response_universal import ( + LLMContextAggregatorPair, + LLMUserAggregatorParams, +) from pipecat.processors.audio.audio_buffer_processor import AudioBufferProcessor from pipecat.processors.frame_processor import FrameDirection from pipecat.runner.types import RunnerArguments @@ -207,7 +210,6 @@ async def run_example_pipeline(script_path: Path, eval_config: EvalConfig): audio_in_enabled=True, audio_out_enabled=True, video_in_enabled=True, - vad_analyzer=SileroVADAnalyzer(), ), ) @@ -309,7 +311,12 @@ async def run_eval_pipeline( ] context = LLMContext(messages, tools) - context_aggregator = LLMContextAggregatorPair(context) + context_aggregator = LLMContextAggregatorPair( + context, + user_params=LLMUserAggregatorParams( + vad_analyzer=SileroVADAnalyzer(), + ), + ) audio_buffer = AudioBufferProcessor() From a98ca9b65b19f6c43da5c3cbc3e39995b151cc95 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Aleix=20Conchillo=20Flaqu=C3=A9?= Date: Fri, 30 Jan 2026 11:38:26 -0800 Subject: [PATCH 0311/1060] LLMService: make sure function call timeout handler is started --- src/pipecat/services/llm_service.py | 31 ++++++++++++++++++++--------- 1 file changed, 22 insertions(+), 9 deletions(-) diff --git a/src/pipecat/services/llm_service.py b/src/pipecat/services/llm_service.py index 035f1b2f2..82c2e7303 100644 --- a/src/pipecat/services/llm_service.py +++ b/src/pipecat/services/llm_service.py @@ -601,15 +601,7 @@ class LLMService(AIService): cancel_on_interruption=item.cancel_on_interruption, ) - # Start a timeout task for deferred function calls - async def timeout_handler(): - await asyncio.sleep(self._function_call_timeout_secs) - logger.warning( - f"{self} Function call [{runner_item.function_name}:{runner_item.tool_call_id}] timed out after {self._function_call_timeout_secs} seconds" - ) - await function_call_result_callback(None) - - timeout_task = self.create_task(timeout_handler()) + timeout_task: Optional[asyncio.Task] = None # Define a callback function that pushes a FunctionCallResultFrame upstream & downstream. async def function_call_result_callback( @@ -631,6 +623,24 @@ class LLMService(AIService): properties=properties, ) + # Start a timeout task for deferred function calls + async def timeout_handler(): + try: + await asyncio.sleep(self._function_call_timeout_secs) + logger.warning( + f"{self} Function call [{runner_item.function_name}:{runner_item.tool_call_id}] timed out after {self._function_call_timeout_secs} seconds" + ) + await function_call_result_callback(None) + except asyncio.CancelledError: + raise + + timeout_task = self.create_task(timeout_handler()) + + # Yield to the event loop so the timeout task coroutine gets entered + # before it could be cancelled. Without this, cancelling the task before + # it starts would leave the coroutine in a "never awaited" state. + await asyncio.sleep(0) + try: if isinstance(item.handler, DirectFunctionWrapper): # Handler is a DirectFunctionWrapper @@ -667,6 +677,9 @@ class LLMService(AIService): ) await item.handler(params) except Exception as e: + # Cancel timeout task if it exists + if timeout_task and not timeout_task.done(): + await self.cancel_task(timeout_task) error_message = f"Error executing function call [{runner_item.function_name}]: {e}" logger.error(f"{self} {error_message}") await self.push_error(error_msg=error_message, exception=e, fatal=False) From 63a23246d542668867e9bac5426749c39439ed04 Mon Sep 17 00:00:00 2001 From: Mark Backman Date: Fri, 30 Jan 2026 14:57:15 -0500 Subject: [PATCH 0312/1060] Add UserTurnCompletionLLMServiceMixin (#3518) * Added UserTurnCompletionLLMServiceMixin class * Added 22-filter-incomplete-turns.py foundational example * Removed old 22 natural conversation foundational examples * Added test_user_turn_completion_mixin.py --- changelog/3518.added.md | 1 + .../22-filter-incomplete-turns.py | 180 ++++ .../foundational/22-natural-conversation.py | 212 ----- .../22b-natural-conversation-proposal.py | 414 --------- .../22c-natural-conversation-mixed-llms.py | 622 -------------- .../22d-natural-conversation-gemini-audio.py | 813 ------------------ .../aggregators/llm_response_universal.py | 58 +- src/pipecat/services/anthropic/llm.py | 2 +- src/pipecat/services/aws/llm.py | 2 +- src/pipecat/services/google/llm.py | 2 +- src/pipecat/services/llm_service.py | 47 +- src/pipecat/services/openai/base_llm.py | 2 +- .../turns/user_turn_completion_mixin.py | 428 +++++++++ tests/test_context_aggregators_universal.py | 48 ++ tests/test_user_turn_completion_mixin.py | 117 +++ 15 files changed, 881 insertions(+), 2067 deletions(-) create mode 100644 changelog/3518.added.md create mode 100644 examples/foundational/22-filter-incomplete-turns.py delete mode 100644 examples/foundational/22-natural-conversation.py delete mode 100644 examples/foundational/22b-natural-conversation-proposal.py delete mode 100644 examples/foundational/22c-natural-conversation-mixed-llms.py delete mode 100644 examples/foundational/22d-natural-conversation-gemini-audio.py create mode 100644 src/pipecat/turns/user_turn_completion_mixin.py create mode 100644 tests/test_user_turn_completion_mixin.py diff --git a/changelog/3518.added.md b/changelog/3518.added.md new file mode 100644 index 000000000..b9740f024 --- /dev/null +++ b/changelog/3518.added.md @@ -0,0 +1 @@ +- Added `UserTurnCompletionLLMServiceMixin` for LLM services to detect and filter incomplete user turns. When enabled via `filter_incomplete_user_turns` in `LLMUserAggregatorParams`, the LLM outputs a turn completion marker at the start of each response: ✓ (complete), ○ (incomplete short), or ◐ (incomplete long). Incomplete turns are suppressed, and configurable timeouts automatically re-prompt the user. diff --git a/examples/foundational/22-filter-incomplete-turns.py b/examples/foundational/22-filter-incomplete-turns.py new file mode 100644 index 000000000..967750c48 --- /dev/null +++ b/examples/foundational/22-filter-incomplete-turns.py @@ -0,0 +1,180 @@ +# +# Copyright (c) 2024-2026, Daily +# +# SPDX-License-Identifier: BSD 2-Clause License +# + +"""Example 22: Filter Incomplete Turns + +Demonstrates LLM-based turn completion detection to suppress bot responses when +the user was cut off mid-thought. The LLM outputs one of three markers: +- ✓ (complete): User finished their thought, respond normally +- ○ (incomplete short): User was cut off, wait ~5s then prompt +- ◐ (incomplete long): User needs time to think, wait ~15s then prompt + +When incomplete is detected, the bot's response is suppressed. After the timeout +expires, the LLM is automatically prompted to re-engage the user. +""" + +import os + +from dotenv import load_dotenv +from loguru import logger + +from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3 +from pipecat.audio.vad.silero import SileroVADAnalyzer +from pipecat.audio.vad.vad_analyzer import VADParams +from pipecat.frames.frames import LLMRunFrame +from pipecat.pipeline.pipeline import Pipeline +from pipecat.pipeline.runner import PipelineRunner +from pipecat.pipeline.task import PipelineParams, PipelineTask +from pipecat.processors.aggregators.llm_context import LLMContext +from pipecat.processors.aggregators.llm_response_universal import ( + AssistantTurnStoppedMessage, + LLMContextAggregatorPair, + LLMUserAggregatorParams, + UserTurnStoppedMessage, +) +from pipecat.runner.types import RunnerArguments +from pipecat.runner.utils import create_transport +from pipecat.services.cartesia.tts import CartesiaTTSService +from pipecat.services.deepgram.stt import DeepgramSTTService +from pipecat.services.openai.llm import OpenAILLMService +from pipecat.transports.base_transport import BaseTransport, TransportParams +from pipecat.transports.daily.transport import DailyParams +from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams +from pipecat.turns.user_stop import TurnAnalyzerUserTurnStopStrategy +from pipecat.turns.user_turn_strategies import UserTurnStrategies + +load_dotenv(override=True) + + +# We store functions so objects (e.g. SileroVADAnalyzer) don't get +# instantiated. The function will be called when the desired transport gets +# selected. +transport_params = { + "daily": lambda: DailyParams( + audio_in_enabled=True, + audio_out_enabled=True, + vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), + ), + "twilio": lambda: FastAPIWebsocketParams( + audio_in_enabled=True, + audio_out_enabled=True, + vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), + ), + "webrtc": lambda: TransportParams( + audio_in_enabled=True, + audio_out_enabled=True, + vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), + ), +} + + +async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): + logger.info(f"Starting bot") + + stt = DeepgramSTTService(api_key=os.getenv("DEEPGRAM_API_KEY")) + + llm = OpenAILLMService(api_key=os.getenv("OPENAI_API_KEY")) + + tts = CartesiaTTSService( + api_key=os.getenv("CARTESIA_API_KEY"), + voice_id="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady + ) + + messages = [ + { + "role": "system", + "content": f"""You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.""", + } + ] + + context = LLMContext(messages) + user_aggregator, assistant_aggregator = LLMContextAggregatorPair( + context, + user_params=LLMUserAggregatorParams( + user_turn_strategies=UserTurnStrategies( + stop=[TurnAnalyzerUserTurnStopStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3())] + ), + # Enable turn completion filtering - the LLM will output: + # ✓ = complete (respond normally) + # ○ = incomplete short (wait 5s, then prompt) + # ◐ = incomplete long (wait 15s, then prompt) + filter_incomplete_user_turns=True, + # Optional: customize turn completion behavior + # turn_completion_config=TurnCompletionConfig( + # incomplete_short_timeout=5.0, + # incomplete_long_timeout=15.0, + # incomplete_short_prompt="Custom prompt...", + # incomplete_long_prompt="Custom prompt...", + # instructions="Custom turn completion instructions...", + # ), + ), + ) + + pipeline = Pipeline( + [ + transport.input(), # Transport user input + stt, + user_aggregator, # User responses + llm, # LLM + tts, # TTS + transport.output(), # Transport bot output + assistant_aggregator, # Assistant spoken responses + ] + ) + + task = PipelineTask( + pipeline, + params=PipelineParams( + enable_metrics=True, + enable_usage_metrics=True, + ), + idle_timeout_secs=runner_args.pipeline_idle_timeout_secs, + ) + + @transport.event_handler("on_client_connected") + async def on_client_connected(transport, client): + logger.info(f"Client connected") + # Kick off the conversation. + messages.append( + { + "role": "system", + "content": "Please introduce yourself to the user, asking them a question that will require a complete response. To start, say 'Let me start with a fun one. If you could travel anywhere in the world right now, where would you go and why?'", + } + ) + await task.queue_frames([LLMRunFrame()]) + + @transport.event_handler("on_client_disconnected") + async def on_client_disconnected(transport, client): + logger.info(f"Client disconnected") + await task.cancel() + + @user_aggregator.event_handler("on_user_turn_stopped") + async def on_user_turn_stopped(aggregator, strategy, message: UserTurnStoppedMessage): + timestamp = f"[{message.timestamp}] " if message.timestamp else "" + line = f"{timestamp}user: {message.content}" + logger.info(f"Transcript: {line}") + + @assistant_aggregator.event_handler("on_assistant_turn_stopped") + async def on_assistant_turn_stopped(aggregator, message: AssistantTurnStoppedMessage): + timestamp = f"[{message.timestamp}] " if message.timestamp else "" + line = f"{timestamp}assistant: {message.content}" + logger.info(f"Transcript: {line}") + + runner = PipelineRunner(handle_sigint=runner_args.handle_sigint) + + await runner.run(task) + + +async def bot(runner_args: RunnerArguments): + """Main bot entry point compatible with Pipecat Cloud.""" + transport = await create_transport(runner_args, transport_params) + await run_bot(transport, runner_args) + + +if __name__ == "__main__": + from pipecat.runner.run import main + + main() diff --git a/examples/foundational/22-natural-conversation.py b/examples/foundational/22-natural-conversation.py deleted file mode 100644 index 94887daaf..000000000 --- a/examples/foundational/22-natural-conversation.py +++ /dev/null @@ -1,212 +0,0 @@ -# -# Copyright (c) 2024-2026, Daily -# -# SPDX-License-Identifier: BSD 2-Clause License -# - - -import os - -from dotenv import load_dotenv -from loguru import logger - -from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3 -from pipecat.audio.vad.silero import SileroVADAnalyzer -from pipecat.audio.vad.vad_analyzer import VADParams -from pipecat.frames.frames import LLMRunFrame, TextFrame -from pipecat.pipeline.parallel_pipeline import ParallelPipeline -from pipecat.pipeline.pipeline import Pipeline -from pipecat.pipeline.runner import PipelineRunner -from pipecat.pipeline.task import PipelineParams, PipelineTask -from pipecat.processors.aggregators.gated_llm_context import GatedLLMContextAggregator -from pipecat.processors.aggregators.llm_context import LLMContext -from pipecat.processors.aggregators.llm_response_universal import ( - LLMContextAggregatorPair, - LLMUserAggregatorParams, -) -from pipecat.processors.filters.null_filter import NullFilter -from pipecat.processors.filters.wake_notifier_filter import WakeNotifierFilter -from pipecat.processors.user_idle_processor import UserIdleProcessor -from pipecat.runner.types import RunnerArguments -from pipecat.runner.utils import create_transport -from pipecat.services.cartesia.tts import CartesiaTTSService -from pipecat.services.deepgram.stt import DeepgramSTTService -from pipecat.services.llm_service import LLMService -from pipecat.services.openai.llm import OpenAIContextAggregatorPair, OpenAILLMService -from pipecat.transports.base_transport import BaseTransport, TransportParams -from pipecat.transports.daily.transport import DailyParams -from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams -from pipecat.turns.user_stop import TurnAnalyzerUserTurnStopStrategy -from pipecat.turns.user_turn_strategies import UserTurnStrategies -from pipecat.utils.sync.event_notifier import EventNotifier - -load_dotenv(override=True) - - -class TurnDetectionLLM(Pipeline): - def __init__(self, llm: LLMService, context_aggregator: OpenAIContextAggregatorPair): - # This is the LLM that will be used to detect if the user has finished a - # statement. This doesn't really need to be an LLM, we could use NLP - # libraries for that, but it was easier as an example because we - # leverage the context aggregators. - statement_llm = OpenAILLMService(api_key=os.getenv("OPENAI_API_KEY")) - - statement_messages = [ - { - "role": "system", - "content": "Determine if the user's statement is a complete sentence or question, ending in a natural pause or punctuation. Return 'YES' if it is complete and 'NO' if it seems to leave a thought unfinished.", - }, - ] - - statement_context = LLMContext(statement_messages) - statement_context_aggregator = LLMContextAggregatorPair(statement_context) - - # We have instructed the LLM to return 'YES' if it thinks the user - # completed a sentence. So, if it's 'YES' we will return true in this - # predicate which will wake up the notifier. - async def wake_check_filter(frame): - logger.debug(f"Completeness check frame: {frame}") - return frame.text == "YES" - - # This is a notifier that we use to synchronize the two LLMs. - notifier = EventNotifier() - - # This a filter that will wake up the notifier if the given predicate - # (wake_check_filter) returns true. - completness_check = WakeNotifierFilter( - notifier, types=(TextFrame,), filter=wake_check_filter - ) - - # This processor keeps the last context and will let it through once the - # notifier is woken up. We start with the gate open because we send an - # initial context frame to start the conversation. - gated_context_aggregator = GatedLLMContextAggregator(notifier=notifier, start_open=True) - - # Notify if the user hasn't said anything. - async def user_idle_notifier(frame): - await notifier.notify() - - # Sometimes the LLM will fail detecting if a user has completed a - # sentence, this will wake up the notifier if that happens. - user_idle = UserIdleProcessor(callback=user_idle_notifier, timeout=3.0) - - # The ParallePipeline input are the user transcripts. We have two - # contexts. The first one will be used to determine if the user finished - # a statement and if so the notifier will be woken up. The second - # context is simply the regular context but it's gated waiting for the - # notifier to be woken up. - super().__init__( - [ - ParallelPipeline( - [ - statement_context_aggregator.user(), - statement_llm, - completness_check, - NullFilter(), - ], - [context_aggregator.user(), gated_context_aggregator, llm], - ), - user_idle, - ] - ) - - -# We use lambdas to defer transport parameter creation until the transport -# type is selected at runtime. -transport_params = { - "daily": lambda: DailyParams( - audio_in_enabled=True, - audio_out_enabled=True, - ), - "webrtc": lambda: TransportParams( - audio_in_enabled=True, - audio_out_enabled=True, - ), - "twilio": lambda: FastAPIWebsocketParams( - audio_in_enabled=True, - audio_out_enabled=True, - ), -} - - -async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): - logger.info(f"Starting bot") - - stt = DeepgramSTTService(api_key=os.getenv("DEEPGRAM_API_KEY")) - - tts = CartesiaTTSService( - api_key=os.getenv("CARTESIA_API_KEY"), - voice_id="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady - ) - - # This is the regular LLM. - llm_main = OpenAILLMService(api_key=os.getenv("OPENAI_API_KEY")) - - messages = [ - { - "role": "system", - "content": "You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", - }, - ] - - context = LLMContext(messages) - context_aggregator = LLMContextAggregatorPair( - context, - user_params=LLMUserAggregatorParams( - user_turn_strategies=UserTurnStrategies( - stop=[TurnAnalyzerUserTurnStopStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3())] - ), - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), - ), - ) - - # LLM + turn detection (with an extra LLM as a judge) - llm = TurnDetectionLLM(llm_main, context_aggregator) - - pipeline = Pipeline( - [ - transport.input(), # Transport user input - stt, # STT - llm, # LLM with turn detection - tts, # TTS - transport.output(), # Transport bot output - context_aggregator.assistant(), # Assistant spoken responses - ] - ) - - task = PipelineTask( - pipeline, - params=PipelineParams( - enable_metrics=True, - enable_usage_metrics=True, - ), - idle_timeout_secs=runner_args.pipeline_idle_timeout_secs, - ) - - @transport.event_handler("on_client_connected") - async def on_client_connected(transport, client): - logger.info(f"Client connected") - # Kick off the conversation. - messages.append({"role": "system", "content": "Please introduce yourself to the user."}) - await task.queue_frames([LLMRunFrame()]) - - @transport.event_handler("on_client_disconnected") - async def on_client_disconnected(transport, client): - logger.info(f"Client disconnected") - await task.cancel() - - runner = PipelineRunner(handle_sigint=runner_args.handle_sigint) - - await runner.run(task) - - -async def bot(runner_args: RunnerArguments): - """Main bot entry point compatible with Pipecat Cloud.""" - transport = await create_transport(runner_args, transport_params) - await run_bot(transport, runner_args) - - -if __name__ == "__main__": - from pipecat.runner.run import main - - main() diff --git a/examples/foundational/22b-natural-conversation-proposal.py b/examples/foundational/22b-natural-conversation-proposal.py deleted file mode 100644 index 5bcb16e6e..000000000 --- a/examples/foundational/22b-natural-conversation-proposal.py +++ /dev/null @@ -1,414 +0,0 @@ -# -# Copyright (c) 2024-2026, Daily -# -# SPDX-License-Identifier: BSD 2-Clause License -# - -import asyncio -import os - -from dotenv import load_dotenv -from loguru import logger - -from pipecat.adapters.schemas.function_schema import FunctionSchema -from pipecat.adapters.schemas.tools_schema import ToolsSchema -from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3 -from pipecat.audio.vad.silero import SileroVADAnalyzer -from pipecat.audio.vad.vad_analyzer import VADParams -from pipecat.frames.frames import ( - CancelFrame, - EndFrame, - Frame, - FunctionCallInProgressFrame, - FunctionCallResultFrame, - InterruptionFrame, - LLMContextFrame, - LLMRunFrame, - StartFrame, - SystemFrame, - TextFrame, - TranscriptionFrame, - TTSSpeakFrame, - UserStartedSpeakingFrame, - UserStoppedSpeakingFrame, -) -from pipecat.pipeline.parallel_pipeline import ParallelPipeline -from pipecat.pipeline.pipeline import Pipeline -from pipecat.pipeline.runner import PipelineRunner -from pipecat.pipeline.task import PipelineParams, PipelineTask -from pipecat.processors.aggregators.llm_context import LLMContext -from pipecat.processors.aggregators.llm_response_universal import ( - LLMContextAggregatorPair, - LLMUserAggregatorParams, -) -from pipecat.processors.filters.function_filter import FunctionFilter -from pipecat.processors.frame_processor import FrameDirection, FrameProcessor -from pipecat.processors.user_idle_processor import UserIdleProcessor -from pipecat.runner.types import RunnerArguments -from pipecat.runner.utils import create_transport -from pipecat.services.cartesia.tts import CartesiaTTSService -from pipecat.services.deepgram.stt import DeepgramSTTService -from pipecat.services.llm_service import FunctionCallParams, LLMService -from pipecat.services.openai.llm import OpenAILLMService -from pipecat.transports.base_transport import BaseTransport, TransportParams -from pipecat.transports.daily.transport import DailyParams -from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams -from pipecat.turns.user_stop import TurnAnalyzerUserTurnStopStrategy -from pipecat.turns.user_turn_strategies import UserTurnStrategies -from pipecat.utils.sync.base_notifier import BaseNotifier -from pipecat.utils.sync.event_notifier import EventNotifier -from pipecat.utils.time import time_now_iso8601 - -load_dotenv(override=True) - - -classifier_statement = "Determine if the user's statement ends with a complete thought and you should respond. The user text is transcribed speech. It may contain multiple fragments concatentated together. You are trying to determine only the completeness of the last user statement. The previous assistant statement is provided only for context. Categorize the text as either complete with the user now expecting a response, or incomplete. Return 'YES' if text is likely complete and the user is expecting a response. Return 'NO' if the text seems to be a partial expression or unfinished thought." - - -class StatementJudgeContextFilter(FrameProcessor): - async def process_frame(self, frame: Frame, direction: FrameDirection): - await super().process_frame(frame, direction) - # We must not block system frames. - if isinstance(frame, SystemFrame): - await self.push_frame(frame, direction) - return - - # We only want to handle LLMContextFrames, and only want to push through a simplified - # context frame that contains a system prompt and the most recent user messages, - # concatenated. - if isinstance(frame, LLMContextFrame): - logger.debug(f"Context Frame: {frame}") - # Take text content from the most recent user messages. - messages = frame.context.get_messages() - user_text_messages = [] - last_assistant_message = None - for message in reversed(messages): - if message["role"] != "user": - if message["role"] == "assistant": - last_assistant_message = message - break - if isinstance(message["content"], str): - user_text_messages.append(message["content"]) - elif isinstance(message["content"], list): - for content in message["content"]: - if content["type"] == "text": - user_text_messages.insert(0, content["text"]) - # If we have any user text content, push a context frame with the simplified context. - if user_text_messages: - logger.debug(f"User text messages: {user_text_messages}") - user_message = " ".join(reversed(user_text_messages)) - logger.debug(f"User message: {user_message}") - messages = [ - { - "role": "system", - "content": classifier_statement, - } - ] - if last_assistant_message: - messages.append(last_assistant_message) - messages.append({"role": "user", "content": user_message}) - await self.push_frame(LLMContextFrame(LLMContext(messages))) - - -class CompletenessCheck(FrameProcessor): - def __init__(self, notifier: BaseNotifier): - super().__init__() - self._notifier = notifier - - async def process_frame(self, frame: Frame, direction: FrameDirection): - await super().process_frame(frame, direction) - - if isinstance(frame, TextFrame) and frame.text == "YES": - logger.debug("Completeness check YES") - await self.broadcast_frame(UserStoppedSpeakingFrame) - await self._notifier.notify() - elif isinstance(frame, TextFrame) and frame.text == "NO": - logger.debug("Completeness check NO") - else: - await self.push_frame(frame, direction) - - -class OutputGate(FrameProcessor): - def __init__(self, *, notifier: BaseNotifier, start_open: bool = False, **kwargs): - super().__init__(**kwargs) - self._gate_open = start_open - self._frames_buffer = [] - self._notifier = notifier - self._gate_task = None - - def close_gate(self): - self._gate_open = False - - def open_gate(self): - self._gate_open = True - - async def process_frame(self, frame: Frame, direction: FrameDirection): - await super().process_frame(frame, direction) - - # We must not block system frames. - if isinstance(frame, SystemFrame): - if isinstance(frame, StartFrame): - await self._start() - if isinstance(frame, (EndFrame, CancelFrame)): - await self._stop() - if isinstance(frame, InterruptionFrame): - self._frames_buffer = [] - self.close_gate() - await self.push_frame(frame, direction) - return - - # Don't block function call frames - if isinstance(frame, (FunctionCallInProgressFrame, FunctionCallResultFrame)): - await self.push_frame(frame, direction) - return - - # Ignore frames that are not following the direction of this gate. - if direction != FrameDirection.DOWNSTREAM: - await self.push_frame(frame, direction) - return - - if self._gate_open: - await self.push_frame(frame, direction) - return - - self._frames_buffer.append((frame, direction)) - - async def _start(self): - self._frames_buffer = [] - if not self._gate_task: - self._gate_task = self.create_task(self._gate_task_handler()) - - async def _stop(self): - if self._gate_task: - await self.cancel_task(self._gate_task) - self._gate_task = None - - async def _gate_task_handler(self): - while True: - try: - await self._notifier.wait() - self.open_gate() - for frame, direction in self._frames_buffer: - await self.push_frame(frame, direction) - self._frames_buffer = [] - except asyncio.CancelledError: - break - - -async def fetch_weather_from_api(params: FunctionCallParams): - await params.result_callback({"conditions": "nice", "temperature": "75"}) - - -class TurnDetectionLLM(Pipeline): - def __init__(self, llm: LLMService): - # This is the LLM that will be used to detect if the user has finished a - # statement. This doesn't really need to be an LLM, we could use NLP - # libraries for that, but we have the machinery to use an LLM, so we - # might as well! - statement_llm = OpenAILLMService(api_key=os.getenv("OPENAI_API_KEY")) - - # We have instructed the LLM to return 'YES' if it thinks the user - # completed a sentence. So, if it's 'YES' we will return true in this - # predicate which will wake up the notifier. - async def wake_check_filter(frame): - logger.debug(f"Completeness check frame: {frame}") - return frame.text == "YES" - - # This is a notifier that we use to synchronize the two LLMs. - notifier = EventNotifier() - - # This turns the LLM context into an inference request to classify the user's speech - # as complete or incomplete. - statement_judge_context_filter = StatementJudgeContextFilter() - - # This sends a UserStoppedSpeakingFrame and triggers the notifier event - completeness_check = CompletenessCheck(notifier=notifier) - - # # Notify if the user hasn't said anything. - async def user_idle_notifier(frame): - await notifier.notify() - - # Sometimes the LLM will fail detecting if a user has completed a - # sentence, this will wake up the notifier if that happens. - user_idle = UserIdleProcessor(callback=user_idle_notifier, timeout=5.0) - - # We start with the gate open because we send an initial context frame - # to start the conversation. - bot_output_gate = OutputGate(notifier=notifier, start_open=True) - - async def pass_only_llm_trigger_frames(frame): - return ( - isinstance(frame, LLMContextFrame) - or isinstance(frame, InterruptionFrame) - or isinstance(frame, FunctionCallInProgressFrame) - or isinstance(frame, FunctionCallResultFrame) - ) - - async def filter_all(frame): - return False - - super().__init__( - [ - ParallelPipeline( - [ - # Ignore everything except an LLMContextFrame. Pass a specially constructed - # simplified context frame to the statement classifier LLM. The only frame this - # sub-pipeline will output is a UserStoppedSpeakingFrame. - statement_judge_context_filter, - statement_llm, - completeness_check, - FunctionFilter(filter=filter_all, direction=FrameDirection.UPSTREAM), - ], - [ - # Block everything except frames that trigger LLM inference. - FunctionFilter(filter=pass_only_llm_trigger_frames), - llm, - bot_output_gate, # Buffer all llm/tts output until notified. - ], - ), - user_idle, - ] - ) - - -# We use lambdas to defer transport parameter creation until the transport -# type is selected at runtime. -transport_params = { - "daily": lambda: DailyParams( - audio_in_enabled=True, - audio_out_enabled=True, - ), - "twilio": lambda: FastAPIWebsocketParams( - audio_in_enabled=True, - audio_out_enabled=True, - ), - "webrtc": lambda: TransportParams( - audio_in_enabled=True, - audio_out_enabled=True, - ), -} - - -async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): - logger.info(f"Starting bot") - - stt = DeepgramSTTService(api_key=os.getenv("DEEPGRAM_API_KEY")) - - tts = CartesiaTTSService( - api_key=os.getenv("CARTESIA_API_KEY"), - voice_id="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady - ) - - # This is the regular LLM. - llm_main = OpenAILLMService(api_key=os.getenv("OPENAI_API_KEY")) - # You can also register a function_name of None to get all functions - # sent to the same callback with an additional function_name parameter. - llm_main.register_function("get_current_weather", fetch_weather_from_api) - - @llm_main.event_handler("on_function_calls_started") - async def on_function_calls_started(service, function_calls): - await tts.queue_frame(TTSSpeakFrame("Let me check on that.")) - - weather_function = FunctionSchema( - name="get_current_weather", - description="Get the current weather", - properties={ - "location": { - "type": "string", - "description": "The city and state, e.g. San Francisco, CA", - }, - "format": { - "type": "string", - "enum": ["celsius", "fahrenheit"], - "description": "The temperature unit to use. Infer this from the users location.", - }, - }, - required=["location", "format"], - ) - tools = ToolsSchema(standard_tools=[weather_function]) - - messages = [ - { - "role": "system", - "content": "You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", - }, - ] - - context = LLMContext(messages, tools) - user_aggregator, assistant_aggregator = LLMContextAggregatorPair( - context, - user_params=LLMUserAggregatorParams( - user_turn_strategies=UserTurnStrategies( - stop=[TurnAnalyzerUserTurnStopStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3())] - ), - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), - ), - ) - - # LLM + turn detection (with an extra LLM as a judge) - llm = TurnDetectionLLM(llm_main) - - pipeline = Pipeline( - [ - transport.input(), - stt, - user_aggregator, - llm, - tts, - transport.output(), - assistant_aggregator, - ] - ) - - task = PipelineTask( - pipeline, - params=PipelineParams( - enable_metrics=True, - enable_usage_metrics=True, - ), - idle_timeout_secs=runner_args.pipeline_idle_timeout_secs, - ) - - @transport.event_handler("on_client_connected") - async def on_client_connected(transport, client): - logger.info(f"Client connected") - # Kick off the conversation. - messages.append({"role": "system", "content": "Please introduce yourself to the user."}) - await task.queue_frames([LLMRunFrame()]) - - @transport.event_handler("on_app_message") - async def on_app_message(transport, message, sender): - logger.debug(f"Received app message: {message}") - if "message" not in message: - return - - await task.queue_frames( - [ - UserStartedSpeakingFrame(), - TranscriptionFrame( - user_id="", timestamp=time_now_iso8601(), text=message["message"] - ), - UserStoppedSpeakingFrame(), - ] - ) - - @transport.event_handler("on_client_disconnected") - async def on_client_disconnected(transport, client): - logger.info(f"Client disconnected") - await task.cancel() - - runner = PipelineRunner(handle_sigint=runner_args.handle_sigint) - - await runner.run(task) - - -async def bot(runner_args: RunnerArguments): - """Main bot entry point compatible with Pipecat Cloud.""" - transport = await create_transport(runner_args, transport_params) - await run_bot(transport, runner_args) - - -if __name__ == "__main__": - from pipecat.runner.run import main - - main() diff --git a/examples/foundational/22c-natural-conversation-mixed-llms.py b/examples/foundational/22c-natural-conversation-mixed-llms.py deleted file mode 100644 index e7565ffbe..000000000 --- a/examples/foundational/22c-natural-conversation-mixed-llms.py +++ /dev/null @@ -1,622 +0,0 @@ -# -# Copyright (c) 2024-2026, Daily -# -# SPDX-License-Identifier: BSD 2-Clause License -# - -import asyncio -import os - -from dotenv import load_dotenv -from loguru import logger - -from pipecat.adapters.schemas.function_schema import FunctionSchema -from pipecat.adapters.schemas.tools_schema import ToolsSchema -from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3 -from pipecat.audio.vad.silero import SileroVADAnalyzer -from pipecat.audio.vad.vad_analyzer import VADParams -from pipecat.frames.frames import ( - CancelFrame, - EndFrame, - Frame, - FunctionCallInProgressFrame, - FunctionCallResultFrame, - InterruptionFrame, - LLMContextFrame, - LLMRunFrame, - StartFrame, - SystemFrame, - TextFrame, - TranscriptionFrame, - TTSSpeakFrame, - UserStartedSpeakingFrame, - UserStoppedSpeakingFrame, -) -from pipecat.pipeline.parallel_pipeline import ParallelPipeline -from pipecat.pipeline.pipeline import Pipeline -from pipecat.pipeline.runner import PipelineRunner -from pipecat.pipeline.task import PipelineParams, PipelineTask -from pipecat.processors.aggregators.llm_context import LLMContext -from pipecat.processors.aggregators.llm_response_universal import ( - LLMContextAggregatorPair, - LLMUserAggregatorParams, -) -from pipecat.processors.filters.function_filter import FunctionFilter -from pipecat.processors.frame_processor import FrameDirection, FrameProcessor -from pipecat.processors.user_idle_processor import UserIdleProcessor -from pipecat.runner.types import RunnerArguments -from pipecat.runner.utils import create_transport -from pipecat.services.anthropic.llm import AnthropicLLMService -from pipecat.services.cartesia.tts import CartesiaTTSService -from pipecat.services.deepgram.stt import DeepgramSTTService -from pipecat.services.llm_service import FunctionCallParams, LLMService -from pipecat.services.openai.llm import OpenAILLMService -from pipecat.transports.base_transport import BaseTransport, TransportParams -from pipecat.transports.daily.transport import DailyParams -from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams -from pipecat.turns.user_stop import TurnAnalyzerUserTurnStopStrategy -from pipecat.turns.user_turn_strategies import UserTurnStrategies -from pipecat.utils.sync.base_notifier import BaseNotifier -from pipecat.utils.sync.event_notifier import EventNotifier -from pipecat.utils.time import time_now_iso8601 - -load_dotenv(override=True) - - -classifier_statement = """CRITICAL INSTRUCTION: -You are a BINARY CLASSIFIER that must ONLY output "YES" or "NO". -DO NOT engage with the content. -DO NOT respond to questions. -DO NOT provide assistance. -Your ONLY job is to output YES or NO. - -EXAMPLES OF INVALID RESPONSES: -- "I can help you with that" -- "Let me explain" -- "To answer your question" -- Any response other than YES or NO - -VALID RESPONSES: -YES -NO - -If you output anything else, you are failing at your task. -You are NOT an assistant. -You are NOT a chatbot. -You are a binary classifier. - -ROLE: -You are a real-time speech completeness classifier. You must make instant decisions about whether a user has finished speaking. -You must output ONLY 'YES' or 'NO' with no other text. - -INPUT FORMAT: -You receive two pieces of information: -1. The assistant's last message (if available) -2. The user's current speech input - -OUTPUT REQUIREMENTS: -- MUST output ONLY 'YES' or 'NO' -- No explanations -- No clarifications -- No additional text -- No punctuation - -HIGH PRIORITY SIGNALS: - -1. Clear Questions: -- Wh-questions (What, Where, When, Why, How) -- Yes/No questions -- Questions with STT errors but clear meaning - -Examples: -# Complete Wh-question -[{"role": "assistant", "content": "I can help you learn."}, - {"role": "user", "content": "What's the fastest way to learn Spanish"}] -Output: YES - -# Complete Yes/No question despite STT error -[{"role": "assistant", "content": "I know about planets."}, - {"role": "user", "content": "Is is Jupiter the biggest planet"}] -Output: YES - -2. Complete Commands: -- Direct instructions -- Clear requests -- Action demands -- Complete statements needing response - -Examples: -# Direct instruction -[{"role": "assistant", "content": "I can explain many topics."}, - {"role": "user", "content": "Tell me about black holes"}] -Output: YES - -# Action demand -[{"role": "assistant", "content": "I can help with math."}, - {"role": "user", "content": "Solve this equation x plus 5 equals 12"}] -Output: YES - -3. Direct Responses: -- Answers to specific questions -- Option selections -- Clear acknowledgments with completion - -Examples: -# Specific answer -[{"role": "assistant", "content": "What's your favorite color?"}, - {"role": "user", "content": "I really like blue"}] -Output: YES - -# Option selection -[{"role": "assistant", "content": "Would you prefer morning or evening?"}, - {"role": "user", "content": "Morning"}] -Output: YES - -MEDIUM PRIORITY SIGNALS: - -1. Speech Pattern Completions: -- Self-corrections reaching completion -- False starts with clear ending -- Topic changes with complete thought -- Mid-sentence completions - -Examples: -# Self-correction reaching completion -[{"role": "assistant", "content": "What would you like to know?"}, - {"role": "user", "content": "Tell me about... no wait, explain how rainbows form"}] -Output: YES - -# Topic change with complete thought -[{"role": "assistant", "content": "The weather is nice today."}, - {"role": "user", "content": "Actually can you tell me who invented the telephone"}] -Output: YES - -# Mid-sentence completion -[{"role": "assistant", "content": "Hello I'm ready."}, - {"role": "user", "content": "What's the capital of? France"}] -Output: YES - -2. Context-Dependent Brief Responses: -- Acknowledgments (okay, sure, alright) -- Agreements (yes, yeah) -- Disagreements (no, nah) -- Confirmations (correct, exactly) - -Examples: -# Acknowledgment -[{"role": "assistant", "content": "Should we talk about history?"}, - {"role": "user", "content": "Sure"}] -Output: YES - -# Disagreement with completion -[{"role": "assistant", "content": "Is that what you meant?"}, - {"role": "user", "content": "No not really"}] -Output: YES - -LOW PRIORITY SIGNALS: - -1. STT Artifacts (Consider but don't over-weight): -- Repeated words -- Unusual punctuation -- Capitalization errors -- Word insertions/deletions - -Examples: -# Word repetition but complete -[{"role": "assistant", "content": "I can help with that."}, - {"role": "user", "content": "What what is the time right now"}] -Output: YES - -# Missing punctuation but complete -[{"role": "assistant", "content": "I can explain that."}, - {"role": "user", "content": "Please tell me how computers work"}] -Output: YES - -2. Speech Features: -- Filler words (um, uh, like) -- Thinking pauses -- Word repetitions -- Brief hesitations - -Examples: -# Filler words but complete -[{"role": "assistant", "content": "What would you like to know?"}, - {"role": "user", "content": "Um uh how do airplanes fly"}] -Output: YES - -# Thinking pause but incomplete -[{"role": "assistant", "content": "I can explain anything."}, - {"role": "user", "content": "Well um I want to know about the"}] -Output: NO - -DECISION RULES: - -1. Return YES if: -- ANY high priority signal shows clear completion -- Medium priority signals combine to show completion -- Meaning is clear despite low priority artifacts - -2. Return NO if: -- No high priority signals present -- Thought clearly trails off -- Multiple incomplete indicators -- User appears mid-formulation - -3. When uncertain: -- If you can understand the intent → YES -- If meaning is unclear → NO -- Always make a binary decision -- Never request clarification - -Examples: -# Incomplete despite corrections -[{"role": "assistant", "content": "What would you like to know about?"}, - {"role": "user", "content": "Can you tell me about"}] -Output: NO - -# Complete despite multiple artifacts -[{"role": "assistant", "content": "I can help you learn."}, - {"role": "user", "content": "How do you I mean what's the best way to learn programming"}] -Output: YES - -# Trailing off incomplete -[{"role": "assistant", "content": "I can explain anything."}, - {"role": "user", "content": "I was wondering if you could tell me why"}] -Output: NO -""" - -conversational_system_message = """You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way. - -Please be very concise in your responses. Unless you are explicitly asked to do otherwise, give me the shortest complete answer possible without unnecessary elaboration. Generally you should answer with a single sentence. -""" - - -class StatementJudgeContextFilter(FrameProcessor): - async def process_frame(self, frame: Frame, direction: FrameDirection): - await super().process_frame(frame, direction) - # We must not block system frames. - if isinstance(frame, SystemFrame): - await self.push_frame(frame, direction) - return - - # We only want to handle LLMContextFrames, and only want to push through a simplified - # context frame that contains a system prompt and the most recent user messages, - if isinstance(frame, LLMContextFrame): - # Take text content from the most recent user messages. - messages = frame.context.get_messages() - user_text_messages = [] - last_assistant_message = None - for message in reversed(messages): - if message["role"] != "user": - if message["role"] == "assistant": - last_assistant_message = message - break - if isinstance(message["content"], str): - user_text_messages.append(message["content"]) - elif isinstance(message["content"], list): - for content in message["content"]: - if content["type"] == "text": - user_text_messages.insert(0, content["text"]) - # If we have any user text content, push a context frame with the simplified context. - if user_text_messages: - user_message = " ".join(reversed(user_text_messages)) - logger.debug(f"!!! {user_message}") - messages = [ - { - "role": "system", - "content": classifier_statement, - } - ] - if last_assistant_message: - messages.append(last_assistant_message) - messages.append({"role": "user", "content": user_message}) - await self.push_frame(LLMContextFrame(LLMContext(messages))) - - -class CompletenessCheck(FrameProcessor): - def __init__(self, notifier: BaseNotifier): - super().__init__() - self._notifier = notifier - - async def process_frame(self, frame: Frame, direction: FrameDirection): - await super().process_frame(frame, direction) - - if isinstance(frame, TextFrame) and frame.text == "YES": - logger.debug("!!! Completeness check YES") - await self.broadcast_frame(UserStoppedSpeakingFrame) - await self._notifier.notify() - elif isinstance(frame, TextFrame) and frame.text == "NO": - logger.debug("!!! Completeness check NO") - else: - await self.push_frame(frame, direction) - - -class OutputGate(FrameProcessor): - def __init__(self, *, notifier: BaseNotifier, start_open: bool = False, **kwargs): - super().__init__(**kwargs) - self._gate_open = start_open - self._frames_buffer = [] - self._notifier = notifier - self._gate_task = None - - def close_gate(self): - self._gate_open = False - - def open_gate(self): - self._gate_open = True - - async def process_frame(self, frame: Frame, direction: FrameDirection): - await super().process_frame(frame, direction) - - # We must not block system frames. - if isinstance(frame, SystemFrame): - if isinstance(frame, StartFrame): - await self._start() - if isinstance(frame, (EndFrame, CancelFrame)): - await self._stop() - if isinstance(frame, InterruptionFrame): - self._frames_buffer = [] - self.close_gate() - await self.push_frame(frame, direction) - return - - # Don't block function call frames - if isinstance(frame, (FunctionCallInProgressFrame, FunctionCallResultFrame)): - await self.push_frame(frame, direction) - return - - # Ignore frames that are not following the direction of this gate. - if direction != FrameDirection.DOWNSTREAM: - await self.push_frame(frame, direction) - return - - if self._gate_open: - await self.push_frame(frame, direction) - return - - self._frames_buffer.append((frame, direction)) - - async def _start(self): - self._frames_buffer = [] - if not self._gate_task: - self._gate_task = self.create_task(self._gate_task_handler()) - - async def _stop(self): - if self._gate_task: - await self.cancel_task(self._gate_task) - self._gate_task = None - - async def _gate_task_handler(self): - while True: - try: - await self._notifier.wait() - self.open_gate() - for frame, direction in self._frames_buffer: - await self.push_frame(frame, direction) - self._frames_buffer = [] - except asyncio.CancelledError: - break - - -class TurnDetectionLLM(Pipeline): - def __init__(self, llm: LLMService): - # This is the LLM that will be used to detect if the user has finished a - # statement. This doesn't really need to be an LLM, we could use NLP - # libraries for that, but we have the machinery to use an LLM, so we might as well! - statement_llm = AnthropicLLMService(api_key=os.getenv("ANTHROPIC_API_KEY")) - - # This is a notifier that we use to synchronize the two LLMs. - notifier = EventNotifier() - - # This turns the LLM context into an inference request to classify the user's speech - # as complete or incomplete. - statement_judge_context_filter = StatementJudgeContextFilter() - - # This sends a UserStoppedSpeakingFrame and triggers the notifier event - completeness_check = CompletenessCheck(notifier=notifier) - - # # Notify if the user hasn't said anything. - async def user_idle_notifier(frame): - await notifier.notify() - - # Sometimes the LLM will fail detecting if a user has completed a - # sentence, this will wake up the notifier if that happens. - user_idle = UserIdleProcessor(callback=user_idle_notifier, timeout=5.0) - - # We start with the gate open because we send an initial context frame - # to start the conversation. - bot_output_gate = OutputGate(notifier=notifier, start_open=True) - - async def block_user_stopped_speaking(frame): - return not isinstance(frame, UserStoppedSpeakingFrame) - - async def pass_only_llm_trigger_frames(frame): - return ( - isinstance(frame, LLMContextFrame) - or isinstance(frame, InterruptionFrame) - or isinstance(frame, FunctionCallInProgressFrame) - or isinstance(frame, FunctionCallResultFrame) - ) - - async def filter_all(frame): - return False - - super().__init__( - [ - ParallelPipeline( - [ - # Pass everything except UserStoppedSpeaking to the elements after - # this ParallelPipeline - FunctionFilter(filter=block_user_stopped_speaking), - ], - [ - # Ignore everything except an LLMContextFrame. Pass a specially constructed - # simplified context frame to the statement classifier LLM. The only frame this - # sub-pipeline will output is a UserStoppedSpeakingFrame. - statement_judge_context_filter, - statement_llm, - completeness_check, - FunctionFilter(filter=filter_all, direction=FrameDirection.UPSTREAM), - ], - [ - # Block everything except frames that trigger LLM inference. - FunctionFilter(filter=pass_only_llm_trigger_frames), - llm, - bot_output_gate, # Buffer all llm/tts output until notified. - ], - ), - user_idle, - ] - ) - - -async def fetch_weather_from_api(params: FunctionCallParams): - await params.result_callback({"conditions": "nice", "temperature": "75"}) - - -# We use lambdas to defer transport parameter creation until the transport -# type is selected at runtime. -transport_params = { - "daily": lambda: DailyParams( - audio_in_enabled=True, - audio_out_enabled=True, - ), - "twilio": lambda: FastAPIWebsocketParams( - audio_in_enabled=True, - audio_out_enabled=True, - ), - "webrtc": lambda: TransportParams( - audio_in_enabled=True, - audio_out_enabled=True, - ), -} - - -async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): - logger.info(f"Starting bot") - - stt = DeepgramSTTService(api_key=os.getenv("DEEPGRAM_API_KEY")) - - tts = CartesiaTTSService( - api_key=os.getenv("CARTESIA_API_KEY"), - voice_id="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady - ) - - # This is the regular LLM. - llm_main = OpenAILLMService(api_key=os.getenv("OPENAI_API_KEY")) - # Register a function_name of None to get all functions - # sent to the same callback with an additional function_name parameter. - llm_main.register_function("get_current_weather", fetch_weather_from_api) - - @llm_main.event_handler("on_function_calls_started") - async def on_function_calls_started(service, function_calls): - await tts.queue_frame(TTSSpeakFrame("Let me check on that.")) - - weather_function = FunctionSchema( - name="get_current_weather", - description="Get the current weather", - properties={ - "location": { - "type": "string", - "description": "The city and state, e.g. San Francisco, CA", - }, - "format": { - "type": "string", - "enum": ["celsius", "fahrenheit"], - "description": "The temperature unit to use. Infer this from the users location.", - }, - }, - required=["location", "format"], - ) - tools = ToolsSchema(standard_tools=[weather_function]) - - messages = [ - { - "role": "system", - "content": conversational_system_message, - }, - ] - - context = LLMContext(messages, tools) - user_aggregator, assistant_aggregator = LLMContextAggregatorPair( - context, - user_params=LLMUserAggregatorParams( - user_turn_strategies=UserTurnStrategies( - stop=[TurnAnalyzerUserTurnStopStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3())] - ), - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), - ), - ) - - # LLM + turn detection (with an extra LLM as a judge) - llm = TurnDetectionLLM(llm_main) - - pipeline = Pipeline( - [ - transport.input(), - stt, - user_aggregator, - llm, - tts, - transport.output(), - assistant_aggregator, - ] - ) - - task = PipelineTask( - pipeline, - params=PipelineParams( - enable_metrics=True, - enable_usage_metrics=True, - ), - idle_timeout_secs=runner_args.pipeline_idle_timeout_secs, - ) - - @transport.event_handler("on_client_connected") - async def on_client_connected(transport, client): - logger.info(f"Client connected") - # Kick off the conversation. - messages.append( - { - "role": "user", - "content": "Start by just saying \"Hello I'm ready.\" Don't say anything else.", - } - ) - await task.queue_frames([LLMRunFrame()]) - - @transport.event_handler("on_app_message") - async def on_app_message(transport, message, sender): - logger.debug(f"Received app message: {message}") - if "message" not in message: - return - - await task.queue_frames( - [ - UserStartedSpeakingFrame(), - TranscriptionFrame( - user_id="", timestamp=time_now_iso8601(), text=message["message"] - ), - UserStoppedSpeakingFrame(), - ] - ) - - @transport.event_handler("on_client_disconnected") - async def on_client_disconnected(transport, client): - logger.info(f"Client disconnected") - await task.cancel() - - runner = PipelineRunner(handle_sigint=runner_args.handle_sigint) - - await runner.run(task) - - -async def bot(runner_args: RunnerArguments): - """Main bot entry point compatible with Pipecat Cloud.""" - transport = await create_transport(runner_args, transport_params) - await run_bot(transport, runner_args) - - -if __name__ == "__main__": - from pipecat.runner.run import main - - main() diff --git a/examples/foundational/22d-natural-conversation-gemini-audio.py b/examples/foundational/22d-natural-conversation-gemini-audio.py deleted file mode 100644 index 2ff1172f3..000000000 --- a/examples/foundational/22d-natural-conversation-gemini-audio.py +++ /dev/null @@ -1,813 +0,0 @@ -# -# Copyright (c) 2024-2026, Daily -# -# SPDX-License-Identifier: BSD 2-Clause License -# - -import asyncio -import os -import time - -from dotenv import load_dotenv -from loguru import logger - -from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3 -from pipecat.audio.vad.silero import SileroVADAnalyzer -from pipecat.audio.vad.vad_analyzer import VADParams -from pipecat.frames.frames import ( - CancelFrame, - EndFrame, - Frame, - FunctionCallInProgressFrame, - FunctionCallResultFrame, - InputAudioRawFrame, - InterruptionFrame, - LLMContextFrame, - LLMFullResponseStartFrame, - StartFrame, - SystemFrame, - TextFrame, - TranscriptionFrame, - UserStartedSpeakingFrame, - UserStoppedSpeakingFrame, -) -from pipecat.pipeline.parallel_pipeline import ParallelPipeline -from pipecat.pipeline.pipeline import Pipeline -from pipecat.pipeline.runner import PipelineRunner -from pipecat.pipeline.task import PipelineParams, PipelineTask -from pipecat.processors.aggregators.llm_context import LLMContext -from pipecat.processors.aggregators.llm_response import ( - LLMAssistantAggregatorParams, - LLMAssistantResponseAggregator, -) -from pipecat.processors.aggregators.llm_response_universal import ( - LLMContextAggregatorPair, - LLMUserAggregatorParams, -) -from pipecat.processors.filters.function_filter import FunctionFilter -from pipecat.processors.frame_processor import FrameDirection, FrameProcessor -from pipecat.runner.types import RunnerArguments -from pipecat.runner.utils import create_transport -from pipecat.services.cartesia.tts import CartesiaTTSService -from pipecat.services.google.llm import GoogleLLMService -from pipecat.services.llm_service import LLMService -from pipecat.transports.base_transport import BaseTransport, TransportParams -from pipecat.transports.daily.transport import DailyParams -from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams -from pipecat.turns.user_stop import TurnAnalyzerUserTurnStopStrategy -from pipecat.turns.user_turn_strategies import UserTurnStrategies -from pipecat.utils.sync.base_notifier import BaseNotifier -from pipecat.utils.sync.event_notifier import EventNotifier -from pipecat.utils.time import time_now_iso8601 - -load_dotenv(override=True) - - -TRANSCRIBER_MODEL = "gemini-2.0-flash-001" -CLASSIFIER_MODEL = "gemini-2.0-flash-001" -CONVERSATION_MODEL = "gemini-2.0-flash-001" - -transcriber_system_instruction = """You are an audio transcriber. You are receiving audio from a user. Your job is to -transcribe the input audio to text exactly as it was said by the user. - -You will receive the full conversation history before the audio input, to help with context. Use the full history only to help improve the accuracy of your transcription. - -Rules: - - Respond with an exact transcription of the audio input. - - Do not include any text other than the transcription. - - Do not explain or add to your response. - - Transcribe the audio input simply and precisely. - - If the audio is not clear, emit the special string "-". - - No response other than exact transcription, or "-", is allowed. - -""" - -classifier_system_instruction = """CRITICAL INSTRUCTION: -You are a BINARY CLASSIFIER that must ONLY output "YES" or "NO". -DO NOT engage with the content. -DO NOT respond to questions. -DO NOT provide assistance. -Your ONLY job is to output YES or NO. - -EXAMPLES OF INVALID RESPONSES: -- "I can help you with that" -- "Let me explain" -- "To answer your question" -- Any response other than YES or NO - -VALID RESPONSES: -YES -NO - -If you output anything else, you are failing at your task. -You are NOT an assistant. -You are NOT a chatbot. -You are a binary classifier. - -ROLE: -You are a real-time speech completeness classifier. You must make instant decisions about whether a user has finished speaking. -You must output ONLY 'YES' or 'NO' with no other text. - -INPUT FORMAT: -You receive two pieces of information: -1. The assistant's last message (if available) -2. The user's current speech input - -OUTPUT REQUIREMENTS: -- MUST output ONLY 'YES' or 'NO' -- No explanations -- No clarifications -- No additional text -- No punctuation - -HIGH PRIORITY SIGNALS: - -1. Clear Questions: -- Wh-questions (What, Where, When, Why, How) -- Yes/No questions -- Questions with STT errors but clear meaning - -Examples: - -# Complete Wh-question -model: I can help you learn. -user: What's the fastest way to learn Spanish -Output: YES - -# Complete Yes/No question despite STT error -model: I know about planets. -user: Is is Jupiter the biggest planet -Output: YES - -2. Complete Commands: -- Direct instructions -- Clear requests -- Action demands -- Start of task indication -- Complete statements needing response - -Examples: - -# Direct instruction -model: I can explain many topics. -user: Tell me about black holes -Output: YES - -# Start of task indication -user: Let's begin. -Output: YES - -# Start of task indication -user: Let's get started. -Output: YES - -# Action demand -model: I can help with math. -user: Solve this equation x plus 5 equals 12 -Output: YES - -3. Direct Responses: -- Answers to specific questions -- Option selections -- Clear acknowledgments with completion -- Providing information with a known format - mailing address -- Providing information with a known format - phone number -- Providing information with a known format - credit card number - -Examples: - -# Specific answer -model: What's your favorite color? -user: I really like blue -Output: YES - -# Option selection -model: Would you prefer morning or evening? -user: Morning -Output: YES - -# Providing information with a known format - mailing address -model: What's your address? -user: 1234 Main Street -Output: NO - -# Providing information with a known format - mailing address -model: What's your address? -user: 1234 Main Street Irving Texas 75063 -Output: Yes - -# Providing information with a known format - phone number -model: What's your phone number? -user: 41086753 -Output: NO - -# Providing information with a known format - phone number -model: What's your phone number? -user: 4108675309 -Output: Yes - -# Providing information with a known format - phone number -model: What's your phone number? -user: 220 -Output: No - -# Providing information with a known format - credit card number -model: What's your credit card number? -user: 5556 -Output: NO - -# Providing information with a known format - phone number -model: What's your credit card number? -user: 5556710454680800 -Output: Yes - -model: What's your credit card number? -user: 414067 -Output: NO - - -MEDIUM PRIORITY SIGNALS: - -1. Speech Pattern Completions: -- Self-corrections reaching completion -- False starts with clear ending -- Topic changes with complete thought -- Mid-sentence completions - -Examples: - -# Self-correction reaching completion -model: What would you like to know? -user: Tell me about... no wait, explain how rainbows form -Output: YES - -# Topic change with complete thought -model: The weather is nice today. -user: Actually can you tell me who invented the telephone -Output: YES - -# Mid-sentence completion -model: Hello I'm ready. -user: What's the capital of? France -Output: YES - -2. Context-Dependent Brief Responses: -- Acknowledgments (okay, sure, alright) -- Agreements (yes, yeah) -- Disagreements (no, nah) -- Confirmations (correct, exactly) - -Examples: - -# Acknowledgment -model: Should we talk about history? -user: Sure -Output: YES - -# Disagreement with completion -model: Is that what you meant? -user: No not really -Output: YES - -LOW PRIORITY SIGNALS: - -1. STT Artifacts (Consider but don't over-weight): -- Repeated words -- Unusual punctuation -- Capitalization errors -- Word insertions/deletions - -Examples: - -# Word repetition but complete -model: I can help with that. -user: What what is the time right now -Output: YES - -# Missing punctuation but complete -model: I can explain that. -user: Please tell me how computers work -Output: YES - -2. Speech Features: -- Filler words (um, uh, like) -- Thinking pauses -- Word repetitions -- Brief hesitations - -Examples: - -# Filler words but complete -model: What would you like to know? -user: Um uh how do airplanes fly -Output: YES - -# Thinking pause but incomplete -model: I can explain anything. -user: Well um I want to know about the -Output: NO - -DECISION RULES: - -1. Return YES if: -- ANY high priority signal shows clear completion -- Medium priority signals combine to show completion -- Meaning is clear despite low priority artifacts - -2. Return NO if: -- No high priority signals present -- Thought clearly trails off -- Multiple incomplete indicators -- User appears mid-formulation - -3. When uncertain: -- If you can understand the intent → YES -- If meaning is unclear → NO -- Always make a binary decision -- Never request clarification - -Examples: - -# Incomplete despite corrections -model: What would you like to know about? -user: Can you tell me about -Output: NO - -# Complete despite multiple artifacts -model: I can help you learn. -user: How do you I mean what's the best way to learn programming -Output: YES - -# Trailing off incomplete -model: I can explain anything. -user: I was wondering if you could tell me why -Output: NO -""" - -conversation_system_instruction = """You are a helpful assistant participating in a voice converation. - -Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way. - -If you know that a number string is a phone number from the context of the conversation, write it as a phone number. For example 210-333-4567. - -If you know that a number string is a credit card number, write it as a credit card number. For example 4111-1111-1111-1111. - -Please be very concise in your responses. Unless you are explicitly asked to do otherwise, give me shortest complete answer possible without unnecessary elaboration. Generally you should answer with a single sentence. -""" - - -class AudioAccumulator(FrameProcessor): - """Buffers user audio until the user stops speaking. - - Always pushes a fresh context with a single audio message. - """ - - def __init__(self, **kwargs): - super().__init__(**kwargs) - self._audio_frames = [] - self._start_secs = 0.2 # this should match VAD start_secs (hardcoding for now) - self._max_buffer_size_secs = 30 - self._user_speaking_vad_state = False - self._user_speaking_utterance_state = False - - async def reset(self): - self._audio_frames = [] - self._user_speaking_vad_state = False - self._user_speaking_utterance_state = False - - async def process_frame(self, frame: Frame, direction: FrameDirection): - await super().process_frame(frame, direction) - - # ignore context frame - if isinstance(frame, LLMContextFrame): - return - - if isinstance(frame, TranscriptionFrame): - # We could gracefully handle both audio input and text/transcription input ... - # but let's leave that as an exercise to the reader. :-) - return - if isinstance(frame, UserStartedSpeakingFrame): - self._user_speaking_vad_state = True - self._user_speaking_utterance_state = True - - elif isinstance(frame, UserStoppedSpeakingFrame): - data = b"".join(frame.audio for frame in self._audio_frames) - logger.debug( - f"Processing audio buffer seconds: ({len(self._audio_frames)}) ({len(data)}) {len(data) / 2 / 16000}" - ) - self._user_speaking = False - context = LLMContext() - await context.add_audio_frames_message(audio_frames=self._audio_frames) - await self.push_frame(LLMContextFrame(context=context)) - elif isinstance(frame, InputAudioRawFrame): - # Append the audio frame to our buffer. Treat the buffer as a ring buffer, dropping the oldest - # frames as necessary. - # Use a small buffer size when an utterance is not in progress. Just big enough to backfill the start_secs. - # Use a larger buffer size when an utterance is in progress. - # Assume all audio frames have the same duration. - self._audio_frames.append(frame) - frame_duration = len(frame.audio) / 2 * frame.num_channels / frame.sample_rate - buffer_duration = frame_duration * len(self._audio_frames) - # logger.debug(f"!!! Frame duration: {frame_duration}") - if self._user_speaking_utterance_state: - while buffer_duration > self._max_buffer_size_secs: - self._audio_frames.pop(0) - buffer_duration -= frame_duration - else: - while buffer_duration > self._start_secs: - self._audio_frames.pop(0) - buffer_duration -= frame_duration - - await self.push_frame(frame, direction) - - -class CompletenessCheck(FrameProcessor): - """Checks the result of the classifier LLM to determine if the user has finished speaking. - - Triggers the notifier if the user has finished speaking. Also triggers the notifier if an - idle timeout is reached. - """ - - wait_time = 5.0 - - def __init__(self, notifier: BaseNotifier, audio_accumulator: AudioAccumulator, **kwargs): - super().__init__() - self._notifier = notifier - self._audio_accumulator = audio_accumulator - self._idle_task = None - self._wakeup_time = 0 - - async def process_frame(self, frame: Frame, direction: FrameDirection): - await super().process_frame(frame, direction) - - if isinstance(frame, (EndFrame, CancelFrame)): - if self._idle_task: - await self.cancel_task(self._idle_task) - self._idle_task = None - await self.push_frame(frame, direction) - elif isinstance(frame, UserStartedSpeakingFrame): - if self._idle_task: - await self.cancel_task(self._idle_task) - elif isinstance(frame, TextFrame) and frame.text.startswith("YES"): - logger.debug("Completeness check YES") - if self._idle_task: - await self.cancel_task(self._idle_task) - await self.broadcast_frame(UserStoppedSpeakingFrame) - await self._audio_accumulator.reset() - await self._notifier.notify() - elif isinstance(frame, TextFrame): - if frame.text.strip(): - logger.debug(f"Completeness check NO - '{frame.text}'") - # start timer to wake up if necessary - if self._wakeup_time: - self._wakeup_time = time.time() + self.wait_time - else: - # logger.debug("!!! CompletenessCheck idle wait START") - self._wakeup_time = time.time() + self.wait_time - self._idle_task = self.create_task(self._idle_task_handler()) - else: - await self.push_frame(frame, direction) - - async def _idle_task_handler(self): - try: - while time.time() < self._wakeup_time: - await asyncio.sleep(0.01) - # logger.debug(f"!!! CompletenessCheck idle wait OVER") - await self._audio_accumulator.reset() - await self._notifier.notify() - except asyncio.CancelledError: - # logger.debug(f"!!! CompletenessCheck idle wait CANCEL") - pass - except Exception as e: - logger.error(f"CompletenessCheck idle wait error: {e}") - raise e - finally: - # logger.debug(f"!!! CompletenessCheck idle wait FINALLY") - self._wakeup_time = 0 - self._idle_task = None - - -class LLMAggregatorBuffer(LLMAssistantResponseAggregator): - """Buffers the output of the transcription LLM. Used by the bot output gate.""" - - def __init__(self, **kwargs): - super().__init__(params=LLMAssistantAggregatorParams(expect_stripped_words=False)) - self._transcription = "" - - async def process_frame(self, frame: Frame, direction: FrameDirection): - await super().process_frame(frame, direction) - # parent method pushes frames - if isinstance(frame, UserStartedSpeakingFrame): - self._transcription = "" - - async def push_aggregation(self): - if self._aggregation: - self._transcription = self._aggregation - self._aggregation = "" - - logger.debug(f"[Transcription] {self._transcription}") - - async def wait_for_transcription(self): - while not self._transcription: - await asyncio.sleep(0.01) - tx = self._transcription - self._transcription = "" - return tx - - -class ConversationAudioContextAssembler(FrameProcessor): - """Takes the single-message context generated by the AudioAccumulator and adds it to the conversation LLM's context.""" - - def __init__(self, context: LLMContext, **kwargs): - super().__init__(**kwargs) - self._context = context - - async def process_frame(self, frame: Frame, direction: FrameDirection): - await super().process_frame(frame, direction) - - # We must not block system frames. - if isinstance(frame, SystemFrame): - await self.push_frame(frame, direction) - return - - if isinstance(frame, LLMContextFrame): - last_message = frame.context.get_messages()[-1] - self._context._messages.append(last_message) - await self.push_frame(LLMContextFrame(context=self._context)) - - -class OutputGate(FrameProcessor): - """Buffers output frames until the notifier is triggered. - - When the notifier fires, waits until a transcription is ready, then: - 1. Replaces the last user audio message with the transcription. - 2. Flushes the frames buffer. - """ - - def __init__( - self, - notifier: BaseNotifier, - context: LLMContext, - llm_transcription_buffer: LLMAggregatorBuffer, - **kwargs, - ): - super().__init__(**kwargs) - self._gate_open = False - self._frames_buffer = [] - self._notifier = notifier - self._context = context - self._transcription_buffer = llm_transcription_buffer - self._gate_task = None - - def close_gate(self): - self._gate_open = False - - def open_gate(self): - self._gate_open = True - - async def process_frame(self, frame: Frame, direction: FrameDirection): - await super().process_frame(frame, direction) - - # We must not block system frames. - if isinstance(frame, SystemFrame): - if isinstance(frame, StartFrame): - await self._start() - if isinstance(frame, (EndFrame, CancelFrame)): - await self._stop() - if isinstance(frame, InterruptionFrame): - self._frames_buffer = [] - self.close_gate() - await self.push_frame(frame, direction) - return - - # Don't block function call frames - if isinstance(frame, (FunctionCallInProgressFrame, FunctionCallResultFrame)): - await self.push_frame(frame, direction) - return - - # Ignore frames that are not following the direction of this gate. - if direction != FrameDirection.DOWNSTREAM: - await self.push_frame(frame, direction) - return - - if isinstance(frame, LLMFullResponseStartFrame): - # Remove the audio message from the context. We will never need it again. - # If the completeness check fails, a new audio message will be appended to the context. - # If the completeness check succeeds, our notifier will fire and we will append the - # transcription to the context. - self._context._messages.pop() - - if self._gate_open: - await self.push_frame(frame, direction) - return - - self._frames_buffer.append((frame, direction)) - - async def _start(self): - self._frames_buffer = [] - if not self._gate_task: - self._gate_task = self.create_task(self._gate_task_handler()) - - async def _stop(self): - if self._gate_task: - await self.cancel_task(self._gate_task) - self._gate_task = None - - async def _gate_task_handler(self): - while True: - try: - await self._notifier.wait() - - transcription = await self._transcription_buffer.wait_for_transcription() or "-" - self._context.add_message({"role": "user", "content": transcription}) - - self.open_gate() - for frame, direction in self._frames_buffer: - await self.push_frame(frame, direction) - self._frames_buffer = [] - except asyncio.CancelledError: - break - - -class TurnDetectionLLM(Pipeline): - def __init__(self, llm: LLMService, context: LLMContext): - # This is the LLM that will transcribe user speech. - tx_llm = GoogleLLMService( - name="Transcriber", - model=TRANSCRIBER_MODEL, - api_key=os.getenv("GOOGLE_API_KEY"), - temperature=0.0, - system_instruction=transcriber_system_instruction, - ) - - # This is the LLM that will classify user speech as complete or incomplete. - classifier_llm = GoogleLLMService( - name="Classifier", - model=CLASSIFIER_MODEL, - api_key=os.getenv("GOOGLE_API_KEY"), - temperature=0.0, - system_instruction=classifier_system_instruction, - ) - - # This is a notifier that we use to synchronize the two LLMs. - notifier = EventNotifier() - - # This turns the LLM context into an inference request to classify the user's speech - # as complete or incomplete. - # statement_judge_context_filter = StatementJudgeAudioContextAccumulator(notifier=notifier) - - audio_accumulator = AudioAccumulator() - # This sends a UserStoppedSpeakingFrame and triggers the notifier event - completeness_check = CompletenessCheck( - notifier=notifier, audio_accumulator=audio_accumulator - ) - - async def block_user_stopped_speaking(frame): - return not isinstance(frame, UserStoppedSpeakingFrame) - - conversation_audio_context_assembler = ConversationAudioContextAssembler(context=context) - - llm_aggregator_buffer = LLMAggregatorBuffer() - - bot_output_gate = OutputGate( - notifier=notifier, context=context, llm_transcription_buffer=llm_aggregator_buffer - ) - - super().__init__( - [ - audio_accumulator, - ParallelPipeline( - [ - # Pass everything except UserStoppedSpeaking to the elements after - # this ParallelPipeline - FunctionFilter(filter=block_user_stopped_speaking), - ], - [ - ParallelPipeline( - [ - classifier_llm, - completeness_check, - ], - [ - tx_llm, - llm_aggregator_buffer, - ], - ) - ], - [ - conversation_audio_context_assembler, - llm, - bot_output_gate, # buffer output until notified, then flush frames and update context - ], - ), - ] - ) - - -# We use lambdas to defer transport parameter creation until the transport -# type is selected at runtime. -transport_params = { - "daily": lambda: DailyParams( - audio_in_enabled=True, - audio_out_enabled=True, - ), - "twilio": lambda: FastAPIWebsocketParams( - audio_in_enabled=True, - audio_out_enabled=True, - ), - "webrtc": lambda: TransportParams( - audio_in_enabled=True, - audio_out_enabled=True, - ), -} - - -async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): - logger.info(f"Starting bot") - - tts = CartesiaTTSService( - api_key=os.getenv("CARTESIA_API_KEY"), - voice_id="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady - ) - - # This is the regular LLM that responds conversationally. - conversation_llm = GoogleLLMService( - name="Conversation", - model=CONVERSATION_MODEL, - api_key=os.getenv("GOOGLE_API_KEY"), - system_instruction=conversation_system_instruction, - ) - - context = LLMContext() - user_aggregator, assistant_aggregator = LLMContextAggregatorPair( - context, - user_params=LLMUserAggregatorParams( - user_turn_strategies=UserTurnStrategies( - stop=[TurnAnalyzerUserTurnStopStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3())] - ), - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), - ), - ) - - llm = TurnDetectionLLM(conversation_llm, context) - - pipeline = Pipeline( - [ - transport.input(), - user_aggregator, - llm, - tts, - transport.output(), - assistant_aggregator, - ], - ) - - task = PipelineTask( - pipeline, - params=PipelineParams( - enable_metrics=True, - enable_usage_metrics=True, - ), - idle_timeout_secs=runner_args.pipeline_idle_timeout_secs, - ) - - @transport.event_handler("on_client_connected") - async def on_client_connected(transport, client): - logger.info(f"Client connected") - - @transport.event_handler("on_app_message") - async def on_app_message(transport, message, sender): - logger.debug(f"Received app message: {message}, sender: {sender}") # TODO: revert - if "message" not in message: - return - - await task.queue_frames( - [ - UserStartedSpeakingFrame(), - TranscriptionFrame( - user_id="", timestamp=time_now_iso8601(), text=message["message"] - ), - UserStoppedSpeakingFrame(), - ] - ) - - @transport.event_handler("on_client_disconnected") - async def on_client_disconnected(transport, client): - logger.info(f"Client disconnected") - await task.cancel() - - runner = PipelineRunner(handle_sigint=runner_args.handle_sigint) - - await runner.run(task) - - -async def bot(runner_args: RunnerArguments): - """Main bot entry point compatible with Pipecat Cloud.""" - transport = await create_transport(runner_args, transport_params) - await run_bot(transport, runner_args) - - -if __name__ == "__main__": - from pipecat.runner.run import main - - main() diff --git a/src/pipecat/processors/aggregators/llm_response_universal.py b/src/pipecat/processors/aggregators/llm_response_universal.py index 5d3432929..db28b85c1 100644 --- a/src/pipecat/processors/aggregators/llm_response_universal.py +++ b/src/pipecat/processors/aggregators/llm_response_universal.py @@ -47,6 +47,7 @@ from pipecat.frames.frames import ( LLMThoughtEndFrame, LLMThoughtStartFrame, LLMThoughtTextFrame, + LLMUpdateSettingsFrame, SpeechControlParamsFrame, StartFrame, TextFrame, @@ -69,6 +70,7 @@ from pipecat.turns.user_idle_controller import UserIdleController from pipecat.turns.user_mute import BaseUserMuteStrategy from pipecat.turns.user_start import BaseUserTurnStartStrategy, UserTurnStartedParams from pipecat.turns.user_stop import BaseUserTurnStopStrategy, UserTurnStoppedParams +from pipecat.turns.user_turn_completion_mixin import UserTurnCompletionConfig from pipecat.turns.user_turn_controller import UserTurnController from pipecat.turns.user_turn_strategies import ExternalUserTurnStrategies, UserTurnStrategies from pipecat.utils.string import TextPartForConcatenation, concatenate_aggregated_text @@ -89,6 +91,13 @@ class LLMUserAggregatorParams: has been idle (not speaking) for this duration. Set to None to disable idle detection. vad_analyzer: Voice Activity Detection analyzer instance. + filter_incomplete_user_turns: Whether to filter out incomplete user turns. + When enabled, the LLM outputs a turn completion marker at the start of + each response: ✓ (complete), ○ (incomplete short), or ◐ (incomplete long). + Incomplete responses are suppressed and timeouts trigger re-prompting. + user_turn_completion_config: Configuration for turn completion behavior including + custom instructions, timeouts, and prompts. Only used when + filter_incomplete_user_turns is True. """ user_turn_strategies: Optional[UserTurnStrategies] = None @@ -96,6 +105,8 @@ class LLMUserAggregatorParams: user_turn_stop_timeout: float = 5.0 user_idle_timeout: Optional[float] = None vad_analyzer: Optional[VADAnalyzer] = None + filter_incomplete_user_turns: bool = False + user_turn_completion_config: Optional[UserTurnCompletionConfig] = None @dataclass @@ -488,6 +499,24 @@ class LLMUserAggregator(LLMContextAggregator): for s in self._params.user_mute_strategies: await s.setup(self.task_manager) + # Enable incomplete turn filtering on the LLM if configured + if self._params.filter_incomplete_user_turns: + # Get config or use defaults + config = self._params.user_turn_completion_config or UserTurnCompletionConfig() + + # Enable the feature on the LLM with config + await self.push_frame( + LLMUpdateSettingsFrame( + settings={ + "filter_incomplete_user_turns": True, + "user_turn_completion_config": config, + } + ) + ) + + # Auto-inject turn completion instructions into context + self._context.add_message({"role": "system", "content": config.completion_instructions}) + async def _stop(self, frame: EndFrame): await self._maybe_emit_user_turn_stopped(on_session_end=True) await self._cleanup() @@ -1145,13 +1174,40 @@ class LLMAssistantAggregator(LLMContextAggregator): async def _trigger_assistant_turn_stopped(self): aggregation = await self.push_aggregation() if aggregation: + # Strip turn completion markers from the transcript + content = self._maybe_strip_turn_completion_markers(aggregation) message = AssistantTurnStoppedMessage( - content=aggregation, timestamp=self._assistant_turn_start_timestamp + content=content, timestamp=self._assistant_turn_start_timestamp ) await self._call_event_handler("on_assistant_turn_stopped", message) self._assistant_turn_start_timestamp = "" + def _maybe_strip_turn_completion_markers(self, text: str) -> str: + """Strip turn completion markers from assistant transcript. + + These markers (✓, ○, ◐) are used internally for turn completion + detection and shouldn't appear in the final transcript. + """ + from pipecat.turns.user_turn_completion_mixin import ( + USER_TURN_COMPLETE_MARKER, + USER_TURN_INCOMPLETE_LONG_MARKER, + USER_TURN_INCOMPLETE_SHORT_MARKER, + ) + + marker_found = False + for marker in ( + USER_TURN_COMPLETE_MARKER, + USER_TURN_INCOMPLETE_SHORT_MARKER, + USER_TURN_INCOMPLETE_LONG_MARKER, + ): + if marker in text: + text = text.replace(marker, "") + marker_found = True + + # Only strip whitespace if we removed a marker + return text.strip() if marker_found else text + class LLMContextAggregatorPair: """Pair of LLM context aggregators for updating context with user and assistant messages.""" diff --git a/src/pipecat/services/anthropic/llm.py b/src/pipecat/services/anthropic/llm.py index 1d9bd6df9..b184ea29d 100644 --- a/src/pipecat/services/anthropic/llm.py +++ b/src/pipecat/services/anthropic/llm.py @@ -439,7 +439,7 @@ class AnthropicLLMService(LLMService): if event.type == "content_block_delta": if hasattr(event.delta, "text"): - await self.push_frame(LLMTextFrame(event.delta.text)) + await self._push_llm_text(event.delta.text) completion_tokens_estimate += self._estimate_tokens(event.delta.text) elif hasattr(event.delta, "partial_json") and tool_use_block: json_accumulator += event.delta.partial_json diff --git a/src/pipecat/services/aws/llm.py b/src/pipecat/services/aws/llm.py index 1bfee4be0..32562109a 100644 --- a/src/pipecat/services/aws/llm.py +++ b/src/pipecat/services/aws/llm.py @@ -1107,7 +1107,7 @@ class AWSBedrockLLMService(LLMService): if "contentBlockDelta" in event: delta = event["contentBlockDelta"]["delta"] if "text" in delta: - await self.push_frame(LLMTextFrame(delta["text"])) + await self._push_llm_text(delta["text"]) completion_tokens_estimate += self._estimate_tokens(delta["text"]) elif "toolUse" in delta and "input" in delta["toolUse"]: # Handle partial JSON for tool use diff --git a/src/pipecat/services/google/llm.py b/src/pipecat/services/google/llm.py index fd6c2c54e..0e7556f83 100644 --- a/src/pipecat/services/google/llm.py +++ b/src/pipecat/services/google/llm.py @@ -1023,7 +1023,7 @@ class GoogleLLMService(LLMService): await self.push_frame(LLMThoughtEndFrame()) else: accumulated_text += part.text - await self.push_frame(LLMTextFrame(part.text)) + await self._push_llm_text(part.text) elif part.function_call: function_call = part.function_call function_call_id = function_call.id or str(uuid.uuid4()) diff --git a/src/pipecat/services/llm_service.py b/src/pipecat/services/llm_service.py index 035f1b2f2..7f3d2270a 100644 --- a/src/pipecat/services/llm_service.py +++ b/src/pipecat/services/llm_service.py @@ -56,6 +56,7 @@ from pipecat.processors.aggregators.llm_response import ( from pipecat.processors.aggregators.openai_llm_context import OpenAILLMContext from pipecat.processors.frame_processor import FrameDirection from pipecat.services.ai_service import AIService +from pipecat.turns.user_turn_completion_mixin import UserTurnCompletionLLMServiceMixin # Type alias for a callable that handles LLM function calls. FunctionCallHandler = Callable[["FunctionCallParams"], Awaitable[None]] @@ -142,7 +143,7 @@ class FunctionCallRunnerItem: run_llm: Optional[bool] = None -class LLMService(AIService): +class LLMService(UserTurnCompletionLLMServiceMixin, AIService): """Base class for all LLM services. Handles function calling registration and execution with support for both @@ -186,6 +187,7 @@ class LLMService(AIService): super().__init__(**kwargs) self._run_in_parallel = run_in_parallel self._function_call_timeout_secs = function_call_timeout_secs + self._filter_incomplete_user_turns: bool = False self._start_callbacks = {} self._adapter = self.adapter_class() self._functions: Dict[Optional[str], FunctionCallRegistryItem] = {} @@ -295,6 +297,35 @@ class LLMService(AIService): if not self._run_in_parallel: await self._cancel_sequential_runner_task() + async def _update_settings(self, settings: Mapping[str, Any]): + """Update LLM service settings. + + Handles turn completion settings specially since they are not model + parameters and should not be passed to the underlying LLM API. + + Args: + settings: Dictionary of settings to update. + """ + # Turn completion settings to extract (not model parameters) + turn_completion_keys = {"filter_incomplete_user_turns", "user_turn_completion_config"} + + # Handle turn completion settings + if "filter_incomplete_user_turns" in settings: + self._filter_incomplete_user_turns = settings["filter_incomplete_user_turns"] + logger.info( + f"{self}: Incomplete turn filtering {'enabled' if self._filter_incomplete_user_turns else 'disabled'}" + ) + + # Configure the mixin with config object + if self._filter_incomplete_user_turns and "user_turn_completion_config" in settings: + self.set_user_turn_completion_config(settings["user_turn_completion_config"]) + + # Remove turn completion settings before passing to parent + settings = {k: v for k, v in settings.items() if k not in turn_completion_keys} + + # Let the parent handle remaining model parameters + await super()._update_settings(settings) + async def process_frame(self, frame: Frame, direction: FrameDirection): """Process a frame. @@ -322,6 +353,20 @@ class LLMService(AIService): await super().push_frame(frame, direction) + async def _push_llm_text(self, text: str): + """Push LLM text, using turn completion detection if enabled. + + This helper method simplifies text pushing in LLM implementations by + handling the conditional logic for turn completion internally. + + Args: + text: The text content from the LLM to push. + """ + if self._filter_incomplete_user_turns: + await self._push_turn_text(text) + else: + await self.push_frame(LLMTextFrame(text)) + async def _handle_interruptions(self, _: InterruptionFrame): for function_name, entry in self._functions.items(): if entry.cancel_on_interruption: diff --git a/src/pipecat/services/openai/base_llm.py b/src/pipecat/services/openai/base_llm.py index 0243cc917..ef6cfbbe9 100644 --- a/src/pipecat/services/openai/base_llm.py +++ b/src/pipecat/services/openai/base_llm.py @@ -422,7 +422,7 @@ class BaseOpenAILLMService(LLMService): # Keep iterating through the response to collect all the argument fragments arguments += tool_call.function.arguments elif chunk.choices[0].delta.content: - await self.push_frame(LLMTextFrame(chunk.choices[0].delta.content)) + await self._push_llm_text(chunk.choices[0].delta.content) # When gpt-4o-audio / gpt-4o-mini-audio is used for llm or stt+llm # we need to get LLMTextFrame for the transcript diff --git a/src/pipecat/turns/user_turn_completion_mixin.py b/src/pipecat/turns/user_turn_completion_mixin.py new file mode 100644 index 000000000..3aea01be9 --- /dev/null +++ b/src/pipecat/turns/user_turn_completion_mixin.py @@ -0,0 +1,428 @@ +# +# Copyright (c) 2024-2026, Daily +# +# SPDX-License-Identifier: BSD 2-Clause License +# + +"""Mixin for adding turn completion detection to LLM services. + +This mixin enables LLM services to detect and process turn completion markers +(COMPLETE/INCOMPLETE) in LLM responses, allowing for smarter conversation flow +where the LLM can indicate whether the user's input was complete or if they +were interrupted mid-thought. +""" + +import asyncio +from dataclasses import dataclass +from typing import Literal, Optional + +from loguru import logger + +from pipecat.frames.frames import ( + Frame, + InterruptionFrame, + LLMFullResponseEndFrame, + LLMMessagesAppendFrame, + LLMRunFrame, + LLMTextFrame, +) +from pipecat.processors.frame_processor import FrameDirection + +# Turn completion markers +USER_TURN_COMPLETE_MARKER = "✓" +USER_TURN_INCOMPLETE_SHORT_MARKER = "○" # Short wait - user likely continues soon +USER_TURN_INCOMPLETE_LONG_MARKER = "◐" # Long wait - user needs more time + +# Default prompts for incomplete timeouts +DEFAULT_INCOMPLETE_SHORT_PROMPT = """The user paused briefly. Generate a brief, natural prompt to encourage them to continue. + +IMPORTANT: You MUST respond with ✓ followed by your message. Do NOT output ○ or ◐ - the user has already been given time to continue. + +Your response should: +- Be contextually relevant to what was just discussed +- Sound natural and conversational +- Be very concise (1 sentence max) +- Gently prompt them to continue + +Example format: ✓ Go ahead, I'm listening. + +Generate your ✓ response now.""" + +DEFAULT_INCOMPLETE_LONG_PROMPT = """The user has been quiet for a while. Generate a friendly check-in message. + +IMPORTANT: You MUST respond with ✓ followed by your message. Do NOT output ○ or ◐ - the user has already been given plenty of time. + +Your response should: +- Acknowledge they might be thinking or busy +- Offer to help or continue when ready +- Be warm and understanding +- Be brief (1 sentence) + +Example format: ✓ No rush! Let me know when you're ready to continue. + +Generate your ✓ response now.""" + +# System prompt instructions for turn completion that can be appended to any base prompt +USER_TURN_COMPLETION_INSTRUCTIONS = """ +CRITICAL INSTRUCTION - MANDATORY RESPONSE FORMAT: +Every single response MUST begin with a turn completion indicator. This is not optional. + +TURN COMPLETION DECISION FRAMEWORK: +Ask yourself: "Has the user provided enough information for me to give a meaningful, substantive response?" + +Mark as COMPLETE (✓) when: +- The user has answered your question with actual content +- The user has made a complete request or statement +- The user has provided all necessary information for you to respond meaningfully +- The conversation can naturally progress to your substantive response + +Mark as INCOMPLETE SHORT (○) when the user will likely continue soon: +- The user was clearly cut off mid-sentence or mid-word +- The user is in the middle of a thought that got interrupted +- Brief technical interruption (they'll resume in a few seconds) + +Mark as INCOMPLETE LONG (◐) when the user needs more time: +- The user explicitly asks for time: "let me think", "give me a minute", "hold on" +- The user is clearly pondering or deliberating: "hmm", "well...", "that's a good question" +- The user acknowledged but hasn't answered yet: "That's interesting..." +- The response feels like a preamble before the actual answer + +RESPOND in one of these three formats: +1. If COMPLETE: `✓` followed by a space and your full substantive response +2. If INCOMPLETE SHORT: ONLY the character `○` (user will continue in a few seconds) +3. If INCOMPLETE LONG: ONLY the character `◐` (user needs more time to think) + +KEY INSIGHT: Grammatically complete ≠ conversationally complete +- "That's a really good question." is grammatically complete but conversationally incomplete (use ◐) +- "I'd go to Japan because I love" is mid-sentence (use ○) + +EXAMPLES: + +You ask: "Where would you travel?" +User: "I'd go to Japan because I love" +→ `○` +(Cut off mid-sentence - they'll continue in seconds) + +You ask: "Where would you travel?" +User: "That's a good question. Let me think..." +→ `◐` +(User is deliberating - give them time) + +You ask: "Where would you travel?" +User: "Hmm, hold on a second." +→ `◐` +(User explicitly asked for time) + +You ask: "Where would you travel?" +User: "I'd go to Japan because I love the culture." +→ `✓ Japan is a wonderful choice! The blend of ancient traditions and modern innovation is truly unique. Have you been before?` +(Complete answer - give full response) + +User: "I need help with" +→ `○` +(Cut off mid-request - they'll finish soon) + +User: "Well, let me think about that for a moment." +→ `◐` +(User needs time to think) + +User: "Can you help me book a flight to New York next week?" +→ `✓ I'd be happy to help you with that! Let me gather some information...` +(Complete request - provide full response) + +User: "Give me a minute to gather my thoughts." +→ `◐` +(User explicitly asked for time) + +FORMAT REQUIREMENTS: +- ALWAYS use single-character indicators: `✓` (complete), `○` (short wait), or `◐` (long wait) +- For COMPLETE: `✓` followed by a space and your full response +- For INCOMPLETE: ONLY the single character (`○` or `◐`) with absolutely nothing else +- Your turn indicator must be the very first character in your response + +Remember: Focus on conversational completeness and how long the user might need. Was it a mid-sentence cutoff (○) or do they need time to think (◐)?""" + + +@dataclass +class UserTurnCompletionConfig: + """Configuration for turn completion behavior. + + Attributes: + instructions: Custom instructions for turn completion. If not provided, + uses default USER_TURN_COMPLETION_INSTRUCTIONS. + incomplete_short_timeout: Seconds to wait after short incomplete (○) before prompting. + incomplete_long_timeout: Seconds to wait after long incomplete (◐) before prompting. + incomplete_short_prompt: Custom prompt when short timeout expires. + incomplete_long_prompt: Custom prompt when long timeout expires. + """ + + instructions: Optional[str] = None + incomplete_short_timeout: float = 5.0 + incomplete_long_timeout: float = 10.0 + incomplete_short_prompt: Optional[str] = None + incomplete_long_prompt: Optional[str] = None + + @property + def completion_instructions(self) -> str: + """Turn completion instructions, using default if not set.""" + return self.instructions or USER_TURN_COMPLETION_INSTRUCTIONS + + @property + def short_prompt(self) -> str: + """Short incomplete prompt, using default if not set.""" + return self.incomplete_short_prompt or DEFAULT_INCOMPLETE_SHORT_PROMPT + + @property + def long_prompt(self) -> str: + """Long incomplete prompt, using default if not set.""" + return self.incomplete_long_prompt or DEFAULT_INCOMPLETE_LONG_PROMPT + + +class UserTurnCompletionLLMServiceMixin: + """Mixin that adds turn completion detection to LLM services. + + This mixin provides methods to push LLM text with turn completion detection. + It processes turn completion markers to enable smarter conversation flow: + + - ✓ (COMPLETE): Push response normally + - ○ (INCOMPLETE SHORT): Suppress response, wait ~5s, then prompt + - ◐ (INCOMPLETE LONG): Suppress response, wait ~15s, then prompt + + When incomplete timeouts expire, the mixin automatically prompts the LLM + with a contextual follow-up message to re-engage the user. + + Usage: + The LLM service controls when to use turn completion by calling + _push_turn_text instead of push_frame: + + # With turn completion: + if self._filter_incomplete_user_turns: + await self._push_turn_text(chunk.text) + else: + await self.push_frame(LLMTextFrame(chunk.text)) + + The mixin requires that the base class has a `push_frame` method compatible + with FrameProcessor's signature. + """ + + def __init__(self, *args, **kwargs): + """Initialize the turn completion mixin. + + Args: + *args: Positional arguments passed to parent class. + **kwargs: Keyword arguments passed to parent class. + """ + super().__init__(*args, **kwargs) + self._turn_text_buffer = "" + # Safety mechanism: True when incomplete is detected. While the prompt + # instructs the LLM to output ONLY the marker for incomplete turns, this flag + # ensures graceful degradation if the LLM disobeys and outputs additional text. + self._turn_suppressed = False + self._turn_complete_found = False # True when ✓ (COMPLETE) is detected + + # Timeout handling + self._user_turn_completion_config = UserTurnCompletionConfig() + self._incomplete_timeout_task: Optional[asyncio.Task] = None + self._incomplete_type: Optional[Literal["short", "long"]] = None + + def set_user_turn_completion_config(self, config: UserTurnCompletionConfig): + """Set the turn completion configuration. + + Args: + config: The turn completion configuration. + """ + self._user_turn_completion_config = config + + async def _start_incomplete_timeout(self, incomplete_type: Literal["short", "long"]): + """Start a timeout task for incomplete turn handling. + + Args: + incomplete_type: Either "short" or "long" to determine timeout duration. + """ + # Cancel any existing timeout + await self._cancel_incomplete_timeout() + + self._incomplete_type = incomplete_type + + if incomplete_type == "short": + timeout = self._user_turn_completion_config.incomplete_short_timeout + else: + timeout = self._user_turn_completion_config.incomplete_long_timeout + + logger.debug(f"Starting {incomplete_type} incomplete timeout ({timeout}s)") + self._incomplete_timeout_task = self.create_task( + self._incomplete_timeout_handler(incomplete_type, timeout), + f"_incomplete_timeout_{incomplete_type}", + ) + + async def _cancel_incomplete_timeout(self): + """Cancel any pending incomplete timeout task.""" + if self._incomplete_timeout_task and not self._incomplete_timeout_task.done(): + logger.debug("Cancelling incomplete timeout") + await self.cancel_task(self._incomplete_timeout_task) + self._incomplete_timeout_task = None + self._incomplete_type = None + + async def _incomplete_timeout_handler( + self, incomplete_type: Literal["short", "long"], timeout: float + ): + """Handle incomplete timeout expiration. + + Args: + incomplete_type: Either "short" or "long". + timeout: The timeout duration in seconds. + """ + try: + await asyncio.sleep(timeout) + + # Timeout expired - reset state before prompting LLM + logger.info(f"Incomplete {incomplete_type} timeout expired, prompting LLM") + await self._turn_reset() + self._incomplete_timeout_task = None + self._incomplete_type = None + + # Get the appropriate prompt + if incomplete_type == "short": + prompt = self._user_turn_completion_config.short_prompt + else: + prompt = self._user_turn_completion_config.long_prompt + + # Push through pipeline to trigger LLM response + await self.push_frame( + LLMMessagesAppendFrame(messages=[{"role": "system", "content": prompt}]) + ) + await self.push_frame(LLMRunFrame()) + + except asyncio.CancelledError: + # Timeout was cancelled (user spoke or interruption) + pass + + async def _turn_reset(self): + """Reset turn completion state between responses. + + Call this at the end of each LLM response to clear buffered text and reset state. + If no marker was found, pushes the buffered text to avoid losing content. + + Note: This does NOT cancel pending incomplete timeouts. Timeouts are only + cancelled on InterruptionFrame (when user speaks). + """ + # Check if no marker was found in this response + marker_found = self._turn_suppressed or self._turn_complete_found + if not marker_found and self._turn_text_buffer: + # Graceful degradation: push the buffered text so it's not lost + logger.warning( + f"{self}: filter_incomplete_user_turns is enabled but LLM response did not " + f"contain turn completion markers (✓/○/◐). Pushing text anyway. " + "The system prompt may be missing turn completion instructions." + ) + await self.push_frame(LLMTextFrame(self._turn_text_buffer)) + + self._turn_text_buffer = "" + self._turn_suppressed = False + self._turn_complete_found = False + + async def process_frame(self, frame: Frame, direction: FrameDirection): + """Process frames, handling turn completion state resets. + + Args: + frame: The frame to process. + direction: The direction of frame processing. + """ + # Handle interruptions by cancelling timeout and resetting state + if isinstance(frame, InterruptionFrame): + await self._cancel_incomplete_timeout() + await self._turn_reset() + # Reset turn state at end of LLM response (but don't cancel timeout - + # incomplete timeouts should continue running) + elif isinstance(frame, LLMFullResponseEndFrame): + await self._turn_reset() + + # Pass frame to parent + await super().process_frame(frame, direction) + + async def _push_turn_text(self, text: str): + """Push LLM text with turn completion detection. + + This method should be used instead of `push_frame(LLMTextFrame(text))` when + turn completion is enabled. It will: + 1. Detect turn markers (✓, ○, or ◐) + 2. When ○ (SHORT) is found: suppress text, start short timeout + 3. When ◐ (LONG) is found: suppress text, start long timeout + 4. When ✓ (COMPLETE) is found: push all text with marker marked as skip_tts + 5. After marker detected: all subsequent text flows through immediately + + Args: + text: The text content from the LLM to push. + """ + # If we've already detected incomplete, suppress all remaining text. + # This is a safety mechanism in case the LLM disobeys the prompt and outputs + # additional text after the marker (e.g., "○ Please continue..."). + if self._turn_suppressed: + return + + # If ✓ (COMPLETE) was already found, push text immediately without buffering + if self._turn_complete_found: + await self.push_frame(LLMTextFrame(text)) + return + + # Add text to buffer + self._turn_text_buffer += text + + # Check for incomplete markers (○ short, ◐ long) + # These indicate the user was cut off or needs time - we suppress the bot's + # response and start a timeout to re-prompt later. + incomplete_type: Optional[Literal["short", "long"]] = None + if USER_TURN_INCOMPLETE_SHORT_MARKER in self._turn_text_buffer: + incomplete_type = "short" + elif USER_TURN_INCOMPLETE_LONG_MARKER in self._turn_text_buffer: + incomplete_type = "long" + + if incomplete_type: + marker = ( + USER_TURN_INCOMPLETE_SHORT_MARKER + if incomplete_type == "short" + else USER_TURN_INCOMPLETE_LONG_MARKER + ) + logger.debug( + f"INCOMPLETE {incomplete_type.upper()} ({marker}) detected, suppressing text" + ) + self._turn_suppressed = True + + # Push the marker with skip_tts=True so it's added to context (maintains + # conversation continuity per prompt instructions) but not spoken by TTS + frame = LLMTextFrame(self._turn_text_buffer) + frame.skip_tts = True + await self.push_frame(frame) + + self._turn_text_buffer = "" + await self._start_incomplete_timeout(incomplete_type) + return + + # Check for ✓ (COMPLETE) marker - user's turn was complete, respond normally + if USER_TURN_COMPLETE_MARKER in self._turn_text_buffer: + logger.debug(f"COMPLETE ({USER_TURN_COMPLETE_MARKER}) detected, pushing buffered text") + + # Split buffer at the marker to handle cases where marker and text + # arrive in the same chunk (e.g., "✓ Hello!" from some LLMs) + marker_pos = self._turn_text_buffer.index(USER_TURN_COMPLETE_MARKER) + marker_end = marker_pos + len(USER_TURN_COMPLETE_MARKER) + + # Push the marker with skip_tts=True - adds to context but not spoken + marker_text = self._turn_text_buffer[:marker_end] + frame = LLMTextFrame(marker_text) + frame.skip_tts = True + await self.push_frame(frame) + + # Push remaining text after marker as normal speech + remaining_text = self._turn_text_buffer[marker_end:] + if remaining_text: + # Strip leading space after marker if present (✓ Hello -> Hello) + if remaining_text.startswith(" "): + remaining_text = remaining_text[1:] + if remaining_text: + await self.push_frame(LLMTextFrame(remaining_text)) + + # Mark complete - all subsequent text flows through immediately + self._turn_text_buffer = "" + self._turn_complete_found = True + return diff --git a/tests/test_context_aggregators_universal.py b/tests/test_context_aggregators_universal.py index e840fd8f5..e612fbf5f 100644 --- a/tests/test_context_aggregators_universal.py +++ b/tests/test_context_aggregators_universal.py @@ -567,6 +567,54 @@ class TestLLMAssistantAggregator(unittest.IsolatedAsyncioTestCase): self.assertEqual(len(stop_messages), 1) self.assertEqual(stop_messages[0].content, "Hello from Pipecat!") + async def test_turn_completion_markers_stripped_from_transcript(self): + """Turn completion markers should be stripped from assistant transcript.""" + from pipecat.turns.user_turn_completion_mixin import ( + USER_TURN_COMPLETE_MARKER, + USER_TURN_INCOMPLETE_SHORT_MARKER, + ) + + context = LLMContext() + aggregator = LLMAssistantAggregator(context) + + stop_messages = [] + + @aggregator.event_handler("on_assistant_turn_stopped") + async def on_assistant_turn_stopped(aggregator, message: AssistantTurnStoppedMessage): + stop_messages.append(message) + + # Send text with a turn completion marker + frames_to_send = [ + LLMFullResponseStartFrame(), + LLMTextFrame(f"{USER_TURN_COMPLETE_MARKER} Hello from Pipecat!"), + LLMFullResponseEndFrame(), + ] + await run_test(aggregator, frames_to_send=frames_to_send) + + # The marker should be stripped from the transcript + self.assertEqual(len(stop_messages), 1) + self.assertEqual(stop_messages[0].content, "Hello from Pipecat!") + + # Test incomplete markers are also stripped + stop_messages.clear() + context2 = LLMContext() + aggregator2 = LLMAssistantAggregator(context2) + + @aggregator2.event_handler("on_assistant_turn_stopped") + async def on_assistant_turn_stopped2(aggregator, message: AssistantTurnStoppedMessage): + stop_messages.append(message) + + frames_to_send = [ + LLMFullResponseStartFrame(), + LLMTextFrame(USER_TURN_INCOMPLETE_SHORT_MARKER), + LLMFullResponseEndFrame(), + ] + await run_test(aggregator2, frames_to_send=frames_to_send) + + # The incomplete marker should be stripped (resulting in empty content) + self.assertEqual(len(stop_messages), 1) + self.assertEqual(stop_messages[0].content, "") + if __name__ == "__main__": unittest.main() diff --git a/tests/test_user_turn_completion_mixin.py b/tests/test_user_turn_completion_mixin.py new file mode 100644 index 000000000..d258cff9a --- /dev/null +++ b/tests/test_user_turn_completion_mixin.py @@ -0,0 +1,117 @@ +# +# Copyright (c) 2024-2026, Daily +# +# SPDX-License-Identifier: BSD 2-Clause License +# + +import unittest +from unittest.mock import AsyncMock + +from pipecat.frames.frames import LLMTextFrame +from pipecat.processors.frame_processor import FrameProcessor +from pipecat.turns.user_turn_completion_mixin import ( + USER_TURN_COMPLETE_MARKER, + USER_TURN_INCOMPLETE_LONG_MARKER, + USER_TURN_INCOMPLETE_SHORT_MARKER, + UserTurnCompletionLLMServiceMixin, +) + + +class MockProcessor(UserTurnCompletionLLMServiceMixin, FrameProcessor): + """Simple mock processor using the turn completion mixin.""" + + pass + + +class TestUserUserTurnCompletionLLMServiceMixin(unittest.IsolatedAsyncioTestCase): + """Tests for UserUserTurnCompletionLLMServiceMixin functionality.""" + + async def test_complete_marker_pushes_text(self): + """Test that ✓ marker is detected and text after it is pushed normally.""" + processor = MockProcessor() + + # Capture frames that get pushed + pushed_frames = [] + processor.push_frame = AsyncMock( + side_effect=lambda f, *args, **kwargs: pushed_frames.append(f) + ) + + # Simulate LLM generating: "✓ Hello there!" + await processor._push_turn_text(f"{USER_TURN_COMPLETE_MARKER} Hello there!") + + # Should have 2 text frames: marker (skip_tts) and content (normal) + self.assertEqual(len(pushed_frames), 2) + + # First frame should be the marker with skip_tts=True + self.assertIsInstance(pushed_frames[0], LLMTextFrame) + self.assertEqual(pushed_frames[0].text, USER_TURN_COMPLETE_MARKER) + self.assertTrue(pushed_frames[0].skip_tts) + + # Second frame should be the actual text without skip_tts + self.assertIsInstance(pushed_frames[1], LLMTextFrame) + self.assertEqual(pushed_frames[1].text, "Hello there!") + self.assertFalse(pushed_frames[1].skip_tts) + + async def test_incomplete_short_marker_suppresses_text(self): + """Test that ○ marker suppresses text with skip_tts.""" + processor = MockProcessor() + + pushed_frames = [] + processor.push_frame = AsyncMock( + side_effect=lambda f, *args, **kwargs: pushed_frames.append(f) + ) + # Mock timeout to avoid needing task manager + processor._start_incomplete_timeout = AsyncMock() + + await processor._push_turn_text(USER_TURN_INCOMPLETE_SHORT_MARKER) + + # Should have 1 text frame with skip_tts=True + self.assertEqual(len(pushed_frames), 1) + self.assertIsInstance(pushed_frames[0], LLMTextFrame) + self.assertEqual(pushed_frames[0].text, USER_TURN_INCOMPLETE_SHORT_MARKER) + self.assertTrue(pushed_frames[0].skip_tts) + + async def test_incomplete_long_marker_suppresses_text(self): + """Test that ◐ marker suppresses text with skip_tts.""" + processor = MockProcessor() + + pushed_frames = [] + processor.push_frame = AsyncMock( + side_effect=lambda f, *args, **kwargs: pushed_frames.append(f) + ) + # Mock timeout to avoid needing task manager + processor._start_incomplete_timeout = AsyncMock() + + await processor._push_turn_text(USER_TURN_INCOMPLETE_LONG_MARKER) + + # Should have 1 text frame with skip_tts=True + self.assertEqual(len(pushed_frames), 1) + self.assertIsInstance(pushed_frames[0], LLMTextFrame) + self.assertEqual(pushed_frames[0].text, USER_TURN_INCOMPLETE_LONG_MARKER) + self.assertTrue(pushed_frames[0].skip_tts) + + async def test_text_buffered_until_marker_found(self): + """Test that text is buffered until a marker is detected.""" + processor = MockProcessor() + + pushed_frames = [] + processor.push_frame = AsyncMock( + side_effect=lambda f, *args, **kwargs: pushed_frames.append(f) + ) + + # Simulate token-by-token streaming without marker + await processor._push_turn_text("Hello") + await processor._push_turn_text(" there") + + # No frames should be pushed yet (buffering) + self.assertEqual(len(pushed_frames), 0) + + # Now send the complete marker + await processor._push_turn_text(f" {USER_TURN_COMPLETE_MARKER} How are you?") + + # Now frames should be pushed + self.assertEqual(len(pushed_frames), 2) + + +if __name__ == "__main__": + unittest.main() From 93160f1455e5fe607f35a993ceab0582299e5509 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Aleix=20Conchillo=20Flaqu=C3=A9?= Date: Fri, 30 Jan 2026 12:08:12 -0800 Subject: [PATCH 0313/1060] scripts(evals): remove vad_analyzer from transport --- scripts/evals/eval.py | 1 - 1 file changed, 1 deletion(-) diff --git a/scripts/evals/eval.py b/scripts/evals/eval.py index d7272806c..d97464ada 100644 --- a/scripts/evals/eval.py +++ b/scripts/evals/eval.py @@ -237,7 +237,6 @@ async def run_eval_pipeline( audio_in_enabled=True, audio_out_enabled=True, video_out_enabled=True, - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=2.0)), ), ) From c92ec1552e4f7eb9fc8141653ea5356481916780 Mon Sep 17 00:00:00 2001 From: Mark Backman Date: Fri, 30 Jan 2026 15:10:53 -0500 Subject: [PATCH 0314/1060] Add 22 foundational to release evals --- examples/foundational/22-filter-incomplete-turns.py | 9 +++------ scripts/evals/eval.py | 3 +-- scripts/evals/run-release-evals.py | 10 ++++++++++ 3 files changed, 14 insertions(+), 8 deletions(-) diff --git a/examples/foundational/22-filter-incomplete-turns.py b/examples/foundational/22-filter-incomplete-turns.py index 967750c48..27e37901f 100644 --- a/examples/foundational/22-filter-incomplete-turns.py +++ b/examples/foundational/22-filter-incomplete-turns.py @@ -49,24 +49,20 @@ from pipecat.turns.user_turn_strategies import UserTurnStrategies load_dotenv(override=True) -# We store functions so objects (e.g. SileroVADAnalyzer) don't get -# instantiated. The function will be called when the desired transport gets -# selected. +# We use lambdas to defer transport parameter creation until the transport +# type is selected at runtime. transport_params = { "daily": lambda: DailyParams( audio_in_enabled=True, audio_out_enabled=True, - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), "twilio": lambda: FastAPIWebsocketParams( audio_in_enabled=True, audio_out_enabled=True, - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), "webrtc": lambda: TransportParams( audio_in_enabled=True, audio_out_enabled=True, - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), } @@ -97,6 +93,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): user_turn_strategies=UserTurnStrategies( stop=[TurnAnalyzerUserTurnStopStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3())] ), + vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), # Enable turn completion filtering - the LLM will output: # ✓ = complete (respond normally) # ○ = incomplete short (wait 5s, then prompt) diff --git a/scripts/evals/eval.py b/scripts/evals/eval.py index d7272806c..91971aee7 100644 --- a/scripts/evals/eval.py +++ b/scripts/evals/eval.py @@ -237,7 +237,6 @@ async def run_eval_pipeline( audio_in_enabled=True, audio_out_enabled=True, video_out_enabled=True, - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=2.0)), ), ) @@ -314,7 +313,7 @@ async def run_eval_pipeline( context_aggregator = LLMContextAggregatorPair( context, user_params=LLMUserAggregatorParams( - vad_analyzer=SileroVADAnalyzer(), + vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=2.0)), ), ) diff --git a/scripts/evals/run-release-evals.py b/scripts/evals/run-release-evals.py index 090b1b96c..f0e2e9a89 100644 --- a/scripts/evals/run-release-evals.py +++ b/scripts/evals/run-release-evals.py @@ -90,6 +90,11 @@ EVAL_ORDER = EvalConfig( eval_speaks_first=True, ) +EVAL_COMPLETE_TURN = EvalConfig( + prompt="I would go to Japan because I love the culture and want to try authentic ramen.", + eval="The user provides a relevant response about Japan or travel, showing the conversation continues normally.", +) + TESTS_07 = [ # 07 series @@ -210,6 +215,10 @@ TESTS_21 = [ ("21a-tavus-video-service.py", EVAL_SIMPLE_MATH), ] +TESTS_22 = [ + ("22-filter-incomplete-turns.py", EVAL_COMPLETE_TURN), +] + TESTS_26 = [ ("26-gemini-live.py", EVAL_SIMPLE_MATH), ("26a-gemini-live-transcription.py", EVAL_SIMPLE_MATH), @@ -266,6 +275,7 @@ TESTS = [ *TESTS_15, *TESTS_19, *TESTS_21, + *TESTS_22, *TESTS_26, *TESTS_27, *TESTS_40, From 604d5d0b14136ca7128f77a3fe8ad06156431eea Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Aleix=20Conchillo=20Flaqu=C3=A9?= Date: Fri, 30 Jan 2026 16:14:02 -0800 Subject: [PATCH 0315/1060] examples: update 07zi and 07zj to use vad_analyzer form LLMUserAggregator --- examples/foundational/07zi-interruptible-piper.py | 4 +--- examples/foundational/07zj-interruptible-kokoro.py | 4 +--- 2 files changed, 2 insertions(+), 6 deletions(-) diff --git a/examples/foundational/07zi-interruptible-piper.py b/examples/foundational/07zi-interruptible-piper.py index 67286741d..6a5507d25 100644 --- a/examples/foundational/07zi-interruptible-piper.py +++ b/examples/foundational/07zi-interruptible-piper.py @@ -41,17 +41,14 @@ transport_params = { "daily": lambda: DailyParams( audio_in_enabled=True, audio_out_enabled=True, - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), "twilio": lambda: FastAPIWebsocketParams( audio_in_enabled=True, audio_out_enabled=True, - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), "webrtc": lambda: TransportParams( audio_in_enabled=True, audio_out_enabled=True, - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), } @@ -79,6 +76,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): user_turn_strategies=UserTurnStrategies( stop=[TurnAnalyzerUserTurnStopStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3())] ), + vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), ) diff --git a/examples/foundational/07zj-interruptible-kokoro.py b/examples/foundational/07zj-interruptible-kokoro.py index 6381e994f..ffebd9315 100644 --- a/examples/foundational/07zj-interruptible-kokoro.py +++ b/examples/foundational/07zj-interruptible-kokoro.py @@ -41,17 +41,14 @@ transport_params = { "daily": lambda: DailyParams( audio_in_enabled=True, audio_out_enabled=True, - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), "twilio": lambda: FastAPIWebsocketParams( audio_in_enabled=True, audio_out_enabled=True, - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), "webrtc": lambda: TransportParams( audio_in_enabled=True, audio_out_enabled=True, - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), } @@ -79,6 +76,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): user_turn_strategies=UserTurnStrategies( stop=[TurnAnalyzerUserTurnStopStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3())] ), + vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), ) From e7792339189fde00d9f11f4b0e6bf1896be1b252 Mon Sep 17 00:00:00 2001 From: Mark Backman Date: Fri, 30 Jan 2026 21:01:35 -0500 Subject: [PATCH 0316/1060] Fix IVRNavigator to push AggregatedTextFrame when switching to conversation mode --- changelog/3604.fixed.md | 1 + src/pipecat/extensions/ivr/ivr_navigator.py | 11 +++++++++-- tests/test_ivr_navigation.py | 3 ++- 3 files changed, 12 insertions(+), 3 deletions(-) create mode 100644 changelog/3604.fixed.md diff --git a/changelog/3604.fixed.md b/changelog/3604.fixed.md new file mode 100644 index 000000000..257e1c630 --- /dev/null +++ b/changelog/3604.fixed.md @@ -0,0 +1 @@ +- Fixed an issue in the `IVRNavigator` where the `TextFrame`s pushed had incorrect spacing. Now, the internal `IVRProcessor` pushes `AggregatedTextFrame`s when in conversation mode. This allows for controlling spacing of the outputted, aggregated text. \ No newline at end of file diff --git a/src/pipecat/extensions/ivr/ivr_navigator.py b/src/pipecat/extensions/ivr/ivr_navigator.py index 0c299d634..64a6d0942 100644 --- a/src/pipecat/extensions/ivr/ivr_navigator.py +++ b/src/pipecat/extensions/ivr/ivr_navigator.py @@ -18,6 +18,7 @@ from loguru import logger from pipecat.audio.dtmf.types import KeypadEntry from pipecat.audio.vad.vad_analyzer import VADParams from pipecat.frames.frames import ( + AggregatedTextFrame, EndFrame, Frame, LLMContextFrame, @@ -153,13 +154,19 @@ class IVRProcessor(FrameProcessor): # Process text through the pattern aggregator async for result in self._aggregator.aggregate(frame.text): # Push aggregated text that doesn't contain XML patterns - await self.push_frame(LLMTextFrame(result.text), direction) + await self.push_frame( + AggregatedTextFrame(text=result.text, aggregated_by=result.type), + direction, + ) elif isinstance(frame, (LLMFullResponseEndFrame, EndFrame)): # Flush any remaining text from the aggregator remaining = await self._aggregator.flush() if remaining: - await self.push_frame(LLMTextFrame(remaining.text), direction) + await self.push_frame( + AggregatedTextFrame(text=remaining.text, aggregated_by=remaining.type), + direction, + ) # Push the end frame await self.push_frame(frame, direction) diff --git a/tests/test_ivr_navigation.py b/tests/test_ivr_navigation.py index ee43bdf62..e1737437a 100644 --- a/tests/test_ivr_navigation.py +++ b/tests/test_ivr_navigation.py @@ -10,6 +10,7 @@ from unittest.mock import AsyncMock from pipecat.audio.vad.vad_analyzer import VADParams from pipecat.extensions.ivr.ivr_navigator import IVRProcessor from pipecat.frames.frames import ( + AggregatedTextFrame, LLMFullResponseEndFrame, LLMMessagesUpdateFrame, LLMTextFrame, @@ -339,7 +340,7 @@ class TestIVRNavigation(unittest.IsolatedAsyncioTestCase): ] expected_down_frames = [ - LLMTextFrame, # Should pass through unchanged + AggregatedTextFrame, # LLMTextFrames aggregrated and converted to AggregatedTextFrame LLMFullResponseEndFrame, ] From fee633cb92053ff5c9d0f999cbb4da5504109b2e Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Aleix=20Conchillo=20Flaqu=C3=A9?= Date: Fri, 30 Jan 2026 21:23:42 -0800 Subject: [PATCH 0317/1060] scripts(evals): disable kokoro for now --- scripts/evals/run-release-evals.py | 3 ++- 1 file changed, 2 insertions(+), 1 deletion(-) diff --git a/scripts/evals/run-release-evals.py b/scripts/evals/run-release-evals.py index f0e2e9a89..0fbc4af57 100644 --- a/scripts/evals/run-release-evals.py +++ b/scripts/evals/run-release-evals.py @@ -144,7 +144,8 @@ TESTS_07 = [ ("07zg-interruptible-camb.py", EVAL_SIMPLE_MATH), ("07zh-interruptible-hathora.py", EVAL_SIMPLE_MATH), ("07zi-interruptible-piper.py", EVAL_SIMPLE_MATH), - ("07zj-interruptible-kokoro.py", EVAL_SIMPLE_MATH), + # Some issue with loguru. + # ("07zj-interruptible-kokoro.py", EVAL_SIMPLE_MATH), # Needs a local XTTS docker instance running. # ("07i-interruptible-xtts.py", EVAL_SIMPLE_MATH), # Needs a Krisp license. From d87f3543c7ccb441f868ec217bbc8e753a34468b Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Aleix=20Conchillo=20Flaqu=C3=A9?= Date: Fri, 30 Jan 2026 22:33:39 -0800 Subject: [PATCH 0318/1060] GeminiLiveLLMService: let the transcription timeout handler be scheduled --- changelog/3605.fixed.md | 1 + src/pipecat/services/google/gemini_live/llm.py | 2 ++ 2 files changed, 3 insertions(+) create mode 100644 changelog/3605.fixed.md diff --git a/changelog/3605.fixed.md b/changelog/3605.fixed.md new file mode 100644 index 000000000..405dc4db2 --- /dev/null +++ b/changelog/3605.fixed.md @@ -0,0 +1 @@ +- Fixed `GeminiLiveLLMService` transcription timeout handler not being scheduled by yielding to the event loop after task creation. diff --git a/src/pipecat/services/google/gemini_live/llm.py b/src/pipecat/services/google/gemini_live/llm.py index 895489955..e209f3d0a 100644 --- a/src/pipecat/services/google/gemini_live/llm.py +++ b/src/pipecat/services/google/gemini_live/llm.py @@ -1689,6 +1689,8 @@ class GeminiLiveLLMService(LLMService): self._transcription_timeout_task = self.create_task( self._transcription_timeout_handler() ) + # Let the event loop schedule the taks before it gets cancelled. + await asyncio.sleep(0) async def _handle_msg_output_transcription(self, message: LiveServerMessage): """Handle the output transcription message.""" From ef51c2a5c6aa6fb0ed53d0f55427eb6e329e4d80 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Aleix=20Conchillo=20Flaqu=C3=A9?= Date: Fri, 30 Jan 2026 22:48:26 -0800 Subject: [PATCH 0319/1060] changelog: fix 3582 changed file --- changelog/{3582.change.md => 3582.changed.md} | 0 1 file changed, 0 insertions(+), 0 deletions(-) rename changelog/{3582.change.md => 3582.changed.md} (100%) diff --git a/changelog/3582.change.md b/changelog/3582.changed.md similarity index 100% rename from changelog/3582.change.md rename to changelog/3582.changed.md From 614b8e1a62cd0633cfa5279620653cfdacea4053 Mon Sep 17 00:00:00 2001 From: aconchillo <951761+aconchillo@users.noreply.github.com> Date: Sat, 31 Jan 2026 06:51:06 +0000 Subject: [PATCH 0320/1060] Update changelog for version 0.0.101 --- CHANGELOG.md | 252 +++++++++++++++++++++++++++++++++++ changelog/3406.fixed.md | 1 - changelog/3408.added.md | 4 - changelog/3408.changed.md | 1 - changelog/3408.removed.md | 1 - changelog/3429.added.md | 1 - changelog/3495.changed.2.md | 1 - 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2026-01-30 + +### Added + +- Additions for `AICFilter` and `AICVADAnalyzer`: + - Added model downloading support to `AICFilter` with `model_id` and + `model_download_dir` parameters. + - Added `model_path` parameter to `AICFilter` for loading local `.aicmodel` + files. + - Added unit tests for `AICFilter` and `AICVADAnalyzer`. + (PR [#3408](https://github.com/pipecat-ai/pipecat/pull/3408)) + +- Added handling for `server_content.interrupted` signal in the Gemini Live + service for faster interruption response in the case where there isn't + already turn tracking in the pipeline, e.g. local VAD + context aggregators. + When there is already turn tracking in the pipeline, the additional + interruption does no harm. + (PR [#3429](https://github.com/pipecat-ai/pipecat/pull/3429)) + +- Added new `GenesysFrameSerializer` for the Genesys AudioHook WebSocket + protocol, enabling bidirectional audio streaming between Pipecat pipelines + and Genesys Cloud contact center. + (PR [#3500](https://github.com/pipecat-ai/pipecat/pull/3500)) + +- Added `reached_upstream_types` and `reached_downstream_types` read-only + properties to `PipelineTask` for inspecting current frame filters. + (PR [#3510](https://github.com/pipecat-ai/pipecat/pull/3510)) + +- Added `add_reached_upstream_filter()` and `add_reached_downstream_filter()` + methods to `PipelineTask` for appending frame types. + (PR [#3510](https://github.com/pipecat-ai/pipecat/pull/3510)) + +- Added `UserTurnCompletionLLMServiceMixin` for LLM services to detect and + filter incomplete user turns. When enabled via `filter_incomplete_user_turns` + in `LLMUserAggregatorParams`, the LLM outputs a turn completion marker at the + start of each response: ✓ (complete), ○ (incomplete short), or ◐ (incomplete + long). Incomplete turns are suppressed, and configurable timeouts + automatically re-prompt the user. + (PR [#3518](https://github.com/pipecat-ai/pipecat/pull/3518)) + +- Added `FrameProcessor.broadcast_frame_instance(frame)` method to broadcast a + frame instance by extracting its fields and creating new instances for each + direction. + (PR [#3519](https://github.com/pipecat-ai/pipecat/pull/3519)) + +- `PipelineTask` now automatically adds `RTVIProcessor` and registers + `RTVIObserver` when `enable_rtvi=True` (default), simplifying pipeline setup. + (PR [#3519](https://github.com/pipecat-ai/pipecat/pull/3519)) + +- Added `RTVIProcessor.create_rtvi_observer()` factory method for creating RTVI + observers. + (PR [#3519](https://github.com/pipecat-ai/pipecat/pull/3519)) + +- Added `video_out_codec` parameter to `TransportParams` allowing configuration + of the preferred video codec (e.g., `"VP8"`, `"H264"`, `"H265"`) for video + output in `DailyTransport`. + (PR [#3520](https://github.com/pipecat-ai/pipecat/pull/3520)) + +- Added `location` parameter to Google TTS services (`GoogleHttpTTSService`, + `GoogleTTSService`, `GeminiTTSService`) for regional endpoint support. + (PR [#3523](https://github.com/pipecat-ai/pipecat/pull/3523)) + +- Added new `PIPECAT_SMART_TURN_LOG_DATA` environment variable, which causes + Smart Turn input data to be saved to disk + (PR [#3525](https://github.com/pipecat-ai/pipecat/pull/3525)) + +- Added `result_callback` parameter to `UserImageRequestFrame` to support + deferred function call results. + (PR [#3571](https://github.com/pipecat-ai/pipecat/pull/3571)) + +- Added `function_call_timeout_secs` parameter to `LLMService` to configure + timeout for deferred function calls (defaults to 10.0 seconds). + (PR [#3571](https://github.com/pipecat-ai/pipecat/pull/3571)) + +- Added `vad_analyzer` parameter to `LLMUserAggregatorParams`. VAD analysis is + now handled inside the `LLMUserAggregator` rather than in the transport, + keeping voice activity detection closer to where it is consumed. The + `vad_analyzer` on `BaseInputTransport` is now deprecated. + + ```python + context_aggregator = LLMContextAggregatorPair( + context, + user_params=LLMUserAggregatorParams( + vad_analyzer=SileroVADAnalyzer(), + ), + ) + ``` + (PR [#3583](https://github.com/pipecat-ai/pipecat/pull/3583)) + +- Added `VADProcessor` for detecting speech in audio streams within a pipeline. + Pushes `VADUserStartedSpeakingFrame`, `VADUserStoppedSpeakingFrame`, and + `UserSpeakingFrame` downstream based on VAD state changes. + (PR [#3583](https://github.com/pipecat-ai/pipecat/pull/3583)) + +- Added `VADController` for managing voice activity detection state and + emitting speech events independently of transport or pipeline processors. + (PR [#3583](https://github.com/pipecat-ai/pipecat/pull/3583)) + +- Added local `PiperTTSService` for offline text-to-speech using Piper voice + models. The existing HTTP-based service has been renamed to + `PiperHttpTTSService`. + (PR [#3585](https://github.com/pipecat-ai/pipecat/pull/3585)) + +- `main()` in `pipecat.runner.run` now accepts an optional + `argparse.ArgumentParser`, allowing bots to define custom CLI arguments + accessible via `runner_args.cli_args`. + (PR [#3590](https://github.com/pipecat-ai/pipecat/pull/3590)) + +- Added `KokoroTTSService` for local text-to-speech synthesis using the + Kokoro-82M model. + (PR [#3595](https://github.com/pipecat-ai/pipecat/pull/3595)) + +### Changed + +- Updated `AICFilter` and `AICVADAnalyzer` to use aic-sdk ~= 2.0.1. + (PR [#3408](https://github.com/pipecat-ai/pipecat/pull/3408)) + +- Improved the STT TTFB (Time To First Byte) measurement, reporting the delay + between when the user stops speaking and when the final transcription is + received. Note: Unlike traditional TTFB which measures from a discrete + request, STT services receive continuous audio input—so we measure from + speech end to final transcript, which captures the latency that matters for + voice AI applications. In support of this change, added `finalized` field to + `TranscriptionFrame` to indicate when a transcript is the final result for an + utterance. + (PR [#3495](https://github.com/pipecat-ai/pipecat/pull/3495)) + +- `SarvamSTTService` now defaults `vad_signals` and `high_vad_sensitivity` to + `None` (omitted from connection parameters), improving latency by ~300ms + compared to the previous defaults. + (PR [#3495](https://github.com/pipecat-ai/pipecat/pull/3495)) + +- Changed frame filter storage from tuples to sets in `PipelineTask`. + (PR [#3510](https://github.com/pipecat-ai/pipecat/pull/3510)) + +- Changed default Inworld TTS model from `inworld-tts-1` to + `inworld-tts-1.5-max`. + (PR [#3531](https://github.com/pipecat-ai/pipecat/pull/3531)) + +- `FrameSerializer` now subclasses from `BaseObject` to enable event support. + (PR [#3560](https://github.com/pipecat-ai/pipecat/pull/3560)) + +- Added support for TTFS in `SpeechmaticsSTTService` and set the default mode + to `EXTERNAL` to support Pipecat-controlled VAD. + - Changed dependency to `speechmatics-voice[smart]>=0.2.8` + (PR [#3562](https://github.com/pipecat-ai/pipecat/pull/3562)) + +- ⚠️ Changed function call handling to use timeout-based completion instead of + immediate callback execution. + - Function calls that defer their results (e.g., `UserImageRequestFrame`) + now use a timeout mechanism + - The `result_callback` is invoked automatically when the deferred + operation completes or after timeout + - This change affects examples using `UserImageRequestFrame` - the + `result_callback` should now be passed to the frame instead of being called + immediately + (PR [#3571](https://github.com/pipecat-ai/pipecat/pull/3571)) + +- Pipecat runner now uses `DAILY_ROOM_URL` instead of `DAILY_SAMPLE_ROOM_URL`. + (PR [#3582](https://github.com/pipecat-ai/pipecat/pull/3582)) + +- Updates to `GradiumSTTService`: + - Now flushes pending transcriptions when VAD detects the user stopped + speaking, improving response latency. + - `GradiumSTTService` now supports `InputParams` for configuring `language` + and `delay_in_frames` settings. + (PR [#3587](https://github.com/pipecat-ai/pipecat/pull/3587)) + +### Deprecated + +- ⚠️ Deprecated `vad_analyzer` parameter on `BaseInputTransport`. Pass + `vad_analyzer` to `LLMUserAggregatorParams` instead or use `VADProcessor` in + the pipeline. + (PR [#3583](https://github.com/pipecat-ai/pipecat/pull/3583)) + +### Removed + +- Removed deprecated `AICFilter` parameters: `enhancement_level`, `voice_gain`, + `noise_gate_enable`. + (PR [#3408](https://github.com/pipecat-ai/pipecat/pull/3408)) + +### Fixed + +- Fixed an issue where if you were using `OpenRouterLLMService` with a Gemini + model, it wouldn't handle multiple `"system"` messages as expected (and as we + do in `GoogleLLMService`), which is to convert subsequent ones into `"user"` + messages. Instead, the latest `"system"` message would overwrite the previous + ones. + (PR [#3406](https://github.com/pipecat-ai/pipecat/pull/3406)) + +- Transports now properly broadcast `InputTransportMessageFrame` frames both + upstream and downstream instead of only pushing downstream. + (PR [#3519](https://github.com/pipecat-ai/pipecat/pull/3519)) + +- Fixed `FrameProcessor.broadcast_frame()` to deep copy kwargs, preventing + shared mutable references between the downstream and upstream frame + instances. + (PR [#3519](https://github.com/pipecat-ai/pipecat/pull/3519)) + +- Fixed OpenAI LLM services to emit `ErrorFrame` on completion timeout, + enabling proper error handling and LLMSwitcher failover. + (PR [#3529](https://github.com/pipecat-ai/pipecat/pull/3529)) + +- Fixed a logging issue where non-ASCII characters (e.g., Japanese, Chinese, + etc.) were being unnecessarily escaped to Unicode sequences when function + call occurred. + (PR [#3536](https://github.com/pipecat-ai/pipecat/pull/3536)) + +- Fixed how audio tracks are synchronized inside the `AudioBufferProcessor` to + fix timing issues where silence and audio were misaligned between user and + bot buffers. + (PR [#3541](https://github.com/pipecat-ai/pipecat/pull/3541)) + +- Fixed race condition in `OpenAIRealtimeBetaLLMService` that could cause an + error when truncating the conversation. + (PR [#3567](https://github.com/pipecat-ai/pipecat/pull/3567)) + +- Fixed an infinite loop in `WebsocketService` that blocked the event loop when + a remote server closed the connection gracefully. + (PR [#3574](https://github.com/pipecat-ai/pipecat/pull/3574)) + +- Fixed `LLMUserAggregator` and `LLMAssistantAggregator` not emitting pending + transcripts via `on_user_turn_stopped` and `on_assistant_turn_stopped` events + when the conversation ends (`EndFrame`) or is cancelled (`CancelFrame`). + (PR [#3575](https://github.com/pipecat-ai/pipecat/pull/3575)) + +- Added missing `LiveKitRunnerArguments` and `LiveKitTransport` support in + runner utilities to enable LiveKit transport configuration. + (PR [#3580](https://github.com/pipecat-ai/pipecat/pull/3580)) + +- Fixed race condition in `OpenAIRealtimeLLMService` that could cause an error + when truncating the conversation. + (PR [#3581](https://github.com/pipecat-ai/pipecat/pull/3581)) + +- Fixed `PiperHttpTTSService` (olf `PiperTTSService`) to resample audio output + based on the model's sample rate parsed from the WAV header. + (PR [#3585](https://github.com/pipecat-ai/pipecat/pull/3585)) + +- Fixed `UserTurnController` to reset user turn timeout when interim + transcriptions are received. + (PR [#3594](https://github.com/pipecat-ai/pipecat/pull/3594)) + +- Fixed an issue in the `IVRNavigator` where the `TextFrame`s pushed had + incorrect spacing. Now, the internal `IVRProcessor` pushes + `AggregatedTextFrame`s when in conversation mode. This allows for controlling + spacing of the outputted, aggregated text. + (PR [#3604](https://github.com/pipecat-ai/pipecat/pull/3604)) + +- Fixed `GeminiLiveLLMService` transcription timeout handler not being + scheduled by yielding to the event loop after task creation. + (PR [#3605](https://github.com/pipecat-ai/pipecat/pull/3605)) + ## [0.0.100] - 2026-01-20 ### Added diff --git a/changelog/3406.fixed.md b/changelog/3406.fixed.md deleted file mode 100644 index b4eae4548..000000000 --- a/changelog/3406.fixed.md +++ /dev/null @@ -1 +0,0 @@ -- Fixed an issue where if you were using `OpenRouterLLMService` with a Gemini model, it wouldn't handle multiple `"system"` messages as expected (and as we do in `GoogleLLMService`), which is to convert subsequent ones into `"user"` messages. Instead, the latest `"system"` message would overwrite the previous ones. diff --git a/changelog/3408.added.md b/changelog/3408.added.md deleted file mode 100644 index 04f1311cc..000000000 --- a/changelog/3408.added.md +++ /dev/null @@ -1,4 +0,0 @@ -- Additions for `AICFilter` and `AICVADAnalyzer`: - - Added model downloading support to `AICFilter` with `model_id` and `model_download_dir` parameters. - - Added `model_path` parameter to `AICFilter` for loading local `.aicmodel` files. - - Added unit tests for `AICFilter` and `AICVADAnalyzer`. diff --git a/changelog/3408.changed.md b/changelog/3408.changed.md deleted file mode 100644 index 9436b6074..000000000 --- a/changelog/3408.changed.md +++ /dev/null @@ -1 +0,0 @@ -- Updated `AICFilter` and `AICVADAnalyzer` to use aic-sdk ~= 2.0.1. diff --git a/changelog/3408.removed.md b/changelog/3408.removed.md deleted file mode 100644 index f578bf5d0..000000000 --- a/changelog/3408.removed.md +++ /dev/null @@ -1 +0,0 @@ -- Removed deprecated `AICFilter` parameters: `enhancement_level`, `voice_gain`, `noise_gate_enable`. diff --git a/changelog/3429.added.md b/changelog/3429.added.md deleted file mode 100644 index 905dcac78..000000000 --- a/changelog/3429.added.md +++ /dev/null @@ -1 +0,0 @@ -- Added handling for `server_content.interrupted` signal in the Gemini Live service for faster interruption response in the case where there isn't already turn tracking in the pipeline, e.g. local VAD + context aggregators. When there is already turn tracking in the pipeline, the additional interruption does no harm. diff --git a/changelog/3495.changed.2.md b/changelog/3495.changed.2.md deleted file mode 100644 index cf1f526b8..000000000 --- a/changelog/3495.changed.2.md +++ /dev/null @@ -1 +0,0 @@ -- `SarvamSTTService` now defaults `vad_signals` and `high_vad_sensitivity` to `None` (omitted from connection parameters), improving latency by ~300ms compared to the previous defaults. diff --git a/changelog/3495.changed.md b/changelog/3495.changed.md deleted file mode 100644 index c690ebc09..000000000 --- a/changelog/3495.changed.md +++ /dev/null @@ -1 +0,0 @@ -- Improved the STT TTFB (Time To First Byte) measurement, reporting the delay between when the user stops speaking and when the final transcription is received. Note: Unlike traditional TTFB which measures from a discrete request, STT services receive continuous audio input—so we measure from speech end to final transcript, which captures the latency that matters for voice AI applications. In support of this change, added `finalized` field to `TranscriptionFrame` to indicate when a transcript is the final result for an utterance. diff --git a/changelog/3500.added.md b/changelog/3500.added.md deleted file mode 100644 index 64881e91b..000000000 --- a/changelog/3500.added.md +++ /dev/null @@ -1 +0,0 @@ -- Added new `GenesysFrameSerializer` for the Genesys AudioHook WebSocket protocol, enabling bidirectional audio streaming between Pipecat pipelines and Genesys Cloud contact center. \ No newline at end of file diff --git a/changelog/3510.added.2.md b/changelog/3510.added.2.md deleted file mode 100644 index e03b81ee3..000000000 --- a/changelog/3510.added.2.md +++ /dev/null @@ -1 +0,0 @@ -- Added `add_reached_upstream_filter()` and `add_reached_downstream_filter()` methods to `PipelineTask` for appending frame types. \ No newline at end of file diff --git a/changelog/3510.added.md b/changelog/3510.added.md deleted file mode 100644 index 93d9ef179..000000000 --- a/changelog/3510.added.md +++ /dev/null @@ -1 +0,0 @@ -- Added `reached_upstream_types` and `reached_downstream_types` read-only properties to `PipelineTask` for inspecting current frame filters. \ No newline at end of file diff --git a/changelog/3510.changed.3.md b/changelog/3510.changed.3.md deleted file mode 100644 index ac299f143..000000000 --- a/changelog/3510.changed.3.md +++ /dev/null @@ -1 +0,0 @@ -- Changed frame filter storage from tuples to sets in `PipelineTask`. diff --git a/changelog/3518.added.md b/changelog/3518.added.md deleted file mode 100644 index b9740f024..000000000 --- a/changelog/3518.added.md +++ /dev/null @@ -1 +0,0 @@ -- Added `UserTurnCompletionLLMServiceMixin` for LLM services to detect and filter incomplete user turns. When enabled via `filter_incomplete_user_turns` in `LLMUserAggregatorParams`, the LLM outputs a turn completion marker at the start of each response: ✓ (complete), ○ (incomplete short), or ◐ (incomplete long). Incomplete turns are suppressed, and configurable timeouts automatically re-prompt the user. diff --git a/changelog/3519.added.2.md b/changelog/3519.added.2.md deleted file mode 100644 index 03e2372ad..000000000 --- a/changelog/3519.added.2.md +++ /dev/null @@ -1 +0,0 @@ -- Added `RTVIProcessor.create_rtvi_observer()` factory method for creating RTVI observers. diff --git a/changelog/3519.added.3.md b/changelog/3519.added.3.md deleted file mode 100644 index 7ea1e638c..000000000 --- a/changelog/3519.added.3.md +++ /dev/null @@ -1 +0,0 @@ -- Added `FrameProcessor.broadcast_frame_instance(frame)` method to broadcast a frame instance by extracting its fields and creating new instances for each direction. diff --git a/changelog/3519.added.md b/changelog/3519.added.md deleted file mode 100644 index 5ed2bd522..000000000 --- a/changelog/3519.added.md +++ /dev/null @@ -1 +0,0 @@ -- `PipelineTask` now automatically adds `RTVIProcessor` and registers `RTVIObserver` when `enable_rtvi=True` (default), simplifying pipeline setup. diff --git a/changelog/3519.fixed.2.md b/changelog/3519.fixed.2.md deleted file mode 100644 index bcd384f7f..000000000 --- a/changelog/3519.fixed.2.md +++ /dev/null @@ -1 +0,0 @@ -- Fixed `FrameProcessor.broadcast_frame()` to deep copy kwargs, preventing shared mutable references between the downstream and upstream frame instances. diff --git a/changelog/3519.fixed.md b/changelog/3519.fixed.md deleted file mode 100644 index cabaa5a3e..000000000 --- a/changelog/3519.fixed.md +++ /dev/null @@ -1 +0,0 @@ -- Transports now properly broadcast `InputTransportMessageFrame` frames both upstream and downstream instead of only pushing downstream. diff --git a/changelog/3520.added.md b/changelog/3520.added.md deleted file mode 100644 index 6e3c37e9f..000000000 --- a/changelog/3520.added.md +++ /dev/null @@ -1 +0,0 @@ -- Added `video_out_codec` parameter to `TransportParams` allowing configuration of the preferred video codec (e.g., `"VP8"`, `"H264"`, `"H265"`) for video output in `DailyTransport`. diff --git a/changelog/3523.added.md b/changelog/3523.added.md deleted file mode 100644 index c6a0acc42..000000000 --- a/changelog/3523.added.md +++ /dev/null @@ -1 +0,0 @@ -- Added `location` parameter to Google TTS services (`GoogleHttpTTSService`, `GoogleTTSService`, `GeminiTTSService`) for regional endpoint support. \ No newline at end of file diff --git a/changelog/3525.added.md b/changelog/3525.added.md deleted file mode 100644 index e34b5e3d5..000000000 --- a/changelog/3525.added.md +++ /dev/null @@ -1 +0,0 @@ -- Added new `PIPECAT_SMART_TURN_LOG_DATA` environment variable, which causes Smart Turn input data to be saved to disk diff --git a/changelog/3529.fixed.md b/changelog/3529.fixed.md deleted file mode 100644 index 91c9eeda0..000000000 --- a/changelog/3529.fixed.md +++ /dev/null @@ -1 +0,0 @@ -- Fixed OpenAI LLM services to emit `ErrorFrame` on completion timeout, enabling proper error handling and LLMSwitcher failover. diff --git a/changelog/3531.changed.md b/changelog/3531.changed.md deleted file mode 100644 index 326d8d4d1..000000000 --- a/changelog/3531.changed.md +++ /dev/null @@ -1,2 +0,0 @@ -- Changed default Inworld TTS model from `inworld-tts-1` to - `inworld-tts-1.5-max`. diff --git a/changelog/3536.fixed.md b/changelog/3536.fixed.md deleted file mode 100644 index f70bd62b6..000000000 --- a/changelog/3536.fixed.md +++ /dev/null @@ -1 +0,0 @@ -- Fixed a logging issue where non-ASCII characters (e.g., Japanese, Chinese, etc.) were being unnecessarily escaped to Unicode sequences when function call occurred. diff --git a/changelog/3541.fixed.md b/changelog/3541.fixed.md deleted file mode 100644 index ac5b59529..000000000 --- a/changelog/3541.fixed.md +++ /dev/null @@ -1 +0,0 @@ -- Fixed how audio tracks are synchronized inside the `AudioBufferProcessor` to fix timing issues where silence and audio were misaligned between user and bot buffers. diff --git a/changelog/3560.changed.md b/changelog/3560.changed.md deleted file mode 100644 index b4ba6aa8b..000000000 --- a/changelog/3560.changed.md +++ /dev/null @@ -1 +0,0 @@ -- `FrameSerializer` now subclasses from `BaseObject` to enable event support. diff --git a/changelog/3562.changed.md b/changelog/3562.changed.md deleted file mode 100644 index 533f37b2f..000000000 --- a/changelog/3562.changed.md +++ /dev/null @@ -1,2 +0,0 @@ -- Added support for TTFS in `SpeechmaticsSTTService` and set the default mode to `EXTERNAL` to support Pipecat-controlled VAD. -- Changed dependency to `speechmatics-voice[smart]>=0.2.8` diff --git a/changelog/3567.fixed.md b/changelog/3567.fixed.md deleted file mode 100644 index 92ecabeca..000000000 --- a/changelog/3567.fixed.md +++ /dev/null @@ -1 +0,0 @@ -- Fixed race condition in `OpenAIRealtimeBetaLLMService` that could cause an error when truncating the conversation. diff --git a/changelog/3571.added.2.md b/changelog/3571.added.2.md deleted file mode 100644 index f9af8dde0..000000000 --- a/changelog/3571.added.2.md +++ /dev/null @@ -1 +0,0 @@ -- Added `function_call_timeout_secs` parameter to `LLMService` to configure timeout for deferred function calls (defaults to 10.0 seconds). diff --git a/changelog/3571.added.md b/changelog/3571.added.md deleted file mode 100644 index 927bbcbc4..000000000 --- a/changelog/3571.added.md +++ /dev/null @@ -1 +0,0 @@ -- Added `result_callback` parameter to `UserImageRequestFrame` to support deferred function call results. diff --git a/changelog/3571.changed.md b/changelog/3571.changed.md deleted file mode 100644 index eb44cae0a..000000000 --- a/changelog/3571.changed.md +++ /dev/null @@ -1,4 +0,0 @@ -- ⚠️ Changed function call handling to use timeout-based completion instead of immediate callback execution. - - Function calls that defer their results (e.g., `UserImageRequestFrame`) now use a timeout mechanism - - The `result_callback` is invoked automatically when the deferred operation completes or after timeout - - This change affects examples using `UserImageRequestFrame` - the `result_callback` should now be passed to the frame instead of being called immediately diff --git a/changelog/3574.fixed.md b/changelog/3574.fixed.md deleted file mode 100644 index 187f172b7..000000000 --- a/changelog/3574.fixed.md +++ /dev/null @@ -1 +0,0 @@ -- Fixed an infinite loop in `WebsocketService` that blocked the event loop when a remote server closed the connection gracefully. \ No newline at end of file diff --git a/changelog/3575.fixed.md b/changelog/3575.fixed.md deleted file mode 100644 index 03c42b1ad..000000000 --- a/changelog/3575.fixed.md +++ /dev/null @@ -1 +0,0 @@ -- Fixed `LLMUserAggregator` and `LLMAssistantAggregator` not emitting pending transcripts via `on_user_turn_stopped` and `on_assistant_turn_stopped` events when the conversation ends (`EndFrame`) or is cancelled (`CancelFrame`). diff --git a/changelog/3580.fixed.md b/changelog/3580.fixed.md deleted file mode 100644 index 47f4aa6a2..000000000 --- a/changelog/3580.fixed.md +++ /dev/null @@ -1 +0,0 @@ -- Added missing `LiveKitRunnerArguments` and `LiveKitTransport` support in runner utilities to enable LiveKit transport configuration. diff --git a/changelog/3581.fixed.md b/changelog/3581.fixed.md deleted file mode 100644 index 688bbcfbe..000000000 --- a/changelog/3581.fixed.md +++ /dev/null @@ -1 +0,0 @@ -- Fixed race condition in `OpenAIRealtimeLLMService` that could cause an error when truncating the conversation. \ No newline at end of file diff --git a/changelog/3582.changed.md b/changelog/3582.changed.md deleted file mode 100644 index 8581fc6cf..000000000 --- a/changelog/3582.changed.md +++ /dev/null @@ -1 +0,0 @@ -- Pipecat runner now uses `DAILY_ROOM_URL` instead of `DAILY_SAMPLE_ROOM_URL`. diff --git a/changelog/3583.added.2.md b/changelog/3583.added.2.md deleted file mode 100644 index f0c5c7d1e..000000000 --- a/changelog/3583.added.2.md +++ /dev/null @@ -1 +0,0 @@ -- Added `VADController` for managing voice activity detection state and emitting speech events independently of transport or pipeline processors. diff --git a/changelog/3583.added.3.md b/changelog/3583.added.3.md deleted file mode 100644 index f5da90407..000000000 --- a/changelog/3583.added.3.md +++ /dev/null @@ -1 +0,0 @@ -- Added `VADProcessor` for detecting speech in audio streams within a pipeline. Pushes `VADUserStartedSpeakingFrame`, `VADUserStoppedSpeakingFrame`, and `UserSpeakingFrame` downstream based on VAD state changes. diff --git a/changelog/3583.added.md b/changelog/3583.added.md deleted file mode 100644 index 47048e226..000000000 --- a/changelog/3583.added.md +++ /dev/null @@ -1,10 +0,0 @@ -- Added `vad_analyzer` parameter to `LLMUserAggregatorParams`. VAD analysis is now handled inside the `LLMUserAggregator` rather than in the transport, keeping voice activity detection closer to where it is consumed. The `vad_analyzer` on `BaseInputTransport` is now deprecated. - - ```python - context_aggregator = LLMContextAggregatorPair( - context, - user_params=LLMUserAggregatorParams( - vad_analyzer=SileroVADAnalyzer(), - ), - ) - ``` diff --git a/changelog/3583.deprecated.md b/changelog/3583.deprecated.md deleted file mode 100644 index d4ea492eb..000000000 --- a/changelog/3583.deprecated.md +++ /dev/null @@ -1 +0,0 @@ -- ⚠️ Deprecated `vad_analyzer` parameter on `BaseInputTransport`. Pass `vad_analyzer` to `LLMUserAggregatorParams` instead or use `VADProcessor` in the pipeline. diff --git a/changelog/3585.added.md b/changelog/3585.added.md deleted file mode 100644 index 7335d2c18..000000000 --- a/changelog/3585.added.md +++ /dev/null @@ -1 +0,0 @@ -- Added local `PiperTTSService` for offline text-to-speech using Piper voice models. The existing HTTP-based service has been renamed to `PiperHttpTTSService`. diff --git a/changelog/3585.fixed.md b/changelog/3585.fixed.md deleted file mode 100644 index 4993ed2f7..000000000 --- a/changelog/3585.fixed.md +++ /dev/null @@ -1 +0,0 @@ -- Fixed `PiperHttpTTSService` (olf `PiperTTSService`) to resample audio output based on the model's sample rate parsed from the WAV header. diff --git a/changelog/3587.changed.md b/changelog/3587.changed.md deleted file mode 100644 index 94ccd7020..000000000 --- a/changelog/3587.changed.md +++ /dev/null @@ -1,3 +0,0 @@ -- Updates to `GradiumSTTService`: - - Now flushes pending transcriptions when VAD detects the user stopped speaking, improving response latency. - - `GradiumSTTService` now supports `InputParams` for configuring `language` and `delay_in_frames` settings. diff --git a/changelog/3590.added.md b/changelog/3590.added.md deleted file mode 100644 index 80e0c3dba..000000000 --- a/changelog/3590.added.md +++ /dev/null @@ -1 +0,0 @@ -- `main()` in `pipecat.runner.run` now accepts an optional `argparse.ArgumentParser`, allowing bots to define custom CLI arguments accessible via `runner_args.cli_args`. diff --git a/changelog/3594.fixed.md b/changelog/3594.fixed.md deleted file mode 100644 index 1c47ff490..000000000 --- a/changelog/3594.fixed.md +++ /dev/null @@ -1 +0,0 @@ -- Fixed `UserTurnController` to reset user turn timeout when interim transcriptions are received. diff --git a/changelog/3595.added.md b/changelog/3595.added.md deleted file mode 100644 index 7f3213eb1..000000000 --- a/changelog/3595.added.md +++ /dev/null @@ -1 +0,0 @@ -- Added `KokoroTTSService` for local text-to-speech synthesis using the Kokoro-82M model. diff --git a/changelog/3604.fixed.md b/changelog/3604.fixed.md deleted file mode 100644 index 257e1c630..000000000 --- a/changelog/3604.fixed.md +++ /dev/null @@ -1 +0,0 @@ -- Fixed an issue in the `IVRNavigator` where the `TextFrame`s pushed had incorrect spacing. Now, the internal `IVRProcessor` pushes `AggregatedTextFrame`s when in conversation mode. This allows for controlling spacing of the outputted, aggregated text. \ No newline at end of file diff --git a/changelog/3605.fixed.md b/changelog/3605.fixed.md deleted file mode 100644 index 405dc4db2..000000000 --- a/changelog/3605.fixed.md +++ /dev/null @@ -1 +0,0 @@ -- Fixed `GeminiLiveLLMService` transcription timeout handler not being scheduled by yielding to the event loop after task creation. From a587e1b99a105677c3dcf677c83b1de88a99da6b Mon Sep 17 00:00:00 2001 From: Mark Backman Date: Sat, 31 Jan 2026 09:52:24 -0500 Subject: [PATCH 0321/1060] Update quickstart for 0.0.101 --- examples/quickstart/bot.py | 8 +------- 1 file changed, 1 insertion(+), 7 deletions(-) diff --git a/examples/quickstart/bot.py b/examples/quickstart/bot.py index bf75616d0..19a9206eb 100644 --- a/examples/quickstart/bot.py +++ b/examples/quickstart/bot.py @@ -48,7 +48,6 @@ from pipecat.processors.aggregators.llm_response_universal import ( LLMContextAggregatorPair, LLMUserAggregatorParams, ) -from pipecat.processors.frameworks.rtvi import RTVIObserver, RTVIProcessor from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport from pipecat.services.cartesia.tts import CartesiaTTSService @@ -92,15 +91,13 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): user_turn_strategies=UserTurnStrategies( stop=[TurnAnalyzerUserTurnStopStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3())] ), + vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), ) - rtvi = RTVIProcessor() - pipeline = Pipeline( [ transport.input(), # Transport user input - rtvi, # RTVI processor stt, user_aggregator, # User responses llm, # LLM @@ -116,7 +113,6 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): enable_metrics=True, enable_usage_metrics=True, ), - observers=[RTVIObserver(rtvi)], ) @transport.event_handler("on_client_connected") @@ -143,12 +139,10 @@ async def bot(runner_args: RunnerArguments): "daily": lambda: DailyParams( audio_in_enabled=True, audio_out_enabled=True, - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), "webrtc": lambda: TransportParams( audio_in_enabled=True, audio_out_enabled=True, - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), ), } From acc9923c0a3294ed55af35504ea3ceee2c015010 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Aleix=20Conchillo=20Flaqu=C3=A9?= Date: Sat, 31 Jan 2026 13:19:36 -0800 Subject: [PATCH 0322/1060] PipelineTask: don't add RTVIObserver if already there --- changelog/3610.fixed.md | 1 + src/pipecat/pipeline/task.py | 44 +++++++++++++++++++++++++++--------- 2 files changed, 34 insertions(+), 11 deletions(-) create mode 100644 changelog/3610.fixed.md diff --git a/changelog/3610.fixed.md b/changelog/3610.fixed.md new file mode 100644 index 000000000..7a004d110 --- /dev/null +++ b/changelog/3610.fixed.md @@ -0,0 +1 @@ +- Fixed `PipelineTask` adding duplicate `RTVIProcessor` and `RTVIObserver` when they were already provided in the pipeline or observers list. They are now detected and skipped, with appropriate warnings and errors logged for mismatched configurations. diff --git a/src/pipecat/pipeline/task.py b/src/pipecat/pipeline/task.py index 60df77ff9..6ae3c55a9 100644 --- a/src/pipecat/pipeline/task.py +++ b/src/pipecat/pipeline/task.py @@ -49,7 +49,7 @@ from pipecat.pipeline.pipeline import Pipeline, PipelineSink, PipelineSource from pipecat.pipeline.task_observer import TaskObserver from pipecat.processors.aggregators.llm_response import LLMUserContextAggregator from pipecat.processors.frame_processor import FrameDirection, FrameProcessor, FrameProcessorSetup -from pipecat.processors.frameworks.rtvi import RTVIObserverParams, RTVIProcessor +from pipecat.processors.frameworks.rtvi import RTVIObserver, RTVIObserverParams, RTVIProcessor from pipecat.utils.asyncio.task_manager import BaseTaskManager, TaskManager, TaskManagerParams from pipecat.utils.tracing.setup import is_tracing_available from pipecat.utils.tracing.turn_trace_observer import TurnTraceObserver @@ -315,14 +315,33 @@ class PipelineTask(BasePipelineTask): # RTVI support self._rtvi = None - if enable_rtvi: + external_rtvi = self._find_processor(pipeline, RTVIProcessor) + external_observer_found = any(isinstance(o, RTVIObserver) for o in observers) + + if external_rtvi and not external_observer_found: + logger.error( + f"{self}: RTVIProcessor found in pipeline but no RTVIObserver in observers. " + "Make sure to add both." + ) + elif not external_rtvi and external_observer_found: + logger.error( + f"{self}: RTVIObserver found in observers but no RTVIProcessor in pipeline. " + "Make sure to add both." + ) + elif external_rtvi and external_observer_found: + logger.warning( + f"{self}: RTVIProcessor and RTVIObserver found, skipping default ones. " + "They are both added by default, no need to add them yourself." + ) + elif enable_rtvi: self._rtvi = rtvi_processor or RTVIProcessor() - observers.append(self._rtvi.create_rtvi_observer(params=rtvi_observer_params)) @self.rtvi.event_handler("on_client_ready") async def on_client_ready(rtvi: RTVIProcessor): await rtvi.set_bot_ready() + observers.append(self._rtvi.create_rtvi_observer(params=rtvi_observer_params)) + # This is the idle event. When selected frames are pushed from any # processor we consider the pipeline is not idle. We use an observer # which will be listening any part of the pipeline. @@ -1012,7 +1031,7 @@ class PipelineTask(BasePipelineTask): start_metadata = {} # NOTE(aleix): Remove when OpenAILLMContext/LLMUserContextAggregator is removed. - if self._find_deprecated_openaillmcontext(self._pipeline): + if self._find_processor(self._pipeline, LLMUserContextAggregator): start_metadata["deprecated_openaillmcontext"] = True # Update with user provided metadata. @@ -1020,12 +1039,15 @@ class PipelineTask(BasePipelineTask): return start_metadata - def _find_deprecated_openaillmcontext(self, processor: FrameProcessor) -> bool: - """Check whether there is a deprecated LLMUserContextAggregator in the pipeline.""" - if isinstance(processor, LLMUserContextAggregator): - return True + def _find_processor( + self, processor: FrameProcessor, processor_type: Type[FrameProcessor] + ) -> Optional[FrameProcessor]: + """Recursively find a processor of the given type in the pipeline.""" + if isinstance(processor, processor_type): + return processor for p in processor.processors: - if self._find_deprecated_openaillmcontext(p): - return True - return False + found = self._find_processor(p, processor_type) + if found: + return found + return None From 675c7c43e381c0f94a8671eda7e819256c4c1720 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Aleix=20Conchillo=20Flaqu=C3=A9?= Date: Sat, 31 Jan 2026 15:31:15 -0800 Subject: [PATCH 0323/1060] examples: update 07zd to use vad_analyzer in LLMUserAggregator --- .../07zd-interruptible-aicoustics.py | 64 ++++++++----------- 1 file changed, 27 insertions(+), 37 deletions(-) diff --git a/examples/foundational/07zd-interruptible-aicoustics.py b/examples/foundational/07zd-interruptible-aicoustics.py index 2a355ba18..add1b04ec 100644 --- a/examples/foundational/07zd-interruptible-aicoustics.py +++ b/examples/foundational/07zd-interruptible-aicoustics.py @@ -38,13 +38,6 @@ from pipecat.turns.user_turn_strategies import UserTurnStrategies load_dotenv(override=True) -# Create audio buffer processor so we can hear the audio fitler results. -audiobuffer = AudioBufferProcessor( - num_channels=2, # 1 for mono, 2 for stereo (user left, bot right) - enable_turn_audio=False, # Enable per-turn audio recording -) - - def _create_aic_filter() -> AICFilter: license_key = os.getenv("AICOUSTICS_LICENSE_KEY", "") @@ -54,39 +47,29 @@ def _create_aic_filter() -> AICFilter: ) +aic_filter = _create_aic_filter() +aic_vad_analyzer = aic_filter.create_vad_analyzer( + speech_hold_duration=0.05, minimum_speech_duration=0.0, sensitivity=6.0 +) + # We use lambdas to defer transport parameter creation until the transport # type is selected at runtime. transport_params = { - "daily": lambda: ( - lambda aic: DailyParams( - audio_in_enabled=True, - audio_out_enabled=True, - vad_analyzer=aic.create_vad_analyzer( - speech_hold_duration=0.05, minimum_speech_duration=0.0, sensitivity=6.0 - ), - audio_in_filter=aic, - ) - )(_create_aic_filter()), - "twilio": lambda: ( - lambda aic: FastAPIWebsocketParams( - audio_in_enabled=True, - audio_out_enabled=True, - vad_analyzer=aic.create_vad_analyzer( - speech_hold_duration=0.05, minimum_speech_duration=0.0, sensitivity=6.0 - ), - audio_in_filter=aic, - ) - )(_create_aic_filter()), - "webrtc": lambda: ( - lambda aic: TransportParams( - audio_in_enabled=True, - audio_out_enabled=True, - vad_analyzer=aic.create_vad_analyzer( - speech_hold_duration=0.05, minimum_speech_duration=0.0, sensitivity=6.0 - ), - audio_in_filter=aic, - ) - )(_create_aic_filter()), + "daily": lambda: DailyParams( + audio_in_enabled=True, + audio_out_enabled=True, + audio_in_filter=aic_filter, + ), + "twilio": lambda: FastAPIWebsocketParams( + audio_in_enabled=True, + audio_out_enabled=True, + audio_in_filter=aic_filter, + ), + "webrtc": lambda: TransportParams( + audio_in_enabled=True, + audio_out_enabled=True, + audio_in_filter=aic_filter, + ), } @@ -113,12 +96,19 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, user_params=LLMUserAggregatorParams( + vad_analyzer=aic_vad_analyzer, user_turn_strategies=UserTurnStrategies( stop=[TurnAnalyzerUserTurnStopStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3())] ), ), ) + # Create audio buffer processor so we can hear the audio fitler results. + audiobuffer = AudioBufferProcessor( + num_channels=2, # 1 for mono, 2 for stereo (user left, bot right) + enable_turn_audio=False, # Enable per-turn audio recording + ) + pipeline = Pipeline( [ transport.input(), # Transport user input From 95689cc81c6dee5ecf9ae427a0a1c81817781fb6 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Aleix=20Conchillo=20Flaqu=C3=A9?= Date: Sat, 31 Jan 2026 17:18:34 -0800 Subject: [PATCH 0324/1060] KokoroTTSService: use kokoro-onnx instead of kokoro --- changelog/3612.changed.md | 1 + pyproject.toml | 2 +- scripts/evals/run-release-evals.py | 3 +- src/pipecat/services/kokoro/tts.py | 128 +++--- src/pipecat/services/piper/tts.py | 1 - uv.lock | 633 +---------------------------- 6 files changed, 89 insertions(+), 679 deletions(-) create mode 100644 changelog/3612.changed.md diff --git a/changelog/3612.changed.md b/changelog/3612.changed.md new file mode 100644 index 000000000..62323ee10 --- /dev/null +++ b/changelog/3612.changed.md @@ -0,0 +1 @@ +- Changed `KokoroTTSService` to use `kokoro-onnx` instead of `kokoro` as the underlying TTS engine. diff --git a/pyproject.toml b/pyproject.toml index f32fed9e9..4e879984a 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -75,7 +75,7 @@ heygen = [ "livekit>=1.0.13", "pipecat-ai[websockets-base]" ] hume = [ "hume>=0.11.2" ] inworld = [] koala = [ "pvkoala~=2.0.3" ] -kokoro = [ "kokoro>=0.9.4,<1", "requests>=2.32.5,<3" ] +kokoro = [ "kokoro-onnx>=0.5.0,<1", "requests>=2.32.5,<3" ] krisp = [ "pipecat-ai-krisp~=0.4.0" ] langchain = [ "langchain~=0.3.20", "langchain-community~=0.3.20", "langchain-openai~=0.3.9" ] livekit = [ "livekit~=1.0.13", "livekit-api~=1.0.5", "tenacity>=8.2.3,<10.0.0", "pyjwt>=2.10.1" ] diff --git a/scripts/evals/run-release-evals.py b/scripts/evals/run-release-evals.py index 0fbc4af57..f0e2e9a89 100644 --- a/scripts/evals/run-release-evals.py +++ b/scripts/evals/run-release-evals.py @@ -144,8 +144,7 @@ TESTS_07 = [ ("07zg-interruptible-camb.py", EVAL_SIMPLE_MATH), ("07zh-interruptible-hathora.py", EVAL_SIMPLE_MATH), ("07zi-interruptible-piper.py", EVAL_SIMPLE_MATH), - # Some issue with loguru. - # ("07zj-interruptible-kokoro.py", EVAL_SIMPLE_MATH), + ("07zj-interruptible-kokoro.py", EVAL_SIMPLE_MATH), # Needs a local XTTS docker instance running. # ("07i-interruptible-xtts.py", EVAL_SIMPLE_MATH), # Needs a Krisp license. diff --git a/src/pipecat/services/kokoro/tts.py b/src/pipecat/services/kokoro/tts.py index 21c6526f5..b4d309a3f 100644 --- a/src/pipecat/services/kokoro/tts.py +++ b/src/pipecat/services/kokoro/tts.py @@ -4,10 +4,11 @@ # SPDX-License-Identifier: BSD 2-Clause License # -"""Kokoro TTS service implementation.""" +"""Kokoro TTS service implementation using kokoro-onnx.""" -import asyncio -from typing import AsyncGenerator, AsyncIterator, Optional +import os +from pathlib import Path +from typing import AsyncGenerator, Optional import numpy as np from loguru import logger @@ -17,6 +18,7 @@ from pipecat.audio.utils import create_stream_resampler from pipecat.frames.frames import ( ErrorFrame, Frame, + TTSAudioRawFrame, TTSStartedFrame, TTSStoppedFrame, ) @@ -25,33 +27,61 @@ from pipecat.transcriptions.language import Language, resolve_language from pipecat.utils.tracing.service_decorators import traced_tts try: - from kokoro import KPipeline + import requests + from kokoro_onnx import Kokoro except ModuleNotFoundError as e: logger.error(f"Exception: {e}") logger.error("In order to use Kokoro, you need to `pip install pipecat-ai[kokoro]`.") raise Exception(f"Missing module: {e}") +KOKORO_CACHE_DIR = Path(os.path.expanduser("~/.cache/kokoro-onnx")) +KOKORO_MODEL_URL = "https://github.com/thewh1teagle/kokoro-onnx/releases/download/model-files-v1.0/kokoro-v1.0.onnx" +KOKORO_VOICES_URL = ( + "https://github.com/thewh1teagle/kokoro-onnx/releases/download/model-files-v1.0/voices-v1.0.bin" +) + + +def _download_file(url: str, dest: Path): + """Download a file from a URL to a destination path.""" + logger.debug(f"Downloading {url} to {dest}...") + dest.parent.mkdir(parents=True, exist_ok=True) + resp = requests.get(url, stream=True, timeout=300) + resp.raise_for_status() + with open(dest, "wb") as f: + for chunk in resp.iter_content(chunk_size=8192): + f.write(chunk) + logger.debug(f"Downloaded {dest}") + + +def _ensure_model_files(model_path: Path, voices_path: Path): + """Download model files if they don't exist.""" + if not model_path.exists(): + _download_file(KOKORO_MODEL_URL, model_path) + if not voices_path.exists(): + _download_file(KOKORO_VOICES_URL, voices_path) + def language_to_kokoro_language(language: Language) -> str: - """Convert a Language enum to Kokoro language code. + """Convert a Language enum to kokoro-onnx language code. Args: language: The Language enum value to convert. Returns: - The corresponding Kokoro language code, or None if not supported. + The corresponding kokoro-onnx locale code. + """ LANGUAGE_MAP = { - Language.EN: "a", - Language.EN_US: "a", - Language.EN_GB: "b", - Language.ES: "e", - Language.FR: "f", - Language.HI: "h", - Language.IT: "i", - Language.JA: "j", - Language.PT: "p", - Language.ZH: "z", + Language.EN: "en-us", + Language.EN_US: "en-us", + Language.EN_GB: "en-gb", + Language.ES: "es", + Language.FR: "fr", + Language.HI: "hi", + Language.IT: "it", + Language.JA: "ja", + Language.PT: "pt", + Language.ZH: "zh", } return resolve_language(language, LANGUAGE_MAP, use_base_code=True) @@ -60,8 +90,8 @@ def language_to_kokoro_language(language: Language) -> str: class KokoroTTSService(TTSService): """Kokoro TTS service implementation. - Provides local text-to-speech synthesis using the Kokoro-82M model. - Automatically downloads the model on first use. + Provides local text-to-speech synthesis using kokoro-onnx. + Automatically downloads model files on first use. """ class InputParams(BaseModel): @@ -77,7 +107,8 @@ class KokoroTTSService(TTSService): self, *, voice_id: str, - repo_id="hexgrad/Kokoro-82M", + model_path: Optional[str] = None, + voices_path: Optional[str] = None, params: Optional[InputParams] = None, **kwargs, ): @@ -85,10 +116,11 @@ class KokoroTTSService(TTSService): Args: voice_id: Voice identifier to use for synthesis. - repo_id: Hugging Face repository ID for the Kokoro model. - Defaults to "hexgrad/Kokoro-82M". + model_path: Path to the kokoro ONNX model file. Defaults to auto-downloaded file. + voices_path: Path to the voices binary file. Defaults to auto-downloaded file. params: Configuration parameters for synthesis. **kwargs: Additional arguments passed to parent `TTSService`. + """ super().__init__(**kwargs) @@ -96,7 +128,13 @@ class KokoroTTSService(TTSService): self._voice_id = voice_id self._lang_code = language_to_kokoro_language(params.language) - self._pipeline = KPipeline(lang_code=self._lang_code, repo_id=repo_id) + + model = Path(model_path) if model_path else KOKORO_CACHE_DIR / "kokoro-v1.0.onnx" + voices = Path(voices_path) if voices_path else KOKORO_CACHE_DIR / "voices-v1.0.bin" + + _ensure_model_files(model, voices) + + self._kokoro = Kokoro(str(model), str(voices)) self._resampler = create_stream_resampler() @@ -106,50 +144,38 @@ class KokoroTTSService(TTSService): @traced_tts async def run_tts(self, text: str) -> AsyncGenerator[Frame, None]: - """Synthesize speech from text using the Kokoro pipeline. + """Synthesize speech from text using kokoro-onnx. - Runs the Kokoro pipeline in a background thread and streams audio - frames as they become available. + Uses the async streaming API to generate audio frames. Args: text: The text to synthesize. + """ logger.debug(f"{self}: Generating TTS [{text}]") - def async_next(it): - try: - return next(it) - except StopIteration: - return None - - async def async_iterator(iterator) -> AsyncIterator[bytes]: - while True: - item = await asyncio.to_thread(async_next, iterator) - if item is None: - return - - (_, _, audio) = item - - # Kokoro outputs a PyTorch tensor at 24kHz, convert to int16 bytes - audio_np = np.array(audio) - audio_int16 = (audio_np * 32767).astype(np.int16).tobytes() - - yield audio_int16 - try: await self.start_ttfb_metrics() await self.start_tts_usage_metrics(text) yield TTSStartedFrame() - async for frame in self._stream_audio_frames_from_iterator( - async_iterator(self._pipeline(text, voice=self._voice_id)), - in_sample_rate=24000, - ): + stream = self._kokoro.create_stream( + text, voice=self._voice_id, lang=self._lang_code, speed=1.0 + ) + + async for samples, sample_rate in stream: await self.stop_ttfb_metrics() - yield frame + + audio_int16 = (samples * 32767).astype(np.int16).tobytes() + audio_data = await self._resampler.resample( + audio_int16, sample_rate, self.sample_rate + ) + + yield TTSAudioRawFrame( + audio=audio_data, sample_rate=self.sample_rate, num_channels=1 + ) except Exception as e: yield ErrorFrame(error=f"Unknown error occurred: {e}") finally: - logger.debug(f"{self}: Finished TTS [{text}]") await self.stop_ttfb_metrics() yield TTSStoppedFrame() diff --git a/src/pipecat/services/piper/tts.py b/src/pipecat/services/piper/tts.py index bea9e9c6c..e921447ff 100644 --- a/src/pipecat/services/piper/tts.py +++ b/src/pipecat/services/piper/tts.py @@ -227,6 +227,5 @@ class PiperHttpTTSService(TTSService): except Exception as e: yield ErrorFrame(error=f"Unknown error occurred: {e}") finally: - logger.debug(f"{self}: Finished TTS [{text}]") await self.stop_ttfb_metrics() yield TTSStoppedFrame() diff --git a/uv.lock b/uv.lock index e96d3912f..6fd35f166 100644 --- a/uv.lock +++ b/uv.lock @@ -27,15 +27,6 @@ wheels = [ { url = "https://files.pythonhosted.org/packages/5f/a0/d9ef19f780f319c21ee90ecfef4431cbeeca95bec7f14071785c17b6029b/accelerate-1.10.1-py3-none-any.whl", hash = "sha256:3621cff60b9a27ce798857ece05e2b9f56fcc71631cfb31ccf71f0359c311f11", size = 374909, upload-time = "2025-08-25T13:57:04.55Z" }, ] -[[package]] -name = "addict" -version = "2.4.0" -source = { registry = "https://pypi.org/simple" } -sdist = { url = "https://files.pythonhosted.org/packages/85/ef/fd7649da8af11d93979831e8f1f8097e85e82d5bfeabc8c68b39175d8e75/addict-2.4.0.tar.gz", hash = "sha256:b3b2210e0e067a281f5646c8c5db92e99b7231ea8b0eb5f74dbdf9e259d4e494", size = 9186, upload-time = "2020-11-21T16:21:31.416Z" } -wheels = [ - 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{ name = "typer-slim" }, - { name = "wasabi" }, -] -sdist = { url = "https://files.pythonhosted.org/packages/09/d7/edd9c24e60cf8e5de130aa2e8af3b01521f4d0216c371d01212f580d0d8e/weasel-0.4.3.tar.gz", hash = "sha256:f293d6174398e8f478c78481e00c503ee4b82ea7a3e6d0d6a01e46a6b1396845", size = 38733, upload-time = "2025-11-13T23:52:28.193Z" } -wheels = [ - { url = "https://files.pythonhosted.org/packages/a4/74/a148b41572656904a39dfcfed3f84dd1066014eed94e209223ae8e9d088d/weasel-0.4.3-py3-none-any.whl", hash = "sha256:08f65b5d0dbded4879e08a64882de9b9514753d9eaa4c4e2a576e33666ac12cf", size = 50757, upload-time = "2025-11-13T23:52:26.982Z" }, -] - [[package]] name = "websocket-client" version = "1.9.0" From d3ecbb11c1156a8618217f4c6072c165c55b865d Mon Sep 17 00:00:00 2001 From: okue Date: Sun, 1 Feb 2026 20:37:38 +0900 Subject: [PATCH 0325/1060] fix: pass frame class instead of instance to broadcast_frame in websocket transports broadcast_frame() expects a frame class and kwargs, but the three websocket input transports (fastapi, client, server) were incorrectly passing a frame instance. This would cause a TypeError at runtime when an InputTransportMessageFrame was received. --- src/pipecat/transports/websocket/client.py | 2 +- src/pipecat/transports/websocket/fastapi.py | 2 +- src/pipecat/transports/websocket/server.py | 2 +- 3 files changed, 3 insertions(+), 3 deletions(-) diff --git a/src/pipecat/transports/websocket/client.py b/src/pipecat/transports/websocket/client.py index f55b1f919..e24352575 100644 --- a/src/pipecat/transports/websocket/client.py +++ b/src/pipecat/transports/websocket/client.py @@ -300,7 +300,7 @@ class WebsocketClientInputTransport(BaseInputTransport): if isinstance(frame, InputAudioRawFrame) and self._params.audio_in_enabled: await self.push_audio_frame(frame) elif isinstance(frame, InputTransportMessageFrame): - await self.broadcast_frame(frame) + await self.broadcast_frame(InputTransportMessageFrame, message=frame.message) else: await self.push_frame(frame) diff --git a/src/pipecat/transports/websocket/fastapi.py b/src/pipecat/transports/websocket/fastapi.py index a0d02ccec..d4f5809d9 100644 --- a/src/pipecat/transports/websocket/fastapi.py +++ b/src/pipecat/transports/websocket/fastapi.py @@ -313,7 +313,7 @@ class FastAPIWebsocketInputTransport(BaseInputTransport): if isinstance(frame, InputAudioRawFrame): await self.push_audio_frame(frame) elif isinstance(frame, InputTransportMessageFrame): - await self.broadcast_frame(frame) + await self.broadcast_frame(InputTransportMessageFrame, message=frame.message) else: await self.push_frame(frame) except Exception as e: diff --git a/src/pipecat/transports/websocket/server.py b/src/pipecat/transports/websocket/server.py index acd4faf92..16964cb9b 100644 --- a/src/pipecat/transports/websocket/server.py +++ b/src/pipecat/transports/websocket/server.py @@ -217,7 +217,7 @@ class WebsocketServerInputTransport(BaseInputTransport): if isinstance(frame, InputAudioRawFrame): await self.push_audio_frame(frame) elif isinstance(frame, InputTransportMessageFrame): - await self.broadcast_frame(frame) + await self.broadcast_frame(InputTransportMessageFrame, message=frame.message) else: await self.push_frame(frame) except Exception as e: From 50dedf350d94bc4393e19c42f1be8a67c0d99cdd Mon Sep 17 00:00:00 2001 From: Om Chauhan Date: Mon, 2 Feb 2026 08:38:54 +0530 Subject: [PATCH 0326/1060] fix: ensure function call timeout task is always cancelled --- src/pipecat/services/llm_service.py | 15 +++++++-------- 1 file changed, 7 insertions(+), 8 deletions(-) diff --git a/src/pipecat/services/llm_service.py b/src/pipecat/services/llm_service.py index 08da591c5..e354543e4 100644 --- a/src/pipecat/services/llm_service.py +++ b/src/pipecat/services/llm_service.py @@ -681,12 +681,11 @@ class LLMService(UserTurnCompletionLLMServiceMixin, AIService): timeout_task = self.create_task(timeout_handler()) - # Yield to the event loop so the timeout task coroutine gets entered - # before it could be cancelled. Without this, cancelling the task before - # it starts would leave the coroutine in a "never awaited" state. - await asyncio.sleep(0) - try: + # Yield to the event loop so the timeout task coroutine gets entered + # before it could be cancelled. Without this, cancelling the task before + # it starts would leave the coroutine in a "never awaited" state. + await asyncio.sleep(0) if isinstance(item.handler, DirectFunctionWrapper): # Handler is a DirectFunctionWrapper await item.handler.invoke( @@ -722,12 +721,12 @@ class LLMService(UserTurnCompletionLLMServiceMixin, AIService): ) await item.handler(params) except Exception as e: - # Cancel timeout task if it exists - if timeout_task and not timeout_task.done(): - await self.cancel_task(timeout_task) error_message = f"Error executing function call [{runner_item.function_name}]: {e}" logger.error(f"{self} {error_message}") await self.push_error(error_msg=error_message, exception=e, fatal=False) + finally: + if timeout_task and not timeout_task.done(): + await self.cancel_task(timeout_task) async def _cancel_function_call(self, function_name: Optional[str]): cancelled_tasks = set() From 763002f2bcb621b30fbd4fcab447a380a316aa08 Mon Sep 17 00:00:00 2001 From: James Hush Date: Mon, 2 Feb 2026 14:27:49 +0800 Subject: [PATCH 0327/1060] Fix sentence splitting for CJK and other non-Latin languages in TTS pipeline MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit NLTK's sent_tokenize() only supports ~15 European languages and defaults to English. For Japanese, Chinese, Korean, Hindi, Arabic, and other non-Latin languages, NLTK fails to recognize sentence boundaries like 。？！ causing text to accumulate until flush instead of being emitted sentence-by-sentence. Add a fallback in match_endofsentence() that scans for unambiguous non-Latin sentence-ending punctuation when NLTK fails to split the text. Latin punctuation (. ! ? ; …) is excluded from the fallback since NLTK handles those correctly and they can be ambiguous (abbreviations, decimals, etc.). Co-Authored-By: Claude Opus 4.5 --- src/pipecat/utils/string.py | 23 +++++++++++- tests/test_simple_text_aggregator.py | 56 ++++++++++++++++++++++++++++ tests/test_utils_string.py | 40 ++++++++++++++++++++ 3 files changed, 118 insertions(+), 1 deletion(-) diff --git a/src/pipecat/utils/string.py b/src/pipecat/utils/string.py index 3a5d69cad..20fcdb2e0 100644 --- a/src/pipecat/utils/string.py +++ b/src/pipecat/utils/string.py @@ -89,6 +89,17 @@ SENTENCE_ENDING_PUNCTUATION: FrozenSet[str] = frozenset( } ) +# Latin punctuation that NLTK handles well — these need NLTK's disambiguation +# because "." can appear in abbreviations, decimals, etc. +_LATIN_SENTENCE_ENDING_PUNCTUATION: FrozenSet[str] = frozenset({".", "!", "?", ";", "…"}) + +# Non-Latin sentence-ending punctuation that is always unambiguous and never needs +# NLTK's disambiguation logic. Used as a fallback when NLTK doesn't support the +# language (e.g., Japanese, Chinese, Korean, Hindi, Arabic). +UNAMBIGUOUS_SENTENCE_ENDING_PUNCTUATION: FrozenSet[str] = ( + SENTENCE_ENDING_PUNCTUATION - _LATIN_SENTENCE_ENDING_PUNCTUATION +) + StartEndTags = Tuple[str, str] @@ -144,7 +155,17 @@ def match_endofsentence(text: str) -> int: # common for text to be single words, so we need to ensure # sentence-ending punctuation is present. if len(sentences) == 1 and first_sentence == text: - return len(text) if text and text[-1] in SENTENCE_ENDING_PUNCTUATION else 0 + if text and text[-1] in SENTENCE_ENDING_PUNCTUATION: + return len(text) + # Fallback for languages not supported by NLTK (e.g., Japanese, Chinese, + # Korean, Hindi, Arabic). NLTK returned the entire text as a single + # sentence, and the last character is not sentence-ending punctuation + # (it's a lookahead character). Scan for unambiguous non-Latin sentence- + # ending punctuation that doesn't need NLTK's disambiguation. + for i, ch in enumerate(text): + if ch in UNAMBIGUOUS_SENTENCE_ENDING_PUNCTUATION: + return i + 1 + return 0 # If there are multiple sentences, the first one is complete by definition # (NLTK found a boundary, so there must be proper punctuation) diff --git a/tests/test_simple_text_aggregator.py b/tests/test_simple_text_aggregator.py index ef51cfc49..4b3613e27 100644 --- a/tests/test_simple_text_aggregator.py +++ b/tests/test_simple_text_aggregator.py @@ -124,6 +124,62 @@ class TestSimpleTextAggregator(unittest.IsolatedAsyncioTestCase): result = await self.aggregator.flush() assert result.text == "W" + async def test_japanese_multiple_sentences(self): + """Test that Japanese sentences are properly split during streaming.""" + text = "こんにちは。元気ですか？" + results = [agg async for agg in self.aggregator.aggregate(text)] + + # First sentence detected when 元 arrives as lookahead after 。 + assert len(results) == 1 + assert results[0].text == "こんにちは。" + + # Flush returns the second sentence + result = await self.aggregator.flush() + assert result.text == "元気ですか？" + + async def test_japanese_sentence_with_lookahead(self): + """Test that a Japanese sentence is detected with a lookahead character.""" + text = "こんにちは。元" + results = [agg async for agg in self.aggregator.aggregate(text)] + + # 。 triggers lookahead, then 元 confirms it + assert len(results) == 1 + assert results[0].text == "こんにちは。" + + # Flush returns remainder + result = await self.aggregator.flush() + assert result.text == "元" + + async def test_chinese_streaming_tokens(self): + """Test Chinese text split across multiple streaming tokens.""" + aggregator = SimpleTextAggregator() + + tokens = ["你好", "世界", "。", "下一", "句话", "。"] + all_results = [] + for token in tokens: + results = [agg async for agg in aggregator.aggregate(token)] + all_results.extend(results) + + # First sentence detected when 下 arrives after 。 + assert len(all_results) == 1 + assert all_results[0].text == "你好世界。" + + # Flush returns the second sentence + result = await aggregator.flush() + assert result.text == "下一句话。" + + async def test_japanese_single_sentence_flush(self): + """Test that a single Japanese sentence with no lookahead flushes correctly.""" + text = "こんにちは。" + results = [agg async for agg in self.aggregator.aggregate(text)] + + # No lookahead yet - waiting + assert len(results) == 0 + + # Flush returns the complete sentence + result = await self.aggregator.flush() + assert result.text == "こんにちは。" + if __name__ == "__main__": unittest.main() diff --git a/tests/test_utils_string.py b/tests/test_utils_string.py index 4afde718c..5130c1daa 100644 --- a/tests/test_utils_string.py +++ b/tests/test_utils_string.py @@ -153,6 +153,46 @@ class TestUtilsString(unittest.IsolatedAsyncioTestCase): for sentence in latin_script_sentences: assert match_endofsentence(sentence), f"Failed for Latin script: {sentence}" + async def test_endofsentence_cjk_with_lookahead(self): + """Test sentence detection for CJK text with lookahead characters. + + This tests the NLTK fallback path: NLTK returns entire text as one + sentence because it doesn't support CJK languages, but unambiguous + punctuation is detected via the fallback scan. + """ + # Japanese: sentence + lookahead character + assert match_endofsentence("こんにちは。元") == 6 + assert match_endofsentence("元気ですか？は") == 6 + assert match_endofsentence("ありがとう！次") == 6 + + # Chinese: sentence + lookahead character + assert match_endofsentence("你好世界。下") == 5 + assert match_endofsentence("你好吗？我") == 4 + + # Korean: sentence + lookahead character + assert match_endofsentence("안녕하세요。다") == 6 + + # Multiple CJK sentences with lookahead - should return first sentence + assert match_endofsentence("こんにちは。元気ですか？は") == 6 + + # Indic script with lookahead + assert match_endofsentence("हैलो।अ") == 5 + + # Arabic with lookahead + assert match_endofsentence("مرحبا؟ك") == 6 + + async def test_endofsentence_latin_not_affected_by_fallback(self): + """Verify that the CJK fallback does not change behavior for Latin text.""" + # These should still return 0 - Latin "." is NOT in the unambiguous set + assert not match_endofsentence("Mr. S") + assert not match_endofsentence("Ok, Mr. Smith let's ") + assert not match_endofsentence("The number pi is 3.14159") + assert not match_endofsentence("America, or the U.S") + + # These should still return correct values via NLTK path + assert match_endofsentence("This is a sentence. This is another one") == 19 + assert match_endofsentence("For information, call 411.") == 26 + async def test_endofsentence_streaming_tokens(self): """Test the specific use case of streaming LLM tokens.""" From 774041e9a1951f5aec84eeb89e612d797d428962 Mon Sep 17 00:00:00 2001 From: James Hush Date: Mon, 2 Feb 2026 14:47:22 +0800 Subject: [PATCH 0328/1060] Add changelog for PR #3617 Co-Authored-By: Claude Opus 4.5 --- changelog/3617.fixed.md | 5 +++++ 1 file changed, 5 insertions(+) create mode 100644 changelog/3617.fixed.md diff --git a/changelog/3617.fixed.md b/changelog/3617.fixed.md new file mode 100644 index 000000000..b9739a42b --- /dev/null +++ b/changelog/3617.fixed.md @@ -0,0 +1,5 @@ +- Fixed sentence splitting for Japanese, Chinese, Korean, and other non-Latin + languages in TTS pipeline. NLTK's sentence tokenizer does not support CJK + languages, causing text to accumulate until flush instead of being split at + sentence boundaries. Added fallback detection for unambiguous non-Latin + sentence-ending punctuation (e.g., `。`, `？`, `！`). From ba2b7c05d6c1c3c64152603fbbf09da90d8d6e23 Mon Sep 17 00:00:00 2001 From: Mark Backman Date: Tue, 25 Nov 2025 23:35:03 -0500 Subject: [PATCH 0329/1060] Add ResembleAITTSService --- env.example | 4 + .../07zi-interruptible-resemble.py | 135 +++++++ pyproject.toml | 1 + src/pipecat/services/resembleai/__init__.py | 0 src/pipecat/services/resembleai/tts.py | 366 ++++++++++++++++++ uv.lock | 12 +- 6 files changed, 517 insertions(+), 1 deletion(-) create mode 100644 examples/foundational/07zi-interruptible-resemble.py create mode 100644 src/pipecat/services/resembleai/__init__.py create mode 100644 src/pipecat/services/resembleai/tts.py diff --git a/env.example b/env.example index e662ea54b..6e7db21e2 100644 --- a/env.example +++ b/env.example @@ -156,6 +156,10 @@ PLIVO_AUTH_TOKEN=... # Qwen QWEN_API_KEY=... +# Resemble AI +RESEMBLE_API_KEY= +RESEMBLE_VOICE_UUID= + # Rime RIME_API_KEY=... RIME_VOICE_ID=... diff --git a/examples/foundational/07zi-interruptible-resemble.py b/examples/foundational/07zi-interruptible-resemble.py new file mode 100644 index 000000000..5cbf1288d --- /dev/null +++ b/examples/foundational/07zi-interruptible-resemble.py @@ -0,0 +1,135 @@ +# +# Copyright (c) 2024-2026, Daily +# +# SPDX-License-Identifier: BSD 2-Clause License +# + +import os + +from dotenv import load_dotenv +from loguru import logger + +from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3 +from pipecat.audio.vad.silero import SileroVADAnalyzer +from pipecat.audio.vad.vad_analyzer import VADParams +from pipecat.frames.frames import LLMRunFrame +from pipecat.pipeline.pipeline import Pipeline +from pipecat.pipeline.runner import PipelineRunner +from pipecat.pipeline.task import PipelineParams, PipelineTask +from pipecat.processors.aggregators.llm_context import LLMContext +from pipecat.processors.aggregators.llm_response_universal import ( + LLMContextAggregatorPair, + LLMUserAggregatorParams, +) +from pipecat.runner.types import RunnerArguments +from pipecat.runner.utils import create_transport +from pipecat.services.deepgram.stt import DeepgramSTTService +from pipecat.services.openai.llm import OpenAILLMService +from pipecat.services.resembleai.tts import ResembleAITTSService +from pipecat.transports.base_transport import BaseTransport, TransportParams +from pipecat.transports.daily.transport import DailyParams +from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams +from pipecat.turns.user_stop import TurnAnalyzerUserTurnStopStrategy +from pipecat.turns.user_turn_strategies import UserTurnStrategies + +load_dotenv(override=True) + +# We store functions so objects (e.g. SileroVADAnalyzer) don't get +# instantiated. The function will be called when the desired transport gets +# selected. +transport_params = { + "daily": lambda: DailyParams( + audio_in_enabled=True, + audio_out_enabled=True, + vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), + ), + "twilio": lambda: FastAPIWebsocketParams( + audio_in_enabled=True, + audio_out_enabled=True, + vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), + ), + "webrtc": lambda: TransportParams( + audio_in_enabled=True, + audio_out_enabled=True, + vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), + ), +} + + +async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): + logger.info(f"Starting bot") + + stt = DeepgramSTTService(api_key=os.getenv("DEEPGRAM_API_KEY")) + + tts = ResembleAITTSService( + api_key=os.getenv("RESEMBLE_API_KEY"), + voice_id=os.getenv("RESEMBLE_VOICE_UUID"), + ) + + llm = OpenAILLMService(api_key=os.getenv("OPENAI_API_KEY")) + + messages = [ + { + "role": "system", + "content": "You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + }, + ] + + context = LLMContext(messages) + user_aggregator, assistant_aggregator = LLMContextAggregatorPair( + context, + user_params=LLMUserAggregatorParams( + user_turn_strategies=UserTurnStrategies( + stop=[TurnAnalyzerUserTurnStopStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3())] + ), + ), + ) + + pipeline = Pipeline( + [ + transport.input(), # Transport user input + stt, + user_aggregator, # User responses + llm, # LLM + tts, # TTS + transport.output(), # Transport bot output + assistant_aggregator, # Assistant spoken responses + ] + ) + + task = PipelineTask( + pipeline, + params=PipelineParams( + enable_metrics=True, + enable_usage_metrics=True, + ), + idle_timeout_secs=runner_args.pipeline_idle_timeout_secs, + ) + + @transport.event_handler("on_client_connected") + async def on_client_connected(transport, client): + logger.info(f"Client connected") + # Kick off the conversation. + messages.append({"role": "system", "content": "Please introduce yourself to the user."}) + await task.queue_frames([LLMRunFrame()]) + + @transport.event_handler("on_client_disconnected") + async def on_client_disconnected(transport, client): + logger.info(f"Client disconnected") + await task.cancel() + + runner = PipelineRunner(handle_sigint=runner_args.handle_sigint) + + await runner.run(task) + + +async def bot(runner_args: RunnerArguments): + """Main bot entry point compatible with Pipecat Cloud.""" + transport = await create_transport(runner_args, transport_params) + await run_bot(transport, runner_args) + + +if __name__ == "__main__": + from pipecat.runner.run import main + + main() diff --git a/pyproject.toml b/pyproject.toml index 4e879984a..0e27d597a 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -100,6 +100,7 @@ piper = [ "piper-tts>=1.3.0,<2", "requests>=2.32.5,<3" ] playht = [ "pipecat-ai[websockets-base]" ] qwen = [] remote-smart-turn = [] +resembleai = [ "pipecat-ai[websockets-base]" ] rime = [ "pipecat-ai[websockets-base]" ] riva = [ "pipecat-ai[nvidia]" ] runner = [ "python-dotenv>=1.0.0,<2.0.0", "uvicorn>=0.32.0,<1.0.0", "fastapi>=0.115.6,<0.128.0", "pipecat-ai-small-webrtc-prebuilt>=2.0.4"] diff --git a/src/pipecat/services/resembleai/__init__.py b/src/pipecat/services/resembleai/__init__.py new file mode 100644 index 000000000..e69de29bb diff --git a/src/pipecat/services/resembleai/tts.py b/src/pipecat/services/resembleai/tts.py new file mode 100644 index 000000000..ae97982b7 --- /dev/null +++ b/src/pipecat/services/resembleai/tts.py @@ -0,0 +1,366 @@ +# +# Copyright (c) 2024–2025, Daily +# +# SPDX-License-Identifier: BSD 2-Clause License +# + +"""Resemble AI text-to-speech service implementations.""" + +import base64 +import json +from typing import AsyncGenerator, Optional + +from loguru import logger + +from pipecat.frames.frames import ( + CancelFrame, + EndFrame, + ErrorFrame, + Frame, + InterruptionFrame, + StartFrame, + TTSAudioRawFrame, + TTSStartedFrame, + TTSStoppedFrame, +) +from pipecat.processors.frame_processor import FrameDirection +from pipecat.services.tts_service import AudioContextWordTTSService +from pipecat.transcriptions.language import Language +from pipecat.utils.text.base_text_aggregator import BaseTextAggregator +from pipecat.utils.tracing.service_decorators import traced_tts + +try: + from websockets.asyncio.client import connect as websocket_connect + from websockets.protocol import State +except ModuleNotFoundError as e: + logger.error(f"Exception: {e}") + logger.error("In order to use Resemble AI, you need to `pip install pipecat-ai[resembleai]`.") + raise Exception(f"Missing module: {e}") + + +class ResembleAITTSService(AudioContextWordTTSService): + """Resemble AI TTS service with WebSocket streaming and word timestamps. + + Provides text-to-speech using Resemble AI's streaming WebSocket API. + Supports word-level timestamps and audio context management for handling + multiple simultaneous synthesis requests with proper interruption support. + """ + + def __init__( + self, + *, + api_key: str, + voice_id: str, + url: str = "wss://websocket.cluster.resemble.ai/stream", + precision: Optional[str] = "PCM_16", + output_format: Optional[str] = "wav", + sample_rate: Optional[int] = 22050, + **kwargs, + ): + """Initialize the Resemble AI TTS service. + + Args: + api_key: Resemble AI API key for authentication. + voice_id: Voice UUID to use for synthesis. + url: WebSocket URL for Resemble AI TTS API. + precision: PCM bit depth (PCM_32, PCM_24, PCM_16, or MULAW). + output_format: Audio format (wav or mp3). + sample_rate: Audio sample rate (8000, 16000, 22050, 32000, or 44100). Defaults to 22050. + **kwargs: Additional arguments passed to the parent service. + """ + super().__init__( + sample_rate=sample_rate, + **kwargs, + ) + + self._api_key = api_key + self._voice_id = voice_id + self._url = url + self._settings = { + "precision": precision, + "output_format": output_format, + "sample_rate": sample_rate, + } + + self._websocket = None + self._request_id_counter = 0 + self._current_request_id = None + self._receive_task = None + + self.set_voice(voice_id) + + def can_generate_metrics(self) -> bool: + """Check if this service can generate processing metrics. + + Returns: + True, as Resemble AI service supports metrics generation. + """ + return True + + def _build_msg(self, text: str = "") -> str: + """Build a JSON message for the Resemble AI WebSocket API. + + Args: + text: The text or SSML to synthesize. + + Returns: + JSON string containing the request payload. + """ + msg = { + "voice_uuid": self._voice_id, + "data": text, + "binary_response": False, # Use JSON frames to get timestamps + "request_id": self._request_id_counter, + "output_format": self._settings["output_format"], + "sample_rate": self._settings["sample_rate"], + "precision": self._settings["precision"], + "no_audio_header": True, + } + + self._request_id_counter += 1 + return json.dumps(msg) + + async def start(self, frame: StartFrame): + """Start the Resemble AI TTS service. + + Args: + frame: The start frame containing initialization parameters. + """ + await super().start(frame) + self._settings["sample_rate"] = self.sample_rate + await self._connect() + + async def stop(self, frame: EndFrame): + """Stop the Resemble AI TTS service. + + Args: + frame: The end frame. + """ + await super().stop(frame) + await self._disconnect() + + async def cancel(self, frame: CancelFrame): + """Cancel the Resemble AI TTS service. + + Args: + frame: The cancel frame. + """ + await super().cancel(frame) + await self._disconnect() + + async def _connect(self): + """Connect to the Resemble AI WebSocket.""" + await self._connect_websocket() + + if self._websocket and not self._receive_task: + self._receive_task = self.create_task(self._receive_task_handler(self._report_error)) + + async def _disconnect(self): + """Disconnect from the Resemble AI WebSocket.""" + if self._receive_task: + await self.cancel_task(self._receive_task) + self._receive_task = None + + await self._disconnect_websocket() + + async def _connect_websocket(self): + """Establish WebSocket connection to Resemble AI.""" + try: + if self._websocket and self._websocket.state is State.OPEN: + return + logger.debug("Connecting to Resemble AI TTS") + headers = {"Authorization": f"Bearer {self._api_key}"} + self._websocket = await websocket_connect(self._url, additional_headers=headers) + await self._call_event_handler("on_connected") + except Exception as e: + logger.error(f"{self} exception: {e}") + await self.push_error(ErrorFrame(error=f"{self} error: {e}")) + self._websocket = None + await self._call_event_handler("on_connection_error", f"{e}") + + async def _disconnect_websocket(self): + """Close WebSocket connection to Resemble AI.""" + try: + await self.stop_all_metrics() + + if self._websocket: + logger.debug("Disconnecting from Resemble AI") + await self._websocket.close() + except Exception as e: + logger.error(f"{self} exception: {e}") + await self.push_error(ErrorFrame(error=f"{self} error: {e}")) + finally: + self._current_request_id = None + self._websocket = None + await self._call_event_handler("on_disconnected") + + def _get_websocket(self): + """Get the current WebSocket connection. + + Returns: + The active WebSocket connection. + + Raises: + Exception: If websocket is not connected. + """ + if self._websocket: + return self._websocket + raise Exception("Websocket not connected") + + async def _handle_interruption(self, frame: InterruptionFrame, direction: FrameDirection): + """Handle interruption by stopping current synthesis. + + Args: + frame: The interruption frame. + direction: The direction of frame processing. + """ + await super()._handle_interruption(frame, direction) + await self.stop_all_metrics() + # Note: Resemble AI doesn't have an explicit cancel mechanism, + # but we can stop processing by resetting our current request_id + self._current_request_id = None + + async def flush_audio(self): + """Flush any pending audio and finalize the current context.""" + if not self._current_request_id: + return + logger.trace(f"{self}: flushing audio") + # For Resemble AI, we just wait for the audio_end message + # which is handled in _process_messages + self._current_request_id = None + + async def _process_messages(self): + """Process incoming WebSocket messages from Resemble AI.""" + async for message in self._get_websocket(): + try: + msg = json.loads(message) + except json.JSONDecodeError: + logger.error(f"{self} received invalid JSON: {message}") + continue + + if not msg: + continue + + msg_type = msg.get("type") + request_id = msg.get("request_id") + + # Convert request_id to string for audio context tracking + request_id_str = str(request_id) + + # Check if this message belongs to a valid audio context + if not self.audio_context_available(request_id_str): + continue + + if msg_type == "audio": + await self.stop_ttfb_metrics() + await self.start_word_timestamps() + + # Decode base64 audio content + audio_content = msg.get("audio_content", "") + if audio_content: + audio_data = base64.b64decode(audio_content) + frame = TTSAudioRawFrame( + audio=audio_data, + sample_rate=self.sample_rate, + num_channels=1, + ) + await self.append_to_audio_context(request_id_str, frame) + + # Process timestamps if available + timestamps = msg.get("audio_timestamps", {}) + if timestamps: + graph_chars = timestamps.get("graph_chars", []) + graph_times = timestamps.get("graph_times", []) + + # Convert graph_times (start, end pairs) to word timestamps + word_times = [] + for char, times in zip(graph_chars, graph_times): + if times and len(times) >= 2: + start_time = times[0] + word_times.append((char, start_time)) + + if word_times: + await self.add_word_timestamps(word_times) + + elif msg_type == "audio_end": + await self.stop_ttfb_metrics() + await self.add_word_timestamps([("TTSStoppedFrame", 0), ("Reset", 0)]) + await self.remove_audio_context(request_id_str) + # Clear current request if this was it + if self._current_request_id == request_id: + self._current_request_id = None + + elif msg_type == "error": + error_name = msg.get("error_name", "Unknown") + error_msg = msg.get("message", "Unknown error") + status_code = msg.get("status_code", 0) + logger.error(f"{self} error: {error_name} (status {status_code}): {error_msg}") + await self.push_frame(TTSStoppedFrame()) + await self.stop_all_metrics() + await self.push_error(ErrorFrame(error=f"{self} error: {error_name} - {error_msg}")) + + # Clear current request if this was it + if self._current_request_id == request_id: + self._current_request_id = None + + # Check if this is an unrecoverable error (connection-level failure) + if status_code in [401, 403]: + # Close and reconnect for auth errors + await self._disconnect_websocket() + await self._connect_websocket() + else: + logger.warning(f"{self} unknown message type: {msg_type}") + + async def _receive_messages(self): + """Main loop for receiving messages from Resemble AI.""" + while True: + try: + await self._process_messages() + except Exception as e: + logger.error(f"{self} error in receive loop: {e}") + # Try to reconnect + logger.debug(f"{self} Resemble AI connection lost, reconnecting") + await self._connect_websocket() + + @traced_tts + async def run_tts(self, text: str) -> AsyncGenerator[Frame, None]: + """Generate speech from text using Resemble AI's streaming API. + + Args: + text: The text to synthesize into speech. + + Yields: + Frame: Audio frames containing the synthesized speech. + """ + logger.debug(f"{self}: Generating TTS [{text}]") 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"cartesia", "camb", "cerebras", "daily", "deepgram", "deepseek", "elevenlabs", "fal", "fireworks", "fish", "gladia", "google", "gradium", "grok", "groq", "gstreamer", "heygen", "hume", "inworld", "koala", "kokoro", "krisp", "langchain", "livekit", "lmnt", "local", "local-smart-turn", "local-smart-turn-v3", "mcp", "mem0", "mistral", "mlx-whisper", "moondream", "neuphonic", "noisereduce", "nvidia", "openai", "rnnoise", "openpipe", "openrouter", "perplexity", "piper", "playht", "qwen", "remote-smart-turn", "resembleai", "rime", "riva", "runner", "sagemaker", "sambanova", "sarvam", "sentry", "silero", "simli", "soniox", "soundfile", "speechmatics", "strands", "tavus", "together", "tracing", "ultravox", "webrtc", "websocket", "websockets-base", "whisper"] [package.metadata.requires-dev] dev = [ From a592b7fdf0941bb06df863e02309ef44b69d7928 Mon Sep 17 00:00:00 2001 From: Mark Backman Date: Thu, 29 Jan 2026 00:06:09 -0500 Subject: [PATCH 0330/1060] Update per PR 1789, align with ErrorFrame norms --- changelog/3134.added.md | 1 + src/pipecat/services/resembleai/tts.py | 105 +++++++++++++++++++++---- 2 files changed, 92 insertions(+), 14 deletions(-) create mode 100644 changelog/3134.added.md diff --git a/changelog/3134.added.md b/changelog/3134.added.md new file mode 100644 index 000000000..adddde398 --- /dev/null +++ b/changelog/3134.added.md @@ -0,0 +1 @@ +- Added `ResembleAITTSService` for text-to-speech using Resemble AI's streaming WebSocket API with word-level timestamps and jitter buffering for smooth audio playback. diff --git a/src/pipecat/services/resembleai/tts.py b/src/pipecat/services/resembleai/tts.py index ae97982b7..21a8c7a78 100644 --- a/src/pipecat/services/resembleai/tts.py +++ b/src/pipecat/services/resembleai/tts.py @@ -87,6 +87,18 @@ class ResembleAITTSService(AudioContextWordTTSService): self._current_request_id = None self._receive_task = None + # Per-request audio buffers to handle concurrent TTS requests + # ResembleAI may send odd-length data even for PCM_16, so buffering helps us + # create properly aligned frames while maintaining smooth audio output + self._audio_buffers: dict[str, bytearray] = {} + self._buffer_threshold_bytes = 2208 + + # Jitter buffer: accumulate audio before starting playback to absorb network latency + # ResembleAI sends audio in bursts with 300-450ms gaps between them + # We need to buffer enough to cover these gaps before starting playback + self._jitter_buffer_bytes = 44100 # ~1000ms at 22050Hz to handle 400ms+ network gaps + self._playback_started: dict[str, bool] = {} # Track if we've started playback per request + self.set_voice(voice_id) def can_generate_metrics(self) -> bool: @@ -173,8 +185,7 @@ class ResembleAITTSService(AudioContextWordTTSService): self._websocket = await websocket_connect(self._url, additional_headers=headers) await self._call_event_handler("on_connected") except Exception as e: - logger.error(f"{self} exception: {e}") - await self.push_error(ErrorFrame(error=f"{self} error: {e}")) + await self.push_error(error_msg=f"Unknown error occurred: {e}", exception=e) self._websocket = None await self._call_event_handler("on_connection_error", f"{e}") @@ -185,13 +196,16 @@ class ResembleAITTSService(AudioContextWordTTSService): if self._websocket: logger.debug("Disconnecting from Resemble AI") + # ResembleAI doesn't send disconnect acknowledgement, set close_timeout to 0 + self._websocket.close_timeout = 0 await self._websocket.close() except Exception as e: - logger.error(f"{self} exception: {e}") - await self.push_error(ErrorFrame(error=f"{self} error: {e}")) + await self.push_error(error_msg=f"Unknown error occurred: {e}", exception=e) finally: self._current_request_id = None self._websocket = None + self._audio_buffers.clear() + self._playback_started.clear() await self._call_event_handler("on_disconnected") def _get_websocket(self): @@ -235,7 +249,7 @@ class ResembleAITTSService(AudioContextWordTTSService): try: msg = json.loads(message) except json.JSONDecodeError: - logger.error(f"{self} received invalid JSON: {message}") + await self.push_error(error_msg=f"Received invalid JSON: {message}") continue if not msg: @@ -257,10 +271,44 @@ class ResembleAITTSService(AudioContextWordTTSService): # Decode base64 audio content audio_content = msg.get("audio_content", "") - if audio_content: - audio_data = base64.b64decode(audio_content) + if not audio_content: + continue + + audio_bytes = base64.b64decode(audio_content) + if len(audio_bytes) == 0: + continue + + # Get or create buffer for this request + if request_id_str not in self._audio_buffers: + self._audio_buffers[request_id_str] = bytearray() + self._playback_started[request_id_str] = False + buffer = self._audio_buffers[request_id_str] + + # Add to buffer + buffer.extend(audio_bytes) + + # Wait for jitter buffer to fill before starting playback + # This absorbs network latency gaps (ResembleAI sends in bursts) + if not self._playback_started.get(request_id_str, False): + if len(buffer) < self._jitter_buffer_bytes: + continue + self._playback_started[request_id_str] = True + + # Send complete (even-byte) chunks for PCM_16 alignment + while len(buffer) >= self._buffer_threshold_bytes: + chunk_size = self._buffer_threshold_bytes + if chunk_size % 2 != 0: + chunk_size -= 1 + + chunk_to_send = bytes(buffer[:chunk_size]) + self._audio_buffers[request_id_str] = buffer[chunk_size:] + buffer = self._audio_buffers[request_id_str] + + if len(chunk_to_send) == 0: + continue + frame = TTSAudioRawFrame( - audio=audio_data, + audio=chunk_to_send, sample_rate=self.sample_rate, num_channels=1, ) @@ -284,6 +332,28 @@ class ResembleAITTSService(AudioContextWordTTSService): elif msg_type == "audio_end": await self.stop_ttfb_metrics() + + # Flush remaining buffer, ensuring even length for PCM_16 + buffer = self._audio_buffers.get(request_id_str, bytearray()) + if buffer: + remaining = bytes(buffer) + # PCM_16 requires even number of bytes + if len(remaining) % 2 != 0: + remaining = remaining[:-1] + if remaining: + frame = TTSAudioRawFrame( + audio=remaining, + sample_rate=self.sample_rate, + num_channels=1, + ) + await self.append_to_audio_context(request_id_str, frame) + + # Clean up buffer and playback tracking for this request + if request_id_str in self._audio_buffers: + del self._audio_buffers[request_id_str] + if request_id_str in self._playback_started: + del self._playback_started[request_id_str] + await self.add_word_timestamps([("TTSStoppedFrame", 0), ("Reset", 0)]) await self.remove_audio_context(request_id_str) # Clear current request if this was it @@ -294,7 +364,16 @@ class ResembleAITTSService(AudioContextWordTTSService): error_name = msg.get("error_name", "Unknown") error_msg = msg.get("message", "Unknown error") status_code = msg.get("status_code", 0) - logger.error(f"{self} error: {error_name} (status {status_code}): {error_msg}") + await self.push_error( + error_msg=f"Error: {error_name} (status {status_code}): {error_msg}" + ) + + # Clean up buffer and playback tracking for this request + if request_id_str in self._audio_buffers: + del self._audio_buffers[request_id_str] + if request_id_str in self._playback_started: + del self._playback_started[request_id_str] + await self.push_frame(TTSStoppedFrame()) await self.stop_all_metrics() await self.push_error(ErrorFrame(error=f"{self} error: {error_name} - {error_msg}")) @@ -317,7 +396,7 @@ class ResembleAITTSService(AudioContextWordTTSService): try: await self._process_messages() except Exception as e: - logger.error(f"{self} error in receive loop: {e}") + await self.push_error(error_msg=f"Error in receive loop: {e}", exception=e) # Try to reconnect logger.debug(f"{self} Resemble AI connection lost, reconnecting") await self._connect_websocket() @@ -354,13 +433,11 @@ class ResembleAITTSService(AudioContextWordTTSService): await self._get_websocket().send(msg) await self.start_tts_usage_metrics(text) except Exception as e: - logger.error(f"{self} exception: {e}") - yield ErrorFrame(error=f"{self} error: {e}") + yield ErrorFrame(error=f"Unknown error occurred: {e}") yield TTSStoppedFrame() await self._disconnect() await self._connect() return yield None except Exception as e: - logger.error(f"{self} exception: {e}") - yield ErrorFrame(error=f"{self} error: {e}") + yield ErrorFrame(error=f"Unknown error occurred: {e}") From 5cda72d138d1e8a3e05018227e3d267bfdb87104 Mon Sep 17 00:00:00 2001 From: Mark Backman Date: Mon, 2 Feb 2026 09:05:03 -0500 Subject: [PATCH 0331/1060] Add Resemble TTS to README --- README.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/README.md b/README.md index e3ebaba09..6d6a56612 100644 --- a/README.md +++ b/README.md @@ -75,7 +75,7 @@ Catch new features, interviews, and how-tos on our [Pipecat TV](https://www.yout | ------------------- | ----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | | Speech-to-Text | [AssemblyAI](https://docs.pipecat.ai/server/services/stt/assemblyai), [AWS](https://docs.pipecat.ai/server/services/stt/aws), [Azure](https://docs.pipecat.ai/server/services/stt/azure), [Cartesia](https://docs.pipecat.ai/server/services/stt/cartesia), [Deepgram](https://docs.pipecat.ai/server/services/stt/deepgram), [ElevenLabs](https://docs.pipecat.ai/server/services/stt/elevenlabs), [Fal Wizper](https://docs.pipecat.ai/server/services/stt/fal), [Gladia](https://docs.pipecat.ai/server/services/stt/gladia), [Google](https://docs.pipecat.ai/server/services/stt/google), [Gradium](https://docs.pipecat.ai/server/services/stt/gradium), [Groq (Whisper)](https://docs.pipecat.ai/server/services/stt/groq), [Hathora](https://docs.pipecat.ai/server/services/stt/hathora), [NVIDIA Riva](https://docs.pipecat.ai/server/services/stt/riva), [OpenAI (Whisper)](https://docs.pipecat.ai/server/services/stt/openai), [SambaNova (Whisper)](https://docs.pipecat.ai/server/services/stt/sambanova), [Sarvam](https://docs.pipecat.ai/server/services/stt/sarvam), [Soniox](https://docs.pipecat.ai/server/services/stt/soniox), [Speechmatics](https://docs.pipecat.ai/server/services/stt/speechmatics), [Whisper](https://docs.pipecat.ai/server/services/stt/whisper) | | LLMs | [Anthropic](https://docs.pipecat.ai/server/services/llm/anthropic), [AWS](https://docs.pipecat.ai/server/services/llm/aws), [Azure](https://docs.pipecat.ai/server/services/llm/azure), [Cerebras](https://docs.pipecat.ai/server/services/llm/cerebras), [DeepSeek](https://docs.pipecat.ai/server/services/llm/deepseek), [Fireworks AI](https://docs.pipecat.ai/server/services/llm/fireworks), [Gemini](https://docs.pipecat.ai/server/services/llm/gemini), [Grok](https://docs.pipecat.ai/server/services/llm/grok), [Groq](https://docs.pipecat.ai/server/services/llm/groq), [Mistral](https://docs.pipecat.ai/server/services/llm/mistral), [NVIDIA NIM](https://docs.pipecat.ai/server/services/llm/nim), [Ollama](https://docs.pipecat.ai/server/services/llm/ollama), [OpenAI](https://docs.pipecat.ai/server/services/llm/openai), [OpenRouter](https://docs.pipecat.ai/server/services/llm/openrouter), [Perplexity](https://docs.pipecat.ai/server/services/llm/perplexity), [Qwen](https://docs.pipecat.ai/server/services/llm/qwen), [SambaNova](https://docs.pipecat.ai/server/services/llm/sambanova) [Together AI](https://docs.pipecat.ai/server/services/llm/together) | -| Text-to-Speech | [Async](https://docs.pipecat.ai/server/services/tts/asyncai), [AWS](https://docs.pipecat.ai/server/services/tts/aws), [Azure](https://docs.pipecat.ai/server/services/tts/azure), [Camb AI](https://docs.pipecat.ai/server/services/tts/camb), [Cartesia](https://docs.pipecat.ai/server/services/tts/cartesia), [Deepgram](https://docs.pipecat.ai/server/services/tts/deepgram), [ElevenLabs](https://docs.pipecat.ai/server/services/tts/elevenlabs), [Fish](https://docs.pipecat.ai/server/services/tts/fish), [Google](https://docs.pipecat.ai/server/services/tts/google), [Gradium](https://docs.pipecat.ai/server/services/tts/gradium), [Groq](https://docs.pipecat.ai/server/services/tts/groq), [Hathora](https://docs.pipecat.ai/server/services/tts/hathora), [Hume](https://docs.pipecat.ai/server/services/tts/hume), [Inworld](https://docs.pipecat.ai/server/services/tts/inworld), [LMNT](https://docs.pipecat.ai/server/services/tts/lmnt), [MiniMax](https://docs.pipecat.ai/server/services/tts/minimax), [Neuphonic](https://docs.pipecat.ai/server/services/tts/neuphonic), [NVIDIA Riva](https://docs.pipecat.ai/server/services/tts/riva), [OpenAI](https://docs.pipecat.ai/server/services/tts/openai), [Piper](https://docs.pipecat.ai/server/services/tts/piper), [PlayHT](https://docs.pipecat.ai/server/services/tts/playht), [Rime](https://docs.pipecat.ai/server/services/tts/rime), [Sarvam](https://docs.pipecat.ai/server/services/tts/sarvam), [Speechmatics](https://docs.pipecat.ai/server/services/tts/speechmatics), [XTTS](https://docs.pipecat.ai/server/services/tts/xtts) | +| Text-to-Speech | [Async](https://docs.pipecat.ai/server/services/tts/asyncai), [AWS](https://docs.pipecat.ai/server/services/tts/aws), [Azure](https://docs.pipecat.ai/server/services/tts/azure), [Camb AI](https://docs.pipecat.ai/server/services/tts/camb), [Cartesia](https://docs.pipecat.ai/server/services/tts/cartesia), [Deepgram](https://docs.pipecat.ai/server/services/tts/deepgram), [ElevenLabs](https://docs.pipecat.ai/server/services/tts/elevenlabs), [Fish](https://docs.pipecat.ai/server/services/tts/fish), [Google](https://docs.pipecat.ai/server/services/tts/google), [Gradium](https://docs.pipecat.ai/server/services/tts/gradium), [Groq](https://docs.pipecat.ai/server/services/tts/groq), [Hathora](https://docs.pipecat.ai/server/services/tts/hathora), [Hume](https://docs.pipecat.ai/server/services/tts/hume), [Inworld](https://docs.pipecat.ai/server/services/tts/inworld), [LMNT](https://docs.pipecat.ai/server/services/tts/lmnt), [MiniMax](https://docs.pipecat.ai/server/services/tts/minimax), [Neuphonic](https://docs.pipecat.ai/server/services/tts/neuphonic), [NVIDIA Riva](https://docs.pipecat.ai/server/services/tts/riva), [OpenAI](https://docs.pipecat.ai/server/services/tts/openai), [Piper](https://docs.pipecat.ai/server/services/tts/piper), [PlayHT](https://docs.pipecat.ai/server/services/tts/playht), [Resemble](https://docs.pipecat.ai/server/services/tts/resemble), [Rime](https://docs.pipecat.ai/server/services/tts/rime), [Sarvam](https://docs.pipecat.ai/server/services/tts/sarvam), [Speechmatics](https://docs.pipecat.ai/server/services/tts/speechmatics), [XTTS](https://docs.pipecat.ai/server/services/tts/xtts) | | Speech-to-Speech | [AWS Nova Sonic](https://docs.pipecat.ai/server/services/s2s/aws), [Gemini Multimodal Live](https://docs.pipecat.ai/server/services/s2s/gemini), [Grok Voice Agent](https://docs.pipecat.ai/server/services/s2s/grok), [OpenAI Realtime](https://docs.pipecat.ai/server/services/s2s/openai), [Ultravox](https://docs.pipecat.ai/server/services/s2s/ultravox), | | Transport | [Daily (WebRTC)](https://docs.pipecat.ai/server/services/transport/daily), [FastAPI Websocket](https://docs.pipecat.ai/server/services/transport/fastapi-websocket), [SmallWebRTCTransport](https://docs.pipecat.ai/server/services/transport/small-webrtc), [WebSocket Server](https://docs.pipecat.ai/server/services/transport/websocket-server), Local | | Serializers | [Exotel](https://docs.pipecat.ai/server/utilities/serializers/exotel), [Plivo](https://docs.pipecat.ai/server/utilities/serializers/plivo), [Twilio](https://docs.pipecat.ai/server/utilities/serializers/twilio), [Telnyx](https://docs.pipecat.ai/server/utilities/serializers/telnyx), [Vonage](https://docs.pipecat.ai/server/utilities/serializers/vonage) | From 86147f15f3b7977bf7b93830a2152c2c2f891d39 Mon Sep 17 00:00:00 2001 From: Mark Backman Date: Mon, 2 Feb 2026 09:07:05 -0500 Subject: [PATCH 0332/1060] Renumber the Resemble foundational example --- ...i-interruptible-resemble.py => 07zk-interruptible-resemble.py} | 0 1 file changed, 0 insertions(+), 0 deletions(-) rename examples/foundational/{07zi-interruptible-resemble.py => 07zk-interruptible-resemble.py} (100%) diff --git a/examples/foundational/07zi-interruptible-resemble.py b/examples/foundational/07zk-interruptible-resemble.py similarity index 100% rename from examples/foundational/07zi-interruptible-resemble.py rename to examples/foundational/07zk-interruptible-resemble.py From 4c10ddb7bb48b6dc332a5b36e646e1537891185e Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Aleix=20Conchillo=20Flaqu=C3=A9?= Date: Mon, 2 Feb 2026 16:24:38 -0800 Subject: [PATCH 0333/1060] upgrade uv.lock --- uv.lock | 517 ++++++++++++++++++++++++++++++++++---------------------- 1 file changed, 315 insertions(+), 202 deletions(-) diff --git a/uv.lock b/uv.lock index 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Adds explicit StopAsyncIteration handling for both first and second message retrieval. Co-Authored-By: Claude Sonnet 4.5 --- src/pipecat/runner/utils.py | 27 ++++++++++++++++++--------- 1 file changed, 18 insertions(+), 9 deletions(-) diff --git a/src/pipecat/runner/utils.py b/src/pipecat/runner/utils.py index f54453d93..2a56bb0f4 100644 --- a/src/pipecat/runner/utils.py +++ b/src/pipecat/runner/utils.py @@ -147,19 +147,28 @@ async def parse_telephony_websocket(websocket: WebSocket): try: # First message - first_message_raw = await start_data.__anext__() - logger.trace(f"First message: {first_message_raw}") try: - first_message = json.loads(first_message_raw) - except json.JSONDecodeError: - first_message = {} + first_message_raw = await start_data.__anext__() + logger.trace(f"First message: {first_message_raw}") + try: + first_message = json.loads(first_message_raw) + except json.JSONDecodeError: + first_message = {} + except StopAsyncIteration: + logger.error("WebSocket closed without sending any messages") + raise ValueError("WebSocket closed before receiving telephony handshake messages") # Second message - second_message_raw = await start_data.__anext__() - logger.trace(f"Second message: {second_message_raw}") try: - second_message = json.loads(second_message_raw) - except json.JSONDecodeError: + second_message_raw = await start_data.__anext__() + logger.trace(f"Second message: {second_message_raw}") + try: + second_message = json.loads(second_message_raw) + except json.JSONDecodeError: + second_message = {} + except StopAsyncIteration: + # Only one message received - use it for detection + logger.warning("Only received one WebSocket message, expected two") second_message = {} # Try auto-detection on both messages From b030f1178dc4b42e07e89276346a730c850f8a83 Mon Sep 17 00:00:00 2001 From: James Hush Date: Tue, 3 Feb 2026 16:26:09 +0800 Subject: [PATCH 0335/1060] Add changelog and improve docstring for parse_telephony_websocket - Added changelog entry for bug fix - Enhanced docstring with Args and Raises sections Co-Authored-By: Claude Sonnet 4.5 --- changelog/3629.fixed.md | 1 + src/pipecat/runner/utils.py | 6 ++++++ 2 files changed, 7 insertions(+) create mode 100644 changelog/3629.fixed.md diff --git a/changelog/3629.fixed.md b/changelog/3629.fixed.md new file mode 100644 index 000000000..12792f47d --- /dev/null +++ b/changelog/3629.fixed.md @@ -0,0 +1 @@ +- Fixed `StopAsyncIteration` exceptions in `parse_telephony_websocket()` when WebSocket connections close before sending expected messages. diff --git a/src/pipecat/runner/utils.py b/src/pipecat/runner/utils.py index 2a56bb0f4..a3be74436 100644 --- a/src/pipecat/runner/utils.py +++ b/src/pipecat/runner/utils.py @@ -96,6 +96,9 @@ def _detect_transport_type_from_message(message_data: dict) -> str: async def parse_telephony_websocket(websocket: WebSocket): """Parse telephony WebSocket messages and return transport type and call data. + Args: + websocket: FastAPI WebSocket connection from telephony provider. + Returns: tuple: (transport_type: str, call_data: dict) @@ -136,6 +139,9 @@ async def parse_telephony_websocket(websocket: WebSocket): "to": str, } + Raises: + ValueError: If WebSocket closes before sending any messages. + Example usage:: transport_type, call_data = await parse_telephony_websocket(websocket) From b427d534ae5889e6e1e8f5c224a08eb04cff8b50 Mon Sep 17 00:00:00 2001 From: James Hush Date: Tue, 3 Feb 2026 16:33:36 +0800 Subject: [PATCH 0336/1060] Add tests for parse_telephony_websocket StopAsyncIteration handling Tests cover: - No messages received (raises ValueError) - One message received (logs warning, continues) - Two messages received (normal operation) - All telephony providers (Twilio, Telnyx, Plivo, Exotel) Co-Authored-By: Claude Sonnet 4.5 --- tests/test_runner_utils.py | 153 +++++++++++++++++++++++++++++++++++++ 1 file changed, 153 insertions(+) create mode 100644 tests/test_runner_utils.py diff --git a/tests/test_runner_utils.py b/tests/test_runner_utils.py new file mode 100644 index 000000000..e5fe28786 --- /dev/null +++ b/tests/test_runner_utils.py @@ -0,0 +1,153 @@ +# +# Copyright (c) 2024-2026, Daily +# +# SPDX-License-Identifier: BSD 2-Clause License +# + +import json +import unittest +from unittest.mock import AsyncMock, MagicMock + +from pipecat.runner.utils import parse_telephony_websocket + + +class MockAsyncIterator: + """Mock async iterator for WebSocket messages.""" + + def __init__(self, messages): + self.messages = messages + self.index = 0 + + def __aiter__(self): + return self + + async def __anext__(self): + if self.index >= len(self.messages): + raise StopAsyncIteration + message = self.messages[self.index] + self.index += 1 + return message + + +class TestParseTelephonyWebSocket(unittest.IsolatedAsyncioTestCase): + async def test_no_messages_raises_value_error(self): + """Test that no messages raises ValueError.""" + mock_websocket = MagicMock() + mock_websocket.iter_text.return_value = MockAsyncIterator([]) + + with self.assertRaises(ValueError) as context: + await parse_telephony_websocket(mock_websocket) + + self.assertIn("WebSocket closed before receiving", str(context.exception)) + + async def test_one_message_logs_warning_and_continues(self): + """Test that one message logs warning but continues processing.""" + twilio_message = json.dumps( + { + "event": "start", + "start": { + "streamSid": "MZ123", + "callSid": "CA123", + "customParameters": {"user_id": "test_user"}, + }, + } + ) + + mock_websocket = MagicMock() + mock_websocket.iter_text.return_value = MockAsyncIterator([twilio_message]) + + transport_type, call_data = await parse_telephony_websocket(mock_websocket) + + self.assertEqual(transport_type, "twilio") + self.assertEqual(call_data["stream_id"], "MZ123") + self.assertEqual(call_data["call_id"], "CA123") + + async def test_two_messages_normal_operation(self): + """Test normal operation with two messages.""" + first_message = json.dumps({"event": "connected"}) + twilio_message = json.dumps( + { + "event": "start", + "start": { + "streamSid": "MZ456", + "callSid": "CA456", + "customParameters": {}, + }, + } + ) + + mock_websocket = MagicMock() + mock_websocket.iter_text.return_value = MockAsyncIterator([first_message, twilio_message]) + + transport_type, call_data = await parse_telephony_websocket(mock_websocket) + + self.assertEqual(transport_type, "twilio") + self.assertEqual(call_data["stream_id"], "MZ456") + self.assertEqual(call_data["call_id"], "CA456") + + async def test_telnyx_detection(self): + """Test Telnyx provider detection.""" + telnyx_message = json.dumps( + { + "stream_id": "stream_123", + "start": { + "call_control_id": "cc_123", + "media_format": {"encoding": "PCMU"}, + "from": "+15551234567", + "to": "+15559876543", + }, + } + ) + + mock_websocket = MagicMock() + mock_websocket.iter_text.return_value = MockAsyncIterator([telnyx_message]) + + transport_type, call_data = await parse_telephony_websocket(mock_websocket) + + self.assertEqual(transport_type, "telnyx") + self.assertEqual(call_data["stream_id"], "stream_123") + self.assertEqual(call_data["call_control_id"], "cc_123") + + async def test_plivo_detection(self): + """Test Plivo provider detection.""" + plivo_message = json.dumps( + {"start": {"streamId": "stream_plivo_123", "callId": "call_plivo_123"}} + ) + + mock_websocket = MagicMock() + mock_websocket.iter_text.return_value = MockAsyncIterator([plivo_message]) + + transport_type, call_data = await parse_telephony_websocket(mock_websocket) + + self.assertEqual(transport_type, "plivo") + self.assertEqual(call_data["stream_id"], "stream_plivo_123") + self.assertEqual(call_data["call_id"], "call_plivo_123") + + async def test_exotel_detection(self): + """Test Exotel provider detection.""" + exotel_message = json.dumps( + { + "event": "start", + "start": { + "stream_sid": "stream_exo_123", + "call_sid": "call_exo_123", + "account_sid": "acc_123", + "from": "+15551111111", + "to": "+15552222222", + }, + } + ) + + mock_websocket = MagicMock() + mock_websocket.iter_text.return_value = MockAsyncIterator([exotel_message]) + + transport_type, call_data = await parse_telephony_websocket(mock_websocket) + + self.assertEqual(transport_type, "exotel") + self.assertEqual(call_data["stream_id"], "stream_exo_123") + self.assertEqual(call_data["call_id"], "call_exo_123") + self.assertEqual(call_data["account_sid"], "acc_123") + + +if __name__ == "__main__": + unittest.main() From 90bead06ab8fce226bb25f5e28b830dbeb88b151 Mon Sep 17 00:00:00 2001 From: James Hush Date: Tue, 3 Feb 2026 16:42:13 +0800 Subject: [PATCH 0337/1060] Apply suggestions from code review Co-authored-by: Copilot <175728472+Copilot@users.noreply.github.com> --- src/pipecat/runner/utils.py | 2 +- tests/test_runner_utils.py | 2 +- 2 files changed, 2 insertions(+), 2 deletions(-) diff --git a/src/pipecat/runner/utils.py b/src/pipecat/runner/utils.py index a3be74436..5188beae2 100644 --- a/src/pipecat/runner/utils.py +++ b/src/pipecat/runner/utils.py @@ -161,7 +161,7 @@ async def parse_telephony_websocket(websocket: WebSocket): except json.JSONDecodeError: first_message = {} except StopAsyncIteration: - logger.error("WebSocket closed without sending any messages") + raise ValueError("WebSocket closed before receiving telephony handshake messages") # Second message diff --git a/tests/test_runner_utils.py b/tests/test_runner_utils.py index e5fe28786..18f156cbb 100644 --- a/tests/test_runner_utils.py +++ b/tests/test_runner_utils.py @@ -6,7 +6,7 @@ import json import unittest -from unittest.mock import AsyncMock, MagicMock +from unittest.mock import MagicMock from pipecat.runner.utils import parse_telephony_websocket From 803a20cc00e26be38a56d7cf2201713bce1cf469 Mon Sep 17 00:00:00 2001 From: James Hush Date: Tue, 3 Feb 2026 16:46:44 +0800 Subject: [PATCH 0338/1060] Fix formatting: remove extra blank line Co-Authored-By: Claude Sonnet 4.5 --- src/pipecat/runner/utils.py | 1 - 1 file changed, 1 deletion(-) diff --git a/src/pipecat/runner/utils.py b/src/pipecat/runner/utils.py index 5188beae2..2208b7db4 100644 --- a/src/pipecat/runner/utils.py +++ b/src/pipecat/runner/utils.py @@ -161,7 +161,6 @@ async def parse_telephony_websocket(websocket: WebSocket): except json.JSONDecodeError: first_message = {} except StopAsyncIteration: - raise ValueError("WebSocket closed before receiving telephony handshake messages") # Second message From 1665ce181ae1400ad518f4bbfbe087c42cf9421b Mon Sep 17 00:00:00 2001 From: dhruvladia-sarvam Date: Tue, 3 Feb 2026 14:33:41 +0530 Subject: [PATCH 0339/1060] refactor(sarvam): centralize model configuration with dataclasses --- src/pipecat/services/sarvam/stt.py | 176 ++++++++++--------- src/pipecat/services/sarvam/tts.py | 266 ++++++++++++++--------------- 2 files changed, 227 insertions(+), 215 deletions(-) diff --git a/src/pipecat/services/sarvam/stt.py b/src/pipecat/services/sarvam/stt.py index ec5e42df0..799c79921 100644 --- a/src/pipecat/services/sarvam/stt.py +++ b/src/pipecat/services/sarvam/stt.py @@ -6,7 +6,8 @@ can handle multiple audio formats for Indian language speech recognition. """ import base64 -from typing import Literal, Optional +from dataclasses import dataclass +from typing import Dict, Literal, Optional from loguru import logger from pydantic import BaseModel @@ -68,6 +69,60 @@ def language_to_sarvam_language(language: Language) -> str: return resolve_language(language, LANGUAGE_MAP, use_base_code=False) +@dataclass(frozen=True) +class ModelConfig: + """Immutable configuration for a Sarvam STT model. + + Attributes: + supports_prompt: Whether the model accepts prompt parameter. + supports_mode: Whether the model accepts mode parameter. + supports_language: Whether the model accepts language parameter. + default_language: Default language code (None = auto-detect). + default_mode: Default mode (None = not applicable). + use_translate_endpoint: Whether to use speech_to_text_translate_streaming endpoint. + use_translate_method: Whether to use translate() method instead of transcribe(). + """ + + supports_prompt: bool + supports_mode: bool + supports_language: bool + default_language: Optional[str] + default_mode: Optional[str] + use_translate_endpoint: bool + use_translate_method: bool + + +MODEL_CONFIGS: Dict[str, ModelConfig] = { + "saarika:v2.5": ModelConfig( + supports_prompt=False, + supports_mode=False, + supports_language=True, + default_language="unknown", + default_mode=None, + use_translate_endpoint=False, + use_translate_method=False, + ), + "saaras:v2.5": ModelConfig( + supports_prompt=True, + supports_mode=False, + supports_language=False, + default_language=None, # Auto-detects language + default_mode=None, + use_translate_endpoint=True, + use_translate_method=True, + ), + "saaras:v3": ModelConfig( + supports_prompt=True, + supports_mode=True, + supports_language=True, + default_language="en-IN", + default_mode="transcribe", + use_translate_endpoint=False, + use_translate_method=False, + ), +} + + class SarvamSTTService(STTService): """Sarvam speech-to-text service. @@ -103,9 +158,6 @@ class SarvamSTTService(STTService): model: str = "saarika:v2.5", sample_rate: Optional[int] = None, input_audio_codec: str = "wav", - mode: Optional[ - Literal["transcribe", "translate", "verbatim", "translit", "codemix"] - ] = None, params: Optional[InputParams] = None, **kwargs, ): @@ -119,73 +171,44 @@ class SarvamSTTService(STTService): - "saaras:v3": Advanced STT model (supports mode and prompts) sample_rate: Audio sample rate. Defaults to 16000 if not specified. input_audio_codec: Audio codec/format of the input file. Defaults to "wav". - mode: Mode of operation for saaras:v3 models only. Options: transcribe, translate, - verbatim, translit, codemix. Defaults to "transcribe" for saaras:v3. params: Configuration parameters for Sarvam STT service. **kwargs: Additional arguments passed to the parent STTService. """ params = params or SarvamSTTService.InputParams() - # Allow mode to be passed directly or via params - if mode is not None and params.mode is None: - params = params.model_copy(update={"mode": mode}) - # Validate allowed models - allowed_models = {"saarika:v2.5", "saaras:v3", "saaras:v2.5"} - if model not in allowed_models: - allowed_models_list = ", ".join(sorted(allowed_models)) - raise ValueError(f"Unsupported model '{model}'. Allowed values: {allowed_models_list}.") + # Get model configuration (validates model exists) + if model not in MODEL_CONFIGS: + allowed = ", ".join(sorted(MODEL_CONFIGS.keys())) + raise ValueError(f"Unsupported model '{model}'. Allowed values: {allowed}.") - # Validate model-specific parameter restrictions - if "saarika" in model.lower(): - # saarika models don't accept prompt or mode - if params.prompt is not None: - raise ValueError( - f"Model '{model}' does not accept prompt parameter. " - "Prompts are only supported for saaras models (v2.5 and v3)." - ) - if params.mode is not None: - raise ValueError( - f"Model '{model}' does not accept mode parameter. " - "Mode is only supported for saaras:v3 model." - ) - elif model.lower() == "saaras:v2.5": - # saaras:v2.5 supports prompt but not mode - if params.mode is not None: - raise ValueError( - f"Model '{model}' does not accept mode parameter. " - "Mode is only supported for saaras:v3 model." - ) - if params.language is not None: - raise ValueError( - f"Model '{model}' does not accept language parameter. " - "saaras:v2.5 (STT-Translate) auto-detects language." - ) + self._config = MODEL_CONFIGS[model] + + # Validate parameters against model capabilities + if params.prompt is not None and not self._config.supports_prompt: + raise ValueError(f"Model '{model}' does not support prompt parameter.") + if params.mode is not None and not self._config.supports_mode: + raise ValueError(f"Model '{model}' does not support mode parameter.") + if params.language is not None and not self._config.supports_language: + raise ValueError( + f"Model '{model}' does not support language parameter (auto-detects language)." + ) super().__init__(sample_rate=sample_rate, **kwargs) self.set_model_name(model) self._api_key = api_key self._language_code: Optional[Language] = params.language - # Set language string based on model type - # - saarika:v2.5: uses language_code or defaults to "unknown" - # - saaras:v2.5: auto-detects language (no language_code needed) - # - saaras:v3: uses language_code or defaults to "en-IN" + + # Set language string: use provided language or model's default if params.language: self._language_string = language_to_sarvam_language(params.language) - elif "saarika" in model.lower(): - self._language_string = "unknown" - elif model.lower() == "saaras:v2.5": - self._language_string = None # STT-Translate auto-detects language - elif model.lower() == "saaras:v3": - self._language_string = "en-IN" else: - self._language_string = None + self._language_string = self._config.default_language + self._prompt = params.prompt - # Set mode for saaras:v3, default to "transcribe" - if model.lower() == "saaras:v3": - self._mode = params.mode if params.mode is not None else "transcribe" - else: - self._mode = None + + # Set mode: use provided mode or model's default + self._mode = params.mode if params.mode is not None else self._config.default_mode # Store connection parameters self._vad_signals = params.vad_signals @@ -250,13 +273,12 @@ class SarvamSTTService(STTService): language: The language to use for speech recognition. Raises: - ValueError: If called on saaras:v2.5 model which auto-detects language. + ValueError: If called on a model that auto-detects language. """ - # saaras:v2.5 (STT-Translate) auto-detects language - if self.model_name.lower() == "saaras:v2.5": + if not self._config.supports_language: raise ValueError( - f"Model '{self.model_name}' does not accept language parameter. " - "saaras:v2.5 (STT-Translate) auto-detects language." + f"Model '{self.model_name}' does not support language parameter " + "(auto-detects language)." ) logger.info(f"Switching STT language to: [{language}]") @@ -271,16 +293,12 @@ class SarvamSTTService(STTService): Args: prompt: Prompt text to guide transcription/translation style/context. Pass None to clear/disable prompt. - Only applicable to saaras models (v2.5 and v3). + Only applicable to models that support prompts. """ - # saarika models do not accept prompt parameter - if "saarika" in self.model_name.lower(): + if not self._config.supports_prompt: if prompt is not None: - raise ValueError( - f"Model '{self.model_name}' does not accept prompt parameter. " - "Prompts are only supported for saaras models (v2.5 and v3)." - ) - # If prompt is None and it's saarika, just silently return (no-op) + raise ValueError(f"Model '{self.model_name}' does not support prompt parameter.") + # If prompt is None and model doesn't support prompts, silently return (no-op) return logger.info(f"Updating {self.model_name} prompt.") @@ -347,12 +365,10 @@ class SarvamSTTService(STTService): "sample_rate": self.sample_rate, } - # Use appropriate method based on model type - if self.model_name.lower() == "saaras:v2.5": - # STT-Translate: auto-detects input language and returns translated text + # Use appropriate method based on model configuration + if self._config.use_translate_method: await self._socket_client.translate(**method_kwargs) else: - # saarika:v2.5 and saaras:v3 use transcribe await self._socket_client.transcribe(**method_kwargs) except Exception as e: @@ -377,12 +393,12 @@ class SarvamSTTService(STTService): "sample_rate": str(self.sample_rate), } - # Add language_code for models that require it (not saaras:v2.5 which auto-detects) + # Add language_code for models that support it if self._language_string is not None: connect_kwargs["language_code"] = self._language_string - # Add mode for saaras:v3 only - if self.model_name.lower() == "saaras:v3" and self._mode is not None: + # Add mode for models that support it + if self._config.supports_mode and self._mode is not None: connect_kwargs["mode"] = self._mode def _connect_with_sdk_headers(connect_fn, **kwargs): @@ -394,15 +410,13 @@ class SarvamSTTService(STTService): pass return connect_fn(**kwargs) - # Choose the appropriate endpoint based on model - if self.model_name.lower() == "saaras:v2.5": - # STT-Translate: auto-detects input language and returns translated text + # Choose the appropriate endpoint based on model configuration + if self._config.use_translate_endpoint: self._websocket_context = _connect_with_sdk_headers( self._sarvam_client.speech_to_text_translate_streaming.connect, **connect_kwargs, ) else: - # saarika:v2.5 and saaras:v3 use speech_to_text_streaming self._websocket_context = _connect_with_sdk_headers( self._sarvam_client.speech_to_text_streaming.connect, **connect_kwargs, @@ -411,8 +425,8 @@ class SarvamSTTService(STTService): # Enter the async context manager self._socket_client = await self._websocket_context.__aenter__() - # Set prompt if provided (only for saaras models, after connection) - if self._prompt is not None and "saaras" in self.model_name.lower(): + # Set prompt if provided (only for models that support prompts) + if self._prompt is not None and self._config.supports_prompt: await self._socket_client.set_prompt(self._prompt) # Register event handler for incoming messages diff --git a/src/pipecat/services/sarvam/tts.py b/src/pipecat/services/sarvam/tts.py index bd63558a8..b6819185a 100644 --- a/src/pipecat/services/sarvam/tts.py +++ b/src/pipecat/services/sarvam/tts.py @@ -31,8 +31,9 @@ See https://docs.sarvam.ai/api-reference-docs/text-to-speech/stream for full API import asyncio import base64 import json +from dataclasses import dataclass from enum import Enum -from typing import Any, AsyncGenerator, List, Mapping, Optional +from typing import Any, AsyncGenerator, Dict, List, Mapping, Optional, Tuple import aiohttp from loguru import logger @@ -133,16 +134,52 @@ class SarvamTTSSpeakerV3(str, Enum): SOPHIA = "sophia" -# Default sample rates per model -SARVAM_DEFAULT_SAMPLE_RATES = { - SarvamTTSModel.BULBUL_V2: 22050, - SarvamTTSModel.BULBUL_V3_BETA: 24000, -} +@dataclass(frozen=True) +class TTSModelConfig: + """Immutable configuration for a Sarvam TTS model. -# Default speakers per model -SARVAM_DEFAULT_SPEAKERS = { - SarvamTTSModel.BULBUL_V2: SarvamTTSSpeakerV2.ANUSHKA.value, - SarvamTTSModel.BULBUL_V3_BETA: SarvamTTSSpeakerV3.ADITYA.value, + Attributes: + supports_pitch: Whether the model accepts pitch parameter. + supports_loudness: Whether the model accepts loudness parameter. + supports_temperature: Whether the model accepts temperature parameter. + default_sample_rate: Default audio sample rate in Hz. + default_speaker: Default speaker voice ID. + pace_range: Valid range for pace parameter (min, max). + preprocessing_always_enabled: Whether preprocessing is always enabled. + speakers: Tuple of available speaker names for this model. + """ + + supports_pitch: bool + supports_loudness: bool + supports_temperature: bool + default_sample_rate: int + default_speaker: str + pace_range: Tuple[float, float] + preprocessing_always_enabled: bool + speakers: Tuple[str, ...] + + +TTS_MODEL_CONFIGS: Dict[str, TTSModelConfig] = { + "bulbul:v2": TTSModelConfig( + supports_pitch=True, + supports_loudness=True, + supports_temperature=False, + default_sample_rate=22050, + default_speaker="anushka", + pace_range=(0.3, 3.0), + preprocessing_always_enabled=False, + speakers=tuple(s.value for s in SarvamTTSSpeakerV2), + ), + "bulbul:v3-beta": TTSModelConfig( + supports_pitch=False, + supports_loudness=False, + supports_temperature=True, + default_sample_rate=24000, + default_speaker="aditya", + pace_range=(0.5, 2.0), + preprocessing_always_enabled=True, + speakers=tuple(s.value for s in SarvamTTSSpeakerV3), + ), } @@ -155,9 +192,10 @@ def get_speakers_for_model(model: str) -> List[str]: Returns: List of speaker names available for the model. """ - if model in (SarvamTTSModel.BULBUL_V3_BETA.value): - return [s.value for s in SarvamTTSSpeakerV3] - return [s.value for s in SarvamTTSSpeakerV2] + if model in TTS_MODEL_CONFIGS: + return list(TTS_MODEL_CONFIGS[model].speakers) + # Default to v2 speakers for unknown models + return list(TTS_MODEL_CONFIGS["bulbul:v2"].speakers) def language_to_sarvam_language(language: Language) -> Optional[str]: @@ -304,35 +342,26 @@ class SarvamHttpTTSService(TTSService): Args: api_key: Sarvam AI API subscription key. aiohttp_session: Shared aiohttp session for making requests. - voice_id: Speaker voice ID. If None, uses model-appropriate default: - - bulbul:v2: "anushka" - - bulbul:v3-beta/v3: "aditya" + voice_id: Speaker voice ID. If None, uses model-appropriate default. model: TTS model to use. Options: - "bulbul:v2" (default): Standard model with pitch/loudness support - "bulbul:v3-beta": Advanced model with temperature control - - "bulbul:v3": Alias for v3-beta base_url: Sarvam AI API base URL. Defaults to "https://api.sarvam.ai". sample_rate: Audio sample rate in Hz (8000, 16000, 22050, 24000). - If None, uses model-specific default (v2: 22050, v3: 24000). + If None, uses model-specific default. params: Additional voice and preprocessing parameters. If None, uses defaults. **kwargs: Additional arguments passed to parent TTSService. - - Note: - When using bulbul:v3-beta: - - pitch and loudness parameters are ignored - - pace range is limited to 0.5-2.0 - - preprocessing is always enabled - - use SarvamTTSSpeakerV3 speakers (e.g., "aditya", "ritu") """ - # Determine if using v3 model - is_v3_model = model in ( - SarvamTTSModel.BULBUL_V3_BETA.value, - "bulbul:v3-beta", - ) + # Get model configuration (validates model exists) + if model not in TTS_MODEL_CONFIGS: + allowed = ", ".join(sorted(TTS_MODEL_CONFIGS.keys())) + raise ValueError(f"Unsupported model '{model}'. Allowed values: {allowed}.") + + self._config = TTS_MODEL_CONFIGS[model] # Set default sample rate based on model if not specified if sample_rate is None: - sample_rate = 24000 if is_v3_model else 22050 + sample_rate = self._config.default_sample_rate super().__init__(sample_rate=sample_rate, **kwargs) @@ -340,55 +369,46 @@ class SarvamHttpTTSService(TTSService): # Set default voice based on model if not specified if voice_id is None: - voice_id = "aditya" if is_v3_model else "anushka" + voice_id = self._config.default_speaker self._api_key = api_key self._base_url = base_url self._session = aiohttp_session - self._is_v3_model = is_v3_model - # Build base settings common to all models + # Validate and clamp pace to model's valid range + pace = params.pace + pace_min, pace_max = self._config.pace_range + if pace is not None and (pace < pace_min or pace > pace_max): + logger.warning(f"Pace {pace} is outside model range ({pace_min}-{pace_max}). Clamping.") + pace = max(pace_min, min(pace_max, pace)) + + # Build base settings self._settings = { "language": ( self.language_to_service_language(params.language) if params.language else "en-IN" ), - "enable_preprocessing": params.enable_preprocessing if not is_v3_model else True, + "enable_preprocessing": ( + True if self._config.preprocessing_always_enabled else params.enable_preprocessing + ), + "pace": pace, + "model": model, } - # Add model-specific parameters - if is_v3_model: - # Validate pace for v3 (0.5-2.0) - pace = params.pace - if pace is not None and (pace < 0.5 or pace > 2.0): - logger.warning( - f"Pace {pace} is outside v3 model range (0.5-2.0). Clamping to valid range." - ) - pace = max(0.5, min(2.0, pace)) + # Add parameters based on model support + if self._config.supports_pitch: + self._settings["pitch"] = params.pitch + elif params.pitch != 0.0: + logger.warning(f"pitch parameter is ignored for {model}") - self._settings.update( - { - "temperature": params.temperature, - "pace": pace, - "model": model, - } - ) - # Log warning if v2-only parameters are set - if params.pitch != 0.0: - logger.warning(f"pitch parameter is ignored for {model}") - if params.loudness != 1.0: - logger.warning(f"loudness parameter is ignored for {model}") - else: - self._settings.update( - { - "pitch": params.pitch, - "pace": params.pace, - "loudness": params.loudness, - "model": model, - } - ) - # Log warning if v3-only parameters are set - if params.temperature != 0.6: - logger.warning(f"temperature parameter is ignored for {model}") + if self._config.supports_loudness: + self._settings["loudness"] = params.loudness + elif params.loudness != 1.0: + logger.warning(f"loudness parameter is ignored for {model}") + + if self._config.supports_temperature: + self._settings["temperature"] = params.temperature + elif params.temperature != 0.6: + logger.warning(f"temperature parameter is ignored for {model}") self.set_model_name(model) self.set_voice(voice_id) @@ -436,7 +456,7 @@ class SarvamHttpTTSService(TTSService): try: await self.start_ttfb_metrics() - # Build payload based on model type + # Build payload with common parameters payload = { "text": text, "target_language_code": self._settings["language"], @@ -444,19 +464,16 @@ class SarvamHttpTTSService(TTSService): "sample_rate": self.sample_rate, "enable_preprocessing": self._settings["enable_preprocessing"], "model": self._model_name, + "pace": self._settings.get("pace", 1.0), } - # Add model-specific parameters - if self._is_v3_model: - # v3 models use temperature and pace (0.5-2.0) - payload["temperature"] = self._settings.get("temperature", 0.6) - if "pace" in self._settings: - payload["pace"] = self._settings["pace"] - else: - # v2 models use pitch, pace, loudness + # Add model-specific parameters based on config + if self._config.supports_pitch: payload["pitch"] = self._settings.get("pitch", 0.0) - payload["pace"] = self._settings.get("pace", 1.0) + if self._config.supports_loudness: payload["loudness"] = self._settings.get("loudness", 1.0) + if self._config.supports_temperature: + payload["temperature"] = self._settings.get("temperature", 0.6) headers = { "api-subscription-key": self._api_key, @@ -669,35 +686,26 @@ class SarvamTTSService(InterruptibleTTSService): model: TTS model to use. Options: - "bulbul:v2" (default): Standard model with pitch/loudness support - "bulbul:v3-beta": Advanced model with temperature control - - "bulbul:v3": Alias for v3-beta - voice_id: Speaker voice ID. If None, uses model-appropriate default: - - bulbul:v2: "anushka" - - bulbul:v3-beta/v3: "aditya" + voice_id: Speaker voice ID. If None, uses model-appropriate default. url: WebSocket URL for the TTS backend (default production URL). aggregate_sentences: Merge multiple sentences into one audio chunk (default True). sample_rate: Output audio sample rate in Hz (8000, 16000, 22050, 24000). - If None, uses model-specific default (v2: 22050, v3: 24000). + If None, uses model-specific default. params: Optional input parameters to override defaults. **kwargs: Arguments forwarded to InterruptibleTTSService. - Note: - When using bulbul:v3-beta: - - pitch and loudness parameters are ignored - - pace range is limited to 0.5-2.0 - - preprocessing is always enabled - - use SarvamTTSSpeakerV3 speakers (e.g., "aditya", "ritu") - See https://docs.sarvam.ai/api-reference-docs/text-to-speech/stream """ - # Determine if using v3 model - is_v3_model = model in ( - SarvamTTSModel.BULBUL_V3_BETA.value, - "bulbul:v3-beta", - ) + # Get model configuration (validates model exists) + if model not in TTS_MODEL_CONFIGS: + allowed = ", ".join(sorted(TTS_MODEL_CONFIGS.keys())) + raise ValueError(f"Unsupported model '{model}'. Allowed values: {allowed}.") + + self._config = TTS_MODEL_CONFIGS[model] # Set default sample rate based on model if not specified if sample_rate is None: - sample_rate = 24000 if is_v3_model else 22050 + sample_rate = self._config.default_sample_rate # Initialize parent class first super().__init__( @@ -712,9 +720,7 @@ class SarvamTTSService(InterruptibleTTSService): # Set default voice based on model if not specified if voice_id is None: - voice_id = "aditya" if is_v3_model else "anushka" - - self._is_v3_model = is_v3_model + voice_id = self._config.default_speaker # WebSocket endpoint URL with model query parameter self._websocket_url = f"{url}?model={model}" @@ -722,54 +728,46 @@ class SarvamTTSService(InterruptibleTTSService): self.set_model_name(model) self.set_voice(voice_id) - # Build base settings common to all models + # Validate and clamp pace to model's valid range + pace = params.pace + pace_min, pace_max = self._config.pace_range + if pace is not None and (pace < pace_min or pace > pace_max): + logger.warning(f"Pace {pace} is outside model range ({pace_min}-{pace_max}). Clamping.") + pace = max(pace_min, min(pace_max, pace)) + + # Build base settings self._settings = { "target_language_code": ( self.language_to_service_language(params.language) if params.language else "en-IN" ), "speaker": voice_id, "speech_sample_rate": str(sample_rate), - "enable_preprocessing": params.enable_preprocessing if not is_v3_model else True, + "enable_preprocessing": ( + True if self._config.preprocessing_always_enabled else params.enable_preprocessing + ), "min_buffer_size": params.min_buffer_size, "max_chunk_length": params.max_chunk_length, "output_audio_codec": params.output_audio_codec, "output_audio_bitrate": params.output_audio_bitrate, + "pace": pace, + "model": model, } - # Add model-specific parameters - if is_v3_model: - # Validate pace for v3 (0.5-2.0) - pace = params.pace - if pace is not None and (pace < 0.5 or pace > 2.0): - logger.warning( - f"Pace {pace} is outside v3 model range (0.5-2.0). Clamping to valid range." - ) - pace = max(0.5, min(2.0, pace)) + # Add parameters based on model support + if self._config.supports_pitch: + self._settings["pitch"] = params.pitch + elif params.pitch != 0.0: + logger.warning(f"pitch parameter is ignored for {model}") - self._settings.update( - { - "temperature": params.temperature, - "pace": pace, - "model": model, - } - ) - # Log warning if v2-only parameters are set - if params.pitch != 0.0: - logger.warning(f"pitch parameter is ignored for {model}") - if params.loudness != 1.0: - logger.warning(f"loudness parameter is ignored for {model}") - else: - self._settings.update( - { - "pitch": params.pitch, - "pace": params.pace, - "loudness": params.loudness, - "model": model, - } - ) - # Log warning if v3-only parameters are set - if params.temperature != 0.6: - logger.warning(f"temperature parameter is ignored for {model}") + if self._config.supports_loudness: + self._settings["loudness"] = params.loudness + elif params.loudness != 1.0: + logger.warning(f"loudness parameter is ignored for {model}") + + if self._config.supports_temperature: + self._settings["temperature"] = params.temperature + elif params.temperature != 0.6: + logger.warning(f"temperature parameter is ignored for {model}") self._started = False self._receive_task = None From 8d3e10f0542c3d6d326b377e52ad41e6df6dc7d7 Mon Sep 17 00:00:00 2001 From: Luke Payyapilli Date: Fri, 23 Jan 2026 10:11:22 -0500 Subject: [PATCH 0340/1060] Make EndFrame and StopFrame uninterruptible to prevent pipeline freeze --- src/pipecat/frames/frames.py | 12 +++- tests/test_frame_processor.py | 101 ++++++++++++++++++++++++++++++++++ 2 files changed, 111 insertions(+), 2 deletions(-) diff --git a/src/pipecat/frames/frames.py b/src/pipecat/frames/frames.py index 8df97d313..b0e196a22 100644 --- a/src/pipecat/frames/frames.py +++ b/src/pipecat/frames/frames.py @@ -1751,7 +1751,7 @@ class BotInterruptionFrame(InterruptionTaskFrame): @dataclass -class EndFrame(ControlFrame): +class EndFrame(ControlFrame, UninterruptibleFrame): """Frame indicating pipeline has ended and should shut down. Indicates that a pipeline has ended and frame processors and pipelines @@ -1760,6 +1760,10 @@ class EndFrame(ControlFrame): that this is a control frame, which means it will be received in the order it was sent. + This frame is marked as UninterruptibleFrame to ensure it is not lost when + an InterruptionFrame is processed. Terminal frames must survive interruption + to guarantee proper pipeline shutdown. + Parameters: reason: Optional reason for pushing an end frame. """ @@ -1771,12 +1775,16 @@ class EndFrame(ControlFrame): @dataclass -class StopFrame(ControlFrame): +class StopFrame(ControlFrame, UninterruptibleFrame): """Frame indicating pipeline should stop but keep processors running. Indicates that a pipeline should be stopped but that the pipeline processors should be kept in a running state. This is normally queued from the pipeline task. + + This frame is marked as UninterruptibleFrame to ensure it is not lost when + an InterruptionFrame is processed. Terminal frames must survive interruption + to guarantee proper pipeline control. """ pass diff --git a/tests/test_frame_processor.py b/tests/test_frame_processor.py index f44181858..3a47520b3 100644 --- a/tests/test_frame_processor.py +++ b/tests/test_frame_processor.py @@ -15,6 +15,7 @@ from pipecat.frames.frames import ( Frame, InterruptionFrame, OutputTransportMessageUrgentFrame, + StopFrame, SystemFrame, TextFrame, UninterruptibleFrame, @@ -348,6 +349,106 @@ class TestFrameProcessor(unittest.IsolatedAsyncioTestCase): self.assertIs(down_frame.metadata, orig.metadata) self.assertIs(up_frame.metadata, orig.metadata) + async def test_terminal_frames_survive_interruption(self): + """Test that EndFrame survives interruption (it is uninterruptible). + + This test simulates issue #3524 where an InterruptionFrame during slow + processing would cause terminal frames to be lost, freezing the pipeline. + """ + received_frames: List[Frame] = [] + + class DelayAndInterruptProcessor(FrameProcessor): + """This processor delays processing and then generates an interruption. + + When processing a TextFrame, it sleeps and then pushes an + InterruptionFrame to simulate what happens when interruption occurs + while a terminal frame is in the queue. + """ + + async def process_frame(self, frame: Frame, direction: FrameDirection): + await super().process_frame(frame, direction) + if isinstance(frame, TextFrame): + # Delay to allow EndFrame to be queued + await asyncio.sleep(0.1) + # Push interruption - this should NOT discard the EndFrame + await self.push_frame(InterruptionFrame(), direction) + await self.push_frame(frame, direction) + + class CaptureFrameProcessor(FrameProcessor): + async def process_frame(self, frame: Frame, direction: FrameDirection): + await super().process_frame(frame, direction) + received_frames.append(frame) + await self.push_frame(frame, direction) + + pipeline = Pipeline([DelayAndInterruptProcessor(), CaptureFrameProcessor()]) + + frames_to_send = [ + TextFrame(text="trigger"), + ] + expected_down_frames = [ + InterruptionFrame, + TextFrame, + ] + await run_test( + pipeline, + frames_to_send=frames_to_send, + expected_down_frames=expected_down_frames, + ) + + # Verify EndFrame was received by our capture processor (survived interruption) + # Note: run_test filters EndFrame from expected_down_frames when send_end_frame=True, + # but our capture processor sees it before that filtering. + end_frames = [f for f in received_frames if isinstance(f, EndFrame)] + self.assertEqual(len(end_frames), 1, "EndFrame should survive interruption") + + async def test_stop_frame_survives_interruption(self): + """Test that StopFrame survives interruption (it is uninterruptible). + + Similar to test_terminal_frames_survive_interruption but specifically + for StopFrame. + """ + received_frames: List[Frame] = [] + + class DelayAndInterruptProcessor(FrameProcessor): + """This processor delays processing and then generates an interruption.""" + + async def process_frame(self, frame: Frame, direction: FrameDirection): + await super().process_frame(frame, direction) + if isinstance(frame, TextFrame): + # Delay to allow StopFrame to be queued + await asyncio.sleep(0.1) + # Push interruption - this should NOT discard the StopFrame + await self.push_frame(InterruptionFrame(), direction) + await self.push_frame(frame, direction) + + class CaptureFrameProcessor(FrameProcessor): + async def process_frame(self, frame: Frame, direction: FrameDirection): + await super().process_frame(frame, direction) + received_frames.append(frame) + await self.push_frame(frame, direction) + + pipeline = Pipeline([DelayAndInterruptProcessor(), CaptureFrameProcessor()]) + + frames_to_send = [ + TextFrame(text="trigger"), + StopFrame(), + ] + expected_down_frames = [ + InterruptionFrame, + TextFrame, + StopFrame, + ] + await run_test( + pipeline, + frames_to_send=frames_to_send, + expected_down_frames=expected_down_frames, + send_end_frame=False, + ) + + # Verify StopFrame was received (survived interruption) + stop_frames = [f for f in received_frames if isinstance(f, StopFrame)] + self.assertEqual(len(stop_frames), 1, "StopFrame should survive interruption") + if __name__ == "__main__": unittest.main() From 5d5b19e1d2fd9bde951eea94740114ce074f501c Mon Sep 17 00:00:00 2001 From: Luke Payyapilli Date: Fri, 23 Jan 2026 10:19:14 -0500 Subject: [PATCH 0341/1060] Add changelog entry --- changelog/3542.fixed.md | 1 + 1 file changed, 1 insertion(+) create mode 100644 changelog/3542.fixed.md diff --git a/changelog/3542.fixed.md b/changelog/3542.fixed.md new file mode 100644 index 000000000..523754b28 --- /dev/null +++ b/changelog/3542.fixed.md @@ -0,0 +1 @@ +- Fixed pipeline freeze when `InterruptionFrame` discards `EndFrame` or `StopFrame` by making terminal frames uninterruptible. From 84cd9346f9e1d19ffdaab9e32373a71e63e5dae7 Mon Sep 17 00:00:00 2001 From: Mark Backman Date: Tue, 3 Feb 2026 08:52:02 -0500 Subject: [PATCH 0342/1060] Add native RTVI function call lifecycle messages --- changelog/3630.added.md | 1 + src/pipecat/processors/frameworks/rtvi.py | 87 ++++++++++++++++++++++- 2 files changed, 87 insertions(+), 1 deletion(-) create mode 100644 changelog/3630.added.md diff --git a/changelog/3630.added.md b/changelog/3630.added.md new file mode 100644 index 000000000..f4b9e8060 --- /dev/null +++ b/changelog/3630.added.md @@ -0,0 +1 @@ +- Added native RTVI function call lifecycle messages (`llm-function-call-start`, `llm-function-call`, `llm-function-call-cancelled`, `llm-function-call-result`) for visual feedback when bot executes functions. \ No newline at end of file diff --git a/src/pipecat/processors/frameworks/rtvi.py b/src/pipecat/processors/frameworks/rtvi.py index 87ad556d9..ce2322da8 100644 --- a/src/pipecat/processors/frameworks/rtvi.py +++ b/src/pipecat/processors/frameworks/rtvi.py @@ -44,7 +44,10 @@ from pipecat.frames.frames import ( EndTaskFrame, ErrorFrame, Frame, + FunctionCallCancelFrame, + FunctionCallInProgressFrame, FunctionCallResultFrame, + FunctionCallsStartedFrame, InputAudioRawFrame, InputTransportMessageFrame, InterimTranscriptionFrame, @@ -655,7 +658,7 @@ class RTVILLMFunctionCallStartMessage(BaseModel): """ label: RTVIMessageLiteral = RTVI_MESSAGE_LABEL - type: Literal["llm-function-call-start"] = "llm-function-call-start" + type: Literal["llm-function-call-started"] = "llm-function-call-started" data: RTVILLMFunctionCallStartMessageData @@ -671,6 +674,52 @@ class RTVILLMFunctionCallResultData(BaseModel): result: dict | str +class RTVILLMFunctionCallInProgressMessageData(BaseModel): + """Data for LLM function call in-progress notification. + + Contains function call details including name, ID, and arguments. + """ + + function_name: str + tool_call_id: str + args: Mapping[str, Any] + + +class RTVILLMFunctionCallInProgressMessage(BaseModel): + """Message notifying that an LLM function call is in progress. + + Sent when the LLM function call execution begins. + """ + + label: RTVIMessageLiteral = RTVI_MESSAGE_LABEL + type: Literal["llm-function-call-in-progress"] = "llm-function-call-in-progress" + data: RTVILLMFunctionCallInProgressMessageData + + +class RTVILLMFunctionCallStoppedMessageData(BaseModel): + """Data for LLM function call stopped notification. + + Contains details about the function call that stopped, including + whether it was cancelled or completed with a result. + """ + + function_name: str + tool_call_id: str + cancelled: bool + result: Optional[Any] = None + + +class RTVILLMFunctionCallStoppedMessage(BaseModel): + """Message notifying that an LLM function call has stopped. + + Sent when a function call completes (with result) or is cancelled. + """ + + label: RTVIMessageLiteral = RTVI_MESSAGE_LABEL + type: Literal["llm-function-call-stopped"] = "llm-function-call-stopped" + data: RTVILLMFunctionCallStoppedMessageData + + class RTVIBotLLMStartedMessage(BaseModel): """Message indicating bot LLM processing has started.""" @@ -1139,6 +1188,42 @@ class RTVIObserver(BaseObserver): await self._handle_aggregated_llm_text(frame) elif isinstance(frame, MetricsFrame) and self._params.metrics_enabled: await self._handle_metrics(frame) + elif isinstance(frame, FunctionCallsStartedFrame): + for function_call in frame.function_calls: + message = RTVILLMFunctionCallStartMessage( + data=RTVILLMFunctionCallStartMessageData( + function_name=function_call.function_name + ) + ) + await self.send_rtvi_message(message) + elif isinstance(frame, FunctionCallInProgressFrame): + message = RTVILLMFunctionCallInProgressMessage( + data=RTVILLMFunctionCallInProgressMessageData( + function_name=frame.function_name, + tool_call_id=frame.tool_call_id, + args=frame.arguments, + ) + ) + await self.send_rtvi_message(message) + elif isinstance(frame, FunctionCallCancelFrame): + message = RTVILLMFunctionCallStoppedMessage( + data=RTVILLMFunctionCallStoppedMessageData( + function_name=frame.function_name, + tool_call_id=frame.tool_call_id, + cancelled=True, + ) + ) + await self.send_rtvi_message(message) + elif isinstance(frame, FunctionCallResultFrame): + message = RTVILLMFunctionCallStoppedMessage( + data=RTVILLMFunctionCallStoppedMessageData( + function_name=frame.function_name, + tool_call_id=frame.tool_call_id, + cancelled=False, + result=frame.result if frame.result else None, + ) + ) + await self.send_rtvi_message(message) elif isinstance(frame, RTVIServerMessageFrame): message = RTVIServerMessage(data=frame.data) await self.send_rtvi_message(message) From 40c84faff557a66ded3d1204e1d24cd5123d1381 Mon Sep 17 00:00:00 2001 From: Mark Backman Date: Tue, 3 Feb 2026 09:46:05 -0500 Subject: [PATCH 0343/1060] Remove handle_function_call_start --- src/pipecat/processors/frameworks/rtvi.py | 27 ----------------------- 1 file changed, 27 deletions(-) diff --git a/src/pipecat/processors/frameworks/rtvi.py b/src/pipecat/processors/frameworks/rtvi.py index ce2322da8..93a11d7ae 100644 --- a/src/pipecat/processors/frameworks/rtvi.py +++ b/src/pipecat/processors/frameworks/rtvi.py @@ -1585,33 +1585,6 @@ class RTVIProcessor(FrameProcessor): message = RTVILLMFunctionCallMessage(data=fn) await self.push_transport_message(message, exclude_none=False) - async def handle_function_call_start( - self, function_name: str, llm: FrameProcessor, context: OpenAILLMContext - ): - """Handle the start of a function call from the LLM. - - .. deprecated:: 0.0.66 - This method is deprecated and will be removed in a future version. - Use `RTVIProcessor.handle_function_call()` instead. - - Args: - function_name: Name of the function being called. - llm: The LLM processor making the call. - context: The LLM context. - """ - import warnings - - with warnings.catch_warnings(): - warnings.simplefilter("always") - warnings.warn( - "Function `RTVIProcessor.handle_function_call_start()` is deprecated, use `RTVIProcessor.handle_function_call()` instead.", - DeprecationWarning, - ) - - fn = RTVILLMFunctionCallStartMessageData(function_name=function_name) - message = RTVILLMFunctionCallStartMessage(data=fn) - await self.push_transport_message(message, exclude_none=False) - async def process_frame(self, frame: Frame, direction: FrameDirection): """Process incoming frames through the RTVI processor. From c1857d255d394915536c4537f8686453b6d04500 Mon Sep 17 00:00:00 2001 From: Mark Backman Date: Tue, 3 Feb 2026 12:00:04 -0500 Subject: [PATCH 0344/1060] Avoid nesting try/excepts --- src/pipecat/runner/utils.py | 44 ++++++++++++++++++------------------- 1 file changed, 21 insertions(+), 23 deletions(-) diff --git a/src/pipecat/runner/utils.py b/src/pipecat/runner/utils.py index 2208b7db4..d0bb44a88 100644 --- a/src/pipecat/runner/utils.py +++ b/src/pipecat/runner/utils.py @@ -149,33 +149,31 @@ async def parse_telephony_websocket(websocket: WebSocket): user_id = call_data["body"]["user_id"] """ # Read first two messages - start_data = websocket.iter_text() + message_stream = websocket.iter_text() + first_message = {} + second_message = {} try: - # First message - try: - first_message_raw = await start_data.__anext__() - logger.trace(f"First message: {first_message_raw}") - try: - first_message = json.loads(first_message_raw) - except json.JSONDecodeError: - first_message = {} - except StopAsyncIteration: - raise ValueError("WebSocket closed before receiving telephony handshake messages") + # First message - required + first_message_raw = await message_stream.__anext__() + logger.trace(f"First message: {first_message_raw}") + first_message = json.loads(first_message_raw) if first_message_raw else {} + except json.JSONDecodeError: + pass + except StopAsyncIteration: + raise ValueError("WebSocket closed before receiving telephony handshake messages") - # Second message - try: - second_message_raw = await start_data.__anext__() - logger.trace(f"Second message: {second_message_raw}") - try: - second_message = json.loads(second_message_raw) - except json.JSONDecodeError: - second_message = {} - except StopAsyncIteration: - # Only one message received - use it for detection - logger.warning("Only received one WebSocket message, expected two") - second_message = {} + try: + # Second message - optional, some providers may only send one + second_message_raw = await message_stream.__anext__() + logger.trace(f"Second message: {second_message_raw}") + second_message = json.loads(second_message_raw) if second_message_raw else {} + except json.JSONDecodeError: + pass + except StopAsyncIteration: + logger.warning("Only received one WebSocket message, expected two") + try: # Try auto-detection on both messages detected_type_first = _detect_transport_type_from_message(first_message) detected_type_second = _detect_transport_type_from_message(second_message) From c3a4da4a295c1a4343c05f4705e8bafc7b47cf6e Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Aleix=20Conchillo=20Flaqu=C3=A9?= Date: Mon, 2 Feb 2026 16:44:32 -0800 Subject: [PATCH 0345/1060] PipelineTask: also call set_bot_ready() for external RTVI processors --- changelog/3623.fixed.md | 1 + src/pipecat/pipeline/task.py | 15 +++++++++------ 2 files changed, 10 insertions(+), 6 deletions(-) create mode 100644 changelog/3623.fixed.md diff --git a/changelog/3623.fixed.md b/changelog/3623.fixed.md new file mode 100644 index 000000000..3eab6d90c --- /dev/null +++ b/changelog/3623.fixed.md @@ -0,0 +1 @@ +- Fixed `PipelineTask` to also call `set_bot_ready()` when an external `RTVIProcessor` is provided. diff --git a/src/pipecat/pipeline/task.py b/src/pipecat/pipeline/task.py index 6ae3c55a9..4ccc879b8 100644 --- a/src/pipecat/pipeline/task.py +++ b/src/pipecat/pipeline/task.py @@ -15,7 +15,7 @@ import asyncio import importlib.util import os from pathlib import Path -from typing import Any, AsyncIterable, Dict, Iterable, List, Optional, Set, Tuple, Type +from typing import Any, AsyncIterable, Dict, Iterable, List, Optional, Set, Tuple, Type, TypeVar from loguru import logger from pydantic import BaseModel, ConfigDict, Field @@ -62,6 +62,9 @@ IDLE_TIMEOUT_SECS = 300 CANCEL_TIMEOUT_SECS = 20.0 +T = TypeVar("T") + + class IdleFrameObserver(BaseObserver): """Idle timeout observer. @@ -333,15 +336,17 @@ class PipelineTask(BasePipelineTask): f"{self}: RTVIProcessor and RTVIObserver found, skipping default ones. " "They are both added by default, no need to add them yourself." ) + self._rtvi = external_rtvi elif enable_rtvi: self._rtvi = rtvi_processor or RTVIProcessor() + observers.append(self._rtvi.create_rtvi_observer(params=rtvi_observer_params)) + if self._rtvi: + # Automatically call RTVIProcessor.set_bot_ready() @self.rtvi.event_handler("on_client_ready") async def on_client_ready(rtvi: RTVIProcessor): await rtvi.set_bot_ready() - observers.append(self._rtvi.create_rtvi_observer(params=rtvi_observer_params)) - # This is the idle event. When selected frames are pushed from any # processor we consider the pipeline is not idle. We use an observer # which will be listening any part of the pipeline. @@ -1039,9 +1044,7 @@ class PipelineTask(BasePipelineTask): return start_metadata - def _find_processor( - self, processor: FrameProcessor, processor_type: Type[FrameProcessor] - ) -> Optional[FrameProcessor]: + def _find_processor(self, processor: FrameProcessor, processor_type: Type[T]) -> Optional[T]: """Recursively find a processor of the given type in the pipeline.""" if isinstance(processor, processor_type): return processor From 2a26b9f7a36982b8b13203cf0fc3ee5a2061ea54 Mon Sep 17 00:00:00 2001 From: Mark Backman Date: Mon, 2 Feb 2026 23:34:20 -0500 Subject: [PATCH 0346/1060] Fix: Broadcast SpeechControlParamsFrame from VADController --- changelog/3628.fixed.md | 1 + src/pipecat/audio/vad/vad_controller.py | 2 ++ src/pipecat/processors/audio/vad_processor.py | 8 ++++--- tests/test_vad_controller.py | 24 +++++++++++++++++-- tests/test_vad_processor.py | 21 ++++++++++------ 5 files changed, 44 insertions(+), 12 deletions(-) create mode 100644 changelog/3628.fixed.md diff --git a/changelog/3628.fixed.md b/changelog/3628.fixed.md new file mode 100644 index 000000000..69a00c30e --- /dev/null +++ b/changelog/3628.fixed.md @@ -0,0 +1 @@ +- Fixed `VADController` not broadcasting `SpeechControlParamsFrame` on startup, which prevented STT services from receiving VAD params needed for TTFB measurement. diff --git a/src/pipecat/audio/vad/vad_controller.py b/src/pipecat/audio/vad/vad_controller.py index 66f7199e5..1db590e10 100644 --- a/src/pipecat/audio/vad/vad_controller.py +++ b/src/pipecat/audio/vad/vad_controller.py @@ -106,6 +106,8 @@ class VADController(BaseObject): async def _start(self, frame: StartFrame): self._vad_analyzer.set_sample_rate(frame.audio_in_sample_rate) + # Broadcast initial VAD params so other services (e.g. STT) can use them + await self.broadcast_frame(SpeechControlParamsFrame, vad_params=self._vad_analyzer.params) async def _handle_audio(self, frame: InputAudioRawFrame): """Process an audio chunk and emit speech events as needed. diff --git a/src/pipecat/processors/audio/vad_processor.py b/src/pipecat/processors/audio/vad_processor.py index 074ea57e6..824164b58 100644 --- a/src/pipecat/processors/audio/vad_processor.py +++ b/src/pipecat/processors/audio/vad_processor.py @@ -93,8 +93,10 @@ class VADProcessor(FrameProcessor): """ await super().process_frame(frame, direction) + # Forward the frame first, then let VAD controller process. This ensures: + # 1. StartFrame reaches downstream before SpeechControlParamsFrame is broadcast + # 2. Audio flows through immediately while VAD detection happens after + await self.push_frame(frame, direction) + # Let the VAD controller handle the frame await self._vad_controller.process_frame(frame) - - # Always forward the frame - await self.push_frame(frame, direction) diff --git a/tests/test_vad_controller.py b/tests/test_vad_controller.py index b649a906f..c208b5122 100644 --- a/tests/test_vad_controller.py +++ b/tests/test_vad_controller.py @@ -7,9 +7,9 @@ import unittest from typing import List -from pipecat.audio.vad.vad_analyzer import VADAnalyzer, VADState +from pipecat.audio.vad.vad_analyzer import VADAnalyzer, VADParams, VADState from pipecat.audio.vad.vad_controller import VADController -from pipecat.frames.frames import Frame, InputAudioRawFrame, StartFrame +from pipecat.frames.frames import Frame, InputAudioRawFrame, SpeechControlParamsFrame, StartFrame from pipecat.processors.frame_processor import FrameDirection @@ -185,6 +185,26 @@ class TestVADController(unittest.IsolatedAsyncioTestCase): await controller.process_frame(audio_frame) self.assertEqual(events_triggered, []) + async def test_start_frame_broadcasts_vad_params(self): + """Test that StartFrame triggers broadcast of SpeechControlParamsFrame with VAD params.""" + analyzer = MockVADAnalyzer() + controller = VADController(analyzer) + + broadcast_calls: List[tuple] = [] + + @controller.event_handler("on_broadcast_frame") + async def on_broadcast_frame(_controller, frame_cls, **kwargs): + broadcast_calls.append((frame_cls, kwargs)) + + start_frame = StartFrame(audio_in_sample_rate=16000, audio_out_sample_rate=16000) + await controller.process_frame(start_frame) + + # Should have broadcast SpeechControlParamsFrame with VAD params + self.assertEqual(len(broadcast_calls), 1) + self.assertEqual(broadcast_calls[0][0], SpeechControlParamsFrame) + self.assertIn("vad_params", broadcast_calls[0][1]) + self.assertIsInstance(broadcast_calls[0][1]["vad_params"], VADParams) + if __name__ == "__main__": unittest.main() diff --git a/tests/test_vad_processor.py b/tests/test_vad_processor.py index 2acb4f29d..afb6e1482 100644 --- a/tests/test_vad_processor.py +++ b/tests/test_vad_processor.py @@ -10,6 +10,7 @@ from typing import List from pipecat.audio.vad.vad_analyzer import VADAnalyzer, VADState from pipecat.frames.frames import ( InputAudioRawFrame, + SpeechControlParamsFrame, UserSpeakingFrame, VADUserStartedSpeakingFrame, VADUserStoppedSpeakingFrame, @@ -52,7 +53,7 @@ class TestVADProcessor(unittest.IsolatedAsyncioTestCase): await run_test( processor, frames_to_send=[self._make_audio_frame()], - expected_down_frames=[InputAudioRawFrame], + expected_down_frames=[SpeechControlParamsFrame, InputAudioRawFrame], ) async def test_pushes_started_speaking_frame(self): @@ -60,14 +61,16 @@ class TestVADProcessor(unittest.IsolatedAsyncioTestCase): analyzer = MockVADAnalyzer([VADState.QUIET, VADState.SPEAKING]) processor = VADProcessor(vad_analyzer=analyzer) + # Audio frames are forwarded first, then VAD processes and broadcasts VAD frames await run_test( processor, frames_to_send=[self._make_audio_frame(), self._make_audio_frame()], expected_down_frames=[ + SpeechControlParamsFrame, + InputAudioRawFrame, InputAudioRawFrame, VADUserStartedSpeakingFrame, UserSpeakingFrame, - InputAudioRawFrame, ], ) @@ -76,15 +79,17 @@ class TestVADProcessor(unittest.IsolatedAsyncioTestCase): analyzer = MockVADAnalyzer([VADState.SPEAKING, VADState.QUIET]) processor = VADProcessor(vad_analyzer=analyzer) + # Audio frames are forwarded first, then VAD processes and broadcasts VAD frames await run_test( processor, frames_to_send=[self._make_audio_frame(), self._make_audio_frame()], expected_down_frames=[ + SpeechControlParamsFrame, + InputAudioRawFrame, VADUserStartedSpeakingFrame, UserSpeakingFrame, InputAudioRawFrame, VADUserStoppedSpeakingFrame, - InputAudioRawFrame, ], ) @@ -93,15 +98,17 @@ class TestVADProcessor(unittest.IsolatedAsyncioTestCase): analyzer = MockVADAnalyzer([VADState.SPEAKING, VADState.SPEAKING]) processor = VADProcessor(vad_analyzer=analyzer) + # Audio frames are forwarded first, then VAD processes and broadcasts VAD frames await run_test( processor, frames_to_send=[self._make_audio_frame(), self._make_audio_frame()], expected_down_frames=[ + SpeechControlParamsFrame, + InputAudioRawFrame, VADUserStartedSpeakingFrame, UserSpeakingFrame, InputAudioRawFrame, UserSpeakingFrame, - InputAudioRawFrame, ], ) @@ -113,7 +120,7 @@ class TestVADProcessor(unittest.IsolatedAsyncioTestCase): await run_test( processor, frames_to_send=[self._make_audio_frame()], - expected_down_frames=[InputAudioRawFrame], + expected_down_frames=[SpeechControlParamsFrame, InputAudioRawFrame], ) async def test_no_vad_frames_on_stopping_state(self): @@ -124,7 +131,7 @@ class TestVADProcessor(unittest.IsolatedAsyncioTestCase): await run_test( processor, frames_to_send=[self._make_audio_frame()], - expected_down_frames=[InputAudioRawFrame], + expected_down_frames=[SpeechControlParamsFrame, InputAudioRawFrame], ) async def test_no_vad_frames_when_quiet(self): @@ -135,7 +142,7 @@ class TestVADProcessor(unittest.IsolatedAsyncioTestCase): await run_test( processor, frames_to_send=[self._make_audio_frame(), self._make_audio_frame()], - expected_down_frames=[InputAudioRawFrame, InputAudioRawFrame], + expected_down_frames=[SpeechControlParamsFrame, InputAudioRawFrame, InputAudioRawFrame], ) From 65b1a8ce364c2b7d2e012cf894ce7182396f30dd Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Aleix=20Conchillo=20Flaqu=C3=A9?= Date: Tue, 3 Feb 2026 18:04:54 -0800 Subject: [PATCH 0347/1060] initial CLAUDE.md --- CLAUDE.md | 148 ++++++++++++++++++++++++++++++++++++++++++++++++++++++ 1 file changed, 148 insertions(+) create mode 100644 CLAUDE.md diff --git a/CLAUDE.md b/CLAUDE.md new file mode 100644 index 000000000..7fa962a60 --- /dev/null +++ b/CLAUDE.md @@ -0,0 +1,148 @@ +# CLAUDE.md + +This file provides guidance to Claude Code (claude.ai/code) when working with code in this repository. + +## Project Overview + +Pipecat is an open-source Python framework for building real-time voice and multimodal conversational AI agents. It orchestrates audio/video, AI services, transports, and conversation pipelines using a frame-based architecture. + +## Common Commands + +```bash +# Setup development environment +uv sync --group dev --all-extras --no-extra gstreamer --no-extra krisp + +# Install pre-commit hooks +uv run pre-commit install + +# Run all tests +uv run pytest + +# Run a single test file +uv run pytest tests/test_name.py + +# Run a specific test +uv run pytest tests/test_name.py::test_function_name + +# Preview changelog +towncrier build --draft --version Unreleased + +# Update dependencies (after editing pyproject.toml) +uv lock && uv sync +``` + +## Architecture + +### Frame-Based Pipeline Processing + +All data flows as **Frame** objects through a pipeline of **FrameProcessors**: + +``` +Transport Input → Pipeline Source → [Processor1] → [Processor2] → ... → Pipeline Sink → Transport Output +``` + +**Key components:** + +- **Frames** (`src/pipecat/frames/frames.py`): Data units (audio, text, video) and control signals. Flow DOWNSTREAM (input→output) or UPSTREAM (acknowledgments/errors). + +- **FrameProcessor** (`src/pipecat/processors/frame_processor.py`): Base processing unit. Each processor receives frames, processes them, and pushes results downstream. + +- **Pipeline** (`src/pipecat/pipeline/pipeline.py`): Chains processors together. + +- **ParallelPipeline** (`src/pipecat/pipeline/parallel_pipeline.py`): Runs multiple pipelines in parallel. + +- **Transports** (`src/pipecat/transports/`): External I/O layer (Daily WebRTC, LiveKit WebRTC, WebSocket, Local). Abstract interface via `BaseTransport`. + +- **Services** (`src/pipecat/services/`): 60+ AI provider integrations (STT, TTS, LLM, etc.). Extend base classes: `AIService`, `LLMService`, `STTService`, `TTSService`, `VisionService`. + +### Important Patterns + +- **Context Aggregation**: `LLMContext` accumulates messages for LLM calls; `UserResponse` aggregates user input + +- **Turn Management**: Turn management is done through `LLMUserAggregator` and +`LLMAssistantAggregator`, created with `LLMContextAggregatorPair` + +- **User turn strategies**: Detection of when the user starts and stops speaking is done via user turn start/stop strategies. They push `UserStartedSpeakingFrame` and `UserStoppedSpeakingFrame` respectively. + +- **Interruptions**: Interruptions are usually triggered by a user turn start strategy (e.g. `VADUserTurnStartStrategy`) but they can be triggered by other processors as well, in which case the user turn start strategies don't need to. + +- **Uninterruptible Frames**: These are frames that will not be removed from internal queues even if there's an interruption. For example, `EndFrame` and `StopFrame`. + +- **Events**: Most classes in Pipecat have `BaseObject` as the very base class. `BaseObject` has support for events. Events can run in the background in an async task (default) or synchronously (`sync=True`) if we want immediate action. Synchronous event handlers need to exectue fast.. + +### Key Directories + +| Directory | Purpose | +|---------------------------|----------------------------------------------------| +| `src/pipecat/frames/` | Frame definitions (100+ types) | +| `src/pipecat/processors/` | FrameProcessor base + aggregators, filters, audio | +| `src/pipecat/pipeline/` | Pipeline orchestration | +| `src/pipecat/services/` | AI service integrations (60+ providers) | +| `src/pipecat/transports/` | Transport layer (Daily, LiveKit, WebSocket, Local) | +| `src/pipecat/audio/` | VAD, filters, mixers, turn detection, DTMF | +| `src/pipecat/turns/` | User turn management | + +## Code Style + +- **Docstrings**: Google-style. Classes describe purpose; `__init__` has `Args:` section; dataclasses use `Parameters:` section. +- **Linting**: Ruff (line length 100). Pre-commit hooks enforce formatting. +- **Type hints**: Required for complex async code. + +### Docstring Example + +```python +class MyService(LLMService): + """Description of what the service does. + + More detailed description. + + Event handlers available: + + - on_connected: Called when we are connected + + Example:: + + @service.event_handler("on_connected") + async def on_connected(service, frame): + ... + """ + + def __init__(self, param1: str, **kwargs): + """Initialize the service. + + Args: + param1: Description of param1. + **kwargs: Additional arguments passed to parent. + """ + super().__init__(**kwargs) +``` + +## Changelog + +Every user-facing PR needs a changelog fragment in `changelog/`: + +``` +changelog/..md +``` + +Types: `added`, `changed`, `deprecated`, `removed`, `fixed`, `security`, `other` + +Content format (include the `-`): + +```markdown +- Added support for new feature X. +``` + +Skip changelog for: documentation-only, internal refactoring, test-only, CI changes. + +## Service Implementation + +When adding a new service: + +1. Extend the appropriate base class (`STTService`, `TTSService`, `LLMService`, etc.) +2. Implement required abstract methods +3. Handle necessary frames +4. By default, all frames should be pushed in the direction they came +5. Push `ErrorFrame` on failures +6. Add metrics tracking via `MetricsData` if relevant +7. Follow the pattern of existing services in `src/pipecat/services/` From e6b06414b3f745ce46b41b3462cdc14ab293bc80 Mon Sep 17 00:00:00 2001 From: dhruvladia-sarvam Date: Wed, 4 Feb 2026 16:46:35 +0530 Subject: [PATCH 0348/1060] change default speaker for bulbul:v3-beta to shubh --- src/pipecat/services/sarvam/tts.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/src/pipecat/services/sarvam/tts.py b/src/pipecat/services/sarvam/tts.py index b6819185a..5feeffd72 100644 --- a/src/pipecat/services/sarvam/tts.py +++ b/src/pipecat/services/sarvam/tts.py @@ -175,7 +175,7 @@ TTS_MODEL_CONFIGS: Dict[str, TTSModelConfig] = { supports_loudness=False, supports_temperature=True, default_sample_rate=24000, - default_speaker="aditya", + default_speaker="shubh", pace_range=(0.5, 2.0), preprocessing_always_enabled=True, speakers=tuple(s.value for s in SarvamTTSSpeakerV3), From 55a3b10e70cd617955743225a8c8cbe4ac955231 Mon Sep 17 00:00:00 2001 From: Luke Payyapilli Date: Wed, 4 Feb 2026 09:52:26 -0500 Subject: [PATCH 0349/1060] fix(openai): close stream on cancellation to prevent socket leaks --- changelog/3589.fixed.md | 1 + src/pipecat/services/openai/base_llm.py | 125 ++++++++++++------------ tests/test_openai_llm_timeout.py | 66 +++++++++++++ 3 files changed, 131 insertions(+), 61 deletions(-) create mode 100644 changelog/3589.fixed.md diff --git a/changelog/3589.fixed.md b/changelog/3589.fixed.md new file mode 100644 index 000000000..fda03ac70 --- /dev/null +++ b/changelog/3589.fixed.md @@ -0,0 +1 @@ +- Fixed OpenAI LLM stream not being closed on cancellation/exception, which could leak sockets. diff --git a/src/pipecat/services/openai/base_llm.py b/src/pipecat/services/openai/base_llm.py index ef6cfbbe9..54e514508 100644 --- a/src/pipecat/services/openai/base_llm.py +++ b/src/pipecat/services/openai/base_llm.py @@ -362,74 +362,77 @@ class BaseOpenAILLMService(LLMService): else self._stream_chat_completions_universal_context(context) ) - async for chunk in chunk_stream: - if chunk.usage: - cached_tokens = ( - chunk.usage.prompt_tokens_details.cached_tokens - if chunk.usage.prompt_tokens_details - else None - ) - reasoning_tokens = ( - chunk.usage.completion_tokens_details.reasoning_tokens - if chunk.usage.completion_tokens_details - else None - ) - tokens = LLMTokenUsage( - prompt_tokens=chunk.usage.prompt_tokens, - completion_tokens=chunk.usage.completion_tokens, - total_tokens=chunk.usage.total_tokens, - cache_read_input_tokens=cached_tokens, - reasoning_tokens=reasoning_tokens, - ) - await self.start_llm_usage_metrics(tokens) + # Use context manager to ensure stream is closed on cancellation/exception. + # Without this, CancelledError during iteration leaves the underlying socket open. + async with chunk_stream: + async for chunk in chunk_stream: + if chunk.usage: + cached_tokens = ( + chunk.usage.prompt_tokens_details.cached_tokens + if chunk.usage.prompt_tokens_details + else None + ) + reasoning_tokens = ( + chunk.usage.completion_tokens_details.reasoning_tokens + if chunk.usage.completion_tokens_details + else None + ) + tokens = LLMTokenUsage( + prompt_tokens=chunk.usage.prompt_tokens, + completion_tokens=chunk.usage.completion_tokens, + total_tokens=chunk.usage.total_tokens, + cache_read_input_tokens=cached_tokens, + reasoning_tokens=reasoning_tokens, + ) + await self.start_llm_usage_metrics(tokens) - if chunk.model and self.get_full_model_name() != chunk.model: - self.set_full_model_name(chunk.model) + if chunk.model and self.get_full_model_name() != chunk.model: + self.set_full_model_name(chunk.model) - if chunk.choices is None or len(chunk.choices) == 0: - continue + if chunk.choices is None or len(chunk.choices) == 0: + continue - await self.stop_ttfb_metrics() + await self.stop_ttfb_metrics() - if not chunk.choices[0].delta: - continue + if not chunk.choices[0].delta: + continue - if chunk.choices[0].delta.tool_calls: - # We're streaming the LLM response to enable the fastest response times. - # For text, we just yield each chunk as we receive it and count on consumers - # to do whatever coalescing they need (eg. to pass full sentences to TTS) - # - # If the LLM is a function call, we'll do some coalescing here. - # If the response contains a function name, we'll yield a frame to tell consumers - # that they can start preparing to call the function with that name. - # We accumulate all the arguments for the rest of the streamed response, then when - # the response is done, we package up all the arguments and the function name and - # yield a frame containing the function name and the arguments. + if chunk.choices[0].delta.tool_calls: + # We're streaming the LLM response to enable the fastest response times. + # For text, we just yield each chunk as we receive it and count on consumers + # to do whatever coalescing they need (eg. to pass full sentences to TTS) + # + # If the LLM is a function call, we'll do some coalescing here. + # If the response contains a function name, we'll yield a frame to tell consumers + # that they can start preparing to call the function with that name. + # We accumulate all the arguments for the rest of the streamed response, then when + # the response is done, we package up all the arguments and the function name and + # yield a frame containing the function name and the arguments. - tool_call = chunk.choices[0].delta.tool_calls[0] - if tool_call.index != func_idx: - functions_list.append(function_name) - arguments_list.append(arguments) - tool_id_list.append(tool_call_id) - function_name = "" - arguments = "" - tool_call_id = "" - func_idx += 1 - if tool_call.function and tool_call.function.name: - function_name += tool_call.function.name - tool_call_id = tool_call.id - if tool_call.function and tool_call.function.arguments: - # Keep iterating through the response to collect all the argument fragments - arguments += tool_call.function.arguments - elif chunk.choices[0].delta.content: - await self._push_llm_text(chunk.choices[0].delta.content) + tool_call = chunk.choices[0].delta.tool_calls[0] + if tool_call.index != func_idx: + functions_list.append(function_name) + arguments_list.append(arguments) + tool_id_list.append(tool_call_id) + function_name = "" + arguments = "" + tool_call_id = "" + func_idx += 1 + if tool_call.function and tool_call.function.name: + function_name += tool_call.function.name + tool_call_id = tool_call.id + if tool_call.function and tool_call.function.arguments: + # Keep iterating through the response to collect all the argument fragments + arguments += tool_call.function.arguments + elif chunk.choices[0].delta.content: + await self._push_llm_text(chunk.choices[0].delta.content) - # When gpt-4o-audio / gpt-4o-mini-audio is used for llm or stt+llm - # we need to get LLMTextFrame for the transcript - elif hasattr(chunk.choices[0].delta, "audio") and chunk.choices[0].delta.audio.get( - "transcript" - ): - await self.push_frame(LLMTextFrame(chunk.choices[0].delta.audio["transcript"])) + # When gpt-4o-audio / gpt-4o-mini-audio is used for llm or stt+llm + # we need to get LLMTextFrame for the transcript + elif hasattr(chunk.choices[0].delta, "audio") and chunk.choices[0].delta.audio.get( + "transcript" + ): + await self.push_frame(LLMTextFrame(chunk.choices[0].delta.audio["transcript"])) # if we got a function name and arguments, check to see if it's a function with # a registered handler. If so, run the registered callback, save the result to diff --git a/tests/test_openai_llm_timeout.py b/tests/test_openai_llm_timeout.py index 37e4523a9..4ba459a29 100644 --- a/tests/test_openai_llm_timeout.py +++ b/tests/test_openai_llm_timeout.py @@ -127,6 +127,72 @@ async def test_openai_llm_timeout_still_pushes_end_frame(): service.stop_processing_metrics.assert_called_once() +@pytest.mark.asyncio +async def test_openai_llm_stream_closed_on_cancellation(): + """Test that the stream is closed when CancelledError occurs during iteration. + + This prevents socket leaks when the pipeline is interrupted (e.g., user interruption). + See issue #3589. + """ + import asyncio + + with patch.object(OpenAILLMService, "create_client"): + service = OpenAILLMService(model="gpt-4") + service._client = AsyncMock() + + # Track if close was called + stream_closed = False + + class MockAsyncStream: + """Mock AsyncStream that tracks close() calls and raises CancelledError.""" + + def __init__(self): + self.iteration_count = 0 + + async def __aenter__(self): + return self + + async def __aexit__(self, exc_type, exc_val, exc_tb): + nonlocal stream_closed + stream_closed = True + return False + + def __aiter__(self): + return self + + async def __anext__(self): + self.iteration_count += 1 + if self.iteration_count > 1: + # Simulate cancellation during iteration + raise asyncio.CancelledError() + # Return a minimal chunk for first iteration + mock_chunk = AsyncMock() + mock_chunk.usage = None + mock_chunk.model = None + mock_chunk.choices = [] + return mock_chunk + + mock_stream = MockAsyncStream() + + # Mock the stream creation methods + service._stream_chat_completions_specific_context = AsyncMock(return_value=mock_stream) + service._stream_chat_completions_universal_context = AsyncMock(return_value=mock_stream) + service.start_ttfb_metrics = AsyncMock() + service.stop_ttfb_metrics = AsyncMock() + service.start_llm_usage_metrics = AsyncMock() + + context = LLMContext( + messages=[{"role": "user", "content": "Hello"}], + ) + + # Process context should raise CancelledError but stream should still be closed + with pytest.raises(asyncio.CancelledError): + await service._process_context(context) + + # Verify stream was closed despite the cancellation + assert stream_closed, "Stream should be closed even when CancelledError occurs" + + @pytest.mark.asyncio async def test_openai_llm_emits_error_frame_on_exception(): """Test that OpenAI LLM service emits ErrorFrame when a general exception occurs. From e0e3b5250bee9b21621fa6a95771109ab4fe142e Mon Sep 17 00:00:00 2001 From: Mark Backman Date: Tue, 3 Feb 2026 10:11:36 -0500 Subject: [PATCH 0350/1060] Add RTVIObserverParams to control what information is included in function call events --- changelog/3630.added.md | 2 +- src/pipecat/processors/frameworks/rtvi.py | 136 +++++++++++++++++----- 2 files changed, 107 insertions(+), 31 deletions(-) diff --git a/changelog/3630.added.md b/changelog/3630.added.md index f4b9e8060..8647a71cc 100644 --- a/changelog/3630.added.md +++ b/changelog/3630.added.md @@ -1 +1 @@ -- Added native RTVI function call lifecycle messages (`llm-function-call-start`, `llm-function-call`, `llm-function-call-cancelled`, `llm-function-call-result`) for visual feedback when bot executes functions. \ No newline at end of file +- Added native RTVI function call lifecycle messages (`llm-function-call-started`, `llm-function-call-in-progress`, `llm-function-call-stopped`) for visual feedback when bot executes functions. \ No newline at end of file diff --git a/src/pipecat/processors/frameworks/rtvi.py b/src/pipecat/processors/frameworks/rtvi.py index 93a11d7ae..87ec15ee2 100644 --- a/src/pipecat/processors/frameworks/rtvi.py +++ b/src/pipecat/processors/frameworks/rtvi.py @@ -14,7 +14,8 @@ and frame observation for the RTVI protocol. import asyncio import base64 import time -from dataclasses import dataclass +from dataclasses import dataclass, field +from enum import Enum from typing import ( Any, Awaitable, @@ -645,10 +646,11 @@ class RTVIAppendToContext(BaseModel): class RTVILLMFunctionCallStartMessageData(BaseModel): """Data for LLM function call start notification. - Contains the function name being called. + Contains the function name being called. Fields may be omitted based on + the configured function_call_report_level for security. """ - function_name: str + function_name: Optional[str] = None class RTVILLMFunctionCallStartMessage(BaseModel): @@ -678,11 +680,12 @@ class RTVILLMFunctionCallInProgressMessageData(BaseModel): """Data for LLM function call in-progress notification. Contains function call details including name, ID, and arguments. + Fields may be omitted based on the configured function_call_report_level for security. """ - function_name: str tool_call_id: str - args: Mapping[str, Any] + function_name: Optional[str] = None + args: Optional[Mapping[str, Any]] = None class RTVILLMFunctionCallInProgressMessage(BaseModel): @@ -701,11 +704,12 @@ class RTVILLMFunctionCallStoppedMessageData(BaseModel): Contains details about the function call that stopped, including whether it was cancelled or completed with a result. + Fields may be omitted based on the configured function_call_report_level for security. """ - function_name: str tool_call_id: str cancelled: bool + function_name: Optional[str] = None result: Optional[Any] = None @@ -964,6 +968,24 @@ class RTVIServerMessageFrame(SystemFrame): return f"{self.name}(data: {self.data})" +class RTVIFunctionCallReportLevel(str, Enum): + """Level of detail to include in function call RTVI events. + + Controls what information is exposed in function call events for security. + + Values: + DISABLED: No events emitted for this function call. + NONE: Events only with tool_call_id, no function name or metadata (most secure). + NAME: Events with function name, no arguments or results. + FULL: Events with function name, arguments, and results. + """ + + DISABLED = "disabled" + NONE = "none" + NAME = "name" + FULL = "full" + + @dataclass class RTVIObserverParams: """Parameters for configuring RTVI Observer behavior. @@ -992,6 +1014,22 @@ class RTVIObserverParams: transformed text. To register, provide a list of tuples of (aggregation_type | '*', transform_function). audio_level_period_secs: How often audio levels should be sent if enabled. + function_call_report_level: Controls what information is exposed in function call + events for security. A dict mapping function names to levels, where ``"*"`` + sets the default level for unlisted functions:: + + function_call_report_level={ + "*": RTVIFunctionCallReportLevel.DISABLED, # Default: no events + "get_weather": RTVIFunctionCallReportLevel.FULL, # Expose everything + } + + Levels: + - DISABLED: No events emitted for this function. + - NONE: Events with tool_call_id only (most secure when events needed). + - NAME: Adds function name to events. + - FULL: Adds function name, arguments, and results. + + Defaults to ``{"*": RTVIFunctionCallReportLevel.NONE}``. """ bot_output_enabled: bool = True @@ -1016,6 +1054,9 @@ class RTVIObserverParams: ] ] = None audio_level_period_secs: float = 0.15 + function_call_report_level: Dict[str, RTVIFunctionCallReportLevel] = field( + default_factory=lambda: {"*": RTVIFunctionCallReportLevel.NONE} + ) class RTVIObserver(BaseObserver): @@ -1104,6 +1145,21 @@ class RTVIObserver(BaseObserver): if not (agg_type == aggregation_type and func == transform_function) ] + def _get_function_call_report_level(self, function_name: str) -> RTVIFunctionCallReportLevel: + """Get the report level for a specific function call. + + Args: + function_name: The name of the function to get the report level for. + + Returns: + The report level for the function. Looks up the function name first, + then falls back to "*" key, then NONE. + """ + levels = self._params.function_call_report_level + if function_name in levels: + return levels[function_name] + return levels.get("*", RTVIFunctionCallReportLevel.NONE) + async def _logger_sink(self, message): """Logger sink so we can send system logs to RTVI clients.""" message = RTVISystemLogMessage(data=RTVITextMessageData(text=message)) @@ -1190,40 +1246,60 @@ class RTVIObserver(BaseObserver): await self._handle_metrics(frame) elif isinstance(frame, FunctionCallsStartedFrame): for function_call in frame.function_calls: - message = RTVILLMFunctionCallStartMessage( - data=RTVILLMFunctionCallStartMessageData( - function_name=function_call.function_name - ) - ) + report_level = self._get_function_call_report_level(function_call.function_name) + if report_level == RTVIFunctionCallReportLevel.DISABLED: + continue + data = RTVILLMFunctionCallStartMessageData() + if report_level in ( + RTVIFunctionCallReportLevel.NAME, + RTVIFunctionCallReportLevel.FULL, + ): + data.function_name = function_call.function_name + message = RTVILLMFunctionCallStartMessage(data=data) await self.send_rtvi_message(message) elif isinstance(frame, FunctionCallInProgressFrame): - message = RTVILLMFunctionCallInProgressMessage( - data=RTVILLMFunctionCallInProgressMessageData( - function_name=frame.function_name, - tool_call_id=frame.tool_call_id, - args=frame.arguments, - ) - ) - await self.send_rtvi_message(message) + report_level = self._get_function_call_report_level(frame.function_name) + if report_level != RTVIFunctionCallReportLevel.DISABLED: + data = RTVILLMFunctionCallInProgressMessageData(tool_call_id=frame.tool_call_id) + if report_level in ( + RTVIFunctionCallReportLevel.NAME, + RTVIFunctionCallReportLevel.FULL, + ): + data.function_name = frame.function_name + if report_level == RTVIFunctionCallReportLevel.FULL: + data.args = frame.arguments + message = RTVILLMFunctionCallInProgressMessage(data=data) + await self.send_rtvi_message(message) elif isinstance(frame, FunctionCallCancelFrame): - message = RTVILLMFunctionCallStoppedMessage( - data=RTVILLMFunctionCallStoppedMessageData( - function_name=frame.function_name, + report_level = self._get_function_call_report_level(frame.function_name) + if report_level != RTVIFunctionCallReportLevel.DISABLED: + data = RTVILLMFunctionCallStoppedMessageData( tool_call_id=frame.tool_call_id, cancelled=True, ) - ) - await self.send_rtvi_message(message) + if report_level in ( + RTVIFunctionCallReportLevel.NAME, + RTVIFunctionCallReportLevel.FULL, + ): + data.function_name = frame.function_name + message = RTVILLMFunctionCallStoppedMessage(data=data) + await self.send_rtvi_message(message) elif isinstance(frame, FunctionCallResultFrame): - message = RTVILLMFunctionCallStoppedMessage( - data=RTVILLMFunctionCallStoppedMessageData( - function_name=frame.function_name, + report_level = self._get_function_call_report_level(frame.function_name) + if report_level != RTVIFunctionCallReportLevel.DISABLED: + data = RTVILLMFunctionCallStoppedMessageData( tool_call_id=frame.tool_call_id, cancelled=False, - result=frame.result if frame.result else None, ) - ) - await self.send_rtvi_message(message) + if report_level in ( + RTVIFunctionCallReportLevel.NAME, + RTVIFunctionCallReportLevel.FULL, + ): + data.function_name = frame.function_name + if report_level == RTVIFunctionCallReportLevel.FULL: + data.result = frame.result if frame.result else None + message = RTVILLMFunctionCallStoppedMessage(data=data) + await self.send_rtvi_message(message) elif isinstance(frame, RTVIServerMessageFrame): message = RTVIServerMessage(data=frame.data) await self.send_rtvi_message(message) From cc68e00125060d8d74c3ad243552a9ee4f1d7a32 Mon Sep 17 00:00:00 2001 From: Mark Backman Date: Wed, 4 Feb 2026 11:17:23 -0500 Subject: [PATCH 0351/1060] Deprecate llm-function-call message --- src/pipecat/processors/frameworks/rtvi.py | 25 +++++++++++++++++++---- 1 file changed, 21 insertions(+), 4 deletions(-) diff --git a/src/pipecat/processors/frameworks/rtvi.py b/src/pipecat/processors/frameworks/rtvi.py index 87ec15ee2..cbd435d30 100644 --- a/src/pipecat/processors/frameworks/rtvi.py +++ b/src/pipecat/processors/frameworks/rtvi.py @@ -77,10 +77,7 @@ from pipecat.metrics.metrics import ( TTSUsageMetricsData, ) from pipecat.observers.base_observer import BaseObserver, FramePushed -from pipecat.processors.aggregators.openai_llm_context import ( - OpenAILLMContext, - OpenAILLMContextFrame, -) +from pipecat.processors.aggregators.openai_llm_context import OpenAILLMContextFrame from pipecat.processors.frame_processor import FrameDirection, FrameProcessor from pipecat.services.llm_service import ( FunctionCallParams, # TODO(aleix): we shouldn't import `services` from `processors` @@ -581,6 +578,9 @@ class RTVILLMFunctionCallMessageData(BaseModel): """Data for LLM function call notification. Contains function call details including name, ID, and arguments. + + .. deprecated:: 0.0.102 + Use ``RTVILLMFunctionCallInProgressMessageData`` instead. """ function_name: str @@ -592,6 +592,10 @@ class RTVILLMFunctionCallMessage(BaseModel): """Message notifying of an LLM function call. Sent when the LLM makes a function call. + + .. deprecated:: 0.0.102 + Use ``RTVILLMFunctionCallInProgressMessage`` with the + ``llm-function-call-in-progress`` event type instead. """ label: RTVIMessageLiteral = RTVI_MESSAGE_LABEL @@ -1652,7 +1656,20 @@ class RTVIProcessor(FrameProcessor): Args: params: The function call parameters. + + .. deprecated:: 0.0.102 + This method is deprecated. Function call events are now automatically + sent by ``RTVIObserver`` using the ``llm-function-call-in-progress`` event. + Configure reporting level via ``RTVIObserverParams.function_call_report_level``. """ + import warnings + + warnings.warn( + "handle_function_call is deprecated. Function call events are now " + "automatically sent by RTVIObserver using llm-function-call-in-progress.", + DeprecationWarning, + stacklevel=2, + ) fn = RTVILLMFunctionCallMessageData( function_name=params.function_name, tool_call_id=params.tool_call_id, From ecb02d90492284d5bbb75d3be7c512f5de4ef7f4 Mon Sep 17 00:00:00 2001 From: Mark Backman Date: Wed, 4 Feb 2026 11:17:38 -0500 Subject: [PATCH 0352/1060] Bump RTVI_PROTOCOL_VERSION to 1.2.0 --- src/pipecat/processors/frameworks/rtvi.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/src/pipecat/processors/frameworks/rtvi.py b/src/pipecat/processors/frameworks/rtvi.py index cbd435d30..61c3ef57e 100644 --- a/src/pipecat/processors/frameworks/rtvi.py +++ b/src/pipecat/processors/frameworks/rtvi.py @@ -87,7 +87,7 @@ from pipecat.transports.base_output import BaseOutputTransport from pipecat.transports.base_transport import BaseTransport from pipecat.utils.string import match_endofsentence -RTVI_PROTOCOL_VERSION = "1.1.0" +RTVI_PROTOCOL_VERSION = "1.2.0" RTVI_MESSAGE_LABEL = "rtvi-ai" RTVIMessageLiteral = Literal["rtvi-ai"] From 46da6cd91b352d7285808578ed0de9ade50bd64a Mon Sep 17 00:00:00 2001 From: Mark Backman Date: Wed, 4 Feb 2026 11:19:30 -0500 Subject: [PATCH 0353/1060] Update changelogs --- changelog/3630.added.md | 2 +- changelog/3630.deprecated.md | 1 + 2 files changed, 2 insertions(+), 1 deletion(-) create mode 100644 changelog/3630.deprecated.md diff --git a/changelog/3630.added.md b/changelog/3630.added.md index 8647a71cc..3e27ca3e5 100644 --- a/changelog/3630.added.md +++ b/changelog/3630.added.md @@ -1 +1 @@ -- Added native RTVI function call lifecycle messages (`llm-function-call-started`, `llm-function-call-in-progress`, `llm-function-call-stopped`) for visual feedback when bot executes functions. \ No newline at end of file +- Added RTVI function call lifecycle events (`llm-function-call-started`, `llm-function-call-in-progress`, `llm-function-call-stopped`) with configurable security levels via `RTVIObserverParams.function_call_report_level`. Supports per-function control over what information is exposed (`DISABLED`, `NONE`, `NAME`, or `FULL`). \ No newline at end of file diff --git a/changelog/3630.deprecated.md b/changelog/3630.deprecated.md new file mode 100644 index 000000000..b1967f683 --- /dev/null +++ b/changelog/3630.deprecated.md @@ -0,0 +1 @@ +- Deprecated `RTVILLMFunctionCallMessage`, `RTVILLMFunctionCallMessageData`, and `RTVIProcessor.handle_function_call()`. Use the new `llm-function-call-in-progress` event sent automatically by `RTVIObserver` instead. From 7c7408a0487b4daab2ca56f81505debe1852e3ac Mon Sep 17 00:00:00 2001 From: Derek Haynes Date: Thu, 5 Feb 2026 06:02:12 -0700 Subject: [PATCH 0354/1060] Fix orphan spans in tracing during flow initialization and transitions Co-Authored-By: Claude Opus 4.5 --- src/pipecat/utils/tracing/service_decorators.py | 11 +++++++++-- src/pipecat/utils/tracing/turn_trace_observer.py | 11 ++++++----- 2 files changed, 15 insertions(+), 7 deletions(-) diff --git a/src/pipecat/utils/tracing/service_decorators.py b/src/pipecat/utils/tracing/service_decorators.py index 68dda6562..f151a16ae 100644 --- a/src/pipecat/utils/tracing/service_decorators.py +++ b/src/pipecat/utils/tracing/service_decorators.py @@ -32,6 +32,7 @@ from pipecat.utils.tracing.service_attributes import ( add_stt_span_attributes, add_tts_span_attributes, ) +from pipecat.utils.tracing.conversation_context_provider import get_current_conversation_context from pipecat.utils.tracing.setup import is_tracing_available from pipecat.utils.tracing.turn_context_provider import get_current_turn_context @@ -58,7 +59,8 @@ def _noop_decorator(func): def _get_parent_service_context(self): """Get the parent service span context (internal use only). - This looks for the service span that was created when the service was initialized. + This looks for the service span that was created when the service was initialized, + or falls back to the conversation context if available. Args: self: The service instance. @@ -73,7 +75,12 @@ def _get_parent_service_context(self): if hasattr(self, "_span") and self._span: return trace.set_span_in_context(self._span) - # If we can't find a stored span, default to current context + # Fall back to conversation context if available + conversation_context = get_current_conversation_context() + if conversation_context: + return conversation_context + + # Last resort: use current context (may create orphan spans) return context_api.get_current() diff --git a/src/pipecat/utils/tracing/turn_trace_observer.py b/src/pipecat/utils/tracing/turn_trace_observer.py index a76d9bb8f..59b0bd2ae 100644 --- a/src/pipecat/utils/tracing/turn_trace_observer.py +++ b/src/pipecat/utils/tracing/turn_trace_observer.py @@ -15,6 +15,7 @@ from typing import TYPE_CHECKING, Dict, Optional from loguru import logger +from pipecat.frames.frames import StartFrame from pipecat.observers.base_observer import BaseObserver, FramePushed from pipecat.observers.turn_tracking_observer import TurnTrackingObserver from pipecat.utils.tracing.conversation_context_provider import ConversationContextProvider @@ -81,13 +82,15 @@ class TurnTraceObserver(BaseObserver): async def on_push_frame(self, data: FramePushed): """Process a frame without modifying it. - This observer doesn't need to process individual frames as it - relies on turn start/end events from the turn tracker. + Handles StartFrame to begin conversation tracing early, ensuring + that any spans created before Turn 1 (e.g., from flow initialization) + are properly attached to the conversation trace. Args: data: The frame push event data. """ - pass + if isinstance(data.frame, StartFrame) and not self._conversation_span: + self.start_conversation_tracing(self._conversation_id) def start_conversation_tracing(self, conversation_id: Optional[str] = None): """Start a new conversation span. @@ -159,8 +162,6 @@ class TurnTraceObserver(BaseObserver): if not is_tracing_available() or not self._tracer: return - # If this is the first turn and no conversation span exists yet, - # start the conversation tracing (will generate ID if needed) if turn_number == 1 and not self._conversation_span: self.start_conversation_tracing(self._conversation_id) From 752e16f5533eb03a866c0ab2cb75056bcf9ffb4b Mon Sep 17 00:00:00 2001 From: filipi87 Date: Thu, 5 Feb 2026 10:51:03 -0300 Subject: [PATCH 0355/1060] Ignoring RTVI messages inside TwilioSerializer by default. --- src/pipecat/serializers/twilio.py | 7 +++++++ 1 file changed, 7 insertions(+) diff --git a/src/pipecat/serializers/twilio.py b/src/pipecat/serializers/twilio.py index 2e60399fd..aead33b95 100644 --- a/src/pipecat/serializers/twilio.py +++ b/src/pipecat/serializers/twilio.py @@ -27,6 +27,7 @@ from pipecat.frames.frames import ( OutputTransportMessageUrgentFrame, StartFrame, ) +from pipecat.processors.frameworks.rtvi import RTVI_MESSAGE_LABEL from pipecat.serializers.base_serializer import FrameSerializer @@ -54,6 +55,7 @@ class TwilioFrameSerializer(FrameSerializer): twilio_sample_rate: int = 8000 sample_rate: Optional[int] = None auto_hang_up: bool = True + ignore_rtvi_messages: Optional[bool] = True def __init__( self, @@ -167,6 +169,11 @@ class TwilioFrameSerializer(FrameSerializer): return json.dumps(answer) elif isinstance(frame, (OutputTransportMessageFrame, OutputTransportMessageUrgentFrame)): + if ( + self._params.ignore_rtvi_messages + and frame.message.get("label") == RTVI_MESSAGE_LABEL + ): + return None return json.dumps(frame.message) # Return None for unhandled frames From 54db37ea478bbfe5e343053b9bee664865b62d59 Mon Sep 17 00:00:00 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Mon Sep 17 00:00:00 2001 From: filipi87 Date: Tue, 3 Feb 2026 15:24:57 -0300 Subject: [PATCH 0357/1060] Add changelog entry Co-Authored-By: Claude Sonnet 4.5 --- changelog/3635.fixed.md | 1 + 1 file changed, 1 insertion(+) create mode 100644 changelog/3635.fixed.md diff --git a/changelog/3635.fixed.md b/changelog/3635.fixed.md new file mode 100644 index 000000000..3f83e1365 --- /dev/null +++ b/changelog/3635.fixed.md @@ -0,0 +1 @@ +- Fixed WebSocket transport error when broadcasting `InputTransportMessageFrame` by correctly instantiating the frame with its message parameter. From 0d45b48f7b793974168d886d2cceba549776506c Mon Sep 17 00:00:00 2001 From: Derek Haynes Date: Thu, 5 Feb 2026 11:26:58 -0700 Subject: [PATCH 0358/1060] Fix import placement --- src/pipecat/utils/tracing/service_decorators.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/src/pipecat/utils/tracing/service_decorators.py b/src/pipecat/utils/tracing/service_decorators.py index f151a16ae..42babd5cd 100644 --- a/src/pipecat/utils/tracing/service_decorators.py +++ b/src/pipecat/utils/tracing/service_decorators.py @@ -25,6 +25,7 @@ if TYPE_CHECKING: from pipecat.processors.aggregators.llm_context import NOT_GIVEN, LLMContext from pipecat.processors.aggregators.openai_llm_context import OpenAILLMContext +from pipecat.utils.tracing.conversation_context_provider import get_current_conversation_context from pipecat.utils.tracing.service_attributes import ( add_gemini_live_span_attributes, add_llm_span_attributes, @@ -32,7 +33,6 @@ from pipecat.utils.tracing.service_attributes import ( add_stt_span_attributes, add_tts_span_attributes, ) -from pipecat.utils.tracing.conversation_context_provider import get_current_conversation_context from pipecat.utils.tracing.setup import is_tracing_available from pipecat.utils.tracing.turn_context_provider import get_current_turn_context From 8fb0e379658bf67d51934c7c12abf26f9daa1da0 Mon Sep 17 00:00:00 2001 From: Derek Haynes Date: Thu, 5 Feb 2026 11:35:22 -0700 Subject: [PATCH 0359/1060] Update changelog for #3649 --- changelog/3649.fixed.md | 1 + 1 file changed, 1 insertion(+) create mode 100644 changelog/3649.fixed.md diff --git a/changelog/3649.fixed.md b/changelog/3649.fixed.md new file mode 100644 index 000000000..28c8231dd --- /dev/null +++ b/changelog/3649.fixed.md @@ -0,0 +1 @@ +- Fixed orphan OpenTelemetry spans during flow initialization and transitions in tracing. From 2b4f507d3701855ce0cc13fbca61cc1e1af1a116 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Aleix=20Conchillo=20Flaqu=C3=A9?= Date: Thu, 5 Feb 2026 11:06:00 -0800 Subject: [PATCH 0360/1060] CLAUDE.md: add RTVI and serializers --- CLAUDE.md | 7 ++++++- 1 file changed, 6 insertions(+), 1 deletion(-) diff --git a/CLAUDE.md b/CLAUDE.md index 7fa962a60..1d745755b 100644 --- a/CLAUDE.md +++ b/CLAUDE.md @@ -55,6 +55,10 @@ Transport Input → Pipeline Source → [Processor1] → [Processor2] → ... - **Services** (`src/pipecat/services/`): 60+ AI provider integrations (STT, TTS, LLM, etc.). Extend base classes: `AIService`, `LLMService`, `STTService`, `TTSService`, `VisionService`. +- **Serializers** (`src/pipecat/serializers/`): Convert frames to/from wire formats for WebSocket transports. `FrameSerializer` base class defines `serialize()` and `deserialize()`. Telephony serializers (Twilio, Plivo, Vonage, Telnyx, Exotel, Genesys) handle provider-specific protocols and audio encoding (e.g., μ-law). + +- **RTVI** (`src/pipecat/processors/frameworks/rtvi.py`): Real-Time Voice Interface protocol bridging clients and the pipeline. `RTVIProcessor` handles incoming client messages (text input, audio, function call results). `RTVIObserver` converts pipeline frames to outgoing messages: user/bot speaking events, transcriptions, LLM/TTS lifecycle, function calls, metrics, and audio levels. + ### Important Patterns - **Context Aggregation**: `LLMContext` accumulates messages for LLM calls; `UserResponse` aggregates user input @@ -68,7 +72,7 @@ Transport Input → Pipeline Source → [Processor1] → [Processor2] → ... - **Uninterruptible Frames**: These are frames that will not be removed from internal queues even if there's an interruption. For example, `EndFrame` and `StopFrame`. -- **Events**: Most classes in Pipecat have `BaseObject` as the very base class. `BaseObject` has support for events. Events can run in the background in an async task (default) or synchronously (`sync=True`) if we want immediate action. Synchronous event handlers need to exectue fast.. +- **Events**: Most classes in Pipecat have `BaseObject` as the very base class. `BaseObject` has support for events. Events can run in the background in an async task (default) or synchronously (`sync=True`) if we want immediate action. Synchronous event handlers need to exectue fast. ### Key Directories @@ -79,6 +83,7 @@ Transport Input → Pipeline Source → [Processor1] → [Processor2] → ... | `src/pipecat/pipeline/` | Pipeline orchestration | | `src/pipecat/services/` | AI service integrations (60+ providers) | | `src/pipecat/transports/` | Transport layer (Daily, LiveKit, WebSocket, Local) | +| `src/pipecat/serializers/`| Frame serialization for WebSocket protocols | | `src/pipecat/audio/` | VAD, filters, mixers, turn detection, DTMF | | `src/pipecat/turns/` | User turn management | From 93138466d690de88e2007f7ec53b7cea97a4fe6a Mon Sep 17 00:00:00 2001 From: Derek Haynes Date: Mon, 5 Jan 2026 12:16:22 -0700 Subject: [PATCH 0361/1060] Feat: Add user-bot latency to OTel turn spans This adds user-to-bot response latency tracking to OpenTelemetry spans: - Created UserBotLatencyObserver as a reusable component for tracking user-to-bot response latency - Records the value as an attribute on turn spans (turn.user_bot_latency_seconds) - Updated TurnTraceObserver to use UserBotLatencyObserver, following the same pattern as TurnTrackingObserver - Updated PipelineTask to automatically create and wire UserBotLatencyObserver when tracing is enabled (same as TurnTrackingObserver) --- .../foundational/29-turn-tracking-observer.py | 7 +- .../loggers/user_bot_latency_log_observer.py | 68 ++++++++-------- .../observers/user_bot_latency_observer.py | 81 +++++++++++++++++++ src/pipecat/pipeline/task.py | 7 ++ .../utils/tracing/turn_trace_observer.py | 35 ++++++-- 5 files changed, 154 insertions(+), 44 deletions(-) create mode 100644 src/pipecat/observers/user_bot_latency_observer.py diff --git a/examples/foundational/29-turn-tracking-observer.py b/examples/foundational/29-turn-tracking-observer.py index b6d8dcd88..04151bf26 100644 --- a/examples/foundational/29-turn-tracking-observer.py +++ b/examples/foundational/29-turn-tracking-observer.py @@ -15,6 +15,7 @@ from pipecat.audio.vad.silero import SileroVADAnalyzer from pipecat.audio.vad.vad_analyzer import VADParams from pipecat.frames.frames import LLMRunFrame from pipecat.observers.loggers.user_bot_latency_log_observer import UserBotLatencyLogObserver +from pipecat.observers.user_bot_latency_observer import UserBotLatencyObserver from pipecat.pipeline.pipeline import Pipeline from pipecat.pipeline.runner import PipelineRunner from pipecat.pipeline.task import PipelineParams, PipelineTask @@ -96,6 +97,10 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): ] ) + # Create latency tracking observers + latency_tracker = UserBotLatencyObserver() + latency_log_observer = UserBotLatencyLogObserver(latency_tracker) + task = PipelineTask( pipeline, params=PipelineParams( @@ -103,7 +108,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): enable_usage_metrics=True, ), idle_timeout_secs=runner_args.pipeline_idle_timeout_secs, - observers=[UserBotLatencyLogObserver()], + observers=[latency_tracker, latency_log_observer], ) turn_observer = task.turn_tracking_observer diff --git a/src/pipecat/observers/loggers/user_bot_latency_log_observer.py b/src/pipecat/observers/loggers/user_bot_latency_log_observer.py index b8dff734e..e46be9541 100644 --- a/src/pipecat/observers/loggers/user_bot_latency_log_observer.py +++ b/src/pipecat/observers/loggers/user_bot_latency_log_observer.py @@ -6,67 +6,63 @@ """Observer for measuring user-to-bot response latency.""" -import time from statistics import mean from loguru import logger from pipecat.frames.frames import ( - BotStartedSpeakingFrame, CancelFrame, EndFrame, - VADUserStartedSpeakingFrame, - VADUserStoppedSpeakingFrame, ) from pipecat.observers.base_observer import BaseObserver, FramePushed -from pipecat.processors.frame_processor import FrameDirection +from pipecat.observers.user_bot_latency_observer import UserBotLatencyObserver class UserBotLatencyLogObserver(BaseObserver): - """Observer that measures time between user stopping speech and bot starting speech. + """Observer that logs user-to-bot response latency. - This helps measure how quickly the AI services respond by tracking - conversation turn timing and logging latency metrics. + Uses UserBotLatencyObserver to track latency measurements and provides + logging and statistics. Logs individual latencies and a summary with + average, min, and max values when the pipeline ends. """ - def __init__(self): - """Initialize the latency observer. + def __init__(self, latency_tracker: UserBotLatencyObserver, **kwargs): + """Initialize the latency log observer. - Sets up tracking for processed frames and user speech timing - to calculate response latencies. + Args: + latency_tracker: The latency tracking observer to monitor. + **kwargs: Additional arguments passed to parent class. """ - super().__init__() - self._user_bot_latency_processed_frames = set() - self._user_stopped_time = 0 + super().__init__(**kwargs) + self._latency_tracker = latency_tracker self._latencies = [] + if latency_tracker: + + @latency_tracker.event_handler("on_latency_measured") + async def on_latency_measured(tracker, latency_seconds): + await self._handle_latency_measured(latency_seconds) + async def on_push_frame(self, data: FramePushed): - """Process frames to track speech timing and calculate latency. + """Process frames to handle pipeline end events. Args: data: Frame push event containing the frame and direction information. """ - # Only process downstream frames - if data.direction != FrameDirection.DOWNSTREAM: - return - - # Skip already processed frames - if data.frame.id in self._user_bot_latency_processed_frames: - return - - self._user_bot_latency_processed_frames.add(data.frame.id) - - if isinstance(data.frame, VADUserStartedSpeakingFrame): - self._user_stopped_time = 0 - elif isinstance(data.frame, VADUserStoppedSpeakingFrame): - self._user_stopped_time = time.time() - elif isinstance(data.frame, (EndFrame, CancelFrame)): + if isinstance(data.frame, (EndFrame, CancelFrame)): self._log_summary() - elif isinstance(data.frame, BotStartedSpeakingFrame) and self._user_stopped_time: - latency = time.time() - self._user_stopped_time - self._user_stopped_time = 0 - self._latencies.append(latency) - self._log_latency(latency) + + async def _handle_latency_measured(self, latency_seconds: float): + """Handle latency measurement events. + + Called when the latency tracker measures user-to-bot latency. + Stores the latency and logs it. + + Args: + latency_seconds: The measured latency in seconds. + """ + self._latencies.append(latency_seconds) + self._log_latency(latency_seconds) def _log_summary(self): if not self._latencies: diff --git a/src/pipecat/observers/user_bot_latency_observer.py b/src/pipecat/observers/user_bot_latency_observer.py new file mode 100644 index 000000000..475da0c5d --- /dev/null +++ b/src/pipecat/observers/user_bot_latency_observer.py @@ -0,0 +1,81 @@ +"""Observer for tracking user-to-bot response latency. + +This module provides an observer that monitors the time between when a user +stops speaking and when the bot starts speaking, emitting events when latency +is measured. +""" + +import time +from typing import Optional, Set + +from pipecat.frames.frames import ( + BotStartedSpeakingFrame, + VADUserStartedSpeakingFrame, + VADUserStoppedSpeakingFrame, +) +from pipecat.observers.base_observer import BaseObserver, FramePushed +from pipecat.processors.frame_processor import FrameDirection + + +class UserBotLatencyObserver(BaseObserver): + """Observer that tracks user-to-bot response latency. + + Measures the time between when a user stops speaking (VADUserStoppedSpeakingFrame) + and when the bot starts speaking (BotStartedSpeakingFrame). Emits events when + latency is measured, allowing consumers to log, trace, or otherwise process + the latency data. + + This observer follows the composition pattern used by TurnTrackingObserver, + acting as a reusable component for latency measurement. + + Events: + on_latency_measured(observer, latency_seconds): Emitted when user-to-bot + latency is calculated. Includes the latency value in seconds as a float. + """ + + def __init__(self, **kwargs): + """Initialize the user-bot latency observer. + + Sets up tracking for processed frames and user speech timing + to calculate response latencies. + + Args: + **kwargs: Additional arguments passed to parent class. + """ + super().__init__(**kwargs) + self._user_stopped_time: Optional[float] = None + self._processed_frames: Set[str] = set() + + self._register_event_handler("on_latency_measured") + + async def on_push_frame(self, data: FramePushed): + """Process frames to track speech timing and calculate latency. + + Tracks VAD events and bot speaking events to measure the time between + user stopping speech and bot starting speech. + + Args: + data: Frame push event containing the frame and direction information. + """ + # Only process downstream frames + if data.direction != FrameDirection.DOWNSTREAM: + return + + # Skip already processed frames + if data.frame.id in self._processed_frames: + return + + self._processed_frames.add(data.frame.id) + + # Track VAD and bot speaking events for latency + if isinstance(data.frame, VADUserStartedSpeakingFrame): + # Reset when user starts speaking + self._user_stopped_time = None + elif isinstance(data.frame, VADUserStoppedSpeakingFrame): + # Record timestamp when user stops speaking + self._user_stopped_time = time.time() + elif isinstance(data.frame, BotStartedSpeakingFrame) and self._user_stopped_time: + # Calculate and emit latency + latency = time.time() - self._user_stopped_time + self._user_stopped_time = None + await self._call_event_handler("on_latency_measured", latency) diff --git a/src/pipecat/pipeline/task.py b/src/pipecat/pipeline/task.py index 4ccc879b8..e643164eb 100644 --- a/src/pipecat/pipeline/task.py +++ b/src/pipecat/pipeline/task.py @@ -43,6 +43,7 @@ from pipecat.frames.frames import ( from pipecat.metrics.metrics import ProcessingMetricsData, TTFBMetricsData from pipecat.observers.base_observer import BaseObserver, FramePushed from pipecat.observers.turn_tracking_observer import TurnTrackingObserver +from pipecat.observers.user_bot_latency_observer import UserBotLatencyObserver from pipecat.pipeline.base_pipeline import BasePipeline from pipecat.pipeline.base_task import BasePipelineTask, PipelineTaskParams from pipecat.pipeline.pipeline import Pipeline, PipelineSink, PipelineSource @@ -287,13 +288,19 @@ class PipelineTask(BasePipelineTask): observers = self._params.observers observers = observers or [] self._turn_tracking_observer: Optional[TurnTrackingObserver] = None + self._user_bot_latency_observer: Optional[UserBotLatencyObserver] = None self._turn_trace_observer: Optional[TurnTraceObserver] = None if self._enable_turn_tracking: self._turn_tracking_observer = TurnTrackingObserver() observers.append(self._turn_tracking_observer) if self._enable_tracing and self._turn_tracking_observer: + # Create latency observer for tracing + self._user_bot_latency_observer = UserBotLatencyObserver() + observers.append(self._user_bot_latency_observer) + # Create turn trace observer with latency tracking self._turn_trace_observer = TurnTraceObserver( self._turn_tracking_observer, + latency_tracker=self._user_bot_latency_observer, conversation_id=self._conversation_id, additional_span_attributes=self._additional_span_attributes, ) diff --git a/src/pipecat/utils/tracing/turn_trace_observer.py b/src/pipecat/utils/tracing/turn_trace_observer.py index 59b0bd2ae..78a9c9ea9 100644 --- a/src/pipecat/utils/tracing/turn_trace_observer.py +++ b/src/pipecat/utils/tracing/turn_trace_observer.py @@ -18,6 +18,7 @@ from loguru import logger from pipecat.frames.frames import StartFrame from pipecat.observers.base_observer import BaseObserver, FramePushed from pipecat.observers.turn_tracking_observer import TurnTrackingObserver +from pipecat.observers.user_bot_latency_observer import UserBotLatencyObserver from pipecat.utils.tracing.conversation_context_provider import ConversationContextProvider from pipecat.utils.tracing.setup import is_tracing_available from pipecat.utils.tracing.turn_context_provider import TurnContextProvider @@ -45,6 +46,7 @@ class TurnTraceObserver(BaseObserver): def __init__( self, turn_tracker: TurnTrackingObserver, + latency_tracker: UserBotLatencyObserver, conversation_id: Optional[str] = None, additional_span_attributes: Optional[dict] = None, **kwargs, @@ -53,12 +55,14 @@ class TurnTraceObserver(BaseObserver): Args: turn_tracker: The turn tracking observer to monitor. + latency_tracker: The latency tracking observer for user-bot latency. conversation_id: Optional conversation ID for grouping turns. additional_span_attributes: Additional attributes to add to spans. **kwargs: Additional arguments passed to parent class. """ super().__init__(**kwargs) self._turn_tracker = turn_tracker + self._latency_tracker = latency_tracker self._current_span: Optional["Span"] = None self._current_turn_number: int = 0 self._trace_context_map: Dict[int, "SpanContext"] = {} @@ -69,15 +73,32 @@ class TurnTraceObserver(BaseObserver): self._conversation_id = conversation_id self._additional_span_attributes = additional_span_attributes or {} - if turn_tracker: + @turn_tracker.event_handler("on_turn_started") + async def on_turn_started(tracker, turn_number): + await self._handle_turn_started(turn_number) - @turn_tracker.event_handler("on_turn_started") - async def on_turn_started(tracker, turn_number): - await self._handle_turn_started(turn_number) + @turn_tracker.event_handler("on_turn_ended") + async def on_turn_ended(tracker, turn_number, duration, was_interrupted): + await self._handle_turn_ended(turn_number, duration, was_interrupted) - @turn_tracker.event_handler("on_turn_ended") - async def on_turn_ended(tracker, turn_number, duration, was_interrupted): - await self._handle_turn_ended(turn_number, duration, was_interrupted) + @latency_tracker.event_handler("on_latency_measured") + async def on_latency_measured(tracker, latency_seconds): + await self._handle_latency_measured(latency_seconds) + + async def _handle_latency_measured(self, latency_seconds: float): + """Handle latency measurement events. + + Called when the latency tracker measures user-to-bot latency. + Adds the latency as an attribute to the current turn span. + + Args: + latency_seconds: The measured latency in seconds. + """ + if self._current_span and is_tracing_available(): + self._current_span.set_attribute("turn.user_bot_latency_seconds", latency_seconds) + logger.debug( + f"Turn {self._current_turn_number} user-bot latency: {latency_seconds:.3f}s" + ) async def on_push_frame(self, data: FramePushed): """Process a frame without modifying it. From f6c919354f963401a7b8cdcdb5e01b972936c563 Mon Sep 17 00:00:00 2001 From: Derek Haynes Date: Mon, 5 Jan 2026 12:16:30 -0700 Subject: [PATCH 0362/1060] Add test for user bot latency --- tests/test_user_bot_latency_observer.py | 137 ++++++++++++++++++++++++ 1 file changed, 137 insertions(+) create mode 100644 tests/test_user_bot_latency_observer.py diff --git a/tests/test_user_bot_latency_observer.py b/tests/test_user_bot_latency_observer.py new file mode 100644 index 000000000..1b7325d14 --- /dev/null +++ b/tests/test_user_bot_latency_observer.py @@ -0,0 +1,137 @@ +import unittest + +from pipecat.frames.frames import ( + BotStartedSpeakingFrame, + VADUserStartedSpeakingFrame, + VADUserStoppedSpeakingFrame, +) +from pipecat.observers.user_bot_latency_observer import UserBotLatencyObserver +from pipecat.processors.filters.identity_filter import IdentityFilter +from pipecat.tests.utils import run_test + + +class TestUserBotLatencyObserver(unittest.IsolatedAsyncioTestCase): + """Tests for UserBotLatencyObserver.""" + + async def test_normal_latency_measurement(self): + """Test basic latency measurement from user stop to bot start.""" + # Create observer + observer = UserBotLatencyObserver() + + # Create identity filter (passes all frames through) + processor = IdentityFilter() + + # Capture latency events + latencies = [] + + @observer.event_handler("on_latency_measured") + async def on_latency(obs, latency_seconds): + latencies.append(latency_seconds) + + # Define frame sequence + frames_to_send = [ + VADUserStoppedSpeakingFrame(), + BotStartedSpeakingFrame(), + ] + + expected_down_frames = [ + VADUserStoppedSpeakingFrame, + BotStartedSpeakingFrame, + ] + + # Run test + await run_test( + processor, + frames_to_send=frames_to_send, + expected_down_frames=expected_down_frames, + observers=[observer], + ) + + # Verify latency was measured + self.assertEqual(len(latencies), 1) + self.assertGreater(latencies[0], 0) + self.assertLess(latencies[0], 1.0) # Should be very quick + + async def test_multiple_latency_measurements(self): + """Test that multiple user-bot exchanges produce separate latency events.""" + # Create observer + observer = UserBotLatencyObserver() + + # Create identity filter + processor = IdentityFilter() + + # Capture latency events + latencies = [] + + @observer.event_handler("on_latency_measured") + async def on_latency(obs, latency_seconds): + latencies.append(latency_seconds) + + # Define frame sequence with two complete cycles + frames_to_send = [ + # First cycle + VADUserStoppedSpeakingFrame(), + BotStartedSpeakingFrame(), + # Second cycle + VADUserStoppedSpeakingFrame(), + BotStartedSpeakingFrame(), + ] + + expected_down_frames = [ + VADUserStoppedSpeakingFrame, + BotStartedSpeakingFrame, + VADUserStoppedSpeakingFrame, + BotStartedSpeakingFrame, + ] + + # Run test + await run_test( + processor, + frames_to_send=frames_to_send, + expected_down_frames=expected_down_frames, + observers=[observer], + ) + + # Verify two separate latencies were measured + self.assertEqual(len(latencies), 2) + self.assertGreater(latencies[0], 0) + self.assertGreater(latencies[1], 0) + + async def test_no_measurement_without_user_stop(self): + """Test that latency is not measured if bot starts without user stopping first.""" + # Create observer + observer = UserBotLatencyObserver() + + # Create identity filter + processor = IdentityFilter() + + # Capture latency events + latencies = [] + + @observer.event_handler("on_latency_measured") + async def on_latency(obs, latency_seconds): + latencies.append(latency_seconds) + + # Define frame sequence - bot starts without user stop + frames_to_send = [ + BotStartedSpeakingFrame(), + ] + + expected_down_frames = [ + BotStartedSpeakingFrame, + ] + + # Run test + await run_test( + processor, + frames_to_send=frames_to_send, + expected_down_frames=expected_down_frames, + observers=[observer], + ) + + # Verify no latency was measured + self.assertEqual(len(latencies), 0) + + +if __name__ == "__main__": + unittest.main() From 879155935106b74ca1eeb2c933eea7388c36bd48 Mon Sep 17 00:00:00 2001 From: Derek Haynes Date: Mon, 5 Jan 2026 12:20:23 -0700 Subject: [PATCH 0363/1060] Add changelog entry for PR #3355 --- changelog/3355.added.md | 1 + 1 file changed, 1 insertion(+) create mode 100644 changelog/3355.added.md diff --git a/changelog/3355.added.md b/changelog/3355.added.md new file mode 100644 index 000000000..ec8209f57 --- /dev/null +++ b/changelog/3355.added.md @@ -0,0 +1 @@ +- Added `UserBotLatencyObserver` for tracking user-to-bot response latency. When tracing is enabled, latency measurements are automatically recorded as `turn.user_bot_latency_seconds` attributes on OpenTelemetry turn spans. From 56d8ef2bf4aaaa98e1465ff91afa42822e85dbae Mon Sep 17 00:00:00 2001 From: Mark Backman Date: Thu, 5 Feb 2026 10:58:05 -0500 Subject: [PATCH 0364/1060] Deprecate UserBotLatencyLogObserver, update 29 example --- changelog/3355.deprecated.md | 1 + .../foundational/29-turn-tracking-observer.py | 13 +-- .../loggers/user_bot_latency_log_observer.py | 90 ++++++++++++------- 3 files changed, 66 insertions(+), 38 deletions(-) create mode 100644 changelog/3355.deprecated.md diff --git a/changelog/3355.deprecated.md b/changelog/3355.deprecated.md new file mode 100644 index 000000000..7406268a7 --- /dev/null +++ b/changelog/3355.deprecated.md @@ -0,0 +1 @@ +- Deprecated `UserBotLatencyLogObserver`. Use `UserBotLatencyObserver` directly with its `on_latency_measured` event handler instead. diff --git a/examples/foundational/29-turn-tracking-observer.py b/examples/foundational/29-turn-tracking-observer.py index 04151bf26..272254eb6 100644 --- a/examples/foundational/29-turn-tracking-observer.py +++ b/examples/foundational/29-turn-tracking-observer.py @@ -14,7 +14,6 @@ from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnal from pipecat.audio.vad.silero import SileroVADAnalyzer from pipecat.audio.vad.vad_analyzer import VADParams from pipecat.frames.frames import LLMRunFrame -from pipecat.observers.loggers.user_bot_latency_log_observer import UserBotLatencyLogObserver from pipecat.observers.user_bot_latency_observer import UserBotLatencyObserver from pipecat.pipeline.pipeline import Pipeline from pipecat.pipeline.runner import PipelineRunner @@ -97,9 +96,8 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): ] ) - # Create latency tracking observers - latency_tracker = UserBotLatencyObserver() - latency_log_observer = UserBotLatencyLogObserver(latency_tracker) + # Create latency tracking observer + latency_observer = UserBotLatencyObserver() task = PipelineTask( pipeline, @@ -108,9 +106,14 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): enable_usage_metrics=True, ), idle_timeout_secs=runner_args.pipeline_idle_timeout_secs, - observers=[latency_tracker, latency_log_observer], + observers=[latency_observer], ) + # Log latency measurements using the event handler + @latency_observer.event_handler("on_latency_measured") + async def on_latency_measured(observer, latency_seconds): + logger.info(f"⏱️ User-to-bot latency: {latency_seconds:.3f}s") + turn_observer = task.turn_tracking_observer if turn_observer: diff --git a/src/pipecat/observers/loggers/user_bot_latency_log_observer.py b/src/pipecat/observers/loggers/user_bot_latency_log_observer.py index e46be9541..044d4dea6 100644 --- a/src/pipecat/observers/loggers/user_bot_latency_log_observer.py +++ b/src/pipecat/observers/loggers/user_bot_latency_log_observer.py @@ -4,65 +4,89 @@ # SPDX-License-Identifier: BSD 2-Clause License # -"""Observer for measuring user-to-bot response latency.""" +"""Observer for measuring user-to-bot response latency. +.. deprecated:: 0.0.102 + This module is deprecated. Use :class:`UserBotLatencyObserver` directly + with its ``on_latency_measured`` event handler instead. +""" + +import time +import warnings from statistics import mean from loguru import logger from pipecat.frames.frames import ( + BotStartedSpeakingFrame, CancelFrame, EndFrame, + VADUserStartedSpeakingFrame, + VADUserStoppedSpeakingFrame, ) from pipecat.observers.base_observer import BaseObserver, FramePushed -from pipecat.observers.user_bot_latency_observer import UserBotLatencyObserver +from pipecat.processors.frame_processor import FrameDirection class UserBotLatencyLogObserver(BaseObserver): - """Observer that logs user-to-bot response latency. + """Observer that measures time between user stopping speech and bot starting speech. - Uses UserBotLatencyObserver to track latency measurements and provides - logging and statistics. Logs individual latencies and a summary with - average, min, and max values when the pipeline ends. + This helps measure how quickly the AI services respond by tracking + conversation turn timing and logging latency metrics. + + .. deprecated:: 0.0.102 + This class is deprecated. Use :class:`UserBotLatencyObserver` directly + with its ``on_latency_measured`` event handler for custom logging. """ - def __init__(self, latency_tracker: UserBotLatencyObserver, **kwargs): - """Initialize the latency log observer. + def __init__(self): + """Initialize the latency observer. - Args: - latency_tracker: The latency tracking observer to monitor. - **kwargs: Additional arguments passed to parent class. + Sets up tracking for processed frames and user speech timing + to calculate response latencies. + + .. deprecated:: 0.0.102 + This class is deprecated. Use :class:`UserBotLatencyObserver` + directly with its ``on_latency_measured`` event handler. """ - super().__init__(**kwargs) - self._latency_tracker = latency_tracker + warnings.warn( + "UserBotLatencyLogObserver is deprecated and will be removed in a future version. " + "Use UserBotLatencyObserver directly with its on_latency_measured event handler instead.", + DeprecationWarning, + stacklevel=2, + ) + super().__init__() + self._user_bot_latency_processed_frames = set() + self._user_stopped_time = 0 self._latencies = [] - if latency_tracker: - - @latency_tracker.event_handler("on_latency_measured") - async def on_latency_measured(tracker, latency_seconds): - await self._handle_latency_measured(latency_seconds) - async def on_push_frame(self, data: FramePushed): - """Process frames to handle pipeline end events. + """Process frames to track speech timing and calculate latency. Args: data: Frame push event containing the frame and direction information. """ - if isinstance(data.frame, (EndFrame, CancelFrame)): + # Only process downstream frames + if data.direction != FrameDirection.DOWNSTREAM: + return + + # Skip already processed frames + if data.frame.id in self._user_bot_latency_processed_frames: + return + + self._user_bot_latency_processed_frames.add(data.frame.id) + + if isinstance(data.frame, VADUserStartedSpeakingFrame): + self._user_stopped_time = 0 + elif isinstance(data.frame, VADUserStoppedSpeakingFrame): + self._user_stopped_time = time.time() + elif isinstance(data.frame, (EndFrame, CancelFrame)): self._log_summary() - - async def _handle_latency_measured(self, latency_seconds: float): - """Handle latency measurement events. - - Called when the latency tracker measures user-to-bot latency. - Stores the latency and logs it. - - Args: - latency_seconds: The measured latency in seconds. - """ - self._latencies.append(latency_seconds) - self._log_latency(latency_seconds) + elif isinstance(data.frame, BotStartedSpeakingFrame) and self._user_stopped_time: + latency = time.time() - self._user_stopped_time + self._user_stopped_time = 0 + self._latencies.append(latency) + self._log_latency(latency) def _log_summary(self): if not self._latencies: From fef9e3ea32e55be42ac288488dc0152dc955d866 Mon Sep 17 00:00:00 2001 From: Ian Lee Date: Thu, 29 Jan 2026 11:42:14 -0800 Subject: [PATCH 0365/1060] Add auto_mode support for inworld plugin --- src/pipecat/services/inworld/tts.py | 16 ++++++++++++++++ 1 file changed, 16 insertions(+) diff --git a/src/pipecat/services/inworld/tts.py b/src/pipecat/services/inworld/tts.py index 4e6ec3f4e..cb9078b30 100644 --- a/src/pipecat/services/inworld/tts.py +++ b/src/pipecat/services/inworld/tts.py @@ -414,6 +414,11 @@ class InworldTTSService(AudioContextWordTTSService): apply_text_normalization: Whether to apply text normalization. max_buffer_delay_ms: Maximum buffer delay in milliseconds. buffer_char_threshold: Buffer character threshold. + auto_mode: Whether to use auto mode. Recommended when texts are sent + in full sentences/phrases. When enabled, the server controls + flushing of buffered text to achieve minimal latency while + maintaining high quality audio output. If None (default), + automatically set based on aggregate_sentences. """ temperature: Optional[float] = None @@ -421,6 +426,7 @@ class InworldTTSService(AudioContextWordTTSService): apply_text_normalization: Optional[str] = None max_buffer_delay_ms: Optional[int] = None buffer_char_threshold: Optional[int] = None + auto_mode: Optional[bool] = None def __init__( self, @@ -432,6 +438,7 @@ class InworldTTSService(AudioContextWordTTSService): sample_rate: Optional[int] = None, encoding: str = "LINEAR16", params: InputParams = None, + aggregate_sentences: bool = True, **kwargs: Any, ): """Initialize the Inworld WebSocket TTS service. @@ -444,6 +451,7 @@ class InworldTTSService(AudioContextWordTTSService): sample_rate: Audio sample rate in Hz. encoding: Audio encoding format. params: Input parameters for Inworld WebSocket TTS configuration. + aggregate_sentences: Whether to aggregate sentences before synthesis. **kwargs: Additional arguments passed to the parent class. """ super().__init__( @@ -451,6 +459,7 @@ class InworldTTSService(AudioContextWordTTSService): push_stop_frames=True, pause_frame_processing=True, sample_rate=sample_rate, + aggregate_sentences=aggregate_sentences, **kwargs, ) @@ -475,6 +484,11 @@ class InworldTTSService(AudioContextWordTTSService): if params.apply_text_normalization is not None: self._settings["applyTextNormalization"] = params.apply_text_normalization + if params.auto_mode is not None: + self._settings["autoMode"] = params.auto_mode + else: + self._settings["autoMode"] = aggregate_sentences + self._buffer_settings = { "maxBufferDelayMs": params.max_buffer_delay_ms, "bufferCharThreshold": params.buffer_char_threshold, @@ -818,6 +832,8 @@ class InworldTTSService(AudioContextWordTTSService): create_config["temperature"] = self._settings["temperature"] if "applyTextNormalization" in self._settings: create_config["applyTextNormalization"] = self._settings["applyTextNormalization"] + if "autoMode" in self._settings: + create_config["autoMode"] = self._settings["autoMode"] # Set buffer settings for timely audio generation. # Use provided values or defaults that work well for streaming LLM output. From cbe131636df597fb70a927ce6a80ad194d6f8791 Mon Sep 17 00:00:00 2001 From: Ian Lee Date: Tue, 3 Feb 2026 11:41:33 -0800 Subject: [PATCH 0366/1060] add changelog --- 3593.added.md | 1 + 1 file changed, 1 insertion(+) create mode 100644 3593.added.md diff --git a/3593.added.md b/3593.added.md new file mode 100644 index 000000000..432db3636 --- /dev/null +++ b/3593.added.md @@ -0,0 +1 @@ +- Added support for Inworld TTS Websocket Auto Mode for improved latency From d10467e043109e36ca603498ffe826ae6b9fd27e Mon Sep 17 00:00:00 2001 From: Ian Lee Date: Tue, 3 Feb 2026 21:55:53 -0800 Subject: [PATCH 0367/1060] update timestamps reset handling --- 3593.added.md | 1 - src/pipecat/services/inworld/tts.py | 47 ++++++++++++++++++++++++++--- 2 files changed, 43 insertions(+), 5 deletions(-) delete mode 100644 3593.added.md diff --git a/3593.added.md b/3593.added.md deleted file mode 100644 index 432db3636..000000000 --- a/3593.added.md +++ /dev/null @@ -1 +0,0 @@ -- Added support for Inworld TTS Websocket Auto Mode for improved latency diff --git a/src/pipecat/services/inworld/tts.py b/src/pipecat/services/inworld/tts.py index cb9078b30..16898c67f 100644 --- a/src/pipecat/services/inworld/tts.py +++ b/src/pipecat/services/inworld/tts.py @@ -499,6 +499,14 @@ class InworldTTSService(AudioContextWordTTSService): self._context_id = None self._started = False + # Track cumulative time across generations for monotonic timestamps within a turn. + # When auto_mode is enabled, the server controls generations and timestamps reset + # to 0 after each generation, as indicated by a "flushCompleted" message. We + # add _cumulative_time to maintain monotonically increasing timestamps. + self._cumulative_time = 0.0 + # Track the end time of the last word in the current generation + self._generation_end_time = 0.0 + self.set_voice(voice_id) self.set_model_name(model) @@ -559,27 +567,50 @@ class InworldTTSService(AudioContextWordTTSService): await super().push_frame(frame, direction) if isinstance(frame, (TTSStoppedFrame, InterruptionFrame)): self._started = False + logger.trace( + f"{self}: Resetting timestamp tracking due to {type(frame).__name__} - " + f"cumulative_time was {self._cumulative_time}" + ) + self._cumulative_time = 0.0 + self._generation_end_time = 0.0 if isinstance(frame, TTSStoppedFrame): await self.add_word_timestamps([("Reset", 0)]) def _calculate_word_times(self, timestamp_info: Dict[str, Any]) -> List[Tuple[str, float]]: """Calculate word timestamps from Inworld WebSocket API response. + Adds cumulative time offset to maintain monotonically increasing timestamps + across multiple generations within an agent turn. Also tracks the generation + end time for updating cumulative time on flush. + Args: timestamp_info: The timestamp information from Inworld API. Returns: - A list of (word, timestamp) tuples. + List of (word, timestamp) tuples with cumulative offset applied. """ word_times: List[Tuple[str, float]] = [] alignment = timestamp_info.get("wordAlignment", {}) words = alignment.get("words", []) start_times = alignment.get("wordStartTimeSeconds", []) + end_times = alignment.get("wordEndTimeSeconds", []) if words and start_times and len(words) == len(start_times): for i, word in enumerate(words): - word_times.append((word, start_times[i])) + word_start = self._cumulative_time + start_times[i] + word_times.append((word, word_start)) + + # Track cumulative end time for this generation + if end_times and len(end_times) > 0: + self._generation_end_time = self._cumulative_time + end_times[-1] + + logger.trace( + f"{self}: Word timestamps - raw_start_times={start_times}, " + f"cumulative_offset={self._cumulative_time}, " + f"adjusted_times={[t for _, t in word_times]}, " + f"generation_end_time={self._generation_end_time}" + ) return word_times @@ -604,6 +635,8 @@ class InworldTTSService(AudioContextWordTTSService): self._context_id = None self._started = False + self._cumulative_time = 0.0 + self._generation_end_time = 0.0 logger.trace(f"{self}: Interruption handled, context reset to None") def _get_websocket(self): @@ -693,6 +726,8 @@ class InworldTTSService(AudioContextWordTTSService): self._started = False self._context_id = None self._websocket = None + self._cumulative_time = 0.0 + self._generation_end_time = 0.0 await self._call_event_handler("on_disconnected") async def _receive_messages(self): @@ -779,9 +814,13 @@ class InworldTTSService(AudioContextWordTTSService): if "contextCreated" in result: logger.trace(f"{self}: Context created on server: {ctx_id}") - # Handle flush completion - context is still valid, just acknowledge it + # Handle flush completion, which indicates the end of a generation if "flushCompleted" in result: - logger.trace(f"{self}: Flush completed for context {ctx_id}") + logger.trace( + f"{self}: Generation completed - updating cumulative_time: " + f"{self._cumulative_time} -> {self._generation_end_time}" + ) + self._cumulative_time = self._generation_end_time # Handle context closed - context no longer exists on server if "contextClosed" in result: From 22398e1410f2b7b104a9b6eb11fd65d0cb8f569a Mon Sep 17 00:00:00 2001 From: Ian Lee Date: Thu, 5 Feb 2026 11:38:04 -0800 Subject: [PATCH 0368/1060] add changelog back --- changelog/3593.added.md | 2 ++ 1 file changed, 2 insertions(+) create mode 100644 changelog/3593.added.md diff --git a/changelog/3593.added.md b/changelog/3593.added.md new file mode 100644 index 000000000..67b2394d2 --- /dev/null +++ b/changelog/3593.added.md @@ -0,0 +1,2 @@ +- Added support for Inworld TTS Websocket Auto Mode for improved latency +- Updated timestamps to be cumulative within an agent turn, using flushCompleted message as an indication of when timestamps from the server are reset to 0 \ No newline at end of file From 6af4d872a8c20e5d778c8386c10395dadc0c7552 Mon Sep 17 00:00:00 2001 From: filipi87 Date: Thu, 5 Feb 2026 16:52:53 -0300 Subject: [PATCH 0369/1060] Refactoring the serializers to ignore the RTVI messages by default. --- src/pipecat/serializers/base_serializer.py | 51 +++++++++++++++++++++- src/pipecat/serializers/exotel.py | 8 +++- src/pipecat/serializers/genesys.py | 9 ++-- src/pipecat/serializers/plivo.py | 8 +++- src/pipecat/serializers/protobuf.py | 13 ++++-- src/pipecat/serializers/twilio.py | 12 ++--- src/pipecat/serializers/vonage.py | 7 ++- 7 files changed, 87 insertions(+), 21 deletions(-) diff --git a/src/pipecat/serializers/base_serializer.py b/src/pipecat/serializers/base_serializer.py index 9cc38cdc6..edf005a81 100644 --- a/src/pipecat/serializers/base_serializer.py +++ b/src/pipecat/serializers/base_serializer.py @@ -7,8 +7,17 @@ """Frame serialization interfaces for Pipecat.""" from abc import ABC, abstractmethod +from typing import Optional -from pipecat.frames.frames import Frame, StartFrame +from pydantic import BaseModel + +from pipecat.frames.frames import ( + Frame, + OutputTransportMessageFrame, + OutputTransportMessageUrgentFrame, + StartFrame, +) +from pipecat.processors.frameworks.rtvi import RTVI_MESSAGE_LABEL from pipecat.utils.base_object import BaseObject @@ -20,6 +29,46 @@ class FrameSerializer(BaseObject): serialize/deserialize methods. """ + class InputParams(BaseModel): + """Base configuration parameters for FrameSerializer. + + Parameters: + ignore_rtvi_messages: Whether to ignore RTVI protocol messages during serialization. + Defaults to True to prevent RTVI messages from being sent to external transports. + """ + + ignore_rtvi_messages: bool = True + + def __init__(self, params: Optional[InputParams] = None, **kwargs): + """Initialize the FrameSerializer. + + Args: + params: Configuration parameters. + **kwargs: Additional arguments passed to BaseObject (e.g., name). + """ + super().__init__(**kwargs) + self._params = params or FrameSerializer.InputParams() + + def should_ignore_frame(self, frame: Frame) -> bool: + """Check if a frame should be ignored during serialization. + + This method filters out RTVI protocol messages when ignore_rtvi_messages is enabled. + Subclasses can override this to add additional filtering logic. + + Args: + frame: The frame to check. + + Returns: + True if the frame should be ignored, False otherwise. + """ + if ( + self._params.ignore_rtvi_messages + and isinstance(frame, (OutputTransportMessageFrame, OutputTransportMessageUrgentFrame)) + and frame.message.get("label") == RTVI_MESSAGE_LABEL + ): + return True + return False + async def setup(self, frame: StartFrame): """Initialize the serializer with startup configuration. diff --git a/src/pipecat/serializers/exotel.py b/src/pipecat/serializers/exotel.py index 61d6eeada..74e3f28b0 100644 --- a/src/pipecat/serializers/exotel.py +++ b/src/pipecat/serializers/exotel.py @@ -39,12 +39,13 @@ class ExotelFrameSerializer(FrameSerializer): https://support.exotel.com/support/solutions/articles/3000108630-working-with-the-stream-and-voicebot-applet """ - class InputParams(BaseModel): + class InputParams(FrameSerializer.InputParams): """Configuration parameters for ExotelFrameSerializer. Parameters: exotel_sample_rate: Sample rate used by Exotel, defaults to 8000 Hz. sample_rate: Optional override for pipeline input sample rate. + ignore_rtvi_messages: Inherited from base FrameSerializer, defaults to True. """ exotel_sample_rate: int = 8000 @@ -60,9 +61,10 @@ class ExotelFrameSerializer(FrameSerializer): call_sid: The associated Exotel Call SID (optional, not used in this implementation). params: Configuration parameters. """ + super().__init__(params or ExotelFrameSerializer.InputParams()) + self._stream_sid = stream_sid self._call_sid = call_sid - self._params = params or ExotelFrameSerializer.InputParams() self._exotel_sample_rate = self._params.exotel_sample_rate self._sample_rate = 0 # Pipeline input rate @@ -113,6 +115,8 @@ class ExotelFrameSerializer(FrameSerializer): return json.dumps(answer) elif isinstance(frame, (OutputTransportMessageFrame, OutputTransportMessageUrgentFrame)): + if self.should_ignore_frame(frame): + return None return json.dumps(frame.message) return None diff --git a/src/pipecat/serializers/genesys.py b/src/pipecat/serializers/genesys.py index d5d37d12b..24b68eb81 100644 --- a/src/pipecat/serializers/genesys.py +++ b/src/pipecat/serializers/genesys.py @@ -131,7 +131,7 @@ class GenesysAudioHookSerializer(FrameSerializer): PROTOCOL_VERSION = "2" - class InputParams(BaseModel): + class InputParams(FrameSerializer.InputParams): """Configuration parameters for GenesysAudioHookSerializer. Attributes: @@ -144,6 +144,7 @@ class GenesysAudioHookSerializer(FrameSerializer): supported_languages: List of language codes the bot supports (e.g., ["en-US", "es-ES"]). selected_language: Default language code to use. start_paused: Whether to start the session in paused state. + ignore_rtvi_messages: Inherited from base FrameSerializer, defaults to True. """ genesys_sample_rate: int = 8000 @@ -167,8 +168,7 @@ class GenesysAudioHookSerializer(FrameSerializer): params: Configuration parameters. **kwargs: Additional arguments passed to BaseObject (e.g., name). """ - super().__init__(**kwargs) - self._params = params or GenesysAudioHookSerializer.InputParams() + super().__init__(params or GenesysAudioHookSerializer.InputParams(), **kwargs) self._genesys_sample_rate = self._params.genesys_sample_rate self._sample_rate = 0 # Pipeline input rate, set in setup() @@ -604,6 +604,9 @@ class GenesysAudioHookSerializer(FrameSerializer): return json.dumps(self.create_barge_in_event()) elif isinstance(frame, (OutputTransportMessageFrame, OutputTransportMessageUrgentFrame)): + # Filter out RTVI messages using base class method + if self.should_ignore_frame(frame): + return None # Only pass through AudioHook protocol messages (those with "version" field) # Filter out RTVI and other non-AudioHook messages if isinstance(frame.message, dict) and "version" in frame.message: diff --git a/src/pipecat/serializers/plivo.py b/src/pipecat/serializers/plivo.py index 2a57d3698..3341e5ffa 100644 --- a/src/pipecat/serializers/plivo.py +++ b/src/pipecat/serializers/plivo.py @@ -42,13 +42,14 @@ class PlivoFrameSerializer(FrameSerializer): credentials to be provided. """ - class InputParams(BaseModel): + class InputParams(FrameSerializer.InputParams): """Configuration parameters for PlivoFrameSerializer. Parameters: plivo_sample_rate: Sample rate used by Plivo, defaults to 8000 Hz. sample_rate: Optional override for pipeline input sample rate. auto_hang_up: Whether to automatically terminate call on EndFrame. + ignore_rtvi_messages: Inherited from base FrameSerializer, defaults to True. """ plivo_sample_rate: int = 8000 @@ -72,11 +73,12 @@ class PlivoFrameSerializer(FrameSerializer): auth_token: Plivo auth token (required for auto hang-up). params: Configuration parameters. """ + super().__init__(params or PlivoFrameSerializer.InputParams()) + self._stream_id = stream_id self._call_id = call_id self._auth_id = auth_id self._auth_token = auth_token - self._params = params or PlivoFrameSerializer.InputParams() self._plivo_sample_rate = self._params.plivo_sample_rate self._sample_rate = 0 # Pipeline input rate @@ -140,6 +142,8 @@ class PlivoFrameSerializer(FrameSerializer): return json.dumps(answer) elif isinstance(frame, (OutputTransportMessageFrame, OutputTransportMessageUrgentFrame)): + if self.should_ignore_frame(frame): + return None return json.dumps(frame.message) # Return None for unhandled frames diff --git a/src/pipecat/serializers/protobuf.py b/src/pipecat/serializers/protobuf.py index 912f20b42..fd21af2bf 100644 --- a/src/pipecat/serializers/protobuf.py +++ b/src/pipecat/serializers/protobuf.py @@ -8,6 +8,7 @@ import dataclasses import json +from typing import Optional from loguru import logger @@ -60,9 +61,13 @@ class ProtobufFrameSerializer(FrameSerializer): } DESERIALIZABLE_FIELDS = {v: k for k, v in DESERIALIZABLE_TYPES.items()} - def __init__(self): - """Initialize the Protobuf frame serializer.""" - pass + def __init__(self, params: Optional[FrameSerializer.InputParams] = None): + """Initialize the Protobuf frame serializer. + + Args: + params: Configuration parameters. + """ + super().__init__(params) async def serialize(self, frame: Frame) -> str | bytes | None: """Serialize a frame to Protocol Buffer binary format. @@ -75,6 +80,8 @@ class ProtobufFrameSerializer(FrameSerializer): """ # Wrapping this messages as a JSONFrame to send if isinstance(frame, (OutputTransportMessageFrame, OutputTransportMessageUrgentFrame)): + if self.should_ignore_frame(frame): + return None frame = MessageFrame( data=json.dumps(frame.message), ) diff --git a/src/pipecat/serializers/twilio.py b/src/pipecat/serializers/twilio.py index aead33b95..72fec4f28 100644 --- a/src/pipecat/serializers/twilio.py +++ b/src/pipecat/serializers/twilio.py @@ -27,7 +27,6 @@ from pipecat.frames.frames import ( OutputTransportMessageUrgentFrame, StartFrame, ) -from pipecat.processors.frameworks.rtvi import RTVI_MESSAGE_LABEL from pipecat.serializers.base_serializer import FrameSerializer @@ -43,19 +42,19 @@ class TwilioFrameSerializer(FrameSerializer): credentials to be provided. """ - class InputParams(BaseModel): + class InputParams(FrameSerializer.InputParams): """Configuration parameters for TwilioFrameSerializer. Parameters: twilio_sample_rate: Sample rate used by Twilio, defaults to 8000 Hz. sample_rate: Optional override for pipeline input sample rate. auto_hang_up: Whether to automatically terminate call on EndFrame. + ignore_rtvi_messages: Inherited from base FrameSerializer, defaults to True. """ twilio_sample_rate: int = 8000 sample_rate: Optional[int] = None auto_hang_up: bool = True - ignore_rtvi_messages: Optional[bool] = True def __init__( self, @@ -78,7 +77,7 @@ class TwilioFrameSerializer(FrameSerializer): edge: Twilio edge location (e.g., "sydney", "dublin"). Must be specified with region. params: Configuration parameters. """ - self._params = params or TwilioFrameSerializer.InputParams() + super().__init__(params or TwilioFrameSerializer.InputParams()) # Validate hangup-related parameters if auto_hang_up is enabled if self._params.auto_hang_up: @@ -169,10 +168,7 @@ class TwilioFrameSerializer(FrameSerializer): return json.dumps(answer) elif isinstance(frame, (OutputTransportMessageFrame, OutputTransportMessageUrgentFrame)): - if ( - self._params.ignore_rtvi_messages - and frame.message.get("label") == RTVI_MESSAGE_LABEL - ): + if self.should_ignore_frame(frame): return None return json.dumps(frame.message) diff --git a/src/pipecat/serializers/vonage.py b/src/pipecat/serializers/vonage.py index 3213e8bba..01fed08f8 100644 --- a/src/pipecat/serializers/vonage.py +++ b/src/pipecat/serializers/vonage.py @@ -37,13 +37,14 @@ class VonageFrameSerializer(FrameSerializer): Ref docs: https://developer.vonage.com/en/video/guides/audio-connector """ - class InputParams(BaseModel): + class InputParams(FrameSerializer.InputParams): """Configuration parameters for VonageFrameSerializer. Parameters: vonage_sample_rate: Sample rate used by Vonage, defaults to 16000 Hz. Common values: 8000, 16000, 24000 Hz. sample_rate: Optional override for pipeline input sample rate. + ignore_rtvi_messages: Inherited from base FrameSerializer, defaults to True. """ vonage_sample_rate: int = 16000 @@ -55,7 +56,7 @@ class VonageFrameSerializer(FrameSerializer): Args: params: Configuration parameters. """ - self._params = params or VonageFrameSerializer.InputParams() + super().__init__(params or VonageFrameSerializer.InputParams()) self._vonage_sample_rate = self._params.vonage_sample_rate self._sample_rate = 0 # Pipeline input rate @@ -100,6 +101,8 @@ class VonageFrameSerializer(FrameSerializer): # Vonage expects raw binary PCM data (not base64 encoded) return serialized_data elif isinstance(frame, (OutputTransportMessageFrame, OutputTransportMessageUrgentFrame)): + if self.should_ignore_frame(frame): + return None # Allow sending custom JSON commands (e.g., notify) return json.dumps(frame.message) From 8b9da632d18f92e418f32e555e8fe045a1796622 Mon Sep 17 00:00:00 2001 From: Mark Backman Date: Thu, 5 Feb 2026 15:03:30 -0500 Subject: [PATCH 0370/1060] Add OpenAIRealtimeSTTService --- changelog/3656.added.md | 1 + .../07g-interruptible-openai-http.py | 135 +++++ .../foundational/07g-interruptible-openai.py | 10 +- .../foundational/13m-openai-transcription.py | 88 +++ scripts/evals/run-release-evals.py | 1 + src/pipecat/services/openai/stt.py | 565 +++++++++++++++++- 6 files changed, 796 insertions(+), 4 deletions(-) create mode 100644 changelog/3656.added.md create mode 100644 examples/foundational/07g-interruptible-openai-http.py create mode 100644 examples/foundational/13m-openai-transcription.py diff --git a/changelog/3656.added.md b/changelog/3656.added.md new file mode 100644 index 000000000..0918be248 --- /dev/null +++ b/changelog/3656.added.md @@ -0,0 +1 @@ +- Added `OpenAIRealtimeSTTService` for real-time streaming speech-to-text using OpenAI's Realtime API WebSocket transcription sessions. Supports local VAD and server-side VAD modes, noise reduction, and automatic reconnection. diff --git a/examples/foundational/07g-interruptible-openai-http.py b/examples/foundational/07g-interruptible-openai-http.py new file mode 100644 index 000000000..f2b38c8cf --- /dev/null +++ b/examples/foundational/07g-interruptible-openai-http.py @@ -0,0 +1,135 @@ +# +# Copyright (c) 2024-2026, Daily +# +# SPDX-License-Identifier: BSD 2-Clause License +# + + +import os + +from dotenv import load_dotenv +from loguru import logger + +from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3 +from pipecat.audio.vad.silero import SileroVADAnalyzer +from pipecat.audio.vad.vad_analyzer import VADParams +from pipecat.frames.frames import LLMRunFrame +from pipecat.pipeline.pipeline import Pipeline +from pipecat.pipeline.runner import PipelineRunner +from pipecat.pipeline.task import PipelineParams, PipelineTask +from pipecat.processors.aggregators.llm_context import LLMContext +from pipecat.processors.aggregators.llm_response_universal import ( + LLMContextAggregatorPair, + LLMUserAggregatorParams, +) +from pipecat.runner.types import RunnerArguments +from pipecat.runner.utils import create_transport +from pipecat.services.openai.llm import OpenAILLMService +from pipecat.services.openai.stt import OpenAISTTService +from pipecat.services.openai.tts import OpenAITTSService +from pipecat.transports.base_transport import BaseTransport, TransportParams +from pipecat.transports.daily.transport import DailyParams +from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams +from pipecat.turns.user_stop import TurnAnalyzerUserTurnStopStrategy +from pipecat.turns.user_turn_strategies import UserTurnStrategies + +load_dotenv(override=True) + +# We use lambdas to defer transport parameter creation until the transport +# type is selected at runtime. +transport_params = { + "daily": lambda: DailyParams( + audio_in_enabled=True, + audio_out_enabled=True, + ), + "twilio": lambda: FastAPIWebsocketParams( + audio_in_enabled=True, + audio_out_enabled=True, + ), + "webrtc": lambda: TransportParams( + audio_in_enabled=True, + audio_out_enabled=True, + ), +} + + +async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): + logger.info(f"Starting bot") + + stt = OpenAISTTService( + api_key=os.getenv("OPENAI_API_KEY"), + model="gpt-4o-transcribe", + prompt="Expect words related to dogs, such as breed names.", + ) + + tts = OpenAITTSService(api_key=os.getenv("OPENAI_API_KEY"), voice="ballad") + + llm = OpenAILLMService(api_key=os.getenv("OPENAI_API_KEY")) + + messages = [ + { + "role": "system", + "content": "You are very knowledgable about dogs. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + }, + ] + + context = LLMContext(messages) + user_aggregator, assistant_aggregator = LLMContextAggregatorPair( + context, + user_params=LLMUserAggregatorParams( + user_turn_strategies=UserTurnStrategies( + stop=[TurnAnalyzerUserTurnStopStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3())] + ), + vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), + ), + ) + + pipeline = Pipeline( + [ + transport.input(), # Transport user input + stt, # STT + user_aggregator, # User responses + llm, # LLM + tts, # TTS + transport.output(), # Transport bot output + assistant_aggregator, # Assistant spoken responses + ] + ) + + task = PipelineTask( + pipeline, + params=PipelineParams( + audio_out_sample_rate=24000, + enable_metrics=True, + enable_usage_metrics=True, + ), + idle_timeout_secs=runner_args.pipeline_idle_timeout_secs, + ) + + @transport.event_handler("on_client_connected") + async def on_client_connected(transport, client): + logger.info(f"Client connected") + # Kick off the conversation. + messages.append({"role": "system", "content": "Please introduce yourself to the user."}) + await task.queue_frames([LLMRunFrame()]) + + @transport.event_handler("on_client_disconnected") + async def on_client_disconnected(transport, client): + logger.info(f"Client disconnected") + await task.cancel() + + runner = PipelineRunner(handle_sigint=runner_args.handle_sigint) + + await runner.run(task) + + +async def bot(runner_args: RunnerArguments): + """Main bot entry point compatible with Pipecat Cloud.""" + transport = await create_transport(runner_args, transport_params) + await run_bot(transport, runner_args) + + +if __name__ == "__main__": + from pipecat.runner.run import main + + main() diff --git a/examples/foundational/07g-interruptible-openai.py b/examples/foundational/07g-interruptible-openai.py index f2b38c8cf..f9bb09f21 100644 --- a/examples/foundational/07g-interruptible-openai.py +++ b/examples/foundational/07g-interruptible-openai.py @@ -25,8 +25,9 @@ from pipecat.processors.aggregators.llm_response_universal import ( from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport from pipecat.services.openai.llm import OpenAILLMService -from pipecat.services.openai.stt import OpenAISTTService +from pipecat.services.openai.stt import OpenAIRealtimeSTTService from pipecat.services.openai.tts import OpenAITTSService +from pipecat.transcriptions.language import Language from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams @@ -56,10 +57,15 @@ transport_params = { async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): logger.info(f"Starting bot") - stt = OpenAISTTService( + stt = OpenAIRealtimeSTTService( api_key=os.getenv("OPENAI_API_KEY"), model="gpt-4o-transcribe", prompt="Expect words related to dogs, such as breed names.", + language=Language.EN, + # Uses local VAD by default. + # To enable server-side VAD, set turn_detection=None or + # a dict with server_vad settings. + # turn_detection={"type": "server_vad", "threshold": 0.5}, ) tts = OpenAITTSService(api_key=os.getenv("OPENAI_API_KEY"), voice="ballad") diff --git a/examples/foundational/13m-openai-transcription.py b/examples/foundational/13m-openai-transcription.py new file mode 100644 index 000000000..2ef35cb3f --- /dev/null +++ b/examples/foundational/13m-openai-transcription.py @@ -0,0 +1,88 @@ +# +# Copyright (c) 2024-2026, Daily +# +# SPDX-License-Identifier: BSD 2-Clause License +# + +import os + +import aiohttp +from dotenv import load_dotenv +from loguru import logger + +from pipecat.audio.vad.silero import SileroVADAnalyzer +from pipecat.frames.frames import Frame, TranscriptionFrame +from pipecat.pipeline.pipeline import Pipeline +from pipecat.pipeline.runner import PipelineRunner +from pipecat.pipeline.task import PipelineTask +from pipecat.processors.frame_processor import FrameDirection, FrameProcessor +from pipecat.runner.types import RunnerArguments +from pipecat.runner.utils import create_transport +from pipecat.services.openai.stt import OpenAIRealtimeSTTService +from pipecat.transports.base_transport import BaseTransport, TransportParams +from pipecat.transports.daily.transport import DailyParams +from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams + +load_dotenv(override=True) + + +class TranscriptionLogger(FrameProcessor): + async def process_frame(self, frame: Frame, direction: FrameDirection): + await super().process_frame(frame, direction) + + if isinstance(frame, TranscriptionFrame): + print(f"Transcription: {frame.text}") + + # Push all frames through + await self.push_frame(frame, direction) + + +# We use lambdas to defer transport parameter creation until the transport +# type is selected at runtime. +transport_params = { + "daily": lambda: DailyParams(audio_in_enabled=True, vad_analyzer=SileroVADAnalyzer()), + "twilio": lambda: FastAPIWebsocketParams( + audio_in_enabled=True, vad_analyzer=SileroVADAnalyzer() + ), + "webrtc": lambda: TransportParams(audio_in_enabled=True, vad_analyzer=SileroVADAnalyzer()), +} + + +async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): + logger.info(f"Starting bot") + + stt = OpenAIRealtimeSTTService( + api_key=os.getenv("OPENAI_API_KEY"), + model="gpt-4o-transcribe", + prompt="Expect words related to dogs, such as breed names.", + ) + + tl = TranscriptionLogger() + + pipeline = Pipeline([transport.input(), stt, tl]) + + task = PipelineTask( + pipeline, + idle_timeout_secs=runner_args.pipeline_idle_timeout_secs, + ) + + @transport.event_handler("on_client_disconnected") + async def on_client_disconnected(transport, client): + logger.info(f"Client disconnected") + await task.cancel() + + runner = PipelineRunner(handle_sigint=runner_args.handle_sigint) + + await runner.run(task) + + +async def bot(runner_args: RunnerArguments): + """Main bot entry point compatible with Pipecat Cloud.""" + transport = await create_transport(runner_args, transport_params) + await run_bot(transport, runner_args) + + +if __name__ == "__main__": + from pipecat.runner.run import main + + main() diff --git a/scripts/evals/run-release-evals.py b/scripts/evals/run-release-evals.py index f0e2e9a89..19e5d2649 100644 --- a/scripts/evals/run-release-evals.py +++ b/scripts/evals/run-release-evals.py @@ -111,6 +111,7 @@ TESTS_07 = [ ("07f-interruptible-azure.py", EVAL_SIMPLE_MATH), ("07f-interruptible-azure-http.py", EVAL_SIMPLE_MATH), ("07g-interruptible-openai.py", EVAL_SIMPLE_MATH), + ("07g-interruptible-openai-http.py", EVAL_SIMPLE_MATH), ("07h-interruptible-openpipe.py", EVAL_SIMPLE_MATH), ("07j-interruptible-gladia.py", EVAL_SIMPLE_MATH), ("07j-interruptible-gladia-vad.py", EVAL_SIMPLE_MATH), diff --git a/src/pipecat/services/openai/stt.py b/src/pipecat/services/openai/stt.py index 538b69990..db3cf277c 100644 --- a/src/pipecat/services/openai/stt.py +++ b/src/pipecat/services/openai/stt.py @@ -4,12 +4,48 @@ # SPDX-License-Identifier: BSD 2-Clause License # -"""OpenAI Speech-to-Text service implementation using OpenAI's transcription API.""" +"""OpenAI Speech-to-Text service implementations. -from typing import Optional +Provides two STT services: +- ``OpenAISTTService``: REST-based transcription using the Audio API + (Whisper / GPT-4o). +- ``OpenAIRealtimeSTTService``: WebSocket-based streaming transcription + using the Realtime API in transcription-only mode. +""" + +import base64 +import json +from typing import AsyncGenerator, Literal, Optional, Union + +from loguru import logger + +from pipecat.audio.utils import create_stream_resampler +from pipecat.frames.frames import ( + CancelFrame, + EndFrame, + Frame, + InterimTranscriptionFrame, + StartFrame, + TranscriptionFrame, + UserStartedSpeakingFrame, + UserStoppedSpeakingFrame, + VADUserStartedSpeakingFrame, + VADUserStoppedSpeakingFrame, +) +from pipecat.processors.frame_processor import FrameDirection +from pipecat.services.stt_service import WebsocketSTTService from pipecat.services.whisper.base_stt import BaseWhisperSTTService, Transcription from pipecat.transcriptions.language import Language +from pipecat.utils.time import time_now_iso8601 +from pipecat.utils.tracing.service_decorators import traced_stt + +try: + from websockets.asyncio.client import connect as websocket_connect + from websockets.protocol import State +except ModuleNotFoundError: + websocket_connect = None + State = None class OpenAISTTService(BaseWhisperSTTService): @@ -77,3 +113,528 @@ class OpenAISTTService(BaseWhisperSTTService): kwargs["temperature"] = self._temperature return await self._client.audio.transcriptions.create(**kwargs) + + +_OPENAI_SAMPLE_RATE = 24000 + + +class OpenAIRealtimeSTTService(WebsocketSTTService): + """OpenAI Realtime Speech-to-Text service using WebSocket transcription sessions. + + Uses OpenAI's Realtime API in transcription-only mode for real-time streaming + speech recognition with optional server-side VAD and noise reduction. The model + does not generate conversational responses — only transcription output. + + This service supports two VAD modes: + + **Local VAD** (default): Disable server-side VAD and use + a local VAD processor in the pipeline instead. When a + ``VADUserStoppedSpeakingFrame`` is received, the service commits the + audio buffer so that the server begins transcription for the completed + speech segment. + + **Server-side VAD** (``turn_detection=None``): The OpenAI server performs voice-activity + detection. The service broadcasts ``UserStartedSpeakingFrame`` and + ``UserStoppedSpeakingFrame`` when the server detects speech boundaries. + Do **not** use a separate VAD processor in the pipeline in this mode. + + Audio is sent as 24 kHz 16-bit mono PCM as required by the OpenAI Realtime + API. If the pipeline runs at a different sample rate (e.g. 16 kHz for Silero + VAD compatibility), audio is automatically upsampled before sending. + + Example:: + + stt = OpenAIRealtimeSTTService( + api_key="sk-...", + model="gpt-4o-transcribe", + noise_reduction="near_field", + ) + """ + + def __init__( + self, + *, + api_key: str, + model: str = "gpt-4o-transcribe", + base_url: str = "wss://api.openai.com/v1/realtime", + language: Optional[Language] = Language.EN, + prompt: Optional[str] = None, + turn_detection: Optional[Union[dict, Literal[False]]] = False, + noise_reduction: Optional[Literal["near_field", "far_field"]] = None, + should_interrupt: bool = True, + **kwargs, + ): + """Initialize the OpenAI Realtime STT service. + + Args: + api_key: OpenAI API key for authentication. + model: Transcription model. Supported values are + ``"gpt-4o-transcribe"`` and ``"gpt-4o-mini-transcribe"``. + Defaults to ``"gpt-4o-transcribe"``. + base_url: WebSocket base URL for the Realtime API. + Defaults to ``"wss://api.openai.com/v1/realtime"``. + language: Language of the audio input. Defaults to English. + prompt: Optional prompt text to guide transcription style + or provide keyword hints. + turn_detection: Server-side VAD configuration. Defaults to + ``False`` (disabled), which relies on a local VAD + processor in the pipeline. Pass ``None`` to use server + defaults (``server_vad``), or a dict with custom + settings (e.g. ``{"type": "server_vad", "threshold": 0.5}``). + noise_reduction: Noise reduction mode. ``"near_field"`` for + close microphones, ``"far_field"`` for distant + microphones, or ``None`` to disable. + should_interrupt: Whether to interrupt bot output when + speech is detected by server-side VAD. Only applies when + turn detection is enabled. Defaults to True. + **kwargs: Additional arguments passed to parent + WebsocketSTTService. + """ + if websocket_connect is None: + raise ImportError( + "websockets is required for OpenAIRealtimeSTTService. " + "Install it with: pip install pipecat-ai[openai]" + ) + + super().__init__(**kwargs) + + self._api_key = api_key + self._base_url = base_url + self.set_model_name(model) + + self._language_code = self._language_to_code(language) if language else None + self._prompt = prompt + self._turn_detection = turn_detection + self._noise_reduction = noise_reduction + self._should_interrupt = should_interrupt + + self._receive_task = None + self._session_ready = False + self._resampler = create_stream_resampler() + + # Server-side VAD is disabled by default (turn_detection=False). + # Set to None or a dict to enable server-side VAD. + self._server_vad_enabled = turn_detection is not False + + @staticmethod + def _language_to_code(language: Language) -> str: + """Convert a Language enum value to an ISO-639-1 code. + + Args: + language: The Language enum value. + + Returns: + Two-letter ISO-639-1 language code. + """ + # Language.value is e.g. "en", "en-US", "fr", "zh". + return language.value.split("-")[0].lower() + + def can_generate_metrics(self) -> bool: + """Check if the service can generate processing metrics. + + Returns: + True, as this service supports metrics generation. + """ + return True + + async def set_language(self, language: Language): + """Set the language for speech recognition. + + If the session is already active, sends an updated configuration + to the server. + + Args: + language: The language to use for speech recognition. + """ + self._language_code = self._language_to_code(language) + if self._session_ready: + await self._send_session_update() + + async def start(self, frame: StartFrame): + """Start the service and establish WebSocket connection. + + Args: + frame: The start frame triggering service initialization. + """ + await super().start(frame) + await self._connect() + + async def stop(self, frame: EndFrame): + """Stop the service and close WebSocket connection. + + Args: + frame: The end frame triggering service shutdown. + """ + await super().stop(frame) + await self._disconnect() + + async def cancel(self, frame: CancelFrame): + """Cancel the service and close WebSocket connection. + + Args: + frame: The cancel frame triggering service cancellation. + """ + await super().cancel(frame) + await self._disconnect() + + async def run_stt(self, audio: bytes) -> AsyncGenerator[Frame, None]: + """Send audio data to the transcription session. + + Audio is streamed over the WebSocket. Transcription results arrive + asynchronously via the receive task and are pushed as + ``InterimTranscriptionFrame`` or ``TranscriptionFrame``. + + Args: + audio: Raw audio bytes (16-bit mono PCM at the pipeline + sample rate). Automatically resampled to 24 kHz. + + Yields: + None — results are delivered via the WebSocket receive task. + """ + await self._send_audio(audio) + yield None + + async def process_frame(self, frame: Frame, direction: FrameDirection): + """Process frames from the pipeline. + + Extends the base STT service to handle local VAD events when + server-side VAD is disabled. On ``VADUserStoppedSpeakingFrame``, + commits the audio buffer so the server begins transcription for + the completed speech segment. + + Args: + frame: The frame to process. + direction: The direction of frame flow in the pipeline. + """ + await super().process_frame(frame, direction) + + # Handle local VAD events when server-side VAD is disabled. + if not self._server_vad_enabled: + if isinstance(frame, VADUserStartedSpeakingFrame): + await self.start_processing_metrics() + elif isinstance(frame, VADUserStoppedSpeakingFrame): + await self._commit_audio_buffer() + + # ------------------------------------------------------------------ + # WebSocket connection management + # ------------------------------------------------------------------ + + async def _connect(self): + """Connect to the transcription endpoint and start receiving.""" + await super()._connect() + await self._connect_websocket() + if self._websocket and not self._receive_task: + self._receive_task = self.create_task(self._receive_task_handler(self._report_error)) + + async def _disconnect(self): + """Disconnect and clean up background tasks.""" + await super()._disconnect() + if self._receive_task: + await self.cancel_task(self._receive_task, timeout=1.0) + self._receive_task = None + await self._disconnect_websocket() + + async def _connect_websocket(self): + """Establish the WebSocket connection to the transcription endpoint.""" + try: + if self._websocket and self._websocket.state is State.OPEN: + return + + self._session_ready = False + url = f"{self._base_url}?intent=transcription" + self._websocket = await websocket_connect( + uri=url, + additional_headers={ + "Authorization": f"Bearer {self._api_key}", + }, + ) + await self._call_event_handler("on_connected") + except Exception as e: + await self.push_error( + error_msg=f"Error connecting to OpenAI Realtime STT: {e}", + exception=e, + ) + self._websocket = None + + async def _disconnect_websocket(self): + """Close the WebSocket connection.""" + try: + self._session_ready = False + if self._websocket: + await self._websocket.close() + except Exception as e: + await self.push_error( + error_msg=f"Error disconnecting: {e}", + exception=e, + ) + finally: + self._websocket = None + await self._call_event_handler("on_disconnected") + + async def _ws_send(self, message: dict): + """Send a JSON message over the WebSocket. + + Args: + message: The message dict to serialize and send. + """ + try: + if not self._disconnecting and self._websocket: + await self._websocket.send(json.dumps(message)) + except Exception as e: + if self._disconnecting or not self._websocket: + return + await self.push_error( + error_msg=f"Error sending message: {e}", + exception=e, + ) + + # ------------------------------------------------------------------ + # Client events + # ------------------------------------------------------------------ + + async def _send_session_update(self): + """Send ``session.update`` to configure the transcription session.""" + transcription: dict = {"model": self.model_name} + + if self._language_code: + transcription["language"] = self._language_code + + if self._prompt: + transcription["prompt"] = self._prompt + + input_audio: dict = { + "format": { + "type": "audio/pcm", + "rate": _OPENAI_SAMPLE_RATE, + }, + "transcription": transcription, + } + + # Turn detection + if self._turn_detection is False: + input_audio["turn_detection"] = None + elif self._turn_detection is not None: + input_audio["turn_detection"] = self._turn_detection + + # Noise reduction + if self._noise_reduction: + input_audio["noise_reduction"] = { + "type": self._noise_reduction, + } + + await self._ws_send( + { + "type": "session.update", + "session": { + "type": "transcription", + "audio": { + "input": input_audio, + }, + }, + } + ) + + async def _send_audio(self, audio: bytes): + """Send audio data via ``input_audio_buffer.append``. + + Resamples from the pipeline sample rate to 24 kHz if needed. + + Args: + audio: Raw audio bytes at the pipeline sample rate. + """ + audio = await self._resampler.resample(audio, self.sample_rate, _OPENAI_SAMPLE_RATE) + if not audio: + return + payload = base64.b64encode(audio).decode("utf-8") + await self._ws_send( + { + "type": "input_audio_buffer.append", + "audio": payload, + } + ) + + async def _commit_audio_buffer(self): + """Commit the current audio buffer for transcription.""" + await self._ws_send({"type": "input_audio_buffer.commit"}) + + async def _clear_audio_buffer(self): + """Clear the current audio buffer.""" + await self._ws_send({"type": "input_audio_buffer.clear"}) + + # ------------------------------------------------------------------ + # Server event handling + # ------------------------------------------------------------------ + + async def _receive_messages(self): + """Receive and dispatch server events from the transcription session. + + Called by ``WebsocketService._receive_task_handler`` which wraps + this method with automatic reconnection on connection errors. + """ + async for message in self._websocket: + try: + evt = json.loads(message) + except json.JSONDecodeError: + logger.warning("Failed to parse WebSocket message") + continue + + evt_type = evt.get("type", "") + + if evt_type == "session.created": + await self._handle_session_created(evt) + elif evt_type == "session.updated": + await self._handle_session_updated(evt) + elif evt_type == "conversation.item.input_audio_transcription.delta": + await self._handle_transcription_delta(evt) + elif evt_type == "conversation.item.input_audio_transcription.completed": + await self._handle_transcription_completed(evt) + elif evt_type == "conversation.item.input_audio_transcription.failed": + await self._handle_transcription_failed(evt) + elif evt_type == "input_audio_buffer.speech_started": + await self._handle_speech_started(evt) + elif evt_type == "input_audio_buffer.speech_stopped": + await self._handle_speech_stopped(evt) + elif evt_type == "input_audio_buffer.committed": + logger.trace(f"Audio buffer committed: item_id={evt.get('item_id', '')}") + elif evt_type == "error": + await self._handle_error(evt) + else: + logger.trace(f"Unhandled event: {evt_type}") + + async def _handle_session_created(self, evt: dict): + """Handle ``session.created``. + + Sent immediately after connecting. We respond by configuring the + session with our desired settings. + + Args: + evt: The session created event from the server. + """ + logger.debug("Transcription session created, sending configuration") + await self._send_session_update() + + async def _handle_session_updated(self, evt: dict): + """Handle ``session.updated``. + + The session is now fully configured and ready to transcribe. + + Args: + evt: The session updated event from the server. + """ + logger.debug("Transcription session configured and ready") + self._session_ready = True + + async def _handle_transcription_delta(self, evt: dict): + """Handle incremental transcription text. + + For ``gpt-4o-transcribe`` and ``gpt-4o-mini-transcribe``, deltas + contain streaming partial text. For ``whisper-1``, each delta + contains the full turn transcript. + + Args: + evt: The delta event from the server. + """ + delta = evt.get("delta", "") + if delta: + await self.push_frame( + InterimTranscriptionFrame( + delta, + self._user_id, + time_now_iso8601(), + result=evt, + ) + ) + + async def _handle_transcription_completed(self, evt: dict): + """Handle a completed transcription for a speech segment. + + Pushes a ``TranscriptionFrame`` and records the result for + tracing. + + Args: + evt: The completed event containing the full transcript. + """ + transcript = evt.get("transcript", "") + if transcript: + await self.push_frame( + TranscriptionFrame( + transcript, + self._user_id, + time_now_iso8601(), + result=evt, + ) + ) + await self._handle_transcription_trace(transcript, True) + await self.stop_processing_metrics() + + @traced_stt + async def _handle_transcription_trace( + self, + transcript: str, + is_final: bool, + language: Optional[Language] = None, + ): + """Record transcription result for tracing. + + Args: + transcript: The transcribed text. + is_final: Whether this is a final transcription result. + language: Optional language of the transcription. + """ + pass + + async def _handle_speech_started(self, evt: dict): + """Handle server-side VAD speech start. + + Broadcasts ``UserStartedSpeakingFrame`` and optionally triggers + interruption of current bot output. + + Args: + evt: The ``input_audio_buffer.speech_started`` event. + """ + logger.debug("Server VAD: speech started") + await self.broadcast_frame(UserStartedSpeakingFrame) + if self._should_interrupt: + await self.push_interruption_task_frame_and_wait() + await self.start_processing_metrics() + + async def _handle_speech_stopped(self, evt: dict): + """Handle server-side VAD speech stop. + + Broadcasts ``UserStoppedSpeakingFrame``. The audio buffer is + automatically committed by the server when VAD is enabled. + + Args: + evt: The ``input_audio_buffer.speech_stopped`` event. + """ + logger.debug("Server VAD: speech stopped") + await self.broadcast_frame(UserStoppedSpeakingFrame) + + async def _handle_transcription_failed(self, evt: dict): + """Handle a transcription failure for a speech segment. + + Logs the error but does not treat it as fatal — the session + remains active for subsequent turns. + + Args: + evt: The failed event containing error details. + """ + error = evt.get("error", {}) + error_msg = error.get("message", "Transcription failed") + await self.push_error(error_msg=f"OpenAI Realtime STT error: {error_msg}") + + async def _handle_error(self, evt: dict): + """Handle a fatal error from the transcription session. + + Raises an exception so that ``WebsocketService`` can decide + whether to attempt reconnection. + + Args: + evt: The error event. + """ + error = evt.get("error", {}) + error_msg = error.get("message", "Unknown error") + error_code = error.get("code", "") + msg = f"OpenAI Realtime STT error [{error_code}]: {error_msg}" + await self.push_error(error_msg=msg) + raise Exception(msg) From d11e1cd631d2db5d16521f0b8bd09a555636f22c Mon Sep 17 00:00:00 2001 From: Mark Backman Date: Thu, 5 Feb 2026 15:07:47 -0500 Subject: [PATCH 0371/1060] Update 13k to use ElevenLabsRealtimeSTTService --- .../13k-elevenlabs-transcription.py | 32 ++++++++----------- 1 file changed, 14 insertions(+), 18 deletions(-) diff --git a/examples/foundational/13k-elevenlabs-transcription.py b/examples/foundational/13k-elevenlabs-transcription.py index f27bbb52a..2b0b8143f 100644 --- a/examples/foundational/13k-elevenlabs-transcription.py +++ b/examples/foundational/13k-elevenlabs-transcription.py @@ -18,7 +18,7 @@ from pipecat.pipeline.task import PipelineTask from pipecat.processors.frame_processor import FrameDirection, FrameProcessor from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport -from pipecat.services.elevenlabs.stt import ElevenLabsSTTService +from pipecat.services.elevenlabs.stt import ElevenLabsRealtimeSTTService from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams @@ -51,29 +51,25 @@ transport_params = { async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): logger.info(f"Starting bot") - async with aiohttp.ClientSession() as session: - stt = ElevenLabsSTTService( - api_key=os.getenv("ELEVENLABS_API_KEY"), - aiohttp_session=session, - ) + stt = ElevenLabsRealtimeSTTService(api_key=os.getenv("ELEVENLABS_API_KEY")) - tl = TranscriptionLogger() + tl = TranscriptionLogger() - pipeline = Pipeline([transport.input(), stt, tl]) + pipeline = Pipeline([transport.input(), stt, tl]) - task = PipelineTask( - pipeline, - idle_timeout_secs=runner_args.pipeline_idle_timeout_secs, - ) + task = PipelineTask( + pipeline, + idle_timeout_secs=runner_args.pipeline_idle_timeout_secs, + ) - @transport.event_handler("on_client_disconnected") - async def on_client_disconnected(transport, client): - logger.info(f"Client disconnected") - await task.cancel() + @transport.event_handler("on_client_disconnected") + async def on_client_disconnected(transport, client): + logger.info(f"Client disconnected") + await task.cancel() - runner = PipelineRunner(handle_sigint=runner_args.handle_sigint) + runner = PipelineRunner(handle_sigint=runner_args.handle_sigint) - await runner.run(task) + await runner.run(task) async def bot(runner_args: RunnerArguments): From 76f63e54e2dd857a0acc624a6a3c35048d77676d Mon Sep 17 00:00:00 2001 From: filipi87 Date: Thu, 5 Feb 2026 18:07:14 -0300 Subject: [PATCH 0372/1060] =?UTF-8?q?Changing=20the=20=E2=80=98no=20audio?= =?UTF-8?q?=20received=E2=80=99=20log=20from=20warning=20to=20debug.?= MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit --- src/pipecat/transports/base_input.py | 4 +--- 1 file changed, 1 insertion(+), 3 deletions(-) diff --git a/src/pipecat/transports/base_input.py b/src/pipecat/transports/base_input.py index 5f62045f1..b76ae61ef 100644 --- a/src/pipecat/transports/base_input.py +++ b/src/pipecat/transports/base_input.py @@ -449,9 +449,7 @@ class BaseInputTransport(FrameProcessor): if not audio_received: continue - logger.warning( - f"{self}: audio not received for more than {AUDIO_INPUT_TIMEOUT_SECS}" - ) + logger.debug(f"{self}: audio not received for more than {AUDIO_INPUT_TIMEOUT_SECS}") ################################################################### # DEPRECATED. From 90700d10aaa070fbe0abc8fb3888a9165256c71a Mon Sep 17 00:00:00 2001 From: Mark Backman Date: Thu, 5 Feb 2026 18:08:52 -0500 Subject: [PATCH 0373/1060] Upgrade protobuf to >=5.29.6 --- pyproject.toml | 2 +- uv.lock | 18 +++++++++--------- 2 files changed, 10 insertions(+), 10 deletions(-) diff --git a/pyproject.toml b/pyproject.toml index 0a5e5d646..2dece87e8 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -29,7 +29,7 @@ dependencies = [ "nltk>=3.9.1,<4", "numpy>=1.26.4,<3", "Pillow>=11.1.0,<12", - "protobuf~=5.29.3", + "protobuf~=5.29.6", "pydantic>=2.10.6,<3", "pyloudnorm~=0.1.1", "resampy~=0.4.3", diff --git a/uv.lock b/uv.lock index 79c0da5f6..d13bed1b8 100644 --- a/uv.lock +++ b/uv.lock @@ -4737,7 +4737,7 @@ requires-dist = [ { name = "pipecat-ai-krisp", marker = "extra == 'krisp'", specifier = "~=0.4.0" }, { name = "pipecat-ai-small-webrtc-prebuilt", marker = "extra == 'runner'", specifier = ">=2.1.0" }, { name = "piper-tts", marker = "extra == 'piper'", specifier = ">=1.3.0,<2" }, - 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changelog/3593.change.md | 1 + src/pipecat/services/inworld/tts.py | 2 +- 3 files changed, 2 insertions(+), 2 deletions(-) create mode 100644 changelog/3593.change.md diff --git a/changelog/3593.added.md b/changelog/3593.added.md index 67b2394d2..432db3636 100644 --- a/changelog/3593.added.md +++ b/changelog/3593.added.md @@ -1,2 +1 @@ - Added support for Inworld TTS Websocket Auto Mode for improved latency -- Updated timestamps to be cumulative within an agent turn, using flushCompleted message as an indication of when timestamps from the server are reset to 0 \ No newline at end of file diff --git a/changelog/3593.change.md b/changelog/3593.change.md new file mode 100644 index 000000000..a21549f36 --- /dev/null +++ b/changelog/3593.change.md @@ -0,0 +1 @@ +- Updated timestamps to be cumulative within an agent turn, using flushCompleted message as an indication of when timestamps from the server are reset to 0 diff --git a/src/pipecat/services/inworld/tts.py b/src/pipecat/services/inworld/tts.py index 16898c67f..fee6c49ac 100644 --- a/src/pipecat/services/inworld/tts.py +++ b/src/pipecat/services/inworld/tts.py @@ -501,7 +501,7 @@ class InworldTTSService(AudioContextWordTTSService): # Track cumulative time across generations for monotonic timestamps within a turn. # When auto_mode is enabled, the server controls generations and timestamps reset - # to 0 after each generation, as indicated by a "flushCompleted" message. We + # to 0 after each generation, as indicated by a "flushCompleted" message. We # add _cumulative_time to maintain monotonically increasing timestamps. self._cumulative_time = 0.0 # Track the end time of the last word in the current generation From 29c53b99a49157f2b28056426b5389bf2544aa18 Mon Sep 17 00:00:00 2001 From: Luke Payyapilli Date: Fri, 6 Feb 2026 09:58:37 -0500 Subject: [PATCH 0375/1060] fix: close stream on cancellation for SambaNova and Google OpenAI services --- src/pipecat/services/google/llm_openai.py | 87 ++++++++++---------- src/pipecat/services/sambanova/llm.py | 97 ++++++++++++----------- tests/test_google_llm_openai.py | 81 +++++++++++++++++++ tests/test_sambanova_llm.py | 72 +++++++++++++++++ 4 files changed, 248 insertions(+), 89 deletions(-) create mode 100644 tests/test_google_llm_openai.py create mode 100644 tests/test_sambanova_llm.py diff --git a/src/pipecat/services/google/llm_openai.py b/src/pipecat/services/google/llm_openai.py index c781fe0d3..5d396b583 100644 --- a/src/pipecat/services/google/llm_openai.py +++ b/src/pipecat/services/google/llm_openai.py @@ -91,52 +91,55 @@ class GoogleLLMOpenAIBetaService(OpenAILLMService): ChatCompletionChunk ] = await self._stream_chat_completions_specific_context(context) - async for chunk in chunk_stream: - if chunk.usage: - tokens = LLMTokenUsage( - prompt_tokens=chunk.usage.prompt_tokens or 0, - completion_tokens=chunk.usage.completion_tokens or 0, - total_tokens=chunk.usage.total_tokens or 0, - ) - await self.start_llm_usage_metrics(tokens) + # Use context manager to ensure stream is closed on cancellation/exception. + # Without this, CancelledError during iteration leaves the underlying socket open. + async with chunk_stream: + async for chunk in chunk_stream: + if chunk.usage: + tokens = LLMTokenUsage( + prompt_tokens=chunk.usage.prompt_tokens or 0, + completion_tokens=chunk.usage.completion_tokens or 0, + total_tokens=chunk.usage.total_tokens or 0, + ) + await self.start_llm_usage_metrics(tokens) - if chunk.choices is None or len(chunk.choices) == 0: - continue + if chunk.choices is None or len(chunk.choices) == 0: + continue - await self.stop_ttfb_metrics() + await self.stop_ttfb_metrics() - if not chunk.choices[0].delta: - continue + if not chunk.choices[0].delta: + continue - if chunk.choices[0].delta.tool_calls: - # We're streaming the LLM response to enable the fastest response times. - # For text, we just yield each chunk as we receive it and count on consumers - # to do whatever coalescing they need (eg. to pass full sentences to TTS) - # - # If the LLM is a function call, we'll do some coalescing here. - # If the response contains a function name, we'll yield a frame to tell consumers - # that they can start preparing to call the function with that name. - # We accumulate all the arguments for the rest of the streamed response, then when - # the response is done, we package up all the arguments and the function name and - # yield a frame containing the function name and the arguments. - logger.debug(f"Tool call: {chunk.choices[0].delta.tool_calls}") - tool_call = chunk.choices[0].delta.tool_calls[0] - if tool_call.index != func_idx: - functions_list.append(function_name) - arguments_list.append(arguments) - tool_id_list.append(tool_call_id) - function_name = "" - arguments = "" - tool_call_id = "" - func_idx += 1 - if tool_call.function and tool_call.function.name: - function_name += tool_call.function.name - tool_call_id = tool_call.id - if tool_call.function and tool_call.function.arguments: - # Keep iterating through the response to collect all the argument fragments - arguments += tool_call.function.arguments - elif chunk.choices[0].delta.content: - await self.push_frame(LLMTextFrame(chunk.choices[0].delta.content)) + if chunk.choices[0].delta.tool_calls: + # We're streaming the LLM response to enable the fastest response times. + # For text, we just yield each chunk as we receive it and count on consumers + # to do whatever coalescing they need (eg. to pass full sentences to TTS) + # + # If the LLM is a function call, we'll do some coalescing here. + # If the response contains a function name, we'll yield a frame to tell consumers + # that they can start preparing to call the function with that name. + # We accumulate all the arguments for the rest of the streamed response, then when + # the response is done, we package up all the arguments and the function name and + # yield a frame containing the function name and the arguments. + logger.debug(f"Tool call: {chunk.choices[0].delta.tool_calls}") + tool_call = chunk.choices[0].delta.tool_calls[0] + if tool_call.index != func_idx: + functions_list.append(function_name) + arguments_list.append(arguments) + tool_id_list.append(tool_call_id) + function_name = "" + arguments = "" + tool_call_id = "" + func_idx += 1 + if tool_call.function and tool_call.function.name: + function_name += tool_call.function.name + tool_call_id = tool_call.id + if tool_call.function and tool_call.function.arguments: + # Keep iterating through the response to collect all the argument fragments + arguments += tool_call.function.arguments + elif chunk.choices[0].delta.content: + await self.push_frame(LLMTextFrame(chunk.choices[0].delta.content)) # if we got a function name and arguments, check to see if it's a function with # a registered handler. If so, run the registered callback, save the result to diff --git a/src/pipecat/services/sambanova/llm.py b/src/pipecat/services/sambanova/llm.py index d50978d72..047ce0e6c 100644 --- a/src/pipecat/services/sambanova/llm.py +++ b/src/pipecat/services/sambanova/llm.py @@ -131,59 +131,62 @@ class SambaNovaLLMService(OpenAILLMService): # type: ignore else self._stream_chat_completions_universal_context(context) ) - async for chunk in chunk_stream: - if chunk.usage: - tokens = LLMTokenUsage( - prompt_tokens=chunk.usage.prompt_tokens, - completion_tokens=chunk.usage.completion_tokens, - total_tokens=chunk.usage.total_tokens, - ) - await self.start_llm_usage_metrics(tokens) + # Use context manager to ensure stream is closed on cancellation/exception. + # Without this, CancelledError during iteration leaves the underlying socket open. + async with chunk_stream: + async for chunk in chunk_stream: + if chunk.usage: + tokens = LLMTokenUsage( + prompt_tokens=chunk.usage.prompt_tokens, + completion_tokens=chunk.usage.completion_tokens, + total_tokens=chunk.usage.total_tokens, + ) + await self.start_llm_usage_metrics(tokens) - if chunk.choices is None or len(chunk.choices) == 0: - continue + if chunk.choices is None or len(chunk.choices) == 0: + continue - await self.stop_ttfb_metrics() + await self.stop_ttfb_metrics() - if not chunk.choices[0].delta: - continue + if not chunk.choices[0].delta: + continue - if chunk.choices[0].delta.tool_calls: - # We're streaming the LLM response to enable the fastest response times. - # For text, we just yield each chunk as we receive it and count on consumers - # to do whatever coalescing they need (eg. to pass full sentences to TTS) - # - # If the LLM is a function call, we'll do some coalescing here. - # If the response contains a function name, we'll yield a frame to tell consumers - # that they can start preparing to call the function with that name. - # We accumulate all the arguments for the rest of the streamed response, then when - # the response is done, we package up all the arguments and the function name and - # yield a frame containing the function name and the arguments. + if chunk.choices[0].delta.tool_calls: + # We're streaming the LLM response to enable the fastest response times. + # For text, we just yield each chunk as we receive it and count on consumers + # to do whatever coalescing they need (eg. to pass full sentences to TTS) + # + # If the LLM is a function call, we'll do some coalescing here. + # If the response contains a function name, we'll yield a frame to tell consumers + # that they can start preparing to call the function with that name. + # We accumulate all the arguments for the rest of the streamed response, then when + # the response is done, we package up all the arguments and the function name and + # yield a frame containing the function name and the arguments. - tool_call = chunk.choices[0].delta.tool_calls[0] - if tool_call.index != func_idx: - functions_list.append(function_name) - arguments_list.append(arguments) - tool_id_list.append(tool_call_id) - function_name = "" - arguments = "" - tool_call_id = "" - func_idx += 1 - if tool_call.function and tool_call.function.name: - function_name += tool_call.function.name - tool_call_id = tool_call.id # type: ignore - if tool_call.function and tool_call.function.arguments: - # Keep iterating through the response to collect all the argument fragments - arguments += tool_call.function.arguments - elif chunk.choices[0].delta.content: - await self.push_frame(LLMTextFrame(chunk.choices[0].delta.content)) + tool_call = chunk.choices[0].delta.tool_calls[0] + if tool_call.index != func_idx: + functions_list.append(function_name) + arguments_list.append(arguments) + tool_id_list.append(tool_call_id) + function_name = "" + arguments = "" + tool_call_id = "" + func_idx += 1 + if tool_call.function and tool_call.function.name: + function_name += tool_call.function.name + tool_call_id = tool_call.id # type: ignore + if tool_call.function and tool_call.function.arguments: + # Keep iterating through the response to collect all the argument fragments + arguments += tool_call.function.arguments + elif chunk.choices[0].delta.content: + await self.push_frame(LLMTextFrame(chunk.choices[0].delta.content)) - # When gpt-4o-audio / gpt-4o-mini-audio is used for llm or stt+llm - # we need to get LLMTextFrame for the transcript - elif hasattr(chunk.choices[0].delta, "audio") and chunk.choices[0].delta.audio.get( - "transcript" - ): - await self.push_frame(LLMTextFrame(chunk.choices[0].delta.audio["transcript"])) + # When gpt-4o-audio / gpt-4o-mini-audio is used for llm or stt+llm + # we need to get LLMTextFrame for the transcript + elif hasattr(chunk.choices[0].delta, "audio") and chunk.choices[0].delta.audio.get( + "transcript" + ): + await self.push_frame(LLMTextFrame(chunk.choices[0].delta.audio["transcript"])) # if we got a function name and arguments, check to see if it's a function with # a registered handler. If so, run the registered callback, save the result to diff --git a/tests/test_google_llm_openai.py b/tests/test_google_llm_openai.py new file mode 100644 index 000000000..2940bf7d7 --- /dev/null +++ b/tests/test_google_llm_openai.py @@ -0,0 +1,81 @@ +# +# Copyright (c) 2024-2026, Daily +# +# SPDX-License-Identifier: BSD 2-Clause License +# + +"""Unit tests for Google LLM OpenAI Beta service.""" + +import asyncio +import warnings +from unittest.mock import AsyncMock, patch + +import pytest + +from pipecat.processors.aggregators.openai_llm_context import OpenAILLMContext + +try: + from pipecat.services.google.llm_openai import GoogleLLMOpenAIBetaService + + google_available = True +except Exception: + google_available = False + + +@pytest.mark.asyncio +@pytest.mark.skipif(not google_available, reason="Google dependencies not installed") +async def test_google_llm_openai_stream_closed_on_cancellation(): + """Test that the stream is closed when CancelledError occurs during iteration. + + This prevents socket leaks when the pipeline is interrupted (e.g., user interruption). + See issue #3639. + """ + with patch.object(GoogleLLMOpenAIBetaService, "create_client"): + with warnings.catch_warnings(): + warnings.simplefilter("ignore", DeprecationWarning) + service = GoogleLLMOpenAIBetaService(api_key="test-key", model="test-model") + service._client = AsyncMock() + + stream_closed = False + + class MockAsyncStream: + """Mock AsyncStream that tracks close() calls and raises CancelledError.""" + + def __init__(self): + self.iteration_count = 0 + + async def __aenter__(self): + return self + + async def __aexit__(self, exc_type, exc_val, exc_tb): + nonlocal stream_closed + stream_closed = True + return False + + def __aiter__(self): + return self + + async def __anext__(self): + self.iteration_count += 1 + if self.iteration_count > 1: + raise asyncio.CancelledError() + mock_chunk = AsyncMock() + mock_chunk.usage = None + mock_chunk.choices = [] + return mock_chunk + + mock_stream = MockAsyncStream() + + service._stream_chat_completions_specific_context = AsyncMock(return_value=mock_stream) + service.start_ttfb_metrics = AsyncMock() + service.stop_ttfb_metrics = AsyncMock() + service.start_llm_usage_metrics = AsyncMock() + + context = OpenAILLMContext( + messages=[{"role": "user", "content": "Hello"}], + ) + + with pytest.raises(asyncio.CancelledError): + await service._process_context(context) + + assert stream_closed, "Stream should be closed even when CancelledError occurs" diff --git a/tests/test_sambanova_llm.py b/tests/test_sambanova_llm.py new file mode 100644 index 000000000..6632951fc --- /dev/null +++ b/tests/test_sambanova_llm.py @@ -0,0 +1,72 @@ +# +# Copyright (c) 2024-2026, Daily +# +# SPDX-License-Identifier: BSD 2-Clause License +# + +"""Unit tests for SambaNova LLM service.""" + +import asyncio +from unittest.mock import AsyncMock, patch + +import pytest + +from pipecat.processors.aggregators.llm_context import LLMContext +from pipecat.services.sambanova.llm import SambaNovaLLMService + + +@pytest.mark.asyncio +async def test_sambanova_llm_stream_closed_on_cancellation(): + """Test that the stream is closed when CancelledError occurs during iteration. + + This prevents socket leaks when the pipeline is interrupted (e.g., user interruption). + See issue #3639. + """ + with patch.object(SambaNovaLLMService, "create_client"): + service = SambaNovaLLMService(api_key="test-key", model="test-model") + service._client = AsyncMock() + + stream_closed = False + + class MockAsyncStream: + """Mock AsyncStream that tracks close() calls and raises CancelledError.""" + + def __init__(self): + self.iteration_count = 0 + + async def __aenter__(self): + return self + + async def __aexit__(self, exc_type, exc_val, exc_tb): + nonlocal stream_closed + stream_closed = True + return False + + def __aiter__(self): + return self + + async def __anext__(self): + self.iteration_count += 1 + if self.iteration_count > 1: + raise asyncio.CancelledError() + mock_chunk = AsyncMock() + mock_chunk.usage = None + mock_chunk.choices = [] + return mock_chunk + + mock_stream = MockAsyncStream() + + service._stream_chat_completions_specific_context = AsyncMock(return_value=mock_stream) + service._stream_chat_completions_universal_context = AsyncMock(return_value=mock_stream) + service.start_ttfb_metrics = AsyncMock() + service.stop_ttfb_metrics = AsyncMock() + service.start_llm_usage_metrics = AsyncMock() + + context = LLMContext( + messages=[{"role": "user", "content": "Hello"}], + ) + + with pytest.raises(asyncio.CancelledError): + await service._process_context(context) + + assert stream_closed, "Stream should be closed even when CancelledError occurs" From 1790a84bfd43cc1d351dc0be3bd12ccf2fc9e008 Mon Sep 17 00:00:00 2001 From: Luke Payyapilli Date: Fri, 6 Feb 2026 10:05:02 -0500 Subject: [PATCH 0376/1060] add changelog --- changelog/3663.fixed.md | 1 + 1 file changed, 1 insertion(+) create mode 100644 changelog/3663.fixed.md diff --git a/changelog/3663.fixed.md b/changelog/3663.fixed.md new file mode 100644 index 000000000..be6318aad --- /dev/null +++ b/changelog/3663.fixed.md @@ -0,0 +1 @@ +- Fixed `SambaNovaLLMService` and `GoogleLLMOpenAIBetaService` streams not being closed on cancellation/exception, which could leak sockets. From d4993f0dcff3e23aed13e5827f6c5362d8b401ab Mon Sep 17 00:00:00 2001 From: Mark Backman Date: Fri, 6 Feb 2026 11:36:07 -0500 Subject: [PATCH 0377/1060] Update ElevenLabsSTTService to scribe_v2 --- changelog/3664.changed.md | 1 + src/pipecat/services/elevenlabs/stt.py | 4 ++-- 2 files changed, 3 insertions(+), 2 deletions(-) create mode 100644 changelog/3664.changed.md diff --git a/changelog/3664.changed.md b/changelog/3664.changed.md new file mode 100644 index 000000000..f91dff3bd --- /dev/null +++ b/changelog/3664.changed.md @@ -0,0 +1 @@ +- Update the default model to `scribe_v2` for `ElevenLabsSTTService`. \ No newline at end of file diff --git a/src/pipecat/services/elevenlabs/stt.py b/src/pipecat/services/elevenlabs/stt.py index 469d2c4fa..01df424a0 100644 --- a/src/pipecat/services/elevenlabs/stt.py +++ b/src/pipecat/services/elevenlabs/stt.py @@ -191,7 +191,7 @@ class ElevenLabsSTTService(SegmentedSTTService): api_key: str, aiohttp_session: aiohttp.ClientSession, base_url: str = "https://api.elevenlabs.io", - model: str = "scribe_v1", + model: str = "scribe_v2", sample_rate: Optional[int] = None, params: Optional[InputParams] = None, **kwargs, @@ -202,7 +202,7 @@ class ElevenLabsSTTService(SegmentedSTTService): api_key: ElevenLabs API key for authentication. aiohttp_session: aiohttp ClientSession for HTTP requests. base_url: Base URL for ElevenLabs API. - model: Model ID for transcription. Defaults to "scribe_v1". + model: Model ID for transcription. Defaults to "scribe_v2". sample_rate: Audio sample rate in Hz. If not provided, uses the pipeline's rate. params: Configuration parameters for the STT service. **kwargs: Additional arguments passed to SegmentedSTTService. From 2345090b10541adbb52c4395b336ccdfed1fcec2 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Aleix=20Conchillo=20Flaqu=C3=A9?= Date: Thu, 5 Feb 2026 22:14:50 -0800 Subject: [PATCH 0378/1060] Attach asyncio.Event to InterruptionFrame for completion signaling MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit Move the interruption wait event from per-processor instance state to the frame itself. The event is created in push_interruption_task_frame_and_wait(), threaded through InterruptionTaskFrame → InterruptionFrame, and set when the frame reaches the pipeline sink. This scopes the event to each interruption flow rather than sharing mutable state on the processor. Also adds a 2s timeout warning to help diagnose cases where InterruptionFrame.complete() is never called. --- src/pipecat/frames/frames.py | 43 +++++++++---- src/pipecat/pipeline/task.py | 4 +- .../aggregators/llm_response_universal.py | 6 ++ src/pipecat/processors/frame_processor.py | 60 ++++++++++--------- 4 files changed, 73 insertions(+), 40 deletions(-) diff --git a/src/pipecat/frames/frames.py b/src/pipecat/frames/frames.py index b0e196a22..b7be8045e 100644 --- a/src/pipecat/frames/frames.py +++ b/src/pipecat/frames/frames.py @@ -11,6 +11,7 @@ including data frames, system frames, and control frames for audio, video, text, and LLM processing. """ +import asyncio from dataclasses import dataclass, field from enum import Enum from typing import ( @@ -1118,15 +1119,29 @@ class FrameProcessorResumeUrgentFrame(SystemFrame): @dataclass class InterruptionFrame(SystemFrame): - """Frame indicating user started speaking (interruption detected). + """Frame pushed to interrupt the pipeline. + + This frame is used to interrupt the pipeline. For example, when a user + starts speaking to cancel any in-progress bot output. It can also be pushed + by any processor. + + Parameters: + event: Optional event set when the frame has fully traversed the + pipeline. - Emitted by the BaseInputTransport to indicate that a user has started - speaking (i.e. is interrupting). This is similar to - UserStartedSpeakingFrame except that it should be pushed concurrently - with other frames (so the order is not guaranteed). """ - pass + event: Optional[asyncio.Event] = None + + def complete(self): + """Signal that this interruption has been fully processed. + + Called automatically when the frame reaches the pipeline sink, or + manually when the frame is consumed before reaching it (e.g. when + the user is muted). + """ + if self.event: + self.event.set() @dataclass @@ -1706,15 +1721,19 @@ class StopTaskFrame(TaskFrame): @dataclass class InterruptionTaskFrame(TaskFrame): - """Frame indicating the bot should be interrupted. + """Frame indicating the pipeline should be interrupted. + + This frame should be pushed upstream to indicate the pipeline should be + interrupted. The pipeline task converts this into an `InterruptionFrame` and + sends it downstream. The `event` is passed to the `InterruptionFrame` so it + can signal when the interruption has fully traversed the pipeline. + + Parameters: + event: Optional event passed to the corresponding `InterruptionFrame`. - Emitted when the bot should be interrupted. This will mainly cause the - same actions as if the user interrupted except that the - UserStartedSpeakingFrame and UserStoppedSpeakingFrame won't be generated. - This frame should be pushed upstream. """ - pass + event: Optional[asyncio.Event] = None @dataclass diff --git a/src/pipecat/pipeline/task.py b/src/pipecat/pipeline/task.py index e643164eb..8bda19b18 100644 --- a/src/pipecat/pipeline/task.py +++ b/src/pipecat/pipeline/task.py @@ -864,7 +864,7 @@ class PipelineTask(BasePipelineTask): # pipeline. This is in case the push task is blocked waiting for a # pipeline-ending frame to finish traversing the pipeline. logger.debug(f"{self}: received interruption task frame {frame}") - await self._pipeline.queue_frame(InterruptionFrame()) + await self._pipeline.queue_frame(InterruptionFrame(event=frame.event)) elif isinstance(frame, ErrorFrame): await self._call_event_handler("on_pipeline_error", frame) if frame.fatal: @@ -903,6 +903,8 @@ class PipelineTask(BasePipelineTask): self._pipeline_end_event.set() elif isinstance(frame, CancelFrame): self._pipeline_end_event.set() + elif isinstance(frame, InterruptionFrame): + frame.complete() elif isinstance(frame, HeartbeatFrame): await self._heartbeat_queue.put(frame) diff --git a/src/pipecat/processors/aggregators/llm_response_universal.py b/src/pipecat/processors/aggregators/llm_response_universal.py index db28b85c1..cf65c6443 100644 --- a/src/pipecat/processors/aggregators/llm_response_universal.py +++ b/src/pipecat/processors/aggregators/llm_response_universal.py @@ -552,6 +552,12 @@ class LLMUserAggregator(LLMContextAggregator): if should_mute_frame: logger.trace(f"{frame.name} suppressed - user currently muted") + # When muted, the InterruptionFrame won't propagate further and + # will never reach the pipeline sink. Complete it here so + # push_interruption_task_frame_and_wait() doesn't hang. + if should_mute_frame and isinstance(frame, InterruptionFrame): + frame.complete() + should_mute_next_time = False for s in self._params.user_mute_strategies: should_mute_next_time |= await s.process_frame(frame) diff --git a/src/pipecat/processors/frame_processor.py b/src/pipecat/processors/frame_processor.py index 740c19ae6..f0c9e7183 100644 --- a/src/pipecat/processors/frame_processor.py +++ b/src/pipecat/processors/frame_processor.py @@ -52,6 +52,8 @@ from pipecat.processors.metrics.frame_processor_metrics import FrameProcessorMet from pipecat.utils.asyncio.task_manager import BaseTaskManager from pipecat.utils.base_object import BaseObject +INTERRUPTION_COMPLETION_TIMEOUT = 2.0 + class FrameDirection(Enum): """Direction of frame flow in the processing pipeline. @@ -240,13 +242,9 @@ class FrameProcessor(BaseObject): self.__process_frame_task: Optional[asyncio.Task] = None self.__process_current_frame: Optional[Frame] = None - # To interrupt a pipeline, we push an `InterruptionTaskFrame` upstream. - # Then we wait for the corresponding `InterruptionFrame` to travel from - # the start of the pipeline back to the processor that sent the - # `InterruptionTaskFrame`. This wait is handled using the following - # event. + # Set while awaiting push_interruption_task_frame_and_wait() so that + # _start_interruption() knows not to cancel the process task. self._wait_for_interruption = False - self._wait_interruption_event = asyncio.Event() # Frame processor events. self._register_event_handler("on_before_process_frame", sync=True) @@ -600,10 +598,11 @@ class FrameProcessor(BaseObject): if self._cancelling: return - # If we are waiting for an interruption we will bypass all queued system - # frames and we will process the frame right away. This is because a - # previous system frame might be waiting for the interruption frame and - # it's blocking the input task. + # If we are waiting for an interruption, bypass all queued system frames + # and process the frame right away. This is because a previous system + # frame might be waiting for the interruption frame blocking the input + # task, so this InterruptionFrame would never be dequeued and we'd + # deadlock. if self._wait_for_interruption and isinstance(frame, InterruptionFrame): await self.__process_frame(frame, direction, callback) return @@ -742,31 +741,38 @@ class FrameProcessor(BaseObject): await self._call_event_handler("on_after_push_frame", frame) - # If we are waiting for an interruption and we get an interruption, then - # we can unblock `push_interruption_task_frame_and_wait()`. - if self._wait_for_interruption and isinstance(frame, InterruptionFrame): - self._wait_interruption_event.set() - async def push_interruption_task_frame_and_wait(self): """Push an interruption task frame upstream and wait for the interruption. - This function sends an `InterruptionTaskFrame` upstream to the pipeline - task and waits to receive the corresponding `InterruptionFrame`. When - the function finishes it is guaranteed that the `InterruptionFrame` has - been pushed downstream. + This function sends an `InterruptionTaskFrame` upstream to the + pipeline task. The task creates a corresponding `InterruptionFrame` + and sends it downstream through the pipeline. An `asyncio.Event` is + attached to both frames so the caller can wait until the interruption + has fully traversed the pipeline. The event is set when the + `InterruptionFrame` reaches the pipeline sink. If the frame does + not complete within `INTERRUPTION_COMPLETION_TIMEOUT` seconds, a + warning is logged periodically until it completes. + """ self._wait_for_interruption = True - await self.push_frame(InterruptionTaskFrame(), FrameDirection.UPSTREAM) + event = asyncio.Event() - # Wait for an `InterruptionFrame` to come to this processor and be - # pushed. Take a look at `push_frame()` to see how we first push the - # `InterruptionFrame` and then we set the event in order to maintain - # frame ordering. - await self._wait_interruption_event.wait() + await self.push_frame(InterruptionTaskFrame(event=event), FrameDirection.UPSTREAM) - # Clean the event. - self._wait_interruption_event.clear() + # Wait for the `InterruptionFrame` to complete and log a warning + # periodically if it takes too long. + while not event.is_set(): + try: + await asyncio.wait_for(event.wait(), timeout=INTERRUPTION_COMPLETION_TIMEOUT) + except asyncio.TimeoutError: + logger.warning( + f"{self}: InterruptionFrame has not completed after" + f" {INTERRUPTION_COMPLETION_TIMEOUT}s. Make sure" + " InterruptionFrame.complete() is being called (e.g. if the" + " frame is being blocked or consumed before reaching the" + " pipeline sink)." + ) self._wait_for_interruption = False From a352b2d7a01cfebc8bc610b8210ef73f63be02f1 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Aleix=20Conchillo=20Flaqu=C3=A9?= Date: Thu, 5 Feb 2026 22:54:36 -0800 Subject: [PATCH 0379/1060] Add tests for InterruptionFrame completion event Add tests for the event-based interruption completion: complete() sets the event, complete() is safe without an event, the event fires at the pipeline sink, and a warning is logged when the frame is blocked. Also remove the unconditional await after the timeout so the function returns instead of hanging when complete() is never called. --- tests/test_frame_processor.py | 111 +++++++++++++++++++++++++++++++++- 1 file changed, 110 insertions(+), 1 deletion(-) diff --git a/tests/test_frame_processor.py b/tests/test_frame_processor.py index 3a47520b3..2ce4b7880 100644 --- a/tests/test_frame_processor.py +++ b/tests/test_frame_processor.py @@ -9,6 +9,8 @@ import unittest from dataclasses import dataclass, field from typing import List +from loguru import logger + from pipecat.frames.frames import ( DataFrame, EndFrame, @@ -22,7 +24,11 @@ from pipecat.frames.frames import ( ) from pipecat.pipeline.pipeline import Pipeline from pipecat.processors.filters.identity_filter import IdentityFilter -from pipecat.processors.frame_processor import FrameDirection, FrameProcessor +from pipecat.processors.frame_processor import ( + INTERRUPTION_COMPLETION_TIMEOUT, + FrameDirection, + FrameProcessor, +) from pipecat.tests.utils import SleepFrame, run_test @@ -449,6 +455,109 @@ class TestFrameProcessor(unittest.IsolatedAsyncioTestCase): stop_frames = [f for f in received_frames if isinstance(f, StopFrame)] self.assertEqual(len(stop_frames), 1, "StopFrame should survive interruption") + async def test_interruption_frame_complete_sets_event(self): + """Test that InterruptionFrame.complete() sets the event.""" + event = asyncio.Event() + frame = InterruptionFrame(event=event) + self.assertFalse(event.is_set()) + frame.complete() + self.assertTrue(event.is_set()) + + async def test_interruption_frame_complete_without_event(self): + """Test that InterruptionFrame.complete() is safe without an event.""" + frame = InterruptionFrame() + frame.complete() # Should not raise + + async def test_interruption_event_set_at_pipeline_sink(self): + """Test that the event from push_interruption_task_frame_and_wait() + is set when the InterruptionFrame reaches the pipeline sink.""" + event_was_set = False + + class InterruptOnTextProcessor(FrameProcessor): + async def process_frame(self, frame: Frame, direction: FrameDirection): + nonlocal event_was_set + + await super().process_frame(frame, direction) + if isinstance(frame, TextFrame): + await self.push_interruption_task_frame_and_wait() + + event_was_set = True + await self.push_frame(OutputTransportMessageUrgentFrame(message="done")) + else: + await self.push_frame(frame, direction) + + pipeline = Pipeline([InterruptOnTextProcessor()]) + + frames_to_send = [ + TextFrame(text="trigger"), + ] + expected_down_frames = [ + InterruptionFrame, + OutputTransportMessageUrgentFrame, + ] + await run_test( + pipeline, + frames_to_send=frames_to_send, + expected_down_frames=expected_down_frames, + ) + self.assertTrue(event_was_set, "Event should be set after InterruptionFrame completes") + + async def test_interruption_completion_timeout_warning(self): + """Test that a warning is logged when an InterruptionFrame is blocked + and never reaches the pipeline sink.""" + warnings = [] + handler_id = logger.add( + lambda msg: warnings.append(str(msg)), level="WARNING", format="{message}" + ) + + try: + + class BlockInterruptionProcessor(FrameProcessor): + """Blocks InterruptionFrames, completing them after a delay.""" + + async def process_frame(self, frame: Frame, direction: FrameDirection): + await super().process_frame(frame, direction) + if isinstance(frame, InterruptionFrame): + # Complete after the timeout so the warning fires + # but the test doesn't hang. + async def delayed_complete(): + await asyncio.sleep(INTERRUPTION_COMPLETION_TIMEOUT + 1.0) + frame.complete() + + asyncio.create_task(delayed_complete()) + return + await self.push_frame(frame, direction) + + class InterruptOnTextProcessor(FrameProcessor): + async def process_frame(self, frame: Frame, direction: FrameDirection): + await super().process_frame(frame, direction) + if isinstance(frame, TextFrame): + await self.push_interruption_task_frame_and_wait() + await self.push_frame(OutputTransportMessageUrgentFrame(message="done")) + else: + await self.push_frame(frame, direction) + + pipeline = Pipeline([BlockInterruptionProcessor(), InterruptOnTextProcessor()]) + + frames_to_send = [ + TextFrame(text="trigger"), + ] + expected_down_frames = [ + OutputTransportMessageUrgentFrame, + ] + await run_test( + pipeline, + frames_to_send=frames_to_send, + expected_down_frames=expected_down_frames, + ) + finally: + logger.remove(handler_id) + + self.assertTrue( + any("InterruptionFrame has not completed" in w for w in warnings), + "Expected a timeout warning about InterruptionFrame not completing", + ) + if __name__ == "__main__": unittest.main() From d5105a78e6994c94f74af4ee488c8d58713b90cc Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Aleix=20Conchillo=20Flaqu=C3=A9?= Date: Fri, 6 Feb 2026 09:45:20 -0800 Subject: [PATCH 0380/1060] STTMuteFilter should call frame.complete() when InterruptionFrame is blocked --- .../processors/filters/stt_mute_filter.py | 6 ++++ tests/test_stt_mute_filter.py | 29 +++++++++++++++++++ 2 files changed, 35 insertions(+) diff --git a/src/pipecat/processors/filters/stt_mute_filter.py b/src/pipecat/processors/filters/stt_mute_filter.py index 9f522a20d..f5d008e28 100644 --- a/src/pipecat/processors/filters/stt_mute_filter.py +++ b/src/pipecat/processors/filters/stt_mute_filter.py @@ -234,6 +234,12 @@ class STTMuteFilter(FrameProcessor): await self.push_frame(frame, direction) else: logger.trace(f"{frame.__class__.__name__} suppressed - STT currently muted") + + # When muted, the InterruptionFrame won't propagate further + # and will never reach the pipeline sink. Complete it here so + # push_interruption_task_frame_and_wait() doesn't hang. + if isinstance(frame, InterruptionFrame): + frame.complete() else: # Pass all other frames through await self.push_frame(frame, direction) diff --git a/tests/test_stt_mute_filter.py b/tests/test_stt_mute_filter.py index 5682aaf22..adf4611df 100644 --- a/tests/test_stt_mute_filter.py +++ b/tests/test_stt_mute_filter.py @@ -4,6 +4,7 @@ # SPDX-License-Identifier: BSD 2-Clause License # +import asyncio import unittest from pipecat.frames.frames import ( @@ -14,6 +15,7 @@ from pipecat.frames.frames import ( FunctionCallsStartedFrame, InputAudioRawFrame, InterimTranscriptionFrame, + InterruptionFrame, TranscriptionFrame, UserStartedSpeakingFrame, UserStoppedSpeakingFrame, @@ -327,6 +329,33 @@ class TestSTTMuteFilter(unittest.IsolatedAsyncioTestCase): expected_down_frames=expected_returned_frames, ) + async def test_interruption_frame_completed_when_muted(self): + """Test that InterruptionFrame.complete() is called when the frame is + suppressed due to muting, so push_interruption_task_frame_and_wait() + doesn't hang.""" + filter = STTMuteFilter(config=STTMuteConfig(strategies={STTMuteStrategy.ALWAYS})) + + event = asyncio.Event() + + frames_to_send = [ + BotStartedSpeakingFrame(), + InterruptionFrame(event=event), + BotStoppedSpeakingFrame(), + ] + + expected_returned_frames = [ + BotStartedSpeakingFrame, + BotStoppedSpeakingFrame, + ] + + await run_test( + filter, + frames_to_send=frames_to_send, + expected_down_frames=expected_returned_frames, + ) + + self.assertTrue(event.is_set(), "InterruptionFrame.complete() should be called when muted") + if __name__ == "__main__": unittest.main() From b9e79bd06afec69958b4166980b335fd31e3d980 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Aleix=20Conchillo=20Flaqu=C3=A9?= Date: Fri, 6 Feb 2026 10:00:15 -0800 Subject: [PATCH 0381/1060] CLAUDE.md: explain about InterruptionFrame.complete() --- CLAUDE.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/CLAUDE.md b/CLAUDE.md index 1d745755b..162615ab2 100644 --- a/CLAUDE.md +++ b/CLAUDE.md @@ -68,7 +68,7 @@ Transport Input → Pipeline Source → [Processor1] → [Processor2] → ... - **User turn strategies**: Detection of when the user starts and stops speaking is done via user turn start/stop strategies. They push `UserStartedSpeakingFrame` and `UserStoppedSpeakingFrame` respectively. -- **Interruptions**: Interruptions are usually triggered by a user turn start strategy (e.g. `VADUserTurnStartStrategy`) but they can be triggered by other processors as well, in which case the user turn start strategies don't need to. +- **Interruptions**: Interruptions are usually triggered by a user turn start strategy (e.g. `VADUserTurnStartStrategy`) but they can be triggered by other processors as well, in which case the user turn start strategies don't need to. An `InterruptionFrame` carries an optional `asyncio.Event` that is set when the frame reaches the pipeline sink. If a processor stops an `InterruptionFrame` from propagating downstream (i.e., doesn't push it), it **must** call `frame.complete()` to avoid stalling `push_interruption_task_frame_and_wait()` callers. - **Uninterruptible Frames**: These are frames that will not be removed from internal queues even if there's an interruption. For example, `EndFrame` and `StopFrame`. From 5b67e76de7711d2bc7d1d5e5634a019b12f3d86c Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Aleix=20Conchillo=20Flaqu=C3=A9?= Date: Thu, 5 Feb 2026 22:17:31 -0800 Subject: [PATCH 0382/1060] Add changelog for PR #3660 --- changelog/3660.changed.md | 1 + 1 file changed, 1 insertion(+) create mode 100644 changelog/3660.changed.md diff --git a/changelog/3660.changed.md b/changelog/3660.changed.md new file mode 100644 index 000000000..e5077b73b --- /dev/null +++ b/changelog/3660.changed.md @@ -0,0 +1 @@ +- Moved interruption wait event from per-processor instance state to `InterruptionFrame` itself. Added `InterruptionFrame.complete()` to signal when the interruption has fully traversed the pipeline. Custom processors that block or consume an `InterruptionFrame` before it reaches the pipeline sink must call `frame.complete()` to avoid stalling `push_interruption_task_frame_and_wait()`. A warning is logged if completion does not happen within 2 seconds. From 7f65204c3b017cb6e5ae09582dc6763ac1534840 Mon Sep 17 00:00:00 2001 From: Mark Backman Date: Fri, 6 Feb 2026 13:42:42 -0500 Subject: [PATCH 0383/1060] DeepgramSTTService: disable smart_format by default --- changelog/3666.changed.md | 1 + src/pipecat/services/deepgram/stt.py | 2 +- 2 files changed, 2 insertions(+), 1 deletion(-) create mode 100644 changelog/3666.changed.md diff --git a/changelog/3666.changed.md b/changelog/3666.changed.md new file mode 100644 index 000000000..0fbdbc59c --- /dev/null +++ b/changelog/3666.changed.md @@ -0,0 +1 @@ +- Changed the `DeepgramSTTService` default setting for `smart_format` to `False`, as agents don't need smart formatting. Disabling this setting provides a small performance improvement, as well. \ No newline at end of file diff --git a/src/pipecat/services/deepgram/stt.py b/src/pipecat/services/deepgram/stt.py index 20dfba724..0c326deb3 100644 --- a/src/pipecat/services/deepgram/stt.py +++ b/src/pipecat/services/deepgram/stt.py @@ -106,7 +106,7 @@ class DeepgramSTTService(STTService): model="nova-3-general", channels=1, interim_results=True, - smart_format=True, + smart_format=False, punctuate=True, profanity_filter=True, vad_events=False, From 4945cfbd8fe34d16efe324c12cbc9852756da77b Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Aleix=20Conchillo=20Flaqu=C3=A9?= Date: Fri, 6 Feb 2026 15:12:48 -0800 Subject: [PATCH 0384/1060] Buffer internal frames during ParallelPipeline lifecycle synchronization Processors inside parallel sub-pipelines can push frames during StartFrame/EndFrame/CancelFrame processing. Previously these frames could escape the ParallelPipeline before all branches finished processing the lifecycle frame. Now they are buffered and flushed after synchronization completes. --- changelog/3668.fixed.md | 1 + src/pipecat/pipeline/parallel_pipeline.py | 24 +++++++++++++++++-- tests/test_pipeline.py | 28 +++++++++++++++++++++++ 3 files changed, 51 insertions(+), 2 deletions(-) create mode 100644 changelog/3668.fixed.md diff --git a/changelog/3668.fixed.md b/changelog/3668.fixed.md new file mode 100644 index 000000000..6885a7591 --- /dev/null +++ b/changelog/3668.fixed.md @@ -0,0 +1 @@ +- Fixed `ParallelPipeline` allowing frames pushed by internal processors to escape during lifecycle frame (`StartFrame`/`EndFrame`/`CancelFrame`) synchronization. These frames are now buffered and flushed after all branches complete. diff --git a/src/pipecat/pipeline/parallel_pipeline.py b/src/pipecat/pipeline/parallel_pipeline.py index 81beeead8..88ea04638 100644 --- a/src/pipecat/pipeline/parallel_pipeline.py +++ b/src/pipecat/pipeline/parallel_pipeline.py @@ -52,6 +52,8 @@ class ParallelPipeline(BasePipeline): self._seen_ids = set() self._frame_counter: Dict[int, int] = {} + self._synchronizing: bool = False + self._buffered_frames: list[tuple[Frame, FrameDirection]] = [] logger.debug(f"Creating {self} pipelines") @@ -143,6 +145,7 @@ class ParallelPipeline(BasePipeline): # Parallel pipeline synchronized frames. if isinstance(frame, (StartFrame, EndFrame, CancelFrame)): self._frame_counter[frame.id] = len(self._pipelines) + self._synchronizing = True await self.pause_processing_system_frames() await self.pause_processing_frames() @@ -151,10 +154,18 @@ class ParallelPipeline(BasePipeline): await p.queue_frame(frame, direction) async def _parallel_push_frame(self, frame: Frame, direction: FrameDirection): - """Push frames while avoiding duplicates using frame ID tracking.""" + """Push frames while avoiding duplicates using frame ID tracking. + + During lifecycle frame synchronization, non-lifecycle frames are buffered + to prevent them from escaping the parallel pipeline before all branches + have finished processing the lifecycle frame. + """ if frame.id not in self._seen_ids: self._seen_ids.add(frame.id) - await self.push_frame(frame, direction) + if self._synchronizing: + self._buffered_frames.append((frame, direction)) + else: + await self.push_frame(frame, direction) async def _pipeline_sink_push_frame(self, frame: Frame, direction: FrameDirection): # Parallel pipeline synchronized frames. @@ -167,8 +178,17 @@ class ParallelPipeline(BasePipeline): # Only push the frame when all pipelines have processed it. if frame_counter == 0: + self._synchronizing = False await self._parallel_push_frame(frame, direction) + await self._flush_buffered_frames() await self.resume_processing_system_frames() await self.resume_processing_frames() else: await self._parallel_push_frame(frame, direction) + + async def _flush_buffered_frames(self): + """Flush frames that were buffered during lifecycle frame synchronization.""" + frames = self._buffered_frames + self._buffered_frames = [] + for frame, direction in frames: + await self.push_frame(frame, direction) diff --git a/tests/test_pipeline.py b/tests/test_pipeline.py index dda9e583d..71121a3fc 100644 --- a/tests/test_pipeline.py +++ b/tests/test_pipeline.py @@ -96,6 +96,34 @@ class TestParallelPipeline(unittest.IsolatedAsyncioTestCase): expected_down_frames=expected_down_frames, ) + async def test_parallel_internal_frames_buffered_during_start(self): + """Frames pushed by internal processors during StartFrame processing + should be buffered and only released after StartFrame synchronization + completes.""" + + class EmitOnStartProcessor(FrameProcessor): + """Pushes a TextFrame when it receives a StartFrame.""" + + async def process_frame(self, frame: Frame, direction: FrameDirection): + await super().process_frame(frame, direction) + await self.push_frame(frame, direction) + if isinstance(frame, StartFrame): + await self.push_frame(TextFrame(text="from start")) + + pipeline = ParallelPipeline([EmitOnStartProcessor()], [IdentityFilter()]) + + frames_to_send = [TextFrame(text="Hello!")] + + # StartFrame should come first, then the TextFrame emitted during + # StartFrame processing, then the regular TextFrame. + expected_down_frames = [StartFrame, TextFrame, TextFrame] + await run_test( + pipeline, + frames_to_send=frames_to_send, + expected_down_frames=expected_down_frames, + ignore_start=False, + ) + class TestPipelineTask(unittest.IsolatedAsyncioTestCase): async def test_task_single(self): From 57df03aade6e050a9984d3a541bd9af8119e74d1 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Aleix=20Conchillo=20Flaqu=C3=A9?= Date: Fri, 6 Feb 2026 15:12:53 -0800 Subject: [PATCH 0385/1060] Update CLAUDE.md with PR workflow instructions --- CLAUDE.md | 26 ++++++++------------------ 1 file changed, 8 insertions(+), 18 deletions(-) diff --git a/CLAUDE.md b/CLAUDE.md index 162615ab2..d7ef2619c 100644 --- a/CLAUDE.md +++ b/CLAUDE.md @@ -27,6 +27,10 @@ uv run pytest tests/test_name.py::test_function_name # Preview changelog towncrier build --draft --version Unreleased +# Lint and format check +uv run ruff check +uv run ruff format --check + # Update dependencies (after editing pyproject.toml) uv lock && uv sync ``` @@ -122,24 +126,6 @@ class MyService(LLMService): super().__init__(**kwargs) ``` -## Changelog - -Every user-facing PR needs a changelog fragment in `changelog/`: - -``` -changelog/..md -``` - -Types: `added`, `changed`, `deprecated`, `removed`, `fixed`, `security`, `other` - -Content format (include the `-`): - -```markdown -- Added support for new feature X. -``` - -Skip changelog for: documentation-only, internal refactoring, test-only, CI changes. - ## Service Implementation When adding a new service: @@ -151,3 +137,7 @@ When adding a new service: 5. Push `ErrorFrame` on failures 6. Add metrics tracking via `MetricsData` if relevant 7. Follow the pattern of existing services in `src/pipecat/services/` + +## Pull Requests + +After creating a PR, use `/changelog ` to generate the changelog file and `/pr-description ` to update the PR description. From cd03d449cb9cfb48592cdfef9c77efa73fdb15bf Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Aleix=20Conchillo=20Flaqu=C3=A9?= Date: Fri, 6 Feb 2026 15:12:58 -0800 Subject: [PATCH 0386/1060] Update changelog skill with skip rules and allowed types --- .claude/skills/changelog/SKILL.md | 19 +++++++++++++------ 1 file changed, 13 insertions(+), 6 deletions(-) diff --git a/.claude/skills/changelog/SKILL.md b/.claude/skills/changelog/SKILL.md index 0feb6b92c..89e13a40e 100644 --- a/.claude/skills/changelog/SKILL.md +++ b/.claude/skills/changelog/SKILL.md @@ -7,23 +7,30 @@ Create changelog files for the important commits in this PR. The PR number is pr ## Instructions -1. First, check what commits are on the current branch compared to main: +1. Skip changelog for: documentation-only, internal refactoring, test-only, CI changes. + +2. First, check what commits are on the current branch compared to main: ``` git log main..HEAD --oneline ``` -2. For each significant change, create a changelog file in the `changelog/` folder using the format: +3. For each significant change, create a changelog file in the `changelog/` folder using the format: + Allowed types: `added`, `changed`, `deprecated`, `removed`, `fixed`, `security`, `performance`, `other` - `{PR_NUMBER}.added.md` - for new features - - `{PR_NUMBER}.added.2.md`, `{PR_NUMBER}.added.3.md` - for additional new features + - `{PR_NUMBER}.added.2.md`, `{PR_NUMBER}.added.3.md` - for additional entries of the same type - `{PR_NUMBER}.changed.md` - for changes to existing functionality - `{PR_NUMBER}.fixed.md` - for bug fixes - `{PR_NUMBER}.deprecated.md` - for deprecations + - `{PR_NUMBER}.removed.md` - for removed features + - `{PR_NUMBER}.security.md` - for security fixes + - `{PR_NUMBER}.performance.md` - for performance improvements + - `{PR_NUMBER}.other.md` - for other changes -3. Each changelog file should at least contain a main single line starting with `- ` followed by a clear description of the change. +4. Each changelog file should at least contain a main single line starting with `- ` followed by a clear description of the change. -4. If the change is complicated, changelog files can have indented lines after the main line with additional details or code samples. +5. If the change is complicated, changelog files can have indented lines after the main line with additional details or code samples. -5. Use ⚠️ emoji prefix for breaking changes. +6. Use ⚠️ emoji prefix for breaking changes. ## Example From 5cb8d914316f63ec7610137eb04267250a669cce Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Aleix=20Conchillo=20Flaqu=C3=A9?= Date: Fri, 6 Feb 2026 16:45:23 -0800 Subject: [PATCH 0387/1060] added changelog file for #3616 --- changelog/3616.fixed.md | 1 + 1 file changed, 1 insertion(+) create mode 100644 changelog/3616.fixed.md diff --git a/changelog/3616.fixed.md b/changelog/3616.fixed.md new file mode 100644 index 000000000..392502161 --- /dev/null +++ b/changelog/3616.fixed.md @@ -0,0 +1 @@ +- Fixed function call timeout task not being cancelled when the handler completes without calling `result_callback` or is cancelled externally, which caused `RuntimeWarning: coroutine was never awaited`. From a5fc2b16501778ea5f837eae502b4c2d7d4cd751 Mon Sep 17 00:00:00 2001 From: Mark Backman Date: Thu, 5 Feb 2026 18:26:17 -0500 Subject: [PATCH 0388/1060] Set VADParams stop_secs to 0.2 by default --- changelog/{3593.change.md => 3593.changed.md} | 0 changelog/3659.changed.md | 10 ++++++++++ examples/foundational/04-transports-small-webrtc.py | 3 +-- examples/foundational/04a-transports-daily.py | 3 +-- examples/foundational/04b-transports-livekit.py | 3 +-- examples/foundational/06-listen-and-respond.py | 3 +-- examples/foundational/06a-image-sync.py | 3 +-- .../foundational/07-interruptible-cartesia-http.py | 3 +-- examples/foundational/07-interruptible.py | 3 +-- .../foundational/07a-interruptible-speechmatics.py | 3 +-- examples/foundational/07b-interruptible-langchain.py | 3 +-- .../foundational/07c-interruptible-deepgram-http.py | 3 +-- .../07c-interruptible-deepgram-sagemaker.py | 3 +-- examples/foundational/07c-interruptible-deepgram.py | 3 +-- .../foundational/07d-interruptible-elevenlabs-http.py | 3 +-- examples/foundational/07d-interruptible-elevenlabs.py | 3 +-- examples/foundational/07e-interruptible-playht-http.py | 3 +-- examples/foundational/07e-interruptible-playht.py | 3 +-- examples/foundational/07f-interruptible-azure-http.py | 3 +-- examples/foundational/07f-interruptible-azure.py | 3 +-- examples/foundational/07g-interruptible-openai.py | 3 +-- examples/foundational/07h-interruptible-openpipe.py | 3 +-- examples/foundational/07i-interruptible-xtts.py | 3 +-- examples/foundational/07j-interruptible-gladia-vad.py | 3 +-- examples/foundational/07j-interruptible-gladia.py | 3 +-- examples/foundational/07k-interruptible-lmnt.py | 3 +-- examples/foundational/07l-interruptible-groq.py | 3 +-- examples/foundational/07m-interruptible-aws-strands.py | 3 +-- examples/foundational/07m-interruptible-aws.py | 3 +-- .../foundational/07n-interruptible-gemini-image.py | 3 +-- examples/foundational/07n-interruptible-gemini.py | 3 +-- examples/foundational/07n-interruptible-google-http.py | 3 +-- examples/foundational/07n-interruptible-google.py | 3 +-- examples/foundational/07o-interruptible-assemblyai.py | 3 +-- examples/foundational/07p-interruptible-krisp-viva.py | 3 +-- examples/foundational/07p-interruptible-krisp.py | 3 +-- examples/foundational/07q-interruptible-rime-http.py | 3 +-- examples/foundational/07q-interruptible-rime.py | 3 +-- examples/foundational/07r-interruptible-nvidia.py | 3 +-- .../foundational/07s-interruptible-google-audio-in.py | 3 +-- examples/foundational/07t-interruptible-fish.py | 3 +-- .../foundational/07v-interruptible-neuphonic-http.py | 3 +-- examples/foundational/07v-interruptible-neuphonic.py | 3 +-- examples/foundational/07w-interruptible-fal.py | 3 +-- examples/foundational/07x-interruptible-local.py | 3 +-- examples/foundational/07y-interruptible-minimax.py | 3 +-- examples/foundational/07z-interruptible-sarvam-http.py | 3 +-- examples/foundational/07z-interruptible-sarvam.py | 3 +-- examples/foundational/07za-interruptible-soniox.py | 3 +-- .../foundational/07zb-interruptible-inworld-http.py | 3 +-- examples/foundational/07zb-interruptible-inworld.py | 3 +-- .../foundational/07zc-interruptible-asyncai-http.py | 3 +-- examples/foundational/07zc-interruptible-asyncai.py | 3 +-- examples/foundational/07ze-interruptible-hume.py | 3 +-- examples/foundational/07zf-interruptible-gradium.py | 3 +-- examples/foundational/07zg-interruptible-camb.py | 3 +-- examples/foundational/07zh-interruptible-hathora.py | 3 +-- examples/foundational/07zi-interruptible-piper.py | 3 +-- examples/foundational/07zj-interruptible-kokoro.py | 3 +-- examples/foundational/07zk-interruptible-resemble.py | 7 +++---- examples/foundational/08-custom-frame-processor.py | 3 +-- examples/foundational/10-wake-phrase.py | 3 +-- examples/foundational/11-sound-effects.py | 3 +-- examples/foundational/12-describe-image-openai.py | 3 +-- examples/foundational/12a-describe-image-anthropic.py | 3 +-- examples/foundational/12b-describe-image-aws.py | 3 +-- .../foundational/12c-describe-image-gemini-flash.py | 3 +-- examples/foundational/14-function-calling.py | 3 +-- .../foundational/14a-function-calling-anthropic.py | 3 +-- examples/foundational/14c-function-calling-together.py | 3 +-- .../14d-function-calling-anthropic-video.py | 3 +-- .../foundational/14d-function-calling-aws-video.py | 3 +-- .../14d-function-calling-gemini-flash-video.py | 3 +-- .../14d-function-calling-moondream-video.py | 3 +-- .../foundational/14d-function-calling-openai-video.py | 3 +-- examples/foundational/14e-function-calling-google.py | 3 +-- examples/foundational/14f-function-calling-groq.py | 3 +-- examples/foundational/14g-function-calling-grok.py | 3 +-- examples/foundational/14h-function-calling-azure.py | 3 +-- .../foundational/14i-function-calling-fireworks.py | 3 +-- examples/foundational/14j-function-calling-nvidia.py | 3 +-- examples/foundational/14k-function-calling-cerebras.py | 3 +-- examples/foundational/14l-function-calling-deepseek.py | 3 +-- .../foundational/14m-function-calling-openrouter.py | 3 +-- .../foundational/14n-function-calling-perplexity.py | 3 +-- .../14o-function-calling-gemini-openai-format.py | 7 +++---- .../14p-function-calling-gemini-vertex-ai.py | 3 +-- examples/foundational/14q-function-calling-qwen.py | 3 +-- examples/foundational/14r-function-calling-aws.py | 3 +-- .../foundational/14s-function-calling-sambanova.py | 3 +-- examples/foundational/14t-function-calling-direct.py | 3 +-- examples/foundational/14u-function-calling-ollama.py | 3 +-- examples/foundational/14v-function-calling-openai.py | 3 +-- examples/foundational/14w-function-calling-mistral.py | 3 +-- examples/foundational/14x-function-calling-openpipe.py | 3 +-- examples/foundational/15-switch-voices.py | 3 +-- examples/foundational/15a-switch-languages.py | 3 +-- examples/foundational/16-gpu-container-local-bot.py | 3 +-- examples/foundational/17-detect-user-idle.py | 3 +-- examples/foundational/20a-persistent-context-openai.py | 3 +-- .../foundational/20c-persistent-context-anthropic.py | 3 +-- examples/foundational/20d-persistent-context-gemini.py | 3 +-- examples/foundational/21-tavus-transport.py | 3 +-- examples/foundational/21a-tavus-video-service.py | 3 +-- examples/foundational/22-filter-incomplete-turns.py | 3 +-- examples/foundational/23-bot-background-sound.py | 7 +++---- examples/foundational/24-user-mute-strategy.py | 3 +-- examples/foundational/27-simli-layer.py | 3 +-- examples/foundational/28-user-assistant-turns.py | 3 +-- examples/foundational/29-turn-tracking-observer.py | 3 +-- examples/foundational/30-observer.py | 3 +-- examples/foundational/32-gemini-grounding-metadata.py | 3 +-- examples/foundational/33-gemini-rag.py | 3 +-- examples/foundational/34-audio-recording.py | 3 +-- .../foundational/35-pattern-pair-voice-switching.py | 3 +-- examples/foundational/36-user-email-gathering.py | 3 +-- examples/foundational/37-mem0.py | 3 +-- examples/foundational/38-smart-turn-fal.py | 3 +-- examples/foundational/38a-smart-turn-local-coreml.py | 3 +-- examples/foundational/38b-smart-turn-local.py | 3 +-- examples/foundational/39-mcp-stdio.py | 3 +-- examples/foundational/39a-mcp-streamable-http.py | 3 +-- .../39b-mcp-streamable-http-gemini-live.py | 3 +-- examples/foundational/39c-multiple-mcp.py | 3 +-- examples/foundational/42-interruption-config.py | 3 +-- examples/foundational/43-heygen-transport.py | 3 +-- examples/foundational/43a-heygen-video-service.py | 3 +-- examples/foundational/44-voicemail-detection.py | 3 +-- examples/foundational/45-before-and-after-events.py | 3 +-- examples/foundational/46-video-processing.py | 3 +-- examples/foundational/47-sentry-metrics.py | 3 +-- examples/foundational/48-service-switcher.py | 3 +-- examples/foundational/49a-thinking-anthropic.py | 3 +-- examples/foundational/49b-thinking-google.py | 3 +-- .../foundational/49c-thinking-functions-anthropic.py | 3 +-- examples/foundational/49d-thinking-functions-google.py | 3 +-- examples/foundational/52-live-translation.py | 3 +-- examples/foundational/53-concurrent-llm-evaluation.py | 3 +-- src/pipecat/audio/vad/vad_analyzer.py | 2 +- 139 files changed, 153 insertions(+), 279 deletions(-) rename changelog/{3593.change.md => 3593.changed.md} (100%) create mode 100644 changelog/3659.changed.md diff --git a/changelog/3593.change.md b/changelog/3593.changed.md similarity index 100% rename from changelog/3593.change.md rename to changelog/3593.changed.md diff --git a/changelog/3659.changed.md b/changelog/3659.changed.md new file mode 100644 index 000000000..583f45f82 --- /dev/null +++ b/changelog/3659.changed.md @@ -0,0 +1,10 @@ +- ⚠️ The default `VADParams` `stop_secs` default is changing from `0.8` seconds + to `0.2` seconds. This change both simplifies the developer experience and + improves the performance of STT services. With a shorter `stop_secs` value, + STT services using a local VAD can finalize sooner, resulting in faster + transcription. + + - `SpeechTimeoutUserTurnStopStrategy`: control how long to wait for + additional user speech using `user_speech_timeout` (default: 0.6 sec). + - `TurnAnalyzerUserTurnStopStrategy`: the turn analyzer automatically adjusts + the user wait time based on the audio input. \ No newline at end of file diff --git a/examples/foundational/04-transports-small-webrtc.py b/examples/foundational/04-transports-small-webrtc.py index 0ccff0229..83fa1861f 100644 --- a/examples/foundational/04-transports-small-webrtc.py +++ b/examples/foundational/04-transports-small-webrtc.py @@ -19,7 +19,6 @@ from pipecat_ai_small_webrtc_prebuilt.frontend import SmallWebRTCPrebuiltUI from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3 from pipecat.audio.vad.silero import SileroVADAnalyzer -from pipecat.audio.vad.vad_analyzer import VADParams from pipecat.frames.frames import LLMRunFrame from pipecat.pipeline.pipeline import Pipeline from pipecat.pipeline.runner import PipelineRunner @@ -90,7 +89,7 @@ async def run_example(webrtc_connection: SmallWebRTCConnection): user_turn_strategies=UserTurnStrategies( stop=[TurnAnalyzerUserTurnStopStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3())] ), - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), + vad_analyzer=SileroVADAnalyzer(), ), ) diff --git a/examples/foundational/04a-transports-daily.py b/examples/foundational/04a-transports-daily.py index 9a2a9288b..2608187a6 100644 --- a/examples/foundational/04a-transports-daily.py +++ b/examples/foundational/04a-transports-daily.py @@ -14,7 +14,6 @@ from loguru import logger from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3 from pipecat.audio.vad.silero import SileroVADAnalyzer -from pipecat.audio.vad.vad_analyzer import VADParams from pipecat.frames.frames import LLMRunFrame from pipecat.pipeline.pipeline import Pipeline from pipecat.pipeline.runner import PipelineRunner @@ -75,7 +74,7 @@ async def main(): TurnAnalyzerUserTurnStopStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3()) ] ), - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), + vad_analyzer=SileroVADAnalyzer(), ), ) diff --git a/examples/foundational/04b-transports-livekit.py b/examples/foundational/04b-transports-livekit.py index 8f100e720..05141acde 100644 --- a/examples/foundational/04b-transports-livekit.py +++ b/examples/foundational/04b-transports-livekit.py @@ -14,7 +14,6 @@ from loguru import logger from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3 from pipecat.audio.vad.silero import SileroVADAnalyzer -from pipecat.audio.vad.vad_analyzer import VADParams from pipecat.frames.frames import ( InterruptionFrame, TranscriptionFrame, @@ -83,7 +82,7 @@ async def main(): user_turn_strategies=UserTurnStrategies( stop=[TurnAnalyzerUserTurnStopStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3())] ), - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), + vad_analyzer=SileroVADAnalyzer(), ), ) diff --git a/examples/foundational/06-listen-and-respond.py b/examples/foundational/06-listen-and-respond.py index b23e85766..4fe7045c6 100644 --- a/examples/foundational/06-listen-and-respond.py +++ b/examples/foundational/06-listen-and-respond.py @@ -11,7 +11,6 @@ from loguru import logger from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3 from pipecat.audio.vad.silero import SileroVADAnalyzer -from pipecat.audio.vad.vad_analyzer import VADParams from pipecat.frames.frames import Frame, LLMRunFrame, MetricsFrame from pipecat.metrics.metrics import ( LLMUsageMetricsData, @@ -108,7 +107,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): user_turn_strategies=UserTurnStrategies( stop=[TurnAnalyzerUserTurnStopStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3())] ), - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), + vad_analyzer=SileroVADAnalyzer(), ), ) diff --git a/examples/foundational/06a-image-sync.py b/examples/foundational/06a-image-sync.py index 8ff1a6069..a2f0ff4a5 100644 --- a/examples/foundational/06a-image-sync.py +++ b/examples/foundational/06a-image-sync.py @@ -12,7 +12,6 @@ from PIL import Image from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3 from pipecat.audio.vad.silero import SileroVADAnalyzer -from pipecat.audio.vad.vad_analyzer import VADParams from pipecat.frames.frames import ( BotStartedSpeakingFrame, BotStoppedSpeakingFrame, @@ -123,7 +122,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): user_turn_strategies=UserTurnStrategies( stop=[TurnAnalyzerUserTurnStopStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3())] ), - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), + vad_analyzer=SileroVADAnalyzer(), ), ) diff --git a/examples/foundational/07-interruptible-cartesia-http.py b/examples/foundational/07-interruptible-cartesia-http.py index b5a7eb026..6cf9f3deb 100644 --- a/examples/foundational/07-interruptible-cartesia-http.py +++ b/examples/foundational/07-interruptible-cartesia-http.py @@ -11,7 +11,6 @@ from loguru import logger from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3 from pipecat.audio.vad.silero import SileroVADAnalyzer -from pipecat.audio.vad.vad_analyzer import VADParams from pipecat.frames.frames import LLMRunFrame from pipecat.pipeline.pipeline import Pipeline from pipecat.pipeline.runner import PipelineRunner @@ -79,7 +78,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): user_turn_strategies=UserTurnStrategies( stop=[TurnAnalyzerUserTurnStopStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3())] ), - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), + vad_analyzer=SileroVADAnalyzer(), ), ) diff --git a/examples/foundational/07-interruptible.py b/examples/foundational/07-interruptible.py index a016bdeaf..57588c567 100644 --- a/examples/foundational/07-interruptible.py +++ b/examples/foundational/07-interruptible.py @@ -11,7 +11,6 @@ from loguru import logger from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3 from pipecat.audio.vad.silero import SileroVADAnalyzer -from pipecat.audio.vad.vad_analyzer import VADParams from pipecat.frames.frames import LLMRunFrame from pipecat.pipeline.pipeline import Pipeline from pipecat.pipeline.runner import PipelineRunner @@ -78,7 +77,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): user_turn_strategies=UserTurnStrategies( stop=[TurnAnalyzerUserTurnStopStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3())] ), - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), + vad_analyzer=SileroVADAnalyzer(), ), ) diff --git a/examples/foundational/07a-interruptible-speechmatics.py b/examples/foundational/07a-interruptible-speechmatics.py index ebca5caf6..2df8dd39b 100644 --- a/examples/foundational/07a-interruptible-speechmatics.py +++ b/examples/foundational/07a-interruptible-speechmatics.py @@ -12,7 +12,6 @@ from loguru import logger from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3 from pipecat.audio.vad.silero import SileroVADAnalyzer -from pipecat.audio.vad.vad_analyzer import VADParams from pipecat.frames.frames import LLMRunFrame from pipecat.pipeline.pipeline import Pipeline from pipecat.pipeline.runner import PipelineRunner @@ -121,7 +120,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): TurnAnalyzerUserTurnStopStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3()) ] ), - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), + vad_analyzer=SileroVADAnalyzer(), ), ) diff --git a/examples/foundational/07b-interruptible-langchain.py b/examples/foundational/07b-interruptible-langchain.py index af1f3082a..911193276 100644 --- a/examples/foundational/07b-interruptible-langchain.py +++ b/examples/foundational/07b-interruptible-langchain.py @@ -17,7 +17,6 @@ from loguru import logger from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3 from pipecat.audio.vad.silero import SileroVADAnalyzer -from pipecat.audio.vad.vad_analyzer import VADParams from pipecat.frames.frames import LLMMessagesUpdateFrame from pipecat.pipeline.pipeline import Pipeline from pipecat.pipeline.runner import PipelineRunner @@ -105,7 +104,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): user_turn_strategies=UserTurnStrategies( stop=[TurnAnalyzerUserTurnStopStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3())] ), - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), + vad_analyzer=SileroVADAnalyzer(), ), ) diff --git a/examples/foundational/07c-interruptible-deepgram-http.py b/examples/foundational/07c-interruptible-deepgram-http.py index fe2d5c5d8..ffe1f9f60 100644 --- a/examples/foundational/07c-interruptible-deepgram-http.py +++ b/examples/foundational/07c-interruptible-deepgram-http.py @@ -13,7 +13,6 @@ from loguru import logger from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3 from pipecat.audio.vad.silero import SileroVADAnalyzer -from pipecat.audio.vad.vad_analyzer import VADParams from pipecat.frames.frames import LLMRunFrame from pipecat.pipeline.pipeline import Pipeline from pipecat.pipeline.runner import PipelineRunner @@ -85,7 +84,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): TurnAnalyzerUserTurnStopStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3()) ] ), - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), + vad_analyzer=SileroVADAnalyzer(), ), ) diff --git a/examples/foundational/07c-interruptible-deepgram-sagemaker.py b/examples/foundational/07c-interruptible-deepgram-sagemaker.py index 20edf1693..05a822706 100644 --- a/examples/foundational/07c-interruptible-deepgram-sagemaker.py +++ b/examples/foundational/07c-interruptible-deepgram-sagemaker.py @@ -12,7 +12,6 @@ from loguru import logger from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3 from pipecat.audio.vad.silero import SileroVADAnalyzer -from pipecat.audio.vad.vad_analyzer import VADParams from pipecat.frames.frames import LLMRunFrame from pipecat.pipeline.pipeline import Pipeline from pipecat.pipeline.runner import PipelineRunner @@ -88,7 +87,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): user_turn_strategies=UserTurnStrategies( stop=[TurnAnalyzerUserTurnStopStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3())] ), - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), + vad_analyzer=SileroVADAnalyzer(), ), ) diff --git a/examples/foundational/07c-interruptible-deepgram.py b/examples/foundational/07c-interruptible-deepgram.py index f4fa91485..f31166d13 100644 --- a/examples/foundational/07c-interruptible-deepgram.py +++ b/examples/foundational/07c-interruptible-deepgram.py @@ -12,7 +12,6 @@ from loguru import logger from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3 from pipecat.audio.vad.silero import SileroVADAnalyzer -from pipecat.audio.vad.vad_analyzer import VADParams from pipecat.frames.frames import LLMRunFrame from pipecat.pipeline.pipeline import Pipeline from pipecat.pipeline.runner import PipelineRunner @@ -77,7 +76,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): user_turn_strategies=UserTurnStrategies( stop=[TurnAnalyzerUserTurnStopStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3())] ), - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), + vad_analyzer=SileroVADAnalyzer(), ), ) diff --git a/examples/foundational/07d-interruptible-elevenlabs-http.py b/examples/foundational/07d-interruptible-elevenlabs-http.py index 612527e8d..b48a40641 100644 --- a/examples/foundational/07d-interruptible-elevenlabs-http.py +++ b/examples/foundational/07d-interruptible-elevenlabs-http.py @@ -13,7 +13,6 @@ from loguru import logger from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3 from pipecat.audio.vad.silero import SileroVADAnalyzer -from pipecat.audio.vad.vad_analyzer import VADParams from pipecat.frames.frames import LLMRunFrame from pipecat.pipeline.pipeline import Pipeline from pipecat.pipeline.runner import PipelineRunner @@ -89,7 +88,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): TurnAnalyzerUserTurnStopStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3()) ] ), - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), + vad_analyzer=SileroVADAnalyzer(), ), ) diff --git a/examples/foundational/07d-interruptible-elevenlabs.py b/examples/foundational/07d-interruptible-elevenlabs.py index 103d94d48..0bcb55c48 100644 --- a/examples/foundational/07d-interruptible-elevenlabs.py +++ b/examples/foundational/07d-interruptible-elevenlabs.py @@ -12,7 +12,6 @@ from loguru import logger from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3 from pipecat.audio.vad.silero import SileroVADAnalyzer -from pipecat.audio.vad.vad_analyzer import VADParams from pipecat.frames.frames import LLMRunFrame from pipecat.pipeline.pipeline import Pipeline from pipecat.pipeline.runner import PipelineRunner @@ -80,7 +79,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): user_turn_strategies=UserTurnStrategies( stop=[TurnAnalyzerUserTurnStopStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3())] ), - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), + vad_analyzer=SileroVADAnalyzer(), ), ) diff --git a/examples/foundational/07e-interruptible-playht-http.py b/examples/foundational/07e-interruptible-playht-http.py index c982e45fd..67c5e2c0c 100644 --- a/examples/foundational/07e-interruptible-playht-http.py +++ b/examples/foundational/07e-interruptible-playht-http.py @@ -12,7 +12,6 @@ from loguru import logger from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3 from pipecat.audio.vad.silero import SileroVADAnalyzer -from pipecat.audio.vad.vad_analyzer import VADParams from pipecat.frames.frames import LLMRunFrame from pipecat.pipeline.pipeline import Pipeline from pipecat.pipeline.runner import PipelineRunner @@ -80,7 +79,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): user_turn_strategies=UserTurnStrategies( stop=[TurnAnalyzerUserTurnStopStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3())] ), - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), + vad_analyzer=SileroVADAnalyzer(), ), ) diff --git a/examples/foundational/07e-interruptible-playht.py b/examples/foundational/07e-interruptible-playht.py index fe3ee0349..4c4f42d79 100644 --- a/examples/foundational/07e-interruptible-playht.py +++ b/examples/foundational/07e-interruptible-playht.py @@ -12,7 +12,6 @@ from loguru import logger from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3 from pipecat.audio.vad.silero import SileroVADAnalyzer -from pipecat.audio.vad.vad_analyzer import VADParams from pipecat.frames.frames import LLMRunFrame from pipecat.pipeline.pipeline import Pipeline from pipecat.pipeline.runner import PipelineRunner @@ -82,7 +81,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): user_turn_strategies=UserTurnStrategies( stop=[TurnAnalyzerUserTurnStopStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3())] ), - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), + vad_analyzer=SileroVADAnalyzer(), ), ) diff --git a/examples/foundational/07f-interruptible-azure-http.py b/examples/foundational/07f-interruptible-azure-http.py index daec3166d..81e505f52 100644 --- a/examples/foundational/07f-interruptible-azure-http.py +++ b/examples/foundational/07f-interruptible-azure-http.py @@ -12,7 +12,6 @@ from loguru import logger from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3 from pipecat.audio.vad.silero import SileroVADAnalyzer -from pipecat.audio.vad.vad_analyzer import VADParams from pipecat.frames.frames import LLMRunFrame from pipecat.pipeline.pipeline import Pipeline from pipecat.pipeline.runner import PipelineRunner @@ -86,7 +85,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): user_turn_strategies=UserTurnStrategies( stop=[TurnAnalyzerUserTurnStopStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3())] ), - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), + vad_analyzer=SileroVADAnalyzer(), ), ) diff --git a/examples/foundational/07f-interruptible-azure.py b/examples/foundational/07f-interruptible-azure.py index b1ea08ee4..5a1cdd693 100644 --- a/examples/foundational/07f-interruptible-azure.py +++ b/examples/foundational/07f-interruptible-azure.py @@ -12,7 +12,6 @@ from loguru import logger from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3 from pipecat.audio.vad.silero import SileroVADAnalyzer -from pipecat.audio.vad.vad_analyzer import VADParams from pipecat.frames.frames import LLMRunFrame from pipecat.pipeline.pipeline import Pipeline from pipecat.pipeline.runner import PipelineRunner @@ -86,7 +85,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): user_turn_strategies=UserTurnStrategies( stop=[TurnAnalyzerUserTurnStopStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3())] ), - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), + vad_analyzer=SileroVADAnalyzer(), ), ) diff --git a/examples/foundational/07g-interruptible-openai.py b/examples/foundational/07g-interruptible-openai.py index f2b38c8cf..1f08f3868 100644 --- a/examples/foundational/07g-interruptible-openai.py +++ b/examples/foundational/07g-interruptible-openai.py @@ -12,7 +12,6 @@ from loguru import logger from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3 from pipecat.audio.vad.silero import SileroVADAnalyzer -from pipecat.audio.vad.vad_analyzer import VADParams from pipecat.frames.frames import LLMRunFrame from pipecat.pipeline.pipeline import Pipeline from pipecat.pipeline.runner import PipelineRunner @@ -80,7 +79,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): user_turn_strategies=UserTurnStrategies( stop=[TurnAnalyzerUserTurnStopStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3())] ), - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), + vad_analyzer=SileroVADAnalyzer(), ), ) diff --git a/examples/foundational/07h-interruptible-openpipe.py b/examples/foundational/07h-interruptible-openpipe.py index c038800bf..03dcd4e46 100644 --- a/examples/foundational/07h-interruptible-openpipe.py +++ b/examples/foundational/07h-interruptible-openpipe.py @@ -13,7 +13,6 @@ from loguru import logger from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3 from pipecat.audio.vad.silero import SileroVADAnalyzer -from pipecat.audio.vad.vad_analyzer import VADParams from pipecat.frames.frames import LLMRunFrame from pipecat.pipeline.pipeline import Pipeline from pipecat.pipeline.runner import PipelineRunner @@ -85,7 +84,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): user_turn_strategies=UserTurnStrategies( stop=[TurnAnalyzerUserTurnStopStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3())] ), - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), + vad_analyzer=SileroVADAnalyzer(), ), ) diff --git a/examples/foundational/07i-interruptible-xtts.py b/examples/foundational/07i-interruptible-xtts.py index 427fab46c..e8ee3a76f 100644 --- a/examples/foundational/07i-interruptible-xtts.py +++ b/examples/foundational/07i-interruptible-xtts.py @@ -13,7 +13,6 @@ from loguru import logger from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3 from pipecat.audio.vad.silero import SileroVADAnalyzer -from pipecat.audio.vad.vad_analyzer import VADParams from pipecat.frames.frames import LLMRunFrame from pipecat.pipeline.pipeline import Pipeline from pipecat.pipeline.runner import PipelineRunner @@ -85,7 +84,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): TurnAnalyzerUserTurnStopStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3()) ] ), - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), + vad_analyzer=SileroVADAnalyzer(), ), ) diff --git a/examples/foundational/07j-interruptible-gladia-vad.py b/examples/foundational/07j-interruptible-gladia-vad.py index 77cc9e58f..f0874f0f3 100644 --- a/examples/foundational/07j-interruptible-gladia-vad.py +++ b/examples/foundational/07j-interruptible-gladia-vad.py @@ -11,7 +11,6 @@ from dotenv import load_dotenv from loguru import logger from pipecat.audio.vad.silero import SileroVADAnalyzer -from pipecat.audio.vad.vad_analyzer import VADParams from pipecat.frames.frames import LLMRunFrame from pipecat.pipeline.pipeline import Pipeline from pipecat.pipeline.runner import PipelineRunner @@ -86,7 +85,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): context, user_params=LLMUserAggregatorParams( user_turn_strategies=ExternalUserTurnStrategies(), - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), + vad_analyzer=SileroVADAnalyzer(), ), ) diff --git a/examples/foundational/07j-interruptible-gladia.py b/examples/foundational/07j-interruptible-gladia.py index ee29e11df..13d07a1a8 100644 --- a/examples/foundational/07j-interruptible-gladia.py +++ b/examples/foundational/07j-interruptible-gladia.py @@ -12,7 +12,6 @@ from loguru import logger from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3 from pipecat.audio.vad.silero import SileroVADAnalyzer -from pipecat.audio.vad.vad_analyzer import VADParams from pipecat.frames.frames import LLMRunFrame from pipecat.pipeline.pipeline import Pipeline from pipecat.pipeline.runner import PipelineRunner @@ -89,7 +88,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): user_turn_strategies=UserTurnStrategies( stop=[TurnAnalyzerUserTurnStopStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3())] ), - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), + vad_analyzer=SileroVADAnalyzer(), ), ) diff --git a/examples/foundational/07k-interruptible-lmnt.py b/examples/foundational/07k-interruptible-lmnt.py index 4f7547c1f..008531972 100644 --- a/examples/foundational/07k-interruptible-lmnt.py +++ b/examples/foundational/07k-interruptible-lmnt.py @@ -12,7 +12,6 @@ from loguru import logger from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3 from pipecat.audio.vad.silero import SileroVADAnalyzer -from pipecat.audio.vad.vad_analyzer import VADParams from pipecat.frames.frames import LLMRunFrame from pipecat.pipeline.pipeline import Pipeline from pipecat.pipeline.runner import PipelineRunner @@ -76,7 +75,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): user_turn_strategies=UserTurnStrategies( stop=[TurnAnalyzerUserTurnStopStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3())] ), - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), + vad_analyzer=SileroVADAnalyzer(), ), ) diff --git a/examples/foundational/07l-interruptible-groq.py b/examples/foundational/07l-interruptible-groq.py index a838766b2..cbf42f96f 100644 --- a/examples/foundational/07l-interruptible-groq.py +++ b/examples/foundational/07l-interruptible-groq.py @@ -12,7 +12,6 @@ from loguru import logger from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3 from pipecat.audio.vad.silero import SileroVADAnalyzer -from pipecat.audio.vad.vad_analyzer import VADParams from pipecat.frames.frames import LLMRunFrame from pipecat.pipeline.pipeline import Pipeline from pipecat.pipeline.runner import PipelineRunner @@ -78,7 +77,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): user_turn_strategies=UserTurnStrategies( stop=[TurnAnalyzerUserTurnStopStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3())] ), - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), + vad_analyzer=SileroVADAnalyzer(), ), ) diff --git a/examples/foundational/07m-interruptible-aws-strands.py b/examples/foundational/07m-interruptible-aws-strands.py index cc8167661..247f48645 100644 --- a/examples/foundational/07m-interruptible-aws-strands.py +++ b/examples/foundational/07m-interruptible-aws-strands.py @@ -10,7 +10,6 @@ from loguru import logger from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3 from pipecat.audio.vad.silero import SileroVADAnalyzer -from pipecat.audio.vad.vad_analyzer import VADParams from pipecat.frames.frames import LLMMessagesAppendFrame from pipecat.pipeline.pipeline import Pipeline from pipecat.pipeline.runner import PipelineRunner @@ -123,7 +122,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): user_turn_strategies=UserTurnStrategies( stop=[TurnAnalyzerUserTurnStopStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3())] ), - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), + vad_analyzer=SileroVADAnalyzer(), ), ) diff --git a/examples/foundational/07m-interruptible-aws.py b/examples/foundational/07m-interruptible-aws.py index c10a5f33d..5be842202 100644 --- a/examples/foundational/07m-interruptible-aws.py +++ b/examples/foundational/07m-interruptible-aws.py @@ -10,7 +10,6 @@ from loguru import logger from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3 from pipecat.audio.vad.silero import SileroVADAnalyzer -from pipecat.audio.vad.vad_analyzer import VADParams from pipecat.frames.frames import LLMRunFrame from pipecat.pipeline.pipeline import Pipeline from pipecat.pipeline.runner import PipelineRunner @@ -82,7 +81,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): user_turn_strategies=UserTurnStrategies( stop=[TurnAnalyzerUserTurnStopStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3())] ), - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), + vad_analyzer=SileroVADAnalyzer(), ), ) diff --git a/examples/foundational/07n-interruptible-gemini-image.py b/examples/foundational/07n-interruptible-gemini-image.py index 4ae497660..b412d8bf0 100644 --- a/examples/foundational/07n-interruptible-gemini-image.py +++ b/examples/foundational/07n-interruptible-gemini-image.py @@ -27,7 +27,6 @@ from loguru import logger from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3 from pipecat.audio.vad.silero import SileroVADAnalyzer -from pipecat.audio.vad.vad_analyzer import VADParams from pipecat.frames.frames import LLMRunFrame from pipecat.pipeline.pipeline import Pipeline from pipecat.pipeline.runner import PipelineRunner @@ -104,7 +103,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): user_turn_strategies=UserTurnStrategies( stop=[TurnAnalyzerUserTurnStopStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3())] ), - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), + vad_analyzer=SileroVADAnalyzer(), ), ) diff --git a/examples/foundational/07n-interruptible-gemini.py b/examples/foundational/07n-interruptible-gemini.py index 2539759c5..5323a0875 100644 --- a/examples/foundational/07n-interruptible-gemini.py +++ b/examples/foundational/07n-interruptible-gemini.py @@ -12,7 +12,6 @@ from loguru import logger from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3 from pipecat.audio.vad.silero import SileroVADAnalyzer -from pipecat.audio.vad.vad_analyzer import VADParams from pipecat.frames.frames import LLMRunFrame from pipecat.pipeline.pipeline import Pipeline from pipecat.pipeline.runner import PipelineRunner @@ -109,7 +108,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): user_turn_strategies=UserTurnStrategies( stop=[TurnAnalyzerUserTurnStopStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3())] ), - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), + vad_analyzer=SileroVADAnalyzer(), ), ) diff --git a/examples/foundational/07n-interruptible-google-http.py b/examples/foundational/07n-interruptible-google-http.py index 88bd56e79..ae5a1d3ba 100644 --- a/examples/foundational/07n-interruptible-google-http.py +++ b/examples/foundational/07n-interruptible-google-http.py @@ -12,7 +12,6 @@ from loguru import logger from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3 from pipecat.audio.vad.silero import SileroVADAnalyzer -from pipecat.audio.vad.vad_analyzer import VADParams from pipecat.frames.frames import LLMRunFrame from pipecat.pipeline.pipeline import Pipeline from pipecat.pipeline.runner import PipelineRunner @@ -92,7 +91,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): user_turn_strategies=UserTurnStrategies( stop=[TurnAnalyzerUserTurnStopStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3())] ), - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), + vad_analyzer=SileroVADAnalyzer(), ), ) diff --git a/examples/foundational/07n-interruptible-google.py b/examples/foundational/07n-interruptible-google.py index 8f1781ce5..4591db940 100644 --- a/examples/foundational/07n-interruptible-google.py +++ b/examples/foundational/07n-interruptible-google.py @@ -12,7 +12,6 @@ from loguru import logger from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3 from pipecat.audio.vad.silero import SileroVADAnalyzer -from pipecat.audio.vad.vad_analyzer import VADParams from pipecat.frames.frames import LLMRunFrame from pipecat.pipeline.pipeline import Pipeline from pipecat.pipeline.runner import PipelineRunner @@ -92,7 +91,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): user_turn_strategies=UserTurnStrategies( stop=[TurnAnalyzerUserTurnStopStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3())] ), - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), + vad_analyzer=SileroVADAnalyzer(), ), ) diff --git a/examples/foundational/07o-interruptible-assemblyai.py b/examples/foundational/07o-interruptible-assemblyai.py index 258825c50..fe48c93e4 100644 --- a/examples/foundational/07o-interruptible-assemblyai.py +++ b/examples/foundational/07o-interruptible-assemblyai.py @@ -12,7 +12,6 @@ from loguru import logger from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3 from pipecat.audio.vad.silero import SileroVADAnalyzer -from pipecat.audio.vad.vad_analyzer import VADParams from pipecat.frames.frames import LLMRunFrame from pipecat.pipeline.pipeline import Pipeline from pipecat.pipeline.runner import PipelineRunner @@ -82,7 +81,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): user_turn_strategies=UserTurnStrategies( stop=[TurnAnalyzerUserTurnStopStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3())] ), - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), + vad_analyzer=SileroVADAnalyzer(), ), ) diff --git a/examples/foundational/07p-interruptible-krisp-viva.py b/examples/foundational/07p-interruptible-krisp-viva.py index d502bdcc4..160514818 100644 --- a/examples/foundational/07p-interruptible-krisp-viva.py +++ b/examples/foundational/07p-interruptible-krisp-viva.py @@ -30,7 +30,6 @@ from loguru import logger from pipecat.audio.filters.krisp_viva_filter import KrispVivaFilter from pipecat.audio.turn.krisp_viva_turn import KrispVivaTurn from pipecat.audio.vad.silero import SileroVADAnalyzer -from pipecat.audio.vad.vad_analyzer import VADParams from pipecat.frames.frames import LLMRunFrame from pipecat.pipeline.pipeline import Pipeline from pipecat.pipeline.runner import PipelineRunner @@ -97,7 +96,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): user_turn_strategies=UserTurnStrategies( stop=[TurnAnalyzerUserTurnStopStrategy(turn_analyzer=KrispVivaTurn())] ), - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), + vad_analyzer=SileroVADAnalyzer(), ), ) diff --git a/examples/foundational/07p-interruptible-krisp.py b/examples/foundational/07p-interruptible-krisp.py index 02451ece4..5205b290b 100644 --- a/examples/foundational/07p-interruptible-krisp.py +++ b/examples/foundational/07p-interruptible-krisp.py @@ -13,7 +13,6 @@ from loguru import logger from pipecat.audio.filters.krisp_filter import KrispFilter from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3 from pipecat.audio.vad.silero import SileroVADAnalyzer -from pipecat.audio.vad.vad_analyzer import VADParams from pipecat.frames.frames import LLMRunFrame from pipecat.pipeline.pipeline import Pipeline from pipecat.pipeline.runner import PipelineRunner @@ -80,7 +79,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): user_turn_strategies=UserTurnStrategies( stop=[TurnAnalyzerUserTurnStopStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3())] ), - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), + vad_analyzer=SileroVADAnalyzer(), ), ) diff --git a/examples/foundational/07q-interruptible-rime-http.py b/examples/foundational/07q-interruptible-rime-http.py index bfceb1bb3..9bece02fb 100644 --- a/examples/foundational/07q-interruptible-rime-http.py +++ b/examples/foundational/07q-interruptible-rime-http.py @@ -13,7 +13,6 @@ from loguru import logger from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3 from pipecat.audio.vad.silero import SileroVADAnalyzer -from pipecat.audio.vad.vad_analyzer import VADParams from pipecat.frames.frames import LLMRunFrame from pipecat.pipeline.pipeline import Pipeline from pipecat.pipeline.runner import PipelineRunner @@ -87,7 +86,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): TurnAnalyzerUserTurnStopStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3()) ] ), - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), + vad_analyzer=SileroVADAnalyzer(), ), ) diff --git a/examples/foundational/07q-interruptible-rime.py b/examples/foundational/07q-interruptible-rime.py index 5113b2c3c..2692872ce 100644 --- a/examples/foundational/07q-interruptible-rime.py +++ b/examples/foundational/07q-interruptible-rime.py @@ -12,7 +12,6 @@ from loguru import logger from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3 from pipecat.audio.vad.silero import SileroVADAnalyzer -from pipecat.audio.vad.vad_analyzer import VADParams from pipecat.frames.frames import LLMRunFrame from pipecat.pipeline.pipeline import Pipeline from pipecat.pipeline.runner import PipelineRunner @@ -79,7 +78,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): user_turn_strategies=UserTurnStrategies( stop=[TurnAnalyzerUserTurnStopStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3())] ), - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), + vad_analyzer=SileroVADAnalyzer(), ), ) diff --git a/examples/foundational/07r-interruptible-nvidia.py b/examples/foundational/07r-interruptible-nvidia.py index dda75256d..1702c59dd 100644 --- a/examples/foundational/07r-interruptible-nvidia.py +++ b/examples/foundational/07r-interruptible-nvidia.py @@ -12,7 +12,6 @@ from loguru import logger from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3 from pipecat.audio.vad.silero import SileroVADAnalyzer -from pipecat.audio.vad.vad_analyzer import VADParams from pipecat.frames.frames import LLMRunFrame from pipecat.pipeline.pipeline import Pipeline from pipecat.pipeline.runner import PipelineRunner @@ -78,7 +77,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): user_turn_strategies=UserTurnStrategies( stop=[TurnAnalyzerUserTurnStopStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3())] ), - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), + vad_analyzer=SileroVADAnalyzer(), ), ) diff --git a/examples/foundational/07s-interruptible-google-audio-in.py b/examples/foundational/07s-interruptible-google-audio-in.py index 54c0da1b9..7d8d5afce 100644 --- a/examples/foundational/07s-interruptible-google-audio-in.py +++ b/examples/foundational/07s-interruptible-google-audio-in.py @@ -14,7 +14,6 @@ from loguru import logger from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3 from pipecat.audio.vad.silero import SileroVADAnalyzer -from pipecat.audio.vad.vad_analyzer import VADParams from pipecat.frames.frames import ( Frame, InputAudioRawFrame, @@ -251,7 +250,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): user_turn_strategies=UserTurnStrategies( stop=[TurnAnalyzerUserTurnStopStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3())] ), - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), + vad_analyzer=SileroVADAnalyzer(), ), ) audio_collector = UserAudioCollector(context, user_aggregator) diff --git a/examples/foundational/07t-interruptible-fish.py b/examples/foundational/07t-interruptible-fish.py index 5a7c368f1..c059771eb 100644 --- a/examples/foundational/07t-interruptible-fish.py +++ b/examples/foundational/07t-interruptible-fish.py @@ -12,7 +12,6 @@ from loguru import logger from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3 from pipecat.audio.vad.silero import SileroVADAnalyzer -from pipecat.audio.vad.vad_analyzer import VADParams from pipecat.frames.frames import LLMRunFrame from pipecat.pipeline.pipeline import Pipeline from pipecat.pipeline.runner import PipelineRunner @@ -80,7 +79,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): user_turn_strategies=UserTurnStrategies( stop=[TurnAnalyzerUserTurnStopStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3())] ), - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), + vad_analyzer=SileroVADAnalyzer(), ), ) diff --git a/examples/foundational/07v-interruptible-neuphonic-http.py b/examples/foundational/07v-interruptible-neuphonic-http.py index 3c82608bc..e115c8f06 100644 --- a/examples/foundational/07v-interruptible-neuphonic-http.py +++ b/examples/foundational/07v-interruptible-neuphonic-http.py @@ -13,7 +13,6 @@ from loguru import logger from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3 from pipecat.audio.vad.silero import SileroVADAnalyzer -from pipecat.audio.vad.vad_analyzer import VADParams from pipecat.frames.frames import LLMRunFrame from pipecat.pipeline.pipeline import Pipeline from pipecat.pipeline.runner import PipelineRunner @@ -86,7 +85,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): TurnAnalyzerUserTurnStopStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3()) ] ), - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), + vad_analyzer=SileroVADAnalyzer(), ), ) diff --git a/examples/foundational/07v-interruptible-neuphonic.py b/examples/foundational/07v-interruptible-neuphonic.py index fd0c3361c..f4f3d3a3a 100644 --- a/examples/foundational/07v-interruptible-neuphonic.py +++ b/examples/foundational/07v-interruptible-neuphonic.py @@ -12,7 +12,6 @@ from loguru import logger from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3 from pipecat.audio.vad.silero import SileroVADAnalyzer -from pipecat.audio.vad.vad_analyzer import VADParams from pipecat.frames.frames import LLMRunFrame from pipecat.pipeline.pipeline import Pipeline from pipecat.pipeline.runner import PipelineRunner @@ -79,7 +78,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): user_turn_strategies=UserTurnStrategies( stop=[TurnAnalyzerUserTurnStopStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3())] ), - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), + vad_analyzer=SileroVADAnalyzer(), ), ) diff --git a/examples/foundational/07w-interruptible-fal.py b/examples/foundational/07w-interruptible-fal.py index b6dda13a9..cddf9bb5a 100644 --- a/examples/foundational/07w-interruptible-fal.py +++ b/examples/foundational/07w-interruptible-fal.py @@ -12,7 +12,6 @@ from loguru import logger from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3 from pipecat.audio.vad.silero import SileroVADAnalyzer -from pipecat.audio.vad.vad_analyzer import VADParams from pipecat.frames.frames import LLMRunFrame from pipecat.pipeline.pipeline import Pipeline from pipecat.pipeline.runner import PipelineRunner @@ -82,7 +81,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): user_turn_strategies=UserTurnStrategies( stop=[TurnAnalyzerUserTurnStopStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3())] ), - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), + vad_analyzer=SileroVADAnalyzer(), ), ) diff --git a/examples/foundational/07x-interruptible-local.py b/examples/foundational/07x-interruptible-local.py index aeb1b1f32..a5a3bcda3 100644 --- a/examples/foundational/07x-interruptible-local.py +++ b/examples/foundational/07x-interruptible-local.py @@ -13,7 +13,6 @@ from loguru import logger from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3 from pipecat.audio.vad.silero import SileroVADAnalyzer -from pipecat.audio.vad.vad_analyzer import VADParams from pipecat.frames.frames import LLMRunFrame from pipecat.pipeline.pipeline import Pipeline from pipecat.pipeline.runner import PipelineRunner @@ -67,7 +66,7 @@ async def main(): user_turn_strategies=UserTurnStrategies( stop=[TurnAnalyzerUserTurnStopStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3())] ), - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), + vad_analyzer=SileroVADAnalyzer(), ), ) diff --git a/examples/foundational/07y-interruptible-minimax.py b/examples/foundational/07y-interruptible-minimax.py index 1bd8f716f..a0e325956 100644 --- a/examples/foundational/07y-interruptible-minimax.py +++ b/examples/foundational/07y-interruptible-minimax.py @@ -13,7 +13,6 @@ from loguru import logger from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3 from pipecat.audio.vad.silero import SileroVADAnalyzer -from pipecat.audio.vad.vad_analyzer import VADParams from pipecat.frames.frames import LLMRunFrame from pipecat.pipeline.pipeline import Pipeline from pipecat.pipeline.runner import PipelineRunner @@ -88,7 +87,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): TurnAnalyzerUserTurnStopStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3()) ] ), - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), + vad_analyzer=SileroVADAnalyzer(), ), ) diff --git a/examples/foundational/07z-interruptible-sarvam-http.py b/examples/foundational/07z-interruptible-sarvam-http.py index a5b656b1a..ff2b636b8 100644 --- a/examples/foundational/07z-interruptible-sarvam-http.py +++ b/examples/foundational/07z-interruptible-sarvam-http.py @@ -13,7 +13,6 @@ from loguru import logger from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3 from pipecat.audio.vad.silero import SileroVADAnalyzer -from pipecat.audio.vad.vad_analyzer import VADParams from pipecat.frames.frames import LLMRunFrame from pipecat.pipeline.pipeline import Pipeline from pipecat.pipeline.runner import PipelineRunner @@ -90,7 +89,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): TurnAnalyzerUserTurnStopStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3()) ] ), - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), + vad_analyzer=SileroVADAnalyzer(), ), ) diff --git a/examples/foundational/07z-interruptible-sarvam.py b/examples/foundational/07z-interruptible-sarvam.py index 3ead95eb0..492aec4e1 100644 --- a/examples/foundational/07z-interruptible-sarvam.py +++ b/examples/foundational/07z-interruptible-sarvam.py @@ -11,7 +11,6 @@ from loguru import logger from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3 from pipecat.audio.vad.silero import SileroVADAnalyzer -from pipecat.audio.vad.vad_analyzer import VADParams from pipecat.frames.frames import LLMRunFrame from pipecat.pipeline.pipeline import Pipeline from pipecat.pipeline.runner import PipelineRunner @@ -82,7 +81,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): user_turn_strategies=UserTurnStrategies( stop=[TurnAnalyzerUserTurnStopStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3())] ), - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), + vad_analyzer=SileroVADAnalyzer(), ), ) diff --git a/examples/foundational/07za-interruptible-soniox.py b/examples/foundational/07za-interruptible-soniox.py index 5f1a45fe8..55596b8dc 100644 --- a/examples/foundational/07za-interruptible-soniox.py +++ b/examples/foundational/07za-interruptible-soniox.py @@ -12,7 +12,6 @@ from loguru import logger from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3 from pipecat.audio.vad.silero import SileroVADAnalyzer -from pipecat.audio.vad.vad_analyzer import VADParams from pipecat.frames.frames import LLMRunFrame from pipecat.pipeline.pipeline import Pipeline from pipecat.pipeline.runner import PipelineRunner @@ -79,7 +78,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): user_turn_strategies=UserTurnStrategies( stop=[TurnAnalyzerUserTurnStopStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3())] ), - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), + vad_analyzer=SileroVADAnalyzer(), ), ) diff --git a/examples/foundational/07zb-interruptible-inworld-http.py b/examples/foundational/07zb-interruptible-inworld-http.py index 90fb20bd0..6ec35f124 100644 --- a/examples/foundational/07zb-interruptible-inworld-http.py +++ b/examples/foundational/07zb-interruptible-inworld-http.py @@ -12,7 +12,6 @@ from loguru import logger from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3 from pipecat.audio.vad.silero import SileroVADAnalyzer -from pipecat.audio.vad.vad_analyzer import VADParams from pipecat.frames.frames import LLMRunFrame, TTSTextFrame from pipecat.observers.loggers.debug_log_observer import DebugLogObserver, FrameEndpoint from pipecat.pipeline.pipeline import Pipeline @@ -86,7 +85,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): TurnAnalyzerUserTurnStopStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3()) ] ), - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), + vad_analyzer=SileroVADAnalyzer(), ), ) diff --git a/examples/foundational/07zb-interruptible-inworld.py b/examples/foundational/07zb-interruptible-inworld.py index 9c8fa720b..0d3bcb52e 100644 --- a/examples/foundational/07zb-interruptible-inworld.py +++ b/examples/foundational/07zb-interruptible-inworld.py @@ -11,7 +11,6 @@ from loguru import logger from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3 from pipecat.audio.vad.silero import SileroVADAnalyzer -from pipecat.audio.vad.vad_analyzer import VADParams from pipecat.frames.frames import LLMRunFrame, TTSTextFrame from pipecat.observers.loggers.debug_log_observer import DebugLogObserver, FrameEndpoint from pipecat.pipeline.pipeline import Pipeline @@ -81,7 +80,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): user_turn_strategies=UserTurnStrategies( stop=[TurnAnalyzerUserTurnStopStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3())] ), - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), + vad_analyzer=SileroVADAnalyzer(), ), ) diff --git a/examples/foundational/07zc-interruptible-asyncai-http.py b/examples/foundational/07zc-interruptible-asyncai-http.py index dff140ac3..59fafa98d 100644 --- a/examples/foundational/07zc-interruptible-asyncai-http.py +++ b/examples/foundational/07zc-interruptible-asyncai-http.py @@ -13,7 +13,6 @@ from loguru import logger from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3 from pipecat.audio.vad.silero import SileroVADAnalyzer -from pipecat.audio.vad.vad_analyzer import VADParams from pipecat.frames.frames import LLMRunFrame from pipecat.pipeline.pipeline import Pipeline from pipecat.pipeline.runner import PipelineRunner @@ -86,7 +85,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): TurnAnalyzerUserTurnStopStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3()) ] ), - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), + vad_analyzer=SileroVADAnalyzer(), ), ) diff --git a/examples/foundational/07zc-interruptible-asyncai.py b/examples/foundational/07zc-interruptible-asyncai.py index 3596f40a1..de14107fe 100644 --- a/examples/foundational/07zc-interruptible-asyncai.py +++ b/examples/foundational/07zc-interruptible-asyncai.py @@ -12,7 +12,6 @@ from loguru import logger from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3 from pipecat.audio.vad.silero import SileroVADAnalyzer -from pipecat.audio.vad.vad_analyzer import VADParams from pipecat.frames.frames import LLMRunFrame from pipecat.pipeline.pipeline import Pipeline from pipecat.pipeline.runner import PipelineRunner @@ -80,7 +79,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): user_turn_strategies=UserTurnStrategies( stop=[TurnAnalyzerUserTurnStopStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3())] ), - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), + vad_analyzer=SileroVADAnalyzer(), ), ) diff --git a/examples/foundational/07ze-interruptible-hume.py b/examples/foundational/07ze-interruptible-hume.py index a864032c4..4bef4bbe1 100644 --- a/examples/foundational/07ze-interruptible-hume.py +++ b/examples/foundational/07ze-interruptible-hume.py @@ -11,7 +11,6 @@ from loguru import logger from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3 from pipecat.audio.vad.silero import SileroVADAnalyzer -from pipecat.audio.vad.vad_analyzer import VADParams from pipecat.frames.frames import LLMRunFrame, TTSTextFrame from pipecat.observers.loggers.debug_log_observer import DebugLogObserver, FrameEndpoint from pipecat.pipeline.pipeline import Pipeline @@ -82,7 +81,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): user_turn_strategies=UserTurnStrategies( stop=[TurnAnalyzerUserTurnStopStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3())] ), - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), + vad_analyzer=SileroVADAnalyzer(), ), ) diff --git a/examples/foundational/07zf-interruptible-gradium.py b/examples/foundational/07zf-interruptible-gradium.py index 02f33f41b..16e2eeb8a 100644 --- a/examples/foundational/07zf-interruptible-gradium.py +++ b/examples/foundational/07zf-interruptible-gradium.py @@ -11,7 +11,6 @@ from loguru import logger from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3 from pipecat.audio.vad.silero import SileroVADAnalyzer -from pipecat.audio.vad.vad_analyzer import VADParams from pipecat.frames.frames import LLMRunFrame from pipecat.pipeline.pipeline import Pipeline from pipecat.pipeline.runner import PipelineRunner @@ -86,7 +85,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): user_turn_strategies=UserTurnStrategies( stop=[TurnAnalyzerUserTurnStopStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3())] ), - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), + vad_analyzer=SileroVADAnalyzer(), ), ) diff --git a/examples/foundational/07zg-interruptible-camb.py b/examples/foundational/07zg-interruptible-camb.py index d0312a5f7..a0f31d68e 100644 --- a/examples/foundational/07zg-interruptible-camb.py +++ b/examples/foundational/07zg-interruptible-camb.py @@ -11,7 +11,6 @@ from loguru import logger from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3 from pipecat.audio.vad.silero import SileroVADAnalyzer -from pipecat.audio.vad.vad_analyzer import VADParams from pipecat.frames.frames import LLMRunFrame from pipecat.pipeline.pipeline import Pipeline from pipecat.pipeline.runner import PipelineRunner @@ -81,7 +80,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): user_turn_strategies=UserTurnStrategies( stop=[TurnAnalyzerUserTurnStopStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3())] ), - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), + vad_analyzer=SileroVADAnalyzer(), ), ) diff --git a/examples/foundational/07zh-interruptible-hathora.py b/examples/foundational/07zh-interruptible-hathora.py index c7876217f..048de1e3d 100644 --- a/examples/foundational/07zh-interruptible-hathora.py +++ b/examples/foundational/07zh-interruptible-hathora.py @@ -11,7 +11,6 @@ from loguru import logger from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3 from pipecat.audio.vad.silero import SileroVADAnalyzer -from pipecat.audio.vad.vad_analyzer import VADParams from pipecat.frames.frames import LLMRunFrame from pipecat.pipeline.pipeline import Pipeline from pipecat.pipeline.runner import PipelineRunner @@ -84,7 +83,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): user_turn_strategies=UserTurnStrategies( stop=[TurnAnalyzerUserTurnStopStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3())] ), - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), + vad_analyzer=SileroVADAnalyzer(), ), ) diff --git a/examples/foundational/07zi-interruptible-piper.py b/examples/foundational/07zi-interruptible-piper.py index 6a5507d25..0bd722f21 100644 --- a/examples/foundational/07zi-interruptible-piper.py +++ b/examples/foundational/07zi-interruptible-piper.py @@ -11,7 +11,6 @@ from loguru import logger from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3 from pipecat.audio.vad.silero import SileroVADAnalyzer -from pipecat.audio.vad.vad_analyzer import VADParams from pipecat.frames.frames import LLMRunFrame from pipecat.pipeline.pipeline import Pipeline from pipecat.pipeline.runner import PipelineRunner @@ -76,7 +75,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): user_turn_strategies=UserTurnStrategies( stop=[TurnAnalyzerUserTurnStopStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3())] ), - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), + vad_analyzer=SileroVADAnalyzer(), ), ) diff --git a/examples/foundational/07zj-interruptible-kokoro.py b/examples/foundational/07zj-interruptible-kokoro.py index ffebd9315..f275c23b3 100644 --- a/examples/foundational/07zj-interruptible-kokoro.py +++ b/examples/foundational/07zj-interruptible-kokoro.py @@ -11,7 +11,6 @@ from loguru import logger from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3 from pipecat.audio.vad.silero import SileroVADAnalyzer -from pipecat.audio.vad.vad_analyzer import VADParams from pipecat.frames.frames import LLMRunFrame from pipecat.pipeline.pipeline import Pipeline from pipecat.pipeline.runner import PipelineRunner @@ -76,7 +75,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): user_turn_strategies=UserTurnStrategies( stop=[TurnAnalyzerUserTurnStopStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3())] ), - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), + vad_analyzer=SileroVADAnalyzer(), ), ) diff --git a/examples/foundational/07zk-interruptible-resemble.py b/examples/foundational/07zk-interruptible-resemble.py index 5cbf1288d..4cb8271bb 100644 --- a/examples/foundational/07zk-interruptible-resemble.py +++ b/examples/foundational/07zk-interruptible-resemble.py @@ -11,7 +11,6 @@ from loguru import logger from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3 from pipecat.audio.vad.silero import SileroVADAnalyzer -from pipecat.audio.vad.vad_analyzer import VADParams from pipecat.frames.frames import LLMRunFrame from pipecat.pipeline.pipeline import Pipeline from pipecat.pipeline.runner import PipelineRunner @@ -41,17 +40,17 @@ transport_params = { "daily": lambda: DailyParams( audio_in_enabled=True, audio_out_enabled=True, - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), + vad_analyzer=SileroVADAnalyzer(), ), "twilio": lambda: FastAPIWebsocketParams( audio_in_enabled=True, audio_out_enabled=True, - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), + vad_analyzer=SileroVADAnalyzer(), ), "webrtc": lambda: TransportParams( audio_in_enabled=True, audio_out_enabled=True, - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), + vad_analyzer=SileroVADAnalyzer(), ), } diff --git a/examples/foundational/08-custom-frame-processor.py b/examples/foundational/08-custom-frame-processor.py index c561c46f3..779e891af 100644 --- a/examples/foundational/08-custom-frame-processor.py +++ b/examples/foundational/08-custom-frame-processor.py @@ -11,7 +11,6 @@ from loguru import logger from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3 from pipecat.audio.vad.silero import SileroVADAnalyzer -from pipecat.audio.vad.vad_analyzer import VADParams from pipecat.frames.frames import ( Frame, LLMRunFrame, @@ -118,7 +117,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): user_turn_strategies=UserTurnStrategies( stop=[TurnAnalyzerUserTurnStopStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3())] ), - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), + vad_analyzer=SileroVADAnalyzer(), ), ) diff --git a/examples/foundational/10-wake-phrase.py b/examples/foundational/10-wake-phrase.py index f87255814..c2a5357bd 100644 --- a/examples/foundational/10-wake-phrase.py +++ b/examples/foundational/10-wake-phrase.py @@ -11,7 +11,6 @@ from loguru import logger from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3 from pipecat.audio.vad.silero import SileroVADAnalyzer -from pipecat.audio.vad.vad_analyzer import VADParams from pipecat.frames.frames import TTSSpeakFrame from pipecat.pipeline.pipeline import Pipeline from pipecat.pipeline.runner import PipelineRunner @@ -81,7 +80,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): user_turn_strategies=UserTurnStrategies( stop=[TurnAnalyzerUserTurnStopStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3())] ), - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), + vad_analyzer=SileroVADAnalyzer(), ), ) diff --git a/examples/foundational/11-sound-effects.py b/examples/foundational/11-sound-effects.py index 297db8a45..9cae7e205 100644 --- a/examples/foundational/11-sound-effects.py +++ b/examples/foundational/11-sound-effects.py @@ -12,7 +12,6 @@ from loguru import logger from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3 from pipecat.audio.vad.silero import SileroVADAnalyzer -from pipecat.audio.vad.vad_analyzer import VADParams from pipecat.frames.frames import ( Frame, LLMContextFrame, @@ -129,7 +128,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): user_turn_strategies=UserTurnStrategies( stop=[TurnAnalyzerUserTurnStopStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3())] ), - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), + vad_analyzer=SileroVADAnalyzer(), ), ) out_sound = OutboundSoundEffectWrapper() diff --git a/examples/foundational/12-describe-image-openai.py b/examples/foundational/12-describe-image-openai.py index 413573eb7..835584a21 100644 --- a/examples/foundational/12-describe-image-openai.py +++ b/examples/foundational/12-describe-image-openai.py @@ -13,7 +13,6 @@ from PIL import Image from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3 from pipecat.audio.vad.silero import SileroVADAnalyzer -from pipecat.audio.vad.vad_analyzer import VADParams from pipecat.frames.frames import LLMRunFrame from pipecat.pipeline.pipeline import Pipeline from pipecat.pipeline.runner import PipelineRunner @@ -76,7 +75,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): user_turn_strategies=UserTurnStrategies( stop=[TurnAnalyzerUserTurnStopStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3())] ), - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), + vad_analyzer=SileroVADAnalyzer(), ), ) diff --git a/examples/foundational/12a-describe-image-anthropic.py b/examples/foundational/12a-describe-image-anthropic.py index 0b611c143..45f85ede9 100644 --- a/examples/foundational/12a-describe-image-anthropic.py +++ b/examples/foundational/12a-describe-image-anthropic.py @@ -13,7 +13,6 @@ from PIL import Image from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3 from pipecat.audio.vad.silero import SileroVADAnalyzer -from pipecat.audio.vad.vad_analyzer import VADParams from pipecat.frames.frames import LLMRunFrame from pipecat.pipeline.pipeline import Pipeline from pipecat.pipeline.runner import PipelineRunner @@ -76,7 +75,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): user_turn_strategies=UserTurnStrategies( stop=[TurnAnalyzerUserTurnStopStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3())] ), - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), + vad_analyzer=SileroVADAnalyzer(), ), ) diff --git a/examples/foundational/12b-describe-image-aws.py b/examples/foundational/12b-describe-image-aws.py index 4c62a1fbf..d27c655e4 100644 --- a/examples/foundational/12b-describe-image-aws.py +++ b/examples/foundational/12b-describe-image-aws.py @@ -13,7 +13,6 @@ from PIL import Image from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3 from pipecat.audio.vad.silero import SileroVADAnalyzer -from pipecat.audio.vad.vad_analyzer import VADParams from pipecat.frames.frames import LLMRunFrame from pipecat.pipeline.pipeline import Pipeline from pipecat.pipeline.runner import PipelineRunner @@ -83,7 +82,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): user_turn_strategies=UserTurnStrategies( stop=[TurnAnalyzerUserTurnStopStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3())] ), - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), + vad_analyzer=SileroVADAnalyzer(), ), ) diff --git a/examples/foundational/12c-describe-image-gemini-flash.py b/examples/foundational/12c-describe-image-gemini-flash.py index b1cd3fd73..809386ef4 100644 --- a/examples/foundational/12c-describe-image-gemini-flash.py +++ b/examples/foundational/12c-describe-image-gemini-flash.py @@ -13,7 +13,6 @@ from PIL import Image from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3 from pipecat.audio.vad.silero import SileroVADAnalyzer -from pipecat.audio.vad.vad_analyzer import VADParams from pipecat.frames.frames import LLMRunFrame from pipecat.pipeline.pipeline import Pipeline from pipecat.pipeline.runner import PipelineRunner @@ -76,7 +75,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): user_turn_strategies=UserTurnStrategies( stop=[TurnAnalyzerUserTurnStopStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3())] ), - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), + vad_analyzer=SileroVADAnalyzer(), ), ) diff --git a/examples/foundational/14-function-calling.py b/examples/foundational/14-function-calling.py index a1cda33f6..be292333b 100644 --- a/examples/foundational/14-function-calling.py +++ b/examples/foundational/14-function-calling.py @@ -13,7 +13,6 @@ from pipecat.adapters.schemas.function_schema import FunctionSchema from pipecat.adapters.schemas.tools_schema import ToolsSchema from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3 from pipecat.audio.vad.silero import SileroVADAnalyzer -from pipecat.audio.vad.vad_analyzer import VADParams from pipecat.frames.frames import LLMRunFrame, TTSSpeakFrame from pipecat.pipeline.pipeline import Pipeline from pipecat.pipeline.runner import PipelineRunner @@ -128,7 +127,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): user_turn_strategies=UserTurnStrategies( stop=[TurnAnalyzerUserTurnStopStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3())] ), - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), + vad_analyzer=SileroVADAnalyzer(), ), ) diff --git a/examples/foundational/14a-function-calling-anthropic.py b/examples/foundational/14a-function-calling-anthropic.py index 783ea7c7c..24e3140c5 100644 --- a/examples/foundational/14a-function-calling-anthropic.py +++ b/examples/foundational/14a-function-calling-anthropic.py @@ -14,7 +14,6 @@ from pipecat.adapters.schemas.function_schema import FunctionSchema from pipecat.adapters.schemas.tools_schema import ToolsSchema from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3 from pipecat.audio.vad.silero import SileroVADAnalyzer -from pipecat.audio.vad.vad_analyzer import VADParams from pipecat.frames.frames import LLMRunFrame from pipecat.pipeline.pipeline import Pipeline from pipecat.pipeline.runner import PipelineRunner @@ -123,7 +122,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): user_turn_strategies=UserTurnStrategies( stop=[TurnAnalyzerUserTurnStopStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3())] ), - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), + vad_analyzer=SileroVADAnalyzer(), ), ) diff --git a/examples/foundational/14c-function-calling-together.py b/examples/foundational/14c-function-calling-together.py index 49f5b98e3..4db8a881c 100644 --- a/examples/foundational/14c-function-calling-together.py +++ b/examples/foundational/14c-function-calling-together.py @@ -14,7 +14,6 @@ from pipecat.adapters.schemas.function_schema import FunctionSchema from pipecat.adapters.schemas.tools_schema import ToolsSchema from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3 from pipecat.audio.vad.silero import SileroVADAnalyzer -from pipecat.audio.vad.vad_analyzer import VADParams from pipecat.frames.frames import LLMRunFrame, TTSSpeakFrame from pipecat.pipeline.pipeline import Pipeline from pipecat.pipeline.runner import PipelineRunner @@ -114,7 +113,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): user_turn_strategies=UserTurnStrategies( stop=[TurnAnalyzerUserTurnStopStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3())] ), - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), + vad_analyzer=SileroVADAnalyzer(), ), ) diff --git a/examples/foundational/14d-function-calling-anthropic-video.py b/examples/foundational/14d-function-calling-anthropic-video.py index 971016fdf..efac52186 100644 --- a/examples/foundational/14d-function-calling-anthropic-video.py +++ b/examples/foundational/14d-function-calling-anthropic-video.py @@ -13,7 +13,6 @@ from pipecat.adapters.schemas.function_schema import FunctionSchema from pipecat.adapters.schemas.tools_schema import ToolsSchema from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3 from pipecat.audio.vad.silero import SileroVADAnalyzer -from pipecat.audio.vad.vad_analyzer import VADParams from pipecat.frames.frames import LLMRunFrame, TTSSpeakFrame, UserImageRequestFrame from pipecat.pipeline.pipeline import Pipeline from pipecat.pipeline.runner import PipelineRunner @@ -136,7 +135,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): user_turn_strategies=UserTurnStrategies( stop=[TurnAnalyzerUserTurnStopStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3())] ), - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), + vad_analyzer=SileroVADAnalyzer(), ), ) diff --git a/examples/foundational/14d-function-calling-aws-video.py b/examples/foundational/14d-function-calling-aws-video.py index a78500819..9f60f534c 100644 --- a/examples/foundational/14d-function-calling-aws-video.py +++ b/examples/foundational/14d-function-calling-aws-video.py @@ -13,7 +13,6 @@ from pipecat.adapters.schemas.function_schema import FunctionSchema from pipecat.adapters.schemas.tools_schema import ToolsSchema from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3 from pipecat.audio.vad.silero import SileroVADAnalyzer -from pipecat.audio.vad.vad_analyzer import VADParams from pipecat.frames.frames import LLMRunFrame, TTSSpeakFrame, UserImageRequestFrame from pipecat.pipeline.pipeline import Pipeline from pipecat.pipeline.runner import PipelineRunner @@ -143,7 +142,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): user_turn_strategies=UserTurnStrategies( stop=[TurnAnalyzerUserTurnStopStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3())] ), - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), + vad_analyzer=SileroVADAnalyzer(), ), ) diff --git a/examples/foundational/14d-function-calling-gemini-flash-video.py b/examples/foundational/14d-function-calling-gemini-flash-video.py index 9470f19ca..5d89e5b58 100644 --- a/examples/foundational/14d-function-calling-gemini-flash-video.py +++ b/examples/foundational/14d-function-calling-gemini-flash-video.py @@ -13,7 +13,6 @@ from pipecat.adapters.schemas.function_schema import FunctionSchema from pipecat.adapters.schemas.tools_schema import ToolsSchema from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3 from pipecat.audio.vad.silero import SileroVADAnalyzer -from pipecat.audio.vad.vad_analyzer import VADParams from pipecat.frames.frames import LLMRunFrame, TTSSpeakFrame, UserImageRequestFrame from pipecat.pipeline.pipeline import Pipeline from pipecat.pipeline.runner import PipelineRunner @@ -136,7 +135,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): user_turn_strategies=UserTurnStrategies( stop=[TurnAnalyzerUserTurnStopStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3())] ), - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), + vad_analyzer=SileroVADAnalyzer(), ), ) diff --git a/examples/foundational/14d-function-calling-moondream-video.py b/examples/foundational/14d-function-calling-moondream-video.py index 263b51215..adb943406 100644 --- a/examples/foundational/14d-function-calling-moondream-video.py +++ b/examples/foundational/14d-function-calling-moondream-video.py @@ -13,7 +13,6 @@ from pipecat.adapters.schemas.function_schema import FunctionSchema from pipecat.adapters.schemas.tools_schema import ToolsSchema from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3 from pipecat.audio.vad.silero import SileroVADAnalyzer -from pipecat.audio.vad.vad_analyzer import VADParams from pipecat.frames.frames import ( Frame, LLMFullResponseEndFrame, @@ -166,7 +165,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): user_turn_strategies=UserTurnStrategies( stop=[TurnAnalyzerUserTurnStopStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3())] ), - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), + vad_analyzer=SileroVADAnalyzer(), ), ) diff --git a/examples/foundational/14d-function-calling-openai-video.py b/examples/foundational/14d-function-calling-openai-video.py index ea18b0d11..a6b9b7d43 100644 --- a/examples/foundational/14d-function-calling-openai-video.py +++ b/examples/foundational/14d-function-calling-openai-video.py @@ -14,7 +14,6 @@ from pipecat.adapters.schemas.function_schema import FunctionSchema from pipecat.adapters.schemas.tools_schema import ToolsSchema from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3 from pipecat.audio.vad.silero import SileroVADAnalyzer -from pipecat.audio.vad.vad_analyzer import VADParams from pipecat.frames.frames import LLMRunFrame, TTSSpeakFrame, UserImageRequestFrame from pipecat.pipeline.pipeline import Pipeline from pipecat.pipeline.runner import PipelineRunner @@ -136,7 +135,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): user_turn_strategies=UserTurnStrategies( stop=[TurnAnalyzerUserTurnStopStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3())] ), - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), + vad_analyzer=SileroVADAnalyzer(), ), ) diff --git a/examples/foundational/14e-function-calling-google.py b/examples/foundational/14e-function-calling-google.py index e8757bb71..2faecd3a6 100644 --- a/examples/foundational/14e-function-calling-google.py +++ b/examples/foundational/14e-function-calling-google.py @@ -14,7 +14,6 @@ from pipecat.adapters.schemas.function_schema import FunctionSchema from pipecat.adapters.schemas.tools_schema import ToolsSchema from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3 from pipecat.audio.vad.silero import SileroVADAnalyzer -from pipecat.audio.vad.vad_analyzer import VADParams from pipecat.frames.frames import LLMRunFrame, TTSSpeakFrame, UserImageRequestFrame from pipecat.pipeline.pipeline import Pipeline from pipecat.pipeline.runner import PipelineRunner @@ -189,7 +188,7 @@ indicate you should use the get_image tool are: user_turn_strategies=UserTurnStrategies( stop=[TurnAnalyzerUserTurnStopStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3())] ), - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), + vad_analyzer=SileroVADAnalyzer(), ), ) diff --git a/examples/foundational/14f-function-calling-groq.py b/examples/foundational/14f-function-calling-groq.py index ff410cb6e..7320e53f0 100644 --- a/examples/foundational/14f-function-calling-groq.py +++ b/examples/foundational/14f-function-calling-groq.py @@ -14,7 +14,6 @@ from pipecat.adapters.schemas.function_schema import FunctionSchema from pipecat.adapters.schemas.tools_schema import ToolsSchema from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3 from pipecat.audio.vad.silero import SileroVADAnalyzer -from pipecat.audio.vad.vad_analyzer import VADParams from pipecat.frames.frames import LLMRunFrame, TTSSpeakFrame from pipecat.pipeline.pipeline import Pipeline from pipecat.pipeline.runner import PipelineRunner @@ -111,7 +110,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): user_turn_strategies=UserTurnStrategies( stop=[TurnAnalyzerUserTurnStopStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3())] ), - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), + vad_analyzer=SileroVADAnalyzer(), ), ) diff --git a/examples/foundational/14g-function-calling-grok.py b/examples/foundational/14g-function-calling-grok.py index ba087c2f9..fba6067de 100644 --- a/examples/foundational/14g-function-calling-grok.py +++ b/examples/foundational/14g-function-calling-grok.py @@ -14,7 +14,6 @@ from pipecat.adapters.schemas.function_schema import FunctionSchema from pipecat.adapters.schemas.tools_schema import ToolsSchema from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3 from pipecat.audio.vad.silero import SileroVADAnalyzer -from pipecat.audio.vad.vad_analyzer import VADParams from pipecat.frames.frames import LLMRunFrame from pipecat.pipeline.pipeline import Pipeline from pipecat.pipeline.runner import PipelineRunner @@ -107,7 +106,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): user_turn_strategies=UserTurnStrategies( stop=[TurnAnalyzerUserTurnStopStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3())] ), - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), + vad_analyzer=SileroVADAnalyzer(), ), ) diff --git a/examples/foundational/14h-function-calling-azure.py b/examples/foundational/14h-function-calling-azure.py index c4036c282..ed17e1cc6 100644 --- a/examples/foundational/14h-function-calling-azure.py +++ b/examples/foundational/14h-function-calling-azure.py @@ -14,7 +14,6 @@ from pipecat.adapters.schemas.function_schema import FunctionSchema from pipecat.adapters.schemas.tools_schema import ToolsSchema from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3 from pipecat.audio.vad.silero import SileroVADAnalyzer -from pipecat.audio.vad.vad_analyzer import VADParams from pipecat.frames.frames import LLMRunFrame, TTSSpeakFrame from pipecat.pipeline.pipeline import Pipeline from pipecat.pipeline.runner import PipelineRunner @@ -115,7 +114,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): user_turn_strategies=UserTurnStrategies( stop=[TurnAnalyzerUserTurnStopStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3())] ), - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), + vad_analyzer=SileroVADAnalyzer(), ), ) diff --git a/examples/foundational/14i-function-calling-fireworks.py b/examples/foundational/14i-function-calling-fireworks.py index 61dc21af5..475987b5f 100644 --- a/examples/foundational/14i-function-calling-fireworks.py +++ b/examples/foundational/14i-function-calling-fireworks.py @@ -14,7 +14,6 @@ from pipecat.adapters.schemas.function_schema import FunctionSchema from pipecat.adapters.schemas.tools_schema import ToolsSchema from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3 from pipecat.audio.vad.silero import SileroVADAnalyzer -from pipecat.audio.vad.vad_analyzer import VADParams from pipecat.frames.frames import LLMRunFrame from pipecat.pipeline.pipeline import Pipeline from pipecat.pipeline.runner import PipelineRunner @@ -118,7 +117,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): user_turn_strategies=UserTurnStrategies( stop=[TurnAnalyzerUserTurnStopStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3())] ), - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), + vad_analyzer=SileroVADAnalyzer(), ), ) diff --git a/examples/foundational/14j-function-calling-nvidia.py b/examples/foundational/14j-function-calling-nvidia.py index 52c737d18..2489661d2 100644 --- a/examples/foundational/14j-function-calling-nvidia.py +++ b/examples/foundational/14j-function-calling-nvidia.py @@ -14,7 +14,6 @@ from pipecat.adapters.schemas.function_schema import FunctionSchema from pipecat.adapters.schemas.tools_schema import ToolsSchema from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3 from pipecat.audio.vad.silero import SileroVADAnalyzer -from pipecat.audio.vad.vad_analyzer import VADParams from pipecat.frames.frames import LLMRunFrame, TTSSpeakFrame from pipecat.pipeline.pipeline import Pipeline from pipecat.pipeline.runner import PipelineRunner @@ -120,7 +119,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): user_turn_strategies=UserTurnStrategies( stop=[TurnAnalyzerUserTurnStopStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3())] ), - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), + vad_analyzer=SileroVADAnalyzer(), ), ) diff --git a/examples/foundational/14k-function-calling-cerebras.py b/examples/foundational/14k-function-calling-cerebras.py index fc1c821e1..8163e95b7 100644 --- a/examples/foundational/14k-function-calling-cerebras.py +++ b/examples/foundational/14k-function-calling-cerebras.py @@ -14,7 +14,6 @@ from pipecat.adapters.schemas.function_schema import FunctionSchema from pipecat.adapters.schemas.tools_schema import ToolsSchema from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3 from pipecat.audio.vad.silero import SileroVADAnalyzer -from pipecat.audio.vad.vad_analyzer import VADParams from pipecat.frames.frames import LLMRunFrame, TTSSpeakFrame from pipecat.pipeline.pipeline import Pipeline from pipecat.pipeline.runner import PipelineRunner @@ -121,7 +120,7 @@ Start by asking me for my location. Then, use 'get_weather_current' to give me a user_turn_strategies=UserTurnStrategies( stop=[TurnAnalyzerUserTurnStopStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3())] ), - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), + vad_analyzer=SileroVADAnalyzer(), ), ) diff --git a/examples/foundational/14l-function-calling-deepseek.py b/examples/foundational/14l-function-calling-deepseek.py index 8be0b93d7..63730976d 100644 --- a/examples/foundational/14l-function-calling-deepseek.py +++ b/examples/foundational/14l-function-calling-deepseek.py @@ -14,7 +14,6 @@ from pipecat.adapters.schemas.function_schema import FunctionSchema from pipecat.adapters.schemas.tools_schema import ToolsSchema from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3 from pipecat.audio.vad.silero import SileroVADAnalyzer -from pipecat.audio.vad.vad_analyzer import VADParams from pipecat.frames.frames import LLMRunFrame, TTSSpeakFrame from pipecat.pipeline.pipeline import Pipeline from pipecat.pipeline.runner import PipelineRunner @@ -121,7 +120,7 @@ Start by asking me for my location. Then, use 'get_weather_current' to give me a user_turn_strategies=UserTurnStrategies( stop=[TurnAnalyzerUserTurnStopStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3())] ), - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), + vad_analyzer=SileroVADAnalyzer(), ), ) diff --git a/examples/foundational/14m-function-calling-openrouter.py b/examples/foundational/14m-function-calling-openrouter.py index eddf7e0e2..1cd47e6fb 100644 --- a/examples/foundational/14m-function-calling-openrouter.py +++ b/examples/foundational/14m-function-calling-openrouter.py @@ -14,7 +14,6 @@ from pipecat.adapters.schemas.function_schema import FunctionSchema from pipecat.adapters.schemas.tools_schema import ToolsSchema from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3 from pipecat.audio.vad.silero import SileroVADAnalyzer -from pipecat.audio.vad.vad_analyzer import VADParams from pipecat.frames.frames import LLMRunFrame, TTSSpeakFrame from pipecat.pipeline.pipeline import Pipeline from pipecat.pipeline.runner import PipelineRunner @@ -115,7 +114,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): user_turn_strategies=UserTurnStrategies( stop=[TurnAnalyzerUserTurnStopStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3())] ), - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), + vad_analyzer=SileroVADAnalyzer(), ), ) diff --git a/examples/foundational/14n-function-calling-perplexity.py b/examples/foundational/14n-function-calling-perplexity.py index 33d12fe88..e8b0a6f53 100644 --- a/examples/foundational/14n-function-calling-perplexity.py +++ b/examples/foundational/14n-function-calling-perplexity.py @@ -18,7 +18,6 @@ from loguru import logger from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3 from pipecat.audio.vad.silero import SileroVADAnalyzer -from pipecat.audio.vad.vad_analyzer import VADParams from pipecat.frames.frames import LLMRunFrame from pipecat.pipeline.pipeline import Pipeline from pipecat.pipeline.runner import PipelineRunner @@ -85,7 +84,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): user_turn_strategies=UserTurnStrategies( stop=[TurnAnalyzerUserTurnStopStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3())] ), - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), + vad_analyzer=SileroVADAnalyzer(), ), ) diff --git a/examples/foundational/14o-function-calling-gemini-openai-format.py b/examples/foundational/14o-function-calling-gemini-openai-format.py index 4490d30b0..c87c5278e 100644 --- a/examples/foundational/14o-function-calling-gemini-openai-format.py +++ b/examples/foundational/14o-function-calling-gemini-openai-format.py @@ -14,7 +14,6 @@ from pipecat.adapters.schemas.function_schema import FunctionSchema from pipecat.adapters.schemas.tools_schema import ToolsSchema from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3 from pipecat.audio.vad.silero import SileroVADAnalyzer -from pipecat.audio.vad.vad_analyzer import VADParams from pipecat.frames.frames import LLMRunFrame, TTSSpeakFrame from pipecat.pipeline.pipeline import Pipeline from pipecat.pipeline.runner import PipelineRunner @@ -43,19 +42,19 @@ transport_params = { "daily": lambda: DailyParams( audio_in_enabled=True, audio_out_enabled=True, - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), + vad_analyzer=SileroVADAnalyzer(), turn_analyzer=LocalSmartTurnAnalyzerV3(), ), "twilio": lambda: FastAPIWebsocketParams( audio_in_enabled=True, audio_out_enabled=True, - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), + vad_analyzer=SileroVADAnalyzer(), turn_analyzer=LocalSmartTurnAnalyzerV3(), ), "webrtc": lambda: TransportParams( audio_in_enabled=True, audio_out_enabled=True, - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), + vad_analyzer=SileroVADAnalyzer(), turn_analyzer=LocalSmartTurnAnalyzerV3(), ), } diff --git a/examples/foundational/14p-function-calling-gemini-vertex-ai.py b/examples/foundational/14p-function-calling-gemini-vertex-ai.py index e75c288ad..cbff8d2f7 100644 --- a/examples/foundational/14p-function-calling-gemini-vertex-ai.py +++ b/examples/foundational/14p-function-calling-gemini-vertex-ai.py @@ -14,7 +14,6 @@ from pipecat.adapters.schemas.function_schema import FunctionSchema from pipecat.adapters.schemas.tools_schema import ToolsSchema from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3 from pipecat.audio.vad.silero import SileroVADAnalyzer -from pipecat.audio.vad.vad_analyzer import VADParams from pipecat.frames.frames import LLMRunFrame, TTSSpeakFrame from pipecat.pipeline.pipeline import Pipeline from pipecat.pipeline.runner import PipelineRunner @@ -116,7 +115,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): user_turn_strategies=UserTurnStrategies( stop=[TurnAnalyzerUserTurnStopStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3())] ), - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), + vad_analyzer=SileroVADAnalyzer(), ), ) diff --git a/examples/foundational/14q-function-calling-qwen.py b/examples/foundational/14q-function-calling-qwen.py index 2363c840f..4f80989a1 100644 --- a/examples/foundational/14q-function-calling-qwen.py +++ b/examples/foundational/14q-function-calling-qwen.py @@ -14,7 +14,6 @@ from pipecat.adapters.schemas.function_schema import FunctionSchema from pipecat.adapters.schemas.tools_schema import ToolsSchema from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3 from pipecat.audio.vad.silero import SileroVADAnalyzer -from pipecat.audio.vad.vad_analyzer import VADParams from pipecat.frames.frames import LLMRunFrame, TTSSpeakFrame from pipecat.pipeline.pipeline import Pipeline from pipecat.pipeline.runner import PipelineRunner @@ -113,7 +112,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): user_turn_strategies=UserTurnStrategies( stop=[TurnAnalyzerUserTurnStopStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3())] ), - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), + vad_analyzer=SileroVADAnalyzer(), ), ) diff --git a/examples/foundational/14r-function-calling-aws.py b/examples/foundational/14r-function-calling-aws.py index 7e144dc9e..4ccfbbd3e 100644 --- a/examples/foundational/14r-function-calling-aws.py +++ b/examples/foundational/14r-function-calling-aws.py @@ -12,7 +12,6 @@ from pipecat.adapters.schemas.function_schema import FunctionSchema from pipecat.adapters.schemas.tools_schema import ToolsSchema from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3 from pipecat.audio.vad.silero import SileroVADAnalyzer -from pipecat.audio.vad.vad_analyzer import VADParams from pipecat.frames.frames import LLMRunFrame from pipecat.pipeline.pipeline import Pipeline from pipecat.pipeline.runner import PipelineRunner @@ -128,7 +127,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): user_turn_strategies=UserTurnStrategies( stop=[TurnAnalyzerUserTurnStopStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3())] ), - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), + vad_analyzer=SileroVADAnalyzer(), ), ) diff --git a/examples/foundational/14s-function-calling-sambanova.py b/examples/foundational/14s-function-calling-sambanova.py index 025aa1cc9..a33567d11 100644 --- a/examples/foundational/14s-function-calling-sambanova.py +++ b/examples/foundational/14s-function-calling-sambanova.py @@ -14,7 +14,6 @@ from pipecat.adapters.schemas.function_schema import FunctionSchema from pipecat.adapters.schemas.tools_schema import ToolsSchema from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3 from pipecat.audio.vad.silero import SileroVADAnalyzer -from pipecat.audio.vad.vad_analyzer import VADParams from pipecat.frames.frames import LLMRunFrame, TTSSpeakFrame from pipecat.pipeline.pipeline import Pipeline from pipecat.pipeline.runner import PipelineRunner @@ -117,7 +116,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): user_turn_strategies=UserTurnStrategies( stop=[TurnAnalyzerUserTurnStopStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3())] ), - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), + vad_analyzer=SileroVADAnalyzer(), ), ) diff --git a/examples/foundational/14t-function-calling-direct.py b/examples/foundational/14t-function-calling-direct.py index 59e09a76a..fd9c0a3c9 100644 --- a/examples/foundational/14t-function-calling-direct.py +++ b/examples/foundational/14t-function-calling-direct.py @@ -13,7 +13,6 @@ from loguru import logger from pipecat.adapters.schemas.tools_schema import ToolsSchema from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3 from pipecat.audio.vad.silero import SileroVADAnalyzer -from pipecat.audio.vad.vad_analyzer import VADParams from pipecat.frames.frames import LLMRunFrame, TTSSpeakFrame from pipecat.pipeline.pipeline import Pipeline from pipecat.pipeline.runner import PipelineRunner @@ -114,7 +113,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): user_turn_strategies=UserTurnStrategies( stop=[TurnAnalyzerUserTurnStopStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3())] ), - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), + vad_analyzer=SileroVADAnalyzer(), ), ) diff --git a/examples/foundational/14u-function-calling-ollama.py b/examples/foundational/14u-function-calling-ollama.py index ed04c2236..56e36dfdc 100644 --- a/examples/foundational/14u-function-calling-ollama.py +++ b/examples/foundational/14u-function-calling-ollama.py @@ -14,7 +14,6 @@ from pipecat.adapters.schemas.function_schema import FunctionSchema from pipecat.adapters.schemas.tools_schema import ToolsSchema from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3 from pipecat.audio.vad.silero import SileroVADAnalyzer -from pipecat.audio.vad.vad_analyzer import VADParams from pipecat.frames.frames import LLMRunFrame, TTSSpeakFrame from pipecat.pipeline.pipeline import Pipeline from pipecat.pipeline.runner import PipelineRunner @@ -129,7 +128,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): user_turn_strategies=UserTurnStrategies( stop=[TurnAnalyzerUserTurnStopStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3())] ), - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), + vad_analyzer=SileroVADAnalyzer(), ), ) diff --git a/examples/foundational/14v-function-calling-openai.py b/examples/foundational/14v-function-calling-openai.py index 7265ce73a..c56d82abf 100644 --- a/examples/foundational/14v-function-calling-openai.py +++ b/examples/foundational/14v-function-calling-openai.py @@ -13,7 +13,6 @@ from pipecat.adapters.schemas.function_schema import FunctionSchema from pipecat.adapters.schemas.tools_schema import ToolsSchema from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3 from pipecat.audio.vad.silero import SileroVADAnalyzer -from pipecat.audio.vad.vad_analyzer import VADParams from pipecat.frames.frames import LLMRunFrame, TTSSpeakFrame from pipecat.pipeline.pipeline import Pipeline from pipecat.pipeline.runner import PipelineRunner @@ -136,7 +135,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): user_turn_strategies=UserTurnStrategies( stop=[TurnAnalyzerUserTurnStopStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3())] ), - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), + vad_analyzer=SileroVADAnalyzer(), ), ) diff --git a/examples/foundational/14w-function-calling-mistral.py b/examples/foundational/14w-function-calling-mistral.py index 03b344df5..09ad525d5 100644 --- a/examples/foundational/14w-function-calling-mistral.py +++ b/examples/foundational/14w-function-calling-mistral.py @@ -13,7 +13,6 @@ from pipecat.adapters.schemas.function_schema import FunctionSchema from pipecat.adapters.schemas.tools_schema import ToolsSchema from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3 from pipecat.audio.vad.silero import SileroVADAnalyzer -from pipecat.audio.vad.vad_analyzer import VADParams from pipecat.frames.frames import LLMRunFrame from pipecat.pipeline.pipeline import Pipeline from pipecat.pipeline.runner import PipelineRunner @@ -124,7 +123,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): user_turn_strategies=UserTurnStrategies( stop=[TurnAnalyzerUserTurnStopStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3())] ), - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), + vad_analyzer=SileroVADAnalyzer(), ), ) diff --git a/examples/foundational/14x-function-calling-openpipe.py b/examples/foundational/14x-function-calling-openpipe.py index 7a4a5f2e7..fa877cdb1 100644 --- a/examples/foundational/14x-function-calling-openpipe.py +++ b/examples/foundational/14x-function-calling-openpipe.py @@ -14,7 +14,6 @@ from pipecat.adapters.schemas.function_schema import FunctionSchema from pipecat.adapters.schemas.tools_schema import ToolsSchema from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3 from pipecat.audio.vad.silero import SileroVADAnalyzer -from pipecat.audio.vad.vad_analyzer import VADParams from pipecat.frames.frames import LLMRunFrame, TTSSpeakFrame from pipecat.pipeline.pipeline import Pipeline from pipecat.pipeline.runner import PipelineRunner @@ -134,7 +133,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): user_turn_strategies=UserTurnStrategies( stop=[TurnAnalyzerUserTurnStopStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3())] ), - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), + vad_analyzer=SileroVADAnalyzer(), ), ) diff --git a/examples/foundational/15-switch-voices.py b/examples/foundational/15-switch-voices.py index d0684b045..c76ff2172 100644 --- a/examples/foundational/15-switch-voices.py +++ b/examples/foundational/15-switch-voices.py @@ -14,7 +14,6 @@ from pipecat.adapters.schemas.function_schema import FunctionSchema from pipecat.adapters.schemas.tools_schema import ToolsSchema from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3 from pipecat.audio.vad.silero import SileroVADAnalyzer -from pipecat.audio.vad.vad_analyzer import VADParams from pipecat.frames.frames import Frame, LLMRunFrame from pipecat.pipeline.parallel_pipeline import ParallelPipeline from pipecat.pipeline.pipeline import Pipeline @@ -146,7 +145,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): user_turn_strategies=UserTurnStrategies( stop=[TurnAnalyzerUserTurnStopStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3())] ), - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), + vad_analyzer=SileroVADAnalyzer(), ), ) diff --git a/examples/foundational/15a-switch-languages.py b/examples/foundational/15a-switch-languages.py index c92b6b5e5..6674fb0cf 100644 --- a/examples/foundational/15a-switch-languages.py +++ b/examples/foundational/15a-switch-languages.py @@ -15,7 +15,6 @@ from pipecat.adapters.schemas.function_schema import FunctionSchema from pipecat.adapters.schemas.tools_schema import ToolsSchema from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3 from pipecat.audio.vad.silero import SileroVADAnalyzer -from pipecat.audio.vad.vad_analyzer import VADParams from pipecat.frames.frames import Frame, LLMRunFrame from pipecat.pipeline.parallel_pipeline import ParallelPipeline from pipecat.pipeline.pipeline import Pipeline @@ -136,7 +135,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): user_turn_strategies=UserTurnStrategies( stop=[TurnAnalyzerUserTurnStopStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3())] ), - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), + vad_analyzer=SileroVADAnalyzer(), ), ) diff --git a/examples/foundational/16-gpu-container-local-bot.py b/examples/foundational/16-gpu-container-local-bot.py index 84e28259b..e24c5e984 100644 --- a/examples/foundational/16-gpu-container-local-bot.py +++ b/examples/foundational/16-gpu-container-local-bot.py @@ -12,7 +12,6 @@ from loguru import logger from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3 from pipecat.audio.vad.silero import SileroVADAnalyzer -from pipecat.audio.vad.vad_analyzer import VADParams from pipecat.frames.frames import LLMRunFrame from pipecat.pipeline.pipeline import Pipeline from pipecat.pipeline.runner import PipelineRunner @@ -90,7 +89,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): user_turn_strategies=UserTurnStrategies( stop=[TurnAnalyzerUserTurnStopStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3())] ), - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), + vad_analyzer=SileroVADAnalyzer(), ), ) diff --git a/examples/foundational/17-detect-user-idle.py b/examples/foundational/17-detect-user-idle.py index a7d7c6f69..cf6763ab8 100644 --- a/examples/foundational/17-detect-user-idle.py +++ b/examples/foundational/17-detect-user-idle.py @@ -12,7 +12,6 @@ from loguru import logger from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3 from pipecat.audio.vad.silero import SileroVADAnalyzer -from pipecat.audio.vad.vad_analyzer import VADParams from pipecat.frames.frames import ( EndTaskFrame, LLMMessagesAppendFrame, @@ -123,7 +122,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): stop=[TurnAnalyzerUserTurnStopStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3())] ), user_idle_timeout=5.0, # Detect user idle after 5 seconds - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), + vad_analyzer=SileroVADAnalyzer(), ), ) diff --git a/examples/foundational/20a-persistent-context-openai.py b/examples/foundational/20a-persistent-context-openai.py index a98a7cd36..612a602b6 100644 --- a/examples/foundational/20a-persistent-context-openai.py +++ b/examples/foundational/20a-persistent-context-openai.py @@ -16,7 +16,6 @@ from pipecat.adapters.schemas.function_schema import FunctionSchema from pipecat.adapters.schemas.tools_schema import ToolsSchema from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3 from pipecat.audio.vad.silero import SileroVADAnalyzer -from pipecat.audio.vad.vad_analyzer import VADParams from pipecat.frames.frames import LLMRunFrame, TTSSpeakFrame from pipecat.pipeline.pipeline import Pipeline from pipecat.pipeline.runner import PipelineRunner @@ -203,7 +202,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): user_turn_strategies=UserTurnStrategies( stop=[TurnAnalyzerUserTurnStopStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3())] ), - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), + vad_analyzer=SileroVADAnalyzer(), ), ) diff --git a/examples/foundational/20c-persistent-context-anthropic.py b/examples/foundational/20c-persistent-context-anthropic.py index ae38ee7b7..f279c595f 100644 --- a/examples/foundational/20c-persistent-context-anthropic.py +++ b/examples/foundational/20c-persistent-context-anthropic.py @@ -16,7 +16,6 @@ from pipecat.adapters.schemas.function_schema import FunctionSchema from pipecat.adapters.schemas.tools_schema import ToolsSchema from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3 from pipecat.audio.vad.silero import SileroVADAnalyzer -from pipecat.audio.vad.vad_analyzer import VADParams from pipecat.frames.frames import LLMRunFrame, TTSSpeakFrame from pipecat.pipeline.pipeline import Pipeline from pipecat.pipeline.runner import PipelineRunner @@ -214,7 +213,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): user_turn_strategies=UserTurnStrategies( stop=[TurnAnalyzerUserTurnStopStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3())] ), - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), + vad_analyzer=SileroVADAnalyzer(), ), ) diff --git a/examples/foundational/20d-persistent-context-gemini.py b/examples/foundational/20d-persistent-context-gemini.py index 145fe1151..3d38d0381 100644 --- a/examples/foundational/20d-persistent-context-gemini.py +++ b/examples/foundational/20d-persistent-context-gemini.py @@ -16,7 +16,6 @@ from pipecat.adapters.schemas.function_schema import FunctionSchema from pipecat.adapters.schemas.tools_schema import ToolsSchema from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3 from pipecat.audio.vad.silero import SileroVADAnalyzer -from pipecat.audio.vad.vad_analyzer import VADParams from pipecat.frames.frames import LLMRunFrame, UserImageRequestFrame from pipecat.pipeline.pipeline import Pipeline from pipecat.pipeline.runner import PipelineRunner @@ -281,7 +280,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): user_turn_strategies=UserTurnStrategies( stop=[TurnAnalyzerUserTurnStopStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3())] ), - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), + vad_analyzer=SileroVADAnalyzer(), ), ) diff --git a/examples/foundational/21-tavus-transport.py b/examples/foundational/21-tavus-transport.py index b4f5c159a..f6948849d 100644 --- a/examples/foundational/21-tavus-transport.py +++ b/examples/foundational/21-tavus-transport.py @@ -14,7 +14,6 @@ from loguru import logger from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3 from pipecat.audio.vad.silero import SileroVADAnalyzer -from pipecat.audio.vad.vad_analyzer import VADParams from pipecat.frames.frames import LLMRunFrame from pipecat.pipeline.pipeline import Pipeline from pipecat.pipeline.runner import PipelineRunner @@ -48,7 +47,7 @@ async def main(): audio_in_enabled=True, audio_out_enabled=True, microphone_out_enabled=False, - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), + vad_analyzer=SileroVADAnalyzer(), ), ) diff --git a/examples/foundational/21a-tavus-video-service.py b/examples/foundational/21a-tavus-video-service.py index e9446975b..9d32754b6 100644 --- a/examples/foundational/21a-tavus-video-service.py +++ b/examples/foundational/21a-tavus-video-service.py @@ -13,7 +13,6 @@ from loguru import logger from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3 from pipecat.audio.vad.silero import SileroVADAnalyzer -from pipecat.audio.vad.vad_analyzer import VADParams from pipecat.frames.frames import LLMRunFrame from pipecat.pipeline.pipeline import Pipeline from pipecat.pipeline.runner import PipelineRunner @@ -92,7 +91,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): TurnAnalyzerUserTurnStopStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3()) ] ), - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), + vad_analyzer=SileroVADAnalyzer(), ), ) diff --git a/examples/foundational/22-filter-incomplete-turns.py b/examples/foundational/22-filter-incomplete-turns.py index 27e37901f..50f05ff84 100644 --- a/examples/foundational/22-filter-incomplete-turns.py +++ b/examples/foundational/22-filter-incomplete-turns.py @@ -23,7 +23,6 @@ from loguru import logger from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3 from pipecat.audio.vad.silero import SileroVADAnalyzer -from pipecat.audio.vad.vad_analyzer import VADParams from pipecat.frames.frames import LLMRunFrame from pipecat.pipeline.pipeline import Pipeline from pipecat.pipeline.runner import PipelineRunner @@ -93,7 +92,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): user_turn_strategies=UserTurnStrategies( stop=[TurnAnalyzerUserTurnStopStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3())] ), - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), + vad_analyzer=SileroVADAnalyzer(), # Enable turn completion filtering - the LLM will output: # ✓ = complete (respond normally) # ○ = incomplete short (wait 5s, then prompt) diff --git a/examples/foundational/23-bot-background-sound.py b/examples/foundational/23-bot-background-sound.py index 75f9a3b21..6254ad169 100644 --- a/examples/foundational/23-bot-background-sound.py +++ b/examples/foundational/23-bot-background-sound.py @@ -14,7 +14,6 @@ from loguru import logger from pipecat.audio.mixers.soundfile_mixer import SoundfileMixer from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3 from pipecat.audio.vad.silero import SileroVADAnalyzer -from pipecat.audio.vad.vad_analyzer import VADParams from pipecat.frames.frames import LLMRunFrame, MixerEnableFrame, MixerUpdateSettingsFrame from pipecat.pipeline.pipeline import Pipeline from pipecat.pipeline.runner import PipelineRunner @@ -52,7 +51,7 @@ transport_params = { default_sound="office", volume=2.0, ), - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), + vad_analyzer=SileroVADAnalyzer(), ), "twilio": lambda: FastAPIWebsocketParams( audio_in_enabled=True, @@ -62,7 +61,7 @@ transport_params = { default_sound="office", volume=2.0, ), - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), + vad_analyzer=SileroVADAnalyzer(), ), "webrtc": lambda: TransportParams( audio_in_enabled=True, @@ -72,7 +71,7 @@ transport_params = { default_sound="office", volume=2.0, ), - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), + vad_analyzer=SileroVADAnalyzer(), ), } diff --git a/examples/foundational/24-user-mute-strategy.py b/examples/foundational/24-user-mute-strategy.py index e55d8c3cb..7f50c38a5 100644 --- a/examples/foundational/24-user-mute-strategy.py +++ b/examples/foundational/24-user-mute-strategy.py @@ -15,7 +15,6 @@ from pipecat.adapters.schemas.function_schema import FunctionSchema from pipecat.adapters.schemas.tools_schema import ToolsSchema from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3 from pipecat.audio.vad.silero import SileroVADAnalyzer -from pipecat.audio.vad.vad_analyzer import VADParams from pipecat.frames.frames import LLMRunFrame from pipecat.pipeline.pipeline import Pipeline from pipecat.pipeline.runner import PipelineRunner @@ -116,7 +115,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): MuteUntilFirstBotCompleteUserMuteStrategy(), FunctionCallUserMuteStrategy(), ], - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), + vad_analyzer=SileroVADAnalyzer(), ), ) diff --git a/examples/foundational/27-simli-layer.py b/examples/foundational/27-simli-layer.py index 7176b2a51..317a4b5ca 100644 --- a/examples/foundational/27-simli-layer.py +++ b/examples/foundational/27-simli-layer.py @@ -12,7 +12,6 @@ from loguru import logger from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3 from pipecat.audio.vad.silero import SileroVADAnalyzer -from pipecat.audio.vad.vad_analyzer import VADParams from pipecat.frames.frames import LLMRunFrame from pipecat.pipeline.pipeline import Pipeline from pipecat.pipeline.runner import PipelineRunner @@ -88,7 +87,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): user_turn_strategies=UserTurnStrategies( stop=[TurnAnalyzerUserTurnStopStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3())] ), - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), + vad_analyzer=SileroVADAnalyzer(), ), ) diff --git a/examples/foundational/28-user-assistant-turns.py b/examples/foundational/28-user-assistant-turns.py index 5d380cfc0..70bfc81c5 100644 --- a/examples/foundational/28-user-assistant-turns.py +++ b/examples/foundational/28-user-assistant-turns.py @@ -12,7 +12,6 @@ from loguru import logger from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3 from pipecat.audio.vad.silero import SileroVADAnalyzer -from pipecat.audio.vad.vad_analyzer import VADParams from pipecat.frames.frames import LLMRunFrame from pipecat.pipeline.pipeline import Pipeline from pipecat.pipeline.runner import PipelineRunner @@ -145,7 +144,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): user_turn_strategies=UserTurnStrategies( stop=[TurnAnalyzerUserTurnStopStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3())] ), - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), + vad_analyzer=SileroVADAnalyzer(), ), ) diff --git a/examples/foundational/29-turn-tracking-observer.py b/examples/foundational/29-turn-tracking-observer.py index 272254eb6..abff15cd2 100644 --- a/examples/foundational/29-turn-tracking-observer.py +++ b/examples/foundational/29-turn-tracking-observer.py @@ -12,7 +12,6 @@ from loguru import logger from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3 from pipecat.audio.vad.silero import SileroVADAnalyzer -from pipecat.audio.vad.vad_analyzer import VADParams from pipecat.frames.frames import LLMRunFrame from pipecat.observers.user_bot_latency_observer import UserBotLatencyObserver from pipecat.pipeline.pipeline import Pipeline @@ -80,7 +79,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): user_turn_strategies=UserTurnStrategies( stop=[TurnAnalyzerUserTurnStopStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3())] ), - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), + vad_analyzer=SileroVADAnalyzer(), ), ) diff --git a/examples/foundational/30-observer.py b/examples/foundational/30-observer.py index 4d1567eed..4951bfe96 100644 --- a/examples/foundational/30-observer.py +++ b/examples/foundational/30-observer.py @@ -12,7 +12,6 @@ from loguru import logger from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3 from pipecat.audio.vad.silero import SileroVADAnalyzer -from pipecat.audio.vad.vad_analyzer import VADParams from pipecat.frames.frames import ( BotStartedSpeakingFrame, BotStoppedSpeakingFrame, @@ -127,7 +126,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): user_turn_strategies=UserTurnStrategies( stop=[TurnAnalyzerUserTurnStopStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3())] ), - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), + vad_analyzer=SileroVADAnalyzer(), ), ) diff --git a/examples/foundational/32-gemini-grounding-metadata.py b/examples/foundational/32-gemini-grounding-metadata.py index 910498800..cb215bfa9 100644 --- a/examples/foundational/32-gemini-grounding-metadata.py +++ b/examples/foundational/32-gemini-grounding-metadata.py @@ -14,7 +14,6 @@ from loguru import logger from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3 from pipecat.audio.vad.silero import SileroVADAnalyzer -from pipecat.audio.vad.vad_analyzer import VADParams from pipecat.frames.frames import LLMRunFrame from pipecat.observers.base_observer import BaseObserver, FramePushed from pipecat.pipeline.pipeline import Pipeline @@ -127,7 +126,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): user_turn_strategies=UserTurnStrategies( stop=[TurnAnalyzerUserTurnStopStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3())] ), - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), + vad_analyzer=SileroVADAnalyzer(), ), ) diff --git a/examples/foundational/33-gemini-rag.py b/examples/foundational/33-gemini-rag.py index c8ad5eb97..1200bbbab 100644 --- a/examples/foundational/33-gemini-rag.py +++ b/examples/foundational/33-gemini-rag.py @@ -59,7 +59,6 @@ from pipecat.adapters.schemas.function_schema import FunctionSchema from pipecat.adapters.schemas.tools_schema import ToolsSchema from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3 from pipecat.audio.vad.silero import SileroVADAnalyzer -from pipecat.audio.vad.vad_analyzer import VADParams from pipecat.frames.frames import LLMRunFrame from pipecat.pipeline.pipeline import Pipeline from pipecat.pipeline.runner import PipelineRunner @@ -228,7 +227,7 @@ Your response will be turned into speech so use only simple words and punctuatio user_turn_strategies=UserTurnStrategies( stop=[TurnAnalyzerUserTurnStopStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3())] ), - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), + vad_analyzer=SileroVADAnalyzer(), ), ) diff --git a/examples/foundational/34-audio-recording.py b/examples/foundational/34-audio-recording.py index 687540f01..9db398ad6 100644 --- a/examples/foundational/34-audio-recording.py +++ b/examples/foundational/34-audio-recording.py @@ -52,7 +52,6 @@ from loguru import logger from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3 from pipecat.audio.vad.silero import SileroVADAnalyzer -from pipecat.audio.vad.vad_analyzer import VADParams from pipecat.frames.frames import LLMRunFrame from pipecat.pipeline.pipeline import Pipeline from pipecat.pipeline.runner import PipelineRunner @@ -138,7 +137,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): user_turn_strategies=UserTurnStrategies( stop=[TurnAnalyzerUserTurnStopStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3())] ), - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), + vad_analyzer=SileroVADAnalyzer(), ), ) diff --git a/examples/foundational/35-pattern-pair-voice-switching.py b/examples/foundational/35-pattern-pair-voice-switching.py index 26a346ae4..f56043046 100644 --- a/examples/foundational/35-pattern-pair-voice-switching.py +++ b/examples/foundational/35-pattern-pair-voice-switching.py @@ -46,7 +46,6 @@ from loguru import logger from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3 from pipecat.audio.vad.silero import SileroVADAnalyzer -from pipecat.audio.vad.vad_analyzer import VADParams from pipecat.frames.frames import LLMRunFrame from pipecat.pipeline.pipeline import Pipeline from pipecat.pipeline.runner import PipelineRunner @@ -203,7 +202,7 @@ Remember: Use narrator voice for EVERYTHING except the actual quoted dialogue."" user_turn_strategies=UserTurnStrategies( stop=[TurnAnalyzerUserTurnStopStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3())] ), - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), + vad_analyzer=SileroVADAnalyzer(), ), ) diff --git a/examples/foundational/36-user-email-gathering.py b/examples/foundational/36-user-email-gathering.py index 64bd72bcd..22b878121 100644 --- a/examples/foundational/36-user-email-gathering.py +++ b/examples/foundational/36-user-email-gathering.py @@ -14,7 +14,6 @@ from pipecat.adapters.schemas.function_schema import FunctionSchema from pipecat.adapters.schemas.tools_schema import ToolsSchema from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3 from pipecat.audio.vad.silero import SileroVADAnalyzer -from pipecat.audio.vad.vad_analyzer import VADParams from pipecat.frames.frames import LLMRunFrame from pipecat.pipeline.pipeline import Pipeline from pipecat.pipeline.runner import PipelineRunner @@ -119,7 +118,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): user_turn_strategies=UserTurnStrategies( stop=[TurnAnalyzerUserTurnStopStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3())] ), - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), + vad_analyzer=SileroVADAnalyzer(), ), ) diff --git a/examples/foundational/37-mem0.py b/examples/foundational/37-mem0.py index f8ee7079e..214f5a6d7 100644 --- a/examples/foundational/37-mem0.py +++ b/examples/foundational/37-mem0.py @@ -49,7 +49,6 @@ from loguru import logger from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3 from pipecat.audio.vad.silero import SileroVADAnalyzer -from pipecat.audio.vad.vad_analyzer import VADParams from pipecat.frames.frames import LLMRunFrame from pipecat.pipeline.pipeline import Pipeline from pipecat.pipeline.runner import PipelineRunner @@ -248,7 +247,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): user_turn_strategies=UserTurnStrategies( stop=[TurnAnalyzerUserTurnStopStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3())] ), - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), + vad_analyzer=SileroVADAnalyzer(), ), ) diff --git a/examples/foundational/38-smart-turn-fal.py b/examples/foundational/38-smart-turn-fal.py index 8af8b58f8..ed4bfbae8 100644 --- a/examples/foundational/38-smart-turn-fal.py +++ b/examples/foundational/38-smart-turn-fal.py @@ -13,7 +13,6 @@ from loguru import logger from pipecat.audio.turn.smart_turn.fal_smart_turn import FalSmartTurnAnalyzer from pipecat.audio.vad.silero import SileroVADAnalyzer -from pipecat.audio.vad.vad_analyzer import VADParams from pipecat.frames.frames import LLMRunFrame from pipecat.pipeline.pipeline import Pipeline from pipecat.pipeline.runner import PipelineRunner @@ -88,7 +87,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): ) ] ), - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), + vad_analyzer=SileroVADAnalyzer(), ), ) diff --git a/examples/foundational/38a-smart-turn-local-coreml.py b/examples/foundational/38a-smart-turn-local-coreml.py index e2796d6a6..4284c675c 100644 --- a/examples/foundational/38a-smart-turn-local-coreml.py +++ b/examples/foundational/38a-smart-turn-local-coreml.py @@ -12,7 +12,6 @@ from loguru import logger from pipecat.audio.turn.smart_turn.local_coreml_smart_turn import LocalCoreMLSmartTurnAnalyzer from pipecat.audio.vad.silero import SileroVADAnalyzer -from pipecat.audio.vad.vad_analyzer import VADParams from pipecat.frames.frames import LLMRunFrame from pipecat.pipeline.pipeline import Pipeline from pipecat.pipeline.runner import PipelineRunner @@ -102,7 +101,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): ) ] ), - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), + vad_analyzer=SileroVADAnalyzer(), ), ) diff --git a/examples/foundational/38b-smart-turn-local.py b/examples/foundational/38b-smart-turn-local.py index 03ce79bc6..1eaf2e9c4 100644 --- a/examples/foundational/38b-smart-turn-local.py +++ b/examples/foundational/38b-smart-turn-local.py @@ -12,7 +12,6 @@ from loguru import logger from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3 from pipecat.audio.vad.silero import SileroVADAnalyzer -from pipecat.audio.vad.vad_analyzer import VADParams from pipecat.frames.frames import LLMRunFrame from pipecat.pipeline.pipeline import Pipeline from pipecat.pipeline.runner import PipelineRunner @@ -79,7 +78,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): user_turn_strategies=UserTurnStrategies( stop=[TurnAnalyzerUserTurnStopStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3())] ), - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), + vad_analyzer=SileroVADAnalyzer(), ), ) diff --git a/examples/foundational/39-mcp-stdio.py b/examples/foundational/39-mcp-stdio.py index 95237e6ad..ac39d4b59 100644 --- a/examples/foundational/39-mcp-stdio.py +++ b/examples/foundational/39-mcp-stdio.py @@ -19,7 +19,6 @@ from PIL import Image from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3 from pipecat.audio.vad.silero import SileroVADAnalyzer -from pipecat.audio.vad.vad_analyzer import VADParams from pipecat.frames.frames import ( Frame, FunctionCallResultFrame, @@ -197,7 +196,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): TurnAnalyzerUserTurnStopStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3()) ] ), - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), + vad_analyzer=SileroVADAnalyzer(), ), ) diff --git a/examples/foundational/39a-mcp-streamable-http.py b/examples/foundational/39a-mcp-streamable-http.py index 27b9e5a36..828c22d1f 100644 --- a/examples/foundational/39a-mcp-streamable-http.py +++ b/examples/foundational/39a-mcp-streamable-http.py @@ -13,7 +13,6 @@ from mcp.client.session_group import StreamableHttpParameters from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3 from pipecat.audio.vad.silero import SileroVADAnalyzer -from pipecat.audio.vad.vad_analyzer import VADParams from pipecat.frames.frames import LLMRunFrame from pipecat.pipeline.pipeline import Pipeline from pipecat.pipeline.runner import PipelineRunner @@ -107,7 +106,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): user_turn_strategies=UserTurnStrategies( stop=[TurnAnalyzerUserTurnStopStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3())] ), - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), + vad_analyzer=SileroVADAnalyzer(), ), ) diff --git a/examples/foundational/39b-mcp-streamable-http-gemini-live.py b/examples/foundational/39b-mcp-streamable-http-gemini-live.py index 38ac36f8f..d124f30ac 100644 --- a/examples/foundational/39b-mcp-streamable-http-gemini-live.py +++ b/examples/foundational/39b-mcp-streamable-http-gemini-live.py @@ -13,7 +13,6 @@ from mcp.client.session_group import StreamableHttpParameters from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3 from pipecat.audio.vad.silero import SileroVADAnalyzer -from pipecat.audio.vad.vad_analyzer import VADParams from pipecat.frames.frames import LLMRunFrame from pipecat.pipeline.pipeline import Pipeline from pipecat.pipeline.runner import PipelineRunner @@ -111,7 +110,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): user_turn_strategies=UserTurnStrategies( stop=[TurnAnalyzerUserTurnStopStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3())] ), - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), + vad_analyzer=SileroVADAnalyzer(), ), ) diff --git a/examples/foundational/39c-multiple-mcp.py b/examples/foundational/39c-multiple-mcp.py index bb3dbd953..e06a5888b 100644 --- a/examples/foundational/39c-multiple-mcp.py +++ b/examples/foundational/39c-multiple-mcp.py @@ -21,7 +21,6 @@ from PIL import Image from pipecat.adapters.schemas.tools_schema import ToolsSchema from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3 from pipecat.audio.vad.silero import SileroVADAnalyzer -from pipecat.audio.vad.vad_analyzer import VADParams from pipecat.frames.frames import ( Frame, FunctionCallResultFrame, @@ -197,7 +196,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): TurnAnalyzerUserTurnStopStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3()) ] ), - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), + vad_analyzer=SileroVADAnalyzer(), ), ) mcp_image_processor = UrlToImageProcessor(aiohttp_session=session) diff --git a/examples/foundational/42-interruption-config.py b/examples/foundational/42-interruption-config.py index f4279e80f..a45fc14a5 100644 --- a/examples/foundational/42-interruption-config.py +++ b/examples/foundational/42-interruption-config.py @@ -11,7 +11,6 @@ from loguru import logger from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3 from pipecat.audio.vad.silero import SileroVADAnalyzer -from pipecat.audio.vad.vad_analyzer import VADParams from pipecat.frames.frames import LLMRunFrame from pipecat.observers.loggers.transcription_log_observer import TranscriptionLogObserver from pipecat.pipeline.pipeline import Pipeline @@ -82,7 +81,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): start=[MinWordsUserTurnStartStrategy(min_words=3)], stop=[TurnAnalyzerUserTurnStopStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3())], ), - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), + vad_analyzer=SileroVADAnalyzer(), ), ) diff --git a/examples/foundational/43-heygen-transport.py b/examples/foundational/43-heygen-transport.py index 42f44c3f9..d5059b55e 100644 --- a/examples/foundational/43-heygen-transport.py +++ b/examples/foundational/43-heygen-transport.py @@ -14,7 +14,6 @@ from loguru import logger from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3 from pipecat.audio.vad.silero import SileroVADAnalyzer -from pipecat.audio.vad.vad_analyzer import VADParams from pipecat.frames.frames import LLMRunFrame from pipecat.pipeline.pipeline import Pipeline from pipecat.pipeline.runner import PipelineRunner @@ -46,7 +45,7 @@ async def main(): params=HeyGenParams( audio_in_enabled=True, audio_out_enabled=True, - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), + vad_analyzer=SileroVADAnalyzer(), ), ) diff --git a/examples/foundational/43a-heygen-video-service.py b/examples/foundational/43a-heygen-video-service.py index 294e907bf..dd38d7084 100644 --- a/examples/foundational/43a-heygen-video-service.py +++ b/examples/foundational/43a-heygen-video-service.py @@ -12,7 +12,6 @@ from loguru import logger from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3 from pipecat.audio.vad.silero import SileroVADAnalyzer -from pipecat.audio.vad.vad_analyzer import VADParams from pipecat.frames.frames import LLMRunFrame from pipecat.pipeline.pipeline import Pipeline from pipecat.pipeline.runner import PipelineRunner @@ -93,7 +92,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): TurnAnalyzerUserTurnStopStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3()) ] ), - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), + vad_analyzer=SileroVADAnalyzer(), ), ) diff --git a/examples/foundational/44-voicemail-detection.py b/examples/foundational/44-voicemail-detection.py index 1ab1cdf7f..76fd95d61 100644 --- a/examples/foundational/44-voicemail-detection.py +++ b/examples/foundational/44-voicemail-detection.py @@ -11,7 +11,6 @@ from loguru import logger from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3 from pipecat.audio.vad.silero import SileroVADAnalyzer -from pipecat.audio.vad.vad_analyzer import VADParams from pipecat.extensions.voicemail.voicemail_detector import VoicemailDetector from pipecat.frames.frames import TTSSpeakFrame from pipecat.pipeline.pipeline import Pipeline @@ -82,7 +81,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): user_turn_strategies=UserTurnStrategies( stop=[TurnAnalyzerUserTurnStopStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3())] ), - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), + vad_analyzer=SileroVADAnalyzer(), ), ) diff --git a/examples/foundational/45-before-and-after-events.py b/examples/foundational/45-before-and-after-events.py index 4664979e1..ab02d3fd4 100644 --- a/examples/foundational/45-before-and-after-events.py +++ b/examples/foundational/45-before-and-after-events.py @@ -12,7 +12,6 @@ from loguru import logger from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3 from pipecat.audio.vad.silero import SileroVADAnalyzer -from pipecat.audio.vad.vad_analyzer import VADParams from pipecat.frames.frames import DataFrame, LLMRunFrame from pipecat.pipeline.pipeline import Pipeline from pipecat.pipeline.runner import PipelineRunner @@ -90,7 +89,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): user_turn_strategies=UserTurnStrategies( stop=[TurnAnalyzerUserTurnStopStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3())] ), - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), + vad_analyzer=SileroVADAnalyzer(), ), ) diff --git a/examples/foundational/46-video-processing.py b/examples/foundational/46-video-processing.py index ee490bfce..dea8ce30e 100644 --- a/examples/foundational/46-video-processing.py +++ b/examples/foundational/46-video-processing.py @@ -12,7 +12,6 @@ from loguru import logger from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3 from pipecat.audio.vad.silero import SileroVADAnalyzer -from pipecat.audio.vad.vad_analyzer import VADParams from pipecat.frames.frames import Frame, InputImageRawFrame, LLMRunFrame, OutputImageRawFrame from pipecat.pipeline.pipeline import Pipeline from pipecat.pipeline.runner import PipelineRunner @@ -120,7 +119,7 @@ async def run_bot(pipecat_transport): user_turn_strategies=UserTurnStrategies( stop=[TurnAnalyzerUserTurnStopStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3())] ), - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), + vad_analyzer=SileroVADAnalyzer(), ), ) diff --git a/examples/foundational/47-sentry-metrics.py b/examples/foundational/47-sentry-metrics.py index 85196f10a..013337f59 100644 --- a/examples/foundational/47-sentry-metrics.py +++ b/examples/foundational/47-sentry-metrics.py @@ -12,7 +12,6 @@ from loguru import logger from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3 from pipecat.audio.vad.silero import SileroVADAnalyzer -from pipecat.audio.vad.vad_analyzer import VADParams from pipecat.frames.frames import LLMRunFrame from pipecat.pipeline.pipeline import Pipeline from pipecat.pipeline.runner import PipelineRunner @@ -93,7 +92,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): user_turn_strategies=UserTurnStrategies( stop=[TurnAnalyzerUserTurnStopStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3())] ), - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), + vad_analyzer=SileroVADAnalyzer(), ), ) diff --git a/examples/foundational/48-service-switcher.py b/examples/foundational/48-service-switcher.py index e2b796018..eb75791ea 100644 --- a/examples/foundational/48-service-switcher.py +++ b/examples/foundational/48-service-switcher.py @@ -14,7 +14,6 @@ from pipecat.adapters.schemas.function_schema import FunctionSchema from pipecat.adapters.schemas.tools_schema import ToolsSchema from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3 from pipecat.audio.vad.silero import SileroVADAnalyzer -from pipecat.audio.vad.vad_analyzer import VADParams from pipecat.frames.frames import LLMRunFrame, ManuallySwitchServiceFrame from pipecat.pipeline.llm_switcher import LLMSwitcher from pipecat.pipeline.pipeline import Pipeline @@ -138,7 +137,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): user_turn_strategies=UserTurnStrategies( stop=[TurnAnalyzerUserTurnStopStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3())] ), - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), + vad_analyzer=SileroVADAnalyzer(), ), ) diff --git a/examples/foundational/49a-thinking-anthropic.py b/examples/foundational/49a-thinking-anthropic.py index 521a92282..6a14b43f2 100644 --- a/examples/foundational/49a-thinking-anthropic.py +++ b/examples/foundational/49a-thinking-anthropic.py @@ -11,7 +11,6 @@ from loguru import logger from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3 from pipecat.audio.vad.silero import SileroVADAnalyzer -from pipecat.audio.vad.vad_analyzer import VADParams from pipecat.frames.frames import LLMRunFrame from pipecat.pipeline.pipeline import Pipeline from pipecat.pipeline.runner import PipelineRunner @@ -84,7 +83,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): user_turn_strategies=UserTurnStrategies( stop=[TurnAnalyzerUserTurnStopStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3())] ), - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), + vad_analyzer=SileroVADAnalyzer(), ), ) diff --git a/examples/foundational/49b-thinking-google.py b/examples/foundational/49b-thinking-google.py index 223a77e1e..75c60d4b3 100644 --- a/examples/foundational/49b-thinking-google.py +++ b/examples/foundational/49b-thinking-google.py @@ -11,7 +11,6 @@ from loguru import logger from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3 from pipecat.audio.vad.silero import SileroVADAnalyzer -from pipecat.audio.vad.vad_analyzer import VADParams from pipecat.frames.frames import LLMRunFrame from pipecat.pipeline.pipeline import Pipeline from pipecat.pipeline.runner import PipelineRunner @@ -89,7 +88,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): user_turn_strategies=UserTurnStrategies( stop=[TurnAnalyzerUserTurnStopStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3())] ), - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), + vad_analyzer=SileroVADAnalyzer(), ), ) diff --git a/examples/foundational/49c-thinking-functions-anthropic.py b/examples/foundational/49c-thinking-functions-anthropic.py index baa13b5d1..de382a9ad 100644 --- a/examples/foundational/49c-thinking-functions-anthropic.py +++ b/examples/foundational/49c-thinking-functions-anthropic.py @@ -12,7 +12,6 @@ from loguru import logger from pipecat.adapters.schemas.tools_schema import ToolsSchema from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3 from pipecat.audio.vad.silero import SileroVADAnalyzer -from pipecat.audio.vad.vad_analyzer import VADParams from pipecat.frames.frames import LLMRunFrame from pipecat.pipeline.pipeline import Pipeline from pipecat.pipeline.runner import PipelineRunner @@ -110,7 +109,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): user_turn_strategies=UserTurnStrategies( stop=[TurnAnalyzerUserTurnStopStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3())] ), - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), + vad_analyzer=SileroVADAnalyzer(), ), ) diff --git a/examples/foundational/49d-thinking-functions-google.py b/examples/foundational/49d-thinking-functions-google.py index c03b37c0d..4cea483c0 100644 --- a/examples/foundational/49d-thinking-functions-google.py +++ b/examples/foundational/49d-thinking-functions-google.py @@ -12,7 +12,6 @@ from loguru import logger from pipecat.adapters.schemas.tools_schema import ToolsSchema from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3 from pipecat.audio.vad.silero import SileroVADAnalyzer -from pipecat.audio.vad.vad_analyzer import VADParams from pipecat.frames.frames import LLMRunFrame from pipecat.pipeline.pipeline import Pipeline from pipecat.pipeline.runner import PipelineRunner @@ -115,7 +114,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): user_turn_strategies=UserTurnStrategies( stop=[TurnAnalyzerUserTurnStopStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3())] ), - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), + vad_analyzer=SileroVADAnalyzer(), ), ) diff --git a/examples/foundational/52-live-translation.py b/examples/foundational/52-live-translation.py index 6545d64c3..18195ef1d 100644 --- a/examples/foundational/52-live-translation.py +++ b/examples/foundational/52-live-translation.py @@ -12,7 +12,6 @@ from loguru import logger from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3 from pipecat.audio.vad.silero import SileroVADAnalyzer -from pipecat.audio.vad.vad_analyzer import VADParams from pipecat.pipeline.pipeline import Pipeline from pipecat.pipeline.runner import PipelineRunner from pipecat.pipeline.task import PipelineParams, PipelineTask @@ -86,7 +85,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): start=[TranscriptionUserTurnStartStrategy(enable_interruptions=False)], stop=[TurnAnalyzerUserTurnStopStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3())], ), - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), + vad_analyzer=SileroVADAnalyzer(), ), ) diff --git a/examples/foundational/53-concurrent-llm-evaluation.py b/examples/foundational/53-concurrent-llm-evaluation.py index 7aff957a5..9e0fa73ad 100644 --- a/examples/foundational/53-concurrent-llm-evaluation.py +++ b/examples/foundational/53-concurrent-llm-evaluation.py @@ -12,7 +12,6 @@ from loguru import logger from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3 from pipecat.audio.vad.silero import SileroVADAnalyzer -from pipecat.audio.vad.vad_analyzer import VADParams from pipecat.frames.frames import LLMRunFrame from pipecat.pipeline.parallel_pipeline import ParallelPipeline from pipecat.pipeline.pipeline import Pipeline @@ -95,7 +94,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): # across multiple parallel aggregators. The VADProcessor emits # VADUserStartedSpeakingFrame and VADUserStoppedSpeakingFrame which the # UserTurnProcessor needs to manage turn lifecycle. - vad_processor = VADProcessor(vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2))) + vad_processor = VADProcessor(vad_analyzer=SileroVADAnalyzer()) # We use this external user turn processor. This processor will push # UserStartedSpeakingFrame and UserStoppedSpeakingFrame as well as diff --git a/src/pipecat/audio/vad/vad_analyzer.py b/src/pipecat/audio/vad/vad_analyzer.py index 254b0619e..2c3ef5531 100644 --- a/src/pipecat/audio/vad/vad_analyzer.py +++ b/src/pipecat/audio/vad/vad_analyzer.py @@ -24,7 +24,7 @@ from pipecat.audio.utils import calculate_audio_volume, exp_smoothing VAD_CONFIDENCE = 0.7 VAD_START_SECS = 0.2 -VAD_STOP_SECS = 0.8 +VAD_STOP_SECS = 0.2 VAD_MIN_VOLUME = 0.6 From f3d99adf8f45c57234d52adbab0299c25dfa8d9d Mon Sep 17 00:00:00 2001 From: Ian Lee Date: Fri, 6 Feb 2026 12:43:23 -0800 Subject: [PATCH 0389/1060] [inworld] aggregate_sentence mode needs trailing space --- changelog/3667.fixed.md | 1 + src/pipecat/services/inworld/tts.py | 3 +++ 2 files changed, 4 insertions(+) create mode 100644 changelog/3667.fixed.md diff --git a/changelog/3667.fixed.md b/changelog/3667.fixed.md new file mode 100644 index 000000000..1a83c0125 --- /dev/null +++ b/changelog/3667.fixed.md @@ -0,0 +1 @@ +- Fixed an issue in `InworldTTSService` where punctuation was pronounced. Now, the `InworldTTSService` ensures proper spacing between sentences, resolving pronunciation issues. \ No newline at end of file diff --git a/src/pipecat/services/inworld/tts.py b/src/pipecat/services/inworld/tts.py index fee6c49ac..d8798b75e 100644 --- a/src/pipecat/services/inworld/tts.py +++ b/src/pipecat/services/inworld/tts.py @@ -439,6 +439,7 @@ class InworldTTSService(AudioContextWordTTSService): encoding: str = "LINEAR16", params: InputParams = None, aggregate_sentences: bool = True, + append_trailing_space: bool = True, **kwargs: Any, ): """Initialize the Inworld WebSocket TTS service. @@ -452,6 +453,7 @@ class InworldTTSService(AudioContextWordTTSService): encoding: Audio encoding format. params: Input parameters for Inworld WebSocket TTS configuration. aggregate_sentences: Whether to aggregate sentences before synthesis. + append_trailing_space: Whether to append a trailing space to text before sending to TTS. **kwargs: Additional arguments passed to the parent class. """ super().__init__( @@ -460,6 +462,7 @@ class InworldTTSService(AudioContextWordTTSService): pause_frame_processing=True, sample_rate=sample_rate, aggregate_sentences=aggregate_sentences, + append_trailing_space=append_trailing_space, **kwargs, ) From 3494a94cac33009e3f45c626019c9af48dd4e891 Mon Sep 17 00:00:00 2001 From: Mark Backman Date: Sun, 8 Feb 2026 11:06:48 -0500 Subject: [PATCH 0390/1060] Add Claude code-review skill --- .claude/skills/code-review/SKILL.md | 107 ++++++++++++++++++++++++++++ 1 file changed, 107 insertions(+) create mode 100644 .claude/skills/code-review/SKILL.md diff --git a/.claude/skills/code-review/SKILL.md b/.claude/skills/code-review/SKILL.md new file mode 100644 index 000000000..036a7f935 --- /dev/null +++ b/.claude/skills/code-review/SKILL.md @@ -0,0 +1,107 @@ +--- +name: code-review +description: Automated code review for pull requests using multiple specialized agents +disable-model-invocation: true +allowed-tools: Bash(gh issue view:*), Bash(gh search:*), Bash(gh issue list:*), Bash(gh pr comment:*), Bash(gh pr diff:*), Bash(gh pr view:*), Bash(gh pr list:*) +--- + +Provide a code review for the given pull request. + +**Agent assumptions (applies to all agents and subagents):** + +- All tools are functional and will work without error. Do not test tools or make exploratory calls. Make sure this is clear to every subagent that is launched. +- Only call a tool if it is required to complete the task. Every tool call should have a clear purpose. + +To do this, follow these steps precisely: + +1. Launch a haiku agent to check if any of the following are true: + - The pull request is closed + - The pull request is a draft + - The pull request does not need code review (e.g. automated PR, trivial change that is obviously correct) + - Claude has already commented on this PR (check `gh pr view --comments` for comments left by claude) + + If any condition is true, stop and do not proceed. + +Note: Still review Claude generated PR's. + +2. Launch a haiku agent to return a list of file paths (not their contents) for all relevant CLAUDE.md files including: + - The root CLAUDE.md file, if it exists + - Any CLAUDE.md files in directories containing files modified by the pull request + +3. Launch a sonnet agent to view the pull request and return a summary of the changes + +4. Launch 4 agents in parallel to independently review the changes. Each agent should return the list of issues, where each issue includes a description and the reason it was flagged (e.g. "CLAUDE.md adherence", "bug"). The agents should do the following: + + Agents 1 + 2: CLAUDE.md compliance sonnet agents + Audit changes for CLAUDE.md compliance in parallel. Note: When evaluating CLAUDE.md compliance for a file, you should only consider CLAUDE.md files that share a file path with the file or parents. + + Agent 3: Opus bug agent (parallel subagent with agent 4) + Scan for obvious bugs. Focus only on the diff itself without reading extra context. Flag only significant bugs; ignore nitpicks and likely false positives. Do not flag issues that you cannot validate without looking at context outside of the git diff. + + Agent 4: Opus bug agent (parallel subagent with agent 3) + Look for problems that exist in the introduced code. This could be security issues, incorrect logic, etc. Only look for issues that fall within the changed code. + + **CRITICAL: We only want HIGH SIGNAL issues.** Flag issues where: + - The code will fail to compile or parse (syntax errors, type errors, missing imports, unresolved references) + - The code will definitely produce wrong results regardless of inputs (clear logic errors) + - Clear, unambiguous CLAUDE.md violations where you can quote the exact rule being broken + + Do NOT flag: + - Code style or quality concerns + - Potential issues that depend on specific inputs or state + - Subjective suggestions or improvements + + If you are not certain an issue is real, do not flag it. False positives erode trust and waste reviewer time. + + In addition to the above, each subagent should be told the PR title and description. This will help provide context regarding the author's intent. + +5. For each issue found in the previous step by agents 3 and 4, launch parallel subagents to validate the issue. These subagents should get the PR title and description along with a description of the issue. The agent's job is to review the issue to validate that the stated issue is truly an issue with high confidence. For example, if an issue such as "variable is not defined" was flagged, the subagent's job would be to validate that is actually true in the code. Another example would be CLAUDE.md issues. The agent should validate that the CLAUDE.md rule that was violated is scoped for this file and is actually violated. Use Opus subagents for bugs and logic issues, and sonnet agents for CLAUDE.md violations. + +6. Filter out any issues that were not validated in step 5. This step will give us our list of high signal issues for our review. + +7. If issues were found, skip to step 8 to post comments. + + If NO issues were found, post a summary comment using `gh pr comment` (if `--comment` argument is provided): + "No issues found. Checked for bugs and CLAUDE.md compliance." + +8. Create a list of all comments that you plan on leaving. This is only for you to make sure you are comfortable with the comments. Do not post this list anywhere. + +9. Post inline comments for each issue using `gh pr review` with inline comments. For each comment: + - Provide a brief description of the issue + - For small, self-contained fixes, include a committable suggestion block + - For larger fixes (6+ lines, structural changes, or changes spanning multiple locations), describe the issue and suggested fix without a suggestion block + - Never post a committable suggestion UNLESS committing the suggestion fixes the issue entirely. If follow up steps are required, do not leave a committable suggestion. + + **IMPORTANT: Only post ONE comment per unique issue. Do not post duplicate comments.** + +Use this list when evaluating issues in Steps 4 and 5 (these are false positives, do NOT flag): + +- Pre-existing issues +- Something that appears to be a bug but is actually correct +- Pedantic nitpicks that a senior engineer would not flag +- Issues that a linter will catch (do not run the linter to verify) +- General code quality concerns (e.g., lack of test coverage, general security issues) unless explicitly required in CLAUDE.md +- Issues mentioned in CLAUDE.md but explicitly silenced in the code (e.g., via a lint ignore comment) + +Notes: + +- Use gh CLI to interact with GitHub (e.g., fetch pull requests, create comments). Do not use web fetch. +- Create a todo list before starting. +- You must cite and link each issue in inline comments (e.g., if referring to a CLAUDE.md, include a link to it). +- If no issues are found, post a comment with the following format: + +--- + +## Code review + +No issues found. Checked for bugs and CLAUDE.md compliance. + +--- + +- When linking to code in inline comments, follow the following format precisely, otherwise the Markdown preview won't render correctly: `https://github.com/OWNER/REPO/blob/FULL_SHA/path/to/file.py#L10-L15` + - Requires full git sha + - You must provide the full sha. Commands like `https://github.com/owner/repo/blob/$(git rev-parse HEAD)/foo/bar` will not work, since your comment will be directly rendered in Markdown. + - Repo name must match the repo you're code reviewing + - # sign after the file name + - Line range format is L[start]-L[end] + - Provide at least 1 line of context before and after, centered on the line you are commenting about (eg. if you are commenting about lines 5-6, you should link to `L4-7`) From 90ad2a4e8185f1f35fb5c8f55e9f278e8c81e43e Mon Sep 17 00:00:00 2001 From: Mark Backman Date: Sun, 8 Feb 2026 14:44:48 -0500 Subject: [PATCH 0391/1060] Remove SequentialMergePipeline --- .../pipeline/to_be_updated/merge_pipeline.py | 53 ------------------- 1 file changed, 53 deletions(-) delete mode 100644 src/pipecat/pipeline/to_be_updated/merge_pipeline.py diff --git a/src/pipecat/pipeline/to_be_updated/merge_pipeline.py b/src/pipecat/pipeline/to_be_updated/merge_pipeline.py deleted file mode 100644 index 0254b6309..000000000 --- a/src/pipecat/pipeline/to_be_updated/merge_pipeline.py +++ /dev/null @@ -1,53 +0,0 @@ -# -# Copyright (c) 2024-2026, Daily -# -# SPDX-License-Identifier: BSD 2-Clause License -# - -"""Sequential pipeline merging for Pipecat. - -This module provides a pipeline implementation that sequentially merges -the output from multiple pipelines, processing them one after another -in a specified order. -""" - -from typing import List - -from pipecat.frames.frames import EndFrame, EndPipeFrame -from pipecat.pipeline.pipeline import Pipeline - - -class SequentialMergePipeline(Pipeline): - """Pipeline that sequentially merges output from multiple pipelines. - - This pipeline merges the sink queues from a list of pipelines by processing - frames from each pipeline's sink sequentially in the order specified. Each - pipeline runs to completion before the next one begins processing. - """ - - def __init__(self, pipelines: List[Pipeline]): - """Initialize the sequential merge pipeline. - - Args: - pipelines: List of pipelines to merge sequentially. Pipelines will - be processed in the order they appear in this list. - """ - super().__init__([]) - self.pipelines = pipelines - - async def run_pipeline(self): - """Run all pipelines sequentially and merge their output. - - Processes each pipeline in order, consuming all frames from each - pipeline's sink until an EndFrame or EndPipeFrame is encountered, - then moves to the next pipeline. After all pipelines complete, - sends a final EndFrame to signal completion. - """ - for idx, pipeline in enumerate(self.pipelines): - while True: - frame = await pipeline.sink.get() - if isinstance(frame, EndFrame) or isinstance(frame, EndPipeFrame): - break - await self.sink.put(frame) - - await self.sink.put(EndFrame()) From 12f27f9cdad0e2003c27184e11a96ba3a6550ba8 Mon Sep 17 00:00:00 2001 From: Om Chauhan Date: Sun, 1 Feb 2026 19:31:49 +0530 Subject: [PATCH 0392/1060] fix(daily): queue outbound messages until transport joins --- src/pipecat/transports/daily/transport.py | 23 ++++++++++++++++++++++- 1 file changed, 22 insertions(+), 1 deletion(-) diff --git a/src/pipecat/transports/daily/transport.py b/src/pipecat/transports/daily/transport.py index 20a0be29f..37ae8a167 100644 --- a/src/pipecat/transports/daily/transport.py +++ b/src/pipecat/transports/daily/transport.py @@ -501,6 +501,8 @@ class DailyTransportClient(EventHandler): self._event_task = None self._audio_task = None self._video_task = None + self._message_queue: Optional[asyncio.Queue] = None + self._message_task = None # Input and ouput sample rates. They will be initialize on setup(). self._in_sample_rate = 0 @@ -567,7 +569,9 @@ class DailyTransportClient(EventHandler): error: An error description or None. """ if not self._joined: - return "Unable to send messages before joining." + if self._message_queue: + await self._message_queue.put((frame,)) + return None participant_id = None if isinstance( @@ -673,6 +677,12 @@ class DailyTransportClient(EventHandler): f"{self}::event_callback_task", ) + self._message_queue = asyncio.Queue() + self._message_task = self._task_manager.create_task( + self._message_task_handler(self._message_queue), + f"{self}::message_task", + ) + async def cleanup(self): """Cleanup client resources and cancel tasks.""" if self._event_task and self._task_manager: @@ -684,6 +694,9 @@ class DailyTransportClient(EventHandler): if self._video_task and self._task_manager: await self._task_manager.cancel_task(self._video_task) self._video_task = None + if self._message_task and self._task_manager: + await self._task_manager.cancel_task(self._message_task) + self._message_task = None # Make sure we don't block the event loop in case `client.release()` # takes extra time. await self._get_event_loop().run_in_executor(self._executor, self._cleanup) @@ -1541,6 +1554,14 @@ class DailyTransportClient(EventHandler): await callback(*args) queue.task_done() + async def _message_task_handler(self, queue: asyncio.Queue): + """Handle queued messages after transport is joined.""" + while True: + await self._joined_event.wait() + (frame,) = await queue.get() + await self.send_message(frame) + queue.task_done() + def _get_event_loop(self) -> asyncio.AbstractEventLoop: """Get the event loop from the task manager.""" if not self._task_manager: From 9f380170d718251a5300938cc36723a6c0117131 Mon Sep 17 00:00:00 2001 From: Om Chauhan Date: Sun, 1 Feb 2026 20:35:05 +0530 Subject: [PATCH 0393/1060] added changelog --- changelog/3615.fixed.md | 1 + 1 file changed, 1 insertion(+) create mode 100644 changelog/3615.fixed.md diff --git a/changelog/3615.fixed.md b/changelog/3615.fixed.md new file mode 100644 index 000000000..b14dfd70f --- /dev/null +++ b/changelog/3615.fixed.md @@ -0,0 +1 @@ +- Fixed race condition where `RTVIObserver` could send messages before `DailyTransport` join completed. Outbound messages are now queued & delivered after the transport is ready. From a4e187e13896cbf178f85cf522769a1cbb5e0865 Mon Sep 17 00:00:00 2001 From: Om Chauhan Date: Mon, 9 Feb 2026 06:04:08 +0530 Subject: [PATCH 0394/1060] replace background task with flush-on-join --- src/pipecat/transports/daily/transport.py | 27 +++++++---------------- 1 file changed, 8 insertions(+), 19 deletions(-) diff --git a/src/pipecat/transports/daily/transport.py b/src/pipecat/transports/daily/transport.py index 37ae8a167..a955b1c12 100644 --- a/src/pipecat/transports/daily/transport.py +++ b/src/pipecat/transports/daily/transport.py @@ -501,8 +501,7 @@ class DailyTransportClient(EventHandler): self._event_task = None self._audio_task = None self._video_task = None - self._message_queue: Optional[asyncio.Queue] = None - self._message_task = None + self._join_message_queue: list = [] # Input and ouput sample rates. They will be initialize on setup(). self._in_sample_rate = 0 @@ -569,8 +568,7 @@ class DailyTransportClient(EventHandler): error: An error description or None. """ if not self._joined: - if self._message_queue: - await self._message_queue.put((frame,)) + self._join_message_queue.append(frame) return None participant_id = None @@ -677,12 +675,6 @@ class DailyTransportClient(EventHandler): f"{self}::event_callback_task", ) - self._message_queue = asyncio.Queue() - self._message_task = self._task_manager.create_task( - self._message_task_handler(self._message_queue), - f"{self}::message_task", - ) - async def cleanup(self): """Cleanup client resources and cancel tasks.""" if self._event_task and self._task_manager: @@ -694,9 +686,6 @@ class DailyTransportClient(EventHandler): if self._video_task and self._task_manager: await self._task_manager.cancel_task(self._video_task) self._video_task = None - if self._message_task and self._task_manager: - await self._task_manager.cancel_task(self._message_task) - self._message_task = None # Make sure we don't block the event loop in case `client.release()` # takes extra time. await self._get_event_loop().run_in_executor(self._executor, self._cleanup) @@ -781,6 +770,8 @@ class DailyTransportClient(EventHandler): await self._callbacks.on_joined(data) self._joined_event.set() + + await self._flush_join_messages() else: error_msg = f"Error joining {self._room_url}: {error}" logger.error(error_msg) @@ -1554,13 +1545,11 @@ class DailyTransportClient(EventHandler): await callback(*args) queue.task_done() - async def _message_task_handler(self, queue: asyncio.Queue): - """Handle queued messages after transport is joined.""" - while True: - await self._joined_event.wait() - (frame,) = await queue.get() + async def _flush_join_messages(self): + """Send any messages that were queued before join completed.""" + for frame in self._join_message_queue: await self.send_message(frame) - queue.task_done() + self._join_message_queue.clear() def _get_event_loop(self) -> asyncio.AbstractEventLoop: """Get the event loop from the task manager.""" From 947ff03c9f023d58d59a41454c1896c49bf7290a Mon Sep 17 00:00:00 2001 From: dhruvladia-sarvam Date: Mon, 9 Feb 2026 13:04:45 +0530 Subject: [PATCH 0395/1060] v3 addition --- src/pipecat/services/sarvam/tts.py | 20 ++++++++++++++++++++ 1 file changed, 20 insertions(+) diff --git a/src/pipecat/services/sarvam/tts.py b/src/pipecat/services/sarvam/tts.py index 5feeffd72..2e767eb6a 100644 --- a/src/pipecat/services/sarvam/tts.py +++ b/src/pipecat/services/sarvam/tts.py @@ -25,6 +25,15 @@ Indian languages and two model variants: kavya, amit, dev, ishita, shreya, ratan, varun, manan, sumit, roopa, kabir, aayan, shubh, ashutosh, advait, amelia, sophia +- **bulbul:v3**: Advanced TTS model with temperature control + - Does NOT support: pitch, loudness + - Supports: pace (0.5-2.0), temperature (0.01-1.0) + - Default sample rate: 24000 Hz + - Preprocessing is always enabled + - Speakers: aditya (default), ritu, priya, neha, rahul, pooja, rohan, simran, + kavya, amit, dev, ishita, shreya, ratan, varun, manan, sumit, roopa, kabir, + aayan, shubh, ashutosh, advait, amelia, sophia + See https://docs.sarvam.ai/api-reference-docs/text-to-speech/stream for full API details. """ @@ -83,6 +92,7 @@ class SarvamTTSModel(str, Enum): BULBUL_V2 = "bulbul:v2" BULBUL_V3_BETA = "bulbul:v3-beta" + BULBUL_V3 = "bulbul:v3" class SarvamTTSSpeakerV2(str, Enum): @@ -180,6 +190,16 @@ TTS_MODEL_CONFIGS: Dict[str, TTSModelConfig] = { preprocessing_always_enabled=True, speakers=tuple(s.value for s in SarvamTTSSpeakerV3), ), + "bulbul:v3": TTSModelConfig( + supports_pitch=False, + supports_loudness=False, + supports_temperature=True, + default_sample_rate=24000, + default_speaker="shubh", + pace_range=(0.5, 2.0), + preprocessing_always_enabled=True, + speakers=tuple(s.value for s in SarvamTTSSpeakerV3), + ), } From 67d39a97f7f97d97047d598081d3e26fc8835337 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?G=C3=B6kmen=20G=C3=B6rgen?= Date: Mon, 9 Feb 2026 11:51:28 +0100 Subject: [PATCH 0396/1060] AIC model caching. --- src/pipecat/audio/filters/aic_filter.py | 196 ++++++++++++++++++++++-- tests/test_aic_filter.py | 125 ++++++++++++--- 2 files changed, 291 insertions(+), 30 deletions(-) diff --git a/src/pipecat/audio/filters/aic_filter.py b/src/pipecat/audio/filters/aic_filter.py index 7f0626776..399e6cd2e 100644 --- a/src/pipecat/audio/filters/aic_filter.py +++ b/src/pipecat/audio/filters/aic_filter.py @@ -12,10 +12,13 @@ the Koala filter and integrates with Pipecat's input transport pipeline. Classes: AICFilter: For aic-sdk (uses 'aic_sdk' module) + AICModelManager: Singleton manager for read-only AIC Model instances. """ +import asyncio from pathlib import Path -from typing import List, Optional +from threading import Lock +from typing import List, Optional, Tuple import numpy as np from aic_sdk import ( @@ -33,6 +36,174 @@ from pipecat.audio.vad.aic_vad import AICVADAnalyzer from pipecat.frames.frames import FilterControlFrame, FilterEnableFrame +class AICModelManager: + """Singleton manager for read-only AIC Model instances with reference counting. + + Caches Model instances by path or (model_id + download_dir). Multiple + AICFilter instances using the same model share one Model; the manager + acquires on first use and releases when the last reference is dropped. + """ + + _cache: dict[str, Tuple[Model, int]] = {} # key -> (model, ref_count) + _lock = Lock() + _loading: dict[ + str, asyncio.Task[Model] + ] = {} # key -> load task (deduplicates concurrent loads) + + @classmethod + def _increment_reference(cls, cache_key: str, entry: Tuple[Model, int]) -> Tuple[Model, str]: + """Increment reference count for cached entry. Caller must hold _lock.""" + cached_model, ref_count = entry + cls._cache[cache_key] = (cached_model, ref_count + 1) + logger.debug(f"AIC model cache key={cache_key!r} ref_count={ref_count + 1}") + return cached_model, cache_key + + @classmethod + def _store_new_reference(cls, cache_key: str, model: Model) -> Tuple[Model, str]: + """Store new model in cache with ref count 1. Caller must hold _lock.""" + cls._cache[cache_key] = (model, 1) + logger.debug(f"AIC model cached key={cache_key!r} ref_count=1") + return model, cache_key + + @classmethod + async def _load_model_from_file( + cls, + cache_key: str, + *, + model_path: Optional[Path] = None, + model_id: Optional[str] = None, + model_download_dir: Optional[Path] = None, + ) -> Model: + """Run the actual load (file or download). Separate to allow create_task and deduplication.""" + if model_path is not None: + logger.debug(f"Loading AIC model from file: {model_path}") + return Model.from_file(str(model_path)) + + if model_id is not None and model_download_dir is not None: + logger.debug(f"Downloading AIC model: {model_id}") + model_download_dir.mkdir(parents=True, exist_ok=True) + path = await Model.download_async(model_id, str(model_download_dir)) + logger.debug(f"Model downloaded to: {path}") + return Model.from_file(path) + + raise ValueError("Unexpected model_path or (model_id and model_download_dir) state.") + + @staticmethod + def _get_cache_key( + *, + model_path: Optional[Path] = None, + model_id: Optional[str] = None, + model_download_dir: Optional[Path] = None, + ) -> str: + """Build a stable cache key for the model. + + Args: + model_path: Path to a local .aicmodel file. + model_id: Model identifier (See https://artifacts.ai-coustics.io/ for available models). + model_download_dir: Directory used for downloading models. + + Returns: + A string key unique per (path) or (model_id + download_dir). + """ + if model_path is not None: + return f"path:{model_path.resolve()}" + + if model_id is not None and model_download_dir is not None: + return f"id:{model_id}:{model_download_dir.resolve()}" + + raise ValueError("Either model_path or (model_id and model_download_dir) must be set.") + + @classmethod + async def acquire( + cls, + *, + model_path: Optional[Path] = None, + model_id: Optional[str] = None, + model_download_dir: Optional[Path] = None, + ) -> Tuple[Model, str]: + """Get or load a Model and increment its reference count. + + Call this when starting a filter. Store the returned key and pass it + to release() when stopping the filter. + + Args: + model_path: Path to a local .aicmodel file. If set, model_id is ignored. + model_id: Model identifier to download from CDN. + model_download_dir: Directory for downloading models. Required if + model_id is used. + + Returns: + Tuple of (shared Model instance, cache key for release). + + Raises: + ValueError: If neither model_path nor (model_id + model_download_dir) + is provided, or if model_id is set without model_download_dir. + """ + cache_key = cls._get_cache_key( + model_path=model_path, + model_id=model_id, + model_download_dir=model_download_dir, + ) + + with cls._lock: + entry = cls._cache.get(cache_key) + if entry is not None: + return cls._increment_reference(cache_key, entry) + + # Deduplicate concurrent loads for the same key + load_task = cls._loading.get(cache_key) + if load_task is None: + load_task = asyncio.create_task( + cls._load_model_from_file( + cache_key, + model_path=model_path, + model_id=model_id, + model_download_dir=model_download_dir, + ) + ) + cls._loading[cache_key] = load_task + + try: + model = await load_task + finally: + with cls._lock: + cls._loading.pop(cache_key, None) + + with cls._lock: + entry = cls._cache.get(cache_key) + if entry is not None: + return cls._increment_reference(cache_key, entry) + return cls._store_new_reference(cache_key, model) + + @classmethod + def release(cls, key: str) -> None: + """Release a reference to a cached model. + + Call this when stopping a filter, with the key returned from + get_model(). When the last reference is released, the model + is removed from the cache. + + Args: + key: Cache key returned by get_model(). + """ + with cls._lock: + entry = cls._cache.get(key) + + if entry is None: + logger.warning(f"AIC model release unknown key={key!r}") + return + + model, ref_count = entry + ref_count -= 1 + + if ref_count <= 0: + del cls._cache[key] + logger.debug(f"AIC model evicted key={key!r}") + else: + cls._cache[key] = (model, ref_count) + logger.debug(f"AIC model key={key!r} ref_count={ref_count}") + + class AICFilter(BaseAudioFilter): """Audio filter using ai-coustics' AIC SDK for real-time enhancement. @@ -91,7 +262,8 @@ class AICFilter(BaseAudioFilter): 32768.0 # 2^15, for normalizing int16 (-32768 to 32767) to float32 (-1.0 to 1.0) ) - # AIC SDK objects + # AIC SDK objects; model is shared via AICModelManager + self._model_cache_key: Optional[str] = None self._model = None self._processor = None self._processor_ctx = None @@ -162,16 +334,12 @@ class AICFilter(BaseAudioFilter): """ self._sample_rate = sample_rate - # Load or download model - if self._model_path: - logger.debug(f"Loading AIC model from: {self._model_path}") - self._model = Model.from_file(str(self._model_path)) - else: - logger.debug(f"Downloading AIC model: {self._model_id}") - self._model_download_dir.mkdir(parents=True, exist_ok=True) - model_path = await Model.download_async(self._model_id, str(self._model_download_dir)) - logger.debug(f"Model downloaded to: {model_path}") - self._model = Model.from_file(model_path) + # Acquire shared read-only model from singleton manager + self._model, self._model_cache_key = await AICModelManager.acquire( + model_path=self._model_path, + model_id=self._model_id, + model_download_dir=self._model_download_dir, + ) # Get optimal frames for this sample rate self._frames_per_block = self._model.get_optimal_num_frames(self._sample_rate) @@ -242,6 +410,10 @@ class AICFilter(BaseAudioFilter): self._aic_ready = False self._audio_buffer.clear() + if self._model_cache_key is not None: + AICModelManager.release(self._model_cache_key) + self._model_cache_key = None + async def process_frame(self, frame: FilterControlFrame): """Process control frames to enable/disable filtering. diff --git a/tests/test_aic_filter.py b/tests/test_aic_filter.py index 6499084af..c36022a7b 100644 --- a/tests/test_aic_filter.py +++ b/tests/test_aic_filter.py @@ -5,6 +5,7 @@ # import asyncio +import time import unittest from pathlib import Path from unittest.mock import AsyncMock, MagicMock, patch @@ -23,6 +24,13 @@ except ImportError: AIC_FILTER_MODULE = "pipecat.audio.filters.aic_filter" +def _model_manager_ref_count(manager, key: str) -> int: + """Test helper: return reference count for a cache key (reads internal cache).""" + with manager._lock: + entry = manager._cache.get(key) + return entry[1] if entry else 0 + + class MockProcessor: """A lightweight mock for AIC ProcessorAsync that mimics real behavior.""" @@ -99,10 +107,11 @@ class TestAICFilter(unittest.IsolatedAsyncioTestCase): @classmethod def setUpClass(cls): """Import AICFilter after confirming aic_sdk is available.""" - from pipecat.audio.filters.aic_filter import AICFilter + from pipecat.audio.filters.aic_filter import AICFilter, AICModelManager from pipecat.frames.frames import FilterEnableFrame cls.AICFilter = AICFilter + cls.AICModelManager = AICModelManager cls.FilterEnableFrame = FilterEnableFrame def setUp(self): @@ -122,13 +131,13 @@ class TestAICFilter(unittest.IsolatedAsyncioTestCase): async def _start_filter_with_mocks(self, filter_instance, sample_rate=16000): """Start a filter with mocked SDK components.""" + cache_key = "test-cache-key" with ( - patch(f"{AIC_FILTER_MODULE}.Model") as mock_model_cls, + patch(f"{AIC_FILTER_MODULE}.AICModelManager") as mock_manager_cls, patch(f"{AIC_FILTER_MODULE}.ProcessorConfig") as mock_config_cls, patch(f"{AIC_FILTER_MODULE}.ProcessorAsync", return_value=self.mock_processor), ): - mock_model_cls.from_file.return_value = self.mock_model - mock_model_cls.download_async = AsyncMock(return_value="/tmp/model") + mock_manager_cls.acquire = AsyncMock(return_value=(self.mock_model, cache_key)) mock_config_cls.optimal.return_value = MagicMock() await filter_instance.start(sample_rate) @@ -171,37 +180,44 @@ class TestAICFilter(unittest.IsolatedAsyncioTestCase): filter_instance = self._create_filter_with_mocks(model_id=None, model_path=model_path) with ( - patch(f"{AIC_FILTER_MODULE}.Model") as mock_model_cls, + patch(f"{AIC_FILTER_MODULE}.AICModelManager") as mock_manager_cls, patch(f"{AIC_FILTER_MODULE}.ProcessorConfig") as mock_config_cls, patch(f"{AIC_FILTER_MODULE}.ProcessorAsync", return_value=self.mock_processor), ): - mock_model_cls.from_file.return_value = self.mock_model + mock_manager_cls.acquire = AsyncMock( + return_value=(self.mock_model, "path:/tmp/test.aicmodel") + ) mock_config_cls.optimal.return_value = MagicMock() await filter_instance.start(16000) - mock_model_cls.from_file.assert_called_once_with(str(model_path)) + mock_manager_cls.acquire.assert_called_once() + call_kw = mock_manager_cls.acquire.call_args[1] + self.assertEqual(call_kw["model_path"], model_path) + self.assertIsNone(call_kw["model_id"]) self.assertTrue(filter_instance._aic_ready) self.assertEqual(filter_instance._sample_rate, 16000) self.assertEqual(filter_instance._frames_per_block, 160) async def test_start_with_model_id_downloads(self): - """Test starting filter with model_id triggers download.""" + """Test starting filter with model_id uses manager (download happens in manager).""" filter_instance = self._create_filter_with_mocks() with ( - patch(f"{AIC_FILTER_MODULE}.Model") as mock_model_cls, + patch(f"{AIC_FILTER_MODULE}.AICModelManager") as mock_manager_cls, patch(f"{AIC_FILTER_MODULE}.ProcessorConfig") as mock_config_cls, patch(f"{AIC_FILTER_MODULE}.ProcessorAsync", return_value=self.mock_processor), ): - mock_model_cls.from_file.return_value = self.mock_model - mock_model_cls.download_async = AsyncMock(return_value="/tmp/model") + mock_manager_cls.acquire = AsyncMock( + return_value=(self.mock_model, "id:test-model:/custom/cache") + ) mock_config_cls.optimal.return_value = MagicMock() await filter_instance.start(16000) - mock_model_cls.download_async.assert_called_once() - mock_model_cls.from_file.assert_called_once() + mock_manager_cls.acquire.assert_called_once() + call_kw = mock_manager_cls.acquire.call_args[1] + self.assertEqual(call_kw["model_id"], "test-model") self.assertTrue(filter_instance._aic_ready) async def test_start_creates_processor(self): @@ -209,14 +225,13 @@ class TestAICFilter(unittest.IsolatedAsyncioTestCase): filter_instance = self._create_filter_with_mocks() with ( - patch(f"{AIC_FILTER_MODULE}.Model") as mock_model_cls, + patch(f"{AIC_FILTER_MODULE}.AICModelManager") as mock_manager_cls, patch(f"{AIC_FILTER_MODULE}.ProcessorConfig") as mock_config_cls, patch( f"{AIC_FILTER_MODULE}.ProcessorAsync", return_value=self.mock_processor ) as mock_processor_cls, ): - mock_model_cls.from_file.return_value = self.mock_model - mock_model_cls.download_async = AsyncMock(return_value="/tmp/model") + mock_manager_cls.acquire = AsyncMock(return_value=(self.mock_model, "test-cache-key")) mock_config_cls.optimal.return_value = MagicMock() await filter_instance.start(16000) @@ -241,17 +256,21 @@ class TestAICFilter(unittest.IsolatedAsyncioTestCase): self.assertEqual(bypass_params[-1][1], 0.0) async def test_stop_cleans_up_resources(self): - """Test that stop properly cleans up resources.""" + """Test that stop properly cleans up resources and releases model reference.""" filter_instance = self._create_filter_with_mocks() await self._start_filter_with_mocks(filter_instance) + cache_key = filter_instance._model_cache_key - await filter_instance.stop() + with patch(f"{AIC_FILTER_MODULE}.AICModelManager.release") as mock_release: + await filter_instance.stop() + mock_release.assert_called_once_with(cache_key) self.assertTrue(self.mock_processor.processor_ctx.reset_called) self.assertIsNone(filter_instance._processor) self.assertIsNone(filter_instance._processor_ctx) self.assertIsNone(filter_instance._vad_ctx) self.assertIsNone(filter_instance._model) + self.assertIsNone(filter_instance._model_cache_key) self.assertFalse(filter_instance._aic_ready) async def test_stop_without_start(self): @@ -261,6 +280,76 @@ class TestAICFilter(unittest.IsolatedAsyncioTestCase): # Should not raise await filter_instance.stop() + async def test_model_manager_reference_count(self): + """Test that AICModelManager reference count increments and decrements correctly.""" + model_path = Path("/tmp/refcount-test.aicmodel") + mock_model = MockModel() + manager = self.AICModelManager + + with patch(f"{AIC_FILTER_MODULE}.Model") as mock_model_cls: + mock_model_cls.from_file.return_value = mock_model + + # Acquire first reference + model1, key = await manager.acquire(model_path=model_path) + self.assertEqual(model1, mock_model) + self.assertEqual(_model_manager_ref_count(manager, key), 1) + + # Acquire second reference (same key, cached) + model2, key2 = await manager.acquire(model_path=model_path) + self.assertIs(model2, model1) + self.assertEqual(key2, key) + self.assertEqual(_model_manager_ref_count(manager, key), 2) + + # Release one reference + manager.release(key) + self.assertEqual(_model_manager_ref_count(manager, key), 1) + + # Release last reference (model evicted from cache) + manager.release(key) + self.assertEqual(_model_manager_ref_count(manager, key), 0) + + async def test_model_manager_concurrent_load_deduplication(self): + """Test that concurrent acquire calls for the same key share a single load task.""" + model_path = Path("/tmp/concurrent-load-test.aicmodel") + mock_model = MockModel() + manager = self.AICModelManager + load_count = 0 + + def from_file_once(path): + nonlocal load_count + load_count += 1 + time.sleep(0.02) # yield so other acquire callers can hit _loading and await same task + return mock_model + + with patch(f"{AIC_FILTER_MODULE}.Model") as mock_model_cls: + mock_model_cls.from_file.side_effect = from_file_once + + # Start several acquire calls concurrently before any completes + results = await asyncio.gather( + manager.acquire(model_path=model_path), + manager.acquire(model_path=model_path), + manager.acquire(model_path=model_path), + ) + + self.assertEqual( + load_count, 1, "Model.from_file should be called once for concurrent callers" + ) + model1, key1 = results[0] + model2, key2 = results[1] + model3, key3 = results[2] + self.assertIs(model1, mock_model) + self.assertIs(model2, mock_model) + self.assertIs(model3, mock_model) + self.assertEqual(key1, key2) + self.assertEqual(key2, key3) + self.assertEqual(_model_manager_ref_count(manager, key1), 3) + + # Release all references + manager.release(key1) + manager.release(key1) + manager.release(key1) + self.assertEqual(_model_manager_ref_count(manager, key1), 0) + async def test_process_frame_enable(self): """Test processing FilterEnableFrame to enable filtering.""" filter_instance = self._create_filter_with_mocks() From ed3ec045aae2775b2df2717d203f2270a325e3f4 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?G=C3=B6kmen=20G=C3=B6rgen?= Date: Mon, 9 Feb 2026 12:04:09 +0100 Subject: [PATCH 0397/1060] add changelog file. --- changelog/3684.changed.md | 2 ++ 1 file changed, 2 insertions(+) create mode 100644 changelog/3684.changed.md diff --git a/changelog/3684.changed.md b/changelog/3684.changed.md new file mode 100644 index 000000000..017fc9946 --- /dev/null +++ b/changelog/3684.changed.md @@ -0,0 +1,2 @@ +- `AICFilter` now shares read-only AIC models via a singleton `AICModelManager` in `aic_filter.py`. + - Multiple filters using the same `model path` or `(model_id, model_download_dir)` share one loaded model, with reference counting and concurrent load deduplication. From 5f64dae0cfefbed996d9059b8542e5ab0c297b63 Mon Sep 17 00:00:00 2001 From: Mark Backman Date: Sat, 7 Feb 2026 11:42:09 -0500 Subject: [PATCH 0398/1060] Filter RTVIObserver to downstream frames only and broadcast FunctionCallCancelFrame RTVIObserver now skips upstream frames to prevent duplicate RTVI messages when frames are broadcast in both directions. Also changed FunctionCallCancelFrame to use broadcast_frame for consistency with other function call frames. --- changelog/3672.changed.md | 1 + changelog/3672.fixed.md | 1 + src/pipecat/processors/frameworks/rtvi.py | 8 +++++++- src/pipecat/services/llm_service.py | 5 +++-- 4 files changed, 12 insertions(+), 3 deletions(-) create mode 100644 changelog/3672.changed.md create mode 100644 changelog/3672.fixed.md diff --git a/changelog/3672.changed.md b/changelog/3672.changed.md new file mode 100644 index 000000000..9722d00e0 --- /dev/null +++ b/changelog/3672.changed.md @@ -0,0 +1 @@ +- Changed `FunctionCallCancelFrame` to broadcast in both directions for consistency with other function call frames. diff --git a/changelog/3672.fixed.md b/changelog/3672.fixed.md new file mode 100644 index 000000000..1f68ed008 --- /dev/null +++ b/changelog/3672.fixed.md @@ -0,0 +1 @@ +- Fixed `RTVIObserver` sending duplicate client messages for frames that are broadcast in both directions (e.g. `UserStartedSpeakingFrame`, `FunctionCallResultFrame`). diff --git a/src/pipecat/processors/frameworks/rtvi.py b/src/pipecat/processors/frameworks/rtvi.py index 61c3ef57e..b6a65a35b 100644 --- a/src/pipecat/processors/frameworks/rtvi.py +++ b/src/pipecat/processors/frameworks/rtvi.py @@ -1023,7 +1023,7 @@ class RTVIObserverParams: sets the default level for unlisted functions:: function_call_report_level={ - "*": RTVIFunctionCallReportLevel.DISABLED, # Default: no events + "*": RTVIFunctionCallReportLevel.NONE, # Default: events with no metadata "get_weather": RTVIFunctionCallReportLevel.FULL, # Expose everything } @@ -1199,6 +1199,12 @@ class RTVIObserver(BaseObserver): frame = data.frame direction = data.direction + # Only process downstream frames. Some frames are broadcast in both + # directions (e.g. UserStartedSpeakingFrame, FunctionCallResultFrame), + # and we only want to send one RTVI message per event. + if direction != FrameDirection.DOWNSTREAM: + return + # If we have already seen this frame, let's skip it. if frame.id in self._frames_seen: return diff --git a/src/pipecat/services/llm_service.py b/src/pipecat/services/llm_service.py index e354543e4..c59b102b4 100644 --- a/src/pipecat/services/llm_service.py +++ b/src/pipecat/services/llm_service.py @@ -745,8 +745,9 @@ class LLMService(UserTurnCompletionLLMServiceMixin, AIService): await self.cancel_task(task) cancelled_tasks.add(task) - frame = FunctionCallCancelFrame(function_name=name, tool_call_id=tool_call_id) - await self.push_frame(frame) + await self.broadcast_frame( + FunctionCallCancelFrame, function_name=name, tool_call_id=tool_call_id + ) logger.debug(f"{self} Function call [{name}:{tool_call_id}] has been cancelled") From 34b068d6579a46ab83399b343f64a7ca36425e9b Mon Sep 17 00:00:00 2001 From: Mark Backman Date: Tue, 3 Feb 2026 22:32:34 -0500 Subject: [PATCH 0399/1060] Improve user turn stop timing by triggering timeout from VAD stop Refactor TranscriptionUserTurnStopStrategy and TurnAnalyzerUserTurnStopStrategy to use VADUserStoppedSpeakingFrame as the ground truth for when speech ended, rather than triggering timeouts from transcription frames. --- changelog/3637.added.3.md | 1 + changelog/3637.added.md | 6 + changelog/3637.changed.2.md | 5 + changelog/3637.changed.3.md | 1 + changelog/3637.changed.4.md | 1 + changelog/3637.changed.md | 1 + changelog/3637.removed.md | 1 + src/pipecat/frames/frames.py | 68 +++++- .../loggers/user_bot_latency_log_observer.py | 2 +- .../observers/user_bot_latency_observer.py | 2 +- src/pipecat/pipeline/service_switcher.py | 63 +++++- .../aggregators/llm_response_universal.py | 10 +- src/pipecat/processors/audio/vad_processor.py | 10 +- src/pipecat/services/assemblyai/stt.py | 10 +- src/pipecat/services/aws/stt.py | 6 +- src/pipecat/services/azure/stt.py | 6 +- src/pipecat/services/cartesia/stt.py | 6 +- src/pipecat/services/deepgram/flux/stt.py | 6 +- src/pipecat/services/deepgram/stt.py | 6 +- .../services/deepgram/stt_sagemaker.py | 6 +- src/pipecat/services/elevenlabs/stt.py | 9 + src/pipecat/services/fal/stt.py | 5 + src/pipecat/services/gladia/stt.py | 6 +- src/pipecat/services/google/stt.py | 6 +- src/pipecat/services/gradium/stt.py | 6 +- src/pipecat/services/groq/stt.py | 5 + src/pipecat/services/hathora/stt.py | 5 + src/pipecat/services/nvidia/stt.py | 11 +- src/pipecat/services/openai/stt.py | 13 +- src/pipecat/services/sambanova/stt.py | 5 + src/pipecat/services/sarvam/stt.py | 6 +- src/pipecat/services/soniox/stt.py | 6 +- src/pipecat/services/speechmatics/stt.py | 6 +- src/pipecat/services/stt_latency.py | 53 +++++ src/pipecat/services/stt_service.py | 47 ++-- src/pipecat/services/whisper/base_stt.py | 6 +- src/pipecat/transports/base_input.py | 31 ++- src/pipecat/turns/user_stop/__init__.py | 4 +- .../speech_timeout_user_turn_stop_strategy.py | 202 ++++++++++++++++++ .../transcription_user_turn_stop_strategy.py | 136 ++---------- .../turn_analyzer_user_turn_stop_strategy.py | 146 ++++++++----- src/pipecat/turns/user_turn_strategies.py | 6 +- tests/test_context_aggregators_universal.py | 27 ++- tests/test_service_switcher.py | 123 +++++++++++ tests/test_user_turn_controller.py | 10 +- tests/test_user_turn_processor.py | 20 +- tests/test_user_turn_stop_strategy.py | 108 ++++++---- 47 files changed, 933 insertions(+), 292 deletions(-) create mode 100644 changelog/3637.added.3.md create mode 100644 changelog/3637.added.md create mode 100644 changelog/3637.changed.2.md create mode 100644 changelog/3637.changed.3.md create mode 100644 changelog/3637.changed.4.md create mode 100644 changelog/3637.changed.md create mode 100644 changelog/3637.removed.md create mode 100644 src/pipecat/services/stt_latency.py create mode 100644 src/pipecat/turns/user_stop/speech_timeout_user_turn_stop_strategy.py diff --git a/changelog/3637.added.3.md b/changelog/3637.added.3.md new file mode 100644 index 000000000..9a17e748b --- /dev/null +++ b/changelog/3637.added.3.md @@ -0,0 +1 @@ +- Added `RequestMetadataFrame` and metadata handling for `ServiceSwitcher` to ensure STT services correctly emit `STTMetadataFrame` when switching between services. Only the active service's metadata is propagated downstream, switching services triggers the newly active service to re-emit its metadata, and proper frame ordering is maintained at startup. diff --git a/changelog/3637.added.md b/changelog/3637.added.md new file mode 100644 index 000000000..ec28f91f4 --- /dev/null +++ b/changelog/3637.added.md @@ -0,0 +1,6 @@ +- Added `STTMetadataFrame` to broadcast STT service latency information at pipeline start. + - STT services broadcast P99 time-to-final-segment (`ttfs_p99_latency`) to downstream processors + - Turn stop strategies automatically configure their STT timeout from this metadata + - Developers can override `ttfs_p99_latency` via constructor argument for custom deployments + - Added measured P99 values for STT providers. + - See [stt-benchmark](https://github.com/pipecat-ai/stt-benchmark) to measure latency for your configuration diff --git a/changelog/3637.changed.2.md b/changelog/3637.changed.2.md new file mode 100644 index 000000000..e8fbb811a --- /dev/null +++ b/changelog/3637.changed.2.md @@ -0,0 +1,5 @@ +- Improved user turn stop timing in `TranscriptionUserTurnStopStrategy` and `TurnAnalyzerUserTurnStopStrategy`. + - Timeout now starts on `VADUserStoppedSpeakingFrame` for tighter, more predictable timing + - Added support for finalized transcripts (`TranscriptionFrame.finalized=True`) to trigger earlier + - Added fallback timeout for edge cases where transcripts arrive without VAD events + - Removed `InterimTranscriptionFrame` handling (no longer affects timing) diff --git a/changelog/3637.changed.3.md b/changelog/3637.changed.3.md new file mode 100644 index 000000000..95f14c29c --- /dev/null +++ b/changelog/3637.changed.3.md @@ -0,0 +1 @@ +- Updated the `VADUserStartedSpeakingFrame` to include `start_secs` and `timestamp` and `VADUserStoppedSpeakingFrame` to include `stop_secs` and `timestamp`, removing the need to separately handle the `SpeechControlParamsFrame` for VADParams values. diff --git a/changelog/3637.changed.4.md b/changelog/3637.changed.4.md new file mode 100644 index 000000000..97f244cb7 --- /dev/null +++ b/changelog/3637.changed.4.md @@ -0,0 +1 @@ +- ⚠️ Renamed `TranscriptionUserTurnStopStrategy` to `SpeechTimeoutUserTurnStopStrategy`. The old name is deprecated and will be removed in a future release. diff --git a/changelog/3637.changed.md b/changelog/3637.changed.md new file mode 100644 index 000000000..4556f4d65 --- /dev/null +++ b/changelog/3637.changed.md @@ -0,0 +1 @@ +- ⚠️ Renamed `timeout` parameter to `user_speech_timeout` in `TranscriptionUserTurnStopStrategy`. diff --git a/changelog/3637.removed.md b/changelog/3637.removed.md new file mode 100644 index 000000000..695bce96d --- /dev/null +++ b/changelog/3637.removed.md @@ -0,0 +1 @@ +- ⚠️ Removed `timeout` parameter from `TurnAnalyzerUserTurnStopStrategy`. The timeout is now managed internally based on STT latency. diff --git a/src/pipecat/frames/frames.py b/src/pipecat/frames/frames.py index b7be8045e..296009f64 100644 --- a/src/pipecat/frames/frames.py +++ b/src/pipecat/frames/frames.py @@ -12,6 +12,7 @@ and LLM processing. """ import asyncio +import time from dataclasses import dataclass, field from enum import Enum from typing import ( @@ -1270,16 +1271,32 @@ class EmulateUserStoppedSpeakingFrame(SystemFrame): @dataclass class VADUserStartedSpeakingFrame(SystemFrame): - """Frame emitted when VAD definitively detects user started speaking.""" + """Frame emitted when VAD definitively detects user started speaking. - pass + Parameters: + start_secs: The VAD start_secs duration that was used to confirm the user + started speaking. This represents the speech duration that had to + elapse before the VAD determined speech began. + timestamp: Wall-clock time when the VAD made its determination. + """ + + start_secs: float = 0.0 + timestamp: float = field(default_factory=time.time) @dataclass class VADUserStoppedSpeakingFrame(SystemFrame): - """Frame emitted when VAD definitively detects user stopped speaking.""" + """Frame emitted when VAD definitively detects user stopped speaking. - pass + Parameters: + stop_secs: The VAD stop_secs duration that was used to confirm the user + stopped speaking. This represents the silence duration that had to + elapse before the VAD determined speech ended. + timestamp: Wall-clock time when the VAD made its determination. + """ + + stop_secs: float = 0.0 + timestamp: float = field(default_factory=time.time) @dataclass @@ -1651,6 +1668,49 @@ class SpeechControlParamsFrame(SystemFrame): turn_params: Optional[BaseTurnParams] = None +@dataclass +class ServiceMetadataFrame(SystemFrame): + """Base metadata frame for services. + + Broadcast by services at pipeline start to share service-specific + configuration and performance characteristics with downstream processors. + + Parameters: + service_name: The name of the service broadcasting this metadata. + """ + + service_name: str + + +@dataclass +class STTMetadataFrame(ServiceMetadataFrame): + """Metadata from STT service. + + Broadcast by STT services to inform downstream processors (like turn + strategies) about STT latency characteristics. + + Parameters: + ttfs_p99_latency: Time to final segment P99 latency in seconds. + This is the expected time from when speech ends to when the + final transcript is received, at the 99th percentile. + """ + + ttfs_p99_latency: float + + +@dataclass +class RequestMetadataFrame(ControlFrame): + """Request services to re-emit their metadata frames. + + Used by ServiceSwitcher when switching active services to ensure + downstream processors receive updated metadata from the newly active service. + Services that receive this frame should re-push their metadata frame + (e.g., STTMetadataFrame for STT services). + """ + + pass + + # # Task frames # diff --git a/src/pipecat/observers/loggers/user_bot_latency_log_observer.py b/src/pipecat/observers/loggers/user_bot_latency_log_observer.py index 044d4dea6..b15f989d1 100644 --- a/src/pipecat/observers/loggers/user_bot_latency_log_observer.py +++ b/src/pipecat/observers/loggers/user_bot_latency_log_observer.py @@ -79,7 +79,7 @@ class UserBotLatencyLogObserver(BaseObserver): if isinstance(data.frame, VADUserStartedSpeakingFrame): self._user_stopped_time = 0 elif isinstance(data.frame, VADUserStoppedSpeakingFrame): - self._user_stopped_time = time.time() + self._user_stopped_time = data.frame.timestamp elif isinstance(data.frame, (EndFrame, CancelFrame)): self._log_summary() elif isinstance(data.frame, BotStartedSpeakingFrame) and self._user_stopped_time: diff --git a/src/pipecat/observers/user_bot_latency_observer.py b/src/pipecat/observers/user_bot_latency_observer.py index 475da0c5d..17612ca76 100644 --- a/src/pipecat/observers/user_bot_latency_observer.py +++ b/src/pipecat/observers/user_bot_latency_observer.py @@ -73,7 +73,7 @@ class UserBotLatencyObserver(BaseObserver): self._user_stopped_time = None elif isinstance(data.frame, VADUserStoppedSpeakingFrame): # Record timestamp when user stops speaking - self._user_stopped_time = time.time() + self._user_stopped_time = data.frame.timestamp elif isinstance(data.frame, BotStartedSpeakingFrame) and self._user_stopped_time: # Calculate and emit latency latency = time.time() - self._user_stopped_time diff --git a/src/pipecat/pipeline/service_switcher.py b/src/pipecat/pipeline/service_switcher.py index dc73496a3..7bbd8ae74 100644 --- a/src/pipecat/pipeline/service_switcher.py +++ b/src/pipecat/pipeline/service_switcher.py @@ -13,6 +13,8 @@ from pipecat.frames.frames import ( ControlFrame, Frame, ManuallySwitchServiceFrame, + RequestMetadataFrame, + ServiceMetadataFrame, ServiceSwitcherFrame, ) from pipecat.pipeline.parallel_pipeline import ParallelPipeline @@ -123,7 +125,18 @@ class ServiceSwitcher(ParallelPipeline, Generic[StrategyType]): self.strategy = strategy class ServiceSwitcherFilter(FunctionFilter): - """An internal filter that allows frames to pass through to the wrapped service only if it's the active service.""" + """An internal filter that gates frame flow based on active service. + + Two filters "sandwich" each service, allowing frames through only + when the wrapped service is active. The pipeline layout is:: + + DownstreamFilter → Service → UpstreamFilter + + The filter names refer to which *direction* of frame flow they + filter, not their physical position: the downstream filter sits + *before* the service (filtering frames flowing into it) and the + upstream filter sits *after* it (filtering frames flowing back out). + """ def __init__( self, @@ -136,7 +149,9 @@ class ServiceSwitcher(ParallelPipeline, Generic[StrategyType]): Args: wrapped_service: The service that this filter wraps. active_service: The currently active service. - direction: The direction of frame flow to filter. + direction: The direction of frame flow this filter gates + (DOWNSTREAM for the filter before the service, + UPSTREAM for the filter after it). """ self._wrapped_service = wrapped_service self._active_service = active_service @@ -149,19 +164,54 @@ class ServiceSwitcher(ParallelPipeline, Generic[StrategyType]): async def process_frame(self, frame, direction): """Process a frame through the filter, handling special internal filter-updating frames.""" if isinstance(frame, ServiceSwitcher.ServiceSwitcherFilterFrame): + old_active = self._active_service self._active_service = frame.active_service - # Two ServiceSwitcherFilters "sandwich" a service. Push the - # frame only to update the other side of the sandwich, but - # otherwise don't let it leave the sandwich. + # Two ServiceSwitcherFilters "sandwich" a service. The + # frame enters via the downstream filter first. Push it + # through so the upstream filter also updates its state. if direction == self._direction: await self.push_frame(frame, direction) + # This is the upstream filter (the second to update). At + # this point both filters know the new active service, so + # it's safe to request metadata — the resulting + # ServiceMetadataFrame will pass both filters on its way + # out. Only do this for the newly active service's sandwich. + elif ( + self._direction == FrameDirection.UPSTREAM + and self._wrapped_service == frame.active_service + and old_active != self._wrapped_service + ): + await self.push_frame(RequestMetadataFrame(), FrameDirection.UPSTREAM) + return + + # RequestMetadataFrame is pushed upstream by the upstream filter + # (above) and consumed by the service. Guard against services + # that don't consume it: only forward in the filter's own + # direction (so it can reach the service) and only for the + # active service. Block in all other cases to prevent it from + # escaping the sandwich. + if isinstance(frame, RequestMetadataFrame): + if direction == self._direction and self._wrapped_service == self._active_service: + await self.push_frame(frame, direction) + return + + # Block ServiceMetadataFrame from inactive services. + if isinstance(frame, ServiceMetadataFrame): + if self._wrapped_service != self._active_service: + return + await self.push_frame(frame, direction) return await super().process_frame(frame, direction) @dataclass class ServiceSwitcherFilterFrame(ControlFrame): - """An internal frame used by ServiceSwitcher to filter frames based on active service.""" + """An internal frame used to update filter state on service switch. + + Sent when a service switch occurs to update the active service in + the sandwich filters and trigger metadata emission from the newly + active service. + """ active_service: FrameProcessor @@ -178,6 +228,7 @@ class ServiceSwitcher(ParallelPipeline, Generic[StrategyType]): def _make_pipeline_definition( service: FrameProcessor, strategy: ServiceSwitcherStrategy ) -> Any: + # Layout: DownstreamFilter → Service → UpstreamFilter return [ ServiceSwitcher.ServiceSwitcherFilter( wrapped_service=service, diff --git a/src/pipecat/processors/aggregators/llm_response_universal.py b/src/pipecat/processors/aggregators/llm_response_universal.py index cf65c6443..a6bcea668 100644 --- a/src/pipecat/processors/aggregators/llm_response_universal.py +++ b/src/pipecat/processors/aggregators/llm_response_universal.py @@ -664,10 +664,16 @@ class LLMUserAggregator(LLMContextAggregator): await self._queued_broadcast_frame(frame_cls, **kwargs) async def _on_vad_speech_started(self, controller): - await self._queued_broadcast_frame(VADUserStartedSpeakingFrame) + await self._queued_broadcast_frame( + VADUserStartedSpeakingFrame, + start_secs=controller._vad_analyzer.params.start_secs, + ) async def _on_vad_speech_stopped(self, controller): - await self._queued_broadcast_frame(VADUserStoppedSpeakingFrame) + await self._queued_broadcast_frame( + VADUserStoppedSpeakingFrame, + stop_secs=controller._vad_analyzer.params.stop_secs, + ) async def _on_vad_speech_activity(self, controller): await self._queued_broadcast_frame(UserSpeakingFrame) diff --git a/src/pipecat/processors/audio/vad_processor.py b/src/pipecat/processors/audio/vad_processor.py index 824164b58..9145f52cb 100644 --- a/src/pipecat/processors/audio/vad_processor.py +++ b/src/pipecat/processors/audio/vad_processor.py @@ -64,12 +64,18 @@ class VADProcessor(FrameProcessor): @self._vad_controller.event_handler("on_speech_started") async def on_speech_started(_controller): logger.debug(f"{self}: User started speaking") - await self.broadcast_frame(VADUserStartedSpeakingFrame) + await self.broadcast_frame( + VADUserStartedSpeakingFrame, + start_secs=_controller._vad_analyzer.params.start_secs, + ) @self._vad_controller.event_handler("on_speech_stopped") async def on_speech_stopped(_controller): logger.debug(f"{self}: User stopped speaking") - await self.broadcast_frame(VADUserStoppedSpeakingFrame) + await self.broadcast_frame( + VADUserStoppedSpeakingFrame, + stop_secs=_controller._vad_analyzer.params.stop_secs, + ) @self._vad_controller.event_handler("on_speech_activity") async def on_speech_activity(_controller): diff --git a/src/pipecat/services/assemblyai/stt.py b/src/pipecat/services/assemblyai/stt.py index 99b4f423d..94fad23b7 100644 --- a/src/pipecat/services/assemblyai/stt.py +++ b/src/pipecat/services/assemblyai/stt.py @@ -12,7 +12,7 @@ WebSocket API for streaming audio transcription. import asyncio import json -from typing import Any, AsyncGenerator, Dict +from typing import Any, AsyncGenerator, Dict, Optional from urllib.parse import urlencode from loguru import logger @@ -29,6 +29,7 @@ from pipecat.frames.frames import ( VADUserStoppedSpeakingFrame, ) from pipecat.processors.frame_processor import FrameDirection +from pipecat.services.stt_latency import ASSEMBLYAI_TTFS_P99 from pipecat.services.stt_service import WebsocketSTTService from pipecat.transcriptions.language import Language from pipecat.utils.time import time_now_iso8601 @@ -67,6 +68,7 @@ class AssemblyAISTTService(WebsocketSTTService): api_endpoint_base_url: str = "wss://streaming.assemblyai.com/v3/ws", connection_params: AssemblyAIConnectionParams = AssemblyAIConnectionParams(), vad_force_turn_endpoint: bool = True, + ttfs_p99_latency: Optional[float] = ASSEMBLYAI_TTFS_P99, **kwargs, ): """Initialize the AssemblyAI STT service. @@ -77,9 +79,13 @@ class AssemblyAISTTService(WebsocketSTTService): api_endpoint_base_url: WebSocket endpoint URL. Defaults to AssemblyAI's streaming endpoint. connection_params: Connection configuration parameters. Defaults to AssemblyAIConnectionParams(). vad_force_turn_endpoint: Whether to force turn endpoint on VAD stop. Defaults to True. + ttfs_p99_latency: P99 latency from speech end to final transcript in seconds. + Override for your deployment. See https://github.com/pipecat-ai/stt-benchmark **kwargs: Additional arguments passed to parent STTService class. """ - super().__init__(sample_rate=connection_params.sample_rate, **kwargs) + super().__init__( + sample_rate=connection_params.sample_rate, ttfs_p99_latency=ttfs_p99_latency, **kwargs + ) self._api_key = api_key self._language = language diff --git a/src/pipecat/services/aws/stt.py b/src/pipecat/services/aws/stt.py index 8beefe051..f78bc4d4b 100644 --- a/src/pipecat/services/aws/stt.py +++ b/src/pipecat/services/aws/stt.py @@ -28,6 +28,7 @@ from pipecat.frames.frames import ( TranscriptionFrame, ) from pipecat.services.aws.utils import build_event_message, decode_event, get_presigned_url +from pipecat.services.stt_latency import AWS_TRANSCRIBE_TTFS_P99 from pipecat.services.stt_service import WebsocketSTTService from pipecat.transcriptions.language import Language, resolve_language from pipecat.utils.time import time_now_iso8601 @@ -59,6 +60,7 @@ class AWSTranscribeSTTService(WebsocketSTTService): region: Optional[str] = None, sample_rate: int = 16000, language: Language = Language.EN, + ttfs_p99_latency: Optional[float] = AWS_TRANSCRIBE_TTFS_P99, **kwargs, ): """Initialize the AWS Transcribe STT service. @@ -70,9 +72,11 @@ class AWSTranscribeSTTService(WebsocketSTTService): region: AWS region for the service. sample_rate: Audio sample rate in Hz. Must be 8000 or 16000. Defaults to 16000. language: Language for transcription. Defaults to English. + ttfs_p99_latency: P99 latency from speech end to final transcript in seconds. + Override for your deployment. See https://github.com/pipecat-ai/stt-benchmark **kwargs: Additional arguments passed to parent STTService class. """ - super().__init__(**kwargs) + super().__init__(ttfs_p99_latency=ttfs_p99_latency, **kwargs) self._settings = { "sample_rate": sample_rate, diff --git a/src/pipecat/services/azure/stt.py b/src/pipecat/services/azure/stt.py index d45eb71df..1bc7ec70a 100644 --- a/src/pipecat/services/azure/stt.py +++ b/src/pipecat/services/azure/stt.py @@ -25,6 +25,7 @@ from pipecat.frames.frames import ( TranscriptionFrame, ) from pipecat.services.azure.common import language_to_azure_language +from pipecat.services.stt_latency import AZURE_TTFS_P99 from pipecat.services.stt_service import STTService from pipecat.transcriptions.language import Language from pipecat.utils.time import time_now_iso8601 @@ -63,6 +64,7 @@ class AzureSTTService(STTService): language: Language = Language.EN_US, sample_rate: Optional[int] = None, endpoint_id: Optional[str] = None, + ttfs_p99_latency: Optional[float] = AZURE_TTFS_P99, **kwargs, ): """Initialize the Azure STT service. @@ -73,9 +75,11 @@ class AzureSTTService(STTService): language: Language for speech recognition. Defaults to English (US). sample_rate: Audio sample rate in Hz. If None, uses service default. endpoint_id: Custom model endpoint id. + ttfs_p99_latency: P99 latency from speech end to final transcript in seconds. + Override for your deployment. See https://github.com/pipecat-ai/stt-benchmark **kwargs: Additional arguments passed to parent STTService. """ - super().__init__(sample_rate=sample_rate, **kwargs) + super().__init__(sample_rate=sample_rate, ttfs_p99_latency=ttfs_p99_latency, **kwargs) self._speech_config = SpeechConfig( subscription=api_key, diff --git a/src/pipecat/services/cartesia/stt.py b/src/pipecat/services/cartesia/stt.py index c0bfb3e8d..2c76412f2 100644 --- a/src/pipecat/services/cartesia/stt.py +++ b/src/pipecat/services/cartesia/stt.py @@ -27,6 +27,7 @@ from pipecat.frames.frames import ( VADUserStoppedSpeakingFrame, ) from pipecat.processors.frame_processor import FrameDirection +from pipecat.services.stt_latency import CARTESIA_TTFS_P99 from pipecat.services.stt_service import WebsocketSTTService from pipecat.transcriptions.language import Language from pipecat.utils.time import time_now_iso8601 @@ -137,6 +138,7 @@ class CartesiaSTTService(WebsocketSTTService): base_url: str = "", sample_rate: int = 16000, live_options: Optional[CartesiaLiveOptions] = None, + ttfs_p99_latency: Optional[float] = CARTESIA_TTFS_P99, **kwargs, ): """Initialize CartesiaSTTService with API key and options. @@ -146,10 +148,12 @@ class CartesiaSTTService(WebsocketSTTService): base_url: Custom API endpoint URL. If empty, uses default. sample_rate: Audio sample rate in Hz. Defaults to 16000. live_options: Configuration options for transcription service. + ttfs_p99_latency: P99 latency from speech end to final transcript in seconds. + Override for your deployment. See https://github.com/pipecat-ai/stt-benchmark **kwargs: Additional arguments passed to parent STTService. """ sample_rate = sample_rate or (live_options.sample_rate if live_options else None) - super().__init__(sample_rate=sample_rate, **kwargs) + super().__init__(sample_rate=sample_rate, ttfs_p99_latency=ttfs_p99_latency, **kwargs) default_options = CartesiaLiveOptions( model="ink-whisper", diff --git a/src/pipecat/services/deepgram/flux/stt.py b/src/pipecat/services/deepgram/flux/stt.py index 756827171..547eca0de 100644 --- a/src/pipecat/services/deepgram/flux/stt.py +++ b/src/pipecat/services/deepgram/flux/stt.py @@ -161,7 +161,11 @@ class DeepgramFluxSTTService(WebsocketSTTService): # was never destroyed. # So we can keep it here as false, because inside the method send_with_retry, it will # already try to reconnect if needed. - super().__init__(sample_rate=sample_rate, reconnect_on_error=False, **kwargs) + super().__init__( + sample_rate=sample_rate, + reconnect_on_error=False, + **kwargs, + ) self._api_key = api_key self._url = url diff --git a/src/pipecat/services/deepgram/stt.py b/src/pipecat/services/deepgram/stt.py index 0c326deb3..0f79499ba 100644 --- a/src/pipecat/services/deepgram/stt.py +++ b/src/pipecat/services/deepgram/stt.py @@ -23,6 +23,7 @@ from pipecat.frames.frames import ( VADUserStoppedSpeakingFrame, ) from pipecat.processors.frame_processor import FrameDirection +from pipecat.services.stt_latency import DEEPGRAM_TTFS_P99 from pipecat.services.stt_service import STTService from pipecat.transcriptions.language import Language from pipecat.utils.time import time_now_iso8601 @@ -61,6 +62,7 @@ class DeepgramSTTService(STTService): live_options: Optional[LiveOptions] = None, addons: Optional[Dict] = None, should_interrupt: bool = True, + ttfs_p99_latency: Optional[float] = DEEPGRAM_TTFS_P99, **kwargs, ): """Initialize the Deepgram STT service. @@ -81,13 +83,15 @@ class DeepgramSTTService(STTService): .. deprecated:: 0.0.99 This parameter will be removed along with `vad_events` support. + ttfs_p99_latency: P99 latency from speech end to final transcript in seconds. + Override for your deployment. See https://github.com/pipecat-ai/stt-benchmark **kwargs: Additional arguments passed to the parent STTService. Note: The `vad_events` option in LiveOptions is deprecated as of version 0.0.99 and will be removed in a future version. Please use the Silero VAD instead. """ sample_rate = sample_rate or (live_options.sample_rate if live_options else None) - super().__init__(sample_rate=sample_rate, **kwargs) + super().__init__(sample_rate=sample_rate, ttfs_p99_latency=ttfs_p99_latency, **kwargs) if url: import warnings diff --git a/src/pipecat/services/deepgram/stt_sagemaker.py b/src/pipecat/services/deepgram/stt_sagemaker.py index 0f7e6f988..99f6cf487 100644 --- a/src/pipecat/services/deepgram/stt_sagemaker.py +++ b/src/pipecat/services/deepgram/stt_sagemaker.py @@ -31,6 +31,7 @@ from pipecat.frames.frames import ( ) from pipecat.processors.frame_processor import FrameDirection from pipecat.services.aws.sagemaker.bidi_client import SageMakerBidiClient +from pipecat.services.stt_latency import DEEPGRAM_SAGEMAKER_TTFS_P99 from pipecat.services.stt_service import STTService from pipecat.transcriptions.language import Language from pipecat.utils.time import time_now_iso8601 @@ -81,6 +82,7 @@ class DeepgramSageMakerSTTService(STTService): region: str, sample_rate: Optional[int] = None, live_options: Optional[LiveOptions] = None, + ttfs_p99_latency: Optional[float] = DEEPGRAM_SAGEMAKER_TTFS_P99, **kwargs, ): """Initialize the Deepgram SageMaker STT service. @@ -93,10 +95,12 @@ class DeepgramSageMakerSTTService(STTService): live_options or defaults to the value from StartFrame. live_options: Deepgram LiveOptions for detailed configuration. If None, uses sensible defaults (nova-3 model, English, interim results enabled). + ttfs_p99_latency: P99 latency from speech end to final transcript in seconds. + Override for your deployment. See https://github.com/pipecat-ai/stt-benchmark **kwargs: Additional arguments passed to the parent STTService. """ sample_rate = sample_rate or (live_options.sample_rate if live_options else None) - super().__init__(sample_rate=sample_rate, **kwargs) + super().__init__(sample_rate=sample_rate, ttfs_p99_latency=ttfs_p99_latency, **kwargs) self._endpoint_name = endpoint_name self._region = region diff --git a/src/pipecat/services/elevenlabs/stt.py b/src/pipecat/services/elevenlabs/stt.py index 01df424a0..bf853ac98 100644 --- a/src/pipecat/services/elevenlabs/stt.py +++ b/src/pipecat/services/elevenlabs/stt.py @@ -33,6 +33,7 @@ from pipecat.frames.frames import ( VADUserStoppedSpeakingFrame, ) from pipecat.processors.frame_processor import FrameDirection +from pipecat.services.stt_latency import ELEVENLABS_REALTIME_TTFS_P99, ELEVENLABS_TTFS_P99 from pipecat.services.stt_service import SegmentedSTTService, WebsocketSTTService from pipecat.transcriptions.language import Language, resolve_language from pipecat.utils.time import time_now_iso8601 @@ -194,6 +195,7 @@ class ElevenLabsSTTService(SegmentedSTTService): model: str = "scribe_v2", sample_rate: Optional[int] = None, params: Optional[InputParams] = None, + ttfs_p99_latency: Optional[float] = ELEVENLABS_TTFS_P99, **kwargs, ): """Initialize the ElevenLabs STT service. @@ -205,10 +207,13 @@ class ElevenLabsSTTService(SegmentedSTTService): model: Model ID for transcription. Defaults to "scribe_v2". sample_rate: Audio sample rate in Hz. If not provided, uses the pipeline's rate. params: Configuration parameters for the STT service. + ttfs_p99_latency: P99 latency from speech end to final transcript in seconds. + Override for your deployment. See https://github.com/pipecat-ai/stt-benchmark **kwargs: Additional arguments passed to SegmentedSTTService. """ super().__init__( sample_rate=sample_rate, + ttfs_p99_latency=ttfs_p99_latency, **kwargs, ) @@ -436,6 +441,7 @@ class ElevenLabsRealtimeSTTService(WebsocketSTTService): model: str = "scribe_v2_realtime", sample_rate: Optional[int] = None, params: Optional[InputParams] = None, + ttfs_p99_latency: Optional[float] = ELEVENLABS_REALTIME_TTFS_P99, **kwargs, ): """Initialize the ElevenLabs Realtime STT service. @@ -446,10 +452,13 @@ class ElevenLabsRealtimeSTTService(WebsocketSTTService): model: Model ID for transcription. Defaults to "scribe_v2_realtime". sample_rate: Audio sample rate in Hz. If not provided, uses the pipeline's rate. params: Configuration parameters for the STT service. + ttfs_p99_latency: P99 latency from speech end to final transcript in seconds. + Override for your deployment. See https://github.com/pipecat-ai/stt-benchmark **kwargs: Additional arguments passed to WebsocketSTTService. """ super().__init__( sample_rate=sample_rate, + ttfs_p99_latency=ttfs_p99_latency, **kwargs, ) diff --git a/src/pipecat/services/fal/stt.py b/src/pipecat/services/fal/stt.py index 114865778..4e8a655ec 100644 --- a/src/pipecat/services/fal/stt.py +++ b/src/pipecat/services/fal/stt.py @@ -17,6 +17,7 @@ from loguru import logger from pydantic import BaseModel from pipecat.frames.frames import ErrorFrame, Frame, TranscriptionFrame +from pipecat.services.stt_latency import FAL_TTFS_P99 from pipecat.services.stt_service import SegmentedSTTService from pipecat.transcriptions.language import Language, resolve_language from pipecat.utils.time import time_now_iso8601 @@ -173,6 +174,7 @@ class FalSTTService(SegmentedSTTService): api_key: Optional[str] = None, sample_rate: Optional[int] = None, params: Optional[InputParams] = None, + ttfs_p99_latency: Optional[float] = FAL_TTFS_P99, **kwargs, ): """Initialize the FalSTTService with API key and parameters. @@ -181,10 +183,13 @@ class FalSTTService(SegmentedSTTService): api_key: Fal API key. If not provided, will check FAL_KEY environment variable. sample_rate: Audio sample rate in Hz. If not provided, uses the pipeline's rate. params: Configuration parameters for the Wizper API. + ttfs_p99_latency: P99 latency from speech end to final transcript in seconds. + Override for your deployment. See https://github.com/pipecat-ai/stt-benchmark **kwargs: Additional arguments passed to SegmentedSTTService. """ super().__init__( sample_rate=sample_rate, + ttfs_p99_latency=ttfs_p99_latency, **kwargs, ) diff --git a/src/pipecat/services/gladia/stt.py b/src/pipecat/services/gladia/stt.py index e4229fe97..243152d68 100644 --- a/src/pipecat/services/gladia/stt.py +++ b/src/pipecat/services/gladia/stt.py @@ -32,6 +32,7 @@ from pipecat.frames.frames import ( UserStoppedSpeakingFrame, ) from pipecat.services.gladia.config import GladiaInputParams +from pipecat.services.stt_latency import GLADIA_TTFS_P99 from pipecat.services.stt_service import WebsocketSTTService from pipecat.transcriptions.language import Language, resolve_language from pipecat.utils.time import time_now_iso8601 @@ -205,6 +206,7 @@ class GladiaSTTService(WebsocketSTTService): params: Optional[GladiaInputParams] = None, max_buffer_size: int = 1024 * 1024 * 20, # 20MB default buffer should_interrupt: bool = True, + ttfs_p99_latency: Optional[float] = GLADIA_TTFS_P99, **kwargs, ): """Initialize the Gladia STT service. @@ -225,9 +227,11 @@ class GladiaSTTService(WebsocketSTTService): max_buffer_size: Maximum size of audio buffer in bytes. Defaults to 20MB. should_interrupt: Determine whether the bot should be interrupted when Gladia VAD detects user speech. Defaults to True. + ttfs_p99_latency: P99 latency from speech end to final transcript in seconds. + Override for your deployment. See https://github.com/pipecat-ai/stt-benchmark **kwargs: Additional arguments passed to the STTService parent class. """ - super().__init__(sample_rate=sample_rate, **kwargs) + super().__init__(sample_rate=sample_rate, ttfs_p99_latency=ttfs_p99_latency, **kwargs) params = params or GladiaInputParams() diff --git a/src/pipecat/services/google/stt.py b/src/pipecat/services/google/stt.py index edb2ccec0..23396b0b8 100644 --- a/src/pipecat/services/google/stt.py +++ b/src/pipecat/services/google/stt.py @@ -34,6 +34,7 @@ from pipecat.frames.frames import ( StartFrame, TranscriptionFrame, ) +from pipecat.services.stt_latency import GOOGLE_TTFS_P99 from pipecat.services.stt_service import STTService from pipecat.transcriptions.language import Language, resolve_language from pipecat.utils.time import time_now_iso8601 @@ -438,6 +439,7 @@ class GoogleSTTService(STTService): location: str = "global", sample_rate: Optional[int] = None, params: Optional[InputParams] = None, + ttfs_p99_latency: Optional[float] = GOOGLE_TTFS_P99, **kwargs, ): """Initialize the Google STT service. @@ -448,9 +450,11 @@ class GoogleSTTService(STTService): location: Google Cloud location (e.g., "global", "us-central1"). sample_rate: Audio sample rate in Hertz. params: Configuration parameters for the service. + ttfs_p99_latency: P99 latency from speech end to final transcript in seconds. + Override for your deployment. See https://github.com/pipecat-ai/stt-benchmark **kwargs: Additional arguments passed to STTService. """ - super().__init__(sample_rate=sample_rate, **kwargs) + super().__init__(sample_rate=sample_rate, ttfs_p99_latency=ttfs_p99_latency, **kwargs) params = params or GoogleSTTService.InputParams() diff --git a/src/pipecat/services/gradium/stt.py b/src/pipecat/services/gradium/stt.py index 2de899dc9..7433c2549 100644 --- a/src/pipecat/services/gradium/stt.py +++ b/src/pipecat/services/gradium/stt.py @@ -27,6 +27,7 @@ from pipecat.frames.frames import ( VADUserStoppedSpeakingFrame, ) from pipecat.processors.frame_processor import FrameDirection +from pipecat.services.stt_latency import GRADIUM_TTFS_P99 from pipecat.services.stt_service import WebsocketSTTService from pipecat.transcriptions.language import Language, resolve_language from pipecat.utils.time import time_now_iso8601 @@ -94,6 +95,7 @@ class GradiumSTTService(WebsocketSTTService): api_endpoint_base_url: str = "wss://eu.api.gradium.ai/api/speech/asr", params: Optional[InputParams] = None, json_config: Optional[str] = None, + ttfs_p99_latency: Optional[float] = GRADIUM_TTFS_P99, **kwargs, ): """Initialize the Gradium STT service. @@ -107,9 +109,11 @@ class GradiumSTTService(WebsocketSTTService): .. deprecated:: 0.0.101 Use `params` instead for type-safe configuration. + ttfs_p99_latency: P99 latency from speech end to final transcript in seconds. + Override for your deployment. See https://github.com/pipecat-ai/stt-benchmark **kwargs: Additional arguments passed to parent STTService class. """ - super().__init__(sample_rate=SAMPLE_RATE, **kwargs) + super().__init__(sample_rate=SAMPLE_RATE, ttfs_p99_latency=ttfs_p99_latency, **kwargs) if json_config is not None: import warnings diff --git a/src/pipecat/services/groq/stt.py b/src/pipecat/services/groq/stt.py index 3aadd0e73..52cb0a7cc 100644 --- a/src/pipecat/services/groq/stt.py +++ b/src/pipecat/services/groq/stt.py @@ -8,6 +8,7 @@ from typing import Optional +from pipecat.services.stt_latency import GROQ_TTFS_P99 from pipecat.services.whisper.base_stt import BaseWhisperSTTService, Transcription from pipecat.transcriptions.language import Language @@ -28,6 +29,7 @@ class GroqSTTService(BaseWhisperSTTService): language: Optional[Language] = Language.EN, prompt: Optional[str] = None, temperature: Optional[float] = None, + ttfs_p99_latency: Optional[float] = GROQ_TTFS_P99, **kwargs, ): """Initialize Groq STT service. @@ -39,6 +41,8 @@ class GroqSTTService(BaseWhisperSTTService): language: Language of the audio input. Defaults to English. prompt: Optional text to guide the model's style or continue a previous segment. temperature: Optional sampling temperature between 0 and 1. Defaults to 0.0. + ttfs_p99_latency: P99 latency from speech end to final transcript in seconds. + Override for your deployment. See https://github.com/pipecat-ai/stt-benchmark **kwargs: Additional arguments passed to BaseWhisperSTTService. """ super().__init__( @@ -48,6 +52,7 @@ class GroqSTTService(BaseWhisperSTTService): language=language, prompt=prompt, temperature=temperature, + ttfs_p99_latency=ttfs_p99_latency, **kwargs, ) diff --git a/src/pipecat/services/hathora/stt.py b/src/pipecat/services/hathora/stt.py index 81e8f0ea6..defdc355d 100644 --- a/src/pipecat/services/hathora/stt.py +++ b/src/pipecat/services/hathora/stt.py @@ -18,6 +18,7 @@ from pipecat.frames.frames import ( Frame, TranscriptionFrame, ) +from pipecat.services.stt_latency import HATHORA_TTFS_P99 from pipecat.services.stt_service import SegmentedSTTService from pipecat.transcriptions.language import Language from pipecat.utils.time import time_now_iso8601 @@ -53,6 +54,7 @@ class HathoraSTTService(SegmentedSTTService): api_key: Optional[str] = None, base_url: str = "https://api.models.hathora.dev/inference/v1/stt", params: Optional[InputParams] = None, + ttfs_p99_latency: Optional[float] = HATHORA_TTFS_P99, **kwargs, ): """Initialize the Hathora STT service. @@ -66,10 +68,13 @@ class HathoraSTTService(SegmentedSTTService): provision one [here](https://models.hathora.dev/tokens). base_url: Base API URL for the Hathora STT service. params: Configuration parameters. + ttfs_p99_latency: P99 latency from speech end to final transcript in seconds. + Override for your deployment. See https://github.com/pipecat-ai/stt-benchmark **kwargs: Additional arguments passed to the parent class. """ super().__init__( sample_rate=sample_rate, + ttfs_p99_latency=ttfs_p99_latency, **kwargs, ) self._model = model diff --git a/src/pipecat/services/nvidia/stt.py b/src/pipecat/services/nvidia/stt.py index 3af3fe78c..8eb6d7bb5 100644 --- a/src/pipecat/services/nvidia/stt.py +++ b/src/pipecat/services/nvidia/stt.py @@ -22,6 +22,7 @@ from pipecat.frames.frames import ( StartFrame, TranscriptionFrame, ) +from pipecat.services.stt_latency import NVIDIA_TTFS_P99 from pipecat.services.stt_service import SegmentedSTTService, STTService from pipecat.transcriptions.language import Language, resolve_language from pipecat.utils.time import time_now_iso8601 @@ -117,6 +118,7 @@ class NvidiaSTTService(STTService): sample_rate: Optional[int] = None, params: Optional[InputParams] = None, use_ssl: bool = True, + ttfs_p99_latency: Optional[float] = NVIDIA_TTFS_P99, **kwargs, ): """Initialize the NVIDIA Riva STT service. @@ -128,9 +130,11 @@ class NvidiaSTTService(STTService): sample_rate: Audio sample rate in Hz. If None, uses pipeline default. params: Additional configuration parameters for NVIDIA Riva. use_ssl: Whether to use SSL for the NVIDIA Riva server. Defaults to True. + ttfs_p99_latency: P99 latency from speech end to final transcript in seconds. + Override for your deployment. See https://github.com/pipecat-ai/stt-benchmark **kwargs: Additional arguments passed to STTService. """ - super().__init__(sample_rate=sample_rate, **kwargs) + super().__init__(sample_rate=sample_rate, ttfs_p99_latency=ttfs_p99_latency, **kwargs) params = params or NvidiaSTTService.InputParams() @@ -413,6 +417,7 @@ class NvidiaSegmentedSTTService(SegmentedSTTService): sample_rate: Optional[int] = None, params: Optional[InputParams] = None, use_ssl: bool = True, + ttfs_p99_latency: Optional[float] = NVIDIA_TTFS_P99, **kwargs, ): """Initialize the NVIDIA Riva segmented STT service. @@ -424,9 +429,11 @@ class NvidiaSegmentedSTTService(SegmentedSTTService): sample_rate: Audio sample rate in Hz. If not provided, uses the pipeline's rate params: Additional configuration parameters for NVIDIA Riva use_ssl: Whether to use SSL for the NVIDIA Riva server. Defaults to True. + ttfs_p99_latency: P99 latency from speech end to final transcript in seconds. + Override for your deployment. See https://github.com/pipecat-ai/stt-benchmark **kwargs: Additional arguments passed to SegmentedSTTService """ - super().__init__(sample_rate=sample_rate, **kwargs) + super().__init__(sample_rate=sample_rate, ttfs_p99_latency=ttfs_p99_latency, **kwargs) params = params or NvidiaSegmentedSTTService.InputParams() diff --git a/src/pipecat/services/openai/stt.py b/src/pipecat/services/openai/stt.py index db3cf277c..4dd16be6e 100644 --- a/src/pipecat/services/openai/stt.py +++ b/src/pipecat/services/openai/stt.py @@ -34,6 +34,7 @@ from pipecat.frames.frames import ( VADUserStoppedSpeakingFrame, ) from pipecat.processors.frame_processor import FrameDirection +from pipecat.services.stt_latency import OPENAI_REALTIME_TTFS_P99, OPENAI_TTFS_P99 from pipecat.services.stt_service import WebsocketSTTService from pipecat.services.whisper.base_stt import BaseWhisperSTTService, Transcription from pipecat.transcriptions.language import Language @@ -64,6 +65,7 @@ class OpenAISTTService(BaseWhisperSTTService): language: Optional[Language] = Language.EN, prompt: Optional[str] = None, temperature: Optional[float] = None, + ttfs_p99_latency: Optional[float] = OPENAI_TTFS_P99, **kwargs, ): """Initialize OpenAI STT service. @@ -75,6 +77,8 @@ class OpenAISTTService(BaseWhisperSTTService): language: Language of the audio input. Defaults to English. prompt: Optional text to guide the model's style or continue a previous segment. temperature: Optional sampling temperature between 0 and 1. Defaults to 0.0. + ttfs_p99_latency: P99 latency from speech end to final transcript in seconds. + Override for your deployment. See https://github.com/pipecat-ai/stt-benchmark **kwargs: Additional arguments passed to BaseWhisperSTTService. """ super().__init__( @@ -84,6 +88,7 @@ class OpenAISTTService(BaseWhisperSTTService): language=language, prompt=prompt, temperature=temperature, + ttfs_p99_latency=ttfs_p99_latency, **kwargs, ) @@ -162,6 +167,7 @@ class OpenAIRealtimeSTTService(WebsocketSTTService): turn_detection: Optional[Union[dict, Literal[False]]] = False, noise_reduction: Optional[Literal["near_field", "far_field"]] = None, should_interrupt: bool = True, + ttfs_p99_latency: Optional[float] = OPENAI_REALTIME_TTFS_P99, **kwargs, ): """Initialize the OpenAI Realtime STT service. @@ -187,6 +193,8 @@ class OpenAIRealtimeSTTService(WebsocketSTTService): should_interrupt: Whether to interrupt bot output when speech is detected by server-side VAD. Only applies when turn detection is enabled. Defaults to True. + ttfs_p99_latency: P99 latency from speech end to final transcript in seconds. + Override for your deployment. See https://github.com/pipecat-ai/stt-benchmark **kwargs: Additional arguments passed to parent WebsocketSTTService. """ @@ -196,7 +204,10 @@ class OpenAIRealtimeSTTService(WebsocketSTTService): "Install it with: pip install pipecat-ai[openai]" ) - super().__init__(**kwargs) + super().__init__( + ttfs_p99_latency=ttfs_p99_latency, + **kwargs, + ) self._api_key = api_key self._base_url = base_url diff --git a/src/pipecat/services/sambanova/stt.py b/src/pipecat/services/sambanova/stt.py index 311f37307..a1cbe8a22 100644 --- a/src/pipecat/services/sambanova/stt.py +++ b/src/pipecat/services/sambanova/stt.py @@ -10,6 +10,7 @@ from typing import Any, Optional from loguru import logger +from pipecat.services.stt_latency import SAMBANOVA_TTFS_P99 from pipecat.services.whisper.base_stt import BaseWhisperSTTService, Transcription from pipecat.transcriptions.language import Language @@ -30,6 +31,7 @@ class SambaNovaSTTService(BaseWhisperSTTService): # type: ignore language: Optional[Language] = Language.EN, prompt: Optional[str] = None, temperature: Optional[float] = None, + ttfs_p99_latency: Optional[float] = SAMBANOVA_TTFS_P99, **kwargs: Any, ) -> None: """Initialize SambaNova STT service. @@ -41,6 +43,8 @@ class SambaNovaSTTService(BaseWhisperSTTService): # type: ignore language: Language of the audio input. Defaults to English. prompt: Optional text to guide the model's style or continue a previous segment. temperature: Optional sampling temperature between 0 and 1. Defaults to 0.0. + ttfs_p99_latency: P99 latency from speech end to final transcript in seconds. + Override for your deployment. See https://github.com/pipecat-ai/stt-benchmark **kwargs: Additional arguments passed to `pipecat.services.whisper.base_stt.BaseWhisperSTTService`. """ super().__init__( @@ -50,6 +54,7 @@ class SambaNovaSTTService(BaseWhisperSTTService): # type: ignore language=language, prompt=prompt, temperature=temperature, + ttfs_p99_latency=ttfs_p99_latency, **kwargs, ) diff --git a/src/pipecat/services/sarvam/stt.py b/src/pipecat/services/sarvam/stt.py index 799c79921..e0da8520d 100644 --- a/src/pipecat/services/sarvam/stt.py +++ b/src/pipecat/services/sarvam/stt.py @@ -26,6 +26,7 @@ from pipecat.frames.frames import ( ) from pipecat.processors.frame_processor import FrameDirection from pipecat.services.sarvam._sdk import sdk_headers +from pipecat.services.stt_latency import SARVAM_TTFS_P99 from pipecat.services.stt_service import STTService from pipecat.transcriptions.language import Language, resolve_language from pipecat.utils.time import time_now_iso8601 @@ -159,6 +160,7 @@ class SarvamSTTService(STTService): sample_rate: Optional[int] = None, input_audio_codec: str = "wav", params: Optional[InputParams] = None, + ttfs_p99_latency: Optional[float] = SARVAM_TTFS_P99, **kwargs, ): """Initialize the Sarvam STT service. @@ -172,6 +174,8 @@ class SarvamSTTService(STTService): sample_rate: Audio sample rate. Defaults to 16000 if not specified. input_audio_codec: Audio codec/format of the input file. Defaults to "wav". params: Configuration parameters for Sarvam STT service. + ttfs_p99_latency: P99 latency from speech end to final transcript in seconds. + Override for your deployment. See https://github.com/pipecat-ai/stt-benchmark **kwargs: Additional arguments passed to the parent STTService. """ params = params or SarvamSTTService.InputParams() @@ -193,7 +197,7 @@ class SarvamSTTService(STTService): f"Model '{model}' does not support language parameter (auto-detects language)." ) - super().__init__(sample_rate=sample_rate, **kwargs) + super().__init__(sample_rate=sample_rate, ttfs_p99_latency=ttfs_p99_latency, **kwargs) self.set_model_name(model) self._api_key = api_key diff --git a/src/pipecat/services/soniox/stt.py b/src/pipecat/services/soniox/stt.py index 6f8c92d26..268e34508 100644 --- a/src/pipecat/services/soniox/stt.py +++ b/src/pipecat/services/soniox/stt.py @@ -24,6 +24,7 @@ from pipecat.frames.frames import ( VADUserStoppedSpeakingFrame, ) from pipecat.processors.frame_processor import FrameDirection +from pipecat.services.stt_latency import SONIOX_TTFS_P99 from pipecat.services.stt_service import WebsocketSTTService from pipecat.transcriptions.language import Language from pipecat.utils.time import time_now_iso8601 @@ -152,6 +153,7 @@ class SonioxSTTService(WebsocketSTTService): sample_rate: Optional[int] = None, params: Optional[SonioxInputParams] = None, vad_force_turn_endpoint: bool = False, + ttfs_p99_latency: Optional[float] = SONIOX_TTFS_P99, **kwargs, ): """Initialize the Soniox STT service. @@ -163,9 +165,11 @@ class SonioxSTTService(WebsocketSTTService): params: Additional configuration parameters, such as language hints, context and speaker diarization. vad_force_turn_endpoint: Listen to `VADUserStoppedSpeakingFrame` to send finalize message to Soniox. If disabled, Soniox will detect the end of the speech. + ttfs_p99_latency: P99 latency from speech end to final transcript in seconds. + Override for your deployment. See https://github.com/pipecat-ai/stt-benchmark **kwargs: Additional arguments passed to the STTService. """ - super().__init__(sample_rate=sample_rate, **kwargs) + super().__init__(sample_rate=sample_rate, ttfs_p99_latency=ttfs_p99_latency, **kwargs) params = params or SonioxInputParams() self._api_key = api_key diff --git a/src/pipecat/services/speechmatics/stt.py b/src/pipecat/services/speechmatics/stt.py index 41434addf..ca949a9fd 100644 --- a/src/pipecat/services/speechmatics/stt.py +++ b/src/pipecat/services/speechmatics/stt.py @@ -31,6 +31,7 @@ from pipecat.frames.frames import ( VADUserStoppedSpeakingFrame, ) from pipecat.processors.frame_processor import FrameDirection +from pipecat.services.stt_latency import SPEECHMATICS_TTFS_P99 from pipecat.services.stt_service import STTService from pipecat.transcriptions.language import Language, resolve_language from pipecat.utils.tracing.service_decorators import traced_stt @@ -288,6 +289,7 @@ class SpeechmaticsSTTService(STTService): sample_rate: int | None = None, params: InputParams | None = None, should_interrupt: bool = True, + ttfs_p99_latency: float | None = SPEECHMATICS_TTFS_P99, **kwargs, ): """Initialize the Speechmatics STT service. @@ -300,9 +302,11 @@ class SpeechmaticsSTTService(STTService): sample_rate: Optional audio sample rate in Hz. params: Optional[InputParams]: Input parameters for the service. should_interrupt: Determine whether the bot should be interrupted when Speechmatics turn_detection_mode is configured to detect user speech. + ttfs_p99_latency: P99 latency from speech end to final transcript in seconds. + Override for your deployment. See https://github.com/pipecat-ai/stt-benchmark **kwargs: Additional arguments passed to STTService. """ - super().__init__(sample_rate=sample_rate, **kwargs) + super().__init__(sample_rate=sample_rate, ttfs_p99_latency=ttfs_p99_latency, **kwargs) # Service parameters self._api_key: str = api_key or os.getenv("SPEECHMATICS_API_KEY") diff --git a/src/pipecat/services/stt_latency.py b/src/pipecat/services/stt_latency.py new file mode 100644 index 000000000..bf895e1e4 --- /dev/null +++ b/src/pipecat/services/stt_latency.py @@ -0,0 +1,53 @@ +# +# Copyright (c) 2024-2026, Daily +# +# SPDX-License-Identifier: BSD 2-Clause License +# + +"""STT service latency defaults. + +This module contains P99 time-to-final-segment (TTFS) latency values for STT +services. TTFS measures the time from when speech ends to when the final +transcript is received. + +These values are used by turn stop strategies to optimize timing. Each STT +service publishes its latency via STTMetadataFrame at pipeline start. + +To measure latency for your specific deployment (region, network conditions, +self-hosted instances), use the STT benchmark tool: +https://github.com/pipecat-ai/stt-benchmark + +Run the TTFS benchmark for your service and configuration, then pass the +measured value to your STT service constructor: + + stt = DeepgramSTTService(api_key="...", ttfs_p99_latency=0.45) +""" + +# Conservative fallback for services without measured values +DEFAULT_TTFS_P99: float = 1.0 + +# Measured P99 TTFS latency values (in seconds) +ASSEMBLYAI_TTFS_P99: float = 0.42 +AWS_TRANSCRIBE_TTFS_P99: float = 1.90 +AZURE_TTFS_P99: float = 1.80 +CARTESIA_TTFS_P99: float = 0.81 +DEEPGRAM_TTFS_P99: float = 0.35 +DEEPGRAM_SAGEMAKER_TTFS_P99: float = 0.35 +ELEVENLABS_TTFS_P99: float = 2.01 +ELEVENLABS_REALTIME_TTFS_P99: float = 0.41 +FAL_TTFS_P99: float = 2.07 +GLADIA_TTFS_P99: float = 1.49 +GOOGLE_TTFS_P99: float = 1.57 +GRADIUM_TTFS_P99: float = 1.61 +GROQ_TTFS_P99: float = 1.54 +HATHORA_TTFS_P99: float = 0.87 +OPENAI_TTFS_P99: float = 2.01 +OPENAI_REALTIME_TTFS_P99: float = 1.66 +SAMBANOVA_TTFS_P99: float = 2.20 +SARVAM_TTFS_P99: float = 1.17 +SONIOX_TTFS_P99: float = 0.35 +SPEECHMATICS_TTFS_P99: float = 0.74 + +# These services run locally and should be replaced with measured values +NVIDIA_TTFS_P99: float = DEFAULT_TTFS_P99 +WHISPER_TTFS_P99: float = DEFAULT_TTFS_P99 diff --git a/src/pipecat/services/stt_service.py b/src/pipecat/services/stt_service.py index 21422d6ef..53840221c 100644 --- a/src/pipecat/services/stt_service.py +++ b/src/pipecat/services/stt_service.py @@ -21,8 +21,9 @@ from pipecat.frames.frames import ( Frame, InterruptionFrame, MetricsFrame, - SpeechControlParamsFrame, + RequestMetadataFrame, StartFrame, + STTMetadataFrame, STTMuteFrame, STTUpdateSettingsFrame, TranscriptionFrame, @@ -32,6 +33,7 @@ from pipecat.frames.frames import ( from pipecat.metrics.metrics import TTFBMetricsData from pipecat.processors.frame_processor import FrameDirection from pipecat.services.ai_service import AIService +from pipecat.services.stt_latency import DEFAULT_TTFS_P99 from pipecat.services.websocket_service import WebsocketService from pipecat.transcriptions.language import Language @@ -65,11 +67,11 @@ class STTService(AIService): def __init__( self, + *, audio_passthrough=True, - # STT input sample rate sample_rate: Optional[int] = None, - # STT TTFB timeout - time to wait after VAD stop before reporting TTFB stt_ttfb_timeout: float = 2.0, + ttfs_p99_latency: Optional[float] = None, **kwargs, ): """Initialize the STT service. @@ -85,6 +87,10 @@ class STTService(AIService): request to first response byte). Since STT receives continuous audio, we measure from when the user stops speaking to when the final transcript arrives—capturing the latency that matters for voice AI applications. + ttfs_p99_latency: P99 latency from speech end to final transcript in seconds. + This is broadcast via STTMetadataFrame at pipeline start for downstream + processors (e.g., turn strategies) to optimize timing. Subclasses provide + measured defaults; pass a value here to override for your deployment. **kwargs: Additional arguments passed to the parent AIService. """ super().__init__(**kwargs) @@ -95,11 +101,11 @@ class STTService(AIService): self._tracing_enabled: bool = False self._muted: bool = False self._user_id: str = "" + self._ttfs_p99_latency = ttfs_p99_latency # STT TTFB tracking state self._stt_ttfb_timeout = stt_ttfb_timeout self._ttfb_timeout_task: Optional[asyncio.Task] = None - self._vad_stop_secs: Optional[float] = None self._speech_end_time: Optional[float] = None self._user_speaking: bool = False self._last_transcription_time: Optional[float] = None @@ -254,16 +260,20 @@ class STTService(AIService): """ await super().process_frame(frame, direction) - if isinstance(frame, AudioRawFrame): + if isinstance(frame, StartFrame): + # Push StartFrame first, then metadata so downstream receives them in order + await self.push_frame(frame, direction) + await self._push_stt_metadata() + elif isinstance(frame, RequestMetadataFrame): + # Don't push the RequestMetadataFrame, just push the metadata + await self._push_stt_metadata() + elif isinstance(frame, AudioRawFrame): # In this service we accumulate audio internally and at the end we # push a TextFrame. We also push audio downstream in case someone # else needs it. await self.process_audio_frame(frame, direction) if self._audio_passthrough: await self.push_frame(frame, direction) - elif isinstance(frame, SpeechControlParamsFrame): - await self._handle_speech_control_params(frame) - await self.push_frame(frame, direction) elif isinstance(frame, VADUserStartedSpeakingFrame): await self._handle_vad_user_started_speaking(frame) await self.push_frame(frame, direction) @@ -314,14 +324,13 @@ class STTService(AIService): await super().push_frame(frame, direction) - async def _handle_speech_control_params(self, frame: SpeechControlParamsFrame): - """Handle speech control parameters frame to extract VAD stop_secs. - - Args: - frame: The speech control parameters frame. - """ - if frame.vad_params is not None: - self._vad_stop_secs = frame.vad_params.stop_secs + async def _push_stt_metadata(self): + """Push STT metadata frame for downstream processors (e.g., turn strategies).""" + ttfs = self._ttfs_p99_latency + if ttfs is None: + ttfs = DEFAULT_TTFS_P99 + logger.warning(f"{self.name}: ttfs_p99_latency not set, using default {ttfs}s") + await self.broadcast_frame(STTMetadataFrame, service_name=self.name, ttfs_p99_latency=ttfs) async def _cancel_ttfb_timeout(self): """Cancel any pending TTFB timeout task.""" @@ -369,14 +378,14 @@ class STTService(AIService): """ self._user_speaking = False - # Skip TTFB measurement if we don't have VAD params - if self._vad_stop_secs is None: + # Skip TTFB measurement if stop_secs is not set + if frame.stop_secs == 0.0: return # Calculate the actual speech end time (current time minus VAD stop delay). # This approximates when the last user audio was sent to the STT service, # which we use to measure against the eventual transcription response. - self._speech_end_time = time.time() - self._vad_stop_secs + self._speech_end_time = frame.timestamp - frame.stop_secs # Start timeout task (any previous timeout was cancelled by VADUserStartedSpeakingFrame # or InterruptionFrame) diff --git a/src/pipecat/services/whisper/base_stt.py b/src/pipecat/services/whisper/base_stt.py index 79d2723f1..bc999dba4 100644 --- a/src/pipecat/services/whisper/base_stt.py +++ b/src/pipecat/services/whisper/base_stt.py @@ -17,6 +17,7 @@ from openai import AsyncOpenAI from openai.types.audio import Transcription from pipecat.frames.frames import ErrorFrame, Frame, TranscriptionFrame +from pipecat.services.stt_latency import WHISPER_TTFS_P99 from pipecat.services.stt_service import SegmentedSTTService from pipecat.transcriptions.language import Language, resolve_language from pipecat.utils.time import time_now_iso8601 @@ -115,6 +116,7 @@ class BaseWhisperSTTService(SegmentedSTTService): prompt: Optional[str] = None, temperature: Optional[float] = None, include_prob_metrics: bool = False, + ttfs_p99_latency: Optional[float] = WHISPER_TTFS_P99, **kwargs, ): """Initialize the Whisper STT service. @@ -129,9 +131,11 @@ class BaseWhisperSTTService(SegmentedSTTService): include_prob_metrics: If True, enables probability metrics in API response. Each service implements this differently (see child classes). Defaults to False. + ttfs_p99_latency: P99 latency from speech end to final transcript in seconds. + Override for your deployment. See https://github.com/pipecat-ai/stt-benchmark **kwargs: Additional arguments passed to SegmentedSTTService. """ - super().__init__(**kwargs) + super().__init__(ttfs_p99_latency=ttfs_p99_latency, **kwargs) self.set_model_name(model) self._client = self._create_client(api_key, base_url) self._language = self.language_to_service_language(language or Language.EN) diff --git a/src/pipecat/transports/base_input.py b/src/pipecat/transports/base_input.py index b76ae61ef..771fe39e1 100644 --- a/src/pipecat/transports/base_input.py +++ b/src/pipecat/transports/base_input.py @@ -464,7 +464,12 @@ class BaseInputTransport(FrameProcessor): if self._params.turn_analyzer: await self._deprecated_handle_user_interruption(VADState.QUIET) else: - await self.push_frame(VADUserStoppedSpeakingFrame()) + stop_secs = ( + self._params.vad_analyzer.params.stop_secs + if self._params.vad_analyzer + else 0.0 + ) + await self.push_frame(VADUserStoppedSpeakingFrame(stop_secs=stop_secs)) ################################################################### # @@ -492,9 +497,17 @@ class BaseInputTransport(FrameProcessor): and new_vad_state != VADState.STOPPING ): if new_vad_state == VADState.SPEAKING: - await self.push_frame(VADUserStartedSpeakingFrame()) + start_secs = ( + self._params.vad_analyzer.params.start_secs + if self._params.vad_analyzer + else 0.0 + ) + await self.push_frame(VADUserStartedSpeakingFrame(start_secs=start_secs)) elif new_vad_state == VADState.QUIET: - await self.push_frame(VADUserStoppedSpeakingFrame()) + stop_secs = ( + self._params.vad_analyzer.params.stop_secs if self._params.vad_analyzer else 0.0 + ) + await self.push_frame(VADUserStoppedSpeakingFrame(stop_secs=stop_secs)) vad_state = new_vad_state return vad_state @@ -574,11 +587,19 @@ class BaseInputTransport(FrameProcessor): or not self._params.turn_analyzer.speech_triggered ) if new_vad_state == VADState.SPEAKING: - await self.push_frame(VADUserStartedSpeakingFrame()) + start_secs = ( + self._params.vad_analyzer.params.start_secs + if self._params.vad_analyzer + else 0.0 + ) + await self.push_frame(VADUserStartedSpeakingFrame(start_secs=start_secs)) if can_create_user_frames: interruption_state = VADState.SPEAKING elif new_vad_state == VADState.QUIET: - await self.push_frame(VADUserStoppedSpeakingFrame()) + stop_secs = ( + self._params.vad_analyzer.params.stop_secs if self._params.vad_analyzer else 0.0 + ) + await self.push_frame(VADUserStoppedSpeakingFrame(stop_secs=stop_secs)) if can_create_user_frames: interruption_state = VADState.QUIET diff --git a/src/pipecat/turns/user_stop/__init__.py b/src/pipecat/turns/user_stop/__init__.py index b95a71d15..7ff676744 100644 --- a/src/pipecat/turns/user_stop/__init__.py +++ b/src/pipecat/turns/user_stop/__init__.py @@ -6,13 +6,13 @@ from .base_user_turn_stop_strategy import BaseUserTurnStopStrategy, UserTurnStoppedParams from .external_user_turn_stop_strategy import ExternalUserTurnStopStrategy -from .transcription_user_turn_stop_strategy import TranscriptionUserTurnStopStrategy +from .speech_timeout_user_turn_stop_strategy import SpeechTimeoutUserTurnStopStrategy from .turn_analyzer_user_turn_stop_strategy import TurnAnalyzerUserTurnStopStrategy __all__ = [ "BaseUserTurnStopStrategy", "ExternalUserTurnStopStrategy", + "SpeechTimeoutUserTurnStopStrategy", "UserTurnStoppedParams", - "TranscriptionUserTurnStopStrategy", "TurnAnalyzerUserTurnStopStrategy", ] diff --git a/src/pipecat/turns/user_stop/speech_timeout_user_turn_stop_strategy.py b/src/pipecat/turns/user_stop/speech_timeout_user_turn_stop_strategy.py new file mode 100644 index 000000000..66d6fa703 --- /dev/null +++ b/src/pipecat/turns/user_stop/speech_timeout_user_turn_stop_strategy.py @@ -0,0 +1,202 @@ +# +# Copyright (c) 2024-2026, Daily +# +# SPDX-License-Identifier: BSD 2-Clause License +# + +"""Speech timeout-based user turn stop strategy.""" + +import asyncio +import time +from typing import Optional + +from pipecat.frames.frames import ( + Frame, + STTMetadataFrame, + TranscriptionFrame, + VADUserStartedSpeakingFrame, + VADUserStoppedSpeakingFrame, +) +from pipecat.turns.user_stop.base_user_turn_stop_strategy import BaseUserTurnStopStrategy +from pipecat.utils.asyncio.task_manager import BaseTaskManager + + +class SpeechTimeoutUserTurnStopStrategy(BaseUserTurnStopStrategy): + """User turn stop strategy that uses a configurable timeout to determine if the user is done speaking. + + After the user stops speaking (detected by VAD), this strategy waits for a + configurable timeout before triggering the end of the user's turn. The + timeout accounts for two factors: + + - user_speech_timeout: Time to wait for the user to potentially say more + after they pause. + - stt_timeout: The P99 time for the STT service to return a transcription + after the user stops speaking, adjusted by the VAD stop_secs. + + For services that support finalization (TranscriptionFrame.finalized=True), + the turn can be triggered immediately once the finalized transcript is + received and the user resume speaking timeout has elapsed. + """ + + def __init__(self, *, user_speech_timeout: float = 0.6, **kwargs): + """Initialize the speech timeout-based user turn stop strategy. + + Args: + user_speech_timeout: Time to wait for the user to potentially + say more after they pause speaking. Defaults to 0.6 seconds. + **kwargs: Additional keyword arguments. + """ + super().__init__(**kwargs) + self._user_speech_timeout = user_speech_timeout + self._stt_timeout: float = 0.0 # STT P99 latency from STTMetadataFrame + self._stop_secs: float = 0.0 # VAD stop_secs from VADUserStoppedSpeakingFrame + + self._text = "" + self._vad_user_speaking = False + self._transcript_finalized = False + self._vad_stopped_time: Optional[float] = None + self._timeout_task: Optional[asyncio.Task] = None + + async def reset(self): + """Reset the strategy to its initial state.""" + await super().reset() + self._text = "" + self._vad_user_speaking = False + self._transcript_finalized = False + self._vad_stopped_time = None + + async def setup(self, task_manager: BaseTaskManager): + """Initialize the strategy with the given task manager. + + Args: + task_manager: The task manager to be associated with this instance. + """ + await super().setup(task_manager) + + async def cleanup(self): + """Cleanup the strategy.""" + await super().cleanup() + if self._timeout_task: + await self.task_manager.cancel_task(self._timeout_task) + self._timeout_task = None + + async def process_frame(self, frame: Frame): + """Process an incoming frame to update strategy state. + + Updates internal transcription text and VAD state. The user end turn + will be triggered when appropriate based on the collected frames. + + Args: + frame: The frame to be analyzed. + + """ + if isinstance(frame, STTMetadataFrame): + self._stt_timeout = frame.ttfs_p99_latency + elif isinstance(frame, VADUserStartedSpeakingFrame): + await self._handle_vad_user_started_speaking(frame) + elif isinstance(frame, VADUserStoppedSpeakingFrame): + await self._handle_vad_user_stopped_speaking(frame) + elif isinstance(frame, TranscriptionFrame): + await self._handle_transcription(frame) + + async def _handle_vad_user_started_speaking(self, _: VADUserStartedSpeakingFrame): + """Handle when the VAD indicates the user is speaking.""" + self._vad_user_speaking = True + self._transcript_finalized = False + self._vad_stopped_time = None + # Cancel any pending timeout + if self._timeout_task: + await self.task_manager.cancel_task(self._timeout_task) + self._timeout_task = None + + async def _handle_vad_user_stopped_speaking(self, frame: VADUserStoppedSpeakingFrame): + """Handle when the VAD indicates the user has stopped speaking.""" + self._vad_user_speaking = False + self._stop_secs = frame.stop_secs + self._vad_stopped_time = frame.timestamp + + # Start the timeout task + timeout = self._calculate_timeout() + self._timeout_task = self.task_manager.create_task( + self._timeout_handler(timeout), f"{self}::_timeout_handler" + ) + + async def _handle_transcription(self, frame: TranscriptionFrame): + """Handle user transcription.""" + self._text += frame.text + if frame.finalized: + self._transcript_finalized = True + # For finalized transcripts, check if we can trigger early + await self._maybe_trigger_user_turn_stopped() + + # Fallback: handle transcripts when no VAD stop was received. + # This handles edge cases where transcripts arrive without VAD firing. + # _vad_stopped_time is None means VAD stopped hasn't been received yet. + # In fallback mode, reset timeout on each transcript to wait for inactivity. + if not self._vad_user_speaking and self._vad_stopped_time is None: + # Cancel existing fallback timeout if any + if self._timeout_task: + await self.task_manager.cancel_task(self._timeout_task) + timeout = self._calculate_timeout() + self._timeout_task = self.task_manager.create_task( + self._timeout_handler(timeout), f"{self}::_timeout_handler" + ) + + def _calculate_timeout(self) -> float: + """Calculate the timeout value based on current state. + + Returns: + The timeout in seconds to wait after VAD stopped speaking. + """ + # Adjust STT timeout by VAD stop_secs since that time has already elapsed + effective_stt_wait = max(0, self._stt_timeout - self._stop_secs) + + # If transcript is already finalized, we don't need to wait for STT + if self._transcript_finalized: + return self._user_speech_timeout + + return max(effective_stt_wait, self._user_speech_timeout) + + async def _timeout_handler(self, timeout: float): + """Wait for the timeout then trigger user turn stopped if conditions met. + + Args: + timeout: The timeout in seconds to wait. + """ + try: + await asyncio.sleep(timeout) + except asyncio.CancelledError: + return + finally: + self._timeout_task = None + + await self._maybe_trigger_user_turn_stopped() + + async def _maybe_trigger_user_turn_stopped(self): + """Trigger user turn stopped if conditions are met. + + Conditions: + - User is not currently speaking + - We have transcription text + - Either the timeout has elapsed OR we have a finalized transcript + and user_speech_timeout has elapsed + """ + if self._vad_user_speaking or not self._text: + return + + # For finalized transcripts, check if user_speech_timeout has elapsed. + # If elapsed, trigger user turn stopped immediately. Else, wait for user resume + # speaking timeout. + if self._transcript_finalized and self._vad_stopped_time is not None: + elapsed = time.time() - self._vad_stopped_time + if elapsed >= self._user_speech_timeout: + # Cancel any remaining timeout since we're triggering now + if self._timeout_task: + await self.task_manager.cancel_task(self._timeout_task) + self._timeout_task = None + await self.trigger_user_turn_stopped() + return + + # For non-finalized, only trigger if timeout task has completed + if self._timeout_task is None: + await self.trigger_user_turn_stopped() diff --git a/src/pipecat/turns/user_stop/transcription_user_turn_stop_strategy.py b/src/pipecat/turns/user_stop/transcription_user_turn_stop_strategy.py index 5e037e6f7..a57aaad6d 100644 --- a/src/pipecat/turns/user_stop/transcription_user_turn_stop_strategy.py +++ b/src/pipecat/turns/user_stop/transcription_user_turn_stop_strategy.py @@ -4,124 +4,28 @@ # SPDX-License-Identifier: BSD 2-Clause License # -"""Transcription time-based user turn stop strategy.""" +"""Transcription-based user turn stop strategy (deprecated). -import asyncio -from typing import Optional +.. deprecated:: 0.0.102 + This module is deprecated. Please use + ``pipecat.turns.user_stop.speech_timeout_user_turn_stop_strategy.SpeechTimeoutUserTurnStopStrategy`` + instead. +""" -from pipecat.frames.frames import ( - Frame, - InterimTranscriptionFrame, - TranscriptionFrame, - VADUserStartedSpeakingFrame, - VADUserStoppedSpeakingFrame, +import warnings + +from pipecat.turns.user_stop.speech_timeout_user_turn_stop_strategy import ( + SpeechTimeoutUserTurnStopStrategy, ) -from pipecat.turns.user_stop.base_user_turn_stop_strategy import BaseUserTurnStopStrategy -from pipecat.utils.asyncio.task_manager import BaseTaskManager +with warnings.catch_warnings(): + warnings.simplefilter("always") + warnings.warn( + "TranscriptionUserTurnStopStrategy is deprecated. " + "Please use SpeechTimeoutUserTurnStopStrategy from " + "pipecat.turns.user_stop.speech_timeout_user_turn_stop_strategy instead.", + DeprecationWarning, + stacklevel=2, + ) -class TranscriptionUserTurnStopStrategy(BaseUserTurnStopStrategy): - """User turn stop strategy based on transcriptions. - - This strategy assumes the user stops speaking once a transcription has been - received. It handles multiple or delayed transcription frames gracefully. - - """ - - def __init__(self, *, timeout: float = 0.5, **kwargs): - """Initialize the transcription-based user turn stop strategy. - - Args: - timeout: A short delay used internally to handle consecutive or - slightly delayed transcriptions. - **kwargs: Additional keyword arguments. - """ - super().__init__(**kwargs) - self._timeout = timeout - self._text = "" - self._vad_user_speaking = False - self._seen_interim_results = False - self._event = asyncio.Event() - self._task: Optional[asyncio.Task] = None - - async def reset(self): - """Reset the strategy to its initial state.""" - await super().reset() - self._text = "" - self._vad_user_speaking = False - self._seen_interim_results = False - self._event.clear() - - async def setup(self, task_manager: BaseTaskManager): - """Initialize the strategy with the given task manager. - - Args: - task_manager: The task manager to be associated with this instance. - """ - await super().setup(task_manager) - self._task = task_manager.create_task(self._task_handler(), f"{self}::_task_handler") - - async def cleanup(self): - """Cleanup the strategy.""" - await super().cleanup() - if self._task: - await self.task_manager.cancel_task(self._task) - self._task = None - - async def process_frame(self, frame: Frame): - """Process an incoming frame to update strategy state. - - Updates internal transcription text and VAD state. The user end turn - will be triggered when appropriate based on the collected frames. - - Args: - frame: The frame to be analyzed. - - """ - if isinstance(frame, VADUserStartedSpeakingFrame): - await self._handle_vad_user_started_speaking(frame) - elif isinstance(frame, VADUserStoppedSpeakingFrame): - await self._handle_vad_user_stopped_speaking(frame) - elif isinstance(frame, InterimTranscriptionFrame): - await self._handle_interim_transcription(frame) - elif isinstance(frame, TranscriptionFrame): - await self._handle_transcription(frame) - - async def _handle_vad_user_started_speaking(self, _: VADUserStartedSpeakingFrame): - """Handle when the VAD indicates the user is speaking.""" - self._vad_user_speaking = True - - async def _handle_vad_user_stopped_speaking(self, _: VADUserStoppedSpeakingFrame): - """Handle when the VAD indicates the user has stopped speaking.""" - self._vad_user_speaking = False - await self._maybe_trigger_user_turn_stopped() - - async def _handle_interim_transcription(self, frame: InterimTranscriptionFrame): - self._seen_interim_results = True - - async def _handle_transcription(self, frame: TranscriptionFrame): - """Handle user transcription.""" - self._text += frame.text - # We just got a final result, so let's reset interim results. - self._seen_interim_results = False - # Reset aggregation timer. - self._event.set() - - async def _task_handler(self): - """Asynchronously monitor transcriptions and trigger user end turn when ready. - - If transcription text exists and the user is not currently speaking, - triggers the user end turn. Handles multiple or delayed transcriptions - gracefully. - - """ - while True: - try: - await asyncio.wait_for(self._event.wait(), timeout=self._timeout) - self._event.clear() - except asyncio.TimeoutError: - await self._maybe_trigger_user_turn_stopped() - - async def _maybe_trigger_user_turn_stopped(self): - if not self._vad_user_speaking and not self._seen_interim_results and self._text: - await self.trigger_user_turn_stopped() +TranscriptionUserTurnStopStrategy = SpeechTimeoutUserTurnStopStrategy diff --git a/src/pipecat/turns/user_stop/turn_analyzer_user_turn_stop_strategy.py b/src/pipecat/turns/user_stop/turn_analyzer_user_turn_stop_strategy.py index 109359c2a..acd4936a3 100644 --- a/src/pipecat/turns/user_stop/turn_analyzer_user_turn_stop_strategy.py +++ b/src/pipecat/turns/user_stop/turn_analyzer_user_turn_stop_strategy.py @@ -13,10 +13,10 @@ from pipecat.audio.turn.base_turn_analyzer import BaseTurnAnalyzer, EndOfTurnSta from pipecat.frames.frames import ( Frame, InputAudioRawFrame, - InterimTranscriptionFrame, MetricsFrame, SpeechControlParamsFrame, StartFrame, + STTMetadataFrame, TranscriptionFrame, VADUserStartedSpeakingFrame, VADUserStoppedSpeakingFrame, @@ -27,30 +27,38 @@ from pipecat.utils.asyncio.task_manager import BaseTaskManager class TurnAnalyzerUserTurnStopStrategy(BaseUserTurnStopStrategy): - """User turn stop strategy using a turn detection model to detect end of user turn. + """User turn stop strategy that uses a turn detection model to determine if the user is done speaking. - This strategy uses the turn detection models to determine when the user has - finished speaking, combining audio, VAD, and transcription frames. Once the - turn is considered complete, the user end of turn is triggered. + This strategy feeds audio, VAD, and transcription frames to a turn + detection model (``BaseTurnAnalyzer``) that predicts when the user has + finished their turn. Once the model indicates the turn is complete, the + strategy waits for a final transcription before triggering the end of + the user's turn. + For services that support finalization (TranscriptionFrame.finalized=True), + the turn can be triggered immediately once the finalized transcript is + received. Otherwise, an STT timeout (adjusted by VAD stop_secs) is used + as a fallback. """ - def __init__(self, *, turn_analyzer: BaseTurnAnalyzer, timeout: float = 0.5, **kwargs): + def __init__(self, *, turn_analyzer: BaseTurnAnalyzer, **kwargs): """Initialize the user turn stop strategy. Args: turn_analyzer: The turn detection analyzer instance to detect end of user turn. - timeout: Short delay used internally to handle frame timing and event triggering. **kwargs: Additional keyword arguments. """ super().__init__(**kwargs) self._turn_analyzer = turn_analyzer - self._timeout = timeout + self._stt_timeout: float = 0.0 # STT P99 latency from STTMetadataFrame + self._stop_secs: float = 0.0 # VAD stop_secs from VADUserStoppedSpeakingFrame + self._text = "" self._turn_complete = False self._vad_user_speaking = False - self._event = asyncio.Event() - self._task: Optional[asyncio.Task] = None + self._vad_stopped_time: Optional[float] = None # Track when VAD stopped was received + self._transcript_finalized = False + self._timeout_task: Optional[asyncio.Task] = None async def reset(self): """Reset the strategy to its initial state.""" @@ -58,7 +66,8 @@ class TurnAnalyzerUserTurnStopStrategy(BaseUserTurnStopStrategy): self._text = "" self._turn_complete = False self._vad_user_speaking = False - self._event.clear() + self._vad_stopped_time = None + self._transcript_finalized = False async def setup(self, task_manager: BaseTaskManager): """Initialize the strategy with the given task manager. @@ -67,15 +76,14 @@ class TurnAnalyzerUserTurnStopStrategy(BaseUserTurnStopStrategy): task_manager: The task manager to be associated with this instance. """ await super().setup(task_manager) - self._task = task_manager.create_task(self._task_handler(), f"{self}::_task_handler") async def cleanup(self): """Cleanup the strategy.""" await super().cleanup() await self._turn_analyzer.cleanup() - if self._task: - await self.task_manager.cancel_task(self._task) - self._task = None + if self._timeout_task: + await self.task_manager.cancel_task(self._timeout_task) + self._timeout_task = None async def process_frame(self, frame: Frame): """Process an incoming frame to update the turn analyzer and strategy state. @@ -87,8 +95,8 @@ class TurnAnalyzerUserTurnStopStrategy(BaseUserTurnStopStrategy): if isinstance(frame, StartFrame): await self._start(frame) - elif isinstance(frame, SpeechControlParamsFrame): - await self._handle_speech_control_params(frame) + elif isinstance(frame, STTMetadataFrame): + self._stt_timeout = frame.ttfs_p99_latency elif isinstance(frame, VADUserStartedSpeakingFrame): await self._handle_vad_user_started_speaking(frame) elif isinstance(frame, VADUserStoppedSpeakingFrame): @@ -97,25 +105,12 @@ class TurnAnalyzerUserTurnStopStrategy(BaseUserTurnStopStrategy): await self._handle_input_audio(frame) elif isinstance(frame, TranscriptionFrame): await self._handle_transcription(frame) - elif isinstance(frame, InterimTranscriptionFrame): - await self._handle_interim_transcription(frame) async def _start(self, frame: StartFrame): """Process the start frame to configure the turn analyzer.""" self._turn_analyzer.set_sample_rate(frame.audio_in_sample_rate) await self.broadcast_frame(SpeechControlParamsFrame, turn_params=self._turn_analyzer.params) - async def _handle_speech_control_params(self, frame: SpeechControlParamsFrame): - """Sync Smart Turn pre-speech buffering with VAD start delay. - - `VADUserStartedSpeakingFrame` is emitted only once VAD has confirmed speech - (after `vad_params.start_secs`). Smart Turn should still include the initial - audio collected during that confirmation window, so we let the analyzer know - when this value has changed. - """ - if frame.vad_params: - self._turn_analyzer.update_vad_start_secs(frame.vad_params.start_secs) - async def _handle_input_audio(self, frame: InputAudioRawFrame): """Handle input audio to check if the turn is completed.""" state = self._turn_analyzer.append_audio(frame.audio, self._vad_user_speaking) @@ -127,14 +122,24 @@ class TurnAnalyzerUserTurnStopStrategy(BaseUserTurnStopStrategy): self._turn_complete = True await self._maybe_trigger_user_turn_stopped() - async def _handle_vad_user_started_speaking(self, _: VADUserStartedSpeakingFrame): + async def _handle_vad_user_started_speaking(self, frame: VADUserStartedSpeakingFrame): """Handle when the VAD indicates the user is speaking.""" + # Sync Smart Turn pre-speech buffering with VAD start delay + self._turn_analyzer.update_vad_start_secs(frame.start_secs) self._turn_complete = False self._vad_user_speaking = True + self._vad_stopped_time = None + self._transcript_finalized = False + # Cancel any pending timeout + if self._timeout_task: + await self.task_manager.cancel_task(self._timeout_task) + self._timeout_task = None - async def _handle_vad_user_stopped_speaking(self, _: VADUserStoppedSpeakingFrame): + async def _handle_vad_user_stopped_speaking(self, frame: VADUserStoppedSpeakingFrame): """Handle when the VAD indicates the user has stopped speaking.""" self._vad_user_speaking = False + self._stop_secs = frame.stop_secs + self._vad_stopped_time = frame.timestamp state, prediction = await self._turn_analyzer.analyze_end_of_turn() await self._handle_prediction_result(prediction) @@ -143,41 +148,76 @@ class TurnAnalyzerUserTurnStopStrategy(BaseUserTurnStopStrategy): # wait for transcriptions. self._turn_complete = state == EndOfTurnState.COMPLETE - # Reset transcription timeout. - self._event.set() + # Start the STT timeout (adjusted by VAD stop_secs since that time already elapsed) + timeout = max(0, self._stt_timeout - self._stop_secs) + self._timeout_task = self.task_manager.create_task( + self._timeout_handler(timeout), f"{self}::_timeout_handler" + ) async def _handle_transcription(self, frame: TranscriptionFrame): """Handle user transcription.""" # We don't really care about the content. self._text = frame.text - # Reset transcription timeout. - self._event.set() + if frame.finalized: + self._transcript_finalized = True + # For finalized transcripts, trigger immediately if turn is complete + await self._maybe_trigger_user_turn_stopped() - async def _handle_interim_transcription(self, frame: InterimTranscriptionFrame): - """Handle user interim transcription.""" - # Reset transcription timeout. - self._event.set() + # Fallback: handle transcripts when no VAD stop was received. + # This handles edge cases where transcripts arrive without VAD firing. + # _vad_stopped_time is None means VAD stopped hasn't been received yet. + # In fallback mode, reset timeout on each transcript to wait for inactivity. + if not self._vad_user_speaking and self._vad_stopped_time is None: + # Cancel existing fallback timeout if any + if self._timeout_task: + await self.task_manager.cancel_task(self._timeout_task) + # Without VAD/turn analyzer data, assume turn is complete + self._turn_complete = True + timeout = max(0, self._stt_timeout - self._stop_secs) + self._timeout_task = self.task_manager.create_task( + self._timeout_handler(timeout), f"{self}::_timeout_handler" + ) async def _handle_prediction_result(self, result: Optional[MetricsData]): """Handle a prediction result event from the turn analyzer.""" if result: await self.push_frame(MetricsFrame(data=[result])) - async def _task_handler(self): - """Asynchronously monitor events and trigger user end of turn when appropriate. - - If we have not received a transcription in the specified amount of time - (and we initially received one) and the turn analyzer said the turn is - done, then the user is done speaking. + async def _timeout_handler(self, timeout: float): + """Wait for the timeout then trigger user turn stopped if conditions met. + Args: + timeout: The timeout in seconds to wait. """ - while True: - try: - await asyncio.wait_for(self._event.wait(), timeout=self._timeout) - self._event.clear() - except asyncio.TimeoutError: - await self._maybe_trigger_user_turn_stopped() + try: + await asyncio.sleep(timeout) + except asyncio.CancelledError: + return + finally: + self._timeout_task = None + + await self._maybe_trigger_user_turn_stopped() async def _maybe_trigger_user_turn_stopped(self): - if self._text and self._turn_complete: + """Trigger user turn stopped if conditions are met. + + Conditions: + - We have transcription text + - Turn analyzer indicates turn is complete + - Either the timeout has elapsed OR we have a finalized transcript + """ + if not self._text or not self._turn_complete: + return + + # For finalized transcripts, trigger immediately + if self._transcript_finalized: + # Cancel any remaining timeout since we're triggering now + if self._timeout_task: + await self.task_manager.cancel_task(self._timeout_task) + self._timeout_task = None + await self.trigger_user_turn_stopped() + return + + # For non-finalized, only trigger if timeout task has completed + if self._timeout_task is None: await self.trigger_user_turn_stopped() diff --git a/src/pipecat/turns/user_turn_strategies.py b/src/pipecat/turns/user_turn_strategies.py index eab64377a..fe637e0ed 100644 --- a/src/pipecat/turns/user_turn_strategies.py +++ b/src/pipecat/turns/user_turn_strategies.py @@ -18,7 +18,7 @@ from pipecat.turns.user_start import ( from pipecat.turns.user_stop import ( BaseUserTurnStopStrategy, ExternalUserTurnStopStrategy, - TranscriptionUserTurnStopStrategy, + SpeechTimeoutUserTurnStopStrategy, ) @@ -29,7 +29,7 @@ class UserTurnStrategies: If no strategies are specified, the following defaults are used: start: [VADUserTurnStartStrategy, TranscriptionUserTurnStartStrategy] - stop: [TranscriptionUserTurnStopStrategy] + stop: [SpeechTimeoutUserTurnStopStrategy] Attributes: start: A list of user turn start strategies used to detect when @@ -46,7 +46,7 @@ class UserTurnStrategies: if not self.start: self.start = [VADUserTurnStartStrategy(), TranscriptionUserTurnStartStrategy()] if not self.stop: - self.stop = [TranscriptionUserTurnStopStrategy()] + self.stop = [SpeechTimeoutUserTurnStopStrategy()] @dataclass diff --git a/tests/test_context_aggregators_universal.py b/tests/test_context_aggregators_universal.py index e612fbf5f..7e09a5449 100644 --- a/tests/test_context_aggregators_universal.py +++ b/tests/test_context_aggregators_universal.py @@ -41,7 +41,7 @@ from pipecat.processors.aggregators.llm_response_universal import ( ) from pipecat.tests.utils import SleepFrame, run_test from pipecat.turns.user_mute import FirstSpeechUserMuteStrategy, FunctionCallUserMuteStrategy -from pipecat.turns.user_stop import TranscriptionUserTurnStopStrategy +from pipecat.turns.user_stop import SpeechTimeoutUserTurnStopStrategy from pipecat.turns.user_turn_strategies import UserTurnStrategies USER_TURN_STOP_TIMEOUT = 0.2 @@ -149,7 +149,16 @@ class TestLLMUserAggregator(unittest.IsolatedAsyncioTestCase): async def test_default_user_turn_strategies(self): context = LLMContext() - user_aggregator = LLMUserAggregator(context) + user_aggregator = LLMUserAggregator( + context, + params=LLMUserAggregatorParams( + user_turn_strategies=UserTurnStrategies( + stop=[ + SpeechTimeoutUserTurnStopStrategy(user_speech_timeout=TRANSCRIPTION_TIMEOUT) + ], + ), + ), + ) should_start = None should_stop = None @@ -173,6 +182,8 @@ class TestLLMUserAggregator(unittest.IsolatedAsyncioTestCase): TranscriptionFrame(text="Hello!", user_id="", timestamp="now"), SleepFrame(), VADUserStoppedSpeakingFrame(), + # Wait for user_speech_timeout to elapse + SleepFrame(sleep=TRANSCRIPTION_TIMEOUT + 0.1), ] expected_down_frames = [ VADUserStartedSpeakingFrame, @@ -241,7 +252,9 @@ class TestLLMUserAggregator(unittest.IsolatedAsyncioTestCase): context, params=LLMUserAggregatorParams( user_turn_strategies=UserTurnStrategies( - stop=[TranscriptionUserTurnStopStrategy(timeout=TRANSCRIPTION_TIMEOUT)], + stop=[ + SpeechTimeoutUserTurnStopStrategy(user_speech_timeout=TRANSCRIPTION_TIMEOUT) + ], ), user_turn_stop_timeout=USER_TURN_STOP_TIMEOUT, ), @@ -270,13 +283,13 @@ class TestLLMUserAggregator(unittest.IsolatedAsyncioTestCase): pipeline = Pipeline([user_aggregator]) + # Transcript arrives before VAD stop, then we wait for user_speech_timeout frames_to_send = [ VADUserStartedSpeakingFrame(), - VADUserStoppedSpeakingFrame(), - SleepFrame(sleep=USER_TURN_STOP_TIMEOUT - 0.1), TranscriptionFrame(text="Hello!", user_id="", timestamp="now"), - SleepFrame(sleep=USER_TURN_STOP_TIMEOUT - 0.1), - SleepFrame(sleep=TRANSCRIPTION_TIMEOUT), + VADUserStoppedSpeakingFrame(), + # Wait for user_speech_timeout (TRANSCRIPTION_TIMEOUT=0.1s) to elapse + SleepFrame(sleep=TRANSCRIPTION_TIMEOUT + 0.05), ] await run_test( pipeline, diff --git a/tests/test_service_switcher.py b/tests/test_service_switcher.py index eef85e761..ac4f315df 100644 --- a/tests/test_service_switcher.py +++ b/tests/test_service_switcher.py @@ -12,6 +12,9 @@ from dataclasses import dataclass from pipecat.frames.frames import ( Frame, ManuallySwitchServiceFrame, + RequestMetadataFrame, + ServiceMetadataFrame, + StartFrame, SystemFrame, TextFrame, ) @@ -54,6 +57,47 @@ class MockFrameProcessor(FrameProcessor): self.frame_count = 0 +@dataclass +class MockMetadataFrame(ServiceMetadataFrame): + """A mock metadata frame for testing ServiceMetadataFrame handling.""" + + pass + + +class MockMetadataService(FrameProcessor): + """A mock service that emits ServiceMetadataFrame like STT services. + + Pushes MockMetadataFrame on StartFrame and RequestMetadataFrame. + """ + + def __init__(self, test_name: str, **kwargs): + super().__init__(name=test_name, **kwargs) + self.test_name = test_name + self.processed_frames = [] + self.metadata_push_count = 0 + + async def process_frame(self, frame: Frame, direction: FrameDirection): + await super().process_frame(frame, direction) + self.processed_frames.append(frame) + + if isinstance(frame, StartFrame): + await self.push_frame(frame, direction) + await self._push_metadata() + elif isinstance(frame, RequestMetadataFrame): + # Don't push RequestMetadataFrame downstream (it's internal) + await self._push_metadata() + else: + await self.push_frame(frame, direction) + + async def _push_metadata(self): + self.metadata_push_count += 1 + await self.push_frame(MockMetadataFrame(service_name=self.test_name)) + + def reset_counters(self): + self.processed_frames = [] + self.metadata_push_count = 0 + + @dataclass class DummySystemFrame(SystemFrame): """A dummy system frame for testing purposes.""" @@ -336,5 +380,84 @@ class TestServiceSwitcher(unittest.IsolatedAsyncioTestCase): self.assertEqual(switcher2_service2_texts[0].text, "After switching second switcher") +class TestServiceSwitcherMetadata(unittest.IsolatedAsyncioTestCase): + """Test cases for ServiceMetadataFrame handling in ServiceSwitcher.""" + + def setUp(self): + """Set up test fixtures with mock metadata services.""" + self.service1 = MockMetadataService("service1") + self.service2 = MockMetadataService("service2") + self.services = [self.service1, self.service2] + + async def test_only_active_service_metadata_at_startup(self): + """Test that only the active service's metadata leaves the ServiceSwitcher at startup.""" + switcher = ServiceSwitcher(self.services, ServiceSwitcherStrategyManual) + + # Run the pipeline (StartFrame triggers metadata emission) + output_frames = [] + + async def capture_frame(frame: Frame): + output_frames.append(frame) + + await run_test( + switcher, + frames_to_send=[TextFrame(text="test")], + expected_down_frames=[MockMetadataFrame, TextFrame], + expected_up_frames=[], + ) + + # Both services push metadata internally on StartFrame, but only the + # active service's metadata passes through the filter + self.assertEqual(self.service1.metadata_push_count, 1) # StartFrame (passes filter) + self.assertEqual(self.service2.metadata_push_count, 1) # StartFrame (blocked by filter) + + async def test_metadata_emitted_on_service_switch(self): + """Test that switching services triggers metadata emission from the new active service.""" + switcher = ServiceSwitcher(self.services, ServiceSwitcherStrategyManual) + + # Reset counters after startup + self.service1.reset_counters() + self.service2.reset_counters() + + await run_test( + switcher, + frames_to_send=[ + TextFrame(text="before switch"), + ManuallySwitchServiceFrame(service=self.service2), + TextFrame(text="after switch"), + ], + expected_down_frames=[ + MockMetadataFrame, # From startup (service1) + TextFrame, + ManuallySwitchServiceFrame, + TextFrame, + MockMetadataFrame, # From service2 after switch + ], + expected_up_frames=[], + ) + + # service2 should have received RequestMetadataFrame after becoming active + request_frames = [ + f for f in self.service2.processed_frames if isinstance(f, RequestMetadataFrame) + ] + self.assertEqual(len(request_frames), 1) + + async def test_inactive_service_metadata_blocked(self): + """Test that metadata from inactive services is blocked.""" + switcher = ServiceSwitcher(self.services, ServiceSwitcherStrategyManual) + + # Run and collect output frames + await run_test( + switcher, + frames_to_send=[TextFrame(text="test")], + expected_down_frames=[MockMetadataFrame, TextFrame], + expected_up_frames=[], + ) + + # service2 pushed metadata on StartFrame, but it should have been blocked + self.assertGreaterEqual(self.service2.metadata_push_count, 1) + # Only one MockMetadataFrame should have left (from service1) + + if __name__ == "__main__": unittest.main() diff --git a/tests/test_user_turn_controller.py b/tests/test_user_turn_controller.py index 5362847ec..72a04a519 100644 --- a/tests/test_user_turn_controller.py +++ b/tests/test_user_turn_controller.py @@ -18,11 +18,13 @@ from pipecat.frames.frames import ( from pipecat.turns.user_start.min_words_user_turn_start_strategy import ( MinWordsUserTurnStartStrategy, ) +from pipecat.turns.user_stop import SpeechTimeoutUserTurnStopStrategy from pipecat.turns.user_turn_controller import UserTurnController from pipecat.turns.user_turn_strategies import ExternalUserTurnStrategies, UserTurnStrategies from pipecat.utils.asyncio.task_manager import TaskManager, TaskManagerParams USER_TURN_STOP_TIMEOUT = 0.2 +TRANSCRIPTION_TIMEOUT = 0.1 class TestUserTurnController(unittest.IsolatedAsyncioTestCase): @@ -31,7 +33,11 @@ class TestUserTurnController(unittest.IsolatedAsyncioTestCase): self.task_manager.setup(TaskManagerParams(loop=asyncio.get_running_loop())) async def test_default_user_turn_strategies(self): - controller = UserTurnController(user_turn_strategies=UserTurnStrategies()) + controller = UserTurnController( + user_turn_strategies=UserTurnStrategies( + stop=[SpeechTimeoutUserTurnStopStrategy(user_speech_timeout=TRANSCRIPTION_TIMEOUT)], + ) + ) await controller.setup(self.task_manager) @@ -60,6 +66,8 @@ class TestUserTurnController(unittest.IsolatedAsyncioTestCase): await controller.process_frame(VADUserStoppedSpeakingFrame()) self.assertTrue(should_start) + # Wait for user_speech_timeout to elapse + await asyncio.sleep(TRANSCRIPTION_TIMEOUT + 0.1) self.assertTrue(should_stop) async def test_user_turn_start_reset(self): diff --git a/tests/test_user_turn_processor.py b/tests/test_user_turn_processor.py index ab4243cc4..02a4b29f6 100644 --- a/tests/test_user_turn_processor.py +++ b/tests/test_user_turn_processor.py @@ -16,7 +16,7 @@ from pipecat.frames.frames import ( ) from pipecat.pipeline.pipeline import Pipeline from pipecat.tests.utils import SleepFrame, run_test -from pipecat.turns.user_stop import TranscriptionUserTurnStopStrategy +from pipecat.turns.user_stop import SpeechTimeoutUserTurnStopStrategy from pipecat.turns.user_turn_processor import UserTurnProcessor from pipecat.turns.user_turn_strategies import UserTurnStrategies @@ -26,7 +26,11 @@ TRANSCRIPTION_TIMEOUT = 0.1 class TestUserTurnProcessor(unittest.IsolatedAsyncioTestCase): async def test_default_user_turn_strategies(self): - user_turn_processor = UserTurnProcessor(user_turn_strategies=UserTurnStrategies()) + user_turn_processor = UserTurnProcessor( + user_turn_strategies=UserTurnStrategies( + stop=[SpeechTimeoutUserTurnStopStrategy(user_speech_timeout=TRANSCRIPTION_TIMEOUT)], + ) + ) should_start = None should_stop = None @@ -48,6 +52,8 @@ class TestUserTurnProcessor(unittest.IsolatedAsyncioTestCase): TranscriptionFrame(text="Hello!", user_id="", timestamp="now"), SleepFrame(), VADUserStoppedSpeakingFrame(), + # Wait for user_speech_timeout to elapse + SleepFrame(sleep=TRANSCRIPTION_TIMEOUT + 0.1), ] expected_down_frames = [ VADUserStartedSpeakingFrame, @@ -109,7 +115,7 @@ class TestUserTurnProcessor(unittest.IsolatedAsyncioTestCase): async def test_user_turn_stop_timeout_transcription(self): user_turn_processor = UserTurnProcessor( user_turn_strategies=UserTurnStrategies( - stop=[TranscriptionUserTurnStopStrategy(timeout=TRANSCRIPTION_TIMEOUT)], + stop=[SpeechTimeoutUserTurnStopStrategy(user_speech_timeout=TRANSCRIPTION_TIMEOUT)], ), user_turn_stop_timeout=USER_TURN_STOP_TIMEOUT, ) @@ -135,13 +141,13 @@ class TestUserTurnProcessor(unittest.IsolatedAsyncioTestCase): pipeline = Pipeline([user_turn_processor]) + # Transcript arrives before VAD stop, then we wait for user_speech_timeout frames_to_send = [ VADUserStartedSpeakingFrame(), - VADUserStoppedSpeakingFrame(), - SleepFrame(sleep=USER_TURN_STOP_TIMEOUT - 0.1), TranscriptionFrame(text="Hello!", user_id="", timestamp="now"), - SleepFrame(sleep=USER_TURN_STOP_TIMEOUT - 0.1), - SleepFrame(sleep=TRANSCRIPTION_TIMEOUT), + VADUserStoppedSpeakingFrame(), + # Wait for user_speech_timeout (TRANSCRIPTION_TIMEOUT=0.1s) to elapse + SleepFrame(sleep=TRANSCRIPTION_TIMEOUT + 0.05), ] await run_test( pipeline, diff --git a/tests/test_user_turn_stop_strategy.py b/tests/test_user_turn_stop_strategy.py index d930705fd..80fb98efc 100644 --- a/tests/test_user_turn_stop_strategy.py +++ b/tests/test_user_turn_stop_strategy.py @@ -9,25 +9,38 @@ import unittest from pipecat.frames.frames import ( InterimTranscriptionFrame, + STTMetadataFrame, TranscriptionFrame, UserStartedSpeakingFrame, UserStoppedSpeakingFrame, VADUserStartedSpeakingFrame, VADUserStoppedSpeakingFrame, ) -from pipecat.turns.user_stop import ExternalUserTurnStopStrategy, TranscriptionUserTurnStopStrategy +from pipecat.turns.user_stop import ExternalUserTurnStopStrategy, SpeechTimeoutUserTurnStopStrategy from pipecat.utils.asyncio.task_manager import TaskManager, TaskManagerParams AGGREGATION_TIMEOUT = 0.1 +# Use 0 STT timeout for deterministic test timing +STT_TIMEOUT = 0.0 -class TestTranscriptionUserTurnStopStrategy(unittest.IsolatedAsyncioTestCase): +class TestSpeechTimeoutUserTurnStopStrategy(unittest.IsolatedAsyncioTestCase): async def asyncSetUp(self) -> None: self.task_manager = TaskManager() self.task_manager.setup(TaskManagerParams(loop=asyncio.get_running_loop())) + async def _create_strategy(self, user_speech_timeout=AGGREGATION_TIMEOUT): + """Create strategy and configure STT timeout via metadata frame.""" + strategy = SpeechTimeoutUserTurnStopStrategy(user_speech_timeout=user_speech_timeout) + await strategy.setup(self.task_manager) + # Set STT timeout via metadata frame (as would happen in real pipeline) + await strategy.process_frame( + STTMetadataFrame(service_name="test", ttfs_p99_latency=STT_TIMEOUT) + ) + return strategy + async def test_ste(self): - strategy = TranscriptionUserTurnStopStrategy() + strategy = await self._create_strategy() should_start = None @@ -46,13 +59,15 @@ class TestTranscriptionUserTurnStopStrategy(unittest.IsolatedAsyncioTestCase): # E await strategy.process_frame(VADUserStoppedSpeakingFrame()) + self.assertIsNone(should_start) - # Transcription comes in between user started/stopped and there are not - # interim, we just trigger bot speech. + # Transcription came in between user started/stopped. Now we wait for + # timeout before triggering. + await asyncio.sleep(AGGREGATION_TIMEOUT + 0.1) self.assertTrue(should_start) async def test_site(self): - strategy = TranscriptionUserTurnStopStrategy() + strategy = await self._create_strategy() should_start = None @@ -77,13 +92,15 @@ class TestTranscriptionUserTurnStopStrategy(unittest.IsolatedAsyncioTestCase): # E await strategy.process_frame(VADUserStoppedSpeakingFrame()) + self.assertIsNone(should_start) - # Transcription comes in between user started/stopped, so we trigger - # speech right away. + # Transcription came in between user started/stopped. Now we wait for + # timeout before triggering. + await asyncio.sleep(AGGREGATION_TIMEOUT + 0.1) self.assertTrue(should_start) async def test_st1iest2e(self): - strategy = TranscriptionUserTurnStopStrategy() + strategy = await self._create_strategy() should_start = None @@ -122,15 +139,14 @@ class TestTranscriptionUserTurnStopStrategy(unittest.IsolatedAsyncioTestCase): # E await strategy.process_frame(VADUserStoppedSpeakingFrame()) + self.assertIsNone(should_start) - # There was an interim before the first user stopped speaking, then we - # got a transcription comes in between user started/stopped, so we - # trigger speech right away. + # Now we wait for timeout before triggering. + await asyncio.sleep(AGGREGATION_TIMEOUT + 0.1) self.assertTrue(should_start) async def test_siet(self): - strategy = TranscriptionUserTurnStopStrategy(timeout=AGGREGATION_TIMEOUT) - await strategy.setup(self.task_manager) + strategy = await self._create_strategy() should_start = None @@ -163,8 +179,7 @@ class TestTranscriptionUserTurnStopStrategy(unittest.IsolatedAsyncioTestCase): self.assertTrue(should_start) async def test_sieit(self): - strategy = TranscriptionUserTurnStopStrategy(timeout=AGGREGATION_TIMEOUT) - await strategy.setup(self.task_manager) + strategy = await self._create_strategy() should_start = None @@ -205,8 +220,7 @@ class TestTranscriptionUserTurnStopStrategy(unittest.IsolatedAsyncioTestCase): self.assertTrue(should_start) async def test_set(self): - strategy = TranscriptionUserTurnStopStrategy(timeout=AGGREGATION_TIMEOUT) - await strategy.setup(self.task_manager) + strategy = await self._create_strategy() should_start = None @@ -235,8 +249,7 @@ class TestTranscriptionUserTurnStopStrategy(unittest.IsolatedAsyncioTestCase): self.assertTrue(should_start) async def test_seit(self): - strategy = TranscriptionUserTurnStopStrategy(timeout=AGGREGATION_TIMEOUT) - await strategy.setup(self.task_manager) + strategy = await self._create_strategy() should_start = None @@ -271,8 +284,7 @@ class TestTranscriptionUserTurnStopStrategy(unittest.IsolatedAsyncioTestCase): self.assertTrue(should_start) async def test_st1et2(self): - strategy = TranscriptionUserTurnStopStrategy(timeout=AGGREGATION_TIMEOUT) - await strategy.setup(self.task_manager) + strategy = await self._create_strategy() should_start = None @@ -291,26 +303,37 @@ class TestTranscriptionUserTurnStopStrategy(unittest.IsolatedAsyncioTestCase): # E await strategy.process_frame(VADUserStoppedSpeakingFrame()) + self.assertIsNone(should_start) - # Transcription comes between user start/stopped speaking, we need to - # trigger speech right away. + # Transcription came between user start/stopped speaking, wait for timeout. + await asyncio.sleep(AGGREGATION_TIMEOUT + 0.1) self.assertTrue(should_start) should_start = None + # Reset for next turn (in real usage, UserTurnController would do this) + await strategy.reset() + + # S - new turn starts + await strategy.process_frame(VADUserStartedSpeakingFrame()) + self.assertIsNone(should_start) + # T2 await strategy.process_frame( TranscriptionFrame(text="How are you?", user_id="cat", timestamp="") ) self.assertIsNone(should_start) + # E + await strategy.process_frame(VADUserStoppedSpeakingFrame()) + self.assertIsNone(should_start) + # Transcription comes after user stopped speaking, we need to wait for # at least the aggregation timeout. await asyncio.sleep(AGGREGATION_TIMEOUT + 0.1) self.assertTrue(should_start) async def test_set1t2(self): - strategy = TranscriptionUserTurnStopStrategy(timeout=AGGREGATION_TIMEOUT) - await strategy.setup(self.task_manager) + strategy = await self._create_strategy() should_start = None @@ -343,8 +366,7 @@ class TestTranscriptionUserTurnStopStrategy(unittest.IsolatedAsyncioTestCase): self.assertTrue(should_start) async def test_siet1it2(self): - strategy = TranscriptionUserTurnStopStrategy(timeout=AGGREGATION_TIMEOUT) - await strategy.setup(self.task_manager) + strategy = await self._create_strategy() should_start = None @@ -388,8 +410,8 @@ class TestTranscriptionUserTurnStopStrategy(unittest.IsolatedAsyncioTestCase): self.assertTrue(should_start) async def test_t(self): - strategy = TranscriptionUserTurnStopStrategy(timeout=AGGREGATION_TIMEOUT) - await strategy.setup(self.task_manager) + """Transcription without VAD - uses fallback timeout.""" + strategy = await self._create_strategy() should_start = None @@ -402,14 +424,13 @@ class TestTranscriptionUserTurnStopStrategy(unittest.IsolatedAsyncioTestCase): await strategy.process_frame(TranscriptionFrame(text="Hello!", user_id="cat", timestamp="")) self.assertIsNone(should_start) - # Transcription comes after user stopped speaking, we need to wait for - # at least the aggregation timeout. + # Transcription without VAD triggers fallback timeout. await asyncio.sleep(AGGREGATION_TIMEOUT + 0.1) self.assertTrue(should_start) async def test_it(self): - strategy = TranscriptionUserTurnStopStrategy(timeout=AGGREGATION_TIMEOUT) - await strategy.setup(self.task_manager) + """Interim + Transcription without VAD - uses fallback timeout.""" + strategy = await self._create_strategy() should_start = None @@ -427,14 +448,12 @@ class TestTranscriptionUserTurnStopStrategy(unittest.IsolatedAsyncioTestCase): await strategy.process_frame(TranscriptionFrame(text="Hello!", user_id="cat", timestamp="")) self.assertIsNone(should_start) - # Transcription comes after user stopped speaking, we need to wait for - # at least the aggregation timeout. + # Transcription without VAD triggers fallback timeout. await asyncio.sleep(AGGREGATION_TIMEOUT + 0.1) self.assertTrue(should_start) async def test_sie_delay_it(self): - strategy = TranscriptionUserTurnStopStrategy(timeout=AGGREGATION_TIMEOUT) - await strategy.setup(self.task_manager) + strategy = await self._create_strategy() should_start = None @@ -456,23 +475,22 @@ class TestTranscriptionUserTurnStopStrategy(unittest.IsolatedAsyncioTestCase): await strategy.process_frame(VADUserStoppedSpeakingFrame()) self.assertIsNone(should_start) - # Delay + # Delay - timeout expires but no transcript yet await asyncio.sleep(AGGREGATION_TIMEOUT + 0.1) + # Still no trigger because no transcript received + self.assertIsNone(should_start) # I await strategy.process_frame( InterimTranscriptionFrame(text="How", user_id="cat", timestamp="") ) - # T + # T (finalized) - triggers immediately since timeout already elapsed await strategy.process_frame( - TranscriptionFrame(text="How are you?", user_id="cat", timestamp="") + TranscriptionFrame(text="How are you?", user_id="cat", timestamp="", finalized=True) ) - self.assertIsNone(should_start) - # Transcription comes after user stopped speaking, we need to wait for - # at least the aggregation timeout. - await asyncio.sleep(AGGREGATION_TIMEOUT + 0.1) + # Finalized transcript received after timeout, triggers immediately self.assertTrue(should_start) From 5e66702cf5018bb8844208913d54166a27e6a190 Mon Sep 17 00:00:00 2001 From: Mark Backman Date: Fri, 6 Feb 2026 19:36:08 -0500 Subject: [PATCH 0400/1060] Improved the accuracy of the UserBotLatencyObserver and UserBotLatencyLogObserver --- changelog/3637.changed.5.md | 1 + .../observers/loggers/user_bot_latency_log_observer.py | 2 +- src/pipecat/observers/user_bot_latency_observer.py | 6 ++++-- 3 files changed, 6 insertions(+), 3 deletions(-) create mode 100644 changelog/3637.changed.5.md diff --git a/changelog/3637.changed.5.md b/changelog/3637.changed.5.md new file mode 100644 index 000000000..367f9f6e3 --- /dev/null +++ b/changelog/3637.changed.5.md @@ -0,0 +1 @@ +- Improved the accuracy of the `UserBotLatencyObserver` and `UserBotLatencyLogObserver` by measuring from the time when the user actually starts speaking. \ No newline at end of file diff --git a/src/pipecat/observers/loggers/user_bot_latency_log_observer.py b/src/pipecat/observers/loggers/user_bot_latency_log_observer.py index b15f989d1..2323a36ee 100644 --- a/src/pipecat/observers/loggers/user_bot_latency_log_observer.py +++ b/src/pipecat/observers/loggers/user_bot_latency_log_observer.py @@ -79,7 +79,7 @@ class UserBotLatencyLogObserver(BaseObserver): if isinstance(data.frame, VADUserStartedSpeakingFrame): self._user_stopped_time = 0 elif isinstance(data.frame, VADUserStoppedSpeakingFrame): - self._user_stopped_time = data.frame.timestamp + self._user_stopped_time = data.frame.timestamp - data.frame.stop_secs elif isinstance(data.frame, (EndFrame, CancelFrame)): self._log_summary() elif isinstance(data.frame, BotStartedSpeakingFrame) and self._user_stopped_time: diff --git a/src/pipecat/observers/user_bot_latency_observer.py b/src/pipecat/observers/user_bot_latency_observer.py index 17612ca76..37d5bc1a0 100644 --- a/src/pipecat/observers/user_bot_latency_observer.py +++ b/src/pipecat/observers/user_bot_latency_observer.py @@ -72,8 +72,10 @@ class UserBotLatencyObserver(BaseObserver): # Reset when user starts speaking self._user_stopped_time = None elif isinstance(data.frame, VADUserStoppedSpeakingFrame): - # Record timestamp when user stops speaking - self._user_stopped_time = data.frame.timestamp + # Record the actual time the user stopped speaking, which is + # the VAD determination time minus the stop_secs silence duration + # that had to elapse before the VAD confirmed speech ended. + self._user_stopped_time = data.frame.timestamp - data.frame.stop_secs elif isinstance(data.frame, BotStartedSpeakingFrame) and self._user_stopped_time: # Calculate and emit latency latency = time.time() - self._user_stopped_time From 2a572aedba7ab349e3e02a90aa39128db1abdbf0 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Aleix=20Conchillo=20Flaqu=C3=A9?= Date: Fri, 6 Feb 2026 19:18:18 -0800 Subject: [PATCH 0401/1060] Simplify ServiceSwitcher with closure-based filters - Make ServiceSwitcherStrategy inherit from BaseObject with properties for services and active_service, and move initial service selection into the base class - Add on_service_switched event to ServiceSwitcherStrategy - handle_frame now returns the switched-to service (or None), allowing ServiceSwitcher to swallow ManuallySwitchServiceFrame on switch and request metadata from the new active service - Override push_frame to suppress RequestMetadataFrame and ServiceMetadataFrame from inactive services - Remove ServiceSwitcherFilter and ServiceSwitcherFilterFrame in favor of plain FunctionFilter instances with closures that check the strategy's active service directly - FunctionFilter: add FilterType alias - FunctionFilter: when direction is None, frames in both directions are filtered instead of just one - Add docstrings to ServiceSwitcher and its components --- src/pipecat/pipeline/llm_switcher.py | 2 +- src/pipecat/pipeline/service_switcher.py | 270 +++++++++--------- .../processors/filters/function_filter.py | 18 +- tests/test_filters.py | 94 ++++++ tests/test_service_switcher.py | 74 +++-- 5 files changed, 297 insertions(+), 161 deletions(-) diff --git a/src/pipecat/pipeline/llm_switcher.py b/src/pipecat/pipeline/llm_switcher.py index 616a65b66..f9f53c066 100644 --- a/src/pipecat/pipeline/llm_switcher.py +++ b/src/pipecat/pipeline/llm_switcher.py @@ -44,7 +44,7 @@ class LLMSwitcher(ServiceSwitcher[StrategyType]): return self.services @property - def active_llm(self) -> Optional[LLMService]: + def active_llm(self) -> LLMService: """Get the currently active LLM. Returns: diff --git a/src/pipecat/pipeline/service_switcher.py b/src/pipecat/pipeline/service_switcher.py index 7bbd8ae74..2c4d54085 100644 --- a/src/pipecat/pipeline/service_switcher.py +++ b/src/pipecat/pipeline/service_switcher.py @@ -6,11 +6,10 @@ """Service switcher for switching between different services at runtime, with different switching strategies.""" -from dataclasses import dataclass +from abc import abstractmethod from typing import Any, Generic, List, Optional, Type, TypeVar from pipecat.frames.frames import ( - ControlFrame, Frame, ManuallySwitchServiceFrame, RequestMetadataFrame, @@ -20,14 +19,25 @@ from pipecat.frames.frames import ( from pipecat.pipeline.parallel_pipeline import ParallelPipeline from pipecat.processors.filters.function_filter import FunctionFilter from pipecat.processors.frame_processor import FrameDirection, FrameProcessor +from pipecat.utils.base_object import BaseObject -class ServiceSwitcherStrategy: +class ServiceSwitcherStrategy(BaseObject): """Base class for service switching strategies. Note: Strategy classes are instantiated internally by ServiceSwitcher. Developers should pass the strategy class (not an instance) to ServiceSwitcher. + + Event handlers available: + + - on_service_switched: Called when the active service changes. + + Example:: + + @strategy.event_handler("on_service_switched") + async def on_service_switched(strategy, service): + ... """ def __init__(self, services: List[FrameProcessor]): @@ -39,20 +49,42 @@ class ServiceSwitcherStrategy: Args: services: List of frame processors to switch between. """ - self.services = services - self.active_service: Optional[FrameProcessor] = None + super().__init__() - def handle_frame(self, frame: ServiceSwitcherFrame, direction: FrameDirection): + if len(services) == 0: + raise Exception(f"ServiceSwitcherStrategy needs at least one service") + + self._services = services + self._active_service = services[0] + + self._register_event_handler("on_service_switched") + + @property + def services(self) -> List[FrameProcessor]: + """Return the list of available services.""" + return self._services + + @property + def active_service(self) -> FrameProcessor: + """Return the currently active service.""" + return self._active_service + + @abstractmethod + async def handle_frame( + self, frame: ServiceSwitcherFrame, direction: FrameDirection + ) -> Optional[FrameProcessor]: """Handle a frame that controls service switching. - This method can be overridden by subclasses to implement specific logic - for handling frames that control service switching. + Subclasses implement this to decide whether a switch should occur. Args: frame: The frame to handle. direction: The direction of the frame (upstream or downstream). + + Returns: + The newly active service if a switch occurred, or None otherwise. """ - raise NotImplementedError("Subclasses must implement this method.") + pass class ServiceSwitcherStrategyManual(ServiceSwitcherStrategy): @@ -69,31 +101,24 @@ class ServiceSwitcherStrategyManual(ServiceSwitcherStrategy): ) """ - def __init__(self, services: List[FrameProcessor]): - """Initialize the manual service switcher strategy with a list of services. - - Note: - This is called internally by ServiceSwitcher. Do not instantiate directly. - - Args: - services: List of frame processors to switch between. - """ - super().__init__(services) - self.active_service = services[0] if services else None - - def handle_frame(self, frame: ServiceSwitcherFrame, direction: FrameDirection): + async def handle_frame( + self, frame: ServiceSwitcherFrame, direction: FrameDirection + ) -> Optional[FrameProcessor]: """Handle a frame that controls service switching. Args: frame: The frame to handle. direction: The direction of the frame (upstream or downstream). + + Returns: + The newly active service if a switch occurred, or None otherwise. """ if isinstance(frame, ManuallySwitchServiceFrame): - self._set_active_if_available(frame.service) - else: - raise ValueError(f"Unsupported frame type: {type(frame)}") + return await self._set_active_if_available(frame.service) - def _set_active_if_available(self, service: FrameProcessor): + return None + + async def _set_active_if_available(self, service: FrameProcessor) -> Optional[FrameProcessor]: """Set the active service to the given one, if it is in the list of available services. If it's not in the list, the request is ignored, as it may have been @@ -101,16 +126,35 @@ class ServiceSwitcherStrategyManual(ServiceSwitcherStrategy): Args: service: The service to set as active. + + Returns: + The newly active service, or None if the service was not found. """ if service in self.services: - self.active_service = service + self._active_service = service + await self._call_event_handler("on_service_switched", service) + return service + return None StrategyType = TypeVar("StrategyType", bound=ServiceSwitcherStrategy) class ServiceSwitcher(ParallelPipeline, Generic[StrategyType]): - """A pipeline that switches between different services at runtime.""" + """Parallel pipeline that routes frames to one active service at a time. + + Wraps each service in a pair of filters that gate frame flow based on + which service is currently active. Switching is controlled by + `ServiceSwitcherFrame` frames and delegated to a pluggable + `ServiceSwitcherStrategy`. + + Example:: + + switcher = ServiceSwitcher( + services=[stt_1, stt_2], + strategy_type=ServiceSwitcherStrategyManual, + ) + """ def __init__(self, services: List[FrameProcessor], strategy_type: Type[StrategyType]): """Initialize the service switcher with a list of services and a switching strategy. @@ -119,101 +163,20 @@ class ServiceSwitcher(ParallelPipeline, Generic[StrategyType]): services: List of frame processors to switch between. strategy_type: The strategy class to use for switching between services. """ - strategy = strategy_type(services) - super().__init__(*self._make_pipeline_definitions(services, strategy)) - self.services = services - self.strategy = strategy + _strategy = strategy_type(services) + super().__init__(*self._make_pipeline_definitions(services, _strategy)) + self._services = services + self._strategy = _strategy - class ServiceSwitcherFilter(FunctionFilter): - """An internal filter that gates frame flow based on active service. + @property + def strategy(self) -> StrategyType: + """Return the active switching strategy.""" + return self._strategy - Two filters "sandwich" each service, allowing frames through only - when the wrapped service is active. The pipeline layout is:: - - DownstreamFilter → Service → UpstreamFilter - - The filter names refer to which *direction* of frame flow they - filter, not their physical position: the downstream filter sits - *before* the service (filtering frames flowing into it) and the - upstream filter sits *after* it (filtering frames flowing back out). - """ - - def __init__( - self, - wrapped_service: FrameProcessor, - active_service: FrameProcessor, - direction: FrameDirection, - ): - """Initialize the service switcher filter with a strategy and direction. - - Args: - wrapped_service: The service that this filter wraps. - active_service: The currently active service. - direction: The direction of frame flow this filter gates - (DOWNSTREAM for the filter before the service, - UPSTREAM for the filter after it). - """ - self._wrapped_service = wrapped_service - self._active_service = active_service - - async def filter(_: Frame) -> bool: - return self._wrapped_service == self._active_service - - super().__init__(filter, direction, filter_system_frames=True) - - async def process_frame(self, frame, direction): - """Process a frame through the filter, handling special internal filter-updating frames.""" - if isinstance(frame, ServiceSwitcher.ServiceSwitcherFilterFrame): - old_active = self._active_service - self._active_service = frame.active_service - # Two ServiceSwitcherFilters "sandwich" a service. The - # frame enters via the downstream filter first. Push it - # through so the upstream filter also updates its state. - if direction == self._direction: - await self.push_frame(frame, direction) - # This is the upstream filter (the second to update). At - # this point both filters know the new active service, so - # it's safe to request metadata — the resulting - # ServiceMetadataFrame will pass both filters on its way - # out. Only do this for the newly active service's sandwich. - elif ( - self._direction == FrameDirection.UPSTREAM - and self._wrapped_service == frame.active_service - and old_active != self._wrapped_service - ): - await self.push_frame(RequestMetadataFrame(), FrameDirection.UPSTREAM) - return - - # RequestMetadataFrame is pushed upstream by the upstream filter - # (above) and consumed by the service. Guard against services - # that don't consume it: only forward in the filter's own - # direction (so it can reach the service) and only for the - # active service. Block in all other cases to prevent it from - # escaping the sandwich. - if isinstance(frame, RequestMetadataFrame): - if direction == self._direction and self._wrapped_service == self._active_service: - await self.push_frame(frame, direction) - return - - # Block ServiceMetadataFrame from inactive services. - if isinstance(frame, ServiceMetadataFrame): - if self._wrapped_service != self._active_service: - return - await self.push_frame(frame, direction) - return - - await super().process_frame(frame, direction) - - @dataclass - class ServiceSwitcherFilterFrame(ControlFrame): - """An internal frame used to update filter state on service switch. - - Sent when a service switch occurs to update the active service in - the sandwich filters and trigger metadata emission from the newly - active service. - """ - - active_service: FrameProcessor + @property + def services(self) -> List[FrameProcessor]: + """Return the list of available services.""" + return self._services @staticmethod def _make_pipeline_definitions( @@ -228,21 +191,53 @@ class ServiceSwitcher(ParallelPipeline, Generic[StrategyType]): def _make_pipeline_definition( service: FrameProcessor, strategy: ServiceSwitcherStrategy ) -> Any: - # Layout: DownstreamFilter → Service → UpstreamFilter + async def filter(_: Frame) -> bool: + return service == strategy.active_service + + # Layout: Filter → Service → Filter + # + # filter_system_frames: we want to run filter functions also on system + # frames. + # + # enable_direct_mode: filter functions are quick so we don't need + # additional tasks. return [ - ServiceSwitcher.ServiceSwitcherFilter( - wrapped_service=service, - active_service=strategy.active_service, + FunctionFilter( + filter=filter, direction=FrameDirection.DOWNSTREAM, + filter_system_frames=True, + enable_direct_mode=True, ), service, - ServiceSwitcher.ServiceSwitcherFilter( - wrapped_service=service, - active_service=strategy.active_service, + FunctionFilter( + filter=filter, direction=FrameDirection.UPSTREAM, + filter_system_frames=True, + enable_direct_mode=True, ), ] + async def push_frame(self, frame: Frame, direction: FrameDirection = FrameDirection.DOWNSTREAM): + """Push a frame out of the service switcher. + + Suppresses `RequestMetadataFrame` (internal to the switcher) and + `ServiceMetadataFrame` from inactive services so only the active + service's metadata reaches downstream processors. One case this happens + is with `StartFrame` since all the filters let it pass, and `StartFrame` + causes the service to generate `ServiceMetadataFrame`. + + """ + # Don't let RequestMetadataFrame out. + if isinstance(frame, RequestMetadataFrame): + return + + # Only let metadata from the active service escape. + if isinstance(frame, ServiceMetadataFrame): + if frame.service_name != self.strategy.active_service.name: + return + + await super().push_frame(frame, direction) + async def process_frame(self, frame: Frame, direction: FrameDirection): """Process a frame, handling frames which affect service switching. @@ -250,11 +245,16 @@ class ServiceSwitcher(ParallelPipeline, Generic[StrategyType]): frame: The frame to process. direction: The direction of the frame (upstream or downstream). """ - await super().process_frame(frame, direction) - if isinstance(frame, ServiceSwitcherFrame): - self.strategy.handle_frame(frame, direction) - service_switcher_filter_frame = ServiceSwitcher.ServiceSwitcherFilterFrame( - active_service=self.strategy.active_service - ) - await super().process_frame(service_switcher_filter_frame, direction) + service = await self.strategy.handle_frame(frame, direction) + + # If we don't switch to a new service we need to keep processing the + # frame. If we switched, we just swallow the frame. + if not service: + await super().process_frame(frame, direction) + + # If we switched to a new service, request its metadata. + if service: + await service.queue_frame(RequestMetadataFrame()) + else: + await super().process_frame(frame, direction) diff --git a/src/pipecat/processors/filters/function_filter.py b/src/pipecat/processors/filters/function_filter.py index 28567653f..46b1945ce 100644 --- a/src/pipecat/processors/filters/function_filter.py +++ b/src/pipecat/processors/filters/function_filter.py @@ -10,11 +10,13 @@ This module provides a processor that filters frames based on a custom function, allowing for flexible frame filtering logic in processing pipelines. """ -from typing import Awaitable, Callable +from typing import Awaitable, Callable, Optional from pipecat.frames.frames import CancelFrame, EndFrame, Frame, StartFrame, SystemFrame from pipecat.processors.frame_processor import FrameDirection, FrameProcessor +FilterType = Callable[[Frame], Awaitable[bool]] + class FunctionFilter(FrameProcessor): """A frame processor that filters frames using a custom function. @@ -26,9 +28,10 @@ class FunctionFilter(FrameProcessor): def __init__( self, - filter: Callable[[Frame], Awaitable[bool]], - direction: FrameDirection = FrameDirection.DOWNSTREAM, + filter: FilterType, + direction: Optional[FrameDirection] = FrameDirection.DOWNSTREAM, filter_system_frames: bool = False, + **kwargs, ): """Initialize the function filter. @@ -36,10 +39,13 @@ class FunctionFilter(FrameProcessor): filter: An async function that takes a Frame and returns True if the frame should pass through, False otherwise. direction: The direction to apply filtering. Only frames moving in - this direction will be filtered. Defaults to DOWNSTREAM. + this direction will be filtered; frames in the other direction + pass through unfiltered. If None, frames in both directions + are filtered. Defaults to DOWNSTREAM. filter_system_frames: Whether to filter system frames. Defaults to False. + **kwargs: Additional arguments passed to parent class. """ - super().__init__() + super().__init__(**kwargs) self._filter = filter self._direction = direction self._filter_system_frames = filter_system_frames @@ -51,7 +57,7 @@ class FunctionFilter(FrameProcessor): def _should_passthrough_frame(self, frame, direction): """Check if a frame should pass through without filtering.""" # Always passthrough frames in the wrong direction - if direction != self._direction: + if self._direction and direction != self._direction: return True # Always passthrough lifecycle frames diff --git a/tests/test_filters.py b/tests/test_filters.py index b62239aeb..564ba4a08 100644 --- a/tests/test_filters.py +++ b/tests/test_filters.py @@ -14,10 +14,12 @@ from pipecat.frames.frames import ( UserStartedSpeakingFrame, UserStoppedSpeakingFrame, ) +from pipecat.pipeline.pipeline import Pipeline from pipecat.processors.filters.frame_filter import FrameFilter from pipecat.processors.filters.function_filter import FunctionFilter from pipecat.processors.filters.identity_filter import IdentityFilter from pipecat.processors.filters.wake_check_filter import WakeCheckFilter +from pipecat.processors.frame_processor import FrameDirection, FrameProcessor from pipecat.tests.utils import run_test @@ -93,6 +95,98 @@ class TestFunctionFilter(unittest.IsolatedAsyncioTestCase): expected_down_frames=expected_down_frames, ) + async def test_no_direction_filters_both_directions(self): + """When direction is None, frames in both directions are filtered.""" + + class UpstreamPusher(FrameProcessor): + """Pushes a TextFrame upstream when it receives a system frame.""" + + async def process_frame(self, frame: Frame, direction: FrameDirection): + await super().process_frame(frame, direction) + await self.push_frame(frame, direction) + if isinstance(frame, UserStartedSpeakingFrame): + await self.push_frame(TextFrame(text="upstream"), FrameDirection.UPSTREAM) + + async def block_text(frame: Frame): + return not isinstance(frame, TextFrame) + + # direction=None: filter applies in both directions. The downstream + # TextFrame is blocked and the upstream TextFrame pushed by + # UpstreamPusher is also blocked. + filter = FunctionFilter(filter=block_text, direction=None) + pipeline = Pipeline([filter, UpstreamPusher()]) + frames_to_send = [ + TextFrame(text="Hello!"), + UserStartedSpeakingFrame(), + ] + expected_down_frames = [UserStartedSpeakingFrame] + expected_up_frames = [] + await run_test( + pipeline, + frames_to_send=frames_to_send, + expected_down_frames=expected_down_frames, + expected_up_frames=expected_up_frames, + ) + + async def test_downstream_direction_passes_upstream(self): + """When direction is DOWNSTREAM, upstream frames pass through unfiltered.""" + + class UpstreamPusher(FrameProcessor): + """Pushes a TextFrame upstream when it receives a system frame.""" + + async def process_frame(self, frame: Frame, direction: FrameDirection): + await super().process_frame(frame, direction) + await self.push_frame(frame, direction) + if isinstance(frame, UserStartedSpeakingFrame): + await self.push_frame(TextFrame(text="upstream"), FrameDirection.UPSTREAM) + + async def block_text(frame: Frame): + return not isinstance(frame, TextFrame) + + # direction=DOWNSTREAM: filter only applies downstream, so the + # upstream TextFrame pushed by UpstreamPusher passes through. + filter = FunctionFilter(filter=block_text) + pipeline = Pipeline([filter, UpstreamPusher()]) + frames_to_send = [UserStartedSpeakingFrame()] + expected_down_frames = [UserStartedSpeakingFrame] + expected_up_frames = [TextFrame] + await run_test( + pipeline, + frames_to_send=frames_to_send, + expected_down_frames=expected_down_frames, + expected_up_frames=expected_up_frames, + ) + + async def test_upstream_direction_passes_downstream(self): + """When direction is UPSTREAM, downstream frames pass through unfiltered.""" + + class UpstreamPusher(FrameProcessor): + """Pushes a TextFrame upstream when it receives a system frame.""" + + async def process_frame(self, frame: Frame, direction: FrameDirection): + await super().process_frame(frame, direction) + await self.push_frame(frame, direction) + if isinstance(frame, UserStartedSpeakingFrame): + await self.push_frame(TextFrame(text="upstream"), FrameDirection.UPSTREAM) + + async def block_text(frame: Frame): + return not isinstance(frame, TextFrame) + + # direction=UPSTREAM: filter only applies upstream, so the + # downstream TextFrame passes through but the upstream TextFrame + # pushed by UpstreamPusher is blocked. + filter = FunctionFilter(filter=block_text, direction=FrameDirection.UPSTREAM) + pipeline = Pipeline([filter, UpstreamPusher()]) + frames_to_send = [TextFrame(text="Hello!"), UserStartedSpeakingFrame()] + expected_down_frames = [UserStartedSpeakingFrame, TextFrame] + expected_up_frames = [] + await run_test( + pipeline, + frames_to_send=frames_to_send, + expected_down_frames=expected_down_frames, + expected_up_frames=expected_up_frames, + ) + class TestWakeCheckFilter(unittest.IsolatedAsyncioTestCase): async def test_no_wake_word(self): diff --git a/tests/test_service_switcher.py b/tests/test_service_switcher.py index ac4f315df..3f1f586fe 100644 --- a/tests/test_service_switcher.py +++ b/tests/test_service_switcher.py @@ -6,6 +6,7 @@ """Unit tests for ServiceSwitcher and related components.""" +import asyncio import unittest from dataclasses import dataclass @@ -122,14 +123,7 @@ class TestServiceSwitcherStrategyManual(unittest.IsolatedAsyncioTestCase): self.assertEqual(strategy.services, self.services) self.assertEqual(strategy.active_service, self.service1) # First service should be active - def test_init_with_empty_services(self): - """Test initialization with an empty list of services.""" - strategy = ServiceSwitcherStrategyManual([]) - - self.assertEqual(strategy.services, []) - self.assertIsNone(strategy.active_service) - - def test_handle_manually_switch_service_frame(self): + async def test_handle_manually_switch_service_frame(self): """Test manual service switching with ManuallySwitchServiceFrame.""" strategy = ServiceSwitcherStrategyManual(self.services) @@ -139,7 +133,7 @@ class TestServiceSwitcherStrategyManual(unittest.IsolatedAsyncioTestCase): # Switch to service2 switch_frame = ManuallySwitchServiceFrame(service=self.service2) - strategy.handle_frame(switch_frame, FrameDirection.DOWNSTREAM) + await strategy.handle_frame(switch_frame, FrameDirection.DOWNSTREAM) self.assertNotEqual(strategy.active_service, self.service1) self.assertEqual(strategy.active_service, self.service2) @@ -147,21 +141,66 @@ class TestServiceSwitcherStrategyManual(unittest.IsolatedAsyncioTestCase): # Switch to service3 switch_frame = ManuallySwitchServiceFrame(service=self.service3) - strategy.handle_frame(switch_frame, FrameDirection.DOWNSTREAM) + await strategy.handle_frame(switch_frame, FrameDirection.DOWNSTREAM) self.assertNotEqual(strategy.active_service, self.service1) self.assertNotEqual(strategy.active_service, self.service2) self.assertEqual(strategy.active_service, self.service3) - def test_handle_frame_unsupported_frame_type(self): + async def test_on_service_switched_event(self): + """Test that on_service_switched event fires with correct arguments.""" + strategy = ServiceSwitcherStrategyManual(self.services) + + switched_events = [] + + @strategy.event_handler("on_service_switched") + async def on_service_switched(strategy, service): + switched_events.append((strategy, service)) + + # Switch to service2 + switch_frame = ManuallySwitchServiceFrame(service=self.service2) + await strategy.handle_frame(switch_frame, FrameDirection.DOWNSTREAM) + await asyncio.sleep(0) # Let async event task run + + self.assertEqual(len(switched_events), 1) + self.assertIsInstance(switched_events[0][0], ServiceSwitcherStrategyManual) + self.assertEqual(switched_events[0][1], self.service2) + + # Switch to service3 + switch_frame = ManuallySwitchServiceFrame(service=self.service3) + await strategy.handle_frame(switch_frame, FrameDirection.DOWNSTREAM) + await asyncio.sleep(0) + + self.assertEqual(len(switched_events), 2) + self.assertEqual(switched_events[1][1], self.service3) + + async def test_on_service_switched_event_not_fired_for_unknown_service(self): + """Test that on_service_switched event does not fire for services not in the list.""" + strategy = ServiceSwitcherStrategyManual(self.services) + + switched_events = [] + + @strategy.event_handler("on_service_switched") + async def on_service_switched(strategy, service): + switched_events.append(service) + + # Try switching to a service not in the list + unknown_service = MockFrameProcessor("unknown") + switch_frame = ManuallySwitchServiceFrame(service=unknown_service) + await strategy.handle_frame(switch_frame, FrameDirection.DOWNSTREAM) + await asyncio.sleep(0) + + self.assertEqual(len(switched_events), 0) + self.assertEqual(strategy.active_service, self.service1) # Unchanged + + async def test_handle_frame_unsupported_frame_type(self): """Test that unsupported frame types raise an error.""" strategy = ServiceSwitcherStrategyManual(self.services) unsupported_frame = TextFrame(text="test") # Not a ServiceSwitcherFrame - with self.assertRaises(ValueError) as context: - strategy.handle_frame(unsupported_frame, FrameDirection.DOWNSTREAM) + result = await strategy.handle_frame(unsupported_frame, FrameDirection.DOWNSTREAM) - self.assertIn("Unsupported frame type", str(context.exception)) + self.assertIsNone(result) class TestServiceSwitcher(unittest.IsolatedAsyncioTestCase): @@ -267,7 +306,7 @@ class TestServiceSwitcher(unittest.IsolatedAsyncioTestCase): ManuallySwitchServiceFrame(service=self.service2), TextFrame("Hello 2"), ], - expected_down_frames=[TextFrame, ManuallySwitchServiceFrame, TextFrame], + expected_down_frames=[TextFrame, TextFrame], expected_up_frames=[], # Expect no error frames ) @@ -333,9 +372,7 @@ class TestServiceSwitcher(unittest.IsolatedAsyncioTestCase): ], expected_down_frames=[ TextFrame, - ManuallySwitchServiceFrame, TextFrame, - ManuallySwitchServiceFrame, TextFrame, ], expected_up_frames=[], # Expect no error frames @@ -429,9 +466,8 @@ class TestServiceSwitcherMetadata(unittest.IsolatedAsyncioTestCase): expected_down_frames=[ MockMetadataFrame, # From startup (service1) TextFrame, - ManuallySwitchServiceFrame, - TextFrame, MockMetadataFrame, # From service2 after switch + TextFrame, ], expected_up_frames=[], ) From 00ec6c77ea03ba74fce7259aa01c93005bd17c83 Mon Sep 17 00:00:00 2001 From: Mark Backman Date: Mon, 9 Feb 2026 12:30:23 -0500 Subject: [PATCH 0402/1060] Emit RTVI events for user mute/unmute state changes Add UserMuteStartedFrame/UserMuteStoppedFrame and corresponding RTVI messages so clients can observe when mute strategies activate/deactivate. --- changelog/3687.added.md | 1 + src/pipecat/frames/frames.py | 22 +++++++++++++ .../aggregators/llm_response_universal.py | 4 +++ src/pipecat/processors/frameworks/rtvi.py | 33 +++++++++++++++++++ 4 files changed, 60 insertions(+) create mode 100644 changelog/3687.added.md diff --git a/changelog/3687.added.md b/changelog/3687.added.md new file mode 100644 index 000000000..38a10fb75 --- /dev/null +++ b/changelog/3687.added.md @@ -0,0 +1 @@ +- Added `UserMuteStartedFrame` and `UserMuteStoppedFrame` system frames, and corresponding `user-mute-started` / `user-mute-stopped` RTVI messages, so clients can observe when mute strategies activate or deactivate. diff --git a/src/pipecat/frames/frames.py b/src/pipecat/frames/frames.py index b7be8045e..cb0dd0cee 100644 --- a/src/pipecat/frames/frames.py +++ b/src/pipecat/frames/frames.py @@ -1208,6 +1208,28 @@ class UserStoppedSpeakingFrame(SystemFrame): emulated: bool = False +@dataclass +class UserMuteStartedFrame(SystemFrame): + """Frame indicating that the user has been muted. + + Emitted when a mute strategy activates, suppressing user frames (audio, + transcription, interruption) from propagating through the pipeline. + """ + + pass + + +@dataclass +class UserMuteStoppedFrame(SystemFrame): + """Frame indicating that the user has been unmuted. + + Emitted when a mute strategy deactivates, allowing user frames to + propagate through the pipeline again. + """ + + pass + + @dataclass class UserSpeakingFrame(SystemFrame): """Frame indicating the user is speaking. diff --git a/src/pipecat/processors/aggregators/llm_response_universal.py b/src/pipecat/processors/aggregators/llm_response_universal.py index cf65c6443..05090dcc0 100644 --- a/src/pipecat/processors/aggregators/llm_response_universal.py +++ b/src/pipecat/processors/aggregators/llm_response_universal.py @@ -53,6 +53,8 @@ from pipecat.frames.frames import ( TextFrame, TranscriptionFrame, UserImageRawFrame, + UserMuteStartedFrame, + UserMuteStoppedFrame, UserSpeakingFrame, UserStartedSpeakingFrame, UserStoppedSpeakingFrame, @@ -569,8 +571,10 @@ class LLMUserAggregator(LLMContextAggregator): # Emit mute state change events if self._user_is_muted: await self._call_event_handler("on_user_mute_started") + await self.broadcast_frame(UserMuteStartedFrame) else: await self._call_event_handler("on_user_mute_stopped") + await self.broadcast_frame(UserMuteStoppedFrame) return should_mute_frame diff --git a/src/pipecat/processors/frameworks/rtvi.py b/src/pipecat/processors/frameworks/rtvi.py index 61c3ef57e..cbb0d706f 100644 --- a/src/pipecat/processors/frameworks/rtvi.py +++ b/src/pipecat/processors/frameworks/rtvi.py @@ -67,6 +67,8 @@ from pipecat.frames.frames import ( TTSStartedFrame, TTSStoppedFrame, TTSTextFrame, + UserMuteStartedFrame, + UserMuteStoppedFrame, UserStartedSpeakingFrame, UserStoppedSpeakingFrame, ) @@ -891,6 +893,20 @@ class RTVIUserStoppedSpeakingMessage(BaseModel): type: Literal["user-stopped-speaking"] = "user-stopped-speaking" +class RTVIUserMuteStartedMessage(BaseModel): + """Message indicating user has been muted.""" + + label: RTVIMessageLiteral = RTVI_MESSAGE_LABEL + type: Literal["user-mute-started"] = "user-mute-started" + + +class RTVIUserMuteStoppedMessage(BaseModel): + """Message indicating user has been unmuted.""" + + label: RTVIMessageLiteral = RTVI_MESSAGE_LABEL + type: Literal["user-mute-stopped"] = "user-mute-stopped" + + class RTVIBotStartedSpeakingMessage(BaseModel): """Message indicating bot has started speaking.""" @@ -1043,6 +1059,7 @@ class RTVIObserverParams: bot_audio_level_enabled: bool = False user_llm_enabled: bool = True user_speaking_enabled: bool = True + user_mute_enabled: bool = True user_transcription_enabled: bool = True user_audio_level_enabled: bool = False metrics_enabled: bool = True @@ -1212,6 +1229,11 @@ class RTVIObserver(BaseObserver): and self._params.user_speaking_enabled ): await self._handle_interruptions(frame) + elif ( + isinstance(frame, (UserMuteStartedFrame, UserMuteStoppedFrame)) + and self._params.user_mute_enabled + ): + await self._handle_user_mute(frame) elif ( isinstance(frame, (BotStartedSpeakingFrame, BotStoppedSpeakingFrame)) and self._params.bot_speaking_enabled @@ -1343,6 +1365,17 @@ class RTVIObserver(BaseObserver): if message: await self.send_rtvi_message(message) + async def _handle_user_mute(self, frame: Frame): + """Handle user mute/unmute frames.""" + message = None + if isinstance(frame, UserMuteStartedFrame): + message = RTVIUserMuteStartedMessage() + elif isinstance(frame, UserMuteStoppedFrame): + message = RTVIUserMuteStoppedMessage() + + if message: + await self.send_rtvi_message(message) + async def _handle_bot_speaking(self, frame: Frame): """Handle bot speaking event frames.""" message = None From 631463e573a797c565b7bbe36364687601a37d47 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Aleix=20Conchillo=20Flaqu=C3=A9?= Date: Mon, 9 Feb 2026 11:25:22 -0800 Subject: [PATCH 0403/1060] Use TurnAnalyzerUserTurnStopStrategy as default stop strategy Change the default user turn stop strategy from TranscriptionUserTurnStopStrategy to TurnAnalyzerUserTurnStopStrategy with LocalSmartTurnAnalyzerV3. Also reduce AUDIO_INPUT_TIMEOUT_SECS from 1.0 to 0.5 and remove its debug log. --- src/pipecat/transports/base_input.py | 4 +--- src/pipecat/turns/user_turn_strategies.py | 7 ++++--- 2 files changed, 5 insertions(+), 6 deletions(-) diff --git a/src/pipecat/transports/base_input.py b/src/pipecat/transports/base_input.py index 771fe39e1..77ff61bba 100644 --- a/src/pipecat/transports/base_input.py +++ b/src/pipecat/transports/base_input.py @@ -48,7 +48,7 @@ from pipecat.metrics.metrics import MetricsData from pipecat.processors.frame_processor import FrameDirection, FrameProcessor from pipecat.transports.base_transport import TransportParams -AUDIO_INPUT_TIMEOUT_SECS = 1.0 +AUDIO_INPUT_TIMEOUT_SECS = 0.5 class BaseInputTransport(FrameProcessor): @@ -449,8 +449,6 @@ class BaseInputTransport(FrameProcessor): if not audio_received: continue - logger.debug(f"{self}: audio not received for more than {AUDIO_INPUT_TIMEOUT_SECS}") - ################################################################### # DEPRECATED. if self._user_speaking: diff --git a/src/pipecat/turns/user_turn_strategies.py b/src/pipecat/turns/user_turn_strategies.py index fe637e0ed..0435f141c 100644 --- a/src/pipecat/turns/user_turn_strategies.py +++ b/src/pipecat/turns/user_turn_strategies.py @@ -9,6 +9,7 @@ from dataclasses import dataclass from typing import List, Optional +from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3 from pipecat.turns.user_start import ( BaseUserTurnStartStrategy, ExternalUserTurnStartStrategy, @@ -18,7 +19,7 @@ from pipecat.turns.user_start import ( from pipecat.turns.user_stop import ( BaseUserTurnStopStrategy, ExternalUserTurnStopStrategy, - SpeechTimeoutUserTurnStopStrategy, + TurnAnalyzerUserTurnStopStrategy, ) @@ -29,7 +30,7 @@ class UserTurnStrategies: If no strategies are specified, the following defaults are used: start: [VADUserTurnStartStrategy, TranscriptionUserTurnStartStrategy] - stop: [SpeechTimeoutUserTurnStopStrategy] + stop: [TurnAnalyzerUserTurnStopStrategy(LocalSmartTurnAnalyzerV3)] Attributes: start: A list of user turn start strategies used to detect when @@ -46,7 +47,7 @@ class UserTurnStrategies: if not self.start: self.start = [VADUserTurnStartStrategy(), TranscriptionUserTurnStartStrategy()] if not self.stop: - self.stop = [SpeechTimeoutUserTurnStopStrategy()] + self.stop = [TurnAnalyzerUserTurnStopStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3())] @dataclass From ca0d2e68c3216b39e45a445836f4821ac016708c Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Aleix=20Conchillo=20Flaqu=C3=A9?= Date: Mon, 9 Feb 2026 11:30:25 -0800 Subject: [PATCH 0404/1060] Add changelog for #3689 --- changelog/3689.changed.md | 1 + 1 file changed, 1 insertion(+) create mode 100644 changelog/3689.changed.md diff --git a/changelog/3689.changed.md b/changelog/3689.changed.md new file mode 100644 index 000000000..98e7dc2b4 --- /dev/null +++ b/changelog/3689.changed.md @@ -0,0 +1 @@ +- Changed default user turn stop strategy from `TranscriptionUserTurnStopStrategy` to `TurnAnalyzerUserTurnStopStrategy` with `LocalSmartTurnAnalyzerV3`. From 944ac925937a40474ee377f04d98af917fa06322 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Aleix=20Conchillo=20Flaqu=C3=A9?= Date: Mon, 9 Feb 2026 11:57:14 -0800 Subject: [PATCH 0405/1060] Fix test_langchain to use explicit stop strategy The default stop strategy changed to TurnAnalyzerUserTurnStopStrategy, which requires actual audio analysis. Use SpeechTimeoutUserTurnStopStrategy explicitly since this test is not testing turn detection. --- .github/workflows/coverage.yaml | 1 + .github/workflows/tests.yaml | 1 + tests/test_langchain.py | 14 ++++++++++++-- 3 files changed, 14 insertions(+), 2 deletions(-) diff --git a/.github/workflows/coverage.yaml b/.github/workflows/coverage.yaml index ae0cb9c57..852611eba 100644 --- a/.github/workflows/coverage.yaml +++ b/.github/workflows/coverage.yaml @@ -39,6 +39,7 @@ jobs: --extra google \ --extra langchain \ --extra livekit \ + --extra local-smart-turn-v3 \ --extra piper \ --extra websocket diff --git a/.github/workflows/tests.yaml b/.github/workflows/tests.yaml index cb35a169c..54495911b 100644 --- a/.github/workflows/tests.yaml +++ b/.github/workflows/tests.yaml @@ -43,6 +43,7 @@ jobs: --extra google \ --extra langchain \ --extra livekit \ + --extra local-smart-turn-v3 \ --extra piper \ --extra websocket diff --git a/tests/test_langchain.py b/tests/test_langchain.py index 8ec8905b4..cc5c8f030 100644 --- a/tests/test_langchain.py +++ b/tests/test_langchain.py @@ -24,10 +24,15 @@ from pipecat.frames.frames import ( ) from pipecat.pipeline.pipeline import Pipeline from pipecat.processors.aggregators.llm_context import LLMContext -from pipecat.processors.aggregators.llm_response_universal import LLMContextAggregatorPair +from pipecat.processors.aggregators.llm_response_universal import ( + LLMContextAggregatorPair, + LLMUserAggregatorParams, +) from pipecat.processors.frame_processor import FrameProcessor from pipecat.processors.frameworks.langchain import LangchainProcessor from pipecat.tests.utils import SleepFrame, run_test +from pipecat.turns.user_stop import SpeechTimeoutUserTurnStopStrategy +from pipecat.turns.user_turn_strategies import UserTurnStrategies class TestLangchain(unittest.IsolatedAsyncioTestCase): @@ -65,7 +70,12 @@ class TestLangchain(unittest.IsolatedAsyncioTestCase): self.mock_proc = self.MockProcessor("token_collector") context = LLMContext() - context_aggregator = LLMContextAggregatorPair(context) + context_aggregator = LLMContextAggregatorPair( + context, + user_params=LLMUserAggregatorParams( + user_turn_strategies=UserTurnStrategies(stop=[SpeechTimeoutUserTurnStopStrategy()]) + ), + ) pipeline = Pipeline( [context_aggregator.user(), proc, self.mock_proc, context_aggregator.assistant()] From cc797ba3cfa60000fba04e946e8270efb0571494 Mon Sep 17 00:00:00 2001 From: Mark Backman Date: Mon, 9 Feb 2026 15:15:31 -0500 Subject: [PATCH 0406/1060] Add shared Claude Code settings to disable commit attribution --- .claude/settings.json | 5 +++++ 1 file changed, 5 insertions(+) create mode 100644 .claude/settings.json diff --git a/.claude/settings.json b/.claude/settings.json new file mode 100644 index 000000000..ce5d2734a --- /dev/null +++ b/.claude/settings.json @@ -0,0 +1,5 @@ +{ + "attribution": { + "commit": "" + } +} From 6305e0456960194ec52ba5b44074ff0dd75ffaf8 Mon Sep 17 00:00:00 2001 From: Mark Backman Date: Sat, 7 Feb 2026 10:53:43 -0500 Subject: [PATCH 0407/1060] Clean up on Sarvam STT and TTS classes --- changelog/3671.added.2.md | 1 + changelog/3671.added.md | 1 + changelog/3671.fixed.md | 1 + src/pipecat/services/sarvam/stt.py | 41 ++++++++++++++++++------ src/pipecat/services/sarvam/tts.py | 50 ++++++++++-------------------- 5 files changed, 50 insertions(+), 44 deletions(-) create mode 100644 changelog/3671.added.2.md create mode 100644 changelog/3671.added.md create mode 100644 changelog/3671.fixed.md diff --git a/changelog/3671.added.2.md b/changelog/3671.added.2.md new file mode 100644 index 000000000..db4caeba5 --- /dev/null +++ b/changelog/3671.added.2.md @@ -0,0 +1 @@ +- Added `bulbul:v3-beta` TTS model support for Sarvam AI with temperature control and 25 new speaker voices. diff --git a/changelog/3671.added.md b/changelog/3671.added.md new file mode 100644 index 000000000..625d443b7 --- /dev/null +++ b/changelog/3671.added.md @@ -0,0 +1 @@ +- Added `saaras:v3` STT model support for Sarvam AI with new `mode` parameter (transcribe, translate, verbatim, translit, codemix) and prompt support. diff --git a/changelog/3671.fixed.md b/changelog/3671.fixed.md new file mode 100644 index 000000000..6e53ea864 --- /dev/null +++ b/changelog/3671.fixed.md @@ -0,0 +1 @@ +- Fixed issues in Sarvam STT and TTS services: missing event handler registration for VAD signals, `Optional[bool]` type annotations, WebSocket state cleanup on API errors, and TTS disconnect/reconnection state management. diff --git a/src/pipecat/services/sarvam/stt.py b/src/pipecat/services/sarvam/stt.py index e0da8520d..998597956 100644 --- a/src/pipecat/services/sarvam/stt.py +++ b/src/pipecat/services/sarvam/stt.py @@ -1,3 +1,9 @@ +# +# Copyright (c) 2024–2026, Daily +# +# SPDX-License-Identifier: BSD 2-Clause License +# + """Sarvam AI Speech-to-Text service implementation. This module provides a streaming Speech-to-Text service using Sarvam AI's WebSocket-based @@ -7,7 +13,7 @@ can handle multiple audio formats for Indian language speech recognition. import base64 from dataclasses import dataclass -from typing import Dict, Literal, Optional +from typing import AsyncGenerator, Dict, Literal, Optional from loguru import logger from pydantic import BaseModel @@ -149,8 +155,8 @@ class SarvamSTTService(STTService): language: Optional[Language] = None prompt: Optional[str] = None mode: Optional[Literal["transcribe", "translate", "verbatim", "translit", "codemix"]] = None - vad_signals: bool = None - high_vad_sensitivity: bool = None + vad_signals: Optional[bool] = None + high_vad_sensitivity: Optional[bool] = None def __init__( self, @@ -233,6 +239,12 @@ class SarvamSTTService(STTService): self._websocket_context = None self._socket_client = None self._receive_task = None + + if self._vad_signals: + self._register_event_handler("on_speech_started") + self._register_event_handler("on_speech_stopped") + self._register_event_handler("on_utterance_end") + logger.info(f"Sarvam STT initialized with SDK headers: {self._sdk_headers}") def language_to_service_language(self, language: Language) -> str: @@ -337,7 +349,7 @@ class SarvamSTTService(STTService): await super().cancel(frame) await self._disconnect() - async def run_stt(self, audio: bytes): + async def run_stt(self, audio: bytes) -> AsyncGenerator[Frame, None]: """Send audio data to Sarvam for transcription. Args: @@ -385,18 +397,25 @@ class SarvamSTTService(STTService): logger.debug("Connecting to Sarvam") try: - # Convert boolean parameters to string for SDK - vad_signals_str = "true" if self._vad_signals else "false" - high_vad_sensitivity_str = "true" if self._high_vad_sensitivity else "false" - # Build common connection parameters connect_kwargs = { "model": self.model_name, - "vad_signals": vad_signals_str, - "high_vad_sensitivity": high_vad_sensitivity_str, "sample_rate": str(self.sample_rate), } + # Enable flush signal when using Pipecat's VAD (not Sarvam's) so that + # the flush() call on user-stopped-speaking is honored by the server. + if not self._vad_signals: + connect_kwargs["flush_signal"] = "true" + + # Only send vad parameters when explicitly set (avoid overriding server defaults) + if self._vad_signals is not None: + connect_kwargs["vad_signals"] = "true" if self._vad_signals else "false" + if self._high_vad_sensitivity is not None: + connect_kwargs["high_vad_sensitivity"] = ( + "true" if self._high_vad_sensitivity else "false" + ) + # Add language_code for models that support it if self._language_string is not None: connect_kwargs["language_code"] = self._language_string @@ -447,6 +466,8 @@ class SarvamSTTService(STTService): logger.info("Connected to Sarvam successfully") except ApiError as e: + self._socket_client = None + self._websocket_context = None await self.push_error(error_msg=f"Sarvam API error: {e}", exception=e) except Exception as e: self._socket_client = None diff --git a/src/pipecat/services/sarvam/tts.py b/src/pipecat/services/sarvam/tts.py index 2e767eb6a..778a29005 100644 --- a/src/pipecat/services/sarvam/tts.py +++ b/src/pipecat/services/sarvam/tts.py @@ -525,7 +525,7 @@ class SarvamHttpTTSService(TTSService): audio_data = base64.b64decode(base64_audio) # Strip WAV header (first 44 bytes) if present - if audio_data.startswith(b"RIFF"): + if len(audio_data) > 44 and audio_data.startswith(b"RIFF"): logger.debug("Stripping WAV header from Sarvam audio data") audio_data = audio_data[44:] @@ -792,7 +792,6 @@ class SarvamTTSService(InterruptibleTTSService): self._started = False self._receive_task = None self._keepalive_task = None - self._disconnecting = False def can_generate_metrics(self) -> bool: """Check if this service can generate processing metrics. @@ -844,10 +843,13 @@ class SarvamTTSService(InterruptibleTTSService): await self._disconnect() async def flush_audio(self): - """Flush any pending audio synthesis by sending stop command.""" - if self._websocket: - msg = {"type": "flush"} - await self._websocket.send(json.dumps(msg)) + """Flush any pending audio synthesis by sending flush command.""" + try: + if self._websocket: + msg = {"type": "flush"} + await self._websocket.send(json.dumps(msg)) + except Exception as e: + await self.push_error(error_msg=f"Error sending flush to Sarvam: {e}", exception=e) async def push_frame(self, frame: Frame, direction: FrameDirection = FrameDirection.DOWNSTREAM): """Push a frame downstream with special handling for stop conditions. @@ -894,29 +896,15 @@ class SarvamTTSService(InterruptibleTTSService): """Disconnect from Sarvam WebSocket and clean up tasks.""" await super()._disconnect() - try: - # First, set a flag to prevent new operations - self._disconnecting = True + if self._receive_task: + await self.cancel_task(self._receive_task) + self._receive_task = None - # Cancel background tasks BEFORE closing websocket - if self._receive_task: - await self.cancel_task(self._receive_task, timeout=2.0) - self._receive_task = None + if self._keepalive_task: + await self.cancel_task(self._keepalive_task) + self._keepalive_task = None - if self._keepalive_task: - await self.cancel_task(self._keepalive_task, timeout=2.0) - self._keepalive_task = None - - # Now close the websocket - await self._disconnect_websocket() - - except Exception as e: - await self.push_error(error_msg=f"Unknown error occurred: {e}", exception=e) - finally: - # Reset state only after everything is cleaned up - self._started = False - self._websocket = None - self._disconnecting = False + await self._disconnect_websocket() async def _connect_websocket(self): """Establish WebSocket connection to Sarvam API.""" @@ -996,6 +984,7 @@ class SarvamTTSService(InterruptibleTTSService): if "too long" in error_msg.lower() or "timeout" in error_msg.lower(): logger.warning("Connection timeout detected, service may need restart") + self._started = False await self.push_frame(ErrorFrame(error=f"TTS Error: {error_msg}")) async def _keepalive_task_handler(self): @@ -1007,19 +996,12 @@ class SarvamTTSService(InterruptibleTTSService): async def _send_keepalive(self): """Send keepalive message to maintain connection.""" - if self._disconnecting: - return - if self._websocket and self._websocket.state == State.OPEN: msg = {"type": "ping"} await self._websocket.send(json.dumps(msg)) async def _send_text(self, text: str): """Send text to Sarvam WebSocket for synthesis.""" - if self._disconnecting: - logger.warning("Service is disconnecting, ignoring text send") - return - if self._websocket and self._websocket.state == State.OPEN: msg = {"type": "text", "data": {"text": text}} await self._websocket.send(json.dumps(msg)) From 981253c70386f43faf09dfb59eeb3c710b009758 Mon Sep 17 00:00:00 2001 From: Mark Backman Date: Mon, 9 Feb 2026 16:44:22 -0500 Subject: [PATCH 0408/1060] Rename RequestMetadataFrame to ServiceSwitcherRequestMetadataFrame with service targeting Add a `service` field so the frame targets a specific service, allowing ServiceSwitcher.push_frame to consume it only when the targeted service matches the active service. STTService and test mocks now push the frame downstream after handling instead of silently consuming it. --- changelog/3692.changed.md | 1 + src/pipecat/frames/frames.py | 9 ++++++--- src/pipecat/pipeline/service_switcher.py | 23 +++++++++++++---------- src/pipecat/services/stt_service.py | 6 +++--- tests/test_service_switcher.py | 14 ++++++++------ 5 files changed, 31 insertions(+), 22 deletions(-) create mode 100644 changelog/3692.changed.md diff --git a/changelog/3692.changed.md b/changelog/3692.changed.md new file mode 100644 index 000000000..adb9e1d62 --- /dev/null +++ b/changelog/3692.changed.md @@ -0,0 +1 @@ +- Renamed `RequestMetadataFrame` to `ServiceSwitcherRequestMetadataFrame` and added a `service` field to target a specific service. The frame is now pushed downstream by services after handling instead of being silently consumed. diff --git a/src/pipecat/frames/frames.py b/src/pipecat/frames/frames.py index c88180b46..de33c6187 100644 --- a/src/pipecat/frames/frames.py +++ b/src/pipecat/frames/frames.py @@ -1721,16 +1721,19 @@ class STTMetadataFrame(ServiceMetadataFrame): @dataclass -class RequestMetadataFrame(ControlFrame): - """Request services to re-emit their metadata frames. +class ServiceSwitcherRequestMetadataFrame(ControlFrame): + """Request a service to re-emit its metadata frames. Used by ServiceSwitcher when switching active services to ensure downstream processors receive updated metadata from the newly active service. Services that receive this frame should re-push their metadata frame (e.g., STTMetadataFrame for STT services). + + Parameters: + service: The target service that should re-emit its metadata. """ - pass + service: "FrameProcessor" # diff --git a/src/pipecat/pipeline/service_switcher.py b/src/pipecat/pipeline/service_switcher.py index 2c4d54085..d18f00e7c 100644 --- a/src/pipecat/pipeline/service_switcher.py +++ b/src/pipecat/pipeline/service_switcher.py @@ -12,9 +12,9 @@ from typing import Any, Generic, List, Optional, Type, TypeVar from pipecat.frames.frames import ( Frame, ManuallySwitchServiceFrame, - RequestMetadataFrame, ServiceMetadataFrame, ServiceSwitcherFrame, + ServiceSwitcherRequestMetadataFrame, ) from pipecat.pipeline.parallel_pipeline import ParallelPipeline from pipecat.processors.filters.function_filter import FunctionFilter @@ -220,16 +220,19 @@ class ServiceSwitcher(ParallelPipeline, Generic[StrategyType]): async def push_frame(self, frame: Frame, direction: FrameDirection = FrameDirection.DOWNSTREAM): """Push a frame out of the service switcher. - Suppresses `RequestMetadataFrame` (internal to the switcher) and - `ServiceMetadataFrame` from inactive services so only the active - service's metadata reaches downstream processors. One case this happens - is with `StartFrame` since all the filters let it pass, and `StartFrame` - causes the service to generate `ServiceMetadataFrame`. + Suppresses `ServiceSwitcherRequestMetadataFrame` targeting the active + service (since it has already been handled) and `ServiceMetadataFrame` + from inactive services so only the active service's metadata reaches + downstream processors. One case this happens is with `StartFrame` since + all the filters let it pass, and `StartFrame` causes the service to + generate `ServiceMetadataFrame`. """ - # Don't let RequestMetadataFrame out. - if isinstance(frame, RequestMetadataFrame): - return + # Consume ServiceSwitcherRequestMetadataFrame once the targeted service + # has handled it (i.e. the active service). + if isinstance(frame, ServiceSwitcherRequestMetadataFrame): + if frame.service == self.strategy.active_service: + return # Only let metadata from the active service escape. if isinstance(frame, ServiceMetadataFrame): @@ -255,6 +258,6 @@ class ServiceSwitcher(ParallelPipeline, Generic[StrategyType]): # If we switched to a new service, request its metadata. if service: - await service.queue_frame(RequestMetadataFrame()) + await service.queue_frame(ServiceSwitcherRequestMetadataFrame(service=service)) else: await super().process_frame(frame, direction) diff --git a/src/pipecat/services/stt_service.py b/src/pipecat/services/stt_service.py index 53840221c..7e9ed4c9f 100644 --- a/src/pipecat/services/stt_service.py +++ b/src/pipecat/services/stt_service.py @@ -21,7 +21,7 @@ from pipecat.frames.frames import ( Frame, InterruptionFrame, MetricsFrame, - RequestMetadataFrame, + ServiceSwitcherRequestMetadataFrame, StartFrame, STTMetadataFrame, STTMuteFrame, @@ -264,9 +264,9 @@ class STTService(AIService): # Push StartFrame first, then metadata so downstream receives them in order await self.push_frame(frame, direction) await self._push_stt_metadata() - elif isinstance(frame, RequestMetadataFrame): - # Don't push the RequestMetadataFrame, just push the metadata + elif isinstance(frame, ServiceSwitcherRequestMetadataFrame): await self._push_stt_metadata() + await self.push_frame(frame, direction) elif isinstance(frame, AudioRawFrame): # In this service we accumulate audio internally and at the end we # push a TextFrame. We also push audio downstream in case someone diff --git a/tests/test_service_switcher.py b/tests/test_service_switcher.py index 3f1f586fe..4df6696af 100644 --- a/tests/test_service_switcher.py +++ b/tests/test_service_switcher.py @@ -13,8 +13,8 @@ from dataclasses import dataclass from pipecat.frames.frames import ( Frame, ManuallySwitchServiceFrame, - RequestMetadataFrame, ServiceMetadataFrame, + ServiceSwitcherRequestMetadataFrame, StartFrame, SystemFrame, TextFrame, @@ -68,7 +68,7 @@ class MockMetadataFrame(ServiceMetadataFrame): class MockMetadataService(FrameProcessor): """A mock service that emits ServiceMetadataFrame like STT services. - Pushes MockMetadataFrame on StartFrame and RequestMetadataFrame. + Pushes MockMetadataFrame on StartFrame and ServiceSwitcherRequestMetadataFrame. """ def __init__(self, test_name: str, **kwargs): @@ -84,9 +84,9 @@ class MockMetadataService(FrameProcessor): if isinstance(frame, StartFrame): await self.push_frame(frame, direction) await self._push_metadata() - elif isinstance(frame, RequestMetadataFrame): - # Don't push RequestMetadataFrame downstream (it's internal) + elif isinstance(frame, ServiceSwitcherRequestMetadataFrame): await self._push_metadata() + await self.push_frame(frame, direction) else: await self.push_frame(frame, direction) @@ -472,9 +472,11 @@ class TestServiceSwitcherMetadata(unittest.IsolatedAsyncioTestCase): expected_up_frames=[], ) - # service2 should have received RequestMetadataFrame after becoming active + # service2 should have received ServiceSwitcherRequestMetadataFrame after becoming active request_frames = [ - f for f in self.service2.processed_frames if isinstance(f, RequestMetadataFrame) + f + for f in self.service2.processed_frames + if isinstance(f, ServiceSwitcherRequestMetadataFrame) ] self.assertEqual(len(request_frames), 1) From f2688deb0df98223e202a7107dedeb15b709fd0b Mon Sep 17 00:00:00 2001 From: mattie ruth backman Date: Mon, 9 Feb 2026 16:27:15 -0500 Subject: [PATCH 0409/1060] Update args field in RTVILLMFunctionCallInProgressMessageData to match API of existing RTVILLMFunctionCallResultData. --- src/pipecat/processors/frameworks/rtvi.py | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/src/pipecat/processors/frameworks/rtvi.py b/src/pipecat/processors/frameworks/rtvi.py index a803c18f8..d85cae11f 100644 --- a/src/pipecat/processors/frameworks/rtvi.py +++ b/src/pipecat/processors/frameworks/rtvi.py @@ -691,7 +691,7 @@ class RTVILLMFunctionCallInProgressMessageData(BaseModel): tool_call_id: str function_name: Optional[str] = None - args: Optional[Mapping[str, Any]] = None + arguments: Optional[Mapping[str, Any]] = None class RTVILLMFunctionCallInProgressMessage(BaseModel): @@ -1299,7 +1299,7 @@ class RTVIObserver(BaseObserver): ): data.function_name = frame.function_name if report_level == RTVIFunctionCallReportLevel.FULL: - data.args = frame.arguments + data.arguments = frame.arguments message = RTVILLMFunctionCallInProgressMessage(data=data) await self.send_rtvi_message(message) elif isinstance(frame, FunctionCallCancelFrame): From 83a837940184a43038dcc2307264cd75cd95df52 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Aleix=20Conchillo=20Flaqu=C3=A9?= Date: Mon, 9 Feb 2026 14:32:32 -0800 Subject: [PATCH 0410/1060] examples: remove the now default turn analyzer user turn stop strategy --- examples/foundational/04-transports-small-webrtc.py | 10 +--------- examples/foundational/04a-transports-daily.py | 12 +----------- examples/foundational/04b-transports-livekit.py | 10 +--------- examples/foundational/06-listen-and-respond.py | 10 +--------- examples/foundational/06a-image-sync.py | 10 +--------- .../foundational/07-interruptible-cartesia-http.py | 10 +--------- examples/foundational/07-interruptible.py | 10 +--------- .../foundational/07a-interruptible-speechmatics.py | 12 +----------- examples/foundational/07b-interruptible-langchain.py | 10 +--------- .../foundational/07c-interruptible-deepgram-http.py | 12 +----------- .../07c-interruptible-deepgram-sagemaker.py | 10 +--------- examples/foundational/07c-interruptible-deepgram.py | 10 +--------- .../07d-interruptible-elevenlabs-http.py | 12 +----------- .../foundational/07d-interruptible-elevenlabs.py | 10 +--------- .../foundational/07e-interruptible-playht-http.py | 10 +--------- examples/foundational/07e-interruptible-playht.py | 10 +--------- .../foundational/07f-interruptible-azure-http.py | 10 +--------- examples/foundational/07f-interruptible-azure.py | 10 +--------- .../foundational/07g-interruptible-openai-http.py | 10 +--------- examples/foundational/07g-interruptible-openai.py | 10 +--------- examples/foundational/07h-interruptible-openpipe.py | 10 +--------- examples/foundational/07i-interruptible-xtts.py | 12 +----------- examples/foundational/07j-interruptible-gladia.py | 10 +--------- examples/foundational/07k-interruptible-lmnt.py | 10 +--------- examples/foundational/07l-interruptible-groq.py | 10 +--------- .../foundational/07m-interruptible-aws-strands.py | 10 +--------- examples/foundational/07m-interruptible-aws.py | 10 +--------- .../foundational/07n-interruptible-gemini-image.py | 10 +--------- examples/foundational/07n-interruptible-gemini.py | 10 +--------- .../foundational/07n-interruptible-google-http.py | 10 +--------- examples/foundational/07n-interruptible-google.py | 10 +--------- .../foundational/07o-interruptible-assemblyai.py | 10 +--------- .../foundational/07p-interruptible-krisp-viva.py | 2 -- examples/foundational/07p-interruptible-krisp.py | 10 +--------- examples/foundational/07q-interruptible-rime-http.py | 12 +----------- examples/foundational/07q-interruptible-rime.py | 10 +--------- examples/foundational/07r-interruptible-nvidia.py | 10 +--------- .../07s-interruptible-google-audio-in.py | 10 +--------- examples/foundational/07t-interruptible-fish.py | 10 +--------- .../foundational/07v-interruptible-neuphonic-http.py | 12 +----------- examples/foundational/07v-interruptible-neuphonic.py | 10 +--------- examples/foundational/07w-interruptible-fal.py | 10 +--------- examples/foundational/07x-interruptible-local.py | 10 +--------- examples/foundational/07y-interruptible-minimax.py | 12 +----------- .../foundational/07z-interruptible-sarvam-http.py | 12 +----------- examples/foundational/07z-interruptible-sarvam.py | 10 +--------- examples/foundational/07za-interruptible-soniox.py | 10 +--------- .../foundational/07zb-interruptible-inworld-http.py | 12 +----------- examples/foundational/07zb-interruptible-inworld.py | 10 +--------- .../foundational/07zc-interruptible-asyncai-http.py | 12 +----------- examples/foundational/07zc-interruptible-asyncai.py | 10 +--------- .../foundational/07zd-interruptible-aicoustics.py | 10 +--------- examples/foundational/07ze-interruptible-hume.py | 10 +--------- examples/foundational/07zf-interruptible-gradium.py | 10 +--------- examples/foundational/07zg-interruptible-camb.py | 10 +--------- examples/foundational/07zh-interruptible-hathora.py | 12 ++---------- examples/foundational/07zi-interruptible-piper.py | 10 +--------- examples/foundational/07zj-interruptible-kokoro.py | 10 +--------- examples/foundational/07zk-interruptible-resemble.py | 9 +-------- examples/foundational/08-custom-frame-processor.py | 10 +--------- examples/foundational/10-wake-phrase.py | 10 +--------- examples/foundational/11-sound-effects.py | 10 +--------- examples/foundational/12-describe-image-openai.py | 10 +--------- .../foundational/12a-describe-image-anthropic.py | 10 +--------- examples/foundational/12b-describe-image-aws.py | 10 +--------- .../foundational/12c-describe-image-gemini-flash.py | 10 +--------- examples/foundational/14-function-calling.py | 10 +--------- .../foundational/14a-function-calling-anthropic.py | 10 +--------- .../foundational/14c-function-calling-together.py | 10 +--------- .../14d-function-calling-anthropic-video.py | 10 +--------- .../foundational/14d-function-calling-aws-video.py | 10 +--------- .../14d-function-calling-gemini-flash-video.py | 10 +--------- .../14d-function-calling-moondream-video.py | 10 +--------- .../14d-function-calling-openai-video.py | 10 +--------- examples/foundational/14e-function-calling-google.py | 10 +--------- examples/foundational/14f-function-calling-groq.py | 10 +--------- examples/foundational/14g-function-calling-grok.py | 10 +--------- examples/foundational/14h-function-calling-azure.py | 10 +--------- .../foundational/14i-function-calling-fireworks.py | 10 +--------- examples/foundational/14j-function-calling-nvidia.py | 10 +--------- .../foundational/14k-function-calling-cerebras.py | 10 +--------- .../foundational/14l-function-calling-deepseek.py | 12 ++---------- .../foundational/14m-function-calling-openrouter.py | 10 +--------- .../foundational/14n-function-calling-perplexity.py | 10 +--------- .../14p-function-calling-gemini-vertex-ai.py | 10 +--------- examples/foundational/14q-function-calling-qwen.py | 10 +--------- examples/foundational/14r-function-calling-aws.py | 10 +--------- .../foundational/14s-function-calling-sambanova.py | 10 +--------- examples/foundational/14t-function-calling-direct.py | 12 ++---------- examples/foundational/14u-function-calling-ollama.py | 10 +--------- examples/foundational/14v-function-calling-openai.py | 10 +--------- .../foundational/14w-function-calling-mistral.py | 10 +--------- .../foundational/14x-function-calling-openpipe.py | 10 +--------- examples/foundational/15-switch-voices.py | 10 +--------- examples/foundational/15a-switch-languages.py | 10 +--------- examples/foundational/16-gpu-container-local-bot.py | 10 +--------- examples/foundational/17-detect-user-idle.py | 6 ------ .../foundational/20a-persistent-context-openai.py | 10 +--------- .../foundational/20c-persistent-context-anthropic.py | 10 +--------- .../foundational/20d-persistent-context-gemini.py | 10 +--------- examples/foundational/21-tavus-transport.py | 12 +----------- examples/foundational/21a-tavus-video-service.py | 12 +----------- examples/foundational/22-filter-incomplete-turns.py | 6 ------ examples/foundational/23-bot-background-sound.py | 12 +----------- examples/foundational/24-user-mute-strategy.py | 6 ------ examples/foundational/27-simli-layer.py | 10 +--------- examples/foundational/28-user-assistant-turns.py | 10 +--------- examples/foundational/29-turn-tracking-observer.py | 10 +--------- examples/foundational/30-observer.py | 10 +--------- .../foundational/32-gemini-grounding-metadata.py | 10 +--------- examples/foundational/33-gemini-rag.py | 10 +--------- examples/foundational/34-audio-recording.py | 10 +--------- .../foundational/35-pattern-pair-voice-switching.py | 10 +--------- examples/foundational/36-user-email-gathering.py | 10 +--------- examples/foundational/37-mem0.py | 10 +--------- examples/foundational/38b-smart-turn-local.py | 10 +--------- examples/foundational/39-mcp-stdio.py | 12 +----------- examples/foundational/39a-mcp-streamable-http.py | 10 +--------- .../39b-mcp-streamable-http-gemini-live.py | 10 +--------- examples/foundational/39c-multiple-mcp.py | 12 +----------- examples/foundational/42-interruption-config.py | 3 --- examples/foundational/43-heygen-transport.py | 12 +----------- examples/foundational/43a-heygen-video-service.py | 12 +----------- examples/foundational/44-voicemail-detection.py | 10 +--------- examples/foundational/45-before-and-after-events.py | 10 +--------- examples/foundational/46-video-processing.py | 10 +--------- examples/foundational/47-sentry-metrics.py | 10 +--------- examples/foundational/48-service-switcher.py | 10 +--------- examples/foundational/49a-thinking-anthropic.py | 10 +--------- examples/foundational/49b-thinking-google.py | 10 +--------- .../foundational/49c-thinking-functions-anthropic.py | 10 +--------- .../foundational/49d-thinking-functions-google.py | 10 +--------- examples/foundational/52-live-translation.py | 3 --- .../foundational/53-concurrent-llm-evaluation.py | 10 ++-------- 134 files changed, 132 insertions(+), 1215 deletions(-) diff --git a/examples/foundational/04-transports-small-webrtc.py b/examples/foundational/04-transports-small-webrtc.py index 83fa1861f..7196dbb05 100644 --- a/examples/foundational/04-transports-small-webrtc.py +++ b/examples/foundational/04-transports-small-webrtc.py @@ -17,7 +17,6 @@ from fastapi.responses import RedirectResponse from loguru import logger from pipecat_ai_small_webrtc_prebuilt.frontend import SmallWebRTCPrebuiltUI -from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3 from pipecat.audio.vad.silero import SileroVADAnalyzer from pipecat.frames.frames import LLMRunFrame from pipecat.pipeline.pipeline import Pipeline @@ -34,8 +33,6 @@ from pipecat.services.openai.llm import OpenAILLMService from pipecat.transports.base_transport import TransportParams from pipecat.transports.smallwebrtc.connection import IceServer, SmallWebRTCConnection from pipecat.transports.smallwebrtc.transport import SmallWebRTCTransport -from pipecat.turns.user_stop import TurnAnalyzerUserTurnStopStrategy -from pipecat.turns.user_turn_strategies import UserTurnStrategies load_dotenv(override=True) @@ -85,12 +82,7 @@ async def run_example(webrtc_connection: SmallWebRTCConnection): context = LLMContext(messages) user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, - user_params=LLMUserAggregatorParams( - user_turn_strategies=UserTurnStrategies( - stop=[TurnAnalyzerUserTurnStopStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3())] - ), - vad_analyzer=SileroVADAnalyzer(), - ), + user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()), ) pipeline = Pipeline( diff --git a/examples/foundational/04a-transports-daily.py b/examples/foundational/04a-transports-daily.py index 2608187a6..d1d88dbec 100644 --- a/examples/foundational/04a-transports-daily.py +++ b/examples/foundational/04a-transports-daily.py @@ -12,7 +12,6 @@ import aiohttp from dotenv import load_dotenv from loguru import logger -from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3 from pipecat.audio.vad.silero import SileroVADAnalyzer from pipecat.frames.frames import LLMRunFrame from pipecat.pipeline.pipeline import Pipeline @@ -27,8 +26,6 @@ from pipecat.runner.daily import configure from pipecat.services.cartesia.tts import CartesiaTTSService from pipecat.services.openai.llm import OpenAILLMService from pipecat.transports.daily.transport import DailyParams, DailyTransport -from pipecat.turns.user_stop import TurnAnalyzerUserTurnStopStrategy -from pipecat.turns.user_turn_strategies import UserTurnStrategies load_dotenv(override=True) @@ -68,14 +65,7 @@ async def main(): context = LLMContext(messages) user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, - user_params=LLMUserAggregatorParams( - user_turn_strategies=UserTurnStrategies( - stop=[ - TurnAnalyzerUserTurnStopStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3()) - ] - ), - vad_analyzer=SileroVADAnalyzer(), - ), + user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()), ) pipeline = Pipeline( diff --git a/examples/foundational/04b-transports-livekit.py b/examples/foundational/04b-transports-livekit.py index 05141acde..b577b453e 100644 --- a/examples/foundational/04b-transports-livekit.py +++ b/examples/foundational/04b-transports-livekit.py @@ -12,7 +12,6 @@ import sys from dotenv import load_dotenv from loguru import logger -from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3 from pipecat.audio.vad.silero import SileroVADAnalyzer from pipecat.frames.frames import ( InterruptionFrame, @@ -34,8 +33,6 @@ from pipecat.services.cartesia.tts import CartesiaTTSService from pipecat.services.deepgram.stt import DeepgramSTTService from pipecat.services.openai.llm import OpenAILLMService from pipecat.transports.livekit.transport import LiveKitParams, LiveKitTransport -from pipecat.turns.user_stop import TurnAnalyzerUserTurnStopStrategy -from pipecat.turns.user_turn_strategies import UserTurnStrategies load_dotenv(override=True) @@ -78,12 +75,7 @@ async def main(): context = LLMContext(messages) user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, - user_params=LLMUserAggregatorParams( - user_turn_strategies=UserTurnStrategies( - stop=[TurnAnalyzerUserTurnStopStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3())] - ), - vad_analyzer=SileroVADAnalyzer(), - ), + user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()), ) pipeline = Pipeline( diff --git a/examples/foundational/06-listen-and-respond.py b/examples/foundational/06-listen-and-respond.py index 4fe7045c6..14dee63ad 100644 --- a/examples/foundational/06-listen-and-respond.py +++ b/examples/foundational/06-listen-and-respond.py @@ -9,7 +9,6 @@ import os from dotenv import load_dotenv from loguru import logger -from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3 from pipecat.audio.vad.silero import SileroVADAnalyzer from pipecat.frames.frames import Frame, LLMRunFrame, MetricsFrame from pipecat.metrics.metrics import ( @@ -35,8 +34,6 @@ from pipecat.services.openai.llm import OpenAILLMService from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams -from pipecat.turns.user_stop import TurnAnalyzerUserTurnStopStrategy -from pipecat.turns.user_turn_strategies import UserTurnStrategies load_dotenv(override=True) @@ -103,12 +100,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): context = LLMContext(messages) user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, - user_params=LLMUserAggregatorParams( - user_turn_strategies=UserTurnStrategies( - stop=[TurnAnalyzerUserTurnStopStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3())] - ), - vad_analyzer=SileroVADAnalyzer(), - ), + user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()), ) pipeline = Pipeline( diff --git a/examples/foundational/06a-image-sync.py b/examples/foundational/06a-image-sync.py index a2f0ff4a5..be0e4fe78 100644 --- a/examples/foundational/06a-image-sync.py +++ b/examples/foundational/06a-image-sync.py @@ -10,7 +10,6 @@ from dotenv import load_dotenv from loguru import logger from PIL import Image -from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3 from pipecat.audio.vad.silero import SileroVADAnalyzer from pipecat.frames.frames import ( BotStartedSpeakingFrame, @@ -35,8 +34,6 @@ from pipecat.services.deepgram.stt import DeepgramSTTService from pipecat.services.openai.llm import OpenAILLMService from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams -from pipecat.turns.user_stop import TurnAnalyzerUserTurnStopStrategy -from pipecat.turns.user_turn_strategies import UserTurnStrategies load_dotenv(override=True) @@ -118,12 +115,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): context = LLMContext(messages) user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, - user_params=LLMUserAggregatorParams( - user_turn_strategies=UserTurnStrategies( - stop=[TurnAnalyzerUserTurnStopStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3())] - ), - vad_analyzer=SileroVADAnalyzer(), - ), + user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()), ) image_sync_aggregator = ImageSyncAggregator( diff --git a/examples/foundational/07-interruptible-cartesia-http.py b/examples/foundational/07-interruptible-cartesia-http.py index 6cf9f3deb..e65fb3750 100644 --- a/examples/foundational/07-interruptible-cartesia-http.py +++ b/examples/foundational/07-interruptible-cartesia-http.py @@ -9,7 +9,6 @@ import os from dotenv import load_dotenv from loguru import logger -from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3 from pipecat.audio.vad.silero import SileroVADAnalyzer from pipecat.frames.frames import LLMRunFrame from pipecat.pipeline.pipeline import Pipeline @@ -28,8 +27,6 @@ from pipecat.services.openai.llm import OpenAILLMService from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams -from pipecat.turns.user_stop import TurnAnalyzerUserTurnStopStrategy -from pipecat.turns.user_turn_strategies import UserTurnStrategies load_dotenv(override=True) @@ -74,12 +71,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): context = LLMContext(messages) user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, - user_params=LLMUserAggregatorParams( - user_turn_strategies=UserTurnStrategies( - stop=[TurnAnalyzerUserTurnStopStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3())] - ), - vad_analyzer=SileroVADAnalyzer(), - ), + user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()), ) pipeline = Pipeline( diff --git a/examples/foundational/07-interruptible.py b/examples/foundational/07-interruptible.py index 57588c567..c5964506a 100644 --- a/examples/foundational/07-interruptible.py +++ b/examples/foundational/07-interruptible.py @@ -9,7 +9,6 @@ import os from dotenv import load_dotenv from loguru import logger -from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3 from pipecat.audio.vad.silero import SileroVADAnalyzer from pipecat.frames.frames import LLMRunFrame from pipecat.pipeline.pipeline import Pipeline @@ -28,8 +27,6 @@ from pipecat.services.openai.llm import OpenAILLMService from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams -from pipecat.turns.user_stop import TurnAnalyzerUserTurnStopStrategy -from pipecat.turns.user_turn_strategies import UserTurnStrategies load_dotenv(override=True) @@ -73,12 +70,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): context = LLMContext(messages) user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, - user_params=LLMUserAggregatorParams( - user_turn_strategies=UserTurnStrategies( - stop=[TurnAnalyzerUserTurnStopStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3())] - ), - vad_analyzer=SileroVADAnalyzer(), - ), + user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()), ) pipeline = Pipeline( diff --git a/examples/foundational/07a-interruptible-speechmatics.py b/examples/foundational/07a-interruptible-speechmatics.py index 2df8dd39b..f8b4cdf19 100644 --- a/examples/foundational/07a-interruptible-speechmatics.py +++ b/examples/foundational/07a-interruptible-speechmatics.py @@ -10,7 +10,6 @@ import aiohttp from dotenv import load_dotenv from loguru import logger -from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3 from pipecat.audio.vad.silero import SileroVADAnalyzer from pipecat.frames.frames import LLMRunFrame from pipecat.pipeline.pipeline import Pipeline @@ -31,8 +30,6 @@ from pipecat.transcriptions.language import Language from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams -from pipecat.turns.user_stop import TurnAnalyzerUserTurnStopStrategy -from pipecat.turns.user_turn_strategies import UserTurnStrategies load_dotenv(override=True) @@ -114,14 +111,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): context = LLMContext(messages) user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, - user_params=LLMUserAggregatorParams( - user_turn_strategies=UserTurnStrategies( - stop=[ - TurnAnalyzerUserTurnStopStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3()) - ] - ), - vad_analyzer=SileroVADAnalyzer(), - ), + user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()), ) pipeline = Pipeline( diff --git a/examples/foundational/07b-interruptible-langchain.py b/examples/foundational/07b-interruptible-langchain.py index 911193276..21290b576 100644 --- a/examples/foundational/07b-interruptible-langchain.py +++ b/examples/foundational/07b-interruptible-langchain.py @@ -15,7 +15,6 @@ from langchain_core.runnables.history import RunnableWithMessageHistory from langchain_openai import ChatOpenAI from loguru import logger -from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3 from pipecat.audio.vad.silero import SileroVADAnalyzer from pipecat.frames.frames import LLMMessagesUpdateFrame from pipecat.pipeline.pipeline import Pipeline @@ -34,8 +33,6 @@ from pipecat.services.deepgram.stt import DeepgramSTTService from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams -from pipecat.turns.user_stop import TurnAnalyzerUserTurnStopStrategy -from pipecat.turns.user_turn_strategies import UserTurnStrategies load_dotenv(override=True) @@ -100,12 +97,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): context = LLMContext() user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, - user_params=LLMUserAggregatorParams( - user_turn_strategies=UserTurnStrategies( - stop=[TurnAnalyzerUserTurnStopStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3())] - ), - vad_analyzer=SileroVADAnalyzer(), - ), + user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()), ) pipeline = Pipeline( diff --git a/examples/foundational/07c-interruptible-deepgram-http.py b/examples/foundational/07c-interruptible-deepgram-http.py index ffe1f9f60..53fc77722 100644 --- a/examples/foundational/07c-interruptible-deepgram-http.py +++ b/examples/foundational/07c-interruptible-deepgram-http.py @@ -11,7 +11,6 @@ import aiohttp from dotenv import load_dotenv from loguru import logger -from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3 from pipecat.audio.vad.silero import SileroVADAnalyzer from pipecat.frames.frames import LLMRunFrame from pipecat.pipeline.pipeline import Pipeline @@ -30,8 +29,6 @@ from pipecat.services.openai.llm import OpenAILLMService from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams -from pipecat.turns.user_stop import TurnAnalyzerUserTurnStopStrategy -from pipecat.turns.user_turn_strategies import UserTurnStrategies load_dotenv(override=True) @@ -78,14 +75,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): context = LLMContext(messages) user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, - user_params=LLMUserAggregatorParams( - user_turn_strategies=UserTurnStrategies( - stop=[ - TurnAnalyzerUserTurnStopStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3()) - ] - ), - vad_analyzer=SileroVADAnalyzer(), - ), + user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()), ) pipeline = Pipeline( diff --git a/examples/foundational/07c-interruptible-deepgram-sagemaker.py b/examples/foundational/07c-interruptible-deepgram-sagemaker.py index 05a822706..51a4b1bcb 100644 --- a/examples/foundational/07c-interruptible-deepgram-sagemaker.py +++ b/examples/foundational/07c-interruptible-deepgram-sagemaker.py @@ -10,7 +10,6 @@ import os from dotenv import load_dotenv from loguru import logger -from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3 from pipecat.audio.vad.silero import SileroVADAnalyzer from pipecat.frames.frames import LLMRunFrame from pipecat.pipeline.pipeline import Pipeline @@ -29,8 +28,6 @@ from pipecat.services.deepgram.tts import DeepgramTTSService from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams -from pipecat.turns.user_stop import TurnAnalyzerUserTurnStopStrategy -from pipecat.turns.user_turn_strategies import UserTurnStrategies load_dotenv(override=True) @@ -83,12 +80,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): context = LLMContext(messages) user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, - user_params=LLMUserAggregatorParams( - user_turn_strategies=UserTurnStrategies( - stop=[TurnAnalyzerUserTurnStopStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3())] - ), - vad_analyzer=SileroVADAnalyzer(), - ), + user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()), ) pipeline = Pipeline( diff --git a/examples/foundational/07c-interruptible-deepgram.py b/examples/foundational/07c-interruptible-deepgram.py index f31166d13..0133ad150 100644 --- a/examples/foundational/07c-interruptible-deepgram.py +++ b/examples/foundational/07c-interruptible-deepgram.py @@ -10,7 +10,6 @@ import os from dotenv import load_dotenv from loguru import logger -from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3 from pipecat.audio.vad.silero import SileroVADAnalyzer from pipecat.frames.frames import LLMRunFrame from pipecat.pipeline.pipeline import Pipeline @@ -29,8 +28,6 @@ from pipecat.services.openai.llm import OpenAILLMService from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams -from pipecat.turns.user_stop import TurnAnalyzerUserTurnStopStrategy -from pipecat.turns.user_turn_strategies import UserTurnStrategies load_dotenv(override=True) @@ -72,12 +69,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): context = LLMContext(messages) user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, - user_params=LLMUserAggregatorParams( - user_turn_strategies=UserTurnStrategies( - stop=[TurnAnalyzerUserTurnStopStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3())] - ), - vad_analyzer=SileroVADAnalyzer(), - ), + user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()), ) pipeline = Pipeline( diff --git a/examples/foundational/07d-interruptible-elevenlabs-http.py b/examples/foundational/07d-interruptible-elevenlabs-http.py index b48a40641..0299c1300 100644 --- a/examples/foundational/07d-interruptible-elevenlabs-http.py +++ b/examples/foundational/07d-interruptible-elevenlabs-http.py @@ -11,7 +11,6 @@ import aiohttp from dotenv import load_dotenv from loguru import logger -from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3 from pipecat.audio.vad.silero import SileroVADAnalyzer from pipecat.frames.frames import LLMRunFrame from pipecat.pipeline.pipeline import Pipeline @@ -30,8 +29,6 @@ from pipecat.services.openai.llm import OpenAILLMService from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams -from pipecat.turns.user_stop import TurnAnalyzerUserTurnStopStrategy -from pipecat.turns.user_turn_strategies import UserTurnStrategies load_dotenv(override=True) @@ -82,14 +79,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): context = LLMContext(messages) user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, - user_params=LLMUserAggregatorParams( - user_turn_strategies=UserTurnStrategies( - stop=[ - TurnAnalyzerUserTurnStopStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3()) - ] - ), - vad_analyzer=SileroVADAnalyzer(), - ), + user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()), ) pipeline = Pipeline( diff --git a/examples/foundational/07d-interruptible-elevenlabs.py b/examples/foundational/07d-interruptible-elevenlabs.py index 0bcb55c48..feaf41255 100644 --- a/examples/foundational/07d-interruptible-elevenlabs.py +++ b/examples/foundational/07d-interruptible-elevenlabs.py @@ -10,7 +10,6 @@ import os from dotenv import load_dotenv from loguru import logger -from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3 from pipecat.audio.vad.silero import SileroVADAnalyzer from pipecat.frames.frames import LLMRunFrame from pipecat.pipeline.pipeline import Pipeline @@ -29,8 +28,6 @@ from pipecat.services.openai.llm import OpenAILLMService from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams -from pipecat.turns.user_stop import TurnAnalyzerUserTurnStopStrategy -from pipecat.turns.user_turn_strategies import UserTurnStrategies load_dotenv(override=True) @@ -75,12 +72,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): context = LLMContext(messages) user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, - user_params=LLMUserAggregatorParams( - user_turn_strategies=UserTurnStrategies( - stop=[TurnAnalyzerUserTurnStopStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3())] - ), - vad_analyzer=SileroVADAnalyzer(), - ), + user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()), ) pipeline = Pipeline( diff --git a/examples/foundational/07e-interruptible-playht-http.py b/examples/foundational/07e-interruptible-playht-http.py index 67c5e2c0c..c56de3b9f 100644 --- a/examples/foundational/07e-interruptible-playht-http.py +++ b/examples/foundational/07e-interruptible-playht-http.py @@ -10,7 +10,6 @@ import os from dotenv import load_dotenv from loguru import logger -from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3 from pipecat.audio.vad.silero import SileroVADAnalyzer from pipecat.frames.frames import LLMRunFrame from pipecat.pipeline.pipeline import Pipeline @@ -29,8 +28,6 @@ from pipecat.services.playht.tts import PlayHTHttpTTSService from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams -from pipecat.turns.user_stop import TurnAnalyzerUserTurnStopStrategy -from pipecat.turns.user_turn_strategies import UserTurnStrategies load_dotenv(override=True) @@ -75,12 +72,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): context = LLMContext(messages) user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, - user_params=LLMUserAggregatorParams( - user_turn_strategies=UserTurnStrategies( - stop=[TurnAnalyzerUserTurnStopStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3())] - ), - vad_analyzer=SileroVADAnalyzer(), - ), + user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()), ) pipeline = Pipeline( diff --git a/examples/foundational/07e-interruptible-playht.py b/examples/foundational/07e-interruptible-playht.py index 4c4f42d79..b42f8f6a2 100644 --- a/examples/foundational/07e-interruptible-playht.py +++ b/examples/foundational/07e-interruptible-playht.py @@ -10,7 +10,6 @@ import os from dotenv import load_dotenv from loguru import logger -from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3 from pipecat.audio.vad.silero import SileroVADAnalyzer from pipecat.frames.frames import LLMRunFrame from pipecat.pipeline.pipeline import Pipeline @@ -30,8 +29,6 @@ from pipecat.transcriptions.language import Language from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams -from pipecat.turns.user_stop import TurnAnalyzerUserTurnStopStrategy -from pipecat.turns.user_turn_strategies import UserTurnStrategies load_dotenv(override=True) @@ -77,12 +74,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): context = LLMContext(messages) user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, - user_params=LLMUserAggregatorParams( - user_turn_strategies=UserTurnStrategies( - stop=[TurnAnalyzerUserTurnStopStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3())] - ), - vad_analyzer=SileroVADAnalyzer(), - ), + user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()), ) pipeline = Pipeline( diff --git a/examples/foundational/07f-interruptible-azure-http.py b/examples/foundational/07f-interruptible-azure-http.py index 81e505f52..3d8bdf073 100644 --- a/examples/foundational/07f-interruptible-azure-http.py +++ b/examples/foundational/07f-interruptible-azure-http.py @@ -10,7 +10,6 @@ import os from dotenv import load_dotenv from loguru import logger -from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3 from pipecat.audio.vad.silero import SileroVADAnalyzer from pipecat.frames.frames import LLMRunFrame from pipecat.pipeline.pipeline import Pipeline @@ -29,8 +28,6 @@ from pipecat.services.azure.tts import AzureHttpTTSService from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams -from pipecat.turns.user_stop import TurnAnalyzerUserTurnStopStrategy -from pipecat.turns.user_turn_strategies import UserTurnStrategies load_dotenv(override=True) @@ -81,12 +78,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): context = LLMContext(messages) user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, - user_params=LLMUserAggregatorParams( - user_turn_strategies=UserTurnStrategies( - stop=[TurnAnalyzerUserTurnStopStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3())] - ), - vad_analyzer=SileroVADAnalyzer(), - ), + user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()), ) pipeline = Pipeline( diff --git a/examples/foundational/07f-interruptible-azure.py b/examples/foundational/07f-interruptible-azure.py index 5a1cdd693..03b399a5a 100644 --- a/examples/foundational/07f-interruptible-azure.py +++ b/examples/foundational/07f-interruptible-azure.py @@ -10,7 +10,6 @@ import os from dotenv import load_dotenv from loguru import logger -from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3 from pipecat.audio.vad.silero import SileroVADAnalyzer from pipecat.frames.frames import LLMRunFrame from pipecat.pipeline.pipeline import Pipeline @@ -29,8 +28,6 @@ from pipecat.services.azure.tts import AzureTTSService from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams -from pipecat.turns.user_stop import TurnAnalyzerUserTurnStopStrategy -from pipecat.turns.user_turn_strategies import UserTurnStrategies load_dotenv(override=True) @@ -81,12 +78,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): context = LLMContext(messages) user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, - user_params=LLMUserAggregatorParams( - user_turn_strategies=UserTurnStrategies( - stop=[TurnAnalyzerUserTurnStopStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3())] - ), - vad_analyzer=SileroVADAnalyzer(), - ), + user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()), ) pipeline = Pipeline( diff --git a/examples/foundational/07g-interruptible-openai-http.py b/examples/foundational/07g-interruptible-openai-http.py index f2b38c8cf..325fd4ae4 100644 --- a/examples/foundational/07g-interruptible-openai-http.py +++ b/examples/foundational/07g-interruptible-openai-http.py @@ -10,7 +10,6 @@ import os from dotenv import load_dotenv from loguru import logger -from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3 from pipecat.audio.vad.silero import SileroVADAnalyzer from pipecat.audio.vad.vad_analyzer import VADParams from pipecat.frames.frames import LLMRunFrame @@ -30,8 +29,6 @@ from pipecat.services.openai.tts import OpenAITTSService from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams -from pipecat.turns.user_stop import TurnAnalyzerUserTurnStopStrategy -from pipecat.turns.user_turn_strategies import UserTurnStrategies load_dotenv(override=True) @@ -76,12 +73,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): context = LLMContext(messages) user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, - user_params=LLMUserAggregatorParams( - user_turn_strategies=UserTurnStrategies( - stop=[TurnAnalyzerUserTurnStopStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3())] - ), - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), - ), + user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()), ) pipeline = Pipeline( diff --git a/examples/foundational/07g-interruptible-openai.py b/examples/foundational/07g-interruptible-openai.py index 28c5608fb..551742a57 100644 --- a/examples/foundational/07g-interruptible-openai.py +++ b/examples/foundational/07g-interruptible-openai.py @@ -10,7 +10,6 @@ import os from dotenv import load_dotenv from loguru import logger -from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3 from pipecat.audio.vad.silero import SileroVADAnalyzer from pipecat.frames.frames import LLMRunFrame from pipecat.pipeline.pipeline import Pipeline @@ -30,8 +29,6 @@ from pipecat.transcriptions.language import Language from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams -from pipecat.turns.user_stop import TurnAnalyzerUserTurnStopStrategy -from pipecat.turns.user_turn_strategies import UserTurnStrategies load_dotenv(override=True) @@ -81,12 +78,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): context = LLMContext(messages) user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, - user_params=LLMUserAggregatorParams( - user_turn_strategies=UserTurnStrategies( - stop=[TurnAnalyzerUserTurnStopStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3())] - ), - vad_analyzer=SileroVADAnalyzer(), - ), + user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()), ) pipeline = Pipeline( diff --git a/examples/foundational/07h-interruptible-openpipe.py b/examples/foundational/07h-interruptible-openpipe.py index 03dcd4e46..052ddfd14 100644 --- a/examples/foundational/07h-interruptible-openpipe.py +++ b/examples/foundational/07h-interruptible-openpipe.py @@ -11,7 +11,6 @@ import time from dotenv import load_dotenv from loguru import logger -from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3 from pipecat.audio.vad.silero import SileroVADAnalyzer from pipecat.frames.frames import LLMRunFrame from pipecat.pipeline.pipeline import Pipeline @@ -30,8 +29,6 @@ from pipecat.services.openpipe.llm import OpenPipeLLMService from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams -from pipecat.turns.user_stop import TurnAnalyzerUserTurnStopStrategy -from pipecat.turns.user_turn_strategies import UserTurnStrategies load_dotenv(override=True) @@ -80,12 +77,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): context = LLMContext(messages) user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, - user_params=LLMUserAggregatorParams( - user_turn_strategies=UserTurnStrategies( - stop=[TurnAnalyzerUserTurnStopStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3())] - ), - vad_analyzer=SileroVADAnalyzer(), - ), + user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()), ) pipeline = Pipeline( diff --git a/examples/foundational/07i-interruptible-xtts.py b/examples/foundational/07i-interruptible-xtts.py index e8ee3a76f..8b2b3d6d5 100644 --- a/examples/foundational/07i-interruptible-xtts.py +++ b/examples/foundational/07i-interruptible-xtts.py @@ -11,7 +11,6 @@ import aiohttp from dotenv import load_dotenv from loguru import logger -from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3 from pipecat.audio.vad.silero import SileroVADAnalyzer from pipecat.frames.frames import LLMRunFrame from pipecat.pipeline.pipeline import Pipeline @@ -30,8 +29,6 @@ from pipecat.services.xtts.tts import XTTSService from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams -from pipecat.turns.user_stop import TurnAnalyzerUserTurnStopStrategy -from pipecat.turns.user_turn_strategies import UserTurnStrategies load_dotenv(override=True) @@ -78,14 +75,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): context = LLMContext(messages) user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, - user_params=LLMUserAggregatorParams( - user_turn_strategies=UserTurnStrategies( - stop=[ - TurnAnalyzerUserTurnStopStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3()) - ] - ), - vad_analyzer=SileroVADAnalyzer(), - ), + user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()), ) pipeline = Pipeline( diff --git a/examples/foundational/07j-interruptible-gladia.py b/examples/foundational/07j-interruptible-gladia.py index 13d07a1a8..4bebffce7 100644 --- a/examples/foundational/07j-interruptible-gladia.py +++ b/examples/foundational/07j-interruptible-gladia.py @@ -10,7 +10,6 @@ import os from dotenv import load_dotenv from loguru import logger -from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3 from pipecat.audio.vad.silero import SileroVADAnalyzer from pipecat.frames.frames import LLMRunFrame from pipecat.pipeline.pipeline import Pipeline @@ -31,8 +30,6 @@ from pipecat.transcriptions.language import Language from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams -from pipecat.turns.user_stop import TurnAnalyzerUserTurnStopStrategy -from pipecat.turns.user_turn_strategies import UserTurnStrategies load_dotenv(override=True) @@ -84,12 +81,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): context = LLMContext(messages) user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, - user_params=LLMUserAggregatorParams( - user_turn_strategies=UserTurnStrategies( - stop=[TurnAnalyzerUserTurnStopStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3())] - ), - vad_analyzer=SileroVADAnalyzer(), - ), + user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()), ) pipeline = Pipeline( diff --git a/examples/foundational/07k-interruptible-lmnt.py b/examples/foundational/07k-interruptible-lmnt.py index 008531972..a6d1c56b4 100644 --- a/examples/foundational/07k-interruptible-lmnt.py +++ b/examples/foundational/07k-interruptible-lmnt.py @@ -10,7 +10,6 @@ import os from dotenv import load_dotenv from loguru import logger -from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3 from pipecat.audio.vad.silero import SileroVADAnalyzer from pipecat.frames.frames import LLMRunFrame from pipecat.pipeline.pipeline import Pipeline @@ -29,8 +28,6 @@ from pipecat.services.openai.llm import OpenAILLMService from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams -from pipecat.turns.user_stop import TurnAnalyzerUserTurnStopStrategy -from pipecat.turns.user_turn_strategies import UserTurnStrategies load_dotenv(override=True) @@ -71,12 +68,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): context = LLMContext(messages) user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, - user_params=LLMUserAggregatorParams( - user_turn_strategies=UserTurnStrategies( - stop=[TurnAnalyzerUserTurnStopStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3())] - ), - vad_analyzer=SileroVADAnalyzer(), - ), + user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()), ) pipeline = Pipeline( diff --git a/examples/foundational/07l-interruptible-groq.py b/examples/foundational/07l-interruptible-groq.py index cbf42f96f..5c92814e3 100644 --- a/examples/foundational/07l-interruptible-groq.py +++ b/examples/foundational/07l-interruptible-groq.py @@ -10,7 +10,6 @@ import os from dotenv import load_dotenv from loguru import logger -from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3 from pipecat.audio.vad.silero import SileroVADAnalyzer from pipecat.frames.frames import LLMRunFrame from pipecat.pipeline.pipeline import Pipeline @@ -29,8 +28,6 @@ from pipecat.services.groq.tts import GroqTTSService from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams -from pipecat.turns.user_stop import TurnAnalyzerUserTurnStopStrategy -from pipecat.turns.user_turn_strategies import UserTurnStrategies load_dotenv(override=True) @@ -73,12 +70,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): context = LLMContext(messages) user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, - user_params=LLMUserAggregatorParams( - user_turn_strategies=UserTurnStrategies( - stop=[TurnAnalyzerUserTurnStopStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3())] - ), - vad_analyzer=SileroVADAnalyzer(), - ), + user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()), ) pipeline = Pipeline( diff --git a/examples/foundational/07m-interruptible-aws-strands.py b/examples/foundational/07m-interruptible-aws-strands.py index 247f48645..2e0fc18d8 100644 --- a/examples/foundational/07m-interruptible-aws-strands.py +++ b/examples/foundational/07m-interruptible-aws-strands.py @@ -8,7 +8,6 @@ from dotenv import load_dotenv from loguru import logger -from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3 from pipecat.audio.vad.silero import SileroVADAnalyzer from pipecat.frames.frames import LLMMessagesAppendFrame from pipecat.pipeline.pipeline import Pipeline @@ -27,8 +26,6 @@ from pipecat.services.aws.tts import AWSPollyTTSService from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams -from pipecat.turns.user_stop import TurnAnalyzerUserTurnStopStrategy -from pipecat.turns.user_turn_strategies import UserTurnStrategies # Strands agent setup try: @@ -118,12 +115,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): context = LLMContext() user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, - user_params=LLMUserAggregatorParams( - user_turn_strategies=UserTurnStrategies( - stop=[TurnAnalyzerUserTurnStopStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3())] - ), - vad_analyzer=SileroVADAnalyzer(), - ), + user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()), ) pipeline = Pipeline( diff --git a/examples/foundational/07m-interruptible-aws.py b/examples/foundational/07m-interruptible-aws.py index 5be842202..eac193531 100644 --- a/examples/foundational/07m-interruptible-aws.py +++ b/examples/foundational/07m-interruptible-aws.py @@ -8,7 +8,6 @@ from dotenv import load_dotenv from loguru import logger -from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3 from pipecat.audio.vad.silero import SileroVADAnalyzer from pipecat.frames.frames import LLMRunFrame from pipecat.pipeline.pipeline import Pipeline @@ -27,8 +26,6 @@ from pipecat.services.aws.tts import AWSPollyTTSService from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams -from pipecat.turns.user_stop import TurnAnalyzerUserTurnStopStrategy -from pipecat.turns.user_turn_strategies import UserTurnStrategies load_dotenv(override=True) @@ -77,12 +74,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): context = LLMContext(messages) user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, - user_params=LLMUserAggregatorParams( - user_turn_strategies=UserTurnStrategies( - stop=[TurnAnalyzerUserTurnStopStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3())] - ), - vad_analyzer=SileroVADAnalyzer(), - ), + user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()), ) pipeline = Pipeline( diff --git a/examples/foundational/07n-interruptible-gemini-image.py b/examples/foundational/07n-interruptible-gemini-image.py index b412d8bf0..21fea9d1b 100644 --- a/examples/foundational/07n-interruptible-gemini-image.py +++ b/examples/foundational/07n-interruptible-gemini-image.py @@ -25,7 +25,6 @@ import os from dotenv import load_dotenv from loguru import logger -from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3 from pipecat.audio.vad.silero import SileroVADAnalyzer from pipecat.frames.frames import LLMRunFrame from pipecat.pipeline.pipeline import Pipeline @@ -44,8 +43,6 @@ from pipecat.services.google.tts import GoogleTTSService from pipecat.transcriptions.language import Language from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams -from pipecat.turns.user_stop import TurnAnalyzerUserTurnStopStrategy -from pipecat.turns.user_turn_strategies import UserTurnStrategies load_dotenv(override=True) @@ -99,12 +96,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): context = LLMContext(messages) user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, - user_params=LLMUserAggregatorParams( - user_turn_strategies=UserTurnStrategies( - stop=[TurnAnalyzerUserTurnStopStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3())] - ), - vad_analyzer=SileroVADAnalyzer(), - ), + user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()), ) pipeline = Pipeline( diff --git a/examples/foundational/07n-interruptible-gemini.py b/examples/foundational/07n-interruptible-gemini.py index 5323a0875..08315fcfa 100644 --- a/examples/foundational/07n-interruptible-gemini.py +++ b/examples/foundational/07n-interruptible-gemini.py @@ -10,7 +10,6 @@ import os from dotenv import load_dotenv from loguru import logger -from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3 from pipecat.audio.vad.silero import SileroVADAnalyzer from pipecat.frames.frames import LLMRunFrame from pipecat.pipeline.pipeline import Pipeline @@ -30,8 +29,6 @@ from pipecat.transcriptions.language import Language from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams -from pipecat.turns.user_stop import TurnAnalyzerUserTurnStopStrategy -from pipecat.turns.user_turn_strategies import UserTurnStrategies load_dotenv(override=True) @@ -104,12 +101,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): context = LLMContext(messages) user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, - user_params=LLMUserAggregatorParams( - user_turn_strategies=UserTurnStrategies( - stop=[TurnAnalyzerUserTurnStopStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3())] - ), - vad_analyzer=SileroVADAnalyzer(), - ), + user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()), ) pipeline = Pipeline( diff --git a/examples/foundational/07n-interruptible-google-http.py b/examples/foundational/07n-interruptible-google-http.py index ae5a1d3ba..e1fd0002f 100644 --- a/examples/foundational/07n-interruptible-google-http.py +++ b/examples/foundational/07n-interruptible-google-http.py @@ -10,7 +10,6 @@ import os from dotenv import load_dotenv from loguru import logger -from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3 from pipecat.audio.vad.silero import SileroVADAnalyzer from pipecat.frames.frames import LLMRunFrame from pipecat.pipeline.pipeline import Pipeline @@ -30,8 +29,6 @@ from pipecat.transcriptions.language import Language from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams -from pipecat.turns.user_stop import TurnAnalyzerUserTurnStopStrategy -from pipecat.turns.user_turn_strategies import UserTurnStrategies load_dotenv(override=True) @@ -87,12 +84,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): context = LLMContext(messages) user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, - user_params=LLMUserAggregatorParams( - user_turn_strategies=UserTurnStrategies( - stop=[TurnAnalyzerUserTurnStopStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3())] - ), - vad_analyzer=SileroVADAnalyzer(), - ), + user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()), ) pipeline = Pipeline( diff --git a/examples/foundational/07n-interruptible-google.py b/examples/foundational/07n-interruptible-google.py index 4591db940..e5c792c12 100644 --- a/examples/foundational/07n-interruptible-google.py +++ b/examples/foundational/07n-interruptible-google.py @@ -10,7 +10,6 @@ import os from dotenv import load_dotenv from loguru import logger -from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3 from pipecat.audio.vad.silero import SileroVADAnalyzer from pipecat.frames.frames import LLMRunFrame from pipecat.pipeline.pipeline import Pipeline @@ -30,8 +29,6 @@ from pipecat.transcriptions.language import Language from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams -from pipecat.turns.user_stop import TurnAnalyzerUserTurnStopStrategy -from pipecat.turns.user_turn_strategies import UserTurnStrategies load_dotenv(override=True) @@ -87,12 +84,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): context = LLMContext(messages) user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, - user_params=LLMUserAggregatorParams( - user_turn_strategies=UserTurnStrategies( - stop=[TurnAnalyzerUserTurnStopStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3())] - ), - vad_analyzer=SileroVADAnalyzer(), - ), + user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()), ) pipeline = Pipeline( diff --git a/examples/foundational/07o-interruptible-assemblyai.py b/examples/foundational/07o-interruptible-assemblyai.py index fe48c93e4..b65116b46 100644 --- a/examples/foundational/07o-interruptible-assemblyai.py +++ b/examples/foundational/07o-interruptible-assemblyai.py @@ -10,7 +10,6 @@ import os from dotenv import load_dotenv from loguru import logger -from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3 from pipecat.audio.vad.silero import SileroVADAnalyzer from pipecat.frames.frames import LLMRunFrame from pipecat.pipeline.pipeline import Pipeline @@ -29,8 +28,6 @@ from pipecat.services.openai.llm import OpenAILLMService from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams -from pipecat.turns.user_stop import TurnAnalyzerUserTurnStopStrategy -from pipecat.turns.user_turn_strategies import UserTurnStrategies load_dotenv(override=True) @@ -77,12 +74,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): context = LLMContext(messages) user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, - user_params=LLMUserAggregatorParams( - user_turn_strategies=UserTurnStrategies( - stop=[TurnAnalyzerUserTurnStopStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3())] - ), - vad_analyzer=SileroVADAnalyzer(), - ), + user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()), ) pipeline = Pipeline( diff --git a/examples/foundational/07p-interruptible-krisp-viva.py b/examples/foundational/07p-interruptible-krisp-viva.py index 160514818..259f02aa5 100644 --- a/examples/foundational/07p-interruptible-krisp-viva.py +++ b/examples/foundational/07p-interruptible-krisp-viva.py @@ -47,8 +47,6 @@ from pipecat.services.openai.llm import OpenAILLMService from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams -from pipecat.turns.user_stop import TurnAnalyzerUserTurnStopStrategy -from pipecat.turns.user_turn_strategies import UserTurnStrategies load_dotenv(override=True) diff --git a/examples/foundational/07p-interruptible-krisp.py b/examples/foundational/07p-interruptible-krisp.py index 5205b290b..6a17a57eb 100644 --- a/examples/foundational/07p-interruptible-krisp.py +++ b/examples/foundational/07p-interruptible-krisp.py @@ -11,7 +11,6 @@ from dotenv import load_dotenv from loguru import logger from pipecat.audio.filters.krisp_filter import KrispFilter -from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3 from pipecat.audio.vad.silero import SileroVADAnalyzer from pipecat.frames.frames import LLMRunFrame from pipecat.pipeline.pipeline import Pipeline @@ -30,8 +29,6 @@ from pipecat.services.openai.llm import OpenAILLMService from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams -from pipecat.turns.user_stop import TurnAnalyzerUserTurnStopStrategy -from pipecat.turns.user_turn_strategies import UserTurnStrategies load_dotenv(override=True) @@ -75,12 +72,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): context = LLMContext(messages) user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, - user_params=LLMUserAggregatorParams( - user_turn_strategies=UserTurnStrategies( - stop=[TurnAnalyzerUserTurnStopStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3())] - ), - vad_analyzer=SileroVADAnalyzer(), - ), + user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()), ) pipeline = Pipeline( diff --git a/examples/foundational/07q-interruptible-rime-http.py b/examples/foundational/07q-interruptible-rime-http.py index 9bece02fb..902b6b231 100644 --- a/examples/foundational/07q-interruptible-rime-http.py +++ b/examples/foundational/07q-interruptible-rime-http.py @@ -11,7 +11,6 @@ import aiohttp from dotenv import load_dotenv from loguru import logger -from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3 from pipecat.audio.vad.silero import SileroVADAnalyzer from pipecat.frames.frames import LLMRunFrame from pipecat.pipeline.pipeline import Pipeline @@ -30,8 +29,6 @@ from pipecat.services.rime.tts import RimeHttpTTSService from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams -from pipecat.turns.user_stop import TurnAnalyzerUserTurnStopStrategy -from pipecat.turns.user_turn_strategies import UserTurnStrategies load_dotenv(override=True) @@ -80,14 +77,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): context = LLMContext(messages) user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, - user_params=LLMUserAggregatorParams( - user_turn_strategies=UserTurnStrategies( - stop=[ - TurnAnalyzerUserTurnStopStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3()) - ] - ), - vad_analyzer=SileroVADAnalyzer(), - ), + user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()), ) pipeline = Pipeline( diff --git a/examples/foundational/07q-interruptible-rime.py b/examples/foundational/07q-interruptible-rime.py index 2692872ce..1042d05ee 100644 --- a/examples/foundational/07q-interruptible-rime.py +++ b/examples/foundational/07q-interruptible-rime.py @@ -10,7 +10,6 @@ import os from dotenv import load_dotenv from loguru import logger -from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3 from pipecat.audio.vad.silero import SileroVADAnalyzer from pipecat.frames.frames import LLMRunFrame from pipecat.pipeline.pipeline import Pipeline @@ -29,8 +28,6 @@ from pipecat.services.rime.tts import RimeTTSService from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams -from pipecat.turns.user_stop import TurnAnalyzerUserTurnStopStrategy -from pipecat.turns.user_turn_strategies import UserTurnStrategies load_dotenv(override=True) @@ -74,12 +71,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): context = LLMContext(messages) user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, - user_params=LLMUserAggregatorParams( - user_turn_strategies=UserTurnStrategies( - stop=[TurnAnalyzerUserTurnStopStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3())] - ), - vad_analyzer=SileroVADAnalyzer(), - ), + user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()), ) pipeline = Pipeline( diff --git a/examples/foundational/07r-interruptible-nvidia.py b/examples/foundational/07r-interruptible-nvidia.py index 1702c59dd..18e0b5d5f 100644 --- a/examples/foundational/07r-interruptible-nvidia.py +++ b/examples/foundational/07r-interruptible-nvidia.py @@ -10,7 +10,6 @@ import os from dotenv import load_dotenv from loguru import logger -from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3 from pipecat.audio.vad.silero import SileroVADAnalyzer from pipecat.frames.frames import LLMRunFrame from pipecat.pipeline.pipeline import Pipeline @@ -29,8 +28,6 @@ from pipecat.services.nvidia.tts import NvidiaTTSService from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams -from pipecat.turns.user_stop import TurnAnalyzerUserTurnStopStrategy -from pipecat.turns.user_turn_strategies import UserTurnStrategies load_dotenv(override=True) @@ -73,12 +70,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): context = LLMContext(messages) user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, - user_params=LLMUserAggregatorParams( - user_turn_strategies=UserTurnStrategies( - stop=[TurnAnalyzerUserTurnStopStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3())] - ), - vad_analyzer=SileroVADAnalyzer(), - ), + user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()), ) pipeline = Pipeline( diff --git a/examples/foundational/07s-interruptible-google-audio-in.py b/examples/foundational/07s-interruptible-google-audio-in.py index 7d8d5afce..707db107e 100644 --- a/examples/foundational/07s-interruptible-google-audio-in.py +++ b/examples/foundational/07s-interruptible-google-audio-in.py @@ -12,7 +12,6 @@ from dotenv import load_dotenv from google.genai.types import Content, Part from loguru import logger -from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3 from pipecat.audio.vad.silero import SileroVADAnalyzer from pipecat.frames.frames import ( Frame, @@ -43,8 +42,6 @@ from pipecat.transcriptions.language import Language from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams -from pipecat.turns.user_stop import TurnAnalyzerUserTurnStopStrategy -from pipecat.turns.user_turn_strategies import UserTurnStrategies load_dotenv(override=True) @@ -246,12 +243,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): context = LLMContext(messages) user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, - user_params=LLMUserAggregatorParams( - user_turn_strategies=UserTurnStrategies( - stop=[TurnAnalyzerUserTurnStopStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3())] - ), - vad_analyzer=SileroVADAnalyzer(), - ), + user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()), ) audio_collector = UserAudioCollector(context, user_aggregator) pull_transcript_out_of_llm_output = TranscriptExtractor(context) diff --git a/examples/foundational/07t-interruptible-fish.py b/examples/foundational/07t-interruptible-fish.py index c059771eb..2df978475 100644 --- a/examples/foundational/07t-interruptible-fish.py +++ b/examples/foundational/07t-interruptible-fish.py @@ -10,7 +10,6 @@ import os from dotenv import load_dotenv from loguru import logger -from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3 from pipecat.audio.vad.silero import SileroVADAnalyzer from pipecat.frames.frames import LLMRunFrame from pipecat.pipeline.pipeline import Pipeline @@ -29,8 +28,6 @@ from pipecat.services.openai.llm import OpenAILLMService from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams -from pipecat.turns.user_stop import TurnAnalyzerUserTurnStopStrategy -from pipecat.turns.user_turn_strategies import UserTurnStrategies load_dotenv(override=True) @@ -75,12 +72,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): context = LLMContext(messages) user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, - user_params=LLMUserAggregatorParams( - user_turn_strategies=UserTurnStrategies( - stop=[TurnAnalyzerUserTurnStopStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3())] - ), - vad_analyzer=SileroVADAnalyzer(), - ), + user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()), ) pipeline = Pipeline( diff --git a/examples/foundational/07v-interruptible-neuphonic-http.py b/examples/foundational/07v-interruptible-neuphonic-http.py index e115c8f06..d3f27613e 100644 --- a/examples/foundational/07v-interruptible-neuphonic-http.py +++ b/examples/foundational/07v-interruptible-neuphonic-http.py @@ -11,7 +11,6 @@ import aiohttp from dotenv import load_dotenv from loguru import logger -from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3 from pipecat.audio.vad.silero import SileroVADAnalyzer from pipecat.frames.frames import LLMRunFrame from pipecat.pipeline.pipeline import Pipeline @@ -30,8 +29,6 @@ from pipecat.services.openai.llm import OpenAILLMService from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams -from pipecat.turns.user_stop import TurnAnalyzerUserTurnStopStrategy -from pipecat.turns.user_turn_strategies import UserTurnStrategies load_dotenv(override=True) @@ -79,14 +76,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): context = LLMContext(messages) user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, - user_params=LLMUserAggregatorParams( - user_turn_strategies=UserTurnStrategies( - stop=[ - TurnAnalyzerUserTurnStopStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3()) - ] - ), - vad_analyzer=SileroVADAnalyzer(), - ), + user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()), ) pipeline = Pipeline( diff --git a/examples/foundational/07v-interruptible-neuphonic.py b/examples/foundational/07v-interruptible-neuphonic.py index f4f3d3a3a..c1ee64f3e 100644 --- a/examples/foundational/07v-interruptible-neuphonic.py +++ b/examples/foundational/07v-interruptible-neuphonic.py @@ -10,7 +10,6 @@ import os from dotenv import load_dotenv from loguru import logger -from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3 from pipecat.audio.vad.silero import SileroVADAnalyzer from pipecat.frames.frames import LLMRunFrame from pipecat.pipeline.pipeline import Pipeline @@ -29,8 +28,6 @@ from pipecat.services.openai.llm import OpenAILLMService from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams -from pipecat.turns.user_stop import TurnAnalyzerUserTurnStopStrategy -from pipecat.turns.user_turn_strategies import UserTurnStrategies load_dotenv(override=True) @@ -74,12 +71,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): context = LLMContext(messages) user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, - user_params=LLMUserAggregatorParams( - user_turn_strategies=UserTurnStrategies( - stop=[TurnAnalyzerUserTurnStopStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3())] - ), - vad_analyzer=SileroVADAnalyzer(), - ), + user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()), ) pipeline = Pipeline( diff --git a/examples/foundational/07w-interruptible-fal.py b/examples/foundational/07w-interruptible-fal.py index cddf9bb5a..41fad024a 100644 --- a/examples/foundational/07w-interruptible-fal.py +++ b/examples/foundational/07w-interruptible-fal.py @@ -10,7 +10,6 @@ import os from dotenv import load_dotenv from loguru import logger -from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3 from pipecat.audio.vad.silero import SileroVADAnalyzer from pipecat.frames.frames import LLMRunFrame from pipecat.pipeline.pipeline import Pipeline @@ -29,8 +28,6 @@ from pipecat.services.openai.llm import OpenAILLMService from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams -from pipecat.turns.user_stop import TurnAnalyzerUserTurnStopStrategy -from pipecat.turns.user_turn_strategies import UserTurnStrategies load_dotenv(override=True) @@ -77,12 +74,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): context = LLMContext(messages) user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, - user_params=LLMUserAggregatorParams( - user_turn_strategies=UserTurnStrategies( - stop=[TurnAnalyzerUserTurnStopStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3())] - ), - vad_analyzer=SileroVADAnalyzer(), - ), + user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()), ) pipeline = Pipeline( diff --git a/examples/foundational/07x-interruptible-local.py b/examples/foundational/07x-interruptible-local.py index a5a3bcda3..65e5836bc 100644 --- a/examples/foundational/07x-interruptible-local.py +++ b/examples/foundational/07x-interruptible-local.py @@ -11,7 +11,6 @@ import sys from dotenv import load_dotenv from loguru import logger -from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3 from pipecat.audio.vad.silero import SileroVADAnalyzer from pipecat.frames.frames import LLMRunFrame from pipecat.pipeline.pipeline import Pipeline @@ -26,8 +25,6 @@ from pipecat.services.cartesia.tts import CartesiaTTSService from pipecat.services.deepgram.stt import DeepgramSTTService from pipecat.services.openai.llm import OpenAILLMService from pipecat.transports.local.audio import LocalAudioTransport, LocalAudioTransportParams -from pipecat.turns.user_stop import TurnAnalyzerUserTurnStopStrategy -from pipecat.turns.user_turn_strategies import UserTurnStrategies load_dotenv(override=True) @@ -62,12 +59,7 @@ async def main(): context = LLMContext(messages) user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, - user_params=LLMUserAggregatorParams( - user_turn_strategies=UserTurnStrategies( - stop=[TurnAnalyzerUserTurnStopStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3())] - ), - vad_analyzer=SileroVADAnalyzer(), - ), + user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()), ) pipeline = Pipeline( diff --git a/examples/foundational/07y-interruptible-minimax.py b/examples/foundational/07y-interruptible-minimax.py index a0e325956..1900b1ba8 100644 --- a/examples/foundational/07y-interruptible-minimax.py +++ b/examples/foundational/07y-interruptible-minimax.py @@ -11,7 +11,6 @@ import aiohttp from dotenv import load_dotenv from loguru import logger -from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3 from pipecat.audio.vad.silero import SileroVADAnalyzer from pipecat.frames.frames import LLMRunFrame from pipecat.pipeline.pipeline import Pipeline @@ -31,8 +30,6 @@ from pipecat.transcriptions.language import Language from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams -from pipecat.turns.user_stop import TurnAnalyzerUserTurnStopStrategy -from pipecat.turns.user_turn_strategies import UserTurnStrategies load_dotenv(override=True) @@ -81,14 +78,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): context = LLMContext(messages) user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, - user_params=LLMUserAggregatorParams( - user_turn_strategies=UserTurnStrategies( - stop=[ - TurnAnalyzerUserTurnStopStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3()) - ] - ), - vad_analyzer=SileroVADAnalyzer(), - ), + user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()), ) pipeline = Pipeline( diff --git a/examples/foundational/07z-interruptible-sarvam-http.py b/examples/foundational/07z-interruptible-sarvam-http.py index ff2b636b8..e65be1f8e 100644 --- a/examples/foundational/07z-interruptible-sarvam-http.py +++ b/examples/foundational/07z-interruptible-sarvam-http.py @@ -11,7 +11,6 @@ import aiohttp from dotenv import load_dotenv from loguru import logger -from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3 from pipecat.audio.vad.silero import SileroVADAnalyzer from pipecat.frames.frames import LLMRunFrame from pipecat.pipeline.pipeline import Pipeline @@ -31,8 +30,6 @@ from pipecat.transcriptions.language import Language from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams -from pipecat.turns.user_stop import TurnAnalyzerUserTurnStopStrategy -from pipecat.turns.user_turn_strategies import UserTurnStrategies load_dotenv(override=True) @@ -83,14 +80,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): context = LLMContext(messages) user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, - user_params=LLMUserAggregatorParams( - user_turn_strategies=UserTurnStrategies( - stop=[ - TurnAnalyzerUserTurnStopStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3()) - ] - ), - vad_analyzer=SileroVADAnalyzer(), - ), + user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()), ) pipeline = Pipeline( diff --git a/examples/foundational/07z-interruptible-sarvam.py b/examples/foundational/07z-interruptible-sarvam.py index 492aec4e1..82e070be2 100644 --- a/examples/foundational/07z-interruptible-sarvam.py +++ b/examples/foundational/07z-interruptible-sarvam.py @@ -9,7 +9,6 @@ import os from dotenv import load_dotenv from loguru import logger -from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3 from pipecat.audio.vad.silero import SileroVADAnalyzer from pipecat.frames.frames import LLMRunFrame from pipecat.pipeline.pipeline import Pipeline @@ -28,8 +27,6 @@ from pipecat.services.sarvam.tts import SarvamTTSService from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams -from pipecat.turns.user_stop import TurnAnalyzerUserTurnStopStrategy -from pipecat.turns.user_turn_strategies import UserTurnStrategies load_dotenv(override=True) @@ -77,12 +74,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): context = LLMContext(messages) user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, - user_params=LLMUserAggregatorParams( - user_turn_strategies=UserTurnStrategies( - stop=[TurnAnalyzerUserTurnStopStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3())] - ), - vad_analyzer=SileroVADAnalyzer(), - ), + user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()), ) pipeline = Pipeline( diff --git a/examples/foundational/07za-interruptible-soniox.py b/examples/foundational/07za-interruptible-soniox.py index 55596b8dc..95677c045 100644 --- a/examples/foundational/07za-interruptible-soniox.py +++ b/examples/foundational/07za-interruptible-soniox.py @@ -10,7 +10,6 @@ import os from dotenv import load_dotenv from loguru import logger -from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3 from pipecat.audio.vad.silero import SileroVADAnalyzer from pipecat.frames.frames import LLMRunFrame from pipecat.pipeline.pipeline import Pipeline @@ -29,8 +28,6 @@ from pipecat.services.soniox.stt import SonioxSTTService from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams -from pipecat.turns.user_stop import TurnAnalyzerUserTurnStopStrategy -from pipecat.turns.user_turn_strategies import UserTurnStrategies load_dotenv(override=True) @@ -74,12 +71,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): context = LLMContext(messages) user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, - user_params=LLMUserAggregatorParams( - user_turn_strategies=UserTurnStrategies( - stop=[TurnAnalyzerUserTurnStopStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3())] - ), - vad_analyzer=SileroVADAnalyzer(), - ), + user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()), ) pipeline = Pipeline( diff --git a/examples/foundational/07zb-interruptible-inworld-http.py b/examples/foundational/07zb-interruptible-inworld-http.py index 6ec35f124..c6441e1c3 100644 --- a/examples/foundational/07zb-interruptible-inworld-http.py +++ b/examples/foundational/07zb-interruptible-inworld-http.py @@ -10,7 +10,6 @@ import aiohttp from dotenv import load_dotenv from loguru import logger -from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3 from pipecat.audio.vad.silero import SileroVADAnalyzer from pipecat.frames.frames import LLMRunFrame, TTSTextFrame from pipecat.observers.loggers.debug_log_observer import DebugLogObserver, FrameEndpoint @@ -31,8 +30,6 @@ from pipecat.transports.base_output import BaseOutputTransport from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams -from pipecat.turns.user_stop import TurnAnalyzerUserTurnStopStrategy -from pipecat.turns.user_turn_strategies import UserTurnStrategies load_dotenv(override=True) @@ -79,14 +76,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): context = LLMContext(messages) user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, - user_params=LLMUserAggregatorParams( - user_turn_strategies=UserTurnStrategies( - stop=[ - TurnAnalyzerUserTurnStopStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3()) - ] - ), - vad_analyzer=SileroVADAnalyzer(), - ), + user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()), ) pipeline = Pipeline( diff --git a/examples/foundational/07zb-interruptible-inworld.py b/examples/foundational/07zb-interruptible-inworld.py index 0d3bcb52e..9af1302d3 100644 --- a/examples/foundational/07zb-interruptible-inworld.py +++ b/examples/foundational/07zb-interruptible-inworld.py @@ -9,7 +9,6 @@ import os from dotenv import load_dotenv from loguru import logger -from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3 from pipecat.audio.vad.silero import SileroVADAnalyzer from pipecat.frames.frames import LLMRunFrame, TTSTextFrame from pipecat.observers.loggers.debug_log_observer import DebugLogObserver, FrameEndpoint @@ -30,8 +29,6 @@ from pipecat.transports.base_output import BaseOutputTransport from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams -from pipecat.turns.user_stop import TurnAnalyzerUserTurnStopStrategy -from pipecat.turns.user_turn_strategies import UserTurnStrategies load_dotenv(override=True) @@ -76,12 +73,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): context = LLMContext(messages) user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, - user_params=LLMUserAggregatorParams( - user_turn_strategies=UserTurnStrategies( - stop=[TurnAnalyzerUserTurnStopStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3())] - ), - vad_analyzer=SileroVADAnalyzer(), - ), + user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()), ) pipeline = Pipeline( diff --git a/examples/foundational/07zc-interruptible-asyncai-http.py b/examples/foundational/07zc-interruptible-asyncai-http.py index 59fafa98d..3720736bd 100644 --- a/examples/foundational/07zc-interruptible-asyncai-http.py +++ b/examples/foundational/07zc-interruptible-asyncai-http.py @@ -11,7 +11,6 @@ import aiohttp from dotenv import load_dotenv from loguru import logger -from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3 from pipecat.audio.vad.silero import SileroVADAnalyzer from pipecat.frames.frames import LLMRunFrame from pipecat.pipeline.pipeline import Pipeline @@ -30,8 +29,6 @@ from pipecat.services.openai.llm import OpenAILLMService from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams -from pipecat.turns.user_stop import TurnAnalyzerUserTurnStopStrategy -from pipecat.turns.user_turn_strategies import UserTurnStrategies load_dotenv(override=True) @@ -79,14 +76,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): context = LLMContext(messages) user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, - user_params=LLMUserAggregatorParams( - user_turn_strategies=UserTurnStrategies( - stop=[ - TurnAnalyzerUserTurnStopStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3()) - ] - ), - vad_analyzer=SileroVADAnalyzer(), - ), + user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()), ) pipeline = Pipeline( diff --git a/examples/foundational/07zc-interruptible-asyncai.py b/examples/foundational/07zc-interruptible-asyncai.py index de14107fe..31d8fb437 100644 --- a/examples/foundational/07zc-interruptible-asyncai.py +++ b/examples/foundational/07zc-interruptible-asyncai.py @@ -10,7 +10,6 @@ import os from dotenv import load_dotenv from loguru import logger -from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3 from pipecat.audio.vad.silero import SileroVADAnalyzer from pipecat.frames.frames import LLMRunFrame from pipecat.pipeline.pipeline import Pipeline @@ -29,8 +28,6 @@ from pipecat.services.openai.llm import OpenAILLMService from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams -from pipecat.turns.user_stop import TurnAnalyzerUserTurnStopStrategy -from pipecat.turns.user_turn_strategies import UserTurnStrategies load_dotenv(override=True) @@ -75,12 +72,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): context = LLMContext(messages) user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, - user_params=LLMUserAggregatorParams( - user_turn_strategies=UserTurnStrategies( - stop=[TurnAnalyzerUserTurnStopStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3())] - ), - vad_analyzer=SileroVADAnalyzer(), - ), + user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()), ) pipeline = Pipeline( diff --git a/examples/foundational/07zd-interruptible-aicoustics.py b/examples/foundational/07zd-interruptible-aicoustics.py index add1b04ec..61298a706 100644 --- a/examples/foundational/07zd-interruptible-aicoustics.py +++ b/examples/foundational/07zd-interruptible-aicoustics.py @@ -13,7 +13,6 @@ from dotenv import load_dotenv from loguru import logger from pipecat.audio.filters.aic_filter import AICFilter -from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3 from pipecat.frames.frames import LLMRunFrame from pipecat.pipeline.pipeline import Pipeline from pipecat.pipeline.runner import PipelineRunner @@ -32,8 +31,6 @@ from pipecat.services.openai.llm import OpenAILLMService from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams -from pipecat.turns.user_stop import TurnAnalyzerUserTurnStopStrategy -from pipecat.turns.user_turn_strategies import UserTurnStrategies load_dotenv(override=True) @@ -95,12 +92,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): context = LLMContext(messages) user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, - user_params=LLMUserAggregatorParams( - vad_analyzer=aic_vad_analyzer, - user_turn_strategies=UserTurnStrategies( - stop=[TurnAnalyzerUserTurnStopStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3())] - ), - ), + user_params=LLMUserAggregatorParams(vad_analyzer=aic_vad_analyzer), ) # Create audio buffer processor so we can hear the audio fitler results. diff --git a/examples/foundational/07ze-interruptible-hume.py b/examples/foundational/07ze-interruptible-hume.py index 4bef4bbe1..820e12a73 100644 --- a/examples/foundational/07ze-interruptible-hume.py +++ b/examples/foundational/07ze-interruptible-hume.py @@ -9,7 +9,6 @@ import os from dotenv import load_dotenv from loguru import logger -from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3 from pipecat.audio.vad.silero import SileroVADAnalyzer from pipecat.frames.frames import LLMRunFrame, TTSTextFrame from pipecat.observers.loggers.debug_log_observer import DebugLogObserver, FrameEndpoint @@ -30,8 +29,6 @@ from pipecat.transports.base_output import BaseOutputTransport from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams -from pipecat.turns.user_stop import TurnAnalyzerUserTurnStopStrategy -from pipecat.turns.user_turn_strategies import UserTurnStrategies load_dotenv(override=True) @@ -77,12 +74,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): context = LLMContext(messages) user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, - user_params=LLMUserAggregatorParams( - user_turn_strategies=UserTurnStrategies( - stop=[TurnAnalyzerUserTurnStopStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3())] - ), - vad_analyzer=SileroVADAnalyzer(), - ), + user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()), ) pipeline = Pipeline( diff --git a/examples/foundational/07zf-interruptible-gradium.py b/examples/foundational/07zf-interruptible-gradium.py index 16e2eeb8a..7c823325f 100644 --- a/examples/foundational/07zf-interruptible-gradium.py +++ b/examples/foundational/07zf-interruptible-gradium.py @@ -9,7 +9,6 @@ import os from dotenv import load_dotenv from loguru import logger -from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3 from pipecat.audio.vad.silero import SileroVADAnalyzer from pipecat.frames.frames import LLMRunFrame from pipecat.pipeline.pipeline import Pipeline @@ -29,8 +28,6 @@ from pipecat.transcriptions.language import Language from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams -from pipecat.turns.user_stop import TurnAnalyzerUserTurnStopStrategy -from pipecat.turns.user_turn_strategies import UserTurnStrategies load_dotenv(override=True) @@ -81,12 +78,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): context = LLMContext(messages) user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, - user_params=LLMUserAggregatorParams( - user_turn_strategies=UserTurnStrategies( - stop=[TurnAnalyzerUserTurnStopStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3())] - ), - vad_analyzer=SileroVADAnalyzer(), - ), + user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()), ) pipeline = Pipeline( diff --git a/examples/foundational/07zg-interruptible-camb.py b/examples/foundational/07zg-interruptible-camb.py index a0f31d68e..ace1fd8b3 100644 --- a/examples/foundational/07zg-interruptible-camb.py +++ b/examples/foundational/07zg-interruptible-camb.py @@ -9,7 +9,6 @@ import os from dotenv import load_dotenv from loguru import logger -from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3 from pipecat.audio.vad.silero import SileroVADAnalyzer from pipecat.frames.frames import LLMRunFrame from pipecat.pipeline.pipeline import Pipeline @@ -28,8 +27,6 @@ from pipecat.services.openai.llm import OpenAILLMService from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams -from pipecat.turns.user_stop import TurnAnalyzerUserTurnStopStrategy -from pipecat.turns.user_turn_strategies import UserTurnStrategies load_dotenv(override=True) @@ -76,12 +73,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): context = LLMContext(messages) user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, - user_params=LLMUserAggregatorParams( - user_turn_strategies=UserTurnStrategies( - stop=[TurnAnalyzerUserTurnStopStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3())] - ), - vad_analyzer=SileroVADAnalyzer(), - ), + user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()), ) pipeline = Pipeline( diff --git a/examples/foundational/07zh-interruptible-hathora.py b/examples/foundational/07zh-interruptible-hathora.py index 048de1e3d..7e903035e 100644 --- a/examples/foundational/07zh-interruptible-hathora.py +++ b/examples/foundational/07zh-interruptible-hathora.py @@ -1,5 +1,5 @@ # -# Copyright (c) 2024–2025, Daily +# Copyright (c) 2024–2026, Daily # # SPDX-License-Identifier: BSD 2-Clause License # @@ -9,7 +9,6 @@ import os from dotenv import load_dotenv from loguru import logger -from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3 from pipecat.audio.vad.silero import SileroVADAnalyzer from pipecat.frames.frames import LLMRunFrame from pipecat.pipeline.pipeline import Pipeline @@ -28,8 +27,6 @@ from pipecat.services.openai.llm import OpenAILLMService from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams -from pipecat.turns.user_stop import TurnAnalyzerUserTurnStopStrategy -from pipecat.turns.user_turn_strategies import UserTurnStrategies load_dotenv(override=True) @@ -79,12 +76,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): context = LLMContext(messages) context_aggregator = LLMContextAggregatorPair( context, - user_params=LLMUserAggregatorParams( - user_turn_strategies=UserTurnStrategies( - stop=[TurnAnalyzerUserTurnStopStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3())] - ), - vad_analyzer=SileroVADAnalyzer(), - ), + user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()), ) pipeline = Pipeline( diff --git a/examples/foundational/07zi-interruptible-piper.py b/examples/foundational/07zi-interruptible-piper.py index 0bd722f21..73b8d0f84 100644 --- a/examples/foundational/07zi-interruptible-piper.py +++ b/examples/foundational/07zi-interruptible-piper.py @@ -9,7 +9,6 @@ import os from dotenv import load_dotenv from loguru import logger -from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3 from pipecat.audio.vad.silero import SileroVADAnalyzer from pipecat.frames.frames import LLMRunFrame from pipecat.pipeline.pipeline import Pipeline @@ -28,8 +27,6 @@ from pipecat.services.piper.tts import PiperTTSService from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams -from pipecat.turns.user_stop import TurnAnalyzerUserTurnStopStrategy -from pipecat.turns.user_turn_strategies import UserTurnStrategies load_dotenv(override=True) @@ -71,12 +68,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): context = LLMContext(messages) user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, - user_params=LLMUserAggregatorParams( - user_turn_strategies=UserTurnStrategies( - stop=[TurnAnalyzerUserTurnStopStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3())] - ), - vad_analyzer=SileroVADAnalyzer(), - ), + user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()), ) pipeline = Pipeline( diff --git a/examples/foundational/07zj-interruptible-kokoro.py b/examples/foundational/07zj-interruptible-kokoro.py index f275c23b3..685388813 100644 --- a/examples/foundational/07zj-interruptible-kokoro.py +++ b/examples/foundational/07zj-interruptible-kokoro.py @@ -9,7 +9,6 @@ import os from dotenv import load_dotenv from loguru import logger -from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3 from pipecat.audio.vad.silero import SileroVADAnalyzer from pipecat.frames.frames import LLMRunFrame from pipecat.pipeline.pipeline import Pipeline @@ -28,8 +27,6 @@ from pipecat.services.openai.llm import OpenAILLMService from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams -from pipecat.turns.user_stop import TurnAnalyzerUserTurnStopStrategy -from pipecat.turns.user_turn_strategies import UserTurnStrategies load_dotenv(override=True) @@ -71,12 +68,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): context = LLMContext(messages) user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, - user_params=LLMUserAggregatorParams( - user_turn_strategies=UserTurnStrategies( - stop=[TurnAnalyzerUserTurnStopStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3())] - ), - vad_analyzer=SileroVADAnalyzer(), - ), + user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()), ) pipeline = Pipeline( diff --git a/examples/foundational/07zk-interruptible-resemble.py b/examples/foundational/07zk-interruptible-resemble.py index 4cb8271bb..3594d5b4f 100644 --- a/examples/foundational/07zk-interruptible-resemble.py +++ b/examples/foundational/07zk-interruptible-resemble.py @@ -9,7 +9,6 @@ import os from dotenv import load_dotenv from loguru import logger -from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3 from pipecat.audio.vad.silero import SileroVADAnalyzer from pipecat.frames.frames import LLMRunFrame from pipecat.pipeline.pipeline import Pipeline @@ -28,8 +27,6 @@ from pipecat.services.resembleai.tts import ResembleAITTSService from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams -from pipecat.turns.user_stop import TurnAnalyzerUserTurnStopStrategy -from pipecat.turns.user_turn_strategies import UserTurnStrategies load_dotenv(override=True) @@ -77,11 +74,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): context = LLMContext(messages) user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, - user_params=LLMUserAggregatorParams( - user_turn_strategies=UserTurnStrategies( - stop=[TurnAnalyzerUserTurnStopStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3())] - ), - ), + user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()), ) pipeline = Pipeline( diff --git a/examples/foundational/08-custom-frame-processor.py b/examples/foundational/08-custom-frame-processor.py index 779e891af..ba55eec7d 100644 --- a/examples/foundational/08-custom-frame-processor.py +++ b/examples/foundational/08-custom-frame-processor.py @@ -9,7 +9,6 @@ import os from dotenv import load_dotenv from loguru import logger -from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3 from pipecat.audio.vad.silero import SileroVADAnalyzer from pipecat.frames.frames import ( Frame, @@ -32,8 +31,6 @@ from pipecat.services.deepgram.stt import DeepgramSTTService from pipecat.services.openai.llm import OpenAILLMService from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams -from pipecat.turns.user_stop import TurnAnalyzerUserTurnStopStrategy -from pipecat.turns.user_turn_strategies import UserTurnStrategies load_dotenv(override=True) @@ -113,12 +110,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): context = LLMContext(messages) user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, - user_params=LLMUserAggregatorParams( - user_turn_strategies=UserTurnStrategies( - stop=[TurnAnalyzerUserTurnStopStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3())] - ), - vad_analyzer=SileroVADAnalyzer(), - ), + user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()), ) metrics_frame_processor = MetricsFrameLogger() diff --git a/examples/foundational/10-wake-phrase.py b/examples/foundational/10-wake-phrase.py index c2a5357bd..c7f53e496 100644 --- a/examples/foundational/10-wake-phrase.py +++ b/examples/foundational/10-wake-phrase.py @@ -9,7 +9,6 @@ import os from dotenv import load_dotenv from loguru import logger -from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3 from pipecat.audio.vad.silero import SileroVADAnalyzer from pipecat.frames.frames import TTSSpeakFrame from pipecat.pipeline.pipeline import Pipeline @@ -29,8 +28,6 @@ from pipecat.services.openai.llm import OpenAILLMService from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams -from pipecat.turns.user_stop import TurnAnalyzerUserTurnStopStrategy -from pipecat.turns.user_turn_strategies import UserTurnStrategies load_dotenv(override=True) @@ -76,12 +73,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): context = LLMContext(messages) user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, - user_params=LLMUserAggregatorParams( - user_turn_strategies=UserTurnStrategies( - stop=[TurnAnalyzerUserTurnStopStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3())] - ), - vad_analyzer=SileroVADAnalyzer(), - ), + user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()), ) pipeline = Pipeline( diff --git a/examples/foundational/11-sound-effects.py b/examples/foundational/11-sound-effects.py index 9cae7e205..156778317 100644 --- a/examples/foundational/11-sound-effects.py +++ b/examples/foundational/11-sound-effects.py @@ -10,7 +10,6 @@ import wave from dotenv import load_dotenv from loguru import logger -from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3 from pipecat.audio.vad.silero import SileroVADAnalyzer from pipecat.frames.frames import ( Frame, @@ -37,8 +36,6 @@ from pipecat.services.openai.llm import OpenAILLMService from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams -from pipecat.turns.user_stop import TurnAnalyzerUserTurnStopStrategy -from pipecat.turns.user_turn_strategies import UserTurnStrategies load_dotenv(override=True) @@ -124,12 +121,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): context = LLMContext(messages) user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, - user_params=LLMUserAggregatorParams( - user_turn_strategies=UserTurnStrategies( - stop=[TurnAnalyzerUserTurnStopStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3())] - ), - vad_analyzer=SileroVADAnalyzer(), - ), + user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()), ) out_sound = OutboundSoundEffectWrapper() in_sound = InboundSoundEffectWrapper() diff --git a/examples/foundational/12-describe-image-openai.py b/examples/foundational/12-describe-image-openai.py index 835584a21..afa334429 100644 --- a/examples/foundational/12-describe-image-openai.py +++ b/examples/foundational/12-describe-image-openai.py @@ -11,7 +11,6 @@ from dotenv import load_dotenv from loguru import logger from PIL import Image -from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3 from pipecat.audio.vad.silero import SileroVADAnalyzer from pipecat.frames.frames import LLMRunFrame from pipecat.pipeline.pipeline import Pipeline @@ -29,8 +28,6 @@ from pipecat.services.deepgram.stt import DeepgramSTTService from pipecat.services.openai.llm import OpenAILLMService from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams -from pipecat.turns.user_stop import TurnAnalyzerUserTurnStopStrategy -from pipecat.turns.user_turn_strategies import UserTurnStrategies load_dotenv(override=True) @@ -71,12 +68,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): context = LLMContext(messages) user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, - user_params=LLMUserAggregatorParams( - user_turn_strategies=UserTurnStrategies( - stop=[TurnAnalyzerUserTurnStopStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3())] - ), - vad_analyzer=SileroVADAnalyzer(), - ), + user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()), ) pipeline = Pipeline( diff --git a/examples/foundational/12a-describe-image-anthropic.py b/examples/foundational/12a-describe-image-anthropic.py index 45f85ede9..2b34c6220 100644 --- a/examples/foundational/12a-describe-image-anthropic.py +++ b/examples/foundational/12a-describe-image-anthropic.py @@ -11,7 +11,6 @@ from dotenv import load_dotenv from loguru import logger from PIL import Image -from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3 from pipecat.audio.vad.silero import SileroVADAnalyzer from pipecat.frames.frames import LLMRunFrame from pipecat.pipeline.pipeline import Pipeline @@ -29,8 +28,6 @@ from pipecat.services.cartesia.tts import CartesiaTTSService from pipecat.services.deepgram.stt import DeepgramSTTService from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams -from pipecat.turns.user_stop import TurnAnalyzerUserTurnStopStrategy -from pipecat.turns.user_turn_strategies import UserTurnStrategies load_dotenv(override=True) @@ -71,12 +68,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): context = LLMContext(messages) user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, - user_params=LLMUserAggregatorParams( - user_turn_strategies=UserTurnStrategies( - stop=[TurnAnalyzerUserTurnStopStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3())] - ), - vad_analyzer=SileroVADAnalyzer(), - ), + user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()), ) pipeline = Pipeline( diff --git a/examples/foundational/12b-describe-image-aws.py b/examples/foundational/12b-describe-image-aws.py index d27c655e4..84a391121 100644 --- a/examples/foundational/12b-describe-image-aws.py +++ b/examples/foundational/12b-describe-image-aws.py @@ -11,7 +11,6 @@ from dotenv import load_dotenv from loguru import logger from PIL import Image -from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3 from pipecat.audio.vad.silero import SileroVADAnalyzer from pipecat.frames.frames import LLMRunFrame from pipecat.pipeline.pipeline import Pipeline @@ -29,8 +28,6 @@ from pipecat.services.cartesia.tts import CartesiaTTSService from pipecat.services.deepgram.stt import DeepgramSTTService from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams -from pipecat.turns.user_stop import TurnAnalyzerUserTurnStopStrategy -from pipecat.turns.user_turn_strategies import UserTurnStrategies load_dotenv(override=True) @@ -78,12 +75,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): context = LLMContext(messages) user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, - user_params=LLMUserAggregatorParams( - user_turn_strategies=UserTurnStrategies( - stop=[TurnAnalyzerUserTurnStopStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3())] - ), - vad_analyzer=SileroVADAnalyzer(), - ), + user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()), ) pipeline = Pipeline( diff --git a/examples/foundational/12c-describe-image-gemini-flash.py b/examples/foundational/12c-describe-image-gemini-flash.py index 809386ef4..212dc5b32 100644 --- a/examples/foundational/12c-describe-image-gemini-flash.py +++ b/examples/foundational/12c-describe-image-gemini-flash.py @@ -11,7 +11,6 @@ from dotenv import load_dotenv from loguru import logger from PIL import Image -from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3 from pipecat.audio.vad.silero import SileroVADAnalyzer from pipecat.frames.frames import LLMRunFrame from pipecat.pipeline.pipeline import Pipeline @@ -29,8 +28,6 @@ from pipecat.services.deepgram.stt import DeepgramSTTService from pipecat.services.google.llm import GoogleLLMService from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams -from pipecat.turns.user_stop import TurnAnalyzerUserTurnStopStrategy -from pipecat.turns.user_turn_strategies import UserTurnStrategies load_dotenv(override=True) @@ -71,12 +68,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): context = LLMContext(messages) user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, - user_params=LLMUserAggregatorParams( - user_turn_strategies=UserTurnStrategies( - stop=[TurnAnalyzerUserTurnStopStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3())] - ), - vad_analyzer=SileroVADAnalyzer(), - ), + user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()), ) pipeline = Pipeline( diff --git a/examples/foundational/14-function-calling.py b/examples/foundational/14-function-calling.py index be292333b..27e666d0b 100644 --- a/examples/foundational/14-function-calling.py +++ b/examples/foundational/14-function-calling.py @@ -11,7 +11,6 @@ from loguru import logger from pipecat.adapters.schemas.function_schema import FunctionSchema from pipecat.adapters.schemas.tools_schema import ToolsSchema -from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3 from pipecat.audio.vad.silero import SileroVADAnalyzer from pipecat.frames.frames import LLMRunFrame, TTSSpeakFrame from pipecat.pipeline.pipeline import Pipeline @@ -31,8 +30,6 @@ from pipecat.services.openai.llm import OpenAILLMService from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams -from pipecat.turns.user_stop import TurnAnalyzerUserTurnStopStrategy -from pipecat.turns.user_turn_strategies import UserTurnStrategies load_dotenv(override=True) @@ -123,12 +120,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): context = LLMContext(messages, tools) user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, - user_params=LLMUserAggregatorParams( - user_turn_strategies=UserTurnStrategies( - stop=[TurnAnalyzerUserTurnStopStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3())] - ), - vad_analyzer=SileroVADAnalyzer(), - ), + user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()), ) pipeline = Pipeline( diff --git a/examples/foundational/14a-function-calling-anthropic.py b/examples/foundational/14a-function-calling-anthropic.py index 24e3140c5..165d4b220 100644 --- a/examples/foundational/14a-function-calling-anthropic.py +++ b/examples/foundational/14a-function-calling-anthropic.py @@ -12,7 +12,6 @@ from loguru import logger from pipecat.adapters.schemas.function_schema import FunctionSchema from pipecat.adapters.schemas.tools_schema import ToolsSchema -from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3 from pipecat.audio.vad.silero import SileroVADAnalyzer from pipecat.frames.frames import LLMRunFrame from pipecat.pipeline.pipeline import Pipeline @@ -32,8 +31,6 @@ from pipecat.services.llm_service import FunctionCallParams from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams -from pipecat.turns.user_stop import TurnAnalyzerUserTurnStopStrategy -from pipecat.turns.user_turn_strategies import UserTurnStrategies load_dotenv(override=True) @@ -118,12 +115,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): context = LLMContext(messages, tools) user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, - user_params=LLMUserAggregatorParams( - user_turn_strategies=UserTurnStrategies( - stop=[TurnAnalyzerUserTurnStopStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3())] - ), - vad_analyzer=SileroVADAnalyzer(), - ), + user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()), ) pipeline = Pipeline( diff --git a/examples/foundational/14c-function-calling-together.py b/examples/foundational/14c-function-calling-together.py index 4db8a881c..28dd8c466 100644 --- a/examples/foundational/14c-function-calling-together.py +++ b/examples/foundational/14c-function-calling-together.py @@ -12,7 +12,6 @@ from loguru import logger from pipecat.adapters.schemas.function_schema import FunctionSchema from pipecat.adapters.schemas.tools_schema import ToolsSchema -from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3 from pipecat.audio.vad.silero import SileroVADAnalyzer from pipecat.frames.frames import LLMRunFrame, TTSSpeakFrame from pipecat.pipeline.pipeline import Pipeline @@ -32,8 +31,6 @@ from pipecat.services.together.llm import TogetherLLMService from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams -from pipecat.turns.user_stop import TurnAnalyzerUserTurnStopStrategy -from pipecat.turns.user_turn_strategies import UserTurnStrategies load_dotenv(override=True) @@ -109,12 +106,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): context = LLMContext(messages, tools) user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, - user_params=LLMUserAggregatorParams( - user_turn_strategies=UserTurnStrategies( - stop=[TurnAnalyzerUserTurnStopStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3())] - ), - vad_analyzer=SileroVADAnalyzer(), - ), + user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()), ) pipeline = Pipeline( diff --git a/examples/foundational/14d-function-calling-anthropic-video.py b/examples/foundational/14d-function-calling-anthropic-video.py index efac52186..630a0aaac 100644 --- a/examples/foundational/14d-function-calling-anthropic-video.py +++ b/examples/foundational/14d-function-calling-anthropic-video.py @@ -11,7 +11,6 @@ from loguru import logger from pipecat.adapters.schemas.function_schema import FunctionSchema from pipecat.adapters.schemas.tools_schema import ToolsSchema -from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3 from pipecat.audio.vad.silero import SileroVADAnalyzer from pipecat.frames.frames import LLMRunFrame, TTSSpeakFrame, UserImageRequestFrame from pipecat.pipeline.pipeline import Pipeline @@ -35,8 +34,6 @@ from pipecat.services.deepgram.stt import DeepgramSTTService from pipecat.services.llm_service import FunctionCallParams from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams -from pipecat.turns.user_stop import TurnAnalyzerUserTurnStopStrategy -from pipecat.turns.user_turn_strategies import UserTurnStrategies load_dotenv(override=True) @@ -131,12 +128,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): context = LLMContext(messages, tools) user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, - user_params=LLMUserAggregatorParams( - user_turn_strategies=UserTurnStrategies( - stop=[TurnAnalyzerUserTurnStopStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3())] - ), - vad_analyzer=SileroVADAnalyzer(), - ), + user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()), ) pipeline = Pipeline( diff --git a/examples/foundational/14d-function-calling-aws-video.py b/examples/foundational/14d-function-calling-aws-video.py index 9f60f534c..2b22faada 100644 --- a/examples/foundational/14d-function-calling-aws-video.py +++ b/examples/foundational/14d-function-calling-aws-video.py @@ -11,7 +11,6 @@ from loguru import logger from pipecat.adapters.schemas.function_schema import FunctionSchema from pipecat.adapters.schemas.tools_schema import ToolsSchema -from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3 from pipecat.audio.vad.silero import SileroVADAnalyzer from pipecat.frames.frames import LLMRunFrame, TTSSpeakFrame, UserImageRequestFrame from pipecat.pipeline.pipeline import Pipeline @@ -35,8 +34,6 @@ from pipecat.services.deepgram.stt import DeepgramSTTService from pipecat.services.llm_service import FunctionCallParams from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams -from pipecat.turns.user_stop import TurnAnalyzerUserTurnStopStrategy -from pipecat.turns.user_turn_strategies import UserTurnStrategies load_dotenv(override=True) @@ -138,12 +135,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): context = LLMContext(messages, tools) user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, - user_params=LLMUserAggregatorParams( - user_turn_strategies=UserTurnStrategies( - stop=[TurnAnalyzerUserTurnStopStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3())] - ), - vad_analyzer=SileroVADAnalyzer(), - ), + user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()), ) pipeline = Pipeline( diff --git a/examples/foundational/14d-function-calling-gemini-flash-video.py b/examples/foundational/14d-function-calling-gemini-flash-video.py index 5d89e5b58..e3d4ca8a4 100644 --- a/examples/foundational/14d-function-calling-gemini-flash-video.py +++ b/examples/foundational/14d-function-calling-gemini-flash-video.py @@ -11,7 +11,6 @@ from loguru import logger from pipecat.adapters.schemas.function_schema import FunctionSchema from pipecat.adapters.schemas.tools_schema import ToolsSchema -from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3 from pipecat.audio.vad.silero import SileroVADAnalyzer from pipecat.frames.frames import LLMRunFrame, TTSSpeakFrame, UserImageRequestFrame from pipecat.pipeline.pipeline import Pipeline @@ -35,8 +34,6 @@ from pipecat.services.google.llm import GoogleLLMService from pipecat.services.llm_service import FunctionCallParams from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams -from pipecat.turns.user_stop import TurnAnalyzerUserTurnStopStrategy -from pipecat.turns.user_turn_strategies import UserTurnStrategies load_dotenv(override=True) @@ -131,12 +128,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): context = LLMContext(messages, tools) user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, - user_params=LLMUserAggregatorParams( - user_turn_strategies=UserTurnStrategies( - stop=[TurnAnalyzerUserTurnStopStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3())] - ), - vad_analyzer=SileroVADAnalyzer(), - ), + user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()), ) pipeline = Pipeline( diff --git a/examples/foundational/14d-function-calling-moondream-video.py b/examples/foundational/14d-function-calling-moondream-video.py index adb943406..77e9282f4 100644 --- a/examples/foundational/14d-function-calling-moondream-video.py +++ b/examples/foundational/14d-function-calling-moondream-video.py @@ -11,7 +11,6 @@ from loguru import logger from pipecat.adapters.schemas.function_schema import FunctionSchema from pipecat.adapters.schemas.tools_schema import ToolsSchema -from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3 from pipecat.audio.vad.silero import SileroVADAnalyzer from pipecat.frames.frames import ( Frame, @@ -45,8 +44,6 @@ from pipecat.services.moondream.vision import MoondreamService from pipecat.services.openai.llm import OpenAILLMService from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams -from pipecat.turns.user_stop import TurnAnalyzerUserTurnStopStrategy -from pipecat.turns.user_turn_strategies import UserTurnStrategies load_dotenv(override=True) @@ -161,12 +158,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): context = LLMContext(messages, tools) user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, - user_params=LLMUserAggregatorParams( - user_turn_strategies=UserTurnStrategies( - stop=[TurnAnalyzerUserTurnStopStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3())] - ), - vad_analyzer=SileroVADAnalyzer(), - ), + user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()), ) # If you run into weird description, try with use_cpu=True diff --git a/examples/foundational/14d-function-calling-openai-video.py b/examples/foundational/14d-function-calling-openai-video.py index a6b9b7d43..88c0e8ba3 100644 --- a/examples/foundational/14d-function-calling-openai-video.py +++ b/examples/foundational/14d-function-calling-openai-video.py @@ -12,7 +12,6 @@ from loguru import logger from pipecat.adapters.schemas.function_schema import FunctionSchema from pipecat.adapters.schemas.tools_schema import ToolsSchema -from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3 from pipecat.audio.vad.silero import SileroVADAnalyzer from pipecat.frames.frames import LLMRunFrame, TTSSpeakFrame, UserImageRequestFrame from pipecat.pipeline.pipeline import Pipeline @@ -36,8 +35,6 @@ from pipecat.services.llm_service import FunctionCallParams from pipecat.services.openai.llm import OpenAILLMService from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams -from pipecat.turns.user_stop import TurnAnalyzerUserTurnStopStrategy -from pipecat.turns.user_turn_strategies import UserTurnStrategies load_dotenv(override=True) @@ -131,12 +128,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): context = LLMContext(messages, tools) user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, - user_params=LLMUserAggregatorParams( - user_turn_strategies=UserTurnStrategies( - stop=[TurnAnalyzerUserTurnStopStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3())] - ), - vad_analyzer=SileroVADAnalyzer(), - ), + user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()), ) pipeline = Pipeline( diff --git a/examples/foundational/14e-function-calling-google.py b/examples/foundational/14e-function-calling-google.py index 2faecd3a6..cae32146e 100644 --- a/examples/foundational/14e-function-calling-google.py +++ b/examples/foundational/14e-function-calling-google.py @@ -12,7 +12,6 @@ from loguru import logger from pipecat.adapters.schemas.function_schema import FunctionSchema from pipecat.adapters.schemas.tools_schema import ToolsSchema -from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3 from pipecat.audio.vad.silero import SileroVADAnalyzer from pipecat.frames.frames import LLMRunFrame, TTSSpeakFrame, UserImageRequestFrame from pipecat.pipeline.pipeline import Pipeline @@ -36,8 +35,6 @@ from pipecat.services.google.llm import GoogleLLMService from pipecat.services.llm_service import FunctionCallParams from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams -from pipecat.turns.user_stop import TurnAnalyzerUserTurnStopStrategy -from pipecat.turns.user_turn_strategies import UserTurnStrategies load_dotenv(override=True) @@ -184,12 +181,7 @@ indicate you should use the get_image tool are: context = LLMContext(messages, tools) user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, - user_params=LLMUserAggregatorParams( - user_turn_strategies=UserTurnStrategies( - stop=[TurnAnalyzerUserTurnStopStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3())] - ), - vad_analyzer=SileroVADAnalyzer(), - ), + user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()), ) pipeline = Pipeline( diff --git a/examples/foundational/14f-function-calling-groq.py b/examples/foundational/14f-function-calling-groq.py index 7320e53f0..2c922d296 100644 --- a/examples/foundational/14f-function-calling-groq.py +++ b/examples/foundational/14f-function-calling-groq.py @@ -12,7 +12,6 @@ from loguru import logger from pipecat.adapters.schemas.function_schema import FunctionSchema from pipecat.adapters.schemas.tools_schema import ToolsSchema -from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3 from pipecat.audio.vad.silero import SileroVADAnalyzer from pipecat.frames.frames import LLMRunFrame, TTSSpeakFrame from pipecat.pipeline.pipeline import Pipeline @@ -32,8 +31,6 @@ from pipecat.services.llm_service import FunctionCallParams from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams -from pipecat.turns.user_stop import TurnAnalyzerUserTurnStopStrategy -from pipecat.turns.user_turn_strategies import UserTurnStrategies load_dotenv(override=True) @@ -106,12 +103,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): context = LLMContext(messages, tools) user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, - user_params=LLMUserAggregatorParams( - user_turn_strategies=UserTurnStrategies( - stop=[TurnAnalyzerUserTurnStopStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3())] - ), - vad_analyzer=SileroVADAnalyzer(), - ), + user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()), ) pipeline = Pipeline( diff --git a/examples/foundational/14g-function-calling-grok.py b/examples/foundational/14g-function-calling-grok.py index fba6067de..e8529aba5 100644 --- a/examples/foundational/14g-function-calling-grok.py +++ b/examples/foundational/14g-function-calling-grok.py @@ -12,7 +12,6 @@ from loguru import logger from pipecat.adapters.schemas.function_schema import FunctionSchema from pipecat.adapters.schemas.tools_schema import ToolsSchema -from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3 from pipecat.audio.vad.silero import SileroVADAnalyzer from pipecat.frames.frames import LLMRunFrame from pipecat.pipeline.pipeline import Pipeline @@ -32,8 +31,6 @@ from pipecat.services.llm_service import FunctionCallParams from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams -from pipecat.turns.user_stop import TurnAnalyzerUserTurnStopStrategy -from pipecat.turns.user_turn_strategies import UserTurnStrategies load_dotenv(override=True) @@ -102,12 +99,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): context = LLMContext(messages, tools) user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, - user_params=LLMUserAggregatorParams( - user_turn_strategies=UserTurnStrategies( - stop=[TurnAnalyzerUserTurnStopStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3())] - ), - vad_analyzer=SileroVADAnalyzer(), - ), + user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()), ) pipeline = Pipeline( diff --git a/examples/foundational/14h-function-calling-azure.py b/examples/foundational/14h-function-calling-azure.py index ed17e1cc6..fb9407f1a 100644 --- a/examples/foundational/14h-function-calling-azure.py +++ b/examples/foundational/14h-function-calling-azure.py @@ -12,7 +12,6 @@ from loguru import logger from pipecat.adapters.schemas.function_schema import FunctionSchema from pipecat.adapters.schemas.tools_schema import ToolsSchema -from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3 from pipecat.audio.vad.silero import SileroVADAnalyzer from pipecat.frames.frames import LLMRunFrame, TTSSpeakFrame from pipecat.pipeline.pipeline import Pipeline @@ -32,8 +31,6 @@ from pipecat.services.llm_service import FunctionCallParams from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams -from pipecat.turns.user_stop import TurnAnalyzerUserTurnStopStrategy -from pipecat.turns.user_turn_strategies import UserTurnStrategies load_dotenv(override=True) @@ -110,12 +107,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): context = LLMContext(messages, tools) user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, - user_params=LLMUserAggregatorParams( - user_turn_strategies=UserTurnStrategies( - stop=[TurnAnalyzerUserTurnStopStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3())] - ), - vad_analyzer=SileroVADAnalyzer(), - ), + user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()), ) pipeline = Pipeline( diff --git a/examples/foundational/14i-function-calling-fireworks.py b/examples/foundational/14i-function-calling-fireworks.py index 475987b5f..7a350f84f 100644 --- a/examples/foundational/14i-function-calling-fireworks.py +++ b/examples/foundational/14i-function-calling-fireworks.py @@ -12,7 +12,6 @@ from loguru import logger from pipecat.adapters.schemas.function_schema import FunctionSchema from pipecat.adapters.schemas.tools_schema import ToolsSchema -from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3 from pipecat.audio.vad.silero import SileroVADAnalyzer from pipecat.frames.frames import LLMRunFrame from pipecat.pipeline.pipeline import Pipeline @@ -32,8 +31,6 @@ from pipecat.services.llm_service import FunctionCallParams from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams -from pipecat.turns.user_stop import TurnAnalyzerUserTurnStopStrategy -from pipecat.turns.user_turn_strategies import UserTurnStrategies load_dotenv(override=True) @@ -113,12 +110,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): context = LLMContext(messages, tools) user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, - user_params=LLMUserAggregatorParams( - user_turn_strategies=UserTurnStrategies( - stop=[TurnAnalyzerUserTurnStopStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3())] - ), - vad_analyzer=SileroVADAnalyzer(), - ), + user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()), ) pipeline = Pipeline( diff --git a/examples/foundational/14j-function-calling-nvidia.py b/examples/foundational/14j-function-calling-nvidia.py index 2489661d2..e079c228f 100644 --- a/examples/foundational/14j-function-calling-nvidia.py +++ b/examples/foundational/14j-function-calling-nvidia.py @@ -12,7 +12,6 @@ from loguru import logger from pipecat.adapters.schemas.function_schema import FunctionSchema from pipecat.adapters.schemas.tools_schema import ToolsSchema -from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3 from pipecat.audio.vad.silero import SileroVADAnalyzer from pipecat.frames.frames import LLMRunFrame, TTSSpeakFrame from pipecat.pipeline.pipeline import Pipeline @@ -32,8 +31,6 @@ from pipecat.services.nvidia.llm import NvidiaLLMService from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams -from pipecat.turns.user_stop import TurnAnalyzerUserTurnStopStrategy -from pipecat.turns.user_turn_strategies import UserTurnStrategies load_dotenv(override=True) @@ -115,12 +112,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): context = LLMContext(messages, tools) user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, - user_params=LLMUserAggregatorParams( - user_turn_strategies=UserTurnStrategies( - stop=[TurnAnalyzerUserTurnStopStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3())] - ), - vad_analyzer=SileroVADAnalyzer(), - ), + user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()), ) pipeline = Pipeline( diff --git a/examples/foundational/14k-function-calling-cerebras.py b/examples/foundational/14k-function-calling-cerebras.py index 8163e95b7..ab340c77c 100644 --- a/examples/foundational/14k-function-calling-cerebras.py +++ b/examples/foundational/14k-function-calling-cerebras.py @@ -12,7 +12,6 @@ from loguru import logger from pipecat.adapters.schemas.function_schema import FunctionSchema from pipecat.adapters.schemas.tools_schema import ToolsSchema -from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3 from pipecat.audio.vad.silero import SileroVADAnalyzer from pipecat.frames.frames import LLMRunFrame, TTSSpeakFrame from pipecat.pipeline.pipeline import Pipeline @@ -32,8 +31,6 @@ from pipecat.services.llm_service import FunctionCallParams from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams -from pipecat.turns.user_stop import TurnAnalyzerUserTurnStopStrategy -from pipecat.turns.user_turn_strategies import UserTurnStrategies load_dotenv(override=True) @@ -116,12 +113,7 @@ Start by asking me for my location. Then, use 'get_weather_current' to give me a context = LLMContext(messages, tools) user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, - user_params=LLMUserAggregatorParams( - user_turn_strategies=UserTurnStrategies( - stop=[TurnAnalyzerUserTurnStopStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3())] - ), - vad_analyzer=SileroVADAnalyzer(), - ), + user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()), ) pipeline = Pipeline( diff --git a/examples/foundational/14l-function-calling-deepseek.py b/examples/foundational/14l-function-calling-deepseek.py index 63730976d..2d54fbe07 100644 --- a/examples/foundational/14l-function-calling-deepseek.py +++ b/examples/foundational/14l-function-calling-deepseek.py @@ -1,5 +1,5 @@ # -# Copyright (c) 2025, Daily +# Copyright (c) 2024-2026, Daily # # SPDX-License-Identifier: BSD 2-Clause License # @@ -12,7 +12,6 @@ from loguru import logger from pipecat.adapters.schemas.function_schema import FunctionSchema from pipecat.adapters.schemas.tools_schema import ToolsSchema -from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3 from pipecat.audio.vad.silero import SileroVADAnalyzer from pipecat.frames.frames import LLMRunFrame, TTSSpeakFrame from pipecat.pipeline.pipeline import Pipeline @@ -32,8 +31,6 @@ from pipecat.services.llm_service import FunctionCallParams from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams -from pipecat.turns.user_stop import TurnAnalyzerUserTurnStopStrategy -from pipecat.turns.user_turn_strategies import UserTurnStrategies load_dotenv(override=True) @@ -116,12 +113,7 @@ Start by asking me for my location. Then, use 'get_weather_current' to give me a context = LLMContext(messages, tools) user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, - user_params=LLMUserAggregatorParams( - user_turn_strategies=UserTurnStrategies( - stop=[TurnAnalyzerUserTurnStopStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3())] - ), - vad_analyzer=SileroVADAnalyzer(), - ), + user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()), ) pipeline = Pipeline( diff --git a/examples/foundational/14m-function-calling-openrouter.py b/examples/foundational/14m-function-calling-openrouter.py index 1cd47e6fb..5d6589a75 100644 --- a/examples/foundational/14m-function-calling-openrouter.py +++ b/examples/foundational/14m-function-calling-openrouter.py @@ -12,7 +12,6 @@ from loguru import logger from pipecat.adapters.schemas.function_schema import FunctionSchema from pipecat.adapters.schemas.tools_schema import ToolsSchema -from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3 from pipecat.audio.vad.silero import SileroVADAnalyzer from pipecat.frames.frames import LLMRunFrame, TTSSpeakFrame from pipecat.pipeline.pipeline import Pipeline @@ -32,8 +31,6 @@ from pipecat.services.openrouter.llm import OpenRouterLLMService from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams -from pipecat.turns.user_stop import TurnAnalyzerUserTurnStopStrategy -from pipecat.turns.user_turn_strategies import UserTurnStrategies load_dotenv(override=True) @@ -110,12 +107,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): context = LLMContext(messages, tools) user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, - user_params=LLMUserAggregatorParams( - user_turn_strategies=UserTurnStrategies( - stop=[TurnAnalyzerUserTurnStopStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3())] - ), - vad_analyzer=SileroVADAnalyzer(), - ), + user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()), ) pipeline = Pipeline( diff --git a/examples/foundational/14n-function-calling-perplexity.py b/examples/foundational/14n-function-calling-perplexity.py index e8b0a6f53..40041aa34 100644 --- a/examples/foundational/14n-function-calling-perplexity.py +++ b/examples/foundational/14n-function-calling-perplexity.py @@ -16,7 +16,6 @@ import os from dotenv import load_dotenv from loguru import logger -from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3 from pipecat.audio.vad.silero import SileroVADAnalyzer from pipecat.frames.frames import LLMRunFrame from pipecat.pipeline.pipeline import Pipeline @@ -35,8 +34,6 @@ from pipecat.services.perplexity.llm import PerplexityLLMService from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams -from pipecat.turns.user_stop import TurnAnalyzerUserTurnStopStrategy -from pipecat.turns.user_turn_strategies import UserTurnStrategies load_dotenv(override=True) @@ -80,12 +77,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): context = LLMContext(messages) user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, - user_params=LLMUserAggregatorParams( - user_turn_strategies=UserTurnStrategies( - stop=[TurnAnalyzerUserTurnStopStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3())] - ), - vad_analyzer=SileroVADAnalyzer(), - ), + user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()), ) pipeline = Pipeline( diff --git a/examples/foundational/14p-function-calling-gemini-vertex-ai.py b/examples/foundational/14p-function-calling-gemini-vertex-ai.py index cbff8d2f7..a71f3c8d1 100644 --- a/examples/foundational/14p-function-calling-gemini-vertex-ai.py +++ b/examples/foundational/14p-function-calling-gemini-vertex-ai.py @@ -12,7 +12,6 @@ from loguru import logger from pipecat.adapters.schemas.function_schema import FunctionSchema from pipecat.adapters.schemas.tools_schema import ToolsSchema -from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3 from pipecat.audio.vad.silero import SileroVADAnalyzer from pipecat.frames.frames import LLMRunFrame, TTSSpeakFrame from pipecat.pipeline.pipeline import Pipeline @@ -32,8 +31,6 @@ from pipecat.services.llm_service import FunctionCallParams from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams -from pipecat.turns.user_stop import TurnAnalyzerUserTurnStopStrategy -from pipecat.turns.user_turn_strategies import UserTurnStrategies load_dotenv(override=True) @@ -111,12 +108,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): context = LLMContext(messages, tools) user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, - user_params=LLMUserAggregatorParams( - user_turn_strategies=UserTurnStrategies( - stop=[TurnAnalyzerUserTurnStopStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3())] - ), - vad_analyzer=SileroVADAnalyzer(), - ), + user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()), ) pipeline = Pipeline( diff --git a/examples/foundational/14q-function-calling-qwen.py b/examples/foundational/14q-function-calling-qwen.py index 4f80989a1..72130b8fd 100644 --- a/examples/foundational/14q-function-calling-qwen.py +++ b/examples/foundational/14q-function-calling-qwen.py @@ -12,7 +12,6 @@ from loguru import logger from pipecat.adapters.schemas.function_schema import FunctionSchema from pipecat.adapters.schemas.tools_schema import ToolsSchema -from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3 from pipecat.audio.vad.silero import SileroVADAnalyzer from pipecat.frames.frames import LLMRunFrame, TTSSpeakFrame from pipecat.pipeline.pipeline import Pipeline @@ -32,8 +31,6 @@ from pipecat.services.qwen.llm import QwenLLMService from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams -from pipecat.turns.user_stop import TurnAnalyzerUserTurnStopStrategy -from pipecat.turns.user_turn_strategies import UserTurnStrategies load_dotenv(override=True) @@ -108,12 +105,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): context = LLMContext(messages, tools) user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, - user_params=LLMUserAggregatorParams( - user_turn_strategies=UserTurnStrategies( - stop=[TurnAnalyzerUserTurnStopStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3())] - ), - vad_analyzer=SileroVADAnalyzer(), - ), + user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()), ) pipeline = Pipeline( diff --git a/examples/foundational/14r-function-calling-aws.py b/examples/foundational/14r-function-calling-aws.py index 4ccfbbd3e..37d29ea7f 100644 --- a/examples/foundational/14r-function-calling-aws.py +++ b/examples/foundational/14r-function-calling-aws.py @@ -10,7 +10,6 @@ from loguru import logger from pipecat.adapters.schemas.function_schema import FunctionSchema from pipecat.adapters.schemas.tools_schema import ToolsSchema -from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3 from pipecat.audio.vad.silero import SileroVADAnalyzer from pipecat.frames.frames import LLMRunFrame from pipecat.pipeline.pipeline import Pipeline @@ -30,8 +29,6 @@ from pipecat.services.llm_service import FunctionCallParams from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams -from pipecat.turns.user_stop import TurnAnalyzerUserTurnStopStrategy -from pipecat.turns.user_turn_strategies import UserTurnStrategies load_dotenv(override=True) @@ -123,12 +120,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): context = LLMContext(messages, tools) user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, - user_params=LLMUserAggregatorParams( - user_turn_strategies=UserTurnStrategies( - stop=[TurnAnalyzerUserTurnStopStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3())] - ), - vad_analyzer=SileroVADAnalyzer(), - ), + user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()), ) pipeline = Pipeline( diff --git a/examples/foundational/14s-function-calling-sambanova.py b/examples/foundational/14s-function-calling-sambanova.py index a33567d11..79c43a473 100644 --- a/examples/foundational/14s-function-calling-sambanova.py +++ b/examples/foundational/14s-function-calling-sambanova.py @@ -12,7 +12,6 @@ from loguru import logger from pipecat.adapters.schemas.function_schema import FunctionSchema from pipecat.adapters.schemas.tools_schema import ToolsSchema -from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3 from pipecat.audio.vad.silero import SileroVADAnalyzer from pipecat.frames.frames import LLMRunFrame, TTSSpeakFrame from pipecat.pipeline.pipeline import Pipeline @@ -32,8 +31,6 @@ from pipecat.services.sambanova.stt import SambaNovaSTTService from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams -from pipecat.turns.user_stop import TurnAnalyzerUserTurnStopStrategy -from pipecat.turns.user_turn_strategies import UserTurnStrategies load_dotenv(override=True) @@ -112,12 +109,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): context = LLMContext(messages, tools) user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, - user_params=LLMUserAggregatorParams( - user_turn_strategies=UserTurnStrategies( - stop=[TurnAnalyzerUserTurnStopStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3())] - ), - vad_analyzer=SileroVADAnalyzer(), - ), + user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()), ) pipeline = Pipeline( diff --git a/examples/foundational/14t-function-calling-direct.py b/examples/foundational/14t-function-calling-direct.py index fd9c0a3c9..fc12101aa 100644 --- a/examples/foundational/14t-function-calling-direct.py +++ b/examples/foundational/14t-function-calling-direct.py @@ -1,5 +1,5 @@ # -# Copyright (c) 2025, Daily +# Copyright (c) 2024-2026, Daily # # SPDX-License-Identifier: BSD 2-Clause License # @@ -11,7 +11,6 @@ from dotenv import load_dotenv from loguru import logger from pipecat.adapters.schemas.tools_schema import ToolsSchema -from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3 from pipecat.audio.vad.silero import SileroVADAnalyzer from pipecat.frames.frames import LLMRunFrame, TTSSpeakFrame from pipecat.pipeline.pipeline import Pipeline @@ -31,8 +30,6 @@ from pipecat.services.openai.llm import OpenAILLMService from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams -from pipecat.turns.user_stop import TurnAnalyzerUserTurnStopStrategy -from pipecat.turns.user_turn_strategies import UserTurnStrategies load_dotenv(override=True) @@ -109,12 +106,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): context = LLMContext(messages, tools) user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, - user_params=LLMUserAggregatorParams( - user_turn_strategies=UserTurnStrategies( - stop=[TurnAnalyzerUserTurnStopStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3())] - ), - vad_analyzer=SileroVADAnalyzer(), - ), + user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()), ) pipeline = Pipeline( diff --git a/examples/foundational/14u-function-calling-ollama.py b/examples/foundational/14u-function-calling-ollama.py index 56e36dfdc..7da07b329 100644 --- a/examples/foundational/14u-function-calling-ollama.py +++ b/examples/foundational/14u-function-calling-ollama.py @@ -12,7 +12,6 @@ from loguru import logger from pipecat.adapters.schemas.function_schema import FunctionSchema from pipecat.adapters.schemas.tools_schema import ToolsSchema -from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3 from pipecat.audio.vad.silero import SileroVADAnalyzer from pipecat.frames.frames import LLMRunFrame, TTSSpeakFrame from pipecat.pipeline.pipeline import Pipeline @@ -32,8 +31,6 @@ from pipecat.services.ollama.llm import OLLamaLLMService from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams -from pipecat.turns.user_stop import TurnAnalyzerUserTurnStopStrategy -from pipecat.turns.user_turn_strategies import UserTurnStrategies load_dotenv(override=True) @@ -124,12 +121,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): context = LLMContext(messages, tools) user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, - user_params=LLMUserAggregatorParams( - user_turn_strategies=UserTurnStrategies( - stop=[TurnAnalyzerUserTurnStopStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3())] - ), - vad_analyzer=SileroVADAnalyzer(), - ), + user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()), ) pipeline = Pipeline( diff --git a/examples/foundational/14v-function-calling-openai.py b/examples/foundational/14v-function-calling-openai.py index c56d82abf..ad4aba063 100644 --- a/examples/foundational/14v-function-calling-openai.py +++ b/examples/foundational/14v-function-calling-openai.py @@ -11,7 +11,6 @@ from loguru import logger from pipecat.adapters.schemas.function_schema import FunctionSchema from pipecat.adapters.schemas.tools_schema import ToolsSchema -from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3 from pipecat.audio.vad.silero import SileroVADAnalyzer from pipecat.frames.frames import LLMRunFrame, TTSSpeakFrame from pipecat.pipeline.pipeline import Pipeline @@ -31,8 +30,6 @@ from pipecat.services.openai.tts import OpenAITTSService from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams -from pipecat.turns.user_stop import TurnAnalyzerUserTurnStopStrategy -from pipecat.turns.user_turn_strategies import UserTurnStrategies load_dotenv(override=True) @@ -131,12 +128,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): context = LLMContext(messages, tools) user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, - user_params=LLMUserAggregatorParams( - user_turn_strategies=UserTurnStrategies( - stop=[TurnAnalyzerUserTurnStopStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3())] - ), - vad_analyzer=SileroVADAnalyzer(), - ), + user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()), ) pipeline = Pipeline( diff --git a/examples/foundational/14w-function-calling-mistral.py b/examples/foundational/14w-function-calling-mistral.py index 09ad525d5..c62e8be05 100644 --- a/examples/foundational/14w-function-calling-mistral.py +++ b/examples/foundational/14w-function-calling-mistral.py @@ -11,7 +11,6 @@ from loguru import logger from pipecat.adapters.schemas.function_schema import FunctionSchema from pipecat.adapters.schemas.tools_schema import ToolsSchema -from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3 from pipecat.audio.vad.silero import SileroVADAnalyzer from pipecat.frames.frames import LLMRunFrame from pipecat.pipeline.pipeline import Pipeline @@ -31,8 +30,6 @@ from pipecat.services.mistral.llm import MistralLLMService from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams -from pipecat.turns.user_stop import TurnAnalyzerUserTurnStopStrategy -from pipecat.turns.user_turn_strategies import UserTurnStrategies load_dotenv(override=True) @@ -119,12 +116,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): context = LLMContext(messages, tools) user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, - user_params=LLMUserAggregatorParams( - user_turn_strategies=UserTurnStrategies( - stop=[TurnAnalyzerUserTurnStopStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3())] - ), - vad_analyzer=SileroVADAnalyzer(), - ), + user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()), ) pipeline = Pipeline( diff --git a/examples/foundational/14x-function-calling-openpipe.py b/examples/foundational/14x-function-calling-openpipe.py index fa877cdb1..576da02a4 100644 --- a/examples/foundational/14x-function-calling-openpipe.py +++ b/examples/foundational/14x-function-calling-openpipe.py @@ -12,7 +12,6 @@ from loguru import logger from pipecat.adapters.schemas.function_schema import FunctionSchema from pipecat.adapters.schemas.tools_schema import ToolsSchema -from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3 from pipecat.audio.vad.silero import SileroVADAnalyzer from pipecat.frames.frames import LLMRunFrame, TTSSpeakFrame from pipecat.pipeline.pipeline import Pipeline @@ -32,8 +31,6 @@ from pipecat.services.openpipe.llm import OpenPipeLLMService from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams -from pipecat.turns.user_stop import TurnAnalyzerUserTurnStopStrategy -from pipecat.turns.user_turn_strategies import UserTurnStrategies load_dotenv(override=True) @@ -129,12 +126,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): context = LLMContext(messages, tools) user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, - user_params=LLMUserAggregatorParams( - user_turn_strategies=UserTurnStrategies( - stop=[TurnAnalyzerUserTurnStopStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3())] - ), - vad_analyzer=SileroVADAnalyzer(), - ), + user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()), ) pipeline = Pipeline( diff --git a/examples/foundational/15-switch-voices.py b/examples/foundational/15-switch-voices.py index c76ff2172..343f9faf1 100644 --- a/examples/foundational/15-switch-voices.py +++ b/examples/foundational/15-switch-voices.py @@ -12,7 +12,6 @@ from loguru import logger from pipecat.adapters.schemas.function_schema import FunctionSchema from pipecat.adapters.schemas.tools_schema import ToolsSchema -from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3 from pipecat.audio.vad.silero import SileroVADAnalyzer from pipecat.frames.frames import Frame, LLMRunFrame from pipecat.pipeline.parallel_pipeline import ParallelPipeline @@ -34,8 +33,6 @@ from pipecat.services.openai.llm import OpenAILLMService from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams -from pipecat.turns.user_stop import TurnAnalyzerUserTurnStopStrategy -from pipecat.turns.user_turn_strategies import UserTurnStrategies load_dotenv(override=True) @@ -141,12 +138,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): context = LLMContext(messages, tools) user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, - user_params=LLMUserAggregatorParams( - user_turn_strategies=UserTurnStrategies( - stop=[TurnAnalyzerUserTurnStopStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3())] - ), - vad_analyzer=SileroVADAnalyzer(), - ), + user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()), ) pipeline = Pipeline( diff --git a/examples/foundational/15a-switch-languages.py b/examples/foundational/15a-switch-languages.py index 6674fb0cf..eb25a0511 100644 --- a/examples/foundational/15a-switch-languages.py +++ b/examples/foundational/15a-switch-languages.py @@ -13,7 +13,6 @@ from loguru import logger from pipecat.adapters.schemas.function_schema import FunctionSchema from pipecat.adapters.schemas.tools_schema import ToolsSchema -from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3 from pipecat.audio.vad.silero import SileroVADAnalyzer from pipecat.frames.frames import Frame, LLMRunFrame from pipecat.pipeline.parallel_pipeline import ParallelPipeline @@ -35,8 +34,6 @@ from pipecat.services.openai.llm import OpenAILLMService from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams -from pipecat.turns.user_stop import TurnAnalyzerUserTurnStopStrategy -from pipecat.turns.user_turn_strategies import UserTurnStrategies load_dotenv(override=True) @@ -131,12 +128,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): context = LLMContext(messages, tools) user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, - user_params=LLMUserAggregatorParams( - user_turn_strategies=UserTurnStrategies( - stop=[TurnAnalyzerUserTurnStopStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3())] - ), - vad_analyzer=SileroVADAnalyzer(), - ), + user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()), ) pipeline = Pipeline( diff --git a/examples/foundational/16-gpu-container-local-bot.py b/examples/foundational/16-gpu-container-local-bot.py index e24c5e984..93bd65200 100644 --- a/examples/foundational/16-gpu-container-local-bot.py +++ b/examples/foundational/16-gpu-container-local-bot.py @@ -10,7 +10,6 @@ import os from dotenv import load_dotenv from loguru import logger -from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3 from pipecat.audio.vad.silero import SileroVADAnalyzer from pipecat.frames.frames import LLMRunFrame from pipecat.pipeline.pipeline import Pipeline @@ -33,8 +32,6 @@ from pipecat.transports.daily.transport import ( DailyParams, ) from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams -from pipecat.turns.user_stop import TurnAnalyzerUserTurnStopStrategy -from pipecat.turns.user_turn_strategies import UserTurnStrategies load_dotenv(override=True) @@ -85,12 +82,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): context = LLMContext(messages) user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, - user_params=LLMUserAggregatorParams( - user_turn_strategies=UserTurnStrategies( - stop=[TurnAnalyzerUserTurnStopStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3())] - ), - vad_analyzer=SileroVADAnalyzer(), - ), + user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()), ) pipeline = Pipeline( diff --git a/examples/foundational/17-detect-user-idle.py b/examples/foundational/17-detect-user-idle.py index cf6763ab8..ae2727c6a 100644 --- a/examples/foundational/17-detect-user-idle.py +++ b/examples/foundational/17-detect-user-idle.py @@ -10,7 +10,6 @@ import os from dotenv import load_dotenv from loguru import logger -from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3 from pipecat.audio.vad.silero import SileroVADAnalyzer from pipecat.frames.frames import ( EndTaskFrame, @@ -35,8 +34,6 @@ from pipecat.services.openai.llm import OpenAILLMService from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams -from pipecat.turns.user_stop import TurnAnalyzerUserTurnStopStrategy -from pipecat.turns.user_turn_strategies import UserTurnStrategies load_dotenv(override=True) @@ -118,9 +115,6 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, user_params=LLMUserAggregatorParams( - user_turn_strategies=UserTurnStrategies( - stop=[TurnAnalyzerUserTurnStopStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3())] - ), user_idle_timeout=5.0, # Detect user idle after 5 seconds vad_analyzer=SileroVADAnalyzer(), ), diff --git a/examples/foundational/20a-persistent-context-openai.py b/examples/foundational/20a-persistent-context-openai.py index 612a602b6..be40add52 100644 --- a/examples/foundational/20a-persistent-context-openai.py +++ b/examples/foundational/20a-persistent-context-openai.py @@ -14,7 +14,6 @@ from loguru import logger from pipecat.adapters.schemas.function_schema import FunctionSchema from pipecat.adapters.schemas.tools_schema import ToolsSchema -from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3 from pipecat.audio.vad.silero import SileroVADAnalyzer from pipecat.frames.frames import LLMRunFrame, TTSSpeakFrame from pipecat.pipeline.pipeline import Pipeline @@ -34,8 +33,6 @@ from pipecat.services.openai.llm import OpenAILLMService from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams -from pipecat.turns.user_stop import TurnAnalyzerUserTurnStopStrategy -from pipecat.turns.user_turn_strategies import UserTurnStrategies load_dotenv(override=True) @@ -198,12 +195,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): context = LLMContext(messages, tools) user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, - user_params=LLMUserAggregatorParams( - user_turn_strategies=UserTurnStrategies( - stop=[TurnAnalyzerUserTurnStopStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3())] - ), - vad_analyzer=SileroVADAnalyzer(), - ), + user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()), ) pipeline = Pipeline( diff --git a/examples/foundational/20c-persistent-context-anthropic.py b/examples/foundational/20c-persistent-context-anthropic.py index f279c595f..d99f4debf 100644 --- a/examples/foundational/20c-persistent-context-anthropic.py +++ b/examples/foundational/20c-persistent-context-anthropic.py @@ -14,7 +14,6 @@ from loguru import logger from pipecat.adapters.schemas.function_schema import FunctionSchema from pipecat.adapters.schemas.tools_schema import ToolsSchema -from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3 from pipecat.audio.vad.silero import SileroVADAnalyzer from pipecat.frames.frames import LLMRunFrame, TTSSpeakFrame from pipecat.pipeline.pipeline import Pipeline @@ -34,8 +33,6 @@ from pipecat.services.llm_service import FunctionCallParams from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams -from pipecat.turns.user_stop import TurnAnalyzerUserTurnStopStrategy -from pipecat.turns.user_turn_strategies import UserTurnStrategies load_dotenv(override=True) @@ -209,12 +206,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): context = LLMContext(messages, tools) user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, - user_params=LLMUserAggregatorParams( - user_turn_strategies=UserTurnStrategies( - stop=[TurnAnalyzerUserTurnStopStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3())] - ), - vad_analyzer=SileroVADAnalyzer(), - ), + user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()), ) pipeline = Pipeline( diff --git a/examples/foundational/20d-persistent-context-gemini.py b/examples/foundational/20d-persistent-context-gemini.py index 3d38d0381..3bcd3c106 100644 --- a/examples/foundational/20d-persistent-context-gemini.py +++ b/examples/foundational/20d-persistent-context-gemini.py @@ -14,7 +14,6 @@ from loguru import logger from pipecat.adapters.schemas.function_schema import FunctionSchema from pipecat.adapters.schemas.tools_schema import ToolsSchema -from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3 from pipecat.audio.vad.silero import SileroVADAnalyzer from pipecat.frames.frames import LLMRunFrame, UserImageRequestFrame from pipecat.pipeline.pipeline import Pipeline @@ -38,8 +37,6 @@ from pipecat.services.google.llm import GoogleLLMService from pipecat.services.llm_service import FunctionCallParams from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams -from pipecat.turns.user_stop import TurnAnalyzerUserTurnStopStrategy -from pipecat.turns.user_turn_strategies import UserTurnStrategies load_dotenv(override=True) @@ -276,12 +273,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): context = LLMContext(messages, tools) user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, - user_params=LLMUserAggregatorParams( - user_turn_strategies=UserTurnStrategies( - stop=[TurnAnalyzerUserTurnStopStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3())] - ), - vad_analyzer=SileroVADAnalyzer(), - ), + user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()), ) pipeline = Pipeline( diff --git a/examples/foundational/21-tavus-transport.py b/examples/foundational/21-tavus-transport.py index f6948849d..925001212 100644 --- a/examples/foundational/21-tavus-transport.py +++ b/examples/foundational/21-tavus-transport.py @@ -12,7 +12,6 @@ import aiohttp from dotenv import load_dotenv from loguru import logger -from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3 from pipecat.audio.vad.silero import SileroVADAnalyzer from pipecat.frames.frames import LLMRunFrame from pipecat.pipeline.pipeline import Pipeline @@ -27,8 +26,6 @@ from pipecat.services.cartesia.tts import CartesiaTTSService from pipecat.services.deepgram.stt import DeepgramSTTService from pipecat.services.google.llm import GoogleLLMService from pipecat.transports.tavus.transport import TavusParams, TavusTransport -from pipecat.turns.user_stop import TurnAnalyzerUserTurnStopStrategy -from pipecat.turns.user_turn_strategies import UserTurnStrategies load_dotenv(override=True) @@ -47,7 +44,6 @@ async def main(): audio_in_enabled=True, audio_out_enabled=True, microphone_out_enabled=False, - vad_analyzer=SileroVADAnalyzer(), ), ) @@ -70,13 +66,7 @@ async def main(): context = LLMContext(messages) user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, - user_params=LLMUserAggregatorParams( - user_turn_strategies=UserTurnStrategies( - stop=[ - TurnAnalyzerUserTurnStopStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3()) - ] - ), - ), + user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()), ) pipeline = Pipeline( diff --git a/examples/foundational/21a-tavus-video-service.py b/examples/foundational/21a-tavus-video-service.py index 9d32754b6..eff214b3a 100644 --- a/examples/foundational/21a-tavus-video-service.py +++ b/examples/foundational/21a-tavus-video-service.py @@ -11,7 +11,6 @@ import aiohttp from dotenv import load_dotenv from loguru import logger -from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3 from pipecat.audio.vad.silero import SileroVADAnalyzer from pipecat.frames.frames import LLMRunFrame from pipecat.pipeline.pipeline import Pipeline @@ -30,8 +29,6 @@ from pipecat.services.google.llm import GoogleLLMService from pipecat.services.tavus.video import TavusVideoService from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams -from pipecat.turns.user_stop import TurnAnalyzerUserTurnStopStrategy -from pipecat.turns.user_turn_strategies import UserTurnStrategies load_dotenv(override=True) @@ -85,14 +82,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): context = LLMContext(messages) user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, - user_params=LLMUserAggregatorParams( - user_turn_strategies=UserTurnStrategies( - stop=[ - TurnAnalyzerUserTurnStopStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3()) - ] - ), - vad_analyzer=SileroVADAnalyzer(), - ), + user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()), ) pipeline = Pipeline( diff --git a/examples/foundational/22-filter-incomplete-turns.py b/examples/foundational/22-filter-incomplete-turns.py index 50f05ff84..b7d094d1e 100644 --- a/examples/foundational/22-filter-incomplete-turns.py +++ b/examples/foundational/22-filter-incomplete-turns.py @@ -21,7 +21,6 @@ import os from dotenv import load_dotenv from loguru import logger -from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3 from pipecat.audio.vad.silero import SileroVADAnalyzer from pipecat.frames.frames import LLMRunFrame from pipecat.pipeline.pipeline import Pipeline @@ -42,8 +41,6 @@ from pipecat.services.openai.llm import OpenAILLMService from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams -from pipecat.turns.user_stop import TurnAnalyzerUserTurnStopStrategy -from pipecat.turns.user_turn_strategies import UserTurnStrategies load_dotenv(override=True) @@ -89,9 +86,6 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, user_params=LLMUserAggregatorParams( - user_turn_strategies=UserTurnStrategies( - stop=[TurnAnalyzerUserTurnStopStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3())] - ), vad_analyzer=SileroVADAnalyzer(), # Enable turn completion filtering - the LLM will output: # ✓ = complete (respond normally) diff --git a/examples/foundational/23-bot-background-sound.py b/examples/foundational/23-bot-background-sound.py index 6254ad169..f2b99af19 100644 --- a/examples/foundational/23-bot-background-sound.py +++ b/examples/foundational/23-bot-background-sound.py @@ -12,7 +12,6 @@ from dotenv import load_dotenv from loguru import logger from pipecat.audio.mixers.soundfile_mixer import SoundfileMixer -from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3 from pipecat.audio.vad.silero import SileroVADAnalyzer from pipecat.frames.frames import LLMRunFrame, MixerEnableFrame, MixerUpdateSettingsFrame from pipecat.pipeline.pipeline import Pipeline @@ -31,8 +30,6 @@ from pipecat.services.openai.llm import OpenAILLMService from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams -from pipecat.turns.user_stop import TurnAnalyzerUserTurnStopStrategy -from pipecat.turns.user_turn_strategies import UserTurnStrategies load_dotenv(override=True) @@ -51,7 +48,6 @@ transport_params = { default_sound="office", volume=2.0, ), - vad_analyzer=SileroVADAnalyzer(), ), "twilio": lambda: FastAPIWebsocketParams( audio_in_enabled=True, @@ -61,7 +57,6 @@ transport_params = { default_sound="office", volume=2.0, ), - vad_analyzer=SileroVADAnalyzer(), ), "webrtc": lambda: TransportParams( audio_in_enabled=True, @@ -71,7 +66,6 @@ transport_params = { default_sound="office", volume=2.0, ), - vad_analyzer=SileroVADAnalyzer(), ), } @@ -96,11 +90,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): context = LLMContext(messages) user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, - user_params=LLMUserAggregatorParams( - user_turn_strategies=UserTurnStrategies( - stop=[TurnAnalyzerUserTurnStopStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3())] - ), - ), + user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()), ) pipeline = Pipeline( diff --git a/examples/foundational/24-user-mute-strategy.py b/examples/foundational/24-user-mute-strategy.py index 7f50c38a5..0a1d2ffde 100644 --- a/examples/foundational/24-user-mute-strategy.py +++ b/examples/foundational/24-user-mute-strategy.py @@ -13,7 +13,6 @@ from loguru import logger from pipecat.adapters.schemas.function_schema import FunctionSchema from pipecat.adapters.schemas.tools_schema import ToolsSchema -from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3 from pipecat.audio.vad.silero import SileroVADAnalyzer from pipecat.frames.frames import LLMRunFrame from pipecat.pipeline.pipeline import Pipeline @@ -37,8 +36,6 @@ from pipecat.turns.user_mute import ( FunctionCallUserMuteStrategy, MuteUntilFirstBotCompleteUserMuteStrategy, ) -from pipecat.turns.user_stop import TurnAnalyzerUserTurnStopStrategy -from pipecat.turns.user_turn_strategies import UserTurnStrategies load_dotenv(override=True) @@ -108,9 +105,6 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, user_params=LLMUserAggregatorParams( - user_turn_strategies=UserTurnStrategies( - stop=[TurnAnalyzerUserTurnStopStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3())] - ), user_mute_strategies=[ MuteUntilFirstBotCompleteUserMuteStrategy(), FunctionCallUserMuteStrategy(), diff --git a/examples/foundational/27-simli-layer.py b/examples/foundational/27-simli-layer.py index 317a4b5ca..7c44d083a 100644 --- a/examples/foundational/27-simli-layer.py +++ b/examples/foundational/27-simli-layer.py @@ -10,7 +10,6 @@ import os from dotenv import load_dotenv from loguru import logger -from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3 from pipecat.audio.vad.silero import SileroVADAnalyzer from pipecat.frames.frames import LLMRunFrame from pipecat.pipeline.pipeline import Pipeline @@ -29,8 +28,6 @@ from pipecat.services.openai.llm import OpenAILLMService from pipecat.services.simli.video import SimliVideoService from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams -from pipecat.turns.user_stop import TurnAnalyzerUserTurnStopStrategy -from pipecat.turns.user_turn_strategies import UserTurnStrategies load_dotenv(override=True) @@ -83,12 +80,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): context = LLMContext(messages) user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, - user_params=LLMUserAggregatorParams( - user_turn_strategies=UserTurnStrategies( - stop=[TurnAnalyzerUserTurnStopStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3())] - ), - vad_analyzer=SileroVADAnalyzer(), - ), + user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()), ) pipeline = Pipeline( diff --git a/examples/foundational/28-user-assistant-turns.py b/examples/foundational/28-user-assistant-turns.py index 70bfc81c5..da38a894e 100644 --- a/examples/foundational/28-user-assistant-turns.py +++ b/examples/foundational/28-user-assistant-turns.py @@ -10,7 +10,6 @@ from typing import Optional from dotenv import load_dotenv from loguru import logger -from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3 from pipecat.audio.vad.silero import SileroVADAnalyzer from pipecat.frames.frames import LLMRunFrame from pipecat.pipeline.pipeline import Pipeline @@ -31,8 +30,6 @@ from pipecat.services.openai.llm import OpenAILLMService from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams -from pipecat.turns.user_stop import TurnAnalyzerUserTurnStopStrategy -from pipecat.turns.user_turn_strategies import UserTurnStrategies load_dotenv(override=True) @@ -140,12 +137,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): context = LLMContext(messages) user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, - user_params=LLMUserAggregatorParams( - user_turn_strategies=UserTurnStrategies( - stop=[TurnAnalyzerUserTurnStopStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3())] - ), - vad_analyzer=SileroVADAnalyzer(), - ), + user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()), ) # Create transcript processor and handler diff --git a/examples/foundational/29-turn-tracking-observer.py b/examples/foundational/29-turn-tracking-observer.py index abff15cd2..321197db2 100644 --- a/examples/foundational/29-turn-tracking-observer.py +++ b/examples/foundational/29-turn-tracking-observer.py @@ -10,7 +10,6 @@ import os from dotenv import load_dotenv from loguru import logger -from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3 from pipecat.audio.vad.silero import SileroVADAnalyzer from pipecat.frames.frames import LLMRunFrame from pipecat.observers.user_bot_latency_observer import UserBotLatencyObserver @@ -30,8 +29,6 @@ from pipecat.services.openai.llm import OpenAILLMService from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams -from pipecat.turns.user_stop import TurnAnalyzerUserTurnStopStrategy -from pipecat.turns.user_turn_strategies import UserTurnStrategies load_dotenv(override=True) @@ -75,12 +72,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): context = LLMContext(messages) user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, - user_params=LLMUserAggregatorParams( - user_turn_strategies=UserTurnStrategies( - stop=[TurnAnalyzerUserTurnStopStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3())] - ), - vad_analyzer=SileroVADAnalyzer(), - ), + user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()), ) pipeline = Pipeline( diff --git a/examples/foundational/30-observer.py b/examples/foundational/30-observer.py index 4951bfe96..02a609061 100644 --- a/examples/foundational/30-observer.py +++ b/examples/foundational/30-observer.py @@ -10,7 +10,6 @@ import os from dotenv import load_dotenv from loguru import logger -from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3 from pipecat.audio.vad.silero import SileroVADAnalyzer from pipecat.frames.frames import ( BotStartedSpeakingFrame, @@ -43,8 +42,6 @@ from pipecat.transports.base_output import BaseOutputTransport from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams -from pipecat.turns.user_stop import TurnAnalyzerUserTurnStopStrategy -from pipecat.turns.user_turn_strategies import UserTurnStrategies load_dotenv(override=True) @@ -122,12 +119,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): context = LLMContext(messages) user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, - user_params=LLMUserAggregatorParams( - user_turn_strategies=UserTurnStrategies( - stop=[TurnAnalyzerUserTurnStopStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3())] - ), - vad_analyzer=SileroVADAnalyzer(), - ), + user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()), ) pipeline = Pipeline( diff --git a/examples/foundational/32-gemini-grounding-metadata.py b/examples/foundational/32-gemini-grounding-metadata.py index cb215bfa9..19844b1fa 100644 --- a/examples/foundational/32-gemini-grounding-metadata.py +++ b/examples/foundational/32-gemini-grounding-metadata.py @@ -12,7 +12,6 @@ from pathlib import Path from dotenv import load_dotenv from loguru import logger -from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3 from pipecat.audio.vad.silero import SileroVADAnalyzer from pipecat.frames.frames import LLMRunFrame from pipecat.observers.base_observer import BaseObserver, FramePushed @@ -33,8 +32,6 @@ from pipecat.services.llm_service import LLMService from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams -from pipecat.turns.user_stop import TurnAnalyzerUserTurnStopStrategy -from pipecat.turns.user_turn_strategies import UserTurnStrategies sys.path.append(str(Path(__file__).parent.parent)) @@ -122,12 +119,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): ) user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, - user_params=LLMUserAggregatorParams( - user_turn_strategies=UserTurnStrategies( - stop=[TurnAnalyzerUserTurnStopStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3())] - ), - vad_analyzer=SileroVADAnalyzer(), - ), + user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()), ) pipeline = Pipeline( diff --git a/examples/foundational/33-gemini-rag.py b/examples/foundational/33-gemini-rag.py index 1200bbbab..ae95ce117 100644 --- a/examples/foundational/33-gemini-rag.py +++ b/examples/foundational/33-gemini-rag.py @@ -57,7 +57,6 @@ from loguru import logger from pipecat.adapters.schemas.function_schema import FunctionSchema from pipecat.adapters.schemas.tools_schema import ToolsSchema -from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3 from pipecat.audio.vad.silero import SileroVADAnalyzer from pipecat.frames.frames import LLMRunFrame from pipecat.pipeline.pipeline import Pipeline @@ -77,8 +76,6 @@ from pipecat.services.llm_service import FunctionCallParams from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams -from pipecat.turns.user_stop import TurnAnalyzerUserTurnStopStrategy -from pipecat.turns.user_turn_strategies import UserTurnStrategies load_dotenv(override=True) @@ -223,12 +220,7 @@ Your response will be turned into speech so use only simple words and punctuatio context = LLMContext(messages, tools) user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, - user_params=LLMUserAggregatorParams( - user_turn_strategies=UserTurnStrategies( - stop=[TurnAnalyzerUserTurnStopStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3())] - ), - vad_analyzer=SileroVADAnalyzer(), - ), + user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()), ) pipeline = Pipeline( diff --git a/examples/foundational/34-audio-recording.py b/examples/foundational/34-audio-recording.py index 9db398ad6..46366379f 100644 --- a/examples/foundational/34-audio-recording.py +++ b/examples/foundational/34-audio-recording.py @@ -50,7 +50,6 @@ import aiofiles from dotenv import load_dotenv from loguru import logger -from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3 from pipecat.audio.vad.silero import SileroVADAnalyzer from pipecat.frames.frames import LLMRunFrame from pipecat.pipeline.pipeline import Pipeline @@ -70,8 +69,6 @@ from pipecat.services.openai.llm import OpenAILLMService from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams -from pipecat.turns.user_stop import TurnAnalyzerUserTurnStopStrategy -from pipecat.turns.user_turn_strategies import UserTurnStrategies load_dotenv(override=True) @@ -133,12 +130,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): context = LLMContext(messages) user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, - user_params=LLMUserAggregatorParams( - user_turn_strategies=UserTurnStrategies( - stop=[TurnAnalyzerUserTurnStopStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3())] - ), - vad_analyzer=SileroVADAnalyzer(), - ), + user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()), ) pipeline = Pipeline( diff --git a/examples/foundational/35-pattern-pair-voice-switching.py b/examples/foundational/35-pattern-pair-voice-switching.py index f56043046..4b269ac3e 100644 --- a/examples/foundational/35-pattern-pair-voice-switching.py +++ b/examples/foundational/35-pattern-pair-voice-switching.py @@ -44,7 +44,6 @@ import os from dotenv import load_dotenv from loguru import logger -from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3 from pipecat.audio.vad.silero import SileroVADAnalyzer from pipecat.frames.frames import LLMRunFrame from pipecat.pipeline.pipeline import Pipeline @@ -63,8 +62,6 @@ from pipecat.services.openai.llm import OpenAILLMService from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams -from pipecat.turns.user_stop import TurnAnalyzerUserTurnStopStrategy -from pipecat.turns.user_turn_strategies import UserTurnStrategies from pipecat.utils.text.pattern_pair_aggregator import ( MatchAction, PatternMatch, @@ -198,12 +195,7 @@ Remember: Use narrator voice for EVERYTHING except the actual quoted dialogue."" context = LLMContext(messages) user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, - user_params=LLMUserAggregatorParams( - user_turn_strategies=UserTurnStrategies( - stop=[TurnAnalyzerUserTurnStopStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3())] - ), - vad_analyzer=SileroVADAnalyzer(), - ), + user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()), ) # Create pipeline diff --git a/examples/foundational/36-user-email-gathering.py b/examples/foundational/36-user-email-gathering.py index 22b878121..969a63efe 100644 --- a/examples/foundational/36-user-email-gathering.py +++ b/examples/foundational/36-user-email-gathering.py @@ -12,7 +12,6 @@ from loguru import logger from pipecat.adapters.schemas.function_schema import FunctionSchema from pipecat.adapters.schemas.tools_schema import ToolsSchema -from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3 from pipecat.audio.vad.silero import SileroVADAnalyzer from pipecat.frames.frames import LLMRunFrame from pipecat.pipeline.pipeline import Pipeline @@ -32,8 +31,6 @@ from pipecat.services.openai.llm import OpenAILLMService from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams -from pipecat.turns.user_stop import TurnAnalyzerUserTurnStopStrategy -from pipecat.turns.user_turn_strategies import UserTurnStrategies load_dotenv(override=True) @@ -114,12 +111,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): context = LLMContext(messages, tools) user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, - user_params=LLMUserAggregatorParams( - user_turn_strategies=UserTurnStrategies( - stop=[TurnAnalyzerUserTurnStopStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3())] - ), - vad_analyzer=SileroVADAnalyzer(), - ), + user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()), ) pipeline = Pipeline( diff --git a/examples/foundational/37-mem0.py b/examples/foundational/37-mem0.py index 214f5a6d7..423695e9c 100644 --- a/examples/foundational/37-mem0.py +++ b/examples/foundational/37-mem0.py @@ -47,7 +47,6 @@ from typing import Union from dotenv import load_dotenv from loguru import logger -from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3 from pipecat.audio.vad.silero import SileroVADAnalyzer from pipecat.frames.frames import LLMRunFrame from pipecat.pipeline.pipeline import Pipeline @@ -67,8 +66,6 @@ from pipecat.services.openai.llm import OpenAILLMService from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams -from pipecat.turns.user_stop import TurnAnalyzerUserTurnStopStrategy -from pipecat.turns.user_turn_strategies import UserTurnStrategies load_dotenv(override=True) @@ -243,12 +240,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): context = LLMContext(messages) user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, - user_params=LLMUserAggregatorParams( - user_turn_strategies=UserTurnStrategies( - stop=[TurnAnalyzerUserTurnStopStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3())] - ), - vad_analyzer=SileroVADAnalyzer(), - ), + user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()), ) pipeline = Pipeline( diff --git a/examples/foundational/38b-smart-turn-local.py b/examples/foundational/38b-smart-turn-local.py index 1eaf2e9c4..2872a0e76 100644 --- a/examples/foundational/38b-smart-turn-local.py +++ b/examples/foundational/38b-smart-turn-local.py @@ -10,7 +10,6 @@ import os from dotenv import load_dotenv from loguru import logger -from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3 from pipecat.audio.vad.silero import SileroVADAnalyzer from pipecat.frames.frames import LLMRunFrame from pipecat.pipeline.pipeline import Pipeline @@ -29,8 +28,6 @@ from pipecat.services.openai.llm import OpenAILLMService from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams -from pipecat.turns.user_stop import TurnAnalyzerUserTurnStopStrategy -from pipecat.turns.user_turn_strategies import UserTurnStrategies load_dotenv(override=True) @@ -74,12 +71,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): context = LLMContext(messages) user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, - user_params=LLMUserAggregatorParams( - user_turn_strategies=UserTurnStrategies( - stop=[TurnAnalyzerUserTurnStopStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3())] - ), - vad_analyzer=SileroVADAnalyzer(), - ), + user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()), ) pipeline = Pipeline( diff --git a/examples/foundational/39-mcp-stdio.py b/examples/foundational/39-mcp-stdio.py index ac39d4b59..2daf21626 100644 --- a/examples/foundational/39-mcp-stdio.py +++ b/examples/foundational/39-mcp-stdio.py @@ -17,7 +17,6 @@ from loguru import logger from mcp import StdioServerParameters from PIL import Image -from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3 from pipecat.audio.vad.silero import SileroVADAnalyzer from pipecat.frames.frames import ( Frame, @@ -42,8 +41,6 @@ from pipecat.services.deepgram.stt import DeepgramSTTService from pipecat.services.mcp_service import MCPClient from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams -from pipecat.turns.user_stop import TurnAnalyzerUserTurnStopStrategy -from pipecat.turns.user_turn_strategies import UserTurnStrategies load_dotenv(override=True) @@ -190,14 +187,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): context = LLMContext(messages, tools) user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, - user_params=LLMUserAggregatorParams( - user_turn_strategies=UserTurnStrategies( - stop=[ - TurnAnalyzerUserTurnStopStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3()) - ] - ), - vad_analyzer=SileroVADAnalyzer(), - ), + user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()), ) pipeline = Pipeline( diff --git a/examples/foundational/39a-mcp-streamable-http.py b/examples/foundational/39a-mcp-streamable-http.py index 828c22d1f..2af2ba9cb 100644 --- a/examples/foundational/39a-mcp-streamable-http.py +++ b/examples/foundational/39a-mcp-streamable-http.py @@ -11,7 +11,6 @@ from dotenv import load_dotenv from loguru import logger from mcp.client.session_group import StreamableHttpParameters -from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3 from pipecat.audio.vad.silero import SileroVADAnalyzer from pipecat.frames.frames import LLMRunFrame from pipecat.pipeline.pipeline import Pipeline @@ -31,8 +30,6 @@ from pipecat.services.mcp_service import MCPClient from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams -from pipecat.turns.user_stop import TurnAnalyzerUserTurnStopStrategy -from pipecat.turns.user_turn_strategies import UserTurnStrategies load_dotenv(override=True) @@ -102,12 +99,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): context = LLMContext(messages, tools) user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, - user_params=LLMUserAggregatorParams( - user_turn_strategies=UserTurnStrategies( - stop=[TurnAnalyzerUserTurnStopStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3())] - ), - vad_analyzer=SileroVADAnalyzer(), - ), + user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()), ) pipeline = Pipeline( diff --git a/examples/foundational/39b-mcp-streamable-http-gemini-live.py b/examples/foundational/39b-mcp-streamable-http-gemini-live.py index d124f30ac..c4c427bd8 100644 --- a/examples/foundational/39b-mcp-streamable-http-gemini-live.py +++ b/examples/foundational/39b-mcp-streamable-http-gemini-live.py @@ -11,7 +11,6 @@ from dotenv import load_dotenv from loguru import logger from mcp.client.session_group import StreamableHttpParameters -from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3 from pipecat.audio.vad.silero import SileroVADAnalyzer from pipecat.frames.frames import LLMRunFrame from pipecat.pipeline.pipeline import Pipeline @@ -31,8 +30,6 @@ from pipecat.services.mcp_service import MCPClient from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams -from pipecat.turns.user_stop import TurnAnalyzerUserTurnStopStrategy -from pipecat.turns.user_turn_strategies import UserTurnStrategies load_dotenv(override=True) @@ -106,12 +103,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): context = LLMContext([{"role": "user", "content": "Please introduce yourself."}]) user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, - user_params=LLMUserAggregatorParams( - user_turn_strategies=UserTurnStrategies( - stop=[TurnAnalyzerUserTurnStopStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3())] - ), - vad_analyzer=SileroVADAnalyzer(), - ), + user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()), ) pipeline = Pipeline( diff --git a/examples/foundational/39c-multiple-mcp.py b/examples/foundational/39c-multiple-mcp.py index e06a5888b..5f662cdb8 100644 --- a/examples/foundational/39c-multiple-mcp.py +++ b/examples/foundational/39c-multiple-mcp.py @@ -19,7 +19,6 @@ from mcp.client.session_group import StreamableHttpParameters from PIL import Image from pipecat.adapters.schemas.tools_schema import ToolsSchema -from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3 from pipecat.audio.vad.silero import SileroVADAnalyzer from pipecat.frames.frames import ( Frame, @@ -44,8 +43,6 @@ from pipecat.services.deepgram.stt import DeepgramSTTService from pipecat.services.mcp_service import MCPClient from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams -from pipecat.turns.user_stop import TurnAnalyzerUserTurnStopStrategy -from pipecat.turns.user_turn_strategies import UserTurnStrategies load_dotenv(override=True) @@ -190,14 +187,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): context = LLMContext(messages, all_tools) user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, - user_params=LLMUserAggregatorParams( - user_turn_strategies=UserTurnStrategies( - stop=[ - TurnAnalyzerUserTurnStopStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3()) - ] - ), - vad_analyzer=SileroVADAnalyzer(), - ), + user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()), ) mcp_image_processor = UrlToImageProcessor(aiohttp_session=session) diff --git a/examples/foundational/42-interruption-config.py b/examples/foundational/42-interruption-config.py index a45fc14a5..1310af908 100644 --- a/examples/foundational/42-interruption-config.py +++ b/examples/foundational/42-interruption-config.py @@ -9,7 +9,6 @@ import os from dotenv import load_dotenv from loguru import logger -from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3 from pipecat.audio.vad.silero import SileroVADAnalyzer from pipecat.frames.frames import LLMRunFrame from pipecat.observers.loggers.transcription_log_observer import TranscriptionLogObserver @@ -30,7 +29,6 @@ from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams from pipecat.turns.user_start import MinWordsUserTurnStartStrategy -from pipecat.turns.user_stop import TurnAnalyzerUserTurnStopStrategy from pipecat.turns.user_turn_strategies import UserTurnStrategies load_dotenv(override=True) @@ -79,7 +77,6 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): user_params=LLMUserAggregatorParams( user_turn_strategies=UserTurnStrategies( start=[MinWordsUserTurnStartStrategy(min_words=3)], - stop=[TurnAnalyzerUserTurnStopStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3())], ), vad_analyzer=SileroVADAnalyzer(), ), diff --git a/examples/foundational/43-heygen-transport.py b/examples/foundational/43-heygen-transport.py index d5059b55e..5cc56644b 100644 --- a/examples/foundational/43-heygen-transport.py +++ b/examples/foundational/43-heygen-transport.py @@ -12,7 +12,6 @@ import aiohttp from dotenv import load_dotenv from loguru import logger -from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3 from pipecat.audio.vad.silero import SileroVADAnalyzer from pipecat.frames.frames import LLMRunFrame from pipecat.pipeline.pipeline import Pipeline @@ -27,8 +26,6 @@ from pipecat.services.cartesia.tts import CartesiaTTSService from pipecat.services.deepgram.stt import DeepgramSTTService from pipecat.services.google.llm import GoogleLLMService from pipecat.transports.heygen.transport import HeyGenParams, HeyGenTransport, ServiceType -from pipecat.turns.user_stop import TurnAnalyzerUserTurnStopStrategy -from pipecat.turns.user_turn_strategies import UserTurnStrategies load_dotenv(override=True) @@ -45,7 +42,6 @@ async def main(): params=HeyGenParams( audio_in_enabled=True, audio_out_enabled=True, - vad_analyzer=SileroVADAnalyzer(), ), ) @@ -68,13 +64,7 @@ async def main(): context = LLMContext(messages) user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, - user_params=LLMUserAggregatorParams( - user_turn_strategies=UserTurnStrategies( - stop=[ - TurnAnalyzerUserTurnStopStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3()) - ] - ), - ), + user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()), ) pipeline = Pipeline( diff --git a/examples/foundational/43a-heygen-video-service.py b/examples/foundational/43a-heygen-video-service.py index dd38d7084..bae88e2b5 100644 --- a/examples/foundational/43a-heygen-video-service.py +++ b/examples/foundational/43a-heygen-video-service.py @@ -10,7 +10,6 @@ import aiohttp from dotenv import load_dotenv from loguru import logger -from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3 from pipecat.audio.vad.silero import SileroVADAnalyzer from pipecat.frames.frames import LLMRunFrame from pipecat.pipeline.pipeline import Pipeline @@ -30,8 +29,6 @@ from pipecat.services.heygen.client import ServiceType from pipecat.services.heygen.video import HeyGenVideoService from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams, DailyTransport -from pipecat.turns.user_stop import TurnAnalyzerUserTurnStopStrategy -from pipecat.turns.user_turn_strategies import UserTurnStrategies load_dotenv(override=True) @@ -86,14 +83,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): context = LLMContext(messages) user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, - user_params=LLMUserAggregatorParams( - user_turn_strategies=UserTurnStrategies( - stop=[ - TurnAnalyzerUserTurnStopStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3()) - ] - ), - vad_analyzer=SileroVADAnalyzer(), - ), + user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()), ) pipeline = Pipeline( diff --git a/examples/foundational/44-voicemail-detection.py b/examples/foundational/44-voicemail-detection.py index 76fd95d61..175cef695 100644 --- a/examples/foundational/44-voicemail-detection.py +++ b/examples/foundational/44-voicemail-detection.py @@ -9,7 +9,6 @@ import os from dotenv import load_dotenv from loguru import logger -from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3 from pipecat.audio.vad.silero import SileroVADAnalyzer from pipecat.extensions.voicemail.voicemail_detector import VoicemailDetector from pipecat.frames.frames import TTSSpeakFrame @@ -29,8 +28,6 @@ from pipecat.services.openai.llm import OpenAILLMService from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams -from pipecat.turns.user_stop import TurnAnalyzerUserTurnStopStrategy -from pipecat.turns.user_turn_strategies import UserTurnStrategies load_dotenv(override=True) @@ -77,12 +74,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): context = LLMContext(messages) user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, - user_params=LLMUserAggregatorParams( - user_turn_strategies=UserTurnStrategies( - stop=[TurnAnalyzerUserTurnStopStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3())] - ), - vad_analyzer=SileroVADAnalyzer(), - ), + user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()), ) pipeline = Pipeline( diff --git a/examples/foundational/45-before-and-after-events.py b/examples/foundational/45-before-and-after-events.py index ab02d3fd4..52dfbddaf 100644 --- a/examples/foundational/45-before-and-after-events.py +++ b/examples/foundational/45-before-and-after-events.py @@ -10,7 +10,6 @@ from dataclasses import dataclass from dotenv import load_dotenv from loguru import logger -from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3 from pipecat.audio.vad.silero import SileroVADAnalyzer from pipecat.frames.frames import DataFrame, LLMRunFrame from pipecat.pipeline.pipeline import Pipeline @@ -29,8 +28,6 @@ from pipecat.services.openai.llm import OpenAILLMService from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams -from pipecat.turns.user_stop import TurnAnalyzerUserTurnStopStrategy -from pipecat.turns.user_turn_strategies import UserTurnStrategies load_dotenv(override=True) @@ -85,12 +82,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): context = LLMContext(messages) user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, - user_params=LLMUserAggregatorParams( - user_turn_strategies=UserTurnStrategies( - stop=[TurnAnalyzerUserTurnStopStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3())] - ), - vad_analyzer=SileroVADAnalyzer(), - ), + user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()), ) pipeline = Pipeline( diff --git a/examples/foundational/46-video-processing.py b/examples/foundational/46-video-processing.py index dea8ce30e..0551728a8 100644 --- a/examples/foundational/46-video-processing.py +++ b/examples/foundational/46-video-processing.py @@ -10,7 +10,6 @@ import numpy as np from dotenv import load_dotenv from loguru import logger -from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3 from pipecat.audio.vad.silero import SileroVADAnalyzer from pipecat.frames.frames import Frame, InputImageRawFrame, LLMRunFrame, OutputImageRawFrame from pipecat.pipeline.pipeline import Pipeline @@ -27,8 +26,6 @@ from pipecat.runner.utils import create_transport from pipecat.services.google.gemini_live.llm import GeminiLiveLLMService from pipecat.transports.base_transport import TransportParams from pipecat.transports.daily.transport import DailyParams, DailyTransport -from pipecat.turns.user_stop import TurnAnalyzerUserTurnStopStrategy -from pipecat.turns.user_turn_strategies import UserTurnStrategies load_dotenv(override=True) @@ -115,12 +112,7 @@ async def run_bot(pipecat_transport): context = LLMContext(messages) user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, - user_params=LLMUserAggregatorParams( - user_turn_strategies=UserTurnStrategies( - stop=[TurnAnalyzerUserTurnStopStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3())] - ), - vad_analyzer=SileroVADAnalyzer(), - ), + user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()), ) pipeline = Pipeline( diff --git a/examples/foundational/47-sentry-metrics.py b/examples/foundational/47-sentry-metrics.py index 013337f59..e0649998d 100644 --- a/examples/foundational/47-sentry-metrics.py +++ b/examples/foundational/47-sentry-metrics.py @@ -10,7 +10,6 @@ import sentry_sdk from dotenv import load_dotenv from loguru import logger -from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3 from pipecat.audio.vad.silero import SileroVADAnalyzer from pipecat.frames.frames import LLMRunFrame from pipecat.pipeline.pipeline import Pipeline @@ -30,8 +29,6 @@ from pipecat.services.openai.llm import OpenAILLMService from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams -from pipecat.turns.user_stop import TurnAnalyzerUserTurnStopStrategy -from pipecat.turns.user_turn_strategies import UserTurnStrategies load_dotenv(override=True) @@ -88,12 +85,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): context = LLMContext(messages) user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, - user_params=LLMUserAggregatorParams( - user_turn_strategies=UserTurnStrategies( - stop=[TurnAnalyzerUserTurnStopStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3())] - ), - vad_analyzer=SileroVADAnalyzer(), - ), + user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()), ) pipeline = Pipeline( diff --git a/examples/foundational/48-service-switcher.py b/examples/foundational/48-service-switcher.py index eb75791ea..4aaafa508 100644 --- a/examples/foundational/48-service-switcher.py +++ b/examples/foundational/48-service-switcher.py @@ -12,7 +12,6 @@ from loguru import logger from pipecat.adapters.schemas.function_schema import FunctionSchema from pipecat.adapters.schemas.tools_schema import ToolsSchema -from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3 from pipecat.audio.vad.silero import SileroVADAnalyzer from pipecat.frames.frames import LLMRunFrame, ManuallySwitchServiceFrame from pipecat.pipeline.llm_switcher import LLMSwitcher @@ -37,8 +36,6 @@ from pipecat.services.openai.llm import OpenAILLMService from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams -from pipecat.turns.user_stop import TurnAnalyzerUserTurnStopStrategy -from pipecat.turns.user_turn_strategies import UserTurnStrategies load_dotenv(override=True) @@ -133,12 +130,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): context = LLMContext(messages, tools) user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, - user_params=LLMUserAggregatorParams( - user_turn_strategies=UserTurnStrategies( - stop=[TurnAnalyzerUserTurnStopStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3())] - ), - vad_analyzer=SileroVADAnalyzer(), - ), + user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()), ) pipeline = Pipeline( diff --git a/examples/foundational/49a-thinking-anthropic.py b/examples/foundational/49a-thinking-anthropic.py index 6a14b43f2..97e82666b 100644 --- a/examples/foundational/49a-thinking-anthropic.py +++ b/examples/foundational/49a-thinking-anthropic.py @@ -9,7 +9,6 @@ import os from dotenv import load_dotenv from loguru import logger -from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3 from pipecat.audio.vad.silero import SileroVADAnalyzer from pipecat.frames.frames import LLMRunFrame from pipecat.pipeline.pipeline import Pipeline @@ -29,8 +28,6 @@ from pipecat.services.deepgram.stt import DeepgramSTTService from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams -from pipecat.turns.user_stop import TurnAnalyzerUserTurnStopStrategy -from pipecat.turns.user_turn_strategies import UserTurnStrategies load_dotenv(override=True) @@ -79,12 +76,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): context = LLMContext(messages) user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, - user_params=LLMUserAggregatorParams( - user_turn_strategies=UserTurnStrategies( - stop=[TurnAnalyzerUserTurnStopStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3())] - ), - vad_analyzer=SileroVADAnalyzer(), - ), + user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()), ) pipeline = Pipeline( diff --git a/examples/foundational/49b-thinking-google.py b/examples/foundational/49b-thinking-google.py index 75c60d4b3..855347729 100644 --- a/examples/foundational/49b-thinking-google.py +++ b/examples/foundational/49b-thinking-google.py @@ -9,7 +9,6 @@ import os from dotenv import load_dotenv from loguru import logger -from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3 from pipecat.audio.vad.silero import SileroVADAnalyzer from pipecat.frames.frames import LLMRunFrame from pipecat.pipeline.pipeline import Pipeline @@ -29,8 +28,6 @@ from pipecat.services.google.llm import GoogleLLMService from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams -from pipecat.turns.user_stop import TurnAnalyzerUserTurnStopStrategy -from pipecat.turns.user_turn_strategies import UserTurnStrategies load_dotenv(override=True) @@ -84,12 +81,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): context = LLMContext(messages) user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, - user_params=LLMUserAggregatorParams( - user_turn_strategies=UserTurnStrategies( - stop=[TurnAnalyzerUserTurnStopStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3())] - ), - vad_analyzer=SileroVADAnalyzer(), - ), + user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()), ) pipeline = Pipeline( diff --git a/examples/foundational/49c-thinking-functions-anthropic.py b/examples/foundational/49c-thinking-functions-anthropic.py index de382a9ad..6b16a67e1 100644 --- a/examples/foundational/49c-thinking-functions-anthropic.py +++ b/examples/foundational/49c-thinking-functions-anthropic.py @@ -10,7 +10,6 @@ from dotenv import load_dotenv from loguru import logger from pipecat.adapters.schemas.tools_schema import ToolsSchema -from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3 from pipecat.audio.vad.silero import SileroVADAnalyzer from pipecat.frames.frames import LLMRunFrame from pipecat.pipeline.pipeline import Pipeline @@ -31,8 +30,6 @@ from pipecat.services.llm_service import FunctionCallParams from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams -from pipecat.turns.user_stop import TurnAnalyzerUserTurnStopStrategy -from pipecat.turns.user_turn_strategies import UserTurnStrategies load_dotenv(override=True) @@ -105,12 +102,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): context = LLMContext(messages, tools) user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, - user_params=LLMUserAggregatorParams( - user_turn_strategies=UserTurnStrategies( - stop=[TurnAnalyzerUserTurnStopStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3())] - ), - vad_analyzer=SileroVADAnalyzer(), - ), + user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()), ) pipeline = Pipeline( diff --git a/examples/foundational/49d-thinking-functions-google.py b/examples/foundational/49d-thinking-functions-google.py index 4cea483c0..a377bf5ef 100644 --- a/examples/foundational/49d-thinking-functions-google.py +++ b/examples/foundational/49d-thinking-functions-google.py @@ -10,7 +10,6 @@ from dotenv import load_dotenv from loguru import logger from pipecat.adapters.schemas.tools_schema import ToolsSchema -from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3 from pipecat.audio.vad.silero import SileroVADAnalyzer from pipecat.frames.frames import LLMRunFrame from pipecat.pipeline.pipeline import Pipeline @@ -31,8 +30,6 @@ from pipecat.services.llm_service import FunctionCallParams from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams -from pipecat.turns.user_stop import TurnAnalyzerUserTurnStopStrategy -from pipecat.turns.user_turn_strategies import UserTurnStrategies load_dotenv(override=True) @@ -110,12 +107,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): context = LLMContext(messages, tools) user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, - user_params=LLMUserAggregatorParams( - user_turn_strategies=UserTurnStrategies( - stop=[TurnAnalyzerUserTurnStopStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3())] - ), - vad_analyzer=SileroVADAnalyzer(), - ), + user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()), ) pipeline = Pipeline( diff --git a/examples/foundational/52-live-translation.py b/examples/foundational/52-live-translation.py index 18195ef1d..30583c1b8 100644 --- a/examples/foundational/52-live-translation.py +++ b/examples/foundational/52-live-translation.py @@ -10,7 +10,6 @@ import os from dotenv import load_dotenv from loguru import logger -from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3 from pipecat.audio.vad.silero import SileroVADAnalyzer from pipecat.pipeline.pipeline import Pipeline from pipecat.pipeline.runner import PipelineRunner @@ -29,7 +28,6 @@ from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams from pipecat.turns.user_start import TranscriptionUserTurnStartStrategy -from pipecat.turns.user_stop import TurnAnalyzerUserTurnStopStrategy from pipecat.turns.user_turn_strategies import UserTurnStrategies load_dotenv(override=True) @@ -83,7 +81,6 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): user_params=LLMUserAggregatorParams( user_turn_strategies=UserTurnStrategies( start=[TranscriptionUserTurnStartStrategy(enable_interruptions=False)], - stop=[TurnAnalyzerUserTurnStopStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3())], ), vad_analyzer=SileroVADAnalyzer(), ), diff --git a/examples/foundational/53-concurrent-llm-evaluation.py b/examples/foundational/53-concurrent-llm-evaluation.py index 9e0fa73ad..9fb44a44f 100644 --- a/examples/foundational/53-concurrent-llm-evaluation.py +++ b/examples/foundational/53-concurrent-llm-evaluation.py @@ -10,7 +10,6 @@ import os from dotenv import load_dotenv from loguru import logger -from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3 from pipecat.audio.vad.silero import SileroVADAnalyzer from pipecat.frames.frames import LLMRunFrame from pipecat.pipeline.parallel_pipeline import ParallelPipeline @@ -32,9 +31,8 @@ from pipecat.services.openai.llm import OpenAILLMService from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams -from pipecat.turns.user_stop import TurnAnalyzerUserTurnStopStrategy from pipecat.turns.user_turn_processor import UserTurnProcessor -from pipecat.turns.user_turn_strategies import ExternalUserTurnStrategies, UserTurnStrategies +from pipecat.turns.user_turn_strategies import ExternalUserTurnStrategies load_dotenv(override=True) @@ -100,11 +98,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): # UserStartedSpeakingFrame and UserStoppedSpeakingFrame as well as # interruptions. This can be used in advanced cases when there are multiple # aggregators in the pipeline. - user_turn_processor = UserTurnProcessor( - user_turn_strategies=UserTurnStrategies( - stop=[TurnAnalyzerUserTurnStopStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3())] - ), - ) + user_turn_processor = UserTurnProcessor() # We use external user turn strategies for both aggregators since the turn # management is done by the common UserTurnProcessor. From 3867bc63029565678959820f90d7186cb6e58154 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Aleix=20Conchillo=20Flaqu=C3=A9?= Date: Mon, 9 Feb 2026 14:33:08 -0800 Subject: [PATCH 0411/1060] LLMUserAggregator: update turn analyzer warning --- .../aggregators/llm_response_universal.py | 20 +------------------ 1 file changed, 1 insertion(+), 19 deletions(-) diff --git a/src/pipecat/processors/aggregators/llm_response_universal.py b/src/pipecat/processors/aggregators/llm_response_universal.py index 9cc3dabd8..3b162d48f 100644 --- a/src/pipecat/processors/aggregators/llm_response_universal.py +++ b/src/pipecat/processors/aggregators/llm_response_universal.py @@ -598,25 +598,7 @@ class LLMUserAggregator(LLMContextAggregator): if not frame.turn_params: return - logger.warning( - f"{self}: `turn_analyzer` in base input transport is deprecated. " - "Use `LLMUserAggregator`'s new `user_turn_strategies` parameter with " - "`TurnAnalyzerUserTurnStopStrategy` instead:\n" - "\n" - " context_aggregator = LLMContextAggregatorPair(\n" - " context,\n" - " user_params=LLMUserAggregatorParams(\n" - " ...,\n" - " user_turn_strategies=UserTurnStrategies(\n" - " stop=[\n" - " TurnAnalyzerUserTurnStopStrategy(\n" - " turn_analyzer=LocalSmartTurnAnalyzerV3(params=SmartTurnParams())\n" - " )\n" - " ],\n" - " )\n" - " ),\n" - " )" - ) + logger.warning(f"{self}: `turn_analyzer` in base input transport is deprecated.") await self._user_turn_controller.update_strategies(ExternalUserTurnStrategies()) From ca224834b20af8619bbfd5b89d8bd44813ee1a33 Mon Sep 17 00:00:00 2001 From: Mark Backman Date: Mon, 9 Feb 2026 18:11:12 -0500 Subject: [PATCH 0412/1060] Add observers, error handling, task management, and testing to CLAUDE.md --- CLAUDE.md | 11 +++++++++++ 1 file changed, 11 insertions(+) diff --git a/CLAUDE.md b/CLAUDE.md index d7ef2619c..de5efec0f 100644 --- a/CLAUDE.md +++ b/CLAUDE.md @@ -63,6 +63,8 @@ Transport Input → Pipeline Source → [Processor1] → [Processor2] → ... - **RTVI** (`src/pipecat/processors/frameworks/rtvi.py`): Real-Time Voice Interface protocol bridging clients and the pipeline. `RTVIProcessor` handles incoming client messages (text input, audio, function call results). `RTVIObserver` converts pipeline frames to outgoing messages: user/bot speaking events, transcriptions, LLM/TTS lifecycle, function calls, metrics, and audio levels. +- **Observers** (`src/pipecat/observers/`): Monitor frame flow without modifying the pipeline. Passed to `PipelineTask` via the `observers` parameter. Implement `on_process_frame()` and `on_push_frame()` callbacks. + ### Important Patterns - **Context Aggregation**: `LLMContext` accumulates messages for LLM calls; `UserResponse` aggregates user input @@ -78,6 +80,10 @@ Transport Input → Pipeline Source → [Processor1] → [Processor2] → ... - **Events**: Most classes in Pipecat have `BaseObject` as the very base class. `BaseObject` has support for events. Events can run in the background in an async task (default) or synchronously (`sync=True`) if we want immediate action. Synchronous event handlers need to exectue fast. +- **Async Task Management**: Always use `self.create_task(coroutine, name)` instead of raw `asyncio.create_task()`. The `TaskManager` automatically tracks tasks and cleans them up on processor shutdown. Use `await self.cancel_task(task, timeout)` for cancellation. + +- **Error Handling**: Use `await self.push_error(msg, exception, fatal)` to push errors upstream. Services should use `fatal=False` (the default) so application code can handle errors and take action (e.g. switch to another service). + ### Key Directories | Directory | Purpose | @@ -88,6 +94,7 @@ Transport Input → Pipeline Source → [Processor1] → [Processor2] → ... | `src/pipecat/services/` | AI service integrations (60+ providers) | | `src/pipecat/transports/` | Transport layer (Daily, LiveKit, WebSocket, Local) | | `src/pipecat/serializers/`| Frame serialization for WebSocket protocols | +| `src/pipecat/observers/` | Pipeline observers for monitoring frame flow | | `src/pipecat/audio/` | VAD, filters, mixers, turn detection, DTMF | | `src/pipecat/turns/` | User turn management | @@ -138,6 +145,10 @@ When adding a new service: 6. Add metrics tracking via `MetricsData` if relevant 7. Follow the pattern of existing services in `src/pipecat/services/` +## Testing + +Test utilities live in `src/pipecat/tests/utils.py`. Use `run_test()` to send frames through a pipeline and assert expected output frames in each direction. Use `SleepFrame(sleep=N)` to add delays between frames. + ## Pull Requests After creating a PR, use `/changelog ` to generate the changelog file and `/pr-description ` to update the PR description. From 946f0f4e77f89c00654756ed95f7536086ca2331 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Aleix=20Conchillo=20Flaqu=C3=A9?= Date: Mon, 9 Feb 2026 16:19:11 -0800 Subject: [PATCH 0413/1060] CLAUDE.md: add pipeline task and pipeline runner --- CLAUDE.md | 12 ++++++++---- 1 file changed, 8 insertions(+), 4 deletions(-) diff --git a/CLAUDE.md b/CLAUDE.md index de5efec0f..cf4c5baec 100644 --- a/CLAUDE.md +++ b/CLAUDE.md @@ -42,7 +42,7 @@ uv lock && uv sync All data flows as **Frame** objects through a pipeline of **FrameProcessors**: ``` -Transport Input → Pipeline Source → [Processor1] → [Processor2] → ... → Pipeline Sink → Transport Output +[Processor1] → [Processor2] → ... → [ProcessorN] ``` **Key components:** @@ -55,7 +55,11 @@ Transport Input → Pipeline Source → [Processor1] → [Processor2] → ... - **ParallelPipeline** (`src/pipecat/pipeline/parallel_pipeline.py`): Runs multiple pipelines in parallel. -- **Transports** (`src/pipecat/transports/`): External I/O layer (Daily WebRTC, LiveKit WebRTC, WebSocket, Local). Abstract interface via `BaseTransport`. +- **Transports** (`src/pipecat/transports/`): Transports are frame processors used for external I/O layer (Daily WebRTC, LiveKit WebRTC, WebSocket, Local). Abstract interface via `BaseTransport`, `BaseInputTransport` and `BaseOutputTransport`. + +- **Pipeline Task (`src/pipecat/pipeline/task.py`)**: Runs and manages a pipeline. Pipeline tasks send the first frame, `StartFrame`, to the pipeline in order for processors to know they can start processing and pushing frames. Pipeline tasks internally create a pipeline with two additional processors, a source processor before the user-defined pipeline and a sink processor at the end. Those are used for multiple things: error handling, pipeline task level events, heartbeat monitoring, etc. + +- **Pipeline Runner (`src/pipecat/pipeline/runner.py`)**: High-level entry point for executing pipeline tasks. Handles signal management (SIGINT/SIGTERM) for graceful shutdown and optional garbage collection. Run a single pipeline task with `await runner.run(task)` or multiple concurrently with `await asyncio.gather(runner.run(task1), runner.run(task2))`. - **Services** (`src/pipecat/services/`): 60+ AI provider integrations (STT, TTS, LLM, etc.). Extend base classes: `AIService`, `LLMService`, `STTService`, `TTSService`, `VisionService`. @@ -78,7 +82,7 @@ Transport Input → Pipeline Source → [Processor1] → [Processor2] → ... - **Uninterruptible Frames**: These are frames that will not be removed from internal queues even if there's an interruption. For example, `EndFrame` and `StopFrame`. -- **Events**: Most classes in Pipecat have `BaseObject` as the very base class. `BaseObject` has support for events. Events can run in the background in an async task (default) or synchronously (`sync=True`) if we want immediate action. Synchronous event handlers need to exectue fast. +- **Events**: Most classes in Pipecat have `BaseObject` as the very base class. `BaseObject` has support for events. Events can run in the background in an async task (default) or synchronously (`sync=True`) if we want immediate action. Synchronous event handlers need to execute fast. - **Async Task Management**: Always use `self.create_task(coroutine, name)` instead of raw `asyncio.create_task()`. The `TaskManager` automatically tracks tasks and cleans them up on processor shutdown. Use `await self.cancel_task(task, timeout)` for cancellation. @@ -147,7 +151,7 @@ When adding a new service: ## Testing -Test utilities live in `src/pipecat/tests/utils.py`. Use `run_test()` to send frames through a pipeline and assert expected output frames in each direction. Use `SleepFrame(sleep=N)` to add delays between frames. +Test utilities live in `src/pipecat/tests/utils.py`. Use `run_test()` to send frames through a pipeline and assert expected output frames in each direction. Use `SleepFrame(sleep=N)` to add delays between frames. ## Pull Requests From 7684a94c33dc3e26af70231fcffd4e205af16a94 Mon Sep 17 00:00:00 2001 From: Mark Backman Date: Wed, 4 Feb 2026 19:15:57 -0500 Subject: [PATCH 0414/1060] AssemblyAISTTService: Disable turn detection when setting vad_force_turn_endpoint to True --- changelog/3644.changed.md | 1 + src/pipecat/services/assemblyai/stt.py | 56 +++++++++++++++++++++++++- 2 files changed, 56 insertions(+), 1 deletion(-) create mode 100644 changelog/3644.changed.md diff --git a/changelog/3644.changed.md b/changelog/3644.changed.md new file mode 100644 index 000000000..8b1511b9f --- /dev/null +++ b/changelog/3644.changed.md @@ -0,0 +1 @@ +- `AssemblyAISTTService` now automatically configures optimal settings for manual turn detection when `vad_force_turn_endpoint=True`. This sets `end_of_turn_confidence_threshold=1.0` and `max_turn_silence=2000` by default, which disables model-based turn detection and reduces latency by relying on external VAD for turn endpoints. Warnings are logged if conflicting settings are detected. diff --git a/src/pipecat/services/assemblyai/stt.py b/src/pipecat/services/assemblyai/stt.py index 94fad23b7..41a0ae2a0 100644 --- a/src/pipecat/services/assemblyai/stt.py +++ b/src/pipecat/services/assemblyai/stt.py @@ -78,11 +78,19 @@ class AssemblyAISTTService(WebsocketSTTService): language: Language code for transcription. Defaults to English (Language.EN). api_endpoint_base_url: WebSocket endpoint URL. Defaults to AssemblyAI's streaming endpoint. connection_params: Connection configuration parameters. Defaults to AssemblyAIConnectionParams(). - vad_force_turn_endpoint: Whether to force turn endpoint on VAD stop. Defaults to True. + vad_force_turn_endpoint: Whether to force turn endpoint on VAD stop. When True, + disables AssemblyAI's model-based turn detection and relies on external VAD + to trigger turn endpoints. Automatically sets end_of_turn_confidence_threshold=1.0 + and max_turn_silence=2000 unless explicitly overridden. Defaults to True. ttfs_p99_latency: P99 latency from speech end to final transcript in seconds. Override for your deployment. See https://github.com/pipecat-ai/stt-benchmark **kwargs: Additional arguments passed to parent STTService class. """ + # When vad_force_turn_endpoint is enabled, configure connection params for manual + # turn detection mode (disable model-based turn detection) + if vad_force_turn_endpoint: + connection_params = self._configure_manual_turn_mode(connection_params) + super().__init__( sample_rate=connection_params.sample_rate, ttfs_p99_latency=ttfs_p99_latency, **kwargs ) @@ -103,6 +111,52 @@ class AssemblyAISTTService(WebsocketSTTService): self._chunk_size_ms = 50 self._chunk_size_bytes = 0 + def _configure_manual_turn_mode( + self, connection_params: AssemblyAIConnectionParams + ) -> AssemblyAIConnectionParams: + """Configure connection params for manual turn detection mode. + + When vad_force_turn_endpoint is enabled, we want to disable AssemblyAI's + model-based turn detection and rely on external VAD. This requires: + - end_of_turn_confidence_threshold=1.0 (disable semantic turn detection) + - max_turn_silence=2000 (high value since VAD handles turn endings) + + Args: + connection_params: The user-provided connection parameters. + + Returns: + Updated connection parameters configured for manual turn mode. + """ + updates = {} + + # Check end_of_turn_confidence_threshold + if connection_params.end_of_turn_confidence_threshold is None: + updates["end_of_turn_confidence_threshold"] = 1.0 + elif connection_params.end_of_turn_confidence_threshold != 1.0: + logger.warning( + f"vad_force_turn_endpoint is enabled but end_of_turn_confidence_threshold " + f"is set to {connection_params.end_of_turn_confidence_threshold}. " + f"For manual turn detection mode, this should be 1.0 to disable " + f"model-based turn detection. The current value will be used." + ) + + # Check max_turn_silence + if connection_params.max_turn_silence is None: + updates["max_turn_silence"] = 2000 + elif connection_params.max_turn_silence < 1000: + logger.warning( + f"vad_force_turn_endpoint is enabled but max_turn_silence is set to " + f"{connection_params.max_turn_silence}ms. With manual turn detection, " + f"a higher value (e.g., 2000ms) is recommended to avoid premature " + f"turn endings. The current value will be used." + ) + + # Apply updates if any + if updates: + connection_params = connection_params.model_copy(update=updates) + + return connection_params + def can_generate_metrics(self) -> bool: """Check if the service can generate metrics. From 18d91d6df3f7796cd99c4f04c70b54c151c3bd0a Mon Sep 17 00:00:00 2001 From: Eoin <33495030+eoinoreilly30@users.noreply.github.com> Date: Mon, 9 Feb 2026 06:57:24 +0000 Subject: [PATCH 0415/1060] Add new voice options 'marin' and 'cedar' --- src/pipecat/services/openai/tts.py | 4 +++- 1 file changed, 3 insertions(+), 1 deletion(-) diff --git a/src/pipecat/services/openai/tts.py b/src/pipecat/services/openai/tts.py index 593ff7d4c..0c7388970 100644 --- a/src/pipecat/services/openai/tts.py +++ b/src/pipecat/services/openai/tts.py @@ -28,7 +28,7 @@ from pipecat.services.tts_service import TTSService from pipecat.utils.tracing.service_decorators import traced_tts ValidVoice = Literal[ - "alloy", "ash", "ballad", "coral", "echo", "fable", "onyx", "nova", "sage", "shimmer", "verse" + "alloy", "ash", "ballad", "coral", "echo", "fable", "onyx", "nova", "sage", "shimmer", "verse", "marin", "cedar" ] VALID_VOICES: Dict[str, ValidVoice] = { @@ -43,6 +43,8 @@ VALID_VOICES: Dict[str, ValidVoice] = { "sage": "sage", "shimmer": "shimmer", "verse": "verse", + "marin": "marin", + "cedar": "cedar", } From f3c1cd4cd6c2b4e85bb697a88ebaee8877032f66 Mon Sep 17 00:00:00 2001 From: Eoin Date: Tue, 10 Feb 2026 12:25:07 +0900 Subject: [PATCH 0416/1060] Lint --- src/pipecat/services/openai/tts.py | 20 ++++++++++++++++---- 1 file changed, 16 insertions(+), 4 deletions(-) diff --git a/src/pipecat/services/openai/tts.py b/src/pipecat/services/openai/tts.py index 0c7388970..444ae883f 100644 --- a/src/pipecat/services/openai/tts.py +++ b/src/pipecat/services/openai/tts.py @@ -28,23 +28,35 @@ from pipecat.services.tts_service import TTSService from pipecat.utils.tracing.service_decorators import traced_tts ValidVoice = Literal[ - "alloy", "ash", "ballad", "coral", "echo", "fable", "onyx", "nova", "sage", "shimmer", "verse", "marin", "cedar" + "alloy", + "ash", + "ballad", + "cedar", + "coral", + "echo", + "fable", + "marin", + "nova", + "onyx", + "sage", + "shimmer", + "verse", ] VALID_VOICES: Dict[str, ValidVoice] = { "alloy": "alloy", "ash": "ash", "ballad": "ballad", + "cedar": "cedar", "coral": "coral", "echo": "echo", "fable": "fable", - "onyx": "onyx", + "marin": "marin", "nova": "nova", + "onyx": "onyx", "sage": "sage", "shimmer": "shimmer", "verse": "verse", - "marin": "marin", - "cedar": "cedar", } From dfc0856d54a17f42f49084be653f4987d854012e Mon Sep 17 00:00:00 2001 From: Eoin Date: Tue, 10 Feb 2026 12:31:14 +0900 Subject: [PATCH 0417/1060] Added changelog entry --- changelog/3682.added.md | 1 + 1 file changed, 1 insertion(+) create mode 100644 changelog/3682.added.md diff --git a/changelog/3682.added.md b/changelog/3682.added.md new file mode 100644 index 000000000..c9a5061b7 --- /dev/null +++ b/changelog/3682.added.md @@ -0,0 +1 @@ +- Added new OpenAI TTS voice options `marin` and `cedar`. From d47d95e1f0f29493aca68368ff7c080f1df6d6a8 Mon Sep 17 00:00:00 2001 From: Mark Backman Date: Mon, 9 Feb 2026 23:20:11 -0500 Subject: [PATCH 0418/1060] Update SonioxSTTService default model to stt-rt-v4 --- changelog/3697.changed.md | 1 + examples/foundational/07za-interruptible-soniox.py | 8 +++++++- src/pipecat/services/soniox/stt.py | 2 +- 3 files changed, 9 insertions(+), 2 deletions(-) create mode 100644 changelog/3697.changed.md diff --git a/changelog/3697.changed.md b/changelog/3697.changed.md new file mode 100644 index 000000000..ce7bf49d7 --- /dev/null +++ b/changelog/3697.changed.md @@ -0,0 +1 @@ +- Update `SonioxSTTService` default model to `stt-rt-v4`. \ No newline at end of file diff --git a/examples/foundational/07za-interruptible-soniox.py b/examples/foundational/07za-interruptible-soniox.py index 95677c045..b896a43b9 100644 --- a/examples/foundational/07za-interruptible-soniox.py +++ b/examples/foundational/07za-interruptible-soniox.py @@ -24,7 +24,8 @@ from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport from pipecat.services.cartesia.tts import CartesiaTTSService from pipecat.services.openai.llm import OpenAILLMService -from pipecat.services.soniox.stt import SonioxSTTService +from pipecat.services.soniox.stt import SonioxInputParams, SonioxSTTService +from pipecat.transcriptions.language import Language from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams @@ -52,6 +53,11 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): stt = SonioxSTTService( api_key=os.getenv("SONIOX_API_KEY"), + vad_force_turn_endpoint=True, + params=SonioxInputParams( + language_hints=[Language.EN], + language_hints_strict=True, + ), ) tts = CartesiaTTSService( diff --git a/src/pipecat/services/soniox/stt.py b/src/pipecat/services/soniox/stt.py index 268e34508..e3e9e3e5c 100644 --- a/src/pipecat/services/soniox/stt.py +++ b/src/pipecat/services/soniox/stt.py @@ -93,7 +93,7 @@ class SonioxInputParams(BaseModel): client_reference_id: Client reference ID to use for transcription. """ - model: str = "stt-rt-preview" + model: str = "stt-rt-v4" audio_format: Optional[str] = "pcm_s16le" num_channels: Optional[int] = 1 From 28e8b61eb41e10e29e5d4059fd9073fc0d81d5ad Mon Sep 17 00:00:00 2001 From: Ashot Date: Tue, 10 Feb 2026 15:23:51 +0400 Subject: [PATCH 0419/1060] chore: update Async API URL and default model --- src/pipecat/services/asyncai/tts.py | 14 +++++++------- 1 file changed, 7 insertions(+), 7 deletions(-) diff --git a/src/pipecat/services/asyncai/tts.py b/src/pipecat/services/asyncai/tts.py index fbc760562..f27e6bfbf 100644 --- a/src/pipecat/services/asyncai/tts.py +++ b/src/pipecat/services/asyncai/tts.py @@ -94,8 +94,8 @@ class AsyncAITTSService(AudioContextTTSService): api_key: str, voice_id: str, version: str = "v1", - url: str = "wss://api.async.ai/text_to_speech/websocket/ws", - model: str = "asyncflow_multilingual_v1.0", + url: str = "wss://api.async.com/text_to_speech/websocket/ws", + model: str = "async_flash_v1.0", sample_rate: Optional[int] = None, encoding: str = "pcm_s16le", container: str = "raw", @@ -108,10 +108,10 @@ class AsyncAITTSService(AudioContextTTSService): Args: api_key: Async API key. voice_id: UUID of the voice to use for synthesis. See docs for a full list: - https://docs.async.ai/list-voices-16699698e0 + https://docs.async.com/list-voices-16699698e0 version: Async API version. url: WebSocket URL for Async TTS API. - model: TTS model to use (e.g., "asyncflow_multilingual_v1.0"). + model: TTS model to use (e.g., "async_flash_v1.0"). sample_rate: Audio sample rate. encoding: Audio encoding format. container: Audio container format. @@ -435,8 +435,8 @@ class AsyncAIHttpTTSService(TTSService): api_key: str, voice_id: str, aiohttp_session: aiohttp.ClientSession, - model: str = "asyncflow_multilingual_v1.0", - url: str = "https://api.async.ai", + model: str = "async_flash_v1.0", + url: str = "https://api.async.com", version: str = "v1", sample_rate: Optional[int] = None, encoding: str = "pcm_s16le", @@ -450,7 +450,7 @@ class AsyncAIHttpTTSService(TTSService): api_key: Async API key. voice_id: ID of the voice to use for synthesis. aiohttp_session: An aiohttp session for making HTTP requests. - model: TTS model to use (e.g., "asyncflow_multilingual_v1.0"). + model: TTS model to use (e.g., "async_flash_v1.0"). url: Base URL for Async API. version: API version string for Async API. sample_rate: Audio sample rate. From 7bd8dfe898d6d20617d40fd266719471619e3efd Mon Sep 17 00:00:00 2001 From: Mark Backman Date: Tue, 10 Feb 2026 08:19:24 -0500 Subject: [PATCH 0420/1060] Add changelog for PR 3700 --- changelog/3701.changed.md | 1 + 1 file changed, 1 insertion(+) create mode 100644 changelog/3701.changed.md diff --git a/changelog/3701.changed.md b/changelog/3701.changed.md new file mode 100644 index 000000000..03c0d787e --- /dev/null +++ b/changelog/3701.changed.md @@ -0,0 +1 @@ +- Updated the default model to `async_flash_v1.0` and base URL to `https://api.async.com` for `AsyncAITTSService`. \ No newline at end of file From 88e981c01342088cf997b06700fae9eac2200ea3 Mon Sep 17 00:00:00 2001 From: Mark Backman Date: Tue, 10 Feb 2026 09:16:03 -0500 Subject: [PATCH 0421/1060] Set vad_force_turn_endpoint to False in SonioxSTTService --- changelog/3697.changed.2.md | 1 + examples/foundational/07za-interruptible-soniox.py | 1 - src/pipecat/services/soniox/stt.py | 5 +++-- 3 files changed, 4 insertions(+), 3 deletions(-) create mode 100644 changelog/3697.changed.2.md diff --git a/changelog/3697.changed.2.md b/changelog/3697.changed.2.md new file mode 100644 index 000000000..0307bd59a --- /dev/null +++ b/changelog/3697.changed.2.md @@ -0,0 +1 @@ +- Update `SonioxSTTService` to set `vad_force_turn_endpoint` to `True`. This setting disabled the turn detection logic available natively in Soniox. Instead, Soniox relies on a local VAD to finalize the transcript. This configuration meaningfully reduces the time to final segment for Soniox. With this setting enabled, Soniox outputs a transcript in ~250ms (median). Pipecat enables smart-turn detection by default using the `LocalSmartTurnAnalyzerV3`. To use the native turn detection logic in Soniox, just set `vad_force_turn_endpoint` to `False`. \ No newline at end of file diff --git a/examples/foundational/07za-interruptible-soniox.py b/examples/foundational/07za-interruptible-soniox.py index b896a43b9..a60cfe992 100644 --- a/examples/foundational/07za-interruptible-soniox.py +++ b/examples/foundational/07za-interruptible-soniox.py @@ -53,7 +53,6 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): stt = SonioxSTTService( api_key=os.getenv("SONIOX_API_KEY"), - vad_force_turn_endpoint=True, params=SonioxInputParams( language_hints=[Language.EN], language_hints_strict=True, diff --git a/src/pipecat/services/soniox/stt.py b/src/pipecat/services/soniox/stt.py index e3e9e3e5c..fb5b78e4a 100644 --- a/src/pipecat/services/soniox/stt.py +++ b/src/pipecat/services/soniox/stt.py @@ -152,7 +152,7 @@ class SonioxSTTService(WebsocketSTTService): url: str = "wss://stt-rt.soniox.com/transcribe-websocket", sample_rate: Optional[int] = None, params: Optional[SonioxInputParams] = None, - vad_force_turn_endpoint: bool = False, + vad_force_turn_endpoint: bool = True, ttfs_p99_latency: Optional[float] = SONIOX_TTFS_P99, **kwargs, ): @@ -164,7 +164,8 @@ class SonioxSTTService(WebsocketSTTService): sample_rate: Audio sample rate. params: Additional configuration parameters, such as language hints, context and speaker diarization. - vad_force_turn_endpoint: Listen to `VADUserStoppedSpeakingFrame` to send finalize message to Soniox. If disabled, Soniox will detect the end of the speech. + vad_force_turn_endpoint: Listen to `VADUserStoppedSpeakingFrame` to send finalize message to Soniox. + If disabled, Soniox will detect the end of the speech. Defaults to True. ttfs_p99_latency: P99 latency from speech end to final transcript in seconds. Override for your deployment. See https://github.com/pipecat-ai/stt-benchmark **kwargs: Additional arguments passed to the STTService. From f206aaa28d7c845941c56c5201806a6b0e8349ba Mon Sep 17 00:00:00 2001 From: filipi87 Date: Tue, 10 Feb 2026 11:22:26 -0300 Subject: [PATCH 0422/1060] - Added context_id field to all TTS-related frames (TTSAudioRawFrame, TTSStartedFrame, TTSStoppedFrame, AggregatedTextFrame, TTSTextFrame) - Added append_to_context parameter to TTSSpeakFrame for conditional LLM context addition --- src/pipecat/frames/frames.py | 35 +++++++++++++++++++++++++++++------ 1 file changed, 29 insertions(+), 6 deletions(-) diff --git a/src/pipecat/frames/frames.py b/src/pipecat/frames/frames.py index de33c6187..7b821a9bc 100644 --- a/src/pipecat/frames/frames.py +++ b/src/pipecat/frames/frames.py @@ -279,9 +279,12 @@ class TTSAudioRawFrame(OutputAudioRawFrame): """Audio data frame generated by Text-to-Speech services. A chunk of output audio generated by a TTS service, ready for playback. + + Parameters: + context_id: Unique identifier for the TTS context that generated this audio. """ - pass + context_id: Optional[str] = None @dataclass @@ -343,6 +346,11 @@ class TextFrame(DataFrame): Parameters: text: The text content. + skip_tts: Whether this text should be skipped by the TTS service. + includes_inter_frame_spaces: Whether any necessary inter-frame (leading/trailing) spaces are already + included in the text. + append_to_context: Whether this text should be appended to the LLM context. + Defaults to True. """ text: str @@ -397,9 +405,11 @@ class AggregatedTextFrame(TextFrame): Parameters: aggregated_by: Method used to aggregate the text frames. + context_id: Unique identifier for the TTS context that generated this text. """ aggregated_by: AggregationType | str + context_id: Optional[str] = None @dataclass @@ -411,9 +421,13 @@ class VisionTextFrame(LLMTextFrame): @dataclass class TTSTextFrame(AggregatedTextFrame): - """Text frame generated by Text-to-Speech services.""" + """Text frame generated by Text-to-Speech services. - pass + Parameters: + context_id: Unique identifier for the TTS context that generated this text. + """ + + context_id: Optional[str] = None @dataclass @@ -923,9 +937,11 @@ class TTSSpeakFrame(DataFrame): Parameters: text: The text to be spoken. + append_to_context: Whether to append the text to the context. """ text: str + append_to_context: Optional[bool] = None @dataclass @@ -2023,16 +2039,23 @@ class TTSStartedFrame(ControlFrame): TTSStoppedFrame. These frames can be used for aggregating audio frames in a transport to optimize the size of frames sent to the session, without needing to control this in the TTS service. + + Parameters: + context_id: Unique identifier for this TTS context. """ - pass + context_id: Optional[str] = None @dataclass class TTSStoppedFrame(ControlFrame): - """Frame indicating the end of a TTS response.""" + """Frame indicating the end of a TTS response. - pass + Parameters: + context_id: Unique identifier for this TTS context. + """ + + context_id: Optional[str] = None @dataclass From 1dccbe7c0b32cd7bb0105f244950e9ed14386651 Mon Sep 17 00:00:00 2001 From: filipi87 Date: Tue, 10 Feb 2026 11:27:13 -0300 Subject: [PATCH 0423/1060] Simplified context aggregators, _handle_text() to only check frame.append_to_context instead of also checking self._started --- src/pipecat/processors/aggregators/llm_response.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/src/pipecat/processors/aggregators/llm_response.py b/src/pipecat/processors/aggregators/llm_response.py index e11ededbf..44e5ce252 100644 --- a/src/pipecat/processors/aggregators/llm_response.py +++ b/src/pipecat/processors/aggregators/llm_response.py @@ -1059,7 +1059,7 @@ class LLMAssistantContextAggregator(LLMContextResponseAggregator): await self.push_aggregation() async def _handle_text(self, frame: TextFrame): - if not self._started or not frame.append_to_context: + if not frame.append_to_context: return if self._params.expect_stripped_words: From 9bb712a47b4ece26dde95fb2b41e8e866c4ed1df Mon Sep 17 00:00:00 2001 From: filipi87 Date: Tue, 10 Feb 2026 11:27:30 -0300 Subject: [PATCH 0424/1060] Simplified universal context aggregators, _handle_text() to only check frame.append_to_context instead of also checking self._started --- .../aggregators/llm_response_universal.py | 21 ++++++------------- 1 file changed, 6 insertions(+), 15 deletions(-) diff --git a/src/pipecat/processors/aggregators/llm_response_universal.py b/src/pipecat/processors/aggregators/llm_response_universal.py index 3b162d48f..574af7bbf 100644 --- a/src/pipecat/processors/aggregators/llm_response_universal.py +++ b/src/pipecat/processors/aggregators/llm_response_universal.py @@ -52,6 +52,7 @@ from pipecat.frames.frames import ( StartFrame, TextFrame, TranscriptionFrame, + TranslationFrame, UserImageRawFrame, UserMuteStartedFrame, UserMuteStoppedFrame, @@ -795,7 +796,6 @@ class LLMAssistantAggregator(LLMContextAggregator): DeprecationWarning, ) - self._started = 0 self._function_calls_in_progress: Dict[str, Optional[FunctionCallInProgressFrame]] = {} self._function_calls_image_results: Dict[str, UserImageRawFrame] = {} self._context_updated_tasks: Set[asyncio.Task] = set() @@ -917,12 +917,10 @@ class LLMAssistantAggregator(LLMContextAggregator): async def _handle_interruptions(self, frame: InterruptionFrame): await self._trigger_assistant_turn_stopped() - self._started = 0 await self.reset() async def _handle_end_or_cancel(self, frame: Frame): await self._trigger_assistant_turn_stopped() - self._started = 0 async def _handle_function_calls_started(self, frame: FunctionCallsStartedFrame): function_names = [f"{f.function_name}:{f.tool_call_id}" for f in frame.function_calls] @@ -1067,15 +1065,17 @@ class LLMAssistantAggregator(LLMContextAggregator): ) async def _handle_llm_start(self, _: LLMFullResponseStartFrame): - self._started += 1 await self._trigger_assistant_turn_started() async def _handle_llm_end(self, _: LLMFullResponseEndFrame): - self._started -= 1 await self._trigger_assistant_turn_stopped() async def _handle_text(self, frame: TextFrame): - if not self._started or not frame.append_to_context: + # Skip TextFrame types not intended to build the assistant context + if isinstance(frame, (TranscriptionFrame, TranslationFrame, InterimTranscriptionFrame)): + return + + if not frame.append_to_context: return # Make sure we really have text (spaces count, too!) @@ -1089,18 +1089,12 @@ class LLMAssistantAggregator(LLMContextAggregator): ) async def _handle_thought_start(self, frame: LLMThoughtStartFrame): - if not self._started: - return - await self._reset_thought_aggregation() self._thought_append_to_context = frame.append_to_context self._thought_llm = frame.llm self._thought_start_time = time_now_iso8601() async def _handle_thought_text(self, frame: LLMThoughtTextFrame): - if not self._started: - return - # Make sure we really have text (spaces count, too!) if len(frame.text) == 0: return @@ -1112,9 +1106,6 @@ class LLMAssistantAggregator(LLMContextAggregator): ) async def _handle_thought_end(self, frame: LLMThoughtEndFrame): - if not self._started: - return - thought = concatenate_aggregated_text(self._thought_aggregation) if self._thought_append_to_context: From 19cd2422619eaa79952927f0ff26c1636faa6515 Mon Sep 17 00:00:00 2001 From: filipi87 Date: Tue, 10 Feb 2026 11:27:58 -0300 Subject: [PATCH 0425/1060] Added TTS context tracking system to trace audio generation through the pipeline. --- src/pipecat/services/tts_service.py | 109 ++++++++++++++++++++++++---- 1 file changed, 93 insertions(+), 16 deletions(-) diff --git a/src/pipecat/services/tts_service.py b/src/pipecat/services/tts_service.py index 37aad0372..239d2398b 100644 --- a/src/pipecat/services/tts_service.py +++ b/src/pipecat/services/tts_service.py @@ -7,7 +7,9 @@ """Base classes for Text-to-speech services.""" import asyncio +import uuid from abc import abstractmethod +from dataclasses import dataclass from typing import ( Any, AsyncGenerator, @@ -58,6 +60,17 @@ from pipecat.utils.text.simple_text_aggregator import SimpleTextAggregator from pipecat.utils.time import seconds_to_nanoseconds +@dataclass +class TTSContext: + """Context information for a TTS request. + + Attributes: + append_to_context: Whether this TTS output should be appended to the conversation context. + """ + + append_to_context: bool = True + + class TTSService(AIService): """Base class for text-to-speech services. @@ -66,9 +79,10 @@ class TTSService(AIService): sentence aggregation, silence insertion, and frame processing control. Event handlers: - on_connected: Called when connected to the STT service. - on_connected: Called when disconnected from the STT service. - on_connection_error: Called when a connection to the STT service error occurs. + on_connected: Called when connected to the TTS service. + on_disconnected: Called when disconnected from the TTS service. + on_connection_error: Called when a connection to the TTS service error occurs. + on_tts_request: Called before a TTS request is made, with the context ID and text. Example:: @@ -81,8 +95,12 @@ class TTSService(AIService): logger.debug(f"TTS disconnected") @tts.event_handler("on_connection_error") - async def on_connection_error(stt: TTSService, error: str): + async def on_connection_error(tts: TTSService, error: str): logger.error(f"TTS connection error: {error}") + + @tts.event_handler("on_tts_request") + async def on_tts_request(tts: TTSService, context_id: str, text: str): + logger.debug(f"TTS request: {context_id} - {text}") """ def __init__( @@ -209,10 +227,12 @@ class TTSService(AIService): self._stop_frame_queue: asyncio.Queue = asyncio.Queue() self._processing_text: bool = False + self._tts_contexts: Dict[str, TTSContext] = {} self._register_event_handler("on_connected") self._register_event_handler("on_disconnected") self._register_event_handler("on_connection_error") + self._register_event_handler("on_tts_request") @property def sample_rate(self) -> int: @@ -256,15 +276,26 @@ class TTSService(AIService): """ self._voice_id = voice + def create_context_id(self) -> str: + """Generate a unique context ID for a TTS request. + + This method can be overridden by subclasses to provide custom context ID generation. + + Returns: + A unique string identifier for the TTS context. + """ + return str(uuid.uuid4()) + # Converts the text to audio. @abstractmethod - async def run_tts(self, text: str) -> AsyncGenerator[Frame, None]: + async def run_tts(self, text: str, context_id: str) -> AsyncGenerator[Frame, None]: """Run text-to-speech synthesis on the provided text. This method must be implemented by subclasses to provide actual TTS functionality. Args: text: The text to synthesize into speech. + context_id: Unique identifier for this TTS context. Yields: Frame: Audio frames containing the synthesized speech. @@ -463,7 +494,10 @@ class TTSService(AIService): # Store if we were processing text or not so we can set it back. processing_text = self._processing_text # Assumption: text in TTSSpeakFrame does not include inter-frame spaces - await self._push_tts_frames(AggregatedTextFrame(frame.text, AggregationType.SENTENCE)) + await self._push_tts_frames( + AggregatedTextFrame(frame.text, AggregationType.SENTENCE), + append_tts_text_to_context=frame.append_to_context, + ) # We pause processing incoming frames because we are sending data to # the TTS. We pause to avoid audio overlapping. await self._maybe_pause_frame_processing() @@ -484,6 +518,12 @@ class TTSService(AIService): frame: The frame to push. direction: The direction to push the frame. """ + # Clean up context when we see TTSStoppedFrame + if isinstance(frame, TTSStoppedFrame) and frame.context_id: + if frame.context_id in self._tts_contexts: + logger.debug(f"{self} cleaning up TTS context {frame.context_id}") + del self._tts_contexts[frame.context_id] + if self._push_silence_after_stop and isinstance(frame, TTSStoppedFrame): silence_num_bytes = int(self._silence_time_s * self.sample_rate * 2) # 16-bit silence_frame = TTSAudioRawFrame( @@ -513,6 +553,7 @@ class TTSService(AIService): *, strip_wav_header: bool = False, in_sample_rate: Optional[int] = None, + context_id: Optional[str] = None, ) -> AsyncGenerator[Frame, None]: """Stream audio frames from an async byte iterator with optional resampling. @@ -526,6 +567,7 @@ class TTSService(AIService): strip_wav_header: Strip WAV header and parse source sample rate from it. in_sample_rate: Source sample rate for raw PCM data. Overrides WAV-detected rate if both are provided. + context_id: Unique identifier for this TTS context. """ buffer = bytearray() @@ -555,7 +597,10 @@ class TTSService(AIService): buffer = buffer[aligned_length:] # keep any leftover byte if len(aligned_chunk) > 0: - yield TTSAudioRawFrame(aligned_chunk, self.sample_rate, 1) + frame = TTSAudioRawFrame( + bytes(aligned_chunk), self.sample_rate, 1, context_id=context_id + ) + yield frame if len(buffer) > 0: # Make sure we don't need an extra padding byte. @@ -601,7 +646,10 @@ class TTSService(AIService): ) async def _push_tts_frames( - self, src_frame: AggregatedTextFrame, includes_inter_frame_spaces: Optional[bool] = False + self, + src_frame: AggregatedTextFrame, + includes_inter_frame_spaces: Optional[bool] = False, + append_tts_text_to_context: Optional[bool] = True, ): type = src_frame.aggregated_by text = src_frame.text @@ -636,11 +684,15 @@ class TTSService(AIService): await self.stop_processing_metrics() return + # Create context ID and store metadata + context_id = self.create_context_id() + # To support use cases that may want to know the text before it's spoken, we # push the AggregatedTextFrame version before transforming and sending to TTS. # However, we do not want to add this text to the assistant context until it # is spoken, so we set append_to_context to False. src_frame.append_to_context = False + src_frame.context_id = context_id await self.push_frame(src_frame) # Note: Text transformations are meant to only affect the text sent to the TTS for @@ -653,9 +705,19 @@ class TTSService(AIService): if aggregation_type == type or aggregation_type == "*": transformed_text = await transform(transformed_text, type) + self._tts_contexts[context_id] = TTSContext( + append_to_context=append_tts_text_to_context + if append_tts_text_to_context is not None + else True + ) + # Apply any final text preparation (e.g., trailing space) prepared_text = self._prepare_text_for_tts(transformed_text) - await self.process_generator(self.run_tts(prepared_text)) + + # Trigger event before starting TTS + await self._call_event_handler("on_tts_request", context_id, prepared_text) + + await self.process_generator(self.run_tts(prepared_text, context_id)) await self.stop_processing_metrics() @@ -669,6 +731,10 @@ class TTSService(AIService): # or transformations. frame = TTSTextFrame(text, aggregated_by=type) frame.includes_inter_frame_spaces = includes_inter_frame_spaces + frame.context_id = context_id + # Only override append_to_context if explicitly set + if append_tts_text_to_context is not None: + frame.append_to_context = append_tts_text_to_context await self.push_frame(frame) async def _stop_frame_handler(self): @@ -721,18 +787,24 @@ class WordTTSService(TTSService): """Reset word timestamp tracking.""" self._initial_word_timestamp = -1 - async def add_word_timestamps(self, word_times: List[Tuple[str, float]]): + async def add_word_timestamps( + self, word_times: List[Tuple[str, float]], context_id: Optional[str] = None + ): """Add word timestamps to the processing queue. Args: word_times: List of (word, timestamp) tuples where timestamp is in seconds. + context_id: Unique identifier for the TTS context. """ + # Transform to include context_id in each tuple + word_times_with_context = [(word, timestamp, context_id) for word, timestamp in word_times] + if self._initial_word_timestamp == -1: # Cache word timestamps and don't add them until we have started # (i.e. we have some audio). - self._initial_word_times.extend(word_times) + self._initial_word_times.extend(word_times_with_context) else: - await self._add_word_timestamps(word_times) + await self._add_word_timestamps(word_times_with_context) async def start(self, frame: StartFrame): """Start the word TTS service. @@ -790,15 +862,15 @@ class WordTTSService(TTSService): await self.cancel_task(self._words_task) self._words_task = None - async def _add_word_timestamps(self, word_times: List[Tuple[str, float]]): - for word, timestamp in word_times: - await self._words_queue.put((word, seconds_to_nanoseconds(timestamp))) + async def _add_word_timestamps(self, word_times_with_context: List[Tuple[str, float, str]]): + for word, timestamp, context_id in word_times_with_context: + await self._words_queue.put((word, seconds_to_nanoseconds(timestamp), context_id)) async def _words_task_handler(self): last_pts = 0 while True: frame = None - (word, timestamp) = await self._words_queue.get() + (word, timestamp, context_id) = await self._words_queue.get() if word == "Reset" and timestamp == 0: await self.reset_word_timestamps() if self._llm_response_started: @@ -808,11 +880,16 @@ class WordTTSService(TTSService): elif word == "TTSStoppedFrame" and timestamp == 0: frame = TTSStoppedFrame() frame.pts = last_pts + frame.context_id = context_id else: # Assumption: word-by-word text frames don't include spaces, so # we can rely on the default includes_inter_frame_spaces=False frame = TTSTextFrame(word, aggregated_by=AggregationType.WORD) frame.pts = self._initial_word_timestamp + timestamp + frame.context_id = context_id + # Look up append_to_context from context metadata + if context_id in self._tts_contexts: + frame.append_to_context = self._tts_contexts[context_id].append_to_context if frame: last_pts = frame.pts await self.push_frame(frame) From a47d7f98ee5b6c3978a44cd2470347dbaed534ed Mon Sep 17 00:00:00 2001 From: filipi87 Date: Tue, 10 Feb 2026 11:28:08 -0300 Subject: [PATCH 0426/1060] Refactored all 30+ TTS service implementations to support context tracking --- src/pipecat/services/asyncai/tts.py | 46 +++++------- src/pipecat/services/aws/tts.py | 11 +-- src/pipecat/services/azure/tts.py | 38 ++++++---- src/pipecat/services/camb/tts.py | 9 ++- src/pipecat/services/cartesia/tts.py | 30 ++++---- src/pipecat/services/deepgram/tts.py | 19 +++-- src/pipecat/services/elevenlabs/tts.py | 92 ++++++++++------------- src/pipecat/services/fish/tts.py | 9 +-- src/pipecat/services/google/tts.py | 33 ++++---- src/pipecat/services/gradium/tts.py | 15 +++- src/pipecat/services/groq/tts.py | 9 ++- src/pipecat/services/hathora/tts.py | 8 +- src/pipecat/services/hume/tts.py | 11 ++- src/pipecat/services/inworld/tts.py | 79 +++++++++----------- src/pipecat/services/kokoro/tts.py | 12 ++- src/pipecat/services/lmnt/tts.py | 20 ++--- src/pipecat/services/minimax/tts.py | 8 +- src/pipecat/services/neuphonic/tts.py | 40 +++++----- src/pipecat/services/nvidia/tts.py | 10 ++- src/pipecat/services/openai/tts.py | 9 ++- src/pipecat/services/piper/tts.py | 19 +++-- src/pipecat/services/playht/tts.py | 43 ++++++----- src/pipecat/services/resembleai/tts.py | 95 +++++++++++------------- src/pipecat/services/rime/tts.py | 44 ++++++----- src/pipecat/services/sarvam/tts.py | 34 +++++---- src/pipecat/services/speechmatics/tts.py | 8 +- src/pipecat/services/xtts/tts.py | 15 ++-- 27 files changed, 404 insertions(+), 362 deletions(-) diff --git a/src/pipecat/services/asyncai/tts.py b/src/pipecat/services/asyncai/tts.py index f27e6bfbf..4ff6c928d 100644 --- a/src/pipecat/services/asyncai/tts.py +++ b/src/pipecat/services/asyncai/tts.py @@ -9,7 +9,6 @@ import asyncio import base64 import json -import uuid from typing import AsyncGenerator, Optional import aiohttp @@ -148,7 +147,6 @@ class AsyncAITTSService(AudioContextTTSService): self._receive_task = None self._keepalive_task = None - self._started = False self._context_id = None def can_generate_metrics(self) -> bool: @@ -265,7 +263,6 @@ class AsyncAITTSService(AudioContextTTSService): finally: self._websocket = None self._context_id = None - self._started = False await self._call_event_handler("on_disconnected") def _get_websocket(self): @@ -289,8 +286,6 @@ class AsyncAITTSService(AudioContextTTSService): direction: The direction to push the frame. """ await super().push_frame(frame, direction) - if isinstance(frame, (TTSStoppedFrame, InterruptionFrame)): - self._started = False async def _receive_messages(self): async for message in self._get_websocket(): @@ -323,7 +318,7 @@ class AsyncAITTSService(AudioContextTTSService): if msg.get("audio"): await self.stop_ttfb_metrics() audio = base64.b64decode(msg["audio"]) - frame = TTSAudioRawFrame(audio, self.sample_rate, 1) + frame = TTSAudioRawFrame(audio, self.sample_rate, 1, context_id=received_ctx_id) await self.append_to_audio_context(received_ctx_id, frame) async def _keepalive_task_handler(self): @@ -365,14 +360,14 @@ class AsyncAITTSService(AudioContextTTSService): except Exception as e: logger.error(f"Error closing context on interruption: {e}") self._context_id = None - self._started = False @traced_tts - async def run_tts(self, text: str) -> AsyncGenerator[Frame, None]: + async def run_tts(self, text: str, context_id: str) -> AsyncGenerator[Frame, None]: """Generate speech from text using Async API websocket endpoint. Args: text: The text to synthesize into speech. + context_id: The context ID for tracking audio frames. Yields: Frame: Audio frames containing the synthesized speech. @@ -384,28 +379,21 @@ class AsyncAITTSService(AudioContextTTSService): await self._connect() try: - if not self._started: - await self.start_ttfb_metrics() - yield TTSStartedFrame() - self._started = True + await self.start_ttfb_metrics() + yield TTSStartedFrame(context_id=context_id) - if not self._context_id: - self._context_id = str(uuid.uuid4()) - if not self.audio_context_available(self._context_id): - await self.create_audio_context(self._context_id) + if not self._context_id: + self._context_id = context_id + if not self.audio_context_available(self._context_id): + await self.create_audio_context(self._context_id) - msg = self._build_msg(text=text, force=True, context_id=self._context_id) - await self._get_websocket().send(msg) - await self.start_tts_usage_metrics(text) - else: - if self._websocket and self._context_id: - msg = self._build_msg(text=text, force=True, context_id=self._context_id) - await self._get_websocket().send(msg) + msg = self._build_msg(text=text, force=True, context_id=self._context_id) + await self._get_websocket().send(msg) + await self.start_tts_usage_metrics(text) except Exception as e: yield ErrorFrame(error=f"Unknown error occurred: {e}") - yield TTSStoppedFrame() - self._started = False + yield TTSStoppedFrame(context_id=context_id) return yield None except Exception as e: @@ -510,11 +498,12 @@ class AsyncAIHttpTTSService(TTSService): self._settings["output_format"]["sample_rate"] = self.sample_rate @traced_tts - async def run_tts(self, text: str) -> AsyncGenerator[Frame, None]: + async def run_tts(self, text: str, context_id: str) -> AsyncGenerator[Frame, None]: """Generate speech from text using Async's HTTP streaming API. Args: text: The text to synthesize into speech. + context_id: The context ID for tracking audio frames. Yields: Frame: Audio frames containing the synthesized speech. @@ -531,7 +520,7 @@ class AsyncAIHttpTTSService(TTSService): "output_format": self._settings["output_format"], "language": self._settings["language"], } - yield TTSStartedFrame() + yield TTSStartedFrame(context_id=context_id) headers = { "version": self._api_version, "x-api-key": self._api_key, @@ -560,6 +549,7 @@ class AsyncAIHttpTTSService(TTSService): audio=audio_data, sample_rate=self.sample_rate, num_channels=1, + context_id=context_id, ) yield frame @@ -568,4 +558,4 @@ class AsyncAIHttpTTSService(TTSService): await self.push_error(error_msg=f"Unknown error occurred: {e}", exception=e) finally: await self.stop_ttfb_metrics() - yield TTSStoppedFrame() + yield TTSStoppedFrame(context_id=context_id) diff --git a/src/pipecat/services/aws/tts.py b/src/pipecat/services/aws/tts.py index 358a894c7..b902564d2 100644 --- a/src/pipecat/services/aws/tts.py +++ b/src/pipecat/services/aws/tts.py @@ -253,11 +253,12 @@ class AWSPollyTTSService(TTSService): return ssml @traced_tts - async def run_tts(self, text: str) -> AsyncGenerator[Frame, None]: + async def run_tts(self, text: str, context_id: str) -> AsyncGenerator[Frame, None]: """Generate speech from text using AWS Polly. Args: text: The text to synthesize into speech. + context_id: The context ID for tracking audio frames. Yields: Frame: Audio frames containing the synthesized speech. @@ -298,7 +299,7 @@ class AWSPollyTTSService(TTSService): await self.start_tts_usage_metrics(text) - yield TTSStartedFrame() + yield TTSStartedFrame(context_id=context_id) CHUNK_SIZE = self.chunk_size @@ -306,16 +307,16 @@ class AWSPollyTTSService(TTSService): chunk = audio_data[i : i + CHUNK_SIZE] if len(chunk) > 0: await self.stop_ttfb_metrics() - frame = TTSAudioRawFrame(chunk, self.sample_rate, 1) + frame = TTSAudioRawFrame(chunk, self.sample_rate, 1, context_id=context_id) yield frame - yield TTSStoppedFrame() + yield TTSStoppedFrame(context_id=context_id) except (BotoCoreError, ClientError) as error: error_message = f"AWS Polly TTS error: {str(error)}" yield ErrorFrame(error=error_message) finally: - yield TTSStoppedFrame() + yield TTSStoppedFrame(context_id=context_id) class PollyTTSService(AWSPollyTTSService): diff --git a/src/pipecat/services/azure/tts.py b/src/pipecat/services/azure/tts.py index dc0c56e7b..7d4aa0253 100644 --- a/src/pipecat/services/azure/tts.py +++ b/src/pipecat/services/azure/tts.py @@ -277,7 +277,6 @@ class AzureTTSService(WordTTSService, AzureBaseTTSService): self._audio_queue = asyncio.Queue() self._word_boundary_queue = asyncio.Queue() self._word_processor_task = None - self._started = False self._first_chunk = True self._cumulative_audio_offset: float = 0.0 # Cumulative audio duration in seconds self._current_sentence_base_offset: float = 0.0 # Base offset for current sentence @@ -287,6 +286,9 @@ class AzureTTSService(WordTTSService, AzureBaseTTSService): ) self._last_word: Optional[str] = None # Track last word for punctuation merging self._last_timestamp: Optional[float] = None # Track last timestamp + self._current_context_id: Optional[str] = ( + None # Track current context_id for word timestamps + ) def can_generate_metrics(self) -> bool: """Check if this service can generate processing metrics. @@ -478,7 +480,10 @@ class AzureTTSService(WordTTSService, AzureBaseTTSService): while True: try: word, timestamp_seconds = await self._word_boundary_queue.get() - await self.add_word_timestamps([(word, timestamp_seconds)]) + if self._current_context_id: + await self.add_word_timestamps( + [(word, timestamp_seconds)], self._current_context_id + ) self._word_boundary_queue.task_done() except asyncio.CancelledError: break @@ -536,12 +541,11 @@ class AzureTTSService(WordTTSService, AzureBaseTTSService): await super().push_frame(frame, direction) if isinstance(frame, (TTSStoppedFrame, InterruptionFrame)): self._reset_state() - if isinstance(frame, TTSStoppedFrame): - await self.add_word_timestamps([("Reset", 0)]) + if isinstance(frame, TTSStoppedFrame) and self._current_context_id: + await self.add_word_timestamps([("Reset", 0)], self._current_context_id) def _reset_state(self): """Reset TTS state between turns.""" - self._started = False self._first_chunk = True self._cumulative_audio_offset = 0.0 self._current_sentence_base_offset = 0.0 @@ -549,6 +553,7 @@ class AzureTTSService(WordTTSService, AzureBaseTTSService): self._current_sentence_max_word_offset = 0.0 self._last_word = None self._last_timestamp = None + self._current_context_id = None async def flush_audio(self): """Flush any pending audio data.""" @@ -592,11 +597,12 @@ class AzureTTSService(WordTTSService, AzureBaseTTSService): break @traced_tts - async def run_tts(self, text: str) -> AsyncGenerator[Frame, None]: + async def run_tts(self, text: str, context_id: str) -> AsyncGenerator[Frame, None]: """Generate speech from text using Azure's streaming synthesis. Args: text: The text to synthesize into speech. + context_id: The context ID for tracking audio frames. Yields: Frame: Audio frames containing synthesized speech data. @@ -615,11 +621,10 @@ class AzureTTSService(WordTTSService, AzureBaseTTSService): return try: - if not self._started: - await self.start_ttfb_metrics() - yield TTSStartedFrame() - self._started = True - self._first_chunk = True + await self.start_ttfb_metrics() + yield TTSStartedFrame(context_id=context_id) + self._first_chunk = True + self._current_context_id = context_id # Capture base offset BEFORE starting synthesis to avoid race conditions # Word boundary callbacks will use this value @@ -647,6 +652,7 @@ class AzureTTSService(WordTTSService, AzureBaseTTSService): audio=chunk, sample_rate=self.sample_rate, num_channels=1, + context_id=context_id, ) yield frame @@ -662,7 +668,7 @@ class AzureTTSService(WordTTSService, AzureBaseTTSService): except Exception as e: yield ErrorFrame(error=f"Unknown error occurred: {e}") - yield TTSStoppedFrame() + yield TTSStoppedFrame(context_id=context_id) self._reset_state() return @@ -738,11 +744,12 @@ class AzureHttpTTSService(TTSService, AzureBaseTTSService): ) @traced_tts - async def run_tts(self, text: str) -> AsyncGenerator[Frame, None]: + async def run_tts(self, text: str, context_id: str) -> AsyncGenerator[Frame, None]: """Generate speech from text using Azure's HTTP synthesis API. Args: text: The text to synthesize into speech. + context_id: The context ID for tracking audio frames. Yields: Frame: Audio frames containing the complete synthesized speech. @@ -758,14 +765,15 @@ class AzureHttpTTSService(TTSService, AzureBaseTTSService): if result.reason == ResultReason.SynthesizingAudioCompleted: await self.start_tts_usage_metrics(text) await self.stop_ttfb_metrics() - yield TTSStartedFrame() + yield TTSStartedFrame(context_id=context_id) # Azure always sends a 44-byte header. Strip it off. yield TTSAudioRawFrame( audio=result.audio_data[44:], sample_rate=self.sample_rate, num_channels=1, + context_id=context_id, ) - yield TTSStoppedFrame() + yield TTSStoppedFrame(context_id=context_id) elif result.reason == ResultReason.Canceled: cancellation_details = result.cancellation_details logger.warning(f"Speech synthesis canceled: {cancellation_details.reason}") diff --git a/src/pipecat/services/camb/tts.py b/src/pipecat/services/camb/tts.py index 00b4eaf9b..def57d3a0 100644 --- a/src/pipecat/services/camb/tts.py +++ b/src/pipecat/services/camb/tts.py @@ -259,11 +259,12 @@ class CambTTSService(TTSService): self._sample_rate = MODEL_SAMPLE_RATES.get(self.model_name, 22050) @traced_tts - async def run_tts(self, text: str) -> AsyncGenerator[Frame, None]: + async def run_tts(self, text: str, context_id: str) -> AsyncGenerator[Frame, None]: """Generate speech from text using Camb.ai's TTS API. Args: text: The text to synthesize into speech (max 3000 characters). + context_id: The context ID for tracking audio frames. Yields: Frame: Audio frames containing the synthesized speech. @@ -292,7 +293,7 @@ class CambTTSService(TTSService): tts_kwargs["user_instructions"] = self._settings["user_instructions"] await self.start_tts_usage_metrics(text) - yield TTSStartedFrame() + yield TTSStartedFrame(context_id=context_id) assert self._client is not None, "Camb.ai TTS service not initialized" @@ -312,6 +313,7 @@ class CambTTSService(TTSService): audio=aligned_audio, sample_rate=self.sample_rate, num_channels=1, + context_id=context_id, ) # Yield any remaining complete samples @@ -322,9 +324,10 @@ class CambTTSService(TTSService): audio=aligned_audio, sample_rate=self.sample_rate, num_channels=1, + context_id=context_id, ) except Exception as e: yield ErrorFrame(error=f"Camb.ai TTS error: {e}") finally: - yield TTSStoppedFrame() + yield TTSStoppedFrame(context_id=context_id) diff --git a/src/pipecat/services/cartesia/tts.py b/src/pipecat/services/cartesia/tts.py index 6bfb8703d..791c60a18 100644 --- a/src/pipecat/services/cartesia/tts.py +++ b/src/pipecat/services/cartesia/tts.py @@ -8,7 +8,6 @@ import base64 import json -import uuid import warnings from enum import Enum from typing import AsyncGenerator, List, Literal, Optional @@ -554,16 +553,17 @@ class CartesiaTTSService(AudioContextWordTTSService): msg = json.loads(message) if not msg or not self.audio_context_available(msg["context_id"]): continue + ctx_id = msg["context_id"] if msg["type"] == "done": await self.stop_ttfb_metrics() - await self.add_word_timestamps([("TTSStoppedFrame", 0), ("Reset", 0)]) - await self.remove_audio_context(msg["context_id"]) + await self.add_word_timestamps([("TTSStoppedFrame", 0), ("Reset", 0)], ctx_id) + await self.remove_audio_context(ctx_id) elif msg["type"] == "timestamps": # Process the timestamps based on language before adding them processed_timestamps = self._process_word_timestamps_for_language( msg["word_timestamps"]["words"], msg["word_timestamps"]["start"] ) - await self.add_word_timestamps(processed_timestamps) + await self.add_word_timestamps(processed_timestamps, ctx_id) elif msg["type"] == "chunk": await self.stop_ttfb_metrics() await self.start_word_timestamps() @@ -571,10 +571,11 @@ class CartesiaTTSService(AudioContextWordTTSService): audio=base64.b64decode(msg["data"]), sample_rate=self.sample_rate, num_channels=1, + context_id=ctx_id, ) - await self.append_to_audio_context(msg["context_id"], frame) + await self.append_to_audio_context(ctx_id, frame) elif msg["type"] == "error": - await self.push_frame(TTSStoppedFrame()) + await self.push_frame(TTSStoppedFrame(context_id=ctx_id)) await self.stop_all_metrics() await self.push_error(error_msg=f"Error: {msg}") self._context_id = None @@ -590,11 +591,12 @@ class CartesiaTTSService(AudioContextWordTTSService): await self._connect_websocket() @traced_tts - async def run_tts(self, text: str) -> AsyncGenerator[Frame, None]: + async def run_tts(self, text: str, context_id: str) -> AsyncGenerator[Frame, None]: """Generate speech from text using Cartesia's streaming API. Args: text: The text to synthesize into speech. + context_id: The context ID for tracking audio frames. Yields: Frame: Audio frames containing the synthesized speech. @@ -607,8 +609,8 @@ class CartesiaTTSService(AudioContextWordTTSService): if not self._context_id: await self.start_ttfb_metrics() - yield TTSStartedFrame() - self._context_id = str(uuid.uuid4()) + yield TTSStartedFrame(context_id=context_id) + self._context_id = context_id await self.create_audio_context(self._context_id) msg = self._build_msg(text=text) @@ -618,7 +620,7 @@ class CartesiaTTSService(AudioContextWordTTSService): await self.start_tts_usage_metrics(text) except Exception as e: yield ErrorFrame(error=f"Unknown error occurred: {e}") - yield TTSStoppedFrame() + yield TTSStoppedFrame(context_id=context_id) await self._disconnect() await self._connect() return @@ -761,11 +763,12 @@ class CartesiaHttpTTSService(TTSService): await self._client.close() @traced_tts - async def run_tts(self, text: str) -> AsyncGenerator[Frame, None]: + async def run_tts(self, text: str, context_id: str) -> AsyncGenerator[Frame, None]: """Generate speech from text using Cartesia's HTTP API. Args: text: The text to synthesize into speech. + context_id: The context ID for tracking audio frames. Yields: Frame: Audio frames containing the synthesized speech. @@ -808,7 +811,7 @@ class CartesiaHttpTTSService(TTSService): if self._settings["pronunciation_dict_id"]: payload["pronunciation_dict_id"] = self._settings["pronunciation_dict_id"] - yield TTSStartedFrame() + yield TTSStartedFrame(context_id=context_id) session = await self._client._get_session() @@ -834,6 +837,7 @@ class CartesiaHttpTTSService(TTSService): audio=audio_data, sample_rate=self.sample_rate, num_channels=1, + context_id=context_id, ) yield frame @@ -842,4 +846,4 @@ class CartesiaHttpTTSService(TTSService): yield ErrorFrame(error=f"Unknown error occurred: {e}") finally: await self.stop_ttfb_metrics() - yield TTSStoppedFrame() + yield TTSStoppedFrame(context_id=context_id) diff --git a/src/pipecat/services/deepgram/tts.py b/src/pipecat/services/deepgram/tts.py index a53ec56d2..12aba4905 100644 --- a/src/pipecat/services/deepgram/tts.py +++ b/src/pipecat/services/deepgram/tts.py @@ -97,6 +97,7 @@ class DeepgramTTSService(WebsocketTTSService): self.set_voice(voice) self._receive_task = None + self._context_id: Optional[str] = None def can_generate_metrics(self) -> bool: """Check if the service can generate metrics. @@ -211,6 +212,7 @@ class DeepgramTTSService(WebsocketTTSService): logger.error(f"{self} exception: {e}") await self.push_error(ErrorFrame(error=f"{self} error: {e}")) finally: + self._context_id = None self._websocket = None await self._call_event_handler("on_disconnected") @@ -242,7 +244,7 @@ class DeepgramTTSService(WebsocketTTSService): if isinstance(message, bytes): # Binary message contains audio data await self.stop_ttfb_metrics() - frame = TTSAudioRawFrame(message, self.sample_rate, 1) + frame = TTSAudioRawFrame(message, self.sample_rate, 1, context_id=self._context_id) await self.push_frame(frame) elif isinstance(message, str): # Text message contains metadata or control messages @@ -283,11 +285,12 @@ class DeepgramTTSService(WebsocketTTSService): logger.error(f"{self} error sending Flush message: {e}") @traced_tts - async def run_tts(self, text: str) -> AsyncGenerator[Frame, None]: + async def run_tts(self, text: str, context_id: str) -> AsyncGenerator[Frame, None]: """Generate speech from text using Deepgram's WebSocket TTS API. Args: text: The text to synthesize into speech. + context_id: The context ID for tracking audio frames. Yields: Frame: Audio frames containing the synthesized speech, plus start/stop frames. @@ -302,7 +305,9 @@ class DeepgramTTSService(WebsocketTTSService): await self.start_ttfb_metrics() await self.start_tts_usage_metrics(text) - yield TTSStartedFrame() + yield TTSStartedFrame(context_id=context_id) + # Store context_id for use in _receive_messages + self._context_id = context_id # Send text message to Deepgram # Note: We don't send Flush here - that should only be sent when the @@ -366,11 +371,12 @@ class DeepgramHttpTTSService(TTSService): return True @traced_tts - async def run_tts(self, text: str) -> AsyncGenerator[Frame, None]: + async def run_tts(self, text: str, context_id: str) -> AsyncGenerator[Frame, None]: """Generate speech from text using Deepgram's TTS API. Args: text: The text to synthesize into speech. + context_id: The context ID for tracking audio frames. Yields: Frame: Audio frames containing the synthesized speech, plus start/stop frames. @@ -404,7 +410,7 @@ class DeepgramHttpTTSService(TTSService): raise Exception(f"HTTP {response.status}: {error_text}") await self.start_tts_usage_metrics(text) - yield TTSStartedFrame() + yield TTSStartedFrame(context_id=context_id) CHUNK_SIZE = self.chunk_size @@ -419,9 +425,10 @@ class DeepgramHttpTTSService(TTSService): audio=chunk, sample_rate=self.sample_rate, num_channels=1, + context_id=context_id, ) - yield TTSStoppedFrame() + yield TTSStoppedFrame(context_id=context_id) except Exception as e: yield ErrorFrame(f"Error getting audio: {str(e)}") diff --git a/src/pipecat/services/elevenlabs/tts.py b/src/pipecat/services/elevenlabs/tts.py index 02ccd0ab3..4dab0c01a 100644 --- a/src/pipecat/services/elevenlabs/tts.py +++ b/src/pipecat/services/elevenlabs/tts.py @@ -13,7 +13,6 @@ with support for streaming audio, word timestamps, and voice customization. import asyncio import base64 import json -import uuid from typing import Any, AsyncGenerator, Dict, List, Literal, Mapping, Optional, Tuple, Union import aiohttp @@ -337,9 +336,6 @@ class ElevenLabsTTSService(AudioContextWordTTSService): self._voice_settings = self._set_voice_settings() self._pronunciation_dictionary_locators = params.pronunciation_dictionary_locators - # Indicates if we have sent TTSStartedFrame. It will reset to False when - # there's an interruption or TTSStoppedFrame. - self._started = False self._cumulative_time = 0 # Track partial words that span across alignment chunks self._partial_word = "" @@ -426,7 +422,6 @@ class ElevenLabsTTSService(AudioContextWordTTSService): except Exception as e: await self.push_error(error_msg=f"Unknown error occurred: {e}", exception=e) self._context_id = None - self._started = False async def start(self, frame: StartFrame): """Start the ElevenLabs TTS service. @@ -473,9 +468,8 @@ class ElevenLabsTTSService(AudioContextWordTTSService): """ await super().push_frame(frame, direction) if isinstance(frame, (TTSStoppedFrame, InterruptionFrame)): - self._started = False if isinstance(frame, TTSStoppedFrame): - await self.add_word_timestamps([("Reset", 0)]) + await self.add_word_timestamps([("Reset", 0)], self._context_id) async def _connect(self): await super()._connect() @@ -557,7 +551,6 @@ class ElevenLabsTTSService(AudioContextWordTTSService): except Exception as e: await self.push_error(error_msg=f"Unknown error occurred: {e}", exception=e) finally: - self._started = False self._context_id = None self._websocket = None await self._call_event_handler("on_disconnected") @@ -587,7 +580,6 @@ class ElevenLabsTTSService(AudioContextWordTTSService): except Exception as e: await self.push_error(error_msg=f"Unknown error occurred: {e}", exception=e) self._context_id = None - self._started = False self._partial_word = "" self._partial_word_start_time = 0.0 @@ -624,7 +616,7 @@ class ElevenLabsTTSService(AudioContextWordTTSService): await self.start_word_timestamps() audio = base64.b64decode(msg["audio"]) - frame = TTSAudioRawFrame(audio, self.sample_rate, 1) + frame = TTSAudioRawFrame(audio, self.sample_rate, 1, context_id=received_ctx_id) await self.append_to_audio_context(received_ctx_id, frame) if msg.get("alignment"): @@ -639,7 +631,7 @@ class ElevenLabsTTSService(AudioContextWordTTSService): ) if word_times: - await self.add_word_timestamps(word_times) + await self.add_word_timestamps(word_times, received_ctx_id) # Calculate the actual end time of this audio chunk char_start_times_ms = alignment.get("charStartTimesMs", []) @@ -689,11 +681,12 @@ class ElevenLabsTTSService(AudioContextWordTTSService): await self._websocket.send(json.dumps(msg)) @traced_tts - async def run_tts(self, text: str) -> AsyncGenerator[Frame, None]: + async def run_tts(self, text: str, context_id: str) -> AsyncGenerator[Frame, None]: """Generate speech from text using ElevenLabs' streaming WebSocket API. Args: text: The text to synthesize into speech. + context_id: The context ID for tracking audio frames. Yields: Frame: Audio frames containing the synthesized speech. @@ -705,41 +698,37 @@ class ElevenLabsTTSService(AudioContextWordTTSService): await self._connect() try: - if not self._started: - await self.start_ttfb_metrics() - yield TTSStartedFrame() - self._started = True - self._cumulative_time = 0 - self._partial_word = "" - self._partial_word_start_time = 0.0 - # If a context ID does not exist, create a new one and - # register it. If an ID exists, that means the Pipeline - # doesn't allow user interruptions, so continue using the - # current ID. When interruptions are allowed, user speech - # results in an interruption, which resets the context ID. - if not self._context_id: - self._context_id = str(uuid.uuid4()) - if not self.audio_context_available(self._context_id): - await self.create_audio_context(self._context_id) + await self.start_ttfb_metrics() + yield TTSStartedFrame(context_id=context_id) + self._cumulative_time = 0 + self._partial_word = "" + self._partial_word_start_time = 0.0 + # If a context ID does not exist, use the provided one. + # If an ID exists, that means the Pipeline doesn't allow + # user interruptions, so continue using the current ID. + # When interruptions are allowed, user speech results in + # an interruption, which resets the context ID. + if not self._context_id: + self._context_id = context_id + if not self.audio_context_available(self._context_id): + await self.create_audio_context(self._context_id) - # Initialize context with voice settings and pronunciation dictionaries - msg = {"text": " ", "context_id": self._context_id} - if self._voice_settings: - msg["voice_settings"] = self._voice_settings - if self._pronunciation_dictionary_locators: - msg["pronunciation_dictionary_locators"] = [ - locator.model_dump() - for locator in self._pronunciation_dictionary_locators - ] - await self._websocket.send(json.dumps(msg)) - logger.trace(f"Created new context {self._context_id}") + # Initialize context with voice settings and pronunciation dictionaries + msg = {"text": " ", "context_id": self._context_id} + if self._voice_settings: + msg["voice_settings"] = self._voice_settings + if self._pronunciation_dictionary_locators: + msg["pronunciation_dictionary_locators"] = [ + locator.model_dump() for locator in self._pronunciation_dictionary_locators + ] + await self._websocket.send(json.dumps(msg)) + logger.trace(f"Created new context {self._context_id}") await self._send_text(text) await self.start_tts_usage_metrics(text) except Exception as e: - yield TTSStoppedFrame() + yield TTSStoppedFrame(context_id=context_id) yield ErrorFrame(error=f"Unknown error occurred: {e}") - self._started = False return yield None except Exception as e: @@ -840,7 +829,6 @@ class ElevenLabsHttpTTSService(WordTTSService): # Track cumulative time to properly sequence word timestamps across utterances self._cumulative_time = 0 - self._started = False # Store previous text for context within a turn self._previous_text = "" @@ -879,7 +867,6 @@ class ElevenLabsHttpTTSService(WordTTSService): def _reset_state(self): """Reset internal state variables.""" self._cumulative_time = 0 - self._started = False self._previous_text = "" self._partial_word = "" self._partial_word_start_time = 0.0 @@ -976,7 +963,7 @@ class ElevenLabsHttpTTSService(WordTTSService): return word_times @traced_tts - async def run_tts(self, text: str) -> AsyncGenerator[Frame, None]: + async def run_tts(self, text: str, context_id: str) -> AsyncGenerator[Frame, None]: """Generate speech from text using ElevenLabs streaming API with timestamps. Makes a request to the ElevenLabs API to generate audio and timing data. @@ -985,6 +972,7 @@ class ElevenLabsHttpTTSService(WordTTSService): Args: text: Text to convert to speech. + context_id: The context ID for tracking audio frames. Yields: Frame: Audio and control frames containing the synthesized speech. @@ -1048,11 +1036,9 @@ class ElevenLabsHttpTTSService(WordTTSService): await self.start_tts_usage_metrics(text) - # Start TTS sequence if not already started - if not self._started: - await self.start_word_timestamps() - yield TTSStartedFrame() - self._started = True + # Start TTS sequence + await self.start_word_timestamps() + yield TTSStartedFrame(context_id=context_id) # Track the duration of this utterance based on the last character's end time utterance_duration = 0 @@ -1069,7 +1055,9 @@ class ElevenLabsHttpTTSService(WordTTSService): if data and "audio_base64" in data: await self.stop_ttfb_metrics() audio = base64.b64decode(data["audio_base64"]) - yield TTSAudioRawFrame(audio, self.sample_rate, 1) + yield TTSAudioRawFrame( + audio, self.sample_rate, 1, context_id=context_id + ) # Process alignment if present if data and "alignment" in data: @@ -1085,7 +1073,7 @@ class ElevenLabsHttpTTSService(WordTTSService): # Calculate word timestamps word_times = self.calculate_word_times(alignment) if word_times: - await self.add_word_timestamps(word_times) + await self.add_word_timestamps(word_times, context_id) except json.JSONDecodeError as e: logger.warning(f"Failed to parse JSON from stream: {e}") continue @@ -1097,7 +1085,7 @@ class ElevenLabsHttpTTSService(WordTTSService): # since this is the end of the utterance if self._partial_word: final_word_time = [(self._partial_word, self._partial_word_start_time)] - await self.add_word_timestamps(final_word_time) + await self.add_word_timestamps(final_word_time, context_id) self._partial_word = "" self._partial_word_start_time = 0.0 diff --git a/src/pipecat/services/fish/tts.py b/src/pipecat/services/fish/tts.py index 357b82346..93a718429 100644 --- a/src/pipecat/services/fish/tts.py +++ b/src/pipecat/services/fish/tts.py @@ -135,7 +135,6 @@ class FishAudioTTSService(InterruptibleTTSService): self._websocket = None self._receive_task = None self._request_id = None - self._started = False self._settings = { "sample_rate": 0, @@ -249,7 +248,6 @@ class FishAudioTTSService(InterruptibleTTSService): await self.push_error(error_msg=f"Unknown error occurred: {e}", exception=e) finally: self._request_id = None - self._started = False self._websocket = None await self._call_event_handler("on_disconnected") @@ -291,11 +289,12 @@ class FishAudioTTSService(InterruptibleTTSService): await self.push_error(error_msg=f"Unknown error occurred: {e}", exception=e) @traced_tts - async def run_tts(self, text: str) -> AsyncGenerator[Frame, None]: + async def run_tts(self, text: str, context_id: str) -> AsyncGenerator[Frame, None]: """Generate speech from text using Fish Audio's streaming API. Args: text: The text to synthesize into speech. + context_id: The context ID for tracking audio frames. Yields: Frame: Audio frames and control frames for the synthesized speech. @@ -308,7 +307,7 @@ class FishAudioTTSService(InterruptibleTTSService): if not self._request_id: await self.start_ttfb_metrics() await self.start_tts_usage_metrics(text) - yield TTSStartedFrame() + yield TTSStartedFrame(context_id=context_id) self._request_id = str(uuid.uuid4()) # Send the text @@ -325,7 +324,7 @@ class FishAudioTTSService(InterruptibleTTSService): await self._get_websocket().send(ormsgpack.packb(flush_message)) except Exception as e: yield ErrorFrame(error=f"Unknown error occurred: {e}") - yield TTSStoppedFrame() + yield TTSStoppedFrame(context_id=context_id) await self._disconnect() await self._connect() diff --git a/src/pipecat/services/google/tts.py b/src/pipecat/services/google/tts.py index 2c22fb9c5..4016286df 100644 --- a/src/pipecat/services/google/tts.py +++ b/src/pipecat/services/google/tts.py @@ -682,11 +682,12 @@ class GoogleHttpTTSService(TTSService): return ssml @traced_tts - async def run_tts(self, text: str) -> AsyncGenerator[Frame, None]: + async def run_tts(self, text: str, context_id: str) -> AsyncGenerator[Frame, None]: """Generate speech from text using Google's HTTP TTS API. Args: text: The text to synthesize into speech. + context_id: The context ID for tracking audio frames. Yields: Frame: Audio frames containing the synthesized speech. @@ -731,7 +732,7 @@ class GoogleHttpTTSService(TTSService): await self.start_tts_usage_metrics(text) - yield TTSStartedFrame() + yield TTSStartedFrame(context_id=context_id) # Skip the first 44 bytes to remove the WAV header audio_content = response.audio_content[44:] @@ -743,10 +744,10 @@ class GoogleHttpTTSService(TTSService): if not chunk: break await self.stop_ttfb_metrics() - frame = TTSAudioRawFrame(chunk, self.sample_rate, 1) + frame = TTSAudioRawFrame(chunk, self.sample_rate, 1, context_id=context_id) yield frame - yield TTSStoppedFrame() + yield TTSStoppedFrame(context_id=context_id) except Exception as e: error_message = f"TTS generation error: {str(e)}" @@ -828,6 +829,7 @@ class GoogleBaseTTSService(TTSService): self, streaming_config: texttospeech_v1.StreamingSynthesizeConfig, text: str, + context_id: str, prompt: Optional[str] = None, ) -> AsyncGenerator[Frame, None]: """Shared streaming synthesis logic. @@ -835,6 +837,7 @@ class GoogleBaseTTSService(TTSService): Args: streaming_config: The streaming configuration. text: The text to synthesize. + context_id: Unique identifier for this TTS context. prompt: Optional prompt for style instructions (Gemini only). Yields: @@ -856,7 +859,7 @@ class GoogleBaseTTSService(TTSService): streaming_responses = await self._client.streaming_synthesize(request_generator()) await self.start_tts_usage_metrics(text) - yield TTSStartedFrame() + yield TTSStartedFrame(context_id=context_id) audio_buffer = b"" first_chunk_for_ttfb = False @@ -876,12 +879,12 @@ class GoogleBaseTTSService(TTSService): while len(audio_buffer) >= CHUNK_SIZE: piece = audio_buffer[:CHUNK_SIZE] audio_buffer = audio_buffer[CHUNK_SIZE:] - yield TTSAudioRawFrame(piece, self.sample_rate, 1) + yield TTSAudioRawFrame(piece, self.sample_rate, 1, context_id=context_id) if audio_buffer: - yield TTSAudioRawFrame(audio_buffer, self.sample_rate, 1) + yield TTSAudioRawFrame(audio_buffer, self.sample_rate, 1, context_id=context_id) - yield TTSStoppedFrame() + yield TTSStoppedFrame(context_id=context_id) class GoogleTTSService(GoogleBaseTTSService): @@ -976,11 +979,12 @@ class GoogleTTSService(GoogleBaseTTSService): await super()._update_settings(settings) @traced_tts - async def run_tts(self, text: str) -> AsyncGenerator[Frame, None]: + async def run_tts(self, text: str, context_id: str) -> AsyncGenerator[Frame, None]: """Generate streaming speech from text using Google's streaming API. Args: text: The text to synthesize into speech. + context_id: The context ID for tracking audio frames. Yields: Frame: Audio frames containing the synthesized speech as it's generated. @@ -1014,7 +1018,7 @@ class GoogleTTSService(GoogleBaseTTSService): ) # Use base class streaming logic - async for frame in self._stream_tts(streaming_config, text): + async for frame in self._stream_tts(streaming_config, text, context_id): yield frame except Exception as e: @@ -1213,11 +1217,12 @@ class GeminiTTSService(GoogleBaseTTSService): await super()._update_settings(settings) @traced_tts - async def run_tts(self, text: str) -> AsyncGenerator[Frame, None]: + async def run_tts(self, text: str, context_id: str) -> AsyncGenerator[Frame, None]: """Generate streaming speech from text using Gemini TTS models. Args: - text: The text to synthesize into speech. Can include markup tags + text: The text to synthesize into speech. + context_id: The context ID for tracking audio frames. Can include markup tags like [sigh], [laughing], [whispering] for expressive control. Yields: @@ -1267,7 +1272,9 @@ class GeminiTTSService(GoogleBaseTTSService): ) # Use base class streaming logic with prompt support - async for frame in self._stream_tts(streaming_config, text, self._settings["prompt"]): + async for frame in self._stream_tts( + streaming_config, text, context_id, self._settings["prompt"] + ): yield frame except Exception as e: diff --git a/src/pipecat/services/gradium/tts.py b/src/pipecat/services/gradium/tts.py index df33753ce..0e9865cf0 100644 --- a/src/pipecat/services/gradium/tts.py +++ b/src/pipecat/services/gradium/tts.py @@ -95,6 +95,7 @@ class GradiumTTSService(InterruptibleWordTTSService): # State tracking self._receive_task = None + self._current_context_id: Optional[str] = None def can_generate_metrics(self) -> bool: """Check if this service can generate processing metrics. @@ -261,11 +262,15 @@ class GradiumTTSService(InterruptibleWordTTSService): audio=base64.b64decode(msg["audio"]), sample_rate=self.sample_rate, num_channels=1, + context_id=self._current_context_id, ) await self.push_frame(frame) elif msg["type"] == "text": - await self.add_word_timestamps([(msg["text"], msg["start_s"])]) + if self._current_context_id: + await self.add_word_timestamps( + [(msg["text"], msg["start_s"])], self._current_context_id + ) elif msg["type"] == "end_of_stream": await self.push_frame(TTSStoppedFrame()) await self.stop_all_metrics() @@ -285,11 +290,12 @@ class GradiumTTSService(InterruptibleWordTTSService): await super().push_frame(frame, direction) @traced_tts - async def run_tts(self, text: str) -> AsyncGenerator[Frame, None]: + async def run_tts(self, text: str, context_id: str) -> AsyncGenerator[Frame, None]: """Generate speech from text using Gradium's streaming API. Args: text: The text to convert to speech. + context_id: Unique identifier for this TTS context. Yields: Frame: Audio frames containing the synthesized speech. @@ -302,14 +308,15 @@ class GradiumTTSService(InterruptibleWordTTSService): await self._connect() try: - yield TTSStartedFrame() + self._current_context_id = context_id + yield TTSStartedFrame(context_id=context_id) msg = self._build_msg(text=text) await self._get_websocket().send(json.dumps(msg)) await self.start_tts_usage_metrics(text) except Exception as e: yield ErrorFrame(error=f"Unknown error occurred: {e}") - yield TTSStoppedFrame() + yield TTSStoppedFrame(context_id=context_id) await self._disconnect() await self._connect() return diff --git a/src/pipecat/services/groq/tts.py b/src/pipecat/services/groq/tts.py index e66dc07e7..331af8eb7 100644 --- a/src/pipecat/services/groq/tts.py +++ b/src/pipecat/services/groq/tts.py @@ -112,11 +112,12 @@ class GroqTTSService(TTSService): return True @traced_tts - async def run_tts(self, text: str) -> AsyncGenerator[Frame, None]: + async def run_tts(self, text: str, context_id: str) -> AsyncGenerator[Frame, None]: """Generate speech from text using Groq's TTS API. Args: text: The text to synthesize into speech. + context_id: The context ID for tracking audio frames. Yields: Frame: Audio frames containing the synthesized speech data. @@ -124,7 +125,7 @@ class GroqTTSService(TTSService): logger.debug(f"{self}: Generating TTS [{text}]") measuring_ttfb = True await self.start_ttfb_metrics() - yield TTSStartedFrame() + yield TTSStartedFrame(context_id=context_id) try: response = await self._client.audio.speech.create( @@ -144,8 +145,8 @@ class GroqTTSService(TTSService): frame_rate = w.getframerate() num_frames = w.getnframes() bytes = w.readframes(num_frames) - yield TTSAudioRawFrame(bytes, frame_rate, channels) + yield TTSAudioRawFrame(bytes, frame_rate, channels, context_id=context_id) except Exception as e: yield ErrorFrame(error=f"Unknown error occurred: {e}") - yield TTSStoppedFrame() + yield TTSStoppedFrame(context_id=context_id) diff --git a/src/pipecat/services/hathora/tts.py b/src/pipecat/services/hathora/tts.py index e59c4ad46..80cbd4fe8 100644 --- a/src/pipecat/services/hathora/tts.py +++ b/src/pipecat/services/hathora/tts.py @@ -115,11 +115,12 @@ class HathoraTTSService(TTSService): return True @traced_tts - async def run_tts(self, text: str) -> AsyncGenerator[Frame, None]: + async def run_tts(self, text: str, context_id: str) -> AsyncGenerator[Frame, None]: """Run text-to-speech synthesis on the provided text. Args: text: The text to synthesize into speech. + context_id: The context ID for tracking audio frames. Yields: Frame: Audio frames containing the synthesized speech. @@ -142,7 +143,7 @@ class HathoraTTSService(TTSService): for option in self._settings["config"] ] - yield TTSStartedFrame() + yield TTSStartedFrame(context_id=context_id) async with aiohttp.ClientSession() as session: async with session.post( @@ -161,6 +162,7 @@ class HathoraTTSService(TTSService): audio=pcm_audio, sample_rate=self.sample_rate, num_channels=num_channels, + context_id=context_id, ) yield frame @@ -170,4 +172,4 @@ class HathoraTTSService(TTSService): finally: await self.stop_ttfb_metrics() await self.stop_processing_metrics() - yield TTSStoppedFrame() + yield TTSStoppedFrame(context_id=context_id) diff --git a/src/pipecat/services/hume/tts.py b/src/pipecat/services/hume/tts.py index 7f8943816..2d98e1f8c 100644 --- a/src/pipecat/services/hume/tts.py +++ b/src/pipecat/services/hume/tts.py @@ -209,11 +209,12 @@ class HumeTTSService(WordTTSService): await super().update_setting(key, value) @traced_tts - async def run_tts(self, text: str) -> AsyncGenerator[Frame, None]: + async def run_tts(self, text: str, context_id: str) -> AsyncGenerator[Frame, None]: """Generate speech from text using Hume TTS with word timestamps. Args: text: The text to be synthesized. + context_id: Unique identifier for this TTS context. Returns: An async generator that yields `Frame` objects, including @@ -245,7 +246,7 @@ class HumeTTSService(WordTTSService): # Start TTS sequence if not already started if not self._started: await self.start_word_timestamps() - yield TTSStartedFrame() + yield TTSStartedFrame(context_id=context_id) self._started = True try: @@ -281,6 +282,7 @@ class HumeTTSService(WordTTSService): audio=self._audio_bytes, sample_rate=self.sample_rate, num_channels=1, + context_id=context_id, ) yield frame self._audio_bytes = b"" @@ -297,7 +299,9 @@ class HumeTTSService(WordTTSService): utterance_duration = max(utterance_duration, word_end_time) # Add word timestamp - await self.add_word_timestamps([(timestamp.text, word_start_time)]) + await self.add_word_timestamps( + [(timestamp.text, word_start_time)], context_id + ) # Flush any remaining audio bytes if self._audio_bytes: @@ -305,6 +309,7 @@ class HumeTTSService(WordTTSService): audio=self._audio_bytes, sample_rate=self.sample_rate, num_channels=1, + context_id=context_id, ) yield frame diff --git a/src/pipecat/services/inworld/tts.py b/src/pipecat/services/inworld/tts.py index d8798b75e..2ea94399b 100644 --- a/src/pipecat/services/inworld/tts.py +++ b/src/pipecat/services/inworld/tts.py @@ -16,7 +16,6 @@ Inworld’s text-to-speech (TTS) models offer ultra-realistic, context-aware spe import asyncio import base64 import json -import uuid from typing import Any, AsyncGenerator, Dict, List, Optional, Tuple import aiohttp @@ -125,7 +124,6 @@ class InworldHttpTTSService(WordTTSService): if params.speaking_rate is not None: self._settings["audioConfig"]["speakingRate"] = params.speaking_rate - self._started = False self._cumulative_time = 0.0 self.set_voice(voice_id) @@ -173,7 +171,6 @@ class InworldHttpTTSService(WordTTSService): """ await super().push_frame(frame, direction) if isinstance(frame, (InterruptionFrame, TTSStoppedFrame)): - self._started = False self._cumulative_time = 0.0 if isinstance(frame, TTSStoppedFrame): await self.add_word_timestamps([("Reset", 0)]) @@ -214,11 +211,12 @@ class InworldHttpTTSService(WordTTSService): return (word_times, chunk_end_time) @traced_tts - async def run_tts(self, text: str) -> AsyncGenerator[Frame, None]: + async def run_tts(self, text: str, context_id: str) -> AsyncGenerator[Frame, None]: """Generate TTS audio for the given text. Args: text: The text to generate TTS audio for. + context_id: Unique identifier for this TTS context. Returns: An asynchronous generator of frames. @@ -246,10 +244,8 @@ class InworldHttpTTSService(WordTTSService): try: await self.start_ttfb_metrics() - if not self._started: - await self.start_word_timestamps() - yield TTSStartedFrame() - self._started = True + await self.start_word_timestamps() + yield TTSStartedFrame(context_id=context_id) async with self._session.post( self._base_url, json=payload, headers=headers @@ -261,10 +257,10 @@ class InworldHttpTTSService(WordTTSService): return if self._streaming: - async for frame in self._process_streaming_response(response): + async for frame in self._process_streaming_response(response, context_id): yield frame else: - async for frame in self._process_non_streaming_response(response): + async for frame in self._process_non_streaming_response(response, context_id): yield frame await self.start_tts_usage_metrics(text) @@ -276,12 +272,13 @@ class InworldHttpTTSService(WordTTSService): await self.stop_all_metrics() async def _process_streaming_response( - self, response: aiohttp.ClientResponse + self, response: aiohttp.ClientResponse, context_id: str ) -> AsyncGenerator[Frame, None]: """Process a streaming response from the Inworld API. Args: response: The response from the Inworld API. + context_id: Unique identifier for this TTS context. Yields: An asynchronous generator of frames. @@ -306,7 +303,7 @@ class InworldHttpTTSService(WordTTSService): if "result" in chunk_data and "audioContent" in chunk_data["result"]: await self.stop_ttfb_metrics() async for frame in self._process_audio_chunk( - base64.b64decode(chunk_data["result"]["audioContent"]) + base64.b64decode(chunk_data["result"]["audioContent"]), context_id ): yield frame @@ -314,7 +311,7 @@ class InworldHttpTTSService(WordTTSService): timestamp_info = chunk_data["result"]["timestampInfo"] word_times, chunk_end_time = self._calculate_word_times(timestamp_info) if word_times: - await self.add_word_timestamps(word_times) + await self.add_word_timestamps(word_times, context_id) # Track the maximum end time across all chunks utterance_duration = max(utterance_duration, chunk_end_time) @@ -327,12 +324,13 @@ class InworldHttpTTSService(WordTTSService): self._cumulative_time += utterance_duration async def _process_non_streaming_response( - self, response: aiohttp.ClientResponse + self, response: aiohttp.ClientResponse, context_id: str ) -> AsyncGenerator[Frame, None]: """Process a non-streaming response from the Inworld API. Args: response: The response from the Inworld API. + context_id: Unique identifier for this TTS context. Returns: An asynchronous generator of frames. @@ -349,7 +347,7 @@ class InworldHttpTTSService(WordTTSService): timestamp_info = response_data["timestampInfo"] word_times, chunk_end_time = self._calculate_word_times(timestamp_info) if word_times: - await self.add_word_timestamps(word_times) + await self.add_word_timestamps(word_times, context_id) utterance_duration = chunk_end_time audio_data = base64.b64decode(response_data["audioContent"]) @@ -363,20 +361,21 @@ class InworldHttpTTSService(WordTTSService): if chunk: await self.stop_ttfb_metrics() yield TTSAudioRawFrame( - audio=chunk, - sample_rate=self.sample_rate, - num_channels=1, + audio=chunk, sample_rate=self.sample_rate, num_channels=1, context_id=context_id ) # After processing all audio, add the utterance duration to cumulative time if utterance_duration > 0: self._cumulative_time += utterance_duration - async def _process_audio_chunk(self, audio_chunk: bytes) -> AsyncGenerator[Frame, None]: + async def _process_audio_chunk( + self, audio_chunk: bytes, context_id: str + ) -> AsyncGenerator[Frame, None]: """Process an audio chunk from the Inworld API. Args: audio_chunk: The audio chunk to process. + context_id: Unique identifier for this TTS context. Returns: An asynchronous generator of frames. @@ -394,6 +393,7 @@ class InworldHttpTTSService(WordTTSService): audio=audio_data, sample_rate=self.sample_rate, num_channels=1, + context_id=context_id, ) @@ -500,7 +500,6 @@ class InworldTTSService(AudioContextWordTTSService): self._receive_task = None self._keepalive_task = None self._context_id = None - self._started = False # Track cumulative time across generations for monotonic timestamps within a turn. # When auto_mode is enabled, the server controls generations and timestamps reset @@ -569,7 +568,6 @@ class InworldTTSService(AudioContextWordTTSService): """ await super().push_frame(frame, direction) if isinstance(frame, (TTSStoppedFrame, InterruptionFrame)): - self._started = False logger.trace( f"{self}: Resetting timestamp tracking due to {type(frame).__name__} - " f"cumulative_time was {self._cumulative_time}" @@ -637,7 +635,6 @@ class InworldTTSService(AudioContextWordTTSService): await self.push_error(error_msg=f"Unknown error occurred: {e}", exception=e) self._context_id = None - self._started = False self._cumulative_time = 0.0 self._generation_end_time = 0.0 logger.trace(f"{self}: Interruption handled, context reset to None") @@ -726,7 +723,6 @@ class InworldTTSService(AudioContextWordTTSService): except Exception as e: await self.push_error(error_msg=f"Unknown error occurred: {e}", exception=e) finally: - self._started = False self._context_id = None self._websocket = None self._cumulative_time = 0.0 @@ -801,7 +797,7 @@ class InworldTTSService(AudioContextWordTTSService): audio = base64.b64decode(audio_b64) if len(audio) > 44 and audio.startswith(b"RIFF"): audio = audio[44:] - frame = TTSAudioRawFrame(audio, self.sample_rate, 1) + frame = TTSAudioRawFrame(audio, self.sample_rate, 1, context_id=ctx_id) if ctx_id: await self.append_to_audio_context(ctx_id, frame) @@ -811,7 +807,7 @@ class InworldTTSService(AudioContextWordTTSService): if timestamp_info: word_times = self._calculate_word_times(timestamp_info) if word_times: - await self.add_word_timestamps(word_times) + await self.add_word_timestamps(word_times, ctx_id) # Handle context created confirmation if "contextCreated" in result: @@ -832,10 +828,9 @@ class InworldTTSService(AudioContextWordTTSService): # Only reset if this is our current context if ctx_id == self._context_id: self._context_id = None - self._started = False if ctx_id and self.audio_context_available(ctx_id): await self.remove_audio_context(ctx_id) - await self.add_word_timestamps([("TTSStoppedFrame", 0), ("Reset", 0)]) + await self.add_word_timestamps([("TTSStoppedFrame", 0), ("Reset", 0)], ctx_id) async def _keepalive_task_handler(self): """Send periodic keepalive messages to maintain WebSocket connection.""" @@ -917,11 +912,12 @@ class InworldTTSService(AudioContextWordTTSService): await self.send_with_retry(json.dumps(msg), self._report_error) @traced_tts - async def run_tts(self, text: str) -> AsyncGenerator[Frame, None]: + async def run_tts(self, text: str, context_id: str) -> AsyncGenerator[Frame, None]: """Generate TTS audio for the given text using the Inworld WebSocket TTS service. Args: text: The text to generate TTS audio for. + context_id: Unique identifier for this TTS context. Returns: An asynchronous generator of frames. @@ -933,28 +929,25 @@ class InworldTTSService(AudioContextWordTTSService): await self._connect() try: - if not self._started: - await self.start_ttfb_metrics() - yield TTSStartedFrame() - self._started = True + await self.start_ttfb_metrics() + yield TTSStartedFrame(context_id=context_id) - if not self._context_id: - self._context_id = str(uuid.uuid4()) - logger.trace(f"{self}: Creating new context {self._context_id}") - await self.create_audio_context(self._context_id) - await self._send_context(self._context_id) - elif not self.audio_context_available(self._context_id): - # Context exists on server but local tracking was removed - logger.trace(f"{self}: Recreating local audio context {self._context_id}") - await self.create_audio_context(self._context_id) + if not self._context_id: + self._context_id = context_id + logger.trace(f"{self}: Creating new context {self._context_id}") + await self.create_audio_context(self._context_id) + await self._send_context(self._context_id) + elif not self.audio_context_available(self._context_id): + # Context exists on server but local tracking was removed + logger.trace(f"{self}: Recreating local audio context {self._context_id}") + await self.create_audio_context(self._context_id) await self._send_text(self._context_id, text) await self.start_tts_usage_metrics(text) except Exception as e: yield ErrorFrame(error=f"Unknown error occurred: {e}") - yield TTSStoppedFrame() - self._started = False + yield TTSStoppedFrame(context_id=context_id) return yield None except Exception as e: diff --git a/src/pipecat/services/kokoro/tts.py b/src/pipecat/services/kokoro/tts.py index b4d309a3f..49ede2409 100644 --- a/src/pipecat/services/kokoro/tts.py +++ b/src/pipecat/services/kokoro/tts.py @@ -143,13 +143,14 @@ class KokoroTTSService(TTSService): return True @traced_tts - async def run_tts(self, text: str) -> AsyncGenerator[Frame, None]: + async def run_tts(self, text: str, context_id: str) -> AsyncGenerator[Frame, None]: """Synthesize speech from text using kokoro-onnx. Uses the async streaming API to generate audio frames. Args: text: The text to synthesize. + context_id: Unique identifier for this TTS context. """ logger.debug(f"{self}: Generating TTS [{text}]") @@ -157,7 +158,7 @@ class KokoroTTSService(TTSService): try: await self.start_ttfb_metrics() await self.start_tts_usage_metrics(text) - yield TTSStartedFrame() + yield TTSStartedFrame(context_id=context_id) stream = self._kokoro.create_stream( text, voice=self._voice_id, lang=self._lang_code, speed=1.0 @@ -172,10 +173,13 @@ class KokoroTTSService(TTSService): ) yield TTSAudioRawFrame( - audio=audio_data, sample_rate=self.sample_rate, num_channels=1 + audio=audio_data, + sample_rate=self.sample_rate, + num_channels=1, + context_id=context_id, ) except Exception as e: yield ErrorFrame(error=f"Unknown error occurred: {e}") finally: await self.stop_ttfb_metrics() - yield TTSStoppedFrame() + yield TTSStoppedFrame(context_id=context_id) diff --git a/src/pipecat/services/lmnt/tts.py b/src/pipecat/services/lmnt/tts.py index 911d13923..4c34e28d5 100644 --- a/src/pipecat/services/lmnt/tts.py +++ b/src/pipecat/services/lmnt/tts.py @@ -113,8 +113,8 @@ class LmntTTSService(InterruptibleTTSService): "language": self.language_to_service_language(language), "format": "raw", # Use raw format for direct PCM data } - self._started = False self._receive_task = None + self._context_id: Optional[str] = None def can_generate_metrics(self) -> bool: """Check if this service can generate processing metrics. @@ -170,8 +170,6 @@ class LmntTTSService(InterruptibleTTSService): direction: The direction to push the frame. """ await super().push_frame(frame, direction) - if isinstance(frame, (TTSStoppedFrame, InterruptionFrame)): - self._started = False async def _connect(self): """Connect to LMNT WebSocket and start receive task.""" @@ -236,7 +234,7 @@ class LmntTTSService(InterruptibleTTSService): except Exception as e: await self.push_error(error_msg=f"Error disconnecting from LMNT: {e}", exception=e) finally: - self._started = False + self._context_id = None self._websocket = None await self._call_event_handler("on_disconnected") @@ -262,6 +260,7 @@ class LmntTTSService(InterruptibleTTSService): audio=message, sample_rate=self.sample_rate, num_channels=1, + context_id=self._context_id, ) await self.push_frame(frame) else: @@ -276,11 +275,12 @@ class LmntTTSService(InterruptibleTTSService): logger.error(f"Invalid JSON message: {message}") @traced_tts - async def run_tts(self, text: str) -> AsyncGenerator[Frame, None]: + async def run_tts(self, text: str, context_id: str) -> AsyncGenerator[Frame, None]: """Generate TTS audio from text using LMNT's streaming API. Args: text: The text to synthesize into speech. + context_id: The context ID for tracking audio frames. Yields: Frame: Audio frames containing the synthesized speech. @@ -292,10 +292,10 @@ class LmntTTSService(InterruptibleTTSService): await self._connect() try: - if not self._started: - await self.start_ttfb_metrics() - yield TTSStartedFrame() - self._started = True + await self.start_ttfb_metrics() + # Store context_id for use in _receive_messages + self._context_id = context_id + yield TTSStartedFrame(context_id=context_id) # Send text to LMNT await self._get_websocket().send(json.dumps({"text": text})) @@ -304,7 +304,7 @@ class LmntTTSService(InterruptibleTTSService): await self.start_tts_usage_metrics(text) except Exception as e: yield ErrorFrame(error=f"Unknown error occurred: {e}") - yield TTSStoppedFrame() + yield TTSStoppedFrame(context_id=context_id) await self._disconnect() await self._connect() return diff --git a/src/pipecat/services/minimax/tts.py b/src/pipecat/services/minimax/tts.py index c3e434361..7284d9630 100644 --- a/src/pipecat/services/minimax/tts.py +++ b/src/pipecat/services/minimax/tts.py @@ -284,11 +284,12 @@ class MiniMaxHttpTTSService(TTSService): logger.debug(f"MiniMax TTS initialized with sample_rate: {self.sample_rate}") @traced_tts - async def run_tts(self, text: str) -> AsyncGenerator[Frame, None]: + async def run_tts(self, text: str, context_id: str) -> AsyncGenerator[Frame, None]: """Generate TTS audio from text using MiniMax's streaming API. Args: text: The text to synthesize into speech. + context_id: The context ID for tracking audio frames. Yields: Frame: Audio frames containing the synthesized speech. @@ -318,7 +319,7 @@ class MiniMaxHttpTTSService(TTSService): return await self.start_tts_usage_metrics(text) - yield TTSStartedFrame() + yield TTSStartedFrame(context_id=context_id) # Process the streaming response buffer = bytearray() @@ -377,6 +378,7 @@ class MiniMaxHttpTTSService(TTSService): audio=audio_chunk, sample_rate=self.sample_rate, num_channels=1, + context_id=context_id, ) except ValueError as e: logger.error( @@ -394,4 +396,4 @@ class MiniMaxHttpTTSService(TTSService): yield ErrorFrame(error=f"Unknown error occurred: {e}", exception=e) finally: await self.stop_ttfb_metrics() - yield TTSStoppedFrame() + yield TTSStoppedFrame(context_id=context_id) diff --git a/src/pipecat/services/neuphonic/tts.py b/src/pipecat/services/neuphonic/tts.py index 2666c0cfc..24eb05bd3 100644 --- a/src/pipecat/services/neuphonic/tts.py +++ b/src/pipecat/services/neuphonic/tts.py @@ -135,13 +135,11 @@ class NeuphonicTTSService(InterruptibleTTSService): } self.set_voice(voice_id) - # Indicates if we have sent TTSStartedFrame. It will reset to False when - # there's an interruption or TTSStoppedFrame. - self._started = False self._cumulative_time = 0 self._receive_task = None self._keepalive_task = None + self._context_id: Optional[str] = None def can_generate_metrics(self) -> bool: """Check if this service can generate processing metrics. @@ -213,8 +211,6 @@ class NeuphonicTTSService(InterruptibleTTSService): direction: The direction to push the frame. """ await super().push_frame(frame, direction) - if isinstance(frame, (TTSStoppedFrame, InterruptionFrame)): - self._started = False async def process_frame(self, frame: Frame, direction: FrameDirection): """Process frames with special handling for speech control. @@ -230,7 +226,7 @@ class NeuphonicTTSService(InterruptibleTTSService): # processing more frames until we receive a BotStoppedSpeakingFrame. if isinstance(frame, TTSSpeakFrame): await self.pause_processing_frames() - elif isinstance(frame, LLMFullResponseEndFrame) and self._started: + elif isinstance(frame, LLMFullResponseEndFrame): await self.pause_processing_frames() elif isinstance(frame, BotStoppedSpeakingFrame): await self.resume_processing_frames() @@ -304,7 +300,7 @@ class NeuphonicTTSService(InterruptibleTTSService): except Exception as e: await self.push_error(error_msg=f"Unknown error occurred: {e}", exception=e) finally: - self._started = False + self._context_id = None self._websocket = None await self._call_event_handler("on_disconnected") @@ -317,7 +313,9 @@ class NeuphonicTTSService(InterruptibleTTSService): await self.stop_ttfb_metrics() audio = base64.b64decode(msg["data"]["audio"]) - frame = TTSAudioRawFrame(audio, self.sample_rate, 1) + frame = TTSAudioRawFrame( + audio, self.sample_rate, 1, context_id=self._context_id + ) await self.push_frame(frame) async def _keepalive_task_handler(self): @@ -342,11 +340,12 @@ class NeuphonicTTSService(InterruptibleTTSService): await self._websocket.send(json.dumps(msg)) @traced_tts - async def run_tts(self, text: str) -> AsyncGenerator[Frame, None]: + async def run_tts(self, text: str, context_id: str) -> AsyncGenerator[Frame, None]: """Generate speech from text using Neuphonic's streaming API. Args: text: The text to synthesize into speech. + context_id: Unique identifier for this TTS context. Yields: Frame: Audio frames containing the synthesized speech. @@ -358,17 +357,17 @@ class NeuphonicTTSService(InterruptibleTTSService): await self._connect() try: - if not self._started: - await self.start_ttfb_metrics() - yield TTSStartedFrame() - self._started = True - self._cumulative_time = 0 + await self.start_ttfb_metrics() + # Store context_id for use in _receive_messages + self._context_id = context_id + yield TTSStartedFrame(context_id=context_id) + self._cumulative_time = 0 await self._send_text(text) await self.start_tts_usage_metrics(text) except Exception as e: yield ErrorFrame(error=f"Unknown error occurred: {e}") - yield TTSStoppedFrame() + yield TTSStoppedFrame(context_id=context_id) await self._disconnect() await self._connect() return @@ -502,11 +501,12 @@ class NeuphonicHttpTTSService(TTSService): return None @traced_tts - async def run_tts(self, text: str) -> AsyncGenerator[Frame, None]: + async def run_tts(self, text: str, context_id: str) -> AsyncGenerator[Frame, None]: """Generate speech from text using Neuphonic streaming API. Args: text: The text to convert to speech. + context_id: Unique identifier for this TTS context. Yields: Frame: Audio frames containing the synthesized speech and status information. @@ -542,7 +542,7 @@ class NeuphonicHttpTTSService(TTSService): return await self.start_tts_usage_metrics(text) - yield TTSStartedFrame() + yield TTSStartedFrame(context_id=context_id) # Process SSE stream line by line async for line in response.content: @@ -564,7 +564,9 @@ class NeuphonicHttpTTSService(TTSService): audio_bytes = base64.b64decode(audio_b64) await self.stop_ttfb_metrics() - yield TTSAudioRawFrame(audio_bytes, self.sample_rate, 1) + yield TTSAudioRawFrame( + audio_bytes, self.sample_rate, 1, context_id=context_id + ) except Exception as e: yield ErrorFrame(error=f"Unknown error occurred: {e}") @@ -578,4 +580,4 @@ class NeuphonicHttpTTSService(TTSService): yield ErrorFrame(error=f"Unknown error occurred: {e}") finally: await self.stop_ttfb_metrics() - yield TTSStoppedFrame() + yield TTSStoppedFrame(context_id=context_id) diff --git a/src/pipecat/services/nvidia/tts.py b/src/pipecat/services/nvidia/tts.py index e90462ad9..6bac54e3a 100644 --- a/src/pipecat/services/nvidia/tts.py +++ b/src/pipecat/services/nvidia/tts.py @@ -153,11 +153,12 @@ class NvidiaTTSService(TTSService): logger.debug(f"Initialized NvidiaTTSService with model: {self.model_name}") @traced_tts - async def run_tts(self, text: str) -> AsyncGenerator[Frame, None]: + async def run_tts(self, text: str, context_id: str) -> AsyncGenerator[Frame, None]: """Generate speech from text using NVIDIA Riva TTS. Args: text: The text to synthesize into speech. + context_id: The context ID for tracking audio frames. Yields: Frame: Audio frames containing the synthesized speech data. @@ -193,7 +194,7 @@ class NvidiaTTSService(TTSService): assert self._config is not None, "Synthesis configuration not created" await self.start_ttfb_metrics() - yield TTSStartedFrame() + yield TTSStartedFrame(context_id=context_id) logger.debug(f"{self}: Generating TTS [{text}]") @@ -205,12 +206,13 @@ class NvidiaTTSService(TTSService): audio=resp.audio, sample_rate=self.sample_rate, num_channels=1, + context_id=context_id, ) yield frame await self.start_tts_usage_metrics(text) - yield TTSStoppedFrame() - except asyncio.TimeoutError: + yield TTSStoppedFrame(context_id=context_id) + except asyncio.TimeoutError as e: logger.error(f"{self} timeout waiting for audio response") yield ErrorFrame(error=f"{self} error: {e}") except Exception as e: diff --git a/src/pipecat/services/openai/tts.py b/src/pipecat/services/openai/tts.py index 444ae883f..f59f0b31b 100644 --- a/src/pipecat/services/openai/tts.py +++ b/src/pipecat/services/openai/tts.py @@ -168,11 +168,12 @@ class OpenAITTSService(TTSService): ) @traced_tts - async def run_tts(self, text: str) -> AsyncGenerator[Frame, None]: + async def run_tts(self, text: str, context_id: str) -> AsyncGenerator[Frame, None]: """Generate speech from text using OpenAI's TTS API. Args: text: The text to synthesize into speech. + context_id: The context ID for tracking audio frames. Yields: Frame: Audio frames containing the synthesized speech data. @@ -212,12 +213,12 @@ class OpenAITTSService(TTSService): CHUNK_SIZE = self.chunk_size - yield TTSStartedFrame() + yield TTSStartedFrame(context_id=context_id) async for chunk in r.iter_bytes(CHUNK_SIZE): if len(chunk) > 0: await self.stop_ttfb_metrics() - frame = TTSAudioRawFrame(chunk, self.sample_rate, 1) + frame = TTSAudioRawFrame(chunk, self.sample_rate, 1, context_id=context_id) yield frame - yield TTSStoppedFrame() + yield TTSStoppedFrame(context_id=context_id) except BadRequestError as e: yield ErrorFrame(error=f"Unknown error occurred: {e}") diff --git a/src/pipecat/services/piper/tts.py b/src/pipecat/services/piper/tts.py index e921447ff..a1a038826 100644 --- a/src/pipecat/services/piper/tts.py +++ b/src/pipecat/services/piper/tts.py @@ -86,11 +86,12 @@ class PiperTTSService(TTSService): return True @traced_tts - async def run_tts(self, text: str) -> AsyncGenerator[Frame, None]: + async def run_tts(self, text: str, context_id: str) -> AsyncGenerator[Frame, None]: """Generate speech from text using Piper. Args: text: The text to convert to speech. + context_id: Unique identifier for this TTS context. Yields: Frame: Audio frames containing the synthesized speech and status frames. @@ -116,11 +117,12 @@ class PiperTTSService(TTSService): await self.start_tts_usage_metrics(text) - yield TTSStartedFrame() + yield TTSStartedFrame(context_id=context_id) async for frame in self._stream_audio_frames_from_iterator( async_iterator(self._voice.synthesize(text)), in_sample_rate=self._voice.config.sample_rate, + context_id=context_id, ): await self.stop_ttfb_metrics() yield frame @@ -130,7 +132,7 @@ class PiperTTSService(TTSService): finally: logger.debug(f"{self}: Finished TTS [{text}]") await self.stop_ttfb_metrics() - yield TTSStoppedFrame() + yield TTSStoppedFrame(context_id=context_id) # This assumes a running TTS service running: @@ -184,11 +186,12 @@ class PiperHttpTTSService(TTSService): return True @traced_tts - async def run_tts(self, text: str) -> AsyncGenerator[Frame, None]: + async def run_tts(self, text: str, context_id: str) -> AsyncGenerator[Frame, None]: """Generate speech from text using Piper's HTTP API. Args: text: The text to convert to speech. + context_id: Unique identifier for this TTS context. Yields: Frame: Audio frames containing the synthesized speech and status frames. @@ -215,12 +218,14 @@ class PiperHttpTTSService(TTSService): await self.start_tts_usage_metrics(text) - yield TTSStartedFrame() + yield TTSStartedFrame(context_id=context_id) CHUNK_SIZE = self.chunk_size async for frame in self._stream_audio_frames_from_iterator( - response.content.iter_chunked(CHUNK_SIZE), strip_wav_header=True + response.content.iter_chunked(CHUNK_SIZE), + strip_wav_header=True, + context_id=context_id, ): await self.stop_ttfb_metrics() yield frame @@ -228,4 +233,4 @@ class PiperHttpTTSService(TTSService): yield ErrorFrame(error=f"Unknown error occurred: {e}") finally: await self.stop_ttfb_metrics() - yield TTSStoppedFrame() + yield TTSStoppedFrame(context_id=context_id) diff --git a/src/pipecat/services/playht/tts.py b/src/pipecat/services/playht/tts.py index bc9dd4859..2d4cd0427 100644 --- a/src/pipecat/services/playht/tts.py +++ b/src/pipecat/services/playht/tts.py @@ -13,7 +13,6 @@ supporting both WebSocket streaming and HTTP-based synthesis. import io import json import struct -import uuid import warnings from typing import AsyncGenerator, Optional @@ -169,7 +168,7 @@ class PlayHTTTSService(InterruptibleTTSService): self._user_id = user_id self._websocket_url = None self._receive_task = None - self._request_id = None + self._context_id = None self._settings = { "language": self.language_to_service_language(params.language) @@ -285,7 +284,7 @@ class PlayHTTTSService(InterruptibleTTSService): except Exception as e: await self.push_error(error_msg=f"Error disconnecting: {e}", exception=e) finally: - self._request_id = None + self._context_id = None self._websocket = None await self._call_event_handler("on_disconnected") @@ -328,7 +327,7 @@ class PlayHTTTSService(InterruptibleTTSService): """Handle interruption by stopping metrics and clearing request ID.""" await super()._handle_interruption(frame, direction) await self.stop_all_metrics() - self._request_id = None + self._context_id = None async def _receive_messages(self): """Receive messages from PlayHT websocket.""" @@ -338,7 +337,7 @@ class PlayHTTTSService(InterruptibleTTSService): if message.startswith(b"RIFF"): continue await self.stop_ttfb_metrics() - frame = TTSAudioRawFrame(message, self.sample_rate, 1) + frame = TTSAudioRawFrame(message, self.sample_rate, 1, context_id=self._context_id) await self.push_frame(frame) else: logger.debug(f"Received text message: {message}") @@ -349,20 +348,21 @@ class PlayHTTTSService(InterruptibleTTSService): logger.debug(f"Started processing request: {msg.get('request_id')}") elif msg.get("type") == "end": # Handle end of stream - if "request_id" in msg and msg["request_id"] == self._request_id: - await self.push_frame(TTSStoppedFrame()) - self._request_id = None + if "request_id" in msg and msg["request_id"] == self._context_id: + await self.push_frame(TTSStoppedFrame(context_id=self._context_id)) + self._context_id = None elif "error" in msg: await self.push_error(error_msg=f"Error: {msg['error']}") except json.JSONDecodeError: logger.error(f"Invalid JSON message: {message}") @traced_tts - async def run_tts(self, text: str) -> AsyncGenerator[Frame, None]: + async def run_tts(self, text: str, context_id: str) -> AsyncGenerator[Frame, None]: """Generate TTS audio from text using PlayHT's WebSocket API. Args: text: The text to synthesize into speech. + context_id: The context ID for tracking audio frames. Yields: Frame: Audio frames containing the synthesized speech. @@ -374,10 +374,10 @@ class PlayHTTTSService(InterruptibleTTSService): if not self._websocket or self._websocket.state is State.CLOSED: await self._connect() - if not self._request_id: + if not self._context_id: await self.start_ttfb_metrics() - yield TTSStartedFrame() - self._request_id = str(uuid.uuid4()) + yield TTSStartedFrame(context_id=context_id) + self._context_id = context_id tts_command = { "text": text, @@ -388,7 +388,7 @@ class PlayHTTTSService(InterruptibleTTSService): "language": self._settings["language"], "speed": self._settings["speed"], "seed": self._settings["seed"], - "request_id": self._request_id, + "request_id": self._context_id, } try: @@ -396,7 +396,7 @@ class PlayHTTTSService(InterruptibleTTSService): await self.start_tts_usage_metrics(text) except Exception as e: yield ErrorFrame(error=f"Unknown error occurred: {e}") - yield TTSStoppedFrame() + yield TTSStoppedFrame(context_id=context_id) await self._disconnect() await self._connect() return @@ -540,11 +540,12 @@ class PlayHTHttpTTSService(TTSService): return language_to_playht_language(language) @traced_tts - async def run_tts(self, text: str) -> AsyncGenerator[Frame, None]: + async def run_tts(self, text: str, context_id: str) -> AsyncGenerator[Frame, None]: """Generate TTS audio from text using PlayHT's HTTP API. Args: text: The text to synthesize into speech. + context_id: The context ID for tracking audio frames. Yields: Frame: Audio frames containing the synthesized speech. @@ -579,7 +580,7 @@ class PlayHTHttpTTSService(TTSService): await self.start_tts_usage_metrics(text) - yield TTSStartedFrame() + yield TTSStartedFrame(context_id=context_id) async with aiohttp.ClientSession() as session: async with session.post( @@ -616,16 +617,20 @@ class PlayHTHttpTTSService(TTSService): audio_data = buffer[fh.tell() :] if len(audio_data) > 0: await self.stop_ttfb_metrics() - frame = TTSAudioRawFrame(audio_data, self.sample_rate, 1) + frame = TTSAudioRawFrame( + audio_data, self.sample_rate, 1, context_id=context_id + ) yield frame in_header = False elif len(chunk) > 0: await self.stop_ttfb_metrics() - frame = TTSAudioRawFrame(chunk, self.sample_rate, 1) + frame = TTSAudioRawFrame( + chunk, self.sample_rate, 1, context_id=context_id + ) yield frame except Exception as e: yield ErrorFrame(error=f"Unknown error occurred: {e}") finally: await self.stop_ttfb_metrics() - yield TTSStoppedFrame() + yield TTSStoppedFrame(context_id=context_id) diff --git a/src/pipecat/services/resembleai/tts.py b/src/pipecat/services/resembleai/tts.py index 21a8c7a78..964b9fa18 100644 --- a/src/pipecat/services/resembleai/tts.py +++ b/src/pipecat/services/resembleai/tts.py @@ -84,9 +84,11 @@ class ResembleAITTSService(AudioContextWordTTSService): self._websocket = None self._request_id_counter = 0 - self._current_request_id = None self._receive_task = None + # Map request_id to context_id for tracking TTS requests + self._request_id_to_context: dict[int, str] = {} + # Per-request audio buffers to handle concurrent TTS requests # ResembleAI may send odd-length data even for PCM_16, so buffering helps us # create properly aligned frames while maintaining smooth audio output @@ -122,7 +124,7 @@ class ResembleAITTSService(AudioContextWordTTSService): "voice_uuid": self._voice_id, "data": text, "binary_response": False, # Use JSON frames to get timestamps - "request_id": self._request_id_counter, + "request_id": self._request_id_counter, # ResembleAI only accepts number "output_format": self._settings["output_format"], "sample_rate": self._settings["sample_rate"], "precision": self._settings["precision"], @@ -202,10 +204,10 @@ class ResembleAITTSService(AudioContextWordTTSService): except Exception as e: await self.push_error(error_msg=f"Unknown error occurred: {e}", exception=e) finally: - self._current_request_id = None self._websocket = None self._audio_buffers.clear() self._playback_started.clear() + self._request_id_to_context.clear() await self._call_event_handler("on_disconnected") def _get_websocket(self): @@ -230,18 +232,12 @@ class ResembleAITTSService(AudioContextWordTTSService): """ await super()._handle_interruption(frame, direction) await self.stop_all_metrics() - # Note: Resemble AI doesn't have an explicit cancel mechanism, - # but we can stop processing by resetting our current request_id - self._current_request_id = None async def flush_audio(self): """Flush any pending audio and finalize the current context.""" - if not self._current_request_id: - return logger.trace(f"{self}: flushing audio") # For Resemble AI, we just wait for the audio_end message # which is handled in _process_messages - self._current_request_id = None async def _process_messages(self): """Process incoming WebSocket messages from Resemble AI.""" @@ -259,10 +255,10 @@ class ResembleAITTSService(AudioContextWordTTSService): request_id = msg.get("request_id") # Convert request_id to string for audio context tracking - request_id_str = str(request_id) + context_id = self._request_id_to_context.get(request_id, str(request_id)) # Check if this message belongs to a valid audio context - if not self.audio_context_available(request_id_str): + if not self.audio_context_available(context_id): continue if msg_type == "audio": @@ -279,20 +275,20 @@ class ResembleAITTSService(AudioContextWordTTSService): continue # Get or create buffer for this request - if request_id_str not in self._audio_buffers: - self._audio_buffers[request_id_str] = bytearray() - self._playback_started[request_id_str] = False - buffer = self._audio_buffers[request_id_str] + if context_id not in self._audio_buffers: + self._audio_buffers[context_id] = bytearray() + self._playback_started[context_id] = False + buffer = self._audio_buffers[context_id] # Add to buffer buffer.extend(audio_bytes) # Wait for jitter buffer to fill before starting playback # This absorbs network latency gaps (ResembleAI sends in bursts) - if not self._playback_started.get(request_id_str, False): + if not self._playback_started.get(context_id, False): if len(buffer) < self._jitter_buffer_bytes: continue - self._playback_started[request_id_str] = True + self._playback_started[context_id] = True # Send complete (even-byte) chunks for PCM_16 alignment while len(buffer) >= self._buffer_threshold_bytes: @@ -301,8 +297,8 @@ class ResembleAITTSService(AudioContextWordTTSService): chunk_size -= 1 chunk_to_send = bytes(buffer[:chunk_size]) - self._audio_buffers[request_id_str] = buffer[chunk_size:] - buffer = self._audio_buffers[request_id_str] + self._audio_buffers[context_id] = buffer[chunk_size:] + buffer = self._audio_buffers[context_id] if len(chunk_to_send) == 0: continue @@ -311,8 +307,9 @@ class ResembleAITTSService(AudioContextWordTTSService): audio=chunk_to_send, sample_rate=self.sample_rate, num_channels=1, + context_id=context_id, ) - await self.append_to_audio_context(request_id_str, frame) + await self.append_to_audio_context(context_id, frame) # Process timestamps if available timestamps = msg.get("audio_timestamps", {}) @@ -328,13 +325,13 @@ class ResembleAITTSService(AudioContextWordTTSService): word_times.append((char, start_time)) if word_times: - await self.add_word_timestamps(word_times) + await self.add_word_timestamps(word_times, context_id) elif msg_type == "audio_end": await self.stop_ttfb_metrics() # Flush remaining buffer, ensuring even length for PCM_16 - buffer = self._audio_buffers.get(request_id_str, bytearray()) + buffer = self._audio_buffers.get(context_id, bytearray()) if buffer: remaining = bytes(buffer) # PCM_16 requires even number of bytes @@ -345,20 +342,21 @@ class ResembleAITTSService(AudioContextWordTTSService): audio=remaining, sample_rate=self.sample_rate, num_channels=1, + context_id=context_id, ) - await self.append_to_audio_context(request_id_str, frame) + await self.append_to_audio_context(context_id, frame) # Clean up buffer and playback tracking for this request - if request_id_str in self._audio_buffers: - del self._audio_buffers[request_id_str] - if request_id_str in self._playback_started: - del self._playback_started[request_id_str] + if context_id in self._audio_buffers: + del self._audio_buffers[context_id] + if context_id in self._playback_started: + del self._playback_started[context_id] + # Clean up request_id mapping + if request_id in self._request_id_to_context: + del self._request_id_to_context[request_id] - await self.add_word_timestamps([("TTSStoppedFrame", 0), ("Reset", 0)]) - await self.remove_audio_context(request_id_str) - # Clear current request if this was it - if self._current_request_id == request_id: - self._current_request_id = None + await self.add_word_timestamps([("TTSStoppedFrame", 0), ("Reset", 0)], context_id) + await self.remove_audio_context(context_id) elif msg_type == "error": error_name = msg.get("error_name", "Unknown") @@ -369,19 +367,15 @@ class ResembleAITTSService(AudioContextWordTTSService): ) # Clean up buffer and playback tracking for this request - if request_id_str in self._audio_buffers: - del self._audio_buffers[request_id_str] - if request_id_str in self._playback_started: - del self._playback_started[request_id_str] + if context_id in self._audio_buffers: + del self._audio_buffers[context_id] + if context_id in self._playback_started: + del self._playback_started[context_id] - await self.push_frame(TTSStoppedFrame()) + await self.push_frame(TTSStoppedFrame(context_id=context_id)) await self.stop_all_metrics() await self.push_error(ErrorFrame(error=f"{self} error: {error_name} - {error_msg}")) - # Clear current request if this was it - if self._current_request_id == request_id: - self._current_request_id = None - # Check if this is an unrecoverable error (connection-level failure) if status_code in [401, 403]: # Close and reconnect for auth errors @@ -402,11 +396,12 @@ class ResembleAITTSService(AudioContextWordTTSService): await self._connect_websocket() @traced_tts - async def run_tts(self, text: str) -> AsyncGenerator[Frame, None]: + async def run_tts(self, text: str, context_id: str) -> AsyncGenerator[Frame, None]: """Generate speech from text using Resemble AI's streaming API. Args: text: The text to synthesize into speech. + context_id: Unique identifier for this TTS context. Yields: Frame: Audio frames containing the synthesized speech. @@ -417,15 +412,13 @@ class ResembleAITTSService(AudioContextWordTTSService): if not self._websocket or self._websocket.state is State.CLOSED: await self._connect() - if not self._current_request_id: - await self.start_ttfb_metrics() - yield TTSStartedFrame() - # Track the current request_id we're processing - self._current_request_id = self._request_id_counter + await self.start_ttfb_metrics() + yield TTSStartedFrame(context_id=context_id) - # Create audio context using request_id (converted to string) - request_id_str = str(self._request_id_counter) - await self.create_audio_context(request_id_str) + # Map request_id to context_id for tracking + self._request_id_to_context[self._request_id_counter] = context_id + + await self.create_audio_context(context_id) msg = self._build_msg(text=text) @@ -434,7 +427,7 @@ class ResembleAITTSService(AudioContextWordTTSService): await self.start_tts_usage_metrics(text) except Exception as e: yield ErrorFrame(error=f"Unknown error occurred: {e}") - yield TTSStoppedFrame() + yield TTSStoppedFrame(context_id=context_id) await self._disconnect() await self._connect() return diff --git a/src/pipecat/services/rime/tts.py b/src/pipecat/services/rime/tts.py index 39f1a626c..e38e840e6 100644 --- a/src/pipecat/services/rime/tts.py +++ b/src/pipecat/services/rime/tts.py @@ -12,7 +12,6 @@ using Rime's API for streaming and batch audio synthesis. import base64 import json -import uuid from typing import Any, AsyncGenerator, Mapping, Optional import aiohttp @@ -387,6 +386,7 @@ class RimeTTSService(AudioContextWordTTSService): if not msg or not self.audio_context_available(msg["contextId"]): continue + context_id = msg["contextId"] if msg["type"] == "chunk": # Process audio chunk await self.stop_ttfb_metrics() @@ -395,8 +395,9 @@ class RimeTTSService(AudioContextWordTTSService): audio=base64.b64decode(msg["data"]), sample_rate=self.sample_rate, num_channels=1, + context_id=context_id, ) - await self.append_to_audio_context(msg["contextId"], frame) + await self.append_to_audio_context(context_id, frame) elif msg["type"] == "timestamps": # Process word timing information @@ -409,7 +410,7 @@ class RimeTTSService(AudioContextWordTTSService): # Calculate word timing pairs word_pairs = self._calculate_word_times(words, starts, ends) if word_pairs: - await self.add_word_timestamps(word_pairs) + await self.add_word_timestamps(word_pairs, context_id=context_id) self._cumulative_time = ends[-1] + self._cumulative_time logger.debug(f"Updated cumulative time to: {self._cumulative_time}") @@ -432,11 +433,12 @@ class RimeTTSService(AudioContextWordTTSService): await self.add_word_timestamps([("Reset", 0)]) @traced_tts - async def run_tts(self, text: str) -> AsyncGenerator[Frame, None]: + async def run_tts(self, text: str, context_id: str) -> AsyncGenerator[Frame, None]: """Generate speech from text using Rime's streaming API. Args: text: The text to convert to speech. + context_id: Unique identifier for this TTS context. Yields: Frame: Audio frames containing the synthesized speech. @@ -449,9 +451,9 @@ class RimeTTSService(AudioContextWordTTSService): try: if not self._context_id: await self.start_ttfb_metrics() - yield TTSStartedFrame() + yield TTSStartedFrame(context_id=context_id) self._cumulative_time = 0 - self._context_id = str(uuid.uuid4()) + self._context_id = context_id await self.create_audio_context(self._context_id) msg = self._build_msg(text=text) @@ -459,7 +461,7 @@ class RimeTTSService(AudioContextWordTTSService): await self.start_tts_usage_metrics(text) except Exception as e: yield ErrorFrame(error=f"Unknown error occurred: {e}") - yield TTSStoppedFrame() + yield TTSStoppedFrame(context_id=context_id) await self._disconnect() await self._connect() return @@ -558,11 +560,12 @@ class RimeHttpTTSService(TTSService): return language_to_rime_language(language) @traced_tts - async def run_tts(self, text: str) -> AsyncGenerator[Frame, None]: + async def run_tts(self, text: str, context_id: str) -> AsyncGenerator[Frame, None]: """Generate speech from text using Rime's HTTP API. Args: text: The text to synthesize into speech. + context_id: The context ID for tracking audio frames. Yields: Frame: Audio frames containing the synthesized speech. @@ -601,13 +604,14 @@ class RimeHttpTTSService(TTSService): await self.start_tts_usage_metrics(text) - yield TTSStartedFrame() + yield TTSStartedFrame(context_id=context_id) CHUNK_SIZE = self.chunk_size async for frame in self._stream_audio_frames_from_iterator( response.content.iter_chunked(CHUNK_SIZE), strip_wav_header=need_to_strip_wav_header, + context_id=context_id, ): await self.stop_ttfb_metrics() yield frame @@ -616,7 +620,7 @@ class RimeHttpTTSService(TTSService): yield ErrorFrame(error=f"Unknown error occurred: {e}") finally: await self.stop_ttfb_metrics() - yield TTSStoppedFrame() + yield TTSStoppedFrame(context_id=context_id) class RimeNonJsonTTSService(InterruptibleTTSService): @@ -716,8 +720,8 @@ class RimeNonJsonTTSService(InterruptibleTTSService): if params.extra: self._settings.update(params.extra) - self._started = False self._receive_task = None + self._context_id: Optional[str] = None def can_generate_metrics(self) -> bool: """Check if this service can generate processing metrics. @@ -767,8 +771,6 @@ class RimeNonJsonTTSService(InterruptibleTTSService): direction: The direction to push the frame. """ await super().push_frame(frame, direction) - if isinstance(frame, (TTSStoppedFrame, InterruptionFrame)): - self._started = False async def _connect(self): """Establish WebSocket connection and start receive task.""" @@ -817,7 +819,7 @@ class RimeNonJsonTTSService(InterruptibleTTSService): except Exception as e: await self.push_error(error_msg=f"Unknown error occurred: {e}", exception=e) finally: - self._started = False + self._context_id = None self._websocket = None await self._call_event_handler("on_disconnected") @@ -847,17 +849,19 @@ class RimeNonJsonTTSService(InterruptibleTTSService): audio=message, sample_rate=self.sample_rate, num_channels=1, + context_id=self._context_id, ) await self.push_frame(frame) except Exception as e: await self.push_error(error_msg=f"Error: {e}", exception=e) @traced_tts - async def run_tts(self, text: str) -> AsyncGenerator[Frame, None]: + async def run_tts(self, text: str, context_id: str) -> AsyncGenerator[Frame, None]: """Generate speech from text using Rime's streaming API. Args: text: The text to synthesize into speech. + context_id: The context ID for tracking audio frames. Yields: Frame: Audio frames containing the synthesized speech. @@ -867,17 +871,17 @@ class RimeNonJsonTTSService(InterruptibleTTSService): if not self._websocket or self._websocket.state is State.CLOSED: await self._connect() try: - if not self._started: - await self.start_ttfb_metrics() - yield TTSStartedFrame() - self._started = True + await self.start_ttfb_metrics() + # Store context_id for use in _receive_messages + self._context_id = context_id + yield TTSStartedFrame(context_id=context_id) # Send bare text (not JSON) await self._get_websocket().send(text) await self.start_tts_usage_metrics(text) except Exception as e: yield ErrorFrame(error=f"Unknown error occurred: {e}") - yield TTSStoppedFrame() + yield TTSStoppedFrame(context_id=context_id) await self._disconnect() await self._connect() return diff --git a/src/pipecat/services/sarvam/tts.py b/src/pipecat/services/sarvam/tts.py index 778a29005..753293c75 100644 --- a/src/pipecat/services/sarvam/tts.py +++ b/src/pipecat/services/sarvam/tts.py @@ -462,11 +462,12 @@ class SarvamHttpTTSService(TTSService): self._settings["sample_rate"] = self.sample_rate @traced_tts - async def run_tts(self, text: str) -> AsyncGenerator[Frame, None]: + async def run_tts(self, text: str, context_id: str) -> AsyncGenerator[Frame, None]: """Generate speech from text using Sarvam AI's API. Args: text: The text to synthesize into speech. + context_id: The context ID for tracking audio frames. Yields: Frame: Audio frames containing the synthesized speech. @@ -503,7 +504,7 @@ class SarvamHttpTTSService(TTSService): url = f"{self._base_url}/text-to-speech" - yield TTSStartedFrame() + yield TTSStartedFrame(context_id=context_id) async with self._session.post(url, json=payload, headers=headers) as response: if response.status != 200: @@ -533,6 +534,7 @@ class SarvamHttpTTSService(TTSService): audio=audio_data, sample_rate=self.sample_rate, num_channels=1, + context_id=context_id, ) yield frame @@ -541,7 +543,7 @@ class SarvamHttpTTSService(TTSService): yield ErrorFrame(error=f"Error generating TTS: {e}", exception=e) finally: await self.stop_ttfb_metrics() - yield TTSStoppedFrame() + yield TTSStoppedFrame(context_id=context_id) class SarvamTTSService(InterruptibleTTSService): @@ -789,9 +791,9 @@ class SarvamTTSService(InterruptibleTTSService): elif params.temperature != 0.6: logger.warning(f"temperature parameter is ignored for {model}") - self._started = False self._receive_task = None self._keepalive_task = None + self._context_id: Optional[str] = None def can_generate_metrics(self) -> bool: """Check if this service can generate processing metrics. @@ -859,8 +861,6 @@ class SarvamTTSService(InterruptibleTTSService): direction: The direction to push the frame. """ await super().push_frame(frame, direction) - if isinstance(frame, (TTSStoppedFrame, InterruptionFrame)): - self._started = False async def process_frame(self, frame: Frame, direction: FrameDirection): """Process a frame and flush audio if it's the end of a full response.""" @@ -956,7 +956,7 @@ class SarvamTTSService(InterruptibleTTSService): except Exception as e: await self.push_error(error_msg=f"Error closing websocket: {e}", exception=e) finally: - self._started = False + self._context_id = None self._websocket = None await self._call_event_handler("on_disconnected") @@ -974,7 +974,9 @@ class SarvamTTSService(InterruptibleTTSService): # Check for interruption before processing audio await self.stop_ttfb_metrics() audio = base64.b64decode(msg["data"]["audio"]) - frame = TTSAudioRawFrame(audio, self.sample_rate, 1) + frame = TTSAudioRawFrame( + audio, self.sample_rate, 1, context_id=self._context_id + ) await self.push_frame(frame) elif msg.get("type") == "error": error_msg = msg["data"]["message"] @@ -984,7 +986,6 @@ class SarvamTTSService(InterruptibleTTSService): if "too long" in error_msg.lower() or "timeout" in error_msg.lower(): logger.warning("Connection timeout detected, service may need restart") - self._started = False await self.push_frame(ErrorFrame(error=f"TTS Error: {error_msg}")) async def _keepalive_task_handler(self): @@ -1009,16 +1010,17 @@ class SarvamTTSService(InterruptibleTTSService): logger.warning("WebSocket not ready, cannot send text") @traced_tts - async def run_tts(self, text: str) -> AsyncGenerator[Frame, None]: + async def run_tts(self, text: str, context_id: str) -> AsyncGenerator[Frame, None]: """Generate speech audio frames from input text using Sarvam TTS. Sends text over WebSocket for synthesis and yields corresponding audio or status frames. Args: text: The text input to synthesize. + context_id: The context ID for tracking audio frames. Yields: - Frame objects including TTSStartedFrame, TTSAudioRawFrame(s), or TTSStoppedFrame. + Frame objects including TTSStartedFrame, TTSAudioRawFrame(s, context_id=context_id), or TTSStoppedFrame. """ logger.debug(f"Generating TTS: [{text}]") @@ -1027,15 +1029,15 @@ class SarvamTTSService(InterruptibleTTSService): await self._connect() try: - if not self._started: - await self.start_ttfb_metrics() - yield TTSStartedFrame() - self._started = True + await self.start_ttfb_metrics() + # Store context_id for use in _receive_messages + self._context_id = context_id + yield TTSStartedFrame(context_id=context_id) await self._send_text(text) await self.start_tts_usage_metrics(text) except Exception as e: yield ErrorFrame(error=f"Unknown error occurred: {e}") - yield TTSStoppedFrame() + yield TTSStoppedFrame(context_id=context_id) await self._disconnect() await self._connect() return diff --git a/src/pipecat/services/speechmatics/tts.py b/src/pipecat/services/speechmatics/tts.py index d7b2f4e2a..0f3ff0cb6 100644 --- a/src/pipecat/services/speechmatics/tts.py +++ b/src/pipecat/services/speechmatics/tts.py @@ -106,11 +106,12 @@ class SpeechmaticsTTSService(TTSService): return True @traced_tts - async def run_tts(self, text: str) -> AsyncGenerator[Frame, None]: + async def run_tts(self, text: str, context_id: str) -> AsyncGenerator[Frame, None]: """Generate speech from text using Speechmatics' HTTP API. Args: text: The text to synthesize into speech. + context_id: The context ID for tracking audio frames. Yields: Frame: Audio frames containing the synthesized speech. @@ -187,7 +188,7 @@ class SpeechmaticsTTSService(TTSService): await self.start_tts_usage_metrics(text) # Emit the TTS started frame - yield TTSStartedFrame() + yield TTSStartedFrame(context_id=context_id) # Process the response in streaming chunks first_chunk = True @@ -216,6 +217,7 @@ class SpeechmaticsTTSService(TTSService): audio=audio_data, sample_rate=self.sample_rate, num_channels=1, + context_id=context_id, ) # Successfully processed the response, break out of retry loop @@ -225,7 +227,7 @@ class SpeechmaticsTTSService(TTSService): yield ErrorFrame(error=f"Error generating TTS: {e}") finally: # Emit the TTS stopped frame - yield TTSStoppedFrame() + yield TTSStoppedFrame(context_id=context_id) def _get_endpoint_url(base_url: str, voice: str, sample_rate: int) -> str: diff --git a/src/pipecat/services/xtts/tts.py b/src/pipecat/services/xtts/tts.py index 2e43d828c..bf4eb4f03 100644 --- a/src/pipecat/services/xtts/tts.py +++ b/src/pipecat/services/xtts/tts.py @@ -148,11 +148,12 @@ class XTTSService(TTSService): self._studio_speakers = await r.json() @traced_tts - async def run_tts(self, text: str) -> AsyncGenerator[Frame, None]: + async def run_tts(self, text: str, context_id: str) -> AsyncGenerator[Frame, None]: """Generate speech from text using XTTS streaming server. Args: text: The text to synthesize into speech. + context_id: The context ID for tracking audio frames. Yields: Frame: Audio frames containing the synthesized speech. @@ -186,7 +187,7 @@ class XTTSService(TTSService): await self.start_tts_usage_metrics(text) - yield TTSStartedFrame() + yield TTSStartedFrame(context_id=context_id) CHUNK_SIZE = self.chunk_size @@ -211,7 +212,9 @@ class XTTSService(TTSService): bytes(process_data), 24000, self.sample_rate ) # Create the frame with the resampled audio - frame = TTSAudioRawFrame(resampled_audio, self.sample_rate, 1) + frame = TTSAudioRawFrame( + resampled_audio, self.sample_rate, 1, context_id=context_id + ) yield frame # Process any remaining data in the buffer. @@ -219,7 +222,9 @@ class XTTSService(TTSService): resampled_audio = await self._resampler.resample( bytes(buffer), 24000, self.sample_rate ) - frame = TTSAudioRawFrame(resampled_audio, self.sample_rate, 1) + frame = TTSAudioRawFrame( + resampled_audio, self.sample_rate, 1, context_id=context_id + ) yield frame - yield TTSStoppedFrame() + yield TTSStoppedFrame(context_id=context_id) From ad1bec458374827432c25ea24cf9f27bc8918f56 Mon Sep 17 00:00:00 2001 From: filipi87 Date: Tue, 10 Feb 2026 11:28:35 -0300 Subject: [PATCH 0427/1060] Updated openai example to use on_tts_request and append_to_text. --- examples/foundational/14d-function-calling-openai-video.py | 6 +++++- 1 file changed, 5 insertions(+), 1 deletion(-) diff --git a/examples/foundational/14d-function-calling-openai-video.py b/examples/foundational/14d-function-calling-openai-video.py index 88c0e8ba3..d948e9caa 100644 --- a/examples/foundational/14d-function-calling-openai-video.py +++ b/examples/foundational/14d-function-calling-openai-video.py @@ -99,7 +99,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): @llm.event_handler("on_function_calls_started") async def on_function_calls_started(service, function_calls): - await tts.queue_frame(TTSSpeakFrame("Let me check on that.")) + await tts.queue_frame(TTSSpeakFrame("Let me check on that.", append_to_context=False)) fetch_image_function = FunctionSchema( name="fetch_user_image", @@ -174,6 +174,10 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): logger.info(f"Client disconnected") await task.cancel() + @tts.event_handler("on_tts_request") + async def on_tts_request(tts, context_id: str, text: str): + logger.debug(f"On TTS request: {context_id}: {text}") + runner = PipelineRunner(handle_sigint=runner_args.handle_sigint) await runner.run(task) From e00b98343eb0c04943dddc1be12fc53afd56d167 Mon Sep 17 00:00:00 2001 From: filipi87 Date: Tue, 10 Feb 2026 11:37:21 -0300 Subject: [PATCH 0428/1060] Changelog entries for TTS context tracking --- changelog/3584.added.2.md | 3 +++ changelog/3584.added.md | 4 ++++ changelog/3584.changed.2.md | 3 +++ changelog/3584.changed.3.md | 4 ++++ changelog/3584.changed.md | 3 +++ 5 files changed, 17 insertions(+) create mode 100644 changelog/3584.added.2.md create mode 100644 changelog/3584.added.md create mode 100644 changelog/3584.changed.2.md create mode 100644 changelog/3584.changed.3.md create mode 100644 changelog/3584.changed.md diff --git a/changelog/3584.added.2.md b/changelog/3584.added.2.md new file mode 100644 index 000000000..3113154fe --- /dev/null +++ b/changelog/3584.added.2.md @@ -0,0 +1,3 @@ +- Added `append_to_context` parameter to `TTSSpeakFrame` for conditional LLM context addition. + - Allows fine-grained control over whether text should be added to conversation context + - Defaults to `True` to maintain backward compatibility diff --git a/changelog/3584.added.md b/changelog/3584.added.md new file mode 100644 index 000000000..08a81ee85 --- /dev/null +++ b/changelog/3584.added.md @@ -0,0 +1,4 @@ +- Added TTS context tracking system with `context_id` field to trace audio generation through the pipeline. + - `TTSAudioRawFrame`, `TTSStartedFrame`, `TTSStoppedFrame` now include `context_id` + - `AggregatedTextFrame` and `TTSTextFrame` now include `context_id` + - Enables tracking which TTS request generated specific audio chunks diff --git a/changelog/3584.changed.2.md b/changelog/3584.changed.2.md new file mode 100644 index 000000000..f5356b4c9 --- /dev/null +++ b/changelog/3584.changed.2.md @@ -0,0 +1,3 @@ +- Simplified context aggregators to use `frame.append_to_context` flag instead of tracking internal state. + - Cleaner logic in `LLMResponseAggregator` and `LLMResponseUniversalAggregator` + - More consistent behavior across aggregator implementations diff --git a/changelog/3584.changed.3.md b/changelog/3584.changed.3.md new file mode 100644 index 000000000..426cfbde7 --- /dev/null +++ b/changelog/3584.changed.3.md @@ -0,0 +1,4 @@ +- ⚠️ `TTSService.run_tts()` now requires a `context_id` parameter for context tracking. + - Custom TTS service implementations must update their `run_tts()` signature + - Before: `async def run_tts(self, text: str) -> AsyncGenerator[Frame, None]:` + - After: `async def run_tts(self, text: str, context_id: str) -> AsyncGenerator[Frame, None]:` diff --git a/changelog/3584.changed.md b/changelog/3584.changed.md new file mode 100644 index 000000000..fd535b7d8 --- /dev/null +++ b/changelog/3584.changed.md @@ -0,0 +1,3 @@ +- Updated all 30+ TTS service implementations to support context tracking with `context_id`. + - Services now generate and propagate context IDs through TTS frames + - Enables end-to-end tracing of TTS requests through the pipeline From 24f90715e32afec4c333829ec8822382d99300ba Mon Sep 17 00:00:00 2001 From: filipi87 Date: Tue, 10 Feb 2026 14:02:09 -0300 Subject: [PATCH 0429/1060] Use LITE as the default mode, and add support for video_settings and is_sandbox in LiveAvatarNewSessionRequest. --- src/pipecat/services/heygen/api_liveavatar.py | 49 +++++++++++++++++-- 1 file changed, 46 insertions(+), 3 deletions(-) diff --git a/src/pipecat/services/heygen/api_liveavatar.py b/src/pipecat/services/heygen/api_liveavatar.py index c9109062a..7b9119542 100644 --- a/src/pipecat/services/heygen/api_liveavatar.py +++ b/src/pipecat/services/heygen/api_liveavatar.py @@ -9,6 +9,7 @@ API to communicate with LiveAvatar Streaming API. """ +from enum import Enum from typing import Any, Dict, Optional import aiohttp @@ -46,17 +47,45 @@ class CustomSDKLiveKitConfig(BaseModel): livekit_client_token: str +class VideoEncoding(str, Enum): + """Enum representing the video encoding.""" + + H264 = "H264" + VP8 = "VP8" + + +class VideoQuality(str, Enum): + """Enum representing different avatar quality levels.""" + + low = "low" + medium = "medium" + high = "high" + very_high = "very_high" + + +class VideoSettings(BaseModel): + """Video encoding settings for session configuration.""" + + encoding: VideoEncoding + quality: VideoQuality = VideoQuality.high + + class LiveAvatarNewSessionRequest(BaseModel): """Request model for creating a LiveAvatar session token. Parameters: - mode (str): Session mode (default: "CUSTOM"). + mode (str): Session mode (default: "LITE"). avatar_id (str): Unique identifier for the avatar. + video_settings (VideoSettings): Video encoding settings. + is_sandbox (bool): Enable sandbox mode (default: False). avatar_persona (AvatarPersona): Avatar persona configuration. + livekit_config (CustomSDKLiveKitConfig): Custom LiveKit configuration. """ - mode: str = "CUSTOM" + mode: str = "LITE" avatar_id: str + video_settings: Optional[VideoSettings] = VideoSettings(encoding=VideoEncoding.VP8) + is_sandbox: Optional[bool] = False avatar_persona: Optional[AvatarPersona] = None livekit_config: Optional[CustomSDKLiveKitConfig] = None @@ -219,7 +248,7 @@ class LiveAvatarApi(BaseAvatarApi): Session token information. """ params: dict[str, Any] = { - "mode": request_data.mode, + "mode": request_data.mode if request_data.mode is not None else "LITE", "avatar_id": request_data.avatar_id, } @@ -234,6 +263,20 @@ class LiveAvatarApi(BaseAvatarApi): avatar_persona = {k: v for k, v in avatar_persona.items() if v is not None} params["avatar_persona"] = avatar_persona + if request_data.is_sandbox is not None: + params["is_sandbox"] = request_data.is_sandbox + + if request_data.video_settings is not None: + video_settings = { + "encoding": request_data.video_settings.encoding.value, + "quality": request_data.video_settings.quality.value, + } + params["video_settings"] = video_settings + else: + # Fall back to VP8 encoding if video_settings is not provided + params["video_settings"] = {"encoding": VideoEncoding.VP8.value} + + logger.debug(f"Creating LiveAvatar session token with params: {params}") response = await self._request("POST", "/sessions/token", params) logger.debug(f"LiveAvatar session token created") From 87a79df0484b3b783fe42f0d09959259397c6c15 Mon Sep 17 00:00:00 2001 From: filipi87 Date: Tue, 10 Feb 2026 14:02:20 -0300 Subject: [PATCH 0430/1060] Updating the heygen examples to use sandbox by default. --- examples/foundational/43-heygen-transport.py | 7 +++++++ examples/foundational/43a-heygen-video-service.py | 7 +++++++ 2 files changed, 14 insertions(+) diff --git a/examples/foundational/43-heygen-transport.py b/examples/foundational/43-heygen-transport.py index 5cc56644b..dd31baa02 100644 --- a/examples/foundational/43-heygen-transport.py +++ b/examples/foundational/43-heygen-transport.py @@ -25,6 +25,7 @@ from pipecat.processors.aggregators.llm_response_universal import ( from pipecat.services.cartesia.tts import CartesiaTTSService from pipecat.services.deepgram.stt import DeepgramSTTService from pipecat.services.google.llm import GoogleLLMService +from pipecat.services.heygen.api_liveavatar import LiveAvatarNewSessionRequest from pipecat.transports.heygen.transport import HeyGenParams, HeyGenTransport, ServiceType load_dotenv(override=True) @@ -43,6 +44,12 @@ async def main(): audio_in_enabled=True, audio_out_enabled=True, ), + session_request=LiveAvatarNewSessionRequest( + is_sandbox=True, + # Sandbox mode only works with this specific avatar + # https://docs.liveavatar.com/docs/developing-in-sandbox-mode#sandbox-mode-behaviors + avatar_id="dd73ea75-1218-4ef3-92ce-606d5f7fbc0a", + ), ) stt = DeepgramSTTService(api_key=os.getenv("DEEPGRAM_API_KEY")) diff --git a/examples/foundational/43a-heygen-video-service.py b/examples/foundational/43a-heygen-video-service.py index bae88e2b5..ba3d4417d 100644 --- a/examples/foundational/43a-heygen-video-service.py +++ b/examples/foundational/43a-heygen-video-service.py @@ -25,6 +25,7 @@ from pipecat.runner.utils import create_transport from pipecat.services.cartesia.tts import CartesiaTTSService from pipecat.services.deepgram.stt import DeepgramSTTService from pipecat.services.google.llm import GoogleLLMService +from pipecat.services.heygen.api_liveavatar import LiveAvatarNewSessionRequest from pipecat.services.heygen.client import ServiceType from pipecat.services.heygen.video import HeyGenVideoService from pipecat.transports.base_transport import BaseTransport, TransportParams @@ -71,6 +72,12 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): api_key=os.getenv("HEYGEN_LIVE_AVATAR_API_KEY"), service_type=ServiceType.LIVE_AVATAR, session=session, + session_request=LiveAvatarNewSessionRequest( + is_sandbox=True, + # Sandbox mode only works with this specific avatar + # https://docs.liveavatar.com/docs/developing-in-sandbox-mode#sandbox-mode-behaviors + avatar_id="dd73ea75-1218-4ef3-92ce-606d5f7fbc0a", + ), ) messages = [ From 5128089d427c1ac11b0081180fad61b4e60aa0d6 Mon Sep 17 00:00:00 2001 From: filipi87 Date: Tue, 10 Feb 2026 14:02:32 -0300 Subject: [PATCH 0431/1060] Add changelog entries for PR #3653. --- changelog/3653.added.2.md | 1 + changelog/3653.added.md | 1 + changelog/3653.changed.md | 1 + 3 files changed, 3 insertions(+) create mode 100644 changelog/3653.added.2.md create mode 100644 changelog/3653.added.md create mode 100644 changelog/3653.changed.md diff --git a/changelog/3653.added.2.md b/changelog/3653.added.2.md new file mode 100644 index 000000000..5207bdeaf --- /dev/null +++ b/changelog/3653.added.2.md @@ -0,0 +1 @@ +- Added support for `video_settings` parameter in `LiveAvatarNewSessionRequest` to configure video encoding (H264/VP8) and quality levels. \ No newline at end of file diff --git a/changelog/3653.added.md b/changelog/3653.added.md new file mode 100644 index 000000000..09c5f3142 --- /dev/null +++ b/changelog/3653.added.md @@ -0,0 +1 @@ +- Added support for `is_sandbox` parameter in `LiveAvatarNewSessionRequest` to enable sandbox mode for HeyGen LiveAvatar sessions. \ No newline at end of file diff --git a/changelog/3653.changed.md b/changelog/3653.changed.md new file mode 100644 index 000000000..a2c9aa3c3 --- /dev/null +++ b/changelog/3653.changed.md @@ -0,0 +1 @@ +- Changed default session mode from "CUSTOM" to "LITE" in HeyGen LiveAvatar integration, with VP8 as the default video encoding. \ No newline at end of file From 314d074c61d0c0ca2c244d5d1c6593b6766d2c3f Mon Sep 17 00:00:00 2001 From: filipi87 Date: Tue, 10 Feb 2026 18:58:12 -0300 Subject: [PATCH 0432/1060] Context summarization feature implementation. --- src/pipecat/frames/frames.py | 50 +++ .../aggregators/llm_context_summarizer.py | 315 ++++++++++++++ .../aggregators/llm_response_universal.py | 52 ++- src/pipecat/services/anthropic/llm.py | 8 +- src/pipecat/services/aws/llm.py | 10 +- src/pipecat/services/google/llm.py | 10 +- src/pipecat/services/llm_service.py | 136 +++++- src/pipecat/services/openai/base_llm.py | 14 +- src/pipecat/utils/context/__init__.py | 0 .../context/llm_context_summarization.py | 396 ++++++++++++++++++ 10 files changed, 984 insertions(+), 7 deletions(-) create mode 100644 src/pipecat/processors/aggregators/llm_context_summarizer.py create mode 100644 src/pipecat/utils/context/__init__.py create mode 100644 src/pipecat/utils/context/llm_context_summarization.py diff --git a/src/pipecat/frames/frames.py b/src/pipecat/frames/frames.py index 7b821a9bc..5634d79ee 100644 --- a/src/pipecat/frames/frames.py +++ b/src/pipecat/frames/frames.py @@ -1991,6 +1991,56 @@ class LLMFullResponseEndFrame(ControlFrame): self.skip_tts = None +@dataclass +class LLMContextSummaryRequestFrame(ControlFrame): + """Frame requesting context summarization from an LLM service. + + Sent by aggregators to LLM services when conversation context needs to be + compressed. The LLM service generates a summary of older messages while + preserving recent conversation history. + + Parameters: + request_id: Unique identifier to match this request with its response. + Used to handle async responses and avoid race conditions. + context: The full LLM context containing all messages to analyze and summarize. + min_messages_to_keep: Number of recent messages to preserve uncompressed. + These messages will not be included in the summary. + target_context_tokens: Maximum token size for the generated summary. This value + is passed directly to the LLM as the max_tokens parameter when generating + the summary text. + summarization_prompt: System prompt instructing the LLM how to generate + the summary. + """ + + request_id: str + context: "LLMContext" + min_messages_to_keep: int + target_context_tokens: int + summarization_prompt: str + + +@dataclass +class LLMContextSummaryResultFrame(ControlFrame, UninterruptibleFrame): + """Frame containing the result of context summarization. + + Sent by LLM services back to aggregators after generating a summary. + Contains the formatted summary message and metadata about what was summarized. + + Parameters: + request_id: Identifier matching the original request. Used to correlate + async responses. + summary: The formatted summary message ready to be inserted into context. + last_summarized_index: Index (0-based) of the last message that was + included in the summary. Messages after this index are preserved. + error: Error message if summarization failed, None on success. + """ + + request_id: str + summary: str + last_summarized_index: int + error: Optional[str] = None + + @dataclass class FunctionCallInProgressFrame(ControlFrame, UninterruptibleFrame): """Frame signaling that a function call is currently executing. diff --git a/src/pipecat/processors/aggregators/llm_context_summarizer.py b/src/pipecat/processors/aggregators/llm_context_summarizer.py new file mode 100644 index 000000000..a1a613ccc --- /dev/null +++ b/src/pipecat/processors/aggregators/llm_context_summarizer.py @@ -0,0 +1,315 @@ +# +# Copyright (c) 2024-2026, Daily +# +# SPDX-License-Identifier: BSD 2-Clause License +# + +"""This module defines a summarizer for managing LLM context summarization.""" + +import uuid +from typing import Optional + +from loguru import logger + +from pipecat.frames.frames import ( + Frame, + InterruptionFrame, + LLMContextSummaryRequestFrame, + LLMContextSummaryResultFrame, + LLMFullResponseStartFrame, +) +from pipecat.processors.aggregators.llm_context import LLMContext +from pipecat.utils.asyncio.task_manager import BaseTaskManager +from pipecat.utils.base_object import BaseObject +from pipecat.utils.context.llm_context_summarization import ( + LLMContextSummarizationConfig, + LLMContextSummarizationUtil, +) + + +class LLMContextSummarizer(BaseObject): + """Summarizer for managing LLM context summarization. + + This class manages automatic context summarization when token or message + limits are reached. It monitors the LLM context size, triggers + summarization requests, and applies the results to compress conversation history. + + Event handlers available: + + - on_request_summarization: Emitted when summarization should be triggered. + The aggregator should broadcast this frame to the LLM service. + + Example:: + + @summarizer.event_handler("on_request_summarization") + async def on_request_summarization(summarizer, frame: LLMContextSummaryRequestFrame): + await aggregator.broadcast_frame( + LLMContextSummaryRequestFrame, + request_id=frame.request_id, + context=frame.context, + ... + ) + """ + + def __init__( + self, + *, + context: LLMContext, + config: Optional[LLMContextSummarizationConfig] = None, + ): + """Initialize the context summarizer. + + Args: + context: The LLM context to monitor and summarize. + config: Configuration for summarization behavior. If None, uses default config. + """ + super().__init__() + + self._context = context + self._config = config or LLMContextSummarizationConfig() + + self._task_manager: Optional[BaseTaskManager] = None + + self._summarization_in_progress = False + self._pending_summary_request_id: Optional[str] = None + + self._register_event_handler("on_request_summarization", sync=True) + + @property + def task_manager(self) -> BaseTaskManager: + """Returns the configured task manager.""" + if not self._task_manager: + raise RuntimeError(f"{self} context summarizer was not properly setup") + return self._task_manager + + async def setup(self, task_manager: BaseTaskManager): + """Initialize the summarizer with the given task manager. + + Args: + task_manager: The task manager to be associated with this instance. + """ + self._task_manager = task_manager + + async def cleanup(self): + """Cleanup the summarizer.""" + await super().cleanup() + await self._clear_summarization_state() + + async def process_frame(self, frame: Frame): + """Process an incoming frame to detect when summarization is needed. + + Args: + frame: The frame to be processed. + """ + if isinstance(frame, LLMFullResponseStartFrame): + await self._handle_llm_response_start(frame) + elif isinstance(frame, LLMContextSummaryResultFrame): + await self._handle_summary_result(frame) + elif isinstance(frame, InterruptionFrame): + await self._handle_interruption() + + async def _handle_llm_response_start(self, frame: LLMFullResponseStartFrame): + """Handle LLM response start to check if summarization is needed. + + Args: + frame: The LLM response start frame. + """ + if self._should_summarize(): + await self._request_summarization() + + async def _handle_interruption(self): + """Handle interruption by canceling summarization in progress. + + Args: + frame: The interruption frame. + """ + # Reset summarization state to allow new requests. This is necessary because + # the request frame (LLMContextSummaryRequestFrame) may have been cancelled + # during interruption. We preserve _pending_summary_request_id to handle the + # response frame (LLMContextSummaryResultFrame), which is uninterruptible and + # will still be delivered. + self._summarization_in_progress = False + + async def _clear_summarization_state(self): + """Cancel pending summarization.""" + if self._summarization_in_progress: + logger.debug(f"{self}: Clearing pending summarization") + self._summarization_in_progress = False + self._pending_summary_request_id = None + + def _should_summarize(self) -> bool: + """Determine if context summarization should be triggered. + + Evaluates whether the current context has reached either the token + threshold or message count threshold that warrants compression. + + Returns: + True if all conditions are met: + - No summarization currently in progress + - AND either: + - Token count exceeds max_context_tokens + - OR message count exceeds max_unsummarized_messages since last summary + """ + logger.trace(f"{self}: Checking if context summarization is needed") + + if self._summarization_in_progress: + logger.debug(f"{self}: Summarization already in progress") + return False + + # Estimate tokens in context + total_tokens = LLMContextSummarizationUtil.estimate_context_tokens(self._context) + num_messages = len(self._context.messages) + + # Check if we've reached the token limit + token_limit = self._config.max_context_tokens + token_limit_exceeded = total_tokens >= token_limit + + # Check if we've exceeded max unsummarized messages + messages_since_summary = len(self._context.messages) - 1 + message_threshold_exceeded = ( + messages_since_summary >= self._config.max_unsummarized_messages + ) + + logger.trace( + f"{self}: Context has {num_messages} messages, " + f"~{total_tokens} tokens (limit: {token_limit}), " + f"{messages_since_summary} messages since last summary " + f"(message threshold: {self._config.max_unsummarized_messages})" + ) + + # Trigger if either limit is exceeded + if not token_limit_exceeded and not message_threshold_exceeded: + logger.trace( + f"{self}: Neither token limit nor message threshold exceeded, skipping summarization" + ) + return False + + reason = [] + if token_limit_exceeded: + reason.append(f"~{total_tokens} tokens (>={token_limit} limit)") + if message_threshold_exceeded: + reason.append( + f"{messages_since_summary} messages (>={self._config.max_unsummarized_messages} threshold)" + ) + + logger.debug(f"{self}: ✓ Summarization needed - {', '.join(reason)}") + return True + + async def _request_summarization(self): + """Request context summarization from LLM service. + + Creates a summarization request frame and emits it via event handler. + Tracks the request ID to match async responses and prevent race conditions. + """ + # Generate unique request ID + request_id = str(uuid.uuid4()) + min_keep = self._config.min_messages_after_summary + + # Mark summarization in progress + self._summarization_in_progress = True + self._pending_summary_request_id = request_id + + logger.debug(f"{self}: Sending summarization request (request_id={request_id})") + + # Create the request frame + request_frame = LLMContextSummaryRequestFrame( + request_id=request_id, + context=self._context, + min_messages_to_keep=min_keep, + target_context_tokens=self._config.target_context_tokens, + summarization_prompt=self._config.summary_prompt, + ) + + # Emit event for aggregator to broadcast + await self._call_event_handler("on_request_summarization", request_frame) + + async def _handle_summary_result(self, frame: LLMContextSummaryResultFrame): + """Handle context summarization result from LLM service. + + Processes the summary result by validating the request ID, checking for + errors, validating context state, and applying the summary. + + Args: + frame: The summary result frame containing the generated summary. + """ + logger.debug(f"{self}: Received summary result (request_id={frame.request_id})") + + # Check if this is the result we're waiting for + if frame.request_id != self._pending_summary_request_id: + logger.debug(f"{self}: Ignoring stale summary result (request_id={frame.request_id})") + return + + # Clear pending state + await self._clear_summarization_state() + + # Check for errors + if frame.error: + logger.error(f"{self}: Context summarization failed: {frame.error}") + return + + # Validate context state + if not self._validate_summary_context(frame.last_summarized_index): + logger.warning(f"{self}: Context state changed, skipping summary application") + return + + # Apply summary + await self._apply_summary(frame.summary, frame.last_summarized_index) + + def _validate_summary_context(self, last_summarized_index: int) -> bool: + """Validate that context state is still valid for applying summary. + + Args: + last_summarized_index: The index of the last summarized message. + + Returns: + True if the context state is still consistent with the summary. + """ + if last_summarized_index < 0: + return False + + # Check if we still have enough messages + if last_summarized_index >= len(self._context.messages): + return False + + min_keep = self._config.min_messages_after_summary + remaining = len(self._context.messages) - 1 - last_summarized_index + if remaining < min_keep: + return False + + return True + + async def _apply_summary(self, summary: str, last_summarized_index: int): + """Apply summary to compress the conversation context. + + Reconstructs the context with: + [first_system_message] + [summary_message] + [recent_messages] + + Args: + summary: The generated summary text. + last_summarized_index: Index of the last message that was summarized. + """ + messages = self._context.messages + + # Find the first system message to preserve + first_system_msg = next((msg for msg in messages if msg.get("role") == "system"), None) + + # Get recent messages to keep + recent_messages = messages[last_summarized_index + 1 :] + + # Create summary message as an assistant message + summary_message = {"role": "assistant", "content": f"Conversation summary: {summary}"} + + # Reconstruct context + new_messages = [] + if first_system_msg: + new_messages.append(first_system_msg) + new_messages.append(summary_message) + new_messages.extend(recent_messages) + + # Update context + self._context.set_messages(new_messages) + + logger.info( + f"{self}: Applied context summary, compressed {last_summarized_index + 1} messages " + f"into summary. Context now has {len(new_messages)} messages (was {len(messages)})" + ) diff --git a/src/pipecat/processors/aggregators/llm_response_universal.py b/src/pipecat/processors/aggregators/llm_response_universal.py index 574af7bbf..6b28b5bf2 100644 --- a/src/pipecat/processors/aggregators/llm_response_universal.py +++ b/src/pipecat/processors/aggregators/llm_response_universal.py @@ -37,6 +37,7 @@ from pipecat.frames.frames import ( InterruptionFrame, LLMContextAssistantTimestampFrame, LLMContextFrame, + LLMContextSummaryRequestFrame, LLMFullResponseEndFrame, LLMFullResponseStartFrame, LLMMessagesAppendFrame, @@ -68,6 +69,7 @@ from pipecat.processors.aggregators.llm_context import ( LLMSpecificMessage, NotGiven, ) +from pipecat.processors.aggregators.llm_context_summarizer import LLMContextSummarizer from pipecat.processors.frame_processor import FrameCallback, FrameDirection, FrameProcessor from pipecat.turns.user_idle_controller import UserIdleController from pipecat.turns.user_mute import BaseUserMuteStrategy @@ -76,6 +78,7 @@ from pipecat.turns.user_stop import BaseUserTurnStopStrategy, UserTurnStoppedPar from pipecat.turns.user_turn_completion_mixin import UserTurnCompletionConfig from pipecat.turns.user_turn_controller import UserTurnController from pipecat.turns.user_turn_strategies import ExternalUserTurnStrategies, UserTurnStrategies +from pipecat.utils.context.llm_context_summarization import LLMContextSummarizationConfig from pipecat.utils.string import TextPartForConcatenation, concatenate_aggregated_text from pipecat.utils.time import time_now_iso8601 @@ -121,9 +124,17 @@ class LLMAssistantAggregatorParams: in text frames by adding spaces between tokens. This parameter is ignored when used with the newer LLMAssistantAggregator, which handles word spacing automatically. + enable_context_summarization: Enable automatic context summarization when token + limits are reached (disabled by default). When enabled, older conversation + messages are automatically compressed into summaries to manage context size. + context_summarization_config: Configuration for context summarization behavior. + Controls thresholds, message preservation, and summarization prompts. If None + and summarization is enabled, uses default configuration values. """ expect_stripped_words: bool = True + enable_context_summarization: bool = False + context_summarization_config: Optional[LLMContextSummarizationConfig] = None @dataclass @@ -807,6 +818,17 @@ class LLMAssistantAggregator(LLMContextAggregator): self._thought_aggregation: List[TextPartForConcatenation] = [] self._thought_start_time: str = "" + # Context summarization + self._summarizer: Optional[LLMContextSummarizer] = None + if self._params.enable_context_summarization: + self._summarizer = LLMContextSummarizer( + context=self._context, + config=self._params.context_summarization_config, + ) + self._summarizer.add_event_handler( + "on_request_summarization", self._on_request_summarization + ) + self._register_event_handler("on_assistant_turn_started") self._register_event_handler("on_assistant_turn_stopped") self._register_event_handler("on_assistant_thought") @@ -840,7 +862,12 @@ class LLMAssistantAggregator(LLMContextAggregator): """ await super().process_frame(frame, direction) - if isinstance(frame, InterruptionFrame): + if isinstance(frame, StartFrame): + # Push StartFrame before start(), because we want StartFrame to be + # processed by every processor before any other frame is processed. + await self.push_frame(frame, direction) + await self._start(frame) + elif isinstance(frame, InterruptionFrame): await self._handle_interruptions(frame) await self.push_frame(frame, direction) elif isinstance(frame, (EndFrame, CancelFrame)): @@ -883,6 +910,14 @@ class LLMAssistantAggregator(LLMContextAggregator): else: await self.push_frame(frame, direction) + # Pass frames to summarizer for monitoring + if self._summarizer: + await self._summarizer.process_frame(frame) + + async def _start(self, frame: StartFrame): + if self._summarizer: + await self._summarizer.setup(self.task_manager) + async def push_aggregation(self) -> str: """Push the current assistant aggregation with timestamp.""" if not self._aggregation: @@ -921,6 +956,8 @@ class LLMAssistantAggregator(LLMContextAggregator): async def _handle_end_or_cancel(self, frame: Frame): await self._trigger_assistant_turn_stopped() + if self._summarizer: + await self._summarizer.cleanup() async def _handle_function_calls_started(self, frame: FunctionCallsStartedFrame): function_names = [f"{f.function_name}:{f.tool_call_id}" for f in frame.function_calls] @@ -1197,6 +1234,19 @@ class LLMAssistantAggregator(LLMContextAggregator): # Only strip whitespace if we removed a marker return text.strip() if marker_found else text + async def _on_request_summarization( + self, summarizer: LLMContextSummarizer, frame: LLMContextSummaryRequestFrame + ): + """Handle summarization request from the summarizer. + + Push the request frame UPSTREAM to the LLM service for processing. + + Args: + summarizer: The summarizer that generated the request. + frame: The summarization request frame to broadcast. + """ + await self.push_frame(frame, FrameDirection.UPSTREAM) + class LLMContextAggregatorPair: """Pair of LLM context aggregators for updating context with user and assistant messages.""" diff --git a/src/pipecat/services/anthropic/llm.py b/src/pipecat/services/anthropic/llm.py index b184ea29d..a21296fe3 100644 --- a/src/pipecat/services/anthropic/llm.py +++ b/src/pipecat/services/anthropic/llm.py @@ -261,11 +261,15 @@ class AnthropicLLMService(LLMService): response = await api_call(**params) return response - async def run_inference(self, context: LLMContext | OpenAILLMContext) -> Optional[str]: + async def run_inference( + self, context: LLMContext | OpenAILLMContext, max_tokens: Optional[int] = None + ) -> Optional[str]: """Run a one-shot, out-of-band (i.e. out-of-pipeline) inference with the given LLM context. Args: context: The LLM context containing conversation history. + max_tokens: Optional maximum number of tokens to generate. If provided, + overrides the service's default max_tokens setting. Returns: The LLM's response as a string, or None if no response is generated. @@ -290,7 +294,7 @@ class AnthropicLLMService(LLMService): # Build params using the same method as streaming completions params = { "model": self.model_name, - "max_tokens": self._settings["max_tokens"], + "max_tokens": max_tokens if max_tokens is not None else self._settings["max_tokens"], "stream": False, "temperature": self._settings["temperature"], "top_k": self._settings["top_k"], diff --git a/src/pipecat/services/aws/llm.py b/src/pipecat/services/aws/llm.py index 32562109a..1778ae74e 100644 --- a/src/pipecat/services/aws/llm.py +++ b/src/pipecat/services/aws/llm.py @@ -844,11 +844,15 @@ class AWSBedrockLLMService(LLMService): inference_config["topP"] = self._settings["top_p"] return inference_config - async def run_inference(self, context: LLMContext | OpenAILLMContext) -> Optional[str]: + async def run_inference( + self, context: LLMContext | OpenAILLMContext, max_tokens: Optional[int] = None + ) -> Optional[str]: """Run a one-shot, out-of-band (i.e. out-of-pipeline) inference with the given LLM context. Args: context: The LLM context containing conversation history. + max_tokens: Optional maximum number of tokens to generate. If provided, + overrides the service's default max_tokens setting. Returns: The LLM's response as a string, or None if no response is generated. @@ -868,6 +872,10 @@ class AWSBedrockLLMService(LLMService): # Prepare request parameters using the same method as streaming inference_config = self._build_inference_config() + # Override maxTokens if provided + if max_tokens is not None: + inference_config["maxTokens"] = max_tokens + request_params = { "modelId": self.model_name, "messages": messages, diff --git a/src/pipecat/services/google/llm.py b/src/pipecat/services/google/llm.py index 0e7556f83..563acadb3 100644 --- a/src/pipecat/services/google/llm.py +++ b/src/pipecat/services/google/llm.py @@ -799,11 +799,15 @@ class GoogleLLMService(LLMService): """Create the Gemini client instance. Subclasses can override this.""" self._client = genai.Client(api_key=self._api_key, http_options=self._http_options) - async def run_inference(self, context: LLMContext | OpenAILLMContext) -> Optional[str]: + async def run_inference( + self, context: LLMContext | OpenAILLMContext, max_tokens: Optional[int] = None + ) -> Optional[str]: """Run a one-shot, out-of-band (i.e. out-of-pipeline) inference with the given LLM context. Args: context: The LLM context containing conversation history. + max_tokens: Optional maximum number of tokens to generate. If provided, + overrides the service's default max_tokens setting. Returns: The LLM's response as a string, or None if no response is generated. @@ -828,6 +832,10 @@ class GoogleLLMService(LLMService): system_instruction=system, tools=tools if tools else None ) + # Override max_output_tokens if provided + if max_tokens is not None: + generation_params["max_output_tokens"] = max_tokens + generation_config = GenerateContentConfig(**generation_params) # Use the new google-genai client's async method diff --git a/src/pipecat/services/llm_service.py b/src/pipecat/services/llm_service.py index c59b102b4..af7e691b0 100644 --- a/src/pipecat/services/llm_service.py +++ b/src/pipecat/services/llm_service.py @@ -39,6 +39,8 @@ from pipecat.frames.frames import ( FunctionCallsStartedFrame, InterruptionFrame, LLMConfigureOutputFrame, + LLMContextSummaryRequestFrame, + LLMContextSummaryResultFrame, LLMFullResponseEndFrame, LLMFullResponseStartFrame, LLMTextFrame, @@ -57,6 +59,9 @@ from pipecat.processors.aggregators.openai_llm_context import OpenAILLMContext from pipecat.processors.frame_processor import FrameDirection from pipecat.services.ai_service import AIService from pipecat.turns.user_turn_completion_mixin import UserTurnCompletionLLMServiceMixin +from pipecat.utils.context.llm_context_summarization import ( + LLMContextSummarizationUtil, +) # Type alias for a callable that handles LLM function calls. FunctionCallHandler = Callable[["FunctionCallParams"], Awaitable[None]] @@ -195,6 +200,7 @@ class LLMService(UserTurnCompletionLLMServiceMixin, AIService): self._sequential_runner_task: Optional[asyncio.Task] = None self._tracing_enabled: bool = False self._skip_tts: Optional[bool] = None + self._summary_task: Optional[asyncio.Task] = None self._register_event_handler("on_function_calls_started") self._register_event_handler("on_completion_timeout") @@ -218,13 +224,17 @@ class LLMService(UserTurnCompletionLLMServiceMixin, AIService): """ return self.get_llm_adapter().create_llm_specific_message(message) - async def run_inference(self, context: LLMContext | OpenAILLMContext) -> Optional[str]: + async def run_inference( + self, context: LLMContext | OpenAILLMContext, max_tokens: Optional[int] = None + ) -> Optional[str]: """Run a one-shot, out-of-band (i.e. out-of-pipeline) inference with the given LLM context. Must be implemented by subclasses. Args: context: The LLM context containing conversation history. + max_tokens: Optional maximum number of tokens to generate. If provided, + overrides the service's default max_tokens/max_completion_tokens setting. Returns: The LLM's response as a string, or None if no response is generated. @@ -286,6 +296,7 @@ class LLMService(UserTurnCompletionLLMServiceMixin, AIService): await super().stop(frame) if not self._run_in_parallel: await self._cancel_sequential_runner_task() + await self._cancel_summary_task() async def cancel(self, frame: CancelFrame): """Cancel the LLM service. @@ -296,6 +307,7 @@ class LLMService(UserTurnCompletionLLMServiceMixin, AIService): await super().cancel(frame) if not self._run_in_parallel: await self._cancel_sequential_runner_task() + await self._cancel_summary_task() async def _update_settings(self, settings: Mapping[str, Any]): """Update LLM service settings. @@ -339,6 +351,8 @@ class LLMService(UserTurnCompletionLLMServiceMixin, AIService): await self._handle_interruptions(frame) elif isinstance(frame, LLMConfigureOutputFrame): self._skip_tts = frame.skip_tts + elif isinstance(frame, LLMContextSummaryRequestFrame): + await self._handle_summary_request(frame) async def push_frame(self, frame: Frame, direction: FrameDirection = FrameDirection.DOWNSTREAM): """Pushes a frame. @@ -372,6 +386,121 @@ class LLMService(UserTurnCompletionLLMServiceMixin, AIService): if entry.cancel_on_interruption: await self._cancel_function_call(function_name) + async def _handle_summary_request(self, frame: LLMContextSummaryRequestFrame): + """Handle context summarization request from aggregator. + + Processes a summarization request by generating a compressed summary + of conversation history. Uses the adapter to format the summary + according to the provider's requirements. Broadcasts the result back + to the aggregator for context reconstruction. + + Args: + frame: The summary request frame containing context and parameters. + """ + logger.debug(f"{self}: Processing summarization request {frame.request_id}") + + # Create a background task to generate the summary without blocking + self._summary_task = self.create_task(self._generate_summary_task(frame)) + + async def _generate_summary_task(self, frame: LLMContextSummaryRequestFrame): + """Background task to generate summary without blocking the pipeline. + + Args: + frame: The summary request frame containing context and parameters. + """ + summary = "" + last_index = -1 + error = None + + try: + summary, last_index = await self._generate_summary(frame) + except Exception as e: + error = f"Error generating context summary: {e}" + await self.push_error(error, exception=e) + + await self.broadcast_frame( + LLMContextSummaryResultFrame, + request_id=frame.request_id, + summary=summary, + last_summarized_index=last_index, + error=error, + ) + + self._summary_task = None + + async def _generate_summary(self, frame: LLMContextSummaryRequestFrame) -> tuple[str, int]: + """Generate a compressed summary of conversation context. + + Uses the message selection logic to identify which messages + to summarize, formats them as a transcript, and invokes the LLM to + generate a concise summary. The summary is formatted according to the + LLM provider's requirements using the adapter. + + Args: + frame: The summary request frame containing context and configuration. + + Returns: + Tuple of (formatted summary message, last_summarized_index). + + Raises: + RuntimeError: If there are no messages to summarize, the service doesn't + support run_inference(), or the LLM returns an empty summary. + + Note: + Requires the service to implement run_inference() method for + synchronous LLM calls. + """ + # Get messages to summarize using utility method + result = LLMContextSummarizationUtil.get_messages_to_summarize( + frame.context, frame.min_messages_to_keep + ) + + if not result.messages: + logger.debug(f"{self}: No messages to summarize") + raise RuntimeError("No messages to summarize") + + logger.debug( + f"{self}: Generating summary for {len(result.messages)} messages " + f"(index 0 to {result.last_summarized_index}), " + f"target_context_tokens={frame.target_context_tokens}" + ) + + # Create summary context + transcript = LLMContextSummarizationUtil.format_messages_for_summary(result.messages) + prompt_messages = [ + { + "role": "system", + "content": frame.summarization_prompt, + }, + { + "role": "user", + "content": f"Conversation history:\n{transcript}", + }, + ] + summary_context = LLMContext(messages=prompt_messages) + + # Generate summary using run_inference + # This will be overridden by each LLM service implementation + try: + summary_text = await self.run_inference( + summary_context, max_tokens=frame.target_context_tokens + ) + except NotImplementedError: + raise RuntimeError( + f"LLM service {self.__class__.__name__} does not implement run_inference" + ) + + if not summary_text: + raise RuntimeError("LLM returned empty summary") + + summary_text = summary_text.strip() + logger.info( + f"{self}: Generated summary of {len(summary_text)} characters " + f"for {len(result.messages)} messages" + ) + + return summary_text, result.last_summarized_index + def register_function( self, function_name: Optional[str], @@ -588,6 +717,11 @@ class LLMService(UserTurnCompletionLLMServiceMixin, AIService): await self.cancel_task(self._sequential_runner_task) self._sequential_runner_task = None + async def _cancel_summary_task(self): + if self._summary_task: + await self.cancel_task(self._summary_task) + self._summary_task = None + async def _sequential_runner_handler(self): while True: runner_item = await self._sequential_runner_queue.get() diff --git a/src/pipecat/services/openai/base_llm.py b/src/pipecat/services/openai/base_llm.py index 54e514508..d8669f622 100644 --- a/src/pipecat/services/openai/base_llm.py +++ b/src/pipecat/services/openai/base_llm.py @@ -265,11 +265,15 @@ class BaseOpenAILLMService(LLMService): params.update(self._settings["extra"]) return params - async def run_inference(self, context: LLMContext | OpenAILLMContext) -> Optional[str]: + async def run_inference( + self, context: LLMContext | OpenAILLMContext, max_tokens: Optional[int] = None + ) -> Optional[str]: """Run a one-shot, out-of-band (i.e. out-of-pipeline) inference with the given LLM context. Args: context: The LLM context containing conversation history. + max_tokens: Optional maximum number of tokens to generate. If provided, + overrides the service's default max_tokens/max_completion_tokens setting. Returns: The LLM's response as a string, or None if no response is generated. @@ -291,6 +295,14 @@ class BaseOpenAILLMService(LLMService): params["stream"] = False params.pop("stream_options", None) + # Override max_tokens if provided + if max_tokens is not None: + # Use max_completion_tokens for newer models, fallback to max_tokens + if "max_completion_tokens" in params: + params["max_completion_tokens"] = max_tokens + else: + params["max_tokens"] = max_tokens + # LLM completion response = await self._client.chat.completions.create(**params) diff --git a/src/pipecat/utils/context/__init__.py b/src/pipecat/utils/context/__init__.py new file mode 100644 index 000000000..e69de29bb diff --git a/src/pipecat/utils/context/llm_context_summarization.py b/src/pipecat/utils/context/llm_context_summarization.py new file mode 100644 index 000000000..6865a00d9 --- /dev/null +++ b/src/pipecat/utils/context/llm_context_summarization.py @@ -0,0 +1,396 @@ +# +# Copyright (c) 2024–2026, Daily +# +# SPDX-License-Identifier: BSD 2-Clause License +# + +"""Utility for context summarization in LLM services. + +This module provides reusable functionality for automatically compressing conversation +context when token limits are reached, enabling efficient long-running conversations. +""" + +from dataclasses import dataclass +from typing import List, Optional + +from loguru import logger + +from pipecat.processors.aggregators.llm_context import LLMContext + +# Token estimation constants +CHARS_PER_TOKEN = 4 # Industry-standard heuristic: 1 token ≈ 4 characters +TOKEN_OVERHEAD_PER_MESSAGE = 10 # Estimated structural overhead per message +IMAGE_TOKEN_ESTIMATE = 500 # Rough estimate for image content +SUMMARY_TOKEN_BUFFER = 0.8 # Keep summary at 80% of available space for safety +MIN_SUMMARY_TOKENS = 100 # Minimum tokens to allocate for summary + +DEFAULT_SUMMARIZATION_PROMPT = """You are summarizing a conversation between a user and an AI assistant. + +Your task: +1. Create a concise summary that preserves: + - Key facts, decisions, and agreements + - Important context needed to continue the conversation + - User preferences and requirements mentioned + - Any unresolved questions or action items + +2. Format: + - Use clear, factual statements + - Group related information + - Prioritize information likely to be referenced later + - Keep the summary concise to fit within the specified token budget + +3. Omit: + - Greetings and small talk + - Redundant information + - Tangential discussions that were resolved + +The conversation transcript follows. Generate only the summary, no other text.""" + + +@dataclass +class LLMContextSummarizationConfig: + """Configuration for context summarization behavior. + + Controls when and how conversation context is automatically compressed + to manage token limits in long-running conversations. + + Parameters: + max_context_tokens: Maximum allowed context size in tokens. When this + limit is reached, summarization is triggered to compress the context. + The tokens are calculated using the industry-standard approximation + of 1 token ≈ 4 characters. + target_context_tokens: Maximum token size for the generated summary. + This value is passed directly to the LLM as the max_tokens parameter + when generating the summary. Should be sized appropriately to allow + the summary plus recent preserved messages to fit within reasonable + context limits. + max_unsummarized_messages: Maximum number of new messages that can + accumulate since the last summary before triggering a new + summarization. This ensures regular compression even if token + limits are not reached. + min_messages_after_summary: Number of recent messages to preserve + uncompressed after each summarization. These messages maintain + immediate conversational context. + summarization_prompt: Custom prompt for the LLM to use when generating + summaries. If None, uses DEFAULT_SUMMARIZATION_PROMPT. + """ + + max_context_tokens: int = 8000 + target_context_tokens: int = 6000 + max_unsummarized_messages: int = 20 + min_messages_after_summary: int = 4 + summarization_prompt: Optional[str] = None + + def __post_init__(self): + """Validate configuration parameters.""" + if self.max_context_tokens <= 0: + raise ValueError("max_context_tokens must be positive") + if self.target_context_tokens <= 0: + raise ValueError("target_context_tokens must be positive") + + # Auto-adjust target_context_tokens if it exceeds max_context_tokens + if self.target_context_tokens > self.max_context_tokens: + # Use 80% of max_context_tokens as a reasonable default + self.target_context_tokens = int(self.max_context_tokens * 0.8) + + if self.max_unsummarized_messages < 1: + raise ValueError("max_unsummarized_messages must be at least 1") + if self.min_messages_after_summary < 0: + raise ValueError("min_messages_after_summary must be positive") + + @property + def summary_prompt(self) -> str: + """Get the summarization prompt to use. + + Returns: + The custom prompt if set, otherwise the default summarization prompt. + """ + return self.summarization_prompt or DEFAULT_SUMMARIZATION_PROMPT + + +@dataclass +class LLMMessagesToSummarize: + """Result of get_messages_to_summarize operation. + + Parameters: + messages: Messages to include in the summary + last_summarized_index: Index of the last message being summarized + """ + + messages: List[dict] + last_summarized_index: int + + +class LLMContextSummarizationUtil: + """Utility providing context summarization capabilities for LLM processing. + + This utility enables automatic conversation context compression when token + limits are reached. It provides functionality for both aggregators + (which decide when to summarize) and LLM services (which generate summaries). + + Key features: + - Token estimation using character-count heuristics (chars // 4) + - Smart message selection (preserves system messages and recent context) + - Function call awareness (avoids summarizing incomplete tool interactions) + - Flexible transcript formatting for summarization + - Maximum summary token calculation with safety buffers + + Usage: + Use the static methods directly on the class: + + tokens = LLMContextSummarizationUtil.estimate_context_tokens(context) + result = LLMContextSummarizationUtil.get_messages_to_summarize(context, 4) + transcript = LLMContextSummarizationUtil.format_messages_for_summary(messages) + + Note: + Token estimation uses the industry-standard heuristic of 1 token ≈ 4 characters. + """ + + @staticmethod + def estimate_tokens(text: str) -> int: + """Estimate token count for text using character count heuristic. + + Uses the industry-standard approximation of 1 token ≈ 4 characters. + This works well across different content types (prose, code, etc.) + and languages. + + Note: + For more accurate token counts, use the model's official tokenizer. + This is a rough estimate suitable for threshold checks and budgeting. + + Args: + text: Text to estimate tokens for + + Returns: + Estimated token count (characters // 4) + """ + if not text: + return 0 + return len(text) // CHARS_PER_TOKEN + + @staticmethod + def estimate_context_tokens(context: LLMContext) -> int: + """Estimate total token count for a context. + + Calculates an approximate token count by analyzing all messages, + including text content, tool calls, and structural overhead. + + Args: + context: LLM context to estimate. + + Returns: + Estimated total token count including: + - Message content (text, images) + - Tool calls and their arguments + - Tool results + - Structural overhead (TOKEN_OVERHEAD_PER_MESSAGE per message) + """ + total = 0 + + for message in context.messages: + # Role and structure overhead + total += TOKEN_OVERHEAD_PER_MESSAGE + + # Message content + content = message.get("content", "") + if isinstance(content, str): + total += LLMContextSummarizationUtil.estimate_tokens(content) + elif isinstance(content, list): + for item in content: + if isinstance(item, dict): + item_type = item.get("type", "") + # Text content + if item_type == "text": + total += LLMContextSummarizationUtil.estimate_tokens( + item.get("text", "") + ) + # Image content + elif item_type in ("image_url", "image"): + # Images are expensive, rough estimate + total += IMAGE_TOKEN_ESTIMATE + + # Tool calls + if "tool_calls" in message: + tool_calls = message["tool_calls"] + if isinstance(tool_calls, list): + for tool_call in tool_calls: + if isinstance(tool_call, dict): + func = tool_call.get("function", {}) + if isinstance(func, dict): + total += LLMContextSummarizationUtil.estimate_tokens( + func.get("name", "") + func.get("arguments", "") + ) + + # Tool call ID + if "tool_call_id" in message: + total += TOKEN_OVERHEAD_PER_MESSAGE + + return total + + @staticmethod + def _get_function_calls_in_progress_index(messages: List[dict], start_idx: int) -> int: + """Find the earliest message index with incomplete function calls. + + Scans messages to identify function/tool calls that haven't received + their results yet. This prevents summarizing incomplete tool interactions + which would break the request-response pairing. + + Args: + messages: List of messages to check. + start_idx: Index to start checking from. + + Returns: + Index of first message with function call in progress, or -1 if all + function calls are complete. + """ + # Track tool call IDs mapped to their message index + pending_tool_calls: dict[str, int] = {} + + for i in range(start_idx, len(messages)): + msg = messages[i] + role = msg.get("role") + + # Check for tool calls in assistant messages + if role == "assistant" and "tool_calls" in msg: + tool_calls = msg.get("tool_calls", []) + if isinstance(tool_calls, list): + for tool_call in tool_calls: + if isinstance(tool_call, dict): + tool_call_id = tool_call.get("id") + if tool_call_id: + pending_tool_calls[tool_call_id] = i + + # Check for tool results + if role == "tool": + tool_call_id = msg.get("tool_call_id") + if tool_call_id and tool_call_id in pending_tool_calls: + pending_tool_calls.pop(tool_call_id) + + # If we have pending tool calls, return the earliest index + if pending_tool_calls: + return min(pending_tool_calls.values()) + + return -1 + + @staticmethod + def get_messages_to_summarize( + context: LLMContext, min_messages_to_keep: int + ) -> LLMMessagesToSummarize: + """Determine which messages should be included in summarization. + + Intelligently selects messages for summarization while preserving: + - The first system message (defines assistant behavior) + - The last N messages (maintains immediate conversation context) + - Incomplete function call sequences (preserves tool interaction integrity) + + Args: + context: The LLM context containing all messages. + min_messages_to_keep: Number of recent messages to exclude from + summarization. + + Returns: + LLMMessagesToSummarize containing the messages to summarize and the + index of the last message included. + """ + messages = context.messages + if len(messages) <= min_messages_to_keep: + return LLMMessagesToSummarize(messages=[], last_summarized_index=-1) + + # Find first system message index + first_system_index = next( + (i for i, msg in enumerate(messages) if msg.get("role") == "system"), -1 + ) + + # Messages to summarize are between first system and recent messages + # We exclude the first system message itself + if first_system_index >= 0: + summary_start = first_system_index + 1 + else: + summary_start = 0 + + # Get messages to keep (last N messages) + summary_end = len(messages) - min_messages_to_keep + + if summary_start >= summary_end: + return LLMMessagesToSummarize(messages=[], last_summarized_index=-1) + + # Check for function calls in progress in the range we want to summarize + function_call_start = LLMContextSummarizationUtil._get_function_calls_in_progress_index( + messages, summary_start + ) + if function_call_start >= 0 and function_call_start < summary_end: + # Stop summarization before the function call + logger.debug( + f"ContextSummarization: Found function call in progress at index {function_call_start}, " + f"stopping summary before it (was going to summarize up to {summary_end})" + ) + # Count how many messages we're skipping + skipped_messages = summary_end - function_call_start + summary_end = function_call_start + if skipped_messages > 0: + logger.info( + f"ContextSummarization: Skipping {skipped_messages} messages with " + f"function calls in progress (will summarize after results are available)" + ) + + if summary_start >= summary_end: + return LLMMessagesToSummarize(messages=[], last_summarized_index=-1) + + messages_to_summarize = messages[summary_start:summary_end] + last_summarized_index = summary_end - 1 + + return LLMMessagesToSummarize( + messages=messages_to_summarize, last_summarized_index=last_summarized_index + ) + + @staticmethod + def format_messages_for_summary(messages: List[dict]) -> str: + """Format messages as a transcript for summarization. + + Args: + messages: Messages to format + + Returns: + Formatted transcript string + """ + transcript_parts = [] + + for msg in messages: + role = msg.get("role", "unknown") + content = msg.get("content", "") + + # Handle different content types + if isinstance(content, str): + text = content + elif isinstance(content, list): + text_parts = [] + for item in content: + if isinstance(item, dict) and item.get("type") == "text": + text_parts.append(item.get("text", "")) + text = " ".join(text_parts) + else: + text = str(content) + + if text: + # Capitalize role for readability + formatted_role = role.upper() + transcript_parts.append(f"{formatted_role}: {text}") + + # Include tool calls if present + if "tool_calls" in msg: + tool_calls = msg.get("tool_calls", []) + if isinstance(tool_calls, list): + for tool_call in tool_calls: + if isinstance(tool_call, dict): + func = tool_call.get("function", {}) + if isinstance(func, dict): + name = func.get("name", "unknown") + args = func.get("arguments", "") + transcript_parts.append(f"TOOL_CALL: {name}({args})") + + # Include tool results + if role == "tool": + tool_call_id = msg.get("tool_call_id", "unknown") + transcript_parts.append(f"TOOL_RESULT[{tool_call_id}]: {text}") + + return "\n\n".join(transcript_parts) From 92b6ecd945497b35c2b3f5e450dc5946360e2301 Mon Sep 17 00:00:00 2001 From: filipi87 Date: Tue, 10 Feb 2026 18:58:22 -0300 Subject: [PATCH 0433/1060] New Claude skill to help refactor and cleanup the code. --- .claude/skills/cleanup/SKILL.md | 307 ++++++++++++++++++++++++++++++++ 1 file changed, 307 insertions(+) create mode 100644 .claude/skills/cleanup/SKILL.md diff --git a/.claude/skills/cleanup/SKILL.md b/.claude/skills/cleanup/SKILL.md new file mode 100644 index 000000000..f7dd6ea98 --- /dev/null +++ b/.claude/skills/cleanup/SKILL.md @@ -0,0 +1,307 @@ +# Code Cleanup Skill + +The **Code Cleanup Skill** reviews, refactors, and documents code changes in your current branch, ensuring alignment with **Pipecat’s architecture, coding standards, and example patterns**. +It focuses on **readability, correctness, performance, and consistency**, while avoiding breaking changes. + +--- + +## Skill Overview + +This skill analyzes all changes introduced in your branch and performs the following actions: + +1. **Analyze Branch Changes** + - Review uncommitted changes and outgoing commits +2. **Refactor for Readability** + - Improve clarity, naming, structure, and modern Python usage +3. **Enhance Performance** + - Identify safe, conservative optimization opportunities +4. **Add Documentation** + - Apply Pipecat-style, Google-format docstrings +5. **Ensure Pattern Consistency** + - Match existing Pipecat services, pipelines, and examples +6. **Validate Examples** + - Ensure examples follow foundational patterns (e.g. `07-interruptible.py`) + +--- + +## Usage + +Invoke the skill using any of the following commands: + +- “Clean up my branch code” +- “Refactor the changes in my branch” +- “Review and improve my branch code” +- `/cleanup` + +--- + +## What This Skill Does + +### 1. Analyze Branch Changes + +The skill retrieves all uncommitted changes and outgoing commits to understand: + +- New files added +- Modified files +- Code additions and deletions +- Overall scope and intent of changes + +--- + +### 2. Code Refactoring + +#### Readability Improvements + +- Replace tuples with named classes or dataclasses +- Improve variable, method, and class naming +- Extract complex logic into well-named helper methods +- Add missing type hints +- Simplify nested or complex conditionals +- Replace deprecated methods and features +- Normalize formatting to match Pipecat style + +#### Performance Enhancements + +- Identify inefficient loops or repeated work +- Suggest appropriate data structures +- Optimize async workflows and I/O +- Remove redundant operations + +> Performance changes are conservative and non-breaking. + +--- + +### 3. Documentation + +Documentation follows **Google-style docstrings**, consistent with Pipecat conventions. + +#### Class Documentation + +```python +class ExampleService: + """Brief one-line description. + + Detailed explanation of the class purpose, responsibilities, + and important behaviors. + + Supported features: + + - Feature 1 + - Feature 2 + - Feature 3 + """ +``` + +#### Method Documentation + +```python +def process_data(self, data: str, options: Optional[dict] = None) -> bool: + """Process incoming data with optional configuration. + + Args: + data: The input data to process. + options: Optional configuration dictionary. + + Returns: + True if processing succeeded, False otherwise. + + Raises: + ValueError: If data is empty or invalid. + """ +``` + +#### Pydantic Model Parameters + +```python +class InputParams(BaseModel): + """Configuration parameters for the service. + + Parameters: + timeout: Request timeout in seconds. + retry_count: Number of retry attempts. + enable_logging: Whether to enable debug logging. + """ + + timeout: Optional[float] = None + retry_count: int = 3 + enable_logging: bool = False +``` + +--- + +### 4. Pattern Consistency Checks + +#### Service Classes + +- Correct inheritance (`TTSService`, `STTService`, `LLMService`) +- Consistent constructor signatures +- Frame emission patterns +- Metrics support: + - `can_generate_metrics()` + - TTFB metrics + - Usage metrics +- Alignment with similar existing services + +#### Examples + +Validated against `examples/foundational/07-interruptible.py`: + +- Proper `create_transport()` usage +- Correct pipeline structure +- Task setup and observers +- Event handler registration +- Runner and bot entrypoint consistency + +--- + +### 5. Specific Implementation Patterns + +#### Service Implementation + +```python +class ExampleTTSService(TTSService): + + def __init__(self, *, api_key: Optional[str] = None, **kwargs): + super().__init__(**kwargs) + self._api_key = api_key or os.getenv("SERVICE_API_KEY") + + def can_generate_metrics(self) -> bool: + return True + + async def run_tts(self, text: str) -> AsyncGenerator[Frame, None]: + try: + await self.start_ttfb_metrics() + yield TTSStartedFrame() + # ... processing ... + yield TTSAudioRawFrame(...) + finally: + await self.stop_ttfb_metrics() +``` + +--- + +#### Example Structure Pattern + +```python +transport_params = { + "daily": lambda: DailyParams(...), + "twilio": lambda: FastAPIWebsocketParams(...), + "webrtc": lambda: TransportParams(...), +} + +async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): + stt = DeepgramSTTService(...) + tts = SomeTTSService(...) + llm = OpenAILLMService(...) + + context = LLMContext(messages) + user_aggregator, assistant_aggregator = LLMContextAggregatorPair(...) + + pipeline = Pipeline([...]) + task = PipelineTask(pipeline, params=..., observers=[...]) + + @transport.event_handler("on_client_connected") + async def on_client_connected(transport, client): + await task.queue_frames([LLMRunFrame()]) + + runner = PipelineRunner(handle_sigint=runner_args.handle_sigint) + await runner.run(task) + +async def bot(runner_args: RunnerArguments): + """Main bot entry point compatible with Pipecat Cloud.""" + transport = await create_transport(runner_args, transport_params) + await run_bot(transport, runner_args) +``` + +--- + +## Execution Flow + +1. Fetch uncommitted and outgoing changes +2. Categorize files (services, examples, tests, utilities) +3. Analyze each file: + - Readability + - Performance + - Documentation + - Pattern consistency +4. Generate actionable recommendations +5. Apply Pipecat standards + +--- + +## Examples + +### Before: Tuple Usage + +```python +def get_audio_info(self) -> Tuple[int, int]: + return (48000, 1) +``` + +### After: Named Class + +```python +class AudioInfo: + """Audio configuration information. + + Parameters: + sample_rate: Sample rate in Hz. + num_channels: Number of audio channels. + """ + + sample_rate: int + num_channels: int + +def get_audio_info(self) -> AudioInfo: + return AudioInfo(sample_rate=48000, num_channels=1) +``` + +--- + +### Before: Missing Documentation + +```python +class NewTTSService(TTSService): + def __init__(self, api_key: str, voice: str): + self._api_key = api_key + self._voice = voice +``` + +### After: Fully Documented + +```python +class NewTTSService(TTSService): + """Text-to-speech service using NewProvider API. + + Streams PCM audio and emits TTSAudioRawFrame frames compatible + with Pipecat transports. + + Supported features: + - Text-to-speech synthesis + - Streaming PCM audio + - Voice customization + - TTFB metrics + """ + + def __init__(self, *, api_key: str, voice: str, **kwargs): + """Initialize the NewTTSService. + + Args: + api_key: API key for authentication. + voice: Voice identifier to use. + **kwargs: Additional arguments passed to the parent service. + """ + super().__init__(**kwargs) + self._api_key = api_key + self.set_voice(voice) +``` + +--- + +## Notes + +- Non-breaking improvements only +- Backward compatibility preserved +- Conservative performance changes +- Google-style docstrings +- Pattern checks follow recent Pipecat code From 9d89afa7d454ce97014bd5d1c6ff51d73a624d1d Mon Sep 17 00:00:00 2001 From: filipi87 Date: Tue, 10 Feb 2026 18:58:33 -0300 Subject: [PATCH 0434/1060] Automated tests for the context summarization feature. --- tests/test_context_summarization.py | 606 ++++++++++++++++++++++++++++ 1 file changed, 606 insertions(+) create mode 100644 tests/test_context_summarization.py diff --git a/tests/test_context_summarization.py b/tests/test_context_summarization.py new file mode 100644 index 000000000..87aaa74d3 --- /dev/null +++ b/tests/test_context_summarization.py @@ -0,0 +1,606 @@ +# +# Copyright (c) 2024–2025, Daily +# +# SPDX-License-Identifier: BSD 2-Clause License +# + +"""Tests for context summarization feature.""" + +import unittest +from unittest.mock import AsyncMock, MagicMock, patch + +from pipecat.frames.frames import LLMContextSummaryRequestFrame +from pipecat.processors.aggregators.llm_context import LLMContext +from pipecat.services.llm_service import LLMService +from pipecat.utils.context.llm_context_summarization import ( + LLMContextSummarizationConfig, + LLMContextSummarizationUtil, +) + + +class TestContextSummarizationMixin(unittest.TestCase): + """Tests for LLMContextSummarizationUtil.""" + + def test_estimate_tokens_simple_text(self): + """Test token estimation with simple text.""" + # Simple sentence: "Hello world" = 11 chars / 4 = 2.75 -> 2 tokens + tokens = LLMContextSummarizationUtil.estimate_tokens("Hello world") + self.assertEqual(tokens, 2) + + # More words: "This is a test message" = 22 chars / 4 = 5.5 -> 5 tokens + tokens = LLMContextSummarizationUtil.estimate_tokens("This is a test message") + self.assertEqual(tokens, 5) + + def test_estimate_tokens_empty(self): + """Test token estimation with empty text.""" + tokens = LLMContextSummarizationUtil.estimate_tokens("") + self.assertEqual(tokens, 0) + + def test_estimate_context_tokens(self): + """Test context token estimation.""" + context = LLMContext() + + # Empty context + self.assertEqual(LLMContextSummarizationUtil.estimate_context_tokens(context), 0) + + # Add messages + context.add_message({"role": "system", "content": "You are helpful"}) # ~4 words + context.add_message({"role": "user", "content": "Hello"}) # ~1 word + context.add_message({"role": "assistant", "content": "Hi there"}) # ~2 words + + # Each message has ~10 token overhead + # Total content: ~7 words * 1.3 = ~9 tokens + # Total overhead: 3 * 10 = 30 tokens + # Expected: ~39 tokens + total = LLMContextSummarizationUtil.estimate_context_tokens(context) + self.assertGreater(total, 30) # At least overhead + self.assertLess(total, 50) # Not too much + + def test_get_messages_to_summarize_basic(self): + """Test basic message extraction for summarization.""" + context = LLMContext() + + # Add messages + context.add_message({"role": "system", "content": "System prompt"}) + context.add_message({"role": "user", "content": "Message 1"}) + context.add_message({"role": "assistant", "content": "Response 1"}) + context.add_message({"role": "user", "content": "Message 2"}) + context.add_message({"role": "assistant", "content": "Response 2"}) + context.add_message({"role": "user", "content": "Message 3"}) + context.add_message({"role": "assistant", "content": "Response 3"}) + + # Keep last 2 messages + result = LLMContextSummarizationUtil.get_messages_to_summarize(context, 2) + + # Get first system message from context + first_system = None + for msg in context.messages: + if msg.get("role") == "system": + first_system = msg + break + + # Should get system message + self.assertIsNotNone(first_system) + self.assertEqual(first_system["content"], "System prompt") + + # Should get middle messages (indices 1-4) + self.assertEqual(len(result.messages), 4) + self.assertEqual(result.messages[0]["content"], "Message 1") + self.assertEqual(result.messages[-1]["content"], "Response 2") + + # Last index should be 4 (0-indexed) + self.assertEqual(result.last_summarized_index, 4) + + def test_get_messages_to_summarize_no_system(self): + """Test message extraction when there's no system message.""" + context = LLMContext() + + # Add messages without system prompt + context.add_message({"role": "user", "content": "Message 1"}) + context.add_message({"role": "assistant", "content": "Response 1"}) + context.add_message({"role": "user", "content": "Message 2"}) + context.add_message({"role": "assistant", "content": "Response 2"}) + + # Keep last 1 message + result = LLMContextSummarizationUtil.get_messages_to_summarize(context, 1) + + # Get first system message from context + first_system = None + for msg in context.messages: + if msg.get("role") == "system": + first_system = msg + break + + # Should have no system message + self.assertIsNone(first_system) + + # Should get first 3 messages + self.assertEqual(len(result.messages), 3) + self.assertEqual(result.last_summarized_index, 2) + + def test_get_messages_to_summarize_insufficient(self): + """Test when there aren't enough messages to summarize.""" + context = LLMContext() + + # Add only 2 messages + context.add_message({"role": "user", "content": "Message 1"}) + context.add_message({"role": "assistant", "content": "Response 1"}) + + # Try to keep 2 messages (same as total) + result = LLMContextSummarizationUtil.get_messages_to_summarize(context, 2) + + # Should return empty + self.assertEqual(len(result.messages), 0) + self.assertEqual(result.last_summarized_index, -1) + + def test_format_messages_for_summary(self): + """Test message formatting for summary.""" + + messages = [ + {"role": "user", "content": "Hello"}, + {"role": "assistant", "content": "Hi there"}, + {"role": "user", "content": "How are you?"}, + ] + + transcript = LLMContextSummarizationUtil.format_messages_for_summary(messages) + + self.assertIn("USER: Hello", transcript) + self.assertIn("ASSISTANT: Hi there", transcript) + self.assertIn("USER: How are you?", transcript) + + def test_format_messages_with_list_content(self): + """Test formatting messages with list content.""" + + messages = [ + { + "role": "user", + "content": [ + {"type": "text", "text": "First part"}, + {"type": "text", "text": "Second part"}, + ], + } + ] + + transcript = LLMContextSummarizationUtil.format_messages_for_summary(messages) + + self.assertIn("USER: First part Second part", transcript) + + +class TestLLMContextSummarizationConfig(unittest.TestCase): + """Tests for LLMContextSummarizationConfig.""" + + def test_default_config(self): + """Test default configuration values.""" + config = LLMContextSummarizationConfig() + + self.assertEqual(config.max_context_tokens, 8000) + self.assertEqual(config.max_unsummarized_messages, 20) + self.assertEqual(config.min_messages_after_summary, 4) + self.assertIsNone(config.summarization_prompt) + + def test_custom_config(self): + """Test custom configuration.""" + config = LLMContextSummarizationConfig( + max_context_tokens=2500, + target_context_tokens=2000, + max_unsummarized_messages=15, + min_messages_after_summary=4, + summarization_prompt="Custom prompt", + ) + + self.assertEqual(config.max_context_tokens, 2500) + self.assertEqual(config.target_context_tokens, 2000) + self.assertEqual(config.max_unsummarized_messages, 15) + self.assertEqual(config.min_messages_after_summary, 4) + self.assertEqual(config.summary_prompt, "Custom prompt") + + def test_summary_prompt_property(self): + """Test summary_prompt property uses default when None.""" + config = LLMContextSummarizationConfig() + self.assertIn("summarizing a conversation", config.summary_prompt.lower()) + + config_with_custom = LLMContextSummarizationConfig(summarization_prompt="Custom") + self.assertEqual(config_with_custom.summary_prompt, "Custom") + + +class TestFunctionCallHandling(unittest.TestCase): + """Tests for function call handling in summarization.""" + + def test_function_call_in_progress_not_summarized(self): + """Test that messages with function calls in progress are not summarized.""" + context = LLMContext() + + # Add messages including a function call without result + context.add_message({"role": "system", "content": "System prompt"}) + context.add_message({"role": "user", "content": "What time is it?"}) + context.add_message( + { + "role": "assistant", + "content": "", + "tool_calls": [ + { + "id": "call_123", + "type": "function", + "function": {"name": "get_time", "arguments": "{}"}, + } + ], + } + ) + # No tool result yet - function call is in progress + context.add_message({"role": "user", "content": "Latest message"}) + + # Try to keep last 1 message + result = LLMContextSummarizationUtil.get_messages_to_summarize(context, 1) + + # Should only get the first user message, stopping before the function call + self.assertEqual(len(result.messages), 1) + self.assertEqual(result.messages[0]["content"], "What time is it?") + self.assertEqual(result.last_summarized_index, 1) + + def test_completed_function_call_can_be_summarized(self): + """Test that completed function calls can be summarized.""" + context = LLMContext() + + # Add messages including a complete function call sequence + context.add_message({"role": "system", "content": "System prompt"}) + context.add_message({"role": "user", "content": "What time is it?"}) + context.add_message( + { + "role": "assistant", + "content": "", + "tool_calls": [ + { + "id": "call_123", + "type": "function", + "function": {"name": "get_time", "arguments": "{}"}, + } + ], + } + ) + # Tool result completes the function call + context.add_message( + {"role": "tool", "tool_call_id": "call_123", "content": '{"time": "10:30 AM"}'} + ) + context.add_message({"role": "assistant", "content": "It's 10:30 AM"}) + context.add_message({"role": "user", "content": "Latest message"}) + + # Try to keep last 1 message + result = LLMContextSummarizationUtil.get_messages_to_summarize(context, 1) + + # Should get all messages except the last one (complete function call is included) + self.assertEqual(len(result.messages), 4) + self.assertEqual(result.messages[0]["content"], "What time is it?") + self.assertEqual(result.messages[-1]["content"], "It's 10:30 AM") + self.assertEqual(result.last_summarized_index, 4) + + def test_multiple_function_calls_in_progress(self): + """Test handling of multiple function calls in progress.""" + context = LLMContext() + + # Add messages with multiple function calls + context.add_message({"role": "system", "content": "System prompt"}) + context.add_message({"role": "user", "content": "Message 1"}) + context.add_message({"role": "assistant", "content": "Response 1"}) + context.add_message({"role": "user", "content": "What's the time and date?"}) + context.add_message( + { + "role": "assistant", + "content": "", + "tool_calls": [ + { + "id": "call_time", + "type": "function", + "function": {"name": "get_time", "arguments": "{}"}, + }, + { + "id": "call_date", + "type": "function", + "function": {"name": "get_date", "arguments": "{}"}, + }, + ], + } + ) + # Only one tool result - other call still in progress + context.add_message( + {"role": "tool", "tool_call_id": "call_time", "content": '{"time": "10:30 AM"}'} + ) + context.add_message({"role": "user", "content": "Latest message"}) + + # Try to keep last 1 message + result = LLMContextSummarizationUtil.get_messages_to_summarize(context, 1) + + # Should stop before the function call that's in progress + # Messages to summarize: indices 1, 2, 3 (stops before index 4 where incomplete call is) + self.assertEqual(len(result.messages), 3) + self.assertEqual(result.last_summarized_index, 3) + + def test_multiple_completed_function_calls(self): + """Test that multiple completed function calls can be summarized.""" + context = LLMContext() + + # Add messages with multiple completed function calls + context.add_message({"role": "system", "content": "System prompt"}) + context.add_message({"role": "user", "content": "What's the time and date?"}) + context.add_message( + { + "role": "assistant", + "content": "", + "tool_calls": [ + { + "id": "call_time", + "type": "function", + "function": {"name": "get_time", "arguments": "{}"}, + }, + { + "id": "call_date", + "type": "function", + "function": {"name": "get_date", "arguments": "{}"}, + }, + ], + } + ) + # Both tool results provided + context.add_message( + {"role": "tool", "tool_call_id": "call_time", "content": '{"time": "10:30 AM"}'} + ) + context.add_message( + { + "role": "tool", + "tool_call_id": "call_date", + "content": '{"date": "January 1, 2024"}', + } + ) + context.add_message({"role": "assistant", "content": "It's 10:30 AM on January 1, 2024"}) + context.add_message({"role": "user", "content": "Latest message"}) + + # Try to keep last 1 message + result = LLMContextSummarizationUtil.get_messages_to_summarize(context, 1) + + # Should get all messages except the last one (all function calls completed) + self.assertEqual(len(result.messages), 5) + self.assertEqual(result.last_summarized_index, 5) + + def test_sequential_function_calls_mixed_completion(self): + """Test sequential function calls with mixed completion states.""" + context = LLMContext() + + # Add messages with sequential function calls + context.add_message({"role": "system", "content": "System prompt"}) + + # First function call - completed + context.add_message({"role": "user", "content": "What time is it?"}) + context.add_message( + { + "role": "assistant", + "content": "", + "tool_calls": [ + { + "id": "call_1", + "type": "function", + "function": {"name": "get_time", "arguments": "{}"}, + } + ], + } + ) + context.add_message( + {"role": "tool", "tool_call_id": "call_1", "content": '{"time": "10:30 AM"}'} + ) + context.add_message({"role": "assistant", "content": "It's 10:30 AM"}) + + # Second function call - in progress + context.add_message({"role": "user", "content": "What's the date?"}) + context.add_message( + { + "role": "assistant", + "content": "", + "tool_calls": [ + { + "id": "call_2", + "type": "function", + "function": {"name": "get_date", "arguments": "{}"}, + } + ], + } + ) + # No result for call_2 yet + context.add_message({"role": "user", "content": "Latest message"}) + + # Try to keep last 1 message + result = LLMContextSummarizationUtil.get_messages_to_summarize(context, 1) + + # Should get messages up to and including the first completed function call + # but stop before the second function call that's in progress + # Messages to summarize: indices 1, 2, 3, 4, 5 (stops before index 6 where incomplete call is) + self.assertEqual(len(result.messages), 5) + self.assertEqual(result.messages[-1]["content"], "What's the date?") + self.assertEqual(result.last_summarized_index, 5) + + def test_function_call_formatting_in_transcript(self): + """Test that function calls are properly formatted in transcript.""" + + messages = [ + {"role": "user", "content": "What time is it?"}, + { + "role": "assistant", + "content": "", + "tool_calls": [ + { + "id": "call_123", + "type": "function", + "function": {"name": "get_time", "arguments": "{}"}, + } + ], + }, + {"role": "tool", "tool_call_id": "call_123", "content": '{"time": "10:30 AM"}'}, + {"role": "assistant", "content": "It's 10:30 AM"}, + ] + + transcript = LLMContextSummarizationUtil.format_messages_for_summary(messages) + + # Check that function call is included + self.assertIn("TOOL_CALL: get_time({})", transcript) + # Check that tool result is included + self.assertIn('TOOL_RESULT[call_123]: {"time": "10:30 AM"}', transcript) + + def test_no_function_calls(self): + """Test that summarization works normally without function calls.""" + context = LLMContext() + + # Add normal conversation without function calls + context.add_message({"role": "system", "content": "System prompt"}) + context.add_message({"role": "user", "content": "Hello"}) + context.add_message({"role": "assistant", "content": "Hi"}) + context.add_message({"role": "user", "content": "How are you?"}) + context.add_message({"role": "assistant", "content": "I'm good"}) + context.add_message({"role": "user", "content": "Latest message"}) + + # Try to keep last 1 message + result = LLMContextSummarizationUtil.get_messages_to_summarize(context, 1) + + # Should get all messages except the last one + self.assertEqual(len(result.messages), 4) + self.assertEqual(result.last_summarized_index, 4) + + +class TestSummaryGenerationExceptions(unittest.IsolatedAsyncioTestCase): + """Tests for summary generation exception handling.""" + + async def test_generate_summary_raises_on_no_messages(self): + """Test that _generate_summary raises RuntimeError when there are no messages to summarize.""" + llm_service = LLMService() + context = LLMContext() + + # Add only one message (system), which isn't enough to summarize + context.add_message({"role": "system", "content": "System prompt"}) + + frame = LLMContextSummaryRequestFrame( + request_id="test", + context=context, + min_messages_to_keep=1, + target_context_tokens=1000, + summarization_prompt="Summarize this", + ) + + with self.assertRaises(RuntimeError) as cm: + await llm_service._generate_summary(frame) + + self.assertEqual(str(cm.exception), "No messages to summarize") + + async def test_generate_summary_raises_on_no_run_inference(self): + """Test that _generate_summary raises RuntimeError when run_inference is not implemented.""" + # Create a minimal LLM service - base class raises NotImplementedError + llm_service = LLMService() + + context = LLMContext() + context.add_message({"role": "user", "content": "Message 1"}) + context.add_message({"role": "assistant", "content": "Response 1"}) + context.add_message({"role": "user", "content": "Message 2"}) + + frame = LLMContextSummaryRequestFrame( + request_id="test", + context=context, + min_messages_to_keep=1, + target_context_tokens=1000, + summarization_prompt="Summarize this", + ) + + with self.assertRaises(RuntimeError) as cm: + await llm_service._generate_summary(frame) + + self.assertIn("does not implement run_inference", str(cm.exception)) + self.assertIn("LLMService", str(cm.exception)) + + async def test_generate_summary_raises_on_empty_response(self): + """Test that _generate_summary raises RuntimeError when LLM returns empty summary.""" + llm_service = LLMService() + # Mock run_inference to return None + llm_service.run_inference = AsyncMock(return_value=None) + + context = LLMContext() + context.add_message({"role": "user", "content": "Message 1"}) + context.add_message({"role": "assistant", "content": "Response 1"}) + context.add_message({"role": "user", "content": "Message 2"}) + + frame = LLMContextSummaryRequestFrame( + request_id="test", + context=context, + min_messages_to_keep=1, + target_context_tokens=1000, + summarization_prompt="Summarize this", + ) + + with self.assertRaises(RuntimeError) as cm: + await llm_service._generate_summary(frame) + + self.assertEqual(str(cm.exception), "LLM returned empty summary") + + async def test_generate_summary_task_handles_exceptions(self): + """Test that _generate_summary_task properly handles exceptions from _generate_summary.""" + llm_service = LLMService() + + # Mock broadcast_frame to capture the result + broadcast_calls = [] + + async def mock_broadcast(frame_class, **kwargs): + broadcast_calls.append((frame_class, kwargs)) + + llm_service.broadcast_frame = mock_broadcast + + # Mock push_error + llm_service.push_error = AsyncMock() + + context = LLMContext() + context.add_message({"role": "system", "content": "System prompt"}) + + frame = LLMContextSummaryRequestFrame( + request_id="test_123", + context=context, + min_messages_to_keep=1, + target_context_tokens=1000, + summarization_prompt="Summarize this", + ) + + # Execute the task + await llm_service._generate_summary_task(frame) + + # Verify broadcast_frame was called with error + self.assertEqual(len(broadcast_calls), 1) + frame_class, kwargs = broadcast_calls[0] + self.assertEqual(kwargs["request_id"], "test_123") + self.assertEqual(kwargs["summary"], "") + self.assertEqual(kwargs["last_summarized_index"], -1) + self.assertEqual( + kwargs["error"], "Error generating context summary: No messages to summarize" + ) + + # Verify push_error was called + llm_service.push_error.assert_called_once() + + async def test_generate_summary_success(self): + """Test that _generate_summary returns successfully with valid input.""" + llm_service = LLMService() + # Mock run_inference to return a summary + llm_service.run_inference = AsyncMock(return_value="This is a summary of the conversation") + + context = LLMContext() + context.add_message({"role": "user", "content": "Message 1"}) + context.add_message({"role": "assistant", "content": "Response 1"}) + context.add_message({"role": "user", "content": "Message 2"}) + + frame = LLMContextSummaryRequestFrame( + request_id="test", + context=context, + min_messages_to_keep=1, + target_context_tokens=1000, + summarization_prompt="Summarize this", + ) + + summary, last_index = await llm_service._generate_summary(frame) + + self.assertEqual(summary, "This is a summary of the conversation") + self.assertGreater(last_index, -1) + self.assertEqual(last_index, 1) # Should be the index of the last summarized message + + +if __name__ == "__main__": + unittest.main() From 4a00e6829faafc67f8f54f64f261e508a7a1280d Mon Sep 17 00:00:00 2001 From: filipi87 Date: Tue, 10 Feb 2026 18:58:44 -0300 Subject: [PATCH 0435/1060] Automated tests for the context summarizer. --- tests/test_llm_context_summarizer.py | 296 +++++++++++++++++++++++++++ 1 file changed, 296 insertions(+) create mode 100644 tests/test_llm_context_summarizer.py diff --git a/tests/test_llm_context_summarizer.py b/tests/test_llm_context_summarizer.py new file mode 100644 index 000000000..7555a8762 --- /dev/null +++ b/tests/test_llm_context_summarizer.py @@ -0,0 +1,296 @@ +# +# Copyright (c) 2024-2026, Daily +# +# SPDX-License-Identifier: BSD 2-Clause License +# + +import asyncio +import unittest + +from pipecat.frames.frames import ( + InterruptionFrame, + LLMContextSummaryRequestFrame, + LLMContextSummaryResultFrame, + LLMFullResponseStartFrame, +) +from pipecat.processors.aggregators.llm_context import LLMContext +from pipecat.processors.aggregators.llm_context_summarizer import LLMContextSummarizer +from pipecat.utils.asyncio.task_manager import TaskManager, TaskManagerParams +from pipecat.utils.context.llm_context_summarization import LLMContextSummarizationConfig + + +class TestLLMContextSummarizer(unittest.IsolatedAsyncioTestCase): + async def asyncSetUp(self): + self.task_manager = TaskManager() + self.task_manager.setup(TaskManagerParams(loop=asyncio.get_running_loop())) + + self.context = LLMContext( + messages=[ + {"role": "system", "content": "You are a helpful assistant."}, + ] + ) + + async def test_summarization_triggered_by_token_limit(self): + """Test that summarization is triggered when token limit is reached.""" + config = LLMContextSummarizationConfig( + max_context_tokens=100, # Very low to trigger easily + max_unsummarized_messages=100, # High so it doesn't trigger by message count + ) + + summarizer = LLMContextSummarizer(context=self.context, config=config) + await summarizer.setup(self.task_manager) + + request_frame = None + + @summarizer.event_handler("on_request_summarization") + async def on_request_summarization(summarizer, frame): + nonlocal request_frame + request_frame = frame + + # Add messages to exceed token limit + for i in range(10): + self.context.add_message( + { + "role": "user", + "content": "This is a test message that adds tokens to the context.", + } + ) + + # Trigger check by processing LLMFullResponseStartFrame + await summarizer.process_frame(LLMFullResponseStartFrame()) + + # Should have triggered summarization + self.assertIsNotNone(request_frame) + self.assertIsInstance(request_frame, LLMContextSummaryRequestFrame) + self.assertEqual(request_frame.context, self.context) + + await summarizer.cleanup() + + async def test_summarization_triggered_by_message_count(self): + """Test that summarization is triggered when message count threshold is reached.""" + config = LLMContextSummarizationConfig( + max_context_tokens=100000, # Very high so it doesn't trigger by tokens + max_unsummarized_messages=5, # Low to trigger easily + ) + + summarizer = LLMContextSummarizer(context=self.context, config=config) + await summarizer.setup(self.task_manager) + + request_frame = None + + @summarizer.event_handler("on_request_summarization") + async def on_request_summarization(summarizer, frame): + nonlocal request_frame + request_frame = frame + + # Add messages to exceed message count + for i in range(6): + self.context.add_message({"role": "user", "content": f"Message {i}"}) + + # Trigger check + await summarizer.process_frame(LLMFullResponseStartFrame()) + + # Should have triggered summarization + self.assertIsNotNone(request_frame) + self.assertIsInstance(request_frame, LLMContextSummaryRequestFrame) + + await summarizer.cleanup() + + async def test_summarization_not_triggered_below_thresholds(self): + """Test that summarization is not triggered when below thresholds.""" + config = LLMContextSummarizationConfig( + max_context_tokens=10000, + max_unsummarized_messages=20, + ) + + summarizer = LLMContextSummarizer(context=self.context, config=config) + await summarizer.setup(self.task_manager) + + request_frame = None + + @summarizer.event_handler("on_request_summarization") + async def on_request_summarization(summarizer, frame): + nonlocal request_frame + request_frame = frame + + # Add a few messages (below threshold) + for i in range(3): + self.context.add_message({"role": "user", "content": "Short message"}) + + # Trigger check + await summarizer.process_frame(LLMFullResponseStartFrame()) + + # Should NOT have triggered summarization + self.assertIsNone(request_frame) + + await summarizer.cleanup() + + async def test_summarization_in_progress_prevents_duplicate(self): + """Test that a summarization in progress prevents triggering another.""" + config = LLMContextSummarizationConfig( + max_context_tokens=50, # Very low + max_unsummarized_messages=100, + ) + + summarizer = LLMContextSummarizer(context=self.context, config=config) + await summarizer.setup(self.task_manager) + + request_count = 0 + + @summarizer.event_handler("on_request_summarization") + async def on_request_summarization(summarizer, frame): + nonlocal request_count + request_count += 1 + + # Add enough messages to trigger + for i in range(10): + self.context.add_message({"role": "user", "content": "Test message to add tokens."}) + + # First trigger - should request summarization + await summarizer.process_frame(LLMFullResponseStartFrame()) + self.assertEqual(request_count, 1) + + # Second trigger while first is in progress - should NOT request again + await summarizer.process_frame(LLMFullResponseStartFrame()) + self.assertEqual(request_count, 1) + + await summarizer.cleanup() + + async def test_summary_result_handling(self): + """Test that summary results are processed and applied correctly.""" + config = LLMContextSummarizationConfig(max_context_tokens=50, min_messages_after_summary=2) + + summarizer = LLMContextSummarizer(context=self.context, config=config) + await summarizer.setup(self.task_manager) + + # Add messages and trigger summarization + for i in range(10): + self.context.add_message({"role": "user", "content": "Test message."}) + + request_frame = None + + @summarizer.event_handler("on_request_summarization") + async def on_request_summarization(summarizer, frame): + nonlocal request_frame + request_frame = frame + + original_message_count = len(self.context.messages) + await summarizer.process_frame(LLMFullResponseStartFrame()) + self.assertIsNotNone(request_frame) + + # Simulate receiving a summary result + summary_result = LLMContextSummaryResultFrame( + request_id=request_frame.request_id, + summary="This is a test summary.", + last_summarized_index=5, + error=None, + ) + + await summarizer.process_frame(summary_result) + + # Should have applied the summary and reduced message count + # Expected: system message + summary message + 2 recent messages = 4 messages + # (since last_summarized_index=5, we keep messages after index 5) + self.assertLess(len(self.context.messages), original_message_count) + + # Check that summary was added + summary_messages = [ + msg + for msg in self.context.messages + if "Conversation summary:" in msg.get("content", "") + ] + self.assertEqual(len(summary_messages), 1) + + await summarizer.cleanup() + + async def test_interruption_cancels_summarization(self): + """Test that an interruption cancels pending summarization.""" + config = LLMContextSummarizationConfig(max_context_tokens=50) + + summarizer = LLMContextSummarizer(context=self.context, config=config) + await summarizer.setup(self.task_manager) + + # Add messages and trigger summarization + for i in range(10): + self.context.add_message({"role": "user", "content": "Test message."}) + + request_count = 0 + + @summarizer.event_handler("on_request_summarization") + async def on_request_summarization(summarizer, frame): + nonlocal request_count + request_count += 1 + + await summarizer.process_frame(LLMFullResponseStartFrame()) + self.assertEqual(request_count, 1) + + # Process interruption + await summarizer.process_frame(InterruptionFrame()) + + # Try to trigger again - should work since the previous one was canceled + await summarizer.process_frame(LLMFullResponseStartFrame()) + self.assertEqual(request_count, 2) + + await summarizer.cleanup() + + async def test_stale_summary_result_ignored(self): + """Test that stale summary results are ignored.""" + config = LLMContextSummarizationConfig(max_context_tokens=50, min_messages_after_summary=2) + + summarizer = LLMContextSummarizer(context=self.context, config=config) + await summarizer.setup(self.task_manager) + + # Add messages and trigger summarization + for i in range(10): + self.context.add_message({"role": "user", "content": "Test message."}) + + request_frame = None + + @summarizer.event_handler("on_request_summarization") + async def on_request_summarization(summarizer, frame): + nonlocal request_frame + request_frame = frame + + original_message_count = len(self.context.messages) + await summarizer.process_frame(LLMFullResponseStartFrame()) + valid_request_id = request_frame.request_id + + # Send a stale summary result (wrong request_id) + stale_result = LLMContextSummaryResultFrame( + request_id="stale-id-123", + summary="Stale summary", + last_summarized_index=3, + error=None, + ) + + await summarizer.process_frame(stale_result) + + # Should be ignored - message count should not change + self.assertEqual(len(self.context.messages), original_message_count) + + # Send the correct summary result + valid_result = LLMContextSummaryResultFrame( + request_id=valid_request_id, + summary="Valid summary", + last_summarized_index=5, + error=None, + ) + + await summarizer.process_frame(valid_result) + + # Should be processed - message count should decrease + self.assertLess(len(self.context.messages), original_message_count) + + # Check that summary was added + summary_messages = [ + msg + for msg in self.context.messages + if "Conversation summary:" in msg.get("content", "") + ] + self.assertEqual(len(summary_messages), 1) + + await summarizer.cleanup() + + +if __name__ == "__main__": + unittest.main() From 5deb80932baf25e37ac10ca1651c7a8f6f104afb Mon Sep 17 00:00:00 2001 From: filipi87 Date: Tue, 10 Feb 2026 18:58:55 -0300 Subject: [PATCH 0436/1060] Context summarization example with OpenAI --- .../54-context-summarization-openai.py | 188 ++++++++++++++++++ 1 file changed, 188 insertions(+) create mode 100644 examples/foundational/54-context-summarization-openai.py diff --git a/examples/foundational/54-context-summarization-openai.py b/examples/foundational/54-context-summarization-openai.py new file mode 100644 index 000000000..652a3af13 --- /dev/null +++ b/examples/foundational/54-context-summarization-openai.py @@ -0,0 +1,188 @@ +# +# Copyright (c) 2024-2026, Daily +# +# SPDX-License-Identifier: BSD 2-Clause License +# + +"""Example demonstrating context summarization feature. + +This example shows how to enable and configure context summarization to automatically +compress conversation history when token limits are approached. It also demonstrates +that summarization correctly handles function calls, preserving incomplete function +call sequences. +""" + +import asyncio +import os + +from dotenv import load_dotenv +from loguru import logger + +from pipecat.adapters.schemas.function_schema import FunctionSchema +from pipecat.adapters.schemas.tools_schema import ToolsSchema +from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3 +from pipecat.audio.vad.silero import SileroVADAnalyzer +from pipecat.audio.vad.vad_analyzer import VADParams +from pipecat.frames.frames import LLMRunFrame +from pipecat.pipeline.pipeline import Pipeline +from pipecat.pipeline.runner import PipelineRunner +from pipecat.pipeline.task import PipelineParams, PipelineTask +from pipecat.processors.aggregators.llm_context import LLMContext +from pipecat.processors.aggregators.llm_response_universal import ( + LLMAssistantAggregatorParams, + LLMContextAggregatorPair, + LLMUserAggregatorParams, +) +from pipecat.runner.types import RunnerArguments +from pipecat.runner.utils import create_transport +from pipecat.services.cartesia.tts import CartesiaTTSService +from pipecat.services.deepgram.stt import DeepgramSTTService +from pipecat.services.llm_service import FunctionCallParams +from pipecat.services.openai.llm import OpenAILLMService +from pipecat.transports.base_transport import BaseTransport, TransportParams +from pipecat.transports.daily.transport import DailyParams +from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams +from pipecat.turns.user_stop import TurnAnalyzerUserTurnStopStrategy +from pipecat.turns.user_turn_strategies import UserTurnStrategies +from pipecat.utils.context.llm_context_summarization import LLMContextSummarizationConfig + +load_dotenv(override=True) + +# We use lambdas to defer transport parameter creation until the transport +# type is selected at runtime. +transport_params = { + "daily": lambda: DailyParams( + audio_in_enabled=True, + audio_out_enabled=True, + ), + "twilio": lambda: FastAPIWebsocketParams( + audio_in_enabled=True, + audio_out_enabled=True, + ), + "webrtc": lambda: TransportParams( + audio_in_enabled=True, + audio_out_enabled=True, + ), +} + + +# Tool functions for the LLM +async def get_current_weather(params: FunctionCallParams): + """Get the current time in a readable format.""" + logger.info("Tool called: get_current_weather") + await asyncio.sleep(1) # Simulate some processing + await params.result_callback({"conditions": "nice", "temperature": "75"}) + + +async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): + logger.info("Starting bot") + + stt = DeepgramSTTService(api_key=os.getenv("DEEPGRAM_API_KEY")) + + tts = CartesiaTTSService( + api_key=os.getenv("CARTESIA_API_KEY"), + voice_id="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady + ) + + llm = OpenAILLMService(api_key=os.getenv("OPENAI_API_KEY")) + + # Register tool functions + llm.register_function("get_current_weather", get_current_weather) + + weather_function = FunctionSchema( + name="get_current_weather", + description="Get the current weather", + properties={ + "location": { + "type": "string", + "description": "The city and state, e.g. San Francisco, CA", + }, + "format": { + "type": "string", + "enum": ["celsius", "fahrenheit"], + "description": "The temperature unit to use. Infer this from the user's location.", + }, + }, + required=["location", "format"], + ) + tools = ToolsSchema(standard_tools=[weather_function]) + + messages = [ + { + "role": "system", + "content": "You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way. You have access to tools to get the current weather - use them when relevant.", + }, + ] + + context = LLMContext(messages, tools=tools) + + # Create aggregators with summarization enabled + user_aggregator, assistant_aggregator = LLMContextAggregatorPair( + context, + user_params=LLMUserAggregatorParams( + user_turn_strategies=UserTurnStrategies( + stop=[TurnAnalyzerUserTurnStopStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3())] + ), + vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), + ), + assistant_params=LLMAssistantAggregatorParams( + enable_context_summarization=True, + # Optional: customize context summarization behavior + # Using low limits to demonstrate the feature quickly + context_summarization_config=LLMContextSummarizationConfig( + max_context_tokens=1000, # Trigger summarization at 1000 tokens + target_context_tokens=800, # Target context size for the summarization + max_unsummarized_messages=10, # Or when 10 new messages accumulate + min_messages_after_summary=2, # Keep last 2 messages uncompressed + ), + ), + ) + + pipeline = Pipeline( + [ + transport.input(), # Transport user input + stt, + user_aggregator, # User responses + llm, # LLM + tts, # TTS + transport.output(), # Transport bot output + assistant_aggregator, # Assistant spoken responses + ] + ) + + task = PipelineTask( + pipeline, + params=PipelineParams( + enable_metrics=True, + enable_usage_metrics=True, + ), + idle_timeout_secs=runner_args.pipeline_idle_timeout_secs, + ) + + @transport.event_handler("on_client_connected") + async def on_client_connected(transport, client): + logger.info("Client connected") + # Kick off the conversation. + messages.append({"role": "system", "content": "Please introduce yourself to the user."}) + await task.queue_frames([LLMRunFrame()]) + + @transport.event_handler("on_client_disconnected") + async def on_client_disconnected(transport, client): + logger.info("Client disconnected") + await task.cancel() + + runner = PipelineRunner(handle_sigint=runner_args.handle_sigint) + + await runner.run(task) + + +async def bot(runner_args: RunnerArguments): + """Main bot entry point compatible with Pipecat Cloud.""" + transport = await create_transport(runner_args, transport_params) + await run_bot(transport, runner_args) + + +if __name__ == "__main__": + from pipecat.runner.run import main + + main() From ba242d487525415ba57431516cea6d774391943f Mon Sep 17 00:00:00 2001 From: filipi87 Date: Tue, 10 Feb 2026 18:59:03 -0300 Subject: [PATCH 0437/1060] Context summarization example with Google --- .../54a-context-summarization-google.py | 188 ++++++++++++++++++ 1 file changed, 188 insertions(+) create mode 100644 examples/foundational/54a-context-summarization-google.py diff --git a/examples/foundational/54a-context-summarization-google.py b/examples/foundational/54a-context-summarization-google.py new file mode 100644 index 000000000..a7fe4ba5e --- /dev/null +++ b/examples/foundational/54a-context-summarization-google.py @@ -0,0 +1,188 @@ +# +# Copyright (c) 2024-2026, Daily +# +# SPDX-License-Identifier: BSD 2-Clause License +# + +"""Example demonstrating context summarization feature. + +This example shows how to enable and configure context summarization to automatically +compress conversation history when token limits are approached. It also demonstrates +that summarization correctly handles function calls, preserving incomplete function +call sequences. +""" + +import asyncio +import os + +from dotenv import load_dotenv +from loguru import logger + +from pipecat.adapters.schemas.function_schema import FunctionSchema +from pipecat.adapters.schemas.tools_schema import ToolsSchema +from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3 +from pipecat.audio.vad.silero import SileroVADAnalyzer +from pipecat.audio.vad.vad_analyzer import VADParams +from pipecat.frames.frames import LLMRunFrame +from pipecat.pipeline.pipeline import Pipeline +from pipecat.pipeline.runner import PipelineRunner +from pipecat.pipeline.task import PipelineParams, PipelineTask +from pipecat.processors.aggregators.llm_context import LLMContext +from pipecat.processors.aggregators.llm_response_universal import ( + LLMAssistantAggregatorParams, + LLMContextAggregatorPair, + LLMUserAggregatorParams, +) +from pipecat.runner.types import RunnerArguments +from pipecat.runner.utils import create_transport +from pipecat.services.cartesia.tts import CartesiaTTSService +from pipecat.services.deepgram.stt import DeepgramSTTService +from pipecat.services.google import GoogleLLMService +from pipecat.services.llm_service import FunctionCallParams +from pipecat.transports.base_transport import BaseTransport, TransportParams +from pipecat.transports.daily.transport import DailyParams +from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams +from pipecat.turns.user_stop import TurnAnalyzerUserTurnStopStrategy +from pipecat.turns.user_turn_strategies import UserTurnStrategies +from pipecat.utils.context.llm_context_summarization import LLMContextSummarizationConfig + +load_dotenv(override=True) + +# We use lambdas to defer transport parameter creation until the transport +# type is selected at runtime. +transport_params = { + "daily": lambda: DailyParams( + audio_in_enabled=True, + audio_out_enabled=True, + ), + "twilio": lambda: FastAPIWebsocketParams( + audio_in_enabled=True, + audio_out_enabled=True, + ), + "webrtc": lambda: TransportParams( + audio_in_enabled=True, + audio_out_enabled=True, + ), +} + + +# Tool functions for the LLM +async def get_current_weather(params: FunctionCallParams): + """Get the current time in a readable format.""" + logger.info("Tool called: get_current_weather") + await asyncio.sleep(1) # Simulate some processing + await params.result_callback({"conditions": "nice", "temperature": "75"}) + + +async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): + logger.info("Starting bot") + + stt = DeepgramSTTService(api_key=os.getenv("DEEPGRAM_API_KEY")) + + tts = CartesiaTTSService( + api_key=os.getenv("CARTESIA_API_KEY"), + voice_id="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady + ) + + llm = GoogleLLMService(api_key=os.getenv("GOOGLE_API_KEY")) + + # Register tool functions + llm.register_function("get_current_weather", get_current_weather) + + weather_function = FunctionSchema( + name="get_current_weather", + description="Get the current weather", + properties={ + "location": { + "type": "string", + "description": "The city and state, e.g. San Francisco, CA", + }, + "format": { + "type": "string", + "enum": ["celsius", "fahrenheit"], + "description": "The temperature unit to use. Infer this from the user's location.", + }, + }, + required=["location", "format"], + ) + tools = ToolsSchema(standard_tools=[weather_function]) + + messages = [ + { + "role": "system", + "content": "You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way. You have access to tools to get the current weather - use them when relevant.", + }, + ] + + context = LLMContext(messages, tools=tools) + + # Create aggregators with summarization enabled + user_aggregator, assistant_aggregator = LLMContextAggregatorPair( + context, + user_params=LLMUserAggregatorParams( + user_turn_strategies=UserTurnStrategies( + stop=[TurnAnalyzerUserTurnStopStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3())] + ), + vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), + ), + assistant_params=LLMAssistantAggregatorParams( + enable_context_summarization=True, + # Optional: customize context summarization behavior + # Using low limits to demonstrate the feature quickly + context_summarization_config=LLMContextSummarizationConfig( + max_context_tokens=1000, # Trigger summarization at 1000 tokens + target_context_tokens=800, # Target context size for the summarization + max_unsummarized_messages=10, # Or when 10 new messages accumulate + min_messages_after_summary=2, # Keep last 2 messages uncompressed + ), + ), + ) + + pipeline = Pipeline( + [ + transport.input(), # Transport user input + stt, + user_aggregator, # User responses + llm, # LLM + tts, # TTS + transport.output(), # Transport bot output + assistant_aggregator, # Assistant spoken responses + ] + ) + + task = PipelineTask( + pipeline, + params=PipelineParams( + enable_metrics=True, + enable_usage_metrics=True, + ), + idle_timeout_secs=runner_args.pipeline_idle_timeout_secs, + ) + + @transport.event_handler("on_client_connected") + async def on_client_connected(transport, client): + logger.info("Client connected") + # Kick off the conversation. + messages.append({"role": "system", "content": "Please introduce yourself to the user."}) + await task.queue_frames([LLMRunFrame()]) + + @transport.event_handler("on_client_disconnected") + async def on_client_disconnected(transport, client): + logger.info("Client disconnected") + await task.cancel() + + runner = PipelineRunner(handle_sigint=runner_args.handle_sigint) + + await runner.run(task) + + +async def bot(runner_args: RunnerArguments): + """Main bot entry point compatible with Pipecat Cloud.""" + transport = await create_transport(runner_args, transport_params) + await run_bot(transport, runner_args) + + +if __name__ == "__main__": + from pipecat.runner.run import main + + main() From 247569795588919345136152276702b6265c4e8d Mon Sep 17 00:00:00 2001 From: filipi87 Date: Tue, 10 Feb 2026 18:59:12 -0300 Subject: [PATCH 0438/1060] Changelog entries for context summarization --- changelog/3621.added.2.md | 1 + changelog/3621.added.md | 5 +++++ 2 files changed, 6 insertions(+) create mode 100644 changelog/3621.added.2.md create mode 100644 changelog/3621.added.md diff --git a/changelog/3621.added.2.md b/changelog/3621.added.2.md new file mode 100644 index 000000000..395c8bdfb --- /dev/null +++ b/changelog/3621.added.2.md @@ -0,0 +1 @@ +- Added new frames for context summarization: `LLMContextSummaryRequestFrame` and `LLMContextSummaryResultFrame`. diff --git a/changelog/3621.added.md b/changelog/3621.added.md new file mode 100644 index 000000000..8b2197eea --- /dev/null +++ b/changelog/3621.added.md @@ -0,0 +1,5 @@ +- Added context summarization feature to automatically compress conversation history when conversation length limits (by token or message count) are reached, enabling efficient long-running conversations. + - Configure via `enable_context_summarization=True` in `LLMAssistantAggregatorParams` + - Customize behavior with `LLMContextSummarizationConfig` (max tokens, thresholds, etc.) + - Automatically preserves incomplete function call sequences during summarization + - See new examples: `examples/foundational/54-context-summarization-openai.py` and `examples/foundational/54a-context-summarization-google.py` From a9a5edd8cafa68650416ed06fa8da6c0d99e7e7b Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Aleix=20Conchillo=20Flaqu=C3=A9?= Date: Tue, 10 Feb 2026 14:06:50 -0800 Subject: [PATCH 0439/1060] pyproject: add local smartturn as a default dependency --- .github/workflows/python-compatibility.yaml | 14 +- pyproject.toml | 6 +- uv.lock | 504 ++++++++++---------- 3 files changed, 260 insertions(+), 264 deletions(-) diff --git a/.github/workflows/python-compatibility.yaml b/.github/workflows/python-compatibility.yaml index 784e6f402..26f58f9dc 100644 --- a/.github/workflows/python-compatibility.yaml +++ b/.github/workflows/python-compatibility.yaml @@ -14,7 +14,7 @@ jobs: strategy: fail-fast: false matrix: - python-version: ['3.10.18', '3.11.13', '3.12.11', '3.13.5'] + python-version: ['3.10.19', '3.11.14', '3.12.12', '3.13.12'] name: Python ${{ matrix.python-version }} steps: @@ -40,20 +40,10 @@ jobs: uv python install ${{ matrix.python-version }} uv python pin ${{ matrix.python-version }} - - name: Test uv sync with all extras (Python < 3.13) - if: "!startsWith(matrix.python-version, '3.13.')" + - name: Test uv sync with all extras run: | uv sync --group dev --all-extras --no-extra krisp - - name: Test uv sync without PyTorch extras (Python 3.13+) - if: startsWith(matrix.python-version, '3.13.') - run: | - uv sync --group dev --all-extras \ - --no-extra krisp \ - --no-extra local-smart-turn \ - --no-extra moondream \ - --no-extra mlx-whisper - - name: Verify installation run: | uv run python --version diff --git a/pyproject.toml b/pyproject.toml index 2dece87e8..fd3db5031 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -38,6 +38,8 @@ dependencies = [ # Pinning numba to resolve package dependencies "numba==0.61.2", "wait_for2>=0.4.1; python_version<'3.12'", + # Pipecat optionals + "pipecat-ai[local-smart-turn-v3]", ] [project.urls] @@ -82,7 +84,7 @@ livekit = [ "livekit~=1.0.13", "livekit-api~=1.0.5", "tenacity>=8.2.3,<10.0.0", lmnt = [ "pipecat-ai[websockets-base]" ] local = [ "pyaudio~=0.2.14" ] local-smart-turn = [ "coremltools>=8.0", "transformers", "torch>=2.5.0,<3", "torchaudio>=2.5.0,<3" ] 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keepalive_interval params to WebsocketSTTService. When enabled, a background task sends silent audio (or a service-specific protocol message) when the connection has been idle, preventing server-side timeout disconnects. Subclasses override _send_keepalive(silence) to wrap the silence in their wire format. The default sends raw PCM bytes. Enables keepalive for ElevenLabs (10s), Gladia (20s), and Soniox (1s), replacing their per-service custom keepalive tasks. --- changelog/3675.fixed.md | 1 + src/pipecat/services/cartesia/stt.py | 27 +++--- src/pipecat/services/elevenlabs/stt.py | 21 ++++- src/pipecat/services/gladia/stt.py | 45 ++++------ src/pipecat/services/soniox/stt.py | 40 ++++----- src/pipecat/services/stt_service.py | 110 ++++++++++++++++++++++++- 6 files changed, 174 insertions(+), 70 deletions(-) create mode 100644 changelog/3675.fixed.md diff --git a/changelog/3675.fixed.md b/changelog/3675.fixed.md new file mode 100644 index 000000000..12e19efac --- /dev/null +++ b/changelog/3675.fixed.md @@ -0,0 +1 @@ +- Fixed WebSocket STT services (ElevenLabs, Cartesia, Gladia, Soniox) disconnecting due to idle timeout when no audio is being sent (e.g. when inactive behind a `ServiceSwitcher`). `WebsocketSTTService` now provides opt-in silence-based keepalive via `keepalive_timeout` and `keepalive_interval` parameters. diff --git a/src/pipecat/services/cartesia/stt.py b/src/pipecat/services/cartesia/stt.py index 2c76412f2..c4429226f 100644 --- a/src/pipecat/services/cartesia/stt.py +++ b/src/pipecat/services/cartesia/stt.py @@ -129,6 +129,11 @@ class CartesiaSTTService(WebsocketSTTService): Provides real-time speech transcription through WebSocket connection to Cartesia's Live transcription service. Supports both interim and final transcriptions with configurable models and languages. + + Cartesia disconnects WebSocket connections after 3 minutes of inactivity. + The timeout resets with each message (audio data or text command) sent to + the server. Silence-based keepalive is enabled by default to prevent this. + See: https://docs.cartesia.ai/api-reference/stt/stt """ def __init__( @@ -153,7 +158,13 @@ class CartesiaSTTService(WebsocketSTTService): **kwargs: Additional arguments passed to parent STTService. """ sample_rate = sample_rate or (live_options.sample_rate if live_options else None) - super().__init__(sample_rate=sample_rate, ttfs_p99_latency=ttfs_p99_latency, **kwargs) + super().__init__( + sample_rate=sample_rate, + ttfs_p99_latency=ttfs_p99_latency, + keepalive_timeout=120, + keepalive_interval=30, + **kwargs, + ) default_options = CartesiaLiveOptions( model="ink-whisper", @@ -248,10 +259,10 @@ class CartesiaSTTService(WebsocketSTTService): yield None async def _connect(self): - await super()._connect() - await self._connect_websocket() + await super()._connect() + if self._websocket and not self._receive_task: self._receive_task = self.create_task(self._receive_task_handler(self._report_error)) @@ -295,7 +306,7 @@ class CartesiaSTTService(WebsocketSTTService): return self._websocket raise Exception("Websocket not connected") - async def _process_messages(self): + async def _receive_messages(self): """Process incoming WebSocket messages.""" async for message in self._get_websocket(): try: @@ -306,14 +317,6 @@ class CartesiaSTTService(WebsocketSTTService): except Exception as e: logger.error(f"Error processing message: {e}") - async def _receive_messages(self): - while True: - await self._process_messages() - # Cartesia times out after 5 minutes of innactivity (no keepalive - # mechanism is available). So, we try to reconnect. - logger.debug(f"{self} Cartesia connection was disconnected (timeout?), reconnecting") - await self._connect_websocket() - async def _process_response(self, data): if "type" in data: if data["type"] == "transcript": diff --git a/src/pipecat/services/elevenlabs/stt.py b/src/pipecat/services/elevenlabs/stt.py index bf853ac98..388f7146b 100644 --- a/src/pipecat/services/elevenlabs/stt.py +++ b/src/pipecat/services/elevenlabs/stt.py @@ -459,6 +459,8 @@ class ElevenLabsRealtimeSTTService(WebsocketSTTService): super().__init__( sample_rate=sample_rate, ttfs_p99_latency=ttfs_p99_latency, + keepalive_timeout=10, + keepalive_interval=5, **kwargs, ) @@ -611,10 +613,10 @@ class ElevenLabsRealtimeSTTService(WebsocketSTTService): async def _connect(self): """Establish WebSocket connection to ElevenLabs Realtime STT.""" - await super()._connect() - await self._connect_websocket() + await super()._connect() + if self._websocket and not self._receive_task: self._receive_task = self.create_task(self._receive_task_handler(self._report_error)) @@ -628,6 +630,21 @@ class ElevenLabsRealtimeSTTService(WebsocketSTTService): await self._disconnect_websocket() + async def _send_keepalive(self, silence: bytes): + """Send silent audio wrapped in ElevenLabs' JSON protocol. + + Args: + silence: Silent 16-bit mono PCM audio bytes. + """ + audio_base64 = base64.b64encode(silence).decode("utf-8") + message = { + "message_type": "input_audio_chunk", + "audio_base_64": audio_base64, + "commit": False, + "sample_rate": self.sample_rate, + } + await self._websocket.send(json.dumps(message)) + async def _connect_websocket(self): """Connect to ElevenLabs Realtime STT WebSocket endpoint.""" try: diff --git a/src/pipecat/services/gladia/stt.py b/src/pipecat/services/gladia/stt.py index 243152d68..475a7213e 100644 --- a/src/pipecat/services/gladia/stt.py +++ b/src/pipecat/services/gladia/stt.py @@ -231,7 +231,13 @@ class GladiaSTTService(WebsocketSTTService): Override for your deployment. See https://github.com/pipecat-ai/stt-benchmark **kwargs: Additional arguments passed to the STTService parent class. """ - super().__init__(sample_rate=sample_rate, ttfs_p99_latency=ttfs_p99_latency, **kwargs) + super().__init__( + sample_rate=sample_rate, + ttfs_p99_latency=ttfs_p99_latency, + keepalive_timeout=20, + keepalive_interval=5, + **kwargs, + ) params = params or GladiaInputParams() @@ -261,7 +267,6 @@ class GladiaSTTService(WebsocketSTTService): self.set_model_name(model) self._params = params self._receive_task = None - self._keepalive_task = None self._settings = {} # Session management @@ -416,8 +421,6 @@ class GladiaSTTService(WebsocketSTTService): Initializes the session if needed and establishes websocket connection. """ - await super()._connect() - # Initialize session if needed if not self._session_url: settings = self._prepare_settings() @@ -428,12 +431,11 @@ class GladiaSTTService(WebsocketSTTService): await self._connect_websocket() + await super()._connect() + if self._websocket and not self._receive_task: self._receive_task = self.create_task(self._receive_task_handler(self._report_error)) - if self._websocket and not self._keepalive_task: - self._keepalive_task = self.create_task(self._keepalive_task_handler()) - async def _disconnect(self): """Disconnect from the Gladia service. @@ -443,10 +445,6 @@ class GladiaSTTService(WebsocketSTTService): self._connection_active = False - if self._keepalive_task: - await self.cancel_task(self._keepalive_task) - self._keepalive_task = None - if self._receive_task: await self.cancel_task(self._receive_task) self._receive_task = None @@ -644,21 +642,10 @@ class GladiaSTTService(WebsocketSTTService): except json.JSONDecodeError: logger.warning(f"{self} Received non-JSON message: {message}") - async def _keepalive_task_handler(self): - """Send periodic empty audio chunks to keep the connection alive.""" - try: - KEEPALIVE_SLEEP = 20 - while self._connection_active: - # Send keepalive (Gladia times out after 30 seconds) - await asyncio.sleep(KEEPALIVE_SLEEP) - if self._websocket and self._websocket.state is State.OPEN: - # Send an empty audio chunk as keepalive - empty_audio = b"" - await self._send_audio(empty_audio) - else: - logger.debug(f"{self} Websocket closed, stopping keepalive") - break - except websockets.exceptions.ConnectionClosed: - logger.debug(f"{self} Connection closed during keepalive") - except Exception as e: - await self.push_error(error_msg=f"Unknown error occurred: {e}", exception=e) + async def _send_keepalive(self, silence: bytes): + """Send an empty audio chunk to keep the Gladia connection alive. + + Args: + silence: Silent PCM audio bytes (unused, Gladia accepts empty chunks). + """ + await self._send_audio(b"") diff --git a/src/pipecat/services/soniox/stt.py b/src/pipecat/services/soniox/stt.py index fb5b78e4a..c9184ba4c 100644 --- a/src/pipecat/services/soniox/stt.py +++ b/src/pipecat/services/soniox/stt.py @@ -6,7 +6,6 @@ """Soniox speech-to-text service implementation.""" -import asyncio import json import time from typing import AsyncGenerator, List, Optional @@ -170,7 +169,13 @@ class SonioxSTTService(WebsocketSTTService): Override for your deployment. See https://github.com/pipecat-ai/stt-benchmark **kwargs: Additional arguments passed to the STTService. """ - super().__init__(sample_rate=sample_rate, ttfs_p99_latency=ttfs_p99_latency, **kwargs) + super().__init__( + sample_rate=sample_rate, + ttfs_p99_latency=ttfs_p99_latency, + keepalive_timeout=1, + keepalive_interval=5, + **kwargs, + ) params = params or SonioxInputParams() self._api_key = api_key @@ -183,7 +188,6 @@ class SonioxSTTService(WebsocketSTTService): self._last_tokens_received: Optional[float] = None self._receive_task = None - self._keepalive_task = None async def start(self, frame: StartFrame): """Start the Soniox STT websocket connection. @@ -269,16 +273,13 @@ class SonioxSTTService(WebsocketSTTService): Establishes websocket connection and starts receive and keepalive tasks. """ - await super()._connect() - await self._connect_websocket() + await super()._connect() + if self._websocket and not self._receive_task: self._receive_task = self.create_task(self._receive_task_handler(self._report_error)) - if self._websocket and not self._keepalive_task: - self._keepalive_task = self.create_task(self._keepalive_task_handler()) - async def _disconnect(self): """Disconnect from the Soniox service. @@ -286,10 +287,6 @@ class SonioxSTTService(WebsocketSTTService): """ await super()._disconnect() - if self._keepalive_task: - await self.cancel_task(self._keepalive_task) - self._keepalive_task = None - if self._receive_task: await self.cancel_task(self._receive_task) self._receive_task = None @@ -462,17 +459,10 @@ class SonioxSTTService(WebsocketSTTService): except Exception as e: logger.warning(f"Error processing message: {e}") - async def _keepalive_task_handler(self): - """Connection has to be open all the time.""" - try: - while True: - logger.trace("Sending keepalive message") - if self._websocket and self._websocket.state is State.OPEN: - await self._websocket.send(KEEPALIVE_MESSAGE) - else: - logger.debug("WebSocket connection closed.") - break - await asyncio.sleep(5) + async def _send_keepalive(self, silence: bytes): + """Send a Soniox protocol-level keepalive message. - except Exception as e: - logger.debug(f"Keepalive task stopped: {e}") + Args: + silence: Silent PCM audio bytes (unused, Soniox uses a protocol message). + """ + await self._websocket.send(KEEPALIVE_MESSAGE) diff --git a/src/pipecat/services/stt_service.py b/src/pipecat/services/stt_service.py index 7e9ed4c9f..b556bb23a 100644 --- a/src/pipecat/services/stt_service.py +++ b/src/pipecat/services/stt_service.py @@ -14,6 +14,7 @@ from abc import abstractmethod from typing import Any, AsyncGenerator, Dict, Mapping, Optional from loguru import logger +from websockets.protocol import State from pipecat.frames.frames import ( AudioRawFrame, @@ -37,6 +38,9 @@ from pipecat.services.stt_latency import DEFAULT_TTFS_P99 from pipecat.services.websocket_service import WebsocketService from pipecat.transcriptions.language import Language +# Duration in seconds of silent audio sent for WebSocket keepalive (100ms). +_KEEPALIVE_SILENCE_DURATION = 0.1 + class STTService(AIService): """Base class for speech-to-text services. @@ -543,18 +547,120 @@ class WebsocketSTTService(STTService, WebsocketService): """Base class for websocket-based STT services. Combines STT functionality with websocket connectivity, providing automatic - error handling and reconnection capabilities. + error handling, reconnection capabilities, and optional silence-based keepalive. + + The keepalive feature sends silent audio when no real audio has been sent for + a configurable timeout, preventing servers from closing idle connections (e.g. + when behind a ServiceSwitcher). Subclasses can override ``_send_keepalive()`` + to wrap the silence in a service-specific protocol. """ - def __init__(self, *, reconnect_on_error: bool = True, **kwargs): + def __init__( + self, + *, + reconnect_on_error: bool = True, + keepalive_timeout: Optional[float] = None, + keepalive_interval: float = 5.0, + **kwargs, + ): """Initialize the Websocket STT service. Args: reconnect_on_error: Whether to automatically reconnect on websocket errors. + keepalive_timeout: Seconds of no audio before sending silence to keep the + connection alive. None disables keepalive. Useful for services that + close idle connections (e.g. behind a ServiceSwitcher). + keepalive_interval: Seconds between idle checks when keepalive is enabled. **kwargs: Additional arguments passed to parent classes. """ STTService.__init__(self, **kwargs) WebsocketService.__init__(self, reconnect_on_error=reconnect_on_error, **kwargs) + self._keepalive_timeout = keepalive_timeout + self._keepalive_interval = keepalive_interval + self._keepalive_task: Optional[asyncio.Task] = None + self._last_audio_time: float = 0 + + async def process_audio_frame(self, frame: AudioRawFrame, direction: FrameDirection): + """Process an audio frame, tracking the last audio time for keepalive. + + Args: + frame: The audio frame to process. + direction: The direction of frame processing. + """ + self._last_audio_time = time.monotonic() + await super().process_audio_frame(frame, direction) + + async def _connect(self): + """Connect and start keepalive task if enabled.""" + await super()._connect() + self._create_keepalive_task() + + async def _disconnect(self): + """Disconnect and cancel keepalive task.""" + await super()._disconnect() + await self._cancel_keepalive_task() + + async def _reconnect_websocket(self, attempt_number: int) -> bool: + """Reconnect and restart keepalive task. + + The keepalive task breaks out of its loop on send errors, so it may + be dead after the websocket failure that triggered this reconnect. + """ + result = await super()._reconnect_websocket(attempt_number) + if result: + await self._cancel_keepalive_task() + self._create_keepalive_task() + return result + + def _create_keepalive_task(self): + """Start the keepalive task if keepalive is enabled.""" + if self._keepalive_timeout is not None: + self._last_audio_time = time.monotonic() + self._keepalive_task = self.create_task( + self._keepalive_task_handler(), name="keepalive" + ) + + async def _cancel_keepalive_task(self): + """Stop the keepalive task if running.""" + if self._keepalive_task: + await self.cancel_task(self._keepalive_task) + self._keepalive_task = None + + async def _keepalive_task_handler(self): + """Send periodic silent audio to prevent the server from closing the connection. + + When keepalive is enabled, this task checks periodically if the connection + has been idle (no audio sent) for longer than keepalive_timeout seconds. + If so, it generates silent 16-bit mono PCM audio and passes it to + _send_keepalive() for service-specific formatting and sending. + """ + while True: + await asyncio.sleep(self._keepalive_interval) + try: + if not self._websocket or self._websocket.state is not State.OPEN: + continue + elapsed = time.monotonic() - self._last_audio_time + if elapsed < self._keepalive_timeout: + continue + num_samples = int(self.sample_rate * _KEEPALIVE_SILENCE_DURATION) + silence = b"\x00" * (num_samples * 2) + await self._send_keepalive(silence) + self._last_audio_time = time.monotonic() + logger.trace(f"{self} sent keepalive silence") + except Exception as e: + logger.warning(f"{self} keepalive error: {e}") + break + + async def _send_keepalive(self, silence: bytes): + """Send silent audio over the websocket to keep the connection alive. + + The default implementation sends raw PCM bytes directly. Subclasses + can override this to wrap the silence in a service-specific protocol. + + Args: + silence: Silent 16-bit mono PCM audio bytes. + """ + await self._websocket.send(silence) async def _report_error(self, error: ErrorFrame): await self._call_event_handler("on_connection_error", error.error) From 883b24f5775333709a5e7f167c293241edb1d4bb Mon Sep 17 00:00:00 2001 From: Mark Backman Date: Tue, 10 Feb 2026 18:14:04 -0500 Subject: [PATCH 0441/1060] Update quickstart for 0.0.102 --- examples/quickstart/bot.py | 16 +--------------- examples/quickstart/pyproject.toml | 7 +++++-- 2 files changed, 6 insertions(+), 17 deletions(-) diff --git a/examples/quickstart/bot.py b/examples/quickstart/bot.py index 19a9206eb..fbe27d783 100644 --- a/examples/quickstart/bot.py +++ b/examples/quickstart/bot.py @@ -27,16 +27,11 @@ from loguru import logger print("🚀 Starting Pipecat bot...") print("⏳ Loading models and imports (20 seconds, first run only)\n") -logger.info("Loading Local Smart Turn Analyzer V3...") -from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3 - -logger.info("✅ Local Smart Turn Analyzer V3 loaded") logger.info("Loading Silero VAD model...") from pipecat.audio.vad.silero import SileroVADAnalyzer logger.info("✅ Silero VAD model loaded") -from pipecat.audio.vad.vad_analyzer import VADParams from pipecat.frames.frames import LLMRunFrame logger.info("Loading pipeline components...") @@ -55,10 +50,6 @@ from pipecat.services.deepgram.stt import DeepgramSTTService from pipecat.services.openai.llm import OpenAILLMService from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams -from pipecat.turns.user_stop.turn_analyzer_user_turn_stop_strategy import ( - TurnAnalyzerUserTurnStopStrategy, -) -from pipecat.turns.user_turn_strategies import UserTurnStrategies logger.info("✅ All components loaded successfully!") @@ -87,12 +78,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): context = LLMContext(messages) user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, - user_params=LLMUserAggregatorParams( - user_turn_strategies=UserTurnStrategies( - stop=[TurnAnalyzerUserTurnStopStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3())] - ), - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), - ), + user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()), ) pipeline = Pipeline( diff --git a/examples/quickstart/pyproject.toml b/examples/quickstart/pyproject.toml index 863e350d4..ee18f96c0 100644 --- a/examples/quickstart/pyproject.toml +++ b/examples/quickstart/pyproject.toml @@ -4,7 +4,7 @@ version = "0.1.0" description = "Quickstart example for building voice AI bots with Pipecat" requires-python = ">=3.10" dependencies = [ - "pipecat-ai[webrtc,daily,silero,deepgram,openai,cartesia,local-smart-turn-v3,runner]", + "pipecat-ai[webrtc,daily,silero,deepgram,openai,cartesia,runner]", "pipecat-ai-cli" ] @@ -17,4 +17,7 @@ dev = [ [tool.ruff] line-length = 100 [tool.ruff.lint] -select = ["I"] \ No newline at end of file +select = ["I"] + + [tool.uv.sources] +pipecat-ai = { path = "../../", editable = true } \ No newline at end of file From 18aad05a7c8230c08a709c9139a176d31fbdb002 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Aleix=20Conchillo=20Flaqu=C3=A9?= Date: Tue, 10 Feb 2026 17:59:21 -0800 Subject: [PATCH 0442/1060] fix(openai): use compatible stream closing for non-OpenAI providers OpenAI's AsyncStream uses close() while async generators (e.g. from OpenPipe) use aclose(). Replace direct async-with on the stream with a helper that handles both protocols. --- src/pipecat/services/openai/base_llm.py | 17 ++++++++++++++--- 1 file changed, 14 insertions(+), 3 deletions(-) diff --git a/src/pipecat/services/openai/base_llm.py b/src/pipecat/services/openai/base_llm.py index d8669f622..2cdde51ea 100644 --- a/src/pipecat/services/openai/base_llm.py +++ b/src/pipecat/services/openai/base_llm.py @@ -9,6 +9,7 @@ import asyncio import base64 import json +from contextlib import asynccontextmanager from typing import Any, Dict, List, Mapping, Optional import httpx @@ -374,9 +375,19 @@ class BaseOpenAILLMService(LLMService): else self._stream_chat_completions_universal_context(context) ) - # Use context manager to ensure stream is closed on cancellation/exception. - # Without this, CancelledError during iteration leaves the underlying socket open. - async with chunk_stream: + # Ensure stream is closed on cancellation/exception to prevent socket + # leaks. OpenAI's AsyncStream uses close(), async generators use aclose(). + @asynccontextmanager + async def _closing(stream): + try: + yield stream + finally: + if hasattr(stream, "aclose"): + await stream.aclose() + elif hasattr(stream, "close"): + await stream.close() + + async with _closing(chunk_stream): async for chunk in chunk_stream: if chunk.usage: cached_tokens = ( From f3eb5b30a08a0208d9bb068294f83eccd8feb4ff Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Aleix=20Conchillo=20Flaqu=C3=A9?= Date: Tue, 10 Feb 2026 18:01:29 -0800 Subject: [PATCH 0443/1060] Add changelog for #3707 --- changelog/3707.fixed.md | 1 + 1 file changed, 1 insertion(+) create mode 100644 changelog/3707.fixed.md diff --git a/changelog/3707.fixed.md b/changelog/3707.fixed.md new file mode 100644 index 000000000..257342c62 --- /dev/null +++ b/changelog/3707.fixed.md @@ -0,0 +1 @@ +- Fixed stream closing compatibility for OpenAI-compatible providers (e.g. OpenPipe) that return async generators instead of `AsyncStream`. From 93f4402198b770e652b05027c04746db93165552 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Aleix=20Conchillo=20Flaqu=C3=A9?= Date: Tue, 10 Feb 2026 18:19:57 -0800 Subject: [PATCH 0444/1060] Update stream close test to match new _closing helper --- tests/test_openai_llm_timeout.py | 6 +----- 1 file changed, 1 insertion(+), 5 deletions(-) diff --git a/tests/test_openai_llm_timeout.py b/tests/test_openai_llm_timeout.py index 4ba459a29..f7876f02f 100644 --- a/tests/test_openai_llm_timeout.py +++ b/tests/test_openai_llm_timeout.py @@ -149,13 +149,9 @@ async def test_openai_llm_stream_closed_on_cancellation(): def __init__(self): self.iteration_count = 0 - async def __aenter__(self): - return self - - async def __aexit__(self, exc_type, exc_val, exc_tb): + async def close(self): nonlocal stream_closed stream_closed = True - return False def __aiter__(self): return self From f1e2001a4e926fb6362663c0a968d617b235f923 Mon Sep 17 00:00:00 2001 From: aconchillo <951761+aconchillo@users.noreply.github.com> Date: Tue, 10 Feb 2026 23:05:22 +0000 Subject: [PATCH 0445/1060] Update changelog for version 0.0.102 --- CHANGELOG.md | 347 +++++++++++++++++++++++++++++++++++ changelog/3134.added.md | 1 - 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2026-02-10 + +### Added + +- Added `ResembleAITTSService` for text-to-speech using Resemble AI's streaming + WebSocket API with word-level timestamps and jitter buffering for smooth + audio playback. + (PR [#3134](https://github.com/pipecat-ai/pipecat/pull/3134)) + +- Added `UserBotLatencyObserver` for tracking user-to-bot response latency. + When tracing is enabled, latency measurements are automatically recorded as + `turn.user_bot_latency_seconds` attributes on OpenTelemetry turn spans. + (PR [#3355](https://github.com/pipecat-ai/pipecat/pull/3355)) + +- Added `append_to_context` parameter to `TTSSpeakFrame` for conditional LLM + context addition. + - Allows fine-grained control over whether text should be added to + conversation context + - Defaults to `True` to maintain backward compatibility + (PR [#3584](https://github.com/pipecat-ai/pipecat/pull/3584)) + +- Added TTS context tracking system with `context_id` field to trace audio + generation through the pipeline. + - `TTSAudioRawFrame`, `TTSStartedFrame`, `TTSStoppedFrame` now include + `context_id` + - `AggregatedTextFrame` and `TTSTextFrame` now include `context_id` + - Enables tracking which TTS request generated specific audio chunks + (PR [#3584](https://github.com/pipecat-ai/pipecat/pull/3584)) + +- Added support for Inworld TTS Websocket Auto Mode for improved latency + (PR [#3593](https://github.com/pipecat-ai/pipecat/pull/3593)) + +- Added new frames for context summarization: `LLMContextSummaryRequestFrame` + and `LLMContextSummaryResultFrame`. + (PR [#3621](https://github.com/pipecat-ai/pipecat/pull/3621)) + +- Added context summarization feature to automatically compress conversation + history when conversation length limits (by token or message count) are + reached, enabling efficient long-running conversations. + - Configure via `enable_context_summarization=True` in + `LLMAssistantAggregatorParams` + - Customize behavior with `LLMContextSummarizationConfig` (max tokens, + thresholds, etc.) + - Automatically preserves incomplete function call sequences during + summarization + - See new examples: + `examples/foundational/54-context-summarization-openai.py` and + `examples/foundational/54a-context-summarization-google.py` + (PR [#3621](https://github.com/pipecat-ai/pipecat/pull/3621)) + +- Added RTVI function call lifecycle events (`llm-function-call-started`, + `llm-function-call-in-progress`, `llm-function-call-stopped`) with + configurable security levels via + `RTVIObserverParams.function_call_report_level`. Supports per-function + control over what information is exposed (`DISABLED`, `NONE`, `NAME`, or + `FULL`). + (PR [#3630](https://github.com/pipecat-ai/pipecat/pull/3630)) + +- Added `RequestMetadataFrame` and metadata handling for `ServiceSwitcher` to + ensure STT services correctly emit `STTMetadataFrame` when switching between + services. Only the active service's metadata is propagated downstream, + switching services triggers the newly active service to re-emit its metadata, + and proper frame ordering is maintained at startup. + (PR [#3637](https://github.com/pipecat-ai/pipecat/pull/3637)) + +- Added `STTMetadataFrame` to broadcast STT service latency information at + pipeline start. + - STT services broadcast P99 time-to-final-segment (`ttfs_p99_latency`) to + downstream processors + - Turn stop strategies automatically configure their STT timeout from this + metadata + - Developers can override `ttfs_p99_latency` via constructor argument for + custom deployments + - Added measured P99 values for STT providers. + - See [stt-benchmark](https://github.com/pipecat-ai/stt-benchmark) to + measure latency for your configuration + (PR [#3637](https://github.com/pipecat-ai/pipecat/pull/3637)) + +- Added support for `is_sandbox` parameter in `LiveAvatarNewSessionRequest` to + enable sandbox mode for HeyGen LiveAvatar sessions. + (PR [#3653](https://github.com/pipecat-ai/pipecat/pull/3653)) + +- Added support for `video_settings` parameter in `LiveAvatarNewSessionRequest` + to configure video encoding (H264/VP8) and quality levels. + (PR [#3653](https://github.com/pipecat-ai/pipecat/pull/3653)) + +- Added `OpenAIRealtimeSTTService` for real-time streaming speech-to-text using + OpenAI's Realtime API WebSocket transcription sessions. Supports local VAD + and server-side VAD modes, noise reduction, and automatic reconnection. + (PR [#3656](https://github.com/pipecat-ai/pipecat/pull/3656)) + +- Added `bulbul:v3-beta` TTS model support for Sarvam AI with temperature + control and 25 new speaker voices. + (PR [#3671](https://github.com/pipecat-ai/pipecat/pull/3671)) + +- Added `saaras:v3` STT model support for Sarvam AI with new `mode` parameter + (transcribe, translate, verbatim, translit, codemix) and prompt support. + (PR [#3671](https://github.com/pipecat-ai/pipecat/pull/3671)) + +- Added new OpenAI TTS voice options `marin` and `cedar`. + (PR [#3682](https://github.com/pipecat-ai/pipecat/pull/3682)) + +- Added `UserMuteStartedFrame` and `UserMuteStoppedFrame` system frames, and + corresponding `user-mute-started` / `user-mute-stopped` RTVI messages, so + clients can observe when mute strategies activate or deactivate. + (PR [#3687](https://github.com/pipecat-ai/pipecat/pull/3687)) + +### Changed + +- Updated all 30+ TTS service implementations to support context tracking with + `context_id`. + - Services now generate and propagate context IDs through TTS frames + - Enables end-to-end tracing of TTS requests through the pipeline + (PR [#3584](https://github.com/pipecat-ai/pipecat/pull/3584)) + +- ⚠️ `TTSService.run_tts()` now requires a `context_id` parameter for context + tracking. + - Custom TTS service implementations must update their `run_tts()` + signature + - Before: `async def run_tts(self, text: str) -> AsyncGenerator[Frame, + None]:` + - After: `async def run_tts(self, text: str, context_id: str) -> + AsyncGenerator[Frame, None]:` + (PR [#3584](https://github.com/pipecat-ai/pipecat/pull/3584)) + +- Simplified context aggregators to use `frame.append_to_context` flag instead + of tracking internal state. + - Cleaner logic in `LLMResponseAggregator` and + `LLMResponseUniversalAggregator` + - More consistent behavior across aggregator implementations + (PR [#3584](https://github.com/pipecat-ai/pipecat/pull/3584)) + +- Updated timestamps to be cumulative within an agent turn, using + flushCompleted message as an indication of when timestamps from the server + are reset to 0 + (PR [#3593](https://github.com/pipecat-ai/pipecat/pull/3593)) + +- Changed `KokoroTTSService` to use `kokoro-onnx` instead of `kokoro` as the + underlying TTS engine. + (PR [#3612](https://github.com/pipecat-ai/pipecat/pull/3612)) + +- Improved user turn stop timing in `TranscriptionUserTurnStopStrategy` and + `TurnAnalyzerUserTurnStopStrategy`. + - Timeout now starts on `VADUserStoppedSpeakingFrame` for tighter, more + predictable timing + - Added support for finalized transcripts + (`TranscriptionFrame.finalized=True`) to trigger earlier + - Added fallback timeout for edge cases where transcripts arrive without + VAD events + - Removed `InterimTranscriptionFrame` handling (no longer affects timing) + (PR [#3637](https://github.com/pipecat-ai/pipecat/pull/3637)) + +- Improved the accuracy of the `UserBotLatencyObserver` and + `UserBotLatencyLogObserver` by measuring from the time when the user actually + starts speaking. + (PR [#3637](https://github.com/pipecat-ai/pipecat/pull/3637)) + +- ⚠️ Renamed `timeout` parameter to `user_speech_timeout` in + `TranscriptionUserTurnStopStrategy`. + (PR [#3637](https://github.com/pipecat-ai/pipecat/pull/3637)) + +- Updated the `VADUserStartedSpeakingFrame` to include `start_secs` and + `timestamp` and `VADUserStoppedSpeakingFrame` to include `stop_secs` and + `timestamp`, removing the need to separately handle the + `SpeechControlParamsFrame` for VADParams values. + (PR [#3637](https://github.com/pipecat-ai/pipecat/pull/3637)) + +- ⚠️ Renamed `TranscriptionUserTurnStopStrategy` to + `SpeechTimeoutUserTurnStopStrategy`. The old name is deprecated and will be + removed in a future release. + (PR [#3637](https://github.com/pipecat-ai/pipecat/pull/3637)) + +- `AssemblyAISTTService` now automatically configures optimal settings for + manual turn detection when `vad_force_turn_endpoint=True`. This sets + `end_of_turn_confidence_threshold=1.0` and `max_turn_silence=2000` by + default, which disables model-based turn detection and reduces latency by + relying on external VAD for turn endpoints. Warnings are logged if + conflicting settings are detected. + (PR [#3644](https://github.com/pipecat-ai/pipecat/pull/3644)) + +- Upgraded the `pipecat-ai-small-webrtc-prebuilt` package to v2.1.0. + (PR [#3652](https://github.com/pipecat-ai/pipecat/pull/3652)) + +- Changed default session mode from "CUSTOM" to "LITE" in HeyGen LiveAvatar + integration, with VP8 as the default video encoding. + (PR [#3653](https://github.com/pipecat-ai/pipecat/pull/3653)) + +- ⚠️ The default `VADParams` `stop_secs` default is changing from `0.8` seconds + to `0.2` seconds. This change both simplifies the developer experience and + improves the performance of STT services. With a shorter `stop_secs` value, + STT services using a local VAD can finalize sooner, resulting in faster + transcription. + - `SpeechTimeoutUserTurnStopStrategy`: control how long to wait for + additional user speech using `user_speech_timeout` (default: 0.6 sec). + - `TurnAnalyzerUserTurnStopStrategy`: the turn analyzer automatically + adjusts the user wait time based on the audio input. + (PR [#3659](https://github.com/pipecat-ai/pipecat/pull/3659)) + +- Moved interruption wait event from per-processor instance state to + `InterruptionFrame` itself. Added `InterruptionFrame.complete()` to signal + when the interruption has fully traversed the pipeline. Custom processors + that block or consume an `InterruptionFrame` before it reaches the pipeline + sink must call `frame.complete()` to avoid stalling + `push_interruption_task_frame_and_wait()`. A warning is logged if completion + does not happen within 2 seconds. + (PR [#3660](https://github.com/pipecat-ai/pipecat/pull/3660)) + +- Update the default model to `scribe_v2` for `ElevenLabsSTTService`. + (PR [#3664](https://github.com/pipecat-ai/pipecat/pull/3664)) + +- Changed the `DeepgramSTTService` default setting for `smart_format` to + `False`, as agents don't need smart formatting. Disabling this setting + provides a small performance improvement, as well. + (PR [#3666](https://github.com/pipecat-ai/pipecat/pull/3666)) + +- Changed `FunctionCallCancelFrame` to broadcast in both directions for + consistency with other function call frames. + (PR [#3672](https://github.com/pipecat-ai/pipecat/pull/3672)) + +- Changed default user turn stop strategy from + `TranscriptionUserTurnStopStrategy` to `TurnAnalyzerUserTurnStopStrategy` + with `LocalSmartTurnAnalyzerV3`. + (PR [#3689](https://github.com/pipecat-ai/pipecat/pull/3689)) + +- Renamed `RequestMetadataFrame` to `ServiceSwitcherRequestMetadataFrame` and + added a `service` field to target a specific service. The frame is now pushed + downstream by services after handling instead of being silently consumed. + (PR [#3692](https://github.com/pipecat-ai/pipecat/pull/3692)) + +- Update `SonioxSTTService` to set `vad_force_turn_endpoint` to `True`. This + setting disabled the turn detection logic available natively in Soniox. + Instead, Soniox relies on a local VAD to finalize the transcript. This + configuration meaningfully reduces the time to final segment for Soniox. With + this setting enabled, Soniox outputs a transcript in ~250ms (median). Pipecat + enables smart-turn detection by default using the `LocalSmartTurnAnalyzerV3`. + To use the native turn detection logic in Soniox, just set + `vad_force_turn_endpoint` to `False`. + (PR [#3697](https://github.com/pipecat-ai/pipecat/pull/3697)) + +- Update `SonioxSTTService` default model to `stt-rt-v4`. + (PR [#3697](https://github.com/pipecat-ai/pipecat/pull/3697)) + +- Updated the default model to `async_flash_v1.0` and base URL to + `https://api.async.com` for `AsyncAITTSService`. + (PR [#3701](https://github.com/pipecat-ai/pipecat/pull/3701)) + +### Deprecated + +- Deprecated `UserBotLatencyLogObserver`. Use `UserBotLatencyObserver` directly + with its `on_latency_measured` event handler instead. + (PR [#3355](https://github.com/pipecat-ai/pipecat/pull/3355)) + +- Deprecated `RTVILLMFunctionCallMessage`, `RTVILLMFunctionCallMessageData`, + and `RTVIProcessor.handle_function_call()`. Use the new + `llm-function-call-in-progress` event sent automatically by `RTVIObserver` + instead. + (PR [#3630](https://github.com/pipecat-ai/pipecat/pull/3630)) + +### Removed + +- ⚠️ Removed `timeout` parameter from `TurnAnalyzerUserTurnStopStrategy`. The + timeout is now managed internally based on STT latency. + (PR [#3637](https://github.com/pipecat-ai/pipecat/pull/3637)) + +### Fixed + +- Fixed pipeline freeze when `InterruptionFrame` discards `EndFrame` or + `StopFrame` by making terminal frames uninterruptible. + (PR [#3542](https://github.com/pipecat-ai/pipecat/pull/3542)) + +- Fixed OpenAI LLM stream not being closed on cancellation/exception, which + could leak sockets. + (PR [#3589](https://github.com/pipecat-ai/pipecat/pull/3589)) + +- Fixed `PipelineTask` adding duplicate `RTVIProcessor` and `RTVIObserver` when + they were already provided in the pipeline or observers list. They are now + detected and skipped, with appropriate warnings and errors logged for + mismatched configurations. + (PR [#3610](https://github.com/pipecat-ai/pipecat/pull/3610)) + +- Fixed function call timeout task not being cancelled when the handler + completes without calling `result_callback` or is cancelled externally, which + caused `RuntimeWarning: coroutine was never awaited`. + (PR [#3616](https://github.com/pipecat-ai/pipecat/pull/3616)) + +- Fixed sentence splitting for Japanese, Chinese, Korean, and other non-Latin + languages in TTS pipeline. NLTK's sentence tokenizer does not support CJK + languages, causing text to accumulate until flush instead of being split at + sentence boundaries. Added fallback detection for unambiguous non-Latin + sentence-ending punctuation (e.g., `。`, `？`, `！`). + (PR [#3617](https://github.com/pipecat-ai/pipecat/pull/3617)) + +- Fixed `PipelineTask` to also call `set_bot_ready()` when an external + `RTVIProcessor` is provided. + (PR [#3623](https://github.com/pipecat-ai/pipecat/pull/3623)) + +- Fixed `VADController` not broadcasting `SpeechControlParamsFrame` on startup, + which prevented STT services from receiving VAD params needed for TTFB + measurement. + (PR [#3628](https://github.com/pipecat-ai/pipecat/pull/3628)) + +- Fixed `StopAsyncIteration` exceptions in `parse_telephony_websocket()` when + WebSocket connections close before sending expected messages. + (PR [#3629](https://github.com/pipecat-ai/pipecat/pull/3629)) + +- Fixed WebSocket transport error when broadcasting + `InputTransportMessageFrame` by correctly instantiating the frame with its + message parameter. + (PR [#3635](https://github.com/pipecat-ai/pipecat/pull/3635)) + +- Fixed orphan OpenTelemetry spans during flow initialization and transitions + in tracing. + (PR [#3649](https://github.com/pipecat-ai/pipecat/pull/3649)) + +- Fixed `SambaNovaLLMService` and `GoogleLLMOpenAIBetaService` streams not + being closed on cancellation/exception, which could leak sockets. + (PR [#3663](https://github.com/pipecat-ai/pipecat/pull/3663)) + +- Fixed an issue in `InworldTTSService` where punctuation was pronounced. Now, + the `InworldTTSService` ensures proper spacing between sentences, resolving + pronunciation issues. + (PR [#3667](https://github.com/pipecat-ai/pipecat/pull/3667)) + +- Fixed `ParallelPipeline` allowing frames pushed by internal processors to + escape during lifecycle frame (`StartFrame`/`EndFrame`/`CancelFrame`) + synchronization. These frames are now buffered and flushed after all branches + complete. + (PR [#3668](https://github.com/pipecat-ai/pipecat/pull/3668)) + +- Fixed issues in Sarvam STT and TTS services: missing event handler + registration for VAD signals, `Optional[bool]` type annotations, WebSocket + state cleanup on API errors, and TTS disconnect/reconnection state + management. + (PR [#3671](https://github.com/pipecat-ai/pipecat/pull/3671)) + +- Fixed `RTVIObserver` sending duplicate client messages for frames that are + broadcast in both directions (e.g. `UserStartedSpeakingFrame`, + `FunctionCallResultFrame`). + (PR [#3672](https://github.com/pipecat-ai/pipecat/pull/3672)) + +- Fixed WebSocket STT services (ElevenLabs, Cartesia, Gladia, Soniox) + disconnecting due to idle timeout when no audio is being sent (e.g. when + inactive behind a `ServiceSwitcher`). `WebsocketSTTService` now provides + opt-in silence-based keepalive via `keepalive_timeout` and + `keepalive_interval` parameters. + (PR [#3675](https://github.com/pipecat-ai/pipecat/pull/3675)) + ## [0.0.101] - 2026-01-30 ### Added diff --git a/changelog/3134.added.md b/changelog/3134.added.md deleted file mode 100644 index adddde398..000000000 --- a/changelog/3134.added.md +++ /dev/null @@ -1 +0,0 @@ -- Added `ResembleAITTSService` for text-to-speech using Resemble AI's streaming WebSocket API with word-level timestamps and jitter buffering for smooth audio playback. diff --git a/changelog/3355.added.md b/changelog/3355.added.md deleted file mode 100644 index ec8209f57..000000000 --- a/changelog/3355.added.md +++ /dev/null @@ -1 +0,0 @@ -- Added `UserBotLatencyObserver` for tracking user-to-bot response latency. When tracing is enabled, latency measurements are automatically recorded as `turn.user_bot_latency_seconds` attributes on OpenTelemetry turn spans. diff --git a/changelog/3355.deprecated.md b/changelog/3355.deprecated.md deleted file mode 100644 index 7406268a7..000000000 --- a/changelog/3355.deprecated.md +++ /dev/null @@ -1 +0,0 @@ -- Deprecated `UserBotLatencyLogObserver`. Use `UserBotLatencyObserver` directly with its `on_latency_measured` event handler instead. diff --git a/changelog/3542.fixed.md b/changelog/3542.fixed.md deleted file mode 100644 index 523754b28..000000000 --- a/changelog/3542.fixed.md +++ /dev/null @@ -1 +0,0 @@ -- Fixed pipeline freeze when `InterruptionFrame` discards `EndFrame` or `StopFrame` by making terminal frames uninterruptible. diff --git a/changelog/3584.added.2.md b/changelog/3584.added.2.md deleted file mode 100644 index 3113154fe..000000000 --- a/changelog/3584.added.2.md +++ /dev/null @@ -1,3 +0,0 @@ -- Added `append_to_context` parameter to `TTSSpeakFrame` for conditional LLM context addition. - - Allows fine-grained control over whether text should be added to conversation context - - Defaults to `True` to maintain backward compatibility diff --git a/changelog/3584.added.md b/changelog/3584.added.md deleted file mode 100644 index 08a81ee85..000000000 --- a/changelog/3584.added.md +++ /dev/null @@ -1,4 +0,0 @@ -- Added TTS context tracking system with `context_id` field to trace audio generation through the pipeline. - - `TTSAudioRawFrame`, `TTSStartedFrame`, `TTSStoppedFrame` now include `context_id` - - `AggregatedTextFrame` and `TTSTextFrame` now include `context_id` - - Enables tracking which TTS request generated specific audio chunks diff --git a/changelog/3584.changed.2.md b/changelog/3584.changed.2.md deleted file mode 100644 index f5356b4c9..000000000 --- a/changelog/3584.changed.2.md +++ /dev/null @@ -1,3 +0,0 @@ -- Simplified context aggregators to use `frame.append_to_context` flag instead of tracking internal state. - - Cleaner logic in `LLMResponseAggregator` and `LLMResponseUniversalAggregator` - - More consistent behavior across aggregator implementations diff --git a/changelog/3584.changed.3.md b/changelog/3584.changed.3.md deleted file mode 100644 index 426cfbde7..000000000 --- a/changelog/3584.changed.3.md +++ /dev/null @@ -1,4 +0,0 @@ -- ⚠️ `TTSService.run_tts()` now requires a `context_id` parameter for context tracking. - - Custom TTS service implementations must update their `run_tts()` signature - - Before: `async def run_tts(self, text: str) -> AsyncGenerator[Frame, None]:` - - After: `async def run_tts(self, text: str, context_id: str) -> AsyncGenerator[Frame, None]:` diff --git a/changelog/3584.changed.md b/changelog/3584.changed.md deleted file mode 100644 index fd535b7d8..000000000 --- a/changelog/3584.changed.md +++ /dev/null @@ -1,3 +0,0 @@ -- Updated all 30+ TTS service implementations to support context tracking with `context_id`. - - Services now generate and propagate context IDs through TTS frames - - Enables end-to-end tracing of TTS requests through the pipeline diff --git a/changelog/3589.fixed.md b/changelog/3589.fixed.md deleted file mode 100644 index fda03ac70..000000000 --- a/changelog/3589.fixed.md +++ /dev/null @@ -1 +0,0 @@ -- Fixed OpenAI LLM stream not being closed on cancellation/exception, which could leak sockets. diff --git a/changelog/3593.added.md b/changelog/3593.added.md deleted file mode 100644 index 432db3636..000000000 --- a/changelog/3593.added.md +++ /dev/null @@ -1 +0,0 @@ -- Added support for Inworld TTS Websocket Auto Mode for improved latency diff --git a/changelog/3593.changed.md b/changelog/3593.changed.md deleted file mode 100644 index a21549f36..000000000 --- a/changelog/3593.changed.md +++ /dev/null @@ -1 +0,0 @@ -- Updated timestamps to be cumulative within an agent turn, using flushCompleted message as an indication of when timestamps from the server are reset to 0 diff --git a/changelog/3610.fixed.md b/changelog/3610.fixed.md deleted file mode 100644 index 7a004d110..000000000 --- a/changelog/3610.fixed.md +++ /dev/null @@ -1 +0,0 @@ -- Fixed `PipelineTask` adding duplicate `RTVIProcessor` and `RTVIObserver` when they were already provided in the pipeline or observers list. They are now detected and skipped, with appropriate warnings and errors logged for mismatched configurations. diff --git a/changelog/3612.changed.md b/changelog/3612.changed.md deleted file mode 100644 index 62323ee10..000000000 --- a/changelog/3612.changed.md +++ /dev/null @@ -1 +0,0 @@ -- Changed `KokoroTTSService` to use `kokoro-onnx` instead of `kokoro` as the underlying TTS engine. diff --git a/changelog/3616.fixed.md b/changelog/3616.fixed.md deleted file mode 100644 index 392502161..000000000 --- a/changelog/3616.fixed.md +++ /dev/null @@ -1 +0,0 @@ -- Fixed function call timeout task not being cancelled when the handler completes without calling `result_callback` or is cancelled externally, which caused `RuntimeWarning: coroutine was never awaited`. diff --git a/changelog/3617.fixed.md b/changelog/3617.fixed.md deleted file mode 100644 index b9739a42b..000000000 --- a/changelog/3617.fixed.md +++ /dev/null @@ -1,5 +0,0 @@ -- Fixed sentence splitting for Japanese, Chinese, Korean, and other non-Latin - languages in TTS pipeline. NLTK's sentence tokenizer does not support CJK - languages, causing text to accumulate until flush instead of being split at - sentence boundaries. Added fallback detection for unambiguous non-Latin - sentence-ending punctuation (e.g., `。`, `？`, `！`). diff --git a/changelog/3621.added.2.md b/changelog/3621.added.2.md deleted file mode 100644 index 395c8bdfb..000000000 --- a/changelog/3621.added.2.md +++ /dev/null @@ -1 +0,0 @@ -- Added new frames for context summarization: `LLMContextSummaryRequestFrame` and `LLMContextSummaryResultFrame`. diff --git a/changelog/3621.added.md b/changelog/3621.added.md deleted file mode 100644 index 8b2197eea..000000000 --- a/changelog/3621.added.md +++ /dev/null @@ -1,5 +0,0 @@ -- Added context summarization feature to automatically compress conversation history when conversation length limits (by token or message count) are reached, enabling efficient long-running conversations. - - Configure via `enable_context_summarization=True` in `LLMAssistantAggregatorParams` - - Customize behavior with `LLMContextSummarizationConfig` (max tokens, thresholds, etc.) - - Automatically preserves incomplete function call sequences during summarization - - See new examples: `examples/foundational/54-context-summarization-openai.py` and `examples/foundational/54a-context-summarization-google.py` diff --git a/changelog/3623.fixed.md b/changelog/3623.fixed.md deleted file mode 100644 index 3eab6d90c..000000000 --- a/changelog/3623.fixed.md +++ /dev/null @@ -1 +0,0 @@ -- Fixed `PipelineTask` to also call `set_bot_ready()` when an external `RTVIProcessor` is provided. diff --git a/changelog/3628.fixed.md b/changelog/3628.fixed.md deleted file mode 100644 index 69a00c30e..000000000 --- a/changelog/3628.fixed.md +++ /dev/null @@ -1 +0,0 @@ -- Fixed `VADController` not broadcasting `SpeechControlParamsFrame` on startup, which prevented STT services from receiving VAD params needed for TTFB measurement. diff --git a/changelog/3629.fixed.md b/changelog/3629.fixed.md deleted file mode 100644 index 12792f47d..000000000 --- a/changelog/3629.fixed.md +++ /dev/null @@ -1 +0,0 @@ -- Fixed `StopAsyncIteration` exceptions in `parse_telephony_websocket()` when WebSocket connections close before sending expected messages. diff --git a/changelog/3630.added.md b/changelog/3630.added.md deleted file mode 100644 index 3e27ca3e5..000000000 --- a/changelog/3630.added.md +++ /dev/null @@ -1 +0,0 @@ -- Added RTVI function call lifecycle events (`llm-function-call-started`, `llm-function-call-in-progress`, `llm-function-call-stopped`) with configurable security levels via `RTVIObserverParams.function_call_report_level`. Supports per-function control over what information is exposed (`DISABLED`, `NONE`, `NAME`, or `FULL`). \ No newline at end of file diff --git a/changelog/3630.deprecated.md b/changelog/3630.deprecated.md deleted file mode 100644 index b1967f683..000000000 --- a/changelog/3630.deprecated.md +++ /dev/null @@ -1 +0,0 @@ -- Deprecated `RTVILLMFunctionCallMessage`, `RTVILLMFunctionCallMessageData`, and `RTVIProcessor.handle_function_call()`. Use the new `llm-function-call-in-progress` event sent automatically by `RTVIObserver` instead. diff --git a/changelog/3635.fixed.md b/changelog/3635.fixed.md deleted file mode 100644 index 3f83e1365..000000000 --- a/changelog/3635.fixed.md +++ /dev/null @@ -1 +0,0 @@ -- Fixed WebSocket transport error when broadcasting `InputTransportMessageFrame` by correctly instantiating the frame with its message parameter. diff --git a/changelog/3637.added.3.md b/changelog/3637.added.3.md deleted file mode 100644 index 9a17e748b..000000000 --- a/changelog/3637.added.3.md +++ /dev/null @@ -1 +0,0 @@ -- Added `RequestMetadataFrame` and metadata handling for `ServiceSwitcher` to ensure STT services correctly emit `STTMetadataFrame` when switching between services. Only the active service's metadata is propagated downstream, switching services triggers the newly active service to re-emit its metadata, and proper frame ordering is maintained at startup. diff --git a/changelog/3637.added.md b/changelog/3637.added.md deleted file mode 100644 index ec28f91f4..000000000 --- a/changelog/3637.added.md +++ /dev/null @@ -1,6 +0,0 @@ -- Added `STTMetadataFrame` to broadcast STT service latency information at pipeline start. - - STT services broadcast P99 time-to-final-segment (`ttfs_p99_latency`) to downstream processors - - Turn stop strategies automatically configure their STT timeout from this metadata - - Developers can override `ttfs_p99_latency` via constructor argument for custom deployments - - Added measured P99 values for STT providers. - - See [stt-benchmark](https://github.com/pipecat-ai/stt-benchmark) to measure latency for your configuration diff --git a/changelog/3637.changed.2.md b/changelog/3637.changed.2.md deleted file mode 100644 index e8fbb811a..000000000 --- a/changelog/3637.changed.2.md +++ /dev/null @@ -1,5 +0,0 @@ -- Improved user turn stop timing in `TranscriptionUserTurnStopStrategy` and `TurnAnalyzerUserTurnStopStrategy`. - - Timeout now starts on `VADUserStoppedSpeakingFrame` for tighter, more predictable timing - - Added support for finalized transcripts (`TranscriptionFrame.finalized=True`) to trigger earlier - - Added fallback timeout for edge cases where transcripts arrive without VAD events - - Removed `InterimTranscriptionFrame` handling (no longer affects timing) diff --git a/changelog/3637.changed.3.md b/changelog/3637.changed.3.md deleted file mode 100644 index 95f14c29c..000000000 --- a/changelog/3637.changed.3.md +++ /dev/null @@ -1 +0,0 @@ -- Updated the `VADUserStartedSpeakingFrame` to include `start_secs` and `timestamp` and `VADUserStoppedSpeakingFrame` to include `stop_secs` and `timestamp`, removing the need to separately handle the `SpeechControlParamsFrame` for VADParams values. diff --git a/changelog/3637.changed.4.md b/changelog/3637.changed.4.md deleted file mode 100644 index 97f244cb7..000000000 --- a/changelog/3637.changed.4.md +++ /dev/null @@ -1 +0,0 @@ -- ⚠️ Renamed `TranscriptionUserTurnStopStrategy` to `SpeechTimeoutUserTurnStopStrategy`. The old name is deprecated and will be removed in a future release. diff --git a/changelog/3637.changed.5.md b/changelog/3637.changed.5.md deleted file mode 100644 index 367f9f6e3..000000000 --- a/changelog/3637.changed.5.md +++ /dev/null @@ -1 +0,0 @@ -- Improved the accuracy of the `UserBotLatencyObserver` and `UserBotLatencyLogObserver` by measuring from the time when the user actually starts speaking. \ No newline at end of file diff --git a/changelog/3637.changed.md b/changelog/3637.changed.md deleted file mode 100644 index 4556f4d65..000000000 --- a/changelog/3637.changed.md +++ /dev/null @@ -1 +0,0 @@ -- ⚠️ Renamed `timeout` parameter to `user_speech_timeout` in `TranscriptionUserTurnStopStrategy`. diff --git a/changelog/3637.removed.md b/changelog/3637.removed.md deleted file mode 100644 index 695bce96d..000000000 --- a/changelog/3637.removed.md +++ /dev/null @@ -1 +0,0 @@ -- ⚠️ Removed `timeout` parameter from `TurnAnalyzerUserTurnStopStrategy`. The timeout is now managed internally based on STT latency. diff --git a/changelog/3644.changed.md b/changelog/3644.changed.md deleted file mode 100644 index 8b1511b9f..000000000 --- a/changelog/3644.changed.md +++ /dev/null @@ -1 +0,0 @@ -- `AssemblyAISTTService` now automatically configures optimal settings for manual turn detection when `vad_force_turn_endpoint=True`. This sets `end_of_turn_confidence_threshold=1.0` and `max_turn_silence=2000` by default, which disables model-based turn detection and reduces latency by relying on external VAD for turn endpoints. Warnings are logged if conflicting settings are detected. diff --git a/changelog/3649.fixed.md b/changelog/3649.fixed.md deleted file mode 100644 index 28c8231dd..000000000 --- a/changelog/3649.fixed.md +++ /dev/null @@ -1 +0,0 @@ -- Fixed orphan OpenTelemetry spans during flow initialization and transitions in tracing. diff --git a/changelog/3652.changed.md b/changelog/3652.changed.md deleted file mode 100644 index ee59a8686..000000000 --- a/changelog/3652.changed.md +++ /dev/null @@ -1 +0,0 @@ -- Upgraded the `pipecat-ai-small-webrtc-prebuilt` package to v2.1.0. \ No newline at end of file diff --git a/changelog/3653.added.2.md b/changelog/3653.added.2.md deleted file mode 100644 index 5207bdeaf..000000000 --- a/changelog/3653.added.2.md +++ /dev/null @@ -1 +0,0 @@ -- Added support for `video_settings` parameter in `LiveAvatarNewSessionRequest` to configure video encoding (H264/VP8) and quality levels. \ No newline at end of file diff --git a/changelog/3653.added.md b/changelog/3653.added.md deleted file mode 100644 index 09c5f3142..000000000 --- a/changelog/3653.added.md +++ /dev/null @@ -1 +0,0 @@ -- Added support for `is_sandbox` parameter in `LiveAvatarNewSessionRequest` to enable sandbox mode for HeyGen LiveAvatar sessions. \ No newline at end of file diff --git a/changelog/3653.changed.md b/changelog/3653.changed.md deleted file mode 100644 index a2c9aa3c3..000000000 --- a/changelog/3653.changed.md +++ /dev/null @@ -1 +0,0 @@ -- Changed default session mode from "CUSTOM" to "LITE" in HeyGen LiveAvatar integration, with VP8 as the default video encoding. \ No newline at end of file diff --git a/changelog/3656.added.md b/changelog/3656.added.md deleted file mode 100644 index 0918be248..000000000 --- a/changelog/3656.added.md +++ /dev/null @@ -1 +0,0 @@ -- Added `OpenAIRealtimeSTTService` for real-time streaming speech-to-text using OpenAI's Realtime API WebSocket transcription sessions. Supports local VAD and server-side VAD modes, noise reduction, and automatic reconnection. diff --git a/changelog/3659.changed.md b/changelog/3659.changed.md deleted file mode 100644 index 583f45f82..000000000 --- a/changelog/3659.changed.md +++ /dev/null @@ -1,10 +0,0 @@ -- ⚠️ The default `VADParams` `stop_secs` default is changing from `0.8` seconds - to `0.2` seconds. This change both simplifies the developer experience and - improves the performance of STT services. With a shorter `stop_secs` value, - STT services using a local VAD can finalize sooner, resulting in faster - transcription. - - - `SpeechTimeoutUserTurnStopStrategy`: control how long to wait for - additional user speech using `user_speech_timeout` (default: 0.6 sec). - - `TurnAnalyzerUserTurnStopStrategy`: the turn analyzer automatically adjusts - the user wait time based on the audio input. \ No newline at end of file diff --git a/changelog/3660.changed.md b/changelog/3660.changed.md deleted file mode 100644 index e5077b73b..000000000 --- a/changelog/3660.changed.md +++ /dev/null @@ -1 +0,0 @@ -- Moved interruption wait event from per-processor instance state to `InterruptionFrame` itself. Added `InterruptionFrame.complete()` to signal when the interruption has fully traversed the pipeline. Custom processors that block or consume an `InterruptionFrame` before it reaches the pipeline sink must call `frame.complete()` to avoid stalling `push_interruption_task_frame_and_wait()`. A warning is logged if completion does not happen within 2 seconds. diff --git a/changelog/3663.fixed.md b/changelog/3663.fixed.md deleted file mode 100644 index be6318aad..000000000 --- a/changelog/3663.fixed.md +++ /dev/null @@ -1 +0,0 @@ -- Fixed `SambaNovaLLMService` and `GoogleLLMOpenAIBetaService` streams not being closed on cancellation/exception, which could leak sockets. diff --git a/changelog/3664.changed.md b/changelog/3664.changed.md deleted file mode 100644 index f91dff3bd..000000000 --- a/changelog/3664.changed.md +++ /dev/null @@ -1 +0,0 @@ -- Update the default model to `scribe_v2` for `ElevenLabsSTTService`. \ No newline at end of file diff --git a/changelog/3666.changed.md b/changelog/3666.changed.md deleted file mode 100644 index 0fbdbc59c..000000000 --- a/changelog/3666.changed.md +++ /dev/null @@ -1 +0,0 @@ -- Changed the `DeepgramSTTService` default setting for `smart_format` to `False`, as agents don't need smart formatting. Disabling this setting provides a small performance improvement, as well. \ No newline at end of file diff --git a/changelog/3667.fixed.md b/changelog/3667.fixed.md deleted file mode 100644 index 1a83c0125..000000000 --- a/changelog/3667.fixed.md +++ /dev/null @@ -1 +0,0 @@ -- Fixed an issue in `InworldTTSService` where punctuation was pronounced. Now, the `InworldTTSService` ensures proper spacing between sentences, resolving pronunciation issues. \ No newline at end of file diff --git a/changelog/3668.fixed.md b/changelog/3668.fixed.md deleted file mode 100644 index 6885a7591..000000000 --- a/changelog/3668.fixed.md +++ /dev/null @@ -1 +0,0 @@ -- Fixed `ParallelPipeline` allowing frames pushed by internal processors to escape during lifecycle frame (`StartFrame`/`EndFrame`/`CancelFrame`) synchronization. These frames are now buffered and flushed after all branches complete. diff --git a/changelog/3671.added.2.md b/changelog/3671.added.2.md deleted file mode 100644 index db4caeba5..000000000 --- a/changelog/3671.added.2.md +++ /dev/null @@ -1 +0,0 @@ -- Added `bulbul:v3-beta` TTS model support for Sarvam AI with temperature control and 25 new speaker voices. diff --git a/changelog/3671.added.md b/changelog/3671.added.md deleted file mode 100644 index 625d443b7..000000000 --- a/changelog/3671.added.md +++ /dev/null @@ -1 +0,0 @@ -- Added `saaras:v3` STT model support for Sarvam AI with new `mode` parameter (transcribe, translate, verbatim, translit, codemix) and prompt support. diff --git a/changelog/3671.fixed.md b/changelog/3671.fixed.md deleted file mode 100644 index 6e53ea864..000000000 --- a/changelog/3671.fixed.md +++ /dev/null @@ -1 +0,0 @@ -- Fixed issues in Sarvam STT and TTS services: missing event handler registration for VAD signals, `Optional[bool]` type annotations, WebSocket state cleanup on API errors, and TTS disconnect/reconnection state management. diff --git a/changelog/3672.changed.md b/changelog/3672.changed.md deleted file mode 100644 index 9722d00e0..000000000 --- a/changelog/3672.changed.md +++ /dev/null @@ -1 +0,0 @@ -- Changed `FunctionCallCancelFrame` to broadcast in both directions for consistency with other function call frames. diff --git a/changelog/3672.fixed.md b/changelog/3672.fixed.md deleted file mode 100644 index 1f68ed008..000000000 --- a/changelog/3672.fixed.md +++ /dev/null @@ -1 +0,0 @@ -- Fixed `RTVIObserver` sending duplicate client messages for frames that are broadcast in both directions (e.g. `UserStartedSpeakingFrame`, `FunctionCallResultFrame`). diff --git a/changelog/3675.fixed.md b/changelog/3675.fixed.md deleted file mode 100644 index 12e19efac..000000000 --- a/changelog/3675.fixed.md +++ /dev/null @@ -1 +0,0 @@ -- Fixed WebSocket STT services (ElevenLabs, Cartesia, Gladia, Soniox) disconnecting due to idle timeout when no audio is being sent (e.g. when inactive behind a `ServiceSwitcher`). `WebsocketSTTService` now provides opt-in silence-based keepalive via `keepalive_timeout` and `keepalive_interval` parameters. diff --git a/changelog/3682.added.md b/changelog/3682.added.md deleted file mode 100644 index c9a5061b7..000000000 --- a/changelog/3682.added.md +++ /dev/null @@ -1 +0,0 @@ -- Added new OpenAI TTS voice options `marin` and `cedar`. diff --git a/changelog/3687.added.md b/changelog/3687.added.md deleted file mode 100644 index 38a10fb75..000000000 --- a/changelog/3687.added.md +++ /dev/null @@ -1 +0,0 @@ -- Added `UserMuteStartedFrame` and `UserMuteStoppedFrame` system frames, and corresponding `user-mute-started` / `user-mute-stopped` RTVI messages, so clients can observe when mute strategies activate or deactivate. diff --git a/changelog/3689.changed.md b/changelog/3689.changed.md deleted file mode 100644 index 98e7dc2b4..000000000 --- a/changelog/3689.changed.md +++ /dev/null @@ -1 +0,0 @@ -- Changed default user turn stop strategy from `TranscriptionUserTurnStopStrategy` to `TurnAnalyzerUserTurnStopStrategy` with `LocalSmartTurnAnalyzerV3`. diff --git a/changelog/3692.changed.md b/changelog/3692.changed.md deleted file mode 100644 index adb9e1d62..000000000 --- a/changelog/3692.changed.md +++ /dev/null @@ -1 +0,0 @@ -- Renamed `RequestMetadataFrame` to `ServiceSwitcherRequestMetadataFrame` and added a `service` field to target a specific service. The frame is now pushed downstream by services after handling instead of being silently consumed. diff --git a/changelog/3697.changed.2.md b/changelog/3697.changed.2.md deleted file mode 100644 index 0307bd59a..000000000 --- a/changelog/3697.changed.2.md +++ /dev/null @@ -1 +0,0 @@ -- Update `SonioxSTTService` to set `vad_force_turn_endpoint` to `True`. This setting disabled the turn detection logic available natively in Soniox. Instead, Soniox relies on a local VAD to finalize the transcript. This configuration meaningfully reduces the time to final segment for Soniox. With this setting enabled, Soniox outputs a transcript in ~250ms (median). Pipecat enables smart-turn detection by default using the `LocalSmartTurnAnalyzerV3`. To use the native turn detection logic in Soniox, just set `vad_force_turn_endpoint` to `False`. \ No newline at end of file diff --git a/changelog/3697.changed.md b/changelog/3697.changed.md deleted file mode 100644 index ce7bf49d7..000000000 --- a/changelog/3697.changed.md +++ /dev/null @@ -1 +0,0 @@ -- Update `SonioxSTTService` default model to `stt-rt-v4`. \ No newline at end of file diff --git a/changelog/3701.changed.md b/changelog/3701.changed.md deleted file mode 100644 index 03c0d787e..000000000 --- a/changelog/3701.changed.md +++ /dev/null @@ -1 +0,0 @@ -- Updated the default model to `async_flash_v1.0` and base URL to `https://api.async.com` for `AsyncAITTSService`. \ No newline at end of file diff --git a/changelog/3707.fixed.md b/changelog/3707.fixed.md deleted file mode 100644 index 257342c62..000000000 --- a/changelog/3707.fixed.md +++ /dev/null @@ -1 +0,0 @@ -- Fixed stream closing compatibility for OpenAI-compatible providers (e.g. OpenPipe) that return async generators instead of `AsyncStream`. From b063d9d43b069de6608155a988fe1cca4a2e5145 Mon Sep 17 00:00:00 2001 From: Mark Backman Date: Tue, 10 Feb 2026 22:06:38 -0500 Subject: [PATCH 0446/1060] Fix quickstart pyproject.toml --- examples/quickstart/pyproject.toml | 3 --- 1 file changed, 3 deletions(-) diff --git a/examples/quickstart/pyproject.toml b/examples/quickstart/pyproject.toml index ee18f96c0..efeee9106 100644 --- a/examples/quickstart/pyproject.toml +++ b/examples/quickstart/pyproject.toml @@ -18,6 +18,3 @@ dev = [ line-length = 100 [tool.ruff.lint] select = ["I"] - - [tool.uv.sources] -pipecat-ai = { path = "../../", editable = true } \ No newline at end of file From 972ad93e1842476a17a0fbac4a3d3df4cbd93123 Mon Sep 17 00:00:00 2001 From: Mark Backman Date: Tue, 10 Feb 2026 22:17:09 -0500 Subject: [PATCH 0447/1060] Fix quickstart pcc-deploy.toml --- examples/quickstart/pcc-deploy.toml | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/examples/quickstart/pcc-deploy.toml b/examples/quickstart/pcc-deploy.toml index 812e2b8e6..f08e8a624 100644 --- a/examples/quickstart/pcc-deploy.toml +++ b/examples/quickstart/pcc-deploy.toml @@ -1,5 +1,5 @@ agent_name = "quickstart-test" -image = "markatdaily/quickstart-test:latest" +image = "your_username/quickstart-test:latest" secret_set = "quickstart-test-secrets" agent_profile = "agent-1x" From 2036757b84062dc0804f77ecf2466c39b3932461 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?G=C3=B6kmen=20G=C3=B6rgen?= Date: Wed, 11 Feb 2026 15:22:37 +0100 Subject: [PATCH 0448/1060] add unit tests for `AICModelManager` and `AICFilter` error handling, model loading, and processor behavior --- changelog/3684.changed.md | 3 +- src/pipecat/audio/filters/aic_filter.py | 15 ++-- tests/test_aic_filter.py | 101 ++++++++++++++++++++++++ 3 files changed, 112 insertions(+), 7 deletions(-) diff --git a/changelog/3684.changed.md b/changelog/3684.changed.md index 017fc9946..1bdb2c89c 100644 --- a/changelog/3684.changed.md +++ b/changelog/3684.changed.md @@ -1,2 +1,3 @@ - `AICFilter` now shares read-only AIC models via a singleton `AICModelManager` in `aic_filter.py`. - - Multiple filters using the same `model path` or `(model_id, model_download_dir)` share one loaded model, with reference counting and concurrent load deduplication. + - Multiple filters using the same model path or `(model_id, model_download_dir)` share one loaded model, with reference counting and concurrent load deduplication. + - Model file I/O runs off the event loop so the filter does not block. diff --git a/src/pipecat/audio/filters/aic_filter.py b/src/pipecat/audio/filters/aic_filter.py index 399e6cd2e..723b3da8f 100644 --- a/src/pipecat/audio/filters/aic_filter.py +++ b/src/pipecat/audio/filters/aic_filter.py @@ -77,16 +77,19 @@ class AICModelManager: """Run the actual load (file or download). Separate to allow create_task and deduplication.""" if model_path is not None: logger.debug(f"Loading AIC model from file: {model_path}") - return Model.from_file(str(model_path)) + model_path_str = str(model_path) - if model_id is not None and model_download_dir is not None: + elif model_id is not None and model_download_dir is not None: logger.debug(f"Downloading AIC model: {model_id}") model_download_dir.mkdir(parents=True, exist_ok=True) - path = await Model.download_async(model_id, str(model_download_dir)) - logger.debug(f"Model downloaded to: {path}") - return Model.from_file(path) + model_path_str = await Model.download_async(model_id, str(model_download_dir)) + logger.debug(f"Model downloaded to: {model_path_str}") - raise ValueError("Unexpected model_path or (model_id and model_download_dir) state.") + else: + raise ValueError("Unexpected model_path or (model_id and model_download_dir) state.") + + loop = asyncio.get_running_loop() + return await loop.run_in_executor(None, lambda: Model.from_file(model_path_str)) @staticmethod def _get_cache_key( diff --git a/tests/test_aic_filter.py b/tests/test_aic_filter.py index c36022a7b..83eca757c 100644 --- a/tests/test_aic_filter.py +++ b/tests/test_aic_filter.py @@ -350,6 +350,107 @@ class TestAICFilter(unittest.IsolatedAsyncioTestCase): manager.release(key1) self.assertEqual(_model_manager_ref_count(manager, key1), 0) + async def test_load_model_from_file_invalid_args_raises(self): + """Test _load_model_from_file defensive else: raises ValueError.""" + manager = self.AICModelManager + with self.assertRaises(ValueError) as ctx: + await manager._load_model_from_file( + "key", + model_path=None, + model_id=None, + model_download_dir=None, + ) + self.assertIn("Unexpected", str(ctx.exception)) + + async def test_model_manager_acquire_by_model_id_hits_download_path(self): + """Test acquire with model_id runs download path in _load_model_from_file.""" + model_id = "test-model-id" + model_download_dir = Path("/tmp/aic-downloads") + mock_model = MockModel() + manager = self.AICModelManager + + with patch(f"{AIC_FILTER_MODULE}.Model") as mock_model_cls: + mock_model_cls.download_async = AsyncMock( + return_value="/tmp/aic-downloads/model.aicmodel" + ) + mock_model_cls.from_file.return_value = mock_model + + model, key = await manager.acquire( + model_id=model_id, + model_download_dir=model_download_dir, + ) + + mock_model_cls.download_async.assert_called_once() + mock_model_cls.from_file.assert_called_once_with("/tmp/aic-downloads/model.aicmodel") + self.assertIs(model, mock_model) + self.assertEqual(_model_manager_ref_count(manager, key), 1) + manager.release(key) + + def test_get_cache_key_invalid_raises(self): + """Test _get_cache_key raises ValueError for invalid args.""" + with self.assertRaises(ValueError) as ctx: + self.AICModelManager._get_cache_key(model_path=None, model_id=None) + self.assertIn("model_path", str(ctx.exception)) + + with self.assertRaises(ValueError) as ctx2: + self.AICModelManager._get_cache_key( + model_path=None, + model_id="x", + model_download_dir=None, + ) + self.assertIn("model_download_dir", str(ctx2.exception)) + + async def test_start_processor_init_failure(self): + """Test start() when ProcessorAsync raises: exception logged, _aic_ready False.""" + filter_instance = self._create_filter_with_mocks() + + with ( + patch(f"{AIC_FILTER_MODULE}.AICModelManager") as mock_manager_cls, + patch(f"{AIC_FILTER_MODULE}.ProcessorConfig") as mock_config_cls, + patch( + f"{AIC_FILTER_MODULE}.ProcessorAsync", + side_effect=RuntimeError("SDK init failed"), + ), + ): + mock_manager_cls.acquire = AsyncMock(return_value=(self.mock_model, "test-key")) + mock_config_cls.optimal.return_value = MagicMock() + + await filter_instance.start(16000) + + self.assertIsNone(filter_instance._processor) + self.assertFalse(filter_instance._aic_ready) + + async def test_start_parameter_fixed_error_logged(self): + """Test start() when set_parameter raises ParameterFixedError: logged, no raise.""" + filter_instance = self._create_filter_with_mocks() + self.mock_processor.processor_ctx.set_parameter = MagicMock( + side_effect=aic_sdk.ParameterFixedError("fixed") + ) + + with ( + patch(f"{AIC_FILTER_MODULE}.AICModelManager") as mock_manager_cls, + patch(f"{AIC_FILTER_MODULE}.ProcessorConfig") as mock_config_cls, + patch(f"{AIC_FILTER_MODULE}.ProcessorAsync", return_value=self.mock_processor), + ): + mock_manager_cls.acquire = AsyncMock(return_value=(self.mock_model, "test-key")) + mock_config_cls.optimal.return_value = MagicMock() + + await filter_instance.start(16000) + + self.assertTrue(filter_instance._aic_ready) + + async def test_process_frame_set_parameter_exception_logged(self): + """Test process_frame when set_parameter raises: exception logged, no raise.""" + filter_instance = self._create_filter_with_mocks() + await self._start_filter_with_mocks(filter_instance) + filter_instance._processor_ctx.set_parameter = MagicMock( + side_effect=ValueError("param error") + ) + + await filter_instance.process_frame(self.FilterEnableFrame(enable=True)) + + self.assertFalse(filter_instance._bypass) + async def test_process_frame_enable(self): """Test processing FilterEnableFrame to enable filtering.""" filter_instance = self._create_filter_with_mocks() From ec2b38dc299d3f04416079aa62d6fdbed62f8527 Mon Sep 17 00:00:00 2001 From: filipi87 Date: Wed, 11 Feb 2026 13:01:25 -0300 Subject: [PATCH 0449/1060] Fixing smallwebrtc transport input audio resampling logic. --- .../transports/smallwebrtc/transport.py | 36 +++++++------------ 1 file changed, 13 insertions(+), 23 deletions(-) diff --git a/src/pipecat/transports/smallwebrtc/transport.py b/src/pipecat/transports/smallwebrtc/transport.py index 7e22fb00c..4389ff5d9 100644 --- a/src/pipecat/transports/smallwebrtc/transport.py +++ b/src/pipecat/transports/smallwebrtc/transport.py @@ -233,9 +233,8 @@ class SmallWebRTCClient: self._out_sample_rate = None self._leave_counter = 0 - # We are always resampling it for 16000 if the sample_rate that we receive is bigger than that. - # otherwise we face issues with Silero VAD - self._pipecat_resampler = AudioResampler("s16", "mono", 16000) + # Audio resampler - will be configured during setup with target sample rate + self._audio_in_resampler = None @self._webrtc_connection.event_handler("connected") async def on_connected(connection: SmallWebRTCConnection): @@ -375,32 +374,22 @@ class SmallWebRTCClient: await asyncio.sleep(0.01) continue - if frame.sample_rate > self._in_sample_rate: - resampled_frames = self._pipecat_resampler.resample(frame) - for resampled_frame in resampled_frames: - # 16-bit PCM bytes - pcm_array = resampled_frame.to_ndarray().astype(np.int16) - pcm_bytes = pcm_array.tobytes() - del pcm_array # free NumPy array immediately + # Resample if needed, otherwise use the frame as-is + frames_to_process = ( + self._audio_in_resampler.resample(frame) + if frame.sample_rate != self._in_sample_rate + else [frame] + ) - audio_frame = InputAudioRawFrame( - audio=pcm_bytes, - sample_rate=resampled_frame.sample_rate, - num_channels=self._audio_in_channels, - ) - audio_frame.pts = frame.pts - del pcm_bytes # reference kept in audio_frame - - yield audio_frame - else: - # 16-bit PCM bytes - pcm_array = frame.to_ndarray().astype(np.int16) + for processed_frame in frames_to_process: + # Convert to 16-bit PCM bytes + pcm_array = processed_frame.to_ndarray().astype(np.int16) pcm_bytes = pcm_array.tobytes() del pcm_array # free NumPy array immediately audio_frame = InputAudioRawFrame( audio=pcm_bytes, - sample_rate=frame.sample_rate, + sample_rate=self._in_sample_rate, num_channels=self._audio_in_channels, ) audio_frame.pts = frame.pts @@ -450,6 +439,7 @@ class SmallWebRTCClient: self._out_sample_rate = _params.audio_out_sample_rate or frame.audio_out_sample_rate self._params = _params self._leave_counter += 1 + self._audio_in_resampler = AudioResampler("s16", "mono", self._in_sample_rate) async def connect(self): """Establish the WebRTC connection.""" From 0c3e59ed61addc6643f4d8c586a909db767833c4 Mon Sep 17 00:00:00 2001 From: filipi87 Date: Wed, 11 Feb 2026 13:07:52 -0300 Subject: [PATCH 0450/1060] Adding changelog entry for the SmallWebRTCTransport fix. --- changelog/3713.fixed.md | 1 + 1 file changed, 1 insertion(+) create mode 100644 changelog/3713.fixed.md diff --git a/changelog/3713.fixed.md b/changelog/3713.fixed.md new file mode 100644 index 000000000..241f0e56a --- /dev/null +++ b/changelog/3713.fixed.md @@ -0,0 +1 @@ +- Fixed `SmallWebRTCTransport` input audio resampling to properly handle all sample rates, including 8kHz audio. From 1fe4538982e0cafa03bbb576f5212f98d62f8ee7 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Aleix=20Conchillo=20Flaqu=C3=A9?= Date: Wed, 11 Feb 2026 09:51:10 -0800 Subject: [PATCH 0451/1060] Update PR submission instructions in CLAUDE.md Expand the Pull Requests section with detailed step-by-step instructions including branch naming, commit guidance, changelog generation, and PR description updates. --- CLAUDE.md | 7 ++++++- 1 file changed, 6 insertions(+), 1 deletion(-) diff --git a/CLAUDE.md b/CLAUDE.md index cf4c5baec..0f4b55e22 100644 --- a/CLAUDE.md +++ b/CLAUDE.md @@ -155,4 +155,9 @@ Test utilities live in `src/pipecat/tests/utils.py`. Use `run_test()` to send fr ## Pull Requests -After creating a PR, use `/changelog ` to generate the changelog file and `/pr-description ` to update the PR description. +To submit a PR you should: + +1. Create a new branch. Ask the user if they want a specific prefix for the branch name. +2. Commit the changes using multiple commits if the changes are unrelated. +3. After creating the PR, use `/changelog ` to generate the changelog files, commit and push them. +4. Use `/pr-description ` to update the PR description. From a80919ceff4a26c2b65a545996f282e5c853300b Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Aleix=20Conchillo=20Flaqu=C3=A9?= Date: Wed, 11 Feb 2026 09:54:39 -0800 Subject: [PATCH 0452/1060] Move PR submission instructions from CLAUDE.md to /pr-submit skill Extract the procedural PR workflow into an actionable skill that can be invoked with /pr-submit. CLAUDE.md is better suited for project context and conventions, not step-by-step procedures. --- .claude/skills/pr-submit/SKILL.md | 28 ++++++++++++++++++++++++++++ CLAUDE.md | 8 -------- 2 files changed, 28 insertions(+), 8 deletions(-) create mode 100644 .claude/skills/pr-submit/SKILL.md diff --git a/.claude/skills/pr-submit/SKILL.md b/.claude/skills/pr-submit/SKILL.md new file mode 100644 index 000000000..5724ddb6e --- /dev/null +++ b/.claude/skills/pr-submit/SKILL.md @@ -0,0 +1,28 @@ +--- +name: pr-submit +description: Create and submit a GitHub PR from the current branch +--- + +Submit the current changes as a GitHub pull request. + +## Instructions + +1. Check the current state of the repository: + - Run `git status` to see staged, unstaged, and untracked changes + - Run `git diff` to see current changes + - Run `git log --oneline -10` to see recent commits + +2. If there are uncommitted changes relevant to the PR: + - Ask the user if they want a specific prefix for the branch name (e.g., `alice/`, `fix/`, `feat/`) + - Create a new branch based on the current branch + - Commit the changes using multiple commits if the changes are unrelated + +3. Push the branch and create the PR: + - Push with `-u` flag to set upstream tracking + - Create the PR using `gh pr create` + +4. After the PR is created: + - Run `/changelog ` to generate changelog files, then commit and push them + - Run `/pr-description ` to update the PR description + +5. Return the PR URL to the user. diff --git a/CLAUDE.md b/CLAUDE.md index 0f4b55e22..7b79fa168 100644 --- a/CLAUDE.md +++ b/CLAUDE.md @@ -153,11 +153,3 @@ When adding a new service: Test utilities live in `src/pipecat/tests/utils.py`. Use `run_test()` to send frames through a pipeline and assert expected output frames in each direction. Use `SleepFrame(sleep=N)` to add delays between frames. -## Pull Requests - -To submit a PR you should: - -1. Create a new branch. Ask the user if they want a specific prefix for the branch name. -2. Commit the changes using multiple commits if the changes are unrelated. -3. After creating the PR, use `/changelog ` to generate the changelog files, commit and push them. -4. Use `/pr-description ` to update the PR description. From beb4e86b5f6dab95fe702cd6295bcd0f90aea291 Mon Sep 17 00:00:00 2001 From: filipi87 Date: Wed, 11 Feb 2026 16:17:28 -0300 Subject: [PATCH 0453/1060] Fixing an issue in RTVI where we were sometimes receiving bot output messages before the bot started speaking. --- src/pipecat/processors/frameworks/rtvi.py | 23 ++++++++++++++++++++--- 1 file changed, 20 insertions(+), 3 deletions(-) diff --git a/src/pipecat/processors/frameworks/rtvi.py b/src/pipecat/processors/frameworks/rtvi.py index d85cae11f..c1497b40b 100644 --- a/src/pipecat/processors/frameworks/rtvi.py +++ b/src/pipecat/processors/frameworks/rtvi.py @@ -1116,6 +1116,10 @@ class RTVIObserver(BaseObserver): self._last_user_audio_level = 0 self._last_bot_audio_level = 0 + # Track bot speaking state for queuing aggregated text frames + self._bot_is_speaking = False + self._queued_aggregated_text_frames: List[AggregatedTextFrame] = [] + if self._params.system_logs_enabled: self._system_logger_id = logger.add(self._logger_sink) @@ -1384,17 +1388,30 @@ class RTVIObserver(BaseObserver): async def _handle_bot_speaking(self, frame: Frame): """Handle bot speaking event frames.""" - message = None if isinstance(frame, BotStartedSpeakingFrame): message = RTVIBotStartedSpeakingMessage() + await self.send_rtvi_message(message) + # Flush any queued aggregated text frames + for queued_frame in self._queued_aggregated_text_frames: + await self._send_aggregated_llm_text(queued_frame) + self._queued_aggregated_text_frames.clear() + self._bot_is_speaking = True elif isinstance(frame, BotStoppedSpeakingFrame): message = RTVIBotStoppedSpeakingMessage() - - if message: await self.send_rtvi_message(message) + self._bot_is_speaking = False async def _handle_aggregated_llm_text(self, frame: AggregatedTextFrame): """Handle aggregated LLM text output frames.""" + if self._bot_is_speaking: + # Bot has already started speaking, send directly + await self._send_aggregated_llm_text(frame) + else: + # Bot hasn't started speaking yet, queue the frame + self._queued_aggregated_text_frames.append(frame) + + async def _send_aggregated_llm_text(self, frame: AggregatedTextFrame): + """Send aggregated LLM text messages.""" # Skip certain aggregator types if configured to do so. if ( self._params.skip_aggregator_types From ed7fde324ed2dd40aefe613ddf9e7b4d4b7b0638 Mon Sep 17 00:00:00 2001 From: filipi87 Date: Wed, 11 Feb 2026 16:23:42 -0300 Subject: [PATCH 0454/1060] Adding changelog entry for the RTVIObserver fix. --- changelog/3718.fixed.md | 1 + 1 file changed, 1 insertion(+) create mode 100644 changelog/3718.fixed.md diff --git a/changelog/3718.fixed.md b/changelog/3718.fixed.md new file mode 100644 index 000000000..68e1d2682 --- /dev/null +++ b/changelog/3718.fixed.md @@ -0,0 +1 @@ +- Fixed a race condition in `RTVIObserver` where bot output messages could be sent before the bot-started-speaking event. From 16b060d9e956f391bdbefd5261377fba77baee98 Mon Sep 17 00:00:00 2001 From: Mark Backman Date: Wed, 11 Feb 2026 18:04:20 -0500 Subject: [PATCH 0455/1060] Fix Grok Realtime voice type validation for server responses The Grok API now returns prefixed voice names (e.g. "human_Ara") in session.updated events, causing Pydantic validation errors. Widen the voice field type from GrokVoice to GrokVoice | str to accept both user-facing names and server-returned values. --- src/pipecat/services/grok/realtime/events.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/src/pipecat/services/grok/realtime/events.py b/src/pipecat/services/grok/realtime/events.py index 4069ff927..1f89a92f7 100644 --- a/src/pipecat/services/grok/realtime/events.py +++ b/src/pipecat/services/grok/realtime/events.py @@ -216,7 +216,7 @@ class SessionProperties(BaseModel): model_config = ConfigDict(arbitrary_types_allowed=True) instructions: Optional[str] = None - voice: Optional[GrokVoice] = "Ara" + voice: Optional[GrokVoice | str] = "Ara" turn_detection: Optional[TurnDetection] = Field( default_factory=lambda: TurnDetection(type="server_vad") ) From a9669472202c789232d3170ca37f723ec9b5acd3 Mon Sep 17 00:00:00 2001 From: Mark Backman Date: Wed, 11 Feb 2026 18:04:58 -0500 Subject: [PATCH 0456/1060] Add changelog for #3720 --- changelog/3720.fixed.md | 1 + 1 file changed, 1 insertion(+) create mode 100644 changelog/3720.fixed.md diff --git a/changelog/3720.fixed.md b/changelog/3720.fixed.md new file mode 100644 index 000000000..c3cb69d34 --- /dev/null +++ b/changelog/3720.fixed.md @@ -0,0 +1 @@ +- Fixed Grok Realtime `session.updated` event parsing failure caused by the API returning prefixed voice names (e.g. `"human_Ara"` instead of `"Ara"`). From dcbcab154287a366e7a24213bef48f57a04c917c Mon Sep 17 00:00:00 2001 From: Ian Lee Date: Tue, 10 Feb 2026 17:52:38 -0800 Subject: [PATCH 0457/1060] [Inworld] add User-Agent and X-Request-Id for better traceability --- changelog/3706.changed.md | 1 + src/pipecat/services/inworld/tts.py | 19 ++++++++++++++++--- 2 files changed, 17 insertions(+), 3 deletions(-) create mode 100644 changelog/3706.changed.md diff --git a/changelog/3706.changed.md b/changelog/3706.changed.md new file mode 100644 index 000000000..0c9876bdc --- /dev/null +++ b/changelog/3706.changed.md @@ -0,0 +1 @@ +- Added `X-User-Agent` and `X-Request-Id` headers to `InworldTTSService` for better traceability. diff --git a/src/pipecat/services/inworld/tts.py b/src/pipecat/services/inworld/tts.py index 2ea94399b..7ba7d6b9d 100644 --- a/src/pipecat/services/inworld/tts.py +++ b/src/pipecat/services/inworld/tts.py @@ -16,11 +16,16 @@ Inworld’s text-to-speech (TTS) models offer ultra-realistic, context-aware spe import asyncio import base64 import json +import uuid from typing import Any, AsyncGenerator, Dict, List, Optional, Tuple import aiohttp import websockets from loguru import logger + +from pipecat import version as pipecat_version + +USER_AGENT = f"pipecat/{pipecat_version()}" from pydantic import BaseModel try: @@ -236,9 +241,12 @@ class InworldHttpTTSService(WordTTSService): # Use WORD timestamps for simplicity and correct spacing/capitalization payload["timestampType"] = self._timestamp_type + request_id = str(uuid.uuid4()) headers = { "Authorization": f"Basic {self._api_key}", "Content-Type": "application/json", + "X-User-Agent": USER_AGENT, + "X-Request-Id": request_id, } try: @@ -252,7 +260,7 @@ class InworldHttpTTSService(WordTTSService): ) as response: if response.status != 200: error_text = await response.text() - logger.error(f"Inworld API error: {error_text}") + logger.error(f"Inworld API error (request_id={request_id}): {error_text}") yield ErrorFrame(error=f"Inworld API error: {error_text}") return @@ -693,8 +701,13 @@ class InworldTTSService(AudioContextWordTTSService): if self._websocket and self._websocket.state is State.OPEN: return - logger.debug("Connecting to Inworld WebSocket TTS") - headers = [("Authorization", f"Basic {self._api_key}")] + request_id = str(uuid.uuid4()) + logger.debug(f"Connecting to Inworld WebSocket TTS (request_id={request_id})") + headers = [ + ("Authorization", f"Basic {self._api_key}"), + ("X-User-Agent", USER_AGENT), + ("X-Request-Id", request_id), + ] self._websocket = await websocket_connect(self._url, additional_headers=headers) await self._call_event_handler("on_connected") except Exception as e: From 358f237507281b7cfbe908f718d5fe60deca614e Mon Sep 17 00:00:00 2001 From: Mark Backman Date: Wed, 11 Feb 2026 21:58:10 -0500 Subject: [PATCH 0458/1060] Replace singleton context providers with pipeline-scoped TracingContext ConversationContextProvider and TurnContextProvider were singletons that stored tracing context as class-level state. When two PipelineTask instances ran concurrently, they would overwrite each other's context, causing service spans to attach to the wrong pipeline's turn span. Replace both singletons with a single TracingContext object owned by each PipelineTask, threaded to services via StartFrame. --- src/pipecat/frames/frames.py | 3 + src/pipecat/pipeline/task.py | 6 + src/pipecat/services/llm_service.py | 1 + src/pipecat/services/stt_service.py | 1 + src/pipecat/services/tts_service.py | 1 + .../tracing/conversation_context_provider.py | 114 ------------------ .../utils/tracing/service_decorators.py | 20 +-- src/pipecat/utils/tracing/tracing_context.py | 109 +++++++++++++++++ .../utils/tracing/turn_context_provider.py | 81 ------------- .../utils/tracing/turn_trace_observer.py | 36 +++--- 10 files changed, 149 insertions(+), 223 deletions(-) delete mode 100644 src/pipecat/utils/tracing/conversation_context_provider.py create mode 100644 src/pipecat/utils/tracing/tracing_context.py delete mode 100644 src/pipecat/utils/tracing/turn_context_provider.py diff --git a/src/pipecat/frames/frames.py b/src/pipecat/frames/frames.py index 5634d79ee..8d237defc 100644 --- a/src/pipecat/frames/frames.py +++ b/src/pipecat/frames/frames.py @@ -42,6 +42,7 @@ from pipecat.utils.utils import obj_count, obj_id if TYPE_CHECKING: from pipecat.processors.aggregators.llm_context import LLMContext, NotGiven from pipecat.processors.frame_processor import FrameProcessor + from pipecat.utils.tracing.tracing_context import TracingContext class DeprecatedKeypadEntry: @@ -1036,6 +1037,7 @@ class StartFrame(SystemFrame): Use `LLMUserAggregator`'s new `user_turn_strategies` parameter instead. report_only_initial_ttfb: Whether to report only initial time-to-first-byte. + tracing_context: Pipeline-scoped tracing context for span hierarchy. """ audio_in_sample_rate: int = 16000 @@ -1046,6 +1048,7 @@ class StartFrame(SystemFrame): enable_usage_metrics: bool = False interruption_strategies: List[BaseInterruptionStrategy] = field(default_factory=list) report_only_initial_ttfb: bool = False + tracing_context: Optional["TracingContext"] = None @dataclass diff --git a/src/pipecat/pipeline/task.py b/src/pipecat/pipeline/task.py index 8bda19b18..2cfe26606 100644 --- a/src/pipecat/pipeline/task.py +++ b/src/pipecat/pipeline/task.py @@ -53,6 +53,7 @@ from pipecat.processors.frame_processor import FrameDirection, FrameProcessor, F from pipecat.processors.frameworks.rtvi import RTVIObserver, RTVIObserverParams, RTVIProcessor from pipecat.utils.asyncio.task_manager import BaseTaskManager, TaskManager, TaskManagerParams from pipecat.utils.tracing.setup import is_tracing_available +from pipecat.utils.tracing.tracing_context import TracingContext from pipecat.utils.tracing.turn_trace_observer import TurnTraceObserver HEARTBEAT_SECS = 1.0 @@ -290,10 +291,13 @@ class PipelineTask(BasePipelineTask): self._turn_tracking_observer: Optional[TurnTrackingObserver] = None self._user_bot_latency_observer: Optional[UserBotLatencyObserver] = None self._turn_trace_observer: Optional[TurnTraceObserver] = None + self._tracing_context: Optional[TracingContext] = None if self._enable_turn_tracking: self._turn_tracking_observer = TurnTrackingObserver() observers.append(self._turn_tracking_observer) if self._enable_tracing and self._turn_tracking_observer: + # Create pipeline-scoped tracing context + self._tracing_context = TracingContext() # Create latency observer for tracing self._user_bot_latency_observer = UserBotLatencyObserver() observers.append(self._user_bot_latency_observer) @@ -303,6 +307,7 @@ class PipelineTask(BasePipelineTask): latency_tracker=self._user_bot_latency_observer, conversation_id=self._conversation_id, additional_span_attributes=self._additional_span_attributes, + tracing_context=self._tracing_context, ) observers.append(self._turn_trace_observer) @@ -813,6 +818,7 @@ class PipelineTask(BasePipelineTask): enable_usage_metrics=self._params.enable_usage_metrics, report_only_initial_ttfb=self._params.report_only_initial_ttfb, interruption_strategies=self._params.interruption_strategies, + tracing_context=self._tracing_context, ) start_frame.metadata = self._create_start_metadata() await self._pipeline.queue_frame(start_frame) diff --git a/src/pipecat/services/llm_service.py b/src/pipecat/services/llm_service.py index af7e691b0..acbd6baae 100644 --- a/src/pipecat/services/llm_service.py +++ b/src/pipecat/services/llm_service.py @@ -286,6 +286,7 @@ class LLMService(UserTurnCompletionLLMServiceMixin, AIService): if not self._run_in_parallel: await self._create_sequential_runner_task() self._tracing_enabled = frame.enable_tracing + self._tracing_context = frame.tracing_context async def stop(self, frame: EndFrame): """Stop the LLM service. diff --git a/src/pipecat/services/stt_service.py b/src/pipecat/services/stt_service.py index b556bb23a..81f369572 100644 --- a/src/pipecat/services/stt_service.py +++ b/src/pipecat/services/stt_service.py @@ -203,6 +203,7 @@ class STTService(AIService): await super().start(frame) self._sample_rate = self._init_sample_rate or frame.audio_in_sample_rate self._tracing_enabled = frame.enable_tracing + self._tracing_context = frame.tracing_context async def cleanup(self): """Clean up STT service resources.""" diff --git a/src/pipecat/services/tts_service.py b/src/pipecat/services/tts_service.py index 239d2398b..00e3e81f8 100644 --- a/src/pipecat/services/tts_service.py +++ b/src/pipecat/services/tts_service.py @@ -350,6 +350,7 @@ class TTSService(AIService): if self._push_stop_frames and not self._stop_frame_task: self._stop_frame_task = self.create_task(self._stop_frame_handler()) self._tracing_enabled = frame.enable_tracing + self._tracing_context = frame.tracing_context async def stop(self, frame: EndFrame): """Stop the TTS service. diff --git a/src/pipecat/utils/tracing/conversation_context_provider.py b/src/pipecat/utils/tracing/conversation_context_provider.py deleted file mode 100644 index 4bb88fe14..000000000 --- a/src/pipecat/utils/tracing/conversation_context_provider.py +++ /dev/null @@ -1,114 +0,0 @@ -# -# Copyright (c) 2024-2026, Daily -# -# SPDX-License-Identifier: BSD 2-Clause License -# - -"""Conversation context provider for OpenTelemetry tracing in Pipecat. - -This module provides a singleton context provider that manages the current -conversation's tracing context, allowing services to create child spans -that are properly associated with the conversation. -""" - -import uuid -from typing import TYPE_CHECKING, Optional - -# Import types for type checking only -if TYPE_CHECKING: - from opentelemetry.context import Context - from opentelemetry.trace import SpanContext - -from pipecat.utils.tracing.setup import is_tracing_available - -if is_tracing_available(): - from opentelemetry.context import Context - from opentelemetry.trace import NonRecordingSpan, SpanContext, set_span_in_context - - -class ConversationContextProvider: - """Provides access to the current conversation's tracing context. - - This is a singleton that can be used to get the current conversation's - span context to create child spans (like turns). - """ - - _instance = None - _current_conversation_context: Optional["Context"] = None - _conversation_id: Optional[str] = None - - @classmethod - def get_instance(cls): - """Get the singleton instance. - - Returns: - The singleton ConversationContextProvider instance. - """ - if cls._instance is None: - cls._instance = ConversationContextProvider() - return cls._instance - - def set_current_conversation_context( - self, span_context: Optional["SpanContext"], conversation_id: Optional[str] = None - ): - """Set the current conversation context. - - Args: - span_context: The span context for the current conversation or None to clear it. - conversation_id: Optional ID for the conversation. - """ - if not is_tracing_available(): - return - - self._conversation_id = conversation_id - - if span_context: - # Create a non-recording span from the span context - non_recording_span = NonRecordingSpan(span_context) - self._current_conversation_context = set_span_in_context(non_recording_span) - else: - self._current_conversation_context = None - - def get_current_conversation_context(self) -> Optional["Context"]: - """Get the OpenTelemetry context for the current conversation. - - Returns: - The current conversation context or None if not available. - """ - return self._current_conversation_context - - def get_conversation_id(self) -> Optional[str]: - """Get the ID for the current conversation. - - Returns: - The current conversation ID or None if not available. - """ - return self._conversation_id - - def generate_conversation_id(self) -> str: - """Generate a new conversation ID. - - Returns: - A new randomly generated UUID string. - """ - return str(uuid.uuid4()) - - -def get_current_conversation_context() -> Optional["Context"]: - """Get the OpenTelemetry context for the current conversation. - - Returns: - The current conversation context or None if not available. - """ - provider = ConversationContextProvider.get_instance() - return provider.get_current_conversation_context() - - -def get_conversation_id() -> Optional[str]: - """Get the ID for the current conversation. - - Returns: - The current conversation ID or None if not available. - """ - provider = ConversationContextProvider.get_instance() - return provider.get_conversation_id() diff --git a/src/pipecat/utils/tracing/service_decorators.py b/src/pipecat/utils/tracing/service_decorators.py index 42babd5cd..a4f0d8c37 100644 --- a/src/pipecat/utils/tracing/service_decorators.py +++ b/src/pipecat/utils/tracing/service_decorators.py @@ -25,7 +25,6 @@ if TYPE_CHECKING: from pipecat.processors.aggregators.llm_context import NOT_GIVEN, LLMContext from pipecat.processors.aggregators.openai_llm_context import OpenAILLMContext -from pipecat.utils.tracing.conversation_context_provider import get_current_conversation_context from pipecat.utils.tracing.service_attributes import ( add_gemini_live_span_attributes, add_llm_span_attributes, @@ -34,7 +33,6 @@ from pipecat.utils.tracing.service_attributes import ( add_tts_span_attributes, ) from pipecat.utils.tracing.setup import is_tracing_available -from pipecat.utils.tracing.turn_context_provider import get_current_turn_context if is_tracing_available(): from opentelemetry import context as context_api @@ -76,7 +74,8 @@ def _get_parent_service_context(self): return trace.set_span_in_context(self._span) # Fall back to conversation context if available - conversation_context = get_current_conversation_context() + tracing_ctx = getattr(self, "_tracing_context", None) + conversation_context = tracing_ctx.get_conversation_context() if tracing_ctx else None if conversation_context: return conversation_context @@ -183,7 +182,8 @@ def traced_tts(func: Optional[Callable] = None, *, name: Optional[str] = None) - span_name = "tts" # Get parent context - turn_context = get_current_turn_context() + tracing_ctx = getattr(self, "_tracing_context", None) + turn_context = tracing_ctx.get_turn_context() if tracing_ctx else None parent_context = turn_context or _get_parent_service_context(self) # Create span @@ -290,7 +290,8 @@ def traced_stt(func: Optional[Callable] = None, *, name: Optional[str] = None) - span_name = "stt" # Get the turn context first, then fall back to service context - turn_context = get_current_turn_context() + tracing_ctx = getattr(self, "_tracing_context", None) + turn_context = tracing_ctx.get_turn_context() if tracing_ctx else None parent_context = turn_context or _get_parent_service_context(self) # Create a new span as child of the turn span or service span @@ -372,7 +373,8 @@ def traced_llm(func: Optional[Callable] = None, *, name: Optional[str] = None) - span_name = "llm" # Get the parent context - turn context if available, otherwise service context - turn_context = get_current_turn_context() + tracing_ctx = getattr(self, "_tracing_context", None) + turn_context = tracing_ctx.get_turn_context() if tracing_ctx else None parent_context = turn_context or _get_parent_service_context(self) # Create a new span as child of the turn span or service span @@ -582,7 +584,8 @@ def traced_gemini_live(operation: str) -> Callable: span_name = f"{operation}" # Get the parent context - turn context if available, otherwise service context - turn_context = get_current_turn_context() + tracing_ctx = getattr(self, "_tracing_context", None) + turn_context = tracing_ctx.get_turn_context() if tracing_ctx else None parent_context = turn_context or _get_parent_service_context(self) # Create a new span as child of the turn span or service span @@ -889,7 +892,8 @@ def traced_openai_realtime(operation: str) -> Callable: span_name = f"{operation}" # Get the parent context - turn context if available, otherwise service context - turn_context = get_current_turn_context() + tracing_ctx = getattr(self, "_tracing_context", None) + turn_context = tracing_ctx.get_turn_context() if tracing_ctx else None parent_context = turn_context or _get_parent_service_context(self) # Create a new span as child of the turn span or service span diff --git a/src/pipecat/utils/tracing/tracing_context.py b/src/pipecat/utils/tracing/tracing_context.py new file mode 100644 index 000000000..c84299701 --- /dev/null +++ b/src/pipecat/utils/tracing/tracing_context.py @@ -0,0 +1,109 @@ +# +# Copyright (c) 2024-2026, Daily +# +# SPDX-License-Identifier: BSD 2-Clause License +# + +"""Pipeline-scoped tracing context for OpenTelemetry tracing in Pipecat. + +This module provides a per-pipeline tracing context that holds the current +conversation and turn span contexts. Each PipelineTask creates its own +TracingContext, ensuring concurrent pipelines do not interfere with each other. +""" + +import uuid +from typing import TYPE_CHECKING, Optional + +if TYPE_CHECKING: + from opentelemetry.context import Context + from opentelemetry.trace import SpanContext + +from pipecat.utils.tracing.setup import is_tracing_available + +if is_tracing_available(): + from opentelemetry.context import Context + from opentelemetry.trace import NonRecordingSpan, SpanContext, set_span_in_context + + +class TracingContext: + """Pipeline-scoped tracing context. + + Holds the current conversation and turn span contexts for a single pipeline. + Created by PipelineTask, passed to TurnTraceObserver (writer) and services + (readers) via StartFrame. + """ + + def __init__(self): + """Initialize the tracing context with empty state.""" + self._conversation_context: Optional["Context"] = None + self._turn_context: Optional["Context"] = None + self._conversation_id: Optional[str] = None + + def set_conversation_context( + self, span_context: Optional["SpanContext"], conversation_id: Optional[str] = None + ): + """Set the current conversation context. + + Args: + span_context: The span context for the current conversation or None to clear it. + conversation_id: Optional ID for the conversation. + """ + if not is_tracing_available(): + return + + self._conversation_id = conversation_id + + if span_context: + non_recording_span = NonRecordingSpan(span_context) + self._conversation_context = set_span_in_context(non_recording_span) + else: + self._conversation_context = None + + def get_conversation_context(self) -> Optional["Context"]: + """Get the OpenTelemetry context for the current conversation. + + Returns: + The current conversation context or None if not available. + """ + return self._conversation_context + + def set_turn_context(self, span_context: Optional["SpanContext"]): + """Set the current turn context. + + Args: + span_context: The span context for the current turn or None to clear it. + """ + if not is_tracing_available(): + return + + if span_context: + non_recording_span = NonRecordingSpan(span_context) + self._turn_context = set_span_in_context(non_recording_span) + else: + self._turn_context = None + + def get_turn_context(self) -> Optional["Context"]: + """Get the OpenTelemetry context for the current turn. + + Returns: + The current turn context or None if not available. + """ + return self._turn_context + + @property + def conversation_id(self) -> Optional[str]: + """Get the ID for the current conversation. + + Returns: + The current conversation ID or None if not available. + """ + return self._conversation_id + + @staticmethod + def generate_conversation_id() -> str: + """Generate a new conversation ID. + + Returns: + A new randomly generated UUID string. + """ + return str(uuid.uuid4()) diff --git a/src/pipecat/utils/tracing/turn_context_provider.py b/src/pipecat/utils/tracing/turn_context_provider.py deleted file mode 100644 index edb165561..000000000 --- a/src/pipecat/utils/tracing/turn_context_provider.py +++ /dev/null @@ -1,81 +0,0 @@ -# -# Copyright (c) 2024-2026, Daily -# -# SPDX-License-Identifier: BSD 2-Clause License -# - -"""Turn context provider for OpenTelemetry tracing in Pipecat. - -This module provides a singleton context provider that manages the current -turn's tracing context, allowing services to create child spans that are -properly associated with the conversation turn. -""" - -from typing import TYPE_CHECKING, Optional - -# Import types for type checking only -if TYPE_CHECKING: - from opentelemetry.context import Context - from opentelemetry.trace import SpanContext - -from pipecat.utils.tracing.setup import is_tracing_available - -if is_tracing_available(): - from opentelemetry.context import Context - from opentelemetry.trace import NonRecordingSpan, SpanContext, set_span_in_context - - -class TurnContextProvider: - """Provides access to the current turn's tracing context. - - This is a singleton that services can use to get the current turn's - span context to create child spans. - """ - - _instance = None - _current_turn_context: Optional["Context"] = None - - @classmethod - def get_instance(cls): - """Get the singleton instance. - - Returns: - The singleton TurnContextProvider instance. - """ - if cls._instance is None: - cls._instance = TurnContextProvider() - return cls._instance - - def set_current_turn_context(self, span_context: Optional["SpanContext"]): - """Set the current turn context. - - Args: - span_context: The span context for the current turn or None to clear it. - """ - if not is_tracing_available(): - return - - if span_context: - # Create a non-recording span from the span context - non_recording_span = NonRecordingSpan(span_context) - self._current_turn_context = set_span_in_context(non_recording_span) - else: - self._current_turn_context = None - - def get_current_turn_context(self) -> Optional["Context"]: - """Get the OpenTelemetry context for the current turn. - - Returns: - The current turn context or None if not available. - """ - return self._current_turn_context - - -def get_current_turn_context() -> Optional["Context"]: - """Get the OpenTelemetry context for the current turn. - - Returns: - The current turn context or None if not available. - """ - provider = TurnContextProvider.get_instance() - return provider.get_current_turn_context() diff --git a/src/pipecat/utils/tracing/turn_trace_observer.py b/src/pipecat/utils/tracing/turn_trace_observer.py index 78a9c9ea9..83c2bcdc2 100644 --- a/src/pipecat/utils/tracing/turn_trace_observer.py +++ b/src/pipecat/utils/tracing/turn_trace_observer.py @@ -19,9 +19,8 @@ from pipecat.frames.frames import StartFrame from pipecat.observers.base_observer import BaseObserver, FramePushed from pipecat.observers.turn_tracking_observer import TurnTrackingObserver from pipecat.observers.user_bot_latency_observer import UserBotLatencyObserver -from pipecat.utils.tracing.conversation_context_provider import ConversationContextProvider from pipecat.utils.tracing.setup import is_tracing_available -from pipecat.utils.tracing.turn_context_provider import TurnContextProvider +from pipecat.utils.tracing.tracing_context import TracingContext # Import types for type checking only if TYPE_CHECKING: @@ -49,6 +48,7 @@ class TurnTraceObserver(BaseObserver): latency_tracker: UserBotLatencyObserver, conversation_id: Optional[str] = None, additional_span_attributes: Optional[dict] = None, + tracing_context: Optional[TracingContext] = None, **kwargs, ): """Initialize the turn trace observer. @@ -58,11 +58,13 @@ class TurnTraceObserver(BaseObserver): latency_tracker: The latency tracking observer for user-bot latency. conversation_id: Optional conversation ID for grouping turns. additional_span_attributes: Additional attributes to add to spans. + tracing_context: Pipeline-scoped tracing context for span hierarchy. **kwargs: Additional arguments passed to parent class. """ super().__init__(**kwargs) self._turn_tracker = turn_tracker self._latency_tracker = latency_tracker + self._tracing_context = tracing_context or TracingContext() self._current_span: Optional["Span"] = None self._current_turn_number: int = 0 self._trace_context_map: Dict[int, "SpanContext"] = {} @@ -123,9 +125,8 @@ class TurnTraceObserver(BaseObserver): return # Generate a conversation ID if not provided - context_provider = ConversationContextProvider.get_instance() if conversation_id is None: - conversation_id = context_provider.generate_conversation_id() + conversation_id = TracingContext.generate_conversation_id() logger.debug(f"Generated new conversation ID: {conversation_id}") self._conversation_id = conversation_id @@ -140,8 +141,8 @@ class TurnTraceObserver(BaseObserver): for k, v in (self._additional_span_attributes or {}).items(): self._conversation_span.set_attribute(k, v) - # Update the conversation context provider - context_provider.set_current_conversation_context( + # Update the tracing context + self._tracing_context.set_conversation_context( self._conversation_span.get_span_context(), conversation_id ) @@ -161,9 +162,8 @@ class TurnTraceObserver(BaseObserver): self._current_span.end() self._current_span = None - # Clear the turn context provider - context_provider = TurnContextProvider.get_instance() - context_provider.set_current_turn_context(None) + # Clear the turn context + self._tracing_context.set_turn_context(None) # Now end the conversation span if it exists if self._conversation_span: @@ -171,9 +171,8 @@ class TurnTraceObserver(BaseObserver): self._conversation_span.end() self._conversation_span = None - # Clear the context provider - context_provider = ConversationContextProvider.get_instance() - context_provider.set_current_conversation_context(None) + # Clear the conversation context + self._tracing_context.set_conversation_context(None) logger.debug(f"Ended tracing for Conversation {self._conversation_id}") self._conversation_id = None @@ -189,8 +188,7 @@ class TurnTraceObserver(BaseObserver): # Get the parent context - conversation if available, otherwise use root context parent_context = None if self._conversation_span: - context_provider = ConversationContextProvider.get_instance() - parent_context = context_provider.get_current_conversation_context() + parent_context = self._tracing_context.get_conversation_context() # Create a new span for this turn self._current_span = self._tracer.start_span("turn", context=parent_context) @@ -207,9 +205,8 @@ class TurnTraceObserver(BaseObserver): # Store the span context so services can become children of this span self._trace_context_map[turn_number] = self._current_span.get_span_context() - # Update the context provider so services can access this span - context_provider = TurnContextProvider.get_instance() - context_provider.set_current_turn_context(self._current_span.get_span_context()) + # Update the tracing context so services can access this span + self._tracing_context.set_turn_context(self._current_span.get_span_context()) logger.debug(f"Started tracing for Turn {turn_number}") @@ -228,9 +225,8 @@ class TurnTraceObserver(BaseObserver): self._current_span.end() self._current_span = None - # Clear the context provider - context_provider = TurnContextProvider.get_instance() - context_provider.set_current_turn_context(None) + # Clear the turn context + self._tracing_context.set_turn_context(None) logger.debug(f"Ended tracing for Turn {turn_number}") From 71a752c971d9ef2231b4f3820df8d55d3b7a683d Mon Sep 17 00:00:00 2001 From: Mark Backman Date: Wed, 11 Feb 2026 22:42:58 -0500 Subject: [PATCH 0459/1060] Add tests for TracingContext and TurnTraceObserver Cover pipeline-scoped tracing context lifecycle, span hierarchy, conversation/turn context management, and concurrent pipeline isolation. --- .github/workflows/coverage.yaml | 1 + .github/workflows/tests.yaml | 1 + tests/test_tracing_context.py | 127 ++++++++ tests/test_turn_trace_observer.py | 505 ++++++++++++++++++++++++++++++ 4 files changed, 634 insertions(+) create mode 100644 tests/test_tracing_context.py create mode 100644 tests/test_turn_trace_observer.py diff --git a/.github/workflows/coverage.yaml b/.github/workflows/coverage.yaml index 852611eba..b78067c97 100644 --- a/.github/workflows/coverage.yaml +++ b/.github/workflows/coverage.yaml @@ -41,6 +41,7 @@ jobs: --extra livekit \ --extra local-smart-turn-v3 \ --extra piper \ + --extra tracing \ --extra websocket - name: Run tests with coverage diff --git a/.github/workflows/tests.yaml b/.github/workflows/tests.yaml index 54495911b..5bdfb94f4 100644 --- a/.github/workflows/tests.yaml +++ b/.github/workflows/tests.yaml @@ -45,6 +45,7 @@ jobs: --extra livekit \ --extra local-smart-turn-v3 \ --extra piper \ + --extra tracing \ --extra websocket - name: Test with pytest diff --git a/tests/test_tracing_context.py b/tests/test_tracing_context.py new file mode 100644 index 000000000..06aa34683 --- /dev/null +++ b/tests/test_tracing_context.py @@ -0,0 +1,127 @@ +# +# Copyright (c) 2024-2026, Daily +# +# SPDX-License-Identifier: BSD 2-Clause License +# + +import unittest + +try: + from opentelemetry.sdk.trace import TracerProvider + + HAS_OPENTELEMETRY = True +except ImportError: + HAS_OPENTELEMETRY = False + +from pipecat.utils.tracing.tracing_context import TracingContext + + +@unittest.skipUnless(HAS_OPENTELEMETRY, "opentelemetry not installed") +class TestTracingContext(unittest.TestCase): + """Tests for TracingContext.""" + + @classmethod + def setUpClass(cls): + """Set up a tracer provider for generating span contexts.""" + cls._provider = TracerProvider() + cls._tracer = cls._provider.get_tracer("test") + + def test_initial_state_is_empty(self): + """Test that a new TracingContext starts with no context set.""" + ctx = TracingContext() + self.assertIsNone(ctx.get_conversation_context()) + self.assertIsNone(ctx.get_turn_context()) + self.assertIsNone(ctx.conversation_id) + + def test_set_and_get_conversation_context(self): + """Test setting and retrieving conversation context.""" + ctx = TracingContext() + span = self._tracer.start_span("conv") + span_context = span.get_span_context() + + ctx.set_conversation_context(span_context, "conv-123") + + self.assertIsNotNone(ctx.get_conversation_context()) + self.assertEqual(ctx.conversation_id, "conv-123") + span.end() + + def test_clear_conversation_context(self): + """Test clearing conversation context by passing None.""" + ctx = TracingContext() + span = self._tracer.start_span("conv") + + ctx.set_conversation_context(span.get_span_context(), "conv-123") + self.assertIsNotNone(ctx.get_conversation_context()) + + ctx.set_conversation_context(None) + self.assertIsNone(ctx.get_conversation_context()) + self.assertIsNone(ctx.conversation_id) + span.end() + + def test_set_and_get_turn_context(self): + """Test setting and retrieving turn context.""" + ctx = TracingContext() + span = self._tracer.start_span("turn") + span_context = span.get_span_context() + + ctx.set_turn_context(span_context) + + self.assertIsNotNone(ctx.get_turn_context()) + span.end() + + def test_clear_turn_context(self): + """Test clearing turn context by passing None.""" + ctx = TracingContext() + span = self._tracer.start_span("turn") + + ctx.set_turn_context(span.get_span_context()) + self.assertIsNotNone(ctx.get_turn_context()) + + ctx.set_turn_context(None) + self.assertIsNone(ctx.get_turn_context()) + span.end() + + def test_generate_conversation_id(self): + """Test that generated conversation IDs are unique UUIDs.""" + id1 = TracingContext.generate_conversation_id() + id2 = TracingContext.generate_conversation_id() + self.assertIsInstance(id1, str) + self.assertNotEqual(id1, id2) + + def test_instances_are_isolated(self): + """Test that two TracingContext instances do not share state.""" + ctx_a = TracingContext() + ctx_b = TracingContext() + + span = self._tracer.start_span("turn") + + ctx_a.set_turn_context(span.get_span_context()) + ctx_a.set_conversation_context(span.get_span_context(), "conv-a") + + # ctx_b should still be empty + self.assertIsNone(ctx_b.get_turn_context()) + self.assertIsNone(ctx_b.get_conversation_context()) + self.assertIsNone(ctx_b.conversation_id) + span.end() + + def test_conversation_and_turn_are_independent(self): + """Test that clearing turn context does not affect conversation context.""" + ctx = TracingContext() + conv_span = self._tracer.start_span("conv") + turn_span = self._tracer.start_span("turn") + + ctx.set_conversation_context(conv_span.get_span_context(), "conv-1") + ctx.set_turn_context(turn_span.get_span_context()) + + # Clear turn but conversation should remain + ctx.set_turn_context(None) + self.assertIsNone(ctx.get_turn_context()) + self.assertIsNotNone(ctx.get_conversation_context()) + self.assertEqual(ctx.conversation_id, "conv-1") + + conv_span.end() + turn_span.end() + + +if __name__ == "__main__": + unittest.main() diff --git a/tests/test_turn_trace_observer.py b/tests/test_turn_trace_observer.py new file mode 100644 index 000000000..41ff41b8b --- /dev/null +++ b/tests/test_turn_trace_observer.py @@ -0,0 +1,505 @@ +# +# Copyright (c) 2024-2026, Daily +# +# SPDX-License-Identifier: BSD 2-Clause License +# + +import asyncio +import threading +import unittest + +try: + from opentelemetry.sdk.trace import TracerProvider + from opentelemetry.sdk.trace.export import SimpleSpanProcessor, SpanExporter, SpanExportResult + + HAS_OPENTELEMETRY = True +except ImportError: + HAS_OPENTELEMETRY = False + +from pipecat.frames.frames import ( + BotStartedSpeakingFrame, + BotStoppedSpeakingFrame, + UserStartedSpeakingFrame, + UserStoppedSpeakingFrame, +) +from pipecat.observers.turn_tracking_observer import TurnTrackingObserver +from pipecat.observers.user_bot_latency_observer import UserBotLatencyObserver +from pipecat.processors.filters.identity_filter import IdentityFilter +from pipecat.tests.utils import SleepFrame, run_test +from pipecat.utils.tracing.tracing_context import TracingContext +from pipecat.utils.tracing.turn_trace_observer import TurnTraceObserver + +if HAS_OPENTELEMETRY: + + class _InMemorySpanExporter(SpanExporter): + """Simple in-memory span exporter for testing.""" + + def __init__(self): + """Initialize the exporter.""" + self._spans = [] + self._lock = threading.Lock() + + def export(self, spans): + """Export spans to memory.""" + with self._lock: + self._spans.extend(spans) + return SpanExportResult.SUCCESS + + def get_finished_spans(self): + """Return collected spans.""" + with self._lock: + return list(self._spans) + + def clear(self): + """Clear collected spans.""" + with self._lock: + self._spans.clear() + + +@unittest.skipUnless(HAS_OPENTELEMETRY, "opentelemetry not installed") +class TestTurnTraceObserver(unittest.IsolatedAsyncioTestCase): + """Tests for TurnTraceObserver.""" + + def setUp(self): + """Set up a fresh provider and exporter for each test. + + We create a dedicated TracerProvider per test and inject its tracer + directly into the observer, avoiding the global provider singleton. + """ + self._exporter = _InMemorySpanExporter() + self._provider = TracerProvider() + self._provider.add_span_processor(SimpleSpanProcessor(self._exporter)) + self._tracer = self._provider.get_tracer("pipecat.turn") + + def tearDown(self): + """Shut down the provider to flush spans.""" + self._provider.shutdown() + + def _create_observers(self, conversation_id=None, tracing_context=None): + """Create a standard set of turn/trace observers. + + Args: + conversation_id: Optional conversation ID. + tracing_context: Optional TracingContext instance. + + Returns: + Tuple of (turn_tracker, latency_tracker, trace_observer, tracing_context). + """ + tracing_context = tracing_context or TracingContext() + turn_tracker = TurnTrackingObserver(turn_end_timeout_secs=0.2) + latency_tracker = UserBotLatencyObserver() + trace_observer = TurnTraceObserver( + turn_tracker, + latency_tracker=latency_tracker, + conversation_id=conversation_id, + tracing_context=tracing_context, + ) + # Inject the test tracer so spans go to our in-memory exporter + trace_observer._tracer = self._tracer + return turn_tracker, latency_tracker, trace_observer, tracing_context + + def _all_observers(self, trace_observer): + """Return the list of observers needed for run_test.""" + return [trace_observer._turn_tracker, trace_observer._latency_tracker, trace_observer] + + def _get_spans_by_name(self, name): + """Return finished spans with the given name.""" + return [s for s in self._exporter.get_finished_spans() if s.name == name] + + async def test_conversation_span_created_on_start_frame(self): + """Test that a conversation span is created when StartFrame is observed.""" + _, _, trace_observer, _ = self._create_observers(conversation_id="test-conv") + processor = IdentityFilter() + + frames_to_send = [ + UserStartedSpeakingFrame(), + UserStoppedSpeakingFrame(), + BotStartedSpeakingFrame(), + BotStoppedSpeakingFrame(), + SleepFrame(sleep=0.4), + ] + + expected_down_frames = [ + UserStartedSpeakingFrame, + UserStoppedSpeakingFrame, + BotStartedSpeakingFrame, + BotStoppedSpeakingFrame, + ] + + await run_test( + processor, + frames_to_send=frames_to_send, + expected_down_frames=expected_down_frames, + observers=self._all_observers(trace_observer), + ) + + # End conversation to flush the conversation span (normally done by PipelineTask._cleanup) + trace_observer.end_conversation_tracing() + + conv_spans = self._get_spans_by_name("conversation") + self.assertEqual(len(conv_spans), 1) + self.assertEqual(conv_spans[0].attributes["conversation.id"], "test-conv") + self.assertEqual(conv_spans[0].attributes["conversation.type"], "voice") + + async def test_turn_spans_created_for_each_turn(self): + """Test that a turn span is created for each conversation turn.""" + _, _, trace_observer, _ = self._create_observers() + processor = IdentityFilter() + + frames_to_send = [ + # Turn 1 + UserStartedSpeakingFrame(), + UserStoppedSpeakingFrame(), + BotStartedSpeakingFrame(), + BotStoppedSpeakingFrame(), + SleepFrame(sleep=0.05), + # Turn 2 + UserStartedSpeakingFrame(), + UserStoppedSpeakingFrame(), + BotStartedSpeakingFrame(), + BotStoppedSpeakingFrame(), + SleepFrame(sleep=0.4), + ] + + expected_down_frames = [ + UserStartedSpeakingFrame, + UserStoppedSpeakingFrame, + BotStartedSpeakingFrame, + BotStoppedSpeakingFrame, + UserStartedSpeakingFrame, + UserStoppedSpeakingFrame, + BotStartedSpeakingFrame, + BotStoppedSpeakingFrame, + ] + + await run_test( + processor, + frames_to_send=frames_to_send, + expected_down_frames=expected_down_frames, + observers=self._all_observers(trace_observer), + ) + + turn_spans = self._get_spans_by_name("turn") + self.assertEqual(len(turn_spans), 2) + turn_numbers = {s.attributes["turn.number"] for s in turn_spans} + self.assertEqual(turn_numbers, {1, 2}) + + async def test_turn_spans_are_children_of_conversation(self): + """Test that turn spans are parented under the conversation span.""" + _, _, trace_observer, _ = self._create_observers() + processor = IdentityFilter() + + frames_to_send = [ + UserStartedSpeakingFrame(), + UserStoppedSpeakingFrame(), + BotStartedSpeakingFrame(), + BotStoppedSpeakingFrame(), + SleepFrame(sleep=0.4), + ] + + expected_down_frames = [ + UserStartedSpeakingFrame, + UserStoppedSpeakingFrame, + BotStartedSpeakingFrame, + BotStoppedSpeakingFrame, + ] + + await run_test( + processor, + frames_to_send=frames_to_send, + expected_down_frames=expected_down_frames, + observers=self._all_observers(trace_observer), + ) + + # End conversation to flush the conversation span + trace_observer.end_conversation_tracing() + + conv_spans = self._get_spans_by_name("conversation") + turn_spans = self._get_spans_by_name("turn") + self.assertEqual(len(conv_spans), 1) + self.assertEqual(len(turn_spans), 1) + + # Turn span's parent should be the conversation span + conv_span_id = conv_spans[0].context.span_id + turn_parent_id = turn_spans[0].parent.span_id + self.assertEqual(turn_parent_id, conv_span_id) + + async def test_interrupted_turn_marked(self): + """Test that an interrupted turn span has was_interrupted=True.""" + _, _, trace_observer, _ = self._create_observers() + processor = IdentityFilter() + + frames_to_send = [ + UserStartedSpeakingFrame(), + UserStoppedSpeakingFrame(), + BotStartedSpeakingFrame(), + # User interrupts + UserStartedSpeakingFrame(), + SleepFrame(sleep=0.4), + ] + + expected_down_frames = [ + UserStartedSpeakingFrame, + UserStoppedSpeakingFrame, + BotStartedSpeakingFrame, + UserStartedSpeakingFrame, + ] + + await run_test( + processor, + frames_to_send=frames_to_send, + expected_down_frames=expected_down_frames, + observers=self._all_observers(trace_observer), + ) + + # End conversation to flush remaining spans + trace_observer.end_conversation_tracing() + + turn_spans = self._get_spans_by_name("turn") + self.assertGreaterEqual(len(turn_spans), 1) + # First turn should be interrupted + interrupted_turns = [s for s in turn_spans if s.attributes.get("turn.was_interrupted")] + self.assertGreaterEqual(len(interrupted_turns), 1) + + async def test_tracing_context_updated_during_turn(self): + """Test that TracingContext is populated during a turn and cleared after.""" + tracing_ctx = TracingContext() + _, _, trace_observer, _ = self._create_observers(tracing_context=tracing_ctx) + processor = IdentityFilter() + + frames_to_send = [ + UserStartedSpeakingFrame(), + UserStoppedSpeakingFrame(), + BotStartedSpeakingFrame(), + BotStoppedSpeakingFrame(), + SleepFrame(sleep=0.4), + ] + + expected_down_frames = [ + UserStartedSpeakingFrame, + UserStoppedSpeakingFrame, + BotStartedSpeakingFrame, + BotStoppedSpeakingFrame, + ] + + await run_test( + processor, + frames_to_send=frames_to_send, + expected_down_frames=expected_down_frames, + observers=self._all_observers(trace_observer), + ) + + # After the turn ends, turn context should be cleared + self.assertIsNone(tracing_ctx.get_turn_context()) + + async def test_tracing_context_cleared_after_conversation_end(self): + """Test that TracingContext is cleared when conversation tracing ends.""" + tracing_ctx = TracingContext() + _, _, trace_observer, _ = self._create_observers(tracing_context=tracing_ctx) + processor = IdentityFilter() + + frames_to_send = [ + UserStartedSpeakingFrame(), + UserStoppedSpeakingFrame(), + BotStartedSpeakingFrame(), + BotStoppedSpeakingFrame(), + SleepFrame(sleep=0.4), + ] + + expected_down_frames = [ + UserStartedSpeakingFrame, + UserStoppedSpeakingFrame, + BotStartedSpeakingFrame, + BotStoppedSpeakingFrame, + ] + + await run_test( + processor, + frames_to_send=frames_to_send, + expected_down_frames=expected_down_frames, + observers=self._all_observers(trace_observer), + ) + + # Manually end conversation tracing (as PipelineTask._cleanup does) + trace_observer.end_conversation_tracing() + + self.assertIsNone(tracing_ctx.get_conversation_context()) + self.assertIsNone(tracing_ctx.get_turn_context()) + self.assertIsNone(tracing_ctx.conversation_id) + + async def test_additional_span_attributes(self): + """Test that additional span attributes are added to the conversation span.""" + extra_attrs = {"deployment.id": "abc-123", "customer.tier": "premium"} + tracing_ctx = TracingContext() + turn_tracker = TurnTrackingObserver(turn_end_timeout_secs=0.2) + latency_tracker = UserBotLatencyObserver() + trace_observer = TurnTraceObserver( + turn_tracker, + latency_tracker=latency_tracker, + additional_span_attributes=extra_attrs, + tracing_context=tracing_ctx, + ) + trace_observer._tracer = self._tracer + processor = IdentityFilter() + + frames_to_send = [ + UserStartedSpeakingFrame(), + UserStoppedSpeakingFrame(), + BotStartedSpeakingFrame(), + BotStoppedSpeakingFrame(), + SleepFrame(sleep=0.4), + ] + + expected_down_frames = [ + UserStartedSpeakingFrame, + UserStoppedSpeakingFrame, + BotStartedSpeakingFrame, + BotStoppedSpeakingFrame, + ] + + await run_test( + processor, + frames_to_send=frames_to_send, + expected_down_frames=expected_down_frames, + observers=[turn_tracker, latency_tracker, trace_observer], + ) + + # End conversation to flush the conversation span + trace_observer.end_conversation_tracing() + + conv_spans = self._get_spans_by_name("conversation") + self.assertEqual(len(conv_spans), 1) + self.assertEqual(conv_spans[0].attributes["deployment.id"], "abc-123") + self.assertEqual(conv_spans[0].attributes["customer.tier"], "premium") + + async def test_concurrent_pipelines_are_isolated(self): + """Test that two pipelines with separate TracingContexts don't interfere.""" + tracing_ctx_a = TracingContext() + tracing_ctx_b = TracingContext() + + _, _, trace_observer_a, _ = self._create_observers( + conversation_id="conv-a", tracing_context=tracing_ctx_a + ) + _, _, trace_observer_b, _ = self._create_observers( + conversation_id="conv-b", tracing_context=tracing_ctx_b + ) + + processor_a = IdentityFilter() + processor_b = IdentityFilter() + + frames = [ + UserStartedSpeakingFrame(), + UserStoppedSpeakingFrame(), + BotStartedSpeakingFrame(), + BotStoppedSpeakingFrame(), + SleepFrame(sleep=0.4), + ] + + expected = [ + UserStartedSpeakingFrame, + UserStoppedSpeakingFrame, + BotStartedSpeakingFrame, + BotStoppedSpeakingFrame, + ] + + # Run both pipelines concurrently + await asyncio.gather( + run_test( + processor_a, + frames_to_send=frames, + expected_down_frames=expected, + observers=self._all_observers(trace_observer_a), + ), + run_test( + processor_b, + frames_to_send=frames, + expected_down_frames=expected, + observers=self._all_observers(trace_observer_b), + ), + ) + + # End both conversations to flush spans + trace_observer_a.end_conversation_tracing() + trace_observer_b.end_conversation_tracing() + + # Each TracingContext should have its own conversation ID + conv_spans = self._get_spans_by_name("conversation") + conv_ids = {s.attributes["conversation.id"] for s in conv_spans} + self.assertEqual(conv_ids, {"conv-a", "conv-b"}) + + # Turn spans should be children of their own conversation span, not cross-linked + turn_spans = self._get_spans_by_name("turn") + conv_span_map = {s.context.span_id: s.attributes["conversation.id"] for s in conv_spans} + for turn_span in turn_spans: + parent_id = turn_span.parent.span_id + turn_conv_id = turn_span.attributes["conversation.id"] + parent_conv_id = conv_span_map[parent_id] + self.assertEqual( + turn_conv_id, + parent_conv_id, + f"Turn span for {turn_conv_id} parented under {parent_conv_id}", + ) + + async def test_end_conversation_closes_active_turn(self): + """Test that end_conversation_tracing closes any active turn span.""" + _, _, trace_observer, _ = self._create_observers() + + # Manually start conversation and a turn + trace_observer.start_conversation_tracing("conv-end-test") + await trace_observer._handle_turn_started(1) + + self.assertIsNotNone(trace_observer._current_span) + self.assertIsNotNone(trace_observer._conversation_span) + + # End conversation — should close both turn and conversation + trace_observer.end_conversation_tracing() + + self.assertIsNone(trace_observer._current_span) + self.assertIsNone(trace_observer._conversation_span) + + # Check span attributes + turn_spans = self._get_spans_by_name("turn") + self.assertEqual(len(turn_spans), 1) + self.assertTrue(turn_spans[0].attributes["turn.was_interrupted"]) + self.assertTrue(turn_spans[0].attributes["turn.ended_by_conversation_end"]) + + async def test_conversation_id_auto_generated(self): + """Test that a conversation ID is auto-generated when none is provided.""" + _, _, trace_observer, _ = self._create_observers(conversation_id=None) + processor = IdentityFilter() + + frames_to_send = [ + UserStartedSpeakingFrame(), + UserStoppedSpeakingFrame(), + BotStartedSpeakingFrame(), + BotStoppedSpeakingFrame(), + SleepFrame(sleep=0.4), + ] + + expected_down_frames = [ + UserStartedSpeakingFrame, + UserStoppedSpeakingFrame, + BotStartedSpeakingFrame, + BotStoppedSpeakingFrame, + ] + + await run_test( + processor, + frames_to_send=frames_to_send, + expected_down_frames=expected_down_frames, + observers=self._all_observers(trace_observer), + ) + + # End conversation to flush the conversation span + trace_observer.end_conversation_tracing() + + conv_spans = self._get_spans_by_name("conversation") + self.assertEqual(len(conv_spans), 1) + # Should have an auto-generated UUID as conversation.id + conv_id = conv_spans[0].attributes["conversation.id"] + self.assertIsNotNone(conv_id) + self.assertGreater(len(conv_id), 0) + + +if __name__ == "__main__": + unittest.main() From 0bf2477d2ca53bb551aa730bc55f21641834df8c Mon Sep 17 00:00:00 2001 From: Mark Backman Date: Thu, 12 Feb 2026 09:41:18 -0500 Subject: [PATCH 0460/1060] Bump Pillow upper bound from <12 to <13 --- 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name = "pillow", specifier = ">=11.1.0,<12" }, + { name = "pillow", specifier = ">=11.1.0,<13" }, { name = "pipecat-ai", extras = ["local-smart-turn-v3"] }, { name = "pipecat-ai", extras = ["nvidia"], marker = "extra == 'riva'" }, { name = "pipecat-ai", extras = ["websockets-base"], marker = "extra == 'assemblyai'" }, From 4667a3d66d5774c823bf87ec3664c4fde0682e33 Mon Sep 17 00:00:00 2001 From: Mark Backman Date: Thu, 12 Feb 2026 09:42:23 -0500 Subject: [PATCH 0461/1060] Add changelog for #3728 --- changelog/3728.changed.md | 1 + 1 file changed, 1 insertion(+) create mode 100644 changelog/3728.changed.md diff --git a/changelog/3728.changed.md b/changelog/3728.changed.md new file mode 100644 index 000000000..bc5ccc74d --- /dev/null +++ b/changelog/3728.changed.md @@ -0,0 +1 @@ +- Bumped Pillow dependency upper bound from `<12` to `<13` to allow Pillow 12.x. From 6d95a2425ca30f775d1da2f15a7546cfff0b30a6 Mon Sep 17 00:00:00 2001 From: filipi87 Date: Thu, 12 Feb 2026 12:54:47 -0300 Subject: [PATCH 0462/1060] Fixing ElevenLabs TTS word timestamp interleaving across sentences. --- src/pipecat/services/elevenlabs/tts.py | 56 ++++++++++++++++---------- 1 file changed, 34 insertions(+), 22 deletions(-) diff --git a/src/pipecat/services/elevenlabs/tts.py b/src/pipecat/services/elevenlabs/tts.py index 4dab0c01a..7df891f0e 100644 --- a/src/pipecat/services/elevenlabs/tts.py +++ b/src/pipecat/services/elevenlabs/tts.py @@ -13,6 +13,7 @@ with support for streaming audio, word timestamps, and voice customization. import asyncio import base64 import json +import uuid from typing import Any, AsyncGenerator, Dict, List, Literal, Mapping, Optional, Tuple, Union import aiohttp @@ -680,6 +681,20 @@ class ElevenLabsTTSService(AudioContextWordTTSService): msg = {"text": text, "context_id": self._context_id} await self._websocket.send(json.dumps(msg)) + def create_context_id(self) -> str: + """Generate a unique context ID for a TTS request in case we don't have one already in progress. + + Returns: + A unique string identifier for the TTS context. + """ + # If a context ID does not exist, create a new one. + # If an ID exists, continue using the current ID. + # When interruptions happens, user speech results in + # an interruption, which resets the context ID. + if not self._context_id: + return str(uuid.uuid4()) + return self._context_id + @traced_tts async def run_tts(self, text: str, context_id: str) -> AsyncGenerator[Frame, None]: """Generate speech from text using ElevenLabs' streaming WebSocket API. @@ -698,31 +713,28 @@ class ElevenLabsTTSService(AudioContextWordTTSService): await self._connect() try: - await self.start_ttfb_metrics() - yield TTSStartedFrame(context_id=context_id) - self._cumulative_time = 0 - self._partial_word = "" - self._partial_word_start_time = 0.0 - # If a context ID does not exist, use the provided one. - # If an ID exists, that means the Pipeline doesn't allow - # user interruptions, so continue using the current ID. - # When interruptions are allowed, user speech results in - # an interruption, which resets the context ID. if not self._context_id: + await self.start_ttfb_metrics() + yield TTSStartedFrame(context_id=context_id) self._context_id = context_id - if not self.audio_context_available(self._context_id): - await self.create_audio_context(self._context_id) + self._cumulative_time = 0 + self._partial_word = "" + self._partial_word_start_time = 0.0 - # Initialize context with voice settings and pronunciation dictionaries - msg = {"text": " ", "context_id": self._context_id} - if self._voice_settings: - msg["voice_settings"] = self._voice_settings - if self._pronunciation_dictionary_locators: - msg["pronunciation_dictionary_locators"] = [ - locator.model_dump() for locator in self._pronunciation_dictionary_locators - ] - await self._websocket.send(json.dumps(msg)) - logger.trace(f"Created new context {self._context_id}") + if not self.audio_context_available(self._context_id): + await self.create_audio_context(self._context_id) + + # Initialize context with voice settings and pronunciation dictionaries + msg = {"text": " ", "context_id": self._context_id} + if self._voice_settings: + msg["voice_settings"] = self._voice_settings + if self._pronunciation_dictionary_locators: + msg["pronunciation_dictionary_locators"] = [ + locator.model_dump() + for locator in self._pronunciation_dictionary_locators + ] + await self._websocket.send(json.dumps(msg)) + logger.trace(f"Created new context {self._context_id}") await self._send_text(text) await self.start_tts_usage_metrics(text) From 2e15b4842cf6f36338b867c79a861622d1dbee52 Mon Sep 17 00:00:00 2001 From: Mark Backman Date: Thu, 12 Feb 2026 11:09:39 -0500 Subject: [PATCH 0463/1060] Move STT keepalive mechanism from WebsocketSTTService to STTService base class This allows non-websocket STT services (like SarvamSTTService, which uses the Sarvam Python SDK for connection management) to reuse the same keepalive pattern. Subclasses override _send_keepalive() and _is_keepalive_ready() for their specific protocol. --- src/pipecat/services/sarvam/stt.py | 43 +++++++- src/pipecat/services/stt_service.py | 153 ++++++++++++++++------------ 2 files changed, 132 insertions(+), 64 deletions(-) diff --git a/src/pipecat/services/sarvam/stt.py b/src/pipecat/services/sarvam/stt.py index 998597956..aae1ae243 100644 --- a/src/pipecat/services/sarvam/stt.py +++ b/src/pipecat/services/sarvam/stt.py @@ -167,6 +167,8 @@ class SarvamSTTService(STTService): input_audio_codec: str = "wav", params: Optional[InputParams] = None, ttfs_p99_latency: Optional[float] = SARVAM_TTFS_P99, + keepalive_timeout: Optional[float] = None, + keepalive_interval: float = 5.0, **kwargs, ): """Initialize the Sarvam STT service. @@ -182,6 +184,9 @@ class SarvamSTTService(STTService): params: Configuration parameters for Sarvam STT service. ttfs_p99_latency: P99 latency from speech end to final transcript in seconds. Override for your deployment. See https://github.com/pipecat-ai/stt-benchmark + keepalive_timeout: Seconds of no audio before sending silence to keep the + connection alive. None disables keepalive. + keepalive_interval: Seconds between idle checks when keepalive is enabled. **kwargs: Additional arguments passed to the parent STTService. """ params = params or SarvamSTTService.InputParams() @@ -203,7 +208,13 @@ class SarvamSTTService(STTService): f"Model '{model}' does not support language parameter (auto-detects language)." ) - super().__init__(sample_rate=sample_rate, ttfs_p99_latency=ttfs_p99_latency, **kwargs) + super().__init__( + sample_rate=sample_rate, + ttfs_p99_latency=ttfs_p99_latency, + keepalive_timeout=keepalive_timeout, + keepalive_interval=keepalive_interval, + **kwargs, + ) self.set_model_name(model) self._api_key = api_key @@ -463,6 +474,8 @@ class SarvamSTTService(STTService): # Start receive task using Pipecat's task management self._receive_task = self.create_task(self._receive_task_handler()) + self._create_keepalive_task() + logger.info("Connected to Sarvam successfully") except ApiError as e: @@ -476,6 +489,8 @@ class SarvamSTTService(STTService): async def _disconnect(self): """Disconnect from Sarvam WebSocket API using SDK.""" + await self._cancel_keepalive_task() + if self._receive_task: await self.cancel_task(self._receive_task) self._receive_task = None @@ -600,6 +615,32 @@ class SarvamSTTService(STTService): } return mapping.get(language_code, Language.HI_IN) + def _is_keepalive_ready(self) -> bool: + """Check if the Sarvam SDK websocket client is connected.""" + return self._socket_client is not None + + async def _send_keepalive(self, silence: bytes): + """Send silent audio via the Sarvam SDK to keep the connection alive. + + Args: + silence: Silent 16-bit mono PCM audio bytes. + """ + audio_base64 = base64.b64encode(silence).decode("utf-8") + encoding = ( + self._input_audio_codec + if self._input_audio_codec.startswith("audio/") + else f"audio/{self._input_audio_codec}" + ) + method_kwargs = { + "audio": audio_base64, + "encoding": encoding, + "sample_rate": self.sample_rate, + } + if self._config.use_translate_method: + await self._socket_client.translate(**method_kwargs) + else: + await self._socket_client.transcribe(**method_kwargs) + async def _start_metrics(self): """Start processing metrics collection.""" await self.start_processing_metrics() diff --git a/src/pipecat/services/stt_service.py b/src/pipecat/services/stt_service.py index b556bb23a..50af598b1 100644 --- a/src/pipecat/services/stt_service.py +++ b/src/pipecat/services/stt_service.py @@ -49,6 +49,12 @@ class STTService(AIService): muting, settings management, and audio processing. Subclasses must implement the run_stt method to provide actual speech recognition. + Includes an optional keepalive mechanism that sends silent audio when no real + audio has been sent for a configurable timeout, preventing servers from closing + idle connections (e.g. when behind a ServiceSwitcher). Subclasses that enable + keepalive must override ``_send_keepalive()`` to deliver the silence in the + appropriate service-specific protocol. + Event handlers: on_connected: Called when connected to the STT service. on_disconnected: Called when disconnected from the STT service. @@ -76,6 +82,8 @@ class STTService(AIService): sample_rate: Optional[int] = None, stt_ttfb_timeout: float = 2.0, ttfs_p99_latency: Optional[float] = None, + keepalive_timeout: Optional[float] = None, + keepalive_interval: float = 5.0, **kwargs, ): """Initialize the STT service. @@ -95,6 +103,10 @@ class STTService(AIService): This is broadcast via STTMetadataFrame at pipeline start for downstream processors (e.g., turn strategies) to optimize timing. Subclasses provide measured defaults; pass a value here to override for your deployment. + keepalive_timeout: Seconds of no audio before sending silence to keep the + connection alive. None disables keepalive. Useful for services that + close idle connections (e.g. behind a ServiceSwitcher). + keepalive_interval: Seconds between idle checks when keepalive is enabled. **kwargs: Additional arguments passed to the parent AIService. """ super().__init__(**kwargs) @@ -116,6 +128,12 @@ class STTService(AIService): self._finalize_pending: bool = False self._finalize_requested: bool = False + # Keepalive state + self._keepalive_timeout = keepalive_timeout + self._keepalive_interval = keepalive_interval + self._keepalive_task: Optional[asyncio.Task] = None + self._last_audio_time: float = 0 + self._register_event_handler("on_connected") self._register_event_handler("on_disconnected") self._register_event_handler("on_connection_error") @@ -208,6 +226,7 @@ class STTService(AIService): """Clean up STT service resources.""" await super().cleanup() await self._cancel_ttfb_timeout() + await self._cancel_keepalive_task() async def _update_settings(self, settings: Mapping[str, Any]): logger.info(f"Updating STT settings: {self._settings}") @@ -239,6 +258,8 @@ class STTService(AIService): if self._muted: return + self._last_audio_time = time.monotonic() + # UserAudioRawFrame contains a user_id (e.g. Daily, Livekit) if hasattr(frame, "user_id"): self._user_id = frame.user_id @@ -436,6 +457,66 @@ class STTService(AIService): ) await super().push_frame(MetricsFrame(data=[ttfb_data])) + def _create_keepalive_task(self): + """Start the keepalive task if keepalive is enabled.""" + if self._keepalive_timeout is not None: + self._last_audio_time = time.monotonic() + self._keepalive_task = self.create_task( + self._keepalive_task_handler(), name="keepalive" + ) + + async def _cancel_keepalive_task(self): + """Stop the keepalive task if running.""" + if self._keepalive_task: + await self.cancel_task(self._keepalive_task) + self._keepalive_task = None + + async def _keepalive_task_handler(self): + """Send periodic silent audio to prevent the server from closing the connection. + + When keepalive is enabled, this task checks periodically if the connection + has been idle (no audio sent) for longer than keepalive_timeout seconds. + If so, it generates silent 16-bit mono PCM audio and passes it to + _send_keepalive() for service-specific formatting and sending. + """ + while True: + await asyncio.sleep(self._keepalive_interval) + try: + if not self._is_keepalive_ready(): + continue + elapsed = time.monotonic() - self._last_audio_time + if elapsed < self._keepalive_timeout: + continue + num_samples = int(self.sample_rate * _KEEPALIVE_SILENCE_DURATION) + silence = b"\x00" * (num_samples * 2) + await self._send_keepalive(silence) + self._last_audio_time = time.monotonic() + logger.trace(f"{self} sent keepalive silence") + except Exception as e: + logger.warning(f"{self} keepalive error: {e}") + break + + def _is_keepalive_ready(self) -> bool: + """Check if the service is ready to send keepalive. + + Subclasses should override this to check their connection state. + + Returns: + True if keepalive can be sent. + """ + return True + + async def _send_keepalive(self, silence: bytes): + """Send silent audio to keep the connection alive. + + Subclasses that enable keepalive must override this to deliver silence + in their service-specific protocol. + + Args: + silence: Silent 16-bit mono PCM audio bytes. + """ + raise NotImplementedError("Subclasses must override _send_keepalive") + class SegmentedSTTService(STTService): """STT service that processes speech in segments using VAD events. @@ -549,46 +630,27 @@ class WebsocketSTTService(STTService, WebsocketService): Combines STT functionality with websocket connectivity, providing automatic error handling, reconnection capabilities, and optional silence-based keepalive. - The keepalive feature sends silent audio when no real audio has been sent for - a configurable timeout, preventing servers from closing idle connections (e.g. - when behind a ServiceSwitcher). Subclasses can override ``_send_keepalive()`` - to wrap the silence in a service-specific protocol. + The keepalive feature (inherited from STTService) sends silent audio when no + real audio has been sent for a configurable timeout, preventing servers from + closing idle connections (e.g. when behind a ServiceSwitcher). Subclasses can + override ``_send_keepalive()`` to wrap the silence in a service-specific protocol. """ def __init__( self, *, reconnect_on_error: bool = True, - keepalive_timeout: Optional[float] = None, - keepalive_interval: float = 5.0, **kwargs, ): """Initialize the Websocket STT service. Args: reconnect_on_error: Whether to automatically reconnect on websocket errors. - keepalive_timeout: Seconds of no audio before sending silence to keep the - connection alive. None disables keepalive. Useful for services that - close idle connections (e.g. behind a ServiceSwitcher). - keepalive_interval: Seconds between idle checks when keepalive is enabled. - **kwargs: Additional arguments passed to parent classes. + **kwargs: Additional arguments passed to parent classes (including + keepalive_timeout and keepalive_interval for STTService). """ STTService.__init__(self, **kwargs) WebsocketService.__init__(self, reconnect_on_error=reconnect_on_error, **kwargs) - self._keepalive_timeout = keepalive_timeout - self._keepalive_interval = keepalive_interval - self._keepalive_task: Optional[asyncio.Task] = None - self._last_audio_time: float = 0 - - async def process_audio_frame(self, frame: AudioRawFrame, direction: FrameDirection): - """Process an audio frame, tracking the last audio time for keepalive. - - Args: - frame: The audio frame to process. - direction: The direction of frame processing. - """ - self._last_audio_time = time.monotonic() - await super().process_audio_frame(frame, direction) async def _connect(self): """Connect and start keepalive task if enabled.""" @@ -612,44 +674,9 @@ class WebsocketSTTService(STTService, WebsocketService): self._create_keepalive_task() return result - def _create_keepalive_task(self): - """Start the keepalive task if keepalive is enabled.""" - if self._keepalive_timeout is not None: - self._last_audio_time = time.monotonic() - self._keepalive_task = self.create_task( - self._keepalive_task_handler(), name="keepalive" - ) - - async def _cancel_keepalive_task(self): - """Stop the keepalive task if running.""" - if self._keepalive_task: - await self.cancel_task(self._keepalive_task) - self._keepalive_task = None - - async def _keepalive_task_handler(self): - """Send periodic silent audio to prevent the server from closing the connection. - - When keepalive is enabled, this task checks periodically if the connection - has been idle (no audio sent) for longer than keepalive_timeout seconds. - If so, it generates silent 16-bit mono PCM audio and passes it to - _send_keepalive() for service-specific formatting and sending. - """ - while True: - await asyncio.sleep(self._keepalive_interval) - try: - if not self._websocket or self._websocket.state is not State.OPEN: - continue - elapsed = time.monotonic() - self._last_audio_time - if elapsed < self._keepalive_timeout: - continue - num_samples = int(self.sample_rate * _KEEPALIVE_SILENCE_DURATION) - silence = b"\x00" * (num_samples * 2) - await self._send_keepalive(silence) - self._last_audio_time = time.monotonic() - logger.trace(f"{self} sent keepalive silence") - except Exception as e: - logger.warning(f"{self} keepalive error: {e}") - break + def _is_keepalive_ready(self) -> bool: + """Check if the websocket is open and ready for keepalive.""" + return self._websocket is not None and self._websocket.state is State.OPEN async def _send_keepalive(self, silence: bytes): """Send silent audio over the websocket to keep the connection alive. From 08beb0264acf4b6b1553d294a9e98d0de20cb76a Mon Sep 17 00:00:00 2001 From: Mark Backman Date: Thu, 12 Feb 2026 13:14:11 -0500 Subject: [PATCH 0464/1060] Add changelog entries for PR #3730 --- changelog/3730.added.md | 1 + changelog/3730.changed.md | 1 + 2 files changed, 2 insertions(+) create mode 100644 changelog/3730.added.md create mode 100644 changelog/3730.changed.md diff --git a/changelog/3730.added.md b/changelog/3730.added.md new file mode 100644 index 000000000..e3ac64278 --- /dev/null +++ b/changelog/3730.added.md @@ -0,0 +1 @@ +- Added keepalive support to `SarvamSTTService` to prevent idle connection timeouts (e.g. when used behind a `ServiceSwitcher`). diff --git a/changelog/3730.changed.md b/changelog/3730.changed.md new file mode 100644 index 000000000..697bc863c --- /dev/null +++ b/changelog/3730.changed.md @@ -0,0 +1 @@ +- Moved STT keepalive mechanism from `WebsocketSTTService` to the `STTService` base class, allowing any STT service (not just websocket-based ones) to use idle-connection keepalive via the `keepalive_timeout` and `keepalive_interval` parameters. From abea22ec574a379f90f6858c10580243f90cf2f1 Mon Sep 17 00:00:00 2001 From: filipi87 Date: Thu, 12 Feb 2026 15:17:47 -0300 Subject: [PATCH 0465/1060] Fixing AsyncAITTSService to reuse the same context when needed. --- src/pipecat/services/asyncai/tts.py | 26 +++++++++++++++++++++----- 1 file changed, 21 insertions(+), 5 deletions(-) diff --git a/src/pipecat/services/asyncai/tts.py b/src/pipecat/services/asyncai/tts.py index 4ff6c928d..e9170f8b6 100644 --- a/src/pipecat/services/asyncai/tts.py +++ b/src/pipecat/services/asyncai/tts.py @@ -9,6 +9,7 @@ import asyncio import base64 import json +import uuid from typing import AsyncGenerator, Optional import aiohttp @@ -270,6 +271,20 @@ class AsyncAITTSService(AudioContextTTSService): return self._websocket raise Exception("Websocket not connected") + def create_context_id(self) -> str: + """Generate a unique context ID for a TTS request in case we don't have one already in progress. + + Returns: + A unique string identifier for the TTS context. + """ + # If a context ID does not exist, create a new one. + # If an ID exists, continue using the current ID. + # When interruptions happen, user speech results in + # an interruption, which resets the context ID. + if not self._context_id: + return str(uuid.uuid4()) + return self._context_id + async def flush_audio(self): """Flush any pending audio.""" if not self._context_id or not self._websocket: @@ -379,13 +394,14 @@ class AsyncAITTSService(AudioContextTTSService): await self._connect() try: - await self.start_ttfb_metrics() - yield TTSStartedFrame(context_id=context_id) - if not self._context_id: + await self.start_ttfb_metrics() + yield TTSStartedFrame(context_id=context_id) + self._context_id = context_id - if not self.audio_context_available(self._context_id): - await self.create_audio_context(self._context_id) + + if not self.audio_context_available(self._context_id): + await self.create_audio_context(self._context_id) msg = self._build_msg(text=text, force=True, context_id=self._context_id) await self._get_websocket().send(msg) From 794811fbdbce6f5efc2a8d376198f7a2e4063966 Mon Sep 17 00:00:00 2001 From: Chad Bailey Date: Wed, 4 Feb 2026 22:21:10 +0000 Subject: [PATCH 0466/1060] Updated WSS endpoint for Rime Arcana v3 support --- src/pipecat/services/rime/tts.py | 18 ++++++++---------- 1 file changed, 8 insertions(+), 10 deletions(-) diff --git a/src/pipecat/services/rime/tts.py b/src/pipecat/services/rime/tts.py index e38e840e6..a1b9f8c58 100644 --- a/src/pipecat/services/rime/tts.py +++ b/src/pipecat/services/rime/tts.py @@ -98,8 +98,8 @@ class RimeTTSService(AudioContextWordTTSService): *, api_key: str, voice_id: str, - url: str = "wss://users.rime.ai/ws2", - model: str = "mistv2", + url: str = "wss://users-ws.rime.ai/ws3", + model: str = "arcana", sample_rate: Optional[int] = None, params: Optional[InputParams] = None, text_aggregator: Optional[BaseTextAggregator] = None, @@ -383,7 +383,7 @@ class RimeTTSService(AudioContextWordTTSService): async for message in self._get_websocket(): msg = json.loads(message) - if not msg or not self.audio_context_available(msg["contextId"]): + if not msg or not self.audio_context_available(msg.get("contextId")): continue context_id = msg["contextId"] @@ -626,20 +626,18 @@ class RimeHttpTTSService(TTSService): class RimeNonJsonTTSService(InterruptibleTTSService): """Pipecat TTS service for Rime's non-JSON WebSocket API. + .. deprecated:: 0.0.102 + Arcana now supports JSON WebSocket with word-level timestamps via the + ``wss://users-ws.rime.ai/ws3`` endpoint. Use :class:`RimeTTSService` + with ``model="arcana"`` instead. + This service enables Text-to-Speech synthesis over WebSocket endpoints that require plain text (not JSON) messages and return raw audio bytes. - It is designed for use with TTS models like Arcana, which currently do - not support JSON-based WebSocket protocols (though this may change in - the future). Limitations: - Does not support word-level timestamps or context IDs. - Intended specifically for integrations where the TTS provider only accepts and returns non-JSON messages. - - Note: - - Arcana and similar models may add JSON WebSocket support in the - future. This service focuses on the current plain text protocol. """ class InputParams(BaseModel): From 3410eb82b37803e84576112e7ab9d88a48cdf91b Mon Sep 17 00:00:00 2001 From: filipi87 Date: Thu, 12 Feb 2026 15:26:49 -0300 Subject: [PATCH 0467/1060] Fixing CartesiaTTSService to reuse the same context when needed. --- src/pipecat/services/cartesia/tts.py | 15 +++++++++++++++ 1 file changed, 15 insertions(+) diff --git a/src/pipecat/services/cartesia/tts.py b/src/pipecat/services/cartesia/tts.py index 791c60a18..1fa9a026a 100644 --- a/src/pipecat/services/cartesia/tts.py +++ b/src/pipecat/services/cartesia/tts.py @@ -8,6 +8,7 @@ import base64 import json +import uuid import warnings from enum import Enum from typing import AsyncGenerator, List, Literal, Optional @@ -539,6 +540,20 @@ class CartesiaTTSService(AudioContextWordTTSService): await self._get_websocket().send(cancel_msg) self._context_id = None + def create_context_id(self) -> str: + """Generate a unique context ID for a TTS request in case we don't have one already in progress. + + Returns: + A unique string identifier for the TTS context. + """ + # If a context ID does not exist, create a new one. + # If an ID exists, continue using the current ID. + # When interruptions happen, user speech results in + # an interruption, which resets the context ID. + if not self._context_id: + return str(uuid.uuid4()) + return self._context_id + async def flush_audio(self): """Flush any pending audio and finalize the current context.""" if not self._context_id or not self._websocket: From 136732afae720857f80a849f8b6221836d2481ac Mon Sep 17 00:00:00 2001 From: filipi87 Date: Thu, 12 Feb 2026 15:46:59 -0300 Subject: [PATCH 0468/1060] Fixing InworldTTSService to reuse the same context when needed. --- src/pipecat/services/inworld/tts.py | 19 ++++++++++++++++--- 1 file changed, 16 insertions(+), 3 deletions(-) diff --git a/src/pipecat/services/inworld/tts.py b/src/pipecat/services/inworld/tts.py index 7ba7d6b9d..845a37bdd 100644 --- a/src/pipecat/services/inworld/tts.py +++ b/src/pipecat/services/inworld/tts.py @@ -924,6 +924,20 @@ class InworldTTSService(AudioContextWordTTSService): msg = {"close_context": {}, "contextId": context_id} await self.send_with_retry(json.dumps(msg), self._report_error) + def create_context_id(self) -> str: + """Generate a unique context ID for a TTS request in case we don't have one already in progress. + + Returns: + A unique string identifier for the TTS context. + """ + # If a context ID does not exist, create a new one. + # If an ID exists, continue using the current ID. + # When interruptions happen, user speech results in + # an interruption, which resets the context ID. + if not self._context_id: + return str(uuid.uuid4()) + return self._context_id + @traced_tts async def run_tts(self, text: str, context_id: str) -> AsyncGenerator[Frame, None]: """Generate TTS audio for the given text using the Inworld WebSocket TTS service. @@ -942,10 +956,9 @@ class InworldTTSService(AudioContextWordTTSService): await self._connect() try: - await self.start_ttfb_metrics() - yield TTSStartedFrame(context_id=context_id) - if not self._context_id: + await self.start_ttfb_metrics() + yield TTSStartedFrame(context_id=context_id) self._context_id = context_id logger.trace(f"{self}: Creating new context {self._context_id}") await self.create_audio_context(self._context_id) From f0995164d9ae8550422dde7afc950ff8c92ab6e8 Mon Sep 17 00:00:00 2001 From: filipi87 Date: Thu, 12 Feb 2026 15:50:18 -0300 Subject: [PATCH 0469/1060] Fixing PlayHTTTSService to reuse the same context when needed. --- src/pipecat/services/playht/tts.py | 15 +++++++++++++++ 1 file changed, 15 insertions(+) diff --git a/src/pipecat/services/playht/tts.py b/src/pipecat/services/playht/tts.py index 2d4cd0427..287463186 100644 --- a/src/pipecat/services/playht/tts.py +++ b/src/pipecat/services/playht/tts.py @@ -13,6 +13,7 @@ supporting both WebSocket streaming and HTTP-based synthesis. import io import json import struct +import uuid import warnings from typing import AsyncGenerator, Optional @@ -323,6 +324,20 @@ class PlayHTTTSService(InterruptibleTTSService): return self._websocket raise Exception("Websocket not connected") + def create_context_id(self) -> str: + """Generate a unique context ID for a TTS request in case we don't have one already in progress. + + Returns: + A unique string identifier for the TTS context. + """ + # If a context ID does not exist, create a new one. + # If an ID exists, continue using the current ID. + # When interruptions happen, user speech results in + # an interruption, which resets the context ID. + if not self._context_id: + return str(uuid.uuid4()) + return self._context_id + async def _handle_interruption(self, frame: InterruptionFrame, direction: FrameDirection): """Handle interruption by stopping metrics and clearing request ID.""" await super()._handle_interruption(frame, direction) From 8866ab1585e257d8f880b71bd46b0ad4091e98ab Mon Sep 17 00:00:00 2001 From: filipi87 Date: Thu, 12 Feb 2026 15:53:38 -0300 Subject: [PATCH 0470/1060] Fixing RimeTTSService to reuse the same context when needed. --- src/pipecat/services/rime/tts.py | 15 +++++++++++++++ 1 file changed, 15 insertions(+) diff --git a/src/pipecat/services/rime/tts.py b/src/pipecat/services/rime/tts.py index e38e840e6..22f1cf4e1 100644 --- a/src/pipecat/services/rime/tts.py +++ b/src/pipecat/services/rime/tts.py @@ -12,6 +12,7 @@ using Rime's API for streaming and batch audio synthesis. import base64 import json +import uuid from typing import Any, AsyncGenerator, Mapping, Optional import aiohttp @@ -369,6 +370,20 @@ class RimeTTSService(AudioContextWordTTSService): return word_pairs + def create_context_id(self) -> str: + """Generate a unique context ID for a TTS request in case we don't have one already in progress. + + Returns: + A unique string identifier for the TTS context. + """ + # If a context ID does not exist, create a new one. + # If an ID exists, continue using the current ID. + # When interruptions happen, user speech results in + # an interruption, which resets the context ID. + if not self._context_id: + return str(uuid.uuid4()) + return self._context_id + async def flush_audio(self): """Flush any pending audio synthesis.""" if not self._context_id or not self._websocket: From 2b9777b812e8cdb77d13760aebc32726f75db2f2 Mon Sep 17 00:00:00 2001 From: Mark Backman Date: Thu, 12 Feb 2026 14:01:41 -0500 Subject: [PATCH 0471/1060] Update RimeTTSService InputParams for arcana and mistv2 model support Add model-specific params (arcana: repetition_penalty, temperature, top_p; mistv2: no_text_normalization, save_oovs, segment) with dynamic query param building via _build_settings(). Model/voice/param changes now trigger WebSocket reconnection since all settings are URL query params. Co-Authored-By: Claude Opus 4.6 --- .../foundational/07q-interruptible-rime.py | 9 +- src/pipecat/services/rime/tts.py | 162 ++++++++++++++---- 2 files changed, 141 insertions(+), 30 deletions(-) diff --git a/examples/foundational/07q-interruptible-rime.py b/examples/foundational/07q-interruptible-rime.py index 1042d05ee..d381c33dc 100644 --- a/examples/foundational/07q-interruptible-rime.py +++ b/examples/foundational/07q-interruptible-rime.py @@ -25,6 +25,7 @@ from pipecat.runner.utils import create_transport from pipecat.services.deepgram.stt import DeepgramSTTService from pipecat.services.openai.llm import OpenAILLMService from pipecat.services.rime.tts import RimeTTSService +from pipecat.transcriptions.language import Language from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams @@ -56,7 +57,13 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): tts = RimeTTSService( api_key=os.getenv("RIME_API_KEY", ""), - voice_id="rex", + voice_id="luna", + params=RimeTTSService.InputParams( + language=Language.EN, + repetition_penalty=1.0, + temperature=0.5, + top_p=0.9, + ), ) llm = OpenAILLMService(api_key=os.getenv("OPENAI_API_KEY")) diff --git a/src/pipecat/services/rime/tts.py b/src/pipecat/services/rime/tts.py index a1b9f8c58..d8574c75f 100644 --- a/src/pipecat/services/rime/tts.py +++ b/src/pipecat/services/rime/tts.py @@ -81,17 +81,31 @@ class RimeTTSService(AudioContextWordTTSService): Parameters: language: Language for synthesis. Defaults to English. - speed_alpha: Speech speed multiplier. Defaults to 1.0. - reduce_latency: Whether to reduce latency at potential quality cost. - pause_between_brackets: Whether to add pauses between bracketed content. - phonemize_between_brackets: Whether to phonemize bracketed content. + segment: Text segmentation mode ("immediate", "bySentence", "never"). + repetition_penalty: Token repetition penalty (arcana only). + temperature: Sampling temperature (arcana only). + top_p: Cumulative probability threshold (arcana only). + speed_alpha: Speech speed multiplier (mistv2 only). + reduce_latency: Whether to reduce latency at potential quality cost (mistv2 only). + pause_between_brackets: Whether to add pauses between bracketed content (mistv2 only). + phonemize_between_brackets: Whether to phonemize bracketed content (mistv2 only). + no_text_normalization: Whether to disable text normalization (mistv2 only). + save_oovs: Whether to save out-of-vocabulary words (mistv2 only). """ language: Optional[Language] = Language.EN - speed_alpha: Optional[float] = 1.0 - reduce_latency: Optional[bool] = False - pause_between_brackets: Optional[bool] = False - phonemize_between_brackets: Optional[bool] = False + segment: Optional[str] = None + # Arcana params + repetition_penalty: Optional[float] = None + temperature: Optional[float] = None + top_p: Optional[float] = None + # Mistv2 params + speed_alpha: Optional[float] = None + reduce_latency: Optional[bool] = None + pause_between_brackets: Optional[bool] = None + phonemize_between_brackets: Optional[bool] = None + no_text_normalization: Optional[bool] = None + save_oovs: Optional[bool] = None def __init__( self, @@ -142,26 +156,14 @@ class RimeTTSService(AudioContextWordTTSService): # and insert these tags for the purpose of the TTS service alone. self._text_aggregator = SkipTagsAggregator([("spell(", ")")]) - params = params or RimeTTSService.InputParams() + self._params = params or RimeTTSService.InputParams() # Store service configuration self._api_key = api_key self._url = url self._voice_id = voice_id self._model = model - self._settings = { - "speaker": voice_id, - "modelId": model, - "audioFormat": "pcm", - "samplingRate": 0, - "lang": self.language_to_service_language(params.language) - if params.language - else "eng", - "speedAlpha": params.speed_alpha, - "reduceLatency": params.reduce_latency, - "pauseBetweenBrackets": json.dumps(params.pause_between_brackets), - "phonemizeBetweenBrackets": json.dumps(params.phonemize_between_brackets), - } + self._settings = self._build_settings() # State tracking self._context_id = None # Tracks current turn @@ -188,14 +190,60 @@ class RimeTTSService(AudioContextWordTTSService): """ return language_to_rime_language(language) + def _build_settings(self) -> dict: + """Build query params for the WebSocket URL based on the current model and params. + + Returns: + Dictionary of query parameters. Only explicitly-set values are included. + """ + settings = { + "speaker": self._voice_id, + "modelId": self._model, + "audioFormat": "pcm", + "samplingRate": self.sample_rate or 0, + } + if self._params.language: + settings["lang"] = self.language_to_service_language(self._params.language) or "eng" + if self._params.segment is not None: + settings["segment"] = self._params.segment + + if self._model == "arcana": + if self._params.repetition_penalty is not None: + settings["repetition_penalty"] = self._params.repetition_penalty + if self._params.temperature is not None: + settings["temperature"] = self._params.temperature + if self._params.top_p is not None: + settings["top_p"] = self._params.top_p + else: # mistv2/mist + if self._params.speed_alpha is not None: + settings["speedAlpha"] = self._params.speed_alpha + if self._params.reduce_latency is not None: + settings["reduceLatency"] = self._params.reduce_latency + if self._params.pause_between_brackets is not None: + settings["pauseBetweenBrackets"] = json.dumps(self._params.pause_between_brackets) + if self._params.phonemize_between_brackets is not None: + settings["phonemizeBetweenBrackets"] = json.dumps( + self._params.phonemize_between_brackets + ) + if self._params.no_text_normalization is not None: + settings["noTextNormalization"] = json.dumps(self._params.no_text_normalization) + if self._params.save_oovs is not None: + settings["saveOovs"] = json.dumps(self._params.save_oovs) + + return settings + async def set_model(self, model: str): - """Update the TTS model. + """Update the TTS model and reconnect. Args: model: The model name to use for synthesis. """ self._model = model + self._settings = self._build_settings() await super().set_model(model) + if self._websocket: + await self._disconnect() + await self._connect() # A set of Rime-specific helpers for text transformations def SPELL(text: str) -> str: @@ -223,12 +271,68 @@ class RimeTTSService(AudioContextWordTTSService): return f"[{text}]" async def _update_settings(self, settings: Mapping[str, Any]): - """Update service settings and reconnect if voice changed.""" - prev_voice = self._voice_id + """Update service settings and reconnect if necessary. + + Since all settings are WebSocket URL query parameters, + any setting change requires reconnecting to apply the new values. + """ + prev_settings = self._settings.copy() await super()._update_settings(settings) - if not prev_voice == self._voice_id: + + needs_reconnect = False + + if "voice" in settings or "voice_id" in settings: self._settings["speaker"] = self._voice_id - logger.info(f"Switching TTS voice to: [{self._voice_id}]") + if prev_settings.get("speaker") != self._voice_id: + logger.info(f"Switching TTS voice to: [{self._voice_id}]") + needs_reconnect = True + + if "model" in settings: + self._settings = self._build_settings() + needs_reconnect = True + + if "language" in settings: + new_lang = self.language_to_service_language(settings["language"]) + if new_lang and new_lang != prev_settings.get("lang"): + logger.info(f"Updating language to: [{new_lang}]") + self._settings["lang"] = new_lang + needs_reconnect = True + + # Arcana params + for key, settings_key in [ + ("repetition_penalty", "repetition_penalty"), + ("temperature", "temperature"), + ("top_p", "top_p"), + ]: + if key in settings and settings[key] != prev_settings.get(settings_key): + self._settings[settings_key] = settings[key] + needs_reconnect = True + + # Mistv2 params + for key, settings_key in [ + ("speed_alpha", "speedAlpha"), + ("reduce_latency", "reduceLatency"), + ]: + if key in settings and settings[key] != prev_settings.get(settings_key): + self._settings[settings_key] = settings[key] + needs_reconnect = True + + # Mistv2 boolean params (need json.dumps) + for key, settings_key in [ + ("pause_between_brackets", "pauseBetweenBrackets"), + ("phonemize_between_brackets", "phonemizeBetweenBrackets"), + ("no_text_normalization", "noTextNormalization"), + ("save_oovs", "saveOovs"), + ]: + if key in settings and json.dumps(settings[key]) != prev_settings.get(settings_key): + self._settings[settings_key] = json.dumps(settings[key]) + needs_reconnect = True + + if "segment" in settings and settings["segment"] != prev_settings.get("segment"): + self._settings["segment"] = settings["segment"] + needs_reconnect = True + + if needs_reconnect and self._websocket: await self._disconnect() await self._connect() @@ -255,7 +359,7 @@ class RimeTTSService(AudioContextWordTTSService): frame: The start frame containing initialization parameters. """ await super().start(frame) - self._settings["samplingRate"] = self.sample_rate + self._settings = self._build_settings() await self._connect() async def stop(self, frame: EndFrame): @@ -301,7 +405,7 @@ class RimeTTSService(AudioContextWordTTSService): if self._websocket and self._websocket.state is State.OPEN: return - params = "&".join(f"{k}={v}" for k, v in self._settings.items()) + params = "&".join(f"{k}={v}" for k, v in self._settings.items() if v is not None) url = f"{self._url}?{params}" headers = {"Authorization": f"Bearer {self._api_key}"} self._websocket = await websocket_connect(url, additional_headers=headers) From 18afe37bd16f255067301d470743c802c1ea8c3c Mon Sep 17 00:00:00 2001 From: Mark Backman Date: Thu, 12 Feb 2026 14:04:56 -0500 Subject: [PATCH 0472/1060] Add changelog entries for PR #3642 --- changelog/3642.added.md | 1 + changelog/3642.changed.md | 1 + examples/foundational/07q-interruptible-rime.py | 7 ------- 3 files changed, 2 insertions(+), 7 deletions(-) create mode 100644 changelog/3642.added.md create mode 100644 changelog/3642.changed.md diff --git a/changelog/3642.added.md b/changelog/3642.added.md new file mode 100644 index 000000000..47668bf59 --- /dev/null +++ b/changelog/3642.added.md @@ -0,0 +1 @@ +- Added model-specific `InputParams` to `RimeTTSService`: arcana params (`repetition_penalty`, `temperature`, `top_p`) and mistv2 params (`no_text_normalization`, `save_oovs`, `segment`). Model, voice, and param changes now trigger WebSocket reconnection. diff --git a/changelog/3642.changed.md b/changelog/3642.changed.md new file mode 100644 index 000000000..96a43fbb8 --- /dev/null +++ b/changelog/3642.changed.md @@ -0,0 +1 @@ +- ⚠️ `RimeTTSService` now defaults to `model="arcana"` and the `wss://users-ws.rime.ai/ws3` endpoint. `InputParams` defaults changed from mistv2-specific values to `None` — only explicitly-set params are sent as query params. diff --git a/examples/foundational/07q-interruptible-rime.py b/examples/foundational/07q-interruptible-rime.py index d381c33dc..27e010273 100644 --- a/examples/foundational/07q-interruptible-rime.py +++ b/examples/foundational/07q-interruptible-rime.py @@ -25,7 +25,6 @@ from pipecat.runner.utils import create_transport from pipecat.services.deepgram.stt import DeepgramSTTService from pipecat.services.openai.llm import OpenAILLMService from pipecat.services.rime.tts import RimeTTSService -from pipecat.transcriptions.language import Language from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams @@ -58,12 +57,6 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): tts = RimeTTSService( api_key=os.getenv("RIME_API_KEY", ""), voice_id="luna", - params=RimeTTSService.InputParams( - language=Language.EN, - repetition_penalty=1.0, - temperature=0.5, - top_p=0.9, - ), ) llm = OpenAILLMService(api_key=os.getenv("OPENAI_API_KEY")) From 9569625f03ad013945e00d335adc5c9a2bd25e44 Mon Sep 17 00:00:00 2001 From: filipi87 Date: Thu, 12 Feb 2026 16:11:02 -0300 Subject: [PATCH 0473/1060] Changelog entries for the TTS fixes. --- changelog/3729.fixed.2.md | 1 + changelog/3729.fixed.md | 1 + 2 files changed, 2 insertions(+) create mode 100644 changelog/3729.fixed.2.md create mode 100644 changelog/3729.fixed.md diff --git a/changelog/3729.fixed.2.md b/changelog/3729.fixed.2.md new file mode 100644 index 000000000..6d4f33d93 --- /dev/null +++ b/changelog/3729.fixed.2.md @@ -0,0 +1 @@ +- Fixed context ID reuse issue in `ElevenLabsTTSService`, `InworldTTSService`, `RimeTTSService`, `CartesiaTTSService`, `AsyncAITTSService`, and `PlayHTTTSService`. Services now properly reuse the same context ID across multiple `run_tts()` invocations within a single LLM turn, preventing context tracking issues and incorrect lifecycle signaling. diff --git a/changelog/3729.fixed.md b/changelog/3729.fixed.md new file mode 100644 index 000000000..b8be759fb --- /dev/null +++ b/changelog/3729.fixed.md @@ -0,0 +1 @@ +- Fixed word timestamp interleaving issue in `ElevenLabsTTSService` when processing multiple sentences within a single LLM turn. From 94f01af54514c4f14786a35dd444069bfaa1a99a Mon Sep 17 00:00:00 2001 From: Ian Lee Date: Mon, 2 Feb 2026 18:18:02 -0800 Subject: [PATCH 0474/1060] [inworld] Allow Async delivery of timestamps info * speed up first audio chunk latency --- changelog/3625.added.md | 1 + src/pipecat/services/inworld/tts.py | 30 +++++++++++++++++++++-------- 2 files changed, 23 insertions(+), 8 deletions(-) create mode 100644 changelog/3625.added.md diff --git a/changelog/3625.added.md b/changelog/3625.added.md new file mode 100644 index 000000000..ddf787567 --- /dev/null +++ b/changelog/3625.added.md @@ -0,0 +1 @@ +- Added `"timestampTransportStrategy": "ASYNC"` to `InworldAITTSService`. This allows timestamps info to trail audio chunks arrival, resulting in much better first audio chunk latency diff --git a/src/pipecat/services/inworld/tts.py b/src/pipecat/services/inworld/tts.py index 845a37bdd..9f7c0cff1 100644 --- a/src/pipecat/services/inworld/tts.py +++ b/src/pipecat/services/inworld/tts.py @@ -17,7 +17,7 @@ import asyncio import base64 import json import uuid -from typing import Any, AsyncGenerator, Dict, List, Optional, Tuple +from typing import Any, AsyncGenerator, Dict, List, Literal, Optional, Tuple import aiohttp import websockets @@ -65,10 +65,12 @@ class InworldHttpTTSService(WordTTSService): Parameters: temperature: Temperature for speech synthesis. speaking_rate: Speaking rate for speech synthesis. + timestamp_transport_strategy: The strategy to use for timestamp transport. """ temperature: Optional[float] = None speaking_rate: Optional[float] = None + timestamp_transport_strategy: Optional[Literal["ASYNC", "SYNC"]] = None def __init__( self, @@ -128,6 +130,8 @@ class InworldHttpTTSService(WordTTSService): self._settings["temperature"] = params.temperature if params.speaking_rate is not None: self._settings["audioConfig"]["speakingRate"] = params.speaking_rate + if params.timestamp_transport_strategy is not None: + self._settings["timestampTransportStrategy"] = params.timestamp_transport_strategy self._cumulative_time = 0.0 @@ -240,6 +244,8 @@ class InworldHttpTTSService(WordTTSService): # Use WORD timestamps for simplicity and correct spacing/capitalization payload["timestampType"] = self._timestamp_type + if "timestampTransportStrategy" in self._settings: + payload["timestampTransportStrategy"] = self._settings["timestampTransportStrategy"] request_id = str(uuid.uuid4()) headers = { @@ -427,6 +433,7 @@ class InworldTTSService(AudioContextWordTTSService): flushing of buffered text to achieve minimal latency while maintaining high quality audio output. If None (default), automatically set based on aggregate_sentences. + timestamp_transport_strategy: The strategy to use for timestamp transport. """ temperature: Optional[float] = None @@ -434,7 +441,8 @@ class InworldTTSService(AudioContextWordTTSService): apply_text_normalization: Optional[str] = None max_buffer_delay_ms: Optional[int] = None buffer_char_threshold: Optional[int] = None - auto_mode: Optional[bool] = None + auto_mode: Optional[bool] = True + timestamp_transport_strategy: Optional[Literal["ASYNC", "SYNC"]] = None def __init__( self, @@ -494,6 +502,8 @@ class InworldTTSService(AudioContextWordTTSService): self._settings["audioConfig"]["speakingRate"] = params.speaking_rate if params.apply_text_normalization is not None: self._settings["applyTextNormalization"] = params.apply_text_normalization + if params.timestamp_transport_strategy is not None: + self._settings["timestampTransportStrategy"] = params.timestamp_transport_strategy if params.auto_mode is not None: self._settings["autoMode"] = params.auto_mode @@ -815,12 +825,12 @@ class InworldTTSService(AudioContextWordTTSService): if ctx_id: await self.append_to_audio_context(ctx_id, frame) - # timestampInfo is inside audioChunk - timestamp_info = audio_chunk.get("timestampInfo") - if timestamp_info: - word_times = self._calculate_word_times(timestamp_info) - if word_times: - await self.add_word_timestamps(word_times, ctx_id) + # timestampInfo is inside audioChunk + timestamp_info = audio_chunk.get("timestampInfo") + if timestamp_info: + word_times = self._calculate_word_times(timestamp_info) + if word_times: + await self.add_word_timestamps(word_times, ctx_id) # Handle context created confirmation if "contextCreated" in result: @@ -884,6 +894,10 @@ class InworldTTSService(AudioContextWordTTSService): create_config["applyTextNormalization"] = self._settings["applyTextNormalization"] if "autoMode" in self._settings: create_config["autoMode"] = self._settings["autoMode"] + if "timestampTransportStrategy" in self._settings: + create_config["timestampTransportStrategy"] = self._settings[ + "timestampTransportStrategy" + ] # Set buffer settings for timely audio generation. # Use provided values or defaults that work well for streaming LLM output. From 3fce88555fc2aba5ac5dea80e218100a5b12c43c Mon Sep 17 00:00:00 2001 From: Mark Backman Date: Fri, 13 Feb 2026 09:39:44 -0500 Subject: [PATCH 0475/1060] Improve events docstrings --- src/pipecat/services/deepgram/flux/stt.py | 14 +++++ src/pipecat/services/deepgram/stt.py | 11 ++++ src/pipecat/services/sarvam/stt.py | 12 ++++ src/pipecat/services/speechmatics/stt.py | 10 ++++ src/pipecat/transports/daily/transport.py | 55 +++++++++++++++++++ src/pipecat/transports/heygen/transport.py | 11 ++++ src/pipecat/transports/livekit/transport.py | 35 ++++++++++++ .../transports/smallwebrtc/transport.py | 12 ++++ src/pipecat/transports/tavus/transport.py | 11 ++++ src/pipecat/transports/websocket/client.py | 11 ++++ src/pipecat/transports/websocket/fastapi.py | 12 ++++ src/pipecat/transports/websocket/server.py | 13 +++++ 12 files changed, 207 insertions(+) diff --git a/src/pipecat/services/deepgram/flux/stt.py b/src/pipecat/services/deepgram/flux/stt.py index 547eca0de..5b091862c 100644 --- a/src/pipecat/services/deepgram/flux/stt.py +++ b/src/pipecat/services/deepgram/flux/stt.py @@ -73,6 +73,20 @@ class DeepgramFluxSTTService(WebsocketSTTService): Provides real-time speech recognition using Deepgram's WebSocket API with Flux capabilities. Supports configurable models, VAD events, and various audio processing options including advanced turn detection and EagerEndOfTurn events for improved conversational AI performance. + + Event handlers available (in addition to WebsocketSTTService events): + + - on_speech_started(service): Deepgram detected start of speech + - on_utterance_end(service): Deepgram detected end of utterance + - on_end_of_turn(service): Deepgram detected end of turn (EOT) + - on_eager_end_of_turn(service): Deepgram predicted end of turn (EagerEOT) + - on_turn_resumed(service): User resumed speaking after EagerEOT + + Example:: + + @stt.event_handler("on_end_of_turn") + async def on_end_of_turn(service): + ... """ class InputParams(BaseModel): diff --git a/src/pipecat/services/deepgram/stt.py b/src/pipecat/services/deepgram/stt.py index 0f79499ba..c4f72e6c3 100644 --- a/src/pipecat/services/deepgram/stt.py +++ b/src/pipecat/services/deepgram/stt.py @@ -50,6 +50,17 @@ class DeepgramSTTService(STTService): Provides real-time speech recognition using Deepgram's WebSocket API. Supports configurable models, languages, and various audio processing options. + + Event handlers available (in addition to STTService events): + + - on_speech_started(service): Deepgram detected start of speech + - on_utterance_end(service): Deepgram detected end of utterance + + Example:: + + @stt.event_handler("on_speech_started") + async def on_speech_started(service): + ... """ def __init__( diff --git a/src/pipecat/services/sarvam/stt.py b/src/pipecat/services/sarvam/stt.py index aae1ae243..13277fe96 100644 --- a/src/pipecat/services/sarvam/stt.py +++ b/src/pipecat/services/sarvam/stt.py @@ -134,6 +134,18 @@ class SarvamSTTService(STTService): """Sarvam speech-to-text service. Provides real-time speech recognition using Sarvam's WebSocket API. + + Event handlers available (in addition to STTService events): + + - on_connected(service): Connected to Sarvam WebSocket + - on_disconnected(service): Disconnected from Sarvam WebSocket + - on_connection_error(service, error): Connection error occurred + + Example:: + + @stt.event_handler("on_connected") + async def on_connected(service): + ... """ class InputParams(BaseModel): diff --git a/src/pipecat/services/speechmatics/stt.py b/src/pipecat/services/speechmatics/stt.py index ca949a9fd..72f3f3990 100644 --- a/src/pipecat/services/speechmatics/stt.py +++ b/src/pipecat/services/speechmatics/stt.py @@ -86,6 +86,16 @@ class SpeechmaticsSTTService(STTService): This service provides real-time speech-to-text transcription using the Speechmatics API. It supports partial and final transcriptions, multiple languages, various audio formats, and speaker diarization. + + Event handlers available (in addition to STTService events): + + - on_speakers_result(service, speakers): Speaker diarization results received + + Example:: + + @stt.event_handler("on_speakers_result") + async def on_speakers_result(service, speakers): + ... """ # Export related classes as class attributes diff --git a/src/pipecat/transports/daily/transport.py b/src/pipecat/transports/daily/transport.py index 20a0be29f..e3b246253 100644 --- a/src/pipecat/transports/daily/transport.py +++ b/src/pipecat/transports/daily/transport.py @@ -2039,6 +2039,61 @@ class DailyTransport(BaseTransport): Provides comprehensive Daily integration including audio/video streaming, transcription, recording, dial-in/out functionality, and real-time communication features for conversational AI applications. + + Event handlers available: + + - on_joined: Called when the bot joins the room. Args: (data: dict) + - on_left: Called when the bot leaves the room. + - on_before_leave: [sync] Called just before the bot leaves the room. + - on_error: Called when a transport error occurs. Args: (error: str) + - on_call_state_updated: Called when the call state changes. Args: (state: str) + - on_first_participant_joined: Called when the first participant joins. + Args: (participant: dict) + - on_participant_joined: Called when any participant joins. + Args: (participant: dict) + - on_participant_left: Called when a participant leaves. + Args: (participant: dict, reason: str) + - on_participant_updated: Called when a participant's state changes. + Args: (participant: dict) + - on_client_connected: Called when a participant connects (alias for + on_participant_joined). Args: (participant: dict) + - on_client_disconnected: Called when a participant disconnects (alias for + on_participant_left). Args: (participant: dict) + - on_active_speaker_changed: Called when the active speaker changes. + Args: (participant: dict) + - on_app_message: Called when an app message is received. + Args: (message: Any, sender: str) + - on_transcription_message: Called when a transcription message is received. + Args: (message: dict) + - on_recording_started: Called when recording starts. Args: (status: str) + - on_recording_stopped: Called when recording stops. Args: (stream_id: str) + - on_recording_error: Called when a recording error occurs. + Args: (stream_id: str, message: str) + - on_dialin_connected: Called when a dial-in call connects. Args: (data: dict) + - on_dialin_ready: Called when the SIP endpoint is ready. + Args: (sip_endpoint: str) + - on_dialin_stopped: Called when a dial-in call stops. Args: (data: dict) + - on_dialin_error: Called when a dial-in error occurs. Args: (data: dict) + - on_dialin_warning: Called when a dial-in warning occurs. Args: (data: dict) + - on_dialout_answered: Called when a dial-out call is answered. Args: (data: dict) + - on_dialout_connected: Called when a dial-out call connects. Args: (data: dict) + - on_dialout_stopped: Called when a dial-out call stops. Args: (data: dict) + - on_dialout_error: Called when a dial-out error occurs. Args: (data: dict) + - on_dialout_warning: Called when a dial-out warning occurs. Args: (data: dict) + + Example:: + + @transport.event_handler("on_first_participant_joined") + async def on_first_participant_joined(transport, participant): + await task.queue_frame(TTSSpeakFrame("Hello!")) + + @transport.event_handler("on_participant_left") + async def on_participant_left(transport, participant, reason): + await task.queue_frame(EndFrame()) + + @transport.event_handler("on_app_message") + async def on_app_message(transport, message, sender): + logger.info(f"Message from {sender}: {message}") """ def __init__( diff --git a/src/pipecat/transports/heygen/transport.py b/src/pipecat/transports/heygen/transport.py index 2ff1c7d56..dbeded3e5 100644 --- a/src/pipecat/transports/heygen/transport.py +++ b/src/pipecat/transports/heygen/transport.py @@ -289,6 +289,17 @@ class HeyGenTransport(BaseTransport): When used, the Pipecat bot joins the same virtual room as the HeyGen Avatar and the user. This is achieved by using `HeyGenTransport`, which initiates the conversation via `HeyGenApi` and obtains a room URL that all participants connect to. + + Event handlers available: + + - on_client_connected(transport, participant): Participant connected to the session + - on_client_disconnected(transport, participant): Participant disconnected from the session + + Example:: + + @transport.event_handler("on_client_connected") + async def on_client_connected(transport, participant): + ... """ def __init__( diff --git a/src/pipecat/transports/livekit/transport.py b/src/pipecat/transports/livekit/transport.py index ab7325c68..1902e7cd3 100644 --- a/src/pipecat/transports/livekit/transport.py +++ b/src/pipecat/transports/livekit/transport.py @@ -950,6 +950,41 @@ class LiveKitTransport(BaseTransport): Provides comprehensive LiveKit integration including audio streaming, data messaging, participant management, and room event handling for conversational AI applications. + + Event handlers available: + + - on_connected: Called when the bot connects to the room. + - on_disconnected: Called when the bot disconnects from the room. + - on_before_disconnect: [sync] Called just before the bot disconnects. + - on_call_state_updated: Called when the call state changes. Args: (state: str) + - on_first_participant_joined: Called when the first participant joins. + Args: (participant_id: str) + - on_participant_connected: Called when a participant connects. + Args: (participant_id: str) + - on_participant_disconnected: Called when a participant disconnects. + Args: (participant_id: str) + - on_participant_left: Called when a participant leaves. + Args: (participant_id: str, reason: str) + - on_audio_track_subscribed: Called when an audio track is subscribed. + Args: (participant_id: str) + - on_audio_track_unsubscribed: Called when an audio track is unsubscribed. + Args: (participant_id: str) + - on_video_track_subscribed: Called when a video track is subscribed. + Args: (participant_id: str) + - on_video_track_unsubscribed: Called when a video track is unsubscribed. + Args: (participant_id: str) + - on_data_received: Called when data is received from a participant. + Args: (data: bytes, participant_id: str) + + Example:: + + @transport.event_handler("on_first_participant_joined") + async def on_first_participant_joined(transport, participant_id): + await task.queue_frame(TTSSpeakFrame("Hello!")) + + @transport.event_handler("on_participant_disconnected") + async def on_participant_disconnected(transport, participant_id): + await task.queue_frame(EndFrame()) """ def __init__( diff --git a/src/pipecat/transports/smallwebrtc/transport.py b/src/pipecat/transports/smallwebrtc/transport.py index 4389ff5d9..dc91588a3 100644 --- a/src/pipecat/transports/smallwebrtc/transport.py +++ b/src/pipecat/transports/smallwebrtc/transport.py @@ -864,6 +864,18 @@ class SmallWebRTCTransport(BaseTransport): Provides bidirectional audio and video streaming over WebRTC connections with support for application messaging and connection event handling. + + Event handlers available: + + - on_client_connected(transport, client): Client connected to WebRTC session + - on_client_disconnected(transport, client): Client disconnected from WebRTC session + - on_client_message(transport, message, client): Received a data channel message + + Example:: + + @transport.event_handler("on_client_connected") + async def on_client_connected(transport, client): + ... """ def __init__( diff --git a/src/pipecat/transports/tavus/transport.py b/src/pipecat/transports/tavus/transport.py index 8e91e2713..c8a79d386 100644 --- a/src/pipecat/transports/tavus/transport.py +++ b/src/pipecat/transports/tavus/transport.py @@ -661,6 +661,17 @@ class TavusTransport(BaseTransport): When used, the Pipecat bot joins the same virtual room as the Tavus Avatar and the user. This is achieved by using `TavusTransportClient`, which initiates the conversation via `TavusApi` and obtains a room URL that all participants connect to. + + Event handlers available: + + - on_client_connected(transport, participant): Participant connected to the session + - on_client_disconnected(transport, participant): Participant disconnected from the session + + Example:: + + @transport.event_handler("on_client_connected") + async def on_client_connected(transport, participant): + ... """ def __init__( diff --git a/src/pipecat/transports/websocket/client.py b/src/pipecat/transports/websocket/client.py index e24352575..b5b99ee97 100644 --- a/src/pipecat/transports/websocket/client.py +++ b/src/pipecat/transports/websocket/client.py @@ -471,6 +471,17 @@ class WebsocketClientTransport(BaseTransport): Provides a complete WebSocket client transport implementation with input and output capabilities, connection management, and event handling. + + Event handlers available: + + - on_connected(transport): Connected to WebSocket server + - on_disconnected(transport): Disconnected from WebSocket server + + Example:: + + @transport.event_handler("on_connected") + async def on_connected(transport): + ... """ def __init__( diff --git a/src/pipecat/transports/websocket/fastapi.py b/src/pipecat/transports/websocket/fastapi.py index d4f5809d9..f52123e52 100644 --- a/src/pipecat/transports/websocket/fastapi.py +++ b/src/pipecat/transports/websocket/fastapi.py @@ -534,6 +534,18 @@ class FastAPIWebsocketTransport(BaseTransport): Provides bidirectional WebSocket communication with frame serialization, session management, and event handling for client connections and timeouts. + + Event handlers available: + + - on_client_connected(transport, websocket): Client WebSocket connected + - on_client_disconnected(transport, websocket): Client WebSocket disconnected + - on_session_timeout(transport, websocket): Session timed out + + Example:: + + @transport.event_handler("on_client_connected") + async def on_client_connected(transport, websocket): + ... """ def __init__( diff --git a/src/pipecat/transports/websocket/server.py b/src/pipecat/transports/websocket/server.py index 16964cb9b..e5f628fa4 100644 --- a/src/pipecat/transports/websocket/server.py +++ b/src/pipecat/transports/websocket/server.py @@ -421,6 +421,19 @@ class WebsocketServerTransport(BaseTransport): Provides a complete WebSocket server implementation with separate input and output transports, client connection management, and event handling for real-time audio and data streaming applications. + + Event handlers available: + + - on_client_connected(transport, websocket): Client WebSocket connected + - on_client_disconnected(transport, websocket): Client WebSocket disconnected + - on_session_timeout(transport, websocket): Session timed out + - on_websocket_ready(transport): WebSocket server is ready to accept connections + + Example:: + + @transport.event_handler("on_client_connected") + async def on_client_connected(transport, websocket): + ... """ def __init__( From 25ca2964777311d81b955816c7d5ac67da86f793 Mon Sep 17 00:00:00 2001 From: Mark Backman Date: Fri, 13 Feb 2026 11:21:24 -0500 Subject: [PATCH 0476/1060] Move tracing fields to AIService and extract _get_turn_context helper Consolidate _tracing_enabled and _tracing_context from LLMService, STTService, and TTSService into the shared AIService base class. Extract _get_turn_context() helper in service_decorators.py to encapsulate the repeated pattern across all traced decorators. --- src/pipecat/services/ai_service.py | 5 ++- src/pipecat/services/llm_service.py | 3 -- src/pipecat/services/stt_service.py | 3 -- src/pipecat/services/tts_service.py | 4 --- .../utils/tracing/service_decorators.py | 33 ++++++++++--------- 5 files changed, 22 insertions(+), 26 deletions(-) diff --git a/src/pipecat/services/ai_service.py b/src/pipecat/services/ai_service.py index c03ab9d0e..52b42663f 100644 --- a/src/pipecat/services/ai_service.py +++ b/src/pipecat/services/ai_service.py @@ -44,6 +44,8 @@ class AIService(FrameProcessor): self._model_name: str = "" self._settings: Dict[str, Any] = {} self._session_properties: Dict[str, Any] = {} + self._tracing_enabled: bool = False + self._tracing_context = None @property def model_name(self) -> str: @@ -72,7 +74,8 @@ class AIService(FrameProcessor): Args: frame: The start frame containing initialization parameters. """ - pass + self._tracing_enabled = frame.enable_tracing + self._tracing_context = frame.tracing_context async def stop(self, frame: EndFrame): """Stop the AI service. diff --git a/src/pipecat/services/llm_service.py b/src/pipecat/services/llm_service.py index acbd6baae..c8af00b80 100644 --- a/src/pipecat/services/llm_service.py +++ b/src/pipecat/services/llm_service.py @@ -198,7 +198,6 @@ class LLMService(UserTurnCompletionLLMServiceMixin, AIService): self._functions: Dict[Optional[str], FunctionCallRegistryItem] = {} self._function_call_tasks: Dict[Optional[asyncio.Task], FunctionCallRunnerItem] = {} self._sequential_runner_task: Optional[asyncio.Task] = None - self._tracing_enabled: bool = False self._skip_tts: Optional[bool] = None self._summary_task: Optional[asyncio.Task] = None @@ -285,8 +284,6 @@ class LLMService(UserTurnCompletionLLMServiceMixin, AIService): await super().start(frame) if not self._run_in_parallel: await self._create_sequential_runner_task() - self._tracing_enabled = frame.enable_tracing - self._tracing_context = frame.tracing_context async def stop(self, frame: EndFrame): """Stop the LLM service. diff --git a/src/pipecat/services/stt_service.py b/src/pipecat/services/stt_service.py index 81f369572..1d8d1590f 100644 --- a/src/pipecat/services/stt_service.py +++ b/src/pipecat/services/stt_service.py @@ -102,7 +102,6 @@ class STTService(AIService): self._init_sample_rate = sample_rate self._sample_rate = 0 self._settings: Dict[str, Any] = {} - self._tracing_enabled: bool = False self._muted: bool = False self._user_id: str = "" self._ttfs_p99_latency = ttfs_p99_latency @@ -202,8 +201,6 @@ class STTService(AIService): """ await super().start(frame) self._sample_rate = self._init_sample_rate or frame.audio_in_sample_rate - self._tracing_enabled = frame.enable_tracing - self._tracing_context = frame.tracing_context async def cleanup(self): """Clean up STT service resources.""" diff --git a/src/pipecat/services/tts_service.py b/src/pipecat/services/tts_service.py index 00e3e81f8..02c799d0f 100644 --- a/src/pipecat/services/tts_service.py +++ b/src/pipecat/services/tts_service.py @@ -208,8 +208,6 @@ class TTSService(AIService): # TODO: Deprecate _text_filters when added to LLMTextProcessor self._text_filters: Sequence[BaseTextFilter] = text_filters or [] self._transport_destination: Optional[str] = transport_destination - self._tracing_enabled: bool = False - if text_filter: import warnings @@ -349,8 +347,6 @@ class TTSService(AIService): self._sample_rate = self._init_sample_rate or frame.audio_out_sample_rate if self._push_stop_frames and not self._stop_frame_task: self._stop_frame_task = self.create_task(self._stop_frame_handler()) - self._tracing_enabled = frame.enable_tracing - self._tracing_context = frame.tracing_context async def stop(self, frame: EndFrame): """Stop the TTS service. diff --git a/src/pipecat/utils/tracing/service_decorators.py b/src/pipecat/utils/tracing/service_decorators.py index a4f0d8c37..fae7f7e77 100644 --- a/src/pipecat/utils/tracing/service_decorators.py +++ b/src/pipecat/utils/tracing/service_decorators.py @@ -54,6 +54,19 @@ def _noop_decorator(func): return func +def _get_turn_context(self): + """Get the current turn's tracing context if available. + + Args: + self: The service instance. + + Returns: + The turn context, or None if unavailable. + """ + tracing_ctx = getattr(self, "_tracing_context", None) + return tracing_ctx.get_turn_context() if tracing_ctx else None + + def _get_parent_service_context(self): """Get the parent service span context (internal use only). @@ -182,9 +195,7 @@ def traced_tts(func: Optional[Callable] = None, *, name: Optional[str] = None) - span_name = "tts" # Get parent context - tracing_ctx = getattr(self, "_tracing_context", None) - turn_context = tracing_ctx.get_turn_context() if tracing_ctx else None - parent_context = turn_context or _get_parent_service_context(self) + parent_context = _get_turn_context(self) or _get_parent_service_context(self) # Create span tracer = trace.get_tracer("pipecat") @@ -290,9 +301,7 @@ def traced_stt(func: Optional[Callable] = None, *, name: Optional[str] = None) - span_name = "stt" # Get the turn context first, then fall back to service context - tracing_ctx = getattr(self, "_tracing_context", None) - turn_context = tracing_ctx.get_turn_context() if tracing_ctx else None - parent_context = turn_context or _get_parent_service_context(self) + parent_context = _get_turn_context(self) or _get_parent_service_context(self) # Create a new span as child of the turn span or service span tracer = trace.get_tracer("pipecat") @@ -373,9 +382,7 @@ def traced_llm(func: Optional[Callable] = None, *, name: Optional[str] = None) - span_name = "llm" # Get the parent context - turn context if available, otherwise service context - tracing_ctx = getattr(self, "_tracing_context", None) - turn_context = tracing_ctx.get_turn_context() if tracing_ctx else None - parent_context = turn_context or _get_parent_service_context(self) + parent_context = _get_turn_context(self) or _get_parent_service_context(self) # Create a new span as child of the turn span or service span tracer = trace.get_tracer("pipecat") @@ -584,9 +591,7 @@ def traced_gemini_live(operation: str) -> Callable: span_name = f"{operation}" # Get the parent context - turn context if available, otherwise service context - tracing_ctx = getattr(self, "_tracing_context", None) - turn_context = tracing_ctx.get_turn_context() if tracing_ctx else None - parent_context = turn_context or _get_parent_service_context(self) + parent_context = _get_turn_context(self) or _get_parent_service_context(self) # Create a new span as child of the turn span or service span tracer = trace.get_tracer("pipecat") @@ -892,9 +897,7 @@ def traced_openai_realtime(operation: str) -> Callable: span_name = f"{operation}" # Get the parent context - turn context if available, otherwise service context - tracing_ctx = getattr(self, "_tracing_context", None) - turn_context = tracing_ctx.get_turn_context() if tracing_ctx else None - parent_context = turn_context or _get_parent_service_context(self) + parent_context = _get_turn_context(self) or _get_parent_service_context(self) # Create a new span as child of the turn span or service span tracer = trace.get_tracer("pipecat") From 01b7a93e08844e28f9371ef93b71eaa2d465d98b Mon Sep 17 00:00:00 2001 From: Mark Backman Date: Thu, 12 Feb 2026 18:40:33 -0500 Subject: [PATCH 0477/1060] Deprecate unused Traceable/class_decorators module and fix stale comments The class_decorators.py module (Traceable, @traceable, @traced) is not used anywhere in the codebase. Mark it deprecated and fix the misleading comment in service_decorators.py that referenced it as if it were active. --- changelog/3733.deprecated.md | 1 + src/pipecat/utils/tracing/class_decorators.py | 13 +++++++++++++ src/pipecat/utils/tracing/service_decorators.py | 5 +++-- 3 files changed, 17 insertions(+), 2 deletions(-) create mode 100644 changelog/3733.deprecated.md diff --git a/changelog/3733.deprecated.md b/changelog/3733.deprecated.md new file mode 100644 index 000000000..8b1fb29bb --- /dev/null +++ b/changelog/3733.deprecated.md @@ -0,0 +1 @@ +- Deprecated unused `Traceable`, `@traceable`, `@traced`, and `AttachmentStrategy` in `pipecat.utils.tracing.class_decorators`. This module will be removed in a future release. diff --git a/src/pipecat/utils/tracing/class_decorators.py b/src/pipecat/utils/tracing/class_decorators.py index 571a74804..73dacbe51 100644 --- a/src/pipecat/utils/tracing/class_decorators.py +++ b/src/pipecat/utils/tracing/class_decorators.py @@ -7,6 +7,11 @@ """Base OpenTelemetry tracing decorators and utilities for Pipecat. +.. deprecated:: 0.0.103 + This module is unused and will be removed in a future release. + Service tracing is handled by the decorators in + :mod:`pipecat.utils.tracing.service_decorators`. + This module provides class and method level tracing capabilities similar to the original NVIDIA implementation. """ @@ -16,8 +21,16 @@ import contextlib import enum import functools import inspect +import warnings from typing import Callable, Optional, TypeVar +warnings.warn( + "pipecat.utils.tracing.class_decorators is deprecated and will be removed in a future " + "release. Use pipecat.utils.tracing.service_decorators instead.", + DeprecationWarning, + stacklevel=2, +) + from pipecat.utils.tracing.setup import is_tracing_available # Import OpenTelemetry if available diff --git a/src/pipecat/utils/tracing/service_decorators.py b/src/pipecat/utils/tracing/service_decorators.py index fae7f7e77..0fd939162 100644 --- a/src/pipecat/utils/tracing/service_decorators.py +++ b/src/pipecat/utils/tracing/service_decorators.py @@ -82,11 +82,12 @@ def _get_parent_service_context(self): if not is_tracing_available(): return None - # The parent span was created when Traceable was initialized and stored as self._span + # TODO: Remove this block and delete class_decorators.py once Traceable is removed. + # Legacy: support for classes inheriting from Traceable (currently unused, deprecated). if hasattr(self, "_span") and self._span: return trace.set_span_in_context(self._span) - # Fall back to conversation context if available + # Use the conversation context set by TurnTraceObserver via TracingContext. tracing_ctx = getattr(self, "_tracing_context", None) conversation_context = tracing_ctx.get_conversation_context() if tracing_ctx else None if conversation_context: From 3adb2f50a6d03e11b619bba1730ea8c4d07ecd9c Mon Sep 17 00:00:00 2001 From: Luke Payyapilli Date: Fri, 13 Feb 2026 11:59:56 -0500 Subject: [PATCH 0478/1060] Fix LLMUserAggregator broadcasting mute events before StartFrame --- changelog/3737.fixed.md | 1 + .../aggregators/llm_response_universal.py | 9 ++++ tests/test_context_aggregators_universal.py | 44 ++++++++++++++++++- 3 files changed, 53 insertions(+), 1 deletion(-) create mode 100644 changelog/3737.fixed.md diff --git a/changelog/3737.fixed.md b/changelog/3737.fixed.md new file mode 100644 index 000000000..6dee96f82 --- /dev/null +++ b/changelog/3737.fixed.md @@ -0,0 +1 @@ +- Fixed `LLMUserAggregator` broadcasting mute events before `StartFrame` reaches downstream processors. diff --git a/src/pipecat/processors/aggregators/llm_response_universal.py b/src/pipecat/processors/aggregators/llm_response_universal.py index 6b28b5bf2..8450842c8 100644 --- a/src/pipecat/processors/aggregators/llm_response_universal.py +++ b/src/pipecat/processors/aggregators/llm_response_universal.py @@ -549,6 +549,15 @@ class LLMUserAggregator(LLMContextAggregator): await s.cleanup() async def _maybe_mute_frame(self, frame: Frame): + # Control frames must flow unconditionally — never feed them to mute + # strategies. Without this guard, strategies like + # MuteUntilFirstBotCompleteUserMuteStrategy fire on_user_mute_started + # and broadcast UserMuteStartedFrame before StartFrame is pushed + # downstream, causing downstream processors to receive frames before + # StartFrame and log errors. + if isinstance(frame, (StartFrame, EndFrame, CancelFrame)): + return False + should_mute_frame = self._user_is_muted and isinstance( frame, ( diff --git a/tests/test_context_aggregators_universal.py b/tests/test_context_aggregators_universal.py index 7e09a5449..1bba463b0 100644 --- a/tests/test_context_aggregators_universal.py +++ b/tests/test_context_aggregators_universal.py @@ -24,7 +24,9 @@ from pipecat.frames.frames import ( LLMThoughtEndFrame, LLMThoughtStartFrame, LLMThoughtTextFrame, + StartFrame, TranscriptionFrame, + UserMuteStartedFrame, UserStartedSpeakingFrame, UserStoppedSpeakingFrame, VADUserStartedSpeakingFrame, @@ -40,7 +42,11 @@ from pipecat.processors.aggregators.llm_response_universal import ( LLMUserAggregatorParams, ) from pipecat.tests.utils import SleepFrame, run_test -from pipecat.turns.user_mute import FirstSpeechUserMuteStrategy, FunctionCallUserMuteStrategy +from pipecat.turns.user_mute import ( + FirstSpeechUserMuteStrategy, + FunctionCallUserMuteStrategy, + MuteUntilFirstBotCompleteUserMuteStrategy, +) from pipecat.turns.user_stop import SpeechTimeoutUserTurnStopStrategy from pipecat.turns.user_turn_strategies import UserTurnStrategies @@ -386,6 +392,42 @@ class TestLLMUserAggregator(unittest.IsolatedAsyncioTestCase): self.assertIsNone(strategy) # strategy is None for end/cancel self.assertEqual(message.content, "Hello!") + async def test_start_frame_before_mute_event(self): + """StartFrame must reach downstream before mute events are broadcast. + + With MuteUntilFirstBotCompleteUserMuteStrategy, the mute logic should + not run on control frames (StartFrame, EndFrame, CancelFrame). This + ensures StartFrame reaches downstream processors before + UserMuteStartedFrame is broadcast. + + The default TurnAnalyzerUserTurnStopStrategy broadcasts a + SpeechControlParamsFrame when it processes StartFrame, which gets + re-queued to the aggregator. That non-control frame legitimately + triggers the mute state change, so UserMuteStartedFrame follows + StartFrame — but crucially, after it. + """ + context = LLMContext() + + user_aggregator = LLMUserAggregator( + context, + params=LLMUserAggregatorParams( + user_mute_strategies=[MuteUntilFirstBotCompleteUserMuteStrategy()], + ), + ) + + pipeline = Pipeline([user_aggregator]) + + # run_test internally sends StartFrame via PipelineRunner. With + # ignore_start=False we can verify ordering: StartFrame must arrive + # before UserMuteStartedFrame. Before the fix, UserMuteStartedFrame + # was broadcast before StartFrame reached downstream processors. + (down_frames, _) = await run_test( + pipeline, + frames_to_send=[], + expected_down_frames=[StartFrame, UserMuteStartedFrame], + ignore_start=False, + ) + class TestLLMAssistantAggregator(unittest.IsolatedAsyncioTestCase): async def test_empty(self): From 2454bedf29b42f0964373e55f6b43429368834f2 Mon Sep 17 00:00:00 2001 From: Mark Backman Date: Fri, 13 Feb 2026 12:28:18 -0500 Subject: [PATCH 0479/1060] Add /update-docs skill for keeping docs in sync with source changes Adds a Claude Code skill that analyzes the current branch diff against main, maps changed source files to their doc pages, and makes targeted updates to Configuration, InputParams, Usage, Notes, and Event Handlers sections. --- .claude/skills/update-docs/SKILL.md | 250 ++++++++++++++++++ .../skills/update-docs/SOURCE_DOC_MAPPING.md | 79 ++++++ 2 files changed, 329 insertions(+) create mode 100644 .claude/skills/update-docs/SKILL.md create mode 100644 .claude/skills/update-docs/SOURCE_DOC_MAPPING.md diff --git a/.claude/skills/update-docs/SKILL.md b/.claude/skills/update-docs/SKILL.md new file mode 100644 index 000000000..f70febf96 --- /dev/null +++ b/.claude/skills/update-docs/SKILL.md @@ -0,0 +1,250 @@ +--- +name: update-docs +description: Update documentation pages to match source code changes on the current branch +--- + +Update documentation pages to reflect source code changes on the current branch. Analyzes the diff against main, maps changed source files to their corresponding doc pages, and makes targeted edits. + +## Arguments + +``` +/update-docs [DOCS_PATH] +``` + +- `DOCS_PATH` (optional): Path to the docs repository root. If not provided, ask the user. + +Examples: +- `/update-docs /Users/me/src/docs` +- `/update-docs` + +## Instructions + +### Step 1: Resolve docs path + +If `DOCS_PATH` was provided as an argument, use it. Otherwise, ask the user for the path to their docs repository. + +Verify the path exists and contains `server/services/` subdirectory. + +### Step 2: Create docs branch + +Get the current pipecat branch name: +```bash +git rev-parse --abbrev-ref HEAD +``` + +In the docs repo, create a new branch off main with a matching name: +```bash +cd DOCS_PATH && git checkout main && git pull && git checkout -b {branch-name}-docs +``` + +For example, if the pipecat branch is `feat/new-service`, the docs branch becomes `feat/new-service-docs`. + +All doc edits in subsequent steps are made on this branch. + +### Step 3: Detect changed source files + +Run: +```bash +git diff main..HEAD --name-only +``` + +Filter to files that could affect documentation: +- `src/pipecat/services/**/*.py` (service implementations) +- `src/pipecat/transports/**/*.py` (transport implementations) +- `src/pipecat/serializers/**/*.py` (serializer implementations) +- `src/pipecat/processors/**/*.py` (processor implementations) +- `src/pipecat/audio/**/*.py` (audio utilities) +- `src/pipecat/turns/**/*.py` (turn management) +- `src/pipecat/observers/**/*.py` (observers) +- `src/pipecat/pipeline/**/*.py` (pipeline core) + +Ignore `__init__.py`, `__pycache__`, test files, and files that only contain type re-exports. + +### Step 4: Map source files to doc pages + +For each changed source file, find the corresponding doc page. Read the mapping file at `.claude/skills/update-docs/SOURCE_DOC_MAPPING.md` and apply its tiered lookup: tier 1 (known exceptions) → tier 2 (pattern matching) → tier 3 (search fallback). **First match wins.** + +### Step 5: Analyze each source-doc pair + +For each mapped pair: + +1. **Read the full source file** to understand current state +2. **Read the diff** for that file: `git diff main..HEAD -- ` +3. **Read the current doc page** in full + +Identify what changed by comparing source to docs: + +- **Constructor parameters**: Compare `__init__` signature to the Configuration section's `` entries +- **InputParams fields**: Compare `InputParams(BaseModel)` class fields to the InputParams table +- **Event handlers**: Compare `_register_event_handler` calls and event handler definitions to Event Handlers section +- **Class names / imports**: Check if Usage examples reference correct names +- **Behavioral changes**: Check if Notes section needs updating + +### Step 6: Make targeted edits + +For each doc page that needs updates, edit **only the sections that need changes**. Preserve all other content exactly as-is. + +#### Rules + +- **Never remove content** unless the corresponding source code was removed +- **Never rewrite sections** that are already accurate +- **Match existing formatting** — if the page uses `` tags, use them; if it uses tables, use tables +- **Keep descriptions concise** — match the tone and length of surrounding content +- **Preserve CardGroup, links, and examples** unless they reference removed functionality +- **Don't touch frontmatter** unless the class was renamed + +#### Section-specific guidance + +**Configuration** (constructor params): +- Use `` format if the page already uses it +- Add new params in logical order (required first, then optional) +- Remove params that no longer exist in source +- Update types/defaults that changed + +**InputParams** (runtime settings): +- Use markdown table format: `| Parameter | Type | Default | Description |` +- Match the field names and types from the `InputParams(BaseModel)` class +- Include the default values from the source + +**Usage** (code examples): +- Update import paths, class names, and parameter names +- Only modify examples if they would break or be misleading with the new API +- Don't rewrite working examples just to add new optional params + +**Notes**: +- Add notes for new behavioral gotchas or breaking changes +- Remove notes about limitations that were fixed +- Keep existing notes that are still accurate + +**Event Handlers**: +- Update the event table and example code +- Add new events, remove deleted ones +- Update handler signatures if they changed + +**Overview / Key Features / Prerequisites**: +- Only update if the PR fundamentally changes what the service does (new capability, removed capability, renamed class) +- Most PRs will NOT need changes to these sections + +### Step 7: Update guides + +Guides at `DOCS_PATH/guides/` reference specific class names, parameters, imports, and code patterns. After completing reference doc edits, check if any guides need updates too. + +For each changed source file, collect the class names, renamed parameters, and changed imports from the diff. Search the guides directory: +```bash +grep -rl "ClassName\|old_param_name" DOCS_PATH/guides/ +``` + +For each guide that references changed code: +1. Read the full guide +2. Update class names, parameter names, import paths, and code examples that are now incorrect +3. **Don't rewrite prose** — only fix the specific references that changed +4. Leave guides alone if they reference the service generally but don't use any changed APIs + +Guide directories: +- `guides/learn/` — conceptual tutorials (pipeline, LLM, STT, TTS, etc.) +- `guides/fundamentals/` — practical how-tos (metrics, recording, transcripts, etc.) +- `guides/features/` — feature-specific guides (Gemini Live, OpenAI audio, WhatsApp, etc.) +- `guides/telephony/` — telephony integration guides (Twilio, Plivo, Telnyx, etc.) + +### Step 8: Handle unmapped files + +After processing all mapped pairs, report any source files that: +- Had no doc page mapping (neither tier 1, 2, nor 3) +- Are not marked as "(skip)" in the tier-1 table + +For each unmapped file, tell the user: +- The source file path +- The main class(es) it defines +- Whether a new doc page should be created + +If the user wants a new page, create it using this template structure: +``` +--- +title: "Service Name" +description: "Brief description" +--- + +## Overview + +[Description from class docstring or source analysis] + + + [Cards for API reference and examples if available] + + +## Installation + +```bash +pip install "pipecat-ai[package-name]" +``` + +## Prerequisites + +[Environment variables and account setup] + +## Configuration + +[ParamField entries for constructor params] + +## InputParams + +[Table of InputParams fields, if the service has them] + +## Usage + +### Basic Setup + +```python +[Minimal working example] +``` + +## Notes + +[Important caveats] + +## Event Handlers + +[Event table and example code] +``` + +### Step 9: Output summary + +After all edits are complete, print a summary: + +``` +## Documentation Updates + +### Updated reference pages +- `server/services/stt/deepgram.mdx` — Updated Configuration (added `new_param`), InputParams (updated `language` default) +- `server/services/tts/elevenlabs.mdx` — Updated Event Handlers (added `on_connected`) + +### Updated guides +- `guides/learn/speech-to-text.mdx` — Updated code example (renamed `old_param` → `new_param`) + +### Unmapped source files +- `src/pipecat/services/newprovider/tts.py` — NewProviderTTSService (no doc page exists) + +### Skipped files +- `src/pipecat/services/ai_service.py` — internal base class +``` + +## Guidelines + +- **Be conservative** — only change what the diff warrants. Don't "improve" docs beyond what changed in source. +- **Read before editing** — always read the full doc page before making changes so you understand the existing structure. +- **Preserve voice** — match the writing style of the existing doc page, don't impose a different tone. +- **One PR at a time** — this skill operates on the current branch's diff against main. Don't look at other branches. +- **Parallel analysis** — when multiple source files map to different doc pages, analyze and edit them in parallel for efficiency. +- **Shared source files** — files like `services/google/google.py` are shared bases. Check which services import from them and update all affected doc pages. + +## Checklist + +Before finishing, verify: + +- [ ] All changed source files were checked against the mapping table +- [ ] Each doc page edit matches the actual source code change (not guessed) +- [ ] No content was removed unless the corresponding source was removed +- [ ] New parameters have accurate types and defaults from source +- [ ] Formatting matches the existing page style +- [ ] Guides referencing changed APIs were checked and updated +- [ ] Unmapped files were reported to the user diff --git a/.claude/skills/update-docs/SOURCE_DOC_MAPPING.md b/.claude/skills/update-docs/SOURCE_DOC_MAPPING.md new file mode 100644 index 000000000..d2e200be7 --- /dev/null +++ b/.claude/skills/update-docs/SOURCE_DOC_MAPPING.md @@ -0,0 +1,79 @@ +# Source-to-Doc Mapping + +Maps pipecat source files to their documentation pages. Source paths are relative to `src/pipecat/`. Doc paths are relative to `DOCS_PATH`. + +## Name mismatches + +These source paths don't follow the standard `services/{provider}/{type}.py` → `server/services/{type}/{provider}.mdx` pattern. + +| Source path | Doc page | +|---|---| +| `services/google/llm.py` | `server/services/llm/gemini.mdx` | +| `services/google/llm_vertex.py` | `server/services/llm/google-vertex.mdx` | +| `services/google/google.py` | (shared base — check which services use it) | +| `services/google/gemini_live/**` | `server/services/s2s/gemini-live.mdx` | +| `services/google/gemini_live/llm_vertex.py` | `server/services/s2s/gemini-live-vertex.mdx` | +| `services/aws_nova_sonic/**` | `server/services/s2s/aws.mdx` | +| `services/ultravox/**` | `server/services/s2s/ultravox.mdx` | +| `services/grok/realtime/**` | `server/services/s2s/grok.mdx` | +| `services/openai/realtime/**` | `server/services/s2s/openai.mdx` | +| `processors/frameworks/rtvi.py` | `server/frameworks/rtvi/rtvi-processor.mdx` and `server/frameworks/rtvi/rtvi-observer.mdx` | +| `processors/transcript_processor.py` | `server/utilities/transcript-processor.mdx` | +| `processors/user_idle_processor.py` | `server/utilities/user-idle-processor.mdx` | +| `processors/idle_frame_processor.py` | `server/pipeline/pipeline-idle-detection.mdx` | +| `pipeline/task.py` | `server/pipeline/pipeline-task.mdx` | +| `runner/run.py` | `server/utilities/runner/guide.mdx` | + +## Skip list + +These files should never trigger doc updates. + +| Pattern | Reason | +|---|---| +| `services/ai_service.py` | Internal base class | +| `services/stt_service.py` | Internal base class | +| `services/tts_service.py` | Internal base class | +| `services/llm_service.py` | Internal base class | +| `services/websocket_service.py` | Internal base class | +| `services/openai_realtime_beta/**` | Deprecated | +| `services/openai_realtime/**` | Deprecated | +| `services/gemini_multimodal_live/**` | Deprecated | +| `services/aws/agent_core.py` | Internal | +| `services/aws/sagemaker/**` | No doc page | +| `transports/base_transport.py` | Internal base class | +| `transports/base_input.py` | Internal base class | +| `transports/base_output.py` | Internal base class | +| `transports/websocket/client.py` | No doc page | +| `serializers/base_serializer.py` | Internal base class | +| `serializers/protobuf.py` | Internal | +| `processors/audio/**` | Internal | +| `pipeline/pipeline.py` | Core architecture, not a service doc | + +## Pattern matching + +For files not in the tables above, apply these patterns. Convert underscores to hyphens in provider names for doc filenames. + +| Source pattern | Doc pattern | +|---|---| +| `services/{provider}/stt*.py` | `server/services/stt/{provider}.mdx` | +| `services/{provider}/tts*.py` | `server/services/tts/{provider}.mdx` | +| `services/{provider}/llm*.py` | `server/services/llm/{provider}.mdx` | +| `services/{provider}/image*.py` | `server/services/image-generation/{provider}.mdx` | +| `services/{provider}/video*.py` | `server/services/video/{provider}.mdx` | +| `services/{provider}/realtime/**` | `server/services/s2s/{provider}.mdx` | +| `transports/{name}/**` | `server/services/transport/{name}.mdx` | +| `serializers/{name}.py` | `server/services/serializers/{name}.mdx` | +| `observers/**` | `server/utilities/observers/` (match by class name) | +| `audio/vad/**` | `server/utilities/audio/` (match by class name) | +| `audio/filters/**` | `server/utilities/audio/` (match by class name) | +| `audio/mixers/**` | `server/utilities/audio/` (match by class name) | +| `processors/filters/**` | `server/utilities/filters/` (match by class name) | + +If the doc file doesn't exist at the resolved path, the file is **unmapped**. + +## Search fallback + +For files that don't match any table or pattern above: +1. Extract the main class name(s) from the source file +2. Search the docs directory for that class name: `grep -r "ClassName" DOCS_PATH/server/` +3. If found in a doc page, use that as the mapping From e50b138ab21da65fad3182c91d66a286054d6615 Mon Sep 17 00:00:00 2001 From: Mark Backman Date: Thu, 12 Feb 2026 22:03:55 -0500 Subject: [PATCH 0480/1060] Fix double execution of service functions when tracing errors occur The outer try/except in each service decorator caught both tracing setup errors and application errors from the wrapped function. If the function itself raised (e.g. LLM rate limit, TTS timeout), the exception was caught and the function was called a second time. Fix by tracking whether the original function was called via a fn_called flag. If the function was already called, re-raise the exception instead of falling back to untraced re-execution. --- .../utils/tracing/service_decorators.py | 76 +++++++++++-------- 1 file changed, 44 insertions(+), 32 deletions(-) diff --git a/src/pipecat/utils/tracing/service_decorators.py b/src/pipecat/utils/tracing/service_decorators.py index 0fd939162..968fe8e8a 100644 --- a/src/pipecat/utils/tracing/service_decorators.py +++ b/src/pipecat/utils/tracing/service_decorators.py @@ -230,19 +230,21 @@ def traced_tts(func: Optional[Callable] = None, *, name: Optional[str] = None) - @functools.wraps(f) async def gen_wrapper(self, text, *args, **kwargs): - try: - # Check if tracing is enabled for this service instance - if not getattr(self, "_tracing_enabled", False): - async for item in f(self, text, *args, **kwargs): - yield item - return + if not getattr(self, "_tracing_enabled", False): + async for item in f(self, text, *args, **kwargs): + yield item + return + fn_called = False + try: async with tracing_context(self, text): + fn_called = True async for item in f(self, text, *args, **kwargs): yield item except Exception as e: + if fn_called: + raise logging.error(f"Error in TTS tracing (continuing without tracing): {e}") - # If tracing fails, fall back to the original function async for item in f(self, text, *args, **kwargs): yield item @@ -251,16 +253,18 @@ def traced_tts(func: Optional[Callable] = None, *, name: Optional[str] = None) - @functools.wraps(f) async def wrapper(self, text, *args, **kwargs): - try: - # Check if tracing is enabled for this service instance - if not getattr(self, "_tracing_enabled", False): - return await f(self, text, *args, **kwargs) + if not getattr(self, "_tracing_enabled", False): + return await f(self, text, *args, **kwargs) + fn_called = False + try: async with tracing_context(self, text): + fn_called = True return await f(self, text, *args, **kwargs) except Exception as e: + if fn_called: + raise logging.error(f"Error in TTS tracing (continuing without tracing): {e}") - # If tracing fails, fall back to the original function return await f(self, text, *args, **kwargs) return wrapper @@ -293,11 +297,11 @@ def traced_stt(func: Optional[Callable] = None, *, name: Optional[str] = None) - def decorator(f): @functools.wraps(f) async def wrapper(self, transcript, is_final, language=None): - try: - # Check if tracing is enabled for this service instance - if not getattr(self, "_tracing_enabled", False): - return await f(self, transcript, is_final, language) + if not getattr(self, "_tracing_enabled", False): + return await f(self, transcript, is_final, language) + fn_called = False + try: service_class_name = self.__class__.__name__ span_name = "stt" @@ -332,14 +336,16 @@ def traced_stt(func: Optional[Callable] = None, *, name: Optional[str] = None) - ) # Call the original function + fn_called = True return await f(self, transcript, is_final, language) except Exception as e: # Log any exception but don't disrupt the main flow logging.warning(f"Error in STT transcription tracing: {e}") raise except Exception as e: + if fn_called: + raise logging.error(f"Error in STT tracing (continuing without tracing): {e}") - # If tracing fails, fall back to the original function return await f(self, transcript, is_final, language) return wrapper @@ -374,11 +380,11 @@ def traced_llm(func: Optional[Callable] = None, *, name: Optional[str] = None) - def decorator(f): @functools.wraps(f) async def wrapper(self, context, *args, **kwargs): - try: - # Check if tracing is enabled for this service instance - if not getattr(self, "_tracing_enabled", False): - return await f(self, context, *args, **kwargs) + if not getattr(self, "_tracing_enabled", False): + return await f(self, context, *args, **kwargs) + fn_called = False + try: service_class_name = self.__class__.__name__ span_name = "llm" @@ -525,6 +531,7 @@ def traced_llm(func: Optional[Callable] = None, *, name: Optional[str] = None) - # Don't raise - let the function execute anyway # Run function with modified push_frame to capture the output + fn_called = True result = await f(self, context, *args, **kwargs) # Add aggregated output after function completes, if available @@ -550,8 +557,9 @@ def traced_llm(func: Optional[Callable] = None, *, name: Optional[str] = None) - if ttfb is not None: current_span.set_attribute("metrics.ttfb", ttfb) except Exception as e: + if fn_called: + raise logging.error(f"Error in LLM tracing (continuing without tracing): {e}") - # If tracing fails, fall back to the original function return await f(self, context, *args, **kwargs) return wrapper @@ -583,11 +591,11 @@ def traced_gemini_live(operation: str) -> Callable: def decorator(func): @functools.wraps(func) async def wrapper(self, *args, **kwargs): - try: - # Check if tracing is enabled for this service instance - if not getattr(self, "_tracing_enabled", False): - return await func(self, *args, **kwargs) + if not getattr(self, "_tracing_enabled", False): + return await func(self, *args, **kwargs) + fn_called = False + try: service_class_name = self.__class__.__name__ span_name = f"{operation}" @@ -849,6 +857,7 @@ def traced_gemini_live(operation: str) -> Callable: current_span.set_attribute("metrics.ttfb", ttfb) # Run the original function + fn_called = True result = await func(self, *args, **kwargs) return result @@ -859,8 +868,9 @@ def traced_gemini_live(operation: str) -> Callable: raise except Exception as e: + if fn_called: + raise logging.error(f"Error in Gemini Live tracing (continuing without tracing): {e}") - # If tracing fails, fall back to the original function return await func(self, *args, **kwargs) return wrapper @@ -889,11 +899,11 @@ def traced_openai_realtime(operation: str) -> Callable: def decorator(func): @functools.wraps(func) async def wrapper(self, *args, **kwargs): - try: - # Check if tracing is enabled for this service instance - if not getattr(self, "_tracing_enabled", False): - return await func(self, *args, **kwargs) + if not getattr(self, "_tracing_enabled", False): + return await func(self, *args, **kwargs) + fn_called = False + try: service_class_name = self.__class__.__name__ span_name = f"{operation}" @@ -1072,6 +1082,7 @@ def traced_openai_realtime(operation: str) -> Callable: current_span.set_attribute("metrics.ttfb", ttfb) # Run the original function + fn_called = True result = await func(self, *args, **kwargs) return result @@ -1082,8 +1093,9 @@ def traced_openai_realtime(operation: str) -> Callable: raise except Exception as e: + if fn_called: + raise logging.error(f"Error in OpenAI Realtime tracing (continuing without tracing): {e}") - # If tracing fails, fall back to the original function return await func(self, *args, **kwargs) return wrapper From a5f95acaf59e3e8a526362e65cc546b970048257 Mon Sep 17 00:00:00 2001 From: Mark Backman Date: Thu, 12 Feb 2026 22:07:09 -0500 Subject: [PATCH 0481/1060] Add changelog for PR #3735 --- changelog/3735.fixed.md | 1 + 1 file changed, 1 insertion(+) create mode 100644 changelog/3735.fixed.md diff --git a/changelog/3735.fixed.md b/changelog/3735.fixed.md new file mode 100644 index 000000000..02de936c7 --- /dev/null +++ b/changelog/3735.fixed.md @@ -0,0 +1 @@ +- Fixed tracing service decorators executing the wrapped function twice when the function itself raised an exception (e.g., LLM rate limit, TTS timeout). From f7af9f1efd992ddc6d7564278a120540b669cc53 Mon Sep 17 00:00:00 2001 From: Mark Backman Date: Fri, 13 Feb 2026 13:14:45 -0500 Subject: [PATCH 0482/1060] Broaden /update-docs scope to detect missing doc sections --- .claude/skills/update-docs/SKILL.md | 10 +++++----- .claude/skills/update-docs/SOURCE_DOC_MAPPING.md | 4 ++-- 2 files changed, 7 insertions(+), 7 deletions(-) diff --git a/.claude/skills/update-docs/SKILL.md b/.claude/skills/update-docs/SKILL.md index f70febf96..f24d56f00 100644 --- a/.claude/skills/update-docs/SKILL.md +++ b/.claude/skills/update-docs/SKILL.md @@ -146,17 +146,17 @@ Guide directories: - `guides/features/` — feature-specific guides (Gemini Live, OpenAI audio, WhatsApp, etc.) - `guides/telephony/` — telephony integration guides (Twilio, Plivo, Telnyx, etc.) -### Step 8: Handle unmapped files +### Step 8: Identify doc gaps -After processing all mapped pairs, report any source files that: -- Had no doc page mapping (neither tier 1, 2, nor 3) -- Are not marked as "(skip)" in the tier-1 table +After processing all mapped pairs, check for two kinds of gaps: -For each unmapped file, tell the user: +**Missing pages**: Source files that had no doc page mapping (neither tier 1, 2, nor 3) and are not marked as "(skip)". For each, tell the user: - The source file path - The main class(es) it defines - Whether a new doc page should be created +**Missing sections**: Mapped doc pages that are missing standard sections compared to the source. For example, a transport page with no Configuration section, or a service page with no InputParams table when the source defines `InputParams(BaseModel)`. Flag these and offer to add the missing sections. + If the user wants a new page, create it using this template structure: ``` --- diff --git a/.claude/skills/update-docs/SOURCE_DOC_MAPPING.md b/.claude/skills/update-docs/SOURCE_DOC_MAPPING.md index d2e200be7..03e6cbbf1 100644 --- a/.claude/skills/update-docs/SOURCE_DOC_MAPPING.md +++ b/.claude/skills/update-docs/SOURCE_DOC_MAPPING.md @@ -22,7 +22,8 @@ These source paths don't follow the standard `services/{provider}/{type}.py` → | `processors/user_idle_processor.py` | `server/utilities/user-idle-processor.mdx` | | `processors/idle_frame_processor.py` | `server/pipeline/pipeline-idle-detection.mdx` | | `pipeline/task.py` | `server/pipeline/pipeline-task.mdx` | -| `runner/run.py` | `server/utilities/runner/guide.mdx` | +| `pipeline/runner.py` | `server/utilities/runner/guide.mdx` | +| `transports/base_transport.py` | `server/services/transport/transport-params.mdx` | ## Skip list @@ -40,7 +41,6 @@ These files should never trigger doc updates. | `services/gemini_multimodal_live/**` | Deprecated | | `services/aws/agent_core.py` | Internal | | `services/aws/sagemaker/**` | No doc page | -| `transports/base_transport.py` | Internal base class | | `transports/base_input.py` | Internal base class | | `transports/base_output.py` | Internal base class | | `transports/websocket/client.py` | No doc page | From 2489c76bc6c3127964b2b2a81ca2799daf698226 Mon Sep 17 00:00:00 2001 From: filipi87 Date: Fri, 13 Feb 2026 16:43:25 -0300 Subject: [PATCH 0483/1060] Using the latest version of pipecat-ai-small-webrtc-prebuilt. --- pyproject.toml | 2 +- uv.lock | 8 ++++---- 2 files changed, 5 insertions(+), 5 deletions(-) diff --git a/pyproject.toml b/pyproject.toml index 35b95f7b4..71baec1f1 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -105,7 +105,7 @@ remote-smart-turn = [] resembleai = [ "pipecat-ai[websockets-base]" ] rime = [ "pipecat-ai[websockets-base]" ] riva = [ "pipecat-ai[nvidia]" ] -runner = [ "python-dotenv>=1.0.0,<2.0.0", "uvicorn>=0.32.0,<1.0.0", "fastapi>=0.115.6,<0.128.0", "pipecat-ai-small-webrtc-prebuilt>=2.1.0"] +runner = [ "python-dotenv>=1.0.0,<2.0.0", "uvicorn>=0.32.0,<1.0.0", "fastapi>=0.115.6,<0.128.0", "pipecat-ai-small-webrtc-prebuilt>=2.2.0"] sagemaker = ["aws_sdk_sagemaker_runtime_http2; python_version>='3.12'"] sambanova = [] sarvam = [ "sarvamai==0.1.21", "pipecat-ai[websockets-base]" ] diff --git a/uv.lock b/uv.lock index 8a5eadbe7..0a3206c0f 100644 --- a/uv.lock +++ b/uv.lock @@ -4734,7 +4734,7 @@ requires-dist = [ { name = "pipecat-ai", extras = ["websockets-base"], marker = "extra == 'ultravox'" }, { name = "pipecat-ai", extras = ["websockets-base"], marker = "extra == 'websocket'" }, { name = "pipecat-ai-krisp", marker = "extra == 'krisp'", specifier = "~=0.4.0" }, - { name = "pipecat-ai-small-webrtc-prebuilt", marker = "extra == 'runner'", specifier = ">=2.1.0" }, + { name = "pipecat-ai-small-webrtc-prebuilt", marker = "extra == 'runner'", specifier = ">=2.2.0" }, { name = "piper-tts", marker = "extra == 'piper'", specifier = ">=1.3.0,<2" }, { name = "protobuf", specifier = "~=5.29.6" }, { name = "pvkoala", marker = "extra == 'koala'", specifier = "~=2.0.3" }, @@ -4805,14 +4805,14 @@ sdist = { url = "https://files.pythonhosted.org/packages/1d/37/0f1d11d1dc33234a3 [[package]] name = "pipecat-ai-small-webrtc-prebuilt" -version = "2.1.0" +version = "2.2.0" source = { registry = "https://pypi.org/simple" } dependencies = [ { name = "fastapi", extra = ["all"] }, ] -sdist = { url = "https://files.pythonhosted.org/packages/4a/8b/c945a27503560d50c56f497e43209f43c81616ede5d3d2b38eeb4044dbbc/pipecat_ai_small_webrtc_prebuilt-2.1.0.tar.gz", hash = "sha256:c883304a159dee01eec74b162e51352b32c362ca19d281226a71d92b5ba1c600", size = 596971, upload-time = "2026-02-05T17:01:08.074Z" } +sdist = { url = "https://files.pythonhosted.org/packages/9a/9f/b06cc0e2eaeda811959c216dade3ed38c30d20e6327a2b22f80125072c5a/pipecat_ai_small_webrtc_prebuilt-2.2.0.tar.gz", hash = "sha256:5d73fe619225b97e383863a901060d1c986f088f4de004477856b085aaba76c4", size = 466005, upload-time = "2026-02-13T19:28:54.626Z" } wheels = [ - { url = "https://files.pythonhosted.org/packages/8e/f6/5754d86d513822fb4466549eb6bca05c7246676f1b5b199c9646a5475182/pipecat_ai_small_webrtc_prebuilt-2.1.0-py3-none-any.whl", hash = "sha256:0882d147f69d8cc07397ee68b75c554f4d2d75d8023207e7fb86760616bc58aa", size = 597535, upload-time = "2026-02-05T17:01:06.622Z" }, + { url = "https://files.pythonhosted.org/packages/26/71/20a015cea25dc57129ed6426fdf37a09aefe37f4dd60e3a42ba2d9e3bd1b/pipecat_ai_small_webrtc_prebuilt-2.2.0-py3-none-any.whl", hash = "sha256:e7917d23f51e5418667541a3e241b2de28a43eea35a5a9486721be3da04e719d", size = 466257, upload-time = "2026-02-13T19:28:53.188Z" }, ] [[package]] From 8a4ab611bebc81091aedee94a8218de92083b092 Mon Sep 17 00:00:00 2001 From: Paul Kompfner Date: Wed, 11 Feb 2026 10:50:11 -0500 Subject: [PATCH 0484/1060] Broad service settings refactor, with the primary aim of making service settings discoverable and strongly-typed. Service settings can be updated at runtime with `*UpdateSettingsFrame`s. MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit Does not (yet) touch `InputParams`, to avoid scope creep and touching something currently part of the public API. But there is a lot of overlap between `*Settings` object fields and `InputParams` fields. Other than discoverability/typing, these are some other improvements brought by this refactor: - There is now a single code path (see `_update_settings_from_typed`) where services can respond to settings changes (by, say, reconnecting if needed), improving maintainability and guaranteeing one and only one reconnection no matter which settings changed - `set_language`/`set_model`/`set_voice`—which we're assuming are usable as public methods, though *not* recommended over `*UpdateSettingsFrame`—all use the same code path as settings updates. They're also now all consistent in that, if a service needs to respond to a change (by, say, reconnecting if needed), any of these methods will kick off that process. Note that this is technically a behavior change. - Several services now properly react to changed settings by reconnecting: - `AWSTranscribeSTTService` - `AzureSTTService` - `SonioxSTTService` - `GladiaSTTService` - `SpeechmaticsSTTService` - `AssemblyAISTTService` - `CartesiaSTTService` - `FishAudioTTSService` (would previously only reconnect when `model` changed) - `GoogleSTTService` - `SpeechmaticsSTTService` (which previously only handled *some* settings updates through a nonstandard public `update_params` method) - `GradiumSTTService` - `NvidiaSegmentedSTTService` (which previously only handled changes to language) - Bookkeeping across various services has been reduced, mostly by deduping ivars; the `self._settings` ivar is treated as the source of truth NOTE: I pretty much guarantee that there are services missed in this PR in terms of bringing to consistency with how updates are handled (like whether changes in certain fields trigger reconnects when they need to). We can squash remaining inconsistencies as we stumble onto them, service by service. The goal here is to get things *mostly* in order, and establish the infrastructure and patterns we'll need going forward. --- .claude/skills/cleanup/SKILL.md | 2 +- .../35-pattern-pair-voice-switching.py | 2 +- src/pipecat/frames/frames.py | 11 +- src/pipecat/services/ai_service.py | 41 ++- src/pipecat/services/anthropic/llm.py | 77 +++-- src/pipecat/services/assemblyai/stt.py | 60 +++- src/pipecat/services/asyncai/tts.py | 67 ++-- src/pipecat/services/aws/llm.py | 56 ++-- src/pipecat/services/aws/stt.py | 73 +++-- src/pipecat/services/aws/tts.py | 60 ++-- src/pipecat/services/azure/stt.py | 52 ++- src/pipecat/services/azure/tts.py | 87 +++-- src/pipecat/services/camb/tts.py | 33 +- src/pipecat/services/cartesia/stt.py | 41 ++- src/pipecat/services/cartesia/tts.py | 153 +++++---- src/pipecat/services/cerebras/llm.py | 10 +- src/pipecat/services/deepgram/stt.py | 85 +++-- .../services/deepgram/stt_sagemaker.py | 83 +++-- src/pipecat/services/deepgram/tts.py | 37 ++- src/pipecat/services/deepseek/llm.py | 12 +- src/pipecat/services/elevenlabs/stt.py | 203 +++++++----- src/pipecat/services/elevenlabs/tts.py | 272 +++++++++++----- src/pipecat/services/fal/stt.py | 60 ++-- src/pipecat/services/fireworks/llm.py | 12 +- src/pipecat/services/fish/tts.py | 81 +++-- src/pipecat/services/gladia/stt.py | 86 +++-- .../services/google/gemini_live/llm.py | 117 ++++--- src/pipecat/services/google/llm.py | 52 +-- src/pipecat/services/google/stt.py | 241 +++++++++----- src/pipecat/services/google/tts.py | 201 +++++++----- src/pipecat/services/gradium/stt.py | 46 ++- src/pipecat/services/gradium/tts.py | 47 +-- src/pipecat/services/grok/realtime/llm.py | 65 ++-- src/pipecat/services/groq/tts.py | 33 +- src/pipecat/services/hathora/stt.py | 35 +- src/pipecat/services/hathora/tts.py | 38 ++- src/pipecat/services/hume/tts.py | 4 +- src/pipecat/services/inworld/tts.py | 120 ++++--- src/pipecat/services/kokoro/tts.py | 19 ++ src/pipecat/services/llm_service.py | 13 + src/pipecat/services/lmnt/tts.py | 29 +- src/pipecat/services/minimax/tts.py | 118 +++++-- src/pipecat/services/mistral/llm.py | 16 +- src/pipecat/services/neuphonic/tts.py | 61 ++-- src/pipecat/services/nvidia/stt.py | 128 ++++---- src/pipecat/services/nvidia/tts.py | 2 +- src/pipecat/services/openai/base_llm.py | 62 ++-- src/pipecat/services/openai/realtime/llm.py | 60 +++- src/pipecat/services/openai/stt.py | 51 ++- src/pipecat/services/openai/tts.py | 44 ++- .../services/openai_realtime_beta/openai.py | 51 ++- src/pipecat/services/perplexity/llm.py | 20 +- src/pipecat/services/playht/tts.py | 88 +++-- src/pipecat/services/resembleai/tts.py | 38 ++- src/pipecat/services/rime/tts.py | 279 +++++++++------- src/pipecat/services/sambanova/llm.py | 10 +- src/pipecat/services/sarvam/stt.py | 145 ++++++--- src/pipecat/services/sarvam/tts.py | 187 ++++++++--- src/pipecat/services/settings.py | 297 +++++++++++++++++ src/pipecat/services/soniox/stt.py | 76 ++++- src/pipecat/services/speechmatics/stt.py | 245 +++++++++++--- src/pipecat/services/speechmatics/tts.py | 2 +- src/pipecat/services/stt_service.py | 52 ++- src/pipecat/services/tts_service.py | 72 +++- src/pipecat/services/ultravox/llm.py | 24 +- src/pipecat/services/whisper/base_stt.py | 61 ++-- src/pipecat/services/whisper/stt.py | 79 +++-- src/pipecat/services/xtts/tts.py | 32 +- tests/test_settings.py | 308 ++++++++++++++++++ 69 files changed, 3943 insertions(+), 1481 deletions(-) create mode 100644 src/pipecat/services/settings.py create mode 100644 tests/test_settings.py diff --git a/.claude/skills/cleanup/SKILL.md b/.claude/skills/cleanup/SKILL.md index f7dd6ea98..c0f4945b7 100644 --- a/.claude/skills/cleanup/SKILL.md +++ b/.claude/skills/cleanup/SKILL.md @@ -293,7 +293,7 @@ class NewTTSService(TTSService): """ super().__init__(**kwargs) self._api_key = api_key - self.set_voice(voice) + self._voice_id = voice ``` --- diff --git a/examples/foundational/35-pattern-pair-voice-switching.py b/examples/foundational/35-pattern-pair-voice-switching.py index 4b269ac3e..cacc04459 100644 --- a/examples/foundational/35-pattern-pair-voice-switching.py +++ b/examples/foundational/35-pattern-pair-voice-switching.py @@ -117,7 +117,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): # First flush any existing audio to finish the current context await tts.flush_audio() # Then set the new voice - tts.set_voice(VOICE_IDS[voice_name]) + await tts.set_voice(VOICE_IDS[voice_name]) logger.info(f"Switched to {voice_name} voice") else: logger.warning(f"Unknown voice: {voice_name}") diff --git a/src/pipecat/frames/frames.py b/src/pipecat/frames/frames.py index 5634d79ee..dd12929b9 100644 --- a/src/pipecat/frames/frames.py +++ b/src/pipecat/frames/frames.py @@ -42,6 +42,7 @@ from pipecat.utils.utils import obj_count, obj_id if TYPE_CHECKING: from pipecat.processors.aggregators.llm_context import LLMContext, NotGiven from pipecat.processors.frame_processor import FrameProcessor + from pipecat.services.settings import ServiceSettings class DeprecatedKeypadEntry: @@ -2112,13 +2113,17 @@ class TTSStoppedFrame(ControlFrame): class ServiceUpdateSettingsFrame(ControlFrame): """Base frame for updating service settings. - A control frame containing a request to update service settings. + Supports both the legacy ``settings`` dict and the new typed ``update`` + object. When both are provided, ``update`` takes precedence. Parameters: - settings: Dictionary of setting name to value mappings. + settings: Dictionary of setting name to value mappings (legacy). + update: Typed :class:`~pipecat.services.settings.ServiceSettings` + object describing the delta to apply. """ - settings: Mapping[str, Any] + settings: Mapping[str, Any] = field(default_factory=dict) + update: Optional["ServiceSettings"] = None @dataclass diff --git a/src/pipecat/services/ai_service.py b/src/pipecat/services/ai_service.py index c03ab9d0e..97b7b6443 100644 --- a/src/pipecat/services/ai_service.py +++ b/src/pipecat/services/ai_service.py @@ -10,7 +10,7 @@ Provides the foundation for all AI services in the Pipecat framework, including model management, settings handling, and frame processing lifecycle methods. """ -from typing import Any, AsyncGenerator, Dict, Mapping +from typing import Any, AsyncGenerator, Dict, Mapping, Set from loguru import logger @@ -23,6 +23,7 @@ from pipecat.frames.frames import ( ) from pipecat.metrics.metrics import MetricsData from pipecat.processors.frame_processor import FrameDirection, FrameProcessor +from pipecat.services.settings import ServiceSettings class AIService(FrameProcessor): @@ -42,7 +43,7 @@ class AIService(FrameProcessor): """ super().__init__(**kwargs) self._model_name: str = "" - self._settings: Dict[str, Any] = {} + self._settings: Dict[str, Any] | ServiceSettings = {} self._session_properties: Dict[str, Any] = {} @property @@ -135,6 +136,42 @@ class AIService(FrameProcessor): else: logger.warning(f"Unknown setting for {self.name} service: {key}") + async def _update_settings_from_typed(self, update: ServiceSettings) -> Set[str]: + """Apply a typed settings update and return the set of changed field names. + + If ``_settings`` is a :class:`ServiceSettings` object, the update is + applied to it and the changed-field set is returned. The ``model`` + field is handled specially: when it changes, ``set_model_name`` is + called. + + Services that have been migrated to typed settings should override + this method (calling ``super()``) to react to specific changed fields + (e.g. reconnect on voice change). + + Args: + update: A typed settings delta. + + Returns: + Set of field names whose values actually changed. + """ + if not isinstance(self._settings, ServiceSettings): + logger.warning( + f"{self.name}: received typed settings update but _settings " + f"is not a ServiceSettings — falling back to dict-based update" + ) + await self._update_settings(update.to_dict()) + return set() + + changed = self._settings.apply_update(update) + + if "model" in changed: + self.set_model_name(self._settings.model) + + if changed: + logger.info(f"{self.name}: updated settings fields: {changed}") + + return changed + async def process_frame(self, frame: Frame, direction: FrameDirection): """Process frames and handle service lifecycle. diff --git a/src/pipecat/services/anthropic/llm.py b/src/pipecat/services/anthropic/llm.py index a21296fe3..36ee104f5 100644 --- a/src/pipecat/services/anthropic/llm.py +++ b/src/pipecat/services/anthropic/llm.py @@ -16,8 +16,8 @@ import copy import io import json import re -from dataclasses import dataclass -from typing import Any, Dict, List, Literal, Optional, Union +from dataclasses import dataclass, field +from typing import Any, ClassVar, Dict, List, Literal, Optional, Union import httpx from loguru import logger @@ -42,7 +42,6 @@ from pipecat.frames.frames import ( LLMThoughtEndFrame, LLMThoughtStartFrame, LLMThoughtTextFrame, - LLMUpdateSettingsFrame, UserImageRawFrame, ) from pipecat.metrics.metrics import LLMTokenUsage @@ -59,6 +58,8 @@ from pipecat.processors.aggregators.openai_llm_context import ( ) from pipecat.processors.frame_processor import FrameDirection from pipecat.services.llm_service import FunctionCallFromLLM, LLMService +from pipecat.services.settings import NOT_GIVEN as _NOT_GIVEN +from pipecat.services.settings import LLMSettings from pipecat.utils.tracing.service_decorators import traced_llm try: @@ -69,6 +70,19 @@ except ModuleNotFoundError as e: raise Exception(f"Missing module: {e}") +@dataclass +class AnthropicLLMSettings(LLMSettings): + """Typed settings for Anthropic LLM services. + + Parameters: + enable_prompt_caching: Whether to enable prompt caching. + thinking: Extended thinking configuration. + """ + + enable_prompt_caching: Any = field(default_factory=lambda: _NOT_GIVEN) + thinking: Any = field(default_factory=lambda: _NOT_GIVEN) + + @dataclass class AnthropicContextAggregatorPair: """Pair of context aggregators for Anthropic conversations. @@ -210,9 +224,10 @@ class AnthropicLLMService(LLMService): self.set_model_name(model) self._retry_timeout_secs = retry_timeout_secs self._retry_on_timeout = retry_on_timeout - self._settings = { - "max_tokens": params.max_tokens, - "enable_prompt_caching": ( + self._settings = AnthropicLLMSettings( + model=model, + max_tokens=params.max_tokens, + enable_prompt_caching=( params.enable_prompt_caching if params.enable_prompt_caching is not None else ( @@ -221,12 +236,12 @@ class AnthropicLLMService(LLMService): else False ) ), - "temperature": params.temperature, - "top_k": params.top_k, - "top_p": params.top_p, - "thinking": params.thinking, - "extra": params.extra if isinstance(params.extra, dict) else {}, - } + temperature=params.temperature, + top_k=params.top_k, + top_p=params.top_p, + thinking=params.thinking, + extra=params.extra if isinstance(params.extra, dict) else {}, + ) def can_generate_metrics(self) -> bool: """Check if this service can generate usage metrics. @@ -280,7 +295,7 @@ class AnthropicLLMService(LLMService): if isinstance(context, LLMContext): adapter: AnthropicLLMAdapter = self.get_llm_adapter() invocation_params = adapter.get_llm_invocation_params( - context, enable_prompt_caching=self._settings["enable_prompt_caching"] + context, enable_prompt_caching=self._settings.enable_prompt_caching ) messages = invocation_params["messages"] system = invocation_params["system"] @@ -294,20 +309,20 @@ class AnthropicLLMService(LLMService): # Build params using the same method as streaming completions params = { "model": self.model_name, - "max_tokens": max_tokens if max_tokens is not None else self._settings["max_tokens"], + "max_tokens": max_tokens if max_tokens is not None else self._settings.max_tokens, "stream": False, - "temperature": self._settings["temperature"], - "top_k": self._settings["top_k"], - "top_p": self._settings["top_p"], + "temperature": self._settings.temperature, + "top_k": self._settings.top_k, + "top_p": self._settings.top_p, "messages": messages, "system": system, "tools": tools, "betas": ["interleaved-thinking-2025-05-14"], } - if self._settings["thinking"]: - params["thinking"] = self._settings["thinking"].model_dump(exclude_unset=True) + if self._settings.thinking: + params["thinking"] = self._settings.thinking.model_dump(exclude_unset=True) - params.update(self._settings["extra"]) + params.update(self._settings.extra) # LLM completion response = await self._client.beta.messages.create(**params) @@ -358,14 +373,14 @@ class AnthropicLLMService(LLMService): if isinstance(context, LLMContext): adapter: AnthropicLLMAdapter = self.get_llm_adapter() params = adapter.get_llm_invocation_params( - context, enable_prompt_caching=self._settings["enable_prompt_caching"] + context, enable_prompt_caching=self._settings.enable_prompt_caching ) return params # Anthropic-specific context messages = ( context.get_messages_with_cache_control_markers() - if self._settings["enable_prompt_caching"] + if self._settings.enable_prompt_caching else context.messages ) return AnthropicLLMInvocationParams( @@ -408,21 +423,21 @@ class AnthropicLLMService(LLMService): params = { "model": self.model_name, - "max_tokens": self._settings["max_tokens"], + "max_tokens": self._settings.max_tokens, "stream": True, - "temperature": self._settings["temperature"], - "top_k": self._settings["top_k"], - "top_p": self._settings["top_p"], + "temperature": self._settings.temperature, + "top_k": self._settings.top_k, + "top_p": self._settings.top_p, } # Add thinking parameter if set - if self._settings["thinking"]: - params["thinking"] = self._settings["thinking"].model_dump(exclude_unset=True) + if self._settings.thinking: + params["thinking"] = self._settings.thinking.model_dump(exclude_unset=True) # Messages, system, tools params.update(params_from_context) - params.update(self._settings["extra"]) + params.update(self._settings.extra) # "Interleaved thinking" needed to allow thinking between sequences # of function calls, when extended thinking is enabled. @@ -576,11 +591,9 @@ class AnthropicLLMService(LLMService): # NOTE: LLMMessagesFrame is deprecated, so we don't support the newer universal # LLMContext with it context = AnthropicLLMContext.from_messages(frame.messages) - elif isinstance(frame, LLMUpdateSettingsFrame): - await self._update_settings(frame.settings) elif isinstance(frame, LLMEnablePromptCachingFrame): logger.debug(f"Setting enable prompt caching to: [{frame.enable}]") - self._settings["enable_prompt_caching"] = frame.enable + self._settings.enable_prompt_caching = frame.enable else: await self.push_frame(frame, direction) diff --git a/src/pipecat/services/assemblyai/stt.py b/src/pipecat/services/assemblyai/stt.py index 41a0ae2a0..278873fdf 100644 --- a/src/pipecat/services/assemblyai/stt.py +++ b/src/pipecat/services/assemblyai/stt.py @@ -12,6 +12,7 @@ WebSocket API for streaming audio transcription. import asyncio import json +from dataclasses import dataclass, field from typing import Any, AsyncGenerator, Dict, Optional from urllib.parse import urlencode @@ -29,6 +30,7 @@ from pipecat.frames.frames import ( VADUserStoppedSpeakingFrame, ) from pipecat.processors.frame_processor import FrameDirection +from pipecat.services.settings import NOT_GIVEN, STTSettings from pipecat.services.stt_latency import ASSEMBLYAI_TTFS_P99 from pipecat.services.stt_service import WebsocketSTTService from pipecat.transcriptions.language import Language @@ -52,6 +54,19 @@ except ModuleNotFoundError as e: raise Exception(f"Missing module: {e}") +@dataclass +class AssemblyAISTTSettings(STTSettings): + """Typed settings for the AssemblyAI STT service. + + See :class:`AssemblyAIConnectionParams` for detailed parameter descriptions. + + Parameters: + connection_params: Connection configuration parameters. + """ + + connection_params: AssemblyAIConnectionParams = field(default_factory=lambda: NOT_GIVEN) + + class AssemblyAISTTService(WebsocketSTTService): """AssemblyAI real-time speech-to-text service. @@ -96,9 +111,11 @@ class AssemblyAISTTService(WebsocketSTTService): ) self._api_key = api_key - self._language = language + self._settings: AssemblyAISTTSettings = AssemblyAISTTSettings( + language=language, + connection_params=connection_params, + ) self._api_endpoint_base_url = api_endpoint_base_url - self._connection_params = connection_params self._vad_force_turn_endpoint = vad_force_turn_endpoint self._termination_event = asyncio.Event() @@ -165,6 +182,35 @@ class AssemblyAISTTService(WebsocketSTTService): """ return True + async def _update_settings_from_typed(self, update: STTSettings) -> set[str]: + """Apply a typed settings update and reconnect if anything changed. + + Any change triggers a WebSocket reconnect since all connection + parameters are encoded in the WebSocket URL. + + Args: + update: A :class:`STTSettings` (or ``AssemblyAISTTSettings``) delta. + + Returns: + Set of field names whose values actually changed. + """ + changed = await super()._update_settings_from_typed(update) + + if not changed: + return changed + + # Re-apply manual turn mode config if vad_force_turn_endpoint is active + # and connection_params were updated. + if self._vad_force_turn_endpoint and "connection_params" in changed: + self._settings.connection_params = self._configure_manual_turn_mode( + self._settings.connection_params + ) + + await self._disconnect() + await self._connect() + + return changed + async def start(self, frame: StartFrame): """Start the speech-to-text service. @@ -239,7 +285,7 @@ class AssemblyAISTTService(WebsocketSTTService): def _build_ws_url(self) -> str: """Build WebSocket URL with query parameters using urllib.parse.urlencode.""" params = {} - for k, v in self._connection_params.model_dump().items(): + for k, v in self._settings.connection_params.model_dump().items(): if v is not None: if k == "keyterms_prompt": params[k] = json.dumps(v) @@ -415,18 +461,18 @@ class AssemblyAISTTService(WebsocketSTTService): if not message.transcript: return if message.end_of_turn and ( - not self._connection_params.formatted_finals or message.turn_is_formatted + not self._settings.connection_params.formatted_finals or message.turn_is_formatted ): await self.push_frame( TranscriptionFrame( message.transcript, self._user_id, time_now_iso8601(), - self._language, + self._settings.language, message, ) ) - await self._trace_transcription(message.transcript, True, self._language) + await self._trace_transcription(message.transcript, True, self._settings.language) await self.stop_processing_metrics() else: await self.push_frame( @@ -434,7 +480,7 @@ class AssemblyAISTTService(WebsocketSTTService): message.transcript, self._user_id, time_now_iso8601(), - self._language, + self._settings.language, message, ) ) diff --git a/src/pipecat/services/asyncai/tts.py b/src/pipecat/services/asyncai/tts.py index 4ff6c928d..aecf69a26 100644 --- a/src/pipecat/services/asyncai/tts.py +++ b/src/pipecat/services/asyncai/tts.py @@ -9,6 +9,7 @@ import asyncio import base64 import json +from dataclasses import dataclass, field from typing import AsyncGenerator, Optional import aiohttp @@ -27,6 +28,7 @@ from pipecat.frames.frames import ( TTSStoppedFrame, ) from pipecat.processors.frame_processor import FrameDirection +from pipecat.services.settings import NOT_GIVEN, TTSSettings from pipecat.services.tts_service import AudioContextTTSService, TTSService from pipecat.transcriptions.language import Language, resolve_language from pipecat.utils.tracing.service_decorators import traced_tts @@ -72,6 +74,21 @@ def language_to_async_language(language: Language) -> Optional[str]: return resolve_language(language, LANGUAGE_MAP, use_base_code=True) +@dataclass +class AsyncAITTSSettings(TTSSettings): + """Typed settings for Async AI TTS services. + + Parameters: + output_container: Audio container format (e.g. "raw"). + output_encoding: Audio encoding format (e.g. "pcm_s16le"). + output_sample_rate: Audio sample rate in Hz. + """ + + output_container: str = field(default_factory=lambda: NOT_GIVEN) + output_encoding: str = field(default_factory=lambda: NOT_GIVEN) + output_sample_rate: int = field(default_factory=lambda: NOT_GIVEN) + + class AsyncAITTSService(AudioContextTTSService): """Async TTS service with WebSocket streaming. @@ -131,19 +148,21 @@ class AsyncAITTSService(AudioContextTTSService): self._api_key = api_key self._api_version = version self._url = url - self._settings = { - "output_format": { + self._settings: AsyncAITTSSettings = AsyncAITTSSettings( + model=model, + voice=voice_id, + output_format={ "container": container, "encoding": encoding, "sample_rate": 0, }, - "language": self.language_to_service_language(params.language) + language=self.language_to_service_language(params.language) if params.language else None, - } + ) self.set_model_name(model) - self.set_voice(voice_id) + self._voice_id = voice_id self._receive_task = None self._keepalive_task = None @@ -179,7 +198,7 @@ class AsyncAITTSService(AudioContextTTSService): frame: The start frame containing initialization parameters. """ await super().start(frame) - self._settings["output_format"]["sample_rate"] = self.sample_rate + self._settings.output_sample_rate = self.sample_rate await self._connect() async def stop(self, frame: EndFrame): @@ -235,8 +254,12 @@ class AsyncAITTSService(AudioContextTTSService): init_msg = { "model_id": self._model_name, "voice": {"mode": "id", "id": self._voice_id}, - "output_format": self._settings["output_format"], - "language": self._settings["language"], + "output_format": { + "container": self._settings.output_container, + "encoding": self._settings.output_encoding, + "sample_rate": self._settings.output_sample_rate, + }, + "language": self._settings.language, } await self._get_websocket().send(json.dumps(init_msg)) @@ -454,17 +477,17 @@ class AsyncAIHttpTTSService(TTSService): self._api_key = api_key self._base_url = url self._api_version = version - self._settings = { - "output_format": { - "container": container, - "encoding": encoding, - "sample_rate": 0, - }, - "language": self.language_to_service_language(params.language) + self._settings: AsyncAITTSSettings = AsyncAITTSSettings( + model=model, + voice=voice_id, + output_container=container, + output_encoding=encoding, + output_sample_rate=0, + language=self.language_to_service_language(params.language) if params.language else None, - } - self.set_voice(voice_id) + ) + self._voice_id = voice_id self.set_model_name(model) self._session = aiohttp_session @@ -495,7 +518,7 @@ class AsyncAIHttpTTSService(TTSService): frame: The start frame containing initialization parameters. """ await super().start(frame) - self._settings["output_format"]["sample_rate"] = self.sample_rate + self._settings.output_sample_rate = self.sample_rate @traced_tts async def run_tts(self, text: str, context_id: str) -> AsyncGenerator[Frame, None]: @@ -517,8 +540,12 @@ class AsyncAIHttpTTSService(TTSService): "model_id": self._model_name, "transcript": text, "voice": voice_config, - "output_format": self._settings["output_format"], - "language": self._settings["language"], + "output_format": { + "container": self._settings.output_container, + "encoding": self._settings.output_encoding, + "sample_rate": self._settings.output_sample_rate, + }, + "language": self._settings.language, } yield TTSStartedFrame(context_id=context_id) headers = { diff --git a/src/pipecat/services/aws/llm.py b/src/pipecat/services/aws/llm.py index 1778ae74e..032cee060 100644 --- a/src/pipecat/services/aws/llm.py +++ b/src/pipecat/services/aws/llm.py @@ -18,8 +18,8 @@ import io import json import os import re -from dataclasses import dataclass -from typing import Any, Dict, List, Optional +from dataclasses import dataclass, field +from typing import Any, ClassVar, Dict, List, Optional from loguru import logger from PIL import Image @@ -40,7 +40,6 @@ from pipecat.frames.frames import ( LLMFullResponseStartFrame, LLMMessagesFrame, LLMTextFrame, - LLMUpdateSettingsFrame, UserImageRawFrame, ) from pipecat.metrics.metrics import LLMTokenUsage @@ -57,6 +56,7 @@ from pipecat.processors.aggregators.openai_llm_context import ( ) from pipecat.processors.frame_processor import FrameDirection from pipecat.services.llm_service import LLMService +from pipecat.services.settings import NOT_GIVEN, LLMSettings from pipecat.utils.tracing.service_decorators import traced_llm try: @@ -71,6 +71,19 @@ except ModuleNotFoundError as e: raise Exception(f"Missing module: {e}") +@dataclass +class AWSBedrockLLMSettings(LLMSettings): + """Typed settings for AWS Bedrock LLM services. + + Parameters: + latency: Performance mode - "standard" or "optimized". + additional_model_request_fields: Additional model-specific parameters. + """ + + latency: Any = field(default_factory=lambda: NOT_GIVEN) + additional_model_request_fields: Any = field(default_factory=lambda: NOT_GIVEN) + + @dataclass class AWSBedrockContextAggregatorPair: """Container for AWS Bedrock context aggregators. @@ -806,15 +819,16 @@ class AWSBedrockLLMService(LLMService): self.set_model_name(model) self._retry_timeout_secs = retry_timeout_secs self._retry_on_timeout = retry_on_timeout - self._settings = { - "max_tokens": params.max_tokens, - "temperature": params.temperature, - "top_p": params.top_p, - "latency": params.latency, - "additional_model_request_fields": params.additional_model_request_fields + self._settings = AWSBedrockLLMSettings( + model=model, + max_tokens=params.max_tokens, + temperature=params.temperature, + top_p=params.top_p, + latency=params.latency, + additional_model_request_fields=params.additional_model_request_fields if isinstance(params.additional_model_request_fields, dict) else {}, - } + ) logger.info(f"Using AWS Bedrock model: {model}") @@ -836,12 +850,12 @@ class AWSBedrockLLMService(LLMService): Dictionary containing only the inference parameters that are not None. """ inference_config = {} - if self._settings["max_tokens"] is not None: - inference_config["maxTokens"] = self._settings["max_tokens"] - if self._settings["temperature"] is not None: - inference_config["temperature"] = self._settings["temperature"] - if self._settings["top_p"] is not None: - inference_config["topP"] = self._settings["top_p"] + if self._settings.max_tokens is not None: + inference_config["maxTokens"] = self._settings.max_tokens + if self._settings.temperature is not None: + inference_config["temperature"] = self._settings.temperature + if self._settings.top_p is not None: + inference_config["topP"] = self._settings.top_p return inference_config async def run_inference( @@ -879,7 +893,7 @@ class AWSBedrockLLMService(LLMService): request_params = { "modelId": self.model_name, "messages": messages, - "additionalModelRequestFields": self._settings["additional_model_request_fields"], + "additionalModelRequestFields": self._settings.additional_model_request_fields, } if inference_config: @@ -1036,7 +1050,7 @@ class AWSBedrockLLMService(LLMService): request_params = { "modelId": self.model_name, "messages": messages, - "additionalModelRequestFields": self._settings["additional_model_request_fields"], + "additionalModelRequestFields": self._settings.additional_model_request_fields, } # Only add inference config if it has parameters @@ -1081,8 +1095,8 @@ class AWSBedrockLLMService(LLMService): request_params["toolConfig"] = tool_config # Add performance config if latency is specified - if self._settings["latency"] in ["standard", "optimized"]: - request_params["performanceConfig"] = {"latency": self._settings["latency"]} + if self._settings.latency in ["standard", "optimized"]: + request_params["performanceConfig"] = {"latency": self._settings.latency} # Log request params with messages redacted for logging if isinstance(context, LLMContext): @@ -1207,8 +1221,6 @@ class AWSBedrockLLMService(LLMService): # NOTE: LLMMessagesFrame is deprecated, so we don't support the newer universal # LLMContext with it context = AWSBedrockLLMContext.from_messages(frame.messages) - elif isinstance(frame, LLMUpdateSettingsFrame): - await self._update_settings(frame.settings) else: await self.push_frame(frame, direction) diff --git a/src/pipecat/services/aws/stt.py b/src/pipecat/services/aws/stt.py index f78bc4d4b..cb52da12a 100644 --- a/src/pipecat/services/aws/stt.py +++ b/src/pipecat/services/aws/stt.py @@ -14,6 +14,7 @@ import json import os import random import string +from dataclasses import dataclass, field from typing import AsyncGenerator, Optional from loguru import logger @@ -28,6 +29,7 @@ from pipecat.frames.frames import ( TranscriptionFrame, ) from pipecat.services.aws.utils import build_event_message, decode_event, get_presigned_url +from pipecat.services.settings import NOT_GIVEN, STTSettings from pipecat.services.stt_latency import AWS_TRANSCRIBE_TTFS_P99 from pipecat.services.stt_service import WebsocketSTTService from pipecat.transcriptions.language import Language, resolve_language @@ -43,6 +45,25 @@ except ModuleNotFoundError as e: raise Exception(f"Missing module: {e}") +@dataclass +class AWSTranscribeSTTSettings(STTSettings): + """Typed settings for the AWS Transcribe STT service. + + Parameters: + sample_rate: Audio sample rate in Hz (8000 or 16000). + media_encoding: Audio encoding format (e.g. "linear16"). + number_of_channels: Number of audio channels. + show_speaker_label: Whether to show speaker labels. + enable_channel_identification: Whether to enable channel identification. + """ + + sample_rate: int = field(default_factory=lambda: NOT_GIVEN) + media_encoding: str = field(default_factory=lambda: NOT_GIVEN) + number_of_channels: int = field(default_factory=lambda: NOT_GIVEN) + show_speaker_label: bool = field(default_factory=lambda: NOT_GIVEN) + enable_channel_identification: bool = field(default_factory=lambda: NOT_GIVEN) + + class AWSTranscribeSTTService(WebsocketSTTService): """AWS Transcribe Speech-to-Text service using WebSocket streaming. @@ -78,21 +99,21 @@ class AWSTranscribeSTTService(WebsocketSTTService): """ super().__init__(ttfs_p99_latency=ttfs_p99_latency, **kwargs) - self._settings = { - "sample_rate": sample_rate, - "language": language, - "media_encoding": "linear16", # AWS expects raw PCM - "number_of_channels": 1, - "show_speaker_label": False, - "enable_channel_identification": False, - } + self._settings: AWSTranscribeSTTSettings = AWSTranscribeSTTSettings( + language=language, + sample_rate=sample_rate, + media_encoding="linear16", + number_of_channels=1, + show_speaker_label=False, + enable_channel_identification=False, + ) # Validate sample rate - AWS Transcribe only supports 8000 Hz or 16000 Hz if sample_rate not in [8000, 16000]: logger.warning( f"AWS Transcribe only supports 8000 Hz or 16000 Hz sample rates. Converting from {sample_rate} Hz to 16000 Hz." ) - self._settings["sample_rate"] = 16000 + self._settings.sample_rate = 16000 self._credentials = { "aws_access_key_id": aws_access_key_id or os.getenv("AWS_ACCESS_KEY_ID"), @@ -117,6 +138,20 @@ class AWSTranscribeSTTService(WebsocketSTTService): } return encoding_map.get(encoding, encoding) + async def _update_settings_from_typed(self, update: STTSettings) -> set[str]: + """Apply a typed settings update, reconnecting if needed. + + Any change to connection-relevant settings (model, language, etc.) + triggers a WebSocket reconnect so the new configuration takes effect. + """ + changed = await super()._update_settings_from_typed(update) + + if changed and self._websocket: + await self._disconnect() + await self._connect() + + return changed + async def start(self, frame: StartFrame): """Initialize the connection when the service starts. @@ -208,9 +243,9 @@ class AWSTranscribeSTTService(WebsocketSTTService): logger.debug("Connecting to AWS Transcribe WebSocket") - language_code = self.language_to_service_language(Language(self._settings["language"])) + language_code = self.language_to_service_language(Language(self._settings.language)) if not language_code: - raise ValueError(f"Unsupported language: {self._settings['language']}") + raise ValueError(f"Unsupported language: {self._settings.language}") # Generate random websocket key websocket_key = "".join( @@ -237,14 +272,14 @@ class AWSTranscribeSTTService(WebsocketSTTService): }, language_code=language_code, media_encoding=self.get_service_encoding( - self._settings["media_encoding"] + self._settings.media_encoding ), # Convert to AWS format - sample_rate=self._settings["sample_rate"], - number_of_channels=self._settings["number_of_channels"], + sample_rate=self._settings.sample_rate, + number_of_channels=self._settings.number_of_channels, enable_partial_results_stabilization=True, partial_results_stability="high", - show_speaker_label=self._settings["show_speaker_label"], - enable_channel_identification=self._settings["enable_channel_identification"], + show_speaker_label=self._settings.show_speaker_label, + enable_channel_identification=self._settings.enable_channel_identification, ) logger.debug(f"{self} Connecting to WebSocket with URL: {presigned_url[:100]}...") @@ -479,14 +514,14 @@ class AWSTranscribeSTTService(WebsocketSTTService): transcript, self._user_id, time_now_iso8601(), - self._settings["language"], + self._settings.language, result=result, ) ) await self._handle_transcription( transcript, is_final, - self._settings["language"], + self._settings.language, ) await self.stop_processing_metrics() else: @@ -495,7 +530,7 @@ class AWSTranscribeSTTService(WebsocketSTTService): transcript, self._user_id, time_now_iso8601(), - self._settings["language"], + self._settings.language, result=result, ) ) diff --git a/src/pipecat/services/aws/tts.py b/src/pipecat/services/aws/tts.py index b902564d2..5086b1469 100644 --- a/src/pipecat/services/aws/tts.py +++ b/src/pipecat/services/aws/tts.py @@ -11,6 +11,7 @@ supporting multiple languages, voices, and SSML features. """ import os +from dataclasses import dataclass, field from typing import AsyncGenerator, List, Optional from loguru import logger @@ -24,6 +25,7 @@ from pipecat.frames.frames import ( TTSStartedFrame, TTSStoppedFrame, ) +from pipecat.services.settings import NOT_GIVEN, TTSSettings from pipecat.services.tts_service import TTSService from pipecat.transcriptions.language import Language, resolve_language from pipecat.utils.tracing.service_decorators import traced_tts @@ -121,6 +123,25 @@ def language_to_aws_language(language: Language) -> Optional[str]: return resolve_language(language, LANGUAGE_MAP, use_base_code=False) +@dataclass +class AWSPollyTTSSettings(TTSSettings): + """Typed settings for AWS Polly TTS service. + + Parameters: + engine: TTS engine to use ('standard', 'neural', etc.). + pitch: Voice pitch adjustment (for standard engine only). + rate: Speech rate adjustment. + volume: Voice volume adjustment. + lexicon_names: List of pronunciation lexicons to apply. + """ + + engine: str = field(default_factory=lambda: NOT_GIVEN) + pitch: str = field(default_factory=lambda: NOT_GIVEN) + rate: str = field(default_factory=lambda: NOT_GIVEN) + volume: str = field(default_factory=lambda: NOT_GIVEN) + lexicon_names: List[str] = field(default_factory=lambda: NOT_GIVEN) + + class AWSPollyTTSService(TTSService): """AWS Polly text-to-speech service. @@ -185,20 +206,21 @@ class AWSPollyTTSService(TTSService): } self._aws_session = aioboto3.Session() - self._settings = { - "engine": params.engine, - "language": self.language_to_service_language(params.language) + self._settings: AWSPollyTTSSettings = AWSPollyTTSSettings( + voice=voice_id, + engine=params.engine, + language=self.language_to_service_language(params.language) if params.language else "en-US", - "pitch": params.pitch, - "rate": params.rate, - "volume": params.volume, - "lexicon_names": params.lexicon_names, - } + pitch=params.pitch, + rate=params.rate, + volume=params.volume, + lexicon_names=params.lexicon_names, + ) self._resampler = create_stream_resampler() - self.set_voice(voice_id) + self._voice_id = voice_id def can_generate_metrics(self) -> bool: """Check if this service can generate processing metrics. @@ -222,19 +244,19 @@ class AWSPollyTTSService(TTSService): def _construct_ssml(self, text: str) -> str: ssml = "" - language = self._settings["language"] + language = self._settings.language ssml += f"" prosody_attrs = [] # Prosody tags are only supported for standard and neural engines - if self._settings["engine"] == "standard": - if self._settings["pitch"]: - prosody_attrs.append(f"pitch='{self._settings['pitch']}'") + if self._settings.engine == "standard": + if self._settings.pitch: + prosody_attrs.append(f"pitch='{self._settings.pitch}'") - if self._settings["rate"]: - prosody_attrs.append(f"rate='{self._settings['rate']}'") - if self._settings["volume"]: - prosody_attrs.append(f"volume='{self._settings['volume']}'") + if self._settings.rate: + prosody_attrs.append(f"rate='{self._settings.rate}'") + if self._settings.volume: + prosody_attrs.append(f"volume='{self._settings.volume}'") if prosody_attrs: ssml += f"" @@ -276,10 +298,10 @@ class AWSPollyTTSService(TTSService): "TextType": "ssml", "OutputFormat": "pcm", "VoiceId": self._voice_id, - "Engine": self._settings["engine"], + "Engine": self._settings.engine, # AWS only supports 8000 and 16000 for PCM. We select 16000. "SampleRate": "16000", - "LexiconNames": self._settings["lexicon_names"], + "LexiconNames": self._settings.lexicon_names, } # Filter out None values diff --git a/src/pipecat/services/azure/stt.py b/src/pipecat/services/azure/stt.py index 1bc7ec70a..bf3f70653 100644 --- a/src/pipecat/services/azure/stt.py +++ b/src/pipecat/services/azure/stt.py @@ -11,6 +11,7 @@ Speech SDK for real-time audio transcription. """ import asyncio +from dataclasses import dataclass, field from typing import AsyncGenerator, Optional from loguru import logger @@ -25,6 +26,7 @@ from pipecat.frames.frames import ( TranscriptionFrame, ) from pipecat.services.azure.common import language_to_azure_language +from pipecat.services.settings import NOT_GIVEN, STTSettings from pipecat.services.stt_latency import AZURE_TTFS_P99 from pipecat.services.stt_service import STTService from pipecat.transcriptions.language import Language @@ -48,6 +50,19 @@ except ModuleNotFoundError as e: raise Exception(f"Missing module: {e}") +@dataclass +class AzureSTTSettings(STTSettings): + """Typed settings for the Azure STT service. + + Parameters: + region: Azure region for the Speech service. + sample_rate: Audio sample rate in Hz. + """ + + region: str = field(default_factory=lambda: NOT_GIVEN) + sample_rate: Optional[int] = field(default_factory=lambda: NOT_GIVEN) + + class AzureSTTService(STTService): """Azure Speech-to-Text service for real-time audio transcription. @@ -92,11 +107,11 @@ class AzureSTTService(STTService): self._audio_stream = None self._speech_recognizer = None - self._settings = { - "region": region, - "language": language_to_azure_language(language), - "sample_rate": sample_rate, - } + self._settings: AzureSTTSettings = AzureSTTSettings( + region=region, + language=language_to_azure_language(language), + sample_rate=sample_rate, + ) def can_generate_metrics(self) -> bool: """Check if this service can generate performance metrics. @@ -106,6 +121,29 @@ class AzureSTTService(STTService): """ return True + async def _update_settings_from_typed(self, update: STTSettings) -> set[str]: + """Apply a typed settings update, reconfiguring the recognizer if needed. + + When ``language`` changes the ``SpeechConfig`` is updated and the + speech recognizer is restarted so that the new language takes effect. + """ + changed = await super()._update_settings_from_typed(update) + + if "language" in changed: + # Convert Language enum to Azure language code if needed. + lang = self._settings.language + if isinstance(lang, Language): + lang = language_to_azure_language(lang) + self._settings.language = lang + self._speech_config.speech_recognition_language = lang + + # Restart the recognizer with the new config. + if self._speech_recognizer: + self._speech_recognizer.stop_continuous_recognition_async() + self._speech_recognizer.start_continuous_recognition_async() + + return changed + async def run_stt(self, audio: bytes) -> AsyncGenerator[Frame, None]: """Process audio data for speech-to-text conversion. @@ -198,7 +236,7 @@ class AzureSTTService(STTService): def _on_handle_recognized(self, event): if event.result.reason == ResultReason.RecognizedSpeech and len(event.result.text) > 0: - language = getattr(event.result, "language", None) or self._settings.get("language") + language = getattr(event.result, "language", None) or self._settings.language frame = TranscriptionFrame( event.result.text, self._user_id, @@ -213,7 +251,7 @@ class AzureSTTService(STTService): def _on_handle_recognizing(self, event): if event.result.reason == ResultReason.RecognizingSpeech and len(event.result.text) > 0: - language = getattr(event.result, "language", None) or self._settings.get("language") + language = getattr(event.result, "language", None) or self._settings.language frame = InterimTranscriptionFrame( event.result.text, self._user_id, diff --git a/src/pipecat/services/azure/tts.py b/src/pipecat/services/azure/tts.py index 7d4aa0253..04b51d10b 100644 --- a/src/pipecat/services/azure/tts.py +++ b/src/pipecat/services/azure/tts.py @@ -7,6 +7,7 @@ """Azure Cognitive Services Text-to-Speech service implementations.""" import asyncio +from dataclasses import dataclass, field from typing import AsyncGenerator, Optional from loguru import logger @@ -25,6 +26,7 @@ from pipecat.frames.frames import ( ) from pipecat.processors.frame_processor import FrameDirection from pipecat.services.azure.common import language_to_azure_language +from pipecat.services.settings import NOT_GIVEN, TTSSettings from pipecat.services.tts_service import TTSService, WordTTSService from pipecat.transcriptions.language import Language from pipecat.utils.tracing.service_decorators import traced_tts @@ -65,6 +67,31 @@ def sample_rate_to_output_format(sample_rate: int) -> SpeechSynthesisOutputForma return sample_rate_map.get(sample_rate, SpeechSynthesisOutputFormat.Raw24Khz16BitMonoPcm) +@dataclass +class AzureTTSSettings(TTSSettings): + """Typed settings for Azure TTS services. + + Parameters: + emphasis: Emphasis level for speech ("strong", "moderate", "reduced"). + language: Language for synthesis. Defaults to English (US). + pitch: Voice pitch adjustment (e.g., "+10%", "-5Hz", "high"). + rate: Speech rate adjustment (e.g., "1.0", "1.25", "slow", "fast"). + role: Voice role for expression (e.g., "YoungAdultFemale"). + style: Speaking style (e.g., "cheerful", "sad", "excited"). + style_degree: Intensity of the speaking style (0.01 to 2.0). + volume: Volume level (e.g., "+20%", "loud", "x-soft"). + """ + + emphasis: str = field(default_factory=lambda: NOT_GIVEN) + language: str = field(default_factory=lambda: NOT_GIVEN) + pitch: str = field(default_factory=lambda: NOT_GIVEN) + rate: str = field(default_factory=lambda: NOT_GIVEN) + role: str = field(default_factory=lambda: NOT_GIVEN) + style: str = field(default_factory=lambda: NOT_GIVEN) + style_degree: str = field(default_factory=lambda: NOT_GIVEN) + volume: str = field(default_factory=lambda: NOT_GIVEN) + + class AzureBaseTTSService: """Base mixin class for Azure Cognitive Services text-to-speech implementations. @@ -126,18 +153,18 @@ class AzureBaseTTSService: """ params = params or AzureBaseTTSService.InputParams() - self._settings = { - "emphasis": params.emphasis, - "language": self.language_to_service_language(params.language) + self._settings: AzureTTSSettings = AzureTTSSettings( + emphasis=params.emphasis, + language=self.language_to_service_language(params.language) if params.language else "en-US", - "pitch": params.pitch, - "rate": params.rate, - "role": params.role, - "style": params.style, - "style_degree": params.style_degree, - "volume": params.volume, - } + pitch=params.pitch, + rate=params.rate, + role=params.role, + style=params.style, + style_degree=params.style_degree, + volume=params.volume, + ) self._api_key = api_key self._region = region @@ -156,7 +183,7 @@ class AzureBaseTTSService: return language_to_azure_language(language) def _construct_ssml(self, text: str) -> str: - language = self._settings["language"] + language = self._settings.language # Escape special characters escaped_text = self._escape_text(text) @@ -169,38 +196,38 @@ class AzureBaseTTSService: "" ) - if self._settings["style"]: - ssml += f"" - if self._settings["emphasis"]: - ssml += f"" + if self._settings.emphasis: + ssml += f"" ssml += escaped_text - if self._settings["emphasis"]: + if self._settings.emphasis: ssml += "" if prosody_attrs: ssml += "" - if self._settings["style"]: + if self._settings.style: ssml += "" ssml += "" @@ -314,7 +341,7 @@ class AzureTTSService(WordTTSService, AzureBaseTTSService): subscription=self._api_key, region=self._region, ) - self._speech_config.speech_synthesis_language = self._settings["language"] + self._speech_config.speech_synthesis_language = self._settings.language self._speech_config.set_speech_synthesis_output_format( sample_rate_to_output_format(self.sample_rate) ) @@ -364,7 +391,7 @@ class AzureTTSService(WordTTSService, AzureBaseTTSService): Returns: True if the language is CJK, False otherwise. """ - language = self._settings.get("language", "").lower() + language = (self._settings.language if self._settings.language else "").lower() # Check if language starts with CJK language codes return language.startswith(("zh", "ja", "ko", "cmn", "yue", "wuu")) @@ -735,7 +762,7 @@ class AzureHttpTTSService(TTSService, AzureBaseTTSService): subscription=self._api_key, region=self._region, ) - self._speech_config.speech_synthesis_language = self._settings["language"] + self._speech_config.speech_synthesis_language = self._settings.language self._speech_config.set_speech_synthesis_output_format( sample_rate_to_output_format(self.sample_rate) ) diff --git a/src/pipecat/services/camb/tts.py b/src/pipecat/services/camb/tts.py index def57d3a0..8a6f67231 100644 --- a/src/pipecat/services/camb/tts.py +++ b/src/pipecat/services/camb/tts.py @@ -16,7 +16,8 @@ Features: - Model-specific sample rates: mars-pro (48kHz), mars-flash (22.05kHz) """ -from typing import Any, AsyncGenerator, Dict, Optional +from dataclasses import dataclass, field +from typing import AsyncGenerator, Dict, Optional from camb import StreamTtsOutputConfiguration from camb.client import AsyncCambAI @@ -31,6 +32,7 @@ from pipecat.frames.frames import ( TTSStartedFrame, TTSStoppedFrame, ) +from pipecat.services.settings import NOT_GIVEN, TTSSettings from pipecat.services.tts_service import TTSService from pipecat.transcriptions.language import Language, resolve_language from pipecat.utils.tracing.service_decorators import traced_tts @@ -133,6 +135,18 @@ def _get_aligned_audio(buffer: bytes) -> tuple[bytes, bytes]: return buffer[:aligned_size], buffer[aligned_size:] +@dataclass +class CambTTSSettings(TTSSettings): + """Typed settings for Camb.ai TTS service. + + Parameters: + user_instructions: Custom instructions for mars-instruct model only. + Ignored for other models. Max 1000 characters. + """ + + user_instructions: str = field(default_factory=lambda: NOT_GIVEN) + + class CambTTSService(TTSService): """Camb.ai MARS text-to-speech service using the official SDK. @@ -212,15 +226,16 @@ class CambTTSService(TTSService): ) # Build settings - self._settings = { - "language": ( + self._settings: CambTTSSettings = CambTTSSettings( + model=model, + voice=voice_id, + language=( self.language_to_service_language(params.language) if params.language else "en-us" ), - "user_instructions": params.user_instructions, - } + user_instructions=params.user_instructions, + ) self.set_model_name(model) - self.set_voice(str(voice_id)) self._voice_id = voice_id self._client = None @@ -283,14 +298,14 @@ class CambTTSService(TTSService): tts_kwargs: Dict[str, Any] = { "text": text, "voice_id": self._voice_id, - "language": self._settings["language"], + "language": self._settings.language, "speech_model": self.model_name, "output_configuration": StreamTtsOutputConfiguration(format="pcm_s16le"), } # Add user instructions if using mars-instruct model - if self._model_name == "mars-instruct" and self._settings.get("user_instructions"): - tts_kwargs["user_instructions"] = self._settings["user_instructions"] + if self._model_name == "mars-instruct" and self._settings.user_instructions: + tts_kwargs["user_instructions"] = self._settings.user_instructions await self.start_tts_usage_metrics(text) yield TTSStartedFrame(context_id=context_id) diff --git a/src/pipecat/services/cartesia/stt.py b/src/pipecat/services/cartesia/stt.py index c4429226f..624801bfb 100644 --- a/src/pipecat/services/cartesia/stt.py +++ b/src/pipecat/services/cartesia/stt.py @@ -12,6 +12,7 @@ the Cartesia Live transcription API for real-time speech recognition. import json import urllib.parse +from dataclasses import dataclass, field from typing import AsyncGenerator, Optional from loguru import logger @@ -27,6 +28,7 @@ from pipecat.frames.frames import ( VADUserStoppedSpeakingFrame, ) from pipecat.processors.frame_processor import FrameDirection +from pipecat.services.settings import NOT_GIVEN, STTSettings from pipecat.services.stt_latency import CARTESIA_TTFS_P99 from pipecat.services.stt_service import WebsocketSTTService from pipecat.transcriptions.language import Language @@ -42,6 +44,17 @@ except ModuleNotFoundError as e: raise Exception(f"Missing module: {e}") +@dataclass +class CartesiaSTTSettings(STTSettings): + """Typed settings for the Cartesia STT service. + + Parameters: + encoding: Audio encoding format (e.g. ``"pcm_s16le"``). + """ + + encoding: str = field(default_factory=lambda: NOT_GIVEN) + + class CartesiaLiveOptions: """Configuration options for Cartesia Live STT service. @@ -181,7 +194,11 @@ class CartesiaSTTService(WebsocketSTTService): k: v for k, v in merged_options.items() if not isinstance(v, str) or v != "None" } - self._settings = merged_options + self._settings: CartesiaSTTSettings = CartesiaSTTSettings( + model=merged_options["model"], + language=merged_options.get("language"), + encoding=merged_options.get("encoding", "pcm_s16le"), + ) self.set_model_name(merged_options["model"]) self._api_key = api_key self._base_url = base_url or "api.cartesia.ai" @@ -275,13 +292,33 @@ class CartesiaSTTService(WebsocketSTTService): await self._disconnect_websocket() + async def _update_settings_from_typed(self, update: STTSettings) -> set[str]: + """Apply a typed settings update and reconnect if anything changed. + + Args: + update: A :class:`STTSettings` (or ``CartesiaSTTSettings``) delta. + + Returns: + Set of field names whose values actually changed. + """ + changed = await super()._update_settings_from_typed(update) + if changed: + await self._disconnect() + await self._connect() + return changed + async def _connect_websocket(self): try: if self._websocket and self._websocket.state is State.OPEN: return logger.debug("Connecting to Cartesia STT") - params = self._settings + params = { + "model": self._settings.model, + "language": self._settings.language, + "encoding": self._settings.encoding, + "sample_rate": str(self.sample_rate), + } ws_url = f"wss://{self._base_url}/stt/websocket?{urllib.parse.urlencode(params)}" headers = {"Cartesia-Version": "2025-04-16", "X-API-Key": self._api_key} diff --git a/src/pipecat/services/cartesia/tts.py b/src/pipecat/services/cartesia/tts.py index 791c60a18..531aafdf7 100644 --- a/src/pipecat/services/cartesia/tts.py +++ b/src/pipecat/services/cartesia/tts.py @@ -9,8 +9,9 @@ import base64 import json import warnings +from dataclasses import dataclass, field from enum import Enum -from typing import AsyncGenerator, List, Literal, Optional +from typing import Any, AsyncGenerator, List, Literal, Optional from loguru import logger from pydantic import BaseModel, Field @@ -27,6 +28,7 @@ from pipecat.frames.frames import ( TTSStoppedFrame, ) from pipecat.processors.frame_processor import FrameDirection +from pipecat.services.settings import NOT_GIVEN, TTSSettings, is_given from pipecat.services.tts_service import AudioContextWordTTSService, TTSService from pipecat.transcriptions.language import Language, resolve_language from pipecat.utils.text.base_text_aggregator import BaseTextAggregator @@ -191,6 +193,31 @@ class CartesiaEmotion(str, Enum): DETERMINED = "determined" +@dataclass +class CartesiaTTSSettings(TTSSettings): + """Typed settings for Cartesia TTS services. + + Parameters: + output_container: Audio container format (e.g. "raw"). + output_encoding: Audio encoding format (e.g. "pcm_s16le"). + output_sample_rate: Audio sample rate in Hz. + speed: Voice speed control for non-Sonic-3 models (literal values). + emotion: List of emotion controls for non-Sonic-3 models. + generation_config: Generation configuration for Sonic-3 models. Includes volume, + speed (numeric), and emotion (string) parameters. + pronunciation_dict_id: The ID of the pronunciation dictionary to use for + custom pronunciations. + """ + + output_container: str = field(default_factory=lambda: NOT_GIVEN) + output_encoding: str = field(default_factory=lambda: NOT_GIVEN) + output_sample_rate: int = field(default_factory=lambda: NOT_GIVEN) + speed: str = field(default_factory=lambda: NOT_GIVEN) + emotion: List[str] = field(default_factory=lambda: NOT_GIVEN) + generation_config: GenerationConfig = field(default_factory=lambda: NOT_GIVEN) + pronunciation_dict_id: str = field(default_factory=lambda: NOT_GIVEN) + + class CartesiaTTSService(AudioContextWordTTSService): """Cartesia TTS service with WebSocket streaming and word timestamps. @@ -289,22 +316,20 @@ class CartesiaTTSService(AudioContextWordTTSService): self._api_key = api_key self._cartesia_version = cartesia_version self._url = url - self._settings = { - "output_format": { - "container": container, - "encoding": encoding, - "sample_rate": 0, - }, - "language": self.language_to_service_language(params.language) + self._settings: CartesiaTTSSettings = CartesiaTTSSettings( + output_container=container, + output_encoding=encoding, + output_sample_rate=0, + language=self.language_to_service_language(params.language) if params.language else None, - "speed": params.speed, - "emotion": params.emotion, - "generation_config": params.generation_config, - "pronunciation_dict_id": params.pronunciation_dict_id, - } + speed=params.speed, + emotion=params.emotion, + generation_config=params.generation_config, + pronunciation_dict_id=params.pronunciation_dict_id, + ) self.set_model_name(model) - self.set_voice(voice_id) + self._voice_id = voice_id self._context_id = None self._receive_task = None @@ -317,16 +342,6 @@ class CartesiaTTSService(AudioContextWordTTSService): """ return True - async def set_model(self, model: str): - """Set the TTS model. - - Args: - model: The model name to use for synthesis. - """ - self._model_id = model - await super().set_model(model) - logger.info(f"Switching TTS model to: [{model}]") - def language_to_service_language(self, language: Language) -> Optional[str]: """Convert a Language enum to Cartesia language format. @@ -391,7 +406,7 @@ class CartesiaTTSService(AudioContextWordTTSService): Returns: List of (word, start_time) tuples processed for the language. """ - current_language = self._settings.get("language") + current_language = self._settings.language # Check if this is a CJK language (if language is None, treat as non-CJK) if current_language and self._is_cjk_language(current_language): @@ -414,7 +429,7 @@ class CartesiaTTSService(AudioContextWordTTSService): voice_config["mode"] = "id" voice_config["id"] = self._voice_id - if self._settings["emotion"]: + if is_given(self._settings.emotion) and self._settings.emotion: with warnings.catch_warnings(): warnings.simplefilter("always") warnings.warn( @@ -423,8 +438,7 @@ class CartesiaTTSService(AudioContextWordTTSService): stacklevel=2, ) voice_config["__experimental_controls"] = {} - if self._settings["emotion"]: - voice_config["__experimental_controls"]["emotion"] = self._settings["emotion"] + voice_config["__experimental_controls"]["emotion"] = self._settings.emotion msg = { "transcript": text, @@ -432,24 +446,28 @@ class CartesiaTTSService(AudioContextWordTTSService): "context_id": self._context_id, "model_id": self.model_name, "voice": voice_config, - "output_format": self._settings["output_format"], + "output_format": { + "container": self._settings.output_container, + "encoding": self._settings.output_encoding, + "sample_rate": self._settings.output_sample_rate, + }, "add_timestamps": add_timestamps, "use_original_timestamps": False if self.model_name == "sonic" else True, } - if self._settings["language"]: - msg["language"] = self._settings["language"] + if is_given(self._settings.language) and self._settings.language: + msg["language"] = self._settings.language - if self._settings["speed"]: - msg["speed"] = self._settings["speed"] + if is_given(self._settings.speed) and self._settings.speed: + msg["speed"] = self._settings.speed - if self._settings["generation_config"]: - msg["generation_config"] = self._settings["generation_config"].model_dump( + if is_given(self._settings.generation_config) and self._settings.generation_config: + msg["generation_config"] = self._settings.generation_config.model_dump( exclude_none=True ) - if self._settings["pronunciation_dict_id"]: - msg["pronunciation_dict_id"] = self._settings["pronunciation_dict_id"] + if is_given(self._settings.pronunciation_dict_id) and self._settings.pronunciation_dict_id: + msg["pronunciation_dict_id"] = self._settings.pronunciation_dict_id return json.dumps(msg) @@ -460,7 +478,7 @@ class CartesiaTTSService(AudioContextWordTTSService): frame: The start frame containing initialization parameters. """ await super().start(frame) - self._settings["output_format"]["sample_rate"] = self.sample_rate + self._settings.output_sample_rate = self.sample_rate await self._connect() async def stop(self, frame: EndFrame): @@ -694,21 +712,21 @@ class CartesiaHttpTTSService(TTSService): self._api_key = api_key self._base_url = base_url self._cartesia_version = cartesia_version - self._settings = { - "output_format": { - "container": container, - "encoding": encoding, - "sample_rate": 0, - }, - "language": self.language_to_service_language(params.language) + self._settings: CartesiaTTSSettings = CartesiaTTSSettings( + model=model, + voice=voice_id, + output_container=container, + output_encoding=encoding, + output_sample_rate=0, + language=self.language_to_service_language(params.language) if params.language else None, - "speed": params.speed, - "emotion": params.emotion, - "generation_config": params.generation_config, - "pronunciation_dict_id": params.pronunciation_dict_id, - } - self.set_voice(voice_id) + speed=params.speed, + emotion=params.emotion, + generation_config=params.generation_config, + pronunciation_dict_id=params.pronunciation_dict_id, + ) + self._voice_id = voice_id self.set_model_name(model) self._client = AsyncCartesia( @@ -742,7 +760,7 @@ class CartesiaHttpTTSService(TTSService): frame: The start frame containing initialization parameters. """ await super().start(frame) - self._settings["output_format"]["sample_rate"] = self.sample_rate + self._settings.output_sample_rate = self.sample_rate async def stop(self, frame: EndFrame): """Stop the Cartesia HTTP TTS service. @@ -778,7 +796,7 @@ class CartesiaHttpTTSService(TTSService): try: voice_config = {"mode": "id", "id": self._voice_id} - if self._settings["emotion"]: + if is_given(self._settings.emotion) and self._settings.emotion: with warnings.catch_warnings(): warnings.simplefilter("always") warnings.warn( @@ -786,30 +804,39 @@ class CartesiaHttpTTSService(TTSService): DeprecationWarning, stacklevel=2, ) - voice_config["__experimental_controls"] = {"emotion": self._settings["emotion"]} + voice_config["__experimental_controls"] = {"emotion": self._settings.emotion} await self.start_ttfb_metrics() + output_format = { + "container": self._settings.output_container, + "encoding": self._settings.output_encoding, + "sample_rate": self._settings.output_sample_rate, + } + payload = { "model_id": self._model_name, "transcript": text, "voice": voice_config, - "output_format": self._settings["output_format"], + "output_format": output_format, } - if self._settings["language"]: - payload["language"] = self._settings["language"] + if is_given(self._settings.language) and self._settings.language: + payload["language"] = self._settings.language - if self._settings["speed"]: - payload["speed"] = self._settings["speed"] + if is_given(self._settings.speed) and self._settings.speed: + payload["speed"] = self._settings.speed - if self._settings["generation_config"]: - payload["generation_config"] = self._settings["generation_config"].model_dump( + if is_given(self._settings.generation_config) and self._settings.generation_config: + payload["generation_config"] = self._settings.generation_config.model_dump( exclude_none=True ) - if self._settings["pronunciation_dict_id"]: - payload["pronunciation_dict_id"] = self._settings["pronunciation_dict_id"] + if ( + is_given(self._settings.pronunciation_dict_id) + and self._settings.pronunciation_dict_id + ): + payload["pronunciation_dict_id"] = self._settings.pronunciation_dict_id yield TTSStartedFrame(context_id=context_id) diff --git a/src/pipecat/services/cerebras/llm.py b/src/pipecat/services/cerebras/llm.py index 54ea45ddb..01a8165f8 100644 --- a/src/pipecat/services/cerebras/llm.py +++ b/src/pipecat/services/cerebras/llm.py @@ -68,14 +68,14 @@ class CerebrasLLMService(OpenAILLMService): params = { "model": self.model_name, "stream": True, - "seed": self._settings["seed"], - "temperature": self._settings["temperature"], - "top_p": self._settings["top_p"], - "max_completion_tokens": self._settings["max_completion_tokens"], + "seed": self._settings.seed, + "temperature": self._settings.temperature, + "top_p": self._settings.top_p, + "max_completion_tokens": self._settings.max_completion_tokens, } # Messages, tools, tool_choice params.update(params_from_context) - params.update(self._settings["extra"]) + params.update(self._settings.extra) return params diff --git a/src/pipecat/services/deepgram/stt.py b/src/pipecat/services/deepgram/stt.py index 0f79499ba..91d4308cb 100644 --- a/src/pipecat/services/deepgram/stt.py +++ b/src/pipecat/services/deepgram/stt.py @@ -6,6 +6,7 @@ """Deepgram speech-to-text service implementation.""" +from dataclasses import dataclass, field from typing import AsyncGenerator, Dict, Optional from loguru import logger @@ -23,6 +24,7 @@ from pipecat.frames.frames import ( VADUserStoppedSpeakingFrame, ) from pipecat.processors.frame_processor import FrameDirection +from pipecat.services.settings import NOT_GIVEN, STTSettings, is_given from pipecat.services.stt_latency import DEEPGRAM_TTFS_P99 from pipecat.services.stt_service import STTService from pipecat.transcriptions.language import Language @@ -45,6 +47,17 @@ except ModuleNotFoundError as e: raise Exception(f"Missing module: {e}") +@dataclass +class DeepgramSTTSettings(STTSettings): + """Typed settings for the Deepgram STT service. + + Parameters: + live_options: Deepgram ``LiveOptions`` for detailed configuration. + """ + + live_options: LiveOptions = field(default_factory=lambda: NOT_GIVEN) + + class DeepgramSTTService(STTService): """Deepgram speech-to-text service. @@ -129,11 +142,17 @@ class DeepgramSTTService(STTService): merged_options["language"] = merged_options["language"].value self.set_model_name(merged_options["model"]) - self._settings = merged_options + merged_live_options = LiveOptions(**merged_options) + self._settings: DeepgramSTTSettings = DeepgramSTTSettings( + model=merged_options.get("model"), + language=merged_options.get("language"), + live_options=merged_live_options, + ) + self._addons = addons self._should_interrupt = should_interrupt - if merged_options.get("vad_events"): + if merged_live_options.vad_events: import warnings with warnings.catch_warnings(): @@ -164,7 +183,7 @@ class DeepgramSTTService(STTService): Returns: True if VAD events are enabled in the current settings. """ - return self._settings["vad_events"] + return self._settings.live_options.vad_events def can_generate_metrics(self) -> bool: """Check if this service can generate processing metrics. @@ -174,28 +193,48 @@ class DeepgramSTTService(STTService): """ return True - async def set_model(self, model: str): - """Set the Deepgram model and reconnect. + async def _update_settings_from_typed(self, update: STTSettings) -> set[str]: + """Apply a typed settings update, keeping ``live_options`` in sync. - Args: - model: The Deepgram model name to use. + Top-level ``model`` and ``language`` are the source of truth. When + they are given in *update* their values are propagated into + ``live_options``. When only ``live_options`` is given, its ``model`` + and ``language`` are propagated *up* to the top-level fields. + + Any change triggers a WebSocket reconnect. """ - await super().set_model(model) - logger.info(f"Switching STT model to: [{model}]") - self._settings["model"] = model + # Determine which top-level fields are explicitly provided. + model_given = isinstance(update, DeepgramSTTSettings) and is_given( + getattr(update, "model", NOT_GIVEN) + ) + language_given = isinstance(update, DeepgramSTTSettings) and is_given( + getattr(update, "language", NOT_GIVEN) + ) + + changed = await super()._update_settings_from_typed(update) + + if not changed: + return changed + + # --- Sync model -------------------------------------------------- + if model_given: + # Top-level model wins → push into live_options. + self._settings.live_options.model = self._settings.model + elif "live_options" in changed and self._settings.live_options.model is not None: + # Only live_options was given → pull model up. + self._settings.model = self._settings.live_options.model + self.set_model_name(self._settings.model) + + # --- Sync language ----------------------------------------------- + if language_given: + self._settings.live_options.language = self._settings.language + elif "live_options" in changed and self._settings.live_options.language is not None: + self._settings.language = self._settings.live_options.language + await self._disconnect() await self._connect() - async def set_language(self, language: Language): - """Set the recognition language and reconnect. - - Args: - language: The language to use for speech recognition. - """ - logger.info(f"Switching STT language to: [{language}]") - self._settings["language"] = language - await self._disconnect() - await self._connect() + return changed async def start(self, frame: StartFrame): """Start the Deepgram STT service. @@ -204,7 +243,7 @@ class DeepgramSTTService(STTService): frame: The start frame containing initialization parameters. """ await super().start(frame) - self._settings["sample_rate"] = self.sample_rate + self._settings.live_options.sample_rate = self.sample_rate await self._connect() async def stop(self, frame: EndFrame): @@ -257,7 +296,9 @@ class DeepgramSTTService(STTService): self._on_utterance_end, ) - if not await self._connection.start(options=self._settings, addons=self._addons): + if not await self._connection.start( + options=self._settings.live_options, addons=self._addons + ): await self.push_error(error_msg=f"Unable to connect to Deepgram") else: headers = { diff --git a/src/pipecat/services/deepgram/stt_sagemaker.py b/src/pipecat/services/deepgram/stt_sagemaker.py index 99f6cf487..95242ade6 100644 --- a/src/pipecat/services/deepgram/stt_sagemaker.py +++ b/src/pipecat/services/deepgram/stt_sagemaker.py @@ -14,6 +14,7 @@ languages, and various Deepgram features. import asyncio import json +from dataclasses import dataclass, field from typing import AsyncGenerator, Optional from loguru import logger @@ -31,6 +32,7 @@ from pipecat.frames.frames import ( ) from pipecat.processors.frame_processor import FrameDirection from pipecat.services.aws.sagemaker.bidi_client import SageMakerBidiClient +from pipecat.services.settings import NOT_GIVEN, STTSettings, is_given from pipecat.services.stt_latency import DEEPGRAM_SAGEMAKER_TTFS_P99 from pipecat.services.stt_service import STTService from pipecat.transcriptions.language import Language @@ -47,6 +49,17 @@ except ModuleNotFoundError as e: raise Exception(f"Missing module: {e}") +@dataclass +class DeepgramSageMakerSTTSettings(STTSettings): + """Typed settings for the Deepgram SageMaker STT service. + + Parameters: + live_options: Deepgram ``LiveOptions`` for detailed configuration. + """ + + live_options: LiveOptions = field(default_factory=lambda: NOT_GIVEN) + + class DeepgramSageMakerSTTService(STTService): """Deepgram speech-to-text service for AWS SageMaker. @@ -129,7 +142,12 @@ class DeepgramSageMakerSTTService(STTService): merged_options["language"] = merged_options["language"].value self.set_model_name(merged_options["model"]) - self._settings = merged_options + merged_live_options = LiveOptions(**merged_options) + self._settings: DeepgramSageMakerSTTSettings = DeepgramSageMakerSTTSettings( + model=merged_options.get("model"), + language=merged_options.get("language"), + live_options=merged_live_options, + ) self._client: Optional[SageMakerBidiClient] = None self._response_task: Optional[asyncio.Task] = None @@ -143,35 +161,40 @@ class DeepgramSageMakerSTTService(STTService): """ return True - async def set_model(self, model: str): - """Set the Deepgram model and reconnect. + async def _update_settings_from_typed(self, update: STTSettings) -> set[str]: + """Apply a typed settings update, keeping ``live_options`` in sync. - Disconnects from the current session, updates the model setting, and - establishes a new connection with the updated model. + Top-level ``model`` and ``language`` are the source of truth. When + they change their values are propagated into ``live_options``. - Args: - model: The Deepgram model name to use (e.g., "nova-3"). + Any change triggers a reconnect. """ - await super().set_model(model) - logger.info(f"Switching STT model to: [{model}]") - self._settings["model"] = model - await self._disconnect() - await self._connect() - - async def set_language(self, language: Language): - """Set the recognition language and reconnect. - - Disconnects from the current session, updates the language setting, and - establishes a new connection with the updated language. - - Args: - language: The language to use for speech recognition (e.g., Language.EN, - Language.ES). - """ - logger.info(f"Switching STT language to: [{language}]") - self._settings["language"] = language + model_given = isinstance(update, DeepgramSageMakerSTTSettings) and is_given( + getattr(update, "model", NOT_GIVEN) + ) + language_given = isinstance(update, DeepgramSageMakerSTTSettings) and is_given( + getattr(update, "language", NOT_GIVEN) + ) + + changed = await super()._update_settings_from_typed(update) + + if not changed: + return changed + + # Sync model into live_options + if model_given and "model" in changed: + self._settings.live_options.model = self._settings.model + + # Sync language into live_options + if language_given and "language" in changed: + lang = self._settings.language + if isinstance(lang, Language): + lang = lang.value + self._settings.live_options.language = lang + await self._disconnect() await self._connect() + return changed async def start(self, frame: StartFrame): """Start the Deepgram SageMaker STT service. @@ -180,7 +203,7 @@ class DeepgramSageMakerSTTService(STTService): frame: The start frame containing initialization parameters. """ await super().start(frame) - self._settings["sample_rate"] = self.sample_rate + self._settings.live_options.sample_rate = self.sample_rate await self._connect() async def stop(self, frame: EndFrame): @@ -226,12 +249,12 @@ class DeepgramSageMakerSTTService(STTService): """ logger.debug("Connecting to Deepgram on SageMaker...") - # Update sample rate in settings - self._settings["sample_rate"] = self.sample_rate + # Update sample rate in live_options + self._settings.live_options.sample_rate = self.sample_rate - # Build query string from settings, converting booleans to strings + # Build query string from live_options, converting booleans to strings query_params = {} - for key, value in self._settings.items(): + for key, value in self._settings.live_options.to_dict().items(): if value is not None: # Convert boolean values to lowercase strings for Deepgram API if isinstance(value, bool): diff --git a/src/pipecat/services/deepgram/tts.py b/src/pipecat/services/deepgram/tts.py index 12aba4905..4c698dcea 100644 --- a/src/pipecat/services/deepgram/tts.py +++ b/src/pipecat/services/deepgram/tts.py @@ -11,6 +11,7 @@ for generating speech from text using various voice models. """ import json +from dataclasses import dataclass, field from typing import AsyncGenerator, Optional import aiohttp @@ -29,6 +30,7 @@ from pipecat.frames.frames import ( TTSStoppedFrame, ) from pipecat.processors.frame_processor import FrameDirection +from pipecat.services.settings import NOT_GIVEN, TTSSettings from pipecat.services.tts_service import TTSService, WebsocketTTSService from pipecat.utils.tracing.service_decorators import traced_tts @@ -43,6 +45,17 @@ except ModuleNotFoundError as e: raise Exception(f"Missing module: {e}") +@dataclass +class DeepgramTTSSettings(TTSSettings): + """Typed settings for Deepgram TTS service. + + Parameters: + encoding: Audio encoding format (linear16, mulaw, alaw). + """ + + encoding: str = field(default_factory=lambda: NOT_GIVEN) + + class DeepgramTTSService(WebsocketTTSService): """Deepgram WebSocket-based text-to-speech service. @@ -91,10 +104,12 @@ class DeepgramTTSService(WebsocketTTSService): self._api_key = api_key self._base_url = base_url - self._settings = { - "encoding": encoding, - } - self.set_voice(voice) + self._settings: DeepgramTTSSettings = DeepgramTTSSettings( + model=voice, + voice=voice, + encoding=encoding, + ) + self._voice_id = voice self._receive_task = None self._context_id: Optional[str] = None @@ -177,7 +192,7 @@ class DeepgramTTSService(WebsocketTTSService): # Build WebSocket URL with query parameters params = [] params.append(f"model={self._voice_id}") - params.append(f"encoding={self._settings['encoding']}") + params.append(f"encoding={self._settings.encoding}") params.append(f"sample_rate={self.sample_rate}") url = f"{self._base_url}/v1/speak?{'&'.join(params)}" @@ -357,10 +372,12 @@ class DeepgramHttpTTSService(TTSService): self._api_key = api_key self._session = aiohttp_session self._base_url = base_url - self._settings = { - "encoding": encoding, - } - self.set_voice(voice) + self._settings: DeepgramTTSSettings = DeepgramTTSSettings( + model=voice, + voice=voice, + encoding=encoding, + ) + self._voice_id = voice def can_generate_metrics(self) -> bool: """Check if the service can generate metrics. @@ -390,7 +407,7 @@ class DeepgramHttpTTSService(TTSService): params = { "model": self._voice_id, - "encoding": self._settings["encoding"], + "encoding": self._settings.encoding, "sample_rate": self.sample_rate, "container": "none", } diff --git a/src/pipecat/services/deepseek/llm.py b/src/pipecat/services/deepseek/llm.py index 56f1ddd18..806dce13d 100644 --- a/src/pipecat/services/deepseek/llm.py +++ b/src/pipecat/services/deepseek/llm.py @@ -68,15 +68,15 @@ class DeepSeekLLMService(OpenAILLMService): "model": self.model_name, "stream": True, "stream_options": {"include_usage": True}, - "frequency_penalty": self._settings["frequency_penalty"], - "presence_penalty": self._settings["presence_penalty"], - "temperature": self._settings["temperature"], - "top_p": self._settings["top_p"], - "max_tokens": self._settings["max_tokens"], + "frequency_penalty": self._settings.frequency_penalty, + "presence_penalty": self._settings.presence_penalty, + "temperature": self._settings.temperature, + "top_p": self._settings.top_p, + "max_tokens": self._settings.max_tokens, } # Messages, tools, tool_choice params.update(params_from_context) - params.update(self._settings["extra"]) + params.update(self._settings.extra) return params diff --git a/src/pipecat/services/elevenlabs/stt.py b/src/pipecat/services/elevenlabs/stt.py index 388f7146b..950dc5de9 100644 --- a/src/pipecat/services/elevenlabs/stt.py +++ b/src/pipecat/services/elevenlabs/stt.py @@ -14,6 +14,7 @@ transcription results directly. import base64 import io import json +from dataclasses import dataclass, field from enum import Enum from typing import AsyncGenerator, Optional @@ -33,6 +34,7 @@ from pipecat.frames.frames import ( VADUserStoppedSpeakingFrame, ) from pipecat.processors.frame_processor import FrameDirection +from pipecat.services.settings import NOT_GIVEN, STTSettings, is_given from pipecat.services.stt_latency import ELEVENLABS_REALTIME_TTFS_P99, ELEVENLABS_TTFS_P99 from pipecat.services.stt_service import SegmentedSTTService, WebsocketSTTService from pipecat.transcriptions.language import Language, resolve_language @@ -167,6 +169,44 @@ def language_to_elevenlabs_language(language: Language) -> Optional[str]: return resolve_language(language, LANGUAGE_MAP, use_base_code=False) +@dataclass +class ElevenLabsSTTSettings(STTSettings): + """Typed settings for the ElevenLabs file-based STT service. + + Parameters: + tag_audio_events: Whether to include audio event tags in transcription. + """ + + tag_audio_events: bool = field(default_factory=lambda: NOT_GIVEN) + + +@dataclass +class ElevenLabsRealtimeSTTSettings(STTSettings): + """Typed settings for the ElevenLabs Realtime STT service. + + See ``ElevenLabsRealtimeSTTService.InputParams`` for detailed descriptions. + + Parameters: + commit_strategy: How to segment speech - manual (Pipecat VAD) or vad (ElevenLabs VAD). + vad_silence_threshold_secs: Seconds of silence before VAD commits (0.3-3.0). + vad_threshold: VAD sensitivity (0.1-0.9, lower is more sensitive). + min_speech_duration_ms: Minimum speech duration for VAD (50-2000ms). + min_silence_duration_ms: Minimum silence duration for VAD (50-2000ms). + include_timestamps: Whether to include word-level timestamps in transcripts. + enable_logging: Whether to enable logging on ElevenLabs' side. + include_language_detection: Whether to include language detection in transcripts. + """ + + commit_strategy: CommitStrategy = field(default_factory=lambda: NOT_GIVEN) + vad_silence_threshold_secs: float = field(default_factory=lambda: NOT_GIVEN) + vad_threshold: float = field(default_factory=lambda: NOT_GIVEN) + min_speech_duration_ms: int = field(default_factory=lambda: NOT_GIVEN) + min_silence_duration_ms: int = field(default_factory=lambda: NOT_GIVEN) + include_timestamps: bool = field(default_factory=lambda: NOT_GIVEN) + enable_logging: bool = field(default_factory=lambda: NOT_GIVEN) + include_language_detection: bool = field(default_factory=lambda: NOT_GIVEN) + + class ElevenLabsSTTService(SegmentedSTTService): """Speech-to-text service using ElevenLabs' file-based API. @@ -223,13 +263,15 @@ class ElevenLabsSTTService(SegmentedSTTService): self._base_url = base_url self._session = aiohttp_session self._model_id = model - self._tag_audio_events = params.tag_audio_events - self._settings = { - "language": self.language_to_service_language(params.language) + self._settings: ElevenLabsSTTSettings = ElevenLabsSTTSettings( + model=model, + language=self.language_to_service_language(params.language) if params.language else "eng", - } + tag_audio_events=params.tag_audio_events, + ) + self.set_model_name(model) def can_generate_metrics(self) -> bool: """Check if the service can generate processing metrics. @@ -250,27 +292,30 @@ class ElevenLabsSTTService(SegmentedSTTService): """ return language_to_elevenlabs_language(language) - async def set_language(self, language: Language): - """Set the transcription language. + async def _update_settings_from_typed(self, update: STTSettings) -> set[str]: + """Apply a typed settings update. + + Converts language to ElevenLabs format before applying and keeps + ``_model_id`` in sync with the model setting. Args: - language: The language to use for speech-to-text transcription. + update: A :class:`STTSettings` (or ``ElevenLabsSTTSettings``) delta. + + Returns: + Set of field names whose values actually changed. """ - logger.info(f"Switching STT language to: [{language}]") - self._settings["language"] = self.language_to_service_language(language) + # Convert language to ElevenLabs format before applying + if is_given(update.language) and isinstance(update.language, Language): + converted = self.language_to_service_language(update.language) + if converted is not None: + update.language = converted - async def set_model(self, model: str): - """Set the STT model. + changed = await super()._update_settings_from_typed(update) - Args: - model: The model name to use for transcription. + if "model" in changed: + self._model_id = self._settings.model - Note: - ElevenLabs STT API does not currently support model selection. - This method is provided for interface compatibility. - """ - await super().set_model(model) - logger.info(f"Model setting [{model}] noted, but ElevenLabs STT uses default model") + return changed async def _transcribe_audio(self, audio_data: bytes) -> dict: """Upload audio data to ElevenLabs and get transcription result. @@ -298,8 +343,8 @@ class ElevenLabsSTTService(SegmentedSTTService): # Add required model_id, language_code, and tag_audio_events data.add_field("model_id", self._model_id) - data.add_field("language_code", self._settings["language"]) - data.add_field("tag_audio_events", str(self._tag_audio_events).lower()) + data.add_field("language_code", self._settings.language) + data.add_field("tag_audio_events", str(self._settings.tag_audio_events).lower()) async with self._session.post(url, data=data, headers=headers) as response: if response.status != 200: @@ -469,11 +514,22 @@ class ElevenLabsRealtimeSTTService(WebsocketSTTService): self._api_key = api_key self._base_url = base_url self._model_id = model - self._params = params self._audio_format = "" # initialized in start() self._receive_task = None - self._settings = {"language": params.language_code} + self._settings: ElevenLabsRealtimeSTTSettings = ElevenLabsRealtimeSTTSettings( + model=model, + language=params.language_code, + commit_strategy=params.commit_strategy, + vad_silence_threshold_secs=params.vad_silence_threshold_secs, + vad_threshold=params.vad_threshold, + min_speech_duration_ms=params.min_speech_duration_ms, + min_silence_duration_ms=params.min_silence_duration_ms, + include_timestamps=params.include_timestamps, + enable_logging=params.enable_logging, + include_language_detection=params.include_language_detection, + ) + self.set_model_name(model) def can_generate_metrics(self) -> bool: """Check if the service can generate processing metrics. @@ -483,42 +539,35 @@ class ElevenLabsRealtimeSTTService(WebsocketSTTService): """ return True - async def set_language(self, language: Language): - """Set the transcription language. + async def _update_settings_from_typed(self, update: STTSettings) -> set[str]: + """Apply a typed settings update and reconnect if anything changed. + + Converts language to ElevenLabs format before applying and keeps + ``_model_id`` in sync. Args: - language: The language to use for speech-to-text transcription. + update: A :class:`STTSettings` (or ``ElevenLabsRealtimeSTTSettings``) delta. - Note: - Changing language requires reconnecting to the WebSocket. + Returns: + Set of field names whose values actually changed. """ - logger.info(f"Switching STT language to: [{language}]") - new_language = ( - language_to_elevenlabs_language(language) - if isinstance(language, Language) - else language - ) - self._params.language_code = new_language - self._settings["language"] = new_language - # Reconnect with new settings - await self._disconnect() - await self._connect() - - async def set_model(self, model: str): - """Set the STT model. - - Args: - model: The model name to use for transcription. - - Note: - Changing model requires reconnecting to the WebSocket. - """ - await super().set_model(model) - logger.info(f"Switching STT model to: [{model}]") - self._model_id = model - # Reconnect with new settings + # Convert language to ElevenLabs format before applying + if is_given(update.language) and isinstance(update.language, Language): + converted = language_to_elevenlabs_language(update.language) + if converted is not None: + update.language = converted + + changed = await super()._update_settings_from_typed(update) + + if not changed: + return changed + + if "model" in changed: + self._model_id = self._settings.model + await self._disconnect() await self._connect() + return changed async def start(self, frame: StartFrame): """Start the STT service and establish WebSocket connection. @@ -566,7 +615,7 @@ class ElevenLabsRealtimeSTTService(WebsocketSTTService): await self._start_metrics() elif isinstance(frame, VADUserStoppedSpeakingFrame): # Send commit when user stops speaking (manual commit mode) - if self._params.commit_strategy == CommitStrategy.MANUAL: + if self._settings.commit_strategy == CommitStrategy.MANUAL: if self._websocket and self._websocket.state is State.OPEN: try: commit_message = { @@ -656,36 +705,40 @@ class ElevenLabsRealtimeSTTService(WebsocketSTTService): # Build query parameters params = [f"model_id={self._model_id}"] - if self._params.language_code: - params.append(f"language_code={self._params.language_code}") + if self._settings.language: + params.append(f"language_code={self._settings.language}") params.append(f"audio_format={self._audio_format}") - params.append(f"commit_strategy={self._params.commit_strategy.value}") + params.append(f"commit_strategy={self._settings.commit_strategy.value}") # Add optional parameters - if self._params.include_timestamps: - params.append(f"include_timestamps={str(self._params.include_timestamps).lower()}") - - if self._params.enable_logging: - params.append(f"enable_logging={str(self._params.enable_logging).lower()}") - - if self._params.include_language_detection: + if self._settings.include_timestamps: params.append( - f"include_language_detection={str(self._params.include_language_detection).lower()}" + f"include_timestamps={str(self._settings.include_timestamps).lower()}" + ) + + if self._settings.enable_logging: + params.append(f"enable_logging={str(self._settings.enable_logging).lower()}") + + if self._settings.include_language_detection: + params.append( + f"include_language_detection={str(self._settings.include_language_detection).lower()}" ) # Add VAD parameters if using VAD commit strategy and values are specified - if self._params.commit_strategy == CommitStrategy.VAD: - if self._params.vad_silence_threshold_secs is not None: + if self._settings.commit_strategy == CommitStrategy.VAD: + if self._settings.vad_silence_threshold_secs is not None: params.append( - f"vad_silence_threshold_secs={self._params.vad_silence_threshold_secs}" + f"vad_silence_threshold_secs={self._settings.vad_silence_threshold_secs}" + ) + if self._settings.vad_threshold is not None: + params.append(f"vad_threshold={self._settings.vad_threshold}") + if self._settings.min_speech_duration_ms is not None: + params.append(f"min_speech_duration_ms={self._settings.min_speech_duration_ms}") + if self._settings.min_silence_duration_ms is not None: + params.append( + f"min_silence_duration_ms={self._settings.min_silence_duration_ms}" ) - if self._params.vad_threshold is not None: - params.append(f"vad_threshold={self._params.vad_threshold}") - if self._params.min_speech_duration_ms is not None: - params.append(f"min_speech_duration_ms={self._params.min_speech_duration_ms}") - if self._params.min_silence_duration_ms is not None: - params.append(f"min_silence_duration_ms={self._params.min_silence_duration_ms}") ws_url = f"wss://{self._base_url}/v1/speech-to-text/realtime?{'&'.join(params)}" @@ -817,7 +870,7 @@ class ElevenLabsRealtimeSTTService(WebsocketSTTService): """ # If timestamps are enabled, skip this message and wait for the # committed_transcript_with_timestamps message which contains all the data - if self._params.include_timestamps: + if self._settings.include_timestamps: return text = data.get("text", "").strip() diff --git a/src/pipecat/services/elevenlabs/tts.py b/src/pipecat/services/elevenlabs/tts.py index 4dab0c01a..b061383f3 100644 --- a/src/pipecat/services/elevenlabs/tts.py +++ b/src/pipecat/services/elevenlabs/tts.py @@ -13,7 +13,19 @@ with support for streaming audio, word timestamps, and voice customization. import asyncio import base64 import json -from typing import Any, AsyncGenerator, Dict, List, Literal, Mapping, Optional, Tuple, Union +from dataclasses import dataclass, field +from typing import ( + Any, + AsyncGenerator, + ClassVar, + Dict, + List, + Literal, + Mapping, + Optional, + Tuple, + Union, +) import aiohttp from loguru import logger @@ -32,6 +44,7 @@ from pipecat.frames.frames import ( TTSStoppedFrame, ) from pipecat.processors.frame_processor import FrameDirection +from pipecat.services.settings import NOT_GIVEN, TTSSettings, is_given from pipecat.services.tts_service import ( AudioContextWordTTSService, WordTTSService, @@ -136,12 +149,12 @@ def output_format_from_sample_rate(sample_rate: int) -> str: def build_elevenlabs_voice_settings( - settings: Dict[str, Any], + settings: Union[Dict[str, Any], "TTSSettings"], ) -> Optional[Dict[str, Union[float, bool]]]: """Build voice settings dictionary for ElevenLabs based on provided settings. Args: - settings: Dictionary containing voice settings parameters. + settings: Dictionary or typed settings containing voice settings parameters. Returns: Dictionary of voice settings or None if no valid settings are provided. @@ -150,8 +163,11 @@ def build_elevenlabs_voice_settings( voice_settings = {} for key in voice_setting_keys: - if key in settings and settings[key] is not None: - voice_settings[key] = settings[key] + val = ( + getattr(settings, key, None) if isinstance(settings, TTSSettings) else settings.get(key) + ) + if val is not None and is_given(val): + voice_settings[key] = val return voice_settings or None @@ -168,6 +184,75 @@ class PronunciationDictionaryLocator(BaseModel): version_id: str +@dataclass +class ElevenLabsTTSSettings(TTSSettings): + """Typed settings for the ElevenLabs WebSocket TTS service. + + Fields that appear in the WebSocket URL (``voice``, ``model``, + ``language``) require a full reconnect when changed. Fields that + affect the voice character (``stability``, ``similarity_boost``, + ``style``, ``use_speaker_boost``, ``speed``) can be applied by closing + the current audio context so a new one is opened with updated settings. + + Parameters: + stability: Voice stability control (0.0 to 1.0). + similarity_boost: Similarity boost control (0.0 to 1.0). + style: Style control for voice expression (0.0 to 1.0). + use_speaker_boost: Whether to use speaker boost enhancement. + speed: Voice speed control (0.7 to 1.2). + auto_mode: Whether to enable automatic mode optimization. + enable_ssml_parsing: Whether to parse SSML tags in text. + enable_logging: Whether to enable ElevenLabs logging. + apply_text_normalization: Text normalization mode ("auto", "on", "off"). + """ + + stability: float = field(default_factory=lambda: NOT_GIVEN) + similarity_boost: float = field(default_factory=lambda: NOT_GIVEN) + style: float = field(default_factory=lambda: NOT_GIVEN) + use_speaker_boost: bool = field(default_factory=lambda: NOT_GIVEN) + speed: float = field(default_factory=lambda: NOT_GIVEN) + auto_mode: str = field(default_factory=lambda: NOT_GIVEN) + enable_ssml_parsing: bool = field(default_factory=lambda: NOT_GIVEN) + enable_logging: bool = field(default_factory=lambda: NOT_GIVEN) + apply_text_normalization: str = field(default_factory=lambda: NOT_GIVEN) + + #: Fields in the WS URL — changing any of these requires a reconnect. + URL_FIELDS: ClassVar[frozenset[str]] = frozenset({"voice", "model", "language"}) + + #: Fields affecting voice character — changing these requires closing the + #: current audio context so the next one picks up new settings. + VOICE_SETTINGS_FIELDS: ClassVar[frozenset[str]] = frozenset( + {"stability", "similarity_boost", "style", "use_speaker_boost", "speed"} + ) + + _aliases: ClassVar[Dict[str, str]] = {"voice_id": "voice"} + + +@dataclass +class ElevenLabsHttpTTSSettings(TTSSettings): + """Typed settings for the ElevenLabs HTTP TTS service. + + Parameters: + optimize_streaming_latency: Latency optimization level (0-4). + stability: Voice stability control (0.0 to 1.0). + similarity_boost: Similarity boost control (0.0 to 1.0). + style: Style control for voice expression (0.0 to 1.0). + use_speaker_boost: Whether to use speaker boost enhancement. + speed: Voice speed control (0.25 to 4.0). + apply_text_normalization: Text normalization mode ("auto", "on", "off"). + """ + + optimize_streaming_latency: int = field(default_factory=lambda: NOT_GIVEN) + stability: float = field(default_factory=lambda: NOT_GIVEN) + similarity_boost: float = field(default_factory=lambda: NOT_GIVEN) + style: float = field(default_factory=lambda: NOT_GIVEN) + use_speaker_boost: bool = field(default_factory=lambda: NOT_GIVEN) + speed: float = field(default_factory=lambda: NOT_GIVEN) + apply_text_normalization: str = field(default_factory=lambda: NOT_GIVEN) + + _aliases: ClassVar[Dict[str, str]] = {"voice_id": "voice"} + + def calculate_word_times( alignment_info: Mapping[str, Any], cumulative_time: float, @@ -316,22 +401,25 @@ class ElevenLabsTTSService(AudioContextWordTTSService): self._api_key = api_key self._url = url - self._settings = { - "language": self.language_to_service_language(params.language) - if params.language - else None, - "stability": params.stability, - "similarity_boost": params.similarity_boost, - "style": params.style, - "use_speaker_boost": params.use_speaker_boost, - "speed": params.speed, - "auto_mode": str(params.auto_mode).lower(), - "enable_ssml_parsing": params.enable_ssml_parsing, - "enable_logging": params.enable_logging, - "apply_text_normalization": params.apply_text_normalization, - } + self._settings: ElevenLabsTTSSettings = ElevenLabsTTSSettings( + model=model, + voice=voice_id, + language=( + self.language_to_service_language(params.language) if params.language else None + ), + stability=params.stability, + similarity_boost=params.similarity_boost, + style=params.style, + use_speaker_boost=params.use_speaker_boost, + speed=params.speed, + auto_mode=str(params.auto_mode).lower(), + enable_ssml_parsing=params.enable_ssml_parsing, + enable_logging=params.enable_logging, + apply_text_normalization=params.apply_text_normalization, + ) self.set_model_name(model) - self.set_voice(voice_id) + self._voice_id = voice_id + self._output_format = "" # initialized in start() self._voice_settings = self._set_voice_settings() self._pronunciation_dictionary_locators = params.pronunciation_dictionary_locators @@ -366,54 +454,57 @@ class ElevenLabsTTSService(AudioContextWordTTSService): return language_to_elevenlabs_language(language) def _set_voice_settings(self): - return build_elevenlabs_voice_settings(self._settings) + ts = self._settings + voice_setting_keys = [ + "stability", + "similarity_boost", + "style", + "use_speaker_boost", + "speed", + ] + voice_settings = {} + for key in voice_setting_keys: + val = getattr(ts, key, None) + if val is not None and is_given(val): + voice_settings[key] = val + return voice_settings or None - async def set_model(self, model: str): - """Set the TTS model and reconnect. + async def _update_settings_from_typed(self, update: TTSSettings) -> set[str]: + """Apply a typed settings update, reconnecting as needed. + + Uses the declarative ``URL_FIELDS`` and ``VOICE_SETTINGS_FIELDS`` + sets on :class:`ElevenLabsTTSSettings` to decide whether to + reconnect the WebSocket or close the current audio context. Args: - model: The model name to use for synthesis. + update: A :class:`TTSSettings` (or ``ElevenLabsTTSSettings``) delta. + + Returns: + Set of field names whose values actually changed. """ - await super().set_model(model) - logger.info(f"Switching TTS model to: [{model}]") - await self._disconnect() - await self._connect() + changed = await super()._update_settings_from_typed(update) - async def _update_settings(self, settings: Mapping[str, Any]): - """Update service settings and reconnect if voice, model, or language changed.""" - # Track previous values for settings that require reconnection - prev_voice = self._voice_id - prev_model = self.model_name - prev_language = self._settings.get("language") - # Create snapshot of current voice settings to detect changes after update - prev_voice_settings = self._voice_settings.copy() if self._voice_settings else None + if not changed: + return changed - await super()._update_settings(settings) - - # Update voice settings for the next context creation + # Rebuild voice settings for next context self._voice_settings = self._set_voice_settings() - # Check if URL-level settings changed (these require reconnection) - url_changed = ( - prev_voice != self._voice_id - or prev_model != self.model_name - or prev_language != self._settings.get("language") - ) - - # Check if only voice settings changed (speed, stability, etc.) - voice_settings_changed = prev_voice_settings != self._voice_settings + url_changed = bool(changed & ElevenLabsTTSSettings.URL_FIELDS) + voice_settings_changed = bool(changed & ElevenLabsTTSSettings.VOICE_SETTINGS_FIELDS) if url_changed: - # These settings are in the WebSocket URL, so we need to reconnect logger.debug( - f"URL-level setting changed (voice/model/language), reconnecting WebSocket" + f"URL-level setting changed ({changed & ElevenLabsTTSSettings.URL_FIELDS}), " + f"reconnecting WebSocket" ) await self._disconnect() await self._connect() elif voice_settings_changed and self._context_id: - # Voice settings can be updated by closing current context - # so new one gets created with updated voice settings - logger.debug(f"Voice settings changed, closing current context to apply changes") + logger.debug( + f"Voice settings changed ({changed & ElevenLabsTTSSettings.VOICE_SETTINGS_FIELDS}), " + f"closing current context to apply changes" + ) try: if self._websocket: await self._websocket.send( @@ -423,6 +514,8 @@ class ElevenLabsTTSService(AudioContextWordTTSService): await self.push_error(error_msg=f"Unknown error occurred: {e}", exception=e) self._context_id = None + return changed + async def start(self, frame: StartFrame): """Start the ElevenLabs TTS service. @@ -505,19 +598,19 @@ class ElevenLabsTTSService(AudioContextWordTTSService): voice_id = self._voice_id model = self.model_name output_format = self._output_format - url = f"{self._url}/v1/text-to-speech/{voice_id}/multi-stream-input?model_id={model}&output_format={output_format}&auto_mode={self._settings['auto_mode']}" + url = f"{self._url}/v1/text-to-speech/{voice_id}/multi-stream-input?model_id={model}&output_format={output_format}&auto_mode={self._settings.auto_mode}" - if self._settings["enable_ssml_parsing"]: - url += f"&enable_ssml_parsing={self._settings['enable_ssml_parsing']}" + if self._settings.enable_ssml_parsing: + url += f"&enable_ssml_parsing={self._settings.enable_ssml_parsing}" - if self._settings["enable_logging"]: - url += f"&enable_logging={self._settings['enable_logging']}" + if self._settings.enable_logging: + url += f"&enable_logging={self._settings.enable_logging}" - if self._settings["apply_text_normalization"] is not None: - url += f"&apply_text_normalization={self._settings['apply_text_normalization']}" + if self._settings.apply_text_normalization is not None: + url += f"&apply_text_normalization={self._settings.apply_text_normalization}" # Language can only be used with the ELEVENLABS_MULTILINGUAL_MODELS - language = self._settings["language"] + language = self._settings.language if model in ELEVENLABS_MULTILINGUAL_MODELS and language is not None: url += f"&language_code={language}" logger.debug(f"Using language code: {language}") @@ -809,20 +902,22 @@ class ElevenLabsHttpTTSService(WordTTSService): self._params = params self._session = aiohttp_session - self._settings = { - "language": self.language_to_service_language(params.language) + self._settings: ElevenLabsHttpTTSSettings = ElevenLabsHttpTTSSettings( + model=model, + voice=voice_id, + language=self.language_to_service_language(params.language) if params.language else None, - "optimize_streaming_latency": params.optimize_streaming_latency, - "stability": params.stability, - "similarity_boost": params.similarity_boost, - "style": params.style, - "use_speaker_boost": params.use_speaker_boost, - "speed": params.speed, - "apply_text_normalization": params.apply_text_normalization, - } + optimize_streaming_latency=params.optimize_streaming_latency, + stability=params.stability, + similarity_boost=params.similarity_boost, + style=params.style, + use_speaker_boost=params.use_speaker_boost, + speed=params.speed, + apply_text_normalization=params.apply_text_normalization, + ) self.set_model_name(model) - self.set_voice(voice_id) + self._voice_id = voice_id self._output_format = "" # initialized in start() self._voice_settings = self._set_voice_settings() self._pronunciation_dictionary_locators = params.pronunciation_dictionary_locators @@ -859,10 +954,19 @@ class ElevenLabsHttpTTSService(WordTTSService): def _set_voice_settings(self): return build_elevenlabs_voice_settings(self._settings) - async def _update_settings(self, settings: Mapping[str, Any]): - await super()._update_settings(settings) - # Update voice settings for the next context creation - self._voice_settings = self._set_voice_settings() + async def _update_settings_from_typed(self, update: TTSSettings) -> set[str]: + """Apply a typed settings update and rebuild voice settings. + + Args: + update: A :class:`TTSSettings` (or ``ElevenLabsHttpTTSSettings``) delta. + + Returns: + Set of field names whose values actually changed. + """ + changed = await super()._update_settings_from_typed(update) + if changed: + self._voice_settings = self._set_voice_settings() + return changed def _reset_state(self): """Reset internal state variables.""" @@ -999,10 +1103,13 @@ class ElevenLabsHttpTTSService(WordTTSService): locator.model_dump() for locator in self._pronunciation_dictionary_locators ] - if self._settings["apply_text_normalization"] is not None: - payload["apply_text_normalization"] = self._settings["apply_text_normalization"] + if ( + is_given(self._settings.apply_text_normalization) + and self._settings.apply_text_normalization is not None + ): + payload["apply_text_normalization"] = self._settings.apply_text_normalization - language = self._settings["language"] + language = self._settings.language if self._model_name in ELEVENLABS_MULTILINGUAL_MODELS and language: payload["language_code"] = language logger.debug(f"Using language code: {language}") @@ -1020,8 +1127,11 @@ class ElevenLabsHttpTTSService(WordTTSService): params = { "output_format": self._output_format, } - if self._settings["optimize_streaming_latency"] is not None: - params["optimize_streaming_latency"] = self._settings["optimize_streaming_latency"] + if ( + is_given(self._settings.optimize_streaming_latency) + and self._settings.optimize_streaming_latency is not None + ): + params["optimize_streaming_latency"] = self._settings.optimize_streaming_latency try: await self.start_ttfb_metrics() diff --git a/src/pipecat/services/fal/stt.py b/src/pipecat/services/fal/stt.py index 4e8a655ec..eef0e0487 100644 --- a/src/pipecat/services/fal/stt.py +++ b/src/pipecat/services/fal/stt.py @@ -11,12 +11,14 @@ transcription using segmented audio processing. """ import os +from dataclasses import dataclass, field from typing import AsyncGenerator, Optional from loguru import logger from pydantic import BaseModel from pipecat.frames.frames import ErrorFrame, Frame, TranscriptionFrame +from pipecat.services.settings import NOT_GIVEN, STTSettings from pipecat.services.stt_latency import FAL_TTFS_P99 from pipecat.services.stt_service import SegmentedSTTService from pipecat.transcriptions.language import Language, resolve_language @@ -146,6 +148,22 @@ def language_to_fal_language(language: Language) -> Optional[str]: return resolve_language(language, LANGUAGE_MAP, use_base_code=True) +@dataclass +class FalSTTSettings(STTSettings): + """Typed settings for the Fal Wizper STT service. + + Parameters: + task: Task to perform ('transcribe' or 'translate'). Defaults to + 'transcribe'. + chunk_level: Level of chunking ('segment'). Defaults to 'segment'. + version: Version of Wizper model to use. Defaults to '3'. + """ + + task: str = field(default_factory=lambda: NOT_GIVEN) + chunk_level: str = field(default_factory=lambda: NOT_GIVEN) + version: str = field(default_factory=lambda: NOT_GIVEN) + + class FalSTTService(SegmentedSTTService): """Speech-to-text service using Fal's Wizper API. @@ -203,14 +221,14 @@ class FalSTTService(SegmentedSTTService): ) self._fal_client = fal_client.AsyncClient(key=api_key or os.getenv("FAL_KEY")) - self._settings = { - "task": params.task, - "language": self.language_to_service_language(params.language) + self._settings: FalSTTSettings = FalSTTSettings( + language=self.language_to_service_language(params.language) if params.language else "en", - "chunk_level": params.chunk_level, - "version": params.version, - } + task=params.task, + chunk_level=params.chunk_level, + version=params.version, + ) def can_generate_metrics(self) -> bool: """Check if the service can generate processing metrics. @@ -231,23 +249,17 @@ class FalSTTService(SegmentedSTTService): """ return language_to_fal_language(language) - async def set_language(self, language: Language): - """Set the transcription language. + async def _update_settings_from_typed(self, update: STTSettings) -> set[str]: + """Apply a typed settings update, converting language if changed.""" + changed = await super()._update_settings_from_typed(update) - Args: - language: The language to use for speech-to-text transcription. - """ - logger.info(f"Switching STT language to: [{language}]") - self._settings["language"] = self.language_to_service_language(language) + if "language" in changed: + # Convert the Language enum to a Fal language code. + lang = self._settings.language + if isinstance(lang, Language): + self._settings.language = self.language_to_service_language(lang) - async def set_model(self, model: str): - """Set the STT model. - - Args: - model: The model name to use for transcription. - """ - await super().set_model(model) - logger.info(f"Switching STT model to: [{model}]") + return changed @traced_stt async def _handle_transcription( @@ -276,19 +288,19 @@ class FalSTTService(SegmentedSTTService): data_uri = fal_client.encode(audio, "audio/x-wav") response = await self._fal_client.run( "fal-ai/wizper", - arguments={"audio_url": data_uri, **self._settings}, + arguments={"audio_url": data_uri, **self._settings.given_fields()}, ) if response and "text" in response: text = response["text"].strip() if text: # Only yield non-empty text - await self._handle_transcription(text, True, self._settings["language"]) + await self._handle_transcription(text, True, self._settings.language) logger.debug(f"Transcription: [{text}]") yield TranscriptionFrame( text, self._user_id, time_now_iso8601(), - Language(self._settings["language"]), + Language(self._settings.language), result=response, ) diff --git a/src/pipecat/services/fireworks/llm.py b/src/pipecat/services/fireworks/llm.py index d7bf57908..9338d8c5a 100644 --- a/src/pipecat/services/fireworks/llm.py +++ b/src/pipecat/services/fireworks/llm.py @@ -68,15 +68,15 @@ class FireworksLLMService(OpenAILLMService): params = { "model": self.model_name, "stream": True, - "frequency_penalty": self._settings["frequency_penalty"], - "presence_penalty": self._settings["presence_penalty"], - "temperature": self._settings["temperature"], - "top_p": self._settings["top_p"], - "max_tokens": self._settings["max_tokens"], + "frequency_penalty": self._settings.frequency_penalty, + "presence_penalty": self._settings.presence_penalty, + "temperature": self._settings.temperature, + "top_p": self._settings.top_p, + "max_tokens": self._settings.max_tokens, } # Messages, tools, tool_choice params.update(params_from_context) - params.update(self._settings["extra"]) + params.update(self._settings.extra) return params diff --git a/src/pipecat/services/fish/tts.py b/src/pipecat/services/fish/tts.py index 93a718429..5517758ad 100644 --- a/src/pipecat/services/fish/tts.py +++ b/src/pipecat/services/fish/tts.py @@ -11,6 +11,7 @@ for streaming text-to-speech synthesis with customizable voice parameters. """ import uuid +from dataclasses import dataclass, field from typing import AsyncGenerator, Literal, Optional from loguru import logger @@ -28,6 +29,7 @@ from pipecat.frames.frames import ( TTSStoppedFrame, ) from pipecat.processors.frame_processor import FrameDirection +from pipecat.services.settings import NOT_GIVEN, TTSSettings from pipecat.services.tts_service import InterruptibleTTSService from pipecat.transcriptions.language import Language from pipecat.utils.tracing.service_decorators import traced_tts @@ -45,6 +47,29 @@ except ModuleNotFoundError as e: FishAudioOutputFormat = Literal["opus", "mp3", "pcm", "wav"] +@dataclass +class FishAudioTTSSettings(TTSSettings): + """Typed settings for Fish Audio TTS service. + + Parameters: + fish_sample_rate: Audio sample rate sent to the API. + latency: Latency mode ("normal" or "balanced"). Defaults to "normal". + format: Audio output format. + normalize: Whether to normalize audio output. Defaults to True. + prosody_speed: Speech speed multiplier (0.5-2.0). Defaults to 1.0. + prosody_volume: Volume adjustment in dB. Defaults to 0. + reference_id: Reference ID of the voice model. + """ + + fish_sample_rate: int = field(default_factory=lambda: NOT_GIVEN) + latency: str = field(default_factory=lambda: NOT_GIVEN) + format: str = field(default_factory=lambda: NOT_GIVEN) + normalize: bool = field(default_factory=lambda: NOT_GIVEN) + prosody_speed: float = field(default_factory=lambda: NOT_GIVEN) + prosody_volume: int = field(default_factory=lambda: NOT_GIVEN) + reference_id: str = field(default_factory=lambda: NOT_GIVEN) + + class FishAudioTTSService(InterruptibleTTSService): """Fish Audio text-to-speech service with WebSocket streaming. @@ -136,17 +161,16 @@ class FishAudioTTSService(InterruptibleTTSService): self._receive_task = None self._request_id = None - self._settings = { - "sample_rate": 0, - "latency": params.latency, - "format": output_format, - "normalize": params.normalize, - "prosody": { - "speed": params.prosody_speed, - "volume": params.prosody_volume, - }, - "reference_id": reference_id, - } + self._settings: FishAudioTTSSettings = FishAudioTTSSettings( + voice=reference_id, + fish_sample_rate=0, + latency=params.latency, + format=output_format, + normalize=params.normalize, + prosody_speed=params.prosody_speed, + prosody_volume=params.prosody_volume, + reference_id=reference_id, + ) self.set_model_name(model_id) @@ -158,16 +182,22 @@ class FishAudioTTSService(InterruptibleTTSService): """ return True - async def set_model(self, model: str): - """Set the TTS model and reconnect. + async def _update_settings_from_typed(self, update: TTSSettings) -> set[str]: + """Apply a typed settings update and reconnect if needed. + + Any change to voice or model triggers a WebSocket reconnect. Args: - model: The model name to use for synthesis. + update: A :class:`TTSSettings` (or ``FishAudioTTSSettings``) delta. + + Returns: + Set of field names whose values actually changed. """ - await super().set_model(model) - logger.info(f"Switching TTS model to: [{model}]") - await self._disconnect() - await self._connect() + changed = await super()._update_settings_from_typed(update) + if changed: + await self._disconnect() + await self._connect() + return changed async def start(self, frame: StartFrame): """Start the Fish Audio TTS service. @@ -176,7 +206,7 @@ class FishAudioTTSService(InterruptibleTTSService): frame: The start frame containing initialization parameters. """ await super().start(frame) - self._settings["sample_rate"] = self.sample_rate + self._settings.fish_sample_rate = self.sample_rate await self._connect() async def stop(self, frame: EndFrame): @@ -225,7 +255,18 @@ class FishAudioTTSService(InterruptibleTTSService): self._websocket = await websocket_connect(self._base_url, additional_headers=headers) # Send initial start message with ormsgpack - start_message = {"event": "start", "request": {"text": "", **self._settings}} + request_settings = { + "sample_rate": self._settings.fish_sample_rate, + "latency": self._settings.latency, + "format": self._settings.format, + "normalize": self._settings.normalize, + "prosody": { + "speed": self._settings.prosody_speed, + "volume": self._settings.prosody_volume, + }, + "reference_id": self._settings.reference_id, + } + start_message = {"event": "start", "request": {"text": "", **request_settings}} await self._websocket.send(ormsgpack.packb(start_message)) logger.debug("Sent start message to Fish Audio") diff --git a/src/pipecat/services/gladia/stt.py b/src/pipecat/services/gladia/stt.py index 475a7213e..76a1620e1 100644 --- a/src/pipecat/services/gladia/stt.py +++ b/src/pipecat/services/gladia/stt.py @@ -14,6 +14,7 @@ import asyncio import base64 import json import warnings +from dataclasses import dataclass, field from typing import Any, AsyncGenerator, Dict, Literal, Optional import aiohttp @@ -32,6 +33,7 @@ from pipecat.frames.frames import ( UserStoppedSpeakingFrame, ) from pipecat.services.gladia.config import GladiaInputParams +from pipecat.services.settings import NOT_GIVEN, STTSettings from pipecat.services.stt_latency import GLADIA_TTFS_P99 from pipecat.services.stt_service import WebsocketSTTService from pipecat.transcriptions.language import Language, resolve_language @@ -178,6 +180,17 @@ class _InputParamsDescriptor: return GladiaInputParams +@dataclass +class GladiaSTTSettings(STTSettings): + """Typed settings for Gladia STT service. + + Parameters: + input_params: Gladia ``GladiaInputParams`` for detailed configuration. + """ + + input_params: GladiaInputParams = field(default_factory=lambda: NOT_GIVEN) + + class GladiaSTTService(WebsocketSTTService): """Speech-to-Text service using Gladia's API. @@ -265,9 +278,8 @@ class GladiaSTTService(WebsocketSTTService): self._region = region self._url = url self.set_model_name(model) - self._params = params self._receive_task = None - self._settings = {} + self._settings = GladiaSTTSettings(model=model, input_params=params) # Session management self._session_url = None @@ -307,31 +319,33 @@ class GladiaSTTService(WebsocketSTTService): return language_to_gladia_language(language) def _prepare_settings(self) -> Dict[str, Any]: + params = self._settings.input_params + settings = { - "encoding": self._params.encoding or "wav/pcm", - "bit_depth": self._params.bit_depth or 16, + "encoding": params.encoding or "wav/pcm", + "bit_depth": params.bit_depth or 16, "sample_rate": self.sample_rate, - "channels": self._params.channels or 1, + "channels": params.channels or 1, "model": self._model_name, } # Add custom_metadata if provided - settings["custom_metadata"] = dict(self._params.custom_metadata or {}) + settings["custom_metadata"] = dict(params.custom_metadata or {}) settings["custom_metadata"]["pipecat"] = pipecat_version() # Add endpointing parameters if provided - if self._params.endpointing is not None: - settings["endpointing"] = self._params.endpointing - if self._params.maximum_duration_without_endpointing is not None: + if params.endpointing is not None: + settings["endpointing"] = params.endpointing + if params.maximum_duration_without_endpointing is not None: settings["maximum_duration_without_endpointing"] = ( - self._params.maximum_duration_without_endpointing + params.maximum_duration_without_endpointing ) # Add language configuration (prioritize language_config over deprecated language) - if self._params.language_config: - settings["language_config"] = self._params.language_config.model_dump(exclude_none=True) - elif self._params.language: # Backward compatibility for deprecated parameter - language_code = self.language_to_service_language(self._params.language) + if params.language_config: + settings["language_config"] = params.language_config.model_dump(exclude_none=True) + elif params.language: # Backward compatibility for deprecated parameter + language_code = self.language_to_service_language(params.language) if language_code: settings["language_config"] = { "languages": [language_code], @@ -339,21 +353,18 @@ class GladiaSTTService(WebsocketSTTService): } # Add pre_processing configuration if provided - if self._params.pre_processing: - settings["pre_processing"] = self._params.pre_processing.model_dump(exclude_none=True) + if params.pre_processing: + settings["pre_processing"] = params.pre_processing.model_dump(exclude_none=True) # Add realtime_processing configuration if provided - if self._params.realtime_processing: - settings["realtime_processing"] = self._params.realtime_processing.model_dump( + if params.realtime_processing: + settings["realtime_processing"] = params.realtime_processing.model_dump( exclude_none=True ) # Add messages_config if provided - if self._params.messages_config: - settings["messages_config"] = self._params.messages_config.model_dump(exclude_none=True) - - # Store settings for tracing - self._settings = settings + if params.messages_config: + settings["messages_config"] = params.messages_config.model_dump(exclude_none=True) return settings @@ -366,6 +377,31 @@ class GladiaSTTService(WebsocketSTTService): await super().start(frame) await self._connect() + async def _update_settings_from_typed(self, update: GladiaSTTSettings) -> set[str]: + """Apply typed settings update. + + Gladia sessions are fixed at creation time, so any change requires + a full session teardown and reconnect. + + Args: + update: A typed settings delta. + + Returns: + Set of field names whose values actually changed. + """ + changed = await super()._update_settings_from_typed(update) + + if not changed: + return changed + + # Gladia sessions are fixed — need to tear down and recreate + self._session_url = None + self._session_id = None + await self._disconnect() + await self._connect() + + return changed + async def stop(self, frame: EndFrame): """Stop the Gladia STT websocket connection. @@ -522,7 +558,7 @@ class GladiaSTTService(WebsocketSTTService): Broadcasts UserStartedSpeakingFrame and optionally triggers interruption when VAD is enabled. """ - if not self._params.enable_vad or self._is_speaking: + if not self._settings.input_params.enable_vad or self._is_speaking: return logger.debug(f"{self} User started speaking") @@ -537,7 +573,7 @@ class GladiaSTTService(WebsocketSTTService): Broadcasts UserStoppedSpeakingFrame when VAD is enabled. """ - if not self._params.enable_vad or not self._is_speaking: + if not self._settings.input_params.enable_vad or not self._is_speaking: return self._is_speaking = False await self.broadcast_frame(UserStoppedSpeakingFrame) diff --git a/src/pipecat/services/google/gemini_live/llm.py b/src/pipecat/services/google/gemini_live/llm.py index e209f3d0a..1edab5783 100644 --- a/src/pipecat/services/google/gemini_live/llm.py +++ b/src/pipecat/services/google/gemini_live/llm.py @@ -17,9 +17,9 @@ import io import time import uuid import warnings -from dataclasses import dataclass +from dataclasses import dataclass, field from enum import Enum -from typing import Any, Dict, List, Optional, Union +from typing import Any, ClassVar, Dict, List, Optional, Union from loguru import logger from PIL import Image @@ -47,7 +47,6 @@ from pipecat.frames.frames import ( LLMThoughtEndFrame, LLMThoughtStartFrame, LLMThoughtTextFrame, - LLMUpdateSettingsFrame, StartFrame, TranscriptionFrame, TTSAudioRawFrame, @@ -77,6 +76,7 @@ from pipecat.services.openai.llm import ( OpenAIAssistantContextAggregator, OpenAIUserContextAggregator, ) +from pipecat.services.settings import NOT_GIVEN, LLMSettings from pipecat.transcriptions.language import Language, resolve_language from pipecat.utils.string import match_endofsentence from pipecat.utils.time import time_now_iso8601 @@ -602,6 +602,31 @@ class InputParams(BaseModel): extra: Optional[Dict[str, Any]] = Field(default_factory=dict) +@dataclass +class GeminiLiveLLMSettings(LLMSettings): + """Typed settings for Gemini Live LLM services. + + Parameters: + modalities: Response modalities. + language: Language for generation. + media_resolution: Media resolution setting. + vad: Voice activity detection parameters. + context_window_compression: Context window compression configuration. + thinking: Thinking configuration. + enable_affective_dialog: Whether to enable affective dialog. + proactivity: Proactivity configuration. + """ + + modalities: Any = field(default_factory=lambda: NOT_GIVEN) + language: Any = field(default_factory=lambda: NOT_GIVEN) + media_resolution: Any = field(default_factory=lambda: NOT_GIVEN) + vad: Any = field(default_factory=lambda: NOT_GIVEN) + context_window_compression: Any = field(default_factory=lambda: NOT_GIVEN) + thinking: Any = field(default_factory=lambda: NOT_GIVEN) + enable_affective_dialog: Any = field(default_factory=lambda: NOT_GIVEN) + proactivity: Any = field(default_factory=lambda: NOT_GIVEN) + + class GeminiLiveLLMService(LLMService): """Provides access to Google's Gemini Live API. @@ -714,25 +739,26 @@ class GeminiLiveLLMService(LLMService): self._consecutive_failures = 0 self._connection_start_time = None - self._settings = { - "frequency_penalty": params.frequency_penalty, - "max_tokens": params.max_tokens, - "presence_penalty": params.presence_penalty, - "temperature": params.temperature, - "top_k": params.top_k, - "top_p": params.top_p, - "modalities": params.modalities, - "language": self._language_code, - "media_resolution": params.media_resolution, - "vad": params.vad, - "context_window_compression": params.context_window_compression.model_dump() + self._settings = GeminiLiveLLMSettings( + model=model, + frequency_penalty=params.frequency_penalty, + max_tokens=params.max_tokens, + presence_penalty=params.presence_penalty, + temperature=params.temperature, + top_k=params.top_k, + top_p=params.top_p, + modalities=params.modalities, + language=self._language_code, + media_resolution=params.media_resolution, + vad=params.vad, + context_window_compression=params.context_window_compression.model_dump() if params.context_window_compression else {}, - "thinking": params.thinking or {}, - "enable_affective_dialog": params.enable_affective_dialog or False, - "proactivity": params.proactivity or {}, - "extra": params.extra if isinstance(params.extra, dict) else {}, - } + thinking=params.thinking or {}, + enable_affective_dialog=params.enable_affective_dialog or False, + proactivity=params.proactivity or {}, + extra=params.extra if isinstance(params.extra, dict) else {}, + ) self._file_api_base_url = file_api_base_url self._file_api: Optional[GeminiFileAPI] = None @@ -798,7 +824,7 @@ class GeminiLiveLLMService(LLMService): Args: modalities: The modalities to use for responses. """ - self._settings["modalities"] = modalities + self._settings.modalities = modalities def set_language(self, language: Language): """Set the language for generation. @@ -808,7 +834,7 @@ class GeminiLiveLLMService(LLMService): """ self._language = language self._language_code = language_to_gemini_language(language) or "en-US" - self._settings["language"] = self._language_code + self._settings.language = self._language_code logger.info(f"Set Gemini language to: {self._language_code}") async def set_context(self, context: OpenAILLMContext): @@ -866,7 +892,7 @@ class GeminiLiveLLMService(LLMService): async def _handle_interruption(self): if self._bot_is_responding: await self._set_bot_is_responding(False) - if self._settings.get("modalities") == GeminiModalities.AUDIO: + if self._settings.modalities == GeminiModalities.AUDIO: await self.push_frame(TTSStoppedFrame()) # Do not send LLMFullResponseEndFrame here - an interruption # already tells the assistant context aggregator that the response @@ -947,8 +973,6 @@ class GeminiLiveLLMService(LLMService): # uses this frame *without* a user context aggregator still works # (we have an example that does just that, actually). await self._create_single_response(frame.messages) - elif isinstance(frame, LLMUpdateSettingsFrame): - await self._update_settings(frame.settings) elif isinstance(frame, LLMSetToolsFrame): await self._update_settings() else: @@ -1074,20 +1098,20 @@ class GeminiLiveLLMService(LLMService): # Assemble basic configuration config = LiveConnectConfig( generation_config=GenerationConfig( - frequency_penalty=self._settings["frequency_penalty"], - max_output_tokens=self._settings["max_tokens"], - presence_penalty=self._settings["presence_penalty"], - temperature=self._settings["temperature"], - top_k=self._settings["top_k"], - top_p=self._settings["top_p"], - response_modalities=[Modality(self._settings["modalities"].value)], + frequency_penalty=self._settings.frequency_penalty, + max_output_tokens=self._settings.max_tokens, + presence_penalty=self._settings.presence_penalty, + temperature=self._settings.temperature, + top_k=self._settings.top_k, + top_p=self._settings.top_p, + response_modalities=[Modality(self._settings.modalities.value)], speech_config=SpeechConfig( voice_config=VoiceConfig( prebuilt_voice_config={"voice_name": self._voice_id} ), - language_code=self._settings["language"], + language_code=self._settings.language, ), - media_resolution=MediaResolution(self._settings["media_resolution"].value), + media_resolution=MediaResolution(self._settings.media_resolution.value), ), input_audio_transcription=AudioTranscriptionConfig(), output_audio_transcription=AudioTranscriptionConfig(), @@ -1095,37 +1119,36 @@ class GeminiLiveLLMService(LLMService): ) # Add context window compression to configuration, if enabled - if self._settings.get("context_window_compression", {}).get("enabled", False): + cwc = self._settings.context_window_compression or {} + if cwc.get("enabled", False): compression_config = ContextWindowCompressionConfig() # Add sliding window (always true if compression is enabled) compression_config.sliding_window = SlidingWindow() # Add trigger_tokens if specified - trigger_tokens = self._settings.get("context_window_compression", {}).get( - "trigger_tokens" - ) + trigger_tokens = cwc.get("trigger_tokens") if trigger_tokens is not None: compression_config.trigger_tokens = trigger_tokens config.context_window_compression = compression_config # Add thinking configuration to configuration, if provided - if self._settings.get("thinking"): - config.thinking_config = self._settings["thinking"] + if self._settings.thinking: + config.thinking_config = self._settings.thinking # Add affective dialog setting, if provided - if self._settings.get("enable_affective_dialog", False): - config.enable_affective_dialog = self._settings["enable_affective_dialog"] + if self._settings.enable_affective_dialog: + config.enable_affective_dialog = self._settings.enable_affective_dialog # Add proactivity configuration to configuration, if provided - if self._settings.get("proactivity"): - config.proactivity = self._settings["proactivity"] + if self._settings.proactivity: + config.proactivity = self._settings.proactivity # Add VAD configuration to configuration, if provided - if self._settings.get("vad"): + if self._settings.vad: vad_config = AutomaticActivityDetection() - vad_params = self._settings["vad"] + vad_params = self._settings.vad has_vad_settings = False # Only add parameters that are explicitly set @@ -1604,7 +1627,7 @@ class GeminiLiveLLMService(LLMService): text: The transcription text to push result: Optional LiveServerMessage that triggered this transcription """ - await self._handle_user_transcription(text, True, self._settings["language"]) + await self._handle_user_transcription(text, True, self._settings.language) await self.push_frame( TranscriptionFrame( text=text, diff --git a/src/pipecat/services/google/llm.py b/src/pipecat/services/google/llm.py index 563acadb3..692106241 100644 --- a/src/pipecat/services/google/llm.py +++ b/src/pipecat/services/google/llm.py @@ -15,8 +15,8 @@ import io import json import os import uuid -from dataclasses import dataclass -from typing import Any, AsyncIterator, Dict, List, Literal, Optional +from dataclasses import dataclass, field +from typing import Any, AsyncIterator, ClassVar, Dict, List, Literal, Optional from loguru import logger from PIL import Image @@ -39,7 +39,6 @@ from pipecat.frames.frames import ( LLMThoughtEndFrame, LLMThoughtStartFrame, LLMThoughtTextFrame, - LLMUpdateSettingsFrame, ) from pipecat.metrics.metrics import LLMTokenUsage from pipecat.processors.aggregators.llm_context import LLMContext @@ -59,6 +58,7 @@ from pipecat.services.openai.llm import ( OpenAIAssistantContextAggregator, OpenAIUserContextAggregator, ) +from pipecat.services.settings import NOT_GIVEN, LLMSettings from pipecat.utils.tracing.service_decorators import traced_llm # Suppress gRPC fork warnings @@ -673,6 +673,17 @@ class GoogleLLMContext(OpenAILLMContext): self._messages = [m for m in self._messages if m.parts] +@dataclass +class GoogleLLMSettings(LLMSettings): + """Typed settings for Google LLM services. + + Parameters: + thinking: Thinking configuration. + """ + + thinking: Any = field(default_factory=lambda: NOT_GIVEN) + + class GoogleLLMService(LLMService): """Google AI (Gemini) LLM service implementation. @@ -773,14 +784,15 @@ class GoogleLLMService(LLMService): self._system_instruction = system_instruction self._http_options = update_google_client_http_options(http_options) - self._settings = { - "max_tokens": params.max_tokens, - "temperature": params.temperature, - "top_k": params.top_k, - "top_p": params.top_p, - "thinking": params.thinking, - "extra": params.extra if isinstance(params.extra, dict) else {}, - } + self._settings = GoogleLLMSettings( + model=model, + max_tokens=params.max_tokens, + temperature=params.temperature, + top_k=params.top_k, + top_p=params.top_p, + thinking=params.thinking, + extra=params.extra if isinstance(params.extra, dict) else {}, + ) self._tools = tools self._tool_config = tool_config @@ -874,10 +886,10 @@ class GoogleLLMService(LLMService): k: v for k, v in { "system_instruction": system_instruction, - "temperature": self._settings["temperature"], - "top_p": self._settings["top_p"], - "top_k": self._settings["top_k"], - "max_output_tokens": self._settings["max_tokens"], + "temperature": self._settings.temperature, + "top_p": self._settings.top_p, + "top_k": self._settings.top_k, + "max_output_tokens": self._settings.max_tokens, "tools": tools, "tool_config": tool_config, }.items() @@ -885,13 +897,13 @@ class GoogleLLMService(LLMService): } # Add thinking parameters if configured - if self._settings["thinking"]: - generation_params["thinking_config"] = self._settings["thinking"].model_dump( + if self._settings.thinking: + generation_params["thinking_config"] = self._settings.thinking.model_dump( exclude_unset=True ) - if self._settings["extra"]: - generation_params.update(self._settings["extra"]) + if self._settings.extra: + generation_params.update(self._settings.extra) return generation_params @@ -1190,8 +1202,6 @@ class GoogleLLMService(LLMService): # NOTE: LLMMessagesFrame is deprecated, so we don't support the newer universal # LLMContext with it context = GoogleLLMContext(frame.messages) - elif isinstance(frame, LLMUpdateSettingsFrame): - await self._update_settings(frame.settings) else: await self.push_frame(frame, direction) diff --git a/src/pipecat/services/google/stt.py b/src/pipecat/services/google/stt.py index 23396b0b8..8f762da9d 100644 --- a/src/pipecat/services/google/stt.py +++ b/src/pipecat/services/google/stt.py @@ -15,13 +15,15 @@ import asyncio import json import os import time +import warnings +from dataclasses import dataclass, field from pipecat.utils.tracing.service_decorators import traced_stt # Suppress gRPC fork warnings os.environ["GRPC_ENABLE_FORK_SUPPORT"] = "false" -from typing import AsyncGenerator, List, Optional, Union +from typing import Any, AsyncGenerator, List, Optional, Union from loguru import logger from pydantic import BaseModel, Field, field_validator @@ -34,6 +36,7 @@ from pipecat.frames.frames import ( StartFrame, TranscriptionFrame, ) +from pipecat.services.settings import NOT_GIVEN, STTSettings from pipecat.services.stt_latency import GOOGLE_TTFS_P99 from pipecat.services.stt_service import STTService from pipecat.transcriptions.language import Language, resolve_language @@ -355,6 +358,44 @@ def language_to_google_stt_language(language: Language) -> Optional[str]: return resolve_language(language, LANGUAGE_MAP, use_base_code=False) +@dataclass +class GoogleSTTSettings(STTSettings): + """Typed settings for Google Cloud Speech-to-Text V2. + + Parameters: + languages: List of ``Language`` enums for recognition + (e.g. ``[Language.EN_US]``). Preferred over ``language_codes``. + language_codes: List of Google STT language code strings + (e.g. ``["en-US"]``). + + .. deprecated:: 0.0.103 + Use ``languages`` instead. If both are provided, ``languages`` + takes precedence. This field is here just for backward + compatibility with dict-based settings updates. + use_separate_recognition_per_channel: Process each audio channel separately. + enable_automatic_punctuation: Add punctuation to transcripts. + enable_spoken_punctuation: Include spoken punctuation in transcript. + enable_spoken_emojis: Include spoken emojis in transcript. + profanity_filter: Filter profanity from transcript. + enable_word_time_offsets: Include timing information for each word. + enable_word_confidence: Include confidence scores for each word. + enable_interim_results: Stream partial recognition results. + enable_voice_activity_events: Detect voice activity in audio. + """ + + languages: Any = field(default_factory=lambda: NOT_GIVEN) + language_codes: Any = field(default_factory=lambda: NOT_GIVEN) + use_separate_recognition_per_channel: Any = field(default_factory=lambda: NOT_GIVEN) + enable_automatic_punctuation: Any = field(default_factory=lambda: NOT_GIVEN) + enable_spoken_punctuation: Any = field(default_factory=lambda: NOT_GIVEN) + enable_spoken_emojis: Any = field(default_factory=lambda: NOT_GIVEN) + profanity_filter: Any = field(default_factory=lambda: NOT_GIVEN) + enable_word_time_offsets: Any = field(default_factory=lambda: NOT_GIVEN) + enable_word_confidence: Any = field(default_factory=lambda: NOT_GIVEN) + enable_interim_results: Any = field(default_factory=lambda: NOT_GIVEN) + enable_voice_activity_events: Any = field(default_factory=lambda: NOT_GIVEN) + + class GoogleSTTService(STTService): """Google Cloud Speech-to-Text V2 service implementation. @@ -508,21 +549,19 @@ class GoogleSTTService(STTService): self._client = speech_v2.SpeechAsyncClient(credentials=creds, client_options=client_options) - self._settings = { - "language_codes": [ - self.language_to_service_language(lang) for lang in params.language_list - ], - "model": params.model, - "use_separate_recognition_per_channel": params.use_separate_recognition_per_channel, - "enable_automatic_punctuation": params.enable_automatic_punctuation, - "enable_spoken_punctuation": params.enable_spoken_punctuation, - "enable_spoken_emojis": params.enable_spoken_emojis, - "profanity_filter": params.profanity_filter, - "enable_word_time_offsets": params.enable_word_time_offsets, - "enable_word_confidence": params.enable_word_confidence, - "enable_interim_results": params.enable_interim_results, - "enable_voice_activity_events": params.enable_voice_activity_events, - } + self._settings = GoogleSTTSettings( + languages=list(params.language_list), + model=params.model, + use_separate_recognition_per_channel=params.use_separate_recognition_per_channel, + enable_automatic_punctuation=params.enable_automatic_punctuation, + enable_spoken_punctuation=params.enable_spoken_punctuation, + enable_spoken_emojis=params.enable_spoken_emojis, + profanity_filter=params.profanity_filter, + enable_word_time_offsets=params.enable_word_time_offsets, + enable_word_confidence=params.enable_word_confidence, + enable_interim_results=params.enable_interim_results, + enable_voice_activity_events=params.enable_voice_activity_events, + ) def can_generate_metrics(self) -> bool: """Check if the service can generate metrics. @@ -545,6 +584,23 @@ class GoogleSTTService(STTService): return [language_to_google_stt_language(lang) or "en-US" for lang in language] return language_to_google_stt_language(language) or "en-US" + def _get_language_codes(self) -> List[str]: + """Resolve the current language settings to Google STT language code strings. + + Prefers ``languages`` (``Language`` enums) over the deprecated + ``language_codes`` (raw strings). Falls back to ``["en-US"]``. + + Returns: + List[str]: Google STT language code strings. + """ + from pipecat.services.settings import is_given + + if is_given(self._settings.languages): + return [self.language_to_service_language(lang) for lang in self._settings.languages] + if is_given(self._settings.language_codes): + return list(self._settings.language_codes) + return ["en-US"] + async def _reconnect_if_needed(self): """Reconnect the stream if it's currently active.""" if self._streaming_task: @@ -552,41 +608,65 @@ class GoogleSTTService(STTService): await self._disconnect() await self._connect() - async def set_language(self, language: Language): - """Update the service's recognition language. - - A convenience method for setting a single language. - - Args: - language: New language for recognition. - """ - logger.debug(f"Switching STT language to: {language}") - await self.set_languages([language]) - async def set_languages(self, languages: List[Language]): """Update the service's recognition languages. + .. deprecated:: + Use ``STTUpdateSettingsFrame`` with ``GoogleSTTSettings(languages=...)`` + instead. + Args: languages: List of languages for recognition. First language is primary. """ + with warnings.catch_warnings(): + warnings.simplefilter("always") + warnings.warn( + "set_languages() is deprecated. Use STTUpdateSettingsFrame with " + "GoogleSTTSettings(languages=...) instead.", + DeprecationWarning, + ) logger.debug(f"Switching STT languages to: {languages}") - self._settings["language_codes"] = [ - self.language_to_service_language(lang) for lang in languages - ] - # Recreate stream with new languages - await self._reconnect_if_needed() + await self._update_settings_from_typed(GoogleSTTSettings(languages=list(languages))) - async def set_model(self, model: str): - """Update the service's recognition model. + async def _update_settings_from_typed(self, update: GoogleSTTSettings) -> set[str]: + """Apply typed settings update and reconnect if anything changed. + + Handles ``language`` from base ``set_language`` by converting it to + ``languages``. Emits a deprecation warning if ``language_codes`` is + used. All other fields (model, boolean flags) are applied directly. + Reconnects the stream on any change. Args: - model: The new recognition model to use. + update: A typed settings delta. + + Returns: + Set of field names whose values actually changed. """ - logger.debug(f"Switching STT model to: {model}") - await super().set_model(model) - self._settings["model"] = model - # Recreate stream with new model - await self._reconnect_if_needed() + from pipecat.services.settings import is_given + + # If base set_language sent a Language value, convert to languages list + if is_given(update.language): + update.languages = [update.language] + # Clear language so the base class doesn't try to store it + update.language = NOT_GIVEN + + # Warn on deprecated language_codes usage + if is_given(update.language_codes): + with warnings.catch_warnings(): + warnings.simplefilter("always") + warnings.warn( + "GoogleSTTSettings.language_codes is deprecated. " + "Use GoogleSTTSettings.languages (List[Language]) instead.", + DeprecationWarning, + stacklevel=2, + ) + + changed = await super()._update_settings_from_typed(update) + + if changed: + await self._reconnect_if_needed() + + return changed async def start(self, frame: StartFrame): """Start the STT service and establish connection. @@ -632,6 +712,10 @@ class GoogleSTTService(STTService): ) -> None: """Update service options dynamically. + .. deprecated:: + Use ``STTUpdateSettingsFrame`` with ``GoogleSTTSettings(...)`` + instead. + Args: languages: New list of recognition languages. model: New recognition model. @@ -649,55 +733,42 @@ class GoogleSTTService(STTService): Changes that affect the streaming configuration will cause the stream to be reconnected. """ - # Update settings with new values + with warnings.catch_warnings(): + warnings.simplefilter("always") + warnings.warn( + "update_options() is deprecated. Use STTUpdateSettingsFrame with " + "GoogleSTTSettings(...) instead.", + DeprecationWarning, + ) + # Build a typed settings delta from the provided options + update = GoogleSTTSettings() + if languages is not None: - logger.debug(f"Updating language to: {languages}") - self._settings["language_codes"] = [ - self.language_to_service_language(lang) for lang in languages - ] - + update.languages = list(languages) if model is not None: - logger.debug(f"Updating model to: {model}") - self._settings["model"] = model - + update.model = model if enable_automatic_punctuation is not None: - logger.debug(f"Updating automatic punctuation to: {enable_automatic_punctuation}") - self._settings["enable_automatic_punctuation"] = enable_automatic_punctuation - + update.enable_automatic_punctuation = enable_automatic_punctuation if enable_spoken_punctuation is not None: - logger.debug(f"Updating spoken punctuation to: {enable_spoken_punctuation}") - self._settings["enable_spoken_punctuation"] = enable_spoken_punctuation - + update.enable_spoken_punctuation = enable_spoken_punctuation if enable_spoken_emojis is not None: - logger.debug(f"Updating spoken emojis to: {enable_spoken_emojis}") - self._settings["enable_spoken_emojis"] = enable_spoken_emojis - + update.enable_spoken_emojis = enable_spoken_emojis if profanity_filter is not None: - logger.debug(f"Updating profanity filter to: {profanity_filter}") - self._settings["profanity_filter"] = profanity_filter - + update.profanity_filter = profanity_filter if enable_word_time_offsets is not None: - logger.debug(f"Updating word time offsets to: {enable_word_time_offsets}") - self._settings["enable_word_time_offsets"] = enable_word_time_offsets - + update.enable_word_time_offsets = enable_word_time_offsets if enable_word_confidence is not None: - logger.debug(f"Updating word confidence to: {enable_word_confidence}") - self._settings["enable_word_confidence"] = enable_word_confidence - + update.enable_word_confidence = enable_word_confidence if enable_interim_results is not None: - logger.debug(f"Updating interim results to: {enable_interim_results}") - self._settings["enable_interim_results"] = enable_interim_results - + update.enable_interim_results = enable_interim_results if enable_voice_activity_events is not None: - logger.debug(f"Updating voice activity events to: {enable_voice_activity_events}") - self._settings["enable_voice_activity_events"] = enable_voice_activity_events + update.enable_voice_activity_events = enable_voice_activity_events if location is not None: logger.debug(f"Updating location to: {location}") self._location = location - # Reconnect the stream for updates - await self._reconnect_if_needed() + await self._update_settings_from_typed(update) async def _connect(self): """Initialize streaming recognition config and stream.""" @@ -714,20 +785,20 @@ class GoogleSTTService(STTService): sample_rate_hertz=self.sample_rate, audio_channel_count=1, ), - language_codes=self._settings["language_codes"], - model=self._settings["model"], + language_codes=self._get_language_codes(), + model=self._settings.model, features=cloud_speech.RecognitionFeatures( - enable_automatic_punctuation=self._settings["enable_automatic_punctuation"], - enable_spoken_punctuation=self._settings["enable_spoken_punctuation"], - enable_spoken_emojis=self._settings["enable_spoken_emojis"], - profanity_filter=self._settings["profanity_filter"], - enable_word_time_offsets=self._settings["enable_word_time_offsets"], - enable_word_confidence=self._settings["enable_word_confidence"], + enable_automatic_punctuation=self._settings.enable_automatic_punctuation, + enable_spoken_punctuation=self._settings.enable_spoken_punctuation, + enable_spoken_emojis=self._settings.enable_spoken_emojis, + profanity_filter=self._settings.profanity_filter, + enable_word_time_offsets=self._settings.enable_word_time_offsets, + enable_word_confidence=self._settings.enable_word_confidence, ), ), streaming_features=cloud_speech.StreamingRecognitionFeatures( - enable_voice_activity_events=self._settings["enable_voice_activity_events"], - interim_results=self._settings["enable_interim_results"], + enable_voice_activity_events=self._settings.enable_voice_activity_events, + interim_results=self._settings.enable_interim_results, ), ) @@ -857,7 +928,7 @@ class GoogleSTTService(STTService): if not transcript: continue - primary_language = self._settings["language_codes"][0] + primary_language = self._get_language_codes()[0] if result.is_final: self._last_transcript_was_final = True diff --git a/src/pipecat/services/google/tts.py b/src/pipecat/services/google/tts.py index 4016286df..d015571d0 100644 --- a/src/pipecat/services/google/tts.py +++ b/src/pipecat/services/google/tts.py @@ -23,7 +23,8 @@ from pipecat.utils.tracing.service_decorators import traced_tts # Suppress gRPC fork warnings os.environ["GRPC_ENABLE_FORK_SUPPORT"] = "false" -from typing import Any, AsyncGenerator, List, Literal, Mapping, Optional +from dataclasses import dataclass, field +from typing import AsyncGenerator, List, Literal, Optional from loguru import logger from pydantic import BaseModel @@ -36,6 +37,7 @@ from pipecat.frames.frames import ( TTSStartedFrame, TTSStoppedFrame, ) +from pipecat.services.settings import NOT_GIVEN, TTSSettings, is_given from pipecat.services.tts_service import TTSService from pipecat.transcriptions.language import Language, resolve_language @@ -474,6 +476,63 @@ def language_to_gemini_tts_language(language: Language) -> Optional[str]: return resolve_language(language, LANGUAGE_MAP, use_base_code=False) +@dataclass +class GoogleHttpTTSSettings(TTSSettings): + """Typed settings for Google HTTP TTS service. + + Parameters: + pitch: Voice pitch adjustment (e.g., "+2st", "-50%"). + rate: Speaking rate adjustment (e.g., "slow", "fast", "125%"). Used for + SSML prosody tags (non-Chirp voices). + speaking_rate: Speaking rate for AudioConfig (Chirp/Journey voices). + Range [0.25, 2.0]. + volume: Volume adjustment (e.g., "loud", "soft", "+6dB"). + emphasis: Emphasis level for the text. + language: Language for synthesis. Defaults to English. + gender: Voice gender preference. + google_style: Google-specific voice style. + """ + + pitch: str = field(default_factory=lambda: NOT_GIVEN) + rate: str = field(default_factory=lambda: NOT_GIVEN) + speaking_rate: float = field(default_factory=lambda: NOT_GIVEN) + volume: str = field(default_factory=lambda: NOT_GIVEN) + emphasis: str = field(default_factory=lambda: NOT_GIVEN) + language: str = field(default_factory=lambda: NOT_GIVEN) + gender: str = field(default_factory=lambda: NOT_GIVEN) + google_style: str = field(default_factory=lambda: NOT_GIVEN) + + +@dataclass +class GoogleStreamTTSSettings(TTSSettings): + """Typed settings for Google streaming TTS service. + + Parameters: + language: Language for synthesis. Defaults to English. + speaking_rate: The speaking rate, in the range [0.25, 2.0]. + """ + + language: str = field(default_factory=lambda: NOT_GIVEN) + speaking_rate: float = field(default_factory=lambda: NOT_GIVEN) + + +@dataclass +class GeminiTTSSettings(TTSSettings): + """Typed settings for Gemini TTS service. + + Parameters: + language: Language for synthesis. Defaults to English. + prompt: Optional style instructions for how to synthesize the content. + multi_speaker: Whether to enable multi-speaker support. + speaker_configs: List of speaker configurations for multi-speaker mode. + """ + + language: str = field(default_factory=lambda: NOT_GIVEN) + prompt: str = field(default_factory=lambda: NOT_GIVEN) + multi_speaker: bool = field(default_factory=lambda: NOT_GIVEN) + speaker_configs: List[dict] = field(default_factory=lambda: NOT_GIVEN) + + class GoogleHttpTTSService(TTSService): """Google Cloud Text-to-Speech HTTP service with SSML support. @@ -538,19 +597,19 @@ class GoogleHttpTTSService(TTSService): params = params or GoogleHttpTTSService.InputParams() self._location = location - self._settings = { - "pitch": params.pitch, - "rate": params.rate, - "speaking_rate": params.speaking_rate, - "volume": params.volume, - "emphasis": params.emphasis, - "language": self.language_to_service_language(params.language) + self._settings: GoogleHttpTTSSettings = GoogleHttpTTSSettings( + pitch=params.pitch, + rate=params.rate, + speaking_rate=params.speaking_rate, + volume=params.volume, + emphasis=params.emphasis, + language=self.language_to_service_language(params.language) if params.language else "en-US", - "gender": params.gender, - "google_style": params.google_style, - } - self.set_voice(voice_id) + gender=params.gender, + google_style=params.google_style, + ) + self._voice_id = voice_id self._client: texttospeech_v1.TextToSpeechAsyncClient = self._create_client( credentials, credentials_path ) @@ -619,21 +678,20 @@ class GoogleHttpTTSService(TTSService): """ return language_to_google_tts_language(language) - async def _update_settings(self, settings: Mapping[str, Any]): - """Override to handle speaking_rate updates for Chirp/Journey voices. + async def _update_settings_from_typed(self, update: TTSSettings) -> set[str]: + """Override to handle speaking_rate validation. Args: - settings: Dictionary of settings to update. Can include 'speaking_rate' (float) + update: Typed settings delta. Can include 'speaking_rate' (float). """ - if "speaking_rate" in settings: - rate_value = float(settings["speaking_rate"]) - if 0.25 <= rate_value <= 2.0: - self._settings["speaking_rate"] = rate_value - else: + if isinstance(update, GoogleHttpTTSSettings) and is_given(update.speaking_rate): + rate_value = float(update.speaking_rate) + if not (0.25 <= rate_value <= 2.0): logger.warning( f"Invalid speaking_rate value: {rate_value}. Must be between 0.25 and 2.0" ) - await super()._update_settings(settings) + update.speaking_rate = NOT_GIVEN + return await super()._update_settings_from_typed(update) def _construct_ssml(self, text: str) -> str: ssml = "" @@ -641,39 +699,39 @@ class GoogleHttpTTSService(TTSService): # Voice tag voice_attrs = [f"name='{self._voice_id}'"] - language = self._settings["language"] + language = self._settings.language voice_attrs.append(f"language='{language}'") - if self._settings["gender"]: - voice_attrs.append(f"gender='{self._settings['gender']}'") + if self._settings.gender: + voice_attrs.append(f"gender='{self._settings.gender}'") ssml += f"" # Prosody tag prosody_attrs = [] - if self._settings["pitch"]: - prosody_attrs.append(f"pitch='{self._settings['pitch']}'") - if self._settings["rate"]: - prosody_attrs.append(f"rate='{self._settings['rate']}'") - if self._settings["volume"]: - prosody_attrs.append(f"volume='{self._settings['volume']}'") + if self._settings.pitch: + prosody_attrs.append(f"pitch='{self._settings.pitch}'") + if self._settings.rate: + prosody_attrs.append(f"rate='{self._settings.rate}'") + if self._settings.volume: + prosody_attrs.append(f"volume='{self._settings.volume}'") if prosody_attrs: ssml += f"" # Emphasis tag - if self._settings["emphasis"]: - ssml += f"" + if self._settings.emphasis: + ssml += f"" # Google style tag - if self._settings["google_style"]: - ssml += f"" + if self._settings.google_style: + ssml += f"" ssml += text # Close tags - if self._settings["google_style"]: + if self._settings.google_style: ssml += "" - if self._settings["emphasis"]: + if self._settings.emphasis: ssml += "" if prosody_attrs: ssml += "" @@ -710,7 +768,7 @@ class GoogleHttpTTSService(TTSService): synthesis_input = texttospeech_v1.SynthesisInput(ssml=ssml) voice = texttospeech_v1.VoiceSelectionParams( - language_code=self._settings["language"], name=self._voice_id + language_code=self._settings.language, name=self._voice_id ) # Build audio config with conditional speaking_rate audio_config_params = { @@ -719,8 +777,8 @@ class GoogleHttpTTSService(TTSService): } # For Chirp and Journey voices, include speaking_rate in AudioConfig - if (is_chirp_voice or is_journey_voice) and self._settings["speaking_rate"] is not None: - audio_config_params["speaking_rate"] = self._settings["speaking_rate"] + if (is_chirp_voice or is_journey_voice) and self._settings.speaking_rate is not None: + audio_config_params["speaking_rate"] = self._settings.speaking_rate audio_config = texttospeech_v1.AudioConfig(**audio_config_params) @@ -950,33 +1008,32 @@ class GoogleTTSService(GoogleBaseTTSService): params = params or GoogleTTSService.InputParams() self._location = location - self._settings = { - "language": self.language_to_service_language(params.language) + self._settings: GoogleStreamTTSSettings = GoogleStreamTTSSettings( + language=self.language_to_service_language(params.language) if params.language else "en-US", - "speaking_rate": params.speaking_rate, - } - self.set_voice(voice_id) + speaking_rate=params.speaking_rate, + ) + self._voice_id = voice_id self._voice_cloning_key = voice_cloning_key self._client: texttospeech_v1.TextToSpeechAsyncClient = self._create_client( credentials, credentials_path ) - async def _update_settings(self, settings: Mapping[str, Any]): - """Override to handle speaking_rate updates for streaming API. + async def _update_settings_from_typed(self, update: TTSSettings) -> set[str]: + """Override to handle speaking_rate validation. Args: - settings: Dictionary of settings to update. Can include 'speaking_rate' (float) + update: Typed settings delta. Can include 'speaking_rate' (float). """ - if "speaking_rate" in settings: - rate_value = float(settings["speaking_rate"]) - if 0.25 <= rate_value <= 2.0: - self._settings["speaking_rate"] = rate_value - else: + if isinstance(update, GoogleStreamTTSSettings) and is_given(update.speaking_rate): + rate_value = float(update.speaking_rate) + if not (0.25 <= rate_value <= 2.0): logger.warning( f"Invalid speaking_rate value: {rate_value}. Must be between 0.25 and 2.0" ) - await super()._update_settings(settings) + update.speaking_rate = NOT_GIVEN + return await super()._update_settings_from_typed(update) @traced_tts async def run_tts(self, text: str, context_id: str) -> AsyncGenerator[Frame, None]: @@ -1000,11 +1057,11 @@ class GoogleTTSService(GoogleBaseTTSService): voice_cloning_key=self._voice_cloning_key ) voice = texttospeech_v1.VoiceSelectionParams( - language_code=self._settings["language"], voice_clone=voice_clone_params + language_code=self._settings.language, voice_clone=voice_clone_params ) else: voice = texttospeech_v1.VoiceSelectionParams( - language_code=self._settings["language"], name=self._voice_id + language_code=self._settings.language, name=self._voice_id ) # Create streaming config @@ -1013,7 +1070,7 @@ class GoogleTTSService(GoogleBaseTTSService): streaming_audio_config=texttospeech_v1.StreamingAudioConfig( audio_encoding=texttospeech_v1.AudioEncoding.PCM, sample_rate_hertz=self.sample_rate, - speaking_rate=self._settings["speaking_rate"], + speaking_rate=self._settings.speaking_rate, ), ) @@ -1159,14 +1216,14 @@ class GeminiTTSService(GoogleBaseTTSService): self._location = location self._model = model self._voice_id = voice_id - self._settings = { - "language": self.language_to_service_language(params.language) + self._settings: GeminiTTSSettings = GeminiTTSSettings( + language=self.language_to_service_language(params.language) if params.language else "en-US", - "prompt": params.prompt, - "multi_speaker": params.multi_speaker, - "speaker_configs": params.speaker_configs, - } + prompt=params.prompt, + multi_speaker=params.multi_speaker, + speaker_configs=params.speaker_configs, + ) self._client: texttospeech_v1.TextToSpeechAsyncClient = self._create_client( credentials, credentials_path @@ -1183,7 +1240,7 @@ class GeminiTTSService(GoogleBaseTTSService): """ return language_to_gemini_tts_language(language) - def set_voice(self, voice_id: str): + async def set_voice(self, voice_id: str): """Set the voice for TTS generation. Args: @@ -1206,15 +1263,13 @@ class GeminiTTSService(GoogleBaseTTSService): f"Current rate of {self.sample_rate}Hz may cause issues." ) - async def _update_settings(self, settings: Mapping[str, Any]): + async def _update_settings_from_typed(self, update: TTSSettings) -> set[str]: """Override to handle prompt updates. Args: - settings: Dictionary of settings to update. Can include 'prompt' (str) + update: Typed settings delta. Can include 'prompt' (str). """ - if "prompt" in settings: - self._settings["prompt"] = settings["prompt"] - await super()._update_settings(settings) + return await super()._update_settings_from_typed(update) @traced_tts async def run_tts(self, text: str, context_id: str) -> AsyncGenerator[Frame, None]: @@ -1234,10 +1289,10 @@ class GeminiTTSService(GoogleBaseTTSService): await self.start_ttfb_metrics() # Build voice selection params - if self._settings["multi_speaker"] and self._settings["speaker_configs"]: + if self._settings.multi_speaker and self._settings.speaker_configs: # Multi-speaker mode speaker_voice_configs = [] - for speaker_config in self._settings["speaker_configs"]: + for speaker_config in self._settings.speaker_configs: speaker_voice_configs.append( texttospeech_v1.MultispeakerPrebuiltVoice( speaker_alias=speaker_config["speaker_alias"], @@ -1250,14 +1305,14 @@ class GeminiTTSService(GoogleBaseTTSService): ) voice = texttospeech_v1.VoiceSelectionParams( - language_code=self._settings["language"], + language_code=self._settings.language, model_name=self._model, multi_speaker_voice_config=multi_speaker_voice_config, ) else: # Single speaker mode voice = texttospeech_v1.VoiceSelectionParams( - language_code=self._settings["language"], + language_code=self._settings.language, name=self._voice_id, model_name=self._model, ) @@ -1273,7 +1328,7 @@ class GeminiTTSService(GoogleBaseTTSService): # Use base class streaming logic with prompt support async for frame in self._stream_tts( - streaming_config, text, context_id, self._settings["prompt"] + streaming_config, text, context_id, self._settings.prompt ): yield frame diff --git a/src/pipecat/services/gradium/stt.py b/src/pipecat/services/gradium/stt.py index 7433c2549..2bad8cf30 100644 --- a/src/pipecat/services/gradium/stt.py +++ b/src/pipecat/services/gradium/stt.py @@ -12,6 +12,7 @@ WebSocket API for streaming audio transcription. import base64 import json +from dataclasses import dataclass, field from typing import AsyncGenerator, Optional from loguru import logger @@ -27,6 +28,7 @@ from pipecat.frames.frames import ( VADUserStoppedSpeakingFrame, ) from pipecat.processors.frame_processor import FrameDirection +from pipecat.services.settings import NOT_GIVEN, STTSettings, is_given from pipecat.services.stt_latency import GRADIUM_TTFS_P99 from pipecat.services.stt_service import WebsocketSTTService from pipecat.transcriptions.language import Language, resolve_language @@ -64,6 +66,18 @@ def language_to_gradium_language(language: Language) -> Optional[str]: return resolve_language(language, LANGUAGE_MAP, use_base_code=True) +@dataclass +class GradiumSTTSettings(STTSettings): + """Typed settings for the Gradium STT service. + + Parameters: + delay_in_frames: Delay in audio frames (80ms each) before text is + generated. Higher delays allow more context but increase latency. + """ + + delay_in_frames: int = field(default_factory=lambda: NOT_GIVEN) + + class GradiumSTTService(WebsocketSTTService): """Gradium real-time speech-to-text service. @@ -127,9 +141,15 @@ class GradiumSTTService(WebsocketSTTService): self._api_key = api_key self._api_endpoint_base_url = api_endpoint_base_url self._websocket = None - self._params = params or GradiumSTTService.InputParams() self._json_config = json_config + params = params or GradiumSTTService.InputParams() + + self._settings: GradiumSTTSettings = GradiumSTTSettings( + language=params.language, + delay_in_frames=params.delay_in_frames if params.delay_in_frames else NOT_GIVEN, + ) + self._receive_task = None self._audio_buffer = bytearray() @@ -149,16 +169,22 @@ class GradiumSTTService(WebsocketSTTService): """ return True - async def set_language(self, language: Language): - """Set the recognition language and reconnect. + async def _update_settings_from_typed(self, update: STTSettings) -> set[str]: + """Apply a typed settings update, sync params, and reconnect. Args: - language: The language to use for speech recognition. + update: A :class:`STTSettings` (or ``GradiumSTTSettings``) delta. + + Returns: + Set of field names whose values actually changed. """ - logger.info(f"Switching STT language to: [{language}]") - self._params.language = language + changed = await super()._update_settings_from_typed(update) + if not changed: + return changed + await self._disconnect() await self._connect() + return changed async def start(self, frame: StartFrame): """Start the speech-to-text service. @@ -298,12 +324,12 @@ class GradiumSTTService(WebsocketSTTService): json_config = {} if self._json_config: json_config = json.loads(self._json_config) - if self._params.language: - gradium_language = language_to_gradium_language(self._params.language) + if is_given(self._settings.language) and self._settings.language: + gradium_language = language_to_gradium_language(self._settings.language) if gradium_language: json_config["language"] = gradium_language - if self._params.delay_in_frames: - json_config["delay_in_frames"] = self._params.delay_in_frames + if is_given(self._settings.delay_in_frames) and self._settings.delay_in_frames: + json_config["delay_in_frames"] = self._settings.delay_in_frames if json_config: setup_msg["json_config"] = json_config await self._websocket.send(json.dumps(setup_msg)) diff --git a/src/pipecat/services/gradium/tts.py b/src/pipecat/services/gradium/tts.py index 0e9865cf0..e129fba68 100644 --- a/src/pipecat/services/gradium/tts.py +++ b/src/pipecat/services/gradium/tts.py @@ -6,7 +6,8 @@ import base64 import json -from typing import Any, AsyncGenerator, Mapping, Optional +from dataclasses import dataclass, field +from typing import AsyncGenerator, Optional from loguru import logger from pydantic import BaseModel @@ -22,6 +23,7 @@ from pipecat.frames.frames import ( TTSStoppedFrame, ) from pipecat.processors.frame_processor import FrameDirection +from pipecat.services.settings import NOT_GIVEN, TTSSettings from pipecat.services.tts_service import InterruptibleWordTTSService from pipecat.utils.tracing.service_decorators import traced_tts @@ -37,6 +39,17 @@ except ModuleNotFoundError as e: SAMPLE_RATE = 48000 +@dataclass +class GradiumTTSSettings(TTSSettings): + """Typed settings for the Gradium TTS service. + + Parameters: + output_format: Audio output format. + """ + + output_format: str = field(default_factory=lambda: NOT_GIVEN) + + class GradiumTTSService(InterruptibleWordTTSService): """Text-to-Speech service using Gradium's websocket API.""" @@ -86,12 +99,11 @@ class GradiumTTSService(InterruptibleWordTTSService): self._url = url self._voice_id = voice_id self._json_config = json_config - self._model = model - self._settings = { - "voice_id": voice_id, - "model_name": model, - "output_format": "pcm", - } + self._settings: GradiumTTSSettings = GradiumTTSSettings( + model=model, + voice=voice_id, + output_format="pcm", + ) # State tracking self._receive_task = None @@ -105,24 +117,21 @@ class GradiumTTSService(InterruptibleWordTTSService): """ return True - async def set_model(self, model: str): - """Update the TTS model. + async def _update_settings_from_typed(self, update: TTSSettings) -> set[str]: + """Apply a typed settings update and reconnect if voice changed. Args: - model: The model name to use for synthesis. - """ - self._model = model - await super().set_model(model) + update: A :class:`TTSSettings` (or ``GradiumTTSSettings``) delta. - async def _update_settings(self, settings: Mapping[str, Any]): - """Update service settings and reconnect if voice changed.""" + Returns: + Set of field names whose values actually changed. + """ prev_voice = self._voice_id - await super()._update_settings(settings) - if not prev_voice == self._voice_id: - self._settings["voice_id"] = self._voice_id - logger.info(f"Switching TTS voice to: [{self._voice_id}]") + changed = await super()._update_settings_from_typed(update) + if self._voice_id != prev_voice: await self._disconnect() await self._connect() + return changed def _build_msg(self, text: str = "") -> dict: """Build JSON message for Gradium API.""" diff --git a/src/pipecat/services/grok/realtime/llm.py b/src/pipecat/services/grok/realtime/llm.py index e1355ce31..7cb619a7d 100644 --- a/src/pipecat/services/grok/realtime/llm.py +++ b/src/pipecat/services/grok/realtime/llm.py @@ -13,8 +13,8 @@ https://docs.x.ai/docs/guides/voice/agent import base64 import json import time -from dataclasses import dataclass -from typing import Optional +from dataclasses import dataclass, field +from typing import Any, Optional from loguru import logger @@ -56,6 +56,7 @@ from pipecat.processors.aggregators.llm_response_universal import ( from pipecat.processors.aggregators.openai_llm_context import OpenAILLMContext from pipecat.processors.frame_processor import FrameDirection from pipecat.services.llm_service import FunctionCallFromLLM, LLMService +from pipecat.services.settings import NOT_GIVEN, LLMSettings from pipecat.utils.time import time_now_iso8601 from . import events @@ -85,6 +86,17 @@ class CurrentAudioResponse: total_size: int = 0 +@dataclass +class GrokRealtimeLLMSettings(LLMSettings): + """Typed settings for Grok Realtime LLM services. + + Parameters: + session_properties: Grok Realtime session configuration. + """ + + session_properties: Any = field(default_factory=lambda: NOT_GIVEN) + + class GrokRealtimeLLMService(LLMService): """Grok Realtime Voice Agent LLM service providing real-time audio and text communication. @@ -134,9 +146,8 @@ class GrokRealtimeLLMService(LLMService): self.api_key = api_key self.base_url = base_url - # Initialize session_properties - self._session_properties: events.SessionProperties = ( - session_properties or events.SessionProperties() + self._settings = GrokRealtimeLLMSettings( + session_properties=session_properties or events.SessionProperties(), ) self._audio_input_paused = start_audio_paused @@ -186,13 +197,13 @@ class GrokRealtimeLLMService(LLMService): Configured sample rate or None if not manually configured. For PCMU/PCMA formats, returns 8000 Hz (G.711 standard). """ - if not self._session_properties.audio: + if not self._settings.session_properties.audio: return None audio_config = ( - self._session_properties.audio.input + self._settings.session_properties.audio.input if direction == "input" - else self._session_properties.audio.output + else self._settings.session_properties.audio.output ) if audio_config and audio_config.format: @@ -222,8 +233,8 @@ class GrokRealtimeLLMService(LLMService): def _is_turn_detection_enabled(self) -> bool: """Check if server-side VAD is enabled.""" - if self._session_properties.turn_detection: - return self._session_properties.turn_detection.type == "server_vad" + if self._settings.session_properties.turn_detection: + return self._settings.session_properties.turn_detection.type == "server_vad" return False async def _handle_interruption(self): @@ -290,18 +301,18 @@ class GrokRealtimeLLMService(LLMService): await super().start(frame) # Ensure audio configuration exists with both input and output - if not self._session_properties.audio: - self._session_properties.audio = events.AudioConfiguration() + if not self._settings.session_properties.audio: + self._settings.session_properties.audio = events.AudioConfiguration() # Fill in missing input configuration - if not self._session_properties.audio.input: - self._session_properties.audio.input = events.AudioInput( + if not self._settings.session_properties.audio.input: + self._settings.session_properties.audio.input = events.AudioInput( format=events.PCMAudioFormat(rate=frame.audio_in_sample_rate) ) # Fill in missing output configuration - if not self._session_properties.audio.output: - self._session_properties.audio.output = events.AudioOutput( + if not self._settings.session_properties.audio.output: + self._settings.session_properties.audio.output = events.AudioOutput( format=events.PCMAudioFormat(rate=frame.audio_out_sample_rate) ) @@ -336,6 +347,16 @@ class GrokRealtimeLLMService(LLMService): frame: The frame to process. direction: The direction of frame flow in the pipeline. """ + # Legacy dict path: frame.settings contains SessionProperties fields, + # not our Settings fields, so we construct SessionProperties directly. + # The new typed path (frame.update) falls through to super, which calls + # _update_settings_from_typed → our override handles the rest. + if isinstance(frame, LLMUpdateSettingsFrame) and frame.update is None: + self._settings.session_properties = events.SessionProperties(**frame.settings) + await self._update_settings() + await self.push_frame(frame, direction) + return + await super().process_frame(frame, direction) if isinstance(frame, TranscriptionFrame): @@ -355,9 +376,6 @@ class GrokRealtimeLLMService(LLMService): await self._handle_bot_stopped_speaking() elif isinstance(frame, LLMMessagesAppendFrame): await self._handle_messages_append(frame) - elif isinstance(frame, LLMUpdateSettingsFrame): - self._session_properties = events.SessionProperties(**frame.settings) - await self._update_settings() elif isinstance(frame, LLMSetToolsFrame): await self._update_settings() @@ -436,9 +454,16 @@ class GrokRealtimeLLMService(LLMService): return await self.push_error(error_msg=f"Error sending client event: {e}", exception=e) + async def _update_settings_from_typed(self, update): + """Apply a typed settings update, sending a session update if needed.""" + changed = await super()._update_settings_from_typed(update) + if "session_properties" in changed: + await self._update_settings() + return changed + async def _update_settings(self): """Update session settings on the server.""" - settings = self._session_properties + settings = self._settings.session_properties adapter: GrokRealtimeLLMAdapter = self.get_llm_adapter() if self._context: diff --git a/src/pipecat/services/groq/tts.py b/src/pipecat/services/groq/tts.py index 331af8eb7..678a2426d 100644 --- a/src/pipecat/services/groq/tts.py +++ b/src/pipecat/services/groq/tts.py @@ -8,6 +8,7 @@ import io import wave +from dataclasses import dataclass, field from typing import AsyncGenerator, Optional from loguru import logger @@ -20,6 +21,7 @@ from pipecat.frames.frames import ( TTSStartedFrame, TTSStoppedFrame, ) +from pipecat.services.settings import NOT_GIVEN, TTSSettings from pipecat.services.tts_service import TTSService from pipecat.transcriptions.language import Language from pipecat.utils.tracing.service_decorators import traced_tts @@ -32,6 +34,21 @@ except ModuleNotFoundError as e: raise Exception(f"Missing module: {e}") +@dataclass +class GroqTTSSettings(TTSSettings): + """Typed settings for the Groq TTS service. + + Parameters: + output_format: Audio output format. + speed: Speech speed multiplier. Defaults to 1.0. + groq_sample_rate: Audio sample rate. + """ + + output_format: str = field(default_factory=lambda: NOT_GIVEN) + speed: float = field(default_factory=lambda: NOT_GIVEN) + groq_sample_rate: int = field(default_factory=lambda: NOT_GIVEN) + + class GroqTTSService(TTSService): """Groq text-to-speech service implementation. @@ -92,14 +109,14 @@ class GroqTTSService(TTSService): self._voice_id = voice_id self._params = params - self._settings = { - "model": model_name, - "voice_id": voice_id, - "output_format": output_format, - "language": str(params.language) if params.language else "en", - "speed": params.speed, - "sample_rate": sample_rate, - } + self._settings: GroqTTSSettings = GroqTTSSettings( + model=model_name, + voice=voice_id, + language=str(params.language) if params.language else "en", + output_format=output_format, + speed=params.speed, + groq_sample_rate=sample_rate, + ) self._client = AsyncGroq(api_key=self._api_key) diff --git a/src/pipecat/services/hathora/stt.py b/src/pipecat/services/hathora/stt.py index defdc355d..b0e3beead 100644 --- a/src/pipecat/services/hathora/stt.py +++ b/src/pipecat/services/hathora/stt.py @@ -8,6 +8,7 @@ import base64 import os +from dataclasses import dataclass, field from typing import AsyncGenerator, Optional import aiohttp @@ -18,6 +19,7 @@ from pipecat.frames.frames import ( Frame, TranscriptionFrame, ) +from pipecat.services.settings import NOT_GIVEN, STTSettings from pipecat.services.stt_latency import HATHORA_TTFS_P99 from pipecat.services.stt_service import SegmentedSTTService from pipecat.transcriptions.language import Language @@ -27,6 +29,19 @@ from pipecat.utils.tracing.service_decorators import traced_stt from .utils import ConfigOption +@dataclass +class HathoraSTTSettings(STTSettings): + """Typed settings for the Hathora STT service. + + Parameters: + config: Some models support additional config, refer to + `docs `_ for each model to see + what is supported. + """ + + config: Optional[list] = field(default_factory=lambda: NOT_GIVEN) + + class HathoraSTTService(SegmentedSTTService): """This service supports several different speech-to-text models hosted by Hathora. @@ -83,10 +98,11 @@ class HathoraSTTService(SegmentedSTTService): params = params or HathoraSTTService.InputParams() - self._settings = { - "language": params.language, - "config": params.config, - } + self._settings: HathoraSTTSettings = HathoraSTTSettings( + model=model, + language=params.language, + config=params.config, + ) self.set_model_name(model) @@ -123,12 +139,11 @@ class HathoraSTTService(SegmentedSTTService): "model": self._model, } - if self._settings["language"] is not None: - payload["language"] = self._settings["language"] - if self._settings["config"] is not None: + if self._settings.language is not None: + payload["language"] = self._settings.language + if self._settings.config is not None: payload["model_config"] = [ - {"name": option.name, "value": option.value} - for option in self._settings["config"] + {"name": option.name, "value": option.value} for option in self._settings.config ] base64_audio = base64.b64encode(audio).decode("utf-8") @@ -147,7 +162,7 @@ class HathoraSTTService(SegmentedSTTService): if text: # Only yield non-empty text # Hathora's API currently doesn't return language info # so we default to the requested language or "en" - response_language = self._settings["language"] or "en" + response_language = self._settings.language or "en" await self._handle_transcription(text, True, response_language) yield TranscriptionFrame( text, diff --git a/src/pipecat/services/hathora/tts.py b/src/pipecat/services/hathora/tts.py index 80cbd4fe8..b821b1e05 100644 --- a/src/pipecat/services/hathora/tts.py +++ b/src/pipecat/services/hathora/tts.py @@ -9,6 +9,7 @@ import io import os import wave +from dataclasses import dataclass, field from typing import AsyncGenerator, Optional, Tuple import aiohttp @@ -21,6 +22,7 @@ from pipecat.frames.frames import ( TTSStartedFrame, TTSStoppedFrame, ) +from pipecat.services.settings import NOT_GIVEN, TTSSettings from pipecat.services.tts_service import TTSService from pipecat.utils.tracing.service_decorators import traced_tts @@ -45,6 +47,21 @@ def _decode_audio_payload( return audio_bytes, fallback_sample_rate, fallback_channels +@dataclass +class HathoraTTSSettings(TTSSettings): + """Typed settings for Hathora TTS service. + + Parameters: + speed: Speech speed multiplier (if supported by model). + config: Some models support additional config, refer to + [docs](https://models.hathora.dev) for each model to see + what is supported. + """ + + speed: float = field(default_factory=lambda: NOT_GIVEN) + config: list = field(default_factory=lambda: NOT_GIVEN) + + class HathoraTTSService(TTSService): """This service supports several different text-to-speech models hosted by Hathora. @@ -98,13 +115,15 @@ class HathoraTTSService(TTSService): params = params or HathoraTTSService.InputParams() - self._settings = { - "speed": params.speed, - "config": params.config, - } + self._settings: HathoraTTSSettings = HathoraTTSSettings( + model=model, + voice=voice_id, + speed=params.speed, + config=params.config, + ) self.set_model_name(model) - self.set_voice(voice_id) + self._voice_id = voice_id def can_generate_metrics(self) -> bool: """Check if this service can generate processing metrics. @@ -135,12 +154,11 @@ class HathoraTTSService(TTSService): if self._voice_id is not None: payload["voice"] = self._voice_id - if self._settings["speed"] is not None: - payload["speed"] = self._settings["speed"] - if self._settings["config"] is not None: + if self._settings.speed is not None: + payload["speed"] = self._settings.speed + if self._settings.config is not None: payload["model_config"] = [ - {"name": option.name, "value": option.value} - for option in self._settings["config"] + {"name": option.name, "value": option.value} for option in self._settings.config ] yield TTSStartedFrame(context_id=context_id) diff --git a/src/pipecat/services/hume/tts.py b/src/pipecat/services/hume/tts.py index 2d98e1f8c..3b45cc249 100644 --- a/src/pipecat/services/hume/tts.py +++ b/src/pipecat/services/hume/tts.py @@ -117,7 +117,7 @@ class HumeTTSService(WordTTSService): self._params = params or HumeTTSService.InputParams() # Store voice in the base class (mirrors other services) - self.set_voice(voice_id) + self._voice_id = voice_id self._audio_bytes = b"" @@ -196,7 +196,7 @@ class HumeTTSService(WordTTSService): key_l = (key or "").lower() if key_l == "voice_id": - self.set_voice(str(value)) + await self.set_voice(str(value)) logger.debug(f"HumeTTSService voice_id set to: {self.voice}") elif key_l == "description": self._params.description = None if value is None else str(value) diff --git a/src/pipecat/services/inworld/tts.py b/src/pipecat/services/inworld/tts.py index 2ea94399b..68c140187 100644 --- a/src/pipecat/services/inworld/tts.py +++ b/src/pipecat/services/inworld/tts.py @@ -16,6 +16,7 @@ Inworld’s text-to-speech (TTS) models offer ultra-realistic, context-aware spe import asyncio import base64 import json +from dataclasses import dataclass, field from typing import Any, AsyncGenerator, Dict, List, Optional, Tuple import aiohttp @@ -23,6 +24,8 @@ import websockets from loguru import logger from pydantic import BaseModel +from pipecat.services.settings import NOT_GIVEN, TTSSettings, is_given + try: from websockets.asyncio.client import connect as websocket_connect from websockets.protocol import State @@ -47,6 +50,31 @@ from pipecat.services.tts_service import AudioContextWordTTSService, WordTTSServ from pipecat.utils.tracing.service_decorators import traced_tts +@dataclass +class InworldTTSSettings(TTSSettings): + """Typed settings for Inworld TTS services. + + Parameters: + audio_encoding: Audio encoding format (e.g. LINEAR16). + audio_sample_rate: Audio sample rate in Hz. + speaking_rate: Speaking rate for speech synthesis. + temperature: Temperature for speech synthesis. + auto_mode: Whether to use auto mode. Recommended when texts are sent + in full sentences/phrases. When enabled, the server controls + flushing of buffered text to achieve minimal latency while + maintaining high quality audio output. If None (default), + automatically set based on aggregate_sentences. + apply_text_normalization: Whether to apply text normalization. + """ + + audio_encoding: str = field(default_factory=lambda: NOT_GIVEN) + audio_sample_rate: int = field(default_factory=lambda: NOT_GIVEN) + speaking_rate: float = field(default_factory=lambda: NOT_GIVEN) + temperature: float = field(default_factory=lambda: NOT_GIVEN) + auto_mode: bool = field(default_factory=lambda: NOT_GIVEN) + apply_text_normalization: str = field(default_factory=lambda: NOT_GIVEN) + + class InworldHttpTTSService(WordTTSService): """Inworld AI HTTP-based TTS service. @@ -110,23 +138,21 @@ class InworldHttpTTSService(WordTTSService): else: self._base_url = "https://api.inworld.ai/tts/v1/voice" - self._settings = { - "voiceId": voice_id, - "modelId": model, - "audioConfig": { - "audioEncoding": encoding, - "sampleRateHertz": 0, - }, - } + self._settings: InworldTTSSettings = InworldTTSSettings( + model=model, + voice=voice_id, + audio_encoding=encoding, + audio_sample_rate=0, + ) if params.temperature is not None: - self._settings["temperature"] = params.temperature + self._settings.temperature = params.temperature if params.speaking_rate is not None: - self._settings["audioConfig"]["speakingRate"] = params.speaking_rate + self._settings.speaking_rate = params.speaking_rate self._cumulative_time = 0.0 - self.set_voice(voice_id) + self._voice_id = voice_id self.set_model_name(model) def can_generate_metrics(self) -> bool: @@ -144,7 +170,7 @@ class InworldHttpTTSService(WordTTSService): frame: The start frame. """ await super().start(frame) - self._settings["audioConfig"]["sampleRateHertz"] = self.sample_rate + self._settings.audio_sample_rate = self.sample_rate async def stop(self, frame: EndFrame): """Stop the Inworld TTS service. @@ -223,15 +249,22 @@ class InworldHttpTTSService(WordTTSService): """ logger.debug(f"{self}: Generating TTS [{text}] (streaming={self._streaming})") + audio_config = { + "audioEncoding": self._settings.audio_encoding, + "sampleRateHertz": self._settings.audio_sample_rate, + } + if is_given(self._settings.speaking_rate): + audio_config["speakingRate"] = self._settings.speaking_rate + payload = { "text": text, - "voiceId": self._settings["voiceId"], - "modelId": self._settings["modelId"], - "audioConfig": self._settings["audioConfig"], + "voiceId": self._settings.voice, + "modelId": self._settings.model, + "audioConfig": audio_config, } - if "temperature" in self._settings: - payload["temperature"] = self._settings["temperature"] + if is_given(self._settings.temperature): + payload["temperature"] = self._settings.temperature # Use WORD timestamps for simplicity and correct spacing/capitalization payload["timestampType"] = self._timestamp_type @@ -470,27 +503,25 @@ class InworldTTSService(AudioContextWordTTSService): self._api_key = api_key self._url = url - self._settings: Dict[str, Any] = { - "voiceId": voice_id, - "modelId": model, - "audioConfig": { - "audioEncoding": encoding, - "sampleRateHertz": 0, - }, - } + self._settings: InworldTTSSettings = InworldTTSSettings( + model=model, + voice=voice_id, + audio_encoding=encoding, + audio_sample_rate=0, + ) self._timestamp_type = "WORD" if params.temperature is not None: - self._settings["temperature"] = params.temperature + self._settings.temperature = params.temperature if params.speaking_rate is not None: - self._settings["audioConfig"]["speakingRate"] = params.speaking_rate + self._settings.speaking_rate = params.speaking_rate if params.apply_text_normalization is not None: - self._settings["applyTextNormalization"] = params.apply_text_normalization + self._settings.apply_text_normalization = params.apply_text_normalization if params.auto_mode is not None: - self._settings["autoMode"] = params.auto_mode + self._settings.auto_mode = params.auto_mode else: - self._settings["autoMode"] = aggregate_sentences + self._settings.auto_mode = aggregate_sentences self._buffer_settings = { "maxBufferDelayMs": params.max_buffer_delay_ms, @@ -509,7 +540,7 @@ class InworldTTSService(AudioContextWordTTSService): # Track the end time of the last word in the current generation self._generation_end_time = 0.0 - self.set_voice(voice_id) + self._voice_id = voice_id self.set_model_name(model) def can_generate_metrics(self) -> bool: @@ -527,7 +558,7 @@ class InworldTTSService(AudioContextWordTTSService): frame: The start frame. """ await super().start(frame) - self._settings["audioConfig"]["sampleRateHertz"] = self.sample_rate + self._settings.audio_sample_rate = self.sample_rate await self._connect() async def stop(self, frame: EndFrame): @@ -859,18 +890,25 @@ class InworldTTSService(AudioContextWordTTSService): Args: context_id: The context ID. """ + audio_config = { + "audioEncoding": self._settings.audio_encoding, + "sampleRateHertz": self._settings.audio_sample_rate, + } + if is_given(self._settings.speaking_rate): + audio_config["speakingRate"] = self._settings.speaking_rate + create_config: Dict[str, Any] = { - "voiceId": self._settings["voiceId"], - "modelId": self._settings["modelId"], - "audioConfig": self._settings["audioConfig"], + "voiceId": self._settings.voice, + "modelId": self._settings.model, + "audioConfig": audio_config, } - if "temperature" in self._settings: - create_config["temperature"] = self._settings["temperature"] - if "applyTextNormalization" in self._settings: - create_config["applyTextNormalization"] = self._settings["applyTextNormalization"] - if "autoMode" in self._settings: - create_config["autoMode"] = self._settings["autoMode"] + if is_given(self._settings.temperature): + create_config["temperature"] = self._settings.temperature + if is_given(self._settings.apply_text_normalization): + create_config["applyTextNormalization"] = self._settings.apply_text_normalization + if is_given(self._settings.auto_mode): + create_config["autoMode"] = self._settings.auto_mode # Set buffer settings for timely audio generation. # Use provided values or defaults that work well for streaming LLM output. diff --git a/src/pipecat/services/kokoro/tts.py b/src/pipecat/services/kokoro/tts.py index 49ede2409..242446de9 100644 --- a/src/pipecat/services/kokoro/tts.py +++ b/src/pipecat/services/kokoro/tts.py @@ -7,6 +7,7 @@ """Kokoro TTS service implementation using kokoro-onnx.""" import os +from dataclasses import dataclass, field from pathlib import Path from typing import AsyncGenerator, Optional @@ -22,6 +23,7 @@ from pipecat.frames.frames import ( TTSStartedFrame, TTSStoppedFrame, ) +from pipecat.services.settings import NOT_GIVEN, TTSSettings from pipecat.services.tts_service import TTSService from pipecat.transcriptions.language import Language, resolve_language from pipecat.utils.tracing.service_decorators import traced_tts @@ -87,6 +89,17 @@ def language_to_kokoro_language(language: Language) -> str: return resolve_language(language, LANGUAGE_MAP, use_base_code=True) +@dataclass +class KokoroTTSSettings(TTSSettings): + """Typed settings for the Kokoro TTS service. + + Parameters: + lang_code: Kokoro language code for synthesis. + """ + + lang_code: str = field(default_factory=lambda: NOT_GIVEN) + + class KokoroTTSService(TTSService): """Kokoro TTS service implementation. @@ -129,6 +142,12 @@ class KokoroTTSService(TTSService): self._voice_id = voice_id self._lang_code = language_to_kokoro_language(params.language) + self._settings: KokoroTTSSettings = KokoroTTSSettings( + voice=voice_id, + language=language_to_kokoro_language(params.language), + lang_code=language_to_kokoro_language(params.language), + ) + model = Path(model_path) if model_path else KOKORO_CACHE_DIR / "kokoro-v1.0.onnx" voices = Path(voices_path) if voices_path else KOKORO_CACHE_DIR / "voices-v1.0.bin" diff --git a/src/pipecat/services/llm_service.py b/src/pipecat/services/llm_service.py index af7e691b0..77af50f15 100644 --- a/src/pipecat/services/llm_service.py +++ b/src/pipecat/services/llm_service.py @@ -44,6 +44,7 @@ from pipecat.frames.frames import ( LLMFullResponseEndFrame, LLMFullResponseStartFrame, LLMTextFrame, + LLMUpdateSettingsFrame, StartFrame, UserImageRequestFrame, ) @@ -58,6 +59,7 @@ from pipecat.processors.aggregators.llm_response import ( from pipecat.processors.aggregators.openai_llm_context import OpenAILLMContext from pipecat.processors.frame_processor import FrameDirection from pipecat.services.ai_service import AIService +from pipecat.services.settings import ServiceSettings from pipecat.turns.user_turn_completion_mixin import UserTurnCompletionLLMServiceMixin from pipecat.utils.context.llm_context_summarization import ( LLMContextSummarizationUtil, @@ -351,6 +353,17 @@ class LLMService(UserTurnCompletionLLMServiceMixin, AIService): await self._handle_interruptions(frame) elif isinstance(frame, LLMConfigureOutputFrame): self._skip_tts = frame.skip_tts + elif isinstance(frame, LLMUpdateSettingsFrame): + # New path: typed settings update object. + if frame.update is not None: + await self._update_settings_from_typed(frame.update) + # Legacy path: plain dict, but service uses typed settings — convert. + elif isinstance(self._settings, ServiceSettings): + update = type(self._settings).from_mapping(frame.settings) + await self._update_settings_from_typed(update) + # Legacy path: plain dict, service still uses dict-based settings. + else: + await self._update_settings(frame.settings) elif isinstance(frame, LLMContextSummaryRequestFrame): await self._handle_summary_request(frame) diff --git a/src/pipecat/services/lmnt/tts.py b/src/pipecat/services/lmnt/tts.py index 4c34e28d5..97569fa1d 100644 --- a/src/pipecat/services/lmnt/tts.py +++ b/src/pipecat/services/lmnt/tts.py @@ -7,6 +7,7 @@ """LMNT text-to-speech service implementation.""" import json +from dataclasses import dataclass, field from typing import AsyncGenerator, Optional from loguru import logger @@ -23,6 +24,7 @@ from pipecat.frames.frames import ( TTSStoppedFrame, ) from pipecat.processors.frame_processor import FrameDirection +from pipecat.services.settings import NOT_GIVEN, TTSSettings from pipecat.services.tts_service import InterruptibleTTSService from pipecat.transcriptions.language import Language, resolve_language from pipecat.utils.tracing.service_decorators import traced_tts @@ -71,6 +73,17 @@ def language_to_lmnt_language(language: Language) -> Optional[str]: return resolve_language(language, LANGUAGE_MAP, use_base_code=True) +@dataclass +class LmntTTSSettings(TTSSettings): + """Typed settings for LMNT TTS service. + + Parameters: + format: Audio output format. Defaults to "raw". + """ + + format: str = field(default_factory=lambda: NOT_GIVEN) + + class LmntTTSService(InterruptibleTTSService): """LMNT real-time text-to-speech service. @@ -107,12 +120,14 @@ class LmntTTSService(InterruptibleTTSService): ) self._api_key = api_key - self.set_voice(voice_id) + self._voice_id = voice_id self.set_model_name(model) - self._settings = { - "language": self.language_to_service_language(language), - "format": "raw", # Use raw format for direct PCM data - } + self._settings: LmntTTSSettings = LmntTTSSettings( + model=model, + voice=voice_id, + language=self.language_to_service_language(language), + format="raw", + ) self._receive_task = None self._context_id: Optional[str] = None @@ -202,9 +217,9 @@ class LmntTTSService(InterruptibleTTSService): init_msg = { "X-API-Key": self._api_key, "voice": self._voice_id, - "format": self._settings["format"], + "format": self._settings.format, "sample_rate": self.sample_rate, - "language": self._settings["language"], + "language": self._settings.language, "model": self.model_name, } diff --git a/src/pipecat/services/minimax/tts.py b/src/pipecat/services/minimax/tts.py index 7284d9630..6ce3e4b45 100644 --- a/src/pipecat/services/minimax/tts.py +++ b/src/pipecat/services/minimax/tts.py @@ -11,6 +11,7 @@ for streaming text-to-speech synthesis. """ import json +from dataclasses import dataclass, field from typing import AsyncGenerator, Optional import aiohttp @@ -25,6 +26,7 @@ from pipecat.frames.frames import ( TTSStartedFrame, TTSStoppedFrame, ) +from pipecat.services.settings import NOT_GIVEN, TTSSettings, is_given from pipecat.services.tts_service import TTSService from pipecat.transcriptions.language import Language, resolve_language from pipecat.utils.tracing.service_decorators import traced_tts @@ -85,6 +87,40 @@ def language_to_minimax_language(language: Language) -> Optional[str]: return resolve_language(language, LANGUAGE_MAP, use_base_code=False) +@dataclass +class MiniMaxTTSSettings(TTSSettings): + """Typed settings for MiniMax TTS service. + + Parameters: + stream: Whether to use streaming mode. + speed: Speech speed (range: 0.5 to 2.0). + volume: Speech volume (range: 0 to 10). + pitch: Pitch adjustment (range: -12 to 12). + emotion: Emotional tone (options: "happy", "sad", "angry", "fearful", + "disgusted", "surprised", "calm", "fluent"). + text_normalization: Enable text normalization (Chinese/English). + latex_read: Enable LaTeX formula reading. + audio_bitrate: Audio bitrate in bps. + audio_format: Audio output format. + audio_channel: Number of audio channels. + audio_sample_rate: Audio sample rate in Hz. + language_boost: Language boost string for multilingual support. + """ + + stream: bool = field(default_factory=lambda: NOT_GIVEN) + speed: float = field(default_factory=lambda: NOT_GIVEN) + volume: float = field(default_factory=lambda: NOT_GIVEN) + pitch: int = field(default_factory=lambda: NOT_GIVEN) + emotion: str = field(default_factory=lambda: NOT_GIVEN) + text_normalization: bool = field(default_factory=lambda: NOT_GIVEN) + latex_read: bool = field(default_factory=lambda: NOT_GIVEN) + audio_bitrate: int = field(default_factory=lambda: NOT_GIVEN) + audio_format: str = field(default_factory=lambda: NOT_GIVEN) + audio_channel: int = field(default_factory=lambda: NOT_GIVEN) + audio_sample_rate: int = field(default_factory=lambda: NOT_GIVEN) + language_boost: str = field(default_factory=lambda: NOT_GIVEN) + + class MiniMaxHttpTTSService(TTSService): """Text-to-speech service using MiniMax's T2A (Text-to-Audio) API. @@ -172,29 +208,27 @@ class MiniMaxHttpTTSService(TTSService): self._voice_id = voice_id # Create voice settings - self._settings = { - "stream": True, - "voice_setting": { - "speed": params.speed, - "vol": params.volume, - "pitch": params.pitch, - }, - "audio_setting": { - "bitrate": 128000, - "format": "pcm", - "channel": 1, - }, - } + self._settings: MiniMaxTTSSettings = MiniMaxTTSSettings( + model=model, + voice=voice_id, + stream=True, + speed=params.speed, + volume=params.volume, + pitch=params.pitch, + audio_bitrate=128000, + audio_format="pcm", + audio_channel=1, + ) # Set voice and model - self.set_voice(voice_id) + self._voice_id = voice_id self.set_model_name(model) # Add language boost if provided if params.language: service_lang = self.language_to_service_language(params.language) if service_lang: - self._settings["language_boost"] = service_lang + self._settings.language_boost = service_lang # Add optional emotion if provided if params.emotion: @@ -210,7 +244,7 @@ class MiniMaxHttpTTSService(TTSService): "fluent", ] if params.emotion in supported_emotions: - self._settings["voice_setting"]["emotion"] = params.emotion + self._settings.emotion = params.emotion else: logger.warning( f"Unsupported emotion: {params.emotion}. Supported emotions: {supported_emotions}" @@ -226,15 +260,15 @@ class MiniMaxHttpTTSService(TTSService): "Parameter `english_normalization` is deprecated and will be removed in a future version. Use `text_normalization` instead.", DeprecationWarning, ) - self._settings["voice_setting"]["text_normalization"] = params.english_normalization + self._settings.text_normalization = params.english_normalization # Add text_normalization if provided (corrected parameter name) if params.text_normalization is not None: - self._settings["voice_setting"]["text_normalization"] = params.text_normalization + self._settings.text_normalization = params.text_normalization # Add latex_read if provided if params.latex_read is not None: - self._settings["voice_setting"]["latex_read"] = params.latex_read + self._settings.latex_read = params.latex_read def can_generate_metrics(self) -> bool: """Check if this service can generate processing metrics. @@ -263,16 +297,6 @@ class MiniMaxHttpTTSService(TTSService): """ self._model_name = model - def set_voice(self, voice: str): - """Set the voice to use. - - Args: - voice: The voice identifier to use for synthesis. - """ - self._voice_id = voice - if "voice_setting" in self._settings: - self._settings["voice_setting"]["voice_id"] = voice - async def start(self, frame: StartFrame): """Start the MiniMax TTS service. @@ -280,7 +304,7 @@ class MiniMaxHttpTTSService(TTSService): frame: The start frame containing initialization parameters. """ await super().start(frame) - self._settings["audio_setting"]["sample_rate"] = self.sample_rate + self._settings.audio_sample_rate = self.sample_rate logger.debug(f"MiniMax TTS initialized with sample_rate: {self.sample_rate}") @traced_tts @@ -302,10 +326,38 @@ class MiniMaxHttpTTSService(TTSService): "Authorization": f"Bearer {self._api_key}", } + # Build voice_setting dict for API + voice_setting = { + "voice_id": self._voice_id, + "speed": self._settings.speed, + "vol": self._settings.volume, + "pitch": self._settings.pitch, + } + if is_given(self._settings.emotion): + voice_setting["emotion"] = self._settings.emotion + if is_given(self._settings.text_normalization): + voice_setting["text_normalization"] = self._settings.text_normalization + if is_given(self._settings.latex_read): + voice_setting["latex_read"] = self._settings.latex_read + + # Build audio_setting dict for API + audio_setting = { + "bitrate": self._settings.audio_bitrate, + "format": self._settings.audio_format, + "channel": self._settings.audio_channel, + "sample_rate": self._settings.audio_sample_rate, + } + # Create payload from settings - payload = self._settings.copy() - payload["model"] = self._model_name - payload["text"] = text + payload = { + "stream": self._settings.stream, + "voice_setting": voice_setting, + "audio_setting": audio_setting, + "model": self._model_name, + "text": text, + } + if is_given(self._settings.language_boost): + payload["language_boost"] = self._settings.language_boost try: await self.start_ttfb_metrics() diff --git a/src/pipecat/services/mistral/llm.py b/src/pipecat/services/mistral/llm.py index 54361ef28..7a8f5b71a 100644 --- a/src/pipecat/services/mistral/llm.py +++ b/src/pipecat/services/mistral/llm.py @@ -185,19 +185,19 @@ class MistralLLMService(OpenAILLMService): "messages": fixed_messages, "tools": params_from_context["tools"], "tool_choice": params_from_context["tool_choice"], - "frequency_penalty": self._settings["frequency_penalty"], - "presence_penalty": self._settings["presence_penalty"], - "temperature": self._settings["temperature"], - "top_p": self._settings["top_p"], - "max_tokens": self._settings["max_tokens"], + "frequency_penalty": self._settings.frequency_penalty, + "presence_penalty": self._settings.presence_penalty, + "temperature": self._settings.temperature, + "top_p": self._settings.top_p, + "max_tokens": self._settings.max_tokens, } # Handle Mistral-specific parameter mapping # Mistral uses "random_seed" instead of "seed" - if self._settings["seed"]: - params["random_seed"] = self._settings["seed"] + if self._settings.seed: + params["random_seed"] = self._settings.seed # Add any extra parameters - params.update(self._settings["extra"]) + params.update(self._settings.extra) return params diff --git a/src/pipecat/services/neuphonic/tts.py b/src/pipecat/services/neuphonic/tts.py index 24eb05bd3..b7019e6d6 100644 --- a/src/pipecat/services/neuphonic/tts.py +++ b/src/pipecat/services/neuphonic/tts.py @@ -13,7 +13,8 @@ text-to-speech API for real-time audio synthesis. import asyncio import base64 import json -from typing import Any, AsyncGenerator, Mapping, Optional +from dataclasses import dataclass, field +from typing import AsyncGenerator, Optional import aiohttp from loguru import logger @@ -34,6 +35,7 @@ from pipecat.frames.frames import ( TTSStoppedFrame, ) from pipecat.processors.frame_processor import FrameDirection +from pipecat.services.settings import NOT_GIVEN, TTSSettings from pipecat.services.tts_service import InterruptibleTTSService, TTSService from pipecat.transcriptions.language import Language, resolve_language from pipecat.utils.tracing.service_decorators import traced_tts @@ -72,6 +74,23 @@ def language_to_neuphonic_lang_code(language: Language) -> Optional[str]: return resolve_language(language, LANGUAGE_MAP, use_base_code=True) +@dataclass +class NeuphonicTTSSettings(TTSSettings): + """Typed settings for Neuphonic TTS service. + + Parameters: + lang_code: Neuphonic language code. + speed: Speech speed multiplier. Defaults to 1.0. + encoding: Audio encoding format. + sampling_rate: Audio sample rate. + """ + + lang_code: str = field(default_factory=lambda: NOT_GIVEN) + speed: float = field(default_factory=lambda: NOT_GIVEN) + encoding: str = field(default_factory=lambda: NOT_GIVEN) + sampling_rate: int = field(default_factory=lambda: NOT_GIVEN) + + class NeuphonicTTSService(InterruptibleTTSService): """Neuphonic real-time text-to-speech service using WebSocket streaming. @@ -127,13 +146,13 @@ class NeuphonicTTSService(InterruptibleTTSService): self._api_key = api_key self._url = url - self._settings = { - "lang_code": self.language_to_service_language(params.language), - "speed": params.speed, - "encoding": encoding, - "sampling_rate": sample_rate, - } - self.set_voice(voice_id) + self._settings: NeuphonicTTSSettings = NeuphonicTTSSettings( + lang_code=self.language_to_service_language(params.language), + speed=params.speed, + encoding=encoding, + sampling_rate=sample_rate, + ) + self._voice_id = voice_id self._cumulative_time = 0 @@ -160,15 +179,14 @@ class NeuphonicTTSService(InterruptibleTTSService): """ return language_to_neuphonic_lang_code(language) - async def _update_settings(self, settings: Mapping[str, Any]): - """Update service settings and reconnect with new configuration.""" - if "voice_id" in settings: - self.set_voice(settings["voice_id"]) - - await super()._update_settings(settings) - await self._disconnect() - await self._connect() - logger.info(f"Switching TTS to settings: [{self._settings}]") + async def _update_settings_from_typed(self, update: TTSSettings) -> set[str]: + """Apply a typed settings update and reconnect with new configuration.""" + changed = await super()._update_settings_from_typed(update) + if changed: + await self._disconnect() + await self._connect() + logger.info(f"Switching TTS to settings: [{self._settings}]") + return changed async def start(self, frame: StartFrame): """Start the Neuphonic TTS service. @@ -266,7 +284,10 @@ class NeuphonicTTSService(InterruptibleTTSService): logger.debug("Connecting to Neuphonic") tts_config = { - **self._settings, + "lang_code": self._settings.lang_code, + "speed": self._settings.speed, + "encoding": self._settings.encoding, + "sampling_rate": self._settings.sampling_rate, "voice_id": self._voice_id, } @@ -275,7 +296,7 @@ class NeuphonicTTSService(InterruptibleTTSService): if value is not None: query_params.append(f"{key}={value}") - url = f"{self._url}/speak/{self._settings['lang_code']}" + url = f"{self._url}/speak/{self._settings.lang_code}" if query_params: url += f"?{'&'.join(query_params)}" @@ -429,7 +450,7 @@ class NeuphonicHttpTTSService(TTSService): self._lang_code = self.language_to_service_language(params.language) or "en" self._speed = params.speed self._encoding = encoding - self.set_voice(voice_id) + self._voice_id = voice_id def can_generate_metrics(self) -> bool: """Check if this service can generate processing metrics. diff --git a/src/pipecat/services/nvidia/stt.py b/src/pipecat/services/nvidia/stt.py index 8eb6d7bb5..c65d6da62 100644 --- a/src/pipecat/services/nvidia/stt.py +++ b/src/pipecat/services/nvidia/stt.py @@ -8,6 +8,7 @@ import asyncio from concurrent.futures import CancelledError as FuturesCancelledError +from dataclasses import dataclass, field from typing import AsyncGenerator, List, Mapping, Optional from loguru import logger @@ -22,6 +23,7 @@ from pipecat.frames.frames import ( StartFrame, TranscriptionFrame, ) +from pipecat.services.settings import NOT_GIVEN, STTSettings from pipecat.services.stt_latency import NVIDIA_TTFS_P99 from pipecat.services.stt_service import SegmentedSTTService, STTService from pipecat.transcriptions.language import Language, resolve_language @@ -89,6 +91,32 @@ def language_to_nvidia_riva_language(language: Language) -> Optional[str]: return resolve_language(language, LANGUAGE_MAP, use_base_code=False) +@dataclass +class NvidiaSTTSettings(STTSettings): + """Typed settings for the NVIDIA Riva streaming STT service.""" + + pass + + +@dataclass +class NvidiaSegmentedSTTSettings(STTSettings): + """Typed settings for the NVIDIA Riva segmented STT service. + + Parameters: + profanity_filter: Whether to filter profanity from results. + automatic_punctuation: Whether to add automatic punctuation. + verbatim_transcripts: Whether to return verbatim transcripts. + boosted_lm_words: List of words to boost in language model. + boosted_lm_score: Score boost for specified words. + """ + + profanity_filter: bool = field(default_factory=lambda: NOT_GIVEN) + automatic_punctuation: bool = field(default_factory=lambda: NOT_GIVEN) + verbatim_transcripts: bool = field(default_factory=lambda: NOT_GIVEN) + boosted_lm_words: Optional[List[str]] = field(default_factory=lambda: NOT_GIVEN) + boosted_lm_score: float = field(default_factory=lambda: NOT_GIVEN) + + class NvidiaSTTService(STTService): """Real-time speech-to-text service using NVIDIA Riva streaming ASR. @@ -141,12 +169,6 @@ class NvidiaSTTService(STTService): self._server = server self._api_key = api_key self._use_ssl = use_ssl - self._profanity_filter = False - self._automatic_punctuation = True - self._no_verbatim_transcripts = False - self._language_code = params.language - self._boosted_lm_words = None - self._boosted_lm_score = 4.0 self._start_history = -1 self._start_threshold = -1.0 self._stop_history = -1 @@ -156,14 +178,9 @@ class NvidiaSTTService(STTService): self._custom_configuration = "" self._function_id = model_function_map.get("function_id") - self._settings = { - "language": str(params.language), - "profanity_filter": self._profanity_filter, - "automatic_punctuation": self._automatic_punctuation, - "verbatim_transcripts": not self._no_verbatim_transcripts, - "boosted_lm_words": self._boosted_lm_words, - "boosted_lm_score": self._boosted_lm_score, - } + self._settings: NvidiaSTTSettings = NvidiaSTTSettings( + language=params.language, + ) self.set_model_name(model_function_map.get("model_name")) @@ -186,22 +203,18 @@ class NvidiaSTTService(STTService): config = riva.client.StreamingRecognitionConfig( config=riva.client.RecognitionConfig( encoding=riva.client.AudioEncoding.LINEAR_PCM, - language_code=self._language_code, + language_code=self._settings.language, model="", max_alternatives=1, - profanity_filter=self._profanity_filter, - enable_automatic_punctuation=self._automatic_punctuation, - verbatim_transcripts=not self._no_verbatim_transcripts, + profanity_filter=False, + enable_automatic_punctuation=True, + verbatim_transcripts=True, sample_rate_hertz=self.sample_rate, audio_channel_count=1, ), interim_results=True, ) - riva.client.add_word_boosting_to_config( - config, self._boosted_lm_words, self._boosted_lm_score - ) - riva.client.add_endpoint_parameters_to_config( config, self._start_history, @@ -318,14 +331,14 @@ class NvidiaSTTService(STTService): transcript, self._user_id, time_now_iso8601(), - self._language_code, + self._settings.language, result=result, ) ) await self._handle_transcription( transcript=transcript, is_final=result.is_final, - language=self._language_code, + language=self._settings.language, ) else: await self.push_frame( @@ -333,7 +346,7 @@ class NvidiaSTTService(STTService): transcript, self._user_id, time_now_iso8601(), - self._language_code, + self._settings.language, result=result, ) ) @@ -445,18 +458,6 @@ class NvidiaSegmentedSTTService(SegmentedSTTService): self._server = server self._use_ssl = use_ssl self._function_id = model_function_map.get("function_id") - self._model_name = model_function_map.get("model_name") - - # Store the language as a Language enum and as a string - self._language_enum = params.language or Language.EN_US - self._language = self.language_to_service_language(self._language_enum) or "en-US" - - # Configure transcription parameters - self._profanity_filter = params.profanity_filter - self._automatic_punctuation = params.automatic_punctuation - self._verbatim_transcripts = params.verbatim_transcripts - self._boosted_lm_words = params.boosted_lm_words - self._boosted_lm_score = params.boosted_lm_score # Voice activity detection thresholds (use NVIDIA Riva defaults) self._start_history = -1 @@ -467,10 +468,16 @@ class NvidiaSegmentedSTTService(SegmentedSTTService): self._stop_threshold_eou = -1.0 self._custom_configuration = "" - # Create NVIDIA Riva client self._config = None self._asr_service = None - self._settings = {"language": self._language_enum} + self._settings: NvidiaSegmentedSTTSettings = NvidiaSegmentedSTTSettings( + language=params.language or Language.EN_US, + profanity_filter=params.profanity_filter, + automatic_punctuation=params.automatic_punctuation, + verbatim_transcripts=params.verbatim_transcripts, + boosted_lm_words=params.boosted_lm_words, + boosted_lm_score=params.boosted_lm_score, + ) def language_to_service_language(self, language: Language) -> Optional[str]: """Convert pipecat Language enum to NVIDIA Riva's language code. @@ -498,21 +505,25 @@ class NvidiaSegmentedSTTService(SegmentedSTTService): auth = riva.client.Auth(None, self._use_ssl, self._server, metadata) self._asr_service = riva.client.ASRService(auth) + def _get_language_code(self) -> str: + """Resolve the current language enum to an NVIDIA Riva language code string.""" + return self.language_to_service_language(self._settings.language) or "en-US" + def _create_recognition_config(self): """Create the NVIDIA Riva ASR recognition configuration.""" # Create base configuration config = riva.client.RecognitionConfig( - language_code=self._language, # Now using the string, not a tuple + language_code=self._get_language_code(), max_alternatives=1, - profanity_filter=self._profanity_filter, - enable_automatic_punctuation=self._automatic_punctuation, - verbatim_transcripts=self._verbatim_transcripts, + profanity_filter=self._settings.profanity_filter, + enable_automatic_punctuation=self._settings.automatic_punctuation, + verbatim_transcripts=self._settings.verbatim_transcripts, ) # Add word boosting if specified - if self._boosted_lm_words: + if self._settings.boosted_lm_words: riva.client.add_word_boosting_to_config( - config, self._boosted_lm_words, self._boosted_lm_score + config, self._settings.boosted_lm_words, self._settings.boosted_lm_score ) # Add voice activity detection parameters @@ -567,20 +578,21 @@ class NvidiaSegmentedSTTService(SegmentedSTTService): self._config = self._create_recognition_config() logger.debug(f"Initialized NvidiaSegmentedSTTService with model: {self.model_name}") - async def set_language(self, language: Language): - """Set the language for the STT service. + async def _update_settings_from_typed(self, update: STTSettings) -> set[str]: + """Apply a typed settings update and sync internal state. Args: - language: Target language for transcription. - """ - logger.info(f"Switching STT language to: [{language}]") - self._language_enum = language - self._language = self.language_to_service_language(language) or "en-US" - self._settings["language"] = language + update: A :class:`STTSettings` (or ``NvidiaSegmentedSTTSettings``) delta. - # Update configuration with new language - if self._config: - self._config.language_code = self._language + Returns: + Set of field names whose values actually changed. + """ + changed = await super()._update_settings_from_typed(update) + + if changed: + self._config = self._create_recognition_config() + + return changed @traced_stt async def _handle_transcription( @@ -633,11 +645,11 @@ class NvidiaSegmentedSTTService(SegmentedSTTService): text, self._user_id, time_now_iso8601(), - self._language_enum, + self._settings.language, ) transcription_found = True - await self._handle_transcription(text, True, self._language_enum) + await self._handle_transcription(text, True, self._settings.language) if not transcription_found: logger.debug(f"{self}: No transcription results found in NVIDIA Riva response") diff --git a/src/pipecat/services/nvidia/tts.py b/src/pipecat/services/nvidia/tts.py index 6bac54e3a..8a018d6aa 100644 --- a/src/pipecat/services/nvidia/tts.py +++ b/src/pipecat/services/nvidia/tts.py @@ -100,7 +100,7 @@ class NvidiaTTSService(TTSService): self._function_id = model_function_map.get("function_id") self._use_ssl = use_ssl self.set_model_name(model_function_map.get("model_name")) - self.set_voice(voice_id) + self._voice_id = voice_id self._service = None self._config = None diff --git a/src/pipecat/services/openai/base_llm.py b/src/pipecat/services/openai/base_llm.py index 2cdde51ea..2ac53794c 100644 --- a/src/pipecat/services/openai/base_llm.py +++ b/src/pipecat/services/openai/base_llm.py @@ -10,7 +10,8 @@ import asyncio import base64 import json from contextlib import asynccontextmanager -from typing import Any, Dict, List, Mapping, Optional +from dataclasses import dataclass, field +from typing import Any, ClassVar, Dict, List, Mapping, Optional import httpx from loguru import logger @@ -32,7 +33,6 @@ from pipecat.frames.frames import ( LLMFullResponseStartFrame, LLMMessagesFrame, LLMTextFrame, - LLMUpdateSettingsFrame, ) from pipecat.metrics.metrics import LLMTokenUsage from pipecat.processors.aggregators.llm_context import LLMContext @@ -42,9 +42,24 @@ from pipecat.processors.aggregators.openai_llm_context import ( ) from pipecat.processors.frame_processor import FrameDirection from pipecat.services.llm_service import FunctionCallFromLLM, LLMService +from pipecat.services.settings import NOT_GIVEN as _NOT_GIVEN +from pipecat.services.settings import LLMSettings from pipecat.utils.tracing.service_decorators import traced_llm +@dataclass +class OpenAILLMSettings(LLMSettings): + """Typed settings for OpenAI-compatible LLM services. + + Parameters: + max_completion_tokens: Maximum completion tokens to generate. + service_tier: Service tier to use (e.g., "auto", "flex", "priority"). + """ + + max_completion_tokens: Any = field(default_factory=lambda: _NOT_GIVEN) + service_tier: Any = field(default_factory=lambda: _NOT_GIVEN) + + class BaseOpenAILLMService(LLMService): """Base class for all services that use the AsyncOpenAI client. @@ -120,17 +135,18 @@ class BaseOpenAILLMService(LLMService): params = params or BaseOpenAILLMService.InputParams() - self._settings = { - "frequency_penalty": params.frequency_penalty, - "presence_penalty": params.presence_penalty, - "seed": params.seed, - "temperature": params.temperature, - "top_p": params.top_p, - "max_tokens": params.max_tokens, - "max_completion_tokens": params.max_completion_tokens, - "service_tier": params.service_tier, - "extra": params.extra if isinstance(params.extra, dict) else {}, - } + self._settings = OpenAILLMSettings( + model=model, + frequency_penalty=params.frequency_penalty, + presence_penalty=params.presence_penalty, + seed=params.seed, + temperature=params.temperature, + top_p=params.top_p, + max_tokens=params.max_tokens, + max_completion_tokens=params.max_completion_tokens, + service_tier=params.service_tier, + extra=params.extra if isinstance(params.extra, dict) else {}, + ) self._retry_timeout_secs = retry_timeout_secs self._retry_on_timeout = retry_on_timeout self.set_model_name(model) @@ -250,20 +266,20 @@ class BaseOpenAILLMService(LLMService): "model": self.model_name, "stream": True, "stream_options": {"include_usage": True}, - "frequency_penalty": self._settings["frequency_penalty"], - "presence_penalty": self._settings["presence_penalty"], - "seed": self._settings["seed"], - "temperature": self._settings["temperature"], - "top_p": self._settings["top_p"], - "max_tokens": self._settings["max_tokens"], - "max_completion_tokens": self._settings["max_completion_tokens"], - "service_tier": self._settings["service_tier"], + "frequency_penalty": self._settings.frequency_penalty, + "presence_penalty": self._settings.presence_penalty, + "seed": self._settings.seed, + "temperature": self._settings.temperature, + "top_p": self._settings.top_p, + "max_tokens": self._settings.max_tokens, + "max_completion_tokens": self._settings.max_completion_tokens, + "service_tier": self._settings.service_tier, } # Messages, tools, tool_choice params.update(params_from_context) - params.update(self._settings["extra"]) + params.update(self._settings.extra) return params async def run_inference( @@ -508,8 +524,6 @@ class BaseOpenAILLMService(LLMService): # NOTE: LLMMessagesFrame is deprecated, so we don't support the newer universal # LLMContext with it context = OpenAILLMContext.from_messages(frame.messages) - elif isinstance(frame, LLMUpdateSettingsFrame): - await self._update_settings(frame.settings) else: await self.push_frame(frame, direction) diff --git a/src/pipecat/services/openai/realtime/llm.py b/src/pipecat/services/openai/realtime/llm.py index cf249408c..abd66963b 100644 --- a/src/pipecat/services/openai/realtime/llm.py +++ b/src/pipecat/services/openai/realtime/llm.py @@ -10,8 +10,8 @@ import base64 import io import json import time -from dataclasses import dataclass -from typing import Optional +from dataclasses import dataclass, field +from typing import Any, Optional from loguru import logger from PIL import Image @@ -59,6 +59,7 @@ from pipecat.processors.aggregators.openai_llm_context import ( ) from pipecat.processors.frame_processor import FrameDirection from pipecat.services.llm_service import FunctionCallFromLLM, LLMService +from pipecat.services.settings import NOT_GIVEN, LLMSettings from pipecat.transcriptions.language import Language from pipecat.utils.time import time_now_iso8601 from pipecat.utils.tracing.service_decorators import traced_openai_realtime, traced_stt @@ -90,6 +91,17 @@ class CurrentAudioResponse: total_size: int = 0 +@dataclass +class OpenAIRealtimeLLMSettings(LLMSettings): + """Typed settings for OpenAI Realtime LLM services. + + Parameters: + session_properties: OpenAI Realtime session configuration. + """ + + session_properties: Any = field(default_factory=lambda: NOT_GIVEN) + + class OpenAIRealtimeLLMService(LLMService): """OpenAI Realtime LLM service providing real-time audio and text communication. @@ -161,9 +173,9 @@ class OpenAIRealtimeLLMService(LLMService): self.base_url = full_url self.set_model_name(model) - # Initialize session_properties - self._session_properties: events.SessionProperties = ( - session_properties or events.SessionProperties() + self._settings = OpenAIRealtimeLLMSettings( + model=model, + session_properties=session_properties or events.SessionProperties(), ) self._audio_input_paused = start_audio_paused self._video_input_paused = start_video_paused @@ -227,12 +239,12 @@ class OpenAIRealtimeLLMService(LLMService): def _is_modality_enabled(self, modality: str) -> bool: """Check if a specific modality is enabled, "text" or "audio".""" - modalities = self._session_properties.output_modalities or ["audio", "text"] + modalities = self._settings.session_properties.output_modalities or ["audio", "text"] return modality in modalities def _get_enabled_modalities(self) -> list[str]: """Get the list of enabled modalities.""" - modalities = self._session_properties.output_modalities or ["audio", "text"] + modalities = self._settings.session_properties.output_modalities or ["audio", "text"] # API only supports single modality responses: either ["text"] or ["audio"] if "audio" in modalities: return ["audio"] @@ -305,9 +317,9 @@ class OpenAIRealtimeLLMService(LLMService): # None and False are different. Check for False. None means we're using OpenAI's # built-in turn detection defaults. turn_detection_disabled = ( - self._session_properties.audio - and self._session_properties.audio.input - and self._session_properties.audio.input.turn_detection is False + self._settings.session_properties.audio + and self._settings.session_properties.audio.input + and self._settings.session_properties.audio.input.turn_detection is False ) if turn_detection_disabled: await self.send_client_event(events.InputAudioBufferClearEvent()) @@ -327,9 +339,9 @@ class OpenAIRealtimeLLMService(LLMService): # None and False are different. Check for False. None means we're using OpenAI's # built-in turn detection defaults. turn_detection_disabled = ( - self._session_properties.audio - and self._session_properties.audio.input - and self._session_properties.audio.input.turn_detection is False + self._settings.session_properties.audio + and self._settings.session_properties.audio.input + and self._settings.session_properties.audio.input.turn_detection is False ) if turn_detection_disabled: await self.send_client_event(events.InputAudioBufferCommitEvent()) @@ -397,6 +409,16 @@ class OpenAIRealtimeLLMService(LLMService): frame: The frame to process. direction: The direction of frame flow in the pipeline. """ + # Legacy dict path: frame.settings contains SessionProperties fields, + # not our Settings fields, so we construct SessionProperties directly. + # The new typed path (frame.update) falls through to super, which calls + # _update_settings_from_typed → our override handles the rest. + if isinstance(frame, LLMUpdateSettingsFrame) and frame.update is None: + self._settings.session_properties = events.SessionProperties(**frame.settings) + await self._update_settings() + await self.push_frame(frame, direction) + return + await super().process_frame(frame, direction) if isinstance(frame, TranscriptionFrame): @@ -424,9 +446,6 @@ class OpenAIRealtimeLLMService(LLMService): await self._handle_bot_stopped_speaking() elif isinstance(frame, LLMMessagesAppendFrame): await self._handle_messages_append(frame) - elif isinstance(frame, LLMUpdateSettingsFrame): - self._session_properties = events.SessionProperties(**frame.settings) - await self._update_settings() elif isinstance(frame, LLMSetToolsFrame): await self._update_settings() @@ -513,8 +532,15 @@ class OpenAIRealtimeLLMService(LLMService): # treat a send-side error as fatal. await self.push_error(error_msg=f"Error sending client event: {e}", exception=e) + async def _update_settings_from_typed(self, update): + """Apply a typed settings update, sending a session update if needed.""" + changed = await super()._update_settings_from_typed(update) + if "session_properties" in changed: + await self._update_settings() + return changed + async def _update_settings(self): - settings = self._session_properties + settings = self._settings.session_properties adapter: OpenAIRealtimeLLMAdapter = self.get_llm_adapter() if self._context: diff --git a/src/pipecat/services/openai/stt.py b/src/pipecat/services/openai/stt.py index 4dd16be6e..12eada24e 100644 --- a/src/pipecat/services/openai/stt.py +++ b/src/pipecat/services/openai/stt.py @@ -16,6 +16,7 @@ Provides two STT services: import base64 import json +from dataclasses import dataclass, field from typing import AsyncGenerator, Literal, Optional, Union from loguru import logger @@ -34,6 +35,7 @@ from pipecat.frames.frames import ( VADUserStoppedSpeakingFrame, ) from pipecat.processors.frame_processor import FrameDirection +from pipecat.services.settings import NOT_GIVEN, STTSettings, is_given from pipecat.services.stt_latency import OPENAI_REALTIME_TTFS_P99, OPENAI_TTFS_P99 from pipecat.services.stt_service import WebsocketSTTService from pipecat.services.whisper.base_stt import BaseWhisperSTTService, Transcription @@ -123,6 +125,17 @@ class OpenAISTTService(BaseWhisperSTTService): _OPENAI_SAMPLE_RATE = 24000 +@dataclass +class OpenAIRealtimeSTTSettings(STTSettings): + """Typed settings for the OpenAI Realtime STT service. + + Parameters: + prompt: Optional prompt text to guide transcription style. + """ + + prompt: Optional[str] = field(default_factory=lambda: NOT_GIVEN) + + class OpenAIRealtimeSTTService(WebsocketSTTService): """OpenAI Realtime Speech-to-Text service using WebSocket transcription sessions. @@ -213,12 +226,17 @@ class OpenAIRealtimeSTTService(WebsocketSTTService): self._base_url = base_url self.set_model_name(model) - self._language_code = self._language_to_code(language) if language else None self._prompt = prompt self._turn_detection = turn_detection self._noise_reduction = noise_reduction self._should_interrupt = should_interrupt + self._settings: OpenAIRealtimeSTTSettings = OpenAIRealtimeSTTSettings( + model=model, + language=language, + prompt=prompt, + ) + self._receive_task = None self._session_ready = False self._resampler = create_stream_resampler() @@ -248,19 +266,31 @@ class OpenAIRealtimeSTTService(WebsocketSTTService): """ return True - async def set_language(self, language: Language): - """Set the language for speech recognition. + async def _update_settings_from_typed(self, update: STTSettings) -> set[str]: + """Apply a typed settings update and send session update if needed. - If the session is already active, sends an updated configuration - to the server. + Keeps ``_language_code`` and ``_prompt`` in sync with typed settings + and sends a ``session.update`` to the server when the session is active. Args: - language: The language to use for speech recognition. + update: A :class:`STTSettings` (or ``OpenAIRealtimeSTTSettings``) delta. + + Returns: + Set of field names whose values actually changed. """ - self._language_code = self._language_to_code(language) + changed = await super()._update_settings_from_typed(update) + + if not changed: + return changed + + if "prompt" in changed and isinstance(self._settings, OpenAIRealtimeSTTSettings): + self._prompt = self._settings.prompt + if self._session_ready: await self._send_session_update() + return changed + async def start(self, frame: StartFrame): """Start the service and establish WebSocket connection. @@ -407,8 +437,11 @@ class OpenAIRealtimeSTTService(WebsocketSTTService): """Send ``session.update`` to configure the transcription session.""" transcription: dict = {"model": self.model_name} - if self._language_code: - transcription["language"] = self._language_code + language_code = ( + self._language_to_code(self._settings.language) if self._settings.language else None + ) + if language_code: + transcription["language"] = language_code if self._prompt: transcription["prompt"] = self._prompt diff --git a/src/pipecat/services/openai/tts.py b/src/pipecat/services/openai/tts.py index f59f0b31b..ee1e34316 100644 --- a/src/pipecat/services/openai/tts.py +++ b/src/pipecat/services/openai/tts.py @@ -10,6 +10,7 @@ This module provides integration with OpenAI's text-to-speech API for generating high-quality synthetic speech from text input. """ +from dataclasses import dataclass, field from typing import AsyncGenerator, Dict, Literal, Optional from loguru import logger @@ -24,6 +25,7 @@ from pipecat.frames.frames import ( TTSStartedFrame, TTSStoppedFrame, ) +from pipecat.services.settings import NOT_GIVEN, TTSSettings from pipecat.services.tts_service import TTSService from pipecat.utils.tracing.service_decorators import traced_tts @@ -60,6 +62,19 @@ VALID_VOICES: Dict[str, ValidVoice] = { } +@dataclass +class OpenAITTSSettings(TTSSettings): + """Typed settings for OpenAI TTS service. + + Parameters: + instructions: Instructions to guide voice synthesis behavior. + speed: Voice speed control (0.25 to 4.0, default 1.0). + """ + + instructions: str = field(default_factory=lambda: NOT_GIVEN) + speed: float = field(default_factory=lambda: NOT_GIVEN) + + class OpenAITTSService(TTSService): """OpenAI Text-to-Speech service that generates audio from text. @@ -118,7 +133,7 @@ class OpenAITTSService(TTSService): super().__init__(sample_rate=sample_rate, **kwargs) self.set_model_name(model) - self.set_voice(voice) + self._voice_id = voice self._client = AsyncOpenAI(api_key=api_key, base_url=base_url) if instructions or speed: @@ -132,10 +147,12 @@ class OpenAITTSService(TTSService): stacklevel=2, ) - self._settings = { - "instructions": params.instructions if params else instructions, - "speed": params.speed if params else speed, - } + self._settings: OpenAITTSSettings = OpenAITTSSettings( + model=model, + voice=voice, + instructions=params.instructions if params else instructions, + speed=params.speed if params else speed, + ) def can_generate_metrics(self) -> bool: """Check if this service can generate processing metrics. @@ -145,15 +162,6 @@ class OpenAITTSService(TTSService): """ return True - async def set_model(self, model: str): - """Set the TTS model to use. - - Args: - model: The model name to use for text-to-speech synthesis. - """ - logger.info(f"Switching TTS model to: [{model}]") - self.set_model_name(model) - async def start(self, frame: StartFrame): """Start the OpenAI TTS service. @@ -190,11 +198,11 @@ class OpenAITTSService(TTSService): "response_format": "pcm", } - if self._settings["instructions"]: - create_params["instructions"] = self._settings["instructions"] + if self._settings.instructions: + create_params["instructions"] = self._settings.instructions - if self._settings["speed"]: - create_params["speed"] = self._settings["speed"] + if self._settings.speed: + create_params["speed"] = self._settings.speed async with self._client.audio.speech.with_streaming_response.create( **create_params diff --git a/src/pipecat/services/openai_realtime_beta/openai.py b/src/pipecat/services/openai_realtime_beta/openai.py index 1199d8556..d37b1434e 100644 --- a/src/pipecat/services/openai_realtime_beta/openai.py +++ b/src/pipecat/services/openai_realtime_beta/openai.py @@ -10,8 +10,8 @@ import base64 import json import time import warnings -from dataclasses import dataclass -from typing import Optional +from dataclasses import dataclass, field +from typing import Any, Optional from loguru import logger @@ -54,6 +54,7 @@ from pipecat.processors.aggregators.openai_llm_context import ( from pipecat.processors.frame_processor import FrameDirection from pipecat.services.llm_service import FunctionCallFromLLM, LLMService from pipecat.services.openai.llm import OpenAIContextAggregatorPair +from pipecat.services.settings import NOT_GIVEN, LLMSettings from pipecat.transcriptions.language import Language from pipecat.utils.time import time_now_iso8601 from pipecat.utils.tracing.service_decorators import traced_openai_realtime, traced_stt @@ -91,6 +92,17 @@ class CurrentAudioResponse: total_size: int = 0 +@dataclass +class OpenAIRealtimeBetaLLMSettings(LLMSettings): + """Typed settings for OpenAI Realtime Beta LLM services. + + Parameters: + session_properties: OpenAI Realtime session configuration. + """ + + session_properties: Any = field(default_factory=lambda: NOT_GIVEN) + + class OpenAIRealtimeBetaLLMService(LLMService): """OpenAI Realtime Beta LLM service providing real-time audio and text communication. @@ -146,8 +158,9 @@ class OpenAIRealtimeBetaLLMService(LLMService): self.base_url = full_url self.set_model_name(model) - self._session_properties: events.SessionProperties = ( - session_properties or events.SessionProperties() + self._settings = OpenAIRealtimeBetaLLMSettings( + model=model, + session_properties=session_properties or events.SessionProperties(), ) self._audio_input_paused = start_audio_paused self._send_transcription_frames = send_transcription_frames @@ -187,12 +200,12 @@ class OpenAIRealtimeBetaLLMService(LLMService): def _is_modality_enabled(self, modality: str) -> bool: """Check if a specific modality is enabled, "text" or "audio".""" - modalities = self._session_properties.modalities or ["audio", "text"] + modalities = self._settings.session_properties.modalities or ["audio", "text"] return modality in modalities def _get_enabled_modalities(self) -> list[str]: """Get the list of enabled modalities.""" - return self._session_properties.modalities or ["audio", "text"] + return self._settings.session_properties.modalities or ["audio", "text"] async def retrieve_conversation_item(self, item_id: str): """Retrieve a conversation item by ID from the server. @@ -259,7 +272,7 @@ class OpenAIRealtimeBetaLLMService(LLMService): async def _handle_interruption(self): # None and False are different. Check for False. None means we're using OpenAI's # built-in turn detection defaults. - if self._session_properties.turn_detection is False: + if self._settings.session_properties.turn_detection is False: await self.send_client_event(events.InputAudioBufferClearEvent()) await self.send_client_event(events.ResponseCancelEvent()) await self._truncate_current_audio_response() @@ -276,7 +289,7 @@ class OpenAIRealtimeBetaLLMService(LLMService): async def _handle_user_stopped_speaking(self, frame): # None and False are different. Check for False. None means we're using OpenAI's # built-in turn detection defaults. - if self._session_properties.turn_detection is False: + if self._settings.session_properties.turn_detection is False: await self.send_client_event(events.InputAudioBufferCommitEvent()) await self.send_client_event(events.ResponseCreateEvent()) @@ -342,6 +355,16 @@ class OpenAIRealtimeBetaLLMService(LLMService): frame: The frame to process. direction: The direction of frame flow in the pipeline. """ + # Legacy dict path: frame.settings contains SessionProperties fields, + # not our Settings fields, so we construct SessionProperties directly. + # The new typed path (frame.update) falls through to super, which calls + # _update_settings_from_typed → our override handles the rest. + if isinstance(frame, LLMUpdateSettingsFrame) and frame.update is None: + self._settings.session_properties = events.SessionProperties(**frame.settings) + await self._update_settings() + await self.push_frame(frame, direction) + return + await super().process_frame(frame, direction) if isinstance(frame, TranscriptionFrame): @@ -377,9 +400,6 @@ class OpenAIRealtimeBetaLLMService(LLMService): await self._handle_messages_append(frame) elif isinstance(frame, RealtimeMessagesUpdateFrame): self._context = frame.context - elif isinstance(frame, LLMUpdateSettingsFrame): - self._session_properties = events.SessionProperties(**frame.settings) - await self._update_settings() elif isinstance(frame, LLMSetToolsFrame): await self._update_settings() elif isinstance(frame, RealtimeFunctionCallResultFrame): @@ -456,8 +476,15 @@ class OpenAIRealtimeBetaLLMService(LLMService): # treat a send-side error as fatal. await self.push_error(error_msg=f"Error sending client event: {e}", exception=e) + async def _update_settings_from_typed(self, update): + """Apply a typed settings update, sending a session update if needed.""" + changed = await super()._update_settings_from_typed(update) + if "session_properties" in changed: + await self._update_settings() + return changed + async def _update_settings(self): - settings = self._session_properties + settings = self._settings.session_properties # tools given in the context override the tools in the session properties if self._context and self._context.tools: settings.tools = self._context.tools diff --git a/src/pipecat/services/perplexity/llm.py b/src/pipecat/services/perplexity/llm.py index 4ea23aa82..d2dd40a57 100644 --- a/src/pipecat/services/perplexity/llm.py +++ b/src/pipecat/services/perplexity/llm.py @@ -72,16 +72,16 @@ class PerplexityLLMService(OpenAILLMService): } # Add OpenAI-compatible parameters if they're set - if self._settings["frequency_penalty"] is not NOT_GIVEN: - params["frequency_penalty"] = self._settings["frequency_penalty"] - if self._settings["presence_penalty"] is not NOT_GIVEN: - params["presence_penalty"] = self._settings["presence_penalty"] - if self._settings["temperature"] is not NOT_GIVEN: - params["temperature"] = self._settings["temperature"] - if self._settings["top_p"] is not NOT_GIVEN: - params["top_p"] = self._settings["top_p"] - if self._settings["max_tokens"] is not NOT_GIVEN: - params["max_tokens"] = self._settings["max_tokens"] + if self._settings.frequency_penalty is not NOT_GIVEN: + params["frequency_penalty"] = self._settings.frequency_penalty + if self._settings.presence_penalty is not NOT_GIVEN: + params["presence_penalty"] = self._settings.presence_penalty + if self._settings.temperature is not NOT_GIVEN: + params["temperature"] = self._settings.temperature + if self._settings.top_p is not NOT_GIVEN: + params["top_p"] = self._settings.top_p + if self._settings.max_tokens is not NOT_GIVEN: + params["max_tokens"] = self._settings.max_tokens return params diff --git a/src/pipecat/services/playht/tts.py b/src/pipecat/services/playht/tts.py index 2d4cd0427..f79f54560 100644 --- a/src/pipecat/services/playht/tts.py +++ b/src/pipecat/services/playht/tts.py @@ -14,6 +14,7 @@ import io import json import struct import warnings +from dataclasses import dataclass, field from typing import AsyncGenerator, Optional import aiohttp @@ -32,6 +33,7 @@ from pipecat.frames.frames import ( TTSStoppedFrame, ) from pipecat.processors.frame_processor import FrameDirection +from pipecat.services.settings import NOT_GIVEN, TTSSettings, is_given from pipecat.services.tts_service import InterruptibleTTSService, TTSService from pipecat.transcriptions.language import Language, resolve_language from pipecat.utils.tracing.service_decorators import traced_tts @@ -97,6 +99,25 @@ def language_to_playht_language(language: Language) -> Optional[str]: return resolve_language(language, LANGUAGE_MAP, use_base_code=False) +@dataclass +class PlayHTTTSSettings(TTSSettings): + """Typed settings for PlayHT TTS services. + + Parameters: + output_format: Audio output format. + voice_engine: Voice engine to use. + speed: Speech speed multiplier. Defaults to 1.0. + seed: Random seed for voice consistency. + playht_sample_rate: Audio sample rate sent to the API. + """ + + output_format: str = field(default_factory=lambda: NOT_GIVEN) + voice_engine: str = field(default_factory=lambda: NOT_GIVEN) + speed: float = field(default_factory=lambda: NOT_GIVEN) + seed: int = field(default_factory=lambda: NOT_GIVEN) + playht_sample_rate: int = field(default_factory=lambda: NOT_GIVEN) + + class PlayHTTTSService(InterruptibleTTSService): """PlayHT WebSocket-based text-to-speech service. @@ -170,17 +191,19 @@ class PlayHTTTSService(InterruptibleTTSService): self._receive_task = None self._context_id = None - self._settings = { - "language": self.language_to_service_language(params.language) + self._settings: PlayHTTTSSettings = PlayHTTTSSettings( + model=voice_engine, + voice=voice_url, + language=self.language_to_service_language(params.language) if params.language else "english", - "output_format": output_format, - "voice_engine": voice_engine, - "speed": params.speed, - "seed": params.seed, - } + output_format=output_format, + voice_engine=voice_engine, + speed=params.speed, + seed=params.seed, + ) self.set_model_name(voice_engine) - self.set_voice(voice_url) + self._voice_id = voice_url def can_generate_metrics(self) -> bool: """Check if this service can generate processing metrics. @@ -304,13 +327,13 @@ class PlayHTTTSService(InterruptibleTTSService): # Handle the new response format with multiple URLs if "websocket_urls" in data: # Select URL based on voice_engine - if self._settings["voice_engine"] in data["websocket_urls"]: + if self._settings.voice_engine in data["websocket_urls"]: self._websocket_url = data["websocket_urls"][ - self._settings["voice_engine"] + self._settings.voice_engine ] else: raise ValueError( - f"Unsupported voice engine: {self._settings['voice_engine']}" + f"Unsupported voice engine: {self._settings.voice_engine}" ) else: raise ValueError("Invalid response: missing websocket_urls") @@ -382,12 +405,12 @@ class PlayHTTTSService(InterruptibleTTSService): tts_command = { "text": text, "voice": self._voice_id, - "voice_engine": self._settings["voice_engine"], - "output_format": self._settings["output_format"], + "voice_engine": self._settings.voice_engine, + "output_format": self._settings.output_format, "sample_rate": self.sample_rate, - "language": self._settings["language"], - "speed": self._settings["speed"], - "seed": self._settings["seed"], + "language": self._settings.language, + "speed": self._settings.speed, + "seed": self._settings.seed, "request_id": self._context_id, } @@ -499,17 +522,18 @@ class PlayHTHttpTTSService(TTSService): # Extract the base engine name voice_engine = voice_engine.replace("-ws", "") - self._settings = { - "language": self.language_to_service_language(params.language) + self._settings: PlayHTTTSSettings = PlayHTTTSSettings( + voice=voice_url, + language=self.language_to_service_language(params.language) if params.language else "english", - "output_format": output_format, - "voice_engine": voice_engine, - "speed": params.speed, - "seed": params.seed, - } + output_format=output_format, + voice_engine=voice_engine, + speed=params.speed, + seed=params.seed, + ) self.set_model_name(voice_engine) - self.set_voice(voice_url) + self._voice_id = voice_url async def start(self, frame: StartFrame): """Start the PlayHT HTTP TTS service. @@ -518,7 +542,7 @@ class PlayHTHttpTTSService(TTSService): frame: The start frame containing initialization parameters. """ await super().start(frame) - self._settings["sample_rate"] = self.sample_rate + self._settings.playht_sample_rate = self.sample_rate def can_generate_metrics(self) -> bool: """Check if this service can generate processing metrics. @@ -559,17 +583,17 @@ class PlayHTHttpTTSService(TTSService): payload = { "text": text, "voice": self._voice_id, - "voice_engine": self._settings["voice_engine"], - "output_format": self._settings["output_format"], + "voice_engine": self._settings.voice_engine, + "output_format": self._settings.output_format, "sample_rate": self.sample_rate, - "language": self._settings["language"], + "language": self._settings.language, } # Add optional parameters if they exist - if self._settings["speed"] is not None: - payload["speed"] = self._settings["speed"] - if self._settings["seed"] is not None: - payload["seed"] = self._settings["seed"] + if self._settings.speed is not None: + payload["speed"] = self._settings.speed + if self._settings.seed is not None: + payload["seed"] = self._settings.seed headers = { "Authorization": f"Bearer {self._api_key}", diff --git a/src/pipecat/services/resembleai/tts.py b/src/pipecat/services/resembleai/tts.py index 964b9fa18..08f9b81bd 100644 --- a/src/pipecat/services/resembleai/tts.py +++ b/src/pipecat/services/resembleai/tts.py @@ -8,6 +8,7 @@ import base64 import json +from dataclasses import dataclass, field from typing import AsyncGenerator, Optional from loguru import logger @@ -24,6 +25,7 @@ from pipecat.frames.frames import ( TTSStoppedFrame, ) from pipecat.processors.frame_processor import FrameDirection +from pipecat.services.settings import NOT_GIVEN, TTSSettings from pipecat.services.tts_service import AudioContextWordTTSService from pipecat.transcriptions.language import Language from pipecat.utils.text.base_text_aggregator import BaseTextAggregator @@ -38,6 +40,21 @@ except ModuleNotFoundError as e: raise Exception(f"Missing module: {e}") +@dataclass +class ResembleAITTSSettings(TTSSettings): + """Typed settings for Resemble AI TTS service. + + Parameters: + precision: PCM bit depth (PCM_32, PCM_24, PCM_16, or MULAW). + output_format: Audio format (wav or mp3). + resemble_sample_rate: Audio sample rate sent to the API. + """ + + precision: str = field(default_factory=lambda: NOT_GIVEN) + output_format: str = field(default_factory=lambda: NOT_GIVEN) + resemble_sample_rate: int = field(default_factory=lambda: NOT_GIVEN) + + class ResembleAITTSService(AudioContextWordTTSService): """Resemble AI TTS service with WebSocket streaming and word timestamps. @@ -76,11 +93,12 @@ class ResembleAITTSService(AudioContextWordTTSService): self._api_key = api_key self._voice_id = voice_id self._url = url - self._settings = { - "precision": precision, - "output_format": output_format, - "sample_rate": sample_rate, - } + self._settings: ResembleAITTSSettings = ResembleAITTSSettings( + voice=voice_id, + precision=precision, + output_format=output_format, + resemble_sample_rate=sample_rate, + ) self._websocket = None self._request_id_counter = 0 @@ -101,7 +119,7 @@ class ResembleAITTSService(AudioContextWordTTSService): self._jitter_buffer_bytes = 44100 # ~1000ms at 22050Hz to handle 400ms+ network gaps self._playback_started: dict[str, bool] = {} # Track if we've started playback per request - self.set_voice(voice_id) + self._voice_id = voice_id def can_generate_metrics(self) -> bool: """Check if this service can generate processing metrics. @@ -125,9 +143,9 @@ class ResembleAITTSService(AudioContextWordTTSService): "data": text, "binary_response": False, # Use JSON frames to get timestamps "request_id": self._request_id_counter, # ResembleAI only accepts number - "output_format": self._settings["output_format"], - "sample_rate": self._settings["sample_rate"], - "precision": self._settings["precision"], + "output_format": self._settings.output_format, + "sample_rate": self._settings.resemble_sample_rate, + "precision": self._settings.precision, "no_audio_header": True, } @@ -141,7 +159,7 @@ class ResembleAITTSService(AudioContextWordTTSService): frame: The start frame containing initialization parameters. """ await super().start(frame) - self._settings["sample_rate"] = self.sample_rate + self._settings.resemble_sample_rate = self.sample_rate await self._connect() async def stop(self, frame: EndFrame): diff --git a/src/pipecat/services/rime/tts.py b/src/pipecat/services/rime/tts.py index e38e840e6..5a3ed67a2 100644 --- a/src/pipecat/services/rime/tts.py +++ b/src/pipecat/services/rime/tts.py @@ -12,7 +12,8 @@ using Rime's API for streaming and batch audio synthesis. import base64 import json -from typing import Any, AsyncGenerator, Mapping, Optional +from dataclasses import dataclass, field +from typing import AsyncGenerator, Optional import aiohttp from loguru import logger @@ -30,6 +31,7 @@ from pipecat.frames.frames import ( TTSStoppedFrame, ) from pipecat.processors.frame_processor import FrameDirection +from pipecat.services.settings import NOT_GIVEN, TTSSettings, is_given from pipecat.services.tts_service import ( AudioContextWordTTSService, InterruptibleTTSService, @@ -68,6 +70,62 @@ def language_to_rime_language(language: Language) -> str: return resolve_language(language, LANGUAGE_MAP, use_base_code=False) +@dataclass +class RimeTTSSettings(TTSSettings): + """Typed settings for Rime WS JSON and HTTP TTS services. + + Parameters: + speaker: Voice speaker ID. + modelId: Rime model identifier. + audioFormat: Audio output format. + samplingRate: Audio sample rate. + lang: Rime language code. + speedAlpha: Speech speed multiplier. Defaults to 1.0. + reduceLatency: Whether to reduce latency at potential quality cost. + pauseBetweenBrackets: Whether to add pauses between bracketed content. + phonemizeBetweenBrackets: Whether to phonemize bracketed content. + inlineSpeedAlpha: Inline speed control markup. + """ + + speaker: str = field(default_factory=lambda: NOT_GIVEN) + modelId: str = field(default_factory=lambda: NOT_GIVEN) + audioFormat: str = field(default_factory=lambda: NOT_GIVEN) + samplingRate: int = field(default_factory=lambda: NOT_GIVEN) + lang: str = field(default_factory=lambda: NOT_GIVEN) + speedAlpha: float = field(default_factory=lambda: NOT_GIVEN) + reduceLatency: bool = field(default_factory=lambda: NOT_GIVEN) + pauseBetweenBrackets: bool = field(default_factory=lambda: NOT_GIVEN) + phonemizeBetweenBrackets: bool = field(default_factory=lambda: NOT_GIVEN) + inlineSpeedAlpha: str = field(default_factory=lambda: NOT_GIVEN) + + +@dataclass +class RimeNonJsonTTSSettings(TTSSettings): + """Typed settings for Rime non-JSON WS TTS service. + + Parameters: + speaker: Voice speaker ID. + modelId: Rime model identifier. + audioFormat: Audio output format. + samplingRate: Audio sample rate. + lang: Rime language code. + segment: Text segmentation mode ("immediate", "bySentence", "never"). + repetition_penalty: Token repetition penalty (1.0-2.0). + temperature: Sampling temperature (0.0-1.0). + top_p: Cumulative probability threshold (0.0-1.0). + """ + + speaker: str = field(default_factory=lambda: NOT_GIVEN) + modelId: str = field(default_factory=lambda: NOT_GIVEN) + audioFormat: str = field(default_factory=lambda: NOT_GIVEN) + samplingRate: int = field(default_factory=lambda: NOT_GIVEN) + lang: str = field(default_factory=lambda: NOT_GIVEN) + segment: str = field(default_factory=lambda: NOT_GIVEN) + repetition_penalty: float = field(default_factory=lambda: NOT_GIVEN) + temperature: float = field(default_factory=lambda: NOT_GIVEN) + top_p: float = field(default_factory=lambda: NOT_GIVEN) + + class RimeTTSService(AudioContextWordTTSService): """Text-to-Speech service using Rime's websocket API. @@ -149,19 +207,17 @@ class RimeTTSService(AudioContextWordTTSService): self._url = url self._voice_id = voice_id self._model = model - self._settings = { - "speaker": voice_id, - "modelId": model, - "audioFormat": "pcm", - "samplingRate": 0, - "lang": self.language_to_service_language(params.language) - if params.language - else "eng", - "speedAlpha": params.speed_alpha, - "reduceLatency": params.reduce_latency, - "pauseBetweenBrackets": json.dumps(params.pause_between_brackets), - "phonemizeBetweenBrackets": json.dumps(params.phonemize_between_brackets), - } + self._settings: RimeTTSSettings = RimeTTSSettings( + speaker=voice_id, + modelId=model, + audioFormat="pcm", + samplingRate=0, + lang=self.language_to_service_language(params.language) if params.language else "eng", + speedAlpha=params.speed_alpha, + reduceLatency=params.reduce_latency, + pauseBetweenBrackets=json.dumps(params.pause_between_brackets), + phonemizeBetweenBrackets=json.dumps(params.phonemize_between_brackets), + ) # State tracking self._context_id = None # Tracks current turn @@ -188,15 +244,6 @@ class RimeTTSService(AudioContextWordTTSService): """ return language_to_rime_language(language) - async def set_model(self, model: str): - """Update the TTS model. - - Args: - model: The model name to use for synthesis. - """ - self._model = model - await super().set_model(model) - # A set of Rime-specific helpers for text transformations def SPELL(text: str) -> str: """Wrap text in Rime spell function.""" @@ -222,15 +269,15 @@ class RimeTTSService(AudioContextWordTTSService): self._extra_msg_fields["inlineSpeedAlpha"] = ",".join(speed_vals + [str(speed)]) return f"[{text}]" - async def _update_settings(self, settings: Mapping[str, Any]): - """Update service settings and reconnect if voice changed.""" + async def _update_settings_from_typed(self, update: TTSSettings) -> set[str]: + """Apply a typed settings update and reconnect if voice changed.""" prev_voice = self._voice_id - await super()._update_settings(settings) - if not prev_voice == self._voice_id: - self._settings["speaker"] = self._voice_id - logger.info(f"Switching TTS voice to: [{self._voice_id}]") + changed = await super()._update_settings_from_typed(update) + if "voice" in changed: + self._settings.speaker = self._voice_id await self._disconnect() await self._connect() + return changed def _build_msg(self, text: str = "") -> dict: """Build JSON message for Rime API.""" @@ -255,7 +302,7 @@ class RimeTTSService(AudioContextWordTTSService): frame: The start frame containing initialization parameters. """ await super().start(frame) - self._settings["samplingRate"] = self.sample_rate + self._settings.samplingRate = self.sample_rate await self._connect() async def stop(self, frame: EndFrame): @@ -301,7 +348,20 @@ class RimeTTSService(AudioContextWordTTSService): if self._websocket and self._websocket.state is State.OPEN: return - params = "&".join(f"{k}={v}" for k, v in self._settings.items()) + params = "&".join( + f"{k}={v}" + for k, v in { + "speaker": self._settings.speaker, + "modelId": self._settings.modelId, + "audioFormat": self._settings.audioFormat, + "samplingRate": self._settings.samplingRate, + "lang": self._settings.lang, + "speedAlpha": self._settings.speedAlpha, + "reduceLatency": self._settings.reduceLatency, + "pauseBetweenBrackets": self._settings.pauseBetweenBrackets, + "phonemizeBetweenBrackets": self._settings.phonemizeBetweenBrackets, + }.items() + ) url = f"{self._url}?{params}" headers = {"Authorization": f"Bearer {self._api_key}"} self._websocket = await websocket_connect(url, additional_headers=headers) @@ -525,21 +585,17 @@ class RimeHttpTTSService(TTSService): self._api_key = api_key self._session = aiohttp_session self._base_url = "https://users.rime.ai/v1/rime-tts" - self._settings = { - "lang": self.language_to_service_language(params.language) - if params.language - else "eng", - "speedAlpha": params.speed_alpha, - "reduceLatency": params.reduce_latency, - "pauseBetweenBrackets": params.pause_between_brackets, - "phonemizeBetweenBrackets": params.phonemize_between_brackets, - } - self.set_voice(voice_id) + self._settings: RimeTTSSettings = RimeTTSSettings( + lang=self.language_to_service_language(params.language) if params.language else "eng", + speedAlpha=params.speed_alpha, + reduceLatency=params.reduce_latency, + pauseBetweenBrackets=params.pause_between_brackets, + phonemizeBetweenBrackets=params.phonemize_between_brackets, + inlineSpeedAlpha=params.inline_speed_alpha if params.inline_speed_alpha else NOT_GIVEN, + ) + self._voice_id = voice_id self.set_model_name(model) - if params.inline_speed_alpha: - self._settings["inlineSpeedAlpha"] = params.inline_speed_alpha - def can_generate_metrics(self) -> bool: """Check if this service can generate processing metrics. @@ -578,7 +634,15 @@ class RimeHttpTTSService(TTSService): "Content-Type": "application/json", } - payload = self._settings.copy() + payload = { + "lang": self._settings.lang, + "speedAlpha": self._settings.speedAlpha, + "reduceLatency": self._settings.reduceLatency, + "pauseBetweenBrackets": self._settings.pauseBetweenBrackets, + "phonemizeBetweenBrackets": self._settings.phonemizeBetweenBrackets, + } + if is_given(self._settings.inlineSpeedAlpha): + payload["inlineSpeedAlpha"] = self._settings.inlineSpeedAlpha payload["text"] = text payload["speaker"] = self._voice_id payload["modelId"] = self._model_name @@ -699,26 +763,24 @@ class RimeNonJsonTTSService(InterruptibleTTSService): self._url = url self._voice_id = voice_id self._model = model - self._settings = { - "speaker": voice_id, - "modelId": model, - "audioFormat": audio_format, - "samplingRate": sample_rate, - } - - if params.language: - self._settings["lang"] = self.language_to_service_language(params.language) - if params.segment is not None: - self._settings["segment"] = params.segment - if params.repetition_penalty is not None: - self._settings["repetition_penalty"] = params.repetition_penalty - if params.temperature is not None: - self._settings["temperature"] = params.temperature - if params.top_p is not None: - self._settings["top_p"] = params.top_p + self._settings: RimeNonJsonTTSSettings = RimeNonJsonTTSSettings( + speaker=voice_id, + modelId=model, + audioFormat=audio_format, + samplingRate=sample_rate, + lang=self.language_to_service_language(params.language) + if params.language + else NOT_GIVEN, + segment=params.segment if params.segment is not None else NOT_GIVEN, + repetition_penalty=params.repetition_penalty + if params.repetition_penalty is not None + else NOT_GIVEN, + temperature=params.temperature if params.temperature is not None else NOT_GIVEN, + top_p=params.top_p if params.top_p is not None else NOT_GIVEN, + ) # Add any extra parameters for future compatibility if params.extra: - self._settings.update(params.extra) + self._settings.extra.update(params.extra) self._receive_task = None self._context_id: Optional[str] = None @@ -750,7 +812,7 @@ class RimeNonJsonTTSService(InterruptibleTTSService): frame: The start frame containing initialization parameters. """ await super().start(frame) - self._settings["samplingRate"] = self.sample_rate + self._settings.samplingRate = self.sample_rate await self._connect() async def stop(self, frame: EndFrame): @@ -794,8 +856,26 @@ class RimeNonJsonTTSService(InterruptibleTTSService): try: if self._websocket and self._websocket.state is State.OPEN: return - # Build URL with query parameters (only non-None values) - params = "&".join(f"{k}={v}" for k, v in self._settings.items() if v is not None) + # Build URL with query parameters (only given, non-None values) + settings_dict = { + "speaker": self._settings.speaker, + "modelId": self._settings.modelId, + "audioFormat": self._settings.audioFormat, + "samplingRate": self._settings.samplingRate, + } + if is_given(self._settings.lang): + settings_dict["lang"] = self._settings.lang + if is_given(self._settings.segment): + settings_dict["segment"] = self._settings.segment + if is_given(self._settings.repetition_penalty): + settings_dict["repetition_penalty"] = self._settings.repetition_penalty + if is_given(self._settings.temperature): + settings_dict["temperature"] = self._settings.temperature + if is_given(self._settings.top_p): + settings_dict["top_p"] = self._settings.top_p + # Include extras + settings_dict.update(self._settings.extra) + params = "&".join(f"{k}={v}" for k, v in settings_dict.items() if v is not None) url = f"{self._url}?{params}" headers = {"Authorization": f"Bearer {self._api_key}"} self._websocket = await websocket_connect( @@ -889,68 +969,23 @@ class RimeNonJsonTTSService(InterruptibleTTSService): except Exception as e: yield ErrorFrame(error=f"Unknown error occurred: {e}") - async def _update_settings(self, settings: Mapping[str, Any]): - """Update service settings and reconnect if necessary. + async def _update_settings_from_typed(self, update: TTSSettings) -> set[str]: + """Apply a typed settings update and reconnect if necessary. Since all settings are WebSocket URL query parameters, any setting change requires reconnecting to apply the new values. """ - needs_reconnect = False + changed = await super()._update_settings_from_typed(update) - # Track previous values from self._settings only - prev_settings = self._settings.copy() + # Sync voice and model to settings dict fields + if "voice" in changed: + self._settings.speaker = self._voice_id + if "model" in changed: + self._settings.modelId = self._model_name - # Let parent class handle standard settings (voice, model, language) - await super()._update_settings(settings) - - # Check if voice changed and update settings dict - if "voice" in settings or "voice_id" in settings: - self._settings["speaker"] = self._voice_id - if prev_settings.get("speaker") != self._voice_id: - logger.info(f"Switching TTS voice to: [{self._voice_id}]") - needs_reconnect = True - - # Check if model changed and update settings dict - if "model" in settings: - self._settings["modelId"] = self._model - if prev_settings.get("modelId") != self._model: - logger.info(f"Switching TTS model to: [{self._model}]") - needs_reconnect = True - - # Handle language explicitly - if "language" in settings: - new_lang = self.language_to_service_language(settings["language"]) - if new_lang and new_lang != prev_settings.get("lang"): - logger.info(f"Updating language to: [{new_lang}]") - self._settings["lang"] = new_lang - needs_reconnect = True - - # Check other parameters - for key in ["segment", "repetition_penalty", "temperature", "top_p"]: - if key in settings and settings[key] != prev_settings.get(key): - logger.info(f"Updating {key} to: [{settings[key]}]") - self._settings[key] = settings[key] - needs_reconnect = True - - # Handle extra parameters - for key, value in settings.items(): - if key not in [ - "voice", - "voice_id", - "model", - "language", - "segment", - "repetition_penalty", - "temperature", - "top_p", - ]: - if value != prev_settings.get(key): - logger.info(f"Updating extra parameter {key} to: [{value}]") - self._settings[key] = value - needs_reconnect = True - - # Reconnect if any setting changed - if needs_reconnect: + if changed: logger.debug("Settings changed, reconnecting WebSocket with new parameters") await self._disconnect() await self._connect() + + return changed diff --git a/src/pipecat/services/sambanova/llm.py b/src/pipecat/services/sambanova/llm.py index 047ce0e6c..99c7bca2c 100644 --- a/src/pipecat/services/sambanova/llm.py +++ b/src/pipecat/services/sambanova/llm.py @@ -87,16 +87,16 @@ class SambaNovaLLMService(OpenAILLMService): # type: ignore "model": self.model_name, "stream": True, "stream_options": {"include_usage": True}, - "temperature": self._settings["temperature"], - "top_p": self._settings["top_p"], - "max_tokens": self._settings["max_tokens"], - "max_completion_tokens": self._settings["max_completion_tokens"], + "temperature": self._settings.temperature, + "top_p": self._settings.top_p, + "max_tokens": self._settings.max_tokens, + "max_completion_tokens": self._settings.max_completion_tokens, } # Messages, tools, tool_choice params.update(params_from_context) - params.update(self._settings["extra"]) + params.update(self._settings.extra) return params @traced_llm # type: ignore diff --git a/src/pipecat/services/sarvam/stt.py b/src/pipecat/services/sarvam/stt.py index 998597956..e2bc6a08f 100644 --- a/src/pipecat/services/sarvam/stt.py +++ b/src/pipecat/services/sarvam/stt.py @@ -12,7 +12,7 @@ can handle multiple audio formats for Indian language speech recognition. """ import base64 -from dataclasses import dataclass +from dataclasses import dataclass, field from typing import AsyncGenerator, Dict, Literal, Optional from loguru import logger @@ -32,6 +32,7 @@ from pipecat.frames.frames import ( ) from pipecat.processors.frame_processor import FrameDirection from pipecat.services.sarvam._sdk import sdk_headers +from pipecat.services.settings import NOT_GIVEN, STTSettings, is_given from pipecat.services.stt_latency import SARVAM_TTFS_P99 from pipecat.services.stt_service import STTService from pipecat.transcriptions.language import Language, resolve_language @@ -130,6 +131,23 @@ MODEL_CONFIGS: Dict[str, ModelConfig] = { } +@dataclass +class SarvamSTTSettings(STTSettings): + """Typed settings for the Sarvam STT service. + + Parameters: + prompt: Optional prompt to guide transcription/translation style. + mode: Mode of operation (transcribe, translate, verbatim, etc.). + vad_signals: Enable VAD signals in response. + high_vad_sensitivity: Enable high VAD sensitivity. + """ + + prompt: Optional[str] = field(default_factory=lambda: NOT_GIVEN) + mode: Optional[str] = field(default_factory=lambda: NOT_GIVEN) + vad_signals: Optional[bool] = field(default_factory=lambda: NOT_GIVEN) + high_vad_sensitivity: Optional[bool] = field(default_factory=lambda: NOT_GIVEN) + + class SarvamSTTService(STTService): """Sarvam speech-to-text service. @@ -207,22 +225,8 @@ class SarvamSTTService(STTService): self.set_model_name(model) self._api_key = api_key - self._language_code: Optional[Language] = params.language - - # Set language string: use provided language or model's default - if params.language: - self._language_string = language_to_sarvam_language(params.language) - else: - self._language_string = self._config.default_language - - self._prompt = params.prompt - - # Set mode: use provided mode or model's default - self._mode = params.mode if params.mode is not None else self._config.default_mode # Store connection parameters - self._vad_signals = params.vad_signals - self._high_vad_sensitivity = params.high_vad_sensitivity self._input_audio_codec = input_audio_codec # Initialize Sarvam SDK client @@ -240,7 +244,19 @@ class SarvamSTTService(STTService): self._socket_client = None self._receive_task = None - if self._vad_signals: + # Resolve mode default from model config + mode = params.mode if params.mode is not None else self._config.default_mode + + self._settings: SarvamSTTSettings = SarvamSTTSettings( + model=model, + language=params.language, + prompt=params.prompt if params.prompt is not None else NOT_GIVEN, + mode=mode if mode is not None else NOT_GIVEN, + vad_signals=params.vad_signals, + high_vad_sensitivity=params.high_vad_sensitivity, + ) + + if params.vad_signals: self._register_event_handler("on_speech_started") self._register_event_handler("on_speech_stopped") self._register_event_handler("on_utterance_end") @@ -258,6 +274,12 @@ class SarvamSTTService(STTService): """ return language_to_sarvam_language(language) + def _get_language_string(self) -> Optional[str]: + """Resolve the current language setting to a Sarvam language code string.""" + if self._settings.language: + return language_to_sarvam_language(self._settings.language) + return self._config.default_language + def can_generate_metrics(self) -> bool: """Check if this service can generate processing metrics. @@ -275,42 +297,74 @@ class SarvamSTTService(STTService): await super().process_frame(frame, direction) # Only handle VAD frames when not using Sarvam's VAD signals - if not self._vad_signals: + if not self._settings.vad_signals: if isinstance(frame, VADUserStartedSpeakingFrame): await self._start_metrics() elif isinstance(frame, VADUserStoppedSpeakingFrame): if self._socket_client: await self._socket_client.flush() - async def set_language(self, language: Language): - """Set the recognition language and reconnect. + async def _update_settings_from_typed(self, update: STTSettings) -> set[str]: + """Apply a typed settings update, validate, sync state, and reconnect. Args: - language: The language to use for speech recognition. + update: A :class:`STTSettings` (or ``SarvamSTTSettings``) delta. + + Returns: + Set of field names whose values actually changed. Raises: - ValueError: If called on a model that auto-detects language. + ValueError: If a setting is not supported by the current model. """ - if not self._config.supports_language: - raise ValueError( - f"Model '{self.model_name}' does not support language parameter " - "(auto-detects language)." - ) + # Validate against model capabilities before applying + if is_given(update.language) and update.language is not None: + if not self._config.supports_language: + raise ValueError( + f"Model '{self.model_name}' does not support language parameter " + "(auto-detects language)." + ) + + if isinstance(update, SarvamSTTSettings): + if is_given(update.prompt) and update.prompt is not None: + if not self._config.supports_prompt: + raise ValueError( + f"Model '{self.model_name}' does not support prompt parameter." + ) + if is_given(update.mode) and update.mode is not None: + if not self._config.supports_mode: + raise ValueError(f"Model '{self.model_name}' does not support mode parameter.") + + changed = await super()._update_settings_from_typed(update) + + if not changed: + return changed - logger.info(f"Switching STT language to: [{language}]") - self._language_code = language - self._language_string = language_to_sarvam_language(language) await self._disconnect() await self._connect() + return changed async def set_prompt(self, prompt: Optional[str]): """Set the transcription/translation prompt and reconnect. + .. deprecated:: + Use ``STTUpdateSettingsFrame(SarvamSTTSettings(prompt=...))`` instead. + Args: prompt: Prompt text to guide transcription/translation style/context. Pass None to clear/disable prompt. Only applicable to models that support prompts. """ + import warnings + + with warnings.catch_warnings(): + warnings.simplefilter("always") + warnings.warn( + f"{self.__class__.__name__}.set_prompt() is deprecated. " + "Use STTUpdateSettingsFrame(SarvamSTTSettings(prompt=...)) instead.", + DeprecationWarning, + stacklevel=2, + ) + if not self._config.supports_prompt: if prompt is not None: raise ValueError(f"Model '{self.model_name}' does not support prompt parameter.") @@ -318,7 +372,7 @@ class SarvamSTTService(STTService): return logger.info(f"Updating {self.model_name} prompt.") - self._prompt = prompt + self._settings.prompt = prompt await self._disconnect() await self._connect() @@ -405,24 +459,25 @@ class SarvamSTTService(STTService): # Enable flush signal when using Pipecat's VAD (not Sarvam's) so that # the flush() call on user-stopped-speaking is honored by the server. - if not self._vad_signals: + if not self._settings.vad_signals: connect_kwargs["flush_signal"] = "true" # Only send vad parameters when explicitly set (avoid overriding server defaults) - if self._vad_signals is not None: - connect_kwargs["vad_signals"] = "true" if self._vad_signals else "false" - if self._high_vad_sensitivity is not None: + if self._settings.vad_signals is not None: + connect_kwargs["vad_signals"] = "true" if self._settings.vad_signals else "false" + if self._settings.high_vad_sensitivity is not None: connect_kwargs["high_vad_sensitivity"] = ( - "true" if self._high_vad_sensitivity else "false" + "true" if self._settings.high_vad_sensitivity else "false" ) # Add language_code for models that support it - if self._language_string is not None: - connect_kwargs["language_code"] = self._language_string + language_string = self._get_language_string() + if language_string is not None: + connect_kwargs["language_code"] = language_string # Add mode for models that support it - if self._config.supports_mode and self._mode is not None: - connect_kwargs["mode"] = self._mode + if self._config.supports_mode and is_given(self._settings.mode): + connect_kwargs["mode"] = self._settings.mode def _connect_with_sdk_headers(connect_fn, **kwargs): # Different SDK versions may use different kwarg names. @@ -449,8 +504,8 @@ class SarvamSTTService(STTService): self._socket_client = await self._websocket_context.__aenter__() # Set prompt if provided (only for models that support prompts) - if self._prompt is not None and self._config.supports_prompt: - await self._socket_client.set_prompt(self._prompt) + if is_given(self._settings.prompt) and self._config.supports_prompt: + await self._socket_client.set_prompt(self._settings.prompt) # Register event handler for incoming messages def _message_handler(message): @@ -544,10 +599,12 @@ class SarvamSTTService(STTService): # Prefer language from message (auto-detected for translate models). Fallback to configured. if language_code: language = self._map_language_code_to_enum(language_code) - elif self._language_string: - language = self._map_language_code_to_enum(self._language_string) else: - language = Language.HI_IN + language_string = self._get_language_string() + if language_string: + language = self._map_language_code_to_enum(language_string) + else: + language = Language.HI_IN # Emit utterance end event await self._call_event_handler("on_utterance_end") diff --git a/src/pipecat/services/sarvam/tts.py b/src/pipecat/services/sarvam/tts.py index 753293c75..e28914b4c 100644 --- a/src/pipecat/services/sarvam/tts.py +++ b/src/pipecat/services/sarvam/tts.py @@ -40,9 +40,9 @@ See https://docs.sarvam.ai/api-reference-docs/text-to-speech/stream for full API import asyncio import base64 import json -from dataclasses import dataclass +from dataclasses import dataclass, field from enum import Enum -from typing import Any, AsyncGenerator, Dict, List, Mapping, Optional, Tuple +from typing import AsyncGenerator, Dict, List, Optional, Tuple import aiohttp from loguru import logger @@ -62,6 +62,7 @@ from pipecat.frames.frames import ( ) from pipecat.processors.frame_processor import FrameDirection from pipecat.services.sarvam._sdk import sdk_headers +from pipecat.services.settings import NOT_GIVEN, TTSSettings, is_given from pipecat.services.tts_service import InterruptibleTTSService, TTSService from pipecat.transcriptions.language import Language, resolve_language from pipecat.utils.tracing.service_decorators import traced_tts @@ -244,6 +245,80 @@ def language_to_sarvam_language(language: Language) -> Optional[str]: return resolve_language(language, LANGUAGE_MAP, use_base_code=False) +@dataclass +class SarvamHttpTTSSettings(TTSSettings): + """Typed settings for Sarvam HTTP TTS service. + + Parameters: + language: Sarvam language code. + enable_preprocessing: Whether to enable text preprocessing. Defaults to False. + **Note:** Always enabled for bulbul:v3-beta (cannot be disabled). + pace: Speech pace multiplier. Defaults to 1.0. + - bulbul:v2: Range 0.3 to 3.0 + - bulbul:v3-beta: Range 0.5 to 2.0 + pitch: Voice pitch adjustment (-0.75 to 0.75). Defaults to 0.0. + **Note:** Only supported for bulbul:v2. Ignored for v3 models. + loudness: Volume multiplier (0.3 to 3.0). Defaults to 1.0. + **Note:** Only supported for bulbul:v2. Ignored for v3 models. + temperature: Controls output randomness for bulbul:v3-beta (0.01 to 1.0). + Lower values = more deterministic, higher = more random. Defaults to 0.6. + **Note:** Only supported for bulbul:v3-beta. Ignored for v2. + sample_rate: Audio sample rate. + """ + + language: str = field(default_factory=lambda: NOT_GIVEN) + enable_preprocessing: bool = field(default_factory=lambda: NOT_GIVEN) + pace: float = field(default_factory=lambda: NOT_GIVEN) + pitch: float = field(default_factory=lambda: NOT_GIVEN) + loudness: float = field(default_factory=lambda: NOT_GIVEN) + temperature: float = field(default_factory=lambda: NOT_GIVEN) + sarvam_sample_rate: int = field(default_factory=lambda: NOT_GIVEN) + + +@dataclass +class SarvamWSTTSSettings(TTSSettings): + """Typed settings for Sarvam WebSocket TTS service. + + Parameters: + target_language_code: Sarvam language code. + speaker: Voice speaker ID. + speech_sample_rate: Audio sample rate as string. + enable_preprocessing: Enable text preprocessing. Defaults to False. + **Note:** Always enabled for bulbul:v3-beta. + min_buffer_size: Minimum characters to buffer before generating audio. + Lower values reduce latency but may affect quality. Defaults to 50. + max_chunk_length: Maximum characters processed in a single chunk. + Controls memory usage and processing efficiency. Defaults to 150. + output_audio_codec: Audio codec format. Options: linear16, mulaw, alaw, + opus, flac, aac, wav, mp3. Defaults to "linear16". + output_audio_bitrate: Audio bitrate (32k, 64k, 96k, 128k, 192k). + Defaults to "128k". + pace: Speech pace multiplier. Defaults to 1.0. + - bulbul:v2: Range 0.3 to 3.0 + - bulbul:v3-beta: Range 0.5 to 2.0 + pitch: Voice pitch adjustment (-0.75 to 0.75). Defaults to 0.0. + **Note:** Only supported for bulbul:v2. Ignored for v3 models. + loudness: Volume multiplier (0.3 to 3.0). Defaults to 1.0. + **Note:** Only supported for bulbul:v2. Ignored for v3 models. + temperature: Controls output randomness for bulbul:v3-beta (0.01 to 1.0). + Lower = more deterministic, higher = more random. Defaults to 0.6. + **Note:** Only supported for bulbul:v3-beta. Ignored for v2. + """ + + target_language_code: str = field(default_factory=lambda: NOT_GIVEN) + speaker: str = field(default_factory=lambda: NOT_GIVEN) + speech_sample_rate: str = field(default_factory=lambda: NOT_GIVEN) + enable_preprocessing: bool = field(default_factory=lambda: NOT_GIVEN) + min_buffer_size: int = field(default_factory=lambda: NOT_GIVEN) + max_chunk_length: int = field(default_factory=lambda: NOT_GIVEN) + output_audio_codec: str = field(default_factory=lambda: NOT_GIVEN) + output_audio_bitrate: str = field(default_factory=lambda: NOT_GIVEN) + pace: float = field(default_factory=lambda: NOT_GIVEN) + pitch: float = field(default_factory=lambda: NOT_GIVEN) + loudness: float = field(default_factory=lambda: NOT_GIVEN) + temperature: float = field(default_factory=lambda: NOT_GIVEN) + + class SarvamHttpTTSService(TTSService): """Text-to-Speech service using Sarvam AI's API. @@ -403,35 +478,35 @@ class SarvamHttpTTSService(TTSService): pace = max(pace_min, min(pace_max, pace)) # Build base settings - self._settings = { - "language": ( + self._settings: SarvamHttpTTSSettings = SarvamHttpTTSSettings( + language=( self.language_to_service_language(params.language) if params.language else "en-IN" ), - "enable_preprocessing": ( + enable_preprocessing=( True if self._config.preprocessing_always_enabled else params.enable_preprocessing ), - "pace": pace, - "model": model, - } + pace=pace, + model=model, + ) # Add parameters based on model support if self._config.supports_pitch: - self._settings["pitch"] = params.pitch + self._settings.pitch = params.pitch elif params.pitch != 0.0: logger.warning(f"pitch parameter is ignored for {model}") if self._config.supports_loudness: - self._settings["loudness"] = params.loudness + self._settings.loudness = params.loudness elif params.loudness != 1.0: logger.warning(f"loudness parameter is ignored for {model}") if self._config.supports_temperature: - self._settings["temperature"] = params.temperature + self._settings.temperature = params.temperature elif params.temperature != 0.6: logger.warning(f"temperature parameter is ignored for {model}") self.set_model_name(model) - self.set_voice(voice_id) + self._voice_id = voice_id def can_generate_metrics(self) -> bool: """Check if this service can generate processing metrics. @@ -459,7 +534,7 @@ class SarvamHttpTTSService(TTSService): frame: The start frame containing initialization parameters. """ await super().start(frame) - self._settings["sample_rate"] = self.sample_rate + self._settings.sarvam_sample_rate = self.sample_rate @traced_tts async def run_tts(self, text: str, context_id: str) -> AsyncGenerator[Frame, None]: @@ -480,21 +555,25 @@ class SarvamHttpTTSService(TTSService): # Build payload with common parameters payload = { "text": text, - "target_language_code": self._settings["language"], + "target_language_code": self._settings.language, "speaker": self._voice_id, "sample_rate": self.sample_rate, - "enable_preprocessing": self._settings["enable_preprocessing"], + "enable_preprocessing": self._settings.enable_preprocessing, "model": self._model_name, - "pace": self._settings.get("pace", 1.0), + "pace": self._settings.pace if is_given(self._settings.pace) else 1.0, } # Add model-specific parameters based on config if self._config.supports_pitch: - payload["pitch"] = self._settings.get("pitch", 0.0) + payload["pitch"] = self._settings.pitch if is_given(self._settings.pitch) else 0.0 if self._config.supports_loudness: - payload["loudness"] = self._settings.get("loudness", 1.0) + payload["loudness"] = ( + self._settings.loudness if is_given(self._settings.loudness) else 1.0 + ) if self._config.supports_temperature: - payload["temperature"] = self._settings.get("temperature", 0.6) + payload["temperature"] = ( + self._settings.temperature if is_given(self._settings.temperature) else 0.6 + ) headers = { "api-subscription-key": self._api_key, @@ -748,7 +827,7 @@ class SarvamTTSService(InterruptibleTTSService): self._websocket_url = f"{url}?model={model}" self._api_key = api_key self.set_model_name(model) - self.set_voice(voice_id) + self._voice_id = voice_id # Validate and clamp pace to model's valid range pace = params.pace @@ -758,36 +837,36 @@ class SarvamTTSService(InterruptibleTTSService): pace = max(pace_min, min(pace_max, pace)) # Build base settings - self._settings = { - "target_language_code": ( + self._settings: SarvamWSTTSSettings = SarvamWSTTSSettings( + target_language_code=( self.language_to_service_language(params.language) if params.language else "en-IN" ), - "speaker": voice_id, - "speech_sample_rate": str(sample_rate), - "enable_preprocessing": ( + speaker=voice_id, + speech_sample_rate=str(sample_rate), + enable_preprocessing=( True if self._config.preprocessing_always_enabled else params.enable_preprocessing ), - "min_buffer_size": params.min_buffer_size, - "max_chunk_length": params.max_chunk_length, - "output_audio_codec": params.output_audio_codec, - "output_audio_bitrate": params.output_audio_bitrate, - "pace": pace, - "model": model, - } + min_buffer_size=params.min_buffer_size, + max_chunk_length=params.max_chunk_length, + output_audio_codec=params.output_audio_codec, + output_audio_bitrate=params.output_audio_bitrate, + pace=pace, + model=model, + ) # Add parameters based on model support if self._config.supports_pitch: - self._settings["pitch"] = params.pitch + self._settings.pitch = params.pitch elif params.pitch != 0.0: logger.warning(f"pitch parameter is ignored for {model}") if self._config.supports_loudness: - self._settings["loudness"] = params.loudness + self._settings.loudness = params.loudness elif params.loudness != 1.0: logger.warning(f"loudness parameter is ignored for {model}") if self._config.supports_temperature: - self._settings["temperature"] = params.temperature + self._settings.temperature = params.temperature elif params.temperature != 0.6: logger.warning(f"temperature parameter is ignored for {model}") @@ -823,7 +902,7 @@ class SarvamTTSService(InterruptibleTTSService): await super().start(frame) # WebSocket API expects sample rate as string - self._settings["speech_sample_rate"] = str(self.sample_rate) + self._settings.speech_sample_rate = str(self.sample_rate) await self._connect() async def stop(self, frame: EndFrame): @@ -870,13 +949,12 @@ class SarvamTTSService(InterruptibleTTSService): if isinstance(frame, (LLMFullResponseEndFrame, EndFrame)): await self.flush_audio() - async def _update_settings(self, settings: Mapping[str, Any]): - """Update service settings and reconnect if voice changed.""" - prev_voice = self._voice_id - await super()._update_settings(settings) - if not prev_voice == self._voice_id: - logger.info(f"Switching TTS voice to: [{self._voice_id}]") + async def _update_settings_from_typed(self, update: TTSSettings) -> set[str]: + """Apply a typed settings update and resend config if voice changed.""" + changed = await super()._update_settings_from_typed(update) + if "voice" in changed: await self._send_config() + return changed async def _connect(self): """Connect to Sarvam WebSocket and start background tasks.""" @@ -934,9 +1012,28 @@ class SarvamTTSService(InterruptibleTTSService): """Send initial configuration message.""" if not self._websocket: raise Exception("WebSocket not connected") - self._settings["speaker"] = self._voice_id - logger.debug(f"Config being sent is {self._settings}") - config_message = {"type": "config", "data": self._settings} + self._settings.speaker = self._voice_id + # Build config dict for the API + config_data = { + "target_language_code": self._settings.target_language_code, + "speaker": self._settings.speaker, + "speech_sample_rate": self._settings.speech_sample_rate, + "enable_preprocessing": self._settings.enable_preprocessing, + "min_buffer_size": self._settings.min_buffer_size, + "max_chunk_length": self._settings.max_chunk_length, + "output_audio_codec": self._settings.output_audio_codec, + "output_audio_bitrate": self._settings.output_audio_bitrate, + "pace": self._settings.pace, + "model": self._settings.model, + } + if is_given(self._settings.pitch): + config_data["pitch"] = self._settings.pitch + if is_given(self._settings.loudness): + config_data["loudness"] = self._settings.loudness + if is_given(self._settings.temperature): + config_data["temperature"] = self._settings.temperature + logger.debug(f"Config being sent is {config_data}") + config_message = {"type": "config", "data": config_data} try: await self._websocket.send(json.dumps(config_message)) diff --git a/src/pipecat/services/settings.py b/src/pipecat/services/settings.py new file mode 100644 index 000000000..fbec5cdf8 --- /dev/null +++ b/src/pipecat/services/settings.py @@ -0,0 +1,297 @@ +# +# Copyright (c) 2024-2026, Daily +# +# SPDX-License-Identifier: BSD 2-Clause License +# + +"""Typed settings infrastructure for Pipecat AI services. + +This module provides typed dataclass-based settings objects that replace the +stringly-typed ``Mapping[str, Any]`` dictionaries previously used for service +configuration. Each service type has a corresponding settings class (e.g. +``TTSSettings``, ``LLMSettings``) whose fields use the ``NOT_GIVEN`` sentinel +to distinguish "leave unchanged" from an explicit ``None``. + +Key concepts: + +- **NOT_GIVEN sentinel**: A value meaning "this field was not provided in the + update". Distinct from ``None`` (which may be a valid value for a setting). +- **Settings as both state and delta**: The same class is used for the + service's current settings *and* for update objects. Fields set to + ``NOT_GIVEN`` are simply skipped when applying an update. +- **apply_update**: Applies a delta onto a target settings object and returns + the set of field names that actually changed. +- **from_mapping**: Constructs a typed settings object from a plain dict, + supporting field aliases (e.g. ``"voice_id"`` → ``"voice"``). +- **Extras**: Unknown keys land in the ``extra`` dict so services that have + non-standard settings don't lose data. +""" + +from __future__ import annotations + +import copy +from dataclasses import dataclass, field, fields +from typing import Any, ClassVar, Dict, Mapping, Optional, Set, Type, TypeVar + +from loguru import logger + +# --------------------------------------------------------------------------- +# NOT_GIVEN sentinel +# --------------------------------------------------------------------------- + + +class _NotGiven: + """Sentinel indicating a settings field was not provided. + + ``NOT_GIVEN`` means "the caller did not supply this value" — distinct from + ``None``, which may be a legitimate setting value. It is used as the + default for every settings field so that ``apply_update`` can tell which + fields the caller actually wants to change. + """ + + _instance: Optional[_NotGiven] = None + + def __new__(cls) -> _NotGiven: + if cls._instance is None: + cls._instance = super().__new__(cls) + return cls._instance + + def __repr__(self) -> str: + return "NOT_GIVEN" + + def __bool__(self) -> bool: + return False + + +NOT_GIVEN: _NotGiven = _NotGiven() +"""Singleton sentinel meaning "this field was not included in the update".""" + + +def is_given(value: Any) -> bool: + """Check whether a value was explicitly provided (i.e. is not ``NOT_GIVEN``). + + Args: + value: The value to check. + + Returns: + ``True`` if *value* is anything other than ``NOT_GIVEN``. + """ + return not isinstance(value, _NotGiven) + + +# --------------------------------------------------------------------------- +# Base ServiceSettings +# --------------------------------------------------------------------------- + +_S = TypeVar("_S", bound="ServiceSettings") + + +@dataclass +class ServiceSettings: + """Base class for typed service settings. + + Every AI service type (LLM, TTS, STT) extends this with its own fields. + Fields default to ``NOT_GIVEN`` so that an instance can represent either + the full current state **or** a sparse update delta. + + Parameters: + model: The model identifier used by the service. + extra: Overflow dict for service-specific keys that don't map to a + declared field. + """ + + # -- common fields ------------------------------------------------------- + + model: Any = field(default_factory=lambda: NOT_GIVEN) + """AI model identifier (e.g. ``"gpt-4o"``, ``"eleven_turbo_v2_5"``).""" + + extra: Dict[str, Any] = field(default_factory=dict) + """Catch-all for service-specific keys that have no declared field.""" + + # -- class-level configuration ------------------------------------------- + + _aliases: ClassVar[Dict[str, str]] = {} + """Map of alternative key names to canonical field names. + + For example ``{"voice_id": "voice"}`` lets callers use either spelling. + Subclasses should override this as needed. + """ + + # -- public API ---------------------------------------------------------- + + def given_fields(self) -> Dict[str, Any]: + """Return a dict of only the fields that were explicitly provided. + + Skips ``NOT_GIVEN`` values and the ``extra`` field itself. Entries + from ``extra`` are included at the top level. + + Returns: + Dictionary mapping field names to their provided values. + """ + result: Dict[str, Any] = {} + for f in fields(self): + if f.name == "extra": + continue + val = getattr(self, f.name) + if is_given(val): + result[f.name] = val + result.update(self.extra) + return result + + def apply_update(self: _S, update: _S) -> Set[str]: + """Apply *update* onto this settings object, returning changed field names. + + Only fields in *update* that are **given** (i.e. not ``NOT_GIVEN``) + are considered. A field is "changed" if its new value differs from + the current value. + + The ``extra`` dicts are merged: keys present in the update overwrite + keys in the target. + + Args: + update: A settings object of the same type containing the delta. + + Returns: + The set of field names whose values actually changed. + + Examples:: + + current = TTSSettings(voice="alice", language="en") + delta = TTSSettings(voice="bob") + changed = current.apply_update(delta) + # changed == {"voice"} + # current.voice == "bob", current.language == "en" + """ + changed: Set[str] = set() + for f in fields(self): + if f.name == "extra": + continue + new_val = getattr(update, f.name) + if not is_given(new_val): + continue + old_val = getattr(self, f.name) + if old_val != new_val: + setattr(self, f.name, new_val) + changed.add(f.name) + + # Merge extra + for key, new_val in update.extra.items(): + old_val = self.extra.get(key, NOT_GIVEN) + if old_val != new_val: + self.extra[key] = new_val + changed.add(key) + + return changed + + @classmethod + def from_mapping(cls: Type[_S], settings: Mapping[str, Any]) -> _S: + """Construct a typed settings object from a plain dictionary. + + Keys are matched to dataclass fields by name. Keys listed in + ``_aliases`` are translated to their canonical name first. Any + remaining unrecognized keys are placed into ``extra``. + + Args: + settings: A dictionary of setting names to values. + + Returns: + A new settings instance with the corresponding fields populated. + + Examples:: + + update = TTSSettings.from_mapping({"voice_id": "alice", "speed": 1.2}) + # update.voice == "alice" (via alias) + # update.extra == {"speed": 1.2} + """ + field_names = {f.name for f in fields(cls)} - {"extra"} + kwargs: Dict[str, Any] = {} + extra: Dict[str, Any] = {} + + for key, value in settings.items(): + # Resolve aliases first + canonical = cls._aliases.get(key, key) + if canonical in field_names: + kwargs[canonical] = value + else: + extra[key] = value + + instance = cls(**kwargs) + instance.extra = extra + return instance + + def to_dict(self) -> Dict[str, Any]: + """Serialize to a flat dictionary, including extra. + + Only given (non-``NOT_GIVEN``) values are included. This is the + inverse of ``from_mapping`` and useful for passing settings to APIs + that expect plain dicts. + + Returns: + A flat dictionary of all given settings. + """ + return self.given_fields() + + def copy(self: _S) -> _S: + """Return a deep copy of this settings instance. + + Returns: + A new settings object with the same field values. + """ + return copy.deepcopy(self) + + +# --------------------------------------------------------------------------- +# Service-specific settings +# --------------------------------------------------------------------------- + + +@dataclass +class LLMSettings(ServiceSettings): + """Typed settings for LLM services. + + Parameters: + model: LLM model identifier. + temperature: Sampling temperature. + max_tokens: Maximum tokens to generate. + top_p: Nucleus sampling probability. + top_k: Top-k sampling parameter. + frequency_penalty: Frequency penalty. + presence_penalty: Presence penalty. + seed: Random seed for reproducibility. + """ + + temperature: Any = field(default_factory=lambda: NOT_GIVEN) + max_tokens: Any = field(default_factory=lambda: NOT_GIVEN) + top_p: Any = field(default_factory=lambda: NOT_GIVEN) + top_k: Any = field(default_factory=lambda: NOT_GIVEN) + frequency_penalty: Any = field(default_factory=lambda: NOT_GIVEN) + presence_penalty: Any = field(default_factory=lambda: NOT_GIVEN) + seed: Any = field(default_factory=lambda: NOT_GIVEN) + + +@dataclass +class TTSSettings(ServiceSettings): + """Typed settings for TTS services. + + Parameters: + model: TTS model identifier. + voice: Voice identifier or name. + language: Language for speech synthesis. + """ + + voice: Any = field(default_factory=lambda: NOT_GIVEN) + language: Any = field(default_factory=lambda: NOT_GIVEN) + + _aliases: ClassVar[Dict[str, str]] = {"voice_id": "voice"} + + +@dataclass +class STTSettings(ServiceSettings): + """Typed settings for STT services. + + Parameters: + model: STT model identifier. + language: Language for speech recognition. + """ + + language: Any = field(default_factory=lambda: NOT_GIVEN) diff --git a/src/pipecat/services/soniox/stt.py b/src/pipecat/services/soniox/stt.py index c9184ba4c..9d732a356 100644 --- a/src/pipecat/services/soniox/stt.py +++ b/src/pipecat/services/soniox/stt.py @@ -8,7 +8,8 @@ import json import time -from typing import AsyncGenerator, List, Optional +from dataclasses import dataclass, field +from typing import Any, AsyncGenerator, List, Optional from loguru import logger from pydantic import BaseModel @@ -23,6 +24,7 @@ from pipecat.frames.frames import ( VADUserStoppedSpeakingFrame, ) from pipecat.processors.frame_processor import FrameDirection +from pipecat.services.settings import NOT_GIVEN, STTSettings, is_given from pipecat.services.stt_latency import SONIOX_TTFS_P99 from pipecat.services.stt_service import WebsocketSTTService from pipecat.transcriptions.language import Language @@ -134,6 +136,17 @@ def _prepare_language_hints( return list(set(prepared_languages)) +@dataclass +class SonioxSTTSettings(STTSettings): + """Typed settings for Soniox STT service. + + Parameters: + input_params: Soniox ``SonioxInputParams`` for detailed configuration. + """ + + input_params: SonioxInputParams = field(default_factory=lambda: NOT_GIVEN) + + class SonioxSTTService(WebsocketSTTService): """Speech-to-Text service using Soniox's WebSocket API. @@ -181,9 +194,13 @@ class SonioxSTTService(WebsocketSTTService): self._api_key = api_key self._url = url self.set_model_name(params.model) - self._params = params self._vad_force_turn_endpoint = vad_force_turn_endpoint + self._settings = SonioxSTTSettings( + model=params.model, + input_params=params, + ) + self._final_transcription_buffer = [] self._last_tokens_received: Optional[float] = None @@ -198,6 +215,43 @@ class SonioxSTTService(WebsocketSTTService): await super().start(frame) await self._connect() + async def _update_settings_from_typed(self, update: SonioxSTTSettings) -> set[str]: + """Apply a typed settings update, keeping ``input_params`` in sync. + + Top-level ``model`` is the source of truth. When it is given in + *update* its value is propagated into ``input_params``. When only + ``input_params`` is given, its ``model`` is propagated *up* to the + top-level field. + + Any change triggers a WebSocket reconnect. + + Args: + update: A typed settings delta. + + Returns: + Set of field names whose values actually changed. + """ + model_given = is_given(getattr(update, "model", NOT_GIVEN)) + + changed = await super()._update_settings_from_typed(update) + + if not changed: + return changed + + # --- Sync model -------------------------------------------------- + if model_given: + # Top-level model wins → push into input_params. + self._settings.input_params.model = self._settings.model + elif "input_params" in changed and self._settings.input_params.model is not None: + # Only input_params was given → pull model up. + self._settings.model = self._settings.input_params.model + self.set_model_name(self._settings.model) + + await self._disconnect() + await self._connect() + + return changed + async def stop(self, frame: EndFrame): """Stop the Soniox STT websocket connection. @@ -311,7 +365,9 @@ class SonioxSTTService(WebsocketSTTService): # Either one or the other is required. enable_endpoint_detection = not self._vad_force_turn_endpoint - context = self._params.context + params = self._settings.input_params + + context = params.context if isinstance(context, SonioxContextObject): context = context.model_dump() @@ -319,16 +375,16 @@ class SonioxSTTService(WebsocketSTTService): config = { "api_key": self._api_key, "model": self._model_name, - "audio_format": self._params.audio_format, - "num_channels": self._params.num_channels or 1, + "audio_format": params.audio_format, + "num_channels": params.num_channels or 1, "enable_endpoint_detection": enable_endpoint_detection, "sample_rate": self.sample_rate, - "language_hints": _prepare_language_hints(self._params.language_hints), - "language_hints_strict": self._params.language_hints_strict, + "language_hints": _prepare_language_hints(params.language_hints), + "language_hints_strict": params.language_hints_strict, "context": context, - "enable_speaker_diarization": self._params.enable_speaker_diarization, - "enable_language_identification": self._params.enable_language_identification, - "client_reference_id": self._params.client_reference_id, + "enable_speaker_diarization": params.enable_speaker_diarization, + "enable_language_identification": params.enable_language_identification, + "client_reference_id": params.client_reference_id, } # Send the configuration message. diff --git a/src/pipecat/services/speechmatics/stt.py b/src/pipecat/services/speechmatics/stt.py index ca949a9fd..d04bb564d 100644 --- a/src/pipecat/services/speechmatics/stt.py +++ b/src/pipecat/services/speechmatics/stt.py @@ -8,8 +8,10 @@ import asyncio import os +import warnings +from dataclasses import dataclass, field from enum import Enum -from typing import Any, AsyncGenerator +from typing import Any, AsyncGenerator, ClassVar from dotenv import load_dotenv from loguru import logger @@ -31,6 +33,7 @@ from pipecat.frames.frames import ( VADUserStoppedSpeakingFrame, ) from pipecat.processors.frame_processor import FrameDirection +from pipecat.services.settings import NOT_GIVEN, STTSettings, is_given from pipecat.services.stt_latency import SPEECHMATICS_TTFS_P99 from pipecat.services.stt_service import STTService from pipecat.transcriptions.language import Language, resolve_language @@ -80,6 +83,81 @@ class TurnDetectionMode(str, Enum): SMART_TURN = "smart_turn" +@dataclass +class SpeechmaticsSTTSettings(STTSettings): + """Typed settings for Speechmatics STT service. + + See ``SpeechmaticsSTTService.InputParams`` for detailed descriptions of each field. + + Parameters: + model: The operating point / model name. + domain: Domain for Speechmatics API. + turn_detection_mode: Endpoint handling mode. + speaker_active_format: Formatter for active speaker ID. + speaker_passive_format: Formatter for passive speaker ID. + focus_speakers: List of speaker IDs to focus on. + ignore_speakers: List of speaker IDs to ignore. + focus_mode: Speaker focus mode for diarization. + known_speakers: List of known speaker labels and identifiers. + additional_vocab: List of additional vocabulary entries. + audio_encoding: Audio encoding format. + operating_point: Operating point for accuracy vs. latency. + max_delay: Maximum delay in seconds for transcription. + end_of_utterance_silence_trigger: Maximum delay for end of utterance trigger. + end_of_utterance_max_delay: Maximum delay for end of utterance. + punctuation_overrides: Punctuation overrides. + include_partials: Include partial segment fragments. + split_sentences: Emit finalized sentences mid-turn. + enable_diarization: Enable speaker diarization. + speaker_sensitivity: Diarization sensitivity. + max_speakers: Maximum number of speakers to detect. + prefer_current_speaker: Prefer current speaker ID. + extra_params: Extra parameters for the STT engine. + """ + + domain: str = field(default_factory=lambda: NOT_GIVEN) + turn_detection_mode: TurnDetectionMode = field(default_factory=lambda: NOT_GIVEN) + speaker_active_format: str = field(default_factory=lambda: NOT_GIVEN) + speaker_passive_format: str = field(default_factory=lambda: NOT_GIVEN) + focus_speakers: list = field(default_factory=lambda: NOT_GIVEN) + ignore_speakers: list = field(default_factory=lambda: NOT_GIVEN) + focus_mode: Any = field(default_factory=lambda: NOT_GIVEN) + known_speakers: list = field(default_factory=lambda: NOT_GIVEN) + additional_vocab: list = field(default_factory=lambda: NOT_GIVEN) + audio_encoding: Any = field(default_factory=lambda: NOT_GIVEN) + operating_point: Any = field(default_factory=lambda: NOT_GIVEN) + max_delay: float = field(default_factory=lambda: NOT_GIVEN) + end_of_utterance_silence_trigger: float = field(default_factory=lambda: NOT_GIVEN) + end_of_utterance_max_delay: float = field(default_factory=lambda: NOT_GIVEN) + punctuation_overrides: dict = field(default_factory=lambda: NOT_GIVEN) + include_partials: bool = field(default_factory=lambda: NOT_GIVEN) + split_sentences: bool = field(default_factory=lambda: NOT_GIVEN) + enable_diarization: bool = field(default_factory=lambda: NOT_GIVEN) + speaker_sensitivity: float = field(default_factory=lambda: NOT_GIVEN) + max_speakers: int = field(default_factory=lambda: NOT_GIVEN) + prefer_current_speaker: bool = field(default_factory=lambda: NOT_GIVEN) + extra_params: dict = field(default_factory=lambda: NOT_GIVEN) + + #: Fields that can be updated on a live connection via the Speechmatics + #: diarization-config API — no reconnect needed. + HOT_FIELDS: ClassVar[frozenset[str]] = frozenset( + { + "focus_speakers", + "ignore_speakers", + "focus_mode", + } + ) + + #: Fields that are purely local (formatting templates) — no reconnect + #: and no API call needed. + LOCAL_FIELDS: ClassVar[frozenset[str]] = frozenset( + { + "speaker_active_format", + "speaker_passive_format", + } + ) + + class SpeechmaticsSTTService(STTService): """Speechmatics STT service implementation. @@ -327,30 +405,56 @@ class SpeechmaticsSTTService(STTService): # Deprecation check self._check_deprecated_args(kwargs, params) - # Voice agent + # Output formatting defaults + speaker_active_format = params.speaker_active_format + if speaker_active_format is None: + speaker_active_format = ( + "@{speaker_id}: {text}" if params.enable_diarization else "{text}" + ) + speaker_passive_format = params.speaker_passive_format or speaker_active_format + + # Typed settings — seeded from InputParams + self._settings = SpeechmaticsSTTSettings( + language=params.language, + domain=params.domain, + turn_detection_mode=params.turn_detection_mode, + speaker_active_format=speaker_active_format, + speaker_passive_format=speaker_passive_format, + focus_speakers=params.focus_speakers, + ignore_speakers=params.ignore_speakers, + focus_mode=params.focus_mode, + known_speakers=params.known_speakers, + additional_vocab=params.additional_vocab, + audio_encoding=params.audio_encoding, + operating_point=params.operating_point, + max_delay=params.max_delay, + end_of_utterance_silence_trigger=params.end_of_utterance_silence_trigger, + end_of_utterance_max_delay=params.end_of_utterance_max_delay, + punctuation_overrides=params.punctuation_overrides, + include_partials=params.include_partials, + split_sentences=params.split_sentences, + enable_diarization=params.enable_diarization, + speaker_sensitivity=params.speaker_sensitivity, + max_speakers=params.max_speakers, + prefer_current_speaker=params.prefer_current_speaker, + extra_params=params.extra_params, + ) + + # Build SDK config from settings self._client: VoiceAgentClient | None = None - self._config: VoiceAgentConfig = self._prepare_config(params) + self._config: VoiceAgentConfig = self._build_config() # Outbound frame queue self._outbound_frames: asyncio.Queue[Frame] = asyncio.Queue() - # Output formatting - if params.speaker_active_format is None: - params.speaker_active_format = ( - "@{speaker_id}: {text}" if params.enable_diarization else "{text}" - ) - # Framework options self._enable_vad: bool = self._config.end_of_utterance_mode not in [ EndOfUtteranceMode.FIXED, EndOfUtteranceMode.EXTERNAL, ] - self._speaker_active_format: str = params.speaker_active_format - self._speaker_passive_format: str = ( - params.speaker_passive_format or params.speaker_active_format - ) - # Model + metrics + # Model + metrics (operating_point comes from the SDK config/preset) + self._settings.model = self._config.operating_point.value self.set_model_name(self._config.operating_point.value) # Message queue @@ -374,6 +478,56 @@ class SpeechmaticsSTTService(STTService): await super().start(frame) await self._connect() + async def _update_settings_from_typed(self, update: SpeechmaticsSTTSettings) -> set[str]: + """Apply typed settings update, reconnecting only when necessary. + + Fields are classified into three categories (see + ``SpeechmaticsSTTSettings``): + + * **HOT_FIELDS** – diarization speaker settings that can be pushed + to a live Speechmatics connection without reconnecting. + * **LOCAL_FIELDS** – formatting templates evaluated locally; no + reconnect or API call needed. + * Everything else – baked into ``VoiceAgentConfig`` at connection + time and therefore require a full disconnect / reconnect. + + Args: + update: A typed settings delta. + + Returns: + Set of field names whose values actually changed. + """ + changed = await super()._update_settings_from_typed(update) + + if not changed: + return changed + + no_reconnect = SpeechmaticsSTTSettings.HOT_FIELDS | SpeechmaticsSTTSettings.LOCAL_FIELDS + needs_reconnect = bool(changed - no_reconnect) + + if needs_reconnect: + # Connection-level fields changed — rebuild the SDK config + # from the now-updated self._settings, then reconnect. + self._config = self._build_config() + await self._disconnect() + await self._connect() + elif changed & SpeechmaticsSTTSettings.HOT_FIELDS: + if self._config.enable_diarization: + # Only hot-updatable fields changed — push to the live session. + self._config.speaker_config.focus_speakers = self._settings.focus_speakers + self._config.speaker_config.ignore_speakers = self._settings.ignore_speakers + self._config.speaker_config.focus_mode = self._settings.focus_mode + if self._client: + self._client.update_diarization_config(self._config.speaker_config) + else: + # Diarization not enabled — need a full reconnect to apply. + self._config = self._build_config() + await self._disconnect() + await self._connect() + # LOCAL_FIELDS: already applied by super(); nothing else to do. + + return changed + async def stop(self, frame: EndFrame): """Called when the session ends.""" await super().stop(frame) @@ -484,28 +638,35 @@ class SpeechmaticsSTTService(STTService): # CONFIGURATION # ============================================================================ - def _prepare_config(self, params: InputParams) -> VoiceAgentConfig: - """Parse the InputParams into VoiceAgentConfig.""" - # Preset - config = VoiceAgentConfigPreset.load(params.turn_detection_mode.value) + def _build_config(self) -> VoiceAgentConfig: + """Build a ``VoiceAgentConfig`` from the current ``self._settings``. + + Used both at init time and before reconnecting so the connection + always reflects the latest settings. + """ + s = self._settings + + # Preset from turn detection mode + config = VoiceAgentConfigPreset.load(s.turn_detection_mode.value) # Language + domain - config.language = self._language_to_speechmatics_language(params.language) - config.domain = params.domain - config.output_locale = self._locale_to_speechmatics_locale(config.language, params.language) + language = s.language + config.language = self._language_to_speechmatics_language(language) + config.domain = s.domain if is_given(s.domain) else None + config.output_locale = self._locale_to_speechmatics_locale(config.language, language) # Speaker config config.speaker_config = SpeakerFocusConfig( - focus_speakers=params.focus_speakers, - ignore_speakers=params.ignore_speakers, - focus_mode=params.focus_mode, + focus_speakers=s.focus_speakers if is_given(s.focus_speakers) else [], + ignore_speakers=s.ignore_speakers if is_given(s.ignore_speakers) else [], + focus_mode=s.focus_mode if is_given(s.focus_mode) else SpeakerFocusMode.RETAIN, ) - config.known_speakers = params.known_speakers + config.known_speakers = s.known_speakers if is_given(s.known_speakers) else [] # Custom dictionary - config.additional_vocab = params.additional_vocab + config.additional_vocab = s.additional_vocab if is_given(s.additional_vocab) else [] - # Advanced parameters + # Advanced parameters — only set if given (not NOT_GIVEN or None) for param in [ "operating_point", "max_delay", @@ -519,21 +680,20 @@ class SpeechmaticsSTTService(STTService): "max_speakers", "prefer_current_speaker", ]: - if getattr(params, param) is not None: - setattr(config, param, getattr(params, param)) + val = getattr(s, param) + if is_given(val) and val is not None: + setattr(config, param, val) # Extra parameters - if isinstance(params.extra_params, dict): - for key, value in params.extra_params.items(): + if is_given(s.extra_params) and isinstance(s.extra_params, dict): + for key, value in s.extra_params.items(): if hasattr(config, key): setattr(config, key, value) # Enable sentences - config.speech_segment_config = SpeechSegmentConfig( - emit_sentences=params.split_sentences or False - ) + split = s.split_sentences if is_given(s.split_sentences) else False + config.speech_segment_config = SpeechSegmentConfig(emit_sentences=split or False) - # Return the complete config return config def update_params( @@ -542,12 +702,23 @@ class SpeechmaticsSTTService(STTService): ) -> None: """Updates the speaker configuration. + .. deprecated:: + Use ``STTUpdateSettingsFrame`` with + ``SpeechmaticsSTTSettings(...)`` instead. + This can update the speakers to listen to or ignore during an in-flight transcription. Only available if diarization is enabled. Args: params: Update parameters for the service. """ + with warnings.catch_warnings(): + warnings.simplefilter("always") + warnings.warn( + "update_params() is deprecated. Use STTUpdateSettingsFrame with " + "SpeechmaticsSTTSettings(...) instead.", + DeprecationWarning, + ) # Check possible if not self._config.enable_diarization: raise ValueError("Diarization is not enabled") @@ -717,9 +888,9 @@ class SpeechmaticsSTTService(STTService): def attr_from_segment(segment: dict[str, Any]) -> dict[str, Any]: # Formats the output text based on the speaker and defined formats from the config. text = ( - self._speaker_active_format + self._settings.speaker_active_format if segment.get("is_active", True) - else self._speaker_passive_format + else self._settings.speaker_passive_format ).format( **{ "speaker_id": segment.get("speaker_id", "UU"), diff --git a/src/pipecat/services/speechmatics/tts.py b/src/pipecat/services/speechmatics/tts.py index 0f3ff0cb6..0907b4e26 100644 --- a/src/pipecat/services/speechmatics/tts.py +++ b/src/pipecat/services/speechmatics/tts.py @@ -95,7 +95,7 @@ class SpeechmaticsTTSService(TTSService): self._params = params or SpeechmaticsTTSService.InputParams() # Set voice from constructor parameter - self.set_voice(voice_id) + self._voice_id = voice_id def can_generate_metrics(self) -> bool: """Check if this service can generate processing metrics. diff --git a/src/pipecat/services/stt_service.py b/src/pipecat/services/stt_service.py index b556bb23a..d4e5f4cb5 100644 --- a/src/pipecat/services/stt_service.py +++ b/src/pipecat/services/stt_service.py @@ -34,6 +34,7 @@ from pipecat.frames.frames import ( from pipecat.metrics.metrics import TTFBMetricsData from pipecat.processors.frame_processor import FrameDirection from pipecat.services.ai_service import AIService +from pipecat.services.settings import ServiceSettings, STTSettings from pipecat.services.stt_latency import DEFAULT_TTFS_P99 from pipecat.services.websocket_service import WebsocketService from pipecat.transcriptions.language import Language @@ -101,7 +102,6 @@ class STTService(AIService): self._audio_passthrough = audio_passthrough self._init_sample_rate = sample_rate self._sample_rate = 0 - self._settings: Dict[str, Any] = {} self._tracing_enabled: bool = False self._muted: bool = False self._user_id: str = "" @@ -166,18 +166,36 @@ class STTService(AIService): async def set_model(self, model: str): """Set the speech recognition model. + When the service has been migrated to typed settings this routes + through :meth:`_update_settings_from_typed` so that concrete + services can react (e.g. reconnect) in a single place. + Args: model: The name of the model to use for speech recognition. """ - self.set_model_name(model) + logger.info(f"Switching STT model to: [{model}]") + if isinstance(self._settings, ServiceSettings): + settings_cls = type(self._settings) + await self._update_settings_from_typed(settings_cls(model=model)) + else: + self.set_model_name(model) async def set_language(self, language: Language): """Set the language for speech recognition. + When the service has been migrated to typed settings this routes + through :meth:`_update_settings_from_typed` so that concrete + services can react (e.g. reconnect) in a single place. + Args: language: The language to use for speech recognition. """ - pass + logger.info(f"Switching STT language to: [{language}]") + if isinstance(self._settings, ServiceSettings): + settings_cls = type(self._settings) + await self._update_settings_from_typed(settings_cls(language=language)) + else: + pass @abstractmethod async def run_stt(self, audio: bytes) -> AsyncGenerator[Frame, None]: @@ -224,6 +242,23 @@ class STTService(AIService): else: logger.warning(f"Unknown setting for STT service: {key}") + async def _update_settings_from_typed(self, update: STTSettings) -> set[str]: + """Apply a typed STT settings update. + + Handles ``model`` (via parent). Does **not** call ``set_language`` + — concrete services should override this method and handle language + changes (including any reconnect logic) based on the returned + changed-field set. + + Args: + update: A typed STT settings delta. + + Returns: + Set of field names whose values actually changed. + """ + changed = await super()._update_settings_from_typed(update) + return changed + async def process_audio_frame(self, frame: AudioRawFrame, direction: FrameDirection): """Process an audio frame for speech recognition. @@ -285,7 +320,16 @@ class STTService(AIService): await self._handle_vad_user_stopped_speaking(frame) await self.push_frame(frame, direction) elif isinstance(frame, STTUpdateSettingsFrame): - await self._update_settings(frame.settings) + # New path: typed settings update object. + if frame.update is not None: + await self._update_settings_from_typed(frame.update) + # Legacy path: plain dict, but service uses typed settings — convert. + elif isinstance(self._settings, ServiceSettings): + update = type(self._settings).from_mapping(frame.settings) + await self._update_settings_from_typed(update) + # Legacy path: plain dict, service still uses dict-based settings. + else: + await self._update_settings(frame.settings) elif isinstance(frame, STTMuteFrame): self._muted = frame.mute logger.debug(f"STT service {'muted' if frame.mute else 'unmuted'}") diff --git a/src/pipecat/services/tts_service.py b/src/pipecat/services/tts_service.py index 239d2398b..4196e7872 100644 --- a/src/pipecat/services/tts_service.py +++ b/src/pipecat/services/tts_service.py @@ -52,6 +52,7 @@ from pipecat.frames.frames import ( ) from pipecat.processors.frame_processor import FrameDirection from pipecat.services.ai_service import AIService +from pipecat.services.settings import ServiceSettings, TTSSettings, is_given from pipecat.services.websocket_service import WebsocketService from pipecat.transcriptions.language import Language from pipecat.utils.text.base_text_aggregator import BaseTextAggregator @@ -189,7 +190,6 @@ class TTSService(AIService): self._init_sample_rate = sample_rate self._sample_rate = 0 self._voice_id: str = "" - self._settings: Dict[str, Any] = {} self._text_aggregator: BaseTextAggregator = text_aggregator or SimpleTextAggregator() if text_aggregator: import warnings @@ -263,18 +263,40 @@ class TTSService(AIService): async def set_model(self, model: str): """Set the TTS model to use. + When the service has been migrated to typed settings this routes + through :meth:`_update_settings_from_typed` so that concrete + services can react (e.g. reconnect) in a single place. + Args: model: The name of the TTS model. """ - self.set_model_name(model) + logger.info(f"Switching TTS model to: [{model}]") + if isinstance(self._settings, ServiceSettings): + settings_cls = type(self._settings) + await self._update_settings_from_typed(settings_cls(model=model)) + else: + self.set_model_name(model) - def set_voice(self, voice: str): + async def set_voice(self, voice: str): """Set the voice for speech synthesis. + When the service has been migrated to typed settings this routes + through :meth:`_update_settings_from_typed` so that concrete + services can react (e.g. reconnect) in a single place. + + .. versionchanged:: 0.0.103 + Now ``async``. In ``__init__`` methods, set + ``self._voice_id`` directly instead of calling this method. + Args: voice: The voice identifier or name. """ - self._voice_id = voice + logger.info(f"Switching TTS voice to: [{voice}]") + if isinstance(self._settings, ServiceSettings): + settings_cls = type(self._settings) + await self._update_settings_from_typed(settings_cls(voice=voice)) + else: + self._voice_id = voice def create_context_id(self) -> str: """Generate a unique context ID for a TTS request. @@ -416,13 +438,42 @@ class TTSService(AIService): elif key == "model": self.set_model_name(value) elif key == "voice" or key == "voice_id": - self.set_voice(value) + self._voice_id = value elif key == "text_filter": for filter in self._text_filters: await filter.update_settings(value) else: logger.warning(f"Unknown setting for TTS service: {key}") + async def _update_settings_from_typed(self, update: TTSSettings) -> set[str]: + """Apply a typed TTS settings update. + + Handles ``model`` (via parent) and syncs ``_voice_id`` when voice + changes. Translates language values before applying. Does **not** + call ``set_voice`` or ``set_model`` directly — concrete services + should override this method and handle reconnect logic based on the + returned changed-field set. + + Args: + update: A typed TTS settings delta. + + Returns: + Set of field names whose values actually changed. + """ + # Translate language *before* applying so the stored value is canonical + if is_given(update.language) and update.language is not None: + converted = self.language_to_service_language(update.language) + if converted is not None: + update.language = converted + + changed = await super()._update_settings_from_typed(update) + + # Keep _voice_id in sync for code that reads it directly + if "voice" in changed and isinstance(self._settings, TTSSettings): + self._voice_id = self._settings.voice + + return changed + async def say(self, text: str): """Immediately speak the provided text. @@ -504,7 +555,16 @@ class TTSService(AIService): await self.flush_audio() self._processing_text = processing_text elif isinstance(frame, TTSUpdateSettingsFrame): - await self._update_settings(frame.settings) + # New path: typed settings update object. + if frame.update is not None: + await self._update_settings_from_typed(frame.update) + # Legacy path: plain dict, but service uses typed settings — convert. + elif isinstance(self._settings, ServiceSettings): + update = type(self._settings).from_mapping(frame.settings) + await self._update_settings_from_typed(update) + # Legacy path: plain dict, service still uses dict-based settings. + else: + await self._update_settings(frame.settings) elif isinstance(frame, BotStoppedSpeakingFrame): await self._maybe_resume_frame_processing() await self.push_frame(frame, direction) diff --git a/src/pipecat/services/ultravox/llm.py b/src/pipecat/services/ultravox/llm.py index d549b11e5..9f0658486 100644 --- a/src/pipecat/services/ultravox/llm.py +++ b/src/pipecat/services/ultravox/llm.py @@ -15,6 +15,7 @@ import asyncio import datetime import json import uuid +from dataclasses import dataclass, field from typing import Any, Dict, List, Literal, Optional, Union import aiohttp @@ -34,7 +35,6 @@ from pipecat.frames.frames import ( LLMFullResponseEndFrame, LLMFullResponseStartFrame, LLMTextFrame, - LLMUpdateSettingsFrame, StartFrame, TranscriptionFrame, TTSAudioRawFrame, @@ -56,6 +56,7 @@ from pipecat.processors.aggregators.openai_llm_context import ( ) from pipecat.processors.frame_processor import FrameDirection from pipecat.services.llm_service import FunctionCallFromLLM, LLMService +from pipecat.services.settings import NOT_GIVEN, LLMSettings from pipecat.utils.time import time_now_iso8601 try: @@ -66,6 +67,17 @@ except ModuleNotFoundError as e: raise Exception(f"Missing module: {e}") +@dataclass +class UltravoxRealtimeLLMSettings(LLMSettings): + """Settings for UltravoxRealtimeLLMService. + + Parameters: + output_medium: The output medium for the model ("voice" or "text"). + """ + + output_medium: str = field(default=NOT_GIVEN) + + class AgentInputParams(BaseModel): """Input parameters for Ultravox Realtime generation using a pre-defined Agent. @@ -163,6 +175,7 @@ class UltravoxRealtimeLLMService(LLMService): **kwargs: Additional arguments passed to parent LLMService. """ super().__init__(**kwargs) + self._settings = UltravoxRealtimeLLMSettings() self._params = params if one_shot_selected_tools: if not isinstance(self._params, OneShotInputParams): @@ -310,6 +323,12 @@ class UltravoxRealtimeLLMService(LLMService): await self.cancel_task(self._receive_task, timeout=1.0) self._receive_task = None + async def _update_settings_from_typed(self, update: UltravoxRealtimeLLMSettings): + changed = await super()._update_settings_from_typed(update) + if "output_medium" in changed: + await self._update_output_medium(self._settings.output_medium) + return changed + # # frame processing # StartFrame, StopFrame, CancelFrame implemented in base class @@ -331,9 +350,6 @@ class UltravoxRealtimeLLMService(LLMService): else LLMContext.from_openai_context(frame.context) ) await self._handle_context(context) - elif isinstance(frame, LLMUpdateSettingsFrame): - if "output_medium" in frame.settings: - await self._update_output_medium(frame.settings.get("output_medium")) elif isinstance(frame, InputTextRawFrame): await self._send_user_text(frame.text) await self.push_frame(frame, direction) diff --git a/src/pipecat/services/whisper/base_stt.py b/src/pipecat/services/whisper/base_stt.py index bc999dba4..2a02c6ce7 100644 --- a/src/pipecat/services/whisper/base_stt.py +++ b/src/pipecat/services/whisper/base_stt.py @@ -10,6 +10,7 @@ This module provides common functionality for services implementing the Whisper interface, including language mapping, metrics generation, and error handling. """ +from dataclasses import dataclass, field from typing import AsyncGenerator, Optional from loguru import logger @@ -17,6 +18,7 @@ from openai import AsyncOpenAI from openai.types.audio import Transcription from pipecat.frames.frames import ErrorFrame, Frame, TranscriptionFrame +from pipecat.services.settings import NOT_GIVEN, STTSettings from pipecat.services.stt_latency import WHISPER_TTFS_P99 from pipecat.services.stt_service import SegmentedSTTService from pipecat.transcriptions.language import Language, resolve_language @@ -24,6 +26,22 @@ from pipecat.utils.time import time_now_iso8601 from pipecat.utils.tracing.service_decorators import traced_stt +@dataclass +class BaseWhisperSTTSettings(STTSettings): + """Typed settings for Whisper API-based STT services. + + Parameters: + base_url: API base URL. + prompt: Optional text to guide the model's style or continue + a previous segment. + temperature: Sampling temperature between 0 and 1. + """ + + base_url: Optional[str] = field(default_factory=lambda: NOT_GIVEN) + prompt: Optional[str] = field(default_factory=lambda: NOT_GIVEN) + temperature: Optional[float] = field(default_factory=lambda: NOT_GIVEN) + + def language_to_whisper_language(language: Language) -> Optional[str]: """Maps pipecat Language enum to Whisper API language codes. @@ -143,26 +161,36 @@ class BaseWhisperSTTService(SegmentedSTTService): self._temperature = temperature self._include_prob_metrics = include_prob_metrics - self._settings = { - "base_url": base_url, - "language": self._language, - "prompt": self._prompt, - "temperature": self._temperature, - } + self._settings: BaseWhisperSTTSettings = BaseWhisperSTTSettings( + model=model, + language=self._language, + base_url=base_url, + prompt=self._prompt, + temperature=self._temperature, + ) def _create_client(self, api_key: Optional[str], base_url: Optional[str]): return AsyncOpenAI(api_key=api_key, base_url=base_url) - async def set_model(self, model: str): - """Set the model name for transcription. + async def _update_settings_from_typed(self, update: STTSettings) -> set[str]: + """Apply a typed settings update, syncing instance variables. - Args: - model: The name of the model to use. + Keeps ``_language``, ``_prompt``, and ``_temperature`` in sync with + the typed settings fields. """ - self.set_model_name(model) + changed = await super()._update_settings_from_typed(update) + + if "language" in changed: + self._language = self.language_to_service_language(Language(self._settings.language)) + if "prompt" in changed: + self._prompt = self._settings.prompt + if "temperature" in changed: + self._temperature = self._settings.temperature + + return changed def can_generate_metrics(self) -> bool: - """Indicates whether this service can generate metrics. + """Whether this service can generate processing metrics. Returns: bool: True, as this service supports metric generation. @@ -180,15 +208,6 @@ class BaseWhisperSTTService(SegmentedSTTService): """ return language_to_whisper_language(language) - async def set_language(self, language: Language): - """Set the language for transcription. - - Args: - language: The Language enum value to use for transcription. - """ - logger.info(f"Switching STT language to: [{language}]") - self._language = self.language_to_service_language(language) - @traced_stt async def _handle_transcription( self, transcript: str, is_final: bool, language: Optional[Language] = None diff --git a/src/pipecat/services/whisper/stt.py b/src/pipecat/services/whisper/stt.py index f11978cc2..30451e6d0 100644 --- a/src/pipecat/services/whisper/stt.py +++ b/src/pipecat/services/whisper/stt.py @@ -11,6 +11,7 @@ supporting both Faster Whisper and MLX Whisper backends for efficient inference. """ import asyncio +from dataclasses import dataclass, field from enum import Enum from typing import AsyncGenerator, Optional @@ -19,6 +20,7 @@ from loguru import logger from typing_extensions import TYPE_CHECKING, override from pipecat.frames.frames import ErrorFrame, Frame, TranscriptionFrame +from pipecat.services.settings import NOT_GIVEN, STTSettings from pipecat.services.stt_service import SegmentedSTTService from pipecat.transcriptions.language import Language, resolve_language from pipecat.utils.time import time_now_iso8601 @@ -172,6 +174,36 @@ def language_to_whisper_language(language: Language) -> Optional[str]: return resolve_language(language, LANGUAGE_MAP, use_base_code=True) +@dataclass +class WhisperSTTSettings(STTSettings): + """Typed settings for the local Whisper (Faster Whisper) STT service. + + Parameters: + device: Inference device ('cpu', 'cuda', or 'auto'). + compute_type: Compute type for inference ('default', 'int8', etc.). + no_speech_prob: Probability threshold for filtering non-speech segments. + """ + + device: str = field(default_factory=lambda: NOT_GIVEN) + compute_type: str = field(default_factory=lambda: NOT_GIVEN) + no_speech_prob: float = field(default_factory=lambda: NOT_GIVEN) + + +@dataclass +class WhisperMLXSTTSettings(STTSettings): + """Typed settings for the MLX Whisper STT service. + + Parameters: + no_speech_prob: Probability threshold for filtering non-speech segments. + temperature: Sampling temperature (0.0-1.0). + engine: Whisper engine identifier. + """ + + no_speech_prob: float = field(default_factory=lambda: NOT_GIVEN) + temperature: float = field(default_factory=lambda: NOT_GIVEN) + engine: str = field(default_factory=lambda: NOT_GIVEN) + + class WhisperSTTService(SegmentedSTTService): """Class to transcribe audio with a locally-downloaded Whisper model. @@ -206,12 +238,13 @@ class WhisperSTTService(SegmentedSTTService): self._no_speech_prob = no_speech_prob self._model: Optional[WhisperModel] = None - self._settings = { - "language": language, - "device": self._device, - "compute_type": self._compute_type, - "no_speech_prob": self._no_speech_prob, - } + self._settings: WhisperSTTSettings = WhisperSTTSettings( + model=model if isinstance(model, str) else model.value, + language=language, + device=self._device, + compute_type=self._compute_type, + no_speech_prob=self._no_speech_prob, + ) self._load() @@ -234,15 +267,6 @@ class WhisperSTTService(SegmentedSTTService): """ return language_to_whisper_language(language) - async def set_language(self, language: Language): - """Set the language for transcription. - - Args: - language: The Language enum value to use for transcription. - """ - logger.info(f"Switching STT language to: [{language}]") - self._settings["language"] = language - def _load(self): """Loads the Whisper model. @@ -293,7 +317,7 @@ class WhisperSTTService(SegmentedSTTService): # Divide by 32768 because we have signed 16-bit data. audio_float = np.frombuffer(audio, dtype=np.int16).astype(np.float32) / 32768.0 - whisper_lang = self.language_to_service_language(self._settings["language"]) + whisper_lang = self.language_to_service_language(self._settings.language) segments, _ = await asyncio.to_thread( self._model.transcribe, audio_float, language=whisper_lang ) @@ -305,13 +329,13 @@ class WhisperSTTService(SegmentedSTTService): await self.stop_processing_metrics() if text: - await self._handle_transcription(text, True, self._settings["language"]) + await self._handle_transcription(text, True, self._settings.language) logger.debug(f"Transcription: [{text}]") yield TranscriptionFrame( text, self._user_id, time_now_iso8601(), - self._settings["language"], + self._settings.language, ) @@ -347,12 +371,13 @@ class WhisperSTTServiceMLX(WhisperSTTService): self._no_speech_prob = no_speech_prob self._temperature = temperature - self._settings = { - "language": language, - "no_speech_prob": self._no_speech_prob, - "temperature": self._temperature, - "engine": "mlx", - } + self._settings: WhisperMLXSTTSettings = WhisperMLXSTTSettings( + model=model if isinstance(model, str) else model.value, + language=language, + no_speech_prob=self._no_speech_prob, + temperature=self._temperature, + engine="mlx", + ) # No need to call _load() as MLX Whisper loads models on demand @@ -390,7 +415,7 @@ class WhisperSTTServiceMLX(WhisperSTTService): # Divide by 32768 because we have signed 16-bit data. audio_float = np.frombuffer(audio, dtype=np.int16).astype(np.float32) / 32768.0 - whisper_lang = self.language_to_service_language(self._settings["language"]) + whisper_lang = self.language_to_service_language(self._settings.language) chunk = await asyncio.to_thread( mlx_whisper.transcribe, audio_float, @@ -413,13 +438,13 @@ class WhisperSTTServiceMLX(WhisperSTTService): await self.stop_processing_metrics() if text: - await self._handle_transcription(text, True, self._settings["language"]) + await self._handle_transcription(text, True, self._settings.language) logger.debug(f"Transcription: [{text}]") yield TranscriptionFrame( text, self._user_id, time_now_iso8601(), - self._settings["language"], + self._settings.language, ) except Exception as e: diff --git a/src/pipecat/services/xtts/tts.py b/src/pipecat/services/xtts/tts.py index bf4eb4f03..664d3d4be 100644 --- a/src/pipecat/services/xtts/tts.py +++ b/src/pipecat/services/xtts/tts.py @@ -10,7 +10,8 @@ This module provides integration with Coqui XTTS streaming server for text-to-speech synthesis using local Docker deployment. """ -from typing import Any, AsyncGenerator, Dict, Optional +from dataclasses import dataclass, field +from typing import AsyncGenerator, Dict, Optional import aiohttp from loguru import logger @@ -24,6 +25,7 @@ from pipecat.frames.frames import ( TTSStartedFrame, TTSStoppedFrame, ) +from pipecat.services.settings import NOT_GIVEN, TTSSettings from pipecat.services.tts_service import TTSService from pipecat.transcriptions.language import Language, resolve_language from pipecat.utils.tracing.service_decorators import traced_tts @@ -68,6 +70,17 @@ def language_to_xtts_language(language: Language) -> Optional[str]: return resolve_language(language, LANGUAGE_MAP, use_base_code=True) +@dataclass +class XTTSTTSSettings(TTSSettings): + """Typed settings for XTTS TTS service. + + Parameters: + base_url: Base URL of the XTTS streaming server. + """ + + base_url: str = field(default_factory=lambda: NOT_GIVEN) + + class XTTSService(TTSService): """Coqui XTTS text-to-speech service. @@ -98,11 +111,12 @@ class XTTSService(TTSService): """ super().__init__(sample_rate=sample_rate, **kwargs) - self._settings = { - "language": self.language_to_service_language(language), - "base_url": base_url, - } - self.set_voice(voice_id) + self._settings: XTTSTTSSettings = XTTSTTSSettings( + voice=voice_id, + language=self.language_to_service_language(language), + base_url=base_url, + ) + self._voice_id = voice_id self._studio_speakers: Optional[Dict[str, Any]] = None self._aiohttp_session = aiohttp_session @@ -138,7 +152,7 @@ class XTTSService(TTSService): if self._studio_speakers: return - async with self._aiohttp_session.get(self._settings["base_url"] + "/studio_speakers") as r: + async with self._aiohttp_session.get(self._settings.base_url + "/studio_speakers") as r: if r.status != 200: text = await r.text() await self.push_error( @@ -166,11 +180,11 @@ class XTTSService(TTSService): embeddings = self._studio_speakers[self._voice_id] - url = self._settings["base_url"] + "/tts_stream" + url = self._settings.base_url + "/tts_stream" payload = { "text": text.replace(".", "").replace("*", ""), - "language": self._settings["language"], + "language": self._settings.language, "speaker_embedding": embeddings["speaker_embedding"], "gpt_cond_latent": embeddings["gpt_cond_latent"], "add_wav_header": False, diff --git a/tests/test_settings.py b/tests/test_settings.py new file mode 100644 index 000000000..62583b00b --- /dev/null +++ b/tests/test_settings.py @@ -0,0 +1,308 @@ +# +# Copyright (c) 2024-2026, Daily +# +# SPDX-License-Identifier: BSD 2-Clause License +# + +"""Tests for the typed settings infrastructure in pipecat.services.settings.""" + +import pytest + +from pipecat.services.settings import ( + NOT_GIVEN, + LLMSettings, + ServiceSettings, + STTSettings, + TTSSettings, + _NotGiven, + is_given, +) + +# --------------------------------------------------------------------------- +# NOT_GIVEN sentinel +# --------------------------------------------------------------------------- + + +class TestNotGiven: + def test_singleton(self): + """NOT_GIVEN is a singleton — every reference is the same object.""" + assert _NotGiven() is _NotGiven() + assert NOT_GIVEN is _NotGiven() + + def test_repr(self): + assert repr(NOT_GIVEN) == "NOT_GIVEN" + + def test_bool_is_false(self): + assert not NOT_GIVEN + assert bool(NOT_GIVEN) is False + + def test_is_given_with_not_given(self): + assert is_given(NOT_GIVEN) is False + + def test_is_given_with_none(self): + assert is_given(None) is True + + def test_is_given_with_values(self): + assert is_given(0) is True + assert is_given("") is True + assert is_given(False) is True + assert is_given(42) is True + assert is_given("hello") is True + + +# --------------------------------------------------------------------------- +# ServiceSettings base +# --------------------------------------------------------------------------- + + +class TestServiceSettings: + def test_default_fields_are_not_given(self): + s = ServiceSettings() + assert not is_given(s.model) + assert s.extra == {} + + def test_given_fields_empty_by_default(self): + s = ServiceSettings() + assert s.given_fields() == {} + + def test_given_fields_includes_set_values(self): + s = ServiceSettings(model="gpt-4o") + assert s.given_fields() == {"model": "gpt-4o"} + + def test_given_fields_includes_extra(self): + s = ServiceSettings(model="gpt-4o") + s.extra = {"custom_key": 42} + result = s.given_fields() + assert result == {"model": "gpt-4o", "custom_key": 42} + + def test_to_dict(self): + s = ServiceSettings(model="gpt-4o") + assert s.to_dict() == {"model": "gpt-4o"} + + def test_copy_is_deep(self): + s = ServiceSettings(model="gpt-4o") + s.extra = {"nested": {"a": 1}} + c = s.copy() + assert c.model == "gpt-4o" + assert c.extra == {"nested": {"a": 1}} + # Mutating the copy shouldn't affect the original + c.extra["nested"]["a"] = 999 + assert s.extra["nested"]["a"] == 1 + + +# --------------------------------------------------------------------------- +# apply_update +# --------------------------------------------------------------------------- + + +class TestApplyUpdate: + def test_apply_update_basic(self): + current = TTSSettings(voice="alice", language="en") + delta = TTSSettings(voice="bob") + changed = current.apply_update(delta) + assert changed == {"voice"} + assert current.voice == "bob" + assert current.language == "en" + + def test_apply_update_no_change(self): + current = TTSSettings(voice="alice", language="en") + delta = TTSSettings(voice="alice") + changed = current.apply_update(delta) + assert changed == set() + assert current.voice == "alice" + + def test_apply_update_not_given_skipped(self): + current = TTSSettings(voice="alice", language="en") + delta = TTSSettings() # all NOT_GIVEN + changed = current.apply_update(delta) + assert changed == set() + assert current.voice == "alice" + assert current.language == "en" + + def test_apply_update_multiple_fields(self): + current = LLMSettings(temperature=0.7, max_tokens=100) + delta = LLMSettings(temperature=0.9, max_tokens=200, top_p=0.95) + changed = current.apply_update(delta) + assert changed == {"temperature", "max_tokens", "top_p"} + assert current.temperature == 0.9 + assert current.max_tokens == 200 + assert current.top_p == 0.95 + + def test_apply_update_extra_merged(self): + current = TTSSettings(voice="alice") + current.extra = {"speed": 1.0, "stability": 0.5} + delta = TTSSettings() + delta.extra = {"speed": 1.2} + changed = current.apply_update(delta) + assert "speed" in changed + assert current.extra == {"speed": 1.2, "stability": 0.5} + + def test_apply_update_extra_no_change(self): + current = TTSSettings(voice="alice") + current.extra = {"speed": 1.0} + delta = TTSSettings() + delta.extra = {"speed": 1.0} + changed = current.apply_update(delta) + assert changed == set() + + def test_apply_update_model_field(self): + current = ServiceSettings(model="old-model") + delta = ServiceSettings(model="new-model") + changed = current.apply_update(delta) + assert changed == {"model"} + assert current.model == "new-model" + + def test_apply_update_none_is_a_valid_value(self): + """Setting a field to None should be treated as a change from NOT_GIVEN.""" + current = TTSSettings() + delta = TTSSettings(language=None) + changed = current.apply_update(delta) + assert "language" in changed + assert current.language is None + + def test_apply_update_none_to_value(self): + current = TTSSettings(language=None) + delta = TTSSettings(language="en") + changed = current.apply_update(delta) + assert "language" in changed + assert current.language == "en" + + +# --------------------------------------------------------------------------- +# from_mapping +# --------------------------------------------------------------------------- + + +class TestFromMapping: + def test_basic_mapping(self): + s = TTSSettings.from_mapping({"voice": "alice", "language": "en"}) + assert s.voice == "alice" + assert s.language == "en" + assert not is_given(s.model) + + def test_alias_resolution(self): + """'voice_id' is an alias for 'voice' in TTSSettings.""" + s = TTSSettings.from_mapping({"voice_id": "alice"}) + assert s.voice == "alice" + + def test_unknown_keys_go_to_extra(self): + s = TTSSettings.from_mapping({"voice": "alice", "speed": 1.2, "stability": 0.5}) + assert s.voice == "alice" + assert s.extra == {"speed": 1.2, "stability": 0.5} + + def test_model_field(self): + s = LLMSettings.from_mapping({"model": "gpt-4o", "temperature": 0.7}) + assert s.model == "gpt-4o" + assert s.temperature == 0.7 + + def test_empty_mapping(self): + s = ServiceSettings.from_mapping({}) + assert s.given_fields() == {} + + def test_all_unknown_keys(self): + s = ServiceSettings.from_mapping({"foo": 1, "bar": 2}) + assert not is_given(s.model) + assert s.extra == {"foo": 1, "bar": 2} + + def test_llm_settings_from_mapping(self): + s = LLMSettings.from_mapping({"temperature": 0.5, "max_tokens": 1000, "custom_param": True}) + assert s.temperature == 0.5 + assert s.max_tokens == 1000 + assert s.extra == {"custom_param": True} + + def test_stt_settings_from_mapping(self): + s = STTSettings.from_mapping({"language": "fr", "model": "whisper-large"}) + assert s.language == "fr" + assert s.model == "whisper-large" + + +# --------------------------------------------------------------------------- +# LLMSettings specifics +# --------------------------------------------------------------------------- + + +class TestLLMSettings: + def test_all_fields_not_given_by_default(self): + s = LLMSettings() + for name in ( + "model", + "temperature", + "max_tokens", + "top_p", + "top_k", + "frequency_penalty", + "presence_penalty", + "seed", + ): + assert not is_given(getattr(s, name)), f"{name} should be NOT_GIVEN" + + def test_given_fields(self): + s = LLMSettings(temperature=0.7, seed=42) + assert s.given_fields() == {"temperature": 0.7, "seed": 42} + + +# --------------------------------------------------------------------------- +# TTSSettings specifics +# --------------------------------------------------------------------------- + + +class TestTTSSettings: + def test_all_fields_not_given_by_default(self): + s = TTSSettings() + for name in ("model", "voice", "language"): + assert not is_given(getattr(s, name)), f"{name} should be NOT_GIVEN" + + def test_aliases_class_var(self): + assert TTSSettings._aliases == {"voice_id": "voice"} + + def test_given_fields(self): + s = TTSSettings(voice="alice") + assert s.given_fields() == {"voice": "alice"} + + +# --------------------------------------------------------------------------- +# STTSettings specifics +# --------------------------------------------------------------------------- + + +class TestSTTSettings: + def test_all_fields_not_given_by_default(self): + s = STTSettings() + for name in ("model", "language"): + assert not is_given(getattr(s, name)), f"{name} should be NOT_GIVEN" + + def test_given_fields(self): + s = STTSettings(language="en", model="whisper-large") + assert s.given_fields() == {"language": "en", "model": "whisper-large"} + + +# --------------------------------------------------------------------------- +# Integration: roundtrip from_mapping → apply_update +# --------------------------------------------------------------------------- + + +class TestRoundtrip: + def test_from_mapping_then_apply_update(self): + """Simulate the real flow: dict arrives via frame, gets converted, applied.""" + # Simulating current service state + current = TTSSettings(model="eleven_turbo_v2_5", voice="alice", language="en") + current.extra = {"stability": 0.5, "speed": 1.0} + + # Incoming dict-based update + raw = {"voice_id": "bob", "speed": 1.2} + delta = TTSSettings.from_mapping(raw) + + changed = current.apply_update(delta) + assert changed == {"voice", "speed"} + assert current.voice == "bob" + assert current.language == "en" + assert current.extra["speed"] == 1.2 + assert current.extra["stability"] == 0.5 + + def test_from_mapping_preserves_model(self): + current = LLMSettings(model="gpt-4o", temperature=0.7) + delta = LLMSettings.from_mapping({"model": "gpt-4o-mini", "temperature": 0.9}) + changed = current.apply_update(delta) + assert changed == {"model", "temperature"} + assert current.model == "gpt-4o-mini" + assert current.temperature == 0.9 From 444cbb64991c0bb67a42df46320b0919dee16fd6 Mon Sep 17 00:00:00 2001 From: Paul Kompfner Date: Fri, 13 Feb 2026 10:31:25 -0500 Subject: [PATCH 0485/1060] Add turn-completion fields to LLMSettings and handle them in the typed-service-settings path. `filter_incomplete_user_turns` and `user_turn_completion_config` were only handled in the legacy dict-based `_update_settings` code path. This adds them to `LLMSettings` and introduces `LLMService._update_settings_from_typed` so the typed path handles them too. --- src/pipecat/services/llm_service.py | 25 ++++++++++++++++++++++++- src/pipecat/services/settings.py | 16 +++++++++++++++- 2 files changed, 39 insertions(+), 2 deletions(-) diff --git a/src/pipecat/services/llm_service.py b/src/pipecat/services/llm_service.py index 77af50f15..3a6e64def 100644 --- a/src/pipecat/services/llm_service.py +++ b/src/pipecat/services/llm_service.py @@ -59,7 +59,7 @@ from pipecat.processors.aggregators.llm_response import ( from pipecat.processors.aggregators.openai_llm_context import OpenAILLMContext from pipecat.processors.frame_processor import FrameDirection from pipecat.services.ai_service import AIService -from pipecat.services.settings import ServiceSettings +from pipecat.services.settings import LLMSettings, ServiceSettings, is_given from pipecat.turns.user_turn_completion_mixin import UserTurnCompletionLLMServiceMixin from pipecat.utils.context.llm_context_summarization import ( LLMContextSummarizationUtil, @@ -311,6 +311,29 @@ class LLMService(UserTurnCompletionLLMServiceMixin, AIService): await self._cancel_sequential_runner_task() await self._cancel_summary_task() + async def _update_settings_from_typed(self, update: LLMSettings) -> set[str]: + """Apply a typed settings update, handling turn-completion fields. + + Args: + update: A typed LLM settings delta. + + Returns: + Set of field names whose values actually changed. + """ + changed = await super()._update_settings_from_typed(update) + + if "filter_incomplete_user_turns" in changed: + self._filter_incomplete_user_turns = self._settings.filter_incomplete_user_turns + logger.info( + f"{self}: Incomplete turn filtering " + f"{'enabled' if self._filter_incomplete_user_turns else 'disabled'}" + ) + + if "user_turn_completion_config" in changed and self._filter_incomplete_user_turns: + self.set_user_turn_completion_config(self._settings.user_turn_completion_config) + + return changed + async def _update_settings(self, settings: Mapping[str, Any]): """Update LLM service settings. diff --git a/src/pipecat/services/settings.py b/src/pipecat/services/settings.py index fbec5cdf8..718996984 100644 --- a/src/pipecat/services/settings.py +++ b/src/pipecat/services/settings.py @@ -31,10 +31,13 @@ from __future__ import annotations import copy from dataclasses import dataclass, field, fields -from typing import Any, ClassVar, Dict, Mapping, Optional, Set, Type, TypeVar +from typing import TYPE_CHECKING, Any, ClassVar, Dict, Mapping, Optional, Set, Type, TypeVar from loguru import logger +if TYPE_CHECKING: + from pipecat.turns.user_turn_completion_mixin import UserTurnCompletionConfig + # --------------------------------------------------------------------------- # NOT_GIVEN sentinel # --------------------------------------------------------------------------- @@ -258,6 +261,13 @@ class LLMSettings(ServiceSettings): frequency_penalty: Frequency penalty. presence_penalty: Presence penalty. seed: Random seed for reproducibility. + filter_incomplete_user_turns: Enable LLM-based turn completion detection + to suppress bot responses when the user was cut off mid-thought. + See ``examples/foundational/22-filter-incomplete-turns.py`` and + ``UserTurnCompletionLLMServiceMixin``. + user_turn_completion_config: Configuration for turn completion behavior + when ``filter_incomplete_user_turns`` is enabled. Controls timeouts + and prompts for incomplete turns. """ temperature: Any = field(default_factory=lambda: NOT_GIVEN) @@ -267,6 +277,10 @@ class LLMSettings(ServiceSettings): frequency_penalty: Any = field(default_factory=lambda: NOT_GIVEN) presence_penalty: Any = field(default_factory=lambda: NOT_GIVEN) seed: Any = field(default_factory=lambda: NOT_GIVEN) + filter_incomplete_user_turns: bool | _NotGiven = field(default_factory=lambda: NOT_GIVEN) + user_turn_completion_config: UserTurnCompletionConfig | _NotGiven = field( + default_factory=lambda: NOT_GIVEN + ) @dataclass From e43351f5f8738fb2b8f7355de749f1e673077683 Mon Sep 17 00:00:00 2001 From: Paul Kompfner Date: Fri, 13 Feb 2026 11:29:37 -0500 Subject: [PATCH 0486/1060] Add class-level `_settings` type annotations to all service classes for better editor support. Standardize all STT, TTS, and LLM service classes to declare `_settings` with the narrowed Settings type as a class-level annotation. This gives editors and type checkers the specific type when hovering or autocompleting on `self._settings` in each service and its subclasses. Inline `self._settings: Type = ...` assignments are replaced with plain `self._settings = ...`. --- src/pipecat/services/anthropic/llm.py | 2 ++ src/pipecat/services/assemblyai/stt.py | 4 +++- src/pipecat/services/asyncai/tts.py | 8 ++++++-- src/pipecat/services/aws/llm.py | 2 ++ src/pipecat/services/aws/stt.py | 4 +++- src/pipecat/services/aws/tts.py | 4 +++- src/pipecat/services/azure/stt.py | 4 +++- src/pipecat/services/azure/tts.py | 4 +++- src/pipecat/services/camb/tts.py | 4 +++- src/pipecat/services/cartesia/stt.py | 4 +++- src/pipecat/services/cartesia/tts.py | 8 ++++++-- src/pipecat/services/deepgram/stt.py | 4 +++- src/pipecat/services/deepgram/stt_sagemaker.py | 4 +++- src/pipecat/services/deepgram/tts.py | 8 ++++++-- src/pipecat/services/elevenlabs/stt.py | 8 ++++++-- src/pipecat/services/elevenlabs/tts.py | 8 ++++++-- src/pipecat/services/fal/stt.py | 4 +++- src/pipecat/services/fish/tts.py | 4 +++- src/pipecat/services/gladia/stt.py | 2 ++ src/pipecat/services/google/gemini_live/llm.py | 2 ++ src/pipecat/services/google/llm.py | 2 ++ src/pipecat/services/google/stt.py | 2 ++ src/pipecat/services/google/tts.py | 12 +++++++++--- src/pipecat/services/gradium/stt.py | 4 +++- src/pipecat/services/gradium/tts.py | 4 +++- src/pipecat/services/grok/realtime/llm.py | 2 ++ src/pipecat/services/groq/tts.py | 4 +++- src/pipecat/services/hathora/stt.py | 4 +++- src/pipecat/services/hathora/tts.py | 4 +++- src/pipecat/services/inworld/tts.py | 8 ++++++-- src/pipecat/services/kokoro/tts.py | 4 +++- src/pipecat/services/llm_service.py | 2 ++ src/pipecat/services/lmnt/tts.py | 4 +++- src/pipecat/services/minimax/tts.py | 4 +++- src/pipecat/services/neuphonic/tts.py | 4 +++- src/pipecat/services/nvidia/stt.py | 8 ++++++-- src/pipecat/services/openai/base_llm.py | 2 ++ src/pipecat/services/openai/realtime/llm.py | 2 ++ src/pipecat/services/openai/stt.py | 4 +++- src/pipecat/services/openai/tts.py | 4 +++- src/pipecat/services/openai_realtime_beta/openai.py | 2 ++ src/pipecat/services/playht/tts.py | 8 ++++++-- src/pipecat/services/resembleai/tts.py | 4 +++- src/pipecat/services/rime/tts.py | 12 +++++++++--- src/pipecat/services/sarvam/stt.py | 4 +++- src/pipecat/services/sarvam/tts.py | 8 ++++++-- src/pipecat/services/soniox/stt.py | 2 ++ src/pipecat/services/speechmatics/stt.py | 2 ++ src/pipecat/services/stt_service.py | 2 ++ src/pipecat/services/tts_service.py | 2 ++ src/pipecat/services/ultravox/llm.py | 2 ++ src/pipecat/services/whisper/base_stt.py | 4 +++- src/pipecat/services/whisper/stt.py | 8 ++++++-- src/pipecat/services/xtts/tts.py | 4 +++- 54 files changed, 188 insertions(+), 52 deletions(-) diff --git a/src/pipecat/services/anthropic/llm.py b/src/pipecat/services/anthropic/llm.py index 36ee104f5..25611d0d1 100644 --- a/src/pipecat/services/anthropic/llm.py +++ b/src/pipecat/services/anthropic/llm.py @@ -129,6 +129,8 @@ class AnthropicLLMService(LLMService): Can use custom clients like AsyncAnthropicBedrock and AsyncAnthropicVertex. """ + _settings: AnthropicLLMSettings + # Overriding the default adapter to use the Anthropic one. adapter_class = AnthropicLLMAdapter diff --git a/src/pipecat/services/assemblyai/stt.py b/src/pipecat/services/assemblyai/stt.py index 278873fdf..910d1e005 100644 --- a/src/pipecat/services/assemblyai/stt.py +++ b/src/pipecat/services/assemblyai/stt.py @@ -75,6 +75,8 @@ class AssemblyAISTTService(WebsocketSTTService): for audio processing and connection management. """ + _settings: AssemblyAISTTSettings + def __init__( self, *, @@ -111,7 +113,7 @@ class AssemblyAISTTService(WebsocketSTTService): ) self._api_key = api_key - self._settings: AssemblyAISTTSettings = AssemblyAISTTSettings( + self._settings = AssemblyAISTTSettings( language=language, connection_params=connection_params, ) diff --git a/src/pipecat/services/asyncai/tts.py b/src/pipecat/services/asyncai/tts.py index aecf69a26..2b0740956 100644 --- a/src/pipecat/services/asyncai/tts.py +++ b/src/pipecat/services/asyncai/tts.py @@ -95,6 +95,8 @@ class AsyncAITTSService(AudioContextTTSService): Provides text-to-speech using Async's streaming WebSocket API. """ + _settings: AsyncAITTSSettings + class InputParams(BaseModel): """Input parameters for Async TTS configuration. @@ -148,7 +150,7 @@ class AsyncAITTSService(AudioContextTTSService): self._api_key = api_key self._api_version = version self._url = url - self._settings: AsyncAITTSSettings = AsyncAITTSSettings( + self._settings = AsyncAITTSSettings( model=model, voice=voice_id, output_format={ @@ -431,6 +433,8 @@ class AsyncAIHttpTTSService(TTSService): connection is not required or desired. """ + _settings: AsyncAITTSSettings + class InputParams(BaseModel): """Input parameters for Async API. @@ -477,7 +481,7 @@ class AsyncAIHttpTTSService(TTSService): self._api_key = api_key self._base_url = url self._api_version = version - self._settings: AsyncAITTSSettings = AsyncAITTSSettings( + self._settings = AsyncAITTSSettings( model=model, voice=voice_id, output_container=container, diff --git a/src/pipecat/services/aws/llm.py b/src/pipecat/services/aws/llm.py index 032cee060..50de0de2c 100644 --- a/src/pipecat/services/aws/llm.py +++ b/src/pipecat/services/aws/llm.py @@ -743,6 +743,8 @@ class AWSBedrockLLMService(LLMService): vision capabilities. """ + _settings: AWSBedrockLLMSettings + # Overriding the default adapter to use the Anthropic one. adapter_class = AWSBedrockLLMAdapter diff --git a/src/pipecat/services/aws/stt.py b/src/pipecat/services/aws/stt.py index cb52da12a..cd8a7103c 100644 --- a/src/pipecat/services/aws/stt.py +++ b/src/pipecat/services/aws/stt.py @@ -72,6 +72,8 @@ class AWSTranscribeSTTService(WebsocketSTTService): final transcription results. """ + _settings: AWSTranscribeSTTSettings + def __init__( self, *, @@ -99,7 +101,7 @@ class AWSTranscribeSTTService(WebsocketSTTService): """ super().__init__(ttfs_p99_latency=ttfs_p99_latency, **kwargs) - self._settings: AWSTranscribeSTTSettings = AWSTranscribeSTTSettings( + self._settings = AWSTranscribeSTTSettings( language=language, sample_rate=sample_rate, media_encoding="linear16", diff --git a/src/pipecat/services/aws/tts.py b/src/pipecat/services/aws/tts.py index 5086b1469..b7f6386ca 100644 --- a/src/pipecat/services/aws/tts.py +++ b/src/pipecat/services/aws/tts.py @@ -150,6 +150,8 @@ class AWSPollyTTSService(TTSService): options including prosody controls. """ + _settings: AWSPollyTTSSettings + class InputParams(BaseModel): """Input parameters for AWS Polly TTS configuration. @@ -206,7 +208,7 @@ class AWSPollyTTSService(TTSService): } self._aws_session = aioboto3.Session() - self._settings: AWSPollyTTSSettings = AWSPollyTTSSettings( + self._settings = AWSPollyTTSSettings( voice=voice_id, engine=params.engine, language=self.language_to_service_language(params.language) diff --git a/src/pipecat/services/azure/stt.py b/src/pipecat/services/azure/stt.py index bf3f70653..95840bde9 100644 --- a/src/pipecat/services/azure/stt.py +++ b/src/pipecat/services/azure/stt.py @@ -71,6 +71,8 @@ class AzureSTTService(STTService): provides real-time transcription results with timing information. """ + _settings: AzureSTTSettings + def __init__( self, *, @@ -107,7 +109,7 @@ class AzureSTTService(STTService): self._audio_stream = None self._speech_recognizer = None - self._settings: AzureSTTSettings = AzureSTTSettings( + self._settings = AzureSTTSettings( region=region, language=language_to_azure_language(language), sample_rate=sample_rate, diff --git a/src/pipecat/services/azure/tts.py b/src/pipecat/services/azure/tts.py index 04b51d10b..ba6d8ac13 100644 --- a/src/pipecat/services/azure/tts.py +++ b/src/pipecat/services/azure/tts.py @@ -100,6 +100,8 @@ class AzureBaseTTSService: This is a mixin class and should be used alongside TTSService or its subclasses. """ + _settings: AzureTTSSettings + # Define SSML escape mappings based on SSML reserved characters # See - https://learn.microsoft.com/en-us/azure/ai-services/speech-service/speech-synthesis-markup-structure SSML_ESCAPE_CHARS = { @@ -153,7 +155,7 @@ class AzureBaseTTSService: """ params = params or AzureBaseTTSService.InputParams() - self._settings: AzureTTSSettings = AzureTTSSettings( + self._settings = AzureTTSSettings( emphasis=params.emphasis, language=self.language_to_service_language(params.language) if params.language diff --git a/src/pipecat/services/camb/tts.py b/src/pipecat/services/camb/tts.py index 8a6f67231..c484a3c80 100644 --- a/src/pipecat/services/camb/tts.py +++ b/src/pipecat/services/camb/tts.py @@ -170,6 +170,8 @@ class CambTTSService(TTSService): ) """ + _settings: CambTTSSettings + class InputParams(BaseModel): """Input parameters for Camb.ai TTS configuration. @@ -226,7 +228,7 @@ class CambTTSService(TTSService): ) # Build settings - self._settings: CambTTSSettings = CambTTSSettings( + self._settings = CambTTSSettings( model=model, voice=voice_id, language=( diff --git a/src/pipecat/services/cartesia/stt.py b/src/pipecat/services/cartesia/stt.py index 624801bfb..7f684f886 100644 --- a/src/pipecat/services/cartesia/stt.py +++ b/src/pipecat/services/cartesia/stt.py @@ -149,6 +149,8 @@ class CartesiaSTTService(WebsocketSTTService): See: https://docs.cartesia.ai/api-reference/stt/stt """ + _settings: CartesiaSTTSettings + def __init__( self, *, @@ -194,7 +196,7 @@ class CartesiaSTTService(WebsocketSTTService): k: v for k, v in merged_options.items() if not isinstance(v, str) or v != "None" } - self._settings: CartesiaSTTSettings = CartesiaSTTSettings( + self._settings = CartesiaSTTSettings( model=merged_options["model"], language=merged_options.get("language"), encoding=merged_options.get("encoding", "pcm_s16le"), diff --git a/src/pipecat/services/cartesia/tts.py b/src/pipecat/services/cartesia/tts.py index 531aafdf7..117853e36 100644 --- a/src/pipecat/services/cartesia/tts.py +++ b/src/pipecat/services/cartesia/tts.py @@ -226,6 +226,8 @@ class CartesiaTTSService(AudioContextWordTTSService): customization options including speed and emotion controls. """ + _settings: CartesiaTTSSettings + class InputParams(BaseModel): """Input parameters for Cartesia TTS configuration. @@ -316,7 +318,7 @@ class CartesiaTTSService(AudioContextWordTTSService): self._api_key = api_key self._cartesia_version = cartesia_version self._url = url - self._settings: CartesiaTTSSettings = CartesiaTTSSettings( + self._settings = CartesiaTTSSettings( output_container=container, output_encoding=encoding, output_sample_rate=0, @@ -655,6 +657,8 @@ class CartesiaHttpTTSService(TTSService): integration is preferred. """ + _settings: CartesiaTTSSettings + class InputParams(BaseModel): """Input parameters for Cartesia HTTP TTS configuration. @@ -712,7 +716,7 @@ class CartesiaHttpTTSService(TTSService): self._api_key = api_key self._base_url = base_url self._cartesia_version = cartesia_version - self._settings: CartesiaTTSSettings = CartesiaTTSSettings( + self._settings = CartesiaTTSSettings( model=model, voice=voice_id, output_container=container, diff --git a/src/pipecat/services/deepgram/stt.py b/src/pipecat/services/deepgram/stt.py index 91d4308cb..2beaec80c 100644 --- a/src/pipecat/services/deepgram/stt.py +++ b/src/pipecat/services/deepgram/stt.py @@ -65,6 +65,8 @@ class DeepgramSTTService(STTService): Supports configurable models, languages, and various audio processing options. """ + _settings: DeepgramSTTSettings + def __init__( self, *, @@ -143,7 +145,7 @@ class DeepgramSTTService(STTService): self.set_model_name(merged_options["model"]) merged_live_options = LiveOptions(**merged_options) - self._settings: DeepgramSTTSettings = DeepgramSTTSettings( + self._settings = DeepgramSTTSettings( model=merged_options.get("model"), language=merged_options.get("language"), live_options=merged_live_options, diff --git a/src/pipecat/services/deepgram/stt_sagemaker.py b/src/pipecat/services/deepgram/stt_sagemaker.py index 95242ade6..68ec9651b 100644 --- a/src/pipecat/services/deepgram/stt_sagemaker.py +++ b/src/pipecat/services/deepgram/stt_sagemaker.py @@ -88,6 +88,8 @@ class DeepgramSageMakerSTTService(STTService): ) """ + _settings: DeepgramSageMakerSTTSettings + def __init__( self, *, @@ -143,7 +145,7 @@ class DeepgramSageMakerSTTService(STTService): self.set_model_name(merged_options["model"]) merged_live_options = LiveOptions(**merged_options) - self._settings: DeepgramSageMakerSTTSettings = DeepgramSageMakerSTTSettings( + self._settings = DeepgramSageMakerSTTSettings( model=merged_options.get("model"), language=merged_options.get("language"), live_options=merged_live_options, diff --git a/src/pipecat/services/deepgram/tts.py b/src/pipecat/services/deepgram/tts.py index 4c698dcea..7ae0fb9ac 100644 --- a/src/pipecat/services/deepgram/tts.py +++ b/src/pipecat/services/deepgram/tts.py @@ -64,6 +64,8 @@ class DeepgramTTSService(WebsocketTTSService): message for conversational AI use cases. """ + _settings: DeepgramTTSSettings + SUPPORTED_ENCODINGS = ("linear16", "mulaw", "alaw") def __init__( @@ -104,7 +106,7 @@ class DeepgramTTSService(WebsocketTTSService): self._api_key = api_key self._base_url = base_url - self._settings: DeepgramTTSSettings = DeepgramTTSSettings( + self._settings = DeepgramTTSSettings( model=voice, voice=voice, encoding=encoding, @@ -345,6 +347,8 @@ class DeepgramHttpTTSService(TTSService): configurable sample rates and quality settings. """ + _settings: DeepgramTTSSettings + def __init__( self, *, @@ -372,7 +376,7 @@ class DeepgramHttpTTSService(TTSService): self._api_key = api_key self._session = aiohttp_session self._base_url = base_url - self._settings: DeepgramTTSSettings = DeepgramTTSSettings( + self._settings = DeepgramTTSSettings( model=voice, voice=voice, encoding=encoding, diff --git a/src/pipecat/services/elevenlabs/stt.py b/src/pipecat/services/elevenlabs/stt.py index 950dc5de9..b33fee710 100644 --- a/src/pipecat/services/elevenlabs/stt.py +++ b/src/pipecat/services/elevenlabs/stt.py @@ -215,6 +215,8 @@ class ElevenLabsSTTService(SegmentedSTTService): The service uploads audio files to ElevenLabs and receives transcription results directly. """ + _settings: ElevenLabsSTTSettings + class InputParams(BaseModel): """Configuration parameters for ElevenLabs STT API. @@ -264,7 +266,7 @@ class ElevenLabsSTTService(SegmentedSTTService): self._session = aiohttp_session self._model_id = model - self._settings: ElevenLabsSTTSettings = ElevenLabsSTTSettings( + self._settings = ElevenLabsSTTSettings( model=model, language=self.language_to_service_language(params.language) if params.language @@ -449,6 +451,8 @@ class ElevenLabsRealtimeSTTService(WebsocketSTTService): commit transcript segments, providing consistency with other STT services. """ + _settings: ElevenLabsRealtimeSTTSettings + class InputParams(BaseModel): """Configuration parameters for ElevenLabs Realtime STT API. @@ -517,7 +521,7 @@ class ElevenLabsRealtimeSTTService(WebsocketSTTService): self._audio_format = "" # initialized in start() self._receive_task = None - self._settings: ElevenLabsRealtimeSTTSettings = ElevenLabsRealtimeSTTSettings( + self._settings = ElevenLabsRealtimeSTTSettings( model=model, language=params.language_code, commit_strategy=params.commit_strategy, diff --git a/src/pipecat/services/elevenlabs/tts.py b/src/pipecat/services/elevenlabs/tts.py index b061383f3..cd3a99e1e 100644 --- a/src/pipecat/services/elevenlabs/tts.py +++ b/src/pipecat/services/elevenlabs/tts.py @@ -321,6 +321,8 @@ class ElevenLabsTTSService(AudioContextWordTTSService): customization options including stability, similarity boost, and speed controls. """ + _settings: ElevenLabsTTSSettings + class InputParams(BaseModel): """Input parameters for ElevenLabs TTS configuration. @@ -401,7 +403,7 @@ class ElevenLabsTTSService(AudioContextWordTTSService): self._api_key = api_key self._url = url - self._settings: ElevenLabsTTSSettings = ElevenLabsTTSSettings( + self._settings = ElevenLabsTTSSettings( model=model, voice=voice_id, language=( @@ -836,6 +838,8 @@ class ElevenLabsHttpTTSService(WordTTSService): connection is not required or desired. """ + _settings: ElevenLabsHttpTTSSettings + class InputParams(BaseModel): """Input parameters for ElevenLabs HTTP TTS configuration. @@ -902,7 +906,7 @@ class ElevenLabsHttpTTSService(WordTTSService): self._params = params self._session = aiohttp_session - self._settings: ElevenLabsHttpTTSSettings = ElevenLabsHttpTTSSettings( + self._settings = ElevenLabsHttpTTSSettings( model=model, voice=voice_id, language=self.language_to_service_language(params.language) diff --git a/src/pipecat/services/fal/stt.py b/src/pipecat/services/fal/stt.py index eef0e0487..a459d15dd 100644 --- a/src/pipecat/services/fal/stt.py +++ b/src/pipecat/services/fal/stt.py @@ -171,6 +171,8 @@ class FalSTTService(SegmentedSTTService): segments. It inherits from SegmentedSTTService to handle audio buffering and speech detection. """ + _settings: FalSTTSettings + class InputParams(BaseModel): """Configuration parameters for Fal's Wizper API. @@ -221,7 +223,7 @@ class FalSTTService(SegmentedSTTService): ) self._fal_client = fal_client.AsyncClient(key=api_key or os.getenv("FAL_KEY")) - self._settings: FalSTTSettings = FalSTTSettings( + self._settings = FalSTTSettings( language=self.language_to_service_language(params.language) if params.language else "en", diff --git a/src/pipecat/services/fish/tts.py b/src/pipecat/services/fish/tts.py index 5517758ad..5c56d0c91 100644 --- a/src/pipecat/services/fish/tts.py +++ b/src/pipecat/services/fish/tts.py @@ -78,6 +78,8 @@ class FishAudioTTSService(InterruptibleTTSService): audio generation with interruption handling. """ + _settings: FishAudioTTSSettings + class InputParams(BaseModel): """Input parameters for Fish Audio TTS configuration. @@ -161,7 +163,7 @@ class FishAudioTTSService(InterruptibleTTSService): self._receive_task = None self._request_id = None - self._settings: FishAudioTTSSettings = FishAudioTTSSettings( + self._settings = FishAudioTTSSettings( voice=reference_id, fish_sample_rate=0, latency=params.latency, diff --git a/src/pipecat/services/gladia/stt.py b/src/pipecat/services/gladia/stt.py index 76a1620e1..d56150a29 100644 --- a/src/pipecat/services/gladia/stt.py +++ b/src/pipecat/services/gladia/stt.py @@ -204,6 +204,8 @@ class GladiaSTTService(WebsocketSTTService): Use :class:`~pipecat.services.gladia.config.GladiaInputParams` directly instead. """ + _settings: GladiaSTTSettings + # Maintain backward compatibility InputParams = _InputParamsDescriptor() diff --git a/src/pipecat/services/google/gemini_live/llm.py b/src/pipecat/services/google/gemini_live/llm.py index 1edab5783..2e8a2efbd 100644 --- a/src/pipecat/services/google/gemini_live/llm.py +++ b/src/pipecat/services/google/gemini_live/llm.py @@ -635,6 +635,8 @@ class GeminiLiveLLMService(LLMService): responses, and tool usage. """ + _settings: GeminiLiveLLMSettings + # Overriding the default adapter to use the Gemini one. adapter_class = GeminiLLMAdapter diff --git a/src/pipecat/services/google/llm.py b/src/pipecat/services/google/llm.py index 692106241..7f6dd724c 100644 --- a/src/pipecat/services/google/llm.py +++ b/src/pipecat/services/google/llm.py @@ -692,6 +692,8 @@ class GoogleLLMService(LLMService): expected by the Google AI model. """ + _settings: GoogleLLMSettings + # Overriding the default adapter to use the Gemini one. adapter_class = GeminiLLMAdapter diff --git a/src/pipecat/services/google/stt.py b/src/pipecat/services/google/stt.py index 8f762da9d..585b766f4 100644 --- a/src/pipecat/services/google/stt.py +++ b/src/pipecat/services/google/stt.py @@ -412,6 +412,8 @@ class GoogleSTTService(STTService): ValueError: If project ID is not found in credentials. """ + _settings: GoogleSTTSettings + # Google Cloud's STT service has a connection time limit of 5 minutes per stream. # They've shared an "endless streaming" example that guided this implementation: # https://cloud.google.com/speech-to-text/docs/transcribe-streaming-audio#endless-streaming diff --git a/src/pipecat/services/google/tts.py b/src/pipecat/services/google/tts.py index d015571d0..46ec96f3e 100644 --- a/src/pipecat/services/google/tts.py +++ b/src/pipecat/services/google/tts.py @@ -547,6 +547,8 @@ class GoogleHttpTTSService(TTSService): Chirp and Journey voices don't support SSML and will use plain text input. """ + _settings: GoogleHttpTTSSettings + class InputParams(BaseModel): """Input parameters for Google HTTP TTS voice customization. @@ -597,7 +599,7 @@ class GoogleHttpTTSService(TTSService): params = params or GoogleHttpTTSService.InputParams() self._location = location - self._settings: GoogleHttpTTSSettings = GoogleHttpTTSSettings( + self._settings = GoogleHttpTTSSettings( pitch=params.pitch, rate=params.rate, speaking_rate=params.speaking_rate, @@ -968,6 +970,8 @@ class GoogleTTSService(GoogleBaseTTSService): ) """ + _settings: GoogleStreamTTSSettings + class InputParams(BaseModel): """Input parameters for Google streaming TTS configuration. @@ -1008,7 +1012,7 @@ class GoogleTTSService(GoogleBaseTTSService): params = params or GoogleTTSService.InputParams() self._location = location - self._settings: GoogleStreamTTSSettings = GoogleStreamTTSSettings( + self._settings = GoogleStreamTTSSettings( language=self.language_to_service_language(params.language) if params.language else "en-US", @@ -1109,6 +1113,8 @@ class GeminiTTSService(GoogleBaseTTSService): ) """ + _settings: GeminiTTSSettings + GOOGLE_SAMPLE_RATE = 24000 # Google TTS always outputs at 24kHz # List of available Gemini TTS voices @@ -1216,7 +1222,7 @@ class GeminiTTSService(GoogleBaseTTSService): self._location = location self._model = model self._voice_id = voice_id - self._settings: GeminiTTSSettings = GeminiTTSSettings( + self._settings = GeminiTTSSettings( language=self.language_to_service_language(params.language) if params.language else "en-US", diff --git a/src/pipecat/services/gradium/stt.py b/src/pipecat/services/gradium/stt.py index 2bad8cf30..ff2002625 100644 --- a/src/pipecat/services/gradium/stt.py +++ b/src/pipecat/services/gradium/stt.py @@ -86,6 +86,8 @@ class GradiumSTTService(WebsocketSTTService): for audio processing and connection management. """ + _settings: GradiumSTTSettings + class InputParams(BaseModel): """Configuration parameters for Gradium STT API. @@ -145,7 +147,7 @@ class GradiumSTTService(WebsocketSTTService): params = params or GradiumSTTService.InputParams() - self._settings: GradiumSTTSettings = GradiumSTTSettings( + self._settings = GradiumSTTSettings( language=params.language, delay_in_frames=params.delay_in_frames if params.delay_in_frames else NOT_GIVEN, ) diff --git a/src/pipecat/services/gradium/tts.py b/src/pipecat/services/gradium/tts.py index e129fba68..5dc355b91 100644 --- a/src/pipecat/services/gradium/tts.py +++ b/src/pipecat/services/gradium/tts.py @@ -53,6 +53,8 @@ class GradiumTTSSettings(TTSSettings): class GradiumTTSService(InterruptibleWordTTSService): """Text-to-Speech service using Gradium's websocket API.""" + _settings: GradiumTTSSettings + class InputParams(BaseModel): """Configuration parameters for Gradium TTS service. @@ -99,7 +101,7 @@ class GradiumTTSService(InterruptibleWordTTSService): self._url = url self._voice_id = voice_id self._json_config = json_config - self._settings: GradiumTTSSettings = GradiumTTSSettings( + self._settings = GradiumTTSSettings( model=model, voice=voice_id, output_format="pcm", diff --git a/src/pipecat/services/grok/realtime/llm.py b/src/pipecat/services/grok/realtime/llm.py index 7cb619a7d..dfe039bbc 100644 --- a/src/pipecat/services/grok/realtime/llm.py +++ b/src/pipecat/services/grok/realtime/llm.py @@ -113,6 +113,8 @@ class GrokRealtimeLLMService(LLMService): - Server-side VAD (Voice Activity Detection) """ + _settings: GrokRealtimeLLMSettings + # Use the Grok-specific adapter adapter_class = GrokRealtimeLLMAdapter diff --git a/src/pipecat/services/groq/tts.py b/src/pipecat/services/groq/tts.py index 678a2426d..8e551725f 100644 --- a/src/pipecat/services/groq/tts.py +++ b/src/pipecat/services/groq/tts.py @@ -57,6 +57,8 @@ class GroqTTSService(TTSService): and output formats. """ + _settings: GroqTTSSettings + class InputParams(BaseModel): """Input parameters for Groq TTS configuration. @@ -109,7 +111,7 @@ class GroqTTSService(TTSService): self._voice_id = voice_id self._params = params - self._settings: GroqTTSSettings = GroqTTSSettings( + self._settings = GroqTTSSettings( model=model_name, voice=voice_id, language=str(params.language) if params.language else "en", diff --git a/src/pipecat/services/hathora/stt.py b/src/pipecat/services/hathora/stt.py index b0e3beead..8af53958d 100644 --- a/src/pipecat/services/hathora/stt.py +++ b/src/pipecat/services/hathora/stt.py @@ -48,6 +48,8 @@ class HathoraSTTService(SegmentedSTTService): [Documentation](https://models.hathora.dev) """ + _settings: HathoraSTTSettings + class InputParams(BaseModel): """Optional input parameters for Hathora STT configuration. @@ -98,7 +100,7 @@ class HathoraSTTService(SegmentedSTTService): params = params or HathoraSTTService.InputParams() - self._settings: HathoraSTTSettings = HathoraSTTSettings( + self._settings = HathoraSTTSettings( model=model, language=params.language, config=params.config, diff --git a/src/pipecat/services/hathora/tts.py b/src/pipecat/services/hathora/tts.py index b821b1e05..2b3a5ddb1 100644 --- a/src/pipecat/services/hathora/tts.py +++ b/src/pipecat/services/hathora/tts.py @@ -68,6 +68,8 @@ class HathoraTTSService(TTSService): [Documentation](https://models.hathora.dev) """ + _settings: HathoraTTSSettings + class InputParams(BaseModel): """Optional input parameters for Hathora TTS configuration. @@ -115,7 +117,7 @@ class HathoraTTSService(TTSService): params = params or HathoraTTSService.InputParams() - self._settings: HathoraTTSSettings = HathoraTTSSettings( + self._settings = HathoraTTSSettings( model=model, voice=voice_id, speed=params.speed, diff --git a/src/pipecat/services/inworld/tts.py b/src/pipecat/services/inworld/tts.py index 68c140187..7f4374b93 100644 --- a/src/pipecat/services/inworld/tts.py +++ b/src/pipecat/services/inworld/tts.py @@ -82,6 +82,8 @@ class InworldHttpTTSService(WordTTSService): Outputs LINEAR16 audio at configurable sample rates with word-level timestamps. """ + _settings: InworldTTSSettings + class InputParams(BaseModel): """Input parameters for Inworld TTS configuration. @@ -138,7 +140,7 @@ class InworldHttpTTSService(WordTTSService): else: self._base_url = "https://api.inworld.ai/tts/v1/voice" - self._settings: InworldTTSSettings = InworldTTSSettings( + self._settings = InworldTTSSettings( model=model, voice=voice_id, audio_encoding=encoding, @@ -438,6 +440,8 @@ class InworldTTSService(AudioContextWordTTSService): with word-level timestamps. """ + _settings: InworldTTSSettings + class InputParams(BaseModel): """Input parameters for Inworld WebSocket TTS configuration. @@ -503,7 +507,7 @@ class InworldTTSService(AudioContextWordTTSService): self._api_key = api_key self._url = url - self._settings: InworldTTSSettings = InworldTTSSettings( + self._settings = InworldTTSSettings( model=model, voice=voice_id, audio_encoding=encoding, diff --git a/src/pipecat/services/kokoro/tts.py b/src/pipecat/services/kokoro/tts.py index 242446de9..6d46441f6 100644 --- a/src/pipecat/services/kokoro/tts.py +++ b/src/pipecat/services/kokoro/tts.py @@ -107,6 +107,8 @@ class KokoroTTSService(TTSService): Automatically downloads model files on first use. """ + _settings: KokoroTTSSettings + class InputParams(BaseModel): """Input parameters for Kokoro TTS configuration. @@ -142,7 +144,7 @@ class KokoroTTSService(TTSService): self._voice_id = voice_id self._lang_code = language_to_kokoro_language(params.language) - self._settings: KokoroTTSSettings = KokoroTTSSettings( + self._settings = KokoroTTSSettings( voice=voice_id, language=language_to_kokoro_language(params.language), lang_code=language_to_kokoro_language(params.language), diff --git a/src/pipecat/services/llm_service.py b/src/pipecat/services/llm_service.py index 3a6e64def..693448cd5 100644 --- a/src/pipecat/services/llm_service.py +++ b/src/pipecat/services/llm_service.py @@ -174,6 +174,8 @@ class LLMService(UserTurnCompletionLLMServiceMixin, AIService): logger.info(f"Starting {len(function_calls)} function calls") """ + _settings: LLMSettings + # OpenAILLMAdapter is used as the default adapter since it aligns with most LLM implementations. # However, subclasses should override this with a more specific adapter when necessary. adapter_class: Type[BaseLLMAdapter] = OpenAILLMAdapter diff --git a/src/pipecat/services/lmnt/tts.py b/src/pipecat/services/lmnt/tts.py index 97569fa1d..9fa727c5f 100644 --- a/src/pipecat/services/lmnt/tts.py +++ b/src/pipecat/services/lmnt/tts.py @@ -92,6 +92,8 @@ class LmntTTSService(InterruptibleTTSService): language settings. """ + _settings: LmntTTSSettings + def __init__( self, *, @@ -122,7 +124,7 @@ class LmntTTSService(InterruptibleTTSService): self._api_key = api_key self._voice_id = voice_id self.set_model_name(model) - self._settings: LmntTTSSettings = LmntTTSSettings( + self._settings = LmntTTSSettings( model=model, voice=voice_id, language=self.language_to_service_language(language), diff --git a/src/pipecat/services/minimax/tts.py b/src/pipecat/services/minimax/tts.py index 6ce3e4b45..db236d6e4 100644 --- a/src/pipecat/services/minimax/tts.py +++ b/src/pipecat/services/minimax/tts.py @@ -132,6 +132,8 @@ class MiniMaxHttpTTSService(TTSService): https://www.minimax.io/platform/document/T2A%20V2?key=66719005a427f0c8a5701643 """ + _settings: MiniMaxTTSSettings + class InputParams(BaseModel): """Configuration parameters for MiniMax TTS. @@ -208,7 +210,7 @@ class MiniMaxHttpTTSService(TTSService): self._voice_id = voice_id # Create voice settings - self._settings: MiniMaxTTSSettings = MiniMaxTTSSettings( + self._settings = MiniMaxTTSSettings( model=model, voice=voice_id, stream=True, diff --git a/src/pipecat/services/neuphonic/tts.py b/src/pipecat/services/neuphonic/tts.py index b7019e6d6..de92c48a2 100644 --- a/src/pipecat/services/neuphonic/tts.py +++ b/src/pipecat/services/neuphonic/tts.py @@ -99,6 +99,8 @@ class NeuphonicTTSService(InterruptibleTTSService): parameters for high-quality speech generation. """ + _settings: NeuphonicTTSSettings + class InputParams(BaseModel): """Input parameters for Neuphonic TTS configuration. @@ -146,7 +148,7 @@ class NeuphonicTTSService(InterruptibleTTSService): self._api_key = api_key self._url = url - self._settings: NeuphonicTTSSettings = NeuphonicTTSSettings( + self._settings = NeuphonicTTSSettings( lang_code=self.language_to_service_language(params.language), speed=params.speed, encoding=encoding, diff --git a/src/pipecat/services/nvidia/stt.py b/src/pipecat/services/nvidia/stt.py index c65d6da62..3a36e062e 100644 --- a/src/pipecat/services/nvidia/stt.py +++ b/src/pipecat/services/nvidia/stt.py @@ -125,6 +125,8 @@ class NvidiaSTTService(STTService): processing for low-latency applications. """ + _settings: NvidiaSTTSettings + class InputParams(BaseModel): """Configuration parameters for NVIDIA Riva STT service. @@ -178,7 +180,7 @@ class NvidiaSTTService(STTService): self._custom_configuration = "" self._function_id = model_function_map.get("function_id") - self._settings: NvidiaSTTSettings = NvidiaSTTSettings( + self._settings = NvidiaSTTSettings( language=params.language, ) @@ -399,6 +401,8 @@ class NvidiaSegmentedSTTService(SegmentedSTTService): audio buffering and speech detection. """ + _settings: NvidiaSegmentedSTTSettings + class InputParams(BaseModel): """Configuration parameters for NVIDIA Riva segmented STT service. @@ -470,7 +474,7 @@ class NvidiaSegmentedSTTService(SegmentedSTTService): self._config = None self._asr_service = None - self._settings: NvidiaSegmentedSTTSettings = NvidiaSegmentedSTTSettings( + self._settings = NvidiaSegmentedSTTSettings( language=params.language or Language.EN_US, profanity_filter=params.profanity_filter, automatic_punctuation=params.automatic_punctuation, diff --git a/src/pipecat/services/openai/base_llm.py b/src/pipecat/services/openai/base_llm.py index 2ac53794c..454087508 100644 --- a/src/pipecat/services/openai/base_llm.py +++ b/src/pipecat/services/openai/base_llm.py @@ -70,6 +70,8 @@ class BaseOpenAILLMService(LLMService): configurations. """ + _settings: OpenAILLMSettings + class InputParams(BaseModel): """Input parameters for OpenAI model configuration. diff --git a/src/pipecat/services/openai/realtime/llm.py b/src/pipecat/services/openai/realtime/llm.py index abd66963b..825639950 100644 --- a/src/pipecat/services/openai/realtime/llm.py +++ b/src/pipecat/services/openai/realtime/llm.py @@ -110,6 +110,8 @@ class OpenAIRealtimeLLMService(LLMService): management, and real-time transcription. """ + _settings: OpenAIRealtimeLLMSettings + # Overriding the default adapter to use the OpenAIRealtimeLLMAdapter one. adapter_class = OpenAIRealtimeLLMAdapter diff --git a/src/pipecat/services/openai/stt.py b/src/pipecat/services/openai/stt.py index 12eada24e..266b2964b 100644 --- a/src/pipecat/services/openai/stt.py +++ b/src/pipecat/services/openai/stt.py @@ -169,6 +169,8 @@ class OpenAIRealtimeSTTService(WebsocketSTTService): ) """ + _settings: OpenAIRealtimeSTTSettings + def __init__( self, *, @@ -231,7 +233,7 @@ class OpenAIRealtimeSTTService(WebsocketSTTService): self._noise_reduction = noise_reduction self._should_interrupt = should_interrupt - self._settings: OpenAIRealtimeSTTSettings = OpenAIRealtimeSTTSettings( + self._settings = OpenAIRealtimeSTTSettings( model=model, language=language, prompt=prompt, diff --git a/src/pipecat/services/openai/tts.py b/src/pipecat/services/openai/tts.py index ee1e34316..3572d287e 100644 --- a/src/pipecat/services/openai/tts.py +++ b/src/pipecat/services/openai/tts.py @@ -83,6 +83,8 @@ class OpenAITTSService(TTSService): speech synthesis with streaming audio output. """ + _settings: OpenAITTSSettings + OPENAI_SAMPLE_RATE = 24000 # OpenAI TTS always outputs at 24kHz class InputParams(BaseModel): @@ -147,7 +149,7 @@ class OpenAITTSService(TTSService): stacklevel=2, ) - self._settings: OpenAITTSSettings = OpenAITTSSettings( + self._settings = OpenAITTSSettings( model=model, voice=voice, instructions=params.instructions if params else instructions, diff --git a/src/pipecat/services/openai_realtime_beta/openai.py b/src/pipecat/services/openai_realtime_beta/openai.py index d37b1434e..b7703ad98 100644 --- a/src/pipecat/services/openai_realtime_beta/openai.py +++ b/src/pipecat/services/openai_realtime_beta/openai.py @@ -115,6 +115,8 @@ class OpenAIRealtimeBetaLLMService(LLMService): management, and real-time transcription. """ + _settings: OpenAIRealtimeBetaLLMSettings + # Overriding the default adapter to use the OpenAIRealtimeLLMAdapter one. adapter_class = OpenAIRealtimeLLMAdapter diff --git a/src/pipecat/services/playht/tts.py b/src/pipecat/services/playht/tts.py index f79f54560..7d61ffd87 100644 --- a/src/pipecat/services/playht/tts.py +++ b/src/pipecat/services/playht/tts.py @@ -131,6 +131,8 @@ class PlayHTTTSService(InterruptibleTTSService): language settings. """ + _settings: PlayHTTTSSettings + class InputParams(BaseModel): """Input parameters for PlayHT TTS configuration. @@ -191,7 +193,7 @@ class PlayHTTTSService(InterruptibleTTSService): self._receive_task = None self._context_id = None - self._settings: PlayHTTTSSettings = PlayHTTTSSettings( + self._settings = PlayHTTTSSettings( model=voice_engine, voice=voice_url, language=self.language_to_service_language(params.language) @@ -444,6 +446,8 @@ class PlayHTHttpTTSService(TTSService): required and simpler integration is preferred. """ + _settings: PlayHTTTSSettings + class InputParams(BaseModel): """Input parameters for PlayHT HTTP TTS configuration. @@ -522,7 +526,7 @@ class PlayHTHttpTTSService(TTSService): # Extract the base engine name voice_engine = voice_engine.replace("-ws", "") - self._settings: PlayHTTTSSettings = PlayHTTTSSettings( + self._settings = PlayHTTTSSettings( voice=voice_url, language=self.language_to_service_language(params.language) if params.language diff --git a/src/pipecat/services/resembleai/tts.py b/src/pipecat/services/resembleai/tts.py index 08f9b81bd..cd3da1767 100644 --- a/src/pipecat/services/resembleai/tts.py +++ b/src/pipecat/services/resembleai/tts.py @@ -63,6 +63,8 @@ class ResembleAITTSService(AudioContextWordTTSService): multiple simultaneous synthesis requests with proper interruption support. """ + _settings: ResembleAITTSSettings + def __init__( self, *, @@ -93,7 +95,7 @@ class ResembleAITTSService(AudioContextWordTTSService): self._api_key = api_key self._voice_id = voice_id self._url = url - self._settings: ResembleAITTSSettings = ResembleAITTSSettings( + self._settings = ResembleAITTSSettings( voice=voice_id, precision=precision, output_format=output_format, diff --git a/src/pipecat/services/rime/tts.py b/src/pipecat/services/rime/tts.py index 5a3ed67a2..4af9fe63b 100644 --- a/src/pipecat/services/rime/tts.py +++ b/src/pipecat/services/rime/tts.py @@ -134,6 +134,8 @@ class RimeTTSService(AudioContextWordTTSService): within a turn. """ + _settings: RimeTTSSettings + class InputParams(BaseModel): """Configuration parameters for Rime TTS service. @@ -207,7 +209,7 @@ class RimeTTSService(AudioContextWordTTSService): self._url = url self._voice_id = voice_id self._model = model - self._settings: RimeTTSSettings = RimeTTSSettings( + self._settings = RimeTTSSettings( speaker=voice_id, modelId=model, audioFormat="pcm", @@ -537,6 +539,8 @@ class RimeHttpTTSService(TTSService): Suitable for use cases where streaming is not required. """ + _settings: RimeTTSSettings + class InputParams(BaseModel): """Configuration parameters for Rime HTTP TTS service. @@ -585,7 +589,7 @@ class RimeHttpTTSService(TTSService): self._api_key = api_key self._session = aiohttp_session self._base_url = "https://users.rime.ai/v1/rime-tts" - self._settings: RimeTTSSettings = RimeTTSSettings( + self._settings = RimeTTSSettings( lang=self.language_to_service_language(params.language) if params.language else "eng", speedAlpha=params.speed_alpha, reduceLatency=params.reduce_latency, @@ -706,6 +710,8 @@ class RimeNonJsonTTSService(InterruptibleTTSService): future. This service focuses on the current plain text protocol. """ + _settings: RimeNonJsonTTSSettings + class InputParams(BaseModel): """Configuration parameters for Rime Non-JSON WebSocket TTS service. @@ -763,7 +769,7 @@ class RimeNonJsonTTSService(InterruptibleTTSService): self._url = url self._voice_id = voice_id self._model = model - self._settings: RimeNonJsonTTSSettings = RimeNonJsonTTSSettings( + self._settings = RimeNonJsonTTSSettings( speaker=voice_id, modelId=model, audioFormat=audio_format, diff --git a/src/pipecat/services/sarvam/stt.py b/src/pipecat/services/sarvam/stt.py index e2bc6a08f..834171b32 100644 --- a/src/pipecat/services/sarvam/stt.py +++ b/src/pipecat/services/sarvam/stt.py @@ -154,6 +154,8 @@ class SarvamSTTService(STTService): Provides real-time speech recognition using Sarvam's WebSocket API. """ + _settings: SarvamSTTSettings + class InputParams(BaseModel): """Configuration parameters for Sarvam STT service. @@ -247,7 +249,7 @@ class SarvamSTTService(STTService): # Resolve mode default from model config mode = params.mode if params.mode is not None else self._config.default_mode - self._settings: SarvamSTTSettings = SarvamSTTSettings( + self._settings = SarvamSTTSettings( model=model, language=params.language, prompt=params.prompt if params.prompt is not None else NOT_GIVEN, diff --git a/src/pipecat/services/sarvam/tts.py b/src/pipecat/services/sarvam/tts.py index e28914b4c..ec51a85d5 100644 --- a/src/pipecat/services/sarvam/tts.py +++ b/src/pipecat/services/sarvam/tts.py @@ -371,6 +371,8 @@ class SarvamHttpTTSService(TTSService): ) """ + _settings: SarvamHttpTTSSettings + class InputParams(BaseModel): """Input parameters for Sarvam TTS configuration. @@ -478,7 +480,7 @@ class SarvamHttpTTSService(TTSService): pace = max(pace_min, min(pace_max, pace)) # Build base settings - self._settings: SarvamHttpTTSSettings = SarvamHttpTTSSettings( + self._settings = SarvamHttpTTSSettings( language=( self.language_to_service_language(params.language) if params.language else "en-IN" ), @@ -684,6 +686,8 @@ class SarvamTTSService(InterruptibleTTSService): See https://docs.sarvam.ai/api-reference-docs/text-to-speech/stream for API details. """ + _settings: SarvamWSTTSSettings + class InputParams(BaseModel): """Configuration parameters for Sarvam TTS WebSocket service. @@ -837,7 +841,7 @@ class SarvamTTSService(InterruptibleTTSService): pace = max(pace_min, min(pace_max, pace)) # Build base settings - self._settings: SarvamWSTTSSettings = SarvamWSTTSSettings( + self._settings = SarvamWSTTSSettings( target_language_code=( self.language_to_service_language(params.language) if params.language else "en-IN" ), diff --git a/src/pipecat/services/soniox/stt.py b/src/pipecat/services/soniox/stt.py index 9d732a356..c3d9638c1 100644 --- a/src/pipecat/services/soniox/stt.py +++ b/src/pipecat/services/soniox/stt.py @@ -157,6 +157,8 @@ class SonioxSTTService(WebsocketSTTService): For complete API documentation, see: https://soniox.com/docs/speech-to-text/api-reference/websocket-api """ + _settings: SonioxSTTSettings + def __init__( self, *, diff --git a/src/pipecat/services/speechmatics/stt.py b/src/pipecat/services/speechmatics/stt.py index d04bb564d..462c2fc6f 100644 --- a/src/pipecat/services/speechmatics/stt.py +++ b/src/pipecat/services/speechmatics/stt.py @@ -166,6 +166,8 @@ class SpeechmaticsSTTService(STTService): and speaker diarization. """ + _settings: SpeechmaticsSTTSettings + # Export related classes as class attributes TurnDetectionMode = TurnDetectionMode AudioEncoding = AudioEncoding diff --git a/src/pipecat/services/stt_service.py b/src/pipecat/services/stt_service.py index d4e5f4cb5..22cd4f03d 100644 --- a/src/pipecat/services/stt_service.py +++ b/src/pipecat/services/stt_service.py @@ -70,6 +70,8 @@ class STTService(AIService): logger.error(f"STT connection error: {error}") """ + _settings: STTSettings + def __init__( self, *, diff --git a/src/pipecat/services/tts_service.py b/src/pipecat/services/tts_service.py index 4196e7872..49bb29970 100644 --- a/src/pipecat/services/tts_service.py +++ b/src/pipecat/services/tts_service.py @@ -104,6 +104,8 @@ class TTSService(AIService): logger.debug(f"TTS request: {context_id} - {text}") """ + _settings: TTSSettings + def __init__( self, *, diff --git a/src/pipecat/services/ultravox/llm.py b/src/pipecat/services/ultravox/llm.py index 9f0658486..6f5e5d2ee 100644 --- a/src/pipecat/services/ultravox/llm.py +++ b/src/pipecat/services/ultravox/llm.py @@ -158,6 +158,8 @@ class UltravoxRealtimeLLMService(LLMService): by the model and may not always align with its understanding of user input. """ + _settings: UltravoxRealtimeLLMSettings + def __init__( self, *, diff --git a/src/pipecat/services/whisper/base_stt.py b/src/pipecat/services/whisper/base_stt.py index 2a02c6ce7..6c35824a4 100644 --- a/src/pipecat/services/whisper/base_stt.py +++ b/src/pipecat/services/whisper/base_stt.py @@ -124,6 +124,8 @@ class BaseWhisperSTTService(SegmentedSTTService): including metrics generation and error handling. """ + _settings: BaseWhisperSTTSettings + def __init__( self, *, @@ -161,7 +163,7 @@ class BaseWhisperSTTService(SegmentedSTTService): self._temperature = temperature self._include_prob_metrics = include_prob_metrics - self._settings: BaseWhisperSTTSettings = BaseWhisperSTTSettings( + self._settings = BaseWhisperSTTSettings( model=model, language=self._language, base_url=base_url, diff --git a/src/pipecat/services/whisper/stt.py b/src/pipecat/services/whisper/stt.py index 30451e6d0..d5f4c3f1b 100644 --- a/src/pipecat/services/whisper/stt.py +++ b/src/pipecat/services/whisper/stt.py @@ -211,6 +211,8 @@ class WhisperSTTService(SegmentedSTTService): segments. It supports multiple languages and various model sizes. """ + _settings: WhisperSTTSettings + def __init__( self, *, @@ -238,7 +240,7 @@ class WhisperSTTService(SegmentedSTTService): self._no_speech_prob = no_speech_prob self._model: Optional[WhisperModel] = None - self._settings: WhisperSTTSettings = WhisperSTTSettings( + self._settings = WhisperSTTSettings( model=model if isinstance(model, str) else model.value, language=language, device=self._device, @@ -346,6 +348,8 @@ class WhisperSTTServiceMLX(WhisperSTTService): segments. It's optimized for Apple Silicon and supports multiple languages and quantizations. """ + _settings: WhisperMLXSTTSettings + def __init__( self, *, @@ -371,7 +375,7 @@ class WhisperSTTServiceMLX(WhisperSTTService): self._no_speech_prob = no_speech_prob self._temperature = temperature - self._settings: WhisperMLXSTTSettings = WhisperMLXSTTSettings( + self._settings = WhisperMLXSTTSettings( model=model if isinstance(model, str) else model.value, language=language, no_speech_prob=self._no_speech_prob, diff --git a/src/pipecat/services/xtts/tts.py b/src/pipecat/services/xtts/tts.py index 664d3d4be..4415f9f53 100644 --- a/src/pipecat/services/xtts/tts.py +++ b/src/pipecat/services/xtts/tts.py @@ -89,6 +89,8 @@ class XTTSService(TTSService): studio speakers configuration. """ + _settings: XTTSTTSSettings + def __init__( self, *, @@ -111,7 +113,7 @@ class XTTSService(TTSService): """ super().__init__(sample_rate=sample_rate, **kwargs) - self._settings: XTTSTTSSettings = XTTSTTSSettings( + self._settings = XTTSTTSSettings( voice=voice_id, language=self.language_to_service_language(language), base_url=base_url, From e37f2f99c473350de24f2ec3e52f98132fbc2c19 Mon Sep 17 00:00:00 2001 From: Paul Kompfner Date: Fri, 13 Feb 2026 11:39:34 -0500 Subject: [PATCH 0487/1060] Deprecate `set_model`, `set_voice`, and `set_language` in favor of `*UpdateSettingsFrame`. --- src/pipecat/services/stt_service.py | 25 +++++++++++++++++++------ src/pipecat/services/tts_service.py | 29 +++++++++++++++++++---------- 2 files changed, 38 insertions(+), 16 deletions(-) diff --git a/src/pipecat/services/stt_service.py b/src/pipecat/services/stt_service.py index 22cd4f03d..3ce143d92 100644 --- a/src/pipecat/services/stt_service.py +++ b/src/pipecat/services/stt_service.py @@ -9,6 +9,7 @@ import asyncio import io import time +import warnings import wave from abc import abstractmethod from typing import Any, AsyncGenerator, Dict, Mapping, Optional @@ -168,13 +169,19 @@ class STTService(AIService): async def set_model(self, model: str): """Set the speech recognition model. - When the service has been migrated to typed settings this routes - through :meth:`_update_settings_from_typed` so that concrete - services can react (e.g. reconnect) in a single place. + .. deprecated:: 0.0.103 + Use ``STTUpdateSettingsFrame(model=...)`` instead. Args: model: The name of the model to use for speech recognition. """ + with warnings.catch_warnings(): + warnings.simplefilter("always") + warnings.warn( + "'set_model' is deprecated, use 'STTUpdateSettingsFrame(model=...)' instead.", + DeprecationWarning, + stacklevel=2, + ) logger.info(f"Switching STT model to: [{model}]") if isinstance(self._settings, ServiceSettings): settings_cls = type(self._settings) @@ -185,13 +192,19 @@ class STTService(AIService): async def set_language(self, language: Language): """Set the language for speech recognition. - When the service has been migrated to typed settings this routes - through :meth:`_update_settings_from_typed` so that concrete - services can react (e.g. reconnect) in a single place. + .. deprecated:: 0.0.103 + Use ``STTUpdateSettingsFrame(language=...)`` instead. Args: language: The language to use for speech recognition. """ + with warnings.catch_warnings(): + warnings.simplefilter("always") + warnings.warn( + "'set_language' is deprecated, use 'STTUpdateSettingsFrame(language=...)' instead.", + DeprecationWarning, + stacklevel=2, + ) logger.info(f"Switching STT language to: [{language}]") if isinstance(self._settings, ServiceSettings): settings_cls = type(self._settings) diff --git a/src/pipecat/services/tts_service.py b/src/pipecat/services/tts_service.py index 49bb29970..b16ebdb24 100644 --- a/src/pipecat/services/tts_service.py +++ b/src/pipecat/services/tts_service.py @@ -8,6 +8,7 @@ import asyncio import uuid +import warnings from abc import abstractmethod from dataclasses import dataclass from typing import ( @@ -265,13 +266,19 @@ class TTSService(AIService): async def set_model(self, model: str): """Set the TTS model to use. - When the service has been migrated to typed settings this routes - through :meth:`_update_settings_from_typed` so that concrete - services can react (e.g. reconnect) in a single place. + .. deprecated:: 0.0.103 + Use ``TTSUpdateSettingsFrame(model=...)`` instead. Args: model: The name of the TTS model. """ + with warnings.catch_warnings(): + warnings.simplefilter("always") + warnings.warn( + "'set_model' is deprecated, use 'TTSUpdateSettingsFrame(model=...)' instead.", + DeprecationWarning, + stacklevel=2, + ) logger.info(f"Switching TTS model to: [{model}]") if isinstance(self._settings, ServiceSettings): settings_cls = type(self._settings) @@ -282,17 +289,19 @@ class TTSService(AIService): async def set_voice(self, voice: str): """Set the voice for speech synthesis. - When the service has been migrated to typed settings this routes - through :meth:`_update_settings_from_typed` so that concrete - services can react (e.g. reconnect) in a single place. - - .. versionchanged:: 0.0.103 - Now ``async``. In ``__init__`` methods, set - ``self._voice_id`` directly instead of calling this method. + .. deprecated:: 0.0.103 + Use ``TTSUpdateSettingsFrame(voice=...)`` instead. Args: voice: The voice identifier or name. """ + with warnings.catch_warnings(): + warnings.simplefilter("always") + warnings.warn( + "'set_voice' is deprecated, use 'TTSUpdateSettingsFrame(voice=...)' instead.", + DeprecationWarning, + stacklevel=2, + ) logger.info(f"Switching TTS voice to: [{voice}]") if isinstance(self._settings, ServiceSettings): settings_cls = type(self._settings) From ab92a0e1d7ca7b1a8b1dca558218a1054a71489c Mon Sep 17 00:00:00 2001 From: Paul Kompfner Date: Fri, 13 Feb 2026 12:09:31 -0500 Subject: [PATCH 0488/1060] Remove/deprecate service-specific `set_model` and `set_voice` overrides. MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit - NvidiaSTTService.set_model: convert to proper DeprecationWarning (model can't change at runtime for Riva streaming STT) - NvidiaTTSService.set_model: same treatment for Riva TTS - NvidiaSegmentedSTTService.set_model: remove — base class now routes through _update_settings_from_typed which re-creates the recognition config - GeminiTTSService.set_voice: remove — move AVAILABLE_VOICES validation into _update_settings_from_typed so it fires on both legacy and new paths --- src/pipecat/services/google/tts.py | 20 +++++-------- src/pipecat/services/nvidia/stt.py | 47 ++++++++++++++---------------- src/pipecat/services/nvidia/tts.py | 30 ++++++++++++++----- 3 files changed, 52 insertions(+), 45 deletions(-) diff --git a/src/pipecat/services/google/tts.py b/src/pipecat/services/google/tts.py index 46ec96f3e..2b9ada224 100644 --- a/src/pipecat/services/google/tts.py +++ b/src/pipecat/services/google/tts.py @@ -1246,16 +1246,6 @@ class GeminiTTSService(GoogleBaseTTSService): """ return language_to_gemini_tts_language(language) - async def set_voice(self, voice_id: str): - """Set the voice for TTS generation. - - Args: - voice_id: Name of the voice to use from AVAILABLE_VOICES. - """ - if voice_id not in self.AVAILABLE_VOICES: - logger.warning(f"Voice '{voice_id}' not in known voices list. Using anyway.") - self._voice_id = voice_id - async def start(self, frame: StartFrame): """Start the Gemini TTS service. @@ -1270,11 +1260,17 @@ class GeminiTTSService(GoogleBaseTTSService): ) async def _update_settings_from_typed(self, update: TTSSettings) -> set[str]: - """Override to handle prompt updates. + """Apply a typed settings update with voice validation. Args: - update: Typed settings delta. Can include 'prompt' (str). + update: Typed settings delta. Can include 'voice', 'prompt', etc. + + Returns: + Set of field names whose values actually changed. """ + if is_given(update.voice) and update.voice not in self.AVAILABLE_VOICES: + logger.warning(f"Voice '{update.voice}' not in known voices list. Using anyway.") + return await super()._update_settings_from_typed(update) @traced_tts diff --git a/src/pipecat/services/nvidia/stt.py b/src/pipecat/services/nvidia/stt.py index 3a36e062e..6190e169d 100644 --- a/src/pipecat/services/nvidia/stt.py +++ b/src/pipecat/services/nvidia/stt.py @@ -241,18 +241,31 @@ class NvidiaSTTService(STTService): async def set_model(self, model: str): """Set the ASR model for transcription. + .. deprecated:: 0.0.103 + Model cannot be changed after initialization for NVIDIA Riva streaming STT. + Set model and function id in the constructor instead, e.g.:: + + NvidiaSTTService( + api_key=..., + model_function_map={"function_id": "", "model_name": ""}, + ) + Args: model: Model name to set. - - Note: - Model cannot be changed after initialization. Use model_function_map - parameter in constructor instead. """ - logger.warning(f"Cannot set model after initialization. Set model and function id like so:") - example = {"function_id": "", "model_name": ""} - logger.warning( - f"{self.__class__.__name__}(api_key=, model_function_map={example})" - ) + import warnings + + with warnings.catch_warnings(): + warnings.simplefilter("always") + warnings.warn( + "'set_model' is deprecated. Model cannot be changed after initialization" + " for NVIDIA Riva streaming STT. Set model and function id in the" + " constructor instead, e.g.:" + " NvidiaSTTService(api_key=..., model_function_map=" + "{'function_id': '', 'model_name': ''})", + DeprecationWarning, + stacklevel=2, + ) async def start(self, frame: StartFrame): """Start the NVIDIA Riva STT service and initialize streaming configuration. @@ -555,22 +568,6 @@ class NvidiaSegmentedSTTService(SegmentedSTTService): """ return True - async def set_model(self, model: str): - """Set the ASR model for transcription. - - Args: - model: Model name to set. - - Note: - Model cannot be changed after initialization. Use model_function_map - parameter in constructor instead. - """ - logger.warning(f"Cannot set model after initialization. Set model and function id like so:") - example = {"function_id": "", "model_name": ""} - logger.warning( - f"{self.__class__.__name__}(api_key=, model_function_map={example})" - ) - async def start(self, frame: StartFrame): """Initialize the service when the pipeline starts. diff --git a/src/pipecat/services/nvidia/tts.py b/src/pipecat/services/nvidia/tts.py index 8a018d6aa..27ace15fb 100644 --- a/src/pipecat/services/nvidia/tts.py +++ b/src/pipecat/services/nvidia/tts.py @@ -106,18 +106,32 @@ class NvidiaTTSService(TTSService): self._config = None async def set_model(self, model: str): - """Attempt to set the TTS model. + """Set the TTS model. - Note: Model cannot be changed after initialization for Riva service. + .. deprecated:: 0.0.103 + Model cannot be changed after initialization for NVIDIA Riva TTS. + Set model and function id in the constructor instead, e.g.:: + + NvidiaTTSService( + api_key=..., + model_function_map={"function_id": "", "model_name": ""}, + ) Args: - model: The model name to set (operation not supported). + model: The model name to set. """ - logger.warning(f"Cannot set model after initialization. Set model and function id like so:") - example = {"function_id": "", "model_name": ""} - logger.warning( - f"{self.__class__.__name__}(api_key=, model_function_map={example})" - ) + import warnings + + with warnings.catch_warnings(): + warnings.simplefilter("always") + warnings.warn( + "'set_model' is deprecated. Model cannot be changed after initialization" + " for NVIDIA Riva TTS. Set model and function id in the constructor" + " instead, e.g.: NvidiaTTSService(api_key=..., model_function_map=" + "{'function_id': '', 'model_name': ''})", + DeprecationWarning, + stacklevel=2, + ) def _initialize_client(self): if self._service is not None: From b08548af9dc65227df7c49b26c46b43509e5bb13 Mon Sep 17 00:00:00 2001 From: Paul Kompfner Date: Fri, 13 Feb 2026 14:30:49 -0500 Subject: [PATCH 0489/1060] Remove typed-settings migration scaffolding and rename `_update_settings_from_typed` to `_update_settings`. Now that all services use typed `ServiceSettings` objects, this removes the interim scaffolding that supported both dict-based and typed settings paths in parallel. Specifically: removes old dict-based `_update_settings(settings: Mapping)` methods from base classes, removes `isinstance(self._settings, ServiceSettings)` guards, simplifies `process_frame` branching, and renames `_update_settings_from_typed` to `_update_settings` across all ~30 service implementations. Also renames the no-arg `_update_settings()` helper on realtime services to `_send_session_update()` to avoid collision, adds `from_mapping` overrides on `GoogleLLMSettings` and `AnthropicLLMSettings` for ThinkingConfig dict-to-object conversion, and replaces a broken no-arg `_update_settings()` call in Gemini Live with a TODO. --- src/pipecat/frames/frames.py | 8 +-- src/pipecat/services/ai_service.py | 69 +++---------------- src/pipecat/services/anthropic/llm.py | 16 ++++- src/pipecat/services/assemblyai/stt.py | 8 +-- src/pipecat/services/asyncai/tts.py | 2 +- src/pipecat/services/aws/llm.py | 2 +- src/pipecat/services/aws/stt.py | 8 +-- src/pipecat/services/aws/tts.py | 2 +- src/pipecat/services/azure/stt.py | 8 +-- src/pipecat/services/azure/tts.py | 2 +- src/pipecat/services/camb/tts.py | 2 +- src/pipecat/services/cartesia/stt.py | 8 +-- src/pipecat/services/cartesia/tts.py | 2 +- src/pipecat/services/deepgram/stt.py | 8 +-- .../services/deepgram/stt_sagemaker.py | 8 +-- src/pipecat/services/deepgram/tts.py | 2 +- src/pipecat/services/elevenlabs/stt.py | 16 ++--- src/pipecat/services/elevenlabs/tts.py | 18 ++--- src/pipecat/services/fal/stt.py | 8 +-- src/pipecat/services/fish/tts.py | 8 +-- src/pipecat/services/gladia/stt.py | 10 +-- .../services/google/gemini_live/llm.py | 5 +- src/pipecat/services/google/llm.py | 24 ++++--- src/pipecat/services/google/stt.py | 16 ++--- src/pipecat/services/google/tts.py | 26 +++---- src/pipecat/services/gradium/stt.py | 8 +-- src/pipecat/services/gradium/tts.py | 8 +-- src/pipecat/services/grok/realtime/llm.py | 28 ++++---- src/pipecat/services/groq/tts.py | 2 +- src/pipecat/services/hathora/stt.py | 2 +- src/pipecat/services/hathora/tts.py | 2 +- src/pipecat/services/inworld/tts.py | 2 +- src/pipecat/services/kokoro/tts.py | 2 +- src/pipecat/services/llm_service.py | 51 +++----------- src/pipecat/services/lmnt/tts.py | 2 +- src/pipecat/services/minimax/tts.py | 2 +- src/pipecat/services/neuphonic/tts.py | 8 +-- src/pipecat/services/nvidia/stt.py | 10 +-- src/pipecat/services/openai/base_llm.py | 2 +- src/pipecat/services/openai/realtime/llm.py | 28 ++++---- src/pipecat/services/openai/stt.py | 10 +-- src/pipecat/services/openai/tts.py | 2 +- .../services/openai_realtime_beta/openai.py | 28 ++++---- src/pipecat/services/playht/tts.py | 2 +- src/pipecat/services/resembleai/tts.py | 2 +- src/pipecat/services/rime/tts.py | 16 ++--- src/pipecat/services/sarvam/stt.py | 8 +-- src/pipecat/services/sarvam/tts.py | 10 +-- src/pipecat/services/settings.py | 26 +++---- src/pipecat/services/soniox/stt.py | 10 +-- src/pipecat/services/speechmatics/stt.py | 12 ++-- src/pipecat/services/stt_service.py | 53 ++++---------- src/pipecat/services/tts_service.py | 56 ++++----------- src/pipecat/services/ultravox/llm.py | 4 +- src/pipecat/services/whisper/base_stt.py | 10 +-- src/pipecat/services/whisper/stt.py | 4 +- src/pipecat/services/xtts/tts.py | 2 +- 57 files changed, 291 insertions(+), 407 deletions(-) diff --git a/src/pipecat/frames/frames.py b/src/pipecat/frames/frames.py index dd12929b9..be3b4e4a7 100644 --- a/src/pipecat/frames/frames.py +++ b/src/pipecat/frames/frames.py @@ -2113,13 +2113,13 @@ class TTSStoppedFrame(ControlFrame): class ServiceUpdateSettingsFrame(ControlFrame): """Base frame for updating service settings. - Supports both the legacy ``settings`` dict and the new typed ``update`` - object. When both are provided, ``update`` takes precedence. + Supports both a ``settings`` dict (for backward compatibility) and an + ``update`` object. When both are provided, ``update`` takes precedence. Parameters: settings: Dictionary of setting name to value mappings (legacy). - update: Typed :class:`~pipecat.services.settings.ServiceSettings` - object describing the delta to apply. + update: :class:`~pipecat.services.settings.ServiceSettings` object + describing the delta to apply. """ settings: Mapping[str, Any] = field(default_factory=dict) diff --git a/src/pipecat/services/ai_service.py b/src/pipecat/services/ai_service.py index 97b7b6443..2c6c10be4 100644 --- a/src/pipecat/services/ai_service.py +++ b/src/pipecat/services/ai_service.py @@ -10,7 +10,7 @@ Provides the foundation for all AI services in the Pipecat framework, including model management, settings handling, and frame processing lifecycle methods. """ -from typing import Any, AsyncGenerator, Dict, Mapping, Set +from typing import Any, AsyncGenerator, Dict, Set from loguru import logger @@ -43,7 +43,7 @@ class AIService(FrameProcessor): """ super().__init__(**kwargs) self._model_name: str = "" - self._settings: Dict[str, Any] | ServiceSettings = {} + self._settings: ServiceSettings = ServiceSettings() self._session_properties: Dict[str, Any] = {} @property @@ -97,71 +97,22 @@ class AIService(FrameProcessor): """ pass - async def _update_settings(self, settings: Mapping[str, Any]): - from pipecat.services.openai.realtime.events import SessionProperties + async def _update_settings(self, update: ServiceSettings) -> Set[str]: + """Apply a settings update and return the set of changed field names. - for key, value in settings.items(): - logger.debug("Update request for:", key, value) + The update is applied to ``_settings`` and the changed-field set is + returned. The ``model`` field is handled specially: when it changes, + ``set_model_name`` is called. - if key in self._settings: - logger.info(f"Updating LLM setting {key} to: [{value}]") - self._settings[key] = value - elif key in SessionProperties.model_fields: - logger.debug("Attempting to update", key, value) - - try: - from pipecat.services.openai.realtime.events import TurnDetection - - if isinstance(self._session_properties, SessionProperties): - current_properties = self._session_properties - else: - current_properties = SessionProperties(**self._session_properties) - - if key == "turn_detection" and isinstance(value, dict): - turn_detection = TurnDetection(**value) - setattr(current_properties, key, turn_detection) - else: - setattr(current_properties, key, value) - - validated_properties = SessionProperties.model_validate( - current_properties.model_dump() - ) - logger.info(f"Updating LLM setting {key} to: [{value}]") - self._session_properties = validated_properties.model_dump() - except Exception as e: - logger.warning(f"Unexpected error updating session property {key}: {e}") - elif key == "model": - logger.info(f"Updating LLM setting {key} to: [{value}]") - self.set_model_name(value) - else: - logger.warning(f"Unknown setting for {self.name} service: {key}") - - async def _update_settings_from_typed(self, update: ServiceSettings) -> Set[str]: - """Apply a typed settings update and return the set of changed field names. - - If ``_settings`` is a :class:`ServiceSettings` object, the update is - applied to it and the changed-field set is returned. The ``model`` - field is handled specially: when it changes, ``set_model_name`` is - called. - - Services that have been migrated to typed settings should override - this method (calling ``super()``) to react to specific changed fields - (e.g. reconnect on voice change). + Concrete services should override this method (calling ``super()``) + to react to specific changed fields (e.g. reconnect on voice change). Args: - update: A typed settings delta. + update: A settings delta. Returns: Set of field names whose values actually changed. """ - if not isinstance(self._settings, ServiceSettings): - logger.warning( - f"{self.name}: received typed settings update but _settings " - f"is not a ServiceSettings — falling back to dict-based update" - ) - await self._update_settings(update.to_dict()) - return set() - changed = self._settings.apply_update(update) if "model" in changed: diff --git a/src/pipecat/services/anthropic/llm.py b/src/pipecat/services/anthropic/llm.py index 25611d0d1..159b666d1 100644 --- a/src/pipecat/services/anthropic/llm.py +++ b/src/pipecat/services/anthropic/llm.py @@ -59,7 +59,7 @@ from pipecat.processors.aggregators.openai_llm_context import ( from pipecat.processors.frame_processor import FrameDirection from pipecat.services.llm_service import FunctionCallFromLLM, LLMService from pipecat.services.settings import NOT_GIVEN as _NOT_GIVEN -from pipecat.services.settings import LLMSettings +from pipecat.services.settings import LLMSettings, is_given from pipecat.utils.tracing.service_decorators import traced_llm try: @@ -72,7 +72,7 @@ except ModuleNotFoundError as e: @dataclass class AnthropicLLMSettings(LLMSettings): - """Typed settings for Anthropic LLM services. + """Settings for Anthropic LLM services. Parameters: enable_prompt_caching: Whether to enable prompt caching. @@ -82,6 +82,18 @@ class AnthropicLLMSettings(LLMSettings): enable_prompt_caching: Any = field(default_factory=lambda: _NOT_GIVEN) thinking: Any = field(default_factory=lambda: _NOT_GIVEN) + @classmethod + def from_mapping(cls, settings): + """Convert a plain dict to settings, coercing thinking dicts. + + For backward compatibility, a ``thinking`` value that is a plain dict + is converted to a :class:`AnthropicLLMService.ThinkingConfig`. + """ + instance = super().from_mapping(settings) + if is_given(instance.thinking) and isinstance(instance.thinking, dict): + instance.thinking = AnthropicLLMService.ThinkingConfig(**instance.thinking) + return instance + @dataclass class AnthropicContextAggregatorPair: diff --git a/src/pipecat/services/assemblyai/stt.py b/src/pipecat/services/assemblyai/stt.py index 910d1e005..2e7b1230b 100644 --- a/src/pipecat/services/assemblyai/stt.py +++ b/src/pipecat/services/assemblyai/stt.py @@ -56,7 +56,7 @@ except ModuleNotFoundError as e: @dataclass class AssemblyAISTTSettings(STTSettings): - """Typed settings for the AssemblyAI STT service. + """Settings for the AssemblyAI STT service. See :class:`AssemblyAIConnectionParams` for detailed parameter descriptions. @@ -184,8 +184,8 @@ class AssemblyAISTTService(WebsocketSTTService): """ return True - async def _update_settings_from_typed(self, update: STTSettings) -> set[str]: - """Apply a typed settings update and reconnect if anything changed. + async def _update_settings(self, update: STTSettings) -> set[str]: + """Apply a settings update and reconnect if anything changed. Any change triggers a WebSocket reconnect since all connection parameters are encoded in the WebSocket URL. @@ -196,7 +196,7 @@ class AssemblyAISTTService(WebsocketSTTService): Returns: Set of field names whose values actually changed. """ - changed = await super()._update_settings_from_typed(update) + changed = await super()._update_settings(update) if not changed: return changed diff --git a/src/pipecat/services/asyncai/tts.py b/src/pipecat/services/asyncai/tts.py index 2b0740956..05ba14113 100644 --- a/src/pipecat/services/asyncai/tts.py +++ b/src/pipecat/services/asyncai/tts.py @@ -76,7 +76,7 @@ def language_to_async_language(language: Language) -> Optional[str]: @dataclass class AsyncAITTSSettings(TTSSettings): - """Typed settings for Async AI TTS services. + """Settings for Async AI TTS services. Parameters: output_container: Audio container format (e.g. "raw"). diff --git a/src/pipecat/services/aws/llm.py b/src/pipecat/services/aws/llm.py index 50de0de2c..3fca8e374 100644 --- a/src/pipecat/services/aws/llm.py +++ b/src/pipecat/services/aws/llm.py @@ -73,7 +73,7 @@ except ModuleNotFoundError as e: @dataclass class AWSBedrockLLMSettings(LLMSettings): - """Typed settings for AWS Bedrock LLM services. + """Settings for AWS Bedrock LLM services. Parameters: latency: Performance mode - "standard" or "optimized". diff --git a/src/pipecat/services/aws/stt.py b/src/pipecat/services/aws/stt.py index cd8a7103c..6a91c2973 100644 --- a/src/pipecat/services/aws/stt.py +++ b/src/pipecat/services/aws/stt.py @@ -47,7 +47,7 @@ except ModuleNotFoundError as e: @dataclass class AWSTranscribeSTTSettings(STTSettings): - """Typed settings for the AWS Transcribe STT service. + """Settings for the AWS Transcribe STT service. Parameters: sample_rate: Audio sample rate in Hz (8000 or 16000). @@ -140,13 +140,13 @@ class AWSTranscribeSTTService(WebsocketSTTService): } return encoding_map.get(encoding, encoding) - async def _update_settings_from_typed(self, update: STTSettings) -> set[str]: - """Apply a typed settings update, reconnecting if needed. + async def _update_settings(self, update: STTSettings) -> set[str]: + """Apply a settings update, reconnecting if needed. Any change to connection-relevant settings (model, language, etc.) triggers a WebSocket reconnect so the new configuration takes effect. """ - changed = await super()._update_settings_from_typed(update) + changed = await super()._update_settings(update) if changed and self._websocket: await self._disconnect() diff --git a/src/pipecat/services/aws/tts.py b/src/pipecat/services/aws/tts.py index b7f6386ca..47c524196 100644 --- a/src/pipecat/services/aws/tts.py +++ b/src/pipecat/services/aws/tts.py @@ -125,7 +125,7 @@ def language_to_aws_language(language: Language) -> Optional[str]: @dataclass class AWSPollyTTSSettings(TTSSettings): - """Typed settings for AWS Polly TTS service. + """Settings for AWS Polly TTS service. Parameters: engine: TTS engine to use ('standard', 'neural', etc.). diff --git a/src/pipecat/services/azure/stt.py b/src/pipecat/services/azure/stt.py index 95840bde9..319296a47 100644 --- a/src/pipecat/services/azure/stt.py +++ b/src/pipecat/services/azure/stt.py @@ -52,7 +52,7 @@ except ModuleNotFoundError as e: @dataclass class AzureSTTSettings(STTSettings): - """Typed settings for the Azure STT service. + """Settings for the Azure STT service. Parameters: region: Azure region for the Speech service. @@ -123,13 +123,13 @@ class AzureSTTService(STTService): """ return True - async def _update_settings_from_typed(self, update: STTSettings) -> set[str]: - """Apply a typed settings update, reconfiguring the recognizer if needed. + async def _update_settings(self, update: STTSettings) -> set[str]: + """Apply a settings update, reconfiguring the recognizer if needed. When ``language`` changes the ``SpeechConfig`` is updated and the speech recognizer is restarted so that the new language takes effect. """ - changed = await super()._update_settings_from_typed(update) + changed = await super()._update_settings(update) if "language" in changed: # Convert Language enum to Azure language code if needed. diff --git a/src/pipecat/services/azure/tts.py b/src/pipecat/services/azure/tts.py index ba6d8ac13..b72b33901 100644 --- a/src/pipecat/services/azure/tts.py +++ b/src/pipecat/services/azure/tts.py @@ -69,7 +69,7 @@ def sample_rate_to_output_format(sample_rate: int) -> SpeechSynthesisOutputForma @dataclass class AzureTTSSettings(TTSSettings): - """Typed settings for Azure TTS services. + """Settings for Azure TTS services. Parameters: emphasis: Emphasis level for speech ("strong", "moderate", "reduced"). diff --git a/src/pipecat/services/camb/tts.py b/src/pipecat/services/camb/tts.py index c484a3c80..4176b4413 100644 --- a/src/pipecat/services/camb/tts.py +++ b/src/pipecat/services/camb/tts.py @@ -137,7 +137,7 @@ def _get_aligned_audio(buffer: bytes) -> tuple[bytes, bytes]: @dataclass class CambTTSSettings(TTSSettings): - """Typed settings for Camb.ai TTS service. + """Settings for Camb.ai TTS service. Parameters: user_instructions: Custom instructions for mars-instruct model only. diff --git a/src/pipecat/services/cartesia/stt.py b/src/pipecat/services/cartesia/stt.py index 7f684f886..5116965ec 100644 --- a/src/pipecat/services/cartesia/stt.py +++ b/src/pipecat/services/cartesia/stt.py @@ -46,7 +46,7 @@ except ModuleNotFoundError as e: @dataclass class CartesiaSTTSettings(STTSettings): - """Typed settings for the Cartesia STT service. + """Settings for the Cartesia STT service. Parameters: encoding: Audio encoding format (e.g. ``"pcm_s16le"``). @@ -294,8 +294,8 @@ class CartesiaSTTService(WebsocketSTTService): await self._disconnect_websocket() - async def _update_settings_from_typed(self, update: STTSettings) -> set[str]: - """Apply a typed settings update and reconnect if anything changed. + async def _update_settings(self, update: STTSettings) -> set[str]: + """Apply a settings update and reconnect if anything changed. Args: update: A :class:`STTSettings` (or ``CartesiaSTTSettings``) delta. @@ -303,7 +303,7 @@ class CartesiaSTTService(WebsocketSTTService): Returns: Set of field names whose values actually changed. """ - changed = await super()._update_settings_from_typed(update) + changed = await super()._update_settings(update) if changed: await self._disconnect() await self._connect() diff --git a/src/pipecat/services/cartesia/tts.py b/src/pipecat/services/cartesia/tts.py index 117853e36..cff365443 100644 --- a/src/pipecat/services/cartesia/tts.py +++ b/src/pipecat/services/cartesia/tts.py @@ -195,7 +195,7 @@ class CartesiaEmotion(str, Enum): @dataclass class CartesiaTTSSettings(TTSSettings): - """Typed settings for Cartesia TTS services. + """Settings for Cartesia TTS services. Parameters: output_container: Audio container format (e.g. "raw"). diff --git a/src/pipecat/services/deepgram/stt.py b/src/pipecat/services/deepgram/stt.py index 2beaec80c..32759069b 100644 --- a/src/pipecat/services/deepgram/stt.py +++ b/src/pipecat/services/deepgram/stt.py @@ -49,7 +49,7 @@ except ModuleNotFoundError as e: @dataclass class DeepgramSTTSettings(STTSettings): - """Typed settings for the Deepgram STT service. + """Settings for the Deepgram STT service. Parameters: live_options: Deepgram ``LiveOptions`` for detailed configuration. @@ -195,8 +195,8 @@ class DeepgramSTTService(STTService): """ return True - async def _update_settings_from_typed(self, update: STTSettings) -> set[str]: - """Apply a typed settings update, keeping ``live_options`` in sync. + async def _update_settings(self, update: STTSettings) -> set[str]: + """Apply a settings update, keeping ``live_options`` in sync. Top-level ``model`` and ``language`` are the source of truth. When they are given in *update* their values are propagated into @@ -213,7 +213,7 @@ class DeepgramSTTService(STTService): getattr(update, "language", NOT_GIVEN) ) - changed = await super()._update_settings_from_typed(update) + changed = await super()._update_settings(update) if not changed: return changed diff --git a/src/pipecat/services/deepgram/stt_sagemaker.py b/src/pipecat/services/deepgram/stt_sagemaker.py index 68ec9651b..e503592d7 100644 --- a/src/pipecat/services/deepgram/stt_sagemaker.py +++ b/src/pipecat/services/deepgram/stt_sagemaker.py @@ -51,7 +51,7 @@ except ModuleNotFoundError as e: @dataclass class DeepgramSageMakerSTTSettings(STTSettings): - """Typed settings for the Deepgram SageMaker STT service. + """Settings for the Deepgram SageMaker STT service. Parameters: live_options: Deepgram ``LiveOptions`` for detailed configuration. @@ -163,8 +163,8 @@ class DeepgramSageMakerSTTService(STTService): """ return True - async def _update_settings_from_typed(self, update: STTSettings) -> set[str]: - """Apply a typed settings update, keeping ``live_options`` in sync. + async def _update_settings(self, update: STTSettings) -> set[str]: + """Apply a settings update, keeping ``live_options`` in sync. Top-level ``model`` and ``language`` are the source of truth. When they change their values are propagated into ``live_options``. @@ -178,7 +178,7 @@ class DeepgramSageMakerSTTService(STTService): getattr(update, "language", NOT_GIVEN) ) - changed = await super()._update_settings_from_typed(update) + changed = await super()._update_settings(update) if not changed: return changed diff --git a/src/pipecat/services/deepgram/tts.py b/src/pipecat/services/deepgram/tts.py index 7ae0fb9ac..bccbace26 100644 --- a/src/pipecat/services/deepgram/tts.py +++ b/src/pipecat/services/deepgram/tts.py @@ -47,7 +47,7 @@ except ModuleNotFoundError as e: @dataclass class DeepgramTTSSettings(TTSSettings): - """Typed settings for Deepgram TTS service. + """Settings for Deepgram TTS service. Parameters: encoding: Audio encoding format (linear16, mulaw, alaw). diff --git a/src/pipecat/services/elevenlabs/stt.py b/src/pipecat/services/elevenlabs/stt.py index b33fee710..d2b7a8f99 100644 --- a/src/pipecat/services/elevenlabs/stt.py +++ b/src/pipecat/services/elevenlabs/stt.py @@ -171,7 +171,7 @@ def language_to_elevenlabs_language(language: Language) -> Optional[str]: @dataclass class ElevenLabsSTTSettings(STTSettings): - """Typed settings for the ElevenLabs file-based STT service. + """Settings for the ElevenLabs file-based STT service. Parameters: tag_audio_events: Whether to include audio event tags in transcription. @@ -182,7 +182,7 @@ class ElevenLabsSTTSettings(STTSettings): @dataclass class ElevenLabsRealtimeSTTSettings(STTSettings): - """Typed settings for the ElevenLabs Realtime STT service. + """Settings for the ElevenLabs Realtime STT service. See ``ElevenLabsRealtimeSTTService.InputParams`` for detailed descriptions. @@ -294,8 +294,8 @@ class ElevenLabsSTTService(SegmentedSTTService): """ return language_to_elevenlabs_language(language) - async def _update_settings_from_typed(self, update: STTSettings) -> set[str]: - """Apply a typed settings update. + async def _update_settings(self, update: STTSettings) -> set[str]: + """Apply a settings update. Converts language to ElevenLabs format before applying and keeps ``_model_id`` in sync with the model setting. @@ -312,7 +312,7 @@ class ElevenLabsSTTService(SegmentedSTTService): if converted is not None: update.language = converted - changed = await super()._update_settings_from_typed(update) + changed = await super()._update_settings(update) if "model" in changed: self._model_id = self._settings.model @@ -543,8 +543,8 @@ class ElevenLabsRealtimeSTTService(WebsocketSTTService): """ return True - async def _update_settings_from_typed(self, update: STTSettings) -> set[str]: - """Apply a typed settings update and reconnect if anything changed. + async def _update_settings(self, update: STTSettings) -> set[str]: + """Apply a settings update and reconnect if anything changed. Converts language to ElevenLabs format before applying and keeps ``_model_id`` in sync. @@ -561,7 +561,7 @@ class ElevenLabsRealtimeSTTService(WebsocketSTTService): if converted is not None: update.language = converted - changed = await super()._update_settings_from_typed(update) + changed = await super()._update_settings(update) if not changed: return changed diff --git a/src/pipecat/services/elevenlabs/tts.py b/src/pipecat/services/elevenlabs/tts.py index cd3a99e1e..9643fa6ba 100644 --- a/src/pipecat/services/elevenlabs/tts.py +++ b/src/pipecat/services/elevenlabs/tts.py @@ -154,7 +154,7 @@ def build_elevenlabs_voice_settings( """Build voice settings dictionary for ElevenLabs based on provided settings. Args: - settings: Dictionary or typed settings containing voice settings parameters. + settings: Dictionary or settings containing voice settings parameters. Returns: Dictionary of voice settings or None if no valid settings are provided. @@ -186,7 +186,7 @@ class PronunciationDictionaryLocator(BaseModel): @dataclass class ElevenLabsTTSSettings(TTSSettings): - """Typed settings for the ElevenLabs WebSocket TTS service. + """Settings for the ElevenLabs WebSocket TTS service. Fields that appear in the WebSocket URL (``voice``, ``model``, ``language``) require a full reconnect when changed. Fields that @@ -230,7 +230,7 @@ class ElevenLabsTTSSettings(TTSSettings): @dataclass class ElevenLabsHttpTTSSettings(TTSSettings): - """Typed settings for the ElevenLabs HTTP TTS service. + """Settings for the ElevenLabs HTTP TTS service. Parameters: optimize_streaming_latency: Latency optimization level (0-4). @@ -471,8 +471,8 @@ class ElevenLabsTTSService(AudioContextWordTTSService): voice_settings[key] = val return voice_settings or None - async def _update_settings_from_typed(self, update: TTSSettings) -> set[str]: - """Apply a typed settings update, reconnecting as needed. + async def _update_settings(self, update: TTSSettings) -> set[str]: + """Apply a settings update, reconnecting as needed. Uses the declarative ``URL_FIELDS`` and ``VOICE_SETTINGS_FIELDS`` sets on :class:`ElevenLabsTTSSettings` to decide whether to @@ -484,7 +484,7 @@ class ElevenLabsTTSService(AudioContextWordTTSService): Returns: Set of field names whose values actually changed. """ - changed = await super()._update_settings_from_typed(update) + changed = await super()._update_settings(update) if not changed: return changed @@ -958,8 +958,8 @@ class ElevenLabsHttpTTSService(WordTTSService): def _set_voice_settings(self): return build_elevenlabs_voice_settings(self._settings) - async def _update_settings_from_typed(self, update: TTSSettings) -> set[str]: - """Apply a typed settings update and rebuild voice settings. + async def _update_settings(self, update: TTSSettings) -> set[str]: + """Apply a settings update and rebuild voice settings. Args: update: A :class:`TTSSettings` (or ``ElevenLabsHttpTTSSettings``) delta. @@ -967,7 +967,7 @@ class ElevenLabsHttpTTSService(WordTTSService): Returns: Set of field names whose values actually changed. """ - changed = await super()._update_settings_from_typed(update) + changed = await super()._update_settings(update) if changed: self._voice_settings = self._set_voice_settings() return changed diff --git a/src/pipecat/services/fal/stt.py b/src/pipecat/services/fal/stt.py index a459d15dd..ff6628f6c 100644 --- a/src/pipecat/services/fal/stt.py +++ b/src/pipecat/services/fal/stt.py @@ -150,7 +150,7 @@ def language_to_fal_language(language: Language) -> Optional[str]: @dataclass class FalSTTSettings(STTSettings): - """Typed settings for the Fal Wizper STT service. + """Settings for the Fal Wizper STT service. Parameters: task: Task to perform ('transcribe' or 'translate'). Defaults to @@ -251,9 +251,9 @@ class FalSTTService(SegmentedSTTService): """ return language_to_fal_language(language) - async def _update_settings_from_typed(self, update: STTSettings) -> set[str]: - """Apply a typed settings update, converting language if changed.""" - changed = await super()._update_settings_from_typed(update) + async def _update_settings(self, update: STTSettings) -> set[str]: + """Apply a settings update, converting language if changed.""" + changed = await super()._update_settings(update) if "language" in changed: # Convert the Language enum to a Fal language code. diff --git a/src/pipecat/services/fish/tts.py b/src/pipecat/services/fish/tts.py index 5c56d0c91..daa884af8 100644 --- a/src/pipecat/services/fish/tts.py +++ b/src/pipecat/services/fish/tts.py @@ -49,7 +49,7 @@ FishAudioOutputFormat = Literal["opus", "mp3", "pcm", "wav"] @dataclass class FishAudioTTSSettings(TTSSettings): - """Typed settings for Fish Audio TTS service. + """Settings for Fish Audio TTS service. Parameters: fish_sample_rate: Audio sample rate sent to the API. @@ -184,8 +184,8 @@ class FishAudioTTSService(InterruptibleTTSService): """ return True - async def _update_settings_from_typed(self, update: TTSSettings) -> set[str]: - """Apply a typed settings update and reconnect if needed. + async def _update_settings(self, update: TTSSettings) -> set[str]: + """Apply a settings update and reconnect if needed. Any change to voice or model triggers a WebSocket reconnect. @@ -195,7 +195,7 @@ class FishAudioTTSService(InterruptibleTTSService): Returns: Set of field names whose values actually changed. """ - changed = await super()._update_settings_from_typed(update) + changed = await super()._update_settings(update) if changed: await self._disconnect() await self._connect() diff --git a/src/pipecat/services/gladia/stt.py b/src/pipecat/services/gladia/stt.py index d56150a29..bb8f05e61 100644 --- a/src/pipecat/services/gladia/stt.py +++ b/src/pipecat/services/gladia/stt.py @@ -182,7 +182,7 @@ class _InputParamsDescriptor: @dataclass class GladiaSTTSettings(STTSettings): - """Typed settings for Gladia STT service. + """Settings for Gladia STT service. Parameters: input_params: Gladia ``GladiaInputParams`` for detailed configuration. @@ -379,19 +379,19 @@ class GladiaSTTService(WebsocketSTTService): await super().start(frame) await self._connect() - async def _update_settings_from_typed(self, update: GladiaSTTSettings) -> set[str]: - """Apply typed settings update. + async def _update_settings(self, update: GladiaSTTSettings) -> set[str]: + """Apply settings update. Gladia sessions are fixed at creation time, so any change requires a full session teardown and reconnect. Args: - update: A typed settings delta. + update: A settings delta. Returns: Set of field names whose values actually changed. """ - changed = await super()._update_settings_from_typed(update) + changed = await super()._update_settings(update) if not changed: return changed diff --git a/src/pipecat/services/google/gemini_live/llm.py b/src/pipecat/services/google/gemini_live/llm.py index 2e8a2efbd..7a7aed08c 100644 --- a/src/pipecat/services/google/gemini_live/llm.py +++ b/src/pipecat/services/google/gemini_live/llm.py @@ -604,7 +604,7 @@ class InputParams(BaseModel): @dataclass class GeminiLiveLLMSettings(LLMSettings): - """Typed settings for Gemini Live LLM services. + """Settings for Gemini Live LLM services. Parameters: modalities: Response modalities. @@ -976,7 +976,8 @@ class GeminiLiveLLMService(LLMService): # (we have an example that does just that, actually). await self._create_single_response(frame.messages) elif isinstance(frame, LLMSetToolsFrame): - await self._update_settings() + # TODO: implement runtime tool updates for Gemini Live. + pass else: await self.push_frame(frame, direction) diff --git a/src/pipecat/services/google/llm.py b/src/pipecat/services/google/llm.py index 7f6dd724c..bf1958f66 100644 --- a/src/pipecat/services/google/llm.py +++ b/src/pipecat/services/google/llm.py @@ -58,7 +58,7 @@ from pipecat.services.openai.llm import ( OpenAIAssistantContextAggregator, OpenAIUserContextAggregator, ) -from pipecat.services.settings import NOT_GIVEN, LLMSettings +from pipecat.services.settings import NOT_GIVEN, LLMSettings, is_given from pipecat.utils.tracing.service_decorators import traced_llm # Suppress gRPC fork warnings @@ -675,7 +675,7 @@ class GoogleLLMContext(OpenAILLMContext): @dataclass class GoogleLLMSettings(LLMSettings): - """Typed settings for Google LLM services. + """Settings for Google LLM services. Parameters: thinking: Thinking configuration. @@ -683,6 +683,18 @@ class GoogleLLMSettings(LLMSettings): thinking: Any = field(default_factory=lambda: NOT_GIVEN) + @classmethod + def from_mapping(cls, settings): + """Convert a plain dict to settings, coercing thinking dicts. + + For backward compatibility, a ``thinking`` value that is a plain dict + is converted to a :class:`GoogleLLMService.ThinkingConfig`. + """ + instance = super().from_mapping(settings) + if is_given(instance.thinking) and isinstance(instance.thinking, dict): + instance.thinking = GoogleLLMService.ThinkingConfig(**instance.thinking) + return instance + class GoogleLLMService(LLMService): """Google AI (Gemini) LLM service implementation. @@ -1227,14 +1239,6 @@ class GoogleLLMService(LLMService): # Do nothing - we're shutting down anyway pass - async def _update_settings(self, settings): - """Override to handle ThinkingConfig validation.""" - # Convert thinking dict to ThinkingConfig if needed - if "thinking" in settings and isinstance(settings["thinking"], dict): - settings = dict(settings) # Make a copy to avoid modifying the original - settings["thinking"] = self.ThinkingConfig(**settings["thinking"]) - await super()._update_settings(settings) - def create_context_aggregator( self, context: OpenAILLMContext, diff --git a/src/pipecat/services/google/stt.py b/src/pipecat/services/google/stt.py index 585b766f4..d4ffb0d91 100644 --- a/src/pipecat/services/google/stt.py +++ b/src/pipecat/services/google/stt.py @@ -360,7 +360,7 @@ def language_to_google_stt_language(language: Language) -> Optional[str]: @dataclass class GoogleSTTSettings(STTSettings): - """Typed settings for Google Cloud Speech-to-Text V2. + """Settings for Google Cloud Speech-to-Text V2. Parameters: languages: List of ``Language`` enums for recognition @@ -628,10 +628,10 @@ class GoogleSTTService(STTService): DeprecationWarning, ) logger.debug(f"Switching STT languages to: {languages}") - await self._update_settings_from_typed(GoogleSTTSettings(languages=list(languages))) + await self._update_settings(GoogleSTTSettings(languages=list(languages))) - async def _update_settings_from_typed(self, update: GoogleSTTSettings) -> set[str]: - """Apply typed settings update and reconnect if anything changed. + async def _update_settings(self, update: GoogleSTTSettings) -> set[str]: + """Apply settings update and reconnect if anything changed. Handles ``language`` from base ``set_language`` by converting it to ``languages``. Emits a deprecation warning if ``language_codes`` is @@ -639,7 +639,7 @@ class GoogleSTTService(STTService): Reconnects the stream on any change. Args: - update: A typed settings delta. + update: A settings delta. Returns: Set of field names whose values actually changed. @@ -663,7 +663,7 @@ class GoogleSTTService(STTService): stacklevel=2, ) - changed = await super()._update_settings_from_typed(update) + changed = await super()._update_settings(update) if changed: await self._reconnect_if_needed() @@ -742,7 +742,7 @@ class GoogleSTTService(STTService): "GoogleSTTSettings(...) instead.", DeprecationWarning, ) - # Build a typed settings delta from the provided options + # Build a settings delta from the provided options update = GoogleSTTSettings() if languages is not None: @@ -770,7 +770,7 @@ class GoogleSTTService(STTService): logger.debug(f"Updating location to: {location}") self._location = location - await self._update_settings_from_typed(update) + await self._update_settings(update) async def _connect(self): """Initialize streaming recognition config and stream.""" diff --git a/src/pipecat/services/google/tts.py b/src/pipecat/services/google/tts.py index 2b9ada224..9769aa665 100644 --- a/src/pipecat/services/google/tts.py +++ b/src/pipecat/services/google/tts.py @@ -478,7 +478,7 @@ def language_to_gemini_tts_language(language: Language) -> Optional[str]: @dataclass class GoogleHttpTTSSettings(TTSSettings): - """Typed settings for Google HTTP TTS service. + """Settings for Google HTTP TTS service. Parameters: pitch: Voice pitch adjustment (e.g., "+2st", "-50%"). @@ -505,7 +505,7 @@ class GoogleHttpTTSSettings(TTSSettings): @dataclass class GoogleStreamTTSSettings(TTSSettings): - """Typed settings for Google streaming TTS service. + """Settings for Google streaming TTS service. Parameters: language: Language for synthesis. Defaults to English. @@ -518,7 +518,7 @@ class GoogleStreamTTSSettings(TTSSettings): @dataclass class GeminiTTSSettings(TTSSettings): - """Typed settings for Gemini TTS service. + """Settings for Gemini TTS service. Parameters: language: Language for synthesis. Defaults to English. @@ -680,11 +680,11 @@ class GoogleHttpTTSService(TTSService): """ return language_to_google_tts_language(language) - async def _update_settings_from_typed(self, update: TTSSettings) -> set[str]: + async def _update_settings(self, update: TTSSettings) -> set[str]: """Override to handle speaking_rate validation. Args: - update: Typed settings delta. Can include 'speaking_rate' (float). + update: Settings delta. Can include 'speaking_rate' (float). """ if isinstance(update, GoogleHttpTTSSettings) and is_given(update.speaking_rate): rate_value = float(update.speaking_rate) @@ -693,7 +693,7 @@ class GoogleHttpTTSService(TTSService): f"Invalid speaking_rate value: {rate_value}. Must be between 0.25 and 2.0" ) update.speaking_rate = NOT_GIVEN - return await super()._update_settings_from_typed(update) + return await super()._update_settings(update) def _construct_ssml(self, text: str) -> str: ssml = "" @@ -1024,11 +1024,11 @@ class GoogleTTSService(GoogleBaseTTSService): credentials, credentials_path ) - async def _update_settings_from_typed(self, update: TTSSettings) -> set[str]: + async def _update_settings(self, update: TTSSettings) -> set[str]: """Override to handle speaking_rate validation. Args: - update: Typed settings delta. Can include 'speaking_rate' (float). + update: Settings delta. Can include 'speaking_rate' (float). """ if isinstance(update, GoogleStreamTTSSettings) and is_given(update.speaking_rate): rate_value = float(update.speaking_rate) @@ -1037,7 +1037,7 @@ class GoogleTTSService(GoogleBaseTTSService): f"Invalid speaking_rate value: {rate_value}. Must be between 0.25 and 2.0" ) update.speaking_rate = NOT_GIVEN - return await super()._update_settings_from_typed(update) + return await super()._update_settings(update) @traced_tts async def run_tts(self, text: str, context_id: str) -> AsyncGenerator[Frame, None]: @@ -1259,11 +1259,11 @@ class GeminiTTSService(GoogleBaseTTSService): f"Current rate of {self.sample_rate}Hz may cause issues." ) - async def _update_settings_from_typed(self, update: TTSSettings) -> set[str]: - """Apply a typed settings update with voice validation. + async def _update_settings(self, update: TTSSettings) -> set[str]: + """Apply a settings update with voice validation. Args: - update: Typed settings delta. Can include 'voice', 'prompt', etc. + update: Settings delta. Can include 'voice', 'prompt', etc. Returns: Set of field names whose values actually changed. @@ -1271,7 +1271,7 @@ class GeminiTTSService(GoogleBaseTTSService): if is_given(update.voice) and update.voice not in self.AVAILABLE_VOICES: logger.warning(f"Voice '{update.voice}' not in known voices list. Using anyway.") - return await super()._update_settings_from_typed(update) + return await super()._update_settings(update) @traced_tts async def run_tts(self, text: str, context_id: str) -> AsyncGenerator[Frame, None]: diff --git a/src/pipecat/services/gradium/stt.py b/src/pipecat/services/gradium/stt.py index ff2002625..3b634cbd2 100644 --- a/src/pipecat/services/gradium/stt.py +++ b/src/pipecat/services/gradium/stt.py @@ -68,7 +68,7 @@ def language_to_gradium_language(language: Language) -> Optional[str]: @dataclass class GradiumSTTSettings(STTSettings): - """Typed settings for the Gradium STT service. + """Settings for the Gradium STT service. Parameters: delay_in_frames: Delay in audio frames (80ms each) before text is @@ -171,8 +171,8 @@ class GradiumSTTService(WebsocketSTTService): """ return True - async def _update_settings_from_typed(self, update: STTSettings) -> set[str]: - """Apply a typed settings update, sync params, and reconnect. + async def _update_settings(self, update: STTSettings) -> set[str]: + """Apply a settings update, sync params, and reconnect. Args: update: A :class:`STTSettings` (or ``GradiumSTTSettings``) delta. @@ -180,7 +180,7 @@ class GradiumSTTService(WebsocketSTTService): Returns: Set of field names whose values actually changed. """ - changed = await super()._update_settings_from_typed(update) + changed = await super()._update_settings(update) if not changed: return changed diff --git a/src/pipecat/services/gradium/tts.py b/src/pipecat/services/gradium/tts.py index 5dc355b91..bc4945bcf 100644 --- a/src/pipecat/services/gradium/tts.py +++ b/src/pipecat/services/gradium/tts.py @@ -41,7 +41,7 @@ SAMPLE_RATE = 48000 @dataclass class GradiumTTSSettings(TTSSettings): - """Typed settings for the Gradium TTS service. + """Settings for the Gradium TTS service. Parameters: output_format: Audio output format. @@ -119,8 +119,8 @@ class GradiumTTSService(InterruptibleWordTTSService): """ return True - async def _update_settings_from_typed(self, update: TTSSettings) -> set[str]: - """Apply a typed settings update and reconnect if voice changed. + async def _update_settings(self, update: TTSSettings) -> set[str]: + """Apply a settings update and reconnect if voice changed. Args: update: A :class:`TTSSettings` (or ``GradiumTTSSettings``) delta. @@ -129,7 +129,7 @@ class GradiumTTSService(InterruptibleWordTTSService): Set of field names whose values actually changed. """ prev_voice = self._voice_id - changed = await super()._update_settings_from_typed(update) + changed = await super()._update_settings(update) if self._voice_id != prev_voice: await self._disconnect() await self._connect() diff --git a/src/pipecat/services/grok/realtime/llm.py b/src/pipecat/services/grok/realtime/llm.py index dfe039bbc..f31769774 100644 --- a/src/pipecat/services/grok/realtime/llm.py +++ b/src/pipecat/services/grok/realtime/llm.py @@ -88,7 +88,7 @@ class CurrentAudioResponse: @dataclass class GrokRealtimeLLMSettings(LLMSettings): - """Typed settings for Grok Realtime LLM services. + """Settings for Grok Realtime LLM services. Parameters: session_properties: Grok Realtime session configuration. @@ -349,13 +349,13 @@ class GrokRealtimeLLMService(LLMService): frame: The frame to process. direction: The direction of frame flow in the pipeline. """ - # Legacy dict path: frame.settings contains SessionProperties fields, - # not our Settings fields, so we construct SessionProperties directly. - # The new typed path (frame.update) falls through to super, which calls - # _update_settings_from_typed → our override handles the rest. + # Backward-compatible dict path: frame.settings contains SessionProperties + # fields, not our Settings fields, so we construct SessionProperties + # directly. The frame.update path falls through to super, which calls + # _update_settings → our override handles the rest. if isinstance(frame, LLMUpdateSettingsFrame) and frame.update is None: self._settings.session_properties = events.SessionProperties(**frame.settings) - await self._update_settings() + await self._send_session_update() await self.push_frame(frame, direction) return @@ -379,7 +379,7 @@ class GrokRealtimeLLMService(LLMService): elif isinstance(frame, LLMMessagesAppendFrame): await self._handle_messages_append(frame) elif isinstance(frame, LLMSetToolsFrame): - await self._update_settings() + await self._send_session_update() await self.push_frame(frame, direction) @@ -456,14 +456,14 @@ class GrokRealtimeLLMService(LLMService): return await self.push_error(error_msg=f"Error sending client event: {e}", exception=e) - async def _update_settings_from_typed(self, update): - """Apply a typed settings update, sending a session update if needed.""" - changed = await super()._update_settings_from_typed(update) + async def _update_settings(self, update): + """Apply a settings update, sending a session update if needed.""" + changed = await super()._update_settings(update) if "session_properties" in changed: - await self._update_settings() + await self._send_session_update() return changed - async def _update_settings(self): + async def _send_session_update(self): """Update session settings on the server.""" settings = self._settings.session_properties adapter: GrokRealtimeLLMAdapter = self.get_llm_adapter() @@ -543,7 +543,7 @@ class GrokRealtimeLLMService(LLMService): async def _handle_evt_conversation_created(self, evt): """Handle conversation.created event - first event after connecting.""" - await self._update_settings() + await self._send_session_update() async def _handle_evt_response_created(self, evt): """Handle response.created event - response generation started.""" @@ -746,7 +746,7 @@ class GrokRealtimeLLMService(LLMService): self._messages_added_manually[evt.item.id] = True await self.send_client_event(evt) - await self._update_settings() + await self._send_session_update() self._llm_needs_conversation_setup = False logger.debug("Creating Grok response") diff --git a/src/pipecat/services/groq/tts.py b/src/pipecat/services/groq/tts.py index 8e551725f..d0b5fbd7c 100644 --- a/src/pipecat/services/groq/tts.py +++ b/src/pipecat/services/groq/tts.py @@ -36,7 +36,7 @@ except ModuleNotFoundError as e: @dataclass class GroqTTSSettings(TTSSettings): - """Typed settings for the Groq TTS service. + """Settings for the Groq TTS service. Parameters: output_format: Audio output format. diff --git a/src/pipecat/services/hathora/stt.py b/src/pipecat/services/hathora/stt.py index 8af53958d..a620ed79a 100644 --- a/src/pipecat/services/hathora/stt.py +++ b/src/pipecat/services/hathora/stt.py @@ -31,7 +31,7 @@ from .utils import ConfigOption @dataclass class HathoraSTTSettings(STTSettings): - """Typed settings for the Hathora STT service. + """Settings for the Hathora STT service. Parameters: config: Some models support additional config, refer to diff --git a/src/pipecat/services/hathora/tts.py b/src/pipecat/services/hathora/tts.py index 2b3a5ddb1..f3524734a 100644 --- a/src/pipecat/services/hathora/tts.py +++ b/src/pipecat/services/hathora/tts.py @@ -49,7 +49,7 @@ def _decode_audio_payload( @dataclass class HathoraTTSSettings(TTSSettings): - """Typed settings for Hathora TTS service. + """Settings for Hathora TTS service. Parameters: speed: Speech speed multiplier (if supported by model). diff --git a/src/pipecat/services/inworld/tts.py b/src/pipecat/services/inworld/tts.py index 7f4374b93..2f6a13bd1 100644 --- a/src/pipecat/services/inworld/tts.py +++ b/src/pipecat/services/inworld/tts.py @@ -52,7 +52,7 @@ from pipecat.utils.tracing.service_decorators import traced_tts @dataclass class InworldTTSSettings(TTSSettings): - """Typed settings for Inworld TTS services. + """Settings for Inworld TTS services. Parameters: audio_encoding: Audio encoding format (e.g. LINEAR16). diff --git a/src/pipecat/services/kokoro/tts.py b/src/pipecat/services/kokoro/tts.py index 6d46441f6..b88511437 100644 --- a/src/pipecat/services/kokoro/tts.py +++ b/src/pipecat/services/kokoro/tts.py @@ -91,7 +91,7 @@ def language_to_kokoro_language(language: Language) -> str: @dataclass class KokoroTTSSettings(TTSSettings): - """Typed settings for the Kokoro TTS service. + """Settings for the Kokoro TTS service. Parameters: lang_code: Kokoro language code for synthesis. diff --git a/src/pipecat/services/llm_service.py b/src/pipecat/services/llm_service.py index 693448cd5..97d49192c 100644 --- a/src/pipecat/services/llm_service.py +++ b/src/pipecat/services/llm_service.py @@ -59,7 +59,7 @@ from pipecat.processors.aggregators.llm_response import ( from pipecat.processors.aggregators.openai_llm_context import OpenAILLMContext from pipecat.processors.frame_processor import FrameDirection from pipecat.services.ai_service import AIService -from pipecat.services.settings import LLMSettings, ServiceSettings, is_given +from pipecat.services.settings import LLMSettings, is_given from pipecat.turns.user_turn_completion_mixin import UserTurnCompletionLLMServiceMixin from pipecat.utils.context.llm_context_summarization import ( LLMContextSummarizationUtil, @@ -313,16 +313,16 @@ class LLMService(UserTurnCompletionLLMServiceMixin, AIService): await self._cancel_sequential_runner_task() await self._cancel_summary_task() - async def _update_settings_from_typed(self, update: LLMSettings) -> set[str]: - """Apply a typed settings update, handling turn-completion fields. + async def _update_settings(self, update: LLMSettings) -> set[str]: + """Apply a settings update, handling turn-completion fields. Args: - update: A typed LLM settings delta. + update: An LLM settings delta. Returns: Set of field names whose values actually changed. """ - changed = await super()._update_settings_from_typed(update) + changed = await super()._update_settings(update) if "filter_incomplete_user_turns" in changed: self._filter_incomplete_user_turns = self._settings.filter_incomplete_user_turns @@ -336,35 +336,6 @@ class LLMService(UserTurnCompletionLLMServiceMixin, AIService): return changed - async def _update_settings(self, settings: Mapping[str, Any]): - """Update LLM service settings. - - Handles turn completion settings specially since they are not model - parameters and should not be passed to the underlying LLM API. - - Args: - settings: Dictionary of settings to update. - """ - # Turn completion settings to extract (not model parameters) - turn_completion_keys = {"filter_incomplete_user_turns", "user_turn_completion_config"} - - # Handle turn completion settings - if "filter_incomplete_user_turns" in settings: - self._filter_incomplete_user_turns = settings["filter_incomplete_user_turns"] - logger.info( - f"{self}: Incomplete turn filtering {'enabled' if self._filter_incomplete_user_turns else 'disabled'}" - ) - - # Configure the mixin with config object - if self._filter_incomplete_user_turns and "user_turn_completion_config" in settings: - self.set_user_turn_completion_config(settings["user_turn_completion_config"]) - - # Remove turn completion settings before passing to parent - settings = {k: v for k, v in settings.items() if k not in turn_completion_keys} - - # Let the parent handle remaining model parameters - await super()._update_settings(settings) - async def process_frame(self, frame: Frame, direction: FrameDirection): """Process a frame. @@ -379,16 +350,12 @@ class LLMService(UserTurnCompletionLLMServiceMixin, AIService): elif isinstance(frame, LLMConfigureOutputFrame): self._skip_tts = frame.skip_tts elif isinstance(frame, LLMUpdateSettingsFrame): - # New path: typed settings update object. if frame.update is not None: - await self._update_settings_from_typed(frame.update) - # Legacy path: plain dict, but service uses typed settings — convert. - elif isinstance(self._settings, ServiceSettings): + await self._update_settings(frame.update) + elif frame.settings: + # Backward-compatible path: convert legacy dict to settings object. update = type(self._settings).from_mapping(frame.settings) - await self._update_settings_from_typed(update) - # Legacy path: plain dict, service still uses dict-based settings. - else: - await self._update_settings(frame.settings) + await self._update_settings(update) elif isinstance(frame, LLMContextSummaryRequestFrame): await self._handle_summary_request(frame) diff --git a/src/pipecat/services/lmnt/tts.py b/src/pipecat/services/lmnt/tts.py index 9fa727c5f..1b23c8ae2 100644 --- a/src/pipecat/services/lmnt/tts.py +++ b/src/pipecat/services/lmnt/tts.py @@ -75,7 +75,7 @@ def language_to_lmnt_language(language: Language) -> Optional[str]: @dataclass class LmntTTSSettings(TTSSettings): - """Typed settings for LMNT TTS service. + """Settings for LMNT TTS service. Parameters: format: Audio output format. Defaults to "raw". diff --git a/src/pipecat/services/minimax/tts.py b/src/pipecat/services/minimax/tts.py index db236d6e4..ab04925f3 100644 --- a/src/pipecat/services/minimax/tts.py +++ b/src/pipecat/services/minimax/tts.py @@ -89,7 +89,7 @@ def language_to_minimax_language(language: Language) -> Optional[str]: @dataclass class MiniMaxTTSSettings(TTSSettings): - """Typed settings for MiniMax TTS service. + """Settings for MiniMax TTS service. Parameters: stream: Whether to use streaming mode. diff --git a/src/pipecat/services/neuphonic/tts.py b/src/pipecat/services/neuphonic/tts.py index de92c48a2..0680de4f6 100644 --- a/src/pipecat/services/neuphonic/tts.py +++ b/src/pipecat/services/neuphonic/tts.py @@ -76,7 +76,7 @@ def language_to_neuphonic_lang_code(language: Language) -> Optional[str]: @dataclass class NeuphonicTTSSettings(TTSSettings): - """Typed settings for Neuphonic TTS service. + """Settings for Neuphonic TTS service. Parameters: lang_code: Neuphonic language code. @@ -181,9 +181,9 @@ class NeuphonicTTSService(InterruptibleTTSService): """ return language_to_neuphonic_lang_code(language) - async def _update_settings_from_typed(self, update: TTSSettings) -> set[str]: - """Apply a typed settings update and reconnect with new configuration.""" - changed = await super()._update_settings_from_typed(update) + async def _update_settings(self, update: TTSSettings) -> set[str]: + """Apply a settings update and reconnect with new configuration.""" + changed = await super()._update_settings(update) if changed: await self._disconnect() await self._connect() diff --git a/src/pipecat/services/nvidia/stt.py b/src/pipecat/services/nvidia/stt.py index 6190e169d..ff76a6900 100644 --- a/src/pipecat/services/nvidia/stt.py +++ b/src/pipecat/services/nvidia/stt.py @@ -93,14 +93,14 @@ def language_to_nvidia_riva_language(language: Language) -> Optional[str]: @dataclass class NvidiaSTTSettings(STTSettings): - """Typed settings for the NVIDIA Riva streaming STT service.""" + """Settings for the NVIDIA Riva streaming STT service.""" pass @dataclass class NvidiaSegmentedSTTSettings(STTSettings): - """Typed settings for the NVIDIA Riva segmented STT service. + """Settings for the NVIDIA Riva segmented STT service. Parameters: profanity_filter: Whether to filter profanity from results. @@ -579,8 +579,8 @@ class NvidiaSegmentedSTTService(SegmentedSTTService): self._config = self._create_recognition_config() logger.debug(f"Initialized NvidiaSegmentedSTTService with model: {self.model_name}") - async def _update_settings_from_typed(self, update: STTSettings) -> set[str]: - """Apply a typed settings update and sync internal state. + async def _update_settings(self, update: STTSettings) -> set[str]: + """Apply a settings update and sync internal state. Args: update: A :class:`STTSettings` (or ``NvidiaSegmentedSTTSettings``) delta. @@ -588,7 +588,7 @@ class NvidiaSegmentedSTTService(SegmentedSTTService): Returns: Set of field names whose values actually changed. """ - changed = await super()._update_settings_from_typed(update) + changed = await super()._update_settings(update) if changed: self._config = self._create_recognition_config() diff --git a/src/pipecat/services/openai/base_llm.py b/src/pipecat/services/openai/base_llm.py index 454087508..13cbc07cb 100644 --- a/src/pipecat/services/openai/base_llm.py +++ b/src/pipecat/services/openai/base_llm.py @@ -49,7 +49,7 @@ from pipecat.utils.tracing.service_decorators import traced_llm @dataclass class OpenAILLMSettings(LLMSettings): - """Typed settings for OpenAI-compatible LLM services. + """Settings for OpenAI-compatible LLM services. Parameters: max_completion_tokens: Maximum completion tokens to generate. diff --git a/src/pipecat/services/openai/realtime/llm.py b/src/pipecat/services/openai/realtime/llm.py index 825639950..f6e8b1646 100644 --- a/src/pipecat/services/openai/realtime/llm.py +++ b/src/pipecat/services/openai/realtime/llm.py @@ -93,7 +93,7 @@ class CurrentAudioResponse: @dataclass class OpenAIRealtimeLLMSettings(LLMSettings): - """Typed settings for OpenAI Realtime LLM services. + """Settings for OpenAI Realtime LLM services. Parameters: session_properties: OpenAI Realtime session configuration. @@ -411,13 +411,13 @@ class OpenAIRealtimeLLMService(LLMService): frame: The frame to process. direction: The direction of frame flow in the pipeline. """ - # Legacy dict path: frame.settings contains SessionProperties fields, - # not our Settings fields, so we construct SessionProperties directly. - # The new typed path (frame.update) falls through to super, which calls - # _update_settings_from_typed → our override handles the rest. + # Backward-compatible dict path: frame.settings contains SessionProperties + # fields, not our Settings fields, so we construct SessionProperties + # directly. The frame.update path falls through to super, which calls + # _update_settings → our override handles the rest. if isinstance(frame, LLMUpdateSettingsFrame) and frame.update is None: self._settings.session_properties = events.SessionProperties(**frame.settings) - await self._update_settings() + await self._send_session_update() await self.push_frame(frame, direction) return @@ -449,7 +449,7 @@ class OpenAIRealtimeLLMService(LLMService): elif isinstance(frame, LLMMessagesAppendFrame): await self._handle_messages_append(frame) elif isinstance(frame, LLMSetToolsFrame): - await self._update_settings() + await self._send_session_update() await self.push_frame(frame, direction) @@ -534,14 +534,14 @@ class OpenAIRealtimeLLMService(LLMService): # treat a send-side error as fatal. await self.push_error(error_msg=f"Error sending client event: {e}", exception=e) - async def _update_settings_from_typed(self, update): - """Apply a typed settings update, sending a session update if needed.""" - changed = await super()._update_settings_from_typed(update) + async def _update_settings(self, update): + """Apply a settings update, sending a session update if needed.""" + changed = await super()._update_settings(update) if "session_properties" in changed: - await self._update_settings() + await self._send_session_update() return changed - async def _update_settings(self): + async def _send_session_update(self): settings = self._settings.session_properties adapter: OpenAIRealtimeLLMAdapter = self.get_llm_adapter() @@ -613,7 +613,7 @@ class OpenAIRealtimeLLMService(LLMService): async def _handle_evt_session_created(self, evt): # session.created is received right after connecting. Send a message # to configure the session properties. - await self._update_settings() + await self._send_session_update() async def _handle_evt_session_updated(self, evt): # If this is our first context frame, run the LLM @@ -896,7 +896,7 @@ class OpenAIRealtimeLLMService(LLMService): await self.send_client_event(evt) # Send new settings if needed - await self._update_settings() + await self._send_session_update() # We're done configuring the LLM for this session self._llm_needs_conversation_setup = False diff --git a/src/pipecat/services/openai/stt.py b/src/pipecat/services/openai/stt.py index 266b2964b..458f40133 100644 --- a/src/pipecat/services/openai/stt.py +++ b/src/pipecat/services/openai/stt.py @@ -127,7 +127,7 @@ _OPENAI_SAMPLE_RATE = 24000 @dataclass class OpenAIRealtimeSTTSettings(STTSettings): - """Typed settings for the OpenAI Realtime STT service. + """Settings for the OpenAI Realtime STT service. Parameters: prompt: Optional prompt text to guide transcription style. @@ -268,10 +268,10 @@ class OpenAIRealtimeSTTService(WebsocketSTTService): """ return True - async def _update_settings_from_typed(self, update: STTSettings) -> set[str]: - """Apply a typed settings update and send session update if needed. + async def _update_settings(self, update: STTSettings) -> set[str]: + """Apply a settings update and send session update if needed. - Keeps ``_language_code`` and ``_prompt`` in sync with typed settings + Keeps ``_language_code`` and ``_prompt`` in sync with settings and sends a ``session.update`` to the server when the session is active. Args: @@ -280,7 +280,7 @@ class OpenAIRealtimeSTTService(WebsocketSTTService): Returns: Set of field names whose values actually changed. """ - changed = await super()._update_settings_from_typed(update) + changed = await super()._update_settings(update) if not changed: return changed diff --git a/src/pipecat/services/openai/tts.py b/src/pipecat/services/openai/tts.py index 3572d287e..f283a7912 100644 --- a/src/pipecat/services/openai/tts.py +++ b/src/pipecat/services/openai/tts.py @@ -64,7 +64,7 @@ VALID_VOICES: Dict[str, ValidVoice] = { @dataclass class OpenAITTSSettings(TTSSettings): - """Typed settings for OpenAI TTS service. + """Settings for OpenAI TTS service. Parameters: instructions: Instructions to guide voice synthesis behavior. diff --git a/src/pipecat/services/openai_realtime_beta/openai.py b/src/pipecat/services/openai_realtime_beta/openai.py index b7703ad98..b456ed0b8 100644 --- a/src/pipecat/services/openai_realtime_beta/openai.py +++ b/src/pipecat/services/openai_realtime_beta/openai.py @@ -94,7 +94,7 @@ class CurrentAudioResponse: @dataclass class OpenAIRealtimeBetaLLMSettings(LLMSettings): - """Typed settings for OpenAI Realtime Beta LLM services. + """Settings for OpenAI Realtime Beta LLM services. Parameters: session_properties: OpenAI Realtime session configuration. @@ -357,13 +357,13 @@ class OpenAIRealtimeBetaLLMService(LLMService): frame: The frame to process. direction: The direction of frame flow in the pipeline. """ - # Legacy dict path: frame.settings contains SessionProperties fields, - # not our Settings fields, so we construct SessionProperties directly. - # The new typed path (frame.update) falls through to super, which calls - # _update_settings_from_typed → our override handles the rest. + # Backward-compatible dict path: frame.settings contains SessionProperties + # fields, not our Settings fields, so we construct SessionProperties + # directly. The frame.update path falls through to super, which calls + # _update_settings → our override handles the rest. if isinstance(frame, LLMUpdateSettingsFrame) and frame.update is None: self._settings.session_properties = events.SessionProperties(**frame.settings) - await self._update_settings() + await self._send_session_update() await self.push_frame(frame, direction) return @@ -403,7 +403,7 @@ class OpenAIRealtimeBetaLLMService(LLMService): elif isinstance(frame, RealtimeMessagesUpdateFrame): self._context = frame.context elif isinstance(frame, LLMSetToolsFrame): - await self._update_settings() + await self._send_session_update() elif isinstance(frame, RealtimeFunctionCallResultFrame): await self._handle_function_call_result(frame.result_frame) @@ -478,14 +478,14 @@ class OpenAIRealtimeBetaLLMService(LLMService): # treat a send-side error as fatal. await self.push_error(error_msg=f"Error sending client event: {e}", exception=e) - async def _update_settings_from_typed(self, update): - """Apply a typed settings update, sending a session update if needed.""" - changed = await super()._update_settings_from_typed(update) + async def _update_settings(self, update): + """Apply a settings update, sending a session update if needed.""" + changed = await super()._update_settings(update) if "session_properties" in changed: - await self._update_settings() + await self._send_session_update() return changed - async def _update_settings(self): + async def _send_session_update(self): settings = self._settings.session_properties # tools given in the context override the tools in the session properties if self._context and self._context.tools: @@ -540,7 +540,7 @@ class OpenAIRealtimeBetaLLMService(LLMService): async def _handle_evt_session_created(self, evt): # session.created is received right after connecting. Send a message # to configure the session properties. - await self._update_settings() + await self._send_session_update() async def _handle_evt_session_updated(self, evt): # If this is our first context frame, run the LLM @@ -779,7 +779,7 @@ class OpenAIRealtimeBetaLLMService(LLMService): self._context.llm_needs_initial_messages = False if self._context.llm_needs_settings_update: - await self._update_settings() + await self._send_session_update() self._context.llm_needs_settings_update = False logger.debug(f"Creating response: {self._context.get_messages_for_logging()}") diff --git a/src/pipecat/services/playht/tts.py b/src/pipecat/services/playht/tts.py index 7d61ffd87..b63e5d648 100644 --- a/src/pipecat/services/playht/tts.py +++ b/src/pipecat/services/playht/tts.py @@ -101,7 +101,7 @@ def language_to_playht_language(language: Language) -> Optional[str]: @dataclass class PlayHTTTSSettings(TTSSettings): - """Typed settings for PlayHT TTS services. + """Settings for PlayHT TTS services. Parameters: output_format: Audio output format. diff --git a/src/pipecat/services/resembleai/tts.py b/src/pipecat/services/resembleai/tts.py index cd3da1767..08df23abe 100644 --- a/src/pipecat/services/resembleai/tts.py +++ b/src/pipecat/services/resembleai/tts.py @@ -42,7 +42,7 @@ except ModuleNotFoundError as e: @dataclass class ResembleAITTSSettings(TTSSettings): - """Typed settings for Resemble AI TTS service. + """Settings for Resemble AI TTS service. Parameters: precision: PCM bit depth (PCM_32, PCM_24, PCM_16, or MULAW). diff --git a/src/pipecat/services/rime/tts.py b/src/pipecat/services/rime/tts.py index 4af9fe63b..5f8a5cef6 100644 --- a/src/pipecat/services/rime/tts.py +++ b/src/pipecat/services/rime/tts.py @@ -72,7 +72,7 @@ def language_to_rime_language(language: Language) -> str: @dataclass class RimeTTSSettings(TTSSettings): - """Typed settings for Rime WS JSON and HTTP TTS services. + """Settings for Rime WS JSON and HTTP TTS services. Parameters: speaker: Voice speaker ID. @@ -101,7 +101,7 @@ class RimeTTSSettings(TTSSettings): @dataclass class RimeNonJsonTTSSettings(TTSSettings): - """Typed settings for Rime non-JSON WS TTS service. + """Settings for Rime non-JSON WS TTS service. Parameters: speaker: Voice speaker ID. @@ -271,10 +271,10 @@ class RimeTTSService(AudioContextWordTTSService): self._extra_msg_fields["inlineSpeedAlpha"] = ",".join(speed_vals + [str(speed)]) return f"[{text}]" - async def _update_settings_from_typed(self, update: TTSSettings) -> set[str]: - """Apply a typed settings update and reconnect if voice changed.""" + async def _update_settings(self, update: TTSSettings) -> set[str]: + """Apply a settings update and reconnect if voice changed.""" prev_voice = self._voice_id - changed = await super()._update_settings_from_typed(update) + changed = await super()._update_settings(update) if "voice" in changed: self._settings.speaker = self._voice_id await self._disconnect() @@ -975,13 +975,13 @@ class RimeNonJsonTTSService(InterruptibleTTSService): except Exception as e: yield ErrorFrame(error=f"Unknown error occurred: {e}") - async def _update_settings_from_typed(self, update: TTSSettings) -> set[str]: - """Apply a typed settings update and reconnect if necessary. + async def _update_settings(self, update: TTSSettings) -> set[str]: + """Apply a settings update and reconnect if necessary. Since all settings are WebSocket URL query parameters, any setting change requires reconnecting to apply the new values. """ - changed = await super()._update_settings_from_typed(update) + changed = await super()._update_settings(update) # Sync voice and model to settings dict fields if "voice" in changed: diff --git a/src/pipecat/services/sarvam/stt.py b/src/pipecat/services/sarvam/stt.py index 834171b32..68427fbc4 100644 --- a/src/pipecat/services/sarvam/stt.py +++ b/src/pipecat/services/sarvam/stt.py @@ -133,7 +133,7 @@ MODEL_CONFIGS: Dict[str, ModelConfig] = { @dataclass class SarvamSTTSettings(STTSettings): - """Typed settings for the Sarvam STT service. + """Settings for the Sarvam STT service. Parameters: prompt: Optional prompt to guide transcription/translation style. @@ -306,8 +306,8 @@ class SarvamSTTService(STTService): if self._socket_client: await self._socket_client.flush() - async def _update_settings_from_typed(self, update: STTSettings) -> set[str]: - """Apply a typed settings update, validate, sync state, and reconnect. + async def _update_settings(self, update: STTSettings) -> set[str]: + """Apply a settings update, validate, sync state, and reconnect. Args: update: A :class:`STTSettings` (or ``SarvamSTTSettings``) delta. @@ -336,7 +336,7 @@ class SarvamSTTService(STTService): if not self._config.supports_mode: raise ValueError(f"Model '{self.model_name}' does not support mode parameter.") - changed = await super()._update_settings_from_typed(update) + changed = await super()._update_settings(update) if not changed: return changed diff --git a/src/pipecat/services/sarvam/tts.py b/src/pipecat/services/sarvam/tts.py index ec51a85d5..56ce3bef0 100644 --- a/src/pipecat/services/sarvam/tts.py +++ b/src/pipecat/services/sarvam/tts.py @@ -247,7 +247,7 @@ def language_to_sarvam_language(language: Language) -> Optional[str]: @dataclass class SarvamHttpTTSSettings(TTSSettings): - """Typed settings for Sarvam HTTP TTS service. + """Settings for Sarvam HTTP TTS service. Parameters: language: Sarvam language code. @@ -277,7 +277,7 @@ class SarvamHttpTTSSettings(TTSSettings): @dataclass class SarvamWSTTSSettings(TTSSettings): - """Typed settings for Sarvam WebSocket TTS service. + """Settings for Sarvam WebSocket TTS service. Parameters: target_language_code: Sarvam language code. @@ -953,9 +953,9 @@ class SarvamTTSService(InterruptibleTTSService): if isinstance(frame, (LLMFullResponseEndFrame, EndFrame)): await self.flush_audio() - async def _update_settings_from_typed(self, update: TTSSettings) -> set[str]: - """Apply a typed settings update and resend config if voice changed.""" - changed = await super()._update_settings_from_typed(update) + async def _update_settings(self, update: TTSSettings) -> set[str]: + """Apply a settings update and resend config if voice changed.""" + changed = await super()._update_settings(update) if "voice" in changed: await self._send_config() return changed diff --git a/src/pipecat/services/settings.py b/src/pipecat/services/settings.py index 718996984..d63e1f539 100644 --- a/src/pipecat/services/settings.py +++ b/src/pipecat/services/settings.py @@ -4,13 +4,12 @@ # SPDX-License-Identifier: BSD 2-Clause License # -"""Typed settings infrastructure for Pipecat AI services. +"""Settings infrastructure for Pipecat AI services. -This module provides typed dataclass-based settings objects that replace the -stringly-typed ``Mapping[str, Any]`` dictionaries previously used for service -configuration. Each service type has a corresponding settings class (e.g. -``TTSSettings``, ``LLMSettings``) whose fields use the ``NOT_GIVEN`` sentinel -to distinguish "leave unchanged" from an explicit ``None``. +This module provides dataclass-based settings objects for service configuration. +Each service type has a corresponding settings class (e.g. ``TTSSettings``, +``LLMSettings``) whose fields use the ``NOT_GIVEN`` sentinel to distinguish +"leave unchanged" from an explicit ``None``. Key concepts: @@ -21,7 +20,7 @@ Key concepts: ``NOT_GIVEN`` are simply skipped when applying an update. - **apply_update**: Applies a delta onto a target settings object and returns the set of field names that actually changed. -- **from_mapping**: Constructs a typed settings object from a plain dict, +- **from_mapping**: Constructs a settings object from a plain dict, supporting field aliases (e.g. ``"voice_id"`` → ``"voice"``). - **Extras**: Unknown keys land in the ``extra`` dict so services that have non-standard settings don't lose data. @@ -91,7 +90,7 @@ _S = TypeVar("_S", bound="ServiceSettings") @dataclass class ServiceSettings: - """Base class for typed service settings. + """Base class for service settings. Every AI service type (LLM, TTS, STT) extends this with its own fields. Fields default to ``NOT_GIVEN`` so that an instance can represent either @@ -188,7 +187,10 @@ class ServiceSettings: @classmethod def from_mapping(cls: Type[_S], settings: Mapping[str, Any]) -> _S: - """Construct a typed settings object from a plain dictionary. + """Construct a settings object from a plain dictionary. + + This exists for backward compatibility with code that passes plain + dicts via ``*UpdateSettingsFrame(settings={...})``. Keys are matched to dataclass fields by name. Keys listed in ``_aliases`` are translated to their canonical name first. Any @@ -250,7 +252,7 @@ class ServiceSettings: @dataclass class LLMSettings(ServiceSettings): - """Typed settings for LLM services. + """Settings for LLM services. Parameters: model: LLM model identifier. @@ -285,7 +287,7 @@ class LLMSettings(ServiceSettings): @dataclass class TTSSettings(ServiceSettings): - """Typed settings for TTS services. + """Settings for TTS services. Parameters: model: TTS model identifier. @@ -301,7 +303,7 @@ class TTSSettings(ServiceSettings): @dataclass class STTSettings(ServiceSettings): - """Typed settings for STT services. + """Settings for STT services. Parameters: model: STT model identifier. diff --git a/src/pipecat/services/soniox/stt.py b/src/pipecat/services/soniox/stt.py index c3d9638c1..a74a14ee9 100644 --- a/src/pipecat/services/soniox/stt.py +++ b/src/pipecat/services/soniox/stt.py @@ -138,7 +138,7 @@ def _prepare_language_hints( @dataclass class SonioxSTTSettings(STTSettings): - """Typed settings for Soniox STT service. + """Settings for Soniox STT service. Parameters: input_params: Soniox ``SonioxInputParams`` for detailed configuration. @@ -217,8 +217,8 @@ class SonioxSTTService(WebsocketSTTService): await super().start(frame) await self._connect() - async def _update_settings_from_typed(self, update: SonioxSTTSettings) -> set[str]: - """Apply a typed settings update, keeping ``input_params`` in sync. + async def _update_settings(self, update: SonioxSTTSettings) -> set[str]: + """Apply a settings update, keeping ``input_params`` in sync. Top-level ``model`` is the source of truth. When it is given in *update* its value is propagated into ``input_params``. When only @@ -228,14 +228,14 @@ class SonioxSTTService(WebsocketSTTService): Any change triggers a WebSocket reconnect. Args: - update: A typed settings delta. + update: A settings delta. Returns: Set of field names whose values actually changed. """ model_given = is_given(getattr(update, "model", NOT_GIVEN)) - changed = await super()._update_settings_from_typed(update) + changed = await super()._update_settings(update) if not changed: return changed diff --git a/src/pipecat/services/speechmatics/stt.py b/src/pipecat/services/speechmatics/stt.py index 462c2fc6f..5bacc208a 100644 --- a/src/pipecat/services/speechmatics/stt.py +++ b/src/pipecat/services/speechmatics/stt.py @@ -85,7 +85,7 @@ class TurnDetectionMode(str, Enum): @dataclass class SpeechmaticsSTTSettings(STTSettings): - """Typed settings for Speechmatics STT service. + """Settings for Speechmatics STT service. See ``SpeechmaticsSTTService.InputParams`` for detailed descriptions of each field. @@ -415,7 +415,7 @@ class SpeechmaticsSTTService(STTService): ) speaker_passive_format = params.speaker_passive_format or speaker_active_format - # Typed settings — seeded from InputParams + # Settings — seeded from InputParams self._settings = SpeechmaticsSTTSettings( language=params.language, domain=params.domain, @@ -480,8 +480,8 @@ class SpeechmaticsSTTService(STTService): await super().start(frame) await self._connect() - async def _update_settings_from_typed(self, update: SpeechmaticsSTTSettings) -> set[str]: - """Apply typed settings update, reconnecting only when necessary. + async def _update_settings(self, update: SpeechmaticsSTTSettings) -> set[str]: + """Apply settings update, reconnecting only when necessary. Fields are classified into three categories (see ``SpeechmaticsSTTSettings``): @@ -494,12 +494,12 @@ class SpeechmaticsSTTService(STTService): time and therefore require a full disconnect / reconnect. Args: - update: A typed settings delta. + update: A settings delta. Returns: Set of field names whose values actually changed. """ - changed = await super()._update_settings_from_typed(update) + changed = await super()._update_settings(update) if not changed: return changed diff --git a/src/pipecat/services/stt_service.py b/src/pipecat/services/stt_service.py index 3ce143d92..e92095297 100644 --- a/src/pipecat/services/stt_service.py +++ b/src/pipecat/services/stt_service.py @@ -12,7 +12,7 @@ import time import warnings import wave from abc import abstractmethod -from typing import Any, AsyncGenerator, Dict, Mapping, Optional +from typing import Any, AsyncGenerator, Optional from loguru import logger from websockets.protocol import State @@ -35,7 +35,7 @@ from pipecat.frames.frames import ( from pipecat.metrics.metrics import TTFBMetricsData from pipecat.processors.frame_processor import FrameDirection from pipecat.services.ai_service import AIService -from pipecat.services.settings import ServiceSettings, STTSettings +from pipecat.services.settings import STTSettings from pipecat.services.stt_latency import DEFAULT_TTFS_P99 from pipecat.services.websocket_service import WebsocketService from pipecat.transcriptions.language import Language @@ -183,11 +183,8 @@ class STTService(AIService): stacklevel=2, ) logger.info(f"Switching STT model to: [{model}]") - if isinstance(self._settings, ServiceSettings): - settings_cls = type(self._settings) - await self._update_settings_from_typed(settings_cls(model=model)) - else: - self.set_model_name(model) + settings_cls = type(self._settings) + await self._update_settings(settings_cls(model=model)) async def set_language(self, language: Language): """Set the language for speech recognition. @@ -206,11 +203,8 @@ class STTService(AIService): stacklevel=2, ) logger.info(f"Switching STT language to: [{language}]") - if isinstance(self._settings, ServiceSettings): - settings_cls = type(self._settings) - await self._update_settings_from_typed(settings_cls(language=language)) - else: - pass + settings_cls = type(self._settings) + await self._update_settings(settings_cls(language=language)) @abstractmethod async def run_stt(self, audio: bytes) -> AsyncGenerator[Frame, None]: @@ -242,23 +236,8 @@ class STTService(AIService): await super().cleanup() await self._cancel_ttfb_timeout() - async def _update_settings(self, settings: Mapping[str, Any]): - logger.info(f"Updating STT settings: {self._settings}") - for key, value in settings.items(): - if key in self._settings: - logger.info(f"Updating STT setting {key} to: [{value}]") - self._settings[key] = value - if key == "language": - await self.set_language(value) - elif key == "language": - await self.set_language(value) - elif key == "model": - self.set_model_name(value) - else: - logger.warning(f"Unknown setting for STT service: {key}") - - async def _update_settings_from_typed(self, update: STTSettings) -> set[str]: - """Apply a typed STT settings update. + async def _update_settings(self, update: STTSettings) -> set[str]: + """Apply an STT settings update. Handles ``model`` (via parent). Does **not** call ``set_language`` — concrete services should override this method and handle language @@ -266,12 +245,12 @@ class STTService(AIService): changed-field set. Args: - update: A typed STT settings delta. + update: An STT settings delta. Returns: Set of field names whose values actually changed. """ - changed = await super()._update_settings_from_typed(update) + changed = await super()._update_settings(update) return changed async def process_audio_frame(self, frame: AudioRawFrame, direction: FrameDirection): @@ -335,16 +314,12 @@ class STTService(AIService): await self._handle_vad_user_stopped_speaking(frame) await self.push_frame(frame, direction) elif isinstance(frame, STTUpdateSettingsFrame): - # New path: typed settings update object. if frame.update is not None: - await self._update_settings_from_typed(frame.update) - # Legacy path: plain dict, but service uses typed settings — convert. - elif isinstance(self._settings, ServiceSettings): + await self._update_settings(frame.update) + elif frame.settings: + # Backward-compatible path: convert legacy dict to settings object. update = type(self._settings).from_mapping(frame.settings) - await self._update_settings_from_typed(update) - # Legacy path: plain dict, service still uses dict-based settings. - else: - await self._update_settings(frame.settings) + await self._update_settings(update) elif isinstance(frame, STTMuteFrame): self._muted = frame.mute logger.debug(f"STT service {'muted' if frame.mute else 'unmuted'}") diff --git a/src/pipecat/services/tts_service.py b/src/pipecat/services/tts_service.py index b16ebdb24..a696e538d 100644 --- a/src/pipecat/services/tts_service.py +++ b/src/pipecat/services/tts_service.py @@ -19,7 +19,6 @@ from typing import ( Callable, Dict, List, - Mapping, Optional, Sequence, Tuple, @@ -53,7 +52,7 @@ from pipecat.frames.frames import ( ) from pipecat.processors.frame_processor import FrameDirection from pipecat.services.ai_service import AIService -from pipecat.services.settings import ServiceSettings, TTSSettings, is_given +from pipecat.services.settings import TTSSettings, is_given from pipecat.services.websocket_service import WebsocketService from pipecat.transcriptions.language import Language from pipecat.utils.text.base_text_aggregator import BaseTextAggregator @@ -280,11 +279,8 @@ class TTSService(AIService): stacklevel=2, ) logger.info(f"Switching TTS model to: [{model}]") - if isinstance(self._settings, ServiceSettings): - settings_cls = type(self._settings) - await self._update_settings_from_typed(settings_cls(model=model)) - else: - self.set_model_name(model) + settings_cls = type(self._settings) + await self._update_settings(settings_cls(model=model)) async def set_voice(self, voice: str): """Set the voice for speech synthesis. @@ -303,11 +299,8 @@ class TTSService(AIService): stacklevel=2, ) logger.info(f"Switching TTS voice to: [{voice}]") - if isinstance(self._settings, ServiceSettings): - settings_cls = type(self._settings) - await self._update_settings_from_typed(settings_cls(voice=voice)) - else: - self._voice_id = voice + settings_cls = type(self._settings) + await self._update_settings(settings_cls(voice=voice)) def create_context_id(self) -> str: """Generate a unique context ID for a TTS request. @@ -439,25 +432,8 @@ class TTSService(AIService): if not (agg_type == aggregation_type and func == transform_function) ] - async def _update_settings(self, settings: Mapping[str, Any]): - for key, value in settings.items(): - if key in self._settings: - logger.info(f"Updating TTS setting {key} to: [{value}]") - self._settings[key] = value - if key == "language": - self._settings[key] = self.language_to_service_language(value) - elif key == "model": - self.set_model_name(value) - elif key == "voice" or key == "voice_id": - self._voice_id = value - elif key == "text_filter": - for filter in self._text_filters: - await filter.update_settings(value) - else: - logger.warning(f"Unknown setting for TTS service: {key}") - - async def _update_settings_from_typed(self, update: TTSSettings) -> set[str]: - """Apply a typed TTS settings update. + async def _update_settings(self, update: TTSSettings) -> set[str]: + """Apply a TTS settings update. Handles ``model`` (via parent) and syncs ``_voice_id`` when voice changes. Translates language values before applying. Does **not** @@ -466,7 +442,7 @@ class TTSService(AIService): returned changed-field set. Args: - update: A typed TTS settings delta. + update: A TTS settings delta. Returns: Set of field names whose values actually changed. @@ -477,10 +453,10 @@ class TTSService(AIService): if converted is not None: update.language = converted - changed = await super()._update_settings_from_typed(update) + changed = await super()._update_settings(update) # Keep _voice_id in sync for code that reads it directly - if "voice" in changed and isinstance(self._settings, TTSSettings): + if "voice" in changed: self._voice_id = self._settings.voice return changed @@ -566,16 +542,12 @@ class TTSService(AIService): await self.flush_audio() self._processing_text = processing_text elif isinstance(frame, TTSUpdateSettingsFrame): - # New path: typed settings update object. if frame.update is not None: - await self._update_settings_from_typed(frame.update) - # Legacy path: plain dict, but service uses typed settings — convert. - elif isinstance(self._settings, ServiceSettings): + await self._update_settings(frame.update) + elif frame.settings: + # Backward-compatible path: convert legacy dict to settings object. update = type(self._settings).from_mapping(frame.settings) - await self._update_settings_from_typed(update) - # Legacy path: plain dict, service still uses dict-based settings. - else: - await self._update_settings(frame.settings) + await self._update_settings(update) elif isinstance(frame, BotStoppedSpeakingFrame): await self._maybe_resume_frame_processing() await self.push_frame(frame, direction) diff --git a/src/pipecat/services/ultravox/llm.py b/src/pipecat/services/ultravox/llm.py index 6f5e5d2ee..434a54ab6 100644 --- a/src/pipecat/services/ultravox/llm.py +++ b/src/pipecat/services/ultravox/llm.py @@ -325,8 +325,8 @@ class UltravoxRealtimeLLMService(LLMService): await self.cancel_task(self._receive_task, timeout=1.0) self._receive_task = None - async def _update_settings_from_typed(self, update: UltravoxRealtimeLLMSettings): - changed = await super()._update_settings_from_typed(update) + async def _update_settings(self, update: UltravoxRealtimeLLMSettings): + changed = await super()._update_settings(update) if "output_medium" in changed: await self._update_output_medium(self._settings.output_medium) return changed diff --git a/src/pipecat/services/whisper/base_stt.py b/src/pipecat/services/whisper/base_stt.py index 6c35824a4..6ff85efeb 100644 --- a/src/pipecat/services/whisper/base_stt.py +++ b/src/pipecat/services/whisper/base_stt.py @@ -28,7 +28,7 @@ from pipecat.utils.tracing.service_decorators import traced_stt @dataclass class BaseWhisperSTTSettings(STTSettings): - """Typed settings for Whisper API-based STT services. + """Settings for Whisper API-based STT services. Parameters: base_url: API base URL. @@ -174,13 +174,13 @@ class BaseWhisperSTTService(SegmentedSTTService): def _create_client(self, api_key: Optional[str], base_url: Optional[str]): return AsyncOpenAI(api_key=api_key, base_url=base_url) - async def _update_settings_from_typed(self, update: STTSettings) -> set[str]: - """Apply a typed settings update, syncing instance variables. + async def _update_settings(self, update: STTSettings) -> set[str]: + """Apply a settings update, syncing instance variables. Keeps ``_language``, ``_prompt``, and ``_temperature`` in sync with - the typed settings fields. + the settings fields. """ - changed = await super()._update_settings_from_typed(update) + changed = await super()._update_settings(update) if "language" in changed: self._language = self.language_to_service_language(Language(self._settings.language)) diff --git a/src/pipecat/services/whisper/stt.py b/src/pipecat/services/whisper/stt.py index d5f4c3f1b..a96c26992 100644 --- a/src/pipecat/services/whisper/stt.py +++ b/src/pipecat/services/whisper/stt.py @@ -176,7 +176,7 @@ def language_to_whisper_language(language: Language) -> Optional[str]: @dataclass class WhisperSTTSettings(STTSettings): - """Typed settings for the local Whisper (Faster Whisper) STT service. + """Settings for the local Whisper (Faster Whisper) STT service. Parameters: device: Inference device ('cpu', 'cuda', or 'auto'). @@ -191,7 +191,7 @@ class WhisperSTTSettings(STTSettings): @dataclass class WhisperMLXSTTSettings(STTSettings): - """Typed settings for the MLX Whisper STT service. + """Settings for the MLX Whisper STT service. Parameters: no_speech_prob: Probability threshold for filtering non-speech segments. diff --git a/src/pipecat/services/xtts/tts.py b/src/pipecat/services/xtts/tts.py index 4415f9f53..3ba332138 100644 --- a/src/pipecat/services/xtts/tts.py +++ b/src/pipecat/services/xtts/tts.py @@ -72,7 +72,7 @@ def language_to_xtts_language(language: Language) -> Optional[str]: @dataclass class XTTSTTSSettings(TTSSettings): - """Typed settings for XTTS TTS service. + """Settings for XTTS TTS service. Parameters: base_url: Base URL of the XTTS streaming server. From 66b7b4a5d4232ba6a38be38c6247648cc5db99d6 Mon Sep 17 00:00:00 2001 From: Paul Kompfner Date: Fri, 13 Feb 2026 16:04:49 -0500 Subject: [PATCH 0490/1060] Update COMMUNITY_INTEGRATIONS.md for the new dataclass-based service settings pattern. --- COMMUNITY_INTEGRATIONS.md | 54 +++++++++++++++++++++++++++++++-------- 1 file changed, 43 insertions(+), 11 deletions(-) diff --git a/COMMUNITY_INTEGRATIONS.md b/COMMUNITY_INTEGRATIONS.md index a26836a52..c169cb5ab 100644 --- a/COMMUNITY_INTEGRATIONS.md +++ b/COMMUNITY_INTEGRATIONS.md @@ -235,22 +235,54 @@ def can_generate_metrics(self) -> bool: ### Dynamic Settings Updates -STT, LLM, and TTS services support `ServiceUpdateSettingsFrame` for dynamic configuration changes. The base STTService has an `_update_settings()` method that handles settings, and the private `_settings` `Dict` is used to store settings and provide access to the subclass. +STT, LLM, and TTS services support runtime configuration changes via `*UpdateSettingsFrame`s (e.g. `STTUpdateSettingsFrame`, `TTSUpdateSettingsFrame`, `LLMUpdateSettingsFrame`). + +Each service declares a settings dataclass that extends the appropriate base (`STTSettings`, `TTSSettings`, `LLMSettings`). Fields default to `NOT_GIVEN` so that update objects can represent sparse deltas: ```python -async def set_language(self, language: Language): - """Set the recognition language and reconnect. +from dataclasses import dataclass, field - Args: - language: The language to use for speech recognition. +from pipecat.services.settings import STTSettings, NOT_GIVEN + +@dataclass +class MySTTSettings(STTSettings): + """Settings for my STT service. + + Parameters: + region: Cloud region for the service. """ - logger.info(f"Switching STT language to: [{language}]") - self._settings["language"] = language - await self._disconnect() - await self._connect() + + region: str = field(default_factory=lambda: NOT_GIVEN) ``` -Note that, in this example, Deepgram requires the websocket connection be disconnected and reconnected to reinitialize the service with the new value. Consider if your service requires reconnection. +The service stores its current settings in `self._settings` and declares the type with a class-level annotation for editor support: + +```python +class MySTTService(STTService): + + _settings: MySTTSettings + + def __init__(self, *, model: str, region: str, **kwargs): + super().__init__(**kwargs) + self._settings = MySTTSettings(model=model, region=region) +``` + +To react to runtime setting changes, override `_update_settings`. The base implementation applies the delta to `self._settings` and returns the set of field names that changed. Your override should call `super()` first, then act on the changed fields: + +```python +async def _update_settings(self, update: STTSettings) -> set[str]: + """Apply a settings update, reconfiguring the recognizer if needed.""" + changed = await super()._update_settings(update) + + if "language" in changed: + # Restart the recognizer with the new language. + await self._disconnect() + await self._connect() + + return changed +``` + +Note that, in this example, the service requires a reconnect to apply the new language. Consider whether your service requires reconnection or can apply changes in-place. ### Sample Rate Handling @@ -260,7 +292,7 @@ Sample rates are set via PipelineParams and passed to each frame processor at in async def start(self, frame: StartFrame): """Start the service.""" await super().start(frame) - self._settings["output_format"]["sample_rate"] = self.sample_rate + self._settings.output_sample_rate = self.sample_rate await self._connect() ``` From 012ef41ff4b9ffe2f71423100476f748ed7b3a7f Mon Sep 17 00:00:00 2001 From: Mark Backman Date: Sat, 14 Feb 2026 08:22:33 -0500 Subject: [PATCH 0491/1060] Redesign UserIdleController to use BotStoppedSpeakingFrame Replace the continuous heartbeat-based timer (UserSpeakingFrame/BotSpeakingFrame + asyncio.Event loop) with a simple one-shot timer that starts when BotStoppedSpeakingFrame is received and cancels on UserStartedSpeakingFrame or BotStartedSpeakingFrame. This eliminates false idle triggers caused by gaps between the user finishing speaking and the bot starting to speak (LLM/TTS latency). Guard the timer start with two conditions to prevent false triggers: - User turn in progress: during interruptions, BotStoppedSpeaking arrives while the user is still speaking mid-turn. - Function calls in progress: FunctionCallsStarted arrives before BotStoppedSpeaking because the bot speaks concurrently with the function call starting, so the timer must wait for the result and subsequent bot response. --- examples/foundational/17-detect-user-idle.py | 54 +++- .../aggregators/llm_response_universal.py | 6 + src/pipecat/turns/user_idle_controller.py | 146 ++++------ src/pipecat/turns/user_turn_processor.py | 6 + tests/test_user_idle_controller.py | 272 ++++++++++-------- 5 files changed, 277 insertions(+), 207 deletions(-) diff --git a/examples/foundational/17-detect-user-idle.py b/examples/foundational/17-detect-user-idle.py index ae2727c6a..bb0ea8873 100644 --- a/examples/foundational/17-detect-user-idle.py +++ b/examples/foundational/17-detect-user-idle.py @@ -5,11 +5,14 @@ # +import asyncio import os from dotenv import load_dotenv from loguru import logger +from pipecat.adapters.schemas.function_schema import FunctionSchema +from pipecat.adapters.schemas.tools_schema import ToolsSchema from pipecat.audio.vad.silero import SileroVADAnalyzer from pipecat.frames.frames import ( EndTaskFrame, @@ -30,6 +33,7 @@ from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport from pipecat.services.cartesia.tts import CartesiaTTSService from pipecat.services.deepgram.stt import DeepgramSTTService +from pipecat.services.llm_service import FunctionCallParams from pipecat.services.openai.llm import OpenAILLMService from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams @@ -74,6 +78,17 @@ class IdleHandler: await aggregator.push_frame(EndTaskFrame(), FrameDirection.UPSTREAM) +async def fetch_weather_from_api(params: FunctionCallParams): + # Simulate a slow API call, waiting longer than the user idle timeout. + await asyncio.sleep(3) + await params.result_callback({"conditions": "nice", "temperature": "75"}) + + +async def fetch_restaurant_recommendation(params: FunctionCallParams): + await asyncio.sleep(6) + await params.result_callback({"name": "The Golden Dragon"}) + + # We use lambdas to defer transport parameter creation until the transport # type is selected at runtime. transport_params = { @@ -104,6 +119,42 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): llm = OpenAILLMService(api_key=os.getenv("OPENAI_API_KEY")) + llm.register_function("get_current_weather", fetch_weather_from_api) + llm.register_function("get_restaurant_recommendation", fetch_restaurant_recommendation) + + @llm.event_handler("on_function_calls_started") + async def on_function_calls_started(service, function_calls): + await tts.queue_frame(TTSSpeakFrame("Let me check on that.")) + + weather_function = FunctionSchema( + name="get_current_weather", + description="Get the current weather", + properties={ + "location": { + "type": "string", + "description": "The city and state, e.g. San Francisco, CA", + }, + "format": { + "type": "string", + "enum": ["celsius", "fahrenheit"], + "description": "The temperature unit to use. Infer this from the user's location.", + }, + }, + required=["location", "format"], + ) + restaurant_function = FunctionSchema( + name="get_restaurant_recommendation", + description="Get a restaurant recommendation", + properties={ + "location": { + "type": "string", + "description": "The city and state, e.g. San Francisco, CA", + }, + }, + required=["location"], + ) + tools = ToolsSchema(standard_tools=[weather_function, restaurant_function]) + messages = [ { "role": "system", @@ -111,7 +162,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): }, ] - context = LLMContext(messages) + context = LLMContext(messages, tools) user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, user_params=LLMUserAggregatorParams( @@ -146,6 +197,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): @user_aggregator.event_handler("on_user_turn_idle") async def on_user_turn_idle(aggregator): + logger.info(f"User turn idle") await idle_handler.handle_idle(aggregator) @user_aggregator.event_handler("on_user_turn_started") diff --git a/src/pipecat/processors/aggregators/llm_response_universal.py b/src/pipecat/processors/aggregators/llm_response_universal.py index 6b28b5bf2..0fb538b1a 100644 --- a/src/pipecat/processors/aggregators/llm_response_universal.py +++ b/src/pipecat/processors/aggregators/llm_response_universal.py @@ -689,6 +689,9 @@ class LLMUserAggregator(LLMContextAggregator): if params.enable_user_speaking_frames: await self.broadcast_frame(UserStartedSpeakingFrame) + if self._user_idle_controller: + await self._user_idle_controller.process_frame(UserStartedSpeakingFrame()) + if params.enable_interruptions and self._allow_interruptions: await self.push_interruption_task_frame_and_wait() @@ -705,6 +708,9 @@ class LLMUserAggregator(LLMContextAggregator): if params.enable_user_speaking_frames: await self.broadcast_frame(UserStoppedSpeakingFrame) + if self._user_idle_controller: + await self._user_idle_controller.process_frame(UserStoppedSpeakingFrame()) + await self._maybe_emit_user_turn_stopped(strategy) async def _on_user_turn_stop_timeout(self, controller): diff --git a/src/pipecat/turns/user_idle_controller.py b/src/pipecat/turns/user_idle_controller.py index cce35b9cb..b4dc80772 100644 --- a/src/pipecat/turns/user_idle_controller.py +++ b/src/pipecat/turns/user_idle_controller.py @@ -10,12 +10,14 @@ import asyncio from typing import Optional from pipecat.frames.frames import ( - BotSpeakingFrame, + BotStartedSpeakingFrame, + BotStoppedSpeakingFrame, Frame, + FunctionCallCancelFrame, FunctionCallResultFrame, FunctionCallsStartedFrame, - UserSpeakingFrame, UserStartedSpeakingFrame, + UserStoppedSpeakingFrame, ) from pipecat.utils.asyncio.task_manager import BaseTaskManager from pipecat.utils.base_object import BaseObject @@ -25,14 +27,14 @@ class UserIdleController(BaseObject): """Controller for managing user idle detection. This class monitors user activity and triggers an event when the user has been - idle (not speaking) for a configured timeout period. It only starts monitoring - after the first conversation activity and does not trigger while the bot is - speaking or function calls are in progress. + idle (not speaking) for a configured timeout period after the bot finishes + speaking. The timer starts when BotStoppedSpeakingFrame is received and is + cancelled when someone starts speaking again (UserStartedSpeakingFrame or + BotStartedSpeakingFrame). - The controller tracks activity using continuous frames (UserSpeakingFrame and - BotSpeakingFrame) which are emitted repeatedly while speaking is happening, and - state-based tracking for function calls (FunctionCallsStartedFrame and - FunctionCallResultFrame) which are only sent at start and end. + The timer is suppressed while a user turn is in progress to avoid false + triggers during interruptions (where BotStoppedSpeakingFrame arrives while + the user is still speaking). Event handlers available: @@ -62,11 +64,9 @@ class UserIdleController(BaseObject): self._task_manager: Optional[BaseTaskManager] = None - self._conversation_started = False - self._function_call_in_progress = False - - self.user_idle_event = asyncio.Event() - self.user_idle_task: Optional[asyncio.Task] = None + self._user_turn_in_progress: bool = False + self._function_calls_in_progress: int = 0 + self._idle_timer_task: Optional[asyncio.Task] = None self._register_event_handler("on_user_turn_idle", sync=True) @@ -85,19 +85,10 @@ class UserIdleController(BaseObject): """ self._task_manager = task_manager - if not self.user_idle_task: - self.user_idle_task = self.task_manager.create_task( - self.user_idle_task_handler(), - f"{self}::user_idle_task_handler", - ) - async def cleanup(self): """Cleanup the controller.""" await super().cleanup() - - if self.user_idle_task: - await self.task_manager.cancel_task(self.user_idle_task) - self.user_idle_task = None + await self._cancel_idle_timer() async def process_frame(self, frame: Frame): """Process an incoming frame to track user activity state. @@ -105,69 +96,52 @@ class UserIdleController(BaseObject): Args: frame: The frame to be processed. """ - # Start monitoring on first conversation activity - if not self._conversation_started: - if isinstance(frame, (UserStartedSpeakingFrame, BotSpeakingFrame)): - self._conversation_started = True - self.user_idle_event.set() - else: - return - - # Reset idle timer on continuous activity frames - if isinstance(frame, (UserSpeakingFrame, BotSpeakingFrame)): - await self._handle_activity(frame) - # Track function call state (start/end frames, not continuous) + if isinstance(frame, BotStoppedSpeakingFrame): + # Only start the timer if the user isn't mid-turn and no function + # calls are pending. + # + # Interruption case: the frame order is UserStartedSpeaking → + # BotStoppedSpeaking → (user keeps talking) → UserStoppedSpeaking. + # Without the user-turn guard the timer would start while the user + # is still speaking. + # + # Function call case: normally FunctionCallsStarted arrives after + # BotStoppedSpeaking and cancels the timer directly. But a race + # condition can cause FunctionCallsStarted to arrive before + # BotStoppedSpeaking when pushing a TTSSpeakFrame in the + # on_function_calls_started event handler, so the counter guard + # prevents the timer from starting while a function call is in progress. + if not self._user_turn_in_progress and self._function_calls_in_progress == 0: + await self._start_idle_timer() + elif isinstance(frame, BotStartedSpeakingFrame): + await self._cancel_idle_timer() + elif isinstance(frame, UserStartedSpeakingFrame): + self._user_turn_in_progress = True + await self._cancel_idle_timer() + elif isinstance(frame, UserStoppedSpeakingFrame): + self._user_turn_in_progress = False elif isinstance(frame, FunctionCallsStartedFrame): - await self._handle_function_calls_started(frame) - elif isinstance(frame, FunctionCallResultFrame): - await self._handle_function_call_result(frame) + self._function_calls_in_progress += len(frame.function_calls) + await self._cancel_idle_timer() + elif isinstance(frame, (FunctionCallResultFrame, FunctionCallCancelFrame)): + self._function_calls_in_progress = max(0, self._function_calls_in_progress - 1) - async def _handle_activity(self, _: UserSpeakingFrame | BotSpeakingFrame): - """Handle continuous activity frames that should reset the idle timer. + async def _start_idle_timer(self): + """Start (or restart) the idle timer.""" + await self._cancel_idle_timer() + self._idle_timer_task = self.task_manager.create_task( + self._idle_timer_expired(), + f"{self}::idle_timer", + ) - These frames are emitted continuously while the user or bot is speaking, - so we simply reset the timer whenever we receive them. + async def _cancel_idle_timer(self): + """Cancel the idle timer if running.""" + if self._idle_timer_task: + await self.task_manager.cancel_task(self._idle_timer_task) + self._idle_timer_task = None - Args: - frame: The activity frame to process. - """ - self.user_idle_event.set() - - async def _handle_function_calls_started(self, _: FunctionCallsStartedFrame): - """Handle function calls started event. - - Function calls can take longer than the timeout, so we track their state - to prevent idle callbacks while they're in progress. - - Args: - frame: The FunctionCallsStartedFrame to process. - """ - self._function_call_in_progress = True - self.user_idle_event.set() - - async def _handle_function_call_result(self, _: FunctionCallResultFrame): - """Handle function call result event. - - Args: - frame: The FunctionCallResultFrame to process. - """ - self._function_call_in_progress = False - self.user_idle_event.set() - - async def user_idle_task_handler(self): - """Monitors for idle timeout and triggers events. - - Runs in a loop until cancelled. The idle timer is reset whenever activity - frames are received (UserSpeakingFrame or BotSpeakingFrame). Function calls - are tracked via state since they only send start/end frames. If no activity - is detected for the configured timeout period and no function call is in - progress, the on_user_turn_idle event is triggered. - """ - while True: - try: - await asyncio.wait_for(self.user_idle_event.wait(), timeout=self._user_idle_timeout) - self.user_idle_event.clear() - except asyncio.TimeoutError: - # Only trigger if conversation has started and no function call is in progress - if self._conversation_started and not self._function_call_in_progress: - await self._call_event_handler("on_user_turn_idle") + async def _idle_timer_expired(self): + """Sleep for the timeout duration then fire the idle event.""" + await asyncio.sleep(self._user_idle_timeout) + self._idle_timer_task = None + await self._call_event_handler("on_user_turn_idle") diff --git a/src/pipecat/turns/user_turn_processor.py b/src/pipecat/turns/user_turn_processor.py index 6c771811e..720a8b854 100644 --- a/src/pipecat/turns/user_turn_processor.py +++ b/src/pipecat/turns/user_turn_processor.py @@ -189,6 +189,9 @@ class UserTurnProcessor(FrameProcessor): if params.enable_user_speaking_frames: await self.broadcast_frame(UserStartedSpeakingFrame) + if self._user_idle_controller: + await self._user_idle_controller.process_frame(UserStartedSpeakingFrame()) + if params.enable_interruptions and self._allow_interruptions: await self.push_interruption_task_frame_and_wait() @@ -205,6 +208,9 @@ class UserTurnProcessor(FrameProcessor): if params.enable_user_speaking_frames: await self.broadcast_frame(UserStoppedSpeakingFrame) + if self._user_idle_controller: + await self._user_idle_controller.process_frame(UserStoppedSpeakingFrame()) + await self._call_event_handler("on_user_turn_stopped", strategy) async def _on_user_turn_stop_timeout(self, controller): diff --git a/tests/test_user_idle_controller.py b/tests/test_user_idle_controller.py index 4b6cbe1d3..6975d6e74 100644 --- a/tests/test_user_idle_controller.py +++ b/tests/test_user_idle_controller.py @@ -6,12 +6,13 @@ import asyncio import unittest +import unittest.mock from pipecat.frames.frames import ( - BotSpeakingFrame, + BotStartedSpeakingFrame, + BotStoppedSpeakingFrame, FunctionCallResultFrame, FunctionCallsStartedFrame, - UserSpeakingFrame, UserStartedSpeakingFrame, ) from pipecat.turns.user_idle_controller import UserIdleController @@ -25,8 +26,8 @@ class TestUserIdleController(unittest.IsolatedAsyncioTestCase): self.task_manager = TaskManager() self.task_manager.setup(TaskManagerParams(loop=asyncio.get_running_loop())) - async def test_basic_idle_detection(self): - """Test that idle event is triggered after timeout when no activity.""" + async def test_idle_after_bot_stops_speaking(self): + """Test that idle event fires after BotStoppedSpeakingFrame + timeout.""" controller = UserIdleController(user_idle_timeout=USER_IDLE_TIMEOUT) await controller.setup(self.task_manager) @@ -37,18 +38,16 @@ class TestUserIdleController(unittest.IsolatedAsyncioTestCase): nonlocal idle_triggered idle_triggered = True - # Start conversation - await controller.process_frame(UserStartedSpeakingFrame()) + await controller.process_frame(BotStoppedSpeakingFrame()) - # Wait for idle timeout await asyncio.sleep(USER_IDLE_TIMEOUT + 0.1) self.assertTrue(idle_triggered) await controller.cleanup() - async def test_user_speaking_resets_idle_timer(self): - """Test that continuous UserSpeakingFrame frames reset the idle timer.""" + async def test_user_speaking_cancels_timer(self): + """Test that UserStartedSpeakingFrame cancels the idle timer.""" controller = UserIdleController(user_idle_timeout=USER_IDLE_TIMEOUT) await controller.setup(self.task_manager) @@ -59,20 +58,18 @@ class TestUserIdleController(unittest.IsolatedAsyncioTestCase): nonlocal idle_triggered idle_triggered = True - # Start conversation + await controller.process_frame(BotStoppedSpeakingFrame()) + await asyncio.sleep(USER_IDLE_TIMEOUT * 0.3) await controller.process_frame(UserStartedSpeakingFrame()) - # Send UserSpeakingFrame continuously to reset timer - for _ in range(5): - await asyncio.sleep(USER_IDLE_TIMEOUT * 0.5) # 50% of timeout period - await controller.process_frame(UserSpeakingFrame()) + await asyncio.sleep(USER_IDLE_TIMEOUT + 0.1) self.assertFalse(idle_triggered) await controller.cleanup() - async def test_bot_speaking_resets_idle_timer(self): - """Test that BotSpeakingFrame frames reset the idle timer.""" + async def test_bot_speaking_cancels_timer(self): + """Test that BotStartedSpeakingFrame cancels the idle timer.""" controller = UserIdleController(user_idle_timeout=USER_IDLE_TIMEOUT) await controller.setup(self.task_manager) @@ -83,102 +80,61 @@ class TestUserIdleController(unittest.IsolatedAsyncioTestCase): nonlocal idle_triggered idle_triggered = True - # Start conversation + await controller.process_frame(BotStoppedSpeakingFrame()) + await asyncio.sleep(USER_IDLE_TIMEOUT * 0.3) + await controller.process_frame(BotStartedSpeakingFrame()) + + await asyncio.sleep(USER_IDLE_TIMEOUT + 0.1) + + self.assertFalse(idle_triggered) + + await controller.cleanup() + + async def test_no_idle_before_bot_speaks(self): + """Test that idle does not fire if no BotStoppedSpeakingFrame is received.""" + controller = UserIdleController(user_idle_timeout=USER_IDLE_TIMEOUT) + await controller.setup(self.task_manager) + + idle_triggered = False + + @controller.event_handler("on_user_turn_idle") + async def on_user_turn_idle(controller): + nonlocal idle_triggered + idle_triggered = True + + # Wait without any frames + await asyncio.sleep(USER_IDLE_TIMEOUT + 0.1) + + self.assertFalse(idle_triggered) + + await controller.cleanup() + + async def test_interruption_no_false_trigger(self): + """Test that BotStoppedSpeakingFrame during a user turn does not start the timer.""" + controller = UserIdleController(user_idle_timeout=USER_IDLE_TIMEOUT) + await controller.setup(self.task_manager) + + idle_triggered = False + + @controller.event_handler("on_user_turn_idle") + async def on_user_turn_idle(controller): + nonlocal idle_triggered + idle_triggered = True + + # User starts speaking (interruption) await controller.process_frame(UserStartedSpeakingFrame()) + # Bot stops speaking due to interruption + await controller.process_frame(BotStoppedSpeakingFrame()) - # Bot speaking should reset timer - for _ in range(5): - await asyncio.sleep(USER_IDLE_TIMEOUT * 0.6) # 60% of timeout - await controller.process_frame(BotSpeakingFrame()) - - self.assertFalse(idle_triggered) - - await controller.cleanup() - - async def test_function_call_prevents_idle(self): - """Test that function calls in progress prevent idle event.""" - controller = UserIdleController(user_idle_timeout=USER_IDLE_TIMEOUT) - await controller.setup(self.task_manager) - - idle_triggered = False - - @controller.event_handler("on_user_turn_idle") - async def on_user_turn_idle(controller): - nonlocal idle_triggered - idle_triggered = True - - # Start conversation - await controller.process_frame(UserStartedSpeakingFrame()) - - # Start function call - await controller.process_frame(FunctionCallsStartedFrame(function_calls=[])) - - # Wait longer than idle timeout - await asyncio.sleep(USER_IDLE_TIMEOUT + 0.1) - - # Should not trigger idle because function call is in progress - self.assertFalse(idle_triggered) - - # Complete function call - await controller.process_frame( - FunctionCallResultFrame( - function_name="test", - tool_call_id="123", - arguments={}, - result=None, - run_llm=False, - ) - ) - - # Now idle should trigger - await asyncio.sleep(USER_IDLE_TIMEOUT + 0.1) - self.assertTrue(idle_triggered) - - await controller.cleanup() - - async def test_no_idle_before_conversation_starts(self): - """Test that idle monitoring doesn't start before first conversation activity.""" - controller = UserIdleController(user_idle_timeout=USER_IDLE_TIMEOUT) - await controller.setup(self.task_manager) - - idle_triggered = False - - @controller.event_handler("on_user_turn_idle") - async def on_user_turn_idle(controller): - nonlocal idle_triggered - idle_triggered = True - - # Wait without starting conversation + # Wait - timer should NOT have started because user turn is in progress await asyncio.sleep(USER_IDLE_TIMEOUT + 0.1) self.assertFalse(idle_triggered) await controller.cleanup() - async def test_idle_starts_with_bot_speaking(self): - """Test that monitoring starts with BotSpeakingFrame, not just user speech.""" - controller = UserIdleController(user_idle_timeout=USER_IDLE_TIMEOUT) - await controller.setup(self.task_manager) - - idle_triggered = False - - @controller.event_handler("on_user_turn_idle") - async def on_user_turn_idle(controller): - nonlocal idle_triggered - idle_triggered = True - - # Start conversation with bot speaking - await controller.process_frame(BotSpeakingFrame()) - - # Wait for idle timeout - await asyncio.sleep(USER_IDLE_TIMEOUT + 0.1) - - self.assertTrue(idle_triggered) - - await controller.cleanup() - - async def test_multiple_idle_events(self): - """Test that idle event can trigger multiple times.""" + async def test_idle_cycle(self): + """Test that idle fires, then can fire again after another bot speaking cycle.""" controller = UserIdleController(user_idle_timeout=USER_IDLE_TIMEOUT) await controller.setup(self.task_manager) @@ -189,29 +145,105 @@ class TestUserIdleController(unittest.IsolatedAsyncioTestCase): nonlocal idle_count idle_count += 1 - # Start conversation - await controller.process_frame(UserStartedSpeakingFrame()) - - # First idle + # First cycle: bot stops → idle fires + await controller.process_frame(BotStoppedSpeakingFrame()) await asyncio.sleep(USER_IDLE_TIMEOUT + 0.1) - first_count = idle_count - self.assertGreaterEqual(first_count, 1) + self.assertEqual(idle_count, 1) - # Second idle + # Second cycle: bot starts → bot stops → idle fires again + await controller.process_frame(BotStartedSpeakingFrame()) + await controller.process_frame(BotStoppedSpeakingFrame()) await asyncio.sleep(USER_IDLE_TIMEOUT + 0.1) - second_count = idle_count - self.assertGreater(second_count, first_count) + self.assertEqual(idle_count, 2) - # User activity resets timer - await controller.process_frame(UserSpeakingFrame()) + await controller.cleanup() - # Give a moment for the timer to reset - await asyncio.sleep(0.1) + async def test_cleanup_cancels_timer(self): + """Test that cleanup cancels a pending idle timer.""" + controller = UserIdleController(user_idle_timeout=USER_IDLE_TIMEOUT) + await controller.setup(self.task_manager) + + idle_triggered = False + + @controller.event_handler("on_user_turn_idle") + async def on_user_turn_idle(controller): + nonlocal idle_triggered + idle_triggered = True + + await controller.process_frame(BotStoppedSpeakingFrame()) + await asyncio.sleep(USER_IDLE_TIMEOUT * 0.3) + await controller.cleanup() - # Third idle await asyncio.sleep(USER_IDLE_TIMEOUT + 0.1) - third_count = idle_count - self.assertGreater(third_count, second_count) + + self.assertFalse(idle_triggered) + + async def test_function_call_cancels_timer(self): + """Test normal ordering: BotStopped starts timer, FunctionCallsStarted cancels it.""" + controller = UserIdleController(user_idle_timeout=USER_IDLE_TIMEOUT) + await controller.setup(self.task_manager) + + idle_triggered = False + + @controller.event_handler("on_user_turn_idle") + async def on_user_turn_idle(controller): + nonlocal idle_triggered + idle_triggered = True + + # Bot finishes speaking, timer starts + await controller.process_frame(BotStoppedSpeakingFrame()) + # Function call starts shortly after, cancels the timer + await asyncio.sleep(USER_IDLE_TIMEOUT * 0.3) + await controller.process_frame( + FunctionCallsStartedFrame(function_calls=[unittest.mock.Mock()]) + ) + + # Wait longer than timeout — should not fire + await asyncio.sleep(USER_IDLE_TIMEOUT + 0.1) + self.assertFalse(idle_triggered) + + await controller.cleanup() + + async def test_function_call_suppresses_timer(self): + """Test race condition: FunctionCallsStarted arrives before BotStopped. + + A race condition can cause FunctionCallsStarted to arrive before + BotStoppedSpeaking. The counter guard prevents the timer from starting + while a function call is in progress. + """ + controller = UserIdleController(user_idle_timeout=USER_IDLE_TIMEOUT) + await controller.setup(self.task_manager) + + idle_triggered = False + + @controller.event_handler("on_user_turn_idle") + async def on_user_turn_idle(controller): + nonlocal idle_triggered + idle_triggered = True + + # LLM emits function call and "let me check" concurrently + await controller.process_frame( + FunctionCallsStartedFrame(function_calls=[unittest.mock.Mock()]) + ) + await controller.process_frame(BotStartedSpeakingFrame()) + await controller.process_frame(BotStoppedSpeakingFrame()) + + # Wait longer than timeout — should not fire (function call in progress) + await asyncio.sleep(USER_IDLE_TIMEOUT + 0.1) + self.assertFalse(idle_triggered) + + # Function call completes, bot speaks result + await controller.process_frame( + FunctionCallResultFrame( + function_name="test", tool_call_id="123", arguments={}, result="ok" + ) + ) + await controller.process_frame(BotStartedSpeakingFrame()) + await controller.process_frame(BotStoppedSpeakingFrame()) + + # Now the timer should start and fire + await asyncio.sleep(USER_IDLE_TIMEOUT + 0.1) + self.assertTrue(idle_triggered) await controller.cleanup() From cb7023681f0ce157945c7abcfed9e038a71d0041 Mon Sep 17 00:00:00 2001 From: Mark Backman Date: Sat, 14 Feb 2026 08:57:46 -0500 Subject: [PATCH 0492/1060] Add changelog for PR #3744 --- changelog/3744.fixed.md | 1 + 1 file changed, 1 insertion(+) create mode 100644 changelog/3744.fixed.md diff --git a/changelog/3744.fixed.md b/changelog/3744.fixed.md new file mode 100644 index 000000000..d2b3f665f --- /dev/null +++ b/changelog/3744.fixed.md @@ -0,0 +1 @@ +- Fixed `UserIdleController` false idle triggers caused by gaps between user and bot activity frames. The idle timer now starts only after `BotStoppedSpeakingFrame` and is suppressed during active user turns and function calls. From 8f5e5e8e7c4a2d923ce9255708aac5ef6f895147 Mon Sep 17 00:00:00 2001 From: Mark Backman Date: Sat, 14 Feb 2026 09:41:42 -0500 Subject: [PATCH 0493/1060] Update comment in _maybe_mute_frame --- .../processors/aggregators/llm_response_universal.py | 10 ++++------ 1 file changed, 4 insertions(+), 6 deletions(-) diff --git a/src/pipecat/processors/aggregators/llm_response_universal.py b/src/pipecat/processors/aggregators/llm_response_universal.py index 8450842c8..0a6e05d6b 100644 --- a/src/pipecat/processors/aggregators/llm_response_universal.py +++ b/src/pipecat/processors/aggregators/llm_response_universal.py @@ -549,12 +549,10 @@ class LLMUserAggregator(LLMContextAggregator): await s.cleanup() async def _maybe_mute_frame(self, frame: Frame): - # Control frames must flow unconditionally — never feed them to mute - # strategies. Without this guard, strategies like - # MuteUntilFirstBotCompleteUserMuteStrategy fire on_user_mute_started - # and broadcast UserMuteStartedFrame before StartFrame is pushed - # downstream, causing downstream processors to receive frames before - # StartFrame and log errors. + # Lifecycle frames should never be muted and should not trigger mute + # state changes. Evaluating mute strategies on StartFrame would + # broadcast UserMuteStartedFrame before StartFrame reaches downstream + # processors. if isinstance(frame, (StartFrame, EndFrame, CancelFrame)): return False From 507765625fcbc5e144b2f82e22464161925d79dd Mon Sep 17 00:00:00 2001 From: Mark Backman Date: Sat, 14 Feb 2026 09:47:59 -0500 Subject: [PATCH 0494/1060] Make UserIdleController always-on with dynamic timeout updates Always create UserIdleController (timeout=0 means disabled), removing all Optional guards. Add UserIdleTimeoutUpdateFrame to allow changing the idle timeout at runtime. --- changelog/3748.added.md | 1 + changelog/3748.changed.md | 1 + examples/foundational/17-detect-user-idle.py | 7 ++ src/pipecat/frames/frames.py | 14 ++++ .../aggregators/llm_response_universal.py | 37 ++++------ src/pipecat/turns/user_idle_controller.py | 12 +++- src/pipecat/turns/user_turn_processor.py | 34 +++------ tests/test_user_idle_controller.py | 71 +++++++++++++++++++ 8 files changed, 129 insertions(+), 48 deletions(-) create mode 100644 changelog/3748.added.md create mode 100644 changelog/3748.changed.md diff --git a/changelog/3748.added.md b/changelog/3748.added.md new file mode 100644 index 000000000..223f8bf4b --- /dev/null +++ b/changelog/3748.added.md @@ -0,0 +1 @@ +- Added `UserIdleTimeoutUpdateFrame` to enable or disable user idle detection at runtime by updating the timeout dynamically. diff --git a/changelog/3748.changed.md b/changelog/3748.changed.md new file mode 100644 index 000000000..61be61c6b --- /dev/null +++ b/changelog/3748.changed.md @@ -0,0 +1 @@ +- `UserIdleController` is now always created with a default timeout of 0 (disabled). The `user_idle_timeout` parameter changed from `Optional[float] = None` to `float = 0` in `UserTurnProcessor`, `LLMUserAggregatorParams`, and `UserIdleController`. diff --git a/examples/foundational/17-detect-user-idle.py b/examples/foundational/17-detect-user-idle.py index bb0ea8873..e6af5a364 100644 --- a/examples/foundational/17-detect-user-idle.py +++ b/examples/foundational/17-detect-user-idle.py @@ -19,6 +19,7 @@ from pipecat.frames.frames import ( LLMMessagesAppendFrame, LLMRunFrame, TTSSpeakFrame, + UserIdleTimeoutUpdateFrame, ) from pipecat.pipeline.pipeline import Pipeline from pipecat.pipeline.runner import PipelineRunner @@ -210,6 +211,12 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): # Kick off the conversation. messages.append({"role": "system", "content": "Please introduce yourself to the user."}) await task.queue_frames([LLMRunFrame()]) + await asyncio.sleep(30) + logger.info(f"Disabling idle detection") + await task.queue_frames([UserIdleTimeoutUpdateFrame(timeout=0)]) + await asyncio.sleep(30) + logger.info(f"Enabling idle detection") + await task.queue_frames([UserIdleTimeoutUpdateFrame(timeout=5)]) @transport.event_handler("on_client_disconnected") async def on_client_disconnected(transport, client): diff --git a/src/pipecat/frames/frames.py b/src/pipecat/frames/frames.py index 8d237defc..c6c4421cd 100644 --- a/src/pipecat/frames/frames.py +++ b/src/pipecat/frames/frames.py @@ -2145,6 +2145,20 @@ class STTUpdateSettingsFrame(ServiceUpdateSettingsFrame): pass +@dataclass +class UserIdleTimeoutUpdateFrame(SystemFrame): + """Frame for updating the user idle timeout at runtime. + + Setting timeout to 0 disables idle detection. Setting a positive value + enables it. + + Parameters: + timeout: The new idle timeout in seconds. 0 disables idle detection. + """ + + timeout: float + + @dataclass class VADParamsUpdateFrame(ControlFrame): """Frame for updating VAD parameters. diff --git a/src/pipecat/processors/aggregators/llm_response_universal.py b/src/pipecat/processors/aggregators/llm_response_universal.py index 0fb538b1a..f05f064fb 100644 --- a/src/pipecat/processors/aggregators/llm_response_universal.py +++ b/src/pipecat/processors/aggregators/llm_response_universal.py @@ -92,9 +92,9 @@ class LLMUserAggregatorParams: user_mute_strategies: List of user mute strategies. user_turn_stop_timeout: Time in seconds to wait before considering the user's turn finished. - user_idle_timeout: Optional timeout in seconds for detecting user idle state. - If set, the aggregator will emit an `on_user_turn_idle` event when the user - has been idle (not speaking) for this duration. Set to None to disable + user_idle_timeout: Timeout in seconds for detecting user idle state. + The aggregator will emit an `on_user_turn_idle` event when the user + has been idle (not speaking) for this duration. Set to 0 to disable idle detection. vad_analyzer: Voice Activity Detection analyzer instance. filter_incomplete_user_turns: Whether to filter out incomplete user turns. @@ -109,7 +109,7 @@ class LLMUserAggregatorParams: user_turn_strategies: Optional[UserTurnStrategies] = None user_mute_strategies: List[BaseUserMuteStrategy] = field(default_factory=list) user_turn_stop_timeout: float = 5.0 - user_idle_timeout: Optional[float] = None + user_idle_timeout: float = 0 vad_analyzer: Optional[VADAnalyzer] = None filter_incomplete_user_turns: bool = False user_turn_completion_config: Optional[UserTurnCompletionConfig] = None @@ -404,15 +404,10 @@ class LLMUserAggregator(LLMContextAggregator): "on_user_turn_stop_timeout", self._on_user_turn_stop_timeout ) - # Optional user idle controller - self._user_idle_controller: Optional[UserIdleController] = None - if self._params.user_idle_timeout: - self._user_idle_controller = UserIdleController( - user_idle_timeout=self._params.user_idle_timeout - ) - self._user_idle_controller.add_event_handler( - "on_user_turn_idle", self._on_user_turn_idle - ) + self._user_idle_controller = UserIdleController( + user_idle_timeout=self._params.user_idle_timeout + ) + self._user_idle_controller.add_event_handler("on_user_turn_idle", self._on_user_turn_idle) # VAD controller self._vad_controller: Optional[VADController] = None @@ -489,8 +484,7 @@ class LLMUserAggregator(LLMContextAggregator): await self._user_turn_controller.process_frame(frame) - if self._user_idle_controller: - await self._user_idle_controller.process_frame(frame) + await self._user_idle_controller.process_frame(frame) async def push_aggregation(self) -> str: """Push the current aggregation.""" @@ -507,8 +501,7 @@ class LLMUserAggregator(LLMContextAggregator): async def _start(self, frame: StartFrame): await self._user_turn_controller.setup(self.task_manager) - if self._user_idle_controller: - await self._user_idle_controller.setup(self.task_manager) + await self._user_idle_controller.setup(self.task_manager) for s in self._params.user_mute_strategies: await s.setup(self.task_manager) @@ -541,9 +534,7 @@ class LLMUserAggregator(LLMContextAggregator): async def _cleanup(self): await self._user_turn_controller.cleanup() - - if self._user_idle_controller: - await self._user_idle_controller.cleanup() + await self._user_idle_controller.cleanup() for s in self._params.user_mute_strategies: await s.cleanup() @@ -689,8 +680,7 @@ class LLMUserAggregator(LLMContextAggregator): if params.enable_user_speaking_frames: await self.broadcast_frame(UserStartedSpeakingFrame) - if self._user_idle_controller: - await self._user_idle_controller.process_frame(UserStartedSpeakingFrame()) + await self._user_idle_controller.process_frame(UserStartedSpeakingFrame()) if params.enable_interruptions and self._allow_interruptions: await self.push_interruption_task_frame_and_wait() @@ -708,8 +698,7 @@ class LLMUserAggregator(LLMContextAggregator): if params.enable_user_speaking_frames: await self.broadcast_frame(UserStoppedSpeakingFrame) - if self._user_idle_controller: - await self._user_idle_controller.process_frame(UserStoppedSpeakingFrame()) + await self._user_idle_controller.process_frame(UserStoppedSpeakingFrame()) await self._maybe_emit_user_turn_stopped(strategy) diff --git a/src/pipecat/turns/user_idle_controller.py b/src/pipecat/turns/user_idle_controller.py index b4dc80772..b3b7e8074 100644 --- a/src/pipecat/turns/user_idle_controller.py +++ b/src/pipecat/turns/user_idle_controller.py @@ -16,6 +16,7 @@ from pipecat.frames.frames import ( FunctionCallCancelFrame, FunctionCallResultFrame, FunctionCallsStartedFrame, + UserIdleTimeoutUpdateFrame, UserStartedSpeakingFrame, UserStoppedSpeakingFrame, ) @@ -51,12 +52,13 @@ class UserIdleController(BaseObject): def __init__( self, *, - user_idle_timeout: float, + user_idle_timeout: float = 0, ): """Initialize the user idle controller. Args: user_idle_timeout: Timeout in seconds before considering the user idle. + 0 disables idle detection. """ super().__init__() @@ -96,6 +98,12 @@ class UserIdleController(BaseObject): Args: frame: The frame to be processed. """ + if isinstance(frame, UserIdleTimeoutUpdateFrame): + self._user_idle_timeout = frame.timeout + if self._user_idle_timeout <= 0: + await self._cancel_idle_timer() + return + if isinstance(frame, BotStoppedSpeakingFrame): # Only start the timer if the user isn't mid-turn and no function # calls are pending. @@ -128,6 +136,8 @@ class UserIdleController(BaseObject): async def _start_idle_timer(self): """Start (or restart) the idle timer.""" + if self._user_idle_timeout <= 0: + return await self._cancel_idle_timer() self._idle_timer_task = self.task_manager.create_task( self._idle_timer_expired(), diff --git a/src/pipecat/turns/user_turn_processor.py b/src/pipecat/turns/user_turn_processor.py index 720a8b854..7f8995202 100644 --- a/src/pipecat/turns/user_turn_processor.py +++ b/src/pipecat/turns/user_turn_processor.py @@ -66,7 +66,7 @@ class UserTurnProcessor(FrameProcessor): *, user_turn_strategies: Optional[UserTurnStrategies] = None, user_turn_stop_timeout: float = 5.0, - user_idle_timeout: Optional[float] = None, + user_idle_timeout: float = 0, **kwargs, ): """Initialize the user turn processor. @@ -75,9 +75,9 @@ class UserTurnProcessor(FrameProcessor): user_turn_strategies: Configured strategies for starting and stopping user turns. user_turn_stop_timeout: Timeout in seconds to automatically stop a user turn if no activity is detected. - user_idle_timeout: Optional timeout in seconds for detecting user idle state. - If set, the processor will emit an `on_user_turn_idle` event when the user - has been idle (not speaking) for this duration. Set to None to disable + user_idle_timeout: Timeout in seconds for detecting user idle state. + The processor will emit an `on_user_turn_idle` event when the user + has been idle (not speaking) for this duration. Set to 0 to disable idle detection. **kwargs: Additional keyword arguments. """ @@ -104,13 +104,8 @@ class UserTurnProcessor(FrameProcessor): "on_user_turn_stop_timeout", self._on_user_turn_stop_timeout ) - # Optional user idle controller - self._user_idle_controller: Optional[UserIdleController] = None - if user_idle_timeout: - self._user_idle_controller = UserIdleController(user_idle_timeout=user_idle_timeout) - self._user_idle_controller.add_event_handler( - "on_user_turn_idle", self._on_user_turn_idle - ) + self._user_idle_controller = UserIdleController(user_idle_timeout=user_idle_timeout) + self._user_idle_controller.add_event_handler("on_user_turn_idle", self._on_user_turn_idle) async def cleanup(self): """Clean up processor resources.""" @@ -149,14 +144,11 @@ class UserTurnProcessor(FrameProcessor): await self._user_turn_controller.process_frame(frame) - if self._user_idle_controller: - await self._user_idle_controller.process_frame(frame) + await self._user_idle_controller.process_frame(frame) async def _start(self, frame: StartFrame): await self._user_turn_controller.setup(self.task_manager) - - if self._user_idle_controller: - await self._user_idle_controller.setup(self.task_manager) + await self._user_idle_controller.setup(self.task_manager) async def _stop(self, frame: EndFrame): await self._cleanup() @@ -166,9 +158,7 @@ class UserTurnProcessor(FrameProcessor): async def _cleanup(self): await self._user_turn_controller.cleanup() - - if self._user_idle_controller: - await self._user_idle_controller.cleanup() + await self._user_idle_controller.cleanup() async def _on_push_frame( self, controller, frame: Frame, direction: FrameDirection = FrameDirection.DOWNSTREAM @@ -189,8 +179,7 @@ class UserTurnProcessor(FrameProcessor): if params.enable_user_speaking_frames: await self.broadcast_frame(UserStartedSpeakingFrame) - if self._user_idle_controller: - await self._user_idle_controller.process_frame(UserStartedSpeakingFrame()) + await self._user_idle_controller.process_frame(UserStartedSpeakingFrame()) if params.enable_interruptions and self._allow_interruptions: await self.push_interruption_task_frame_and_wait() @@ -208,8 +197,7 @@ class UserTurnProcessor(FrameProcessor): if params.enable_user_speaking_frames: await self.broadcast_frame(UserStoppedSpeakingFrame) - if self._user_idle_controller: - await self._user_idle_controller.process_frame(UserStoppedSpeakingFrame()) + await self._user_idle_controller.process_frame(UserStoppedSpeakingFrame()) await self._call_event_handler("on_user_turn_stopped", strategy) diff --git a/tests/test_user_idle_controller.py b/tests/test_user_idle_controller.py index 6975d6e74..646223d37 100644 --- a/tests/test_user_idle_controller.py +++ b/tests/test_user_idle_controller.py @@ -13,6 +13,7 @@ from pipecat.frames.frames import ( BotStoppedSpeakingFrame, FunctionCallResultFrame, FunctionCallsStartedFrame, + UserIdleTimeoutUpdateFrame, UserStartedSpeakingFrame, ) from pipecat.turns.user_idle_controller import UserIdleController @@ -247,6 +248,76 @@ class TestUserIdleController(unittest.IsolatedAsyncioTestCase): await controller.cleanup() + async def test_disabled_by_default(self): + """Test that timeout=0 means idle detection is disabled.""" + controller = UserIdleController() + await controller.setup(self.task_manager) + + idle_triggered = False + + @controller.event_handler("on_user_turn_idle") + async def on_user_turn_idle(controller): + nonlocal idle_triggered + idle_triggered = True + + await controller.process_frame(BotStoppedSpeakingFrame()) + await asyncio.sleep(USER_IDLE_TIMEOUT + 0.1) + + self.assertFalse(idle_triggered) + + await controller.cleanup() + + async def test_enable_via_frame(self): + """Test enabling idle detection at runtime via UserIdleTimeoutUpdateFrame.""" + controller = UserIdleController() + await controller.setup(self.task_manager) + + idle_triggered = False + + @controller.event_handler("on_user_turn_idle") + async def on_user_turn_idle(controller): + nonlocal idle_triggered + idle_triggered = True + + # Initially disabled — no idle fires + await controller.process_frame(BotStoppedSpeakingFrame()) + await asyncio.sleep(USER_IDLE_TIMEOUT + 0.1) + self.assertFalse(idle_triggered) + + # Enable idle detection + await controller.process_frame(UserIdleTimeoutUpdateFrame(timeout=USER_IDLE_TIMEOUT)) + await controller.process_frame(BotStoppedSpeakingFrame()) + await asyncio.sleep(USER_IDLE_TIMEOUT + 0.1) + + self.assertTrue(idle_triggered) + + await controller.cleanup() + + async def test_disable_via_frame(self): + """Test disabling idle detection at runtime via UserIdleTimeoutUpdateFrame.""" + controller = UserIdleController(user_idle_timeout=USER_IDLE_TIMEOUT) + await controller.setup(self.task_manager) + + idle_triggered = False + + @controller.event_handler("on_user_turn_idle") + async def on_user_turn_idle(controller): + nonlocal idle_triggered + idle_triggered = True + + # Start the timer + await controller.process_frame(BotStoppedSpeakingFrame()) + await asyncio.sleep(USER_IDLE_TIMEOUT * 0.3) + + # Disable — should cancel running timer + await controller.process_frame(UserIdleTimeoutUpdateFrame(timeout=0)) + + await asyncio.sleep(USER_IDLE_TIMEOUT + 0.1) + + self.assertFalse(idle_triggered) + + await controller.cleanup() + if __name__ == "__main__": unittest.main() From 36de6003d05de621e5a70d48eab4bbe911bd0093 Mon Sep 17 00:00:00 2001 From: Mark Backman Date: Mon, 16 Feb 2026 11:34:16 -0700 Subject: [PATCH 0495/1060] Switch Gradium TTS to AudioContextWordTTSService for multiplexing Use client_req_id-based multiplexing instead of disconnecting and reconnecting the websocket on every interruption. This follows the same pattern used by Cartesia, ElevenLabs, and other services via AudioContextWordTTSService. Key changes: - Base class: InterruptibleWordTTSService -> AudioContextWordTTSService - Add close_ws_on_eos: False to setup message to keep connection alive - Add client_req_id to text, end_of_stream messages for demultiplexing - Route audio via append_to_audio_context() instead of push_frame() - Silently drop messages for cancelled/unknown contexts on interruption - Add _handle_interruption() that resets context without reconnecting - Remove no-op push_frame() override --- src/pipecat/services/gradium/tts.py | 79 ++++++++++++++++++----------- 1 file changed, 48 insertions(+), 31 deletions(-) diff --git a/src/pipecat/services/gradium/tts.py b/src/pipecat/services/gradium/tts.py index 0e9865cf0..bde77f846 100644 --- a/src/pipecat/services/gradium/tts.py +++ b/src/pipecat/services/gradium/tts.py @@ -16,13 +16,14 @@ from pipecat.frames.frames import ( EndFrame, ErrorFrame, Frame, + InterruptionFrame, StartFrame, TTSAudioRawFrame, TTSStartedFrame, TTSStoppedFrame, ) from pipecat.processors.frame_processor import FrameDirection -from pipecat.services.tts_service import InterruptibleWordTTSService +from pipecat.services.tts_service import AudioContextWordTTSService from pipecat.utils.tracing.service_decorators import traced_tts try: @@ -37,7 +38,7 @@ except ModuleNotFoundError as e: SAMPLE_RATE = 48000 -class GradiumTTSService(InterruptibleWordTTSService): +class GradiumTTSService(AudioContextWordTTSService): """Text-to-Speech service using Gradium's websocket API.""" class InputParams(BaseModel): @@ -71,7 +72,6 @@ class GradiumTTSService(InterruptibleWordTTSService): params: Additional configuration parameters. **kwargs: Additional arguments passed to parent class. """ - # Initialize with parent class settings for proper frame handling super().__init__( push_stop_frames=True, pause_frame_processing=True, @@ -95,7 +95,7 @@ class GradiumTTSService(InterruptibleWordTTSService): # State tracking self._receive_task = None - self._current_context_id: Optional[str] = None + self._context_id: Optional[str] = None def can_generate_metrics(self) -> bool: """Check if this service can generate processing metrics. @@ -126,7 +126,10 @@ class GradiumTTSService(InterruptibleWordTTSService): def _build_msg(self, text: str = "") -> dict: """Build JSON message for Gradium API.""" - return {"text": text, "type": "text"} + msg = {"text": text, "type": "text"} + if self._context_id: + msg["client_req_id"] = self._context_id + return msg async def start(self, frame: StartFrame): """Start the service and establish websocket connection. @@ -197,6 +200,7 @@ class GradiumTTSService(InterruptibleWordTTSService): "type": "setup", "output_format": "pcm", "voice_id": self._voice_id, + "close_ws_on_eos": False, } if self._json_config is not None: setup_msg["json_config"] = self._json_config @@ -234,18 +238,35 @@ class GradiumTTSService(InterruptibleWordTTSService): async def flush_audio(self): """Flush any pending audio synthesis.""" - if not self._websocket: + if not self._context_id or not self._websocket: return try: - msg = {"type": "end_of_stream"} + msg = {"type": "end_of_stream", "client_req_id": self._context_id} await self._websocket.send(json.dumps(msg)) + self._context_id = None except ConnectionClosedOK: logger.debug(f"{self}: connection closed normally during flush") except Exception as e: logger.error(f"{self} exception: {e}") + async def _handle_interruption(self, frame: InterruptionFrame, direction: FrameDirection): + """Handle interruption by resetting context state. + + The parent AudioContextTTSService._handle_interruption() cancels the audio context + task and creates a new one. We reset _context_id so the next run_tts() creates a + fresh context. No websocket reconnection needed — audio from the old client_req_id + will be silently dropped since the audio context no longer exists. + + Args: + frame: The interruption frame. + direction: The direction of the frame. + """ + await super()._handle_interruption(frame, direction) + await self.stop_all_metrics() + self._context_id = None + async def _receive_messages(self): - """Process incoming websocket messages.""" + """Process incoming websocket messages, demultiplexing by client_req_id.""" # TODO(laurent): This should not be necessary as it should happen when # receiving the messages but this does not seem to always be the case # and that may lead to a busy polling loop. @@ -253,41 +274,35 @@ class GradiumTTSService(InterruptibleWordTTSService): raise ConnectionClosedOK(None, None) async for message in self._get_websocket(): msg = json.loads(message) + ctx_id = msg.get("client_req_id") if msg["type"] == "audio": - # Process audio chunk + if not ctx_id or not self.audio_context_available(ctx_id): + continue await self.stop_ttfb_metrics() await self.start_word_timestamps() frame = TTSAudioRawFrame( audio=base64.b64decode(msg["audio"]), sample_rate=self.sample_rate, num_channels=1, - context_id=self._current_context_id, + context_id=ctx_id, ) - await self.push_frame(frame) + await self.append_to_audio_context(ctx_id, frame) elif msg["type"] == "text": - if self._current_context_id: - await self.add_word_timestamps( - [(msg["text"], msg["start_s"])], self._current_context_id - ) + if ctx_id and self.audio_context_available(ctx_id): + await self.add_word_timestamps([(msg["text"], msg["start_s"])], ctx_id) + elif msg["type"] == "end_of_stream": - await self.push_frame(TTSStoppedFrame()) + if ctx_id and self.audio_context_available(ctx_id): + await self.add_word_timestamps([("TTSStoppedFrame", 0), ("Reset", 0)], ctx_id) + await self.remove_audio_context(ctx_id) await self.stop_all_metrics() elif msg["type"] == "error": - await self.push_frame(TTSStoppedFrame()) + await self.push_frame(TTSStoppedFrame(context_id=ctx_id)) await self.stop_all_metrics() - await self.push_error(error_msg=f"Error: {msg['message']}") - - async def push_frame(self, frame: Frame, direction: FrameDirection = FrameDirection.DOWNSTREAM): - """Push frame and handle end-of-turn conditions. - - Args: - frame: The frame to push. - direction: The direction to push the frame. - """ - await super().push_frame(frame, direction) + await self.push_error(error_msg=f"Error: {msg.get('message', msg)}") @traced_tts async def run_tts(self, text: str, context_id: str) -> AsyncGenerator[Frame, None]: @@ -300,16 +315,18 @@ class GradiumTTSService(InterruptibleWordTTSService): Yields: Frame: Audio frames containing the synthesized speech. """ - _state = self._websocket.state if self._websocket is not None else None - logger.debug(f"{self}: Generating TTS [{text}] {_state}") + logger.debug(f"{self}: Generating TTS [{text}]") try: if not self._websocket or self._websocket.state is State.CLOSED: self._websocket = None await self._connect() try: - self._current_context_id = context_id - yield TTSStartedFrame(context_id=context_id) + if not self._context_id: + await self.start_ttfb_metrics() + yield TTSStartedFrame(context_id=context_id) + self._context_id = context_id + await self.create_audio_context(self._context_id) msg = self._build_msg(text=text) await self._get_websocket().send(json.dumps(msg)) From f181e12d8f458517e237db5c2ad8cfc0fa5cf084 Mon Sep 17 00:00:00 2001 From: Mark Backman Date: Mon, 16 Feb 2026 11:35:45 -0700 Subject: [PATCH 0496/1060] Add changelog for PR #3759 --- changelog/3759.performance.md | 1 + 1 file changed, 1 insertion(+) create mode 100644 changelog/3759.performance.md diff --git a/changelog/3759.performance.md b/changelog/3759.performance.md new file mode 100644 index 000000000..1bdc17a17 --- /dev/null +++ b/changelog/3759.performance.md @@ -0,0 +1 @@ +- Switched `GradiumTTSService` from `InterruptibleWordTTSService` to `AudioContextWordTTSService`, eliminating websocket disconnect/reconnect on every interruption by using `client_req_id`-based multiplexing. From b345f48ac119412c213472879dc704bbe6123344 Mon Sep 17 00:00:00 2001 From: Sam Sykes Date: Tue, 17 Feb 2026 09:55:43 +0000 Subject: [PATCH 0497/1060] fix: update dependency specifier for speechmatics-voice Change the version specifier from >=0.2.8 to ~=0.2.8 for the speechmatics-voice package to ensure compatibility with future patch versions. --- pyproject.toml | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/pyproject.toml b/pyproject.toml index 71baec1f1..28c1a7e8c 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -114,7 +114,7 @@ silero = [ "onnxruntime~=1.23.2" ] simli = [ "simli-ai~=1.0.3"] soniox = [ "pipecat-ai[websockets-base]" ] soundfile = [ "soundfile~=0.13.1" ] -speechmatics = [ "speechmatics-voice[smart]>=0.2.8" ] +speechmatics = [ "speechmatics-voice[smart]~=0.2.8" ] strands = [ "strands-agents>=1.9.1,<2" ] tavus=[] together = [] From 65fb88e61efcb09f08634eb0e72e892efc40b94d Mon Sep 17 00:00:00 2001 From: Sam Sykes Date: Tue, 17 Feb 2026 09:58:17 +0000 Subject: [PATCH 0498/1060] chore: update version specifier for speechmatics-voice Change the version specifier from `>=0.2.8` to `~=0.2.8` for the `speechmatics-voice` package. This ensures compatibility with future patch versions while preventing potential breaking changes from minor updates. --- changelog/3761.changed.md | 1 + 1 file changed, 1 insertion(+) create mode 100644 changelog/3761.changed.md diff --git a/changelog/3761.changed.md b/changelog/3761.changed.md new file mode 100644 index 000000000..71618502c --- /dev/null +++ b/changelog/3761.changed.md @@ -0,0 +1 @@ +- Change the version specifier from `>=0.2.8` to `~=0.2.8` for the `speechmatics-voice` package to ensure compatibility with future patch versions. From 3a77b4c1d8af4090fe35328f45fea1c432302869 Mon Sep 17 00:00:00 2001 From: Paul Kompfner Date: Tue, 17 Feb 2026 09:35:58 -0500 Subject: [PATCH 0499/1060] =?UTF-8?q?In=20services=20that=20don't=20handle?= =?UTF-8?q?=20runtime=20settings=20updates=E2=80=94or=20don't=20handle=20t?= =?UTF-8?q?hem=20for=20*all*=20available=20settings=E2=80=94log=20a=20warn?= =?UTF-8?q?ing=20about=20which=20fields=20specifically=20aren't=20handled.?= =?UTF-8?q?=20Revert=20new=20apply-settings-updates=20logic=20across=20var?= =?UTF-8?q?ious=20services,=20to=20reduce=20PR=20testing=20scope.=20This?= =?UTF-8?q?=20logic=20can=20be=20added=20service=20by=20service=20graduall?= =?UTF-8?q?y=20as=20future=20work.?= MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit Note that for services that previously handled applying updates (through methods like `set_model` and `set_language`), we're keeping the update-applying logic (some or most of which is already well-tested) and expanding it to cover all relevant settings fields. Services under this bucket are: - Deepgram STT - Deepgram Sagemaker STT - Elevenlabs STT - Google STT - Gradium STT - OpenAI STT - Speechmatics STT --- src/pipecat/services/ai_service.py | 14 +++++++++++ src/pipecat/services/assemblyai/stt.py | 24 ++++++++++--------- src/pipecat/services/aws/nova_sonic/llm.py | 24 +++++++++++++++++++ src/pipecat/services/aws/stt.py | 18 +++++++++----- src/pipecat/services/azure/stt.py | 21 +++++++++------- src/pipecat/services/cartesia/stt.py | 14 +++++++---- src/pipecat/services/cartesia/tts.py | 19 +++++++++++++++ src/pipecat/services/deepgram/flux/stt.py | 20 ++++++++++++++++ src/pipecat/services/elevenlabs/tts.py | 6 +++++ src/pipecat/services/gladia/stt.py | 16 +++++++------ .../services/google/gemini_live/llm.py | 19 +++++++++++++++ src/pipecat/services/gradium/tts.py | 2 ++ src/pipecat/services/inworld/tts.py | 19 +++++++++++++++ src/pipecat/services/playht/tts.py | 19 +++++++++++++++ src/pipecat/services/rime/tts.py | 2 ++ src/pipecat/services/sarvam/stt.py | 13 ++++++---- src/pipecat/services/sarvam/tts.py | 1 + src/pipecat/services/soniox/stt.py | 10 +++++--- src/pipecat/services/ultravox/llm.py | 1 + 19 files changed, 218 insertions(+), 44 deletions(-) diff --git a/src/pipecat/services/ai_service.py b/src/pipecat/services/ai_service.py index 2c6c10be4..64af3b4b2 100644 --- a/src/pipecat/services/ai_service.py +++ b/src/pipecat/services/ai_service.py @@ -123,6 +123,20 @@ class AIService(FrameProcessor): return changed + def _warn_unhandled_updated_settings(self, unhandled: Set[str]): + """Log a warning for settings changes that won't take effect at runtime. + + Convenience helper for ``_update_settings`` overrides. Call with the + set of field names that changed but that the service does not (yet) + apply at runtime. + + Args: + unhandled: Field names that changed but are not applied. + """ + if unhandled: + fields = ", ".join(sorted(unhandled)) + logger.warning(f"{self.name}: runtime update of [{fields}] is not currently supported") + async def process_frame(self, frame: Frame, direction: FrameDirection): """Process frames and handle service lifecycle. diff --git a/src/pipecat/services/assemblyai/stt.py b/src/pipecat/services/assemblyai/stt.py index 2e7b1230b..a291e6903 100644 --- a/src/pipecat/services/assemblyai/stt.py +++ b/src/pipecat/services/assemblyai/stt.py @@ -185,10 +185,9 @@ class AssemblyAISTTService(WebsocketSTTService): return True async def _update_settings(self, update: STTSettings) -> set[str]: - """Apply a settings update and reconnect if anything changed. + """Apply a settings update. - Any change triggers a WebSocket reconnect since all connection - parameters are encoded in the WebSocket URL. + Settings are stored but not applied to the active connection. Args: update: A :class:`STTSettings` (or ``AssemblyAISTTSettings``) delta. @@ -201,15 +200,18 @@ class AssemblyAISTTService(WebsocketSTTService): if not changed: return changed - # Re-apply manual turn mode config if vad_force_turn_endpoint is active - # and connection_params were updated. - if self._vad_force_turn_endpoint and "connection_params" in changed: - self._settings.connection_params = self._configure_manual_turn_mode( - self._settings.connection_params - ) + # TODO: someday we could reconnect here to apply updated settings. + # Code might look something like the below: + # # Re-apply manual turn mode config if vad_force_turn_endpoint is active + # # and connection_params were updated. + # if self._vad_force_turn_endpoint and "connection_params" in changed: + # self._settings.connection_params = self._configure_manual_turn_mode( + # self._settings.connection_params + # ) + # await self._disconnect() + # await self._connect() - await self._disconnect() - await self._connect() + self._warn_unhandled_updated_settings(changed) return changed diff --git a/src/pipecat/services/aws/nova_sonic/llm.py b/src/pipecat/services/aws/nova_sonic/llm.py index 05baba2bd..92bd0ea1f 100644 --- a/src/pipecat/services/aws/nova_sonic/llm.py +++ b/src/pipecat/services/aws/nova_sonic/llm.py @@ -60,6 +60,7 @@ from pipecat.processors.aggregators.openai_llm_context import ( ) from pipecat.processors.frame_processor import FrameDirection from pipecat.services.llm_service import LLMService +from pipecat.services.settings import LLMSettings from pipecat.utils.time import time_now_iso8601 try: @@ -302,6 +303,29 @@ class AWSNovaSonicLLMService(LLMService): with wave.open(file_path.open("rb"), "rb") as wav_file: self._assistant_response_trigger_audio = wav_file.readframes(wav_file.getnframes()) + # + # settings + # + + async def _update_settings(self, update: LLMSettings) -> set[str]: + """Apply a settings update. + + Settings are stored but not applied to the active connection. + """ + changed = await super()._update_settings(update) + + if not changed: + return changed + + # TODO: someday we could reconnect here to apply updated settings. + # Code might look something like the below: + # await self._disconnect() + # await self._connect() + + self._warn_unhandled_updated_settings(changed) + + return changed + # # standard AIService frame handling # diff --git a/src/pipecat/services/aws/stt.py b/src/pipecat/services/aws/stt.py index 6a91c2973..dda58e2ba 100644 --- a/src/pipecat/services/aws/stt.py +++ b/src/pipecat/services/aws/stt.py @@ -141,16 +141,22 @@ class AWSTranscribeSTTService(WebsocketSTTService): return encoding_map.get(encoding, encoding) async def _update_settings(self, update: STTSettings) -> set[str]: - """Apply a settings update, reconnecting if needed. + """Apply a settings update. - Any change to connection-relevant settings (model, language, etc.) - triggers a WebSocket reconnect so the new configuration takes effect. + Settings are stored but not applied to the active connection. """ changed = await super()._update_settings(update) - if changed and self._websocket: - await self._disconnect() - await self._connect() + if not changed: + return changed + + # TODO: someday we could reconnect here to apply updated settings. + # Code might look something like the below: + # if changed and self._websocket: + # await self._disconnect() + # await self._connect() + + self._warn_unhandled_updated_settings(changed) return changed diff --git a/src/pipecat/services/azure/stt.py b/src/pipecat/services/azure/stt.py index 319296a47..a9ecd67e7 100644 --- a/src/pipecat/services/azure/stt.py +++ b/src/pipecat/services/azure/stt.py @@ -124,25 +124,28 @@ class AzureSTTService(STTService): return True async def _update_settings(self, update: STTSettings) -> set[str]: - """Apply a settings update, reconfiguring the recognizer if needed. + """Apply a settings update. - When ``language`` changes the ``SpeechConfig`` is updated and the - speech recognizer is restarted so that the new language takes effect. + Settings are stored but not applied to the active recognizer. """ changed = await super()._update_settings(update) if "language" in changed: - # Convert Language enum to Azure language code if needed. + # Convert Language enum to Azure language code for consistency. lang = self._settings.language if isinstance(lang, Language): lang = language_to_azure_language(lang) self._settings.language = lang - self._speech_config.speech_recognition_language = lang - # Restart the recognizer with the new config. - if self._speech_recognizer: - self._speech_recognizer.stop_continuous_recognition_async() - self._speech_recognizer.start_continuous_recognition_async() + # TODO: someday we could reconnect here to apply updated settings. + # Code might look something like the below: + # if "language" in changed: + # self._speech_config.speech_recognition_language = self._settings.language + # if self._speech_recognizer: + # self._speech_recognizer.stop_continuous_recognition_async() + # self._speech_recognizer.start_continuous_recognition_async() + + self._warn_unhandled_updated_settings(changed) return changed diff --git a/src/pipecat/services/cartesia/stt.py b/src/pipecat/services/cartesia/stt.py index 5116965ec..a069dface 100644 --- a/src/pipecat/services/cartesia/stt.py +++ b/src/pipecat/services/cartesia/stt.py @@ -295,7 +295,7 @@ class CartesiaSTTService(WebsocketSTTService): await self._disconnect_websocket() async def _update_settings(self, update: STTSettings) -> set[str]: - """Apply a settings update and reconnect if anything changed. + """Apply a settings update. Args: update: A :class:`STTSettings` (or ``CartesiaSTTSettings``) delta. @@ -304,9 +304,15 @@ class CartesiaSTTService(WebsocketSTTService): Set of field names whose values actually changed. """ changed = await super()._update_settings(update) - if changed: - await self._disconnect() - await self._connect() + + # TODO: someday we could reconnect here to apply updated settings. + # Code might look something like the below: + # if changed: + # await self._disconnect() + # await self._connect() + + self._warn_unhandled_updated_settings(changed) + return changed async def _connect_websocket(self): diff --git a/src/pipecat/services/cartesia/tts.py b/src/pipecat/services/cartesia/tts.py index cff365443..00620fdb0 100644 --- a/src/pipecat/services/cartesia/tts.py +++ b/src/pipecat/services/cartesia/tts.py @@ -344,6 +344,25 @@ class CartesiaTTSService(AudioContextWordTTSService): """ return True + async def _update_settings(self, update: TTSSettings) -> set[str]: + """Apply a settings update. + + Settings are stored but not applied to the active connection. + """ + changed = await super()._update_settings(update) + + if not changed: + return changed + + # TODO: someday we could reconnect here to apply updated settings. + # Code might look something like the below: + # await self._disconnect() + # await self._connect() + + self._warn_unhandled_updated_settings(changed) + + return changed + def language_to_service_language(self, language: Language) -> Optional[str]: """Convert a Language enum to Cartesia language format. diff --git a/src/pipecat/services/deepgram/flux/stt.py b/src/pipecat/services/deepgram/flux/stt.py index 547eca0de..14e77c2d3 100644 --- a/src/pipecat/services/deepgram/flux/stt.py +++ b/src/pipecat/services/deepgram/flux/stt.py @@ -27,6 +27,7 @@ from pipecat.frames.frames import ( UserStartedSpeakingFrame, UserStoppedSpeakingFrame, ) +from pipecat.services.settings import STTSettings from pipecat.services.stt_service import WebsocketSTTService from pipecat.transcriptions.language import Language from pipecat.utils.time import time_now_iso8601 @@ -329,6 +330,25 @@ class DeepgramFluxSTTService(WebsocketSTTService): """ return True + async def _update_settings(self, update: STTSettings) -> set[str]: + """Apply a settings update. + + Settings are stored but not applied to the active connection. + """ + changed = await super()._update_settings(update) + + if not changed: + return changed + + # TODO: someday we could reconnect here to apply updated settings. + # Code might look something like the below: + # await self._disconnect() + # await self._connect() + + self._warn_unhandled_updated_settings(changed) + + return changed + async def start(self, frame: StartFrame): """Start the Deepgram Flux STT service. diff --git a/src/pipecat/services/elevenlabs/tts.py b/src/pipecat/services/elevenlabs/tts.py index 9643fa6ba..79f05bbf8 100644 --- a/src/pipecat/services/elevenlabs/tts.py +++ b/src/pipecat/services/elevenlabs/tts.py @@ -516,6 +516,12 @@ class ElevenLabsTTSService(AudioContextWordTTSService): await self.push_error(error_msg=f"Unknown error occurred: {e}", exception=e) self._context_id = None + if not url_changed: + # Reconnect applies all settings; only warn about fields not handled + # by voice settings or URL changes. + handled = ElevenLabsTTSSettings.URL_FIELDS | ElevenLabsTTSSettings.VOICE_SETTINGS_FIELDS + self._warn_unhandled_updated_settings(changed - handled) + return changed async def start(self, frame: StartFrame): diff --git a/src/pipecat/services/gladia/stt.py b/src/pipecat/services/gladia/stt.py index bb8f05e61..500b88052 100644 --- a/src/pipecat/services/gladia/stt.py +++ b/src/pipecat/services/gladia/stt.py @@ -382,8 +382,7 @@ class GladiaSTTService(WebsocketSTTService): async def _update_settings(self, update: GladiaSTTSettings) -> set[str]: """Apply settings update. - Gladia sessions are fixed at creation time, so any change requires - a full session teardown and reconnect. + Settings are stored but not applied to the active session. Args: update: A settings delta. @@ -396,11 +395,14 @@ class GladiaSTTService(WebsocketSTTService): if not changed: return changed - # Gladia sessions are fixed — need to tear down and recreate - self._session_url = None - self._session_id = None - await self._disconnect() - await self._connect() + # TODO: someday we could reconnect here to apply updated settings. + # Code might look something like the below: + # self._session_url = None + # self._session_id = None + # await self._disconnect() + # await self._connect() + + self._warn_unhandled_updated_settings(changed) return changed diff --git a/src/pipecat/services/google/gemini_live/llm.py b/src/pipecat/services/google/gemini_live/llm.py index 7a7aed08c..ecca52396 100644 --- a/src/pipecat/services/google/gemini_live/llm.py +++ b/src/pipecat/services/google/gemini_live/llm.py @@ -804,6 +804,25 @@ class GeminiLiveLLMService(LLMService): """ return True + async def _update_settings(self, update: LLMSettings) -> set[str]: + """Apply a settings update. + + Settings are stored but not applied to the active connection. + """ + changed = await super()._update_settings(update) + + if not changed: + return changed + + # TODO: someday we could reconnect here to apply updated settings. + # Code might look something like the below: + # await self._disconnect() + # await self._connect() + + self._warn_unhandled_updated_settings(changed) + + return changed + def set_audio_input_paused(self, paused: bool): """Set the audio input pause state. diff --git a/src/pipecat/services/gradium/tts.py b/src/pipecat/services/gradium/tts.py index bc4945bcf..947404baa 100644 --- a/src/pipecat/services/gradium/tts.py +++ b/src/pipecat/services/gradium/tts.py @@ -133,6 +133,8 @@ class GradiumTTSService(InterruptibleWordTTSService): if self._voice_id != prev_voice: await self._disconnect() await self._connect() + else: + self._warn_unhandled_updated_settings(changed) return changed def _build_msg(self, text: str = "") -> dict: diff --git a/src/pipecat/services/inworld/tts.py b/src/pipecat/services/inworld/tts.py index 2f6a13bd1..80d95aef9 100644 --- a/src/pipecat/services/inworld/tts.py +++ b/src/pipecat/services/inworld/tts.py @@ -165,6 +165,25 @@ class InworldHttpTTSService(WordTTSService): """ return True + async def _update_settings(self, update: TTSSettings) -> set[str]: + """Apply a settings update. + + Settings are stored but not applied to the active connection. + """ + changed = await super()._update_settings(update) + + if not changed: + return changed + + # TODO: someday we could reconnect here to apply updated settings. + # Code might look something like the below: + # await self._disconnect() + # await self._connect() + + self._warn_unhandled_updated_settings(changed) + + return changed + async def start(self, frame: StartFrame): """Start the Inworld TTS service. diff --git a/src/pipecat/services/playht/tts.py b/src/pipecat/services/playht/tts.py index b63e5d648..ece3f2c17 100644 --- a/src/pipecat/services/playht/tts.py +++ b/src/pipecat/services/playht/tts.py @@ -215,6 +215,25 @@ class PlayHTTTSService(InterruptibleTTSService): """ return True + async def _update_settings(self, update: TTSSettings) -> set[str]: + """Apply a settings update. + + Settings are stored but not applied to the active connection. + """ + changed = await super()._update_settings(update) + + if not changed: + return changed + + # TODO: someday we could reconnect here to apply updated settings. + # Code might look something like the below: + # await self._disconnect() + # await self._connect() + + self._warn_unhandled_updated_settings(changed) + + return changed + def language_to_service_language(self, language: Language) -> Optional[str]: """Convert a Language enum to PlayHT service language format. diff --git a/src/pipecat/services/rime/tts.py b/src/pipecat/services/rime/tts.py index 5f8a5cef6..e87cf9f4f 100644 --- a/src/pipecat/services/rime/tts.py +++ b/src/pipecat/services/rime/tts.py @@ -279,6 +279,8 @@ class RimeTTSService(AudioContextWordTTSService): self._settings.speaker = self._voice_id await self._disconnect() await self._connect() + else: + self._warn_unhandled_updated_settings(changed) return changed def _build_msg(self, text: str = "") -> dict: diff --git a/src/pipecat/services/sarvam/stt.py b/src/pipecat/services/sarvam/stt.py index 68427fbc4..271b12ffe 100644 --- a/src/pipecat/services/sarvam/stt.py +++ b/src/pipecat/services/sarvam/stt.py @@ -338,11 +338,16 @@ class SarvamSTTService(STTService): changed = await super()._update_settings(update) - if not changed: - return changed + # TODO: someday we could reconnect here to apply updated settings. + # Code might look something like the below: + # if not changed: + # return changed + + # await self._disconnect() + # await self._connect() + + self._warn_unhandled_updated_settings(changed) - await self._disconnect() - await self._connect() return changed async def set_prompt(self, prompt: Optional[str]): diff --git a/src/pipecat/services/sarvam/tts.py b/src/pipecat/services/sarvam/tts.py index 56ce3bef0..6842eda35 100644 --- a/src/pipecat/services/sarvam/tts.py +++ b/src/pipecat/services/sarvam/tts.py @@ -958,6 +958,7 @@ class SarvamTTSService(InterruptibleTTSService): changed = await super()._update_settings(update) if "voice" in changed: await self._send_config() + self._warn_unhandled_updated_settings(changed - {"voice"}) return changed async def _connect(self): diff --git a/src/pipecat/services/soniox/stt.py b/src/pipecat/services/soniox/stt.py index a74a14ee9..29ca33ad5 100644 --- a/src/pipecat/services/soniox/stt.py +++ b/src/pipecat/services/soniox/stt.py @@ -225,7 +225,7 @@ class SonioxSTTService(WebsocketSTTService): ``input_params`` is given, its ``model`` is propagated *up* to the top-level field. - Any change triggers a WebSocket reconnect. + Settings are stored but not applied to the active connection. Args: update: A settings delta. @@ -249,8 +249,12 @@ class SonioxSTTService(WebsocketSTTService): self._settings.model = self._settings.input_params.model self.set_model_name(self._settings.model) - await self._disconnect() - await self._connect() + # TODO: someday we could reconnect here to apply updated settings. + # Code might look something like the below: + # await self._disconnect() + # await self._connect() + + self._warn_unhandled_updated_settings(changed) return changed diff --git a/src/pipecat/services/ultravox/llm.py b/src/pipecat/services/ultravox/llm.py index 434a54ab6..07dc107eb 100644 --- a/src/pipecat/services/ultravox/llm.py +++ b/src/pipecat/services/ultravox/llm.py @@ -329,6 +329,7 @@ class UltravoxRealtimeLLMService(LLMService): changed = await super()._update_settings(update) if "output_medium" in changed: await self._update_output_medium(self._settings.output_medium) + self._warn_unhandled_updated_settings(changed - {"output_medium"}) return changed # From fa6a6dabee584138a9744b190bb8d7321c5c751c Mon Sep 17 00:00:00 2001 From: Paul Kompfner Date: Tue, 17 Feb 2026 11:02:13 -0500 Subject: [PATCH 0500/1060] Fix `DeepgramSageMakerSTTService._update_settings` live_options sync to match `DeepgramSTTService` pattern. MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit Add missing reverse sync (live_options → top-level model/language) and `set_model_name()` call. --- .../services/deepgram/stt_sagemaker.py | 20 ++++++++++++++----- 1 file changed, 15 insertions(+), 5 deletions(-) diff --git a/src/pipecat/services/deepgram/stt_sagemaker.py b/src/pipecat/services/deepgram/stt_sagemaker.py index e503592d7..08acc6530 100644 --- a/src/pipecat/services/deepgram/stt_sagemaker.py +++ b/src/pipecat/services/deepgram/stt_sagemaker.py @@ -167,10 +167,13 @@ class DeepgramSageMakerSTTService(STTService): """Apply a settings update, keeping ``live_options`` in sync. Top-level ``model`` and ``language`` are the source of truth. When - they change their values are propagated into ``live_options``. + they are given in *update* their values are propagated into + ``live_options``. When only ``live_options`` is given, its ``model`` + and ``language`` are propagated *up* to the top-level fields. Any change triggers a reconnect. """ + # Determine which top-level fields are explicitly provided. model_given = isinstance(update, DeepgramSageMakerSTTSettings) and is_given( getattr(update, "model", NOT_GIVEN) ) @@ -183,16 +186,23 @@ class DeepgramSageMakerSTTService(STTService): if not changed: return changed - # Sync model into live_options - if model_given and "model" in changed: + # --- Sync model -------------------------------------------------- + if model_given: + # Top-level model wins → push into live_options. self._settings.live_options.model = self._settings.model + elif "live_options" in changed and self._settings.live_options.model is not None: + # Only live_options was given → pull model up. + self._settings.model = self._settings.live_options.model + self.set_model_name(self._settings.model) - # Sync language into live_options - if language_given and "language" in changed: + # --- Sync language ----------------------------------------------- + if language_given: lang = self._settings.language if isinstance(lang, Language): lang = lang.value self._settings.live_options.language = lang + elif "live_options" in changed and self._settings.live_options.language is not None: + self._settings.language = self._settings.live_options.language await self._disconnect() await self._connect() From 02c2778b8d77a5b9f5877db05395a2159cf13f4a Mon Sep 17 00:00:00 2001 From: Paul Kompfner Date: Tue, 17 Feb 2026 11:07:27 -0500 Subject: [PATCH 0501/1060] Document `_warn_unhandled_updated_settings` pattern in COMMUNITY_INTEGRATIONS.md. --- COMMUNITY_INTEGRATIONS.md | 17 ++++++++++++++++- 1 file changed, 16 insertions(+), 1 deletion(-) diff --git a/COMMUNITY_INTEGRATIONS.md b/COMMUNITY_INTEGRATIONS.md index c169cb5ab..a7cfa6103 100644 --- a/COMMUNITY_INTEGRATIONS.md +++ b/COMMUNITY_INTEGRATIONS.md @@ -282,7 +282,22 @@ async def _update_settings(self, update: STTSettings) -> set[str]: return changed ``` -Note that, in this example, the service requires a reconnect to apply the new language. Consider whether your service requires reconnection or can apply changes in-place. +Note that, in this example, the service requires a reconnect to apply the new language. Consider, for each setting, whether your service requires reconnection or can apply changes in-place. + +If your service can't yet apply certain settings at runtime, call `self._warn_unhandled_updated_settings(changed)` with the set of unhandled field names so users get a clear log message: + +```python +async def _update_settings(self, update: STTSettings) -> set[str]: + changed = await super()._update_settings(update) + + if not changed: + return changed + + # TODO: someday we could reconnect here to apply updated settings. + self._warn_unhandled_updated_settings(changed) + + return changed +``` ### Sample Rate Handling From 3b1ba57452111c69afbbab023fb59c5bd0cb9594 Mon Sep 17 00:00:00 2001 From: Paul Kompfner Date: Tue, 17 Feb 2026 11:49:15 -0500 Subject: [PATCH 0502/1060] Change `apply_update` / `_update_settings` return type from `set[str]` to `dict[str, Any]`. The dict maps each changed field name to its pre-update value, enabling services to do granular diffing of complex settings objects. Existing call-site patterns (`"field" in changed`, `if changed`, iteration) work unchanged; set-difference sites use `changed.keys() - {...}`. --- COMMUNITY_INTEGRATIONS.md | 10 +++++--- src/pipecat/services/ai_service.py | 24 +++++++++--------- src/pipecat/services/assemblyai/stt.py | 4 +-- src/pipecat/services/aws/nova_sonic/llm.py | 2 +- src/pipecat/services/aws/stt.py | 4 +-- src/pipecat/services/azure/stt.py | 4 +-- src/pipecat/services/cartesia/stt.py | 6 ++--- src/pipecat/services/cartesia/tts.py | 2 +- src/pipecat/services/deepgram/flux/stt.py | 2 +- src/pipecat/services/deepgram/stt.py | 4 +-- .../services/deepgram/stt_sagemaker.py | 4 +-- src/pipecat/services/elevenlabs/stt.py | 10 ++++---- src/pipecat/services/elevenlabs/tts.py | 10 ++++---- src/pipecat/services/fal/stt.py | 4 +-- src/pipecat/services/fish/tts.py | 6 ++--- src/pipecat/services/gladia/stt.py | 4 +-- .../services/google/gemini_live/llm.py | 2 +- src/pipecat/services/google/stt.py | 4 +-- src/pipecat/services/google/tts.py | 10 ++++---- src/pipecat/services/gradium/stt.py | 6 ++--- src/pipecat/services/gradium/tts.py | 6 ++--- src/pipecat/services/inworld/tts.py | 2 +- src/pipecat/services/llm_service.py | 4 +-- src/pipecat/services/neuphonic/tts.py | 4 +-- src/pipecat/services/nvidia/stt.py | 6 ++--- src/pipecat/services/openai/stt.py | 6 ++--- src/pipecat/services/playht/tts.py | 4 +-- src/pipecat/services/rime/tts.py | 6 ++--- src/pipecat/services/sarvam/stt.py | 6 ++--- src/pipecat/services/sarvam/tts.py | 6 ++--- src/pipecat/services/settings.py | 20 ++++++++------- src/pipecat/services/soniox/stt.py | 4 +-- src/pipecat/services/speechmatics/stt.py | 6 ++--- src/pipecat/services/stt_service.py | 6 ++--- src/pipecat/services/tts_service.py | 6 ++--- src/pipecat/services/ultravox/llm.py | 2 +- src/pipecat/services/whisper/base_stt.py | 4 +-- tests/test_settings.py | 25 +++++++++++++------ 38 files changed, 129 insertions(+), 116 deletions(-) diff --git a/COMMUNITY_INTEGRATIONS.md b/COMMUNITY_INTEGRATIONS.md index a7cfa6103..f52e30b58 100644 --- a/COMMUNITY_INTEGRATIONS.md +++ b/COMMUNITY_INTEGRATIONS.md @@ -267,10 +267,10 @@ class MySTTService(STTService): self._settings = MySTTSettings(model=model, region=region) ``` -To react to runtime setting changes, override `_update_settings`. The base implementation applies the delta to `self._settings` and returns the set of field names that changed. Your override should call `super()` first, then act on the changed fields: +To react to runtime setting changes, override `_update_settings`. The base implementation applies the delta to `self._settings` and returns a `dict` mapping each changed field name to its **pre-update** value. Your override should call `super()` first, then act on the changed fields: ```python -async def _update_settings(self, update: STTSettings) -> set[str]: +async def _update_settings(self, update: STTSettings) -> dict[str, Any]: """Apply a settings update, reconfiguring the recognizer if needed.""" changed = await super()._update_settings(update) @@ -282,12 +282,14 @@ async def _update_settings(self, update: STTSettings) -> set[str]: return changed ``` +The dict keys work like a set for membership tests (`"language" in changed`) and truthiness (`if changed`). Use `changed.keys() - {"language"}` for set difference, or `changed["language"]` to inspect the previous value of a field. + Note that, in this example, the service requires a reconnect to apply the new language. Consider, for each setting, whether your service requires reconnection or can apply changes in-place. -If your service can't yet apply certain settings at runtime, call `self._warn_unhandled_updated_settings(changed)` with the set of unhandled field names so users get a clear log message: +If your service can't yet apply certain settings at runtime, call `self._warn_unhandled_updated_settings(changed)` with the unhandled field names so users get a clear log message: ```python -async def _update_settings(self, update: STTSettings) -> set[str]: +async def _update_settings(self, update: STTSettings) -> dict[str, Any]: changed = await super()._update_settings(update) if not changed: diff --git a/src/pipecat/services/ai_service.py b/src/pipecat/services/ai_service.py index 64af3b4b2..ec78549c2 100644 --- a/src/pipecat/services/ai_service.py +++ b/src/pipecat/services/ai_service.py @@ -10,7 +10,7 @@ Provides the foundation for all AI services in the Pipecat framework, including model management, settings handling, and frame processing lifecycle methods. """ -from typing import Any, AsyncGenerator, Dict, Set +from typing import Any, AsyncGenerator, Dict from loguru import logger @@ -97,12 +97,13 @@ class AIService(FrameProcessor): """ pass - async def _update_settings(self, update: ServiceSettings) -> Set[str]: - """Apply a settings update and return the set of changed field names. + async def _update_settings(self, update: ServiceSettings) -> Dict[str, Any]: + """Apply a settings update and return the changed fields. - The update is applied to ``_settings`` and the changed-field set is - returned. The ``model`` field is handled specially: when it changes, - ``set_model_name`` is called. + The update is applied to ``_settings`` and a dict mapping each changed + field name to its **pre-update** value is returned. The ``model`` + field is handled specially: when it changes, ``set_model_name`` is + called. Concrete services should override this method (calling ``super()``) to react to specific changed fields (e.g. reconnect on voice change). @@ -111,7 +112,7 @@ class AIService(FrameProcessor): update: A settings delta. Returns: - Set of field names whose values actually changed. + Dict mapping changed field names to their previous values. """ changed = self._settings.apply_update(update) @@ -119,16 +120,15 @@ class AIService(FrameProcessor): self.set_model_name(self._settings.model) if changed: - logger.info(f"{self.name}: updated settings fields: {changed}") + logger.info(f"{self.name}: updated settings fields: {set(changed)}") return changed - def _warn_unhandled_updated_settings(self, unhandled: Set[str]): + def _warn_unhandled_updated_settings(self, unhandled): """Log a warning for settings changes that won't take effect at runtime. - Convenience helper for ``_update_settings`` overrides. Call with the - set of field names that changed but that the service does not (yet) - apply at runtime. + Convenience helper for ``_update_settings`` overrides. Accepts any + iterable of field names (a ``dict``, ``set``, ``dict_keys``, etc.). Args: unhandled: Field names that changed but are not applied. diff --git a/src/pipecat/services/assemblyai/stt.py b/src/pipecat/services/assemblyai/stt.py index a291e6903..23b7d149b 100644 --- a/src/pipecat/services/assemblyai/stt.py +++ b/src/pipecat/services/assemblyai/stt.py @@ -184,7 +184,7 @@ class AssemblyAISTTService(WebsocketSTTService): """ return True - async def _update_settings(self, update: STTSettings) -> set[str]: + async def _update_settings(self, update: STTSettings) -> dict[str, Any]: """Apply a settings update. Settings are stored but not applied to the active connection. @@ -193,7 +193,7 @@ class AssemblyAISTTService(WebsocketSTTService): update: A :class:`STTSettings` (or ``AssemblyAISTTSettings``) delta. Returns: - Set of field names whose values actually changed. + Dict mapping changed field names to their previous values. """ changed = await super()._update_settings(update) diff --git a/src/pipecat/services/aws/nova_sonic/llm.py b/src/pipecat/services/aws/nova_sonic/llm.py index 92bd0ea1f..91c2374e3 100644 --- a/src/pipecat/services/aws/nova_sonic/llm.py +++ b/src/pipecat/services/aws/nova_sonic/llm.py @@ -307,7 +307,7 @@ class AWSNovaSonicLLMService(LLMService): # settings # - async def _update_settings(self, update: LLMSettings) -> set[str]: + async def _update_settings(self, update: LLMSettings) -> dict[str, Any]: """Apply a settings update. Settings are stored but not applied to the active connection. diff --git a/src/pipecat/services/aws/stt.py b/src/pipecat/services/aws/stt.py index dda58e2ba..ae502e8be 100644 --- a/src/pipecat/services/aws/stt.py +++ b/src/pipecat/services/aws/stt.py @@ -15,7 +15,7 @@ import os import random import string from dataclasses import dataclass, field -from typing import AsyncGenerator, Optional +from typing import Any, AsyncGenerator, Optional from loguru import logger @@ -140,7 +140,7 @@ class AWSTranscribeSTTService(WebsocketSTTService): } return encoding_map.get(encoding, encoding) - async def _update_settings(self, update: STTSettings) -> set[str]: + async def _update_settings(self, update: STTSettings) -> dict[str, Any]: """Apply a settings update. Settings are stored but not applied to the active connection. diff --git a/src/pipecat/services/azure/stt.py b/src/pipecat/services/azure/stt.py index a9ecd67e7..8a5b09e26 100644 --- a/src/pipecat/services/azure/stt.py +++ b/src/pipecat/services/azure/stt.py @@ -12,7 +12,7 @@ Speech SDK for real-time audio transcription. import asyncio from dataclasses import dataclass, field -from typing import AsyncGenerator, Optional +from typing import Any, AsyncGenerator, Optional from loguru import logger @@ -123,7 +123,7 @@ class AzureSTTService(STTService): """ return True - async def _update_settings(self, update: STTSettings) -> set[str]: + async def _update_settings(self, update: STTSettings) -> dict[str, Any]: """Apply a settings update. Settings are stored but not applied to the active recognizer. diff --git a/src/pipecat/services/cartesia/stt.py b/src/pipecat/services/cartesia/stt.py index a069dface..6629d05bb 100644 --- a/src/pipecat/services/cartesia/stt.py +++ b/src/pipecat/services/cartesia/stt.py @@ -13,7 +13,7 @@ the Cartesia Live transcription API for real-time speech recognition. import json import urllib.parse from dataclasses import dataclass, field -from typing import AsyncGenerator, Optional +from typing import Any, AsyncGenerator, Optional from loguru import logger @@ -294,14 +294,14 @@ class CartesiaSTTService(WebsocketSTTService): await self._disconnect_websocket() - async def _update_settings(self, update: STTSettings) -> set[str]: + async def _update_settings(self, update: STTSettings) -> dict[str, Any]: """Apply a settings update. Args: update: A :class:`STTSettings` (or ``CartesiaSTTSettings``) delta. Returns: - Set of field names whose values actually changed. + Dict mapping changed field names to their previous values. """ changed = await super()._update_settings(update) diff --git a/src/pipecat/services/cartesia/tts.py b/src/pipecat/services/cartesia/tts.py index 00620fdb0..2544d3b98 100644 --- a/src/pipecat/services/cartesia/tts.py +++ b/src/pipecat/services/cartesia/tts.py @@ -344,7 +344,7 @@ class CartesiaTTSService(AudioContextWordTTSService): """ return True - async def _update_settings(self, update: TTSSettings) -> set[str]: + async def _update_settings(self, update: TTSSettings) -> dict[str, Any]: """Apply a settings update. Settings are stored but not applied to the active connection. diff --git a/src/pipecat/services/deepgram/flux/stt.py b/src/pipecat/services/deepgram/flux/stt.py index 14e77c2d3..dcb5e3429 100644 --- a/src/pipecat/services/deepgram/flux/stt.py +++ b/src/pipecat/services/deepgram/flux/stt.py @@ -330,7 +330,7 @@ class DeepgramFluxSTTService(WebsocketSTTService): """ return True - async def _update_settings(self, update: STTSettings) -> set[str]: + async def _update_settings(self, update: STTSettings) -> dict[str, Any]: """Apply a settings update. Settings are stored but not applied to the active connection. diff --git a/src/pipecat/services/deepgram/stt.py b/src/pipecat/services/deepgram/stt.py index 32759069b..f52932b2c 100644 --- a/src/pipecat/services/deepgram/stt.py +++ b/src/pipecat/services/deepgram/stt.py @@ -7,7 +7,7 @@ """Deepgram speech-to-text service implementation.""" from dataclasses import dataclass, field -from typing import AsyncGenerator, Dict, Optional +from typing import Any, AsyncGenerator, Dict, Optional from loguru import logger @@ -195,7 +195,7 @@ class DeepgramSTTService(STTService): """ return True - async def _update_settings(self, update: STTSettings) -> set[str]: + async def _update_settings(self, update: STTSettings) -> dict[str, Any]: """Apply a settings update, keeping ``live_options`` in sync. Top-level ``model`` and ``language`` are the source of truth. When diff --git a/src/pipecat/services/deepgram/stt_sagemaker.py b/src/pipecat/services/deepgram/stt_sagemaker.py index 08acc6530..870ded11f 100644 --- a/src/pipecat/services/deepgram/stt_sagemaker.py +++ b/src/pipecat/services/deepgram/stt_sagemaker.py @@ -15,7 +15,7 @@ languages, and various Deepgram features. import asyncio import json from dataclasses import dataclass, field -from typing import AsyncGenerator, Optional +from typing import Any, AsyncGenerator, Optional from loguru import logger @@ -163,7 +163,7 @@ class DeepgramSageMakerSTTService(STTService): """ return True - async def _update_settings(self, update: STTSettings) -> set[str]: + async def _update_settings(self, update: STTSettings) -> dict[str, Any]: """Apply a settings update, keeping ``live_options`` in sync. Top-level ``model`` and ``language`` are the source of truth. When diff --git a/src/pipecat/services/elevenlabs/stt.py b/src/pipecat/services/elevenlabs/stt.py index d2b7a8f99..fd938c12e 100644 --- a/src/pipecat/services/elevenlabs/stt.py +++ b/src/pipecat/services/elevenlabs/stt.py @@ -16,7 +16,7 @@ import io import json from dataclasses import dataclass, field from enum import Enum -from typing import AsyncGenerator, Optional +from typing import Any, AsyncGenerator, Optional import aiohttp from loguru import logger @@ -294,7 +294,7 @@ class ElevenLabsSTTService(SegmentedSTTService): """ return language_to_elevenlabs_language(language) - async def _update_settings(self, update: STTSettings) -> set[str]: + async def _update_settings(self, update: STTSettings) -> dict[str, Any]: """Apply a settings update. Converts language to ElevenLabs format before applying and keeps @@ -304,7 +304,7 @@ class ElevenLabsSTTService(SegmentedSTTService): update: A :class:`STTSettings` (or ``ElevenLabsSTTSettings``) delta. Returns: - Set of field names whose values actually changed. + Dict mapping changed field names to their previous values. """ # Convert language to ElevenLabs format before applying if is_given(update.language) and isinstance(update.language, Language): @@ -543,7 +543,7 @@ class ElevenLabsRealtimeSTTService(WebsocketSTTService): """ return True - async def _update_settings(self, update: STTSettings) -> set[str]: + async def _update_settings(self, update: STTSettings) -> dict[str, Any]: """Apply a settings update and reconnect if anything changed. Converts language to ElevenLabs format before applying and keeps @@ -553,7 +553,7 @@ class ElevenLabsRealtimeSTTService(WebsocketSTTService): update: A :class:`STTSettings` (or ``ElevenLabsRealtimeSTTSettings``) delta. Returns: - Set of field names whose values actually changed. + Dict mapping changed field names to their previous values. """ # Convert language to ElevenLabs format before applying if is_given(update.language) and isinstance(update.language, Language): diff --git a/src/pipecat/services/elevenlabs/tts.py b/src/pipecat/services/elevenlabs/tts.py index 79f05bbf8..022b08b94 100644 --- a/src/pipecat/services/elevenlabs/tts.py +++ b/src/pipecat/services/elevenlabs/tts.py @@ -471,7 +471,7 @@ class ElevenLabsTTSService(AudioContextWordTTSService): voice_settings[key] = val return voice_settings or None - async def _update_settings(self, update: TTSSettings) -> set[str]: + async def _update_settings(self, update: TTSSettings) -> dict[str, Any]: """Apply a settings update, reconnecting as needed. Uses the declarative ``URL_FIELDS`` and ``VOICE_SETTINGS_FIELDS`` @@ -482,7 +482,7 @@ class ElevenLabsTTSService(AudioContextWordTTSService): update: A :class:`TTSSettings` (or ``ElevenLabsTTSSettings``) delta. Returns: - Set of field names whose values actually changed. + Dict mapping changed field names to their previous values. """ changed = await super()._update_settings(update) @@ -520,7 +520,7 @@ class ElevenLabsTTSService(AudioContextWordTTSService): # Reconnect applies all settings; only warn about fields not handled # by voice settings or URL changes. handled = ElevenLabsTTSSettings.URL_FIELDS | ElevenLabsTTSSettings.VOICE_SETTINGS_FIELDS - self._warn_unhandled_updated_settings(changed - handled) + self._warn_unhandled_updated_settings(changed.keys() - handled) return changed @@ -964,14 +964,14 @@ class ElevenLabsHttpTTSService(WordTTSService): def _set_voice_settings(self): return build_elevenlabs_voice_settings(self._settings) - async def _update_settings(self, update: TTSSettings) -> set[str]: + async def _update_settings(self, update: TTSSettings) -> dict[str, Any]: """Apply a settings update and rebuild voice settings. Args: update: A :class:`TTSSettings` (or ``ElevenLabsHttpTTSSettings``) delta. Returns: - Set of field names whose values actually changed. + Dict mapping changed field names to their previous values. """ changed = await super()._update_settings(update) if changed: diff --git a/src/pipecat/services/fal/stt.py b/src/pipecat/services/fal/stt.py index ff6628f6c..28b611865 100644 --- a/src/pipecat/services/fal/stt.py +++ b/src/pipecat/services/fal/stt.py @@ -12,7 +12,7 @@ transcription using segmented audio processing. import os from dataclasses import dataclass, field -from typing import AsyncGenerator, Optional +from typing import Any, AsyncGenerator, Optional from loguru import logger from pydantic import BaseModel @@ -251,7 +251,7 @@ class FalSTTService(SegmentedSTTService): """ return language_to_fal_language(language) - async def _update_settings(self, update: STTSettings) -> set[str]: + async def _update_settings(self, update: STTSettings) -> dict[str, Any]: """Apply a settings update, converting language if changed.""" changed = await super()._update_settings(update) diff --git a/src/pipecat/services/fish/tts.py b/src/pipecat/services/fish/tts.py index daa884af8..4da4b6673 100644 --- a/src/pipecat/services/fish/tts.py +++ b/src/pipecat/services/fish/tts.py @@ -12,7 +12,7 @@ for streaming text-to-speech synthesis with customizable voice parameters. import uuid from dataclasses import dataclass, field -from typing import AsyncGenerator, Literal, Optional +from typing import Any, AsyncGenerator, Literal, Optional from loguru import logger from pydantic import BaseModel @@ -184,7 +184,7 @@ class FishAudioTTSService(InterruptibleTTSService): """ return True - async def _update_settings(self, update: TTSSettings) -> set[str]: + async def _update_settings(self, update: TTSSettings) -> dict[str, Any]: """Apply a settings update and reconnect if needed. Any change to voice or model triggers a WebSocket reconnect. @@ -193,7 +193,7 @@ class FishAudioTTSService(InterruptibleTTSService): update: A :class:`TTSSettings` (or ``FishAudioTTSSettings``) delta. Returns: - Set of field names whose values actually changed. + Dict mapping changed field names to their previous values. """ changed = await super()._update_settings(update) if changed: diff --git a/src/pipecat/services/gladia/stt.py b/src/pipecat/services/gladia/stt.py index 500b88052..25922e7aa 100644 --- a/src/pipecat/services/gladia/stt.py +++ b/src/pipecat/services/gladia/stt.py @@ -379,7 +379,7 @@ class GladiaSTTService(WebsocketSTTService): await super().start(frame) await self._connect() - async def _update_settings(self, update: GladiaSTTSettings) -> set[str]: + async def _update_settings(self, update: GladiaSTTSettings) -> dict[str, Any]: """Apply settings update. Settings are stored but not applied to the active session. @@ -388,7 +388,7 @@ class GladiaSTTService(WebsocketSTTService): update: A settings delta. Returns: - Set of field names whose values actually changed. + Dict mapping changed field names to their previous values. """ changed = await super()._update_settings(update) diff --git a/src/pipecat/services/google/gemini_live/llm.py b/src/pipecat/services/google/gemini_live/llm.py index ecca52396..3047e258d 100644 --- a/src/pipecat/services/google/gemini_live/llm.py +++ b/src/pipecat/services/google/gemini_live/llm.py @@ -804,7 +804,7 @@ class GeminiLiveLLMService(LLMService): """ return True - async def _update_settings(self, update: LLMSettings) -> set[str]: + async def _update_settings(self, update: LLMSettings) -> dict[str, Any]: """Apply a settings update. Settings are stored but not applied to the active connection. diff --git a/src/pipecat/services/google/stt.py b/src/pipecat/services/google/stt.py index d4ffb0d91..cdd583c8e 100644 --- a/src/pipecat/services/google/stt.py +++ b/src/pipecat/services/google/stt.py @@ -630,7 +630,7 @@ class GoogleSTTService(STTService): logger.debug(f"Switching STT languages to: {languages}") await self._update_settings(GoogleSTTSettings(languages=list(languages))) - async def _update_settings(self, update: GoogleSTTSettings) -> set[str]: + async def _update_settings(self, update: GoogleSTTSettings) -> dict[str, Any]: """Apply settings update and reconnect if anything changed. Handles ``language`` from base ``set_language`` by converting it to @@ -642,7 +642,7 @@ class GoogleSTTService(STTService): update: A settings delta. Returns: - Set of field names whose values actually changed. + Dict mapping changed field names to their previous values. """ from pipecat.services.settings import is_given diff --git a/src/pipecat/services/google/tts.py b/src/pipecat/services/google/tts.py index 9769aa665..e47aa384a 100644 --- a/src/pipecat/services/google/tts.py +++ b/src/pipecat/services/google/tts.py @@ -24,7 +24,7 @@ from pipecat.utils.tracing.service_decorators import traced_tts os.environ["GRPC_ENABLE_FORK_SUPPORT"] = "false" from dataclasses import dataclass, field -from typing import AsyncGenerator, List, Literal, Optional +from typing import Any, AsyncGenerator, List, Literal, Optional from loguru import logger from pydantic import BaseModel @@ -680,7 +680,7 @@ class GoogleHttpTTSService(TTSService): """ return language_to_google_tts_language(language) - async def _update_settings(self, update: TTSSettings) -> set[str]: + async def _update_settings(self, update: TTSSettings) -> dict[str, Any]: """Override to handle speaking_rate validation. Args: @@ -1024,7 +1024,7 @@ class GoogleTTSService(GoogleBaseTTSService): credentials, credentials_path ) - async def _update_settings(self, update: TTSSettings) -> set[str]: + async def _update_settings(self, update: TTSSettings) -> dict[str, Any]: """Override to handle speaking_rate validation. Args: @@ -1259,14 +1259,14 @@ class GeminiTTSService(GoogleBaseTTSService): f"Current rate of {self.sample_rate}Hz may cause issues." ) - async def _update_settings(self, update: TTSSettings) -> set[str]: + async def _update_settings(self, update: TTSSettings) -> dict[str, Any]: """Apply a settings update with voice validation. Args: update: Settings delta. Can include 'voice', 'prompt', etc. Returns: - Set of field names whose values actually changed. + Dict mapping changed field names to their previous values. """ if is_given(update.voice) and update.voice not in self.AVAILABLE_VOICES: logger.warning(f"Voice '{update.voice}' not in known voices list. Using anyway.") diff --git a/src/pipecat/services/gradium/stt.py b/src/pipecat/services/gradium/stt.py index 3b634cbd2..381f76884 100644 --- a/src/pipecat/services/gradium/stt.py +++ b/src/pipecat/services/gradium/stt.py @@ -13,7 +13,7 @@ WebSocket API for streaming audio transcription. import base64 import json from dataclasses import dataclass, field -from typing import AsyncGenerator, Optional +from typing import Any, AsyncGenerator, Optional from loguru import logger from pydantic import BaseModel @@ -171,14 +171,14 @@ class GradiumSTTService(WebsocketSTTService): """ return True - async def _update_settings(self, update: STTSettings) -> set[str]: + async def _update_settings(self, update: STTSettings) -> dict[str, Any]: """Apply a settings update, sync params, and reconnect. Args: update: A :class:`STTSettings` (or ``GradiumSTTSettings``) delta. Returns: - Set of field names whose values actually changed. + Dict mapping changed field names to their previous values. """ changed = await super()._update_settings(update) if not changed: diff --git a/src/pipecat/services/gradium/tts.py b/src/pipecat/services/gradium/tts.py index 947404baa..3bffbb5bf 100644 --- a/src/pipecat/services/gradium/tts.py +++ b/src/pipecat/services/gradium/tts.py @@ -7,7 +7,7 @@ import base64 import json from dataclasses import dataclass, field -from typing import AsyncGenerator, Optional +from typing import Any, AsyncGenerator, Optional from loguru import logger from pydantic import BaseModel @@ -119,14 +119,14 @@ class GradiumTTSService(InterruptibleWordTTSService): """ return True - async def _update_settings(self, update: TTSSettings) -> set[str]: + async def _update_settings(self, update: TTSSettings) -> dict[str, Any]: """Apply a settings update and reconnect if voice changed. Args: update: A :class:`TTSSettings` (or ``GradiumTTSSettings``) delta. Returns: - Set of field names whose values actually changed. + Dict mapping changed field names to their previous values. """ prev_voice = self._voice_id changed = await super()._update_settings(update) diff --git a/src/pipecat/services/inworld/tts.py b/src/pipecat/services/inworld/tts.py index 80d95aef9..c291f3156 100644 --- a/src/pipecat/services/inworld/tts.py +++ b/src/pipecat/services/inworld/tts.py @@ -165,7 +165,7 @@ class InworldHttpTTSService(WordTTSService): """ return True - async def _update_settings(self, update: TTSSettings) -> set[str]: + async def _update_settings(self, update: TTSSettings) -> dict[str, Any]: """Apply a settings update. Settings are stored but not applied to the active connection. diff --git a/src/pipecat/services/llm_service.py b/src/pipecat/services/llm_service.py index 97d49192c..860a472c9 100644 --- a/src/pipecat/services/llm_service.py +++ b/src/pipecat/services/llm_service.py @@ -313,14 +313,14 @@ class LLMService(UserTurnCompletionLLMServiceMixin, AIService): await self._cancel_sequential_runner_task() await self._cancel_summary_task() - async def _update_settings(self, update: LLMSettings) -> set[str]: + async def _update_settings(self, update: LLMSettings) -> dict[str, Any]: """Apply a settings update, handling turn-completion fields. Args: update: An LLM settings delta. Returns: - Set of field names whose values actually changed. + Dict mapping changed field names to their previous values. """ changed = await super()._update_settings(update) diff --git a/src/pipecat/services/neuphonic/tts.py b/src/pipecat/services/neuphonic/tts.py index 0680de4f6..0797f9b1b 100644 --- a/src/pipecat/services/neuphonic/tts.py +++ b/src/pipecat/services/neuphonic/tts.py @@ -14,7 +14,7 @@ import asyncio import base64 import json from dataclasses import dataclass, field -from typing import AsyncGenerator, Optional +from typing import Any, AsyncGenerator, Optional import aiohttp from loguru import logger @@ -181,7 +181,7 @@ class NeuphonicTTSService(InterruptibleTTSService): """ return language_to_neuphonic_lang_code(language) - async def _update_settings(self, update: TTSSettings) -> set[str]: + async def _update_settings(self, update: TTSSettings) -> dict[str, Any]: """Apply a settings update and reconnect with new configuration.""" changed = await super()._update_settings(update) if changed: diff --git a/src/pipecat/services/nvidia/stt.py b/src/pipecat/services/nvidia/stt.py index ff76a6900..b0d11fc2b 100644 --- a/src/pipecat/services/nvidia/stt.py +++ b/src/pipecat/services/nvidia/stt.py @@ -9,7 +9,7 @@ import asyncio from concurrent.futures import CancelledError as FuturesCancelledError from dataclasses import dataclass, field -from typing import AsyncGenerator, List, Mapping, Optional +from typing import Any, AsyncGenerator, List, Mapping, Optional from loguru import logger from pydantic import BaseModel @@ -579,14 +579,14 @@ class NvidiaSegmentedSTTService(SegmentedSTTService): self._config = self._create_recognition_config() logger.debug(f"Initialized NvidiaSegmentedSTTService with model: {self.model_name}") - async def _update_settings(self, update: STTSettings) -> set[str]: + async def _update_settings(self, update: STTSettings) -> dict[str, Any]: """Apply a settings update and sync internal state. Args: update: A :class:`STTSettings` (or ``NvidiaSegmentedSTTSettings``) delta. Returns: - Set of field names whose values actually changed. + Dict mapping changed field names to their previous values. """ changed = await super()._update_settings(update) diff --git a/src/pipecat/services/openai/stt.py b/src/pipecat/services/openai/stt.py index 458f40133..6daefd1da 100644 --- a/src/pipecat/services/openai/stt.py +++ b/src/pipecat/services/openai/stt.py @@ -17,7 +17,7 @@ Provides two STT services: import base64 import json from dataclasses import dataclass, field -from typing import AsyncGenerator, Literal, Optional, Union +from typing import Any, AsyncGenerator, Literal, Optional, Union from loguru import logger @@ -268,7 +268,7 @@ class OpenAIRealtimeSTTService(WebsocketSTTService): """ return True - async def _update_settings(self, update: STTSettings) -> set[str]: + async def _update_settings(self, update: STTSettings) -> dict[str, Any]: """Apply a settings update and send session update if needed. Keeps ``_language_code`` and ``_prompt`` in sync with settings @@ -278,7 +278,7 @@ class OpenAIRealtimeSTTService(WebsocketSTTService): update: A :class:`STTSettings` (or ``OpenAIRealtimeSTTSettings``) delta. Returns: - Set of field names whose values actually changed. + Dict mapping changed field names to their previous values. """ changed = await super()._update_settings(update) diff --git a/src/pipecat/services/playht/tts.py b/src/pipecat/services/playht/tts.py index ece3f2c17..1965c9ea3 100644 --- a/src/pipecat/services/playht/tts.py +++ b/src/pipecat/services/playht/tts.py @@ -15,7 +15,7 @@ import json import struct import warnings from dataclasses import dataclass, field -from typing import AsyncGenerator, Optional +from typing import Any, AsyncGenerator, Optional import aiohttp from loguru import logger @@ -215,7 +215,7 @@ class PlayHTTTSService(InterruptibleTTSService): """ return True - async def _update_settings(self, update: TTSSettings) -> set[str]: + async def _update_settings(self, update: TTSSettings) -> dict[str, Any]: """Apply a settings update. Settings are stored but not applied to the active connection. diff --git a/src/pipecat/services/rime/tts.py b/src/pipecat/services/rime/tts.py index e87cf9f4f..9e916025c 100644 --- a/src/pipecat/services/rime/tts.py +++ b/src/pipecat/services/rime/tts.py @@ -13,7 +13,7 @@ using Rime's API for streaming and batch audio synthesis. import base64 import json from dataclasses import dataclass, field -from typing import AsyncGenerator, Optional +from typing import Any, AsyncGenerator, Optional import aiohttp from loguru import logger @@ -271,7 +271,7 @@ class RimeTTSService(AudioContextWordTTSService): self._extra_msg_fields["inlineSpeedAlpha"] = ",".join(speed_vals + [str(speed)]) return f"[{text}]" - async def _update_settings(self, update: TTSSettings) -> set[str]: + async def _update_settings(self, update: TTSSettings) -> dict[str, Any]: """Apply a settings update and reconnect if voice changed.""" prev_voice = self._voice_id changed = await super()._update_settings(update) @@ -977,7 +977,7 @@ class RimeNonJsonTTSService(InterruptibleTTSService): except Exception as e: yield ErrorFrame(error=f"Unknown error occurred: {e}") - async def _update_settings(self, update: TTSSettings) -> set[str]: + async def _update_settings(self, update: TTSSettings) -> dict[str, Any]: """Apply a settings update and reconnect if necessary. Since all settings are WebSocket URL query parameters, diff --git a/src/pipecat/services/sarvam/stt.py b/src/pipecat/services/sarvam/stt.py index 271b12ffe..80e6d6ca2 100644 --- a/src/pipecat/services/sarvam/stt.py +++ b/src/pipecat/services/sarvam/stt.py @@ -13,7 +13,7 @@ can handle multiple audio formats for Indian language speech recognition. import base64 from dataclasses import dataclass, field -from typing import AsyncGenerator, Dict, Literal, Optional +from typing import Any, AsyncGenerator, Dict, Literal, Optional from loguru import logger from pydantic import BaseModel @@ -306,14 +306,14 @@ class SarvamSTTService(STTService): if self._socket_client: await self._socket_client.flush() - async def _update_settings(self, update: STTSettings) -> set[str]: + async def _update_settings(self, update: STTSettings) -> dict[str, Any]: """Apply a settings update, validate, sync state, and reconnect. Args: update: A :class:`STTSettings` (or ``SarvamSTTSettings``) delta. Returns: - Set of field names whose values actually changed. + Dict mapping changed field names to their previous values. Raises: ValueError: If a setting is not supported by the current model. diff --git a/src/pipecat/services/sarvam/tts.py b/src/pipecat/services/sarvam/tts.py index 6842eda35..99a0827f5 100644 --- a/src/pipecat/services/sarvam/tts.py +++ b/src/pipecat/services/sarvam/tts.py @@ -42,7 +42,7 @@ import base64 import json from dataclasses import dataclass, field from enum import Enum -from typing import AsyncGenerator, Dict, List, Optional, Tuple +from typing import Any, AsyncGenerator, Dict, List, Optional, Tuple import aiohttp from loguru import logger @@ -953,12 +953,12 @@ class SarvamTTSService(InterruptibleTTSService): if isinstance(frame, (LLMFullResponseEndFrame, EndFrame)): await self.flush_audio() - async def _update_settings(self, update: TTSSettings) -> set[str]: + async def _update_settings(self, update: TTSSettings) -> dict[str, Any]: """Apply a settings update and resend config if voice changed.""" changed = await super()._update_settings(update) if "voice" in changed: await self._send_config() - self._warn_unhandled_updated_settings(changed - {"voice"}) + self._warn_unhandled_updated_settings(changed.keys() - {"voice"}) return changed async def _connect(self): diff --git a/src/pipecat/services/settings.py b/src/pipecat/services/settings.py index d63e1f539..eae120842 100644 --- a/src/pipecat/services/settings.py +++ b/src/pipecat/services/settings.py @@ -19,7 +19,7 @@ Key concepts: service's current settings *and* for update objects. Fields set to ``NOT_GIVEN`` are simply skipped when applying an update. - **apply_update**: Applies a delta onto a target settings object and returns - the set of field names that actually changed. + a dict mapping each changed field name to its previous value. - **from_mapping**: Constructs a settings object from a plain dict, supporting field aliases (e.g. ``"voice_id"`` → ``"voice"``). - **Extras**: Unknown keys land in the ``extra`` dict so services that have @@ -30,7 +30,7 @@ from __future__ import annotations import copy from dataclasses import dataclass, field, fields -from typing import TYPE_CHECKING, Any, ClassVar, Dict, Mapping, Optional, Set, Type, TypeVar +from typing import TYPE_CHECKING, Any, ClassVar, Dict, Mapping, Optional, Type, TypeVar from loguru import logger @@ -140,8 +140,8 @@ class ServiceSettings: result.update(self.extra) return result - def apply_update(self: _S, update: _S) -> Set[str]: - """Apply *update* onto this settings object, returning changed field names. + def apply_update(self: _S, update: _S) -> Dict[str, Any]: + """Apply *update* onto this settings object, returning changed fields. Only fields in *update* that are **given** (i.e. not ``NOT_GIVEN``) are considered. A field is "changed" if its new value differs from @@ -154,17 +154,19 @@ class ServiceSettings: update: A settings object of the same type containing the delta. Returns: - The set of field names whose values actually changed. + A dict mapping each changed field name to its **pre-update** value. + Use ``changed.keys()`` for the set of names, or index with + ``changed["field"]`` to inspect the old value. Examples:: current = TTSSettings(voice="alice", language="en") delta = TTSSettings(voice="bob") changed = current.apply_update(delta) - # changed == {"voice"} + # changed == {"voice": "alice"} # current.voice == "bob", current.language == "en" """ - changed: Set[str] = set() + changed: Dict[str, Any] = {} for f in fields(self): if f.name == "extra": continue @@ -174,14 +176,14 @@ class ServiceSettings: old_val = getattr(self, f.name) if old_val != new_val: setattr(self, f.name, new_val) - changed.add(f.name) + changed[f.name] = old_val # Merge extra for key, new_val in update.extra.items(): old_val = self.extra.get(key, NOT_GIVEN) if old_val != new_val: self.extra[key] = new_val - changed.add(key) + changed[key] = old_val return changed diff --git a/src/pipecat/services/soniox/stt.py b/src/pipecat/services/soniox/stt.py index 29ca33ad5..5c4b49cbe 100644 --- a/src/pipecat/services/soniox/stt.py +++ b/src/pipecat/services/soniox/stt.py @@ -217,7 +217,7 @@ class SonioxSTTService(WebsocketSTTService): await super().start(frame) await self._connect() - async def _update_settings(self, update: SonioxSTTSettings) -> set[str]: + async def _update_settings(self, update: SonioxSTTSettings) -> dict[str, Any]: """Apply a settings update, keeping ``input_params`` in sync. Top-level ``model`` is the source of truth. When it is given in @@ -231,7 +231,7 @@ class SonioxSTTService(WebsocketSTTService): update: A settings delta. Returns: - Set of field names whose values actually changed. + Dict mapping changed field names to their previous values. """ model_given = is_given(getattr(update, "model", NOT_GIVEN)) diff --git a/src/pipecat/services/speechmatics/stt.py b/src/pipecat/services/speechmatics/stt.py index 5bacc208a..c6fe0d16e 100644 --- a/src/pipecat/services/speechmatics/stt.py +++ b/src/pipecat/services/speechmatics/stt.py @@ -480,7 +480,7 @@ class SpeechmaticsSTTService(STTService): await super().start(frame) await self._connect() - async def _update_settings(self, update: SpeechmaticsSTTSettings) -> set[str]: + async def _update_settings(self, update: SpeechmaticsSTTSettings) -> dict[str, Any]: """Apply settings update, reconnecting only when necessary. Fields are classified into three categories (see @@ -497,7 +497,7 @@ class SpeechmaticsSTTService(STTService): update: A settings delta. Returns: - Set of field names whose values actually changed. + Dict mapping changed field names to their previous values. """ changed = await super()._update_settings(update) @@ -505,7 +505,7 @@ class SpeechmaticsSTTService(STTService): return changed no_reconnect = SpeechmaticsSTTSettings.HOT_FIELDS | SpeechmaticsSTTSettings.LOCAL_FIELDS - needs_reconnect = bool(changed - no_reconnect) + needs_reconnect = bool(changed.keys() - no_reconnect) if needs_reconnect: # Connection-level fields changed — rebuild the SDK config diff --git a/src/pipecat/services/stt_service.py b/src/pipecat/services/stt_service.py index e92095297..d6dd31824 100644 --- a/src/pipecat/services/stt_service.py +++ b/src/pipecat/services/stt_service.py @@ -236,19 +236,19 @@ class STTService(AIService): await super().cleanup() await self._cancel_ttfb_timeout() - async def _update_settings(self, update: STTSettings) -> set[str]: + async def _update_settings(self, update: STTSettings) -> dict[str, Any]: """Apply an STT settings update. Handles ``model`` (via parent). Does **not** call ``set_language`` — concrete services should override this method and handle language changes (including any reconnect logic) based on the returned - changed-field set. + changed-field dict. Args: update: An STT settings delta. Returns: - Set of field names whose values actually changed. + Dict mapping changed field names to their previous values. """ changed = await super()._update_settings(update) return changed diff --git a/src/pipecat/services/tts_service.py b/src/pipecat/services/tts_service.py index a696e538d..bb5cff69f 100644 --- a/src/pipecat/services/tts_service.py +++ b/src/pipecat/services/tts_service.py @@ -432,20 +432,20 @@ class TTSService(AIService): if not (agg_type == aggregation_type and func == transform_function) ] - async def _update_settings(self, update: TTSSettings) -> set[str]: + async def _update_settings(self, update: TTSSettings) -> dict[str, Any]: """Apply a TTS settings update. Handles ``model`` (via parent) and syncs ``_voice_id`` when voice changes. Translates language values before applying. Does **not** call ``set_voice`` or ``set_model`` directly — concrete services should override this method and handle reconnect logic based on the - returned changed-field set. + returned changed-field dict. Args: update: A TTS settings delta. Returns: - Set of field names whose values actually changed. + Dict mapping changed field names to their previous values. """ # Translate language *before* applying so the stored value is canonical if is_given(update.language) and update.language is not None: diff --git a/src/pipecat/services/ultravox/llm.py b/src/pipecat/services/ultravox/llm.py index 07dc107eb..ef8baacb4 100644 --- a/src/pipecat/services/ultravox/llm.py +++ b/src/pipecat/services/ultravox/llm.py @@ -329,7 +329,7 @@ class UltravoxRealtimeLLMService(LLMService): changed = await super()._update_settings(update) if "output_medium" in changed: await self._update_output_medium(self._settings.output_medium) - self._warn_unhandled_updated_settings(changed - {"output_medium"}) + self._warn_unhandled_updated_settings(changed.keys() - {"output_medium"}) return changed # diff --git a/src/pipecat/services/whisper/base_stt.py b/src/pipecat/services/whisper/base_stt.py index 6ff85efeb..a67ad1cbc 100644 --- a/src/pipecat/services/whisper/base_stt.py +++ b/src/pipecat/services/whisper/base_stt.py @@ -11,7 +11,7 @@ interface, including language mapping, metrics generation, and error handling. """ from dataclasses import dataclass, field -from typing import AsyncGenerator, Optional +from typing import Any, AsyncGenerator, Optional from loguru import logger from openai import AsyncOpenAI @@ -174,7 +174,7 @@ class BaseWhisperSTTService(SegmentedSTTService): def _create_client(self, api_key: Optional[str], base_url: Optional[str]): return AsyncOpenAI(api_key=api_key, base_url=base_url) - async def _update_settings(self, update: STTSettings) -> set[str]: + async def _update_settings(self, update: STTSettings) -> dict[str, Any]: """Apply a settings update, syncing instance variables. Keeps ``_language``, ``_prompt``, and ``_temperature`` in sync with diff --git a/tests/test_settings.py b/tests/test_settings.py index 62583b00b..71d66fc35 100644 --- a/tests/test_settings.py +++ b/tests/test_settings.py @@ -100,7 +100,8 @@ class TestApplyUpdate: current = TTSSettings(voice="alice", language="en") delta = TTSSettings(voice="bob") changed = current.apply_update(delta) - assert changed == {"voice"} + assert changed.keys() == {"voice"} + assert changed["voice"] == "alice" # old value assert current.voice == "bob" assert current.language == "en" @@ -108,14 +109,14 @@ class TestApplyUpdate: current = TTSSettings(voice="alice", language="en") delta = TTSSettings(voice="alice") changed = current.apply_update(delta) - assert changed == set() + assert changed == {} assert current.voice == "alice" def test_apply_update_not_given_skipped(self): current = TTSSettings(voice="alice", language="en") delta = TTSSettings() # all NOT_GIVEN changed = current.apply_update(delta) - assert changed == set() + assert changed == {} assert current.voice == "alice" assert current.language == "en" @@ -123,7 +124,9 @@ class TestApplyUpdate: current = LLMSettings(temperature=0.7, max_tokens=100) delta = LLMSettings(temperature=0.9, max_tokens=200, top_p=0.95) changed = current.apply_update(delta) - assert changed == {"temperature", "max_tokens", "top_p"} + assert changed.keys() == {"temperature", "max_tokens", "top_p"} + assert changed["temperature"] == 0.7 + assert changed["max_tokens"] == 100 assert current.temperature == 0.9 assert current.max_tokens == 200 assert current.top_p == 0.95 @@ -135,6 +138,7 @@ class TestApplyUpdate: delta.extra = {"speed": 1.2} changed = current.apply_update(delta) assert "speed" in changed + assert changed["speed"] == 1.0 # old value assert current.extra == {"speed": 1.2, "stability": 0.5} def test_apply_update_extra_no_change(self): @@ -143,13 +147,14 @@ class TestApplyUpdate: delta = TTSSettings() delta.extra = {"speed": 1.0} changed = current.apply_update(delta) - assert changed == set() + assert changed == {} def test_apply_update_model_field(self): current = ServiceSettings(model="old-model") delta = ServiceSettings(model="new-model") changed = current.apply_update(delta) - assert changed == {"model"} + assert changed.keys() == {"model"} + assert changed["model"] == "old-model" assert current.model == "new-model" def test_apply_update_none_is_a_valid_value(self): @@ -165,6 +170,7 @@ class TestApplyUpdate: delta = TTSSettings(language="en") changed = current.apply_update(delta) assert "language" in changed + assert changed["language"] is None # old value was None assert current.language == "en" @@ -293,7 +299,9 @@ class TestRoundtrip: delta = TTSSettings.from_mapping(raw) changed = current.apply_update(delta) - assert changed == {"voice", "speed"} + assert changed.keys() == {"voice", "speed"} + assert changed["voice"] == "alice" + assert changed["speed"] == 1.0 assert current.voice == "bob" assert current.language == "en" assert current.extra["speed"] == 1.2 @@ -303,6 +311,7 @@ class TestRoundtrip: current = LLMSettings(model="gpt-4o", temperature=0.7) delta = LLMSettings.from_mapping({"model": "gpt-4o-mini", "temperature": 0.9}) changed = current.apply_update(delta) - assert changed == {"model", "temperature"} + assert changed.keys() == {"model", "temperature"} + assert changed["model"] == "gpt-4o" assert current.model == "gpt-4o-mini" assert current.temperature == 0.9 From d2372c127add23aa9f19832fe65401fea7328e17 Mon Sep 17 00:00:00 2001 From: Paul Kompfner Date: Tue, 17 Feb 2026 11:56:37 -0500 Subject: [PATCH 0503/1060] Add specific type annotations to `ServiceSettings` fields, replacing `Any` with `str`, `float`, `int` unions as appropriate. --- src/pipecat/services/settings.py | 18 +++++++++--------- 1 file changed, 9 insertions(+), 9 deletions(-) diff --git a/src/pipecat/services/settings.py b/src/pipecat/services/settings.py index eae120842..54a25124b 100644 --- a/src/pipecat/services/settings.py +++ b/src/pipecat/services/settings.py @@ -104,7 +104,7 @@ class ServiceSettings: # -- common fields ------------------------------------------------------- - model: Any = field(default_factory=lambda: NOT_GIVEN) + model: str | _NotGiven = field(default_factory=lambda: NOT_GIVEN) """AI model identifier (e.g. ``"gpt-4o"``, ``"eleven_turbo_v2_5"``).""" extra: Dict[str, Any] = field(default_factory=dict) @@ -274,13 +274,13 @@ class LLMSettings(ServiceSettings): and prompts for incomplete turns. """ - temperature: Any = field(default_factory=lambda: NOT_GIVEN) - max_tokens: Any = field(default_factory=lambda: NOT_GIVEN) - top_p: Any = field(default_factory=lambda: NOT_GIVEN) - top_k: Any = field(default_factory=lambda: NOT_GIVEN) - frequency_penalty: Any = field(default_factory=lambda: NOT_GIVEN) - presence_penalty: Any = field(default_factory=lambda: NOT_GIVEN) - seed: Any = field(default_factory=lambda: NOT_GIVEN) + temperature: float | _NotGiven = field(default_factory=lambda: NOT_GIVEN) + max_tokens: int | _NotGiven = field(default_factory=lambda: NOT_GIVEN) + top_p: float | _NotGiven = field(default_factory=lambda: NOT_GIVEN) + top_k: int | _NotGiven = field(default_factory=lambda: NOT_GIVEN) + frequency_penalty: float | _NotGiven = field(default_factory=lambda: NOT_GIVEN) + presence_penalty: float | _NotGiven = field(default_factory=lambda: NOT_GIVEN) + seed: int | _NotGiven = field(default_factory=lambda: NOT_GIVEN) filter_incomplete_user_turns: bool | _NotGiven = field(default_factory=lambda: NOT_GIVEN) user_turn_completion_config: UserTurnCompletionConfig | _NotGiven = field( default_factory=lambda: NOT_GIVEN @@ -297,7 +297,7 @@ class TTSSettings(ServiceSettings): language: Language for speech synthesis. """ - voice: Any = field(default_factory=lambda: NOT_GIVEN) + voice: str | _NotGiven = field(default_factory=lambda: NOT_GIVEN) language: Any = field(default_factory=lambda: NOT_GIVEN) _aliases: ClassVar[Dict[str, str]] = {"voice_id": "voice"} From 247f0bbcd33c995ad3b7da70780b0617c09f1e18 Mon Sep 17 00:00:00 2001 From: Luke Payyapilli Date: Tue, 17 Feb 2026 13:04:10 -0500 Subject: [PATCH 0504/1060] Fix async generator cleanup to prevent uvloop crash on Python 3.12+ --- changelog/3698.fixed.md | 1 + src/pipecat/services/openai/base_llm.py | 25 ++++++--- tests/test_openai_llm_timeout.py | 74 +++++++++++++++++++++++++ 3 files changed, 92 insertions(+), 8 deletions(-) create mode 100644 changelog/3698.fixed.md diff --git a/changelog/3698.fixed.md b/changelog/3698.fixed.md new file mode 100644 index 000000000..c040e9efb --- /dev/null +++ b/changelog/3698.fixed.md @@ -0,0 +1 @@ +- Fixed async generator cleanup in OpenAI LLM streaming to prevent `AttributeError` with uvloop on Python 3.12+ (MagicStack/uvloop#699). diff --git a/src/pipecat/services/openai/base_llm.py b/src/pipecat/services/openai/base_llm.py index 2cdde51ea..ebe9eda91 100644 --- a/src/pipecat/services/openai/base_llm.py +++ b/src/pipecat/services/openai/base_llm.py @@ -375,20 +375,29 @@ class BaseOpenAILLMService(LLMService): else self._stream_chat_completions_universal_context(context) ) - # Ensure stream is closed on cancellation/exception to prevent socket - # leaks. OpenAI's AsyncStream uses close(), async generators use aclose(). + # Ensure stream and its async iterator are closed on cancellation/exception + # to prevent socket leaks and uvloop crashes. Closing the iterator first + # cascades cleanup through nested async generators (httpx/httpcore internals), + # preventing uvloop's broken asyncgen finalizer from firing on Python 3.12+ + # (MagicStack/uvloop#699). @asynccontextmanager async def _closing(stream): + chunk_iter = stream.__aiter__() try: - yield stream + yield chunk_iter finally: - if hasattr(stream, "aclose"): - await stream.aclose() - elif hasattr(stream, "close"): + # Close the iterator first to cascade cleanup through + # nested async generators (httpx/httpcore internals). + if hasattr(chunk_iter, "aclose"): + await chunk_iter.aclose() + # Then close the stream to release HTTP resources. + if hasattr(stream, "close"): await stream.close() + elif hasattr(stream, "aclose"): + await stream.aclose() - async with _closing(chunk_stream): - async for chunk in chunk_stream: + async with _closing(chunk_stream) as chunk_iter: + async for chunk in chunk_iter: if chunk.usage: cached_tokens = ( chunk.usage.prompt_tokens_details.cached_tokens diff --git a/tests/test_openai_llm_timeout.py b/tests/test_openai_llm_timeout.py index f7876f02f..8ee776a9b 100644 --- a/tests/test_openai_llm_timeout.py +++ b/tests/test_openai_llm_timeout.py @@ -223,3 +223,77 @@ async def test_openai_llm_emits_error_frame_on_exception(): assert "Error during completion" in pushed_errors[0]["error_msg"] assert "API Error" in pushed_errors[0]["error_msg"] assert isinstance(pushed_errors[0]["exception"], RuntimeError) + + +@pytest.mark.asyncio +async def test_openai_llm_async_iterator_closed_on_stream_end(): + """Test that the async iterator is explicitly closed after stream consumption. + + This prevents uvloop's broken asyncgen finalizer from firing on Python 3.12+ + when async generators are garbage-collected without explicit cleanup. + See MagicStack/uvloop#699. + """ + with patch.object(OpenAILLMService, "create_client"): + service = OpenAILLMService(model="gpt-4") + service._client = AsyncMock() + + # Track if the iterator's aclose was called + iterator_aclosed = False + stream_closed = False + + class MockAsyncIterator: + """Mock async iterator that tracks aclose() calls.""" + + def __init__(self): + self.iteration_count = 0 + + def __aiter__(self): + return self + + async def __anext__(self): + self.iteration_count += 1 + if self.iteration_count > 2: + raise StopAsyncIteration() + # Return a minimal chunk + mock_chunk = AsyncMock() + mock_chunk.usage = None + mock_chunk.model = None + mock_chunk.choices = [] + return mock_chunk + + async def aclose(self): + nonlocal iterator_aclosed + iterator_aclosed = True + + class MockAsyncStream: + """Mock stream whose __aiter__ returns a separate iterator object.""" + + def __init__(self, iterator): + self._iterator = iterator + + def __aiter__(self): + return self._iterator + + async def close(self): + nonlocal stream_closed + stream_closed = True + + mock_iterator = MockAsyncIterator() + mock_stream = MockAsyncStream(mock_iterator) + + service._stream_chat_completions_specific_context = AsyncMock(return_value=mock_stream) + service._stream_chat_completions_universal_context = AsyncMock(return_value=mock_stream) + service.start_ttfb_metrics = AsyncMock() + service.stop_ttfb_metrics = AsyncMock() + service.start_llm_usage_metrics = AsyncMock() + + context = LLMContext( + messages=[{"role": "user", "content": "Hello"}], + ) + + await service._process_context(context) + + # Verify the iterator was explicitly closed (prevents uvloop crash) + assert iterator_aclosed, "Async iterator should be explicitly closed" + # Verify the stream was also closed (releases HTTP resources) + assert stream_closed, "Stream should be closed to release HTTP resources" From 7dc16b1d9210c9be2c464d47182b6840766de21a Mon Sep 17 00:00:00 2001 From: Paul Kompfner Date: Tue, 17 Feb 2026 14:49:26 -0500 Subject: [PATCH 0505/1060] Type `language` fields and centralize conversion in STT services. MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit Change `TTSSettings.language` and `STTSettings.language` from `Any` to `Language | str | _NotGiven`. Add `language_to_service_language` base method and centralized `isinstance`-guarded conversion in `STTService._update_settings` (mirroring TTS). Update the TTS guard from `is not None` to `isinstance(…, Language)` so raw strings pass through unchanged. Remove now-redundant per-service language conversion from `_update_settings` overrides (ElevenLabs, Azure, Fal, Whisper). Add `language_to_service_language` to Azure STT so the centralized conversion picks it up. Fix AWS and NVIDIA STT `__init__` to convert language at construction time, then simplify their runtime accessors to read `_settings.language` directly. --- src/pipecat/services/aws/stt.py | 6 +++--- src/pipecat/services/azure/stt.py | 18 +++++++++++------- src/pipecat/services/elevenlabs/stt.py | 14 +------------- src/pipecat/services/fal/stt.py | 9 +-------- src/pipecat/services/nvidia/stt.py | 7 ++++--- src/pipecat/services/settings.py | 14 ++++++++++---- src/pipecat/services/stt_service.py | 24 +++++++++++++++++++++--- src/pipecat/services/tts_service.py | 2 +- src/pipecat/services/whisper/base_stt.py | 2 +- src/pipecat/services/whisper/stt.py | 6 ++---- 10 files changed, 55 insertions(+), 47 deletions(-) diff --git a/src/pipecat/services/aws/stt.py b/src/pipecat/services/aws/stt.py index ae502e8be..21220e646 100644 --- a/src/pipecat/services/aws/stt.py +++ b/src/pipecat/services/aws/stt.py @@ -102,7 +102,7 @@ class AWSTranscribeSTTService(WebsocketSTTService): super().__init__(ttfs_p99_latency=ttfs_p99_latency, **kwargs) self._settings = AWSTranscribeSTTSettings( - language=language, + language=self.language_to_service_language(language) or "en-US", sample_rate=sample_rate, media_encoding="linear16", number_of_channels=1, @@ -251,9 +251,9 @@ class AWSTranscribeSTTService(WebsocketSTTService): logger.debug("Connecting to AWS Transcribe WebSocket") - language_code = self.language_to_service_language(Language(self._settings.language)) + language_code = self._settings.language if not language_code: - raise ValueError(f"Unsupported language: {self._settings.language}") + raise ValueError(f"Unsupported language: {language_code}") # Generate random websocket key websocket_key = "".join( diff --git a/src/pipecat/services/azure/stt.py b/src/pipecat/services/azure/stt.py index 8a5b09e26..7f9d3f1ba 100644 --- a/src/pipecat/services/azure/stt.py +++ b/src/pipecat/services/azure/stt.py @@ -123,6 +123,17 @@ class AzureSTTService(STTService): """ return True + def language_to_service_language(self, language: Language) -> Optional[str]: + """Convert a Language enum to Azure service-specific language code. + + Args: + language: The language to convert. + + Returns: + The Azure-specific language identifier, or None if not supported. + """ + return language_to_azure_language(language) + async def _update_settings(self, update: STTSettings) -> dict[str, Any]: """Apply a settings update. @@ -130,13 +141,6 @@ class AzureSTTService(STTService): """ changed = await super()._update_settings(update) - if "language" in changed: - # Convert Language enum to Azure language code for consistency. - lang = self._settings.language - if isinstance(lang, Language): - lang = language_to_azure_language(lang) - self._settings.language = lang - # TODO: someday we could reconnect here to apply updated settings. # Code might look something like the below: # if "language" in changed: diff --git a/src/pipecat/services/elevenlabs/stt.py b/src/pipecat/services/elevenlabs/stt.py index fd938c12e..0ef137006 100644 --- a/src/pipecat/services/elevenlabs/stt.py +++ b/src/pipecat/services/elevenlabs/stt.py @@ -34,7 +34,7 @@ from pipecat.frames.frames import ( VADUserStoppedSpeakingFrame, ) from pipecat.processors.frame_processor import FrameDirection -from pipecat.services.settings import NOT_GIVEN, STTSettings, is_given +from pipecat.services.settings import NOT_GIVEN, STTSettings from pipecat.services.stt_latency import ELEVENLABS_REALTIME_TTFS_P99, ELEVENLABS_TTFS_P99 from pipecat.services.stt_service import SegmentedSTTService, WebsocketSTTService from pipecat.transcriptions.language import Language, resolve_language @@ -306,12 +306,6 @@ class ElevenLabsSTTService(SegmentedSTTService): Returns: Dict mapping changed field names to their previous values. """ - # Convert language to ElevenLabs format before applying - if is_given(update.language) and isinstance(update.language, Language): - converted = self.language_to_service_language(update.language) - if converted is not None: - update.language = converted - changed = await super()._update_settings(update) if "model" in changed: @@ -555,12 +549,6 @@ class ElevenLabsRealtimeSTTService(WebsocketSTTService): Returns: Dict mapping changed field names to their previous values. """ - # Convert language to ElevenLabs format before applying - if is_given(update.language) and isinstance(update.language, Language): - converted = language_to_elevenlabs_language(update.language) - if converted is not None: - update.language = converted - changed = await super()._update_settings(update) if not changed: diff --git a/src/pipecat/services/fal/stt.py b/src/pipecat/services/fal/stt.py index 28b611865..a29d8d70d 100644 --- a/src/pipecat/services/fal/stt.py +++ b/src/pipecat/services/fal/stt.py @@ -252,15 +252,8 @@ class FalSTTService(SegmentedSTTService): return language_to_fal_language(language) async def _update_settings(self, update: STTSettings) -> dict[str, Any]: - """Apply a settings update, converting language if changed.""" + """Apply a settings update.""" changed = await super()._update_settings(update) - - if "language" in changed: - # Convert the Language enum to a Fal language code. - lang = self._settings.language - if isinstance(lang, Language): - self._settings.language = self.language_to_service_language(lang) - return changed @traced_stt diff --git a/src/pipecat/services/nvidia/stt.py b/src/pipecat/services/nvidia/stt.py index b0d11fc2b..8e1babec7 100644 --- a/src/pipecat/services/nvidia/stt.py +++ b/src/pipecat/services/nvidia/stt.py @@ -488,7 +488,8 @@ class NvidiaSegmentedSTTService(SegmentedSTTService): self._config = None self._asr_service = None self._settings = NvidiaSegmentedSTTSettings( - language=params.language or Language.EN_US, + language=self.language_to_service_language(params.language or Language.EN_US) + or "en-US", profanity_filter=params.profanity_filter, automatic_punctuation=params.automatic_punctuation, verbatim_transcripts=params.verbatim_transcripts, @@ -523,8 +524,8 @@ class NvidiaSegmentedSTTService(SegmentedSTTService): self._asr_service = riva.client.ASRService(auth) def _get_language_code(self) -> str: - """Resolve the current language enum to an NVIDIA Riva language code string.""" - return self.language_to_service_language(self._settings.language) or "en-US" + """Get the current NVIDIA Riva language code string.""" + return self._settings.language or "en-US" def _create_recognition_config(self): """Create the NVIDIA Riva ASR recognition configuration.""" diff --git a/src/pipecat/services/settings.py b/src/pipecat/services/settings.py index 54a25124b..fdc1c15e6 100644 --- a/src/pipecat/services/settings.py +++ b/src/pipecat/services/settings.py @@ -34,6 +34,8 @@ from typing import TYPE_CHECKING, Any, ClassVar, Dict, Mapping, Optional, Type, from loguru import logger +from pipecat.transcriptions.language import Language + if TYPE_CHECKING: from pipecat.turns.user_turn_completion_mixin import UserTurnCompletionConfig @@ -294,11 +296,13 @@ class TTSSettings(ServiceSettings): Parameters: model: TTS model identifier. voice: Voice identifier or name. - language: Language for speech synthesis. + language: Language for speech synthesis. Accepts a ``Language`` enum + (converted to a service-specific string) or a raw string (stored + as-is). """ voice: str | _NotGiven = field(default_factory=lambda: NOT_GIVEN) - language: Any = field(default_factory=lambda: NOT_GIVEN) + language: Language | str | _NotGiven = field(default_factory=lambda: NOT_GIVEN) _aliases: ClassVar[Dict[str, str]] = {"voice_id": "voice"} @@ -309,7 +313,9 @@ class STTSettings(ServiceSettings): Parameters: model: STT model identifier. - language: Language for speech recognition. + language: Language for speech recognition. Accepts a ``Language`` enum + (converted to a service-specific string) or a raw string (stored + as-is). """ - language: Any = field(default_factory=lambda: NOT_GIVEN) + language: Language | str | _NotGiven = field(default_factory=lambda: NOT_GIVEN) diff --git a/src/pipecat/services/stt_service.py b/src/pipecat/services/stt_service.py index d6dd31824..ae04ed33f 100644 --- a/src/pipecat/services/stt_service.py +++ b/src/pipecat/services/stt_service.py @@ -35,7 +35,7 @@ from pipecat.frames.frames import ( from pipecat.metrics.metrics import TTFBMetricsData from pipecat.processors.frame_processor import FrameDirection from pipecat.services.ai_service import AIService -from pipecat.services.settings import STTSettings +from pipecat.services.settings import STTSettings, is_given from pipecat.services.stt_latency import DEFAULT_TTFS_P99 from pipecat.services.websocket_service import WebsocketService from pipecat.transcriptions.language import Language @@ -206,6 +206,17 @@ class STTService(AIService): settings_cls = type(self._settings) await self._update_settings(settings_cls(language=language)) + def language_to_service_language(self, language: Language) -> Optional[str]: + """Convert a language to the service-specific language format. + + Args: + language: The language to convert. + + Returns: + The service-specific language identifier, or None if not supported. + """ + return Language(language) + @abstractmethod async def run_stt(self, audio: bytes) -> AsyncGenerator[Frame, None]: """Run speech-to-text on the provided audio data. @@ -239,8 +250,9 @@ class STTService(AIService): async def _update_settings(self, update: STTSettings) -> dict[str, Any]: """Apply an STT settings update. - Handles ``model`` (via parent). Does **not** call ``set_language`` - — concrete services should override this method and handle language + Handles ``model`` (via parent). Translates ``Language`` enum values + before applying so the stored value is a service-specific string. + Concrete services should override this method and handle language changes (including any reconnect logic) based on the returned changed-field dict. @@ -250,6 +262,12 @@ class STTService(AIService): Returns: Dict mapping changed field names to their previous values. """ + # Translate language *before* applying so the stored value is canonical + if is_given(update.language) and isinstance(update.language, Language): + converted = self.language_to_service_language(update.language) + if converted is not None: + update.language = converted + changed = await super()._update_settings(update) return changed diff --git a/src/pipecat/services/tts_service.py b/src/pipecat/services/tts_service.py index bb5cff69f..4b4b47a50 100644 --- a/src/pipecat/services/tts_service.py +++ b/src/pipecat/services/tts_service.py @@ -448,7 +448,7 @@ class TTSService(AIService): Dict mapping changed field names to their previous values. """ # Translate language *before* applying so the stored value is canonical - if is_given(update.language) and update.language is not None: + if is_given(update.language) and isinstance(update.language, Language): converted = self.language_to_service_language(update.language) if converted is not None: update.language = converted diff --git a/src/pipecat/services/whisper/base_stt.py b/src/pipecat/services/whisper/base_stt.py index a67ad1cbc..d50c24eb2 100644 --- a/src/pipecat/services/whisper/base_stt.py +++ b/src/pipecat/services/whisper/base_stt.py @@ -183,7 +183,7 @@ class BaseWhisperSTTService(SegmentedSTTService): changed = await super()._update_settings(update) if "language" in changed: - self._language = self.language_to_service_language(Language(self._settings.language)) + self._language = self._settings.language if "prompt" in changed: self._prompt = self._settings.prompt if "temperature" in changed: diff --git a/src/pipecat/services/whisper/stt.py b/src/pipecat/services/whisper/stt.py index a96c26992..d4efcb166 100644 --- a/src/pipecat/services/whisper/stt.py +++ b/src/pipecat/services/whisper/stt.py @@ -319,9 +319,8 @@ class WhisperSTTService(SegmentedSTTService): # Divide by 32768 because we have signed 16-bit data. audio_float = np.frombuffer(audio, dtype=np.int16).astype(np.float32) / 32768.0 - whisper_lang = self.language_to_service_language(self._settings.language) segments, _ = await asyncio.to_thread( - self._model.transcribe, audio_float, language=whisper_lang + self._model.transcribe, audio_float, language=self._settings.language ) text: str = "" for segment in segments: @@ -419,13 +418,12 @@ class WhisperSTTServiceMLX(WhisperSTTService): # Divide by 32768 because we have signed 16-bit data. audio_float = np.frombuffer(audio, dtype=np.int16).astype(np.float32) / 32768.0 - whisper_lang = self.language_to_service_language(self._settings.language) chunk = await asyncio.to_thread( mlx_whisper.transcribe, audio_float, path_or_hf_repo=self.model_name, temperature=self._temperature, - language=whisper_lang, + language=self._settings.language, ) text: str = "" for segment in chunk.get("segments", []): From 1cec8d119dd16343e0f7294e2727ebd6045cc7b6 Mon Sep 17 00:00:00 2001 From: Paul Kompfner Date: Tue, 17 Feb 2026 14:57:38 -0500 Subject: [PATCH 0506/1060] Expand `language` field docstrings to clarify storage invariant. The union type reflects the input side; after construction and `_update_settings`, the stored value is always a service-specific string. --- src/pipecat/services/settings.py | 22 ++++++++++++++++------ 1 file changed, 16 insertions(+), 6 deletions(-) diff --git a/src/pipecat/services/settings.py b/src/pipecat/services/settings.py index fdc1c15e6..056621845 100644 --- a/src/pipecat/services/settings.py +++ b/src/pipecat/services/settings.py @@ -296,9 +296,14 @@ class TTSSettings(ServiceSettings): Parameters: model: TTS model identifier. voice: Voice identifier or name. - language: Language for speech synthesis. Accepts a ``Language`` enum - (converted to a service-specific string) or a raw string (stored - as-is). + language: Language for speech synthesis. The union type reflects the + *input* side: callers may pass a ``Language`` enum or a raw string. + However, the **stored** value is always a service-specific string + — ``TTSService._update_settings`` converts ``Language`` enums via + ``language_to_service_language()`` before writing, and ``__init__`` + methods do the same at construction time. Code that reads + ``self._settings.language`` after initialisation can treat it as + ``str``. """ voice: str | _NotGiven = field(default_factory=lambda: NOT_GIVEN) @@ -313,9 +318,14 @@ class STTSettings(ServiceSettings): Parameters: model: STT model identifier. - language: Language for speech recognition. Accepts a ``Language`` enum - (converted to a service-specific string) or a raw string (stored - as-is). + language: Language for speech recognition. The union type reflects the + *input* side: callers may pass a ``Language`` enum or a raw string. + However, the **stored** value is always a service-specific string + — ``STTService._update_settings`` converts ``Language`` enums via + ``language_to_service_language()`` before writing, and ``__init__`` + methods do the same at construction time. Code that reads + ``self._settings.language`` after initialisation can treat it as + ``str``. """ language: Language | str | _NotGiven = field(default_factory=lambda: NOT_GIVEN) From 1cad4210ce0094258db0da783aa2bc4d41f69e98 Mon Sep 17 00:00:00 2001 From: Paul Kompfner Date: Tue, 17 Feb 2026 15:07:45 -0500 Subject: [PATCH 0507/1060] Deprecate dict-based `*UpdateSettingsFrame(settings={...})` code path in STT, TTS, and LLM services. The dataclass-based API (`*UpdateSettingsFrame(update=*Settings(...))`) is the preferred path since 0.0.103. The dict path still works but now emits a `DeprecationWarning`. --- src/pipecat/frames/frames.py | 6 +++++- src/pipecat/services/llm_service.py | 8 ++++++++ src/pipecat/services/stt_service.py | 8 ++++++++ src/pipecat/services/tts_service.py | 8 ++++++++ 4 files changed, 29 insertions(+), 1 deletion(-) diff --git a/src/pipecat/frames/frames.py b/src/pipecat/frames/frames.py index be3b4e4a7..0e9127130 100644 --- a/src/pipecat/frames/frames.py +++ b/src/pipecat/frames/frames.py @@ -2117,7 +2117,11 @@ class ServiceUpdateSettingsFrame(ControlFrame): ``update`` object. When both are provided, ``update`` takes precedence. Parameters: - settings: Dictionary of setting name to value mappings (legacy). + settings: Dictionary of setting name to value mappings. + + .. deprecated:: 0.0.103 + Use ``update`` with a typed settings object instead. + update: :class:`~pipecat.services.settings.ServiceSettings` object describing the delta to apply. """ diff --git a/src/pipecat/services/llm_service.py b/src/pipecat/services/llm_service.py index 860a472c9..83d60defb 100644 --- a/src/pipecat/services/llm_service.py +++ b/src/pipecat/services/llm_service.py @@ -354,6 +354,14 @@ class LLMService(UserTurnCompletionLLMServiceMixin, AIService): await self._update_settings(frame.update) elif frame.settings: # Backward-compatible path: convert legacy dict to settings object. + with warnings.catch_warnings(): + warnings.simplefilter("always") + warnings.warn( + "Passing a dict via LLMUpdateSettingsFrame(settings={...}) is deprecated " + "since 0.0.103, use LLMUpdateSettingsFrame(update=LLMSettings(...)) instead.", + DeprecationWarning, + stacklevel=2, + ) update = type(self._settings).from_mapping(frame.settings) await self._update_settings(update) elif isinstance(frame, LLMContextSummaryRequestFrame): diff --git a/src/pipecat/services/stt_service.py b/src/pipecat/services/stt_service.py index ae04ed33f..fdcefcbd5 100644 --- a/src/pipecat/services/stt_service.py +++ b/src/pipecat/services/stt_service.py @@ -336,6 +336,14 @@ class STTService(AIService): await self._update_settings(frame.update) elif frame.settings: # Backward-compatible path: convert legacy dict to settings object. + with warnings.catch_warnings(): + warnings.simplefilter("always") + warnings.warn( + "Passing a dict via STTUpdateSettingsFrame(settings={...}) is deprecated " + "since 0.0.103, use STTUpdateSettingsFrame(update=STTSettings(...)) instead.", + DeprecationWarning, + stacklevel=2, + ) update = type(self._settings).from_mapping(frame.settings) await self._update_settings(update) elif isinstance(frame, STTMuteFrame): diff --git a/src/pipecat/services/tts_service.py b/src/pipecat/services/tts_service.py index 4b4b47a50..996a780ed 100644 --- a/src/pipecat/services/tts_service.py +++ b/src/pipecat/services/tts_service.py @@ -546,6 +546,14 @@ class TTSService(AIService): await self._update_settings(frame.update) elif frame.settings: # Backward-compatible path: convert legacy dict to settings object. + with warnings.catch_warnings(): + warnings.simplefilter("always") + warnings.warn( + "Passing a dict via TTSUpdateSettingsFrame(settings={...}) is deprecated " + "since 0.0.103, use TTSUpdateSettingsFrame(update=TTSSettings(...)) instead.", + DeprecationWarning, + stacklevel=2, + ) update = type(self._settings).from_mapping(frame.settings) await self._update_settings(update) elif isinstance(frame, BotStoppedSpeakingFrame): From 94a651cee2e375676a95d5097bb26ae1e2a877de Mon Sep 17 00:00:00 2001 From: Paul Kompfner Date: Tue, 17 Feb 2026 15:15:18 -0500 Subject: [PATCH 0508/1060] Remove dead `ServiceSettings.to_dict` method --- src/pipecat/services/settings.py | 12 ------------ tests/test_settings.py | 4 ---- 2 files changed, 16 deletions(-) diff --git a/src/pipecat/services/settings.py b/src/pipecat/services/settings.py index 056621845..0721cf3cd 100644 --- a/src/pipecat/services/settings.py +++ b/src/pipecat/services/settings.py @@ -228,18 +228,6 @@ class ServiceSettings: instance.extra = extra return instance - def to_dict(self) -> Dict[str, Any]: - """Serialize to a flat dictionary, including extra. - - Only given (non-``NOT_GIVEN``) values are included. This is the - inverse of ``from_mapping`` and useful for passing settings to APIs - that expect plain dicts. - - Returns: - A flat dictionary of all given settings. - """ - return self.given_fields() - def copy(self: _S) -> _S: """Return a deep copy of this settings instance. diff --git a/tests/test_settings.py b/tests/test_settings.py index 71d66fc35..85f89987c 100644 --- a/tests/test_settings.py +++ b/tests/test_settings.py @@ -75,10 +75,6 @@ class TestServiceSettings: result = s.given_fields() assert result == {"model": "gpt-4o", "custom_key": 42} - def test_to_dict(self): - s = ServiceSettings(model="gpt-4o") - assert s.to_dict() == {"model": "gpt-4o"} - def test_copy_is_deep(self): s = ServiceSettings(model="gpt-4o") s.extra = {"nested": {"a": 1}} From 5ea2d47d3998c9e5d85c21f3e525e36b3d7f7516 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Radek=20Sedl=C3=A1k?= Date: Tue, 17 Feb 2026 21:36:19 +0100 Subject: [PATCH 0509/1060] feat: Add support for private endpoint in Azure STT --- changelog/3764.added.md | 1 + src/pipecat/services/azure/stt.py | 4 ++++ 2 files changed, 5 insertions(+) create mode 100644 changelog/3764.added.md diff --git a/changelog/3764.added.md b/changelog/3764.added.md new file mode 100644 index 000000000..5da82f0c1 --- /dev/null +++ b/changelog/3764.added.md @@ -0,0 +1 @@ +- Added support for specifying private endpoints for Azure Speech-to-Text, enabling use in private networks behind firewalls. \ No newline at end of file diff --git a/src/pipecat/services/azure/stt.py b/src/pipecat/services/azure/stt.py index 1bc7ec70a..cc4fcb7ae 100644 --- a/src/pipecat/services/azure/stt.py +++ b/src/pipecat/services/azure/stt.py @@ -63,6 +63,7 @@ class AzureSTTService(STTService): region: str, language: Language = Language.EN_US, sample_rate: Optional[int] = None, + private_endpoint: Optional[str] = None, endpoint_id: Optional[str] = None, ttfs_p99_latency: Optional[float] = AZURE_TTFS_P99, **kwargs, @@ -74,6 +75,8 @@ class AzureSTTService(STTService): region: Azure region for the Speech service (e.g., 'eastus'). language: Language for speech recognition. Defaults to English (US). sample_rate: Audio sample rate in Hz. If None, uses service default. + private_endpoint: Private endpoint for STT behind firewall. + See https://docs.azure.cn/en-us/ai-services/speech-service/speech-services-private-link?tabs=portal endpoint_id: Custom model endpoint id. ttfs_p99_latency: P99 latency from speech end to final transcript in seconds. Override for your deployment. See https://github.com/pipecat-ai/stt-benchmark @@ -85,6 +88,7 @@ class AzureSTTService(STTService): subscription=api_key, region=region, speech_recognition_language=language_to_azure_language(language), + endpoint=private_endpoint, ) if endpoint_id: From 68ebd3d063eb0f0fbc39b8b70f33028a88410b7f Mon Sep 17 00:00:00 2001 From: Paul Kompfner Date: Tue, 17 Feb 2026 15:44:41 -0500 Subject: [PATCH 0510/1060] Migrate HumeTTSService to standard `TTSSettings` pattern and remove dead `TTSService.update_setting` HumeTTSService now stores its params (description, speed, trailing_silence) in a proper `HumeTTSSettings` dataclass instead of a separate `_params` Pydantic model, making it work with `TTSUpdateSettingsFrame(update=...)`. The old `update_setting(key, value)` method is kept but deprecated. Also removes the unused no-op `TTSService.update_setting` base method, which was never called by the `TTSUpdateSettingsFrame` pipeline. --- src/pipecat/services/hume/tts.py | 83 +++++++++++++++++++++-------- src/pipecat/services/tts_service.py | 9 ---- 2 files changed, 60 insertions(+), 32 deletions(-) diff --git a/src/pipecat/services/hume/tts.py b/src/pipecat/services/hume/tts.py index 3b45cc249..27c4b417e 100644 --- a/src/pipecat/services/hume/tts.py +++ b/src/pipecat/services/hume/tts.py @@ -6,6 +6,8 @@ import base64 import os +import warnings +from dataclasses import dataclass, field from typing import Any, AsyncGenerator, Optional import httpx @@ -24,6 +26,7 @@ from pipecat.frames.frames import ( TTSStoppedFrame, ) from pipecat.processors.frame_processor import FrameDirection +from pipecat.services.settings import NOT_GIVEN, TTSSettings, _NotGiven from pipecat.services.tts_service import WordTTSService from pipecat.utils.tracing.service_decorators import traced_tts @@ -46,6 +49,21 @@ DEFAULT_HEADERS = { } +@dataclass +class HumeTTSSettings(TTSSettings): + """Settings for Hume TTS service. + + Parameters: + description: Natural-language acting directions (up to 100 characters). + speed: Speaking-rate multiplier (0.5-2.0). + trailing_silence: Seconds of silence to append at the end (0-5). + """ + + description: str | None | _NotGiven = field(default_factory=lambda: NOT_GIVEN) + speed: float | None | _NotGiven = field(default_factory=lambda: NOT_GIVEN) + trailing_silence: float | None | _NotGiven = field(default_factory=lambda: NOT_GIVEN) + + class HumeTTSService(WordTTSService): """Hume Octave Text-to-Speech service. @@ -61,6 +79,8 @@ class HumeTTSService(WordTTSService): - Provides metrics for Time To First Byte (TTFB) and TTS usage. """ + _settings: HumeTTSSettings + class InputParams(BaseModel): """Optional synthesis parameters for Hume TTS. @@ -114,9 +134,14 @@ class HumeTTSService(WordTTSService): self._http_client = httpx.AsyncClient(headers=DEFAULT_HEADERS) self._client = AsyncHumeClient(api_key=api_key, httpx_client=self._http_client) - self._params = params or HumeTTSService.InputParams() - # Store voice in the base class (mirrors other services) + params = params or HumeTTSService.InputParams() + self._settings = HumeTTSSettings( + voice=voice_id, + description=params.description, + speed=params.speed, + trailing_silence=params.trailing_silence, + ) self._voice_id = voice_id self._audio_bytes = b"" @@ -183,7 +208,10 @@ class HumeTTSService(WordTTSService): await self.add_word_timestamps([("Reset", 0)]) async def update_setting(self, key: str, value: Any) -> None: - """Runtime updates via `TTSUpdateSettingsFrame`. + """Runtime updates via key/value pair. + + .. deprecated:: 0.0.103 + Use ``TTSUpdateSettingsFrame(update=HumeTTSSettings(...))`` instead. Args: key: The name of the setting to update. Recognized keys are: @@ -193,20 +221,29 @@ class HumeTTSService(WordTTSService): - "trailing_silence" value: The new value for the setting. """ - key_l = (key or "").lower() + with warnings.catch_warnings(): + warnings.simplefilter("always") + warnings.warn( + "'update_setting' is deprecated, use " + "'TTSUpdateSettingsFrame(update=HumeTTSSettings(...))' instead.", + DeprecationWarning, + stacklevel=2, + ) - if key_l == "voice_id": - await self.set_voice(str(value)) - logger.debug(f"HumeTTSService voice_id set to: {self.voice}") - elif key_l == "description": - self._params.description = None if value is None else str(value) - elif key_l == "speed": - self._params.speed = None if value is None else float(value) - elif key_l == "trailing_silence": - self._params.trailing_silence = None if value is None else float(value) - else: - # Defer unknown keys to the base class - await super().update_setting(key, value) + key_l = (key or "").lower() + known_keys = {"voice_id", "voice", "description", "speed", "trailing_silence"} + + if key_l in known_keys: + kwargs: dict[str, Any] = {} + if key_l in ("voice_id", "voice"): + kwargs["voice"] = str(value) + elif key_l == "description": + kwargs["description"] = None if value is None else str(value) + elif key_l == "speed": + kwargs["speed"] = None if value is None else float(value) + elif key_l == "trailing_silence": + kwargs["trailing_silence"] = None if value is None else float(value) + await self._update_settings(HumeTTSSettings(**kwargs)) @traced_tts async def run_tts(self, text: str, context_id: str) -> AsyncGenerator[Frame, None]: @@ -228,12 +265,12 @@ class HumeTTSService(WordTTSService): "text": text, "voice": PostedUtteranceVoiceWithId(id=self._voice_id), } - if self._params.description is not None: - utterance_kwargs["description"] = self._params.description - if self._params.speed is not None: - utterance_kwargs["speed"] = self._params.speed - if self._params.trailing_silence is not None: - utterance_kwargs["trailing_silence"] = self._params.trailing_silence + if self._settings.description is not None: + utterance_kwargs["description"] = self._settings.description + if self._settings.speed is not None: + utterance_kwargs["speed"] = self._settings.speed + if self._settings.trailing_silence is not None: + utterance_kwargs["trailing_silence"] = self._settings.trailing_silence utterance = PostedUtterance(**utterance_kwargs) @@ -257,7 +294,7 @@ class HumeTTSService(WordTTSService): # Use version "2" by default if no description is provided # Version "1" is needed when description is used - version = "1" if self._params.description is not None else "2" + version = "1" if self._settings.description is not None else "2" # Track the duration of this utterance based on the last timestamp utterance_duration = 0.0 diff --git a/src/pipecat/services/tts_service.py b/src/pipecat/services/tts_service.py index 996a780ed..6cd33b3e4 100644 --- a/src/pipecat/services/tts_service.py +++ b/src/pipecat/services/tts_service.py @@ -352,15 +352,6 @@ class TTSService(AIService): return text + " " return text - async def update_setting(self, key: str, value: Any): - """Update a service-specific setting. - - Args: - key: The setting key to update. - value: The new value for the setting. - """ - pass - async def flush_audio(self): """Flush any buffered audio data.""" pass From ce51df677c7a3aebfd5e0505f4633a9b41bf4bed Mon Sep 17 00:00:00 2001 From: Paul Kompfner Date: Tue, 17 Feb 2026 17:07:14 -0500 Subject: [PATCH 0511/1060] Add backward-compat `_aliases` and `from_mapping` overrides to TTS settings MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit The migration from plain-dict `self._settings` to typed dataclasses renamed keys and flattened nested dicts. The deprecated dict-based `TTSUpdateSettingsFrame(settings={...})` code path calls `from_mapping`, which silently dropped old keys into `extra`. - Add `_aliases` so renamed flat keys (e.g. `sample_rate` → `fish_sample_rate`, camelCase Inworld keys) resolve correctly. - Override `from_mapping` to destructure nested dicts (`output_format`, `prosody`, `audioConfig`, `voice_setting`, `audio_setting`) into their flat field equivalents. - Fix AsyncAI constructor bug passing `output_format={...}` dict instead of individual `output_container`/`output_encoding`/`output_sample_rate` fields. --- src/pipecat/services/asyncai/tts.py | 21 ++++++++++++----- src/pipecat/services/cartesia/tts.py | 13 ++++++++++- src/pipecat/services/fish/tts.py | 14 +++++++++++- src/pipecat/services/groq/tts.py | 4 +++- src/pipecat/services/inworld/tts.py | 21 ++++++++++++++++- src/pipecat/services/minimax/tts.py | 31 +++++++++++++++++++++++++- src/pipecat/services/resembleai/tts.py | 7 +++++- 7 files changed, 99 insertions(+), 12 deletions(-) diff --git a/src/pipecat/services/asyncai/tts.py b/src/pipecat/services/asyncai/tts.py index 05ba14113..489d7cbff 100644 --- a/src/pipecat/services/asyncai/tts.py +++ b/src/pipecat/services/asyncai/tts.py @@ -10,7 +10,7 @@ import asyncio import base64 import json from dataclasses import dataclass, field -from typing import AsyncGenerator, Optional +from typing import Any, AsyncGenerator, ClassVar, Dict, Mapping, Optional import aiohttp from loguru import logger @@ -88,6 +88,17 @@ class AsyncAITTSSettings(TTSSettings): output_encoding: str = field(default_factory=lambda: NOT_GIVEN) output_sample_rate: int = field(default_factory=lambda: NOT_GIVEN) + @classmethod + def from_mapping(cls, settings: Mapping[str, Any]) -> "AsyncAITTSSettings": + """Construct settings from a plain dict, destructuring legacy nested ``output_format``.""" + flat = dict(settings) + nested = flat.pop("output_format", None) + if isinstance(nested, dict): + flat.setdefault("output_container", nested.get("container")) + flat.setdefault("output_encoding", nested.get("encoding")) + flat.setdefault("output_sample_rate", nested.get("sample_rate")) + return super().from_mapping(flat) + class AsyncAITTSService(AudioContextTTSService): """Async TTS service with WebSocket streaming. @@ -153,11 +164,9 @@ class AsyncAITTSService(AudioContextTTSService): self._settings = AsyncAITTSSettings( model=model, voice=voice_id, - output_format={ - "container": container, - "encoding": encoding, - "sample_rate": 0, - }, + output_container=container, + output_encoding=encoding, + output_sample_rate=0, language=self.language_to_service_language(params.language) if params.language else None, diff --git a/src/pipecat/services/cartesia/tts.py b/src/pipecat/services/cartesia/tts.py index 2544d3b98..edee9e2ea 100644 --- a/src/pipecat/services/cartesia/tts.py +++ b/src/pipecat/services/cartesia/tts.py @@ -11,7 +11,7 @@ import json import warnings from dataclasses import dataclass, field from enum import Enum -from typing import Any, AsyncGenerator, List, Literal, Optional +from typing import Any, AsyncGenerator, ClassVar, Dict, List, Literal, Mapping, Optional from loguru import logger from pydantic import BaseModel, Field @@ -217,6 +217,17 @@ class CartesiaTTSSettings(TTSSettings): generation_config: GenerationConfig = field(default_factory=lambda: NOT_GIVEN) pronunciation_dict_id: str = field(default_factory=lambda: NOT_GIVEN) + @classmethod + def from_mapping(cls, settings: Mapping[str, Any]) -> "CartesiaTTSSettings": + """Construct settings from a plain dict, destructuring legacy nested ``output_format``.""" + flat = dict(settings) + nested = flat.pop("output_format", None) + if isinstance(nested, dict): + flat.setdefault("output_container", nested.get("container")) + flat.setdefault("output_encoding", nested.get("encoding")) + flat.setdefault("output_sample_rate", nested.get("sample_rate")) + return super().from_mapping(flat) + class CartesiaTTSService(AudioContextWordTTSService): """Cartesia TTS service with WebSocket streaming and word timestamps. diff --git a/src/pipecat/services/fish/tts.py b/src/pipecat/services/fish/tts.py index 4da4b6673..7dd06d705 100644 --- a/src/pipecat/services/fish/tts.py +++ b/src/pipecat/services/fish/tts.py @@ -12,7 +12,7 @@ for streaming text-to-speech synthesis with customizable voice parameters. import uuid from dataclasses import dataclass, field -from typing import Any, AsyncGenerator, Literal, Optional +from typing import Any, AsyncGenerator, ClassVar, Dict, Literal, Mapping, Optional from loguru import logger from pydantic import BaseModel @@ -69,6 +69,18 @@ class FishAudioTTSSettings(TTSSettings): prosody_volume: int = field(default_factory=lambda: NOT_GIVEN) reference_id: str = field(default_factory=lambda: NOT_GIVEN) + _aliases: ClassVar[Dict[str, str]] = {"voice_id": "voice", "sample_rate": "fish_sample_rate"} + + @classmethod + def from_mapping(cls, settings: Mapping[str, Any]) -> "FishAudioTTSSettings": + """Construct settings from a plain dict, destructuring legacy nested ``prosody``.""" + flat = dict(settings) + nested = flat.pop("prosody", None) + if isinstance(nested, dict): + flat.setdefault("prosody_speed", nested.get("speed")) + flat.setdefault("prosody_volume", nested.get("volume")) + return super().from_mapping(flat) + class FishAudioTTSService(InterruptibleTTSService): """Fish Audio text-to-speech service with WebSocket streaming. diff --git a/src/pipecat/services/groq/tts.py b/src/pipecat/services/groq/tts.py index d0b5fbd7c..e4c10f2e9 100644 --- a/src/pipecat/services/groq/tts.py +++ b/src/pipecat/services/groq/tts.py @@ -9,7 +9,7 @@ import io import wave from dataclasses import dataclass, field -from typing import AsyncGenerator, Optional +from typing import AsyncGenerator, ClassVar, Dict, Optional from loguru import logger from pydantic import BaseModel @@ -48,6 +48,8 @@ class GroqTTSSettings(TTSSettings): speed: float = field(default_factory=lambda: NOT_GIVEN) groq_sample_rate: int = field(default_factory=lambda: NOT_GIVEN) + _aliases: ClassVar[Dict[str, str]] = {"voice_id": "voice", "sample_rate": "groq_sample_rate"} + class GroqTTSService(TTSService): """Groq text-to-speech service implementation. diff --git a/src/pipecat/services/inworld/tts.py b/src/pipecat/services/inworld/tts.py index c291f3156..acc6187cb 100644 --- a/src/pipecat/services/inworld/tts.py +++ b/src/pipecat/services/inworld/tts.py @@ -17,7 +17,7 @@ import asyncio import base64 import json from dataclasses import dataclass, field -from typing import Any, AsyncGenerator, Dict, List, Optional, Tuple +from typing import Any, AsyncGenerator, ClassVar, Dict, List, Mapping, Optional, Tuple import aiohttp import websockets @@ -74,6 +74,25 @@ class InworldTTSSettings(TTSSettings): auto_mode: bool = field(default_factory=lambda: NOT_GIVEN) apply_text_normalization: str = field(default_factory=lambda: NOT_GIVEN) + _aliases: ClassVar[Dict[str, str]] = { + "voice_id": "voice", + "voiceId": "voice", + "modelId": "model", + "applyTextNormalization": "apply_text_normalization", + "autoMode": "auto_mode", + } + + @classmethod + def from_mapping(cls, settings: Mapping[str, Any]) -> "InworldTTSSettings": + """Construct settings from a plain dict, destructuring legacy nested ``audioConfig``.""" + flat = dict(settings) + nested = flat.pop("audioConfig", None) + if isinstance(nested, dict): + flat.setdefault("audio_encoding", nested.get("audioEncoding")) + flat.setdefault("audio_sample_rate", nested.get("sampleRateHertz")) + flat.setdefault("speaking_rate", nested.get("speakingRate")) + return super().from_mapping(flat) + class InworldHttpTTSService(WordTTSService): """Inworld AI HTTP-based TTS service. diff --git a/src/pipecat/services/minimax/tts.py b/src/pipecat/services/minimax/tts.py index ab04925f3..6a107d950 100644 --- a/src/pipecat/services/minimax/tts.py +++ b/src/pipecat/services/minimax/tts.py @@ -12,7 +12,7 @@ for streaming text-to-speech synthesis. import json from dataclasses import dataclass, field -from typing import AsyncGenerator, Optional +from typing import Any, AsyncGenerator, ClassVar, Dict, Mapping, Optional import aiohttp from loguru import logger @@ -120,6 +120,35 @@ class MiniMaxTTSSettings(TTSSettings): audio_sample_rate: int = field(default_factory=lambda: NOT_GIVEN) language_boost: str = field(default_factory=lambda: NOT_GIVEN) + _aliases: ClassVar[Dict[str, str]] = {"voice_id": "voice"} + + @classmethod + def from_mapping(cls, settings: Mapping[str, Any]) -> "MiniMaxTTSSettings": + """Construct settings from a plain dict, destructuring legacy nested dicts. + + Handles ``voice_setting`` (with ``vol`` → ``volume`` rename) and + ``audio_setting`` (with prefixed field mapping). + """ + flat = dict(settings) + + voice = flat.pop("voice_setting", None) + if isinstance(voice, dict): + flat.setdefault("speed", voice.get("speed")) + flat.setdefault("volume", voice.get("vol")) + flat.setdefault("pitch", voice.get("pitch")) + flat.setdefault("emotion", voice.get("emotion")) + flat.setdefault("text_normalization", voice.get("text_normalization")) + flat.setdefault("latex_read", voice.get("latex_read")) + + audio = flat.pop("audio_setting", None) + if isinstance(audio, dict): + flat.setdefault("audio_bitrate", audio.get("bitrate")) + flat.setdefault("audio_format", audio.get("format")) + flat.setdefault("audio_channel", audio.get("channel")) + flat.setdefault("audio_sample_rate", audio.get("sample_rate")) + + return super().from_mapping(flat) + class MiniMaxHttpTTSService(TTSService): """Text-to-speech service using MiniMax's T2A (Text-to-Audio) API. diff --git a/src/pipecat/services/resembleai/tts.py b/src/pipecat/services/resembleai/tts.py index 08df23abe..acba883e4 100644 --- a/src/pipecat/services/resembleai/tts.py +++ b/src/pipecat/services/resembleai/tts.py @@ -9,7 +9,7 @@ import base64 import json from dataclasses import dataclass, field -from typing import AsyncGenerator, Optional +from typing import AsyncGenerator, ClassVar, Dict, Optional from loguru import logger @@ -54,6 +54,11 @@ class ResembleAITTSSettings(TTSSettings): output_format: str = field(default_factory=lambda: NOT_GIVEN) resemble_sample_rate: int = field(default_factory=lambda: NOT_GIVEN) + _aliases: ClassVar[Dict[str, str]] = { + "voice_id": "voice", + "sample_rate": "resemble_sample_rate", + } + class ResembleAITTSService(AudioContextWordTTSService): """Resemble AI TTS service with WebSocket streaming and word timestamps. From 80062239116b0c3bf071f9e9c0474397a2324694 Mon Sep 17 00:00:00 2001 From: Ian Lee Date: Tue, 17 Feb 2026 15:07:39 -0800 Subject: [PATCH 0512/1060] [inworld] default timestamp transport strategy to ASYNC --- changelog/3765.changed.md | 1 + src/pipecat/services/inworld/tts.py | 4 ++-- 2 files changed, 3 insertions(+), 2 deletions(-) create mode 100644 changelog/3765.changed.md diff --git a/changelog/3765.changed.md b/changelog/3765.changed.md new file mode 100644 index 000000000..11c4866d5 --- /dev/null +++ b/changelog/3765.changed.md @@ -0,0 +1 @@ +- Update `InworldTTSService` and `InworldHttpTTSService` to use `ASYNC` timestamp transport strategy by default diff --git a/src/pipecat/services/inworld/tts.py b/src/pipecat/services/inworld/tts.py index 9f7c0cff1..9767c1b0a 100644 --- a/src/pipecat/services/inworld/tts.py +++ b/src/pipecat/services/inworld/tts.py @@ -70,7 +70,7 @@ class InworldHttpTTSService(WordTTSService): temperature: Optional[float] = None speaking_rate: Optional[float] = None - timestamp_transport_strategy: Optional[Literal["ASYNC", "SYNC"]] = None + timestamp_transport_strategy: Optional[Literal["ASYNC", "SYNC"]] = "ASYNC" def __init__( self, @@ -442,7 +442,7 @@ class InworldTTSService(AudioContextWordTTSService): max_buffer_delay_ms: Optional[int] = None buffer_char_threshold: Optional[int] = None auto_mode: Optional[bool] = True - timestamp_transport_strategy: Optional[Literal["ASYNC", "SYNC"]] = None + timestamp_transport_strategy: Optional[Literal["ASYNC", "SYNC"]] = "ASYNC" def __init__( self, From cd379671aa5a91d77afc5dbbb5a005fdb2b20623 Mon Sep 17 00:00:00 2001 From: Tanmay Chaudhari <7712083+tanmayc25@users.noreply.github.com> Date: Wed, 18 Feb 2026 14:18:16 +0530 Subject: [PATCH 0513/1060] fix: use audio.sample_rate instead of audio.audio_frames in TavusInputTransport --- src/pipecat/transports/tavus/transport.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/src/pipecat/transports/tavus/transport.py b/src/pipecat/transports/tavus/transport.py index c8a79d386..dd63cb790 100644 --- a/src/pipecat/transports/tavus/transport.py +++ b/src/pipecat/transports/tavus/transport.py @@ -519,7 +519,7 @@ class TavusInputTransport(BaseInputTransport): """Handle received participant audio data.""" frame = InputAudioRawFrame( audio=audio.audio_frames, - sample_rate=audio.audio_frames, + sample_rate=audio.sample_rate, num_channels=audio.num_channels, ) frame.transport_source = audio_source From 6066eec8532a97387e7e3d71b8f729daff5b84d9 Mon Sep 17 00:00:00 2001 From: Tanmay Chaudhari <7712083+tanmayc25@users.noreply.github.com> Date: Wed, 18 Feb 2026 14:31:16 +0530 Subject: [PATCH 0514/1060] Add changelog for PR #3768 --- changelog/3768.fixed.md | 1 + 1 file changed, 1 insertion(+) create mode 100644 changelog/3768.fixed.md diff --git a/changelog/3768.fixed.md b/changelog/3768.fixed.md new file mode 100644 index 000000000..4c8d6438e --- /dev/null +++ b/changelog/3768.fixed.md @@ -0,0 +1 @@ +- Fixed incorrect `sample_rate` assignment in `TavusInputTransport._on_participant_audio_data` (was using `audio.audio_frames` instead of `audio.sample_rate`). From d7d94a29f044be4065a35a0cc2cc119b1efe5687 Mon Sep 17 00:00:00 2001 From: Paul Kompfner Date: Wed, 18 Feb 2026 09:46:23 -0500 Subject: [PATCH 0515/1060] Add foundational examples (55) for runtime settings updates via `*UpdateSettingsFrame` 42 examples covering STT (13), TTS (21), LLM (4), and realtime (4) services. Each demonstrates updating service settings 10 seconds after client connects, verifying the typed settings machinery end-to-end for every provider. --- .../55a-update-settings-deepgram-stt.py | 131 +++++++++++++++++ .../55b-update-settings-azure-stt.py | 134 +++++++++++++++++ .../55c-update-settings-google-stt.py | 131 +++++++++++++++++ .../55d-update-settings-assemblyai-stt.py | 131 +++++++++++++++++ .../55e-update-settings-gladia-stt.py | 131 +++++++++++++++++ ...update-settings-elevenlabs-realtime-stt.py | 134 +++++++++++++++++ .../55g-update-settings-elevenlabs-stt.py | 136 +++++++++++++++++ .../55h-update-settings-speechmatics-stt.py | 131 +++++++++++++++++ .../55i-update-settings-whisper-api-stt.py | 137 ++++++++++++++++++ .../55j-update-settings-sarvam-stt.py | 131 +++++++++++++++++ .../55k-update-settings-soniox-stt.py | 131 +++++++++++++++++ .../55l-update-settings-aws-transcribe-stt.py | 131 +++++++++++++++++ .../55m-update-settings-cartesia-stt.py | 131 +++++++++++++++++ .../55n-update-settings-cartesia-tts.py | 131 +++++++++++++++++ .../55o-update-settings-elevenlabs-tts.py | 130 +++++++++++++++++ .../55p-update-settings-openai-tts.py | 126 ++++++++++++++++ .../55q-update-settings-deepgram-tts.py | 127 ++++++++++++++++ .../55r-update-settings-azure-tts.py | 130 +++++++++++++++++ .../55s-update-settings-google-http-tts.py | 127 ++++++++++++++++ .../55t-update-settings-playht-tts.py | 129 +++++++++++++++++ .../55u-update-settings-rime-tts.py | 128 ++++++++++++++++ .../55v-update-settings-lmnt-tts.py | 128 ++++++++++++++++ .../55w-update-settings-fish-tts.py | 127 ++++++++++++++++ .../55x-update-settings-minimax-tts.py | 133 +++++++++++++++++ .../55y-update-settings-groq-tts.py | 125 ++++++++++++++++ .../55z-update-settings-hume-tts.py | 134 +++++++++++++++++ .../55za-update-settings-neuphonic-tts.py | 125 ++++++++++++++++ .../55zb-update-settings-inworld-tts.py | 129 +++++++++++++++++ .../55zc-update-settings-gemini-tts.py | 129 +++++++++++++++++ .../55zd-update-settings-aws-polly-tts.py | 127 ++++++++++++++++ .../55ze-update-settings-sarvam-tts.py | 125 ++++++++++++++++ .../55zf-update-settings-camb-tts.py | 129 +++++++++++++++++ .../55zg-update-settings-hathora-tts.py | 128 ++++++++++++++++ .../55zh-update-settings-resembleai-tts.py | 132 +++++++++++++++++ .../55zi-update-settings-openai-llm.py | 131 +++++++++++++++++ .../55zj-update-settings-anthropic-llm.py | 130 +++++++++++++++++ .../55zk-update-settings-google-llm.py | 130 +++++++++++++++++ .../55zl-update-settings-openai-realtime.py | 118 +++++++++++++++ .../55zm-update-settings-gemini-live.py | 118 +++++++++++++++ .../55zn-update-settings-ultravox-realtime.py | 124 ++++++++++++++++ .../55zo-update-settings-grok-realtime.py | 118 +++++++++++++++ .../55zp-update-settings-aws-bedrock-llm.py | 130 +++++++++++++++++ 42 files changed, 5418 insertions(+) create mode 100644 examples/foundational/55a-update-settings-deepgram-stt.py create mode 100644 examples/foundational/55b-update-settings-azure-stt.py create mode 100644 examples/foundational/55c-update-settings-google-stt.py create mode 100644 examples/foundational/55d-update-settings-assemblyai-stt.py create mode 100644 examples/foundational/55e-update-settings-gladia-stt.py create mode 100644 examples/foundational/55f-update-settings-elevenlabs-realtime-stt.py create mode 100644 examples/foundational/55g-update-settings-elevenlabs-stt.py create mode 100644 examples/foundational/55h-update-settings-speechmatics-stt.py create mode 100644 examples/foundational/55i-update-settings-whisper-api-stt.py create mode 100644 examples/foundational/55j-update-settings-sarvam-stt.py create mode 100644 examples/foundational/55k-update-settings-soniox-stt.py create mode 100644 examples/foundational/55l-update-settings-aws-transcribe-stt.py create mode 100644 examples/foundational/55m-update-settings-cartesia-stt.py create mode 100644 examples/foundational/55n-update-settings-cartesia-tts.py create mode 100644 examples/foundational/55o-update-settings-elevenlabs-tts.py create mode 100644 examples/foundational/55p-update-settings-openai-tts.py create mode 100644 examples/foundational/55q-update-settings-deepgram-tts.py create mode 100644 examples/foundational/55r-update-settings-azure-tts.py create mode 100644 examples/foundational/55s-update-settings-google-http-tts.py create mode 100644 examples/foundational/55t-update-settings-playht-tts.py create mode 100644 examples/foundational/55u-update-settings-rime-tts.py create mode 100644 examples/foundational/55v-update-settings-lmnt-tts.py create mode 100644 examples/foundational/55w-update-settings-fish-tts.py create mode 100644 examples/foundational/55x-update-settings-minimax-tts.py create mode 100644 examples/foundational/55y-update-settings-groq-tts.py create mode 100644 examples/foundational/55z-update-settings-hume-tts.py create mode 100644 examples/foundational/55za-update-settings-neuphonic-tts.py create mode 100644 examples/foundational/55zb-update-settings-inworld-tts.py create mode 100644 examples/foundational/55zc-update-settings-gemini-tts.py create mode 100644 examples/foundational/55zd-update-settings-aws-polly-tts.py create mode 100644 examples/foundational/55ze-update-settings-sarvam-tts.py create mode 100644 examples/foundational/55zf-update-settings-camb-tts.py create mode 100644 examples/foundational/55zg-update-settings-hathora-tts.py create mode 100644 examples/foundational/55zh-update-settings-resembleai-tts.py create mode 100644 examples/foundational/55zi-update-settings-openai-llm.py create mode 100644 examples/foundational/55zj-update-settings-anthropic-llm.py create mode 100644 examples/foundational/55zk-update-settings-google-llm.py create mode 100644 examples/foundational/55zl-update-settings-openai-realtime.py create mode 100644 examples/foundational/55zm-update-settings-gemini-live.py create mode 100644 examples/foundational/55zn-update-settings-ultravox-realtime.py create mode 100644 examples/foundational/55zo-update-settings-grok-realtime.py create mode 100644 examples/foundational/55zp-update-settings-aws-bedrock-llm.py diff --git a/examples/foundational/55a-update-settings-deepgram-stt.py b/examples/foundational/55a-update-settings-deepgram-stt.py new file mode 100644 index 000000000..bf1247ed6 --- /dev/null +++ b/examples/foundational/55a-update-settings-deepgram-stt.py @@ -0,0 +1,131 @@ +# +# Copyright (c) 2024-2026, Daily +# +# SPDX-License-Identifier: BSD 2-Clause License +# + +import asyncio +import os + +from dotenv import load_dotenv +from loguru import logger + +from pipecat.audio.vad.silero import SileroVADAnalyzer +from pipecat.frames.frames import LLMRunFrame, STTUpdateSettingsFrame +from pipecat.pipeline.pipeline import Pipeline +from pipecat.pipeline.runner import PipelineRunner +from pipecat.pipeline.task import PipelineParams, PipelineTask +from pipecat.processors.aggregators.llm_context import LLMContext +from pipecat.processors.aggregators.llm_response_universal import ( + LLMContextAggregatorPair, + LLMUserAggregatorParams, +) +from pipecat.runner.types import RunnerArguments +from pipecat.runner.utils import create_transport +from pipecat.services.cartesia.tts import CartesiaTTSService +from pipecat.services.deepgram.stt import DeepgramSTTService, DeepgramSTTSettings +from pipecat.services.openai.llm import OpenAILLMService +from pipecat.transcriptions.language import Language +from pipecat.transports.base_transport import BaseTransport, TransportParams +from pipecat.transports.daily.transport import DailyParams +from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams + +load_dotenv(override=True) + +transport_params = { + "daily": lambda: DailyParams( + audio_in_enabled=True, + audio_out_enabled=True, + ), + "twilio": lambda: FastAPIWebsocketParams( + audio_in_enabled=True, + audio_out_enabled=True, + ), + "webrtc": lambda: TransportParams( + audio_in_enabled=True, + audio_out_enabled=True, + ), +} + + +async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): + logger.info(f"Starting bot") + + stt = DeepgramSTTService(api_key=os.getenv("DEEPGRAM_API_KEY")) + + tts = CartesiaTTSService( + api_key=os.getenv("CARTESIA_API_KEY"), + voice_id="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady + ) + + llm = OpenAILLMService(api_key=os.getenv("OPENAI_API_KEY")) + + messages = [ + { + "role": "system", + "content": "You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + }, + ] + + context = LLMContext(messages) + user_aggregator, assistant_aggregator = LLMContextAggregatorPair( + context, + user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()), + ) + + pipeline = Pipeline( + [ + transport.input(), + stt, + user_aggregator, + llm, + tts, + transport.output(), + assistant_aggregator, + ] + ) + + task = PipelineTask( + pipeline, + params=PipelineParams( + enable_metrics=True, + enable_usage_metrics=True, + ), + idle_timeout_secs=runner_args.pipeline_idle_timeout_secs, + ) + + @transport.event_handler("on_client_connected") + async def on_client_connected(transport, client): + logger.info(f"Client connected") + messages.append({"role": "system", "content": "Please introduce yourself to the user."}) + await task.queue_frames([LLMRunFrame()]) + + async def update_settings(): + await asyncio.sleep(10) + logger.info("Updating Deepgram STT settings: language=es") + await task.queue_frame( + STTUpdateSettingsFrame(update=DeepgramSTTSettings(language=Language.ES)) + ) + + asyncio.create_task(update_settings()) + + @transport.event_handler("on_client_disconnected") + async def on_client_disconnected(transport, client): + logger.info(f"Client disconnected") + await task.cancel() + + runner = PipelineRunner(handle_sigint=runner_args.handle_sigint) + + await runner.run(task) + + +async def bot(runner_args: RunnerArguments): + """Main bot entry point compatible with Pipecat Cloud.""" + transport = await create_transport(runner_args, transport_params) + await run_bot(transport, runner_args) + + +if __name__ == "__main__": + from pipecat.runner.run import main + + main() diff --git a/examples/foundational/55b-update-settings-azure-stt.py b/examples/foundational/55b-update-settings-azure-stt.py new file mode 100644 index 000000000..9ff2a5af7 --- /dev/null +++ b/examples/foundational/55b-update-settings-azure-stt.py @@ -0,0 +1,134 @@ +# +# Copyright (c) 2024-2026, Daily +# +# SPDX-License-Identifier: BSD 2-Clause License +# + +import asyncio +import os + +from dotenv import load_dotenv +from loguru import logger + +from pipecat.audio.vad.silero import SileroVADAnalyzer +from pipecat.frames.frames import LLMRunFrame, STTUpdateSettingsFrame +from pipecat.pipeline.pipeline import Pipeline +from pipecat.pipeline.runner import PipelineRunner +from pipecat.pipeline.task import PipelineParams, PipelineTask +from pipecat.processors.aggregators.llm_context import LLMContext +from pipecat.processors.aggregators.llm_response_universal import ( + LLMContextAggregatorPair, + LLMUserAggregatorParams, +) +from pipecat.runner.types import RunnerArguments +from pipecat.runner.utils import create_transport +from pipecat.services.azure.stt import AzureSTTService, AzureSTTSettings +from pipecat.services.cartesia.tts import CartesiaTTSService +from pipecat.services.openai.llm import OpenAILLMService +from pipecat.transcriptions.language import Language +from pipecat.transports.base_transport import BaseTransport, TransportParams +from pipecat.transports.daily.transport import DailyParams +from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams + +load_dotenv(override=True) + +transport_params = { + "daily": lambda: DailyParams( + audio_in_enabled=True, + audio_out_enabled=True, + ), + "twilio": lambda: FastAPIWebsocketParams( + audio_in_enabled=True, + audio_out_enabled=True, + ), + "webrtc": lambda: TransportParams( + audio_in_enabled=True, + audio_out_enabled=True, + ), +} + + +async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): + logger.info(f"Starting bot") + + stt = AzureSTTService( + api_key=os.getenv("AZURE_SPEECH_API_KEY"), + region=os.getenv("AZURE_SPEECH_REGION"), + ) + + tts = CartesiaTTSService( + api_key=os.getenv("CARTESIA_API_KEY"), + voice_id="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady + ) + + llm = OpenAILLMService(api_key=os.getenv("OPENAI_API_KEY")) + + messages = [ + { + "role": "system", + "content": "You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + }, + ] + + context = LLMContext(messages) + user_aggregator, assistant_aggregator = LLMContextAggregatorPair( + context, + user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()), + ) + + pipeline = Pipeline( + [ + transport.input(), + stt, + user_aggregator, + llm, + tts, + transport.output(), + assistant_aggregator, + ] + ) + + task = PipelineTask( + pipeline, + params=PipelineParams( + enable_metrics=True, + enable_usage_metrics=True, + ), + idle_timeout_secs=runner_args.pipeline_idle_timeout_secs, + ) + + @transport.event_handler("on_client_connected") + async def on_client_connected(transport, client): + logger.info(f"Client connected") + messages.append({"role": "system", "content": "Please introduce yourself to the user."}) + await task.queue_frames([LLMRunFrame()]) + + async def update_settings(): + await asyncio.sleep(10) + logger.info("Updating Azure STT settings: language=es") + await task.queue_frame( + STTUpdateSettingsFrame(update=AzureSTTSettings(language=Language.ES)) + ) + + asyncio.create_task(update_settings()) + + @transport.event_handler("on_client_disconnected") + async def on_client_disconnected(transport, client): + logger.info(f"Client disconnected") + await task.cancel() + + runner = PipelineRunner(handle_sigint=runner_args.handle_sigint) + + await runner.run(task) + + +async def bot(runner_args: RunnerArguments): + """Main bot entry point compatible with Pipecat Cloud.""" + transport = await create_transport(runner_args, transport_params) + await run_bot(transport, runner_args) + + +if __name__ == "__main__": + from pipecat.runner.run import main + + main() diff --git a/examples/foundational/55c-update-settings-google-stt.py b/examples/foundational/55c-update-settings-google-stt.py new file mode 100644 index 000000000..b25046fe3 --- /dev/null +++ b/examples/foundational/55c-update-settings-google-stt.py @@ -0,0 +1,131 @@ +# +# Copyright (c) 2024-2026, Daily +# +# SPDX-License-Identifier: BSD 2-Clause License +# + +import asyncio +import os + +from dotenv import load_dotenv +from loguru import logger + +from pipecat.audio.vad.silero import SileroVADAnalyzer +from pipecat.frames.frames import LLMRunFrame, STTUpdateSettingsFrame +from pipecat.pipeline.pipeline import Pipeline +from pipecat.pipeline.runner import PipelineRunner +from pipecat.pipeline.task import PipelineParams, PipelineTask +from pipecat.processors.aggregators.llm_context import LLMContext +from pipecat.processors.aggregators.llm_response_universal import ( + LLMContextAggregatorPair, + LLMUserAggregatorParams, +) +from pipecat.runner.types import RunnerArguments +from pipecat.runner.utils import create_transport +from pipecat.services.cartesia.tts import CartesiaTTSService +from pipecat.services.google.stt import GoogleSTTService, GoogleSTTSettings +from pipecat.services.openai.llm import OpenAILLMService +from pipecat.transcriptions.language import Language +from pipecat.transports.base_transport import BaseTransport, TransportParams +from pipecat.transports.daily.transport import DailyParams +from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams + +load_dotenv(override=True) + +transport_params = { + "daily": lambda: DailyParams( + audio_in_enabled=True, + audio_out_enabled=True, + ), + "twilio": lambda: FastAPIWebsocketParams( + audio_in_enabled=True, + audio_out_enabled=True, + ), + "webrtc": lambda: TransportParams( + audio_in_enabled=True, + audio_out_enabled=True, + ), +} + + +async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): + logger.info(f"Starting bot") + + stt = GoogleSTTService(credentials=os.getenv("GOOGLE_TEST_CREDENTIALS")) + + tts = CartesiaTTSService( + api_key=os.getenv("CARTESIA_API_KEY"), + voice_id="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady + ) + + llm = OpenAILLMService(api_key=os.getenv("OPENAI_API_KEY")) + + messages = [ + { + "role": "system", + "content": "You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + }, + ] + + context = LLMContext(messages) + user_aggregator, assistant_aggregator = LLMContextAggregatorPair( + context, + user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()), + ) + + pipeline = Pipeline( + [ + transport.input(), + stt, + user_aggregator, + llm, + tts, + transport.output(), + assistant_aggregator, + ] + ) + + task = PipelineTask( + pipeline, + params=PipelineParams( + enable_metrics=True, + enable_usage_metrics=True, + ), + idle_timeout_secs=runner_args.pipeline_idle_timeout_secs, + ) + + @transport.event_handler("on_client_connected") + async def on_client_connected(transport, client): + logger.info(f"Client connected") + messages.append({"role": "system", "content": "Please introduce yourself to the user."}) + await task.queue_frames([LLMRunFrame()]) + + async def update_settings(): + await asyncio.sleep(10) + logger.info("Updating Google STT settings: language=es") + await task.queue_frame( + STTUpdateSettingsFrame(update=GoogleSTTSettings(language=Language.ES)) + ) + + asyncio.create_task(update_settings()) + + @transport.event_handler("on_client_disconnected") + async def on_client_disconnected(transport, client): + logger.info(f"Client disconnected") + await task.cancel() + + runner = PipelineRunner(handle_sigint=runner_args.handle_sigint) + + await runner.run(task) + + +async def bot(runner_args: RunnerArguments): + """Main bot entry point compatible with Pipecat Cloud.""" + transport = await create_transport(runner_args, transport_params) + await run_bot(transport, runner_args) + + +if __name__ == "__main__": + from pipecat.runner.run import main + + main() diff --git a/examples/foundational/55d-update-settings-assemblyai-stt.py b/examples/foundational/55d-update-settings-assemblyai-stt.py new file mode 100644 index 000000000..488f17f54 --- /dev/null +++ b/examples/foundational/55d-update-settings-assemblyai-stt.py @@ -0,0 +1,131 @@ +# +# Copyright (c) 2024-2026, Daily +# +# SPDX-License-Identifier: BSD 2-Clause License +# + +import asyncio +import os + +from dotenv import load_dotenv +from loguru import logger + +from pipecat.audio.vad.silero import SileroVADAnalyzer +from pipecat.frames.frames import LLMRunFrame, STTUpdateSettingsFrame +from pipecat.pipeline.pipeline import Pipeline +from pipecat.pipeline.runner import PipelineRunner +from pipecat.pipeline.task import PipelineParams, PipelineTask +from pipecat.processors.aggregators.llm_context import LLMContext +from pipecat.processors.aggregators.llm_response_universal import ( + LLMContextAggregatorPair, + LLMUserAggregatorParams, +) +from pipecat.runner.types import RunnerArguments +from pipecat.runner.utils import create_transport +from pipecat.services.assemblyai.stt import AssemblyAISTTService, AssemblyAISTTSettings +from pipecat.services.cartesia.tts import CartesiaTTSService +from pipecat.services.openai.llm import OpenAILLMService +from pipecat.transcriptions.language import Language +from pipecat.transports.base_transport import BaseTransport, TransportParams +from pipecat.transports.daily.transport import DailyParams +from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams + +load_dotenv(override=True) + +transport_params = { + "daily": lambda: DailyParams( + audio_in_enabled=True, + audio_out_enabled=True, + ), + "twilio": lambda: FastAPIWebsocketParams( + audio_in_enabled=True, + audio_out_enabled=True, + ), + "webrtc": lambda: TransportParams( + audio_in_enabled=True, + audio_out_enabled=True, + ), +} + + +async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): + logger.info(f"Starting bot") + + stt = AssemblyAISTTService(api_key=os.getenv("ASSEMBLYAI_API_KEY")) + + tts = CartesiaTTSService( + api_key=os.getenv("CARTESIA_API_KEY"), + voice_id="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady + ) + + llm = OpenAILLMService(api_key=os.getenv("OPENAI_API_KEY")) + + messages = [ + { + "role": "system", + "content": "You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + }, + ] + + context = LLMContext(messages) + user_aggregator, assistant_aggregator = LLMContextAggregatorPair( + context, + user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()), + ) + + pipeline = Pipeline( + [ + transport.input(), + stt, + user_aggregator, + llm, + tts, + transport.output(), + assistant_aggregator, + ] + ) + + task = PipelineTask( + pipeline, + params=PipelineParams( + enable_metrics=True, + enable_usage_metrics=True, + ), + idle_timeout_secs=runner_args.pipeline_idle_timeout_secs, + ) + + @transport.event_handler("on_client_connected") + async def on_client_connected(transport, client): + logger.info(f"Client connected") + messages.append({"role": "system", "content": "Please introduce yourself to the user."}) + await task.queue_frames([LLMRunFrame()]) + + async def update_settings(): + await asyncio.sleep(10) + logger.info("Updating AssemblyAI STT settings: language=es") + await task.queue_frame( + STTUpdateSettingsFrame(update=AssemblyAISTTSettings(language=Language.ES)) + ) + + asyncio.create_task(update_settings()) + + @transport.event_handler("on_client_disconnected") + async def on_client_disconnected(transport, client): + logger.info(f"Client disconnected") + await task.cancel() + + runner = PipelineRunner(handle_sigint=runner_args.handle_sigint) + + await runner.run(task) + + +async def bot(runner_args: RunnerArguments): + """Main bot entry point compatible with Pipecat Cloud.""" + transport = await create_transport(runner_args, transport_params) + await run_bot(transport, runner_args) + + +if __name__ == "__main__": + from pipecat.runner.run import main + + main() diff --git a/examples/foundational/55e-update-settings-gladia-stt.py b/examples/foundational/55e-update-settings-gladia-stt.py new file mode 100644 index 000000000..75e524d08 --- /dev/null +++ b/examples/foundational/55e-update-settings-gladia-stt.py @@ -0,0 +1,131 @@ +# +# Copyright (c) 2024-2026, Daily +# +# SPDX-License-Identifier: BSD 2-Clause License +# + +import asyncio +import os + +from dotenv import load_dotenv +from loguru import logger + +from pipecat.audio.vad.silero import SileroVADAnalyzer +from pipecat.frames.frames import LLMRunFrame, STTUpdateSettingsFrame +from pipecat.pipeline.pipeline import Pipeline +from pipecat.pipeline.runner import PipelineRunner +from pipecat.pipeline.task import PipelineParams, PipelineTask +from pipecat.processors.aggregators.llm_context import LLMContext +from pipecat.processors.aggregators.llm_response_universal import ( + LLMContextAggregatorPair, + LLMUserAggregatorParams, +) +from pipecat.runner.types import RunnerArguments +from pipecat.runner.utils import create_transport +from pipecat.services.cartesia.tts import CartesiaTTSService +from pipecat.services.gladia.stt import GladiaSTTService, GladiaSTTSettings +from pipecat.services.openai.llm import OpenAILLMService +from pipecat.transcriptions.language import Language +from pipecat.transports.base_transport import BaseTransport, TransportParams +from pipecat.transports.daily.transport import DailyParams +from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams + +load_dotenv(override=True) + +transport_params = { + "daily": lambda: DailyParams( + audio_in_enabled=True, + audio_out_enabled=True, + ), + "twilio": lambda: FastAPIWebsocketParams( + audio_in_enabled=True, + audio_out_enabled=True, + ), + "webrtc": lambda: TransportParams( + audio_in_enabled=True, + audio_out_enabled=True, + ), +} + + +async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): + logger.info(f"Starting bot") + + stt = GladiaSTTService(api_key=os.getenv("GLADIA_API_KEY")) + + tts = CartesiaTTSService( + api_key=os.getenv("CARTESIA_API_KEY"), + voice_id="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady + ) + + llm = OpenAILLMService(api_key=os.getenv("OPENAI_API_KEY")) + + messages = [ + { + "role": "system", + "content": "You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + }, + ] + + context = LLMContext(messages) + user_aggregator, assistant_aggregator = LLMContextAggregatorPair( + context, + user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()), + ) + + pipeline = Pipeline( + [ + transport.input(), + stt, + user_aggregator, + llm, + tts, + transport.output(), + assistant_aggregator, + ] + ) + + task = PipelineTask( + pipeline, + params=PipelineParams( + enable_metrics=True, + enable_usage_metrics=True, + ), + idle_timeout_secs=runner_args.pipeline_idle_timeout_secs, + ) + + @transport.event_handler("on_client_connected") + async def on_client_connected(transport, client): + logger.info(f"Client connected") + messages.append({"role": "system", "content": "Please introduce yourself to the user."}) + await task.queue_frames([LLMRunFrame()]) + + async def update_settings(): + await asyncio.sleep(10) + logger.info("Updating Gladia STT settings: language=es") + await task.queue_frame( + STTUpdateSettingsFrame(update=GladiaSTTSettings(language=Language.ES)) + ) + + asyncio.create_task(update_settings()) + + @transport.event_handler("on_client_disconnected") + async def on_client_disconnected(transport, client): + logger.info(f"Client disconnected") + await task.cancel() + + runner = PipelineRunner(handle_sigint=runner_args.handle_sigint) + + await runner.run(task) + + +async def bot(runner_args: RunnerArguments): + """Main bot entry point compatible with Pipecat Cloud.""" + transport = await create_transport(runner_args, transport_params) + await run_bot(transport, runner_args) + + +if __name__ == "__main__": + from pipecat.runner.run import main + + main() diff --git a/examples/foundational/55f-update-settings-elevenlabs-realtime-stt.py b/examples/foundational/55f-update-settings-elevenlabs-realtime-stt.py new file mode 100644 index 000000000..f74ea709e --- /dev/null +++ b/examples/foundational/55f-update-settings-elevenlabs-realtime-stt.py @@ -0,0 +1,134 @@ +# +# Copyright (c) 2024-2026, Daily +# +# SPDX-License-Identifier: BSD 2-Clause License +# + +import asyncio +import os + +from dotenv import load_dotenv +from loguru import logger + +from pipecat.audio.vad.silero import SileroVADAnalyzer +from pipecat.frames.frames import LLMRunFrame, STTUpdateSettingsFrame +from pipecat.pipeline.pipeline import Pipeline +from pipecat.pipeline.runner import PipelineRunner +from pipecat.pipeline.task import PipelineParams, PipelineTask +from pipecat.processors.aggregators.llm_context import LLMContext +from pipecat.processors.aggregators.llm_response_universal import ( + LLMContextAggregatorPair, + LLMUserAggregatorParams, +) +from pipecat.runner.types import RunnerArguments +from pipecat.runner.utils import create_transport +from pipecat.services.cartesia.tts import CartesiaTTSService +from pipecat.services.elevenlabs.stt import ( + ElevenLabsRealtimeSTTService, + ElevenLabsRealtimeSTTSettings, +) +from pipecat.services.openai.llm import OpenAILLMService +from pipecat.transcriptions.language import Language +from pipecat.transports.base_transport import BaseTransport, TransportParams +from pipecat.transports.daily.transport import DailyParams +from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams + +load_dotenv(override=True) + +transport_params = { + "daily": lambda: DailyParams( + audio_in_enabled=True, + audio_out_enabled=True, + ), + "twilio": lambda: FastAPIWebsocketParams( + audio_in_enabled=True, + audio_out_enabled=True, + ), + "webrtc": lambda: TransportParams( + audio_in_enabled=True, + audio_out_enabled=True, + ), +} + + +async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): + logger.info(f"Starting bot") + + stt = ElevenLabsRealtimeSTTService(api_key=os.getenv("ELEVENLABS_API_KEY")) + + tts = CartesiaTTSService( + api_key=os.getenv("CARTESIA_API_KEY"), + voice_id="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady + ) + + llm = OpenAILLMService(api_key=os.getenv("OPENAI_API_KEY")) + + messages = [ + { + "role": "system", + "content": "You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + }, + ] + + context = LLMContext(messages) + user_aggregator, assistant_aggregator = LLMContextAggregatorPair( + context, + user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()), + ) + + pipeline = Pipeline( + [ + transport.input(), + stt, + user_aggregator, + llm, + tts, + transport.output(), + assistant_aggregator, + ] + ) + + task = PipelineTask( + pipeline, + params=PipelineParams( + enable_metrics=True, + enable_usage_metrics=True, + ), + idle_timeout_secs=runner_args.pipeline_idle_timeout_secs, + ) + + @transport.event_handler("on_client_connected") + async def on_client_connected(transport, client): + logger.info(f"Client connected") + messages.append({"role": "system", "content": "Please introduce yourself to the user."}) + await task.queue_frames([LLMRunFrame()]) + + async def update_settings(): + await asyncio.sleep(10) + logger.info("Updating ElevenLabs Realtime STT settings: language=es") + await task.queue_frame( + STTUpdateSettingsFrame(update=ElevenLabsRealtimeSTTSettings(language=Language.ES)) + ) + + asyncio.create_task(update_settings()) + + @transport.event_handler("on_client_disconnected") + async def on_client_disconnected(transport, client): + logger.info(f"Client disconnected") + await task.cancel() + + runner = PipelineRunner(handle_sigint=runner_args.handle_sigint) + + await runner.run(task) + + +async def bot(runner_args: RunnerArguments): + """Main bot entry point compatible with Pipecat Cloud.""" + transport = await create_transport(runner_args, transport_params) + await run_bot(transport, runner_args) + + +if __name__ == "__main__": + from pipecat.runner.run import main + + main() diff --git a/examples/foundational/55g-update-settings-elevenlabs-stt.py b/examples/foundational/55g-update-settings-elevenlabs-stt.py new file mode 100644 index 000000000..dd5191218 --- /dev/null +++ b/examples/foundational/55g-update-settings-elevenlabs-stt.py @@ -0,0 +1,136 @@ +# +# Copyright (c) 2024-2026, Daily +# +# SPDX-License-Identifier: BSD 2-Clause License +# + +import asyncio +import os + +import aiohttp +from dotenv import load_dotenv +from loguru import logger + +from pipecat.audio.vad.silero import SileroVADAnalyzer +from pipecat.frames.frames import LLMRunFrame, STTUpdateSettingsFrame +from pipecat.pipeline.pipeline import Pipeline +from pipecat.pipeline.runner import PipelineRunner +from pipecat.pipeline.task import PipelineParams, PipelineTask +from pipecat.processors.aggregators.llm_context import LLMContext +from pipecat.processors.aggregators.llm_response_universal import ( + LLMContextAggregatorPair, + LLMUserAggregatorParams, +) +from pipecat.runner.types import RunnerArguments +from pipecat.runner.utils import create_transport +from pipecat.services.cartesia.tts import CartesiaTTSService +from pipecat.services.elevenlabs.stt import ElevenLabsSTTService, ElevenLabsSTTSettings +from pipecat.services.openai.llm import OpenAILLMService +from pipecat.transcriptions.language import Language +from pipecat.transports.base_transport import BaseTransport, TransportParams +from pipecat.transports.daily.transport import DailyParams +from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams + +load_dotenv(override=True) + +transport_params = { + "daily": lambda: DailyParams( + audio_in_enabled=True, + audio_out_enabled=True, + ), + "twilio": lambda: FastAPIWebsocketParams( + audio_in_enabled=True, + audio_out_enabled=True, + ), + "webrtc": lambda: TransportParams( + audio_in_enabled=True, + audio_out_enabled=True, + ), +} + + +async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): + logger.info(f"Starting bot") + + async with aiohttp.ClientSession() as session: + stt = ElevenLabsSTTService( + api_key=os.getenv("ELEVENLABS_API_KEY"), + aiohttp_session=session, + ) + + tts = CartesiaTTSService( + api_key=os.getenv("CARTESIA_API_KEY"), + voice_id="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady + ) + + llm = OpenAILLMService(api_key=os.getenv("OPENAI_API_KEY")) + + messages = [ + { + "role": "system", + "content": "You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + }, + ] + + context = LLMContext(messages) + user_aggregator, assistant_aggregator = LLMContextAggregatorPair( + context, + user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()), + ) + + pipeline = Pipeline( + [ + transport.input(), + stt, + user_aggregator, + llm, + tts, + transport.output(), + assistant_aggregator, + ] + ) + + task = PipelineTask( + pipeline, + params=PipelineParams( + enable_metrics=True, + enable_usage_metrics=True, + ), + idle_timeout_secs=runner_args.pipeline_idle_timeout_secs, + ) + + @transport.event_handler("on_client_connected") + async def on_client_connected(transport, client): + logger.info(f"Client connected") + messages.append({"role": "system", "content": "Please introduce yourself to the user."}) + await task.queue_frames([LLMRunFrame()]) + + async def update_settings(): + await asyncio.sleep(10) + logger.info("Updating ElevenLabs STT settings: language=es") + await task.queue_frame( + STTUpdateSettingsFrame(update=ElevenLabsSTTSettings(language=Language.ES)) + ) + + asyncio.create_task(update_settings()) + + @transport.event_handler("on_client_disconnected") + async def on_client_disconnected(transport, client): + logger.info(f"Client disconnected") + await task.cancel() + + runner = PipelineRunner(handle_sigint=runner_args.handle_sigint) + + await runner.run(task) + + +async def bot(runner_args: RunnerArguments): + """Main bot entry point compatible with Pipecat Cloud.""" + transport = await create_transport(runner_args, transport_params) + await run_bot(transport, runner_args) + + +if __name__ == "__main__": + from pipecat.runner.run import main + + main() diff --git a/examples/foundational/55h-update-settings-speechmatics-stt.py b/examples/foundational/55h-update-settings-speechmatics-stt.py new file mode 100644 index 000000000..82e207207 --- /dev/null +++ b/examples/foundational/55h-update-settings-speechmatics-stt.py @@ -0,0 +1,131 @@ +# +# Copyright (c) 2024-2026, Daily +# +# SPDX-License-Identifier: BSD 2-Clause License +# + +import asyncio +import os + +from dotenv import load_dotenv +from loguru import logger + +from pipecat.audio.vad.silero import SileroVADAnalyzer +from pipecat.frames.frames import LLMRunFrame, STTUpdateSettingsFrame +from pipecat.pipeline.pipeline import Pipeline +from pipecat.pipeline.runner import PipelineRunner +from pipecat.pipeline.task import PipelineParams, PipelineTask +from pipecat.processors.aggregators.llm_context import LLMContext +from pipecat.processors.aggregators.llm_response_universal import ( + LLMContextAggregatorPair, + LLMUserAggregatorParams, +) +from pipecat.runner.types import RunnerArguments +from pipecat.runner.utils import create_transport +from pipecat.services.cartesia.tts import CartesiaTTSService +from pipecat.services.openai.llm import OpenAILLMService +from pipecat.services.speechmatics.stt import SpeechmaticsSTTService, SpeechmaticsSTTSettings +from pipecat.transcriptions.language import Language +from pipecat.transports.base_transport import BaseTransport, TransportParams +from pipecat.transports.daily.transport import DailyParams +from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams + +load_dotenv(override=True) + +transport_params = { + "daily": lambda: DailyParams( + audio_in_enabled=True, + audio_out_enabled=True, + ), + "twilio": lambda: FastAPIWebsocketParams( + audio_in_enabled=True, + audio_out_enabled=True, + ), + "webrtc": lambda: TransportParams( + audio_in_enabled=True, + audio_out_enabled=True, + ), +} + + +async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): + logger.info(f"Starting bot") + + stt = SpeechmaticsSTTService(api_key=os.getenv("SPEECHMATICS_API_KEY")) + + tts = CartesiaTTSService( + api_key=os.getenv("CARTESIA_API_KEY"), + voice_id="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady + ) + + llm = OpenAILLMService(api_key=os.getenv("OPENAI_API_KEY")) + + messages = [ + { + "role": "system", + "content": "You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + }, + ] + + context = LLMContext(messages) + user_aggregator, assistant_aggregator = LLMContextAggregatorPair( + context, + user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()), + ) + + pipeline = Pipeline( + [ + transport.input(), + stt, + user_aggregator, + llm, + tts, + transport.output(), + assistant_aggregator, + ] + ) + + task = PipelineTask( + pipeline, + params=PipelineParams( + enable_metrics=True, + enable_usage_metrics=True, + ), + idle_timeout_secs=runner_args.pipeline_idle_timeout_secs, + ) + + @transport.event_handler("on_client_connected") + async def on_client_connected(transport, client): + logger.info(f"Client connected") + messages.append({"role": "system", "content": "Please introduce yourself to the user."}) + await task.queue_frames([LLMRunFrame()]) + + async def update_settings(): + await asyncio.sleep(10) + logger.info("Updating Speechmatics STT settings: language=es") + await task.queue_frame( + STTUpdateSettingsFrame(update=SpeechmaticsSTTSettings(language=Language.ES)) + ) + + asyncio.create_task(update_settings()) + + @transport.event_handler("on_client_disconnected") + async def on_client_disconnected(transport, client): + logger.info(f"Client disconnected") + await task.cancel() + + runner = PipelineRunner(handle_sigint=runner_args.handle_sigint) + + await runner.run(task) + + +async def bot(runner_args: RunnerArguments): + """Main bot entry point compatible with Pipecat Cloud.""" + transport = await create_transport(runner_args, transport_params) + await run_bot(transport, runner_args) + + +if __name__ == "__main__": + from pipecat.runner.run import main + + main() diff --git a/examples/foundational/55i-update-settings-whisper-api-stt.py b/examples/foundational/55i-update-settings-whisper-api-stt.py new file mode 100644 index 000000000..b2655bc86 --- /dev/null +++ b/examples/foundational/55i-update-settings-whisper-api-stt.py @@ -0,0 +1,137 @@ +# +# Copyright (c) 2024-2026, Daily +# +# SPDX-License-Identifier: BSD 2-Clause License +# + +import asyncio +import os + +from dotenv import load_dotenv +from loguru import logger + +from pipecat.audio.vad.silero import SileroVADAnalyzer +from pipecat.frames.frames import LLMRunFrame, STTUpdateSettingsFrame +from pipecat.pipeline.pipeline import Pipeline +from pipecat.pipeline.runner import PipelineRunner +from pipecat.pipeline.task import PipelineParams, PipelineTask +from pipecat.processors.aggregators.llm_context import LLMContext +from pipecat.processors.aggregators.llm_response_universal import ( + LLMContextAggregatorPair, + LLMUserAggregatorParams, +) +from pipecat.runner.types import RunnerArguments +from pipecat.runner.utils import create_transport +from pipecat.services.cartesia.tts import CartesiaTTSService +from pipecat.services.openai.llm import OpenAILLMService +from pipecat.services.whisper.base_stt import BaseWhisperSTTService, BaseWhisperSTTSettings +from pipecat.transports.base_transport import BaseTransport, TransportParams +from pipecat.transports.daily.transport import DailyParams +from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams + +load_dotenv(override=True) + +transport_params = { + "daily": lambda: DailyParams( + audio_in_enabled=True, + audio_out_enabled=True, + ), + "twilio": lambda: FastAPIWebsocketParams( + audio_in_enabled=True, + audio_out_enabled=True, + ), + "webrtc": lambda: TransportParams( + audio_in_enabled=True, + audio_out_enabled=True, + ), +} + + +async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): + logger.info(f"Starting bot") + + stt = BaseWhisperSTTService( + model="whisper-1", + api_key=os.getenv("OPENAI_API_KEY"), + ) + + tts = CartesiaTTSService( + api_key=os.getenv("CARTESIA_API_KEY"), + voice_id="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady + ) + + llm = OpenAILLMService(api_key=os.getenv("OPENAI_API_KEY")) + + messages = [ + { + "role": "system", + "content": "You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + }, + ] + + context = LLMContext(messages) + user_aggregator, assistant_aggregator = LLMContextAggregatorPair( + context, + user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()), + ) + + pipeline = Pipeline( + [ + transport.input(), + stt, + user_aggregator, + llm, + tts, + transport.output(), + assistant_aggregator, + ] + ) + + task = PipelineTask( + pipeline, + params=PipelineParams( + enable_metrics=True, + enable_usage_metrics=True, + ), + idle_timeout_secs=runner_args.pipeline_idle_timeout_secs, + ) + + @transport.event_handler("on_client_connected") + async def on_client_connected(transport, client): + logger.info(f"Client connected") + messages.append({"role": "system", "content": "Please introduce yourself to the user."}) + await task.queue_frames([LLMRunFrame()]) + + async def update_settings(): + await asyncio.sleep(10) + logger.info( + 'Updating Whisper API STT settings: prompt="Transcribe in English", temperature=0.5' + ) + await task.queue_frame( + STTUpdateSettingsFrame( + update=BaseWhisperSTTSettings(prompt="Transcribe in English", temperature=0.5) + ) + ) + + asyncio.create_task(update_settings()) + + @transport.event_handler("on_client_disconnected") + async def on_client_disconnected(transport, client): + logger.info(f"Client disconnected") + await task.cancel() + + runner = PipelineRunner(handle_sigint=runner_args.handle_sigint) + + await runner.run(task) + + +async def bot(runner_args: RunnerArguments): + """Main bot entry point compatible with Pipecat Cloud.""" + transport = await create_transport(runner_args, transport_params) + await run_bot(transport, runner_args) + + +if __name__ == "__main__": + from pipecat.runner.run import main + + main() diff --git a/examples/foundational/55j-update-settings-sarvam-stt.py b/examples/foundational/55j-update-settings-sarvam-stt.py new file mode 100644 index 000000000..a4d0cd192 --- /dev/null +++ b/examples/foundational/55j-update-settings-sarvam-stt.py @@ -0,0 +1,131 @@ +# +# Copyright (c) 2024-2026, Daily +# +# SPDX-License-Identifier: BSD 2-Clause License +# + +import asyncio +import os + +from dotenv import load_dotenv +from loguru import logger + +from pipecat.audio.vad.silero import SileroVADAnalyzer +from pipecat.frames.frames import LLMRunFrame, STTUpdateSettingsFrame +from pipecat.pipeline.pipeline import Pipeline +from pipecat.pipeline.runner import PipelineRunner +from pipecat.pipeline.task import PipelineParams, PipelineTask +from pipecat.processors.aggregators.llm_context import LLMContext +from pipecat.processors.aggregators.llm_response_universal import ( + LLMContextAggregatorPair, + LLMUserAggregatorParams, +) +from pipecat.runner.types import RunnerArguments +from pipecat.runner.utils import create_transport +from pipecat.services.cartesia.tts import CartesiaTTSService +from pipecat.services.openai.llm import OpenAILLMService +from pipecat.services.sarvam.stt import SarvamSTTService, SarvamSTTSettings +from pipecat.transcriptions.language import Language +from pipecat.transports.base_transport import BaseTransport, TransportParams +from pipecat.transports.daily.transport import DailyParams +from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams + +load_dotenv(override=True) + +transport_params = { + "daily": lambda: DailyParams( + audio_in_enabled=True, + audio_out_enabled=True, + ), + "twilio": lambda: FastAPIWebsocketParams( + audio_in_enabled=True, + audio_out_enabled=True, + ), + "webrtc": lambda: TransportParams( + audio_in_enabled=True, + audio_out_enabled=True, + ), +} + + +async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): + logger.info(f"Starting bot") + + stt = SarvamSTTService(api_key=os.getenv("SARVAM_API_KEY")) + + tts = CartesiaTTSService( + api_key=os.getenv("CARTESIA_API_KEY"), + voice_id="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady + ) + + llm = OpenAILLMService(api_key=os.getenv("OPENAI_API_KEY")) + + messages = [ + { + "role": "system", + "content": "You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + }, + ] + + context = LLMContext(messages) + user_aggregator, assistant_aggregator = LLMContextAggregatorPair( + context, + user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()), + ) + + pipeline = Pipeline( + [ + transport.input(), + stt, + user_aggregator, + llm, + tts, + transport.output(), + assistant_aggregator, + ] + ) + + task = PipelineTask( + pipeline, + params=PipelineParams( + enable_metrics=True, + enable_usage_metrics=True, + ), + idle_timeout_secs=runner_args.pipeline_idle_timeout_secs, + ) + + @transport.event_handler("on_client_connected") + async def on_client_connected(transport, client): + logger.info(f"Client connected") + messages.append({"role": "system", "content": "Please introduce yourself to the user."}) + await task.queue_frames([LLMRunFrame()]) + + async def update_settings(): + await asyncio.sleep(10) + logger.info("Updating Sarvam STT settings: language=hi") + await task.queue_frame( + STTUpdateSettingsFrame(update=SarvamSTTSettings(language=Language.HI)) + ) + + asyncio.create_task(update_settings()) + + @transport.event_handler("on_client_disconnected") + async def on_client_disconnected(transport, client): + logger.info(f"Client disconnected") + await task.cancel() + + runner = PipelineRunner(handle_sigint=runner_args.handle_sigint) + + await runner.run(task) + + +async def bot(runner_args: RunnerArguments): + """Main bot entry point compatible with Pipecat Cloud.""" + transport = await create_transport(runner_args, transport_params) + await run_bot(transport, runner_args) + + +if __name__ == "__main__": + from pipecat.runner.run import main + + main() diff --git a/examples/foundational/55k-update-settings-soniox-stt.py b/examples/foundational/55k-update-settings-soniox-stt.py new file mode 100644 index 000000000..5f192580b --- /dev/null +++ b/examples/foundational/55k-update-settings-soniox-stt.py @@ -0,0 +1,131 @@ +# +# Copyright (c) 2024-2026, Daily +# +# SPDX-License-Identifier: BSD 2-Clause License +# + +import asyncio +import os + +from dotenv import load_dotenv +from loguru import logger + +from pipecat.audio.vad.silero import SileroVADAnalyzer +from pipecat.frames.frames import LLMRunFrame, STTUpdateSettingsFrame +from pipecat.pipeline.pipeline import Pipeline +from pipecat.pipeline.runner import PipelineRunner +from pipecat.pipeline.task import PipelineParams, PipelineTask +from pipecat.processors.aggregators.llm_context import LLMContext +from pipecat.processors.aggregators.llm_response_universal import ( + LLMContextAggregatorPair, + LLMUserAggregatorParams, +) +from pipecat.runner.types import RunnerArguments +from pipecat.runner.utils import create_transport +from pipecat.services.cartesia.tts import CartesiaTTSService +from pipecat.services.openai.llm import OpenAILLMService +from pipecat.services.soniox.stt import SonioxSTTService, SonioxSTTSettings +from pipecat.transcriptions.language import Language +from pipecat.transports.base_transport import BaseTransport, TransportParams +from pipecat.transports.daily.transport import DailyParams +from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams + +load_dotenv(override=True) + +transport_params = { + "daily": lambda: DailyParams( + audio_in_enabled=True, + audio_out_enabled=True, + ), + "twilio": lambda: FastAPIWebsocketParams( + audio_in_enabled=True, + audio_out_enabled=True, + ), + "webrtc": lambda: TransportParams( + audio_in_enabled=True, + audio_out_enabled=True, + ), +} + + +async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): + logger.info(f"Starting bot") + + stt = SonioxSTTService(api_key=os.getenv("SONIOX_API_KEY")) + + tts = CartesiaTTSService( + api_key=os.getenv("CARTESIA_API_KEY"), + voice_id="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady + ) + + llm = OpenAILLMService(api_key=os.getenv("OPENAI_API_KEY")) + + messages = [ + { + "role": "system", + "content": "You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + }, + ] + + context = LLMContext(messages) + user_aggregator, assistant_aggregator = LLMContextAggregatorPair( + context, + user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()), + ) + + pipeline = Pipeline( + [ + transport.input(), + stt, + user_aggregator, + llm, + tts, + transport.output(), + assistant_aggregator, + ] + ) + + task = PipelineTask( + pipeline, + params=PipelineParams( + enable_metrics=True, + enable_usage_metrics=True, + ), + idle_timeout_secs=runner_args.pipeline_idle_timeout_secs, + ) + + @transport.event_handler("on_client_connected") + async def on_client_connected(transport, client): + logger.info(f"Client connected") + messages.append({"role": "system", "content": "Please introduce yourself to the user."}) + await task.queue_frames([LLMRunFrame()]) + + async def update_settings(): + await asyncio.sleep(10) + logger.info("Updating Soniox STT settings: language=es") + await task.queue_frame( + STTUpdateSettingsFrame(update=SonioxSTTSettings(language=Language.ES)) + ) + + asyncio.create_task(update_settings()) + + @transport.event_handler("on_client_disconnected") + async def on_client_disconnected(transport, client): + logger.info(f"Client disconnected") + await task.cancel() + + runner = PipelineRunner(handle_sigint=runner_args.handle_sigint) + + await runner.run(task) + + +async def bot(runner_args: RunnerArguments): + """Main bot entry point compatible with Pipecat Cloud.""" + transport = await create_transport(runner_args, transport_params) + await run_bot(transport, runner_args) + + +if __name__ == "__main__": + from pipecat.runner.run import main + + main() diff --git a/examples/foundational/55l-update-settings-aws-transcribe-stt.py b/examples/foundational/55l-update-settings-aws-transcribe-stt.py new file mode 100644 index 000000000..469efe32e --- /dev/null +++ b/examples/foundational/55l-update-settings-aws-transcribe-stt.py @@ -0,0 +1,131 @@ +# +# Copyright (c) 2024-2026, Daily +# +# SPDX-License-Identifier: BSD 2-Clause License +# + +import asyncio +import os + +from dotenv import load_dotenv +from loguru import logger + +from pipecat.audio.vad.silero import SileroVADAnalyzer +from pipecat.frames.frames import LLMRunFrame, STTUpdateSettingsFrame +from pipecat.pipeline.pipeline import Pipeline +from pipecat.pipeline.runner import PipelineRunner +from pipecat.pipeline.task import PipelineParams, PipelineTask +from pipecat.processors.aggregators.llm_context import LLMContext +from pipecat.processors.aggregators.llm_response_universal import ( + LLMContextAggregatorPair, + LLMUserAggregatorParams, +) +from pipecat.runner.types import RunnerArguments +from pipecat.runner.utils import create_transport +from pipecat.services.aws.stt import AWSTranscribeSTTService, AWSTranscribeSTTSettings +from pipecat.services.cartesia.tts import CartesiaTTSService +from pipecat.services.openai.llm import OpenAILLMService +from pipecat.transcriptions.language import Language +from pipecat.transports.base_transport import BaseTransport, TransportParams +from pipecat.transports.daily.transport import DailyParams +from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams + +load_dotenv(override=True) + +transport_params = { + "daily": lambda: DailyParams( + audio_in_enabled=True, + audio_out_enabled=True, + ), + "twilio": lambda: FastAPIWebsocketParams( + audio_in_enabled=True, + audio_out_enabled=True, + ), + "webrtc": lambda: TransportParams( + audio_in_enabled=True, + audio_out_enabled=True, + ), +} + + +async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): + logger.info(f"Starting bot") + + stt = AWSTranscribeSTTService() + + tts = CartesiaTTSService( + api_key=os.getenv("CARTESIA_API_KEY"), + voice_id="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady + ) + + llm = OpenAILLMService(api_key=os.getenv("OPENAI_API_KEY")) + + messages = [ + { + "role": "system", + "content": "You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + }, + ] + + context = LLMContext(messages) + user_aggregator, assistant_aggregator = LLMContextAggregatorPair( + context, + user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()), + ) + + pipeline = Pipeline( + [ + transport.input(), + stt, + user_aggregator, + llm, + tts, + transport.output(), + assistant_aggregator, + ] + ) + + task = PipelineTask( + pipeline, + params=PipelineParams( + enable_metrics=True, + enable_usage_metrics=True, + ), + idle_timeout_secs=runner_args.pipeline_idle_timeout_secs, + ) + + @transport.event_handler("on_client_connected") + async def on_client_connected(transport, client): + logger.info(f"Client connected") + messages.append({"role": "system", "content": "Please introduce yourself to the user."}) + await task.queue_frames([LLMRunFrame()]) + + async def update_settings(): + await asyncio.sleep(10) + logger.info("Updating AWS Transcribe STT settings: language=es") + await task.queue_frame( + STTUpdateSettingsFrame(update=AWSTranscribeSTTSettings(language=Language.ES)) + ) + + asyncio.create_task(update_settings()) + + @transport.event_handler("on_client_disconnected") + async def on_client_disconnected(transport, client): + logger.info(f"Client disconnected") + await task.cancel() + + runner = PipelineRunner(handle_sigint=runner_args.handle_sigint) + + await runner.run(task) + + +async def bot(runner_args: RunnerArguments): + """Main bot entry point compatible with Pipecat Cloud.""" + transport = await create_transport(runner_args, transport_params) + await run_bot(transport, runner_args) + + +if __name__ == "__main__": + from pipecat.runner.run import main + + main() diff --git a/examples/foundational/55m-update-settings-cartesia-stt.py b/examples/foundational/55m-update-settings-cartesia-stt.py new file mode 100644 index 000000000..0ed1aa169 --- /dev/null +++ b/examples/foundational/55m-update-settings-cartesia-stt.py @@ -0,0 +1,131 @@ +# +# Copyright (c) 2024-2026, Daily +# +# SPDX-License-Identifier: BSD 2-Clause License +# + +import asyncio +import os + +from dotenv import load_dotenv +from loguru import logger + +from pipecat.audio.vad.silero import SileroVADAnalyzer +from pipecat.frames.frames import LLMRunFrame, STTUpdateSettingsFrame +from pipecat.pipeline.pipeline import Pipeline +from pipecat.pipeline.runner import PipelineRunner +from pipecat.pipeline.task import PipelineParams, PipelineTask +from pipecat.processors.aggregators.llm_context import LLMContext +from pipecat.processors.aggregators.llm_response_universal import ( + LLMContextAggregatorPair, + LLMUserAggregatorParams, +) +from pipecat.runner.types import RunnerArguments +from pipecat.runner.utils import create_transport +from pipecat.services.cartesia.stt import CartesiaSTTService, CartesiaSTTSettings +from pipecat.services.cartesia.tts import CartesiaTTSService +from pipecat.services.openai.llm import OpenAILLMService +from pipecat.transcriptions.language import Language +from pipecat.transports.base_transport import BaseTransport, TransportParams +from pipecat.transports.daily.transport import DailyParams +from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams + +load_dotenv(override=True) + +transport_params = { + "daily": lambda: DailyParams( + audio_in_enabled=True, + audio_out_enabled=True, + ), + "twilio": lambda: FastAPIWebsocketParams( + audio_in_enabled=True, + audio_out_enabled=True, + ), + "webrtc": lambda: TransportParams( + audio_in_enabled=True, + audio_out_enabled=True, + ), +} + + +async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): + logger.info(f"Starting bot") + + stt = CartesiaSTTService(api_key=os.getenv("CARTESIA_API_KEY")) + + tts = CartesiaTTSService( + api_key=os.getenv("CARTESIA_API_KEY"), + voice_id="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady + ) + + llm = OpenAILLMService(api_key=os.getenv("OPENAI_API_KEY")) + + messages = [ + { + "role": "system", + "content": "You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + }, + ] + + context = LLMContext(messages) + user_aggregator, assistant_aggregator = LLMContextAggregatorPair( + context, + user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()), + ) + + pipeline = Pipeline( + [ + transport.input(), + stt, + user_aggregator, + llm, + tts, + transport.output(), + assistant_aggregator, + ] + ) + + task = PipelineTask( + pipeline, + params=PipelineParams( + enable_metrics=True, + enable_usage_metrics=True, + ), + idle_timeout_secs=runner_args.pipeline_idle_timeout_secs, + ) + + @transport.event_handler("on_client_connected") + async def on_client_connected(transport, client): + logger.info(f"Client connected") + messages.append({"role": "system", "content": "Please introduce yourself to the user."}) + await task.queue_frames([LLMRunFrame()]) + + async def update_settings(): + await asyncio.sleep(10) + logger.info("Updating Cartesia STT settings: language=es") + await task.queue_frame( + STTUpdateSettingsFrame(update=CartesiaSTTSettings(language=Language.ES)) + ) + + asyncio.create_task(update_settings()) + + @transport.event_handler("on_client_disconnected") + async def on_client_disconnected(transport, client): + logger.info(f"Client disconnected") + await task.cancel() + + runner = PipelineRunner(handle_sigint=runner_args.handle_sigint) + + await runner.run(task) + + +async def bot(runner_args: RunnerArguments): + """Main bot entry point compatible with Pipecat Cloud.""" + transport = await create_transport(runner_args, transport_params) + await run_bot(transport, runner_args) + + +if __name__ == "__main__": + from pipecat.runner.run import main + + main() diff --git a/examples/foundational/55n-update-settings-cartesia-tts.py b/examples/foundational/55n-update-settings-cartesia-tts.py new file mode 100644 index 000000000..afa9bbeb5 --- /dev/null +++ b/examples/foundational/55n-update-settings-cartesia-tts.py @@ -0,0 +1,131 @@ +# +# Copyright (c) 2024-2026, Daily +# +# SPDX-License-Identifier: BSD 2-Clause License +# + +import asyncio +import os + +from dotenv import load_dotenv +from loguru import logger + +from pipecat.audio.vad.silero import SileroVADAnalyzer +from pipecat.frames.frames import LLMRunFrame, TTSUpdateSettingsFrame +from pipecat.pipeline.pipeline import Pipeline +from pipecat.pipeline.runner import PipelineRunner +from pipecat.pipeline.task import PipelineParams, PipelineTask +from pipecat.processors.aggregators.llm_context import LLMContext +from pipecat.processors.aggregators.llm_response_universal import ( + LLMContextAggregatorPair, + LLMUserAggregatorParams, +) +from pipecat.runner.types import RunnerArguments +from pipecat.runner.utils import create_transport +from pipecat.services.cartesia.tts import CartesiaTTSService, CartesiaTTSSettings +from pipecat.services.deepgram.stt import DeepgramSTTService +from pipecat.services.openai.llm import OpenAILLMService +from pipecat.transports.base_transport import BaseTransport, TransportParams +from pipecat.transports.daily.transport import DailyParams +from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams + +load_dotenv(override=True) + +# We use lambdas to defer transport parameter creation until the transport +# type is selected at runtime. +transport_params = { + "daily": lambda: DailyParams( + audio_in_enabled=True, + audio_out_enabled=True, + ), + "twilio": lambda: FastAPIWebsocketParams( + audio_in_enabled=True, + audio_out_enabled=True, + ), + "webrtc": lambda: TransportParams( + audio_in_enabled=True, + audio_out_enabled=True, + ), +} + + +async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): + logger.info(f"Starting bot") + + stt = DeepgramSTTService(api_key=os.getenv("DEEPGRAM_API_KEY")) + + tts = CartesiaTTSService( + api_key=os.getenv("CARTESIA_API_KEY"), + voice_id="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady + ) + + llm = OpenAILLMService(api_key=os.getenv("OPENAI_API_KEY")) + + messages = [ + { + "role": "system", + "content": "You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + }, + ] + + context = LLMContext(messages) + user_aggregator, assistant_aggregator = LLMContextAggregatorPair( + context, + user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()), + ) + + pipeline = Pipeline( + [ + transport.input(), # Transport user input + stt, + user_aggregator, # User responses + llm, # LLM + tts, # TTS + transport.output(), # Transport bot output + assistant_aggregator, # Assistant spoken responses + ] + ) + + task = PipelineTask( + pipeline, + params=PipelineParams( + enable_metrics=True, + enable_usage_metrics=True, + ), + idle_timeout_secs=runner_args.pipeline_idle_timeout_secs, + ) + + @transport.event_handler("on_client_connected") + async def on_client_connected(transport, client): + logger.info(f"Client connected") + # Kick off the conversation. + messages.append({"role": "system", "content": "Please introduce yourself to the user."}) + await task.queue_frames([LLMRunFrame()]) + + async def update_settings(): + await asyncio.sleep(10) + logger.info("Updating Cartesia TTS settings: speed=fast") + await task.queue_frame(TTSUpdateSettingsFrame(update=CartesiaTTSSettings(speed="fast"))) + + asyncio.create_task(update_settings()) + + @transport.event_handler("on_client_disconnected") + async def on_client_disconnected(transport, client): + logger.info(f"Client disconnected") + await task.cancel() + + runner = PipelineRunner(handle_sigint=runner_args.handle_sigint) + + await runner.run(task) + + +async def bot(runner_args: RunnerArguments): + """Main bot entry point compatible with Pipecat Cloud.""" + transport = await create_transport(runner_args, transport_params) + await run_bot(transport, runner_args) + + +if __name__ == "__main__": + from pipecat.runner.run import main + + main() diff --git a/examples/foundational/55o-update-settings-elevenlabs-tts.py b/examples/foundational/55o-update-settings-elevenlabs-tts.py new file mode 100644 index 000000000..65ccfc41a --- /dev/null +++ b/examples/foundational/55o-update-settings-elevenlabs-tts.py @@ -0,0 +1,130 @@ +# +# Copyright (c) 2024-2026, Daily +# +# SPDX-License-Identifier: BSD 2-Clause License +# + +import asyncio +import os + +from dotenv import load_dotenv +from loguru import logger + +from pipecat.audio.vad.silero import SileroVADAnalyzer +from pipecat.frames.frames import LLMRunFrame, TTSUpdateSettingsFrame +from pipecat.pipeline.pipeline import Pipeline +from pipecat.pipeline.runner import PipelineRunner +from pipecat.pipeline.task import PipelineParams, PipelineTask +from pipecat.processors.aggregators.llm_context import LLMContext +from pipecat.processors.aggregators.llm_response_universal import ( + LLMContextAggregatorPair, + LLMUserAggregatorParams, +) +from pipecat.runner.types import RunnerArguments +from pipecat.runner.utils import create_transport +from pipecat.services.deepgram.stt import DeepgramSTTService +from pipecat.services.elevenlabs.tts import ElevenLabsTTSService, ElevenLabsTTSSettings +from pipecat.services.openai.llm import OpenAILLMService +from pipecat.transports.base_transport import BaseTransport, TransportParams +from pipecat.transports.daily.transport import DailyParams +from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams + +load_dotenv(override=True) + +transport_params = { + "daily": lambda: DailyParams( + audio_in_enabled=True, + audio_out_enabled=True, + ), + "twilio": lambda: FastAPIWebsocketParams( + audio_in_enabled=True, + audio_out_enabled=True, + ), + "webrtc": lambda: TransportParams( + audio_in_enabled=True, + audio_out_enabled=True, + ), +} + + +async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): + logger.info(f"Starting bot") + + stt = DeepgramSTTService(api_key=os.getenv("DEEPGRAM_API_KEY")) + + tts = ElevenLabsTTSService( + api_key=os.getenv("ELEVENLABS_API_KEY"), + voice_id=os.getenv("ELEVENLABS_VOICE_ID"), + ) + + llm = OpenAILLMService(api_key=os.getenv("OPENAI_API_KEY")) + + messages = [ + { + "role": "system", + "content": "You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + }, + ] + + context = LLMContext(messages) + user_aggregator, assistant_aggregator = LLMContextAggregatorPair( + context, + user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()), + ) + + pipeline = Pipeline( + [ + transport.input(), + stt, + user_aggregator, + llm, + tts, + transport.output(), + assistant_aggregator, + ] + ) + + task = PipelineTask( + pipeline, + params=PipelineParams( + enable_metrics=True, + enable_usage_metrics=True, + ), + idle_timeout_secs=runner_args.pipeline_idle_timeout_secs, + ) + + @transport.event_handler("on_client_connected") + async def on_client_connected(transport, client): + logger.info(f"Client connected") + messages.append({"role": "system", "content": "Please introduce yourself to the user."}) + await task.queue_frames([LLMRunFrame()]) + + async def update_settings(): + await asyncio.sleep(10) + logger.info("Updating ElevenLabs TTS settings: speed=1.2, stability=0.3") + await task.queue_frame( + TTSUpdateSettingsFrame(update=ElevenLabsTTSSettings(speed=1.2, stability=0.3)) + ) + + asyncio.create_task(update_settings()) + + @transport.event_handler("on_client_disconnected") + async def on_client_disconnected(transport, client): + logger.info(f"Client disconnected") + await task.cancel() + + runner = PipelineRunner(handle_sigint=runner_args.handle_sigint) + + await runner.run(task) + + +async def bot(runner_args: RunnerArguments): + """Main bot entry point compatible with Pipecat Cloud.""" + transport = await create_transport(runner_args, transport_params) + await run_bot(transport, runner_args) + + +if __name__ == "__main__": + from pipecat.runner.run import main + + main() diff --git a/examples/foundational/55p-update-settings-openai-tts.py b/examples/foundational/55p-update-settings-openai-tts.py new file mode 100644 index 000000000..ebcb1cd54 --- /dev/null +++ b/examples/foundational/55p-update-settings-openai-tts.py @@ -0,0 +1,126 @@ +# +# Copyright (c) 2024-2026, Daily +# +# SPDX-License-Identifier: BSD 2-Clause License +# + +import asyncio +import os + +from dotenv import load_dotenv +from loguru import logger + +from pipecat.audio.vad.silero import SileroVADAnalyzer +from pipecat.frames.frames import LLMRunFrame, TTSUpdateSettingsFrame +from pipecat.pipeline.pipeline import Pipeline +from pipecat.pipeline.runner import PipelineRunner +from pipecat.pipeline.task import PipelineParams, PipelineTask +from pipecat.processors.aggregators.llm_context import LLMContext +from pipecat.processors.aggregators.llm_response_universal import ( + LLMContextAggregatorPair, + LLMUserAggregatorParams, +) +from pipecat.runner.types import RunnerArguments +from pipecat.runner.utils import create_transport +from pipecat.services.deepgram.stt import DeepgramSTTService +from pipecat.services.openai.llm import OpenAILLMService +from pipecat.services.openai.tts import OpenAITTSService, OpenAITTSSettings +from pipecat.transports.base_transport import BaseTransport, TransportParams +from pipecat.transports.daily.transport import DailyParams +from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams + +load_dotenv(override=True) + +transport_params = { + "daily": lambda: DailyParams( + audio_in_enabled=True, + audio_out_enabled=True, + ), + "twilio": lambda: FastAPIWebsocketParams( + audio_in_enabled=True, + audio_out_enabled=True, + ), + "webrtc": lambda: TransportParams( + audio_in_enabled=True, + audio_out_enabled=True, + ), +} + + +async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): + logger.info(f"Starting bot") + + stt = DeepgramSTTService(api_key=os.getenv("DEEPGRAM_API_KEY")) + + tts = OpenAITTSService(api_key=os.getenv("OPENAI_API_KEY")) + + llm = OpenAILLMService(api_key=os.getenv("OPENAI_API_KEY")) + + messages = [ + { + "role": "system", + "content": "You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + }, + ] + + context = LLMContext(messages) + user_aggregator, assistant_aggregator = LLMContextAggregatorPair( + context, + user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()), + ) + + pipeline = Pipeline( + [ + transport.input(), + stt, + user_aggregator, + llm, + tts, + transport.output(), + assistant_aggregator, + ] + ) + + task = PipelineTask( + pipeline, + params=PipelineParams( + audio_out_sample_rate=24000, + enable_metrics=True, + enable_usage_metrics=True, + ), + idle_timeout_secs=runner_args.pipeline_idle_timeout_secs, + ) + + @transport.event_handler("on_client_connected") + async def on_client_connected(transport, client): + logger.info(f"Client connected") + messages.append({"role": "system", "content": "Please introduce yourself to the user."}) + await task.queue_frames([LLMRunFrame()]) + + async def update_settings(): + await asyncio.sleep(10) + logger.info("Updating OpenAI TTS settings: speed=1.5") + await task.queue_frame(TTSUpdateSettingsFrame(update=OpenAITTSSettings(speed=1.5))) + + asyncio.create_task(update_settings()) + + @transport.event_handler("on_client_disconnected") + async def on_client_disconnected(transport, client): + logger.info(f"Client disconnected") + await task.cancel() + + runner = PipelineRunner(handle_sigint=runner_args.handle_sigint) + + await runner.run(task) + + +async def bot(runner_args: RunnerArguments): + """Main bot entry point compatible with Pipecat Cloud.""" + transport = await create_transport(runner_args, transport_params) + await run_bot(transport, runner_args) + + +if __name__ == "__main__": + from pipecat.runner.run import main + + main() diff --git a/examples/foundational/55q-update-settings-deepgram-tts.py b/examples/foundational/55q-update-settings-deepgram-tts.py new file mode 100644 index 000000000..166f6fc26 --- /dev/null +++ b/examples/foundational/55q-update-settings-deepgram-tts.py @@ -0,0 +1,127 @@ +# +# Copyright (c) 2024-2026, Daily +# +# SPDX-License-Identifier: BSD 2-Clause License +# + +import asyncio +import os + +from dotenv import load_dotenv +from loguru import logger + +from pipecat.audio.vad.silero import SileroVADAnalyzer +from pipecat.frames.frames import LLMRunFrame, TTSUpdateSettingsFrame +from pipecat.pipeline.pipeline import Pipeline +from pipecat.pipeline.runner import PipelineRunner +from pipecat.pipeline.task import PipelineParams, PipelineTask +from pipecat.processors.aggregators.llm_context import LLMContext +from pipecat.processors.aggregators.llm_response_universal import ( + LLMContextAggregatorPair, + LLMUserAggregatorParams, +) +from pipecat.runner.types import RunnerArguments +from pipecat.runner.utils import create_transport +from pipecat.services.deepgram.stt import DeepgramSTTService +from pipecat.services.deepgram.tts import DeepgramTTSService, DeepgramTTSSettings +from pipecat.services.openai.llm import OpenAILLMService +from pipecat.transports.base_transport import BaseTransport, TransportParams +from pipecat.transports.daily.transport import DailyParams +from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams + +load_dotenv(override=True) + +transport_params = { + "daily": lambda: DailyParams( + audio_in_enabled=True, + audio_out_enabled=True, + ), + "twilio": lambda: FastAPIWebsocketParams( + audio_in_enabled=True, + audio_out_enabled=True, + ), + "webrtc": lambda: TransportParams( + audio_in_enabled=True, + audio_out_enabled=True, + ), +} + + +async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): + logger.info(f"Starting bot") + + stt = DeepgramSTTService(api_key=os.getenv("DEEPGRAM_API_KEY")) + + tts = DeepgramTTSService(api_key=os.getenv("DEEPGRAM_API_KEY")) + + llm = OpenAILLMService(api_key=os.getenv("OPENAI_API_KEY")) + + messages = [ + { + "role": "system", + "content": "You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + }, + ] + + context = LLMContext(messages) + user_aggregator, assistant_aggregator = LLMContextAggregatorPair( + context, + user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()), + ) + + pipeline = Pipeline( + [ + transport.input(), + stt, + user_aggregator, + llm, + tts, + transport.output(), + assistant_aggregator, + ] + ) + + task = PipelineTask( + pipeline, + params=PipelineParams( + enable_metrics=True, + enable_usage_metrics=True, + ), + idle_timeout_secs=runner_args.pipeline_idle_timeout_secs, + ) + + @transport.event_handler("on_client_connected") + async def on_client_connected(transport, client): + logger.info(f"Client connected") + messages.append({"role": "system", "content": "Please introduce yourself to the user."}) + await task.queue_frames([LLMRunFrame()]) + + async def update_settings(): + await asyncio.sleep(10) + logger.info('Updating Deepgram TTS settings: voice="aura-2-luna-en"') + await task.queue_frame( + TTSUpdateSettingsFrame(update=DeepgramTTSSettings(voice="aura-2-luna-en")) + ) + + asyncio.create_task(update_settings()) + + @transport.event_handler("on_client_disconnected") + async def on_client_disconnected(transport, client): + logger.info(f"Client disconnected") + await task.cancel() + + runner = PipelineRunner(handle_sigint=runner_args.handle_sigint) + + await runner.run(task) + + +async def bot(runner_args: RunnerArguments): + """Main bot entry point compatible with Pipecat Cloud.""" + transport = await create_transport(runner_args, transport_params) + await run_bot(transport, runner_args) + + +if __name__ == "__main__": + from pipecat.runner.run import main + + main() diff --git a/examples/foundational/55r-update-settings-azure-tts.py b/examples/foundational/55r-update-settings-azure-tts.py new file mode 100644 index 000000000..5aa63bef8 --- /dev/null +++ b/examples/foundational/55r-update-settings-azure-tts.py @@ -0,0 +1,130 @@ +# +# Copyright (c) 2024-2026, Daily +# +# SPDX-License-Identifier: BSD 2-Clause License +# + +import asyncio +import os + +from dotenv import load_dotenv +from loguru import logger + +from pipecat.audio.vad.silero import SileroVADAnalyzer +from pipecat.frames.frames import LLMRunFrame, TTSUpdateSettingsFrame +from pipecat.pipeline.pipeline import Pipeline +from pipecat.pipeline.runner import PipelineRunner +from pipecat.pipeline.task import PipelineParams, PipelineTask +from pipecat.processors.aggregators.llm_context import LLMContext +from pipecat.processors.aggregators.llm_response_universal import ( + LLMContextAggregatorPair, + LLMUserAggregatorParams, +) +from pipecat.runner.types import RunnerArguments +from pipecat.runner.utils import create_transport +from pipecat.services.azure.tts import AzureTTSService, AzureTTSSettings +from pipecat.services.deepgram.stt import DeepgramSTTService +from pipecat.services.openai.llm import OpenAILLMService +from pipecat.transports.base_transport import BaseTransport, TransportParams +from pipecat.transports.daily.transport import DailyParams +from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams + +load_dotenv(override=True) + +transport_params = { + "daily": lambda: DailyParams( + audio_in_enabled=True, + audio_out_enabled=True, + ), + "twilio": lambda: FastAPIWebsocketParams( + audio_in_enabled=True, + audio_out_enabled=True, + ), + "webrtc": lambda: TransportParams( + audio_in_enabled=True, + audio_out_enabled=True, + ), +} + + +async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): + logger.info(f"Starting bot") + + stt = DeepgramSTTService(api_key=os.getenv("DEEPGRAM_API_KEY")) + + tts = AzureTTSService( + api_key=os.getenv("AZURE_SPEECH_API_KEY"), + region=os.getenv("AZURE_SPEECH_REGION"), + ) + + llm = OpenAILLMService(api_key=os.getenv("OPENAI_API_KEY")) + + messages = [ + { + "role": "system", + "content": "You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + }, + ] + + context = LLMContext(messages) + user_aggregator, assistant_aggregator = LLMContextAggregatorPair( + context, + user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()), + ) + + pipeline = Pipeline( + [ + transport.input(), + stt, + user_aggregator, + llm, + tts, + transport.output(), + assistant_aggregator, + ] + ) + + task = PipelineTask( + pipeline, + params=PipelineParams( + enable_metrics=True, + enable_usage_metrics=True, + ), + idle_timeout_secs=runner_args.pipeline_idle_timeout_secs, + ) + + @transport.event_handler("on_client_connected") + async def on_client_connected(transport, client): + logger.info(f"Client connected") + messages.append({"role": "system", "content": "Please introduce yourself to the user."}) + await task.queue_frames([LLMRunFrame()]) + + async def update_settings(): + await asyncio.sleep(10) + logger.info('Updating Azure TTS settings: rate="1.3", style="cheerful"') + await task.queue_frame( + TTSUpdateSettingsFrame(update=AzureTTSSettings(rate="1.3", style="cheerful")) + ) + + asyncio.create_task(update_settings()) + + @transport.event_handler("on_client_disconnected") + async def on_client_disconnected(transport, client): + logger.info(f"Client disconnected") + await task.cancel() + + runner = PipelineRunner(handle_sigint=runner_args.handle_sigint) + + await runner.run(task) + + +async def bot(runner_args: RunnerArguments): + """Main bot entry point compatible with Pipecat Cloud.""" + transport = await create_transport(runner_args, transport_params) + await run_bot(transport, runner_args) + + +if __name__ == "__main__": + from pipecat.runner.run import main + + main() diff --git a/examples/foundational/55s-update-settings-google-http-tts.py b/examples/foundational/55s-update-settings-google-http-tts.py new file mode 100644 index 000000000..5033d2b28 --- /dev/null +++ b/examples/foundational/55s-update-settings-google-http-tts.py @@ -0,0 +1,127 @@ +# +# Copyright (c) 2024-2026, Daily +# +# SPDX-License-Identifier: BSD 2-Clause License +# + +import asyncio +import os + +from dotenv import load_dotenv +from loguru import logger + +from pipecat.audio.vad.silero import SileroVADAnalyzer +from pipecat.frames.frames import LLMRunFrame, TTSUpdateSettingsFrame +from pipecat.pipeline.pipeline import Pipeline +from pipecat.pipeline.runner import PipelineRunner +from pipecat.pipeline.task import PipelineParams, PipelineTask +from pipecat.processors.aggregators.llm_context import LLMContext +from pipecat.processors.aggregators.llm_response_universal import ( + LLMContextAggregatorPair, + LLMUserAggregatorParams, +) +from pipecat.runner.types import RunnerArguments +from pipecat.runner.utils import create_transport +from pipecat.services.deepgram.stt import DeepgramSTTService +from pipecat.services.google.tts import GoogleHttpTTSService, GoogleHttpTTSSettings +from pipecat.services.openai.llm import OpenAILLMService +from pipecat.transports.base_transport import BaseTransport, TransportParams +from pipecat.transports.daily.transport import DailyParams +from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams + +load_dotenv(override=True) + +transport_params = { + "daily": lambda: DailyParams( + audio_in_enabled=True, + audio_out_enabled=True, + ), + "twilio": lambda: FastAPIWebsocketParams( + audio_in_enabled=True, + audio_out_enabled=True, + ), + "webrtc": lambda: TransportParams( + audio_in_enabled=True, + audio_out_enabled=True, + ), +} + + +async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): + logger.info(f"Starting bot") + + stt = DeepgramSTTService(api_key=os.getenv("DEEPGRAM_API_KEY")) + + tts = GoogleHttpTTSService(credentials=os.getenv("GOOGLE_TEST_CREDENTIALS")) + + llm = OpenAILLMService(api_key=os.getenv("OPENAI_API_KEY")) + + messages = [ + { + "role": "system", + "content": "You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + }, + ] + + context = LLMContext(messages) + user_aggregator, assistant_aggregator = LLMContextAggregatorPair( + context, + user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()), + ) + + pipeline = Pipeline( + [ + transport.input(), + stt, + user_aggregator, + llm, + tts, + transport.output(), + assistant_aggregator, + ] + ) + + task = PipelineTask( + pipeline, + params=PipelineParams( + enable_metrics=True, + enable_usage_metrics=True, + ), + idle_timeout_secs=runner_args.pipeline_idle_timeout_secs, + ) + + @transport.event_handler("on_client_connected") + async def on_client_connected(transport, client): + logger.info(f"Client connected") + messages.append({"role": "system", "content": "Please introduce yourself to the user."}) + await task.queue_frames([LLMRunFrame()]) + + async def update_settings(): + await asyncio.sleep(10) + logger.info("Updating Google HTTP TTS settings: speaking_rate=1.4") + await task.queue_frame( + TTSUpdateSettingsFrame(update=GoogleHttpTTSSettings(speaking_rate=1.4)) + ) + + asyncio.create_task(update_settings()) + + @transport.event_handler("on_client_disconnected") + async def on_client_disconnected(transport, client): + logger.info(f"Client disconnected") + await task.cancel() + + runner = PipelineRunner(handle_sigint=runner_args.handle_sigint) + + await runner.run(task) + + +async def bot(runner_args: RunnerArguments): + """Main bot entry point compatible with Pipecat Cloud.""" + transport = await create_transport(runner_args, transport_params) + await run_bot(transport, runner_args) + + +if __name__ == "__main__": + from pipecat.runner.run import main + + main() diff --git a/examples/foundational/55t-update-settings-playht-tts.py b/examples/foundational/55t-update-settings-playht-tts.py new file mode 100644 index 000000000..37bf48897 --- /dev/null +++ b/examples/foundational/55t-update-settings-playht-tts.py @@ -0,0 +1,129 @@ +# +# Copyright (c) 2024-2026, Daily +# +# SPDX-License-Identifier: BSD 2-Clause License +# + +import asyncio +import os + +from dotenv import load_dotenv +from loguru import logger + +from pipecat.audio.vad.silero import SileroVADAnalyzer +from pipecat.frames.frames import LLMRunFrame, TTSUpdateSettingsFrame +from pipecat.pipeline.pipeline import Pipeline +from pipecat.pipeline.runner import PipelineRunner +from pipecat.pipeline.task import PipelineParams, PipelineTask +from pipecat.processors.aggregators.llm_context import LLMContext +from pipecat.processors.aggregators.llm_response_universal import ( + LLMContextAggregatorPair, + LLMUserAggregatorParams, +) +from pipecat.runner.types import RunnerArguments +from pipecat.runner.utils import create_transport +from pipecat.services.deepgram.stt import DeepgramSTTService +from pipecat.services.openai.llm import OpenAILLMService +from pipecat.services.playht.tts import PlayHTTTSService, PlayHTTTSSettings +from pipecat.transports.base_transport import BaseTransport, TransportParams +from pipecat.transports.daily.transport import DailyParams +from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams + +load_dotenv(override=True) + +transport_params = { + "daily": lambda: DailyParams( + audio_in_enabled=True, + audio_out_enabled=True, + ), + "twilio": lambda: FastAPIWebsocketParams( + audio_in_enabled=True, + audio_out_enabled=True, + ), + "webrtc": lambda: TransportParams( + audio_in_enabled=True, + audio_out_enabled=True, + ), +} + + +async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): + logger.info(f"Starting bot") + + stt = DeepgramSTTService(api_key=os.getenv("DEEPGRAM_API_KEY")) + + tts = PlayHTTTSService( + api_key=os.getenv("PLAYHT_API_KEY"), + user_id=os.getenv("PLAYHT_USER_ID"), + voice_url=os.getenv("PLAYHT_VOICE_URL", ""), + ) + + llm = OpenAILLMService(api_key=os.getenv("OPENAI_API_KEY")) + + messages = [ + { + "role": "system", + "content": "You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + }, + ] + + context = LLMContext(messages) + user_aggregator, assistant_aggregator = LLMContextAggregatorPair( + context, + user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()), + ) + + pipeline = Pipeline( + [ + transport.input(), + stt, + user_aggregator, + llm, + tts, + transport.output(), + assistant_aggregator, + ] + ) + + task = PipelineTask( + pipeline, + params=PipelineParams( + enable_metrics=True, + enable_usage_metrics=True, + ), + idle_timeout_secs=runner_args.pipeline_idle_timeout_secs, + ) + + @transport.event_handler("on_client_connected") + async def on_client_connected(transport, client): + logger.info(f"Client connected") + messages.append({"role": "system", "content": "Please introduce yourself to the user."}) + await task.queue_frames([LLMRunFrame()]) + + async def update_settings(): + await asyncio.sleep(10) + logger.info("Updating PlayHT TTS settings: speed=1.3") + await task.queue_frame(TTSUpdateSettingsFrame(update=PlayHTTTSSettings(speed=1.3))) + + asyncio.create_task(update_settings()) + + @transport.event_handler("on_client_disconnected") + async def on_client_disconnected(transport, client): + logger.info(f"Client disconnected") + await task.cancel() + + runner = PipelineRunner(handle_sigint=runner_args.handle_sigint) + + await runner.run(task) + + +async def bot(runner_args: RunnerArguments): + """Main bot entry point compatible with Pipecat Cloud.""" + transport = await create_transport(runner_args, transport_params) + await run_bot(transport, runner_args) + + +if __name__ == "__main__": + from pipecat.runner.run import main + + main() diff --git a/examples/foundational/55u-update-settings-rime-tts.py b/examples/foundational/55u-update-settings-rime-tts.py new file mode 100644 index 000000000..31de262aa --- /dev/null +++ b/examples/foundational/55u-update-settings-rime-tts.py @@ -0,0 +1,128 @@ +# +# Copyright (c) 2024-2026, Daily +# +# SPDX-License-Identifier: BSD 2-Clause License +# + +import asyncio +import os + +from dotenv import load_dotenv +from loguru import logger + +from pipecat.audio.vad.silero import SileroVADAnalyzer +from pipecat.frames.frames import LLMRunFrame, TTSUpdateSettingsFrame +from pipecat.pipeline.pipeline import Pipeline +from pipecat.pipeline.runner import PipelineRunner +from pipecat.pipeline.task import PipelineParams, PipelineTask +from pipecat.processors.aggregators.llm_context import LLMContext +from pipecat.processors.aggregators.llm_response_universal import ( + LLMContextAggregatorPair, + LLMUserAggregatorParams, +) +from pipecat.runner.types import RunnerArguments +from pipecat.runner.utils import create_transport +from pipecat.services.deepgram.stt import DeepgramSTTService +from pipecat.services.openai.llm import OpenAILLMService +from pipecat.services.rime.tts import RimeTTSService, RimeTTSSettings +from pipecat.transports.base_transport import BaseTransport, TransportParams +from pipecat.transports.daily.transport import DailyParams +from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams + +load_dotenv(override=True) + +transport_params = { + "daily": lambda: DailyParams( + audio_in_enabled=True, + audio_out_enabled=True, + ), + "twilio": lambda: FastAPIWebsocketParams( + audio_in_enabled=True, + audio_out_enabled=True, + ), + "webrtc": lambda: TransportParams( + audio_in_enabled=True, + audio_out_enabled=True, + ), +} + + +async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): + logger.info(f"Starting bot") + + stt = DeepgramSTTService(api_key=os.getenv("DEEPGRAM_API_KEY")) + + tts = RimeTTSService( + api_key=os.getenv("RIME_API_KEY"), + voice_id="eva", + ) + + llm = OpenAILLMService(api_key=os.getenv("OPENAI_API_KEY")) + + messages = [ + { + "role": "system", + "content": "You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + }, + ] + + context = LLMContext(messages) + user_aggregator, assistant_aggregator = LLMContextAggregatorPair( + context, + user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()), + ) + + pipeline = Pipeline( + [ + transport.input(), + stt, + user_aggregator, + llm, + tts, + transport.output(), + assistant_aggregator, + ] + ) + + task = PipelineTask( + pipeline, + params=PipelineParams( + enable_metrics=True, + enable_usage_metrics=True, + ), + idle_timeout_secs=runner_args.pipeline_idle_timeout_secs, + ) + + @transport.event_handler("on_client_connected") + async def on_client_connected(transport, client): + logger.info(f"Client connected") + messages.append({"role": "system", "content": "Please introduce yourself to the user."}) + await task.queue_frames([LLMRunFrame()]) + + async def update_settings(): + await asyncio.sleep(10) + logger.info("Updating Rime TTS settings: speedAlpha=1.5") + await task.queue_frame(TTSUpdateSettingsFrame(update=RimeTTSSettings(speedAlpha=1.5))) + + asyncio.create_task(update_settings()) + + @transport.event_handler("on_client_disconnected") + async def on_client_disconnected(transport, client): + logger.info(f"Client disconnected") + await task.cancel() + + runner = PipelineRunner(handle_sigint=runner_args.handle_sigint) + + await runner.run(task) + + +async def bot(runner_args: RunnerArguments): + """Main bot entry point compatible with Pipecat Cloud.""" + transport = await create_transport(runner_args, transport_params) + await run_bot(transport, runner_args) + + +if __name__ == "__main__": + from pipecat.runner.run import main + + main() diff --git a/examples/foundational/55v-update-settings-lmnt-tts.py b/examples/foundational/55v-update-settings-lmnt-tts.py new file mode 100644 index 000000000..f61026735 --- /dev/null +++ b/examples/foundational/55v-update-settings-lmnt-tts.py @@ -0,0 +1,128 @@ +# +# Copyright (c) 2024-2026, Daily +# +# SPDX-License-Identifier: BSD 2-Clause License +# + +import asyncio +import os + +from dotenv import load_dotenv +from loguru import logger + +from pipecat.audio.vad.silero import SileroVADAnalyzer +from pipecat.frames.frames import LLMRunFrame, TTSUpdateSettingsFrame +from pipecat.pipeline.pipeline import Pipeline +from pipecat.pipeline.runner import PipelineRunner +from pipecat.pipeline.task import PipelineParams, PipelineTask +from pipecat.processors.aggregators.llm_context import LLMContext +from pipecat.processors.aggregators.llm_response_universal import ( + LLMContextAggregatorPair, + LLMUserAggregatorParams, +) +from pipecat.runner.types import RunnerArguments +from pipecat.runner.utils import create_transport +from pipecat.services.deepgram.stt import DeepgramSTTService +from pipecat.services.lmnt.tts import LmntTTSService, LmntTTSSettings +from pipecat.services.openai.llm import OpenAILLMService +from pipecat.transports.base_transport import BaseTransport, TransportParams +from pipecat.transports.daily.transport import DailyParams +from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams + +load_dotenv(override=True) + +transport_params = { + "daily": lambda: DailyParams( + audio_in_enabled=True, + audio_out_enabled=True, + ), + "twilio": lambda: FastAPIWebsocketParams( + audio_in_enabled=True, + audio_out_enabled=True, + ), + "webrtc": lambda: TransportParams( + audio_in_enabled=True, + audio_out_enabled=True, + ), +} + + +async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): + logger.info(f"Starting bot") + + stt = DeepgramSTTService(api_key=os.getenv("DEEPGRAM_API_KEY")) + + tts = LmntTTSService( + api_key=os.getenv("LMNT_API_KEY"), + voice_id="lily", + ) + + llm = OpenAILLMService(api_key=os.getenv("OPENAI_API_KEY")) + + messages = [ + { + "role": "system", + "content": "You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + }, + ] + + context = LLMContext(messages) + user_aggregator, assistant_aggregator = LLMContextAggregatorPair( + context, + user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()), + ) + + pipeline = Pipeline( + [ + transport.input(), + stt, + user_aggregator, + llm, + tts, + transport.output(), + assistant_aggregator, + ] + ) + + task = PipelineTask( + pipeline, + params=PipelineParams( + enable_metrics=True, + enable_usage_metrics=True, + ), + idle_timeout_secs=runner_args.pipeline_idle_timeout_secs, + ) + + @transport.event_handler("on_client_connected") + async def on_client_connected(transport, client): + logger.info(f"Client connected") + messages.append({"role": "system", "content": "Please introduce yourself to the user."}) + await task.queue_frames([LLMRunFrame()]) + + async def update_settings(): + await asyncio.sleep(10) + logger.info('Updating LMNT TTS settings: voice="lily"') + await task.queue_frame(TTSUpdateSettingsFrame(update=LmntTTSSettings(voice="lily"))) + + asyncio.create_task(update_settings()) + + @transport.event_handler("on_client_disconnected") + async def on_client_disconnected(transport, client): + logger.info(f"Client disconnected") + await task.cancel() + + runner = PipelineRunner(handle_sigint=runner_args.handle_sigint) + + await runner.run(task) + + +async def bot(runner_args: RunnerArguments): + """Main bot entry point compatible with Pipecat Cloud.""" + transport = await create_transport(runner_args, transport_params) + await run_bot(transport, runner_args) + + +if __name__ == "__main__": + from pipecat.runner.run import main + + main() diff --git a/examples/foundational/55w-update-settings-fish-tts.py b/examples/foundational/55w-update-settings-fish-tts.py new file mode 100644 index 000000000..85d942ad7 --- /dev/null +++ b/examples/foundational/55w-update-settings-fish-tts.py @@ -0,0 +1,127 @@ +# +# Copyright (c) 2024-2026, Daily +# +# SPDX-License-Identifier: BSD 2-Clause License +# + +import asyncio +import os + +from dotenv import load_dotenv +from loguru import logger + +from pipecat.audio.vad.silero import SileroVADAnalyzer +from pipecat.frames.frames import LLMRunFrame, TTSUpdateSettingsFrame +from pipecat.pipeline.pipeline import Pipeline +from pipecat.pipeline.runner import PipelineRunner +from pipecat.pipeline.task import PipelineParams, PipelineTask +from pipecat.processors.aggregators.llm_context import LLMContext +from pipecat.processors.aggregators.llm_response_universal import ( + LLMContextAggregatorPair, + LLMUserAggregatorParams, +) +from pipecat.runner.types import RunnerArguments +from pipecat.runner.utils import create_transport +from pipecat.services.deepgram.stt import DeepgramSTTService +from pipecat.services.fish.tts import FishAudioTTSService, FishAudioTTSSettings +from pipecat.services.openai.llm import OpenAILLMService +from pipecat.transports.base_transport import BaseTransport, TransportParams +from pipecat.transports.daily.transport import DailyParams +from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams + +load_dotenv(override=True) + +transport_params = { + "daily": lambda: DailyParams( + audio_in_enabled=True, + audio_out_enabled=True, + ), + "twilio": lambda: FastAPIWebsocketParams( + audio_in_enabled=True, + audio_out_enabled=True, + ), + "webrtc": lambda: TransportParams( + audio_in_enabled=True, + audio_out_enabled=True, + ), +} + + +async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): + logger.info(f"Starting bot") + + stt = DeepgramSTTService(api_key=os.getenv("DEEPGRAM_API_KEY")) + + tts = FishAudioTTSService(api_key=os.getenv("FISH_API_KEY")) + + llm = OpenAILLMService(api_key=os.getenv("OPENAI_API_KEY")) + + messages = [ + { + "role": "system", + "content": "You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + }, + ] + + context = LLMContext(messages) + user_aggregator, assistant_aggregator = LLMContextAggregatorPair( + context, + user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()), + ) + + pipeline = Pipeline( + [ + transport.input(), + stt, + user_aggregator, + llm, + tts, + transport.output(), + assistant_aggregator, + ] + ) + + task = PipelineTask( + pipeline, + params=PipelineParams( + enable_metrics=True, + enable_usage_metrics=True, + ), + idle_timeout_secs=runner_args.pipeline_idle_timeout_secs, + ) + + @transport.event_handler("on_client_connected") + async def on_client_connected(transport, client): + logger.info(f"Client connected") + messages.append({"role": "system", "content": "Please introduce yourself to the user."}) + await task.queue_frames([LLMRunFrame()]) + + async def update_settings(): + await asyncio.sleep(10) + logger.info("Updating Fish Audio TTS settings: prosody_speed=1.5") + await task.queue_frame( + TTSUpdateSettingsFrame(update=FishAudioTTSSettings(prosody_speed=1.5)) + ) + + asyncio.create_task(update_settings()) + + @transport.event_handler("on_client_disconnected") + async def on_client_disconnected(transport, client): + logger.info(f"Client disconnected") + await task.cancel() + + runner = PipelineRunner(handle_sigint=runner_args.handle_sigint) + + await runner.run(task) + + +async def bot(runner_args: RunnerArguments): + """Main bot entry point compatible with Pipecat Cloud.""" + transport = await create_transport(runner_args, transport_params) + await run_bot(transport, runner_args) + + +if __name__ == "__main__": + from pipecat.runner.run import main + + main() diff --git a/examples/foundational/55x-update-settings-minimax-tts.py b/examples/foundational/55x-update-settings-minimax-tts.py new file mode 100644 index 000000000..f5d74b0f3 --- /dev/null +++ b/examples/foundational/55x-update-settings-minimax-tts.py @@ -0,0 +1,133 @@ +# +# Copyright (c) 2024-2026, Daily +# +# SPDX-License-Identifier: BSD 2-Clause License +# + +import asyncio +import os + +import aiohttp +from dotenv import load_dotenv +from loguru import logger + +from pipecat.audio.vad.silero import SileroVADAnalyzer +from pipecat.frames.frames import LLMRunFrame, TTSUpdateSettingsFrame +from pipecat.pipeline.pipeline import Pipeline +from pipecat.pipeline.runner import PipelineRunner +from pipecat.pipeline.task import PipelineParams, PipelineTask +from pipecat.processors.aggregators.llm_context import LLMContext +from pipecat.processors.aggregators.llm_response_universal import ( + LLMContextAggregatorPair, + LLMUserAggregatorParams, +) +from pipecat.runner.types import RunnerArguments +from pipecat.runner.utils import create_transport +from pipecat.services.deepgram.stt import DeepgramSTTService +from pipecat.services.minimax.tts import MiniMaxHttpTTSService, MiniMaxTTSSettings +from pipecat.services.openai.llm import OpenAILLMService +from pipecat.transports.base_transport import BaseTransport, TransportParams +from pipecat.transports.daily.transport import DailyParams +from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams + +load_dotenv(override=True) + +transport_params = { + "daily": lambda: DailyParams( + audio_in_enabled=True, + audio_out_enabled=True, + ), + "twilio": lambda: FastAPIWebsocketParams( + audio_in_enabled=True, + audio_out_enabled=True, + ), + "webrtc": lambda: TransportParams( + audio_in_enabled=True, + audio_out_enabled=True, + ), +} + + +async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): + logger.info(f"Starting bot") + + async with aiohttp.ClientSession() as session: + stt = DeepgramSTTService(api_key=os.getenv("DEEPGRAM_API_KEY")) + + tts = MiniMaxHttpTTSService( + api_key=os.getenv("MINIMAX_API_KEY", ""), + group_id=os.getenv("MINIMAX_GROUP_ID", ""), + aiohttp_session=session, + ) + + llm = OpenAILLMService(api_key=os.getenv("OPENAI_API_KEY")) + + messages = [ + { + "role": "system", + "content": "You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + }, + ] + + context = LLMContext(messages) + user_aggregator, assistant_aggregator = LLMContextAggregatorPair( + context, + user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()), + ) + + pipeline = Pipeline( + [ + transport.input(), + stt, + user_aggregator, + llm, + tts, + transport.output(), + assistant_aggregator, + ] + ) + + task = PipelineTask( + pipeline, + params=PipelineParams( + enable_metrics=True, + enable_usage_metrics=True, + ), + idle_timeout_secs=runner_args.pipeline_idle_timeout_secs, + ) + + @transport.event_handler("on_client_connected") + async def on_client_connected(transport, client): + logger.info(f"Client connected") + messages.append({"role": "system", "content": "Please introduce yourself to the user."}) + await task.queue_frames([LLMRunFrame()]) + + async def update_settings(): + await asyncio.sleep(10) + logger.info('Updating MiniMax TTS settings: speed=1.5, emotion="happy"') + await task.queue_frame( + TTSUpdateSettingsFrame(update=MiniMaxTTSSettings(speed=1.5, emotion="happy")) + ) + + asyncio.create_task(update_settings()) + + @transport.event_handler("on_client_disconnected") + async def on_client_disconnected(transport, client): + logger.info(f"Client disconnected") + await task.cancel() + + runner = PipelineRunner(handle_sigint=runner_args.handle_sigint) + + await runner.run(task) + + +async def bot(runner_args: RunnerArguments): + """Main bot entry point compatible with Pipecat Cloud.""" + transport = await create_transport(runner_args, transport_params) + await run_bot(transport, runner_args) + + +if __name__ == "__main__": + from pipecat.runner.run import main + + main() diff --git a/examples/foundational/55y-update-settings-groq-tts.py b/examples/foundational/55y-update-settings-groq-tts.py new file mode 100644 index 000000000..a7f4936ee --- /dev/null +++ b/examples/foundational/55y-update-settings-groq-tts.py @@ -0,0 +1,125 @@ +# +# Copyright (c) 2024-2026, Daily +# +# SPDX-License-Identifier: BSD 2-Clause License +# + +import asyncio +import os + +from dotenv import load_dotenv +from loguru import logger + +from pipecat.audio.vad.silero import SileroVADAnalyzer +from pipecat.frames.frames import LLMRunFrame, TTSUpdateSettingsFrame +from pipecat.pipeline.pipeline import Pipeline +from pipecat.pipeline.runner import PipelineRunner +from pipecat.pipeline.task import PipelineParams, PipelineTask +from pipecat.processors.aggregators.llm_context import LLMContext +from pipecat.processors.aggregators.llm_response_universal import ( + LLMContextAggregatorPair, + LLMUserAggregatorParams, +) +from pipecat.runner.types import RunnerArguments +from pipecat.runner.utils import create_transport +from pipecat.services.deepgram.stt import DeepgramSTTService +from pipecat.services.groq.tts import GroqTTSService, GroqTTSSettings +from pipecat.services.openai.llm import OpenAILLMService +from pipecat.transports.base_transport import BaseTransport, TransportParams +from pipecat.transports.daily.transport import DailyParams +from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams + +load_dotenv(override=True) + +transport_params = { + "daily": lambda: DailyParams( + audio_in_enabled=True, + audio_out_enabled=True, + ), + "twilio": lambda: FastAPIWebsocketParams( + audio_in_enabled=True, + audio_out_enabled=True, + ), + "webrtc": lambda: TransportParams( + audio_in_enabled=True, + audio_out_enabled=True, + ), +} + + +async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): + logger.info(f"Starting bot") + + stt = DeepgramSTTService(api_key=os.getenv("DEEPGRAM_API_KEY")) + + tts = GroqTTSService(api_key=os.getenv("GROQ_API_KEY")) + + llm = OpenAILLMService(api_key=os.getenv("OPENAI_API_KEY")) + + messages = [ + { + "role": "system", + "content": "You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + }, + ] + + context = LLMContext(messages) + user_aggregator, assistant_aggregator = LLMContextAggregatorPair( + context, + user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()), + ) + + pipeline = Pipeline( + [ + transport.input(), + stt, + user_aggregator, + llm, + tts, + transport.output(), + assistant_aggregator, + ] + ) + + task = PipelineTask( + pipeline, + params=PipelineParams( + enable_metrics=True, + enable_usage_metrics=True, + ), + idle_timeout_secs=runner_args.pipeline_idle_timeout_secs, + ) + + @transport.event_handler("on_client_connected") + async def on_client_connected(transport, client): + logger.info(f"Client connected") + messages.append({"role": "system", "content": "Please introduce yourself to the user."}) + await task.queue_frames([LLMRunFrame()]) + + async def update_settings(): + await asyncio.sleep(10) + logger.info("Updating Groq TTS settings: speed=1.5") + await task.queue_frame(TTSUpdateSettingsFrame(update=GroqTTSSettings(speed=1.5))) + + asyncio.create_task(update_settings()) + + @transport.event_handler("on_client_disconnected") + async def on_client_disconnected(transport, client): + logger.info(f"Client disconnected") + await task.cancel() + + runner = PipelineRunner(handle_sigint=runner_args.handle_sigint) + + await runner.run(task) + + +async def bot(runner_args: RunnerArguments): + """Main bot entry point compatible with Pipecat Cloud.""" + transport = await create_transport(runner_args, transport_params) + await run_bot(transport, runner_args) + + +if __name__ == "__main__": + from pipecat.runner.run import main + + main() diff --git a/examples/foundational/55z-update-settings-hume-tts.py b/examples/foundational/55z-update-settings-hume-tts.py new file mode 100644 index 000000000..f4ec141ca --- /dev/null +++ b/examples/foundational/55z-update-settings-hume-tts.py @@ -0,0 +1,134 @@ +# +# Copyright (c) 2024-2026, Daily +# +# SPDX-License-Identifier: BSD 2-Clause License +# + +import asyncio +import os + +from dotenv import load_dotenv +from loguru import logger + +from pipecat.audio.vad.silero import SileroVADAnalyzer +from pipecat.frames.frames import LLMRunFrame, TTSUpdateSettingsFrame +from pipecat.pipeline.pipeline import Pipeline +from pipecat.pipeline.runner import PipelineRunner +from pipecat.pipeline.task import PipelineParams, PipelineTask +from pipecat.processors.aggregators.llm_context import LLMContext +from pipecat.processors.aggregators.llm_response_universal import ( + LLMContextAggregatorPair, + LLMUserAggregatorParams, +) +from pipecat.runner.types import RunnerArguments +from pipecat.runner.utils import create_transport +from pipecat.services.deepgram.stt import DeepgramSTTService +from pipecat.services.hume.tts import HumeTTSService, HumeTTSSettings +from pipecat.services.openai.llm import OpenAILLMService +from pipecat.transports.base_transport import BaseTransport, TransportParams +from pipecat.transports.daily.transport import DailyParams +from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams + +load_dotenv(override=True) + +transport_params = { + "daily": lambda: DailyParams( + audio_in_enabled=True, + audio_out_enabled=True, + ), + "twilio": lambda: FastAPIWebsocketParams( + audio_in_enabled=True, + audio_out_enabled=True, + ), + "webrtc": lambda: TransportParams( + audio_in_enabled=True, + audio_out_enabled=True, + ), +} + + +async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): + logger.info(f"Starting bot") + + stt = DeepgramSTTService(api_key=os.getenv("DEEPGRAM_API_KEY")) + + tts = HumeTTSService( + api_key=os.getenv("HUME_API_KEY"), + voice_id="ee7ea9f8-c99a-4516-a65d-80235fa3acdc", + ) + + llm = OpenAILLMService(api_key=os.getenv("OPENAI_API_KEY")) + + messages = [ + { + "role": "system", + "content": "You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + }, + ] + + context = LLMContext(messages) + user_aggregator, assistant_aggregator = LLMContextAggregatorPair( + context, + user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()), + ) + + pipeline = Pipeline( + [ + transport.input(), + stt, + user_aggregator, + llm, + tts, + transport.output(), + assistant_aggregator, + ] + ) + + task = PipelineTask( + pipeline, + params=PipelineParams( + enable_metrics=True, + enable_usage_metrics=True, + ), + idle_timeout_secs=runner_args.pipeline_idle_timeout_secs, + ) + + @transport.event_handler("on_client_connected") + async def on_client_connected(transport, client): + logger.info(f"Client connected") + messages.append({"role": "system", "content": "Please introduce yourself to the user."}) + await task.queue_frames([LLMRunFrame()]) + + async def update_settings(): + await asyncio.sleep(10) + logger.info( + 'Updating Hume TTS settings: speed=1.5, description="Speak with excitement"' + ) + await task.queue_frame( + TTSUpdateSettingsFrame( + update=HumeTTSSettings(speed=1.5, description="Speak with excitement") + ) + ) + + asyncio.create_task(update_settings()) + + @transport.event_handler("on_client_disconnected") + async def on_client_disconnected(transport, client): + logger.info(f"Client disconnected") + await task.cancel() + + runner = PipelineRunner(handle_sigint=runner_args.handle_sigint) + + await runner.run(task) + + +async def bot(runner_args: RunnerArguments): + """Main bot entry point compatible with Pipecat Cloud.""" + transport = await create_transport(runner_args, transport_params) + await run_bot(transport, runner_args) + + +if __name__ == "__main__": + from pipecat.runner.run import main + + main() diff --git a/examples/foundational/55za-update-settings-neuphonic-tts.py b/examples/foundational/55za-update-settings-neuphonic-tts.py new file mode 100644 index 000000000..d76ba5c89 --- /dev/null +++ b/examples/foundational/55za-update-settings-neuphonic-tts.py @@ -0,0 +1,125 @@ +# +# Copyright (c) 2024-2026, Daily +# +# SPDX-License-Identifier: BSD 2-Clause License +# + +import asyncio +import os + +from dotenv import load_dotenv +from loguru import logger + +from pipecat.audio.vad.silero import SileroVADAnalyzer +from pipecat.frames.frames import LLMRunFrame, TTSUpdateSettingsFrame +from pipecat.pipeline.pipeline import Pipeline +from pipecat.pipeline.runner import PipelineRunner +from pipecat.pipeline.task import PipelineParams, PipelineTask +from pipecat.processors.aggregators.llm_context import LLMContext +from pipecat.processors.aggregators.llm_response_universal import ( + LLMContextAggregatorPair, + LLMUserAggregatorParams, +) +from pipecat.runner.types import RunnerArguments +from pipecat.runner.utils import create_transport +from pipecat.services.deepgram.stt import DeepgramSTTService +from pipecat.services.neuphonic.tts import NeuphonicTTSService, NeuphonicTTSSettings +from pipecat.services.openai.llm import OpenAILLMService +from pipecat.transports.base_transport import BaseTransport, TransportParams +from pipecat.transports.daily.transport import DailyParams +from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams + +load_dotenv(override=True) + +transport_params = { + "daily": lambda: DailyParams( + audio_in_enabled=True, + audio_out_enabled=True, + ), + "twilio": lambda: FastAPIWebsocketParams( + audio_in_enabled=True, + audio_out_enabled=True, + ), + "webrtc": lambda: TransportParams( + audio_in_enabled=True, + audio_out_enabled=True, + ), +} + + +async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): + logger.info(f"Starting bot") + + stt = DeepgramSTTService(api_key=os.getenv("DEEPGRAM_API_KEY")) + + tts = NeuphonicTTSService(api_key=os.getenv("NEUPHONIC_API_KEY")) + + llm = OpenAILLMService(api_key=os.getenv("OPENAI_API_KEY")) + + messages = [ + { + "role": "system", + "content": "You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + }, + ] + + context = LLMContext(messages) + user_aggregator, assistant_aggregator = LLMContextAggregatorPair( + context, + user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()), + ) + + pipeline = Pipeline( + [ + transport.input(), + stt, + user_aggregator, + llm, + tts, + transport.output(), + assistant_aggregator, + ] + ) + + task = PipelineTask( + pipeline, + params=PipelineParams( + enable_metrics=True, + enable_usage_metrics=True, + ), + idle_timeout_secs=runner_args.pipeline_idle_timeout_secs, + ) + + @transport.event_handler("on_client_connected") + async def on_client_connected(transport, client): + logger.info(f"Client connected") + messages.append({"role": "system", "content": "Please introduce yourself to the user."}) + await task.queue_frames([LLMRunFrame()]) + + async def update_settings(): + await asyncio.sleep(10) + logger.info("Updating Neuphonic TTS settings: speed=1.4") + await task.queue_frame(TTSUpdateSettingsFrame(update=NeuphonicTTSSettings(speed=1.4))) + + asyncio.create_task(update_settings()) + + @transport.event_handler("on_client_disconnected") + async def on_client_disconnected(transport, client): + logger.info(f"Client disconnected") + await task.cancel() + + runner = PipelineRunner(handle_sigint=runner_args.handle_sigint) + + await runner.run(task) + + +async def bot(runner_args: RunnerArguments): + """Main bot entry point compatible with Pipecat Cloud.""" + transport = await create_transport(runner_args, transport_params) + await run_bot(transport, runner_args) + + +if __name__ == "__main__": + from pipecat.runner.run import main + + main() diff --git a/examples/foundational/55zb-update-settings-inworld-tts.py b/examples/foundational/55zb-update-settings-inworld-tts.py new file mode 100644 index 000000000..159d75f8c --- /dev/null +++ b/examples/foundational/55zb-update-settings-inworld-tts.py @@ -0,0 +1,129 @@ +# +# Copyright (c) 2024-2026, Daily +# +# SPDX-License-Identifier: BSD 2-Clause License +# + +import asyncio +import os + +from dotenv import load_dotenv +from loguru import logger + +from pipecat.audio.vad.silero import SileroVADAnalyzer +from pipecat.frames.frames import LLMRunFrame, TTSUpdateSettingsFrame +from pipecat.pipeline.pipeline import Pipeline +from pipecat.pipeline.runner import PipelineRunner +from pipecat.pipeline.task import PipelineParams, PipelineTask +from pipecat.processors.aggregators.llm_context import LLMContext +from pipecat.processors.aggregators.llm_response_universal import ( + LLMContextAggregatorPair, + LLMUserAggregatorParams, +) +from pipecat.runner.types import RunnerArguments +from pipecat.runner.utils import create_transport +from pipecat.services.deepgram.stt import DeepgramSTTService +from pipecat.services.inworld.tts import InworldTTSService, InworldTTSSettings +from pipecat.services.openai.llm import OpenAILLMService +from pipecat.transports.base_transport import BaseTransport, TransportParams +from pipecat.transports.daily.transport import DailyParams +from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams + +load_dotenv(override=True) + +transport_params = { + "daily": lambda: DailyParams( + audio_in_enabled=True, + audio_out_enabled=True, + ), + "twilio": lambda: FastAPIWebsocketParams( + audio_in_enabled=True, + audio_out_enabled=True, + ), + "webrtc": lambda: TransportParams( + audio_in_enabled=True, + audio_out_enabled=True, + ), +} + + +async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): + logger.info(f"Starting bot") + + stt = DeepgramSTTService(api_key=os.getenv("DEEPGRAM_API_KEY")) + + tts = InworldTTSService(api_key=os.getenv("INWORLD_API_KEY")) + + llm = OpenAILLMService(api_key=os.getenv("OPENAI_API_KEY")) + + messages = [ + { + "role": "system", + "content": "You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + }, + ] + + context = LLMContext(messages) + user_aggregator, assistant_aggregator = LLMContextAggregatorPair( + context, + user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()), + ) + + pipeline = Pipeline( + [ + transport.input(), + stt, + user_aggregator, + llm, + tts, + transport.output(), + assistant_aggregator, + ] + ) + + task = PipelineTask( + pipeline, + params=PipelineParams( + enable_metrics=True, + enable_usage_metrics=True, + ), + idle_timeout_secs=runner_args.pipeline_idle_timeout_secs, + ) + + @transport.event_handler("on_client_connected") + async def on_client_connected(transport, client): + logger.info(f"Client connected") + messages.append({"role": "system", "content": "Please introduce yourself to the user."}) + await task.queue_frames([LLMRunFrame()]) + + async def update_settings(): + await asyncio.sleep(10) + logger.info("Updating Inworld TTS settings: speaking_rate=1.3, temperature=0.8") + await task.queue_frame( + TTSUpdateSettingsFrame( + update=InworldTTSSettings(speaking_rate=1.3, temperature=0.8) + ) + ) + + asyncio.create_task(update_settings()) + + @transport.event_handler("on_client_disconnected") + async def on_client_disconnected(transport, client): + logger.info(f"Client disconnected") + await task.cancel() + + runner = PipelineRunner(handle_sigint=runner_args.handle_sigint) + + await runner.run(task) + + +async def bot(runner_args: RunnerArguments): + """Main bot entry point compatible with Pipecat Cloud.""" + transport = await create_transport(runner_args, transport_params) + await run_bot(transport, runner_args) + + +if __name__ == "__main__": + from pipecat.runner.run import main + + main() diff --git a/examples/foundational/55zc-update-settings-gemini-tts.py b/examples/foundational/55zc-update-settings-gemini-tts.py new file mode 100644 index 000000000..958115630 --- /dev/null +++ b/examples/foundational/55zc-update-settings-gemini-tts.py @@ -0,0 +1,129 @@ +# +# Copyright (c) 2024-2026, Daily +# +# SPDX-License-Identifier: BSD 2-Clause License +# + +import asyncio +import os + +from dotenv import load_dotenv +from loguru import logger + +from pipecat.audio.vad.silero import SileroVADAnalyzer +from pipecat.frames.frames import LLMRunFrame, TTSUpdateSettingsFrame +from pipecat.pipeline.pipeline import Pipeline +from pipecat.pipeline.runner import PipelineRunner +from pipecat.pipeline.task import PipelineParams, PipelineTask +from pipecat.processors.aggregators.llm_context import LLMContext +from pipecat.processors.aggregators.llm_response_universal import ( + LLMContextAggregatorPair, + LLMUserAggregatorParams, +) +from pipecat.runner.types import RunnerArguments +from pipecat.runner.utils import create_transport +from pipecat.services.deepgram.stt import DeepgramSTTService +from pipecat.services.google.tts import GeminiTTSService, GeminiTTSSettings +from pipecat.services.openai.llm import OpenAILLMService +from pipecat.transports.base_transport import BaseTransport, TransportParams +from pipecat.transports.daily.transport import DailyParams +from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams + +load_dotenv(override=True) + +transport_params = { + "daily": lambda: DailyParams( + audio_in_enabled=True, + audio_out_enabled=True, + ), + "twilio": lambda: FastAPIWebsocketParams( + audio_in_enabled=True, + audio_out_enabled=True, + ), + "webrtc": lambda: TransportParams( + audio_in_enabled=True, + audio_out_enabled=True, + ), +} + + +async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): + logger.info(f"Starting bot") + + stt = DeepgramSTTService(api_key=os.getenv("DEEPGRAM_API_KEY")) + + tts = GeminiTTSService(api_key=os.getenv("GOOGLE_API_KEY")) + + llm = OpenAILLMService(api_key=os.getenv("OPENAI_API_KEY")) + + messages = [ + { + "role": "system", + "content": "You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + }, + ] + + context = LLMContext(messages) + user_aggregator, assistant_aggregator = LLMContextAggregatorPair( + context, + user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()), + ) + + pipeline = Pipeline( + [ + transport.input(), + stt, + user_aggregator, + llm, + tts, + transport.output(), + assistant_aggregator, + ] + ) + + task = PipelineTask( + pipeline, + params=PipelineParams( + enable_metrics=True, + enable_usage_metrics=True, + ), + idle_timeout_secs=runner_args.pipeline_idle_timeout_secs, + ) + + @transport.event_handler("on_client_connected") + async def on_client_connected(transport, client): + logger.info(f"Client connected") + messages.append({"role": "system", "content": "Please introduce yourself to the user."}) + await task.queue_frames([LLMRunFrame()]) + + async def update_settings(): + await asyncio.sleep(10) + logger.info('Updating Gemini TTS settings: prompt="Speak slowly and dramatically"') + await task.queue_frame( + TTSUpdateSettingsFrame( + update=GeminiTTSSettings(prompt="Speak slowly and dramatically") + ) + ) + + asyncio.create_task(update_settings()) + + @transport.event_handler("on_client_disconnected") + async def on_client_disconnected(transport, client): + logger.info(f"Client disconnected") + await task.cancel() + + runner = PipelineRunner(handle_sigint=runner_args.handle_sigint) + + await runner.run(task) + + +async def bot(runner_args: RunnerArguments): + """Main bot entry point compatible with Pipecat Cloud.""" + transport = await create_transport(runner_args, transport_params) + await run_bot(transport, runner_args) + + +if __name__ == "__main__": + from pipecat.runner.run import main + + main() diff --git a/examples/foundational/55zd-update-settings-aws-polly-tts.py b/examples/foundational/55zd-update-settings-aws-polly-tts.py new file mode 100644 index 000000000..951347ddd --- /dev/null +++ b/examples/foundational/55zd-update-settings-aws-polly-tts.py @@ -0,0 +1,127 @@ +# +# Copyright (c) 2024-2026, Daily +# +# SPDX-License-Identifier: BSD 2-Clause License +# + +import asyncio +import os + +from dotenv import load_dotenv +from loguru import logger + +from pipecat.audio.vad.silero import SileroVADAnalyzer +from pipecat.frames.frames import LLMRunFrame, TTSUpdateSettingsFrame +from pipecat.pipeline.pipeline import Pipeline +from pipecat.pipeline.runner import PipelineRunner +from pipecat.pipeline.task import PipelineParams, PipelineTask +from pipecat.processors.aggregators.llm_context import LLMContext +from pipecat.processors.aggregators.llm_response_universal import ( + LLMContextAggregatorPair, + LLMUserAggregatorParams, +) +from pipecat.runner.types import RunnerArguments +from pipecat.runner.utils import create_transport +from pipecat.services.aws.tts import AWSPollyTTSService, AWSPollyTTSSettings +from pipecat.services.deepgram.stt import DeepgramSTTService +from pipecat.services.openai.llm import OpenAILLMService +from pipecat.transports.base_transport import BaseTransport, TransportParams +from pipecat.transports.daily.transport import DailyParams +from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams + +load_dotenv(override=True) + +transport_params = { + "daily": lambda: DailyParams( + audio_in_enabled=True, + audio_out_enabled=True, + ), + "twilio": lambda: FastAPIWebsocketParams( + audio_in_enabled=True, + audio_out_enabled=True, + ), + "webrtc": lambda: TransportParams( + audio_in_enabled=True, + audio_out_enabled=True, + ), +} + + +async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): + logger.info(f"Starting bot") + + stt = DeepgramSTTService(api_key=os.getenv("DEEPGRAM_API_KEY")) + + tts = AWSPollyTTSService() + + llm = OpenAILLMService(api_key=os.getenv("OPENAI_API_KEY")) + + messages = [ + { + "role": "system", + "content": "You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + }, + ] + + context = LLMContext(messages) + user_aggregator, assistant_aggregator = LLMContextAggregatorPair( + context, + user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()), + ) + + pipeline = Pipeline( + [ + transport.input(), + stt, + user_aggregator, + llm, + tts, + transport.output(), + assistant_aggregator, + ] + ) + + task = PipelineTask( + pipeline, + params=PipelineParams( + enable_metrics=True, + enable_usage_metrics=True, + ), + idle_timeout_secs=runner_args.pipeline_idle_timeout_secs, + ) + + @transport.event_handler("on_client_connected") + async def on_client_connected(transport, client): + logger.info(f"Client connected") + messages.append({"role": "system", "content": "Please introduce yourself to the user."}) + await task.queue_frames([LLMRunFrame()]) + + async def update_settings(): + await asyncio.sleep(10) + logger.info('Updating AWS Polly TTS settings: rate="fast", pitch="+10%"') + await task.queue_frame( + TTSUpdateSettingsFrame(update=AWSPollyTTSSettings(rate="fast", pitch="+10%")) + ) + + asyncio.create_task(update_settings()) + + @transport.event_handler("on_client_disconnected") + async def on_client_disconnected(transport, client): + logger.info(f"Client disconnected") + await task.cancel() + + runner = PipelineRunner(handle_sigint=runner_args.handle_sigint) + + await runner.run(task) + + +async def bot(runner_args: RunnerArguments): + """Main bot entry point compatible with Pipecat Cloud.""" + transport = await create_transport(runner_args, transport_params) + await run_bot(transport, runner_args) + + +if __name__ == "__main__": + from pipecat.runner.run import main + + main() diff --git a/examples/foundational/55ze-update-settings-sarvam-tts.py b/examples/foundational/55ze-update-settings-sarvam-tts.py new file mode 100644 index 000000000..3674d2767 --- /dev/null +++ b/examples/foundational/55ze-update-settings-sarvam-tts.py @@ -0,0 +1,125 @@ +# +# Copyright (c) 2024-2026, Daily +# +# SPDX-License-Identifier: BSD 2-Clause License +# + +import asyncio +import os + +from dotenv import load_dotenv +from loguru import logger + +from pipecat.audio.vad.silero import SileroVADAnalyzer +from pipecat.frames.frames import LLMRunFrame, TTSUpdateSettingsFrame +from pipecat.pipeline.pipeline import Pipeline +from pipecat.pipeline.runner import PipelineRunner +from pipecat.pipeline.task import PipelineParams, PipelineTask +from pipecat.processors.aggregators.llm_context import LLMContext +from pipecat.processors.aggregators.llm_response_universal import ( + LLMContextAggregatorPair, + LLMUserAggregatorParams, +) +from pipecat.runner.types import RunnerArguments +from pipecat.runner.utils import create_transport +from pipecat.services.deepgram.stt import DeepgramSTTService +from pipecat.services.openai.llm import OpenAILLMService +from pipecat.services.sarvam.tts import SarvamTTSService, SarvamWSTTSSettings +from pipecat.transports.base_transport import BaseTransport, TransportParams +from pipecat.transports.daily.transport import DailyParams +from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams + +load_dotenv(override=True) + +transport_params = { + "daily": lambda: DailyParams( + audio_in_enabled=True, + audio_out_enabled=True, + ), + "twilio": lambda: FastAPIWebsocketParams( + audio_in_enabled=True, + audio_out_enabled=True, + ), + "webrtc": lambda: TransportParams( + audio_in_enabled=True, + audio_out_enabled=True, + ), +} + + +async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): + logger.info(f"Starting bot") + + stt = DeepgramSTTService(api_key=os.getenv("DEEPGRAM_API_KEY")) + + tts = SarvamTTSService(api_key=os.getenv("SARVAM_API_KEY")) + + llm = OpenAILLMService(api_key=os.getenv("OPENAI_API_KEY")) + + messages = [ + { + "role": "system", + "content": "You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + }, + ] + + context = LLMContext(messages) + user_aggregator, assistant_aggregator = LLMContextAggregatorPair( + context, + user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()), + ) + + pipeline = Pipeline( + [ + transport.input(), + stt, + user_aggregator, + llm, + tts, + transport.output(), + assistant_aggregator, + ] + ) + + task = PipelineTask( + pipeline, + params=PipelineParams( + enable_metrics=True, + enable_usage_metrics=True, + ), + idle_timeout_secs=runner_args.pipeline_idle_timeout_secs, + ) + + @transport.event_handler("on_client_connected") + async def on_client_connected(transport, client): + logger.info(f"Client connected") + messages.append({"role": "system", "content": "Please introduce yourself to the user."}) + await task.queue_frames([LLMRunFrame()]) + + async def update_settings(): + await asyncio.sleep(10) + logger.info("Updating Sarvam TTS settings: pace=1.3") + await task.queue_frame(TTSUpdateSettingsFrame(update=SarvamWSTTSSettings(pace=1.3))) + + asyncio.create_task(update_settings()) + + @transport.event_handler("on_client_disconnected") + async def on_client_disconnected(transport, client): + logger.info(f"Client disconnected") + await task.cancel() + + runner = PipelineRunner(handle_sigint=runner_args.handle_sigint) + + await runner.run(task) + + +async def bot(runner_args: RunnerArguments): + """Main bot entry point compatible with Pipecat Cloud.""" + transport = await create_transport(runner_args, transport_params) + await run_bot(transport, runner_args) + + +if __name__ == "__main__": + from pipecat.runner.run import main + + main() diff --git a/examples/foundational/55zf-update-settings-camb-tts.py b/examples/foundational/55zf-update-settings-camb-tts.py new file mode 100644 index 000000000..cc629ae03 --- /dev/null +++ b/examples/foundational/55zf-update-settings-camb-tts.py @@ -0,0 +1,129 @@ +# +# Copyright (c) 2024-2026, Daily +# +# SPDX-License-Identifier: BSD 2-Clause License +# + +import asyncio +import os + +from dotenv import load_dotenv +from loguru import logger + +from pipecat.audio.vad.silero import SileroVADAnalyzer +from pipecat.frames.frames import LLMRunFrame, TTSUpdateSettingsFrame +from pipecat.pipeline.pipeline import Pipeline +from pipecat.pipeline.runner import PipelineRunner +from pipecat.pipeline.task import PipelineParams, PipelineTask +from pipecat.processors.aggregators.llm_context import LLMContext +from pipecat.processors.aggregators.llm_response_universal import ( + LLMContextAggregatorPair, + LLMUserAggregatorParams, +) +from pipecat.runner.types import RunnerArguments +from pipecat.runner.utils import create_transport +from pipecat.services.camb.tts import CambTTSService, CambTTSSettings +from pipecat.services.deepgram.stt import DeepgramSTTService +from pipecat.services.openai.llm import OpenAILLMService +from pipecat.transports.base_transport import BaseTransport, TransportParams +from pipecat.transports.daily.transport import DailyParams +from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams + +load_dotenv(override=True) + +transport_params = { + "daily": lambda: DailyParams( + audio_in_enabled=True, + audio_out_enabled=True, + ), + "twilio": lambda: FastAPIWebsocketParams( + audio_in_enabled=True, + audio_out_enabled=True, + ), + "webrtc": lambda: TransportParams( + audio_in_enabled=True, + audio_out_enabled=True, + ), +} + + +async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): + logger.info(f"Starting bot") + + stt = DeepgramSTTService(api_key=os.getenv("DEEPGRAM_API_KEY")) + + tts = CambTTSService(api_key=os.getenv("CAMB_API_KEY")) + + llm = OpenAILLMService(api_key=os.getenv("OPENAI_API_KEY")) + + messages = [ + { + "role": "system", + "content": "You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + }, + ] + + context = LLMContext(messages) + user_aggregator, assistant_aggregator = LLMContextAggregatorPair( + context, + user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()), + ) + + pipeline = Pipeline( + [ + transport.input(), + stt, + user_aggregator, + llm, + tts, + transport.output(), + assistant_aggregator, + ] + ) + + task = PipelineTask( + pipeline, + params=PipelineParams( + enable_metrics=True, + enable_usage_metrics=True, + ), + idle_timeout_secs=runner_args.pipeline_idle_timeout_secs, + ) + + @transport.event_handler("on_client_connected") + async def on_client_connected(transport, client): + logger.info(f"Client connected") + messages.append({"role": "system", "content": "Please introduce yourself to the user."}) + await task.queue_frames([LLMRunFrame()]) + + async def update_settings(): + await asyncio.sleep(10) + logger.info('Updating Camb TTS settings: user_instructions="Speak enthusiastically"') + await task.queue_frame( + TTSUpdateSettingsFrame( + update=CambTTSSettings(user_instructions="Speak enthusiastically") + ) + ) + + asyncio.create_task(update_settings()) + + @transport.event_handler("on_client_disconnected") + async def on_client_disconnected(transport, client): + logger.info(f"Client disconnected") + await task.cancel() + + runner = PipelineRunner(handle_sigint=runner_args.handle_sigint) + + await runner.run(task) + + +async def bot(runner_args: RunnerArguments): + """Main bot entry point compatible with Pipecat Cloud.""" + transport = await create_transport(runner_args, transport_params) + await run_bot(transport, runner_args) + + +if __name__ == "__main__": + from pipecat.runner.run import main + + main() diff --git a/examples/foundational/55zg-update-settings-hathora-tts.py b/examples/foundational/55zg-update-settings-hathora-tts.py new file mode 100644 index 000000000..2c59029b8 --- /dev/null +++ b/examples/foundational/55zg-update-settings-hathora-tts.py @@ -0,0 +1,128 @@ +# +# Copyright (c) 2024-2026, Daily +# +# SPDX-License-Identifier: BSD 2-Clause License +# + +import asyncio +import os + +from dotenv import load_dotenv +from loguru import logger + +from pipecat.audio.vad.silero import SileroVADAnalyzer +from pipecat.frames.frames import LLMRunFrame, TTSUpdateSettingsFrame +from pipecat.pipeline.pipeline import Pipeline +from pipecat.pipeline.runner import PipelineRunner +from pipecat.pipeline.task import PipelineParams, PipelineTask +from pipecat.processors.aggregators.llm_context import LLMContext +from pipecat.processors.aggregators.llm_response_universal import ( + LLMContextAggregatorPair, + LLMUserAggregatorParams, +) +from pipecat.runner.types import RunnerArguments +from pipecat.runner.utils import create_transport +from pipecat.services.deepgram.stt import DeepgramSTTService +from pipecat.services.hathora.tts import HathoraTTSService, HathoraTTSSettings +from pipecat.services.openai.llm import OpenAILLMService +from pipecat.transports.base_transport import BaseTransport, TransportParams +from pipecat.transports.daily.transport import DailyParams +from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams + +load_dotenv(override=True) + +transport_params = { + "daily": lambda: DailyParams( + audio_in_enabled=True, + audio_out_enabled=True, + ), + "twilio": lambda: FastAPIWebsocketParams( + audio_in_enabled=True, + audio_out_enabled=True, + ), + "webrtc": lambda: TransportParams( + audio_in_enabled=True, + audio_out_enabled=True, + ), +} + + +async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): + logger.info(f"Starting bot") + + stt = DeepgramSTTService(api_key=os.getenv("DEEPGRAM_API_KEY")) + + tts = HathoraTTSService( + api_key=os.getenv("HATHORA_API_KEY"), + model="hathora-ai/polar", + ) + + llm = OpenAILLMService(api_key=os.getenv("OPENAI_API_KEY")) + + messages = [ + { + "role": "system", + "content": "You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + }, + ] + + context = LLMContext(messages) + user_aggregator, assistant_aggregator = LLMContextAggregatorPair( + context, + user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()), + ) + + pipeline = Pipeline( + [ + transport.input(), + stt, + user_aggregator, + llm, + tts, + transport.output(), + assistant_aggregator, + ] + ) + + task = PipelineTask( + pipeline, + params=PipelineParams( + enable_metrics=True, + enable_usage_metrics=True, + ), + idle_timeout_secs=runner_args.pipeline_idle_timeout_secs, + ) + + @transport.event_handler("on_client_connected") + async def on_client_connected(transport, client): + logger.info(f"Client connected") + messages.append({"role": "system", "content": "Please introduce yourself to the user."}) + await task.queue_frames([LLMRunFrame()]) + + async def update_settings(): + await asyncio.sleep(10) + logger.info("Updating Hathora TTS settings: speed=1.3") + await task.queue_frame(TTSUpdateSettingsFrame(update=HathoraTTSSettings(speed=1.3))) + + asyncio.create_task(update_settings()) + + @transport.event_handler("on_client_disconnected") + async def on_client_disconnected(transport, client): + logger.info(f"Client disconnected") + await task.cancel() + + runner = PipelineRunner(handle_sigint=runner_args.handle_sigint) + + await runner.run(task) + + +async def bot(runner_args: RunnerArguments): + """Main bot entry point compatible with Pipecat Cloud.""" + transport = await create_transport(runner_args, transport_params) + await run_bot(transport, runner_args) + + +if __name__ == "__main__": + from pipecat.runner.run import main + + main() diff --git a/examples/foundational/55zh-update-settings-resembleai-tts.py b/examples/foundational/55zh-update-settings-resembleai-tts.py new file mode 100644 index 000000000..39ab30eee --- /dev/null +++ b/examples/foundational/55zh-update-settings-resembleai-tts.py @@ -0,0 +1,132 @@ +# +# Copyright (c) 2024-2026, Daily +# +# SPDX-License-Identifier: BSD 2-Clause License +# + +import asyncio +import os + +from dotenv import load_dotenv +from loguru import logger + +from pipecat.audio.vad.silero import SileroVADAnalyzer +from pipecat.frames.frames import LLMRunFrame, TTSUpdateSettingsFrame +from pipecat.pipeline.pipeline import Pipeline +from pipecat.pipeline.runner import PipelineRunner +from pipecat.pipeline.task import PipelineParams, PipelineTask +from pipecat.processors.aggregators.llm_context import LLMContext +from pipecat.processors.aggregators.llm_response_universal import ( + LLMContextAggregatorPair, + LLMUserAggregatorParams, +) +from pipecat.runner.types import RunnerArguments +from pipecat.runner.utils import create_transport +from pipecat.services.deepgram.stt import DeepgramSTTService +from pipecat.services.openai.llm import OpenAILLMService +from pipecat.services.resembleai.tts import ResembleAITTSService, ResembleAITTSSettings +from pipecat.transports.base_transport import BaseTransport, TransportParams +from pipecat.transports.daily.transport import DailyParams +from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams + +load_dotenv(override=True) + +transport_params = { + "daily": lambda: DailyParams( + audio_in_enabled=True, + audio_out_enabled=True, + ), + "twilio": lambda: FastAPIWebsocketParams( + audio_in_enabled=True, + audio_out_enabled=True, + ), + "webrtc": lambda: TransportParams( + audio_in_enabled=True, + audio_out_enabled=True, + ), +} + + +async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): + logger.info(f"Starting bot") + + stt = DeepgramSTTService(api_key=os.getenv("DEEPGRAM_API_KEY")) + + tts = ResembleAITTSService( + api_key=os.getenv("RESEMBLEAI_API_KEY"), + voice_id=os.getenv("RESEMBLEAI_VOICE_ID", ""), + ) + + llm = OpenAILLMService(api_key=os.getenv("OPENAI_API_KEY")) + + messages = [ + { + "role": "system", + "content": "You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + }, + ] + + context = LLMContext(messages) + user_aggregator, assistant_aggregator = LLMContextAggregatorPair( + context, + user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()), + ) + + pipeline = Pipeline( + [ + transport.input(), + stt, + user_aggregator, + llm, + tts, + transport.output(), + assistant_aggregator, + ] + ) + + task = PipelineTask( + pipeline, + params=PipelineParams( + enable_metrics=True, + enable_usage_metrics=True, + ), + idle_timeout_secs=runner_args.pipeline_idle_timeout_secs, + ) + + @transport.event_handler("on_client_connected") + async def on_client_connected(transport, client): + logger.info(f"Client connected") + messages.append({"role": "system", "content": "Please introduce yourself to the user."}) + await task.queue_frames([LLMRunFrame()]) + + async def update_settings(): + await asyncio.sleep(10) + logger.info("Updating ResembleAI TTS settings: voice (changed)") + await task.queue_frame( + TTSUpdateSettingsFrame( + update=ResembleAITTSSettings(voice=os.getenv("RESEMBLEAI_VOICE_ID_ALT", "")) + ) + ) + + asyncio.create_task(update_settings()) + + @transport.event_handler("on_client_disconnected") + async def on_client_disconnected(transport, client): + logger.info(f"Client disconnected") + await task.cancel() + + runner = PipelineRunner(handle_sigint=runner_args.handle_sigint) + + await runner.run(task) + + +async def bot(runner_args: RunnerArguments): + """Main bot entry point compatible with Pipecat Cloud.""" + transport = await create_transport(runner_args, transport_params) + await run_bot(transport, runner_args) + + +if __name__ == "__main__": + from pipecat.runner.run import main + + main() diff --git a/examples/foundational/55zi-update-settings-openai-llm.py b/examples/foundational/55zi-update-settings-openai-llm.py new file mode 100644 index 000000000..d4befeddb --- /dev/null +++ b/examples/foundational/55zi-update-settings-openai-llm.py @@ -0,0 +1,131 @@ +# +# Copyright (c) 2024-2026, Daily +# +# SPDX-License-Identifier: BSD 2-Clause License +# + +import asyncio +import os + +from dotenv import load_dotenv +from loguru import logger + +from pipecat.audio.vad.silero import SileroVADAnalyzer +from pipecat.frames.frames import LLMRunFrame, LLMUpdateSettingsFrame +from pipecat.pipeline.pipeline import Pipeline +from pipecat.pipeline.runner import PipelineRunner +from pipecat.pipeline.task import PipelineParams, PipelineTask +from pipecat.processors.aggregators.llm_context import LLMContext +from pipecat.processors.aggregators.llm_response_universal import ( + LLMContextAggregatorPair, + LLMUserAggregatorParams, +) +from pipecat.runner.types import RunnerArguments +from pipecat.runner.utils import create_transport +from pipecat.services.cartesia.tts import CartesiaTTSService +from pipecat.services.deepgram.stt import DeepgramSTTService +from pipecat.services.openai.base_llm import OpenAILLMSettings +from pipecat.services.openai.llm import OpenAILLMService +from pipecat.transports.base_transport import BaseTransport, TransportParams +from pipecat.transports.daily.transport import DailyParams +from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams + +load_dotenv(override=True) + +transport_params = { + "daily": lambda: DailyParams( + audio_in_enabled=True, + audio_out_enabled=True, + ), + "twilio": lambda: FastAPIWebsocketParams( + audio_in_enabled=True, + audio_out_enabled=True, + ), + "webrtc": lambda: TransportParams( + audio_in_enabled=True, + audio_out_enabled=True, + ), +} + + +async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): + logger.info(f"Starting bot") + + stt = DeepgramSTTService(api_key=os.getenv("DEEPGRAM_API_KEY")) + + tts = CartesiaTTSService( + api_key=os.getenv("CARTESIA_API_KEY"), + voice_id="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady + ) + + llm = OpenAILLMService(api_key=os.getenv("OPENAI_API_KEY")) + + messages = [ + { + "role": "system", + "content": "You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + }, + ] + + context = LLMContext(messages) + user_aggregator, assistant_aggregator = LLMContextAggregatorPair( + context, + user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()), + ) + + pipeline = Pipeline( + [ + transport.input(), + stt, + user_aggregator, + llm, + tts, + transport.output(), + assistant_aggregator, + ] + ) + + task = PipelineTask( + pipeline, + params=PipelineParams( + enable_metrics=True, + enable_usage_metrics=True, + ), + idle_timeout_secs=runner_args.pipeline_idle_timeout_secs, + ) + + @transport.event_handler("on_client_connected") + async def on_client_connected(transport, client): + logger.info(f"Client connected") + messages.append({"role": "system", "content": "Please introduce yourself to the user."}) + await task.queue_frames([LLMRunFrame()]) + + async def update_settings(): + await asyncio.sleep(10) + logger.info("Updating OpenAI LLM settings: temperature=0.1") + await task.queue_frame( + LLMUpdateSettingsFrame(update=OpenAILLMSettings(temperature=0.1)) + ) + + asyncio.create_task(update_settings()) + + @transport.event_handler("on_client_disconnected") + async def on_client_disconnected(transport, client): + logger.info(f"Client disconnected") + await task.cancel() + + runner = PipelineRunner(handle_sigint=runner_args.handle_sigint) + + await runner.run(task) + + +async def bot(runner_args: RunnerArguments): + """Main bot entry point compatible with Pipecat Cloud.""" + transport = await create_transport(runner_args, transport_params) + await run_bot(transport, runner_args) + + +if __name__ == "__main__": + from pipecat.runner.run import main + + main() diff --git a/examples/foundational/55zj-update-settings-anthropic-llm.py b/examples/foundational/55zj-update-settings-anthropic-llm.py new file mode 100644 index 000000000..e2a2af3db --- /dev/null +++ b/examples/foundational/55zj-update-settings-anthropic-llm.py @@ -0,0 +1,130 @@ +# +# Copyright (c) 2024-2026, Daily +# +# SPDX-License-Identifier: BSD 2-Clause License +# + +import asyncio +import os + +from dotenv import load_dotenv +from loguru import logger + +from pipecat.audio.vad.silero import SileroVADAnalyzer +from pipecat.frames.frames import LLMRunFrame, LLMUpdateSettingsFrame +from pipecat.pipeline.pipeline import Pipeline +from pipecat.pipeline.runner import PipelineRunner +from pipecat.pipeline.task import PipelineParams, PipelineTask +from pipecat.processors.aggregators.llm_context import LLMContext +from pipecat.processors.aggregators.llm_response_universal import ( + LLMContextAggregatorPair, + LLMUserAggregatorParams, +) +from pipecat.runner.types import RunnerArguments +from pipecat.runner.utils import create_transport +from pipecat.services.anthropic.llm import AnthropicLLMService, AnthropicLLMSettings +from pipecat.services.cartesia.tts import CartesiaTTSService +from pipecat.services.deepgram.stt import DeepgramSTTService +from pipecat.transports.base_transport import BaseTransport, TransportParams +from pipecat.transports.daily.transport import DailyParams +from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams + +load_dotenv(override=True) + +transport_params = { + "daily": lambda: DailyParams( + audio_in_enabled=True, + audio_out_enabled=True, + ), + "twilio": lambda: FastAPIWebsocketParams( + audio_in_enabled=True, + audio_out_enabled=True, + ), + "webrtc": lambda: TransportParams( + audio_in_enabled=True, + audio_out_enabled=True, + ), +} + + +async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): + logger.info(f"Starting bot") + + stt = DeepgramSTTService(api_key=os.getenv("DEEPGRAM_API_KEY")) + + tts = CartesiaTTSService( + api_key=os.getenv("CARTESIA_API_KEY"), + voice_id="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady + ) + + llm = AnthropicLLMService(api_key=os.getenv("ANTHROPIC_API_KEY")) + + messages = [ + { + "role": "system", + "content": "You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + }, + ] + + context = LLMContext(messages) + user_aggregator, assistant_aggregator = LLMContextAggregatorPair( + context, + user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()), + ) + + pipeline = Pipeline( + [ + transport.input(), + stt, + user_aggregator, + llm, + tts, + transport.output(), + assistant_aggregator, + ] + ) + + task = PipelineTask( + pipeline, + params=PipelineParams( + enable_metrics=True, + enable_usage_metrics=True, + ), + idle_timeout_secs=runner_args.pipeline_idle_timeout_secs, + ) + + @transport.event_handler("on_client_connected") + async def on_client_connected(transport, client): + logger.info(f"Client connected") + messages.append({"role": "system", "content": "Please introduce yourself to the user."}) + await task.queue_frames([LLMRunFrame()]) + + async def update_settings(): + await asyncio.sleep(10) + logger.info("Updating Anthropic LLM settings: temperature=0.1") + await task.queue_frame( + LLMUpdateSettingsFrame(update=AnthropicLLMSettings(temperature=0.1)) + ) + + asyncio.create_task(update_settings()) + + @transport.event_handler("on_client_disconnected") + async def on_client_disconnected(transport, client): + logger.info(f"Client disconnected") + await task.cancel() + + runner = PipelineRunner(handle_sigint=runner_args.handle_sigint) + + await runner.run(task) + + +async def bot(runner_args: RunnerArguments): + """Main bot entry point compatible with Pipecat Cloud.""" + transport = await create_transport(runner_args, transport_params) + await run_bot(transport, runner_args) + + +if __name__ == "__main__": + from pipecat.runner.run import main + + main() diff --git a/examples/foundational/55zk-update-settings-google-llm.py b/examples/foundational/55zk-update-settings-google-llm.py new file mode 100644 index 000000000..6d7ba9573 --- /dev/null +++ b/examples/foundational/55zk-update-settings-google-llm.py @@ -0,0 +1,130 @@ +# +# Copyright (c) 2024-2026, Daily +# +# SPDX-License-Identifier: BSD 2-Clause License +# + +import asyncio +import os + +from dotenv import load_dotenv +from loguru import logger + +from pipecat.audio.vad.silero import SileroVADAnalyzer +from pipecat.frames.frames import LLMRunFrame, LLMUpdateSettingsFrame +from pipecat.pipeline.pipeline import Pipeline +from pipecat.pipeline.runner import PipelineRunner +from pipecat.pipeline.task import PipelineParams, PipelineTask +from pipecat.processors.aggregators.llm_context import LLMContext +from pipecat.processors.aggregators.llm_response_universal import ( + LLMContextAggregatorPair, + LLMUserAggregatorParams, +) +from pipecat.runner.types import RunnerArguments +from pipecat.runner.utils import create_transport +from pipecat.services.cartesia.tts import CartesiaTTSService +from pipecat.services.deepgram.stt import DeepgramSTTService +from pipecat.services.google.llm import GoogleLLMService, GoogleLLMSettings +from pipecat.transports.base_transport import BaseTransport, TransportParams +from pipecat.transports.daily.transport import DailyParams +from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams + +load_dotenv(override=True) + +transport_params = { + "daily": lambda: DailyParams( + audio_in_enabled=True, + audio_out_enabled=True, + ), + "twilio": lambda: FastAPIWebsocketParams( + audio_in_enabled=True, + audio_out_enabled=True, + ), + "webrtc": lambda: TransportParams( + audio_in_enabled=True, + audio_out_enabled=True, + ), +} + + +async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): + logger.info(f"Starting bot") + + stt = DeepgramSTTService(api_key=os.getenv("DEEPGRAM_API_KEY")) + + tts = CartesiaTTSService( + api_key=os.getenv("CARTESIA_API_KEY"), + voice_id="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady + ) + + llm = GoogleLLMService(api_key=os.getenv("GOOGLE_API_KEY")) + + messages = [ + { + "role": "system", + "content": "You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + }, + ] + + context = LLMContext(messages) + user_aggregator, assistant_aggregator = LLMContextAggregatorPair( + context, + user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()), + ) + + pipeline = Pipeline( + [ + transport.input(), + stt, + user_aggregator, + llm, + tts, + transport.output(), + assistant_aggregator, + ] + ) + + task = PipelineTask( + pipeline, + params=PipelineParams( + enable_metrics=True, + enable_usage_metrics=True, + ), + idle_timeout_secs=runner_args.pipeline_idle_timeout_secs, + ) + + @transport.event_handler("on_client_connected") + async def on_client_connected(transport, client): + logger.info(f"Client connected") + messages.append({"role": "system", "content": "Please introduce yourself to the user."}) + await task.queue_frames([LLMRunFrame()]) + + async def update_settings(): + await asyncio.sleep(10) + logger.info("Updating Google LLM settings: temperature=0.1") + await task.queue_frame( + LLMUpdateSettingsFrame(update=GoogleLLMSettings(temperature=0.1)) + ) + + asyncio.create_task(update_settings()) + + @transport.event_handler("on_client_disconnected") + async def on_client_disconnected(transport, client): + logger.info(f"Client disconnected") + await task.cancel() + + runner = PipelineRunner(handle_sigint=runner_args.handle_sigint) + + await runner.run(task) + + +async def bot(runner_args: RunnerArguments): + """Main bot entry point compatible with Pipecat Cloud.""" + transport = await create_transport(runner_args, transport_params) + await run_bot(transport, runner_args) + + +if __name__ == "__main__": + from pipecat.runner.run import main + + main() diff --git a/examples/foundational/55zl-update-settings-openai-realtime.py b/examples/foundational/55zl-update-settings-openai-realtime.py new file mode 100644 index 000000000..9f6daadfd --- /dev/null +++ b/examples/foundational/55zl-update-settings-openai-realtime.py @@ -0,0 +1,118 @@ +# +# Copyright (c) 2024-2026, Daily +# +# SPDX-License-Identifier: BSD 2-Clause License +# + +import asyncio +import os + +from dotenv import load_dotenv +from loguru import logger + +from pipecat.audio.vad.silero import SileroVADAnalyzer +from pipecat.frames.frames import LLMRunFrame, LLMUpdateSettingsFrame +from pipecat.pipeline.pipeline import Pipeline +from pipecat.pipeline.runner import PipelineRunner +from pipecat.pipeline.task import PipelineParams, PipelineTask +from pipecat.processors.aggregators.llm_context import LLMContext +from pipecat.processors.aggregators.llm_response_universal import LLMContextAggregatorPair +from pipecat.runner.types import RunnerArguments +from pipecat.runner.utils import create_transport +from pipecat.services.openai.realtime.llm import ( + OpenAIRealtimeLLMService, + OpenAIRealtimeLLMSettings, +) +from pipecat.transports.base_transport import BaseTransport, TransportParams +from pipecat.transports.daily.transport import DailyParams +from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams + +load_dotenv(override=True) + +transport_params = { + "daily": lambda: DailyParams( + audio_in_enabled=True, + audio_out_enabled=True, + vad_analyzer=SileroVADAnalyzer(), + ), + "twilio": lambda: FastAPIWebsocketParams( + audio_in_enabled=True, + audio_out_enabled=True, + vad_analyzer=SileroVADAnalyzer(), + ), + "webrtc": lambda: TransportParams( + audio_in_enabled=True, + audio_out_enabled=True, + vad_analyzer=SileroVADAnalyzer(), + ), +} + + +async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): + logger.info(f"Starting bot") + + llm = OpenAIRealtimeLLMService(api_key=os.getenv("OPENAI_API_KEY")) + + messages = [ + { + "role": "system", + "content": "You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + }, + ] + + context = LLMContext(messages) + user_aggregator, assistant_aggregator = LLMContextAggregatorPair(context) + + pipeline = Pipeline( + [ + transport.input(), + user_aggregator, + llm, + transport.output(), + assistant_aggregator, + ] + ) + + task = PipelineTask( + pipeline, + params=PipelineParams( + enable_metrics=True, + enable_usage_metrics=True, + ), + idle_timeout_secs=runner_args.pipeline_idle_timeout_secs, + ) + + @transport.event_handler("on_client_connected") + async def on_client_connected(transport, client): + logger.info(f"Client connected") + await task.queue_frames([LLMRunFrame()]) + + async def update_settings(): + await asyncio.sleep(10) + logger.info("Updating OpenAI Realtime LLM settings: temperature=0.1") + await task.queue_frame( + LLMUpdateSettingsFrame(update=OpenAIRealtimeLLMSettings(temperature=0.1)) + ) + + asyncio.create_task(update_settings()) + + @transport.event_handler("on_client_disconnected") + async def on_client_disconnected(transport, client): + logger.info(f"Client disconnected") + await task.cancel() + + runner = PipelineRunner(handle_sigint=runner_args.handle_sigint) + + await runner.run(task) + + +async def bot(runner_args: RunnerArguments): + """Main bot entry point compatible with Pipecat Cloud.""" + transport = await create_transport(runner_args, transport_params) + await run_bot(transport, runner_args) + + +if __name__ == "__main__": + from pipecat.runner.run import main + + main() diff --git a/examples/foundational/55zm-update-settings-gemini-live.py b/examples/foundational/55zm-update-settings-gemini-live.py new file mode 100644 index 000000000..0a5b38529 --- /dev/null +++ b/examples/foundational/55zm-update-settings-gemini-live.py @@ -0,0 +1,118 @@ +# +# Copyright (c) 2024-2026, Daily +# +# SPDX-License-Identifier: BSD 2-Clause License +# + +import asyncio +import os + +from dotenv import load_dotenv +from loguru import logger + +from pipecat.audio.vad.silero import SileroVADAnalyzer +from pipecat.frames.frames import LLMRunFrame, LLMUpdateSettingsFrame +from pipecat.pipeline.pipeline import Pipeline +from pipecat.pipeline.runner import PipelineRunner +from pipecat.pipeline.task import PipelineParams, PipelineTask +from pipecat.processors.aggregators.llm_context import LLMContext +from pipecat.processors.aggregators.llm_response_universal import LLMContextAggregatorPair +from pipecat.runner.types import RunnerArguments +from pipecat.runner.utils import create_transport +from pipecat.services.google.gemini_live.llm import ( + GeminiLiveLLMService, + GeminiLiveLLMSettings, +) +from pipecat.transports.base_transport import BaseTransport, TransportParams +from pipecat.transports.daily.transport import DailyParams +from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams + +load_dotenv(override=True) + +transport_params = { + "daily": lambda: DailyParams( + audio_in_enabled=True, + audio_out_enabled=True, + vad_analyzer=SileroVADAnalyzer(), + ), + "twilio": lambda: FastAPIWebsocketParams( + audio_in_enabled=True, + audio_out_enabled=True, + vad_analyzer=SileroVADAnalyzer(), + ), + "webrtc": lambda: TransportParams( + audio_in_enabled=True, + audio_out_enabled=True, + vad_analyzer=SileroVADAnalyzer(), + ), +} + + +async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): + logger.info(f"Starting bot") + + llm = GeminiLiveLLMService(api_key=os.getenv("GOOGLE_API_KEY")) + + messages = [ + { + "role": "system", + "content": "You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + }, + ] + + context = LLMContext(messages) + user_aggregator, assistant_aggregator = LLMContextAggregatorPair(context) + + pipeline = Pipeline( + [ + transport.input(), + user_aggregator, + llm, + transport.output(), + assistant_aggregator, + ] + ) + + task = PipelineTask( + pipeline, + params=PipelineParams( + enable_metrics=True, + enable_usage_metrics=True, + ), + idle_timeout_secs=runner_args.pipeline_idle_timeout_secs, + ) + + @transport.event_handler("on_client_connected") + async def on_client_connected(transport, client): + logger.info(f"Client connected") + await task.queue_frames([LLMRunFrame()]) + + async def update_settings(): + await asyncio.sleep(10) + logger.info("Updating Gemini Live LLM settings: temperature=0.1") + await task.queue_frame( + LLMUpdateSettingsFrame(update=GeminiLiveLLMSettings(temperature=0.1)) + ) + + asyncio.create_task(update_settings()) + + @transport.event_handler("on_client_disconnected") + async def on_client_disconnected(transport, client): + logger.info(f"Client disconnected") + await task.cancel() + + runner = PipelineRunner(handle_sigint=runner_args.handle_sigint) + + await runner.run(task) + + +async def bot(runner_args: RunnerArguments): + """Main bot entry point compatible with Pipecat Cloud.""" + transport = await create_transport(runner_args, transport_params) + await run_bot(transport, runner_args) + + +if __name__ == "__main__": + from pipecat.runner.run import main + + main() diff --git a/examples/foundational/55zn-update-settings-ultravox-realtime.py b/examples/foundational/55zn-update-settings-ultravox-realtime.py new file mode 100644 index 000000000..7fcb25d83 --- /dev/null +++ b/examples/foundational/55zn-update-settings-ultravox-realtime.py @@ -0,0 +1,124 @@ +# +# Copyright (c) 2024-2026, Daily +# +# SPDX-License-Identifier: BSD 2-Clause License +# + +import asyncio +import os + +from dotenv import load_dotenv +from loguru import logger + +from pipecat.audio.vad.silero import SileroVADAnalyzer +from pipecat.frames.frames import LLMRunFrame, LLMUpdateSettingsFrame +from pipecat.pipeline.pipeline import Pipeline +from pipecat.pipeline.runner import PipelineRunner +from pipecat.pipeline.task import PipelineParams, PipelineTask +from pipecat.processors.aggregators.llm_context import LLMContext +from pipecat.processors.aggregators.llm_response_universal import LLMContextAggregatorPair +from pipecat.runner.types import RunnerArguments +from pipecat.runner.utils import create_transport +from pipecat.services.ultravox.llm import ( + OneShotInputParams, + UltravoxRealtimeLLMService, + UltravoxRealtimeLLMSettings, +) +from pipecat.transports.base_transport import BaseTransport, TransportParams +from pipecat.transports.daily.transport import DailyParams +from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams + +load_dotenv(override=True) + +transport_params = { + "daily": lambda: DailyParams( + audio_in_enabled=True, + audio_out_enabled=True, + vad_analyzer=SileroVADAnalyzer(), + ), + "twilio": lambda: FastAPIWebsocketParams( + audio_in_enabled=True, + audio_out_enabled=True, + vad_analyzer=SileroVADAnalyzer(), + ), + "webrtc": lambda: TransportParams( + audio_in_enabled=True, + audio_out_enabled=True, + vad_analyzer=SileroVADAnalyzer(), + ), +} + + +async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): + logger.info(f"Starting bot") + + llm = UltravoxRealtimeLLMService( + params=OneShotInputParams( + api_key=os.getenv("ULTRAVOX_API_KEY"), + system_prompt="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + ), + ) + + messages = [ + { + "role": "system", + "content": "You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + }, + ] + + context = LLMContext(messages) + user_aggregator, assistant_aggregator = LLMContextAggregatorPair(context) + + pipeline = Pipeline( + [ + transport.input(), + user_aggregator, + llm, + transport.output(), + assistant_aggregator, + ] + ) + + task = PipelineTask( + pipeline, + params=PipelineParams( + enable_metrics=True, + enable_usage_metrics=True, + ), + idle_timeout_secs=runner_args.pipeline_idle_timeout_secs, + ) + + @transport.event_handler("on_client_connected") + async def on_client_connected(transport, client): + logger.info(f"Client connected") + await task.queue_frames([LLMRunFrame()]) + + async def update_settings(): + await asyncio.sleep(10) + logger.info("Updating Ultravox Realtime LLM settings: temperature=0.1") + await task.queue_frame( + LLMUpdateSettingsFrame(update=UltravoxRealtimeLLMSettings(temperature=0.1)) + ) + + asyncio.create_task(update_settings()) + + @transport.event_handler("on_client_disconnected") + async def on_client_disconnected(transport, client): + logger.info(f"Client disconnected") + await task.cancel() + + runner = PipelineRunner(handle_sigint=runner_args.handle_sigint) + + await runner.run(task) + + +async def bot(runner_args: RunnerArguments): + """Main bot entry point compatible with Pipecat Cloud.""" + transport = await create_transport(runner_args, transport_params) + await run_bot(transport, runner_args) + + +if __name__ == "__main__": + from pipecat.runner.run import main + + main() diff --git a/examples/foundational/55zo-update-settings-grok-realtime.py b/examples/foundational/55zo-update-settings-grok-realtime.py new file mode 100644 index 000000000..6366ee933 --- /dev/null +++ b/examples/foundational/55zo-update-settings-grok-realtime.py @@ -0,0 +1,118 @@ +# +# Copyright (c) 2024-2026, Daily +# +# SPDX-License-Identifier: BSD 2-Clause License +# + +import asyncio +import os + +from dotenv import load_dotenv +from loguru import logger + +from pipecat.audio.vad.silero import SileroVADAnalyzer +from pipecat.frames.frames import LLMRunFrame, LLMUpdateSettingsFrame +from pipecat.pipeline.pipeline import Pipeline +from pipecat.pipeline.runner import PipelineRunner +from pipecat.pipeline.task import PipelineParams, PipelineTask +from pipecat.processors.aggregators.llm_context import LLMContext +from pipecat.processors.aggregators.llm_response_universal import LLMContextAggregatorPair +from pipecat.runner.types import RunnerArguments +from pipecat.runner.utils import create_transport +from pipecat.services.grok.realtime.llm import ( + GrokRealtimeLLMService, + GrokRealtimeLLMSettings, +) +from pipecat.transports.base_transport import BaseTransport, TransportParams +from pipecat.transports.daily.transport import DailyParams +from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams + +load_dotenv(override=True) + +transport_params = { + "daily": lambda: DailyParams( + audio_in_enabled=True, + audio_out_enabled=True, + vad_analyzer=SileroVADAnalyzer(), + ), + "twilio": lambda: FastAPIWebsocketParams( + audio_in_enabled=True, + audio_out_enabled=True, + vad_analyzer=SileroVADAnalyzer(), + ), + "webrtc": lambda: TransportParams( + audio_in_enabled=True, + audio_out_enabled=True, + vad_analyzer=SileroVADAnalyzer(), + ), +} + + +async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): + logger.info(f"Starting bot") + + llm = GrokRealtimeLLMService(api_key=os.getenv("XAI_API_KEY")) + + messages = [ + { + "role": "system", + "content": "You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + }, + ] + + context = LLMContext(messages) + user_aggregator, assistant_aggregator = LLMContextAggregatorPair(context) + + pipeline = Pipeline( + [ + transport.input(), + user_aggregator, + llm, + transport.output(), + assistant_aggregator, + ] + ) + + task = PipelineTask( + pipeline, + params=PipelineParams( + enable_metrics=True, + enable_usage_metrics=True, + ), + idle_timeout_secs=runner_args.pipeline_idle_timeout_secs, + ) + + @transport.event_handler("on_client_connected") + async def on_client_connected(transport, client): + logger.info(f"Client connected") + await task.queue_frames([LLMRunFrame()]) + + async def update_settings(): + await asyncio.sleep(10) + logger.info("Updating Grok Realtime LLM settings: temperature=0.1") + await task.queue_frame( + LLMUpdateSettingsFrame(update=GrokRealtimeLLMSettings(temperature=0.1)) + ) + + asyncio.create_task(update_settings()) + + @transport.event_handler("on_client_disconnected") + async def on_client_disconnected(transport, client): + logger.info(f"Client disconnected") + await task.cancel() + + runner = PipelineRunner(handle_sigint=runner_args.handle_sigint) + + await runner.run(task) + + +async def bot(runner_args: RunnerArguments): + """Main bot entry point compatible with Pipecat Cloud.""" + transport = await create_transport(runner_args, transport_params) + await run_bot(transport, runner_args) + + +if __name__ == "__main__": + from pipecat.runner.run import main + + main() diff --git a/examples/foundational/55zp-update-settings-aws-bedrock-llm.py b/examples/foundational/55zp-update-settings-aws-bedrock-llm.py new file mode 100644 index 000000000..0b26774ae --- /dev/null +++ b/examples/foundational/55zp-update-settings-aws-bedrock-llm.py @@ -0,0 +1,130 @@ +# +# Copyright (c) 2024-2026, Daily +# +# SPDX-License-Identifier: BSD 2-Clause License +# + +import asyncio +import os + +from dotenv import load_dotenv +from loguru import logger + +from pipecat.audio.vad.silero import SileroVADAnalyzer +from pipecat.frames.frames import LLMRunFrame, LLMUpdateSettingsFrame +from pipecat.pipeline.pipeline import Pipeline +from pipecat.pipeline.runner import PipelineRunner +from pipecat.pipeline.task import PipelineParams, PipelineTask +from pipecat.processors.aggregators.llm_context import LLMContext +from pipecat.processors.aggregators.llm_response_universal import ( + LLMContextAggregatorPair, + LLMUserAggregatorParams, +) +from pipecat.runner.types import RunnerArguments +from pipecat.runner.utils import create_transport +from pipecat.services.aws.llm import AWSBedrockLLMService, AWSBedrockLLMSettings +from pipecat.services.cartesia.tts import CartesiaTTSService +from pipecat.services.deepgram.stt import DeepgramSTTService +from pipecat.transports.base_transport import BaseTransport, TransportParams +from pipecat.transports.daily.transport import DailyParams +from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams + +load_dotenv(override=True) + +transport_params = { + "daily": lambda: DailyParams( + audio_in_enabled=True, + audio_out_enabled=True, + ), + "twilio": lambda: FastAPIWebsocketParams( + audio_in_enabled=True, + audio_out_enabled=True, + ), + "webrtc": lambda: TransportParams( + audio_in_enabled=True, + audio_out_enabled=True, + ), +} + + +async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): + logger.info(f"Starting bot") + + stt = DeepgramSTTService(api_key=os.getenv("DEEPGRAM_API_KEY")) + + tts = CartesiaTTSService( + api_key=os.getenv("CARTESIA_API_KEY"), + voice_id="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady + ) + + llm = AWSBedrockLLMService(model="anthropic.claude-sonnet-4-20250514-v1:0") + + messages = [ + { + "role": "system", + "content": "You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + }, + ] + + context = LLMContext(messages) + user_aggregator, assistant_aggregator = LLMContextAggregatorPair( + context, + user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()), + ) + + pipeline = Pipeline( + [ + transport.input(), + stt, + user_aggregator, + llm, + tts, + transport.output(), + assistant_aggregator, + ] + ) + + task = PipelineTask( + pipeline, + params=PipelineParams( + enable_metrics=True, + enable_usage_metrics=True, + ), + idle_timeout_secs=runner_args.pipeline_idle_timeout_secs, + ) + + @transport.event_handler("on_client_connected") + async def on_client_connected(transport, client): + logger.info(f"Client connected") + messages.append({"role": "system", "content": "Please introduce yourself to the user."}) + await task.queue_frames([LLMRunFrame()]) + + async def update_settings(): + await asyncio.sleep(10) + logger.info("Updating AWS Bedrock LLM settings: temperature=0.1") + await task.queue_frame( + LLMUpdateSettingsFrame(update=AWSBedrockLLMSettings(temperature=0.1)) + ) + + asyncio.create_task(update_settings()) + + @transport.event_handler("on_client_disconnected") + async def on_client_disconnected(transport, client): + logger.info(f"Client disconnected") + await task.cancel() + + runner = PipelineRunner(handle_sigint=runner_args.handle_sigint) + + await runner.run(task) + + +async def bot(runner_args: RunnerArguments): + """Main bot entry point compatible with Pipecat Cloud.""" + transport = await create_transport(runner_args, transport_params) + await run_bot(transport, runner_args) + + +if __name__ == "__main__": + from pipecat.runner.run import main + + main() From 7910f20e144b1bcf64707ede9066780f62bad69f Mon Sep 17 00:00:00 2001 From: Paul Kompfner Date: Wed, 18 Feb 2026 10:07:33 -0500 Subject: [PATCH 0516/1060] Update comment in Azure TTS explaining how we could support dynamic settings updates in the future --- src/pipecat/services/azure/stt.py | 6 ++++-- 1 file changed, 4 insertions(+), 2 deletions(-) diff --git a/src/pipecat/services/azure/stt.py b/src/pipecat/services/azure/stt.py index 7f9d3f1ba..18fc9b108 100644 --- a/src/pipecat/services/azure/stt.py +++ b/src/pipecat/services/azure/stt.py @@ -146,8 +146,10 @@ class AzureSTTService(STTService): # if "language" in changed: # self._speech_config.speech_recognition_language = self._settings.language # if self._speech_recognizer: - # self._speech_recognizer.stop_continuous_recognition_async() - # self._speech_recognizer.start_continuous_recognition_async() + # # Requires refactoring to set up and tear down recognizer, as + # # language is applied at recognizer initialization + # await self._disconnect() + # await self._connect() self._warn_unhandled_updated_settings(changed) From 1daea78b913fe2ca4f64efc1038eaedcfefba9e7 Mon Sep 17 00:00:00 2001 From: filipi87 Date: Wed, 18 Feb 2026 12:12:49 -0300 Subject: [PATCH 0517/1060] Fix GradiumTTSService to reuse context IDs across multiple run_tts calls and prevent the parent class from pushing text frames. --- src/pipecat/services/gradium/tts.py | 16 ++++++++++++++++ 1 file changed, 16 insertions(+) diff --git a/src/pipecat/services/gradium/tts.py b/src/pipecat/services/gradium/tts.py index bde77f846..ef3cbbfde 100644 --- a/src/pipecat/services/gradium/tts.py +++ b/src/pipecat/services/gradium/tts.py @@ -6,6 +6,7 @@ import base64 import json +import uuid from typing import Any, AsyncGenerator, Mapping, Optional from loguru import logger @@ -74,6 +75,7 @@ class GradiumTTSService(AudioContextWordTTSService): """ super().__init__( push_stop_frames=True, + push_text_frames=False, pause_frame_processing=True, sample_rate=SAMPLE_RATE, **kwargs, @@ -304,6 +306,20 @@ class GradiumTTSService(AudioContextWordTTSService): await self.stop_all_metrics() await self.push_error(error_msg=f"Error: {msg.get('message', msg)}") + def create_context_id(self) -> str: + """Generate a unique context ID for a TTS request in case we don't have one already in progress. + + Returns: + A unique string identifier for the TTS context. + """ + # If a context ID does not exist, create a new one. + # If an ID exists, continue using the current ID. + # When interruptions happens, user speech results in + # an interruption, which resets the context ID. + if not self._context_id: + return str(uuid.uuid4()) + return self._context_id + @traced_tts async def run_tts(self, text: str, context_id: str) -> AsyncGenerator[Frame, None]: """Generate speech from text using Gradium's streaming API. From a7ada79fd9e138399bc0710c9618b37461deb6b7 Mon Sep 17 00:00:00 2001 From: Paul Kompfner Date: Wed, 18 Feb 2026 10:50:53 -0500 Subject: [PATCH 0518/1060] Fix `ElevenLabsRealtimeSTTService`: - Move `CommitStrategy` up in the file so it could be used by `ElevenLabsRealtimeSTTSettings` - Fix a bug where `run_tts` would erroneously try to reconnect if a reconnection was already in flight (like a reconnection triggered by `_update_settings`) --- src/pipecat/services/elevenlabs/stt.py | 35 ++++++++++++++++++-------- 1 file changed, 24 insertions(+), 11 deletions(-) diff --git a/src/pipecat/services/elevenlabs/stt.py b/src/pipecat/services/elevenlabs/stt.py index 0ef137006..e5b7b3843 100644 --- a/src/pipecat/services/elevenlabs/stt.py +++ b/src/pipecat/services/elevenlabs/stt.py @@ -11,6 +11,7 @@ using segmented audio processing. The service uploads audio files and receives transcription results directly. """ +import asyncio import base64 import io import json @@ -169,6 +170,13 @@ def language_to_elevenlabs_language(language: Language) -> Optional[str]: return resolve_language(language, LANGUAGE_MAP, use_base_code=False) +class CommitStrategy(str, Enum): + """Commit strategies for transcript segmentation.""" + + MANUAL = "manual" + VAD = "vad" + + @dataclass class ElevenLabsSTTSettings(STTSettings): """Settings for the ElevenLabs file-based STT service. @@ -426,13 +434,6 @@ def audio_format_from_sample_rate(sample_rate: int) -> str: return "pcm_16000" -class CommitStrategy(str, Enum): - """Commit strategies for transcript segmentation.""" - - MANUAL = "manual" - VAD = "vad" - - class ElevenLabsRealtimeSTTService(WebsocketSTTService): """Speech-to-text service using ElevenLabs' Realtime WebSocket API. @@ -515,6 +516,9 @@ class ElevenLabsRealtimeSTTService(WebsocketSTTService): self._audio_format = "" # initialized in start() self._receive_task = None + self._connected_event = asyncio.Event() + self._connected_event.set() + self._settings = ElevenLabsRealtimeSTTSettings( model=model, language=params.language_code, @@ -630,6 +634,9 @@ class ElevenLabsRealtimeSTTService(WebsocketSTTService): Yields: None - transcription results are handled via WebSocket responses. """ + # Wait for any in-flight _connect() to finish before checking state + await self._connected_event.wait() + # Reconnect if connection is closed if not self._websocket or self._websocket.state is State.CLOSED: await self._connect() @@ -654,12 +661,18 @@ class ElevenLabsRealtimeSTTService(WebsocketSTTService): async def _connect(self): """Establish WebSocket connection to ElevenLabs Realtime STT.""" - await self._connect_websocket() + self._connected_event.clear() + try: + await self._connect_websocket() - await super()._connect() + await super()._connect() - if self._websocket and not self._receive_task: - self._receive_task = self.create_task(self._receive_task_handler(self._report_error)) + if self._websocket and not self._receive_task: + self._receive_task = self.create_task( + self._receive_task_handler(self._report_error) + ) + finally: + self._connected_event.set() async def _disconnect(self): """Close WebSocket connection and cleanup tasks.""" From e98bb1df66889bbf651a41d63ec522ff04a8269f Mon Sep 17 00:00:00 2001 From: Paul Kompfner Date: Wed, 18 Feb 2026 11:06:33 -0500 Subject: [PATCH 0519/1060] Simplify 55* examples: inline the settings update directly in the on_client_connected handler instead of wrapping it in a separate async task --- .../55a-update-settings-deepgram-stt.py | 13 +++++-------- .../55b-update-settings-azure-stt.py | 13 +++++-------- .../55c-update-settings-google-stt.py | 13 +++++-------- .../55d-update-settings-assemblyai-stt.py | 13 +++++-------- .../55e-update-settings-gladia-stt.py | 13 +++++-------- ...update-settings-elevenlabs-realtime-stt.py | 13 +++++-------- .../55g-update-settings-elevenlabs-stt.py | 13 +++++-------- .../55h-update-settings-speechmatics-stt.py | 13 +++++-------- .../55i-update-settings-whisper-api-stt.py | 19 ++++++++----------- .../55j-update-settings-sarvam-stt.py | 13 +++++-------- .../55k-update-settings-soniox-stt.py | 13 +++++-------- .../55l-update-settings-aws-transcribe-stt.py | 13 +++++-------- .../55m-update-settings-cartesia-stt.py | 13 +++++-------- .../55n-update-settings-cartesia-tts.py | 9 +++------ .../55o-update-settings-elevenlabs-tts.py | 13 +++++-------- .../55p-update-settings-openai-tts.py | 9 +++------ .../55q-update-settings-deepgram-tts.py | 13 +++++-------- .../55r-update-settings-azure-tts.py | 13 +++++-------- .../55s-update-settings-google-http-tts.py | 13 +++++-------- .../55t-update-settings-playht-tts.py | 9 +++------ .../55u-update-settings-rime-tts.py | 9 +++------ .../55v-update-settings-lmnt-tts.py | 9 +++------ .../55w-update-settings-fish-tts.py | 13 +++++-------- .../55x-update-settings-minimax-tts.py | 13 +++++-------- .../55y-update-settings-groq-tts.py | 9 +++------ .../55z-update-settings-hume-tts.py | 17 ++++++----------- .../55za-update-settings-neuphonic-tts.py | 9 +++------ .../55zb-update-settings-inworld-tts.py | 15 +++++---------- .../55zc-update-settings-gemini-tts.py | 15 +++++---------- .../55zd-update-settings-aws-polly-tts.py | 13 +++++-------- .../55ze-update-settings-sarvam-tts.py | 9 +++------ .../55zf-update-settings-camb-tts.py | 15 ++++++--------- .../55zg-update-settings-hathora-tts.py | 9 +++------ .../55zh-update-settings-resembleai-tts.py | 15 ++++++--------- .../55zi-update-settings-openai-llm.py | 11 +++-------- .../55zj-update-settings-anthropic-llm.py | 11 +++-------- .../55zk-update-settings-google-llm.py | 11 +++-------- .../55zl-update-settings-openai-realtime.py | 13 +++++-------- .../55zm-update-settings-gemini-live.py | 13 +++++-------- .../55zn-update-settings-ultravox-realtime.py | 13 +++++-------- .../55zo-update-settings-grok-realtime.py | 13 +++++-------- .../55zp-update-settings-aws-bedrock-llm.py | 13 +++++-------- 42 files changed, 192 insertions(+), 330 deletions(-) diff --git a/examples/foundational/55a-update-settings-deepgram-stt.py b/examples/foundational/55a-update-settings-deepgram-stt.py index bf1247ed6..aea9475a8 100644 --- a/examples/foundational/55a-update-settings-deepgram-stt.py +++ b/examples/foundational/55a-update-settings-deepgram-stt.py @@ -100,14 +100,11 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): messages.append({"role": "system", "content": "Please introduce yourself to the user."}) await task.queue_frames([LLMRunFrame()]) - async def update_settings(): - await asyncio.sleep(10) - logger.info("Updating Deepgram STT settings: language=es") - await task.queue_frame( - STTUpdateSettingsFrame(update=DeepgramSTTSettings(language=Language.ES)) - ) - - asyncio.create_task(update_settings()) + await asyncio.sleep(10) + logger.info("Updating Deepgram STT settings: language=es") + await task.queue_frame( + STTUpdateSettingsFrame(update=DeepgramSTTSettings(language=Language.ES)) + ) @transport.event_handler("on_client_disconnected") async def on_client_disconnected(transport, client): diff --git a/examples/foundational/55b-update-settings-azure-stt.py b/examples/foundational/55b-update-settings-azure-stt.py index 9ff2a5af7..7fd0d2ca4 100644 --- a/examples/foundational/55b-update-settings-azure-stt.py +++ b/examples/foundational/55b-update-settings-azure-stt.py @@ -103,14 +103,11 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): messages.append({"role": "system", "content": "Please introduce yourself to the user."}) await task.queue_frames([LLMRunFrame()]) - async def update_settings(): - await asyncio.sleep(10) - logger.info("Updating Azure STT settings: language=es") - await task.queue_frame( - STTUpdateSettingsFrame(update=AzureSTTSettings(language=Language.ES)) - ) - - asyncio.create_task(update_settings()) + await asyncio.sleep(10) + logger.info("Updating Azure STT settings: language=es") + await task.queue_frame( + STTUpdateSettingsFrame(update=AzureSTTSettings(language=Language.ES)) + ) @transport.event_handler("on_client_disconnected") async def on_client_disconnected(transport, client): diff --git a/examples/foundational/55c-update-settings-google-stt.py b/examples/foundational/55c-update-settings-google-stt.py index b25046fe3..dd33bfe75 100644 --- a/examples/foundational/55c-update-settings-google-stt.py +++ b/examples/foundational/55c-update-settings-google-stt.py @@ -100,14 +100,11 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): messages.append({"role": "system", "content": "Please introduce yourself to the user."}) await task.queue_frames([LLMRunFrame()]) - async def update_settings(): - await asyncio.sleep(10) - logger.info("Updating Google STT settings: language=es") - await task.queue_frame( - STTUpdateSettingsFrame(update=GoogleSTTSettings(language=Language.ES)) - ) - - asyncio.create_task(update_settings()) + await asyncio.sleep(10) + logger.info("Updating Google STT settings: language=es") + await task.queue_frame( + STTUpdateSettingsFrame(update=GoogleSTTSettings(language=Language.ES)) + ) @transport.event_handler("on_client_disconnected") async def on_client_disconnected(transport, client): diff --git a/examples/foundational/55d-update-settings-assemblyai-stt.py b/examples/foundational/55d-update-settings-assemblyai-stt.py index 488f17f54..6d6a2532e 100644 --- a/examples/foundational/55d-update-settings-assemblyai-stt.py +++ b/examples/foundational/55d-update-settings-assemblyai-stt.py @@ -100,14 +100,11 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): messages.append({"role": "system", "content": "Please introduce yourself to the user."}) await task.queue_frames([LLMRunFrame()]) - async def update_settings(): - await asyncio.sleep(10) - logger.info("Updating AssemblyAI STT settings: language=es") - await task.queue_frame( - STTUpdateSettingsFrame(update=AssemblyAISTTSettings(language=Language.ES)) - ) - - asyncio.create_task(update_settings()) + await asyncio.sleep(10) + logger.info("Updating AssemblyAI STT settings: language=es") + await task.queue_frame( + STTUpdateSettingsFrame(update=AssemblyAISTTSettings(language=Language.ES)) + ) @transport.event_handler("on_client_disconnected") async def on_client_disconnected(transport, client): diff --git a/examples/foundational/55e-update-settings-gladia-stt.py b/examples/foundational/55e-update-settings-gladia-stt.py index 75e524d08..a2c6f21fe 100644 --- a/examples/foundational/55e-update-settings-gladia-stt.py +++ b/examples/foundational/55e-update-settings-gladia-stt.py @@ -100,14 +100,11 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): messages.append({"role": "system", "content": "Please introduce yourself to the user."}) await task.queue_frames([LLMRunFrame()]) - async def update_settings(): - await asyncio.sleep(10) - logger.info("Updating Gladia STT settings: language=es") - await task.queue_frame( - STTUpdateSettingsFrame(update=GladiaSTTSettings(language=Language.ES)) - ) - - asyncio.create_task(update_settings()) + await asyncio.sleep(10) + logger.info("Updating Gladia STT settings: language=es") + await task.queue_frame( + STTUpdateSettingsFrame(update=GladiaSTTSettings(language=Language.ES)) + ) @transport.event_handler("on_client_disconnected") async def on_client_disconnected(transport, client): diff --git a/examples/foundational/55f-update-settings-elevenlabs-realtime-stt.py b/examples/foundational/55f-update-settings-elevenlabs-realtime-stt.py index f74ea709e..9aee04fbb 100644 --- a/examples/foundational/55f-update-settings-elevenlabs-realtime-stt.py +++ b/examples/foundational/55f-update-settings-elevenlabs-realtime-stt.py @@ -103,14 +103,11 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): messages.append({"role": "system", "content": "Please introduce yourself to the user."}) await task.queue_frames([LLMRunFrame()]) - async def update_settings(): - await asyncio.sleep(10) - logger.info("Updating ElevenLabs Realtime STT settings: language=es") - await task.queue_frame( - STTUpdateSettingsFrame(update=ElevenLabsRealtimeSTTSettings(language=Language.ES)) - ) - - asyncio.create_task(update_settings()) + await asyncio.sleep(10) + logger.info("Updating ElevenLabs Realtime STT settings: language=es") + await task.queue_frame( + STTUpdateSettingsFrame(update=ElevenLabsRealtimeSTTSettings(language=Language.ES)) + ) @transport.event_handler("on_client_disconnected") async def on_client_disconnected(transport, client): diff --git a/examples/foundational/55g-update-settings-elevenlabs-stt.py b/examples/foundational/55g-update-settings-elevenlabs-stt.py index dd5191218..33844935a 100644 --- a/examples/foundational/55g-update-settings-elevenlabs-stt.py +++ b/examples/foundational/55g-update-settings-elevenlabs-stt.py @@ -105,14 +105,11 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): messages.append({"role": "system", "content": "Please introduce yourself to the user."}) await task.queue_frames([LLMRunFrame()]) - async def update_settings(): - await asyncio.sleep(10) - logger.info("Updating ElevenLabs STT settings: language=es") - await task.queue_frame( - STTUpdateSettingsFrame(update=ElevenLabsSTTSettings(language=Language.ES)) - ) - - asyncio.create_task(update_settings()) + await asyncio.sleep(10) + logger.info("Updating ElevenLabs STT settings: language=es") + await task.queue_frame( + STTUpdateSettingsFrame(update=ElevenLabsSTTSettings(language=Language.ES)) + ) @transport.event_handler("on_client_disconnected") async def on_client_disconnected(transport, client): diff --git a/examples/foundational/55h-update-settings-speechmatics-stt.py b/examples/foundational/55h-update-settings-speechmatics-stt.py index 82e207207..46ed44016 100644 --- a/examples/foundational/55h-update-settings-speechmatics-stt.py +++ b/examples/foundational/55h-update-settings-speechmatics-stt.py @@ -100,14 +100,11 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): messages.append({"role": "system", "content": "Please introduce yourself to the user."}) await task.queue_frames([LLMRunFrame()]) - async def update_settings(): - await asyncio.sleep(10) - logger.info("Updating Speechmatics STT settings: language=es") - await task.queue_frame( - STTUpdateSettingsFrame(update=SpeechmaticsSTTSettings(language=Language.ES)) - ) - - asyncio.create_task(update_settings()) + await asyncio.sleep(10) + logger.info("Updating Speechmatics STT settings: language=es") + await task.queue_frame( + STTUpdateSettingsFrame(update=SpeechmaticsSTTSettings(language=Language.ES)) + ) @transport.event_handler("on_client_disconnected") async def on_client_disconnected(transport, client): diff --git a/examples/foundational/55i-update-settings-whisper-api-stt.py b/examples/foundational/55i-update-settings-whisper-api-stt.py index b2655bc86..27581a819 100644 --- a/examples/foundational/55i-update-settings-whisper-api-stt.py +++ b/examples/foundational/55i-update-settings-whisper-api-stt.py @@ -102,18 +102,15 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): messages.append({"role": "system", "content": "Please introduce yourself to the user."}) await task.queue_frames([LLMRunFrame()]) - async def update_settings(): - await asyncio.sleep(10) - logger.info( - 'Updating Whisper API STT settings: prompt="Transcribe in English", temperature=0.5' + await asyncio.sleep(10) + logger.info( + 'Updating Whisper API STT settings: prompt="Transcribe in English", temperature=0.5' + ) + await task.queue_frame( + STTUpdateSettingsFrame( + update=BaseWhisperSTTSettings(prompt="Transcribe in English", temperature=0.5) ) - await task.queue_frame( - STTUpdateSettingsFrame( - update=BaseWhisperSTTSettings(prompt="Transcribe in English", temperature=0.5) - ) - ) - - asyncio.create_task(update_settings()) + ) @transport.event_handler("on_client_disconnected") async def on_client_disconnected(transport, client): diff --git a/examples/foundational/55j-update-settings-sarvam-stt.py b/examples/foundational/55j-update-settings-sarvam-stt.py index a4d0cd192..b7f619987 100644 --- a/examples/foundational/55j-update-settings-sarvam-stt.py +++ b/examples/foundational/55j-update-settings-sarvam-stt.py @@ -100,14 +100,11 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): messages.append({"role": "system", "content": "Please introduce yourself to the user."}) await task.queue_frames([LLMRunFrame()]) - async def update_settings(): - await asyncio.sleep(10) - logger.info("Updating Sarvam STT settings: language=hi") - await task.queue_frame( - STTUpdateSettingsFrame(update=SarvamSTTSettings(language=Language.HI)) - ) - - asyncio.create_task(update_settings()) + await asyncio.sleep(10) + logger.info("Updating Sarvam STT settings: language=hi") + await task.queue_frame( + STTUpdateSettingsFrame(update=SarvamSTTSettings(language=Language.HI)) + ) @transport.event_handler("on_client_disconnected") async def on_client_disconnected(transport, client): diff --git a/examples/foundational/55k-update-settings-soniox-stt.py b/examples/foundational/55k-update-settings-soniox-stt.py index 5f192580b..2cbcd44f4 100644 --- a/examples/foundational/55k-update-settings-soniox-stt.py +++ b/examples/foundational/55k-update-settings-soniox-stt.py @@ -100,14 +100,11 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): messages.append({"role": "system", "content": "Please introduce yourself to the user."}) await task.queue_frames([LLMRunFrame()]) - async def update_settings(): - await asyncio.sleep(10) - logger.info("Updating Soniox STT settings: language=es") - await task.queue_frame( - STTUpdateSettingsFrame(update=SonioxSTTSettings(language=Language.ES)) - ) - - asyncio.create_task(update_settings()) + await asyncio.sleep(10) + logger.info("Updating Soniox STT settings: language=es") + await task.queue_frame( + STTUpdateSettingsFrame(update=SonioxSTTSettings(language=Language.ES)) + ) @transport.event_handler("on_client_disconnected") async def on_client_disconnected(transport, client): diff --git a/examples/foundational/55l-update-settings-aws-transcribe-stt.py b/examples/foundational/55l-update-settings-aws-transcribe-stt.py index 469efe32e..0f4c18981 100644 --- a/examples/foundational/55l-update-settings-aws-transcribe-stt.py +++ b/examples/foundational/55l-update-settings-aws-transcribe-stt.py @@ -100,14 +100,11 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): messages.append({"role": "system", "content": "Please introduce yourself to the user."}) await task.queue_frames([LLMRunFrame()]) - async def update_settings(): - await asyncio.sleep(10) - logger.info("Updating AWS Transcribe STT settings: language=es") - await task.queue_frame( - STTUpdateSettingsFrame(update=AWSTranscribeSTTSettings(language=Language.ES)) - ) - - asyncio.create_task(update_settings()) + await asyncio.sleep(10) + logger.info("Updating AWS Transcribe STT settings: language=es") + await task.queue_frame( + STTUpdateSettingsFrame(update=AWSTranscribeSTTSettings(language=Language.ES)) + ) @transport.event_handler("on_client_disconnected") async def on_client_disconnected(transport, client): diff --git a/examples/foundational/55m-update-settings-cartesia-stt.py b/examples/foundational/55m-update-settings-cartesia-stt.py index 0ed1aa169..6ba27a85e 100644 --- a/examples/foundational/55m-update-settings-cartesia-stt.py +++ b/examples/foundational/55m-update-settings-cartesia-stt.py @@ -100,14 +100,11 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): messages.append({"role": "system", "content": "Please introduce yourself to the user."}) await task.queue_frames([LLMRunFrame()]) - async def update_settings(): - await asyncio.sleep(10) - logger.info("Updating Cartesia STT settings: language=es") - await task.queue_frame( - STTUpdateSettingsFrame(update=CartesiaSTTSettings(language=Language.ES)) - ) - - asyncio.create_task(update_settings()) + await asyncio.sleep(10) + logger.info("Updating Cartesia STT settings: language=es") + await task.queue_frame( + STTUpdateSettingsFrame(update=CartesiaSTTSettings(language=Language.ES)) + ) @transport.event_handler("on_client_disconnected") async def on_client_disconnected(transport, client): diff --git a/examples/foundational/55n-update-settings-cartesia-tts.py b/examples/foundational/55n-update-settings-cartesia-tts.py index afa9bbeb5..38070765c 100644 --- a/examples/foundational/55n-update-settings-cartesia-tts.py +++ b/examples/foundational/55n-update-settings-cartesia-tts.py @@ -102,12 +102,9 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): messages.append({"role": "system", "content": "Please introduce yourself to the user."}) await task.queue_frames([LLMRunFrame()]) - async def update_settings(): - await asyncio.sleep(10) - logger.info("Updating Cartesia TTS settings: speed=fast") - await task.queue_frame(TTSUpdateSettingsFrame(update=CartesiaTTSSettings(speed="fast"))) - - asyncio.create_task(update_settings()) + await asyncio.sleep(10) + logger.info("Updating Cartesia TTS settings: speed=fast") + await task.queue_frame(TTSUpdateSettingsFrame(update=CartesiaTTSSettings(speed="fast"))) @transport.event_handler("on_client_disconnected") async def on_client_disconnected(transport, client): diff --git a/examples/foundational/55o-update-settings-elevenlabs-tts.py b/examples/foundational/55o-update-settings-elevenlabs-tts.py index 65ccfc41a..0ca72ba5b 100644 --- a/examples/foundational/55o-update-settings-elevenlabs-tts.py +++ b/examples/foundational/55o-update-settings-elevenlabs-tts.py @@ -99,14 +99,11 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): messages.append({"role": "system", "content": "Please introduce yourself to the user."}) await task.queue_frames([LLMRunFrame()]) - async def update_settings(): - await asyncio.sleep(10) - logger.info("Updating ElevenLabs TTS settings: speed=1.2, stability=0.3") - await task.queue_frame( - TTSUpdateSettingsFrame(update=ElevenLabsTTSSettings(speed=1.2, stability=0.3)) - ) - - asyncio.create_task(update_settings()) + await asyncio.sleep(10) + logger.info("Updating ElevenLabs TTS settings: speed=1.2, stability=0.3") + await task.queue_frame( + TTSUpdateSettingsFrame(update=ElevenLabsTTSSettings(speed=1.2, stability=0.3)) + ) @transport.event_handler("on_client_disconnected") async def on_client_disconnected(transport, client): diff --git a/examples/foundational/55p-update-settings-openai-tts.py b/examples/foundational/55p-update-settings-openai-tts.py index ebcb1cd54..58e8efde1 100644 --- a/examples/foundational/55p-update-settings-openai-tts.py +++ b/examples/foundational/55p-update-settings-openai-tts.py @@ -97,12 +97,9 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): messages.append({"role": "system", "content": "Please introduce yourself to the user."}) await task.queue_frames([LLMRunFrame()]) - async def update_settings(): - await asyncio.sleep(10) - logger.info("Updating OpenAI TTS settings: speed=1.5") - await task.queue_frame(TTSUpdateSettingsFrame(update=OpenAITTSSettings(speed=1.5))) - - asyncio.create_task(update_settings()) + await asyncio.sleep(10) + logger.info("Updating OpenAI TTS settings: speed=1.5") + await task.queue_frame(TTSUpdateSettingsFrame(update=OpenAITTSSettings(speed=1.5))) @transport.event_handler("on_client_disconnected") async def on_client_disconnected(transport, client): diff --git a/examples/foundational/55q-update-settings-deepgram-tts.py b/examples/foundational/55q-update-settings-deepgram-tts.py index 166f6fc26..4b7f50ae8 100644 --- a/examples/foundational/55q-update-settings-deepgram-tts.py +++ b/examples/foundational/55q-update-settings-deepgram-tts.py @@ -96,14 +96,11 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): messages.append({"role": "system", "content": "Please introduce yourself to the user."}) await task.queue_frames([LLMRunFrame()]) - async def update_settings(): - await asyncio.sleep(10) - logger.info('Updating Deepgram TTS settings: voice="aura-2-luna-en"') - await task.queue_frame( - TTSUpdateSettingsFrame(update=DeepgramTTSSettings(voice="aura-2-luna-en")) - ) - - asyncio.create_task(update_settings()) + await asyncio.sleep(10) + logger.info('Updating Deepgram TTS settings: voice="aura-2-luna-en"') + await task.queue_frame( + TTSUpdateSettingsFrame(update=DeepgramTTSSettings(voice="aura-2-luna-en")) + ) @transport.event_handler("on_client_disconnected") async def on_client_disconnected(transport, client): diff --git a/examples/foundational/55r-update-settings-azure-tts.py b/examples/foundational/55r-update-settings-azure-tts.py index 5aa63bef8..076901707 100644 --- a/examples/foundational/55r-update-settings-azure-tts.py +++ b/examples/foundational/55r-update-settings-azure-tts.py @@ -99,14 +99,11 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): messages.append({"role": "system", "content": "Please introduce yourself to the user."}) await task.queue_frames([LLMRunFrame()]) - async def update_settings(): - await asyncio.sleep(10) - logger.info('Updating Azure TTS settings: rate="1.3", style="cheerful"') - await task.queue_frame( - TTSUpdateSettingsFrame(update=AzureTTSSettings(rate="1.3", style="cheerful")) - ) - - asyncio.create_task(update_settings()) + await asyncio.sleep(10) + logger.info('Updating Azure TTS settings: rate="1.3", style="cheerful"') + await task.queue_frame( + TTSUpdateSettingsFrame(update=AzureTTSSettings(rate="1.3", style="cheerful")) + ) @transport.event_handler("on_client_disconnected") async def on_client_disconnected(transport, client): diff --git a/examples/foundational/55s-update-settings-google-http-tts.py b/examples/foundational/55s-update-settings-google-http-tts.py index 5033d2b28..6c302411a 100644 --- a/examples/foundational/55s-update-settings-google-http-tts.py +++ b/examples/foundational/55s-update-settings-google-http-tts.py @@ -96,14 +96,11 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): messages.append({"role": "system", "content": "Please introduce yourself to the user."}) await task.queue_frames([LLMRunFrame()]) - async def update_settings(): - await asyncio.sleep(10) - logger.info("Updating Google HTTP TTS settings: speaking_rate=1.4") - await task.queue_frame( - TTSUpdateSettingsFrame(update=GoogleHttpTTSSettings(speaking_rate=1.4)) - ) - - asyncio.create_task(update_settings()) + await asyncio.sleep(10) + logger.info("Updating Google HTTP TTS settings: speaking_rate=1.4") + await task.queue_frame( + TTSUpdateSettingsFrame(update=GoogleHttpTTSSettings(speaking_rate=1.4)) + ) @transport.event_handler("on_client_disconnected") async def on_client_disconnected(transport, client): diff --git a/examples/foundational/55t-update-settings-playht-tts.py b/examples/foundational/55t-update-settings-playht-tts.py index 37bf48897..ec468a81c 100644 --- a/examples/foundational/55t-update-settings-playht-tts.py +++ b/examples/foundational/55t-update-settings-playht-tts.py @@ -100,12 +100,9 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): messages.append({"role": "system", "content": "Please introduce yourself to the user."}) await task.queue_frames([LLMRunFrame()]) - async def update_settings(): - await asyncio.sleep(10) - logger.info("Updating PlayHT TTS settings: speed=1.3") - await task.queue_frame(TTSUpdateSettingsFrame(update=PlayHTTTSSettings(speed=1.3))) - - asyncio.create_task(update_settings()) + await asyncio.sleep(10) + logger.info("Updating PlayHT TTS settings: speed=1.3") + await task.queue_frame(TTSUpdateSettingsFrame(update=PlayHTTTSSettings(speed=1.3))) @transport.event_handler("on_client_disconnected") async def on_client_disconnected(transport, client): diff --git a/examples/foundational/55u-update-settings-rime-tts.py b/examples/foundational/55u-update-settings-rime-tts.py index 31de262aa..e95aeb830 100644 --- a/examples/foundational/55u-update-settings-rime-tts.py +++ b/examples/foundational/55u-update-settings-rime-tts.py @@ -99,12 +99,9 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): messages.append({"role": "system", "content": "Please introduce yourself to the user."}) await task.queue_frames([LLMRunFrame()]) - async def update_settings(): - await asyncio.sleep(10) - logger.info("Updating Rime TTS settings: speedAlpha=1.5") - await task.queue_frame(TTSUpdateSettingsFrame(update=RimeTTSSettings(speedAlpha=1.5))) - - asyncio.create_task(update_settings()) + await asyncio.sleep(10) + logger.info("Updating Rime TTS settings: speedAlpha=1.5") + await task.queue_frame(TTSUpdateSettingsFrame(update=RimeTTSSettings(speedAlpha=1.5))) @transport.event_handler("on_client_disconnected") async def on_client_disconnected(transport, client): diff --git a/examples/foundational/55v-update-settings-lmnt-tts.py b/examples/foundational/55v-update-settings-lmnt-tts.py index f61026735..c8e6a3e09 100644 --- a/examples/foundational/55v-update-settings-lmnt-tts.py +++ b/examples/foundational/55v-update-settings-lmnt-tts.py @@ -99,12 +99,9 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): messages.append({"role": "system", "content": "Please introduce yourself to the user."}) await task.queue_frames([LLMRunFrame()]) - async def update_settings(): - await asyncio.sleep(10) - logger.info('Updating LMNT TTS settings: voice="lily"') - await task.queue_frame(TTSUpdateSettingsFrame(update=LmntTTSSettings(voice="lily"))) - - asyncio.create_task(update_settings()) + await asyncio.sleep(10) + logger.info('Updating LMNT TTS settings: voice="lily"') + await task.queue_frame(TTSUpdateSettingsFrame(update=LmntTTSSettings(voice="lily"))) @transport.event_handler("on_client_disconnected") async def on_client_disconnected(transport, client): diff --git a/examples/foundational/55w-update-settings-fish-tts.py b/examples/foundational/55w-update-settings-fish-tts.py index 85d942ad7..be9049333 100644 --- a/examples/foundational/55w-update-settings-fish-tts.py +++ b/examples/foundational/55w-update-settings-fish-tts.py @@ -96,14 +96,11 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): messages.append({"role": "system", "content": "Please introduce yourself to the user."}) await task.queue_frames([LLMRunFrame()]) - async def update_settings(): - await asyncio.sleep(10) - logger.info("Updating Fish Audio TTS settings: prosody_speed=1.5") - await task.queue_frame( - TTSUpdateSettingsFrame(update=FishAudioTTSSettings(prosody_speed=1.5)) - ) - - asyncio.create_task(update_settings()) + await asyncio.sleep(10) + logger.info("Updating Fish Audio TTS settings: prosody_speed=1.5") + await task.queue_frame( + TTSUpdateSettingsFrame(update=FishAudioTTSSettings(prosody_speed=1.5)) + ) @transport.event_handler("on_client_disconnected") async def on_client_disconnected(transport, client): diff --git a/examples/foundational/55x-update-settings-minimax-tts.py b/examples/foundational/55x-update-settings-minimax-tts.py index f5d74b0f3..306b8f2bd 100644 --- a/examples/foundational/55x-update-settings-minimax-tts.py +++ b/examples/foundational/55x-update-settings-minimax-tts.py @@ -102,14 +102,11 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): messages.append({"role": "system", "content": "Please introduce yourself to the user."}) await task.queue_frames([LLMRunFrame()]) - async def update_settings(): - await asyncio.sleep(10) - logger.info('Updating MiniMax TTS settings: speed=1.5, emotion="happy"') - await task.queue_frame( - TTSUpdateSettingsFrame(update=MiniMaxTTSSettings(speed=1.5, emotion="happy")) - ) - - asyncio.create_task(update_settings()) + await asyncio.sleep(10) + logger.info('Updating MiniMax TTS settings: speed=1.5, emotion="happy"') + await task.queue_frame( + TTSUpdateSettingsFrame(update=MiniMaxTTSSettings(speed=1.5, emotion="happy")) + ) @transport.event_handler("on_client_disconnected") async def on_client_disconnected(transport, client): diff --git a/examples/foundational/55y-update-settings-groq-tts.py b/examples/foundational/55y-update-settings-groq-tts.py index a7f4936ee..e6ce851c6 100644 --- a/examples/foundational/55y-update-settings-groq-tts.py +++ b/examples/foundational/55y-update-settings-groq-tts.py @@ -96,12 +96,9 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): messages.append({"role": "system", "content": "Please introduce yourself to the user."}) await task.queue_frames([LLMRunFrame()]) - async def update_settings(): - await asyncio.sleep(10) - logger.info("Updating Groq TTS settings: speed=1.5") - await task.queue_frame(TTSUpdateSettingsFrame(update=GroqTTSSettings(speed=1.5))) - - asyncio.create_task(update_settings()) + await asyncio.sleep(10) + logger.info("Updating Groq TTS settings: speed=1.5") + await task.queue_frame(TTSUpdateSettingsFrame(update=GroqTTSSettings(speed=1.5))) @transport.event_handler("on_client_disconnected") async def on_client_disconnected(transport, client): diff --git a/examples/foundational/55z-update-settings-hume-tts.py b/examples/foundational/55z-update-settings-hume-tts.py index f4ec141ca..abab6abec 100644 --- a/examples/foundational/55z-update-settings-hume-tts.py +++ b/examples/foundational/55z-update-settings-hume-tts.py @@ -99,18 +99,13 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): messages.append({"role": "system", "content": "Please introduce yourself to the user."}) await task.queue_frames([LLMRunFrame()]) - async def update_settings(): - await asyncio.sleep(10) - logger.info( - 'Updating Hume TTS settings: speed=1.5, description="Speak with excitement"' + await asyncio.sleep(10) + logger.info('Updating Hume TTS settings: speed=1.5, description="Speak with excitement"') + await task.queue_frame( + TTSUpdateSettingsFrame( + update=HumeTTSSettings(speed=1.5, description="Speak with excitement") ) - await task.queue_frame( - TTSUpdateSettingsFrame( - update=HumeTTSSettings(speed=1.5, description="Speak with excitement") - ) - ) - - asyncio.create_task(update_settings()) + ) @transport.event_handler("on_client_disconnected") async def on_client_disconnected(transport, client): diff --git a/examples/foundational/55za-update-settings-neuphonic-tts.py b/examples/foundational/55za-update-settings-neuphonic-tts.py index d76ba5c89..187594c7e 100644 --- a/examples/foundational/55za-update-settings-neuphonic-tts.py +++ b/examples/foundational/55za-update-settings-neuphonic-tts.py @@ -96,12 +96,9 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): messages.append({"role": "system", "content": "Please introduce yourself to the user."}) await task.queue_frames([LLMRunFrame()]) - async def update_settings(): - await asyncio.sleep(10) - logger.info("Updating Neuphonic TTS settings: speed=1.4") - await task.queue_frame(TTSUpdateSettingsFrame(update=NeuphonicTTSSettings(speed=1.4))) - - asyncio.create_task(update_settings()) + await asyncio.sleep(10) + logger.info("Updating Neuphonic TTS settings: speed=1.4") + await task.queue_frame(TTSUpdateSettingsFrame(update=NeuphonicTTSSettings(speed=1.4))) @transport.event_handler("on_client_disconnected") async def on_client_disconnected(transport, client): diff --git a/examples/foundational/55zb-update-settings-inworld-tts.py b/examples/foundational/55zb-update-settings-inworld-tts.py index 159d75f8c..d9947c196 100644 --- a/examples/foundational/55zb-update-settings-inworld-tts.py +++ b/examples/foundational/55zb-update-settings-inworld-tts.py @@ -96,16 +96,11 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): messages.append({"role": "system", "content": "Please introduce yourself to the user."}) await task.queue_frames([LLMRunFrame()]) - async def update_settings(): - await asyncio.sleep(10) - logger.info("Updating Inworld TTS settings: speaking_rate=1.3, temperature=0.8") - await task.queue_frame( - TTSUpdateSettingsFrame( - update=InworldTTSSettings(speaking_rate=1.3, temperature=0.8) - ) - ) - - asyncio.create_task(update_settings()) + await asyncio.sleep(10) + logger.info("Updating Inworld TTS settings: speaking_rate=1.3, temperature=0.8") + await task.queue_frame( + TTSUpdateSettingsFrame(update=InworldTTSSettings(speaking_rate=1.3, temperature=0.8)) + ) @transport.event_handler("on_client_disconnected") async def on_client_disconnected(transport, client): diff --git a/examples/foundational/55zc-update-settings-gemini-tts.py b/examples/foundational/55zc-update-settings-gemini-tts.py index 958115630..0bf878871 100644 --- a/examples/foundational/55zc-update-settings-gemini-tts.py +++ b/examples/foundational/55zc-update-settings-gemini-tts.py @@ -96,16 +96,11 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): messages.append({"role": "system", "content": "Please introduce yourself to the user."}) await task.queue_frames([LLMRunFrame()]) - async def update_settings(): - await asyncio.sleep(10) - logger.info('Updating Gemini TTS settings: prompt="Speak slowly and dramatically"') - await task.queue_frame( - TTSUpdateSettingsFrame( - update=GeminiTTSSettings(prompt="Speak slowly and dramatically") - ) - ) - - asyncio.create_task(update_settings()) + await asyncio.sleep(10) + logger.info('Updating Gemini TTS settings: prompt="Speak slowly and dramatically"') + await task.queue_frame( + TTSUpdateSettingsFrame(update=GeminiTTSSettings(prompt="Speak slowly and dramatically")) + ) @transport.event_handler("on_client_disconnected") async def on_client_disconnected(transport, client): diff --git a/examples/foundational/55zd-update-settings-aws-polly-tts.py b/examples/foundational/55zd-update-settings-aws-polly-tts.py index 951347ddd..8abf68e2c 100644 --- a/examples/foundational/55zd-update-settings-aws-polly-tts.py +++ b/examples/foundational/55zd-update-settings-aws-polly-tts.py @@ -96,14 +96,11 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): messages.append({"role": "system", "content": "Please introduce yourself to the user."}) await task.queue_frames([LLMRunFrame()]) - async def update_settings(): - await asyncio.sleep(10) - logger.info('Updating AWS Polly TTS settings: rate="fast", pitch="+10%"') - await task.queue_frame( - TTSUpdateSettingsFrame(update=AWSPollyTTSSettings(rate="fast", pitch="+10%")) - ) - - asyncio.create_task(update_settings()) + await asyncio.sleep(10) + logger.info('Updating AWS Polly TTS settings: rate="fast", pitch="+10%"') + await task.queue_frame( + TTSUpdateSettingsFrame(update=AWSPollyTTSSettings(rate="fast", pitch="+10%")) + ) @transport.event_handler("on_client_disconnected") async def on_client_disconnected(transport, client): diff --git a/examples/foundational/55ze-update-settings-sarvam-tts.py b/examples/foundational/55ze-update-settings-sarvam-tts.py index 3674d2767..07065bfaf 100644 --- a/examples/foundational/55ze-update-settings-sarvam-tts.py +++ b/examples/foundational/55ze-update-settings-sarvam-tts.py @@ -96,12 +96,9 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): messages.append({"role": "system", "content": "Please introduce yourself to the user."}) await task.queue_frames([LLMRunFrame()]) - async def update_settings(): - await asyncio.sleep(10) - logger.info("Updating Sarvam TTS settings: pace=1.3") - await task.queue_frame(TTSUpdateSettingsFrame(update=SarvamWSTTSSettings(pace=1.3))) - - asyncio.create_task(update_settings()) + await asyncio.sleep(10) + logger.info("Updating Sarvam TTS settings: pace=1.3") + await task.queue_frame(TTSUpdateSettingsFrame(update=SarvamWSTTSSettings(pace=1.3))) @transport.event_handler("on_client_disconnected") async def on_client_disconnected(transport, client): diff --git a/examples/foundational/55zf-update-settings-camb-tts.py b/examples/foundational/55zf-update-settings-camb-tts.py index cc629ae03..0b663ef64 100644 --- a/examples/foundational/55zf-update-settings-camb-tts.py +++ b/examples/foundational/55zf-update-settings-camb-tts.py @@ -96,16 +96,13 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): messages.append({"role": "system", "content": "Please introduce yourself to the user."}) await task.queue_frames([LLMRunFrame()]) - async def update_settings(): - await asyncio.sleep(10) - logger.info('Updating Camb TTS settings: user_instructions="Speak enthusiastically"') - await task.queue_frame( - TTSUpdateSettingsFrame( - update=CambTTSSettings(user_instructions="Speak enthusiastically") - ) + await asyncio.sleep(10) + logger.info('Updating Camb TTS settings: user_instructions="Speak enthusiastically"') + await task.queue_frame( + TTSUpdateSettingsFrame( + update=CambTTSSettings(user_instructions="Speak enthusiastically") ) - - asyncio.create_task(update_settings()) + ) @transport.event_handler("on_client_disconnected") async def on_client_disconnected(transport, client): diff --git a/examples/foundational/55zg-update-settings-hathora-tts.py b/examples/foundational/55zg-update-settings-hathora-tts.py index 2c59029b8..363ac7d85 100644 --- a/examples/foundational/55zg-update-settings-hathora-tts.py +++ b/examples/foundational/55zg-update-settings-hathora-tts.py @@ -99,12 +99,9 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): messages.append({"role": "system", "content": "Please introduce yourself to the user."}) await task.queue_frames([LLMRunFrame()]) - async def update_settings(): - await asyncio.sleep(10) - logger.info("Updating Hathora TTS settings: speed=1.3") - await task.queue_frame(TTSUpdateSettingsFrame(update=HathoraTTSSettings(speed=1.3))) - - asyncio.create_task(update_settings()) + await asyncio.sleep(10) + logger.info("Updating Hathora TTS settings: speed=1.3") + await task.queue_frame(TTSUpdateSettingsFrame(update=HathoraTTSSettings(speed=1.3))) @transport.event_handler("on_client_disconnected") async def on_client_disconnected(transport, client): diff --git a/examples/foundational/55zh-update-settings-resembleai-tts.py b/examples/foundational/55zh-update-settings-resembleai-tts.py index 39ab30eee..10d750394 100644 --- a/examples/foundational/55zh-update-settings-resembleai-tts.py +++ b/examples/foundational/55zh-update-settings-resembleai-tts.py @@ -99,16 +99,13 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): messages.append({"role": "system", "content": "Please introduce yourself to the user."}) await task.queue_frames([LLMRunFrame()]) - async def update_settings(): - await asyncio.sleep(10) - logger.info("Updating ResembleAI TTS settings: voice (changed)") - await task.queue_frame( - TTSUpdateSettingsFrame( - update=ResembleAITTSSettings(voice=os.getenv("RESEMBLEAI_VOICE_ID_ALT", "")) - ) + await asyncio.sleep(10) + logger.info("Updating ResembleAI TTS settings: voice (changed)") + await task.queue_frame( + TTSUpdateSettingsFrame( + update=ResembleAITTSSettings(voice=os.getenv("RESEMBLEAI_VOICE_ID_ALT", "")) ) - - asyncio.create_task(update_settings()) + ) @transport.event_handler("on_client_disconnected") async def on_client_disconnected(transport, client): diff --git a/examples/foundational/55zi-update-settings-openai-llm.py b/examples/foundational/55zi-update-settings-openai-llm.py index d4befeddb..a8c253bc2 100644 --- a/examples/foundational/55zi-update-settings-openai-llm.py +++ b/examples/foundational/55zi-update-settings-openai-llm.py @@ -100,14 +100,9 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): messages.append({"role": "system", "content": "Please introduce yourself to the user."}) await task.queue_frames([LLMRunFrame()]) - async def update_settings(): - await asyncio.sleep(10) - logger.info("Updating OpenAI LLM settings: temperature=0.1") - await task.queue_frame( - LLMUpdateSettingsFrame(update=OpenAILLMSettings(temperature=0.1)) - ) - - asyncio.create_task(update_settings()) + await asyncio.sleep(10) + logger.info("Updating OpenAI LLM settings: temperature=0.1") + await task.queue_frame(LLMUpdateSettingsFrame(update=OpenAILLMSettings(temperature=0.1))) @transport.event_handler("on_client_disconnected") async def on_client_disconnected(transport, client): diff --git a/examples/foundational/55zj-update-settings-anthropic-llm.py b/examples/foundational/55zj-update-settings-anthropic-llm.py index e2a2af3db..4c8341a6a 100644 --- a/examples/foundational/55zj-update-settings-anthropic-llm.py +++ b/examples/foundational/55zj-update-settings-anthropic-llm.py @@ -99,14 +99,9 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): messages.append({"role": "system", "content": "Please introduce yourself to the user."}) await task.queue_frames([LLMRunFrame()]) - async def update_settings(): - await asyncio.sleep(10) - logger.info("Updating Anthropic LLM settings: temperature=0.1") - await task.queue_frame( - LLMUpdateSettingsFrame(update=AnthropicLLMSettings(temperature=0.1)) - ) - - asyncio.create_task(update_settings()) + await asyncio.sleep(10) + logger.info("Updating Anthropic LLM settings: temperature=0.1") + await task.queue_frame(LLMUpdateSettingsFrame(update=AnthropicLLMSettings(temperature=0.1))) @transport.event_handler("on_client_disconnected") async def on_client_disconnected(transport, client): diff --git a/examples/foundational/55zk-update-settings-google-llm.py b/examples/foundational/55zk-update-settings-google-llm.py index 6d7ba9573..140c0fccb 100644 --- a/examples/foundational/55zk-update-settings-google-llm.py +++ b/examples/foundational/55zk-update-settings-google-llm.py @@ -99,14 +99,9 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): messages.append({"role": "system", "content": "Please introduce yourself to the user."}) await task.queue_frames([LLMRunFrame()]) - async def update_settings(): - await asyncio.sleep(10) - logger.info("Updating Google LLM settings: temperature=0.1") - await task.queue_frame( - LLMUpdateSettingsFrame(update=GoogleLLMSettings(temperature=0.1)) - ) - - asyncio.create_task(update_settings()) + await asyncio.sleep(10) + logger.info("Updating Google LLM settings: temperature=0.1") + await task.queue_frame(LLMUpdateSettingsFrame(update=GoogleLLMSettings(temperature=0.1))) @transport.event_handler("on_client_disconnected") async def on_client_disconnected(transport, client): diff --git a/examples/foundational/55zl-update-settings-openai-realtime.py b/examples/foundational/55zl-update-settings-openai-realtime.py index 9f6daadfd..2207b6851 100644 --- a/examples/foundational/55zl-update-settings-openai-realtime.py +++ b/examples/foundational/55zl-update-settings-openai-realtime.py @@ -87,14 +87,11 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): logger.info(f"Client connected") await task.queue_frames([LLMRunFrame()]) - async def update_settings(): - await asyncio.sleep(10) - logger.info("Updating OpenAI Realtime LLM settings: temperature=0.1") - await task.queue_frame( - LLMUpdateSettingsFrame(update=OpenAIRealtimeLLMSettings(temperature=0.1)) - ) - - asyncio.create_task(update_settings()) + await asyncio.sleep(10) + logger.info("Updating OpenAI Realtime LLM settings: temperature=0.1") + await task.queue_frame( + LLMUpdateSettingsFrame(update=OpenAIRealtimeLLMSettings(temperature=0.1)) + ) @transport.event_handler("on_client_disconnected") async def on_client_disconnected(transport, client): diff --git a/examples/foundational/55zm-update-settings-gemini-live.py b/examples/foundational/55zm-update-settings-gemini-live.py index 0a5b38529..8ad635fd5 100644 --- a/examples/foundational/55zm-update-settings-gemini-live.py +++ b/examples/foundational/55zm-update-settings-gemini-live.py @@ -87,14 +87,11 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): logger.info(f"Client connected") await task.queue_frames([LLMRunFrame()]) - async def update_settings(): - await asyncio.sleep(10) - logger.info("Updating Gemini Live LLM settings: temperature=0.1") - await task.queue_frame( - LLMUpdateSettingsFrame(update=GeminiLiveLLMSettings(temperature=0.1)) - ) - - asyncio.create_task(update_settings()) + await asyncio.sleep(10) + logger.info("Updating Gemini Live LLM settings: temperature=0.1") + await task.queue_frame( + LLMUpdateSettingsFrame(update=GeminiLiveLLMSettings(temperature=0.1)) + ) @transport.event_handler("on_client_disconnected") async def on_client_disconnected(transport, client): diff --git a/examples/foundational/55zn-update-settings-ultravox-realtime.py b/examples/foundational/55zn-update-settings-ultravox-realtime.py index 7fcb25d83..8c640ccc4 100644 --- a/examples/foundational/55zn-update-settings-ultravox-realtime.py +++ b/examples/foundational/55zn-update-settings-ultravox-realtime.py @@ -93,14 +93,11 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): logger.info(f"Client connected") await task.queue_frames([LLMRunFrame()]) - async def update_settings(): - await asyncio.sleep(10) - logger.info("Updating Ultravox Realtime LLM settings: temperature=0.1") - await task.queue_frame( - LLMUpdateSettingsFrame(update=UltravoxRealtimeLLMSettings(temperature=0.1)) - ) - - asyncio.create_task(update_settings()) + await asyncio.sleep(10) + logger.info("Updating Ultravox Realtime LLM settings: temperature=0.1") + await task.queue_frame( + LLMUpdateSettingsFrame(update=UltravoxRealtimeLLMSettings(temperature=0.1)) + ) @transport.event_handler("on_client_disconnected") async def on_client_disconnected(transport, client): diff --git a/examples/foundational/55zo-update-settings-grok-realtime.py b/examples/foundational/55zo-update-settings-grok-realtime.py index 6366ee933..567eeae2b 100644 --- a/examples/foundational/55zo-update-settings-grok-realtime.py +++ b/examples/foundational/55zo-update-settings-grok-realtime.py @@ -87,14 +87,11 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): logger.info(f"Client connected") await task.queue_frames([LLMRunFrame()]) - async def update_settings(): - await asyncio.sleep(10) - logger.info("Updating Grok Realtime LLM settings: temperature=0.1") - await task.queue_frame( - LLMUpdateSettingsFrame(update=GrokRealtimeLLMSettings(temperature=0.1)) - ) - - asyncio.create_task(update_settings()) + await asyncio.sleep(10) + logger.info("Updating Grok Realtime LLM settings: temperature=0.1") + await task.queue_frame( + LLMUpdateSettingsFrame(update=GrokRealtimeLLMSettings(temperature=0.1)) + ) @transport.event_handler("on_client_disconnected") async def on_client_disconnected(transport, client): diff --git a/examples/foundational/55zp-update-settings-aws-bedrock-llm.py b/examples/foundational/55zp-update-settings-aws-bedrock-llm.py index 0b26774ae..aaf0d973c 100644 --- a/examples/foundational/55zp-update-settings-aws-bedrock-llm.py +++ b/examples/foundational/55zp-update-settings-aws-bedrock-llm.py @@ -99,14 +99,11 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): messages.append({"role": "system", "content": "Please introduce yourself to the user."}) await task.queue_frames([LLMRunFrame()]) - async def update_settings(): - await asyncio.sleep(10) - logger.info("Updating AWS Bedrock LLM settings: temperature=0.1") - await task.queue_frame( - LLMUpdateSettingsFrame(update=AWSBedrockLLMSettings(temperature=0.1)) - ) - - asyncio.create_task(update_settings()) + await asyncio.sleep(10) + logger.info("Updating AWS Bedrock LLM settings: temperature=0.1") + await task.queue_frame( + LLMUpdateSettingsFrame(update=AWSBedrockLLMSettings(temperature=0.1)) + ) @transport.event_handler("on_client_disconnected") async def on_client_disconnected(transport, client): From d913d954dbf65d4e9bd2d734704b8427fd9fadd2 Mon Sep 17 00:00:00 2001 From: Paul Kompfner Date: Wed, 18 Feb 2026 11:34:52 -0500 Subject: [PATCH 0520/1060] Fix `SpeechmaticsSTTService` settings update code, and augment test file to better exercise it --- .../55h-update-settings-speechmatics-stt.py | 27 ++++++++++++++++++- src/pipecat/services/speechmatics/stt.py | 20 +++++++++----- 2 files changed, 40 insertions(+), 7 deletions(-) diff --git a/examples/foundational/55h-update-settings-speechmatics-stt.py b/examples/foundational/55h-update-settings-speechmatics-stt.py index 46ed44016..d041d69d2 100644 --- a/examples/foundational/55h-update-settings-speechmatics-stt.py +++ b/examples/foundational/55h-update-settings-speechmatics-stt.py @@ -51,7 +51,14 @@ transport_params = { async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): logger.info(f"Starting bot") - stt = SpeechmaticsSTTService(api_key=os.getenv("SPEECHMATICS_API_KEY")) + stt = SpeechmaticsSTTService( + api_key=os.getenv("SPEECHMATICS_API_KEY"), + params=SpeechmaticsSTTService.InputParams( + enable_diarization=True, + speaker_active_format="<{speaker_id}>{text}", + speaker_passive_format="<{speaker_id}>{text}", + ), + ) tts = CartesiaTTSService( api_key=os.getenv("CARTESIA_API_KEY"), @@ -106,6 +113,24 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): STTUpdateSettingsFrame(update=SpeechmaticsSTTSettings(language=Language.ES)) ) + await asyncio.sleep(10) + logger.info("Updating Speechmatics STT settings: focus_speakers=['S1']") + await task.queue_frame( + STTUpdateSettingsFrame(update=SpeechmaticsSTTSettings(focus_speakers=["S1"])) + ) + + await asyncio.sleep(10) + logger.info( + "Updating Speechmatics STT settings: speaker_active_format={text}" + ) + await task.queue_frame( + STTUpdateSettingsFrame( + update=SpeechmaticsSTTSettings( + speaker_active_format="{text}" + ) + ) + ) + @transport.event_handler("on_client_disconnected") async def on_client_disconnected(transport, client): logger.info(f"Client disconnected") diff --git a/src/pipecat/services/speechmatics/stt.py b/src/pipecat/services/speechmatics/stt.py index c6fe0d16e..166e19d97 100644 --- a/src/pipecat/services/speechmatics/stt.py +++ b/src/pipecat/services/speechmatics/stt.py @@ -508,12 +508,14 @@ class SpeechmaticsSTTService(STTService): needs_reconnect = bool(changed.keys() - no_reconnect) if needs_reconnect: + logger.debug(f"{self} settings update requires reconnect: {changed.keys()}") # Connection-level fields changed — rebuild the SDK config # from the now-updated self._settings, then reconnect. self._config = self._build_config() await self._disconnect() await self._connect() - elif changed & SpeechmaticsSTTSettings.HOT_FIELDS: + elif changed.keys() & SpeechmaticsSTTSettings.HOT_FIELDS: + logger.debug(f"{self} applying hot settings update: {changed.keys()}") if self._config.enable_diarization: # Only hot-updatable fields changed — push to the live session. self._config.speaker_config.focus_speakers = self._settings.focus_speakers @@ -522,11 +524,17 @@ class SpeechmaticsSTTService(STTService): if self._client: self._client.update_diarization_config(self._config.speaker_config) else: - # Diarization not enabled — need a full reconnect to apply. - self._config = self._build_config() - await self._disconnect() - await self._connect() - # LOCAL_FIELDS: already applied by super(); nothing else to do. + logger.debug( + f"{self} hot settings updated but diarization not enabled: {changed.keys()}. ignoring." + ) + # Diarization not enabled — the new settings will take effect + # if/when diarization is enabled, which does require a reconnect. + elif changed.keys() & SpeechmaticsSTTSettings.LOCAL_FIELDS: + logger.debug( + f"{self} local settings update, no special action required: {changed.keys()}" + ) + # Only local fields changed — no need to push to the STT engine, + # the new settings will take effect immediately. return changed From a14690e3a0150e89e479125dcc25124b056f3910 Mon Sep 17 00:00:00 2001 From: Paul Kompfner Date: Wed, 18 Feb 2026 11:55:14 -0500 Subject: [PATCH 0521/1060] Fix the 55i example --- .../55i-update-settings-whisper-api-stt.py | 20 +++++++++---------- 1 file changed, 9 insertions(+), 11 deletions(-) diff --git a/examples/foundational/55i-update-settings-whisper-api-stt.py b/examples/foundational/55i-update-settings-whisper-api-stt.py index 27581a819..1d5022674 100644 --- a/examples/foundational/55i-update-settings-whisper-api-stt.py +++ b/examples/foundational/55i-update-settings-whisper-api-stt.py @@ -24,7 +24,8 @@ from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport from pipecat.services.cartesia.tts import CartesiaTTSService from pipecat.services.openai.llm import OpenAILLMService -from pipecat.services.whisper.base_stt import BaseWhisperSTTService, BaseWhisperSTTSettings +from pipecat.services.openai.stt import OpenAISTTService +from pipecat.services.whisper.base_stt import BaseWhisperSTTSettings from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams @@ -50,8 +51,11 @@ transport_params = { async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): logger.info(f"Starting bot") - stt = BaseWhisperSTTService( - model="whisper-1", + # This file is meant to exercise Whisper API-based STT services, so we use + # OpenAI's Whisper STT as an example here. Here we could've also used: + # - SambaNova + # - Groq + stt = OpenAISTTService( api_key=os.getenv("OPENAI_API_KEY"), ) @@ -103,14 +107,8 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): await task.queue_frames([LLMRunFrame()]) await asyncio.sleep(10) - logger.info( - 'Updating Whisper API STT settings: prompt="Transcribe in English", temperature=0.5' - ) - await task.queue_frame( - STTUpdateSettingsFrame( - update=BaseWhisperSTTSettings(prompt="Transcribe in English", temperature=0.5) - ) - ) + logger.info('Updating OpenAI STT settings: language="es"') + await task.queue_frame(STTUpdateSettingsFrame(update=BaseWhisperSTTSettings(language="es"))) @transport.event_handler("on_client_disconnected") async def on_client_disconnected(transport, client): From b8b531b66a1b9646bbde37907f7d0534701fe498 Mon Sep 17 00:00:00 2001 From: Paul Kompfner Date: Wed, 18 Feb 2026 12:37:34 -0500 Subject: [PATCH 0522/1060] In Cartesia TTS service, we don't need to override `_update_settings`. Parent class handling is enough, as new settings are picked up on the next `run_tts` (no need to reconnect). --- .../55n-update-settings-cartesia-tts.py | 10 +++++++--- src/pipecat/services/cartesia/tts.py | 19 ------------------- 2 files changed, 7 insertions(+), 22 deletions(-) diff --git a/examples/foundational/55n-update-settings-cartesia-tts.py b/examples/foundational/55n-update-settings-cartesia-tts.py index 38070765c..303c23a25 100644 --- a/examples/foundational/55n-update-settings-cartesia-tts.py +++ b/examples/foundational/55n-update-settings-cartesia-tts.py @@ -22,7 +22,7 @@ from pipecat.processors.aggregators.llm_response_universal import ( ) from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport -from pipecat.services.cartesia.tts import CartesiaTTSService, CartesiaTTSSettings +from pipecat.services.cartesia.tts import CartesiaTTSService, CartesiaTTSSettings, GenerationConfig from pipecat.services.deepgram.stt import DeepgramSTTService from pipecat.services.openai.llm import OpenAILLMService from pipecat.transports.base_transport import BaseTransport, TransportParams @@ -103,8 +103,12 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): await task.queue_frames([LLMRunFrame()]) await asyncio.sleep(10) - logger.info("Updating Cartesia TTS settings: speed=fast") - await task.queue_frame(TTSUpdateSettingsFrame(update=CartesiaTTSSettings(speed="fast"))) + logger.info("Updating Cartesia TTS settings: speed increased to 1.5") + await task.queue_frame( + TTSUpdateSettingsFrame( + update=CartesiaTTSSettings(generation_config=GenerationConfig(speed=1.5)) + ) + ) @transport.event_handler("on_client_disconnected") async def on_client_disconnected(transport, client): diff --git a/src/pipecat/services/cartesia/tts.py b/src/pipecat/services/cartesia/tts.py index edee9e2ea..4e45f50aa 100644 --- a/src/pipecat/services/cartesia/tts.py +++ b/src/pipecat/services/cartesia/tts.py @@ -355,25 +355,6 @@ class CartesiaTTSService(AudioContextWordTTSService): """ return True - async def _update_settings(self, update: TTSSettings) -> dict[str, Any]: - """Apply a settings update. - - Settings are stored but not applied to the active connection. - """ - changed = await super()._update_settings(update) - - if not changed: - return changed - - # TODO: someday we could reconnect here to apply updated settings. - # Code might look something like the below: - # await self._disconnect() - # await self._connect() - - self._warn_unhandled_updated_settings(changed) - - return changed - def language_to_service_language(self, language: Language) -> Optional[str]: """Convert a Language enum to Cartesia language format. From caf5dacbe86ea10c5cb07ec230ba29c7356ed2a4 Mon Sep 17 00:00:00 2001 From: Paul Kompfner Date: Wed, 18 Feb 2026 12:37:50 -0500 Subject: [PATCH 0523/1060] Update 55j example to avoid console warning --- examples/foundational/55j-update-settings-sarvam-stt.py | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/examples/foundational/55j-update-settings-sarvam-stt.py b/examples/foundational/55j-update-settings-sarvam-stt.py index b7f619987..e39c5cb5a 100644 --- a/examples/foundational/55j-update-settings-sarvam-stt.py +++ b/examples/foundational/55j-update-settings-sarvam-stt.py @@ -101,9 +101,9 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): await task.queue_frames([LLMRunFrame()]) await asyncio.sleep(10) - logger.info("Updating Sarvam STT settings: language=hi") + logger.info("Updating Sarvam STT settings: language=en-IN") await task.queue_frame( - STTUpdateSettingsFrame(update=SarvamSTTSettings(language=Language.HI)) + STTUpdateSettingsFrame(update=SarvamSTTSettings(language=Language.EN_IN)) ) @transport.event_handler("on_client_disconnected") From 17886d14e8d2d710b5631be8ed64df27bd5c922b Mon Sep 17 00:00:00 2001 From: Paul Kompfner Date: Wed, 18 Feb 2026 13:47:02 -0500 Subject: [PATCH 0524/1060] Fix `ElevenLabsTTSService` settings update code --- .../foundational/55o-update-settings-elevenlabs-tts.py | 7 +++---- src/pipecat/services/elevenlabs/tts.py | 8 ++++---- 2 files changed, 7 insertions(+), 8 deletions(-) diff --git a/examples/foundational/55o-update-settings-elevenlabs-tts.py b/examples/foundational/55o-update-settings-elevenlabs-tts.py index 0ca72ba5b..6c85e2452 100644 --- a/examples/foundational/55o-update-settings-elevenlabs-tts.py +++ b/examples/foundational/55o-update-settings-elevenlabs-tts.py @@ -25,6 +25,7 @@ from pipecat.runner.utils import create_transport from pipecat.services.deepgram.stt import DeepgramSTTService from pipecat.services.elevenlabs.tts import ElevenLabsTTSService, ElevenLabsTTSSettings from pipecat.services.openai.llm import OpenAILLMService +from pipecat.transcriptions.language import Language from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams @@ -100,10 +101,8 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): await task.queue_frames([LLMRunFrame()]) await asyncio.sleep(10) - logger.info("Updating ElevenLabs TTS settings: speed=1.2, stability=0.3") - await task.queue_frame( - TTSUpdateSettingsFrame(update=ElevenLabsTTSSettings(speed=1.2, stability=0.3)) - ) + logger.info("Updating ElevenLabs TTS settings: speed=1.2") + await task.queue_frame(TTSUpdateSettingsFrame(update=ElevenLabsTTSSettings(speed=0.7))) @transport.event_handler("on_client_disconnected") async def on_client_disconnected(transport, client): diff --git a/src/pipecat/services/elevenlabs/tts.py b/src/pipecat/services/elevenlabs/tts.py index 022b08b94..fbde4a4b7 100644 --- a/src/pipecat/services/elevenlabs/tts.py +++ b/src/pipecat/services/elevenlabs/tts.py @@ -492,19 +492,19 @@ class ElevenLabsTTSService(AudioContextWordTTSService): # Rebuild voice settings for next context self._voice_settings = self._set_voice_settings() - url_changed = bool(changed & ElevenLabsTTSSettings.URL_FIELDS) - voice_settings_changed = bool(changed & ElevenLabsTTSSettings.VOICE_SETTINGS_FIELDS) + url_changed = bool(changed.keys() & ElevenLabsTTSSettings.URL_FIELDS) + voice_settings_changed = bool(changed.keys() & ElevenLabsTTSSettings.VOICE_SETTINGS_FIELDS) if url_changed: logger.debug( - f"URL-level setting changed ({changed & ElevenLabsTTSSettings.URL_FIELDS}), " + f"URL-level setting changed ({changed.keys() & ElevenLabsTTSSettings.URL_FIELDS}), " f"reconnecting WebSocket" ) await self._disconnect() await self._connect() elif voice_settings_changed and self._context_id: logger.debug( - f"Voice settings changed ({changed & ElevenLabsTTSSettings.VOICE_SETTINGS_FIELDS}), " + f"Voice settings changed ({changed.keys() & ElevenLabsTTSSettings.VOICE_SETTINGS_FIELDS}), " f"closing current context to apply changes" ) try: From 28677ec829d043e4804589e7dbc631ff4927b253 Mon Sep 17 00:00:00 2001 From: Paul Kompfner Date: Wed, 18 Feb 2026 13:49:32 -0500 Subject: [PATCH 0525/1060] Tweak 55p example to make the settings update more pronounced --- examples/foundational/55p-update-settings-openai-tts.py | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/examples/foundational/55p-update-settings-openai-tts.py b/examples/foundational/55p-update-settings-openai-tts.py index 58e8efde1..5aef081fc 100644 --- a/examples/foundational/55p-update-settings-openai-tts.py +++ b/examples/foundational/55p-update-settings-openai-tts.py @@ -98,8 +98,8 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): await task.queue_frames([LLMRunFrame()]) await asyncio.sleep(10) - logger.info("Updating OpenAI TTS settings: speed=1.5") - await task.queue_frame(TTSUpdateSettingsFrame(update=OpenAITTSSettings(speed=1.5))) + logger.info("Updating OpenAI TTS settings: speed=2.0") + await task.queue_frame(TTSUpdateSettingsFrame(update=OpenAITTSSettings(speed=2.0))) @transport.event_handler("on_client_disconnected") async def on_client_disconnected(transport, client): From 728a97ade327c58fa276036ba53cbc61caf4b89c Mon Sep 17 00:00:00 2001 From: Paul Kompfner Date: Wed, 18 Feb 2026 14:11:51 -0500 Subject: [PATCH 0526/1060] Update Deepgram TTS to support updating settings dynamically --- .../55q-update-settings-deepgram-tts.py | 6 ++++++ src/pipecat/services/deepgram/tts.py | 19 ++++++++++++++++++- 2 files changed, 24 insertions(+), 1 deletion(-) diff --git a/examples/foundational/55q-update-settings-deepgram-tts.py b/examples/foundational/55q-update-settings-deepgram-tts.py index 4b7f50ae8..636342194 100644 --- a/examples/foundational/55q-update-settings-deepgram-tts.py +++ b/examples/foundational/55q-update-settings-deepgram-tts.py @@ -102,6 +102,12 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): TTSUpdateSettingsFrame(update=DeepgramTTSSettings(voice="aura-2-luna-en")) ) + await asyncio.sleep(10) + logger.info('Updating Deepgram TTS settings: voice="aura-2-aries-en"') + await task.queue_frame( + TTSUpdateSettingsFrame(update=DeepgramTTSSettings(voice="aura-2-aries-en")) + ) + @transport.event_handler("on_client_disconnected") async def on_client_disconnected(transport, client): logger.info(f"Client disconnected") diff --git a/src/pipecat/services/deepgram/tts.py b/src/pipecat/services/deepgram/tts.py index bccbace26..7f4d78f13 100644 --- a/src/pipecat/services/deepgram/tts.py +++ b/src/pipecat/services/deepgram/tts.py @@ -12,7 +12,7 @@ for generating speech from text using various voice models. import json from dataclasses import dataclass, field -from typing import AsyncGenerator, Optional +from typing import Any, AsyncGenerator, Optional import aiohttp from loguru import logger @@ -183,6 +183,23 @@ class DeepgramTTSService(WebsocketTTSService): await self._disconnect_websocket() + async def _update_settings(self, update: TTSSettings) -> dict[str, Any]: + """Apply a settings update. + + Args: + update: A :class:`TTSSettings` (or ``DeepgramTTSSettings``) delta. + + Returns: + Dict mapping changed field names to their previous values. + """ + changed = await super()._update_settings(update) + + if changed: + await self._disconnect() + await self._connect() + + return changed + async def _connect_websocket(self): """Connect to Deepgram WebSocket API with configured settings.""" try: From b4c5cb258bb9687f47925857acb0a26a1892f16d Mon Sep 17 00:00:00 2001 From: Paul Kompfner Date: Wed, 18 Feb 2026 14:15:14 -0500 Subject: [PATCH 0527/1060] Tweak 55r example to make the settings update more pronounced --- examples/foundational/55r-update-settings-azure-tts.py | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/examples/foundational/55r-update-settings-azure-tts.py b/examples/foundational/55r-update-settings-azure-tts.py index 076901707..d156eab43 100644 --- a/examples/foundational/55r-update-settings-azure-tts.py +++ b/examples/foundational/55r-update-settings-azure-tts.py @@ -100,9 +100,9 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): await task.queue_frames([LLMRunFrame()]) await asyncio.sleep(10) - logger.info('Updating Azure TTS settings: rate="1.3", style="cheerful"') + logger.info('Updating Azure TTS settings: rate="0.7", style="sad"') await task.queue_frame( - TTSUpdateSettingsFrame(update=AzureTTSSettings(rate="1.3", style="cheerful")) + TTSUpdateSettingsFrame(update=AzureTTSSettings(rate="0.7", style="sad")) ) @transport.event_handler("on_client_disconnected") From 416e1cf877f7e83dccbfa460bf2d00c27ca761d5 Mon Sep 17 00:00:00 2001 From: Paul Kompfner Date: Wed, 18 Feb 2026 14:33:12 -0500 Subject: [PATCH 0528/1060] Update Rime TTS services to store voice in the standard `settings.voice` field, as opposed to the nonstandard `speaker` field --- .../55u-update-settings-rime-tts.py | 4 ++-- src/pipecat/services/rime/tts.py | 24 ++++++++----------- 2 files changed, 12 insertions(+), 16 deletions(-) diff --git a/examples/foundational/55u-update-settings-rime-tts.py b/examples/foundational/55u-update-settings-rime-tts.py index e95aeb830..25d0515fe 100644 --- a/examples/foundational/55u-update-settings-rime-tts.py +++ b/examples/foundational/55u-update-settings-rime-tts.py @@ -100,8 +100,8 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): await task.queue_frames([LLMRunFrame()]) await asyncio.sleep(10) - logger.info("Updating Rime TTS settings: speedAlpha=1.5") - await task.queue_frame(TTSUpdateSettingsFrame(update=RimeTTSSettings(speedAlpha=1.5))) + logger.info("Updating Rime TTS settings: voice=rex") + await task.queue_frame(TTSUpdateSettingsFrame(update=RimeTTSSettings(voice="rex"))) @transport.event_handler("on_client_disconnected") async def on_client_disconnected(transport, client): diff --git a/src/pipecat/services/rime/tts.py b/src/pipecat/services/rime/tts.py index 9e916025c..d76eafbfa 100644 --- a/src/pipecat/services/rime/tts.py +++ b/src/pipecat/services/rime/tts.py @@ -13,7 +13,7 @@ using Rime's API for streaming and batch audio synthesis. import base64 import json from dataclasses import dataclass, field -from typing import Any, AsyncGenerator, Optional +from typing import Any, AsyncGenerator, ClassVar, Dict, Optional import aiohttp from loguru import logger @@ -75,7 +75,6 @@ class RimeTTSSettings(TTSSettings): """Settings for Rime WS JSON and HTTP TTS services. Parameters: - speaker: Voice speaker ID. modelId: Rime model identifier. audioFormat: Audio output format. samplingRate: Audio sample rate. @@ -87,7 +86,6 @@ class RimeTTSSettings(TTSSettings): inlineSpeedAlpha: Inline speed control markup. """ - speaker: str = field(default_factory=lambda: NOT_GIVEN) modelId: str = field(default_factory=lambda: NOT_GIVEN) audioFormat: str = field(default_factory=lambda: NOT_GIVEN) samplingRate: int = field(default_factory=lambda: NOT_GIVEN) @@ -98,13 +96,14 @@ class RimeTTSSettings(TTSSettings): phonemizeBetweenBrackets: bool = field(default_factory=lambda: NOT_GIVEN) inlineSpeedAlpha: str = field(default_factory=lambda: NOT_GIVEN) + _aliases: ClassVar[Dict[str, str]] = {"speaker": "voice"} + @dataclass class RimeNonJsonTTSSettings(TTSSettings): """Settings for Rime non-JSON WS TTS service. Parameters: - speaker: Voice speaker ID. modelId: Rime model identifier. audioFormat: Audio output format. samplingRate: Audio sample rate. @@ -115,7 +114,6 @@ class RimeNonJsonTTSSettings(TTSSettings): top_p: Cumulative probability threshold (0.0-1.0). """ - speaker: str = field(default_factory=lambda: NOT_GIVEN) modelId: str = field(default_factory=lambda: NOT_GIVEN) audioFormat: str = field(default_factory=lambda: NOT_GIVEN) samplingRate: int = field(default_factory=lambda: NOT_GIVEN) @@ -125,6 +123,8 @@ class RimeNonJsonTTSSettings(TTSSettings): temperature: float = field(default_factory=lambda: NOT_GIVEN) top_p: float = field(default_factory=lambda: NOT_GIVEN) + _aliases: ClassVar[Dict[str, str]] = {"speaker": "voice"} + class RimeTTSService(AudioContextWordTTSService): """Text-to-Speech service using Rime's websocket API. @@ -210,7 +210,7 @@ class RimeTTSService(AudioContextWordTTSService): self._voice_id = voice_id self._model = model self._settings = RimeTTSSettings( - speaker=voice_id, + voice=voice_id, modelId=model, audioFormat="pcm", samplingRate=0, @@ -273,10 +273,8 @@ class RimeTTSService(AudioContextWordTTSService): async def _update_settings(self, update: TTSSettings) -> dict[str, Any]: """Apply a settings update and reconnect if voice changed.""" - prev_voice = self._voice_id changed = await super()._update_settings(update) if "voice" in changed: - self._settings.speaker = self._voice_id await self._disconnect() await self._connect() else: @@ -355,7 +353,7 @@ class RimeTTSService(AudioContextWordTTSService): params = "&".join( f"{k}={v}" for k, v in { - "speaker": self._settings.speaker, + "speaker": self._settings.voice, "modelId": self._settings.modelId, "audioFormat": self._settings.audioFormat, "samplingRate": self._settings.samplingRate, @@ -772,7 +770,7 @@ class RimeNonJsonTTSService(InterruptibleTTSService): self._voice_id = voice_id self._model = model self._settings = RimeNonJsonTTSSettings( - speaker=voice_id, + voice=voice_id, modelId=model, audioFormat=audio_format, samplingRate=sample_rate, @@ -866,7 +864,7 @@ class RimeNonJsonTTSService(InterruptibleTTSService): return # Build URL with query parameters (only given, non-None values) settings_dict = { - "speaker": self._settings.speaker, + "speaker": self._settings.voice, "modelId": self._settings.modelId, "audioFormat": self._settings.audioFormat, "samplingRate": self._settings.samplingRate, @@ -985,9 +983,7 @@ class RimeNonJsonTTSService(InterruptibleTTSService): """ changed = await super()._update_settings(update) - # Sync voice and model to settings dict fields - if "voice" in changed: - self._settings.speaker = self._voice_id + # Sync model to settings dict field if "model" in changed: self._settings.modelId = self._model_name From 0c73b7732717a850030fae2e6a947867328ba463 Mon Sep 17 00:00:00 2001 From: Paul Kompfner Date: Wed, 18 Feb 2026 14:47:38 -0500 Subject: [PATCH 0529/1060] Update Lmnt TTS to support updating settings dynamically --- .../55v-update-settings-lmnt-tts.py | 4 ++-- src/pipecat/services/lmnt/tts.py | 19 ++++++++++++++++++- 2 files changed, 20 insertions(+), 3 deletions(-) diff --git a/examples/foundational/55v-update-settings-lmnt-tts.py b/examples/foundational/55v-update-settings-lmnt-tts.py index c8e6a3e09..d98462e20 100644 --- a/examples/foundational/55v-update-settings-lmnt-tts.py +++ b/examples/foundational/55v-update-settings-lmnt-tts.py @@ -100,8 +100,8 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): await task.queue_frames([LLMRunFrame()]) await asyncio.sleep(10) - logger.info('Updating LMNT TTS settings: voice="lily"') - await task.queue_frame(TTSUpdateSettingsFrame(update=LmntTTSSettings(voice="lily"))) + logger.info('Updating LMNT TTS settings: voice="tyler"') + await task.queue_frame(TTSUpdateSettingsFrame(update=LmntTTSSettings(voice="tyler"))) @transport.event_handler("on_client_disconnected") async def on_client_disconnected(transport, client): diff --git a/src/pipecat/services/lmnt/tts.py b/src/pipecat/services/lmnt/tts.py index 1b23c8ae2..5b2adcaf4 100644 --- a/src/pipecat/services/lmnt/tts.py +++ b/src/pipecat/services/lmnt/tts.py @@ -8,7 +8,7 @@ import json from dataclasses import dataclass, field -from typing import AsyncGenerator, Optional +from typing import Any, AsyncGenerator, Optional from loguru import logger @@ -207,6 +207,23 @@ class LmntTTSService(InterruptibleTTSService): await self._disconnect_websocket() + async def _update_settings(self, update: TTSSettings) -> dict[str, Any]: + """Apply a settings update. + + Args: + update: A :class:`TTSSettings` (or ``LmntTTSSettings``) delta. + + Returns: + Dict mapping changed field names to their previous values. + """ + changed = await super()._update_settings(update) + + if changed: + await self._disconnect() + await self._connect() + + return changed + async def _connect_websocket(self): """Connect to LMNT websocket.""" try: From 323ee00b831c3cf7e045dbebc628362f6c296da5 Mon Sep 17 00:00:00 2001 From: Paul Kompfner Date: Wed, 18 Feb 2026 14:51:48 -0500 Subject: [PATCH 0530/1060] Fix 55w example --- examples/foundational/55w-update-settings-fish-tts.py | 5 ++++- src/pipecat/services/fish/tts.py | 2 ++ 2 files changed, 6 insertions(+), 1 deletion(-) diff --git a/examples/foundational/55w-update-settings-fish-tts.py b/examples/foundational/55w-update-settings-fish-tts.py index be9049333..82722ec34 100644 --- a/examples/foundational/55w-update-settings-fish-tts.py +++ b/examples/foundational/55w-update-settings-fish-tts.py @@ -52,7 +52,10 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): stt = DeepgramSTTService(api_key=os.getenv("DEEPGRAM_API_KEY")) - tts = FishAudioTTSService(api_key=os.getenv("FISH_API_KEY")) + tts = FishAudioTTSService( + api_key=os.getenv("FISH_API_KEY"), + model="4ce7e917cedd4bc2bb2e6ff3a46acaa1", # Barack Obama + ) llm = OpenAILLMService(api_key=os.getenv("OPENAI_API_KEY")) diff --git a/src/pipecat/services/fish/tts.py b/src/pipecat/services/fish/tts.py index 7dd06d705..09ed72099 100644 --- a/src/pipecat/services/fish/tts.py +++ b/src/pipecat/services/fish/tts.py @@ -208,9 +208,11 @@ class FishAudioTTSService(InterruptibleTTSService): Dict mapping changed field names to their previous values. """ changed = await super()._update_settings(update) + if changed: await self._disconnect() await self._connect() + return changed async def start(self, frame: StartFrame): From 0fa51811ea57c9368f62c8c34ae54c3cdcb88e52 Mon Sep 17 00:00:00 2001 From: Paul Kompfner Date: Wed, 18 Feb 2026 15:10:36 -0500 Subject: [PATCH 0531/1060] Fix 55z example --- examples/foundational/55z-update-settings-hume-tts.py | 6 +++--- 1 file changed, 3 insertions(+), 3 deletions(-) diff --git a/examples/foundational/55z-update-settings-hume-tts.py b/examples/foundational/55z-update-settings-hume-tts.py index abab6abec..427b99bab 100644 --- a/examples/foundational/55z-update-settings-hume-tts.py +++ b/examples/foundational/55z-update-settings-hume-tts.py @@ -54,7 +54,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): tts = HumeTTSService( api_key=os.getenv("HUME_API_KEY"), - voice_id="ee7ea9f8-c99a-4516-a65d-80235fa3acdc", + voice_id="f898a92e-685f-43fa-985b-a46920f0650b", ) llm = OpenAILLMService(api_key=os.getenv("OPENAI_API_KEY")) @@ -100,10 +100,10 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): await task.queue_frames([LLMRunFrame()]) await asyncio.sleep(10) - logger.info('Updating Hume TTS settings: speed=1.5, description="Speak with excitement"') + logger.info('Updating Hume TTS settings: speed=2.0, description="Speak with excitement"') await task.queue_frame( TTSUpdateSettingsFrame( - update=HumeTTSSettings(speed=1.5, description="Speak with excitement") + update=HumeTTSSettings(speed=2.0, description="Speak with excitement") ) ) From b00d45484240eb4d21989d92cdbe5ced59b740f0 Mon Sep 17 00:00:00 2001 From: Paul Kompfner Date: Wed, 18 Feb 2026 15:19:57 -0500 Subject: [PATCH 0532/1060] Fix Inworld TTS settings updating --- .../55zb-update-settings-inworld-tts.py | 4 +-- src/pipecat/services/inworld/tts.py | 34 ++++++++----------- 2 files changed, 17 insertions(+), 21 deletions(-) diff --git a/examples/foundational/55zb-update-settings-inworld-tts.py b/examples/foundational/55zb-update-settings-inworld-tts.py index d9947c196..f8a66bdd8 100644 --- a/examples/foundational/55zb-update-settings-inworld-tts.py +++ b/examples/foundational/55zb-update-settings-inworld-tts.py @@ -97,9 +97,9 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): await task.queue_frames([LLMRunFrame()]) await asyncio.sleep(10) - logger.info("Updating Inworld TTS settings: speaking_rate=1.3, temperature=0.8") + logger.info("Updating Inworld TTS settings: speaking_rate=1.5, temperature=0.8") await task.queue_frame( - TTSUpdateSettingsFrame(update=InworldTTSSettings(speaking_rate=1.3, temperature=0.8)) + TTSUpdateSettingsFrame(update=InworldTTSSettings(speaking_rate=1.5, temperature=0.8)) ) @transport.event_handler("on_client_disconnected") diff --git a/src/pipecat/services/inworld/tts.py b/src/pipecat/services/inworld/tts.py index acc6187cb..fea30f3a1 100644 --- a/src/pipecat/services/inworld/tts.py +++ b/src/pipecat/services/inworld/tts.py @@ -184,25 +184,6 @@ class InworldHttpTTSService(WordTTSService): """ return True - async def _update_settings(self, update: TTSSettings) -> dict[str, Any]: - """Apply a settings update. - - Settings are stored but not applied to the active connection. - """ - changed = await super()._update_settings(update) - - if not changed: - return changed - - # TODO: someday we could reconnect here to apply updated settings. - # Code might look something like the below: - # await self._disconnect() - # await self._connect() - - self._warn_unhandled_updated_settings(changed) - - return changed - async def start(self, frame: StartFrame): """Start the Inworld TTS service. @@ -756,6 +737,21 @@ class InworldTTSService(AudioContextWordTTSService): await self._disconnect_websocket() + async def _update_settings(self, update: TTSSettings) -> dict[str, Any]: + """Apply a settings update. + + Settings are stored but not applied to the active connection. + """ + changed = await super()._update_settings(update) + + if not changed: + return changed + + await self._disconnect() + await self._connect() + + return changed + async def _connect_websocket(self): """Connect to the Inworld WebSocket TTS service. From e38f7d945119afe983c608e0f82a945ef49dd01b Mon Sep 17 00:00:00 2001 From: Paul Kompfner Date: Wed, 18 Feb 2026 15:23:23 -0500 Subject: [PATCH 0533/1060] Fix 55zc example --- .../foundational/55zc-update-settings-gemini-tts.py | 11 ++++++++++- 1 file changed, 10 insertions(+), 1 deletion(-) diff --git a/examples/foundational/55zc-update-settings-gemini-tts.py b/examples/foundational/55zc-update-settings-gemini-tts.py index 0bf878871..6af28e69f 100644 --- a/examples/foundational/55zc-update-settings-gemini-tts.py +++ b/examples/foundational/55zc-update-settings-gemini-tts.py @@ -25,6 +25,7 @@ from pipecat.runner.utils import create_transport from pipecat.services.deepgram.stt import DeepgramSTTService from pipecat.services.google.tts import GeminiTTSService, GeminiTTSSettings from pipecat.services.openai.llm import OpenAILLMService +from pipecat.transcriptions.language import Language from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams @@ -52,7 +53,15 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): stt = DeepgramSTTService(api_key=os.getenv("DEEPGRAM_API_KEY")) - tts = GeminiTTSService(api_key=os.getenv("GOOGLE_API_KEY")) + tts = GeminiTTSService( + credentials=os.getenv("GOOGLE_TEST_CREDENTIALS"), + model="gemini-2.5-flash-tts", + voice_id="Charon", + params=GeminiTTSService.InputParams( + language=Language.EN_US, + prompt="You are a helpful AI assistant. Speak in a natural, conversational tone.", + ), + ) llm = OpenAILLMService(api_key=os.getenv("OPENAI_API_KEY")) From b718a23c170266c822a27a7e55073a95906b0f03 Mon Sep 17 00:00:00 2001 From: Paul Kompfner Date: Wed, 18 Feb 2026 15:25:50 -0500 Subject: [PATCH 0534/1060] Tweak 55zd example --- examples/foundational/55zd-update-settings-aws-polly-tts.py | 6 ++---- 1 file changed, 2 insertions(+), 4 deletions(-) diff --git a/examples/foundational/55zd-update-settings-aws-polly-tts.py b/examples/foundational/55zd-update-settings-aws-polly-tts.py index 8abf68e2c..3d9f72cf4 100644 --- a/examples/foundational/55zd-update-settings-aws-polly-tts.py +++ b/examples/foundational/55zd-update-settings-aws-polly-tts.py @@ -97,10 +97,8 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): await task.queue_frames([LLMRunFrame()]) await asyncio.sleep(10) - logger.info('Updating AWS Polly TTS settings: rate="fast", pitch="+10%"') - await task.queue_frame( - TTSUpdateSettingsFrame(update=AWSPollyTTSSettings(rate="fast", pitch="+10%")) - ) + logger.info('Updating AWS Polly TTS settings: rate="fast"') + await task.queue_frame(TTSUpdateSettingsFrame(update=AWSPollyTTSSettings(rate="fast"))) @transport.event_handler("on_client_disconnected") async def on_client_disconnected(transport, client): From d386a0efda8569ab26265d0e726f3cadfe1d10b3 Mon Sep 17 00:00:00 2001 From: Paul Kompfner Date: Wed, 18 Feb 2026 15:31:08 -0500 Subject: [PATCH 0535/1060] Update Sarvam TTS to apply all changes to settings, not just voic --- .../foundational/55ze-update-settings-sarvam-tts.py | 6 +++--- src/pipecat/services/sarvam/tts.py | 11 ++++++----- 2 files changed, 9 insertions(+), 8 deletions(-) diff --git a/examples/foundational/55ze-update-settings-sarvam-tts.py b/examples/foundational/55ze-update-settings-sarvam-tts.py index 07065bfaf..98408c4b8 100644 --- a/examples/foundational/55ze-update-settings-sarvam-tts.py +++ b/examples/foundational/55ze-update-settings-sarvam-tts.py @@ -24,7 +24,7 @@ from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport from pipecat.services.deepgram.stt import DeepgramSTTService from pipecat.services.openai.llm import OpenAILLMService -from pipecat.services.sarvam.tts import SarvamTTSService, SarvamWSTTSSettings +from pipecat.services.sarvam.tts import SarvamTTSService, SarvamTTSSettings from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams @@ -97,8 +97,8 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): await task.queue_frames([LLMRunFrame()]) await asyncio.sleep(10) - logger.info("Updating Sarvam TTS settings: pace=1.3") - await task.queue_frame(TTSUpdateSettingsFrame(update=SarvamWSTTSSettings(pace=1.3))) + logger.info("Updating Sarvam TTS settings: pace=1.5") + await task.queue_frame(TTSUpdateSettingsFrame(update=SarvamTTSSettings(pace=1.5))) @transport.event_handler("on_client_disconnected") async def on_client_disconnected(transport, client): diff --git a/src/pipecat/services/sarvam/tts.py b/src/pipecat/services/sarvam/tts.py index 99a0827f5..aff96f1dd 100644 --- a/src/pipecat/services/sarvam/tts.py +++ b/src/pipecat/services/sarvam/tts.py @@ -276,7 +276,7 @@ class SarvamHttpTTSSettings(TTSSettings): @dataclass -class SarvamWSTTSSettings(TTSSettings): +class SarvamTTSSettings(TTSSettings): """Settings for Sarvam WebSocket TTS service. Parameters: @@ -686,7 +686,7 @@ class SarvamTTSService(InterruptibleTTSService): See https://docs.sarvam.ai/api-reference-docs/text-to-speech/stream for API details. """ - _settings: SarvamWSTTSSettings + _settings: SarvamTTSSettings class InputParams(BaseModel): """Configuration parameters for Sarvam TTS WebSocket service. @@ -841,7 +841,7 @@ class SarvamTTSService(InterruptibleTTSService): pace = max(pace_min, min(pace_max, pace)) # Build base settings - self._settings = SarvamWSTTSSettings( + self._settings = SarvamTTSSettings( target_language_code=( self.language_to_service_language(params.language) if params.language else "en-IN" ), @@ -956,9 +956,10 @@ class SarvamTTSService(InterruptibleTTSService): async def _update_settings(self, update: TTSSettings) -> dict[str, Any]: """Apply a settings update and resend config if voice changed.""" changed = await super()._update_settings(update) - if "voice" in changed: + + if changed: await self._send_config() - self._warn_unhandled_updated_settings(changed.keys() - {"voice"}) + return changed async def _connect(self): From 88a2dbdb822167fb63ec4f9fb4e3d9a2f53bb1c9 Mon Sep 17 00:00:00 2001 From: Paul Kompfner Date: Wed, 18 Feb 2026 15:48:50 -0500 Subject: [PATCH 0536/1060] Update 55zf example to update a setting that is supported by the default Camb TTS model --- examples/foundational/55zf-update-settings-camb-tts.py | 9 +++------ src/pipecat/services/camb/tts.py | 2 +- 2 files changed, 4 insertions(+), 7 deletions(-) diff --git a/examples/foundational/55zf-update-settings-camb-tts.py b/examples/foundational/55zf-update-settings-camb-tts.py index 0b663ef64..1fe758849 100644 --- a/examples/foundational/55zf-update-settings-camb-tts.py +++ b/examples/foundational/55zf-update-settings-camb-tts.py @@ -25,6 +25,7 @@ from pipecat.runner.utils import create_transport from pipecat.services.camb.tts import CambTTSService, CambTTSSettings from pipecat.services.deepgram.stt import DeepgramSTTService from pipecat.services.openai.llm import OpenAILLMService +from pipecat.transcriptions.language import Language from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams @@ -97,12 +98,8 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): await task.queue_frames([LLMRunFrame()]) await asyncio.sleep(10) - logger.info('Updating Camb TTS settings: user_instructions="Speak enthusiastically"') - await task.queue_frame( - TTSUpdateSettingsFrame( - update=CambTTSSettings(user_instructions="Speak enthusiastically") - ) - ) + logger.info("Updating Camb TTS settings: language -> Spanish") + await task.queue_frame(TTSUpdateSettingsFrame(update=CambTTSSettings(language=Language.ES))) @transport.event_handler("on_client_disconnected") async def on_client_disconnected(transport, client): diff --git a/src/pipecat/services/camb/tts.py b/src/pipecat/services/camb/tts.py index 4176b4413..95b0ddd52 100644 --- a/src/pipecat/services/camb/tts.py +++ b/src/pipecat/services/camb/tts.py @@ -17,7 +17,7 @@ Features: """ from dataclasses import dataclass, field -from typing import AsyncGenerator, Dict, Optional +from typing import Any, AsyncGenerator, Dict, Optional from camb import StreamTtsOutputConfiguration from camb.client import AsyncCambAI From c054780477c5b75aba21dd39b31f3e9f20849fd6 Mon Sep 17 00:00:00 2001 From: Paul Kompfner Date: Wed, 18 Feb 2026 15:59:34 -0500 Subject: [PATCH 0537/1060] Fix 55zh example --- .../foundational/55zh-update-settings-resembleai-tts.py | 6 +++--- 1 file changed, 3 insertions(+), 3 deletions(-) diff --git a/examples/foundational/55zh-update-settings-resembleai-tts.py b/examples/foundational/55zh-update-settings-resembleai-tts.py index 10d750394..39b745500 100644 --- a/examples/foundational/55zh-update-settings-resembleai-tts.py +++ b/examples/foundational/55zh-update-settings-resembleai-tts.py @@ -53,8 +53,8 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): stt = DeepgramSTTService(api_key=os.getenv("DEEPGRAM_API_KEY")) tts = ResembleAITTSService( - api_key=os.getenv("RESEMBLEAI_API_KEY"), - voice_id=os.getenv("RESEMBLEAI_VOICE_ID", ""), + api_key=os.getenv("RESEMBLE_API_KEY"), + voice_id=os.getenv("RESEMBLE_VOICE_UUID"), ) llm = OpenAILLMService(api_key=os.getenv("OPENAI_API_KEY")) @@ -103,7 +103,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): logger.info("Updating ResembleAI TTS settings: voice (changed)") await task.queue_frame( TTSUpdateSettingsFrame( - update=ResembleAITTSSettings(voice=os.getenv("RESEMBLEAI_VOICE_ID_ALT", "")) + update=ResembleAITTSSettings(voice=os.getenv("RESEMBLE_VOICE_UUID_ALT")) ) ) From 97d34ef9e195f6474238a0741179e8f48af7c104 Mon Sep 17 00:00:00 2001 From: Paul Kompfner Date: Wed, 18 Feb 2026 16:16:06 -0500 Subject: [PATCH 0538/1060] Update OpenAI Realtime to warn when you try to update settings that can't be updated dynamically. Update corresponding example to demonstrate updating output modality. --- .../55zl-update-settings-openai-realtime.py | 30 +++++++++++++++++-- src/pipecat/services/openai/realtime/llm.py | 7 +++-- 2 files changed, 32 insertions(+), 5 deletions(-) diff --git a/examples/foundational/55zl-update-settings-openai-realtime.py b/examples/foundational/55zl-update-settings-openai-realtime.py index 2207b6851..90663a95c 100644 --- a/examples/foundational/55zl-update-settings-openai-realtime.py +++ b/examples/foundational/55zl-update-settings-openai-realtime.py @@ -16,13 +16,17 @@ from pipecat.pipeline.pipeline import Pipeline from pipecat.pipeline.runner import PipelineRunner from pipecat.pipeline.task import PipelineParams, PipelineTask from pipecat.processors.aggregators.llm_context import LLMContext -from pipecat.processors.aggregators.llm_response_universal import LLMContextAggregatorPair +from pipecat.processors.aggregators.llm_response_universal import ( + AssistantTurnStoppedMessage, + LLMContextAggregatorPair, +) from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport from pipecat.services.openai.realtime.llm import ( OpenAIRealtimeLLMService, OpenAIRealtimeLLMSettings, ) +from pipecat.services.openai_realtime import events from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams @@ -82,15 +86,35 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): idle_timeout_secs=runner_args.pipeline_idle_timeout_secs, ) + @assistant_aggregator.event_handler("on_assistant_turn_stopped") + async def on_assistant_turn_stopped(aggregator, message: AssistantTurnStoppedMessage): + timestamp = f"[{message.timestamp}] " if message.timestamp else "" + line = f"{timestamp}assistant: {message.content}" + logger.info(f"Transcript: {line}") + @transport.event_handler("on_client_connected") async def on_client_connected(transport, client): logger.info(f"Client connected") await task.queue_frames([LLMRunFrame()]) await asyncio.sleep(10) - logger.info("Updating OpenAI Realtime LLM settings: temperature=0.1") + logger.info("Updating OpenAI Realtime LLM settings: output_modalities=['text']") await task.queue_frame( - LLMUpdateSettingsFrame(update=OpenAIRealtimeLLMSettings(temperature=0.1)) + LLMUpdateSettingsFrame( + update=OpenAIRealtimeLLMSettings( + session_properties=events.SessionProperties(output_modalities=["text"]) + ) + ) + ) + + await asyncio.sleep(10) + logger.info("Updating OpenAI Realtime LLM settings: output_modalities=['audio']") + await task.queue_frame( + LLMUpdateSettingsFrame( + update=OpenAIRealtimeLLMSettings( + session_properties=events.SessionProperties(output_modalities=["audio"]) + ) + ) ) @transport.event_handler("on_client_disconnected") diff --git a/src/pipecat/services/openai/realtime/llm.py b/src/pipecat/services/openai/realtime/llm.py index f6e8b1646..3560f0c27 100644 --- a/src/pipecat/services/openai/realtime/llm.py +++ b/src/pipecat/services/openai/realtime/llm.py @@ -59,7 +59,7 @@ from pipecat.processors.aggregators.openai_llm_context import ( ) from pipecat.processors.frame_processor import FrameDirection from pipecat.services.llm_service import FunctionCallFromLLM, LLMService -from pipecat.services.settings import NOT_GIVEN, LLMSettings +from pipecat.services.settings import NOT_GIVEN, LLMSettings, _NotGiven from pipecat.transcriptions.language import Language from pipecat.utils.time import time_now_iso8601 from pipecat.utils.tracing.service_decorators import traced_openai_realtime, traced_stt @@ -99,7 +99,9 @@ class OpenAIRealtimeLLMSettings(LLMSettings): session_properties: OpenAI Realtime session configuration. """ - session_properties: Any = field(default_factory=lambda: NOT_GIVEN) + session_properties: events.SessionProperties | _NotGiven = field( + default_factory=lambda: NOT_GIVEN + ) class OpenAIRealtimeLLMService(LLMService): @@ -539,6 +541,7 @@ class OpenAIRealtimeLLMService(LLMService): changed = await super()._update_settings(update) if "session_properties" in changed: await self._send_session_update() + self._warn_unhandled_updated_settings(changed.keys() - {"session_properties"}) return changed async def _send_session_update(self): From ad942f6e4c81ed07996c822c03b97cb87857f9d6 Mon Sep 17 00:00:00 2001 From: Paul Kompfner Date: Wed, 18 Feb 2026 16:33:05 -0500 Subject: [PATCH 0539/1060] Update 55zn example (UIltravox dynamic settings updates) to exercise changing modality, which is a setting that supports dynamic updates --- .../55zn-update-settings-ultravox-realtime.py | 32 ++++++++++++++++--- 1 file changed, 27 insertions(+), 5 deletions(-) diff --git a/examples/foundational/55zn-update-settings-ultravox-realtime.py b/examples/foundational/55zn-update-settings-ultravox-realtime.py index 8c640ccc4..967d40741 100644 --- a/examples/foundational/55zn-update-settings-ultravox-realtime.py +++ b/examples/foundational/55zn-update-settings-ultravox-realtime.py @@ -5,18 +5,23 @@ # import asyncio +import datetime import os from dotenv import load_dotenv from loguru import logger +from pipecat.adapters.schemas.tools_schema import ToolsSchema from pipecat.audio.vad.silero import SileroVADAnalyzer from pipecat.frames.frames import LLMRunFrame, LLMUpdateSettingsFrame from pipecat.pipeline.pipeline import Pipeline from pipecat.pipeline.runner import PipelineRunner from pipecat.pipeline.task import PipelineParams, PipelineTask from pipecat.processors.aggregators.llm_context import LLMContext -from pipecat.processors.aggregators.llm_response_universal import LLMContextAggregatorPair +from pipecat.processors.aggregators.llm_response_universal import ( + AssistantTurnStoppedMessage, + LLMContextAggregatorPair, +) from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport from pipecat.services.ultravox.llm import ( @@ -52,17 +57,22 @@ transport_params = { async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): logger.info(f"Starting bot") + system_prompt = "You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way." + llm = UltravoxRealtimeLLMService( params=OneShotInputParams( api_key=os.getenv("ULTRAVOX_API_KEY"), - system_prompt="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + system_prompt=system_prompt, + temperature=0.3, + max_duration=datetime.timedelta(minutes=3), ), + one_shot_selected_tools=ToolsSchema(standard_tools=[]), ) messages = [ { "role": "system", - "content": "You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + "content": system_prompt, }, ] @@ -88,15 +98,27 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): idle_timeout_secs=runner_args.pipeline_idle_timeout_secs, ) + @assistant_aggregator.event_handler("on_assistant_turn_stopped") + async def on_assistant_turn_stopped(aggregator, message: AssistantTurnStoppedMessage): + timestamp = f"[{message.timestamp}] " if message.timestamp else "" + line = f"{timestamp}assistant: {message.content}" + logger.info(f"Transcript: {line}") + @transport.event_handler("on_client_connected") async def on_client_connected(transport, client): logger.info(f"Client connected") await task.queue_frames([LLMRunFrame()]) await asyncio.sleep(10) - logger.info("Updating Ultravox Realtime LLM settings: temperature=0.1") + logger.info("Updating Ultravox Realtime LLM settings: output_medium=text") await task.queue_frame( - LLMUpdateSettingsFrame(update=UltravoxRealtimeLLMSettings(temperature=0.1)) + LLMUpdateSettingsFrame(update=UltravoxRealtimeLLMSettings(output_medium="text")) + ) + + await asyncio.sleep(10) + logger.info("Updating Ultravox Realtime LLM settings: output_medium=voice") + await task.queue_frame( + LLMUpdateSettingsFrame(update=UltravoxRealtimeLLMSettings(output_medium="voice")) ) @transport.event_handler("on_client_disconnected") From 39dc4ba99c90d9e228950e62cc845f36184aa461 Mon Sep 17 00:00:00 2001 From: Filipi da Silva Fuchter Date: Wed, 18 Feb 2026 16:58:27 -0500 Subject: [PATCH 0540/1060] Updated changelog/3765.changed.md --- changelog/3765.changed.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/changelog/3765.changed.md b/changelog/3765.changed.md index 11c4866d5..5d3e758d5 100644 --- a/changelog/3765.changed.md +++ b/changelog/3765.changed.md @@ -1 +1 @@ -- Update `InworldTTSService` and `InworldHttpTTSService` to use `ASYNC` timestamp transport strategy by default +- Updated `InworldTTSService` and `InworldHttpTTSService` to use `ASYNC` timestamp transport strategy by default From 2a07138abff910674c56ff18b5fd7afe1472be07 Mon Sep 17 00:00:00 2001 From: Paul Kompfner Date: Wed, 18 Feb 2026 17:12:36 -0500 Subject: [PATCH 0541/1060] Fix Grok Realtime dynamic session properties updating, and update corresponding 55zo example --- .../55zl-update-settings-openai-realtime.py | 2 +- .../55zo-update-settings-grok-realtime.py | 22 +++++-- src/pipecat/services/grok/realtime/llm.py | 59 +++++++++++++------ 3 files changed, 59 insertions(+), 24 deletions(-) diff --git a/examples/foundational/55zl-update-settings-openai-realtime.py b/examples/foundational/55zl-update-settings-openai-realtime.py index 90663a95c..9c18d528e 100644 --- a/examples/foundational/55zl-update-settings-openai-realtime.py +++ b/examples/foundational/55zl-update-settings-openai-realtime.py @@ -22,11 +22,11 @@ from pipecat.processors.aggregators.llm_response_universal import ( ) from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport +from pipecat.services.openai.realtime import events from pipecat.services.openai.realtime.llm import ( OpenAIRealtimeLLMService, OpenAIRealtimeLLMSettings, ) -from pipecat.services.openai_realtime import events from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams diff --git a/examples/foundational/55zo-update-settings-grok-realtime.py b/examples/foundational/55zo-update-settings-grok-realtime.py index 567eeae2b..7d7370f7b 100644 --- a/examples/foundational/55zo-update-settings-grok-realtime.py +++ b/examples/foundational/55zo-update-settings-grok-realtime.py @@ -16,9 +16,13 @@ from pipecat.pipeline.pipeline import Pipeline from pipecat.pipeline.runner import PipelineRunner from pipecat.pipeline.task import PipelineParams, PipelineTask from pipecat.processors.aggregators.llm_context import LLMContext -from pipecat.processors.aggregators.llm_response_universal import LLMContextAggregatorPair +from pipecat.processors.aggregators.llm_response_universal import ( + AssistantTurnStoppedMessage, + LLMContextAggregatorPair, +) from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport +from pipecat.services.grok.realtime import events from pipecat.services.grok.realtime.llm import ( GrokRealtimeLLMService, GrokRealtimeLLMSettings, @@ -51,7 +55,7 @@ transport_params = { async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): logger.info(f"Starting bot") - llm = GrokRealtimeLLMService(api_key=os.getenv("XAI_API_KEY")) + llm = GrokRealtimeLLMService(api_key=os.getenv("GROK_API_KEY")) messages = [ { @@ -82,15 +86,25 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): idle_timeout_secs=runner_args.pipeline_idle_timeout_secs, ) + @assistant_aggregator.event_handler("on_assistant_turn_stopped") + async def on_assistant_turn_stopped(aggregator, message: AssistantTurnStoppedMessage): + timestamp = f"[{message.timestamp}] " if message.timestamp else "" + line = f"{timestamp}assistant: {message.content}" + logger.info(f"Transcript: {line}") + @transport.event_handler("on_client_connected") async def on_client_connected(transport, client): logger.info(f"Client connected") await task.queue_frames([LLMRunFrame()]) await asyncio.sleep(10) - logger.info("Updating Grok Realtime LLM settings: temperature=0.1") + logger.info("Updating Grok Realtime LLM settings: voice='Rex'") await task.queue_frame( - LLMUpdateSettingsFrame(update=GrokRealtimeLLMSettings(temperature=0.1)) + LLMUpdateSettingsFrame( + update=GrokRealtimeLLMSettings( + session_properties=events.SessionProperties(voice="Rex") + ) + ) ) @transport.event_handler("on_client_disconnected") diff --git a/src/pipecat/services/grok/realtime/llm.py b/src/pipecat/services/grok/realtime/llm.py index f31769774..14c93c94a 100644 --- a/src/pipecat/services/grok/realtime/llm.py +++ b/src/pipecat/services/grok/realtime/llm.py @@ -56,7 +56,7 @@ from pipecat.processors.aggregators.llm_response_universal import ( from pipecat.processors.aggregators.openai_llm_context import OpenAILLMContext from pipecat.processors.frame_processor import FrameDirection from pipecat.services.llm_service import FunctionCallFromLLM, LLMService -from pipecat.services.settings import NOT_GIVEN, LLMSettings +from pipecat.services.settings import NOT_GIVEN, LLMSettings, _NotGiven from pipecat.utils.time import time_now_iso8601 from . import events @@ -94,7 +94,9 @@ class GrokRealtimeLLMSettings(LLMSettings): session_properties: Grok Realtime session configuration. """ - session_properties: Any = field(default_factory=lambda: NOT_GIVEN) + session_properties: events.SessionProperties | _NotGiven = field( + default_factory=lambda: NOT_GIVEN + ) class GrokRealtimeLLMService(LLMService): @@ -294,6 +296,27 @@ class GrokRealtimeLLMService(LLMService): # Standard AIService frame handling # + def _ensure_audio_config(self, input_sample_rate: int, output_sample_rate: int): + """Ensure session_properties.audio has input and output configs. + + Fills in any missing audio configuration using the given sample rates. + + Args: + input_sample_rate: Sample rate for audio input (Hz). + output_sample_rate: Sample rate for audio output (Hz). + """ + props = self._settings.session_properties + if not props.audio: + props.audio = events.AudioConfiguration() + if not props.audio.input: + props.audio.input = events.AudioInput( + format=events.PCMAudioFormat(rate=input_sample_rate) + ) + if not props.audio.output: + props.audio.output = events.AudioOutput( + format=events.PCMAudioFormat(rate=output_sample_rate) + ) + async def start(self, frame: StartFrame): """Start the service and establish WebSocket connection. @@ -301,23 +324,7 @@ class GrokRealtimeLLMService(LLMService): frame: The start frame triggering service initialization. """ await super().start(frame) - - # Ensure audio configuration exists with both input and output - if not self._settings.session_properties.audio: - self._settings.session_properties.audio = events.AudioConfiguration() - - # Fill in missing input configuration - if not self._settings.session_properties.audio.input: - self._settings.session_properties.audio.input = events.AudioInput( - format=events.PCMAudioFormat(rate=frame.audio_in_sample_rate) - ) - - # Fill in missing output configuration - if not self._settings.session_properties.audio.output: - self._settings.session_properties.audio.output = events.AudioOutput( - format=events.PCMAudioFormat(rate=frame.audio_out_sample_rate) - ) - + self._ensure_audio_config(frame.audio_in_sample_rate, frame.audio_out_sample_rate) await self._connect() async def stop(self, frame: EndFrame): @@ -458,9 +465,23 @@ class GrokRealtimeLLMService(LLMService): async def _update_settings(self, update): """Apply a settings update, sending a session update if needed.""" + # Capture current sample rates before the update replaces them. + input_rate = self._get_configured_sample_rate("input") + output_rate = self._get_configured_sample_rate("output") + changed = await super()._update_settings(update) + if "session_properties" in changed: + if input_rate and output_rate: + self._ensure_audio_config(input_rate, output_rate) + else: + logger.warning( + "Attempting to apply session properties update without configured sample rates. " + "Audio configuration may be incomplete." + ) await self._send_session_update() + + self._warn_unhandled_updated_settings(changed.keys() - {"session_properties"}) return changed async def _send_session_update(self): From a7edd8e441b630aeb3dafda11e70d4a14913b7bb Mon Sep 17 00:00:00 2001 From: Paul Kompfner Date: Wed, 18 Feb 2026 17:15:22 -0500 Subject: [PATCH 0542/1060] Fix 55zp example --- .../foundational/55zp-update-settings-aws-bedrock-llm.py | 6 +++++- 1 file changed, 5 insertions(+), 1 deletion(-) diff --git a/examples/foundational/55zp-update-settings-aws-bedrock-llm.py b/examples/foundational/55zp-update-settings-aws-bedrock-llm.py index aaf0d973c..1c2781e72 100644 --- a/examples/foundational/55zp-update-settings-aws-bedrock-llm.py +++ b/examples/foundational/55zp-update-settings-aws-bedrock-llm.py @@ -57,7 +57,11 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): voice_id="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady ) - llm = AWSBedrockLLMService(model="anthropic.claude-sonnet-4-20250514-v1:0") + llm = AWSBedrockLLMService( + aws_region="us-west-2", + model="us.anthropic.claude-haiku-4-5-20251001-v1:0", + params=AWSBedrockLLMService.InputParams(temperature=0.8), + ) messages = [ { From fb1bfd03dd60872998218e45bd8748d794bff695 Mon Sep 17 00:00:00 2001 From: antonyesk601 Date: Thu, 19 Feb 2026 10:35:50 +0000 Subject: [PATCH 0543/1060] update SimliClient to latest --- pyproject.toml | 2 +- src/pipecat/services/simli/video.py | 9 +++++---- 2 files changed, 6 insertions(+), 5 deletions(-) diff --git a/pyproject.toml b/pyproject.toml index 28c1a7e8c..e71202252 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -111,7 +111,7 @@ sambanova = [] sarvam = [ "sarvamai==0.1.21", "pipecat-ai[websockets-base]" ] sentry = [ "sentry-sdk>=2.28.0,<3" ] silero = [ "onnxruntime~=1.23.2" ] -simli = [ "simli-ai~=1.0.3"] +simli = [ "simli-ai~=2.0.1"] soniox = [ "pipecat-ai[websockets-base]" ] soundfile = [ "soundfile~=0.13.1" ] speechmatics = [ "speechmatics-voice[smart]~=0.2.8" ] diff --git a/src/pipecat/services/simli/video.py b/src/pipecat/services/simli/video.py index b1f7961af..9fc3665b6 100644 --- a/src/pipecat/services/simli/video.py +++ b/src/pipecat/services/simli/video.py @@ -6,6 +6,8 @@ """Simli video service for real-time avatar generation.""" +from cgitb import enable + import asyncio import warnings from typing import Optional @@ -131,7 +133,6 @@ class SimliVideoService(FrameProcessor): # Build SimliConfig from new parameters # Only pass optional parameters if explicitly provided to use SimliConfig defaults config_kwargs = { - "apiKey": api_key, "faceId": face_id, } if params.max_session_length is not None: @@ -153,10 +154,10 @@ class SimliVideoService(FrameProcessor): config.maxIdleTime += 5 config.maxSessionLength += 5 self._simli_client = SimliClient( + api_key=api_key, config=config, - latencyInterval=latency_interval, simliURL=simli_url, - enable_logging=params.enable_logging or False, + enableSFU=True, ) self._pipecat_resampler: AudioResampler = None @@ -173,7 +174,7 @@ class SimliVideoService(FrameProcessor): """Start the connection to Simli service and begin processing tasks.""" try: if not self._initialized: - await self._simli_client.Initialize() + await self._simli_client.start() self._initialized = True # Create task to consume and process audio and video From a55ba4092113426c03ea901221d7f59334c721f4 Mon Sep 17 00:00:00 2001 From: antonyesk601 Date: Thu, 19 Feb 2026 10:41:17 +0000 Subject: [PATCH 0544/1060] fix: remove misimport --- src/pipecat/services/simli/video.py | 2 -- 1 file changed, 2 deletions(-) diff --git a/src/pipecat/services/simli/video.py b/src/pipecat/services/simli/video.py index 9fc3665b6..880b40428 100644 --- a/src/pipecat/services/simli/video.py +++ b/src/pipecat/services/simli/video.py @@ -6,8 +6,6 @@ """Simli video service for real-time avatar generation.""" -from cgitb import enable - import asyncio import warnings from typing import Optional From 92c380ee7718708aa6cac7ade4836790c3897dfb Mon Sep 17 00:00:00 2001 From: Mark Backman Date: Thu, 19 Feb 2026 07:01:07 -0700 Subject: [PATCH 0545/1060] Add apt-get update before installing system packages in CI The CI was failing because the runner's package index was stale, causing a 404 when fetching libasound2-dev (a dependency of portaudio19-dev). Running apt-get update first refreshes the index. --- .github/workflows/coverage.yaml | 1 + .github/workflows/tests.yaml | 1 + 2 files changed, 2 insertions(+) diff --git a/.github/workflows/coverage.yaml b/.github/workflows/coverage.yaml index b78067c97..df9c388bf 100644 --- a/.github/workflows/coverage.yaml +++ b/.github/workflows/coverage.yaml @@ -29,6 +29,7 @@ jobs: - name: Install system packages run: | + sudo apt-get update sudo apt-get install -y portaudio19-dev - name: Install dependencies diff --git a/.github/workflows/tests.yaml b/.github/workflows/tests.yaml index 5bdfb94f4..5941448f3 100644 --- a/.github/workflows/tests.yaml +++ b/.github/workflows/tests.yaml @@ -33,6 +33,7 @@ jobs: - name: Install system packages run: | + sudo apt-get update sudo apt-get install -y portaudio19-dev - name: Install dependencies From 63df4642b5fdcf01df84185795986f2b2bbeafa6 Mon Sep 17 00:00:00 2001 From: Mark Backman Date: Thu, 19 Feb 2026 07:43:20 -0700 Subject: [PATCH 0546/1060] Fix RTVIObserver missing upstream-only frames by adding broadcasted flag RTVIObserver previously filtered out all upstream frames to avoid duplicate messages from broadcasted frames. This caused upstream-only frames to be silently ignored. Instead, add a `broadcasted` field to the Frame base class that is set by broadcast_frame() and broadcast_frame_instance(), and only skip upstream copies of broadcasted frames. --- src/pipecat/frames/frames.py | 2 ++ src/pipecat/processors/frame_processor.py | 10 ++++++++-- src/pipecat/processors/frameworks/rtvi.py | 7 +++---- 3 files changed, 13 insertions(+), 6 deletions(-) diff --git a/src/pipecat/frames/frames.py b/src/pipecat/frames/frames.py index 8d237defc..c3f6226c6 100644 --- a/src/pipecat/frames/frames.py +++ b/src/pipecat/frames/frames.py @@ -131,6 +131,7 @@ class Frame: id: int = field(init=False) name: str = field(init=False) pts: Optional[int] = field(init=False) + broadcasted: bool = field(init=False) metadata: Dict[str, Any] = field(init=False) transport_source: Optional[str] = field(init=False) transport_destination: Optional[str] = field(init=False) @@ -139,6 +140,7 @@ class Frame: self.id: int = obj_id() self.name: str = f"{self.__class__.__name__}#{obj_count(self)}" self.pts: Optional[int] = None + self.broadcasted: bool = False self.metadata: Dict[str, Any] = {} self.transport_source: Optional[str] = None self.transport_destination: Optional[str] = None diff --git a/src/pipecat/processors/frame_processor.py b/src/pipecat/processors/frame_processor.py index f0c9e7183..48c8c718c 100644 --- a/src/pipecat/processors/frame_processor.py +++ b/src/pipecat/processors/frame_processor.py @@ -787,8 +787,12 @@ class FrameProcessor(BaseObject): frame_cls: The class of the frame to be broadcasted. **kwargs: Keyword arguments to be passed to the frame's constructor. """ - await self.push_frame(frame_cls(**kwargs)) - await self.push_frame(frame_cls(**kwargs), FrameDirection.UPSTREAM) + downstream_frame = frame_cls(**kwargs) + downstream_frame.broadcasted = True + await self.push_frame(downstream_frame) + upstream_frame = frame_cls(**kwargs) + upstream_frame.broadcasted = True + await self.push_frame(upstream_frame, FrameDirection.UPSTREAM) async def broadcast_frame_instance(self, frame: Frame): """Broadcasts a frame instance upstream and downstream. @@ -815,11 +819,13 @@ class FrameProcessor(BaseObject): new_frame = frame_cls(**init_fields) for k, v in extra_fields.items(): setattr(new_frame, k, v) + new_frame.broadcasted = True await self.push_frame(new_frame) new_frame = frame_cls(**init_fields) for k, v in extra_fields.items(): setattr(new_frame, k, v) + new_frame.broadcasted = True await self.push_frame(new_frame, FrameDirection.UPSTREAM) async def __start(self, frame: StartFrame): diff --git a/src/pipecat/processors/frameworks/rtvi.py b/src/pipecat/processors/frameworks/rtvi.py index c1497b40b..8c7bb15ef 100644 --- a/src/pipecat/processors/frameworks/rtvi.py +++ b/src/pipecat/processors/frameworks/rtvi.py @@ -1220,10 +1220,9 @@ class RTVIObserver(BaseObserver): frame = data.frame direction = data.direction - # Only process downstream frames. Some frames are broadcast in both - # directions (e.g. UserStartedSpeakingFrame, FunctionCallResultFrame), - # and we only want to send one RTVI message per event. - if direction != FrameDirection.DOWNSTREAM: + # For broadcasted frames (pushed in both directions), only process + # the downstream copy to avoid sending duplicate RTVI messages. + if frame.broadcasted and direction != FrameDirection.DOWNSTREAM: return # If we have already seen this frame, let's skip it. From 50ef4909e3a97020b103d27716d3a7c9c9e28a10 Mon Sep 17 00:00:00 2001 From: Mark Backman Date: Thu, 19 Feb 2026 07:44:52 -0700 Subject: [PATCH 0547/1060] Add changelog entries for PR #3774 --- changelog/3774.added.md | 1 + changelog/3774.fixed.md | 1 + 2 files changed, 2 insertions(+) create mode 100644 changelog/3774.added.md create mode 100644 changelog/3774.fixed.md diff --git a/changelog/3774.added.md b/changelog/3774.added.md new file mode 100644 index 000000000..032d8238f --- /dev/null +++ b/changelog/3774.added.md @@ -0,0 +1 @@ +- Added `broadcasted` field to the base `Frame` class. This field is automatically set to `True` by `broadcast_frame()` and `broadcast_frame_instance()` to distinguish broadcasted frames from single-direction frames. diff --git a/changelog/3774.fixed.md b/changelog/3774.fixed.md new file mode 100644 index 000000000..a839f56ed --- /dev/null +++ b/changelog/3774.fixed.md @@ -0,0 +1 @@ +- Fixed `RTVIObserver` not processing upstream-only frames. Previously, all upstream frames were filtered out to avoid duplicate messages from broadcasted frames. Now only upstream copies of broadcasted frames are skipped. From 421696e1c25d5b387e47b476f87d28889add7e06 Mon Sep 17 00:00:00 2001 From: Paul Kompfner Date: Thu, 19 Feb 2026 11:28:29 -0500 Subject: [PATCH 0548/1060] Replace `Any` with specific types and add `| _NotGiven` to all `*Settings` field annotations across 49 service files Every `*Settings` dataclass field whose default is `NOT_GIVEN` now carries `_NotGiven` in its type union so the type system accurately reflects the three-state semantics (real value, `None` where applicable, or not-yet-specified). Fields previously typed as bare `Any`, `str`, `float`, `bool`, `list`, `dict`, or `Optional[X]` are now narrowed to the specific type from the corresponding `InputParams` Pydantic model. --- src/pipecat/services/anthropic/llm.py | 8 ++-- src/pipecat/services/assemblyai/stt.py | 6 ++- src/pipecat/services/asyncai/tts.py | 8 ++-- src/pipecat/services/aws/llm.py | 8 ++-- src/pipecat/services/aws/stt.py | 12 ++--- src/pipecat/services/aws/tts.py | 12 ++--- src/pipecat/services/azure/stt.py | 6 +-- src/pipecat/services/azure/tts.py | 18 +++---- src/pipecat/services/camb/tts.py | 4 +- src/pipecat/services/cartesia/stt.py | 4 +- src/pipecat/services/cartesia/tts.py | 16 +++---- src/pipecat/services/deepgram/stt.py | 4 +- .../services/deepgram/stt_sagemaker.py | 4 +- src/pipecat/services/deepgram/tts.py | 4 +- src/pipecat/services/elevenlabs/stt.py | 20 ++++---- src/pipecat/services/elevenlabs/tts.py | 38 ++++++++------- src/pipecat/services/fal/stt.py | 8 ++-- src/pipecat/services/fish/tts.py | 16 +++---- src/pipecat/services/gladia/stt.py | 4 +- .../services/google/gemini_live/llm.py | 20 ++++---- src/pipecat/services/google/llm.py | 6 ++- src/pipecat/services/google/stt.py | 26 +++++----- src/pipecat/services/google/tts.py | 40 +++++++++------- src/pipecat/services/gradium/stt.py | 4 +- src/pipecat/services/gradium/tts.py | 4 +- src/pipecat/services/groq/tts.py | 8 ++-- src/pipecat/services/hathora/stt.py | 4 +- src/pipecat/services/hathora/tts.py | 6 +-- src/pipecat/services/inworld/tts.py | 14 +++--- src/pipecat/services/kokoro/tts.py | 4 +- src/pipecat/services/lmnt/tts.py | 4 +- src/pipecat/services/minimax/tts.py | 26 +++++----- src/pipecat/services/neuphonic/tts.py | 10 ++-- src/pipecat/services/nvidia/stt.py | 12 ++--- src/pipecat/services/openai/base_llm.py | 6 +-- src/pipecat/services/openai/stt.py | 4 +- src/pipecat/services/openai/tts.py | 6 +-- .../services/openai_realtime_beta/openai.py | 8 ++-- src/pipecat/services/playht/tts.py | 12 ++--- src/pipecat/services/resembleai/tts.py | 8 ++-- src/pipecat/services/rime/tts.py | 36 +++++++------- src/pipecat/services/sarvam/stt.py | 10 ++-- src/pipecat/services/sarvam/tts.py | 40 ++++++++-------- src/pipecat/services/soniox/stt.py | 4 +- src/pipecat/services/speechmatics/stt.py | 48 ++++++++++--------- src/pipecat/services/ultravox/llm.py | 4 +- src/pipecat/services/whisper/base_stt.py | 8 ++-- src/pipecat/services/whisper/stt.py | 14 +++--- src/pipecat/services/xtts/tts.py | 4 +- 49 files changed, 314 insertions(+), 286 deletions(-) diff --git a/src/pipecat/services/anthropic/llm.py b/src/pipecat/services/anthropic/llm.py index 159b666d1..4416aa018 100644 --- a/src/pipecat/services/anthropic/llm.py +++ b/src/pipecat/services/anthropic/llm.py @@ -59,7 +59,7 @@ from pipecat.processors.aggregators.openai_llm_context import ( from pipecat.processors.frame_processor import FrameDirection from pipecat.services.llm_service import FunctionCallFromLLM, LLMService from pipecat.services.settings import NOT_GIVEN as _NOT_GIVEN -from pipecat.services.settings import LLMSettings, is_given +from pipecat.services.settings import LLMSettings, _NotGiven, is_given from pipecat.utils.tracing.service_decorators import traced_llm try: @@ -79,8 +79,10 @@ class AnthropicLLMSettings(LLMSettings): thinking: Extended thinking configuration. """ - enable_prompt_caching: Any = field(default_factory=lambda: _NOT_GIVEN) - thinking: Any = field(default_factory=lambda: _NOT_GIVEN) + enable_prompt_caching: bool | _NotGiven = field(default_factory=lambda: _NOT_GIVEN) + thinking: "AnthropicLLMService.ThinkingConfig" | _NotGiven = field( + default_factory=lambda: _NOT_GIVEN + ) @classmethod def from_mapping(cls, settings): diff --git a/src/pipecat/services/assemblyai/stt.py b/src/pipecat/services/assemblyai/stt.py index 23b7d149b..6a33b6a20 100644 --- a/src/pipecat/services/assemblyai/stt.py +++ b/src/pipecat/services/assemblyai/stt.py @@ -30,7 +30,7 @@ from pipecat.frames.frames import ( VADUserStoppedSpeakingFrame, ) from pipecat.processors.frame_processor import FrameDirection -from pipecat.services.settings import NOT_GIVEN, STTSettings +from pipecat.services.settings import NOT_GIVEN, STTSettings, _NotGiven from pipecat.services.stt_latency import ASSEMBLYAI_TTFS_P99 from pipecat.services.stt_service import WebsocketSTTService from pipecat.transcriptions.language import Language @@ -64,7 +64,9 @@ class AssemblyAISTTSettings(STTSettings): connection_params: Connection configuration parameters. """ - connection_params: AssemblyAIConnectionParams = field(default_factory=lambda: NOT_GIVEN) + connection_params: AssemblyAIConnectionParams | _NotGiven = field( + default_factory=lambda: NOT_GIVEN + ) class AssemblyAISTTService(WebsocketSTTService): diff --git a/src/pipecat/services/asyncai/tts.py b/src/pipecat/services/asyncai/tts.py index 489d7cbff..d01fd4396 100644 --- a/src/pipecat/services/asyncai/tts.py +++ b/src/pipecat/services/asyncai/tts.py @@ -28,7 +28,7 @@ from pipecat.frames.frames import ( TTSStoppedFrame, ) from pipecat.processors.frame_processor import FrameDirection -from pipecat.services.settings import NOT_GIVEN, TTSSettings +from pipecat.services.settings import NOT_GIVEN, TTSSettings, _NotGiven from pipecat.services.tts_service import AudioContextTTSService, TTSService from pipecat.transcriptions.language import Language, resolve_language from pipecat.utils.tracing.service_decorators import traced_tts @@ -84,9 +84,9 @@ class AsyncAITTSSettings(TTSSettings): output_sample_rate: Audio sample rate in Hz. """ - output_container: str = field(default_factory=lambda: NOT_GIVEN) - output_encoding: str = field(default_factory=lambda: NOT_GIVEN) - output_sample_rate: int = field(default_factory=lambda: NOT_GIVEN) + output_container: str | _NotGiven = field(default_factory=lambda: NOT_GIVEN) + output_encoding: str | _NotGiven = field(default_factory=lambda: NOT_GIVEN) + output_sample_rate: int | _NotGiven = field(default_factory=lambda: NOT_GIVEN) @classmethod def from_mapping(cls, settings: Mapping[str, Any]) -> "AsyncAITTSSettings": diff --git a/src/pipecat/services/aws/llm.py b/src/pipecat/services/aws/llm.py index 3fca8e374..b39d518ec 100644 --- a/src/pipecat/services/aws/llm.py +++ b/src/pipecat/services/aws/llm.py @@ -56,7 +56,7 @@ from pipecat.processors.aggregators.openai_llm_context import ( ) from pipecat.processors.frame_processor import FrameDirection from pipecat.services.llm_service import LLMService -from pipecat.services.settings import NOT_GIVEN, LLMSettings +from pipecat.services.settings import NOT_GIVEN, LLMSettings, _NotGiven from pipecat.utils.tracing.service_decorators import traced_llm try: @@ -80,8 +80,10 @@ class AWSBedrockLLMSettings(LLMSettings): additional_model_request_fields: Additional model-specific parameters. """ - latency: Any = field(default_factory=lambda: NOT_GIVEN) - additional_model_request_fields: Any = field(default_factory=lambda: NOT_GIVEN) + latency: str | _NotGiven = field(default_factory=lambda: NOT_GIVEN) + additional_model_request_fields: Dict[str, Any] | _NotGiven = field( + default_factory=lambda: NOT_GIVEN + ) @dataclass diff --git a/src/pipecat/services/aws/stt.py b/src/pipecat/services/aws/stt.py index 21220e646..09552ecfc 100644 --- a/src/pipecat/services/aws/stt.py +++ b/src/pipecat/services/aws/stt.py @@ -29,7 +29,7 @@ from pipecat.frames.frames import ( TranscriptionFrame, ) from pipecat.services.aws.utils import build_event_message, decode_event, get_presigned_url -from pipecat.services.settings import NOT_GIVEN, STTSettings +from pipecat.services.settings import NOT_GIVEN, STTSettings, _NotGiven from pipecat.services.stt_latency import AWS_TRANSCRIBE_TTFS_P99 from pipecat.services.stt_service import WebsocketSTTService from pipecat.transcriptions.language import Language, resolve_language @@ -57,11 +57,11 @@ class AWSTranscribeSTTSettings(STTSettings): enable_channel_identification: Whether to enable channel identification. """ - sample_rate: int = field(default_factory=lambda: NOT_GIVEN) - media_encoding: str = field(default_factory=lambda: NOT_GIVEN) - number_of_channels: int = field(default_factory=lambda: NOT_GIVEN) - show_speaker_label: bool = field(default_factory=lambda: NOT_GIVEN) - enable_channel_identification: bool = field(default_factory=lambda: NOT_GIVEN) + sample_rate: int | _NotGiven = field(default_factory=lambda: NOT_GIVEN) + media_encoding: str | _NotGiven = field(default_factory=lambda: NOT_GIVEN) + number_of_channels: int | _NotGiven = field(default_factory=lambda: NOT_GIVEN) + show_speaker_label: bool | _NotGiven = field(default_factory=lambda: NOT_GIVEN) + enable_channel_identification: bool | _NotGiven = field(default_factory=lambda: NOT_GIVEN) class AWSTranscribeSTTService(WebsocketSTTService): diff --git a/src/pipecat/services/aws/tts.py b/src/pipecat/services/aws/tts.py index 47c524196..e223a1abc 100644 --- a/src/pipecat/services/aws/tts.py +++ b/src/pipecat/services/aws/tts.py @@ -25,7 +25,7 @@ from pipecat.frames.frames import ( TTSStartedFrame, TTSStoppedFrame, ) -from pipecat.services.settings import NOT_GIVEN, TTSSettings +from pipecat.services.settings import NOT_GIVEN, TTSSettings, _NotGiven from pipecat.services.tts_service import TTSService from pipecat.transcriptions.language import Language, resolve_language from pipecat.utils.tracing.service_decorators import traced_tts @@ -135,11 +135,11 @@ class AWSPollyTTSSettings(TTSSettings): lexicon_names: List of pronunciation lexicons to apply. """ - engine: str = field(default_factory=lambda: NOT_GIVEN) - pitch: str = field(default_factory=lambda: NOT_GIVEN) - rate: str = field(default_factory=lambda: NOT_GIVEN) - volume: str = field(default_factory=lambda: NOT_GIVEN) - lexicon_names: List[str] = field(default_factory=lambda: NOT_GIVEN) + engine: str | _NotGiven = field(default_factory=lambda: NOT_GIVEN) + pitch: str | _NotGiven = field(default_factory=lambda: NOT_GIVEN) + rate: str | _NotGiven = field(default_factory=lambda: NOT_GIVEN) + volume: str | _NotGiven = field(default_factory=lambda: NOT_GIVEN) + lexicon_names: List[str] | _NotGiven = field(default_factory=lambda: NOT_GIVEN) class AWSPollyTTSService(TTSService): diff --git a/src/pipecat/services/azure/stt.py b/src/pipecat/services/azure/stt.py index 18fc9b108..d161b3829 100644 --- a/src/pipecat/services/azure/stt.py +++ b/src/pipecat/services/azure/stt.py @@ -26,7 +26,7 @@ from pipecat.frames.frames import ( TranscriptionFrame, ) from pipecat.services.azure.common import language_to_azure_language -from pipecat.services.settings import NOT_GIVEN, STTSettings +from pipecat.services.settings import NOT_GIVEN, STTSettings, _NotGiven from pipecat.services.stt_latency import AZURE_TTFS_P99 from pipecat.services.stt_service import STTService from pipecat.transcriptions.language import Language @@ -59,8 +59,8 @@ class AzureSTTSettings(STTSettings): sample_rate: Audio sample rate in Hz. """ - region: str = field(default_factory=lambda: NOT_GIVEN) - sample_rate: Optional[int] = field(default_factory=lambda: NOT_GIVEN) + region: str | _NotGiven = field(default_factory=lambda: NOT_GIVEN) + sample_rate: int | None | _NotGiven = field(default_factory=lambda: NOT_GIVEN) class AzureSTTService(STTService): diff --git a/src/pipecat/services/azure/tts.py b/src/pipecat/services/azure/tts.py index b72b33901..b69e60b69 100644 --- a/src/pipecat/services/azure/tts.py +++ b/src/pipecat/services/azure/tts.py @@ -26,7 +26,7 @@ from pipecat.frames.frames import ( ) from pipecat.processors.frame_processor import FrameDirection from pipecat.services.azure.common import language_to_azure_language -from pipecat.services.settings import NOT_GIVEN, TTSSettings +from pipecat.services.settings import NOT_GIVEN, TTSSettings, _NotGiven from pipecat.services.tts_service import TTSService, WordTTSService from pipecat.transcriptions.language import Language from pipecat.utils.tracing.service_decorators import traced_tts @@ -82,14 +82,14 @@ class AzureTTSSettings(TTSSettings): volume: Volume level (e.g., "+20%", "loud", "x-soft"). """ - emphasis: str = field(default_factory=lambda: NOT_GIVEN) - language: str = field(default_factory=lambda: NOT_GIVEN) - pitch: str = field(default_factory=lambda: NOT_GIVEN) - rate: str = field(default_factory=lambda: NOT_GIVEN) - role: str = field(default_factory=lambda: NOT_GIVEN) - style: str = field(default_factory=lambda: NOT_GIVEN) - style_degree: str = field(default_factory=lambda: NOT_GIVEN) - volume: str = field(default_factory=lambda: NOT_GIVEN) + emphasis: str | _NotGiven = field(default_factory=lambda: NOT_GIVEN) + language: str | _NotGiven = field(default_factory=lambda: NOT_GIVEN) + pitch: str | _NotGiven = field(default_factory=lambda: NOT_GIVEN) + rate: str | _NotGiven = field(default_factory=lambda: NOT_GIVEN) + role: str | _NotGiven = field(default_factory=lambda: NOT_GIVEN) + style: str | _NotGiven = field(default_factory=lambda: NOT_GIVEN) + style_degree: str | _NotGiven = field(default_factory=lambda: NOT_GIVEN) + volume: str | _NotGiven = field(default_factory=lambda: NOT_GIVEN) class AzureBaseTTSService: diff --git a/src/pipecat/services/camb/tts.py b/src/pipecat/services/camb/tts.py index 95b0ddd52..40dabd17e 100644 --- a/src/pipecat/services/camb/tts.py +++ b/src/pipecat/services/camb/tts.py @@ -32,7 +32,7 @@ from pipecat.frames.frames import ( TTSStartedFrame, TTSStoppedFrame, ) -from pipecat.services.settings import NOT_GIVEN, TTSSettings +from pipecat.services.settings import NOT_GIVEN, TTSSettings, _NotGiven from pipecat.services.tts_service import TTSService from pipecat.transcriptions.language import Language, resolve_language from pipecat.utils.tracing.service_decorators import traced_tts @@ -144,7 +144,7 @@ class CambTTSSettings(TTSSettings): Ignored for other models. Max 1000 characters. """ - user_instructions: str = field(default_factory=lambda: NOT_GIVEN) + user_instructions: str | None | _NotGiven = field(default_factory=lambda: NOT_GIVEN) class CambTTSService(TTSService): diff --git a/src/pipecat/services/cartesia/stt.py b/src/pipecat/services/cartesia/stt.py index 6629d05bb..e3270936b 100644 --- a/src/pipecat/services/cartesia/stt.py +++ b/src/pipecat/services/cartesia/stt.py @@ -28,7 +28,7 @@ from pipecat.frames.frames import ( VADUserStoppedSpeakingFrame, ) from pipecat.processors.frame_processor import FrameDirection -from pipecat.services.settings import NOT_GIVEN, STTSettings +from pipecat.services.settings import NOT_GIVEN, STTSettings, _NotGiven from pipecat.services.stt_latency import CARTESIA_TTFS_P99 from pipecat.services.stt_service import WebsocketSTTService from pipecat.transcriptions.language import Language @@ -52,7 +52,7 @@ class CartesiaSTTSettings(STTSettings): encoding: Audio encoding format (e.g. ``"pcm_s16le"``). """ - encoding: str = field(default_factory=lambda: NOT_GIVEN) + encoding: str | _NotGiven = field(default_factory=lambda: NOT_GIVEN) class CartesiaLiveOptions: diff --git a/src/pipecat/services/cartesia/tts.py b/src/pipecat/services/cartesia/tts.py index 4e45f50aa..0d8936fdd 100644 --- a/src/pipecat/services/cartesia/tts.py +++ b/src/pipecat/services/cartesia/tts.py @@ -28,7 +28,7 @@ from pipecat.frames.frames import ( TTSStoppedFrame, ) from pipecat.processors.frame_processor import FrameDirection -from pipecat.services.settings import NOT_GIVEN, TTSSettings, is_given +from pipecat.services.settings import NOT_GIVEN, TTSSettings, _NotGiven, is_given from pipecat.services.tts_service import AudioContextWordTTSService, TTSService from pipecat.transcriptions.language import Language, resolve_language from pipecat.utils.text.base_text_aggregator import BaseTextAggregator @@ -209,13 +209,13 @@ class CartesiaTTSSettings(TTSSettings): custom pronunciations. """ - output_container: str = field(default_factory=lambda: NOT_GIVEN) - output_encoding: str = field(default_factory=lambda: NOT_GIVEN) - output_sample_rate: int = field(default_factory=lambda: NOT_GIVEN) - speed: str = field(default_factory=lambda: NOT_GIVEN) - emotion: List[str] = field(default_factory=lambda: NOT_GIVEN) - generation_config: GenerationConfig = field(default_factory=lambda: NOT_GIVEN) - pronunciation_dict_id: str = field(default_factory=lambda: NOT_GIVEN) + output_container: str | _NotGiven = field(default_factory=lambda: NOT_GIVEN) + output_encoding: str | _NotGiven = field(default_factory=lambda: NOT_GIVEN) + output_sample_rate: int | _NotGiven = field(default_factory=lambda: NOT_GIVEN) + speed: Literal["slow", "normal", "fast"] | _NotGiven = field(default_factory=lambda: NOT_GIVEN) + emotion: List[str] | _NotGiven = field(default_factory=lambda: NOT_GIVEN) + generation_config: GenerationConfig | _NotGiven = field(default_factory=lambda: NOT_GIVEN) + pronunciation_dict_id: str | _NotGiven = field(default_factory=lambda: NOT_GIVEN) @classmethod def from_mapping(cls, settings: Mapping[str, Any]) -> "CartesiaTTSSettings": diff --git a/src/pipecat/services/deepgram/stt.py b/src/pipecat/services/deepgram/stt.py index f52932b2c..8d4a72fc3 100644 --- a/src/pipecat/services/deepgram/stt.py +++ b/src/pipecat/services/deepgram/stt.py @@ -24,7 +24,7 @@ from pipecat.frames.frames import ( VADUserStoppedSpeakingFrame, ) from pipecat.processors.frame_processor import FrameDirection -from pipecat.services.settings import NOT_GIVEN, STTSettings, is_given +from pipecat.services.settings import NOT_GIVEN, STTSettings, _NotGiven, is_given from pipecat.services.stt_latency import DEEPGRAM_TTFS_P99 from pipecat.services.stt_service import STTService from pipecat.transcriptions.language import Language @@ -55,7 +55,7 @@ class DeepgramSTTSettings(STTSettings): live_options: Deepgram ``LiveOptions`` for detailed configuration. """ - live_options: LiveOptions = field(default_factory=lambda: NOT_GIVEN) + live_options: LiveOptions | _NotGiven = field(default_factory=lambda: NOT_GIVEN) class DeepgramSTTService(STTService): diff --git a/src/pipecat/services/deepgram/stt_sagemaker.py b/src/pipecat/services/deepgram/stt_sagemaker.py index 870ded11f..3184bf7f8 100644 --- a/src/pipecat/services/deepgram/stt_sagemaker.py +++ b/src/pipecat/services/deepgram/stt_sagemaker.py @@ -32,7 +32,7 @@ from pipecat.frames.frames import ( ) from pipecat.processors.frame_processor import FrameDirection from pipecat.services.aws.sagemaker.bidi_client import SageMakerBidiClient -from pipecat.services.settings import NOT_GIVEN, STTSettings, is_given +from pipecat.services.settings import NOT_GIVEN, STTSettings, _NotGiven, is_given from pipecat.services.stt_latency import DEEPGRAM_SAGEMAKER_TTFS_P99 from pipecat.services.stt_service import STTService from pipecat.transcriptions.language import Language @@ -57,7 +57,7 @@ class DeepgramSageMakerSTTSettings(STTSettings): live_options: Deepgram ``LiveOptions`` for detailed configuration. """ - live_options: LiveOptions = field(default_factory=lambda: NOT_GIVEN) + live_options: LiveOptions | _NotGiven = field(default_factory=lambda: NOT_GIVEN) class DeepgramSageMakerSTTService(STTService): diff --git a/src/pipecat/services/deepgram/tts.py b/src/pipecat/services/deepgram/tts.py index 7f4d78f13..3458a4529 100644 --- a/src/pipecat/services/deepgram/tts.py +++ b/src/pipecat/services/deepgram/tts.py @@ -30,7 +30,7 @@ from pipecat.frames.frames import ( TTSStoppedFrame, ) from pipecat.processors.frame_processor import FrameDirection -from pipecat.services.settings import NOT_GIVEN, TTSSettings +from pipecat.services.settings import NOT_GIVEN, TTSSettings, _NotGiven from pipecat.services.tts_service import TTSService, WebsocketTTSService from pipecat.utils.tracing.service_decorators import traced_tts @@ -53,7 +53,7 @@ class DeepgramTTSSettings(TTSSettings): encoding: Audio encoding format (linear16, mulaw, alaw). """ - encoding: str = field(default_factory=lambda: NOT_GIVEN) + encoding: str | _NotGiven = field(default_factory=lambda: NOT_GIVEN) class DeepgramTTSService(WebsocketTTSService): diff --git a/src/pipecat/services/elevenlabs/stt.py b/src/pipecat/services/elevenlabs/stt.py index e5b7b3843..c3e6b29e7 100644 --- a/src/pipecat/services/elevenlabs/stt.py +++ b/src/pipecat/services/elevenlabs/stt.py @@ -35,7 +35,7 @@ from pipecat.frames.frames import ( VADUserStoppedSpeakingFrame, ) from pipecat.processors.frame_processor import FrameDirection -from pipecat.services.settings import NOT_GIVEN, STTSettings +from pipecat.services.settings import NOT_GIVEN, STTSettings, _NotGiven from pipecat.services.stt_latency import ELEVENLABS_REALTIME_TTFS_P99, ELEVENLABS_TTFS_P99 from pipecat.services.stt_service import SegmentedSTTService, WebsocketSTTService from pipecat.transcriptions.language import Language, resolve_language @@ -185,7 +185,7 @@ class ElevenLabsSTTSettings(STTSettings): tag_audio_events: Whether to include audio event tags in transcription. """ - tag_audio_events: bool = field(default_factory=lambda: NOT_GIVEN) + tag_audio_events: bool | _NotGiven = field(default_factory=lambda: NOT_GIVEN) @dataclass @@ -205,14 +205,14 @@ class ElevenLabsRealtimeSTTSettings(STTSettings): include_language_detection: Whether to include language detection in transcripts. """ - commit_strategy: CommitStrategy = field(default_factory=lambda: NOT_GIVEN) - vad_silence_threshold_secs: float = field(default_factory=lambda: NOT_GIVEN) - vad_threshold: float = field(default_factory=lambda: NOT_GIVEN) - min_speech_duration_ms: int = field(default_factory=lambda: NOT_GIVEN) - min_silence_duration_ms: int = field(default_factory=lambda: NOT_GIVEN) - include_timestamps: bool = field(default_factory=lambda: NOT_GIVEN) - enable_logging: bool = field(default_factory=lambda: NOT_GIVEN) - include_language_detection: bool = field(default_factory=lambda: NOT_GIVEN) + commit_strategy: CommitStrategy | _NotGiven = field(default_factory=lambda: NOT_GIVEN) + vad_silence_threshold_secs: float | None | _NotGiven = field(default_factory=lambda: NOT_GIVEN) + vad_threshold: float | None | _NotGiven = field(default_factory=lambda: NOT_GIVEN) + min_speech_duration_ms: int | None | _NotGiven = field(default_factory=lambda: NOT_GIVEN) + min_silence_duration_ms: int | None | _NotGiven = field(default_factory=lambda: NOT_GIVEN) + include_timestamps: bool | _NotGiven = field(default_factory=lambda: NOT_GIVEN) + enable_logging: bool | _NotGiven = field(default_factory=lambda: NOT_GIVEN) + include_language_detection: bool | _NotGiven = field(default_factory=lambda: NOT_GIVEN) class ElevenLabsSTTService(SegmentedSTTService): diff --git a/src/pipecat/services/elevenlabs/tts.py b/src/pipecat/services/elevenlabs/tts.py index fbde4a4b7..9503866a7 100644 --- a/src/pipecat/services/elevenlabs/tts.py +++ b/src/pipecat/services/elevenlabs/tts.py @@ -44,7 +44,7 @@ from pipecat.frames.frames import ( TTSStoppedFrame, ) from pipecat.processors.frame_processor import FrameDirection -from pipecat.services.settings import NOT_GIVEN, TTSSettings, is_given +from pipecat.services.settings import NOT_GIVEN, TTSSettings, _NotGiven, is_given from pipecat.services.tts_service import ( AudioContextWordTTSService, WordTTSService, @@ -206,15 +206,17 @@ class ElevenLabsTTSSettings(TTSSettings): apply_text_normalization: Text normalization mode ("auto", "on", "off"). """ - stability: float = field(default_factory=lambda: NOT_GIVEN) - similarity_boost: float = field(default_factory=lambda: NOT_GIVEN) - style: float = field(default_factory=lambda: NOT_GIVEN) - use_speaker_boost: bool = field(default_factory=lambda: NOT_GIVEN) - speed: float = field(default_factory=lambda: NOT_GIVEN) - auto_mode: str = field(default_factory=lambda: NOT_GIVEN) - enable_ssml_parsing: bool = field(default_factory=lambda: NOT_GIVEN) - enable_logging: bool = field(default_factory=lambda: NOT_GIVEN) - apply_text_normalization: str = field(default_factory=lambda: NOT_GIVEN) + stability: float | None | _NotGiven = field(default_factory=lambda: NOT_GIVEN) + similarity_boost: float | None | _NotGiven = field(default_factory=lambda: NOT_GIVEN) + style: float | None | _NotGiven = field(default_factory=lambda: NOT_GIVEN) + use_speaker_boost: bool | None | _NotGiven = field(default_factory=lambda: NOT_GIVEN) + speed: float | None | _NotGiven = field(default_factory=lambda: NOT_GIVEN) + auto_mode: bool | None | _NotGiven = field(default_factory=lambda: NOT_GIVEN) + enable_ssml_parsing: bool | None | _NotGiven = field(default_factory=lambda: NOT_GIVEN) + enable_logging: bool | None | _NotGiven = field(default_factory=lambda: NOT_GIVEN) + apply_text_normalization: Literal["auto", "on", "off"] | None | _NotGiven = field( + default_factory=lambda: NOT_GIVEN + ) #: Fields in the WS URL — changing any of these requires a reconnect. URL_FIELDS: ClassVar[frozenset[str]] = frozenset({"voice", "model", "language"}) @@ -242,13 +244,15 @@ class ElevenLabsHttpTTSSettings(TTSSettings): apply_text_normalization: Text normalization mode ("auto", "on", "off"). """ - optimize_streaming_latency: int = field(default_factory=lambda: NOT_GIVEN) - stability: float = field(default_factory=lambda: NOT_GIVEN) - similarity_boost: float = field(default_factory=lambda: NOT_GIVEN) - style: float = field(default_factory=lambda: NOT_GIVEN) - use_speaker_boost: bool = field(default_factory=lambda: NOT_GIVEN) - speed: float = field(default_factory=lambda: NOT_GIVEN) - apply_text_normalization: str = field(default_factory=lambda: NOT_GIVEN) + optimize_streaming_latency: int | None | _NotGiven = field(default_factory=lambda: NOT_GIVEN) + stability: float | None | _NotGiven = field(default_factory=lambda: NOT_GIVEN) + similarity_boost: float | None | _NotGiven = field(default_factory=lambda: NOT_GIVEN) + style: float | None | _NotGiven = field(default_factory=lambda: NOT_GIVEN) + use_speaker_boost: bool | None | _NotGiven = field(default_factory=lambda: NOT_GIVEN) + speed: float | None | _NotGiven = field(default_factory=lambda: NOT_GIVEN) + apply_text_normalization: Literal["auto", "on", "off"] | None | _NotGiven = field( + default_factory=lambda: NOT_GIVEN + ) _aliases: ClassVar[Dict[str, str]] = {"voice_id": "voice"} diff --git a/src/pipecat/services/fal/stt.py b/src/pipecat/services/fal/stt.py index a29d8d70d..bcfc583c6 100644 --- a/src/pipecat/services/fal/stt.py +++ b/src/pipecat/services/fal/stt.py @@ -18,7 +18,7 @@ from loguru import logger from pydantic import BaseModel from pipecat.frames.frames import ErrorFrame, Frame, TranscriptionFrame -from pipecat.services.settings import NOT_GIVEN, STTSettings +from pipecat.services.settings import NOT_GIVEN, STTSettings, _NotGiven from pipecat.services.stt_latency import FAL_TTFS_P99 from pipecat.services.stt_service import SegmentedSTTService from pipecat.transcriptions.language import Language, resolve_language @@ -159,9 +159,9 @@ class FalSTTSettings(STTSettings): version: Version of Wizper model to use. Defaults to '3'. """ - task: str = field(default_factory=lambda: NOT_GIVEN) - chunk_level: str = field(default_factory=lambda: NOT_GIVEN) - version: str = field(default_factory=lambda: NOT_GIVEN) + task: str | _NotGiven = field(default_factory=lambda: NOT_GIVEN) + chunk_level: str | _NotGiven = field(default_factory=lambda: NOT_GIVEN) + version: str | _NotGiven = field(default_factory=lambda: NOT_GIVEN) class FalSTTService(SegmentedSTTService): diff --git a/src/pipecat/services/fish/tts.py b/src/pipecat/services/fish/tts.py index 09ed72099..131495769 100644 --- a/src/pipecat/services/fish/tts.py +++ b/src/pipecat/services/fish/tts.py @@ -29,7 +29,7 @@ from pipecat.frames.frames import ( TTSStoppedFrame, ) from pipecat.processors.frame_processor import FrameDirection -from pipecat.services.settings import NOT_GIVEN, TTSSettings +from pipecat.services.settings import NOT_GIVEN, TTSSettings, _NotGiven from pipecat.services.tts_service import InterruptibleTTSService from pipecat.transcriptions.language import Language from pipecat.utils.tracing.service_decorators import traced_tts @@ -61,13 +61,13 @@ class FishAudioTTSSettings(TTSSettings): reference_id: Reference ID of the voice model. """ - fish_sample_rate: int = field(default_factory=lambda: NOT_GIVEN) - latency: str = field(default_factory=lambda: NOT_GIVEN) - format: str = field(default_factory=lambda: NOT_GIVEN) - normalize: bool = field(default_factory=lambda: NOT_GIVEN) - prosody_speed: float = field(default_factory=lambda: NOT_GIVEN) - prosody_volume: int = field(default_factory=lambda: NOT_GIVEN) - reference_id: str = field(default_factory=lambda: NOT_GIVEN) + fish_sample_rate: int | _NotGiven = field(default_factory=lambda: NOT_GIVEN) + latency: str | None | _NotGiven = field(default_factory=lambda: NOT_GIVEN) + format: str | _NotGiven = field(default_factory=lambda: NOT_GIVEN) + normalize: bool | None | _NotGiven = field(default_factory=lambda: NOT_GIVEN) + prosody_speed: float | None | _NotGiven = field(default_factory=lambda: NOT_GIVEN) + prosody_volume: int | None | _NotGiven = field(default_factory=lambda: NOT_GIVEN) + reference_id: str | None | _NotGiven = field(default_factory=lambda: NOT_GIVEN) _aliases: ClassVar[Dict[str, str]] = {"voice_id": "voice", "sample_rate": "fish_sample_rate"} diff --git a/src/pipecat/services/gladia/stt.py b/src/pipecat/services/gladia/stt.py index 25922e7aa..c92d9469f 100644 --- a/src/pipecat/services/gladia/stt.py +++ b/src/pipecat/services/gladia/stt.py @@ -33,7 +33,7 @@ from pipecat.frames.frames import ( UserStoppedSpeakingFrame, ) from pipecat.services.gladia.config import GladiaInputParams -from pipecat.services.settings import NOT_GIVEN, STTSettings +from pipecat.services.settings import NOT_GIVEN, STTSettings, _NotGiven from pipecat.services.stt_latency import GLADIA_TTFS_P99 from pipecat.services.stt_service import WebsocketSTTService from pipecat.transcriptions.language import Language, resolve_language @@ -188,7 +188,7 @@ class GladiaSTTSettings(STTSettings): input_params: Gladia ``GladiaInputParams`` for detailed configuration. """ - input_params: GladiaInputParams = field(default_factory=lambda: NOT_GIVEN) + input_params: GladiaInputParams | _NotGiven = field(default_factory=lambda: NOT_GIVEN) class GladiaSTTService(WebsocketSTTService): diff --git a/src/pipecat/services/google/gemini_live/llm.py b/src/pipecat/services/google/gemini_live/llm.py index 3047e258d..00b540385 100644 --- a/src/pipecat/services/google/gemini_live/llm.py +++ b/src/pipecat/services/google/gemini_live/llm.py @@ -76,7 +76,7 @@ from pipecat.services.openai.llm import ( OpenAIAssistantContextAggregator, OpenAIUserContextAggregator, ) -from pipecat.services.settings import NOT_GIVEN, LLMSettings +from pipecat.services.settings import NOT_GIVEN, LLMSettings, _NotGiven from pipecat.transcriptions.language import Language, resolve_language from pipecat.utils.string import match_endofsentence from pipecat.utils.time import time_now_iso8601 @@ -617,14 +617,16 @@ class GeminiLiveLLMSettings(LLMSettings): proactivity: Proactivity configuration. """ - modalities: Any = field(default_factory=lambda: NOT_GIVEN) - language: Any = field(default_factory=lambda: NOT_GIVEN) - media_resolution: Any = field(default_factory=lambda: NOT_GIVEN) - vad: Any = field(default_factory=lambda: NOT_GIVEN) - context_window_compression: Any = field(default_factory=lambda: NOT_GIVEN) - thinking: Any = field(default_factory=lambda: NOT_GIVEN) - enable_affective_dialog: Any = field(default_factory=lambda: NOT_GIVEN) - proactivity: Any = field(default_factory=lambda: NOT_GIVEN) + modalities: GeminiModalities | _NotGiven = field(default_factory=lambda: NOT_GIVEN) + language: Language | str | _NotGiven = field(default_factory=lambda: NOT_GIVEN) + media_resolution: GeminiMediaResolution | _NotGiven = field(default_factory=lambda: NOT_GIVEN) + vad: GeminiVADParams | _NotGiven = field(default_factory=lambda: NOT_GIVEN) + context_window_compression: ContextWindowCompressionParams | dict | _NotGiven = field( + default_factory=lambda: NOT_GIVEN + ) + thinking: ThinkingConfig | dict | _NotGiven = field(default_factory=lambda: NOT_GIVEN) + enable_affective_dialog: bool | _NotGiven = field(default_factory=lambda: NOT_GIVEN) + proactivity: ProactivityConfig | dict | _NotGiven = field(default_factory=lambda: NOT_GIVEN) class GeminiLiveLLMService(LLMService): diff --git a/src/pipecat/services/google/llm.py b/src/pipecat/services/google/llm.py index bf1958f66..0a097b770 100644 --- a/src/pipecat/services/google/llm.py +++ b/src/pipecat/services/google/llm.py @@ -58,7 +58,7 @@ from pipecat.services.openai.llm import ( OpenAIAssistantContextAggregator, OpenAIUserContextAggregator, ) -from pipecat.services.settings import NOT_GIVEN, LLMSettings, is_given +from pipecat.services.settings import NOT_GIVEN, LLMSettings, _NotGiven, is_given from pipecat.utils.tracing.service_decorators import traced_llm # Suppress gRPC fork warnings @@ -681,7 +681,9 @@ class GoogleLLMSettings(LLMSettings): thinking: Thinking configuration. """ - thinking: Any = field(default_factory=lambda: NOT_GIVEN) + thinking: "GoogleLLMService.ThinkingConfig" | _NotGiven = field( + default_factory=lambda: NOT_GIVEN + ) @classmethod def from_mapping(cls, settings): diff --git a/src/pipecat/services/google/stt.py b/src/pipecat/services/google/stt.py index cdd583c8e..72d4f12b6 100644 --- a/src/pipecat/services/google/stt.py +++ b/src/pipecat/services/google/stt.py @@ -36,7 +36,7 @@ from pipecat.frames.frames import ( StartFrame, TranscriptionFrame, ) -from pipecat.services.settings import NOT_GIVEN, STTSettings +from pipecat.services.settings import NOT_GIVEN, STTSettings, _NotGiven from pipecat.services.stt_latency import GOOGLE_TTFS_P99 from pipecat.services.stt_service import STTService from pipecat.transcriptions.language import Language, resolve_language @@ -383,17 +383,19 @@ class GoogleSTTSettings(STTSettings): enable_voice_activity_events: Detect voice activity in audio. """ - languages: Any = field(default_factory=lambda: NOT_GIVEN) - language_codes: Any = field(default_factory=lambda: NOT_GIVEN) - use_separate_recognition_per_channel: Any = field(default_factory=lambda: NOT_GIVEN) - enable_automatic_punctuation: Any = field(default_factory=lambda: NOT_GIVEN) - enable_spoken_punctuation: Any = field(default_factory=lambda: NOT_GIVEN) - enable_spoken_emojis: Any = field(default_factory=lambda: NOT_GIVEN) - profanity_filter: Any = field(default_factory=lambda: NOT_GIVEN) - enable_word_time_offsets: Any = field(default_factory=lambda: NOT_GIVEN) - enable_word_confidence: Any = field(default_factory=lambda: NOT_GIVEN) - enable_interim_results: Any = field(default_factory=lambda: NOT_GIVEN) - enable_voice_activity_events: Any = field(default_factory=lambda: NOT_GIVEN) + languages: List[Language] | _NotGiven = field(default_factory=lambda: NOT_GIVEN) + language_codes: List[str] | _NotGiven = field(default_factory=lambda: NOT_GIVEN) + use_separate_recognition_per_channel: bool | _NotGiven = field( + default_factory=lambda: NOT_GIVEN + ) + enable_automatic_punctuation: bool | _NotGiven = field(default_factory=lambda: NOT_GIVEN) + enable_spoken_punctuation: bool | _NotGiven = field(default_factory=lambda: NOT_GIVEN) + enable_spoken_emojis: bool | _NotGiven = field(default_factory=lambda: NOT_GIVEN) + profanity_filter: bool | _NotGiven = field(default_factory=lambda: NOT_GIVEN) + enable_word_time_offsets: bool | _NotGiven = field(default_factory=lambda: NOT_GIVEN) + enable_word_confidence: bool | _NotGiven = field(default_factory=lambda: NOT_GIVEN) + enable_interim_results: bool | _NotGiven = field(default_factory=lambda: NOT_GIVEN) + enable_voice_activity_events: bool | _NotGiven = field(default_factory=lambda: NOT_GIVEN) class GoogleSTTService(STTService): diff --git a/src/pipecat/services/google/tts.py b/src/pipecat/services/google/tts.py index e47aa384a..60bed9c6d 100644 --- a/src/pipecat/services/google/tts.py +++ b/src/pipecat/services/google/tts.py @@ -24,7 +24,7 @@ from pipecat.utils.tracing.service_decorators import traced_tts os.environ["GRPC_ENABLE_FORK_SUPPORT"] = "false" from dataclasses import dataclass, field -from typing import Any, AsyncGenerator, List, Literal, Optional +from typing import Any, AsyncGenerator, Dict, List, Literal, Optional from loguru import logger from pydantic import BaseModel @@ -37,7 +37,7 @@ from pipecat.frames.frames import ( TTSStartedFrame, TTSStoppedFrame, ) -from pipecat.services.settings import NOT_GIVEN, TTSSettings, is_given +from pipecat.services.settings import NOT_GIVEN, TTSSettings, _NotGiven, is_given from pipecat.services.tts_service import TTSService from pipecat.transcriptions.language import Language, resolve_language @@ -493,14 +493,20 @@ class GoogleHttpTTSSettings(TTSSettings): google_style: Google-specific voice style. """ - pitch: str = field(default_factory=lambda: NOT_GIVEN) - rate: str = field(default_factory=lambda: NOT_GIVEN) - speaking_rate: float = field(default_factory=lambda: NOT_GIVEN) - volume: str = field(default_factory=lambda: NOT_GIVEN) - emphasis: str = field(default_factory=lambda: NOT_GIVEN) - language: str = field(default_factory=lambda: NOT_GIVEN) - gender: str = field(default_factory=lambda: NOT_GIVEN) - google_style: str = field(default_factory=lambda: NOT_GIVEN) + pitch: str | None | _NotGiven = field(default_factory=lambda: NOT_GIVEN) + rate: str | None | _NotGiven = field(default_factory=lambda: NOT_GIVEN) + speaking_rate: float | None | _NotGiven = field(default_factory=lambda: NOT_GIVEN) + volume: str | None | _NotGiven = field(default_factory=lambda: NOT_GIVEN) + emphasis: Literal["strong", "moderate", "reduced", "none"] | None | _NotGiven = field( + default_factory=lambda: NOT_GIVEN + ) + language: str | None | _NotGiven = field(default_factory=lambda: NOT_GIVEN) + gender: Literal["male", "female", "neutral"] | None | _NotGiven = field( + default_factory=lambda: NOT_GIVEN + ) + google_style: ( + Literal["apologetic", "calm", "empathetic", "firm", "lively"] | None | _NotGiven + ) = field(default_factory=lambda: NOT_GIVEN) @dataclass @@ -512,8 +518,8 @@ class GoogleStreamTTSSettings(TTSSettings): speaking_rate: The speaking rate, in the range [0.25, 2.0]. """ - language: str = field(default_factory=lambda: NOT_GIVEN) - speaking_rate: float = field(default_factory=lambda: NOT_GIVEN) + language: str | None | _NotGiven = field(default_factory=lambda: NOT_GIVEN) + speaking_rate: float | None | _NotGiven = field(default_factory=lambda: NOT_GIVEN) @dataclass @@ -527,10 +533,12 @@ class GeminiTTSSettings(TTSSettings): speaker_configs: List of speaker configurations for multi-speaker mode. """ - language: str = field(default_factory=lambda: NOT_GIVEN) - prompt: str = field(default_factory=lambda: NOT_GIVEN) - multi_speaker: bool = field(default_factory=lambda: NOT_GIVEN) - speaker_configs: List[dict] = field(default_factory=lambda: NOT_GIVEN) + language: str | None | _NotGiven = field(default_factory=lambda: NOT_GIVEN) + prompt: str | None | _NotGiven = field(default_factory=lambda: NOT_GIVEN) + multi_speaker: bool | _NotGiven = field(default_factory=lambda: NOT_GIVEN) + speaker_configs: list[dict[str, Any]] | None | _NotGiven = field( + default_factory=lambda: NOT_GIVEN + ) class GoogleHttpTTSService(TTSService): diff --git a/src/pipecat/services/gradium/stt.py b/src/pipecat/services/gradium/stt.py index 381f76884..1583fac3c 100644 --- a/src/pipecat/services/gradium/stt.py +++ b/src/pipecat/services/gradium/stt.py @@ -28,7 +28,7 @@ from pipecat.frames.frames import ( VADUserStoppedSpeakingFrame, ) from pipecat.processors.frame_processor import FrameDirection -from pipecat.services.settings import NOT_GIVEN, STTSettings, is_given +from pipecat.services.settings import NOT_GIVEN, STTSettings, _NotGiven, is_given from pipecat.services.stt_latency import GRADIUM_TTFS_P99 from pipecat.services.stt_service import WebsocketSTTService from pipecat.transcriptions.language import Language, resolve_language @@ -75,7 +75,7 @@ class GradiumSTTSettings(STTSettings): generated. Higher delays allow more context but increase latency. """ - delay_in_frames: int = field(default_factory=lambda: NOT_GIVEN) + delay_in_frames: int | _NotGiven = field(default_factory=lambda: NOT_GIVEN) class GradiumSTTService(WebsocketSTTService): diff --git a/src/pipecat/services/gradium/tts.py b/src/pipecat/services/gradium/tts.py index 3bffbb5bf..c41c77436 100644 --- a/src/pipecat/services/gradium/tts.py +++ b/src/pipecat/services/gradium/tts.py @@ -23,7 +23,7 @@ from pipecat.frames.frames import ( TTSStoppedFrame, ) from pipecat.processors.frame_processor import FrameDirection -from pipecat.services.settings import NOT_GIVEN, TTSSettings +from pipecat.services.settings import NOT_GIVEN, TTSSettings, _NotGiven from pipecat.services.tts_service import InterruptibleWordTTSService from pipecat.utils.tracing.service_decorators import traced_tts @@ -47,7 +47,7 @@ class GradiumTTSSettings(TTSSettings): output_format: Audio output format. """ - output_format: str = field(default_factory=lambda: NOT_GIVEN) + output_format: str | _NotGiven = field(default_factory=lambda: NOT_GIVEN) class GradiumTTSService(InterruptibleWordTTSService): diff --git a/src/pipecat/services/groq/tts.py b/src/pipecat/services/groq/tts.py index e4c10f2e9..b3b4c5f57 100644 --- a/src/pipecat/services/groq/tts.py +++ b/src/pipecat/services/groq/tts.py @@ -21,7 +21,7 @@ from pipecat.frames.frames import ( TTSStartedFrame, TTSStoppedFrame, ) -from pipecat.services.settings import NOT_GIVEN, TTSSettings +from pipecat.services.settings import NOT_GIVEN, TTSSettings, _NotGiven from pipecat.services.tts_service import TTSService from pipecat.transcriptions.language import Language from pipecat.utils.tracing.service_decorators import traced_tts @@ -44,9 +44,9 @@ class GroqTTSSettings(TTSSettings): groq_sample_rate: Audio sample rate. """ - output_format: str = field(default_factory=lambda: NOT_GIVEN) - speed: float = field(default_factory=lambda: NOT_GIVEN) - groq_sample_rate: int = field(default_factory=lambda: NOT_GIVEN) + output_format: str | _NotGiven = field(default_factory=lambda: NOT_GIVEN) + speed: float | None | _NotGiven = field(default_factory=lambda: NOT_GIVEN) + groq_sample_rate: int | _NotGiven = field(default_factory=lambda: NOT_GIVEN) _aliases: ClassVar[Dict[str, str]] = {"voice_id": "voice", "sample_rate": "groq_sample_rate"} diff --git a/src/pipecat/services/hathora/stt.py b/src/pipecat/services/hathora/stt.py index a620ed79a..e77e382c0 100644 --- a/src/pipecat/services/hathora/stt.py +++ b/src/pipecat/services/hathora/stt.py @@ -19,7 +19,7 @@ from pipecat.frames.frames import ( Frame, TranscriptionFrame, ) -from pipecat.services.settings import NOT_GIVEN, STTSettings +from pipecat.services.settings import NOT_GIVEN, STTSettings, _NotGiven from pipecat.services.stt_latency import HATHORA_TTFS_P99 from pipecat.services.stt_service import SegmentedSTTService from pipecat.transcriptions.language import Language @@ -39,7 +39,7 @@ class HathoraSTTSettings(STTSettings): what is supported. """ - config: Optional[list] = field(default_factory=lambda: NOT_GIVEN) + config: list[ConfigOption] | _NotGiven = field(default_factory=lambda: NOT_GIVEN) class HathoraSTTService(SegmentedSTTService): diff --git a/src/pipecat/services/hathora/tts.py b/src/pipecat/services/hathora/tts.py index f3524734a..e15dfcc54 100644 --- a/src/pipecat/services/hathora/tts.py +++ b/src/pipecat/services/hathora/tts.py @@ -22,7 +22,7 @@ from pipecat.frames.frames import ( TTSStartedFrame, TTSStoppedFrame, ) -from pipecat.services.settings import NOT_GIVEN, TTSSettings +from pipecat.services.settings import NOT_GIVEN, TTSSettings, _NotGiven from pipecat.services.tts_service import TTSService from pipecat.utils.tracing.service_decorators import traced_tts @@ -58,8 +58,8 @@ class HathoraTTSSettings(TTSSettings): what is supported. """ - speed: float = field(default_factory=lambda: NOT_GIVEN) - config: list = field(default_factory=lambda: NOT_GIVEN) + speed: float | _NotGiven = field(default_factory=lambda: NOT_GIVEN) + config: list[ConfigOption] | _NotGiven = field(default_factory=lambda: NOT_GIVEN) class HathoraTTSService(TTSService): diff --git a/src/pipecat/services/inworld/tts.py b/src/pipecat/services/inworld/tts.py index fea30f3a1..bdbbb82d7 100644 --- a/src/pipecat/services/inworld/tts.py +++ b/src/pipecat/services/inworld/tts.py @@ -24,7 +24,7 @@ import websockets from loguru import logger from pydantic import BaseModel -from pipecat.services.settings import NOT_GIVEN, TTSSettings, is_given +from pipecat.services.settings import NOT_GIVEN, TTSSettings, _NotGiven, is_given try: from websockets.asyncio.client import connect as websocket_connect @@ -67,12 +67,12 @@ class InworldTTSSettings(TTSSettings): apply_text_normalization: Whether to apply text normalization. """ - audio_encoding: str = field(default_factory=lambda: NOT_GIVEN) - audio_sample_rate: int = field(default_factory=lambda: NOT_GIVEN) - speaking_rate: float = field(default_factory=lambda: NOT_GIVEN) - temperature: float = field(default_factory=lambda: NOT_GIVEN) - auto_mode: bool = field(default_factory=lambda: NOT_GIVEN) - apply_text_normalization: str = field(default_factory=lambda: NOT_GIVEN) + audio_encoding: str | _NotGiven = field(default_factory=lambda: NOT_GIVEN) + audio_sample_rate: int | _NotGiven = field(default_factory=lambda: NOT_GIVEN) + speaking_rate: float | _NotGiven = field(default_factory=lambda: NOT_GIVEN) + temperature: float | _NotGiven = field(default_factory=lambda: NOT_GIVEN) + auto_mode: bool | _NotGiven = field(default_factory=lambda: NOT_GIVEN) + apply_text_normalization: str | _NotGiven = field(default_factory=lambda: NOT_GIVEN) _aliases: ClassVar[Dict[str, str]] = { "voice_id": "voice", diff --git a/src/pipecat/services/kokoro/tts.py b/src/pipecat/services/kokoro/tts.py index b88511437..735145da7 100644 --- a/src/pipecat/services/kokoro/tts.py +++ b/src/pipecat/services/kokoro/tts.py @@ -23,7 +23,7 @@ from pipecat.frames.frames import ( TTSStartedFrame, TTSStoppedFrame, ) -from pipecat.services.settings import NOT_GIVEN, TTSSettings +from pipecat.services.settings import NOT_GIVEN, TTSSettings, _NotGiven from pipecat.services.tts_service import TTSService from pipecat.transcriptions.language import Language, resolve_language from pipecat.utils.tracing.service_decorators import traced_tts @@ -97,7 +97,7 @@ class KokoroTTSSettings(TTSSettings): lang_code: Kokoro language code for synthesis. """ - lang_code: str = field(default_factory=lambda: NOT_GIVEN) + lang_code: str | _NotGiven = field(default_factory=lambda: NOT_GIVEN) class KokoroTTSService(TTSService): diff --git a/src/pipecat/services/lmnt/tts.py b/src/pipecat/services/lmnt/tts.py index 5b2adcaf4..94f4a1a9e 100644 --- a/src/pipecat/services/lmnt/tts.py +++ b/src/pipecat/services/lmnt/tts.py @@ -24,7 +24,7 @@ from pipecat.frames.frames import ( TTSStoppedFrame, ) from pipecat.processors.frame_processor import FrameDirection -from pipecat.services.settings import NOT_GIVEN, TTSSettings +from pipecat.services.settings import NOT_GIVEN, TTSSettings, _NotGiven from pipecat.services.tts_service import InterruptibleTTSService from pipecat.transcriptions.language import Language, resolve_language from pipecat.utils.tracing.service_decorators import traced_tts @@ -81,7 +81,7 @@ class LmntTTSSettings(TTSSettings): format: Audio output format. Defaults to "raw". """ - format: str = field(default_factory=lambda: NOT_GIVEN) + format: str | _NotGiven = field(default_factory=lambda: NOT_GIVEN) class LmntTTSService(InterruptibleTTSService): diff --git a/src/pipecat/services/minimax/tts.py b/src/pipecat/services/minimax/tts.py index 6a107d950..290439704 100644 --- a/src/pipecat/services/minimax/tts.py +++ b/src/pipecat/services/minimax/tts.py @@ -26,7 +26,7 @@ from pipecat.frames.frames import ( TTSStartedFrame, TTSStoppedFrame, ) -from pipecat.services.settings import NOT_GIVEN, TTSSettings, is_given +from pipecat.services.settings import NOT_GIVEN, TTSSettings, _NotGiven, is_given from pipecat.services.tts_service import TTSService from pipecat.transcriptions.language import Language, resolve_language from pipecat.utils.tracing.service_decorators import traced_tts @@ -107,18 +107,18 @@ class MiniMaxTTSSettings(TTSSettings): language_boost: Language boost string for multilingual support. """ - stream: bool = field(default_factory=lambda: NOT_GIVEN) - speed: float = field(default_factory=lambda: NOT_GIVEN) - volume: float = field(default_factory=lambda: NOT_GIVEN) - pitch: int = field(default_factory=lambda: NOT_GIVEN) - emotion: str = field(default_factory=lambda: NOT_GIVEN) - text_normalization: bool = field(default_factory=lambda: NOT_GIVEN) - latex_read: bool = field(default_factory=lambda: NOT_GIVEN) - audio_bitrate: int = field(default_factory=lambda: NOT_GIVEN) - audio_format: str = field(default_factory=lambda: NOT_GIVEN) - audio_channel: int = field(default_factory=lambda: NOT_GIVEN) - audio_sample_rate: int = field(default_factory=lambda: NOT_GIVEN) - language_boost: str = field(default_factory=lambda: NOT_GIVEN) + stream: bool | _NotGiven = field(default_factory=lambda: NOT_GIVEN) + speed: float | None | _NotGiven = field(default_factory=lambda: NOT_GIVEN) + volume: float | None | _NotGiven = field(default_factory=lambda: NOT_GIVEN) + pitch: int | None | _NotGiven = field(default_factory=lambda: NOT_GIVEN) + emotion: str | None | _NotGiven = field(default_factory=lambda: NOT_GIVEN) + text_normalization: bool | None | _NotGiven = field(default_factory=lambda: NOT_GIVEN) + latex_read: bool | None | _NotGiven = field(default_factory=lambda: NOT_GIVEN) + audio_bitrate: int | _NotGiven = field(default_factory=lambda: NOT_GIVEN) + audio_format: str | _NotGiven = field(default_factory=lambda: NOT_GIVEN) + audio_channel: int | _NotGiven = field(default_factory=lambda: NOT_GIVEN) + audio_sample_rate: int | _NotGiven = field(default_factory=lambda: NOT_GIVEN) + language_boost: str | None | _NotGiven = field(default_factory=lambda: NOT_GIVEN) _aliases: ClassVar[Dict[str, str]] = {"voice_id": "voice"} diff --git a/src/pipecat/services/neuphonic/tts.py b/src/pipecat/services/neuphonic/tts.py index 0797f9b1b..2e51297ab 100644 --- a/src/pipecat/services/neuphonic/tts.py +++ b/src/pipecat/services/neuphonic/tts.py @@ -35,7 +35,7 @@ from pipecat.frames.frames import ( TTSStoppedFrame, ) from pipecat.processors.frame_processor import FrameDirection -from pipecat.services.settings import NOT_GIVEN, TTSSettings +from pipecat.services.settings import NOT_GIVEN, TTSSettings, _NotGiven from pipecat.services.tts_service import InterruptibleTTSService, TTSService from pipecat.transcriptions.language import Language, resolve_language from pipecat.utils.tracing.service_decorators import traced_tts @@ -85,10 +85,10 @@ class NeuphonicTTSSettings(TTSSettings): sampling_rate: Audio sample rate. """ - lang_code: str = field(default_factory=lambda: NOT_GIVEN) - speed: float = field(default_factory=lambda: NOT_GIVEN) - encoding: str = field(default_factory=lambda: NOT_GIVEN) - sampling_rate: int = field(default_factory=lambda: NOT_GIVEN) + lang_code: str | _NotGiven = field(default_factory=lambda: NOT_GIVEN) + speed: float | _NotGiven = field(default_factory=lambda: NOT_GIVEN) + encoding: str | _NotGiven = field(default_factory=lambda: NOT_GIVEN) + sampling_rate: int | _NotGiven = field(default_factory=lambda: NOT_GIVEN) class NeuphonicTTSService(InterruptibleTTSService): diff --git a/src/pipecat/services/nvidia/stt.py b/src/pipecat/services/nvidia/stt.py index 8e1babec7..a79119c34 100644 --- a/src/pipecat/services/nvidia/stt.py +++ b/src/pipecat/services/nvidia/stt.py @@ -23,7 +23,7 @@ from pipecat.frames.frames import ( StartFrame, TranscriptionFrame, ) -from pipecat.services.settings import NOT_GIVEN, STTSettings +from pipecat.services.settings import NOT_GIVEN, STTSettings, _NotGiven from pipecat.services.stt_latency import NVIDIA_TTFS_P99 from pipecat.services.stt_service import SegmentedSTTService, STTService from pipecat.transcriptions.language import Language, resolve_language @@ -110,11 +110,11 @@ class NvidiaSegmentedSTTSettings(STTSettings): boosted_lm_score: Score boost for specified words. """ - profanity_filter: bool = field(default_factory=lambda: NOT_GIVEN) - automatic_punctuation: bool = field(default_factory=lambda: NOT_GIVEN) - verbatim_transcripts: bool = field(default_factory=lambda: NOT_GIVEN) - boosted_lm_words: Optional[List[str]] = field(default_factory=lambda: NOT_GIVEN) - boosted_lm_score: float = field(default_factory=lambda: NOT_GIVEN) + profanity_filter: bool | _NotGiven = field(default_factory=lambda: NOT_GIVEN) + automatic_punctuation: bool | _NotGiven = field(default_factory=lambda: NOT_GIVEN) + verbatim_transcripts: bool | _NotGiven = field(default_factory=lambda: NOT_GIVEN) + boosted_lm_words: List[str] | _NotGiven = field(default_factory=lambda: NOT_GIVEN) + boosted_lm_score: float | _NotGiven = field(default_factory=lambda: NOT_GIVEN) class NvidiaSTTService(STTService): diff --git a/src/pipecat/services/openai/base_llm.py b/src/pipecat/services/openai/base_llm.py index 13cbc07cb..5b624010f 100644 --- a/src/pipecat/services/openai/base_llm.py +++ b/src/pipecat/services/openai/base_llm.py @@ -43,7 +43,7 @@ from pipecat.processors.aggregators.openai_llm_context import ( from pipecat.processors.frame_processor import FrameDirection from pipecat.services.llm_service import FunctionCallFromLLM, LLMService from pipecat.services.settings import NOT_GIVEN as _NOT_GIVEN -from pipecat.services.settings import LLMSettings +from pipecat.services.settings import LLMSettings, _NotGiven from pipecat.utils.tracing.service_decorators import traced_llm @@ -56,8 +56,8 @@ class OpenAILLMSettings(LLMSettings): service_tier: Service tier to use (e.g., "auto", "flex", "priority"). """ - max_completion_tokens: Any = field(default_factory=lambda: _NOT_GIVEN) - service_tier: Any = field(default_factory=lambda: _NOT_GIVEN) + max_completion_tokens: int | _NotGiven = field(default_factory=lambda: _NOT_GIVEN) + service_tier: str | _NotGiven = field(default_factory=lambda: _NOT_GIVEN) class BaseOpenAILLMService(LLMService): diff --git a/src/pipecat/services/openai/stt.py b/src/pipecat/services/openai/stt.py index 6daefd1da..82ad8c0f0 100644 --- a/src/pipecat/services/openai/stt.py +++ b/src/pipecat/services/openai/stt.py @@ -35,7 +35,7 @@ from pipecat.frames.frames import ( VADUserStoppedSpeakingFrame, ) from pipecat.processors.frame_processor import FrameDirection -from pipecat.services.settings import NOT_GIVEN, STTSettings, is_given +from pipecat.services.settings import NOT_GIVEN, STTSettings, _NotGiven, is_given from pipecat.services.stt_latency import OPENAI_REALTIME_TTFS_P99, OPENAI_TTFS_P99 from pipecat.services.stt_service import WebsocketSTTService from pipecat.services.whisper.base_stt import BaseWhisperSTTService, Transcription @@ -133,7 +133,7 @@ class OpenAIRealtimeSTTSettings(STTSettings): prompt: Optional prompt text to guide transcription style. """ - prompt: Optional[str] = field(default_factory=lambda: NOT_GIVEN) + prompt: str | _NotGiven = field(default_factory=lambda: NOT_GIVEN) class OpenAIRealtimeSTTService(WebsocketSTTService): diff --git a/src/pipecat/services/openai/tts.py b/src/pipecat/services/openai/tts.py index f283a7912..2253e369a 100644 --- a/src/pipecat/services/openai/tts.py +++ b/src/pipecat/services/openai/tts.py @@ -25,7 +25,7 @@ from pipecat.frames.frames import ( TTSStartedFrame, TTSStoppedFrame, ) -from pipecat.services.settings import NOT_GIVEN, TTSSettings +from pipecat.services.settings import NOT_GIVEN, TTSSettings, _NotGiven from pipecat.services.tts_service import TTSService from pipecat.utils.tracing.service_decorators import traced_tts @@ -71,8 +71,8 @@ class OpenAITTSSettings(TTSSettings): speed: Voice speed control (0.25 to 4.0, default 1.0). """ - instructions: str = field(default_factory=lambda: NOT_GIVEN) - speed: float = field(default_factory=lambda: NOT_GIVEN) + instructions: str | _NotGiven = field(default_factory=lambda: NOT_GIVEN) + speed: float | _NotGiven = field(default_factory=lambda: NOT_GIVEN) class OpenAITTSService(TTSService): diff --git a/src/pipecat/services/openai_realtime_beta/openai.py b/src/pipecat/services/openai_realtime_beta/openai.py index b456ed0b8..ef40dcb15 100644 --- a/src/pipecat/services/openai_realtime_beta/openai.py +++ b/src/pipecat/services/openai_realtime_beta/openai.py @@ -11,7 +11,7 @@ import json import time import warnings from dataclasses import dataclass, field -from typing import Any, Optional +from typing import Optional from loguru import logger @@ -54,7 +54,7 @@ from pipecat.processors.aggregators.openai_llm_context import ( from pipecat.processors.frame_processor import FrameDirection from pipecat.services.llm_service import FunctionCallFromLLM, LLMService from pipecat.services.openai.llm import OpenAIContextAggregatorPair -from pipecat.services.settings import NOT_GIVEN, LLMSettings +from pipecat.services.settings import NOT_GIVEN, LLMSettings, _NotGiven from pipecat.transcriptions.language import Language from pipecat.utils.time import time_now_iso8601 from pipecat.utils.tracing.service_decorators import traced_openai_realtime, traced_stt @@ -100,7 +100,9 @@ class OpenAIRealtimeBetaLLMSettings(LLMSettings): session_properties: OpenAI Realtime session configuration. """ - session_properties: Any = field(default_factory=lambda: NOT_GIVEN) + session_properties: events.SessionProperties | _NotGiven = field( + default_factory=lambda: NOT_GIVEN + ) class OpenAIRealtimeBetaLLMService(LLMService): diff --git a/src/pipecat/services/playht/tts.py b/src/pipecat/services/playht/tts.py index 1965c9ea3..b5c683fbe 100644 --- a/src/pipecat/services/playht/tts.py +++ b/src/pipecat/services/playht/tts.py @@ -33,7 +33,7 @@ from pipecat.frames.frames import ( TTSStoppedFrame, ) from pipecat.processors.frame_processor import FrameDirection -from pipecat.services.settings import NOT_GIVEN, TTSSettings, is_given +from pipecat.services.settings import NOT_GIVEN, TTSSettings, _NotGiven, is_given from pipecat.services.tts_service import InterruptibleTTSService, TTSService from pipecat.transcriptions.language import Language, resolve_language from pipecat.utils.tracing.service_decorators import traced_tts @@ -111,11 +111,11 @@ class PlayHTTTSSettings(TTSSettings): playht_sample_rate: Audio sample rate sent to the API. """ - output_format: str = field(default_factory=lambda: NOT_GIVEN) - voice_engine: str = field(default_factory=lambda: NOT_GIVEN) - speed: float = field(default_factory=lambda: NOT_GIVEN) - seed: int = field(default_factory=lambda: NOT_GIVEN) - playht_sample_rate: int = field(default_factory=lambda: NOT_GIVEN) + output_format: str | _NotGiven = field(default_factory=lambda: NOT_GIVEN) + voice_engine: str | _NotGiven = field(default_factory=lambda: NOT_GIVEN) + speed: float | None | _NotGiven = field(default_factory=lambda: NOT_GIVEN) + seed: int | None | _NotGiven = field(default_factory=lambda: NOT_GIVEN) + playht_sample_rate: int | _NotGiven = field(default_factory=lambda: NOT_GIVEN) class PlayHTTTSService(InterruptibleTTSService): diff --git a/src/pipecat/services/resembleai/tts.py b/src/pipecat/services/resembleai/tts.py index acba883e4..f2873a8a1 100644 --- a/src/pipecat/services/resembleai/tts.py +++ b/src/pipecat/services/resembleai/tts.py @@ -25,7 +25,7 @@ from pipecat.frames.frames import ( TTSStoppedFrame, ) from pipecat.processors.frame_processor import FrameDirection -from pipecat.services.settings import NOT_GIVEN, TTSSettings +from pipecat.services.settings import NOT_GIVEN, TTSSettings, _NotGiven from pipecat.services.tts_service import AudioContextWordTTSService from pipecat.transcriptions.language import Language from pipecat.utils.text.base_text_aggregator import BaseTextAggregator @@ -50,9 +50,9 @@ class ResembleAITTSSettings(TTSSettings): resemble_sample_rate: Audio sample rate sent to the API. """ - precision: str = field(default_factory=lambda: NOT_GIVEN) - output_format: str = field(default_factory=lambda: NOT_GIVEN) - resemble_sample_rate: int = field(default_factory=lambda: NOT_GIVEN) + precision: str | None | _NotGiven = field(default_factory=lambda: NOT_GIVEN) + output_format: str | None | _NotGiven = field(default_factory=lambda: NOT_GIVEN) + resemble_sample_rate: int | None | _NotGiven = field(default_factory=lambda: NOT_GIVEN) _aliases: ClassVar[Dict[str, str]] = { "voice_id": "voice", diff --git a/src/pipecat/services/rime/tts.py b/src/pipecat/services/rime/tts.py index d76eafbfa..87596cefd 100644 --- a/src/pipecat/services/rime/tts.py +++ b/src/pipecat/services/rime/tts.py @@ -31,7 +31,7 @@ from pipecat.frames.frames import ( TTSStoppedFrame, ) from pipecat.processors.frame_processor import FrameDirection -from pipecat.services.settings import NOT_GIVEN, TTSSettings, is_given +from pipecat.services.settings import NOT_GIVEN, TTSSettings, _NotGiven, is_given from pipecat.services.tts_service import ( AudioContextWordTTSService, InterruptibleTTSService, @@ -86,15 +86,15 @@ class RimeTTSSettings(TTSSettings): inlineSpeedAlpha: Inline speed control markup. """ - modelId: str = field(default_factory=lambda: NOT_GIVEN) - audioFormat: str = field(default_factory=lambda: NOT_GIVEN) - samplingRate: int = field(default_factory=lambda: NOT_GIVEN) - lang: str = field(default_factory=lambda: NOT_GIVEN) - speedAlpha: float = field(default_factory=lambda: NOT_GIVEN) - reduceLatency: bool = field(default_factory=lambda: NOT_GIVEN) - pauseBetweenBrackets: bool = field(default_factory=lambda: NOT_GIVEN) - phonemizeBetweenBrackets: bool = field(default_factory=lambda: NOT_GIVEN) - inlineSpeedAlpha: str = field(default_factory=lambda: NOT_GIVEN) + modelId: str | _NotGiven = field(default_factory=lambda: NOT_GIVEN) + audioFormat: str | _NotGiven = field(default_factory=lambda: NOT_GIVEN) + samplingRate: int | _NotGiven = field(default_factory=lambda: NOT_GIVEN) + lang: str | _NotGiven = field(default_factory=lambda: NOT_GIVEN) + speedAlpha: float | None | _NotGiven = field(default_factory=lambda: NOT_GIVEN) + reduceLatency: bool | None | _NotGiven = field(default_factory=lambda: NOT_GIVEN) + pauseBetweenBrackets: bool | None | _NotGiven = field(default_factory=lambda: NOT_GIVEN) + phonemizeBetweenBrackets: bool | None | _NotGiven = field(default_factory=lambda: NOT_GIVEN) + inlineSpeedAlpha: str | None | _NotGiven = field(default_factory=lambda: NOT_GIVEN) _aliases: ClassVar[Dict[str, str]] = {"speaker": "voice"} @@ -114,14 +114,14 @@ class RimeNonJsonTTSSettings(TTSSettings): top_p: Cumulative probability threshold (0.0-1.0). """ - modelId: str = field(default_factory=lambda: NOT_GIVEN) - audioFormat: str = field(default_factory=lambda: NOT_GIVEN) - samplingRate: int = field(default_factory=lambda: NOT_GIVEN) - lang: str = field(default_factory=lambda: NOT_GIVEN) - segment: str = field(default_factory=lambda: NOT_GIVEN) - repetition_penalty: float = field(default_factory=lambda: NOT_GIVEN) - temperature: float = field(default_factory=lambda: NOT_GIVEN) - top_p: float = field(default_factory=lambda: NOT_GIVEN) + modelId: str | _NotGiven = field(default_factory=lambda: NOT_GIVEN) + audioFormat: str | _NotGiven = field(default_factory=lambda: NOT_GIVEN) + samplingRate: int | _NotGiven = field(default_factory=lambda: NOT_GIVEN) + lang: str | _NotGiven = field(default_factory=lambda: NOT_GIVEN) + segment: str | None | _NotGiven = field(default_factory=lambda: NOT_GIVEN) + repetition_penalty: float | None | _NotGiven = field(default_factory=lambda: NOT_GIVEN) + temperature: float | None | _NotGiven = field(default_factory=lambda: NOT_GIVEN) + top_p: float | None | _NotGiven = field(default_factory=lambda: NOT_GIVEN) _aliases: ClassVar[Dict[str, str]] = {"speaker": "voice"} diff --git a/src/pipecat/services/sarvam/stt.py b/src/pipecat/services/sarvam/stt.py index 80e6d6ca2..aa6baef14 100644 --- a/src/pipecat/services/sarvam/stt.py +++ b/src/pipecat/services/sarvam/stt.py @@ -32,7 +32,7 @@ from pipecat.frames.frames import ( ) from pipecat.processors.frame_processor import FrameDirection from pipecat.services.sarvam._sdk import sdk_headers -from pipecat.services.settings import NOT_GIVEN, STTSettings, is_given +from pipecat.services.settings import NOT_GIVEN, STTSettings, _NotGiven, is_given from pipecat.services.stt_latency import SARVAM_TTFS_P99 from pipecat.services.stt_service import STTService from pipecat.transcriptions.language import Language, resolve_language @@ -142,10 +142,10 @@ class SarvamSTTSettings(STTSettings): high_vad_sensitivity: Enable high VAD sensitivity. """ - prompt: Optional[str] = field(default_factory=lambda: NOT_GIVEN) - mode: Optional[str] = field(default_factory=lambda: NOT_GIVEN) - vad_signals: Optional[bool] = field(default_factory=lambda: NOT_GIVEN) - high_vad_sensitivity: Optional[bool] = field(default_factory=lambda: NOT_GIVEN) + prompt: str | None | _NotGiven = field(default_factory=lambda: NOT_GIVEN) + mode: str | None | _NotGiven = field(default_factory=lambda: NOT_GIVEN) + vad_signals: bool | None | _NotGiven = field(default_factory=lambda: NOT_GIVEN) + high_vad_sensitivity: bool | None | _NotGiven = field(default_factory=lambda: NOT_GIVEN) class SarvamSTTService(STTService): diff --git a/src/pipecat/services/sarvam/tts.py b/src/pipecat/services/sarvam/tts.py index aff96f1dd..332643fc9 100644 --- a/src/pipecat/services/sarvam/tts.py +++ b/src/pipecat/services/sarvam/tts.py @@ -62,7 +62,7 @@ from pipecat.frames.frames import ( ) from pipecat.processors.frame_processor import FrameDirection from pipecat.services.sarvam._sdk import sdk_headers -from pipecat.services.settings import NOT_GIVEN, TTSSettings, is_given +from pipecat.services.settings import NOT_GIVEN, TTSSettings, _NotGiven, is_given from pipecat.services.tts_service import InterruptibleTTSService, TTSService from pipecat.transcriptions.language import Language, resolve_language from pipecat.utils.tracing.service_decorators import traced_tts @@ -266,13 +266,13 @@ class SarvamHttpTTSSettings(TTSSettings): sample_rate: Audio sample rate. """ - language: str = field(default_factory=lambda: NOT_GIVEN) - enable_preprocessing: bool = field(default_factory=lambda: NOT_GIVEN) - pace: float = field(default_factory=lambda: NOT_GIVEN) - pitch: float = field(default_factory=lambda: NOT_GIVEN) - loudness: float = field(default_factory=lambda: NOT_GIVEN) - temperature: float = field(default_factory=lambda: NOT_GIVEN) - sarvam_sample_rate: int = field(default_factory=lambda: NOT_GIVEN) + language: str | None | _NotGiven = field(default_factory=lambda: NOT_GIVEN) + enable_preprocessing: bool | None | _NotGiven = field(default_factory=lambda: NOT_GIVEN) + pace: float | None | _NotGiven = field(default_factory=lambda: NOT_GIVEN) + pitch: float | None | _NotGiven = field(default_factory=lambda: NOT_GIVEN) + loudness: float | None | _NotGiven = field(default_factory=lambda: NOT_GIVEN) + temperature: float | None | _NotGiven = field(default_factory=lambda: NOT_GIVEN) + sarvam_sample_rate: int | _NotGiven = field(default_factory=lambda: NOT_GIVEN) @dataclass @@ -305,18 +305,18 @@ class SarvamTTSSettings(TTSSettings): **Note:** Only supported for bulbul:v3-beta. Ignored for v2. """ - target_language_code: str = field(default_factory=lambda: NOT_GIVEN) - speaker: str = field(default_factory=lambda: NOT_GIVEN) - speech_sample_rate: str = field(default_factory=lambda: NOT_GIVEN) - enable_preprocessing: bool = field(default_factory=lambda: NOT_GIVEN) - min_buffer_size: int = field(default_factory=lambda: NOT_GIVEN) - max_chunk_length: int = field(default_factory=lambda: NOT_GIVEN) - output_audio_codec: str = field(default_factory=lambda: NOT_GIVEN) - output_audio_bitrate: str = field(default_factory=lambda: NOT_GIVEN) - pace: float = field(default_factory=lambda: NOT_GIVEN) - pitch: float = field(default_factory=lambda: NOT_GIVEN) - loudness: float = field(default_factory=lambda: NOT_GIVEN) - temperature: float = field(default_factory=lambda: NOT_GIVEN) + target_language_code: str | None | _NotGiven = field(default_factory=lambda: NOT_GIVEN) + speaker: str | _NotGiven = field(default_factory=lambda: NOT_GIVEN) + speech_sample_rate: str | _NotGiven = field(default_factory=lambda: NOT_GIVEN) + enable_preprocessing: bool | None | _NotGiven = field(default_factory=lambda: NOT_GIVEN) + min_buffer_size: int | None | _NotGiven = field(default_factory=lambda: NOT_GIVEN) + max_chunk_length: int | None | _NotGiven = field(default_factory=lambda: NOT_GIVEN) + output_audio_codec: str | None | _NotGiven = field(default_factory=lambda: NOT_GIVEN) + output_audio_bitrate: str | None | _NotGiven = field(default_factory=lambda: NOT_GIVEN) + pace: float | None | _NotGiven = field(default_factory=lambda: NOT_GIVEN) + pitch: float | None | _NotGiven = field(default_factory=lambda: NOT_GIVEN) + loudness: float | None | _NotGiven = field(default_factory=lambda: NOT_GIVEN) + temperature: float | None | _NotGiven = field(default_factory=lambda: NOT_GIVEN) class SarvamHttpTTSService(TTSService): diff --git a/src/pipecat/services/soniox/stt.py b/src/pipecat/services/soniox/stt.py index 5c4b49cbe..1f34c061c 100644 --- a/src/pipecat/services/soniox/stt.py +++ b/src/pipecat/services/soniox/stt.py @@ -24,7 +24,7 @@ from pipecat.frames.frames import ( VADUserStoppedSpeakingFrame, ) from pipecat.processors.frame_processor import FrameDirection -from pipecat.services.settings import NOT_GIVEN, STTSettings, is_given +from pipecat.services.settings import NOT_GIVEN, STTSettings, _NotGiven, is_given from pipecat.services.stt_latency import SONIOX_TTFS_P99 from pipecat.services.stt_service import WebsocketSTTService from pipecat.transcriptions.language import Language @@ -144,7 +144,7 @@ class SonioxSTTSettings(STTSettings): input_params: Soniox ``SonioxInputParams`` for detailed configuration. """ - input_params: SonioxInputParams = field(default_factory=lambda: NOT_GIVEN) + input_params: SonioxInputParams | _NotGiven = field(default_factory=lambda: NOT_GIVEN) class SonioxSTTService(WebsocketSTTService): diff --git a/src/pipecat/services/speechmatics/stt.py b/src/pipecat/services/speechmatics/stt.py index 166e19d97..2e23765b2 100644 --- a/src/pipecat/services/speechmatics/stt.py +++ b/src/pipecat/services/speechmatics/stt.py @@ -33,7 +33,7 @@ from pipecat.frames.frames import ( VADUserStoppedSpeakingFrame, ) from pipecat.processors.frame_processor import FrameDirection -from pipecat.services.settings import NOT_GIVEN, STTSettings, is_given +from pipecat.services.settings import NOT_GIVEN, STTSettings, _NotGiven, is_given from pipecat.services.stt_latency import SPEECHMATICS_TTFS_P99 from pipecat.services.stt_service import STTService from pipecat.transcriptions.language import Language, resolve_language @@ -115,28 +115,30 @@ class SpeechmaticsSTTSettings(STTSettings): extra_params: Extra parameters for the STT engine. """ - domain: str = field(default_factory=lambda: NOT_GIVEN) - turn_detection_mode: TurnDetectionMode = field(default_factory=lambda: NOT_GIVEN) - speaker_active_format: str = field(default_factory=lambda: NOT_GIVEN) - speaker_passive_format: str = field(default_factory=lambda: NOT_GIVEN) - focus_speakers: list = field(default_factory=lambda: NOT_GIVEN) - ignore_speakers: list = field(default_factory=lambda: NOT_GIVEN) - focus_mode: Any = field(default_factory=lambda: NOT_GIVEN) - known_speakers: list = field(default_factory=lambda: NOT_GIVEN) - additional_vocab: list = field(default_factory=lambda: NOT_GIVEN) - audio_encoding: Any = field(default_factory=lambda: NOT_GIVEN) - operating_point: Any = field(default_factory=lambda: NOT_GIVEN) - max_delay: float = field(default_factory=lambda: NOT_GIVEN) - end_of_utterance_silence_trigger: float = field(default_factory=lambda: NOT_GIVEN) - end_of_utterance_max_delay: float = field(default_factory=lambda: NOT_GIVEN) - punctuation_overrides: dict = field(default_factory=lambda: NOT_GIVEN) - include_partials: bool = field(default_factory=lambda: NOT_GIVEN) - split_sentences: bool = field(default_factory=lambda: NOT_GIVEN) - enable_diarization: bool = field(default_factory=lambda: NOT_GIVEN) - speaker_sensitivity: float = field(default_factory=lambda: NOT_GIVEN) - max_speakers: int = field(default_factory=lambda: NOT_GIVEN) - prefer_current_speaker: bool = field(default_factory=lambda: NOT_GIVEN) - extra_params: dict = field(default_factory=lambda: NOT_GIVEN) + domain: str | _NotGiven = field(default_factory=lambda: NOT_GIVEN) + turn_detection_mode: TurnDetectionMode | _NotGiven = field(default_factory=lambda: NOT_GIVEN) + speaker_active_format: str | _NotGiven = field(default_factory=lambda: NOT_GIVEN) + speaker_passive_format: str | _NotGiven = field(default_factory=lambda: NOT_GIVEN) + focus_speakers: list[str] | _NotGiven = field(default_factory=lambda: NOT_GIVEN) + ignore_speakers: list[str] | _NotGiven = field(default_factory=lambda: NOT_GIVEN) + focus_mode: SpeakerFocusMode | _NotGiven = field(default_factory=lambda: NOT_GIVEN) + known_speakers: list[SpeakerIdentifier] | _NotGiven = field(default_factory=lambda: NOT_GIVEN) + additional_vocab: list[AdditionalVocabEntry] | _NotGiven = field( + default_factory=lambda: NOT_GIVEN + ) + audio_encoding: AudioEncoding | _NotGiven = field(default_factory=lambda: NOT_GIVEN) + operating_point: OperatingPoint | _NotGiven = field(default_factory=lambda: NOT_GIVEN) + max_delay: float | _NotGiven = field(default_factory=lambda: NOT_GIVEN) + end_of_utterance_silence_trigger: float | _NotGiven = field(default_factory=lambda: NOT_GIVEN) + end_of_utterance_max_delay: float | _NotGiven = field(default_factory=lambda: NOT_GIVEN) + punctuation_overrides: dict[str, Any] | _NotGiven = field(default_factory=lambda: NOT_GIVEN) + include_partials: bool | _NotGiven = field(default_factory=lambda: NOT_GIVEN) + split_sentences: bool | _NotGiven = field(default_factory=lambda: NOT_GIVEN) + enable_diarization: bool | _NotGiven = field(default_factory=lambda: NOT_GIVEN) + speaker_sensitivity: float | _NotGiven = field(default_factory=lambda: NOT_GIVEN) + max_speakers: int | _NotGiven = field(default_factory=lambda: NOT_GIVEN) + prefer_current_speaker: bool | _NotGiven = field(default_factory=lambda: NOT_GIVEN) + extra_params: dict[str, Any] | _NotGiven = field(default_factory=lambda: NOT_GIVEN) #: Fields that can be updated on a live connection via the Speechmatics #: diarization-config API — no reconnect needed. diff --git a/src/pipecat/services/ultravox/llm.py b/src/pipecat/services/ultravox/llm.py index ef8baacb4..436653c7e 100644 --- a/src/pipecat/services/ultravox/llm.py +++ b/src/pipecat/services/ultravox/llm.py @@ -56,7 +56,7 @@ from pipecat.processors.aggregators.openai_llm_context import ( ) from pipecat.processors.frame_processor import FrameDirection from pipecat.services.llm_service import FunctionCallFromLLM, LLMService -from pipecat.services.settings import NOT_GIVEN, LLMSettings +from pipecat.services.settings import NOT_GIVEN, LLMSettings, _NotGiven from pipecat.utils.time import time_now_iso8601 try: @@ -75,7 +75,7 @@ class UltravoxRealtimeLLMSettings(LLMSettings): output_medium: The output medium for the model ("voice" or "text"). """ - output_medium: str = field(default=NOT_GIVEN) + output_medium: str | _NotGiven = field(default=NOT_GIVEN) class AgentInputParams(BaseModel): diff --git a/src/pipecat/services/whisper/base_stt.py b/src/pipecat/services/whisper/base_stt.py index d50c24eb2..74ca2d102 100644 --- a/src/pipecat/services/whisper/base_stt.py +++ b/src/pipecat/services/whisper/base_stt.py @@ -18,7 +18,7 @@ from openai import AsyncOpenAI from openai.types.audio import Transcription from pipecat.frames.frames import ErrorFrame, Frame, TranscriptionFrame -from pipecat.services.settings import NOT_GIVEN, STTSettings +from pipecat.services.settings import NOT_GIVEN, STTSettings, _NotGiven from pipecat.services.stt_latency import WHISPER_TTFS_P99 from pipecat.services.stt_service import SegmentedSTTService from pipecat.transcriptions.language import Language, resolve_language @@ -37,9 +37,9 @@ class BaseWhisperSTTSettings(STTSettings): temperature: Sampling temperature between 0 and 1. """ - base_url: Optional[str] = field(default_factory=lambda: NOT_GIVEN) - prompt: Optional[str] = field(default_factory=lambda: NOT_GIVEN) - temperature: Optional[float] = field(default_factory=lambda: NOT_GIVEN) + base_url: str | _NotGiven = field(default_factory=lambda: NOT_GIVEN) + prompt: str | _NotGiven = field(default_factory=lambda: NOT_GIVEN) + temperature: float | _NotGiven = field(default_factory=lambda: NOT_GIVEN) def language_to_whisper_language(language: Language) -> Optional[str]: diff --git a/src/pipecat/services/whisper/stt.py b/src/pipecat/services/whisper/stt.py index d4efcb166..033d815d9 100644 --- a/src/pipecat/services/whisper/stt.py +++ b/src/pipecat/services/whisper/stt.py @@ -20,7 +20,7 @@ from loguru import logger from typing_extensions import TYPE_CHECKING, override from pipecat.frames.frames import ErrorFrame, Frame, TranscriptionFrame -from pipecat.services.settings import NOT_GIVEN, STTSettings +from pipecat.services.settings import NOT_GIVEN, STTSettings, _NotGiven from pipecat.services.stt_service import SegmentedSTTService from pipecat.transcriptions.language import Language, resolve_language from pipecat.utils.time import time_now_iso8601 @@ -184,9 +184,9 @@ class WhisperSTTSettings(STTSettings): no_speech_prob: Probability threshold for filtering non-speech segments. """ - device: str = field(default_factory=lambda: NOT_GIVEN) - compute_type: str = field(default_factory=lambda: NOT_GIVEN) - no_speech_prob: float = field(default_factory=lambda: NOT_GIVEN) + device: str | _NotGiven = field(default_factory=lambda: NOT_GIVEN) + compute_type: str | _NotGiven = field(default_factory=lambda: NOT_GIVEN) + no_speech_prob: float | _NotGiven = field(default_factory=lambda: NOT_GIVEN) @dataclass @@ -199,9 +199,9 @@ class WhisperMLXSTTSettings(STTSettings): engine: Whisper engine identifier. """ - no_speech_prob: float = field(default_factory=lambda: NOT_GIVEN) - temperature: float = field(default_factory=lambda: NOT_GIVEN) - engine: str = field(default_factory=lambda: NOT_GIVEN) + no_speech_prob: float | _NotGiven = field(default_factory=lambda: NOT_GIVEN) + temperature: float | _NotGiven = field(default_factory=lambda: NOT_GIVEN) + engine: str | _NotGiven = field(default_factory=lambda: NOT_GIVEN) class WhisperSTTService(SegmentedSTTService): diff --git a/src/pipecat/services/xtts/tts.py b/src/pipecat/services/xtts/tts.py index 3ba332138..65aa25e36 100644 --- a/src/pipecat/services/xtts/tts.py +++ b/src/pipecat/services/xtts/tts.py @@ -25,7 +25,7 @@ from pipecat.frames.frames import ( TTSStartedFrame, TTSStoppedFrame, ) -from pipecat.services.settings import NOT_GIVEN, TTSSettings +from pipecat.services.settings import NOT_GIVEN, TTSSettings, _NotGiven from pipecat.services.tts_service import TTSService from pipecat.transcriptions.language import Language, resolve_language from pipecat.utils.tracing.service_decorators import traced_tts @@ -78,7 +78,7 @@ class XTTSTTSSettings(TTSSettings): base_url: Base URL of the XTTS streaming server. """ - base_url: str = field(default_factory=lambda: NOT_GIVEN) + base_url: str | _NotGiven = field(default_factory=lambda: NOT_GIVEN) class XTTSService(TTSService): From 200716e8fecb1a3265f59680244d7bf35d8cada6 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Aleix=20Conchillo=20Flaqu=C3=A9?= Date: Wed, 11 Feb 2026 11:41:31 -0800 Subject: [PATCH 0549/1060] Add SIP transfer and SIP REFER frames to Daily transport Add write_transport_frame() hook to BaseOutputTransport so subclasses can handle custom frame types that flow through the audio queue. Add DailySIPTransferFrame and DailySIPReferFrame as DataFrame subclasses that queue with audio, ensuring SIP operations execute only after the bot finishes its current utterance. Override write_transport_frame in DailyOutputTransport to dispatch these frames to the existing sip_call_transfer() and sip_refer() client methods. Also switch DailyOutputTransport.send_message error handling from logger.error to push_error for consistency. --- src/pipecat/transports/base_output.py | 14 +++++++ src/pipecat/transports/daily/transport.py | 50 ++++++++++++++++++++++- 2 files changed, 62 insertions(+), 2 deletions(-) diff --git a/src/pipecat/transports/base_output.py b/src/pipecat/transports/base_output.py index c4f59a61d..6fe31aab5 100644 --- a/src/pipecat/transports/base_output.py +++ b/src/pipecat/transports/base_output.py @@ -237,6 +237,18 @@ class BaseOutputTransport(FrameProcessor): else: await self._write_dtmf_audio(frame) + async def write_transport_frame(self, frame: Frame): + """Handle a queued frame after preceding audio has been sent. + + Override in transport subclasses to handle custom frame types that + flow through the audio queue. Called by the media sender after the + frame has waited for any preceding audio to finish. + + Args: + frame: The frame to handle. + """ + pass + def _supports_native_dtmf(self) -> bool: """Override in transport implementations that support native DTMF. @@ -681,6 +693,8 @@ class BaseOutputTransport(FrameProcessor): await self._transport.send_message(frame) elif isinstance(frame, OutputDTMFFrame): await self._transport.write_dtmf(frame) + else: + await self._transport.write_transport_frame(frame) def _next_frame(self) -> AsyncGenerator[Frame, None]: """Generate the next frame for audio processing. diff --git a/src/pipecat/transports/daily/transport.py b/src/pipecat/transports/daily/transport.py index e3b246253..fd3f4e30b 100644 --- a/src/pipecat/transports/daily/transport.py +++ b/src/pipecat/transports/daily/transport.py @@ -15,7 +15,7 @@ import asyncio import time from concurrent.futures import CancelledError as FuturesCancelledError from concurrent.futures import ThreadPoolExecutor -from dataclasses import dataclass +from dataclasses import dataclass, field from typing import Any, Awaitable, Callable, Dict, Mapping, Optional, Tuple import aiohttp @@ -26,6 +26,7 @@ from pipecat.audio.vad.vad_analyzer import VADAnalyzer, VADParams from pipecat.frames.frames import ( CancelFrame, ControlFrame, + DataFrame, EndFrame, Frame, InputAudioRawFrame, @@ -182,6 +183,36 @@ class DailyInputTransportMessageUrgentFrame(DailyInputTransportMessageFrame): ) +@dataclass +class DailySIPTransferFrame(DataFrame): + """SIP call transfer frame for transport queuing. + + A SIP call transfer that will be queued. The transfer will happen after any + preceding audio finishes playing, allowing the bot to complete its current + utterance before the transfer occurs. + + Parameters: + settings: SIP call transfer settings. + """ + + settings: Mapping[str, Any] = field(default_factory=dict) + + +@dataclass +class DailySIPReferFrame(DataFrame): + """SIP REFER frame for transport queuing. + + A SIP REFER that will be queued. The REFER will happen after any preceding + audio finishes playing, allowing the bot to complete its current utterance + before the REFER occurs. + + Parameters: + settings: SIP REFER settings. + """ + + settings: Mapping[str, Any] = field(default_factory=dict) + + @dataclass class DailyUpdateRemoteParticipantsFrame(ControlFrame): """Frame to update remote participants in Daily calls. @@ -1968,7 +1999,7 @@ class DailyOutputTransport(BaseOutputTransport): """ error = await self._client.send_message(frame) if error: - logger.error(f"Unable to send message: {error}") + await self.push_error(f"{self}: Unable to send message: {error}") async def register_video_destination(self, destination: str): """Register a video output destination. @@ -2011,6 +2042,21 @@ class DailyOutputTransport(BaseOutputTransport): """ return await self._client.write_video_frame(frame) + async def write_transport_frame(self, frame: Frame): + """Handle queued SIP frames after preceding audio has been sent. + + Args: + frame: The frame to handle. + """ + if isinstance(frame, DailySIPTransferFrame): + error = await self._client.sip_call_transfer(frame.settings) + if error: + await self.push_error(f"{self}: Unable to transfer SIP call: {error}") + elif isinstance(frame, DailySIPReferFrame): + error = await self._client.sip_refer(frame.settings) + if error: + await self.push_error(f"{self}: Unable to perform SIP REFER: {error}") + def _supports_native_dtmf(self) -> bool: """Daily supports native DTMF via telephone events. From 7501ba2e45f2c4d9521b621ef5390c7819da5e7a Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Aleix=20Conchillo=20Flaqu=C3=A9?= Date: Wed, 11 Feb 2026 11:58:14 -0800 Subject: [PATCH 0550/1060] Undeprecate DailyUpdateRemoteParticipantsFrame Remove the deprecation warning and __post_init__ override. Also fix the default value for remote_participants to use field(default_factory=dict) instead of None. --- changelog/3719.changed.md | 1 + src/pipecat/transports/daily/transport.py | 47 +++++------------------ 2 files changed, 10 insertions(+), 38 deletions(-) create mode 100644 changelog/3719.changed.md diff --git a/changelog/3719.changed.md b/changelog/3719.changed.md new file mode 100644 index 000000000..f42d0303b --- /dev/null +++ b/changelog/3719.changed.md @@ -0,0 +1 @@ +- `DailyUpdateRemoteParticipantsFrame` is no longer deprecated and is now queued with audio like other transport frames. diff --git a/src/pipecat/transports/daily/transport.py b/src/pipecat/transports/daily/transport.py index fd3f4e30b..5df7bcffd 100644 --- a/src/pipecat/transports/daily/transport.py +++ b/src/pipecat/transports/daily/transport.py @@ -25,7 +25,6 @@ from pydantic import BaseModel from pipecat.audio.vad.vad_analyzer import VADAnalyzer, VADParams from pipecat.frames.frames import ( CancelFrame, - ControlFrame, DataFrame, EndFrame, Frame, @@ -214,34 +213,14 @@ class DailySIPReferFrame(DataFrame): @dataclass -class DailyUpdateRemoteParticipantsFrame(ControlFrame): +class DailyUpdateRemoteParticipantsFrame(DataFrame): """Frame to update remote participants in Daily calls. - .. deprecated:: 0.0.87 - `DailyUpdateRemoteParticipantsFrame` is deprecated and will be removed in a future version. - Create your own custom frame and use a custom processor to handle it or use, for example, - `on_after_push_frame` event instead in the output transport. - Parameters: remote_participants: See https://reference-python.daily.co/api_reference.html#daily.CallClient.update_remote_participants. """ - remote_participants: Mapping[str, Any] = None - - def __post_init__(self): - super().__post_init__() - import warnings - - with warnings.catch_warnings(): - warnings.simplefilter("always") - warnings.warn( - "DailyUpdateRemoteParticipantsFrame is deprecated and will be removed in a future version." - "Instead, create your own custom frame and handle it in the " - '`@transport.output().event_handler("on_after_push_frame")` event handler or a ' - "custom processor.", - DeprecationWarning, - stacklevel=2, - ) + remote_participants: Mapping[str, Any] = field(default_factory=dict) class WebRTCVADAnalyzer(VADAnalyzer): @@ -1977,18 +1956,6 @@ class DailyOutputTransport(BaseOutputTransport): # Leave the room. await self._client.leave() - async def process_frame(self, frame: Frame, direction: FrameDirection): - """Process outgoing frames, including transport messages. - - Args: - frame: The frame to process. - direction: The direction of frame flow in the pipeline. - """ - await super().process_frame(frame, direction) - - if isinstance(frame, DailyUpdateRemoteParticipantsFrame): - await self._client.update_remote_participants(frame.remote_participants) - async def send_message( self, frame: OutputTransportMessageFrame | OutputTransportMessageUrgentFrame ): @@ -1999,7 +1966,7 @@ class DailyOutputTransport(BaseOutputTransport): """ error = await self._client.send_message(frame) if error: - await self.push_error(f"{self}: Unable to send message: {error}") + await self.push_error(f"Unable to send message: {error}") async def register_video_destination(self, destination: str): """Register a video output destination. @@ -2051,11 +2018,15 @@ class DailyOutputTransport(BaseOutputTransport): if isinstance(frame, DailySIPTransferFrame): error = await self._client.sip_call_transfer(frame.settings) if error: - await self.push_error(f"{self}: Unable to transfer SIP call: {error}") + await self.push_error(f"Unable to transfer SIP call: {error}") elif isinstance(frame, DailySIPReferFrame): error = await self._client.sip_refer(frame.settings) if error: - await self.push_error(f"{self}: Unable to perform SIP REFER: {error}") + await self.push_error(f"Unable to perform SIP REFER: {error}") + elif isinstance(frame, DailyUpdateRemoteParticipantsFrame): + error = await self._client.update_remote_participants(frame.remote_participants) + if error: + await self.push_error(f"Unable to update remote participants: {error}") def _supports_native_dtmf(self) -> bool: """Daily supports native DTMF via telephone events. From baa61468a1848e4023b027b7fbbd277466a7876e Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Aleix=20Conchillo=20Flaqu=C3=A9?= Date: Wed, 11 Feb 2026 12:09:12 -0800 Subject: [PATCH 0551/1060] Add changelog entries for PR #3719 --- changelog/3719.added.2.md | 1 + changelog/3719.added.md | 1 + 2 files changed, 2 insertions(+) create mode 100644 changelog/3719.added.2.md create mode 100644 changelog/3719.added.md diff --git a/changelog/3719.added.2.md b/changelog/3719.added.2.md new file mode 100644 index 000000000..77d8956d7 --- /dev/null +++ b/changelog/3719.added.2.md @@ -0,0 +1 @@ +- Added `write_transport_frame()` hook to `BaseOutputTransport` allowing transport subclasses to handle custom frame types that flow through the audio queue. diff --git a/changelog/3719.added.md b/changelog/3719.added.md new file mode 100644 index 000000000..bc1c2d6b1 --- /dev/null +++ b/changelog/3719.added.md @@ -0,0 +1 @@ +- Added `DailySIPTransferFrame` and `DailySIPReferFrame` to the Daily transport. These frames queue SIP transfer and SIP REFER operations with audio, so the operation executes only after the bot finishes its current utterance. From 352361bdd2d6abfb85b875883603f2152f3411b4 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Aleix=20Conchillo=20Flaqu=C3=A9?= Date: Wed, 11 Feb 2026 12:09:07 -0800 Subject: [PATCH 0552/1060] Update changelog skill to avoid line wrapping --- .claude/skills/changelog/SKILL.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/.claude/skills/changelog/SKILL.md b/.claude/skills/changelog/SKILL.md index 89e13a40e..1ef8f324e 100644 --- a/.claude/skills/changelog/SKILL.md +++ b/.claude/skills/changelog/SKILL.md @@ -26,7 +26,7 @@ Create changelog files for the important commits in this PR. The PR number is pr - `{PR_NUMBER}.performance.md` - for performance improvements - `{PR_NUMBER}.other.md` - for other changes -4. Each changelog file should at least contain a main single line starting with `- ` followed by a clear description of the change. +4. Each changelog file should at least contain a main single line starting with `- ` followed by a clear description of the change. No line wrapping. 5. If the change is complicated, changelog files can have indented lines after the main line with additional details or code samples. From b1cee140b9cabc6fb7bc78727a85e47a2251d134 Mon Sep 17 00:00:00 2001 From: filipi87 Date: Thu, 19 Feb 2026 15:06:50 -0300 Subject: [PATCH 0553/1060] Refactoring to use broadcasted_sibling_id instead of broadcasted field. --- changelog/3774.added.md | 2 +- src/pipecat/frames/frames.py | 7 +++++-- src/pipecat/processors/frame_processor.py | 23 ++++++++++++----------- src/pipecat/processors/frameworks/rtvi.py | 2 +- 4 files changed, 19 insertions(+), 15 deletions(-) diff --git a/changelog/3774.added.md b/changelog/3774.added.md index 032d8238f..8e442999c 100644 --- a/changelog/3774.added.md +++ b/changelog/3774.added.md @@ -1 +1 @@ -- Added `broadcasted` field to the base `Frame` class. This field is automatically set to `True` by `broadcast_frame()` and `broadcast_frame_instance()` to distinguish broadcasted frames from single-direction frames. +- Added `broadcasted_sibling_id` field to the base `Frame` class. This field is automatically set by `broadcast_frame()` and `broadcast_frame_instance()` to the ID of the paired frame pushed in the opposite direction, allowing receivers to identify broadcast pairs. diff --git a/src/pipecat/frames/frames.py b/src/pipecat/frames/frames.py index c3f6226c6..e6bc008ab 100644 --- a/src/pipecat/frames/frames.py +++ b/src/pipecat/frames/frames.py @@ -123,6 +123,9 @@ class Frame: id: Unique identifier for the frame instance. name: Human-readable name combining class name and instance count. pts: Presentation timestamp in nanoseconds. + broadcasted_sibling_id: ID of the paired frame when this frame was + broadcast in both directions. Set automatically by + ``broadcast_frame()`` and ``broadcast_frame_instance()``. metadata: Dictionary for arbitrary frame metadata. transport_source: Name of the transport source that created this frame. transport_destination: Name of the transport destination for this frame. @@ -131,7 +134,7 @@ class Frame: id: int = field(init=False) name: str = field(init=False) pts: Optional[int] = field(init=False) - broadcasted: bool = field(init=False) + broadcasted_sibling_id: Optional[int] = field(init=False) metadata: Dict[str, Any] = field(init=False) transport_source: Optional[str] = field(init=False) transport_destination: Optional[str] = field(init=False) @@ -140,7 +143,7 @@ class Frame: self.id: int = obj_id() self.name: str = f"{self.__class__.__name__}#{obj_count(self)}" self.pts: Optional[int] = None - self.broadcasted: bool = False + self.broadcasted_sibling_id: Optional[int] = None self.metadata: Dict[str, Any] = {} self.transport_source: Optional[str] = None self.transport_destination: Optional[str] = None diff --git a/src/pipecat/processors/frame_processor.py b/src/pipecat/processors/frame_processor.py index 48c8c718c..6bdd9ae1d 100644 --- a/src/pipecat/processors/frame_processor.py +++ b/src/pipecat/processors/frame_processor.py @@ -788,10 +788,10 @@ class FrameProcessor(BaseObject): **kwargs: Keyword arguments to be passed to the frame's constructor. """ downstream_frame = frame_cls(**kwargs) - downstream_frame.broadcasted = True - await self.push_frame(downstream_frame) upstream_frame = frame_cls(**kwargs) - upstream_frame.broadcasted = True + downstream_frame.broadcasted_sibling_id = upstream_frame.id + upstream_frame.broadcasted_sibling_id = downstream_frame.id + await self.push_frame(downstream_frame) await self.push_frame(upstream_frame, FrameDirection.UPSTREAM) async def broadcast_frame_instance(self, frame: Frame): @@ -816,17 +816,18 @@ class FrameProcessor(BaseObject): if not f.init and f.name not in ("id", "name") } - new_frame = frame_cls(**init_fields) + downstream_frame = frame_cls(**init_fields) for k, v in extra_fields.items(): - setattr(new_frame, k, v) - new_frame.broadcasted = True - await self.push_frame(new_frame) + setattr(downstream_frame, k, v) - new_frame = frame_cls(**init_fields) + upstream_frame = frame_cls(**init_fields) for k, v in extra_fields.items(): - setattr(new_frame, k, v) - new_frame.broadcasted = True - await self.push_frame(new_frame, FrameDirection.UPSTREAM) + setattr(upstream_frame, k, v) + + downstream_frame.broadcasted_sibling_id = upstream_frame.id + upstream_frame.broadcasted_sibling_id = downstream_frame.id + await self.push_frame(downstream_frame) + await self.push_frame(upstream_frame, FrameDirection.UPSTREAM) async def __start(self, frame: StartFrame): """Handle the start frame to initialize processor state. diff --git a/src/pipecat/processors/frameworks/rtvi.py b/src/pipecat/processors/frameworks/rtvi.py index 8c7bb15ef..55be46452 100644 --- a/src/pipecat/processors/frameworks/rtvi.py +++ b/src/pipecat/processors/frameworks/rtvi.py @@ -1222,7 +1222,7 @@ class RTVIObserver(BaseObserver): # For broadcasted frames (pushed in both directions), only process # the downstream copy to avoid sending duplicate RTVI messages. - if frame.broadcasted and direction != FrameDirection.DOWNSTREAM: + if frame.broadcasted_sibling_id is not None and direction != FrameDirection.DOWNSTREAM: return # If we have already seen this frame, let's skip it. From d608c400f93eba752aee43d534a4d5f089bf6555 Mon Sep 17 00:00:00 2001 From: filipi87 Date: Thu, 19 Feb 2026 15:49:22 -0300 Subject: [PATCH 0554/1060] Preventing the duplicated BotStartedSpeakingFrame and BotStoppedSpeakingFrame. --- src/pipecat/transports/base_output.py | 10 ++++++++++ 1 file changed, 10 insertions(+) diff --git a/src/pipecat/transports/base_output.py b/src/pipecat/transports/base_output.py index c4f59a61d..4f072c0df 100644 --- a/src/pipecat/transports/base_output.py +++ b/src/pipecat/transports/base_output.py @@ -613,6 +613,11 @@ class BaseOutputTransport(FrameProcessor): downstream_frame.transport_destination = self._destination upstream_frame = BotStartedSpeakingFrame() upstream_frame.transport_destination = self._destination + + # Setting the siblings id + upstream_frame.broadcasted_sibling_id = downstream_frame.id + downstream_frame.broadcasted_sibling_id = upstream_frame.id + await self._transport.push_frame(downstream_frame) await self._transport.push_frame(upstream_frame, FrameDirection.UPSTREAM) @@ -635,6 +640,11 @@ class BaseOutputTransport(FrameProcessor): downstream_frame.transport_destination = self._destination upstream_frame = BotStoppedSpeakingFrame() upstream_frame.transport_destination = self._destination + + # Setting the siblings id + upstream_frame.broadcasted_sibling_id = downstream_frame.id + downstream_frame.broadcasted_sibling_id = upstream_frame.id + await self._transport.push_frame(downstream_frame) await self._transport.push_frame(upstream_frame, FrameDirection.UPSTREAM) From 859cd7c9205c5675903784af5503fcfe79245dbf Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Aleix=20Conchillo=20Flaqu=C3=A9?= Date: Thu, 19 Feb 2026 10:52:24 -0800 Subject: [PATCH 0555/1060] Refactor STT TTFB metrics to use base class start/stop pattern MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit Eliminate custom _emit_stt_ttfb_metric and manual timestamp tracking in STTService by reusing FrameProcessor's start_ttfb_metrics/stop_ttfb_metrics with new start_time/end_time parameters. This keeps the chronological start→stop ordering and removes _speech_end_time and _last_transcription_time state from STTService. --- src/pipecat/processors/frame_processor.py | 50 +++++++++++++------ .../metrics/frame_processor_metrics.py | 43 ++++++++++++---- src/pipecat/services/stt_service.py | 48 +++--------------- 3 files changed, 74 insertions(+), 67 deletions(-) diff --git a/src/pipecat/processors/frame_processor.py b/src/pipecat/processors/frame_processor.py index f0c9e7183..7423c4845 100644 --- a/src/pipecat/processors/frame_processor.py +++ b/src/pipecat/processors/frame_processor.py @@ -419,27 +419,49 @@ class FrameProcessor(BaseObject): """ self._metrics.set_core_metrics_data(data) - async def start_ttfb_metrics(self): - """Start time-to-first-byte metrics collection.""" - if self.can_generate_metrics() and self.metrics_enabled: - await self._metrics.start_ttfb_metrics(self._report_only_initial_ttfb) + async def start_ttfb_metrics(self, *, start_time: Optional[float] = None): + """Start time-to-first-byte metrics collection. - async def stop_ttfb_metrics(self): - """Stop time-to-first-byte metrics collection and push results.""" + Args: + start_time: Optional timestamp to use as the start time. If None, + uses the current time. + """ if self.can_generate_metrics() and self.metrics_enabled: - frame = await self._metrics.stop_ttfb_metrics() + await self._metrics.start_ttfb_metrics( + start_time=start_time, report_only_initial_ttfb=self._report_only_initial_ttfb + ) + + async def stop_ttfb_metrics(self, *, end_time: Optional[float] = None): + """Stop time-to-first-byte metrics collection and push results. + + Args: + end_time: Optional timestamp to use as the end time. If None, uses + the current time. + """ + if self.can_generate_metrics() and self.metrics_enabled: + frame = await self._metrics.stop_ttfb_metrics(end_time=end_time) if frame: await self.push_frame(frame) - async def start_processing_metrics(self): - """Start processing metrics collection.""" - if self.can_generate_metrics() and self.metrics_enabled: - await self._metrics.start_processing_metrics() + async def start_processing_metrics(self, *, start_time: Optional[float] = None): + """Start processing metrics collection. - async def stop_processing_metrics(self): - """Stop processing metrics collection and push results.""" + Args: + start_time: Optional timestamp to use as the start time. If None, + uses the current time. + """ if self.can_generate_metrics() and self.metrics_enabled: - frame = await self._metrics.stop_processing_metrics() + await self._metrics.start_processing_metrics(start_time=start_time) + + async def stop_processing_metrics(self, *, end_time: Optional[float] = None): + """Stop processing metrics collection and push results. + + Args: + end_time: Optional timestamp to use as the end time. If None, uses + the current time. + """ + if self.can_generate_metrics() and self.metrics_enabled: + frame = await self._metrics.stop_processing_metrics(end_time=end_time) if frame: await self.push_frame(frame) diff --git a/src/pipecat/processors/metrics/frame_processor_metrics.py b/src/pipecat/processors/metrics/frame_processor_metrics.py index b8beba6e2..c82fd9698 100644 --- a/src/pipecat/processors/metrics/frame_processor_metrics.py +++ b/src/pipecat/processors/metrics/frame_processor_metrics.py @@ -107,49 +107,70 @@ class FrameProcessorMetrics(BaseObject): """ self._core_metrics_data = MetricsData(processor=name) - async def start_ttfb_metrics(self, report_only_initial_ttfb): + async def start_ttfb_metrics( + self, *, start_time: Optional[float] = None, report_only_initial_ttfb: bool + ): """Start measuring time-to-first-byte (TTFB). Args: + start_time: Optional timestamp to use as the start time. If None, + uses the current time. report_only_initial_ttfb: Whether to report only the first TTFB measurement. """ if self._should_report_ttfb: - self._start_ttfb_time = time.time() + self._start_ttfb_time = start_time or time.time() self._last_ttfb_time = 0 self._should_report_ttfb = not report_only_initial_ttfb - async def stop_ttfb_metrics(self): + async def stop_ttfb_metrics(self, *, end_time: Optional[float] = None): """Stop TTFB measurement and generate metrics frame. + Args: + end_time: Optional timestamp to use as the end time. If None, uses + the current time. + Returns: MetricsFrame containing TTFB data, or None if not measuring. """ if self._start_ttfb_time == 0: return None - self._last_ttfb_time = time.time() - self._start_ttfb_time - logger.debug(f"{self._processor_name()} TTFB: {self._last_ttfb_time}") + end_time = end_time or time.time() + + self._last_ttfb_time = end_time - self._start_ttfb_time + logger.debug(f"{self._processor_name()} TTFB: {self._last_ttfb_time:.3f}s") ttfb = TTFBMetricsData( processor=self._processor_name(), value=self._last_ttfb_time, model=self._model_name() ) self._start_ttfb_time = 0 return MetricsFrame(data=[ttfb]) - async def start_processing_metrics(self): - """Start measuring processing time.""" - self._start_processing_time = time.time() + async def start_processing_metrics(self, *, start_time: Optional[float] = None): + """Start measuring processing time. - async def stop_processing_metrics(self): + Args: + start_time: Optional timestamp to use as the start time. If None, + uses the current time. + """ + self._start_processing_time = start_time or time.time() + + async def stop_processing_metrics(self, *, end_time: Optional[float] = None): """Stop processing time measurement and generate metrics frame. + Args: + end_time: Optional timestamp to use as the end time. If None, uses + the current time. + Returns: MetricsFrame containing processing duration data, or None if not measuring. """ if self._start_processing_time == 0: return None - value = time.time() - self._start_processing_time - logger.debug(f"{self._processor_name()} processing time: {value}") + end_time = end_time or time.time() + + value = end_time - self._start_processing_time + logger.debug(f"{self._processor_name()} processing time: {value:.3f}s") processing = ProcessingMetricsData( processor=self._processor_name(), value=value, model=self._model_name() ) diff --git a/src/pipecat/services/stt_service.py b/src/pipecat/services/stt_service.py index 6d431c523..bad8e2e28 100644 --- a/src/pipecat/services/stt_service.py +++ b/src/pipecat/services/stt_service.py @@ -21,7 +21,6 @@ from pipecat.frames.frames import ( ErrorFrame, Frame, InterruptionFrame, - MetricsFrame, ServiceSwitcherRequestMetadataFrame, StartFrame, STTMetadataFrame, @@ -31,7 +30,6 @@ from pipecat.frames.frames import ( VADUserStartedSpeakingFrame, VADUserStoppedSpeakingFrame, ) -from pipecat.metrics.metrics import TTFBMetricsData from pipecat.processors.frame_processor import FrameDirection from pipecat.services.ai_service import AIService from pipecat.services.stt_latency import DEFAULT_TTFS_P99 @@ -121,9 +119,7 @@ class STTService(AIService): # STT TTFB tracking state self._stt_ttfb_timeout = stt_ttfb_timeout self._ttfb_timeout_task: Optional[asyncio.Task] = None - self._speech_end_time: Optional[float] = None self._user_speaking: bool = False - self._last_transcription_time: Optional[float] = None self._finalize_pending: bool = False self._finalize_requested: bool = False @@ -327,23 +323,16 @@ class STTService(AIService): direction: The direction to push the frame. """ if isinstance(frame, TranscriptionFrame): - # Store the transcription time for TTFB calculation - self._last_transcription_time = time.time() - # Set finalized from pending state and auto-reset if self._finalize_pending: frame.finalized = True self._finalize_pending = False # If this is a finalized transcription, report TTFB immediately - if frame.finalized and self._speech_end_time is not None: - ttfb = self._last_transcription_time - self._speech_end_time - await self._emit_stt_ttfb_metric(ttfb) + if frame.finalized: + await self.stop_ttfb_metrics() # Cancel the timeout since we've already reported await self._cancel_ttfb_timeout() - # Clear state - self._speech_end_time = None - self._last_transcription_time = None await super().push_frame(frame, direction) @@ -373,8 +362,6 @@ class STTService(AIService): while user is still speaking. """ await self._cancel_ttfb_timeout() - self._speech_end_time = None - self._last_transcription_time = None async def _handle_vad_user_started_speaking(self, frame: VADUserStartedSpeakingFrame): """Handle VAD user started speaking frame to start tracking transcriptions. @@ -408,7 +395,8 @@ class STTService(AIService): # Calculate the actual speech end time (current time minus VAD stop delay). # This approximates when the last user audio was sent to the STT service, # which we use to measure against the eventual transcription response. - self._speech_end_time = frame.timestamp - frame.stop_secs + speech_end_time = frame.timestamp - frame.stop_secs + await self.start_ttfb_metrics(start_time=speech_end_time) # Start timeout task (any previous timeout was cancelled by VADUserStartedSpeakingFrame # or InterruptionFrame) @@ -417,44 +405,20 @@ class STTService(AIService): ) async def _ttfb_timeout_handler(self): - """Wait for timeout then report TTFB using the last transcription timestamp. + """Wait for timeout then report TTFB. This timeout allows the final transcription to arrive before we calculate and report TTFB. If no transcription arrived, no TTFB is reported. """ try: await asyncio.sleep(self._stt_ttfb_timeout) - - # Report TTFB if we have both speech end time and transcription time - if self._speech_end_time is not None and self._last_transcription_time is not None: - ttfb = self._last_transcription_time - self._speech_end_time - await self._emit_stt_ttfb_metric(ttfb) - - # Clear state after reporting - self._speech_end_time = None - self._last_transcription_time = None + await self.stop_ttfb_metrics() except asyncio.CancelledError: # Task was cancelled (new utterance or interruption), which is expected behavior pass finally: self._ttfb_timeout_task = None - async def _emit_stt_ttfb_metric(self, ttfb: float): - """Emit STT TTFB metric if value is non-negative. - - Args: - ttfb: The TTFB value in seconds. - """ - if ttfb >= 0: - logger.debug(f"{self} TTFB: {ttfb:.3f}s") - if self.metrics_enabled: - ttfb_data = TTFBMetricsData( - processor=self.name, - model=self.model_name, - value=ttfb, - ) - await super().push_frame(MetricsFrame(data=[ttfb_data])) - 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From 5b2fa69bdc5f6a888508a0c52189d2add6899b32 Mon Sep 17 00:00:00 2001 From: filipi87 Date: Thu, 19 Feb 2026 16:24:07 -0300 Subject: [PATCH 0558/1060] Renaming from broadcasted_sibling_id to broadcast_sibling_id --- changelog/3774.added.md | 2 +- src/pipecat/frames/frames.py | 6 +++--- src/pipecat/processors/frame_processor.py | 8 ++++---- src/pipecat/processors/frameworks/rtvi.py | 2 +- src/pipecat/transports/base_output.py | 8 ++++---- 5 files changed, 13 insertions(+), 13 deletions(-) diff --git a/changelog/3774.added.md b/changelog/3774.added.md index 8e442999c..e72599e60 100644 --- a/changelog/3774.added.md +++ b/changelog/3774.added.md @@ -1 +1 @@ -- Added `broadcasted_sibling_id` field to the base `Frame` class. This field is automatically set by `broadcast_frame()` and `broadcast_frame_instance()` to the ID of the paired frame pushed in the opposite direction, allowing receivers to identify broadcast pairs. +- Added `broadcast_sibling_id` field to the base `Frame` class. This field is automatically set by `broadcast_frame()` and `broadcast_frame_instance()` to the ID of the paired frame pushed in the opposite direction, allowing receivers to identify broadcast pairs. diff --git a/src/pipecat/frames/frames.py b/src/pipecat/frames/frames.py index e6bc008ab..62c0d1352 100644 --- a/src/pipecat/frames/frames.py +++ b/src/pipecat/frames/frames.py @@ -123,7 +123,7 @@ class Frame: id: Unique identifier for the frame instance. name: Human-readable name combining class name and instance count. pts: Presentation timestamp in nanoseconds. - broadcasted_sibling_id: ID of the paired frame when this frame was + broadcast_sibling_id: ID of the paired frame when this frame was broadcast in both directions. Set automatically by ``broadcast_frame()`` and ``broadcast_frame_instance()``. metadata: Dictionary for arbitrary frame metadata. @@ -134,7 +134,7 @@ class Frame: id: int = field(init=False) name: str = field(init=False) pts: Optional[int] = field(init=False) - broadcasted_sibling_id: Optional[int] = field(init=False) + broadcast_sibling_id: Optional[int] = field(init=False) metadata: Dict[str, Any] = field(init=False) transport_source: Optional[str] = field(init=False) transport_destination: Optional[str] = field(init=False) @@ -143,7 +143,7 @@ class Frame: self.id: int = obj_id() self.name: str = f"{self.__class__.__name__}#{obj_count(self)}" self.pts: Optional[int] = None - self.broadcasted_sibling_id: Optional[int] = None + self.broadcast_sibling_id: Optional[int] = None self.metadata: Dict[str, Any] = {} self.transport_source: Optional[str] = None self.transport_destination: Optional[str] = None diff --git a/src/pipecat/processors/frame_processor.py b/src/pipecat/processors/frame_processor.py index 6bdd9ae1d..0d20214b2 100644 --- a/src/pipecat/processors/frame_processor.py +++ b/src/pipecat/processors/frame_processor.py @@ -789,8 +789,8 @@ class FrameProcessor(BaseObject): """ downstream_frame = frame_cls(**kwargs) upstream_frame = frame_cls(**kwargs) - downstream_frame.broadcasted_sibling_id = upstream_frame.id - upstream_frame.broadcasted_sibling_id = downstream_frame.id + downstream_frame.broadcast_sibling_id = upstream_frame.id + upstream_frame.broadcast_sibling_id = downstream_frame.id await self.push_frame(downstream_frame) await self.push_frame(upstream_frame, FrameDirection.UPSTREAM) @@ -824,8 +824,8 @@ class FrameProcessor(BaseObject): for k, v in extra_fields.items(): setattr(upstream_frame, k, v) - downstream_frame.broadcasted_sibling_id = upstream_frame.id - upstream_frame.broadcasted_sibling_id = downstream_frame.id + downstream_frame.broadcast_sibling_id = upstream_frame.id + upstream_frame.broadcast_sibling_id = downstream_frame.id await self.push_frame(downstream_frame) await self.push_frame(upstream_frame, FrameDirection.UPSTREAM) diff --git a/src/pipecat/processors/frameworks/rtvi.py b/src/pipecat/processors/frameworks/rtvi.py index 55be46452..a8b66ccdd 100644 --- a/src/pipecat/processors/frameworks/rtvi.py +++ b/src/pipecat/processors/frameworks/rtvi.py @@ -1222,7 +1222,7 @@ class RTVIObserver(BaseObserver): # For broadcasted frames (pushed in both directions), only process # the downstream copy to avoid sending duplicate RTVI messages. - if frame.broadcasted_sibling_id is not None and direction != FrameDirection.DOWNSTREAM: + if frame.broadcast_sibling_id is not None and direction != FrameDirection.DOWNSTREAM: return # If we have already seen this frame, let's skip it. diff --git a/src/pipecat/transports/base_output.py b/src/pipecat/transports/base_output.py index 4f072c0df..1a5083128 100644 --- a/src/pipecat/transports/base_output.py +++ b/src/pipecat/transports/base_output.py @@ -615,8 +615,8 @@ class BaseOutputTransport(FrameProcessor): upstream_frame.transport_destination = self._destination # Setting the siblings id - upstream_frame.broadcasted_sibling_id = downstream_frame.id - downstream_frame.broadcasted_sibling_id = upstream_frame.id + upstream_frame.broadcast_sibling_id = downstream_frame.id + downstream_frame.broadcast_sibling_id = upstream_frame.id await self._transport.push_frame(downstream_frame) await self._transport.push_frame(upstream_frame, FrameDirection.UPSTREAM) @@ -642,8 +642,8 @@ class BaseOutputTransport(FrameProcessor): upstream_frame.transport_destination = self._destination # Setting the siblings id - upstream_frame.broadcasted_sibling_id = downstream_frame.id - downstream_frame.broadcasted_sibling_id = upstream_frame.id + upstream_frame.broadcast_sibling_id = downstream_frame.id + downstream_frame.broadcast_sibling_id = upstream_frame.id await self._transport.push_frame(downstream_frame) await self._transport.push_frame(upstream_frame, FrameDirection.UPSTREAM) From cc54ff4708ee69476ab0fdb160d2a3b1556d72c3 Mon Sep 17 00:00:00 2001 From: Paul Kompfner Date: Thu, 19 Feb 2026 14:42:08 -0500 Subject: [PATCH 0559/1060] Add more 55-series examples --- .../55n-update-settings-cartesia-http-tts.py | 133 +++++++++++++++++ ...55o-update-settings-elevenlabs-http-tts.py | 132 +++++++++++++++++ .../55o-update-settings-elevenlabs-tts.py | 2 +- .../55q-update-settings-deepgram-http-tts.py | 137 ++++++++++++++++++ .../55q-update-settings-deepgram-tts.py | 12 +- .../55r-update-settings-azure-http-tts.py | 127 ++++++++++++++++ 6 files changed, 536 insertions(+), 7 deletions(-) create mode 100644 examples/foundational/55n-update-settings-cartesia-http-tts.py create mode 100644 examples/foundational/55o-update-settings-elevenlabs-http-tts.py create mode 100644 examples/foundational/55q-update-settings-deepgram-http-tts.py create mode 100644 examples/foundational/55r-update-settings-azure-http-tts.py diff --git a/examples/foundational/55n-update-settings-cartesia-http-tts.py b/examples/foundational/55n-update-settings-cartesia-http-tts.py new file mode 100644 index 000000000..27cee5b8f --- /dev/null +++ b/examples/foundational/55n-update-settings-cartesia-http-tts.py @@ -0,0 +1,133 @@ +# +# Copyright (c) 2024-2026, Daily +# +# SPDX-License-Identifier: BSD 2-Clause License +# + +import asyncio +import os + +from dotenv import load_dotenv +from loguru import logger + +from pipecat.audio.vad.silero import SileroVADAnalyzer +from pipecat.frames.frames import LLMRunFrame, TTSUpdateSettingsFrame +from pipecat.pipeline.pipeline import Pipeline +from pipecat.pipeline.runner import PipelineRunner +from pipecat.pipeline.task import PipelineParams, PipelineTask +from pipecat.processors.aggregators.llm_context import LLMContext +from pipecat.processors.aggregators.llm_response_universal import ( + LLMContextAggregatorPair, + LLMUserAggregatorParams, +) +from pipecat.runner.types import RunnerArguments +from pipecat.runner.utils import create_transport +from pipecat.services.cartesia.tts import ( + CartesiaHttpTTSService, + CartesiaTTSSettings, + GenerationConfig, +) +from pipecat.services.deepgram.stt import DeepgramSTTService +from pipecat.services.openai.llm import OpenAILLMService +from pipecat.transports.base_transport import BaseTransport, TransportParams +from pipecat.transports.daily.transport import DailyParams +from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams + +load_dotenv(override=True) + +transport_params = { + "daily": lambda: DailyParams( + audio_in_enabled=True, + audio_out_enabled=True, + ), + "twilio": lambda: FastAPIWebsocketParams( + audio_in_enabled=True, + audio_out_enabled=True, + ), + "webrtc": lambda: TransportParams( + audio_in_enabled=True, + audio_out_enabled=True, + ), +} + + +async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): + logger.info(f"Starting bot") + + stt = DeepgramSTTService(api_key=os.getenv("DEEPGRAM_API_KEY")) + + tts = CartesiaHttpTTSService( + api_key=os.getenv("CARTESIA_API_KEY"), + voice_id="71a7ad14-091c-4e8e-a314-022ece01c121", + ) + + llm = OpenAILLMService(api_key=os.getenv("OPENAI_API_KEY")) + + messages = [ + { + "role": "system", + "content": "You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + }, + ] + + context = LLMContext(messages) + user_aggregator, assistant_aggregator = LLMContextAggregatorPair( + context, + user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()), + ) + + pipeline = Pipeline( + [ + transport.input(), + stt, + user_aggregator, + llm, + tts, + transport.output(), + assistant_aggregator, + ] + ) + + task = PipelineTask( + pipeline, + params=PipelineParams( + enable_metrics=True, + enable_usage_metrics=True, + ), + idle_timeout_secs=runner_args.pipeline_idle_timeout_secs, + ) + + @transport.event_handler("on_client_connected") + async def on_client_connected(transport, client): + logger.info(f"Client connected") + messages.append({"role": "system", "content": "Please introduce yourself to the user."}) + await task.queue_frames([LLMRunFrame()]) + + await asyncio.sleep(10) + logger.info("Updating Cartesia HTTP TTS settings: speed increased to 1.5") + await task.queue_frame( + TTSUpdateSettingsFrame( + update=CartesiaTTSSettings(generation_config=GenerationConfig(speed=1.5)) + ) + ) + + @transport.event_handler("on_client_disconnected") + async def on_client_disconnected(transport, client): + logger.info(f"Client disconnected") + await task.cancel() + + runner = PipelineRunner(handle_sigint=runner_args.handle_sigint) + + await runner.run(task) + + +async def bot(runner_args: RunnerArguments): + """Main bot entry point compatible with Pipecat Cloud.""" + transport = await create_transport(runner_args, transport_params) + await run_bot(transport, runner_args) + + +if __name__ == "__main__": + from pipecat.runner.run import main + + main() diff --git a/examples/foundational/55o-update-settings-elevenlabs-http-tts.py b/examples/foundational/55o-update-settings-elevenlabs-http-tts.py new file mode 100644 index 000000000..a67202702 --- /dev/null +++ b/examples/foundational/55o-update-settings-elevenlabs-http-tts.py @@ -0,0 +1,132 @@ +# +# Copyright (c) 2024-2026, Daily +# +# SPDX-License-Identifier: BSD 2-Clause License +# + + +import asyncio +import os + +import aiohttp +from dotenv import load_dotenv +from loguru import logger + +from pipecat.audio.vad.silero import SileroVADAnalyzer +from pipecat.frames.frames import LLMRunFrame, TTSUpdateSettingsFrame +from pipecat.pipeline.pipeline import Pipeline +from pipecat.pipeline.runner import PipelineRunner +from pipecat.pipeline.task import PipelineParams, PipelineTask +from pipecat.processors.aggregators.llm_context import LLMContext +from pipecat.processors.aggregators.llm_response_universal import ( + LLMContextAggregatorPair, + LLMUserAggregatorParams, +) +from pipecat.runner.types import RunnerArguments +from pipecat.runner.utils import create_transport +from pipecat.services.deepgram.stt import DeepgramSTTService +from pipecat.services.elevenlabs.tts import ElevenLabsHttpTTSService, ElevenLabsHttpTTSSettings +from pipecat.services.openai.llm import OpenAILLMService +from pipecat.transports.base_transport import BaseTransport, TransportParams +from pipecat.transports.daily.transport import DailyParams +from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams + +load_dotenv(override=True) + + +transport_params = { + "daily": lambda: DailyParams( + audio_in_enabled=True, + audio_out_enabled=True, + ), + "twilio": lambda: FastAPIWebsocketParams( + audio_in_enabled=True, + audio_out_enabled=True, + ), + "webrtc": lambda: TransportParams( + audio_in_enabled=True, + audio_out_enabled=True, + ), +} + + +async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): + logger.info(f"Starting bot") + + async with aiohttp.ClientSession() as session: + stt = DeepgramSTTService(api_key=os.getenv("DEEPGRAM_API_KEY")) + + tts = ElevenLabsHttpTTSService( + api_key=os.getenv("ELEVENLABS_API_KEY"), + voice_id=os.getenv("ELEVENLABS_VOICE_ID"), + aiohttp_session=session, + ) + + llm = OpenAILLMService(api_key=os.getenv("OPENAI_API_KEY")) + + messages = [ + { + "role": "system", + "content": "You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + }, + ] + + context = LLMContext(messages) + user_aggregator, assistant_aggregator = LLMContextAggregatorPair( + context, + user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()), + ) + + pipeline = Pipeline( + [ + transport.input(), + stt, + user_aggregator, + llm, + tts, + transport.output(), + assistant_aggregator, + ] + ) + + task = PipelineTask( + pipeline, + params=PipelineParams( + enable_metrics=True, + enable_usage_metrics=True, + ), + idle_timeout_secs=runner_args.pipeline_idle_timeout_secs, + ) + + @transport.event_handler("on_client_connected") + async def on_client_connected(transport, client): + logger.info(f"Client connected") + messages.append({"role": "system", "content": "Please introduce yourself to the user."}) + await task.queue_frames([LLMRunFrame()]) + + await asyncio.sleep(10) + logger.info("Updating ElevenLabs TTS settings: speed=0.7") + await task.queue_frame( + TTSUpdateSettingsFrame(update=ElevenLabsHttpTTSSettings(speed=0.7)) + ) + + @transport.event_handler("on_client_disconnected") + async def on_client_disconnected(transport, client): + logger.info(f"Client disconnected") + await task.cancel() + + runner = PipelineRunner(handle_sigint=runner_args.handle_sigint) + + await runner.run(task) + + +async def bot(runner_args: RunnerArguments): + """Main bot entry point compatible with Pipecat Cloud.""" + transport = await create_transport(runner_args, transport_params) + await run_bot(transport, runner_args) + + +if __name__ == "__main__": + from pipecat.runner.run import main + + main() diff --git a/examples/foundational/55o-update-settings-elevenlabs-tts.py b/examples/foundational/55o-update-settings-elevenlabs-tts.py index 6c85e2452..4186f07ae 100644 --- a/examples/foundational/55o-update-settings-elevenlabs-tts.py +++ b/examples/foundational/55o-update-settings-elevenlabs-tts.py @@ -101,7 +101,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): await task.queue_frames([LLMRunFrame()]) await asyncio.sleep(10) - logger.info("Updating ElevenLabs TTS settings: speed=1.2") + logger.info("Updating ElevenLabs TTS settings: speed=0.7") await task.queue_frame(TTSUpdateSettingsFrame(update=ElevenLabsTTSSettings(speed=0.7))) @transport.event_handler("on_client_disconnected") diff --git a/examples/foundational/55q-update-settings-deepgram-http-tts.py b/examples/foundational/55q-update-settings-deepgram-http-tts.py new file mode 100644 index 000000000..64bbea587 --- /dev/null +++ b/examples/foundational/55q-update-settings-deepgram-http-tts.py @@ -0,0 +1,137 @@ +# +# Copyright (c) 2024-2026, Daily +# +# SPDX-License-Identifier: BSD 2-Clause License +# + + +import asyncio +import os + +import aiohttp +from dotenv import load_dotenv +from loguru import logger + +from pipecat.audio.vad.silero import SileroVADAnalyzer +from pipecat.frames.frames import LLMRunFrame, TTSUpdateSettingsFrame +from pipecat.pipeline.pipeline import Pipeline +from pipecat.pipeline.runner import PipelineRunner +from pipecat.pipeline.task import PipelineParams, PipelineTask +from pipecat.processors.aggregators.llm_context import LLMContext +from pipecat.processors.aggregators.llm_response_universal import ( + LLMContextAggregatorPair, + LLMUserAggregatorParams, +) +from pipecat.runner.types import RunnerArguments +from pipecat.runner.utils import create_transport +from pipecat.services.deepgram.stt import DeepgramSTTService +from pipecat.services.deepgram.tts import DeepgramHttpTTSService, DeepgramTTSSettings +from pipecat.services.openai.llm import OpenAILLMService +from pipecat.transports.base_transport import BaseTransport, TransportParams +from pipecat.transports.daily.transport import DailyParams +from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams + +load_dotenv(override=True) + + +transport_params = { + "daily": lambda: DailyParams( + audio_in_enabled=True, + audio_out_enabled=True, + ), + "twilio": lambda: FastAPIWebsocketParams( + audio_in_enabled=True, + audio_out_enabled=True, + ), + "webrtc": lambda: TransportParams( + audio_in_enabled=True, + audio_out_enabled=True, + ), +} + + +async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): + logger.info(f"Starting bot") + + async with aiohttp.ClientSession() as session: + stt = DeepgramSTTService(api_key=os.getenv("DEEPGRAM_API_KEY")) + + tts = DeepgramHttpTTSService( + api_key=os.getenv("DEEPGRAM_API_KEY"), + aiohttp_session=session, + ) + + llm = OpenAILLMService(api_key=os.getenv("OPENAI_API_KEY")) + + messages = [ + { + "role": "system", + "content": "You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + }, + ] + + context = LLMContext(messages) + user_aggregator, assistant_aggregator = LLMContextAggregatorPair( + context, + user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()), + ) + + pipeline = Pipeline( + [ + transport.input(), + stt, + user_aggregator, + llm, + tts, + transport.output(), + assistant_aggregator, + ] + ) + + task = PipelineTask( + pipeline, + params=PipelineParams( + enable_metrics=True, + enable_usage_metrics=True, + ), + idle_timeout_secs=runner_args.pipeline_idle_timeout_secs, + ) + + @transport.event_handler("on_client_connected") + async def on_client_connected(transport, client): + logger.info(f"Client connected") + messages.append({"role": "system", "content": "Please introduce yourself to the user."}) + await task.queue_frames([LLMRunFrame()]) + + await asyncio.sleep(10) + logger.info('Updating Deepgram TTS settings: voice="aura-2-aries-en"') + await task.queue_frame( + TTSUpdateSettingsFrame(update=DeepgramTTSSettings(voice="aura-2-aries-en")) + ) + + await asyncio.sleep(10) + logger.info('Updating Deepgram TTS settings: voice="aura-2-luna-en"') + await task.queue_frame( + TTSUpdateSettingsFrame(update=DeepgramTTSSettings(voice="aura-2-luna-en")) + ) + + @transport.event_handler("on_client_disconnected") + async def on_client_disconnected(transport, client): + logger.info(f"Client disconnected") + await task.cancel() + + runner = PipelineRunner(handle_sigint=runner_args.handle_sigint) + + await runner.run(task) + + +async def bot(runner_args: RunnerArguments): + """Main bot entry point compatible with Pipecat Cloud.""" + transport = await create_transport(runner_args, transport_params) + await run_bot(transport, runner_args) + + +if __name__ == "__main__": + from pipecat.runner.run import main + + main() diff --git a/examples/foundational/55q-update-settings-deepgram-tts.py b/examples/foundational/55q-update-settings-deepgram-tts.py index 636342194..9d94a50da 100644 --- a/examples/foundational/55q-update-settings-deepgram-tts.py +++ b/examples/foundational/55q-update-settings-deepgram-tts.py @@ -96,18 +96,18 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): messages.append({"role": "system", "content": "Please introduce yourself to the user."}) await task.queue_frames([LLMRunFrame()]) - await asyncio.sleep(10) - logger.info('Updating Deepgram TTS settings: voice="aura-2-luna-en"') - await task.queue_frame( - TTSUpdateSettingsFrame(update=DeepgramTTSSettings(voice="aura-2-luna-en")) - ) - await asyncio.sleep(10) logger.info('Updating Deepgram TTS settings: voice="aura-2-aries-en"') await task.queue_frame( TTSUpdateSettingsFrame(update=DeepgramTTSSettings(voice="aura-2-aries-en")) ) + await asyncio.sleep(10) + logger.info('Updating Deepgram TTS settings: voice="aura-2-luna-en"') + await task.queue_frame( + TTSUpdateSettingsFrame(update=DeepgramTTSSettings(voice="aura-2-luna-en")) + ) + @transport.event_handler("on_client_disconnected") async def on_client_disconnected(transport, client): logger.info(f"Client disconnected") diff --git a/examples/foundational/55r-update-settings-azure-http-tts.py b/examples/foundational/55r-update-settings-azure-http-tts.py new file mode 100644 index 000000000..3132580ed --- /dev/null +++ b/examples/foundational/55r-update-settings-azure-http-tts.py @@ -0,0 +1,127 @@ +# +# Copyright (c) 2024-2026, Daily +# +# SPDX-License-Identifier: BSD 2-Clause License +# + +import asyncio +import os + +from dotenv import load_dotenv +from loguru import logger + +from pipecat.audio.vad.silero import SileroVADAnalyzer +from pipecat.frames.frames import LLMRunFrame, TTSUpdateSettingsFrame +from pipecat.pipeline.pipeline import Pipeline +from pipecat.pipeline.runner import PipelineRunner +from pipecat.pipeline.task import PipelineParams, PipelineTask +from pipecat.processors.aggregators.llm_context import LLMContext +from pipecat.processors.aggregators.llm_response_universal import ( + LLMContextAggregatorPair, + LLMUserAggregatorParams, +) +from pipecat.runner.types import RunnerArguments +from pipecat.runner.utils import create_transport +from pipecat.services.azure.tts import AzureHttpTTSService, AzureTTSSettings +from pipecat.services.deepgram.stt import DeepgramSTTService +from pipecat.services.openai.llm import OpenAILLMService +from pipecat.transports.base_transport import BaseTransport, TransportParams +from pipecat.transports.daily.transport import DailyParams +from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams + +load_dotenv(override=True) + +transport_params = { + "daily": lambda: DailyParams( + audio_in_enabled=True, + audio_out_enabled=True, + ), + "twilio": lambda: FastAPIWebsocketParams( + audio_in_enabled=True, + audio_out_enabled=True, + ), + "webrtc": lambda: TransportParams( + audio_in_enabled=True, + audio_out_enabled=True, + ), +} + + +async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): + logger.info(f"Starting bot") + + stt = DeepgramSTTService(api_key=os.getenv("DEEPGRAM_API_KEY")) + + tts = AzureHttpTTSService( + api_key=os.getenv("AZURE_SPEECH_API_KEY"), + region=os.getenv("AZURE_SPEECH_REGION"), + ) + + llm = OpenAILLMService(api_key=os.getenv("OPENAI_API_KEY")) + + messages = [ + { + "role": "system", + "content": "You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + }, + ] + + context = LLMContext(messages) + user_aggregator, assistant_aggregator = LLMContextAggregatorPair( + context, + user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()), + ) + + pipeline = Pipeline( + [ + transport.input(), + stt, + user_aggregator, + llm, + tts, + transport.output(), + assistant_aggregator, + ] + ) + + task = PipelineTask( + pipeline, + params=PipelineParams( + enable_metrics=True, + enable_usage_metrics=True, + ), + idle_timeout_secs=runner_args.pipeline_idle_timeout_secs, + ) + + @transport.event_handler("on_client_connected") + async def on_client_connected(transport, client): + logger.info(f"Client connected") + messages.append({"role": "system", "content": "Please introduce yourself to the user."}) + await task.queue_frames([LLMRunFrame()]) + + await asyncio.sleep(10) + logger.info('Updating Azure TTS settings: rate="0.7", style="sad"') + await task.queue_frame( + TTSUpdateSettingsFrame(update=AzureTTSSettings(rate="0.7", style="sad")) + ) + + @transport.event_handler("on_client_disconnected") + async def on_client_disconnected(transport, client): + logger.info(f"Client disconnected") + await task.cancel() + + runner = PipelineRunner(handle_sigint=runner_args.handle_sigint) + + await runner.run(task) + + +async def bot(runner_args: RunnerArguments): + """Main bot entry point compatible with Pipecat Cloud.""" + transport = await create_transport(runner_args, transport_params) + await run_bot(transport, runner_args) + + +if __name__ == "__main__": + from pipecat.runner.run import main + + main() From ebb42a3c6d39fc6d9abdc305868c5dd0c855eeb2 Mon Sep 17 00:00:00 2001 From: Paul Kompfner Date: Thu, 19 Feb 2026 15:06:48 -0500 Subject: [PATCH 0560/1060] Fix forward reference crash in Google and Anthropic LLM ThinkingConfig ThinkingConfig was defined as an inner class on the service but referenced in the Settings dataclass declared before the service class, causing a crash at import time. Move ThinkingConfig to a standalone class defined before Settings, and keep a class attribute alias for backward compatibility. --- src/pipecat/services/anthropic/llm.py | 50 +++++++++--------- src/pipecat/services/google/llm.py | 76 ++++++++++++++------------- 2 files changed, 64 insertions(+), 62 deletions(-) diff --git a/src/pipecat/services/anthropic/llm.py b/src/pipecat/services/anthropic/llm.py index 4416aa018..68ebf7ab1 100644 --- a/src/pipecat/services/anthropic/llm.py +++ b/src/pipecat/services/anthropic/llm.py @@ -70,6 +70,25 @@ except ModuleNotFoundError as e: raise Exception(f"Missing module: {e}") +class AnthropicThinkingConfig(BaseModel): + """Configuration for extended thinking. + + Parameters: + type: Type of thinking mode (currently only "enabled" or "disabled"). + budget_tokens: Maximum number of tokens for thinking. + With today's models, the minimum is 1024. + Only allowed if type is "enabled". + """ + + # Why `| str` here? To not break compatibility in case Anthropic adds + # more types in the future. + type: Literal["enabled", "disabled"] | str + + # Why not enforce minimnum of 1024 here? To not break compatibility in + # case Anthropic changes this requirement in the future. + budget_tokens: int + + @dataclass class AnthropicLLMSettings(LLMSettings): """Settings for Anthropic LLM services. @@ -80,20 +99,18 @@ class AnthropicLLMSettings(LLMSettings): """ enable_prompt_caching: bool | _NotGiven = field(default_factory=lambda: _NOT_GIVEN) - thinking: "AnthropicLLMService.ThinkingConfig" | _NotGiven = field( - default_factory=lambda: _NOT_GIVEN - ) + thinking: AnthropicThinkingConfig | _NotGiven = field(default_factory=lambda: _NOT_GIVEN) @classmethod def from_mapping(cls, settings): """Convert a plain dict to settings, coercing thinking dicts. For backward compatibility, a ``thinking`` value that is a plain dict - is converted to a :class:`AnthropicLLMService.ThinkingConfig`. + is converted to a :class:`AnthropicThinkingConfig`. """ instance = super().from_mapping(settings) if is_given(instance.thinking) and isinstance(instance.thinking, dict): - instance.thinking = AnthropicLLMService.ThinkingConfig(**instance.thinking) + instance.thinking = AnthropicThinkingConfig(**instance.thinking) return instance @@ -148,23 +165,8 @@ class AnthropicLLMService(LLMService): # Overriding the default adapter to use the Anthropic one. adapter_class = AnthropicLLMAdapter - class ThinkingConfig(BaseModel): - """Configuration for extended thinking. - - Parameters: - type: Type of thinking mode (currently only "enabled" or "disabled"). - budget_tokens: Maximum number of tokens for thinking. - With today's models, the minimum is 1024. - Only allowed if type is "enabled". - """ - - # Why `| str` here? To not break compatibility in case Anthropic adds - # more types in the future. - type: Literal["enabled", "disabled"] | str - - # Why not enforce minimnum of 1024 here? To not break compatibility in - # case Anthropic changes this requirement in the future. - budget_tokens: int + # Backward compatibility: ThinkingConfig used to be defined inline here. + ThinkingConfig = AnthropicThinkingConfig class InputParams(BaseModel): """Input parameters for Anthropic model inference. @@ -193,9 +195,7 @@ class AnthropicLLMService(LLMService): temperature: Optional[float] = Field(default_factory=lambda: NOT_GIVEN, ge=0.0, le=1.0) top_k: Optional[int] = Field(default_factory=lambda: NOT_GIVEN, ge=0) top_p: Optional[float] = Field(default_factory=lambda: NOT_GIVEN, ge=0.0, le=1.0) - thinking: Optional["AnthropicLLMService.ThinkingConfig"] = Field( - default_factory=lambda: NOT_GIVEN - ) + thinking: Optional[AnthropicThinkingConfig] = Field(default_factory=lambda: NOT_GIVEN) extra: Optional[Dict[str, Any]] = Field(default_factory=dict) def model_post_init(self, __context): diff --git a/src/pipecat/services/google/llm.py b/src/pipecat/services/google/llm.py index 0a097b770..f5a6db78c 100644 --- a/src/pipecat/services/google/llm.py +++ b/src/pipecat/services/google/llm.py @@ -673,6 +673,39 @@ class GoogleLLMContext(OpenAILLMContext): self._messages = [m for m in self._messages if m.parts] +class GoogleThinkingConfig(BaseModel): + """Configuration for controlling the model's internal "thinking" process used before generating a response. + + Gemini 2.5 and 3 series models have this thinking process. + + Parameters: + thinking_level: Thinking level for Gemini 3 models. + For Gemini 3 Pro, this can be "low" or "high". + For Gemini 3 Flash, this can be "minimal", "low", "medium", or "high". + If not provided, Gemini 3 models default to "high". + Note: Gemini 2.5 series must use thinking_budget instead. + thinking_budget: Token budget for thinking, for Gemini 2.5 series. + -1 for dynamic thinking (model decides), 0 to disable thinking, + or a specific token count (e.g., 128-32768 for 2.5 Pro). + If not provided, most models today default to dynamic thinking. + See https://ai.google.dev/gemini-api/docs/thinking#set-budget + for default values and allowed ranges. + Note: Gemini 3 models must use thinking_level instead. + include_thoughts: Whether to include thought summaries in the response. + Today's models default to not including thoughts (False). + """ + + thinking_budget: Optional[int] = Field(default=None) + + # Why `| str` here? To not break compatibility in case Google adds more + # levels in the future. + thinking_level: Optional[Literal["low", "high", "medium", "minimal"] | str] = Field( + default=None + ) + + include_thoughts: Optional[bool] = Field(default=None) + + @dataclass class GoogleLLMSettings(LLMSettings): """Settings for Google LLM services. @@ -681,20 +714,18 @@ class GoogleLLMSettings(LLMSettings): thinking: Thinking configuration. """ - thinking: "GoogleLLMService.ThinkingConfig" | _NotGiven = field( - default_factory=lambda: NOT_GIVEN - ) + thinking: GoogleThinkingConfig | _NotGiven = field(default_factory=lambda: NOT_GIVEN) @classmethod def from_mapping(cls, settings): """Convert a plain dict to settings, coercing thinking dicts. For backward compatibility, a ``thinking`` value that is a plain dict - is converted to a :class:`GoogleLLMService.ThinkingConfig`. + is converted to a :class:`GoogleThinkingConfig`. """ instance = super().from_mapping(settings) if is_given(instance.thinking) and isinstance(instance.thinking, dict): - instance.thinking = GoogleLLMService.ThinkingConfig(**instance.thinking) + instance.thinking = GoogleThinkingConfig(**instance.thinking) return instance @@ -711,37 +742,8 @@ class GoogleLLMService(LLMService): # Overriding the default adapter to use the Gemini one. adapter_class = GeminiLLMAdapter - class ThinkingConfig(BaseModel): - """Configuration for controlling the model's internal "thinking" process used before generating a response. - - Gemini 2.5 and 3 series models have this thinking process. - - Parameters: - thinking_level: Thinking level for Gemini 3 models. - For Gemini 3 Pro, this can be "low" or "high". - For Gemini 3 Flash, this can be "minimal", "low", "medium", or "high". - If not provided, Gemini 3 models default to "high". - Note: Gemini 2.5 series must use thinking_budget instead. - thinking_budget: Token budget for thinking, for Gemini 2.5 series. - -1 for dynamic thinking (model decides), 0 to disable thinking, - or a specific token count (e.g., 128-32768 for 2.5 Pro). - If not provided, most models today default to dynamic thinking. - See https://ai.google.dev/gemini-api/docs/thinking#set-budget - for default values and allowed ranges. - Note: Gemini 3 models must use thinking_level instead. - include_thoughts: Whether to include thought summaries in the response. - Today's models default to not including thoughts (False). - """ - - thinking_budget: Optional[int] = Field(default=None) - - # Why `| str` here? To not break compatibility in case Google adds more - # levels in the future. - thinking_level: Optional[Literal["low", "high", "medium", "minimal"] | str] = Field( - default=None - ) - - include_thoughts: Optional[bool] = Field(default=None) + # Backward compatibility: ThinkingConfig used to be defined inline here. + ThinkingConfig = GoogleThinkingConfig class InputParams(BaseModel): """Input parameters for Google AI models. @@ -764,7 +766,7 @@ class GoogleLLMService(LLMService): temperature: Optional[float] = Field(default=None, ge=0.0, le=2.0) top_k: Optional[int] = Field(default=None, ge=0) top_p: Optional[float] = Field(default=None, ge=0.0, le=1.0) - thinking: Optional["GoogleLLMService.ThinkingConfig"] = Field(default=None) + thinking: Optional[GoogleThinkingConfig] = Field(default=None) extra: Optional[Dict[str, Any]] = Field(default_factory=dict) def __init__( From 63caa403cb51f092329d6ef554e4361a0c75ad6b Mon Sep 17 00:00:00 2001 From: filipi87 Date: Thu, 19 Feb 2026 17:31:25 -0300 Subject: [PATCH 0561/1060] Improving RTVI doc description. --- src/pipecat/processors/frameworks/rtvi.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/src/pipecat/processors/frameworks/rtvi.py b/src/pipecat/processors/frameworks/rtvi.py index a8b66ccdd..eb074699a 100644 --- a/src/pipecat/processors/frameworks/rtvi.py +++ b/src/pipecat/processors/frameworks/rtvi.py @@ -1220,7 +1220,7 @@ class RTVIObserver(BaseObserver): frame = data.frame direction = data.direction - # For broadcasted frames (pushed in both directions), only process + # For broadcast frames (pushed in both directions), only process # the downstream copy to avoid sending duplicate RTVI messages. if frame.broadcast_sibling_id is not None and direction != FrameDirection.DOWNSTREAM: return From 3a8d3cc8419228530c4c520210004c74181378c6 Mon Sep 17 00:00:00 2001 From: filipi87 Date: Thu, 19 Feb 2026 18:36:12 -0300 Subject: [PATCH 0562/1060] Allowing to define the list of frame processors whose frames should be silently ignored by the RTVI observer. --- .../53-concurrent-llm-rtvi-ignored-sources.py | 193 ++++++++++++++++++ src/pipecat/processors/frameworks/rtvi.py | 37 ++++ 2 files changed, 230 insertions(+) create mode 100644 examples/foundational/53-concurrent-llm-rtvi-ignored-sources.py diff --git a/examples/foundational/53-concurrent-llm-rtvi-ignored-sources.py b/examples/foundational/53-concurrent-llm-rtvi-ignored-sources.py new file mode 100644 index 000000000..c679a4cc4 --- /dev/null +++ b/examples/foundational/53-concurrent-llm-rtvi-ignored-sources.py @@ -0,0 +1,193 @@ +# +# Copyright (c) 2024-2026, Daily +# +# SPDX-License-Identifier: BSD 2-Clause License +# + +"""RTVIObserver ignored sources example. + +This example shows how to suppress RTVI messages from a specific pipeline +processor so that secondary branches don't leak events to the client. + +""" + +import os + +from dotenv import load_dotenv +from loguru import logger + +from pipecat.audio.vad.silero import SileroVADAnalyzer +from pipecat.frames.frames import LLMRunFrame +from pipecat.pipeline.parallel_pipeline import ParallelPipeline +from pipecat.pipeline.pipeline import Pipeline +from pipecat.pipeline.runner import PipelineRunner +from pipecat.pipeline.task import PipelineParams, PipelineTask +from pipecat.processors.aggregators.llm_context import LLMContext +from pipecat.processors.aggregators.llm_response_universal import ( + LLMContextAggregatorPair, + LLMUserAggregatorParams, +) +from pipecat.processors.audio.vad_processor import VADProcessor +from pipecat.processors.frameworks.rtvi import RTVIObserverParams +from pipecat.runner.types import RunnerArguments +from pipecat.runner.utils import create_transport +from pipecat.services.cartesia.tts import CartesiaTTSService +from pipecat.services.deepgram.stt import DeepgramSTTService +from pipecat.services.openai.llm import OpenAILLMService +from pipecat.transports.base_transport import BaseTransport, TransportParams +from pipecat.transports.daily.transport import DailyParams +from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams +from pipecat.turns.user_turn_processor import UserTurnProcessor +from pipecat.turns.user_turn_strategies import ExternalUserTurnStrategies + +load_dotenv(override=True) + +# We use lambdas to defer transport parameter creation until the transport +# type is selected at runtime. +transport_params = { + "daily": lambda: DailyParams( + audio_in_enabled=True, + audio_out_enabled=True, + ), + "twilio": lambda: FastAPIWebsocketParams( + audio_in_enabled=True, + audio_out_enabled=True, + ), + "webrtc": lambda: TransportParams( + audio_in_enabled=True, + audio_out_enabled=True, + ), +} + + +async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): + logger.info("Starting bot") + + stt = DeepgramSTTService(api_key=os.getenv("DEEPGRAM_API_KEY")) + + tts = CartesiaTTSService( + api_key=os.getenv("CARTESIA_API_KEY"), + voice_id="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady + ) + + # Main LLM — drives the conversation. Its RTVI events reach the client. + main_llm = OpenAILLMService(api_key=os.getenv("OPENAI_API_KEY")) + + main_messages = [ + { + "role": "system", + "content": "You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + }, + ] + + # Evaluator LLM — silently grades the user's message in the background. + # Its RTVI events will be suppressed so the client is unaware of this branch. + evaluator_llm = OpenAILLMService( + api_key=os.getenv("OPENAI_API_KEY"), + name="EvaluatorLLM", + ) + + evaluator_messages = [ + { + "role": "system", + "content": ( + "You are a silent quality evaluator. When given a user message, " + "respond with a single JSON object: " + '{"score": <1-5>, "reason": ""}. ' + "Do not respond conversationally." + ), + }, + ] + + main_context = LLMContext(main_messages) + evaluator_context = LLMContext(evaluator_messages) + + # We use an external VADProcessor because the UserTurnProcessor is shared + # across multiple parallel aggregators. The VADProcessor emits + # VADUserStartedSpeakingFrame and VADUserStoppedSpeakingFrame which the + # UserTurnProcessor needs to manage turn lifecycle. + vad_processor = VADProcessor(vad_analyzer=SileroVADAnalyzer()) + + # We use this external user turn processor. This processor will push + # UserStartedSpeakingFrame and UserStoppedSpeakingFrame as well as + # interruptions. This can be used in advanced cases when there are multiple + # aggregators in the pipeline. + user_turn_processor = UserTurnProcessor() + + # We use external user turn strategies for both aggregators since the turn + # management is done by the common UserTurnProcessor. + main_context_aggregator = LLMContextAggregatorPair( + main_context, + user_params=LLMUserAggregatorParams(user_turn_strategies=ExternalUserTurnStrategies()), + ) + evaluator_context_aggregator = LLMContextAggregatorPair( + evaluator_context, + user_params=LLMUserAggregatorParams(user_turn_strategies=ExternalUserTurnStrategies()), + ) + + pipeline = Pipeline( + [ + transport.input(), # Transport user input + stt, # STT + vad_processor, + user_turn_processor, + ParallelPipeline( + # Main branch: speaks to the user. + [ + main_context_aggregator.user(), + main_llm, + tts, + transport.output(), + main_context_aggregator.assistant(), + ], + # Evaluator branch: silent background scoring, no audio output. + [ + evaluator_context_aggregator.user(), + evaluator_llm, + evaluator_context_aggregator.assistant(), + ], + ), + ] + ) + + task = PipelineTask( + pipeline, + params=PipelineParams( + enable_metrics=True, + enable_usage_metrics=True, + ), + rtvi_observer_params=RTVIObserverParams( + ignored_sources=[evaluator_llm] + ), + idle_timeout_secs=runner_args.pipeline_idle_timeout_secs, + ) + + @transport.event_handler("on_client_connected") + async def on_client_connected(transport, client): + logger.info("Client connected") + main_messages.append( + {"role": "system", "content": "Please introduce yourself to the user."} + ) + evaluator_messages.append({"role": "system", "content": "Ready to evaluate user messages."}) + await task.queue_frames([LLMRunFrame()]) + + @transport.event_handler("on_client_disconnected") + async def on_client_disconnected(transport, client): + logger.info("Client disconnected") + await task.cancel() + + runner = PipelineRunner(handle_sigint=runner_args.handle_sigint) + + await runner.run(task) + + +async def bot(runner_args: RunnerArguments): + """Main bot entry point compatible with Pipecat Cloud.""" + transport = await create_transport(runner_args, transport_params) + await run_bot(transport, runner_args) + + +if __name__ == "__main__": + from pipecat.runner.run import main + + main() diff --git a/src/pipecat/processors/frameworks/rtvi.py b/src/pipecat/processors/frameworks/rtvi.py index eb074699a..e01e95714 100644 --- a/src/pipecat/processors/frameworks/rtvi.py +++ b/src/pipecat/processors/frameworks/rtvi.py @@ -25,6 +25,7 @@ from typing import ( Literal, Mapping, Optional, + Set, Tuple, Union, ) @@ -1026,6 +1027,11 @@ class RTVIObserverParams: metrics_enabled: Indicates if metrics messages should be sent. system_logs_enabled: Indicates if system logs should be sent. errors_enabled: [Deprecated] Indicates if errors messages should be sent. + ignored_sources: List of frame processors whose frames should be silently ignored + by this observer. Useful for suppressing RTVI messages from secondary pipeline + branches (e.g. a silent evaluation LLM) that should not be visible to clients. + Sources can also be added and removed dynamically via ``add_ignored_source()`` + and ``remove_ignored_source()``. skip_aggregator_types: List of aggregation types to skip sending as tts/output messages. Note: if using this to avoid sending secure information, be sure to also disable bot_llm_enabled to avoid leaking through LLM messages. @@ -1065,6 +1071,7 @@ class RTVIObserverParams: metrics_enabled: bool = True system_logs_enabled: bool = False errors_enabled: Optional[bool] = None + ignored_sources: List[FrameProcessor] = field(default_factory=list) skip_aggregator_types: Optional[List[AggregationType | str]] = None bot_output_transforms: Optional[ List[ @@ -1110,6 +1117,7 @@ class RTVIObserver(BaseObserver): self._rtvi = rtvi self._params = params or RTVIObserverParams() + self._ignored_sources: Set[FrameProcessor] = set(self._params.ignored_sources) self._frames_seen = set() self._bot_transcription = "" @@ -1170,6 +1178,31 @@ class RTVIObserver(BaseObserver): if not (agg_type == aggregation_type and func == transform_function) ] + def add_ignored_source(self, source: FrameProcessor): + """Ignore all frames pushed by the given processor. + + Any frame whose source matches ``source`` will be silently skipped, + preventing RTVI messages from being emitted for activity in that + processor. Useful for suppressing events from secondary pipeline + branches (e.g. a silent evaluation LLM) that should not be visible + to clients. + + Args: + source: The frame processor to ignore. + """ + self._ignored_sources.add(source) + + def remove_ignored_source(self, source: FrameProcessor): + """Stop ignoring frames pushed by the given processor. + + Reverses a previous call to ``add_ignored_source()``. If ``source`` + was not previously ignored this is a no-op. + + Args: + source: The frame processor to stop ignoring. + """ + self._ignored_sources.discard(source) + def _get_function_call_report_level(self, function_name: str) -> RTVIFunctionCallReportLevel: """Get the report level for a specific function call. @@ -1220,6 +1253,10 @@ class RTVIObserver(BaseObserver): frame = data.frame direction = data.direction + # Frames from explicitly ignored sources are always skipped. + if self._ignored_sources and src in self._ignored_sources: + return + # For broadcast frames (pushed in both directions), only process # the downstream copy to avoid sending duplicate RTVI messages. if frame.broadcast_sibling_id is not None and direction != FrameDirection.DOWNSTREAM: From 18630c94788f18d32b68751c9fe1a9383b6742eb Mon Sep 17 00:00:00 2001 From: filipi87 Date: Thu, 19 Feb 2026 18:41:05 -0300 Subject: [PATCH 0563/1060] Adding changelog entry for RTVI observer ignored_sources feature. --- changelog/3779.added.md | 1 + .../foundational/53-concurrent-llm-rtvi-ignored-sources.py | 4 +--- 2 files changed, 2 insertions(+), 3 deletions(-) create mode 100644 changelog/3779.added.md diff --git a/changelog/3779.added.md b/changelog/3779.added.md new file mode 100644 index 000000000..8800cfc04 --- /dev/null +++ b/changelog/3779.added.md @@ -0,0 +1 @@ +- Added `ignored_sources` parameter to `RTVIObserverParams` and `add_ignored_source()`/`remove_ignored_source()` methods to `RTVIObserver` to suppress RTVI messages from specific pipeline processors (e.g. a silent evaluation LLM). diff --git a/examples/foundational/53-concurrent-llm-rtvi-ignored-sources.py b/examples/foundational/53-concurrent-llm-rtvi-ignored-sources.py index c679a4cc4..b16f8831f 100644 --- a/examples/foundational/53-concurrent-llm-rtvi-ignored-sources.py +++ b/examples/foundational/53-concurrent-llm-rtvi-ignored-sources.py @@ -156,9 +156,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): enable_metrics=True, enable_usage_metrics=True, ), - rtvi_observer_params=RTVIObserverParams( - ignored_sources=[evaluator_llm] - ), + rtvi_observer_params=RTVIObserverParams(ignored_sources=[evaluator_llm]), idle_timeout_secs=runner_args.pipeline_idle_timeout_secs, ) From 6c609031ee8d6fc3262801d659ad6b700c76e817 Mon Sep 17 00:00:00 2001 From: Paul Kompfner Date: Thu, 19 Feb 2026 15:12:39 -0500 Subject: [PATCH 0564/1060] Add more 55-series examples Also: - remove unnecessary pass-through `_update_settings` implementation in `FalSTTService` - warn that `AsyncAITTSService` doesn't currently support runtime settings updates - update how `GradiumTTSService._update_settings` checks for voice changes - remove a couple of unnecessary args (because they specified defaults) in other examples --- .../14n-function-calling-perplexity.py | 2 +- .../14s-function-calling-sambanova.py | 5 +- .../55s-update-settings-google-stream-tts.py | 124 ++++++++++++++++ .../55u-update-settings-rime-http-tts.py | 128 ++++++++++++++++ .../55zb-update-settings-inworld-http-tts.py | 130 ++++++++++++++++ .../55ze-update-settings-sarvam-http-tts.py | 126 ++++++++++++++++ .../55zi-update-settings-azure-llm.py | 130 ++++++++++++++++ .../55zk-update-settings-google-vertex-llm.py | 130 ++++++++++++++++ .../55zl-update-settings-azure-realtime.py | 140 ++++++++++++++++++ ...55zm-update-settings-gemini-live-vertex.py | 117 +++++++++++++++ .../55zq-update-settings-fal-stt.py | 125 ++++++++++++++++ .../55zr-update-settings-gradium-stt.py | 128 ++++++++++++++++ .../55zs-update-settings-hathora-stt.py | 129 ++++++++++++++++ ...zt-update-settings-nvidia-segmented-stt.py | 127 ++++++++++++++++ .../55zt-update-settings-nvidia-stt.py | 128 ++++++++++++++++ ...5zu-update-settings-openai-realtime-stt.py | 128 ++++++++++++++++ .../55zv-update-settings-asyncai-http-tts.py | 133 +++++++++++++++++ .../55zv-update-settings-asyncai-tts.py | 128 ++++++++++++++++ .../55zw-update-settings-gradium-tts.py | 128 ++++++++++++++++ .../55zx-update-settings-cerebras-llm.py | 126 ++++++++++++++++ .../55zy-update-settings-deepseek-llm.py | 126 ++++++++++++++++ .../55zz-update-settings-fireworks-llm.py | 129 ++++++++++++++++ .../55zza-update-settings-grok-llm.py | 126 ++++++++++++++++ .../55zzb-update-settings-groq-llm.py | 128 ++++++++++++++++ .../55zzc-update-settings-mistral-llm.py | 126 ++++++++++++++++ .../55zzd-update-settings-nvidia-llm.py | 128 ++++++++++++++++ .../55zze-update-settings-ollama-llm.py | 126 ++++++++++++++++ .../55zzf-update-settings-openrouter-llm.py | 126 ++++++++++++++++ .../55zzg-update-settings-perplexity-llm.py | 125 ++++++++++++++++ .../55zzh-update-settings-qwen-llm.py | 126 ++++++++++++++++ .../55zzi-update-settings-sambanova-llm.py | 126 ++++++++++++++++ .../55zzj-update-settings-together-llm.py | 129 ++++++++++++++++ src/pipecat/services/asyncai/tts.py | 14 ++ src/pipecat/services/fal/stt.py | 5 - src/pipecat/services/gradium/tts.py | 3 +- 35 files changed, 3843 insertions(+), 12 deletions(-) create mode 100644 examples/foundational/55s-update-settings-google-stream-tts.py create mode 100644 examples/foundational/55u-update-settings-rime-http-tts.py create mode 100644 examples/foundational/55zb-update-settings-inworld-http-tts.py create mode 100644 examples/foundational/55ze-update-settings-sarvam-http-tts.py create mode 100644 examples/foundational/55zi-update-settings-azure-llm.py create mode 100644 examples/foundational/55zk-update-settings-google-vertex-llm.py create mode 100644 examples/foundational/55zl-update-settings-azure-realtime.py create mode 100644 examples/foundational/55zm-update-settings-gemini-live-vertex.py create mode 100644 examples/foundational/55zq-update-settings-fal-stt.py create mode 100644 examples/foundational/55zr-update-settings-gradium-stt.py create mode 100644 examples/foundational/55zs-update-settings-hathora-stt.py create mode 100644 examples/foundational/55zt-update-settings-nvidia-segmented-stt.py create mode 100644 examples/foundational/55zt-update-settings-nvidia-stt.py create mode 100644 examples/foundational/55zu-update-settings-openai-realtime-stt.py create mode 100644 examples/foundational/55zv-update-settings-asyncai-http-tts.py create mode 100644 examples/foundational/55zv-update-settings-asyncai-tts.py create mode 100644 examples/foundational/55zw-update-settings-gradium-tts.py create mode 100644 examples/foundational/55zx-update-settings-cerebras-llm.py create mode 100644 examples/foundational/55zy-update-settings-deepseek-llm.py create mode 100644 examples/foundational/55zz-update-settings-fireworks-llm.py create mode 100644 examples/foundational/55zza-update-settings-grok-llm.py create mode 100644 examples/foundational/55zzb-update-settings-groq-llm.py create mode 100644 examples/foundational/55zzc-update-settings-mistral-llm.py create mode 100644 examples/foundational/55zzd-update-settings-nvidia-llm.py create mode 100644 examples/foundational/55zze-update-settings-ollama-llm.py create mode 100644 examples/foundational/55zzf-update-settings-openrouter-llm.py create mode 100644 examples/foundational/55zzg-update-settings-perplexity-llm.py create mode 100644 examples/foundational/55zzh-update-settings-qwen-llm.py create mode 100644 examples/foundational/55zzi-update-settings-sambanova-llm.py create mode 100644 examples/foundational/55zzj-update-settings-together-llm.py diff --git a/examples/foundational/14n-function-calling-perplexity.py b/examples/foundational/14n-function-calling-perplexity.py index 40041aa34..2f1a18d52 100644 --- a/examples/foundational/14n-function-calling-perplexity.py +++ b/examples/foundational/14n-function-calling-perplexity.py @@ -65,7 +65,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): voice_id="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady ) - llm = PerplexityLLMService(api_key=os.getenv("PERPLEXITY_API_KEY"), model="sonar") + llm = PerplexityLLMService(api_key=os.getenv("PERPLEXITY_API_KEY")) messages = [ { diff --git a/examples/foundational/14s-function-calling-sambanova.py b/examples/foundational/14s-function-calling-sambanova.py index 79c43a473..76eb390c0 100644 --- a/examples/foundational/14s-function-calling-sambanova.py +++ b/examples/foundational/14s-function-calling-sambanova.py @@ -70,10 +70,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): voice_id="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady ) - llm = SambaNovaLLMService( - api_key=os.getenv("SAMBANOVA_API_KEY"), - model="Llama-4-Maverick-17B-128E-Instruct", - ) + llm = SambaNovaLLMService(api_key=os.getenv("SAMBANOVA_API_KEY")) # You can also register a function_name of None to get all functions # sent to the same callback with an additional function_name parameter. llm.register_function("get_current_weather", fetch_weather_from_api) diff --git a/examples/foundational/55s-update-settings-google-stream-tts.py b/examples/foundational/55s-update-settings-google-stream-tts.py new file mode 100644 index 000000000..42e07c64b --- /dev/null +++ b/examples/foundational/55s-update-settings-google-stream-tts.py @@ -0,0 +1,124 @@ +# +# Copyright (c) 2024-2026, Daily +# +# SPDX-License-Identifier: BSD 2-Clause License +# + +import asyncio +import os + +from dotenv import load_dotenv +from loguru import logger + +from pipecat.audio.vad.silero import SileroVADAnalyzer +from pipecat.frames.frames import LLMRunFrame, TTSUpdateSettingsFrame +from pipecat.pipeline.pipeline import Pipeline +from pipecat.pipeline.runner import PipelineRunner +from pipecat.pipeline.task import PipelineParams, PipelineTask +from pipecat.processors.aggregators.llm_context import LLMContext +from pipecat.processors.aggregators.llm_response_universal import ( + LLMContextAggregatorPair, + LLMUserAggregatorParams, +) +from pipecat.runner.types import RunnerArguments +from pipecat.runner.utils import create_transport +from pipecat.services.deepgram.stt import DeepgramSTTService +from pipecat.services.google.tts import GoogleStreamTTSSettings, GoogleTTSService +from pipecat.services.openai.llm import OpenAILLMService +from pipecat.transports.base_transport import BaseTransport, TransportParams +from pipecat.transports.daily.transport import DailyParams +from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams + +load_dotenv(override=True) + +transport_params = { + "daily": lambda: DailyParams( + audio_in_enabled=True, + audio_out_enabled=True, + ), + "twilio": lambda: FastAPIWebsocketParams( + audio_in_enabled=True, + audio_out_enabled=True, + ), + "webrtc": lambda: TransportParams( + audio_in_enabled=True, + audio_out_enabled=True, + ), +} + + +async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): + logger.info(f"Starting bot") + + stt = DeepgramSTTService(api_key=os.getenv("DEEPGRAM_API_KEY")) + + tts = GoogleTTSService(credentials=os.getenv("GOOGLE_TEST_CREDENTIALS")) + + llm = OpenAILLMService(api_key=os.getenv("OPENAI_API_KEY")) + + messages = [ + { + "role": "system", + "content": "You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + }, + ] + + context = LLMContext(messages) + user_aggregator, assistant_aggregator = LLMContextAggregatorPair( + context, + user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()), + ) + + pipeline = Pipeline( + [ + transport.input(), + stt, + user_aggregator, + llm, + tts, + transport.output(), + assistant_aggregator, + ] + ) + + task = PipelineTask( + pipeline, + params=PipelineParams( + enable_metrics=True, + enable_usage_metrics=True, + ), + idle_timeout_secs=runner_args.pipeline_idle_timeout_secs, + ) + + @transport.event_handler("on_client_connected") + async def on_client_connected(transport, client): + logger.info(f"Client connected") + messages.append({"role": "system", "content": "Please introduce yourself to the user."}) + await task.queue_frames([LLMRunFrame()]) + + await asyncio.sleep(10) + logger.info("Updating Google Stream TTS settings: speaking_rate=1.4") + await task.queue_frame( + TTSUpdateSettingsFrame(update=GoogleStreamTTSSettings(speaking_rate=1.4)) + ) + + @transport.event_handler("on_client_disconnected") + async def on_client_disconnected(transport, client): + logger.info(f"Client disconnected") + await task.cancel() + + runner = PipelineRunner(handle_sigint=runner_args.handle_sigint) + + await runner.run(task) + + +async def bot(runner_args: RunnerArguments): + """Main bot entry point compatible with Pipecat Cloud.""" + transport = await create_transport(runner_args, transport_params) + await run_bot(transport, runner_args) + + +if __name__ == "__main__": + from pipecat.runner.run import main + + main() diff --git a/examples/foundational/55u-update-settings-rime-http-tts.py b/examples/foundational/55u-update-settings-rime-http-tts.py new file mode 100644 index 000000000..7b1c9b0fe --- /dev/null +++ b/examples/foundational/55u-update-settings-rime-http-tts.py @@ -0,0 +1,128 @@ +# +# Copyright (c) 2024-2026, Daily +# +# SPDX-License-Identifier: BSD 2-Clause License +# + + +import asyncio +import os + +import aiohttp +from dotenv import load_dotenv +from loguru import logger + +from pipecat.audio.vad.silero import SileroVADAnalyzer +from pipecat.frames.frames import LLMRunFrame, TTSUpdateSettingsFrame +from pipecat.pipeline.pipeline import Pipeline +from pipecat.pipeline.runner import PipelineRunner +from pipecat.pipeline.task import PipelineParams, PipelineTask +from pipecat.processors.aggregators.llm_context import LLMContext +from pipecat.processors.aggregators.llm_response_universal import ( + LLMContextAggregatorPair, + LLMUserAggregatorParams, +) +from pipecat.runner.types import RunnerArguments +from pipecat.runner.utils import create_transport +from pipecat.services.deepgram.stt import DeepgramSTTService +from pipecat.services.openai.llm import OpenAILLMService +from pipecat.services.rime.tts import RimeHttpTTSService, RimeTTSSettings +from pipecat.transports.base_transport import BaseTransport, TransportParams +from pipecat.transports.daily.transport import DailyParams +from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams + +load_dotenv(override=True) + + +transport_params = { + "daily": lambda: DailyParams( + audio_in_enabled=True, + audio_out_enabled=True, + ), + "twilio": lambda: FastAPIWebsocketParams( + audio_in_enabled=True, + audio_out_enabled=True, + ), + "webrtc": lambda: TransportParams( + audio_in_enabled=True, + audio_out_enabled=True, + ), +} + + +async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): + logger.info(f"Starting bot") + + async with aiohttp.ClientSession() as session: + stt = DeepgramSTTService(api_key=os.getenv("DEEPGRAM_API_KEY")) + + tts = RimeHttpTTSService( + api_key=os.getenv("RIME_API_KEY"), voice_id="eva", aiohttp_session=session + ) + + llm = OpenAILLMService(api_key=os.getenv("OPENAI_API_KEY")) + + messages = [ + { + "role": "system", + "content": "You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + }, + ] + + context = LLMContext(messages) + user_aggregator, assistant_aggregator = LLMContextAggregatorPair( + context, + user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()), + ) + + pipeline = Pipeline( + [ + transport.input(), + stt, + user_aggregator, + llm, + tts, + transport.output(), + assistant_aggregator, + ] + ) + + task = PipelineTask( + pipeline, + params=PipelineParams( + enable_metrics=True, + enable_usage_metrics=True, + ), + idle_timeout_secs=runner_args.pipeline_idle_timeout_secs, + ) + + @transport.event_handler("on_client_connected") + async def on_client_connected(transport, client): + logger.info(f"Client connected") + messages.append({"role": "system", "content": "Please introduce yourself to the user."}) + await task.queue_frames([LLMRunFrame()]) + + await asyncio.sleep(10) + logger.info("Updating Rime TTS settings: voice=rex") + await task.queue_frame(TTSUpdateSettingsFrame(update=RimeTTSSettings(voice="rex"))) + + @transport.event_handler("on_client_disconnected") + async def on_client_disconnected(transport, client): + logger.info(f"Client disconnected") + await task.cancel() + + runner = PipelineRunner(handle_sigint=runner_args.handle_sigint) + + await runner.run(task) + + +async def bot(runner_args: RunnerArguments): + """Main bot entry point compatible with Pipecat Cloud.""" + transport = await create_transport(runner_args, transport_params) + await run_bot(transport, runner_args) + + +if __name__ == "__main__": + from pipecat.runner.run import main + + main() diff --git a/examples/foundational/55zb-update-settings-inworld-http-tts.py b/examples/foundational/55zb-update-settings-inworld-http-tts.py new file mode 100644 index 000000000..933a27013 --- /dev/null +++ b/examples/foundational/55zb-update-settings-inworld-http-tts.py @@ -0,0 +1,130 @@ +# +# Copyright (c) 2024-2026, Daily +# +# SPDX-License-Identifier: BSD 2-Clause License +# + + +import asyncio +import os + +import aiohttp +from dotenv import load_dotenv +from loguru import logger + +from pipecat.audio.vad.silero import SileroVADAnalyzer +from pipecat.frames.frames import LLMRunFrame, TTSUpdateSettingsFrame +from pipecat.pipeline.pipeline import Pipeline +from pipecat.pipeline.runner import PipelineRunner +from pipecat.pipeline.task import PipelineParams, PipelineTask +from pipecat.processors.aggregators.llm_context import LLMContext +from pipecat.processors.aggregators.llm_response_universal import ( + LLMContextAggregatorPair, + LLMUserAggregatorParams, +) +from pipecat.runner.types import RunnerArguments +from pipecat.runner.utils import create_transport +from pipecat.services.deepgram.stt import DeepgramSTTService +from pipecat.services.inworld.tts import InworldHttpTTSService, InworldTTSSettings +from pipecat.services.openai.llm import OpenAILLMService +from pipecat.transports.base_transport import BaseTransport, TransportParams +from pipecat.transports.daily.transport import DailyParams +from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams + +load_dotenv(override=True) + + +transport_params = { + "daily": lambda: DailyParams( + audio_in_enabled=True, + audio_out_enabled=True, + ), + "twilio": lambda: FastAPIWebsocketParams( + audio_in_enabled=True, + audio_out_enabled=True, + ), + "webrtc": lambda: TransportParams( + audio_in_enabled=True, + audio_out_enabled=True, + ), +} + + +async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): + logger.info(f"Starting bot") + + async with aiohttp.ClientSession() as session: + stt = DeepgramSTTService(api_key=os.getenv("DEEPGRAM_API_KEY")) + + tts = InworldHttpTTSService(api_key=os.getenv("INWORLD_API_KEY"), aiohttp_session=session) + + llm = OpenAILLMService(api_key=os.getenv("OPENAI_API_KEY")) + + messages = [ + { + "role": "system", + "content": "You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + }, + ] + + context = LLMContext(messages) + user_aggregator, assistant_aggregator = LLMContextAggregatorPair( + context, + user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()), + ) + + pipeline = Pipeline( + [ + transport.input(), + stt, + user_aggregator, + llm, + tts, + transport.output(), + assistant_aggregator, + ] + ) + + task = PipelineTask( + pipeline, + params=PipelineParams( + enable_metrics=True, + enable_usage_metrics=True, + ), + idle_timeout_secs=runner_args.pipeline_idle_timeout_secs, + ) + + @transport.event_handler("on_client_connected") + async def on_client_connected(transport, client): + logger.info(f"Client connected") + messages.append({"role": "system", "content": "Please introduce yourself to the user."}) + await task.queue_frames([LLMRunFrame()]) + + await asyncio.sleep(10) + logger.info("Updating Inworld TTS settings: speaking_rate=1.5, temperature=0.8") + await task.queue_frame( + TTSUpdateSettingsFrame( + update=InworldTTSSettings(speaking_rate=1.5, temperature=0.8) + ) + ) + + @transport.event_handler("on_client_disconnected") + async def on_client_disconnected(transport, client): + logger.info(f"Client disconnected") + await task.cancel() + + runner = PipelineRunner(handle_sigint=runner_args.handle_sigint) + + await runner.run(task) + + +async def bot(runner_args: RunnerArguments): + """Main bot entry point compatible with Pipecat Cloud.""" + transport = await create_transport(runner_args, transport_params) + await run_bot(transport, runner_args) + + +if __name__ == "__main__": + from pipecat.runner.run import main + + main() diff --git a/examples/foundational/55ze-update-settings-sarvam-http-tts.py b/examples/foundational/55ze-update-settings-sarvam-http-tts.py new file mode 100644 index 000000000..0afce361a --- /dev/null +++ b/examples/foundational/55ze-update-settings-sarvam-http-tts.py @@ -0,0 +1,126 @@ +# +# Copyright (c) 2024-2026, Daily +# +# SPDX-License-Identifier: BSD 2-Clause License +# + + +import asyncio +import os + +import aiohttp +from dotenv import load_dotenv +from loguru import logger + +from pipecat.audio.vad.silero import SileroVADAnalyzer +from pipecat.frames.frames import LLMRunFrame, TTSUpdateSettingsFrame +from pipecat.pipeline.pipeline import Pipeline +from pipecat.pipeline.runner import PipelineRunner +from pipecat.pipeline.task import PipelineParams, PipelineTask +from pipecat.processors.aggregators.llm_context import LLMContext +from pipecat.processors.aggregators.llm_response_universal import ( + LLMContextAggregatorPair, + LLMUserAggregatorParams, +) +from pipecat.runner.types import RunnerArguments +from pipecat.runner.utils import create_transport +from pipecat.services.deepgram.stt import DeepgramSTTService +from pipecat.services.openai.llm import OpenAILLMService +from pipecat.services.sarvam.tts import SarvamHttpTTSService, SarvamHttpTTSSettings +from pipecat.transports.base_transport import BaseTransport, TransportParams +from pipecat.transports.daily.transport import DailyParams +from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams + +load_dotenv(override=True) + + +transport_params = { + "daily": lambda: DailyParams( + audio_in_enabled=True, + audio_out_enabled=True, + ), + "twilio": lambda: FastAPIWebsocketParams( + audio_in_enabled=True, + audio_out_enabled=True, + ), + "webrtc": lambda: TransportParams( + audio_in_enabled=True, + audio_out_enabled=True, + ), +} + + +async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): + logger.info(f"Starting bot") + + async with aiohttp.ClientSession() as session: + stt = DeepgramSTTService(api_key=os.getenv("DEEPGRAM_API_KEY")) + + tts = SarvamHttpTTSService(api_key=os.getenv("SARVAM_API_KEY"), aiohttp_session=session) + + llm = OpenAILLMService(api_key=os.getenv("OPENAI_API_KEY")) + + messages = [ + { + "role": "system", + "content": "You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + }, + ] + + context = LLMContext(messages) + user_aggregator, assistant_aggregator = LLMContextAggregatorPair( + context, + user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()), + ) + + pipeline = Pipeline( + [ + transport.input(), + stt, + user_aggregator, + llm, + tts, + transport.output(), + assistant_aggregator, + ] + ) + + task = PipelineTask( + pipeline, + params=PipelineParams( + enable_metrics=True, + enable_usage_metrics=True, + ), + idle_timeout_secs=runner_args.pipeline_idle_timeout_secs, + ) + + @transport.event_handler("on_client_connected") + async def on_client_connected(transport, client): + logger.info(f"Client connected") + messages.append({"role": "system", "content": "Please introduce yourself to the user."}) + await task.queue_frames([LLMRunFrame()]) + + await asyncio.sleep(10) + logger.info("Updating Sarvam TTS settings: pace=1.5") + await task.queue_frame(TTSUpdateSettingsFrame(update=SarvamHttpTTSSettings(pace=1.5))) + + @transport.event_handler("on_client_disconnected") + async def on_client_disconnected(transport, client): + logger.info(f"Client disconnected") + await task.cancel() + + runner = PipelineRunner(handle_sigint=runner_args.handle_sigint) + + await runner.run(task) + + +async def bot(runner_args: RunnerArguments): + """Main bot entry point compatible with Pipecat Cloud.""" + transport = await create_transport(runner_args, transport_params) + await run_bot(transport, runner_args) + + +if __name__ == "__main__": + from pipecat.runner.run import main + + main() diff --git a/examples/foundational/55zi-update-settings-azure-llm.py b/examples/foundational/55zi-update-settings-azure-llm.py new file mode 100644 index 000000000..94cb723e3 --- /dev/null +++ b/examples/foundational/55zi-update-settings-azure-llm.py @@ -0,0 +1,130 @@ +# +# Copyright (c) 2024-2026, Daily +# +# SPDX-License-Identifier: BSD 2-Clause License +# + +import asyncio +import os + +from dotenv import load_dotenv +from loguru import logger + +from pipecat.audio.vad.silero import SileroVADAnalyzer +from pipecat.frames.frames import LLMRunFrame, LLMUpdateSettingsFrame +from pipecat.pipeline.pipeline import Pipeline +from pipecat.pipeline.runner import PipelineRunner +from pipecat.pipeline.task import PipelineParams, PipelineTask +from pipecat.processors.aggregators.llm_context import LLMContext +from pipecat.processors.aggregators.llm_response_universal import ( + LLMContextAggregatorPair, + LLMUserAggregatorParams, +) +from pipecat.runner.types import RunnerArguments +from pipecat.runner.utils import create_transport +from pipecat.services.azure.llm import AzureLLMService +from pipecat.services.cartesia.tts import CartesiaTTSService +from pipecat.services.deepgram.stt import DeepgramSTTService +from pipecat.services.openai.base_llm import OpenAILLMSettings +from pipecat.transports.base_transport import BaseTransport, TransportParams +from pipecat.transports.daily.transport import DailyParams +from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams + +load_dotenv(override=True) + +transport_params = { + "daily": lambda: DailyParams( + audio_in_enabled=True, + audio_out_enabled=True, + ), + "twilio": lambda: FastAPIWebsocketParams( + audio_in_enabled=True, + audio_out_enabled=True, + ), + "webrtc": lambda: TransportParams( + audio_in_enabled=True, + audio_out_enabled=True, + ), +} + + +async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): + logger.info(f"Starting bot") + + stt = DeepgramSTTService(api_key=os.getenv("DEEPGRAM_API_KEY")) + + tts = CartesiaTTSService( + api_key=os.getenv("CARTESIA_API_KEY"), + voice_id="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady + ) + + llm = AzureLLMService( + api_key=os.getenv("AZURE_CHATGPT_API_KEY"), + endpoint=os.getenv("AZURE_CHATGPT_ENDPOINT"), + model=os.getenv("AZURE_CHATGPT_MODEL"), + ) + + messages = [ + { + "role": "system", + "content": "You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + }, + ] + + context = LLMContext(messages) + user_aggregator, assistant_aggregator = LLMContextAggregatorPair( + context, + user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()), + ) + + pipeline = Pipeline( + [ + transport.input(), + stt, + user_aggregator, + llm, + tts, + transport.output(), + assistant_aggregator, + ] + ) + + task = PipelineTask( + pipeline, + params=PipelineParams( + enable_metrics=True, + enable_usage_metrics=True, + ), + idle_timeout_secs=runner_args.pipeline_idle_timeout_secs, + ) + + @transport.event_handler("on_client_connected") + async def on_client_connected(transport, client): + logger.info(f"Client connected") + messages.append({"role": "system", "content": "Please introduce yourself to the user."}) + await task.queue_frames([LLMRunFrame()]) + + await asyncio.sleep(10) + logger.info("Updating Azure LLM settings: temperature=0.1") + await task.queue_frame(LLMUpdateSettingsFrame(update=OpenAILLMSettings(temperature=0.1))) + + @transport.event_handler("on_client_disconnected") + async def on_client_disconnected(transport, client): + logger.info(f"Client disconnected") + await task.cancel() + + runner = PipelineRunner(handle_sigint=runner_args.handle_sigint) + + await runner.run(task) + + +async def bot(runner_args: RunnerArguments): + """Main bot entry point compatible with Pipecat Cloud.""" + transport = await create_transport(runner_args, transport_params) + await run_bot(transport, runner_args) + + +if __name__ == "__main__": + from pipecat.runner.run import main + + main() diff --git a/examples/foundational/55zk-update-settings-google-vertex-llm.py b/examples/foundational/55zk-update-settings-google-vertex-llm.py new file mode 100644 index 000000000..41c0b8a37 --- /dev/null +++ b/examples/foundational/55zk-update-settings-google-vertex-llm.py @@ -0,0 +1,130 @@ +# +# Copyright (c) 2024-2026, Daily +# +# SPDX-License-Identifier: BSD 2-Clause License +# + +import asyncio +import os + +from dotenv import load_dotenv +from loguru import logger + +from pipecat.audio.vad.silero import SileroVADAnalyzer +from pipecat.frames.frames import LLMRunFrame, LLMUpdateSettingsFrame +from pipecat.pipeline.pipeline import Pipeline +from pipecat.pipeline.runner import PipelineRunner +from pipecat.pipeline.task import PipelineParams, PipelineTask +from pipecat.processors.aggregators.llm_context import LLMContext +from pipecat.processors.aggregators.llm_response_universal import ( + LLMContextAggregatorPair, + LLMUserAggregatorParams, +) +from pipecat.runner.types import RunnerArguments +from pipecat.runner.utils import create_transport +from pipecat.services.cartesia.tts import CartesiaTTSService +from pipecat.services.deepgram.stt import DeepgramSTTService +from pipecat.services.google.llm import GoogleLLMSettings +from pipecat.services.google.llm_vertex import GoogleVertexLLMService +from pipecat.transports.base_transport import BaseTransport, TransportParams +from pipecat.transports.daily.transport import DailyParams +from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams + +load_dotenv(override=True) + +transport_params = { + "daily": lambda: DailyParams( + audio_in_enabled=True, + audio_out_enabled=True, + ), + "twilio": lambda: FastAPIWebsocketParams( + audio_in_enabled=True, + audio_out_enabled=True, + ), + "webrtc": lambda: TransportParams( + audio_in_enabled=True, + audio_out_enabled=True, + ), +} + + +async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): + logger.info(f"Starting bot") + + stt = DeepgramSTTService(api_key=os.getenv("DEEPGRAM_API_KEY")) + + tts = CartesiaTTSService( + api_key=os.getenv("CARTESIA_API_KEY"), + voice_id="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady + ) + + llm = GoogleVertexLLMService( + credentials=os.getenv("GOOGLE_VERTEX_TEST_CREDENTIALS"), + project_id=os.getenv("GOOGLE_CLOUD_PROJECT_ID"), + location=os.getenv("GOOGLE_CLOUD_LOCATION"), + ) + + messages = [ + { + "role": "system", + "content": "You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + }, + ] + + context = LLMContext(messages) + user_aggregator, assistant_aggregator = LLMContextAggregatorPair( + context, + user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()), + ) + + pipeline = Pipeline( + [ + transport.input(), + stt, + user_aggregator, + llm, + tts, + transport.output(), + assistant_aggregator, + ] + ) + + task = PipelineTask( + pipeline, + params=PipelineParams( + enable_metrics=True, + enable_usage_metrics=True, + ), + idle_timeout_secs=runner_args.pipeline_idle_timeout_secs, + ) + + @transport.event_handler("on_client_connected") + async def on_client_connected(transport, client): + logger.info(f"Client connected") + messages.append({"role": "system", "content": "Please introduce yourself to the user."}) + await task.queue_frames([LLMRunFrame()]) + + await asyncio.sleep(10) + logger.info("Updating Google Vertex LLM settings: temperature=0.1") + await task.queue_frame(LLMUpdateSettingsFrame(update=GoogleLLMSettings(temperature=0.1))) + + @transport.event_handler("on_client_disconnected") + async def on_client_disconnected(transport, client): + logger.info(f"Client disconnected") + await task.cancel() + + runner = PipelineRunner(handle_sigint=runner_args.handle_sigint) + + await runner.run(task) + + +async def bot(runner_args: RunnerArguments): + """Main bot entry point compatible with Pipecat Cloud.""" + transport = await create_transport(runner_args, transport_params) + await run_bot(transport, runner_args) + + +if __name__ == "__main__": + from pipecat.runner.run import main + + main() diff --git a/examples/foundational/55zl-update-settings-azure-realtime.py b/examples/foundational/55zl-update-settings-azure-realtime.py new file mode 100644 index 000000000..b8f049db0 --- /dev/null +++ b/examples/foundational/55zl-update-settings-azure-realtime.py @@ -0,0 +1,140 @@ +# +# Copyright (c) 2024-2026, Daily +# +# SPDX-License-Identifier: BSD 2-Clause License +# + +import asyncio +import os + +from dotenv import load_dotenv +from loguru import logger + +from pipecat.audio.vad.silero import SileroVADAnalyzer +from pipecat.frames.frames import LLMRunFrame, LLMUpdateSettingsFrame +from pipecat.pipeline.pipeline import Pipeline +from pipecat.pipeline.runner import PipelineRunner +from pipecat.pipeline.task import PipelineParams, PipelineTask +from pipecat.processors.aggregators.llm_context import LLMContext +from pipecat.processors.aggregators.llm_response_universal import ( + AssistantTurnStoppedMessage, + LLMContextAggregatorPair, +) +from pipecat.runner.types import RunnerArguments +from pipecat.runner.utils import create_transport +from pipecat.services.azure.realtime.llm import AzureRealtimeLLMService +from pipecat.services.openai.realtime import events +from pipecat.services.openai.realtime.llm import OpenAIRealtimeLLMSettings +from pipecat.transports.base_transport import BaseTransport, TransportParams +from pipecat.transports.daily.transport import DailyParams +from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams + +load_dotenv(override=True) + +transport_params = { + "daily": lambda: DailyParams( + audio_in_enabled=True, + audio_out_enabled=True, + vad_analyzer=SileroVADAnalyzer(), + ), + "twilio": lambda: FastAPIWebsocketParams( + audio_in_enabled=True, + audio_out_enabled=True, + vad_analyzer=SileroVADAnalyzer(), + ), + "webrtc": lambda: TransportParams( + audio_in_enabled=True, + audio_out_enabled=True, + vad_analyzer=SileroVADAnalyzer(), + ), +} + + +async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): + logger.info(f"Starting bot") + + llm = AzureRealtimeLLMService( + api_key=os.getenv("AZURE_REALTIME_API_KEY"), + base_url=os.getenv("AZURE_REALTIME_BASE_URL"), + ) + + messages = [ + { + "role": "system", + "content": "You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + }, + ] + + context = LLMContext(messages) + user_aggregator, assistant_aggregator = LLMContextAggregatorPair(context) + + pipeline = Pipeline( + [ + transport.input(), + user_aggregator, + llm, + transport.output(), + assistant_aggregator, + ] + ) + + task = PipelineTask( + pipeline, + params=PipelineParams( + enable_metrics=True, + enable_usage_metrics=True, + ), + idle_timeout_secs=runner_args.pipeline_idle_timeout_secs, + ) + + @assistant_aggregator.event_handler("on_assistant_turn_stopped") + async def on_assistant_turn_stopped(aggregator, message: AssistantTurnStoppedMessage): + timestamp = f"[{message.timestamp}] " if message.timestamp else "" + line = f"{timestamp}assistant: {message.content}" + logger.info(f"Transcript: {line}") + + @transport.event_handler("on_client_connected") + async def on_client_connected(transport, client): + logger.info(f"Client connected") + await task.queue_frames([LLMRunFrame()]) + + await asyncio.sleep(10) + logger.info("Updating Azure Realtime LLM settings: output_modalities=['text']") + await task.queue_frame( + LLMUpdateSettingsFrame( + update=OpenAIRealtimeLLMSettings( + session_properties=events.SessionProperties(output_modalities=["text"]) + ) + ) + ) + + await asyncio.sleep(10) + logger.info("Updating Azure Realtime LLM settings: output_modalities=['audio']") + await task.queue_frame( + LLMUpdateSettingsFrame( + update=OpenAIRealtimeLLMSettings( + session_properties=events.SessionProperties(output_modalities=["audio"]) + ) + ) + ) + + @transport.event_handler("on_client_disconnected") + async def on_client_disconnected(transport, client): + logger.info(f"Client disconnected") + await task.cancel() + + runner = PipelineRunner(handle_sigint=runner_args.handle_sigint) + + await runner.run(task) + + +async def bot(runner_args: RunnerArguments): + """Main bot entry point compatible with Pipecat Cloud.""" + transport = await create_transport(runner_args, transport_params) + await run_bot(transport, runner_args) + + +if __name__ == "__main__": + from pipecat.runner.run import main + + main() diff --git a/examples/foundational/55zm-update-settings-gemini-live-vertex.py b/examples/foundational/55zm-update-settings-gemini-live-vertex.py new file mode 100644 index 000000000..575fbe090 --- /dev/null +++ b/examples/foundational/55zm-update-settings-gemini-live-vertex.py @@ -0,0 +1,117 @@ +# +# Copyright (c) 2024-2026, Daily +# +# SPDX-License-Identifier: BSD 2-Clause License +# + +import asyncio +import os + +from dotenv import load_dotenv +from loguru import logger + +from pipecat.audio.vad.silero import SileroVADAnalyzer +from pipecat.frames.frames import LLMRunFrame, LLMUpdateSettingsFrame +from pipecat.pipeline.pipeline import Pipeline +from pipecat.pipeline.runner import PipelineRunner +from pipecat.pipeline.task import PipelineParams, PipelineTask +from pipecat.processors.aggregators.llm_context import LLMContext +from pipecat.processors.aggregators.llm_response_universal import LLMContextAggregatorPair +from pipecat.runner.types import RunnerArguments +from pipecat.runner.utils import create_transport +from pipecat.services.google.gemini_live.llm import GeminiLiveLLMSettings +from pipecat.services.google.gemini_live.llm_vertex import GeminiLiveVertexLLMService +from pipecat.transports.base_transport import BaseTransport, TransportParams +from pipecat.transports.daily.transport import DailyParams +from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams + +load_dotenv(override=True) + +transport_params = { + "daily": lambda: DailyParams( + audio_in_enabled=True, + audio_out_enabled=True, + vad_analyzer=SileroVADAnalyzer(), + ), + "twilio": lambda: FastAPIWebsocketParams( + audio_in_enabled=True, + audio_out_enabled=True, + vad_analyzer=SileroVADAnalyzer(), + ), + "webrtc": lambda: TransportParams( + audio_in_enabled=True, + audio_out_enabled=True, + vad_analyzer=SileroVADAnalyzer(), + ), +} + + +async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): + logger.info(f"Starting bot") + + llm = GeminiLiveVertexLLMService( + credentials=os.getenv("GOOGLE_VERTEX_TEST_CREDENTIALS"), + project_id=os.getenv("GOOGLE_CLOUD_PROJECT_ID"), + location=os.getenv("GOOGLE_CLOUD_LOCATION"), + ) + + messages = [ + { + "role": "system", + "content": "You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + }, + ] + + context = LLMContext(messages) + user_aggregator, assistant_aggregator = LLMContextAggregatorPair(context) + + pipeline = Pipeline( + [ + transport.input(), + user_aggregator, + llm, + transport.output(), + assistant_aggregator, + ] + ) + + task = PipelineTask( + pipeline, + params=PipelineParams( + enable_metrics=True, + enable_usage_metrics=True, + ), + idle_timeout_secs=runner_args.pipeline_idle_timeout_secs, + ) + + @transport.event_handler("on_client_connected") + async def on_client_connected(transport, client): + logger.info(f"Client connected") + await task.queue_frames([LLMRunFrame()]) + + await asyncio.sleep(10) + logger.info("Updating Gemini Live Vertex LLM settings: temperature=0.1") + await task.queue_frame( + LLMUpdateSettingsFrame(update=GeminiLiveLLMSettings(temperature=0.1)) + ) + + @transport.event_handler("on_client_disconnected") + async def on_client_disconnected(transport, client): + logger.info(f"Client disconnected") + await task.cancel() + + runner = PipelineRunner(handle_sigint=runner_args.handle_sigint) + + await runner.run(task) + + +async def bot(runner_args: RunnerArguments): + """Main bot entry point compatible with Pipecat Cloud.""" + transport = await create_transport(runner_args, transport_params) + await run_bot(transport, runner_args) + + +if __name__ == "__main__": + from pipecat.runner.run import main + + main() diff --git a/examples/foundational/55zq-update-settings-fal-stt.py b/examples/foundational/55zq-update-settings-fal-stt.py new file mode 100644 index 000000000..9792961f2 --- /dev/null +++ b/examples/foundational/55zq-update-settings-fal-stt.py @@ -0,0 +1,125 @@ +# +# Copyright (c) 2024-2026, Daily +# +# SPDX-License-Identifier: BSD 2-Clause License +# + +import asyncio +import os + +from dotenv import load_dotenv +from loguru import logger + +from pipecat.audio.vad.silero import SileroVADAnalyzer +from pipecat.frames.frames import LLMRunFrame, STTUpdateSettingsFrame +from pipecat.pipeline.pipeline import Pipeline +from pipecat.pipeline.runner import PipelineRunner +from pipecat.pipeline.task import PipelineParams, PipelineTask +from pipecat.processors.aggregators.llm_context import LLMContext +from pipecat.processors.aggregators.llm_response_universal import ( + LLMContextAggregatorPair, + LLMUserAggregatorParams, +) +from pipecat.runner.types import RunnerArguments +from pipecat.runner.utils import create_transport +from pipecat.services.cartesia.tts import CartesiaTTSService +from pipecat.services.fal.stt import FalSTTService, FalSTTSettings +from pipecat.services.openai.llm import OpenAILLMService +from pipecat.transports.base_transport import BaseTransport, TransportParams +from pipecat.transports.daily.transport import DailyParams +from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams + +load_dotenv(override=True) + +transport_params = { + "daily": lambda: DailyParams( + audio_in_enabled=True, + audio_out_enabled=True, + ), + "twilio": lambda: FastAPIWebsocketParams( + audio_in_enabled=True, + audio_out_enabled=True, + ), + "webrtc": lambda: TransportParams( + audio_in_enabled=True, + audio_out_enabled=True, + ), +} + + +async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): + logger.info(f"Starting bot") + + stt = FalSTTService(api_key=os.getenv("FAL_KEY")) + + tts = CartesiaTTSService( + api_key=os.getenv("CARTESIA_API_KEY"), + voice_id="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady + ) + + llm = OpenAILLMService(api_key=os.getenv("OPENAI_API_KEY")) + + messages = [ + { + "role": "system", + "content": "You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + }, + ] + + context = LLMContext(messages) + user_aggregator, assistant_aggregator = LLMContextAggregatorPair( + context, + user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()), + ) + + pipeline = Pipeline( + [ + transport.input(), + stt, + user_aggregator, + llm, + tts, + transport.output(), + assistant_aggregator, + ] + ) + + task = PipelineTask( + pipeline, + params=PipelineParams( + enable_metrics=True, + enable_usage_metrics=True, + ), + idle_timeout_secs=runner_args.pipeline_idle_timeout_secs, + ) + + @transport.event_handler("on_client_connected") + async def on_client_connected(transport, client): + logger.info(f"Client connected") + messages.append({"role": "system", "content": "Please introduce yourself to the user."}) + await task.queue_frames([LLMRunFrame()]) + + await asyncio.sleep(10) + logger.info('Updating Fal STT settings: task="translate"') + await task.queue_frame(STTUpdateSettingsFrame(update=FalSTTSettings(task="translate"))) + + @transport.event_handler("on_client_disconnected") + async def on_client_disconnected(transport, client): + logger.info(f"Client disconnected") + await task.cancel() + + runner = PipelineRunner(handle_sigint=runner_args.handle_sigint) + + await runner.run(task) + + +async def bot(runner_args: RunnerArguments): + """Main bot entry point compatible with Pipecat Cloud.""" + transport = await create_transport(runner_args, transport_params) + await run_bot(transport, runner_args) + + +if __name__ == "__main__": + from pipecat.runner.run import main + + main() diff --git a/examples/foundational/55zr-update-settings-gradium-stt.py b/examples/foundational/55zr-update-settings-gradium-stt.py new file mode 100644 index 000000000..6a1a25c3c --- /dev/null +++ b/examples/foundational/55zr-update-settings-gradium-stt.py @@ -0,0 +1,128 @@ +# +# Copyright (c) 2024-2026, Daily +# +# SPDX-License-Identifier: BSD 2-Clause License +# + +import asyncio +import os + +from dotenv import load_dotenv +from loguru import logger + +from pipecat.audio.vad.silero import SileroVADAnalyzer +from pipecat.frames.frames import LLMRunFrame, STTUpdateSettingsFrame +from pipecat.pipeline.pipeline import Pipeline +from pipecat.pipeline.runner import PipelineRunner +from pipecat.pipeline.task import PipelineParams, PipelineTask +from pipecat.processors.aggregators.llm_context import LLMContext +from pipecat.processors.aggregators.llm_response_universal import ( + LLMContextAggregatorPair, + LLMUserAggregatorParams, +) +from pipecat.runner.types import RunnerArguments +from pipecat.runner.utils import create_transport +from pipecat.services.cartesia.tts import CartesiaTTSService +from pipecat.services.gradium.stt import GradiumSTTService, GradiumSTTSettings +from pipecat.services.openai.llm import OpenAILLMService +from pipecat.transports.base_transport import BaseTransport, TransportParams +from pipecat.transports.daily.transport import DailyParams +from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams + +load_dotenv(override=True) + +transport_params = { + "daily": lambda: DailyParams( + audio_in_enabled=True, + audio_out_enabled=True, + ), + "twilio": lambda: FastAPIWebsocketParams( + audio_in_enabled=True, + audio_out_enabled=True, + ), + "webrtc": lambda: TransportParams( + audio_in_enabled=True, + audio_out_enabled=True, + ), +} + + +async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): + logger.info(f"Starting bot") + + stt = GradiumSTTService( + api_key=os.getenv("GRADIUM_API_KEY"), + api_endpoint_base_url="wss://us.api.gradium.ai/api/speech/asr", + ) + + tts = CartesiaTTSService( + api_key=os.getenv("CARTESIA_API_KEY"), + voice_id="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady + ) + + llm = OpenAILLMService(api_key=os.getenv("OPENAI_API_KEY")) + + messages = [ + { + "role": "system", + "content": "You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + }, + ] + + context = LLMContext(messages) + user_aggregator, assistant_aggregator = LLMContextAggregatorPair( + context, + user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()), + ) + + pipeline = Pipeline( + [ + transport.input(), + stt, + user_aggregator, + llm, + tts, + transport.output(), + assistant_aggregator, + ] + ) + + task = PipelineTask( + pipeline, + params=PipelineParams( + enable_metrics=True, + enable_usage_metrics=True, + ), + idle_timeout_secs=runner_args.pipeline_idle_timeout_secs, + ) + + @transport.event_handler("on_client_connected") + async def on_client_connected(transport, client): + logger.info(f"Client connected") + messages.append({"role": "system", "content": "Please introduce yourself to the user."}) + await task.queue_frames([LLMRunFrame()]) + + await asyncio.sleep(10) + logger.info("Updating Gradium STT settings: delay_in_frames=5") + await task.queue_frame(STTUpdateSettingsFrame(update=GradiumSTTSettings(delay_in_frames=5))) + + @transport.event_handler("on_client_disconnected") + async def on_client_disconnected(transport, client): + logger.info(f"Client disconnected") + await task.cancel() + + runner = PipelineRunner(handle_sigint=runner_args.handle_sigint) + + await runner.run(task) + + +async def bot(runner_args: RunnerArguments): + """Main bot entry point compatible with Pipecat Cloud.""" + transport = await create_transport(runner_args, transport_params) + await run_bot(transport, runner_args) + + +if __name__ == "__main__": + from pipecat.runner.run import main + + main() diff --git a/examples/foundational/55zs-update-settings-hathora-stt.py b/examples/foundational/55zs-update-settings-hathora-stt.py new file mode 100644 index 000000000..f3aca9c89 --- /dev/null +++ b/examples/foundational/55zs-update-settings-hathora-stt.py @@ -0,0 +1,129 @@ +# +# Copyright (c) 2024-2026, Daily +# +# SPDX-License-Identifier: BSD 2-Clause License +# + +import asyncio +import os + +from dotenv import load_dotenv +from loguru import logger + +from pipecat.audio.vad.silero import SileroVADAnalyzer +from pipecat.frames.frames import LLMRunFrame, STTUpdateSettingsFrame +from pipecat.pipeline.pipeline import Pipeline +from pipecat.pipeline.runner import PipelineRunner +from pipecat.pipeline.task import PipelineParams, PipelineTask +from pipecat.processors.aggregators.llm_context import LLMContext +from pipecat.processors.aggregators.llm_response_universal import ( + LLMContextAggregatorPair, + LLMUserAggregatorParams, +) +from pipecat.runner.types import RunnerArguments +from pipecat.runner.utils import create_transport +from pipecat.services.cartesia.tts import CartesiaTTSService +from pipecat.services.hathora.stt import HathoraSTTService, HathoraSTTSettings +from pipecat.services.hathora.utils import ConfigOption +from pipecat.services.openai.llm import OpenAILLMService +from pipecat.transcriptions.language import Language +from pipecat.transports.base_transport import BaseTransport, TransportParams +from pipecat.transports.daily.transport import DailyParams +from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams + +load_dotenv(override=True) + +transport_params = { + "daily": lambda: DailyParams( + audio_in_enabled=True, + audio_out_enabled=True, + ), + "twilio": lambda: FastAPIWebsocketParams( + audio_in_enabled=True, + audio_out_enabled=True, + ), + "webrtc": lambda: TransportParams( + audio_in_enabled=True, + audio_out_enabled=True, + ), +} + + +async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): + logger.info(f"Starting bot") + + stt = HathoraSTTService(api_key=os.getenv("HATHORA_API_KEY"), model="deepgram-nova3") + + tts = CartesiaTTSService( + api_key=os.getenv("CARTESIA_API_KEY"), + voice_id="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady + ) + + llm = OpenAILLMService(api_key=os.getenv("OPENAI_API_KEY")) + + messages = [ + { + "role": "system", + "content": "You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + }, + ] + + context = LLMContext(messages) + user_aggregator, assistant_aggregator = LLMContextAggregatorPair( + context, + user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()), + ) + + pipeline = Pipeline( + [ + transport.input(), + stt, + user_aggregator, + llm, + tts, + transport.output(), + assistant_aggregator, + ] + ) + + task = PipelineTask( + pipeline, + params=PipelineParams( + enable_metrics=True, + enable_usage_metrics=True, + ), + idle_timeout_secs=runner_args.pipeline_idle_timeout_secs, + ) + + @transport.event_handler("on_client_connected") + async def on_client_connected(transport, client): + logger.info(f"Client connected") + messages.append({"role": "system", "content": "Please introduce yourself to the user."}) + await task.queue_frames([LLMRunFrame()]) + + await asyncio.sleep(10) + logger.info("Updating Hathora STT settings: language=es") + await task.queue_frame( + STTUpdateSettingsFrame(update=HathoraSTTSettings(language=Language.ES)) + ) + + @transport.event_handler("on_client_disconnected") + async def on_client_disconnected(transport, client): + logger.info(f"Client disconnected") + await task.cancel() + + runner = PipelineRunner(handle_sigint=runner_args.handle_sigint) + + await runner.run(task) + + +async def bot(runner_args: RunnerArguments): + """Main bot entry point compatible with Pipecat Cloud.""" + transport = await create_transport(runner_args, transport_params) + await run_bot(transport, runner_args) + + +if __name__ == "__main__": + from pipecat.runner.run import main + + main() diff --git a/examples/foundational/55zt-update-settings-nvidia-segmented-stt.py b/examples/foundational/55zt-update-settings-nvidia-segmented-stt.py new file mode 100644 index 000000000..624da149e --- /dev/null +++ b/examples/foundational/55zt-update-settings-nvidia-segmented-stt.py @@ -0,0 +1,127 @@ +# +# Copyright (c) 2024-2026, Daily +# +# SPDX-License-Identifier: BSD 2-Clause License +# + +import asyncio +import os + +from dotenv import load_dotenv +from loguru import logger + +from pipecat.audio.vad.silero import SileroVADAnalyzer +from pipecat.frames.frames import LLMRunFrame, STTUpdateSettingsFrame +from pipecat.pipeline.pipeline import Pipeline +from pipecat.pipeline.runner import PipelineRunner +from pipecat.pipeline.task import PipelineParams, PipelineTask +from pipecat.processors.aggregators.llm_context import LLMContext +from pipecat.processors.aggregators.llm_response_universal import ( + LLMContextAggregatorPair, + LLMUserAggregatorParams, +) +from pipecat.runner.types import RunnerArguments +from pipecat.runner.utils import create_transport +from pipecat.services.cartesia.tts import CartesiaTTSService +from pipecat.services.nvidia.stt import NvidiaSegmentedSTTService, NvidiaSegmentedSTTSettings +from pipecat.services.openai.llm import OpenAILLMService +from pipecat.transports.base_transport import BaseTransport, TransportParams +from pipecat.transports.daily.transport import DailyParams +from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams + +load_dotenv(override=True) + +transport_params = { + "daily": lambda: DailyParams( + audio_in_enabled=True, + audio_out_enabled=True, + ), + "twilio": lambda: FastAPIWebsocketParams( + audio_in_enabled=True, + audio_out_enabled=True, + ), + "webrtc": lambda: TransportParams( + audio_in_enabled=True, + audio_out_enabled=True, + ), +} + + +async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): + logger.info(f"Starting bot") + + stt = NvidiaSegmentedSTTService(api_key=os.getenv("NVIDIA_API_KEY")) + + tts = CartesiaTTSService( + api_key=os.getenv("CARTESIA_API_KEY"), + voice_id="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady + ) + + llm = OpenAILLMService(api_key=os.getenv("OPENAI_API_KEY")) + + messages = [ + { + "role": "system", + "content": "You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + }, + ] + + context = LLMContext(messages) + user_aggregator, assistant_aggregator = LLMContextAggregatorPair( + context, + user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()), + ) + + pipeline = Pipeline( + [ + transport.input(), + stt, + user_aggregator, + llm, + tts, + transport.output(), + assistant_aggregator, + ] + ) + + task = PipelineTask( + pipeline, + params=PipelineParams( + enable_metrics=True, + enable_usage_metrics=True, + ), + idle_timeout_secs=runner_args.pipeline_idle_timeout_secs, + ) + + @transport.event_handler("on_client_connected") + async def on_client_connected(transport, client): + logger.info(f"Client connected") + messages.append({"role": "system", "content": "Please introduce yourself to the user."}) + await task.queue_frames([LLMRunFrame()]) + + await asyncio.sleep(10) + logger.info("Updating NVIDIA Segmented STT settings: profanity_filter=True") + await task.queue_frame( + STTUpdateSettingsFrame(update=NvidiaSegmentedSTTSettings(profanity_filter=True)) + ) + + @transport.event_handler("on_client_disconnected") + async def on_client_disconnected(transport, client): + logger.info(f"Client disconnected") + await task.cancel() + + runner = PipelineRunner(handle_sigint=runner_args.handle_sigint) + + await runner.run(task) + + +async def bot(runner_args: RunnerArguments): + """Main bot entry point compatible with Pipecat Cloud.""" + transport = await create_transport(runner_args, transport_params) + await run_bot(transport, runner_args) + + +if __name__ == "__main__": + from pipecat.runner.run import main + + main() diff --git a/examples/foundational/55zt-update-settings-nvidia-stt.py b/examples/foundational/55zt-update-settings-nvidia-stt.py new file mode 100644 index 000000000..0e7b6a74a --- /dev/null +++ b/examples/foundational/55zt-update-settings-nvidia-stt.py @@ -0,0 +1,128 @@ +# +# Copyright (c) 2024-2026, Daily +# +# SPDX-License-Identifier: BSD 2-Clause License +# + +import asyncio +import os + +from dotenv import load_dotenv +from loguru import logger + +from pipecat.audio.vad.silero import SileroVADAnalyzer +from pipecat.frames.frames import LLMRunFrame, STTUpdateSettingsFrame +from pipecat.pipeline.pipeline import Pipeline +from pipecat.pipeline.runner import PipelineRunner +from pipecat.pipeline.task import PipelineParams, PipelineTask +from pipecat.processors.aggregators.llm_context import LLMContext +from pipecat.processors.aggregators.llm_response_universal import ( + LLMContextAggregatorPair, + LLMUserAggregatorParams, +) +from pipecat.runner.types import RunnerArguments +from pipecat.runner.utils import create_transport +from pipecat.services.cartesia.tts import CartesiaTTSService +from pipecat.services.nvidia.stt import NvidiaSTTService, NvidiaSTTSettings +from pipecat.services.openai.llm import OpenAILLMService +from pipecat.transcriptions.language import Language +from pipecat.transports.base_transport import BaseTransport, TransportParams +from pipecat.transports.daily.transport import DailyParams +from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams + +load_dotenv(override=True) + +transport_params = { + "daily": lambda: DailyParams( + audio_in_enabled=True, + audio_out_enabled=True, + ), + "twilio": lambda: FastAPIWebsocketParams( + audio_in_enabled=True, + audio_out_enabled=True, + ), + "webrtc": lambda: TransportParams( + audio_in_enabled=True, + audio_out_enabled=True, + ), +} + + +async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): + logger.info(f"Starting bot") + + stt = NvidiaSTTService(api_key=os.getenv("NVIDIA_API_KEY")) + + tts = CartesiaTTSService( + api_key=os.getenv("CARTESIA_API_KEY"), + voice_id="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady + ) + + llm = OpenAILLMService(api_key=os.getenv("OPENAI_API_KEY")) + + messages = [ + { + "role": "system", + "content": "You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + }, + ] + + context = LLMContext(messages) + user_aggregator, assistant_aggregator = LLMContextAggregatorPair( + context, + user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()), + ) + + pipeline = Pipeline( + [ + transport.input(), + stt, + user_aggregator, + llm, + tts, + transport.output(), + assistant_aggregator, + ] + ) + + task = PipelineTask( + pipeline, + params=PipelineParams( + enable_metrics=True, + enable_usage_metrics=True, + ), + idle_timeout_secs=runner_args.pipeline_idle_timeout_secs, + ) + + @transport.event_handler("on_client_connected") + async def on_client_connected(transport, client): + logger.info(f"Client connected") + messages.append({"role": "system", "content": "Please introduce yourself to the user."}) + await task.queue_frames([LLMRunFrame()]) + + await asyncio.sleep(10) + logger.info("Updating NVIDIA STT settings: language=es") + await task.queue_frame( + STTUpdateSettingsFrame(update=NvidiaSTTSettings(language=Language.ES)) + ) + + @transport.event_handler("on_client_disconnected") + async def on_client_disconnected(transport, client): + logger.info(f"Client disconnected") + await task.cancel() + + runner = PipelineRunner(handle_sigint=runner_args.handle_sigint) + + await runner.run(task) + + +async def bot(runner_args: RunnerArguments): + """Main bot entry point compatible with Pipecat Cloud.""" + transport = await create_transport(runner_args, transport_params) + await run_bot(transport, runner_args) + + +if __name__ == "__main__": + from pipecat.runner.run import main + + main() diff --git a/examples/foundational/55zu-update-settings-openai-realtime-stt.py b/examples/foundational/55zu-update-settings-openai-realtime-stt.py new file mode 100644 index 000000000..1f1592df7 --- /dev/null +++ b/examples/foundational/55zu-update-settings-openai-realtime-stt.py @@ -0,0 +1,128 @@ +# +# Copyright (c) 2024-2026, Daily +# +# SPDX-License-Identifier: BSD 2-Clause License +# + +import asyncio +import os + +from dotenv import load_dotenv +from loguru import logger + +from pipecat.audio.vad.silero import SileroVADAnalyzer +from pipecat.frames.frames import LLMRunFrame, STTUpdateSettingsFrame +from pipecat.pipeline.pipeline import Pipeline +from pipecat.pipeline.runner import PipelineRunner +from pipecat.pipeline.task import PipelineParams, PipelineTask +from pipecat.processors.aggregators.llm_context import LLMContext +from pipecat.processors.aggregators.llm_response_universal import ( + LLMContextAggregatorPair, + LLMUserAggregatorParams, +) +from pipecat.runner.types import RunnerArguments +from pipecat.runner.utils import create_transport +from pipecat.services.cartesia.tts import CartesiaTTSService +from pipecat.services.openai.llm import OpenAILLMService +from pipecat.services.openai.stt import OpenAIRealtimeSTTService, OpenAIRealtimeSTTSettings +from pipecat.transcriptions.language import Language +from pipecat.transports.base_transport import BaseTransport, TransportParams +from pipecat.transports.daily.transport import DailyParams +from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams + +load_dotenv(override=True) + +transport_params = { + "daily": lambda: DailyParams( + audio_in_enabled=True, + audio_out_enabled=True, + ), + "twilio": lambda: FastAPIWebsocketParams( + audio_in_enabled=True, + audio_out_enabled=True, + ), + "webrtc": lambda: TransportParams( + audio_in_enabled=True, + audio_out_enabled=True, + ), +} + + +async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): + logger.info(f"Starting bot") + + stt = OpenAIRealtimeSTTService(api_key=os.getenv("OPENAI_API_KEY")) + + tts = CartesiaTTSService( + api_key=os.getenv("CARTESIA_API_KEY"), + voice_id="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady + ) + + llm = OpenAILLMService(api_key=os.getenv("OPENAI_API_KEY")) + + messages = [ + { + "role": "system", + "content": "You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + }, + ] + + context = LLMContext(messages) + user_aggregator, assistant_aggregator = LLMContextAggregatorPair( + context, + user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()), + ) + + pipeline = Pipeline( + [ + transport.input(), + stt, + user_aggregator, + llm, + tts, + transport.output(), + assistant_aggregator, + ] + ) + + task = PipelineTask( + pipeline, + params=PipelineParams( + enable_metrics=True, + enable_usage_metrics=True, + ), + idle_timeout_secs=runner_args.pipeline_idle_timeout_secs, + ) + + @transport.event_handler("on_client_connected") + async def on_client_connected(transport, client): + logger.info(f"Client connected") + messages.append({"role": "system", "content": "Please introduce yourself to the user."}) + await task.queue_frames([LLMRunFrame()]) + + await asyncio.sleep(10) + logger.info("Updating OpenAI Realtime STT settings: language=es") + await task.queue_frame( + STTUpdateSettingsFrame(update=OpenAIRealtimeSTTSettings(language=Language.ES)) + ) + + @transport.event_handler("on_client_disconnected") + async def on_client_disconnected(transport, client): + logger.info(f"Client disconnected") + await task.cancel() + + runner = PipelineRunner(handle_sigint=runner_args.handle_sigint) + + await runner.run(task) + + +async def bot(runner_args: RunnerArguments): + """Main bot entry point compatible with Pipecat Cloud.""" + transport = await create_transport(runner_args, transport_params) + await run_bot(transport, runner_args) + + +if __name__ == "__main__": + from pipecat.runner.run import main + + main() diff --git a/examples/foundational/55zv-update-settings-asyncai-http-tts.py b/examples/foundational/55zv-update-settings-asyncai-http-tts.py new file mode 100644 index 000000000..206a80eed --- /dev/null +++ b/examples/foundational/55zv-update-settings-asyncai-http-tts.py @@ -0,0 +1,133 @@ +# +# Copyright (c) 2024-2026, Daily +# +# SPDX-License-Identifier: BSD 2-Clause License +# + + +import asyncio +import os + +import aiohttp +from dotenv import load_dotenv +from loguru import logger + +from pipecat.audio.vad.silero import SileroVADAnalyzer +from pipecat.frames.frames import LLMRunFrame, TTSUpdateSettingsFrame +from pipecat.pipeline.pipeline import Pipeline +from pipecat.pipeline.runner import PipelineRunner +from pipecat.pipeline.task import PipelineParams, PipelineTask +from pipecat.processors.aggregators.llm_context import LLMContext +from pipecat.processors.aggregators.llm_response_universal import ( + LLMContextAggregatorPair, + LLMUserAggregatorParams, +) +from pipecat.runner.types import RunnerArguments +from pipecat.runner.utils import create_transport +from pipecat.services.asyncai.tts import AsyncAIHttpTTSService, AsyncAITTSSettings +from pipecat.services.deepgram.stt import DeepgramSTTService +from pipecat.services.openai.llm import OpenAILLMService +from pipecat.transcriptions.language import Language +from pipecat.transports.base_transport import BaseTransport, TransportParams +from pipecat.transports.daily.transport import DailyParams +from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams + +load_dotenv(override=True) + + +transport_params = { + "daily": lambda: DailyParams( + audio_in_enabled=True, + audio_out_enabled=True, + ), + "twilio": lambda: FastAPIWebsocketParams( + audio_in_enabled=True, + audio_out_enabled=True, + ), + "webrtc": lambda: TransportParams( + audio_in_enabled=True, + audio_out_enabled=True, + ), +} + + +async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): + logger.info(f"Starting bot") + + async with aiohttp.ClientSession() as session: + stt = DeepgramSTTService(api_key=os.getenv("DEEPGRAM_API_KEY")) + + tts = AsyncAIHttpTTSService( + api_key=os.getenv("ASYNCAI_API_KEY", ""), + voice_id=os.getenv("ASYNCAI_VOICE_ID", "e0f39dc4-f691-4e78-bba5-5c636692cc04"), + aiohttp_session=session, + ) + + llm = OpenAILLMService(api_key=os.getenv("OPENAI_API_KEY")) + + messages = [ + { + "role": "system", + "content": "You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + }, + ] + + context = LLMContext(messages) + user_aggregator, assistant_aggregator = LLMContextAggregatorPair( + context, + user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()), + ) + + pipeline = Pipeline( + [ + transport.input(), + stt, + user_aggregator, + llm, + tts, + transport.output(), + assistant_aggregator, + ] + ) + + task = PipelineTask( + pipeline, + params=PipelineParams( + enable_metrics=True, + enable_usage_metrics=True, + ), + idle_timeout_secs=runner_args.pipeline_idle_timeout_secs, + ) + + @transport.event_handler("on_client_connected") + async def on_client_connected(transport, client): + logger.info(f"Client connected") + messages.append({"role": "system", "content": "Please introduce yourself to the user."}) + await task.queue_frames([LLMRunFrame()]) + + await asyncio.sleep(10) + logger.info("Updating AsyncAI HTTP TTS settings: language=es") + await task.queue_frame( + TTSUpdateSettingsFrame(update=AsyncAITTSSettings(language=Language.ES)) + ) + + @transport.event_handler("on_client_disconnected") + async def on_client_disconnected(transport, client): + logger.info(f"Client disconnected") + await task.cancel() + + runner = PipelineRunner(handle_sigint=runner_args.handle_sigint) + + await runner.run(task) + + +async def bot(runner_args: RunnerArguments): + """Main bot entry point compatible with Pipecat Cloud.""" + transport = await create_transport(runner_args, transport_params) + await run_bot(transport, runner_args) + + +if __name__ == "__main__": + from pipecat.runner.run import main + + main() diff --git a/examples/foundational/55zv-update-settings-asyncai-tts.py b/examples/foundational/55zv-update-settings-asyncai-tts.py new file mode 100644 index 000000000..f910e5fe3 --- /dev/null +++ b/examples/foundational/55zv-update-settings-asyncai-tts.py @@ -0,0 +1,128 @@ +# +# Copyright (c) 2024-2026, Daily +# +# SPDX-License-Identifier: BSD 2-Clause License +# + +import asyncio +import os + +from dotenv import load_dotenv +from loguru import logger + +from pipecat.audio.vad.silero import SileroVADAnalyzer +from pipecat.frames.frames import LLMRunFrame, TTSUpdateSettingsFrame +from pipecat.pipeline.pipeline import Pipeline +from pipecat.pipeline.runner import PipelineRunner +from pipecat.pipeline.task import PipelineParams, PipelineTask +from pipecat.processors.aggregators.llm_context import LLMContext +from pipecat.processors.aggregators.llm_response_universal import ( + LLMContextAggregatorPair, + LLMUserAggregatorParams, +) +from pipecat.runner.types import RunnerArguments +from pipecat.runner.utils import create_transport +from pipecat.services.asyncai.tts import AsyncAITTSService, AsyncAITTSSettings +from pipecat.services.deepgram.stt import DeepgramSTTService +from pipecat.services.openai.llm import OpenAILLMService +from pipecat.transcriptions.language import Language +from pipecat.transports.base_transport import BaseTransport, TransportParams +from pipecat.transports.daily.transport import DailyParams +from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams + +load_dotenv(override=True) + +transport_params = { + "daily": lambda: DailyParams( + audio_in_enabled=True, + audio_out_enabled=True, + ), + "twilio": lambda: FastAPIWebsocketParams( + audio_in_enabled=True, + audio_out_enabled=True, + ), + "webrtc": lambda: TransportParams( + audio_in_enabled=True, + audio_out_enabled=True, + ), +} + + +async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): + logger.info(f"Starting bot") + + stt = DeepgramSTTService(api_key=os.getenv("DEEPGRAM_API_KEY")) + + tts = AsyncAITTSService( + api_key=os.getenv("ASYNCAI_API_KEY", ""), + voice_id=os.getenv("ASYNCAI_VOICE_ID", "e0f39dc4-f691-4e78-bba5-5c636692cc04"), + ) + + llm = OpenAILLMService(api_key=os.getenv("OPENAI_API_KEY")) + + messages = [ + { + "role": "system", + "content": "You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + }, + ] + + context = LLMContext(messages) + user_aggregator, assistant_aggregator = LLMContextAggregatorPair( + context, + user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()), + ) + + pipeline = Pipeline( + [ + transport.input(), + stt, + user_aggregator, + llm, + tts, + transport.output(), + assistant_aggregator, + ] + ) + + task = PipelineTask( + pipeline, + params=PipelineParams( + enable_metrics=True, + enable_usage_metrics=True, + ), + idle_timeout_secs=runner_args.pipeline_idle_timeout_secs, + ) + + @transport.event_handler("on_client_connected") + async def on_client_connected(transport, client): + logger.info(f"Client connected") + messages.append({"role": "system", "content": "Please introduce yourself to the user."}) + await task.queue_frames([LLMRunFrame()]) + + await asyncio.sleep(10) + logger.info("Updating AsyncAI TTS settings: language=es") + await task.queue_frame( + TTSUpdateSettingsFrame(update=AsyncAITTSSettings(language=Language.ES)) + ) + + @transport.event_handler("on_client_disconnected") + async def on_client_disconnected(transport, client): + logger.info(f"Client disconnected") + await task.cancel() + + runner = PipelineRunner(handle_sigint=runner_args.handle_sigint) + + await runner.run(task) + + +async def bot(runner_args: RunnerArguments): + """Main bot entry point compatible with Pipecat Cloud.""" + transport = await create_transport(runner_args, transport_params) + await run_bot(transport, runner_args) + + +if __name__ == "__main__": + from pipecat.runner.run import main + + main() diff --git a/examples/foundational/55zw-update-settings-gradium-tts.py b/examples/foundational/55zw-update-settings-gradium-tts.py new file mode 100644 index 000000000..39090d5fa --- /dev/null +++ b/examples/foundational/55zw-update-settings-gradium-tts.py @@ -0,0 +1,128 @@ +# +# Copyright (c) 2024-2026, Daily +# +# SPDX-License-Identifier: BSD 2-Clause License +# + +import asyncio +import os + +from dotenv import load_dotenv +from loguru import logger + +from pipecat.audio.vad.silero import SileroVADAnalyzer +from pipecat.frames.frames import LLMRunFrame, TTSUpdateSettingsFrame +from pipecat.pipeline.pipeline import Pipeline +from pipecat.pipeline.runner import PipelineRunner +from pipecat.pipeline.task import PipelineParams, PipelineTask +from pipecat.processors.aggregators.llm_context import LLMContext +from pipecat.processors.aggregators.llm_response_universal import ( + LLMContextAggregatorPair, + LLMUserAggregatorParams, +) +from pipecat.runner.types import RunnerArguments +from pipecat.runner.utils import create_transport +from pipecat.services.deepgram.stt import DeepgramSTTService +from pipecat.services.gradium.tts import GradiumTTSService, GradiumTTSSettings +from pipecat.services.openai.llm import OpenAILLMService +from pipecat.transports.base_transport import BaseTransport, TransportParams +from pipecat.transports.daily.transport import DailyParams +from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams + +load_dotenv(override=True) + +transport_params = { + "daily": lambda: DailyParams( + audio_in_enabled=True, + audio_out_enabled=True, + ), + "twilio": lambda: FastAPIWebsocketParams( + audio_in_enabled=True, + audio_out_enabled=True, + ), + "webrtc": lambda: TransportParams( + audio_in_enabled=True, + audio_out_enabled=True, + ), +} + + +async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): + logger.info(f"Starting bot") + + stt = DeepgramSTTService(api_key=os.getenv("DEEPGRAM_API_KEY")) + + tts = GradiumTTSService( + api_key=os.getenv("GRADIUM_API_KEY"), + voice_id="YTpq7expH9539ERJ", + url="wss://us.api.gradium.ai/api/speech/tts", + ) + + llm = OpenAILLMService(api_key=os.getenv("OPENAI_API_KEY")) + + messages = [ + { + "role": "system", + "content": "You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + }, + ] + + context = LLMContext(messages) + user_aggregator, assistant_aggregator = LLMContextAggregatorPair( + context, + user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()), + ) + + pipeline = Pipeline( + [ + transport.input(), + stt, + user_aggregator, + llm, + tts, + transport.output(), + assistant_aggregator, + ] + ) + + task = PipelineTask( + pipeline, + params=PipelineParams( + enable_metrics=True, + enable_usage_metrics=True, + ), + idle_timeout_secs=runner_args.pipeline_idle_timeout_secs, + ) + + @transport.event_handler("on_client_connected") + async def on_client_connected(transport, client): + logger.info(f"Client connected") + messages.append({"role": "system", "content": "Please introduce yourself to the user."}) + await task.queue_frames([LLMRunFrame()]) + + await asyncio.sleep(10) + logger.info('Updating Gradium TTS settings: voice="LFZvm12tW_z0xfGo"') + await task.queue_frame( + TTSUpdateSettingsFrame(update=GradiumTTSSettings(voice="LFZvm12tW_z0xfGo")) + ) + + @transport.event_handler("on_client_disconnected") + async def on_client_disconnected(transport, client): + logger.info(f"Client disconnected") + await task.cancel() + + runner = PipelineRunner(handle_sigint=runner_args.handle_sigint) + + await runner.run(task) + + +async def bot(runner_args: RunnerArguments): + """Main bot entry point compatible with Pipecat Cloud.""" + transport = await create_transport(runner_args, transport_params) + await run_bot(transport, runner_args) + + +if __name__ == "__main__": + from pipecat.runner.run import main + + main() diff --git a/examples/foundational/55zx-update-settings-cerebras-llm.py b/examples/foundational/55zx-update-settings-cerebras-llm.py new file mode 100644 index 000000000..72aa8518d --- /dev/null +++ b/examples/foundational/55zx-update-settings-cerebras-llm.py @@ -0,0 +1,126 @@ +# +# Copyright (c) 2024-2026, Daily +# +# SPDX-License-Identifier: BSD 2-Clause License +# + +import asyncio +import os + +from dotenv import load_dotenv +from loguru import logger + +from pipecat.audio.vad.silero import SileroVADAnalyzer +from pipecat.frames.frames import LLMRunFrame, LLMUpdateSettingsFrame +from pipecat.pipeline.pipeline import Pipeline +from pipecat.pipeline.runner import PipelineRunner +from pipecat.pipeline.task import PipelineParams, PipelineTask +from pipecat.processors.aggregators.llm_context import LLMContext +from pipecat.processors.aggregators.llm_response_universal import ( + LLMContextAggregatorPair, + LLMUserAggregatorParams, +) +from pipecat.runner.types import RunnerArguments +from pipecat.runner.utils import create_transport +from pipecat.services.cartesia.tts import CartesiaTTSService +from pipecat.services.cerebras.llm import CerebrasLLMService +from pipecat.services.deepgram.stt import DeepgramSTTService +from pipecat.services.openai.base_llm import OpenAILLMSettings +from pipecat.transports.base_transport import BaseTransport, TransportParams +from pipecat.transports.daily.transport import DailyParams +from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams + +load_dotenv(override=True) + +transport_params = { + "daily": lambda: DailyParams( + audio_in_enabled=True, + audio_out_enabled=True, + ), + "twilio": lambda: FastAPIWebsocketParams( + audio_in_enabled=True, + audio_out_enabled=True, + ), + "webrtc": lambda: TransportParams( + audio_in_enabled=True, + audio_out_enabled=True, + ), +} + + +async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): + logger.info(f"Starting bot") + + stt = DeepgramSTTService(api_key=os.getenv("DEEPGRAM_API_KEY")) + + tts = CartesiaTTSService( + api_key=os.getenv("CARTESIA_API_KEY"), + voice_id="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady + ) + + llm = CerebrasLLMService(api_key=os.getenv("CEREBRAS_API_KEY")) + + messages = [ + { + "role": "system", + "content": "You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + }, + ] + + context = LLMContext(messages) + user_aggregator, assistant_aggregator = LLMContextAggregatorPair( + context, + user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()), + ) + + pipeline = Pipeline( + [ + transport.input(), + stt, + user_aggregator, + llm, + tts, + transport.output(), + assistant_aggregator, + ] + ) + + task = PipelineTask( + pipeline, + params=PipelineParams( + enable_metrics=True, + enable_usage_metrics=True, + ), + idle_timeout_secs=runner_args.pipeline_idle_timeout_secs, + ) + + @transport.event_handler("on_client_connected") + async def on_client_connected(transport, client): + logger.info(f"Client connected") + messages.append({"role": "system", "content": "Please introduce yourself to the user."}) + await task.queue_frames([LLMRunFrame()]) + + await asyncio.sleep(10) + logger.info("Updating Cerebras LLM settings: temperature=0.1") + await task.queue_frame(LLMUpdateSettingsFrame(update=OpenAILLMSettings(temperature=0.1))) + + @transport.event_handler("on_client_disconnected") + async def on_client_disconnected(transport, client): + logger.info(f"Client disconnected") + await task.cancel() + + runner = PipelineRunner(handle_sigint=runner_args.handle_sigint) + + await runner.run(task) + + +async def bot(runner_args: RunnerArguments): + """Main bot entry point compatible with Pipecat Cloud.""" + transport = await create_transport(runner_args, transport_params) + await run_bot(transport, runner_args) + + +if __name__ == "__main__": + from pipecat.runner.run import main + + main() diff --git a/examples/foundational/55zy-update-settings-deepseek-llm.py b/examples/foundational/55zy-update-settings-deepseek-llm.py new file mode 100644 index 000000000..de4e4149e --- /dev/null +++ b/examples/foundational/55zy-update-settings-deepseek-llm.py @@ -0,0 +1,126 @@ +# +# Copyright (c) 2024-2026, Daily +# +# SPDX-License-Identifier: BSD 2-Clause License +# + +import asyncio +import os + +from dotenv import load_dotenv +from loguru import logger + +from pipecat.audio.vad.silero import SileroVADAnalyzer +from pipecat.frames.frames import LLMRunFrame, LLMUpdateSettingsFrame +from pipecat.pipeline.pipeline import Pipeline +from pipecat.pipeline.runner import PipelineRunner +from pipecat.pipeline.task import PipelineParams, PipelineTask +from pipecat.processors.aggregators.llm_context import LLMContext +from pipecat.processors.aggregators.llm_response_universal import ( + LLMContextAggregatorPair, + LLMUserAggregatorParams, +) +from pipecat.runner.types import RunnerArguments +from pipecat.runner.utils import create_transport +from pipecat.services.cartesia.tts import CartesiaTTSService +from pipecat.services.deepgram.stt import DeepgramSTTService +from pipecat.services.deepseek.llm import DeepSeekLLMService +from pipecat.services.openai.base_llm import OpenAILLMSettings +from pipecat.transports.base_transport import BaseTransport, TransportParams +from pipecat.transports.daily.transport import DailyParams +from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams + +load_dotenv(override=True) + +transport_params = { + "daily": lambda: DailyParams( + audio_in_enabled=True, + audio_out_enabled=True, + ), + "twilio": lambda: FastAPIWebsocketParams( + audio_in_enabled=True, + audio_out_enabled=True, + ), + "webrtc": lambda: TransportParams( + audio_in_enabled=True, + audio_out_enabled=True, + ), +} + + +async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): + logger.info(f"Starting bot") + + stt = DeepgramSTTService(api_key=os.getenv("DEEPGRAM_API_KEY")) + + tts = CartesiaTTSService( + api_key=os.getenv("CARTESIA_API_KEY"), + voice_id="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady + ) + + llm = DeepSeekLLMService(api_key=os.getenv("DEEPSEEK_API_KEY")) + + messages = [ + { + "role": "system", + "content": "You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + }, + ] + + context = LLMContext(messages) + user_aggregator, assistant_aggregator = LLMContextAggregatorPair( + context, + user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()), + ) + + pipeline = Pipeline( + [ + transport.input(), + stt, + user_aggregator, + llm, + tts, + transport.output(), + assistant_aggregator, + ] + ) + + task = PipelineTask( + pipeline, + params=PipelineParams( + enable_metrics=True, + enable_usage_metrics=True, + ), + idle_timeout_secs=runner_args.pipeline_idle_timeout_secs, + ) + + @transport.event_handler("on_client_connected") + async def on_client_connected(transport, client): + logger.info(f"Client connected") + messages.append({"role": "system", "content": "Please introduce yourself to the user."}) + await task.queue_frames([LLMRunFrame()]) + + await asyncio.sleep(10) + logger.info("Updating DeepSeek LLM settings: temperature=0.1") + await task.queue_frame(LLMUpdateSettingsFrame(update=OpenAILLMSettings(temperature=0.1))) + + @transport.event_handler("on_client_disconnected") + async def on_client_disconnected(transport, client): + logger.info(f"Client disconnected") + await task.cancel() + + runner = PipelineRunner(handle_sigint=runner_args.handle_sigint) + + await runner.run(task) + + +async def bot(runner_args: RunnerArguments): + """Main bot entry point compatible with Pipecat Cloud.""" + transport = await create_transport(runner_args, transport_params) + await run_bot(transport, runner_args) + + +if __name__ == "__main__": + from pipecat.runner.run import main + + main() diff --git a/examples/foundational/55zz-update-settings-fireworks-llm.py b/examples/foundational/55zz-update-settings-fireworks-llm.py new file mode 100644 index 000000000..d864cacb2 --- /dev/null +++ b/examples/foundational/55zz-update-settings-fireworks-llm.py @@ -0,0 +1,129 @@ +# +# Copyright (c) 2024-2026, Daily +# +# SPDX-License-Identifier: BSD 2-Clause License +# + +import asyncio +import os + +from dotenv import load_dotenv +from loguru import logger + +from pipecat.audio.vad.silero import SileroVADAnalyzer +from pipecat.frames.frames import LLMRunFrame, LLMUpdateSettingsFrame +from pipecat.pipeline.pipeline import Pipeline +from pipecat.pipeline.runner import PipelineRunner +from pipecat.pipeline.task import PipelineParams, PipelineTask +from pipecat.processors.aggregators.llm_context import LLMContext +from pipecat.processors.aggregators.llm_response_universal import ( + LLMContextAggregatorPair, + LLMUserAggregatorParams, +) +from pipecat.runner.types import RunnerArguments +from pipecat.runner.utils import create_transport +from pipecat.services.cartesia.tts import CartesiaTTSService +from pipecat.services.deepgram.stt import DeepgramSTTService +from pipecat.services.fireworks.llm import FireworksLLMService +from pipecat.services.openai.base_llm import OpenAILLMSettings +from pipecat.transports.base_transport import BaseTransport, TransportParams +from pipecat.transports.daily.transport import DailyParams +from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams + +load_dotenv(override=True) + +transport_params = { + "daily": lambda: DailyParams( + audio_in_enabled=True, + audio_out_enabled=True, + ), + "twilio": lambda: FastAPIWebsocketParams( + audio_in_enabled=True, + audio_out_enabled=True, + ), + "webrtc": lambda: TransportParams( + audio_in_enabled=True, + audio_out_enabled=True, + ), +} + + +async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): + logger.info(f"Starting bot") + + stt = DeepgramSTTService(api_key=os.getenv("DEEPGRAM_API_KEY")) + + tts = CartesiaTTSService( + api_key=os.getenv("CARTESIA_API_KEY"), + voice_id="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady + ) + + llm = FireworksLLMService( + api_key=os.getenv("FIREWORKS_API_KEY"), + model="accounts/fireworks/models/gpt-oss-20b", + ) + + messages = [ + { + "role": "system", + "content": "You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + }, + ] + + context = LLMContext(messages) + user_aggregator, assistant_aggregator = LLMContextAggregatorPair( + context, + user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()), + ) + + pipeline = Pipeline( + [ + transport.input(), + stt, + user_aggregator, + llm, + tts, + transport.output(), + assistant_aggregator, + ] + ) + + task = PipelineTask( + pipeline, + params=PipelineParams( + enable_metrics=True, + enable_usage_metrics=True, + ), + idle_timeout_secs=runner_args.pipeline_idle_timeout_secs, + ) + + @transport.event_handler("on_client_connected") + async def on_client_connected(transport, client): + logger.info(f"Client connected") + messages.append({"role": "system", "content": "Please introduce yourself to the user."}) + await task.queue_frames([LLMRunFrame()]) + + await asyncio.sleep(10) + logger.info("Updating Fireworks LLM settings: temperature=0.1") + await task.queue_frame(LLMUpdateSettingsFrame(update=OpenAILLMSettings(temperature=0.1))) + + @transport.event_handler("on_client_disconnected") + async def on_client_disconnected(transport, client): + logger.info(f"Client disconnected") + await task.cancel() + + runner = PipelineRunner(handle_sigint=runner_args.handle_sigint) + + await runner.run(task) + + +async def bot(runner_args: RunnerArguments): + """Main bot entry point compatible with Pipecat Cloud.""" + transport = await create_transport(runner_args, transport_params) + await run_bot(transport, runner_args) + + +if __name__ == "__main__": + from pipecat.runner.run import main + + main() diff --git a/examples/foundational/55zza-update-settings-grok-llm.py b/examples/foundational/55zza-update-settings-grok-llm.py new file mode 100644 index 000000000..dbf07f21d --- /dev/null +++ b/examples/foundational/55zza-update-settings-grok-llm.py @@ -0,0 +1,126 @@ +# +# Copyright (c) 2024-2026, Daily +# +# SPDX-License-Identifier: BSD 2-Clause License +# + +import asyncio +import os + +from dotenv import load_dotenv +from loguru import logger + +from pipecat.audio.vad.silero import SileroVADAnalyzer +from pipecat.frames.frames import LLMRunFrame, LLMUpdateSettingsFrame +from pipecat.pipeline.pipeline import Pipeline +from pipecat.pipeline.runner import PipelineRunner +from pipecat.pipeline.task import PipelineParams, PipelineTask +from pipecat.processors.aggregators.llm_context import LLMContext +from pipecat.processors.aggregators.llm_response_universal import ( + LLMContextAggregatorPair, + LLMUserAggregatorParams, +) +from pipecat.runner.types import RunnerArguments +from pipecat.runner.utils import create_transport +from pipecat.services.cartesia.tts import CartesiaTTSService +from pipecat.services.deepgram.stt import DeepgramSTTService +from pipecat.services.grok.llm import GrokLLMService +from pipecat.services.openai.base_llm import OpenAILLMSettings +from pipecat.transports.base_transport import BaseTransport, TransportParams +from pipecat.transports.daily.transport import DailyParams +from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams + +load_dotenv(override=True) + +transport_params = { + "daily": lambda: DailyParams( + audio_in_enabled=True, + audio_out_enabled=True, + ), + "twilio": lambda: FastAPIWebsocketParams( + audio_in_enabled=True, + audio_out_enabled=True, + ), + "webrtc": lambda: TransportParams( + audio_in_enabled=True, + audio_out_enabled=True, + ), +} + + +async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): + logger.info(f"Starting bot") + + stt = DeepgramSTTService(api_key=os.getenv("DEEPGRAM_API_KEY")) + + tts = CartesiaTTSService( + api_key=os.getenv("CARTESIA_API_KEY"), + voice_id="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady + ) + + llm = GrokLLMService(api_key=os.getenv("GROK_API_KEY")) + + messages = [ + { + "role": "system", + "content": "You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + }, + ] + + context = LLMContext(messages) + user_aggregator, assistant_aggregator = LLMContextAggregatorPair( + context, + user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()), + ) + + pipeline = Pipeline( + [ + transport.input(), + stt, + user_aggregator, + llm, + tts, + transport.output(), + assistant_aggregator, + ] + ) + + task = PipelineTask( + pipeline, + params=PipelineParams( + enable_metrics=True, + enable_usage_metrics=True, + ), + idle_timeout_secs=runner_args.pipeline_idle_timeout_secs, + ) + + @transport.event_handler("on_client_connected") + async def on_client_connected(transport, client): + logger.info(f"Client connected") + messages.append({"role": "system", "content": "Please introduce yourself to the user."}) + await task.queue_frames([LLMRunFrame()]) + + await asyncio.sleep(10) + logger.info("Updating Grok LLM settings: temperature=0.1") + await task.queue_frame(LLMUpdateSettingsFrame(update=OpenAILLMSettings(temperature=0.1))) + + @transport.event_handler("on_client_disconnected") + async def on_client_disconnected(transport, client): + logger.info(f"Client disconnected") + await task.cancel() + + runner = PipelineRunner(handle_sigint=runner_args.handle_sigint) + + await runner.run(task) + + +async def bot(runner_args: RunnerArguments): + """Main bot entry point compatible with Pipecat Cloud.""" + transport = await create_transport(runner_args, transport_params) + await run_bot(transport, runner_args) + + +if __name__ == "__main__": + from pipecat.runner.run import main + + main() diff --git a/examples/foundational/55zzb-update-settings-groq-llm.py b/examples/foundational/55zzb-update-settings-groq-llm.py new file mode 100644 index 000000000..8244f611a --- /dev/null +++ b/examples/foundational/55zzb-update-settings-groq-llm.py @@ -0,0 +1,128 @@ +# +# Copyright (c) 2024-2026, Daily +# +# SPDX-License-Identifier: BSD 2-Clause License +# + +import asyncio +import os + +from dotenv import load_dotenv +from loguru import logger + +from pipecat.audio.vad.silero import SileroVADAnalyzer +from pipecat.frames.frames import LLMRunFrame, LLMUpdateSettingsFrame +from pipecat.pipeline.pipeline import Pipeline +from pipecat.pipeline.runner import PipelineRunner +from pipecat.pipeline.task import PipelineParams, PipelineTask +from pipecat.processors.aggregators.llm_context import LLMContext +from pipecat.processors.aggregators.llm_response_universal import ( + LLMContextAggregatorPair, + LLMUserAggregatorParams, +) +from pipecat.runner.types import RunnerArguments +from pipecat.runner.utils import create_transport +from pipecat.services.cartesia.tts import CartesiaTTSService +from pipecat.services.deepgram.stt import DeepgramSTTService +from pipecat.services.groq.llm import GroqLLMService +from pipecat.services.openai.base_llm import OpenAILLMSettings +from pipecat.transports.base_transport import BaseTransport, TransportParams +from pipecat.transports.daily.transport import DailyParams +from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams + +load_dotenv(override=True) + +transport_params = { + "daily": lambda: DailyParams( + audio_in_enabled=True, + audio_out_enabled=True, + ), + "twilio": lambda: FastAPIWebsocketParams( + audio_in_enabled=True, + audio_out_enabled=True, + ), + "webrtc": lambda: TransportParams( + audio_in_enabled=True, + audio_out_enabled=True, + ), +} + + +async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): + logger.info(f"Starting bot") + + stt = DeepgramSTTService(api_key=os.getenv("DEEPGRAM_API_KEY")) + + tts = CartesiaTTSService( + api_key=os.getenv("CARTESIA_API_KEY"), + voice_id="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady + ) + + llm = GroqLLMService( + api_key=os.getenv("GROQ_API_KEY"), model="meta-llama/llama-4-maverick-17b-128e-instruct" + ) + + messages = [ + { + "role": "system", + "content": "You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + }, + ] + + context = LLMContext(messages) + user_aggregator, assistant_aggregator = LLMContextAggregatorPair( + context, + user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()), + ) + + pipeline = Pipeline( + [ + transport.input(), + stt, + user_aggregator, + llm, + tts, + transport.output(), + assistant_aggregator, + ] + ) + + task = PipelineTask( + pipeline, + params=PipelineParams( + enable_metrics=True, + enable_usage_metrics=True, + ), + idle_timeout_secs=runner_args.pipeline_idle_timeout_secs, + ) + + @transport.event_handler("on_client_connected") + async def on_client_connected(transport, client): + logger.info(f"Client connected") + messages.append({"role": "system", "content": "Please introduce yourself to the user."}) + await task.queue_frames([LLMRunFrame()]) + + await asyncio.sleep(10) + logger.info("Updating Groq LLM settings: temperature=0.1") + await task.queue_frame(LLMUpdateSettingsFrame(update=OpenAILLMSettings(temperature=0.1))) + + @transport.event_handler("on_client_disconnected") + async def on_client_disconnected(transport, client): + logger.info(f"Client disconnected") + await task.cancel() + + runner = PipelineRunner(handle_sigint=runner_args.handle_sigint) + + await runner.run(task) + + +async def bot(runner_args: RunnerArguments): + """Main bot entry point compatible with Pipecat Cloud.""" + transport = await create_transport(runner_args, transport_params) + await run_bot(transport, runner_args) + + +if __name__ == "__main__": + from pipecat.runner.run import main + + main() diff --git a/examples/foundational/55zzc-update-settings-mistral-llm.py b/examples/foundational/55zzc-update-settings-mistral-llm.py new file mode 100644 index 000000000..642eda3c5 --- /dev/null +++ b/examples/foundational/55zzc-update-settings-mistral-llm.py @@ -0,0 +1,126 @@ +# +# Copyright (c) 2024-2026, Daily +# +# SPDX-License-Identifier: BSD 2-Clause License +# + +import asyncio +import os + +from dotenv import load_dotenv +from loguru import logger + +from pipecat.audio.vad.silero import SileroVADAnalyzer +from pipecat.frames.frames import LLMRunFrame, LLMUpdateSettingsFrame +from pipecat.pipeline.pipeline import Pipeline +from pipecat.pipeline.runner import PipelineRunner +from pipecat.pipeline.task import PipelineParams, PipelineTask +from pipecat.processors.aggregators.llm_context import LLMContext +from pipecat.processors.aggregators.llm_response_universal import ( + LLMContextAggregatorPair, + LLMUserAggregatorParams, +) +from pipecat.runner.types import RunnerArguments +from pipecat.runner.utils import create_transport +from pipecat.services.cartesia.tts import CartesiaTTSService +from pipecat.services.deepgram.stt import DeepgramSTTService +from pipecat.services.mistral.llm import MistralLLMService +from pipecat.services.openai.base_llm import OpenAILLMSettings +from pipecat.transports.base_transport import BaseTransport, TransportParams +from pipecat.transports.daily.transport import DailyParams +from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams + +load_dotenv(override=True) + +transport_params = { + "daily": lambda: DailyParams( + audio_in_enabled=True, + audio_out_enabled=True, + ), + "twilio": lambda: FastAPIWebsocketParams( + audio_in_enabled=True, + audio_out_enabled=True, + ), + "webrtc": lambda: TransportParams( + audio_in_enabled=True, + audio_out_enabled=True, + ), +} + + +async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): + logger.info(f"Starting bot") + + stt = DeepgramSTTService(api_key=os.getenv("DEEPGRAM_API_KEY")) + + tts = CartesiaTTSService( + api_key=os.getenv("CARTESIA_API_KEY"), + voice_id="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady + ) + + llm = MistralLLMService(api_key=os.getenv("MISTRAL_API_KEY")) + + messages = [ + { + "role": "system", + "content": "You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + }, + ] + + context = LLMContext(messages) + user_aggregator, assistant_aggregator = LLMContextAggregatorPair( + context, + user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()), + ) + + pipeline = Pipeline( + [ + transport.input(), + stt, + user_aggregator, + llm, + tts, + transport.output(), + assistant_aggregator, + ] + ) + + task = PipelineTask( + pipeline, + params=PipelineParams( + enable_metrics=True, + enable_usage_metrics=True, + ), + idle_timeout_secs=runner_args.pipeline_idle_timeout_secs, + ) + + @transport.event_handler("on_client_connected") + async def on_client_connected(transport, client): + logger.info(f"Client connected") + messages.append({"role": "system", "content": "Please introduce yourself to the user."}) + await task.queue_frames([LLMRunFrame()]) + + await asyncio.sleep(10) + logger.info("Updating Mistral LLM settings: temperature=0.1") + await task.queue_frame(LLMUpdateSettingsFrame(update=OpenAILLMSettings(temperature=0.1))) + + @transport.event_handler("on_client_disconnected") + async def on_client_disconnected(transport, client): + logger.info(f"Client disconnected") + await task.cancel() + + runner = PipelineRunner(handle_sigint=runner_args.handle_sigint) + + await runner.run(task) + + +async def bot(runner_args: RunnerArguments): + """Main bot entry point compatible with Pipecat Cloud.""" + transport = await create_transport(runner_args, transport_params) + await run_bot(transport, runner_args) + + +if __name__ == "__main__": + from pipecat.runner.run import main + + main() diff --git a/examples/foundational/55zzd-update-settings-nvidia-llm.py b/examples/foundational/55zzd-update-settings-nvidia-llm.py new file mode 100644 index 000000000..5ffa0ff23 --- /dev/null +++ b/examples/foundational/55zzd-update-settings-nvidia-llm.py @@ -0,0 +1,128 @@ +# +# Copyright (c) 2024-2026, Daily +# +# SPDX-License-Identifier: BSD 2-Clause License +# + +import asyncio +import os + +from dotenv import load_dotenv +from loguru import logger + +from pipecat.audio.vad.silero import SileroVADAnalyzer +from pipecat.frames.frames import LLMRunFrame, LLMUpdateSettingsFrame +from pipecat.pipeline.pipeline import Pipeline +from pipecat.pipeline.runner import PipelineRunner +from pipecat.pipeline.task import PipelineParams, PipelineTask +from pipecat.processors.aggregators.llm_context import LLMContext +from pipecat.processors.aggregators.llm_response_universal import ( + LLMContextAggregatorPair, + LLMUserAggregatorParams, +) +from pipecat.runner.types import RunnerArguments +from pipecat.runner.utils import create_transport +from pipecat.services.cartesia.tts import CartesiaTTSService +from pipecat.services.deepgram.stt import DeepgramSTTService +from pipecat.services.nvidia.llm import NvidiaLLMService +from pipecat.services.openai.base_llm import OpenAILLMSettings +from pipecat.transports.base_transport import BaseTransport, TransportParams +from pipecat.transports.daily.transport import DailyParams +from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams + +load_dotenv(override=True) + +transport_params = { + "daily": lambda: DailyParams( + audio_in_enabled=True, + audio_out_enabled=True, + ), + "twilio": lambda: FastAPIWebsocketParams( + audio_in_enabled=True, + audio_out_enabled=True, + ), + "webrtc": lambda: TransportParams( + audio_in_enabled=True, + audio_out_enabled=True, + ), +} + + +async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): + logger.info(f"Starting bot") + + stt = DeepgramSTTService(api_key=os.getenv("DEEPGRAM_API_KEY")) + + tts = CartesiaTTSService( + api_key=os.getenv("CARTESIA_API_KEY"), + voice_id="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady + ) + + llm = NvidiaLLMService( + api_key=os.getenv("NVIDIA_API_KEY"), model="meta/llama-3.1-405b-instruct" + ) + + messages = [ + { + "role": "system", + "content": "You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + }, + ] + + context = LLMContext(messages) + user_aggregator, assistant_aggregator = LLMContextAggregatorPair( + context, + user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()), + ) + + pipeline = Pipeline( + [ + transport.input(), + stt, + user_aggregator, + llm, + tts, + transport.output(), + assistant_aggregator, + ] + ) + + task = PipelineTask( + pipeline, + params=PipelineParams( + enable_metrics=True, + enable_usage_metrics=True, + ), + idle_timeout_secs=runner_args.pipeline_idle_timeout_secs, + ) + + @transport.event_handler("on_client_connected") + async def on_client_connected(transport, client): + logger.info(f"Client connected") + messages.append({"role": "system", "content": "Please introduce yourself to the user."}) + await task.queue_frames([LLMRunFrame()]) + + await asyncio.sleep(10) + logger.info("Updating NVIDIA LLM settings: temperature=0.1") + await task.queue_frame(LLMUpdateSettingsFrame(update=OpenAILLMSettings(temperature=0.1))) + + @transport.event_handler("on_client_disconnected") + async def on_client_disconnected(transport, client): + logger.info(f"Client disconnected") + await task.cancel() + + runner = PipelineRunner(handle_sigint=runner_args.handle_sigint) + + await runner.run(task) + + +async def bot(runner_args: RunnerArguments): + """Main bot entry point compatible with Pipecat Cloud.""" + transport = await create_transport(runner_args, transport_params) + await run_bot(transport, runner_args) + + +if __name__ == "__main__": + from pipecat.runner.run import main + + main() diff --git a/examples/foundational/55zze-update-settings-ollama-llm.py b/examples/foundational/55zze-update-settings-ollama-llm.py new file mode 100644 index 000000000..ca3714943 --- /dev/null +++ b/examples/foundational/55zze-update-settings-ollama-llm.py @@ -0,0 +1,126 @@ +# +# Copyright (c) 2024-2026, Daily +# +# SPDX-License-Identifier: BSD 2-Clause License +# + +import asyncio +import os + +from dotenv import load_dotenv +from loguru import logger + +from pipecat.audio.vad.silero import SileroVADAnalyzer +from pipecat.frames.frames import LLMRunFrame, LLMUpdateSettingsFrame +from pipecat.pipeline.pipeline import Pipeline +from pipecat.pipeline.runner import PipelineRunner +from pipecat.pipeline.task import PipelineParams, PipelineTask +from pipecat.processors.aggregators.llm_context import LLMContext +from pipecat.processors.aggregators.llm_response_universal import ( + LLMContextAggregatorPair, + LLMUserAggregatorParams, +) +from pipecat.runner.types import RunnerArguments +from pipecat.runner.utils import create_transport +from pipecat.services.cartesia.tts import CartesiaTTSService +from pipecat.services.deepgram.stt import DeepgramSTTService +from pipecat.services.ollama.llm import OLLamaLLMService +from pipecat.services.openai.base_llm import OpenAILLMSettings +from pipecat.transports.base_transport import BaseTransport, TransportParams +from pipecat.transports.daily.transport import DailyParams +from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams + +load_dotenv(override=True) + +transport_params = { + "daily": lambda: DailyParams( + audio_in_enabled=True, + audio_out_enabled=True, + ), + "twilio": lambda: FastAPIWebsocketParams( + audio_in_enabled=True, + audio_out_enabled=True, + ), + "webrtc": lambda: TransportParams( + audio_in_enabled=True, + audio_out_enabled=True, + ), +} + + +async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): + logger.info(f"Starting bot") + + stt = DeepgramSTTService(api_key=os.getenv("DEEPGRAM_API_KEY")) + + tts = CartesiaTTSService( + api_key=os.getenv("CARTESIA_API_KEY"), + voice_id="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady + ) + + llm = OLLamaLLMService(model="llama3.2") # Update to the model you're running locally + + messages = [ + { + "role": "system", + "content": "You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + }, + ] + + context = LLMContext(messages) + user_aggregator, assistant_aggregator = LLMContextAggregatorPair( + context, + user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()), + ) + + pipeline = Pipeline( + [ + transport.input(), + stt, + user_aggregator, + llm, + tts, + transport.output(), + assistant_aggregator, + ] + ) + + task = PipelineTask( + pipeline, + params=PipelineParams( + enable_metrics=True, + enable_usage_metrics=True, + ), + idle_timeout_secs=runner_args.pipeline_idle_timeout_secs, + ) + + @transport.event_handler("on_client_connected") + async def on_client_connected(transport, client): + logger.info(f"Client connected") + messages.append({"role": "system", "content": "Please introduce yourself to the user."}) + await task.queue_frames([LLMRunFrame()]) + + await asyncio.sleep(10) + logger.info("Updating OLLama LLM settings: temperature=0.1") + await task.queue_frame(LLMUpdateSettingsFrame(update=OpenAILLMSettings(temperature=0.1))) + + @transport.event_handler("on_client_disconnected") + async def on_client_disconnected(transport, client): + logger.info(f"Client disconnected") + await task.cancel() + + runner = PipelineRunner(handle_sigint=runner_args.handle_sigint) + + await runner.run(task) + + +async def bot(runner_args: RunnerArguments): + """Main bot entry point compatible with Pipecat Cloud.""" + transport = await create_transport(runner_args, transport_params) + await run_bot(transport, runner_args) + + +if __name__ == "__main__": + from pipecat.runner.run import main + + main() diff --git a/examples/foundational/55zzf-update-settings-openrouter-llm.py b/examples/foundational/55zzf-update-settings-openrouter-llm.py new file mode 100644 index 000000000..90606a572 --- /dev/null +++ b/examples/foundational/55zzf-update-settings-openrouter-llm.py @@ -0,0 +1,126 @@ +# +# Copyright (c) 2024-2026, Daily +# +# SPDX-License-Identifier: BSD 2-Clause License +# + +import asyncio +import os + +from dotenv import load_dotenv +from loguru import logger + +from pipecat.audio.vad.silero import SileroVADAnalyzer +from pipecat.frames.frames import LLMRunFrame, LLMUpdateSettingsFrame +from pipecat.pipeline.pipeline import Pipeline +from pipecat.pipeline.runner import PipelineRunner +from pipecat.pipeline.task import PipelineParams, PipelineTask +from pipecat.processors.aggregators.llm_context import LLMContext +from pipecat.processors.aggregators.llm_response_universal import ( + LLMContextAggregatorPair, + LLMUserAggregatorParams, +) +from pipecat.runner.types import RunnerArguments +from pipecat.runner.utils import create_transport +from pipecat.services.cartesia.tts import CartesiaTTSService +from pipecat.services.deepgram.stt import DeepgramSTTService +from pipecat.services.openai.base_llm import OpenAILLMSettings +from pipecat.services.openrouter.llm import OpenRouterLLMService +from pipecat.transports.base_transport import BaseTransport, TransportParams +from pipecat.transports.daily.transport import DailyParams +from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams + +load_dotenv(override=True) + +transport_params = { + "daily": lambda: DailyParams( + audio_in_enabled=True, + audio_out_enabled=True, + ), + "twilio": lambda: FastAPIWebsocketParams( + audio_in_enabled=True, + audio_out_enabled=True, + ), + "webrtc": lambda: TransportParams( + audio_in_enabled=True, + audio_out_enabled=True, + ), +} + + +async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): + logger.info(f"Starting bot") + + stt = DeepgramSTTService(api_key=os.getenv("DEEPGRAM_API_KEY")) + + tts = CartesiaTTSService( + api_key=os.getenv("CARTESIA_API_KEY"), + voice_id="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady + ) + + llm = OpenRouterLLMService(api_key=os.getenv("OPENROUTER_API_KEY")) + + messages = [ + { + "role": "system", + "content": "You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + }, + ] + + context = LLMContext(messages) + user_aggregator, assistant_aggregator = LLMContextAggregatorPair( + context, + user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()), + ) + + pipeline = Pipeline( + [ + transport.input(), + stt, + user_aggregator, + llm, + tts, + transport.output(), + assistant_aggregator, + ] + ) + + task = PipelineTask( + pipeline, + params=PipelineParams( + enable_metrics=True, + enable_usage_metrics=True, + ), + idle_timeout_secs=runner_args.pipeline_idle_timeout_secs, + ) + + @transport.event_handler("on_client_connected") + async def on_client_connected(transport, client): + logger.info(f"Client connected") + messages.append({"role": "system", "content": "Please introduce yourself to the user."}) + await task.queue_frames([LLMRunFrame()]) + + await asyncio.sleep(10) + logger.info("Updating OpenRouter LLM settings: temperature=0.1") + await task.queue_frame(LLMUpdateSettingsFrame(update=OpenAILLMSettings(temperature=0.1))) + + @transport.event_handler("on_client_disconnected") + async def on_client_disconnected(transport, client): + logger.info(f"Client disconnected") + await task.cancel() + + runner = PipelineRunner(handle_sigint=runner_args.handle_sigint) + + await runner.run(task) + + +async def bot(runner_args: RunnerArguments): + """Main bot entry point compatible with Pipecat Cloud.""" + transport = await create_transport(runner_args, transport_params) + await run_bot(transport, runner_args) + + +if __name__ == "__main__": + from pipecat.runner.run import main + + main() diff --git a/examples/foundational/55zzg-update-settings-perplexity-llm.py b/examples/foundational/55zzg-update-settings-perplexity-llm.py new file mode 100644 index 000000000..771b1c794 --- /dev/null +++ b/examples/foundational/55zzg-update-settings-perplexity-llm.py @@ -0,0 +1,125 @@ +# +# Copyright (c) 2024-2026, Daily +# +# SPDX-License-Identifier: BSD 2-Clause License +# + +import asyncio +import os + +from dotenv import load_dotenv +from loguru import logger + +from pipecat.audio.vad.silero import SileroVADAnalyzer +from pipecat.frames.frames import LLMRunFrame, LLMUpdateSettingsFrame +from pipecat.pipeline.pipeline import Pipeline +from pipecat.pipeline.runner import PipelineRunner +from pipecat.pipeline.task import PipelineParams, PipelineTask +from pipecat.processors.aggregators.llm_context import LLMContext +from pipecat.processors.aggregators.llm_response_universal import ( + LLMContextAggregatorPair, + LLMUserAggregatorParams, +) +from pipecat.runner.types import RunnerArguments +from pipecat.runner.utils import create_transport +from pipecat.services.cartesia.tts import CartesiaTTSService +from pipecat.services.deepgram.stt import DeepgramSTTService +from pipecat.services.openai.base_llm import OpenAILLMSettings +from pipecat.services.perplexity.llm import PerplexityLLMService +from pipecat.transports.base_transport import BaseTransport, TransportParams +from pipecat.transports.daily.transport import DailyParams +from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams + +load_dotenv(override=True) + +transport_params = { + "daily": lambda: DailyParams( + audio_in_enabled=True, + audio_out_enabled=True, + ), + "twilio": lambda: FastAPIWebsocketParams( + audio_in_enabled=True, + audio_out_enabled=True, + ), + "webrtc": lambda: TransportParams( + audio_in_enabled=True, + audio_out_enabled=True, + ), +} + + +async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): + logger.info(f"Starting bot") + + stt = DeepgramSTTService(api_key=os.getenv("DEEPGRAM_API_KEY")) + + tts = CartesiaTTSService( + api_key=os.getenv("CARTESIA_API_KEY"), + voice_id="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady + ) + + llm = PerplexityLLMService(api_key=os.getenv("PERPLEXITY_API_KEY")) + + messages = [ + { + "role": "user", + "content": "You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way. Start by introducing yourself.", + }, + ] + + context = LLMContext(messages) + user_aggregator, assistant_aggregator = LLMContextAggregatorPair( + context, + user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()), + ) + + pipeline = Pipeline( + [ + transport.input(), + stt, + user_aggregator, + llm, + tts, + transport.output(), + assistant_aggregator, + ] + ) + + task = PipelineTask( + pipeline, + params=PipelineParams( + enable_metrics=True, + enable_usage_metrics=True, + ), + idle_timeout_secs=runner_args.pipeline_idle_timeout_secs, + ) + + @transport.event_handler("on_client_connected") + async def on_client_connected(transport, client): + logger.info(f"Client connected") + await task.queue_frames([LLMRunFrame()]) + + await asyncio.sleep(10) + logger.info("Updating Perplexity LLM settings: temperature=0.1") + await task.queue_frame(LLMUpdateSettingsFrame(update=OpenAILLMSettings(temperature=0.1))) + + @transport.event_handler("on_client_disconnected") + async def on_client_disconnected(transport, client): + logger.info(f"Client disconnected") + await task.cancel() + + runner = PipelineRunner(handle_sigint=runner_args.handle_sigint) + + await runner.run(task) + + +async def bot(runner_args: RunnerArguments): + """Main bot entry point compatible with Pipecat Cloud.""" + transport = await create_transport(runner_args, transport_params) + await run_bot(transport, runner_args) + + +if __name__ == "__main__": + from pipecat.runner.run import main + + main() diff --git a/examples/foundational/55zzh-update-settings-qwen-llm.py b/examples/foundational/55zzh-update-settings-qwen-llm.py new file mode 100644 index 000000000..81ace2117 --- /dev/null +++ b/examples/foundational/55zzh-update-settings-qwen-llm.py @@ -0,0 +1,126 @@ +# +# Copyright (c) 2024-2026, Daily +# +# SPDX-License-Identifier: BSD 2-Clause License +# + +import asyncio +import os + +from dotenv import load_dotenv +from loguru import logger + +from pipecat.audio.vad.silero import SileroVADAnalyzer +from pipecat.frames.frames import LLMRunFrame, LLMUpdateSettingsFrame +from pipecat.pipeline.pipeline import Pipeline +from pipecat.pipeline.runner import PipelineRunner +from pipecat.pipeline.task import PipelineParams, PipelineTask +from pipecat.processors.aggregators.llm_context import LLMContext +from pipecat.processors.aggregators.llm_response_universal import ( + LLMContextAggregatorPair, + LLMUserAggregatorParams, +) +from pipecat.runner.types import RunnerArguments +from pipecat.runner.utils import create_transport +from pipecat.services.cartesia.tts import CartesiaTTSService +from pipecat.services.deepgram.stt import DeepgramSTTService +from pipecat.services.openai.base_llm import OpenAILLMSettings +from pipecat.services.qwen.llm import QwenLLMService +from pipecat.transports.base_transport import BaseTransport, TransportParams +from pipecat.transports.daily.transport import DailyParams +from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams + +load_dotenv(override=True) + +transport_params = { + "daily": lambda: DailyParams( + audio_in_enabled=True, + audio_out_enabled=True, + ), + "twilio": lambda: FastAPIWebsocketParams( + audio_in_enabled=True, + audio_out_enabled=True, + ), + "webrtc": lambda: TransportParams( + audio_in_enabled=True, + audio_out_enabled=True, + ), +} + + +async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): + logger.info(f"Starting bot") + + stt = DeepgramSTTService(api_key=os.getenv("DEEPGRAM_API_KEY")) + + tts = CartesiaTTSService( + api_key=os.getenv("CARTESIA_API_KEY"), + voice_id="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady + ) + + llm = QwenLLMService(api_key=os.getenv("QWEN_API_KEY"), model="qwen2.5-72b-instruct") + + messages = [ + { + "role": "system", + "content": "You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + }, + ] + + context = LLMContext(messages) + user_aggregator, assistant_aggregator = LLMContextAggregatorPair( + context, + user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()), + ) + + pipeline = Pipeline( + [ + transport.input(), + stt, + user_aggregator, + llm, + tts, + transport.output(), + assistant_aggregator, + ] + ) + + task = PipelineTask( + pipeline, + params=PipelineParams( + enable_metrics=True, + enable_usage_metrics=True, + ), + idle_timeout_secs=runner_args.pipeline_idle_timeout_secs, + ) + + @transport.event_handler("on_client_connected") + async def on_client_connected(transport, client): + logger.info(f"Client connected") + messages.append({"role": "system", "content": "Please introduce yourself to the user."}) + await task.queue_frames([LLMRunFrame()]) + + await asyncio.sleep(10) + logger.info("Updating Qwen LLM settings: temperature=0.1") + await task.queue_frame(LLMUpdateSettingsFrame(update=OpenAILLMSettings(temperature=0.1))) + + @transport.event_handler("on_client_disconnected") + async def on_client_disconnected(transport, client): + logger.info(f"Client disconnected") + await task.cancel() + + runner = PipelineRunner(handle_sigint=runner_args.handle_sigint) + + await runner.run(task) + + +async def bot(runner_args: RunnerArguments): + """Main bot entry point compatible with Pipecat Cloud.""" + transport = await create_transport(runner_args, transport_params) + await run_bot(transport, runner_args) + + +if __name__ == "__main__": + from pipecat.runner.run import main + + main() diff --git a/examples/foundational/55zzi-update-settings-sambanova-llm.py b/examples/foundational/55zzi-update-settings-sambanova-llm.py new file mode 100644 index 000000000..82382a6bd --- /dev/null +++ b/examples/foundational/55zzi-update-settings-sambanova-llm.py @@ -0,0 +1,126 @@ +# +# Copyright (c) 2024-2026, Daily +# +# SPDX-License-Identifier: BSD 2-Clause License +# + +import asyncio +import os + +from dotenv import load_dotenv +from loguru import logger + +from pipecat.audio.vad.silero import SileroVADAnalyzer +from pipecat.frames.frames import LLMRunFrame, LLMUpdateSettingsFrame +from pipecat.pipeline.pipeline import Pipeline +from pipecat.pipeline.runner import PipelineRunner +from pipecat.pipeline.task import PipelineParams, PipelineTask +from pipecat.processors.aggregators.llm_context import LLMContext +from pipecat.processors.aggregators.llm_response_universal import ( + LLMContextAggregatorPair, + LLMUserAggregatorParams, +) +from pipecat.runner.types import RunnerArguments +from pipecat.runner.utils import create_transport +from pipecat.services.cartesia.tts import CartesiaTTSService +from pipecat.services.deepgram.stt import DeepgramSTTService +from pipecat.services.openai.base_llm import OpenAILLMSettings +from pipecat.services.sambanova.llm import SambaNovaLLMService +from pipecat.transports.base_transport import BaseTransport, TransportParams +from pipecat.transports.daily.transport import DailyParams +from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams + +load_dotenv(override=True) + +transport_params = { + "daily": lambda: DailyParams( + audio_in_enabled=True, + audio_out_enabled=True, + ), + "twilio": lambda: FastAPIWebsocketParams( + audio_in_enabled=True, + audio_out_enabled=True, + ), + "webrtc": lambda: TransportParams( + audio_in_enabled=True, + audio_out_enabled=True, + ), +} + + +async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): + logger.info(f"Starting bot") + + stt = DeepgramSTTService(api_key=os.getenv("DEEPGRAM_API_KEY")) + + tts = CartesiaTTSService( + api_key=os.getenv("CARTESIA_API_KEY"), + voice_id="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady + ) + + llm = SambaNovaLLMService(api_key=os.getenv("SAMBANOVA_API_KEY")) + + messages = [ + { + "role": "system", + "content": "You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + }, + ] + + context = LLMContext(messages) + user_aggregator, assistant_aggregator = LLMContextAggregatorPair( + context, + user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()), + ) + + pipeline = Pipeline( + [ + transport.input(), + stt, + user_aggregator, + llm, + tts, + transport.output(), + assistant_aggregator, + ] + ) + + task = PipelineTask( + pipeline, + params=PipelineParams( + enable_metrics=True, + enable_usage_metrics=True, + ), + idle_timeout_secs=runner_args.pipeline_idle_timeout_secs, + ) + + @transport.event_handler("on_client_connected") + async def on_client_connected(transport, client): + logger.info(f"Client connected") + messages.append({"role": "system", "content": "Please introduce yourself to the user."}) + await task.queue_frames([LLMRunFrame()]) + + await asyncio.sleep(10) + logger.info("Updating SambaNova LLM settings: temperature=0.1") + await task.queue_frame(LLMUpdateSettingsFrame(update=OpenAILLMSettings(temperature=0.1))) + + @transport.event_handler("on_client_disconnected") + async def on_client_disconnected(transport, client): + logger.info(f"Client disconnected") + await task.cancel() + + runner = PipelineRunner(handle_sigint=runner_args.handle_sigint) + + await runner.run(task) + + +async def bot(runner_args: RunnerArguments): + """Main bot entry point compatible with Pipecat Cloud.""" + transport = await create_transport(runner_args, transport_params) + await run_bot(transport, runner_args) + + +if __name__ == "__main__": + from pipecat.runner.run import main + + main() diff --git a/examples/foundational/55zzj-update-settings-together-llm.py b/examples/foundational/55zzj-update-settings-together-llm.py new file mode 100644 index 000000000..1f0a0557f --- /dev/null +++ b/examples/foundational/55zzj-update-settings-together-llm.py @@ -0,0 +1,129 @@ +# +# Copyright (c) 2024-2026, Daily +# +# SPDX-License-Identifier: BSD 2-Clause License +# + +import asyncio +import os + +from dotenv import load_dotenv +from loguru import logger + +from pipecat.audio.vad.silero import SileroVADAnalyzer +from pipecat.frames.frames import LLMRunFrame, LLMUpdateSettingsFrame +from pipecat.pipeline.pipeline import Pipeline +from pipecat.pipeline.runner import PipelineRunner +from pipecat.pipeline.task import PipelineParams, PipelineTask +from pipecat.processors.aggregators.llm_context import LLMContext +from pipecat.processors.aggregators.llm_response_universal import ( + LLMContextAggregatorPair, + LLMUserAggregatorParams, +) +from pipecat.runner.types import RunnerArguments +from pipecat.runner.utils import create_transport +from pipecat.services.cartesia.tts import CartesiaTTSService +from pipecat.services.deepgram.stt import DeepgramSTTService +from pipecat.services.openai.base_llm import OpenAILLMSettings +from pipecat.services.together.llm import TogetherLLMService +from pipecat.transports.base_transport import BaseTransport, TransportParams +from pipecat.transports.daily.transport import DailyParams +from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams + +load_dotenv(override=True) + +transport_params = { + "daily": lambda: DailyParams( + audio_in_enabled=True, + audio_out_enabled=True, + ), + "twilio": lambda: FastAPIWebsocketParams( + audio_in_enabled=True, + audio_out_enabled=True, + ), + "webrtc": lambda: TransportParams( + audio_in_enabled=True, + audio_out_enabled=True, + ), +} + + +async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): + logger.info(f"Starting bot") + + stt = DeepgramSTTService(api_key=os.getenv("DEEPGRAM_API_KEY")) + + tts = CartesiaTTSService( + api_key=os.getenv("CARTESIA_API_KEY"), + voice_id="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady + ) + + llm = TogetherLLMService( + api_key=os.getenv("TOGETHER_API_KEY"), + model="meta-llama/Meta-Llama-3.1-70B-Instruct-Turbo", + ) + + messages = [ + { + "role": "system", + "content": "You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + }, + ] + + context = LLMContext(messages) + user_aggregator, assistant_aggregator = LLMContextAggregatorPair( + context, + user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()), + ) + + pipeline = Pipeline( + [ + transport.input(), + stt, + user_aggregator, + llm, + tts, + transport.output(), + assistant_aggregator, + ] + ) + + task = PipelineTask( + pipeline, + params=PipelineParams( + enable_metrics=True, + enable_usage_metrics=True, + ), + idle_timeout_secs=runner_args.pipeline_idle_timeout_secs, + ) + + @transport.event_handler("on_client_connected") + async def on_client_connected(transport, client): + logger.info(f"Client connected") + messages.append({"role": "system", "content": "Please introduce yourself to the user."}) + await task.queue_frames([LLMRunFrame()]) + + await asyncio.sleep(10) + logger.info("Updating Together LLM settings: temperature=0.1") + await task.queue_frame(LLMUpdateSettingsFrame(update=OpenAILLMSettings(temperature=0.1))) + + @transport.event_handler("on_client_disconnected") + async def on_client_disconnected(transport, client): + logger.info(f"Client disconnected") + await task.cancel() + + runner = PipelineRunner(handle_sigint=runner_args.handle_sigint) + + await runner.run(task) + + +async def bot(runner_args: RunnerArguments): + """Main bot entry point compatible with Pipecat Cloud.""" + transport = await create_transport(runner_args, transport_params) + await run_bot(transport, runner_args) + + +if __name__ == "__main__": + from pipecat.runner.run import main + + main() diff --git a/src/pipecat/services/asyncai/tts.py b/src/pipecat/services/asyncai/tts.py index d01fd4396..c19aa08f8 100644 --- a/src/pipecat/services/asyncai/tts.py +++ b/src/pipecat/services/asyncai/tts.py @@ -179,6 +179,20 @@ class AsyncAITTSService(AudioContextTTSService): self._keepalive_task = None self._context_id = None + async def _update_settings(self, update: TTSSettings) -> dict[str, Any]: + """Apply a settings update. + + Settings are stored but not applied to the active connection. + """ + changed = await super()._update_settings(update) + + if not changed: + return changed + + self._warn_unhandled_updated_settings(changed) + + return changed + def can_generate_metrics(self) -> bool: """Check if this service can generate processing metrics. diff --git a/src/pipecat/services/fal/stt.py b/src/pipecat/services/fal/stt.py index bcfc583c6..91b5a25c8 100644 --- a/src/pipecat/services/fal/stt.py +++ b/src/pipecat/services/fal/stt.py @@ -251,11 +251,6 @@ class FalSTTService(SegmentedSTTService): """ return language_to_fal_language(language) - async def _update_settings(self, update: STTSettings) -> dict[str, Any]: - """Apply a settings update.""" - changed = await super()._update_settings(update) - return changed - @traced_stt async def _handle_transcription( self, transcript: str, is_final: bool, language: Optional[str] = None diff --git a/src/pipecat/services/gradium/tts.py b/src/pipecat/services/gradium/tts.py index c41c77436..8c18c9208 100644 --- a/src/pipecat/services/gradium/tts.py +++ b/src/pipecat/services/gradium/tts.py @@ -128,9 +128,8 @@ class GradiumTTSService(InterruptibleWordTTSService): Returns: Dict mapping changed field names to their previous values. """ - prev_voice = self._voice_id changed = await super()._update_settings(update) - if self._voice_id != prev_voice: + if "voice" in changed: await self._disconnect() await self._connect() else: From 463ea3725b1f6784941a40497960a475a823f586 Mon Sep 17 00:00:00 2001 From: Paul Kompfner Date: Thu, 19 Feb 2026 17:12:24 -0500 Subject: [PATCH 0565/1060] Update Deepgram Flux with the new service settings pattern --- .../55a-update-settings-deepgram-flux-stt.py | 128 ++++++++++++++++++ src/pipecat/services/deepgram/flux/stt.py | 86 ++++++++---- 2 files changed, 191 insertions(+), 23 deletions(-) create mode 100644 examples/foundational/55a-update-settings-deepgram-flux-stt.py diff --git a/examples/foundational/55a-update-settings-deepgram-flux-stt.py b/examples/foundational/55a-update-settings-deepgram-flux-stt.py new file mode 100644 index 000000000..d5fb66a2e --- /dev/null +++ b/examples/foundational/55a-update-settings-deepgram-flux-stt.py @@ -0,0 +1,128 @@ +# +# Copyright (c) 2024-2026, Daily +# +# SPDX-License-Identifier: BSD 2-Clause License +# + +import asyncio +import os + +from dotenv import load_dotenv +from loguru import logger + +from pipecat.audio.vad.silero import SileroVADAnalyzer +from pipecat.frames.frames import LLMRunFrame, STTUpdateSettingsFrame +from pipecat.pipeline.pipeline import Pipeline +from pipecat.pipeline.runner import PipelineRunner +from pipecat.pipeline.task import PipelineParams, PipelineTask +from pipecat.processors.aggregators.llm_context import LLMContext +from pipecat.processors.aggregators.llm_response_universal import ( + LLMContextAggregatorPair, + LLMUserAggregatorParams, +) +from pipecat.runner.types import RunnerArguments +from pipecat.runner.utils import create_transport +from pipecat.services.cartesia.tts import CartesiaTTSService +from pipecat.services.deepgram.flux.stt import DeepgramFluxSTTService, DeepgramFluxSTTSettings +from pipecat.services.openai.llm import OpenAILLMService +from pipecat.transcriptions.language import Language +from pipecat.transports.base_transport import BaseTransport, TransportParams +from pipecat.transports.daily.transport import DailyParams +from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams + +load_dotenv(override=True) + +transport_params = { + "daily": lambda: DailyParams( + audio_in_enabled=True, + audio_out_enabled=True, + ), + "twilio": lambda: FastAPIWebsocketParams( + audio_in_enabled=True, + audio_out_enabled=True, + ), + "webrtc": lambda: TransportParams( + audio_in_enabled=True, + audio_out_enabled=True, + ), +} + + +async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): + logger.info(f"Starting bot") + + stt = DeepgramFluxSTTService(api_key=os.getenv("DEEPGRAM_API_KEY")) + + tts = CartesiaTTSService( + api_key=os.getenv("CARTESIA_API_KEY"), + voice_id="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady + ) + + llm = OpenAILLMService(api_key=os.getenv("OPENAI_API_KEY")) + + messages = [ + { + "role": "system", + "content": "You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + }, + ] + + context = LLMContext(messages) + user_aggregator, assistant_aggregator = LLMContextAggregatorPair( + context, + user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()), + ) + + pipeline = Pipeline( + [ + transport.input(), + stt, + user_aggregator, + llm, + tts, + transport.output(), + assistant_aggregator, + ] + ) + + task = PipelineTask( + pipeline, + params=PipelineParams( + enable_metrics=True, + enable_usage_metrics=True, + ), + idle_timeout_secs=runner_args.pipeline_idle_timeout_secs, + ) + + @transport.event_handler("on_client_connected") + async def on_client_connected(transport, client): + logger.info(f"Client connected") + messages.append({"role": "system", "content": "Please introduce yourself to the user."}) + await task.queue_frames([LLMRunFrame()]) + + await asyncio.sleep(10) + logger.info("Updating Deepgram Flux STT settings: language=es") + await task.queue_frame( + STTUpdateSettingsFrame(update=DeepgramFluxSTTSettings(language=Language.ES)) + ) + + @transport.event_handler("on_client_disconnected") + async def on_client_disconnected(transport, client): + logger.info(f"Client disconnected") + await task.cancel() + + runner = PipelineRunner(handle_sigint=runner_args.handle_sigint) + + await runner.run(task) + + +async def bot(runner_args: RunnerArguments): + """Main bot entry point compatible with Pipecat Cloud.""" + transport = await create_transport(runner_args, transport_params) + await run_bot(transport, runner_args) + + +if __name__ == "__main__": + from pipecat.runner.run import main + + main() diff --git a/src/pipecat/services/deepgram/flux/stt.py b/src/pipecat/services/deepgram/flux/stt.py index dcb5e3429..e82fc4dd8 100644 --- a/src/pipecat/services/deepgram/flux/stt.py +++ b/src/pipecat/services/deepgram/flux/stt.py @@ -9,6 +9,7 @@ import asyncio import json import time +from dataclasses import dataclass, field from enum import Enum from typing import Any, AsyncGenerator, Dict, Optional from urllib.parse import urlencode @@ -27,7 +28,7 @@ from pipecat.frames.frames import ( UserStartedSpeakingFrame, UserStoppedSpeakingFrame, ) -from pipecat.services.settings import STTSettings +from pipecat.services.settings import NOT_GIVEN, STTSettings, _NotGiven from pipecat.services.stt_service import WebsocketSTTService from pipecat.transcriptions.language import Language from pipecat.utils.time import time_now_iso8601 @@ -68,6 +69,34 @@ class FluxEventType(str, Enum): UPDATE = "Update" +@dataclass +class DeepgramFluxSTTSettings(STTSettings): + """Settings for the Deepgram Flux STT service. + + Parameters: + eager_eot_threshold: EagerEndOfTurn/TurnResumed threshold. Off by default. + Lower values = more aggressive (faster response, more LLM calls). + Higher values = more conservative (slower response, fewer LLM calls). + eot_threshold: End-of-turn confidence required to finish a turn (default 0.7). + eot_timeout_ms: Time in ms after speech to finish a turn regardless of EOT + confidence (default 5000). + keyterm: Keyterms to boost recognition accuracy for specialized terminology. + mip_opt_out: Opt out of the Deepgram Model Improvement Program (default False). + tag: Tags to label requests for identification during usage reporting. + min_confidence: Minimum confidence required to create a TranscriptionFrame. + encoding: Audio encoding format (e.g. ``"linear16"``). + """ + + eager_eot_threshold: float | None | _NotGiven = field(default_factory=lambda: NOT_GIVEN) + eot_threshold: float | None | _NotGiven = field(default_factory=lambda: NOT_GIVEN) + eot_timeout_ms: int | None | _NotGiven = field(default_factory=lambda: NOT_GIVEN) + keyterm: list | _NotGiven = field(default_factory=lambda: NOT_GIVEN) + mip_opt_out: bool | None | _NotGiven = field(default_factory=lambda: NOT_GIVEN) + tag: list | _NotGiven = field(default_factory=lambda: NOT_GIVEN) + min_confidence: float | None | _NotGiven = field(default_factory=lambda: NOT_GIVEN) + encoding: str | _NotGiven = field(default_factory=lambda: NOT_GIVEN) + + class DeepgramFluxSTTService(WebsocketSTTService): """Deepgram Flux speech-to-text service. @@ -76,6 +105,8 @@ class DeepgramFluxSTTService(WebsocketSTTService): including advanced turn detection and EagerEndOfTurn events for improved conversational AI performance. """ + _settings: DeepgramFluxSTTSettings + class InputParams(BaseModel): """Configuration parameters for Deepgram Flux API. @@ -168,14 +199,23 @@ class DeepgramFluxSTTService(WebsocketSTTService): **kwargs, ) + params = params or DeepgramFluxSTTService.InputParams() + self._settings = DeepgramFluxSTTSettings( + model=model, + language=Language.EN, + encoding=flux_encoding, + eager_eot_threshold=params.eager_eot_threshold, + eot_threshold=params.eot_threshold, + eot_timeout_ms=params.eot_timeout_ms, + keyterm=params.keyterm or [], + mip_opt_out=params.mip_opt_out, + tag=params.tag or [], + min_confidence=params.min_confidence, + ) + self.set_model_name(model) self._api_key = api_key self._url = url - self._model = model - self._params = params or DeepgramFluxSTTService.InputParams() self._should_interrupt = should_interrupt - self._flux_encoding = flux_encoding - # This is the currently only supported language - self._language = Language.EN self._websocket_url = None self._receive_task = None # Flux event handlers @@ -330,7 +370,7 @@ class DeepgramFluxSTTService(WebsocketSTTService): """ return True - async def _update_settings(self, update: STTSettings) -> dict[str, Any]: + async def _update_settings(self, update: DeepgramFluxSTTSettings) -> dict[str, Any]: """Apply a settings update. Settings are stored but not applied to the active connection. @@ -361,29 +401,29 @@ class DeepgramFluxSTTService(WebsocketSTTService): await super().start(frame) url_params = [ - f"model={self._model}", + f"model={self._settings.model}", f"sample_rate={self.sample_rate}", - f"encoding={self._flux_encoding}", + f"encoding={self._settings.encoding}", ] - if self._params.eager_eot_threshold is not None: - url_params.append(f"eager_eot_threshold={self._params.eager_eot_threshold}") + if self._settings.eager_eot_threshold is not None: + url_params.append(f"eager_eot_threshold={self._settings.eager_eot_threshold}") - if self._params.eot_threshold is not None: - url_params.append(f"eot_threshold={self._params.eot_threshold}") + if self._settings.eot_threshold is not None: + url_params.append(f"eot_threshold={self._settings.eot_threshold}") - if self._params.eot_timeout_ms is not None: - url_params.append(f"eot_timeout_ms={self._params.eot_timeout_ms}") + if self._settings.eot_timeout_ms is not None: + url_params.append(f"eot_timeout_ms={self._settings.eot_timeout_ms}") - if self._params.mip_opt_out is not None: - url_params.append(f"mip_opt_out={str(self._params.mip_opt_out).lower()}") + if self._settings.mip_opt_out is not None: + url_params.append(f"mip_opt_out={str(self._settings.mip_opt_out).lower()}") # Add keyterm parameters (can have multiple) - for keyterm in self._params.keyterm: + for keyterm in self._settings.keyterm: url_params.append(urlencode({"keyterm": keyterm})) # Add tag parameters (can have multiple) - for tag_value in self._params.tag: + for tag_value in self._settings.tag: url_params.append(urlencode({"tag": tag_value})) self._websocket_url = f"{self._url}?{'&'.join(url_params)}" @@ -682,7 +722,7 @@ class DeepgramFluxSTTService(WebsocketSTTService): # Compute the average confidence average_confidence = self._calculate_average_confidence(data) - if not self._params.min_confidence or average_confidence > self._params.min_confidence: + if not self._settings.min_confidence or average_confidence > self._settings.min_confidence: # EndOfTurn means Flux has determined the turn is complete, # so this TranscriptionFrame is always finalized await self.push_frame( @@ -690,7 +730,7 @@ class DeepgramFluxSTTService(WebsocketSTTService): transcript, self._user_id, time_now_iso8601(), - self._language, + self._settings.language, result=data, finalized=True, ) @@ -700,7 +740,7 @@ class DeepgramFluxSTTService(WebsocketSTTService): f"Transcription confidence below min_confidence threshold: {average_confidence}" ) - await self._handle_transcription(transcript, True, self._language) + await self._handle_transcription(transcript, True, self._settings.language) await self.stop_processing_metrics() await self.broadcast_frame(UserStoppedSpeakingFrame) await self._call_event_handler("on_end_of_turn", transcript) @@ -744,7 +784,7 @@ class DeepgramFluxSTTService(WebsocketSTTService): transcript, self._user_id, time_now_iso8601(), - self._language, + self._settings.language, result=data, ) ) From fb27642190b170dd2e785628dbd86b257d730eba Mon Sep 17 00:00:00 2001 From: Paul Kompfner Date: Thu, 19 Feb 2026 18:35:59 -0500 Subject: [PATCH 0566/1060] Add `self._settings` to 6 remaining services - AWSNovaSonicLLMService: new `AWSNovaSonicLLMSettings` with `voice_id` and `endpointing_sensitivity`; remove `self._params` entirely, storing audio I/O config as plain instance variables - NeuphonicHttpTTSService: reuse `NeuphonicTTSSettings`; use inherited `language` field instead of bespoke `lang_code` - NvidiaTTSService: new `NvidiaTTSSettings` with `quality` - PiperTTSService / PiperHttpTTSService: new `PiperTTSSettings` / `PiperHttpTTSSettings` (no extra fields) - SpeechmaticsTTSService: new `SpeechmaticsTTSSettings` with `max_retries` Also remove redundant `lang_code` from `NeuphonicTTSSettings` (both WS and HTTP services now use the inherited `TTSSettings.language` field, with automatic enum conversion via the base class). HTTP services (Neuphonic HTTP, Piper HTTP, Speechmatics) don't override `_update_settings` since the base class applies changes to `self._settings` and subsequent requests read from it automatically. --- ...55za-update-settings-neuphonic-http-tts.py | 127 +++++++++++++++++ ...5zzk-update-settings-aws-nova-sonic-llm.py | 124 +++++++++++++++++ .../55zzl-update-settings-nvidia-tts.py | 125 +++++++++++++++++ .../55zzm-update-settings-speechmatics-tts.py | 129 ++++++++++++++++++ src/pipecat/services/aws/nova_sonic/llm.py | 89 ++++++++---- src/pipecat/services/neuphonic/tts.py | 33 +++-- src/pipecat/services/nvidia/tts.py | 44 ++++-- src/pipecat/services/piper/tts.py | 40 +++++- src/pipecat/services/speechmatics/tts.py | 31 +++-- 9 files changed, 678 insertions(+), 64 deletions(-) create mode 100644 examples/foundational/55za-update-settings-neuphonic-http-tts.py create mode 100644 examples/foundational/55zzk-update-settings-aws-nova-sonic-llm.py create mode 100644 examples/foundational/55zzl-update-settings-nvidia-tts.py create mode 100644 examples/foundational/55zzm-update-settings-speechmatics-tts.py diff --git a/examples/foundational/55za-update-settings-neuphonic-http-tts.py b/examples/foundational/55za-update-settings-neuphonic-http-tts.py new file mode 100644 index 000000000..056b32349 --- /dev/null +++ b/examples/foundational/55za-update-settings-neuphonic-http-tts.py @@ -0,0 +1,127 @@ +# +# Copyright (c) 2024-2026, Daily +# +# SPDX-License-Identifier: BSD 2-Clause License +# + +import asyncio +import os + +import aiohttp +from dotenv import load_dotenv +from loguru import logger + +from pipecat.audio.vad.silero import SileroVADAnalyzer +from pipecat.frames.frames import LLMRunFrame, TTSUpdateSettingsFrame +from pipecat.pipeline.pipeline import Pipeline +from pipecat.pipeline.runner import PipelineRunner +from pipecat.pipeline.task import PipelineParams, PipelineTask +from pipecat.processors.aggregators.llm_context import LLMContext +from pipecat.processors.aggregators.llm_response_universal import ( + LLMContextAggregatorPair, + LLMUserAggregatorParams, +) +from pipecat.runner.types import RunnerArguments +from pipecat.runner.utils import create_transport +from pipecat.services.deepgram.stt import DeepgramSTTService +from pipecat.services.neuphonic.tts import NeuphonicHttpTTSService, NeuphonicTTSSettings +from pipecat.services.openai.llm import OpenAILLMService +from pipecat.transports.base_transport import BaseTransport, TransportParams +from pipecat.transports.daily.transport import DailyParams +from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams + +load_dotenv(override=True) + +transport_params = { + "daily": lambda: DailyParams( + audio_in_enabled=True, + audio_out_enabled=True, + ), + "twilio": lambda: FastAPIWebsocketParams( + audio_in_enabled=True, + audio_out_enabled=True, + ), + "webrtc": lambda: TransportParams( + audio_in_enabled=True, + audio_out_enabled=True, + ), +} + + +async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): + logger.info(f"Starting bot") + + stt = DeepgramSTTService(api_key=os.getenv("DEEPGRAM_API_KEY")) + + async with aiohttp.ClientSession() as session: + tts = NeuphonicHttpTTSService( + api_key=os.getenv("NEUPHONIC_API_KEY"), + aiohttp_session=session, + ) + + llm = OpenAILLMService(api_key=os.getenv("OPENAI_API_KEY")) + + messages = [ + { + "role": "system", + "content": "You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + }, + ] + + context = LLMContext(messages) + user_aggregator, assistant_aggregator = LLMContextAggregatorPair( + context, + user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()), + ) + + pipeline = Pipeline( + [ + transport.input(), + stt, + user_aggregator, + llm, + tts, + transport.output(), + assistant_aggregator, + ] + ) + + task = PipelineTask( + pipeline, + params=PipelineParams( + enable_metrics=True, + enable_usage_metrics=True, + ), + idle_timeout_secs=runner_args.pipeline_idle_timeout_secs, + ) + + @transport.event_handler("on_client_connected") + async def on_client_connected(transport, client): + logger.info(f"Client connected") + messages.append({"role": "system", "content": "Please introduce yourself to the user."}) + await task.queue_frames([LLMRunFrame()]) + + await asyncio.sleep(10) + logger.info("Updating Neuphonic HTTP TTS settings: speed=1.4") + await task.queue_frame(TTSUpdateSettingsFrame(update=NeuphonicTTSSettings(speed=1.4))) + + @transport.event_handler("on_client_disconnected") + async def on_client_disconnected(transport, client): + logger.info(f"Client disconnected") + await task.cancel() + + runner = PipelineRunner(handle_sigint=runner_args.handle_sigint) + + await runner.run(task) + + +async def bot(runner_args: RunnerArguments): + """Main bot entry point compatible with Pipecat Cloud.""" + transport = await create_transport(runner_args, transport_params) + await run_bot(transport, runner_args) + + +if __name__ == "__main__": + from pipecat.runner.run import main + + main() diff --git a/examples/foundational/55zzk-update-settings-aws-nova-sonic-llm.py b/examples/foundational/55zzk-update-settings-aws-nova-sonic-llm.py new file mode 100644 index 000000000..1faafdbac --- /dev/null +++ b/examples/foundational/55zzk-update-settings-aws-nova-sonic-llm.py @@ -0,0 +1,124 @@ +# +# Copyright (c) 2024-2026, Daily +# +# SPDX-License-Identifier: BSD 2-Clause License +# + +import asyncio +import os + +from dotenv import load_dotenv +from loguru import logger + +from pipecat.audio.vad.silero import SileroVADAnalyzer +from pipecat.frames.frames import LLMRunFrame, LLMUpdateSettingsFrame +from pipecat.pipeline.pipeline import Pipeline +from pipecat.pipeline.runner import PipelineRunner +from pipecat.pipeline.task import PipelineParams, PipelineTask +from pipecat.processors.aggregators.llm_context import LLMContext +from pipecat.processors.aggregators.llm_response_universal import ( + LLMContextAggregatorPair, + LLMUserAggregatorParams, +) +from pipecat.runner.types import RunnerArguments +from pipecat.runner.utils import create_transport +from pipecat.services.aws.nova_sonic.llm import AWSNovaSonicLLMService, AWSNovaSonicLLMSettings +from pipecat.transports.base_transport import BaseTransport, TransportParams +from pipecat.transports.daily.transport import DailyParams +from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams + +load_dotenv(override=True) + +transport_params = { + "daily": lambda: DailyParams( + audio_in_enabled=True, + audio_out_enabled=True, + ), + "twilio": lambda: FastAPIWebsocketParams( + audio_in_enabled=True, + audio_out_enabled=True, + ), + "webrtc": lambda: TransportParams( + audio_in_enabled=True, + audio_out_enabled=True, + ), +} + + +async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): + logger.info(f"Starting bot") + + llm = AWSNovaSonicLLMService( + secret_access_key=os.getenv("AWS_SECRET_ACCESS_KEY"), + access_key_id=os.getenv("AWS_ACCESS_KEY_ID"), + region=os.getenv("AWS_REGION"), + ) + + messages = [ + { + "role": "system", + "content": "You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + }, + { + "role": "user", + "content": "Tell me a fun fact!", + }, + ] + + context = LLMContext(messages) + user_aggregator, assistant_aggregator = LLMContextAggregatorPair( + context, + user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()), + ) + + pipeline = Pipeline( + [ + transport.input(), + user_aggregator, + llm, + transport.output(), + assistant_aggregator, + ] + ) + + task = PipelineTask( + pipeline, + params=PipelineParams( + enable_metrics=True, + enable_usage_metrics=True, + ), + idle_timeout_secs=runner_args.pipeline_idle_timeout_secs, + ) + + @transport.event_handler("on_client_connected") + async def on_client_connected(transport, client): + logger.info(f"Client connected") + messages.append({"role": "system", "content": "Please introduce yourself to the user."}) + await task.queue_frames([LLMRunFrame()]) + + await asyncio.sleep(10) + logger.info("Updating AWS Nova Sonic LLM settings: temperature=0.1") + await task.queue_frame( + LLMUpdateSettingsFrame(update=AWSNovaSonicLLMSettings(temperature=0.1)) + ) + + @transport.event_handler("on_client_disconnected") + async def on_client_disconnected(transport, client): + logger.info(f"Client disconnected") + await task.cancel() + + runner = PipelineRunner(handle_sigint=runner_args.handle_sigint) + + await runner.run(task) + + +async def bot(runner_args: RunnerArguments): + """Main bot entry point compatible with Pipecat Cloud.""" + transport = await create_transport(runner_args, transport_params) + await run_bot(transport, runner_args) + + +if __name__ == "__main__": + from pipecat.runner.run import main + + main() diff --git a/examples/foundational/55zzl-update-settings-nvidia-tts.py b/examples/foundational/55zzl-update-settings-nvidia-tts.py new file mode 100644 index 000000000..b92651496 --- /dev/null +++ b/examples/foundational/55zzl-update-settings-nvidia-tts.py @@ -0,0 +1,125 @@ +# +# Copyright (c) 2024-2026, Daily +# +# SPDX-License-Identifier: BSD 2-Clause License +# + +import asyncio +import os + +from dotenv import load_dotenv +from loguru import logger + +from pipecat.audio.vad.silero import SileroVADAnalyzer +from pipecat.frames.frames import LLMRunFrame, TTSUpdateSettingsFrame +from pipecat.pipeline.pipeline import Pipeline +from pipecat.pipeline.runner import PipelineRunner +from pipecat.pipeline.task import PipelineParams, PipelineTask +from pipecat.processors.aggregators.llm_context import LLMContext +from pipecat.processors.aggregators.llm_response_universal import ( + LLMContextAggregatorPair, + LLMUserAggregatorParams, +) +from pipecat.runner.types import RunnerArguments +from pipecat.runner.utils import create_transport +from pipecat.services.deepgram.stt import DeepgramSTTService +from pipecat.services.nvidia.tts import NvidiaTTSService, NvidiaTTSSettings +from pipecat.services.openai.llm import OpenAILLMService +from pipecat.transcriptions.language import Language +from pipecat.transports.base_transport import BaseTransport, TransportParams +from pipecat.transports.daily.transport import DailyParams +from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams + +load_dotenv(override=True) + +transport_params = { + "daily": lambda: DailyParams( + audio_in_enabled=True, + audio_out_enabled=True, + ), + "twilio": lambda: FastAPIWebsocketParams( + audio_in_enabled=True, + audio_out_enabled=True, + ), + "webrtc": lambda: TransportParams( + audio_in_enabled=True, + audio_out_enabled=True, + ), +} + + +async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): + logger.info(f"Starting bot") + + stt = DeepgramSTTService(api_key=os.getenv("DEEPGRAM_API_KEY")) + + tts = NvidiaTTSService(api_key=os.getenv("NVIDIA_API_KEY")) + + llm = OpenAILLMService(api_key=os.getenv("OPENAI_API_KEY")) + + messages = [ + { + "role": "system", + "content": "You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + }, + ] + + context = LLMContext(messages) + user_aggregator, assistant_aggregator = LLMContextAggregatorPair( + context, + user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()), + ) + + pipeline = Pipeline( + [ + transport.input(), + stt, + user_aggregator, + llm, + tts, + transport.output(), + assistant_aggregator, + ] + ) + + task = PipelineTask( + pipeline, + params=PipelineParams( + enable_metrics=True, + enable_usage_metrics=True, + ), + idle_timeout_secs=runner_args.pipeline_idle_timeout_secs, + ) + + @transport.event_handler("on_client_connected") + async def on_client_connected(transport, client): + logger.info(f"Client connected") + messages.append({"role": "system", "content": "Please introduce yourself to the user."}) + await task.queue_frames([LLMRunFrame()]) + + await asyncio.sleep(10) + logger.info('Updating NVIDIA TTS settings: language="ES_US"') + await task.queue_frame( + TTSUpdateSettingsFrame(update=NvidiaTTSSettings(language=Language.ES_US)) + ) + + @transport.event_handler("on_client_disconnected") + async def on_client_disconnected(transport, client): + logger.info(f"Client disconnected") + await task.cancel() + + runner = PipelineRunner(handle_sigint=runner_args.handle_sigint) + + await runner.run(task) + + +async def bot(runner_args: RunnerArguments): + """Main bot entry point compatible with Pipecat Cloud.""" + transport = await create_transport(runner_args, transport_params) + await run_bot(transport, runner_args) + + +if __name__ == "__main__": + from pipecat.runner.run import main + + main() diff --git a/examples/foundational/55zzm-update-settings-speechmatics-tts.py b/examples/foundational/55zzm-update-settings-speechmatics-tts.py new file mode 100644 index 000000000..36b66fe53 --- /dev/null +++ b/examples/foundational/55zzm-update-settings-speechmatics-tts.py @@ -0,0 +1,129 @@ +# +# Copyright (c) 2024-2026, Daily +# +# SPDX-License-Identifier: BSD 2-Clause License +# + +import asyncio +import os + +import aiohttp +from dotenv import load_dotenv +from loguru import logger + +from pipecat.audio.vad.silero import SileroVADAnalyzer +from pipecat.frames.frames import LLMRunFrame, TTSUpdateSettingsFrame +from pipecat.pipeline.pipeline import Pipeline +from pipecat.pipeline.runner import PipelineRunner +from pipecat.pipeline.task import PipelineParams, PipelineTask +from pipecat.processors.aggregators.llm_context import LLMContext +from pipecat.processors.aggregators.llm_response_universal import ( + LLMContextAggregatorPair, + LLMUserAggregatorParams, +) +from pipecat.runner.types import RunnerArguments +from pipecat.runner.utils import create_transport +from pipecat.services.deepgram.stt import DeepgramSTTService +from pipecat.services.openai.llm import OpenAILLMService +from pipecat.services.speechmatics.tts import SpeechmaticsTTSService, SpeechmaticsTTSSettings +from pipecat.transports.base_transport import BaseTransport, TransportParams +from pipecat.transports.daily.transport import DailyParams +from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams + +load_dotenv(override=True) + +transport_params = { + "daily": lambda: DailyParams( + audio_in_enabled=True, + audio_out_enabled=True, + ), + "twilio": lambda: FastAPIWebsocketParams( + audio_in_enabled=True, + audio_out_enabled=True, + ), + "webrtc": lambda: TransportParams( + audio_in_enabled=True, + audio_out_enabled=True, + ), +} + + +async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): + logger.info(f"Starting bot") + + stt = DeepgramSTTService(api_key=os.getenv("DEEPGRAM_API_KEY")) + + async with aiohttp.ClientSession() as session: + tts = SpeechmaticsTTSService( + api_key=os.getenv("SPEECHMATICS_API_KEY"), + aiohttp_session=session, + ) + + llm = OpenAILLMService(api_key=os.getenv("OPENAI_API_KEY")) + + messages = [ + { + "role": "system", + "content": "You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + }, + ] + + context = LLMContext(messages) + user_aggregator, assistant_aggregator = LLMContextAggregatorPair( + context, + user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()), + ) + + pipeline = Pipeline( + [ + transport.input(), + stt, + user_aggregator, + llm, + tts, + transport.output(), + assistant_aggregator, + ] + ) + + task = PipelineTask( + pipeline, + params=PipelineParams( + enable_metrics=True, + enable_usage_metrics=True, + ), + idle_timeout_secs=runner_args.pipeline_idle_timeout_secs, + ) + + @transport.event_handler("on_client_connected") + async def on_client_connected(transport, client): + logger.info(f"Client connected") + messages.append({"role": "system", "content": "Please introduce yourself to the user."}) + await task.queue_frames([LLMRunFrame()]) + + await asyncio.sleep(10) + logger.info('Updating Speechmatics TTS settings: voice="theo"') + await task.queue_frame( + TTSUpdateSettingsFrame(update=SpeechmaticsTTSSettings(voice="theo")) + ) + + @transport.event_handler("on_client_disconnected") + async def on_client_disconnected(transport, client): + logger.info(f"Client disconnected") + await task.cancel() + + runner = PipelineRunner(handle_sigint=runner_args.handle_sigint) + + await runner.run(task) + + +async def bot(runner_args: RunnerArguments): + """Main bot entry point compatible with Pipecat Cloud.""" + transport = await create_transport(runner_args, transport_params) + await run_bot(transport, runner_args) + + +if __name__ == "__main__": + from pipecat.runner.run import main + + main() diff --git a/src/pipecat/services/aws/nova_sonic/llm.py b/src/pipecat/services/aws/nova_sonic/llm.py index 91c2374e3..7d2b9c05e 100644 --- a/src/pipecat/services/aws/nova_sonic/llm.py +++ b/src/pipecat/services/aws/nova_sonic/llm.py @@ -16,7 +16,7 @@ import json import time import uuid import wave -from dataclasses import dataclass +from dataclasses import dataclass, field from enum import Enum from importlib.resources import files from typing import Any, List, Optional @@ -60,7 +60,7 @@ from pipecat.processors.aggregators.openai_llm_context import ( ) from pipecat.processors.frame_processor import FrameDirection from pipecat.services.llm_service import LLMService -from pipecat.services.settings import LLMSettings +from pipecat.services.settings import NOT_GIVEN, LLMSettings, _NotGiven from pipecat.utils.time import time_now_iso8601 try: @@ -186,6 +186,20 @@ class Params(BaseModel): endpointing_sensitivity: Optional[str] = Field(default=None) +@dataclass +class AWSNovaSonicLLMSettings(LLMSettings): + """Settings for AWS Nova Sonic LLM service. + + Parameters: + voice_id: Voice for speech synthesis. + endpointing_sensitivity: Controls how quickly Nova Sonic decides the + user has stopped speaking. Can be "LOW", "MEDIUM", or "HIGH". + """ + + voice_id: str | _NotGiven = field(default_factory=lambda: NOT_GIVEN) + endpointing_sensitivity: str | None | _NotGiven = field(default_factory=lambda: NOT_GIVEN) + + class AWSNovaSonicLLMService(LLMService): """AWS Nova Sonic speech-to-speech LLM service. @@ -193,6 +207,8 @@ class AWSNovaSonicLLMService(LLMService): and function calling capabilities using AWS Nova Sonic model. """ + _settings: AWSNovaSonicLLMSettings + # Override the default adapter to use the AWSNovaSonicLLMAdapter one adapter_class = AWSNovaSonicLLMAdapter @@ -243,23 +259,38 @@ class AWSNovaSonicLLMService(LLMService): self._access_key_id = access_key_id self._session_token = session_token self._region = region - self._model = model self._client: Optional[BedrockRuntimeClient] = None - self._voice_id = voice_id - self._params = params or Params() + params = params or Params() + self._settings = AWSNovaSonicLLMSettings( + model=model, + voice_id=voice_id, + temperature=params.temperature, + max_tokens=params.max_tokens, + top_p=params.top_p, + endpointing_sensitivity=params.endpointing_sensitivity, + ) + self.set_model_name(model) + + # Audio I/O config (hardware settings, not runtime-tunable) + self._input_sample_rate = params.input_sample_rate + self._input_sample_size = params.input_sample_size + self._input_channel_count = params.input_channel_count + self._output_sample_rate = params.output_sample_rate + self._output_sample_size = params.output_sample_size + self._output_channel_count = params.output_channel_count self._system_instruction = system_instruction self._tools = tools # Validate endpointing_sensitivity parameter if ( - self._params.endpointing_sensitivity + self._settings.endpointing_sensitivity and not self._is_endpointing_sensitivity_supported() ): logger.warning( f"endpointing_sensitivity is not supported for model '{model}' and will be ignored. " "This parameter is only supported starting with Nova 2 Sonic (amazon.nova-2-sonic-v1:0)." ) - self._params.endpointing_sensitivity = None + self._settings.endpointing_sensitivity = None if not send_transcription_frames: import warnings @@ -307,7 +338,7 @@ class AWSNovaSonicLLMService(LLMService): # settings # - async def _update_settings(self, update: LLMSettings) -> dict[str, Any]: + async def _update_settings(self, update: AWSNovaSonicLLMSettings) -> dict[str, Any]: """Apply a settings update. Settings are stored but not applied to the active connection. @@ -320,7 +351,7 @@ class AWSNovaSonicLLMService(LLMService): # TODO: someday we could reconnect here to apply updated settings. # Code might look something like the below: # await self._disconnect() - # await self._connect() + # await self._start_connecting() self._warn_unhandled_updated_settings(changed) @@ -496,7 +527,7 @@ class AWSNovaSonicLLMService(LLMService): # Start the bidirectional stream self._stream = await self._client.invoke_model_with_bidirectional_stream( - InvokeModelWithBidirectionalStreamOperationInput(model_id=self._model) + InvokeModelWithBidirectionalStreamOperationInput(model_id=self._settings.model) ) # Send session start event @@ -663,7 +694,7 @@ class AWSNovaSonicLLMService(LLMService): def _is_first_generation_sonic_model(self) -> bool: # Nova Sonic (the older model) is identified by "amazon.nova-sonic-v1:0" - return self._model == "amazon.nova-sonic-v1:0" + return self._settings.model == "amazon.nova-sonic-v1:0" def _is_endpointing_sensitivity_supported(self) -> bool: # endpointing_sensitivity is only supported with Nova 2 Sonic (and, @@ -682,9 +713,9 @@ class AWSNovaSonicLLMService(LLMService): turn_detection_config = ( f""", "turnDetectionConfiguration": {{ - "endpointingSensitivity": "{self._params.endpointing_sensitivity}" + "endpointingSensitivity": "{self._settings.endpointing_sensitivity}" }}""" - if self._params.endpointing_sensitivity + if self._settings.endpointing_sensitivity else "" ) @@ -693,9 +724,9 @@ class AWSNovaSonicLLMService(LLMService): "event": {{ "sessionStart": {{ "inferenceConfiguration": {{ - "maxTokens": {self._params.max_tokens}, - "topP": {self._params.top_p}, - "temperature": {self._params.temperature} + "maxTokens": {self._settings.max_tokens}, + "topP": {self._settings.top_p}, + "temperature": {self._settings.temperature} }}{turn_detection_config} }} }} @@ -730,10 +761,10 @@ class AWSNovaSonicLLMService(LLMService): }}, "audioOutputConfiguration": {{ "mediaType": "audio/lpcm", - "sampleRateHertz": {self._params.output_sample_rate}, - "sampleSizeBits": {self._params.output_sample_size}, - "channelCount": {self._params.output_channel_count}, - "voiceId": "{self._voice_id}", + "sampleRateHertz": {self._output_sample_rate}, + "sampleSizeBits": {self._output_sample_size}, + "channelCount": {self._output_channel_count}, + "voiceId": "{self._settings.voice_id}", "encoding": "base64", "audioType": "SPEECH" }}{tools_config} @@ -758,9 +789,9 @@ class AWSNovaSonicLLMService(LLMService): "role": "USER", "audioInputConfiguration": {{ "mediaType": "audio/lpcm", - "sampleRateHertz": {self._params.input_sample_rate}, - "sampleSizeBits": {self._params.input_sample_size}, - "channelCount": {self._params.input_channel_count}, + "sampleRateHertz": {self._input_sample_rate}, + "sampleSizeBits": {self._input_sample_size}, + "channelCount": {self._input_channel_count}, "audioType": "SPEECH", "encoding": "base64" }} @@ -1043,8 +1074,8 @@ class AWSNovaSonicLLMService(LLMService): audio = base64.b64decode(audio_content) frame = TTSAudioRawFrame( audio=audio, - sample_rate=self._params.output_sample_rate, - num_channels=self._params.output_channel_count, + sample_rate=self._output_sample_rate, + num_channels=self._output_channel_count, ) await self.push_frame(frame) @@ -1328,7 +1359,7 @@ class AWSNovaSonicLLMService(LLMService): """ if not self._is_assistant_response_trigger_needed(): logger.warning( - f"Assistant response trigger not needed for model '{self._model}'; skipping. " + f"Assistant response trigger not needed for model '{self._settings.model}'; skipping. " "An LLMRunFrame() should be sufficient to prompt the assistant to respond, " "assuming the context ends in a user message." ) @@ -1356,9 +1387,9 @@ class AWSNovaSonicLLMService(LLMService): chunk_duration = 0.02 # what we might get from InputAudioRawFrame chunk_size = int( chunk_duration - * self._params.input_sample_rate - * self._params.input_channel_count - * (self._params.input_sample_size / 8) + * self._input_sample_rate + * self._input_channel_count + * (self._input_sample_size / 8) ) # e.g. 0.02 seconds of 16-bit (2-byte) PCM mono audio at 16kHz is 640 bytes # Lead with a bit of blank audio, if needed. diff --git a/src/pipecat/services/neuphonic/tts.py b/src/pipecat/services/neuphonic/tts.py index 2e51297ab..5f58eb3b4 100644 --- a/src/pipecat/services/neuphonic/tts.py +++ b/src/pipecat/services/neuphonic/tts.py @@ -79,13 +79,11 @@ class NeuphonicTTSSettings(TTSSettings): """Settings for Neuphonic TTS service. Parameters: - lang_code: Neuphonic language code. speed: Speech speed multiplier. Defaults to 1.0. encoding: Audio encoding format. sampling_rate: Audio sample rate. """ - lang_code: str | _NotGiven = field(default_factory=lambda: NOT_GIVEN) speed: float | _NotGiven = field(default_factory=lambda: NOT_GIVEN) encoding: str | _NotGiven = field(default_factory=lambda: NOT_GIVEN) sampling_rate: int | _NotGiven = field(default_factory=lambda: NOT_GIVEN) @@ -149,7 +147,7 @@ class NeuphonicTTSService(InterruptibleTTSService): self._api_key = api_key self._url = url self._settings = NeuphonicTTSSettings( - lang_code=self.language_to_service_language(params.language), + language=self.language_to_service_language(params.language), speed=params.speed, encoding=encoding, sampling_rate=sample_rate, @@ -286,7 +284,7 @@ class NeuphonicTTSService(InterruptibleTTSService): logger.debug("Connecting to Neuphonic") tts_config = { - "lang_code": self._settings.lang_code, + "lang_code": self._settings.language, "speed": self._settings.speed, "encoding": self._settings.encoding, "sampling_rate": self._settings.sampling_rate, @@ -298,7 +296,7 @@ class NeuphonicTTSService(InterruptibleTTSService): if value is not None: query_params.append(f"{key}={value}") - url = f"{self._url}/speak/{self._settings.lang_code}" + url = f"{self._url}/speak/{self._settings.language}" if query_params: url += f"?{'&'.join(query_params)}" @@ -407,6 +405,8 @@ class NeuphonicHttpTTSService(TTSService): HTTP-based communication over WebSocket connections. """ + _settings: NeuphonicTTSSettings + class InputParams(BaseModel): """Input parameters for Neuphonic HTTP TTS configuration. @@ -449,10 +449,13 @@ class NeuphonicHttpTTSService(TTSService): self._api_key = api_key self._session = aiohttp_session self._base_url = url.rstrip("/") - self._lang_code = self.language_to_service_language(params.language) or "en" - self._speed = params.speed - self._encoding = encoding - self._voice_id = voice_id + self._settings = NeuphonicTTSSettings( + voice=voice_id, + language=self.language_to_service_language(params.language) or "en", + speed=params.speed, + encoding=encoding, + sampling_rate=sample_rate, + ) def can_generate_metrics(self) -> bool: """Check if this service can generate processing metrics. @@ -536,7 +539,7 @@ class NeuphonicHttpTTSService(TTSService): """ logger.debug(f"Generating TTS: [{text}]") - url = f"{self._base_url}/sse/speak/{self._lang_code}" + url = f"{self._base_url}/sse/speak/{self._settings.language}" headers = { "X-API-KEY": self._api_key, @@ -545,14 +548,14 @@ class NeuphonicHttpTTSService(TTSService): payload = { "text": text, - "lang_code": self._lang_code, - "encoding": self._encoding, + "lang_code": self._settings.language, + "encoding": self._settings.encoding, "sampling_rate": self.sample_rate, - "speed": self._speed, + "speed": self._settings.speed, } - if self._voice_id: - payload["voice_id"] = self._voice_id + if self._settings.voice: + payload["voice_id"] = self._settings.voice try: await self.start_ttfb_metrics() diff --git a/src/pipecat/services/nvidia/tts.py b/src/pipecat/services/nvidia/tts.py index 27ace15fb..22cffc6c1 100644 --- a/src/pipecat/services/nvidia/tts.py +++ b/src/pipecat/services/nvidia/tts.py @@ -12,7 +12,8 @@ gRPC API for high-quality speech synthesis. import asyncio import os -from typing import AsyncGenerator, AsyncIterator, Generator, Mapping, Optional +from dataclasses import dataclass, field +from typing import Any, AsyncGenerator, AsyncIterator, Generator, Mapping, Optional from pipecat.utils.tracing.service_decorators import traced_tts @@ -30,6 +31,7 @@ from pipecat.frames.frames import ( TTSStartedFrame, TTSStoppedFrame, ) +from pipecat.services.settings import NOT_GIVEN, TTSSettings, _NotGiven from pipecat.services.tts_service import TTSService from pipecat.transcriptions.language import Language @@ -42,6 +44,17 @@ except ModuleNotFoundError as e: raise Exception(f"Missing module: {e}") +@dataclass +class NvidiaTTSSettings(TTSSettings): + """Settings for NVIDIA Riva TTS service. + + Parameters: + quality: Audio quality setting (0-100). + """ + + quality: int | _NotGiven = field(default_factory=lambda: NOT_GIVEN) + + class NvidiaTTSService(TTSService): """NVIDIA Riva text-to-speech service. @@ -50,6 +63,8 @@ class NvidiaTTSService(TTSService): configurable quality settings. """ + _settings: NvidiaTTSSettings + class InputParams(BaseModel): """Input parameters for Riva TTS configuration. @@ -94,13 +109,14 @@ class NvidiaTTSService(TTSService): self._server = server self._api_key = api_key - self._voice_id = voice_id - self._language_code = params.language - self._quality = params.quality self._function_id = model_function_map.get("function_id") self._use_ssl = use_ssl + self._settings = NvidiaTTSSettings( + voice=voice_id, + language=params.language, + quality=params.quality, + ) self.set_model_name(model_function_map.get("model_name")) - self._voice_id = voice_id self._service = None self._config = None @@ -133,6 +149,18 @@ class NvidiaTTSService(TTSService): stacklevel=2, ) + async def _update_settings(self, update: NvidiaTTSSettings) -> dict[str, Any]: + """Apply a settings update. + + Settings are stored but not applied to the active connection. + """ + changed = await super()._update_settings(update) + if not changed: + return changed + # TODO: reconnect gRPC client to apply changed settings. + self._warn_unhandled_updated_settings(changed) + return changed + def _initialize_client(self): if self._service is not None: return @@ -181,11 +209,11 @@ class NvidiaTTSService(TTSService): def read_audio_responses() -> Generator[rtts.SynthesizeSpeechResponse, None, None]: responses = self._service.synthesize_online( text, - self._voice_id, - self._language_code, + self._settings.voice, + self._settings.language, sample_rate_hz=self.sample_rate, zero_shot_audio_prompt_file=None, - zero_shot_quality=self._quality, + zero_shot_quality=self._settings.quality, custom_dictionary={}, ) return responses diff --git a/src/pipecat/services/piper/tts.py b/src/pipecat/services/piper/tts.py index a1a038826..0b43d96d2 100644 --- a/src/pipecat/services/piper/tts.py +++ b/src/pipecat/services/piper/tts.py @@ -7,8 +7,9 @@ """Piper TTS service implementation.""" import asyncio +from dataclasses import dataclass from pathlib import Path -from typing import AsyncGenerator, AsyncIterator, Optional +from typing import Any, AsyncGenerator, AsyncIterator, Optional import aiohttp from loguru import logger @@ -19,6 +20,7 @@ from pipecat.frames.frames import ( TTSStartedFrame, TTSStoppedFrame, ) +from pipecat.services.settings import TTSSettings from pipecat.services.tts_service import TTSService from pipecat.utils.tracing.service_decorators import traced_tts @@ -31,6 +33,13 @@ except ModuleNotFoundError as e: raise Exception(f"Missing module: {e}") +@dataclass +class PiperTTSSettings(TTSSettings): + """Settings for Piper TTS service.""" + + pass + + class PiperTTSService(TTSService): """Piper TTS service implementation. @@ -39,6 +48,8 @@ class PiperTTSService(TTSService): match the configured sample rate. """ + _settings: PiperTTSSettings + def __init__( self, *, @@ -60,7 +71,7 @@ class PiperTTSService(TTSService): """ super().__init__(**kwargs) - self._voice_id = voice_id + self._settings = PiperTTSSettings(voice=voice_id) download_dir = download_dir or Path.cwd() @@ -85,6 +96,18 @@ class PiperTTSService(TTSService): """ return True + async def _update_settings(self, update: PiperTTSSettings) -> dict[str, Any]: + """Apply a settings update. + + Settings are stored but not applied to the active connection. + """ + changed = await super()._update_settings(update) + if not changed: + return changed + # TODO: voice changes would require re-downloading and loading the model. + self._warn_unhandled_updated_settings(changed) + return changed + @traced_tts async def run_tts(self, text: str, context_id: str) -> AsyncGenerator[Frame, None]: """Generate speech from text using Piper. @@ -143,6 +166,13 @@ class PiperTTSService(TTSService): # $ uv pip install "piper-tts[http]" # $ uv run python -m piper.http_server -m en_US-ryan-high # +@dataclass +class PiperHttpTTSSettings(TTSSettings): + """Settings for Piper HTTP TTS service.""" + + pass + + class PiperHttpTTSService(TTSService): """Piper HTTP TTS service implementation. @@ -151,6 +181,8 @@ class PiperHttpTTSService(TTSService): rates and automatic WAV header removal. """ + _settings: PiperHttpTTSSettings + def __init__( self, *, @@ -175,7 +207,7 @@ class PiperHttpTTSService(TTSService): self._base_url = base_url self._session = aiohttp_session - self._model_id = voice_id + self._settings = PiperHttpTTSSettings(voice=voice_id) def can_generate_metrics(self) -> bool: """Check if this service can generate processing metrics. @@ -205,7 +237,7 @@ class PiperHttpTTSService(TTSService): data = { "text": text, - "voice": self._model_id, + "voice": self._settings.voice, } async with self._session.post(self._base_url, json=data, headers=headers) as response: diff --git a/src/pipecat/services/speechmatics/tts.py b/src/pipecat/services/speechmatics/tts.py index 0907b4e26..7c8d9fca5 100644 --- a/src/pipecat/services/speechmatics/tts.py +++ b/src/pipecat/services/speechmatics/tts.py @@ -7,7 +7,8 @@ """Speechmatics TTS service integration.""" import asyncio -from typing import AsyncGenerator, Optional +from dataclasses import dataclass, field +from typing import Any, AsyncGenerator, Optional from urllib.parse import urlencode import aiohttp @@ -21,6 +22,7 @@ from pipecat.frames.frames import ( TTSStartedFrame, TTSStoppedFrame, ) +from pipecat.services.settings import NOT_GIVEN, TTSSettings, _NotGiven from pipecat.services.tts_service import TTSService from pipecat.utils.network import exponential_backoff_time from pipecat.utils.tracing.service_decorators import traced_tts @@ -35,6 +37,17 @@ except ModuleNotFoundError as e: raise Exception(f"Missing module: {e}") +@dataclass +class SpeechmaticsTTSSettings(TTSSettings): + """Settings for Speechmatics TTS service. + + Parameters: + max_retries: Maximum number of retries for HTTP requests. + """ + + max_retries: int | _NotGiven = field(default_factory=lambda: NOT_GIVEN) + + class SpeechmaticsTTSService(TTSService): """Speechmatics TTS service implementation. @@ -42,6 +55,8 @@ class SpeechmaticsTTSService(TTSService): It converts text to speech and returns raw PCM audio data for real-time playback. """ + _settings: SpeechmaticsTTSSettings + SPEECHMATICS_SAMPLE_RATE = 16000 class InputParams(BaseModel): @@ -91,11 +106,11 @@ class SpeechmaticsTTSService(TTSService): if not self._api_key: raise ValueError("Missing Speechmatics API key") - # Default parameters - self._params = params or SpeechmaticsTTSService.InputParams() - - # Set voice from constructor parameter - self._voice_id = voice_id + params = params or SpeechmaticsTTSService.InputParams() + self._settings = SpeechmaticsTTSSettings( + voice=voice_id, + max_retries=params.max_retries, + ) def can_generate_metrics(self) -> bool: """Check if this service can generate processing metrics. @@ -131,7 +146,7 @@ class SpeechmaticsTTSService(TTSService): } # Complete HTTP URL - url = _get_endpoint_url(self._base_url, self._voice_id, self.sample_rate) + url = _get_endpoint_url(self._base_url, self._settings.voice, self.sample_rate) try: # Start TTS TTFB metrics @@ -159,7 +174,7 @@ class SpeechmaticsTTSService(TTSService): attempt += 1 # Check if we've exceeded the maximum number of attempts - if attempt >= self._params.max_retries: + if attempt >= self._settings.max_retries: raise ValueError() # Report error frame From bc830c16f1f0695dd336b4e04bf0e65849b432c2 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Aleix=20Conchillo=20Flaqu=C3=A9?= Date: Thu, 19 Feb 2026 20:52:00 -0800 Subject: [PATCH 0567/1060] Fix mutable default arguments in LLMContextAggregatorPair Replace mutable default parameter values with None and instantiate inside the method body to avoid shared state across calls. --- .../processors/aggregators/llm_response_universal.py | 6 ++++-- 1 file changed, 4 insertions(+), 2 deletions(-) diff --git a/src/pipecat/processors/aggregators/llm_response_universal.py b/src/pipecat/processors/aggregators/llm_response_universal.py index c41885655..e5884a868 100644 --- a/src/pipecat/processors/aggregators/llm_response_universal.py +++ b/src/pipecat/processors/aggregators/llm_response_universal.py @@ -1257,8 +1257,8 @@ class LLMContextAggregatorPair: self, context: LLMContext, *, - user_params: LLMUserAggregatorParams = LLMUserAggregatorParams(), - assistant_params: LLMAssistantAggregatorParams = LLMAssistantAggregatorParams(), + user_params: Optional[LLMUserAggregatorParams] = None, + assistant_params: Optional[LLMAssistantAggregatorParams] = None, ): """Initialize the LLM context aggregator pair. @@ -1267,6 +1267,8 @@ class LLMContextAggregatorPair: user_params: Parameters for the user context aggregator. assistant_params: Parameters for the assistant context aggregator. """ + user_params = user_params or LLMUserAggregatorParams() + assistant_params = assistant_params or LLMAssistantAggregatorParams() self._user = LLMUserAggregator(context, params=user_params) self._assistant = LLMAssistantAggregator(context, params=assistant_params) From 2024285c751ed382789e2d34c648bb2d87ae8a1b Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Aleix=20Conchillo=20Flaqu=C3=A9?= Date: Thu, 19 Feb 2026 20:52:31 -0800 Subject: [PATCH 0568/1060] Add changelog entries for PR #3782 --- changelog/3782.fixed.md | 1 + 1 file changed, 1 insertion(+) create mode 100644 changelog/3782.fixed.md diff --git a/changelog/3782.fixed.md b/changelog/3782.fixed.md new file mode 100644 index 000000000..7d21fdeab --- /dev/null +++ b/changelog/3782.fixed.md @@ -0,0 +1 @@ +- Fixed mutable default arguments in `LLMContextAggregatorPair.__init__()` that could cause shared state across instances. From 4d136e1e286696827859a2a3d4b366d2726b1325 Mon Sep 17 00:00:00 2001 From: Mark Backman Date: Fri, 20 Feb 2026 07:15:38 -0700 Subject: [PATCH 0569/1060] Align DeepgramSageMakerSTTService finalize pattern with DeepgramSTTService --- src/pipecat/services/deepgram/stt_sagemaker.py | 15 ++++++++++----- 1 file changed, 10 insertions(+), 5 deletions(-) diff --git a/src/pipecat/services/deepgram/stt_sagemaker.py b/src/pipecat/services/deepgram/stt_sagemaker.py index 99f6cf487..8fc95b726 100644 --- a/src/pipecat/services/deepgram/stt_sagemaker.py +++ b/src/pipecat/services/deepgram/stt_sagemaker.py @@ -368,7 +368,6 @@ class DeepgramSageMakerSTTService(STTService): return is_final = parsed.get("is_final", False) - speech_final = parsed.get("speech_final", False) # Extract language if available language = None @@ -376,8 +375,12 @@ class DeepgramSageMakerSTTService(STTService): language = alternatives[0]["languages"][0] language = Language(language) - if is_final and speech_final: - # Final transcription + if is_final: + # Check if this response is from a finalize() call. + # Only mark as finalized when both we requested it AND Deepgram confirms it. + from_finalize = parsed.get("from_finalize", False) + if from_finalize: + self.confirm_finalize() await self.push_frame( TranscriptionFrame( transcript, @@ -435,10 +438,12 @@ class DeepgramSageMakerSTTService(STTService): if isinstance(frame, VADUserStartedSpeakingFrame): await self._start_metrics() elif isinstance(frame, VADUserStoppedSpeakingFrame): - # Send finalize message to Deepgram when user stops speaking - # This tells Deepgram to flush any remaining audio and return final results + # https://developers.deepgram.com/docs/finalize + # Mark that we're awaiting a from_finalize response + self.request_finalize() if self._client and self._client.is_active: try: await self._client.send_json({"type": "Finalize"}) except Exception as e: logger.warning(f"Error sending Finalize message: {e}") + logger.trace(f"Triggered finalize event on: {frame.name=}, {direction=}") From 43d686c622ebbb6b7eaa38477b1cbaf4aba77d9e Mon Sep 17 00:00:00 2001 From: Mark Backman Date: Fri, 20 Feb 2026 07:17:36 -0700 Subject: [PATCH 0570/1060] Add changelog entry for PR #3784 --- changelog/3784.fixed.md | 1 + 1 file changed, 1 insertion(+) create mode 100644 changelog/3784.fixed.md diff --git a/changelog/3784.fixed.md b/changelog/3784.fixed.md new file mode 100644 index 000000000..e88431f16 --- /dev/null +++ b/changelog/3784.fixed.md @@ -0,0 +1 @@ +- Fixed `DeepgramSageMakerSTTService` to properly track finalize lifecycle using `request_finalize()` / `confirm_finalize()` and use `is_final` (instead of `is_final and speech_final`) for final transcription detection, matching `DeepgramSTTService` behavior. From 5d8a5bf750a314efb82720e336c6264648c2afb9 Mon Sep 17 00:00:00 2001 From: Paul Kompfner Date: Fri, 20 Feb 2026 09:31:22 -0500 Subject: [PATCH 0571/1060] Add initialization of `self._settings` to service superclasses (`STTService`, `TTSService`, `LLMService`), using "generic" settings for those services (`STTSettings`, `TTSSettings`, `LLMSettings`) --- src/pipecat/services/llm_service.py | 1 + src/pipecat/services/stt_service.py | 1 + src/pipecat/services/tts_service.py | 1 + 3 files changed, 3 insertions(+) diff --git a/src/pipecat/services/llm_service.py b/src/pipecat/services/llm_service.py index 83d60defb..9db7ad27a 100644 --- a/src/pipecat/services/llm_service.py +++ b/src/pipecat/services/llm_service.py @@ -205,6 +205,7 @@ class LLMService(UserTurnCompletionLLMServiceMixin, AIService): self._tracing_enabled: bool = False self._skip_tts: Optional[bool] = None self._summary_task: Optional[asyncio.Task] = None + self._settings = LLMSettings() # Here in case subclass doesn't implement more specific settings (hopefully shouldn't happen) self._register_event_handler("on_function_calls_started") self._register_event_handler("on_completion_timeout") diff --git a/src/pipecat/services/stt_service.py b/src/pipecat/services/stt_service.py index fdcefcbd5..47b83ab56 100644 --- a/src/pipecat/services/stt_service.py +++ b/src/pipecat/services/stt_service.py @@ -105,6 +105,7 @@ class STTService(AIService): self._audio_passthrough = audio_passthrough self._init_sample_rate = sample_rate self._sample_rate = 0 + self._settings = STTSettings() # Here in case subclass doesn't implement more specific settings (hopefully shouldn't happen) self._tracing_enabled: bool = False self._muted: bool = False self._user_id: str = "" diff --git a/src/pipecat/services/tts_service.py b/src/pipecat/services/tts_service.py index 6cd33b3e4..ebf0e602a 100644 --- a/src/pipecat/services/tts_service.py +++ b/src/pipecat/services/tts_service.py @@ -192,6 +192,7 @@ class TTSService(AIService): self._init_sample_rate = sample_rate self._sample_rate = 0 self._voice_id: str = "" + self._settings = TTSSettings() # Here in case subclass doesn't implement more specific settings (hopefully shouldn't happen) self._text_aggregator: BaseTextAggregator = text_aggregator or SimpleTextAggregator() if text_aggregator: import warnings From 273692421fab018b3bff661ca281e931010cdada Mon Sep 17 00:00:00 2001 From: Mark Backman Date: Fri, 20 Feb 2026 08:08:00 -0700 Subject: [PATCH 0572/1060] Add DeepgramSageMakerTTSService for Deepgram TTS on AWS SageMaker Adds a TTS service that connects to Deepgram models deployed on AWS SageMaker endpoints via HTTP/2 bidirectional streaming. Supports the Deepgram TTS protocol (Speak, Flush, Clear, Close) over the BiDi client, with interruption handling and per-turn TTFB metrics. Updates the example and env.example with separate STT/TTS endpoint names. --- env.example | 3 +- .../07c-interruptible-deepgram-sagemaker.py | 21 +- .../services/deepgram/tts_sagemaker.py | 315 ++++++++++++++++++ 3 files changed, 333 insertions(+), 6 deletions(-) create mode 100644 src/pipecat/services/deepgram/tts_sagemaker.py diff --git a/env.example b/env.example index 6e7db21e2..bc14ea0bf 100644 --- a/env.example +++ b/env.example @@ -47,7 +47,8 @@ DAILY_ROOM_URL=https://... # Deepgram DEEPGRAM_API_KEY=... -SAGEMAKER_ENDPOINT_NAME=... +SAGEMAKER_STT_ENDPOINT_NAME=... +SAGEMAKER_TTS_ENDPOINT_NAME=... # DeepSeek DEEPSEEK_API_KEY=... diff --git a/examples/foundational/07c-interruptible-deepgram-sagemaker.py b/examples/foundational/07c-interruptible-deepgram-sagemaker.py index 51a4b1bcb..f6d1c9354 100644 --- a/examples/foundational/07c-interruptible-deepgram-sagemaker.py +++ b/examples/foundational/07c-interruptible-deepgram-sagemaker.py @@ -23,8 +23,10 @@ from pipecat.processors.aggregators.llm_response_universal import ( from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport from pipecat.services.aws.llm import AWSBedrockLLMService +from pipecat.services.deepgram.stt import DeepgramSTTService from pipecat.services.deepgram.stt_sagemaker import DeepgramSageMakerSTTService from pipecat.services.deepgram.tts import DeepgramTTSService +from pipecat.services.deepgram.tts_sagemaker import DeepgramSageMakerTTSService from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams @@ -57,12 +59,21 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): # This requires: # - AWS credentials configured (via environment variables or AWS CLI) # - A deployed SageMaker endpoint with Deepgram model - stt = DeepgramSageMakerSTTService( - endpoint_name=os.getenv("SAGEMAKER_ENDPOINT_NAME"), - region=os.getenv("AWS_REGION"), - ) + # stt = DeepgramSageMakerSTTService( + # endpoint_name=os.getenv("SAGEMAKER_STT_ENDPOINT_NAME"), + # region=os.getenv("AWS_REGION"), + # ) + stt = DeepgramSTTService(api_key=os.getenv("DEEPGRAM_API_KEY")) - tts = DeepgramTTSService(api_key=os.getenv("DEEPGRAM_API_KEY"), voice="aura-2-andromeda-en") + # Initialize Deepgram SageMaker TTS Service + # This requires: + # - AWS credentials configured (via environment variables or AWS CLI) + # - A deployed SageMaker endpoint with Deepgram TTS model + tts = DeepgramSageMakerTTSService( + endpoint_name=os.getenv("SAGEMAKER_TTS_ENDPOINT_NAME"), + region=os.getenv("AWS_REGION"), + voice="aura-2-andromeda-en", + ) llm = AWSBedrockLLMService( aws_region=os.getenv("AWS_REGION"), diff --git a/src/pipecat/services/deepgram/tts_sagemaker.py b/src/pipecat/services/deepgram/tts_sagemaker.py new file mode 100644 index 000000000..7c04bc299 --- /dev/null +++ b/src/pipecat/services/deepgram/tts_sagemaker.py @@ -0,0 +1,315 @@ +# +# Copyright (c) 2024-2026, Daily +# +# SPDX-License-Identifier: BSD 2-Clause License +# + +"""Deepgram text-to-speech service for AWS SageMaker. + +This module provides a Pipecat TTS service that connects to Deepgram models +deployed on AWS SageMaker endpoints. Uses HTTP/2 bidirectional streaming for +low-latency real-time speech synthesis with support for interruptions and +streaming audio output. +""" + +import asyncio +import json +from typing import AsyncGenerator, Optional + +from loguru import logger + +from pipecat.frames.frames import ( + BotStoppedSpeakingFrame, + CancelFrame, + EndFrame, + ErrorFrame, + Frame, + InterruptionFrame, + LLMFullResponseEndFrame, + StartFrame, + TTSAudioRawFrame, + TTSStartedFrame, +) +from pipecat.processors.frame_processor import FrameDirection +from pipecat.services.aws.sagemaker.bidi_client import SageMakerBidiClient +from pipecat.services.tts_service import TTSService +from pipecat.utils.tracing.service_decorators import traced_tts + + +class DeepgramSageMakerTTSService(TTSService): + """Deepgram text-to-speech service for AWS SageMaker. + + Provides real-time speech synthesis using Deepgram models deployed on + AWS SageMaker endpoints. Uses HTTP/2 bidirectional streaming for low-latency + audio generation with support for interruptions via the Clear message. + + Requirements: + + - AWS credentials configured (via environment variables, AWS CLI, or instance metadata) + - A deployed SageMaker endpoint with Deepgram TTS model: https://developers.deepgram.com/docs/deploy-amazon-sagemaker + - ``pipecat-ai[sagemaker]`` installed + + Example:: + + tts = DeepgramSageMakerTTSService( + endpoint_name="my-deepgram-tts-endpoint", + region="us-east-2", + voice="aura-2-helena-en", + ) + """ + + def __init__( + self, + *, + endpoint_name: str, + region: str, + voice: str = "aura-2-helena-en", + sample_rate: Optional[int] = None, + encoding: str = "linear16", + **kwargs, + ): + """Initialize the Deepgram SageMaker TTS service. + + Args: + endpoint_name: Name of the SageMaker endpoint with Deepgram TTS model + deployed (e.g., "my-deepgram-tts-endpoint"). + region: AWS region where the endpoint is deployed (e.g., "us-east-2"). + voice: Voice model to use for synthesis. Defaults to "aura-2-helena-en". + sample_rate: Audio sample rate in Hz. If None, uses the value from StartFrame. + encoding: Audio encoding format. Defaults to "linear16". + **kwargs: Additional arguments passed to the parent TTSService. + """ + super().__init__( + sample_rate=sample_rate, + push_stop_frames=True, + pause_frame_processing=True, + append_trailing_space=True, + **kwargs, + ) + + self._endpoint_name = endpoint_name + self._region = region + self._encoding = encoding + self.set_voice(voice) + + self._client: Optional[SageMakerBidiClient] = None + self._response_task: Optional[asyncio.Task] = None + self._context_id: Optional[str] = None + self._ttfb_started: bool = False + + def can_generate_metrics(self) -> bool: + """Check if this service can generate processing metrics. + + Returns: + True, as Deepgram SageMaker TTS service supports metrics generation. + """ + return True + + async def start(self, frame: StartFrame): + """Start the Deepgram SageMaker TTS service. + + Args: + frame: The start frame containing initialization parameters. + """ + await super().start(frame) + await self._connect() + + async def stop(self, frame: EndFrame): + """Stop the Deepgram SageMaker TTS service. + + Args: + frame: The end frame. + """ + await super().stop(frame) + await self._disconnect() + + async def cancel(self, frame: CancelFrame): + """Cancel the Deepgram SageMaker TTS service. + + Args: + frame: The cancel frame. + """ + await super().cancel(frame) + await self._disconnect() + + async def process_frame(self, frame: Frame, direction: FrameDirection): + """Process frames with special handling for LLM response end. + + Args: + frame: The frame to process. + direction: The direction of frame processing. + """ + await super().process_frame(frame, direction) + + if isinstance(frame, (LLMFullResponseEndFrame, EndFrame)): + await self.flush_audio() + elif isinstance(frame, BotStoppedSpeakingFrame): + self._ttfb_started = False + + async def _connect(self): + """Connect to the SageMaker endpoint and start the BiDi session. + + Builds the Deepgram TTS query string, creates the BiDi client, + starts the streaming session, and launches a background task for processing + responses. + """ + logger.debug("Connecting to Deepgram TTS on SageMaker...") + + query_string = ( + f"model={self._voice_id}&encoding={self._encoding}&sample_rate={self.sample_rate}" + ) + + self._client = SageMakerBidiClient( + endpoint_name=self._endpoint_name, + region=self._region, + model_invocation_path="v1/speak", + model_query_string=query_string, + ) + + try: + await self._client.start_session() + + self._response_task = self.create_task(self._process_responses()) + + logger.debug("Connected to Deepgram TTS on SageMaker") + await self._call_event_handler("on_connected") + + except Exception as e: + await self.push_error(error_msg=f"Unknown error occurred: {e}", exception=e) + await self._call_event_handler("on_connection_error", str(e)) + + async def _disconnect(self): + """Disconnect from the SageMaker endpoint. + + Sends a Close message to Deepgram, cancels the response processing task, + and closes the BiDi session. Safe to call multiple times. + """ + if self._client and self._client.is_active: + logger.debug("Disconnecting from Deepgram TTS on SageMaker...") + + try: + await self._client.send_json({"type": "Close"}) + except Exception as e: + logger.warning(f"Failed to send Close message: {e}") + + if self._response_task and not self._response_task.done(): + await self.cancel_task(self._response_task) + + await self._client.close_session() + + logger.debug("Disconnected from Deepgram TTS on SageMaker") + await self._call_event_handler("on_disconnected") + + async def _process_responses(self): + """Process streaming responses from Deepgram TTS on SageMaker. + + Continuously receives responses from the BiDi stream. Attempts to decode + each payload as UTF-8 JSON for control messages (Flushed, Cleared, Metadata, + Warning). If decoding fails, treats the payload as raw audio bytes and pushes + a TTSAudioRawFrame downstream. + """ + try: + while self._client and self._client.is_active: + result = await self._client.receive_response() + + if result is None: + break + + if hasattr(result, "value") and hasattr(result.value, "bytes_"): + if result.value.bytes_: + payload = result.value.bytes_ + + # Try to decode as JSON control message first + try: + response_data = payload.decode("utf-8") + parsed = json.loads(response_data) + msg_type = parsed.get("type") + + if msg_type == "Metadata": + logger.trace(f"Received metadata: {parsed}") + elif msg_type == "Flushed": + logger.trace(f"Received Flushed: {parsed}") + elif msg_type == "Cleared": + logger.trace(f"Received Cleared: {parsed}") + elif msg_type == "Warning": + logger.warning( + f"{self} warning: " + f"{parsed.get('description', 'Unknown warning')}" + ) + else: + logger.debug(f"Received unknown message type: {parsed}") + + except (UnicodeDecodeError, json.JSONDecodeError): + # Not JSON — treat as raw audio bytes + await self.stop_ttfb_metrics() + frame = TTSAudioRawFrame( + payload, + self.sample_rate, + 1, + context_id=self._context_id, + ) + await self.push_frame(frame) + + except asyncio.CancelledError: + logger.debug("TTS response processor cancelled") + except Exception as e: + await self.push_error(error_msg=f"Unknown error occurred: {e}", exception=e) + finally: + logger.debug("TTS response processor stopped") + + async def _handle_interruption(self, frame: InterruptionFrame, direction: FrameDirection): + """Handle interruption by sending Clear message to Deepgram. + + The Clear message will clear Deepgram's internal text buffer and stop + sending audio, allowing for a new response to be generated. + """ + await super()._handle_interruption(frame, direction) + self._ttfb_started = False + + if self._client and self._client.is_active: + try: + await self._client.send_json({"type": "Clear"}) + except Exception as e: + logger.error(f"{self} error sending Clear message: {e}") + + async def flush_audio(self): + """Flush any pending audio synthesis by sending Flush command. + + This should be called when the LLM finishes a complete response to force + generation of audio from Deepgram's internal text buffer. + """ + if self._client and self._client.is_active: + try: + await self._client.send_json({"type": "Flush"}) + except Exception as e: + logger.error(f"{self} error sending Flush message: {e}") + + @traced_tts + async def run_tts(self, text: str, context_id: str) -> AsyncGenerator[Frame, None]: + """Generate speech from text using Deepgram TTS on SageMaker. + + Args: + text: The text to synthesize into speech. + context_id: The context ID for tracking audio frames. + + Yields: + Frame: TTSStartedFrame, then None (audio comes asynchronously via + the response processor). + """ + logger.debug(f"{self}: Generating TTS [{text}]") + + try: + if not self._ttfb_started: + await self.start_ttfb_metrics() + self._ttfb_started = True + await self.start_tts_usage_metrics(text) + + yield TTSStartedFrame(context_id=context_id) + self._context_id = context_id + + await self._client.send_json({"type": "Speak", "text": text}) + + yield None + + except Exception as e: + yield ErrorFrame(error=f"Unknown error occurred: {e}") From 62ada92188aff008e43971a5833db53afc6bb0a8 Mon Sep 17 00:00:00 2001 From: Mark Backman Date: Fri, 20 Feb 2026 08:09:57 -0700 Subject: [PATCH 0573/1060] Add changelog for PR #3785 --- changelog/3785.added.md | 1 + 1 file changed, 1 insertion(+) create mode 100644 changelog/3785.added.md diff --git a/changelog/3785.added.md b/changelog/3785.added.md new file mode 100644 index 000000000..90a4172d4 --- /dev/null +++ b/changelog/3785.added.md @@ -0,0 +1 @@ +- Added `DeepgramSageMakerTTSService` for running Deepgram TTS models deployed on AWS SageMaker endpoints via HTTP/2 bidirectional streaming. Supports the Deepgram TTS protocol (Speak, Flush, Clear, Close), interruption handling, and per-turn TTFB metrics. From 82ce3ea8de2b0e0577976195c9690dbf7d41ae76 Mon Sep 17 00:00:00 2001 From: Mark Backman Date: Fri, 20 Feb 2026 08:10:41 -0700 Subject: [PATCH 0574/1060] Update 07c example to use DeepgramSageMakerTTSService --- .../07c-interruptible-deepgram-sagemaker.py | 11 ++++------- 1 file changed, 4 insertions(+), 7 deletions(-) diff --git a/examples/foundational/07c-interruptible-deepgram-sagemaker.py b/examples/foundational/07c-interruptible-deepgram-sagemaker.py index f6d1c9354..aced7666f 100644 --- a/examples/foundational/07c-interruptible-deepgram-sagemaker.py +++ b/examples/foundational/07c-interruptible-deepgram-sagemaker.py @@ -23,9 +23,7 @@ from pipecat.processors.aggregators.llm_response_universal import ( from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport from pipecat.services.aws.llm import AWSBedrockLLMService -from pipecat.services.deepgram.stt import DeepgramSTTService from pipecat.services.deepgram.stt_sagemaker import DeepgramSageMakerSTTService -from pipecat.services.deepgram.tts import DeepgramTTSService from pipecat.services.deepgram.tts_sagemaker import DeepgramSageMakerTTSService from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams @@ -59,11 +57,10 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): # This requires: # - AWS credentials configured (via environment variables or AWS CLI) # - A deployed SageMaker endpoint with Deepgram model - # stt = DeepgramSageMakerSTTService( - # endpoint_name=os.getenv("SAGEMAKER_STT_ENDPOINT_NAME"), - # region=os.getenv("AWS_REGION"), - # ) - stt = DeepgramSTTService(api_key=os.getenv("DEEPGRAM_API_KEY")) + stt = DeepgramSageMakerSTTService( + endpoint_name=os.getenv("SAGEMAKER_STT_ENDPOINT_NAME"), + region=os.getenv("AWS_REGION"), + ) # Initialize Deepgram SageMaker TTS Service # This requires: From f4e9825c03b14648704e296745af40a9e7f54c9f Mon Sep 17 00:00:00 2001 From: Paul Kompfner Date: Fri, 20 Feb 2026 10:48:16 -0500 Subject: [PATCH 0575/1060] Remove `self._voice_id` from TTS Service implementations in favor of `self._settings.voice` --- .claude/skills/cleanup/SKILL.md | 3 +-- src/pipecat/services/asyncai/tts.py | 9 +++---- src/pipecat/services/aws/tts.py | 6 ++--- src/pipecat/services/azure/tts.py | 7 ++--- src/pipecat/services/camb/tts.py | 5 ++-- src/pipecat/services/cartesia/tts.py | 10 +++---- src/pipecat/services/deepgram/tts.py | 9 +++---- src/pipecat/services/elevenlabs/tts.py | 8 +++--- src/pipecat/services/google/tts.py | 26 +++++++++---------- src/pipecat/services/gradium/tts.py | 4 +-- src/pipecat/services/groq/tts.py | 4 +-- src/pipecat/services/hathora/tts.py | 6 ++--- src/pipecat/services/hume/tts.py | 4 +-- src/pipecat/services/inworld/tts.py | 4 +-- src/pipecat/services/kokoro/tts.py | 5 ++-- src/pipecat/services/lmnt/tts.py | 4 +-- src/pipecat/services/minimax/tts.py | 8 +++--- src/pipecat/services/neuphonic/tts.py | 7 ++--- src/pipecat/services/openai/tts.py | 5 ++-- src/pipecat/services/playht/tts.py | 9 +++---- src/pipecat/services/resembleai/tts.py | 6 ++--- src/pipecat/services/rime/tts.py | 10 +++---- src/pipecat/services/sarvam/tts.py | 25 ++++++++---------- src/pipecat/services/tts_service.py | 24 +++++++++-------- src/pipecat/services/xtts/tts.py | 5 ++-- .../utils/tracing/service_decorators.py | 5 ++-- 26 files changed, 103 insertions(+), 115 deletions(-) diff --git a/.claude/skills/cleanup/SKILL.md b/.claude/skills/cleanup/SKILL.md index c0f4945b7..5e699d588 100644 --- a/.claude/skills/cleanup/SKILL.md +++ b/.claude/skills/cleanup/SKILL.md @@ -291,9 +291,8 @@ class NewTTSService(TTSService): voice: Voice identifier to use. **kwargs: Additional arguments passed to the parent service. """ - super().__init__(**kwargs) + super().__init__(voice=voice, **kwargs) self._api_key = api_key - self._voice_id = voice ``` --- diff --git a/src/pipecat/services/asyncai/tts.py b/src/pipecat/services/asyncai/tts.py index c19aa08f8..323fa3906 100644 --- a/src/pipecat/services/asyncai/tts.py +++ b/src/pipecat/services/asyncai/tts.py @@ -153,6 +153,7 @@ class AsyncAITTSService(AudioContextTTSService): pause_frame_processing=True, push_stop_frames=True, sample_rate=sample_rate, + voice=voice_id, **kwargs, ) @@ -173,7 +174,6 @@ class AsyncAITTSService(AudioContextTTSService): ) self.set_model_name(model) - self._voice_id = voice_id self._receive_task = None self._keepalive_task = None @@ -278,7 +278,7 @@ class AsyncAITTSService(AudioContextTTSService): ) init_msg = { "model_id": self._model_name, - "voice": {"mode": "id", "id": self._voice_id}, + "voice": {"mode": "id", "id": self._settings.voice}, "output_format": { "container": self._settings.output_container, "encoding": self._settings.output_encoding, @@ -497,7 +497,7 @@ class AsyncAIHttpTTSService(TTSService): params: Additional input parameters for voice customization. **kwargs: Additional arguments passed to the parent TTSService. """ - super().__init__(sample_rate=sample_rate, **kwargs) + super().__init__(sample_rate=sample_rate, voice=voice_id, **kwargs) params = params or AsyncAIHttpTTSService.InputParams() @@ -514,7 +514,6 @@ class AsyncAIHttpTTSService(TTSService): if params.language else None, ) - self._voice_id = voice_id self.set_model_name(model) self._session = aiohttp_session @@ -561,7 +560,7 @@ class AsyncAIHttpTTSService(TTSService): logger.debug(f"{self}: Generating TTS [{text}]") try: - voice_config = {"mode": "id", "id": self._voice_id} + voice_config = {"mode": "id", "id": self._settings.voice} await self.start_ttfb_metrics() payload = { "model_id": self._model_name, diff --git a/src/pipecat/services/aws/tts.py b/src/pipecat/services/aws/tts.py index e223a1abc..a277bc0b2 100644 --- a/src/pipecat/services/aws/tts.py +++ b/src/pipecat/services/aws/tts.py @@ -195,7 +195,7 @@ class AWSPollyTTSService(TTSService): params: Additional input parameters for voice customization. **kwargs: Additional arguments passed to parent TTSService class. """ - super().__init__(sample_rate=sample_rate, **kwargs) + super().__init__(sample_rate=sample_rate, voice=voice_id, **kwargs) params = params or AWSPollyTTSService.InputParams() @@ -222,8 +222,6 @@ class AWSPollyTTSService(TTSService): self._resampler = create_stream_resampler() - self._voice_id = voice_id - def can_generate_metrics(self) -> bool: """Check if this service can generate processing metrics. @@ -299,7 +297,7 @@ class AWSPollyTTSService(TTSService): "Text": ssml, "TextType": "ssml", "OutputFormat": "pcm", - "VoiceId": self._voice_id, + "VoiceId": self._settings.voice, "Engine": self._settings.engine, # AWS only supports 8000 and 16000 for PCM. We select 16000. "SampleRate": "16000", diff --git a/src/pipecat/services/azure/tts.py b/src/pipecat/services/azure/tts.py index b69e60b69..2d4c01dc9 100644 --- a/src/pipecat/services/azure/tts.py +++ b/src/pipecat/services/azure/tts.py @@ -165,12 +165,12 @@ class AzureBaseTTSService: role=params.role, style=params.style, style_degree=params.style_degree, + voice=voice, volume=params.volume, ) self._api_key = api_key self._region = region - self._voice_id = voice self._speech_synthesizer = None def language_to_service_language(self, language: Language) -> Optional[str]: @@ -194,7 +194,7 @@ class AzureBaseTTSService: f"" - f"" + f"" "" ) @@ -295,6 +295,7 @@ class AzureTTSService(WordTTSService, AzureBaseTTSService): push_stop_frames=True, pause_frame_processing=True, sample_rate=sample_rate, + voice=voice, **kwargs, ) @@ -733,7 +734,7 @@ class AzureHttpTTSService(TTSService, AzureBaseTTSService): params: Voice and synthesis parameters configuration. **kwargs: Additional arguments passed to parent TTSService. """ - super().__init__(sample_rate=sample_rate, **kwargs) + super().__init__(sample_rate=sample_rate, voice=voice, **kwargs) # Initialize Azure-specific functionality from mixin self._init_azure_base(api_key=api_key, region=region, voice=voice, params=params) diff --git a/src/pipecat/services/camb/tts.py b/src/pipecat/services/camb/tts.py index 40dabd17e..ec0853424 100644 --- a/src/pipecat/services/camb/tts.py +++ b/src/pipecat/services/camb/tts.py @@ -213,7 +213,7 @@ class CambTTSService(TTSService): params: Additional voice parameters. If None, uses defaults. **kwargs: Additional arguments passed to parent TTSService. """ - super().__init__(sample_rate=sample_rate, **kwargs) + super().__init__(sample_rate=sample_rate, voice=voice_id, **kwargs) self._api_key = api_key self._timeout = timeout @@ -238,7 +238,6 @@ class CambTTSService(TTSService): ) self.set_model_name(model) - self._voice_id = voice_id self._client = None @@ -299,7 +298,7 @@ class CambTTSService(TTSService): # Build SDK parameters tts_kwargs: Dict[str, Any] = { "text": text, - "voice_id": self._voice_id, + "voice_id": self._settings.voice, "language": self._settings.language, "speech_model": self.model_name, "output_configuration": StreamTtsOutputConfiguration(format="pcm_s16le"), diff --git a/src/pipecat/services/cartesia/tts.py b/src/pipecat/services/cartesia/tts.py index 0d8936fdd..a16aa2b39 100644 --- a/src/pipecat/services/cartesia/tts.py +++ b/src/pipecat/services/cartesia/tts.py @@ -313,6 +313,7 @@ class CartesiaTTSService(AudioContextWordTTSService): pause_frame_processing=True, sample_rate=sample_rate, text_aggregator=text_aggregator, + voice=voice_id, **kwargs, ) @@ -340,9 +341,9 @@ class CartesiaTTSService(AudioContextWordTTSService): emotion=params.emotion, generation_config=params.generation_config, pronunciation_dict_id=params.pronunciation_dict_id, + voice=voice_id, ) self.set_model_name(model) - self._voice_id = voice_id self._context_id = None self._receive_task = None @@ -440,7 +441,7 @@ class CartesiaTTSService(AudioContextWordTTSService): ): voice_config = {} voice_config["mode"] = "id" - voice_config["id"] = self._voice_id + voice_config["id"] = self._settings.voice if is_given(self._settings.emotion) and self._settings.emotion: with warnings.catch_warnings(): @@ -720,7 +721,7 @@ class CartesiaHttpTTSService(TTSService): params: Additional input parameters for voice customization. **kwargs: Additional arguments passed to the parent TTSService. """ - super().__init__(sample_rate=sample_rate, **kwargs) + super().__init__(sample_rate=sample_rate, voice=voice_id, **kwargs) params = params or CartesiaHttpTTSService.InputParams() @@ -741,7 +742,6 @@ class CartesiaHttpTTSService(TTSService): generation_config=params.generation_config, pronunciation_dict_id=params.pronunciation_dict_id, ) - self._voice_id = voice_id self.set_model_name(model) self._client = AsyncCartesia( @@ -809,7 +809,7 @@ class CartesiaHttpTTSService(TTSService): logger.debug(f"{self}: Generating TTS [{text}]") try: - voice_config = {"mode": "id", "id": self._voice_id} + voice_config = {"mode": "id", "id": self._settings.voice} if is_given(self._settings.emotion) and self._settings.emotion: with warnings.catch_warnings(): diff --git a/src/pipecat/services/deepgram/tts.py b/src/pipecat/services/deepgram/tts.py index 3458a4529..a8b46ce7e 100644 --- a/src/pipecat/services/deepgram/tts.py +++ b/src/pipecat/services/deepgram/tts.py @@ -101,6 +101,7 @@ class DeepgramTTSService(WebsocketTTSService): pause_frame_processing=True, push_stop_frames=True, append_trailing_space=True, + voice=voice, **kwargs, ) @@ -111,7 +112,6 @@ class DeepgramTTSService(WebsocketTTSService): voice=voice, encoding=encoding, ) - self._voice_id = voice self._receive_task = None self._context_id: Optional[str] = None @@ -210,7 +210,7 @@ class DeepgramTTSService(WebsocketTTSService): # Build WebSocket URL with query parameters params = [] - params.append(f"model={self._voice_id}") + params.append(f"model={self._settings.voice}") params.append(f"encoding={self._settings.encoding}") params.append(f"sample_rate={self.sample_rate}") @@ -388,7 +388,7 @@ class DeepgramHttpTTSService(TTSService): encoding: Audio encoding format. Defaults to "linear16". **kwargs: Additional arguments passed to parent TTSService class. """ - super().__init__(sample_rate=sample_rate, **kwargs) + super().__init__(sample_rate=sample_rate, voice=voice, **kwargs) self._api_key = api_key self._session = aiohttp_session @@ -398,7 +398,6 @@ class DeepgramHttpTTSService(TTSService): voice=voice, encoding=encoding, ) - self._voice_id = voice def can_generate_metrics(self) -> bool: """Check if the service can generate metrics. @@ -427,7 +426,7 @@ class DeepgramHttpTTSService(TTSService): headers = {"Authorization": f"Token {self._api_key}", "Content-Type": "application/json"} params = { - "model": self._voice_id, + "model": self._settings.voice, "encoding": self._settings.encoding, "sample_rate": self.sample_rate, "container": "none", diff --git a/src/pipecat/services/elevenlabs/tts.py b/src/pipecat/services/elevenlabs/tts.py index 9503866a7..73e9027d3 100644 --- a/src/pipecat/services/elevenlabs/tts.py +++ b/src/pipecat/services/elevenlabs/tts.py @@ -400,6 +400,7 @@ class ElevenLabsTTSService(AudioContextWordTTSService): push_stop_frames=True, pause_frame_processing=True, sample_rate=sample_rate, + voice=voice_id, **kwargs, ) @@ -424,7 +425,6 @@ class ElevenLabsTTSService(AudioContextWordTTSService): apply_text_normalization=params.apply_text_normalization, ) self.set_model_name(model) - self._voice_id = voice_id self._output_format = "" # initialized in start() self._voice_settings = self._set_voice_settings() @@ -607,7 +607,7 @@ class ElevenLabsTTSService(AudioContextWordTTSService): logger.debug("Connecting to ElevenLabs") - voice_id = self._voice_id + voice_id = self._settings.voice model = self.model_name output_format = self._output_format url = f"{self._url}/v1/text-to-speech/{voice_id}/multi-stream-input?model_id={model}&output_format={output_format}&auto_mode={self._settings.auto_mode}" @@ -906,6 +906,7 @@ class ElevenLabsHttpTTSService(WordTTSService): push_text_frames=False, push_stop_frames=True, sample_rate=sample_rate, + voice=voice_id, **kwargs, ) @@ -931,7 +932,6 @@ class ElevenLabsHttpTTSService(WordTTSService): apply_text_normalization=params.apply_text_normalization, ) self.set_model_name(model) - self._voice_id = voice_id self._output_format = "" # initialized in start() self._voice_settings = self._set_voice_settings() self._pronunciation_dictionary_locators = params.pronunciation_dictionary_locators @@ -1098,7 +1098,7 @@ class ElevenLabsHttpTTSService(WordTTSService): logger.debug(f"{self}: Generating TTS [{text}]") # Use the with-timestamps endpoint - url = f"{self._base_url}/v1/text-to-speech/{self._voice_id}/stream/with-timestamps" + url = f"{self._base_url}/v1/text-to-speech/{self._settings.voice}/stream/with-timestamps" payload: Dict[str, Union[str, Dict[str, Union[float, bool]]]] = { "text": text, diff --git a/src/pipecat/services/google/tts.py b/src/pipecat/services/google/tts.py index 60bed9c6d..33fa1b2a8 100644 --- a/src/pipecat/services/google/tts.py +++ b/src/pipecat/services/google/tts.py @@ -602,7 +602,7 @@ class GoogleHttpTTSService(TTSService): params: Voice customization parameters including pitch, rate, volume, etc. **kwargs: Additional arguments passed to parent TTSService. """ - super().__init__(sample_rate=sample_rate, **kwargs) + super().__init__(sample_rate=sample_rate, voice=voice_id, **kwargs) params = params or GoogleHttpTTSService.InputParams() @@ -618,8 +618,8 @@ class GoogleHttpTTSService(TTSService): else "en-US", gender=params.gender, google_style=params.google_style, + voice=voice_id, ) - self._voice_id = voice_id self._client: texttospeech_v1.TextToSpeechAsyncClient = self._create_client( credentials, credentials_path ) @@ -707,7 +707,7 @@ class GoogleHttpTTSService(TTSService): ssml = "" # Voice tag - voice_attrs = [f"name='{self._voice_id}'"] + voice_attrs = [f"name='{self._settings.voice}'"] language = self._settings.language voice_attrs.append(f"language='{language}'") @@ -766,8 +766,8 @@ class GoogleHttpTTSService(TTSService): await self.start_ttfb_metrics() # Check if the voice is a Chirp voice (including Chirp 3) or Journey voice - is_chirp_voice = "chirp" in self._voice_id.lower() - is_journey_voice = "journey" in self._voice_id.lower() + is_chirp_voice = "chirp" in self._settings.voice.lower() + is_journey_voice = "journey" in self._settings.voice.lower() # Create synthesis input based on voice_id if is_chirp_voice or is_journey_voice: @@ -778,7 +778,7 @@ class GoogleHttpTTSService(TTSService): synthesis_input = texttospeech_v1.SynthesisInput(ssml=ssml) voice = texttospeech_v1.VoiceSelectionParams( - language_code=self._settings.language, name=self._voice_id + language_code=self._settings.language, name=self._settings.voice ) # Build audio config with conditional speaking_rate audio_config_params = { @@ -1015,7 +1015,7 @@ class GoogleTTSService(GoogleBaseTTSService): params: Language configuration parameters. **kwargs: Additional arguments passed to parent TTSService. """ - super().__init__(sample_rate=sample_rate, **kwargs) + super().__init__(sample_rate=sample_rate, voice=voice_id, **kwargs) params = params or GoogleTTSService.InputParams() @@ -1025,8 +1025,8 @@ class GoogleTTSService(GoogleBaseTTSService): if params.language else "en-US", speaking_rate=params.speaking_rate, + voice=voice_id, ) - self._voice_id = voice_id self._voice_cloning_key = voice_cloning_key self._client: texttospeech_v1.TextToSpeechAsyncClient = self._create_client( credentials, credentials_path @@ -1073,7 +1073,7 @@ class GoogleTTSService(GoogleBaseTTSService): ) else: voice = texttospeech_v1.VoiceSelectionParams( - language_code=self._settings.language, name=self._voice_id + language_code=self._settings.language, name=self._settings.voice ) # Create streaming config @@ -1220,7 +1220,7 @@ class GeminiTTSService(GoogleBaseTTSService): f"Google TTS only supports {self.GOOGLE_SAMPLE_RATE}Hz sample rate. " f"Current rate of {sample_rate}Hz may cause issues." ) - super().__init__(sample_rate=sample_rate, **kwargs) + super().__init__(sample_rate=sample_rate, voice=voice_id, **kwargs) params = params or GeminiTTSService.InputParams() @@ -1229,7 +1229,6 @@ class GeminiTTSService(GoogleBaseTTSService): self._location = location self._model = model - self._voice_id = voice_id self._settings = GeminiTTSSettings( language=self.language_to_service_language(params.language) if params.language @@ -1237,6 +1236,7 @@ class GeminiTTSService(GoogleBaseTTSService): prompt=params.prompt, multi_speaker=params.multi_speaker, speaker_configs=params.speaker_configs, + voice=voice_id, ) self._client: texttospeech_v1.TextToSpeechAsyncClient = self._create_client( @@ -1306,7 +1306,7 @@ class GeminiTTSService(GoogleBaseTTSService): speaker_voice_configs.append( texttospeech_v1.MultispeakerPrebuiltVoice( speaker_alias=speaker_config["speaker_alias"], - speaker_id=speaker_config.get("speaker_id", self._voice_id), + speaker_id=speaker_config.get("speaker_id", self._settings.voice), ) ) @@ -1323,7 +1323,7 @@ class GeminiTTSService(GoogleBaseTTSService): # Single speaker mode voice = texttospeech_v1.VoiceSelectionParams( language_code=self._settings.language, - name=self._voice_id, + name=self._settings.voice, model_name=self._model, ) diff --git a/src/pipecat/services/gradium/tts.py b/src/pipecat/services/gradium/tts.py index 8c18c9208..e3d855c5c 100644 --- a/src/pipecat/services/gradium/tts.py +++ b/src/pipecat/services/gradium/tts.py @@ -91,6 +91,7 @@ class GradiumTTSService(InterruptibleWordTTSService): push_stop_frames=True, pause_frame_processing=True, sample_rate=SAMPLE_RATE, + voice=voice_id, **kwargs, ) @@ -99,7 +100,6 @@ class GradiumTTSService(InterruptibleWordTTSService): # Store service configuration self._api_key = api_key self._url = url - self._voice_id = voice_id self._json_config = json_config self._settings = GradiumTTSSettings( model=model, @@ -208,7 +208,7 @@ class GradiumTTSService(InterruptibleWordTTSService): setup_msg = { "type": "setup", "output_format": "pcm", - "voice_id": self._voice_id, + "voice_id": self._settings.voice, } if self._json_config is not None: setup_msg["json_config"] = self._json_config diff --git a/src/pipecat/services/groq/tts.py b/src/pipecat/services/groq/tts.py index b3b4c5f57..78d744461 100644 --- a/src/pipecat/services/groq/tts.py +++ b/src/pipecat/services/groq/tts.py @@ -102,6 +102,7 @@ class GroqTTSService(TTSService): super().__init__( pause_frame_processing=True, sample_rate=sample_rate, + voice=voice_id, **kwargs, ) @@ -110,7 +111,6 @@ class GroqTTSService(TTSService): self._api_key = api_key self._model_name = model_name self._output_format = output_format - self._voice_id = voice_id self._params = params self._settings = GroqTTSSettings( @@ -151,7 +151,7 @@ class GroqTTSService(TTSService): try: response = await self._client.audio.speech.create( model=self._model_name, - voice=self._voice_id, + voice=self._settings.voice, response_format=self._output_format, input=text, ) diff --git a/src/pipecat/services/hathora/tts.py b/src/pipecat/services/hathora/tts.py index e15dfcc54..6e75feeca 100644 --- a/src/pipecat/services/hathora/tts.py +++ b/src/pipecat/services/hathora/tts.py @@ -109,6 +109,7 @@ class HathoraTTSService(TTSService): """ super().__init__( sample_rate=sample_rate, + voice=voice_id, **kwargs, ) self._model = model @@ -125,7 +126,6 @@ class HathoraTTSService(TTSService): ) self.set_model_name(model) - self._voice_id = voice_id def can_generate_metrics(self) -> bool: """Check if this service can generate processing metrics. @@ -154,8 +154,8 @@ class HathoraTTSService(TTSService): payload = {"model": self._model, "text": text} - if self._voice_id is not None: - payload["voice"] = self._voice_id + if self._settings.voice is not None: + payload["voice"] = self._settings.voice if self._settings.speed is not None: payload["speed"] = self._settings.speed if self._settings.config is not None: diff --git a/src/pipecat/services/hume/tts.py b/src/pipecat/services/hume/tts.py index 27c4b417e..a52922787 100644 --- a/src/pipecat/services/hume/tts.py +++ b/src/pipecat/services/hume/tts.py @@ -126,6 +126,7 @@ class HumeTTSService(WordTTSService): sample_rate=sample_rate, push_text_frames=False, push_stop_frames=True, + voice=voice_id, **kwargs, ) @@ -142,7 +143,6 @@ class HumeTTSService(WordTTSService): speed=params.speed, trailing_silence=params.trailing_silence, ) - self._voice_id = voice_id self._audio_bytes = b"" @@ -263,7 +263,7 @@ class HumeTTSService(WordTTSService): # Build the request payload utterance_kwargs: dict[str, Any] = { "text": text, - "voice": PostedUtteranceVoiceWithId(id=self._voice_id), + "voice": PostedUtteranceVoiceWithId(id=self._settings.voice), } if self._settings.description is not None: utterance_kwargs["description"] = self._settings.description diff --git a/src/pipecat/services/inworld/tts.py b/src/pipecat/services/inworld/tts.py index bdbbb82d7..34dc34933 100644 --- a/src/pipecat/services/inworld/tts.py +++ b/src/pipecat/services/inworld/tts.py @@ -144,6 +144,7 @@ class InworldHttpTTSService(WordTTSService): push_text_frames=False, push_stop_frames=True, sample_rate=sample_rate, + voice=voice_id, **kwargs, ) @@ -173,7 +174,6 @@ class InworldHttpTTSService(WordTTSService): self._cumulative_time = 0.0 - self._voice_id = voice_id self.set_model_name(model) def can_generate_metrics(self) -> bool: @@ -519,6 +519,7 @@ class InworldTTSService(AudioContextWordTTSService): sample_rate=sample_rate, aggregate_sentences=aggregate_sentences, append_trailing_space=append_trailing_space, + voice=voice_id, **kwargs, ) @@ -563,7 +564,6 @@ class InworldTTSService(AudioContextWordTTSService): # Track the end time of the last word in the current generation self._generation_end_time = 0.0 - self._voice_id = voice_id self.set_model_name(model) def can_generate_metrics(self) -> bool: diff --git a/src/pipecat/services/kokoro/tts.py b/src/pipecat/services/kokoro/tts.py index 735145da7..9f2aac368 100644 --- a/src/pipecat/services/kokoro/tts.py +++ b/src/pipecat/services/kokoro/tts.py @@ -137,11 +137,10 @@ class KokoroTTSService(TTSService): **kwargs: Additional arguments passed to parent `TTSService`. """ - super().__init__(**kwargs) + super().__init__(voice=voice_id, **kwargs) params = params or KokoroTTSService.InputParams() - self._voice_id = voice_id self._lang_code = language_to_kokoro_language(params.language) self._settings = KokoroTTSSettings( @@ -182,7 +181,7 @@ class KokoroTTSService(TTSService): yield TTSStartedFrame(context_id=context_id) stream = self._kokoro.create_stream( - text, voice=self._voice_id, lang=self._lang_code, speed=1.0 + text, voice=self._settings.voice, lang=self._lang_code, speed=1.0 ) async for samples, sample_rate in stream: diff --git a/src/pipecat/services/lmnt/tts.py b/src/pipecat/services/lmnt/tts.py index 94f4a1a9e..ab56f2296 100644 --- a/src/pipecat/services/lmnt/tts.py +++ b/src/pipecat/services/lmnt/tts.py @@ -118,11 +118,11 @@ class LmntTTSService(InterruptibleTTSService): push_stop_frames=True, pause_frame_processing=True, sample_rate=sample_rate, + voice=voice_id, **kwargs, ) self._api_key = api_key - self._voice_id = voice_id self.set_model_name(model) self._settings = LmntTTSSettings( model=model, @@ -235,7 +235,7 @@ class LmntTTSService(InterruptibleTTSService): # Build initial connection message init_msg = { "X-API-Key": self._api_key, - "voice": self._voice_id, + "voice": self._settings.voice, "format": self._settings.format, "sample_rate": self.sample_rate, "language": self._settings.language, diff --git a/src/pipecat/services/minimax/tts.py b/src/pipecat/services/minimax/tts.py index 290439704..ca6cfd7bc 100644 --- a/src/pipecat/services/minimax/tts.py +++ b/src/pipecat/services/minimax/tts.py @@ -227,7 +227,7 @@ class MiniMaxHttpTTSService(TTSService): params: Additional configuration parameters. **kwargs: Additional arguments passed to parent TTSService. """ - super().__init__(sample_rate=sample_rate, **kwargs) + super().__init__(sample_rate=sample_rate, voice=voice_id, **kwargs) params = params or MiniMaxHttpTTSService.InputParams() @@ -236,7 +236,6 @@ class MiniMaxHttpTTSService(TTSService): self._base_url = f"{base_url}?GroupId={group_id}" self._session = aiohttp_session self._model_name = model - self._voice_id = voice_id # Create voice settings self._settings = MiniMaxTTSSettings( @@ -251,8 +250,7 @@ class MiniMaxHttpTTSService(TTSService): audio_channel=1, ) - # Set voice and model - self._voice_id = voice_id + # Set model self.set_model_name(model) # Add language boost if provided @@ -359,7 +357,7 @@ class MiniMaxHttpTTSService(TTSService): # Build voice_setting dict for API voice_setting = { - "voice_id": self._voice_id, + "voice_id": self._settings.voice, "speed": self._settings.speed, "vol": self._settings.volume, "pitch": self._settings.pitch, diff --git a/src/pipecat/services/neuphonic/tts.py b/src/pipecat/services/neuphonic/tts.py index 5f58eb3b4..ffcbdcd8c 100644 --- a/src/pipecat/services/neuphonic/tts.py +++ b/src/pipecat/services/neuphonic/tts.py @@ -139,6 +139,7 @@ class NeuphonicTTSService(InterruptibleTTSService): push_stop_frames=True, stop_frame_timeout_s=2.0, sample_rate=sample_rate, + voice=voice_id, **kwargs, ) @@ -151,8 +152,8 @@ class NeuphonicTTSService(InterruptibleTTSService): speed=params.speed, encoding=encoding, sampling_rate=sample_rate, + voice=voice_id, ) - self._voice_id = voice_id self._cumulative_time = 0 @@ -288,7 +289,7 @@ class NeuphonicTTSService(InterruptibleTTSService): "speed": self._settings.speed, "encoding": self._settings.encoding, "sampling_rate": self._settings.sampling_rate, - "voice_id": self._voice_id, + "voice_id": self._settings.voice, } query_params = [] @@ -442,7 +443,7 @@ class NeuphonicHttpTTSService(TTSService): params: Additional input parameters for TTS configuration. **kwargs: Additional arguments passed to parent TTSService. """ - super().__init__(sample_rate=sample_rate, **kwargs) + super().__init__(sample_rate=sample_rate, voice=voice_id, **kwargs) params = params or NeuphonicHttpTTSService.InputParams() diff --git a/src/pipecat/services/openai/tts.py b/src/pipecat/services/openai/tts.py index 2253e369a..764688125 100644 --- a/src/pipecat/services/openai/tts.py +++ b/src/pipecat/services/openai/tts.py @@ -132,10 +132,9 @@ class OpenAITTSService(TTSService): f"OpenAI TTS only supports {self.OPENAI_SAMPLE_RATE}Hz sample rate. " f"Current rate of {sample_rate}Hz may cause issues." ) - super().__init__(sample_rate=sample_rate, **kwargs) + super().__init__(sample_rate=sample_rate, voice=voice, **kwargs) self.set_model_name(model) - self._voice_id = voice self._client = AsyncOpenAI(api_key=api_key, base_url=base_url) if instructions or speed: @@ -196,7 +195,7 @@ class OpenAITTSService(TTSService): create_params = { "input": text, "model": self.model_name, - "voice": VALID_VOICES[self._voice_id], + "voice": VALID_VOICES[self._settings.voice], "response_format": "pcm", } diff --git a/src/pipecat/services/playht/tts.py b/src/pipecat/services/playht/tts.py index b5c683fbe..0242eaac1 100644 --- a/src/pipecat/services/playht/tts.py +++ b/src/pipecat/services/playht/tts.py @@ -173,6 +173,7 @@ class PlayHTTTSService(InterruptibleTTSService): super().__init__( pause_frame_processing=True, sample_rate=sample_rate, + voice=voice_url, **kwargs, ) @@ -205,7 +206,6 @@ class PlayHTTTSService(InterruptibleTTSService): seed=params.seed, ) self.set_model_name(voice_engine) - self._voice_id = voice_url def can_generate_metrics(self) -> bool: """Check if this service can generate processing metrics. @@ -425,7 +425,7 @@ class PlayHTTTSService(InterruptibleTTSService): tts_command = { "text": text, - "voice": self._voice_id, + "voice": self._settings.voice, "voice_engine": self._settings.voice_engine, "output_format": self._settings.output_format, "sample_rate": self.sample_rate, @@ -511,7 +511,7 @@ class PlayHTHttpTTSService(TTSService): params: Additional input parameters for voice customization. **kwargs: Additional arguments passed to parent TTSService. """ - super().__init__(sample_rate=sample_rate, **kwargs) + super().__init__(sample_rate=sample_rate, voice=voice_url, **kwargs) # Warn about deprecated protocol parameter if explicitly provided if protocol: @@ -556,7 +556,6 @@ class PlayHTHttpTTSService(TTSService): seed=params.seed, ) self.set_model_name(voice_engine) - self._voice_id = voice_url async def start(self, frame: StartFrame): """Start the PlayHT HTTP TTS service. @@ -605,7 +604,7 @@ class PlayHTHttpTTSService(TTSService): # Prepare the request payload payload = { "text": text, - "voice": self._voice_id, + "voice": self._settings.voice, "voice_engine": self._settings.voice_engine, "output_format": self._settings.output_format, "sample_rate": self.sample_rate, diff --git a/src/pipecat/services/resembleai/tts.py b/src/pipecat/services/resembleai/tts.py index f2873a8a1..79fdf54a9 100644 --- a/src/pipecat/services/resembleai/tts.py +++ b/src/pipecat/services/resembleai/tts.py @@ -94,11 +94,11 @@ class ResembleAITTSService(AudioContextWordTTSService): """ super().__init__( sample_rate=sample_rate, + voice=voice_id, **kwargs, ) self._api_key = api_key - self._voice_id = voice_id self._url = url self._settings = ResembleAITTSSettings( voice=voice_id, @@ -126,8 +126,6 @@ class ResembleAITTSService(AudioContextWordTTSService): self._jitter_buffer_bytes = 44100 # ~1000ms at 22050Hz to handle 400ms+ network gaps self._playback_started: dict[str, bool] = {} # Track if we've started playback per request - self._voice_id = voice_id - def can_generate_metrics(self) -> bool: """Check if this service can generate processing metrics. @@ -146,7 +144,7 @@ class ResembleAITTSService(AudioContextWordTTSService): JSON string containing the request payload. """ msg = { - "voice_uuid": self._voice_id, + "voice_uuid": self._settings.voice, "data": text, "binary_response": False, # Use JSON frames to get timestamps "request_id": self._request_id_counter, # ResembleAI only accepts number diff --git a/src/pipecat/services/rime/tts.py b/src/pipecat/services/rime/tts.py index 87596cefd..99250bce0 100644 --- a/src/pipecat/services/rime/tts.py +++ b/src/pipecat/services/rime/tts.py @@ -191,6 +191,7 @@ class RimeTTSService(AudioContextWordTTSService): pause_frame_processing=True, append_trailing_space=True, sample_rate=sample_rate, + voice=voice_id, **kwargs, ) @@ -207,7 +208,6 @@ class RimeTTSService(AudioContextWordTTSService): # Store service configuration self._api_key = api_key self._url = url - self._voice_id = voice_id self._model = model self._settings = RimeTTSSettings( voice=voice_id, @@ -582,7 +582,7 @@ class RimeHttpTTSService(TTSService): params: Additional configuration parameters. **kwargs: Additional arguments passed to parent TTSService. """ - super().__init__(sample_rate=sample_rate, **kwargs) + super().__init__(sample_rate=sample_rate, voice=voice_id, **kwargs) params = params or RimeHttpTTSService.InputParams() @@ -596,8 +596,8 @@ class RimeHttpTTSService(TTSService): pauseBetweenBrackets=params.pause_between_brackets, phonemizeBetweenBrackets=params.phonemize_between_brackets, inlineSpeedAlpha=params.inline_speed_alpha if params.inline_speed_alpha else NOT_GIVEN, + voice=voice_id, ) - self._voice_id = voice_id self.set_model_name(model) def can_generate_metrics(self) -> bool: @@ -648,7 +648,7 @@ class RimeHttpTTSService(TTSService): if is_given(self._settings.inlineSpeedAlpha): payload["inlineSpeedAlpha"] = self._settings.inlineSpeedAlpha payload["text"] = text - payload["speaker"] = self._voice_id + payload["speaker"] = self._settings.voice payload["modelId"] = self._model_name payload["samplingRate"] = self.sample_rate @@ -762,12 +762,12 @@ class RimeNonJsonTTSService(InterruptibleTTSService): aggregate_sentences=aggregate_sentences, push_stop_frames=True, pause_frame_processing=True, + voice=voice_id, **kwargs, ) params = params or RimeNonJsonTTSService.InputParams() self._api_key = api_key self._url = url - self._voice_id = voice_id self._model = model self._settings = RimeNonJsonTTSSettings( voice=voice_id, diff --git a/src/pipecat/services/sarvam/tts.py b/src/pipecat/services/sarvam/tts.py index 332643fc9..ba93c7c26 100644 --- a/src/pipecat/services/sarvam/tts.py +++ b/src/pipecat/services/sarvam/tts.py @@ -281,7 +281,6 @@ class SarvamTTSSettings(TTSSettings): Parameters: target_language_code: Sarvam language code. - speaker: Voice speaker ID. speech_sample_rate: Audio sample rate as string. enable_preprocessing: Enable text preprocessing. Defaults to False. **Note:** Always enabled for bulbul:v3-beta. @@ -306,7 +305,6 @@ class SarvamTTSSettings(TTSSettings): """ target_language_code: str | None | _NotGiven = field(default_factory=lambda: NOT_GIVEN) - speaker: str | _NotGiven = field(default_factory=lambda: NOT_GIVEN) speech_sample_rate: str | _NotGiven = field(default_factory=lambda: NOT_GIVEN) enable_preprocessing: bool | None | _NotGiven = field(default_factory=lambda: NOT_GIVEN) min_buffer_size: int | None | _NotGiven = field(default_factory=lambda: NOT_GIVEN) @@ -460,14 +458,14 @@ class SarvamHttpTTSService(TTSService): if sample_rate is None: sample_rate = self._config.default_sample_rate - super().__init__(sample_rate=sample_rate, **kwargs) - params = params or SarvamHttpTTSService.InputParams() # Set default voice based on model if not specified if voice_id is None: voice_id = self._config.default_speaker + super().__init__(sample_rate=sample_rate, voice=voice_id, **kwargs) + self._api_key = api_key self._base_url = base_url self._session = aiohttp_session @@ -489,6 +487,7 @@ class SarvamHttpTTSService(TTSService): ), pace=pace, model=model, + voice=voice_id, ) # Add parameters based on model support @@ -508,7 +507,6 @@ class SarvamHttpTTSService(TTSService): logger.warning(f"temperature parameter is ignored for {model}") self.set_model_name(model) - self._voice_id = voice_id def can_generate_metrics(self) -> bool: """Check if this service can generate processing metrics. @@ -558,7 +556,7 @@ class SarvamHttpTTSService(TTSService): payload = { "text": text, "target_language_code": self._settings.language, - "speaker": self._voice_id, + "speaker": self._settings.voice, "sample_rate": self.sample_rate, "enable_preprocessing": self._settings.enable_preprocessing, "model": self._model_name, @@ -812,6 +810,10 @@ class SarvamTTSService(InterruptibleTTSService): if sample_rate is None: sample_rate = self._config.default_sample_rate + # Set default voice based on model if not specified + if voice_id is None: + voice_id = self._config.default_speaker + # Initialize parent class first super().__init__( aggregate_sentences=aggregate_sentences, @@ -819,19 +821,15 @@ class SarvamTTSService(InterruptibleTTSService): pause_frame_processing=True, push_stop_frames=True, sample_rate=sample_rate, + voice=voice_id, **kwargs, ) params = params or SarvamTTSService.InputParams() - # Set default voice based on model if not specified - if voice_id is None: - voice_id = self._config.default_speaker - # WebSocket endpoint URL with model query parameter self._websocket_url = f"{url}?model={model}" self._api_key = api_key self.set_model_name(model) - self._voice_id = voice_id # Validate and clamp pace to model's valid range pace = params.pace @@ -845,7 +843,6 @@ class SarvamTTSService(InterruptibleTTSService): target_language_code=( self.language_to_service_language(params.language) if params.language else "en-IN" ), - speaker=voice_id, speech_sample_rate=str(sample_rate), enable_preprocessing=( True if self._config.preprocessing_always_enabled else params.enable_preprocessing @@ -856,6 +853,7 @@ class SarvamTTSService(InterruptibleTTSService): output_audio_bitrate=params.output_audio_bitrate, pace=pace, model=model, + voice=voice_id, ) # Add parameters based on model support @@ -1018,11 +1016,10 @@ class SarvamTTSService(InterruptibleTTSService): """Send initial configuration message.""" if not self._websocket: raise Exception("WebSocket not connected") - self._settings.speaker = self._voice_id # Build config dict for the API config_data = { "target_language_code": self._settings.target_language_code, - "speaker": self._settings.speaker, + "speaker": self._settings.voice, "speech_sample_rate": self._settings.speech_sample_rate, "enable_preprocessing": self._settings.enable_preprocessing, "min_buffer_size": self._settings.min_buffer_size, diff --git a/src/pipecat/services/tts_service.py b/src/pipecat/services/tts_service.py index ebf0e602a..4567e2db3 100644 --- a/src/pipecat/services/tts_service.py +++ b/src/pipecat/services/tts_service.py @@ -145,6 +145,11 @@ class TTSService(AIService): text_filter: Optional[BaseTextFilter] = None, # Audio transport destination of the generated frames. transport_destination: Optional[str] = None, + # Voice identifier or name to use for speech synthesis + voice: Optional[str] = None, + # Language to use for speech synthesis. This will be translated to a + # service-specific language identifier before being applied + language: Optional[Language] = None, **kwargs, ): """Initialize the TTS service. @@ -178,6 +183,10 @@ class TTSService(AIService): Use `text_filters` instead, which allows multiple filters. transport_destination: Destination for generated audio frames. + voice: Voice identifier or name to use for speech synthesis. + language: Language to use for speech synthesis. This will be + translated to a service-specific language identifier before + being applied. **kwargs: Additional arguments passed to the parent AIService. """ super().__init__(**kwargs) @@ -191,8 +200,9 @@ class TTSService(AIService): self._append_trailing_space: bool = append_trailing_space self._init_sample_rate = sample_rate self._sample_rate = 0 - self._voice_id: str = "" - self._settings = TTSSettings() # Here in case subclass doesn't implement more specific settings (hopefully shouldn't happen) + self._settings = TTSSettings( + voice=voice, language=language + ) # Here in case subclass doesn't implement more specific settings (hopefully shouldn't happen) self._text_aggregator: BaseTextAggregator = text_aggregator or SimpleTextAggregator() if text_aggregator: import warnings @@ -427,11 +437,7 @@ class TTSService(AIService): async def _update_settings(self, update: TTSSettings) -> dict[str, Any]: """Apply a TTS settings update. - Handles ``model`` (via parent) and syncs ``_voice_id`` when voice - changes. Translates language values before applying. Does **not** - call ``set_voice`` or ``set_model`` directly — concrete services - should override this method and handle reconnect logic based on the - returned changed-field dict. + Translates language to service-specific value before applying. Args: update: A TTS settings delta. @@ -447,10 +453,6 @@ class TTSService(AIService): changed = await super()._update_settings(update) - # Keep _voice_id in sync for code that reads it directly - if "voice" in changed: - self._voice_id = self._settings.voice - return changed async def say(self, text: str): diff --git a/src/pipecat/services/xtts/tts.py b/src/pipecat/services/xtts/tts.py index 65aa25e36..5cc91709f 100644 --- a/src/pipecat/services/xtts/tts.py +++ b/src/pipecat/services/xtts/tts.py @@ -111,14 +111,13 @@ class XTTSService(TTSService): sample_rate: Audio sample rate. If None, uses default. **kwargs: Additional arguments passed to parent TTSService. """ - super().__init__(sample_rate=sample_rate, **kwargs) + super().__init__(sample_rate=sample_rate, voice=voice_id, **kwargs) self._settings = XTTSTTSSettings( voice=voice_id, language=self.language_to_service_language(language), base_url=base_url, ) - self._voice_id = voice_id self._studio_speakers: Optional[Dict[str, Any]] = None self._aiohttp_session = aiohttp_session @@ -180,7 +179,7 @@ class XTTSService(TTSService): logger.error(f"{self} no studio speakers available") return - embeddings = self._studio_speakers[self._voice_id] + embeddings = self._studio_speakers[self._settings.voice] url = self._settings.base_url + "/tts_stream" diff --git a/src/pipecat/utils/tracing/service_decorators.py b/src/pipecat/utils/tracing/service_decorators.py index 42babd5cd..3b23f337a 100644 --- a/src/pipecat/utils/tracing/service_decorators.py +++ b/src/pipecat/utils/tracing/service_decorators.py @@ -190,13 +190,14 @@ def traced_tts(func: Optional[Callable] = None, *, name: Optional[str] = None) - tracer = trace.get_tracer("pipecat") with tracer.start_as_current_span(span_name, context=parent_context) as span: try: + settings = getattr(self, "_settings", {}) add_tts_span_attributes( span=span, service_name=service_class_name, model=getattr(self, "model_name") or "unknown", - voice_id=getattr(self, "_voice_id", "unknown"), + voice_id=getattr(settings, "voice", "unknown"), text=text, - settings=getattr(self, "_settings", {}), + settings=settings, character_count=len(text), operation_name="tts", cartesia_version=getattr(self, "_cartesia_version", None), From f5b86d9cdc616013c28f314ed4541dee2a34c0e3 Mon Sep 17 00:00:00 2001 From: Paul Kompfner Date: Fri, 20 Feb 2026 11:26:28 -0500 Subject: [PATCH 0576/1060] Actually, revert the change making it so that `STTService` takes `model` and `language` args at init time. It'll be up to the subclasses to append those to `_settings` (or better yet, provide their own service-specific `_settings`). This avoids rocking the boat too too much. --- .claude/skills/cleanup/SKILL.md | 2 +- src/pipecat/services/asyncai/tts.py | 3 +-- src/pipecat/services/aws/tts.py | 2 +- src/pipecat/services/azure/tts.py | 3 +-- src/pipecat/services/camb/tts.py | 2 +- src/pipecat/services/cartesia/tts.py | 3 +-- src/pipecat/services/deepgram/tts.py | 3 +-- src/pipecat/services/elevenlabs/tts.py | 2 -- src/pipecat/services/google/tts.py | 6 +++--- src/pipecat/services/gradium/tts.py | 1 - src/pipecat/services/groq/tts.py | 1 - src/pipecat/services/hathora/tts.py | 1 - src/pipecat/services/hume/tts.py | 1 - src/pipecat/services/inworld/tts.py | 2 -- src/pipecat/services/kokoro/tts.py | 2 +- src/pipecat/services/lmnt/tts.py | 1 - src/pipecat/services/minimax/tts.py | 2 +- src/pipecat/services/neuphonic/tts.py | 3 +-- src/pipecat/services/openai/tts.py | 2 +- src/pipecat/services/playht/tts.py | 3 +-- src/pipecat/services/resembleai/tts.py | 1 - src/pipecat/services/rime/tts.py | 4 +--- src/pipecat/services/sarvam/tts.py | 3 +-- src/pipecat/services/tts_service.py | 11 +---------- src/pipecat/services/xtts/tts.py | 2 +- 25 files changed, 19 insertions(+), 47 deletions(-) diff --git a/.claude/skills/cleanup/SKILL.md b/.claude/skills/cleanup/SKILL.md index 5e699d588..48c5e0ee8 100644 --- a/.claude/skills/cleanup/SKILL.md +++ b/.claude/skills/cleanup/SKILL.md @@ -291,7 +291,7 @@ class NewTTSService(TTSService): voice: Voice identifier to use. **kwargs: Additional arguments passed to the parent service. """ - super().__init__(voice=voice, **kwargs) + super().__init__(**kwargs) self._api_key = api_key ``` diff --git a/src/pipecat/services/asyncai/tts.py b/src/pipecat/services/asyncai/tts.py index 323fa3906..31ce83810 100644 --- a/src/pipecat/services/asyncai/tts.py +++ b/src/pipecat/services/asyncai/tts.py @@ -153,7 +153,6 @@ class AsyncAITTSService(AudioContextTTSService): pause_frame_processing=True, push_stop_frames=True, sample_rate=sample_rate, - voice=voice_id, **kwargs, ) @@ -497,7 +496,7 @@ class AsyncAIHttpTTSService(TTSService): params: Additional input parameters for voice customization. **kwargs: Additional arguments passed to the parent TTSService. """ - super().__init__(sample_rate=sample_rate, voice=voice_id, **kwargs) + super().__init__(sample_rate=sample_rate, **kwargs) params = params or AsyncAIHttpTTSService.InputParams() diff --git a/src/pipecat/services/aws/tts.py b/src/pipecat/services/aws/tts.py index a277bc0b2..4e071465d 100644 --- a/src/pipecat/services/aws/tts.py +++ b/src/pipecat/services/aws/tts.py @@ -195,7 +195,7 @@ class AWSPollyTTSService(TTSService): params: Additional input parameters for voice customization. **kwargs: Additional arguments passed to parent TTSService class. """ - super().__init__(sample_rate=sample_rate, voice=voice_id, **kwargs) + super().__init__(sample_rate=sample_rate, **kwargs) params = params or AWSPollyTTSService.InputParams() diff --git a/src/pipecat/services/azure/tts.py b/src/pipecat/services/azure/tts.py index 2d4c01dc9..f1bf9d400 100644 --- a/src/pipecat/services/azure/tts.py +++ b/src/pipecat/services/azure/tts.py @@ -295,7 +295,6 @@ class AzureTTSService(WordTTSService, AzureBaseTTSService): push_stop_frames=True, pause_frame_processing=True, sample_rate=sample_rate, - voice=voice, **kwargs, ) @@ -734,7 +733,7 @@ class AzureHttpTTSService(TTSService, AzureBaseTTSService): params: Voice and synthesis parameters configuration. **kwargs: Additional arguments passed to parent TTSService. """ - super().__init__(sample_rate=sample_rate, voice=voice, **kwargs) + super().__init__(sample_rate=sample_rate, **kwargs) # Initialize Azure-specific functionality from mixin self._init_azure_base(api_key=api_key, region=region, voice=voice, params=params) diff --git a/src/pipecat/services/camb/tts.py b/src/pipecat/services/camb/tts.py index ec0853424..411b4cabf 100644 --- a/src/pipecat/services/camb/tts.py +++ b/src/pipecat/services/camb/tts.py @@ -213,7 +213,7 @@ class CambTTSService(TTSService): params: Additional voice parameters. If None, uses defaults. **kwargs: Additional arguments passed to parent TTSService. """ - super().__init__(sample_rate=sample_rate, voice=voice_id, **kwargs) + super().__init__(sample_rate=sample_rate, **kwargs) self._api_key = api_key self._timeout = timeout diff --git a/src/pipecat/services/cartesia/tts.py b/src/pipecat/services/cartesia/tts.py index a16aa2b39..daddfa6c8 100644 --- a/src/pipecat/services/cartesia/tts.py +++ b/src/pipecat/services/cartesia/tts.py @@ -313,7 +313,6 @@ class CartesiaTTSService(AudioContextWordTTSService): pause_frame_processing=True, sample_rate=sample_rate, text_aggregator=text_aggregator, - voice=voice_id, **kwargs, ) @@ -721,7 +720,7 @@ class CartesiaHttpTTSService(TTSService): params: Additional input parameters for voice customization. **kwargs: Additional arguments passed to the parent TTSService. """ - super().__init__(sample_rate=sample_rate, voice=voice_id, **kwargs) + super().__init__(sample_rate=sample_rate, **kwargs) params = params or CartesiaHttpTTSService.InputParams() diff --git a/src/pipecat/services/deepgram/tts.py b/src/pipecat/services/deepgram/tts.py index a8b46ce7e..23bfecb03 100644 --- a/src/pipecat/services/deepgram/tts.py +++ b/src/pipecat/services/deepgram/tts.py @@ -101,7 +101,6 @@ class DeepgramTTSService(WebsocketTTSService): pause_frame_processing=True, push_stop_frames=True, append_trailing_space=True, - voice=voice, **kwargs, ) @@ -388,7 +387,7 @@ class DeepgramHttpTTSService(TTSService): encoding: Audio encoding format. Defaults to "linear16". **kwargs: Additional arguments passed to parent TTSService class. """ - super().__init__(sample_rate=sample_rate, voice=voice, **kwargs) + super().__init__(sample_rate=sample_rate, **kwargs) self._api_key = api_key self._session = aiohttp_session diff --git a/src/pipecat/services/elevenlabs/tts.py b/src/pipecat/services/elevenlabs/tts.py index 73e9027d3..7de346826 100644 --- a/src/pipecat/services/elevenlabs/tts.py +++ b/src/pipecat/services/elevenlabs/tts.py @@ -400,7 +400,6 @@ class ElevenLabsTTSService(AudioContextWordTTSService): push_stop_frames=True, pause_frame_processing=True, sample_rate=sample_rate, - voice=voice_id, **kwargs, ) @@ -906,7 +905,6 @@ class ElevenLabsHttpTTSService(WordTTSService): push_text_frames=False, push_stop_frames=True, sample_rate=sample_rate, - voice=voice_id, **kwargs, ) diff --git a/src/pipecat/services/google/tts.py b/src/pipecat/services/google/tts.py index 33fa1b2a8..1103c69e4 100644 --- a/src/pipecat/services/google/tts.py +++ b/src/pipecat/services/google/tts.py @@ -602,7 +602,7 @@ class GoogleHttpTTSService(TTSService): params: Voice customization parameters including pitch, rate, volume, etc. **kwargs: Additional arguments passed to parent TTSService. """ - super().__init__(sample_rate=sample_rate, voice=voice_id, **kwargs) + super().__init__(sample_rate=sample_rate, **kwargs) params = params or GoogleHttpTTSService.InputParams() @@ -1015,7 +1015,7 @@ class GoogleTTSService(GoogleBaseTTSService): params: Language configuration parameters. **kwargs: Additional arguments passed to parent TTSService. """ - super().__init__(sample_rate=sample_rate, voice=voice_id, **kwargs) + super().__init__(sample_rate=sample_rate, **kwargs) params = params or GoogleTTSService.InputParams() @@ -1220,7 +1220,7 @@ class GeminiTTSService(GoogleBaseTTSService): f"Google TTS only supports {self.GOOGLE_SAMPLE_RATE}Hz sample rate. " f"Current rate of {sample_rate}Hz may cause issues." ) - super().__init__(sample_rate=sample_rate, voice=voice_id, **kwargs) + super().__init__(sample_rate=sample_rate, **kwargs) params = params or GeminiTTSService.InputParams() diff --git a/src/pipecat/services/gradium/tts.py b/src/pipecat/services/gradium/tts.py index e3d855c5c..85e77f057 100644 --- a/src/pipecat/services/gradium/tts.py +++ b/src/pipecat/services/gradium/tts.py @@ -91,7 +91,6 @@ class GradiumTTSService(InterruptibleWordTTSService): push_stop_frames=True, pause_frame_processing=True, sample_rate=SAMPLE_RATE, - voice=voice_id, **kwargs, ) diff --git a/src/pipecat/services/groq/tts.py b/src/pipecat/services/groq/tts.py index 78d744461..5c3eab636 100644 --- a/src/pipecat/services/groq/tts.py +++ b/src/pipecat/services/groq/tts.py @@ -102,7 +102,6 @@ class GroqTTSService(TTSService): super().__init__( pause_frame_processing=True, sample_rate=sample_rate, - voice=voice_id, **kwargs, ) diff --git a/src/pipecat/services/hathora/tts.py b/src/pipecat/services/hathora/tts.py index 6e75feeca..9778a2f14 100644 --- a/src/pipecat/services/hathora/tts.py +++ b/src/pipecat/services/hathora/tts.py @@ -109,7 +109,6 @@ class HathoraTTSService(TTSService): """ super().__init__( sample_rate=sample_rate, - voice=voice_id, **kwargs, ) self._model = model diff --git a/src/pipecat/services/hume/tts.py b/src/pipecat/services/hume/tts.py index a52922787..d15f13ce1 100644 --- a/src/pipecat/services/hume/tts.py +++ b/src/pipecat/services/hume/tts.py @@ -126,7 +126,6 @@ class HumeTTSService(WordTTSService): sample_rate=sample_rate, push_text_frames=False, push_stop_frames=True, - voice=voice_id, **kwargs, ) diff --git a/src/pipecat/services/inworld/tts.py b/src/pipecat/services/inworld/tts.py index 34dc34933..1b6dee46f 100644 --- a/src/pipecat/services/inworld/tts.py +++ b/src/pipecat/services/inworld/tts.py @@ -144,7 +144,6 @@ class InworldHttpTTSService(WordTTSService): push_text_frames=False, push_stop_frames=True, sample_rate=sample_rate, - voice=voice_id, **kwargs, ) @@ -519,7 +518,6 @@ class InworldTTSService(AudioContextWordTTSService): sample_rate=sample_rate, aggregate_sentences=aggregate_sentences, append_trailing_space=append_trailing_space, - voice=voice_id, **kwargs, ) diff --git a/src/pipecat/services/kokoro/tts.py b/src/pipecat/services/kokoro/tts.py index 9f2aac368..6e848ae87 100644 --- a/src/pipecat/services/kokoro/tts.py +++ b/src/pipecat/services/kokoro/tts.py @@ -137,7 +137,7 @@ class KokoroTTSService(TTSService): **kwargs: Additional arguments passed to parent `TTSService`. """ - super().__init__(voice=voice_id, **kwargs) + super().__init__(**kwargs) params = params or KokoroTTSService.InputParams() diff --git a/src/pipecat/services/lmnt/tts.py b/src/pipecat/services/lmnt/tts.py index ab56f2296..71ffb4f5f 100644 --- a/src/pipecat/services/lmnt/tts.py +++ b/src/pipecat/services/lmnt/tts.py @@ -118,7 +118,6 @@ class LmntTTSService(InterruptibleTTSService): push_stop_frames=True, pause_frame_processing=True, sample_rate=sample_rate, - voice=voice_id, **kwargs, ) diff --git a/src/pipecat/services/minimax/tts.py b/src/pipecat/services/minimax/tts.py index ca6cfd7bc..507febf2d 100644 --- a/src/pipecat/services/minimax/tts.py +++ b/src/pipecat/services/minimax/tts.py @@ -227,7 +227,7 @@ class MiniMaxHttpTTSService(TTSService): params: Additional configuration parameters. **kwargs: Additional arguments passed to parent TTSService. """ - super().__init__(sample_rate=sample_rate, voice=voice_id, **kwargs) + super().__init__(sample_rate=sample_rate, **kwargs) params = params or MiniMaxHttpTTSService.InputParams() diff --git a/src/pipecat/services/neuphonic/tts.py b/src/pipecat/services/neuphonic/tts.py index ffcbdcd8c..dd2360e4c 100644 --- a/src/pipecat/services/neuphonic/tts.py +++ b/src/pipecat/services/neuphonic/tts.py @@ -139,7 +139,6 @@ class NeuphonicTTSService(InterruptibleTTSService): push_stop_frames=True, stop_frame_timeout_s=2.0, sample_rate=sample_rate, - voice=voice_id, **kwargs, ) @@ -443,7 +442,7 @@ class NeuphonicHttpTTSService(TTSService): params: Additional input parameters for TTS configuration. **kwargs: Additional arguments passed to parent TTSService. """ - super().__init__(sample_rate=sample_rate, voice=voice_id, **kwargs) + super().__init__(sample_rate=sample_rate, **kwargs) params = params or NeuphonicHttpTTSService.InputParams() diff --git a/src/pipecat/services/openai/tts.py b/src/pipecat/services/openai/tts.py index 764688125..853647f7f 100644 --- a/src/pipecat/services/openai/tts.py +++ b/src/pipecat/services/openai/tts.py @@ -132,7 +132,7 @@ class OpenAITTSService(TTSService): f"OpenAI TTS only supports {self.OPENAI_SAMPLE_RATE}Hz sample rate. " f"Current rate of {sample_rate}Hz may cause issues." ) - super().__init__(sample_rate=sample_rate, voice=voice, **kwargs) + super().__init__(sample_rate=sample_rate, **kwargs) self.set_model_name(model) self._client = AsyncOpenAI(api_key=api_key, base_url=base_url) diff --git a/src/pipecat/services/playht/tts.py b/src/pipecat/services/playht/tts.py index 0242eaac1..630351164 100644 --- a/src/pipecat/services/playht/tts.py +++ b/src/pipecat/services/playht/tts.py @@ -173,7 +173,6 @@ class PlayHTTTSService(InterruptibleTTSService): super().__init__( pause_frame_processing=True, sample_rate=sample_rate, - voice=voice_url, **kwargs, ) @@ -511,7 +510,7 @@ class PlayHTHttpTTSService(TTSService): params: Additional input parameters for voice customization. **kwargs: Additional arguments passed to parent TTSService. """ - super().__init__(sample_rate=sample_rate, voice=voice_url, **kwargs) + super().__init__(sample_rate=sample_rate, **kwargs) # Warn about deprecated protocol parameter if explicitly provided if protocol: diff --git a/src/pipecat/services/resembleai/tts.py b/src/pipecat/services/resembleai/tts.py index 79fdf54a9..8e436923b 100644 --- a/src/pipecat/services/resembleai/tts.py +++ b/src/pipecat/services/resembleai/tts.py @@ -94,7 +94,6 @@ class ResembleAITTSService(AudioContextWordTTSService): """ super().__init__( sample_rate=sample_rate, - voice=voice_id, **kwargs, ) diff --git a/src/pipecat/services/rime/tts.py b/src/pipecat/services/rime/tts.py index 99250bce0..2f006efc7 100644 --- a/src/pipecat/services/rime/tts.py +++ b/src/pipecat/services/rime/tts.py @@ -191,7 +191,6 @@ class RimeTTSService(AudioContextWordTTSService): pause_frame_processing=True, append_trailing_space=True, sample_rate=sample_rate, - voice=voice_id, **kwargs, ) @@ -582,7 +581,7 @@ class RimeHttpTTSService(TTSService): params: Additional configuration parameters. **kwargs: Additional arguments passed to parent TTSService. """ - super().__init__(sample_rate=sample_rate, voice=voice_id, **kwargs) + super().__init__(sample_rate=sample_rate, **kwargs) params = params or RimeHttpTTSService.InputParams() @@ -762,7 +761,6 @@ class RimeNonJsonTTSService(InterruptibleTTSService): aggregate_sentences=aggregate_sentences, push_stop_frames=True, pause_frame_processing=True, - voice=voice_id, **kwargs, ) params = params or RimeNonJsonTTSService.InputParams() diff --git a/src/pipecat/services/sarvam/tts.py b/src/pipecat/services/sarvam/tts.py index ba93c7c26..cbccd0130 100644 --- a/src/pipecat/services/sarvam/tts.py +++ b/src/pipecat/services/sarvam/tts.py @@ -464,7 +464,7 @@ class SarvamHttpTTSService(TTSService): if voice_id is None: voice_id = self._config.default_speaker - super().__init__(sample_rate=sample_rate, voice=voice_id, **kwargs) + super().__init__(sample_rate=sample_rate, **kwargs) self._api_key = api_key self._base_url = base_url @@ -821,7 +821,6 @@ class SarvamTTSService(InterruptibleTTSService): pause_frame_processing=True, push_stop_frames=True, sample_rate=sample_rate, - voice=voice_id, **kwargs, ) params = params or SarvamTTSService.InputParams() diff --git a/src/pipecat/services/tts_service.py b/src/pipecat/services/tts_service.py index 4567e2db3..e5602d469 100644 --- a/src/pipecat/services/tts_service.py +++ b/src/pipecat/services/tts_service.py @@ -145,11 +145,6 @@ class TTSService(AIService): text_filter: Optional[BaseTextFilter] = None, # Audio transport destination of the generated frames. transport_destination: Optional[str] = None, - # Voice identifier or name to use for speech synthesis - voice: Optional[str] = None, - # Language to use for speech synthesis. This will be translated to a - # service-specific language identifier before being applied - language: Optional[Language] = None, **kwargs, ): """Initialize the TTS service. @@ -183,10 +178,6 @@ class TTSService(AIService): Use `text_filters` instead, which allows multiple filters. transport_destination: Destination for generated audio frames. - voice: Voice identifier or name to use for speech synthesis. - language: Language to use for speech synthesis. This will be - translated to a service-specific language identifier before - being applied. **kwargs: Additional arguments passed to the parent AIService. """ super().__init__(**kwargs) @@ -201,7 +192,7 @@ class TTSService(AIService): self._init_sample_rate = sample_rate self._sample_rate = 0 self._settings = TTSSettings( - voice=voice, language=language + voice="" ) # Here in case subclass doesn't implement more specific settings (hopefully shouldn't happen) self._text_aggregator: BaseTextAggregator = text_aggregator or SimpleTextAggregator() if text_aggregator: diff --git a/src/pipecat/services/xtts/tts.py b/src/pipecat/services/xtts/tts.py index 5cc91709f..ba2eb4fc2 100644 --- a/src/pipecat/services/xtts/tts.py +++ b/src/pipecat/services/xtts/tts.py @@ -111,7 +111,7 @@ class XTTSService(TTSService): sample_rate: Audio sample rate. If None, uses default. **kwargs: Additional arguments passed to parent TTSService. """ - super().__init__(sample_rate=sample_rate, voice=voice_id, **kwargs) + super().__init__(sample_rate=sample_rate, **kwargs) self._settings = XTTSTTSSettings( voice=voice_id, From 125c42335607d4f4641a68cf3b66ba502ce09d94 Mon Sep 17 00:00:00 2001 From: filipi87 Date: Fri, 20 Feb 2026 14:57:44 -0300 Subject: [PATCH 0577/1060] Refactored audio context management in TTS services to improve encapsulation and reduce code duplication --- src/pipecat/services/asyncai/tts.py | 56 +++++++------------- src/pipecat/services/cartesia/tts.py | 38 ++++---------- src/pipecat/services/elevenlabs/tts.py | 73 +++++++++++--------------- src/pipecat/services/gradium/tts.py | 35 ++++-------- src/pipecat/services/inworld/tts.py | 71 +++++++++---------------- src/pipecat/services/resembleai/tts.py | 3 +- src/pipecat/services/rime/tts.py | 36 ++++--------- src/pipecat/services/tts_service.py | 63 +++++++++++++++++++++- 8 files changed, 167 insertions(+), 208 deletions(-) diff --git a/src/pipecat/services/asyncai/tts.py b/src/pipecat/services/asyncai/tts.py index e9170f8b6..69ed90ca1 100644 --- a/src/pipecat/services/asyncai/tts.py +++ b/src/pipecat/services/asyncai/tts.py @@ -9,7 +9,6 @@ import asyncio import base64 import json -import uuid from typing import AsyncGenerator, Optional import aiohttp @@ -148,7 +147,6 @@ class AsyncAITTSService(AudioContextTTSService): self._receive_task = None self._keepalive_task = None - self._context_id = None def can_generate_metrics(self) -> bool: """Check if this service can generate processing metrics. @@ -255,7 +253,7 @@ class AsyncAITTSService(AudioContextTTSService): if self._websocket: logger.debug("Disconnecting from Async") # Close all contexts and the socket - if self._context_id: + if self.has_active_audio_context(): await self._websocket.send(json.dumps({"terminate": True})) await self._websocket.close() logger.debug("Disconnected from Async") @@ -263,7 +261,7 @@ class AsyncAITTSService(AudioContextTTSService): await self.push_error(error_msg=f"Unknown error occurred: {e}", exception=e) finally: self._websocket = None - self._context_id = None + await self.remove_active_audio_context() await self._call_event_handler("on_disconnected") def _get_websocket(self): @@ -271,26 +269,13 @@ class AsyncAITTSService(AudioContextTTSService): return self._websocket raise Exception("Websocket not connected") - def create_context_id(self) -> str: - """Generate a unique context ID for a TTS request in case we don't have one already in progress. - - Returns: - A unique string identifier for the TTS context. - """ - # If a context ID does not exist, create a new one. - # If an ID exists, continue using the current ID. - # When interruptions happen, user speech results in - # an interruption, which resets the context ID. - if not self._context_id: - return str(uuid.uuid4()) - return self._context_id - async def flush_audio(self): """Flush any pending audio.""" - if not self._context_id or not self._websocket: + context_id = self.get_active_audio_context_id() + if not context_id or not self._websocket: return logger.trace(f"{self}: flushing audio") - msg = self._build_msg(text=" ", context_id=self._context_id, force=True) + msg = self._build_msg(text=" ", context_id=context_id, force=True) await self._websocket.send(msg) async def push_frame(self, frame: Frame, direction: FrameDirection = FrameDirection.DOWNSTREAM): @@ -318,11 +303,11 @@ class AsyncAITTSService(AudioContextTTSService): # Check if this message belongs to the current context. if not self.audio_context_available(received_ctx_id): - if self._context_id == received_ctx_id: + if self.get_active_audio_context_id() == received_ctx_id: logger.debug( - f"Received a delayed message, recreating the context: {self._context_id}" + f"Received a delayed message, recreating the context: {received_ctx_id}" ) - await self.create_audio_context(self._context_id) + await self.create_audio_context(received_ctx_id) else: # This can happen if a message is received _after_ we have closed a context # due to user interruption but _before_ the `isFinal` message for the context @@ -343,10 +328,11 @@ class AsyncAITTSService(AudioContextTTSService): await asyncio.sleep(KEEPALIVE_SLEEP) try: if self._websocket and self._websocket.state is State.OPEN: - if self._context_id: + context_id = self.get_active_audio_context_id() + if context_id: keepalive_message = { "transcript": " ", - "context_id": self._context_id, + "context_id": context_id, } logger.trace("Sending keepalive message") else: @@ -362,19 +348,16 @@ class AsyncAITTSService(AudioContextTTSService): async def _handle_interruption(self, frame: InterruptionFrame, direction: FrameDirection): """Handle interruption by closing the current context.""" + context_id = self.get_active_audio_context_id() await super()._handle_interruption(frame, direction) - # Close the current context when interrupted without closing the websocket - if self._context_id and self._websocket: + if context_id and self._websocket: try: await self._websocket.send( - json.dumps( - {"context_id": self._context_id, "close_context": True, "transcript": ""} - ) + json.dumps({"context_id": context_id, "close_context": True, "transcript": ""}) ) except Exception as e: logger.error(f"Error closing context on interruption: {e}") - self._context_id = None @traced_tts async def run_tts(self, text: str, context_id: str) -> AsyncGenerator[Frame, None]: @@ -394,16 +377,13 @@ class AsyncAITTSService(AudioContextTTSService): await self._connect() try: - if not self._context_id: + if not self.has_active_audio_context(): await self.start_ttfb_metrics() yield TTSStartedFrame(context_id=context_id) + if not self.audio_context_available(context_id): + await self.create_audio_context(context_id) - self._context_id = context_id - - if not self.audio_context_available(self._context_id): - await self.create_audio_context(self._context_id) - - msg = self._build_msg(text=text, force=True, context_id=self._context_id) + msg = self._build_msg(text=text, force=True, context_id=context_id) await self._get_websocket().send(msg) await self.start_tts_usage_metrics(text) diff --git a/src/pipecat/services/cartesia/tts.py b/src/pipecat/services/cartesia/tts.py index 1fa9a026a..e30acdcd1 100644 --- a/src/pipecat/services/cartesia/tts.py +++ b/src/pipecat/services/cartesia/tts.py @@ -8,7 +8,6 @@ import base64 import json -import uuid import warnings from enum import Enum from typing import AsyncGenerator, List, Literal, Optional @@ -307,7 +306,6 @@ class CartesiaTTSService(AudioContextWordTTSService): self.set_model_name(model) self.set_voice(voice_id) - self._context_id = None self._receive_task = None def can_generate_metrics(self) -> bool: @@ -430,7 +428,7 @@ class CartesiaTTSService(AudioContextWordTTSService): msg = { "transcript": text, "continue": continue_transcript, - "context_id": self._context_id, + "context_id": self.get_active_audio_context_id(), "model_id": self.model_name, "voice": voice_config, "output_format": self._settings["output_format"], @@ -523,7 +521,7 @@ class CartesiaTTSService(AudioContextWordTTSService): except Exception as e: await self.push_error(error_msg=f"Unknown error occurred: {e}", exception=e) finally: - self._context_id = None + await self.remove_active_audio_context() self._websocket = None await self._call_event_handler("on_disconnected") @@ -533,35 +531,22 @@ class CartesiaTTSService(AudioContextWordTTSService): raise Exception("Websocket not connected") async def _handle_interruption(self, frame: InterruptionFrame, direction: FrameDirection): + context_id = self.get_active_audio_context_id() await super()._handle_interruption(frame, direction) await self.stop_all_metrics() - if self._context_id: - cancel_msg = json.dumps({"context_id": self._context_id, "cancel": True}) + if context_id: + cancel_msg = json.dumps({"context_id": context_id, "cancel": True}) await self._get_websocket().send(cancel_msg) - self._context_id = None - - def create_context_id(self) -> str: - """Generate a unique context ID for a TTS request in case we don't have one already in progress. - - Returns: - A unique string identifier for the TTS context. - """ - # If a context ID does not exist, create a new one. - # If an ID exists, continue using the current ID. - # When interruptions happen, user speech results in - # an interruption, which resets the context ID. - if not self._context_id: - return str(uuid.uuid4()) - return self._context_id async def flush_audio(self): """Flush any pending audio and finalize the current context.""" - if not self._context_id or not self._websocket: + context_id = self.get_active_audio_context_id() + if not context_id or not self._websocket: return logger.trace(f"{self}: flushing audio") msg = self._build_msg(text="", continue_transcript=False) await self._websocket.send(msg) - self._context_id = None + self.reset_active_audio_context() async def _process_messages(self): async for message in self._get_websocket(): @@ -593,7 +578,7 @@ class CartesiaTTSService(AudioContextWordTTSService): await self.push_frame(TTSStoppedFrame(context_id=ctx_id)) await self.stop_all_metrics() await self.push_error(error_msg=f"Error: {msg}") - self._context_id = None + self.reset_active_audio_context() else: await self.push_error(error_msg=f"Error, unknown message type: {msg}") @@ -622,11 +607,10 @@ class CartesiaTTSService(AudioContextWordTTSService): if not self._websocket or self._websocket.state is State.CLOSED: await self._connect() - if not self._context_id: + if not self.has_active_audio_context(): await self.start_ttfb_metrics() yield TTSStartedFrame(context_id=context_id) - self._context_id = context_id - await self.create_audio_context(self._context_id) + await self.create_audio_context(context_id) msg = self._build_msg(text=text) diff --git a/src/pipecat/services/elevenlabs/tts.py b/src/pipecat/services/elevenlabs/tts.py index 7df891f0e..be57a1a3d 100644 --- a/src/pipecat/services/elevenlabs/tts.py +++ b/src/pipecat/services/elevenlabs/tts.py @@ -13,7 +13,6 @@ with support for streaming audio, word timestamps, and voice customization. import asyncio import base64 import json -import uuid from typing import Any, AsyncGenerator, Dict, List, Literal, Mapping, Optional, Tuple, Union import aiohttp @@ -343,7 +342,6 @@ class ElevenLabsTTSService(AudioContextWordTTSService): self._partial_word_start_time = 0.0 # Context management for v1 multi API - self._context_id = None self._receive_task = None self._keepalive_task = None @@ -411,18 +409,19 @@ class ElevenLabsTTSService(AudioContextWordTTSService): ) await self._disconnect() await self._connect() - elif voice_settings_changed and self._context_id: + elif voice_settings_changed and self.has_active_audio_context(): # Voice settings can be updated by closing current context # so new one gets created with updated voice settings logger.debug(f"Voice settings changed, closing current context to apply changes") + context_id = self.get_active_audio_context_id() try: if self._websocket: await self._websocket.send( - json.dumps({"context_id": self._context_id, "close_context": True}) + json.dumps({"context_id": context_id, "close_context": True}) ) except Exception as e: await self.push_error(error_msg=f"Unknown error occurred: {e}", exception=e) - self._context_id = None + self.reset_active_audio_context() async def start(self, frame: StartFrame): """Start the ElevenLabs TTS service. @@ -454,10 +453,11 @@ class ElevenLabsTTSService(AudioContextWordTTSService): async def flush_audio(self): """Flush any pending audio and finalize the current context.""" - if not self._context_id or not self._websocket: + context_id = self.get_active_audio_context_id() + if not context_id or not self._websocket: return logger.trace(f"{self}: flushing audio") - msg = {"context_id": self._context_id, "flush": True} + msg = {"context_id": context_id, "flush": True} await self._websocket.send(json.dumps(msg)) async def push_frame(self, frame: Frame, direction: FrameDirection = FrameDirection.DOWNSTREAM): @@ -470,7 +470,7 @@ class ElevenLabsTTSService(AudioContextWordTTSService): await super().push_frame(frame, direction) if isinstance(frame, (TTSStoppedFrame, InterruptionFrame)): if isinstance(frame, TTSStoppedFrame): - await self.add_word_timestamps([("Reset", 0)], self._context_id) + await self.add_word_timestamps([("Reset", 0)], self.get_active_audio_context_id()) async def _connect(self): await super()._connect() @@ -545,14 +545,14 @@ class ElevenLabsTTSService(AudioContextWordTTSService): if self._websocket: logger.debug("Disconnecting from ElevenLabs") # Close all contexts and the socket - if self._context_id: + if self.has_active_audio_context(): await self._websocket.send(json.dumps({"close_socket": True})) await self._websocket.close() logger.debug("Disconnected from ElevenLabs") except Exception as e: await self.push_error(error_msg=f"Unknown error occurred: {e}", exception=e) finally: - self._context_id = None + await self.remove_active_audio_context() self._websocket = None await self._call_event_handler("on_disconnected") @@ -563,11 +563,12 @@ class ElevenLabsTTSService(AudioContextWordTTSService): async def _handle_interruption(self, frame: InterruptionFrame, direction: FrameDirection): """Handle interruption by closing the current context.""" + # Close the current context when interrupted without closing the websocket + context_id = self.get_active_audio_context_id() await super()._handle_interruption(frame, direction) - # Close the current context when interrupted without closing the websocket - if self._context_id and self._websocket: - logger.trace(f"Closing context {self._context_id} due to interruption") + if context_id and self._websocket: + logger.trace(f"Closing context {context_id} due to interruption") try: # ElevenLabs requires that Pipecat manages the contexts and closes them # when they're not longer in use. Since an InterruptionFrame is pushed @@ -576,11 +577,10 @@ class ElevenLabsTTSService(AudioContextWordTTSService): # Note: We do not need to call remove_audio_context here, as the context is # automatically reset when super ()._handle_interruption is called. await self._websocket.send( - json.dumps({"context_id": self._context_id, "close_context": True}) + json.dumps({"context_id": context_id, "close_context": True}) ) except Exception as e: await self.push_error(error_msg=f"Unknown error occurred: {e}", exception=e) - self._context_id = None self._partial_word = "" self._partial_word_start_time = 0.0 @@ -600,11 +600,11 @@ class ElevenLabsTTSService(AudioContextWordTTSService): # Check if this message belongs to the current context. if not self.audio_context_available(received_ctx_id): - if self._context_id == received_ctx_id: + if self.get_active_audio_context_id() == received_ctx_id: logger.debug( - f"Received a delayed message, recreating the context: {self._context_id}" + f"Received a delayed message, recreating the context: {received_ctx_id}" ) - await self.create_audio_context(self._context_id) + await self.create_audio_context(received_ctx_id) else: # This can happen if a message is received _after_ we have closed a context # due to user interruption but _before_ the `isFinal` message for the context @@ -657,13 +657,14 @@ class ElevenLabsTTSService(AudioContextWordTTSService): await asyncio.sleep(KEEPALIVE_SLEEP) try: if self._websocket and self._websocket.state is State.OPEN: - if self._context_id: + context_id = self.get_active_audio_context_id() + if context_id: # Send keepalive with context ID to keep the connection alive keepalive_message = { "text": "", - "context_id": self._context_id, + "context_id": context_id, } - logger.trace(f"Sending keepalive for context {self._context_id}") + logger.trace(f"Sending keepalive for context {context_id}") else: # It's possible to have a user interruption which clears the context # without generating a new TTS response. In this case, we'll just send @@ -677,24 +678,11 @@ class ElevenLabsTTSService(AudioContextWordTTSService): async def _send_text(self, text: str): """Send text to the WebSocket for synthesis.""" - if self._websocket and self._context_id: - msg = {"text": text, "context_id": self._context_id} + context_id = self.get_active_audio_context_id() + if self._websocket and context_id: + msg = {"text": text, "context_id": context_id} await self._websocket.send(json.dumps(msg)) - def create_context_id(self) -> str: - """Generate a unique context ID for a TTS request in case we don't have one already in progress. - - Returns: - A unique string identifier for the TTS context. - """ - # If a context ID does not exist, create a new one. - # If an ID exists, continue using the current ID. - # When interruptions happens, user speech results in - # an interruption, which resets the context ID. - if not self._context_id: - return str(uuid.uuid4()) - return self._context_id - @traced_tts async def run_tts(self, text: str, context_id: str) -> AsyncGenerator[Frame, None]: """Generate speech from text using ElevenLabs' streaming WebSocket API. @@ -713,19 +701,18 @@ class ElevenLabsTTSService(AudioContextWordTTSService): await self._connect() try: - if not self._context_id: + if not self.has_active_audio_context(): await self.start_ttfb_metrics() yield TTSStartedFrame(context_id=context_id) - self._context_id = context_id self._cumulative_time = 0 self._partial_word = "" self._partial_word_start_time = 0.0 - if not self.audio_context_available(self._context_id): - await self.create_audio_context(self._context_id) + if not self.audio_context_available(context_id): + await self.create_audio_context(context_id) # Initialize context with voice settings and pronunciation dictionaries - msg = {"text": " ", "context_id": self._context_id} + msg = {"text": " ", "context_id": context_id} if self._voice_settings: msg["voice_settings"] = self._voice_settings if self._pronunciation_dictionary_locators: @@ -734,7 +721,7 @@ class ElevenLabsTTSService(AudioContextWordTTSService): for locator in self._pronunciation_dictionary_locators ] await self._websocket.send(json.dumps(msg)) - logger.trace(f"Created new context {self._context_id}") + logger.trace(f"Created new context {context_id}") await self._send_text(text) await self.start_tts_usage_metrics(text) diff --git a/src/pipecat/services/gradium/tts.py b/src/pipecat/services/gradium/tts.py index ef3cbbfde..98e08a9d3 100644 --- a/src/pipecat/services/gradium/tts.py +++ b/src/pipecat/services/gradium/tts.py @@ -6,7 +6,6 @@ import base64 import json -import uuid from typing import Any, AsyncGenerator, Mapping, Optional from loguru import logger @@ -97,7 +96,6 @@ class GradiumTTSService(AudioContextWordTTSService): # State tracking self._receive_task = None - self._context_id: Optional[str] = None def can_generate_metrics(self) -> bool: """Check if this service can generate processing metrics. @@ -129,8 +127,9 @@ class GradiumTTSService(AudioContextWordTTSService): def _build_msg(self, text: str = "") -> dict: """Build JSON message for Gradium API.""" msg = {"text": text, "type": "text"} - if self._context_id: - msg["client_req_id"] = self._context_id + context_id = self.get_active_audio_context_id() + if context_id: + msg["client_req_id"] = context_id return msg async def start(self, frame: StartFrame): @@ -229,6 +228,7 @@ class GradiumTTSService(AudioContextWordTTSService): except Exception as e: await self.push_error(error_msg=f"Unknown error occurred: {e}", exception=e) finally: + await self.remove_active_audio_context() self._websocket = None await self._call_event_handler("on_disconnected") @@ -240,12 +240,13 @@ class GradiumTTSService(AudioContextWordTTSService): async def flush_audio(self): """Flush any pending audio synthesis.""" - if not self._context_id or not self._websocket: + context_id = self.get_active_audio_context_id() + if not context_id or not self._websocket: return try: - msg = {"type": "end_of_stream", "client_req_id": self._context_id} + msg = {"type": "end_of_stream", "client_req_id": context_id} await self._websocket.send(json.dumps(msg)) - self._context_id = None + self.reset_active_audio_context() except ConnectionClosedOK: logger.debug(f"{self}: connection closed normally during flush") except Exception as e: @@ -265,7 +266,6 @@ class GradiumTTSService(AudioContextWordTTSService): """ await super()._handle_interruption(frame, direction) await self.stop_all_metrics() - self._context_id = None async def _receive_messages(self): """Process incoming websocket messages, demultiplexing by client_req_id.""" @@ -306,20 +306,6 @@ class GradiumTTSService(AudioContextWordTTSService): await self.stop_all_metrics() await self.push_error(error_msg=f"Error: {msg.get('message', msg)}") - def create_context_id(self) -> str: - """Generate a unique context ID for a TTS request in case we don't have one already in progress. - - Returns: - A unique string identifier for the TTS context. - """ - # If a context ID does not exist, create a new one. - # If an ID exists, continue using the current ID. - # When interruptions happens, user speech results in - # an interruption, which resets the context ID. - if not self._context_id: - return str(uuid.uuid4()) - return self._context_id - @traced_tts async def run_tts(self, text: str, context_id: str) -> AsyncGenerator[Frame, None]: """Generate speech from text using Gradium's streaming API. @@ -338,11 +324,10 @@ class GradiumTTSService(AudioContextWordTTSService): await self._connect() try: - if not self._context_id: + if not self.has_active_audio_context(): await self.start_ttfb_metrics() yield TTSStartedFrame(context_id=context_id) - self._context_id = context_id - await self.create_audio_context(self._context_id) + await self.create_audio_context(context_id) msg = self._build_msg(text=text) await self._get_websocket().send(json.dumps(msg)) diff --git a/src/pipecat/services/inworld/tts.py b/src/pipecat/services/inworld/tts.py index 9767c1b0a..adf72ce9f 100644 --- a/src/pipecat/services/inworld/tts.py +++ b/src/pipecat/services/inworld/tts.py @@ -517,7 +517,6 @@ class InworldTTSService(AudioContextWordTTSService): self._receive_task = None self._keepalive_task = None - self._context_id = None # Track cumulative time across generations for monotonic timestamps within a turn. # When auto_mode is enabled, the server controls generations and timestamps reset @@ -573,9 +572,10 @@ class InworldTTSService(AudioContextWordTTSService): keeping the context open for subsequent text. The context is only closed on interruption, disconnect, or end of session. """ - if self._context_id and self._websocket: - logger.trace(f"Flushing audio for context {self._context_id}") - await self._send_flush(self._context_id) + context_id = self.get_active_audio_context_id() + if context_id and self._websocket: + logger.trace(f"Flushing audio for context {context_id}") + await self._send_flush(context_id) async def push_frame(self, frame: Frame, direction: FrameDirection = FrameDirection.DOWNSTREAM): """Push a frame and handle state changes. @@ -640,7 +640,7 @@ class InworldTTSService(AudioContextWordTTSService): frame: The interruption frame. direction: The direction of the interruption. """ - old_context_id = self._context_id + old_context_id = self.get_active_audio_context_id() logger.trace(f"{self}: Handling interruption, old context: {old_context_id}") await super()._handle_interruption(frame, direction) @@ -652,7 +652,6 @@ class InworldTTSService(AudioContextWordTTSService): except Exception as e: await self.push_error(error_msg=f"Unknown error occurred: {e}", exception=e) - self._context_id = None self._cumulative_time = 0.0 self._generation_end_time = 0.0 logger.trace(f"{self}: Interruption handled, context reset to None") @@ -736,9 +735,10 @@ class InworldTTSService(AudioContextWordTTSService): if self._websocket: logger.debug("Disconnecting from Inworld WebSocket TTS") - if self._context_id: + context_id = self.get_active_audio_context_id() + if context_id: try: - await self._send_close_context(self._context_id) + await self._send_close_context(context_id) except Exception: pass await self._websocket.close() @@ -746,7 +746,7 @@ class InworldTTSService(AudioContextWordTTSService): except Exception as e: await self.push_error(error_msg=f"Unknown error occurred: {e}", exception=e) finally: - self._context_id = None + await self.remove_active_audio_context() self._websocket = None self._cumulative_time = 0.0 self._generation_end_time = 0.0 @@ -772,7 +772,7 @@ class InworldTTSService(AudioContextWordTTSService): ] logger.debug( f"{self}: Received message types={msg_types}, ctx_id={ctx_id}, " - f"current_ctx={self._context_id}, available={self.audio_context_available(ctx_id) if ctx_id else 'N/A'}" + f"current_ctx={self.get_active_audio_context_id()}, available={self.audio_context_available(ctx_id) if ctx_id else 'N/A'}" ) # Check for errors @@ -784,7 +784,9 @@ class InworldTTSService(AudioContextWordTTSService): # Handle "Context not found" error (code 5) # This can happen when a keepalive message is sent but no context is available. if error_code == 5 and "not found" in error_msg.lower(): - logger.debug(f"{self}: Context {ctx_id or self._context_id} not found.") + logger.debug( + f"{self}: Context {ctx_id or self.get_active_audio_context_id()} not found." + ) continue # For other errors, push error frame @@ -799,11 +801,9 @@ class InworldTTSService(AudioContextWordTTSService): # If the context isn't available but matches our current context ID, # recreate it (handles race conditions during interruption recovery). if ctx_id and not self.audio_context_available(ctx_id): - if self._context_id == ctx_id: - logger.trace( - f"{self}: Recreating audio context for current context: {self._context_id}" - ) - await self.create_audio_context(self._context_id) + if self.get_active_audio_context_id() == ctx_id: + logger.trace(f"{self}: Recreating audio context for current context: {ctx_id}") + await self.create_audio_context(ctx_id) else: # This is a message from an old/closed context - skip it logger.trace(f"{self}: Skipping message from unavailable context: {ctx_id}") @@ -849,8 +849,8 @@ class InworldTTSService(AudioContextWordTTSService): logger.trace(f"{self}: Context closed on server: {ctx_id}") await self.stop_ttfb_metrics() # Only reset if this is our current context - if ctx_id == self._context_id: - self._context_id = None + if ctx_id == self.get_active_audio_context_id(): + self.reset_active_audio_context() if ctx_id and self.audio_context_available(ctx_id): await self.remove_audio_context(ctx_id) await self.add_word_timestamps([("TTSStoppedFrame", 0), ("Reset", 0)], ctx_id) @@ -862,12 +862,13 @@ class InworldTTSService(AudioContextWordTTSService): await asyncio.sleep(KEEPALIVE_SLEEP) try: if self._websocket and self._websocket.state is State.OPEN: - if self._context_id: + context_id = self.get_active_audio_context_id() + if context_id: keepalive_message = { "send_text": {"text": ""}, - "contextId": self._context_id, + "contextId": context_id, } - logger.trace(f"Sending keepalive for context {self._context_id}") + logger.trace(f"Sending keepalive for context {context_id}") else: keepalive_message = {"send_text": {"text": ""}} logger.trace("Sending keepalive without context") @@ -938,20 +939,6 @@ class InworldTTSService(AudioContextWordTTSService): msg = {"close_context": {}, "contextId": context_id} await self.send_with_retry(json.dumps(msg), self._report_error) - def create_context_id(self) -> str: - """Generate a unique context ID for a TTS request in case we don't have one already in progress. - - Returns: - A unique string identifier for the TTS context. - """ - # If a context ID does not exist, create a new one. - # If an ID exists, continue using the current ID. - # When interruptions happen, user speech results in - # an interruption, which resets the context ID. - if not self._context_id: - return str(uuid.uuid4()) - return self._context_id - @traced_tts async def run_tts(self, text: str, context_id: str) -> AsyncGenerator[Frame, None]: """Generate TTS audio for the given text using the Inworld WebSocket TTS service. @@ -970,19 +957,13 @@ class InworldTTSService(AudioContextWordTTSService): await self._connect() try: - if not self._context_id: + if not self.has_active_audio_context(): await self.start_ttfb_metrics() yield TTSStartedFrame(context_id=context_id) - self._context_id = context_id - logger.trace(f"{self}: Creating new context {self._context_id}") - await self.create_audio_context(self._context_id) - await self._send_context(self._context_id) - elif not self.audio_context_available(self._context_id): - # Context exists on server but local tracking was removed - logger.trace(f"{self}: Recreating local audio context {self._context_id}") - await self.create_audio_context(self._context_id) + await self.create_audio_context(context_id) + await self._send_context(context_id) - await self._send_text(self._context_id, text) + await self._send_text(context_id, text) await self.start_tts_usage_metrics(text) except Exception as e: diff --git a/src/pipecat/services/resembleai/tts.py b/src/pipecat/services/resembleai/tts.py index 964b9fa18..c51ccc07b 100644 --- a/src/pipecat/services/resembleai/tts.py +++ b/src/pipecat/services/resembleai/tts.py @@ -25,8 +25,6 @@ from pipecat.frames.frames import ( ) from pipecat.processors.frame_processor import FrameDirection from pipecat.services.tts_service import AudioContextWordTTSService -from pipecat.transcriptions.language import Language -from pipecat.utils.text.base_text_aggregator import BaseTextAggregator from pipecat.utils.tracing.service_decorators import traced_tts try: @@ -70,6 +68,7 @@ class ResembleAITTSService(AudioContextWordTTSService): """ super().__init__( sample_rate=sample_rate, + reuse_context_id_within_turn=False, **kwargs, ) diff --git a/src/pipecat/services/rime/tts.py b/src/pipecat/services/rime/tts.py index cf3c6d5ca..c4b1c870a 100644 --- a/src/pipecat/services/rime/tts.py +++ b/src/pipecat/services/rime/tts.py @@ -12,7 +12,6 @@ using Rime's API for streaming and batch audio synthesis. import base64 import json -import uuid from typing import Any, AsyncGenerator, Mapping, Optional import aiohttp @@ -167,7 +166,6 @@ class RimeTTSService(AudioContextWordTTSService): self._settings = self._build_settings() # State tracking - self._context_id = None # Tracks current turn self._receive_task = None self._cumulative_time = 0 # Accumulates time across messages self._extra_msg_fields = {} # Extra fields for next message @@ -339,7 +337,7 @@ class RimeTTSService(AudioContextWordTTSService): def _build_msg(self, text: str = "") -> dict: """Build JSON message for Rime API.""" - msg = {"text": text, "contextId": self._context_id} + msg = {"text": text, "contextId": self.get_active_audio_context_id()} if self._extra_msg_fields: msg |= self._extra_msg_fields self._extra_msg_fields = {} @@ -427,7 +425,7 @@ class RimeTTSService(AudioContextWordTTSService): except Exception as e: await self.push_error(error_msg=f"Error disconnecting: {e}", exception=e) finally: - self._context_id = None + await self.remove_active_audio_context() self._websocket = None await self._call_event_handler("on_disconnected") @@ -439,11 +437,11 @@ class RimeTTSService(AudioContextWordTTSService): async def _handle_interruption(self, frame: InterruptionFrame, direction: FrameDirection): """Handle interruption by clearing current context.""" + context_id = self.get_active_audio_context_id() await super()._handle_interruption(frame, direction) await self.stop_all_metrics() - if self._context_id: + if context_id: await self._get_websocket().send(json.dumps(self._build_clear_msg())) - self._context_id = None def _calculate_word_times(self, words: list, starts: list, ends: list) -> list: """Calculate word timing pairs with proper spacing and punctuation. @@ -474,28 +472,15 @@ class RimeTTSService(AudioContextWordTTSService): return word_pairs - def create_context_id(self) -> str: - """Generate a unique context ID for a TTS request in case we don't have one already in progress. - - Returns: - A unique string identifier for the TTS context. - """ - # If a context ID does not exist, create a new one. - # If an ID exists, continue using the current ID. - # When interruptions happen, user speech results in - # an interruption, which resets the context ID. - if not self._context_id: - return str(uuid.uuid4()) - return self._context_id - async def flush_audio(self): """Flush any pending audio synthesis.""" - if not self._context_id or not self._websocket: + context_id = self.get_active_audio_context_id() + if not context_id or not self._websocket: return logger.trace(f"{self}: flushing audio") await self._get_websocket().send(json.dumps({"operation": "flush"})) - self._context_id = None + self.reset_active_audio_context() async def _receive_messages(self): """Process incoming websocket messages.""" @@ -537,7 +522,7 @@ class RimeTTSService(AudioContextWordTTSService): await self.push_frame(TTSStoppedFrame()) await self.stop_all_metrics() await self.push_error(error_msg=f"Error: {msg['message']}") - self._context_id = None + self.reset_active_audio_context() async def push_frame(self, frame: Frame, direction: FrameDirection = FrameDirection.DOWNSTREAM): """Push frame and handle end-of-turn conditions. @@ -568,12 +553,11 @@ class RimeTTSService(AudioContextWordTTSService): await self._connect() try: - if not self._context_id: + if not self.has_active_audio_context(): await self.start_ttfb_metrics() yield TTSStartedFrame(context_id=context_id) self._cumulative_time = 0 - self._context_id = context_id - await self.create_audio_context(self._context_id) + await self.create_audio_context(context_id) msg = self._build_msg(text=text) await self._get_websocket().send(json.dumps(msg)) diff --git a/src/pipecat/services/tts_service.py b/src/pipecat/services/tts_service.py index 02c799d0f..1948d3da2 100644 --- a/src/pipecat/services/tts_service.py +++ b/src/pipecat/services/tts_service.py @@ -1042,14 +1042,23 @@ class AudioContextTTSService(WebsocketTTSService): audio from context ID "A" will be played first. """ - def __init__(self, *, reconnect_on_error: bool = True, **kwargs): + def __init__( + self, + *, + reuse_context_id_within_turn: bool = True, + reconnect_on_error: bool = True, + **kwargs, + ): """Initialize the Audio Context TTS service. Args: + reuse_context_id_within_turn: Whether the service should reuse context IDs within the same turn. reconnect_on_error: Whether to automatically reconnect on websocket errors. **kwargs: Additional arguments passed to the parent WebsocketTTSService. """ super().__init__(reconnect_on_error=reconnect_on_error, **kwargs) + self._reuse_context_id_within_turn = reuse_context_id_within_turn + self._context_id = None self._contexts: Dict[str, asyncio.Queue] = {} self._audio_context_task = None @@ -1059,6 +1068,10 @@ class AudioContextTTSService(WebsocketTTSService): Args: context_id: Unique identifier for the audio context. """ + # Set the context ID if not already set + if not self._context_id: + self._context_id = context_id + await self._contexts_queue.put(context_id) self._contexts[context_id] = asyncio.Queue() logger.trace(f"{self} created audio context {context_id}") @@ -1091,6 +1104,32 @@ class AudioContextTTSService(WebsocketTTSService): else: logger.warning(f"{self} unable to remove context {context_id}") + def has_active_audio_context(self) -> bool: + """Check if there is an active audio context. + + Returns: + True if an active audio context exists, False otherwise. + """ + return self._context_id is not None and self.audio_context_available(self._context_id) + + def get_active_audio_context_id(self) -> Optional[str]: + """Get the active audio context ID. + + Returns: + The active context ID, or None if no context is active. + """ + return self._context_id + + async def remove_active_audio_context(self): + """Remove the active audio context.""" + if self._context_id: + await self.remove_audio_context(self._context_id) + self.reset_active_audio_context() + + def reset_active_audio_context(self): + """Reset the active audio context.""" + self._context_id = None + def audio_context_available(self, context_id: str) -> bool: """Check whether the given audio context is registered. @@ -1102,6 +1141,20 @@ class AudioContextTTSService(WebsocketTTSService): """ return context_id in self._contexts + def create_context_id(self) -> str: + """Generate or reuse a context ID based on concurrent TTS support. + + If _reuse_context_id_within_turn is False and a context already exists, + the existing context ID is returned. Otherwise, a new unique context + ID is generated. + + Returns: + A context ID string for the TTS request. + """ + if self._reuse_context_id_within_turn and self._context_id: + return self._context_id + return super().create_context_id() + async def start(self, frame: StartFrame): """Start the audio context TTS service. @@ -1137,6 +1190,7 @@ class AudioContextTTSService(WebsocketTTSService): async def _handle_interruption(self, frame: InterruptionFrame, direction: FrameDirection): await super()._handle_interruption(frame, direction) await self._stop_audio_context_task() + self.reset_active_audio_context() self._create_audio_context_task() def _create_audio_context_task(self): @@ -1155,6 +1209,7 @@ class AudioContextTTSService(WebsocketTTSService): running = True while running: context_id = await self._contexts_queue.get() + self._context_id = context_id if context_id: # Process the audio context until the context doesn't have more @@ -1163,11 +1218,15 @@ class AudioContextTTSService(WebsocketTTSService): # We just finished processing the context, so we can safely remove it. del self._contexts[context_id] + self.reset_active_audio_context() # Append some silence between sentences. silence = b"\x00" * self.sample_rate frame = TTSAudioRawFrame( - audio=silence, sample_rate=self.sample_rate, num_channels=1 + audio=silence, + sample_rate=self.sample_rate, + num_channels=1, + context_id=context_id, ) await self.push_frame(frame) else: From fa659311b6c962e78ff7bc374a26112ceffd1f0a Mon Sep 17 00:00:00 2001 From: filipi87 Date: Fri, 20 Feb 2026 14:57:59 -0300 Subject: [PATCH 0578/1060] Changelog entry --- changelog/3732.changed.md | 3 +++ 1 file changed, 3 insertions(+) create mode 100644 changelog/3732.changed.md diff --git a/changelog/3732.changed.md b/changelog/3732.changed.md new file mode 100644 index 000000000..22681cf04 --- /dev/null +++ b/changelog/3732.changed.md @@ -0,0 +1,3 @@ +- Improved audio context management in `AudioContextTTSService` by moving context ID tracking to the base class and adding `reuse_context_id_within_turn` parameter to control concurrent TTS request handling. + - Added helper methods: `has_active_audio_context()`, `get_active_audio_context_id()`, `remove_active_audio_context()`, `reset_active_audio_context()` + - Simplified Cartesia, ElevenLabs, Inworld, Rime, AsyncAI, and Gradium TTS implementations by removing duplicate context management code From c49eda98e79aaf8441c7508dfa3efe5ac1c74547 Mon Sep 17 00:00:00 2001 From: Daksh Dua Date: Fri, 20 Feb 2026 15:37:14 -0300 Subject: [PATCH 0579/1060] Fix race condition where context times out after sending second transcript --- src/pipecat/services/tts_service.py | 12 ++++++++++++ 1 file changed, 12 insertions(+) diff --git a/src/pipecat/services/tts_service.py b/src/pipecat/services/tts_service.py index 1948d3da2..1e5bdf73f 100644 --- a/src/pipecat/services/tts_service.py +++ b/src/pipecat/services/tts_service.py @@ -1042,6 +1042,8 @@ class AudioContextTTSService(WebsocketTTSService): audio from context ID "A" will be played first. """ + _CONTEXT_KEEPALIVE = object() + def __init__( self, *, @@ -1152,9 +1154,15 @@ class AudioContextTTSService(WebsocketTTSService): A context ID string for the TTS request. """ if self._reuse_context_id_within_turn and self._context_id: + self._refresh_active_audio_context() return self._context_id return super().create_context_id() + def _refresh_active_audio_context(self): + """Signal that the audio context is still in use, resetting the timeout.""" + if self.has_active_audio_context(): + self._contexts[self._context_id].put_nowait(AudioContextTTSService._CONTEXT_KEEPALIVE) + async def start(self, frame: StartFrame): """Start the audio context TTS service. @@ -1242,6 +1250,10 @@ class AudioContextTTSService(WebsocketTTSService): while running: try: frame = await asyncio.wait_for(queue.get(), timeout=AUDIO_CONTEXT_TIMEOUT) + if frame is AudioContextTTSService._CONTEXT_KEEPALIVE: + # Context is still in use, reset the timeout. + continue + if frame: await self.push_frame(frame) running = frame is not None From 023063759aa3ae38289ba23a140289169da5ea1b Mon Sep 17 00:00:00 2001 From: Daksh Dua Date: Fri, 20 Feb 2026 16:00:34 -0300 Subject: [PATCH 0580/1060] Changelog entry for TTS race condition fix. --- changelog/3787.fixed.md | 1 + 1 file changed, 1 insertion(+) create mode 100644 changelog/3787.fixed.md diff --git a/changelog/3787.fixed.md b/changelog/3787.fixed.md new file mode 100644 index 000000000..ff11ada71 --- /dev/null +++ b/changelog/3787.fixed.md @@ -0,0 +1 @@ +- Fixed a race condition in `AudioContextTTSService` where the audio context could time out between consecutive TTS requests within the same turn, causing audio to be discarded. From fecf462139b0f4af9e4a8385f8233f737ae63bcf Mon Sep 17 00:00:00 2001 From: dhruvladia-sarvam Date: Sat, 21 Feb 2026 01:02:37 +0530 Subject: [PATCH 0581/1060] initial --- pyproject.toml | 2 +- src/pipecat/services/sarvam/stt.py | 43 ++++++++++++++++++++++-------- 2 files changed, 33 insertions(+), 12 deletions(-) diff --git a/pyproject.toml b/pyproject.toml index e71202252..db76fa24e 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -108,7 +108,7 @@ riva = [ "pipecat-ai[nvidia]" ] runner = [ "python-dotenv>=1.0.0,<2.0.0", "uvicorn>=0.32.0,<1.0.0", "fastapi>=0.115.6,<0.128.0", "pipecat-ai-small-webrtc-prebuilt>=2.2.0"] sagemaker = ["aws_sdk_sagemaker_runtime_http2; python_version>='3.12'"] sambanova = [] -sarvam = [ "sarvamai==0.1.21", "pipecat-ai[websockets-base]" ] +sarvam = [ "sarvamai==0.1.26a2", "pipecat-ai[websockets-base]" ] sentry = [ "sentry-sdk>=2.28.0,<3" ] silero = [ "onnxruntime~=1.23.2" ] simli = [ "simli-ai~=2.0.1"] diff --git a/src/pipecat/services/sarvam/stt.py b/src/pipecat/services/sarvam/stt.py index 13277fe96..e8f2d55ce 100644 --- a/src/pipecat/services/sarvam/stt.py +++ b/src/pipecat/services/sarvam/stt.py @@ -119,10 +119,10 @@ MODEL_CONFIGS: Dict[str, ModelConfig] = { use_translate_method=True, ), "saaras:v3": ModelConfig( - supports_prompt=True, + supports_prompt=False, supports_mode=True, supports_language=True, - default_language="en-IN", + default_language="unknown", default_mode="transcribe", use_translate_endpoint=False, use_translate_method=False, @@ -155,9 +155,9 @@ class SarvamSTTService(STTService): language: Target language for transcription. - saarika:v2.5: Defaults to "unknown" (auto-detect supported) - saaras:v2.5: Not used (auto-detects language) - - saaras:v3: Defaults to "en-IN" + - saaras:v3: Defaults to "unknown" (auto-detect supported) prompt: Optional prompt to guide transcription/translation style/context. - Only applicable to saaras models (v2.5 and v3). Defaults to None. + Only applicable to saaras:v2.5. Defaults to None. mode: Mode of operation for saaras:v3 models only. Options: transcribe, translate, verbatim, translit, codemix. Defaults to "transcribe" for saaras:v3. vad_signals: Enable VAD signals in response. Defaults to None. @@ -190,7 +190,7 @@ class SarvamSTTService(STTService): model: Sarvam model to use for transcription. Allowed values: - "saarika:v2.5": Standard STT model - "saaras:v2.5": STT-Translate model (auto-detects language, supports prompts) - - "saaras:v3": Advanced STT model (supports mode and prompts) + - "saaras:v3": Advanced STT model (supports mode) sample_rate: Audio sample rate. Defaults to 16000 if not specified. input_audio_codec: Audio codec/format of the input file. Defaults to "wav". params: Configuration parameters for Sarvam STT service. @@ -447,13 +447,32 @@ class SarvamSTTService(STTService): if self._config.supports_mode and self._mode is not None: connect_kwargs["mode"] = self._mode + # Prompt support differs across sarvamai versions. Prefer connect-time prompt + # when available and gracefully degrade if the SDK doesn't accept it. + if self._prompt is not None and self._config.supports_prompt: + connect_kwargs["prompt"] = self._prompt + def _connect_with_sdk_headers(connect_fn, **kwargs): # Different SDK versions may use different kwarg names. - for header_kw in ("headers", "additional_headers", "extra_headers"): + # If prompt is unsupported at connect-time, retry without it. + attempts = [kwargs] + if "prompt" in kwargs: + attempts.append({k: v for k, v in kwargs.items() if k != "prompt"}) + + last_type_error = None + for attempt_kwargs in attempts: + for header_kw in ("headers", "additional_headers", "extra_headers"): + try: + return connect_fn(**attempt_kwargs, **{header_kw: self._sdk_headers}) + except TypeError as e: + last_type_error = e try: - return connect_fn(**kwargs, **{header_kw: self._sdk_headers}) - except TypeError: - pass + return connect_fn(**attempt_kwargs) + except TypeError as e: + last_type_error = e + + if last_type_error is not None: + raise last_type_error return connect_fn(**kwargs) # Choose the appropriate endpoint based on model configuration @@ -471,9 +490,11 @@ class SarvamSTTService(STTService): # Enter the async context manager self._socket_client = await self._websocket_context.__aenter__() - # Set prompt if provided (only for models that support prompts) + # Fallback for SDKs that support runtime prompt updates. if self._prompt is not None and self._config.supports_prompt: - await self._socket_client.set_prompt(self._prompt) + prompt_setter = getattr(self._socket_client, "set_prompt", None) + if callable(prompt_setter): + await prompt_setter(self._prompt) # Register event handler for incoming messages def _message_handler(message): From 29e2a861dc35ede003854fbc2c0f3bac5794b2f2 Mon Sep 17 00:00:00 2001 From: Paul Kompfner Date: Fri, 20 Feb 2026 11:42:24 -0500 Subject: [PATCH 0582/1060] Update `AIService.set_model_name` to `AIService._sync_model_name_to_metrics` to: - indicate clearly that it's not meant for public use - make it clear the `self._settings` is the single source of truth for model information - set the stage for an upcoming change where `AIService` subclasses won't have to ever worry about explicitly calling an `AIService` method to sync model name to metrics Across all services, switch from accessing `self._model_name` or `self.model_name` in favor of `self._settings.model`. --- src/pipecat/services/ai_service.py | 26 ++++++------- src/pipecat/services/anthropic/llm.py | 6 +-- src/pipecat/services/asyncai/tts.py | 7 ++-- src/pipecat/services/aws/llm.py | 6 +-- src/pipecat/services/aws/nova_sonic/llm.py | 2 +- src/pipecat/services/azure/image.py | 3 +- src/pipecat/services/camb/tts.py | 9 ++--- src/pipecat/services/cartesia/stt.py | 2 +- src/pipecat/services/cartesia/tts.py | 11 +++--- src/pipecat/services/cerebras/llm.py | 2 +- src/pipecat/services/deepgram/flux/stt.py | 2 +- src/pipecat/services/deepgram/stt.py | 4 +- .../services/deepgram/stt_sagemaker.py | 4 +- src/pipecat/services/deepseek/llm.py | 2 +- src/pipecat/services/elevenlabs/stt.py | 4 +- src/pipecat/services/elevenlabs/tts.py | 10 ++--- src/pipecat/services/fal/image.py | 5 ++- src/pipecat/services/fireworks/llm.py | 2 +- src/pipecat/services/fish/tts.py | 6 +-- src/pipecat/services/gladia/stt.py | 4 +- .../services/google/gemini_live/llm.py | 6 ++- src/pipecat/services/google/image.py | 4 +- src/pipecat/services/google/llm.py | 10 ++--- src/pipecat/services/groq/stt.py | 2 +- src/pipecat/services/groq/tts.py | 4 +- src/pipecat/services/hathora/stt.py | 3 +- src/pipecat/services/hathora/tts.py | 3 +- src/pipecat/services/inworld/tts.py | 4 +- src/pipecat/services/lmnt/tts.py | 4 +- src/pipecat/services/minimax/tts.py | 15 +------- src/pipecat/services/mistral/llm.py | 2 +- src/pipecat/services/moondream/vision.py | 3 +- src/pipecat/services/nvidia/stt.py | 13 +++---- src/pipecat/services/nvidia/tts.py | 5 ++- src/pipecat/services/openai/base_llm.py | 4 +- src/pipecat/services/openai/image.py | 5 ++- src/pipecat/services/openai/realtime/llm.py | 2 +- src/pipecat/services/openai/stt.py | 18 ++++----- src/pipecat/services/openai/tts.py | 4 +- .../services/openai_realtime_beta/openai.py | 2 +- src/pipecat/services/openrouter/llm.py | 3 +- src/pipecat/services/perplexity/llm.py | 2 +- src/pipecat/services/playht/tts.py | 5 ++- src/pipecat/services/rime/tts.py | 23 +++++------ src/pipecat/services/sambanova/llm.py | 2 +- src/pipecat/services/sambanova/stt.py | 2 +- src/pipecat/services/sarvam/stt.py | 18 +++++---- src/pipecat/services/sarvam/tts.py | 7 ++-- src/pipecat/services/soniox/stt.py | 6 +-- src/pipecat/services/speechmatics/stt.py | 2 +- src/pipecat/services/stt_service.py | 2 +- src/pipecat/services/whisper/base_stt.py | 2 +- src/pipecat/services/whisper/stt.py | 8 ++-- .../utils/tracing/service_decorators.py | 38 +++++++++++-------- 54 files changed, 173 insertions(+), 177 deletions(-) diff --git a/src/pipecat/services/ai_service.py b/src/pipecat/services/ai_service.py index ec78549c2..61ed7d456 100644 --- a/src/pipecat/services/ai_service.py +++ b/src/pipecat/services/ai_service.py @@ -42,27 +42,25 @@ class AIService(FrameProcessor): **kwargs: Additional arguments passed to the parent FrameProcessor. """ super().__init__(**kwargs) - self._model_name: str = "" - self._settings: ServiceSettings = ServiceSettings() + self._settings: ServiceSettings = ServiceSettings(model="") self._session_properties: Dict[str, Any] = {} - @property - def model_name(self) -> str: - """Get the current model name. + def _sync_model_name_to_metrics(self): + """Sync the current AI model name (in `self._settings.model`) for usage in metrics. - Returns: - The name of the AI model being used. - """ - return self._model_name + We don't store model name here because there's already a single source + of truth for it in `self._settings.model`. This method is just for + syncing the model name to the metrics data. - def set_model_name(self, model: str): - """Set the AI model name and update metrics. + TODO: as a next step we should make it so that service classes pass + model into `super().__init__` and `AIService` can be responsible for + syncing its initial value to metrics, just as it's responsible for + syncing any updates to its value to metrics via `_update_settings`. Args: model: The name of the AI model to use. """ - self._model_name = model - self.set_core_metrics_data(MetricsData(processor=self.name, model=self._model_name)) + self.set_core_metrics_data(MetricsData(processor=self.name, model=self._settings.model)) async def start(self, frame: StartFrame): """Start the AI service. @@ -117,7 +115,7 @@ class AIService(FrameProcessor): changed = self._settings.apply_update(update) if "model" in changed: - self.set_model_name(self._settings.model) + self._sync_model_name_to_metrics() if changed: logger.info(f"{self.name}: updated settings fields: {set(changed)}") diff --git a/src/pipecat/services/anthropic/llm.py b/src/pipecat/services/anthropic/llm.py index 68ebf7ab1..c7f27c0d1 100644 --- a/src/pipecat/services/anthropic/llm.py +++ b/src/pipecat/services/anthropic/llm.py @@ -237,7 +237,6 @@ class AnthropicLLMService(LLMService): self._client = client or AsyncAnthropic( api_key=api_key ) # if the client is provided, use it and remove it, otherwise create a new one - self.set_model_name(model) self._retry_timeout_secs = retry_timeout_secs self._retry_on_timeout = retry_on_timeout self._settings = AnthropicLLMSettings( @@ -258,6 +257,7 @@ class AnthropicLLMService(LLMService): thinking=params.thinking, extra=params.extra if isinstance(params.extra, dict) else {}, ) + self._sync_model_name_to_metrics() def can_generate_metrics(self) -> bool: """Check if this service can generate usage metrics. @@ -324,7 +324,7 @@ class AnthropicLLMService(LLMService): # Build params using the same method as streaming completions params = { - "model": self.model_name, + "model": self._settings.model, "max_tokens": max_tokens if max_tokens is not None else self._settings.max_tokens, "stream": False, "temperature": self._settings.temperature, @@ -438,7 +438,7 @@ class AnthropicLLMService(LLMService): await self.start_ttfb_metrics() params = { - "model": self.model_name, + "model": self._settings.model, "max_tokens": self._settings.max_tokens, "stream": True, "temperature": self._settings.temperature, diff --git a/src/pipecat/services/asyncai/tts.py b/src/pipecat/services/asyncai/tts.py index 31ce83810..36b4ab4de 100644 --- a/src/pipecat/services/asyncai/tts.py +++ b/src/pipecat/services/asyncai/tts.py @@ -171,8 +171,7 @@ class AsyncAITTSService(AudioContextTTSService): if params.language else None, ) - - self.set_model_name(model) + self._sync_model_name_to_metrics() self._receive_task = None self._keepalive_task = None @@ -513,7 +512,7 @@ class AsyncAIHttpTTSService(TTSService): if params.language else None, ) - self.set_model_name(model) + self._sync_model_name_to_metrics() self._session = aiohttp_session @@ -562,7 +561,7 @@ class AsyncAIHttpTTSService(TTSService): voice_config = {"mode": "id", "id": self._settings.voice} await self.start_ttfb_metrics() payload = { - "model_id": self._model_name, + "model_id": self._settings.model, "transcript": text, "voice": voice_config, "output_format": { diff --git a/src/pipecat/services/aws/llm.py b/src/pipecat/services/aws/llm.py index b39d518ec..de994463b 100644 --- a/src/pipecat/services/aws/llm.py +++ b/src/pipecat/services/aws/llm.py @@ -820,7 +820,6 @@ class AWSBedrockLLMService(LLMService): "config": client_config, } - self.set_model_name(model) self._retry_timeout_secs = retry_timeout_secs self._retry_on_timeout = retry_on_timeout self._settings = AWSBedrockLLMSettings( @@ -833,6 +832,7 @@ class AWSBedrockLLMService(LLMService): if isinstance(params.additional_model_request_fields, dict) else {}, ) + self._sync_model_name_to_metrics() logger.info(f"Using AWS Bedrock model: {model}") @@ -895,7 +895,7 @@ class AWSBedrockLLMService(LLMService): inference_config["maxTokens"] = max_tokens request_params = { - "modelId": self.model_name, + "modelId": self._settings.model, "messages": messages, "additionalModelRequestFields": self._settings.additional_model_request_fields, } @@ -1052,7 +1052,7 @@ class AWSBedrockLLMService(LLMService): # Prepare request parameters request_params = { - "modelId": self.model_name, + "modelId": self._settings.model, "messages": messages, "additionalModelRequestFields": self._settings.additional_model_request_fields, } diff --git a/src/pipecat/services/aws/nova_sonic/llm.py b/src/pipecat/services/aws/nova_sonic/llm.py index 7d2b9c05e..eba5cc21b 100644 --- a/src/pipecat/services/aws/nova_sonic/llm.py +++ b/src/pipecat/services/aws/nova_sonic/llm.py @@ -269,7 +269,7 @@ class AWSNovaSonicLLMService(LLMService): top_p=params.top_p, endpointing_sensitivity=params.endpointing_sensitivity, ) - self.set_model_name(model) + self._sync_model_name_to_metrics() # Audio I/O config (hardware settings, not runtime-tunable) self._input_sample_rate = params.input_sample_rate diff --git a/src/pipecat/services/azure/image.py b/src/pipecat/services/azure/image.py index 2bddf6c43..f5ce4a9f1 100644 --- a/src/pipecat/services/azure/image.py +++ b/src/pipecat/services/azure/image.py @@ -54,7 +54,8 @@ class AzureImageGenServiceREST(ImageGenService): self._api_key = api_key self._azure_endpoint = endpoint self._api_version = api_version - self.set_model_name(model) + self._settings.model = model + self._sync_model_name_to_metrics() self._image_size = image_size self._aiohttp_session = aiohttp_session diff --git a/src/pipecat/services/camb/tts.py b/src/pipecat/services/camb/tts.py index 411b4cabf..a2887df28 100644 --- a/src/pipecat/services/camb/tts.py +++ b/src/pipecat/services/camb/tts.py @@ -236,8 +236,7 @@ class CambTTSService(TTSService): ), user_instructions=params.user_instructions, ) - - self.set_model_name(model) + self._sync_model_name_to_metrics() self._client = None @@ -272,7 +271,7 @@ class CambTTSService(TTSService): # Use model-specific sample rate if not explicitly specified if not self._init_sample_rate: - self._sample_rate = MODEL_SAMPLE_RATES.get(self.model_name, 22050) + self._sample_rate = MODEL_SAMPLE_RATES.get(self._settings.model, 22050) @traced_tts async def run_tts(self, text: str, context_id: str) -> AsyncGenerator[Frame, None]: @@ -300,12 +299,12 @@ class CambTTSService(TTSService): "text": text, "voice_id": self._settings.voice, "language": self._settings.language, - "speech_model": self.model_name, + "speech_model": self._settings.model, "output_configuration": StreamTtsOutputConfiguration(format="pcm_s16le"), } # Add user instructions if using mars-instruct model - if self._model_name == "mars-instruct" and self._settings.user_instructions: + if self._settings.model == "mars-instruct" and self._settings.user_instructions: tts_kwargs["user_instructions"] = self._settings.user_instructions await self.start_tts_usage_metrics(text) diff --git a/src/pipecat/services/cartesia/stt.py b/src/pipecat/services/cartesia/stt.py index e3270936b..6a30f9a53 100644 --- a/src/pipecat/services/cartesia/stt.py +++ b/src/pipecat/services/cartesia/stt.py @@ -201,7 +201,7 @@ class CartesiaSTTService(WebsocketSTTService): language=merged_options.get("language"), encoding=merged_options.get("encoding", "pcm_s16le"), ) - self.set_model_name(merged_options["model"]) + self._sync_model_name_to_metrics() self._api_key = api_key self._base_url = base_url or "api.cartesia.ai" self._receive_task = None diff --git a/src/pipecat/services/cartesia/tts.py b/src/pipecat/services/cartesia/tts.py index daddfa6c8..1185a2305 100644 --- a/src/pipecat/services/cartesia/tts.py +++ b/src/pipecat/services/cartesia/tts.py @@ -330,6 +330,7 @@ class CartesiaTTSService(AudioContextWordTTSService): self._cartesia_version = cartesia_version self._url = url self._settings = CartesiaTTSSettings( + model=model, output_container=container, output_encoding=encoding, output_sample_rate=0, @@ -342,7 +343,7 @@ class CartesiaTTSService(AudioContextWordTTSService): pronunciation_dict_id=params.pronunciation_dict_id, voice=voice_id, ) - self.set_model_name(model) + self._sync_model_name_to_metrics() self._context_id = None self._receive_task = None @@ -457,7 +458,7 @@ class CartesiaTTSService(AudioContextWordTTSService): "transcript": text, "continue": continue_transcript, "context_id": self._context_id, - "model_id": self.model_name, + "model_id": self._settings.model, "voice": voice_config, "output_format": { "container": self._settings.output_container, @@ -465,7 +466,7 @@ class CartesiaTTSService(AudioContextWordTTSService): "sample_rate": self._settings.output_sample_rate, }, "add_timestamps": add_timestamps, - "use_original_timestamps": False if self.model_name == "sonic" else True, + "use_original_timestamps": False if self._settings.model == "sonic" else True, } if is_given(self._settings.language) and self._settings.language: @@ -741,7 +742,7 @@ class CartesiaHttpTTSService(TTSService): generation_config=params.generation_config, pronunciation_dict_id=params.pronunciation_dict_id, ) - self.set_model_name(model) + self._sync_model_name_to_metrics() self._client = AsyncCartesia( api_key=api_key, @@ -829,7 +830,7 @@ class CartesiaHttpTTSService(TTSService): } payload = { - "model_id": self._model_name, + "model_id": self._settings.model, "transcript": text, "voice": voice_config, "output_format": output_format, diff --git a/src/pipecat/services/cerebras/llm.py b/src/pipecat/services/cerebras/llm.py index 01a8165f8..e1ecceef7 100644 --- a/src/pipecat/services/cerebras/llm.py +++ b/src/pipecat/services/cerebras/llm.py @@ -66,7 +66,7 @@ class CerebrasLLMService(OpenAILLMService): Dictionary of parameters for the chat completion request. """ params = { - "model": self.model_name, + "model": self._settings.model, "stream": True, "seed": self._settings.seed, "temperature": self._settings.temperature, diff --git a/src/pipecat/services/deepgram/flux/stt.py b/src/pipecat/services/deepgram/flux/stt.py index e82fc4dd8..3b6ede086 100644 --- a/src/pipecat/services/deepgram/flux/stt.py +++ b/src/pipecat/services/deepgram/flux/stt.py @@ -212,7 +212,7 @@ class DeepgramFluxSTTService(WebsocketSTTService): tag=params.tag or [], min_confidence=params.min_confidence, ) - self.set_model_name(model) + self._sync_model_name_to_metrics() self._api_key = api_key self._url = url self._should_interrupt = should_interrupt diff --git a/src/pipecat/services/deepgram/stt.py b/src/pipecat/services/deepgram/stt.py index 8d4a72fc3..6e5955450 100644 --- a/src/pipecat/services/deepgram/stt.py +++ b/src/pipecat/services/deepgram/stt.py @@ -143,13 +143,13 @@ class DeepgramSTTService(STTService): if "language" in merged_options and isinstance(merged_options["language"], Language): merged_options["language"] = merged_options["language"].value - self.set_model_name(merged_options["model"]) merged_live_options = LiveOptions(**merged_options) self._settings = DeepgramSTTSettings( model=merged_options.get("model"), language=merged_options.get("language"), live_options=merged_live_options, ) + self._sync_model_name_to_metrics() self._addons = addons self._should_interrupt = should_interrupt @@ -225,7 +225,7 @@ class DeepgramSTTService(STTService): elif "live_options" in changed and self._settings.live_options.model is not None: # Only live_options was given → pull model up. self._settings.model = self._settings.live_options.model - self.set_model_name(self._settings.model) + self._sync_model_name_to_metrics() # --- Sync language ----------------------------------------------- if language_given: diff --git a/src/pipecat/services/deepgram/stt_sagemaker.py b/src/pipecat/services/deepgram/stt_sagemaker.py index 3184bf7f8..71fdf4417 100644 --- a/src/pipecat/services/deepgram/stt_sagemaker.py +++ b/src/pipecat/services/deepgram/stt_sagemaker.py @@ -143,13 +143,13 @@ class DeepgramSageMakerSTTService(STTService): if "language" in merged_options and isinstance(merged_options["language"], Language): merged_options["language"] = merged_options["language"].value - self.set_model_name(merged_options["model"]) merged_live_options = LiveOptions(**merged_options) self._settings = DeepgramSageMakerSTTSettings( model=merged_options.get("model"), language=merged_options.get("language"), live_options=merged_live_options, ) + self._sync_model_name_to_metrics() self._client: Optional[SageMakerBidiClient] = None self._response_task: Optional[asyncio.Task] = None @@ -193,7 +193,7 @@ class DeepgramSageMakerSTTService(STTService): elif "live_options" in changed and self._settings.live_options.model is not None: # Only live_options was given → pull model up. self._settings.model = self._settings.live_options.model - self.set_model_name(self._settings.model) + self._sync_model_name_to_metrics() # --- Sync language ----------------------------------------------- if language_given: diff --git a/src/pipecat/services/deepseek/llm.py b/src/pipecat/services/deepseek/llm.py index 806dce13d..70318c9ba 100644 --- a/src/pipecat/services/deepseek/llm.py +++ b/src/pipecat/services/deepseek/llm.py @@ -65,7 +65,7 @@ class DeepSeekLLMService(OpenAILLMService): Dictionary of parameters for the chat completion request. """ params = { - "model": self.model_name, + "model": self._settings.model, "stream": True, "stream_options": {"include_usage": True}, "frequency_penalty": self._settings.frequency_penalty, diff --git a/src/pipecat/services/elevenlabs/stt.py b/src/pipecat/services/elevenlabs/stt.py index c3e6b29e7..5ff91f597 100644 --- a/src/pipecat/services/elevenlabs/stt.py +++ b/src/pipecat/services/elevenlabs/stt.py @@ -281,7 +281,7 @@ class ElevenLabsSTTService(SegmentedSTTService): else "eng", tag_audio_events=params.tag_audio_events, ) - self.set_model_name(model) + self._sync_model_name_to_metrics() def can_generate_metrics(self) -> bool: """Check if the service can generate processing metrics. @@ -531,7 +531,7 @@ class ElevenLabsRealtimeSTTService(WebsocketSTTService): enable_logging=params.enable_logging, include_language_detection=params.include_language_detection, ) - self.set_model_name(model) + self._sync_model_name_to_metrics() def can_generate_metrics(self) -> bool: """Check if the service can generate processing metrics. diff --git a/src/pipecat/services/elevenlabs/tts.py b/src/pipecat/services/elevenlabs/tts.py index 7de346826..55875cb69 100644 --- a/src/pipecat/services/elevenlabs/tts.py +++ b/src/pipecat/services/elevenlabs/tts.py @@ -423,7 +423,7 @@ class ElevenLabsTTSService(AudioContextWordTTSService): enable_logging=params.enable_logging, apply_text_normalization=params.apply_text_normalization, ) - self.set_model_name(model) + self._sync_model_name_to_metrics() self._output_format = "" # initialized in start() self._voice_settings = self._set_voice_settings() @@ -607,7 +607,7 @@ class ElevenLabsTTSService(AudioContextWordTTSService): logger.debug("Connecting to ElevenLabs") voice_id = self._settings.voice - model = self.model_name + model = self._settings.model output_format = self._output_format url = f"{self._url}/v1/text-to-speech/{voice_id}/multi-stream-input?model_id={model}&output_format={output_format}&auto_mode={self._settings.auto_mode}" @@ -929,7 +929,7 @@ class ElevenLabsHttpTTSService(WordTTSService): speed=params.speed, apply_text_normalization=params.apply_text_normalization, ) - self.set_model_name(model) + self._sync_model_name_to_metrics() self._output_format = "" # initialized in start() self._voice_settings = self._set_voice_settings() self._pronunciation_dictionary_locators = params.pronunciation_dictionary_locators @@ -1100,7 +1100,7 @@ class ElevenLabsHttpTTSService(WordTTSService): payload: Dict[str, Union[str, Dict[str, Union[float, bool]]]] = { "text": text, - "model_id": self._model_name, + "model_id": self._settings.model, } # Include previous text as context if available @@ -1122,7 +1122,7 @@ class ElevenLabsHttpTTSService(WordTTSService): payload["apply_text_normalization"] = self._settings.apply_text_normalization language = self._settings.language - if self._model_name in ELEVENLABS_MULTILINGUAL_MODELS and language: + if self._settings.model in ELEVENLABS_MULTILINGUAL_MODELS and language: payload["language_code"] = language logger.debug(f"Using language code: {language}") elif language: diff --git a/src/pipecat/services/fal/image.py b/src/pipecat/services/fal/image.py index 412cedfbd..fd9d9a22d 100644 --- a/src/pipecat/services/fal/image.py +++ b/src/pipecat/services/fal/image.py @@ -78,7 +78,8 @@ class FalImageGenService(ImageGenService): **kwargs: Additional arguments passed to parent ImageGenService. """ super().__init__(**kwargs) - self.set_model_name(model) + self._settings.model = model + self._sync_model_name_to_metrics() self._params = params self._aiohttp_session = aiohttp_session if key: @@ -103,7 +104,7 @@ class FalImageGenService(ImageGenService): logger.debug(f"Generating image from prompt: {prompt}") response = await fal_client.run_async( - self.model_name, + self._settings.model, arguments={"prompt": prompt, **self._params.model_dump(exclude_none=True)}, ) diff --git a/src/pipecat/services/fireworks/llm.py b/src/pipecat/services/fireworks/llm.py index 9338d8c5a..92deb00b9 100644 --- a/src/pipecat/services/fireworks/llm.py +++ b/src/pipecat/services/fireworks/llm.py @@ -66,7 +66,7 @@ class FireworksLLMService(OpenAILLMService): Dictionary of parameters for the chat completion request. """ params = { - "model": self.model_name, + "model": self._settings.model, "stream": True, "frequency_penalty": self._settings.frequency_penalty, "presence_penalty": self._settings.presence_penalty, diff --git a/src/pipecat/services/fish/tts.py b/src/pipecat/services/fish/tts.py index 131495769..0d84ea7ab 100644 --- a/src/pipecat/services/fish/tts.py +++ b/src/pipecat/services/fish/tts.py @@ -176,6 +176,7 @@ class FishAudioTTSService(InterruptibleTTSService): self._request_id = None self._settings = FishAudioTTSSettings( + model=model_id, voice=reference_id, fish_sample_rate=0, latency=params.latency, @@ -185,8 +186,7 @@ class FishAudioTTSService(InterruptibleTTSService): prosody_volume=params.prosody_volume, reference_id=reference_id, ) - - self.set_model_name(model_id) + self._sync_model_name_to_metrics() def can_generate_metrics(self) -> bool: """Check if this service can generate processing metrics. @@ -267,7 +267,7 @@ class FishAudioTTSService(InterruptibleTTSService): logger.debug("Connecting to Fish Audio") headers = {"Authorization": f"Bearer {self._api_key}"} - headers["model"] = self.model_name + headers["model"] = self._settings.model self._websocket = await websocket_connect(self._base_url, additional_headers=headers) # Send initial start message with ormsgpack diff --git a/src/pipecat/services/gladia/stt.py b/src/pipecat/services/gladia/stt.py index c92d9469f..8d968e00f 100644 --- a/src/pipecat/services/gladia/stt.py +++ b/src/pipecat/services/gladia/stt.py @@ -279,9 +279,9 @@ class GladiaSTTService(WebsocketSTTService): self._api_key = api_key self._region = region self._url = url - self.set_model_name(model) self._receive_task = None self._settings = GladiaSTTSettings(model=model, input_params=params) + self._sync_model_name_to_metrics() # Session management self._session_url = None @@ -328,7 +328,7 @@ class GladiaSTTService(WebsocketSTTService): "bit_depth": params.bit_depth or 16, "sample_rate": self.sample_rate, "channels": params.channels or 1, - "model": self._model_name, + "model": self._settings.model, } # Add custom_metadata if provided diff --git a/src/pipecat/services/google/gemini_live/llm.py b/src/pipecat/services/google/gemini_live/llm.py index 00b540385..84b06a86d 100644 --- a/src/pipecat/services/google/gemini_live/llm.py +++ b/src/pipecat/services/google/gemini_live/llm.py @@ -701,7 +701,6 @@ class GeminiLiveLLMService(LLMService): self._last_sent_time = 0 self._base_url = base_url - self.set_model_name(model) self._voice_id = voice_id self._language_code = params.language @@ -763,6 +762,7 @@ class GeminiLiveLLMService(LLMService): proactivity=params.proactivity or {}, extra=params.extra if isinstance(params.extra, dict) else {}, ) + self._sync_model_name_to_metrics() self._file_api_base_url = file_api_base_url self._file_api: Optional[GeminiFileAPI] = None @@ -1230,7 +1230,9 @@ class GeminiLiveLLMService(LLMService): await self.push_error(error_msg=f"Initialization error: {e}", exception=e) async def _connection_task_handler(self, config: LiveConnectConfig): - async with self._client.aio.live.connect(model=self._model_name, config=config) as session: + async with self._client.aio.live.connect( + model=self._settings.model, config=config + ) as session: logger.info("Connected to Gemini service") # Mark connection start time diff --git a/src/pipecat/services/google/image.py b/src/pipecat/services/google/image.py index fcc8e41d0..f03b1da63 100644 --- a/src/pipecat/services/google/image.py +++ b/src/pipecat/services/google/image.py @@ -79,7 +79,9 @@ class GoogleImageGenService(ImageGenService): http_options = update_google_client_http_options(http_options) self._client = genai.Client(api_key=api_key, http_options=http_options) - self.set_model_name(self._params.model) + + self._settings.model = self._params.model + self._sync_model_name_to_metrics() def can_generate_metrics(self) -> bool: """Check if this service can generate processing metrics. diff --git a/src/pipecat/services/google/llm.py b/src/pipecat/services/google/llm.py index f5a6db78c..2004aa15a 100644 --- a/src/pipecat/services/google/llm.py +++ b/src/pipecat/services/google/llm.py @@ -797,7 +797,6 @@ class GoogleLLMService(LLMService): params = params or GoogleLLMService.InputParams() - self.set_model_name(model) self._api_key = api_key self._system_instruction = system_instruction self._http_options = update_google_client_http_options(http_options) @@ -811,6 +810,7 @@ class GoogleLLMService(LLMService): thinking=params.thinking, extra=params.extra if isinstance(params.extra, dict) else {}, ) + self._sync_model_name_to_metrics() self._tools = tools self._tool_config = tool_config @@ -870,7 +870,7 @@ class GoogleLLMService(LLMService): # Use the new google-genai client's async method response = await self._client.aio.models.generate_content( - model=self._model_name, + model=self._settings.model, contents=messages, config=generation_config, ) @@ -930,10 +930,10 @@ class GoogleLLMService(LLMService): # There's no way to introspect on model capabilities, so # to check for models that we know default to thinkin on # and can be configured to turn it off. - if not self._model_name.startswith("gemini-2.5-flash"): + if not self._settings.model.startswith("gemini-2.5-flash"): return # If we have an image model, we don't use a budget either. - if "image" in self._model_name: + if "image" in self._settings.model: return # If thinking_config is already set, don't override it. if "thinking_config" in generation_params: @@ -974,7 +974,7 @@ class GoogleLLMService(LLMService): await self.start_ttfb_metrics() return await self._client.aio.models.generate_content_stream( - model=self._model_name, + model=self._settings.model, contents=messages, config=generation_config, ) diff --git a/src/pipecat/services/groq/stt.py b/src/pipecat/services/groq/stt.py index 52cb0a7cc..d51e93c68 100644 --- a/src/pipecat/services/groq/stt.py +++ b/src/pipecat/services/groq/stt.py @@ -62,7 +62,7 @@ class GroqSTTService(BaseWhisperSTTService): # Build kwargs dict with only set parameters kwargs = { "file": ("audio.wav", audio, "audio/wav"), - "model": self.model_name, + "model": self._settings.model, # Use verbose_json to get probability metrics "response_format": "verbose_json" if self._include_prob_metrics else "json", "language": self._language, diff --git a/src/pipecat/services/groq/tts.py b/src/pipecat/services/groq/tts.py index 5c3eab636..cc073f8c7 100644 --- a/src/pipecat/services/groq/tts.py +++ b/src/pipecat/services/groq/tts.py @@ -108,7 +108,6 @@ class GroqTTSService(TTSService): params = params or GroqTTSService.InputParams() self._api_key = api_key - self._model_name = model_name self._output_format = output_format self._params = params @@ -120,6 +119,7 @@ class GroqTTSService(TTSService): speed=params.speed, groq_sample_rate=sample_rate, ) + self._sync_model_name_to_metrics() self._client = AsyncGroq(api_key=self._api_key) @@ -149,7 +149,7 @@ class GroqTTSService(TTSService): try: response = await self._client.audio.speech.create( - model=self._model_name, + model=self._settings.model, voice=self._settings.voice, response_format=self._output_format, input=text, diff --git a/src/pipecat/services/hathora/stt.py b/src/pipecat/services/hathora/stt.py index e77e382c0..a08a80aa2 100644 --- a/src/pipecat/services/hathora/stt.py +++ b/src/pipecat/services/hathora/stt.py @@ -105,8 +105,7 @@ class HathoraSTTService(SegmentedSTTService): language=params.language, config=params.config, ) - - self.set_model_name(model) + self._sync_model_name_to_metrics() def can_generate_metrics(self) -> bool: """Check if this service can generate processing metrics. diff --git a/src/pipecat/services/hathora/tts.py b/src/pipecat/services/hathora/tts.py index 9778a2f14..1e7662aab 100644 --- a/src/pipecat/services/hathora/tts.py +++ b/src/pipecat/services/hathora/tts.py @@ -123,8 +123,7 @@ class HathoraTTSService(TTSService): speed=params.speed, config=params.config, ) - - self.set_model_name(model) + self._sync_model_name_to_metrics() def can_generate_metrics(self) -> bool: """Check if this service can generate processing metrics. diff --git a/src/pipecat/services/inworld/tts.py b/src/pipecat/services/inworld/tts.py index 1b6dee46f..1d8aa7e4b 100644 --- a/src/pipecat/services/inworld/tts.py +++ b/src/pipecat/services/inworld/tts.py @@ -173,7 +173,7 @@ class InworldHttpTTSService(WordTTSService): self._cumulative_time = 0.0 - self.set_model_name(model) + self._sync_model_name_to_metrics() def can_generate_metrics(self) -> bool: """Check if this service can generate processing metrics. @@ -562,7 +562,7 @@ class InworldTTSService(AudioContextWordTTSService): # Track the end time of the last word in the current generation self._generation_end_time = 0.0 - self.set_model_name(model) + self._sync_model_name_to_metrics() def can_generate_metrics(self) -> bool: """Check if this service can generate processing metrics. diff --git a/src/pipecat/services/lmnt/tts.py b/src/pipecat/services/lmnt/tts.py index 71ffb4f5f..f70bfa402 100644 --- a/src/pipecat/services/lmnt/tts.py +++ b/src/pipecat/services/lmnt/tts.py @@ -122,13 +122,13 @@ class LmntTTSService(InterruptibleTTSService): ) self._api_key = api_key - self.set_model_name(model) self._settings = LmntTTSSettings( model=model, voice=voice_id, language=self.language_to_service_language(language), format="raw", ) + self._sync_model_name_to_metrics() self._receive_task = None self._context_id: Optional[str] = None @@ -238,7 +238,7 @@ class LmntTTSService(InterruptibleTTSService): "format": self._settings.format, "sample_rate": self.sample_rate, "language": self._settings.language, - "model": self.model_name, + "model": self._settings.model, } # Connect to LMNT's websocket directly diff --git a/src/pipecat/services/minimax/tts.py b/src/pipecat/services/minimax/tts.py index 507febf2d..54925f7e4 100644 --- a/src/pipecat/services/minimax/tts.py +++ b/src/pipecat/services/minimax/tts.py @@ -235,7 +235,6 @@ class MiniMaxHttpTTSService(TTSService): self._group_id = group_id self._base_url = f"{base_url}?GroupId={group_id}" self._session = aiohttp_session - self._model_name = model # Create voice settings self._settings = MiniMaxTTSSettings( @@ -249,9 +248,7 @@ class MiniMaxHttpTTSService(TTSService): audio_format="pcm", audio_channel=1, ) - - # Set model - self.set_model_name(model) + self._sync_model_name_to_metrics() # Add language boost if provided if params.language: @@ -318,14 +315,6 @@ class MiniMaxHttpTTSService(TTSService): """ return language_to_minimax_language(language) - def set_model_name(self, model: str): - """Set the TTS model to use. - - Args: - model: The model name to use for synthesis. - """ - self._model_name = model - async def start(self, frame: StartFrame): """Start the MiniMax TTS service. @@ -382,7 +371,7 @@ class MiniMaxHttpTTSService(TTSService): "stream": self._settings.stream, "voice_setting": voice_setting, "audio_setting": audio_setting, - "model": self._model_name, + "model": self._settings.model, "text": text, } if is_given(self._settings.language_boost): diff --git a/src/pipecat/services/mistral/llm.py b/src/pipecat/services/mistral/llm.py index 7a8f5b71a..984ffb7dd 100644 --- a/src/pipecat/services/mistral/llm.py +++ b/src/pipecat/services/mistral/llm.py @@ -180,7 +180,7 @@ class MistralLLMService(OpenAILLMService): fixed_messages = self._apply_mistral_fixups(params_from_context["messages"]) params = { - "model": self.model_name, + "model": self._settings.model, "stream": True, "messages": fixed_messages, "tools": params_from_context["tools"], diff --git a/src/pipecat/services/moondream/vision.py b/src/pipecat/services/moondream/vision.py index 6a180b4cb..16be15ac5 100644 --- a/src/pipecat/services/moondream/vision.py +++ b/src/pipecat/services/moondream/vision.py @@ -81,7 +81,8 @@ class MoondreamService(VisionService): """ super().__init__(**kwargs) - self.set_model_name(model) + self._settings.model = model + self._sync_model_name_to_metrics() if not use_cpu: device, dtype = detect_device() diff --git a/src/pipecat/services/nvidia/stt.py b/src/pipecat/services/nvidia/stt.py index a79119c34..fd924204e 100644 --- a/src/pipecat/services/nvidia/stt.py +++ b/src/pipecat/services/nvidia/stt.py @@ -181,10 +181,10 @@ class NvidiaSTTService(STTService): self._function_id = model_function_map.get("function_id") self._settings = NvidiaSTTSettings( + model=model_function_map.get("model_name"), language=params.language, ) - - self.set_model_name(model_function_map.get("model_name")) + self._sync_model_name_to_metrics() self._asr_service = None self._queue = None @@ -282,7 +282,7 @@ class NvidiaSTTService(STTService): if not self._thread_task: self._thread_task = self.create_task(self._thread_task_handler()) - logger.debug(f"Initialized NvidiaSTTService with model: {self.model_name}") + logger.debug(f"Initialized NvidiaSTTService with model: {self._settings.model}") async def stop(self, frame: EndFrame): """Stop the NVIDIA Riva STT service and clean up resources. @@ -467,9 +467,6 @@ class NvidiaSegmentedSTTService(SegmentedSTTService): params = params or NvidiaSegmentedSTTService.InputParams() - # Set model name - self.set_model_name(model_function_map.get("model_name")) - # Initialize NVIDIA Riva settings self._api_key = api_key self._server = server @@ -488,6 +485,7 @@ class NvidiaSegmentedSTTService(SegmentedSTTService): self._config = None self._asr_service = None self._settings = NvidiaSegmentedSTTSettings( + model=model_function_map.get("model_name"), language=self.language_to_service_language(params.language or Language.EN_US) or "en-US", profanity_filter=params.profanity_filter, @@ -496,6 +494,7 @@ class NvidiaSegmentedSTTService(SegmentedSTTService): boosted_lm_words=params.boosted_lm_words, boosted_lm_score=params.boosted_lm_score, ) + self._sync_model_name_to_metrics() def language_to_service_language(self, language: Language) -> Optional[str]: """Convert pipecat Language enum to NVIDIA Riva's language code. @@ -578,7 +577,7 @@ class NvidiaSegmentedSTTService(SegmentedSTTService): await super().start(frame) self._initialize_client() self._config = self._create_recognition_config() - logger.debug(f"Initialized NvidiaSegmentedSTTService with model: {self.model_name}") + logger.debug(f"Initialized NvidiaSegmentedSTTService with model: {self._settings.model}") async def _update_settings(self, update: STTSettings) -> dict[str, Any]: """Apply a settings update and sync internal state. diff --git a/src/pipecat/services/nvidia/tts.py b/src/pipecat/services/nvidia/tts.py index 22cffc6c1..ade5da63d 100644 --- a/src/pipecat/services/nvidia/tts.py +++ b/src/pipecat/services/nvidia/tts.py @@ -112,11 +112,12 @@ class NvidiaTTSService(TTSService): self._function_id = model_function_map.get("function_id") self._use_ssl = use_ssl self._settings = NvidiaTTSSettings( + model=model_function_map.get("model_name"), voice=voice_id, language=params.language, quality=params.quality, ) - self.set_model_name(model_function_map.get("model_name")) + self._sync_model_name_to_metrics() self._service = None self._config = None @@ -192,7 +193,7 @@ class NvidiaTTSService(TTSService): await super().start(frame) self._initialize_client() self._config = self._create_synthesis_config() - logger.debug(f"Initialized NvidiaTTSService with model: {self.model_name}") + logger.debug(f"Initialized NvidiaTTSService with model: {self._settings.model}") @traced_tts async def run_tts(self, text: str, context_id: str) -> AsyncGenerator[Frame, None]: diff --git a/src/pipecat/services/openai/base_llm.py b/src/pipecat/services/openai/base_llm.py index 5b624010f..aad88472a 100644 --- a/src/pipecat/services/openai/base_llm.py +++ b/src/pipecat/services/openai/base_llm.py @@ -151,7 +151,7 @@ class BaseOpenAILLMService(LLMService): ) self._retry_timeout_secs = retry_timeout_secs self._retry_on_timeout = retry_on_timeout - self.set_model_name(model) + self._sync_model_name_to_metrics() self._full_model_name: str = "" self._client = self.create_client( api_key=api_key, @@ -265,7 +265,7 @@ class BaseOpenAILLMService(LLMService): Dictionary of parameters for the chat completion request. """ params = { - "model": self.model_name, + "model": self._settings.model, "stream": True, "stream_options": {"include_usage": True}, "frequency_penalty": self._settings.frequency_penalty, diff --git a/src/pipecat/services/openai/image.py b/src/pipecat/services/openai/image.py index d6ca51ae7..36efc5987 100644 --- a/src/pipecat/services/openai/image.py +++ b/src/pipecat/services/openai/image.py @@ -53,7 +53,8 @@ class OpenAIImageGenService(ImageGenService): model: DALL-E model to use for generation. Defaults to "dall-e-3". """ super().__init__() - self.set_model_name(model) + self._settings.model = model + self._sync_model_name_to_metrics() self._image_size = image_size self._client = AsyncOpenAI(api_key=api_key, base_url=base_url) self._aiohttp_session = aiohttp_session @@ -70,7 +71,7 @@ class OpenAIImageGenService(ImageGenService): logger.debug(f"Generating image from prompt: {prompt}") image = await self._client.images.generate( - prompt=prompt, model=self.model_name, n=1, size=self._image_size + prompt=prompt, model=self._settings.model, n=1, size=self._image_size ) image_url = image.data[0].url diff --git a/src/pipecat/services/openai/realtime/llm.py b/src/pipecat/services/openai/realtime/llm.py index 3560f0c27..d765fea75 100644 --- a/src/pipecat/services/openai/realtime/llm.py +++ b/src/pipecat/services/openai/realtime/llm.py @@ -175,12 +175,12 @@ class OpenAIRealtimeLLMService(LLMService): self.api_key = api_key self.base_url = full_url - self.set_model_name(model) self._settings = OpenAIRealtimeLLMSettings( model=model, session_properties=session_properties or events.SessionProperties(), ) + self._sync_model_name_to_metrics() self._audio_input_paused = start_audio_paused self._video_input_paused = start_video_paused self._video_frame_detail = video_frame_detail diff --git a/src/pipecat/services/openai/stt.py b/src/pipecat/services/openai/stt.py index 82ad8c0f0..13a37a2b1 100644 --- a/src/pipecat/services/openai/stt.py +++ b/src/pipecat/services/openai/stt.py @@ -100,24 +100,24 @@ class OpenAISTTService(BaseWhisperSTTService): # Build kwargs dict with only set parameters kwargs = { "file": ("audio.wav", audio, "audio/wav"), - "model": self.model_name, - "language": self._language, + "model": self._settings.model, + "language": self._settings.language, } if self._include_prob_metrics: # GPT-4o-transcribe models only support logprobs (not verbose_json) - if self.model_name in ("gpt-4o-transcribe", "gpt-4o-mini-transcribe"): + if self._settings.model in ("gpt-4o-transcribe", "gpt-4o-mini-transcribe"): kwargs["response_format"] = "json" kwargs["include"] = ["logprobs"] else: # Whisper models support verbose_json kwargs["response_format"] = "verbose_json" - if self._prompt is not None: - kwargs["prompt"] = self._prompt + if self._settings.prompt is not None: + kwargs["prompt"] = self._settings.prompt - if self._temperature is not None: - kwargs["temperature"] = self._temperature + if self._settings.temperature is not None: + kwargs["temperature"] = self._settings.temperature return await self._client.audio.transcriptions.create(**kwargs) @@ -226,7 +226,6 @@ class OpenAIRealtimeSTTService(WebsocketSTTService): self._api_key = api_key self._base_url = base_url - self.set_model_name(model) self._prompt = prompt self._turn_detection = turn_detection @@ -238,6 +237,7 @@ class OpenAIRealtimeSTTService(WebsocketSTTService): language=language, prompt=prompt, ) + self._sync_model_name_to_metrics() self._receive_task = None self._session_ready = False @@ -437,7 +437,7 @@ class OpenAIRealtimeSTTService(WebsocketSTTService): async def _send_session_update(self): """Send ``session.update`` to configure the transcription session.""" - transcription: dict = {"model": self.model_name} + transcription: dict = {"model": self._settings.model} language_code = ( self._language_to_code(self._settings.language) if self._settings.language else None diff --git a/src/pipecat/services/openai/tts.py b/src/pipecat/services/openai/tts.py index 853647f7f..2693bcc27 100644 --- a/src/pipecat/services/openai/tts.py +++ b/src/pipecat/services/openai/tts.py @@ -134,7 +134,6 @@ class OpenAITTSService(TTSService): ) super().__init__(sample_rate=sample_rate, **kwargs) - self.set_model_name(model) self._client = AsyncOpenAI(api_key=api_key, base_url=base_url) if instructions or speed: @@ -154,6 +153,7 @@ class OpenAITTSService(TTSService): instructions=params.instructions if params else instructions, speed=params.speed if params else speed, ) + self._sync_model_name_to_metrics() def can_generate_metrics(self) -> bool: """Check if this service can generate processing metrics. @@ -194,7 +194,7 @@ class OpenAITTSService(TTSService): # Setup API parameters create_params = { "input": text, - "model": self.model_name, + "model": self._settings.model, "voice": VALID_VOICES[self._settings.voice], "response_format": "pcm", } diff --git a/src/pipecat/services/openai_realtime_beta/openai.py b/src/pipecat/services/openai_realtime_beta/openai.py index ef40dcb15..efac34223 100644 --- a/src/pipecat/services/openai_realtime_beta/openai.py +++ b/src/pipecat/services/openai_realtime_beta/openai.py @@ -160,12 +160,12 @@ class OpenAIRealtimeBetaLLMService(LLMService): self.api_key = api_key self.base_url = full_url - self.set_model_name(model) self._settings = OpenAIRealtimeBetaLLMSettings( model=model, session_properties=session_properties or events.SessionProperties(), ) + self._sync_model_name_to_metrics() self._audio_input_paused = start_audio_paused self._send_transcription_frames = send_transcription_frames self._websocket = None diff --git a/src/pipecat/services/openrouter/llm.py b/src/pipecat/services/openrouter/llm.py index a86b18573..c33fda2fc 100644 --- a/src/pipecat/services/openrouter/llm.py +++ b/src/pipecat/services/openrouter/llm.py @@ -72,8 +72,7 @@ class OpenRouterLLMService(OpenAILLMService): Transformed parameters ready for the API call. """ params = super().build_chat_completion_params(params_from_context) - model = getattr(self, "model_name", getattr(self, "model", "")).lower() - if "gemini" in model: + if "gemini" in self._settings.model.lower(): messages = params.get("messages", []) if not messages: return params diff --git a/src/pipecat/services/perplexity/llm.py b/src/pipecat/services/perplexity/llm.py index d2dd40a57..04f25621d 100644 --- a/src/pipecat/services/perplexity/llm.py +++ b/src/pipecat/services/perplexity/llm.py @@ -66,7 +66,7 @@ class PerplexityLLMService(OpenAILLMService): Dictionary of parameters for the chat completion request. """ params = { - "model": self.model_name, + "model": self._settings.model, "stream": True, "messages": params_from_context["messages"], } diff --git a/src/pipecat/services/playht/tts.py b/src/pipecat/services/playht/tts.py index 630351164..26f1e2dad 100644 --- a/src/pipecat/services/playht/tts.py +++ b/src/pipecat/services/playht/tts.py @@ -204,7 +204,7 @@ class PlayHTTTSService(InterruptibleTTSService): speed=params.speed, seed=params.seed, ) - self.set_model_name(voice_engine) + self._sync_model_name_to_metrics() def can_generate_metrics(self) -> bool: """Check if this service can generate processing metrics. @@ -545,6 +545,7 @@ class PlayHTHttpTTSService(TTSService): voice_engine = voice_engine.replace("-ws", "") self._settings = PlayHTTTSSettings( + model=voice_engine, voice=voice_url, language=self.language_to_service_language(params.language) if params.language @@ -554,7 +555,7 @@ class PlayHTHttpTTSService(TTSService): speed=params.speed, seed=params.seed, ) - self.set_model_name(voice_engine) + self._sync_model_name_to_metrics() async def start(self, frame: StartFrame): """Start the PlayHT HTTP TTS service. diff --git a/src/pipecat/services/rime/tts.py b/src/pipecat/services/rime/tts.py index 2f006efc7..d4cb045df 100644 --- a/src/pipecat/services/rime/tts.py +++ b/src/pipecat/services/rime/tts.py @@ -75,7 +75,6 @@ class RimeTTSSettings(TTSSettings): """Settings for Rime WS JSON and HTTP TTS services. Parameters: - modelId: Rime model identifier. audioFormat: Audio output format. samplingRate: Audio sample rate. lang: Rime language code. @@ -86,7 +85,6 @@ class RimeTTSSettings(TTSSettings): inlineSpeedAlpha: Inline speed control markup. """ - modelId: str | _NotGiven = field(default_factory=lambda: NOT_GIVEN) audioFormat: str | _NotGiven = field(default_factory=lambda: NOT_GIVEN) samplingRate: int | _NotGiven = field(default_factory=lambda: NOT_GIVEN) lang: str | _NotGiven = field(default_factory=lambda: NOT_GIVEN) @@ -104,7 +102,6 @@ class RimeNonJsonTTSSettings(TTSSettings): """Settings for Rime non-JSON WS TTS service. Parameters: - modelId: Rime model identifier. audioFormat: Audio output format. samplingRate: Audio sample rate. lang: Rime language code. @@ -114,7 +111,6 @@ class RimeNonJsonTTSSettings(TTSSettings): top_p: Cumulative probability threshold (0.0-1.0). """ - modelId: str | _NotGiven = field(default_factory=lambda: NOT_GIVEN) audioFormat: str | _NotGiven = field(default_factory=lambda: NOT_GIVEN) samplingRate: int | _NotGiven = field(default_factory=lambda: NOT_GIVEN) lang: str | _NotGiven = field(default_factory=lambda: NOT_GIVEN) @@ -210,7 +206,7 @@ class RimeTTSService(AudioContextWordTTSService): self._model = model self._settings = RimeTTSSettings( voice=voice_id, - modelId=model, + model=model, audioFormat="pcm", samplingRate=0, lang=self.language_to_service_language(params.language) if params.language else "eng", @@ -219,6 +215,7 @@ class RimeTTSService(AudioContextWordTTSService): pauseBetweenBrackets=json.dumps(params.pause_between_brackets), phonemizeBetweenBrackets=json.dumps(params.phonemize_between_brackets), ) + self._sync_model_name_to_metrics() # State tracking self._context_id = None # Tracks current turn @@ -353,7 +350,7 @@ class RimeTTSService(AudioContextWordTTSService): f"{k}={v}" for k, v in { "speaker": self._settings.voice, - "modelId": self._settings.modelId, + "modelId": self._settings.model, "audioFormat": self._settings.audioFormat, "samplingRate": self._settings.samplingRate, "lang": self._settings.lang, @@ -589,6 +586,7 @@ class RimeHttpTTSService(TTSService): self._session = aiohttp_session self._base_url = "https://users.rime.ai/v1/rime-tts" self._settings = RimeTTSSettings( + model=model, lang=self.language_to_service_language(params.language) if params.language else "eng", speedAlpha=params.speed_alpha, reduceLatency=params.reduce_latency, @@ -597,7 +595,7 @@ class RimeHttpTTSService(TTSService): inlineSpeedAlpha=params.inline_speed_alpha if params.inline_speed_alpha else NOT_GIVEN, voice=voice_id, ) - self.set_model_name(model) + self._sync_model_name_to_metrics() def can_generate_metrics(self) -> bool: """Check if this service can generate processing metrics. @@ -648,7 +646,7 @@ class RimeHttpTTSService(TTSService): payload["inlineSpeedAlpha"] = self._settings.inlineSpeedAlpha payload["text"] = text payload["speaker"] = self._settings.voice - payload["modelId"] = self._model_name + payload["modelId"] = self._settings.model payload["samplingRate"] = self.sample_rate # Arcana does not support PCM audio @@ -769,7 +767,7 @@ class RimeNonJsonTTSService(InterruptibleTTSService): self._model = model self._settings = RimeNonJsonTTSSettings( voice=voice_id, - modelId=model, + model=model, audioFormat=audio_format, samplingRate=sample_rate, lang=self.language_to_service_language(params.language) @@ -782,6 +780,7 @@ class RimeNonJsonTTSService(InterruptibleTTSService): temperature=params.temperature if params.temperature is not None else NOT_GIVEN, top_p=params.top_p if params.top_p is not None else NOT_GIVEN, ) + self._sync_model_name_to_metrics() # Add any extra parameters for future compatibility if params.extra: self._settings.extra.update(params.extra) @@ -863,7 +862,7 @@ class RimeNonJsonTTSService(InterruptibleTTSService): # Build URL with query parameters (only given, non-None values) settings_dict = { "speaker": self._settings.voice, - "modelId": self._settings.modelId, + "modelId": self._settings.model, "audioFormat": self._settings.audioFormat, "samplingRate": self._settings.samplingRate, } @@ -981,10 +980,6 @@ class RimeNonJsonTTSService(InterruptibleTTSService): """ changed = await super()._update_settings(update) - # Sync model to settings dict field - if "model" in changed: - self._settings.modelId = self._model_name - if changed: logger.debug("Settings changed, reconnecting WebSocket with new parameters") await self._disconnect() diff --git a/src/pipecat/services/sambanova/llm.py b/src/pipecat/services/sambanova/llm.py index 99c7bca2c..016e1740d 100644 --- a/src/pipecat/services/sambanova/llm.py +++ b/src/pipecat/services/sambanova/llm.py @@ -84,7 +84,7 @@ class SambaNovaLLMService(OpenAILLMService): # type: ignore Dictionary of parameters for the chat completion request. """ params = { - "model": self.model_name, + "model": self._settings.model, "stream": True, "stream_options": {"include_usage": True}, "temperature": self._settings.temperature, diff --git a/src/pipecat/services/sambanova/stt.py b/src/pipecat/services/sambanova/stt.py index a1cbe8a22..f313f0d7b 100644 --- a/src/pipecat/services/sambanova/stt.py +++ b/src/pipecat/services/sambanova/stt.py @@ -72,7 +72,7 @@ class SambaNovaSTTService(BaseWhisperSTTService): # type: ignore # Build kwargs dict with only set parameters kwargs = { "file": ("audio.wav", audio, "audio/wav"), - "model": self.model_name, + "model": self._settings.model, "response_format": "json", "language": self._language, } diff --git a/src/pipecat/services/sarvam/stt.py b/src/pipecat/services/sarvam/stt.py index aa6baef14..b2c9560e4 100644 --- a/src/pipecat/services/sarvam/stt.py +++ b/src/pipecat/services/sarvam/stt.py @@ -225,7 +225,6 @@ class SarvamSTTService(STTService): super().__init__(sample_rate=sample_rate, ttfs_p99_latency=ttfs_p99_latency, **kwargs) - self.set_model_name(model) self._api_key = api_key # Store connection parameters @@ -257,6 +256,7 @@ class SarvamSTTService(STTService): vad_signals=params.vad_signals, high_vad_sensitivity=params.high_vad_sensitivity, ) + self._sync_model_name_to_metrics() if params.vad_signals: self._register_event_handler("on_speech_started") @@ -322,7 +322,7 @@ class SarvamSTTService(STTService): if is_given(update.language) and update.language is not None: if not self._config.supports_language: raise ValueError( - f"Model '{self.model_name}' does not support language parameter " + f"Model '{self._settings.model}' does not support language parameter " "(auto-detects language)." ) @@ -330,11 +330,13 @@ class SarvamSTTService(STTService): if is_given(update.prompt) and update.prompt is not None: if not self._config.supports_prompt: raise ValueError( - f"Model '{self.model_name}' does not support prompt parameter." + f"Model '{self._settings.model}' does not support prompt parameter." ) if is_given(update.mode) and update.mode is not None: if not self._config.supports_mode: - raise ValueError(f"Model '{self.model_name}' does not support mode parameter.") + raise ValueError( + f"Model '{self._settings.model}' does not support mode parameter." + ) changed = await super()._update_settings(update) @@ -374,11 +376,13 @@ class SarvamSTTService(STTService): if not self._config.supports_prompt: if prompt is not None: - raise ValueError(f"Model '{self.model_name}' does not support prompt parameter.") + raise ValueError( + f"Model '{self._settings.model}' does not support prompt parameter." + ) # If prompt is None and model doesn't support prompts, silently return (no-op) return - logger.info(f"Updating {self.model_name} prompt.") + logger.info(f"Updating {self._settings.model} prompt.") self._settings.prompt = prompt await self._disconnect() await self._connect() @@ -460,7 +464,7 @@ class SarvamSTTService(STTService): try: # Build common connection parameters connect_kwargs = { - "model": self.model_name, + "model": self._settings.model, "sample_rate": str(self.sample_rate), } diff --git a/src/pipecat/services/sarvam/tts.py b/src/pipecat/services/sarvam/tts.py index cbccd0130..191689f5a 100644 --- a/src/pipecat/services/sarvam/tts.py +++ b/src/pipecat/services/sarvam/tts.py @@ -489,6 +489,7 @@ class SarvamHttpTTSService(TTSService): model=model, voice=voice_id, ) + self._sync_model_name_to_metrics() # Add parameters based on model support if self._config.supports_pitch: @@ -506,8 +507,6 @@ class SarvamHttpTTSService(TTSService): elif params.temperature != 0.6: logger.warning(f"temperature parameter is ignored for {model}") - self.set_model_name(model) - def can_generate_metrics(self) -> bool: """Check if this service can generate processing metrics. @@ -559,7 +558,7 @@ class SarvamHttpTTSService(TTSService): "speaker": self._settings.voice, "sample_rate": self.sample_rate, "enable_preprocessing": self._settings.enable_preprocessing, - "model": self._model_name, + "model": self._settings.model, "pace": self._settings.pace if is_given(self._settings.pace) else 1.0, } @@ -828,7 +827,6 @@ class SarvamTTSService(InterruptibleTTSService): # WebSocket endpoint URL with model query parameter self._websocket_url = f"{url}?model={model}" self._api_key = api_key - self.set_model_name(model) # Validate and clamp pace to model's valid range pace = params.pace @@ -854,6 +852,7 @@ class SarvamTTSService(InterruptibleTTSService): model=model, voice=voice_id, ) + self._sync_model_name_to_metrics() # Add parameters based on model support if self._config.supports_pitch: diff --git a/src/pipecat/services/soniox/stt.py b/src/pipecat/services/soniox/stt.py index 1f34c061c..1e4b49705 100644 --- a/src/pipecat/services/soniox/stt.py +++ b/src/pipecat/services/soniox/stt.py @@ -195,13 +195,13 @@ class SonioxSTTService(WebsocketSTTService): self._api_key = api_key self._url = url - self.set_model_name(params.model) self._vad_force_turn_endpoint = vad_force_turn_endpoint self._settings = SonioxSTTSettings( model=params.model, input_params=params, ) + self._sync_model_name_to_metrics() self._final_transcription_buffer = [] self._last_tokens_received: Optional[float] = None @@ -247,7 +247,7 @@ class SonioxSTTService(WebsocketSTTService): elif "input_params" in changed and self._settings.input_params.model is not None: # Only input_params was given → pull model up. self._settings.model = self._settings.input_params.model - self.set_model_name(self._settings.model) + self._sync_model_name_to_metrics() # TODO: someday we could reconnect here to apply updated settings. # Code might look something like the below: @@ -380,7 +380,7 @@ class SonioxSTTService(WebsocketSTTService): # Send the initial configuration message. config = { "api_key": self._api_key, - "model": self._model_name, + "model": self._settings.model, "audio_format": params.audio_format, "num_channels": params.num_channels or 1, "enable_endpoint_detection": enable_endpoint_detection, diff --git a/src/pipecat/services/speechmatics/stt.py b/src/pipecat/services/speechmatics/stt.py index 2e23765b2..0ec5609b2 100644 --- a/src/pipecat/services/speechmatics/stt.py +++ b/src/pipecat/services/speechmatics/stt.py @@ -459,7 +459,7 @@ class SpeechmaticsSTTService(STTService): # Model + metrics (operating_point comes from the SDK config/preset) self._settings.model = self._config.operating_point.value - self.set_model_name(self._config.operating_point.value) + self._sync_model_name_to_metrics() # Message queue self._stt_msg_queue: asyncio.Queue[dict[str, Any]] = asyncio.Queue() diff --git a/src/pipecat/services/stt_service.py b/src/pipecat/services/stt_service.py index 47b83ab56..de2539932 100644 --- a/src/pipecat/services/stt_service.py +++ b/src/pipecat/services/stt_service.py @@ -492,7 +492,7 @@ class STTService(AIService): if self.metrics_enabled: ttfb_data = TTFBMetricsData( processor=self.name, - model=self.model_name, + model=self._settings.model, value=ttfb, ) await super().push_frame(MetricsFrame(data=[ttfb_data])) diff --git a/src/pipecat/services/whisper/base_stt.py b/src/pipecat/services/whisper/base_stt.py index 74ca2d102..9def3c2f1 100644 --- a/src/pipecat/services/whisper/base_stt.py +++ b/src/pipecat/services/whisper/base_stt.py @@ -156,7 +156,6 @@ class BaseWhisperSTTService(SegmentedSTTService): **kwargs: Additional arguments passed to SegmentedSTTService. """ super().__init__(ttfs_p99_latency=ttfs_p99_latency, **kwargs) - self.set_model_name(model) self._client = self._create_client(api_key, base_url) self._language = self.language_to_service_language(language or Language.EN) self._prompt = prompt @@ -170,6 +169,7 @@ class BaseWhisperSTTService(SegmentedSTTService): prompt=self._prompt, temperature=self._temperature, ) + self._sync_model_name_to_metrics() def _create_client(self, api_key: Optional[str], base_url: Optional[str]): return AsyncOpenAI(api_key=api_key, base_url=base_url) diff --git a/src/pipecat/services/whisper/stt.py b/src/pipecat/services/whisper/stt.py index 033d815d9..205838314 100644 --- a/src/pipecat/services/whisper/stt.py +++ b/src/pipecat/services/whisper/stt.py @@ -236,7 +236,6 @@ class WhisperSTTService(SegmentedSTTService): super().__init__(**kwargs) self._device: str = device self._compute_type = compute_type - self.set_model_name(model if isinstance(model, str) else model.value) self._no_speech_prob = no_speech_prob self._model: Optional[WhisperModel] = None @@ -247,6 +246,7 @@ class WhisperSTTService(SegmentedSTTService): compute_type=self._compute_type, no_speech_prob=self._no_speech_prob, ) + self._sync_model_name_to_metrics() self._load() @@ -281,7 +281,7 @@ class WhisperSTTService(SegmentedSTTService): logger.debug("Loading Whisper model...") self._model = WhisperModel( - self.model_name, device=self._device, compute_type=self._compute_type + self._settings.model, device=self._device, compute_type=self._compute_type ) logger.debug("Loaded Whisper model") except ModuleNotFoundError as e: @@ -370,7 +370,6 @@ class WhisperSTTServiceMLX(WhisperSTTService): # Skip WhisperSTTService.__init__ and call its parent directly SegmentedSTTService.__init__(self, **kwargs) - self.set_model_name(model if isinstance(model, str) else model.value) self._no_speech_prob = no_speech_prob self._temperature = temperature @@ -381,6 +380,7 @@ class WhisperSTTServiceMLX(WhisperSTTService): temperature=self._temperature, engine="mlx", ) + self._sync_model_name_to_metrics() # No need to call _load() as MLX Whisper loads models on demand @@ -421,7 +421,7 @@ class WhisperSTTServiceMLX(WhisperSTTService): chunk = await asyncio.to_thread( mlx_whisper.transcribe, audio_float, - path_or_hf_repo=self.model_name, + path_or_hf_repo=self._settings.model, temperature=self._temperature, language=self._settings.language, ) diff --git a/src/pipecat/utils/tracing/service_decorators.py b/src/pipecat/utils/tracing/service_decorators.py index 3b23f337a..296ff9522 100644 --- a/src/pipecat/utils/tracing/service_decorators.py +++ b/src/pipecat/utils/tracing/service_decorators.py @@ -44,6 +44,23 @@ T = TypeVar("T") R = TypeVar("R") +def _get_model_name(service) -> str: + """Get the model name from a service instance. + + This is a bit of a mess — there were multiple places a model name could live. + Soon, self._settings should be the only source of truth about model name. + In fact...it might already be the case, but juuuuust to be safe, we'll + check all the places we used to store it. + """ + return ( + getattr(getattr(service, "_settings", None), "model", None) + or getattr(service, "_full_model_name", None) + or getattr(service, "model_name", None) + or getattr(service, "_model_name", None) + or "unknown" + ) + + def _noop_decorator(func): """No-op fallback decorator when tracing is unavailable. @@ -194,7 +211,7 @@ def traced_tts(func: Optional[Callable] = None, *, name: Optional[str] = None) - add_tts_span_attributes( span=span, service_name=service_class_name, - model=getattr(self, "model_name") or "unknown", + model=_get_model_name(self), voice_id=getattr(settings, "voice", "unknown"), text=text, settings=settings, @@ -311,7 +328,7 @@ def traced_stt(func: Optional[Callable] = None, *, name: Optional[str] = None) - add_stt_span_attributes( span=current_span, service_name=service_class_name, - model=getattr(self, "model_name") or settings.get("model", "unknown"), + model=_get_model_name(self), transcript=transcript, is_final=is_final, language=str(language) if language else None, @@ -491,10 +508,7 @@ def traced_llm(func: Optional[Callable] = None, *, name: Optional[str] = None) - # Add all available attributes to the span attribute_kwargs = { "service_name": service_class_name, - "model": getattr(self, "_full_model_name", None) - or getattr(self, "model_name", None) - or params.get("model") - or "unknown", + "model": _get_model_name(self), "stream": True, # Most LLM services use streaming "parameters": params, } @@ -593,11 +607,7 @@ def traced_gemini_live(operation: str) -> Callable: ) as current_span: try: # Base service attributes - model_name = ( - getattr(self, "model_name", None) - or getattr(self, "_model_name", None) - or "unknown" - ) + model_name = _get_model_name(self) voice_id = getattr(self, "_voice_id", None) language_code = getattr(self, "_language_code", None) settings = getattr(self, "_settings", {}) @@ -900,11 +910,7 @@ def traced_openai_realtime(operation: str) -> Callable: ) as current_span: try: # Base service attributes - model_name = ( - getattr(self, "model_name", None) - or getattr(self, "_model_name", None) - or "unknown" - ) + model_name = _get_model_name(self) # Operation-specific attribute collection operation_attrs = {} From af4226adbff84c303b9a6a1da43d07d742ab84d2 Mon Sep 17 00:00:00 2001 From: Paul Kompfner Date: Fri, 20 Feb 2026 15:26:17 -0500 Subject: [PATCH 0583/1060] Add changelog entries for service settings refactor PR #3714 --- changelog/3714.changed.md | 1 + changelog/3714.deprecated.md | 1 + 2 files changed, 2 insertions(+) create mode 100644 changelog/3714.changed.md create mode 100644 changelog/3714.deprecated.md diff --git a/changelog/3714.changed.md b/changelog/3714.changed.md new file mode 100644 index 000000000..a3081a7c8 --- /dev/null +++ b/changelog/3714.changed.md @@ -0,0 +1 @@ +- ⚠️ Refactored service settings to use strongly-typed dataclasses (`TTSSettings`, `STTSettings`, `LLMSettings`, and service-specific subclasses) instead of plain dicts. Each service now exposes a `_settings` attribute with discoverable, typed fields. Dict-based `*UpdateSettingsFrame(settings={...})` is deprecated in favor of passing typed settings delta objects. For service maintainers, see changes in COMMUNITY_INTEGRATIONS.md. diff --git a/changelog/3714.deprecated.md b/changelog/3714.deprecated.md new file mode 100644 index 000000000..ee71b2070 --- /dev/null +++ b/changelog/3714.deprecated.md @@ -0,0 +1 @@ +- Deprecated `set_model()`, `set_voice()`, and `set_language()` on AI services in favor of runtime updates via `TTSUpdateSettingsFrame`, `STTUpdateSettingsFrame`, and `LLMUpdateSettingsFrame`. 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=?UTF-8?q?Aleix=20Conchillo=20Flaqu=C3=A9?= Date: Fri, 20 Feb 2026 14:24:22 -0800 Subject: [PATCH 0585/1060] Fix missing await on add_audio_frames_message in Google audio examples The method is async but was being called without await, silently discarding the coroutine. --- examples/foundational/07s-interruptible-google-audio-in.py | 2 +- examples/foundational/25-google-audio-in.py | 2 +- 2 files changed, 2 insertions(+), 2 deletions(-) diff --git a/examples/foundational/07s-interruptible-google-audio-in.py b/examples/foundational/07s-interruptible-google-audio-in.py index 707db107e..1de374a3f 100644 --- a/examples/foundational/07s-interruptible-google-audio-in.py +++ b/examples/foundational/07s-interruptible-google-audio-in.py @@ -96,7 +96,7 @@ class UserAudioCollector(FrameProcessor): self._user_speaking = True elif isinstance(frame, UserStoppedSpeakingFrame): self._user_speaking = False - self._context.add_audio_frames_message(audio_frames=self._audio_frames) + await self._context.add_audio_frames_message(audio_frames=self._audio_frames) await self._user_context_aggregator.push_frame(LLMRunFrame()) elif isinstance(frame, InputAudioRawFrame): diff --git a/examples/foundational/25-google-audio-in.py b/examples/foundational/25-google-audio-in.py index 002aeaa1c..40903e1d5 100644 --- a/examples/foundational/25-google-audio-in.py +++ b/examples/foundational/25-google-audio-in.py @@ -98,7 +98,7 @@ class UserAudioCollector(FrameProcessor): self._user_speaking = True elif isinstance(frame, UserStoppedSpeakingFrame): self._user_speaking = False - self._context.add_audio_frames_message(audio_frames=self._audio_frames) + await self._context.add_audio_frames_message(audio_frames=self._audio_frames) await self._user_context_aggregator.push_frame(LLMContextFrame(context=self._context)) elif isinstance(frame, InputAudioRawFrame): if self._user_speaking: From 827032fefb65246415af137b47dfbe307e958734 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Aleix=20Conchillo=20Flaqu=C3=A9?= Date: Fri, 20 Feb 2026 14:26:41 -0800 Subject: [PATCH 0586/1060] Unblock push_interruption_task_frame_and_wait after timeout When the InterruptionFrame does not complete within the timeout the caller was stuck in an infinite loop logging warnings. Now the event is set after the first timeout so the processor can continue. Also adds a keyword timeout parameter so callers can customize the wait duration. --- src/pipecat/processors/frame_processor.py | 25 ++++++++++++----------- tests/test_frame_processor.py | 5 ++--- 2 files changed, 15 insertions(+), 15 deletions(-) diff --git a/src/pipecat/processors/frame_processor.py b/src/pipecat/processors/frame_processor.py index 4cf32c800..bcdb2d57b 100644 --- a/src/pipecat/processors/frame_processor.py +++ b/src/pipecat/processors/frame_processor.py @@ -52,8 +52,6 @@ from pipecat.processors.metrics.frame_processor_metrics import FrameProcessorMet from pipecat.utils.asyncio.task_manager import BaseTaskManager from pipecat.utils.base_object import BaseObject -INTERRUPTION_COMPLETION_TIMEOUT = 2.0 - class FrameDirection(Enum): """Direction of frame flow in the processing pipeline. @@ -763,7 +761,7 @@ class FrameProcessor(BaseObject): await self._call_event_handler("on_after_push_frame", frame) - async def push_interruption_task_frame_and_wait(self): + async def push_interruption_task_frame_and_wait(self, *, timeout: float = 5.0): """Push an interruption task frame upstream and wait for the interruption. This function sends an `InterruptionTaskFrame` upstream to the @@ -772,9 +770,11 @@ class FrameProcessor(BaseObject): attached to both frames so the caller can wait until the interruption has fully traversed the pipeline. The event is set when the `InterruptionFrame` reaches the pipeline sink. If the frame does - not complete within `INTERRUPTION_COMPLETION_TIMEOUT` seconds, a - warning is logged periodically until it completes. + not complete within the given timeout, a warning is logged and the + event is forcibly set so the caller is unblocked. + Args: + timeout: Maximum seconds to wait for the interruption to complete. """ self._wait_for_interruption = True @@ -782,19 +782,20 @@ class FrameProcessor(BaseObject): await self.push_frame(InterruptionTaskFrame(event=event), FrameDirection.UPSTREAM) - # Wait for the `InterruptionFrame` to complete and log a warning - # periodically if it takes too long. + # Wait for the `InterruptionFrame` to complete and log a warning if it + # takes too long. If it does take too long make sure we unblock it, + # otherwise we will hang here forever. while not event.is_set(): try: - await asyncio.wait_for(event.wait(), timeout=INTERRUPTION_COMPLETION_TIMEOUT) + await asyncio.wait_for(event.wait(), timeout=timeout) except asyncio.TimeoutError: logger.warning( f"{self}: InterruptionFrame has not completed after" - f" {INTERRUPTION_COMPLETION_TIMEOUT}s. Make sure" - " InterruptionFrame.complete() is being called (e.g. if the" - " frame is being blocked or consumed before reaching the" - " pipeline sink)." + f" {timeout}s. Make sure InterruptionFrame.complete()" + " is being called (e.g. if the frame is being blocked" + " or consumed before reaching the pipeline sink)." ) + event.set() self._wait_for_interruption = False diff --git a/tests/test_frame_processor.py b/tests/test_frame_processor.py index 2ce4b7880..138c8e6d8 100644 --- a/tests/test_frame_processor.py +++ b/tests/test_frame_processor.py @@ -25,7 +25,6 @@ from pipecat.frames.frames import ( from pipecat.pipeline.pipeline import Pipeline from pipecat.processors.filters.identity_filter import IdentityFilter from pipecat.processors.frame_processor import ( - INTERRUPTION_COMPLETION_TIMEOUT, FrameDirection, FrameProcessor, ) @@ -521,7 +520,7 @@ class TestFrameProcessor(unittest.IsolatedAsyncioTestCase): # Complete after the timeout so the warning fires # but the test doesn't hang. async def delayed_complete(): - await asyncio.sleep(INTERRUPTION_COMPLETION_TIMEOUT + 1.0) + await asyncio.sleep(1.0) frame.complete() asyncio.create_task(delayed_complete()) @@ -532,7 +531,7 @@ class TestFrameProcessor(unittest.IsolatedAsyncioTestCase): async def process_frame(self, frame: Frame, direction: FrameDirection): await super().process_frame(frame, direction) if isinstance(frame, TextFrame): - await self.push_interruption_task_frame_and_wait() + await self.push_interruption_task_frame_and_wait(timeout=0.5) await self.push_frame(OutputTransportMessageUrgentFrame(message="done")) else: await self.push_frame(frame, direction) From f610fb95f98386d1225ff2cf5b6a7fe26bfced4a Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Aleix=20Conchillo=20Flaqu=C3=A9?= Date: Fri, 20 Feb 2026 14:56:46 -0800 Subject: [PATCH 0587/1060] Add changelog entries for PR #3789 --- changelog/3789.fixed.md | 1 + 1 file changed, 1 insertion(+) create mode 100644 changelog/3789.fixed.md diff --git a/changelog/3789.fixed.md b/changelog/3789.fixed.md new file mode 100644 index 000000000..1bf2be1a3 --- /dev/null +++ b/changelog/3789.fixed.md @@ -0,0 +1 @@ +- Fixed `push_interruption_task_frame_and_wait()` hanging indefinitely when the `InterruptionFrame` does not reach the pipeline sink within the timeout. Added a `timeout` keyword argument to customize the wait duration. From 35aba4128cd06306c40eace546161036c59f9271 Mon Sep 17 00:00:00 2001 From: Joshua Primas Date: Fri, 20 Feb 2026 15:24:48 -0800 Subject: [PATCH 0588/1060] Adding the LemonSlice transport integration --- README.md | 2 +- env.example | 4 + .../foundational/55-lemonslice-transport.py | 117 +++ examples/foundational/README.md | 1 + pyproject.toml | 1 + src/pipecat/transports/lemonslice/__init__.py | 0 .../transports/lemonslice/transport.py | 799 ++++++++++++++++++ src/pipecat/transports/lemonslice/utils.py | 108 +++ uv.lock | 48 +- 9 files changed, 1055 insertions(+), 25 deletions(-) create mode 100644 examples/foundational/55-lemonslice-transport.py create mode 100644 src/pipecat/transports/lemonslice/__init__.py create mode 100644 src/pipecat/transports/lemonslice/transport.py create mode 100644 src/pipecat/transports/lemonslice/utils.py diff --git a/README.md b/README.md index 6d6a56612..38a6aa8b3 100644 --- a/README.md +++ b/README.md @@ -79,7 +79,7 @@ Catch new features, interviews, and how-tos on our [Pipecat TV](https://www.yout | Speech-to-Speech | [AWS Nova Sonic](https://docs.pipecat.ai/server/services/s2s/aws), [Gemini Multimodal Live](https://docs.pipecat.ai/server/services/s2s/gemini), [Grok Voice Agent](https://docs.pipecat.ai/server/services/s2s/grok), [OpenAI Realtime](https://docs.pipecat.ai/server/services/s2s/openai), [Ultravox](https://docs.pipecat.ai/server/services/s2s/ultravox), | | Transport | [Daily (WebRTC)](https://docs.pipecat.ai/server/services/transport/daily), [FastAPI Websocket](https://docs.pipecat.ai/server/services/transport/fastapi-websocket), [SmallWebRTCTransport](https://docs.pipecat.ai/server/services/transport/small-webrtc), [WebSocket Server](https://docs.pipecat.ai/server/services/transport/websocket-server), Local | | Serializers | [Exotel](https://docs.pipecat.ai/server/utilities/serializers/exotel), [Plivo](https://docs.pipecat.ai/server/utilities/serializers/plivo), [Twilio](https://docs.pipecat.ai/server/utilities/serializers/twilio), [Telnyx](https://docs.pipecat.ai/server/utilities/serializers/telnyx), [Vonage](https://docs.pipecat.ai/server/utilities/serializers/vonage) | -| Video | [HeyGen](https://docs.pipecat.ai/server/services/video/heygen), [Tavus](https://docs.pipecat.ai/server/services/video/tavus), [Simli](https://docs.pipecat.ai/server/services/video/simli) | +| Video | [HeyGen](https://docs.pipecat.ai/server/services/video/heygen), [LemonSlice](https://lemonslice.com/docs/self-managed/overview), [Tavus](https://docs.pipecat.ai/server/services/video/tavus), [Simli](https://docs.pipecat.ai/server/services/video/simli) | | Memory | [mem0](https://docs.pipecat.ai/server/services/memory/mem0) | | Vision & Image | [fal](https://docs.pipecat.ai/server/services/image-generation/fal), [Google Imagen](https://docs.pipecat.ai/server/services/image-generation/google-imagen), [Moondream](https://docs.pipecat.ai/server/services/vision/moondream) | | Audio Processing | [Silero VAD](https://docs.pipecat.ai/server/utilities/audio/silero-vad-analyzer), [Krisp](https://docs.pipecat.ai/server/utilities/audio/krisp-filter), [Koala](https://docs.pipecat.ai/server/utilities/audio/koala-filter), [ai-coustics](https://docs.pipecat.ai/server/utilities/audio/aic-filter) | diff --git a/env.example b/env.example index bc14ea0bf..da52b84dc 100644 --- a/env.example +++ b/env.example @@ -107,6 +107,10 @@ KRISP_MODEL_PATH=... KRISP_VIVA_FILTER_MODEL_PATH=... KRISP_VIVA_TURN_MODEL_PATH=... +# LemonSlice +LEMONSLICE_API_KEY=... +LEMONSLICE_AGENT_ID=... + # LiveKit LIVEKIT_API_KEY=... LIVEKIT_API_SECRET=... diff --git a/examples/foundational/55-lemonslice-transport.py b/examples/foundational/55-lemonslice-transport.py new file mode 100644 index 000000000..0bb4b1d31 --- /dev/null +++ b/examples/foundational/55-lemonslice-transport.py @@ -0,0 +1,117 @@ +# +# Copyright (c) 2024-2026, Daily +# +# SPDX-License-Identifier: BSD 2-Clause License +# + +import asyncio +import os +import sys + +import aiohttp +from dotenv import load_dotenv +from loguru import logger + +from pipecat.audio.vad.silero import SileroVADAnalyzer +from pipecat.frames.frames import LLMRunFrame +from pipecat.pipeline.pipeline import Pipeline +from pipecat.pipeline.runner import PipelineRunner +from pipecat.pipeline.task import PipelineParams, PipelineTask +from pipecat.processors.aggregators.llm_context import LLMContext +from pipecat.processors.aggregators.llm_response_universal import ( + LLMContextAggregatorPair, + LLMUserAggregatorParams, +) +from pipecat.services.deepgram.stt import DeepgramSTTService +from pipecat.services.elevenlabs.tts import ElevenLabsTTSService +from pipecat.services.groq.llm import GroqLLMService +from pipecat.transports.lemonslice.transport import LemonSliceParams, LemonSliceTransport + +load_dotenv(override=True) + +logger.remove(0) +logger.add(sys.stderr, level="DEBUG") + + +async def main(): + async with aiohttp.ClientSession() as session: + transport = LemonSliceTransport( + bot_name="Pipecat bot", + api_key=os.getenv("LEMONSLICE_API_KEY"), + agent_id=os.getenv("LEMONSLICE_AGENT_ID"), + session=session, + params=LemonSliceParams( + audio_in_enabled=True, + audio_out_enabled=True, + microphone_out_enabled=False, + ), + ) + + stt = DeepgramSTTService(api_key=os.getenv("DEEPGRAM_API_KEY")) + + llm = GroqLLMService(api_key=os.getenv("GROQ_API_KEY")) + + tts = ElevenLabsTTSService( + api_key=os.getenv("ELEVENLABS_API_KEY", ""), + voice_id="ys3XeJJA4ArWMhRpcX1D", + ) + + messages = [ + { + "role": "system", + "content": "You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + }, + ] + + context = LLMContext(messages) + user_aggregator, assistant_aggregator = LLMContextAggregatorPair( + context, + user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()), + ) + + pipeline = Pipeline( + [ + transport.input(), # Transport user input + stt, # STT + user_aggregator, # User responses + llm, # LLM + tts, # TTS + transport.output(), # Transport bot output + assistant_aggregator, # Assistant spoken responses + ] + ) + + task = PipelineTask( + pipeline, + params=PipelineParams( + audio_in_sample_rate=16000, + audio_out_sample_rate=16000, + enable_metrics=True, + enable_usage_metrics=True, + ), + ) + + @transport.event_handler("on_client_connected") + async def on_client_connected(transport, participant): + logger.info(f"Client connected") + # Kick off the conversation. + messages.append( + { + "role": "system", + "content": "Start by greeting the user and ask how you can help.", + } + ) + await task.queue_frames([LLMRunFrame()]) + + @transport.event_handler("on_client_disconnected") + async def on_client_disconnected(transport, participant): + logger.info(f"Client disconnected") + await task.cancel() + + runner = PipelineRunner() + + await runner.run(task) + + +if __name__ == "__main__": + asyncio.run(main()) diff --git a/examples/foundational/README.md b/examples/foundational/README.md index 9947dd1e6..8fb60a0c2 100644 --- a/examples/foundational/README.md +++ b/examples/foundational/README.md @@ -121,6 +121,7 @@ uv run 07-interruptible.py -t twilio -x NGROK_HOST_NAME - **[19-openai-realtime-beta.py](./19-openai-realtime-beta.py)**: OpenAI Speech-to-Speech (Direct S2S, Function calls) - **[21-tavus-layer-tavus-transport.py](./21-tavus-layer-tavus-transport.py)**: Tavus digital twin (Avatar integration) - **[27-simli-layer.py](./27-simli-layer.py)**: Simli avatar integration (Video synchronization) +- **[55-lemonslice-transport.py](./55-lemonslice-transport.py)**: LemonSlice avatar integration (A/V Synced Avatar integration) ### Performance & Optimization diff --git a/pyproject.toml b/pyproject.toml index db76fa24e..6c6ca66e3 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -80,6 +80,7 @@ koala = [ "pvkoala~=2.0.3" ] kokoro = [ "kokoro-onnx>=0.5.0,<1", "requests>=2.32.5,<3" ] krisp = [ "pipecat-ai-krisp~=0.4.0" ] langchain = [ "langchain~=0.3.20", "langchain-community~=0.3.20", "langchain-openai~=0.3.9" ] +lemonslice = [] livekit = [ "livekit~=1.0.13", "livekit-api~=1.0.5", "tenacity>=8.2.3,<10.0.0", "pyjwt>=2.10.1" ] lmnt = [ "pipecat-ai[websockets-base]" ] local = [ "pyaudio~=0.2.14" ] diff --git a/src/pipecat/transports/lemonslice/__init__.py b/src/pipecat/transports/lemonslice/__init__.py new file mode 100644 index 000000000..e69de29bb diff --git a/src/pipecat/transports/lemonslice/transport.py b/src/pipecat/transports/lemonslice/transport.py new file mode 100644 index 000000000..b11a92172 --- /dev/null +++ b/src/pipecat/transports/lemonslice/transport.py @@ -0,0 +1,799 @@ +# +# Copyright (c) 2024-2026, Daily +# +# SPDX-License-Identifier: BSD 2-Clause License +# + +"""LemonSlice transport for Pipecat. + +This module adds LemonSlice avatars to Daily rooms, enabling +real-time voice conversations with synchronized avatars. +""" + +from functools import partial +from typing import Any, Awaitable, Callable, Mapping, Optional + +import aiohttp +from daily.daily import AudioData +from loguru import logger +from pydantic import BaseModel + +from pipecat.frames.frames import ( + BotStartedSpeakingFrame, + BotStoppedSpeakingFrame, + CancelFrame, + EndFrame, + Frame, + InputAudioRawFrame, + InterruptionFrame, + OutputAudioRawFrame, + OutputTransportMessageFrame, + OutputTransportMessageUrgentFrame, + StartFrame, +) +from pipecat.processors.frame_processor import FrameDirection, FrameProcessor, FrameProcessorSetup +from pipecat.transports.base_input import BaseInputTransport +from pipecat.transports.base_output import BaseOutputTransport +from pipecat.transports.base_transport import BaseTransport, TransportParams +from pipecat.transports.daily.transport import ( + DailyCallbacks, + DailyParams, + DailyTransportClient, +) +from pipecat.transports.lemonslice.utils import LemonSliceApi + + +class LemonSliceCallbacks(BaseModel): + """Callback handlers for LemonSlice events. + + Parameters: + on_participant_joined: Called when a participant joins the conversation. + on_participant_left: Called when a participant leaves the conversation. + """ + + on_participant_joined: Callable[[Mapping[str, Any]], Awaitable[None]] + on_participant_left: Callable[[Mapping[str, Any], str], Awaitable[None]] + + +class LemonSliceParams(DailyParams): + """Configuration parameters for the LemonSlice transport. + + Parameters: + audio_in_enabled: Whether to enable audio input from participants. + audio_out_enabled: Whether to enable audio output to participants. + microphone_out_enabled: Whether to enable microphone output track. + """ + + audio_in_enabled: bool = True + audio_out_enabled: bool = True + microphone_out_enabled: bool = False + + +class LemonSliceTransportClient: + """Transport client that integrates Pipecat with the LemonSlice platform. + + A transport client that integrates a Pipecat Bot with the LemonSlice platform by managing + conversation sessions using the LemonSlice API. + + This client uses `LemonSliceApi` to interact with the LemonSlice backend. LemonSlice either provides + a room URL where the avatar is already present, or adds the LemonSlice avatar to a Daily room + the user supplies. + """ + + def __init__( + self, + *, + bot_name: str, + params: LemonSliceParams = LemonSliceParams(), + callbacks: LemonSliceCallbacks, + api_key: str, + agent_image_url: Optional[str] = None, + agent_id: Optional[str] = None, + agent_prompt: Optional[str] = None, + idle_timeout: Optional[int] = None, + daily_room_url: Optional[str] = None, + daily_token: Optional[str] = None, + lemonslice_properties: Optional[dict] = None, + session: aiohttp.ClientSession, + ) -> None: + """Initialize the LemonSlice transport client. + + Args: + bot_name: The name of the Pipecat bot instance. + params: Optional parameters for LemonSlice operation. + callbacks: Callback handlers for LemonSlice-related events. + api_key: API key for authenticating with LemonSlice API. + agent_image_url: Optional URL to an agent image. + agent_id: Optional ID of LemonSlice agent. + agent_prompt: Optional system prompt for the avatar. + idle_timeout: Optional idle timeout in seconds. + daily_room_url: Optional Daily room URL to add the LemonSlice avatar to. + daily_token: Optional Daily token for authenticating with the room. + lemonslice_properties: Optional additional properties for the session. + session: The aiohttp session for making async HTTP requests. + """ + self._bot_name = bot_name + self._api = LemonSliceApi(api_key, session) + self._agent_id = agent_id + self._agent_image_url = agent_image_url + self._agent_prompt = agent_prompt + self._idle_timeout = idle_timeout + self._daily_room_url = daily_room_url + self._daily_token = daily_token + self._lemonslice_properties = lemonslice_properties + self._session_id: Optional[str] = None + self._control_url: Optional[str] = None + self._daily_transport_client: Optional[DailyTransportClient] = None + self._callbacks = callbacks + self._params = params + + async def _initialize(self) -> str: + """Initialize the conversation and return the room URL.""" + response = await self._api.create_session( + agent_image_url=self._agent_image_url, + agent_id=self._agent_id, + agent_prompt=self._agent_prompt, + idle_timeout=self._idle_timeout, + daily_room_url=self._daily_room_url, + daily_token=self._daily_token, + properties=self._lemonslice_properties, + ) + self._session_id = response["session_id"] + self._control_url = response["control_url"] + return response["room_url"] + + async def setup(self, setup: FrameProcessorSetup): + """Setup the client and initialize the conversation. + + Args: + setup: The frame processor setup configuration. + """ + if self._session_id is not None: + logger.debug(f"Session ID already defined: {self._session_id}") + return + try: + room_url = await self._initialize() + daily_callbacks = DailyCallbacks( + on_active_speaker_changed=partial( + self._on_handle_callback, "on_active_speaker_changed" + ), + on_joined=self._on_joined, + on_left=self._on_left, + on_before_leave=partial(self._on_handle_callback, "on_before_leave"), + on_error=partial(self._on_handle_callback, "on_error"), + on_app_message=partial(self._on_handle_callback, "on_app_message"), + on_call_state_updated=partial(self._on_handle_callback, "on_call_state_updated"), + on_client_connected=partial(self._on_handle_callback, "on_client_connected"), + on_client_disconnected=partial(self._on_handle_callback, "on_client_disconnected"), + on_dialin_connected=partial(self._on_handle_callback, "on_dialin_connected"), + on_dialin_ready=partial(self._on_handle_callback, "on_dialin_ready"), + on_dialin_stopped=partial(self._on_handle_callback, "on_dialin_stopped"), + on_dialin_error=partial(self._on_handle_callback, "on_dialin_error"), + on_dialin_warning=partial(self._on_handle_callback, "on_dialin_warning"), + on_dialout_answered=partial(self._on_handle_callback, "on_dialout_answered"), + on_dialout_connected=partial(self._on_handle_callback, "on_dialout_connected"), + on_dialout_stopped=partial(self._on_handle_callback, "on_dialout_stopped"), + on_dialout_error=partial(self._on_handle_callback, "on_dialout_error"), + on_dialout_warning=partial(self._on_handle_callback, "on_dialout_warning"), + on_participant_joined=self._callbacks.on_participant_joined, + on_participant_left=self._callbacks.on_participant_left, + on_participant_updated=partial(self._on_handle_callback, "on_participant_updated"), + on_transcription_message=partial( + self._on_handle_callback, "on_transcription_message" + ), + on_recording_started=partial(self._on_handle_callback, "on_recording_started"), + on_recording_stopped=partial(self._on_handle_callback, "on_recording_stopped"), + on_recording_error=partial(self._on_handle_callback, "on_recording_error"), + on_transcription_stopped=partial( + self._on_handle_callback, "on_transcription_stopped" + ), + on_transcription_error=partial(self._on_handle_callback, "on_transcription_error"), + ) + self._daily_transport_client = DailyTransportClient( + room_url, None, self._bot_name, self._params, daily_callbacks, "LemonSlicePipecat" + ) + await self._daily_transport_client.setup(setup) + except Exception as e: + logger.error(f"Failed to setup LemonSliceTransportClient: {e}") + if self._session_id and self._control_url: + await self._api.end_session(self._session_id, self._control_url) + self._session_id = None + self._control_url = None + + async def cleanup(self): + """Cleanup client resources.""" + try: + await self._daily_transport_client.cleanup() + except Exception as e: + logger.error(f"Exception during cleanup: {e}") + + async def _on_joined(self, data): + """Handle joined event.""" + logger.debug("LemonSliceTransportClient joined!") + + async def _on_left(self): + """Handle left event.""" + logger.debug("LemonSliceTransportClient left!") + + async def _on_handle_callback(self, event_name, *args, **kwargs): + """Handle generic callback events.""" + logger.trace(f"[Callback] {event_name} called with args={args}, kwargs={kwargs}") + + async def get_bot_name(self) -> str: + """Get the name of the LemonSlice participant. + + Returns: + The name of the LemonSlice participant. + """ + return "LemonSlice" + + async def start(self, frame: StartFrame): + """Start the client and join the room. + + Args: + frame: The start frame containing initialization parameters. + """ + await self._daily_transport_client.start(frame) + await self._daily_transport_client.join() + + async def stop(self): + """Stop the client and end the conversation.""" + await self._daily_transport_client.leave() + if self._session_id and self._control_url: + await self._api.end_session(self._session_id, self._control_url) + self._session_id = None + self._control_url = None + + async def capture_participant_video( + self, + participant_id: str, + callback: Callable, + framerate: int = 30, + video_source: str = "camera", + color_format: str = "RGB", + ): + """Capture video from a participant. + + Args: + participant_id: ID of the participant to capture video from. + callback: Callback function to handle video frames. + framerate: Desired framerate for video capture. + video_source: Video source to capture from. + color_format: Color format for video frames. + """ + await self._daily_transport_client.capture_participant_video( + participant_id, callback, framerate, video_source, color_format + ) + + async def capture_participant_audio( + self, + participant_id: str, + callback: Callable, + audio_source: str = "microphone", + sample_rate: int = 16000, + callback_interval_ms: int = 20, + ): + """Capture audio from a participant. + + Args: + participant_id: ID of the participant to capture audio from. + callback: Callback function to handle audio data. + audio_source: Audio source to capture from. + sample_rate: Desired sample rate for audio capture. + callback_interval_ms: Interval between audio callbacks in milliseconds. + """ + await self._daily_transport_client.capture_participant_audio( + participant_id, callback, audio_source, sample_rate, callback_interval_ms + ) + + async def send_message( + self, frame: OutputTransportMessageFrame | OutputTransportMessageUrgentFrame + ): + """Send a message to participants. + + Args: + frame: The message frame to send. + """ + await self._daily_transport_client.send_message(frame) + + @property + def out_sample_rate(self) -> int: + """Get the output sample rate. + + Returns: + The output sample rate in Hz. + """ + return self._daily_transport_client.out_sample_rate + + @property + def in_sample_rate(self) -> int: + """Get the input sample rate. + + Returns: + The input sample rate in Hz. + """ + return self._daily_transport_client.in_sample_rate + + async def send_interrupt_message(self) -> None: + """Send an interrupt message to the LemonSlice session.""" + logger.info("Sending interrupt message") + transport_frame = OutputTransportMessageUrgentFrame( + message={ + "event": "interrupt", + "session_id": self._session_id, + } + ) + await self.send_message(transport_frame) + + async def send_response_started_message(self) -> None: + """Send a response_started message to the LemonSlice session.""" + logger.info("Sending response_started message") + transport_frame = OutputTransportMessageUrgentFrame( + message={ + "event": "response_started", + "session_id": self._session_id, + } + ) + await self.send_message(transport_frame) + + async def send_response_finished_message(self) -> None: + """Send a response_finished message to the LemonSlice session.""" + logger.info("Sending response_finished message") + transport_frame = OutputTransportMessageUrgentFrame( + message={ + "event": "response_finished", + "session_id": self._session_id, + } + ) + await self.send_message(transport_frame) + + async def update_subscriptions(self, participant_settings=None, profile_settings=None): + """Update subscription settings for participants. + + Args: + participant_settings: Per-participant subscription settings. + profile_settings: Global subscription profile settings. + """ + if not self._daily_transport_client: + return + + await self._daily_transport_client.update_subscriptions( + participant_settings=participant_settings, profile_settings=profile_settings + ) + + async def write_audio_frame(self, frame: OutputAudioRawFrame) -> bool: + """Write an audio frame to the transport. + + Args: + frame: The audio frame to write. + + Returns: + True if the audio frame was written successfully, False otherwise. + """ + if not self._daily_transport_client: + return False + + return await self._daily_transport_client.write_audio_frame(frame) + + async def register_audio_destination(self, destination: str): + """Register an audio destination for output. + + Args: + destination: The destination identifier to register. + """ + if not self._daily_transport_client: + return + + await self._daily_transport_client.register_audio_destination(destination) + + +class LemonSliceInputTransport(BaseInputTransport): + """Input transport for receiving audio and events from LemonSlice. + + Handles incoming audio streams from participants and manages audio capture + from the Daily room connected to LemonSlice. + """ + + def __init__( + self, + client: LemonSliceTransportClient, + params: TransportParams, + **kwargs, + ): + """Initialize the LemonSlice input transport. + + Args: + client: The LemonSlice transport client instance. + params: Transport configuration parameters. + **kwargs: Additional arguments passed to parent class. + """ + super().__init__(params, **kwargs) + self._client = client + self._params = params + # Whether we have seen a StartFrame already. + self._initialized = False + + async def setup(self, setup: FrameProcessorSetup): + """Setup the input transport. + + Args: + setup: The frame processor setup configuration. + """ + await super().setup(setup) + await self._client.setup(setup) + + async def cleanup(self): + """Cleanup input transport resources.""" + await super().cleanup() + await self._client.cleanup() + + async def start(self, frame: StartFrame): + """Start the input transport. + + Args: + frame: The start frame containing initialization parameters. + """ + await super().start(frame) + + if self._initialized: + return + + self._initialized = True + + await self._client.start(frame) + await self.set_transport_ready(frame) + + async def stop(self, frame: EndFrame): + """Stop the input transport. + + Args: + frame: The end frame signaling transport shutdown. + """ + await super().stop(frame) + await self._client.stop() + + async def cancel(self, frame: CancelFrame): + """Cancel the input transport. + + Args: + frame: The cancel frame signaling immediate cancellation. + """ + await super().cancel(frame) + await self._client.stop() + + async def start_capturing_audio(self, participant): + """Start capturing audio from a participant. + + Args: + participant: The participant to capture audio from. + """ + if self._params.audio_in_enabled: + logger.info( + f"LemonSliceTransportClient start capturing audio for participant {participant['id']}" + ) + await self._client.capture_participant_audio( + participant_id=participant["id"], + callback=self._on_participant_audio_data, + sample_rate=self._client.in_sample_rate, + ) + + async def _on_participant_audio_data( + self, participant_id: str, audio: AudioData, audio_source: str + ): + """Handle received participant audio data. + + Args: + participant_id: ID of the participant who sent the audio. + audio: The audio data from the participant. + audio_source: The source of the audio (e.g., microphone). + """ + frame = InputAudioRawFrame( + audio=audio.audio_frames, + sample_rate=audio.sample_rate, + num_channels=audio.num_channels, + ) + frame.transport_source = audio_source + await self.push_audio_frame(frame) + + +class LemonSliceOutputTransport(BaseOutputTransport): + """Output transport for sending audio and events to LemonSlice. + + Handles outgoing audio streams to participants and manages the custom + audio track expected by the LemonSlice platform. + """ + + def __init__( + self, + client: LemonSliceTransportClient, + params: TransportParams, + **kwargs, + ): + """Initialize the LemonSlice output transport. + + Args: + client: The LemonSlice transport client instance. + params: Transport configuration parameters. + **kwargs: Additional arguments passed to parent class. + """ + super().__init__(params, **kwargs) + self._client = client + self._params = params + + # Whether we have seen a StartFrame already. + self._initialized = False + # This is the custom track destination expected by LemonSlice + self._transport_destination: Optional[str] = "stream" + + async def setup(self, setup: FrameProcessorSetup): + """Setup the output transport. + + Args: + setup: The frame processor setup configuration. + """ + await super().setup(setup) + await self._client.setup(setup) + + async def cleanup(self): + """Cleanup output transport resources.""" + await super().cleanup() + await self._client.cleanup() + + async def start(self, frame: StartFrame): + """Start the output transport. + + Args: + frame: The start frame containing initialization parameters. + """ + await super().start(frame) + + if self._initialized: + return + + self._initialized = True + + await self._client.start(frame) + + if self._transport_destination: + await self._client.register_audio_destination(self._transport_destination) + + await self.set_transport_ready(frame) + + async def stop(self, frame: EndFrame): + """Stop the output transport. + + Args: + frame: The end frame signaling transport shutdown. + """ + await super().stop(frame) + await self._client.stop() + + async def cancel(self, frame: CancelFrame): + """Cancel the output transport. + + Args: + frame: The cancel frame signaling immediate cancellation. + """ + await super().cancel(frame) + await self._client.stop() + + async def send_message( + self, frame: OutputTransportMessageFrame | OutputTransportMessageUrgentFrame + ): + """Send a message to participants. + + Args: + frame: The message frame to send. + """ + logger.info(f"LemonSliceTransport sending message {frame}") + await self._client.send_message(frame) + + async def push_frame(self, frame: Frame, direction: FrameDirection = FrameDirection.DOWNSTREAM): + """Push a frame to the next processor in the pipeline. + + Args: + frame: The frame to push. + direction: The direction to push the frame. + """ + # The BotStartedSpeakingFrame and BotStoppedSpeakingFrame are created inside BaseOutputTransport + # This is a workaround, so we can more reliably be aware when the bot has started or stopped speaking + if direction == FrameDirection.DOWNSTREAM: + if isinstance(frame, BotStartedSpeakingFrame): + await self._handle_response_started() + if isinstance(frame, BotStoppedSpeakingFrame): + await self._handle_response_finished() + await super().push_frame(frame, direction) + + async def process_frame(self, frame: Frame, direction: FrameDirection): + """Process frames and handle interruptions. + + Args: + frame: The frame to process. + direction: The direction of frame flow in the pipeline. + """ + await super().process_frame(frame, direction) + if isinstance(frame, InterruptionFrame): + await self._handle_interruptions() + + async def _handle_interruptions(self): + """Handle interruption events by sending interrupt message.""" + await self._client.send_interrupt_message() + + async def _handle_response_started(self): + """Handle bot started speaking events by sending response_started message.""" + await self._client.send_response_started_message() + + async def _handle_response_finished(self): + """Handle tts response stopped events by sending response_finished message.""" + await self._client.send_response_finished_message() + + async def write_audio_frame(self, frame: OutputAudioRawFrame) -> bool: + """Write an audio frame to the LemonSlice transport. + + Args: + frame: The audio frame to write. + + Returns: + True if the audio frame was written successfully, False otherwise. + """ + # This is the custom track destination expected by LemonSlice + frame.transport_destination = self._transport_destination + return await self._client.write_audio_frame(frame) + + async def register_audio_destination(self, destination: str): + """Register an audio destination. + + Args: + destination: The destination identifier to register. + """ + await self._client.register_audio_destination(destination) + + +class LemonSliceTransport(BaseTransport): + """Transport implementation to add a LemonSlice avatar to Daily calls. + + When used, the Pipecat bot joins the same virtual room as the LemonSlice Avatar and the user. + This is achieved by using `LemonSliceTransportClient`, which initiates the conversation via + `LemonSliceApi` and obtains a room URL that all participants connect to. + + Event handlers available: + + - on_client_connected(transport, participant): Participant connected to the session + - on_client_disconnected(transport, participant): Participant disconnected from the session + + Example:: + + @transport.event_handler("on_client_connected") + async def on_client_connected(transport, participant): + ... + """ + + def __init__( + self, + bot_name: str, + session: aiohttp.ClientSession, + api_key: str, + agent_image_url: Optional[str] = None, + agent_id: Optional[str] = None, + agent_prompt: Optional[str] = None, + idle_timeout: Optional[int] = None, + params: LemonSliceParams = LemonSliceParams(), + input_name: Optional[str] = None, + output_name: Optional[str] = None, + daily_room_url: Optional[str] = None, + daily_token: Optional[str] = None, + lemonslice_properties: dict = {}, + ): + """Initialize the LemonSlice transport. + + Args: + bot_name: The name of the Pipecat bot. + session: aiohttp session used for async HTTP requests. + api_key: LemonSlice API key for authentication. + agent_image_url: Optional URL to an agent image. + agent_id: Optional ID of the LemonSlice agent. + agent_prompt: Optional system prompt for the avatar. + idle_timeout: Optional idle timeout in seconds. + params: Optional LemonSlice-specific configuration parameters. + input_name: Optional name for the input transport. + output_name: Optional name for the output transport. + daily_room_url: Optional Daily room URL to add the LemonSlice avatar to. + daily_token: Optional Daily token for authenticating with the room. + lemonslice_properties: Optional additional properties for the session. + """ + super().__init__(input_name=input_name, output_name=output_name) + self._params = params + + callbacks = LemonSliceCallbacks( + on_participant_joined=self._on_participant_joined, + on_participant_left=self._on_participant_left, + ) + self._client = LemonSliceTransportClient( + bot_name="Pipecat", + callbacks=callbacks, + api_key=api_key, + agent_image_url=agent_image_url, + agent_id=agent_id, + agent_prompt=agent_prompt, + idle_timeout=idle_timeout, + daily_room_url=daily_room_url, + daily_token=daily_token, + lemonslice_properties=lemonslice_properties, + session=session, + params=params, + ) + self._input: Optional[LemonSliceInputTransport] = None + self._output: Optional[LemonSliceOutputTransport] = None + self._lemonslice_participant_id = None + + # Register supported handlers. The user will only be able to register + # these handlers. + self._register_event_handler("on_client_connected") + self._register_event_handler("on_client_disconnected") + + async def _on_participant_left(self, participant, reason): + """Handle participant left events.""" + ls_bot_name = await self._client.get_bot_name() + if participant.get("info", {}).get("userName", "") != ls_bot_name: + await self._on_client_disconnected(participant) + + async def _on_participant_joined(self, participant): + """Handle participant joined events.""" + ls_bot_name = await self._client.get_bot_name() + + # Ignore the LemonSlice bot's microphone + if participant.get("info", {}).get("userName", "") == ls_bot_name: + self._lemonslice_participant_id = participant["id"] + else: + await self._on_client_connected(participant) + if self._lemonslice_participant_id: + logger.debug(f"Ignoring {self._lemonslice_participant_id}'s microphone") + await self.update_subscriptions( + participant_settings={ + self._lemonslice_participant_id: { + "media": {"microphone": "unsubscribed"}, + } + } + ) + if self._input: + await self._input.start_capturing_audio(participant) + + async def update_subscriptions(self, participant_settings=None, profile_settings=None): + """Update subscription settings for participants. + + Args: + participant_settings: Per-participant subscription settings. + profile_settings: Global subscription profile settings. + """ + await self._client.update_subscriptions( + participant_settings=participant_settings, + profile_settings=profile_settings, + ) + + def input(self) -> FrameProcessor: + """Get the input transport for receiving media and events. + + Returns: + The LemonSlice input transport instance. + """ + if not self._input: + self._input = LemonSliceInputTransport(client=self._client, params=self._params) + return self._input + + def output(self) -> FrameProcessor: + """Get the output transport for sending media and events. + + Returns: + The LemonSlice output transport instance. + """ + if not self._output: + self._output = LemonSliceOutputTransport(client=self._client, params=self._params) + return self._output + + async def _on_client_connected(self, participant: Any): + """Handle client connected events.""" + await self._call_event_handler("on_client_connected", participant) + + async def _on_client_disconnected(self, participant: Any): + """Handle client disconnected events.""" + await self._call_event_handler("on_client_disconnected", participant) diff --git a/src/pipecat/transports/lemonslice/utils.py b/src/pipecat/transports/lemonslice/utils.py new file mode 100644 index 000000000..98aac3ccb --- /dev/null +++ b/src/pipecat/transports/lemonslice/utils.py @@ -0,0 +1,108 @@ +# +# Copyright (c) 2024-2026, Daily +# +# SPDX-License-Identifier: BSD 2-Clause License +# + +"""LemonSlice API utilities for session management. + +This module provides helper classes for interacting with the LemonSlice API, +including session creation and termination. +""" + +from typing import Any, Optional + +import aiohttp +from loguru import logger + + +class LemonSliceApi: + """Helper class for interacting with the LemonSlice API. + + Provides methods for creating and managing sessions with LemonSlice avatars. + """ + + LEMONSLICE_URL = "https://lemonslice.com/api/liveai/sessions" + + def __init__(self, api_key: str, session: aiohttp.ClientSession): + """Initialize the LemonSliceApi client. + + Args: + api_key: LemonSlice API key for authentication. + session: An aiohttp session for making HTTP requests. + """ + self._api_key = api_key + self._session = session + self._headers = {"Content-Type": "application/json", "x-api-key": self._api_key} + + async def create_session( + self, + *, + agent_image_url: Optional[str] = None, + agent_id: Optional[str] = None, + agent_prompt: Optional[str] = None, + idle_timeout: Optional[int] = None, + daily_room_url: Optional[str] = None, + daily_token: Optional[str] = None, + properties: Optional[dict[str, Any]] = None, + ) -> dict: + """Create a new session with the specified agent_id or agent_image_url. + + Args: + agent_image_url: The URL to an agent image. Provide either agent_id or agent_image_url. + agent_id: ID of a LemonSlice agent. Provide either agent_id or agent_image_url. + agent_prompt: A high-level system prompt that subtly influences the avatar’s movements, expressions, and emotional demeanor. + idle_timeout: Idle timeout in seconds. + daily_room_url: Daily room URL to use for the session. + daily_token: Daily token for authenticating with the room. + properties: Additional properties to pass to the session. + + Returns: + Dictionary containing session_id, room_url, and control_url. + + Raises: + ValueError: If neither agent_id nor agent_image_url is provided. + """ + if not agent_id and not agent_image_url: + raise ValueError("Provide either agent_id or agent_image_url") + if agent_id and agent_image_url: + raise ValueError("Provide exactly one of agent_id or agent_image_url, not both") + + logger.debug( + f"Creating LemonSlice session: agent_id={agent_id}, agent_image_url={agent_image_url}" + ) + payload: dict[str, object] = {"transport_type": "daily"} + if agent_id is not None: + payload["agent_id"] = agent_id + if agent_image_url is not None: + payload["agent_image_url"] = agent_image_url + if agent_prompt is not None: + payload["agent_prompt"] = agent_prompt + if idle_timeout is not None: + payload["idle_timeout"] = idle_timeout + properties_dict: dict[str, Any] = dict(properties) if properties else {} + if daily_room_url is not None: + properties_dict["daily_url"] = daily_room_url + if daily_token is not None: + properties_dict["daily_token"] = daily_token + if properties_dict: + payload["properties"] = properties_dict + async with self._session.post( + self.LEMONSLICE_URL, headers=self._headers, json=payload + ) as r: + r.raise_for_status() + response = await r.json() + logger.debug(f"Created LemonSlice session: {response}") + return response + + async def end_session(self, session_id: str, control_url: str): + """End an existing session. + + Args: + session_id: ID of the session to end. + control_url: The control URL from the create_session response. + """ + payload = {"event": "terminate"} + async with self._session.post(control_url, headers=self._headers, json=payload) as r: + r.raise_for_status() + logger.debug(f"Ended LemonSlice session {session_id}") diff --git a/uv.lock b/uv.lock index 06563ab45..527ffb217 100644 --- a/uv.lock +++ b/uv.lock @@ -4762,7 +4762,7 @@ requires-dist = [ { name = "wait-for2", marker = "python_full_version < '3.12'", specifier = ">=0.4.1" }, { name = "websockets", marker = "extra == 'websockets-base'", specifier = ">=13.1,<16.0" }, ] -provides-extras = ["aic", "anthropic", "assemblyai", "asyncai", "aws", "aws-nova-sonic", "azure", "cartesia", "camb", "cerebras", "daily", "deepgram", "deepseek", "elevenlabs", "fal", "fireworks", "fish", "gladia", "google", "gradium", "grok", "groq", "gstreamer", "heygen", "hume", "inworld", "koala", "kokoro", "krisp", "langchain", "livekit", "lmnt", "local", "local-smart-turn", "local-smart-turn-v3", "mcp", "mem0", "mistral", "mlx-whisper", "moondream", "neuphonic", "noisereduce", "nvidia", 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b/examples/foundational/55-lemonslice-transport.py index 0bb4b1d31..c9f080567 100644 --- a/examples/foundational/55-lemonslice-transport.py +++ b/examples/foundational/55-lemonslice-transport.py @@ -36,7 +36,7 @@ logger.add(sys.stderr, level="DEBUG") async def main(): async with aiohttp.ClientSession() as session: transport = LemonSliceTransport( - bot_name="Pipecat bot", + bot_name="Pipecat", api_key=os.getenv("LEMONSLICE_API_KEY"), agent_id=os.getenv("LEMONSLICE_AGENT_ID"), session=session, @@ -93,7 +93,7 @@ async def main(): @transport.event_handler("on_client_connected") async def on_client_connected(transport, participant): - logger.info(f"Client connected") + logger.info("Client connected") # Kick off the conversation. messages.append( { @@ -105,7 +105,7 @@ async def main(): @transport.event_handler("on_client_disconnected") async def on_client_disconnected(transport, participant): - logger.info(f"Client disconnected") + logger.info("Client disconnected") await task.cancel() runner = PipelineRunner() diff --git a/pyproject.toml b/pyproject.toml index 6c6ca66e3..b312d553e 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -80,7 +80,7 @@ koala = [ "pvkoala~=2.0.3" ] kokoro = [ "kokoro-onnx>=0.5.0,<1", "requests>=2.32.5,<3" ] krisp = [ "pipecat-ai-krisp~=0.4.0" ] langchain = [ "langchain~=0.3.20", "langchain-community~=0.3.20", "langchain-openai~=0.3.9" ] -lemonslice = [] +lemonslice = [ "pipecat-ai[daily]" ] livekit = [ "livekit~=1.0.13", "livekit-api~=1.0.5", "tenacity>=8.2.3,<10.0.0", "pyjwt>=2.10.1" ] lmnt = [ "pipecat-ai[websockets-base]" ] local = [ "pyaudio~=0.2.14" ] diff --git a/src/pipecat/transports/lemonslice/transport.py b/src/pipecat/transports/lemonslice/transport.py index b11a92172..9ef014f79 100644 --- a/src/pipecat/transports/lemonslice/transport.py +++ b/src/pipecat/transports/lemonslice/transport.py @@ -199,11 +199,13 @@ class LemonSliceTransportClient: await self._api.end_session(self._session_id, self._control_url) self._session_id = None self._control_url = None + raise async def cleanup(self): """Cleanup client resources.""" try: - await self._daily_transport_client.cleanup() + if self._daily_transport_client: + await self._daily_transport_client.cleanup() except Exception as e: logger.error(f"Exception during cleanup: {e}") @@ -316,7 +318,7 @@ class LemonSliceTransportClient: async def send_interrupt_message(self) -> None: """Send an interrupt message to the LemonSlice session.""" - logger.info("Sending interrupt message") + logger.debug("Sending interrupt message") transport_frame = OutputTransportMessageUrgentFrame( message={ "event": "interrupt", @@ -338,7 +340,7 @@ class LemonSliceTransportClient: async def send_response_finished_message(self) -> None: """Send a response_finished message to the LemonSlice session.""" - logger.info("Sending response_finished message") + logger.debug("Sending response_finished message") transport_frame = OutputTransportMessageUrgentFrame( message={ "event": "response_finished", @@ -682,7 +684,7 @@ class LemonSliceTransport(BaseTransport): output_name: Optional[str] = None, daily_room_url: Optional[str] = None, daily_token: Optional[str] = None, - lemonslice_properties: dict = {}, + lemonslice_properties: Optional[dict] = None, ): """Initialize the LemonSlice transport. @@ -709,7 +711,7 @@ class LemonSliceTransport(BaseTransport): on_participant_left=self._on_participant_left, ) self._client = LemonSliceTransportClient( - bot_name="Pipecat", + bot_name=bot_name, callbacks=callbacks, api_key=api_key, agent_image_url=agent_image_url, From d38b1d97d4c65a0b0acc6e84047679788d5ab523 Mon Sep 17 00:00:00 2001 From: Joshua Primas Date: Fri, 20 Feb 2026 16:13:44 -0800 Subject: [PATCH 0590/1060] Added changelog --- changelog/3791.added.md | 1 + 1 file changed, 1 insertion(+) create mode 100644 changelog/3791.added.md diff --git a/changelog/3791.added.md b/changelog/3791.added.md new file mode 100644 index 000000000..89767de5e --- /dev/null +++ b/changelog/3791.added.md @@ -0,0 +1 @@ +- Added `LemonSliceTransport` and `LemonSliceApi` to support adding real-time LemonSlice Avatars to any Daily room. \ No newline at end of file From abb20f34ba8eb36fec9d96c22f183093b626da1b Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Aleix=20Conchillo=20Flaqu=C3=A9?= Date: Fri, 20 Feb 2026 16:17:51 -0800 Subject: [PATCH 0591/1060] Update default Anthropic model to claude-sonnet-4-6 Update the default model in AnthropicLLMService and remove the now-unnecessary explicit model from the function calling example. --- examples/foundational/14a-function-calling-anthropic.py | 5 +---- src/pipecat/services/anthropic/llm.py | 4 ++-- 2 files changed, 3 insertions(+), 6 deletions(-) diff --git a/examples/foundational/14a-function-calling-anthropic.py b/examples/foundational/14a-function-calling-anthropic.py index 165d4b220..36030bc2b 100644 --- a/examples/foundational/14a-function-calling-anthropic.py +++ b/examples/foundational/14a-function-calling-anthropic.py @@ -72,10 +72,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): voice_id="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady ) - llm = AnthropicLLMService( - api_key=os.getenv("ANTHROPIC_API_KEY"), - model="claude-3-7-sonnet-latest", - ) + llm = AnthropicLLMService(api_key=os.getenv("ANTHROPIC_API_KEY")) llm.register_function("get_weather", get_weather) llm.register_function("get_restaurant_recommendation", fetch_restaurant_recommendation) diff --git a/src/pipecat/services/anthropic/llm.py b/src/pipecat/services/anthropic/llm.py index a21296fe3..e715c242d 100644 --- a/src/pipecat/services/anthropic/llm.py +++ b/src/pipecat/services/anthropic/llm.py @@ -184,7 +184,7 @@ class AnthropicLLMService(LLMService): self, *, api_key: str, - model: str = "claude-sonnet-4-5-20250929", + model: str = "claude-sonnet-4-6", params: Optional[InputParams] = None, client=None, retry_timeout_secs: Optional[float] = 5.0, @@ -195,7 +195,7 @@ class AnthropicLLMService(LLMService): Args: api_key: Anthropic API key for authentication. - model: Model name to use. Defaults to "claude-sonnet-4-5-20250929". + model: Model name to use. Defaults to "claude-sonnet-4-6". params: Optional model parameters for inference. client: Optional custom Anthropic client instance. retry_timeout_secs: Request timeout in seconds for retry logic. From 521f669051b29da4b312a87d07a59165513aa9d5 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Aleix=20Conchillo=20Flaqu=C3=A9?= Date: Fri, 20 Feb 2026 16:18:21 -0800 Subject: [PATCH 0592/1060] Add changelog entries for PR #3792 --- changelog/3792.changed.md | 1 + 1 file changed, 1 insertion(+) create mode 100644 changelog/3792.changed.md diff --git a/changelog/3792.changed.md b/changelog/3792.changed.md new file mode 100644 index 000000000..ddf7fdc1e --- /dev/null +++ b/changelog/3792.changed.md @@ -0,0 +1 @@ +- Updated default Anthropic model from `claude-sonnet-4-5-20250929` to `claude-sonnet-4-6`. From 18429f80f1c289e47efbe5fec54d4f8ce908a322 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Aleix=20Conchillo=20Flaqu=C3=A9?= Date: Fri, 20 Feb 2026 16:32:40 -0800 Subject: [PATCH 0593/1060] github(changelog): allow performance type --- .github/workflows/generate-changelog.yml | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/.github/workflows/generate-changelog.yml b/.github/workflows/generate-changelog.yml index 005eb94f1..496b3381c 100644 --- a/.github/workflows/generate-changelog.yml +++ b/.github/workflows/generate-changelog.yml @@ -86,7 +86,7 @@ jobs: fi # Validate fragment types - VALID_TYPES="added changed deprecated removed fixed security other" + VALID_TYPES="added changed deprecated removed fixed performance security other" INVALID_FRAGMENTS="" for file in changelog/*.md; do From 6d9c07b9458b8127ea9420250cbc956de977aab4 Mon Sep 17 00:00:00 2001 From: aconchillo <951761+aconchillo@users.noreply.github.com> Date: Sat, 21 Feb 2026 00:33:43 +0000 Subject: [PATCH 0594/1060] Update changelog for version 0.0.103 --- CHANGELOG.md | 209 +++++++++++++++++++++++++++++++++++ changelog/3615.fixed.md | 1 - changelog/3625.added.md | 1 - changelog/3642.added.md | 1 - changelog/3642.changed.md | 1 - changelog/3684.changed.md | 3 - changelog/3698.fixed.md | 1 - changelog/3706.changed.md | 1 - changelog/3713.fixed.md | 1 - changelog/3718.fixed.md | 1 - changelog/3719.added.2.md | 1 - changelog/3719.added.md | 1 - changelog/3719.changed.md | 1 - changelog/3720.fixed.md | 1 - changelog/3728.changed.md | 1 - changelog/3729.fixed.2.md | 1 - changelog/3729.fixed.md | 1 - changelog/3730.added.md | 1 - changelog/3730.changed.md | 1 - changelog/3732.changed.md | 3 - changelog/3733.deprecated.md | 1 - changelog/3735.fixed.md | 1 - changelog/3737.fixed.md | 1 - changelog/3744.fixed.md | 1 - changelog/3748.added.md | 1 - changelog/3748.changed.md | 1 - changelog/3761.changed.md | 1 - changelog/3765.changed.md | 1 - changelog/3768.fixed.md | 1 - changelog/3774.added.md | 1 - changelog/3774.fixed.md | 1 - changelog/3776.changed.md | 1 - changelog/3779.added.md | 1 - changelog/3782.fixed.md | 1 - changelog/3784.fixed.md | 1 - changelog/3785.added.md | 1 - changelog/3787.fixed.md | 1 - changelog/3789.fixed.md | 1 - changelog/3792.changed.md | 1 - 39 files changed, 209 insertions(+), 42 deletions(-) delete mode 100644 changelog/3615.fixed.md delete mode 100644 changelog/3625.added.md delete mode 100644 changelog/3642.added.md delete mode 100644 changelog/3642.changed.md delete mode 100644 changelog/3684.changed.md delete mode 100644 changelog/3698.fixed.md delete mode 100644 changelog/3706.changed.md delete mode 100644 changelog/3713.fixed.md delete mode 100644 changelog/3718.fixed.md delete mode 100644 changelog/3719.added.2.md delete mode 100644 changelog/3719.added.md delete mode 100644 changelog/3719.changed.md delete mode 100644 changelog/3720.fixed.md delete mode 100644 changelog/3728.changed.md delete mode 100644 changelog/3729.fixed.2.md delete mode 100644 changelog/3729.fixed.md delete mode 100644 changelog/3730.added.md delete mode 100644 changelog/3730.changed.md delete mode 100644 changelog/3732.changed.md delete mode 100644 changelog/3733.deprecated.md delete mode 100644 changelog/3735.fixed.md delete mode 100644 changelog/3737.fixed.md delete mode 100644 changelog/3744.fixed.md delete mode 100644 changelog/3748.added.md delete mode 100644 changelog/3748.changed.md delete mode 100644 changelog/3761.changed.md delete mode 100644 changelog/3765.changed.md delete mode 100644 changelog/3768.fixed.md delete mode 100644 changelog/3774.added.md delete mode 100644 changelog/3774.fixed.md delete mode 100644 changelog/3776.changed.md delete mode 100644 changelog/3779.added.md delete mode 100644 changelog/3782.fixed.md delete mode 100644 changelog/3784.fixed.md delete mode 100644 changelog/3785.added.md delete mode 100644 changelog/3787.fixed.md delete mode 100644 changelog/3789.fixed.md delete mode 100644 changelog/3792.changed.md diff --git a/CHANGELOG.md b/CHANGELOG.md index ab41e8163..c917ec992 100644 --- a/CHANGELOG.md +++ b/CHANGELOG.md @@ -7,6 +7,215 @@ and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0 +## [0.0.103] - 2026-02-20 + +### Added + +- Added `"timestampTransportStrategy": "ASYNC"` to `InworldAITTSService`. This + allows timestamps info to trail audio chunks arrival, resulting in much + better first audio chunk latency + (PR [#3625](https://github.com/pipecat-ai/pipecat/pull/3625)) + +- Added model-specific `InputParams` to `RimeTTSService`: arcana params + (`repetition_penalty`, `temperature`, `top_p`) and mistv2 params + (`no_text_normalization`, `save_oovs`, `segment`). Model, voice, and param + changes now trigger WebSocket reconnection. + (PR [#3642](https://github.com/pipecat-ai/pipecat/pull/3642)) + +- Added `write_transport_frame()` hook to `BaseOutputTransport` allowing + transport subclasses to handle custom frame types that flow through the audio + queue. + (PR [#3719](https://github.com/pipecat-ai/pipecat/pull/3719)) + +- Added `DailySIPTransferFrame` and `DailySIPReferFrame` to the Daily + transport. These frames queue SIP transfer and SIP REFER operations with + audio, so the operation executes only after the bot finishes its current + utterance. + (PR [#3719](https://github.com/pipecat-ai/pipecat/pull/3719)) + +- Added keepalive support to `SarvamSTTService` to prevent idle connection + timeouts (e.g. when used behind a `ServiceSwitcher`). + (PR [#3730](https://github.com/pipecat-ai/pipecat/pull/3730)) + +- Added `UserIdleTimeoutUpdateFrame` to enable or disable user idle detection + at runtime by updating the timeout dynamically. + (PR [#3748](https://github.com/pipecat-ai/pipecat/pull/3748)) + +- Added `broadcast_sibling_id` field to the base `Frame` class. This field is + automatically set by `broadcast_frame()` and `broadcast_frame_instance()` to + the ID of the paired frame pushed in the opposite direction, allowing + receivers to identify broadcast pairs. + (PR [#3774](https://github.com/pipecat-ai/pipecat/pull/3774)) + +- Added `ignored_sources` parameter to `RTVIObserverParams` and + `add_ignored_source()`/`remove_ignored_source()` methods to `RTVIObserver` to + suppress RTVI messages from specific pipeline processors (e.g. a silent + evaluation LLM). + (PR [#3779](https://github.com/pipecat-ai/pipecat/pull/3779)) + +- Added `DeepgramSageMakerTTSService` for running Deepgram TTS models deployed + on AWS SageMaker endpoints via HTTP/2 bidirectional streaming. Supports the + Deepgram TTS protocol (Speak, Flush, Clear, Close), interruption handling, + and per-turn TTFB metrics. + (PR [#3785](https://github.com/pipecat-ai/pipecat/pull/3785)) + +### Changed + +- ⚠️ `RimeTTSService` now defaults to `model="arcana"` and the + `wss://users-ws.rime.ai/ws3` endpoint. `InputParams` defaults changed from + mistv2-specific values to `None` — only explicitly-set params are sent as + query params. + (PR [#3642](https://github.com/pipecat-ai/pipecat/pull/3642)) + +- `AICFilter` now shares read-only AIC models via a singleton `AICModelManager` + in `aic_filter.py`. + - Multiple filters using the same model path or `(model_id, + model_download_dir)` share one loaded model, with reference counting and + concurrent load deduplication. + - Model file I/O runs off the event loop so the filter does not block. + (PR [#3684](https://github.com/pipecat-ai/pipecat/pull/3684)) + +- Added `X-User-Agent` and `X-Request-Id` headers to `InworldTTSService` for + better traceability. + (PR [#3706](https://github.com/pipecat-ai/pipecat/pull/3706)) + +- `DailyUpdateRemoteParticipantsFrame` is no longer deprecated and is now + queued with audio like other transport frames. + (PR [#3719](https://github.com/pipecat-ai/pipecat/pull/3719)) + +- Bumped Pillow dependency upper bound from `<12` to `<13` to allow Pillow + 12.x. + (PR [#3728](https://github.com/pipecat-ai/pipecat/pull/3728)) + +- Moved STT keepalive mechanism from `WebsocketSTTService` to the `STTService` + base class, allowing any STT service (not just websocket-based ones) to use + idle-connection keepalive via the `keepalive_timeout` and + `keepalive_interval` parameters. + (PR [#3730](https://github.com/pipecat-ai/pipecat/pull/3730)) + +- Improved audio context management in `AudioContextTTSService` by moving + context ID tracking to the base class and adding + `reuse_context_id_within_turn` parameter to control concurrent TTS request + handling. + - Added helper methods: `has_active_audio_context()`, + `get_active_audio_context_id()`, `remove_active_audio_context()`, + `reset_active_audio_context()` + - Simplified Cartesia, ElevenLabs, Inworld, Rime, AsyncAI, and Gradium TTS + implementations by removing duplicate context management code + (PR [#3732](https://github.com/pipecat-ai/pipecat/pull/3732)) + +- `UserIdleController` is now always created with a default timeout of 0 + (disabled). The `user_idle_timeout` parameter changed from `Optional[float] = + None` to `float = 0` in `UserTurnProcessor`, `LLMUserAggregatorParams`, and + `UserIdleController`. + (PR [#3748](https://github.com/pipecat-ai/pipecat/pull/3748)) + +- Change the version specifier from `>=0.2.8` to `~=0.2.8` for the + `speechmatics-voice` package to ensure compatibility with future patch + versions. + (PR [#3761](https://github.com/pipecat-ai/pipecat/pull/3761)) + +- Updated `InworldTTSService` and `InworldHttpTTSService` to use `ASYNC` + timestamp transport strategy by default + (PR [#3765](https://github.com/pipecat-ai/pipecat/pull/3765)) + +- Added `start_time` and `end_time` parameters to `start_ttfb_metrics()`, + `stop_ttfb_metrics()`, `start_processing_metrics()`, and + `stop_processing_metrics()` in `FrameProcessor` and `FrameProcessorMetrics`, + allowing custom timestamps for metrics measurement. `STTService` now uses + these instead of custom TTFB tracking. + (PR [#3776](https://github.com/pipecat-ai/pipecat/pull/3776)) + +- Updated default Anthropic model from `claude-sonnet-4-5-20250929` to + `claude-sonnet-4-6`. + (PR [#3792](https://github.com/pipecat-ai/pipecat/pull/3792)) + +### Deprecated + +- Deprecated unused `Traceable`, `@traceable`, `@traced`, and + `AttachmentStrategy` in `pipecat.utils.tracing.class_decorators`. This module + will be removed in a future release. + (PR [#3733](https://github.com/pipecat-ai/pipecat/pull/3733)) + +### Fixed + +- Fixed race condition where `RTVIObserver` could send messages before + `DailyTransport` join completed. Outbound messages are now queued & delivered + after the transport is ready. + (PR [#3615](https://github.com/pipecat-ai/pipecat/pull/3615)) + +- Fixed async generator cleanup in OpenAI LLM streaming to prevent + `AttributeError` with uvloop on Python 3.12+ (MagicStack/uvloop#699). + (PR [#3698](https://github.com/pipecat-ai/pipecat/pull/3698)) + +- Fixed `SmallWebRTCTransport` input audio resampling to properly handle all + sample rates, including 8kHz audio. + (PR [#3713](https://github.com/pipecat-ai/pipecat/pull/3713)) + +- Fixed a race condition in `RTVIObserver` where bot output messages could be + sent before the bot-started-speaking event. + (PR [#3718](https://github.com/pipecat-ai/pipecat/pull/3718)) + +- Fixed Grok Realtime `session.updated` event parsing failure caused by the API + returning prefixed voice names (e.g. `"human_Ara"` instead of `"Ara"`). + (PR [#3720](https://github.com/pipecat-ai/pipecat/pull/3720)) + +- Fixed context ID reuse issue in `ElevenLabsTTSService`, `InworldTTSService`, + `RimeTTSService`, `CartesiaTTSService`, `AsyncAITTSService`, and + `PlayHTTTSService`. Services now properly reuse the same context ID across + multiple `run_tts()` invocations within a single LLM turn, preventing context + tracking issues and incorrect lifecycle signaling. + (PR [#3729](https://github.com/pipecat-ai/pipecat/pull/3729)) + +- Fixed word timestamp interleaving issue in `ElevenLabsTTSService` when + processing multiple sentences within a single LLM turn. + (PR [#3729](https://github.com/pipecat-ai/pipecat/pull/3729)) + +- Fixed tracing service decorators executing the wrapped function twice when + the function itself raised an exception (e.g., LLM rate limit, TTS timeout). + (PR [#3735](https://github.com/pipecat-ai/pipecat/pull/3735)) + +- Fixed `LLMUserAggregator` broadcasting mute events before `StartFrame` + reaches downstream processors. + (PR [#3737](https://github.com/pipecat-ai/pipecat/pull/3737)) + +- Fixed `UserIdleController` false idle triggers caused by gaps between user + and bot activity frames. The idle timer now starts only after + `BotStoppedSpeakingFrame` and is suppressed during active user turns and + function calls. + (PR [#3744](https://github.com/pipecat-ai/pipecat/pull/3744)) + +- Fixed incorrect `sample_rate` assignment in + `TavusInputTransport._on_participant_audio_data` (was using + `audio.audio_frames` instead of `audio.sample_rate`). + (PR [#3768](https://github.com/pipecat-ai/pipecat/pull/3768)) + +- Fixed `RTVIObserver` not processing upstream-only frames. Previously, all + upstream frames were filtered out to avoid duplicate messages from + broadcasted frames. Now only upstream copies of broadcasted frames are + skipped. + (PR [#3774](https://github.com/pipecat-ai/pipecat/pull/3774)) + +- Fixed mutable default arguments in `LLMContextAggregatorPair.__init__()` that + could cause shared state across instances. + (PR [#3782](https://github.com/pipecat-ai/pipecat/pull/3782)) + +- Fixed `DeepgramSageMakerSTTService` to properly track finalize lifecycle + using `request_finalize()` / `confirm_finalize()` and use `is_final` (instead + of `is_final and speech_final`) for final transcription detection, matching + `DeepgramSTTService` behavior. + (PR [#3784](https://github.com/pipecat-ai/pipecat/pull/3784)) + +- Fixed a race condition in `AudioContextTTSService` where the audio context + could time out between consecutive TTS requests within the same turn, causing + audio to be discarded. + (PR [#3787](https://github.com/pipecat-ai/pipecat/pull/3787)) + +- Fixed `push_interruption_task_frame_and_wait()` hanging indefinitely when the + `InterruptionFrame` does not reach the pipeline sink within the timeout. + Added a `timeout` keyword argument to customize the wait duration. + (PR [#3789](https://github.com/pipecat-ai/pipecat/pull/3789)) + ## [0.0.102] - 2026-02-10 ### Added diff --git a/changelog/3615.fixed.md b/changelog/3615.fixed.md deleted file mode 100644 index b14dfd70f..000000000 --- a/changelog/3615.fixed.md +++ /dev/null @@ -1 +0,0 @@ -- Fixed race condition where `RTVIObserver` could send messages before `DailyTransport` join completed. Outbound messages are now queued & delivered after the transport is ready. diff --git a/changelog/3625.added.md b/changelog/3625.added.md deleted file mode 100644 index ddf787567..000000000 --- a/changelog/3625.added.md +++ /dev/null @@ -1 +0,0 @@ -- Added `"timestampTransportStrategy": "ASYNC"` to `InworldAITTSService`. This allows timestamps info to trail audio chunks arrival, resulting in much better first audio chunk latency diff --git a/changelog/3642.added.md b/changelog/3642.added.md deleted file mode 100644 index 47668bf59..000000000 --- a/changelog/3642.added.md +++ /dev/null @@ -1 +0,0 @@ -- Added model-specific `InputParams` to `RimeTTSService`: arcana params (`repetition_penalty`, `temperature`, `top_p`) and mistv2 params (`no_text_normalization`, `save_oovs`, `segment`). Model, voice, and param changes now trigger WebSocket reconnection. diff --git a/changelog/3642.changed.md b/changelog/3642.changed.md deleted file mode 100644 index 96a43fbb8..000000000 --- a/changelog/3642.changed.md +++ /dev/null @@ -1 +0,0 @@ -- ⚠️ `RimeTTSService` now defaults to `model="arcana"` and the `wss://users-ws.rime.ai/ws3` endpoint. `InputParams` defaults changed from mistv2-specific values to `None` — only explicitly-set params are sent as query params. diff --git a/changelog/3684.changed.md b/changelog/3684.changed.md deleted file mode 100644 index 1bdb2c89c..000000000 --- a/changelog/3684.changed.md +++ /dev/null @@ -1,3 +0,0 @@ -- `AICFilter` now shares read-only AIC models via a singleton `AICModelManager` in `aic_filter.py`. - - Multiple filters using the same model path or `(model_id, model_download_dir)` share one loaded model, with reference counting and concurrent load deduplication. - - Model file I/O runs off the event loop so the filter does not block. diff --git a/changelog/3698.fixed.md b/changelog/3698.fixed.md deleted file mode 100644 index c040e9efb..000000000 --- a/changelog/3698.fixed.md +++ /dev/null @@ -1 +0,0 @@ -- Fixed async generator cleanup in OpenAI LLM streaming to prevent `AttributeError` with uvloop on Python 3.12+ (MagicStack/uvloop#699). diff --git a/changelog/3706.changed.md b/changelog/3706.changed.md deleted file mode 100644 index 0c9876bdc..000000000 --- a/changelog/3706.changed.md +++ /dev/null @@ -1 +0,0 @@ -- Added `X-User-Agent` and `X-Request-Id` headers to `InworldTTSService` for better traceability. diff --git a/changelog/3713.fixed.md b/changelog/3713.fixed.md deleted file mode 100644 index 241f0e56a..000000000 --- a/changelog/3713.fixed.md +++ /dev/null @@ -1 +0,0 @@ -- Fixed `SmallWebRTCTransport` input audio resampling to properly handle all sample rates, including 8kHz audio. diff --git a/changelog/3718.fixed.md b/changelog/3718.fixed.md deleted file mode 100644 index 68e1d2682..000000000 --- a/changelog/3718.fixed.md +++ /dev/null @@ -1 +0,0 @@ -- Fixed a race condition in `RTVIObserver` where bot output messages could be sent before the bot-started-speaking event. diff --git a/changelog/3719.added.2.md b/changelog/3719.added.2.md deleted file mode 100644 index 77d8956d7..000000000 --- a/changelog/3719.added.2.md +++ /dev/null @@ -1 +0,0 @@ -- Added `write_transport_frame()` hook to `BaseOutputTransport` allowing transport subclasses to handle custom frame types that flow through the audio queue. diff --git a/changelog/3719.added.md b/changelog/3719.added.md deleted file mode 100644 index bc1c2d6b1..000000000 --- a/changelog/3719.added.md +++ /dev/null @@ -1 +0,0 @@ -- Added `DailySIPTransferFrame` and `DailySIPReferFrame` to the Daily transport. These frames queue SIP transfer and SIP REFER operations with audio, so the operation executes only after the bot finishes its current utterance. diff --git a/changelog/3719.changed.md b/changelog/3719.changed.md deleted file mode 100644 index f42d0303b..000000000 --- a/changelog/3719.changed.md +++ /dev/null @@ -1 +0,0 @@ -- `DailyUpdateRemoteParticipantsFrame` is no longer deprecated and is now queued with audio like other transport frames. diff --git a/changelog/3720.fixed.md b/changelog/3720.fixed.md deleted file mode 100644 index c3cb69d34..000000000 --- a/changelog/3720.fixed.md +++ /dev/null @@ -1 +0,0 @@ -- Fixed Grok Realtime `session.updated` event parsing failure caused by the API returning prefixed voice names (e.g. `"human_Ara"` instead of `"Ara"`). diff --git a/changelog/3728.changed.md b/changelog/3728.changed.md deleted file mode 100644 index bc5ccc74d..000000000 --- a/changelog/3728.changed.md +++ /dev/null @@ -1 +0,0 @@ -- Bumped Pillow dependency upper bound from `<12` to `<13` to allow Pillow 12.x. diff --git a/changelog/3729.fixed.2.md b/changelog/3729.fixed.2.md deleted file mode 100644 index 6d4f33d93..000000000 --- a/changelog/3729.fixed.2.md +++ /dev/null @@ -1 +0,0 @@ -- Fixed context ID reuse issue in `ElevenLabsTTSService`, `InworldTTSService`, `RimeTTSService`, `CartesiaTTSService`, `AsyncAITTSService`, and `PlayHTTTSService`. Services now properly reuse the same context ID across multiple `run_tts()` invocations within a single LLM turn, preventing context tracking issues and incorrect lifecycle signaling. diff --git a/changelog/3729.fixed.md b/changelog/3729.fixed.md deleted file mode 100644 index b8be759fb..000000000 --- a/changelog/3729.fixed.md +++ /dev/null @@ -1 +0,0 @@ -- Fixed word timestamp interleaving issue in `ElevenLabsTTSService` when processing multiple sentences within a single LLM turn. diff --git a/changelog/3730.added.md b/changelog/3730.added.md deleted file mode 100644 index e3ac64278..000000000 --- a/changelog/3730.added.md +++ /dev/null @@ -1 +0,0 @@ -- Added keepalive support to `SarvamSTTService` to prevent idle connection timeouts (e.g. when used behind a `ServiceSwitcher`). diff --git a/changelog/3730.changed.md b/changelog/3730.changed.md deleted file mode 100644 index 697bc863c..000000000 --- a/changelog/3730.changed.md +++ /dev/null @@ -1 +0,0 @@ -- Moved STT keepalive mechanism from `WebsocketSTTService` to the `STTService` base class, allowing any STT service (not just websocket-based ones) to use idle-connection keepalive via the `keepalive_timeout` and `keepalive_interval` parameters. diff --git a/changelog/3732.changed.md b/changelog/3732.changed.md deleted file mode 100644 index 22681cf04..000000000 --- a/changelog/3732.changed.md +++ /dev/null @@ -1,3 +0,0 @@ -- Improved audio context management in `AudioContextTTSService` by moving context ID tracking to the base class and adding `reuse_context_id_within_turn` parameter to control concurrent TTS request handling. - - Added helper methods: `has_active_audio_context()`, `get_active_audio_context_id()`, `remove_active_audio_context()`, `reset_active_audio_context()` - - Simplified Cartesia, ElevenLabs, Inworld, Rime, AsyncAI, and Gradium TTS implementations by removing duplicate context management code diff --git a/changelog/3733.deprecated.md b/changelog/3733.deprecated.md deleted file mode 100644 index 8b1fb29bb..000000000 --- a/changelog/3733.deprecated.md +++ /dev/null @@ -1 +0,0 @@ -- Deprecated unused `Traceable`, `@traceable`, `@traced`, and `AttachmentStrategy` in `pipecat.utils.tracing.class_decorators`. This module will be removed in a future release. diff --git a/changelog/3735.fixed.md b/changelog/3735.fixed.md deleted file mode 100644 index 02de936c7..000000000 --- a/changelog/3735.fixed.md +++ /dev/null @@ -1 +0,0 @@ -- Fixed tracing service decorators executing the wrapped function twice when the function itself raised an exception (e.g., LLM rate limit, TTS timeout). diff --git a/changelog/3737.fixed.md b/changelog/3737.fixed.md deleted file mode 100644 index 6dee96f82..000000000 --- a/changelog/3737.fixed.md +++ /dev/null @@ -1 +0,0 @@ -- Fixed `LLMUserAggregator` broadcasting mute events before `StartFrame` reaches downstream processors. diff --git a/changelog/3744.fixed.md b/changelog/3744.fixed.md deleted file mode 100644 index d2b3f665f..000000000 --- a/changelog/3744.fixed.md +++ /dev/null @@ -1 +0,0 @@ -- Fixed `UserIdleController` false idle triggers caused by gaps between user and bot activity frames. The idle timer now starts only after `BotStoppedSpeakingFrame` and is suppressed during active user turns and function calls. diff --git a/changelog/3748.added.md b/changelog/3748.added.md deleted file mode 100644 index 223f8bf4b..000000000 --- a/changelog/3748.added.md +++ /dev/null @@ -1 +0,0 @@ -- Added `UserIdleTimeoutUpdateFrame` to enable or disable user idle detection at runtime by updating the timeout dynamically. diff --git a/changelog/3748.changed.md b/changelog/3748.changed.md deleted file mode 100644 index 61be61c6b..000000000 --- a/changelog/3748.changed.md +++ /dev/null @@ -1 +0,0 @@ -- `UserIdleController` is now always created with a default timeout of 0 (disabled). The `user_idle_timeout` parameter changed from `Optional[float] = None` to `float = 0` in `UserTurnProcessor`, `LLMUserAggregatorParams`, and `UserIdleController`. diff --git a/changelog/3761.changed.md b/changelog/3761.changed.md deleted file mode 100644 index 71618502c..000000000 --- a/changelog/3761.changed.md +++ /dev/null @@ -1 +0,0 @@ -- Change the version specifier from `>=0.2.8` to `~=0.2.8` for the `speechmatics-voice` package to ensure compatibility with future patch versions. diff --git a/changelog/3765.changed.md b/changelog/3765.changed.md deleted file mode 100644 index 5d3e758d5..000000000 --- a/changelog/3765.changed.md +++ /dev/null @@ -1 +0,0 @@ -- Updated `InworldTTSService` and `InworldHttpTTSService` to use `ASYNC` timestamp transport strategy by default diff --git a/changelog/3768.fixed.md b/changelog/3768.fixed.md deleted file mode 100644 index 4c8d6438e..000000000 --- a/changelog/3768.fixed.md +++ /dev/null @@ -1 +0,0 @@ -- Fixed incorrect `sample_rate` assignment in `TavusInputTransport._on_participant_audio_data` (was using `audio.audio_frames` instead of `audio.sample_rate`). diff --git a/changelog/3774.added.md b/changelog/3774.added.md deleted file mode 100644 index e72599e60..000000000 --- a/changelog/3774.added.md +++ /dev/null @@ -1 +0,0 @@ -- Added `broadcast_sibling_id` field to the base `Frame` class. This field is automatically set by `broadcast_frame()` and `broadcast_frame_instance()` to the ID of the paired frame pushed in the opposite direction, allowing receivers to identify broadcast pairs. diff --git a/changelog/3774.fixed.md b/changelog/3774.fixed.md deleted file mode 100644 index a839f56ed..000000000 --- a/changelog/3774.fixed.md +++ /dev/null @@ -1 +0,0 @@ -- Fixed `RTVIObserver` not processing upstream-only frames. Previously, all upstream frames were filtered out to avoid duplicate messages from broadcasted frames. Now only upstream copies of broadcasted frames are skipped. diff --git a/changelog/3776.changed.md b/changelog/3776.changed.md deleted file mode 100644 index 87b5d6128..000000000 --- a/changelog/3776.changed.md +++ /dev/null @@ -1 +0,0 @@ -- Added `start_time` and `end_time` parameters to `start_ttfb_metrics()`, `stop_ttfb_metrics()`, `start_processing_metrics()`, and `stop_processing_metrics()` in `FrameProcessor` and `FrameProcessorMetrics`, allowing custom timestamps for metrics measurement. `STTService` now uses these instead of custom TTFB tracking. diff --git a/changelog/3779.added.md b/changelog/3779.added.md deleted file mode 100644 index 8800cfc04..000000000 --- a/changelog/3779.added.md +++ /dev/null @@ -1 +0,0 @@ -- Added `ignored_sources` parameter to `RTVIObserverParams` and `add_ignored_source()`/`remove_ignored_source()` methods to `RTVIObserver` to suppress RTVI messages from specific pipeline processors (e.g. a silent evaluation LLM). diff --git a/changelog/3782.fixed.md b/changelog/3782.fixed.md deleted file mode 100644 index 7d21fdeab..000000000 --- a/changelog/3782.fixed.md +++ /dev/null @@ -1 +0,0 @@ -- Fixed mutable default arguments in `LLMContextAggregatorPair.__init__()` that could cause shared state across instances. diff --git a/changelog/3784.fixed.md b/changelog/3784.fixed.md deleted file mode 100644 index e88431f16..000000000 --- a/changelog/3784.fixed.md +++ /dev/null @@ -1 +0,0 @@ -- Fixed `DeepgramSageMakerSTTService` to properly track finalize lifecycle using `request_finalize()` / `confirm_finalize()` and use `is_final` (instead of `is_final and speech_final`) for final transcription detection, matching `DeepgramSTTService` behavior. diff --git a/changelog/3785.added.md b/changelog/3785.added.md deleted file mode 100644 index 90a4172d4..000000000 --- a/changelog/3785.added.md +++ /dev/null @@ -1 +0,0 @@ -- Added `DeepgramSageMakerTTSService` for running Deepgram TTS models deployed on AWS SageMaker endpoints via HTTP/2 bidirectional streaming. Supports the Deepgram TTS protocol (Speak, Flush, Clear, Close), interruption handling, and per-turn TTFB metrics. diff --git a/changelog/3787.fixed.md b/changelog/3787.fixed.md deleted file mode 100644 index ff11ada71..000000000 --- a/changelog/3787.fixed.md +++ /dev/null @@ -1 +0,0 @@ -- Fixed a race condition in `AudioContextTTSService` where the audio context could time out between consecutive TTS requests within the same turn, causing audio to be discarded. diff --git a/changelog/3789.fixed.md b/changelog/3789.fixed.md deleted file mode 100644 index 1bf2be1a3..000000000 --- a/changelog/3789.fixed.md +++ /dev/null @@ -1 +0,0 @@ -- Fixed `push_interruption_task_frame_and_wait()` hanging indefinitely when the `InterruptionFrame` does not reach the pipeline sink within the timeout. Added a `timeout` keyword argument to customize the wait duration. diff --git a/changelog/3792.changed.md b/changelog/3792.changed.md deleted file mode 100644 index ddf7fdc1e..000000000 --- a/changelog/3792.changed.md +++ /dev/null @@ -1 +0,0 @@ -- Updated default Anthropic model from `claude-sonnet-4-5-20250929` to `claude-sonnet-4-6`. From f49658de15199f63b803c8ed50ceaef7aa172dc7 Mon Sep 17 00:00:00 2001 From: Om Chauhan Date: Sat, 21 Feb 2026 17:06:54 +0530 Subject: [PATCH 0595/1060] skipping provider-specific messages during summarization --- .../context/llm_context_summarization.py | 18 ++++- tests/test_context_summarization.py | 74 ++++++++++++++++++- 2 files changed, 89 insertions(+), 3 deletions(-) diff --git a/src/pipecat/utils/context/llm_context_summarization.py b/src/pipecat/utils/context/llm_context_summarization.py index 6865a00d9..06551e3bb 100644 --- a/src/pipecat/utils/context/llm_context_summarization.py +++ b/src/pipecat/utils/context/llm_context_summarization.py @@ -15,7 +15,7 @@ from typing import List, Optional from loguru import logger -from pipecat.processors.aggregators.llm_context import LLMContext +from pipecat.processors.aggregators.llm_context import LLMContext, LLMSpecificMessage # Token estimation constants CHARS_PER_TOKEN = 4 # Industry-standard heuristic: 1 token ≈ 4 characters @@ -188,6 +188,9 @@ class LLMContextSummarizationUtil: total = 0 for message in context.messages: + if isinstance(message, LLMSpecificMessage): + continue + # Role and structure overhead total += TOKEN_OVERHEAD_PER_MESSAGE @@ -248,6 +251,9 @@ class LLMContextSummarizationUtil: for i in range(start_idx, len(messages)): msg = messages[i] + if isinstance(msg, LLMSpecificMessage): + continue + role = msg.get("role") # Check for tool calls in assistant messages @@ -298,7 +304,12 @@ class LLMContextSummarizationUtil: # Find first system message index first_system_index = next( - (i for i, msg in enumerate(messages) if msg.get("role") == "system"), -1 + ( + i + for i, msg in enumerate(messages) + if not isinstance(msg, LLMSpecificMessage) and msg.get("role") == "system" + ), + -1, ) # Messages to summarize are between first system and recent messages @@ -356,6 +367,9 @@ class LLMContextSummarizationUtil: transcript_parts = [] for msg in messages: + if isinstance(msg, LLMSpecificMessage): + continue + role = msg.get("role", "unknown") content = msg.get("content", "") diff --git a/tests/test_context_summarization.py b/tests/test_context_summarization.py index 87aaa74d3..36559ed3f 100644 --- a/tests/test_context_summarization.py +++ b/tests/test_context_summarization.py @@ -10,7 +10,7 @@ import unittest from unittest.mock import AsyncMock, MagicMock, patch from pipecat.frames.frames import LLMContextSummaryRequestFrame -from pipecat.processors.aggregators.llm_context import LLMContext +from pipecat.processors.aggregators.llm_context import LLMContext, LLMSpecificMessage from pipecat.services.llm_service import LLMService from pipecat.utils.context.llm_context_summarization import ( LLMContextSummarizationConfig, @@ -602,5 +602,77 @@ class TestSummaryGenerationExceptions(unittest.IsolatedAsyncioTestCase): self.assertEqual(last_index, 1) # Should be the index of the last summarized message +class TestLLMSpecificMessageHandling(unittest.TestCase): + """Tests that LLMSpecificMessage objects are correctly skipped in summarization.""" + + def test_estimate_context_tokens_skips_specific_messages(self): + """Test that estimate_context_tokens skips LLMSpecificMessage objects.""" + context = LLMContext() + context.add_message({"role": "user", "content": "Hello"}) + context.add_message(LLMSpecificMessage(llm="google", message={})) + context.add_message({"role": "assistant", "content": "Hi there"}) + + tokens_with_specific = LLMContextSummarizationUtil.estimate_context_tokens(context) + + context_without = LLMContext() + context_without.add_message({"role": "user", "content": "Hello"}) + context_without.add_message({"role": "assistant", "content": "Hi there"}) + tokens_without = LLMContextSummarizationUtil.estimate_context_tokens(context_without) + + self.assertEqual(tokens_with_specific, tokens_without) + + def test_get_messages_to_summarize_with_specific_messages(self): + """Test that get_messages_to_summarize handles LLMSpecificMessage objects.""" + context = LLMContext() + context.add_message({"role": "system", "content": "System prompt"}) + context.add_message(LLMSpecificMessage(llm="google", message={})) + context.add_message({"role": "user", "content": "Message 1"}) + context.add_message({"role": "assistant", "content": "Response 1"}) + context.add_message(LLMSpecificMessage(llm="google", message={})) + context.add_message({"role": "user", "content": "Message 2"}) + context.add_message({"role": "assistant", "content": "Response 2"}) + + result = LLMContextSummarizationUtil.get_messages_to_summarize(context, 2) + + self.assertGreater(len(result.messages), 0) + self.assertGreater(result.last_summarized_index, 0) + + def test_format_messages_skips_specific_messages(self): + """Test that format_messages_for_summary skips LLMSpecificMessage objects.""" + messages = [ + {"role": "user", "content": "Hello"}, + LLMSpecificMessage(llm="google", message={}), + {"role": "assistant", "content": "Hi there"}, + ] + + transcript = LLMContextSummarizationUtil.format_messages_for_summary(messages) + + self.assertIn("USER: Hello", transcript) + self.assertIn("ASSISTANT: Hi there", transcript) + + def test_function_call_tracking_skips_specific_messages(self): + """Test that _get_function_calls_in_progress_index skips LLMSpecificMessage.""" + messages = [ + {"role": "user", "content": "What time is it?"}, + LLMSpecificMessage(llm="google", message={}), + { + "role": "assistant", + "content": "", + "tool_calls": [ + { + "id": "call_123", + "type": "function", + "function": {"name": "get_time", "arguments": "{}"}, + } + ], + }, + LLMSpecificMessage(llm="google", message={}), + {"role": "tool", "tool_call_id": "call_123", "content": '{"time": "10:30 AM"}'}, + ] + + result = LLMContextSummarizationUtil._get_function_calls_in_progress_index(messages, 0) + self.assertEqual(result, -1) + + if __name__ == "__main__": unittest.main() From 9476b5d184751ddfaff76b478711fc22ba835401 Mon Sep 17 00:00:00 2001 From: Om Chauhan Date: Sat, 21 Feb 2026 17:35:08 +0530 Subject: [PATCH 0596/1060] added changelog --- changelog/3794.fixed.md | 1 + tests/test_context_summarization.py | 4 ++-- 2 files changed, 3 insertions(+), 2 deletions(-) create mode 100644 changelog/3794.fixed.md diff --git a/changelog/3794.fixed.md b/changelog/3794.fixed.md new file mode 100644 index 000000000..e2b3c7c00 --- /dev/null +++ b/changelog/3794.fixed.md @@ -0,0 +1 @@ +- Added `LLMSpecificMessage` handling in `LLMContextSummarizationUtil` to skip provider-specific messages during context summarization. diff --git a/tests/test_context_summarization.py b/tests/test_context_summarization.py index 36559ed3f..3bb1246e9 100644 --- a/tests/test_context_summarization.py +++ b/tests/test_context_summarization.py @@ -634,8 +634,8 @@ class TestLLMSpecificMessageHandling(unittest.TestCase): result = LLMContextSummarizationUtil.get_messages_to_summarize(context, 2) - self.assertGreater(len(result.messages), 0) - self.assertGreater(result.last_summarized_index, 0) + self.assertEqual(len(result.messages), 4) + self.assertEqual(result.last_summarized_index, 4) def test_format_messages_skips_specific_messages(self): """Test that format_messages_for_summary skips LLMSpecificMessage objects.""" From a18aa738e0f792c56e22574a15e30c9a6d8917a1 Mon Sep 17 00:00:00 2001 From: Om Chauhan Date: Sat, 21 Feb 2026 18:26:31 +0530 Subject: [PATCH 0597/1060] fix(realtime): handle response_cancel_not_active as non-fatal --- src/pipecat/services/grok/realtime/llm.py | 7 +++++-- src/pipecat/services/openai/realtime/llm.py | 9 ++++++--- src/pipecat/services/openai_realtime_beta/openai.py | 9 ++++++--- 3 files changed, 17 insertions(+), 8 deletions(-) diff --git a/src/pipecat/services/grok/realtime/llm.py b/src/pipecat/services/grok/realtime/llm.py index e1355ce31..0d3687a26 100644 --- a/src/pipecat/services/grok/realtime/llm.py +++ b/src/pipecat/services/grok/realtime/llm.py @@ -511,8 +511,11 @@ class GrokRealtimeLLMService(LLMService): elif evt.type == "response.function_call_arguments.done": await self._handle_evt_function_call_arguments_done(evt) elif evt.type == "error": - await self._handle_evt_error(evt) - return + if evt.error.code == "response_cancel_not_active": + logger.warning(f"Non-fatal API error: {evt.error.message}") + else: + await self._handle_evt_error(evt) + return async def _handle_evt_conversation_created(self, evt): """Handle conversation.created event - first event after connecting.""" diff --git a/src/pipecat/services/openai/realtime/llm.py b/src/pipecat/services/openai/realtime/llm.py index cf249408c..ebd1fbdbc 100644 --- a/src/pipecat/services/openai/realtime/llm.py +++ b/src/pipecat/services/openai/realtime/llm.py @@ -577,9 +577,12 @@ class OpenAIRealtimeLLMService(LLMService): await self._handle_evt_function_call_arguments_done(evt) elif evt.type == "error": if not await self._maybe_handle_evt_retrieve_conversation_item_error(evt): - await self._handle_evt_error(evt) - # errors are fatal, so exit the receive loop - return + if evt.error.code == "response_cancel_not_active": + logger.warning(f"Non-fatal API error: {evt.error.message}") + else: + await self._handle_evt_error(evt) + # errors are fatal, so exit the receive loop + return @traced_openai_realtime(operation="llm_setup") async def _handle_evt_session_created(self, evt): diff --git a/src/pipecat/services/openai_realtime_beta/openai.py b/src/pipecat/services/openai_realtime_beta/openai.py index 1199d8556..808fbb053 100644 --- a/src/pipecat/services/openai_realtime_beta/openai.py +++ b/src/pipecat/services/openai_realtime_beta/openai.py @@ -503,9 +503,12 @@ class OpenAIRealtimeBetaLLMService(LLMService): await self._handle_evt_audio_transcript_delta(evt) elif evt.type == "error": if not await self._maybe_handle_evt_retrieve_conversation_item_error(evt): - await self._handle_evt_error(evt) - # errors are fatal, so exit the receive loop - return + if evt.error.code == "response_cancel_not_active": + logger.warning(f"Non-fatal API error: {evt.error.message}") + else: + await self._handle_evt_error(evt) + # errors are fatal, so exit the receive loop + return @traced_openai_realtime(operation="llm_setup") async def _handle_evt_session_created(self, evt): From b390dc369c67b93fb04e7797069ed2a7402334bc Mon Sep 17 00:00:00 2001 From: Om Chauhan Date: Sat, 21 Feb 2026 18:33:29 +0530 Subject: [PATCH 0598/1060] added changelog --- changelog/3795.fixed.md | 1 + 1 file changed, 1 insertion(+) create mode 100644 changelog/3795.fixed.md diff --git a/changelog/3795.fixed.md b/changelog/3795.fixed.md new file mode 100644 index 000000000..8c231abac --- /dev/null +++ b/changelog/3795.fixed.md @@ -0,0 +1 @@ +- Treated `response_cancel_not_active` as a non-fatal error in realtime services (`OpenAIRealtimeLLMService`, `GrokRealtimeLLMService`, `OpenAIRealtimeBetaLLMService`) to prevent WebSocket disconnection when cancelling an inactive response. \ No newline at end of file From 6a3718d33d5ab82d3ffe893eaee03dccef51e889 Mon Sep 17 00:00:00 2001 From: Mark Backman Date: Mon, 23 Feb 2026 08:52:12 -0500 Subject: [PATCH 0599/1060] Inline local-smart-turn-v3 deps for Poetry compatibility Replace self-referential `pipecat-ai[local-smart-turn-v3]` extra in core dependencies with the actual packages (`transformers`, `onnxruntime`). Self-referential extras are not supported by Poetry and cause dependency resolution failures. Since these are required by the default turn stop strategy (LocalSmartTurnAnalyzerV3), they belong in core dependencies. - Remove `local-smart-turn-v3` optional extra from pyproject.toml - Remove try/except ModuleNotFoundError guard (now always installed) - Remove `--extra local-smart-turn-v3` from CI workflows --- .github/workflows/coverage.yaml | 1 - .github/workflows/tests.yaml | 1 - changelog/3803.fixed.md | 1 + changelog/3803.removed.md | 1 + pyproject.toml | 7 ++++--- .../turn/smart_turn/local_smart_turn_v3.py | 12 ++---------- uv.lock | 17 +++++++++-------- 7 files changed, 17 insertions(+), 23 deletions(-) create mode 100644 changelog/3803.fixed.md create mode 100644 changelog/3803.removed.md diff --git a/.github/workflows/coverage.yaml b/.github/workflows/coverage.yaml index df9c388bf..d65841a7d 100644 --- a/.github/workflows/coverage.yaml +++ b/.github/workflows/coverage.yaml @@ -40,7 +40,6 @@ jobs: --extra google \ --extra langchain \ --extra livekit \ - --extra local-smart-turn-v3 \ --extra piper \ --extra tracing \ --extra websocket diff --git a/.github/workflows/tests.yaml b/.github/workflows/tests.yaml index 5941448f3..a36a2fbd0 100644 --- a/.github/workflows/tests.yaml +++ b/.github/workflows/tests.yaml @@ -44,7 +44,6 @@ jobs: --extra google \ --extra langchain \ --extra livekit \ - --extra local-smart-turn-v3 \ --extra piper \ --extra tracing \ --extra websocket diff --git a/changelog/3803.fixed.md b/changelog/3803.fixed.md new file mode 100644 index 000000000..73d7c3f19 --- /dev/null +++ b/changelog/3803.fixed.md @@ -0,0 +1 @@ +- Fixed Poetry compatibility by inlining `local-smart-turn-v3` dependencies (`transformers`, `onnxruntime`) into core dependencies instead of using a self-referential extra. diff --git a/changelog/3803.removed.md b/changelog/3803.removed.md new file mode 100644 index 000000000..867c3cfcc --- /dev/null +++ b/changelog/3803.removed.md @@ -0,0 +1 @@ +- Removed `local-smart-turn-v3` optional extra from `pyproject.toml`. The `transformers` and `onnxruntime` packages are now always installed as core dependencies since they are required by the default turn stop strategy, `TurnAnalyzerUserTurnStopStrategy` which uses `LocalSmartTurnAnalyzerV3`. diff --git a/pyproject.toml b/pyproject.toml index db76fa24e..63ff02c06 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -38,8 +38,10 @@ dependencies = [ # Pinning numba to resolve package dependencies "numba==0.61.2", "wait_for2>=0.4.1; python_version<'3.12'", - # Pipecat optionals - "pipecat-ai[local-smart-turn-v3]", + # Required by LocalSmartTurnAnalyzerV3 + # Inlined here instead of using a self-referential extra for Poetry compatibility. + "transformers", + "onnxruntime~=1.23.2", ] [project.urls] @@ -84,7 +86,6 @@ livekit = [ "livekit~=1.0.13", "livekit-api~=1.0.5", "tenacity>=8.2.3,<10.0.0", lmnt = [ "pipecat-ai[websockets-base]" ] local = [ "pyaudio~=0.2.14" ] local-smart-turn = [ "coremltools>=8.0", "transformers", "torch>=2.5.0,<3", 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BaseTransport, runner_args: RunnerArguments): logger.info("Updating ElevenLabs TTS settings: speed=0.7") await task.queue_frame(TTSUpdateSettingsFrame(update=ElevenLabsTTSSettings(speed=0.7))) + await asyncio.sleep(10) + logger.info("Updating ElevenLabs TTS settings: switching to a different voice") + await task.queue_frame( + TTSUpdateSettingsFrame( + update=ElevenLabsTTSSettings(voice=os.getenv("ELEVENLABS_VOICE_ID_ALT")) + ) + ) + @transport.event_handler("on_client_disconnected") async def on_client_disconnected(transport, client): logger.info(f"Client disconnected") From c527e1f30f090365850344acdafbd5bb3277f110 Mon Sep 17 00:00:00 2001 From: Mark Backman Date: Mon, 23 Feb 2026 14:26:16 -0500 Subject: [PATCH 0601/1060] Add dataclass vs Pydantic BaseModel rule to CLAUDE.md Document the existing convention: use @dataclass for frames and internal pipeline data, use Pydantic BaseModel for configuration, parameters, metrics, and external API data. --- CLAUDE.md | 3 +++ 1 file changed, 3 insertions(+) diff --git a/CLAUDE.md b/CLAUDE.md index 7b79fa168..6886fc1ed 100644 --- a/CLAUDE.md +++ b/CLAUDE.md @@ -107,6 +107,9 @@ All data flows as **Frame** objects through a pipeline of **FrameProcessors**: - **Docstrings**: Google-style. Classes describe purpose; `__init__` has `Args:` section; dataclasses use `Parameters:` section. - **Linting**: Ruff (line length 100). Pre-commit hooks enforce formatting. - **Type hints**: Required for complex async code. +- **Dataclass vs Pydantic**: Use `@dataclass` for frames and internal pipeline data (high-frequency, no validation needed). Use Pydantic `BaseModel` for configuration, parameters, metrics, and external API data (benefits from validation and serialization). Specifically: + - `@dataclass`: Frame types, context aggregator pairs, internal data containers + - `BaseModel`: Service `InputParams`, transport/VAD/turn params, metrics data, API request/response models, serializer params ### Docstring Example From 30db5fea7caa1dd7a5a501cca4dff0e3f4ec7265 Mon Sep 17 00:00:00 2001 From: Paul Kompfner Date: Mon, 23 Feb 2026 15:38:57 -0500 Subject: [PATCH 0602/1060] Clarify that ServiceSettings and subclasses represent runtime-updatable settings Update docstrings for ServiceSettings, LLMSettings, TTSSettings, and STTSettings to make clear these capture only the subset of service configuration that can be changed while the pipeline is running via UpdateSettingsFrame, not all constructor parameters. --- src/pipecat/services/settings.py | 20 ++++++++++++++++---- 1 file changed, 16 insertions(+), 4 deletions(-) diff --git a/src/pipecat/services/settings.py b/src/pipecat/services/settings.py index 0721cf3cd..1033305c1 100644 --- a/src/pipecat/services/settings.py +++ b/src/pipecat/services/settings.py @@ -92,7 +92,13 @@ _S = TypeVar("_S", bound="ServiceSettings") @dataclass class ServiceSettings: - """Base class for service settings. + """Base class for runtime-updatable service settings. + + These settings represent the subset of a service's configuration that can + be changed **while the pipeline is running** (e.g. switching the model or + changing the voice). They are *not* meant to capture every constructor + parameter — only those that support live updates via + ``UpdateSettingsFrame``. Every AI service type (LLM, TTS, STT) extends this with its own fields. Fields default to ``NOT_GIVEN`` so that an instance can represent either @@ -244,7 +250,9 @@ class ServiceSettings: @dataclass class LLMSettings(ServiceSettings): - """Settings for LLM services. + """Runtime-updatable settings for LLM services. + + See ``ServiceSettings`` for the general concept. Parameters: model: LLM model identifier. @@ -279,7 +287,9 @@ class LLMSettings(ServiceSettings): @dataclass class TTSSettings(ServiceSettings): - """Settings for TTS services. + """Runtime-updatable settings for TTS services. + + See ``ServiceSettings`` for the general concept. Parameters: model: TTS model identifier. @@ -302,7 +312,9 @@ class TTSSettings(ServiceSettings): @dataclass class STTSettings(ServiceSettings): - """Settings for STT services. + """Runtime-updatable settings for STT services. + + See ``ServiceSettings`` for the general concept. Parameters: model: STT model identifier. From e804060e170c8979512475e7deacca113f59da81 Mon Sep 17 00:00:00 2001 From: Paul Kompfner Date: Mon, 23 Feb 2026 15:45:00 -0500 Subject: [PATCH 0603/1060] Update COMMUNITY_INTEGRATIONS.md _update_settings examples Simplify the reconnect example to show a common pattern (reconnect on any change) and improve the _warn_unhandled_updated_settings example to show selective handling of specific fields. --- COMMUNITY_INTEGRATIONS.md | 20 ++++++++++++-------- 1 file changed, 12 insertions(+), 8 deletions(-) diff --git a/COMMUNITY_INTEGRATIONS.md b/COMMUNITY_INTEGRATIONS.md index 32fbff333..642754451 100644 --- a/COMMUNITY_INTEGRATIONS.md +++ b/COMMUNITY_INTEGRATIONS.md @@ -266,17 +266,18 @@ class MySTTService(STTService): self._sync_model_name_to_metrics() ``` -To react to runtime setting changes, override `_update_settings`. The base implementation applies the delta to `self._settings` and returns a `dict` mapping each changed field name to its **pre-update** value. Your override should call `super()` first, then act on the changed fields: +To react to runtime setting changes, override `_update_settings`. The base implementation applies the delta to `self._settings` and returns a `dict` mapping each changed field name to its **pre-update** value. Your override should call `super()` first, then act on the changed fields. A common implementation might look like: ```python async def _update_settings(self, update: STTSettings) -> dict[str, Any]: """Apply a settings update, reconfiguring the recognizer if needed.""" changed = await super()._update_settings(update) - if "language" in changed: - # Restart the recognizer with the new language. - await self._disconnect() - await self._connect() + if not changed: + return changed + + await self._disconnect() + await self._connect() return changed ``` @@ -285,7 +286,7 @@ The dict keys work like a set for membership tests (`"language" in changed`) and Note that, in this example, the service requires a reconnect to apply the new language. Consider, for each setting, whether your service requires reconnection or can apply changes in-place. -If your service can't yet apply certain settings at runtime, call `self._warn_unhandled_updated_settings(changed)` with the unhandled field names so users get a clear log message: +If your service can't yet apply certain settings at runtime, call `self._warn_unhandled_updated_settings(changed)` with any unhandled field names so users get a clear log message: ```python async def _update_settings(self, update: STTSettings) -> dict[str, Any]: @@ -294,8 +295,11 @@ async def _update_settings(self, update: STTSettings) -> dict[str, Any]: if not changed: return changed - # TODO: someday we could reconnect here to apply updated settings. - self._warn_unhandled_updated_settings(changed) + if "language" in changed: + await self._update_language() + else: + # TODO: handle changes to other settings soon! + self._warn_unhandled_updated_settings(changed.keys() - {"language"}) return changed ``` From ff174dd1c2bda105e683dfc042b6e22d645d8c91 Mon Sep 17 00:00:00 2001 From: Paul Kompfner Date: Mon, 23 Feb 2026 15:58:39 -0500 Subject: [PATCH 0604/1060] Fix STT/TTS Deepgram Sagemaker 55-series examples (examples updating settings at runtime) --- .../55a-update-settings-deepgram-sagemaker-stt.py | 4 ++-- .../55q-update-settings-deepgram-sagemaker-tts.py | 4 ++-- 2 files changed, 4 insertions(+), 4 deletions(-) diff --git a/examples/foundational/55a-update-settings-deepgram-sagemaker-stt.py b/examples/foundational/55a-update-settings-deepgram-sagemaker-stt.py index dc8576261..8e45b5f2a 100644 --- a/examples/foundational/55a-update-settings-deepgram-sagemaker-stt.py +++ b/examples/foundational/55a-update-settings-deepgram-sagemaker-stt.py @@ -55,8 +55,8 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): logger.info(f"Starting bot") stt = DeepgramSageMakerSTTService( - endpoint_name=os.getenv("SAGEMAKER_ENDPOINT_NAME", "my-deepgram-stt-endpoint"), - region=os.getenv("AWS_REGION", "us-east-2"), + endpoint_name=os.getenv("SAGEMAKER_STT_ENDPOINT_NAME"), + region=os.getenv("AWS_REGION"), ) tts = CartesiaTTSService( diff --git a/examples/foundational/55q-update-settings-deepgram-sagemaker-tts.py b/examples/foundational/55q-update-settings-deepgram-sagemaker-tts.py index 2db7af7fe..35fb7cebe 100644 --- a/examples/foundational/55q-update-settings-deepgram-sagemaker-tts.py +++ b/examples/foundational/55q-update-settings-deepgram-sagemaker-tts.py @@ -56,8 +56,8 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): stt = DeepgramSTTService(api_key=os.getenv("DEEPGRAM_API_KEY")) tts = DeepgramSageMakerTTSService( - endpoint_name=os.getenv("SAGEMAKER_ENDPOINT_NAME", "my-deepgram-tts-endpoint"), - region=os.getenv("AWS_REGION", "us-east-2"), + endpoint_name=os.getenv("SAGEMAKER_TTS_ENDPOINT_NAME"), + region=os.getenv("AWS_REGION"), voice="aura-2-helena-en", ) From bcf11ecbd4abda082fc59a9c6d40fabf74403085 Mon Sep 17 00:00:00 2001 From: Paul Kompfner Date: Mon, 23 Feb 2026 16:01:30 -0500 Subject: [PATCH 0605/1060] Looks like the Deepgram Sagemaker TTS services aren't able yet to successfully disconnect/reconnect to apply runtime settings updates. For now, marking them as not yet supporting runtime settings updates. --- src/pipecat/services/deepgram/stt_sagemaker.py | 9 +++++++-- src/pipecat/services/deepgram/tts_sagemaker.py | 12 +++++++++--- 2 files changed, 16 insertions(+), 5 deletions(-) diff --git a/src/pipecat/services/deepgram/stt_sagemaker.py b/src/pipecat/services/deepgram/stt_sagemaker.py index 30a53a4d1..64bb2ba8f 100644 --- a/src/pipecat/services/deepgram/stt_sagemaker.py +++ b/src/pipecat/services/deepgram/stt_sagemaker.py @@ -204,8 +204,13 @@ class DeepgramSageMakerSTTService(STTService): elif "live_options" in changed and self._settings.live_options.language is not None: self._settings.language = self._settings.live_options.language - await self._disconnect() - await self._connect() + # TODO: someday we could reconnect here to apply updated settings. + # Code might look something like the below: + # await self._disconnect() + # await self._connect() + + self._warn_unhandled_updated_settings(changed) + return changed async def start(self, frame: StartFrame): diff --git a/src/pipecat/services/deepgram/tts_sagemaker.py b/src/pipecat/services/deepgram/tts_sagemaker.py index 24f9eaec9..8447c96f0 100644 --- a/src/pipecat/services/deepgram/tts_sagemaker.py +++ b/src/pipecat/services/deepgram/tts_sagemaker.py @@ -228,14 +228,20 @@ class DeepgramSageMakerTTSService(TTSService): """ changed = await super()._update_settings(update) + if not changed: + return changed + # Deepgram uses voice as the model, so keep them in sync for metrics if "voice" in changed: self._settings.model = self._settings.voice self._sync_model_name_to_metrics() - if changed: - await self._disconnect() - await self._connect() + # TODO: someday we could reconnect here to apply updated settings. + # Code might look something like the below: + # await self._disconnect() + # await self._connect() + + self._warn_unhandled_updated_settings(changed) return changed From 7556427862c3dae510e5876b422990b121e0ac2a Mon Sep 17 00:00:00 2001 From: Paul Kompfner Date: Mon, 23 Feb 2026 16:52:11 -0500 Subject: [PATCH 0606/1060] Revise changelog entries for service settings refactor Split the single "changed" entry into separate "added", "changed", and "deprecated" entries for clarity. Add a note about the subtle behavior change in the deprecated set_model/set_voice/set_language methods. --- changelog/3714.added.md | 19 +++++++++++++++++++ changelog/3714.changed.md | 2 +- changelog/3714.deprecated.2.md | 1 + changelog/3714.deprecated.md | 2 ++ 4 files changed, 23 insertions(+), 1 deletion(-) create mode 100644 changelog/3714.added.md create mode 100644 changelog/3714.deprecated.2.md diff --git a/changelog/3714.added.md b/changelog/3714.added.md new file mode 100644 index 000000000..83084675a --- /dev/null +++ b/changelog/3714.added.md @@ -0,0 +1,19 @@ +- Added support for using strongly-typed objects instead of dicts for updating service settings at runtime. + + Instead of, say: + + ```python + await task.queue_frame( + STTUpdateSettingsFrame(settings={"language": Language.ES}) + ) + ``` + + you'd do: + + ```python + await task.queue_frame( + STTUpdateSettingsFrame(update=DeepgramSTTSettings(language=Language.ES)) + ) + ``` + + Each service now vends strongly-typed classes like `DeepgramSTTSettings` representing the service's runtime-updatable settings. diff --git a/changelog/3714.changed.md b/changelog/3714.changed.md index a3081a7c8..bcfb5cbf7 100644 --- a/changelog/3714.changed.md +++ b/changelog/3714.changed.md @@ -1 +1 @@ -- ⚠️ Refactored service settings to use strongly-typed dataclasses (`TTSSettings`, `STTSettings`, `LLMSettings`, and service-specific subclasses) instead of plain dicts. Each service now exposes a `_settings` attribute with discoverable, typed fields. Dict-based `*UpdateSettingsFrame(settings={...})` is deprecated in favor of passing typed settings delta objects. For service maintainers, see changes in COMMUNITY_INTEGRATIONS.md. +- ⚠️ Refactored runtime-updatable service settings to use strongly-typed classes (`TTSSettings`, `STTSettings`, `LLMSettings`, and service-specific subclasses) instead of plain dicts. Each service's `_settings` now holds these strongly-typed objects. For service maintainers, see changes in COMMUNITY_INTEGRATIONS.md. diff --git a/changelog/3714.deprecated.2.md b/changelog/3714.deprecated.2.md new file mode 100644 index 000000000..232c1dee5 --- /dev/null +++ b/changelog/3714.deprecated.2.md @@ -0,0 +1 @@ +- Dict-based `*UpdateSettingsFrame(settings={...})` is deprecated in favor of passing typed settings delta objects with `*UpdateSettingsFrame(update={...})`. diff --git a/changelog/3714.deprecated.md b/changelog/3714.deprecated.md index ee71b2070..75337a642 100644 --- a/changelog/3714.deprecated.md +++ b/changelog/3714.deprecated.md @@ -1 +1,3 @@ - Deprecated `set_model()`, `set_voice()`, and `set_language()` on AI services in favor of runtime updates via `TTSUpdateSettingsFrame`, `STTUpdateSettingsFrame`, and `LLMUpdateSettingsFrame`. + + ⚠️ Note, too, a subtle behavior change in these deprecated methods. Whereas previously only `set_language()` caused the service to actually react to the update (e.g. by reconnecting to a remote service so it an pick up the change), now all these methods do. This change was made as part of a refactor making them all work the same way under the hood. From 71fc078c246533b44b0dc15c0da780f01e38bb47 Mon Sep 17 00:00:00 2001 From: Paul Kompfner Date: Mon, 23 Feb 2026 16:55:11 -0500 Subject: [PATCH 0607/1060] Refine ServiceSettings docstring: clarify NOT_GIVEN semantics and fix frame reference Use wildcard `*UpdateSettingsFrame` to cover all frame types. Clarify that NOT_GIVEN only appears in update deltas, not in the service's current settings state. --- src/pipecat/services/settings.py | 6 ++++-- 1 file changed, 4 insertions(+), 2 deletions(-) diff --git a/src/pipecat/services/settings.py b/src/pipecat/services/settings.py index 1033305c1..4664ecd39 100644 --- a/src/pipecat/services/settings.py +++ b/src/pipecat/services/settings.py @@ -98,11 +98,13 @@ class ServiceSettings: be changed **while the pipeline is running** (e.g. switching the model or changing the voice). They are *not* meant to capture every constructor parameter — only those that support live updates via - ``UpdateSettingsFrame``. + ``*UpdateSettingsFrame``. Every AI service type (LLM, TTS, STT) extends this with its own fields. Fields default to ``NOT_GIVEN`` so that an instance can represent either - the full current state **or** a sparse update delta. + the full current state **or** a sparse update delta. Note that in the full + current state, **all fields will be given** (i.e. ``NOT_GIVEN`` is reserved + for update deltas). Parameters: model: The model identifier used by the service. From 65f563ad34f689ce14a2f6ecd73ecdaba26d3ec3 Mon Sep 17 00:00:00 2001 From: Mark Backman Date: Mon, 23 Feb 2026 21:27:39 -0500 Subject: [PATCH 0608/1060] Add debug logging to KrispVivaTurn analyze_end_of_turn and update example Move speech detection tracking outside the per-frame loop in append_audio since is_speech applies to the whole buffer. Add debug log in analyze_end_of_turn to show state and probability at decision time. Update the Krisp VIVA example to use Cartesia TTS and turn analyzer strategy. --- changelog/3809.changed.md | 1 + examples/foundational/07p-interruptible-krisp-viva.py | 8 ++++++-- scripts/evals/run-release-evals.py | 3 +-- src/pipecat/audio/turn/krisp_viva_turn.py | 3 +++ 4 files changed, 11 insertions(+), 4 deletions(-) create mode 100644 changelog/3809.changed.md diff --git a/changelog/3809.changed.md b/changelog/3809.changed.md new file mode 100644 index 000000000..43aca00f3 --- /dev/null +++ b/changelog/3809.changed.md @@ -0,0 +1 @@ +- Added debug logging to `KrispVivaTurn.analyze_end_of_turn()` to log turn state and probability at decision time. diff --git a/examples/foundational/07p-interruptible-krisp-viva.py b/examples/foundational/07p-interruptible-krisp-viva.py index 259f02aa5..4da42e201 100644 --- a/examples/foundational/07p-interruptible-krisp-viva.py +++ b/examples/foundational/07p-interruptible-krisp-viva.py @@ -41,12 +41,14 @@ from pipecat.processors.aggregators.llm_response_universal import ( ) from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport +from pipecat.services.cartesia.tts import CartesiaTTSService from pipecat.services.deepgram.stt import DeepgramSTTService -from pipecat.services.deepgram.tts import DeepgramTTSService from pipecat.services.openai.llm import OpenAILLMService from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams +from pipecat.turns.user_stop import TurnAnalyzerUserTurnStopStrategy +from pipecat.turns.user_turn_strategies import UserTurnStrategies load_dotenv(override=True) @@ -76,7 +78,9 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): stt = DeepgramSTTService(api_key=os.getenv("DEEPGRAM_API_KEY")) - tts = DeepgramTTSService(api_key=os.getenv("DEEPGRAM_API_KEY"), voice="aura-helios-en") + tts = CartesiaTTSService( + api_key=os.getenv("CARTESIA_API_KEY"), voice_id="71a7ad14-091c-4e8e-a314-022ece01c121" + ) llm = OpenAILLMService(api_key=os.getenv("OPENAI_API_KEY")) diff --git a/scripts/evals/run-release-evals.py b/scripts/evals/run-release-evals.py index 19e5d2649..77fc23a33 100644 --- a/scripts/evals/run-release-evals.py +++ b/scripts/evals/run-release-evals.py @@ -123,6 +123,7 @@ TESTS_07 = [ ("07n-interruptible-google.py", EVAL_SIMPLE_MATH), ("07n-interruptible-google-http.py", EVAL_SIMPLE_MATH), ("07o-interruptible-assemblyai.py", EVAL_SIMPLE_MATH), + ("07p-interruptible-krisp-viva.py", EVAL_SIMPLE_MATH), ("07q-interruptible-rime.py", EVAL_SIMPLE_MATH), ("07q-interruptible-rime-http.py", EVAL_SIMPLE_MATH), ("07r-interruptible-nvidia.py", EVAL_SIMPLE_MATH), @@ -148,8 +149,6 @@ TESTS_07 = [ ("07zj-interruptible-kokoro.py", EVAL_SIMPLE_MATH), # Needs a local XTTS docker instance running. # ("07i-interruptible-xtts.py", EVAL_SIMPLE_MATH), - # Needs a Krisp license. - # ("07p-interruptible-krisp.py", EVAL_SIMPLE_MATH), ] TESTS_12 = [ diff --git a/src/pipecat/audio/turn/krisp_viva_turn.py b/src/pipecat/audio/turn/krisp_viva_turn.py index 04e59421f..59f8aada8 100644 --- a/src/pipecat/audio/turn/krisp_viva_turn.py +++ b/src/pipecat/audio/turn/krisp_viva_turn.py @@ -331,6 +331,9 @@ class KrispVivaTurn(BaseTurnAnalyzer): """ # For real-time processing, the state is determined in append_audio # Return the last state that was computed + logger.debug( + f"Krisp turn analysis: state={self._last_state}, probability={self._last_probability}" + ) return self._last_state, None def clear(self): From 0f7e6e14ab34ba22d66e0678e47aa854c977f24f Mon Sep 17 00:00:00 2001 From: Mark Backman Date: Tue, 24 Feb 2026 08:54:03 -0500 Subject: [PATCH 0609/1060] Bump nltk minimum version from 3.9.1 to 3.9.3 Resolves a security vulnerability flagged by Dependabot (#164). --- changelog/3811.changed.md | 1 + pyproject.toml | 2 +- uv.lock | 8 ++++---- 3 files changed, 6 insertions(+), 5 deletions(-) create mode 100644 changelog/3811.changed.md diff --git a/changelog/3811.changed.md b/changelog/3811.changed.md new file mode 100644 index 000000000..eb3eb492e --- /dev/null +++ b/changelog/3811.changed.md @@ -0,0 +1 @@ +- Bumped `nltk` minimum version from 3.9.1 to 3.9.3 to resolve a security vulnerability. diff --git a/pyproject.toml b/pyproject.toml index 63ff02c06..a45ebb3b3 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -26,7 +26,7 @@ dependencies = [ "docstring_parser~=0.16", "loguru~=0.7.3", "Markdown>=3.7,<4", - "nltk>=3.9.1,<4", + "nltk>=3.9.3,<4", "numpy>=1.26.4,<3", "Pillow>=11.1.0,<13", "protobuf~=5.29.6", diff --git a/uv.lock b/uv.lock index c7adf5406..bd2f64639 100644 --- a/uv.lock +++ b/uv.lock @@ -3686,7 +3686,7 @@ wheels = [ [[package]] name = "nltk" -version = "3.9.2" +version = "3.9.3" source = { registry = "https://pypi.org/simple" } dependencies = [ { name = "click" }, @@ -3694,9 +3694,9 @@ dependencies = [ { name = "regex" }, { name = "tqdm" }, ] -sdist = { url = "https://files.pythonhosted.org/packages/f9/76/3a5e4312c19a028770f86fd7c058cf9f4ec4321c6cf7526bab998a5b683c/nltk-3.9.2.tar.gz", hash = "sha256:0f409e9b069ca4177c1903c3e843eef90c7e92992fa4931ae607da6de49e1419", size = 2887629, upload-time = "2025-10-01T07:19:23.764Z" } +sdist = { url = "https://files.pythonhosted.org/packages/e1/8f/915e1c12df07c70ed779d18ab83d065718a926e70d3ea33eb0cd66ffb7c0/nltk-3.9.3.tar.gz", hash = "sha256:cb5945d6424a98d694c2b9a0264519fab4363711065a46aa0ae7a2195b92e71f", size = 2923673, upload-time = "2026-02-24T12:05:53.833Z" } wheels = [ - { url = "https://files.pythonhosted.org/packages/60/90/81ac364ef94209c100e12579629dc92bf7a709a84af32f8c551b02c07e94/nltk-3.9.2-py3-none-any.whl", hash = "sha256:1e209d2b3009110635ed9709a67a1a3e33a10f799490fa71cf4bec218c11c88a", size = 1513404, upload-time = "2025-10-01T07:19:21.648Z" }, + { url = "https://files.pythonhosted.org/packages/c2/7e/9af5a710a1236e4772de8dfcc6af942a561327bb9f42b5b4a24d0cf100fd/nltk-3.9.3-py3-none-any.whl", hash = "sha256:60b3db6e9995b3dd976b1f0fa7dec22069b2677e759c28eb69b62ddd44870522", size = 1525385, upload-time = "2026-02-24T12:05:46.54Z" }, ] [[package]] @@ -4692,7 +4692,7 @@ requires-dist = [ { name = "mcp", extras = ["cli"], marker = "extra == 'mcp'", specifier = ">=1.11.0,<2" }, { name = "mem0ai", marker = "extra == 'mem0'", specifier = "~=0.1.94" }, { name = "mlx-whisper", marker = "extra == 'mlx-whisper'", specifier = "~=0.4.2" }, - { name = "nltk", specifier = ">=3.9.1,<4" }, + { name = "nltk", specifier = ">=3.9.3,<4" }, { name = "noisereduce", marker = "extra == 'noisereduce'", specifier = "~=3.0.3" }, { name = "numba", specifier = "==0.61.2" }, { name = "numpy", specifier = ">=1.26.4,<3" }, From aff8ab8a40e0d268af8672bab76446317efa1405 Mon Sep 17 00:00:00 2001 From: Mark Backman Date: Mon, 23 Feb 2026 19:42:14 -0500 Subject: [PATCH 0610/1060] Update OpenAI Realtime default model to gpt-realtime-1.5 --- changelog/3807.changed.md | 1 + src/pipecat/services/openai/realtime/llm.py | 2 +- 2 files changed, 2 insertions(+), 1 deletion(-) create mode 100644 changelog/3807.changed.md diff --git a/changelog/3807.changed.md b/changelog/3807.changed.md new file mode 100644 index 000000000..cc99f29fb --- /dev/null +++ b/changelog/3807.changed.md @@ -0,0 +1 @@ +- Updated `OpenAIRealtimeLLMService` default model to `gpt-realtime-1.5`. \ No newline at end of file diff --git a/src/pipecat/services/openai/realtime/llm.py b/src/pipecat/services/openai/realtime/llm.py index d765fea75..750f6ded0 100644 --- a/src/pipecat/services/openai/realtime/llm.py +++ b/src/pipecat/services/openai/realtime/llm.py @@ -121,7 +121,7 @@ class OpenAIRealtimeLLMService(LLMService): self, *, api_key: str, - model: str = "gpt-realtime", + model: str = "gpt-realtime-1.5", base_url: str = "wss://api.openai.com/v1/realtime", session_properties: Optional[events.SessionProperties] = None, start_audio_paused: bool = False, From 6f7664846cace2b4109cd9a207c69deabc700ebc Mon Sep 17 00:00:00 2001 From: Mark Backman Date: Tue, 24 Feb 2026 12:53:55 -0500 Subject: [PATCH 0611/1060] Add can_generate_metrics to Soniox and AWS Transcribe STT services Commit 859cd7c9 refactored STT TTFB measurement to use the base class start_ttfb_metrics/stop_ttfb_metrics, which are gated behind can_generate_metrics(). Soniox and AWS Transcribe never overrode this method (default returns False), so TTFB was silently never reported. --- changelog/3813.fixed.md | 1 + src/pipecat/services/aws/stt.py | 8 ++++++++ src/pipecat/services/soniox/stt.py | 8 ++++++++ 3 files changed, 17 insertions(+) create mode 100644 changelog/3813.fixed.md diff --git a/changelog/3813.fixed.md b/changelog/3813.fixed.md new file mode 100644 index 000000000..9d9115e77 --- /dev/null +++ b/changelog/3813.fixed.md @@ -0,0 +1 @@ +- Fixed STT TTFB metrics not being reported for `SonioxSTTService` and `AWSTranscribeSTTService` due to missing `can_generate_metrics()` override. diff --git a/src/pipecat/services/aws/stt.py b/src/pipecat/services/aws/stt.py index 09552ecfc..c53e3648c 100644 --- a/src/pipecat/services/aws/stt.py +++ b/src/pipecat/services/aws/stt.py @@ -126,6 +126,14 @@ class AWSTranscribeSTTService(WebsocketSTTService): self._receive_task = None + def can_generate_metrics(self) -> bool: + """Check if this service can generate processing metrics. + + Returns: + True, as AWS Transcribe STT supports metrics generation. + """ + return True + def get_service_encoding(self, encoding: str) -> str: """Convert internal encoding format to AWS Transcribe format. diff --git a/src/pipecat/services/soniox/stt.py b/src/pipecat/services/soniox/stt.py index 1e4b49705..61dbb794f 100644 --- a/src/pipecat/services/soniox/stt.py +++ b/src/pipecat/services/soniox/stt.py @@ -208,6 +208,14 @@ class SonioxSTTService(WebsocketSTTService): self._receive_task = None + def can_generate_metrics(self) -> bool: + """Check if this service can generate processing metrics. + + Returns: + True, as Soniox STT supports metrics generation. + """ + return True + async def start(self, frame: StartFrame): """Start the Soniox STT websocket connection. From 23ad1815156614667e23c7bfd37f540e86619cbc Mon Sep 17 00:00:00 2001 From: Mark Backman Date: Tue, 24 Feb 2026 13:09:29 -0500 Subject: [PATCH 0612/1060] Fix Soniox processing metrics to measure token-to-transcript time Move start_processing_metrics from run_stt (called per audio chunk, producing noisy 0ms logs) to _receive_messages when the first final token arrives for a new utterance. The existing stop_processing_metrics in send_endpoint_transcript completes the pair, giving a meaningful measurement of time from first recognition to finalized transcript. --- src/pipecat/services/soniox/stt.py | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/src/pipecat/services/soniox/stt.py b/src/pipecat/services/soniox/stt.py index 61dbb794f..630e11862 100644 --- a/src/pipecat/services/soniox/stt.py +++ b/src/pipecat/services/soniox/stt.py @@ -301,10 +301,8 @@ class SonioxSTTService(WebsocketSTTService): Yields: Frame: None (transcription results come via WebSocket callbacks). """ - await self.start_processing_metrics() if self._websocket and self._websocket.state is State.OPEN: await self._websocket.send(audio) - await self.stop_processing_metrics() yield None @@ -485,6 +483,8 @@ class SonioxSTTService(WebsocketSTTService): # the rest will be sent as interim tokens (even final tokens). await send_endpoint_transcript() else: + if not self._final_transcription_buffer: + await self.start_processing_metrics() self._final_transcription_buffer.append(token) else: non_final_transcription.append(token) From 323477bfa42a6388c4a0aeef0ca76ee6e559ca77 Mon Sep 17 00:00:00 2001 From: filipi87 Date: Tue, 24 Feb 2026 15:48:46 -0300 Subject: [PATCH 0613/1060] Refactoring the services using the WordTTSService. --- src/pipecat/services/azure/tts.py | 8 +- src/pipecat/services/cartesia/tts.py | 5 +- src/pipecat/services/elevenlabs/tts.py | 10 +- src/pipecat/services/gradium/tts.py | 5 +- src/pipecat/services/hume/tts.py | 6 +- src/pipecat/services/inworld/tts.py | 8 +- src/pipecat/services/resembleai/tts.py | 5 +- src/pipecat/services/rime/tts.py | 5 +- src/pipecat/services/tts_service.py | 188 ++++++++++--------------- 9 files changed, 102 insertions(+), 138 deletions(-) diff --git a/src/pipecat/services/azure/tts.py b/src/pipecat/services/azure/tts.py index f1bf9d400..7672a846c 100644 --- a/src/pipecat/services/azure/tts.py +++ b/src/pipecat/services/azure/tts.py @@ -27,7 +27,7 @@ from pipecat.frames.frames import ( from pipecat.processors.frame_processor import FrameDirection from pipecat.services.azure.common import language_to_azure_language from pipecat.services.settings import NOT_GIVEN, TTSSettings, _NotGiven -from pipecat.services.tts_service import TTSService, WordTTSService +from pipecat.services.tts_service import TTSService from pipecat.transcriptions.language import Language from pipecat.utils.tracing.service_decorators import traced_tts @@ -258,7 +258,7 @@ class AzureBaseTTSService: return escaped_text -class AzureTTSService(WordTTSService, AzureBaseTTSService): +class AzureTTSService(TTSService, AzureBaseTTSService): """Azure Cognitive Services streaming TTS service with word timestamps. Provides real-time text-to-speech synthesis using Azure's WebSocket-based @@ -286,14 +286,14 @@ class AzureTTSService(WordTTSService, AzureBaseTTSService): sample_rate: Audio sample rate in Hz. If None, uses service default. params: Voice and synthesis parameters configuration. aggregate_sentences: Whether to aggregate sentences before synthesis. - **kwargs: Additional arguments passed to parent WordTTSService. + **kwargs: Additional arguments passed to the parent TTSService. """ - # Initialize WordTTSService first to set up word timestamp tracking super().__init__( aggregate_sentences=aggregate_sentences, push_text_frames=False, # We'll push text frames based on word timestamps push_stop_frames=True, pause_frame_processing=True, + supports_word_timestamps=True, sample_rate=sample_rate, **kwargs, ) diff --git a/src/pipecat/services/cartesia/tts.py b/src/pipecat/services/cartesia/tts.py index cca540c72..3f6fe2c21 100644 --- a/src/pipecat/services/cartesia/tts.py +++ b/src/pipecat/services/cartesia/tts.py @@ -29,7 +29,7 @@ from pipecat.frames.frames import ( ) from pipecat.processors.frame_processor import FrameDirection from pipecat.services.settings import NOT_GIVEN, TTSSettings, _NotGiven, is_given -from pipecat.services.tts_service import AudioContextWordTTSService, TTSService +from pipecat.services.tts_service import AudioContextTTSService, TTSService from pipecat.transcriptions.language import Language, resolve_language from pipecat.utils.text.base_text_aggregator import BaseTextAggregator from pipecat.utils.text.skip_tags_aggregator import SkipTagsAggregator @@ -229,7 +229,7 @@ class CartesiaTTSSettings(TTSSettings): return super().from_mapping(flat) -class CartesiaTTSService(AudioContextWordTTSService): +class CartesiaTTSService(AudioContextTTSService): """Cartesia TTS service with WebSocket streaming and word timestamps. Provides text-to-speech using Cartesia's streaming WebSocket API. @@ -311,6 +311,7 @@ class CartesiaTTSService(AudioContextWordTTSService): aggregate_sentences=aggregate_sentences, push_text_frames=False, pause_frame_processing=True, + supports_word_timestamps=True, sample_rate=sample_rate, text_aggregator=text_aggregator, **kwargs, diff --git a/src/pipecat/services/elevenlabs/tts.py b/src/pipecat/services/elevenlabs/tts.py index 72fa6c11a..8d51e9dde 100644 --- a/src/pipecat/services/elevenlabs/tts.py +++ b/src/pipecat/services/elevenlabs/tts.py @@ -46,8 +46,8 @@ from pipecat.frames.frames import ( from pipecat.processors.frame_processor import FrameDirection from pipecat.services.settings import NOT_GIVEN, TTSSettings, _NotGiven, is_given from pipecat.services.tts_service import ( - AudioContextWordTTSService, - WordTTSService, + AudioContextTTSService, + TTSService, ) from pipecat.transcriptions.language import Language, resolve_language from pipecat.utils.tracing.service_decorators import traced_tts @@ -317,7 +317,7 @@ def calculate_word_times( return (word_times, new_partial_word, new_partial_word_start_time) -class ElevenLabsTTSService(AudioContextWordTTSService): +class ElevenLabsTTSService(AudioContextTTSService): """ElevenLabs WebSocket-based TTS service with word timestamps. Provides real-time text-to-speech using ElevenLabs' WebSocket streaming API. @@ -399,6 +399,7 @@ class ElevenLabsTTSService(AudioContextWordTTSService): push_text_frames=False, push_stop_frames=True, pause_frame_processing=True, + supports_word_timestamps=True, sample_rate=sample_rate, **kwargs, ) @@ -838,7 +839,7 @@ class ElevenLabsTTSService(AudioContextWordTTSService): yield ErrorFrame(error=f"Unknown error occurred: {e}") -class ElevenLabsHttpTTSService(WordTTSService): +class ElevenLabsHttpTTSService(TTSService): """ElevenLabs HTTP-based TTS service with word timestamps. Provides text-to-speech using ElevenLabs' HTTP streaming API for simpler, @@ -903,6 +904,7 @@ class ElevenLabsHttpTTSService(WordTTSService): aggregate_sentences=aggregate_sentences, push_text_frames=False, push_stop_frames=True, + supports_word_timestamps=True, sample_rate=sample_rate, **kwargs, ) diff --git a/src/pipecat/services/gradium/tts.py b/src/pipecat/services/gradium/tts.py index 8b8995c41..d10f6258d 100644 --- a/src/pipecat/services/gradium/tts.py +++ b/src/pipecat/services/gradium/tts.py @@ -25,7 +25,7 @@ from pipecat.frames.frames import ( ) from pipecat.processors.frame_processor import FrameDirection from pipecat.services.settings import NOT_GIVEN, TTSSettings, _NotGiven -from pipecat.services.tts_service import AudioContextWordTTSService +from pipecat.services.tts_service import AudioContextTTSService from pipecat.utils.tracing.service_decorators import traced_tts try: @@ -51,7 +51,7 @@ class GradiumTTSSettings(TTSSettings): output_format: str | _NotGiven = field(default_factory=lambda: NOT_GIVEN) -class GradiumTTSService(AudioContextWordTTSService): +class GradiumTTSService(AudioContextTTSService): """Text-to-Speech service using Gradium's websocket API.""" _settings: GradiumTTSSettings @@ -91,6 +91,7 @@ class GradiumTTSService(AudioContextWordTTSService): push_stop_frames=True, push_text_frames=False, pause_frame_processing=True, + supports_word_timestamps=True, sample_rate=SAMPLE_RATE, **kwargs, ) diff --git a/src/pipecat/services/hume/tts.py b/src/pipecat/services/hume/tts.py index d15f13ce1..b5a064334 100644 --- a/src/pipecat/services/hume/tts.py +++ b/src/pipecat/services/hume/tts.py @@ -27,7 +27,7 @@ from pipecat.frames.frames import ( ) from pipecat.processors.frame_processor import FrameDirection from pipecat.services.settings import NOT_GIVEN, TTSSettings, _NotGiven -from pipecat.services.tts_service import WordTTSService +from pipecat.services.tts_service import TTSService from pipecat.utils.tracing.service_decorators import traced_tts try: @@ -64,7 +64,7 @@ class HumeTTSSettings(TTSSettings): trailing_silence: float | None | _NotGiven = field(default_factory=lambda: NOT_GIVEN) -class HumeTTSService(WordTTSService): +class HumeTTSService(TTSService): """Hume Octave Text-to-Speech service. Streams PCM audio via Hume's HTTP output streaming (JSON chunks) endpoint @@ -121,11 +121,11 @@ class HumeTTSService(WordTTSService): f"Hume TTS streams at {HUME_SAMPLE_RATE} Hz; configured sample_rate={sample_rate}" ) - # WordTTSService sets push_text_frames=False by default, which we want super().__init__( sample_rate=sample_rate, push_text_frames=False, push_stop_frames=True, + supports_word_timestamps=True, **kwargs, ) diff --git a/src/pipecat/services/inworld/tts.py b/src/pipecat/services/inworld/tts.py index 11e6125c0..8e457aabc 100644 --- a/src/pipecat/services/inworld/tts.py +++ b/src/pipecat/services/inworld/tts.py @@ -51,7 +51,7 @@ from pipecat.frames.frames import ( TTSStoppedFrame, ) from pipecat.processors.frame_processor import FrameDirection -from pipecat.services.tts_service import AudioContextWordTTSService, WordTTSService +from pipecat.services.tts_service import AudioContextTTSService, TTSService from pipecat.utils.tracing.service_decorators import traced_tts @@ -102,7 +102,7 @@ class InworldTTSSettings(TTSSettings): return super().from_mapping(flat) -class InworldHttpTTSService(WordTTSService): +class InworldHttpTTSService(TTSService): """Inworld AI HTTP-based TTS service. Supports both streaming and non-streaming modes via the `streaming` parameter. @@ -153,6 +153,7 @@ class InworldHttpTTSService(WordTTSService): super().__init__( push_text_frames=False, push_stop_frames=True, + supports_word_timestamps=True, sample_rate=sample_rate, **kwargs, ) @@ -467,7 +468,7 @@ class InworldHttpTTSService(WordTTSService): ) -class InworldTTSService(AudioContextWordTTSService): +class InworldTTSService(AudioContextTTSService): """Inworld AI WebSocket-based TTS service. Uses bidirectional WebSocket for lower latency streaming. Supports multiple @@ -534,6 +535,7 @@ class InworldTTSService(AudioContextWordTTSService): push_text_frames=False, push_stop_frames=True, pause_frame_processing=True, + supports_word_timestamps=True, sample_rate=sample_rate, aggregate_sentences=aggregate_sentences, append_trailing_space=append_trailing_space, diff --git a/src/pipecat/services/resembleai/tts.py b/src/pipecat/services/resembleai/tts.py index b8bb4a1da..177a4c10e 100644 --- a/src/pipecat/services/resembleai/tts.py +++ b/src/pipecat/services/resembleai/tts.py @@ -26,7 +26,7 @@ from pipecat.frames.frames import ( ) from pipecat.processors.frame_processor import FrameDirection from pipecat.services.settings import NOT_GIVEN, TTSSettings, _NotGiven -from pipecat.services.tts_service import AudioContextWordTTSService +from pipecat.services.tts_service import AudioContextTTSService from pipecat.utils.tracing.service_decorators import traced_tts try: @@ -58,7 +58,7 @@ class ResembleAITTSSettings(TTSSettings): } -class ResembleAITTSService(AudioContextWordTTSService): +class ResembleAITTSService(AudioContextTTSService): """Resemble AI TTS service with WebSocket streaming and word timestamps. Provides text-to-speech using Resemble AI's streaming WebSocket API. @@ -93,6 +93,7 @@ class ResembleAITTSService(AudioContextWordTTSService): super().__init__( sample_rate=sample_rate, reuse_context_id_within_turn=False, + supports_word_timestamps=True, **kwargs, ) diff --git a/src/pipecat/services/rime/tts.py b/src/pipecat/services/rime/tts.py index 6e03c2461..6e795cc3d 100644 --- a/src/pipecat/services/rime/tts.py +++ b/src/pipecat/services/rime/tts.py @@ -33,7 +33,7 @@ from pipecat.frames.frames import ( from pipecat.processors.frame_processor import FrameDirection from pipecat.services.settings import NOT_GIVEN, TTSSettings, _NotGiven, is_given from pipecat.services.tts_service import ( - AudioContextWordTTSService, + AudioContextTTSService, InterruptibleTTSService, TTSService, ) @@ -130,7 +130,7 @@ class RimeNonJsonTTSSettings(TTSSettings): _aliases: ClassVar[Dict[str, str]] = {"speaker": "voice"} -class RimeTTSService(AudioContextWordTTSService): +class RimeTTSService(AudioContextTTSService): """Text-to-Speech service using Rime's websocket API. Uses Rime's websocket JSON API to convert text to speech with word-level timing @@ -207,6 +207,7 @@ class RimeTTSService(AudioContextWordTTSService): push_text_frames=False, push_stop_frames=True, pause_frame_processing=True, + supports_word_timestamps=True, append_trailing_space=True, sample_rate=sample_rate, **kwargs, diff --git a/src/pipecat/services/tts_service.py b/src/pipecat/services/tts_service.py index 9d9c41b60..e7b57833d 100644 --- a/src/pipecat/services/tts_service.py +++ b/src/pipecat/services/tts_service.py @@ -128,6 +128,8 @@ class TTSService(AIService): append_trailing_space: bool = False, # TTS output sample rate sample_rate: Optional[int] = None, + # if True, enables word-level timestamp tracking and synchronization + supports_word_timestamps: bool = False, # Text aggregator to aggregate incoming tokens and decide when to push to the TTS. text_aggregator: Optional[BaseTextAggregator] = None, # Types of text aggregations that should not be spoken. @@ -160,6 +162,9 @@ class TTSService(AIService): append_trailing_space: Whether to append a trailing space to text before sending to TTS. This helps prevent some TTS services from vocalizing trailing punctuation (e.g., "dot"). sample_rate: Output sample rate for generated audio. + supports_word_timestamps: Whether this service supports word-level timestamp tracking. + When True, enables synchronization of audio with spoken words so only spoken words + are added to the conversation context. text_aggregator: Custom text aggregator for processing incoming text. .. deprecated:: 0.0.95 @@ -231,6 +236,13 @@ class TTSService(AIService): self._processing_text: bool = False self._tts_contexts: Dict[str, TTSContext] = {} + # Word timestamp state (active when supports_word_timestamps=True) + self._supports_word_timestamps: bool = supports_word_timestamps + self._initial_word_timestamp: int = -1 + self._initial_word_times: List[Tuple[str, float, Optional[str]]] = [] + self._words_task: Optional[asyncio.Task] = None + self._llm_response_started: bool = False + self._register_event_handler("on_connected") self._register_event_handler("on_disconnected") self._register_event_handler("on_connection_error") @@ -366,6 +378,8 @@ class TTSService(AIService): self._sample_rate = self._init_sample_rate or frame.audio_out_sample_rate if self._push_stop_frames and not self._stop_frame_task: self._stop_frame_task = self.create_task(self._stop_frame_handler()) + if self._supports_word_timestamps: + self._create_words_task() async def stop(self, frame: EndFrame): """Stop the TTS service. @@ -377,6 +391,8 @@ class TTSService(AIService): if self._stop_frame_task: await self.cancel_task(self._stop_frame_task) self._stop_frame_task = None + if self._words_task: + await self._stop_words_task() async def cancel(self, frame: CancelFrame): """Cancel the TTS service. @@ -388,6 +404,8 @@ class TTSService(AIService): if self._stop_frame_task: await self.cancel_task(self._stop_frame_task) self._stop_frame_task = None + if self._words_task: + await self._stop_words_task() def add_text_transformer( self, @@ -492,6 +510,9 @@ class TTSService(AIService): elif isinstance(frame, InterruptionFrame): await self._handle_interruption(frame, direction) await self.push_frame(frame, direction) + elif isinstance(frame, LLMFullResponseStartFrame): + self._llm_response_started = True + await self.push_frame(frame, direction) elif isinstance(frame, (LLMFullResponseEndFrame, EndFrame)): # We pause processing incoming frames if the LLM response included # text (it might be that it's only a function calling response). We @@ -510,6 +531,9 @@ class TTSService(AIService): await self.push_frame(frame, direction) else: await self.push_frame(frame, direction) + # Flush any pending audio so the TTS service closes the current context. + if self._supports_word_timestamps: + await self.flush_audio() elif isinstance(frame, TTSSpeakFrame): # Store if we were processing text or not so we can set it back. processing_text = self._processing_text @@ -648,6 +672,10 @@ class TTSService(AIService): for filter in self._text_filters: await filter.handle_interruption() + self._llm_response_started = False + if self._supports_word_timestamps: + await self.reset_word_timestamps() + async def _maybe_pause_frame_processing(self): if self._processing_text and self._pause_frame_processing: await self.pause_processing_frames() @@ -786,25 +814,9 @@ class TTSService(AIService): await self.push_frame(TTSStoppedFrame()) has_started = False - -class WordTTSService(TTSService): - """Base class for TTS services that support word timestamps. - - Word timestamps are useful to synchronize audio with text of the spoken - words. This way only the spoken words are added to the conversation context. - """ - - def __init__(self, **kwargs): - """Initialize the Word TTS service. - - Args: - **kwargs: Additional arguments passed to the parent TTSService. - """ - super().__init__(**kwargs) - self._initial_word_timestamp = -1 - self._initial_word_times = [] - self._words_task = None - self._llm_response_started: bool = False + # + # Word timestamp methods (active when supports_word_timestamps=True) + # async def start_word_timestamps(self): """Start tracking word timestamps from the current time.""" @@ -839,55 +851,9 @@ class WordTTSService(TTSService): else: await self._add_word_timestamps(word_times_with_context) - async def start(self, frame: StartFrame): - """Start the word TTS service. - - Args: - frame: The start frame containing initialization parameters. - """ - await super().start(frame) - self._create_words_task() - - async def stop(self, frame: EndFrame): - """Stop the word TTS service. - - Args: - frame: The end frame. - """ - await super().stop(frame) - await self._stop_words_task() - - async def cancel(self, frame: CancelFrame): - """Cancel the word TTS service. - - Args: - frame: The cancel frame. - """ - await super().cancel(frame) - await self._stop_words_task() - - async def process_frame(self, frame: Frame, direction: FrameDirection): - """Process frames with word timestamp awareness. - - Args: - frame: The frame to process. - direction: The direction of frame processing. - """ - await super().process_frame(frame, direction) - - if isinstance(frame, LLMFullResponseStartFrame): - self._llm_response_started = True - elif isinstance(frame, (LLMFullResponseEndFrame, EndFrame)): - await self.flush_audio() - - async def _handle_interruption(self, frame: InterruptionFrame, direction: FrameDirection): - await super()._handle_interruption(frame, direction) - self._llm_response_started = False - await self.reset_word_timestamps() - def _create_words_task(self): if not self._words_task: - self._words_queue = asyncio.Queue() + self._words_queue: asyncio.Queue = asyncio.Queue() self._words_task = self.create_task(self._words_task_handler()) async def _stop_words_task(self): @@ -929,6 +895,23 @@ class WordTTSService(TTSService): self._words_queue.task_done() +class WordTTSService(TTSService): + """Deprecated. Use TTSService with supports_word_timestamps=True instead. + + .. deprecated:: 0.0.104 + Word timestamp functionality has been moved to TTSService. Pass + ``supports_word_timestamps=True`` to TTSService (or any subclass) instead. + """ + + def __init__(self, **kwargs): + """Initialize the Word TTS service. + + Args: + **kwargs: Additional arguments passed to the parent TTSService. + """ + super().__init__(supports_word_timestamps=True, **kwargs) + + class WebsocketTTSService(TTSService, WebsocketService): """Base class for websocket-based TTS services. @@ -1001,10 +984,12 @@ class InterruptibleTTSService(WebsocketTTSService): self._bot_speaking = False -class WebsocketWordTTSService(WordTTSService, WebsocketService): - """Base class for websocket-based TTS services that support word timestamps. +class WebsocketWordTTSService(WebsocketTTSService): + """Deprecated. Use WebsocketTTSService with supports_word_timestamps=True instead. - Combines word timestamp functionality with websocket connectivity. + .. deprecated:: 0.0.104 + Word timestamp functionality has been moved to TTSService. Pass + ``supports_word_timestamps=True`` to WebsocketTTSService instead. """ def __init__(self, *, reconnect_on_error: bool = True, **kwargs): @@ -1014,53 +999,26 @@ class WebsocketWordTTSService(WordTTSService, WebsocketService): reconnect_on_error: Whether to automatically reconnect on websocket errors. **kwargs: Additional arguments passed to parent classes. """ - WordTTSService.__init__(self, **kwargs) - WebsocketService.__init__(self, reconnect_on_error=reconnect_on_error, **kwargs) - - async def _report_error(self, error: ErrorFrame): - await self._call_event_handler("on_connection_error", error.error) - await self.push_error_frame(error) + super().__init__( + supports_word_timestamps=True, reconnect_on_error=reconnect_on_error, **kwargs + ) -class InterruptibleWordTTSService(WebsocketWordTTSService): - """Websocket-based TTS service with word timestamps that handles interruptions. +class InterruptibleWordTTSService(InterruptibleTTSService): + """Deprecated. Use InterruptibleTTSService with supports_word_timestamps=True instead. - For TTS services that support word timestamps but can't correlate generated - audio with requested text. Handles interruptions by reconnecting when needed. + .. deprecated:: 0.0.104 + Word timestamp functionality has been moved to TTSService. Pass + ``supports_word_timestamps=True`` to InterruptibleTTSService instead. """ def __init__(self, **kwargs): """Initialize the Interruptible Word TTS service. Args: - **kwargs: Additional arguments passed to the parent WebsocketWordTTSService. + **kwargs: Additional arguments passed to the parent InterruptibleTTSService. """ - super().__init__(**kwargs) - - # Indicates if the bot is speaking. If the bot is not speaking we don't - # need to reconnect when the user speaks. If the bot is speaking and the - # user interrupts we need to reconnect. - self._bot_speaking = False - - async def _handle_interruption(self, frame: InterruptionFrame, direction: FrameDirection): - await super()._handle_interruption(frame, direction) - if self._bot_speaking: - await self._disconnect() - await self._connect() - - async def process_frame(self, frame: Frame, direction: FrameDirection): - """Process frames with bot speaking state tracking. - - Args: - frame: The frame to process. - direction: The direction of frame processing. - """ - await super().process_frame(frame, direction) - - if isinstance(frame, BotStartedSpeakingFrame): - self._bot_speaking = True - elif isinstance(frame, BotStoppedSpeakingFrame): - self._bot_speaking = False + super().__init__(supports_word_timestamps=True, **kwargs) class AudioContextTTSService(WebsocketTTSService): @@ -1299,15 +1257,12 @@ class AudioContextTTSService(WebsocketTTSService): break -class AudioContextWordTTSService(AudioContextTTSService, WebsocketWordTTSService): - """Websocket-based TTS service with word timestamps and audio context management. +class AudioContextWordTTSService(AudioContextTTSService): + """Deprecated. Use AudioContextTTSService with supports_word_timestamps=True instead. - This is a base class for websocket-based TTS services that support word - timestamps and also allow correlating the generated audio with the requested - text through audio contexts. - - Combines the audio context management capabilities of AudioContextTTSService - with the word timestamp functionality of WebsocketWordTTSService. + .. deprecated:: 0.0.104 + Word timestamp functionality has been moved to TTSService. Pass + ``supports_word_timestamps=True`` to AudioContextTTSService instead. """ def __init__(self, *, reconnect_on_error: bool = True, **kwargs): @@ -1317,5 +1272,6 @@ class AudioContextWordTTSService(AudioContextTTSService, WebsocketWordTTSService reconnect_on_error: Whether to automatically reconnect on websocket errors. **kwargs: Additional arguments passed to parent classes. """ - AudioContextTTSService.__init__(self, reconnect_on_error=reconnect_on_error, **kwargs) - WebsocketWordTTSService.__init__(self, reconnect_on_error=reconnect_on_error, **kwargs) + super().__init__( + supports_word_timestamps=True, reconnect_on_error=reconnect_on_error, **kwargs + ) From 6cda2ff941d094af0726f970cdccd30924387ecf Mon Sep 17 00:00:00 2001 From: filipi87 Date: Tue, 24 Feb 2026 15:49:02 -0300 Subject: [PATCH 0614/1060] Changelog entry for word timestamp refactor and deprecation notes. --- changelog/3786.changed.md | 1 + changelog/3786.deprecated.md | 5 +++++ 2 files changed, 6 insertions(+) create mode 100644 changelog/3786.changed.md create mode 100644 changelog/3786.deprecated.md diff --git a/changelog/3786.changed.md b/changelog/3786.changed.md new file mode 100644 index 000000000..ed8e7e444 --- /dev/null +++ b/changelog/3786.changed.md @@ -0,0 +1 @@ +- Word timestamp support has been moved from `WordTTSService` into `TTSService` via a new `supports_word_timestamps` parameter. Services that previously extended `WordTTSService`, `AudioContextWordTTSService`, or `WebsocketWordTTSService` now pass `supports_word_timestamps=True` to their parent `__init__` instead. diff --git a/changelog/3786.deprecated.md b/changelog/3786.deprecated.md new file mode 100644 index 000000000..7ac5a5b9c --- /dev/null +++ b/changelog/3786.deprecated.md @@ -0,0 +1,5 @@ +- Deprecated `WordTTSService`, `WebsocketWordTTSService`, `AudioContextWordTTSService`, and `InterruptibleWordTTSService`. Use their non-word counterparts with `supports_word_timestamps=True` instead: + - `WordTTSService` → `TTSService(supports_word_timestamps=True)` + - `WebsocketWordTTSService` → `WebsocketTTSService(supports_word_timestamps=True)` + - `AudioContextWordTTSService` → `AudioContextTTSService(supports_word_timestamps=True)` + - `InterruptibleWordTTSService` → `InterruptibleTTSService(supports_word_timestamps=True)` From bcc2b4def48ef5c0c13544ab526df79fe80531d1 Mon Sep 17 00:00:00 2001 From: Paul Kompfner Date: Tue, 24 Feb 2026 10:52:05 -0500 Subject: [PATCH 0615/1060] Make clearer the distinction between "storage-mode" and "delta-mode" usage of `*Settings` objects - Storage mode: for use in `self._settings`. All fields should be specified, i.e. should not be `NOT_GIVEN`. - Delta mode: for use in `*UpdateSettingsFrame`. In service of this, this commit: - Adds a runtime check that all fields are specified in storage mode - Updates all services to specify all fields in stored settings - Updates all services to no longer check for `is_given` in stored settings (not necessary anymore) - Updates relevant docstrings - Renames `update` to `delta` in `*UpdateSettingsFrame` - Updates community integrations guide --- COMMUNITY_INTEGRATIONS.md | 8 +- changelog/3714.added.md | 2 +- changelog/3714.deprecated.2.md | 2 +- .../55a-update-settings-deepgram-flux-stt.py | 2 +- ...-update-settings-deepgram-sagemaker-stt.py | 2 +- .../55a-update-settings-deepgram-stt.py | 2 +- .../55b-update-settings-azure-stt.py | 4 +- .../55c-update-settings-google-stt.py | 2 +- .../55d-update-settings-assemblyai-stt.py | 2 +- .../55e-update-settings-gladia-stt.py | 2 +- ...update-settings-elevenlabs-realtime-stt.py | 2 +- .../55g-update-settings-elevenlabs-stt.py | 2 +- .../55h-update-settings-speechmatics-stt.py | 6 +- .../55i-update-settings-whisper-api-stt.py | 2 +- .../55j-update-settings-sarvam-stt.py | 2 +- .../55k-update-settings-soniox-stt.py | 2 +- .../55l-update-settings-aws-transcribe-stt.py | 2 +- .../55m-update-settings-cartesia-stt.py | 2 +- .../55n-update-settings-cartesia-http-tts.py | 2 +- .../55n-update-settings-cartesia-tts.py | 2 +- ...55o-update-settings-elevenlabs-http-tts.py | 2 +- .../55o-update-settings-elevenlabs-tts.py | 4 +- .../55p-update-settings-openai-tts.py | 2 +- .../55q-update-settings-deepgram-http-tts.py | 4 +- ...-update-settings-deepgram-sagemaker-tts.py | 4 +- .../55q-update-settings-deepgram-tts.py | 4 +- .../55r-update-settings-azure-http-tts.py | 2 +- .../55r-update-settings-azure-tts.py | 2 +- .../55s-update-settings-google-http-tts.py | 2 +- .../55s-update-settings-google-stream-tts.py | 2 +- .../55t-update-settings-playht-tts.py | 2 +- .../55u-update-settings-rime-http-tts.py | 2 +- .../55u-update-settings-rime-tts.py | 2 +- .../55v-update-settings-lmnt-tts.py | 2 +- .../55w-update-settings-fish-tts.py | 2 +- .../55x-update-settings-minimax-tts.py | 2 +- .../55y-update-settings-groq-tts.py | 2 +- .../55z-update-settings-hume-tts.py | 2 +- ...55za-update-settings-neuphonic-http-tts.py | 2 +- .../55za-update-settings-neuphonic-tts.py | 2 +- .../55zb-update-settings-inworld-http-tts.py | 4 +- .../55zb-update-settings-inworld-tts.py | 2 +- .../55zc-update-settings-gemini-tts.py | 2 +- .../55zd-update-settings-aws-polly-tts.py | 2 +- .../55ze-update-settings-sarvam-http-tts.py | 2 +- .../55ze-update-settings-sarvam-tts.py | 2 +- .../55zf-update-settings-camb-tts.py | 2 +- .../55zg-update-settings-hathora-tts.py | 2 +- .../55zh-update-settings-resembleai-tts.py | 2 +- .../55zi-update-settings-azure-llm.py | 2 +- .../55zi-update-settings-openai-llm.py | 2 +- .../55zj-update-settings-anthropic-llm.py | 2 +- .../55zk-update-settings-google-llm.py | 2 +- .../55zk-update-settings-google-vertex-llm.py | 2 +- .../55zl-update-settings-azure-realtime.py | 4 +- .../55zl-update-settings-openai-realtime.py | 4 +- ...55zm-update-settings-gemini-live-vertex.py | 4 +- .../55zm-update-settings-gemini-live.py | 4 +- .../55zn-update-settings-ultravox-realtime.py | 4 +- .../55zo-update-settings-grok-realtime.py | 2 +- .../55zp-update-settings-aws-bedrock-llm.py | 4 +- .../55zq-update-settings-fal-stt.py | 2 +- .../55zr-update-settings-gradium-stt.py | 2 +- .../55zs-update-settings-hathora-stt.py | 2 +- ...zt-update-settings-nvidia-segmented-stt.py | 2 +- .../55zt-update-settings-nvidia-stt.py | 2 +- ...5zu-update-settings-openai-realtime-stt.py | 2 +- .../55zv-update-settings-asyncai-http-tts.py | 2 +- .../55zv-update-settings-asyncai-tts.py | 2 +- .../55zw-update-settings-gradium-tts.py | 2 +- .../55zx-update-settings-cerebras-llm.py | 2 +- .../55zy-update-settings-deepseek-llm.py | 2 +- .../55zz-update-settings-fireworks-llm.py | 2 +- .../55zza-update-settings-grok-llm.py | 2 +- .../55zzb-update-settings-groq-llm.py | 2 +- .../55zzc-update-settings-mistral-llm.py | 2 +- .../55zzd-update-settings-nvidia-llm.py | 2 +- .../55zze-update-settings-ollama-llm.py | 2 +- .../55zzf-update-settings-openrouter-llm.py | 2 +- .../55zzg-update-settings-perplexity-llm.py | 2 +- .../55zzh-update-settings-qwen-llm.py | 2 +- .../55zzi-update-settings-sambanova-llm.py | 2 +- .../55zzj-update-settings-together-llm.py | 2 +- ...5zzk-update-settings-aws-nova-sonic-llm.py | 2 +- .../55zzl-update-settings-nvidia-tts.py | 2 +- .../55zzm-update-settings-speechmatics-tts.py | 2 +- src/pipecat/frames/frames.py | 12 +- src/pipecat/services/ai_service.py | 13 +- src/pipecat/services/anthropic/llm.py | 5 + src/pipecat/services/assemblyai/stt.py | 9 +- src/pipecat/services/asyncai/tts.py | 6 +- src/pipecat/services/aws/llm.py | 6 + src/pipecat/services/aws/nova_sonic/llm.py | 12 +- src/pipecat/services/aws/stt.py | 6 +- src/pipecat/services/aws/tts.py | 1 + src/pipecat/services/azure/stt.py | 7 +- src/pipecat/services/azure/tts.py | 1 + src/pipecat/services/cartesia/stt.py | 8 +- src/pipecat/services/cartesia/tts.py | 25 +- src/pipecat/services/deepgram/flux/stt.py | 6 +- src/pipecat/services/deepgram/stt.py | 16 +- .../services/deepgram/stt_sagemaker.py | 16 +- src/pipecat/services/deepgram/tts.py | 10 +- .../services/deepgram/tts_sagemaker.py | 7 +- src/pipecat/services/elevenlabs/stt.py | 16 +- src/pipecat/services/elevenlabs/tts.py | 32 +-- src/pipecat/services/fal/stt.py | 1 + src/pipecat/services/fish/tts.py | 8 +- src/pipecat/services/gladia/stt.py | 10 +- .../services/google/gemini_live/llm.py | 9 +- src/pipecat/services/google/llm.py | 5 + src/pipecat/services/google/stt.py | 48 ++-- src/pipecat/services/google/tts.py | 39 +-- src/pipecat/services/gradium/stt.py | 17 +- src/pipecat/services/gradium/tts.py | 9 +- src/pipecat/services/grok/realtime/llm.py | 20 +- src/pipecat/services/hume/tts.py | 5 +- src/pipecat/services/inworld/tts.py | 57 ++--- src/pipecat/services/kokoro/tts.py | 1 + src/pipecat/services/llm_service.py | 24 +- src/pipecat/services/lmnt/tts.py | 8 +- src/pipecat/services/minimax/tts.py | 16 +- src/pipecat/services/neuphonic/tts.py | 8 +- src/pipecat/services/nvidia/stt.py | 8 +- src/pipecat/services/nvidia/tts.py | 6 +- src/pipecat/services/openai/base_llm.py | 3 + src/pipecat/services/openai/realtime/llm.py | 19 +- src/pipecat/services/openai/stt.py | 10 +- .../services/openai_realtime_beta/openai.py | 19 +- src/pipecat/services/perplexity/llm.py | 12 +- src/pipecat/services/piper/tts.py | 10 +- src/pipecat/services/playht/tts.py | 10 +- src/pipecat/services/resembleai/tts.py | 1 + src/pipecat/services/rime/tts.py | 100 ++++---- src/pipecat/services/sarvam/stt.py | 34 +-- src/pipecat/services/sarvam/tts.py | 28 ++- src/pipecat/services/settings.py | 232 ++++++++++++------ src/pipecat/services/soniox/stt.py | 12 +- src/pipecat/services/speechmatics/stt.py | 31 +-- src/pipecat/services/speechmatics/tts.py | 2 + src/pipecat/services/stt_service.py | 24 +- src/pipecat/services/tts_service.py | 28 +-- src/pipecat/services/ultravox/llm.py | 18 +- src/pipecat/services/whisper/base_stt.py | 6 +- src/pipecat/services/xtts/tts.py | 1 + 145 files changed, 732 insertions(+), 587 deletions(-) diff --git a/COMMUNITY_INTEGRATIONS.md b/COMMUNITY_INTEGRATIONS.md index 642754451..e11c79f31 100644 --- a/COMMUNITY_INTEGRATIONS.md +++ b/COMMUNITY_INTEGRATIONS.md @@ -260,9 +260,11 @@ class MySTTService(STTService): _settings: MySTTSettings - def __init__(self, *, model: str, region: str, **kwargs): + def __init__(self, *, model: str, language: str, region: str, **kwargs): super().__init__(**kwargs) - self._settings = MySTTSettings(model=model, region=region) + # Initial value must be provided for every field in self._settings + # before service is started + self._settings = MySTTSettings(model=model, language=language, region=region) self._sync_model_name_to_metrics() ``` @@ -298,7 +300,7 @@ async def _update_settings(self, update: STTSettings) -> dict[str, Any]: if "language" in changed: await self._update_language() else: - # TODO: handle changes to other settings soon! + # TODO: this should be temporary - handle changes to other settings soon! self._warn_unhandled_updated_settings(changed.keys() - {"language"}) return changed diff --git a/changelog/3714.added.md b/changelog/3714.added.md index 83084675a..efa54b7d5 100644 --- a/changelog/3714.added.md +++ b/changelog/3714.added.md @@ -12,7 +12,7 @@ ```python await task.queue_frame( - STTUpdateSettingsFrame(update=DeepgramSTTSettings(language=Language.ES)) + STTUpdateSettingsFrame(delta=DeepgramSTTSettings(language=Language.ES)) ) ``` diff --git a/changelog/3714.deprecated.2.md b/changelog/3714.deprecated.2.md index 232c1dee5..d386fa5a4 100644 --- a/changelog/3714.deprecated.2.md +++ b/changelog/3714.deprecated.2.md @@ -1 +1 @@ -- Dict-based `*UpdateSettingsFrame(settings={...})` is deprecated in favor of passing typed settings delta objects with `*UpdateSettingsFrame(update={...})`. +- Dict-based `*UpdateSettingsFrame(settings={...})` is deprecated in favor of passing typed settings delta objects with `*UpdateSettingsFrame(delta={...})`. diff --git a/examples/foundational/55a-update-settings-deepgram-flux-stt.py b/examples/foundational/55a-update-settings-deepgram-flux-stt.py index d5fb66a2e..a482e513c 100644 --- a/examples/foundational/55a-update-settings-deepgram-flux-stt.py +++ b/examples/foundational/55a-update-settings-deepgram-flux-stt.py @@ -103,7 +103,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): await asyncio.sleep(10) logger.info("Updating Deepgram Flux STT settings: language=es") await task.queue_frame( - STTUpdateSettingsFrame(update=DeepgramFluxSTTSettings(language=Language.ES)) + STTUpdateSettingsFrame(delta=DeepgramFluxSTTSettings(language=Language.ES)) ) @transport.event_handler("on_client_disconnected") diff --git a/examples/foundational/55a-update-settings-deepgram-sagemaker-stt.py b/examples/foundational/55a-update-settings-deepgram-sagemaker-stt.py index 8e45b5f2a..05c92e7e2 100644 --- a/examples/foundational/55a-update-settings-deepgram-sagemaker-stt.py +++ b/examples/foundational/55a-update-settings-deepgram-sagemaker-stt.py @@ -109,7 +109,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): await asyncio.sleep(10) logger.info("Updating Deepgram SageMaker STT settings: language=es") await task.queue_frame( - STTUpdateSettingsFrame(update=DeepgramSageMakerSTTSettings(language=Language.ES)) + STTUpdateSettingsFrame(delta=DeepgramSageMakerSTTSettings(language=Language.ES)) ) @transport.event_handler("on_client_disconnected") diff --git a/examples/foundational/55a-update-settings-deepgram-stt.py b/examples/foundational/55a-update-settings-deepgram-stt.py index aea9475a8..39dde69e9 100644 --- a/examples/foundational/55a-update-settings-deepgram-stt.py +++ b/examples/foundational/55a-update-settings-deepgram-stt.py @@ -103,7 +103,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): await asyncio.sleep(10) logger.info("Updating Deepgram STT settings: language=es") await task.queue_frame( - STTUpdateSettingsFrame(update=DeepgramSTTSettings(language=Language.ES)) + STTUpdateSettingsFrame(delta=DeepgramSTTSettings(language=Language.ES)) ) @transport.event_handler("on_client_disconnected") diff --git a/examples/foundational/55b-update-settings-azure-stt.py b/examples/foundational/55b-update-settings-azure-stt.py index 7fd0d2ca4..96e4041d0 100644 --- a/examples/foundational/55b-update-settings-azure-stt.py +++ b/examples/foundational/55b-update-settings-azure-stt.py @@ -105,9 +105,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): await asyncio.sleep(10) logger.info("Updating Azure STT settings: language=es") - await task.queue_frame( - STTUpdateSettingsFrame(update=AzureSTTSettings(language=Language.ES)) - ) + await task.queue_frame(STTUpdateSettingsFrame(delta=AzureSTTSettings(language=Language.ES))) @transport.event_handler("on_client_disconnected") async def on_client_disconnected(transport, client): diff --git a/examples/foundational/55c-update-settings-google-stt.py b/examples/foundational/55c-update-settings-google-stt.py index dd33bfe75..dede5b173 100644 --- a/examples/foundational/55c-update-settings-google-stt.py +++ b/examples/foundational/55c-update-settings-google-stt.py @@ -103,7 +103,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): await asyncio.sleep(10) logger.info("Updating Google STT settings: language=es") await task.queue_frame( - STTUpdateSettingsFrame(update=GoogleSTTSettings(language=Language.ES)) + STTUpdateSettingsFrame(delta=GoogleSTTSettings(language=Language.ES)) ) @transport.event_handler("on_client_disconnected") diff --git a/examples/foundational/55d-update-settings-assemblyai-stt.py b/examples/foundational/55d-update-settings-assemblyai-stt.py index 6d6a2532e..d37c3ec7b 100644 --- a/examples/foundational/55d-update-settings-assemblyai-stt.py +++ b/examples/foundational/55d-update-settings-assemblyai-stt.py @@ -103,7 +103,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): await asyncio.sleep(10) logger.info("Updating AssemblyAI STT settings: language=es") await task.queue_frame( - STTUpdateSettingsFrame(update=AssemblyAISTTSettings(language=Language.ES)) + STTUpdateSettingsFrame(delta=AssemblyAISTTSettings(language=Language.ES)) ) @transport.event_handler("on_client_disconnected") diff --git a/examples/foundational/55e-update-settings-gladia-stt.py b/examples/foundational/55e-update-settings-gladia-stt.py index a2c6f21fe..e5bd5486a 100644 --- a/examples/foundational/55e-update-settings-gladia-stt.py +++ b/examples/foundational/55e-update-settings-gladia-stt.py @@ -103,7 +103,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): await asyncio.sleep(10) logger.info("Updating Gladia STT settings: language=es") await task.queue_frame( - STTUpdateSettingsFrame(update=GladiaSTTSettings(language=Language.ES)) + STTUpdateSettingsFrame(delta=GladiaSTTSettings(language=Language.ES)) ) @transport.event_handler("on_client_disconnected") diff --git a/examples/foundational/55f-update-settings-elevenlabs-realtime-stt.py b/examples/foundational/55f-update-settings-elevenlabs-realtime-stt.py index 9aee04fbb..c3f0a6325 100644 --- a/examples/foundational/55f-update-settings-elevenlabs-realtime-stt.py +++ b/examples/foundational/55f-update-settings-elevenlabs-realtime-stt.py @@ -106,7 +106,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): await asyncio.sleep(10) logger.info("Updating ElevenLabs Realtime STT settings: language=es") await task.queue_frame( - STTUpdateSettingsFrame(update=ElevenLabsRealtimeSTTSettings(language=Language.ES)) + STTUpdateSettingsFrame(delta=ElevenLabsRealtimeSTTSettings(language=Language.ES)) ) @transport.event_handler("on_client_disconnected") diff --git a/examples/foundational/55g-update-settings-elevenlabs-stt.py b/examples/foundational/55g-update-settings-elevenlabs-stt.py index 33844935a..9435bc1ac 100644 --- a/examples/foundational/55g-update-settings-elevenlabs-stt.py +++ b/examples/foundational/55g-update-settings-elevenlabs-stt.py @@ -108,7 +108,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): await asyncio.sleep(10) logger.info("Updating ElevenLabs STT settings: language=es") await task.queue_frame( - STTUpdateSettingsFrame(update=ElevenLabsSTTSettings(language=Language.ES)) + STTUpdateSettingsFrame(delta=ElevenLabsSTTSettings(language=Language.ES)) ) @transport.event_handler("on_client_disconnected") diff --git a/examples/foundational/55h-update-settings-speechmatics-stt.py b/examples/foundational/55h-update-settings-speechmatics-stt.py index d041d69d2..c362d2f9f 100644 --- a/examples/foundational/55h-update-settings-speechmatics-stt.py +++ b/examples/foundational/55h-update-settings-speechmatics-stt.py @@ -110,13 +110,13 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): await asyncio.sleep(10) logger.info("Updating Speechmatics STT settings: language=es") await task.queue_frame( - STTUpdateSettingsFrame(update=SpeechmaticsSTTSettings(language=Language.ES)) + STTUpdateSettingsFrame(delta=SpeechmaticsSTTSettings(language=Language.ES)) ) await asyncio.sleep(10) logger.info("Updating Speechmatics STT settings: focus_speakers=['S1']") await task.queue_frame( - STTUpdateSettingsFrame(update=SpeechmaticsSTTSettings(focus_speakers=["S1"])) + STTUpdateSettingsFrame(delta=SpeechmaticsSTTSettings(focus_speakers=["S1"])) ) await asyncio.sleep(10) @@ -125,7 +125,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): ) await task.queue_frame( STTUpdateSettingsFrame( - update=SpeechmaticsSTTSettings( + delta=SpeechmaticsSTTSettings( speaker_active_format="{text}" ) ) diff --git a/examples/foundational/55i-update-settings-whisper-api-stt.py b/examples/foundational/55i-update-settings-whisper-api-stt.py index 1d5022674..741601c83 100644 --- a/examples/foundational/55i-update-settings-whisper-api-stt.py +++ b/examples/foundational/55i-update-settings-whisper-api-stt.py @@ -108,7 +108,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): await asyncio.sleep(10) logger.info('Updating OpenAI STT settings: language="es"') - await task.queue_frame(STTUpdateSettingsFrame(update=BaseWhisperSTTSettings(language="es"))) + await task.queue_frame(STTUpdateSettingsFrame(delta=BaseWhisperSTTSettings(language="es"))) @transport.event_handler("on_client_disconnected") async def on_client_disconnected(transport, client): diff --git a/examples/foundational/55j-update-settings-sarvam-stt.py b/examples/foundational/55j-update-settings-sarvam-stt.py index e39c5cb5a..cab9656f8 100644 --- a/examples/foundational/55j-update-settings-sarvam-stt.py +++ b/examples/foundational/55j-update-settings-sarvam-stt.py @@ -103,7 +103,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): await asyncio.sleep(10) logger.info("Updating Sarvam STT settings: language=en-IN") await task.queue_frame( - STTUpdateSettingsFrame(update=SarvamSTTSettings(language=Language.EN_IN)) + STTUpdateSettingsFrame(delta=SarvamSTTSettings(language=Language.EN_IN)) ) @transport.event_handler("on_client_disconnected") diff --git a/examples/foundational/55k-update-settings-soniox-stt.py b/examples/foundational/55k-update-settings-soniox-stt.py index 2cbcd44f4..85b5d2ba4 100644 --- a/examples/foundational/55k-update-settings-soniox-stt.py +++ b/examples/foundational/55k-update-settings-soniox-stt.py @@ -103,7 +103,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): await asyncio.sleep(10) logger.info("Updating Soniox STT settings: language=es") await task.queue_frame( - STTUpdateSettingsFrame(update=SonioxSTTSettings(language=Language.ES)) + STTUpdateSettingsFrame(delta=SonioxSTTSettings(language=Language.ES)) ) @transport.event_handler("on_client_disconnected") diff --git a/examples/foundational/55l-update-settings-aws-transcribe-stt.py b/examples/foundational/55l-update-settings-aws-transcribe-stt.py index 0f4c18981..3bfeb2faf 100644 --- a/examples/foundational/55l-update-settings-aws-transcribe-stt.py +++ b/examples/foundational/55l-update-settings-aws-transcribe-stt.py @@ -103,7 +103,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): await asyncio.sleep(10) logger.info("Updating AWS Transcribe STT settings: language=es") await task.queue_frame( - STTUpdateSettingsFrame(update=AWSTranscribeSTTSettings(language=Language.ES)) + STTUpdateSettingsFrame(delta=AWSTranscribeSTTSettings(language=Language.ES)) ) @transport.event_handler("on_client_disconnected") diff --git a/examples/foundational/55m-update-settings-cartesia-stt.py b/examples/foundational/55m-update-settings-cartesia-stt.py index 6ba27a85e..a87847a5a 100644 --- a/examples/foundational/55m-update-settings-cartesia-stt.py +++ b/examples/foundational/55m-update-settings-cartesia-stt.py @@ -103,7 +103,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): await asyncio.sleep(10) logger.info("Updating Cartesia STT settings: language=es") await task.queue_frame( - STTUpdateSettingsFrame(update=CartesiaSTTSettings(language=Language.ES)) + STTUpdateSettingsFrame(delta=CartesiaSTTSettings(language=Language.ES)) ) @transport.event_handler("on_client_disconnected") diff --git a/examples/foundational/55n-update-settings-cartesia-http-tts.py b/examples/foundational/55n-update-settings-cartesia-http-tts.py index 27cee5b8f..02d3bca2a 100644 --- a/examples/foundational/55n-update-settings-cartesia-http-tts.py +++ b/examples/foundational/55n-update-settings-cartesia-http-tts.py @@ -107,7 +107,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): logger.info("Updating Cartesia HTTP TTS settings: speed increased to 1.5") await task.queue_frame( TTSUpdateSettingsFrame( - update=CartesiaTTSSettings(generation_config=GenerationConfig(speed=1.5)) + delta=CartesiaTTSSettings(generation_config=GenerationConfig(speed=1.5)) ) ) diff --git a/examples/foundational/55n-update-settings-cartesia-tts.py b/examples/foundational/55n-update-settings-cartesia-tts.py index 303c23a25..04e9d8fee 100644 --- a/examples/foundational/55n-update-settings-cartesia-tts.py +++ b/examples/foundational/55n-update-settings-cartesia-tts.py @@ -106,7 +106,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): logger.info("Updating Cartesia TTS settings: speed increased to 1.5") await task.queue_frame( TTSUpdateSettingsFrame( - update=CartesiaTTSSettings(generation_config=GenerationConfig(speed=1.5)) + delta=CartesiaTTSSettings(generation_config=GenerationConfig(speed=1.5)) ) ) diff --git a/examples/foundational/55o-update-settings-elevenlabs-http-tts.py b/examples/foundational/55o-update-settings-elevenlabs-http-tts.py index a67202702..2ca51730f 100644 --- a/examples/foundational/55o-update-settings-elevenlabs-http-tts.py +++ b/examples/foundational/55o-update-settings-elevenlabs-http-tts.py @@ -107,7 +107,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): await asyncio.sleep(10) logger.info("Updating ElevenLabs TTS settings: speed=0.7") await task.queue_frame( - TTSUpdateSettingsFrame(update=ElevenLabsHttpTTSSettings(speed=0.7)) + TTSUpdateSettingsFrame(delta=ElevenLabsHttpTTSSettings(speed=0.7)) ) @transport.event_handler("on_client_disconnected") diff --git a/examples/foundational/55o-update-settings-elevenlabs-tts.py b/examples/foundational/55o-update-settings-elevenlabs-tts.py index 3fefa1ffb..ddbfd8b8f 100644 --- a/examples/foundational/55o-update-settings-elevenlabs-tts.py +++ b/examples/foundational/55o-update-settings-elevenlabs-tts.py @@ -102,13 +102,13 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): await asyncio.sleep(10) logger.info("Updating ElevenLabs TTS settings: speed=0.7") - await task.queue_frame(TTSUpdateSettingsFrame(update=ElevenLabsTTSSettings(speed=0.7))) + await task.queue_frame(TTSUpdateSettingsFrame(delta=ElevenLabsTTSSettings(speed=0.7))) await asyncio.sleep(10) logger.info("Updating ElevenLabs TTS settings: switching to a different voice") await task.queue_frame( TTSUpdateSettingsFrame( - update=ElevenLabsTTSSettings(voice=os.getenv("ELEVENLABS_VOICE_ID_ALT")) + delta=ElevenLabsTTSSettings(voice=os.getenv("ELEVENLABS_VOICE_ID_ALT")) ) ) diff --git a/examples/foundational/55p-update-settings-openai-tts.py b/examples/foundational/55p-update-settings-openai-tts.py index 5aef081fc..fcc24fb76 100644 --- a/examples/foundational/55p-update-settings-openai-tts.py +++ b/examples/foundational/55p-update-settings-openai-tts.py @@ -99,7 +99,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): await asyncio.sleep(10) logger.info("Updating OpenAI TTS settings: speed=2.0") - await task.queue_frame(TTSUpdateSettingsFrame(update=OpenAITTSSettings(speed=2.0))) + await task.queue_frame(TTSUpdateSettingsFrame(delta=OpenAITTSSettings(speed=2.0))) @transport.event_handler("on_client_disconnected") async def on_client_disconnected(transport, client): diff --git a/examples/foundational/55q-update-settings-deepgram-http-tts.py b/examples/foundational/55q-update-settings-deepgram-http-tts.py index 64bbea587..d94bf631a 100644 --- a/examples/foundational/55q-update-settings-deepgram-http-tts.py +++ b/examples/foundational/55q-update-settings-deepgram-http-tts.py @@ -106,13 +106,13 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): await asyncio.sleep(10) logger.info('Updating Deepgram TTS settings: voice="aura-2-aries-en"') await task.queue_frame( - TTSUpdateSettingsFrame(update=DeepgramTTSSettings(voice="aura-2-aries-en")) + TTSUpdateSettingsFrame(delta=DeepgramTTSSettings(voice="aura-2-aries-en")) ) await asyncio.sleep(10) logger.info('Updating Deepgram TTS settings: voice="aura-2-luna-en"') await task.queue_frame( - TTSUpdateSettingsFrame(update=DeepgramTTSSettings(voice="aura-2-luna-en")) + TTSUpdateSettingsFrame(delta=DeepgramTTSSettings(voice="aura-2-luna-en")) ) @transport.event_handler("on_client_disconnected") diff --git a/examples/foundational/55q-update-settings-deepgram-sagemaker-tts.py b/examples/foundational/55q-update-settings-deepgram-sagemaker-tts.py index 35fb7cebe..85087d0d2 100644 --- a/examples/foundational/55q-update-settings-deepgram-sagemaker-tts.py +++ b/examples/foundational/55q-update-settings-deepgram-sagemaker-tts.py @@ -106,13 +106,13 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): await asyncio.sleep(10) logger.info('Updating Deepgram SageMaker TTS settings: voice="aura-2-aries-en"') await task.queue_frame( - TTSUpdateSettingsFrame(update=DeepgramSageMakerTTSSettings(voice="aura-2-aries-en")) + TTSUpdateSettingsFrame(delta=DeepgramSageMakerTTSSettings(voice="aura-2-aries-en")) ) await asyncio.sleep(10) logger.info('Updating Deepgram SageMaker TTS settings: voice="aura-2-luna-en"') await task.queue_frame( - TTSUpdateSettingsFrame(update=DeepgramSageMakerTTSSettings(voice="aura-2-luna-en")) + TTSUpdateSettingsFrame(delta=DeepgramSageMakerTTSSettings(voice="aura-2-luna-en")) ) @transport.event_handler("on_client_disconnected") diff --git a/examples/foundational/55q-update-settings-deepgram-tts.py b/examples/foundational/55q-update-settings-deepgram-tts.py index 9d94a50da..e205ffa73 100644 --- a/examples/foundational/55q-update-settings-deepgram-tts.py +++ b/examples/foundational/55q-update-settings-deepgram-tts.py @@ -99,13 +99,13 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): await asyncio.sleep(10) logger.info('Updating Deepgram TTS settings: voice="aura-2-aries-en"') await task.queue_frame( - TTSUpdateSettingsFrame(update=DeepgramTTSSettings(voice="aura-2-aries-en")) + TTSUpdateSettingsFrame(delta=DeepgramTTSSettings(voice="aura-2-aries-en")) ) await asyncio.sleep(10) logger.info('Updating Deepgram TTS settings: voice="aura-2-luna-en"') await task.queue_frame( - TTSUpdateSettingsFrame(update=DeepgramTTSSettings(voice="aura-2-luna-en")) + TTSUpdateSettingsFrame(delta=DeepgramTTSSettings(voice="aura-2-luna-en")) ) @transport.event_handler("on_client_disconnected") diff --git a/examples/foundational/55r-update-settings-azure-http-tts.py b/examples/foundational/55r-update-settings-azure-http-tts.py index 3132580ed..0e4df5e7c 100644 --- a/examples/foundational/55r-update-settings-azure-http-tts.py +++ b/examples/foundational/55r-update-settings-azure-http-tts.py @@ -102,7 +102,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): await asyncio.sleep(10) logger.info('Updating Azure TTS settings: rate="0.7", style="sad"') await task.queue_frame( - TTSUpdateSettingsFrame(update=AzureTTSSettings(rate="0.7", style="sad")) + TTSUpdateSettingsFrame(delta=AzureTTSSettings(rate="0.7", style="sad")) ) @transport.event_handler("on_client_disconnected") diff --git a/examples/foundational/55r-update-settings-azure-tts.py b/examples/foundational/55r-update-settings-azure-tts.py index d156eab43..a32dad5ed 100644 --- a/examples/foundational/55r-update-settings-azure-tts.py +++ b/examples/foundational/55r-update-settings-azure-tts.py @@ -102,7 +102,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): await asyncio.sleep(10) logger.info('Updating Azure TTS settings: rate="0.7", style="sad"') await task.queue_frame( - TTSUpdateSettingsFrame(update=AzureTTSSettings(rate="0.7", style="sad")) + TTSUpdateSettingsFrame(delta=AzureTTSSettings(rate="0.7", style="sad")) ) @transport.event_handler("on_client_disconnected") diff --git a/examples/foundational/55s-update-settings-google-http-tts.py b/examples/foundational/55s-update-settings-google-http-tts.py index 6c302411a..ae3070124 100644 --- a/examples/foundational/55s-update-settings-google-http-tts.py +++ b/examples/foundational/55s-update-settings-google-http-tts.py @@ -99,7 +99,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): await asyncio.sleep(10) logger.info("Updating Google HTTP TTS settings: speaking_rate=1.4") await task.queue_frame( - TTSUpdateSettingsFrame(update=GoogleHttpTTSSettings(speaking_rate=1.4)) + TTSUpdateSettingsFrame(delta=GoogleHttpTTSSettings(speaking_rate=1.4)) ) @transport.event_handler("on_client_disconnected") diff --git a/examples/foundational/55s-update-settings-google-stream-tts.py b/examples/foundational/55s-update-settings-google-stream-tts.py index 42e07c64b..1aba64254 100644 --- a/examples/foundational/55s-update-settings-google-stream-tts.py +++ b/examples/foundational/55s-update-settings-google-stream-tts.py @@ -99,7 +99,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): await asyncio.sleep(10) logger.info("Updating Google Stream TTS settings: speaking_rate=1.4") await task.queue_frame( - TTSUpdateSettingsFrame(update=GoogleStreamTTSSettings(speaking_rate=1.4)) + TTSUpdateSettingsFrame(delta=GoogleStreamTTSSettings(speaking_rate=1.4)) ) @transport.event_handler("on_client_disconnected") diff --git a/examples/foundational/55t-update-settings-playht-tts.py b/examples/foundational/55t-update-settings-playht-tts.py index ec468a81c..d79120d99 100644 --- a/examples/foundational/55t-update-settings-playht-tts.py +++ b/examples/foundational/55t-update-settings-playht-tts.py @@ -102,7 +102,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): await asyncio.sleep(10) logger.info("Updating PlayHT TTS settings: speed=1.3") - await task.queue_frame(TTSUpdateSettingsFrame(update=PlayHTTTSSettings(speed=1.3))) + await task.queue_frame(TTSUpdateSettingsFrame(delta=PlayHTTTSSettings(speed=1.3))) @transport.event_handler("on_client_disconnected") async def on_client_disconnected(transport, client): diff --git a/examples/foundational/55u-update-settings-rime-http-tts.py b/examples/foundational/55u-update-settings-rime-http-tts.py index 7b1c9b0fe..28e58ba08 100644 --- a/examples/foundational/55u-update-settings-rime-http-tts.py +++ b/examples/foundational/55u-update-settings-rime-http-tts.py @@ -104,7 +104,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): await asyncio.sleep(10) logger.info("Updating Rime TTS settings: voice=rex") - await task.queue_frame(TTSUpdateSettingsFrame(update=RimeTTSSettings(voice="rex"))) + await task.queue_frame(TTSUpdateSettingsFrame(delta=RimeTTSSettings(voice="rex"))) @transport.event_handler("on_client_disconnected") async def on_client_disconnected(transport, client): diff --git a/examples/foundational/55u-update-settings-rime-tts.py b/examples/foundational/55u-update-settings-rime-tts.py index 0704645f5..8992cb6db 100644 --- a/examples/foundational/55u-update-settings-rime-tts.py +++ b/examples/foundational/55u-update-settings-rime-tts.py @@ -101,7 +101,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): await asyncio.sleep(10) logger.info("Updating Rime TTS settings: voice=bond") - await task.queue_frame(TTSUpdateSettingsFrame(update=RimeTTSSettings(voice="bond"))) + await task.queue_frame(TTSUpdateSettingsFrame(delta=RimeTTSSettings(voice="bond"))) @transport.event_handler("on_client_disconnected") async def on_client_disconnected(transport, client): diff --git a/examples/foundational/55v-update-settings-lmnt-tts.py b/examples/foundational/55v-update-settings-lmnt-tts.py index d98462e20..01bc15ddf 100644 --- a/examples/foundational/55v-update-settings-lmnt-tts.py +++ b/examples/foundational/55v-update-settings-lmnt-tts.py @@ -101,7 +101,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): await asyncio.sleep(10) logger.info('Updating LMNT TTS settings: voice="tyler"') - await task.queue_frame(TTSUpdateSettingsFrame(update=LmntTTSSettings(voice="tyler"))) + await task.queue_frame(TTSUpdateSettingsFrame(delta=LmntTTSSettings(voice="tyler"))) @transport.event_handler("on_client_disconnected") async def on_client_disconnected(transport, client): diff --git a/examples/foundational/55w-update-settings-fish-tts.py b/examples/foundational/55w-update-settings-fish-tts.py index 82722ec34..72a2160ba 100644 --- a/examples/foundational/55w-update-settings-fish-tts.py +++ b/examples/foundational/55w-update-settings-fish-tts.py @@ -102,7 +102,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): await asyncio.sleep(10) logger.info("Updating Fish Audio TTS settings: prosody_speed=1.5") await task.queue_frame( - TTSUpdateSettingsFrame(update=FishAudioTTSSettings(prosody_speed=1.5)) + TTSUpdateSettingsFrame(delta=FishAudioTTSSettings(prosody_speed=1.5)) ) @transport.event_handler("on_client_disconnected") diff --git a/examples/foundational/55x-update-settings-minimax-tts.py b/examples/foundational/55x-update-settings-minimax-tts.py index 306b8f2bd..fdb486415 100644 --- a/examples/foundational/55x-update-settings-minimax-tts.py +++ b/examples/foundational/55x-update-settings-minimax-tts.py @@ -105,7 +105,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): await asyncio.sleep(10) logger.info('Updating MiniMax TTS settings: speed=1.5, emotion="happy"') await task.queue_frame( - TTSUpdateSettingsFrame(update=MiniMaxTTSSettings(speed=1.5, emotion="happy")) + TTSUpdateSettingsFrame(delta=MiniMaxTTSSettings(speed=1.5, emotion="happy")) ) @transport.event_handler("on_client_disconnected") diff --git a/examples/foundational/55y-update-settings-groq-tts.py b/examples/foundational/55y-update-settings-groq-tts.py index e6ce851c6..86dc1f98a 100644 --- a/examples/foundational/55y-update-settings-groq-tts.py +++ b/examples/foundational/55y-update-settings-groq-tts.py @@ -98,7 +98,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): await asyncio.sleep(10) logger.info("Updating Groq TTS settings: speed=1.5") - await task.queue_frame(TTSUpdateSettingsFrame(update=GroqTTSSettings(speed=1.5))) + await task.queue_frame(TTSUpdateSettingsFrame(delta=GroqTTSSettings(speed=1.5))) @transport.event_handler("on_client_disconnected") async def on_client_disconnected(transport, client): diff --git a/examples/foundational/55z-update-settings-hume-tts.py b/examples/foundational/55z-update-settings-hume-tts.py index 427b99bab..493550469 100644 --- a/examples/foundational/55z-update-settings-hume-tts.py +++ b/examples/foundational/55z-update-settings-hume-tts.py @@ -103,7 +103,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): logger.info('Updating Hume TTS settings: speed=2.0, description="Speak with excitement"') await task.queue_frame( TTSUpdateSettingsFrame( - update=HumeTTSSettings(speed=2.0, description="Speak with excitement") + delta=HumeTTSSettings(speed=2.0, description="Speak with excitement") ) ) diff --git a/examples/foundational/55za-update-settings-neuphonic-http-tts.py b/examples/foundational/55za-update-settings-neuphonic-http-tts.py index 056b32349..6e1d18e4a 100644 --- a/examples/foundational/55za-update-settings-neuphonic-http-tts.py +++ b/examples/foundational/55za-update-settings-neuphonic-http-tts.py @@ -103,7 +103,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): await asyncio.sleep(10) logger.info("Updating Neuphonic HTTP TTS settings: speed=1.4") - await task.queue_frame(TTSUpdateSettingsFrame(update=NeuphonicTTSSettings(speed=1.4))) + await task.queue_frame(TTSUpdateSettingsFrame(delta=NeuphonicTTSSettings(speed=1.4))) @transport.event_handler("on_client_disconnected") async def on_client_disconnected(transport, client): diff --git a/examples/foundational/55za-update-settings-neuphonic-tts.py b/examples/foundational/55za-update-settings-neuphonic-tts.py index 187594c7e..861167a20 100644 --- a/examples/foundational/55za-update-settings-neuphonic-tts.py +++ b/examples/foundational/55za-update-settings-neuphonic-tts.py @@ -98,7 +98,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): await asyncio.sleep(10) logger.info("Updating Neuphonic TTS settings: speed=1.4") - await task.queue_frame(TTSUpdateSettingsFrame(update=NeuphonicTTSSettings(speed=1.4))) + await task.queue_frame(TTSUpdateSettingsFrame(delta=NeuphonicTTSSettings(speed=1.4))) @transport.event_handler("on_client_disconnected") async def on_client_disconnected(transport, client): diff --git a/examples/foundational/55zb-update-settings-inworld-http-tts.py b/examples/foundational/55zb-update-settings-inworld-http-tts.py index 933a27013..99353b87f 100644 --- a/examples/foundational/55zb-update-settings-inworld-http-tts.py +++ b/examples/foundational/55zb-update-settings-inworld-http-tts.py @@ -103,9 +103,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): await asyncio.sleep(10) logger.info("Updating Inworld TTS settings: speaking_rate=1.5, temperature=0.8") await task.queue_frame( - TTSUpdateSettingsFrame( - update=InworldTTSSettings(speaking_rate=1.5, temperature=0.8) - ) + TTSUpdateSettingsFrame(delta=InworldTTSSettings(speaking_rate=1.5, temperature=0.8)) ) @transport.event_handler("on_client_disconnected") diff --git a/examples/foundational/55zb-update-settings-inworld-tts.py b/examples/foundational/55zb-update-settings-inworld-tts.py index f8a66bdd8..104001c15 100644 --- a/examples/foundational/55zb-update-settings-inworld-tts.py +++ b/examples/foundational/55zb-update-settings-inworld-tts.py @@ -99,7 +99,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): await asyncio.sleep(10) logger.info("Updating Inworld TTS settings: speaking_rate=1.5, temperature=0.8") await task.queue_frame( - TTSUpdateSettingsFrame(update=InworldTTSSettings(speaking_rate=1.5, temperature=0.8)) + TTSUpdateSettingsFrame(delta=InworldTTSSettings(speaking_rate=1.5, temperature=0.8)) ) @transport.event_handler("on_client_disconnected") diff --git a/examples/foundational/55zc-update-settings-gemini-tts.py b/examples/foundational/55zc-update-settings-gemini-tts.py index 6af28e69f..21b678047 100644 --- a/examples/foundational/55zc-update-settings-gemini-tts.py +++ b/examples/foundational/55zc-update-settings-gemini-tts.py @@ -108,7 +108,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): await asyncio.sleep(10) logger.info('Updating Gemini TTS settings: prompt="Speak slowly and dramatically"') await task.queue_frame( - TTSUpdateSettingsFrame(update=GeminiTTSSettings(prompt="Speak slowly and dramatically")) + TTSUpdateSettingsFrame(delta=GeminiTTSSettings(prompt="Speak slowly and dramatically")) ) @transport.event_handler("on_client_disconnected") diff --git a/examples/foundational/55zd-update-settings-aws-polly-tts.py b/examples/foundational/55zd-update-settings-aws-polly-tts.py index 3d9f72cf4..4392e7b6f 100644 --- a/examples/foundational/55zd-update-settings-aws-polly-tts.py +++ b/examples/foundational/55zd-update-settings-aws-polly-tts.py @@ -98,7 +98,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): await asyncio.sleep(10) logger.info('Updating AWS Polly TTS settings: rate="fast"') - await task.queue_frame(TTSUpdateSettingsFrame(update=AWSPollyTTSSettings(rate="fast"))) + await task.queue_frame(TTSUpdateSettingsFrame(delta=AWSPollyTTSSettings(rate="fast"))) @transport.event_handler("on_client_disconnected") async def on_client_disconnected(transport, client): diff --git a/examples/foundational/55ze-update-settings-sarvam-http-tts.py b/examples/foundational/55ze-update-settings-sarvam-http-tts.py index 0afce361a..7832a805a 100644 --- a/examples/foundational/55ze-update-settings-sarvam-http-tts.py +++ b/examples/foundational/55ze-update-settings-sarvam-http-tts.py @@ -102,7 +102,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): await asyncio.sleep(10) logger.info("Updating Sarvam TTS settings: pace=1.5") - await task.queue_frame(TTSUpdateSettingsFrame(update=SarvamHttpTTSSettings(pace=1.5))) + await task.queue_frame(TTSUpdateSettingsFrame(delta=SarvamHttpTTSSettings(pace=1.5))) @transport.event_handler("on_client_disconnected") async def on_client_disconnected(transport, client): diff --git a/examples/foundational/55ze-update-settings-sarvam-tts.py b/examples/foundational/55ze-update-settings-sarvam-tts.py index 98408c4b8..e63c6046d 100644 --- a/examples/foundational/55ze-update-settings-sarvam-tts.py +++ b/examples/foundational/55ze-update-settings-sarvam-tts.py @@ -98,7 +98,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): await asyncio.sleep(10) logger.info("Updating Sarvam TTS settings: pace=1.5") - await task.queue_frame(TTSUpdateSettingsFrame(update=SarvamTTSSettings(pace=1.5))) + await task.queue_frame(TTSUpdateSettingsFrame(delta=SarvamTTSSettings(pace=1.5))) @transport.event_handler("on_client_disconnected") async def on_client_disconnected(transport, client): diff --git a/examples/foundational/55zf-update-settings-camb-tts.py b/examples/foundational/55zf-update-settings-camb-tts.py index 1fe758849..82cc4a638 100644 --- a/examples/foundational/55zf-update-settings-camb-tts.py +++ b/examples/foundational/55zf-update-settings-camb-tts.py @@ -99,7 +99,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): await asyncio.sleep(10) logger.info("Updating Camb TTS settings: language -> Spanish") - await task.queue_frame(TTSUpdateSettingsFrame(update=CambTTSSettings(language=Language.ES))) + await task.queue_frame(TTSUpdateSettingsFrame(delta=CambTTSSettings(language=Language.ES))) @transport.event_handler("on_client_disconnected") async def on_client_disconnected(transport, client): diff --git a/examples/foundational/55zg-update-settings-hathora-tts.py b/examples/foundational/55zg-update-settings-hathora-tts.py index 363ac7d85..9f6b6bd0a 100644 --- a/examples/foundational/55zg-update-settings-hathora-tts.py +++ b/examples/foundational/55zg-update-settings-hathora-tts.py @@ -101,7 +101,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): await asyncio.sleep(10) logger.info("Updating Hathora TTS settings: speed=1.3") - await task.queue_frame(TTSUpdateSettingsFrame(update=HathoraTTSSettings(speed=1.3))) + await task.queue_frame(TTSUpdateSettingsFrame(delta=HathoraTTSSettings(speed=1.3))) @transport.event_handler("on_client_disconnected") async def on_client_disconnected(transport, client): diff --git a/examples/foundational/55zh-update-settings-resembleai-tts.py b/examples/foundational/55zh-update-settings-resembleai-tts.py index 39b745500..44688ee25 100644 --- a/examples/foundational/55zh-update-settings-resembleai-tts.py +++ b/examples/foundational/55zh-update-settings-resembleai-tts.py @@ -103,7 +103,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): logger.info("Updating ResembleAI TTS settings: voice (changed)") await task.queue_frame( TTSUpdateSettingsFrame( - update=ResembleAITTSSettings(voice=os.getenv("RESEMBLE_VOICE_UUID_ALT")) + delta=ResembleAITTSSettings(voice=os.getenv("RESEMBLE_VOICE_UUID_ALT")) ) ) diff --git a/examples/foundational/55zi-update-settings-azure-llm.py b/examples/foundational/55zi-update-settings-azure-llm.py index 94cb723e3..43161b103 100644 --- a/examples/foundational/55zi-update-settings-azure-llm.py +++ b/examples/foundational/55zi-update-settings-azure-llm.py @@ -106,7 +106,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): await asyncio.sleep(10) logger.info("Updating Azure LLM settings: temperature=0.1") - await task.queue_frame(LLMUpdateSettingsFrame(update=OpenAILLMSettings(temperature=0.1))) + await task.queue_frame(LLMUpdateSettingsFrame(delta=OpenAILLMSettings(temperature=0.1))) @transport.event_handler("on_client_disconnected") async def on_client_disconnected(transport, client): diff --git a/examples/foundational/55zi-update-settings-openai-llm.py b/examples/foundational/55zi-update-settings-openai-llm.py index a8c253bc2..d84259cc3 100644 --- a/examples/foundational/55zi-update-settings-openai-llm.py +++ b/examples/foundational/55zi-update-settings-openai-llm.py @@ -102,7 +102,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): await asyncio.sleep(10) logger.info("Updating OpenAI LLM settings: temperature=0.1") - await task.queue_frame(LLMUpdateSettingsFrame(update=OpenAILLMSettings(temperature=0.1))) + await task.queue_frame(LLMUpdateSettingsFrame(delta=OpenAILLMSettings(temperature=0.1))) @transport.event_handler("on_client_disconnected") async def on_client_disconnected(transport, client): diff --git a/examples/foundational/55zj-update-settings-anthropic-llm.py b/examples/foundational/55zj-update-settings-anthropic-llm.py index 4c8341a6a..354702880 100644 --- a/examples/foundational/55zj-update-settings-anthropic-llm.py +++ b/examples/foundational/55zj-update-settings-anthropic-llm.py @@ -101,7 +101,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): await asyncio.sleep(10) logger.info("Updating Anthropic LLM settings: temperature=0.1") - await task.queue_frame(LLMUpdateSettingsFrame(update=AnthropicLLMSettings(temperature=0.1))) + await task.queue_frame(LLMUpdateSettingsFrame(delta=AnthropicLLMSettings(temperature=0.1))) @transport.event_handler("on_client_disconnected") async def on_client_disconnected(transport, client): diff --git a/examples/foundational/55zk-update-settings-google-llm.py b/examples/foundational/55zk-update-settings-google-llm.py index 140c0fccb..cd03a34cb 100644 --- a/examples/foundational/55zk-update-settings-google-llm.py +++ b/examples/foundational/55zk-update-settings-google-llm.py @@ -101,7 +101,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): await asyncio.sleep(10) logger.info("Updating Google LLM settings: temperature=0.1") - await task.queue_frame(LLMUpdateSettingsFrame(update=GoogleLLMSettings(temperature=0.1))) + await task.queue_frame(LLMUpdateSettingsFrame(delta=GoogleLLMSettings(temperature=0.1))) @transport.event_handler("on_client_disconnected") async def on_client_disconnected(transport, client): diff --git a/examples/foundational/55zk-update-settings-google-vertex-llm.py b/examples/foundational/55zk-update-settings-google-vertex-llm.py index 41c0b8a37..3feba582f 100644 --- a/examples/foundational/55zk-update-settings-google-vertex-llm.py +++ b/examples/foundational/55zk-update-settings-google-vertex-llm.py @@ -106,7 +106,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): await asyncio.sleep(10) logger.info("Updating Google Vertex LLM settings: temperature=0.1") - await task.queue_frame(LLMUpdateSettingsFrame(update=GoogleLLMSettings(temperature=0.1))) + await task.queue_frame(LLMUpdateSettingsFrame(delta=GoogleLLMSettings(temperature=0.1))) @transport.event_handler("on_client_disconnected") async def on_client_disconnected(transport, client): diff --git a/examples/foundational/55zl-update-settings-azure-realtime.py b/examples/foundational/55zl-update-settings-azure-realtime.py index b8f049db0..247bde14b 100644 --- a/examples/foundational/55zl-update-settings-azure-realtime.py +++ b/examples/foundational/55zl-update-settings-azure-realtime.py @@ -102,7 +102,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): logger.info("Updating Azure Realtime LLM settings: output_modalities=['text']") await task.queue_frame( LLMUpdateSettingsFrame( - update=OpenAIRealtimeLLMSettings( + delta=OpenAIRealtimeLLMSettings( session_properties=events.SessionProperties(output_modalities=["text"]) ) ) @@ -112,7 +112,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): logger.info("Updating Azure Realtime LLM settings: output_modalities=['audio']") await task.queue_frame( LLMUpdateSettingsFrame( - update=OpenAIRealtimeLLMSettings( + delta=OpenAIRealtimeLLMSettings( session_properties=events.SessionProperties(output_modalities=["audio"]) ) ) diff --git a/examples/foundational/55zl-update-settings-openai-realtime.py b/examples/foundational/55zl-update-settings-openai-realtime.py index 9c18d528e..f5c4afa26 100644 --- a/examples/foundational/55zl-update-settings-openai-realtime.py +++ b/examples/foundational/55zl-update-settings-openai-realtime.py @@ -101,7 +101,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): logger.info("Updating OpenAI Realtime LLM settings: output_modalities=['text']") await task.queue_frame( LLMUpdateSettingsFrame( - update=OpenAIRealtimeLLMSettings( + delta=OpenAIRealtimeLLMSettings( session_properties=events.SessionProperties(output_modalities=["text"]) ) ) @@ -111,7 +111,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): logger.info("Updating OpenAI Realtime LLM settings: output_modalities=['audio']") await task.queue_frame( LLMUpdateSettingsFrame( - update=OpenAIRealtimeLLMSettings( + delta=OpenAIRealtimeLLMSettings( session_properties=events.SessionProperties(output_modalities=["audio"]) ) ) diff --git a/examples/foundational/55zm-update-settings-gemini-live-vertex.py b/examples/foundational/55zm-update-settings-gemini-live-vertex.py index 575fbe090..96bd7a1c6 100644 --- a/examples/foundational/55zm-update-settings-gemini-live-vertex.py +++ b/examples/foundational/55zm-update-settings-gemini-live-vertex.py @@ -91,9 +91,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): await asyncio.sleep(10) logger.info("Updating Gemini Live Vertex LLM settings: temperature=0.1") - await task.queue_frame( - LLMUpdateSettingsFrame(update=GeminiLiveLLMSettings(temperature=0.1)) - ) + await task.queue_frame(LLMUpdateSettingsFrame(delta=GeminiLiveLLMSettings(temperature=0.1))) @transport.event_handler("on_client_disconnected") async def on_client_disconnected(transport, client): diff --git a/examples/foundational/55zm-update-settings-gemini-live.py b/examples/foundational/55zm-update-settings-gemini-live.py index 8ad635fd5..a00343ac3 100644 --- a/examples/foundational/55zm-update-settings-gemini-live.py +++ b/examples/foundational/55zm-update-settings-gemini-live.py @@ -89,9 +89,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): await asyncio.sleep(10) logger.info("Updating Gemini Live LLM settings: temperature=0.1") - await task.queue_frame( - LLMUpdateSettingsFrame(update=GeminiLiveLLMSettings(temperature=0.1)) - ) + await task.queue_frame(LLMUpdateSettingsFrame(delta=GeminiLiveLLMSettings(temperature=0.1))) @transport.event_handler("on_client_disconnected") async def on_client_disconnected(transport, client): diff --git a/examples/foundational/55zn-update-settings-ultravox-realtime.py b/examples/foundational/55zn-update-settings-ultravox-realtime.py index 967d40741..5bcbded6b 100644 --- a/examples/foundational/55zn-update-settings-ultravox-realtime.py +++ b/examples/foundational/55zn-update-settings-ultravox-realtime.py @@ -112,13 +112,13 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): await asyncio.sleep(10) logger.info("Updating Ultravox Realtime LLM settings: output_medium=text") await task.queue_frame( - LLMUpdateSettingsFrame(update=UltravoxRealtimeLLMSettings(output_medium="text")) + LLMUpdateSettingsFrame(delta=UltravoxRealtimeLLMSettings(output_medium="text")) ) await asyncio.sleep(10) logger.info("Updating Ultravox Realtime LLM settings: output_medium=voice") await task.queue_frame( - LLMUpdateSettingsFrame(update=UltravoxRealtimeLLMSettings(output_medium="voice")) + LLMUpdateSettingsFrame(delta=UltravoxRealtimeLLMSettings(output_medium="voice")) ) @transport.event_handler("on_client_disconnected") diff --git a/examples/foundational/55zo-update-settings-grok-realtime.py b/examples/foundational/55zo-update-settings-grok-realtime.py index 7d7370f7b..9444f126a 100644 --- a/examples/foundational/55zo-update-settings-grok-realtime.py +++ b/examples/foundational/55zo-update-settings-grok-realtime.py @@ -101,7 +101,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): logger.info("Updating Grok Realtime LLM settings: voice='Rex'") await task.queue_frame( LLMUpdateSettingsFrame( - update=GrokRealtimeLLMSettings( + delta=GrokRealtimeLLMSettings( session_properties=events.SessionProperties(voice="Rex") ) ) diff --git a/examples/foundational/55zp-update-settings-aws-bedrock-llm.py b/examples/foundational/55zp-update-settings-aws-bedrock-llm.py index 1c2781e72..3d3ee8fb5 100644 --- a/examples/foundational/55zp-update-settings-aws-bedrock-llm.py +++ b/examples/foundational/55zp-update-settings-aws-bedrock-llm.py @@ -105,9 +105,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): await asyncio.sleep(10) logger.info("Updating AWS Bedrock LLM settings: temperature=0.1") - await task.queue_frame( - LLMUpdateSettingsFrame(update=AWSBedrockLLMSettings(temperature=0.1)) - ) + await task.queue_frame(LLMUpdateSettingsFrame(delta=AWSBedrockLLMSettings(temperature=0.1))) @transport.event_handler("on_client_disconnected") async def on_client_disconnected(transport, client): diff --git a/examples/foundational/55zq-update-settings-fal-stt.py b/examples/foundational/55zq-update-settings-fal-stt.py index 9792961f2..c0f0a134a 100644 --- a/examples/foundational/55zq-update-settings-fal-stt.py +++ b/examples/foundational/55zq-update-settings-fal-stt.py @@ -101,7 +101,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): await asyncio.sleep(10) logger.info('Updating Fal STT settings: task="translate"') - await task.queue_frame(STTUpdateSettingsFrame(update=FalSTTSettings(task="translate"))) + await task.queue_frame(STTUpdateSettingsFrame(delta=FalSTTSettings(task="translate"))) @transport.event_handler("on_client_disconnected") async def on_client_disconnected(transport, client): diff --git a/examples/foundational/55zr-update-settings-gradium-stt.py b/examples/foundational/55zr-update-settings-gradium-stt.py index 6a1a25c3c..636d27bd8 100644 --- a/examples/foundational/55zr-update-settings-gradium-stt.py +++ b/examples/foundational/55zr-update-settings-gradium-stt.py @@ -104,7 +104,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): await asyncio.sleep(10) logger.info("Updating Gradium STT settings: delay_in_frames=5") - await task.queue_frame(STTUpdateSettingsFrame(update=GradiumSTTSettings(delay_in_frames=5))) + await task.queue_frame(STTUpdateSettingsFrame(delta=GradiumSTTSettings(delay_in_frames=5))) @transport.event_handler("on_client_disconnected") async def on_client_disconnected(transport, client): diff --git a/examples/foundational/55zs-update-settings-hathora-stt.py b/examples/foundational/55zs-update-settings-hathora-stt.py index f3aca9c89..db5ed4d2a 100644 --- a/examples/foundational/55zs-update-settings-hathora-stt.py +++ b/examples/foundational/55zs-update-settings-hathora-stt.py @@ -104,7 +104,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): await asyncio.sleep(10) logger.info("Updating Hathora STT settings: language=es") await task.queue_frame( - STTUpdateSettingsFrame(update=HathoraSTTSettings(language=Language.ES)) + STTUpdateSettingsFrame(delta=HathoraSTTSettings(language=Language.ES)) ) @transport.event_handler("on_client_disconnected") diff --git a/examples/foundational/55zt-update-settings-nvidia-segmented-stt.py b/examples/foundational/55zt-update-settings-nvidia-segmented-stt.py index 624da149e..60a042c5f 100644 --- a/examples/foundational/55zt-update-settings-nvidia-segmented-stt.py +++ b/examples/foundational/55zt-update-settings-nvidia-segmented-stt.py @@ -102,7 +102,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): await asyncio.sleep(10) logger.info("Updating NVIDIA Segmented STT settings: profanity_filter=True") await task.queue_frame( - STTUpdateSettingsFrame(update=NvidiaSegmentedSTTSettings(profanity_filter=True)) + STTUpdateSettingsFrame(delta=NvidiaSegmentedSTTSettings(profanity_filter=True)) ) @transport.event_handler("on_client_disconnected") diff --git a/examples/foundational/55zt-update-settings-nvidia-stt.py b/examples/foundational/55zt-update-settings-nvidia-stt.py index 0e7b6a74a..415f10b12 100644 --- a/examples/foundational/55zt-update-settings-nvidia-stt.py +++ b/examples/foundational/55zt-update-settings-nvidia-stt.py @@ -103,7 +103,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): await asyncio.sleep(10) logger.info("Updating NVIDIA STT settings: language=es") await task.queue_frame( - STTUpdateSettingsFrame(update=NvidiaSTTSettings(language=Language.ES)) + STTUpdateSettingsFrame(delta=NvidiaSTTSettings(language=Language.ES)) ) @transport.event_handler("on_client_disconnected") diff --git a/examples/foundational/55zu-update-settings-openai-realtime-stt.py b/examples/foundational/55zu-update-settings-openai-realtime-stt.py index 1f1592df7..2bcd35f52 100644 --- a/examples/foundational/55zu-update-settings-openai-realtime-stt.py +++ b/examples/foundational/55zu-update-settings-openai-realtime-stt.py @@ -103,7 +103,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): await asyncio.sleep(10) logger.info("Updating OpenAI Realtime STT settings: language=es") await task.queue_frame( - STTUpdateSettingsFrame(update=OpenAIRealtimeSTTSettings(language=Language.ES)) + STTUpdateSettingsFrame(delta=OpenAIRealtimeSTTSettings(language=Language.ES)) ) @transport.event_handler("on_client_disconnected") diff --git a/examples/foundational/55zv-update-settings-asyncai-http-tts.py b/examples/foundational/55zv-update-settings-asyncai-http-tts.py index 206a80eed..9688f1bac 100644 --- a/examples/foundational/55zv-update-settings-asyncai-http-tts.py +++ b/examples/foundational/55zv-update-settings-asyncai-http-tts.py @@ -108,7 +108,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): await asyncio.sleep(10) logger.info("Updating AsyncAI HTTP TTS settings: language=es") await task.queue_frame( - TTSUpdateSettingsFrame(update=AsyncAITTSSettings(language=Language.ES)) + TTSUpdateSettingsFrame(delta=AsyncAITTSSettings(language=Language.ES)) ) @transport.event_handler("on_client_disconnected") diff --git a/examples/foundational/55zv-update-settings-asyncai-tts.py b/examples/foundational/55zv-update-settings-asyncai-tts.py index f910e5fe3..fe096b4be 100644 --- a/examples/foundational/55zv-update-settings-asyncai-tts.py +++ b/examples/foundational/55zv-update-settings-asyncai-tts.py @@ -103,7 +103,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): await asyncio.sleep(10) logger.info("Updating AsyncAI TTS settings: language=es") await task.queue_frame( - TTSUpdateSettingsFrame(update=AsyncAITTSSettings(language=Language.ES)) + TTSUpdateSettingsFrame(delta=AsyncAITTSSettings(language=Language.ES)) ) @transport.event_handler("on_client_disconnected") diff --git a/examples/foundational/55zw-update-settings-gradium-tts.py b/examples/foundational/55zw-update-settings-gradium-tts.py index 39090d5fa..d1069bfa4 100644 --- a/examples/foundational/55zw-update-settings-gradium-tts.py +++ b/examples/foundational/55zw-update-settings-gradium-tts.py @@ -103,7 +103,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): await asyncio.sleep(10) logger.info('Updating Gradium TTS settings: voice="LFZvm12tW_z0xfGo"') await task.queue_frame( - TTSUpdateSettingsFrame(update=GradiumTTSSettings(voice="LFZvm12tW_z0xfGo")) + TTSUpdateSettingsFrame(delta=GradiumTTSSettings(voice="LFZvm12tW_z0xfGo")) ) @transport.event_handler("on_client_disconnected") diff --git a/examples/foundational/55zx-update-settings-cerebras-llm.py b/examples/foundational/55zx-update-settings-cerebras-llm.py index 72aa8518d..6123487a3 100644 --- a/examples/foundational/55zx-update-settings-cerebras-llm.py +++ b/examples/foundational/55zx-update-settings-cerebras-llm.py @@ -102,7 +102,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): await asyncio.sleep(10) logger.info("Updating Cerebras LLM settings: temperature=0.1") - await task.queue_frame(LLMUpdateSettingsFrame(update=OpenAILLMSettings(temperature=0.1))) + await task.queue_frame(LLMUpdateSettingsFrame(delta=OpenAILLMSettings(temperature=0.1))) @transport.event_handler("on_client_disconnected") async def on_client_disconnected(transport, client): diff --git a/examples/foundational/55zy-update-settings-deepseek-llm.py b/examples/foundational/55zy-update-settings-deepseek-llm.py index de4e4149e..60cbab30b 100644 --- a/examples/foundational/55zy-update-settings-deepseek-llm.py +++ b/examples/foundational/55zy-update-settings-deepseek-llm.py @@ -102,7 +102,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): await asyncio.sleep(10) logger.info("Updating DeepSeek LLM settings: temperature=0.1") - await task.queue_frame(LLMUpdateSettingsFrame(update=OpenAILLMSettings(temperature=0.1))) + await task.queue_frame(LLMUpdateSettingsFrame(delta=OpenAILLMSettings(temperature=0.1))) @transport.event_handler("on_client_disconnected") async def on_client_disconnected(transport, client): diff --git a/examples/foundational/55zz-update-settings-fireworks-llm.py b/examples/foundational/55zz-update-settings-fireworks-llm.py index d864cacb2..97554ae19 100644 --- a/examples/foundational/55zz-update-settings-fireworks-llm.py +++ b/examples/foundational/55zz-update-settings-fireworks-llm.py @@ -105,7 +105,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): await asyncio.sleep(10) logger.info("Updating Fireworks LLM settings: temperature=0.1") - await task.queue_frame(LLMUpdateSettingsFrame(update=OpenAILLMSettings(temperature=0.1))) + await task.queue_frame(LLMUpdateSettingsFrame(delta=OpenAILLMSettings(temperature=0.1))) @transport.event_handler("on_client_disconnected") async def on_client_disconnected(transport, client): diff --git a/examples/foundational/55zza-update-settings-grok-llm.py b/examples/foundational/55zza-update-settings-grok-llm.py index dbf07f21d..8ce081e66 100644 --- a/examples/foundational/55zza-update-settings-grok-llm.py +++ b/examples/foundational/55zza-update-settings-grok-llm.py @@ -102,7 +102,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): await asyncio.sleep(10) logger.info("Updating Grok LLM settings: temperature=0.1") - await task.queue_frame(LLMUpdateSettingsFrame(update=OpenAILLMSettings(temperature=0.1))) + await task.queue_frame(LLMUpdateSettingsFrame(delta=OpenAILLMSettings(temperature=0.1))) @transport.event_handler("on_client_disconnected") async def on_client_disconnected(transport, client): diff --git a/examples/foundational/55zzb-update-settings-groq-llm.py b/examples/foundational/55zzb-update-settings-groq-llm.py index 8244f611a..afde4499d 100644 --- a/examples/foundational/55zzb-update-settings-groq-llm.py +++ b/examples/foundational/55zzb-update-settings-groq-llm.py @@ -104,7 +104,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): await asyncio.sleep(10) logger.info("Updating Groq LLM settings: temperature=0.1") - await task.queue_frame(LLMUpdateSettingsFrame(update=OpenAILLMSettings(temperature=0.1))) + await task.queue_frame(LLMUpdateSettingsFrame(delta=OpenAILLMSettings(temperature=0.1))) @transport.event_handler("on_client_disconnected") async def on_client_disconnected(transport, client): diff --git a/examples/foundational/55zzc-update-settings-mistral-llm.py b/examples/foundational/55zzc-update-settings-mistral-llm.py index 642eda3c5..7eba98e97 100644 --- a/examples/foundational/55zzc-update-settings-mistral-llm.py +++ b/examples/foundational/55zzc-update-settings-mistral-llm.py @@ -102,7 +102,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): await asyncio.sleep(10) logger.info("Updating Mistral LLM settings: temperature=0.1") - await task.queue_frame(LLMUpdateSettingsFrame(update=OpenAILLMSettings(temperature=0.1))) + await task.queue_frame(LLMUpdateSettingsFrame(delta=OpenAILLMSettings(temperature=0.1))) @transport.event_handler("on_client_disconnected") async def on_client_disconnected(transport, client): diff --git a/examples/foundational/55zzd-update-settings-nvidia-llm.py b/examples/foundational/55zzd-update-settings-nvidia-llm.py index 5ffa0ff23..ee57a3a24 100644 --- a/examples/foundational/55zzd-update-settings-nvidia-llm.py +++ b/examples/foundational/55zzd-update-settings-nvidia-llm.py @@ -104,7 +104,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): await asyncio.sleep(10) logger.info("Updating NVIDIA LLM settings: temperature=0.1") - await task.queue_frame(LLMUpdateSettingsFrame(update=OpenAILLMSettings(temperature=0.1))) + await task.queue_frame(LLMUpdateSettingsFrame(delta=OpenAILLMSettings(temperature=0.1))) @transport.event_handler("on_client_disconnected") async def on_client_disconnected(transport, client): diff --git a/examples/foundational/55zze-update-settings-ollama-llm.py b/examples/foundational/55zze-update-settings-ollama-llm.py index ca3714943..e22719ec1 100644 --- a/examples/foundational/55zze-update-settings-ollama-llm.py +++ b/examples/foundational/55zze-update-settings-ollama-llm.py @@ -102,7 +102,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): await asyncio.sleep(10) logger.info("Updating OLLama LLM settings: temperature=0.1") - await task.queue_frame(LLMUpdateSettingsFrame(update=OpenAILLMSettings(temperature=0.1))) + await task.queue_frame(LLMUpdateSettingsFrame(delta=OpenAILLMSettings(temperature=0.1))) @transport.event_handler("on_client_disconnected") async def on_client_disconnected(transport, client): diff --git a/examples/foundational/55zzf-update-settings-openrouter-llm.py b/examples/foundational/55zzf-update-settings-openrouter-llm.py index 90606a572..fc3732192 100644 --- a/examples/foundational/55zzf-update-settings-openrouter-llm.py +++ b/examples/foundational/55zzf-update-settings-openrouter-llm.py @@ -102,7 +102,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): await asyncio.sleep(10) logger.info("Updating OpenRouter LLM settings: temperature=0.1") - await task.queue_frame(LLMUpdateSettingsFrame(update=OpenAILLMSettings(temperature=0.1))) + await task.queue_frame(LLMUpdateSettingsFrame(delta=OpenAILLMSettings(temperature=0.1))) @transport.event_handler("on_client_disconnected") async def on_client_disconnected(transport, client): diff --git a/examples/foundational/55zzg-update-settings-perplexity-llm.py b/examples/foundational/55zzg-update-settings-perplexity-llm.py index 771b1c794..f55975685 100644 --- a/examples/foundational/55zzg-update-settings-perplexity-llm.py +++ b/examples/foundational/55zzg-update-settings-perplexity-llm.py @@ -101,7 +101,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): await asyncio.sleep(10) logger.info("Updating Perplexity LLM settings: temperature=0.1") - await task.queue_frame(LLMUpdateSettingsFrame(update=OpenAILLMSettings(temperature=0.1))) + await task.queue_frame(LLMUpdateSettingsFrame(delta=OpenAILLMSettings(temperature=0.1))) @transport.event_handler("on_client_disconnected") async def on_client_disconnected(transport, client): diff --git a/examples/foundational/55zzh-update-settings-qwen-llm.py b/examples/foundational/55zzh-update-settings-qwen-llm.py index 81ace2117..f31dc05a5 100644 --- a/examples/foundational/55zzh-update-settings-qwen-llm.py +++ b/examples/foundational/55zzh-update-settings-qwen-llm.py @@ -102,7 +102,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): await asyncio.sleep(10) logger.info("Updating Qwen LLM settings: temperature=0.1") - await task.queue_frame(LLMUpdateSettingsFrame(update=OpenAILLMSettings(temperature=0.1))) + await task.queue_frame(LLMUpdateSettingsFrame(delta=OpenAILLMSettings(temperature=0.1))) @transport.event_handler("on_client_disconnected") async def on_client_disconnected(transport, client): diff --git a/examples/foundational/55zzi-update-settings-sambanova-llm.py b/examples/foundational/55zzi-update-settings-sambanova-llm.py index 82382a6bd..96122cc03 100644 --- a/examples/foundational/55zzi-update-settings-sambanova-llm.py +++ b/examples/foundational/55zzi-update-settings-sambanova-llm.py @@ -102,7 +102,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): await asyncio.sleep(10) logger.info("Updating SambaNova LLM settings: temperature=0.1") - await task.queue_frame(LLMUpdateSettingsFrame(update=OpenAILLMSettings(temperature=0.1))) + await task.queue_frame(LLMUpdateSettingsFrame(delta=OpenAILLMSettings(temperature=0.1))) @transport.event_handler("on_client_disconnected") async def on_client_disconnected(transport, client): diff --git a/examples/foundational/55zzj-update-settings-together-llm.py b/examples/foundational/55zzj-update-settings-together-llm.py index 1f0a0557f..710ef894a 100644 --- a/examples/foundational/55zzj-update-settings-together-llm.py +++ b/examples/foundational/55zzj-update-settings-together-llm.py @@ -105,7 +105,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): await asyncio.sleep(10) logger.info("Updating Together LLM settings: temperature=0.1") - await task.queue_frame(LLMUpdateSettingsFrame(update=OpenAILLMSettings(temperature=0.1))) + await task.queue_frame(LLMUpdateSettingsFrame(delta=OpenAILLMSettings(temperature=0.1))) @transport.event_handler("on_client_disconnected") async def on_client_disconnected(transport, client): diff --git a/examples/foundational/55zzk-update-settings-aws-nova-sonic-llm.py b/examples/foundational/55zzk-update-settings-aws-nova-sonic-llm.py index 1faafdbac..301270797 100644 --- a/examples/foundational/55zzk-update-settings-aws-nova-sonic-llm.py +++ b/examples/foundational/55zzk-update-settings-aws-nova-sonic-llm.py @@ -99,7 +99,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): await asyncio.sleep(10) logger.info("Updating AWS Nova Sonic LLM settings: temperature=0.1") await task.queue_frame( - LLMUpdateSettingsFrame(update=AWSNovaSonicLLMSettings(temperature=0.1)) + LLMUpdateSettingsFrame(delta=AWSNovaSonicLLMSettings(temperature=0.1)) ) @transport.event_handler("on_client_disconnected") diff --git a/examples/foundational/55zzl-update-settings-nvidia-tts.py b/examples/foundational/55zzl-update-settings-nvidia-tts.py index b92651496..a8bd50dcd 100644 --- a/examples/foundational/55zzl-update-settings-nvidia-tts.py +++ b/examples/foundational/55zzl-update-settings-nvidia-tts.py @@ -100,7 +100,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): await asyncio.sleep(10) logger.info('Updating NVIDIA TTS settings: language="ES_US"') await task.queue_frame( - TTSUpdateSettingsFrame(update=NvidiaTTSSettings(language=Language.ES_US)) + TTSUpdateSettingsFrame(delta=NvidiaTTSSettings(language=Language.ES_US)) ) @transport.event_handler("on_client_disconnected") diff --git a/examples/foundational/55zzm-update-settings-speechmatics-tts.py b/examples/foundational/55zzm-update-settings-speechmatics-tts.py index 36b66fe53..39ed792dd 100644 --- a/examples/foundational/55zzm-update-settings-speechmatics-tts.py +++ b/examples/foundational/55zzm-update-settings-speechmatics-tts.py @@ -104,7 +104,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): await asyncio.sleep(10) logger.info('Updating Speechmatics TTS settings: voice="theo"') await task.queue_frame( - TTSUpdateSettingsFrame(update=SpeechmaticsTTSSettings(voice="theo")) + TTSUpdateSettingsFrame(delta=SpeechmaticsTTSSettings(voice="theo")) ) @transport.event_handler("on_client_disconnected") diff --git a/src/pipecat/frames/frames.py b/src/pipecat/frames/frames.py index 79aedb771..0d6b3f18a 100644 --- a/src/pipecat/frames/frames.py +++ b/src/pipecat/frames/frames.py @@ -2121,21 +2121,21 @@ class TTSStoppedFrame(ControlFrame): class ServiceUpdateSettingsFrame(ControlFrame): """Base frame for updating service settings. - Supports both a ``settings`` dict (for backward compatibility) and an - ``update`` object. When both are provided, ``update`` takes precedence. + Supports both a ``settings`` dict (for backward compatibility) and a + ``delta`` object. When both are provided, ``delta`` takes precedence. Parameters: settings: Dictionary of setting name to value mappings. .. deprecated:: 0.0.103 - Use ``update`` with a typed settings object instead. + Use ``delta`` with a typed settings object instead. - update: :class:`~pipecat.services.settings.ServiceSettings` object - describing the delta to apply. + delta: :class:`~pipecat.services.settings.ServiceSettings` delta-mode + object describing the fields to change. """ settings: Mapping[str, Any] = field(default_factory=dict) - update: Optional["ServiceSettings"] = None + delta: Optional["ServiceSettings"] = None @dataclass diff --git a/src/pipecat/services/ai_service.py b/src/pipecat/services/ai_service.py index 8b32d7222..f092c2b49 100644 --- a/src/pipecat/services/ai_service.py +++ b/src/pipecat/services/ai_service.py @@ -42,7 +42,7 @@ class AIService(FrameProcessor): **kwargs: Additional arguments passed to the parent FrameProcessor. """ super().__init__(**kwargs) - self._settings: ServiceSettings = ServiceSettings(model="") + self._settings: ServiceSettings = ServiceSettings() # Here in case subclass doesn't implement more specific settings (hopefully shouldn't happen) self._session_properties: Dict[str, Any] = {} self._tracing_enabled: bool = False self._tracing_context = None @@ -73,6 +73,7 @@ class AIService(FrameProcessor): Args: frame: The start frame containing initialization parameters. """ + self._settings.validate_complete() self._tracing_enabled = frame.enable_tracing self._tracing_context = frame.tracing_context @@ -98,10 +99,10 @@ class AIService(FrameProcessor): """ pass - async def _update_settings(self, update: ServiceSettings) -> Dict[str, Any]: - """Apply a settings update and return the changed fields. + async def _update_settings(self, delta: ServiceSettings) -> Dict[str, Any]: + """Apply a settings delta and return the changed fields. - The update is applied to ``_settings`` and a dict mapping each changed + The delta is applied to ``_settings`` and a dict mapping each changed field name to its **pre-update** value is returned. The ``model`` field is handled specially: when it changes, ``set_model_name`` is called. @@ -110,12 +111,12 @@ class AIService(FrameProcessor): to react to specific changed fields (e.g. reconnect on voice change). Args: - update: A settings delta. + delta: A delta-mode settings object. Returns: Dict mapping changed field names to their previous values. """ - changed = self._settings.apply_update(update) + changed = self._settings.apply_update(delta) if "model" in changed: self._sync_model_name_to_metrics() diff --git a/src/pipecat/services/anthropic/llm.py b/src/pipecat/services/anthropic/llm.py index e79792bb0..047159515 100644 --- a/src/pipecat/services/anthropic/llm.py +++ b/src/pipecat/services/anthropic/llm.py @@ -254,6 +254,11 @@ class AnthropicLLMService(LLMService): temperature=params.temperature, top_k=params.top_k, top_p=params.top_p, + frequency_penalty=None, + presence_penalty=None, + seed=None, + filter_incomplete_user_turns=False, + user_turn_completion_config=None, thinking=params.thinking, extra=params.extra if isinstance(params.extra, dict) else {}, ) diff --git a/src/pipecat/services/assemblyai/stt.py b/src/pipecat/services/assemblyai/stt.py index 6a33b6a20..44ae123b7 100644 --- a/src/pipecat/services/assemblyai/stt.py +++ b/src/pipecat/services/assemblyai/stt.py @@ -116,6 +116,7 @@ class AssemblyAISTTService(WebsocketSTTService): self._api_key = api_key self._settings = AssemblyAISTTSettings( + model=None, language=language, connection_params=connection_params, ) @@ -186,18 +187,18 @@ class AssemblyAISTTService(WebsocketSTTService): """ return True - async def _update_settings(self, update: STTSettings) -> dict[str, Any]: - """Apply a settings update. + async def _update_settings(self, delta: STTSettings) -> dict[str, Any]: + """Apply a settings delta. Settings are stored but not applied to the active connection. Args: - update: A :class:`STTSettings` (or ``AssemblyAISTTSettings``) delta. + delta: A :class:`STTSettings` (or ``AssemblyAISTTSettings``) delta. Returns: Dict mapping changed field names to their previous values. """ - changed = await super()._update_settings(update) + changed = await super()._update_settings(delta) if not changed: return changed diff --git a/src/pipecat/services/asyncai/tts.py b/src/pipecat/services/asyncai/tts.py index 289c327b0..d55062c4f 100644 --- a/src/pipecat/services/asyncai/tts.py +++ b/src/pipecat/services/asyncai/tts.py @@ -176,12 +176,12 @@ class AsyncAITTSService(AudioContextTTSService): self._receive_task = None self._keepalive_task = None - async def _update_settings(self, update: TTSSettings) -> dict[str, Any]: - """Apply a settings update. + async def _update_settings(self, delta: TTSSettings) -> dict[str, Any]: + """Apply a settings delta. Settings are stored but not applied to the active connection. """ - changed = await super()._update_settings(update) + changed = await super()._update_settings(delta) if not changed: return changed diff --git a/src/pipecat/services/aws/llm.py b/src/pipecat/services/aws/llm.py index de994463b..34e869c69 100644 --- a/src/pipecat/services/aws/llm.py +++ b/src/pipecat/services/aws/llm.py @@ -827,6 +827,12 @@ class AWSBedrockLLMService(LLMService): max_tokens=params.max_tokens, temperature=params.temperature, top_p=params.top_p, + top_k=None, + frequency_penalty=None, + presence_penalty=None, + seed=None, + filter_incomplete_user_turns=False, + user_turn_completion_config=None, latency=params.latency, additional_model_request_fields=params.additional_model_request_fields if isinstance(params.additional_model_request_fields, dict) diff --git a/src/pipecat/services/aws/nova_sonic/llm.py b/src/pipecat/services/aws/nova_sonic/llm.py index eba5cc21b..e51a1842c 100644 --- a/src/pipecat/services/aws/nova_sonic/llm.py +++ b/src/pipecat/services/aws/nova_sonic/llm.py @@ -267,6 +267,12 @@ class AWSNovaSonicLLMService(LLMService): temperature=params.temperature, max_tokens=params.max_tokens, top_p=params.top_p, + top_k=None, + frequency_penalty=None, + presence_penalty=None, + seed=None, + filter_incomplete_user_turns=False, + user_turn_completion_config=None, endpointing_sensitivity=params.endpointing_sensitivity, ) self._sync_model_name_to_metrics() @@ -338,12 +344,12 @@ class AWSNovaSonicLLMService(LLMService): # settings # - async def _update_settings(self, update: AWSNovaSonicLLMSettings) -> dict[str, Any]: - """Apply a settings update. + async def _update_settings(self, delta: AWSNovaSonicLLMSettings) -> dict[str, Any]: + """Apply a settings delta. Settings are stored but not applied to the active connection. """ - changed = await super()._update_settings(update) + changed = await super()._update_settings(delta) if not changed: return changed diff --git a/src/pipecat/services/aws/stt.py b/src/pipecat/services/aws/stt.py index c53e3648c..1d8ae84f5 100644 --- a/src/pipecat/services/aws/stt.py +++ b/src/pipecat/services/aws/stt.py @@ -148,12 +148,12 @@ class AWSTranscribeSTTService(WebsocketSTTService): } return encoding_map.get(encoding, encoding) - async def _update_settings(self, update: STTSettings) -> dict[str, Any]: - """Apply a settings update. + async def _update_settings(self, delta: STTSettings) -> dict[str, Any]: + """Apply a settings delta. Settings are stored but not applied to the active connection. """ - changed = await super()._update_settings(update) + changed = await super()._update_settings(delta) if not changed: return changed diff --git a/src/pipecat/services/aws/tts.py b/src/pipecat/services/aws/tts.py index 4e071465d..8b06ad7e9 100644 --- a/src/pipecat/services/aws/tts.py +++ b/src/pipecat/services/aws/tts.py @@ -209,6 +209,7 @@ class AWSPollyTTSService(TTSService): self._aws_session = aioboto3.Session() self._settings = AWSPollyTTSSettings( + model=None, voice=voice_id, engine=params.engine, language=self.language_to_service_language(params.language) diff --git a/src/pipecat/services/azure/stt.py b/src/pipecat/services/azure/stt.py index d161b3829..096f236a6 100644 --- a/src/pipecat/services/azure/stt.py +++ b/src/pipecat/services/azure/stt.py @@ -110,6 +110,7 @@ class AzureSTTService(STTService): self._audio_stream = None self._speech_recognizer = None self._settings = AzureSTTSettings( + model=None, region=region, language=language_to_azure_language(language), sample_rate=sample_rate, @@ -134,12 +135,12 @@ class AzureSTTService(STTService): """ return language_to_azure_language(language) - async def _update_settings(self, update: STTSettings) -> dict[str, Any]: - """Apply a settings update. + async def _update_settings(self, delta: STTSettings) -> dict[str, Any]: + """Apply a settings delta. Settings are stored but not applied to the active recognizer. """ - changed = await super()._update_settings(update) + changed = await super()._update_settings(delta) # TODO: someday we could reconnect here to apply updated settings. # Code might look something like the below: diff --git a/src/pipecat/services/azure/tts.py b/src/pipecat/services/azure/tts.py index 7672a846c..3a176055d 100644 --- a/src/pipecat/services/azure/tts.py +++ b/src/pipecat/services/azure/tts.py @@ -156,6 +156,7 @@ class AzureBaseTTSService: params = params or AzureBaseTTSService.InputParams() self._settings = AzureTTSSettings( + model=None, emphasis=params.emphasis, language=self.language_to_service_language(params.language) if params.language diff --git a/src/pipecat/services/cartesia/stt.py b/src/pipecat/services/cartesia/stt.py index 6a30f9a53..20ff04963 100644 --- a/src/pipecat/services/cartesia/stt.py +++ b/src/pipecat/services/cartesia/stt.py @@ -294,16 +294,16 @@ class CartesiaSTTService(WebsocketSTTService): await self._disconnect_websocket() - async def _update_settings(self, update: STTSettings) -> dict[str, Any]: - """Apply a settings update. + async def _update_settings(self, delta: STTSettings) -> dict[str, Any]: + """Apply a settings delta. Args: - update: A :class:`STTSettings` (or ``CartesiaSTTSettings``) delta. + delta: A :class:`STTSettings` (or ``CartesiaSTTSettings``) delta. Returns: Dict mapping changed field names to their previous values. """ - changed = await super()._update_settings(update) + changed = await super()._update_settings(delta) # TODO: someday we could reconnect here to apply updated settings. # Code might look something like the below: diff --git a/src/pipecat/services/cartesia/tts.py b/src/pipecat/services/cartesia/tts.py index 3f6fe2c21..f31cc2421 100644 --- a/src/pipecat/services/cartesia/tts.py +++ b/src/pipecat/services/cartesia/tts.py @@ -28,7 +28,7 @@ from pipecat.frames.frames import ( TTSStoppedFrame, ) from pipecat.processors.frame_processor import FrameDirection -from pipecat.services.settings import NOT_GIVEN, TTSSettings, _NotGiven, is_given +from pipecat.services.settings import NOT_GIVEN, TTSSettings, _NotGiven from pipecat.services.tts_service import AudioContextTTSService, TTSService from pipecat.transcriptions.language import Language, resolve_language from pipecat.utils.text.base_text_aggregator import BaseTextAggregator @@ -443,7 +443,7 @@ class CartesiaTTSService(AudioContextTTSService): voice_config["mode"] = "id" voice_config["id"] = self._settings.voice - if is_given(self._settings.emotion) and self._settings.emotion: + if self._settings.emotion: with warnings.catch_warnings(): warnings.simplefilter("always") warnings.warn( @@ -469,18 +469,18 @@ class CartesiaTTSService(AudioContextTTSService): "use_original_timestamps": False if self._settings.model == "sonic" else True, } - if is_given(self._settings.language) and self._settings.language: + if self._settings.language: msg["language"] = self._settings.language - if is_given(self._settings.speed) and self._settings.speed: + if self._settings.speed: msg["speed"] = self._settings.speed - if is_given(self._settings.generation_config) and self._settings.generation_config: + if self._settings.generation_config: msg["generation_config"] = self._settings.generation_config.model_dump( exclude_none=True ) - if is_given(self._settings.pronunciation_dict_id) and self._settings.pronunciation_dict_id: + if self._settings.pronunciation_dict_id: msg["pronunciation_dict_id"] = self._settings.pronunciation_dict_id return json.dumps(msg) @@ -811,7 +811,7 @@ class CartesiaHttpTTSService(TTSService): try: voice_config = {"mode": "id", "id": self._settings.voice} - if is_given(self._settings.emotion) and self._settings.emotion: + if self._settings.emotion: with warnings.catch_warnings(): warnings.simplefilter("always") warnings.warn( @@ -836,21 +836,18 @@ class CartesiaHttpTTSService(TTSService): "output_format": output_format, } - if is_given(self._settings.language) and self._settings.language: + if self._settings.language: payload["language"] = self._settings.language - if is_given(self._settings.speed) and self._settings.speed: + if self._settings.speed: payload["speed"] = self._settings.speed - if is_given(self._settings.generation_config) and self._settings.generation_config: + if self._settings.generation_config: payload["generation_config"] = self._settings.generation_config.model_dump( exclude_none=True ) - if ( - is_given(self._settings.pronunciation_dict_id) - and self._settings.pronunciation_dict_id - ): + if self._settings.pronunciation_dict_id: payload["pronunciation_dict_id"] = self._settings.pronunciation_dict_id yield TTSStartedFrame(context_id=context_id) diff --git a/src/pipecat/services/deepgram/flux/stt.py b/src/pipecat/services/deepgram/flux/stt.py index 410d272da..f0018d5c8 100644 --- a/src/pipecat/services/deepgram/flux/stt.py +++ b/src/pipecat/services/deepgram/flux/stt.py @@ -384,12 +384,12 @@ class DeepgramFluxSTTService(WebsocketSTTService): """ return True - async def _update_settings(self, update: DeepgramFluxSTTSettings) -> dict[str, Any]: - """Apply a settings update. + async def _update_settings(self, delta: DeepgramFluxSTTSettings) -> dict[str, Any]: + """Apply a settings delta. Settings are stored but not applied to the active connection. """ - changed = await super()._update_settings(update) + changed = await super()._update_settings(delta) if not changed: return changed diff --git a/src/pipecat/services/deepgram/stt.py b/src/pipecat/services/deepgram/stt.py index 28b8a211e..0792ea3c9 100644 --- a/src/pipecat/services/deepgram/stt.py +++ b/src/pipecat/services/deepgram/stt.py @@ -206,25 +206,25 @@ class DeepgramSTTService(STTService): """ return True - async def _update_settings(self, update: STTSettings) -> dict[str, Any]: - """Apply a settings update, keeping ``live_options`` in sync. + async def _update_settings(self, delta: STTSettings) -> dict[str, Any]: + """Apply a settings delta, keeping ``live_options`` in sync. Top-level ``model`` and ``language`` are the source of truth. When - they are given in *update* their values are propagated into + they are given in *delta* their values are propagated into ``live_options``. When only ``live_options`` is given, its ``model`` and ``language`` are propagated *up* to the top-level fields. Any change triggers a WebSocket reconnect. """ # Determine which top-level fields are explicitly provided. - model_given = isinstance(update, DeepgramSTTSettings) and is_given( - getattr(update, "model", NOT_GIVEN) + model_given = isinstance(delta, DeepgramSTTSettings) and is_given( + getattr(delta, "model", NOT_GIVEN) ) - language_given = isinstance(update, DeepgramSTTSettings) and is_given( - getattr(update, "language", NOT_GIVEN) + language_given = isinstance(delta, DeepgramSTTSettings) and is_given( + getattr(delta, "language", NOT_GIVEN) ) - changed = await super()._update_settings(update) + changed = await super()._update_settings(delta) if not changed: return changed diff --git a/src/pipecat/services/deepgram/stt_sagemaker.py b/src/pipecat/services/deepgram/stt_sagemaker.py index 64bb2ba8f..3820f8d84 100644 --- a/src/pipecat/services/deepgram/stt_sagemaker.py +++ b/src/pipecat/services/deepgram/stt_sagemaker.py @@ -163,25 +163,25 @@ class DeepgramSageMakerSTTService(STTService): """ return True - async def _update_settings(self, update: STTSettings) -> dict[str, Any]: - """Apply a settings update, keeping ``live_options`` in sync. + async def _update_settings(self, delta: STTSettings) -> dict[str, Any]: + """Apply a settings delta, keeping ``live_options`` in sync. Top-level ``model`` and ``language`` are the source of truth. When - they are given in *update* their values are propagated into + they are given in *delta* their values are propagated into ``live_options``. When only ``live_options`` is given, its ``model`` and ``language`` are propagated *up* to the top-level fields. Any change triggers a reconnect. """ # Determine which top-level fields are explicitly provided. - model_given = isinstance(update, DeepgramSageMakerSTTSettings) and is_given( - getattr(update, "model", NOT_GIVEN) + model_given = isinstance(delta, DeepgramSageMakerSTTSettings) and is_given( + getattr(delta, "model", NOT_GIVEN) ) - language_given = isinstance(update, DeepgramSageMakerSTTSettings) and is_given( - getattr(update, "language", NOT_GIVEN) + language_given = isinstance(delta, DeepgramSageMakerSTTSettings) and is_given( + getattr(delta, "language", NOT_GIVEN) ) - changed = await super()._update_settings(update) + changed = await super()._update_settings(delta) if not changed: return changed diff --git a/src/pipecat/services/deepgram/tts.py b/src/pipecat/services/deepgram/tts.py index 9216d7aa7..b3973bba2 100644 --- a/src/pipecat/services/deepgram/tts.py +++ b/src/pipecat/services/deepgram/tts.py @@ -109,6 +109,7 @@ class DeepgramTTSService(WebsocketTTSService): self._settings = DeepgramTTSSettings( model=voice, voice=voice, + language=None, encoding=encoding, ) self._sync_model_name_to_metrics() @@ -183,16 +184,16 @@ class DeepgramTTSService(WebsocketTTSService): await self._disconnect_websocket() - async def _update_settings(self, update: TTSSettings) -> dict[str, Any]: - """Apply a settings update. + async def _update_settings(self, delta: TTSSettings) -> dict[str, Any]: + """Apply a settings delta. Args: - update: A :class:`TTSSettings` (or ``DeepgramTTSSettings``) delta. + delta: A :class:`TTSSettings` (or ``DeepgramTTSSettings``) delta. Returns: Dict mapping changed field names to their previous values. """ - changed = await super()._update_settings(update) + changed = await super()._update_settings(delta) # Deepgram uses voice as the model, so keep them in sync for metrics if "voice" in changed: @@ -401,6 +402,7 @@ class DeepgramHttpTTSService(TTSService): self._settings = DeepgramTTSSettings( model=voice, voice=voice, + language=None, encoding=encoding, ) self._sync_model_name_to_metrics() diff --git a/src/pipecat/services/deepgram/tts_sagemaker.py b/src/pipecat/services/deepgram/tts_sagemaker.py index 8447c96f0..798a62bf8 100644 --- a/src/pipecat/services/deepgram/tts_sagemaker.py +++ b/src/pipecat/services/deepgram/tts_sagemaker.py @@ -107,6 +107,7 @@ class DeepgramSageMakerTTSService(TTSService): self._settings = DeepgramSageMakerTTSSettings( model=voice, voice=voice, + language=None, encoding=encoding, ) self._sync_model_name_to_metrics() @@ -220,13 +221,13 @@ class DeepgramSageMakerTTSService(TTSService): logger.debug("Disconnected from Deepgram TTS on SageMaker") await self._call_event_handler("on_disconnected") - async def _update_settings(self, update: TTSSettings) -> dict[str, Any]: - """Apply a settings update and reconnect if necessary. + async def _update_settings(self, delta: TTSSettings) -> dict[str, Any]: + """Apply a settings delta and reconnect if necessary. Since all settings are part of the SageMaker session query string, any setting change requires reconnecting to apply the new values. """ - changed = await super()._update_settings(update) + changed = await super()._update_settings(delta) if not changed: return changed diff --git a/src/pipecat/services/elevenlabs/stt.py b/src/pipecat/services/elevenlabs/stt.py index 5ff91f597..7a821304d 100644 --- a/src/pipecat/services/elevenlabs/stt.py +++ b/src/pipecat/services/elevenlabs/stt.py @@ -302,19 +302,19 @@ class ElevenLabsSTTService(SegmentedSTTService): """ return language_to_elevenlabs_language(language) - async def _update_settings(self, update: STTSettings) -> dict[str, Any]: - """Apply a settings update. + async def _update_settings(self, delta: STTSettings) -> dict[str, Any]: + """Apply a settings delta. Converts language to ElevenLabs format before applying and keeps ``_model_id`` in sync with the model setting. Args: - update: A :class:`STTSettings` (or ``ElevenLabsSTTSettings``) delta. + delta: A :class:`STTSettings` (or ``ElevenLabsSTTSettings``) delta. Returns: Dict mapping changed field names to their previous values. """ - changed = await super()._update_settings(update) + changed = await super()._update_settings(delta) if "model" in changed: self._model_id = self._settings.model @@ -541,19 +541,19 @@ class ElevenLabsRealtimeSTTService(WebsocketSTTService): """ return True - async def _update_settings(self, update: STTSettings) -> dict[str, Any]: - """Apply a settings update and reconnect if anything changed. + async def _update_settings(self, delta: STTSettings) -> dict[str, Any]: + """Apply a settings delta and reconnect if anything changed. Converts language to ElevenLabs format before applying and keeps ``_model_id`` in sync. Args: - update: A :class:`STTSettings` (or ``ElevenLabsRealtimeSTTSettings``) delta. + delta: A :class:`STTSettings` (or ``ElevenLabsRealtimeSTTSettings``) delta. Returns: Dict mapping changed field names to their previous values. """ - changed = await super()._update_settings(update) + changed = await super()._update_settings(delta) if not changed: return changed diff --git a/src/pipecat/services/elevenlabs/tts.py b/src/pipecat/services/elevenlabs/tts.py index 8d51e9dde..20d46481d 100644 --- a/src/pipecat/services/elevenlabs/tts.py +++ b/src/pipecat/services/elevenlabs/tts.py @@ -44,7 +44,7 @@ from pipecat.frames.frames import ( TTSStoppedFrame, ) from pipecat.processors.frame_processor import FrameDirection -from pipecat.services.settings import NOT_GIVEN, TTSSettings, _NotGiven, is_given +from pipecat.services.settings import NOT_GIVEN, TTSSettings, _NotGiven from pipecat.services.tts_service import ( AudioContextTTSService, TTSService, @@ -166,7 +166,7 @@ def build_elevenlabs_voice_settings( val = ( getattr(settings, key, None) if isinstance(settings, TTSSettings) else settings.get(key) ) - if val is not None and is_given(val): + if val is not None: voice_settings[key] = val return voice_settings or None @@ -470,24 +470,24 @@ class ElevenLabsTTSService(AudioContextTTSService): voice_settings = {} for key in voice_setting_keys: val = getattr(ts, key, None) - if val is not None and is_given(val): + if val is not None: voice_settings[key] = val return voice_settings or None - async def _update_settings(self, update: TTSSettings) -> dict[str, Any]: - """Apply a settings update, reconnecting as needed. + async def _update_settings(self, delta: TTSSettings) -> dict[str, Any]: + """Apply a settings delta, reconnecting as needed. Uses the declarative ``URL_FIELDS`` and ``VOICE_SETTINGS_FIELDS`` sets on :class:`ElevenLabsTTSSettings` to decide whether to reconnect the WebSocket or close the current audio context. Args: - update: A :class:`TTSSettings` (or ``ElevenLabsTTSSettings``) delta. + delta: A :class:`TTSSettings` (or ``ElevenLabsTTSSettings``) delta. Returns: Dict mapping changed field names to their previous values. """ - changed = await super()._update_settings(update) + changed = await super()._update_settings(delta) if not changed: return changed @@ -967,16 +967,16 @@ class ElevenLabsHttpTTSService(TTSService): def _set_voice_settings(self): return build_elevenlabs_voice_settings(self._settings) - async def _update_settings(self, update: TTSSettings) -> dict[str, Any]: - """Apply a settings update and rebuild voice settings. + async def _update_settings(self, delta: TTSSettings) -> dict[str, Any]: + """Apply a settings delta and rebuild voice settings. Args: - update: A :class:`TTSSettings` (or ``ElevenLabsHttpTTSSettings``) delta. + delta: A :class:`TTSSettings` (or ``ElevenLabsHttpTTSSettings``) delta. Returns: Dict mapping changed field names to their previous values. """ - changed = await super()._update_settings(update) + changed = await super()._update_settings(delta) if changed: self._voice_settings = self._set_voice_settings() return changed @@ -1116,10 +1116,7 @@ class ElevenLabsHttpTTSService(TTSService): locator.model_dump() for locator in self._pronunciation_dictionary_locators ] - if ( - is_given(self._settings.apply_text_normalization) - and self._settings.apply_text_normalization is not None - ): + if self._settings.apply_text_normalization is not None: payload["apply_text_normalization"] = self._settings.apply_text_normalization language = self._settings.language @@ -1140,10 +1137,7 @@ class ElevenLabsHttpTTSService(TTSService): params = { "output_format": self._output_format, } - if ( - is_given(self._settings.optimize_streaming_latency) - and self._settings.optimize_streaming_latency is not None - ): + if self._settings.optimize_streaming_latency is not None: params["optimize_streaming_latency"] = self._settings.optimize_streaming_latency try: diff --git a/src/pipecat/services/fal/stt.py b/src/pipecat/services/fal/stt.py index 91b5a25c8..923c3c2ea 100644 --- a/src/pipecat/services/fal/stt.py +++ b/src/pipecat/services/fal/stt.py @@ -224,6 +224,7 @@ class FalSTTService(SegmentedSTTService): self._fal_client = fal_client.AsyncClient(key=api_key or os.getenv("FAL_KEY")) self._settings = FalSTTSettings( + model=None, language=self.language_to_service_language(params.language) if params.language else "en", diff --git a/src/pipecat/services/fish/tts.py b/src/pipecat/services/fish/tts.py index 0d84ea7ab..1927b6cac 100644 --- a/src/pipecat/services/fish/tts.py +++ b/src/pipecat/services/fish/tts.py @@ -196,18 +196,18 @@ class FishAudioTTSService(InterruptibleTTSService): """ return True - async def _update_settings(self, update: TTSSettings) -> dict[str, Any]: - """Apply a settings update and reconnect if needed. + async def _update_settings(self, delta: TTSSettings) -> dict[str, Any]: + """Apply a settings delta and reconnect if needed. Any change to voice or model triggers a WebSocket reconnect. Args: - update: A :class:`TTSSettings` (or ``FishAudioTTSSettings``) delta. + delta: A :class:`TTSSettings` (or ``FishAudioTTSSettings``) delta. Returns: Dict mapping changed field names to their previous values. """ - changed = await super()._update_settings(update) + changed = await super()._update_settings(delta) if changed: await self._disconnect() diff --git a/src/pipecat/services/gladia/stt.py b/src/pipecat/services/gladia/stt.py index 8d968e00f..d0a6f5a84 100644 --- a/src/pipecat/services/gladia/stt.py +++ b/src/pipecat/services/gladia/stt.py @@ -280,7 +280,7 @@ class GladiaSTTService(WebsocketSTTService): self._region = region self._url = url self._receive_task = None - self._settings = GladiaSTTSettings(model=model, input_params=params) + self._settings = GladiaSTTSettings(model=model, language=None, input_params=params) self._sync_model_name_to_metrics() # Session management @@ -379,18 +379,18 @@ class GladiaSTTService(WebsocketSTTService): await super().start(frame) await self._connect() - async def _update_settings(self, update: GladiaSTTSettings) -> dict[str, Any]: - """Apply settings update. + async def _update_settings(self, delta: GladiaSTTSettings) -> dict[str, Any]: + """Apply settings delta. Settings are stored but not applied to the active session. Args: - update: A settings delta. + delta: A settings delta. Returns: Dict mapping changed field names to their previous values. """ - changed = await super()._update_settings(update) + changed = await super()._update_settings(delta) if not changed: return changed diff --git a/src/pipecat/services/google/gemini_live/llm.py b/src/pipecat/services/google/gemini_live/llm.py index 84b06a86d..037b23bb3 100644 --- a/src/pipecat/services/google/gemini_live/llm.py +++ b/src/pipecat/services/google/gemini_live/llm.py @@ -750,6 +750,9 @@ class GeminiLiveLLMService(LLMService): temperature=params.temperature, top_k=params.top_k, top_p=params.top_p, + seed=None, + filter_incomplete_user_turns=False, + user_turn_completion_config=None, modalities=params.modalities, language=self._language_code, media_resolution=params.media_resolution, @@ -806,12 +809,12 @@ class GeminiLiveLLMService(LLMService): """ return True - async def _update_settings(self, update: LLMSettings) -> dict[str, Any]: - """Apply a settings update. + async def _update_settings(self, delta: LLMSettings) -> dict[str, Any]: + """Apply a settings delta. Settings are stored but not applied to the active connection. """ - changed = await super()._update_settings(update) + changed = await super()._update_settings(delta) if not changed: return changed diff --git a/src/pipecat/services/google/llm.py b/src/pipecat/services/google/llm.py index 2004aa15a..1c6f56669 100644 --- a/src/pipecat/services/google/llm.py +++ b/src/pipecat/services/google/llm.py @@ -807,6 +807,11 @@ class GoogleLLMService(LLMService): temperature=params.temperature, top_k=params.top_k, top_p=params.top_p, + frequency_penalty=None, + presence_penalty=None, + seed=None, + filter_incomplete_user_turns=False, + user_turn_completion_config=None, thinking=params.thinking, extra=params.extra if isinstance(params.extra, dict) else {}, ) diff --git a/src/pipecat/services/google/stt.py b/src/pipecat/services/google/stt.py index 72d4f12b6..e294be20a 100644 --- a/src/pipecat/services/google/stt.py +++ b/src/pipecat/services/google/stt.py @@ -554,7 +554,9 @@ class GoogleSTTService(STTService): self._client = speech_v2.SpeechAsyncClient(credentials=creds, client_options=client_options) self._settings = GoogleSTTSettings( + language=None, languages=list(params.language_list), + language_codes=None, model=params.model, use_separate_recognition_per_channel=params.use_separate_recognition_per_channel, enable_automatic_punctuation=params.enable_automatic_punctuation, @@ -597,11 +599,9 @@ class GoogleSTTService(STTService): Returns: List[str]: Google STT language code strings. """ - from pipecat.services.settings import is_given - - if is_given(self._settings.languages): + if self._settings.languages: return [self.language_to_service_language(lang) for lang in self._settings.languages] - if is_given(self._settings.language_codes): + if self._settings.language_codes: return list(self._settings.language_codes) return ["en-US"] @@ -632,8 +632,8 @@ class GoogleSTTService(STTService): logger.debug(f"Switching STT languages to: {languages}") await self._update_settings(GoogleSTTSettings(languages=list(languages))) - async def _update_settings(self, update: GoogleSTTSettings) -> dict[str, Any]: - """Apply settings update and reconnect if anything changed. + async def _update_settings(self, delta: GoogleSTTSettings) -> dict[str, Any]: + """Apply settings delta and reconnect if anything changed. Handles ``language`` from base ``set_language`` by converting it to ``languages``. Emits a deprecation warning if ``language_codes`` is @@ -641,7 +641,7 @@ class GoogleSTTService(STTService): Reconnects the stream on any change. Args: - update: A settings delta. + delta: A settings delta. Returns: Dict mapping changed field names to their previous values. @@ -649,13 +649,13 @@ class GoogleSTTService(STTService): from pipecat.services.settings import is_given # If base set_language sent a Language value, convert to languages list - if is_given(update.language): - update.languages = [update.language] + if is_given(delta.language): + delta.languages = [delta.language] # Clear language so the base class doesn't try to store it - update.language = NOT_GIVEN + delta.language = NOT_GIVEN # Warn on deprecated language_codes usage - if is_given(update.language_codes): + if is_given(delta.language_codes): with warnings.catch_warnings(): warnings.simplefilter("always") warnings.warn( @@ -665,7 +665,7 @@ class GoogleSTTService(STTService): stacklevel=2, ) - changed = await super()._update_settings(update) + changed = await super()._update_settings(delta) if changed: await self._reconnect_if_needed() @@ -745,34 +745,34 @@ class GoogleSTTService(STTService): DeprecationWarning, ) # Build a settings delta from the provided options - update = GoogleSTTSettings() + delta = GoogleSTTSettings() if languages is not None: - update.languages = list(languages) + delta.languages = list(languages) if model is not None: - update.model = model + delta.model = model if enable_automatic_punctuation is not None: - update.enable_automatic_punctuation = enable_automatic_punctuation + delta.enable_automatic_punctuation = enable_automatic_punctuation if enable_spoken_punctuation is not None: - update.enable_spoken_punctuation = enable_spoken_punctuation + delta.enable_spoken_punctuation = enable_spoken_punctuation if enable_spoken_emojis is not None: - update.enable_spoken_emojis = enable_spoken_emojis + delta.enable_spoken_emojis = enable_spoken_emojis if profanity_filter is not None: - update.profanity_filter = profanity_filter + delta.profanity_filter = profanity_filter if enable_word_time_offsets is not None: - update.enable_word_time_offsets = enable_word_time_offsets + delta.enable_word_time_offsets = enable_word_time_offsets if enable_word_confidence is not None: - update.enable_word_confidence = enable_word_confidence + delta.enable_word_confidence = enable_word_confidence if enable_interim_results is not None: - update.enable_interim_results = enable_interim_results + delta.enable_interim_results = enable_interim_results if enable_voice_activity_events is not None: - update.enable_voice_activity_events = enable_voice_activity_events + delta.enable_voice_activity_events = enable_voice_activity_events if location is not None: logger.debug(f"Updating location to: {location}") self._location = location - await self._update_settings(update) + await self._update_settings(delta) async def _connect(self): """Initialize streaming recognition config and stream.""" diff --git a/src/pipecat/services/google/tts.py b/src/pipecat/services/google/tts.py index 1103c69e4..3416ee6d4 100644 --- a/src/pipecat/services/google/tts.py +++ b/src/pipecat/services/google/tts.py @@ -608,6 +608,7 @@ class GoogleHttpTTSService(TTSService): self._location = location self._settings = GoogleHttpTTSSettings( + model=None, pitch=params.pitch, rate=params.rate, speaking_rate=params.speaking_rate, @@ -688,20 +689,20 @@ class GoogleHttpTTSService(TTSService): """ return language_to_google_tts_language(language) - async def _update_settings(self, update: TTSSettings) -> dict[str, Any]: + async def _update_settings(self, delta: TTSSettings) -> dict[str, Any]: """Override to handle speaking_rate validation. Args: - update: Settings delta. Can include 'speaking_rate' (float). + delta: Settings delta. Can include 'speaking_rate' (float). """ - if isinstance(update, GoogleHttpTTSSettings) and is_given(update.speaking_rate): - rate_value = float(update.speaking_rate) + if isinstance(delta, GoogleHttpTTSSettings) and is_given(delta.speaking_rate): + rate_value = float(delta.speaking_rate) if not (0.25 <= rate_value <= 2.0): logger.warning( f"Invalid speaking_rate value: {rate_value}. Must be between 0.25 and 2.0" ) - update.speaking_rate = NOT_GIVEN - return await super()._update_settings(update) + delta.speaking_rate = NOT_GIVEN + return await super()._update_settings(delta) def _construct_ssml(self, text: str) -> str: ssml = "" @@ -1021,6 +1022,7 @@ class GoogleTTSService(GoogleBaseTTSService): self._location = location self._settings = GoogleStreamTTSSettings( + model=None, language=self.language_to_service_language(params.language) if params.language else "en-US", @@ -1032,20 +1034,20 @@ class GoogleTTSService(GoogleBaseTTSService): credentials, credentials_path ) - async def _update_settings(self, update: TTSSettings) -> dict[str, Any]: + async def _update_settings(self, delta: TTSSettings) -> dict[str, Any]: """Override to handle speaking_rate validation. Args: - update: Settings delta. Can include 'speaking_rate' (float). + delta: Settings delta. Can include 'speaking_rate' (float). """ - if isinstance(update, GoogleStreamTTSSettings) and is_given(update.speaking_rate): - rate_value = float(update.speaking_rate) + if isinstance(delta, GoogleStreamTTSSettings) and is_given(delta.speaking_rate): + rate_value = float(delta.speaking_rate) if not (0.25 <= rate_value <= 2.0): logger.warning( f"Invalid speaking_rate value: {rate_value}. Must be between 0.25 and 2.0" ) - update.speaking_rate = NOT_GIVEN - return await super()._update_settings(update) + delta.speaking_rate = NOT_GIVEN + return await super()._update_settings(delta) @traced_tts async def run_tts(self, text: str, context_id: str) -> AsyncGenerator[Frame, None]: @@ -1230,6 +1232,7 @@ class GeminiTTSService(GoogleBaseTTSService): self._location = location self._model = model self._settings = GeminiTTSSettings( + model=None, language=self.language_to_service_language(params.language) if params.language else "en-US", @@ -1267,19 +1270,19 @@ class GeminiTTSService(GoogleBaseTTSService): f"Current rate of {self.sample_rate}Hz may cause issues." ) - async def _update_settings(self, update: TTSSettings) -> dict[str, Any]: - """Apply a settings update with voice validation. + async def _update_settings(self, delta: TTSSettings) -> dict[str, Any]: + """Apply a settings delta with voice validation. Args: - update: Settings delta. Can include 'voice', 'prompt', etc. + delta: Settings delta. Can include 'voice', 'prompt', etc. Returns: Dict mapping changed field names to their previous values. """ - if is_given(update.voice) and update.voice not in self.AVAILABLE_VOICES: - logger.warning(f"Voice '{update.voice}' not in known voices list. Using anyway.") + if is_given(delta.voice) and delta.voice not in self.AVAILABLE_VOICES: + logger.warning(f"Voice '{delta.voice}' not in known voices list. Using anyway.") - return await super()._update_settings(update) + return await super()._update_settings(delta) @traced_tts async def run_tts(self, text: str, context_id: str) -> AsyncGenerator[Frame, None]: diff --git a/src/pipecat/services/gradium/stt.py b/src/pipecat/services/gradium/stt.py index 1583fac3c..4ec7bf6ff 100644 --- a/src/pipecat/services/gradium/stt.py +++ b/src/pipecat/services/gradium/stt.py @@ -28,7 +28,7 @@ from pipecat.frames.frames import ( VADUserStoppedSpeakingFrame, ) from pipecat.processors.frame_processor import FrameDirection -from pipecat.services.settings import NOT_GIVEN, STTSettings, _NotGiven, is_given +from pipecat.services.settings import NOT_GIVEN, STTSettings, _NotGiven from pipecat.services.stt_latency import GRADIUM_TTFS_P99 from pipecat.services.stt_service import WebsocketSTTService from pipecat.transcriptions.language import Language, resolve_language @@ -148,8 +148,9 @@ class GradiumSTTService(WebsocketSTTService): params = params or GradiumSTTService.InputParams() self._settings = GradiumSTTSettings( + model=None, language=params.language, - delay_in_frames=params.delay_in_frames if params.delay_in_frames else NOT_GIVEN, + delay_in_frames=params.delay_in_frames or None, ) self._receive_task = None @@ -171,16 +172,16 @@ class GradiumSTTService(WebsocketSTTService): """ return True - async def _update_settings(self, update: STTSettings) -> dict[str, Any]: - """Apply a settings update, sync params, and reconnect. + async def _update_settings(self, delta: STTSettings) -> dict[str, Any]: + """Apply a settings delta, sync params, and reconnect. Args: - update: A :class:`STTSettings` (or ``GradiumSTTSettings``) delta. + delta: A :class:`STTSettings` (or ``GradiumSTTSettings``) delta. Returns: Dict mapping changed field names to their previous values. """ - changed = await super()._update_settings(update) + changed = await super()._update_settings(delta) if not changed: return changed @@ -326,11 +327,11 @@ class GradiumSTTService(WebsocketSTTService): json_config = {} if self._json_config: json_config = json.loads(self._json_config) - if is_given(self._settings.language) and self._settings.language: + if self._settings.language: gradium_language = language_to_gradium_language(self._settings.language) if gradium_language: json_config["language"] = gradium_language - if is_given(self._settings.delay_in_frames) and self._settings.delay_in_frames: + if self._settings.delay_in_frames: json_config["delay_in_frames"] = self._settings.delay_in_frames if json_config: setup_msg["json_config"] = json_config diff --git a/src/pipecat/services/gradium/tts.py b/src/pipecat/services/gradium/tts.py index d10f6258d..703289706 100644 --- a/src/pipecat/services/gradium/tts.py +++ b/src/pipecat/services/gradium/tts.py @@ -105,6 +105,7 @@ class GradiumTTSService(AudioContextTTSService): self._settings = GradiumTTSSettings( model=model, voice=voice_id, + language=None, output_format="pcm", ) @@ -119,16 +120,16 @@ class GradiumTTSService(AudioContextTTSService): """ return True - async def _update_settings(self, update: TTSSettings) -> dict[str, Any]: - """Apply a settings update and reconnect if voice changed. + async def _update_settings(self, delta: TTSSettings) -> dict[str, Any]: + """Apply a settings delta and reconnect if voice changed. Args: - update: A :class:`TTSSettings` (or ``GradiumTTSSettings``) delta. + delta: A :class:`TTSSettings` (or ``GradiumTTSSettings``) delta. Returns: Dict mapping changed field names to their previous values. """ - changed = await super()._update_settings(update) + changed = await super()._update_settings(delta) if "voice" in changed: await self._disconnect() await self._connect() diff --git a/src/pipecat/services/grok/realtime/llm.py b/src/pipecat/services/grok/realtime/llm.py index 14c93c94a..4f6a62e24 100644 --- a/src/pipecat/services/grok/realtime/llm.py +++ b/src/pipecat/services/grok/realtime/llm.py @@ -151,6 +151,16 @@ class GrokRealtimeLLMService(LLMService): self.base_url = base_url self._settings = GrokRealtimeLLMSettings( + model=None, + temperature=None, + max_tokens=None, + top_p=None, + top_k=None, + frequency_penalty=None, + presence_penalty=None, + seed=None, + filter_incomplete_user_turns=False, + user_turn_completion_config=None, session_properties=session_properties or events.SessionProperties(), ) @@ -358,9 +368,9 @@ class GrokRealtimeLLMService(LLMService): """ # Backward-compatible dict path: frame.settings contains SessionProperties # fields, not our Settings fields, so we construct SessionProperties - # directly. The frame.update path falls through to super, which calls + # directly. The frame.delta path falls through to super, which calls # _update_settings → our override handles the rest. - if isinstance(frame, LLMUpdateSettingsFrame) and frame.update is None: + if isinstance(frame, LLMUpdateSettingsFrame) and frame.delta is None: self._settings.session_properties = events.SessionProperties(**frame.settings) await self._send_session_update() await self.push_frame(frame, direction) @@ -463,13 +473,13 @@ class GrokRealtimeLLMService(LLMService): return await self.push_error(error_msg=f"Error sending client event: {e}", exception=e) - async def _update_settings(self, update): - """Apply a settings update, sending a session update if needed.""" + async def _update_settings(self, delta): + """Apply a settings delta, sending a session update if needed.""" # Capture current sample rates before the update replaces them. input_rate = self._get_configured_sample_rate("input") output_rate = self._get_configured_sample_rate("output") - changed = await super()._update_settings(update) + changed = await super()._update_settings(delta) if "session_properties" in changed: if input_rate and output_rate: diff --git a/src/pipecat/services/hume/tts.py b/src/pipecat/services/hume/tts.py index b5a064334..4b13226cc 100644 --- a/src/pipecat/services/hume/tts.py +++ b/src/pipecat/services/hume/tts.py @@ -137,6 +137,7 @@ class HumeTTSService(TTSService): params = params or HumeTTSService.InputParams() self._settings = HumeTTSSettings( + model=None, voice=voice_id, description=params.description, speed=params.speed, @@ -210,7 +211,7 @@ class HumeTTSService(TTSService): """Runtime updates via key/value pair. .. deprecated:: 0.0.103 - Use ``TTSUpdateSettingsFrame(update=HumeTTSSettings(...))`` instead. + Use ``TTSUpdateSettingsFrame(delta=HumeTTSSettings(...))`` instead. Args: key: The name of the setting to update. Recognized keys are: @@ -224,7 +225,7 @@ class HumeTTSService(TTSService): warnings.simplefilter("always") warnings.warn( "'update_setting' is deprecated, use " - "'TTSUpdateSettingsFrame(update=HumeTTSSettings(...))' instead.", + "'TTSUpdateSettingsFrame(delta=HumeTTSSettings(...))' instead.", DeprecationWarning, stacklevel=2, ) diff --git a/src/pipecat/services/inworld/tts.py b/src/pipecat/services/inworld/tts.py index 8e457aabc..2f35dc27c 100644 --- a/src/pipecat/services/inworld/tts.py +++ b/src/pipecat/services/inworld/tts.py @@ -29,7 +29,7 @@ from pipecat import version as pipecat_version USER_AGENT = f"pipecat/{pipecat_version()}" from pydantic import BaseModel -from pipecat.services.settings import NOT_GIVEN, TTSSettings, _NotGiven, is_given +from pipecat.services.settings import NOT_GIVEN, TTSSettings, _NotGiven try: from websockets.asyncio.client import connect as websocket_connect @@ -173,17 +173,16 @@ class InworldHttpTTSService(TTSService): self._settings = InworldTTSSettings( model=model, voice=voice_id, + language=None, audio_encoding=encoding, audio_sample_rate=0, + speaking_rate=params.speaking_rate, + temperature=params.temperature, + timestamp_transport_strategy=params.timestamp_transport_strategy, + auto_mode=None, # Not applicable for HTTP TTS + apply_text_normalization=None, # Not applicable for HTTP TTS ) - if params.temperature is not None: - self._settings.temperature = params.temperature - if params.speaking_rate is not None: - self._settings.speaking_rate = params.speaking_rate - if params.timestamp_transport_strategy is not None: - self._settings.timestamp_transport_strategy = params.timestamp_transport_strategy - self._cumulative_time = 0.0 self._sync_model_name_to_metrics() @@ -286,7 +285,7 @@ class InworldHttpTTSService(TTSService): "audioEncoding": self._settings.audio_encoding, "sampleRateHertz": self._settings.audio_sample_rate, } - if is_given(self._settings.speaking_rate): + if self._settings.speaking_rate is not None: audio_config["speakingRate"] = self._settings.speaking_rate payload = { @@ -296,12 +295,12 @@ class InworldHttpTTSService(TTSService): "audioConfig": audio_config, } - if is_given(self._settings.temperature): + if self._settings.temperature is not None: payload["temperature"] = self._settings.temperature # Use WORD timestamps for simplicity and correct spacing/capitalization payload["timestampType"] = self._timestamp_type - if is_given(self._settings.timestamp_transport_strategy): + if self._settings.timestamp_transport_strategy is not None: payload["timestampTransportStrategy"] = self._settings.timestamp_transport_strategy request_id = str(uuid.uuid4()) @@ -549,25 +548,17 @@ class InworldTTSService(AudioContextTTSService): self._settings = InworldTTSSettings( model=model, voice=voice_id, + language=None, audio_encoding=encoding, audio_sample_rate=0, + speaking_rate=params.speaking_rate, + temperature=params.temperature, + apply_text_normalization=params.apply_text_normalization, + timestamp_transport_strategy=params.timestamp_transport_strategy, + auto_mode=params.auto_mode if params.auto_mode is not None else aggregate_sentences, ) self._timestamp_type = "WORD" - if params.temperature is not None: - self._settings.temperature = params.temperature - if params.speaking_rate is not None: - self._settings.speaking_rate = params.speaking_rate - if params.apply_text_normalization is not None: - self._settings.apply_text_normalization = params.apply_text_normalization - if params.timestamp_transport_strategy is not None: - self._settings.timestamp_transport_strategy = params.timestamp_transport_strategy - - if params.auto_mode is not None: - self._settings.auto_mode = params.auto_mode - else: - self._settings.auto_mode = aggregate_sentences - self._buffer_settings = { "maxBufferDelayMs": params.max_buffer_delay_ms, "bufferCharThreshold": params.buffer_char_threshold, @@ -757,12 +748,12 @@ class InworldTTSService(AudioContextTTSService): await self._disconnect_websocket() - async def _update_settings(self, update: TTSSettings) -> dict[str, Any]: - """Apply a settings update. + async def _update_settings(self, delta: TTSSettings) -> dict[str, Any]: + """Apply a settings delta. Settings are stored but not applied to the active connection. """ - changed = await super()._update_settings(update) + changed = await super()._update_settings(delta) if not changed: return changed @@ -959,7 +950,7 @@ class InworldTTSService(AudioContextTTSService): "audioEncoding": self._settings.audio_encoding, "sampleRateHertz": self._settings.audio_sample_rate, } - if is_given(self._settings.speaking_rate): + if self._settings.speaking_rate is not None: audio_config["speakingRate"] = self._settings.speaking_rate create_config: Dict[str, Any] = { @@ -968,13 +959,13 @@ class InworldTTSService(AudioContextTTSService): "audioConfig": audio_config, } - if is_given(self._settings.temperature): + if self._settings.temperature is not None: create_config["temperature"] = self._settings.temperature - if is_given(self._settings.apply_text_normalization): + if self._settings.apply_text_normalization is not None: create_config["applyTextNormalization"] = self._settings.apply_text_normalization - if is_given(self._settings.auto_mode): + if self._settings.auto_mode is not None: create_config["autoMode"] = self._settings.auto_mode - if is_given(self._settings.timestamp_transport_strategy): + if self._settings.timestamp_transport_strategy is not None: create_config["timestampTransportStrategy"] = ( self._settings.timestamp_transport_strategy ) diff --git a/src/pipecat/services/kokoro/tts.py b/src/pipecat/services/kokoro/tts.py index 6e848ae87..519c565ba 100644 --- a/src/pipecat/services/kokoro/tts.py +++ b/src/pipecat/services/kokoro/tts.py @@ -144,6 +144,7 @@ class KokoroTTSService(TTSService): self._lang_code = language_to_kokoro_language(params.language) self._settings = KokoroTTSSettings( + model=None, voice=voice_id, language=language_to_kokoro_language(params.language), lang_code=language_to_kokoro_language(params.language), diff --git a/src/pipecat/services/llm_service.py b/src/pipecat/services/llm_service.py index e4f1adb45..df1bc6d08 100644 --- a/src/pipecat/services/llm_service.py +++ b/src/pipecat/services/llm_service.py @@ -59,7 +59,7 @@ from pipecat.processors.aggregators.llm_response import ( from pipecat.processors.aggregators.openai_llm_context import OpenAILLMContext from pipecat.processors.frame_processor import FrameDirection from pipecat.services.ai_service import AIService -from pipecat.services.settings import LLMSettings, is_given +from pipecat.services.settings import LLMSettings from pipecat.turns.user_turn_completion_mixin import UserTurnCompletionLLMServiceMixin from pipecat.utils.context.llm_context_summarization import ( LLMContextSummarizationUtil, @@ -312,19 +312,21 @@ class LLMService(UserTurnCompletionLLMServiceMixin, AIService): await self._cancel_sequential_runner_task() await self._cancel_summary_task() - async def _update_settings(self, update: LLMSettings) -> dict[str, Any]: - """Apply a settings update, handling turn-completion fields. + async def _update_settings(self, delta: LLMSettings) -> dict[str, Any]: + """Apply a settings delta, handling turn-completion fields. Args: - update: An LLM settings delta. + delta: An LLM settings delta. Returns: Dict mapping changed field names to their previous values. """ - changed = await super()._update_settings(update) + changed = await super()._update_settings(delta) if "filter_incomplete_user_turns" in changed: - self._filter_incomplete_user_turns = self._settings.filter_incomplete_user_turns + self._filter_incomplete_user_turns = ( + self._settings.filter_incomplete_user_turns or False + ) logger.info( f"{self}: Incomplete turn filtering " f"{'enabled' if self._filter_incomplete_user_turns else 'disabled'}" @@ -349,20 +351,20 @@ class LLMService(UserTurnCompletionLLMServiceMixin, AIService): elif isinstance(frame, LLMConfigureOutputFrame): self._skip_tts = frame.skip_tts elif isinstance(frame, LLMUpdateSettingsFrame): - if frame.update is not None: - await self._update_settings(frame.update) + if frame.delta is not None: + await self._update_settings(frame.delta) elif frame.settings: # Backward-compatible path: convert legacy dict to settings object. with warnings.catch_warnings(): warnings.simplefilter("always") warnings.warn( "Passing a dict via LLMUpdateSettingsFrame(settings={...}) is deprecated " - "since 0.0.103, use LLMUpdateSettingsFrame(update=LLMSettings(...)) instead.", + "since 0.0.103, use LLMUpdateSettingsFrame(delta=LLMSettings(...)) instead.", DeprecationWarning, stacklevel=2, ) - update = type(self._settings).from_mapping(frame.settings) - await self._update_settings(update) + delta = type(self._settings).from_mapping(frame.settings) + await self._update_settings(delta) elif isinstance(frame, LLMContextSummaryRequestFrame): await self._handle_summary_request(frame) diff --git a/src/pipecat/services/lmnt/tts.py b/src/pipecat/services/lmnt/tts.py index f70bfa402..b7ebb19ea 100644 --- a/src/pipecat/services/lmnt/tts.py +++ b/src/pipecat/services/lmnt/tts.py @@ -206,16 +206,16 @@ class LmntTTSService(InterruptibleTTSService): await self._disconnect_websocket() - async def _update_settings(self, update: TTSSettings) -> dict[str, Any]: - """Apply a settings update. + async def _update_settings(self, delta: TTSSettings) -> dict[str, Any]: + """Apply a settings delta. Args: - update: A :class:`TTSSettings` (or ``LmntTTSSettings``) delta. + delta: A :class:`TTSSettings` (or ``LmntTTSSettings``) delta. Returns: Dict mapping changed field names to their previous values. """ - changed = await super()._update_settings(update) + changed = await super()._update_settings(delta) if changed: await self._disconnect() diff --git a/src/pipecat/services/minimax/tts.py b/src/pipecat/services/minimax/tts.py index 54925f7e4..388b7ee9e 100644 --- a/src/pipecat/services/minimax/tts.py +++ b/src/pipecat/services/minimax/tts.py @@ -26,7 +26,7 @@ from pipecat.frames.frames import ( TTSStartedFrame, TTSStoppedFrame, ) -from pipecat.services.settings import NOT_GIVEN, TTSSettings, _NotGiven, is_given +from pipecat.services.settings import NOT_GIVEN, TTSSettings, _NotGiven from pipecat.services.tts_service import TTSService from pipecat.transcriptions.language import Language, resolve_language from pipecat.utils.tracing.service_decorators import traced_tts @@ -240,13 +240,19 @@ class MiniMaxHttpTTSService(TTSService): self._settings = MiniMaxTTSSettings( model=model, voice=voice_id, + language=None, stream=True, speed=params.speed, volume=params.volume, pitch=params.pitch, + language_boost=None, + emotion=None, + text_normalization=None, + latex_read=None, audio_bitrate=128000, audio_format="pcm", audio_channel=1, + audio_sample_rate=0, ) self._sync_model_name_to_metrics() @@ -351,11 +357,11 @@ class MiniMaxHttpTTSService(TTSService): "vol": self._settings.volume, "pitch": self._settings.pitch, } - if is_given(self._settings.emotion): + if self._settings.emotion is not None: voice_setting["emotion"] = self._settings.emotion - if is_given(self._settings.text_normalization): + if self._settings.text_normalization is not None: voice_setting["text_normalization"] = self._settings.text_normalization - if is_given(self._settings.latex_read): + if self._settings.latex_read is not None: voice_setting["latex_read"] = self._settings.latex_read # Build audio_setting dict for API @@ -374,7 +380,7 @@ class MiniMaxHttpTTSService(TTSService): "model": self._settings.model, "text": text, } - if is_given(self._settings.language_boost): + if self._settings.language_boost is not None: payload["language_boost"] = self._settings.language_boost try: diff --git a/src/pipecat/services/neuphonic/tts.py b/src/pipecat/services/neuphonic/tts.py index dd2360e4c..e076958c4 100644 --- a/src/pipecat/services/neuphonic/tts.py +++ b/src/pipecat/services/neuphonic/tts.py @@ -147,6 +147,7 @@ class NeuphonicTTSService(InterruptibleTTSService): self._api_key = api_key self._url = url self._settings = NeuphonicTTSSettings( + model=None, language=self.language_to_service_language(params.language), speed=params.speed, encoding=encoding, @@ -179,9 +180,9 @@ class NeuphonicTTSService(InterruptibleTTSService): """ return language_to_neuphonic_lang_code(language) - async def _update_settings(self, update: TTSSettings) -> dict[str, Any]: - """Apply a settings update and reconnect with new configuration.""" - changed = await super()._update_settings(update) + async def _update_settings(self, delta: TTSSettings) -> dict[str, Any]: + """Apply a settings delta and reconnect with new configuration.""" + changed = await super()._update_settings(delta) if changed: await self._disconnect() await self._connect() @@ -450,6 +451,7 @@ class NeuphonicHttpTTSService(TTSService): self._session = aiohttp_session self._base_url = url.rstrip("/") self._settings = NeuphonicTTSSettings( + model=None, voice=voice_id, language=self.language_to_service_language(params.language) or "en", speed=params.speed, diff --git a/src/pipecat/services/nvidia/stt.py b/src/pipecat/services/nvidia/stt.py index fd924204e..be9002b14 100644 --- a/src/pipecat/services/nvidia/stt.py +++ b/src/pipecat/services/nvidia/stt.py @@ -579,16 +579,16 @@ class NvidiaSegmentedSTTService(SegmentedSTTService): self._config = self._create_recognition_config() logger.debug(f"Initialized NvidiaSegmentedSTTService with model: {self._settings.model}") - async def _update_settings(self, update: STTSettings) -> dict[str, Any]: - """Apply a settings update and sync internal state. + async def _update_settings(self, delta: STTSettings) -> dict[str, Any]: + """Apply a settings delta and sync internal state. Args: - update: A :class:`STTSettings` (or ``NvidiaSegmentedSTTSettings``) delta. + delta: A :class:`STTSettings` (or ``NvidiaSegmentedSTTSettings``) delta. Returns: Dict mapping changed field names to their previous values. """ - changed = await super()._update_settings(update) + changed = await super()._update_settings(delta) if changed: self._config = self._create_recognition_config() diff --git a/src/pipecat/services/nvidia/tts.py b/src/pipecat/services/nvidia/tts.py index ade5da63d..12bcf8c21 100644 --- a/src/pipecat/services/nvidia/tts.py +++ b/src/pipecat/services/nvidia/tts.py @@ -150,12 +150,12 @@ class NvidiaTTSService(TTSService): stacklevel=2, ) - async def _update_settings(self, update: NvidiaTTSSettings) -> dict[str, Any]: - """Apply a settings update. + async def _update_settings(self, delta: NvidiaTTSSettings) -> dict[str, Any]: + """Apply a settings delta. Settings are stored but not applied to the active connection. """ - changed = await super()._update_settings(update) + changed = await super()._update_settings(delta) if not changed: return changed # TODO: reconnect gRPC client to apply changed settings. diff --git a/src/pipecat/services/openai/base_llm.py b/src/pipecat/services/openai/base_llm.py index 960ebd6f7..9ba0583a1 100644 --- a/src/pipecat/services/openai/base_llm.py +++ b/src/pipecat/services/openai/base_llm.py @@ -144,9 +144,12 @@ class BaseOpenAILLMService(LLMService): seed=params.seed, temperature=params.temperature, top_p=params.top_p, + top_k=None, max_tokens=params.max_tokens, max_completion_tokens=params.max_completion_tokens, service_tier=params.service_tier, + filter_incomplete_user_turns=False, + user_turn_completion_config=None, extra=params.extra if isinstance(params.extra, dict) else {}, ) self._retry_timeout_secs = retry_timeout_secs diff --git a/src/pipecat/services/openai/realtime/llm.py b/src/pipecat/services/openai/realtime/llm.py index d765fea75..39c0290fc 100644 --- a/src/pipecat/services/openai/realtime/llm.py +++ b/src/pipecat/services/openai/realtime/llm.py @@ -178,6 +178,15 @@ class OpenAIRealtimeLLMService(LLMService): self._settings = OpenAIRealtimeLLMSettings( model=model, + temperature=None, + max_tokens=None, + top_p=None, + top_k=None, + frequency_penalty=None, + presence_penalty=None, + seed=None, + filter_incomplete_user_turns=False, + user_turn_completion_config=None, session_properties=session_properties or events.SessionProperties(), ) self._sync_model_name_to_metrics() @@ -415,9 +424,9 @@ class OpenAIRealtimeLLMService(LLMService): """ # Backward-compatible dict path: frame.settings contains SessionProperties # fields, not our Settings fields, so we construct SessionProperties - # directly. The frame.update path falls through to super, which calls + # directly. The frame.delta path falls through to super, which calls # _update_settings → our override handles the rest. - if isinstance(frame, LLMUpdateSettingsFrame) and frame.update is None: + if isinstance(frame, LLMUpdateSettingsFrame) and frame.delta is None: self._settings.session_properties = events.SessionProperties(**frame.settings) await self._send_session_update() await self.push_frame(frame, direction) @@ -536,9 +545,9 @@ class OpenAIRealtimeLLMService(LLMService): # treat a send-side error as fatal. await self.push_error(error_msg=f"Error sending client event: {e}", exception=e) - async def _update_settings(self, update): - """Apply a settings update, sending a session update if needed.""" - changed = await super()._update_settings(update) + async def _update_settings(self, delta): + """Apply a settings delta, sending a session update if needed.""" + changed = await super()._update_settings(delta) if "session_properties" in changed: await self._send_session_update() self._warn_unhandled_updated_settings(changed.keys() - {"session_properties"}) diff --git a/src/pipecat/services/openai/stt.py b/src/pipecat/services/openai/stt.py index 13a37a2b1..8b690d015 100644 --- a/src/pipecat/services/openai/stt.py +++ b/src/pipecat/services/openai/stt.py @@ -35,7 +35,7 @@ from pipecat.frames.frames import ( VADUserStoppedSpeakingFrame, ) from pipecat.processors.frame_processor import FrameDirection -from pipecat.services.settings import NOT_GIVEN, STTSettings, _NotGiven, is_given +from pipecat.services.settings import NOT_GIVEN, STTSettings, _NotGiven from pipecat.services.stt_latency import OPENAI_REALTIME_TTFS_P99, OPENAI_TTFS_P99 from pipecat.services.stt_service import WebsocketSTTService from pipecat.services.whisper.base_stt import BaseWhisperSTTService, Transcription @@ -268,19 +268,19 @@ class OpenAIRealtimeSTTService(WebsocketSTTService): """ return True - async def _update_settings(self, update: STTSettings) -> dict[str, Any]: - """Apply a settings update and send session update if needed. + async def _update_settings(self, delta: STTSettings) -> dict[str, Any]: + """Apply a settings delta and send session update if needed. Keeps ``_language_code`` and ``_prompt`` in sync with settings and sends a ``session.update`` to the server when the session is active. Args: - update: A :class:`STTSettings` (or ``OpenAIRealtimeSTTSettings``) delta. + delta: A :class:`STTSettings` (or ``OpenAIRealtimeSTTSettings``) delta. Returns: Dict mapping changed field names to their previous values. """ - changed = await super()._update_settings(update) + changed = await super()._update_settings(delta) if not changed: return changed diff --git a/src/pipecat/services/openai_realtime_beta/openai.py b/src/pipecat/services/openai_realtime_beta/openai.py index efac34223..6ffccfbef 100644 --- a/src/pipecat/services/openai_realtime_beta/openai.py +++ b/src/pipecat/services/openai_realtime_beta/openai.py @@ -163,6 +163,15 @@ class OpenAIRealtimeBetaLLMService(LLMService): self._settings = OpenAIRealtimeBetaLLMSettings( model=model, + temperature=None, + max_tokens=None, + top_p=None, + top_k=None, + frequency_penalty=None, + presence_penalty=None, + seed=None, + filter_incomplete_user_turns=False, + user_turn_completion_config=None, session_properties=session_properties or events.SessionProperties(), ) self._sync_model_name_to_metrics() @@ -361,9 +370,9 @@ class OpenAIRealtimeBetaLLMService(LLMService): """ # Backward-compatible dict path: frame.settings contains SessionProperties # fields, not our Settings fields, so we construct SessionProperties - # directly. The frame.update path falls through to super, which calls + # directly. The frame.delta path falls through to super, which calls # _update_settings → our override handles the rest. - if isinstance(frame, LLMUpdateSettingsFrame) and frame.update is None: + if isinstance(frame, LLMUpdateSettingsFrame) and frame.delta is None: self._settings.session_properties = events.SessionProperties(**frame.settings) await self._send_session_update() await self.push_frame(frame, direction) @@ -480,9 +489,9 @@ class OpenAIRealtimeBetaLLMService(LLMService): # treat a send-side error as fatal. await self.push_error(error_msg=f"Error sending client event: {e}", exception=e) - async def _update_settings(self, update): - """Apply a settings update, sending a session update if needed.""" - changed = await super()._update_settings(update) + async def _update_settings(self, delta): + """Apply a settings delta, sending a session update if needed.""" + changed = await super()._update_settings(delta) if "session_properties" in changed: await self._send_session_update() return changed diff --git a/src/pipecat/services/perplexity/llm.py b/src/pipecat/services/perplexity/llm.py index 04f25621d..e03bace8d 100644 --- a/src/pipecat/services/perplexity/llm.py +++ b/src/pipecat/services/perplexity/llm.py @@ -11,8 +11,6 @@ an OpenAI-compatible interface. It handles Perplexity's unique token usage reporting patterns while maintaining compatibility with the Pipecat framework. """ -from openai import NOT_GIVEN - from pipecat.adapters.services.open_ai_adapter import OpenAILLMInvocationParams from pipecat.metrics.metrics import LLMTokenUsage from pipecat.processors.aggregators.llm_context import LLMContext @@ -72,15 +70,15 @@ class PerplexityLLMService(OpenAILLMService): } # Add OpenAI-compatible parameters if they're set - if self._settings.frequency_penalty is not NOT_GIVEN: + if self._settings.frequency_penalty is not None: params["frequency_penalty"] = self._settings.frequency_penalty - if self._settings.presence_penalty is not NOT_GIVEN: + if self._settings.presence_penalty is not None: params["presence_penalty"] = self._settings.presence_penalty - if self._settings.temperature is not NOT_GIVEN: + if self._settings.temperature is not None: params["temperature"] = self._settings.temperature - if self._settings.top_p is not NOT_GIVEN: + if self._settings.top_p is not None: params["top_p"] = self._settings.top_p - if self._settings.max_tokens is not NOT_GIVEN: + if self._settings.max_tokens is not None: params["max_tokens"] = self._settings.max_tokens return params diff --git a/src/pipecat/services/piper/tts.py b/src/pipecat/services/piper/tts.py index 0b43d96d2..e6a2c6943 100644 --- a/src/pipecat/services/piper/tts.py +++ b/src/pipecat/services/piper/tts.py @@ -71,7 +71,7 @@ class PiperTTSService(TTSService): """ super().__init__(**kwargs) - self._settings = PiperTTSSettings(voice=voice_id) + self._settings = PiperTTSSettings(model=None, voice=voice_id, language=None) download_dir = download_dir or Path.cwd() @@ -96,12 +96,12 @@ class PiperTTSService(TTSService): """ return True - async def _update_settings(self, update: PiperTTSSettings) -> dict[str, Any]: - """Apply a settings update. + async def _update_settings(self, delta: PiperTTSSettings) -> dict[str, Any]: + """Apply a settings delta. Settings are stored but not applied to the active connection. """ - changed = await super()._update_settings(update) + changed = await super()._update_settings(delta) if not changed: return changed # TODO: voice changes would require re-downloading and loading the model. @@ -207,7 +207,7 @@ class PiperHttpTTSService(TTSService): self._base_url = base_url self._session = aiohttp_session - self._settings = PiperHttpTTSSettings(voice=voice_id) + self._settings = PiperHttpTTSSettings(model=None, voice=voice_id, language=None) def can_generate_metrics(self) -> bool: """Check if this service can generate processing metrics. diff --git a/src/pipecat/services/playht/tts.py b/src/pipecat/services/playht/tts.py index ff34725f9..08a87209c 100644 --- a/src/pipecat/services/playht/tts.py +++ b/src/pipecat/services/playht/tts.py @@ -34,7 +34,7 @@ from pipecat.frames.frames import ( TTSStoppedFrame, ) from pipecat.processors.frame_processor import FrameDirection -from pipecat.services.settings import NOT_GIVEN, TTSSettings, _NotGiven, is_given +from pipecat.services.settings import NOT_GIVEN, TTSSettings, _NotGiven from pipecat.services.tts_service import InterruptibleTTSService, TTSService from pipecat.transcriptions.language import Language, resolve_language from pipecat.utils.tracing.service_decorators import traced_tts @@ -204,6 +204,7 @@ class PlayHTTTSService(InterruptibleTTSService): voice_engine=voice_engine, speed=params.speed, seed=params.seed, + playht_sample_rate=0, ) self._sync_model_name_to_metrics() @@ -215,12 +216,12 @@ class PlayHTTTSService(InterruptibleTTSService): """ return True - async def _update_settings(self, update: TTSSettings) -> dict[str, Any]: - """Apply a settings update. + async def _update_settings(self, delta: TTSSettings) -> dict[str, Any]: + """Apply a settings delta. Settings are stored but not applied to the active connection. """ - changed = await super()._update_settings(update) + changed = await super()._update_settings(delta) if not changed: return changed @@ -569,6 +570,7 @@ class PlayHTHttpTTSService(TTSService): voice_engine=voice_engine, speed=params.speed, seed=params.seed, + playht_sample_rate=0, ) self._sync_model_name_to_metrics() diff --git a/src/pipecat/services/resembleai/tts.py b/src/pipecat/services/resembleai/tts.py index 177a4c10e..b1b8d1de8 100644 --- a/src/pipecat/services/resembleai/tts.py +++ b/src/pipecat/services/resembleai/tts.py @@ -100,6 +100,7 @@ class ResembleAITTSService(AudioContextTTSService): self._api_key = api_key self._url = url self._settings = ResembleAITTSSettings( + model=None, voice=voice_id, precision=precision, output_format=output_format, diff --git a/src/pipecat/services/rime/tts.py b/src/pipecat/services/rime/tts.py index 6e795cc3d..6c3ff4e23 100644 --- a/src/pipecat/services/rime/tts.py +++ b/src/pipecat/services/rime/tts.py @@ -31,7 +31,7 @@ from pipecat.frames.frames import ( TTSStoppedFrame, ) from pipecat.processors.frame_processor import FrameDirection -from pipecat.services.settings import NOT_GIVEN, TTSSettings, _NotGiven, is_given +from pipecat.services.settings import NOT_GIVEN, TTSSettings, _NotGiven from pipecat.services.tts_service import ( AudioContextTTSService, InterruptibleTTSService, @@ -233,27 +233,19 @@ class RimeTTSService(AudioContextTTSService): samplingRate=0, # updated in start() language=self.language_to_service_language(params.language) if params.language - else NOT_GIVEN, - segment=params.segment if params.segment is not None else NOT_GIVEN, + else None, + segment=params.segment, # Arcana params - repetition_penalty=params.repetition_penalty - if params.repetition_penalty is not None - else NOT_GIVEN, - temperature=params.temperature if params.temperature is not None else NOT_GIVEN, - top_p=params.top_p if params.top_p is not None else NOT_GIVEN, + repetition_penalty=params.repetition_penalty, + temperature=params.temperature, + top_p=params.top_p, # Mistv2 params - speedAlpha=params.speed_alpha if params.speed_alpha is not None else NOT_GIVEN, - reduceLatency=params.reduce_latency if params.reduce_latency is not None else NOT_GIVEN, - pauseBetweenBrackets=params.pause_between_brackets - if params.pause_between_brackets is not None - else NOT_GIVEN, - phonemizeBetweenBrackets=params.phonemize_between_brackets - if params.phonemize_between_brackets is not None - else NOT_GIVEN, - noTextNormalization=params.no_text_normalization - if params.no_text_normalization is not None - else NOT_GIVEN, - saveOovs=params.save_oovs if params.save_oovs is not None else NOT_GIVEN, + speedAlpha=params.speed_alpha, + reduceLatency=params.reduce_latency, + pauseBetweenBrackets=params.pause_between_brackets, + phonemizeBetweenBrackets=params.phonemize_between_brackets, + noTextNormalization=params.no_text_normalization, + saveOovs=params.save_oovs, ) self._sync_model_name_to_metrics() @@ -295,32 +287,32 @@ class RimeTTSService(AudioContextTTSService): "audioFormat": self._settings.audioFormat, "samplingRate": self._settings.samplingRate, } - if is_given(self._settings.language): + if self._settings.language is not None: params["lang"] = self._settings.language - if is_given(self._settings.segment): + if self._settings.segment is not None: params["segment"] = self._settings.segment if self._settings.model == "arcana": - if is_given(self._settings.repetition_penalty): + if self._settings.repetition_penalty is not None: params["repetition_penalty"] = self._settings.repetition_penalty - if is_given(self._settings.temperature): + if self._settings.temperature is not None: params["temperature"] = self._settings.temperature - if is_given(self._settings.top_p): + if self._settings.top_p is not None: params["top_p"] = self._settings.top_p else: # mistv2/mist - if is_given(self._settings.speedAlpha): + if self._settings.speedAlpha is not None: params["speedAlpha"] = self._settings.speedAlpha - if is_given(self._settings.reduceLatency): + if self._settings.reduceLatency is not None: params["reduceLatency"] = self._settings.reduceLatency - if is_given(self._settings.pauseBetweenBrackets): + if self._settings.pauseBetweenBrackets is not None: params["pauseBetweenBrackets"] = json.dumps(self._settings.pauseBetweenBrackets) - if is_given(self._settings.phonemizeBetweenBrackets): + if self._settings.phonemizeBetweenBrackets is not None: params["phonemizeBetweenBrackets"] = json.dumps( self._settings.phonemizeBetweenBrackets ) - if is_given(self._settings.noTextNormalization): + if self._settings.noTextNormalization is not None: params["noTextNormalization"] = json.dumps(self._settings.noTextNormalization) - if is_given(self._settings.saveOovs): + if self._settings.saveOovs is not None: params["saveOovs"] = json.dumps(self._settings.saveOovs) return params @@ -350,13 +342,13 @@ class RimeTTSService(AudioContextTTSService): self._extra_msg_fields["inlineSpeedAlpha"] = ",".join(speed_vals + [str(speed)]) return f"[{text}]" - async def _update_settings(self, update: TTSSettings) -> dict[str, Any]: - """Apply a settings update and reconnect if necessary. + async def _update_settings(self, delta: TTSSettings) -> dict[str, Any]: + """Apply a settings delta and reconnect if necessary. Since all settings are WebSocket URL query parameters, any setting change requires reconnecting to apply the new values. """ - changed = await super()._update_settings(update) + changed = await super()._update_settings(delta) if changed and self._websocket: await self._disconnect() @@ -665,11 +657,19 @@ class RimeHttpTTSService(TTSService): language=self.language_to_service_language(params.language) if params.language else "eng", + audioFormat="pcm", + samplingRate=0, + segment=None, speedAlpha=params.speed_alpha, reduceLatency=params.reduce_latency, pauseBetweenBrackets=params.pause_between_brackets, phonemizeBetweenBrackets=params.phonemize_between_brackets, - inlineSpeedAlpha=params.inline_speed_alpha if params.inline_speed_alpha else NOT_GIVEN, + noTextNormalization=None, + saveOovs=None, + inlineSpeedAlpha=params.inline_speed_alpha if params.inline_speed_alpha else None, + repetition_penalty=None, + temperature=None, + top_p=None, voice=voice_id, ) self._sync_model_name_to_metrics() @@ -719,7 +719,7 @@ class RimeHttpTTSService(TTSService): "pauseBetweenBrackets": self._settings.pauseBetweenBrackets, "phonemizeBetweenBrackets": self._settings.phonemizeBetweenBrackets, } - if is_given(self._settings.inlineSpeedAlpha): + if self._settings.inlineSpeedAlpha is not None: payload["inlineSpeedAlpha"] = self._settings.inlineSpeedAlpha payload["text"] = text payload["speaker"] = self._settings.voice @@ -846,13 +846,11 @@ class RimeNonJsonTTSService(InterruptibleTTSService): samplingRate=sample_rate, language=self.language_to_service_language(params.language) if params.language - else NOT_GIVEN, - segment=params.segment if params.segment is not None else NOT_GIVEN, - repetition_penalty=params.repetition_penalty - if params.repetition_penalty is not None - else NOT_GIVEN, - temperature=params.temperature if params.temperature is not None else NOT_GIVEN, - top_p=params.top_p if params.top_p is not None else NOT_GIVEN, + else None, + segment=params.segment, + repetition_penalty=params.repetition_penalty, + temperature=params.temperature, + top_p=params.top_p, ) self._sync_model_name_to_metrics() # Add any extra parameters for future compatibility @@ -940,15 +938,15 @@ class RimeNonJsonTTSService(InterruptibleTTSService): "audioFormat": self._settings.audioFormat, "samplingRate": self._settings.samplingRate, } - if is_given(self._settings.language): + if self._settings.language is not None: settings_dict["lang"] = self._settings.language - if is_given(self._settings.segment): + if self._settings.segment is not None: settings_dict["segment"] = self._settings.segment - if is_given(self._settings.repetition_penalty): + if self._settings.repetition_penalty is not None: settings_dict["repetition_penalty"] = self._settings.repetition_penalty - if is_given(self._settings.temperature): + if self._settings.temperature is not None: settings_dict["temperature"] = self._settings.temperature - if is_given(self._settings.top_p): + if self._settings.top_p is not None: settings_dict["top_p"] = self._settings.top_p # Include extras settings_dict.update(self._settings.extra) @@ -1046,13 +1044,13 @@ class RimeNonJsonTTSService(InterruptibleTTSService): except Exception as e: yield ErrorFrame(error=f"Unknown error occurred: {e}") - async def _update_settings(self, update: TTSSettings) -> dict[str, Any]: - """Apply a settings update and reconnect if necessary. + async def _update_settings(self, delta: TTSSettings) -> dict[str, Any]: + """Apply a settings delta and reconnect if necessary. Since all settings are WebSocket URL query parameters, any setting change requires reconnecting to apply the new values. """ - changed = await super()._update_settings(update) + changed = await super()._update_settings(delta) if changed: logger.debug("Settings changed, reconnecting WebSocket with new parameters") diff --git a/src/pipecat/services/sarvam/stt.py b/src/pipecat/services/sarvam/stt.py index 0128c1a22..02d6e250f 100644 --- a/src/pipecat/services/sarvam/stt.py +++ b/src/pipecat/services/sarvam/stt.py @@ -274,8 +274,8 @@ class SarvamSTTService(STTService): self._settings = SarvamSTTSettings( model=model, language=params.language, - prompt=params.prompt if params.prompt is not None else NOT_GIVEN, - mode=mode if mode is not None else NOT_GIVEN, + prompt=params.prompt, + mode=mode, vad_signals=params.vad_signals, high_vad_sensitivity=params.high_vad_sensitivity, ) @@ -329,11 +329,11 @@ class SarvamSTTService(STTService): if self._socket_client: await self._socket_client.flush() - async def _update_settings(self, update: STTSettings) -> dict[str, Any]: - """Apply a settings update, validate, sync state, and reconnect. + async def _update_settings(self, delta: STTSettings) -> dict[str, Any]: + """Apply a settings delta, validate, sync state, and reconnect. Args: - update: A :class:`STTSettings` (or ``SarvamSTTSettings``) delta. + delta: A :class:`STTSettings` (or ``SarvamSTTSettings``) delta. Returns: Dict mapping changed field names to their previous values. @@ -342,26 +342,26 @@ class SarvamSTTService(STTService): ValueError: If a setting is not supported by the current model. """ # Validate against model capabilities before applying - if is_given(update.language) and update.language is not None: + if is_given(delta.language) and delta.language is not None: if not self._config.supports_language: raise ValueError( f"Model '{self._settings.model}' does not support language parameter " "(auto-detects language)." ) - if isinstance(update, SarvamSTTSettings): - if is_given(update.prompt) and update.prompt is not None: + if isinstance(delta, SarvamSTTSettings): + if is_given(delta.prompt) and delta.prompt is not None: if not self._config.supports_prompt: raise ValueError( f"Model '{self._settings.model}' does not support prompt parameter." ) - if is_given(update.mode) and update.mode is not None: + if is_given(delta.mode) and delta.mode is not None: if not self._config.supports_mode: raise ValueError( f"Model '{self._settings.model}' does not support mode parameter." ) - changed = await super()._update_settings(update) + changed = await super()._update_settings(delta) # TODO: someday we could reconnect here to apply updated settings. # Code might look something like the below: @@ -510,16 +510,12 @@ class SarvamSTTService(STTService): connect_kwargs["language_code"] = language_string # Add mode for models that support it - if self._config.supports_mode and is_given(self._settings.mode): + if self._config.supports_mode and self._settings.mode is not None: connect_kwargs["mode"] = self._settings.mode # Prompt support differs across sarvamai versions. Prefer connect-time prompt # when available and gracefully degrade if the SDK doesn't accept it. - if ( - is_given(self._settings.prompt) - and self._settings.prompt is not None - and self._config.supports_prompt - ): + if self._settings.prompt is not None and self._config.supports_prompt: connect_kwargs["prompt"] = self._settings.prompt def _connect_with_sdk_headers(connect_fn, **kwargs): @@ -561,11 +557,7 @@ class SarvamSTTService(STTService): self._socket_client = await self._websocket_context.__aenter__() # Fallback for SDKs that support runtime prompt updates. - if ( - is_given(self._settings.prompt) - and self._settings.prompt is not None - and self._config.supports_prompt - ): + if self._settings.prompt is not None and self._config.supports_prompt: prompt_setter = getattr(self._socket_client, "set_prompt", None) if callable(prompt_setter): await prompt_setter(self._settings.prompt) diff --git a/src/pipecat/services/sarvam/tts.py b/src/pipecat/services/sarvam/tts.py index 191689f5a..45c283ff1 100644 --- a/src/pipecat/services/sarvam/tts.py +++ b/src/pipecat/services/sarvam/tts.py @@ -62,7 +62,7 @@ from pipecat.frames.frames import ( ) from pipecat.processors.frame_processor import FrameDirection from pipecat.services.sarvam._sdk import sdk_headers -from pipecat.services.settings import NOT_GIVEN, TTSSettings, _NotGiven, is_given +from pipecat.services.settings import NOT_GIVEN, TTSSettings, _NotGiven from pipecat.services.tts_service import InterruptibleTTSService, TTSService from pipecat.transcriptions.language import Language, resolve_language from pipecat.utils.tracing.service_decorators import traced_tts @@ -486,6 +486,9 @@ class SarvamHttpTTSService(TTSService): True if self._config.preprocessing_always_enabled else params.enable_preprocessing ), pace=pace, + pitch=None, + loudness=None, + temperature=None, model=model, voice=voice_id, ) @@ -559,19 +562,19 @@ class SarvamHttpTTSService(TTSService): "sample_rate": self.sample_rate, "enable_preprocessing": self._settings.enable_preprocessing, "model": self._settings.model, - "pace": self._settings.pace if is_given(self._settings.pace) else 1.0, + "pace": self._settings.pace if self._settings.pace is not None else 1.0, } # Add model-specific parameters based on config if self._config.supports_pitch: - payload["pitch"] = self._settings.pitch if is_given(self._settings.pitch) else 0.0 + payload["pitch"] = self._settings.pitch if self._settings.pitch is not None else 0.0 if self._config.supports_loudness: payload["loudness"] = ( - self._settings.loudness if is_given(self._settings.loudness) else 1.0 + self._settings.loudness if self._settings.loudness is not None else 1.0 ) if self._config.supports_temperature: payload["temperature"] = ( - self._settings.temperature if is_given(self._settings.temperature) else 0.6 + self._settings.temperature if self._settings.temperature is not None else 0.6 ) headers = { @@ -849,6 +852,9 @@ class SarvamTTSService(InterruptibleTTSService): output_audio_codec=params.output_audio_codec, output_audio_bitrate=params.output_audio_bitrate, pace=pace, + pitch=None, + loudness=None, + temperature=None, model=model, voice=voice_id, ) @@ -949,9 +955,9 @@ class SarvamTTSService(InterruptibleTTSService): if isinstance(frame, (LLMFullResponseEndFrame, EndFrame)): await self.flush_audio() - async def _update_settings(self, update: TTSSettings) -> dict[str, Any]: - """Apply a settings update and resend config if voice changed.""" - changed = await super()._update_settings(update) + async def _update_settings(self, delta: TTSSettings) -> dict[str, Any]: + """Apply a settings delta and resend config if voice changed.""" + changed = await super()._update_settings(delta) if changed: await self._send_config() @@ -1027,11 +1033,11 @@ class SarvamTTSService(InterruptibleTTSService): "pace": self._settings.pace, "model": self._settings.model, } - if is_given(self._settings.pitch): + if self._settings.pitch is not None: config_data["pitch"] = self._settings.pitch - if is_given(self._settings.loudness): + if self._settings.loudness is not None: config_data["loudness"] = self._settings.loudness - if is_given(self._settings.temperature): + if self._settings.temperature is not None: config_data["temperature"] = self._settings.temperature logger.debug(f"Config being sent is {config_data}") config_message = {"type": "config", "data": config_data} diff --git a/src/pipecat/services/settings.py b/src/pipecat/services/settings.py index 4664ecd39..7de476c64 100644 --- a/src/pipecat/services/settings.py +++ b/src/pipecat/services/settings.py @@ -6,24 +6,32 @@ """Settings infrastructure for Pipecat AI services. -This module provides dataclass-based settings objects for service configuration. -Each service type has a corresponding settings class (e.g. ``TTSSettings``, -``LLMSettings``) whose fields use the ``NOT_GIVEN`` sentinel to distinguish -"leave unchanged" from an explicit ``None``. +Each service type has a settings dataclass (``LLMSettings``, ``TTSSettings``, +``STTSettings``, or a service-specific subclass). The same class is used in +two distinct modes: -Key concepts: +**Store mode** — the service's ``self._settings`` object that holds the full +current state. Every field must have a real value; ``NOT_GIVEN`` is never +valid here. Services that don't support an inherited field should set it to +``None``. ``validate_complete()`` (called automatically in +``AIService.start()``) enforces this invariant. -- **NOT_GIVEN sentinel**: A value meaning "this field was not provided in the - update". Distinct from ``None`` (which may be a valid value for a setting). -- **Settings as both state and delta**: The same class is used for the - service's current settings *and* for update objects. Fields set to - ``NOT_GIVEN`` are simply skipped when applying an update. -- **apply_update**: Applies a delta onto a target settings object and returns - a dict mapping each changed field name to its previous value. -- **from_mapping**: Constructs a settings object from a plain dict, - supporting field aliases (e.g. ``"voice_id"`` → ``"voice"``). -- **Extras**: Unknown keys land in the ``extra`` dict so services that have - non-standard settings don't lose data. +**Delta mode** — a sparse update object carried by an +``*UpdateSettingsFrame``. Only the fields the caller wants to change are set; +all others remain at their default of ``NOT_GIVEN``. ``apply_update()`` +merges a delta into a store, skipping any ``NOT_GIVEN`` fields. + +Key helpers: + +- ``NOT_GIVEN`` / ``is_given()`` — sentinel and check for "field not provided + in this delta". +- ``apply_update(delta)`` — merge a delta into a store, returning changed + fields. +- ``from_mapping(dict)`` — build a delta from a plain dict (for backward + compatibility with dict-based ``*UpdateSettingsFrame``). +- ``validate_complete()`` — assert that a store has no ``NOT_GIVEN`` fields. +- ``extra`` dict — overflow for service-specific keys that don't map to a + declared field. """ from __future__ import annotations @@ -45,12 +53,15 @@ if TYPE_CHECKING: class _NotGiven: - """Sentinel indicating a settings field was not provided. + """Sentinel meaning "this field was not included in the delta". - ``NOT_GIVEN`` means "the caller did not supply this value" — distinct from - ``None``, which may be a legitimate setting value. It is used as the - default for every settings field so that ``apply_update`` can tell which - fields the caller actually wants to change. + ``NOT_GIVEN`` is distinct from ``None`` (which is a valid stored value, + typically meaning "this service doesn't support this field"). Every + settings field defaults to ``NOT_GIVEN`` so that delta-mode objects are + sparse by default and ``apply_update`` can skip untouched fields. + + ``NOT_GIVEN`` must never appear in a store-mode object — see + ``validate_complete()``. """ _instance: Optional[_NotGiven] = None @@ -68,11 +79,25 @@ class _NotGiven: NOT_GIVEN: _NotGiven = _NotGiven() -"""Singleton sentinel meaning "this field was not included in the update".""" +"""Singleton sentinel meaning "this field was not included in the delta". + +Valid only in delta-mode settings objects. Must never appear in a service's +``self._settings`` (store mode) — use ``None`` instead for unsupported fields. +""" def is_given(value: Any) -> bool: - """Check whether a value was explicitly provided (i.e. is not ``NOT_GIVEN``). + """Check whether a delta field was explicitly provided. + + Typically used when processing a delta to decide whether a field + should be applied:: + + if is_given(delta.voice): + # caller wants to change the voice + ... + + For store-mode objects this always returns ``True`` (since + ``validate_complete`` ensures no ``NOT_GIVEN`` fields remain). Args: value: The value to check. @@ -94,28 +119,38 @@ _S = TypeVar("_S", bound="ServiceSettings") class ServiceSettings: """Base class for runtime-updatable service settings. - These settings represent the subset of a service's configuration that can + These settings capture the subset of a service's configuration that can be changed **while the pipeline is running** (e.g. switching the model or changing the voice). They are *not* meant to capture every constructor parameter — only those that support live updates via ``*UpdateSettingsFrame``. Every AI service type (LLM, TTS, STT) extends this with its own fields. - Fields default to ``NOT_GIVEN`` so that an instance can represent either - the full current state **or** a sparse update delta. Note that in the full - current state, **all fields will be given** (i.e. ``NOT_GIVEN`` is reserved - for update deltas). + Each instance operates in one of two modes (see module docstring): + + - **Store mode** (``self._settings``): holds the full current state. + Every field must be a real value — ``NOT_GIVEN`` is never valid. + Use ``None`` for inherited fields the service doesn't support. + Enforced at runtime by ``validate_complete()``. + - **Delta mode** (``*UpdateSettingsFrame``): a sparse update. + Only fields the caller wants to change are set; all others stay at + the default ``NOT_GIVEN`` and are skipped by ``apply_update()``. Parameters: - model: The model identifier used by the service. + model: The model identifier used by the service. Set to ``None`` + in store mode if the service has no model concept. extra: Overflow dict for service-specific keys that don't map to a declared field. """ # -- common fields ------------------------------------------------------- - model: str | _NotGiven = field(default_factory=lambda: NOT_GIVEN) - """AI model identifier (e.g. ``"gpt-4o"``, ``"eleven_turbo_v2_5"``).""" + model: str | None | _NotGiven = field(default_factory=lambda: NOT_GIVEN) + """AI model identifier (e.g. ``"gpt-4o"``, ``"eleven_turbo_v2_5"``). + + Defaults to ``NOT_GIVEN`` for delta mode. In store mode, set to a + model string or ``None`` if the service has no model concept. + """ extra: Dict[str, Any] = field(default_factory=dict) """Catch-all for service-specific keys that have no declared field.""" @@ -132,10 +167,14 @@ class ServiceSettings: # -- public API ---------------------------------------------------------- def given_fields(self) -> Dict[str, Any]: - """Return a dict of only the fields that were explicitly provided. + """Return a dict of only the fields that are not ``NOT_GIVEN``. - Skips ``NOT_GIVEN`` values and the ``extra`` field itself. Entries - from ``extra`` are included at the top level. + Primarily useful for delta-mode objects to inspect which fields were + set. For a store-mode object this returns all declared fields (since + none should be ``NOT_GIVEN``). + + Skips the ``extra`` field itself but merges its entries into the + returned dict at the top level. Returns: Dictionary mapping field names to their provided values. @@ -150,18 +189,18 @@ class ServiceSettings: result.update(self.extra) return result - def apply_update(self: _S, update: _S) -> Dict[str, Any]: - """Apply *update* onto this settings object, returning changed fields. + def apply_update(self: _S, delta: _S) -> Dict[str, Any]: + """Merge a delta-mode object into this store-mode object. - Only fields in *update* that are **given** (i.e. not ``NOT_GIVEN``) + Only fields in *delta* that are **given** (i.e. not ``NOT_GIVEN``) are considered. A field is "changed" if its new value differs from the current value. - The ``extra`` dicts are merged: keys present in the update overwrite + The ``extra`` dicts are merged: keys present in the delta overwrite keys in the target. Args: - update: A settings object of the same type containing the delta. + delta: A delta-mode settings object of the same type. Returns: A dict mapping each changed field name to its **pre-update** value. @@ -170,7 +209,9 @@ class ServiceSettings: Examples:: + # store-mode object (all fields given) current = TTSSettings(voice="alice", language="en") + # delta-mode object (only voice is set) delta = TTSSettings(voice="bob") changed = current.apply_update(delta) # changed == {"voice": "alice"} @@ -180,7 +221,7 @@ class ServiceSettings: for f in fields(self): if f.name == "extra": continue - new_val = getattr(update, f.name) + new_val = getattr(delta, f.name) if not is_given(new_val): continue old_val = getattr(self, f.name) @@ -189,7 +230,7 @@ class ServiceSettings: changed[f.name] = old_val # Merge extra - for key, new_val in update.extra.items(): + for key, new_val in delta.extra.items(): old_val = self.extra.get(key, NOT_GIVEN) if old_val != new_val: self.extra[key] = new_val @@ -199,10 +240,12 @@ class ServiceSettings: @classmethod def from_mapping(cls: Type[_S], settings: Mapping[str, Any]) -> _S: - """Construct a settings object from a plain dictionary. + """Build a **delta-mode** settings object from a plain dictionary. This exists for backward compatibility with code that passes plain - dicts via ``*UpdateSettingsFrame(settings={...})``. + dicts via ``*UpdateSettingsFrame(settings={...})``. The returned + object is a delta: only the keys present in *settings* are set; + all other fields remain ``NOT_GIVEN``. Keys are matched to dataclass fields by name. Keys listed in ``_aliases`` are translated to their canonical name first. Any @@ -212,13 +255,14 @@ class ServiceSettings: settings: A dictionary of setting names to values. Returns: - A new settings instance with the corresponding fields populated. + A new delta-mode settings instance. Examples:: - update = TTSSettings.from_mapping({"voice_id": "alice", "speed": 1.2}) - # update.voice == "alice" (via alias) - # update.extra == {"speed": 1.2} + delta = TTSSettings.from_mapping({"voice_id": "alice", "speed": 1.2}) + # delta.voice == "alice" (via alias) + # delta.language is NOT_GIVEN (not in the dict) + # delta.extra == {"speed": 1.2} """ field_names = {f.name for f in fields(cls)} - {"extra"} kwargs: Dict[str, Any] = {} @@ -236,6 +280,31 @@ class ServiceSettings: instance.extra = extra return instance + def validate_complete(self) -> None: + """Check that this is a valid store-mode object (no ``NOT_GIVEN`` fields). + + Called automatically by ``AIService.start()`` to catch fields that a + service forgot to initialize in its ``__init__``. Can also be called + manually after constructing a store-mode settings object. + + Logs a warning for each uninitialized field. Failure to initialize + all fields may or may not cause runtime issues — it depends on + whether and how the service actually reads the field — but it indicates + a deviation from expectations and should be fixed. + """ + missing = [ + f.name + for f in fields(self) + if f.name != "extra" and isinstance(getattr(self, f.name), _NotGiven) + ] + if missing: + names = ", ".join(missing) + logger.error( + f"{type(self).__name__}: the following fields are NOT_GIVEN: {names}. " + f"All settings fields should be initialized in the service's " + f"__init__ (use None for unsupported fields)." + ) + def copy(self: _S) -> _S: """Return a deep copy of this settings instance. @@ -254,7 +323,12 @@ class ServiceSettings: class LLMSettings(ServiceSettings): """Runtime-updatable settings for LLM services. - See ``ServiceSettings`` for the general concept. + Used in both store and delta mode — see ``ServiceSettings``. + + These fields are common across LLM providers. Not every provider supports + every field; in store mode, set unsupported fields to ``None`` (e.g. a + service that doesn't support ``seed`` should initialize it as + ``seed=None``). Parameters: model: LLM model identifier. @@ -274,15 +348,15 @@ class LLMSettings(ServiceSettings): and prompts for incomplete turns. """ - temperature: float | _NotGiven = field(default_factory=lambda: NOT_GIVEN) - max_tokens: int | _NotGiven = field(default_factory=lambda: NOT_GIVEN) - top_p: float | _NotGiven = field(default_factory=lambda: NOT_GIVEN) - top_k: int | _NotGiven = field(default_factory=lambda: NOT_GIVEN) - frequency_penalty: float | _NotGiven = field(default_factory=lambda: NOT_GIVEN) - presence_penalty: float | _NotGiven = field(default_factory=lambda: NOT_GIVEN) - seed: int | _NotGiven = field(default_factory=lambda: NOT_GIVEN) - filter_incomplete_user_turns: bool | _NotGiven = field(default_factory=lambda: NOT_GIVEN) - user_turn_completion_config: UserTurnCompletionConfig | _NotGiven = field( + temperature: float | None | _NotGiven = field(default_factory=lambda: NOT_GIVEN) + max_tokens: int | None | _NotGiven = field(default_factory=lambda: NOT_GIVEN) + top_p: float | None | _NotGiven = field(default_factory=lambda: NOT_GIVEN) + top_k: int | None | _NotGiven = field(default_factory=lambda: NOT_GIVEN) + frequency_penalty: float | None | _NotGiven = field(default_factory=lambda: NOT_GIVEN) + presence_penalty: float | None | _NotGiven = field(default_factory=lambda: NOT_GIVEN) + seed: int | None | _NotGiven = field(default_factory=lambda: NOT_GIVEN) + filter_incomplete_user_turns: bool | None | _NotGiven = field(default_factory=lambda: NOT_GIVEN) + user_turn_completion_config: UserTurnCompletionConfig | None | _NotGiven = field( default_factory=lambda: NOT_GIVEN ) @@ -291,23 +365,25 @@ class LLMSettings(ServiceSettings): class TTSSettings(ServiceSettings): """Runtime-updatable settings for TTS services. - See ``ServiceSettings`` for the general concept. + Used in both store and delta mode — see ``ServiceSettings``. + + In store mode, set unsupported fields to ``None`` (e.g. ``language=None`` + if the service doesn't expose a language setting). Parameters: model: TTS model identifier. voice: Voice identifier or name. - language: Language for speech synthesis. The union type reflects the - *input* side: callers may pass a ``Language`` enum or a raw string. - However, the **stored** value is always a service-specific string - — ``TTSService._update_settings`` converts ``Language`` enums via - ``language_to_service_language()`` before writing, and ``__init__`` - methods do the same at construction time. Code that reads - ``self._settings.language`` after initialisation can treat it as - ``str``. + language: Language for speech synthesis. The union type reflects the + *input* side: callers may pass a ``Language`` enum or a raw string + in a delta. However, the **stored** value (in store mode) is + always a service-specific string or ``None`` — + ``TTSService._update_settings`` converts ``Language`` enums via + ``language_to_service_language()`` before writing, and + ``__init__`` methods do the same at construction time. """ voice: str | _NotGiven = field(default_factory=lambda: NOT_GIVEN) - language: Language | str | _NotGiven = field(default_factory=lambda: NOT_GIVEN) + language: Language | str | None | _NotGiven = field(default_factory=lambda: NOT_GIVEN) _aliases: ClassVar[Dict[str, str]] = {"voice_id": "voice"} @@ -316,18 +392,20 @@ class TTSSettings(ServiceSettings): class STTSettings(ServiceSettings): """Runtime-updatable settings for STT services. - See ``ServiceSettings`` for the general concept. + Used in both store and delta mode — see ``ServiceSettings``. + + In store mode, set unsupported fields to ``None`` (e.g. ``language=None`` + if the service auto-detects language). Parameters: model: STT model identifier. - language: Language for speech recognition. The union type reflects the - *input* side: callers may pass a ``Language`` enum or a raw string. - However, the **stored** value is always a service-specific string - — ``STTService._update_settings`` converts ``Language`` enums via - ``language_to_service_language()`` before writing, and ``__init__`` - methods do the same at construction time. Code that reads - ``self._settings.language`` after initialisation can treat it as - ``str``. + language: Language for speech recognition. The union type reflects the + *input* side: callers may pass a ``Language`` enum or a raw string + in a delta. However, the **stored** value (in store mode) is + always a service-specific string or ``None`` — + ``STTService._update_settings`` converts ``Language`` enums via + ``language_to_service_language()`` before writing, and + ``__init__`` methods do the same at construction time. """ - language: Language | str | _NotGiven = field(default_factory=lambda: NOT_GIVEN) + language: Language | str | None | _NotGiven = field(default_factory=lambda: NOT_GIVEN) diff --git a/src/pipecat/services/soniox/stt.py b/src/pipecat/services/soniox/stt.py index 630e11862..356b23162 100644 --- a/src/pipecat/services/soniox/stt.py +++ b/src/pipecat/services/soniox/stt.py @@ -225,25 +225,25 @@ class SonioxSTTService(WebsocketSTTService): await super().start(frame) await self._connect() - async def _update_settings(self, update: SonioxSTTSettings) -> dict[str, Any]: - """Apply a settings update, keeping ``input_params`` in sync. + async def _update_settings(self, delta: SonioxSTTSettings) -> dict[str, Any]: + """Apply a settings delta, keeping ``input_params`` in sync. Top-level ``model`` is the source of truth. When it is given in - *update* its value is propagated into ``input_params``. When only + *delta* its value is propagated into ``input_params``. When only ``input_params`` is given, its ``model`` is propagated *up* to the top-level field. Settings are stored but not applied to the active connection. Args: - update: A settings delta. + delta: A settings delta. Returns: Dict mapping changed field names to their previous values. """ - model_given = is_given(getattr(update, "model", NOT_GIVEN)) + model_given = is_given(getattr(delta, "model", NOT_GIVEN)) - changed = await super()._update_settings(update) + changed = await super()._update_settings(delta) if not changed: return changed diff --git a/src/pipecat/services/speechmatics/stt.py b/src/pipecat/services/speechmatics/stt.py index 4a476c01f..61bf8b69f 100644 --- a/src/pipecat/services/speechmatics/stt.py +++ b/src/pipecat/services/speechmatics/stt.py @@ -33,7 +33,7 @@ from pipecat.frames.frames import ( VADUserStoppedSpeakingFrame, ) from pipecat.processors.frame_processor import FrameDirection -from pipecat.services.settings import NOT_GIVEN, STTSettings, _NotGiven, is_given +from pipecat.services.settings import NOT_GIVEN, STTSettings, _NotGiven from pipecat.services.stt_latency import SPEECHMATICS_TTFS_P99 from pipecat.services.stt_service import STTService from pipecat.transcriptions.language import Language, resolve_language @@ -429,6 +429,7 @@ class SpeechmaticsSTTService(STTService): # Settings — seeded from InputParams self._settings = SpeechmaticsSTTSettings( + model=None, language=params.language, domain=params.domain, turn_detection_mode=params.turn_detection_mode, @@ -492,8 +493,8 @@ class SpeechmaticsSTTService(STTService): await super().start(frame) await self._connect() - async def _update_settings(self, update: SpeechmaticsSTTSettings) -> dict[str, Any]: - """Apply settings update, reconnecting only when necessary. + async def _update_settings(self, delta: SpeechmaticsSTTSettings) -> dict[str, Any]: + """Apply settings delta, reconnecting only when necessary. Fields are classified into three categories (see ``SpeechmaticsSTTSettings``): @@ -506,12 +507,12 @@ class SpeechmaticsSTTService(STTService): time and therefore require a full disconnect / reconnect. Args: - update: A settings delta. + delta: A settings delta. Returns: Dict mapping changed field names to their previous values. """ - changed = await super()._update_settings(update) + changed = await super()._update_settings(delta) if not changed: return changed @@ -674,21 +675,21 @@ class SpeechmaticsSTTService(STTService): # Language + domain language = s.language config.language = self._language_to_speechmatics_language(language) - config.domain = s.domain if is_given(s.domain) else None + config.domain = s.domain if s.domain is not None else None config.output_locale = self._locale_to_speechmatics_locale(config.language, language) # Speaker config config.speaker_config = SpeakerFocusConfig( - focus_speakers=s.focus_speakers if is_given(s.focus_speakers) else [], - ignore_speakers=s.ignore_speakers if is_given(s.ignore_speakers) else [], - focus_mode=s.focus_mode if is_given(s.focus_mode) else SpeakerFocusMode.RETAIN, + focus_speakers=s.focus_speakers if s.focus_speakers is not None else [], + ignore_speakers=s.ignore_speakers if s.ignore_speakers is not None else [], + focus_mode=s.focus_mode if s.focus_mode is not None else SpeakerFocusMode.RETAIN, ) - config.known_speakers = s.known_speakers if is_given(s.known_speakers) else [] + config.known_speakers = s.known_speakers if s.known_speakers is not None else [] # Custom dictionary - config.additional_vocab = s.additional_vocab if is_given(s.additional_vocab) else [] + config.additional_vocab = s.additional_vocab if s.additional_vocab is not None else [] - # Advanced parameters — only set if given (not NOT_GIVEN or None) + # Advanced parameters — only set if not None for param in [ "operating_point", "max_delay", @@ -703,17 +704,17 @@ class SpeechmaticsSTTService(STTService): "prefer_current_speaker", ]: val = getattr(s, param) - if is_given(val) and val is not None: + if val is not None: setattr(config, param, val) # Extra parameters - if is_given(s.extra_params) and isinstance(s.extra_params, dict): + if isinstance(s.extra_params, dict): for key, value in s.extra_params.items(): if hasattr(config, key): setattr(config, key, value) # Enable sentences - split = s.split_sentences if is_given(s.split_sentences) else False + split = s.split_sentences if s.split_sentences is not None else False config.speech_segment_config = SpeechSegmentConfig(emit_sentences=split or False) return config diff --git a/src/pipecat/services/speechmatics/tts.py b/src/pipecat/services/speechmatics/tts.py index 7c8d9fca5..32fb0c2b3 100644 --- a/src/pipecat/services/speechmatics/tts.py +++ b/src/pipecat/services/speechmatics/tts.py @@ -108,7 +108,9 @@ class SpeechmaticsTTSService(TTSService): params = params or SpeechmaticsTTSService.InputParams() self._settings = SpeechmaticsTTSSettings( + model=None, voice=voice_id, + language=None, max_retries=params.max_retries, ) diff --git a/src/pipecat/services/stt_service.py b/src/pipecat/services/stt_service.py index dfdae6de6..80448223c 100644 --- a/src/pipecat/services/stt_service.py +++ b/src/pipecat/services/stt_service.py @@ -262,8 +262,8 @@ class STTService(AIService): await self._cancel_ttfb_timeout() await self._cancel_keepalive_task() - async def _update_settings(self, update: STTSettings) -> dict[str, Any]: - """Apply an STT settings update. + async def _update_settings(self, delta: STTSettings) -> dict[str, Any]: + """Apply an STT settings delta. Handles ``model`` (via parent). Translates ``Language`` enum values before applying so the stored value is a service-specific string. @@ -272,18 +272,18 @@ class STTService(AIService): changed-field dict. Args: - update: An STT settings delta. + delta: An STT settings delta. Returns: Dict mapping changed field names to their previous values. """ # Translate language *before* applying so the stored value is canonical - if is_given(update.language) and isinstance(update.language, Language): - converted = self.language_to_service_language(update.language) + if is_given(delta.language) and isinstance(delta.language, Language): + converted = self.language_to_service_language(delta.language) if converted is not None: - update.language = converted + delta.language = converted - changed = await super()._update_settings(update) + changed = await super()._update_settings(delta) return changed async def process_audio_frame(self, frame: AudioRawFrame, direction: FrameDirection): @@ -349,20 +349,20 @@ class STTService(AIService): await self._handle_vad_user_stopped_speaking(frame) await self.push_frame(frame, direction) elif isinstance(frame, STTUpdateSettingsFrame): - if frame.update is not None: - await self._update_settings(frame.update) + if frame.delta is not None: + await self._update_settings(frame.delta) elif frame.settings: # Backward-compatible path: convert legacy dict to settings object. with warnings.catch_warnings(): warnings.simplefilter("always") warnings.warn( "Passing a dict via STTUpdateSettingsFrame(settings={...}) is deprecated " - "since 0.0.103, use STTUpdateSettingsFrame(update=STTSettings(...)) instead.", + "since 0.0.103, use STTUpdateSettingsFrame(delta=STTSettings(...)) instead.", DeprecationWarning, stacklevel=2, ) - update = type(self._settings).from_mapping(frame.settings) - await self._update_settings(update) + delta = type(self._settings).from_mapping(frame.settings) + await self._update_settings(delta) elif isinstance(frame, STTMuteFrame): self._muted = frame.mute logger.debug(f"STT service {'muted' if frame.mute else 'unmuted'}") diff --git a/src/pipecat/services/tts_service.py b/src/pipecat/services/tts_service.py index e7b57833d..59920c342 100644 --- a/src/pipecat/services/tts_service.py +++ b/src/pipecat/services/tts_service.py @@ -196,9 +196,7 @@ class TTSService(AIService): self._append_trailing_space: bool = append_trailing_space self._init_sample_rate = sample_rate self._sample_rate = 0 - self._settings = TTSSettings( - voice="" - ) # Here in case subclass doesn't implement more specific settings (hopefully shouldn't happen) + self._settings = TTSSettings() # Here in case subclass doesn't implement more specific settings (hopefully shouldn't happen) self._text_aggregator: BaseTextAggregator = text_aggregator or SimpleTextAggregator() if text_aggregator: import warnings @@ -440,24 +438,24 @@ class TTSService(AIService): if not (agg_type == aggregation_type and func == transform_function) ] - async def _update_settings(self, update: TTSSettings) -> dict[str, Any]: - """Apply a TTS settings update. + async def _update_settings(self, delta: TTSSettings) -> dict[str, Any]: + """Apply a TTS settings delta. Translates language to service-specific value before applying. Args: - update: A TTS settings delta. + delta: A TTS settings delta. Returns: Dict mapping changed field names to their previous values. """ # Translate language *before* applying so the stored value is canonical - if is_given(update.language) and isinstance(update.language, Language): - converted = self.language_to_service_language(update.language) + if is_given(delta.language) and isinstance(delta.language, Language): + converted = self.language_to_service_language(delta.language) if converted is not None: - update.language = converted + delta.language = converted - changed = await super()._update_settings(update) + changed = await super()._update_settings(delta) return changed @@ -548,20 +546,20 @@ class TTSService(AIService): await self.flush_audio() self._processing_text = processing_text elif isinstance(frame, TTSUpdateSettingsFrame): - if frame.update is not None: - await self._update_settings(frame.update) + if frame.delta is not None: + await self._update_settings(frame.delta) elif frame.settings: # Backward-compatible path: convert legacy dict to settings object. with warnings.catch_warnings(): warnings.simplefilter("always") warnings.warn( "Passing a dict via TTSUpdateSettingsFrame(settings={...}) is deprecated " - "since 0.0.103, use TTSUpdateSettingsFrame(update=TTSSettings(...)) instead.", + "since 0.0.103, use TTSUpdateSettingsFrame(delta=TTSSettings(...)) instead.", DeprecationWarning, stacklevel=2, ) - update = type(self._settings).from_mapping(frame.settings) - await self._update_settings(update) + delta = type(self._settings).from_mapping(frame.settings) + await self._update_settings(delta) elif isinstance(frame, BotStoppedSpeakingFrame): await self._maybe_resume_frame_processing() await self.push_frame(frame, direction) diff --git a/src/pipecat/services/ultravox/llm.py b/src/pipecat/services/ultravox/llm.py index 436653c7e..11525258a 100644 --- a/src/pipecat/services/ultravox/llm.py +++ b/src/pipecat/services/ultravox/llm.py @@ -177,7 +177,19 @@ class UltravoxRealtimeLLMService(LLMService): **kwargs: Additional arguments passed to parent LLMService. """ super().__init__(**kwargs) - self._settings = UltravoxRealtimeLLMSettings() + self._settings = UltravoxRealtimeLLMSettings( + model=None, + temperature=None, + max_tokens=None, + top_p=None, + top_k=None, + frequency_penalty=None, + presence_penalty=None, + seed=None, + filter_incomplete_user_turns=False, + user_turn_completion_config=None, + output_medium=None, + ) self._params = params if one_shot_selected_tools: if not isinstance(self._params, OneShotInputParams): @@ -325,8 +337,8 @@ class UltravoxRealtimeLLMService(LLMService): await self.cancel_task(self._receive_task, timeout=1.0) self._receive_task = None - async def _update_settings(self, update: UltravoxRealtimeLLMSettings): - changed = await super()._update_settings(update) + async def _update_settings(self, delta: UltravoxRealtimeLLMSettings): + changed = await super()._update_settings(delta) if "output_medium" in changed: await self._update_output_medium(self._settings.output_medium) self._warn_unhandled_updated_settings(changed.keys() - {"output_medium"}) diff --git a/src/pipecat/services/whisper/base_stt.py b/src/pipecat/services/whisper/base_stt.py index 9def3c2f1..9d2b3ab51 100644 --- a/src/pipecat/services/whisper/base_stt.py +++ b/src/pipecat/services/whisper/base_stt.py @@ -174,13 +174,13 @@ class BaseWhisperSTTService(SegmentedSTTService): def _create_client(self, api_key: Optional[str], base_url: Optional[str]): return AsyncOpenAI(api_key=api_key, base_url=base_url) - async def _update_settings(self, update: STTSettings) -> dict[str, Any]: - """Apply a settings update, syncing instance variables. + async def _update_settings(self, delta: STTSettings) -> dict[str, Any]: + """Apply a settings delta, syncing instance variables. Keeps ``_language``, ``_prompt``, and ``_temperature`` in sync with the settings fields. """ - changed = await super()._update_settings(update) + changed = await super()._update_settings(delta) if "language" in changed: self._language = self._settings.language diff --git a/src/pipecat/services/xtts/tts.py b/src/pipecat/services/xtts/tts.py index ba2eb4fc2..ab06ffb5a 100644 --- a/src/pipecat/services/xtts/tts.py +++ b/src/pipecat/services/xtts/tts.py @@ -114,6 +114,7 @@ class XTTSService(TTSService): super().__init__(sample_rate=sample_rate, **kwargs) self._settings = XTTSTTSSettings( + model=None, voice=voice_id, language=self.language_to_service_language(language), base_url=base_url, From 8c9ccf8f82aa83ed6f877f14eba3dfab0a30cfd5 Mon Sep 17 00:00:00 2001 From: Paul Kompfner Date: Tue, 24 Feb 2026 11:47:29 -0500 Subject: [PATCH 0616/1060] Bump various deprecation messages from mentioning version 0.0.103 to 0.0.104 --- src/pipecat/frames/frames.py | 2 +- src/pipecat/services/google/stt.py | 2 +- src/pipecat/services/hume/tts.py | 2 +- src/pipecat/services/llm_service.py | 2 +- src/pipecat/services/nvidia/stt.py | 2 +- src/pipecat/services/nvidia/tts.py | 2 +- src/pipecat/services/stt_service.py | 6 +++--- src/pipecat/services/tts_service.py | 6 +++--- 8 files changed, 12 insertions(+), 12 deletions(-) diff --git a/src/pipecat/frames/frames.py b/src/pipecat/frames/frames.py index 0d6b3f18a..c69ddc931 100644 --- a/src/pipecat/frames/frames.py +++ b/src/pipecat/frames/frames.py @@ -2127,7 +2127,7 @@ class ServiceUpdateSettingsFrame(ControlFrame): Parameters: settings: Dictionary of setting name to value mappings. - .. deprecated:: 0.0.103 + .. deprecated:: 0.0.104 Use ``delta`` with a typed settings object instead. delta: :class:`~pipecat.services.settings.ServiceSettings` delta-mode diff --git a/src/pipecat/services/google/stt.py b/src/pipecat/services/google/stt.py index e294be20a..ac3afa7a3 100644 --- a/src/pipecat/services/google/stt.py +++ b/src/pipecat/services/google/stt.py @@ -368,7 +368,7 @@ class GoogleSTTSettings(STTSettings): language_codes: List of Google STT language code strings (e.g. ``["en-US"]``). - .. deprecated:: 0.0.103 + .. deprecated:: 0.0.104 Use ``languages`` instead. If both are provided, ``languages`` takes precedence. This field is here just for backward compatibility with dict-based settings updates. diff --git a/src/pipecat/services/hume/tts.py b/src/pipecat/services/hume/tts.py index 4b13226cc..3fb43ff88 100644 --- a/src/pipecat/services/hume/tts.py +++ b/src/pipecat/services/hume/tts.py @@ -210,7 +210,7 @@ class HumeTTSService(TTSService): async def update_setting(self, key: str, value: Any) -> None: """Runtime updates via key/value pair. - .. deprecated:: 0.0.103 + .. deprecated:: 0.0.104 Use ``TTSUpdateSettingsFrame(delta=HumeTTSSettings(...))`` instead. Args: diff --git a/src/pipecat/services/llm_service.py b/src/pipecat/services/llm_service.py index df1bc6d08..1102e85a1 100644 --- a/src/pipecat/services/llm_service.py +++ b/src/pipecat/services/llm_service.py @@ -359,7 +359,7 @@ class LLMService(UserTurnCompletionLLMServiceMixin, AIService): warnings.simplefilter("always") warnings.warn( "Passing a dict via LLMUpdateSettingsFrame(settings={...}) is deprecated " - "since 0.0.103, use LLMUpdateSettingsFrame(delta=LLMSettings(...)) instead.", + "since 0.0.104, use LLMUpdateSettingsFrame(delta=LLMSettings(...)) instead.", DeprecationWarning, stacklevel=2, ) diff --git a/src/pipecat/services/nvidia/stt.py b/src/pipecat/services/nvidia/stt.py index be9002b14..3bbe04f51 100644 --- a/src/pipecat/services/nvidia/stt.py +++ b/src/pipecat/services/nvidia/stt.py @@ -241,7 +241,7 @@ class NvidiaSTTService(STTService): async def set_model(self, model: str): """Set the ASR model for transcription. - .. deprecated:: 0.0.103 + .. deprecated:: 0.0.104 Model cannot be changed after initialization for NVIDIA Riva streaming STT. Set model and function id in the constructor instead, e.g.:: diff --git a/src/pipecat/services/nvidia/tts.py b/src/pipecat/services/nvidia/tts.py index 12bcf8c21..c6a5f371e 100644 --- a/src/pipecat/services/nvidia/tts.py +++ b/src/pipecat/services/nvidia/tts.py @@ -125,7 +125,7 @@ class NvidiaTTSService(TTSService): async def set_model(self, model: str): """Set the TTS model. - .. deprecated:: 0.0.103 + .. deprecated:: 0.0.104 Model cannot be changed after initialization for NVIDIA Riva TTS. Set model and function id in the constructor instead, e.g.:: diff --git a/src/pipecat/services/stt_service.py b/src/pipecat/services/stt_service.py index 80448223c..eedc8b46d 100644 --- a/src/pipecat/services/stt_service.py +++ b/src/pipecat/services/stt_service.py @@ -184,7 +184,7 @@ class STTService(AIService): async def set_model(self, model: str): """Set the speech recognition model. - .. deprecated:: 0.0.103 + .. deprecated:: 0.0.104 Use ``STTUpdateSettingsFrame(model=...)`` instead. Args: @@ -204,7 +204,7 @@ class STTService(AIService): async def set_language(self, language: Language): """Set the language for speech recognition. - .. deprecated:: 0.0.103 + .. deprecated:: 0.0.104 Use ``STTUpdateSettingsFrame(language=...)`` instead. Args: @@ -357,7 +357,7 @@ class STTService(AIService): warnings.simplefilter("always") warnings.warn( "Passing a dict via STTUpdateSettingsFrame(settings={...}) is deprecated " - "since 0.0.103, use STTUpdateSettingsFrame(delta=STTSettings(...)) instead.", + "since 0.0.104, use STTUpdateSettingsFrame(delta=STTSettings(...)) instead.", DeprecationWarning, stacklevel=2, ) diff --git a/src/pipecat/services/tts_service.py b/src/pipecat/services/tts_service.py index 59920c342..1b65521a1 100644 --- a/src/pipecat/services/tts_service.py +++ b/src/pipecat/services/tts_service.py @@ -275,7 +275,7 @@ class TTSService(AIService): async def set_model(self, model: str): """Set the TTS model to use. - .. deprecated:: 0.0.103 + .. deprecated:: 0.0.104 Use ``TTSUpdateSettingsFrame(model=...)`` instead. Args: @@ -295,7 +295,7 @@ class TTSService(AIService): async def set_voice(self, voice: str): """Set the voice for speech synthesis. - .. deprecated:: 0.0.103 + .. deprecated:: 0.0.104 Use ``TTSUpdateSettingsFrame(voice=...)`` instead. Args: @@ -554,7 +554,7 @@ class TTSService(AIService): warnings.simplefilter("always") warnings.warn( "Passing a dict via TTSUpdateSettingsFrame(settings={...}) is deprecated " - "since 0.0.103, use TTSUpdateSettingsFrame(delta=TTSSettings(...)) instead.", + "since 0.0.104, use TTSUpdateSettingsFrame(delta=TTSSettings(...)) instead.", DeprecationWarning, stacklevel=2, ) From 0a89d24f70f25f28b5d89d9529b48b6275ec22e1 Mon Sep 17 00:00:00 2001 From: Paul Kompfner Date: Tue, 24 Feb 2026 12:00:23 -0500 Subject: [PATCH 0617/1060] Update some more services to ensure that there are no un-initialized fields in `self._settings` --- src/pipecat/services/resembleai/tts.py | 1 + src/pipecat/services/sarvam/tts.py | 12 +++++++----- 2 files changed, 8 insertions(+), 5 deletions(-) diff --git a/src/pipecat/services/resembleai/tts.py b/src/pipecat/services/resembleai/tts.py index b1b8d1de8..026d29d3f 100644 --- a/src/pipecat/services/resembleai/tts.py +++ b/src/pipecat/services/resembleai/tts.py @@ -102,6 +102,7 @@ class ResembleAITTSService(AudioContextTTSService): self._settings = ResembleAITTSSettings( model=None, voice=voice_id, + language=None, precision=precision, output_format=output_format, resemble_sample_rate=sample_rate, diff --git a/src/pipecat/services/sarvam/tts.py b/src/pipecat/services/sarvam/tts.py index 45c283ff1..ade547798 100644 --- a/src/pipecat/services/sarvam/tts.py +++ b/src/pipecat/services/sarvam/tts.py @@ -42,7 +42,7 @@ import base64 import json from dataclasses import dataclass, field from enum import Enum -from typing import Any, AsyncGenerator, Dict, List, Optional, Tuple +from typing import Any, AsyncGenerator, ClassVar, Dict, List, Optional, Tuple import aiohttp from loguru import logger @@ -280,7 +280,8 @@ class SarvamTTSSettings(TTSSettings): """Settings for Sarvam WebSocket TTS service. Parameters: - target_language_code: Sarvam language code. + language: Sarvam language code (e.g. ``"hi-IN"``). Uses the standard + ``TTSSettings.language`` field. speech_sample_rate: Audio sample rate as string. enable_preprocessing: Enable text preprocessing. Defaults to False. **Note:** Always enabled for bulbul:v3-beta. @@ -304,7 +305,8 @@ class SarvamTTSSettings(TTSSettings): **Note:** Only supported for bulbul:v3-beta. Ignored for v2. """ - target_language_code: str | None | _NotGiven = field(default_factory=lambda: NOT_GIVEN) + _aliases: ClassVar[Dict[str, str]] = {"target_language_code": "language"} + speech_sample_rate: str | _NotGiven = field(default_factory=lambda: NOT_GIVEN) enable_preprocessing: bool | None | _NotGiven = field(default_factory=lambda: NOT_GIVEN) min_buffer_size: int | None | _NotGiven = field(default_factory=lambda: NOT_GIVEN) @@ -840,7 +842,7 @@ class SarvamTTSService(InterruptibleTTSService): # Build base settings self._settings = SarvamTTSSettings( - target_language_code=( + language=( self.language_to_service_language(params.language) if params.language else "en-IN" ), speech_sample_rate=str(sample_rate), @@ -1022,7 +1024,7 @@ class SarvamTTSService(InterruptibleTTSService): raise Exception("WebSocket not connected") # Build config dict for the API config_data = { - "target_language_code": self._settings.target_language_code, + "target_language_code": self._settings.language, "speaker": self._settings.voice, "speech_sample_rate": self._settings.speech_sample_rate, "enable_preprocessing": self._settings.enable_preprocessing, From b78a293ffb70adae599a98196552d6721cf0db09 Mon Sep 17 00:00:00 2001 From: Paul Kompfner Date: Tue, 24 Feb 2026 12:20:14 -0500 Subject: [PATCH 0618/1060] Flatten `input_params` into individual fields on `SonioxSTTSettings` and `GladiaSTTSettings` MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit This makes each service-specific field individually visible to the delta/update mechanism (`apply_update`, `given_fields`) and removes the need for complex sync logic between `input_params` and top-level fields like `model`. - Soniox: replace `input_params: SonioxInputParams` with 8 individual fields, simplify `_update_settings` by removing model sync logic, remove unused `is_given` import - Gladia: replace `input_params: GladiaInputParams` with 11 individual fields, resolve deprecated `language` → `language_config` at init time rather than at `_prepare_settings` time --- src/pipecat/services/gladia/stt.py | 113 ++++++++++++++++++++--------- src/pipecat/services/soniox/stt.py | 72 ++++++++++-------- 2 files changed, 120 insertions(+), 65 deletions(-) diff --git a/src/pipecat/services/gladia/stt.py b/src/pipecat/services/gladia/stt.py index d0a6f5a84..c1ce02d87 100644 --- a/src/pipecat/services/gladia/stt.py +++ b/src/pipecat/services/gladia/stt.py @@ -32,7 +32,13 @@ from pipecat.frames.frames import ( UserStartedSpeakingFrame, UserStoppedSpeakingFrame, ) -from pipecat.services.gladia.config import GladiaInputParams +from pipecat.services.gladia.config import ( + GladiaInputParams, + LanguageConfig, + MessagesConfig, + PreProcessingConfig, + RealtimeProcessingConfig, +) from pipecat.services.settings import NOT_GIVEN, STTSettings, _NotGiven from pipecat.services.stt_latency import GLADIA_TTFS_P99 from pipecat.services.stt_service import WebsocketSTTService @@ -185,10 +191,36 @@ class GladiaSTTSettings(STTSettings): """Settings for Gladia STT service. Parameters: - input_params: Gladia ``GladiaInputParams`` for detailed configuration. + encoding: Audio encoding format. + bit_depth: Audio bit depth. + channels: Number of audio channels. + custom_metadata: Additional metadata to include with requests. + endpointing: Silence duration in seconds to mark end of speech. + maximum_duration_without_endpointing: Maximum utterance duration without silence. + language_config: Detailed language configuration. + pre_processing: Audio pre-processing options. + realtime_processing: Real-time processing features. + messages_config: WebSocket message filtering options. + enable_vad: Enable VAD to trigger end of utterance detection. """ - input_params: GladiaInputParams | _NotGiven = field(default_factory=lambda: NOT_GIVEN) + encoding: str | None | _NotGiven = field(default_factory=lambda: NOT_GIVEN) + bit_depth: int | None | _NotGiven = field(default_factory=lambda: NOT_GIVEN) + channels: int | None | _NotGiven = field(default_factory=lambda: NOT_GIVEN) + custom_metadata: Dict[str, Any] | None | _NotGiven = field(default_factory=lambda: NOT_GIVEN) + endpointing: float | None | _NotGiven = field(default_factory=lambda: NOT_GIVEN) + maximum_duration_without_endpointing: int | None | _NotGiven = field( + default_factory=lambda: NOT_GIVEN + ) + language_config: LanguageConfig | None | _NotGiven = field(default_factory=lambda: NOT_GIVEN) + pre_processing: PreProcessingConfig | None | _NotGiven = field( + default_factory=lambda: NOT_GIVEN + ) + realtime_processing: RealtimeProcessingConfig | None | _NotGiven = field( + default_factory=lambda: NOT_GIVEN + ) + messages_config: MessagesConfig | None | _NotGiven = field(default_factory=lambda: NOT_GIVEN) + enable_vad: bool | None | _NotGiven = field(default_factory=lambda: NOT_GIVEN) class GladiaSTTService(WebsocketSTTService): @@ -280,7 +312,29 @@ class GladiaSTTService(WebsocketSTTService): self._region = region self._url = url self._receive_task = None - self._settings = GladiaSTTSettings(model=model, language=None, input_params=params) + + # Resolve deprecated language → language_config at init time + language_config = params.language_config + if not language_config and params.language: + language_code = self.language_to_service_language(params.language) + if language_code: + language_config = LanguageConfig(languages=[language_code], code_switching=False) + + self._settings = GladiaSTTSettings( + model=model, + language=None, + encoding=params.encoding, + bit_depth=params.bit_depth, + channels=params.channels, + custom_metadata=params.custom_metadata, + endpointing=params.endpointing, + maximum_duration_without_endpointing=params.maximum_duration_without_endpointing, + language_config=language_config, + pre_processing=params.pre_processing, + realtime_processing=params.realtime_processing, + messages_config=params.messages_config, + enable_vad=params.enable_vad, + ) self._sync_model_name_to_metrics() # Session management @@ -321,52 +375,43 @@ class GladiaSTTService(WebsocketSTTService): return language_to_gladia_language(language) def _prepare_settings(self) -> Dict[str, Any]: - params = self._settings.input_params + s = self._settings settings = { - "encoding": params.encoding or "wav/pcm", - "bit_depth": params.bit_depth or 16, + "encoding": s.encoding or "wav/pcm", + "bit_depth": s.bit_depth or 16, "sample_rate": self.sample_rate, - "channels": params.channels or 1, - "model": self._settings.model, + "channels": s.channels or 1, + "model": s.model, } # Add custom_metadata if provided - settings["custom_metadata"] = dict(params.custom_metadata or {}) + settings["custom_metadata"] = dict(s.custom_metadata or {}) settings["custom_metadata"]["pipecat"] = pipecat_version() # Add endpointing parameters if provided - if params.endpointing is not None: - settings["endpointing"] = params.endpointing - if params.maximum_duration_without_endpointing is not None: + if s.endpointing is not None: + settings["endpointing"] = s.endpointing + if s.maximum_duration_without_endpointing is not None: settings["maximum_duration_without_endpointing"] = ( - params.maximum_duration_without_endpointing + s.maximum_duration_without_endpointing ) - # Add language configuration (prioritize language_config over deprecated language) - if params.language_config: - settings["language_config"] = params.language_config.model_dump(exclude_none=True) - elif params.language: # Backward compatibility for deprecated parameter - language_code = self.language_to_service_language(params.language) - if language_code: - settings["language_config"] = { - "languages": [language_code], - "code_switching": False, - } + # Add language configuration + if s.language_config: + settings["language_config"] = s.language_config.model_dump(exclude_none=True) # Add pre_processing configuration if provided - if params.pre_processing: - settings["pre_processing"] = params.pre_processing.model_dump(exclude_none=True) + if s.pre_processing: + settings["pre_processing"] = s.pre_processing.model_dump(exclude_none=True) # Add realtime_processing configuration if provided - if params.realtime_processing: - settings["realtime_processing"] = params.realtime_processing.model_dump( - exclude_none=True - ) + if s.realtime_processing: + settings["realtime_processing"] = s.realtime_processing.model_dump(exclude_none=True) # Add messages_config if provided - if params.messages_config: - settings["messages_config"] = params.messages_config.model_dump(exclude_none=True) + if s.messages_config: + settings["messages_config"] = s.messages_config.model_dump(exclude_none=True) return settings @@ -562,7 +607,7 @@ class GladiaSTTService(WebsocketSTTService): Broadcasts UserStartedSpeakingFrame and optionally triggers interruption when VAD is enabled. """ - if not self._settings.input_params.enable_vad or self._is_speaking: + if not self._settings.enable_vad or self._is_speaking: return logger.debug(f"{self} User started speaking") @@ -577,7 +622,7 @@ class GladiaSTTService(WebsocketSTTService): Broadcasts UserStoppedSpeakingFrame when VAD is enabled. """ - if not self._settings.input_params.enable_vad or not self._is_speaking: + if not self._settings.enable_vad or not self._is_speaking: return self._is_speaking = False await self.broadcast_frame(UserStoppedSpeakingFrame) diff --git a/src/pipecat/services/soniox/stt.py b/src/pipecat/services/soniox/stt.py index 356b23162..3160d19a6 100644 --- a/src/pipecat/services/soniox/stt.py +++ b/src/pipecat/services/soniox/stt.py @@ -24,7 +24,7 @@ from pipecat.frames.frames import ( VADUserStoppedSpeakingFrame, ) from pipecat.processors.frame_processor import FrameDirection -from pipecat.services.settings import NOT_GIVEN, STTSettings, _NotGiven, is_given +from pipecat.services.settings import NOT_GIVEN, STTSettings, _NotGiven from pipecat.services.stt_latency import SONIOX_TTFS_P99 from pipecat.services.stt_service import WebsocketSTTService from pipecat.transcriptions.language import Language @@ -141,10 +141,28 @@ class SonioxSTTSettings(STTSettings): """Settings for Soniox STT service. Parameters: - input_params: Soniox ``SonioxInputParams`` for detailed configuration. + audio_format: Audio format to use for transcription. + num_channels: Number of channels to use for transcription. + language_hints: List of language hints to use for transcription. + language_hints_strict: If true, strictly enforce language hints. + context: Customization for transcription. String for models with + context_version 1 and SonioxContextObject for models with + context_version 2. + enable_speaker_diarization: Whether to enable speaker diarization. + enable_language_identification: Whether to enable language identification. + client_reference_id: Client reference ID to use for transcription. """ - input_params: SonioxInputParams | _NotGiven = field(default_factory=lambda: NOT_GIVEN) + audio_format: str | None | _NotGiven = field(default_factory=lambda: NOT_GIVEN) + num_channels: int | None | _NotGiven = field(default_factory=lambda: NOT_GIVEN) + language_hints: List[Language] | None | _NotGiven = field(default_factory=lambda: NOT_GIVEN) + language_hints_strict: bool | None | _NotGiven = field(default_factory=lambda: NOT_GIVEN) + context: SonioxContextObject | str | None | _NotGiven = field(default_factory=lambda: NOT_GIVEN) + enable_speaker_diarization: bool | None | _NotGiven = field(default_factory=lambda: NOT_GIVEN) + enable_language_identification: bool | None | _NotGiven = field( + default_factory=lambda: NOT_GIVEN + ) + client_reference_id: str | None | _NotGiven = field(default_factory=lambda: NOT_GIVEN) class SonioxSTTService(WebsocketSTTService): @@ -199,7 +217,15 @@ class SonioxSTTService(WebsocketSTTService): self._settings = SonioxSTTSettings( model=params.model, - input_params=params, + language=None, + audio_format=params.audio_format, + num_channels=params.num_channels, + language_hints=params.language_hints, + language_hints_strict=params.language_hints_strict, + context=params.context, + enable_speaker_diarization=params.enable_speaker_diarization, + enable_language_identification=params.enable_language_identification, + client_reference_id=params.client_reference_id, ) self._sync_model_name_to_metrics() @@ -226,12 +252,7 @@ class SonioxSTTService(WebsocketSTTService): await self._connect() async def _update_settings(self, delta: SonioxSTTSettings) -> dict[str, Any]: - """Apply a settings delta, keeping ``input_params`` in sync. - - Top-level ``model`` is the source of truth. When it is given in - *delta* its value is propagated into ``input_params``. When only - ``input_params`` is given, its ``model`` is propagated *up* to the - top-level field. + """Apply settings delta. Settings are stored but not applied to the active connection. @@ -241,22 +262,11 @@ class SonioxSTTService(WebsocketSTTService): Returns: Dict mapping changed field names to their previous values. """ - model_given = is_given(getattr(delta, "model", NOT_GIVEN)) - changed = await super()._update_settings(delta) if not changed: return changed - # --- Sync model -------------------------------------------------- - if model_given: - # Top-level model wins → push into input_params. - self._settings.input_params.model = self._settings.model - elif "input_params" in changed and self._settings.input_params.model is not None: - # Only input_params was given → pull model up. - self._settings.model = self._settings.input_params.model - self._sync_model_name_to_metrics() - # TODO: someday we could reconnect here to apply updated settings. # Code might look something like the below: # await self._disconnect() @@ -377,26 +387,26 @@ class SonioxSTTService(WebsocketSTTService): # Either one or the other is required. enable_endpoint_detection = not self._vad_force_turn_endpoint - params = self._settings.input_params + s = self._settings - context = params.context + context = s.context if isinstance(context, SonioxContextObject): context = context.model_dump() # Send the initial configuration message. config = { "api_key": self._api_key, - "model": self._settings.model, - "audio_format": params.audio_format, - "num_channels": params.num_channels or 1, + "model": s.model, + "audio_format": s.audio_format, + "num_channels": s.num_channels or 1, "enable_endpoint_detection": enable_endpoint_detection, "sample_rate": self.sample_rate, - "language_hints": _prepare_language_hints(params.language_hints), - "language_hints_strict": params.language_hints_strict, + "language_hints": _prepare_language_hints(s.language_hints), + "language_hints_strict": s.language_hints_strict, "context": context, - "enable_speaker_diarization": params.enable_speaker_diarization, - "enable_language_identification": params.enable_language_identification, - "client_reference_id": params.client_reference_id, + "enable_speaker_diarization": s.enable_speaker_diarization, + "enable_language_identification": s.enable_language_identification, + "client_reference_id": s.client_reference_id, } # Send the configuration message. From b4b9976b9c3adf94a596ec573cbd23a1ce2d0593 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Aleix=20Conchillo=20Flaqu=C3=A9?= Date: Tue, 24 Feb 2026 11:26:34 -0800 Subject: [PATCH 0619/1060] Fix SentryMetrics method signatures to match base class Update start_ttfb_metrics, stop_ttfb_metrics, start_processing_metrics, and stop_processing_metrics to accept start_time/end_time keyword arguments matching the updated FrameProcessorMetrics signatures. Closes #3808 --- changelog/3808.fixed.md | 1 + src/pipecat/processors/metrics/sentry.py | 31 +++++++++++++++--------- 2 files changed, 21 insertions(+), 11 deletions(-) create mode 100644 changelog/3808.fixed.md diff --git a/changelog/3808.fixed.md b/changelog/3808.fixed.md new file mode 100644 index 000000000..6bf105bf6 --- /dev/null +++ b/changelog/3808.fixed.md @@ -0,0 +1 @@ +- Fixed `SentryMetrics` method signatures to match updated `FrameProcessorMetrics` base class, resolving `TypeError` when using `start_time`/`end_time` keyword arguments. diff --git a/src/pipecat/processors/metrics/sentry.py b/src/pipecat/processors/metrics/sentry.py index db2c6de63..c865ee470 100644 --- a/src/pipecat/processors/metrics/sentry.py +++ b/src/pipecat/processors/metrics/sentry.py @@ -7,6 +7,7 @@ """Sentry integration for frame processor metrics.""" import asyncio +from typing import Optional from loguru import logger @@ -70,13 +71,18 @@ class SentryMetrics(FrameProcessorMetrics): logger.trace(f"{self} Flushing Sentry metrics") sentry_sdk.flush(timeout=5.0) - async def start_ttfb_metrics(self, report_only_initial_ttfb): + async def start_ttfb_metrics( + self, *, start_time: Optional[float] = None, report_only_initial_ttfb: bool + ): """Start tracking time-to-first-byte metrics. Args: + start_time: Optional start timestamp override. report_only_initial_ttfb: Whether to report only the initial TTFB measurement. """ - await super().start_ttfb_metrics(report_only_initial_ttfb) + await super().start_ttfb_metrics( + start_time=start_time, report_only_initial_ttfb=report_only_initial_ttfb + ) if self._should_report_ttfb and self._sentry_available: self._ttfb_metrics_tx = sentry_sdk.start_transaction( @@ -87,23 +93,25 @@ class SentryMetrics(FrameProcessorMetrics): f"{self} Sentry transaction started (ID: {self._ttfb_metrics_tx.span_id} Name: {self._ttfb_metrics_tx.name})" ) - async def stop_ttfb_metrics(self): + async def stop_ttfb_metrics(self, *, end_time: Optional[float] = None): """Stop tracking time-to-first-byte metrics. - Queues the TTFB transaction for completion and transmission to Sentry. + Args: + end_time: Optional end timestamp override. """ - await super().stop_ttfb_metrics() + await super().stop_ttfb_metrics(end_time=end_time) if self._sentry_available and self._ttfb_metrics_tx: await self._sentry_queue.put(self._ttfb_metrics_tx) self._ttfb_metrics_tx = None - async def start_processing_metrics(self): + async def start_processing_metrics(self, *, start_time: Optional[float] = None): """Start tracking frame processing metrics. - Creates a new Sentry transaction to track processing performance. + Args: + start_time: Optional start timestamp override. """ - await super().start_processing_metrics() + await super().start_processing_metrics(start_time=start_time) if self._sentry_available: self._processing_metrics_tx = sentry_sdk.start_transaction( @@ -114,12 +122,13 @@ class SentryMetrics(FrameProcessorMetrics): f"{self} Sentry transaction started (ID: {self._processing_metrics_tx.span_id} Name: {self._processing_metrics_tx.name})" ) - async def stop_processing_metrics(self): + async def stop_processing_metrics(self, *, end_time: Optional[float] = None): """Stop tracking frame processing metrics. - Queues the processing transaction for completion and transmission to Sentry. + Args: + end_time: Optional end timestamp override. """ - await super().stop_processing_metrics() + await super().stop_processing_metrics(end_time=end_time) if self._sentry_available and self._processing_metrics_tx: await self._sentry_queue.put(self._processing_metrics_tx) From ee46cbce4c626b3ad1f4bab81a4c26d12c06bbd6 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Aleix=20Conchillo=20Flaqu=C3=A9?= Date: Tue, 24 Feb 2026 11:38:04 -0800 Subject: [PATCH 0620/1060] Move skills to pipecat-ai/skills repo, add README instructions Remove bundled Claude Code skills (changelog, cleanup, code-review, docstring, pr-description, pr-submit) that now live in https://github.com/pipecat-ai/skills. Add a section to the README with installation instructions. The update-docs skill remains as it is specific to this repository. --- .claude/skills/changelog/SKILL.md | 47 ---- .claude/skills/cleanup/SKILL.md | 306 ------------------------- .claude/skills/code-review/SKILL.md | 107 --------- .claude/skills/docstring/SKILL.md | 257 --------------------- .claude/skills/pr-description/SKILL.md | 128 ----------- .claude/skills/pr-submit/SKILL.md | 28 --- README.md | 16 ++ 7 files changed, 16 insertions(+), 873 deletions(-) delete mode 100644 .claude/skills/changelog/SKILL.md delete mode 100644 .claude/skills/cleanup/SKILL.md delete mode 100644 .claude/skills/code-review/SKILL.md delete mode 100644 .claude/skills/docstring/SKILL.md delete mode 100644 .claude/skills/pr-description/SKILL.md delete mode 100644 .claude/skills/pr-submit/SKILL.md diff --git a/.claude/skills/changelog/SKILL.md b/.claude/skills/changelog/SKILL.md deleted file mode 100644 index 1ef8f324e..000000000 --- a/.claude/skills/changelog/SKILL.md +++ /dev/null @@ -1,47 +0,0 @@ ---- -name: changelog -description: Create changelog files for important commits in a PR ---- - -Create changelog files for the important commits in this PR. The PR number is provided as an argument. - -## Instructions - -1. Skip changelog for: documentation-only, internal refactoring, test-only, CI changes. - -2. First, check what commits are on the current branch compared to main: - ``` - git log main..HEAD --oneline - ``` - -3. For each significant change, create a changelog file in the `changelog/` folder using the format: - Allowed types: `added`, `changed`, `deprecated`, `removed`, `fixed`, `security`, `performance`, `other` - - `{PR_NUMBER}.added.md` - for new features - - `{PR_NUMBER}.added.2.md`, `{PR_NUMBER}.added.3.md` - for additional entries of the same type - - `{PR_NUMBER}.changed.md` - for changes to existing functionality - - `{PR_NUMBER}.fixed.md` - for bug fixes - - `{PR_NUMBER}.deprecated.md` - for deprecations - - `{PR_NUMBER}.removed.md` - for removed features - - `{PR_NUMBER}.security.md` - for security fixes - - `{PR_NUMBER}.performance.md` - for performance improvements - - `{PR_NUMBER}.other.md` - for other changes - -4. Each changelog file should at least contain a main single line starting with `- ` followed by a clear description of the change. No line wrapping. - -5. If the change is complicated, changelog files can have indented lines after the main line with additional details or code samples. - -6. Use ⚠️ emoji prefix for breaking changes. - -## Example - -For PR #3519 with a new feature and a bug fix: - -`changelog/3519.added.md`: -``` -- Added `SomeNewFeature` for doing something useful. -``` - -`changelog/3519.fixed.md`: -``` -- Fixed an issue where something was not working correctly. -``` diff --git a/.claude/skills/cleanup/SKILL.md b/.claude/skills/cleanup/SKILL.md deleted file mode 100644 index 48c5e0ee8..000000000 --- a/.claude/skills/cleanup/SKILL.md +++ /dev/null @@ -1,306 +0,0 @@ -# Code Cleanup Skill - -The **Code Cleanup Skill** reviews, refactors, and documents code changes in your current branch, ensuring alignment with **Pipecat’s architecture, coding standards, and example patterns**. -It focuses on **readability, correctness, performance, and consistency**, while avoiding breaking changes. - ---- - -## Skill Overview - -This skill analyzes all changes introduced in your branch and performs the following actions: - -1. **Analyze Branch Changes** - - Review uncommitted changes and outgoing commits -2. **Refactor for Readability** - - Improve clarity, naming, structure, and modern Python usage -3. **Enhance Performance** - - Identify safe, conservative optimization opportunities -4. **Add Documentation** - - Apply Pipecat-style, Google-format docstrings -5. **Ensure Pattern Consistency** - - Match existing Pipecat services, pipelines, and examples -6. **Validate Examples** - - Ensure examples follow foundational patterns (e.g. `07-interruptible.py`) - ---- - -## Usage - -Invoke the skill using any of the following commands: - -- “Clean up my branch code” -- “Refactor the changes in my branch” -- “Review and improve my branch code” -- `/cleanup` - ---- - -## What This Skill Does - -### 1. Analyze Branch Changes - -The skill retrieves all uncommitted changes and outgoing commits to understand: - -- New files added -- Modified files -- Code additions and deletions -- Overall scope and intent of changes - ---- - -### 2. Code Refactoring - -#### Readability Improvements - -- Replace tuples with named classes or dataclasses -- Improve variable, method, and class naming -- Extract complex logic into well-named helper methods -- Add missing type hints -- Simplify nested or complex conditionals -- Replace deprecated methods and features -- Normalize formatting to match Pipecat style - -#### Performance Enhancements - -- Identify inefficient loops or repeated work -- Suggest appropriate data structures -- Optimize async workflows and I/O -- Remove redundant operations - -> Performance changes are conservative and non-breaking. - ---- - -### 3. Documentation - -Documentation follows **Google-style docstrings**, consistent with Pipecat conventions. - -#### Class Documentation - -```python -class ExampleService: - """Brief one-line description. - - Detailed explanation of the class purpose, responsibilities, - and important behaviors. - - Supported features: - - - Feature 1 - - Feature 2 - - Feature 3 - """ -``` - -#### Method Documentation - -```python -def process_data(self, data: str, options: Optional[dict] = None) -> bool: - """Process incoming data with optional configuration. - - Args: - data: The input data to process. - options: Optional configuration dictionary. - - Returns: - True if processing succeeded, False otherwise. - - Raises: - ValueError: If data is empty or invalid. - """ -``` - -#### Pydantic Model Parameters - -```python -class InputParams(BaseModel): - """Configuration parameters for the service. - - Parameters: - timeout: Request timeout in seconds. - retry_count: Number of retry attempts. - enable_logging: Whether to enable debug logging. - """ - - timeout: Optional[float] = None - retry_count: int = 3 - enable_logging: bool = False -``` - ---- - -### 4. Pattern Consistency Checks - -#### Service Classes - -- Correct inheritance (`TTSService`, `STTService`, `LLMService`) -- Consistent constructor signatures -- Frame emission patterns -- Metrics support: - - `can_generate_metrics()` - - TTFB metrics - - Usage metrics -- Alignment with similar existing services - -#### Examples - -Validated against `examples/foundational/07-interruptible.py`: - -- Proper `create_transport()` usage -- Correct pipeline structure -- Task setup and observers -- Event handler registration -- Runner and bot entrypoint consistency - ---- - -### 5. Specific Implementation Patterns - -#### Service Implementation - -```python -class ExampleTTSService(TTSService): - - def __init__(self, *, api_key: Optional[str] = None, **kwargs): - super().__init__(**kwargs) - self._api_key = api_key or os.getenv("SERVICE_API_KEY") - - def can_generate_metrics(self) -> bool: - return True - - async def run_tts(self, text: str) -> AsyncGenerator[Frame, None]: - try: - await self.start_ttfb_metrics() - yield TTSStartedFrame() - # ... processing ... - yield TTSAudioRawFrame(...) - finally: - await self.stop_ttfb_metrics() -``` - ---- - -#### Example Structure Pattern - -```python -transport_params = { - "daily": lambda: DailyParams(...), - "twilio": lambda: FastAPIWebsocketParams(...), - "webrtc": lambda: TransportParams(...), -} - -async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): - stt = DeepgramSTTService(...) - tts = SomeTTSService(...) - llm = OpenAILLMService(...) - - context = LLMContext(messages) - user_aggregator, assistant_aggregator = LLMContextAggregatorPair(...) - - pipeline = Pipeline([...]) - task = PipelineTask(pipeline, params=..., observers=[...]) - - @transport.event_handler("on_client_connected") - async def on_client_connected(transport, client): - await task.queue_frames([LLMRunFrame()]) - - runner = PipelineRunner(handle_sigint=runner_args.handle_sigint) - await runner.run(task) - -async def bot(runner_args: RunnerArguments): - """Main bot entry point compatible with Pipecat Cloud.""" - transport = await create_transport(runner_args, transport_params) - await run_bot(transport, runner_args) -``` - ---- - -## Execution Flow - -1. Fetch uncommitted and outgoing changes -2. Categorize files (services, examples, tests, utilities) -3. Analyze each file: - - Readability - - Performance - - Documentation - - Pattern consistency -4. Generate actionable recommendations -5. Apply Pipecat standards - ---- - -## Examples - -### Before: Tuple Usage - -```python -def get_audio_info(self) -> Tuple[int, int]: - return (48000, 1) -``` - -### After: Named Class - -```python -class AudioInfo: - """Audio configuration information. - - Parameters: - sample_rate: Sample rate in Hz. - num_channels: Number of audio channels. - """ - - sample_rate: int - num_channels: int - -def get_audio_info(self) -> AudioInfo: - return AudioInfo(sample_rate=48000, num_channels=1) -``` - ---- - -### Before: Missing Documentation - -```python -class NewTTSService(TTSService): - def __init__(self, api_key: str, voice: str): - self._api_key = api_key - self._voice = voice -``` - -### After: Fully Documented - -```python -class NewTTSService(TTSService): - """Text-to-speech service using NewProvider API. - - Streams PCM audio and emits TTSAudioRawFrame frames compatible - with Pipecat transports. - - Supported features: - - Text-to-speech synthesis - - Streaming PCM audio - - Voice customization - - TTFB metrics - """ - - def __init__(self, *, api_key: str, voice: str, **kwargs): - """Initialize the NewTTSService. - - Args: - api_key: API key for authentication. - voice: Voice identifier to use. - **kwargs: Additional arguments passed to the parent service. - """ - super().__init__(**kwargs) - self._api_key = api_key -``` - ---- - -## Notes - -- Non-breaking improvements only -- Backward compatibility preserved -- Conservative performance changes -- Google-style docstrings -- Pattern checks follow recent Pipecat code diff --git a/.claude/skills/code-review/SKILL.md b/.claude/skills/code-review/SKILL.md deleted file mode 100644 index 036a7f935..000000000 --- a/.claude/skills/code-review/SKILL.md +++ /dev/null @@ -1,107 +0,0 @@ ---- -name: code-review -description: Automated code review for pull requests using multiple specialized agents -disable-model-invocation: true -allowed-tools: Bash(gh issue view:*), Bash(gh search:*), Bash(gh issue list:*), Bash(gh pr comment:*), Bash(gh pr diff:*), Bash(gh pr view:*), Bash(gh pr list:*) ---- - -Provide a code review for the given pull request. - -**Agent assumptions (applies to all agents and subagents):** - -- All tools are functional and will work without error. Do not test tools or make exploratory calls. Make sure this is clear to every subagent that is launched. -- Only call a tool if it is required to complete the task. Every tool call should have a clear purpose. - -To do this, follow these steps precisely: - -1. Launch a haiku agent to check if any of the following are true: - - The pull request is closed - - The pull request is a draft - - The pull request does not need code review (e.g. automated PR, trivial change that is obviously correct) - - Claude has already commented on this PR (check `gh pr view --comments` for comments left by claude) - - If any condition is true, stop and do not proceed. - -Note: Still review Claude generated PR's. - -2. Launch a haiku agent to return a list of file paths (not their contents) for all relevant CLAUDE.md files including: - - The root CLAUDE.md file, if it exists - - Any CLAUDE.md files in directories containing files modified by the pull request - -3. Launch a sonnet agent to view the pull request and return a summary of the changes - -4. Launch 4 agents in parallel to independently review the changes. Each agent should return the list of issues, where each issue includes a description and the reason it was flagged (e.g. "CLAUDE.md adherence", "bug"). The agents should do the following: - - Agents 1 + 2: CLAUDE.md compliance sonnet agents - Audit changes for CLAUDE.md compliance in parallel. Note: When evaluating CLAUDE.md compliance for a file, you should only consider CLAUDE.md files that share a file path with the file or parents. - - Agent 3: Opus bug agent (parallel subagent with agent 4) - Scan for obvious bugs. Focus only on the diff itself without reading extra context. Flag only significant bugs; ignore nitpicks and likely false positives. Do not flag issues that you cannot validate without looking at context outside of the git diff. - - Agent 4: Opus bug agent (parallel subagent with agent 3) - Look for problems that exist in the introduced code. This could be security issues, incorrect logic, etc. Only look for issues that fall within the changed code. - - **CRITICAL: We only want HIGH SIGNAL issues.** Flag issues where: - - The code will fail to compile or parse (syntax errors, type errors, missing imports, unresolved references) - - The code will definitely produce wrong results regardless of inputs (clear logic errors) - - Clear, unambiguous CLAUDE.md violations where you can quote the exact rule being broken - - Do NOT flag: - - Code style or quality concerns - - Potential issues that depend on specific inputs or state - - Subjective suggestions or improvements - - If you are not certain an issue is real, do not flag it. False positives erode trust and waste reviewer time. - - In addition to the above, each subagent should be told the PR title and description. This will help provide context regarding the author's intent. - -5. For each issue found in the previous step by agents 3 and 4, launch parallel subagents to validate the issue. These subagents should get the PR title and description along with a description of the issue. The agent's job is to review the issue to validate that the stated issue is truly an issue with high confidence. For example, if an issue such as "variable is not defined" was flagged, the subagent's job would be to validate that is actually true in the code. Another example would be CLAUDE.md issues. The agent should validate that the CLAUDE.md rule that was violated is scoped for this file and is actually violated. Use Opus subagents for bugs and logic issues, and sonnet agents for CLAUDE.md violations. - -6. Filter out any issues that were not validated in step 5. This step will give us our list of high signal issues for our review. - -7. If issues were found, skip to step 8 to post comments. - - If NO issues were found, post a summary comment using `gh pr comment` (if `--comment` argument is provided): - "No issues found. Checked for bugs and CLAUDE.md compliance." - -8. Create a list of all comments that you plan on leaving. This is only for you to make sure you are comfortable with the comments. Do not post this list anywhere. - -9. Post inline comments for each issue using `gh pr review` with inline comments. For each comment: - - Provide a brief description of the issue - - For small, self-contained fixes, include a committable suggestion block - - For larger fixes (6+ lines, structural changes, or changes spanning multiple locations), describe the issue and suggested fix without a suggestion block - - Never post a committable suggestion UNLESS committing the suggestion fixes the issue entirely. If follow up steps are required, do not leave a committable suggestion. - - **IMPORTANT: Only post ONE comment per unique issue. Do not post duplicate comments.** - -Use this list when evaluating issues in Steps 4 and 5 (these are false positives, do NOT flag): - -- Pre-existing issues -- Something that appears to be a bug but is actually correct -- Pedantic nitpicks that a senior engineer would not flag -- Issues that a linter will catch (do not run the linter to verify) -- General code quality concerns (e.g., lack of test coverage, general security issues) unless explicitly required in CLAUDE.md -- Issues mentioned in CLAUDE.md but explicitly silenced in the code (e.g., via a lint ignore comment) - -Notes: - -- Use gh CLI to interact with GitHub (e.g., fetch pull requests, create comments). Do not use web fetch. -- Create a todo list before starting. -- You must cite and link each issue in inline comments (e.g., if referring to a CLAUDE.md, include a link to it). -- If no issues are found, post a comment with the following format: - ---- - -## Code review - -No issues found. Checked for bugs and CLAUDE.md compliance. - ---- - -- When linking to code in inline comments, follow the following format precisely, otherwise the Markdown preview won't render correctly: `https://github.com/OWNER/REPO/blob/FULL_SHA/path/to/file.py#L10-L15` - - Requires full git sha - - You must provide the full sha. Commands like `https://github.com/owner/repo/blob/$(git rev-parse HEAD)/foo/bar` will not work, since your comment will be directly rendered in Markdown. - - Repo name must match the repo you're code reviewing - - # sign after the file name - - Line range format is L[start]-L[end] - - Provide at least 1 line of context before and after, centered on the line you are commenting about (eg. if you are commenting about lines 5-6, you should link to `L4-7`) diff --git a/.claude/skills/docstring/SKILL.md b/.claude/skills/docstring/SKILL.md deleted file mode 100644 index 1c1e3c905..000000000 --- a/.claude/skills/docstring/SKILL.md +++ /dev/null @@ -1,257 +0,0 @@ ---- -name: docstring -description: Document a Python module and its classes using Google style ---- - -Document a Python module and its classes using Google-style docstrings following project conventions. The class name is provided as an argument. - -## Instructions - -1. First, find the class in the codebase: - ``` - Search for "class ClassName" in src/pipecat/ - ``` - -2. If multiple files contain that class name: - - List all matches with their file paths - - Ask the user which one they want to document - - Wait for confirmation before proceeding - -3. Once the file is identified, read the module to understand its structure: - - Identify all classes, functions, and important type aliases - - Understand the purpose of each component - -4. Apply documentation in this order: - - Module docstring (at top, after imports) - - Class docstrings - - `__init__` methods (always document constructor parameters) - - Public methods (not starting with `_`) - - Dataclass/config classes with field descriptions - -5. Skip documentation for: - - Private methods (starting with `_`) - - Simple dunder methods (`__str__`, `__repr__`, `__post_init__`) - - Very simple pass-through properties - - **Already documented code** - If a class, method, or function already has a complete docstring that follows the project style, do not modify it. A docstring is complete if it has: - - A one-line summary - - Args section (if it has parameters) - - Returns section (if it returns something meaningful) - - Only add or improve documentation where it is missing or incomplete - -## Module Docstring Format - -```python -"""[One-line description of module purpose]. - -[Optional: Longer explanation of functionality, key classes, or use cases.] -""" -``` - -Example: -```python -"""Neuphonic text-to-speech service implementations. - -This module provides WebSocket and HTTP-based integrations with Neuphonic's -text-to-speech API for real-time audio synthesis. -""" -``` - -## Class Docstring Format - -```python -class ClassName: - """One-line summary describing what the class does. - - [Longer description explaining purpose, behavior, and key features. - Use action-oriented language.] - - [Optional: Event handlers, usage notes, or important caveats.] - """ -``` - -Example: -```python -class FrameProcessor(BaseObject): - """Base class for all frame processors in the pipeline. - - Frame processors are the building blocks of Pipecat pipelines, they can be - linked to form complex processing pipelines. They receive frames, process - them, and pass them to the next or previous processor in the chain. - - Event handlers available: - - - on_before_process_frame: Called before a frame is processed - - on_after_process_frame: Called after a frame is processed - - Example:: - - @processor.event_handler("on_before_process_frame") - async def on_before_process_frame(processor, frame): - ... - - @processor.event_handler("on_after_process_frame") - async def on_after_process_frame(processor, frame): - ... - """ -``` - -Note: When listing event handlers, do NOT use backticks. Include an `Example::` section (with double colon for Sphinx) showing the decorator pattern and function signature for each event. - -## Constructor (`__init__`) Format - -```python -def __init__(self, *, param1: Type, param2: Type = default, **kwargs): - """Initialize the [ClassName]. - - Args: - param1: Description of param1 and its purpose. - param2: Description of param2. Defaults to [default]. - **kwargs: Additional arguments passed to parent class. - """ -``` - -Example: -```python -def __init__( - self, - *, - api_key: str, - voice_id: Optional[str] = None, - sample_rate: Optional[int] = 22050, - **kwargs, -): - """Initialize the Neuphonic TTS service. - - Args: - api_key: Neuphonic API key for authentication. - voice_id: ID of the voice to use for synthesis. - sample_rate: Audio sample rate in Hz. Defaults to 22050. - **kwargs: Additional arguments passed to parent InterruptibleTTSService. - """ -``` - -## Method Docstring Format - -```python -async def method_name(self, param1: Type) -> ReturnType: - """One-line summary of what method does. - - [Longer description if behavior isn't obvious.] - - Args: - param1: Description of param1. - - Returns: - Description of return value. - - Raises: - ExceptionType: When this exception is raised. - """ -``` - -Example: -```python -async def put(self, item: Tuple[Frame, FrameDirection, FrameCallback]): - """Put an item into the priority queue. - - System frames (`SystemFrame`) have higher priority than any other - frames. If a non-frame item is provided it will have the highest priority. - - Args: - item: The item to enqueue. - """ -``` - -## Dataclass/Config Format - -```python -@dataclass -class ConfigName: - """One-line description of configuration. - - [Explanation of when/how to use this config.] - - Parameters: - field1: Description of field1. - field2: Description of field2. Defaults to [default]. - """ - - field1: Type - field2: Type = default_value -``` - -Example: -```python -@dataclass -class FrameProcessorSetup: - """Configuration parameters for frame processor initialization. - - Parameters: - clock: The clock instance for timing operations. - task_manager: The task manager for handling async operations. - observer: Optional observer for monitoring frame processing events. - """ - - clock: BaseClock - task_manager: BaseTaskManager - observer: Optional[BaseObserver] = None -``` - -## Enum Documentation Format - -```python -class EnumName(Enum): - """One-line description of the enum purpose. - - [Longer description of how the enum is used.] - - Parameters: - VALUE1: Description of VALUE1. - VALUE2: Description of VALUE2. - """ - - VALUE1 = 1 - VALUE2 = 2 -``` - -## Writing Style Guidelines - -- **Concise and professional** - No casual language or filler words -- **Action-oriented** - Start with verbs: "Processes...", "Manages...", "Converts..." -- **Purpose before implementation** - Explain WHY before HOW -- **Clear parameter descriptions** - Include type hints, defaults, and purpose -- **No redundant type info** - Type hints are in the signature, don't repeat in description -- **Use backticks for code references** - Wrap class names, method names, event names, parameter names, and code snippets in backticks - -Good: "Neuphonic API key for authentication." -Bad: "str: The API key (string) that is used for authenticating with Neuphonic." - -Good: "Triggers `on_speech_started` when the `VADAnalyzer` detects speech." -Bad: "Triggers on_speech_started when the VADAnalyzer detects speech." - -## Deprecation Notice Format - -When documenting deprecated code: - -```python -"""[Description]. - -.. deprecated:: X.X.X - `ClassName` is deprecated and will be removed in a future version. - Use `NewClassName` instead. -""" -``` - -## Checklist - -Before finishing, verify: - -- [ ] Module has a docstring at the top (after copyright header and imports) -- [ ] All public classes have docstrings -- [ ] All `__init__` methods document their parameters -- [ ] All public methods have docstrings with Args/Returns/Raises as needed -- [ ] Dataclasses use "Parameters:" section for field descriptions -- [ ] Enums document each value in "Parameters:" section -- [ ] Writing is concise and action-oriented -- [ ] No documentation added to private methods (starting with `_`) -- [ ] Existing complete docstrings were left unchanged diff --git a/.claude/skills/pr-description/SKILL.md b/.claude/skills/pr-description/SKILL.md deleted file mode 100644 index 666cf2bd1..000000000 --- a/.claude/skills/pr-description/SKILL.md +++ /dev/null @@ -1,128 +0,0 @@ ---- -name: pr-description -description: Update a GitHub PR description with a summary of changes ---- - -Update a GitHub pull request description based on the changes in the PR. - -## Arguments - -``` -/pr-description [--fixes ] -``` - -- `PR_NUMBER` (required): The pull request number to update -- `--fixes` (optional): Comma-separated issue numbers that this PR fixes (e.g., `--fixes 123,456`) - -Examples: -- `/pr-description 3534` -- `/pr-description 3534 --fixes 123` -- `/pr-description 3534 --fixes 123,456,789` - -## Instructions - -1. First, gather information about the PR: - - Use GitHub plugin to get PR details (title, current description, base branch) - - Use local git to get commits: `git log main..HEAD --oneline` - - Use local git to get the diff: `git diff main..HEAD` - - Parse any `--fixes` argument for issue numbers - -2. Check the existing PR description: - - If it already has a complete, accurate description that reflects the changes, do nothing - - If it's missing sections, incomplete, or outdated compared to the actual changes, proceed to update - - If it only has the template placeholder text, generate a full description - -3. Analyze the changes: - - Understand the purpose of each commit - - Identify any breaking changes (API changes, removed features, behavior changes) - - Look for new features, bug fixes, refactoring, or documentation changes - - Collect issue numbers from: - - The `--fixes` argument (if provided) - - Commit messages (patterns like "Fixes #123", "Closes #456", "Resolves #789") - -4. Generate or update the PR description with these sections: - -## PR Description Format - -### Summary (always include) - -Brief bullet points describing what changed and why. Focus on the *purpose* and *impact*, not implementation details. - -```markdown -## Summary - -- Added X to enable Y -- Fixed bug where Z would happen -- Refactored W for better maintainability -``` - -### Breaking Changes (include only if applicable) - -Document any changes that affect existing users or APIs. - -```markdown -## Breaking Changes - -- `ClassName.method()` now requires a `param` argument -- Removed deprecated `old_function()` - use `new_function()` instead -``` - -### Testing (include when non-obvious) - -How to verify the changes work. Skip for trivial changes. - -```markdown -## Testing - -- Run `uv run pytest tests/test_feature.py` to verify the fix -- Example usage: `uv run examples/new_feature.py` -``` - -### Fixes (include if issues are provided or found in commits) - -List issues this PR fixes. GitHub will automatically close these issues when the PR is merged. - -```markdown -## Fixes - -- Fixes #123 -- Fixes #456 -``` - -Note: Use "Fixes #X" format (not "Closes" or "Resolves") for consistency. Each issue should be on its own line with "Fixes" to ensure GitHub auto-closes them. - -## Guidelines - -- **Be concise** - Reviewers should understand the PR in 30 seconds -- **Focus on why** - The diff shows *what* changed, explain *why* -- **Skip empty sections** - Only include sections that have content -- **Use bullet points** - Easier to scan than paragraphs -- **Don't duplicate the diff** - Avoid listing every file or line changed - -## Example Output - -```markdown -## Summary - -- Added `/docstring` skill for documenting Python modules with Google-style docstrings -- Skill finds classes by name and handles conflicts when multiple matches exist -- Skips already-documented code to avoid unnecessary changes - -## Testing - -/docstring ClassName - -## Fixes - -- Fixes #123 -``` - -## Checklist - -Before updating the PR: - -- [ ] Verified existing description needs updating (not already complete) -- [ ] Summary accurately reflects the changes -- [ ] Breaking changes are clearly documented (if any) -- [ ] No unnecessary sections included -- [ ] Description is concise and scannable diff --git a/.claude/skills/pr-submit/SKILL.md b/.claude/skills/pr-submit/SKILL.md deleted file mode 100644 index 5724ddb6e..000000000 --- a/.claude/skills/pr-submit/SKILL.md +++ /dev/null @@ -1,28 +0,0 @@ ---- -name: pr-submit -description: Create and submit a GitHub PR from the current branch ---- - -Submit the current changes as a GitHub pull request. - -## Instructions - -1. Check the current state of the repository: - - Run `git status` to see staged, unstaged, and untracked changes - - Run `git diff` to see current changes - - Run `git log --oneline -10` to see recent commits - -2. If there are uncommitted changes relevant to the PR: - - Ask the user if they want a specific prefix for the branch name (e.g., `alice/`, `fix/`, `feat/`) - - Create a new branch based on the current branch - - Commit the changes using multiple commits if the changes are unrelated - -3. Push the branch and create the PR: - - Push with `-u` flag to set upstream tracking - - Create the PR using `gh pr create` - -4. After the PR is created: - - Run `/changelog ` to generate changelog files, then commit and push them - - Run `/pr-description ` to update the PR description - -5. Return the PR URL to the user. diff --git a/README.md b/README.md index 6d6a56612..058f23128 100644 --- a/README.md +++ b/README.md @@ -55,6 +55,22 @@ Looking for help debugging your pipeline and processors? Check out [Whisker](htt Love terminal applications? Check out [Tail](https://github.com/pipecat-ai/tail), a terminal dashboard for Pipecat. +### 🤖 Claude Code Skills + +Use [Pipecat Skills](https://github.com/pipecat-ai/skills) with [Claude Code](https://claude.ai/code) to scaffold projects, generate changelogs, deploy to Pipecat Cloud, and more. Install the marketplace with: + +``` +claude plugin marketplace add pipecat-ai/skills +``` + +And install the plugins, for example: + +``` +claude plugin install pipecat-dev@pipecat-skills +``` + +there's more! + ### 📺️ Pipecat TV Channel Catch new features, interviews, and how-tos on our [Pipecat TV](https://www.youtube.com/playlist?list=PLzU2zoMTQIHjqC3v4q2XVSR3hGSzwKFwH) channel. From b6f21ab15da08a6577a6ebbcf401346229273e01 Mon Sep 17 00:00:00 2001 From: Paul Kompfner Date: Tue, 24 Feb 2026 17:07:20 -0500 Subject: [PATCH 0621/1060] =?UTF-8?q?Make=20`ServiceUpdateSettingsFrame`?= =?UTF-8?q?=20uninterruptible=E2=80=94settings=20updates=20are=20generally?= =?UTF-8?q?=20independent=20of=20specific=20utterances.?= MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit Before this change, settings updates were often not applied. For example, a `TTSUpdateSettingsFrame` queued while the bot was speaking would only have an effect at the end of the bot's reply, and any interruption before the end of the reply would "cancel" the update. --- changelog/3819.changed.md | 4 ++++ src/pipecat/frames/frames.py | 2 +- 2 files changed, 5 insertions(+), 1 deletion(-) create mode 100644 changelog/3819.changed.md diff --git a/changelog/3819.changed.md b/changelog/3819.changed.md new file mode 100644 index 000000000..7b43c399c --- /dev/null +++ b/changelog/3819.changed.md @@ -0,0 +1,4 @@ +- `ServiceSettingsUpdateFrame`s are now `UninterruptibleFrame`s. Generally speaking, you don't want a user interruption to prevent a service setting change from going into effect. Note that you usually don't use `ServiceSettingsUpdateFrame` directly, you use one of its subclasses: + - `LLMUpdateSettingsFrame` + - `TTSUpdateSettingsFrame` + - `STTUpdateSettingsFrame` diff --git a/src/pipecat/frames/frames.py b/src/pipecat/frames/frames.py index c69ddc931..d359bcfb1 100644 --- a/src/pipecat/frames/frames.py +++ b/src/pipecat/frames/frames.py @@ -2118,7 +2118,7 @@ class TTSStoppedFrame(ControlFrame): @dataclass -class ServiceUpdateSettingsFrame(ControlFrame): +class ServiceUpdateSettingsFrame(ControlFrame, UninterruptibleFrame): """Base frame for updating service settings. Supports both a ``settings`` dict (for backward compatibility) and a From d91c230b8559c2a7d53dcc46a7163e331c554f77 Mon Sep 17 00:00:00 2001 From: Paul Kompfner Date: Tue, 24 Feb 2026 18:05:27 -0500 Subject: [PATCH 0622/1060] Fix breakage when using a generic settings update (e.g. a `TTSSettings`) instead of a more specific one (e.g. a `RimeTTSSettings`). Both should work, assuming you're only changing fields present in the generic settings. --- src/pipecat/services/settings.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/src/pipecat/services/settings.py b/src/pipecat/services/settings.py index 7de476c64..641cc23f5 100644 --- a/src/pipecat/services/settings.py +++ b/src/pipecat/services/settings.py @@ -221,7 +221,7 @@ class ServiceSettings: for f in fields(self): if f.name == "extra": continue - new_val = getattr(delta, f.name) + new_val = getattr(delta, f.name, NOT_GIVEN) if not is_given(new_val): continue old_val = getattr(self, f.name) From d918a20b759bc280fc14a1f2b2897c5936d14966 Mon Sep 17 00:00:00 2001 From: Paul Kompfner Date: Tue, 24 Feb 2026 18:14:16 -0500 Subject: [PATCH 0623/1060] Fix missing field warning in `RimeTTSService` --- src/pipecat/services/rime/tts.py | 1 + 1 file changed, 1 insertion(+) diff --git a/src/pipecat/services/rime/tts.py b/src/pipecat/services/rime/tts.py index 6c3ff4e23..248c84008 100644 --- a/src/pipecat/services/rime/tts.py +++ b/src/pipecat/services/rime/tts.py @@ -235,6 +235,7 @@ class RimeTTSService(AudioContextTTSService): if params.language else None, segment=params.segment, + inlineSpeedAlpha=None, # Not applicable here # Arcana params repetition_penalty=params.repetition_penalty, temperature=params.temperature, From f421ad9cf672c08ce2bdede5b96824273033b20c Mon Sep 17 00:00:00 2001 From: Mark Backman Date: Tue, 24 Feb 2026 18:57:38 -0500 Subject: [PATCH 0624/1060] Fix STT TTFB timeout measuring to timeout expiry instead of transcript time MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit PR #3776 replaced manual timestamp tracking with stop_ttfb_metrics() in the timeout handler, but without an end_time it uses time.time() at timeout expiry—producing TTFB = timeout + stop_secs (~2.2s) instead of the actual transcript latency. Restore _last_transcript_time tracking so the timeout handler measures to when the transcript arrived, and skip reporting if none arrived. --- src/pipecat/services/stt_service.py | 14 +++++++++++--- 1 file changed, 11 insertions(+), 3 deletions(-) diff --git a/src/pipecat/services/stt_service.py b/src/pipecat/services/stt_service.py index eedc8b46d..20e8cacc9 100644 --- a/src/pipecat/services/stt_service.py +++ b/src/pipecat/services/stt_service.py @@ -127,6 +127,7 @@ class STTService(AIService): self._user_speaking: bool = False self._finalize_pending: bool = False self._finalize_requested: bool = False + self._last_transcript_time: float = 0 # Keepalive state self._keepalive_timeout = keepalive_timeout @@ -385,6 +386,9 @@ class STTService(AIService): direction: The direction to push the frame. """ if isinstance(frame, TranscriptionFrame): + # Store the transcript time for TTFB calculation + self._last_transcript_time = time.time() + # Set finalized from pending state and auto-reset if self._finalize_pending: frame.finalized = True @@ -438,6 +442,7 @@ class STTService(AIService): self._user_speaking = True self._finalize_requested = False self._finalize_pending = False + self._last_transcript_time = 0 async def _handle_vad_user_stopped_speaking(self, frame: VADUserStoppedSpeakingFrame): """Handle VAD user stopped speaking frame. @@ -467,14 +472,17 @@ class STTService(AIService): ) async def _ttfb_timeout_handler(self): - """Wait for timeout then report TTFB. + """Wait for timeout then report TTFB using the last transcript timestamp. This timeout allows the final transcription to arrive before we calculate - and report TTFB. If no transcription arrived, no TTFB is reported. + and report TTFB. Uses _last_transcript_time as the end time so we measure + to when the transcript actually arrived, not when the timeout fired. + If no transcription arrived, no TTFB is reported. """ try: await asyncio.sleep(self._stt_ttfb_timeout) - await self.stop_ttfb_metrics() + if self._last_transcript_time > 0: + await self.stop_ttfb_metrics(end_time=self._last_transcript_time) except asyncio.CancelledError: # Task was cancelled (new utterance or interruption), which is expected behavior pass From f928206b3ade9bf9531245bcd38b6f2d9c17c8fc Mon Sep 17 00:00:00 2001 From: Mark Backman Date: Tue, 24 Feb 2026 19:02:40 -0500 Subject: [PATCH 0625/1060] Add changelog for STT TTFB timeout fix --- changelog/3822.fixed.md | 1 + 1 file changed, 1 insertion(+) create mode 100644 changelog/3822.fixed.md diff --git a/changelog/3822.fixed.md b/changelog/3822.fixed.md new file mode 100644 index 000000000..48218845f --- /dev/null +++ b/changelog/3822.fixed.md @@ -0,0 +1 @@ +- Fixed STT TTFB metrics measuring timeout expiry time instead of actual transcript arrival time. \ No newline at end of file From 69d916ca519df7aa4e83aa584914cb97836999cb Mon Sep 17 00:00:00 2001 From: Mark Backman Date: Tue, 24 Feb 2026 20:51:41 -0500 Subject: [PATCH 0626/1060] Consume InterimTranscriptionFrame and TranslationFrame in LLMUserAggregator These frames were falling through to the else branch and being pushed downstream, unlike TranscriptionFrame which is explicitly consumed. This aligns with how the assistant aggregator already filters them. --- .../aggregators/llm_response_universal.py | 4 ++ tests/test_context_aggregators_universal.py | 40 +++++++++++++++++++ 2 files changed, 44 insertions(+) diff --git a/src/pipecat/processors/aggregators/llm_response_universal.py b/src/pipecat/processors/aggregators/llm_response_universal.py index e5884a868..4a28b38d5 100644 --- a/src/pipecat/processors/aggregators/llm_response_universal.py +++ b/src/pipecat/processors/aggregators/llm_response_universal.py @@ -461,6 +461,10 @@ class LLMUserAggregator(LLMContextAggregator): await self.push_frame(frame, direction) elif isinstance(frame, TranscriptionFrame): await self._handle_transcription(frame) + elif isinstance(frame, (InterimTranscriptionFrame, TranslationFrame)): + # Interim transcriptions and translations are consumed here + # and not pushed downstream, same as final TranscriptionFrame. + pass elif isinstance(frame, LLMRunFrame): await self._handle_llm_run(frame) elif isinstance(frame, LLMMessagesAppendFrame): diff --git a/tests/test_context_aggregators_universal.py b/tests/test_context_aggregators_universal.py index 1bba463b0..e86905e1c 100644 --- a/tests/test_context_aggregators_universal.py +++ b/tests/test_context_aggregators_universal.py @@ -12,6 +12,7 @@ from pipecat.frames.frames import ( FunctionCallFromLLM, FunctionCallResultFrame, FunctionCallsStartedFrame, + InterimTranscriptionFrame, InterruptionFrame, LLMContextAssistantTimestampFrame, LLMContextFrame, @@ -26,6 +27,7 @@ from pipecat.frames.frames import ( LLMThoughtTextFrame, StartFrame, TranscriptionFrame, + TranslationFrame, UserMuteStartedFrame, UserStartedSpeakingFrame, UserStoppedSpeakingFrame, @@ -428,6 +430,44 @@ class TestLLMUserAggregator(unittest.IsolatedAsyncioTestCase): ignore_start=False, ) + async def test_interim_transcription_not_pushed_downstream(self): + """InterimTranscriptionFrame should be consumed and not pushed downstream.""" + context = LLMContext() + pipeline = Pipeline([LLMUserAggregator(context)]) + + frames_to_send = [ + InterimTranscriptionFrame(text="Hel", user_id="", timestamp="now"), + InterimTranscriptionFrame(text="Hello", user_id="", timestamp="now"), + ] + # The interim transcription triggers a user turn start via the default + # TranscriptionUserTurnStartStrategy, so we expect turn-related frames + # but NOT the InterimTranscriptionFrame itself. + expected_down_frames = [ + UserStartedSpeakingFrame, + InterruptionFrame, + ] + (down_frames, _) = await run_test( + pipeline, + frames_to_send=frames_to_send, + expected_down_frames=expected_down_frames, + ) + self.assertFalse(any(isinstance(f, InterimTranscriptionFrame) for f in down_frames)) + + async def test_translation_not_pushed_downstream(self): + """TranslationFrame should be consumed and not pushed downstream.""" + context = LLMContext() + pipeline = Pipeline([LLMUserAggregator(context)]) + + frames_to_send = [ + TranslationFrame(text="Hola!", user_id="", timestamp="now", language="es"), + ] + # No downstream frames expected — translations are consumed. + await run_test( + pipeline, + frames_to_send=frames_to_send, + expected_down_frames=[], + ) + class TestLLMAssistantAggregator(unittest.IsolatedAsyncioTestCase): async def test_empty(self): From 167e68672b33c4903601f45d6eb3eed528ec2cd6 Mon Sep 17 00:00:00 2001 From: Mark Backman Date: Tue, 24 Feb 2026 20:52:16 -0500 Subject: [PATCH 0627/1060] Add changelog for InterimTranscriptionFrame/TranslationFrame fix --- changelog/3825.fixed.md | 1 + 1 file changed, 1 insertion(+) create mode 100644 changelog/3825.fixed.md diff --git a/changelog/3825.fixed.md b/changelog/3825.fixed.md new file mode 100644 index 000000000..7cd9ba508 --- /dev/null +++ b/changelog/3825.fixed.md @@ -0,0 +1 @@ +- Fixed `InterimTranscriptionFrame` and `TranslationFrame` being unintentionally pushed downstream in `LLMUserAggregator`. They are now consumed like `TranscriptionFrame`. From a84930dc3eadb28b408ef61db206f0e48b41fd88 Mon Sep 17 00:00:00 2001 From: Mark Backman Date: Tue, 24 Feb 2026 23:21:52 -0500 Subject: [PATCH 0628/1060] Skip empty audio frames after filter buffering Audio filters like RNNoise, KrispViva, and AIC return empty bytes while buffering audio to accumulate their required frame size. These empty frames were flowing downstream, causing misleading "Empty audio frame received for STT service" warnings. Skip the frame in BaseInputTransport when audio is empty, preventing unnecessary processing in VAD and downstream processors. Fixes #3517 --- changelog/3828.fixed.md | 1 + src/pipecat/transports/base_input.py | 5 +++++ 2 files changed, 6 insertions(+) create mode 100644 changelog/3828.fixed.md diff --git a/changelog/3828.fixed.md b/changelog/3828.fixed.md new file mode 100644 index 000000000..dd2ee257d --- /dev/null +++ b/changelog/3828.fixed.md @@ -0,0 +1 @@ +- Fixed misleading "Empty audio frame received for STT service" warnings when using audio filters (e.g. `RNNoiseFilter`, `KrispVivaFilter`, `AICFilter`) that buffer audio internally. diff --git a/src/pipecat/transports/base_input.py b/src/pipecat/transports/base_input.py index 77ff61bba..49c28149a 100644 --- a/src/pipecat/transports/base_input.py +++ b/src/pipecat/transports/base_input.py @@ -424,6 +424,11 @@ class BaseInputTransport(FrameProcessor): if self._params.audio_in_filter: frame.audio = await self._params.audio_in_filter.filter(frame.audio) + # Skip frames with no audio data (e.g. filter is buffering). + if not frame.audio: + self._audio_in_queue.task_done() + continue + ################################################################### # DEPRECATED. # From 68e19a730b4d17ddb515700314a68c3f2a811503 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Aleix=20Conchillo=20Flaqu=C3=A9?= Date: Tue, 24 Feb 2026 23:47:06 -0800 Subject: [PATCH 0629/1060] Restore dev skills and add marketplace for maintainer workflows Brings back the 6 development workflow skills (changelog, cleanup, code-review, docstring, pr-description, pr-submit) that were moved to pipecat-ai/skills, and adds a .claude-plugin/marketplace.json so other pipecat-ai repos can install them. Updates README contributing section with installation instructions. --- .claude-plugin/marketplace.json | 26 +++ .claude/skills/changelog/SKILL.md | 47 ++++ .claude/skills/cleanup/SKILL.md | 307 +++++++++++++++++++++++++ .claude/skills/code-review/SKILL.md | 107 +++++++++ .claude/skills/docstring/SKILL.md | 256 +++++++++++++++++++++ .claude/skills/pr-description/SKILL.md | 128 +++++++++++ .claude/skills/pr-submit/SKILL.md | 28 +++ README.md | 19 +- 8 files changed, 910 insertions(+), 8 deletions(-) create mode 100644 .claude-plugin/marketplace.json create mode 100644 .claude/skills/changelog/SKILL.md create mode 100644 .claude/skills/cleanup/SKILL.md create mode 100644 .claude/skills/code-review/SKILL.md create mode 100644 .claude/skills/docstring/SKILL.md create mode 100644 .claude/skills/pr-description/SKILL.md create mode 100644 .claude/skills/pr-submit/SKILL.md diff --git a/.claude-plugin/marketplace.json b/.claude-plugin/marketplace.json new file mode 100644 index 000000000..64aac9338 --- /dev/null +++ b/.claude-plugin/marketplace.json @@ -0,0 +1,26 @@ +{ + "name": "pipecat-dev-skills", + "owner": { + "name": "Pipecat" + }, + "metadata": { + "description": "Development workflow skills for contributing to the Pipecat project", + "version": "1.0.0" + }, + "plugins": [ + { + "name": "pipecat-dev", + "description": "Development workflow skills for contributing to the Pipecat project", + "version": "1.0.0", + "source": "./", + "skills": [ + "./.claude/skills/changelog", + "./.claude/skills/cleanup", + "./.claude/skills/code-review", + "./.claude/skills/docstring", + "./.claude/skills/pr-description", + "./.claude/skills/pr-submit" + ] + } + ] +} diff --git a/.claude/skills/changelog/SKILL.md b/.claude/skills/changelog/SKILL.md new file mode 100644 index 000000000..1ef8f324e --- /dev/null +++ b/.claude/skills/changelog/SKILL.md @@ -0,0 +1,47 @@ +--- +name: changelog +description: Create changelog files for important commits in a PR +--- + +Create changelog files for the important commits in this PR. The PR number is provided as an argument. + +## Instructions + +1. Skip changelog for: documentation-only, internal refactoring, test-only, CI changes. + +2. First, check what commits are on the current branch compared to main: + ``` + git log main..HEAD --oneline + ``` + +3. For each significant change, create a changelog file in the `changelog/` folder using the format: + Allowed types: `added`, `changed`, `deprecated`, `removed`, `fixed`, `security`, `performance`, `other` + - `{PR_NUMBER}.added.md` - for new features + - `{PR_NUMBER}.added.2.md`, `{PR_NUMBER}.added.3.md` - for additional entries of the same type + - `{PR_NUMBER}.changed.md` - for changes to existing functionality + - `{PR_NUMBER}.fixed.md` - for bug fixes + - `{PR_NUMBER}.deprecated.md` - for deprecations + - `{PR_NUMBER}.removed.md` - for removed features + - `{PR_NUMBER}.security.md` - for security fixes + - `{PR_NUMBER}.performance.md` - for performance improvements + - `{PR_NUMBER}.other.md` - for other changes + +4. Each changelog file should at least contain a main single line starting with `- ` followed by a clear description of the change. No line wrapping. + +5. If the change is complicated, changelog files can have indented lines after the main line with additional details or code samples. + +6. Use ⚠️ emoji prefix for breaking changes. + +## Example + +For PR #3519 with a new feature and a bug fix: + +`changelog/3519.added.md`: +``` +- Added `SomeNewFeature` for doing something useful. +``` + +`changelog/3519.fixed.md`: +``` +- Fixed an issue where something was not working correctly. +``` diff --git a/.claude/skills/cleanup/SKILL.md b/.claude/skills/cleanup/SKILL.md new file mode 100644 index 000000000..91a61db39 --- /dev/null +++ b/.claude/skills/cleanup/SKILL.md @@ -0,0 +1,307 @@ +# Code Cleanup Skill + +The **Code Cleanup Skill** reviews, refactors, and documents code changes in your current branch, ensuring alignment with **Pipecat's architecture, coding standards, and example patterns**. +It focuses on **readability, correctness, performance, and consistency**, while avoiding breaking changes. + +--- + +## Skill Overview + +This skill analyzes all changes introduced in your branch and performs the following actions: + +1. **Analyze Branch Changes** + - Review uncommitted changes and outgoing commits +2. **Refactor for Readability** + - Improve clarity, naming, structure, and modern Python usage +3. **Enhance Performance** + - Identify safe, conservative optimization opportunities +4. **Add Documentation** + - Apply Pipecat-style, Google-format docstrings +5. **Ensure Pattern Consistency** + - Match existing Pipecat services, pipelines, and examples +6. **Validate Examples** + - Ensure examples follow foundational patterns (e.g. `07-interruptible.py`) + +--- + +## Usage + +Invoke the skill using any of the following commands: + +- "Clean up my branch code" +- "Refactor the changes in my branch" +- "Review and improve my branch code" +- `/cleanup` + +--- + +## What This Skill Does + +### 1. Analyze Branch Changes + +The skill retrieves all uncommitted changes and outgoing commits to understand: + +- New files added +- Modified files +- Code additions and deletions +- Overall scope and intent of changes + +--- + +### 2. Code Refactoring + +#### Readability Improvements + +- Replace tuples with named classes or dataclasses +- Improve variable, method, and class naming +- Extract complex logic into well-named helper methods +- Add missing type hints +- Simplify nested or complex conditionals +- Replace deprecated methods and features +- Normalize formatting to match Pipecat style + +#### Performance Enhancements + +- Identify inefficient loops or repeated work +- Suggest appropriate data structures +- Optimize async workflows and I/O +- Remove redundant operations + +> Performance changes are conservative and non-breaking. + +--- + +### 3. Documentation + +Documentation follows **Google-style docstrings**, consistent with Pipecat conventions. + +#### Class Documentation + +```python +class ExampleService: + """Brief one-line description. + + Detailed explanation of the class purpose, responsibilities, + and important behaviors. + + Supported features: + + - Feature 1 + - Feature 2 + - Feature 3 + """ +``` + +#### Method Documentation + +```python +def process_data(self, data: str, options: Optional[dict] = None) -> bool: + """Process incoming data with optional configuration. + + Args: + data: The input data to process. + options: Optional configuration dictionary. + + Returns: + True if processing succeeded, False otherwise. + + Raises: + ValueError: If data is empty or invalid. + """ +``` + +#### Pydantic Model Parameters + +```python +class InputParams(BaseModel): + """Configuration parameters for the service. + + Parameters: + timeout: Request timeout in seconds. + retry_count: Number of retry attempts. + enable_logging: Whether to enable debug logging. + """ + + timeout: Optional[float] = None + retry_count: int = 3 + enable_logging: bool = False +``` + +--- + +### 4. Pattern Consistency Checks + +#### Service Classes + +- Correct inheritance (`TTSService`, `STTService`, `LLMService`) +- Consistent constructor signatures +- Frame emission patterns +- Metrics support: + - `can_generate_metrics()` + - TTFB metrics + - Usage metrics +- Alignment with similar existing services + +#### Examples + +Validated against `examples/foundational/07-interruptible.py`: + +- Proper `create_transport()` usage +- Correct pipeline structure +- Task setup and observers +- Event handler registration +- Runner and bot entrypoint consistency + +--- + +### 5. Specific Implementation Patterns + +#### Service Implementation + +```python +class ExampleTTSService(TTSService): + + def __init__(self, *, api_key: Optional[str] = None, **kwargs): + super().__init__(**kwargs) + self._api_key = api_key or os.getenv("SERVICE_API_KEY") + + def can_generate_metrics(self) -> bool: + return True + + async def run_tts(self, text: str) -> AsyncGenerator[Frame, None]: + try: + await self.start_ttfb_metrics() + yield TTSStartedFrame() + # ... processing ... + yield TTSAudioRawFrame(...) + finally: + await self.stop_ttfb_metrics() +``` + +--- + +#### Example Structure Pattern + +```python +transport_params = { + "daily": lambda: DailyParams(...), + "twilio": lambda: FastAPIWebsocketParams(...), + "webrtc": lambda: TransportParams(...), +} + +async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): + stt = DeepgramSTTService(...) + tts = SomeTTSService(...) + llm = OpenAILLMService(...) + + context = LLMContext(messages) + user_aggregator, assistant_aggregator = LLMContextAggregatorPair(...) + + pipeline = Pipeline([...]) + task = PipelineTask(pipeline, params=..., observers=[...]) + + @transport.event_handler("on_client_connected") + async def on_client_connected(transport, client): + await task.queue_frames([LLMRunFrame()]) + + runner = PipelineRunner(handle_sigint=runner_args.handle_sigint) + await runner.run(task) + +async def bot(runner_args: RunnerArguments): + """Main bot entry point compatible with Pipecat Cloud.""" + transport = await create_transport(runner_args, transport_params) + await run_bot(transport, runner_args) +``` + +--- + +## Execution Flow + +1. Fetch uncommitted and outgoing changes +2. Categorize files (services, examples, tests, utilities) +3. Analyze each file: + - Readability + - Performance + - Documentation + - Pattern consistency +4. Generate actionable recommendations +5. Apply Pipecat standards + +--- + +## Examples + +### Before: Tuple Usage + +```python +def get_audio_info(self) -> Tuple[int, int]: + return (48000, 1) +``` + +### After: Named Class + +```python +class AudioInfo: + """Audio configuration information. + + Parameters: + sample_rate: Sample rate in Hz. + num_channels: Number of audio channels. + """ + + sample_rate: int + num_channels: int + +def get_audio_info(self) -> AudioInfo: + return AudioInfo(sample_rate=48000, num_channels=1) +``` + +--- + +### Before: Missing Documentation + +```python +class NewTTSService(TTSService): + def __init__(self, api_key: str, voice: str): + self._api_key = api_key + self._voice = voice +``` + +### After: Fully Documented + +```python +class NewTTSService(TTSService): + """Text-to-speech service using NewProvider API. + + Streams PCM audio and emits TTSAudioRawFrame frames compatible + with Pipecat transports. + + Supported features: + - Text-to-speech synthesis + - Streaming PCM audio + - Voice customization + - TTFB metrics + """ + + def __init__(self, *, api_key: str, voice: str, **kwargs): + """Initialize the NewTTSService. + + Args: + api_key: API key for authentication. + voice: Voice identifier to use. + **kwargs: Additional arguments passed to the parent service. + """ + super().__init__(**kwargs) + self._api_key = api_key + self.set_voice(voice) +``` + +--- + +## Notes + +- Non-breaking improvements only +- Backward compatibility preserved +- Conservative performance changes +- Google-style docstrings +- Pattern checks follow recent Pipecat code diff --git a/.claude/skills/code-review/SKILL.md b/.claude/skills/code-review/SKILL.md new file mode 100644 index 000000000..036a7f935 --- /dev/null +++ b/.claude/skills/code-review/SKILL.md @@ -0,0 +1,107 @@ +--- +name: code-review +description: Automated code review for pull requests using multiple specialized agents +disable-model-invocation: true +allowed-tools: Bash(gh issue view:*), Bash(gh search:*), Bash(gh issue list:*), Bash(gh pr comment:*), Bash(gh pr diff:*), Bash(gh pr view:*), Bash(gh pr list:*) +--- + +Provide a code review for the given pull request. + +**Agent assumptions (applies to all agents and subagents):** + +- All tools are functional and will work without error. Do not test tools or make exploratory calls. Make sure this is clear to every subagent that is launched. +- Only call a tool if it is required to complete the task. Every tool call should have a clear purpose. + +To do this, follow these steps precisely: + +1. Launch a haiku agent to check if any of the following are true: + - The pull request is closed + - The pull request is a draft + - The pull request does not need code review (e.g. automated PR, trivial change that is obviously correct) + - Claude has already commented on this PR (check `gh pr view --comments` for comments left by claude) + + If any condition is true, stop and do not proceed. + +Note: Still review Claude generated PR's. + +2. Launch a haiku agent to return a list of file paths (not their contents) for all relevant CLAUDE.md files including: + - The root CLAUDE.md file, if it exists + - Any CLAUDE.md files in directories containing files modified by the pull request + +3. Launch a sonnet agent to view the pull request and return a summary of the changes + +4. Launch 4 agents in parallel to independently review the changes. Each agent should return the list of issues, where each issue includes a description and the reason it was flagged (e.g. "CLAUDE.md adherence", "bug"). The agents should do the following: + + Agents 1 + 2: CLAUDE.md compliance sonnet agents + Audit changes for CLAUDE.md compliance in parallel. Note: When evaluating CLAUDE.md compliance for a file, you should only consider CLAUDE.md files that share a file path with the file or parents. + + Agent 3: Opus bug agent (parallel subagent with agent 4) + Scan for obvious bugs. Focus only on the diff itself without reading extra context. Flag only significant bugs; ignore nitpicks and likely false positives. Do not flag issues that you cannot validate without looking at context outside of the git diff. + + Agent 4: Opus bug agent (parallel subagent with agent 3) + Look for problems that exist in the introduced code. This could be security issues, incorrect logic, etc. Only look for issues that fall within the changed code. + + **CRITICAL: We only want HIGH SIGNAL issues.** Flag issues where: + - The code will fail to compile or parse (syntax errors, type errors, missing imports, unresolved references) + - The code will definitely produce wrong results regardless of inputs (clear logic errors) + - Clear, unambiguous CLAUDE.md violations where you can quote the exact rule being broken + + Do NOT flag: + - Code style or quality concerns + - Potential issues that depend on specific inputs or state + - Subjective suggestions or improvements + + If you are not certain an issue is real, do not flag it. False positives erode trust and waste reviewer time. + + In addition to the above, each subagent should be told the PR title and description. This will help provide context regarding the author's intent. + +5. For each issue found in the previous step by agents 3 and 4, launch parallel subagents to validate the issue. These subagents should get the PR title and description along with a description of the issue. The agent's job is to review the issue to validate that the stated issue is truly an issue with high confidence. For example, if an issue such as "variable is not defined" was flagged, the subagent's job would be to validate that is actually true in the code. Another example would be CLAUDE.md issues. The agent should validate that the CLAUDE.md rule that was violated is scoped for this file and is actually violated. Use Opus subagents for bugs and logic issues, and sonnet agents for CLAUDE.md violations. + +6. Filter out any issues that were not validated in step 5. This step will give us our list of high signal issues for our review. + +7. If issues were found, skip to step 8 to post comments. + + If NO issues were found, post a summary comment using `gh pr comment` (if `--comment` argument is provided): + "No issues found. Checked for bugs and CLAUDE.md compliance." + +8. Create a list of all comments that you plan on leaving. This is only for you to make sure you are comfortable with the comments. Do not post this list anywhere. + +9. Post inline comments for each issue using `gh pr review` with inline comments. For each comment: + - Provide a brief description of the issue + - For small, self-contained fixes, include a committable suggestion block + - For larger fixes (6+ lines, structural changes, or changes spanning multiple locations), describe the issue and suggested fix without a suggestion block + - Never post a committable suggestion UNLESS committing the suggestion fixes the issue entirely. If follow up steps are required, do not leave a committable suggestion. + + **IMPORTANT: Only post ONE comment per unique issue. Do not post duplicate comments.** + +Use this list when evaluating issues in Steps 4 and 5 (these are false positives, do NOT flag): + +- Pre-existing issues +- Something that appears to be a bug but is actually correct +- Pedantic nitpicks that a senior engineer would not flag +- Issues that a linter will catch (do not run the linter to verify) +- General code quality concerns (e.g., lack of test coverage, general security issues) unless explicitly required in CLAUDE.md +- Issues mentioned in CLAUDE.md but explicitly silenced in the code (e.g., via a lint ignore comment) + +Notes: + +- Use gh CLI to interact with GitHub (e.g., fetch pull requests, create comments). Do not use web fetch. +- Create a todo list before starting. +- You must cite and link each issue in inline comments (e.g., if referring to a CLAUDE.md, include a link to it). +- If no issues are found, post a comment with the following format: + +--- + +## Code review + +No issues found. Checked for bugs and CLAUDE.md compliance. + +--- + +- When linking to code in inline comments, follow the following format precisely, otherwise the Markdown preview won't render correctly: `https://github.com/OWNER/REPO/blob/FULL_SHA/path/to/file.py#L10-L15` + - Requires full git sha + - You must provide the full sha. Commands like `https://github.com/owner/repo/blob/$(git rev-parse HEAD)/foo/bar` will not work, since your comment will be directly rendered in Markdown. + - Repo name must match the repo you're code reviewing + - # sign after the file name + - Line range format is L[start]-L[end] + - Provide at least 1 line of context before and after, centered on the line you are commenting about (eg. if you are commenting about lines 5-6, you should link to `L4-7`) diff --git a/.claude/skills/docstring/SKILL.md b/.claude/skills/docstring/SKILL.md new file mode 100644 index 000000000..129d83763 --- /dev/null +++ b/.claude/skills/docstring/SKILL.md @@ -0,0 +1,256 @@ +--- +name: docstring +description: Document a Python module and its classes using Google style +--- + +Document a Python module or class using Google-style docstrings following project conventions. The argument can be a class name or a module path. + +## Instructions + +1. Determine what to document based on the argument: + + **If a module path is provided** (e.g. `src/pipecat/audio/vad/vad_analyzer.py`): + - Use that file directly + + **If a class name is provided** (e.g. `VADAnalyzer`): + - Search for `class ClassName` in `src/pipecat/` + - If multiple files contain that class name, list all matches with their file paths, ask the user which one they want to document, and wait for confirmation + +2. Once the file is identified, read the module to understand its structure: + - Identify all classes, functions, and important type aliases + - Understand the purpose of each component + +4. Apply documentation in this order: + - Module docstring (at top, after imports) + - Class docstrings + - `__init__` methods (always document constructor parameters) + - Public methods (not starting with `_`) + - Dataclass/config classes with field descriptions + +5. Skip documentation for: + - Private methods (starting with `_`) + - Simple dunder methods (`__str__`, `__repr__`, `__post_init__`) + - Very simple pass-through properties + - **Already documented code** - If a class, method, or function already has a complete docstring that follows the project style, do not modify it. A docstring is complete if it has: + - A one-line summary + - Args section (if it has parameters) + - Returns section (if it returns something meaningful) + - Only add or improve documentation where it is missing or incomplete + +## Module Docstring Format + +```python +"""[One-line description of module purpose]. + +[Optional: Longer explanation of functionality, key classes, or use cases.] +""" +``` + +Example: +```python +"""Neuphonic text-to-speech service implementations. + +This module provides WebSocket and HTTP-based integrations with Neuphonic's +text-to-speech API for real-time audio synthesis. +""" +``` + +## Class Docstring Format + +```python +class ClassName: + """One-line summary describing what the class does. + + [Longer description explaining purpose, behavior, and key features. + Use action-oriented language.] + + [Optional: Event handlers, usage notes, or important caveats.] + """ +``` + +Example: +```python +class FrameProcessor(BaseObject): + """Base class for all frame processors in the pipeline. + + Frame processors are the building blocks of Pipecat pipelines, they can be + linked to form complex processing pipelines. They receive frames, process + them, and pass them to the next or previous processor in the chain. + + Event handlers available: + + - on_before_process_frame: Called before a frame is processed + - on_after_process_frame: Called after a frame is processed + + Example:: + + @processor.event_handler("on_before_process_frame") + async def on_before_process_frame(processor, frame): + ... + + @processor.event_handler("on_after_process_frame") + async def on_after_process_frame(processor, frame): + ... + """ +``` + +Note: When listing event handlers, do NOT use backticks. Include an `Example::` section (with double colon for Sphinx) showing the decorator pattern and function signature for each event. + +## Constructor (`__init__`) Format + +```python +def __init__(self, *, param1: Type, param2: Type = default, **kwargs): + """Initialize the [ClassName]. + + Args: + param1: Description of param1 and its purpose. + param2: Description of param2. Defaults to [default]. + **kwargs: Additional arguments passed to parent class. + """ +``` + +Example: +```python +def __init__( + self, + *, + api_key: str, + voice_id: Optional[str] = None, + sample_rate: Optional[int] = 22050, + **kwargs, +): + """Initialize the Neuphonic TTS service. + + Args: + api_key: Neuphonic API key for authentication. + voice_id: ID of the voice to use for synthesis. + sample_rate: Audio sample rate in Hz. Defaults to 22050. + **kwargs: Additional arguments passed to parent InterruptibleTTSService. + """ +``` + +## Method Docstring Format + +```python +async def method_name(self, param1: Type) -> ReturnType: + """One-line summary of what method does. + + [Longer description if behavior isn't obvious.] + + Args: + param1: Description of param1. + + Returns: + Description of return value. + + Raises: + ExceptionType: When this exception is raised. + """ +``` + +Example: +```python +async def put(self, item: Tuple[Frame, FrameDirection, FrameCallback]): + """Put an item into the priority queue. + + System frames (`SystemFrame`) have higher priority than any other + frames. If a non-frame item is provided it will have the highest priority. + + Args: + item: The item to enqueue. + """ +``` + +## Dataclass/Config Format + +```python +@dataclass +class ConfigName: + """One-line description of configuration. + + [Explanation of when/how to use this config.] + + Parameters: + field1: Description of field1. + field2: Description of field2. Defaults to [default]. + """ + + field1: Type + field2: Type = default_value +``` + +Example: +```python +@dataclass +class FrameProcessorSetup: + """Configuration parameters for frame processor initialization. + + Parameters: + clock: The clock instance for timing operations. + task_manager: The task manager for handling async operations. + observer: Optional observer for monitoring frame processing events. + """ + + clock: BaseClock + task_manager: BaseTaskManager + observer: Optional[BaseObserver] = None +``` + +## Enum Documentation Format + +```python +class EnumName(Enum): + """One-line description of the enum purpose. + + [Longer description of how the enum is used.] + + Parameters: + VALUE1: Description of VALUE1. + VALUE2: Description of VALUE2. + """ + + VALUE1 = 1 + VALUE2 = 2 +``` + +## Writing Style Guidelines + +- **Concise and professional** - No casual language or filler words +- **Action-oriented** - Start with verbs: "Processes...", "Manages...", "Converts..." +- **Purpose before implementation** - Explain WHY before HOW +- **Clear parameter descriptions** - Include type hints, defaults, and purpose +- **No redundant type info** - Type hints are in the signature, don't repeat in description +- **Use backticks for code references** - Wrap class names, method names, event names, parameter names, and code snippets in backticks + +Good: "Neuphonic API key for authentication." +Bad: "str: The API key (string) that is used for authenticating with Neuphonic." + +Good: "Triggers `on_speech_started` when the `VADAnalyzer` detects speech." +Bad: "Triggers on_speech_started when the VADAnalyzer detects speech." + +## Deprecation Notice Format + +When documenting deprecated code: + +```python +"""[Description]. + +.. deprecated:: X.X.X + `ClassName` is deprecated and will be removed in a future version. + Use `NewClassName` instead. +""" +``` + +## Checklist + +Before finishing, verify: + +- [ ] Module has a docstring at the top (after copyright header and imports) +- [ ] All public classes have docstrings +- [ ] All `__init__` methods document their parameters +- [ ] All public methods have docstrings with Args/Returns/Raises as needed +- [ ] Dataclasses use "Parameters:" section for field descriptions +- [ ] Enums document each value in "Parameters:" section +- [ ] Writing is concise and action-oriented +- [ ] No documentation added to private methods (starting with `_`) +- [ ] Existing complete docstrings were left unchanged diff --git a/.claude/skills/pr-description/SKILL.md b/.claude/skills/pr-description/SKILL.md new file mode 100644 index 000000000..666cf2bd1 --- /dev/null +++ b/.claude/skills/pr-description/SKILL.md @@ -0,0 +1,128 @@ +--- +name: pr-description +description: Update a GitHub PR description with a summary of changes +--- + +Update a GitHub pull request description based on the changes in the PR. + +## Arguments + +``` +/pr-description [--fixes ] +``` + +- `PR_NUMBER` (required): The pull request number to update +- `--fixes` (optional): Comma-separated issue numbers that this PR fixes (e.g., `--fixes 123,456`) + +Examples: +- `/pr-description 3534` +- `/pr-description 3534 --fixes 123` +- `/pr-description 3534 --fixes 123,456,789` + +## Instructions + +1. First, gather information about the PR: + - Use GitHub plugin to get PR details (title, current description, base branch) + - Use local git to get commits: `git log main..HEAD --oneline` + - Use local git to get the diff: `git diff main..HEAD` + - Parse any `--fixes` argument for issue numbers + +2. Check the existing PR description: + - If it already has a complete, accurate description that reflects the changes, do nothing + - If it's missing sections, incomplete, or outdated compared to the actual changes, proceed to update + - If it only has the template placeholder text, generate a full description + +3. Analyze the changes: + - Understand the purpose of each commit + - Identify any breaking changes (API changes, removed features, behavior changes) + - Look for new features, bug fixes, refactoring, or documentation changes + - Collect issue numbers from: + - The `--fixes` argument (if provided) + - Commit messages (patterns like "Fixes #123", "Closes #456", "Resolves #789") + +4. Generate or update the PR description with these sections: + +## PR Description Format + +### Summary (always include) + +Brief bullet points describing what changed and why. Focus on the *purpose* and *impact*, not implementation details. + +```markdown +## Summary + +- Added X to enable Y +- Fixed bug where Z would happen +- Refactored W for better maintainability +``` + +### Breaking Changes (include only if applicable) + +Document any changes that affect existing users or APIs. + +```markdown +## Breaking Changes + +- `ClassName.method()` now requires a `param` argument +- Removed deprecated `old_function()` - use `new_function()` instead +``` + +### Testing (include when non-obvious) + +How to verify the changes work. Skip for trivial changes. + +```markdown +## Testing + +- Run `uv run pytest tests/test_feature.py` to verify the fix +- Example usage: `uv run examples/new_feature.py` +``` + +### Fixes (include if issues are provided or found in commits) + +List issues this PR fixes. GitHub will automatically close these issues when the PR is merged. + +```markdown +## Fixes + +- Fixes #123 +- Fixes #456 +``` + +Note: Use "Fixes #X" format (not "Closes" or "Resolves") for consistency. Each issue should be on its own line with "Fixes" to ensure GitHub auto-closes them. + +## Guidelines + +- **Be concise** - Reviewers should understand the PR in 30 seconds +- **Focus on why** - The diff shows *what* changed, explain *why* +- **Skip empty sections** - Only include sections that have content +- **Use bullet points** - Easier to scan than paragraphs +- **Don't duplicate the diff** - Avoid listing every file or line changed + +## Example Output + +```markdown +## Summary + +- Added `/docstring` skill for documenting Python modules with Google-style docstrings +- Skill finds classes by name and handles conflicts when multiple matches exist +- Skips already-documented code to avoid unnecessary changes + +## Testing + +/docstring ClassName + +## Fixes + +- Fixes #123 +``` + +## Checklist + +Before updating the PR: + +- [ ] Verified existing description needs updating (not already complete) +- [ ] Summary accurately reflects the changes +- [ ] Breaking changes are clearly documented (if any) +- [ ] No unnecessary sections included +- [ ] Description is concise and scannable diff --git a/.claude/skills/pr-submit/SKILL.md b/.claude/skills/pr-submit/SKILL.md new file mode 100644 index 000000000..5724ddb6e --- /dev/null +++ b/.claude/skills/pr-submit/SKILL.md @@ -0,0 +1,28 @@ +--- +name: pr-submit +description: Create and submit a GitHub PR from the current branch +--- + +Submit the current changes as a GitHub pull request. + +## Instructions + +1. Check the current state of the repository: + - Run `git status` to see staged, unstaged, and untracked changes + - Run `git diff` to see current changes + - Run `git log --oneline -10` to see recent commits + +2. If there are uncommitted changes relevant to the PR: + - Ask the user if they want a specific prefix for the branch name (e.g., `alice/`, `fix/`, `feat/`) + - Create a new branch based on the current branch + - Commit the changes using multiple commits if the changes are unrelated + +3. Push the branch and create the PR: + - Push with `-u` flag to set upstream tracking + - Create the PR using `gh pr create` + +4. After the PR is created: + - Run `/changelog ` to generate changelog files, then commit and push them + - Run `/pr-description ` to update the PR description + +5. Return the PR URL to the user. diff --git a/README.md b/README.md index 058f23128..2221e807e 100644 --- a/README.md +++ b/README.md @@ -57,19 +57,13 @@ Love terminal applications? Check out [Tail](https://github.com/pipecat-ai/tail) ### 🤖 Claude Code Skills -Use [Pipecat Skills](https://github.com/pipecat-ai/skills) with [Claude Code](https://claude.ai/code) to scaffold projects, generate changelogs, deploy to Pipecat Cloud, and more. Install the marketplace with: +Use [Pipecat Skills](https://github.com/pipecat-ai/skills) with [Claude Code](https://claude.ai/code) to scaffold projects, deploy to Pipecat Cloud, and more. Install the marketplace with: ``` claude plugin marketplace add pipecat-ai/skills ``` -And install the plugins, for example: - -``` -claude plugin install pipecat-dev@pipecat-skills -``` - -there's more! +and install any of the available plugins. ### 📺️ Pipecat TV Channel @@ -179,6 +173,15 @@ You can get started with Pipecat running on your local machine, then move your a > **Note**: Some extras (local, gstreamer) require system dependencies. See documentation if you encounter build errors. +### Claude Code Skills + +Install development workflow skills for contributing to Pipecat with [Claude Code](https://claude.ai/code): + +``` +claude plugin marketplace add pipecat-ai/pipecat +claude plugin install pipecat-dev@pipecat-dev-skills +``` + ### Running tests To run all tests, from the root directory: From c09ae6ba6d3b27d4f3c90e022726fc97d42893a3 Mon Sep 17 00:00:00 2001 From: filipi87 Date: Wed, 25 Feb 2026 10:17:54 -0300 Subject: [PATCH 0630/1060] Added two new lifecycle callbacks to AudioContextTTSService: on_audio_context_interrupted() and on_audio_context_completed() --- src/pipecat/services/tts_service.py | 31 +++++++++++++++++++++++++++++ 1 file changed, 31 insertions(+) diff --git a/src/pipecat/services/tts_service.py b/src/pipecat/services/tts_service.py index 1b65521a1..e739a03d2 100644 --- a/src/pipecat/services/tts_service.py +++ b/src/pipecat/services/tts_service.py @@ -1190,6 +1190,7 @@ class AudioContextTTSService(WebsocketTTSService): async def _handle_interruption(self, frame: InterruptionFrame, direction: FrameDirection): await super()._handle_interruption(frame, direction) await self._stop_audio_context_task() + await self.on_audio_context_interrupted(context_id=self._context_id) self.reset_active_audio_context() self._create_audio_context_task() @@ -1218,6 +1219,7 @@ class AudioContextTTSService(WebsocketTTSService): # We just finished processing the context, so we can safely remove it. del self._contexts[context_id] + await self.on_audio_context_completed(context_id=context_id) self.reset_active_audio_context() # Append some silence between sentences. @@ -1254,6 +1256,35 @@ class AudioContextTTSService(WebsocketTTSService): logger.trace(f"{self} time out on audio context {context_id}") break + async def on_audio_context_interrupted(self, context_id: str): + """Called when an audio context is cancelled due to an interruption. + + Override this in a subclass to perform provider-specific cleanup (e.g. + sending a cancel/close message over the WebSocket) when the bot is + interrupted mid-speech. The audio context task has already been stopped + and the active context has **not** yet been reset when this is called, + so ``context_id`` reflects the context that was cut short. + + Args: + context_id: The ID of the audio context that was interrupted, or + ``None`` if no context was active at the time. + """ + pass + + async def on_audio_context_completed(self, context_id: str): + """Called after an audio context has finished playing all of its audio. + + Override this in a subclass to perform provider-specific cleanup (e.g. + sending a close-context message to free server-side resources) once an + audio context has been fully processed. The context entry has already + been removed from the internal context map, and the active context has + **not** yet been reset when this is called. + + Args: + context_id: The ID of the audio context that finished processing. + """ + pass + class AudioContextWordTTSService(AudioContextTTSService): """Deprecated. Use AudioContextTTSService with supports_word_timestamps=True instead. From d899f0af11958f6aa34bf9493589d385e942cbbb Mon Sep 17 00:00:00 2001 From: filipi87 Date: Wed, 25 Feb 2026 10:18:16 -0300 Subject: [PATCH 0631/1060] Refactored all AudioContextTTSService based providers to override the new callbacks instead of _handle_interruption(), making provider-specific cleanup cleaner and more explicit --- src/pipecat/services/asyncai/tts.py | 26 ++++++++++++++++------- src/pipecat/services/cartesia/tts.py | 18 ++++++++++------ src/pipecat/services/elevenlabs/tts.py | 28 +++++++++++++++++-------- src/pipecat/services/gradium/tts.py | 27 ++++++++++++------------ src/pipecat/services/inworld/tts.py | 29 +++++++++++--------------- src/pipecat/services/resembleai/tts.py | 21 ++++++++++--------- src/pipecat/services/rime/tts.py | 19 +++++++++++++---- 7 files changed, 101 insertions(+), 67 deletions(-) diff --git a/src/pipecat/services/asyncai/tts.py b/src/pipecat/services/asyncai/tts.py index d55062c4f..f1f73b7ff 100644 --- a/src/pipecat/services/asyncai/tts.py +++ b/src/pipecat/services/asyncai/tts.py @@ -10,7 +10,7 @@ import asyncio import base64 import json from dataclasses import dataclass, field -from typing import Any, AsyncGenerator, ClassVar, Dict, Mapping, Optional +from typing import Any, AsyncGenerator, Mapping, Optional import aiohttp from loguru import logger @@ -21,7 +21,6 @@ from pipecat.frames.frames import ( EndFrame, ErrorFrame, Frame, - InterruptionFrame, StartFrame, TTSAudioRawFrame, TTSStartedFrame, @@ -392,18 +391,29 @@ class AsyncAITTSService(AudioContextTTSService): logger.warning(f"{self} keepalive error: {e}") break - async def _handle_interruption(self, frame: InterruptionFrame, direction: FrameDirection): - """Handle interruption by closing the current context.""" - context_id = self.get_active_audio_context_id() - await super()._handle_interruption(frame, direction) - # Close the current context when interrupted without closing the websocket + async def _close_context(self, context_id: str): + # Async AI requires explicit context closure to free server-side resources, + # both on interruption and on normal completion. if context_id and self._websocket: try: await self._websocket.send( json.dumps({"context_id": context_id, "close_context": True, "transcript": ""}) ) except Exception as e: - logger.error(f"Error closing context on interruption: {e}") + logger.error(f"{self}: Error closing context {context_id}: {e}") + + async def on_audio_context_interrupted(self, context_id: str): + """Close the Async AI context when the bot is interrupted.""" + await self._close_context(context_id) + + async def on_audio_context_completed(self, context_id: str): + """Close the Async AI context after all audio has been played. + + Async AI does not send a server-side signal when a context is + exhausted, so Pipecat must explicitly close it with + ``close_context: True`` to free server-side resources. + """ + await self._close_context(context_id) @traced_tts async def run_tts(self, text: str, context_id: str) -> AsyncGenerator[Frame, None]: diff --git a/src/pipecat/services/cartesia/tts.py b/src/pipecat/services/cartesia/tts.py index f31cc2421..f45e7c54f 100644 --- a/src/pipecat/services/cartesia/tts.py +++ b/src/pipecat/services/cartesia/tts.py @@ -11,7 +11,7 @@ import json import warnings from dataclasses import dataclass, field from enum import Enum -from typing import Any, AsyncGenerator, ClassVar, Dict, List, Literal, Mapping, Optional +from typing import Any, AsyncGenerator, List, Literal, Mapping, Optional from loguru import logger from pydantic import BaseModel, Field @@ -21,13 +21,11 @@ from pipecat.frames.frames import ( EndFrame, ErrorFrame, Frame, - InterruptionFrame, StartFrame, TTSAudioRawFrame, TTSStartedFrame, TTSStoppedFrame, ) -from pipecat.processors.frame_processor import FrameDirection from pipecat.services.settings import NOT_GIVEN, TTSSettings, _NotGiven from pipecat.services.tts_service import AudioContextTTSService, TTSService from pipecat.transcriptions.language import Language, resolve_language @@ -563,14 +561,22 @@ class CartesiaTTSService(AudioContextTTSService): return self._websocket raise Exception("Websocket not connected") - async def _handle_interruption(self, frame: InterruptionFrame, direction: FrameDirection): - context_id = self.get_active_audio_context_id() - await super()._handle_interruption(frame, direction) + async def on_audio_context_interrupted(self, context_id: str): + """Cancel the active Cartesia context when the bot is interrupted.""" await self.stop_all_metrics() if context_id: cancel_msg = json.dumps({"context_id": context_id, "cancel": True}) await self._get_websocket().send(cancel_msg) + async def on_audio_context_completed(self, context_id: str): + """Close the Cartesia context after all audio has been played. + + No close message is needed: the server already considers the context + done once it has sent its ``done`` message, which is handled in + ``_process_messages``. + """ + pass + async def flush_audio(self): """Flush any pending audio and finalize the current context.""" context_id = self.get_active_audio_context_id() diff --git a/src/pipecat/services/elevenlabs/tts.py b/src/pipecat/services/elevenlabs/tts.py index 20d46481d..25e1aa5dd 100644 --- a/src/pipecat/services/elevenlabs/tts.py +++ b/src/pipecat/services/elevenlabs/tts.py @@ -666,14 +666,11 @@ class ElevenLabsTTSService(AudioContextTTSService): return self._websocket raise Exception("Websocket not connected") - async def _handle_interruption(self, frame: InterruptionFrame, direction: FrameDirection): - """Handle interruption by closing the current context.""" - # Close the current context when interrupted without closing the websocket - context_id = self.get_active_audio_context_id() - await super()._handle_interruption(frame, direction) - + async def _close_context(self, context_id: str): + # ElevenLabs requires that Pipecat explicitly closes contexts to free + # server-side resources, both on interruption and on normal completion. if context_id and self._websocket: - logger.trace(f"Closing context {context_id} due to interruption") + logger.trace(f"{self}: Closing context {context_id}") try: # ElevenLabs requires that Pipecat manages the contexts and closes them # when they're not longer in use. Since an InterruptionFrame is pushed @@ -686,8 +683,21 @@ class ElevenLabsTTSService(AudioContextTTSService): ) except Exception as e: await self.push_error(error_msg=f"Unknown error occurred: {e}", exception=e) - self._partial_word = "" - self._partial_word_start_time = 0.0 + self._partial_word = "" + self._partial_word_start_time = 0.0 + + async def on_audio_context_interrupted(self, context_id: str): + """Close the ElevenLabs context when the bot is interrupted.""" + await self._close_context(context_id) + + async def on_audio_context_completed(self, context_id: str): + """Close the ElevenLabs context after all audio has been played. + + ElevenLabs does not send a server-side signal when a context is + exhausted, so Pipecat must explicitly close it with + ``close_context: True`` to free server-side resources. + """ + await self._close_context(context_id) async def _receive_messages(self): """Handle incoming WebSocket messages from ElevenLabs.""" diff --git a/src/pipecat/services/gradium/tts.py b/src/pipecat/services/gradium/tts.py index 703289706..ee6e6821e 100644 --- a/src/pipecat/services/gradium/tts.py +++ b/src/pipecat/services/gradium/tts.py @@ -17,13 +17,11 @@ from pipecat.frames.frames import ( EndFrame, ErrorFrame, Frame, - InterruptionFrame, StartFrame, TTSAudioRawFrame, TTSStartedFrame, TTSStoppedFrame, ) -from pipecat.processors.frame_processor import FrameDirection from pipecat.services.settings import NOT_GIVEN, TTSSettings, _NotGiven from pipecat.services.tts_service import AudioContextTTSService from pipecat.utils.tracing.service_decorators import traced_tts @@ -265,21 +263,24 @@ class GradiumTTSService(AudioContextTTSService): except Exception as e: logger.error(f"{self} exception: {e}") - async def _handle_interruption(self, frame: InterruptionFrame, direction: FrameDirection): - """Handle interruption by resetting context state. + async def on_audio_context_interrupted(self, context_id: str): + """Called when an audio context is cancelled due to an interruption. - The parent AudioContextTTSService._handle_interruption() cancels the audio context - task and creates a new one. We reset _context_id so the next run_tts() creates a - fresh context. No websocket reconnection needed — audio from the old client_req_id - will be silently dropped since the audio context no longer exists. - - Args: - frame: The interruption frame. - direction: The direction of the frame. + No WebSocket message is needed — audio from the interrupted + ``client_req_id`` will be silently dropped by the base class once the + audio context no longer exists. """ - await super()._handle_interruption(frame, direction) await self.stop_all_metrics() + async def on_audio_context_completed(self, context_id: str): + """Called after an audio context has finished playing all of its audio. + + No close message is needed: Gradium signals completion with an + ``end_of_stream`` message (handled in ``_receive_messages``), after + which the server-side context is already closed. + """ + pass + async def _receive_messages(self): """Process incoming websocket messages, demultiplexing by client_req_id.""" # TODO(laurent): This should not be necessary as it should happen when diff --git a/src/pipecat/services/inworld/tts.py b/src/pipecat/services/inworld/tts.py index 2f35dc27c..22bdf22ff 100644 --- a/src/pipecat/services/inworld/tts.py +++ b/src/pipecat/services/inworld/tts.py @@ -681,28 +681,23 @@ class InworldTTSService(AudioContextTTSService): return word_times - async def _handle_interruption(self, frame: InterruptionFrame, direction: FrameDirection): - """Handle an interruption from the Inworld WebSocket TTS service. - - Args: - frame: The interruption frame. - direction: The direction of the interruption. - """ - old_context_id = self.get_active_audio_context_id() - logger.trace(f"{self}: Handling interruption, old context: {old_context_id}") - - await super()._handle_interruption(frame, direction) - - if old_context_id and self._websocket: - logger.trace(f"{self}: Closing context {old_context_id} due to interruption") + async def _close_context(self, context_id: str): + if context_id and self._websocket: + logger.info(f"{self}: Closing context {context_id} due to interruption or completion") try: - await self._send_close_context(old_context_id) + await self._send_close_context(context_id) except Exception as e: await self.push_error(error_msg=f"Unknown error occurred: {e}", exception=e) - self._cumulative_time = 0.0 self._generation_end_time = 0.0 - logger.trace(f"{self}: Interruption handled, context reset to None") + + async def on_audio_context_interrupted(self, context_id: str): + """Callback invoked when an audio context has been interrupted.""" + await self._close_context(context_id) + + async def on_audio_context_completed(self, context_id: str): + """Callback invoked when an audio context has been completed.""" + await self._close_context(context_id) def _get_websocket(self): """Get the websocket for the Inworld WebSocket TTS service. diff --git a/src/pipecat/services/resembleai/tts.py b/src/pipecat/services/resembleai/tts.py index 026d29d3f..c2ac758a7 100644 --- a/src/pipecat/services/resembleai/tts.py +++ b/src/pipecat/services/resembleai/tts.py @@ -18,13 +18,11 @@ from pipecat.frames.frames import ( EndFrame, ErrorFrame, Frame, - InterruptionFrame, StartFrame, TTSAudioRawFrame, TTSStartedFrame, TTSStoppedFrame, ) -from pipecat.processors.frame_processor import FrameDirection from pipecat.services.settings import NOT_GIVEN, TTSSettings, _NotGiven from pipecat.services.tts_service import AudioContextTTSService from pipecat.utils.tracing.service_decorators import traced_tts @@ -247,16 +245,19 @@ class ResembleAITTSService(AudioContextTTSService): return self._websocket raise Exception("Websocket not connected") - async def _handle_interruption(self, frame: InterruptionFrame, direction: FrameDirection): - """Handle interruption by stopping current synthesis. - - Args: - frame: The interruption frame. - direction: The direction of frame processing. - """ - await super()._handle_interruption(frame, direction) + async def on_audio_context_interrupted(self, context_id: str): + """Stop metrics when the bot is interrupted.""" await self.stop_all_metrics() + async def on_audio_context_completed(self, context_id: str): + """Stop metrics after the Resemble AI context finishes playing. + + No close message is needed: Resemble AI signals completion with an + ``audio_end`` message (handled in ``_process_messages``), after which + the server-side context is already closed. + """ + pass + async def flush_audio(self): """Flush any pending audio and finalize the current context.""" logger.trace(f"{self}: flushing audio") diff --git a/src/pipecat/services/rime/tts.py b/src/pipecat/services/rime/tts.py index 248c84008..83c2305d5 100644 --- a/src/pipecat/services/rime/tts.py +++ b/src/pipecat/services/rime/tts.py @@ -458,14 +458,25 @@ class RimeTTSService(AudioContextTTSService): return self._websocket raise Exception("Websocket not connected") - async def _handle_interruption(self, frame: InterruptionFrame, direction: FrameDirection): - """Handle interruption by clearing current context.""" - context_id = self.get_active_audio_context_id() - await super()._handle_interruption(frame, direction) + async def _close_context(self, context_id: str): + """Clear the Rime speech queue and stop metrics.""" await self.stop_all_metrics() if context_id: await self._get_websocket().send(json.dumps(self._build_clear_msg())) + async def on_audio_context_interrupted(self, context_id: str): + """Clear the Rime speech queue and stop metrics when the bot is interrupted.""" + await self._close_context(context_id) + + async def on_audio_context_completed(self, context_id: str): + """Clear server-side state and stop metrics after the Rime context finishes playing. + + Rime does not send a server-side completion signal (e.g. ``done`` / ``end_of_stream`` / + ``audio_end``), so we explicitly send a ``clear`` message to clean up + any residual server-side state once all audio has been delivered. + """ + await self._close_context(context_id) + def _calculate_word_times(self, words: list, starts: list, ends: list) -> list: """Calculate word timing pairs with proper spacing and punctuation. From 751b1b8100e70be0ea2b72e53d9bb7714f35d25b Mon Sep 17 00:00:00 2001 From: filipi87 Date: Wed, 25 Feb 2026 10:18:25 -0300 Subject: [PATCH 0632/1060] Adding the changelog entries for the tts fixes. --- changelog/3814.added.md | 1 + changelog/3814.fixed.md | 1 + 2 files changed, 2 insertions(+) create mode 100644 changelog/3814.added.md create mode 100644 changelog/3814.fixed.md diff --git a/changelog/3814.added.md b/changelog/3814.added.md new file mode 100644 index 000000000..b6b2ebbf8 --- /dev/null +++ b/changelog/3814.added.md @@ -0,0 +1 @@ +- Added `on_audio_context_interrupted()` and `on_audio_context_completed()` callbacks to `AudioContextTTSService`. Subclasses can override these to perform provider-specific cleanup instead of overriding `_handle_interruption()`. diff --git a/changelog/3814.fixed.md b/changelog/3814.fixed.md new file mode 100644 index 000000000..ecd4871f6 --- /dev/null +++ b/changelog/3814.fixed.md @@ -0,0 +1 @@ +- Fixed an issue where `AudioContextTTSService`-based providers (AsyncAI, ElevenLabs, Inworld, Rime) did not close or clean up their server-side audio contexts after normal speech completion, only on interruption. From 73ee4da7d415d741f8318fabd9139548703b1d64 Mon Sep 17 00:00:00 2001 From: Mark Backman Date: Tue, 24 Feb 2026 10:16:35 -0500 Subject: [PATCH 0633/1060] Add Krisp API key support for new SDK licensing requirement The Krisp VIVA SDK v1.8.0 requires a license key in globalInit(). Add api_key parameter to KrispVivaSDKManager, KrispVivaTurn, and KrispVivaFilter with fallback to KRISP_API_KEY env var. Maintain backwards compatibility with older SDK versions by catching TypeError and falling back to the old 3-arg signature. --- changelog/3809.added.md | 1 + changelog/3809.changed.md | 2 +- env.example | 1 + .../07p-interruptible-krisp-viva.py | 9 ++++--- .../audio/filters/krisp_viva_filter.py | 12 +++++++-- src/pipecat/audio/krisp_instance.py | 26 +++++++++++++++++-- src/pipecat/audio/turn/krisp_viva_turn.py | 5 +++- 7 files changed, 47 insertions(+), 9 deletions(-) create mode 100644 changelog/3809.added.md diff --git a/changelog/3809.added.md b/changelog/3809.added.md new file mode 100644 index 000000000..1bc3a9787 --- /dev/null +++ b/changelog/3809.added.md @@ -0,0 +1 @@ +- Added `api_key` parameter to `KrispVivaSDKManager`, `KrispVivaTurn`, and `KrispVivaFilter` for Krisp SDK v1.8.0 licensing. Falls back to `KRISP_API_KEY` environment variable. Backwards compatible with older SDK versions. diff --git a/changelog/3809.changed.md b/changelog/3809.changed.md index 43aca00f3..ef1c5c5a1 100644 --- a/changelog/3809.changed.md +++ b/changelog/3809.changed.md @@ -1 +1 @@ -- Added debug logging to `KrispVivaTurn.analyze_end_of_turn()` to log turn state and probability at decision time. +- Added `api_key` parameter to `KrispVivaSDKManager`, `KrispVivaTurn`, and `KrispVivaFilter` for Krisp SDK v1.6.1+ licensing. Falls back to `KRISP_VIVA_API_KEY` environment variable. \ No newline at end of file diff --git a/env.example b/env.example index bc14ea0bf..2b850dd19 100644 --- a/env.example +++ b/env.example @@ -104,6 +104,7 @@ INWORLD_API_KEY=... KRISP_MODEL_PATH=... # Krisp Viva +KRISP_VIVA_API_KEY=... KRISP_VIVA_FILTER_MODEL_PATH=... KRISP_VIVA_TURN_MODEL_PATH=... diff --git a/examples/foundational/07p-interruptible-krisp-viva.py b/examples/foundational/07p-interruptible-krisp-viva.py index 4da42e201..62f2a1bc1 100644 --- a/examples/foundational/07p-interruptible-krisp-viva.py +++ b/examples/foundational/07p-interruptible-krisp-viva.py @@ -54,21 +54,24 @@ load_dotenv(override=True) # We use lambdas to defer transport parameter creation until the transport # type is selected at runtime. + +krisp_viva_filter = KrispVivaFilter() + transport_params = { "daily": lambda: DailyParams( audio_in_enabled=True, audio_out_enabled=True, - audio_in_filter=KrispVivaFilter(), + audio_in_filter=krisp_viva_filter, ), "twilio": lambda: FastAPIWebsocketParams( audio_in_enabled=True, audio_out_enabled=True, - audio_in_filter=KrispVivaFilter(), + audio_in_filter=krisp_viva_filter, ), "webrtc": lambda: TransportParams( audio_in_enabled=True, audio_out_enabled=True, - audio_in_filter=KrispVivaFilter(), + audio_in_filter=krisp_viva_filter, ), } diff --git a/src/pipecat/audio/filters/krisp_viva_filter.py b/src/pipecat/audio/filters/krisp_viva_filter.py index ea5bfb8de..1e2f6c81b 100644 --- a/src/pipecat/audio/filters/krisp_viva_filter.py +++ b/src/pipecat/audio/filters/krisp_viva_filter.py @@ -39,7 +39,11 @@ class KrispVivaFilter(BaseAudioFilter): """ def __init__( - self, model_path: str = None, frame_duration: int = 10, noise_suppression_level: int = 100 + self, + model_path: str = None, + frame_duration: int = 10, + noise_suppression_level: int = 100, + api_key: str = "", ) -> None: """Initialize the Krisp noise reduction filter. @@ -48,6 +52,8 @@ class KrispVivaFilter(BaseAudioFilter): If None, uses KRISP_VIVA_FILTER_MODEL_PATH environment variable. frame_duration: Frame duration in milliseconds. noise_suppression_level: Noise suppression level. + api_key: Krisp SDK API key. If empty, falls back to + the KRISP_VIVA_API_KEY environment variable. Raises: ValueError: If model_path is not provided and KRISP_VIVA_FILTER_MODEL_PATH is not set. @@ -57,6 +63,8 @@ class KrispVivaFilter(BaseAudioFilter): """ super().__init__() + self._api_key = api_key + try: # Set model path, checking environment if not specified if model_path: @@ -132,7 +140,7 @@ class KrispVivaFilter(BaseAudioFilter): """ try: # Acquire SDK reference (will initialize on first call) - KrispVivaSDKManager.acquire() + KrispVivaSDKManager.acquire(api_key=self._api_key) self._session = self._create_session(sample_rate, self._frame_duration_ms) except Exception as e: logger.error(f"Failed to start Krisp session: {e}", exc_info=True) diff --git a/src/pipecat/audio/krisp_instance.py b/src/pipecat/audio/krisp_instance.py index fae2c691e..5ebfd24cc 100644 --- a/src/pipecat/audio/krisp_instance.py +++ b/src/pipecat/audio/krisp_instance.py @@ -7,6 +7,7 @@ """Krisp Instance manager for pipecat audio.""" import atexit +import os from threading import Lock from loguru import logger @@ -88,17 +89,26 @@ class KrispVivaSDKManager: _lock = Lock() _reference_count = 0 + @staticmethod + def _license_callback(error, error_message): + """Callback for Krisp SDK licensing errors.""" + logger.error(f"Krisp licensing error: {error} - {error_message}") + @staticmethod def _log_callback(log_message, log_level): """Thread-safe callback for Krisp SDK logging.""" logger.info(f"[{log_level}] {log_message}") @classmethod - def acquire(cls): + def acquire(cls, api_key: str = ""): """Acquire a reference to the SDK (initializes if needed). Call this when creating a filter instance. + Args: + api_key: Krisp SDK API key. If empty, falls back to the + KRISP_VIVA_API_KEY environment variable. + Raises: Exception: If SDK initialization fails (propagated from krisp_audio) """ @@ -106,7 +116,19 @@ class KrispVivaSDKManager: # Initialize SDK on first acquire if cls._reference_count == 0: try: - krisp_audio.globalInit("", cls._log_callback, krisp_audio.LogLevel.Off) + key = api_key or os.environ.get("KRISP_VIVA_API_KEY", "") + try: + # New SDK signature (requires license key) + krisp_audio.globalInit( + "", + key, + cls._license_callback, + cls._log_callback, + krisp_audio.LogLevel.Off, + ) + except TypeError: + # Old SDK signature (no license key) + krisp_audio.globalInit("", cls._log_callback, krisp_audio.LogLevel.Off) cls._initialized = True diff --git a/src/pipecat/audio/turn/krisp_viva_turn.py b/src/pipecat/audio/turn/krisp_viva_turn.py index 59f8aada8..f15c456c2 100644 --- a/src/pipecat/audio/turn/krisp_viva_turn.py +++ b/src/pipecat/audio/turn/krisp_viva_turn.py @@ -63,6 +63,7 @@ class KrispVivaTurn(BaseTurnAnalyzer): model_path: Optional[str] = None, sample_rate: Optional[int] = None, params: Optional[KrispTurnParams] = None, + api_key: str = "", ) -> None: """Initialize the Krisp turn analyzer. @@ -72,6 +73,8 @@ class KrispVivaTurn(BaseTurnAnalyzer): sample_rate: Optional initial sample rate for audio processing. If provided, this will be used as the fixed sample rate. params: Configuration parameters for turn analysis behavior. + api_key: Krisp SDK API key. If empty, falls back to + the KRISP_VIVA_API_KEY environment variable. Raises: ValueError: If model_path is not provided and KRISP_VIVA_TURN_MODEL_PATH is not set. @@ -83,7 +86,7 @@ class KrispVivaTurn(BaseTurnAnalyzer): # Acquire SDK reference (will initialize on first call) try: - KrispVivaSDKManager.acquire() + KrispVivaSDKManager.acquire(api_key=api_key) self._sdk_acquired = True except Exception as e: self._sdk_acquired = False From 0ca8c850fb1cb6db73b5dd65a0b990f4aa203edd Mon Sep 17 00:00:00 2001 From: Mark Backman Date: Tue, 24 Feb 2026 17:42:18 -0500 Subject: [PATCH 0634/1060] Add TurnMetricsData and e2e processing time for KrispVivaTurn Introduce a generic TurnMetricsData class for turn detection metrics, replacing the service-specific SmartTurnMetricsData (now deprecated). Add end-to-end processing time measurement to KrispVivaTurn, tracking the interval from VAD speech-to-silence transition to model threshold crossing. Consume metrics in the strategy _handle_input_audio path so they are pushed immediately when fresh. --- changelog/3809.added.md | 2 +- changelog/3809.changed.md | 2 +- changelog/3809.deprecated.md | 1 + .../07p-interruptible-krisp-viva.py | 3 ++ examples/foundational/38b-smart-turn-local.py | 13 +++---- src/pipecat/audio/turn/krisp_viva_turn.py | 37 +++++++++++++++---- .../audio/turn/smart_turn/base_smart_turn.py | 13 +------ src/pipecat/metrics/metrics.py | 26 +++++++++---- .../observers/loggers/metrics_log_observer.py | 33 +++++++++++------ .../turn_analyzer_user_turn_stop_strategy.py | 10 +++-- 10 files changed, 92 insertions(+), 48 deletions(-) create mode 100644 changelog/3809.deprecated.md diff --git a/changelog/3809.added.md b/changelog/3809.added.md index 1bc3a9787..99047dc76 100644 --- a/changelog/3809.added.md +++ b/changelog/3809.added.md @@ -1 +1 @@ -- Added `api_key` parameter to `KrispVivaSDKManager`, `KrispVivaTurn`, and `KrispVivaFilter` for Krisp SDK v1.8.0 licensing. Falls back to `KRISP_API_KEY` environment variable. Backwards compatible with older SDK versions. +- Added `TurnMetricsData` as a generic metrics class for turn detection, with e2e processing time measurement. `KrispVivaTurn` now emits `TurnMetricsData` with `e2e_processing_time_ms` tracking the interval from VAD speech-to-silence transition to turn completion. diff --git a/changelog/3809.changed.md b/changelog/3809.changed.md index ef1c5c5a1..479eaf6ed 100644 --- a/changelog/3809.changed.md +++ b/changelog/3809.changed.md @@ -1 +1 @@ -- Added `api_key` parameter to `KrispVivaSDKManager`, `KrispVivaTurn`, and `KrispVivaFilter` for Krisp SDK v1.6.1+ licensing. Falls back to `KRISP_VIVA_API_KEY` environment variable. \ No newline at end of file +- Added `api_key` parameter to `KrispVivaSDKManager`, `KrispVivaTurn`, and `KrispVivaFilter` for Krisp SDK v1.6.1+ licensing. Falls back to `KRISP_VIVA_API_KEY` environment variable. diff --git a/changelog/3809.deprecated.md b/changelog/3809.deprecated.md new file mode 100644 index 000000000..f1498ec0b --- /dev/null +++ b/changelog/3809.deprecated.md @@ -0,0 +1 @@ +- Deprecated `SmartTurnMetricsData` in favor of `TurnMetricsData`. `BaseSmartTurn` now emits `TurnMetricsData` directly. diff --git a/examples/foundational/07p-interruptible-krisp-viva.py b/examples/foundational/07p-interruptible-krisp-viva.py index 62f2a1bc1..24929a825 100644 --- a/examples/foundational/07p-interruptible-krisp-viva.py +++ b/examples/foundational/07p-interruptible-krisp-viva.py @@ -31,6 +31,8 @@ from pipecat.audio.filters.krisp_viva_filter import KrispVivaFilter from pipecat.audio.turn.krisp_viva_turn import KrispVivaTurn from pipecat.audio.vad.silero import SileroVADAnalyzer from pipecat.frames.frames import LLMRunFrame +from pipecat.metrics.metrics import TurnMetricsData +from pipecat.observers.loggers.metrics_log_observer import MetricsLogObserver from pipecat.pipeline.pipeline import Pipeline from pipecat.pipeline.runner import PipelineRunner from pipecat.pipeline.task import PipelineParams, PipelineTask @@ -124,6 +126,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): enable_usage_metrics=True, ), idle_timeout_secs=runner_args.pipeline_idle_timeout_secs, + observers=[MetricsLogObserver(include_metrics={TurnMetricsData})], ) @transport.event_handler("on_client_connected") diff --git a/examples/foundational/38b-smart-turn-local.py b/examples/foundational/38b-smart-turn-local.py index 2872a0e76..dc62010fb 100644 --- a/examples/foundational/38b-smart-turn-local.py +++ b/examples/foundational/38b-smart-turn-local.py @@ -12,6 +12,8 @@ from loguru import logger from pipecat.audio.vad.silero import SileroVADAnalyzer from pipecat.frames.frames import LLMRunFrame +from pipecat.metrics.metrics import TurnMetricsData +from pipecat.observers.loggers.metrics_log_observer import MetricsLogObserver from pipecat.pipeline.pipeline import Pipeline from pipecat.pipeline.runner import PipelineRunner from pipecat.pipeline.task import PipelineParams, PipelineTask @@ -77,7 +79,6 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): pipeline = Pipeline( [ transport.input(), # Transport user input - rtvi, stt, user_aggregator, # User responses llm, # LLM @@ -94,17 +95,15 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): enable_usage_metrics=True, ), idle_timeout_secs=runner_args.pipeline_idle_timeout_secs, + observers=[MetricsLogObserver(include_metrics={TurnMetricsData})], ) - @task.rtvi.event_handler("on_client_ready") - async def on_client_ready(rtvi): - # Kick off the conversation - messages.append({"role": "system", "content": "Please introduce yourself to the user."}) - await task.queue_frames([LLMRunFrame()]) - @transport.event_handler("on_client_connected") async def on_client_connected(transport, client): logger.info(f"Client connected") + # Kick off the conversation + messages.append({"role": "system", "content": "Please introduce yourself to the user."}) + await task.queue_frames([LLMRunFrame()]) @transport.event_handler("on_client_disconnected") async def on_client_disconnected(transport, client): diff --git a/src/pipecat/audio/turn/krisp_viva_turn.py b/src/pipecat/audio/turn/krisp_viva_turn.py index f15c456c2..3aa540491 100644 --- a/src/pipecat/audio/turn/krisp_viva_turn.py +++ b/src/pipecat/audio/turn/krisp_viva_turn.py @@ -15,6 +15,7 @@ passed directly to the constructor. """ import os +import time from typing import Optional, Tuple import numpy as np @@ -26,7 +27,7 @@ from pipecat.audio.krisp_instance import ( int_to_krisp_sample_rate, ) from pipecat.audio.turn.base_turn_analyzer import BaseTurnAnalyzer, BaseTurnParams, EndOfTurnState -from pipecat.metrics.metrics import MetricsData +from pipecat.metrics.metrics import MetricsData, TurnMetricsData try: import krisp_audio @@ -118,6 +119,9 @@ class KrispVivaTurn(BaseTurnAnalyzer): self._last_probability = None self._frame_probabilities = [] self._last_state = EndOfTurnState.INCOMPLETE + self._speech_stopped_time: Optional[float] = None + self._e2e_processing_time_ms: Optional[float] = None + self._last_metrics: Optional[TurnMetricsData] = None # Create session with provided sample rate or default to 16000 Hz # This preloads the model to improve latency when set_sample_rate is called later @@ -291,7 +295,14 @@ class KrispVivaTurn(BaseTurnAnalyzer): # Track speech start time if not self._speech_triggered: logger.trace("Speech detected, turn analysis started") + self._e2e_processing_time_ms = None self._speech_triggered = True + # Reset speech stopped time when speech resumes + self._speech_stopped_time = None + else: + # Record the moment speech transitions to non-speech + if self._speech_triggered and self._speech_stopped_time is None: + self._speech_stopped_time = time.perf_counter() # Note: We don't immediately mark as complete on silence detection. # Instead, we wait for the model's probability check below to confirm # end-of-turn based on the threshold. @@ -311,6 +322,18 @@ class KrispVivaTurn(BaseTurnAnalyzer): # Only mark as complete if we've detected speech and the model # confirms with sufficient confidence if self._speech_triggered and prob >= self._params.threshold: + # Calculate e2e processing time: time from speech stop to threshold crossing + if self._speech_stopped_time is not None: + self._e2e_processing_time_ms = ( + time.perf_counter() - self._speech_stopped_time + ) * 1000 + self._last_metrics = TurnMetricsData( + processor="KrispVivaTurn", + is_complete=True, + probability=prob, + e2e_processing_time_ms=self._e2e_processing_time_ms, + ) + logger.debug(f"Krisp turn complete") state = EndOfTurnState.COMPLETE self.clear() break @@ -332,15 +355,15 @@ class KrispVivaTurn(BaseTurnAnalyzer): Tuple containing the end-of-turn state and optional metrics data. Returns the last state determined by append_audio(). """ - # For real-time processing, the state is determined in append_audio - # Return the last state that was computed - logger.debug( - f"Krisp turn analysis: state={self._last_state}, probability={self._last_probability}" - ) - return self._last_state, None + # For real-time processing, the state is determined in append_audio. + # Consume metrics so they aren't pushed twice. + metrics = self._last_metrics + self._last_metrics = None + return self._last_state, metrics def clear(self): """Reset the turn analyzer to its initial state.""" self._speech_triggered = False self._audio_buffer.clear() self._last_state = EndOfTurnState.INCOMPLETE + self._speech_stopped_time = None diff --git a/src/pipecat/audio/turn/smart_turn/base_smart_turn.py b/src/pipecat/audio/turn/smart_turn/base_smart_turn.py index 66b45a8f6..fa652d884 100644 --- a/src/pipecat/audio/turn/smart_turn/base_smart_turn.py +++ b/src/pipecat/audio/turn/smart_turn/base_smart_turn.py @@ -21,7 +21,7 @@ import numpy as np from loguru import logger from pipecat.audio.turn.base_turn_analyzer import BaseTurnAnalyzer, BaseTurnParams, EndOfTurnState -from pipecat.metrics.metrics import MetricsData, SmartTurnMetricsData +from pipecat.metrics.metrics import MetricsData, TurnMetricsData # Default timing parameters STOP_SECS = 3 @@ -222,18 +222,11 @@ class BaseSmartTurn(BaseTurnAnalyzer): # Calculate processing time e2e_processing_time_ms = (end_time - start_time) * 1000 - # Extract metrics from the nested structure - metrics = result.get("metrics", {}) - inference_time = metrics.get("inference_time", 0) - total_time = metrics.get("total_time", 0) - # Prepare the result data - result_data = SmartTurnMetricsData( + result_data = TurnMetricsData( processor="BaseSmartTurn", is_complete=result["prediction"] == 1, probability=result["probability"], - inference_time_ms=inference_time * 1000, - server_total_time_ms=total_time * 1000, e2e_processing_time_ms=e2e_processing_time_ms, ) @@ -241,8 +234,6 @@ class BaseSmartTurn(BaseTurnAnalyzer): f"Prediction: {'Complete' if result_data.is_complete else 'Incomplete'}" ) logger.trace(f"Probability of complete: {result_data.probability:.4f}") - logger.trace(f"Inference time: {result_data.inference_time_ms:.2f}ms") - logger.trace(f"Server total time: {result_data.server_total_time_ms:.2f}ms") logger.trace(f"E2E processing time: {result_data.e2e_processing_time_ms:.2f}ms") except SmartTurnTimeoutException: logger.debug( diff --git a/src/pipecat/metrics/metrics.py b/src/pipecat/metrics/metrics.py index 98903483a..ccf30227a 100644 --- a/src/pipecat/metrics/metrics.py +++ b/src/pipecat/metrics/metrics.py @@ -87,19 +87,31 @@ class TTSUsageMetricsData(MetricsData): value: int -class SmartTurnMetricsData(MetricsData): - """Metrics data for smart turn predictions. +class TurnMetricsData(MetricsData): + """Metrics data for turn detection predictions. Parameters: is_complete: Whether the turn is predicted to be complete. probability: Confidence probability of the turn completion prediction. - inference_time_ms: Time taken for inference in milliseconds. - server_total_time_ms: Total server processing time in milliseconds. - e2e_processing_time_ms: End-to-end processing time in milliseconds. + e2e_processing_time_ms: End-to-end processing time in milliseconds, + measured from VAD speech-to-silence transition to turn completion. """ is_complete: bool probability: float - inference_time_ms: float - server_total_time_ms: float e2e_processing_time_ms: float + + +class SmartTurnMetricsData(TurnMetricsData): + """Metrics data for smart turn predictions. + + .. deprecated:: 0.0.104 + Use :class:`TurnMetricsData` instead. This class will be removed in a future version. + + Parameters: + inference_time_ms: Time taken for inference in milliseconds. + server_total_time_ms: Total server processing time in milliseconds. + """ + + inference_time_ms: float = 0.0 + server_total_time_ms: float = 0.0 diff --git a/src/pipecat/observers/loggers/metrics_log_observer.py b/src/pipecat/observers/loggers/metrics_log_observer.py index a36ab510e..7f4c1635c 100644 --- a/src/pipecat/observers/loggers/metrics_log_observer.py +++ b/src/pipecat/observers/loggers/metrics_log_observer.py @@ -24,6 +24,7 @@ from pipecat.metrics.metrics import ( SmartTurnMetricsData, TTFBMetricsData, TTSUsageMetricsData, + TurnMetricsData, ) from pipecat.observers.base_observer import BaseObserver, FramePushed @@ -37,7 +38,7 @@ class MetricsLogObserver(BaseObserver): - ProcessingMetricsData (General processing time) - LLMUsageMetricsData (Token usage statistics) - TTSUsageMetricsData (Text-to-Speech character counts) - - SmartTurnMetricsData (Turn prediction metrics) + - TurnMetricsData (Turn prediction metrics) This allows developers to track performance metrics, token usage, and other statistics throughout the pipeline. @@ -70,6 +71,17 @@ class MetricsLogObserver(BaseObserver): **kwargs: Additional arguments passed to parent class. """ super().__init__(**kwargs) + # Normalize deprecated types in include_metrics + if include_metrics and SmartTurnMetricsData in include_metrics: + import warnings + + warnings.warn( + "SmartTurnMetricsData is deprecated in include_metrics, " + "use TurnMetricsData instead.", + DeprecationWarning, + stacklevel=2, + ) + include_metrics = (include_metrics - {SmartTurnMetricsData}) | {TurnMetricsData} self._include_metrics = include_metrics self._frames_seen = set() @@ -144,8 +156,8 @@ class MetricsLogObserver(BaseObserver): logger.debug( f"📊 {processor_info} TTS USAGE{model_info}: {metrics_data.value} characters at {time_sec:.3f}s" ) - elif isinstance(metrics_data, SmartTurnMetricsData): - self._log_smart_turn(metrics_data, processor_info, model_info, time_sec) + elif isinstance(metrics_data, TurnMetricsData): + self._log_turn(metrics_data, processor_info, model_info, time_sec) else: # Generic fallback for unknown metrics types logger.debug( @@ -191,28 +203,27 @@ class MetricsLogObserver(BaseObserver): f"📊 {processor_info} LLM TOKEN USAGE{model_info}: {usage_str} at {time_sec:.2f}s" ) - def _log_smart_turn( + def _log_turn( self, - metrics_data: SmartTurnMetricsData, + metrics_data: TurnMetricsData, processor_info: str, model_info: str, time_sec: float, ): - """Log smart turn prediction metrics. + """Log turn prediction metrics. Args: - metrics_data: The smart turn metrics data. + metrics_data: The turn metrics data. processor_info: Formatted processor name string. model_info: Formatted model name string. time_sec: Timestamp in seconds. """ complete_str = "COMPLETE" if metrics_data.is_complete else "INCOMPLETE" + e2e_str = f"{metrics_data.e2e_processing_time_ms:.1f}ms" logger.debug( - f"📊 {processor_info} SMART TURN{model_info}: {complete_str} " + f"📊 {processor_info} TURN{model_info}: {complete_str} " f"(probability: {metrics_data.probability:.2%}, " - f"inference: {metrics_data.inference_time_ms:.1f}ms, " - f"server: {metrics_data.server_total_time_ms:.1f}ms, " - f"e2e: {metrics_data.e2e_processing_time_ms:.1f}ms) " + f"e2e: {e2e_str}) " f"at {time_sec:.2f}s" ) diff --git a/src/pipecat/turns/user_stop/turn_analyzer_user_turn_stop_strategy.py b/src/pipecat/turns/user_stop/turn_analyzer_user_turn_stop_strategy.py index acd4936a3..f141a75b7 100644 --- a/src/pipecat/turns/user_stop/turn_analyzer_user_turn_stop_strategy.py +++ b/src/pipecat/turns/user_stop/turn_analyzer_user_turn_stop_strategy.py @@ -115,10 +115,14 @@ class TurnAnalyzerUserTurnStopStrategy(BaseUserTurnStopStrategy): """Handle input audio to check if the turn is completed.""" state = self._turn_analyzer.append_audio(frame.audio, self._vad_user_speaking) - # If at this point the model says the turn is complete it will be due to - # a timeout, so we mark turn as complete and we trigger the user end of - # turn. + # Streaming analyzers (e.g. KrispVivaTurn) detect turn completion + # frame-by-frame inside append_audio, so COMPLETE is returned here + # rather than in analyze_end_of_turn. Batch analyzers (BaseSmartTurn) + # return COMPLETE here only on a silence timeout. In either case we + # consume and push metrics immediately while they're fresh. if state == EndOfTurnState.COMPLETE: + _, prediction = await self._turn_analyzer.analyze_end_of_turn() + await self._handle_prediction_result(prediction) self._turn_complete = True await self._maybe_trigger_user_turn_stopped() From 81f4672535cd683e233d7bd9a3698172c1d419e0 Mon Sep 17 00:00:00 2001 From: Mark Backman Date: Wed, 25 Feb 2026 09:47:42 -0500 Subject: [PATCH 0635/1060] Add Performance as a changelog fragment option --- CLAUDE.md | 27 +++++++++++++-------------- CONTRIBUTING.md | 4 +--- pyproject.toml | 5 +++++ 3 files changed, 19 insertions(+), 17 deletions(-) diff --git a/CLAUDE.md b/CLAUDE.md index 6886fc1ed..7727975b3 100644 --- a/CLAUDE.md +++ b/CLAUDE.md @@ -25,7 +25,7 @@ uv run pytest tests/test_name.py uv run pytest tests/test_name.py::test_function_name # Preview changelog -towncrier build --draft --version Unreleased +uv run towncrier build --draft --version Unreleased # Lint and format check uv run ruff check @@ -74,7 +74,7 @@ All data flows as **Frame** objects through a pipeline of **FrameProcessors**: - **Context Aggregation**: `LLMContext` accumulates messages for LLM calls; `UserResponse` aggregates user input - **Turn Management**: Turn management is done through `LLMUserAggregator` and -`LLMAssistantAggregator`, created with `LLMContextAggregatorPair` + `LLMAssistantAggregator`, created with `LLMContextAggregatorPair` - **User turn strategies**: Detection of when the user starts and stops speaking is done via user turn start/stop strategies. They push `UserStartedSpeakingFrame` and `UserStoppedSpeakingFrame` respectively. @@ -90,17 +90,17 @@ All data flows as **Frame** objects through a pipeline of **FrameProcessors**: ### Key Directories -| Directory | Purpose | -|---------------------------|----------------------------------------------------| -| `src/pipecat/frames/` | Frame definitions (100+ types) | -| `src/pipecat/processors/` | FrameProcessor base + aggregators, filters, audio | -| `src/pipecat/pipeline/` | Pipeline orchestration | -| `src/pipecat/services/` | AI service integrations (60+ providers) | -| `src/pipecat/transports/` | Transport layer (Daily, LiveKit, WebSocket, Local) | -| `src/pipecat/serializers/`| Frame serialization for WebSocket protocols | -| `src/pipecat/observers/` | Pipeline observers for monitoring frame flow | -| `src/pipecat/audio/` | VAD, filters, mixers, turn detection, DTMF | -| `src/pipecat/turns/` | User turn management | +| Directory | Purpose | +| -------------------------- | -------------------------------------------------- | +| `src/pipecat/frames/` | Frame definitions (100+ types) | +| `src/pipecat/processors/` | FrameProcessor base + aggregators, filters, audio | +| `src/pipecat/pipeline/` | Pipeline orchestration | +| `src/pipecat/services/` | AI service integrations (60+ providers) | +| `src/pipecat/transports/` | Transport layer (Daily, LiveKit, WebSocket, Local) | +| `src/pipecat/serializers/` | Frame serialization for WebSocket protocols | +| `src/pipecat/observers/` | Pipeline observers for monitoring frame flow | +| `src/pipecat/audio/` | VAD, filters, mixers, turn detection, DTMF | +| `src/pipecat/turns/` | User turn management | ## Code Style @@ -155,4 +155,3 @@ When adding a new service: ## Testing Test utilities live in `src/pipecat/tests/utils.py`. Use `run_test()` to send frames through a pipeline and assert expected output frames in each direction. Use `SleepFrame(sleep=N)` to add delays between frames. - diff --git a/CONTRIBUTING.md b/CONTRIBUTING.md index 937532ec9..936a652fa 100644 --- a/CONTRIBUTING.md +++ b/CONTRIBUTING.md @@ -49,12 +49,12 @@ Every pull request that makes a user-facing change should include a changelog en ``` 2. Choose the appropriate type: - - `added.md` - New features - `changed.md` - Changes in existing functionality - `deprecated.md` - Soon-to-be removed features - `removed.md` - Removed features - `fixed.md` - Bug fixes + - `performance.md` - Performance improvements - `security.md` - Security fixes - `other.md` - Other changes (documentation, dependencies, etc.) @@ -80,7 +80,6 @@ Every pull request that makes a user-facing change should include a changelog en ```markdown - Updated service configuration: - - Changed default timeout to 30 seconds - Added retry logic for failed connections ``` @@ -105,7 +104,6 @@ changelog/1234.changed.2.md ```markdown - Updated service configuration: - - Changed default timeout to 30 seconds - Added retry logic for failed connections ``` diff --git a/pyproject.toml b/pyproject.toml index a45ebb3b3..d988fa5cd 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -257,6 +257,11 @@ directory = "fixed" name = "Fixed" showcontent = true +[[tool.towncrier.type]] +directory = "performance" +name = "Performance" +showcontent = true + [[tool.towncrier.type]] directory = "security" name = "Security" From e028194dbe3895839383ac7c840c4279850fd798 Mon Sep 17 00:00:00 2001 From: Mark Backman Date: Wed, 25 Feb 2026 12:20:21 -0500 Subject: [PATCH 0636/1060] Update the pipecat-ai-small-webrtc-prebuilt to 2.3.0 --- pyproject.toml | 2 +- uv.lock | 8 ++++---- 2 files changed, 5 insertions(+), 5 deletions(-) diff --git a/pyproject.toml b/pyproject.toml index a45ebb3b3..cc12deed6 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -106,7 +106,7 @@ remote-smart-turn = [] resembleai = [ "pipecat-ai[websockets-base]" ] rime = [ "pipecat-ai[websockets-base]" ] riva = [ "pipecat-ai[nvidia]" ] -runner = [ "python-dotenv>=1.0.0,<2.0.0", "uvicorn>=0.32.0,<1.0.0", "fastapi>=0.115.6,<0.128.0", "pipecat-ai-small-webrtc-prebuilt>=2.2.0"] +runner = [ "python-dotenv>=1.0.0,<2.0.0", "uvicorn>=0.32.0,<1.0.0", "fastapi>=0.115.6,<0.128.0", "pipecat-ai-small-webrtc-prebuilt>=2.3.0"] sagemaker = ["aws_sdk_sagemaker_runtime_http2; python_version>='3.12'"] sambanova = [] sarvam = [ "sarvamai==0.1.26a2", "pipecat-ai[websockets-base]" ] diff --git a/uv.lock b/uv.lock index bd2f64639..a4450710d 100644 --- a/uv.lock +++ b/uv.lock @@ -4730,7 +4730,7 @@ requires-dist = [ { name = "pipecat-ai", extras = ["websockets-base"], marker = "extra == 'ultravox'" }, { name = "pipecat-ai", extras = ["websockets-base"], marker = "extra == 'websocket'" }, { name = "pipecat-ai-krisp", marker = "extra == 'krisp'", specifier = "~=0.4.0" }, - { name = "pipecat-ai-small-webrtc-prebuilt", marker = "extra == 'runner'", specifier = ">=2.2.0" }, + { name = "pipecat-ai-small-webrtc-prebuilt", marker = "extra == 'runner'", specifier = ">=2.3.0" }, { name = "piper-tts", marker = "extra == 'piper'", specifier = ">=1.3.0,<2" }, { name = "protobuf", specifier = "~=5.29.6" }, { name = "pvkoala", marker = "extra == 'koala'", specifier = "~=2.0.3" }, @@ -4801,14 +4801,14 @@ sdist = { url = "https://files.pythonhosted.org/packages/1d/37/0f1d11d1dc33234a3 [[package]] name = "pipecat-ai-small-webrtc-prebuilt" -version = "2.2.0" +version = "2.3.0" source = { registry = "https://pypi.org/simple" } dependencies = [ { name = "fastapi", extra = ["all"] }, ] -sdist = { url = "https://files.pythonhosted.org/packages/9a/9f/b06cc0e2eaeda811959c216dade3ed38c30d20e6327a2b22f80125072c5a/pipecat_ai_small_webrtc_prebuilt-2.2.0.tar.gz", hash = "sha256:5d73fe619225b97e383863a901060d1c986f088f4de004477856b085aaba76c4", size = 466005, upload-time = "2026-02-13T19:28:54.626Z" } +sdist = { url = "https://files.pythonhosted.org/packages/2e/5f/b0f73bbc6997c22655f0495ce21a4cb176e192df1b5407f66fad8101c697/pipecat_ai_small_webrtc_prebuilt-2.3.0.tar.gz", hash = "sha256:10dc31db9978d68001ae941066fe460c533412a8984df71e5416d4ebeb9c0371", size = 469001, upload-time = "2026-02-25T17:18:43.316Z" } wheels = [ - { url = "https://files.pythonhosted.org/packages/26/71/20a015cea25dc57129ed6426fdf37a09aefe37f4dd60e3a42ba2d9e3bd1b/pipecat_ai_small_webrtc_prebuilt-2.2.0-py3-none-any.whl", hash = "sha256:e7917d23f51e5418667541a3e241b2de28a43eea35a5a9486721be3da04e719d", size = 466257, upload-time = "2026-02-13T19:28:53.188Z" }, + { url = "https://files.pythonhosted.org/packages/5a/bc/6193b639a53f4bac1c0fe29b1f8e0d49085c60e457b02a01e725eb7c093f/pipecat_ai_small_webrtc_prebuilt-2.3.0-py3-none-any.whl", hash = "sha256:b3ddaff8bbd56746fe3c58a2d721d3ccc94d17a33c16d78dcbce73d7526c1a05", size = 468881, upload-time = "2026-02-25T17:18:41.869Z" }, ] [[package]] From ceead60ef23cdf30a98f41fd1fa09ed1f28b81ce Mon Sep 17 00:00:00 2001 From: Stephen Altamirano Date: Wed, 25 Feb 2026 09:43:57 -0800 Subject: [PATCH 0637/1060] Add `append_trailing_space` to all Rime websocket services This was added in 31daa889e83b960fab79d66b2ab014d930e15a2e, but only to `RimeTTSService`, not to `RimeNonJsonTTSService. Bringing these to parity means that users switching between the two, with the same inputs, have more consistent vocalization behaviors. --- changelog/3837.fixed.md | 1 + src/pipecat/services/rime/tts.py | 1 + 2 files changed, 2 insertions(+) create mode 100644 changelog/3837.fixed.md diff --git a/changelog/3837.fixed.md b/changelog/3837.fixed.md new file mode 100644 index 000000000..767e79f45 --- /dev/null +++ b/changelog/3837.fixed.md @@ -0,0 +1 @@ +- Fixed issues with `RimeNonJsonTTSService` where trailing punctuation is sometimes vocalized diff --git a/src/pipecat/services/rime/tts.py b/src/pipecat/services/rime/tts.py index 83c2305d5..484c99857 100644 --- a/src/pipecat/services/rime/tts.py +++ b/src/pipecat/services/rime/tts.py @@ -846,6 +846,7 @@ class RimeNonJsonTTSService(InterruptibleTTSService): aggregate_sentences=aggregate_sentences, push_stop_frames=True, pause_frame_processing=True, + append_trailing_space=True, **kwargs, ) params = params or RimeNonJsonTTSService.InputParams() From 44993fe9e3c55c76c063ce9ccba7b539ae0a2576 Mon Sep 17 00:00:00 2001 From: Mark Backman Date: Wed, 25 Feb 2026 14:09:17 -0500 Subject: [PATCH 0638/1060] Remove PlayHT TTS services --- README.md | 26 +- changelog/3838.removed.md | 1 + docs/api/README.md | 3 +- env.example | 4 - .../07e-interruptible-playht-http.py | 125 ---- .../foundational/07e-interruptible-playht.py | 127 ---- .../55t-update-settings-playht-tts.py | 126 ---- pyproject.toml | 1 - src/pipecat/services/playht/__init__.py | 13 - src/pipecat/services/playht/tts.py | 699 ------------------ uv.lock | 6 +- 11 files changed, 16 insertions(+), 1115 deletions(-) create mode 100644 changelog/3838.removed.md delete mode 100644 examples/foundational/07e-interruptible-playht-http.py delete mode 100644 examples/foundational/07e-interruptible-playht.py delete mode 100644 examples/foundational/55t-update-settings-playht-tts.py delete mode 100644 src/pipecat/services/playht/__init__.py delete mode 100644 src/pipecat/services/playht/tts.py diff --git a/README.md b/README.md index 2221e807e..05874be81 100644 --- a/README.md +++ b/README.md @@ -81,19 +81,19 @@ Catch new features, interviews, and how-tos on our [Pipecat TV](https://www.yout ## 🧩 Available services -| Category | Services | -| ------------------- | ----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | -| Speech-to-Text | [AssemblyAI](https://docs.pipecat.ai/server/services/stt/assemblyai), [AWS](https://docs.pipecat.ai/server/services/stt/aws), [Azure](https://docs.pipecat.ai/server/services/stt/azure), [Cartesia](https://docs.pipecat.ai/server/services/stt/cartesia), [Deepgram](https://docs.pipecat.ai/server/services/stt/deepgram), [ElevenLabs](https://docs.pipecat.ai/server/services/stt/elevenlabs), [Fal Wizper](https://docs.pipecat.ai/server/services/stt/fal), [Gladia](https://docs.pipecat.ai/server/services/stt/gladia), [Google](https://docs.pipecat.ai/server/services/stt/google), [Gradium](https://docs.pipecat.ai/server/services/stt/gradium), [Groq (Whisper)](https://docs.pipecat.ai/server/services/stt/groq), [Hathora](https://docs.pipecat.ai/server/services/stt/hathora), [NVIDIA Riva](https://docs.pipecat.ai/server/services/stt/riva), [OpenAI (Whisper)](https://docs.pipecat.ai/server/services/stt/openai), [SambaNova 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[Fish](https://docs.pipecat.ai/server/services/tts/fish), [Google](https://docs.pipecat.ai/server/services/tts/google), [Gradium](https://docs.pipecat.ai/server/services/tts/gradium), [Groq](https://docs.pipecat.ai/server/services/tts/groq), [Hathora](https://docs.pipecat.ai/server/services/tts/hathora), [Hume](https://docs.pipecat.ai/server/services/tts/hume), [Inworld](https://docs.pipecat.ai/server/services/tts/inworld), [LMNT](https://docs.pipecat.ai/server/services/tts/lmnt), [MiniMax](https://docs.pipecat.ai/server/services/tts/minimax), [Neuphonic](https://docs.pipecat.ai/server/services/tts/neuphonic), [NVIDIA Riva](https://docs.pipecat.ai/server/services/tts/riva), [OpenAI](https://docs.pipecat.ai/server/services/tts/openai), [Piper](https://docs.pipecat.ai/server/services/tts/piper), [PlayHT](https://docs.pipecat.ai/server/services/tts/playht), [Resemble](https://docs.pipecat.ai/server/services/tts/resemble), [Rime](https://docs.pipecat.ai/server/services/tts/rime), [Sarvam](https://docs.pipecat.ai/server/services/tts/sarvam), [Speechmatics](https://docs.pipecat.ai/server/services/tts/speechmatics), [XTTS](https://docs.pipecat.ai/server/services/tts/xtts) | -| Speech-to-Speech | [AWS Nova Sonic](https://docs.pipecat.ai/server/services/s2s/aws), [Gemini Multimodal Live](https://docs.pipecat.ai/server/services/s2s/gemini), [Grok Voice Agent](https://docs.pipecat.ai/server/services/s2s/grok), [OpenAI Realtime](https://docs.pipecat.ai/server/services/s2s/openai), [Ultravox](https://docs.pipecat.ai/server/services/s2s/ultravox), | -| Transport | [Daily (WebRTC)](https://docs.pipecat.ai/server/services/transport/daily), [FastAPI Websocket](https://docs.pipecat.ai/server/services/transport/fastapi-websocket), [SmallWebRTCTransport](https://docs.pipecat.ai/server/services/transport/small-webrtc), [WebSocket Server](https://docs.pipecat.ai/server/services/transport/websocket-server), Local | -| Serializers | [Exotel](https://docs.pipecat.ai/server/utilities/serializers/exotel), [Plivo](https://docs.pipecat.ai/server/utilities/serializers/plivo), [Twilio](https://docs.pipecat.ai/server/utilities/serializers/twilio), [Telnyx](https://docs.pipecat.ai/server/utilities/serializers/telnyx), [Vonage](https://docs.pipecat.ai/server/utilities/serializers/vonage) | -| Video | [HeyGen](https://docs.pipecat.ai/server/services/video/heygen), [Tavus](https://docs.pipecat.ai/server/services/video/tavus), [Simli](https://docs.pipecat.ai/server/services/video/simli) | -| Memory | [mem0](https://docs.pipecat.ai/server/services/memory/mem0) | -| Vision & Image | [fal](https://docs.pipecat.ai/server/services/image-generation/fal), [Google Imagen](https://docs.pipecat.ai/server/services/image-generation/google-imagen), [Moondream](https://docs.pipecat.ai/server/services/vision/moondream) | -| Audio Processing | [Silero VAD](https://docs.pipecat.ai/server/utilities/audio/silero-vad-analyzer), [Krisp](https://docs.pipecat.ai/server/utilities/audio/krisp-filter), [Koala](https://docs.pipecat.ai/server/utilities/audio/koala-filter), [ai-coustics](https://docs.pipecat.ai/server/utilities/audio/aic-filter) | -| Analytics & Metrics | [OpenTelemetry](https://docs.pipecat.ai/server/utilities/opentelemetry), [Sentry](https://docs.pipecat.ai/server/services/analytics/sentry) | +| Category | Services | +| ------------------- | -------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | +| Speech-to-Text | [AssemblyAI](https://docs.pipecat.ai/server/services/stt/assemblyai), [AWS](https://docs.pipecat.ai/server/services/stt/aws), [Azure](https://docs.pipecat.ai/server/services/stt/azure), [Cartesia](https://docs.pipecat.ai/server/services/stt/cartesia), [Deepgram](https://docs.pipecat.ai/server/services/stt/deepgram), [ElevenLabs](https://docs.pipecat.ai/server/services/stt/elevenlabs), [Fal Wizper](https://docs.pipecat.ai/server/services/stt/fal), [Gladia](https://docs.pipecat.ai/server/services/stt/gladia), [Google](https://docs.pipecat.ai/server/services/stt/google), [Gradium](https://docs.pipecat.ai/server/services/stt/gradium), [Groq (Whisper)](https://docs.pipecat.ai/server/services/stt/groq), [Hathora](https://docs.pipecat.ai/server/services/stt/hathora), [NVIDIA Riva](https://docs.pipecat.ai/server/services/stt/riva), [OpenAI (Whisper)](https://docs.pipecat.ai/server/services/stt/openai), [SambaNova (Whisper)](https://docs.pipecat.ai/server/services/stt/sambanova), [Sarvam](https://docs.pipecat.ai/server/services/stt/sarvam), [Soniox](https://docs.pipecat.ai/server/services/stt/soniox), [Speechmatics](https://docs.pipecat.ai/server/services/stt/speechmatics), [Whisper](https://docs.pipecat.ai/server/services/stt/whisper) | +| LLMs | [Anthropic](https://docs.pipecat.ai/server/services/llm/anthropic), [AWS](https://docs.pipecat.ai/server/services/llm/aws), [Azure](https://docs.pipecat.ai/server/services/llm/azure), [Cerebras](https://docs.pipecat.ai/server/services/llm/cerebras), [DeepSeek](https://docs.pipecat.ai/server/services/llm/deepseek), [Fireworks AI](https://docs.pipecat.ai/server/services/llm/fireworks), [Gemini](https://docs.pipecat.ai/server/services/llm/gemini), [Grok](https://docs.pipecat.ai/server/services/llm/grok), [Groq](https://docs.pipecat.ai/server/services/llm/groq), [Mistral](https://docs.pipecat.ai/server/services/llm/mistral), [NVIDIA NIM](https://docs.pipecat.ai/server/services/llm/nim), [Ollama](https://docs.pipecat.ai/server/services/llm/ollama), [OpenAI](https://docs.pipecat.ai/server/services/llm/openai), [OpenRouter](https://docs.pipecat.ai/server/services/llm/openrouter), [Perplexity](https://docs.pipecat.ai/server/services/llm/perplexity), [Qwen](https://docs.pipecat.ai/server/services/llm/qwen), [SambaNova](https://docs.pipecat.ai/server/services/llm/sambanova) [Together AI](https://docs.pipecat.ai/server/services/llm/together) | +| Text-to-Speech | [Async](https://docs.pipecat.ai/server/services/tts/asyncai), [AWS](https://docs.pipecat.ai/server/services/tts/aws), [Azure](https://docs.pipecat.ai/server/services/tts/azure), [Camb AI](https://docs.pipecat.ai/server/services/tts/camb), [Cartesia](https://docs.pipecat.ai/server/services/tts/cartesia), [Deepgram](https://docs.pipecat.ai/server/services/tts/deepgram), [ElevenLabs](https://docs.pipecat.ai/server/services/tts/elevenlabs), [Fish](https://docs.pipecat.ai/server/services/tts/fish), [Google](https://docs.pipecat.ai/server/services/tts/google), [Gradium](https://docs.pipecat.ai/server/services/tts/gradium), [Groq](https://docs.pipecat.ai/server/services/tts/groq), [Hathora](https://docs.pipecat.ai/server/services/tts/hathora), [Hume](https://docs.pipecat.ai/server/services/tts/hume), [Inworld](https://docs.pipecat.ai/server/services/tts/inworld), [LMNT](https://docs.pipecat.ai/server/services/tts/lmnt), [MiniMax](https://docs.pipecat.ai/server/services/tts/minimax), [Neuphonic](https://docs.pipecat.ai/server/services/tts/neuphonic), [NVIDIA Riva](https://docs.pipecat.ai/server/services/tts/riva), [OpenAI](https://docs.pipecat.ai/server/services/tts/openai), [Piper](https://docs.pipecat.ai/server/services/tts/piper), [Resemble](https://docs.pipecat.ai/server/services/tts/resemble), [Rime](https://docs.pipecat.ai/server/services/tts/rime), [Sarvam](https://docs.pipecat.ai/server/services/tts/sarvam), [Speechmatics](https://docs.pipecat.ai/server/services/tts/speechmatics), [XTTS](https://docs.pipecat.ai/server/services/tts/xtts) | +| Speech-to-Speech | [AWS Nova Sonic](https://docs.pipecat.ai/server/services/s2s/aws), [Gemini Multimodal Live](https://docs.pipecat.ai/server/services/s2s/gemini), [Grok Voice Agent](https://docs.pipecat.ai/server/services/s2s/grok), [OpenAI Realtime](https://docs.pipecat.ai/server/services/s2s/openai), [Ultravox](https://docs.pipecat.ai/server/services/s2s/ultravox), | +| Transport | [Daily (WebRTC)](https://docs.pipecat.ai/server/services/transport/daily), [FastAPI Websocket](https://docs.pipecat.ai/server/services/transport/fastapi-websocket), [SmallWebRTCTransport](https://docs.pipecat.ai/server/services/transport/small-webrtc), [WebSocket Server](https://docs.pipecat.ai/server/services/transport/websocket-server), Local | +| Serializers | [Exotel](https://docs.pipecat.ai/server/utilities/serializers/exotel), [Plivo](https://docs.pipecat.ai/server/utilities/serializers/plivo), [Twilio](https://docs.pipecat.ai/server/utilities/serializers/twilio), [Telnyx](https://docs.pipecat.ai/server/utilities/serializers/telnyx), [Vonage](https://docs.pipecat.ai/server/utilities/serializers/vonage) | +| Video | [HeyGen](https://docs.pipecat.ai/server/services/video/heygen), [Tavus](https://docs.pipecat.ai/server/services/video/tavus), [Simli](https://docs.pipecat.ai/server/services/video/simli) | +| Memory | [mem0](https://docs.pipecat.ai/server/services/memory/mem0) | +| Vision & Image | [fal](https://docs.pipecat.ai/server/services/image-generation/fal), [Google Imagen](https://docs.pipecat.ai/server/services/image-generation/google-imagen), [Moondream](https://docs.pipecat.ai/server/services/vision/moondream) | +| Audio Processing | [Silero VAD](https://docs.pipecat.ai/server/utilities/audio/silero-vad-analyzer), [Krisp](https://docs.pipecat.ai/server/utilities/audio/krisp-filter), [Koala](https://docs.pipecat.ai/server/utilities/audio/koala-filter), [ai-coustics](https://docs.pipecat.ai/server/utilities/audio/aic-filter) | +| Analytics & Metrics | [OpenTelemetry](https://docs.pipecat.ai/server/utilities/opentelemetry), [Sentry](https://docs.pipecat.ai/server/services/analytics/sentry) | 📚 [View full services documentation →](https://docs.pipecat.ai/server/services/supported-services) diff --git a/changelog/3838.removed.md b/changelog/3838.removed.md new file mode 100644 index 000000000..fa811cb71 --- /dev/null +++ b/changelog/3838.removed.md @@ -0,0 +1 @@ +- ⚠️ Removed `PlayHTTTSService` and `PlayHTHttpTTSService`. PlayHT has been shut down and is no longer available. diff --git a/docs/api/README.md b/docs/api/README.md index 22b62d45e..e181bc898 100644 --- a/docs/api/README.md +++ b/docs/api/README.md @@ -42,7 +42,7 @@ This script: - Creates a fresh virtual environment - Installs all dependencies as specified in requirements files -- Handles conflicting dependencies (like grpcio versions for Riva and PlayHT) +- Handles conflicting dependencies (like grpcio versions for Riva) - Builds the documentation in an isolated environment - Provides detailed logging of the build process @@ -74,7 +74,6 @@ start _build/html/index.html ├── index.rst # Main documentation entry point ├── requirements-base.txt # Base documentation dependencies ├── requirements-riva.txt # Riva-specific dependencies -├── requirements-playht.txt # PlayHT-specific dependencies ├── build-docs.sh # Local build script └── rtd-test.py # ReadTheDocs test build script ``` diff --git a/env.example b/env.example index 2b850dd19..82308812e 100644 --- a/env.example +++ b/env.example @@ -147,10 +147,6 @@ KOALA_ACCESS_KEY=... # Piper PIPER_BASE_URL=... -# PlayHT -PLAYHT_USER_ID=... -PLAYHT_API_KEY=... - # Plivo PLIVO_AUTH_ID=... PLIVO_AUTH_TOKEN=... diff --git a/examples/foundational/07e-interruptible-playht-http.py b/examples/foundational/07e-interruptible-playht-http.py deleted file mode 100644 index c56de3b9f..000000000 --- a/examples/foundational/07e-interruptible-playht-http.py +++ /dev/null @@ -1,125 +0,0 @@ -# -# Copyright (c) 2024-2026, Daily -# -# SPDX-License-Identifier: BSD 2-Clause License -# - - -import os - -from dotenv import load_dotenv -from loguru import logger - -from pipecat.audio.vad.silero import SileroVADAnalyzer -from pipecat.frames.frames import LLMRunFrame -from pipecat.pipeline.pipeline import Pipeline -from pipecat.pipeline.runner import PipelineRunner -from pipecat.pipeline.task import PipelineParams, PipelineTask -from pipecat.processors.aggregators.llm_context import LLMContext -from pipecat.processors.aggregators.llm_response_universal import ( - LLMContextAggregatorPair, - LLMUserAggregatorParams, -) -from pipecat.runner.types import RunnerArguments -from pipecat.runner.utils import create_transport -from pipecat.services.deepgram.stt import DeepgramSTTService -from pipecat.services.openai.llm import OpenAILLMService -from pipecat.services.playht.tts import PlayHTHttpTTSService -from pipecat.transports.base_transport import BaseTransport, TransportParams -from pipecat.transports.daily.transport import DailyParams -from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams - -load_dotenv(override=True) - -# We use lambdas to defer transport parameter creation until the transport -# type is selected at runtime. -transport_params = { - "daily": lambda: DailyParams( - audio_in_enabled=True, - audio_out_enabled=True, - ), - "twilio": lambda: FastAPIWebsocketParams( - audio_in_enabled=True, - audio_out_enabled=True, - ), - "webrtc": lambda: TransportParams( - audio_in_enabled=True, - audio_out_enabled=True, - ), -} - - -async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): - logger.info(f"Starting bot") - - stt = DeepgramSTTService(api_key=os.getenv("DEEPGRAM_API_KEY")) - - tts = PlayHTHttpTTSService( - user_id=os.getenv("PLAYHT_USER_ID"), - api_key=os.getenv("PLAYHT_API_KEY"), - voice_url="s3://voice-cloning-zero-shot/d9ff78ba-d016-47f6-b0ef-dd630f59414e/female-cs/manifest.json", - ) - - llm = OpenAILLMService(api_key=os.getenv("OPENAI_API_KEY")) - - messages = [ - { - "role": "system", - "content": "You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", - }, - ] - - context = LLMContext(messages) - user_aggregator, assistant_aggregator = LLMContextAggregatorPair( - context, - user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()), - ) - - pipeline = Pipeline( - [ - transport.input(), # Transport user input - stt, - user_aggregator, # User responses - llm, # LLM - tts, # TTS - transport.output(), # Transport bot output - assistant_aggregator, # Assistant spoken responses - ] - ) - - task = PipelineTask( - pipeline, - params=PipelineParams( - enable_metrics=True, - enable_usage_metrics=True, - ), - idle_timeout_secs=runner_args.pipeline_idle_timeout_secs, - ) - - @transport.event_handler("on_client_connected") - async def on_client_connected(transport, client): - logger.info(f"Client connected") - # Kick off the conversation. - messages.append({"role": "system", "content": "Please introduce yourself to the user."}) - await task.queue_frames([LLMRunFrame()]) - - @transport.event_handler("on_client_disconnected") - async def on_client_disconnected(transport, client): - logger.info(f"Client disconnected") - await task.cancel() - - runner = PipelineRunner(handle_sigint=runner_args.handle_sigint) - - await runner.run(task) - - -async def bot(runner_args: RunnerArguments): - """Main bot entry point compatible with Pipecat Cloud.""" - transport = await create_transport(runner_args, transport_params) - await run_bot(transport, runner_args) - - -if __name__ == "__main__": - from pipecat.runner.run import main - - main() diff --git a/examples/foundational/07e-interruptible-playht.py b/examples/foundational/07e-interruptible-playht.py deleted file mode 100644 index b42f8f6a2..000000000 --- a/examples/foundational/07e-interruptible-playht.py +++ /dev/null @@ -1,127 +0,0 @@ -# -# Copyright (c) 2024-2026, Daily -# -# SPDX-License-Identifier: BSD 2-Clause License -# - - -import os - -from dotenv import load_dotenv -from loguru import logger - -from pipecat.audio.vad.silero import SileroVADAnalyzer -from pipecat.frames.frames import LLMRunFrame -from pipecat.pipeline.pipeline import Pipeline -from pipecat.pipeline.runner import PipelineRunner -from pipecat.pipeline.task import PipelineParams, PipelineTask -from pipecat.processors.aggregators.llm_context import LLMContext -from pipecat.processors.aggregators.llm_response_universal import ( - LLMContextAggregatorPair, - LLMUserAggregatorParams, -) -from pipecat.runner.types import RunnerArguments -from pipecat.runner.utils import create_transport -from pipecat.services.deepgram.stt import DeepgramSTTService -from pipecat.services.openai.llm import OpenAILLMService -from pipecat.services.playht.tts import PlayHTTTSService -from pipecat.transcriptions.language import Language -from pipecat.transports.base_transport import BaseTransport, TransportParams -from pipecat.transports.daily.transport import DailyParams -from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams - -load_dotenv(override=True) - -# We use lambdas to defer transport parameter creation until the transport -# type is selected at runtime. -transport_params = { - "daily": lambda: DailyParams( - audio_in_enabled=True, - audio_out_enabled=True, - ), - "twilio": lambda: FastAPIWebsocketParams( - audio_in_enabled=True, - audio_out_enabled=True, - ), - "webrtc": lambda: TransportParams( - audio_in_enabled=True, - audio_out_enabled=True, - ), -} - - -async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): - logger.info(f"Starting bot") - - stt = DeepgramSTTService(api_key=os.getenv("DEEPGRAM_API_KEY")) - - tts = PlayHTTTSService( - user_id=os.getenv("PLAYHT_USER_ID"), - api_key=os.getenv("PLAYHT_API_KEY"), - voice_url="s3://voice-cloning-zero-shot/e46b4027-b38d-4d24-b292-38fbca2be0ef/original/manifest.json", - params=PlayHTTTSService.InputParams(language=Language.EN), - ) - - llm = OpenAILLMService(api_key=os.getenv("OPENAI_API_KEY")) - - messages = [ - { - "role": "system", - "content": "You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", - }, - ] - - context = LLMContext(messages) - user_aggregator, assistant_aggregator = LLMContextAggregatorPair( - context, - user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()), - ) - - pipeline = Pipeline( - [ - transport.input(), # Transport user input - stt, - user_aggregator, # User responses - llm, # LLM - tts, # TTS - transport.output(), # Transport bot output - assistant_aggregator, # Assistant spoken responses - ] - ) - - task = PipelineTask( - pipeline, - params=PipelineParams( - enable_metrics=True, - enable_usage_metrics=True, - ), - idle_timeout_secs=runner_args.pipeline_idle_timeout_secs, - ) - - @transport.event_handler("on_client_connected") - async def on_client_connected(transport, client): - logger.info(f"Client connected") - # Kick off the conversation. - messages.append({"role": "system", "content": "Please introduce yourself to the user."}) - await task.queue_frames([LLMRunFrame()]) - - @transport.event_handler("on_client_disconnected") - async def on_client_disconnected(transport, client): - logger.info(f"Client disconnected") - await task.cancel() - - runner = PipelineRunner(handle_sigint=runner_args.handle_sigint) - - await runner.run(task) - - -async def bot(runner_args: RunnerArguments): - """Main bot entry point compatible with Pipecat Cloud.""" - transport = await create_transport(runner_args, transport_params) - await run_bot(transport, runner_args) - - -if __name__ == "__main__": - from pipecat.runner.run import main - - main() diff --git a/examples/foundational/55t-update-settings-playht-tts.py b/examples/foundational/55t-update-settings-playht-tts.py deleted file mode 100644 index d79120d99..000000000 --- a/examples/foundational/55t-update-settings-playht-tts.py +++ /dev/null @@ -1,126 +0,0 @@ -# -# Copyright (c) 2024-2026, Daily -# -# SPDX-License-Identifier: BSD 2-Clause License -# - -import asyncio -import os - -from dotenv import load_dotenv -from loguru import logger - -from pipecat.audio.vad.silero import SileroVADAnalyzer -from pipecat.frames.frames import LLMRunFrame, TTSUpdateSettingsFrame -from pipecat.pipeline.pipeline import Pipeline -from pipecat.pipeline.runner import PipelineRunner -from pipecat.pipeline.task import PipelineParams, PipelineTask -from pipecat.processors.aggregators.llm_context import LLMContext -from pipecat.processors.aggregators.llm_response_universal import ( - LLMContextAggregatorPair, - LLMUserAggregatorParams, -) -from pipecat.runner.types import RunnerArguments -from pipecat.runner.utils import create_transport -from pipecat.services.deepgram.stt import DeepgramSTTService -from pipecat.services.openai.llm import OpenAILLMService -from pipecat.services.playht.tts import PlayHTTTSService, PlayHTTTSSettings -from pipecat.transports.base_transport import BaseTransport, TransportParams -from pipecat.transports.daily.transport import DailyParams -from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams - -load_dotenv(override=True) - -transport_params = { - "daily": lambda: DailyParams( - audio_in_enabled=True, - audio_out_enabled=True, - ), - "twilio": lambda: FastAPIWebsocketParams( - audio_in_enabled=True, - audio_out_enabled=True, - ), - "webrtc": lambda: TransportParams( - audio_in_enabled=True, - audio_out_enabled=True, - ), -} - - -async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): - logger.info(f"Starting bot") - - stt = DeepgramSTTService(api_key=os.getenv("DEEPGRAM_API_KEY")) - - tts = PlayHTTTSService( - api_key=os.getenv("PLAYHT_API_KEY"), - user_id=os.getenv("PLAYHT_USER_ID"), - voice_url=os.getenv("PLAYHT_VOICE_URL", ""), - ) - - llm = OpenAILLMService(api_key=os.getenv("OPENAI_API_KEY")) - - messages = [ - { - "role": "system", - "content": "You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", - }, - ] - - context = LLMContext(messages) - user_aggregator, assistant_aggregator = LLMContextAggregatorPair( - context, - user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()), - ) - - pipeline = Pipeline( - [ - transport.input(), - stt, - user_aggregator, - llm, - tts, - transport.output(), - assistant_aggregator, - ] - ) - - task = PipelineTask( - pipeline, - params=PipelineParams( - enable_metrics=True, - enable_usage_metrics=True, - ), - idle_timeout_secs=runner_args.pipeline_idle_timeout_secs, - ) - - @transport.event_handler("on_client_connected") - async def on_client_connected(transport, client): - logger.info(f"Client connected") - messages.append({"role": "system", "content": "Please introduce yourself to the user."}) - await task.queue_frames([LLMRunFrame()]) - - await asyncio.sleep(10) - logger.info("Updating PlayHT TTS settings: speed=1.3") - await task.queue_frame(TTSUpdateSettingsFrame(delta=PlayHTTTSSettings(speed=1.3))) - - @transport.event_handler("on_client_disconnected") - async def on_client_disconnected(transport, client): - logger.info(f"Client disconnected") - await task.cancel() - - runner = PipelineRunner(handle_sigint=runner_args.handle_sigint) - - await runner.run(task) - - -async def bot(runner_args: RunnerArguments): - """Main bot entry point compatible with Pipecat Cloud.""" - transport = await create_transport(runner_args, transport_params) - await run_bot(transport, runner_args) - - -if __name__ == "__main__": - from pipecat.runner.run import main - - main() diff --git a/pyproject.toml b/pyproject.toml index a45ebb3b3..a925e70d5 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -100,7 +100,6 @@ openpipe = [ "openpipe>=4.50.0,<6" ] openrouter = [] perplexity = [] piper = [ "piper-tts>=1.3.0,<2", "requests>=2.32.5,<3" ] -playht = [ "pipecat-ai[websockets-base]" ] qwen = [] remote-smart-turn = [] resembleai = [ "pipecat-ai[websockets-base]" ] diff --git a/src/pipecat/services/playht/__init__.py b/src/pipecat/services/playht/__init__.py deleted file mode 100644 index 500ea0fdc..000000000 --- a/src/pipecat/services/playht/__init__.py +++ /dev/null @@ -1,13 +0,0 @@ -# -# Copyright (c) 2024-2026, Daily -# -# SPDX-License-Identifier: BSD 2-Clause License -# - -import sys - -from pipecat.services import DeprecatedModuleProxy - -from .tts import * - -sys.modules[__name__] = DeprecatedModuleProxy(globals(), "playht", "playht.tts") diff --git a/src/pipecat/services/playht/tts.py b/src/pipecat/services/playht/tts.py deleted file mode 100644 index 08a87209c..000000000 --- a/src/pipecat/services/playht/tts.py +++ /dev/null @@ -1,699 +0,0 @@ -# -# Copyright (c) 2024-2026, Daily -# -# SPDX-License-Identifier: BSD 2-Clause License -# - -"""PlayHT text-to-speech service implementations. - -This module provides integration with PlayHT's text-to-speech API -supporting both WebSocket streaming and HTTP-based synthesis. -""" - -import io -import json -import struct -import uuid -import warnings -from dataclasses import dataclass, field -from typing import Any, AsyncGenerator, Optional - -import aiohttp -from loguru import logger -from pydantic import BaseModel - -from pipecat.frames.frames import ( - CancelFrame, - EndFrame, - ErrorFrame, - Frame, - InterruptionFrame, - StartFrame, - TTSAudioRawFrame, - TTSStartedFrame, - TTSStoppedFrame, -) -from pipecat.processors.frame_processor import FrameDirection -from pipecat.services.settings import NOT_GIVEN, TTSSettings, _NotGiven -from pipecat.services.tts_service import InterruptibleTTSService, TTSService -from pipecat.transcriptions.language import Language, resolve_language -from pipecat.utils.tracing.service_decorators import traced_tts - -try: - from websockets.asyncio.client import connect as websocket_connect - from websockets.protocol import State -except ModuleNotFoundError as e: - logger.error(f"Exception: {e}") - logger.error("In order to use PlayHTTTSService, you need to `pip install pipecat-ai[playht]`.") - raise Exception(f"Missing module: {e}") - - -def language_to_playht_language(language: Language) -> Optional[str]: - """Convert a Language enum to PlayHT language code. - - Args: - language: The Language enum value to convert. - - Returns: - The corresponding PlayHT language code, or None if not supported. - """ - LANGUAGE_MAP = { - Language.AF: "afrikans", - Language.AM: "amharic", - Language.AR: "arabic", - Language.BN: "bengali", - Language.BG: "bulgarian", - Language.CA: "catalan", - Language.CS: "czech", - Language.DA: "danish", - Language.DE: "german", - Language.EL: "greek", - Language.EN: "english", - Language.ES: "spanish", - Language.FR: "french", - Language.GL: "galician", - Language.HE: "hebrew", - Language.HI: "hindi", - Language.HR: "croatian", - Language.HU: "hungarian", - Language.ID: "indonesian", - Language.IT: "italian", - Language.JA: "japanese", - Language.KO: "korean", - Language.MS: "malay", - Language.NL: "dutch", - Language.PL: "polish", - Language.PT: "portuguese", - Language.RU: "russian", - Language.SQ: "albanian", - Language.SR: "serbian", - Language.SV: "swedish", - Language.TH: "thai", - Language.TL: "tagalog", - Language.TR: "turkish", - Language.UK: "ukrainian", - Language.UR: "urdu", - Language.XH: "xhosa", - Language.ZH: "mandarin", - } - - return resolve_language(language, LANGUAGE_MAP, use_base_code=False) - - -@dataclass -class PlayHTTTSSettings(TTSSettings): - """Settings for PlayHT TTS services. - - Parameters: - output_format: Audio output format. - voice_engine: Voice engine to use. - speed: Speech speed multiplier. Defaults to 1.0. - seed: Random seed for voice consistency. - playht_sample_rate: Audio sample rate sent to the API. - """ - - output_format: str | _NotGiven = field(default_factory=lambda: NOT_GIVEN) - voice_engine: str | _NotGiven = field(default_factory=lambda: NOT_GIVEN) - speed: float | None | _NotGiven = field(default_factory=lambda: NOT_GIVEN) - seed: int | None | _NotGiven = field(default_factory=lambda: NOT_GIVEN) - playht_sample_rate: int | _NotGiven = field(default_factory=lambda: NOT_GIVEN) - - -class PlayHTTTSService(InterruptibleTTSService): - """PlayHT WebSocket-based text-to-speech service. - - .. deprecated:: 0.0.88 - - This class is deprecated and will be removed in a future version. - PlayHT is shutting down their API on December 31st, 2025. - - Provides real-time text-to-speech synthesis using PlayHT's WebSocket API. - Supports streaming audio generation with configurable voice engines and - language settings. - """ - - _settings: PlayHTTTSSettings - - class InputParams(BaseModel): - """Input parameters for PlayHT TTS configuration. - - Parameters: - language: Language for synthesis. Defaults to English. - speed: Speech speed multiplier. Defaults to 1.0. - seed: Random seed for voice consistency. - """ - - language: Optional[Language] = Language.EN - speed: Optional[float] = 1.0 - seed: Optional[int] = None - - def __init__( - self, - *, - api_key: str, - user_id: str, - voice_url: str, - voice_engine: str = "Play3.0-mini", - sample_rate: Optional[int] = None, - output_format: str = "wav", - params: Optional[InputParams] = None, - **kwargs, - ): - """Initialize the PlayHT WebSocket TTS service. - - Args: - api_key: PlayHT API key for authentication. - user_id: PlayHT user ID for authentication. - voice_url: URL of the voice to use for synthesis. - voice_engine: Voice engine to use. Defaults to "Play3.0-mini". - sample_rate: Audio sample rate. If None, uses default. - output_format: Audio output format. Defaults to "wav". - params: Additional input parameters for voice customization. - **kwargs: Additional arguments passed to parent InterruptibleTTSService. - """ - super().__init__( - pause_frame_processing=True, - sample_rate=sample_rate, - **kwargs, - ) - - with warnings.catch_warnings(): - warnings.simplefilter("always") - warnings.warn( - "PlayHT is shutting down their API on December 31st, 2025. " - "'PlayHTTTSService' is deprecated and will be removed in a future version.", - DeprecationWarning, - stacklevel=2, - ) - - params = params or PlayHTTTSService.InputParams() - - self._api_key = api_key - self._user_id = user_id - self._websocket_url = None - self._receive_task = None - self._context_id = None - - self._settings = PlayHTTTSSettings( - model=voice_engine, - voice=voice_url, - language=self.language_to_service_language(params.language) - if params.language - else "english", - output_format=output_format, - voice_engine=voice_engine, - speed=params.speed, - seed=params.seed, - playht_sample_rate=0, - ) - self._sync_model_name_to_metrics() - - def can_generate_metrics(self) -> bool: - """Check if this service can generate processing metrics. - - Returns: - True, as PlayHT service supports metrics generation. - """ - return True - - async def _update_settings(self, delta: TTSSettings) -> dict[str, Any]: - """Apply a settings delta. - - Settings are stored but not applied to the active connection. - """ - changed = await super()._update_settings(delta) - - if not changed: - return changed - - # TODO: someday we could reconnect here to apply updated settings. - # Code might look something like the below: - # await self._disconnect() - # await self._connect() - - self._warn_unhandled_updated_settings(changed) - - return changed - - def language_to_service_language(self, language: Language) -> Optional[str]: - """Convert a Language enum to PlayHT service language format. - - Args: - language: The language to convert. - - Returns: - The PlayHT-specific language code, or None if not supported. - """ - return language_to_playht_language(language) - - async def start(self, frame: StartFrame): - """Start the PlayHT TTS service. - - Args: - frame: The start frame containing initialization parameters. - """ - await super().start(frame) - await self._connect() - - async def stop(self, frame: EndFrame): - """Stop the PlayHT TTS service. - - Args: - frame: The end frame. - """ - await super().stop(frame) - await self._disconnect() - - async def cancel(self, frame: CancelFrame): - """Cancel the PlayHT TTS service. - - Args: - frame: The cancel frame. - """ - await super().cancel(frame) - await self._disconnect() - - async def _connect(self): - """Connect to PlayHT WebSocket and start receive task.""" - await super()._connect() - - await self._connect_websocket() - - if self._websocket and not self._receive_task: - self._receive_task = self.create_task(self._receive_task_handler(self._report_error)) - - async def _disconnect(self): - """Disconnect from PlayHT WebSocket and clean up tasks.""" - await super()._disconnect() - - if self._receive_task: - await self.cancel_task(self._receive_task) - self._receive_task = None - - await self._disconnect_websocket() - - async def _connect_websocket(self): - """Connect to PlayHT websocket.""" - try: - if self._websocket and self._websocket.state is State.OPEN: - return - - logger.debug("Connecting to PlayHT") - - if not self._websocket_url: - await self._get_websocket_url() - - if not isinstance(self._websocket_url, str): - raise ValueError("WebSocket URL is not a string") - - self._websocket = await websocket_connect(self._websocket_url) - - await self._call_event_handler("on_connected") - except ValueError as e: - logger.error(f"{self} initialization error: {e}") - self._websocket = None - await self._call_event_handler("on_connection_error", f"{e}") - except Exception as e: - await self.push_error(error_msg=f"Error connecting: {e}", exception=e) - self._websocket = None - await self._call_event_handler("on_connection_error", f"{e}") - - async def _disconnect_websocket(self): - """Disconnect from PlayHT websocket.""" - try: - await self.stop_all_metrics() - - if self._websocket: - logger.debug("Disconnecting from PlayHT") - await self._websocket.close() - except Exception as e: - await self.push_error(error_msg=f"Error disconnecting: {e}", exception=e) - finally: - self._context_id = None - self._websocket = None - await self._call_event_handler("on_disconnected") - - async def _get_websocket_url(self): - """Retrieve WebSocket URL from PlayHT API.""" - async with aiohttp.ClientSession() as session: - async with session.post( - "https://api.play.ht/api/v4/websocket-auth", - headers={ - "Authorization": f"Bearer {self._api_key}", - "X-User-Id": self._user_id, - "Content-Type": "application/json", - }, - ) as response: - if response.status in (200, 201): - data = await response.json() - # Handle the new response format with multiple URLs - if "websocket_urls" in data: - # Select URL based on voice_engine - if self._settings.voice_engine in data["websocket_urls"]: - self._websocket_url = data["websocket_urls"][ - self._settings.voice_engine - ] - else: - raise ValueError( - f"Unsupported voice engine: {self._settings.voice_engine}" - ) - else: - raise ValueError("Invalid response: missing websocket_urls") - else: - raise Exception(f"Failed to get WebSocket URL: {response.status}") - - def _get_websocket(self): - """Get the WebSocket connection if available.""" - if self._websocket: - return self._websocket - raise Exception("Websocket not connected") - - def create_context_id(self) -> str: - """Generate a unique context ID for a TTS request in case we don't have one already in progress. - - Returns: - A unique string identifier for the TTS context. - """ - # If a context ID does not exist, create a new one. - # If an ID exists, continue using the current ID. - # When interruptions happen, user speech results in - # an interruption, which resets the context ID. - if not self._context_id: - return str(uuid.uuid4()) - return self._context_id - - async def _handle_interruption(self, frame: InterruptionFrame, direction: FrameDirection): - """Handle interruption by stopping metrics and clearing request ID.""" - await super()._handle_interruption(frame, direction) - await self.stop_all_metrics() - self._context_id = None - - async def _receive_messages(self): - """Receive messages from PlayHT websocket.""" - async for message in self._get_websocket(): - if isinstance(message, bytes): - # Skip the WAV header message - if message.startswith(b"RIFF"): - continue - await self.stop_ttfb_metrics() - frame = TTSAudioRawFrame(message, self.sample_rate, 1, context_id=self._context_id) - await self.push_frame(frame) - else: - logger.debug(f"Received text message: {message}") - try: - msg = json.loads(message) - if msg.get("type") == "start": - # Handle start of stream - logger.debug(f"Started processing request: {msg.get('request_id')}") - elif msg.get("type") == "end": - # Handle end of stream - if "request_id" in msg and msg["request_id"] == self._context_id: - await self.push_frame(TTSStoppedFrame(context_id=self._context_id)) - self._context_id = None - elif "error" in msg: - await self.push_error(error_msg=f"Error: {msg['error']}") - except json.JSONDecodeError: - logger.error(f"Invalid JSON message: {message}") - - @traced_tts - async def run_tts(self, text: str, context_id: str) -> AsyncGenerator[Frame, None]: - """Generate TTS audio from text using PlayHT's WebSocket API. - - Args: - text: The text to synthesize into speech. - context_id: The context ID for tracking audio frames. - - Yields: - Frame: Audio frames containing the synthesized speech. - """ - logger.debug(f"{self}: Generating TTS [{text}]") - - try: - # Reconnect if the websocket is closed - if not self._websocket or self._websocket.state is State.CLOSED: - await self._connect() - - if not self._context_id: - await self.start_ttfb_metrics() - yield TTSStartedFrame(context_id=context_id) - self._context_id = context_id - - tts_command = { - "text": text, - "voice": self._settings.voice, - "voice_engine": self._settings.voice_engine, - "output_format": self._settings.output_format, - "sample_rate": self.sample_rate, - "language": self._settings.language, - "speed": self._settings.speed, - "seed": self._settings.seed, - "request_id": self._context_id, - } - - try: - await self._get_websocket().send(json.dumps(tts_command)) - await self.start_tts_usage_metrics(text) - except Exception as e: - yield ErrorFrame(error=f"Unknown error occurred: {e}") - yield TTSStoppedFrame(context_id=context_id) - await self._disconnect() - await self._connect() - return - - # The actual audio frames will be handled in _receive_task_handler - yield None - - except Exception as e: - yield ErrorFrame(error=f"Unknown error occurred: {e}") - - -class PlayHTHttpTTSService(TTSService): - """PlayHT HTTP-based text-to-speech service. - - .. deprecated:: 0.0.88 - - This class is deprecated and will be removed in a future version. - PlayHT is shutting down their API on December 31st, 2025. - - Provides text-to-speech synthesis using PlayHT's HTTP API for simpler, - non-streaming synthesis. Suitable for use cases where streaming is not - required and simpler integration is preferred. - """ - - _settings: PlayHTTTSSettings - - class InputParams(BaseModel): - """Input parameters for PlayHT HTTP TTS configuration. - - Parameters: - language: Language for synthesis. Defaults to English. - speed: Speech speed multiplier. Defaults to 1.0. - seed: Random seed for voice consistency. - """ - - language: Optional[Language] = Language.EN - speed: Optional[float] = 1.0 - seed: Optional[int] = None - - def __init__( - self, - *, - api_key: str, - user_id: str, - voice_url: str, - voice_engine: str = "Play3.0-mini", - protocol: Optional[str] = None, - output_format: str = "wav", - sample_rate: Optional[int] = None, - params: Optional[InputParams] = None, - **kwargs, - ): - """Initialize the PlayHT HTTP TTS service. - - Args: - api_key: PlayHT API key for authentication. - user_id: PlayHT user ID for authentication. - voice_url: URL of the voice to use for synthesis. - voice_engine: Voice engine to use. Defaults to "Play3.0-mini". - protocol: Protocol to use ("http" or "ws"). - - .. deprecated:: 0.0.80 - This parameter no longer has any effect and will be removed in a future version. - Use PlayHTTTSService for WebSocket or PlayHTHttpTTSService for HTTP. - - output_format: Audio output format. Defaults to "wav". - sample_rate: Audio sample rate. If None, uses default. - params: Additional input parameters for voice customization. - **kwargs: Additional arguments passed to parent TTSService. - """ - super().__init__(sample_rate=sample_rate, **kwargs) - - # Warn about deprecated protocol parameter if explicitly provided - if protocol: - with warnings.catch_warnings(): - warnings.simplefilter("always") - warnings.warn( - "The 'protocol' parameter is deprecated and will be removed in a future version.", - DeprecationWarning, - stacklevel=2, - ) - - with warnings.catch_warnings(): - warnings.simplefilter("always") - warnings.warn( - "PlayHT is shutting down their API on December 31st, 2025. " - "'PlayHTHttpTTSService' is deprecated and will be removed in a future version.", - DeprecationWarning, - stacklevel=2, - ) - - params = params or PlayHTHttpTTSService.InputParams() - - self._user_id = user_id - self._api_key = api_key - - # Check if voice_engine contains protocol information (backward compatibility) - if "-http" in voice_engine: - # Extract the base engine name - voice_engine = voice_engine.replace("-http", "") - elif "-ws" in voice_engine: - # Extract the base engine name - voice_engine = voice_engine.replace("-ws", "") - - self._settings = PlayHTTTSSettings( - model=voice_engine, - voice=voice_url, - language=self.language_to_service_language(params.language) - if params.language - else "english", - output_format=output_format, - voice_engine=voice_engine, - speed=params.speed, - seed=params.seed, - playht_sample_rate=0, - ) - self._sync_model_name_to_metrics() - - async def start(self, frame: StartFrame): - """Start the PlayHT HTTP TTS service. - - Args: - frame: The start frame containing initialization parameters. - """ - await super().start(frame) - self._settings.playht_sample_rate = self.sample_rate - - def can_generate_metrics(self) -> bool: - """Check if this service can generate processing metrics. - - Returns: - True, as PlayHT HTTP service supports metrics generation. - """ - return True - - def language_to_service_language(self, language: Language) -> Optional[str]: - """Convert a Language enum to PlayHT service language format. - - Args: - language: The language to convert. - - Returns: - The PlayHT-specific language code, or None if not supported. - """ - return language_to_playht_language(language) - - @traced_tts - async def run_tts(self, text: str, context_id: str) -> AsyncGenerator[Frame, None]: - """Generate TTS audio from text using PlayHT's HTTP API. - - Args: - text: The text to synthesize into speech. - context_id: The context ID for tracking audio frames. - - Yields: - Frame: Audio frames containing the synthesized speech. - """ - logger.debug(f"{self}: Generating TTS [{text}]") - - try: - await self.start_ttfb_metrics() - - # Prepare the request payload - payload = { - "text": text, - "voice": self._settings.voice, - "voice_engine": self._settings.voice_engine, - "output_format": self._settings.output_format, - "sample_rate": self.sample_rate, - "language": self._settings.language, - } - - # Add optional parameters if they exist - if self._settings.speed is not None: - payload["speed"] = self._settings.speed - if self._settings.seed is not None: - payload["seed"] = self._settings.seed - - headers = { - "Authorization": f"Bearer {self._api_key}", - "X-User-Id": self._user_id, - "Content-Type": "application/json", - "Accept": "*/*", - } - - await self.start_tts_usage_metrics(text) - - yield TTSStartedFrame(context_id=context_id) - - async with aiohttp.ClientSession() as session: - async with session.post( - "https://api.play.ht/api/v2/tts/stream", - headers=headers, - json=payload, - ) as response: - if response.status not in (200, 201): - error_text = await response.text() - raise Exception(f"PlayHT API error {response.status}: {error_text}") - - in_header = True - buffer = b"" - - CHUNK_SIZE = self.chunk_size - - async for chunk in response.content.iter_chunked(CHUNK_SIZE): - if len(chunk) == 0: - continue - - # Skip the RIFF header - if in_header: - buffer += chunk - if len(buffer) <= 36: - continue - else: - fh = io.BytesIO(buffer) - fh.seek(36) - (data, size) = struct.unpack("<4sI", fh.read(8)) - while data != b"data": - fh.read(size) - (data, size) = struct.unpack("<4sI", fh.read(8)) - # Extract audio data after header - audio_data = buffer[fh.tell() :] - if len(audio_data) > 0: - await self.stop_ttfb_metrics() - frame = TTSAudioRawFrame( - audio_data, self.sample_rate, 1, context_id=context_id - ) - yield frame - in_header = False - elif len(chunk) > 0: - await self.stop_ttfb_metrics() - frame = TTSAudioRawFrame( - chunk, self.sample_rate, 1, context_id=context_id - ) - yield frame - - except Exception as e: - yield ErrorFrame(error=f"Unknown error occurred: {e}") - finally: - await self.stop_ttfb_metrics() - yield TTSStoppedFrame(context_id=context_id) diff --git a/uv.lock b/uv.lock index bd2f64639..e2615b170 100644 --- a/uv.lock +++ b/uv.lock @@ -4550,9 +4550,6 @@ piper = [ { name = "piper-tts" }, { name = "requests" }, ] -playht = [ - { name = "websockets" }, -] resembleai = [ { name = "websockets" }, ] @@ -4722,7 +4719,6 @@ requires-dist = [ { name = "pipecat-ai", extras = ["websockets-base"], marker = "extra == 'lmnt'" }, { name = "pipecat-ai", extras = ["websockets-base"], marker = "extra == 'neuphonic'" }, { name = "pipecat-ai", extras = ["websockets-base"], marker = "extra == 'openai'" }, - { name = "pipecat-ai", extras = ["websockets-base"], marker = "extra == 'playht'" }, { name = "pipecat-ai", extras = ["websockets-base"], marker = "extra == 'resembleai'" }, { name = "pipecat-ai", extras = ["websockets-base"], marker = "extra == 'rime'" }, { name = "pipecat-ai", extras = ["websockets-base"], marker = "extra == 'sarvam'" }, @@ -4763,7 +4759,7 @@ requires-dist = [ { name = "wait-for2", marker = "python_full_version < '3.12'", specifier = ">=0.4.1" }, { name = "websockets", marker = "extra == 'websockets-base'", specifier = ">=13.1,<16.0" }, ] -provides-extras = ["aic", "anthropic", "assemblyai", "asyncai", "aws", "aws-nova-sonic", "azure", "cartesia", "camb", "cerebras", "daily", "deepgram", "deepseek", "elevenlabs", "fal", "fireworks", "fish", "gladia", "google", "gradium", "grok", "groq", "gstreamer", "heygen", "hume", "inworld", "koala", "kokoro", "krisp", "langchain", "livekit", "lmnt", "local", "local-smart-turn", "mcp", "mem0", "mistral", "mlx-whisper", "moondream", "neuphonic", "noisereduce", "nvidia", "openai", "rnnoise", "openpipe", "openrouter", "perplexity", "piper", "playht", "qwen", "remote-smart-turn", "resembleai", "rime", "riva", "runner", "sagemaker", "sambanova", "sarvam", "sentry", "silero", "simli", "soniox", "soundfile", "speechmatics", "strands", "tavus", "together", "tracing", "ultravox", "webrtc", "websocket", "websockets-base", "whisper"] +provides-extras = ["aic", "anthropic", "assemblyai", "asyncai", "aws", "aws-nova-sonic", "azure", "cartesia", "camb", "cerebras", "daily", "deepgram", "deepseek", "elevenlabs", "fal", "fireworks", "fish", "gladia", "google", "gradium", "grok", "groq", "gstreamer", "heygen", "hume", "inworld", "koala", "kokoro", "krisp", "langchain", "livekit", "lmnt", "local", "local-smart-turn", "mcp", "mem0", "mistral", "mlx-whisper", "moondream", "neuphonic", "noisereduce", "nvidia", "openai", "rnnoise", "openpipe", "openrouter", "perplexity", "piper", "qwen", "remote-smart-turn", "resembleai", "rime", "riva", "runner", "sagemaker", "sambanova", "sarvam", "sentry", "silero", "simli", "soniox", "soundfile", "speechmatics", "strands", "tavus", "together", "tracing", "ultravox", "webrtc", "websocket", "websockets-base", "whisper"] [package.metadata.requires-dev] dev = [ From 27940d83a2e39a4de8becdd8e434cd6d62fa3001 Mon Sep 17 00:00:00 2001 From: Paul Kompfner Date: Wed, 25 Feb 2026 09:41:23 -0500 Subject: [PATCH 0639/1060] Make it so that `AIService` is the exclusive "syncer" of model name to metrics. MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit The only (rare) exception—where a service directly still needs to directly call `self._sync_model_name_to_metrics()`—is when the model name need to be "pulled" from another field (or nested field) in settings up to settings.model on a settings update. This only occurs in Deepgram services, where we use the voice as the model name. This change has the side-effect of bringing model name to metrics for a number of services that were accidentally omitting it before. --- COMMUNITY_INTEGRATIONS.md | 13 +- src/pipecat/services/ai_service.py | 20 +-- src/pipecat/services/anthropic/llm.py | 52 ++++---- src/pipecat/services/assemblyai/stt.py | 14 +- src/pipecat/services/asyncai/tts.py | 53 ++++---- src/pipecat/services/aws/llm.py | 39 +++--- src/pipecat/services/aws/nova_sonic/llm.py | 36 ++--- src/pipecat/services/aws/stt.py | 20 +-- src/pipecat/services/aws/tts.py | 31 +++-- src/pipecat/services/azure/image.py | 15 ++- src/pipecat/services/azure/stt.py | 18 ++- src/pipecat/services/azure/tts.py | 60 ++++++--- src/pipecat/services/camb/tts.py | 28 ++-- src/pipecat/services/cartesia/stt.py | 24 ++-- src/pipecat/services/cartesia/tts.py | 69 +++++----- src/pipecat/services/deepgram/flux/stt.py | 28 ++-- src/pipecat/services/deepgram/stt.py | 15 ++- .../services/deepgram/stt_sagemaker.py | 21 +-- src/pipecat/services/deepgram/tts.py | 31 ++--- .../services/deepgram/tts_sagemaker.py | 13 +- src/pipecat/services/elevenlabs/stt.py | 50 ++++--- src/pipecat/services/elevenlabs/tts.py | 71 +++++----- src/pipecat/services/fal/image.py | 15 ++- src/pipecat/services/fal/stt.py | 22 +-- src/pipecat/services/fish/tts.py | 38 +++--- src/pipecat/services/gladia/stt.py | 54 ++++---- .../services/google/gemini_live/llm.py | 57 ++++---- src/pipecat/services/google/image.py | 19 ++- src/pipecat/services/google/llm.py | 36 ++--- src/pipecat/services/google/stt.py | 39 +++--- src/pipecat/services/google/tts.py | 86 ++++++------ src/pipecat/services/gradium/stt.py | 23 ++-- src/pipecat/services/gradium/tts.py | 16 +-- src/pipecat/services/grok/realtime/llm.py | 32 ++--- src/pipecat/services/groq/tts.py | 23 ++-- src/pipecat/services/hathora/stt.py | 17 ++- src/pipecat/services/hathora/tts.py | 18 ++- src/pipecat/services/hume/tts.py | 19 +-- src/pipecat/services/image_service.py | 14 +- src/pipecat/services/inworld/tts.py | 61 ++++----- src/pipecat/services/kokoro/tts.py | 19 +-- src/pipecat/services/llm_service.py | 16 ++- src/pipecat/services/lmnt/tts.py | 13 +- src/pipecat/services/minimax/tts.py | 44 +++--- src/pipecat/services/moondream/vision.py | 16 ++- src/pipecat/services/neuphonic/tts.py | 43 +++--- src/pipecat/services/nvidia/stt.py | 47 ++++--- src/pipecat/services/nvidia/tts.py | 20 +-- src/pipecat/services/openai/base_llm.py | 34 ++--- src/pipecat/services/openai/image.py | 15 ++- src/pipecat/services/openai/realtime/llm.py | 33 ++--- src/pipecat/services/openai/stt.py | 12 +- src/pipecat/services/openai/tts.py | 21 +-- .../services/openai_realtime_beta/openai.py | 33 ++--- src/pipecat/services/piper/tts.py | 13 +- src/pipecat/services/resembleai/tts.py | 16 +-- src/pipecat/services/rime/tts.py | 126 +++++++++--------- src/pipecat/services/sarvam/stt.py | 24 ++-- src/pipecat/services/sarvam/tts.py | 110 +++++++-------- src/pipecat/services/settings.py | 22 +++ src/pipecat/services/soniox/stt.py | 29 ++-- src/pipecat/services/speechmatics/stt.py | 38 +++--- src/pipecat/services/speechmatics/tts.py | 21 +-- src/pipecat/services/stt_service.py | 11 +- src/pipecat/services/tts_service.py | 11 +- src/pipecat/services/ultravox/llm.py | 28 ++-- src/pipecat/services/vision_service.py | 14 +- src/pipecat/services/whisper/base_stt.py | 23 ++-- src/pipecat/services/whisper/stt.py | 41 +++--- src/pipecat/services/xtts/tts.py | 16 ++- 70 files changed, 1200 insertions(+), 1019 deletions(-) diff --git a/COMMUNITY_INTEGRATIONS.md b/COMMUNITY_INTEGRATIONS.md index e11c79f31..ff8d08ea5 100644 --- a/COMMUNITY_INTEGRATIONS.md +++ b/COMMUNITY_INTEGRATIONS.md @@ -257,15 +257,16 @@ The service stores its current settings in `self._settings` and declares the typ ```python class MySTTService(STTService): - _settings: MySTTSettings def __init__(self, *, model: str, language: str, region: str, **kwargs): - super().__init__(**kwargs) - # Initial value must be provided for every field in self._settings - # before service is started - self._settings = MySTTSettings(model=model, language=language, region=region) - self._sync_model_name_to_metrics() + # An initial value should be provided for every settings field. + # This will be validated at service start. + # (If you track sample_rate, it can be a placeholder value like 0; see + # "Sample Rate Handling"). + super().__init__( + settings=MySTTSettings(model=model, language=language, region=region), **kwargs + ) ``` To react to runtime setting changes, override `_update_settings`. The base implementation applies the delta to `self._settings` and returns a `dict` mapping each changed field name to its **pre-update** value. Your override should call `super()` first, then act on the changed fields. A common implementation might look like: diff --git a/src/pipecat/services/ai_service.py b/src/pipecat/services/ai_service.py index f092c2b49..c4e45a417 100644 --- a/src/pipecat/services/ai_service.py +++ b/src/pipecat/services/ai_service.py @@ -35,14 +35,21 @@ class AIService(FrameProcessor): this base infrastructure. """ - def __init__(self, **kwargs): + def __init__(self, settings: ServiceSettings | None = None, **kwargs): """Initialize the AI service. Args: + settings: The runtime-updatable settings for the AI service. **kwargs: Additional arguments passed to the parent FrameProcessor. """ super().__init__(**kwargs) - self._settings: ServiceSettings = ServiceSettings() # Here in case subclass doesn't implement more specific settings (hopefully shouldn't happen) + self._settings: ServiceSettings = ( + settings + # Here in case subclass doesn't implement more specific settings + # (which hopefully should be rare) + or ServiceSettings() + ) + self._sync_model_name_to_metrics() self._session_properties: Dict[str, Any] = {} self._tracing_enabled: bool = False self._tracing_context = None @@ -54,15 +61,12 @@ class AIService(FrameProcessor): of truth for it in `self._settings.model`. This method is just for syncing the model name to the metrics data. - TODO: as a next step we should make it so that service classes pass - model into `super().__init__` and `AIService` can be responsible for - syncing its initial value to metrics, just as it's responsible for - syncing any updates to its value to metrics via `_update_settings`. - Args: model: The name of the AI model to use. """ - self.set_core_metrics_data(MetricsData(processor=self.name, model=self._settings.model)) + self.set_core_metrics_data( + MetricsData(processor=self.name, model=self._settings.model or "") + ) async def start(self, frame: StartFrame): """Start the AI service. diff --git a/src/pipecat/services/anthropic/llm.py b/src/pipecat/services/anthropic/llm.py index 047159515..03190ef99 100644 --- a/src/pipecat/services/anthropic/llm.py +++ b/src/pipecat/services/anthropic/llm.py @@ -232,37 +232,39 @@ class AnthropicLLMService(LLMService): retry_on_timeout: Whether to retry the request once if it times out. **kwargs: Additional arguments passed to parent LLMService. """ - super().__init__(**kwargs) params = params or AnthropicLLMService.InputParams() + + super().__init__( + settings=AnthropicLLMSettings( + model=model, + max_tokens=params.max_tokens, + enable_prompt_caching=( + params.enable_prompt_caching + if params.enable_prompt_caching is not None + else ( + params.enable_prompt_caching_beta + if params.enable_prompt_caching_beta is not None + else False + ) + ), + temperature=params.temperature, + top_k=params.top_k, + top_p=params.top_p, + frequency_penalty=None, + presence_penalty=None, + seed=None, + filter_incomplete_user_turns=False, + user_turn_completion_config=None, + thinking=params.thinking, + extra=params.extra if isinstance(params.extra, dict) else {}, + ), + **kwargs, + ) self._client = client or AsyncAnthropic( api_key=api_key ) # if the client is provided, use it and remove it, otherwise create a new one self._retry_timeout_secs = retry_timeout_secs self._retry_on_timeout = retry_on_timeout - self._settings = AnthropicLLMSettings( - model=model, - max_tokens=params.max_tokens, - enable_prompt_caching=( - params.enable_prompt_caching - if params.enable_prompt_caching is not None - else ( - params.enable_prompt_caching_beta - if params.enable_prompt_caching_beta is not None - else False - ) - ), - temperature=params.temperature, - top_k=params.top_k, - top_p=params.top_p, - frequency_penalty=None, - presence_penalty=None, - seed=None, - filter_incomplete_user_turns=False, - user_turn_completion_config=None, - thinking=params.thinking, - extra=params.extra if isinstance(params.extra, dict) else {}, - ) - self._sync_model_name_to_metrics() def can_generate_metrics(self) -> bool: """Check if this service can generate usage metrics. diff --git a/src/pipecat/services/assemblyai/stt.py b/src/pipecat/services/assemblyai/stt.py index 44ae123b7..a89f5fe52 100644 --- a/src/pipecat/services/assemblyai/stt.py +++ b/src/pipecat/services/assemblyai/stt.py @@ -111,15 +111,17 @@ class AssemblyAISTTService(WebsocketSTTService): connection_params = self._configure_manual_turn_mode(connection_params) super().__init__( - sample_rate=connection_params.sample_rate, ttfs_p99_latency=ttfs_p99_latency, **kwargs + sample_rate=connection_params.sample_rate, + ttfs_p99_latency=ttfs_p99_latency, + settings=AssemblyAISTTSettings( + model=None, + language=language, + connection_params=connection_params, + ), + **kwargs, ) self._api_key = api_key - self._settings = AssemblyAISTTSettings( - model=None, - language=language, - connection_params=connection_params, - ) self._api_endpoint_base_url = api_endpoint_base_url self._vad_force_turn_endpoint = vad_force_turn_endpoint diff --git a/src/pipecat/services/asyncai/tts.py b/src/pipecat/services/asyncai/tts.py index f1f73b7ff..334f80d80 100644 --- a/src/pipecat/services/asyncai/tts.py +++ b/src/pipecat/services/asyncai/tts.py @@ -147,30 +147,29 @@ class AsyncAITTSService(AudioContextTTSService): aggregate_sentences: Whether to aggregate sentences within the TTSService. **kwargs: Additional arguments passed to the parent service. """ + params = params or AsyncAITTSService.InputParams() + super().__init__( aggregate_sentences=aggregate_sentences, pause_frame_processing=True, push_stop_frames=True, sample_rate=sample_rate, + settings=AsyncAITTSSettings( + model=model, + voice=voice_id, + output_container=container, + output_encoding=encoding, + output_sample_rate=0, + language=self.language_to_service_language(params.language) + if params.language + else None, + ), **kwargs, ) - params = params or AsyncAITTSService.InputParams() - self._api_key = api_key self._api_version = version self._url = url - self._settings = AsyncAITTSSettings( - model=model, - voice=voice_id, - output_container=container, - output_encoding=encoding, - output_sample_rate=0, - language=self.language_to_service_language(params.language) - if params.language - else None, - ) - self._sync_model_name_to_metrics() self._receive_task = None self._keepalive_task = None @@ -501,24 +500,26 @@ class AsyncAIHttpTTSService(TTSService): params: Additional input parameters for voice customization. **kwargs: Additional arguments passed to the parent TTSService. """ - super().__init__(sample_rate=sample_rate, **kwargs) - params = params or AsyncAIHttpTTSService.InputParams() + super().__init__( + sample_rate=sample_rate, + settings=AsyncAITTSSettings( + model=model, + voice=voice_id, + output_container=container, + output_encoding=encoding, + output_sample_rate=0, + language=self.language_to_service_language(params.language) + if params.language + else None, + ), + **kwargs, + ) + self._api_key = api_key self._base_url = url self._api_version = version - self._settings = AsyncAITTSSettings( - model=model, - voice=voice_id, - output_container=container, - output_encoding=encoding, - output_sample_rate=0, - language=self.language_to_service_language(params.language) - if params.language - else None, - ) - self._sync_model_name_to_metrics() self._session = aiohttp_session diff --git a/src/pipecat/services/aws/llm.py b/src/pipecat/services/aws/llm.py index 34e869c69..540ac4a8e 100644 --- a/src/pipecat/services/aws/llm.py +++ b/src/pipecat/services/aws/llm.py @@ -797,10 +797,28 @@ class AWSBedrockLLMService(LLMService): retry_on_timeout: Whether to retry the request once if it times out. **kwargs: Additional arguments passed to parent LLMService. """ - super().__init__(**kwargs) - params = params or AWSBedrockLLMService.InputParams() + super().__init__( + settings=AWSBedrockLLMSettings( + model=model, + max_tokens=params.max_tokens, + temperature=params.temperature, + top_p=params.top_p, + top_k=None, + frequency_penalty=None, + presence_penalty=None, + seed=None, + filter_incomplete_user_turns=False, + user_turn_completion_config=None, + latency=params.latency, + additional_model_request_fields=params.additional_model_request_fields + if isinstance(params.additional_model_request_fields, dict) + else {}, + ), + **kwargs, + ) + # Initialize the AWS Bedrock client if not client_config: client_config = Config( @@ -822,23 +840,6 @@ class AWSBedrockLLMService(LLMService): self._retry_timeout_secs = retry_timeout_secs self._retry_on_timeout = retry_on_timeout - self._settings = AWSBedrockLLMSettings( - model=model, - max_tokens=params.max_tokens, - temperature=params.temperature, - top_p=params.top_p, - top_k=None, - frequency_penalty=None, - presence_penalty=None, - seed=None, - filter_incomplete_user_turns=False, - user_turn_completion_config=None, - latency=params.latency, - additional_model_request_fields=params.additional_model_request_fields - if isinstance(params.additional_model_request_fields, dict) - else {}, - ) - self._sync_model_name_to_metrics() logger.info(f"Using AWS Bedrock model: {model}") diff --git a/src/pipecat/services/aws/nova_sonic/llm.py b/src/pipecat/services/aws/nova_sonic/llm.py index e51a1842c..29612e593 100644 --- a/src/pipecat/services/aws/nova_sonic/llm.py +++ b/src/pipecat/services/aws/nova_sonic/llm.py @@ -254,28 +254,30 @@ class AWSNovaSonicLLMService(LLMService): **kwargs: Additional arguments passed to the parent LLMService. """ - super().__init__(**kwargs) + params = params or Params() + + super().__init__( + settings=AWSNovaSonicLLMSettings( + model=model, + voice_id=voice_id, + temperature=params.temperature, + max_tokens=params.max_tokens, + top_p=params.top_p, + top_k=None, + frequency_penalty=None, + presence_penalty=None, + seed=None, + filter_incomplete_user_turns=False, + user_turn_completion_config=None, + endpointing_sensitivity=params.endpointing_sensitivity, + ), + **kwargs, + ) self._secret_access_key = secret_access_key self._access_key_id = access_key_id self._session_token = session_token self._region = region self._client: Optional[BedrockRuntimeClient] = None - params = params or Params() - self._settings = AWSNovaSonicLLMSettings( - model=model, - voice_id=voice_id, - temperature=params.temperature, - max_tokens=params.max_tokens, - top_p=params.top_p, - top_k=None, - frequency_penalty=None, - presence_penalty=None, - seed=None, - filter_incomplete_user_turns=False, - user_turn_completion_config=None, - endpointing_sensitivity=params.endpointing_sensitivity, - ) - self._sync_model_name_to_metrics() # Audio I/O config (hardware settings, not runtime-tunable) self._input_sample_rate = params.input_sample_rate diff --git a/src/pipecat/services/aws/stt.py b/src/pipecat/services/aws/stt.py index 1d8ae84f5..7c3fb398e 100644 --- a/src/pipecat/services/aws/stt.py +++ b/src/pipecat/services/aws/stt.py @@ -99,15 +99,17 @@ class AWSTranscribeSTTService(WebsocketSTTService): Override for your deployment. See https://github.com/pipecat-ai/stt-benchmark **kwargs: Additional arguments passed to parent STTService class. """ - super().__init__(ttfs_p99_latency=ttfs_p99_latency, **kwargs) - - self._settings = AWSTranscribeSTTSettings( - language=self.language_to_service_language(language) or "en-US", - sample_rate=sample_rate, - media_encoding="linear16", - number_of_channels=1, - show_speaker_label=False, - enable_channel_identification=False, + super().__init__( + ttfs_p99_latency=ttfs_p99_latency, + settings=AWSTranscribeSTTSettings( + language=self.language_to_service_language(language) or "en-US", + sample_rate=sample_rate, + media_encoding="linear16", + number_of_channels=1, + show_speaker_label=False, + enable_channel_identification=False, + ), + **kwargs, ) # Validate sample rate - AWS Transcribe only supports 8000 Hz or 16000 Hz diff --git a/src/pipecat/services/aws/tts.py b/src/pipecat/services/aws/tts.py index 8b06ad7e9..017477a7a 100644 --- a/src/pipecat/services/aws/tts.py +++ b/src/pipecat/services/aws/tts.py @@ -195,10 +195,25 @@ class AWSPollyTTSService(TTSService): params: Additional input parameters for voice customization. **kwargs: Additional arguments passed to parent TTSService class. """ - super().__init__(sample_rate=sample_rate, **kwargs) - params = params or AWSPollyTTSService.InputParams() + super().__init__( + sample_rate=sample_rate, + settings=AWSPollyTTSSettings( + model=None, + voice=voice_id, + engine=params.engine, + language=self.language_to_service_language(params.language) + if params.language + else "en-US", + pitch=params.pitch, + rate=params.rate, + volume=params.volume, + lexicon_names=params.lexicon_names, + ), + **kwargs, + ) + # Get credentials from environment variables if not provided self._aws_params = { "aws_access_key_id": aws_access_key_id or os.getenv("AWS_ACCESS_KEY_ID"), @@ -208,18 +223,6 @@ class AWSPollyTTSService(TTSService): } self._aws_session = aioboto3.Session() - self._settings = AWSPollyTTSSettings( - model=None, - voice=voice_id, - engine=params.engine, - language=self.language_to_service_language(params.language) - if params.language - else "en-US", - pitch=params.pitch, - rate=params.rate, - volume=params.volume, - lexicon_names=params.lexicon_names, - ) self._resampler = create_stream_resampler() diff --git a/src/pipecat/services/azure/image.py b/src/pipecat/services/azure/image.py index f5ce4a9f1..66cc28504 100644 --- a/src/pipecat/services/azure/image.py +++ b/src/pipecat/services/azure/image.py @@ -12,6 +12,7 @@ using REST endpoints for creating images from text prompts. import asyncio import io +from dataclasses import dataclass from typing import AsyncGenerator import aiohttp @@ -19,6 +20,16 @@ from PIL import Image from pipecat.frames.frames import ErrorFrame, Frame, URLImageRawFrame from pipecat.services.image_service import ImageGenService +from pipecat.services.settings import ImageGenSettings + + +@dataclass +class AzureImageGenSettings(ImageGenSettings): + """Settings for the Azure image generation service. + + Parameters: + model: Azure image generation model identifier. + """ class AzureImageGenServiceREST(ImageGenService): @@ -49,13 +60,11 @@ class AzureImageGenServiceREST(ImageGenService): aiohttp_session: Shared aiohttp session for HTTP requests. api_version: Azure API version string. Defaults to "2023-06-01-preview". """ - super().__init__() + super().__init__(settings=AzureImageGenSettings(model=model)) self._api_key = api_key self._azure_endpoint = endpoint self._api_version = api_version - self._settings.model = model - self._sync_model_name_to_metrics() self._image_size = image_size self._aiohttp_session = aiohttp_session diff --git a/src/pipecat/services/azure/stt.py b/src/pipecat/services/azure/stt.py index 096f236a6..c1a38ec0c 100644 --- a/src/pipecat/services/azure/stt.py +++ b/src/pipecat/services/azure/stt.py @@ -96,7 +96,17 @@ class AzureSTTService(STTService): Override for your deployment. See https://github.com/pipecat-ai/stt-benchmark **kwargs: Additional arguments passed to parent STTService. """ - super().__init__(sample_rate=sample_rate, ttfs_p99_latency=ttfs_p99_latency, **kwargs) + super().__init__( + sample_rate=sample_rate, + ttfs_p99_latency=ttfs_p99_latency, + settings=AzureSTTSettings( + model=None, + region=region, + language=language_to_azure_language(language), + sample_rate=sample_rate, + ), + **kwargs, + ) self._speech_config = SpeechConfig( subscription=api_key, @@ -109,12 +119,6 @@ class AzureSTTService(STTService): self._audio_stream = None self._speech_recognizer = None - self._settings = AzureSTTSettings( - model=None, - region=region, - language=language_to_azure_language(language), - sample_rate=sample_rate, - ) def can_generate_metrics(self) -> bool: """Check if this service can generate performance metrics. diff --git a/src/pipecat/services/azure/tts.py b/src/pipecat/services/azure/tts.py index 3a176055d..b3534b28e 100644 --- a/src/pipecat/services/azure/tts.py +++ b/src/pipecat/services/azure/tts.py @@ -141,7 +141,6 @@ class AzureBaseTTSService: api_key: str, region: str, voice: str = "en-US-SaraNeural", - params: Optional[InputParams] = None, ): """Initialize Azure-specific configuration. @@ -151,25 +150,7 @@ class AzureBaseTTSService: api_key: Azure Cognitive Services subscription key. region: Azure region identifier (e.g., "eastus", "westus2"). voice: Voice name to use for synthesis. Defaults to "en-US-SaraNeural". - params: Voice and synthesis parameters configuration. """ - params = params or AzureBaseTTSService.InputParams() - - self._settings = AzureTTSSettings( - model=None, - emphasis=params.emphasis, - language=self.language_to_service_language(params.language) - if params.language - else "en-US", - pitch=params.pitch, - rate=params.rate, - role=params.role, - style=params.style, - style_degree=params.style_degree, - voice=voice, - volume=params.volume, - ) - self._api_key = api_key self._region = region self._speech_synthesizer = None @@ -289,6 +270,8 @@ class AzureTTSService(TTSService, AzureBaseTTSService): aggregate_sentences: Whether to aggregate sentences before synthesis. **kwargs: Additional arguments passed to the parent TTSService. """ + params = params or AzureBaseTTSService.InputParams() + super().__init__( aggregate_sentences=aggregate_sentences, push_text_frames=False, # We'll push text frames based on word timestamps @@ -296,11 +279,25 @@ class AzureTTSService(TTSService, AzureBaseTTSService): pause_frame_processing=True, supports_word_timestamps=True, sample_rate=sample_rate, + settings=AzureTTSSettings( + model=None, + emphasis=params.emphasis, + language=self.language_to_service_language(params.language) + if params.language + else "en-US", + pitch=params.pitch, + rate=params.rate, + role=params.role, + style=params.style, + style_degree=params.style_degree, + voice=voice, + volume=params.volume, + ), **kwargs, ) # Initialize Azure-specific functionality from mixin - self._init_azure_base(api_key=api_key, region=region, voice=voice, params=params) + self._init_azure_base(api_key=api_key, region=region, voice=voice) self._speech_config = None self._speech_synthesizer = None @@ -734,10 +731,29 @@ class AzureHttpTTSService(TTSService, AzureBaseTTSService): params: Voice and synthesis parameters configuration. **kwargs: Additional arguments passed to parent TTSService. """ - super().__init__(sample_rate=sample_rate, **kwargs) + params = params or AzureBaseTTSService.InputParams() + + super().__init__( + sample_rate=sample_rate, + settings=AzureTTSSettings( + model=None, + emphasis=params.emphasis, + language=self.language_to_service_language(params.language) + if params.language + else "en-US", + pitch=params.pitch, + rate=params.rate, + role=params.role, + style=params.style, + style_degree=params.style_degree, + voice=voice, + volume=params.volume, + ), + **kwargs, + ) # Initialize Azure-specific functionality from mixin - self._init_azure_base(api_key=api_key, region=region, voice=voice, params=params) + self._init_azure_base(api_key=api_key, region=region, voice=voice) self._speech_config = None self._speech_synthesizer = None diff --git a/src/pipecat/services/camb/tts.py b/src/pipecat/services/camb/tts.py index a2887df28..75b299569 100644 --- a/src/pipecat/services/camb/tts.py +++ b/src/pipecat/services/camb/tts.py @@ -213,11 +213,6 @@ class CambTTSService(TTSService): params: Additional voice parameters. If None, uses defaults. **kwargs: Additional arguments passed to parent TTSService. """ - super().__init__(sample_rate=sample_rate, **kwargs) - - self._api_key = api_key - self._timeout = timeout - params = params or CambTTSService.InputParams() # Warn if sample rate doesn't match model's supported rate @@ -227,16 +222,23 @@ class CambTTSService(TTSService): f"sample rate. Current rate of {sample_rate}Hz may cause issues." ) - # Build settings - self._settings = CambTTSSettings( - model=model, - voice=voice_id, - language=( - self.language_to_service_language(params.language) if params.language else "en-us" + super().__init__( + sample_rate=sample_rate, + settings=CambTTSSettings( + model=model, + voice=voice_id, + language=( + self.language_to_service_language(params.language) + if params.language + else "en-us" + ), + user_instructions=params.user_instructions, ), - user_instructions=params.user_instructions, + **kwargs, ) - self._sync_model_name_to_metrics() + + self._api_key = api_key + self._timeout = timeout self._client = None diff --git a/src/pipecat/services/cartesia/stt.py b/src/pipecat/services/cartesia/stt.py index 20ff04963..526fc9116 100644 --- a/src/pipecat/services/cartesia/stt.py +++ b/src/pipecat/services/cartesia/stt.py @@ -173,13 +173,6 @@ class CartesiaSTTService(WebsocketSTTService): **kwargs: Additional arguments passed to parent STTService. """ sample_rate = sample_rate or (live_options.sample_rate if live_options else None) - super().__init__( - sample_rate=sample_rate, - ttfs_p99_latency=ttfs_p99_latency, - keepalive_timeout=120, - keepalive_interval=30, - **kwargs, - ) default_options = CartesiaLiveOptions( model="ink-whisper", @@ -196,12 +189,19 @@ class CartesiaSTTService(WebsocketSTTService): k: v for k, v in merged_options.items() if not isinstance(v, str) or v != "None" } - self._settings = CartesiaSTTSettings( - model=merged_options["model"], - language=merged_options.get("language"), - encoding=merged_options.get("encoding", "pcm_s16le"), + super().__init__( + sample_rate=sample_rate, + ttfs_p99_latency=ttfs_p99_latency, + keepalive_timeout=120, + keepalive_interval=30, + settings=CartesiaSTTSettings( + model=merged_options["model"], + language=merged_options.get("language"), + encoding=merged_options.get("encoding", "pcm_s16le"), + ), + **kwargs, ) - self._sync_model_name_to_metrics() + self._api_key = api_key self._base_url = base_url or "api.cartesia.ai" self._receive_task = None diff --git a/src/pipecat/services/cartesia/tts.py b/src/pipecat/services/cartesia/tts.py index f45e7c54f..edf838e59 100644 --- a/src/pipecat/services/cartesia/tts.py +++ b/src/pipecat/services/cartesia/tts.py @@ -305,6 +305,8 @@ class CartesiaTTSService(AudioContextTTSService): # if we're interrupted. Cartesia gives us word-by-word timestamps. We # can use those to generate text frames ourselves aligned with the # playout timing of the audio! + params = params or CartesiaTTSService.InputParams() + super().__init__( aggregate_sentences=aggregate_sentences, push_text_frames=False, @@ -312,6 +314,20 @@ class CartesiaTTSService(AudioContextTTSService): supports_word_timestamps=True, sample_rate=sample_rate, text_aggregator=text_aggregator, + settings=CartesiaTTSSettings( + model=model, + output_container=container, + output_encoding=encoding, + output_sample_rate=0, + language=self.language_to_service_language(params.language) + if params.language + else None, + speed=params.speed, + emotion=params.emotion, + generation_config=params.generation_config, + pronunciation_dict_id=params.pronunciation_dict_id, + voice=voice_id, + ), **kwargs, ) @@ -323,26 +339,9 @@ class CartesiaTTSService(AudioContextTTSService): # and insert these tags for the purpose of the TTS service alone. self._text_aggregator = SkipTagsAggregator([("", "")]) - params = params or CartesiaTTSService.InputParams() - self._api_key = api_key self._cartesia_version = cartesia_version self._url = url - self._settings = CartesiaTTSSettings( - model=model, - output_container=container, - output_encoding=encoding, - output_sample_rate=0, - language=self.language_to_service_language(params.language) - if params.language - else None, - speed=params.speed, - emotion=params.emotion, - generation_config=params.generation_config, - pronunciation_dict_id=params.pronunciation_dict_id, - voice=voice_id, - ) - self._sync_model_name_to_metrics() self._receive_task = None @@ -727,28 +726,30 @@ class CartesiaHttpTTSService(TTSService): params: Additional input parameters for voice customization. **kwargs: Additional arguments passed to the parent TTSService. """ - super().__init__(sample_rate=sample_rate, **kwargs) - params = params or CartesiaHttpTTSService.InputParams() + super().__init__( + sample_rate=sample_rate, + settings=CartesiaTTSSettings( + model=model, + voice=voice_id, + output_container=container, + output_encoding=encoding, + output_sample_rate=0, + language=self.language_to_service_language(params.language) + if params.language + else None, + speed=params.speed, + emotion=params.emotion, + generation_config=params.generation_config, + pronunciation_dict_id=params.pronunciation_dict_id, + ), + **kwargs, + ) + self._api_key = api_key self._base_url = base_url self._cartesia_version = cartesia_version - self._settings = CartesiaTTSSettings( - model=model, - voice=voice_id, - output_container=container, - output_encoding=encoding, - output_sample_rate=0, - language=self.language_to_service_language(params.language) - if params.language - else None, - speed=params.speed, - emotion=params.emotion, - generation_config=params.generation_config, - pronunciation_dict_id=params.pronunciation_dict_id, - ) - self._sync_model_name_to_metrics() self._client = AsyncCartesia( api_key=api_key, diff --git a/src/pipecat/services/deepgram/flux/stt.py b/src/pipecat/services/deepgram/flux/stt.py index f0018d5c8..d509b267e 100644 --- a/src/pipecat/services/deepgram/flux/stt.py +++ b/src/pipecat/services/deepgram/flux/stt.py @@ -207,26 +207,24 @@ class DeepgramFluxSTTService(WebsocketSTTService): # was never destroyed. # So we can keep it here as false, because inside the method send_with_retry, it will # already try to reconnect if needed. + params = params or DeepgramFluxSTTService.InputParams() super().__init__( sample_rate=sample_rate, reconnect_on_error=False, + settings=DeepgramFluxSTTSettings( + model=model, + language=Language.EN, + encoding=flux_encoding, + eager_eot_threshold=params.eager_eot_threshold, + eot_threshold=params.eot_threshold, + eot_timeout_ms=params.eot_timeout_ms, + keyterm=params.keyterm or [], + mip_opt_out=params.mip_opt_out, + tag=params.tag or [], + min_confidence=params.min_confidence, + ), **kwargs, ) - - params = params or DeepgramFluxSTTService.InputParams() - self._settings = DeepgramFluxSTTSettings( - model=model, - language=Language.EN, - encoding=flux_encoding, - eager_eot_threshold=params.eager_eot_threshold, - eot_threshold=params.eot_threshold, - eot_timeout_ms=params.eot_timeout_ms, - keyterm=params.keyterm or [], - mip_opt_out=params.mip_opt_out, - tag=params.tag or [], - min_confidence=params.min_confidence, - ) - self._sync_model_name_to_metrics() self._api_key = api_key self._url = url self._should_interrupt = should_interrupt diff --git a/src/pipecat/services/deepgram/stt.py b/src/pipecat/services/deepgram/stt.py index 0792ea3c9..aa5c2ce8d 100644 --- a/src/pipecat/services/deepgram/stt.py +++ b/src/pipecat/services/deepgram/stt.py @@ -117,7 +117,6 @@ class DeepgramSTTService(STTService): The `vad_events` option in LiveOptions is deprecated as of version 0.0.99 and will be removed in a future version. Please use the Silero VAD instead. """ sample_rate = sample_rate or (live_options.sample_rate if live_options else None) - super().__init__(sample_rate=sample_rate, ttfs_p99_latency=ttfs_p99_latency, **kwargs) if url: import warnings @@ -155,12 +154,16 @@ class DeepgramSTTService(STTService): merged_options["language"] = merged_options["language"].value merged_live_options = LiveOptions(**merged_options) - self._settings = DeepgramSTTSettings( - model=merged_options.get("model"), - language=merged_options.get("language"), - live_options=merged_live_options, + super().__init__( + sample_rate=sample_rate, + ttfs_p99_latency=ttfs_p99_latency, + settings=DeepgramSTTSettings( + model=merged_options.get("model"), + language=merged_options.get("language"), + live_options=merged_live_options, + ), + **kwargs, ) - self._sync_model_name_to_metrics() self._addons = addons self._should_interrupt = should_interrupt diff --git a/src/pipecat/services/deepgram/stt_sagemaker.py b/src/pipecat/services/deepgram/stt_sagemaker.py index 3820f8d84..bc5eebe37 100644 --- a/src/pipecat/services/deepgram/stt_sagemaker.py +++ b/src/pipecat/services/deepgram/stt_sagemaker.py @@ -115,10 +115,6 @@ class DeepgramSageMakerSTTService(STTService): **kwargs: Additional arguments passed to the parent STTService. """ sample_rate = sample_rate or (live_options.sample_rate if live_options else None) - super().__init__(sample_rate=sample_rate, ttfs_p99_latency=ttfs_p99_latency, **kwargs) - - self._endpoint_name = endpoint_name - self._region = region # Create default options similar to DeepgramSTTService default_options = LiveOptions( @@ -144,12 +140,19 @@ class DeepgramSageMakerSTTService(STTService): merged_options["language"] = merged_options["language"].value merged_live_options = LiveOptions(**merged_options) - self._settings = DeepgramSageMakerSTTSettings( - model=merged_options.get("model"), - language=merged_options.get("language"), - live_options=merged_live_options, + super().__init__( + sample_rate=sample_rate, + ttfs_p99_latency=ttfs_p99_latency, + settings=DeepgramSageMakerSTTSettings( + model=merged_options.get("model"), + language=merged_options.get("language"), + live_options=merged_live_options, + ), + **kwargs, ) - self._sync_model_name_to_metrics() + + self._endpoint_name = endpoint_name + self._region = region self._client: Optional[SageMakerBidiClient] = None self._response_task: Optional[asyncio.Task] = None diff --git a/src/pipecat/services/deepgram/tts.py b/src/pipecat/services/deepgram/tts.py index b3973bba2..c05b90868 100644 --- a/src/pipecat/services/deepgram/tts.py +++ b/src/pipecat/services/deepgram/tts.py @@ -101,18 +101,17 @@ class DeepgramTTSService(WebsocketTTSService): pause_frame_processing=True, push_stop_frames=True, append_trailing_space=True, + settings=DeepgramTTSSettings( + model=voice, + voice=voice, + language=None, + encoding=encoding, + ), **kwargs, ) self._api_key = api_key self._base_url = base_url - self._settings = DeepgramTTSSettings( - model=voice, - voice=voice, - language=None, - encoding=encoding, - ) - self._sync_model_name_to_metrics() self._receive_task = None self._context_id: Optional[str] = None @@ -394,18 +393,20 @@ class DeepgramHttpTTSService(TTSService): encoding: Audio encoding format. Defaults to "linear16". **kwargs: Additional arguments passed to parent TTSService class. """ - super().__init__(sample_rate=sample_rate, **kwargs) + super().__init__( + sample_rate=sample_rate, + settings=DeepgramTTSSettings( + model=voice, + voice=voice, + language=None, + encoding=encoding, + ), + **kwargs, + ) self._api_key = api_key self._session = aiohttp_session self._base_url = base_url - self._settings = DeepgramTTSSettings( - model=voice, - voice=voice, - language=None, - encoding=encoding, - ) - self._sync_model_name_to_metrics() def can_generate_metrics(self) -> bool: """Check if the service can generate metrics. diff --git a/src/pipecat/services/deepgram/tts_sagemaker.py b/src/pipecat/services/deepgram/tts_sagemaker.py index 798a62bf8..b583ce76c 100644 --- a/src/pipecat/services/deepgram/tts_sagemaker.py +++ b/src/pipecat/services/deepgram/tts_sagemaker.py @@ -99,18 +99,17 @@ class DeepgramSageMakerTTSService(TTSService): push_stop_frames=True, pause_frame_processing=True, append_trailing_space=True, + settings=DeepgramSageMakerTTSSettings( + model=voice, + voice=voice, + language=None, + encoding=encoding, + ), **kwargs, ) self._endpoint_name = endpoint_name self._region = region - self._settings = DeepgramSageMakerTTSSettings( - model=voice, - voice=voice, - language=None, - encoding=encoding, - ) - self._sync_model_name_to_metrics() self._client: Optional[SageMakerBidiClient] = None self._response_task: Optional[asyncio.Task] = None diff --git a/src/pipecat/services/elevenlabs/stt.py b/src/pipecat/services/elevenlabs/stt.py index 7a821304d..c3f4300f4 100644 --- a/src/pipecat/services/elevenlabs/stt.py +++ b/src/pipecat/services/elevenlabs/stt.py @@ -261,28 +261,26 @@ class ElevenLabsSTTService(SegmentedSTTService): Override for your deployment. See https://github.com/pipecat-ai/stt-benchmark **kwargs: Additional arguments passed to SegmentedSTTService. """ + params = params or ElevenLabsSTTService.InputParams() + super().__init__( sample_rate=sample_rate, ttfs_p99_latency=ttfs_p99_latency, + settings=ElevenLabsSTTSettings( + model=model, + language=self.language_to_service_language(params.language) + if params.language + else "eng", + tag_audio_events=params.tag_audio_events, + ), **kwargs, ) - params = params or ElevenLabsSTTService.InputParams() - self._api_key = api_key self._base_url = base_url self._session = aiohttp_session self._model_id = model - self._settings = ElevenLabsSTTSettings( - model=model, - language=self.language_to_service_language(params.language) - if params.language - else "eng", - tag_audio_events=params.tag_audio_events, - ) - self._sync_model_name_to_metrics() - def can_generate_metrics(self) -> bool: """Check if the service can generate processing metrics. @@ -500,16 +498,28 @@ class ElevenLabsRealtimeSTTService(WebsocketSTTService): Override for your deployment. See https://github.com/pipecat-ai/stt-benchmark **kwargs: Additional arguments passed to WebsocketSTTService. """ + params = params or ElevenLabsRealtimeSTTService.InputParams() + super().__init__( sample_rate=sample_rate, ttfs_p99_latency=ttfs_p99_latency, keepalive_timeout=10, keepalive_interval=5, + settings=ElevenLabsRealtimeSTTSettings( + model=model, + language=params.language_code, + commit_strategy=params.commit_strategy, + vad_silence_threshold_secs=params.vad_silence_threshold_secs, + vad_threshold=params.vad_threshold, + min_speech_duration_ms=params.min_speech_duration_ms, + min_silence_duration_ms=params.min_silence_duration_ms, + include_timestamps=params.include_timestamps, + enable_logging=params.enable_logging, + include_language_detection=params.include_language_detection, + ), **kwargs, ) - params = params or ElevenLabsRealtimeSTTService.InputParams() - self._api_key = api_key self._base_url = base_url self._model_id = model @@ -519,20 +529,6 @@ class ElevenLabsRealtimeSTTService(WebsocketSTTService): self._connected_event = asyncio.Event() self._connected_event.set() - self._settings = ElevenLabsRealtimeSTTSettings( - model=model, - language=params.language_code, - commit_strategy=params.commit_strategy, - vad_silence_threshold_secs=params.vad_silence_threshold_secs, - vad_threshold=params.vad_threshold, - min_speech_duration_ms=params.min_speech_duration_ms, - min_silence_duration_ms=params.min_silence_duration_ms, - include_timestamps=params.include_timestamps, - enable_logging=params.enable_logging, - include_language_detection=params.include_language_detection, - ) - self._sync_model_name_to_metrics() - def can_generate_metrics(self) -> bool: """Check if the service can generate processing metrics. diff --git a/src/pipecat/services/elevenlabs/tts.py b/src/pipecat/services/elevenlabs/tts.py index 25e1aa5dd..c68d005f1 100644 --- a/src/pipecat/services/elevenlabs/tts.py +++ b/src/pipecat/services/elevenlabs/tts.py @@ -394,6 +394,8 @@ class ElevenLabsTTSService(AudioContextTTSService): # Finally, ElevenLabs doesn't provide information on when the bot stops # speaking for a while, so we want the parent class to send TTSStopFrame # after a short period not receiving any audio. + params = params or ElevenLabsTTSService.InputParams() + super().__init__( aggregate_sentences=aggregate_sentences, push_text_frames=False, @@ -401,30 +403,27 @@ class ElevenLabsTTSService(AudioContextTTSService): pause_frame_processing=True, supports_word_timestamps=True, sample_rate=sample_rate, + settings=ElevenLabsTTSSettings( + model=model, + voice=voice_id, + language=( + self.language_to_service_language(params.language) if params.language else None + ), + stability=params.stability, + similarity_boost=params.similarity_boost, + style=params.style, + use_speaker_boost=params.use_speaker_boost, + speed=params.speed, + auto_mode=str(params.auto_mode).lower(), + enable_ssml_parsing=params.enable_ssml_parsing, + enable_logging=params.enable_logging, + apply_text_normalization=params.apply_text_normalization, + ), **kwargs, ) - params = params or ElevenLabsTTSService.InputParams() - self._api_key = api_key self._url = url - self._settings = ElevenLabsTTSSettings( - model=model, - voice=voice_id, - language=( - self.language_to_service_language(params.language) if params.language else None - ), - stability=params.stability, - similarity_boost=params.similarity_boost, - style=params.style, - use_speaker_boost=params.use_speaker_boost, - speed=params.speed, - auto_mode=str(params.auto_mode).lower(), - enable_ssml_parsing=params.enable_ssml_parsing, - enable_logging=params.enable_logging, - apply_text_normalization=params.apply_text_normalization, - ) - self._sync_model_name_to_metrics() self._output_format = "" # initialized in start() self._voice_settings = self._set_voice_settings() @@ -910,37 +909,35 @@ class ElevenLabsHttpTTSService(TTSService): aggregate_sentences: Whether to aggregate sentences within the TTSService. **kwargs: Additional arguments passed to the parent service. """ + params = params or ElevenLabsHttpTTSService.InputParams() + super().__init__( aggregate_sentences=aggregate_sentences, push_text_frames=False, push_stop_frames=True, supports_word_timestamps=True, sample_rate=sample_rate, + settings=ElevenLabsHttpTTSSettings( + model=model, + voice=voice_id, + language=self.language_to_service_language(params.language) + if params.language + else None, + optimize_streaming_latency=params.optimize_streaming_latency, + stability=params.stability, + similarity_boost=params.similarity_boost, + style=params.style, + use_speaker_boost=params.use_speaker_boost, + speed=params.speed, + apply_text_normalization=params.apply_text_normalization, + ), **kwargs, ) - params = params or ElevenLabsHttpTTSService.InputParams() - self._api_key = api_key self._base_url = base_url - self._params = params self._session = aiohttp_session - self._settings = ElevenLabsHttpTTSSettings( - model=model, - voice=voice_id, - language=self.language_to_service_language(params.language) - if params.language - else None, - optimize_streaming_latency=params.optimize_streaming_latency, - stability=params.stability, - similarity_boost=params.similarity_boost, - style=params.style, - use_speaker_boost=params.use_speaker_boost, - speed=params.speed, - apply_text_normalization=params.apply_text_normalization, - ) - self._sync_model_name_to_metrics() self._output_format = "" # initialized in start() self._voice_settings = self._set_voice_settings() self._pronunciation_dictionary_locators = params.pronunciation_dictionary_locators diff --git a/src/pipecat/services/fal/image.py b/src/pipecat/services/fal/image.py index fd9d9a22d..c16d31b43 100644 --- a/src/pipecat/services/fal/image.py +++ b/src/pipecat/services/fal/image.py @@ -13,6 +13,7 @@ for creating images from text prompts using various AI models. import asyncio import io import os +from dataclasses import dataclass from typing import AsyncGenerator, Dict, Optional, Union import aiohttp @@ -22,6 +23,7 @@ from pydantic import BaseModel from pipecat.frames.frames import ErrorFrame, Frame, URLImageRawFrame from pipecat.services.image_service import ImageGenService +from pipecat.services.settings import ImageGenSettings try: import fal_client @@ -31,6 +33,15 @@ except ModuleNotFoundError as e: raise Exception(f"Missing module: {e}") +@dataclass +class FalImageGenSettings(ImageGenSettings): + """Settings for the Fal image generation service. + + Parameters: + model: Fal.ai model identifier. + """ + + class FalImageGenService(ImageGenService): """Fal's image generation service. @@ -77,9 +88,7 @@ class FalImageGenService(ImageGenService): key: Optional API key for Fal.ai. If provided, sets FAL_KEY environment variable. **kwargs: Additional arguments passed to parent ImageGenService. """ - super().__init__(**kwargs) - self._settings.model = model - self._sync_model_name_to_metrics() + super().__init__(settings=FalImageGenSettings(model=model), **kwargs) self._params = params self._aiohttp_session = aiohttp_session if key: diff --git a/src/pipecat/services/fal/stt.py b/src/pipecat/services/fal/stt.py index 923c3c2ea..bf70c1c2a 100644 --- a/src/pipecat/services/fal/stt.py +++ b/src/pipecat/services/fal/stt.py @@ -207,14 +207,23 @@ class FalSTTService(SegmentedSTTService): Override for your deployment. See https://github.com/pipecat-ai/stt-benchmark **kwargs: Additional arguments passed to SegmentedSTTService. """ + params = params or FalSTTService.InputParams() + super().__init__( sample_rate=sample_rate, ttfs_p99_latency=ttfs_p99_latency, + settings=FalSTTSettings( + model=None, + language=self.language_to_service_language(params.language) + if params.language + else "en", + task=params.task, + chunk_level=params.chunk_level, + version=params.version, + ), **kwargs, ) - params = params or FalSTTService.InputParams() - if api_key: os.environ["FAL_KEY"] = api_key elif "FAL_KEY" not in os.environ: @@ -223,15 +232,6 @@ class FalSTTService(SegmentedSTTService): ) self._fal_client = fal_client.AsyncClient(key=api_key or os.getenv("FAL_KEY")) - self._settings = FalSTTSettings( - model=None, - language=self.language_to_service_language(params.language) - if params.language - else "en", - task=params.task, - chunk_level=params.chunk_level, - version=params.version, - ) def can_generate_metrics(self) -> bool: """Check if the service can generate processing metrics. diff --git a/src/pipecat/services/fish/tts.py b/src/pipecat/services/fish/tts.py index 1927b6cac..9f9d753de 100644 --- a/src/pipecat/services/fish/tts.py +++ b/src/pipecat/services/fish/tts.py @@ -138,13 +138,6 @@ class FishAudioTTSService(InterruptibleTTSService): params: Additional input parameters for voice customization. **kwargs: Additional arguments passed to the parent service. """ - super().__init__( - push_stop_frames=True, - pause_frame_processing=True, - sample_rate=sample_rate, - **kwargs, - ) - params = params or FishAudioTTSService.InputParams() # Validation for model and reference_id parameters @@ -169,25 +162,30 @@ class FishAudioTTSService(InterruptibleTTSService): ) reference_id = model + super().__init__( + push_stop_frames=True, + pause_frame_processing=True, + sample_rate=sample_rate, + settings=FishAudioTTSSettings( + model=model_id, + voice=reference_id, + fish_sample_rate=0, + latency=params.latency, + format=output_format, + normalize=params.normalize, + prosody_speed=params.prosody_speed, + prosody_volume=params.prosody_volume, + reference_id=reference_id, + ), + **kwargs, + ) + self._api_key = api_key self._base_url = "wss://api.fish.audio/v1/tts/live" self._websocket = None self._receive_task = None self._request_id = None - self._settings = FishAudioTTSSettings( - model=model_id, - voice=reference_id, - fish_sample_rate=0, - latency=params.latency, - format=output_format, - normalize=params.normalize, - prosody_speed=params.prosody_speed, - prosody_volume=params.prosody_volume, - reference_id=reference_id, - ) - self._sync_model_name_to_metrics() - def can_generate_metrics(self) -> bool: """Check if this service can generate processing metrics. diff --git a/src/pipecat/services/gladia/stt.py b/src/pipecat/services/gladia/stt.py index c1ce02d87..045a56613 100644 --- a/src/pipecat/services/gladia/stt.py +++ b/src/pipecat/services/gladia/stt.py @@ -278,14 +278,6 @@ class GladiaSTTService(WebsocketSTTService): Override for your deployment. See https://github.com/pipecat-ai/stt-benchmark **kwargs: Additional arguments passed to the STTService parent class. """ - super().__init__( - sample_rate=sample_rate, - ttfs_p99_latency=ttfs_p99_latency, - keepalive_timeout=20, - keepalive_interval=5, - **kwargs, - ) - params = params or GladiaInputParams() if params.language is not None: @@ -308,11 +300,6 @@ class GladiaSTTService(WebsocketSTTService): stacklevel=2, ) - self._api_key = api_key - self._region = region - self._url = url - self._receive_task = None - # Resolve deprecated language → language_config at init time language_config = params.language_config if not language_config and params.language: @@ -320,22 +307,33 @@ class GladiaSTTService(WebsocketSTTService): if language_code: language_config = LanguageConfig(languages=[language_code], code_switching=False) - self._settings = GladiaSTTSettings( - model=model, - language=None, - encoding=params.encoding, - bit_depth=params.bit_depth, - channels=params.channels, - custom_metadata=params.custom_metadata, - endpointing=params.endpointing, - maximum_duration_without_endpointing=params.maximum_duration_without_endpointing, - language_config=language_config, - pre_processing=params.pre_processing, - realtime_processing=params.realtime_processing, - messages_config=params.messages_config, - enable_vad=params.enable_vad, + super().__init__( + sample_rate=sample_rate, + ttfs_p99_latency=ttfs_p99_latency, + keepalive_timeout=20, + keepalive_interval=5, + settings=GladiaSTTSettings( + model=model, + language=None, + encoding=params.encoding, + bit_depth=params.bit_depth, + channels=params.channels, + custom_metadata=params.custom_metadata, + endpointing=params.endpointing, + maximum_duration_without_endpointing=params.maximum_duration_without_endpointing, + language_config=language_config, + pre_processing=params.pre_processing, + realtime_processing=params.realtime_processing, + messages_config=params.messages_config, + enable_vad=params.enable_vad, + ), + **kwargs, ) - self._sync_model_name_to_metrics() + + self._api_key = api_key + self._region = region + self._url = url + self._receive_task = None # Session management self._session_url = None diff --git a/src/pipecat/services/google/gemini_live/llm.py b/src/pipecat/services/google/gemini_live/llm.py index 037b23bb3..d06f941c7 100644 --- a/src/pipecat/services/google/gemini_live/llm.py +++ b/src/pipecat/services/google/gemini_live/llm.py @@ -695,10 +695,38 @@ class GeminiLiveLLMService(LLMService): stacklevel=2, ) - super().__init__(base_url=base_url, **kwargs) - params = params or InputParams() + super().__init__( + base_url=base_url, + settings=GeminiLiveLLMSettings( + model=model, + frequency_penalty=params.frequency_penalty, + max_tokens=params.max_tokens, + presence_penalty=params.presence_penalty, + temperature=params.temperature, + top_k=params.top_k, + top_p=params.top_p, + seed=None, + filter_incomplete_user_turns=False, + user_turn_completion_config=None, + modalities=params.modalities, + language=language_to_gemini_language(params.language) + if params.language + else "en-US", + media_resolution=params.media_resolution, + vad=params.vad, + context_window_compression=params.context_window_compression.model_dump() + if params.context_window_compression + else {}, + thinking=params.thinking or {}, + enable_affective_dialog=params.enable_affective_dialog or False, + proactivity=params.proactivity or {}, + extra=params.extra if isinstance(params.extra, dict) else {}, + ), + **kwargs, + ) + self._last_sent_time = 0 self._base_url = base_url self._voice_id = voice_id @@ -742,31 +770,6 @@ class GeminiLiveLLMService(LLMService): self._consecutive_failures = 0 self._connection_start_time = None - self._settings = GeminiLiveLLMSettings( - model=model, - frequency_penalty=params.frequency_penalty, - max_tokens=params.max_tokens, - presence_penalty=params.presence_penalty, - temperature=params.temperature, - top_k=params.top_k, - top_p=params.top_p, - seed=None, - filter_incomplete_user_turns=False, - user_turn_completion_config=None, - modalities=params.modalities, - language=self._language_code, - media_resolution=params.media_resolution, - vad=params.vad, - context_window_compression=params.context_window_compression.model_dump() - if params.context_window_compression - else {}, - thinking=params.thinking or {}, - enable_affective_dialog=params.enable_affective_dialog or False, - proactivity=params.proactivity or {}, - extra=params.extra if isinstance(params.extra, dict) else {}, - ) - self._sync_model_name_to_metrics() - self._file_api_base_url = file_api_base_url self._file_api: Optional[GeminiFileAPI] = None diff --git a/src/pipecat/services/google/image.py b/src/pipecat/services/google/image.py index f03b1da63..e69faf65e 100644 --- a/src/pipecat/services/google/image.py +++ b/src/pipecat/services/google/image.py @@ -16,6 +16,7 @@ import os # Suppress gRPC fork warnings os.environ["GRPC_ENABLE_FORK_SUPPORT"] = "false" +from dataclasses import dataclass from typing import Any, AsyncGenerator, Optional from loguru import logger @@ -25,6 +26,7 @@ from pydantic import BaseModel, Field from pipecat.frames.frames import ErrorFrame, Frame, URLImageRawFrame from pipecat.services.google.utils import update_google_client_http_options from pipecat.services.image_service import ImageGenService +from pipecat.services.settings import ImageGenSettings try: from google import genai @@ -35,6 +37,15 @@ except ModuleNotFoundError as e: raise Exception(f"Missing module: {e}") +@dataclass +class GoogleImageGenSettings(ImageGenSettings): + """Settings for the Google image generation service. + + Parameters: + model: Google Imagen model identifier. + """ + + class GoogleImageGenService(ImageGenService): """Google AI image generation service using Imagen models. @@ -72,17 +83,15 @@ class GoogleImageGenService(ImageGenService): http_options: HTTP options for the client. **kwargs: Additional arguments passed to the parent ImageGenService. """ - super().__init__(**kwargs) - self._params = params or GoogleImageGenService.InputParams() + params = params or GoogleImageGenService.InputParams() + super().__init__(settings=GoogleImageGenSettings(model=params.model), **kwargs) + self._params = params # Add client header http_options = update_google_client_http_options(http_options) self._client = genai.Client(api_key=api_key, http_options=http_options) - self._settings.model = self._params.model - self._sync_model_name_to_metrics() - def can_generate_metrics(self) -> bool: """Check if this service can generate processing metrics. diff --git a/src/pipecat/services/google/llm.py b/src/pipecat/services/google/llm.py index 1c6f56669..37ccfae9a 100644 --- a/src/pipecat/services/google/llm.py +++ b/src/pipecat/services/google/llm.py @@ -793,29 +793,29 @@ class GoogleLLMService(LLMService): http_options: HTTP options for the client. **kwargs: Additional arguments passed to parent class. """ - super().__init__(**kwargs) - params = params or GoogleLLMService.InputParams() + super().__init__( + settings=GoogleLLMSettings( + model=model, + max_tokens=params.max_tokens, + temperature=params.temperature, + top_k=params.top_k, + top_p=params.top_p, + frequency_penalty=None, + presence_penalty=None, + seed=None, + filter_incomplete_user_turns=False, + user_turn_completion_config=None, + thinking=params.thinking, + extra=params.extra if isinstance(params.extra, dict) else {}, + ), + **kwargs, + ) + self._api_key = api_key self._system_instruction = system_instruction self._http_options = update_google_client_http_options(http_options) - - self._settings = GoogleLLMSettings( - model=model, - max_tokens=params.max_tokens, - temperature=params.temperature, - top_k=params.top_k, - top_p=params.top_p, - frequency_penalty=None, - presence_penalty=None, - seed=None, - filter_incomplete_user_turns=False, - user_turn_completion_config=None, - thinking=params.thinking, - extra=params.extra if isinstance(params.extra, dict) else {}, - ) - self._sync_model_name_to_metrics() self._tools = tools self._tool_config = tool_config diff --git a/src/pipecat/services/google/stt.py b/src/pipecat/services/google/stt.py index ac3afa7a3..95d91d462 100644 --- a/src/pipecat/services/google/stt.py +++ b/src/pipecat/services/google/stt.py @@ -499,10 +499,29 @@ class GoogleSTTService(STTService): Override for your deployment. See https://github.com/pipecat-ai/stt-benchmark **kwargs: Additional arguments passed to STTService. """ - super().__init__(sample_rate=sample_rate, ttfs_p99_latency=ttfs_p99_latency, **kwargs) - params = params or GoogleSTTService.InputParams() + super().__init__( + sample_rate=sample_rate, + ttfs_p99_latency=ttfs_p99_latency, + settings=GoogleSTTSettings( + language=None, + languages=list(params.language_list), + language_codes=None, + model=params.model, + use_separate_recognition_per_channel=params.use_separate_recognition_per_channel, + enable_automatic_punctuation=params.enable_automatic_punctuation, + enable_spoken_punctuation=params.enable_spoken_punctuation, + enable_spoken_emojis=params.enable_spoken_emojis, + profanity_filter=params.profanity_filter, + enable_word_time_offsets=params.enable_word_time_offsets, + enable_word_confidence=params.enable_word_confidence, + enable_interim_results=params.enable_interim_results, + enable_voice_activity_events=params.enable_voice_activity_events, + ), + **kwargs, + ) + self._location = location self._stream = None self._config = None @@ -553,22 +572,6 @@ class GoogleSTTService(STTService): self._client = speech_v2.SpeechAsyncClient(credentials=creds, client_options=client_options) - self._settings = GoogleSTTSettings( - language=None, - languages=list(params.language_list), - language_codes=None, - model=params.model, - use_separate_recognition_per_channel=params.use_separate_recognition_per_channel, - enable_automatic_punctuation=params.enable_automatic_punctuation, - enable_spoken_punctuation=params.enable_spoken_punctuation, - enable_spoken_emojis=params.enable_spoken_emojis, - profanity_filter=params.profanity_filter, - enable_word_time_offsets=params.enable_word_time_offsets, - enable_word_confidence=params.enable_word_confidence, - enable_interim_results=params.enable_interim_results, - enable_voice_activity_events=params.enable_voice_activity_events, - ) - def can_generate_metrics(self) -> bool: """Check if the service can generate metrics. diff --git a/src/pipecat/services/google/tts.py b/src/pipecat/services/google/tts.py index 3416ee6d4..80c71b10f 100644 --- a/src/pipecat/services/google/tts.py +++ b/src/pipecat/services/google/tts.py @@ -602,25 +602,28 @@ class GoogleHttpTTSService(TTSService): params: Voice customization parameters including pitch, rate, volume, etc. **kwargs: Additional arguments passed to parent TTSService. """ - super().__init__(sample_rate=sample_rate, **kwargs) - params = params or GoogleHttpTTSService.InputParams() - self._location = location - self._settings = GoogleHttpTTSSettings( - model=None, - pitch=params.pitch, - rate=params.rate, - speaking_rate=params.speaking_rate, - volume=params.volume, - emphasis=params.emphasis, - language=self.language_to_service_language(params.language) - if params.language - else "en-US", - gender=params.gender, - google_style=params.google_style, - voice=voice_id, + super().__init__( + sample_rate=sample_rate, + settings=GoogleHttpTTSSettings( + model=None, + pitch=params.pitch, + rate=params.rate, + speaking_rate=params.speaking_rate, + volume=params.volume, + emphasis=params.emphasis, + language=self.language_to_service_language(params.language) + if params.language + else "en-US", + gender=params.gender, + google_style=params.google_style, + voice=voice_id, + ), + **kwargs, ) + + self._location = location self._client: texttospeech_v1.TextToSpeechAsyncClient = self._create_client( credentials, credentials_path ) @@ -1016,19 +1019,22 @@ class GoogleTTSService(GoogleBaseTTSService): params: Language configuration parameters. **kwargs: Additional arguments passed to parent TTSService. """ - super().__init__(sample_rate=sample_rate, **kwargs) - params = params or GoogleTTSService.InputParams() - self._location = location - self._settings = GoogleStreamTTSSettings( - model=None, - language=self.language_to_service_language(params.language) - if params.language - else "en-US", - speaking_rate=params.speaking_rate, - voice=voice_id, + super().__init__( + sample_rate=sample_rate, + settings=GoogleStreamTTSSettings( + model=None, + language=self.language_to_service_language(params.language) + if params.language + else "en-US", + speaking_rate=params.speaking_rate, + voice=voice_id, + ), + **kwargs, ) + + self._location = location self._voice_cloning_key = voice_cloning_key self._client: texttospeech_v1.TextToSpeechAsyncClient = self._create_client( credentials, credentials_path @@ -1222,26 +1228,28 @@ class GeminiTTSService(GoogleBaseTTSService): f"Google TTS only supports {self.GOOGLE_SAMPLE_RATE}Hz sample rate. " f"Current rate of {sample_rate}Hz may cause issues." ) - super().__init__(sample_rate=sample_rate, **kwargs) - params = params or GeminiTTSService.InputParams() if voice_id not in self.AVAILABLE_VOICES: logger.warning(f"Voice '{voice_id}' not in known voices list. Using anyway.") - self._location = location - self._model = model - self._settings = GeminiTTSSettings( - model=None, - language=self.language_to_service_language(params.language) - if params.language - else "en-US", - prompt=params.prompt, - multi_speaker=params.multi_speaker, - speaker_configs=params.speaker_configs, - voice=voice_id, + super().__init__( + sample_rate=sample_rate, + settings=GeminiTTSSettings( + model=None, + language=self.language_to_service_language(params.language) + if params.language + else "en-US", + prompt=params.prompt, + multi_speaker=params.multi_speaker, + speaker_configs=params.speaker_configs, + voice=voice_id, + ), + **kwargs, ) + self._location = location + self._model = model self._client: texttospeech_v1.TextToSpeechAsyncClient = self._create_client( credentials, credentials_path ) diff --git a/src/pipecat/services/gradium/stt.py b/src/pipecat/services/gradium/stt.py index 4ec7bf6ff..ac35c6e52 100644 --- a/src/pipecat/services/gradium/stt.py +++ b/src/pipecat/services/gradium/stt.py @@ -129,8 +129,6 @@ class GradiumSTTService(WebsocketSTTService): Override for your deployment. See https://github.com/pipecat-ai/stt-benchmark **kwargs: Additional arguments passed to parent STTService class. """ - super().__init__(sample_rate=SAMPLE_RATE, ttfs_p99_latency=ttfs_p99_latency, **kwargs) - if json_config is not None: import warnings @@ -140,19 +138,24 @@ class GradiumSTTService(WebsocketSTTService): stacklevel=2, ) + params = params or GradiumSTTService.InputParams() + + super().__init__( + sample_rate=SAMPLE_RATE, + ttfs_p99_latency=ttfs_p99_latency, + settings=GradiumSTTSettings( + model=None, + language=params.language, + delay_in_frames=params.delay_in_frames or None, + ), + **kwargs, + ) + self._api_key = api_key self._api_endpoint_base_url = api_endpoint_base_url self._websocket = None self._json_config = json_config - params = params or GradiumSTTService.InputParams() - - self._settings = GradiumSTTSettings( - model=None, - language=params.language, - delay_in_frames=params.delay_in_frames or None, - ) - self._receive_task = None self._audio_buffer = bytearray() diff --git a/src/pipecat/services/gradium/tts.py b/src/pipecat/services/gradium/tts.py index ee6e6821e..c8a83a7f2 100644 --- a/src/pipecat/services/gradium/tts.py +++ b/src/pipecat/services/gradium/tts.py @@ -85,27 +85,27 @@ class GradiumTTSService(AudioContextTTSService): params: Additional configuration parameters. **kwargs: Additional arguments passed to parent class. """ + params = params or GradiumTTSService.InputParams() + super().__init__( push_stop_frames=True, push_text_frames=False, pause_frame_processing=True, supports_word_timestamps=True, sample_rate=SAMPLE_RATE, + settings=GradiumTTSSettings( + model=model, + voice=voice_id, + language=None, + output_format="pcm", + ), **kwargs, ) - params = params or GradiumTTSService.InputParams() - # Store service configuration self._api_key = api_key self._url = url self._json_config = json_config - self._settings = GradiumTTSSettings( - model=model, - voice=voice_id, - language=None, - output_format="pcm", - ) # State tracking self._receive_task = None diff --git a/src/pipecat/services/grok/realtime/llm.py b/src/pipecat/services/grok/realtime/llm.py index 4f6a62e24..c522c6c6f 100644 --- a/src/pipecat/services/grok/realtime/llm.py +++ b/src/pipecat/services/grok/realtime/llm.py @@ -145,25 +145,27 @@ class GrokRealtimeLLMService(LLMService): start_audio_paused: Whether to start with audio input paused. Defaults to False. **kwargs: Additional arguments passed to parent LLMService. """ - super().__init__(base_url=base_url, **kwargs) + super().__init__( + base_url=base_url, + settings=GrokRealtimeLLMSettings( + model=None, + temperature=None, + max_tokens=None, + top_p=None, + top_k=None, + frequency_penalty=None, + presence_penalty=None, + seed=None, + filter_incomplete_user_turns=False, + user_turn_completion_config=None, + session_properties=session_properties or events.SessionProperties(), + ), + **kwargs, + ) self.api_key = api_key self.base_url = base_url - self._settings = GrokRealtimeLLMSettings( - model=None, - temperature=None, - max_tokens=None, - top_p=None, - top_k=None, - frequency_penalty=None, - presence_penalty=None, - seed=None, - filter_incomplete_user_turns=False, - user_turn_completion_config=None, - session_properties=session_properties or events.SessionProperties(), - ) - self._audio_input_paused = start_audio_paused self._websocket = None self._receive_task = None diff --git a/src/pipecat/services/groq/tts.py b/src/pipecat/services/groq/tts.py index cc073f8c7..7e4d40dba 100644 --- a/src/pipecat/services/groq/tts.py +++ b/src/pipecat/services/groq/tts.py @@ -99,27 +99,24 @@ class GroqTTSService(TTSService): if sample_rate != self.GROQ_SAMPLE_RATE: logger.warning(f"Groq TTS only supports {self.GROQ_SAMPLE_RATE}Hz sample rate. ") + params = params or GroqTTSService.InputParams() + super().__init__( pause_frame_processing=True, sample_rate=sample_rate, + settings=GroqTTSSettings( + model=model_name, + voice=voice_id, + language=str(params.language) if params.language else "en", + output_format=output_format, + speed=params.speed, + groq_sample_rate=sample_rate, + ), **kwargs, ) - params = params or GroqTTSService.InputParams() - self._api_key = api_key self._output_format = output_format - self._params = params - - self._settings = GroqTTSSettings( - model=model_name, - voice=voice_id, - language=str(params.language) if params.language else "en", - output_format=output_format, - speed=params.speed, - groq_sample_rate=sample_rate, - ) - self._sync_model_name_to_metrics() self._client = AsyncGroq(api_key=self._api_key) diff --git a/src/pipecat/services/hathora/stt.py b/src/pipecat/services/hathora/stt.py index a08a80aa2..84f4116f3 100644 --- a/src/pipecat/services/hathora/stt.py +++ b/src/pipecat/services/hathora/stt.py @@ -89,24 +89,23 @@ class HathoraSTTService(SegmentedSTTService): Override for your deployment. See https://github.com/pipecat-ai/stt-benchmark **kwargs: Additional arguments passed to the parent class. """ + params = params or HathoraSTTService.InputParams() + super().__init__( sample_rate=sample_rate, ttfs_p99_latency=ttfs_p99_latency, + settings=HathoraSTTSettings( + model=model, + language=params.language, + config=params.config, + ), **kwargs, ) + self._model = model self._api_key = api_key or os.getenv("HATHORA_API_KEY") self._base_url = base_url - params = params or HathoraSTTService.InputParams() - - self._settings = HathoraSTTSettings( - model=model, - language=params.language, - config=params.config, - ) - self._sync_model_name_to_metrics() - def can_generate_metrics(self) -> bool: """Check if this service can generate processing metrics. diff --git a/src/pipecat/services/hathora/tts.py b/src/pipecat/services/hathora/tts.py index 1e7662aab..e16aa3b08 100644 --- a/src/pipecat/services/hathora/tts.py +++ b/src/pipecat/services/hathora/tts.py @@ -107,24 +107,22 @@ class HathoraTTSService(TTSService): params: Configuration parameters. **kwargs: Additional arguments passed to the parent class. """ + params = params or HathoraTTSService.InputParams() + super().__init__( sample_rate=sample_rate, + settings=HathoraTTSSettings( + model=model, + voice=voice_id, + speed=params.speed, + config=params.config, + ), **kwargs, ) self._model = model self._api_key = api_key or os.getenv("HATHORA_API_KEY") self._base_url = base_url - params = params or HathoraTTSService.InputParams() - - self._settings = HathoraTTSSettings( - model=model, - voice=voice_id, - speed=params.speed, - config=params.config, - ) - self._sync_model_name_to_metrics() - def can_generate_metrics(self) -> bool: """Check if this service can generate processing metrics. diff --git a/src/pipecat/services/hume/tts.py b/src/pipecat/services/hume/tts.py index 3fb43ff88..2a075ab36 100644 --- a/src/pipecat/services/hume/tts.py +++ b/src/pipecat/services/hume/tts.py @@ -121,11 +121,21 @@ class HumeTTSService(TTSService): f"Hume TTS streams at {HUME_SAMPLE_RATE} Hz; configured sample_rate={sample_rate}" ) + params = params or HumeTTSService.InputParams() + super().__init__( sample_rate=sample_rate, push_text_frames=False, push_stop_frames=True, supports_word_timestamps=True, + settings=HumeTTSSettings( + model=None, + voice=voice_id, + language=None, # Not applicable here + description=params.description, + speed=params.speed, + trailing_silence=params.trailing_silence, + ), **kwargs, ) @@ -135,15 +145,6 @@ class HumeTTSService(TTSService): self._client = AsyncHumeClient(api_key=api_key, httpx_client=self._http_client) - params = params or HumeTTSService.InputParams() - self._settings = HumeTTSSettings( - model=None, - voice=voice_id, - description=params.description, - speed=params.speed, - trailing_silence=params.trailing_silence, - ) - self._audio_bytes = b"" # Track cumulative time for word timestamps across utterances diff --git a/src/pipecat/services/image_service.py b/src/pipecat/services/image_service.py index 58ab58fa4..f99909444 100644 --- a/src/pipecat/services/image_service.py +++ b/src/pipecat/services/image_service.py @@ -11,11 +11,12 @@ text prompts into images. """ from abc import abstractmethod -from typing import AsyncGenerator +from typing import AsyncGenerator, Optional from pipecat.frames.frames import Frame, TextFrame from pipecat.processors.frame_processor import FrameDirection from pipecat.services.ai_service import AIService +from pipecat.services.settings import ImageGenSettings class ImageGenService(AIService): @@ -26,13 +27,20 @@ class ImageGenService(AIService): generation functionality using their specific AI service. """ - def __init__(self, **kwargs): + def __init__(self, *, settings: Optional[ImageGenSettings] = None, **kwargs): """Initialize the image generation service. Args: + settings: The runtime-updatable settings for the image generation service. **kwargs: Additional arguments passed to the parent AIService. """ - super().__init__(**kwargs) + super().__init__( + settings=settings + # Here in case subclass doesn't implement more specific settings + # (which hopefully should be rare) + or ImageGenSettings(), + **kwargs, + ) # Renders the image. Returns an Image object. @abstractmethod diff --git a/src/pipecat/services/inworld/tts.py b/src/pipecat/services/inworld/tts.py index 22bdf22ff..2fb86b4a6 100644 --- a/src/pipecat/services/inworld/tts.py +++ b/src/pipecat/services/inworld/tts.py @@ -150,16 +150,28 @@ class InworldHttpTTSService(TTSService): params: Input parameters for Inworld TTS configuration. **kwargs: Additional arguments passed to the parent class. """ + params = params or InworldHttpTTSService.InputParams() + super().__init__( push_text_frames=False, push_stop_frames=True, supports_word_timestamps=True, sample_rate=sample_rate, + settings=InworldTTSSettings( + model=model, + voice=voice_id, + language=None, + audio_encoding=encoding, + audio_sample_rate=0, + speaking_rate=params.speaking_rate, + temperature=params.temperature, + timestamp_transport_strategy=params.timestamp_transport_strategy, + auto_mode=None, # Not applicable for HTTP TTS + apply_text_normalization=None, # Not applicable for HTTP TTS + ), **kwargs, ) - params = params or InworldHttpTTSService.InputParams() - self._api_key = api_key self._session = aiohttp_session self._streaming = streaming @@ -170,23 +182,8 @@ class InworldHttpTTSService(TTSService): else: self._base_url = "https://api.inworld.ai/tts/v1/voice" - self._settings = InworldTTSSettings( - model=model, - voice=voice_id, - language=None, - audio_encoding=encoding, - audio_sample_rate=0, - speaking_rate=params.speaking_rate, - temperature=params.temperature, - timestamp_transport_strategy=params.timestamp_transport_strategy, - auto_mode=None, # Not applicable for HTTP TTS - apply_text_normalization=None, # Not applicable for HTTP TTS - ) - self._cumulative_time = 0.0 - self._sync_model_name_to_metrics() - def can_generate_metrics(self) -> bool: """Check if this service can generate processing metrics. @@ -530,6 +527,8 @@ class InworldTTSService(AudioContextTTSService): append_trailing_space: Whether to append a trailing space to text before sending to TTS. **kwargs: Additional arguments passed to the parent class. """ + params = params or InworldTTSService.InputParams() + super().__init__( push_text_frames=False, push_stop_frames=True, @@ -538,25 +537,23 @@ class InworldTTSService(AudioContextTTSService): sample_rate=sample_rate, aggregate_sentences=aggregate_sentences, append_trailing_space=append_trailing_space, + settings=InworldTTSSettings( + model=model, + voice=voice_id, + language=None, + audio_encoding=encoding, + audio_sample_rate=0, + speaking_rate=params.speaking_rate, + temperature=params.temperature, + apply_text_normalization=params.apply_text_normalization, + timestamp_transport_strategy=params.timestamp_transport_strategy, + auto_mode=params.auto_mode if params.auto_mode is not None else aggregate_sentences, + ), **kwargs, ) - params = params or InworldTTSService.InputParams() - self._api_key = api_key self._url = url - self._settings = InworldTTSSettings( - model=model, - voice=voice_id, - language=None, - audio_encoding=encoding, - audio_sample_rate=0, - speaking_rate=params.speaking_rate, - temperature=params.temperature, - apply_text_normalization=params.apply_text_normalization, - timestamp_transport_strategy=params.timestamp_transport_strategy, - auto_mode=params.auto_mode if params.auto_mode is not None else aggregate_sentences, - ) self._timestamp_type = "WORD" self._buffer_settings = { @@ -575,8 +572,6 @@ class InworldTTSService(AudioContextTTSService): # Track the end time of the last word in the current generation self._generation_end_time = 0.0 - self._sync_model_name_to_metrics() - def can_generate_metrics(self) -> bool: """Check if this service can generate processing metrics. diff --git a/src/pipecat/services/kokoro/tts.py b/src/pipecat/services/kokoro/tts.py index 519c565ba..4b35fa46d 100644 --- a/src/pipecat/services/kokoro/tts.py +++ b/src/pipecat/services/kokoro/tts.py @@ -137,19 +137,20 @@ class KokoroTTSService(TTSService): **kwargs: Additional arguments passed to parent `TTSService`. """ - super().__init__(**kwargs) - params = params or KokoroTTSService.InputParams() - self._lang_code = language_to_kokoro_language(params.language) - - self._settings = KokoroTTSSettings( - model=None, - voice=voice_id, - language=language_to_kokoro_language(params.language), - lang_code=language_to_kokoro_language(params.language), + super().__init__( + settings=KokoroTTSSettings( + model=None, + voice=voice_id, + language=language_to_kokoro_language(params.language), + lang_code=language_to_kokoro_language(params.language), + ), + **kwargs, ) + self._lang_code = language_to_kokoro_language(params.language) + model = Path(model_path) if model_path else KOKORO_CACHE_DIR / "kokoro-v1.0.onnx" voices = Path(voices_path) if voices_path else KOKORO_CACHE_DIR / "voices-v1.0.bin" diff --git a/src/pipecat/services/llm_service.py b/src/pipecat/services/llm_service.py index 1102e85a1..a06423754 100644 --- a/src/pipecat/services/llm_service.py +++ b/src/pipecat/services/llm_service.py @@ -181,7 +181,11 @@ class LLMService(UserTurnCompletionLLMServiceMixin, AIService): adapter_class: Type[BaseLLMAdapter] = OpenAILLMAdapter def __init__( - self, run_in_parallel: bool = True, function_call_timeout_secs: float = 10.0, **kwargs + self, + run_in_parallel: bool = True, + function_call_timeout_secs: float = 10.0, + settings: Optional[LLMSettings] = None, + **kwargs, ): """Initialize the LLM service. @@ -190,10 +194,17 @@ class LLMService(UserTurnCompletionLLMServiceMixin, AIService): Defaults to True. function_call_timeout_secs: Timeout in seconds for deferred function calls. Defaults to 10.0 seconds. + settings: The runtime-updatable settings for the LLM service. **kwargs: Additional arguments passed to the parent AIService. """ - super().__init__(**kwargs) + super().__init__( + settings=settings + # Here in case subclass doesn't implement more specific settings + # (which hopefully should be rare) + or LLMSettings(), + **kwargs, + ) self._run_in_parallel = run_in_parallel self._function_call_timeout_secs = function_call_timeout_secs self._filter_incomplete_user_turns: bool = False @@ -204,7 +215,6 @@ class LLMService(UserTurnCompletionLLMServiceMixin, AIService): self._sequential_runner_task: Optional[asyncio.Task] = None self._skip_tts: Optional[bool] = None self._summary_task: Optional[asyncio.Task] = None - self._settings = LLMSettings() # Here in case subclass doesn't implement more specific settings (hopefully shouldn't happen) self._register_event_handler("on_function_calls_started") self._register_event_handler("on_completion_timeout") diff --git a/src/pipecat/services/lmnt/tts.py b/src/pipecat/services/lmnt/tts.py index b7ebb19ea..a2c500ca2 100644 --- a/src/pipecat/services/lmnt/tts.py +++ b/src/pipecat/services/lmnt/tts.py @@ -118,17 +118,16 @@ class LmntTTSService(InterruptibleTTSService): push_stop_frames=True, pause_frame_processing=True, sample_rate=sample_rate, + settings=LmntTTSSettings( + model=model, + voice=voice_id, + language=self.language_to_service_language(language), + format="raw", + ), **kwargs, ) self._api_key = api_key - self._settings = LmntTTSSettings( - model=model, - voice=voice_id, - language=self.language_to_service_language(language), - format="raw", - ) - self._sync_model_name_to_metrics() self._receive_task = None self._context_id: Optional[str] = None diff --git a/src/pipecat/services/minimax/tts.py b/src/pipecat/services/minimax/tts.py index 388b7ee9e..116d24a34 100644 --- a/src/pipecat/services/minimax/tts.py +++ b/src/pipecat/services/minimax/tts.py @@ -227,35 +227,35 @@ class MiniMaxHttpTTSService(TTSService): params: Additional configuration parameters. **kwargs: Additional arguments passed to parent TTSService. """ - super().__init__(sample_rate=sample_rate, **kwargs) - params = params or MiniMaxHttpTTSService.InputParams() + super().__init__( + sample_rate=sample_rate, + settings=MiniMaxTTSSettings( + model=model, + voice=voice_id, + language=None, + stream=True, + speed=params.speed, + volume=params.volume, + pitch=params.pitch, + language_boost=None, + emotion=None, + text_normalization=None, + latex_read=None, + audio_bitrate=128000, + audio_format="pcm", + audio_channel=1, + audio_sample_rate=0, + ), + **kwargs, + ) + self._api_key = api_key self._group_id = group_id self._base_url = f"{base_url}?GroupId={group_id}" self._session = aiohttp_session - # Create voice settings - self._settings = MiniMaxTTSSettings( - model=model, - voice=voice_id, - language=None, - stream=True, - speed=params.speed, - volume=params.volume, - pitch=params.pitch, - language_boost=None, - emotion=None, - text_normalization=None, - latex_read=None, - audio_bitrate=128000, - audio_format="pcm", - audio_channel=1, - audio_sample_rate=0, - ) - self._sync_model_name_to_metrics() - # Add language boost if provided if params.language: service_lang = self.language_to_service_language(params.language) diff --git a/src/pipecat/services/moondream/vision.py b/src/pipecat/services/moondream/vision.py index 16be15ac5..53b98b77a 100644 --- a/src/pipecat/services/moondream/vision.py +++ b/src/pipecat/services/moondream/vision.py @@ -11,6 +11,7 @@ for image analysis and description generation. """ import asyncio +from dataclasses import dataclass from typing import AsyncGenerator, Optional from loguru import logger @@ -24,6 +25,7 @@ from pipecat.frames.frames import ( VisionFullResponseStartFrame, VisionTextFrame, ) +from pipecat.services.settings import VisionSettings from pipecat.services.vision_service import VisionService try: @@ -60,6 +62,15 @@ def detect_device(): return torch.device("cpu"), torch.float32 +@dataclass +class MoondreamSettings(VisionSettings): + """Settings for the Moondream vision service. + + Parameters: + model: Moondream model identifier. + """ + + class MoondreamService(VisionService): """Moondream vision-language model service. @@ -79,10 +90,7 @@ class MoondreamService(VisionService): use_cpu: Whether to force CPU usage instead of hardware acceleration. **kwargs: Additional arguments passed to the parent VisionService. """ - super().__init__(**kwargs) - - self._settings.model = model - self._sync_model_name_to_metrics() + super().__init__(settings=MoondreamSettings(model=model), **kwargs) if not use_cpu: device, dtype = detect_device() diff --git a/src/pipecat/services/neuphonic/tts.py b/src/pipecat/services/neuphonic/tts.py index e076958c4..81b366a8b 100644 --- a/src/pipecat/services/neuphonic/tts.py +++ b/src/pipecat/services/neuphonic/tts.py @@ -134,26 +134,26 @@ class NeuphonicTTSService(InterruptibleTTSService): aggregate_sentences: Whether to aggregate sentences within the TTSService. **kwargs: Additional arguments passed to parent InterruptibleTTSService. """ + params = params or NeuphonicTTSService.InputParams() + super().__init__( aggregate_sentences=aggregate_sentences, push_stop_frames=True, stop_frame_timeout_s=2.0, sample_rate=sample_rate, + settings=NeuphonicTTSSettings( + model=None, + language=self.language_to_service_language(params.language), + speed=params.speed, + encoding=encoding, + sampling_rate=sample_rate, + voice=voice_id, + ), **kwargs, ) - params = params or NeuphonicTTSService.InputParams() - self._api_key = api_key self._url = url - self._settings = NeuphonicTTSSettings( - model=None, - language=self.language_to_service_language(params.language), - speed=params.speed, - encoding=encoding, - sampling_rate=sample_rate, - voice=voice_id, - ) self._cumulative_time = 0 @@ -443,21 +443,24 @@ class NeuphonicHttpTTSService(TTSService): params: Additional input parameters for TTS configuration. **kwargs: Additional arguments passed to parent TTSService. """ - super().__init__(sample_rate=sample_rate, **kwargs) - params = params or NeuphonicHttpTTSService.InputParams() + super().__init__( + sample_rate=sample_rate, + settings=NeuphonicTTSSettings( + model=None, + voice=voice_id, + language=self.language_to_service_language(params.language) or "en", + speed=params.speed, + encoding=encoding, + sampling_rate=sample_rate, + ), + **kwargs, + ) + self._api_key = api_key self._session = aiohttp_session self._base_url = url.rstrip("/") - self._settings = NeuphonicTTSSettings( - model=None, - voice=voice_id, - language=self.language_to_service_language(params.language) or "en", - speed=params.speed, - encoding=encoding, - sampling_rate=sample_rate, - ) def can_generate_metrics(self) -> bool: """Check if this service can generate processing metrics. diff --git a/src/pipecat/services/nvidia/stt.py b/src/pipecat/services/nvidia/stt.py index 3bbe04f51..950515096 100644 --- a/src/pipecat/services/nvidia/stt.py +++ b/src/pipecat/services/nvidia/stt.py @@ -164,10 +164,18 @@ class NvidiaSTTService(STTService): Override for your deployment. See https://github.com/pipecat-ai/stt-benchmark **kwargs: Additional arguments passed to STTService. """ - super().__init__(sample_rate=sample_rate, ttfs_p99_latency=ttfs_p99_latency, **kwargs) - params = params or NvidiaSTTService.InputParams() + super().__init__( + sample_rate=sample_rate, + ttfs_p99_latency=ttfs_p99_latency, + settings=NvidiaSTTSettings( + model=model_function_map.get("model_name"), + language=params.language, + ), + **kwargs, + ) + self._server = server self._api_key = api_key self._use_ssl = use_ssl @@ -180,12 +188,6 @@ class NvidiaSTTService(STTService): self._custom_configuration = "" self._function_id = model_function_map.get("function_id") - self._settings = NvidiaSTTSettings( - model=model_function_map.get("model_name"), - language=params.language, - ) - self._sync_model_name_to_metrics() - self._asr_service = None self._queue = None self._config = None @@ -463,10 +465,24 @@ class NvidiaSegmentedSTTService(SegmentedSTTService): Override for your deployment. See https://github.com/pipecat-ai/stt-benchmark **kwargs: Additional arguments passed to SegmentedSTTService """ - super().__init__(sample_rate=sample_rate, ttfs_p99_latency=ttfs_p99_latency, **kwargs) - params = params or NvidiaSegmentedSTTService.InputParams() + super().__init__( + sample_rate=sample_rate, + ttfs_p99_latency=ttfs_p99_latency, + settings=NvidiaSegmentedSTTSettings( + model=model_function_map.get("model_name"), + language=self.language_to_service_language(params.language or Language.EN_US) + or "en-US", + profanity_filter=params.profanity_filter, + automatic_punctuation=params.automatic_punctuation, + verbatim_transcripts=params.verbatim_transcripts, + boosted_lm_words=params.boosted_lm_words, + boosted_lm_score=params.boosted_lm_score, + ), + **kwargs, + ) + # Initialize NVIDIA Riva settings self._api_key = api_key self._server = server @@ -484,17 +500,6 @@ class NvidiaSegmentedSTTService(SegmentedSTTService): self._config = None self._asr_service = None - self._settings = NvidiaSegmentedSTTSettings( - model=model_function_map.get("model_name"), - language=self.language_to_service_language(params.language or Language.EN_US) - or "en-US", - profanity_filter=params.profanity_filter, - automatic_punctuation=params.automatic_punctuation, - verbatim_transcripts=params.verbatim_transcripts, - boosted_lm_words=params.boosted_lm_words, - boosted_lm_score=params.boosted_lm_score, - ) - self._sync_model_name_to_metrics() def language_to_service_language(self, language: Language) -> Optional[str]: """Convert pipecat Language enum to NVIDIA Riva's language code. diff --git a/src/pipecat/services/nvidia/tts.py b/src/pipecat/services/nvidia/tts.py index c6a5f371e..6785e9631 100644 --- a/src/pipecat/services/nvidia/tts.py +++ b/src/pipecat/services/nvidia/tts.py @@ -103,21 +103,23 @@ class NvidiaTTSService(TTSService): use_ssl: Whether to use SSL for the NVIDIA Riva server. Defaults to True. **kwargs: Additional arguments passed to parent TTSService. """ - super().__init__(sample_rate=sample_rate, **kwargs) - params = params or NvidiaTTSService.InputParams() + super().__init__( + sample_rate=sample_rate, + settings=NvidiaTTSSettings( + model=model_function_map.get("model_name"), + voice=voice_id, + language=params.language, + quality=params.quality, + ), + **kwargs, + ) + self._server = server self._api_key = api_key self._function_id = model_function_map.get("function_id") self._use_ssl = use_ssl - self._settings = NvidiaTTSSettings( - model=model_function_map.get("model_name"), - voice=voice_id, - language=params.language, - quality=params.quality, - ) - self._sync_model_name_to_metrics() self._service = None self._config = None diff --git a/src/pipecat/services/openai/base_llm.py b/src/pipecat/services/openai/base_llm.py index 9ba0583a1..40a2672f8 100644 --- a/src/pipecat/services/openai/base_llm.py +++ b/src/pipecat/services/openai/base_llm.py @@ -133,28 +133,28 @@ class BaseOpenAILLMService(LLMService): retry_on_timeout: Whether to retry the request once if it times out. **kwargs: Additional arguments passed to the parent LLMService. """ - super().__init__(**kwargs) - params = params or BaseOpenAILLMService.InputParams() - self._settings = OpenAILLMSettings( - model=model, - frequency_penalty=params.frequency_penalty, - presence_penalty=params.presence_penalty, - seed=params.seed, - temperature=params.temperature, - top_p=params.top_p, - top_k=None, - max_tokens=params.max_tokens, - max_completion_tokens=params.max_completion_tokens, - service_tier=params.service_tier, - filter_incomplete_user_turns=False, - user_turn_completion_config=None, - extra=params.extra if isinstance(params.extra, dict) else {}, + super().__init__( + settings=OpenAILLMSettings( + model=model, + frequency_penalty=params.frequency_penalty, + presence_penalty=params.presence_penalty, + seed=params.seed, + temperature=params.temperature, + top_p=params.top_p, + top_k=None, + max_tokens=params.max_tokens, + max_completion_tokens=params.max_completion_tokens, + service_tier=params.service_tier, + filter_incomplete_user_turns=False, + user_turn_completion_config=None, + extra=params.extra if isinstance(params.extra, dict) else {}, + ), + **kwargs, ) self._retry_timeout_secs = retry_timeout_secs self._retry_on_timeout = retry_on_timeout - self._sync_model_name_to_metrics() self._full_model_name: str = "" self._client = self.create_client( api_key=api_key, diff --git a/src/pipecat/services/openai/image.py b/src/pipecat/services/openai/image.py index 36efc5987..f35a5ded8 100644 --- a/src/pipecat/services/openai/image.py +++ b/src/pipecat/services/openai/image.py @@ -11,6 +11,7 @@ for creating images from text prompts. """ import io +from dataclasses import dataclass from typing import AsyncGenerator, Literal, Optional import aiohttp @@ -24,6 +25,16 @@ from pipecat.frames.frames import ( URLImageRawFrame, ) from pipecat.services.image_service import ImageGenService +from pipecat.services.settings import ImageGenSettings + + +@dataclass +class OpenAIImageGenSettings(ImageGenSettings): + """Settings for the OpenAI image generation service. + + Parameters: + model: DALL-E model identifier. + """ class OpenAIImageGenService(ImageGenService): @@ -52,9 +63,7 @@ class OpenAIImageGenService(ImageGenService): image_size: Target size for generated images. model: DALL-E model to use for generation. Defaults to "dall-e-3". """ - super().__init__() - self._settings.model = model - self._sync_model_name_to_metrics() + super().__init__(settings=OpenAIImageGenSettings(model=model)) self._image_size = image_size self._client = AsyncOpenAI(api_key=api_key, base_url=base_url) self._aiohttp_session = aiohttp_session diff --git a/src/pipecat/services/openai/realtime/llm.py b/src/pipecat/services/openai/realtime/llm.py index a68304fdc..6665a9a75 100644 --- a/src/pipecat/services/openai/realtime/llm.py +++ b/src/pipecat/services/openai/realtime/llm.py @@ -171,25 +171,26 @@ class OpenAIRealtimeLLMService(LLMService): # Build WebSocket URL with model query parameter # Source: https://platform.openai.com/docs/guides/realtime-websocket full_url = f"{base_url}?model={model}" - super().__init__(base_url=full_url, **kwargs) + super().__init__( + base_url=full_url, + settings=OpenAIRealtimeLLMSettings( + model=model, + temperature=None, + max_tokens=None, + top_p=None, + top_k=None, + frequency_penalty=None, + presence_penalty=None, + seed=None, + filter_incomplete_user_turns=False, + user_turn_completion_config=None, + session_properties=session_properties or events.SessionProperties(), + ), + **kwargs, + ) self.api_key = api_key self.base_url = full_url - - self._settings = OpenAIRealtimeLLMSettings( - model=model, - temperature=None, - max_tokens=None, - top_p=None, - top_k=None, - frequency_penalty=None, - presence_penalty=None, - seed=None, - filter_incomplete_user_turns=False, - user_turn_completion_config=None, - session_properties=session_properties or events.SessionProperties(), - ) - self._sync_model_name_to_metrics() self._audio_input_paused = start_audio_paused self._video_input_paused = start_video_paused self._video_frame_detail = video_frame_detail diff --git a/src/pipecat/services/openai/stt.py b/src/pipecat/services/openai/stt.py index 8b690d015..9a52be114 100644 --- a/src/pipecat/services/openai/stt.py +++ b/src/pipecat/services/openai/stt.py @@ -221,6 +221,11 @@ class OpenAIRealtimeSTTService(WebsocketSTTService): super().__init__( ttfs_p99_latency=ttfs_p99_latency, + settings=OpenAIRealtimeSTTSettings( + model=model, + language=language, + prompt=prompt, + ), **kwargs, ) @@ -232,13 +237,6 @@ class OpenAIRealtimeSTTService(WebsocketSTTService): self._noise_reduction = noise_reduction self._should_interrupt = should_interrupt - self._settings = OpenAIRealtimeSTTSettings( - model=model, - language=language, - prompt=prompt, - ) - self._sync_model_name_to_metrics() - self._receive_task = None self._session_ready = False self._resampler = create_stream_resampler() diff --git a/src/pipecat/services/openai/tts.py b/src/pipecat/services/openai/tts.py index 2693bcc27..f95d79134 100644 --- a/src/pipecat/services/openai/tts.py +++ b/src/pipecat/services/openai/tts.py @@ -132,10 +132,6 @@ class OpenAITTSService(TTSService): f"OpenAI TTS only supports {self.OPENAI_SAMPLE_RATE}Hz sample rate. " f"Current rate of {sample_rate}Hz may cause issues." ) - super().__init__(sample_rate=sample_rate, **kwargs) - - self._client = AsyncOpenAI(api_key=api_key, base_url=base_url) - if instructions or speed: import warnings @@ -147,13 +143,18 @@ class OpenAITTSService(TTSService): stacklevel=2, ) - self._settings = OpenAITTSSettings( - model=model, - voice=voice, - instructions=params.instructions if params else instructions, - speed=params.speed if params else speed, + super().__init__( + sample_rate=sample_rate, + settings=OpenAITTSSettings( + model=model, + voice=voice, + instructions=params.instructions if params else instructions, + speed=params.speed if params else speed, + ), + **kwargs, ) - self._sync_model_name_to_metrics() + + self._client = AsyncOpenAI(api_key=api_key, base_url=base_url) def can_generate_metrics(self) -> bool: """Check if this service can generate processing metrics. diff --git a/src/pipecat/services/openai_realtime_beta/openai.py b/src/pipecat/services/openai_realtime_beta/openai.py index 6ffccfbef..983cd10df 100644 --- a/src/pipecat/services/openai_realtime_beta/openai.py +++ b/src/pipecat/services/openai_realtime_beta/openai.py @@ -156,25 +156,26 @@ class OpenAIRealtimeBetaLLMService(LLMService): ) full_url = f"{base_url}?model={model}" - super().__init__(base_url=full_url, **kwargs) + super().__init__( + base_url=full_url, + settings=OpenAIRealtimeBetaLLMSettings( + model=model, + temperature=None, + max_tokens=None, + top_p=None, + top_k=None, + frequency_penalty=None, + presence_penalty=None, + seed=None, + filter_incomplete_user_turns=False, + user_turn_completion_config=None, + session_properties=session_properties or events.SessionProperties(), + ), + **kwargs, + ) self.api_key = api_key self.base_url = full_url - - self._settings = OpenAIRealtimeBetaLLMSettings( - model=model, - temperature=None, - max_tokens=None, - top_p=None, - top_k=None, - frequency_penalty=None, - presence_penalty=None, - seed=None, - filter_incomplete_user_turns=False, - user_turn_completion_config=None, - session_properties=session_properties or events.SessionProperties(), - ) - self._sync_model_name_to_metrics() self._audio_input_paused = start_audio_paused self._send_transcription_frames = send_transcription_frames self._websocket = None diff --git a/src/pipecat/services/piper/tts.py b/src/pipecat/services/piper/tts.py index e6a2c6943..c4831b839 100644 --- a/src/pipecat/services/piper/tts.py +++ b/src/pipecat/services/piper/tts.py @@ -69,9 +69,10 @@ class PiperTTSService(TTSService): use_cuda: Use CUDA for GPU-accelerated inference. **kwargs: Additional arguments passed to the parent `TTSService`. """ - super().__init__(**kwargs) - - self._settings = PiperTTSSettings(model=None, voice=voice_id, language=None) + super().__init__( + settings=PiperTTSSettings(model=None, voice=voice_id, language=None), + **kwargs, + ) download_dir = download_dir or Path.cwd() @@ -199,7 +200,10 @@ class PiperHttpTTSService(TTSService): voice_id: Piper voice model identifier (e.g. `en_US-ryan-high`). **kwargs: Additional arguments passed to the parent TTSService. """ - super().__init__(**kwargs) + super().__init__( + settings=PiperHttpTTSSettings(model=None, voice=voice_id, language=None), + **kwargs, + ) if base_url.endswith("/"): logger.warning("Base URL ends with a slash, this is not allowed.") @@ -207,7 +211,6 @@ class PiperHttpTTSService(TTSService): self._base_url = base_url self._session = aiohttp_session - self._settings = PiperHttpTTSSettings(model=None, voice=voice_id, language=None) def can_generate_metrics(self) -> bool: """Check if this service can generate processing metrics. diff --git a/src/pipecat/services/resembleai/tts.py b/src/pipecat/services/resembleai/tts.py index c2ac758a7..1c2953b72 100644 --- a/src/pipecat/services/resembleai/tts.py +++ b/src/pipecat/services/resembleai/tts.py @@ -92,19 +92,19 @@ class ResembleAITTSService(AudioContextTTSService): sample_rate=sample_rate, reuse_context_id_within_turn=False, supports_word_timestamps=True, + settings=ResembleAITTSSettings( + model=None, + voice=voice_id, + language=None, + precision=precision, + output_format=output_format, + resemble_sample_rate=sample_rate, + ), **kwargs, ) self._api_key = api_key self._url = url - self._settings = ResembleAITTSSettings( - model=None, - voice=voice_id, - language=None, - precision=precision, - output_format=output_format, - resemble_sample_rate=sample_rate, - ) self._websocket = None self._request_id_counter = 0 diff --git a/src/pipecat/services/rime/tts.py b/src/pipecat/services/rime/tts.py index 484c99857..059db8178 100644 --- a/src/pipecat/services/rime/tts.py +++ b/src/pipecat/services/rime/tts.py @@ -202,6 +202,8 @@ class RimeTTSService(AudioContextTTSService): **kwargs: Additional arguments passed to parent class. """ # Initialize with parent class settings for proper frame handling + params = params or RimeTTSService.InputParams() + super().__init__( aggregate_sentences=aggregate_sentences, push_text_frames=False, @@ -210,6 +212,28 @@ class RimeTTSService(AudioContextTTSService): supports_word_timestamps=True, append_trailing_space=True, sample_rate=sample_rate, + settings=RimeTTSSettings( + model=model, + voice=voice_id, + audioFormat="pcm", + samplingRate=0, # updated in start() + language=self.language_to_service_language(params.language) + if params.language + else None, + segment=params.segment, + inlineSpeedAlpha=None, # Not applicable here + # Arcana params + repetition_penalty=params.repetition_penalty, + temperature=params.temperature, + top_p=params.top_p, + # Mistv2 params + speedAlpha=params.speed_alpha, + reduceLatency=params.reduce_latency, + pauseBetweenBrackets=params.pause_between_brackets, + phonemizeBetweenBrackets=params.phonemize_between_brackets, + noTextNormalization=params.no_text_normalization, + saveOovs=params.save_oovs, + ), **kwargs, ) @@ -221,34 +245,9 @@ class RimeTTSService(AudioContextTTSService): # and insert these tags for the purpose of the TTS service alone. self._text_aggregator = SkipTagsAggregator([("spell(", ")")]) - params = params or RimeTTSService.InputParams() - # Store service configuration self._api_key = api_key self._url = url - self._settings = RimeTTSSettings( - model=model, - voice=voice_id, - audioFormat="pcm", - samplingRate=0, # updated in start() - language=self.language_to_service_language(params.language) - if params.language - else None, - segment=params.segment, - inlineSpeedAlpha=None, # Not applicable here - # Arcana params - repetition_penalty=params.repetition_penalty, - temperature=params.temperature, - top_p=params.top_p, - # Mistv2 params - speedAlpha=params.speed_alpha, - reduceLatency=params.reduce_latency, - pauseBetweenBrackets=params.pause_between_brackets, - phonemizeBetweenBrackets=params.phonemize_between_brackets, - noTextNormalization=params.no_text_normalization, - saveOovs=params.save_oovs, - ) - self._sync_model_name_to_metrics() # State tracking self._receive_task = None @@ -657,34 +656,36 @@ class RimeHttpTTSService(TTSService): params: Additional configuration parameters. **kwargs: Additional arguments passed to parent TTSService. """ - super().__init__(sample_rate=sample_rate, **kwargs) - params = params or RimeHttpTTSService.InputParams() + super().__init__( + sample_rate=sample_rate, + settings=RimeTTSSettings( + model=model, + language=self.language_to_service_language(params.language) + if params.language + else "eng", + audioFormat="pcm", + samplingRate=0, + segment=None, + speedAlpha=params.speed_alpha, + reduceLatency=params.reduce_latency, + pauseBetweenBrackets=params.pause_between_brackets, + phonemizeBetweenBrackets=params.phonemize_between_brackets, + noTextNormalization=None, + saveOovs=None, + inlineSpeedAlpha=params.inline_speed_alpha if params.inline_speed_alpha else None, + repetition_penalty=None, + temperature=None, + top_p=None, + voice=voice_id, + ), + **kwargs, + ) + self._api_key = api_key self._session = aiohttp_session self._base_url = "https://users.rime.ai/v1/rime-tts" - self._settings = RimeTTSSettings( - model=model, - language=self.language_to_service_language(params.language) - if params.language - else "eng", - audioFormat="pcm", - samplingRate=0, - segment=None, - speedAlpha=params.speed_alpha, - reduceLatency=params.reduce_latency, - pauseBetweenBrackets=params.pause_between_brackets, - phonemizeBetweenBrackets=params.phonemize_between_brackets, - noTextNormalization=None, - saveOovs=None, - inlineSpeedAlpha=params.inline_speed_alpha if params.inline_speed_alpha else None, - repetition_penalty=None, - temperature=None, - top_p=None, - voice=voice_id, - ) - self._sync_model_name_to_metrics() def can_generate_metrics(self) -> bool: """Check if this service can generate processing metrics. @@ -841,31 +842,30 @@ class RimeNonJsonTTSService(InterruptibleTTSService): aggregate_sentences: Whether to aggregate sentences within the TTSService. **kwargs: Additional arguments passed to parent class. """ + params = params or RimeNonJsonTTSService.InputParams() super().__init__( sample_rate=sample_rate, aggregate_sentences=aggregate_sentences, push_stop_frames=True, pause_frame_processing=True, append_trailing_space=True, + settings=RimeNonJsonTTSSettings( + voice=voice_id, + model=model, + audioFormat=audio_format, + samplingRate=sample_rate, + language=self.language_to_service_language(params.language) + if params.language + else None, + segment=params.segment, + repetition_penalty=params.repetition_penalty, + temperature=params.temperature, + top_p=params.top_p, + ), **kwargs, ) - params = params or RimeNonJsonTTSService.InputParams() self._api_key = api_key self._url = url - self._settings = RimeNonJsonTTSSettings( - voice=voice_id, - model=model, - audioFormat=audio_format, - samplingRate=sample_rate, - language=self.language_to_service_language(params.language) - if params.language - else None, - segment=params.segment, - repetition_penalty=params.repetition_penalty, - temperature=params.temperature, - top_p=params.top_p, - ) - self._sync_model_name_to_metrics() # Add any extra parameters for future compatibility if params.extra: self._settings.extra.update(params.extra) diff --git a/src/pipecat/services/sarvam/stt.py b/src/pipecat/services/sarvam/stt.py index 02d6e250f..379473c6f 100644 --- a/src/pipecat/services/sarvam/stt.py +++ b/src/pipecat/services/sarvam/stt.py @@ -240,11 +240,22 @@ class SarvamSTTService(STTService): f"Model '{model}' does not support language parameter (auto-detects language)." ) + # Resolve mode default from model config + mode = params.mode if params.mode is not None else self._config.default_mode + super().__init__( sample_rate=sample_rate, ttfs_p99_latency=ttfs_p99_latency, keepalive_timeout=keepalive_timeout, keepalive_interval=keepalive_interval, + settings=SarvamSTTSettings( + model=model, + language=params.language, + prompt=params.prompt, + mode=mode, + vad_signals=params.vad_signals, + high_vad_sensitivity=params.high_vad_sensitivity, + ), **kwargs, ) @@ -268,19 +279,6 @@ class SarvamSTTService(STTService): self._socket_client = None self._receive_task = None - # Resolve mode default from model config - mode = params.mode if params.mode is not None else self._config.default_mode - - self._settings = SarvamSTTSettings( - model=model, - language=params.language, - prompt=params.prompt, - mode=mode, - vad_signals=params.vad_signals, - high_vad_sensitivity=params.high_vad_sensitivity, - ) - self._sync_model_name_to_metrics() - if params.vad_signals: self._register_event_handler("on_speech_started") self._register_event_handler("on_speech_stopped") diff --git a/src/pipecat/services/sarvam/tts.py b/src/pipecat/services/sarvam/tts.py index ade547798..7b63828a1 100644 --- a/src/pipecat/services/sarvam/tts.py +++ b/src/pipecat/services/sarvam/tts.py @@ -466,12 +466,6 @@ class SarvamHttpTTSService(TTSService): if voice_id is None: voice_id = self._config.default_speaker - super().__init__(sample_rate=sample_rate, **kwargs) - - self._api_key = api_key - self._base_url = base_url - self._session = aiohttp_session - # Validate and clamp pace to model's valid range pace = params.pace pace_min, pace_max = self._config.pace_range @@ -479,22 +473,32 @@ class SarvamHttpTTSService(TTSService): logger.warning(f"Pace {pace} is outside model range ({pace_min}-{pace_max}). Clamping.") pace = max(pace_min, min(pace_max, pace)) - # Build base settings - self._settings = SarvamHttpTTSSettings( - language=( - self.language_to_service_language(params.language) if params.language else "en-IN" + super().__init__( + sample_rate=sample_rate, + settings=SarvamHttpTTSSettings( + language=( + self.language_to_service_language(params.language) + if params.language + else "en-IN" + ), + enable_preprocessing=( + True + if self._config.preprocessing_always_enabled + else params.enable_preprocessing + ), + pace=pace, + pitch=None, + loudness=None, + temperature=None, + model=model, + voice=voice_id, ), - enable_preprocessing=( - True if self._config.preprocessing_always_enabled else params.enable_preprocessing - ), - pace=pace, - pitch=None, - loudness=None, - temperature=None, - model=model, - voice=voice_id, + **kwargs, ) - self._sync_model_name_to_metrics() + + self._api_key = api_key + self._base_url = base_url + self._session = aiohttp_session # Add parameters based on model support if self._config.supports_pitch: @@ -818,21 +822,8 @@ class SarvamTTSService(InterruptibleTTSService): if voice_id is None: voice_id = self._config.default_speaker - # Initialize parent class first - super().__init__( - aggregate_sentences=aggregate_sentences, - push_text_frames=True, - pause_frame_processing=True, - push_stop_frames=True, - sample_rate=sample_rate, - **kwargs, - ) params = params or SarvamTTSService.InputParams() - # WebSocket endpoint URL with model query parameter - self._websocket_url = f"{url}?model={model}" - self._api_key = api_key - # Validate and clamp pace to model's valid range pace = params.pace pace_min, pace_max = self._config.pace_range @@ -840,27 +831,42 @@ class SarvamTTSService(InterruptibleTTSService): logger.warning(f"Pace {pace} is outside model range ({pace_min}-{pace_max}). Clamping.") pace = max(pace_min, min(pace_max, pace)) - # Build base settings - self._settings = SarvamTTSSettings( - language=( - self.language_to_service_language(params.language) if params.language else "en-IN" + # Initialize parent class first + super().__init__( + aggregate_sentences=aggregate_sentences, + push_text_frames=True, + pause_frame_processing=True, + push_stop_frames=True, + sample_rate=sample_rate, + settings=SarvamTTSSettings( + language=( + self.language_to_service_language(params.language) + if params.language + else "en-IN" + ), + speech_sample_rate=str(sample_rate), + enable_preprocessing=( + True + if self._config.preprocessing_always_enabled + else params.enable_preprocessing + ), + min_buffer_size=params.min_buffer_size, + max_chunk_length=params.max_chunk_length, + output_audio_codec=params.output_audio_codec, + output_audio_bitrate=params.output_audio_bitrate, + pace=pace, + pitch=None, + loudness=None, + temperature=None, + model=model, + voice=voice_id, ), - speech_sample_rate=str(sample_rate), - enable_preprocessing=( - True if self._config.preprocessing_always_enabled else params.enable_preprocessing - ), - min_buffer_size=params.min_buffer_size, - max_chunk_length=params.max_chunk_length, - output_audio_codec=params.output_audio_codec, - output_audio_bitrate=params.output_audio_bitrate, - pace=pace, - pitch=None, - loudness=None, - temperature=None, - model=model, - voice=voice_id, + **kwargs, ) - self._sync_model_name_to_metrics() + + # WebSocket endpoint URL with model query parameter + self._websocket_url = f"{url}?model={model}" + self._api_key = api_key # Add parameters based on model support if self._config.supports_pitch: diff --git a/src/pipecat/services/settings.py b/src/pipecat/services/settings.py index 641cc23f5..5d215273f 100644 --- a/src/pipecat/services/settings.py +++ b/src/pipecat/services/settings.py @@ -319,6 +319,28 @@ class ServiceSettings: # --------------------------------------------------------------------------- +@dataclass +class ImageGenSettings(ServiceSettings): + """Runtime-updatable settings for image generation services. + + Used in both store and delta mode — see ``ServiceSettings``. + + Parameters: + model: Image generation model identifier. + """ + + +@dataclass +class VisionSettings(ServiceSettings): + """Runtime-updatable settings for vision services. + + Used in both store and delta mode — see ``ServiceSettings``. + + Parameters: + model: Vision model identifier. + """ + + @dataclass class LLMSettings(ServiceSettings): """Runtime-updatable settings for LLM services. diff --git a/src/pipecat/services/soniox/stt.py b/src/pipecat/services/soniox/stt.py index 3160d19a6..32cbee1f4 100644 --- a/src/pipecat/services/soniox/stt.py +++ b/src/pipecat/services/soniox/stt.py @@ -202,33 +202,32 @@ class SonioxSTTService(WebsocketSTTService): Override for your deployment. See https://github.com/pipecat-ai/stt-benchmark **kwargs: Additional arguments passed to the STTService. """ + params = params or SonioxInputParams() + super().__init__( sample_rate=sample_rate, ttfs_p99_latency=ttfs_p99_latency, keepalive_timeout=1, keepalive_interval=5, + settings=SonioxSTTSettings( + model=params.model, + language=None, + audio_format=params.audio_format, + num_channels=params.num_channels, + language_hints=params.language_hints, + language_hints_strict=params.language_hints_strict, + context=params.context, + enable_speaker_diarization=params.enable_speaker_diarization, + enable_language_identification=params.enable_language_identification, + client_reference_id=params.client_reference_id, + ), **kwargs, ) - params = params or SonioxInputParams() self._api_key = api_key self._url = url self._vad_force_turn_endpoint = vad_force_turn_endpoint - self._settings = SonioxSTTSettings( - model=params.model, - language=None, - audio_format=params.audio_format, - num_channels=params.num_channels, - language_hints=params.language_hints, - language_hints_strict=params.language_hints_strict, - context=params.context, - enable_speaker_diarization=params.enable_speaker_diarization, - enable_language_identification=params.enable_language_identification, - client_reference_id=params.client_reference_id, - ) - self._sync_model_name_to_metrics() - self._final_transcription_buffer = [] self._last_tokens_received: Optional[float] = None diff --git a/src/pipecat/services/speechmatics/stt.py b/src/pipecat/services/speechmatics/stt.py index 61bf8b69f..ac18a36e3 100644 --- a/src/pipecat/services/speechmatics/stt.py +++ b/src/pipecat/services/speechmatics/stt.py @@ -398,8 +398,6 @@ class SpeechmaticsSTTService(STTService): Override for your deployment. See https://github.com/pipecat-ai/stt-benchmark **kwargs: Additional arguments passed to STTService. """ - super().__init__(sample_rate=sample_rate, ttfs_p99_latency=ttfs_p99_latency, **kwargs) - # Service parameters self._api_key: str = api_key or os.getenv("SPEECHMATICS_API_KEY") self._base_url: str = ( @@ -428,8 +426,8 @@ class SpeechmaticsSTTService(STTService): speaker_passive_format = params.speaker_passive_format or speaker_active_format # Settings — seeded from InputParams - self._settings = SpeechmaticsSTTSettings( - model=None, + settings = SpeechmaticsSTTSettings( + model=None, # Will be resolved from operating_point after config is built language=params.language, domain=params.domain, turn_detection_mode=params.turn_detection_mode, @@ -455,9 +453,17 @@ class SpeechmaticsSTTService(STTService): extra_params=params.extra_params, ) - # Build SDK config from settings + # Build SDK config from settings, then resolve model from operating_point self._client: VoiceAgentClient | None = None - self._config: VoiceAgentConfig = self._build_config() + self._config: VoiceAgentConfig = self._build_config(settings) + settings.model = self._config.operating_point.value + + super().__init__( + sample_rate=sample_rate, + ttfs_p99_latency=ttfs_p99_latency, + settings=settings, + **kwargs, + ) # Outbound frame queue self._outbound_frames: asyncio.Queue[Frame] = asyncio.Queue() @@ -468,10 +474,6 @@ class SpeechmaticsSTTService(STTService): EndOfUtteranceMode.EXTERNAL, ] - # Model + metrics (operating_point comes from the SDK config/preset) - self._settings.model = self._config.operating_point.value - self._sync_model_name_to_metrics() - # Message queue self._stt_msg_queue: asyncio.Queue[dict[str, Any]] = asyncio.Queue() self._stt_msg_task: asyncio.Task | None = None @@ -524,7 +526,7 @@ class SpeechmaticsSTTService(STTService): logger.debug(f"{self} settings update requires reconnect: {changed.keys()}") # Connection-level fields changed — rebuild the SDK config # from the now-updated self._settings, then reconnect. - self._config = self._build_config() + self._config = self._build_config(self._settings) await self._disconnect() await self._connect() elif changed.keys() & SpeechmaticsSTTSettings.HOT_FIELDS: @@ -661,13 +663,17 @@ class SpeechmaticsSTTService(STTService): # CONFIGURATION # ============================================================================ - def _build_config(self) -> VoiceAgentConfig: - """Build a ``VoiceAgentConfig`` from the current ``self._settings``. + def _build_config(self, settings: SpeechmaticsSTTSettings) -> VoiceAgentConfig: + """Build a ``VoiceAgentConfig`` from the given settings. - Used both at init time and before reconnecting so the connection - always reflects the latest settings. + Used both at init time (with explicit settings, before + ``super().__init__`` has run) and before reconnecting so the + connection always reflects the latest settings. + + Args: + settings: Settings to build from. """ - s = self._settings + s = settings # Preset from turn detection mode config = VoiceAgentConfigPreset.load(s.turn_detection_mode.value) diff --git a/src/pipecat/services/speechmatics/tts.py b/src/pipecat/services/speechmatics/tts.py index 32fb0c2b3..1ddb895aa 100644 --- a/src/pipecat/services/speechmatics/tts.py +++ b/src/pipecat/services/speechmatics/tts.py @@ -95,7 +95,18 @@ class SpeechmaticsTTSService(TTSService): f"Speechmatics TTS only supports {self.SPEECHMATICS_SAMPLE_RATE}Hz sample rate. " f"Current rate of {sample_rate}Hz may cause issues." ) - super().__init__(sample_rate=sample_rate, **kwargs) + params = params or SpeechmaticsTTSService.InputParams() + + super().__init__( + sample_rate=sample_rate, + settings=SpeechmaticsTTSSettings( + model=None, + voice=voice_id, + language=None, + max_retries=params.max_retries, + ), + **kwargs, + ) # Service parameters self._api_key: str = api_key @@ -106,14 +117,6 @@ class SpeechmaticsTTSService(TTSService): if not self._api_key: raise ValueError("Missing Speechmatics API key") - params = params or SpeechmaticsTTSService.InputParams() - self._settings = SpeechmaticsTTSSettings( - model=None, - voice=voice_id, - language=None, - max_retries=params.max_retries, - ) - def can_generate_metrics(self) -> bool: """Check if this service can generate processing metrics. diff --git a/src/pipecat/services/stt_service.py b/src/pipecat/services/stt_service.py index 20e8cacc9..ebf007f6f 100644 --- a/src/pipecat/services/stt_service.py +++ b/src/pipecat/services/stt_service.py @@ -86,6 +86,7 @@ class STTService(AIService): ttfs_p99_latency: Optional[float] = None, keepalive_timeout: Optional[float] = None, keepalive_interval: float = 5.0, + settings: Optional[STTSettings] = None, **kwargs, ): """Initialize the STT service. @@ -109,14 +110,20 @@ class STTService(AIService): connection alive. None disables keepalive. Useful for services that close idle connections (e.g. behind a ServiceSwitcher). keepalive_interval: Seconds between idle checks when keepalive is enabled. + settings: The runtime-updatable settings for the STT service. **kwargs: Additional arguments passed to the parent AIService. """ - super().__init__(**kwargs) + super().__init__( + settings=settings + # Here in case subclass doesn't implement more specific settings + # (which hopefully should be rare) + or STTSettings(), + **kwargs, + ) self._audio_passthrough = audio_passthrough self._init_sample_rate = sample_rate self._sample_rate = 0 - self._settings = STTSettings() # Here in case subclass doesn't implement more specific settings (hopefully shouldn't happen) self._muted: bool = False self._user_id: str = "" self._ttfs_p99_latency = ttfs_p99_latency diff --git a/src/pipecat/services/tts_service.py b/src/pipecat/services/tts_service.py index e739a03d2..e36d4754f 100644 --- a/src/pipecat/services/tts_service.py +++ b/src/pipecat/services/tts_service.py @@ -147,6 +147,7 @@ class TTSService(AIService): text_filter: Optional[BaseTextFilter] = None, # Audio transport destination of the generated frames. transport_destination: Optional[str] = None, + settings: Optional[TTSSettings] = None, **kwargs, ): """Initialize the TTS service. @@ -183,9 +184,16 @@ class TTSService(AIService): Use `text_filters` instead, which allows multiple filters. transport_destination: Destination for generated audio frames. + settings: The runtime-updatable settings for the TTS service. **kwargs: Additional arguments passed to the parent AIService. """ - super().__init__(**kwargs) + super().__init__( + settings=settings + # Here in case subclass doesn't implement more specific settings + # (which hopefully should be rare) + or TTSSettings(), + **kwargs, + ) self._aggregate_sentences: bool = aggregate_sentences self._push_text_frames: bool = push_text_frames self._push_stop_frames: bool = push_stop_frames @@ -196,7 +204,6 @@ class TTSService(AIService): self._append_trailing_space: bool = append_trailing_space self._init_sample_rate = sample_rate self._sample_rate = 0 - self._settings = TTSSettings() # Here in case subclass doesn't implement more specific settings (hopefully shouldn't happen) self._text_aggregator: BaseTextAggregator = text_aggregator or SimpleTextAggregator() if text_aggregator: import warnings diff --git a/src/pipecat/services/ultravox/llm.py b/src/pipecat/services/ultravox/llm.py index 11525258a..d14c3b9ca 100644 --- a/src/pipecat/services/ultravox/llm.py +++ b/src/pipecat/services/ultravox/llm.py @@ -176,19 +176,21 @@ class UltravoxRealtimeLLMService(LLMService): May only be set with OneShotInputParams. **kwargs: Additional arguments passed to parent LLMService. """ - super().__init__(**kwargs) - self._settings = UltravoxRealtimeLLMSettings( - model=None, - temperature=None, - max_tokens=None, - top_p=None, - top_k=None, - frequency_penalty=None, - presence_penalty=None, - seed=None, - filter_incomplete_user_turns=False, - user_turn_completion_config=None, - output_medium=None, + super().__init__( + settings=UltravoxRealtimeLLMSettings( + model=None, + temperature=None, + max_tokens=None, + top_p=None, + top_k=None, + frequency_penalty=None, + presence_penalty=None, + seed=None, + filter_incomplete_user_turns=False, + user_turn_completion_config=None, + output_medium=None, + ), + **kwargs, ) self._params = params if one_shot_selected_tools: diff --git a/src/pipecat/services/vision_service.py b/src/pipecat/services/vision_service.py index d12737d84..572f3b423 100644 --- a/src/pipecat/services/vision_service.py +++ b/src/pipecat/services/vision_service.py @@ -12,11 +12,12 @@ visual content. """ from abc import abstractmethod -from typing import AsyncGenerator +from typing import AsyncGenerator, Optional from pipecat.frames.frames import Frame, UserImageRawFrame from pipecat.processors.frame_processor import FrameDirection from pipecat.services.ai_service import AIService +from pipecat.services.settings import VisionSettings class VisionService(AIService): @@ -27,13 +28,20 @@ class VisionService(AIService): with the AI service infrastructure for metrics and lifecycle management. """ - def __init__(self, **kwargs): + def __init__(self, *, settings: Optional[VisionSettings] = None, **kwargs): """Initialize the vision service. Args: + settings: The runtime-updatable settings for the vision service. **kwargs: Additional arguments passed to the parent AIService. """ - super().__init__(**kwargs) + super().__init__( + settings=settings + # Here in case subclass doesn't implement more specific settings + # (which hopefully should be rare) + or VisionSettings(), + **kwargs, + ) self._describe_text = None @abstractmethod diff --git a/src/pipecat/services/whisper/base_stt.py b/src/pipecat/services/whisper/base_stt.py index 9d2b3ab51..cf3342f4b 100644 --- a/src/pipecat/services/whisper/base_stt.py +++ b/src/pipecat/services/whisper/base_stt.py @@ -155,22 +155,23 @@ class BaseWhisperSTTService(SegmentedSTTService): Override for your deployment. See https://github.com/pipecat-ai/stt-benchmark **kwargs: Additional arguments passed to SegmentedSTTService. """ - super().__init__(ttfs_p99_latency=ttfs_p99_latency, **kwargs) + super().__init__( + ttfs_p99_latency=ttfs_p99_latency, + settings=BaseWhisperSTTSettings( + model=model, + language=self.language_to_service_language(language or Language.EN), + base_url=base_url, + prompt=prompt, + temperature=temperature, + ), + **kwargs, + ) self._client = self._create_client(api_key, base_url) - self._language = self.language_to_service_language(language or Language.EN) + self._language = self._settings.language self._prompt = prompt self._temperature = temperature self._include_prob_metrics = include_prob_metrics - self._settings = BaseWhisperSTTSettings( - model=model, - language=self._language, - base_url=base_url, - prompt=self._prompt, - temperature=self._temperature, - ) - self._sync_model_name_to_metrics() - def _create_client(self, api_key: Optional[str], base_url: Optional[str]): return AsyncOpenAI(api_key=api_key, base_url=base_url) diff --git a/src/pipecat/services/whisper/stt.py b/src/pipecat/services/whisper/stt.py index 205838314..d386d6ed2 100644 --- a/src/pipecat/services/whisper/stt.py +++ b/src/pipecat/services/whisper/stt.py @@ -233,21 +233,21 @@ class WhisperSTTService(SegmentedSTTService): language: The default language for transcription. **kwargs: Additional arguments passed to SegmentedSTTService. """ - super().__init__(**kwargs) + super().__init__( + settings=WhisperSTTSettings( + model=model if isinstance(model, str) else model.value, + language=language, + device=device, + compute_type=compute_type, + no_speech_prob=no_speech_prob, + ), + **kwargs, + ) self._device: str = device self._compute_type = compute_type self._no_speech_prob = no_speech_prob self._model: Optional[WhisperModel] = None - self._settings = WhisperSTTSettings( - model=model if isinstance(model, str) else model.value, - language=language, - device=self._device, - compute_type=self._compute_type, - no_speech_prob=self._no_speech_prob, - ) - self._sync_model_name_to_metrics() - self._load() def can_generate_metrics(self) -> bool: @@ -368,20 +368,21 @@ class WhisperSTTServiceMLX(WhisperSTTService): **kwargs: Additional arguments passed to SegmentedSTTService. """ # Skip WhisperSTTService.__init__ and call its parent directly - SegmentedSTTService.__init__(self, **kwargs) + SegmentedSTTService.__init__( + self, + settings=WhisperMLXSTTSettings( + model=model if isinstance(model, str) else model.value, + language=language, + no_speech_prob=no_speech_prob, + temperature=temperature, + engine="mlx", + ), + **kwargs, + ) self._no_speech_prob = no_speech_prob self._temperature = temperature - self._settings = WhisperMLXSTTSettings( - model=model if isinstance(model, str) else model.value, - language=language, - no_speech_prob=self._no_speech_prob, - temperature=self._temperature, - engine="mlx", - ) - self._sync_model_name_to_metrics() - # No need to call _load() as MLX Whisper loads models on demand @override diff --git a/src/pipecat/services/xtts/tts.py b/src/pipecat/services/xtts/tts.py index ab06ffb5a..8817c09b5 100644 --- a/src/pipecat/services/xtts/tts.py +++ b/src/pipecat/services/xtts/tts.py @@ -111,13 +111,15 @@ class XTTSService(TTSService): sample_rate: Audio sample rate. If None, uses default. **kwargs: Additional arguments passed to parent TTSService. """ - super().__init__(sample_rate=sample_rate, **kwargs) - - self._settings = XTTSTTSSettings( - model=None, - voice=voice_id, - language=self.language_to_service_language(language), - base_url=base_url, + super().__init__( + sample_rate=sample_rate, + settings=XTTSTTSSettings( + model=None, + voice=voice_id, + language=self.language_to_service_language(language), + base_url=base_url, + ), + **kwargs, ) self._studio_speakers: Optional[Dict[str, Any]] = None self._aiohttp_session = aiohttp_session From bca42f7d68b71abdacdaecf008e4a0142d1b3040 Mon Sep 17 00:00:00 2001 From: Paul Kompfner Date: Wed, 25 Feb 2026 14:03:53 -0500 Subject: [PATCH 0640/1060] Fix Hathora 55 series examples, and fix Hathora missing settings field warning --- examples/foundational/55zg-update-settings-hathora-tts.py | 6 +++--- examples/foundational/55zs-update-settings-hathora-stt.py | 4 +++- src/pipecat/services/hathora/tts.py | 1 + 3 files changed, 7 insertions(+), 4 deletions(-) diff --git a/examples/foundational/55zg-update-settings-hathora-tts.py b/examples/foundational/55zg-update-settings-hathora-tts.py index 9f6b6bd0a..80b9bfcce 100644 --- a/examples/foundational/55zg-update-settings-hathora-tts.py +++ b/examples/foundational/55zg-update-settings-hathora-tts.py @@ -54,7 +54,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): tts = HathoraTTSService( api_key=os.getenv("HATHORA_API_KEY"), - model="hathora-ai/polar", + model="hexgrad-kokoro-82m", ) llm = OpenAILLMService(api_key=os.getenv("OPENAI_API_KEY")) @@ -100,8 +100,8 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): await task.queue_frames([LLMRunFrame()]) await asyncio.sleep(10) - logger.info("Updating Hathora TTS settings: speed=1.3") - await task.queue_frame(TTSUpdateSettingsFrame(delta=HathoraTTSSettings(speed=1.3))) + logger.info("Updating Hathora TTS settings: speed=1.5") + await task.queue_frame(TTSUpdateSettingsFrame(delta=HathoraTTSSettings(speed=1.5))) @transport.event_handler("on_client_disconnected") async def on_client_disconnected(transport, client): diff --git a/examples/foundational/55zs-update-settings-hathora-stt.py b/examples/foundational/55zs-update-settings-hathora-stt.py index db5ed4d2a..7a033490a 100644 --- a/examples/foundational/55zs-update-settings-hathora-stt.py +++ b/examples/foundational/55zs-update-settings-hathora-stt.py @@ -52,7 +52,9 @@ transport_params = { async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): logger.info(f"Starting bot") - stt = HathoraSTTService(api_key=os.getenv("HATHORA_API_KEY"), model="deepgram-nova3") + stt = HathoraSTTService( + api_key=os.getenv("HATHORA_API_KEY"), model="nvidia-parakeet-tdt-0.6b-v3" + ) tts = CartesiaTTSService( api_key=os.getenv("CARTESIA_API_KEY"), diff --git a/src/pipecat/services/hathora/tts.py b/src/pipecat/services/hathora/tts.py index e16aa3b08..8d6fb32cb 100644 --- a/src/pipecat/services/hathora/tts.py +++ b/src/pipecat/services/hathora/tts.py @@ -114,6 +114,7 @@ class HathoraTTSService(TTSService): settings=HathoraTTSSettings( model=model, voice=voice_id, + language=None, # Not applicable here speed=params.speed, config=params.config, ), From ff0f3dce3209e38867e0eba97323bb328fb327f4 Mon Sep 17 00:00:00 2001 From: Paul Kompfner Date: Wed, 25 Feb 2026 15:10:11 -0500 Subject: [PATCH 0641/1060] A few Groq-related tweaks: - Wire up passing speed setting to Groq, even though only a value of 1.0 is supported today - Update the 55y example to switch voices instead of changing speed - Add a 55zn example to exercise runtime updates of Groq STT --- .../55y-update-settings-groq-tts.py | 4 +- .../55zzn-update-settings-groq-stt.py | 128 ++++++++++++++++++ src/pipecat/services/groq/tts.py | 3 + 3 files changed, 133 insertions(+), 2 deletions(-) create mode 100644 examples/foundational/55zzn-update-settings-groq-stt.py diff --git a/examples/foundational/55y-update-settings-groq-tts.py b/examples/foundational/55y-update-settings-groq-tts.py index 86dc1f98a..3531509f2 100644 --- a/examples/foundational/55y-update-settings-groq-tts.py +++ b/examples/foundational/55y-update-settings-groq-tts.py @@ -97,8 +97,8 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): await task.queue_frames([LLMRunFrame()]) await asyncio.sleep(10) - logger.info("Updating Groq TTS settings: speed=1.5") - await task.queue_frame(TTSUpdateSettingsFrame(delta=GroqTTSSettings(speed=1.5))) + logger.info("Updating Groq TTS settings: voice=troy") + await task.queue_frame(TTSUpdateSettingsFrame(delta=GroqTTSSettings(voice="troy"))) @transport.event_handler("on_client_disconnected") async def on_client_disconnected(transport, client): diff --git a/examples/foundational/55zzn-update-settings-groq-stt.py b/examples/foundational/55zzn-update-settings-groq-stt.py new file mode 100644 index 000000000..b00ecda81 --- /dev/null +++ b/examples/foundational/55zzn-update-settings-groq-stt.py @@ -0,0 +1,128 @@ +# +# Copyright (c) 2024-2026, Daily +# +# SPDX-License-Identifier: BSD 2-Clause License +# + +import asyncio +import os + +from dotenv import load_dotenv +from loguru import logger + +from pipecat.audio.vad.silero import SileroVADAnalyzer +from pipecat.frames.frames import LLMRunFrame, STTUpdateSettingsFrame +from pipecat.pipeline.pipeline import Pipeline +from pipecat.pipeline.runner import PipelineRunner +from pipecat.pipeline.task import PipelineParams, PipelineTask +from pipecat.processors.aggregators.llm_context import LLMContext +from pipecat.processors.aggregators.llm_response_universal import ( + LLMContextAggregatorPair, + LLMUserAggregatorParams, +) +from pipecat.runner.types import RunnerArguments +from pipecat.runner.utils import create_transport +from pipecat.services.cartesia.tts import CartesiaTTSService +from pipecat.services.groq.stt import GroqSTTService +from pipecat.services.openai.llm import OpenAILLMService +from pipecat.services.whisper.base_stt import BaseWhisperSTTSettings +from pipecat.transports.base_transport import BaseTransport, TransportParams +from pipecat.transports.daily.transport import DailyParams +from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams + +load_dotenv(override=True) + +transport_params = { + "daily": lambda: DailyParams( + audio_in_enabled=True, + audio_out_enabled=True, + ), + "twilio": lambda: FastAPIWebsocketParams( + audio_in_enabled=True, + audio_out_enabled=True, + ), + "webrtc": lambda: TransportParams( + audio_in_enabled=True, + audio_out_enabled=True, + ), +} + + +async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): + logger.info(f"Starting bot") + + stt = GroqSTTService( + api_key=os.getenv("GROQ_API_KEY"), + ) + + tts = CartesiaTTSService( + api_key=os.getenv("CARTESIA_API_KEY"), + voice_id="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady + ) + + llm = OpenAILLMService(api_key=os.getenv("OPENAI_API_KEY")) + + messages = [ + { + "role": "system", + "content": "You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + }, + ] + + context = LLMContext(messages) + user_aggregator, assistant_aggregator = LLMContextAggregatorPair( + context, + user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()), + ) + + pipeline = Pipeline( + [ + transport.input(), + stt, + user_aggregator, + llm, + tts, + transport.output(), + assistant_aggregator, + ] + ) + + task = PipelineTask( + pipeline, + params=PipelineParams( + enable_metrics=True, + enable_usage_metrics=True, + ), + idle_timeout_secs=runner_args.pipeline_idle_timeout_secs, + ) + + @transport.event_handler("on_client_connected") + async def on_client_connected(transport, client): + logger.info(f"Client connected") + messages.append({"role": "system", "content": "Please introduce yourself to the user."}) + await task.queue_frames([LLMRunFrame()]) + + await asyncio.sleep(10) + logger.info('Updating Groq STT settings: language="es"') + await task.queue_frame(STTUpdateSettingsFrame(delta=BaseWhisperSTTSettings(language="es"))) + + @transport.event_handler("on_client_disconnected") + async def on_client_disconnected(transport, client): + logger.info(f"Client disconnected") + await task.cancel() + + runner = PipelineRunner(handle_sigint=runner_args.handle_sigint) + + await runner.run(task) + + +async def bot(runner_args: RunnerArguments): + """Main bot entry point compatible with Pipecat Cloud.""" + transport = await create_transport(runner_args, transport_params) + await run_bot(transport, runner_args) + + +if __name__ == "__main__": + from pipecat.runner.run import main + + main() diff --git a/src/pipecat/services/groq/tts.py b/src/pipecat/services/groq/tts.py index cc073f8c7..95ee6faa3 100644 --- a/src/pipecat/services/groq/tts.py +++ b/src/pipecat/services/groq/tts.py @@ -152,6 +152,9 @@ class GroqTTSService(TTSService): model=self._settings.model, voice=self._settings.voice, response_format=self._output_format, + # Note: as of 2026-02-25, only a speed of 1.0 is supported, but + # here we pass it for completeness and future-proofing + speed=self._settings.speed, input=text, ) From eee2ef7e859c66a60c1d0e976e907f10829d0f6c Mon Sep 17 00:00:00 2001 From: Mark Backman Date: Wed, 25 Feb 2026 15:45:16 -0500 Subject: [PATCH 0642/1060] Add /update-docs skill to claude-plugin --- .claude-plugin/marketplace.json | 3 ++- 1 file changed, 2 insertions(+), 1 deletion(-) diff --git a/.claude-plugin/marketplace.json b/.claude-plugin/marketplace.json index 64aac9338..c628e79e5 100644 --- a/.claude-plugin/marketplace.json +++ b/.claude-plugin/marketplace.json @@ -19,7 +19,8 @@ "./.claude/skills/code-review", "./.claude/skills/docstring", "./.claude/skills/pr-description", - "./.claude/skills/pr-submit" + "./.claude/skills/pr-submit", + "./.claude/skills/update-docs" ] } ] From 781d19150987fa2b8198adf584b90bbae96e1772 Mon Sep 17 00:00:00 2001 From: Paul Kompfner Date: Tue, 24 Feb 2026 21:19:39 -0500 Subject: [PATCH 0643/1060] Remove unnecessary `_model` ivar from `GeminiTTSService`, using `_settings.model` instead --- src/pipecat/services/google/tts.py | 7 +++---- 1 file changed, 3 insertions(+), 4 deletions(-) diff --git a/src/pipecat/services/google/tts.py b/src/pipecat/services/google/tts.py index 80c71b10f..6c71977a0 100644 --- a/src/pipecat/services/google/tts.py +++ b/src/pipecat/services/google/tts.py @@ -1236,7 +1236,7 @@ class GeminiTTSService(GoogleBaseTTSService): super().__init__( sample_rate=sample_rate, settings=GeminiTTSSettings( - model=None, + model=model, language=self.language_to_service_language(params.language) if params.language else "en-US", @@ -1249,7 +1249,6 @@ class GeminiTTSService(GoogleBaseTTSService): ) self._location = location - self._model = model self._client: texttospeech_v1.TextToSpeechAsyncClient = self._create_client( credentials, credentials_path ) @@ -1327,7 +1326,7 @@ class GeminiTTSService(GoogleBaseTTSService): voice = texttospeech_v1.VoiceSelectionParams( language_code=self._settings.language, - model_name=self._model, + model_name=self._settings.model, multi_speaker_voice_config=multi_speaker_voice_config, ) else: @@ -1335,7 +1334,7 @@ class GeminiTTSService(GoogleBaseTTSService): voice = texttospeech_v1.VoiceSelectionParams( language_code=self._settings.language, name=self._settings.voice, - model_name=self._model, + model_name=self._settings.model, ) # Create streaming config From 7ee0400c4c8f81bd17046db48ef2d4d5d6d7bee6 Mon Sep 17 00:00:00 2001 From: Paul Kompfner Date: Tue, 24 Feb 2026 21:22:44 -0500 Subject: [PATCH 0644/1060] Remove unnecessary `_model` ivar from Hathora TTS and STT services, using `_settings.model` instead. --- src/pipecat/services/hathora/stt.py | 4 +--- src/pipecat/services/hathora/tts.py | 3 +-- 2 files changed, 2 insertions(+), 5 deletions(-) diff --git a/src/pipecat/services/hathora/stt.py b/src/pipecat/services/hathora/stt.py index 84f4116f3..27f1aebfb 100644 --- a/src/pipecat/services/hathora/stt.py +++ b/src/pipecat/services/hathora/stt.py @@ -101,8 +101,6 @@ class HathoraSTTService(SegmentedSTTService): ), **kwargs, ) - - self._model = model self._api_key = api_key or os.getenv("HATHORA_API_KEY") self._base_url = base_url @@ -136,7 +134,7 @@ class HathoraSTTService(SegmentedSTTService): url = f"{self._base_url}" payload = { - "model": self._model, + "model": self._settings.model, } if self._settings.language is not None: diff --git a/src/pipecat/services/hathora/tts.py b/src/pipecat/services/hathora/tts.py index 8d6fb32cb..3fb9e747b 100644 --- a/src/pipecat/services/hathora/tts.py +++ b/src/pipecat/services/hathora/tts.py @@ -120,7 +120,6 @@ class HathoraTTSService(TTSService): ), **kwargs, ) - self._model = model self._api_key = api_key or os.getenv("HATHORA_API_KEY") self._base_url = base_url @@ -149,7 +148,7 @@ class HathoraTTSService(TTSService): url = f"{self._base_url}" - payload = {"model": self._model, "text": text} + payload = {"model": self._settings.model, "text": text} if self._settings.voice is not None: payload["voice"] = self._settings.voice From 3d8e3a4043a14891c91b11fee4a3e1e760c57bed Mon Sep 17 00:00:00 2001 From: Paul Kompfner Date: Tue, 24 Feb 2026 21:49:54 -0500 Subject: [PATCH 0645/1060] Remove unnecessary `_model` ivar from ElevenLabs STT services, using `_settings.model` instead. --- src/pipecat/services/elevenlabs/stt.py | 32 +++----------------------- 1 file changed, 3 insertions(+), 29 deletions(-) diff --git a/src/pipecat/services/elevenlabs/stt.py b/src/pipecat/services/elevenlabs/stt.py index c3f4300f4..5422fb193 100644 --- a/src/pipecat/services/elevenlabs/stt.py +++ b/src/pipecat/services/elevenlabs/stt.py @@ -279,7 +279,6 @@ class ElevenLabsSTTService(SegmentedSTTService): self._api_key = api_key self._base_url = base_url self._session = aiohttp_session - self._model_id = model def can_generate_metrics(self) -> bool: """Check if the service can generate processing metrics. @@ -300,25 +299,6 @@ class ElevenLabsSTTService(SegmentedSTTService): """ return language_to_elevenlabs_language(language) - async def _update_settings(self, delta: STTSettings) -> dict[str, Any]: - """Apply a settings delta. - - Converts language to ElevenLabs format before applying and keeps - ``_model_id`` in sync with the model setting. - - Args: - delta: A :class:`STTSettings` (or ``ElevenLabsSTTSettings``) delta. - - Returns: - Dict mapping changed field names to their previous values. - """ - changed = await super()._update_settings(delta) - - if "model" in changed: - self._model_id = self._settings.model - - return changed - async def _transcribe_audio(self, audio_data: bytes) -> dict: """Upload audio data to ElevenLabs and get transcription result. @@ -344,7 +324,7 @@ class ElevenLabsSTTService(SegmentedSTTService): ) # Add required model_id, language_code, and tag_audio_events - data.add_field("model_id", self._model_id) + data.add_field("model_id", self._settings.model) data.add_field("language_code", self._settings.language) data.add_field("tag_audio_events", str(self._settings.tag_audio_events).lower()) @@ -522,7 +502,6 @@ class ElevenLabsRealtimeSTTService(WebsocketSTTService): self._api_key = api_key self._base_url = base_url - self._model_id = model self._audio_format = "" # initialized in start() self._receive_task = None @@ -540,9 +519,6 @@ class ElevenLabsRealtimeSTTService(WebsocketSTTService): async def _update_settings(self, delta: STTSettings) -> dict[str, Any]: """Apply a settings delta and reconnect if anything changed. - Converts language to ElevenLabs format before applying and keeps - ``_model_id`` in sync. - Args: delta: A :class:`STTSettings` (or ``ElevenLabsRealtimeSTTSettings``) delta. @@ -554,11 +530,9 @@ class ElevenLabsRealtimeSTTService(WebsocketSTTService): if not changed: return changed - if "model" in changed: - self._model_id = self._settings.model - await self._disconnect() await self._connect() + return changed async def start(self, frame: StartFrame): @@ -704,7 +678,7 @@ class ElevenLabsRealtimeSTTService(WebsocketSTTService): logger.debug("Connecting to ElevenLabs Realtime STT") # Build query parameters - params = [f"model_id={self._model_id}"] + params = [f"model_id={self._settings.model}"] if self._settings.language: params.append(f"language_code={self._settings.language}") From a4b6db6fb44148709c22c65039f02ef677ad603b Mon Sep 17 00:00:00 2001 From: Paul Kompfner Date: Tue, 24 Feb 2026 15:06:06 -0500 Subject: [PATCH 0646/1060] Flatten `LiveOptions` into individual fields on `DeepgramSTTSettings` and `DeepgramSageMakerSTTSettings` for backward-compatible dict-style updates via `STTUpdateSettingsFrame`; during the big service settings refactor, we accidentally got rid of the ability to update individual `LiveOptions` fields with a sparse update --- ...-update-settings-deepgram-sagemaker-stt.py | 7 + .../55a-update-settings-deepgram-stt.py | 7 + src/pipecat/services/deepgram/stt.py | 119 ++++++++++------- .../services/deepgram/stt_sagemaker.py | 121 ++++++++++-------- 4 files changed, 158 insertions(+), 96 deletions(-) diff --git a/examples/foundational/55a-update-settings-deepgram-sagemaker-stt.py b/examples/foundational/55a-update-settings-deepgram-sagemaker-stt.py index 05c92e7e2..fba722648 100644 --- a/examples/foundational/55a-update-settings-deepgram-sagemaker-stt.py +++ b/examples/foundational/55a-update-settings-deepgram-sagemaker-stt.py @@ -112,6 +112,13 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): STTUpdateSettingsFrame(delta=DeepgramSageMakerSTTSettings(language=Language.ES)) ) + # Old-style dict update (for backward-compat testing): + # await asyncio.sleep(10) + # logger.info("Updating Deepgram SageMaker STT settings via dict: punctuate=False, filler_words=True") + # await task.queue_frame( + # STTUpdateSettingsFrame(settings={"punctuate": False, "filler_words": True}) + # ) + @transport.event_handler("on_client_disconnected") async def on_client_disconnected(transport, client): logger.info(f"Client disconnected") diff --git a/examples/foundational/55a-update-settings-deepgram-stt.py b/examples/foundational/55a-update-settings-deepgram-stt.py index 39dde69e9..20068ab75 100644 --- a/examples/foundational/55a-update-settings-deepgram-stt.py +++ b/examples/foundational/55a-update-settings-deepgram-stt.py @@ -106,6 +106,13 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): STTUpdateSettingsFrame(delta=DeepgramSTTSettings(language=Language.ES)) ) + # Old-style dict update (for backward-compat testing): + # await asyncio.sleep(10) + # logger.info("Updating Deepgram STT settings via dict: punctuate=False, filler_words=True") + # await task.queue_frame( + # STTUpdateSettingsFrame(settings={"punctuate": False, "filler_words": True}) + # ) + @transport.event_handler("on_client_disconnected") async def on_client_disconnected(transport, client): logger.info(f"Client disconnected") diff --git a/src/pipecat/services/deepgram/stt.py b/src/pipecat/services/deepgram/stt.py index aa5c2ce8d..768c4d6eb 100644 --- a/src/pipecat/services/deepgram/stt.py +++ b/src/pipecat/services/deepgram/stt.py @@ -6,7 +6,8 @@ """Deepgram speech-to-text service implementation.""" -from dataclasses import dataclass, field +import inspect +from dataclasses import dataclass, field, fields from typing import Any, AsyncGenerator, Dict, Optional from loguru import logger @@ -24,7 +25,7 @@ from pipecat.frames.frames import ( VADUserStoppedSpeakingFrame, ) from pipecat.processors.frame_processor import FrameDirection -from pipecat.services.settings import NOT_GIVEN, STTSettings, _NotGiven, is_given +from pipecat.services.settings import NOT_GIVEN, STTSettings, _NotGiven from pipecat.services.stt_latency import DEEPGRAM_TTFS_P99 from pipecat.services.stt_service import STTService from pipecat.transcriptions.language import Language @@ -51,11 +52,32 @@ except ModuleNotFoundError as e: class DeepgramSTTSettings(STTSettings): """Settings for the Deepgram STT service. + Some commonly used ``LiveOptions`` fields are declared as top-level + fields here so they can be updated individually via + ``STTUpdateSettingsFrame``. Any *additional* ``LiveOptions`` fields + (e.g. ``filler_words``, ``diarize``, ``utterance_end_ms``) can be + passed through the ``extra`` dict — they will be forwarded to + ``LiveOptions`` when the WebSocket connection is (re)established. + This keeps the settings class future-proof: new Deepgram features work + without code changes on the Pipecat side. + Parameters: - live_options: Deepgram ``LiveOptions`` for detailed configuration. + encoding: Audio encoding format (e.g. ``"linear16"``). + channels: Number of audio channels. + interim_results: Whether to return interim transcription results. + smart_format: Whether to enable Deepgram smart formatting. + punctuate: Whether to add punctuation to transcripts. + profanity_filter: Whether to filter profanity from transcripts. + vad_events: Whether to enable Deepgram VAD events (deprecated). """ - live_options: LiveOptions | _NotGiven = field(default_factory=lambda: NOT_GIVEN) + encoding: str | None | _NotGiven = field(default_factory=lambda: NOT_GIVEN) + channels: int | None | _NotGiven = field(default_factory=lambda: NOT_GIVEN) + interim_results: bool | None | _NotGiven = field(default_factory=lambda: NOT_GIVEN) + smart_format: bool | None | _NotGiven = field(default_factory=lambda: NOT_GIVEN) + punctuate: bool | None | _NotGiven = field(default_factory=lambda: NOT_GIVEN) + profanity_filter: bool | None | _NotGiven = field(default_factory=lambda: NOT_GIVEN) + vad_events: bool | None | _NotGiven = field(default_factory=lambda: NOT_GIVEN) class DeepgramSTTService(STTService): @@ -153,22 +175,29 @@ class DeepgramSTTService(STTService): if "language" in merged_options and isinstance(merged_options["language"], Language): merged_options["language"] = merged_options["language"].value - merged_live_options = LiveOptions(**merged_options) + settings_fields = {f.name for f in fields(DeepgramSTTSettings)} + settings_kwargs = {} + extra = {} + for key, value in merged_options.items(): + if key in settings_fields: + settings_kwargs[key] = value + else: + extra[key] = value + + settings = DeepgramSTTSettings(**settings_kwargs) + settings.extra = extra + super().__init__( sample_rate=sample_rate, ttfs_p99_latency=ttfs_p99_latency, - settings=DeepgramSTTSettings( - model=merged_options.get("model"), - language=merged_options.get("language"), - live_options=merged_live_options, - ), + settings=settings, **kwargs, ) self._addons = addons self._should_interrupt = should_interrupt - if merged_live_options.vad_events: + if self._settings.vad_events: import warnings with warnings.catch_warnings(): @@ -199,7 +228,7 @@ class DeepgramSTTService(STTService): Returns: True if VAD events are enabled in the current settings. """ - return self._settings.live_options.vad_events + return self._settings.vad_events def can_generate_metrics(self) -> bool: """Check if this service can generate processing metrics. @@ -210,43 +239,12 @@ class DeepgramSTTService(STTService): return True async def _update_settings(self, delta: STTSettings) -> dict[str, Any]: - """Apply a settings delta, keeping ``live_options`` in sync. - - Top-level ``model`` and ``language`` are the source of truth. When - they are given in *delta* their values are propagated into - ``live_options``. When only ``live_options`` is given, its ``model`` - and ``language`` are propagated *up* to the top-level fields. - - Any change triggers a WebSocket reconnect. - """ - # Determine which top-level fields are explicitly provided. - model_given = isinstance(delta, DeepgramSTTSettings) and is_given( - getattr(delta, "model", NOT_GIVEN) - ) - language_given = isinstance(delta, DeepgramSTTSettings) and is_given( - getattr(delta, "language", NOT_GIVEN) - ) - + """Apply a settings delta and reconnect if anything changed.""" changed = await super()._update_settings(delta) if not changed: return changed - # --- Sync model -------------------------------------------------- - if model_given: - # Top-level model wins → push into live_options. - self._settings.live_options.model = self._settings.model - elif "live_options" in changed and self._settings.live_options.model is not None: - # Only live_options was given → pull model up. - self._settings.model = self._settings.live_options.model - self._sync_model_name_to_metrics() - - # --- Sync language ----------------------------------------------- - if language_given: - self._settings.live_options.language = self._settings.language - elif "live_options" in changed and self._settings.live_options.language is not None: - self._settings.language = self._settings.live_options.language - await self._disconnect() await self._connect() @@ -259,7 +257,6 @@ class DeepgramSTTService(STTService): frame: The start frame containing initialization parameters. """ await super().start(frame) - self._settings.live_options.sample_rate = self.sample_rate await self._connect() async def stop(self, frame: EndFrame): @@ -292,6 +289,36 @@ class DeepgramSTTService(STTService): await self._connection.send(audio) yield None + def _build_live_options(self) -> LiveOptions: + """Build a ``LiveOptions`` from flat settings fields, sample rate, and extras. + + Returns: + A fully-populated ``LiveOptions`` ready for the Deepgram SDK. + """ + valid_kwargs = set(inspect.signature(LiveOptions.__init__).parameters) - {"self"} + + # Start with extras that are valid LiveOptions kwargs. + opts: dict[str, Any] = {k: v for k, v in self._settings.extra.items() if k in valid_kwargs} + + # Override with flat settings fields (these take precedence). + s = self._settings + opts.update( + { + "model": s.model, + "language": s.language, + "encoding": s.encoding, + "channels": s.channels, + "interim_results": s.interim_results, + "smart_format": s.smart_format, + "punctuate": s.punctuate, + "profanity_filter": s.profanity_filter, + "vad_events": s.vad_events, + "sample_rate": self.sample_rate, + } + ) + + return LiveOptions(**opts) + async def _connect(self): logger.debug("Connecting to Deepgram") @@ -313,7 +340,7 @@ class DeepgramSTTService(STTService): ) if not await self._connection.start( - options=self._settings.live_options, addons=self._addons + options=self._build_live_options(), addons=self._addons ): await self.push_error(error_msg=f"Unable to connect to Deepgram") else: diff --git a/src/pipecat/services/deepgram/stt_sagemaker.py b/src/pipecat/services/deepgram/stt_sagemaker.py index bc5eebe37..97309ab93 100644 --- a/src/pipecat/services/deepgram/stt_sagemaker.py +++ b/src/pipecat/services/deepgram/stt_sagemaker.py @@ -13,8 +13,9 @@ languages, and various Deepgram features. """ import asyncio +import inspect import json -from dataclasses import dataclass, field +from dataclasses import dataclass, field, fields from typing import Any, AsyncGenerator, Optional from loguru import logger @@ -32,7 +33,7 @@ from pipecat.frames.frames import ( ) from pipecat.processors.frame_processor import FrameDirection from pipecat.services.aws.sagemaker.bidi_client import SageMakerBidiClient -from pipecat.services.settings import NOT_GIVEN, STTSettings, _NotGiven, is_given +from pipecat.services.settings import NOT_GIVEN, STTSettings, _NotGiven from pipecat.services.stt_latency import DEEPGRAM_SAGEMAKER_TTFS_P99 from pipecat.services.stt_service import STTService from pipecat.transcriptions.language import Language @@ -53,11 +54,32 @@ except ModuleNotFoundError as e: class DeepgramSageMakerSTTSettings(STTSettings): """Settings for the Deepgram SageMaker STT service. + Some commonly used ``LiveOptions`` fields are declared as top-level + fields here so they can be updated individually via + ``STTUpdateSettingsFrame``. Any *additional* ``LiveOptions`` fields + (e.g. ``filler_words``, ``diarize``, ``utterance_end_ms``) can be + passed through the ``extra`` dict — they will be forwarded to + ``LiveOptions`` when the connection is (re)established. This keeps the + settings class future-proof: new Deepgram features work without code + changes on the Pipecat side. + Parameters: - live_options: Deepgram ``LiveOptions`` for detailed configuration. + encoding: Audio encoding format (e.g. ``"linear16"``). + channels: Number of audio channels. + interim_results: Whether to return interim transcription results. + smart_format: Whether to enable Deepgram smart formatting. + punctuate: Whether to add punctuation to transcripts. + profanity_filter: Whether to filter profanity from transcripts. + vad_events: Whether to enable Deepgram VAD events (deprecated). """ - live_options: LiveOptions | _NotGiven = field(default_factory=lambda: NOT_GIVEN) + encoding: str | None | _NotGiven = field(default_factory=lambda: NOT_GIVEN) + channels: int | None | _NotGiven = field(default_factory=lambda: NOT_GIVEN) + interim_results: bool | None | _NotGiven = field(default_factory=lambda: NOT_GIVEN) + smart_format: bool | None | _NotGiven = field(default_factory=lambda: NOT_GIVEN) + punctuate: bool | None | _NotGiven = field(default_factory=lambda: NOT_GIVEN) + profanity_filter: bool | None | _NotGiven = field(default_factory=lambda: NOT_GIVEN) + vad_events: bool | None | _NotGiven = field(default_factory=lambda: NOT_GIVEN) class DeepgramSageMakerSTTService(STTService): @@ -139,15 +161,22 @@ class DeepgramSageMakerSTTService(STTService): if "language" in merged_options and isinstance(merged_options["language"], Language): merged_options["language"] = merged_options["language"].value - merged_live_options = LiveOptions(**merged_options) + settings_fields = {f.name for f in fields(DeepgramSageMakerSTTSettings)} + settings_kwargs = {} + extra = {} + for key, value in merged_options.items(): + if key in settings_fields: + settings_kwargs[key] = value + else: + extra[key] = value + + settings = DeepgramSageMakerSTTSettings(**settings_kwargs) + settings.extra = extra + super().__init__( sample_rate=sample_rate, ttfs_p99_latency=ttfs_p99_latency, - settings=DeepgramSageMakerSTTSettings( - model=merged_options.get("model"), - language=merged_options.get("language"), - live_options=merged_live_options, - ), + settings=settings, **kwargs, ) @@ -167,46 +196,12 @@ class DeepgramSageMakerSTTService(STTService): return True async def _update_settings(self, delta: STTSettings) -> dict[str, Any]: - """Apply a settings delta, keeping ``live_options`` in sync. - - Top-level ``model`` and ``language`` are the source of truth. When - they are given in *delta* their values are propagated into - ``live_options``. When only ``live_options`` is given, its ``model`` - and ``language`` are propagated *up* to the top-level fields. - - Any change triggers a reconnect. - """ - # Determine which top-level fields are explicitly provided. - model_given = isinstance(delta, DeepgramSageMakerSTTSettings) and is_given( - getattr(delta, "model", NOT_GIVEN) - ) - language_given = isinstance(delta, DeepgramSageMakerSTTSettings) and is_given( - getattr(delta, "language", NOT_GIVEN) - ) - + """Apply a settings delta and warn about unhandled changes.""" changed = await super()._update_settings(delta) if not changed: return changed - # --- Sync model -------------------------------------------------- - if model_given: - # Top-level model wins → push into live_options. - self._settings.live_options.model = self._settings.model - elif "live_options" in changed and self._settings.live_options.model is not None: - # Only live_options was given → pull model up. - self._settings.model = self._settings.live_options.model - self._sync_model_name_to_metrics() - - # --- Sync language ----------------------------------------------- - if language_given: - lang = self._settings.language - if isinstance(lang, Language): - lang = lang.value - self._settings.live_options.language = lang - elif "live_options" in changed and self._settings.live_options.language is not None: - self._settings.language = self._settings.live_options.language - # TODO: someday we could reconnect here to apply updated settings. # Code might look something like the below: # await self._disconnect() @@ -223,7 +218,6 @@ class DeepgramSageMakerSTTService(STTService): frame: The start frame containing initialization parameters. """ await super().start(frame) - self._settings.live_options.sample_rate = self.sample_rate await self._connect() async def stop(self, frame: EndFrame): @@ -260,6 +254,36 @@ class DeepgramSageMakerSTTService(STTService): yield ErrorFrame(error=f"Unknown error occurred: {e}") yield None + def _build_live_options(self) -> LiveOptions: + """Build a ``LiveOptions`` from flat settings fields, sample rate, and extras. + + Returns: + A fully-populated ``LiveOptions`` ready for the Deepgram SDK. + """ + valid_kwargs = set(inspect.signature(LiveOptions.__init__).parameters) - {"self"} + + # Start with extras that are valid LiveOptions kwargs. + opts: dict[str, Any] = {k: v for k, v in self._settings.extra.items() if k in valid_kwargs} + + # Override with flat settings fields (these take precedence). + s = self._settings + opts.update( + { + "model": s.model, + "language": s.language, + "encoding": s.encoding, + "channels": s.channels, + "interim_results": s.interim_results, + "smart_format": s.smart_format, + "punctuate": s.punctuate, + "profanity_filter": s.profanity_filter, + "vad_events": s.vad_events, + "sample_rate": self.sample_rate, + } + ) + + return LiveOptions(**opts) + async def _connect(self): """Connect to the SageMaker endpoint and start the BiDi session. @@ -269,12 +293,9 @@ class DeepgramSageMakerSTTService(STTService): """ logger.debug("Connecting to Deepgram on SageMaker...") - # Update sample rate in live_options - self._settings.live_options.sample_rate = self.sample_rate - # Build query string from live_options, converting booleans to strings query_params = {} - for key, value in self._settings.live_options.to_dict().items(): + for key, value in self._build_live_options().to_dict().items(): if value is not None: # Convert boolean values to lowercase strings for Deepgram API if isinstance(value, bool): From 8b6aa4b912958ceaa619192fb779e9c20897b037 Mon Sep 17 00:00:00 2001 From: Paul Kompfner Date: Wed, 25 Feb 2026 18:18:47 -0500 Subject: [PATCH 0647/1060] Unflatten `LiveOptions` back into a single `live_options` field on `DeepgramSTTSettings` and `DeepgramSageMakerSTTSettings`; add `apply_update` override with delta-merge semantics and `from_mapping` override for backward-compatible dict-style updates --- ...-update-settings-deepgram-sagemaker-stt.py | 11 +- .../55a-update-settings-deepgram-stt.py | 11 +- src/pipecat/services/deepgram/stt.py | 201 +++++++++++------ .../services/deepgram/stt_sagemaker.py | 196 ++++++++++------ tests/test_settings.py | 211 ++++++++++++++++++ 5 files changed, 496 insertions(+), 134 deletions(-) diff --git a/examples/foundational/55a-update-settings-deepgram-sagemaker-stt.py b/examples/foundational/55a-update-settings-deepgram-sagemaker-stt.py index fba722648..e8094183a 100644 --- a/examples/foundational/55a-update-settings-deepgram-sagemaker-stt.py +++ b/examples/foundational/55a-update-settings-deepgram-sagemaker-stt.py @@ -7,6 +7,7 @@ import asyncio import os +from deepgram import LiveOptions from dotenv import load_dotenv from loguru import logger @@ -106,10 +107,16 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): messages.append({"role": "system", "content": "Please introduce yourself to the user."}) await task.queue_frames([LLMRunFrame()]) + # NOTE: after this change, the bot will only respond if you speak Spanish await asyncio.sleep(10) - logger.info("Updating Deepgram SageMaker STT settings: language=es") + logger.info("Updating Deepgram SageMaker STT settings: language=es, punctuate=False") await task.queue_frame( - STTUpdateSettingsFrame(delta=DeepgramSageMakerSTTSettings(language=Language.ES)) + STTUpdateSettingsFrame( + delta=DeepgramSageMakerSTTSettings( + language=Language.ES, + live_options=LiveOptions(punctuate=False), + ) + ) ) # Old-style dict update (for backward-compat testing): diff --git a/examples/foundational/55a-update-settings-deepgram-stt.py b/examples/foundational/55a-update-settings-deepgram-stt.py index 20068ab75..8808f6f4c 100644 --- a/examples/foundational/55a-update-settings-deepgram-stt.py +++ b/examples/foundational/55a-update-settings-deepgram-stt.py @@ -7,6 +7,7 @@ import asyncio import os +from deepgram import LiveOptions from dotenv import load_dotenv from loguru import logger @@ -100,10 +101,16 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): messages.append({"role": "system", "content": "Please introduce yourself to the user."}) await task.queue_frames([LLMRunFrame()]) + # NOTE: after this change, the bot will only respond if you speak Spanish await asyncio.sleep(10) - logger.info("Updating Deepgram STT settings: language=es") + logger.info("Updating Deepgram STT settings: language=es, punctuate=False") await task.queue_frame( - STTUpdateSettingsFrame(delta=DeepgramSTTSettings(language=Language.ES)) + STTUpdateSettingsFrame( + delta=DeepgramSTTSettings( + language=Language.ES, + live_options=LiveOptions(punctuate=False), + ) + ) ) # Old-style dict update (for backward-compat testing): diff --git a/src/pipecat/services/deepgram/stt.py b/src/pipecat/services/deepgram/stt.py index 768c4d6eb..f1c2fd19c 100644 --- a/src/pipecat/services/deepgram/stt.py +++ b/src/pipecat/services/deepgram/stt.py @@ -7,8 +7,8 @@ """Deepgram speech-to-text service implementation.""" import inspect -from dataclasses import dataclass, field, fields -from typing import Any, AsyncGenerator, Dict, Optional +from dataclasses import dataclass, field +from typing import Any, AsyncGenerator, Dict, Mapping, Optional, Type from loguru import logger @@ -25,7 +25,7 @@ from pipecat.frames.frames import ( VADUserStoppedSpeakingFrame, ) from pipecat.processors.frame_processor import FrameDirection -from pipecat.services.settings import NOT_GIVEN, STTSettings, _NotGiven +from pipecat.services.settings import _S, NOT_GIVEN, STTSettings, _NotGiven, is_given from pipecat.services.stt_latency import DEEPGRAM_TTFS_P99 from pipecat.services.stt_service import STTService from pipecat.transcriptions.language import Language @@ -52,32 +52,117 @@ except ModuleNotFoundError as e: class DeepgramSTTSettings(STTSettings): """Settings for the Deepgram STT service. - Some commonly used ``LiveOptions`` fields are declared as top-level - fields here so they can be updated individually via - ``STTUpdateSettingsFrame``. Any *additional* ``LiveOptions`` fields - (e.g. ``filler_words``, ``diarize``, ``utterance_end_ms``) can be - passed through the ``extra`` dict — they will be forwarded to - ``LiveOptions`` when the WebSocket connection is (re)established. - This keeps the settings class future-proof: new Deepgram features work - without code changes on the Pipecat side. + Wraps the Deepgram SDK's ``LiveOptions`` in a single ``live_options`` + field. All Deepgram-specific options (``filler_words``, ``diarize``, + ``utterance_end_ms``, etc.) should be passed directly via + ``LiveOptions``. + + In **delta mode** (i.e. when carried by ``STTUpdateSettingsFrame``), + ``live_options`` is treated as a **delta** — its non-None fields are + merged into the stored ``LiveOptions``, not replaced wholesale. For + example, ``DeepgramSTTSettings(live_options=LiveOptions(punctuate=False))`` + changes only ``punctuate`` and leaves all other options intact. Parameters: - encoding: Audio encoding format (e.g. ``"linear16"``). - channels: Number of audio channels. - interim_results: Whether to return interim transcription results. - smart_format: Whether to enable Deepgram smart formatting. - punctuate: Whether to add punctuation to transcripts. - profanity_filter: Whether to filter profanity from transcripts. - vad_events: Whether to enable Deepgram VAD events (deprecated). + live_options: Deepgram ``LiveOptions`` for STT configuration. + In delta mode only its non-None fields are merged into the + stored options. """ - encoding: str | None | _NotGiven = field(default_factory=lambda: NOT_GIVEN) - channels: int | None | _NotGiven = field(default_factory=lambda: NOT_GIVEN) - interim_results: bool | None | _NotGiven = field(default_factory=lambda: NOT_GIVEN) - smart_format: bool | None | _NotGiven = field(default_factory=lambda: NOT_GIVEN) - punctuate: bool | None | _NotGiven = field(default_factory=lambda: NOT_GIVEN) - profanity_filter: bool | None | _NotGiven = field(default_factory=lambda: NOT_GIVEN) - vad_events: bool | None | _NotGiven = field(default_factory=lambda: NOT_GIVEN) + live_options: LiveOptions | _NotGiven = field(default_factory=lambda: NOT_GIVEN) + + # Valid LiveOptions __init__ parameter names (cached at class level). + _live_options_params: set[str] | None = field(default=None, init=False, repr=False) + + @classmethod + def _get_live_options_params(cls) -> set[str]: + """Return the set of valid ``LiveOptions.__init__`` parameter names.""" + if cls._live_options_params is None: + cls._live_options_params = set(inspect.signature(LiveOptions.__init__).parameters) - { + "self" + } + return cls._live_options_params + + def apply_update(self: _S, delta: _S) -> Dict[str, Any]: + """Merge a delta into this store, with delta-merge for ``live_options``. + + ``live_options`` is merged field-by-field (non-None fields from the + delta overwrite corresponding fields in the stored options) rather + than being replaced wholesale. + + ``model`` and ``language`` are kept in sync bidirectionally between + the top-level settings fields and ``live_options``. + """ + # Pull live_options out of the delta so super() doesn't replace it. + delta_lo = getattr(delta, "live_options", NOT_GIVEN) + if is_given(delta_lo): + delta.live_options = NOT_GIVEN # type: ignore[assignment] + + # Let the base class handle model, language, extra. + changed = super().apply_update(delta) + + # Sync top-level model/language changes into stored live_options. + if "model" in changed: + self.live_options.model = self.model # type: ignore[union-attr] + if "language" in changed: + self.live_options.language = self.language # type: ignore[union-attr] + + # Merge live_options delta. + if is_given(delta_lo): + old_dict = self.live_options.to_dict() # type: ignore[union-attr] + delta_dict = delta_lo.to_dict() + + if delta_dict: + merged = {**old_dict, **delta_dict} + self.live_options = LiveOptions(**merged) + + for key in delta_dict: + old_val = old_dict.get(key, NOT_GIVEN) + if old_val != delta_dict[key]: + changed[key] = old_val + + # Sync model/language from live_options delta to top-level. + if "model" in delta_dict and delta_dict["model"] != self.model: + changed.setdefault("model", self.model) + self.model = delta_dict["model"] + if "language" in delta_dict and delta_dict["language"] != self.language: + changed.setdefault("language", self.language) + self.language = delta_dict["language"] + + return changed + + @classmethod + def from_mapping(cls: Type[_S], settings: Mapping[str, Any]) -> _S: + """Build a delta from a plain dict, routing LiveOptions keys correctly. + + Keys that are valid ``LiveOptions.__init__`` parameters (and not + top-level ``STTSettings`` fields like ``model`` / ``language``) are + collected into a ``LiveOptions`` object. ``model`` and ``language`` + are routed to the top-level settings fields. Truly unknown keys go + to ``extra``. + """ + lo_params = cls._get_live_options_params() + stt_field_names = {"model", "language"} + + kwargs: Dict[str, Any] = {} + lo_kwargs: Dict[str, Any] = {} + extra: Dict[str, Any] = {} + + for key, value in settings.items(): + canonical = cls._aliases.get(key, key) + if canonical in stt_field_names: + kwargs[canonical] = value + elif canonical in lo_params: + lo_kwargs[canonical] = value + else: + extra[key] = value + + if lo_kwargs: + kwargs["live_options"] = LiveOptions(**lo_kwargs) + + instance = cls(**kwargs) + instance.extra = extra + return instance class DeepgramSTTService(STTService): @@ -124,7 +209,9 @@ class DeepgramSTTService(STTService): base_url: Custom Deepgram API base URL. sample_rate: Audio sample rate. If None, uses default or live_options value. - live_options: Deepgram LiveOptions for detailed configuration. + live_options: Deepgram LiveOptions configuration. Treated as a + delta from a set of sensible defaults — only the fields you + set are overridden; all others keep their default values. addons: Additional Deepgram features to enable. should_interrupt: Determine whether the bot should be interrupted when Deepgram VAD events are enabled and the system detects that the user is speaking. @@ -163,29 +250,26 @@ class DeepgramSTTService(STTService): vad_events=False, ) - merged_options = default_options.to_dict() + merged_dict = default_options.to_dict() if live_options: default_model = default_options.model - merged_options.update(live_options.to_dict()) - # NOTE(aleix): Fixes an in deepgram-sdk where `model` is initialized + merged_dict.update(live_options.to_dict()) + # NOTE(aleix): Fixes a bug in deepgram-sdk where `model` is initialized # to the string "None" instead of the value `None`. - if "model" in merged_options and merged_options["model"] == "None": - merged_options["model"] = default_model + if "model" in merged_dict and merged_dict["model"] == "None": + merged_dict["model"] = default_model - if "language" in merged_options and isinstance(merged_options["language"], Language): - merged_options["language"] = merged_options["language"].value + if "language" in merged_dict and isinstance(merged_dict["language"], Language): + merged_dict["language"] = merged_dict["language"].value - settings_fields = {f.name for f in fields(DeepgramSTTSettings)} - settings_kwargs = {} - extra = {} - for key, value in merged_options.items(): - if key in settings_fields: - settings_kwargs[key] = value - else: - extra[key] = value + # Extract model/language for top-level STTSettings fields; everything + # else lives inside LiveOptions. + model = merged_dict.pop("model", None) + language = merged_dict.pop("language", None) - settings = DeepgramSTTSettings(**settings_kwargs) - settings.extra = extra + settings = DeepgramSTTSettings( + model=model, language=language, live_options=LiveOptions(**merged_dict) + ) super().__init__( sample_rate=sample_rate, @@ -197,7 +281,7 @@ class DeepgramSTTService(STTService): self._addons = addons self._should_interrupt = should_interrupt - if self._settings.vad_events: + if self._settings.live_options.vad_events: import warnings with warnings.catch_warnings(): @@ -228,7 +312,7 @@ class DeepgramSTTService(STTService): Returns: True if VAD events are enabled in the current settings. """ - return self._settings.vad_events + return self._settings.live_options.vad_events def can_generate_metrics(self) -> bool: """Check if this service can generate processing metrics. @@ -290,32 +374,17 @@ class DeepgramSTTService(STTService): yield None def _build_live_options(self) -> LiveOptions: - """Build a ``LiveOptions`` from flat settings fields, sample rate, and extras. + """Build a ``LiveOptions`` from stored settings and sample rate. Returns: A fully-populated ``LiveOptions`` ready for the Deepgram SDK. """ - valid_kwargs = set(inspect.signature(LiveOptions.__init__).parameters) - {"self"} + opts: dict[str, Any] = self._settings.live_options.to_dict() - # Start with extras that are valid LiveOptions kwargs. - opts: dict[str, Any] = {k: v for k, v in self._settings.extra.items() if k in valid_kwargs} - - # Override with flat settings fields (these take precedence). - s = self._settings - opts.update( - { - "model": s.model, - "language": s.language, - "encoding": s.encoding, - "channels": s.channels, - "interim_results": s.interim_results, - "smart_format": s.smart_format, - "punctuate": s.punctuate, - "profanity_filter": s.profanity_filter, - "vad_events": s.vad_events, - "sample_rate": self.sample_rate, - } - ) + # Overlay model/language from top-level settings and sample_rate from service. + opts["model"] = self._settings.model + opts["language"] = self._settings.language + opts["sample_rate"] = self.sample_rate return LiveOptions(**opts) diff --git a/src/pipecat/services/deepgram/stt_sagemaker.py b/src/pipecat/services/deepgram/stt_sagemaker.py index 97309ab93..12357a8cd 100644 --- a/src/pipecat/services/deepgram/stt_sagemaker.py +++ b/src/pipecat/services/deepgram/stt_sagemaker.py @@ -15,8 +15,8 @@ languages, and various Deepgram features. import asyncio import inspect import json -from dataclasses import dataclass, field, fields -from typing import Any, AsyncGenerator, Optional +from dataclasses import dataclass, field +from typing import Any, AsyncGenerator, Dict, Mapping, Optional, Type from loguru import logger @@ -33,7 +33,7 @@ from pipecat.frames.frames import ( ) from pipecat.processors.frame_processor import FrameDirection from pipecat.services.aws.sagemaker.bidi_client import SageMakerBidiClient -from pipecat.services.settings import NOT_GIVEN, STTSettings, _NotGiven +from pipecat.services.settings import _S, NOT_GIVEN, STTSettings, _NotGiven, is_given from pipecat.services.stt_latency import DEEPGRAM_SAGEMAKER_TTFS_P99 from pipecat.services.stt_service import STTService from pipecat.transcriptions.language import Language @@ -54,32 +54,117 @@ except ModuleNotFoundError as e: class DeepgramSageMakerSTTSettings(STTSettings): """Settings for the Deepgram SageMaker STT service. - Some commonly used ``LiveOptions`` fields are declared as top-level - fields here so they can be updated individually via - ``STTUpdateSettingsFrame``. Any *additional* ``LiveOptions`` fields - (e.g. ``filler_words``, ``diarize``, ``utterance_end_ms``) can be - passed through the ``extra`` dict — they will be forwarded to - ``LiveOptions`` when the connection is (re)established. This keeps the - settings class future-proof: new Deepgram features work without code - changes on the Pipecat side. + Wraps the Deepgram SDK's ``LiveOptions`` in a single ``live_options`` + field. All Deepgram-specific options (``filler_words``, ``diarize``, + ``utterance_end_ms``, etc.) should be passed directly via + ``LiveOptions``. + + In **delta mode** (i.e. when carried by ``STTUpdateSettingsFrame``), + ``live_options`` is treated as a **delta** — its non-None fields are + merged into the stored ``LiveOptions``, not replaced wholesale. For + example, ``DeepgramSageMakerSTTSettings(live_options=LiveOptions(punctuate=False))`` + changes only ``punctuate`` and leaves all other options intact. Parameters: - encoding: Audio encoding format (e.g. ``"linear16"``). - channels: Number of audio channels. - interim_results: Whether to return interim transcription results. - smart_format: Whether to enable Deepgram smart formatting. - punctuate: Whether to add punctuation to transcripts. - profanity_filter: Whether to filter profanity from transcripts. - vad_events: Whether to enable Deepgram VAD events (deprecated). + live_options: Deepgram ``LiveOptions`` for STT configuration. + In delta mode only its non-None fields are merged into the + stored options. """ - encoding: str | None | _NotGiven = field(default_factory=lambda: NOT_GIVEN) - channels: int | None | _NotGiven = field(default_factory=lambda: NOT_GIVEN) - interim_results: bool | None | _NotGiven = field(default_factory=lambda: NOT_GIVEN) - smart_format: bool | None | _NotGiven = field(default_factory=lambda: NOT_GIVEN) - punctuate: bool | None | _NotGiven = field(default_factory=lambda: NOT_GIVEN) - profanity_filter: bool | None | _NotGiven = field(default_factory=lambda: NOT_GIVEN) - vad_events: bool | None | _NotGiven = field(default_factory=lambda: NOT_GIVEN) + live_options: LiveOptions | _NotGiven = field(default_factory=lambda: NOT_GIVEN) + + # Valid LiveOptions __init__ parameter names (cached at class level). + _live_options_params: set[str] | None = field(default=None, init=False, repr=False) + + @classmethod + def _get_live_options_params(cls) -> set[str]: + """Return the set of valid ``LiveOptions.__init__`` parameter names.""" + if cls._live_options_params is None: + cls._live_options_params = set(inspect.signature(LiveOptions.__init__).parameters) - { + "self" + } + return cls._live_options_params + + def apply_update(self: _S, delta: _S) -> Dict[str, Any]: + """Merge a delta into this store, with delta-merge for ``live_options``. + + ``live_options`` is merged field-by-field (non-None fields from the + delta overwrite corresponding fields in the stored options) rather + than being replaced wholesale. + + ``model`` and ``language`` are kept in sync bidirectionally between + the top-level settings fields and ``live_options``. + """ + # Pull live_options out of the delta so super() doesn't replace it. + delta_lo = getattr(delta, "live_options", NOT_GIVEN) + if is_given(delta_lo): + delta.live_options = NOT_GIVEN # type: ignore[assignment] + + # Let the base class handle model, language, extra. + changed = super().apply_update(delta) + + # Sync top-level model/language changes into stored live_options. + if "model" in changed: + self.live_options.model = self.model # type: ignore[union-attr] + if "language" in changed: + self.live_options.language = self.language # type: ignore[union-attr] + + # Merge live_options delta. + if is_given(delta_lo): + old_dict = self.live_options.to_dict() # type: ignore[union-attr] + delta_dict = delta_lo.to_dict() + + if delta_dict: + merged = {**old_dict, **delta_dict} + self.live_options = LiveOptions(**merged) + + for key in delta_dict: + old_val = old_dict.get(key, NOT_GIVEN) + if old_val != delta_dict[key]: + changed[key] = old_val + + # Sync model/language from live_options delta to top-level. + if "model" in delta_dict and delta_dict["model"] != self.model: + changed.setdefault("model", self.model) + self.model = delta_dict["model"] + if "language" in delta_dict and delta_dict["language"] != self.language: + changed.setdefault("language", self.language) + self.language = delta_dict["language"] + + return changed + + @classmethod + def from_mapping(cls: Type[_S], settings: Mapping[str, Any]) -> _S: + """Build a delta from a plain dict, routing LiveOptions keys correctly. + + Keys that are valid ``LiveOptions.__init__`` parameters (and not + top-level ``STTSettings`` fields like ``model`` / ``language``) are + collected into a ``LiveOptions`` object. ``model`` and ``language`` + are routed to the top-level settings fields. Truly unknown keys go + to ``extra``. + """ + lo_params = cls._get_live_options_params() + stt_field_names = {"model", "language"} + + kwargs: Dict[str, Any] = {} + lo_kwargs: Dict[str, Any] = {} + extra: Dict[str, Any] = {} + + for key, value in settings.items(): + canonical = cls._aliases.get(key, key) + if canonical in stt_field_names: + kwargs[canonical] = value + elif canonical in lo_params: + lo_kwargs[canonical] = value + else: + extra[key] = value + + if lo_kwargs: + kwargs["live_options"] = LiveOptions(**lo_kwargs) + + instance = cls(**kwargs) + instance.extra = extra + return instance class DeepgramSageMakerSTTService(STTService): @@ -130,8 +215,9 @@ class DeepgramSageMakerSTTService(STTService): region: AWS region where the endpoint is deployed (e.g., "us-east-2"). sample_rate: Audio sample rate in Hz. If None, uses value from live_options or defaults to the value from StartFrame. - live_options: Deepgram LiveOptions for detailed configuration. If None, - uses sensible defaults (nova-3 model, English, interim results enabled). + live_options: Deepgram LiveOptions configuration. Treated as a + delta from a set of sensible defaults — only the fields you + set are overridden; all others keep their default values. ttfs_p99_latency: P99 latency from speech end to final transcript in seconds. Override for your deployment. See https://github.com/pipecat-ai/stt-benchmark **kwargs: Additional arguments passed to the parent STTService. @@ -149,29 +235,26 @@ class DeepgramSageMakerSTTService(STTService): ) # Merge with provided options - merged_options = default_options.to_dict() + merged_dict = default_options.to_dict() if live_options: default_model = default_options.model - merged_options.update(live_options.to_dict()) + merged_dict.update(live_options.to_dict()) # Handle the "None" string bug from deepgram-sdk - if "model" in merged_options and merged_options["model"] == "None": - merged_options["model"] = default_model + if "model" in merged_dict and merged_dict["model"] == "None": + merged_dict["model"] = default_model # Convert Language enum to string if needed - if "language" in merged_options and isinstance(merged_options["language"], Language): - merged_options["language"] = merged_options["language"].value + if "language" in merged_dict and isinstance(merged_dict["language"], Language): + merged_dict["language"] = merged_dict["language"].value - settings_fields = {f.name for f in fields(DeepgramSageMakerSTTSettings)} - settings_kwargs = {} - extra = {} - for key, value in merged_options.items(): - if key in settings_fields: - settings_kwargs[key] = value - else: - extra[key] = value + # Extract model/language for top-level STTSettings fields; everything + # else lives inside LiveOptions. + model = merged_dict.pop("model", None) + language = merged_dict.pop("language", None) - settings = DeepgramSageMakerSTTSettings(**settings_kwargs) - settings.extra = extra + settings = DeepgramSageMakerSTTSettings( + model=model, language=language, live_options=LiveOptions(**merged_dict) + ) super().__init__( sample_rate=sample_rate, @@ -255,32 +338,17 @@ class DeepgramSageMakerSTTService(STTService): yield None def _build_live_options(self) -> LiveOptions: - """Build a ``LiveOptions`` from flat settings fields, sample rate, and extras. + """Build a ``LiveOptions`` from stored settings and sample rate. Returns: A fully-populated ``LiveOptions`` ready for the Deepgram SDK. """ - valid_kwargs = set(inspect.signature(LiveOptions.__init__).parameters) - {"self"} + opts: dict[str, Any] = self._settings.live_options.to_dict() - # Start with extras that are valid LiveOptions kwargs. - opts: dict[str, Any] = {k: v for k, v in self._settings.extra.items() if k in valid_kwargs} - - # Override with flat settings fields (these take precedence). - s = self._settings - opts.update( - { - "model": s.model, - "language": s.language, - "encoding": s.encoding, - "channels": s.channels, - "interim_results": s.interim_results, - "smart_format": s.smart_format, - "punctuate": s.punctuate, - "profanity_filter": s.profanity_filter, - "vad_events": s.vad_events, - "sample_rate": self.sample_rate, - } - ) + # Overlay model/language from top-level settings and sample_rate from service. + opts["model"] = self._settings.model + opts["language"] = self._settings.language + opts["sample_rate"] = self.sample_rate return LiveOptions(**opts) diff --git a/tests/test_settings.py b/tests/test_settings.py index 85f89987c..3201e3c24 100644 --- a/tests/test_settings.py +++ b/tests/test_settings.py @@ -7,7 +7,10 @@ """Tests for the typed settings infrastructure in pipecat.services.settings.""" import pytest +from deepgram import LiveOptions +from pipecat.services.deepgram.stt import DeepgramSTTSettings +from pipecat.services.deepgram.stt_sagemaker import DeepgramSageMakerSTTSettings from pipecat.services.settings import ( NOT_GIVEN, LLMSettings, @@ -311,3 +314,211 @@ class TestRoundtrip: assert changed["model"] == "gpt-4o" assert current.model == "gpt-4o-mini" assert current.temperature == 0.9 + + +# --------------------------------------------------------------------------- +# DeepgramSTTSettings: live_options delta merge +# --------------------------------------------------------------------------- + + +class TestDeepgramSTTSettingsApplyUpdate: + def _make_store(self, **lo_kwargs) -> DeepgramSTTSettings: + """Helper to build a store-mode DeepgramSTTSettings.""" + defaults = dict( + encoding="linear16", + channels=1, + interim_results=True, + smart_format=False, + punctuate=True, + profanity_filter=True, + vad_events=False, + ) + defaults.update(lo_kwargs) + s = DeepgramSTTSettings( + model="nova-3-general", + language="en", + live_options=LiveOptions(**defaults), + ) + return s + + def test_apply_update_merges_live_options_as_delta(self): + """Only the given fields in the delta LiveOptions are merged.""" + current = self._make_store() + assert current.live_options.punctuate is True + + delta = DeepgramSTTSettings(live_options=LiveOptions(punctuate=False)) + changed = current.apply_update(delta) + + assert current.live_options.punctuate is False + assert "punctuate" in changed + # Other fields are untouched + assert current.live_options.encoding == "linear16" + assert current.live_options.channels == 1 + + def test_apply_update_syncs_model_from_live_options_to_top_level(self): + """model inside live_options delta should sync to top-level model.""" + current = self._make_store() + assert current.model == "nova-3-general" + + delta = DeepgramSTTSettings(live_options=LiveOptions(model="nova-2")) + changed = current.apply_update(delta) + + assert current.model == "nova-2" + assert "model" in changed + + def test_apply_update_syncs_language_from_live_options_to_top_level(self): + """language inside live_options delta should sync to top-level language.""" + current = self._make_store() + assert current.language == "en" + + delta = DeepgramSTTSettings(live_options=LiveOptions(language="es")) + changed = current.apply_update(delta) + + assert current.language == "es" + assert "language" in changed + + def test_apply_update_syncs_top_level_model_into_live_options(self): + """Top-level model change should propagate into stored live_options.""" + current = self._make_store() + assert current.model == "nova-3-general" + + delta = DeepgramSTTSettings(model="nova-2") + changed = current.apply_update(delta) + + assert current.model == "nova-2" + assert current.live_options.model == "nova-2" + assert "model" in changed + + def test_apply_update_syncs_top_level_language_into_live_options(self): + """Top-level language change should propagate into stored live_options.""" + current = self._make_store() + + delta = DeepgramSTTSettings(language="fr") + changed = current.apply_update(delta) + + assert current.language == "fr" + assert current.live_options.language == "fr" + assert "language" in changed + + def test_apply_update_no_change(self): + """Delta with same values should report no changes.""" + current = self._make_store() + delta = DeepgramSTTSettings(live_options=LiveOptions(punctuate=True)) + changed = current.apply_update(delta) + assert changed == {} + + +class TestDeepgramSTTSettingsFromMapping: + def test_routes_live_options_kwargs(self): + """LiveOptions-valid keys should be collected into live_options.""" + delta = DeepgramSTTSettings.from_mapping({"punctuate": False, "filler_words": True}) + assert is_given(delta.live_options) + assert delta.live_options.punctuate is False + assert delta.live_options.filler_words is True + + def test_routes_model_and_language_to_top_level(self): + """model and language should be top-level fields, not in live_options.""" + delta = DeepgramSTTSettings.from_mapping({"model": "nova-2", "language": "es"}) + assert delta.model == "nova-2" + assert delta.language == "es" + assert not is_given(delta.live_options) + + def test_unknown_keys_go_to_extra(self): + """Keys that aren't LiveOptions params or STT fields go to extra.""" + delta = DeepgramSTTSettings.from_mapping({"unknown_param": 42}) + assert delta.extra == {"unknown_param": 42} + assert not is_given(delta.live_options) + + def test_mixed_keys(self): + """model + LiveOptions keys + unknown keys are routed correctly.""" + delta = DeepgramSTTSettings.from_mapping( + {"model": "nova-2", "punctuate": False, "unknown": "val"} + ) + assert delta.model == "nova-2" + assert delta.live_options.punctuate is False + assert delta.extra == {"unknown": "val"} + + def test_roundtrip_from_mapping_apply_update(self): + """Simulate dict-style update: from_mapping -> apply_update.""" + current = DeepgramSTTSettings( + model="nova-3-general", + language="en", + live_options=LiveOptions( + encoding="linear16", + channels=1, + interim_results=True, + punctuate=True, + profanity_filter=True, + vad_events=False, + ), + ) + + raw = {"punctuate": False, "filler_words": True} + delta = DeepgramSTTSettings.from_mapping(raw) + changed = current.apply_update(delta) + + assert current.live_options.punctuate is False + assert current.live_options.filler_words is True + # Unchanged fields stay put + assert current.live_options.encoding == "linear16" + assert current.model == "nova-3-general" + assert "punctuate" in changed + + def test_roundtrip_model_via_dict(self): + """Dict update with model should change top-level and NOT create live_options.""" + current = DeepgramSTTSettings( + model="nova-3-general", + language="en", + live_options=LiveOptions(encoding="linear16", channels=1), + ) + + raw = {"model": "nova-2"} + delta = DeepgramSTTSettings.from_mapping(raw) + changed = current.apply_update(delta) + + assert current.model == "nova-2" + assert current.live_options.model == "nova-2" + assert "model" in changed + + +# --------------------------------------------------------------------------- +# DeepgramSageMakerSTTSettings: same pattern +# --------------------------------------------------------------------------- + + +class TestDeepgramSageMakerSTTSettingsApplyUpdate: + def _make_store(self, **lo_kwargs) -> DeepgramSageMakerSTTSettings: + defaults = dict( + encoding="linear16", + channels=1, + interim_results=True, + punctuate=True, + ) + defaults.update(lo_kwargs) + return DeepgramSageMakerSTTSettings( + model="nova-3", + language="en", + live_options=LiveOptions(**defaults), + ) + + def test_apply_update_merges_live_options_as_delta(self): + current = self._make_store() + delta = DeepgramSageMakerSTTSettings(live_options=LiveOptions(punctuate=False)) + changed = current.apply_update(delta) + assert current.live_options.punctuate is False + assert "punctuate" in changed + assert current.live_options.encoding == "linear16" + + def test_apply_update_syncs_model_from_live_options(self): + current = self._make_store() + delta = DeepgramSageMakerSTTSettings(live_options=LiveOptions(model="nova-2")) + current.apply_update(delta) + assert current.model == "nova-2" + + def test_from_mapping_routes_correctly(self): + delta = DeepgramSageMakerSTTSettings.from_mapping( + {"model": "nova-2", "punctuate": False, "unknown": "val"} + ) + assert delta.model == "nova-2" + assert delta.live_options.punctuate is False + assert delta.extra == {"unknown": "val"} From e21e8585f07964a6a1de114b259a7fd3a88cba53 Mon Sep 17 00:00:00 2001 From: Paul Kompfner Date: Wed, 25 Feb 2026 18:40:44 -0500 Subject: [PATCH 0648/1060] Add `deepgram` and `sagemaker` extras to CI test dependencies so Deepgram and Deepgram Sagemaker settings tests can run --- .github/workflows/coverage.yaml | 2 ++ .github/workflows/tests.yaml | 2 ++ 2 files changed, 4 insertions(+) diff --git a/.github/workflows/coverage.yaml b/.github/workflows/coverage.yaml index d65841a7d..26d03861b 100644 --- a/.github/workflows/coverage.yaml +++ b/.github/workflows/coverage.yaml @@ -37,10 +37,12 @@ jobs: uv sync --group dev \ --extra anthropic \ --extra aws \ + --extra deepgram \ --extra google \ --extra langchain \ --extra livekit \ --extra piper \ + --extra sagemaker \ --extra tracing \ --extra websocket diff --git a/.github/workflows/tests.yaml b/.github/workflows/tests.yaml index a36a2fbd0..b22d502c4 100644 --- a/.github/workflows/tests.yaml +++ b/.github/workflows/tests.yaml @@ -41,10 +41,12 @@ jobs: uv sync --group dev \ --extra anthropic \ --extra aws \ + --extra deepgram \ --extra google \ --extra langchain \ --extra livekit \ --extra piper \ + --extra sagemaker \ --extra tracing \ --extra websocket From f7434cdde1a1ca90e3ff44bca9883908fcc06b1c Mon Sep 17 00:00:00 2001 From: Mark Backman Date: Tue, 10 Feb 2026 13:54:57 -0500 Subject: [PATCH 0649/1060] Add text aggregation time metric for TTS sentence aggregation Add TextAggregationMetricsData measuring the time from the first LLM token to the first complete sentence, representing the latency cost of sentence aggregation in the TTS pipeline. --- changelog/3696.added.md | 1 + src/pipecat/metrics/metrics.py | 13 ++++++++++ src/pipecat/processors/frame_processor.py | 12 +++++++++ .../metrics/frame_processor_metrics.py | 25 +++++++++++++++++++ 4 files changed, 51 insertions(+) create mode 100644 changelog/3696.added.md diff --git a/changelog/3696.added.md b/changelog/3696.added.md new file mode 100644 index 000000000..39726d930 --- /dev/null +++ b/changelog/3696.added.md @@ -0,0 +1 @@ +- Added `TextAggregationMetricsData` metric measuring the time from the first LLM token to the first complete sentence, representing the latency cost of sentence aggregation in the TTS pipeline. diff --git a/src/pipecat/metrics/metrics.py b/src/pipecat/metrics/metrics.py index ccf30227a..2030306e5 100644 --- a/src/pipecat/metrics/metrics.py +++ b/src/pipecat/metrics/metrics.py @@ -87,6 +87,19 @@ class TTSUsageMetricsData(MetricsData): value: int +class TextAggregationMetricsData(MetricsData): + """Text aggregation time metrics data. + + Measures the time from the first LLM token to the first complete sentence, + representing the latency cost of sentence aggregation in the TTS pipeline. + + Parameters: + value: Aggregation time in seconds. + """ + + value: float + + class TurnMetricsData(MetricsData): """Metrics data for turn detection predictions. diff --git a/src/pipecat/processors/frame_processor.py b/src/pipecat/processors/frame_processor.py index bcdb2d57b..37e8dc10d 100644 --- a/src/pipecat/processors/frame_processor.py +++ b/src/pipecat/processors/frame_processor.py @@ -485,6 +485,18 @@ class FrameProcessor(BaseObject): if frame: await self.push_frame(frame) + async def start_text_aggregation_metrics(self): + """Start text aggregation time metrics collection.""" + if self.can_generate_metrics() and self.metrics_enabled: + await self._metrics.start_text_aggregation_metrics() + + async def stop_text_aggregation_metrics(self): + """Stop text aggregation time metrics collection and push results.""" + if self.can_generate_metrics() and self.metrics_enabled: + frame = await self._metrics.stop_text_aggregation_metrics() + if frame: + await self.push_frame(frame) + async def stop_all_metrics(self): """Stop all active metrics collection.""" await self.stop_ttfb_metrics() diff --git a/src/pipecat/processors/metrics/frame_processor_metrics.py b/src/pipecat/processors/metrics/frame_processor_metrics.py index c82fd9698..cb5bc8a42 100644 --- a/src/pipecat/processors/metrics/frame_processor_metrics.py +++ b/src/pipecat/processors/metrics/frame_processor_metrics.py @@ -17,6 +17,7 @@ from pipecat.metrics.metrics import ( LLMUsageMetricsData, MetricsData, ProcessingMetricsData, + TextAggregationMetricsData, TTFBMetricsData, TTSUsageMetricsData, ) @@ -211,3 +212,27 @@ class FrameProcessorMetrics(BaseObject): ) logger.debug(f"{self._processor_name()} usage characters: {characters.value}") return MetricsFrame(data=[characters]) + + async def start_text_aggregation_metrics(self): + """Start measuring text aggregation time (first token to first sentence).""" + self._start_text_aggregation_time = time.time() + + async def stop_text_aggregation_metrics(self): + """Stop text aggregation measurement and generate metrics frame. + + Returns: + MetricsFrame containing text aggregation time, or None if not measuring. + """ + if ( + not hasattr(self, "_start_text_aggregation_time") + or self._start_text_aggregation_time == 0 + ): + return None + + value = time.time() - self._start_text_aggregation_time + logger.debug(f"{self._processor_name()} text aggregation time: {value}") + aggregation = TextAggregationMetricsData( + processor=self._processor_name(), value=value, model=self._model_name() + ) + self._start_text_aggregation_time = 0 + return MetricsFrame(data=[aggregation]) From d69a337def945729f10fd444d29f1d21203cef8a Mon Sep 17 00:00:00 2001 From: Mark Backman Date: Tue, 10 Feb 2026 13:55:19 -0500 Subject: [PATCH 0650/1060] Add text_aggregation_mode parameter to TTSService Move the sentence vs token aggregation concern into text aggregators so all text flows through them regardless of mode. This enables pattern detection and tag handling to work in TOKEN mode. - Add TextAggregationMode enum (SENTENCE, TOKEN) as the user-facing TTS setting, separate from the internal AggregationType - Add TOKEN mode support to Simple, SkipTags, and PatternPair aggregators - Add text_aggregation_mode parameter to TTSService and all TTS subclasses - Deprecate aggregate_sentences in favor of text_aggregation_mode - Merge TTSService._process_text_frame() into a single codepath --- changelog/3696.changed.md | 1 + changelog/3696.deprecated.md | 1 + examples/foundational/07-interruptible.py | 2 + src/pipecat/frames/frames.py | 12 +- src/pipecat/services/asyncai/tts.py | 13 +- src/pipecat/services/azure/tts.py | 15 +- src/pipecat/services/cartesia/tts.py | 33 +++-- src/pipecat/services/elevenlabs/tts.py | 28 +++- src/pipecat/services/inworld/tts.py | 13 +- src/pipecat/services/neuphonic/tts.py | 13 +- src/pipecat/services/rime/tts.py | 29 +++- src/pipecat/services/sarvam/tts.py | 13 +- src/pipecat/services/tts_service.py | 130 ++++++++++++++---- .../utils/text/base_text_aggregator.py | 20 +++ .../utils/text/pattern_pair_aggregator.py | 41 ++++-- .../utils/text/simple_text_aggregator.py | 32 +++-- .../utils/text/skip_tags_aggregator.py | 29 +++- tests/test_pattern_pair_aggregator.py | 61 ++++++++ tests/test_simple_text_aggregator.py | 34 +++++ tests/test_skip_tags_aggregator.py | 55 ++++++++ 20 files changed, 480 insertions(+), 95 deletions(-) create mode 100644 changelog/3696.changed.md create mode 100644 changelog/3696.deprecated.md diff --git a/changelog/3696.changed.md b/changelog/3696.changed.md new file mode 100644 index 000000000..a495560ba --- /dev/null +++ b/changelog/3696.changed.md @@ -0,0 +1 @@ +- Added `text_aggregation_mode` parameter to `TTSService` and all TTS subclasses with a new `TextAggregationMode` enum (`SENTENCE`, `TOKEN`). All text now flows through text aggregators regardless of mode, enabling pattern detection and tag handling in TOKEN mode. diff --git a/changelog/3696.deprecated.md b/changelog/3696.deprecated.md new file mode 100644 index 000000000..7b371fc21 --- /dev/null +++ b/changelog/3696.deprecated.md @@ -0,0 +1 @@ +- ⚠️ Deprecated `aggregate_sentences` parameter on `TTSService` and all TTS subclasses. Use `text_aggregation_mode=TextAggregationMode.SENTENCE` or `text_aggregation_mode=TextAggregationMode.TOKEN` instead. diff --git a/examples/foundational/07-interruptible.py b/examples/foundational/07-interruptible.py index c5964506a..e47d2c811 100644 --- a/examples/foundational/07-interruptible.py +++ b/examples/foundational/07-interruptible.py @@ -24,6 +24,7 @@ from pipecat.runner.utils import create_transport from pipecat.services.cartesia.tts import CartesiaTTSService from pipecat.services.deepgram.stt import DeepgramSTTService from pipecat.services.openai.llm import OpenAILLMService +from pipecat.services.tts_service import TextAggregationMode from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams @@ -56,6 +57,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): tts = CartesiaTTSService( api_key=os.getenv("CARTESIA_API_KEY"), voice_id="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady + text_aggregation_mode=TextAggregationMode.TOKEN, ) llm = OpenAILLMService(api_key=os.getenv("OPENAI_API_KEY")) diff --git a/src/pipecat/frames/frames.py b/src/pipecat/frames/frames.py index d359bcfb1..55ae975d1 100644 --- a/src/pipecat/frames/frames.py +++ b/src/pipecat/frames/frames.py @@ -14,7 +14,6 @@ and LLM processing. import asyncio import time from dataclasses import dataclass, field -from enum import Enum from typing import ( TYPE_CHECKING, Any, @@ -36,6 +35,7 @@ from pipecat.audio.turn.base_turn_analyzer import BaseTurnParams from pipecat.audio.vad.vad_analyzer import VADParams from pipecat.metrics.metrics import MetricsData from pipecat.transcriptions.language import Language +from pipecat.utils.text.base_text_aggregator import AggregationType from pipecat.utils.time import nanoseconds_to_str from pipecat.utils.utils import obj_count, obj_id @@ -393,16 +393,6 @@ class LLMTextFrame(TextFrame): self.includes_inter_frame_spaces = True -class AggregationType(str, Enum): - """Built-in aggregation strings.""" - - SENTENCE = "sentence" - WORD = "word" - - def __str__(self): - return self.value - - @dataclass class AggregatedTextFrame(TextFrame): """Text frame representing an aggregation of TextFrames. diff --git a/src/pipecat/services/asyncai/tts.py b/src/pipecat/services/asyncai/tts.py index 334f80d80..4f1fd5a58 100644 --- a/src/pipecat/services/asyncai/tts.py +++ b/src/pipecat/services/asyncai/tts.py @@ -28,7 +28,7 @@ from pipecat.frames.frames import ( ) from pipecat.processors.frame_processor import FrameDirection from pipecat.services.settings import NOT_GIVEN, TTSSettings, _NotGiven -from pipecat.services.tts_service import AudioContextTTSService, TTSService +from pipecat.services.tts_service import AudioContextTTSService, TextAggregationMode, TTSService from pipecat.transcriptions.language import Language, resolve_language from pipecat.utils.tracing.service_decorators import traced_tts @@ -128,7 +128,8 @@ class AsyncAITTSService(AudioContextTTSService): encoding: str = "pcm_s16le", container: str = "raw", params: Optional[InputParams] = None, - aggregate_sentences: Optional[bool] = True, + aggregate_sentences: Optional[bool] = None, + text_aggregation_mode: Optional[TextAggregationMode] = None, **kwargs, ): """Initialize the Async TTS service. @@ -144,13 +145,19 @@ class AsyncAITTSService(AudioContextTTSService): encoding: Audio encoding format. container: Audio container format. params: Additional input parameters for voice customization. - aggregate_sentences: Whether to aggregate sentences within the TTSService. + aggregate_sentences: Deprecated. Use text_aggregation_mode instead. + + .. deprecated:: 0.0.104 + Use ``text_aggregation_mode`` instead. + + text_aggregation_mode: How to aggregate text before synthesis. **kwargs: Additional arguments passed to the parent service. """ params = params or AsyncAITTSService.InputParams() super().__init__( aggregate_sentences=aggregate_sentences, + text_aggregation_mode=text_aggregation_mode, pause_frame_processing=True, push_stop_frames=True, sample_rate=sample_rate, diff --git a/src/pipecat/services/azure/tts.py b/src/pipecat/services/azure/tts.py index b3534b28e..f68694eb5 100644 --- a/src/pipecat/services/azure/tts.py +++ b/src/pipecat/services/azure/tts.py @@ -27,7 +27,7 @@ from pipecat.frames.frames import ( from pipecat.processors.frame_processor import FrameDirection from pipecat.services.azure.common import language_to_azure_language from pipecat.services.settings import NOT_GIVEN, TTSSettings, _NotGiven -from pipecat.services.tts_service import TTSService +from pipecat.services.tts_service import TextAggregationMode, TTSService from pipecat.transcriptions.language import Language from pipecat.utils.tracing.service_decorators import traced_tts @@ -256,7 +256,8 @@ class AzureTTSService(TTSService, AzureBaseTTSService): voice: str = "en-US-SaraNeural", sample_rate: Optional[int] = None, params: Optional[AzureBaseTTSService.InputParams] = None, - aggregate_sentences: bool = True, + aggregate_sentences: Optional[bool] = None, + text_aggregation_mode: Optional[TextAggregationMode] = None, **kwargs, ): """Initialize the Azure streaming TTS service. @@ -267,13 +268,19 @@ class AzureTTSService(TTSService, AzureBaseTTSService): voice: Voice name to use for synthesis. Defaults to "en-US-SaraNeural". sample_rate: Audio sample rate in Hz. If None, uses service default. params: Voice and synthesis parameters configuration. - aggregate_sentences: Whether to aggregate sentences before synthesis. - **kwargs: Additional arguments passed to the parent TTSService. + aggregate_sentences: Deprecated. Use text_aggregation_mode instead. + + .. deprecated:: 0.0.104 + Use ``text_aggregation_mode`` instead. + + text_aggregation_mode: How to aggregate text before synthesis. + **kwargs: Additional arguments passed to parent WordTTSService. """ params = params or AzureBaseTTSService.InputParams() super().__init__( aggregate_sentences=aggregate_sentences, + text_aggregation_mode=text_aggregation_mode, push_text_frames=False, # We'll push text frames based on word timestamps push_stop_frames=True, pause_frame_processing=True, diff --git a/src/pipecat/services/cartesia/tts.py b/src/pipecat/services/cartesia/tts.py index edf838e59..0749af062 100644 --- a/src/pipecat/services/cartesia/tts.py +++ b/src/pipecat/services/cartesia/tts.py @@ -27,7 +27,7 @@ from pipecat.frames.frames import ( TTSStoppedFrame, ) from pipecat.services.settings import NOT_GIVEN, TTSSettings, _NotGiven -from pipecat.services.tts_service import AudioContextTTSService, TTSService +from pipecat.services.tts_service import AudioContextTTSService, TextAggregationMode, TTSService from pipecat.transcriptions.language import Language, resolve_language from pipecat.utils.text.base_text_aggregator import BaseTextAggregator from pipecat.utils.text.skip_tags_aggregator import SkipTagsAggregator @@ -272,7 +272,8 @@ class CartesiaTTSService(AudioContextTTSService): container: str = "raw", params: Optional[InputParams] = None, text_aggregator: Optional[BaseTextAggregator] = None, - aggregate_sentences: Optional[bool] = True, + text_aggregation_mode: Optional[TextAggregationMode] = None, + aggregate_sentences: Optional[bool] = None, **kwargs, ): """Initialize the Cartesia TTS service. @@ -292,13 +293,19 @@ class CartesiaTTSService(AudioContextTTSService): .. deprecated:: 0.0.95 Use an LLMTextProcessor before the TTSService for custom text aggregation. + text_aggregation_mode: How to aggregate incoming text before synthesis. aggregate_sentences: Whether to aggregate sentences within the TTSService. + + .. deprecated:: 0.0.104 + Use ``text_aggregation_mode`` instead. + **kwargs: Additional arguments passed to the parent service. """ - # Aggregating sentences still gives cleaner-sounding results and fewer - # artifacts than streaming one word at a time. On average, waiting for a - # full sentence should only "cost" us 15ms or so with GPT-4o or a Llama - # 3 model, and it's worth it for the better audio quality. + # By default, we aggregate sentences before sending to TTS. This adds + # ~200-300ms of latency per sentence (waiting for the sentence-ending + # punctuation token from the LLM). Setting aggregate_sentences=False + # streams tokens directly, which reduces latency. Streaming quality + # is good but less tested than sentence aggregation. # # We also don't want to automatically push LLM response text frames, # because the context aggregators will add them to the LLM context even @@ -308,6 +315,7 @@ class CartesiaTTSService(AudioContextTTSService): params = params or CartesiaTTSService.InputParams() super().__init__( + text_aggregation_mode=text_aggregation_mode, aggregate_sentences=aggregate_sentences, push_text_frames=False, pause_frame_processing=True, @@ -337,7 +345,9 @@ class CartesiaTTSService(AudioContextTTSService): # The preferred way of taking advantage of Cartesia SSML Tags is # to use an LLMTextProcessor and/or a text_transformer to identify # and insert these tags for the purpose of the TTS service alone. - self._text_aggregator = SkipTagsAggregator([("", "")]) + self._text_aggregator = SkipTagsAggregator( + [("", "")], aggregation_type=self._text_aggregation_mode + ) self._api_key = api_key self._cartesia_version = cartesia_version @@ -639,7 +649,10 @@ class CartesiaTTSService(AudioContextTTSService): Yields: Frame: Audio frames containing the synthesized speech. """ - logger.debug(f"{self}: Generating TTS [{text}]") + if not self._is_streaming_tokens: + logger.debug(f"{self}: Generating TTS [{text}]") + else: + logger.trace(f"{self}: Generating TTS [{text}]") try: if not self._websocket or self._websocket.state is State.CLOSED: @@ -654,7 +667,9 @@ class CartesiaTTSService(AudioContextTTSService): try: await self._get_websocket().send(msg) - await self.start_tts_usage_metrics(text) + # Usage metrics are aggregated at flush time when streaming tokens. + if not self._is_streaming_tokens: + await self.start_tts_usage_metrics(text) except Exception as e: yield ErrorFrame(error=f"Unknown error occurred: {e}") yield TTSStoppedFrame(context_id=context_id) diff --git a/src/pipecat/services/elevenlabs/tts.py b/src/pipecat/services/elevenlabs/tts.py index c68d005f1..dcfdebc2f 100644 --- a/src/pipecat/services/elevenlabs/tts.py +++ b/src/pipecat/services/elevenlabs/tts.py @@ -47,6 +47,7 @@ from pipecat.processors.frame_processor import FrameDirection from pipecat.services.settings import NOT_GIVEN, TTSSettings, _NotGiven from pipecat.services.tts_service import ( AudioContextTTSService, + TextAggregationMode, TTSService, ) from pipecat.transcriptions.language import Language, resolve_language @@ -365,7 +366,8 @@ class ElevenLabsTTSService(AudioContextTTSService): url: str = "wss://api.elevenlabs.io", sample_rate: Optional[int] = None, params: Optional[InputParams] = None, - aggregate_sentences: Optional[bool] = True, + text_aggregation_mode: Optional[TextAggregationMode] = None, + aggregate_sentences: Optional[bool] = None, **kwargs, ): """Initialize the ElevenLabs TTS service. @@ -377,13 +379,19 @@ class ElevenLabsTTSService(AudioContextTTSService): url: WebSocket URL for ElevenLabs TTS API. sample_rate: Audio sample rate. If None, uses default. params: Additional input parameters for voice customization. + text_aggregation_mode: How to aggregate incoming text before synthesis. aggregate_sentences: Whether to aggregate sentences within the TTSService. + + .. deprecated:: 0.0.104 + Use ``text_aggregation_mode`` instead. + **kwargs: Additional arguments passed to the parent service. """ - # Aggregating sentences still gives cleaner-sounding results and fewer - # artifacts than streaming one word at a time. On average, waiting for a - # full sentence should only "cost" us 15ms or so with GPT-4o or a Llama - # 3 model, and it's worth it for the better audio quality. + # By default, we aggregate sentences before sending to TTS. This adds + # ~200-300ms of latency per sentence (waiting for the sentence-ending + # punctuation token from the LLM). Setting aggregate_sentences=False + # streams tokens directly. To use this mode, you must set auto_mode=False. + # This eliminates aggregation time, but slows down ElevenLabs. # # We also don't want to automatically push LLM response text frames, # because the context aggregators will add them to the LLM context even @@ -397,6 +405,7 @@ class ElevenLabsTTSService(AudioContextTTSService): params = params or ElevenLabsTTSService.InputParams() super().__init__( + text_aggregation_mode=text_aggregation_mode, aggregate_sentences=aggregate_sentences, push_text_frames=False, push_stop_frames=True, @@ -893,7 +902,8 @@ class ElevenLabsHttpTTSService(TTSService): base_url: str = "https://api.elevenlabs.io", sample_rate: Optional[int] = None, params: Optional[InputParams] = None, - aggregate_sentences: Optional[bool] = True, + text_aggregation_mode: Optional[TextAggregationMode] = None, + aggregate_sentences: Optional[bool] = None, **kwargs, ): """Initialize the ElevenLabs HTTP TTS service. @@ -906,12 +916,18 @@ class ElevenLabsHttpTTSService(TTSService): base_url: Base URL for ElevenLabs HTTP API. sample_rate: Audio sample rate. If None, uses default. params: Additional input parameters for voice customization. + text_aggregation_mode: How to aggregate incoming text before synthesis. aggregate_sentences: Whether to aggregate sentences within the TTSService. + + .. deprecated:: 0.0.104 + Use ``text_aggregation_mode`` instead. + **kwargs: Additional arguments passed to the parent service. """ params = params or ElevenLabsHttpTTSService.InputParams() super().__init__( + text_aggregation_mode=text_aggregation_mode, aggregate_sentences=aggregate_sentences, push_text_frames=False, push_stop_frames=True, diff --git a/src/pipecat/services/inworld/tts.py b/src/pipecat/services/inworld/tts.py index 2fb86b4a6..d3f64c16f 100644 --- a/src/pipecat/services/inworld/tts.py +++ b/src/pipecat/services/inworld/tts.py @@ -51,7 +51,7 @@ from pipecat.frames.frames import ( TTSStoppedFrame, ) from pipecat.processors.frame_processor import FrameDirection -from pipecat.services.tts_service import AudioContextTTSService, TTSService +from pipecat.services.tts_service import AudioContextTTSService, TextAggregationMode, TTSService from pipecat.utils.tracing.service_decorators import traced_tts @@ -509,7 +509,8 @@ class InworldTTSService(AudioContextTTSService): sample_rate: Optional[int] = None, encoding: str = "LINEAR16", params: InputParams = None, - aggregate_sentences: bool = True, + aggregate_sentences: Optional[bool] = None, + text_aggregation_mode: Optional[TextAggregationMode] = None, append_trailing_space: bool = True, **kwargs: Any, ): @@ -523,7 +524,12 @@ class InworldTTSService(AudioContextTTSService): sample_rate: Audio sample rate in Hz. encoding: Audio encoding format. params: Input parameters for Inworld WebSocket TTS configuration. - aggregate_sentences: Whether to aggregate sentences before synthesis. + aggregate_sentences: Deprecated. Use text_aggregation_mode instead. + + .. deprecated:: 0.0.104 + Use ``text_aggregation_mode`` instead. + + text_aggregation_mode: How to aggregate text before synthesis. append_trailing_space: Whether to append a trailing space to text before sending to TTS. **kwargs: Additional arguments passed to the parent class. """ @@ -536,6 +542,7 @@ class InworldTTSService(AudioContextTTSService): supports_word_timestamps=True, sample_rate=sample_rate, aggregate_sentences=aggregate_sentences, + text_aggregation_mode=text_aggregation_mode, append_trailing_space=append_trailing_space, settings=InworldTTSSettings( model=model, diff --git a/src/pipecat/services/neuphonic/tts.py b/src/pipecat/services/neuphonic/tts.py index 81b366a8b..63411c3eb 100644 --- a/src/pipecat/services/neuphonic/tts.py +++ b/src/pipecat/services/neuphonic/tts.py @@ -36,7 +36,7 @@ from pipecat.frames.frames import ( ) from pipecat.processors.frame_processor import FrameDirection from pipecat.services.settings import NOT_GIVEN, TTSSettings, _NotGiven -from pipecat.services.tts_service import InterruptibleTTSService, TTSService +from pipecat.services.tts_service import InterruptibleTTSService, TextAggregationMode, TTSService from pipecat.transcriptions.language import Language, resolve_language from pipecat.utils.tracing.service_decorators import traced_tts @@ -119,7 +119,8 @@ class NeuphonicTTSService(InterruptibleTTSService): sample_rate: Optional[int] = 22050, encoding: str = "pcm_linear", params: Optional[InputParams] = None, - aggregate_sentences: Optional[bool] = True, + aggregate_sentences: Optional[bool] = None, + text_aggregation_mode: Optional[TextAggregationMode] = None, **kwargs, ): """Initialize the Neuphonic TTS service. @@ -131,13 +132,19 @@ class NeuphonicTTSService(InterruptibleTTSService): sample_rate: Audio sample rate in Hz. Defaults to 22050. encoding: Audio encoding format. Defaults to "pcm_linear". params: Additional input parameters for TTS configuration. - aggregate_sentences: Whether to aggregate sentences within the TTSService. + aggregate_sentences: Deprecated. Use text_aggregation_mode instead. + + .. deprecated:: 0.0.104 + Use ``text_aggregation_mode`` instead. + + text_aggregation_mode: How to aggregate text before synthesis. **kwargs: Additional arguments passed to parent InterruptibleTTSService. """ params = params or NeuphonicTTSService.InputParams() super().__init__( aggregate_sentences=aggregate_sentences, + text_aggregation_mode=text_aggregation_mode, push_stop_frames=True, stop_frame_timeout_s=2.0, sample_rate=sample_rate, diff --git a/src/pipecat/services/rime/tts.py b/src/pipecat/services/rime/tts.py index 059db8178..d5f97e028 100644 --- a/src/pipecat/services/rime/tts.py +++ b/src/pipecat/services/rime/tts.py @@ -35,6 +35,7 @@ from pipecat.services.settings import NOT_GIVEN, TTSSettings, _NotGiven from pipecat.services.tts_service import ( AudioContextTTSService, InterruptibleTTSService, + TextAggregationMode, TTSService, ) from pipecat.transcriptions.language import Language, resolve_language @@ -181,7 +182,8 @@ class RimeTTSService(AudioContextTTSService): sample_rate: Optional[int] = None, params: Optional[InputParams] = None, text_aggregator: Optional[BaseTextAggregator] = None, - aggregate_sentences: Optional[bool] = True, + text_aggregation_mode: Optional[TextAggregationMode] = None, + aggregate_sentences: Optional[bool] = None, **kwargs, ): """Initialize Rime TTS service. @@ -198,13 +200,19 @@ class RimeTTSService(AudioContextTTSService): .. deprecated:: 0.0.95 Use an LLMTextProcessor before the TTSService for custom text aggregation. - aggregate_sentences: Whether to aggregate sentences within the TTSService. + text_aggregation_mode: How to aggregate incoming text before synthesis. + aggregate_sentences: Deprecated. Use text_aggregation_mode instead. + + .. deprecated:: 0.0.104 + Use ``text_aggregation_mode`` instead. + **kwargs: Additional arguments passed to parent class. """ # Initialize with parent class settings for proper frame handling params = params or RimeTTSService.InputParams() super().__init__( + text_aggregation_mode=text_aggregation_mode, aggregate_sentences=aggregate_sentences, push_text_frames=False, push_stop_frames=True, @@ -243,7 +251,9 @@ class RimeTTSService(AudioContextTTSService): # The preferred way of taking advantage of Rime spelling is # to use an LLMTextProcessor and/or a text_transformer to identify # and insert these tags for the purpose of the TTS service alone. - self._text_aggregator = SkipTagsAggregator([("spell(", ")")]) + self._text_aggregator = SkipTagsAggregator( + [("spell(", ")")], aggregation_type=self._text_aggregation_mode + ) # Store service configuration self._api_key = api_key @@ -826,7 +836,8 @@ class RimeNonJsonTTSService(InterruptibleTTSService): audio_format: str = "pcm", sample_rate: Optional[int] = None, params: Optional[InputParams] = None, - aggregate_sentences: Optional[bool] = True, + aggregate_sentences: Optional[bool] = None, + text_aggregation_mode: Optional[TextAggregationMode] = None, **kwargs, ): """Initialize Rime Non-JSON WebSocket TTS service. @@ -839,13 +850,21 @@ class RimeNonJsonTTSService(InterruptibleTTSService): audio_format: Audio format to use. sample_rate: Audio sample rate in Hz. params: Additional configuration parameters. - aggregate_sentences: Whether to aggregate sentences within the TTSService. + aggregate_sentences: Deprecated. Use text_aggregation_mode instead. + + .. deprecated:: 0.0.104 + Use ``text_aggregation_mode`` instead. Set to ``TextAggregationMode.SENTENCE`` + to aggregate text into sentences before synthesis, or + ``TextAggregationMode.TOKEN`` to stream tokens directly for lower latency. + + text_aggregation_mode: How to aggregate text before synthesis. **kwargs: Additional arguments passed to parent class. """ params = params or RimeNonJsonTTSService.InputParams() super().__init__( sample_rate=sample_rate, aggregate_sentences=aggregate_sentences, + text_aggregation_mode=text_aggregation_mode, push_stop_frames=True, pause_frame_processing=True, append_trailing_space=True, diff --git a/src/pipecat/services/sarvam/tts.py b/src/pipecat/services/sarvam/tts.py index 7b63828a1..87604a9f9 100644 --- a/src/pipecat/services/sarvam/tts.py +++ b/src/pipecat/services/sarvam/tts.py @@ -63,7 +63,7 @@ from pipecat.frames.frames import ( from pipecat.processors.frame_processor import FrameDirection from pipecat.services.sarvam._sdk import sdk_headers from pipecat.services.settings import NOT_GIVEN, TTSSettings, _NotGiven -from pipecat.services.tts_service import InterruptibleTTSService, TTSService +from pipecat.services.tts_service import InterruptibleTTSService, TextAggregationMode, TTSService from pipecat.transcriptions.language import Language, resolve_language from pipecat.utils.tracing.service_decorators import traced_tts @@ -785,7 +785,8 @@ class SarvamTTSService(InterruptibleTTSService): model: str = "bulbul:v2", voice_id: Optional[str] = None, url: str = "wss://api.sarvam.ai/text-to-speech/ws", - aggregate_sentences: Optional[bool] = True, + aggregate_sentences: Optional[bool] = None, + text_aggregation_mode: Optional[TextAggregationMode] = None, sample_rate: Optional[int] = None, params: Optional[InputParams] = None, **kwargs, @@ -799,7 +800,12 @@ class SarvamTTSService(InterruptibleTTSService): - "bulbul:v3-beta": Advanced model with temperature control voice_id: Speaker voice ID. If None, uses model-appropriate default. url: WebSocket URL for the TTS backend (default production URL). - aggregate_sentences: Merge multiple sentences into one audio chunk (default True). + aggregate_sentences: Deprecated. Use text_aggregation_mode instead. + + .. deprecated:: 0.0.104 + Use ``text_aggregation_mode`` instead. + + text_aggregation_mode: How to aggregate text before synthesis. sample_rate: Output audio sample rate in Hz (8000, 16000, 22050, 24000). If None, uses model-specific default. params: Optional input parameters to override defaults. @@ -834,6 +840,7 @@ class SarvamTTSService(InterruptibleTTSService): # Initialize parent class first super().__init__( aggregate_sentences=aggregate_sentences, + text_aggregation_mode=text_aggregation_mode, push_text_frames=True, pause_frame_processing=True, push_stop_frames=True, diff --git a/src/pipecat/services/tts_service.py b/src/pipecat/services/tts_service.py index e36d4754f..8c61f225d 100644 --- a/src/pipecat/services/tts_service.py +++ b/src/pipecat/services/tts_service.py @@ -11,6 +11,7 @@ import uuid import warnings from abc import abstractmethod from dataclasses import dataclass +from enum import Enum from typing import ( Any, AsyncGenerator, @@ -72,6 +73,23 @@ class TTSContext: append_to_context: bool = True +class TextAggregationMode(str, Enum): + """Controls how incoming text is aggregated before TTS synthesis. + + Parameters: + SENTENCE: Buffer text until sentence boundaries are detected before synthesis. + Produces more natural speech but adds latency (~200-300ms per sentence). + TOKEN: Stream text tokens directly to TTS as they arrive. + Reduces latency but may affect speech quality depending on the TTS provider. + """ + + SENTENCE = "sentence" + TOKEN = "token" + + def __str__(self): + return self.value + + class TTSService(AIService): """Base class for text-to-speech services. @@ -109,7 +127,8 @@ class TTSService(AIService): def __init__( self, *, - aggregate_sentences: bool = True, + text_aggregation_mode: Optional[TextAggregationMode] = None, + aggregate_sentences: Optional[bool] = None, # if True, TTSService will push TextFrames and LLMFullResponseEndFrames, # otherwise subclass must do it push_text_frames: bool = True, @@ -153,7 +172,16 @@ class TTSService(AIService): """Initialize the TTS service. Args: + text_aggregation_mode: How to aggregate incoming text before synthesis. + TextAggregationMode.SENTENCE (default) buffers until sentence boundaries, + TextAggregationMode.TOKEN streams tokens directly for lower latency. aggregate_sentences: Whether to aggregate text into sentences before synthesis. + + .. deprecated:: 0.0.104 + Use ``text_aggregation_mode`` instead. Set to ``TextAggregationMode.SENTENCE`` + to aggregate text into sentences before synthesis, or + ``TextAggregationMode.TOKEN`` to stream tokens directly for lower latency. + push_text_frames: Whether to push TextFrames and LLMFullResponseEndFrames. push_stop_frames: Whether to automatically push TTSStoppedFrames. stop_frame_timeout_s: Idle time before pushing TTSStoppedFrame when push_stop_frames is True. @@ -194,7 +222,33 @@ class TTSService(AIService): or TTSSettings(), **kwargs, ) - self._aggregate_sentences: bool = aggregate_sentences + + # Resolve text_aggregation_mode from the new param or deprecated aggregate_sentences + if aggregate_sentences is not None: + import warnings + + with warnings.catch_warnings(): + warnings.simplefilter("always") + warnings.warn( + "Parameter 'aggregate_sentences' is deprecated. " + "Use 'text_aggregation_mode=TextAggregationMode.SENTENCE' or " + "'text_aggregation_mode=TextAggregationMode.TOKEN' instead.", + DeprecationWarning, + stacklevel=2, + ) + if text_aggregation_mode is None: + text_aggregation_mode = ( + TextAggregationMode.SENTENCE + if aggregate_sentences + else TextAggregationMode.TOKEN + ) + + if text_aggregation_mode is None: + text_aggregation_mode = TextAggregationMode.SENTENCE + + self._text_aggregation_mode: TextAggregationMode = text_aggregation_mode + # Keep for backward compat with subclasses that read self._aggregate_sentences + self._aggregate_sentences: bool = text_aggregation_mode != TextAggregationMode.TOKEN self._push_text_frames: bool = push_text_frames self._push_stop_frames: bool = push_stop_frames self._stop_frame_timeout_s: float = stop_frame_timeout_s @@ -204,7 +258,9 @@ class TTSService(AIService): self._append_trailing_space: bool = append_trailing_space self._init_sample_rate = sample_rate self._sample_rate = 0 - self._text_aggregator: BaseTextAggregator = text_aggregator or SimpleTextAggregator() + self._text_aggregator: BaseTextAggregator = text_aggregator or SimpleTextAggregator( + aggregation_type=self._text_aggregation_mode + ) if text_aggregator: import warnings @@ -240,6 +296,8 @@ class TTSService(AIService): self._processing_text: bool = False self._tts_contexts: Dict[str, TTSContext] = {} + self._streaming_text_log: str = "" + self._aggregation_logged: bool = False # Word timestamp state (active when supports_word_timestamps=True) self._supports_word_timestamps: bool = supports_word_timestamps @@ -253,6 +311,11 @@ class TTSService(AIService): self._register_event_handler("on_connection_error") self._register_event_handler("on_tts_request") + @property + def _is_streaming_tokens(self) -> bool: + """Whether the service is streaming tokens directly without sentence aggregation.""" + return self._text_aggregation_mode == TextAggregationMode.TOKEN + @property def sample_rate(self) -> int: """Get the current sample rate for audio output. @@ -511,6 +574,9 @@ class TTSService(AIService): and not isinstance(frame, InterimTranscriptionFrame) and not isinstance(frame, TranscriptionFrame) ): + if not self._is_streaming_tokens and not self._aggregation_logged: + await self.start_text_aggregation_metrics() + self._aggregation_logged = True await self._process_text_frame(frame) elif isinstance(frame, InterruptionFrame): await self._handle_interruption(frame, direction) @@ -527,8 +593,18 @@ class TTSService(AIService): # Flush any remaining text (including text waiting for lookahead) remaining = await self._text_aggregator.flush() if remaining: + # If this is the first (and only) sentence, stop the aggregation metric. + await self.stop_text_aggregation_metrics() await self._push_tts_frames(AggregatedTextFrame(remaining.text, remaining.type)) + self._aggregation_logged = False + + # Log accumulated streamed text and emit aggregated usage metric. + if self._streaming_text_log: + logger.debug(f"{self}: Generating TTS [{self._streaming_text_log}]") + await self.start_tts_usage_metrics(self._streaming_text_log) + self._streaming_text_log = "" + # Reset aggregator state self._processing_text = False if isinstance(frame, LLMFullResponseEndFrame): @@ -690,26 +766,18 @@ class TTSService(AIService): await self.resume_processing_frames() async def _process_text_frame(self, frame: TextFrame): - text: Optional[str] = None - includes_inter_frame_spaces: bool = False - if not self._aggregate_sentences: - text = frame.text - includes_inter_frame_spaces = frame.includes_inter_frame_spaces - aggregated_by = "token" - - if text: - logger.trace(f"Pushing TTS frames for text: {text}, {aggregated_by}") - await self._push_tts_frames( - AggregatedTextFrame(text, aggregated_by), includes_inter_frame_spaces - ) - else: - async for aggregate in self._text_aggregator.aggregate(frame.text): - text = aggregate.text - aggregated_by = aggregate.type - logger.trace(f"Pushing TTS frames for text: {text}, {aggregated_by}") - await self._push_tts_frames( - AggregatedTextFrame(text, aggregated_by), includes_inter_frame_spaces - ) + async for aggregate in self._text_aggregator.aggregate(frame.text): + includes_inter_frame_spaces = ( + frame.includes_inter_frame_spaces + if aggregate.type == AggregationType.TOKEN + else False + ) + if aggregate.type != AggregationType.TOKEN: + # Stop the aggregation metric on the first sentence only. + await self.stop_text_aggregation_metrics() + await self._push_tts_frames( + AggregatedTextFrame(aggregate.text, aggregate.type), includes_inter_frame_spaces + ) async def _push_tts_frames( self, @@ -739,7 +807,15 @@ class TTSService(AIService): # or when we received an LLMFullResponseEndFrame self._processing_text = True - await self.start_processing_metrics() + # Accumulate text for a single debug log at flush time when streaming tokens. + if self._is_streaming_tokens: + self._streaming_text_log += text + + # Skip per-token processing metrics when streaming. The per-token + # processing time is just websocket send overhead (~0.1ms) and not + # meaningful. TTFB captures the important timing for streaming TTS. + if not self._is_streaming_tokens: + await self.start_processing_metrics() # Process all filters. for filter in self._text_filters: @@ -747,7 +823,8 @@ class TTSService(AIService): text = await filter.filter(text) if not text.strip(): - await self.stop_processing_metrics() + if not self._is_streaming_tokens: + await self.stop_processing_metrics() return # Create context ID and store metadata @@ -785,7 +862,8 @@ class TTSService(AIService): await self.process_generator(self.run_tts(prepared_text, context_id)) - await self.stop_processing_metrics() + if not self._is_streaming_tokens: + await self.stop_processing_metrics() if self._push_text_frames: # In TTS services that support word timestamps, the TTSTextFrames diff --git a/src/pipecat/utils/text/base_text_aggregator.py b/src/pipecat/utils/text/base_text_aggregator.py index 13691d9cd..2b050fcb7 100644 --- a/src/pipecat/utils/text/base_text_aggregator.py +++ b/src/pipecat/utils/text/base_text_aggregator.py @@ -21,6 +21,7 @@ class AggregationType(str, Enum): """Built-in aggregation strings.""" SENTENCE = "sentence" + TOKEN = "token" WORD = "word" def __str__(self): @@ -66,6 +67,25 @@ class BaseTextAggregator(ABC): logic, text manipulation behavior, and state management for interruptions. """ + def __init__(self, *, aggregation_type: AggregationType = AggregationType.SENTENCE): + """Initialize the base text aggregator. + + Args: + aggregation_type: The aggregation strategy to use. SENTENCE buffers + text until sentence boundaries are detected, TOKEN passes text + through immediately, and WORD buffers until word boundaries. + """ + self._aggregation_type = AggregationType(aggregation_type) + + @property + def aggregation_type(self) -> AggregationType: + """Get the aggregation type for this aggregator. + + Returns: + The aggregation type. + """ + return self._aggregation_type + @property @abstractmethod def text(self) -> Aggregation: diff --git a/src/pipecat/utils/text/pattern_pair_aggregator.py b/src/pipecat/utils/text/pattern_pair_aggregator.py index bfaf9291b..835bb8591 100644 --- a/src/pipecat/utils/text/pattern_pair_aggregator.py +++ b/src/pipecat/utils/text/pattern_pair_aggregator.py @@ -96,8 +96,11 @@ class PatternPairAggregator(SimpleTextAggregator): Creates an empty aggregator with no patterns or handlers registered. Text buffering and pattern detection will begin when text is aggregated. + + Args: + **kwargs: Additional arguments passed to SimpleTextAggregator (e.g. aggregation_type). """ - super().__init__() + super().__init__(**kwargs) self._patterns = {} self._handlers = {} self._last_processed_position = 0 # Track where we last checked for complete patterns @@ -146,7 +149,7 @@ class PatternPairAggregator(SimpleTextAggregator): Returns: Self for method chaining. """ - if type in [AggregationType.SENTENCE, AggregationType.WORD]: + if type in [AggregationType.SENTENCE, AggregationType.WORD, AggregationType.TOKEN]: raise ValueError( f"The aggregation type '{type}' is reserved for default behavior and can not be used for custom patterns." ) @@ -321,6 +324,9 @@ class PatternPairAggregator(SimpleTextAggregator): and uses the parent's lookahead logic for sentence detection when no patterns are active. + In TOKEN mode, pattern detection still works but non-pattern text is + yielded as TOKEN aggregations instead of waiting for sentence boundaries. + Args: text: Text to aggregate. @@ -370,18 +376,35 @@ class PatternPairAggregator(SimpleTextAggregator): # boundaries when a pattern begins (e.g., "Here is code ..." yields "Here is code") result = self._text[: pattern_start[0]] self._text = self._text[pattern_start[0] :] - yield PatternMatch( - content=result.strip(), type=AggregationType.SENTENCE, full_match=result + agg_type = ( + AggregationType.TOKEN + if self._aggregation_type == AggregationType.TOKEN + else AggregationType.SENTENCE ) + yield PatternMatch(content=result.strip(), type=agg_type, full_match=result) continue - # Use parent's lookahead logic for sentence detection - aggregation = await super()._check_sentence_with_lookahead(char) - if aggregation: - # Convert to PatternMatch for consistency with return type + if self._aggregation_type != AggregationType.TOKEN: + # Use parent's lookahead logic for sentence detection + aggregation = await super()._check_sentence_with_lookahead(char) + if aggregation: + # Convert to PatternMatch for consistency with return type + yield PatternMatch( + content=aggregation.text, + type=aggregation.type, + full_match=aggregation.text, + ) + + # In TOKEN mode, yield any accumulated text after processing all chars, + # but only if there's no incomplete pattern being buffered. + if self._aggregation_type == AggregationType.TOKEN and self._text: + if self._match_start_of_pattern(self._text) is None: yield PatternMatch( - content=aggregation.text, type=aggregation.type, full_match=aggregation.text + content=self._text, + type=AggregationType.TOKEN, + full_match=self._text, ) + self._text = "" async def handle_interruption(self): """Handle interruptions by clearing the buffer and pattern state. diff --git a/src/pipecat/utils/text/simple_text_aggregator.py b/src/pipecat/utils/text/simple_text_aggregator.py index b0cc698a9..b5b179fcf 100644 --- a/src/pipecat/utils/text/simple_text_aggregator.py +++ b/src/pipecat/utils/text/simple_text_aggregator.py @@ -25,11 +25,15 @@ class SimpleTextAggregator(BaseTextAggregator): most straightforward implementation of text aggregation for TTS processing. """ - def __init__(self): + def __init__(self, **kwargs): """Initialize the simple text aggregator. Creates an empty text buffer ready to begin accumulating text tokens. + + Args: + **kwargs: Additional arguments passed to BaseTextAggregator (e.g. aggregation_type). """ + super().__init__(**kwargs) self._text = "" self._needs_lookahead: bool = False @@ -43,19 +47,25 @@ class SimpleTextAggregator(BaseTextAggregator): return Aggregation(text=self._text.strip(" "), type=AggregationType.SENTENCE) async def aggregate(self, text: str) -> AsyncIterator[Aggregation]: - """Aggregate text and yield completed sentences. + """Aggregate text and yield completed aggregations. - Processes the input text character-by-character. When sentence-ending - punctuation is detected, it waits for non-whitespace lookahead before - calling NLTK. This prevents false positives like "$29." being detected - as a sentence when it's actually "$29.95". + In SENTENCE mode, processes the input text character-by-character. When + sentence-ending punctuation is detected, it waits for non-whitespace + lookahead before calling NLTK. + + In TOKEN mode, yields the text immediately without buffering. Args: text: Text to aggregate. Yields: - Complete sentences as Aggregation objects. + Aggregation objects (sentences in SENTENCE mode, tokens in TOKEN mode). """ + if self._aggregation_type == AggregationType.TOKEN: + if text: + yield Aggregation(text=text, type=AggregationType.TOKEN) + return + # Process text character by character for char in text: self._text += char @@ -114,11 +124,15 @@ class SimpleTextAggregator(BaseTextAggregator): """Flush any remaining text in the buffer. Returns any text remaining in the buffer. This is called at the end - of a stream to ensure all text is processed. + of a stream to ensure all text is processed. In TOKEN mode, returns + None since tokens are yielded immediately. Returns: - Any remaining text as a sentence, or None if buffer is empty. + Any remaining text as a sentence, or None if buffer is empty or in TOKEN mode. """ + if self._aggregation_type == AggregationType.TOKEN: + return None + if self._text: # Return whatever we have in the buffer result = self._text diff --git a/src/pipecat/utils/text/skip_tags_aggregator.py b/src/pipecat/utils/text/skip_tags_aggregator.py index 4232efd7d..1b6a7f156 100644 --- a/src/pipecat/utils/text/skip_tags_aggregator.py +++ b/src/pipecat/utils/text/skip_tags_aggregator.py @@ -14,7 +14,7 @@ as a unit regardless of internal punctuation. from typing import AsyncIterator, Optional, Sequence from pipecat.utils.string import StartEndTags, parse_start_end_tags -from pipecat.utils.text.base_text_aggregator import Aggregation +from pipecat.utils.text.base_text_aggregator import Aggregation, AggregationType from pipecat.utils.text.simple_text_aggregator import SimpleTextAggregator @@ -31,14 +31,15 @@ class SkipTagsAggregator(SimpleTextAggregator): identified and that content within tags is never split at sentence boundaries. """ - def __init__(self, tags: Sequence[StartEndTags]): + def __init__(self, tags: Sequence[StartEndTags], **kwargs): """Initialize the skip tags aggregator. Args: tags: Sequence of StartEndTags objects defining the tag pairs that should prevent sentence boundary detection. + **kwargs: Additional arguments passed to SimpleTextAggregator (e.g. aggregation_type). """ - super().__init__() + super().__init__(**kwargs) self._tags = tags self._current_tag: Optional[StartEndTags] = None self._current_tag_index: int = 0 @@ -50,13 +51,33 @@ class SkipTagsAggregator(SimpleTextAggregator): uses the parent's lookahead logic for sentence detection when not inside tags. + In TOKEN mode, text is passed through immediately unless we're inside + a tag, in which case we buffer until the closing tag is found. + Args: text: Text to aggregate. Yields: Aggregation objects containing text up to a sentence boundary, - marked as SENTENCE type. + marked as SENTENCE type (or TOKEN type in TOKEN mode). """ + if self._aggregation_type == AggregationType.TOKEN: + # In TOKEN mode, process chars for tag tracking but yield the + # full input as a single token when not inside a tag. + for char in text: + self._text += char + + # Update tag state + (self._current_tag, self._current_tag_index) = parse_start_end_tags( + self._text, self._tags, self._current_tag, self._current_tag_index + ) + + # After processing all chars: if not inside a tag, yield accumulated text + if not self._current_tag and self._text: + yield Aggregation(text=self._text, type=AggregationType.TOKEN) + self._text = "" + return + # Process text character by character for char in text: self._text += char diff --git a/tests/test_pattern_pair_aggregator.py b/tests/test_pattern_pair_aggregator.py index bcc8d18f7..6c9e23552 100644 --- a/tests/test_pattern_pair_aggregator.py +++ b/tests/test_pattern_pair_aggregator.py @@ -194,5 +194,66 @@ class TestPatternPairAggregator(unittest.IsolatedAsyncioTestCase): self.assertEqual(self.aggregator.text.text, "") +class TestPatternPairAggregatorTokenMode(unittest.IsolatedAsyncioTestCase): + def setUp(self): + from pipecat.utils.text.base_text_aggregator import AggregationType + + self.aggregator = PatternPairAggregator(aggregation_type=AggregationType.TOKEN) + self.handler = AsyncMock() + self.aggregator.add_pattern( + type="think", + start_pattern="", + end_pattern="", + action=MatchAction.REMOVE, + ) + self.aggregator.on_pattern_match("think", self.handler) + + async def test_token_no_patterns(self): + """Non-pattern text passes through as TOKEN, one per aggregate call.""" + results = [] + for token in ["Hello", " world", "."]: + async for r in self.aggregator.aggregate(token): + results.append(r) + + self.assertEqual(len(results), 3) + self.assertEqual(results[0].text, "Hello") + self.assertEqual(results[1].text, " world") + self.assertEqual(results[2].text, ".") + for r in results: + self.assertEqual(r.type, "token") + + async def test_token_pattern_detection(self): + """Pattern detection still works with word-by-word token delivery.""" + results = [] + for token in ["Hi ", "", "secret", "", " bye"]: + async for r in self.aggregator.aggregate(token): + results.append(r) + + # Handler called once when the pattern completes + self.handler.assert_called_once() + call_args = self.handler.call_args[0][0] + self.assertEqual(call_args.text, "secret") + + # "Hi " yields before pattern starts, pattern is removed, " bye" yields after + self.assertEqual(len(results), 2) + self.assertEqual(results[0].text, "Hi ") + self.assertEqual(results[0].type, "token") + self.assertEqual(results[1].text, " bye") + self.assertEqual(results[1].type, "token") + + async def test_token_incomplete_pattern_buffers(self): + """Incomplete pattern is buffered across calls, not leaked to output.""" + results = [] + for token in ["Hi ", "", "partial"]: + async for r in self.aggregator.aggregate(token): + results.append(r) + + # Only "Hi " should be yielded; "partial" stays buffered + self.assertEqual(len(results), 1) + self.assertEqual(results[0].text, "Hi ") + self.assertEqual(results[0].type, "token") + self.handler.assert_not_called() + + if __name__ == "__main__": unittest.main() diff --git a/tests/test_simple_text_aggregator.py b/tests/test_simple_text_aggregator.py index 4b3613e27..46c77df42 100644 --- a/tests/test_simple_text_aggregator.py +++ b/tests/test_simple_text_aggregator.py @@ -181,5 +181,39 @@ class TestSimpleTextAggregator(unittest.IsolatedAsyncioTestCase): assert result.text == "こんにちは。" +class TestSimpleTextAggregatorTokenMode(unittest.IsolatedAsyncioTestCase): + def setUp(self): + from pipecat.utils.text.base_text_aggregator import AggregationType + + self.aggregator = SimpleTextAggregator(aggregation_type=AggregationType.TOKEN) + + async def test_token_passthrough(self): + """TOKEN mode yields text immediately without buffering.""" + results = [agg async for agg in self.aggregator.aggregate("Hello")] + assert len(results) == 1 + assert results[0].text == "Hello" + assert results[0].type == "token" + + async def test_token_multiple_calls(self): + """Each aggregate call yields its text independently.""" + r1 = [agg async for agg in self.aggregator.aggregate("Hello ")] + r2 = [agg async for agg in self.aggregator.aggregate("world.")] + assert len(r1) == 1 + assert r1[0].text == "Hello " + assert len(r2) == 1 + assert r2[0].text == "world." + + async def test_token_empty_text(self): + """Empty text yields nothing.""" + results = [agg async for agg in self.aggregator.aggregate("")] + assert len(results) == 0 + + async def test_token_flush_returns_none(self): + """Flush returns None in TOKEN mode since nothing is buffered.""" + await self.aggregator.aggregate("Hello").__anext__() + result = await self.aggregator.flush() + assert result is None + + if __name__ == "__main__": unittest.main() diff --git a/tests/test_skip_tags_aggregator.py b/tests/test_skip_tags_aggregator.py index c7fea22c3..882b26e82 100644 --- a/tests/test_skip_tags_aggregator.py +++ b/tests/test_skip_tags_aggregator.py @@ -64,5 +64,60 @@ class TestSkipTagsAggregator(unittest.IsolatedAsyncioTestCase): self.assertEqual(self.aggregator.text.type, "sentence") +class TestSkipTagsAggregatorTokenMode(unittest.IsolatedAsyncioTestCase): + def setUp(self): + from pipecat.utils.text.base_text_aggregator import AggregationType + + self.aggregator = SkipTagsAggregator( + [("", "")], aggregation_type=AggregationType.TOKEN + ) + + async def test_token_no_tags(self): + """No tags: text passes through immediately as TOKEN.""" + results = [agg async for agg in self.aggregator.aggregate("Hello!")] + self.assertEqual(len(results), 1) + self.assertEqual(results[0].text, "Hello!") + self.assertEqual(results[0].type, "token") + + async def test_token_inside_tag_buffers(self): + """Inside a tag, text is buffered until the closing tag is found.""" + results = [agg async for agg in self.aggregator.aggregate("foo@bar")] + # Still inside tag, nothing yielded + self.assertEqual(len(results), 0) + + # Close the tag + results = [agg async for agg in self.aggregator.aggregate("")] + self.assertEqual(len(results), 1) + self.assertEqual(results[0].text, "foo@bar") + self.assertEqual(results[0].type, "token") + + async def test_token_flush_unclosed_tag(self): + """Flush with unclosed tag returns remaining text.""" + async for _ in self.aggregator.aggregate("unclosed"): + pass + result = await self.aggregator.flush() + # TOKEN mode flush returns None (parent behavior) + self.assertIsNone(result) + + async def test_token_text_around_tags(self): + """Simulate word-by-word token delivery with tags.""" + results = [] + # Simulate LLM streaming tokens one at a time + for token in ["Hi ", "", "X", "", " bye"]: + async for agg in self.aggregator.aggregate(token): + results.append(agg) + + self.assertEqual(len(results), 3) + # Text before tag passes through immediately + self.assertEqual(results[0].text, "Hi ") + self.assertEqual(results[0].type, "token") + # Tagged content is buffered until the closing tag, then yielded whole + self.assertEqual(results[1].text, "X") + self.assertEqual(results[1].type, "token") + # Text after tag passes through immediately + self.assertEqual(results[2].text, " bye") + self.assertEqual(results[2].type, "token") + + if __name__ == "__main__": unittest.main() From 3c20eda8bf95a8590d907ba72603a2c319fad473 Mon Sep 17 00:00:00 2001 From: Paul Kompfner Date: Thu, 26 Feb 2026 09:32:52 -0500 Subject: [PATCH 0651/1060] Keep model/language in LiveOptions at construction time so apply_update's bidirectional sync is sufficient; simplify _build_live_options to only add sample_rate --- src/pipecat/services/deepgram/stt.py | 11 +++-------- src/pipecat/services/deepgram/stt_sagemaker.py | 11 +++-------- 2 files changed, 6 insertions(+), 16 deletions(-) diff --git a/src/pipecat/services/deepgram/stt.py b/src/pipecat/services/deepgram/stt.py index f1c2fd19c..b193f899d 100644 --- a/src/pipecat/services/deepgram/stt.py +++ b/src/pipecat/services/deepgram/stt.py @@ -262,10 +262,9 @@ class DeepgramSTTService(STTService): if "language" in merged_dict and isinstance(merged_dict["language"], Language): merged_dict["language"] = merged_dict["language"].value - # Extract model/language for top-level STTSettings fields; everything - # else lives inside LiveOptions. - model = merged_dict.pop("model", None) - language = merged_dict.pop("language", None) + # Sync model/language to top-level STTSettings fields + model = merged_dict.get("model") + language = merged_dict.get("language") settings = DeepgramSTTSettings( model=model, language=language, live_options=LiveOptions(**merged_dict) @@ -380,10 +379,6 @@ class DeepgramSTTService(STTService): A fully-populated ``LiveOptions`` ready for the Deepgram SDK. """ opts: dict[str, Any] = self._settings.live_options.to_dict() - - # Overlay model/language from top-level settings and sample_rate from service. - opts["model"] = self._settings.model - opts["language"] = self._settings.language opts["sample_rate"] = self.sample_rate return LiveOptions(**opts) diff --git a/src/pipecat/services/deepgram/stt_sagemaker.py b/src/pipecat/services/deepgram/stt_sagemaker.py index 12357a8cd..6f91906b7 100644 --- a/src/pipecat/services/deepgram/stt_sagemaker.py +++ b/src/pipecat/services/deepgram/stt_sagemaker.py @@ -247,10 +247,9 @@ class DeepgramSageMakerSTTService(STTService): if "language" in merged_dict and isinstance(merged_dict["language"], Language): merged_dict["language"] = merged_dict["language"].value - # Extract model/language for top-level STTSettings fields; everything - # else lives inside LiveOptions. - model = merged_dict.pop("model", None) - language = merged_dict.pop("language", None) + # Sync model/language to top-level STTSettings fields + model = merged_dict.get("model") + language = merged_dict.get("language") settings = DeepgramSageMakerSTTSettings( model=model, language=language, live_options=LiveOptions(**merged_dict) @@ -344,10 +343,6 @@ class DeepgramSageMakerSTTService(STTService): A fully-populated ``LiveOptions`` ready for the Deepgram SDK. """ opts: dict[str, Any] = self._settings.live_options.to_dict() - - # Overlay model/language from top-level settings and sample_rate from service. - opts["model"] = self._settings.model - opts["language"] = self._settings.language opts["sample_rate"] = self.sample_rate return LiveOptions(**opts) From c184ac09b8323571a4269182e3f9af9fe6d70c1b Mon Sep 17 00:00:00 2001 From: Paul Kompfner Date: Thu, 26 Feb 2026 09:42:15 -0500 Subject: [PATCH 0652/1060] Inline `_build_live_options` into `_connect` in `DeepgramSTTService` and `DeepgramSageMakerSTTService` since it's trivial and only called from one place --- src/pipecat/services/deepgram/stt.py | 19 +++++-------------- .../services/deepgram/stt_sagemaker.py | 17 +++++------------ 2 files changed, 10 insertions(+), 26 deletions(-) diff --git a/src/pipecat/services/deepgram/stt.py b/src/pipecat/services/deepgram/stt.py index b193f899d..59107d0f8 100644 --- a/src/pipecat/services/deepgram/stt.py +++ b/src/pipecat/services/deepgram/stt.py @@ -372,17 +372,6 @@ class DeepgramSTTService(STTService): await self._connection.send(audio) yield None - def _build_live_options(self) -> LiveOptions: - """Build a ``LiveOptions`` from stored settings and sample rate. - - Returns: - A fully-populated ``LiveOptions`` ready for the Deepgram SDK. - """ - opts: dict[str, Any] = self._settings.live_options.to_dict() - opts["sample_rate"] = self.sample_rate - - return LiveOptions(**opts) - async def _connect(self): logger.debug("Connecting to Deepgram") @@ -403,9 +392,11 @@ class DeepgramSTTService(STTService): self._on_utterance_end, ) - if not await self._connection.start( - options=self._build_live_options(), addons=self._addons - ): + live_options = LiveOptions( + **{**self._settings.live_options.to_dict(), "sample_rate": self.sample_rate} + ) + + if not await self._connection.start(options=live_options, addons=self._addons): await self.push_error(error_msg=f"Unable to connect to Deepgram") else: headers = { diff --git a/src/pipecat/services/deepgram/stt_sagemaker.py b/src/pipecat/services/deepgram/stt_sagemaker.py index 6f91906b7..ee2121bec 100644 --- a/src/pipecat/services/deepgram/stt_sagemaker.py +++ b/src/pipecat/services/deepgram/stt_sagemaker.py @@ -336,17 +336,6 @@ class DeepgramSageMakerSTTService(STTService): yield ErrorFrame(error=f"Unknown error occurred: {e}") yield None - def _build_live_options(self) -> LiveOptions: - """Build a ``LiveOptions`` from stored settings and sample rate. - - Returns: - A fully-populated ``LiveOptions`` ready for the Deepgram SDK. - """ - opts: dict[str, Any] = self._settings.live_options.to_dict() - opts["sample_rate"] = self.sample_rate - - return LiveOptions(**opts) - async def _connect(self): """Connect to the SageMaker endpoint and start the BiDi session. @@ -356,9 +345,13 @@ class DeepgramSageMakerSTTService(STTService): """ logger.debug("Connecting to Deepgram on SageMaker...") + live_options = LiveOptions( + **{**self._settings.live_options.to_dict(), "sample_rate": self.sample_rate} + ) + # Build query string from live_options, converting booleans to strings query_params = {} - for key, value in self._build_live_options().to_dict().items(): + for key, value in live_options.to_dict().items(): if value is not None: # Convert boolean values to lowercase strings for Deepgram API if isinstance(value, bool): From 3ae173520ee739c6a3e3948b7a16fedbab1d11be Mon Sep 17 00:00:00 2001 From: Mark Backman Date: Thu, 26 Feb 2026 08:59:38 -0500 Subject: [PATCH 0653/1060] Code review feedback --- examples/foundational/07-interruptible.py | 4 +- src/pipecat/processors/frame_processor.py | 1 + .../metrics/frame_processor_metrics.py | 6 +- src/pipecat/services/cartesia/tts.py | 12 ++-- src/pipecat/services/elevenlabs/tts.py | 7 ++- src/pipecat/services/tts_service.py | 57 +++++++++++++------ 6 files changed, 57 insertions(+), 30 deletions(-) diff --git a/examples/foundational/07-interruptible.py b/examples/foundational/07-interruptible.py index e47d2c811..074e091ea 100644 --- a/examples/foundational/07-interruptible.py +++ b/examples/foundational/07-interruptible.py @@ -57,7 +57,9 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): tts = CartesiaTTSService( api_key=os.getenv("CARTESIA_API_KEY"), voice_id="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady - text_aggregation_mode=TextAggregationMode.TOKEN, + # Alternatively, you can use TextAggregationMode.TOKEN to stream tokens instead of + # sentencesfor faster response times. + # text_aggregation_mode=TextAggregationMode.TOKEN, ) llm = OpenAILLMService(api_key=os.getenv("OPENAI_API_KEY")) diff --git a/src/pipecat/processors/frame_processor.py b/src/pipecat/processors/frame_processor.py index 37e8dc10d..baa52cc70 100644 --- a/src/pipecat/processors/frame_processor.py +++ b/src/pipecat/processors/frame_processor.py @@ -501,6 +501,7 @@ class FrameProcessor(BaseObject): """Stop all active metrics collection.""" await self.stop_ttfb_metrics() await self.stop_processing_metrics() + await self.stop_text_aggregation_metrics() def create_task(self, coroutine: Coroutine, name: Optional[str] = None) -> asyncio.Task: """Create a new task managed by this processor. diff --git a/src/pipecat/processors/metrics/frame_processor_metrics.py b/src/pipecat/processors/metrics/frame_processor_metrics.py index cb5bc8a42..7a52895a2 100644 --- a/src/pipecat/processors/metrics/frame_processor_metrics.py +++ b/src/pipecat/processors/metrics/frame_processor_metrics.py @@ -44,6 +44,7 @@ class FrameProcessorMetrics(BaseObject): self._task_manager = None self._start_ttfb_time = 0 self._start_processing_time = 0 + self._start_text_aggregation_time = 0 self._last_ttfb_time = 0 self._should_report_ttfb = True @@ -223,10 +224,7 @@ class FrameProcessorMetrics(BaseObject): Returns: MetricsFrame containing text aggregation time, or None if not measuring. """ - if ( - not hasattr(self, "_start_text_aggregation_time") - or self._start_text_aggregation_time == 0 - ): + if self._start_text_aggregation_time == 0: return None value = time.time() - self._start_text_aggregation_time diff --git a/src/pipecat/services/cartesia/tts.py b/src/pipecat/services/cartesia/tts.py index 0749af062..2e637c339 100644 --- a/src/pipecat/services/cartesia/tts.py +++ b/src/pipecat/services/cartesia/tts.py @@ -303,9 +303,11 @@ class CartesiaTTSService(AudioContextTTSService): """ # By default, we aggregate sentences before sending to TTS. This adds # ~200-300ms of latency per sentence (waiting for the sentence-ending - # punctuation token from the LLM). Setting aggregate_sentences=False - # streams tokens directly, which reduces latency. Streaming quality - # is good but less tested than sentence aggregation. + # punctuation token from the LLM). Setting + # text_aggregation_mode=TextAggregationMode.TOKEN streams tokens + # directly, which reduces latency. Streaming quality is good but less + # tested than sentence aggregation. + # TODO: Consider making TOKEN the default for Cartesia in 1.0. # # We also don't want to automatically push LLM response text frames, # because the context aggregators will add them to the LLM context even @@ -667,9 +669,7 @@ class CartesiaTTSService(AudioContextTTSService): try: await self._get_websocket().send(msg) - # Usage metrics are aggregated at flush time when streaming tokens. - if not self._is_streaming_tokens: - await self.start_tts_usage_metrics(text) + await self.start_tts_usage_metrics(text) except Exception as e: yield ErrorFrame(error=f"Unknown error occurred: {e}") yield TTSStoppedFrame(context_id=context_id) diff --git a/src/pipecat/services/elevenlabs/tts.py b/src/pipecat/services/elevenlabs/tts.py index dcfdebc2f..1811ed971 100644 --- a/src/pipecat/services/elevenlabs/tts.py +++ b/src/pipecat/services/elevenlabs/tts.py @@ -389,9 +389,10 @@ class ElevenLabsTTSService(AudioContextTTSService): """ # By default, we aggregate sentences before sending to TTS. This adds # ~200-300ms of latency per sentence (waiting for the sentence-ending - # punctuation token from the LLM). Setting aggregate_sentences=False - # streams tokens directly. To use this mode, you must set auto_mode=False. - # This eliminates aggregation time, but slows down ElevenLabs. + # punctuation token from the LLM). Setting + # text_aggregation_mode=TextAggregationMode.TOKEN streams tokens + # directly. To use this mode, you must set auto_mode=False. This + # eliminates aggregation time, but slows down ElevenLabs. # # We also don't want to automatically push LLM response text frames, # because the context aggregators will add them to the LLM context even diff --git a/src/pipecat/services/tts_service.py b/src/pipecat/services/tts_service.py index 8c61f225d..c6d2672d6 100644 --- a/src/pipecat/services/tts_service.py +++ b/src/pipecat/services/tts_service.py @@ -247,8 +247,6 @@ class TTSService(AIService): text_aggregation_mode = TextAggregationMode.SENTENCE self._text_aggregation_mode: TextAggregationMode = text_aggregation_mode - # Keep for backward compat with subclasses that read self._aggregate_sentences - self._aggregate_sentences: bool = text_aggregation_mode != TextAggregationMode.TOKEN self._push_text_frames: bool = push_text_frames self._push_stop_frames: bool = push_stop_frames self._stop_frame_timeout_s: float = stop_frame_timeout_s @@ -296,8 +294,8 @@ class TTSService(AIService): self._processing_text: bool = False self._tts_contexts: Dict[str, TTSContext] = {} - self._streaming_text_log: str = "" - self._aggregation_logged: bool = False + self._streamed_text: str = "" + self._text_aggregation_metrics_started: bool = False # Word timestamp state (active when supports_word_timestamps=True) self._supports_word_timestamps: bool = supports_word_timestamps @@ -316,6 +314,35 @@ class TTSService(AIService): """Whether the service is streaming tokens directly without sentence aggregation.""" return self._text_aggregation_mode == TextAggregationMode.TOKEN + async def start_tts_usage_metrics(self, text: str): + """Record TTS usage metrics. + + When streaming tokens, usage metrics are aggregated and reported at + flush time instead of per token, so individual calls are skipped. + + Args: + text: The text being processed by TTS. + """ + if self._is_streaming_tokens: + return + await super().start_tts_usage_metrics(text) + + async def start_text_aggregation_metrics(self): + """Start text aggregation metrics if not already started. + + Only starts the metric once per LLM response. Skipped when streaming + tokens since per-token aggregation time is not meaningful. + """ + if self._is_streaming_tokens or self._text_aggregation_metrics_started: + return + self._text_aggregation_metrics_started = True + await super().start_text_aggregation_metrics() + + async def stop_text_aggregation_metrics(self): + """Stop text aggregation metrics and reset the started flag.""" + self._text_aggregation_metrics_started = False + await super().stop_text_aggregation_metrics() + @property def sample_rate(self) -> int: """Get the current sample rate for audio output. @@ -574,9 +601,7 @@ class TTSService(AIService): and not isinstance(frame, InterimTranscriptionFrame) and not isinstance(frame, TranscriptionFrame) ): - if not self._is_streaming_tokens and not self._aggregation_logged: - await self.start_text_aggregation_metrics() - self._aggregation_logged = True + await self.start_text_aggregation_metrics() await self._process_text_frame(frame) elif isinstance(frame, InterruptionFrame): await self._handle_interruption(frame, direction) @@ -592,18 +617,16 @@ class TTSService(AIService): # Flush any remaining text (including text waiting for lookahead) remaining = await self._text_aggregator.flush() + # Stop the aggregation metric (no-op if already stopped on first sentence). + await self.stop_text_aggregation_metrics() if remaining: - # If this is the first (and only) sentence, stop the aggregation metric. - await self.stop_text_aggregation_metrics() await self._push_tts_frames(AggregatedTextFrame(remaining.text, remaining.type)) - self._aggregation_logged = False - # Log accumulated streamed text and emit aggregated usage metric. - if self._streaming_text_log: - logger.debug(f"{self}: Generating TTS [{self._streaming_text_log}]") - await self.start_tts_usage_metrics(self._streaming_text_log) - self._streaming_text_log = "" + if self._streamed_text: + logger.debug(f"{self}: Generating TTS [{self._streamed_text}]") + await super().start_tts_usage_metrics(self._streamed_text) + self._streamed_text = "" # Reset aggregator state self._processing_text = False @@ -754,6 +777,8 @@ class TTSService(AIService): await filter.handle_interruption() self._llm_response_started = False + self._streamed_text = "" + self._text_aggregation_metrics_started = False if self._supports_word_timestamps: await self.reset_word_timestamps() @@ -809,7 +834,7 @@ class TTSService(AIService): # Accumulate text for a single debug log at flush time when streaming tokens. if self._is_streaming_tokens: - self._streaming_text_log += text + self._streamed_text += text # Skip per-token processing metrics when streaming. The per-token # processing time is just websocket send overhead (~0.1ms) and not From 907ff58d41ce77da6b6b9270fc2969f1d6106edb Mon Sep 17 00:00:00 2001 From: Mark Backman Date: Mon, 23 Feb 2026 17:11:08 -0500 Subject: [PATCH 0654/1060] Align Ultravox Realtime service with OpenAI/Gemini patterns - Add InterruptionFrame handling with stop_all_metrics() - Add processing metrics (start/stop) at response boundaries - Fix agent transcript handling for voice and text modalities: - Voice mode: push LLMTextFrame (append_to_context=False) and TTSTextFrame for deltas, skip duplicated final text - Text mode: push LLMTextFrame with proper response lifecycle, no TTSTextFrame (downstream TTS handles audio) - Add output_medium parameter to AgentInputParams and OneShotInputParams - Improve TTFB measurement using VAD speech end time - Update example with user turn strategies and transcript events - Add text-only output example (50a-ultravox-realtime-text.py) --- changelog/3806.added.md | 1 + changelog/3806.changed.2.md | 1 + changelog/3806.changed.md | 1 + examples/foundational/50-ultravox-realtime.py | 42 ++- .../50a-ultravox-realtime-text.py | 263 ++++++++++++++++++ src/pipecat/services/ultravox/llm.py | 102 +++++-- 6 files changed, 384 insertions(+), 26 deletions(-) create mode 100644 changelog/3806.added.md create mode 100644 changelog/3806.changed.2.md create mode 100644 changelog/3806.changed.md create mode 100644 examples/foundational/50a-ultravox-realtime-text.py diff --git a/changelog/3806.added.md b/changelog/3806.added.md new file mode 100644 index 000000000..eeddc9825 --- /dev/null +++ b/changelog/3806.added.md @@ -0,0 +1 @@ +- Added `output_medium` parameter to `AgentInputParams` and `OneShotInputParams` in Ultravox service to control initial output medium (text or voice) at call creation time. diff --git a/changelog/3806.changed.2.md b/changelog/3806.changed.2.md new file mode 100644 index 000000000..9d6dfdf76 --- /dev/null +++ b/changelog/3806.changed.2.md @@ -0,0 +1 @@ +- Improved Ultravox TTFB measurement accuracy by using VAD speech end time instead of `UserStoppedSpeakingFrame` timing. diff --git a/changelog/3806.changed.md b/changelog/3806.changed.md new file mode 100644 index 000000000..c8e2fb68c --- /dev/null +++ b/changelog/3806.changed.md @@ -0,0 +1 @@ +- Aligned `UltravoxRealtimeLLMService` frame handling with OpenAI/Gemini realtime services: added `InterruptionFrame` handling with metrics cleanup, processing metrics at response boundaries, and improved agent transcript handling for both voice and text output modalities. diff --git a/examples/foundational/50-ultravox-realtime.py b/examples/foundational/50-ultravox-realtime.py index 5038cbb4c..0908c518c 100644 --- a/examples/foundational/50-ultravox-realtime.py +++ b/examples/foundational/50-ultravox-realtime.py @@ -12,11 +12,18 @@ from loguru import logger from pipecat.adapters.schemas.function_schema import FunctionSchema from pipecat.adapters.schemas.tools_schema import ToolsSchema +from pipecat.audio.vad.silero import SileroVADAnalyzer +from pipecat.audio.vad.vad_analyzer import VADParams from pipecat.pipeline.pipeline import Pipeline from pipecat.pipeline.runner import PipelineRunner from pipecat.pipeline.task import PipelineParams, PipelineTask from pipecat.processors.aggregators.llm_context import LLMContext -from pipecat.processors.aggregators.llm_response_universal import LLMContextAggregatorPair +from pipecat.processors.aggregators.llm_response_universal import ( + AssistantTurnStoppedMessage, + LLMContextAggregatorPair, + LLMUserAggregatorParams, + UserTurnStoppedMessage, +) from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport from pipecat.services.llm_service import FunctionCallParams @@ -24,6 +31,8 @@ from pipecat.services.ultravox.llm import OneShotInputParams, UltravoxRealtimeLL from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams +from pipecat.turns.user_stop import SpeechTimeoutUserTurnStopStrategy +from pipecat.turns.user_turn_strategies import UserTurnStrategies # Load environment variables load_dotenv(override=True) @@ -168,8 +177,21 @@ There is also a secret menu that changes daily. If the user asks about it, use t llm.register_function("get_secret_menu", get_secret_menu) - # Necessary to complete the function call lifecycle in Pipecat. - user_aggregator, assistant_aggregator = LLMContextAggregatorPair(LLMContext([])) + context = LLMContext([]) + + # Necessary to complete the function call lifecycle in Pipecat and + # to produce user and assistant turn stopped events. + user_aggregator, assistant_aggregator = LLMContextAggregatorPair( + context, + user_params=LLMUserAggregatorParams( + user_turn_strategies=UserTurnStrategies( + stop=[SpeechTimeoutUserTurnStopStrategy()], + ), + # Set the VAD analyzer to create reliable TTFB measurements and + # user stop events. + vad_analyzer=SileroVADAnalyzer(), + ), + ) # Build the pipeline pipeline = Pipeline( @@ -177,8 +199,8 @@ There is also a secret menu that changes daily. If the user asks about it, use t transport.input(), user_aggregator, llm, - assistant_aggregator, transport.output(), + assistant_aggregator, ] ) @@ -203,6 +225,18 @@ There is also a secret menu that changes daily. If the user asks about it, use t logger.info(f"Client disconnected") await task.cancel() + @user_aggregator.event_handler("on_user_turn_stopped") + async def on_user_turn_stopped(aggregator, strategy, message: UserTurnStoppedMessage): + timestamp = f"[{message.timestamp}] " if message.timestamp else "" + line = f"{timestamp}user: {message.content}" + logger.info(f"Transcript: {line}") + + @assistant_aggregator.event_handler("on_assistant_turn_stopped") + async def on_assistant_turn_stopped(aggregator, message: AssistantTurnStoppedMessage): + timestamp = f"[{message.timestamp}] " if message.timestamp else "" + line = f"{timestamp}assistant: {message.content}" + logger.info(f"Transcript: {line}") + # Run the pipeline runner = PipelineRunner(handle_sigint=runner_args.handle_sigint) await runner.run(task) diff --git a/examples/foundational/50a-ultravox-realtime-text.py b/examples/foundational/50a-ultravox-realtime-text.py new file mode 100644 index 000000000..8b876048a --- /dev/null +++ b/examples/foundational/50a-ultravox-realtime-text.py @@ -0,0 +1,263 @@ +# +# Copyright (c) 2024-2026, Daily +# +# SPDX-License-Identifier: BSD 2-Clause License +# + +import datetime +import os + +from dotenv import load_dotenv +from loguru import logger + +from pipecat.adapters.schemas.function_schema import FunctionSchema +from pipecat.adapters.schemas.tools_schema import ToolsSchema +from pipecat.audio.vad.silero import SileroVADAnalyzer +from pipecat.audio.vad.vad_analyzer import VADParams +from pipecat.pipeline.pipeline import Pipeline +from pipecat.pipeline.runner import PipelineRunner +from pipecat.pipeline.task import PipelineParams, PipelineTask +from pipecat.processors.aggregators.llm_context import LLMContext +from pipecat.processors.aggregators.llm_response_universal import ( + AssistantTurnStoppedMessage, + LLMContextAggregatorPair, + LLMUserAggregatorParams, + UserTurnStoppedMessage, +) +from pipecat.runner.types import RunnerArguments +from pipecat.runner.utils import create_transport +from pipecat.services.inworld.tts import InworldTTSService +from pipecat.services.llm_service import FunctionCallParams +from pipecat.services.ultravox.llm import OneShotInputParams, UltravoxRealtimeLLMService +from pipecat.transports.base_transport import BaseTransport, TransportParams +from pipecat.transports.daily.transport import DailyParams +from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams +from pipecat.turns.user_stop import SpeechTimeoutUserTurnStopStrategy +from pipecat.turns.user_turn_strategies import UserTurnStrategies + +# Load environment variables +load_dotenv(override=True) + + +# We use lambdas to defer transport parameter creation until the transport +# type is selected at runtime. +transport_params = { + "daily": lambda: DailyParams( + audio_in_enabled=True, + audio_out_enabled=True, + ), + "twilio": lambda: FastAPIWebsocketParams( + audio_in_enabled=True, + audio_out_enabled=True, + ), + "webrtc": lambda: TransportParams( + audio_in_enabled=True, + audio_out_enabled=True, + ), +} + + +async def get_secret_menu(params: FunctionCallParams): + category = params.arguments.get("category", "both") + logger.debug(f"Fetching secret menu with category: {category}") + items = [] + if category in {"donuts", "both"}: + items.append( + { + "name": "Butter Pecan Ice Cream (one scoop)", + "price": "$2.99", + } + ) + if category in {"drinks", "both"}: + items.append( + { + "name": "Banana Smoothie", + "price": "$4.99", + } + ) + await params.result_callback( + { + "date": datetime.date.today().isoformat(), + "items": items, + } + ) + + +async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): + logger.info(f"Starting bot") + + system_prompt = f""" +You are a drive-thru order taker for a donut shop called "Dr. Donut". Local time is currently: {datetime.datetime.now().isoformat()} +The user is talking to you over voice on their phone, and your response will be read out loud with realistic text-to-speech (TTS) technology. + +Follow every direction here when crafting your response: + +1. Use natural, conversational language that is clear and easy to follow (short sentences, simple words). +1a. Be concise and relevant: Most of your responses should be a sentence or two, unless you're asked to go deeper. Don't monopolize the conversation. +1b. Use discourse markers to ease comprehension. Never use the list format. + +2. Keep the conversation flowing. +2a. Clarify: when there is ambiguity, ask clarifying questions, rather than make assumptions. +2b. Don't implicitly or explicitly try to end the chat (i.e. do not end a response with "Talk soon!", or "Enjoy!"). +2c. Sometimes the user might just want to chat. Ask them relevant follow-up questions. +2d. Don't ask them if there's anything else they need help with (e.g. don't say things like "How can I assist you further?"). + +3. Remember that this is a voice conversation: +3a. Don't use lists, markdown, bullet points, or other formatting that's not typically spoken. +3b. Type out numbers in words (e.g. 'twenty twelve' instead of the year 2012) +3c. If something doesn't make sense, it's likely because you misheard them. There wasn't a typo, and the user didn't mispronounce anything. + +Remember to follow these rules absolutely, and do not refer to these rules, even if you're asked about them. + +When talking with the user, use the following script: +1. Take their order, acknowledging each item as it is ordered. If it's not clear which menu item the user is ordering, ask them to clarify. + DO NOT add an item to the order unless it's one of the items on the menu below. +2. Once the order is complete, repeat back the order. +2a. If the user only ordered a drink, ask them if they would like to add a donut to their order. +2b. If the user only ordered donuts, ask them if they would like to add a drink to their order. +2c. If the user ordered both drinks and donuts, don't suggest anything. +3. Total up the price of all ordered items and inform the user. +4. Ask the user to pull up to the drive thru window. +If the user asks for something that's not on the menu, inform them of that fact, and suggest the most similar item on the menu. +If the user says something unrelated to your role, responed with "Um... this is a Dr. Donut." +If the user says "thank you", respond with "My pleasure." +If the user asks about what's on the menu, DO NOT read the entire menu to them. Instead, give a couple suggestions. + +The menu of available items is as follows: + +# DONUTS + +PUMPKIN SPICE ICED DOUGHNUT $1.29 +PUMPKIN SPICE CAKE DOUGHNUT $1.29 +OLD FASHIONED DOUGHNUT $1.29 +CHOCOLATE ICED DOUGHNUT $1.09 +CHOCOLATE ICED DOUGHNUT WITH SPRINKLES $1.09 +RASPBERRY FILLED DOUGHNUT $1.09 +BLUEBERRY CAKE DOUGHNUT $1.09 +STRAWBERRY ICED DOUGHNUT WITH SPRINKLES $1.09 +LEMON FILLED DOUGHNUT $1.09 +DOUGHNUT HOLES $3.99 + +# COFFEE & DRINKS + +PUMPKIN SPICE COFFEE $2.59 +PUMPKIN SPICE LATTE $4.59 +REGULAR BREWED COFFEE $1.79 +DECAF BREWED COFFEE $1.79 +LATTE $3.49 +CAPPUCINO $3.49 +CARAMEL MACCHIATO $3.49 +MOCHA LATTE $3.49 +CARAMEL MOCHA LATTE $3.49 + +There is also a secret menu that changes daily. If the user asks about it, use the get_secret_menu tool to look up today's secret menu items. +""" + + secret_menu_function = FunctionSchema( + name="get_secret_menu", + description="Get today's secret menu items", + properties={ + "category": { + "type": "string", + "enum": ["donuts", "drinks", "both"], + "description": "The category of secret menu items to retrieve. Defaults to both.", + }, + }, + required=[], + ) + + llm = UltravoxRealtimeLLMService( + params=OneShotInputParams( + api_key=os.getenv("ULTRAVOX_API_KEY"), + system_prompt=system_prompt, + temperature=0.3, + max_duration=datetime.timedelta(minutes=3), + output_medium="text", + ), + one_shot_selected_tools=ToolsSchema(standard_tools=[secret_menu_function]), + ) + + llm.register_function("get_secret_menu", get_secret_menu) + + tts = InworldTTSService( + api_key=os.getenv("INWORLD_API_KEY", ""), + voice_id="Ashley", + model="inworld-tts-1", + temperature=1.1, + ) + + context = LLMContext([]) + + # Necessary to complete the function call lifecycle in Pipecat and + # to produce user and assistant turn stopped events. + user_aggregator, assistant_aggregator = LLMContextAggregatorPair( + context, + user_params=LLMUserAggregatorParams( + user_turn_strategies=UserTurnStrategies( + stop=[SpeechTimeoutUserTurnStopStrategy()], + ), + # Set the VAD analyzer to emulate timing of the model. + vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.5)), + ), + ) + + # Build the pipeline + pipeline = Pipeline( + [ + transport.input(), + user_aggregator, + llm, + tts, + transport.output(), + assistant_aggregator, + ] + ) + + # Configure the pipeline task + task = PipelineTask( + pipeline, + params=PipelineParams( + enable_metrics=True, + enable_usage_metrics=True, + ), + idle_timeout_secs=runner_args.pipeline_idle_timeout_secs, + ) + + # Handle client connection event + @transport.event_handler("on_client_connected") + async def on_client_connected(transport, client): + logger.info(f"Client connected") + + # Handle client disconnection events + @transport.event_handler("on_client_disconnected") + async def on_client_disconnected(transport, client): + logger.info(f"Client disconnected") + await task.cancel() + + @user_aggregator.event_handler("on_user_turn_stopped") + async def on_user_turn_stopped(aggregator, strategy, message: UserTurnStoppedMessage): + timestamp = f"[{message.timestamp}] " if message.timestamp else "" + line = f"{timestamp}user: {message.content}" + logger.info(f"Transcript: {line}") + + @assistant_aggregator.event_handler("on_assistant_turn_stopped") + async def on_assistant_turn_stopped(aggregator, message: AssistantTurnStoppedMessage): + timestamp = f"[{message.timestamp}] " if message.timestamp else "" + line = f"{timestamp}assistant: {message.content}" + logger.info(f"Transcript: {line}") + + # Run the pipeline + runner = PipelineRunner(handle_sigint=runner_args.handle_sigint) + await runner.run(task) + + +async def bot(runner_args: RunnerArguments): + """Main bot entry point compatible with Pipecat Cloud.""" + transport = await create_transport(runner_args, transport_params) + await run_bot(transport, runner_args) + + +if __name__ == "__main__": + from pipecat.runner.run import main + + main() diff --git a/src/pipecat/services/ultravox/llm.py b/src/pipecat/services/ultravox/llm.py index d14c3b9ca..07c3c34fe 100644 --- a/src/pipecat/services/ultravox/llm.py +++ b/src/pipecat/services/ultravox/llm.py @@ -31,6 +31,7 @@ from pipecat.frames.frames import ( Frame, InputAudioRawFrame, InputTextRawFrame, + InterruptionFrame, LLMContextFrame, LLMFullResponseEndFrame, LLMFullResponseStartFrame, @@ -42,7 +43,7 @@ from pipecat.frames.frames import ( TTSStoppedFrame, TTSTextFrame, UserAudioRawFrame, - UserStoppedSpeakingFrame, + VADUserStoppedSpeakingFrame, ) from pipecat.processors.aggregators.llm_context import LLMContext from pipecat.processors.aggregators.llm_response import ( @@ -90,6 +91,9 @@ class AgentInputParams(BaseModel): template_context: Context variables to use when instantiating a call with the agent. Defaults to an empty dict. metadata: Metadata to attach to the call. Default to an empty dict. + output_medium: The initial output medium for the agent. Use "text" for text + responses or "voice" for audio responses. Defaults to None, which uses the + agent's default. max_duration: The maximum duration of the call. Defaults to None, which will use the agent's default maximum duration. extra: Extra parameters to include in the agent call creation request. Defaults @@ -101,6 +105,7 @@ class AgentInputParams(BaseModel): agent_id: uuid.UUID template_context: Dict[str, Any] = Field(default_factory=dict) metadata: Dict[str, str] = Field(default_factory=dict) + output_medium: Optional[Literal["text", "voice"]] = None max_duration: Optional[datetime.timedelta] = Field( default=None, ge=datetime.timedelta(seconds=10), le=datetime.timedelta(hours=1) ) @@ -117,6 +122,8 @@ class OneShotInputParams(BaseModel): model: Model identifier to use. Defaults to "fixie-ai/ultravox". voice: Voice identifier for speech generation. Defaults to None. metadata: Metadata to attach to the call. Default to an empty dict. + output_medium: The initial output medium for the agent. Use "text" for text + responses or "voice" for audio responses. Defaults to None (voice). max_duration: The maximum duration of the call. Defaults to one hour. extra: Extra parameters to include in the call creation request. Defaults to an empty dict. See the Ultravox API documentation for valid arguments: @@ -129,6 +136,7 @@ class OneShotInputParams(BaseModel): model: Optional[str] = None voice: Optional[uuid.UUID] = None metadata: Dict[str, str] = Field(default_factory=dict) + output_medium: Optional[Literal["text", "voice"]] = None max_duration: datetime.timedelta = Field( default=datetime.timedelta(hours=1), ge=datetime.timedelta(seconds=10), @@ -210,6 +218,14 @@ class UltravoxRealtimeLLMService(LLMService): self._sample_rate = 48000 self._resampler = create_stream_resampler() + def can_generate_metrics(self) -> bool: + """Check if the service can generate usage metrics. + + Returns: + True if metrics generation is supported. + """ + return True + # # standard AIService frame handling # @@ -237,6 +253,14 @@ class UltravoxRealtimeLLMService(LLMService): except Exception as e: await self.push_error("Failed to connect to Ultravox", e, fatal=True) + @staticmethod + def _output_medium_to_api(medium: Optional[Literal["text", "voice"]]) -> Optional[str]: + if medium == "text": + return "MESSAGE_MEDIUM_TEXT" + elif medium == "voice": + return "MESSAGE_MEDIUM_VOICE" + return None + async def _start_agent_call(self, params: AgentInputParams) -> str: request_body = { "templateContext": params.template_context, @@ -247,6 +271,9 @@ class UltravoxRealtimeLLMService(LLMService): } }, } + initial_output_medium = self._output_medium_to_api(params.output_medium) + if initial_output_medium: + request_body["initialOutputMedium"] = initial_output_medium if params.max_duration: request_body["maxDuration"] = f"{params.max_duration.total_seconds():3f}s" request_body = request_body | params.extra @@ -277,7 +304,11 @@ class UltravoxRealtimeLLMService(LLMService): "inputSampleRate": self._sample_rate, } }, - } | params.extra + } + initial_output_medium = self._output_medium_to_api(params.output_medium) + if initial_output_medium: + request_body["initialOutputMedium"] = initial_output_medium + request_body = request_body | params.extra async with aiohttp.ClientSession() as session: async with session.post( "https://api.ultravox.ai/api/calls", @@ -367,18 +398,17 @@ class UltravoxRealtimeLLMService(LLMService): else LLMContext.from_openai_context(frame.context) ) await self._handle_context(context) + elif isinstance(frame, InterruptionFrame): + await self.stop_all_metrics() + await self.push_frame(frame, direction) elif isinstance(frame, InputTextRawFrame): await self._send_user_text(frame.text) await self.push_frame(frame, direction) elif isinstance(frame, InputAudioRawFrame): await self._send_user_audio(frame) await self.push_frame(frame, direction) - elif isinstance(frame, UserStoppedSpeakingFrame): - # This may or may not align with Ultravox's end of user speech detection, - # which relies on a more complex endpointing model. In particular it will - # yield a seemingly very slow TTFB in the case of endpointing false - # negatives. It will be close in the majority of cases though. - await self.start_ttfb_metrics() + elif isinstance(frame, VADUserStoppedSpeakingFrame): + await self._handle_vad_user_stopped_speaking(frame) await self.push_frame(frame, direction) else: await self.push_frame(frame, direction) @@ -399,6 +429,25 @@ class UltravoxRealtimeLLMService(LLMService): } await self._send(socket_message) + async def _handle_vad_user_stopped_speaking(self, frame: VADUserStoppedSpeakingFrame): + """Handle VAD user stopped speaking frame. + + Calculates the actual speech end time and starts a timeout task to wait + for the final transcription before reporting TTFB. + + Args: + frame: The VAD user stopped speaking frame. + """ + # Skip TTFB measurement if stop_secs is not set + if frame.stop_secs == 0.0: + return + + # Calculate the actual speech end time (current time minus VAD stop delay). + # This approximates when the last user audio was sent to the Ultravox service, + # which we use to measure against the eventual transcription response. + speech_end_time = frame.timestamp - frame.stop_secs + await self.start_ttfb_metrics(start_time=speech_end_time) + async def _send_user_audio(self, frame: InputAudioRawFrame): """Send user audio frame to Ultravox Realtime.""" if not self._socket: @@ -502,6 +551,7 @@ class UltravoxRealtimeLLMService(LLMService): if not audio: return if not self._bot_responding: + await self.start_processing_metrics() await self.stop_ttfb_metrics() await self.push_frame(LLMFullResponseStartFrame()) await self.push_frame(TTSStartedFrame()) @@ -509,6 +559,7 @@ class UltravoxRealtimeLLMService(LLMService): await self.push_frame(TTSAudioRawFrame(audio, self._sample_rate, 1)) async def _handle_response_end(self): + await self.stop_processing_metrics() if self._bot_responding == "voice": await self.push_frame(TTSStoppedFrame()) await self.push_frame(LLMFullResponseEndFrame()) @@ -542,22 +593,29 @@ class UltravoxRealtimeLLMService(LLMService): async def _handle_agent_transcript( self, medium: str, text: Optional[str], delta: Optional[str], final: bool ): - if text or delta: - frame = LLMTextFrame(text=text or delta) - frame.skip_tts = medium == "voice" - await self.push_frame(frame) - if medium == "text": - if text: - await self.stop_ttfb_metrics() - await self.push_frame(LLMFullResponseStartFrame()) - await self.push_frame(TTSStartedFrame()) - await self.push_frame(TTSTextFrame(text=text, aggregated_by=AggregationType.WORD)) - self._bot_responding = "text" - elif final: + if medium == "voice": + # In voice mode, audio is handled by _handle_audio(). Here we push + # text transcripts of the audio for downstream consumers. + if (text or delta) and not final: + frame = LLMTextFrame(text=text or delta) + frame.append_to_context = False + await self.push_frame(frame) + if delta: + tts_frame = TTSTextFrame(text=delta, aggregated_by=AggregationType.WORD) + tts_frame.includes_inter_frame_spaces = True + await self.push_frame(tts_frame) + elif medium == "text": + if final: + await self.stop_processing_metrics() await self.push_frame(LLMFullResponseEndFrame()) self._bot_responding = None - elif delta: - await self.push_frame(TTSTextFrame(text=delta, aggregated_by=AggregationType.WORD)) + elif text or delta: + if not self._bot_responding: + await self.start_processing_metrics() + await self.stop_ttfb_metrics() + await self.push_frame(LLMFullResponseStartFrame()) + self._bot_responding = "text" + await self.push_frame(LLMTextFrame(text=text or delta)) def create_context_aggregator( self, From faed775d9075064af3804be89f94322c36af2c8e Mon Sep 17 00:00:00 2001 From: Paul Kompfner Date: Thu, 26 Feb 2026 11:02:44 -0500 Subject: [PATCH 0655/1060] Extract `_DeepgramSTTSettingsBase` with shared `_merge_live_options_delta` to deduplicate LiveOptions merge logic between `__init__` and `apply_update`, and between the Deepgram STT and SageMaker variants; make top-level model/language take precedence over conflicting live_options values in updates; remove unnecessary Language enum-to-string conversion (Language is a StrEnum) --- src/pipecat/services/deepgram/stt.py | 131 ++++++++++------ .../services/deepgram/stt_sagemaker.py | 145 ++---------------- tests/test_settings.py | 72 +++++---- 3 files changed, 134 insertions(+), 214 deletions(-) diff --git a/src/pipecat/services/deepgram/stt.py b/src/pipecat/services/deepgram/stt.py index 59107d0f8..497d6aae1 100644 --- a/src/pipecat/services/deepgram/stt.py +++ b/src/pipecat/services/deepgram/stt.py @@ -49,19 +49,20 @@ except ModuleNotFoundError as e: @dataclass -class DeepgramSTTSettings(STTSettings): - """Settings for the Deepgram STT service. +class _DeepgramSTTSettingsBase(STTSettings): + """Base settings for Deepgram STT services that use ``LiveOptions``. + + Shared by ``DeepgramSTTSettings`` and ``DeepgramSageMakerSTTSettings``. + Not intended for other Deepgram services that don't use ``LiveOptions``. Wraps the Deepgram SDK's ``LiveOptions`` in a single ``live_options`` - field. All Deepgram-specific options (``filler_words``, ``diarize``, - ``utterance_end_ms``, etc.) should be passed directly via - ``LiveOptions``. + field and provides delta-merge semantics: when used as a delta (e.g. + via ``STTUpdateSettingsFrame``), only the non-None fields of + ``live_options`` are merged into the stored options rather than + replacing them wholesale. - In **delta mode** (i.e. when carried by ``STTUpdateSettingsFrame``), - ``live_options`` is treated as a **delta** — its non-None fields are - merged into the stored ``LiveOptions``, not replaced wholesale. For - example, ``DeepgramSTTSettings(live_options=LiveOptions(punctuate=False))`` - changes only ``punctuate`` and leaves all other options intact. + ``model`` and ``language`` are kept in sync bidirectionally between + the top-level settings fields and the nested ``live_options``. Parameters: live_options: Deepgram ``LiveOptions`` for STT configuration. @@ -83,12 +84,56 @@ class DeepgramSTTSettings(STTSettings): } return cls._live_options_params + def _merge_live_options_delta(self, delta: LiveOptions) -> Dict[str, Any]: + """Merge a ``LiveOptions`` delta into the stored ``live_options``. + + Non-None fields from *delta* overwrite corresponding fields in the + stored ``LiveOptions``. ``model`` and ``language`` are synced to + the top-level settings fields when they change. + + Args: + delta: A ``LiveOptions`` whose non-None fields are the desired + overrides. + + Returns: + Dict mapping each changed key to its **previous** value (same + contract as ``apply_update``). + """ + old_dict = self.live_options.to_dict() # type: ignore[union-attr] + delta_dict = delta.to_dict() + + # Deepgram SDK bug: model initialised to the *string* "None". + if delta_dict.get("model") == "None": + del delta_dict["model"] + + if not delta_dict: + return {} + + merged = {**old_dict, **delta_dict} + self.live_options = LiveOptions(**merged) + + # Track what changed. + changed: Dict[str, Any] = {} + for key in delta_dict: + old_val = old_dict.get(key, NOT_GIVEN) + if old_val != delta_dict[key]: + changed[key] = old_val + + # Sync model/language from live_options delta to top-level fields. + if "model" in delta_dict and delta_dict["model"] != self.model: + changed.setdefault("model", self.model) + self.model = delta_dict["model"] + if "language" in delta_dict and delta_dict["language"] != self.language: + changed.setdefault("language", self.language) + self.language = delta_dict["language"] + + return changed + def apply_update(self: _S, delta: _S) -> Dict[str, Any]: """Merge a delta into this store, with delta-merge for ``live_options``. - ``live_options`` is merged field-by-field (non-None fields from the - delta overwrite corresponding fields in the stored options) rather - than being replaced wholesale. + ``live_options`` is merged field-by-field via + ``_merge_live_options_delta`` rather than being replaced wholesale. ``model`` and ``language`` are kept in sync bidirectionally between the top-level settings fields and ``live_options``. @@ -107,27 +152,17 @@ class DeepgramSTTSettings(STTSettings): if "language" in changed: self.live_options.language = self.language # type: ignore[union-attr] - # Merge live_options delta. + # Merge live_options delta. Top-level model/language take precedence + # over conflicting values in live_options, so write them into the + # delta before merging. if is_given(delta_lo): - old_dict = self.live_options.to_dict() # type: ignore[union-attr] - delta_dict = delta_lo.to_dict() + if "model" in changed: + delta_lo.model = self.model + if "language" in changed: + delta_lo.language = self.language - if delta_dict: - merged = {**old_dict, **delta_dict} - self.live_options = LiveOptions(**merged) - - for key in delta_dict: - old_val = old_dict.get(key, NOT_GIVEN) - if old_val != delta_dict[key]: - changed[key] = old_val - - # Sync model/language from live_options delta to top-level. - if "model" in delta_dict and delta_dict["model"] != self.model: - changed.setdefault("model", self.model) - self.model = delta_dict["model"] - if "language" in delta_dict and delta_dict["language"] != self.language: - changed.setdefault("language", self.language) - self.language = delta_dict["language"] + for key, old_val in self._merge_live_options_delta(delta_lo).items(): + changed.setdefault(key, old_val) return changed @@ -165,6 +200,16 @@ class DeepgramSTTSettings(STTSettings): return instance +@dataclass +class DeepgramSTTSettings(_DeepgramSTTSettingsBase): + """Settings for the Deepgram STT service. + + See ``_DeepgramSTTSettingsBase`` for full documentation. + """ + + pass + + class DeepgramSTTService(STTService): """Deepgram speech-to-text service. @@ -250,25 +295,13 @@ class DeepgramSTTService(STTService): vad_events=False, ) - merged_dict = default_options.to_dict() - if live_options: - default_model = default_options.model - merged_dict.update(live_options.to_dict()) - # NOTE(aleix): Fixes a bug in deepgram-sdk where `model` is initialized - # to the string "None" instead of the value `None`. - if "model" in merged_dict and merged_dict["model"] == "None": - merged_dict["model"] = default_model - - if "language" in merged_dict and isinstance(merged_dict["language"], Language): - merged_dict["language"] = merged_dict["language"].value - - # Sync model/language to top-level STTSettings fields - model = merged_dict.get("model") - language = merged_dict.get("language") - settings = DeepgramSTTSettings( - model=model, language=language, live_options=LiveOptions(**merged_dict) + model=default_options.model, + language=default_options.language, + live_options=default_options, ) + if live_options: + settings._merge_live_options_delta(live_options) super().__init__( sample_rate=sample_rate, diff --git a/src/pipecat/services/deepgram/stt_sagemaker.py b/src/pipecat/services/deepgram/stt_sagemaker.py index ee2121bec..ba4b7dfda 100644 --- a/src/pipecat/services/deepgram/stt_sagemaker.py +++ b/src/pipecat/services/deepgram/stt_sagemaker.py @@ -13,10 +13,9 @@ languages, and various Deepgram features. """ import asyncio -import inspect import json -from dataclasses import dataclass, field -from typing import Any, AsyncGenerator, Dict, Mapping, Optional, Type +from dataclasses import dataclass +from typing import Any, AsyncGenerator, Dict, Optional from loguru import logger @@ -33,7 +32,8 @@ from pipecat.frames.frames import ( ) from pipecat.processors.frame_processor import FrameDirection from pipecat.services.aws.sagemaker.bidi_client import SageMakerBidiClient -from pipecat.services.settings import _S, NOT_GIVEN, STTSettings, _NotGiven, is_given +from pipecat.services.deepgram.stt import _DeepgramSTTSettingsBase +from pipecat.services.settings import STTSettings from pipecat.services.stt_latency import DEEPGRAM_SAGEMAKER_TTFS_P99 from pipecat.services.stt_service import STTService from pipecat.transcriptions.language import Language @@ -51,120 +51,13 @@ except ModuleNotFoundError as e: @dataclass -class DeepgramSageMakerSTTSettings(STTSettings): +class DeepgramSageMakerSTTSettings(_DeepgramSTTSettingsBase): """Settings for the Deepgram SageMaker STT service. - Wraps the Deepgram SDK's ``LiveOptions`` in a single ``live_options`` - field. All Deepgram-specific options (``filler_words``, ``diarize``, - ``utterance_end_ms``, etc.) should be passed directly via - ``LiveOptions``. - - In **delta mode** (i.e. when carried by ``STTUpdateSettingsFrame``), - ``live_options`` is treated as a **delta** — its non-None fields are - merged into the stored ``LiveOptions``, not replaced wholesale. For - example, ``DeepgramSageMakerSTTSettings(live_options=LiveOptions(punctuate=False))`` - changes only ``punctuate`` and leaves all other options intact. - - Parameters: - live_options: Deepgram ``LiveOptions`` for STT configuration. - In delta mode only its non-None fields are merged into the - stored options. + See ``_DeepgramSTTSettingsBase`` for full documentation. """ - live_options: LiveOptions | _NotGiven = field(default_factory=lambda: NOT_GIVEN) - - # Valid LiveOptions __init__ parameter names (cached at class level). - _live_options_params: set[str] | None = field(default=None, init=False, repr=False) - - @classmethod - def _get_live_options_params(cls) -> set[str]: - """Return the set of valid ``LiveOptions.__init__`` parameter names.""" - if cls._live_options_params is None: - cls._live_options_params = set(inspect.signature(LiveOptions.__init__).parameters) - { - "self" - } - return cls._live_options_params - - def apply_update(self: _S, delta: _S) -> Dict[str, Any]: - """Merge a delta into this store, with delta-merge for ``live_options``. - - ``live_options`` is merged field-by-field (non-None fields from the - delta overwrite corresponding fields in the stored options) rather - than being replaced wholesale. - - ``model`` and ``language`` are kept in sync bidirectionally between - the top-level settings fields and ``live_options``. - """ - # Pull live_options out of the delta so super() doesn't replace it. - delta_lo = getattr(delta, "live_options", NOT_GIVEN) - if is_given(delta_lo): - delta.live_options = NOT_GIVEN # type: ignore[assignment] - - # Let the base class handle model, language, extra. - changed = super().apply_update(delta) - - # Sync top-level model/language changes into stored live_options. - if "model" in changed: - self.live_options.model = self.model # type: ignore[union-attr] - if "language" in changed: - self.live_options.language = self.language # type: ignore[union-attr] - - # Merge live_options delta. - if is_given(delta_lo): - old_dict = self.live_options.to_dict() # type: ignore[union-attr] - delta_dict = delta_lo.to_dict() - - if delta_dict: - merged = {**old_dict, **delta_dict} - self.live_options = LiveOptions(**merged) - - for key in delta_dict: - old_val = old_dict.get(key, NOT_GIVEN) - if old_val != delta_dict[key]: - changed[key] = old_val - - # Sync model/language from live_options delta to top-level. - if "model" in delta_dict and delta_dict["model"] != self.model: - changed.setdefault("model", self.model) - self.model = delta_dict["model"] - if "language" in delta_dict and delta_dict["language"] != self.language: - changed.setdefault("language", self.language) - self.language = delta_dict["language"] - - return changed - - @classmethod - def from_mapping(cls: Type[_S], settings: Mapping[str, Any]) -> _S: - """Build a delta from a plain dict, routing LiveOptions keys correctly. - - Keys that are valid ``LiveOptions.__init__`` parameters (and not - top-level ``STTSettings`` fields like ``model`` / ``language``) are - collected into a ``LiveOptions`` object. ``model`` and ``language`` - are routed to the top-level settings fields. Truly unknown keys go - to ``extra``. - """ - lo_params = cls._get_live_options_params() - stt_field_names = {"model", "language"} - - kwargs: Dict[str, Any] = {} - lo_kwargs: Dict[str, Any] = {} - extra: Dict[str, Any] = {} - - for key, value in settings.items(): - canonical = cls._aliases.get(key, key) - if canonical in stt_field_names: - kwargs[canonical] = value - elif canonical in lo_params: - lo_kwargs[canonical] = value - else: - extra[key] = value - - if lo_kwargs: - kwargs["live_options"] = LiveOptions(**lo_kwargs) - - instance = cls(**kwargs) - instance.extra = extra - return instance + pass class DeepgramSageMakerSTTService(STTService): @@ -224,7 +117,6 @@ class DeepgramSageMakerSTTService(STTService): """ sample_rate = sample_rate or (live_options.sample_rate if live_options else None) - # Create default options similar to DeepgramSTTService default_options = LiveOptions( encoding="linear16", language=Language.EN, @@ -234,26 +126,13 @@ class DeepgramSageMakerSTTService(STTService): punctuate=True, ) - # Merge with provided options - merged_dict = default_options.to_dict() - if live_options: - default_model = default_options.model - merged_dict.update(live_options.to_dict()) - # Handle the "None" string bug from deepgram-sdk - if "model" in merged_dict and merged_dict["model"] == "None": - merged_dict["model"] = default_model - - # Convert Language enum to string if needed - if "language" in merged_dict and isinstance(merged_dict["language"], Language): - merged_dict["language"] = merged_dict["language"].value - - # Sync model/language to top-level STTSettings fields - model = merged_dict.get("model") - language = merged_dict.get("language") - settings = DeepgramSageMakerSTTSettings( - model=model, language=language, live_options=LiveOptions(**merged_dict) + model=default_options.model, + language=default_options.language, + live_options=default_options, ) + if live_options: + settings._merge_live_options_delta(live_options) super().__init__( sample_rate=sample_rate, diff --git a/tests/test_settings.py b/tests/test_settings.py index 3201e3c24..47cb6e4cf 100644 --- a/tests/test_settings.py +++ b/tests/test_settings.py @@ -407,6 +407,36 @@ class TestDeepgramSTTSettingsApplyUpdate: changed = current.apply_update(delta) assert changed == {} + def test_apply_update_top_level_model_takes_precedence_over_live_options(self): + """When both top-level model and live_options.model are set, top-level wins.""" + current = self._make_store() + assert current.model == "nova-3-general" + + delta = DeepgramSTTSettings( + model="nova-2", + live_options=LiveOptions(model="nova-3"), + ) + changed = current.apply_update(delta) + + assert current.model == "nova-2" + assert current.live_options.model == "nova-2" + assert "model" in changed + + def test_apply_update_top_level_language_takes_precedence_over_live_options(self): + """When both top-level language and live_options.language are set, top-level wins.""" + current = self._make_store() + assert current.language == "en" + + delta = DeepgramSTTSettings( + language="fr", + live_options=LiveOptions(language="es"), + ) + changed = current.apply_update(delta) + + assert current.language == "fr" + assert current.live_options.language == "fr" + assert "language" in changed + class TestDeepgramSTTSettingsFromMapping: def test_routes_live_options_kwargs(self): @@ -482,43 +512,21 @@ class TestDeepgramSTTSettingsFromMapping: # --------------------------------------------------------------------------- -# DeepgramSageMakerSTTSettings: same pattern +# DeepgramSageMakerSTTSettings: smoke test that the shared base is inherited # --------------------------------------------------------------------------- -class TestDeepgramSageMakerSTTSettingsApplyUpdate: - def _make_store(self, **lo_kwargs) -> DeepgramSageMakerSTTSettings: - defaults = dict( - encoding="linear16", - channels=1, - interim_results=True, - punctuate=True, - ) - defaults.update(lo_kwargs) - return DeepgramSageMakerSTTSettings( +class TestDeepgramSageMakerSTTSettings: + def test_inherits_live_options_behavior(self): + """Smoke test: SageMaker settings inherit the shared base correctly.""" + store = DeepgramSageMakerSTTSettings( model="nova-3", language="en", - live_options=LiveOptions(**defaults), + live_options=LiveOptions(encoding="linear16", channels=1, punctuate=True), ) - - def test_apply_update_merges_live_options_as_delta(self): - current = self._make_store() delta = DeepgramSageMakerSTTSettings(live_options=LiveOptions(punctuate=False)) - changed = current.apply_update(delta) - assert current.live_options.punctuate is False + changed = store.apply_update(delta) + + assert store.live_options.punctuate is False + assert store.live_options.encoding == "linear16" assert "punctuate" in changed - assert current.live_options.encoding == "linear16" - - def test_apply_update_syncs_model_from_live_options(self): - current = self._make_store() - delta = DeepgramSageMakerSTTSettings(live_options=LiveOptions(model="nova-2")) - current.apply_update(delta) - assert current.model == "nova-2" - - def test_from_mapping_routes_correctly(self): - delta = DeepgramSageMakerSTTSettings.from_mapping( - {"model": "nova-2", "punctuate": False, "unknown": "val"} - ) - assert delta.model == "nova-2" - assert delta.live_options.punctuate is False - assert delta.extra == {"unknown": "val"} From fff9db0d8f148954a518b5848de3253b7d433369 Mon Sep 17 00:00:00 2001 From: Rupesh Date: Thu, 26 Feb 2026 13:51:05 -0800 Subject: [PATCH 0656/1060] Remove verbose audio chunk logging from GenesysAudioHookSerializer Fixes #3777 --- src/pipecat/serializers/genesys.py | 1 - 1 file changed, 1 deletion(-) diff --git a/src/pipecat/serializers/genesys.py b/src/pipecat/serializers/genesys.py index 24b68eb81..a25287b5c 100644 --- a/src/pipecat/serializers/genesys.py +++ b/src/pipecat/serializers/genesys.py @@ -642,7 +642,6 @@ class GenesysAudioHookSerializer(FrameSerializer): """ # Binary data = audio if isinstance(data, bytes): - logger.debug(f"[AUDIO IN] Received {len(data)} bytes from Genesys") return await self._deserialize_audio(data) # Text data = JSON control message From bbaa79fef038d50434d3c5008226418c85ce140f Mon Sep 17 00:00:00 2001 From: Rupesh Date: Thu, 26 Feb 2026 14:00:34 -0800 Subject: [PATCH 0657/1060] Add changelog for PR #3850 --- changelog/3850.fixed.md | 1 + 1 file changed, 1 insertion(+) create mode 100644 changelog/3850.fixed.md diff --git a/changelog/3850.fixed.md b/changelog/3850.fixed.md new file mode 100644 index 000000000..cfbdc6cf7 --- /dev/null +++ b/changelog/3850.fixed.md @@ -0,0 +1 @@ +- Removed verbose per-chunk audio logging from `GenesysAudioHookSerializer` that flooded production logs. From 72934bd8ae23de1d4c34e75350e168faa8fe54a6 Mon Sep 17 00:00:00 2001 From: zack Date: Thu, 26 Feb 2026 21:35:47 -0500 Subject: [PATCH 0658/1060] Add u3-rt-pro support and improvements to AssemblyAI STT service MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit - Fix speaker diarization: Add field alias for speaker_label → speaker mapping in TurnMessage model - Add warning for non-optimal min_end_of_turn_silence_when_confident values (recommends 100ms for best latency) - Improve max_turn_silence override warning message clarity - Update custom prompt warning (remove 88% accuracy claim) - Add comprehensive logging for debugging: - Log final connection params after modifications - Log WebSocket URL and parsed parameters - Log speaker field in transcripts - Log text sent to LLM with speaker formatting - Support dynamic configuration updates via STTUpdateSettingsFrame: - keyterms_prompt (when AssemblyAI API supports it) - prompt - max_turn_silence - min_end_of_turn_silence_when_confident --- src/pipecat/services/assemblyai/models.py | 45 ++- src/pipecat/services/assemblyai/stt.py | 441 ++++++++++++++++++---- 2 files changed, 408 insertions(+), 78 deletions(-) diff --git a/src/pipecat/services/assemblyai/models.py b/src/pipecat/services/assemblyai/models.py index ca58cb848..fb883ac99 100644 --- a/src/pipecat/services/assemblyai/models.py +++ b/src/pipecat/services/assemblyai/models.py @@ -12,7 +12,7 @@ transcription WebSocket messages and connection configuration. from typing import List, Literal, Optional -from pydantic import BaseModel, Field +from pydantic import BaseModel, ConfigDict, Field class Word(BaseModel): @@ -68,8 +68,16 @@ class TurnMessage(BaseMessage): transcript: The transcribed text for this turn. end_of_turn_confidence: Confidence score for end-of-turn detection. words: List of individual words with timing and confidence data. + language_code: Detected language code (e.g., "es", "fr"). Only present with + complete utterances or when end_of_turn is True. + language_confidence: Confidence score (0-1) for language detection. Only present + with complete utterances or when end_of_turn is True. + speaker: Speaker label (e.g., "A", "B"). Only present when speaker_labels is + enabled and end_of_turn is True. Maps to 'speaker_label' in JSON response. """ + model_config = ConfigDict(populate_by_name=True) + type: Literal["Turn"] = "Turn" turn_order: int turn_is_formatted: bool @@ -77,6 +85,21 @@ class TurnMessage(BaseMessage): transcript: str end_of_turn_confidence: float words: List[Word] + language_code: Optional[str] = None + language_confidence: Optional[float] = None + speaker: Optional[str] = Field(default=None, alias="speaker_label") + + +class SpeechStartedMessage(BaseMessage): + """Message sent when speech is first detected in the audio stream. + + Parameters: + type: Always "SpeechStarted" for this message type. + timestamp: Audio timestamp in milliseconds when speech was detected. + """ + + type: Literal["SpeechStarted"] = "SpeechStarted" + timestamp: int class TerminationMessage(BaseMessage): @@ -94,7 +117,7 @@ class TerminationMessage(BaseMessage): # Union type for all possible message types -AnyMessage = BeginMessage | TurnMessage | TerminationMessage +AnyMessage = BeginMessage | TurnMessage | SpeechStartedMessage | TerminationMessage class AssemblyAIConnectionParams(BaseModel): @@ -109,7 +132,15 @@ class AssemblyAIConnectionParams(BaseModel): min_end_of_turn_silence_when_confident: Minimum silence duration when confident about end-of-turn. max_turn_silence: Maximum silence duration before forcing end-of-turn. keyterms_prompt: List of key terms to guide transcription. Will be JSON serialized before sending. - speech_model: Select between English and multilingual models. Defaults to "universal-streaming-english". + prompt: Optional text prompt to guide the transcription. Only used when speech_model is "u3-rt-pro". + speech_model: Select between English, multilingual, and u3-rt-pro models. Defaults to "u3-rt-pro". + language_detection: Enable automatic language detection. Only applicable to + universal-streaming-multilingual. When enabled, Turn messages include + language_code and language_confidence fields. Defaults to None (not sent). + format_turns: Whether to format transcript turns. Defaults to True. + speaker_labels: Enable speaker diarization. When enabled, final transcripts + (end_of_turn=True) include a speaker field identifying the speaker + (e.g., "Speaker A", "Speaker B"). Defaults to None (not sent). """ sample_rate: int = 16000 @@ -120,6 +151,10 @@ class AssemblyAIConnectionParams(BaseModel): min_end_of_turn_silence_when_confident: Optional[int] = None max_turn_silence: Optional[int] = None keyterms_prompt: Optional[List[str]] = None - speech_model: Literal["universal-streaming-english", "universal-streaming-multilingual"] = ( - "universal-streaming-english" + prompt: Optional[str] = None + speech_model: Literal["universal-streaming-english", "universal-streaming-multilingual", "u3-rt-pro"] = ( + "u3-rt-pro" ) + language_detection: Optional[bool] = None + format_turns: bool = True + speaker_labels: Optional[bool] = None diff --git a/src/pipecat/services/assemblyai/stt.py b/src/pipecat/services/assemblyai/stt.py index a89f5fe52..edd5ac7b7 100644 --- a/src/pipecat/services/assemblyai/stt.py +++ b/src/pipecat/services/assemblyai/stt.py @@ -13,7 +13,7 @@ WebSocket API for streaming audio transcription. import asyncio import json from dataclasses import dataclass, field -from typing import Any, AsyncGenerator, Dict, Optional +from typing import Any, AsyncGenerator, Dict, Mapping, Optional from urllib.parse import urlencode from loguru import logger @@ -41,6 +41,7 @@ from .models import ( AssemblyAIConnectionParams, BaseMessage, BeginMessage, + SpeechStartedMessage, TerminationMessage, TurnMessage, ) @@ -54,6 +55,26 @@ except ModuleNotFoundError as e: raise Exception(f"Missing module: {e}") +def map_language_from_assemblyai(language_code: str) -> Language: + """Map AssemblyAI language codes to Pipecat Language enum. + + AssemblyAI returns simple language codes like "es", "fr", etc. + This function maps them to the corresponding Language enum values. + + Args: + language_code: AssemblyAI language code (e.g., "es", "fr", "de") + + Returns: + Corresponding Language enum value, defaulting to Language.EN if not found. + """ + try: + # Try to match the language code directly + return Language(language_code.lower()) + except ValueError: + logger.warning(f"Unknown language code from AssemblyAI: {language_code}, defaulting to English") + return Language.EN + + @dataclass class AssemblyAISTTSettings(STTSettings): """Settings for the AssemblyAI STT service. @@ -87,6 +108,8 @@ class AssemblyAISTTService(WebsocketSTTService): api_endpoint_base_url: str = "wss://streaming.assemblyai.com/v3/ws", connection_params: AssemblyAIConnectionParams = AssemblyAIConnectionParams(), vad_force_turn_endpoint: bool = True, + should_interrupt: bool = True, + speaker_format: Optional[str] = None, ttfs_p99_latency: Optional[float] = ASSEMBLYAI_TTFS_P99, **kwargs, ): @@ -97,18 +120,64 @@ class AssemblyAISTTService(WebsocketSTTService): language: Language code for transcription. Defaults to English (Language.EN). api_endpoint_base_url: WebSocket endpoint URL. Defaults to AssemblyAI's streaming endpoint. connection_params: Connection configuration parameters. Defaults to AssemblyAIConnectionParams(). - vad_force_turn_endpoint: Whether to force turn endpoint on VAD stop. When True, - disables AssemblyAI's model-based turn detection and relies on external VAD - to trigger turn endpoints. Automatically sets end_of_turn_confidence_threshold=1.0 - and max_turn_silence=2000 unless explicitly overridden. Defaults to True. + vad_force_turn_endpoint: Controls turn detection mode. + When True (Pipecat mode, default): Forces AssemblyAI to return finals ASAP + so Pipecat's turn detection (e.g., Smart Turn) decides when the user is done. + - min_end_of_turn_silence_when_confident defaults to 100ms (user can override) + - max_turn_silence is ALWAYS set equal to min_end_of_turn_silence_when_confident + - VAD stop sends ForceEndpoint as ceiling + - No UserStarted/StoppedSpeakingFrame emitted from STT + When False (STT mode, u3-rt-pro only): AssemblyAI's model controls turn endings. + - Uses AssemblyAI API defaults for all parameters (unless user explicitly sets them) + - Respects all user-provided connection_params as-is + - Emits UserStarted/StoppedSpeakingFrame from STT + - No ForceEndpoint on VAD stop + should_interrupt: Whether to interrupt the bot when the user starts speaking + in STT mode (vad_force_turn_endpoint=False). Only applies to STT mode. + Defaults to True. + speaker_format: Optional format string for speaker labels when diarization is enabled. + Use {speaker} for speaker label and {text} for transcript text. + Example: "<{speaker}>{text}" or "{speaker}: {text}" + If None, transcript text is not modified. Defaults to None. ttfs_p99_latency: P99 latency from speech end to final transcript in seconds. Override for your deployment. See https://github.com/pipecat-ai/stt-benchmark **kwargs: Additional arguments passed to parent STTService class. """ - # When vad_force_turn_endpoint is enabled, configure connection params for manual - # turn detection mode (disable model-based turn detection) + # STT turn detection (vad_force_turn_endpoint=False) requires the + # SpeechStarted event for reliable barge-in. Only u3-rt-pro supports + # this. Other models must use Pipecat turn detection. + is_u3_pro = connection_params.speech_model == "u3-rt-pro" + if not vad_force_turn_endpoint and not is_u3_pro: + raise ValueError( + f"STT turn detection (vad_force_turn_endpoint=False) requires " + f"u3-rt-pro for SpeechStarted support. Either set " + f"vad_force_turn_endpoint=True for {connection_params.speech_model}, " + f"or use speech_model='u3-rt-pro'." + ) + + # Validate that prompt and keyterms_prompt are not both set + if connection_params.prompt is not None and connection_params.keyterms_prompt is not None: + raise ValueError( + "The prompt and keyterms_prompt parameters cannot be used in the same request. " + "Please choose either one or the other based on your use case. When you use " + "keyterms_prompt, your boosted words are appended to the default prompt automatically. " + "Or to boost within prompt: + Make sure to boost the words in the audio. " + "For more info go to: https://www.assemblyai.com/docs/streaming/universal-3-pro" + ) + + # Warn if user sets a custom prompt (recommend testing without one first) + if connection_params.prompt is not None: + logger.warning( + "Custom prompt detected. We recommend testing with no prompt first, as this " + "will use our optimized default prompt for voice agents. Bad prompts may lead " + "to bad results. If you'd like to create your own prompt, check out our " + "prompting guide at: https://www.assemblyai.com/docs/streaming/prompting" + ) + + # When vad_force_turn_endpoint is enabled, configure connection params + # for Pipecat turn detection mode (fast finals for smart turn analyzer) if vad_force_turn_endpoint: - connection_params = self._configure_manual_turn_mode(connection_params) + connection_params = self._configure_pipecat_turn_mode(connection_params, is_u3_pro) super().__init__( sample_rate=connection_params.sample_rate, @@ -124,6 +193,8 @@ class AssemblyAISTTService(WebsocketSTTService): self._api_key = api_key self._api_endpoint_base_url = api_endpoint_base_url self._vad_force_turn_endpoint = vad_force_turn_endpoint + self._should_interrupt = should_interrupt + self._speaker_format = speaker_format self._termination_event = asyncio.Event() self._received_termination = False @@ -135,45 +206,77 @@ class AssemblyAISTTService(WebsocketSTTService): self._chunk_size_ms = 50 self._chunk_size_bytes = 0 - def _configure_manual_turn_mode( - self, connection_params: AssemblyAIConnectionParams - ) -> AssemblyAIConnectionParams: - """Configure connection params for manual turn detection mode. + self._user_speaking = False + self._vad_speaking = False - When vad_force_turn_endpoint is enabled, we want to disable AssemblyAI's - model-based turn detection and rely on external VAD. This requires: - - end_of_turn_confidence_threshold=1.0 (disable semantic turn detection) - - max_turn_silence=2000 (high value since VAD handles turn endings) + # Log final connection params after any modifications + logger.info(f"{self} Final connection params being sent to AssemblyAI:") + logger.info(f" min_end_of_turn_silence_when_confident: {self._settings.connection_params.min_end_of_turn_silence_when_confident}") + logger.info(f" max_turn_silence: {self._settings.connection_params.max_turn_silence}") + + # Warn if min_end_of_turn_silence_when_confident is not 100ms + if self._settings.connection_params.min_end_of_turn_silence_when_confident != 100: + logger.warning( + f"For best latency, set min_end_of_turn_silence_when_confident to 100ms. " + f"Current value: {self._settings.connection_params.min_end_of_turn_silence_when_confident}ms" + ) + + def _configure_pipecat_turn_mode( + self, connection_params: AssemblyAIConnectionParams, is_u3_pro: bool + ) -> AssemblyAIConnectionParams: + """Configure connection params for Pipecat turn detection mode. + + When vad_force_turn_endpoint is enabled, force AssemblyAI to return + finals as fast as possible so Pipecat's smart turn analyzer can decide + when the user is done speaking. VAD stop is the absolute ceiling. + + u3-rt-pro: + - min_end_of_turn_silence_when_confident defaults to 100ms (user can override) + - max_turn_silence is ALWAYS set equal to min_end_of_turn_silence_when_confident + to avoid double turn detection (AssemblyAI + Pipecat both analyzing) + - If user sets max_turn_silence, it's ignored with a warning + - end_of_turn_confidence_threshold: not set (API default) + + universal-streaming-*: + - end_of_turn_confidence_threshold=0.0 (disable semantic turn detection) + - min_end_of_turn_silence_when_confident=160 + - max_turn_silence: not set (API default) Args: connection_params: The user-provided connection parameters. + is_u3_pro: Whether using u3-rt-pro model. Returns: - Updated connection parameters configured for manual turn mode. + Updated connection parameters configured for Pipecat turn mode. """ updates = {} - # Check end_of_turn_confidence_threshold - if connection_params.end_of_turn_confidence_threshold is None: - updates["end_of_turn_confidence_threshold"] = 1.0 - elif connection_params.end_of_turn_confidence_threshold != 1.0: - logger.warning( - f"vad_force_turn_endpoint is enabled but end_of_turn_confidence_threshold " - f"is set to {connection_params.end_of_turn_confidence_threshold}. " - f"For manual turn detection mode, this should be 1.0 to disable " - f"model-based turn detection. The current value will be used." - ) + if is_u3_pro: + # u3-rt-pro: Synchronize max_turn_silence with min_end_of_turn_silence_when_confident + min_silence = connection_params.min_end_of_turn_silence_when_confident + if min_silence is None: + min_silence = 100 - # Check max_turn_silence - if connection_params.max_turn_silence is None: - updates["max_turn_silence"] = 2000 - elif connection_params.max_turn_silence < 1000: - logger.warning( - f"vad_force_turn_endpoint is enabled but max_turn_silence is set to " - f"{connection_params.max_turn_silence}ms. With manual turn detection, " - f"a higher value (e.g., 2000ms) is recommended to avoid premature " - f"turn endings. The current value will be used." - ) + # Warn if user set max_turn_silence (will be overridden) + if connection_params.max_turn_silence is not None: + logger.warning( + f"Your max_turn_silence value ({connection_params.max_turn_silence}ms) will be " + f"OVERRIDDEN in Pipecat mode (vad_force_turn_endpoint=True). It will be set to " + f"{min_silence}ms (matching min_end_of_turn_silence_when_confident) and SENT to " + f"AssemblyAI to avoid double turn detection. To use your max_turn_silence as-is, " + f"switch to STT mode (vad_force_turn_endpoint=False)." + ) + + updates = { + "min_end_of_turn_silence_when_confident": min_silence, + "max_turn_silence": min_silence, + } + else: + # universal-streaming: Different configuration (works differently) + updates = { + "end_of_turn_confidence_threshold": 0.0, + "min_end_of_turn_silence_when_confident": 160, + } # Apply updates if any if updates: @@ -190,9 +293,14 @@ class AssemblyAISTTService(WebsocketSTTService): return True async def _update_settings(self, delta: STTSettings) -> dict[str, Any]: - """Apply a settings delta. + """Apply a settings delta and send UpdateConfiguration if connected. - Settings are stored but not applied to the active connection. + Stores settings changes and sends UpdateConfiguration message to AssemblyAI + without reconnecting. Supports updating: + - keyterms_prompt: List of terms to boost (can be empty array to clear) + - prompt: Custom prompt text (u3-rt-pro only) + - max_turn_silence: Maximum silence before forcing turn end + - min_end_of_turn_silence_when_confident: Silence before EOT check Args: delta: A :class:`STTSettings` (or ``AssemblyAISTTSettings``) delta. @@ -205,18 +313,63 @@ class AssemblyAISTTService(WebsocketSTTService): if not changed: return changed - # TODO: someday we could reconnect here to apply updated settings. - # Code might look something like the below: - # # Re-apply manual turn mode config if vad_force_turn_endpoint is active - # # and connection_params were updated. - # if self._vad_force_turn_endpoint and "connection_params" in changed: - # self._settings.connection_params = self._configure_manual_turn_mode( - # self._settings.connection_params - # ) - # await self._disconnect() - # await self._connect() + # If websocket is connected, send UpdateConfiguration for supported params + if self._websocket and self._websocket.state is State.OPEN and "connection_params" in changed: + # Build UpdateConfiguration message + update_config = {"type": "UpdateConfiguration"} + conn_params = self._settings.connection_params - self._warn_unhandled_updated_settings(changed) + # Get the old connection_params to see what changed + old_conn_params = changed.get("connection_params") + + # Check each potentially changed parameter + if hasattr(conn_params, "keyterms_prompt"): + if old_conn_params is None or conn_params.keyterms_prompt != old_conn_params.keyterms_prompt: + if conn_params.keyterms_prompt is not None: + update_config["keyterms_prompt"] = conn_params.keyterms_prompt + logger.info(f"Updating keyterms_prompt to: {conn_params.keyterms_prompt}") + + if hasattr(conn_params, "prompt"): + if old_conn_params is None or conn_params.prompt != old_conn_params.prompt: + if conn_params.prompt is not None: + if conn_params.speech_model != "u3-rt-pro": + logger.warning( + f"prompt parameter is only supported with u3-rt-pro model, " + f"current model is {conn_params.speech_model}" + ) + else: + update_config["prompt"] = conn_params.prompt + logger.info(f"Updating prompt") + + if hasattr(conn_params, "max_turn_silence"): + if old_conn_params is None or conn_params.max_turn_silence != old_conn_params.max_turn_silence: + if conn_params.max_turn_silence is not None: + update_config["max_turn_silence"] = conn_params.max_turn_silence + logger.info(f"Updating max_turn_silence to: {conn_params.max_turn_silence}ms") + + if hasattr(conn_params, "min_end_of_turn_silence_when_confident"): + if old_conn_params is None or conn_params.min_end_of_turn_silence_when_confident != old_conn_params.min_end_of_turn_silence_when_confident: + if conn_params.min_end_of_turn_silence_when_confident is not None: + update_config["min_end_of_turn_silence_when_confident"] = conn_params.min_end_of_turn_silence_when_confident + logger.info(f"Updating min_end_of_turn_silence_when_confident to: {conn_params.min_end_of_turn_silence_when_confident}ms") + + # Send update if we have parameters to update + if len(update_config) > 1: # More than just "type" + try: + await self._websocket.send(json.dumps(update_config)) + logger.info(f"Sent UpdateConfiguration: {update_config}") + except Exception as e: + logger.error(f"Failed to send UpdateConfiguration: {e}") + elif "connection_params" in changed: + logger.warning( + "Connection params changed but WebSocket not connected. " + "Settings will be applied on next connection." + ) + + # Warn about other settings that can't be changed dynamically + other_changes = {k: v for k, v in changed.items() if k not in ["connection_params"]} + if other_changes: + self._warn_unhandled_updated_settings(other_changes) return changed @@ -305,7 +458,13 @@ class AssemblyAISTTService(WebsocketSTTService): if params: query_string = urlencode(params) - return f"{self._api_endpoint_base_url}?{query_string}" + full_url = f"{self._api_endpoint_base_url}?{query_string}" + logger.info(f"{self} WebSocket URL being sent to AssemblyAI:") + logger.info(f" {full_url}") + logger.info(f" Parsed params:") + for k, v in params.items(): + logger.info(f" {k}: {v}") + return full_url return self._api_endpoint_base_url async def _connect(self): @@ -421,6 +580,9 @@ class AssemblyAISTTService(WebsocketSTTService): async for message in self._get_websocket(): try: data = json.loads(message) + # Log raw JSON for Turn messages to debug speaker_label + if data.get("type") == "Turn": + logger.debug(f"{self} RAW JSON from AssemblyAI: {json.dumps(data, indent=2)}") await self._handle_message(data) except json.JSONDecodeError: logger.warning(f"Received non-JSON message: {message}") @@ -433,6 +595,8 @@ class AssemblyAISTTService(WebsocketSTTService): return BeginMessage.model_validate(message) elif msg_type == "Turn": return TurnMessage.model_validate(message) + elif msg_type == "SpeechStarted": + return SpeechStartedMessage.model_validate(message) elif msg_type == "Termination": return TerminationMessage.model_validate(message) else: @@ -449,11 +613,37 @@ class AssemblyAISTTService(WebsocketSTTService): ) elif isinstance(parsed_message, TurnMessage): await self._handle_transcription(parsed_message) + elif isinstance(parsed_message, SpeechStartedMessage): + await self._handle_speech_started(parsed_message) elif isinstance(parsed_message, TerminationMessage): await self._handle_termination(parsed_message) except Exception as e: await self.push_error(error_msg=f"Unknown error occurred: {e}", exception=e) + async def _handle_speech_started(self, message: SpeechStartedMessage): + """Handle SpeechStarted event — fast barge-in for Mode 2. + + Broadcasts UserStartedSpeakingFrame to signal the start of user + speech, then pushes an interruption to cancel any bot audio. + SpeechStarted fires before any transcript arrives, so the turn + is cleanly started before any transcription frames are pushed. + + Only applies to Mode 2 (STT turn detection). In Mode 1, VAD + + smart turn analyzer handle interruptions via the aggregator. + """ + logger.debug(f"{self} SpeechStarted received (vad_force_turn_endpoint={self._vad_force_turn_endpoint})") + if self._vad_force_turn_endpoint: + logger.debug(f"{self} SpeechStarted ignored in Pipecat mode") + return # Mode 1: handled by aggregator + + logger.debug(f"{self} Processing SpeechStarted in STT mode") + await self.start_processing_metrics() + await self.broadcast_frame(UserStartedSpeakingFrame) + if self._should_interrupt: + await self.push_interruption_task_frame_and_wait() + self._user_speaking = True + logger.debug(f"{self} _user_speaking set to True") + async def _handle_termination(self, message: TerminationMessage): """Handle termination message.""" self._received_termination = True @@ -466,30 +656,135 @@ class AssemblyAISTTService(WebsocketSTTService): await self.push_frame(EndFrame()) async def _handle_transcription(self, message: TurnMessage): - """Handle transcription results.""" + """Handle transcription results with two-mode turn detection. + + Mode 1 (vad_force_turn_endpoint=True, Pipecat turn detection): + - No UserStarted/StoppedSpeakingFrame from STT + - end_of_turn → TranscriptionFrame (finalized set by base class + if this is a ForceEndpoint response) + - else → InterimTranscriptionFrame + + Mode 2 (vad_force_turn_endpoint=False, STT turn detection): + - UserStartedSpeakingFrame on first transcript + - end_of_turn → TranscriptionFrame + UserStoppedSpeakingFrame + - else → InterimTranscriptionFrame + """ + # Log transcript details + logger.info(f"{self} ===== TRANSCRIPT RECEIVED =====") + logger.info(f" Text: \"{message.transcript}\"") + logger.info(f" end_of_turn: {message.end_of_turn}") + logger.info(f" turn_is_formatted: {message.turn_is_formatted}") + logger.info(f" turn_order: {message.turn_order}") + if message.end_of_turn_confidence is not None: + logger.info(f" end_of_turn_confidence: {message.end_of_turn_confidence}") + logger.info(f" speaker: {message.speaker}") + logger.info(f"===============================") + if not message.transcript: return - if message.end_of_turn and ( - not self._settings.connection_params.formatted_finals or message.turn_is_formatted - ): - await self.push_frame( - TranscriptionFrame( - message.transcript, - self._user_id, - time_now_iso8601(), - self._settings.language, - message, + + # Use detected language if available with sufficient confidence + language = Language.EN + if message.language_code and message.language_confidence: + if message.language_confidence >= 0.7: + language = map_language_from_assemblyai(message.language_code) + else: + logger.warning( + f"Low language detection confidence ({message.language_confidence:.2f}) " + f"for language '{message.language_code}', falling back to English" ) - ) - await self._trace_transcription(message.transcript, True, self._settings.language) - await self.stop_processing_metrics() + + # Handle speaker diarization + speaker_id = self._user_id + transcript_text = message.transcript + + if message.speaker: + speaker_id = message.speaker + # Format transcript with speaker labels if format string provided + if self._speaker_format: + transcript_text = self._speaker_format.format( + speaker=message.speaker, + text=message.transcript + ) + logger.info(f"{self} 🤖 TEXT SENT TO LLM (with speaker format): \"{transcript_text}\"") + else: + logger.info(f"{self} 🤖 TEXT SENT TO LLM (speaker {message.speaker}): \"{transcript_text}\"") else: - await self.push_frame( - InterimTranscriptionFrame( - message.transcript, - self._user_id, - time_now_iso8601(), - self._settings.language, - message, + logger.info(f"{self} 🤖 TEXT SENT TO LLM: \"{transcript_text}\"") + + # Determine if this is a final turn from AssemblyAI + is_final_turn = message.end_of_turn and ( + not self._settings.connection_params.format_turns or message.turn_is_formatted + ) + + if self._vad_force_turn_endpoint: + # --- Mode 1: Pipecat turn detection --- + # No UserStarted/StoppedSpeakingFrame — VAD + smart turn analyzer handle this + if is_final_turn: + finalize_confirmed = bool(message.turn_is_formatted) + if finalize_confirmed: + self.confirm_finalize() + logger.debug(f"{self} Final transcript: \"{transcript_text}\"") + await self.push_frame( + TranscriptionFrame( + transcript_text, + speaker_id, + time_now_iso8601(), + language, + message, + ) + ) + await self._trace_transcription(transcript_text, True, language) + await self.stop_processing_metrics() + else: + logger.debug(f"{self} Interim transcript: \"{transcript_text}\"") + await self.push_frame( + InterimTranscriptionFrame( + transcript_text, + speaker_id, + time_now_iso8601(), + language, + message, + ) + ) + else: + # --- Mode 2: STT turn detection --- + # SpeechStarted handles UserStartedSpeakingFrame + interruption. + # If SpeechStarted hasn't fired yet (shouldn't happen, but guard), + # broadcast here as fallback. + logger.debug(f"{self} Transcript received in STT mode (_user_speaking={self._user_speaking})") + if not self._user_speaking: + logger.warning(f"{self} Transcript arrived before SpeechStarted, broadcasting fallback UserStartedSpeakingFrame") + await self.broadcast_frame(UserStartedSpeakingFrame) + self._user_speaking = True + + if is_final_turn: + if message.turn_is_formatted: + self.confirm_finalize() + await self.push_frame( + TranscriptionFrame( + transcript_text, + speaker_id, + time_now_iso8601(), + language, + message, + finalized=True, + ) + ) + await self._trace_transcription(transcript_text, True, language) + await self.stop_processing_metrics() + # AAI is authoritative — emit UserStoppedSpeakingFrame immediately. + # broadcast_frame pushes downstream (same queue as TranscriptionFrame + # above, so ordering is preserved) and upstream. + await self.broadcast_frame(UserStoppedSpeakingFrame) + self._user_speaking = False + else: + await self.push_frame( + InterimTranscriptionFrame( + transcript_text, + speaker_id, + time_now_iso8601(), + language, + message, + ) ) - ) From cd07937c5dcc413000ede5bbc8a232f477a6cd25 Mon Sep 17 00:00:00 2001 From: zack Date: Thu, 26 Feb 2026 22:18:02 -0500 Subject: [PATCH 0659/1060] Fix missing imports: Add UserStartedSpeakingFrame and UserStoppedSpeakingFrame --- src/pipecat/services/assemblyai/stt.py | 2 ++ 1 file changed, 2 insertions(+) diff --git a/src/pipecat/services/assemblyai/stt.py b/src/pipecat/services/assemblyai/stt.py index edd5ac7b7..9881c145f 100644 --- a/src/pipecat/services/assemblyai/stt.py +++ b/src/pipecat/services/assemblyai/stt.py @@ -26,6 +26,8 @@ from pipecat.frames.frames import ( InterimTranscriptionFrame, StartFrame, TranscriptionFrame, + UserStartedSpeakingFrame, + UserStoppedSpeakingFrame, VADUserStartedSpeakingFrame, VADUserStoppedSpeakingFrame, ) From 3e04f5d05f7095fbf7c51392ab5de711afca95f7 Mon Sep 17 00:00:00 2001 From: Mark Backman Date: Fri, 27 Feb 2026 09:18:15 -0500 Subject: [PATCH 0660/1060] Add GitHub Actions workflow to auto-update docs on PR merge Runs Claude Code Action after PRs merge to main when source files in services/transports/serializers/processors/audio/turns/observers/pipeline are changed. Creates a docs PR on pipecat-ai/docs with targeted edits following the existing update-docs skill instructions. --- .github/workflows/update-docs.yml | 154 ++++++++++++++++++++++++++++++ 1 file changed, 154 insertions(+) create mode 100644 .github/workflows/update-docs.yml diff --git a/.github/workflows/update-docs.yml b/.github/workflows/update-docs.yml new file mode 100644 index 000000000..03323e87f --- /dev/null +++ b/.github/workflows/update-docs.yml @@ -0,0 +1,154 @@ +name: Update Documentation on PR Merge + +on: + pull_request: + types: [closed] + branches: [main] + paths: + - "src/pipecat/services/**" + - "src/pipecat/transports/**" + - "src/pipecat/serializers/**" + - "src/pipecat/processors/**" + - "src/pipecat/audio/**" + - "src/pipecat/turns/**" + - "src/pipecat/observers/**" + - "src/pipecat/pipeline/**" + workflow_dispatch: + inputs: + pr_number: + description: "PR number to generate docs for" + required: true + type: string + +jobs: + update-docs: + if: >- + github.event_name == 'workflow_dispatch' || + github.event.pull_request.merged == true + runs-on: ubuntu-latest + timeout-minutes: 15 + permissions: + contents: read + pull-requests: read + id-token: write + steps: + - name: Checkout pipecat + uses: actions/checkout@v4 + with: + fetch-depth: 0 + + - name: Checkout docs + uses: actions/checkout@v4 + with: + repository: pipecat-ai/docs + token: ${{ secrets.DOCS_SYNC_TOKEN }} + path: _docs + + - name: Get version info + id: version + run: | + echo "release=$(git describe --tags --abbrev=0 2>/dev/null || echo 'unknown')" >> "$GITHUB_OUTPUT" + echo "dev=$(git describe --tags 2>/dev/null || echo 'unknown')" >> "$GITHUB_OUTPUT" + + - name: Resolve PR number + id: pr + run: | + if [ "${{ github.event_name }}" = "workflow_dispatch" ]; then + echo "number=${{ inputs.pr_number }}" >> "$GITHUB_OUTPUT" + else + echo "number=${{ github.event.pull_request.number }}" >> "$GITHUB_OUTPUT" + fi + + - name: Update documentation + uses: anthropics/claude-code-action@v1 + env: + DOCS_SYNC_TOKEN: ${{ secrets.DOCS_SYNC_TOKEN }} + with: + anthropic_api_key: ${{ secrets.ANTHROPIC_API_KEY }} + prompt: | + You are updating documentation for the pipecat-ai/docs repository based on + changes merged in PR #${{ steps.pr.outputs.number }} of pipecat-ai/pipecat. + + ## Setup + + 1. Read the skill instructions at `.claude/skills/update-docs/SKILL.md` + 2. Read the source-to-doc mapping at `.claude/skills/update-docs/SOURCE_DOC_MAPPING.md` + 3. The docs repository is checked out at `./_docs/` + 4. Current pipecat version: ${{ steps.version.outputs.release }} (release), ${{ steps.version.outputs.dev }} (dev) + + ## Get the diff + + Run `gh pr diff ${{ steps.pr.outputs.number }}` to see what changed in the PR. + Also run `gh pr diff ${{ steps.pr.outputs.number }} --name-only` to get the list of changed files. + Filter to source files matching the directories listed in SKILL.md Step 3. + + If no relevant source files were changed, exit with "No documentation changes needed." + + ## Follow the skill instructions + + Apply the SKILL.md workflow (Steps 3-9) with these adaptations for automation: + + ### Docs path + Use `./_docs/` — it's already checked out. Do not ask for a path. + + ### Branch management + - Branch name: `docs/pr-${{ steps.pr.outputs.number }}` + - Work inside `./_docs/` for all doc edits and git operations + - Check if the branch already exists on the remote: + ```bash + cd _docs && git fetch origin docs/pr-${{ steps.pr.outputs.number }} 2>/dev/null + ``` + - If it exists: check it out (supports workflow re-runs) + - If not: create it from main + + ### Git config + Before committing in `_docs`, set: + ```bash + git config user.name "github-actions[bot]" + git config user.email "github-actions[bot]@users.noreply.github.com" + ``` + + ### No interactive questions + Do not ask questions. If you encounter gaps (unmapped files, missing sections, + ambiguous changes), note them in the PR body under "## Gaps identified". + + ### Creating the docs PR + After committing all changes in `_docs`, push and create a PR: + ```bash + cd _docs + git push -u origin docs/pr-${{ steps.pr.outputs.number }} + GH_TOKEN=$DOCS_SYNC_TOKEN gh pr create \ + --repo pipecat-ai/docs \ + --title "docs: update for pipecat PR #${{ steps.pr.outputs.number }}" \ + --body "$(cat <<'BODY' + Automated documentation update for [pipecat PR #${{ steps.pr.outputs.number }}](https://github.com/pipecat-ai/pipecat/pull/${{ steps.pr.outputs.number }}). + + Pipecat version: ${{ steps.version.outputs.release }} (${{ steps.version.outputs.dev }}) + + ## Changes + + + ## Gaps identified + + BODY + )" + ``` + + ### Re-run handling + If `gh pr create` fails because a PR from that branch already exists, + push the updated commits and use `gh pr edit` to update the body instead. + + ### No-op + If after analyzing the diff you determine no documentation changes are needed + (e.g., only skip-listed files changed, or changes don't affect public API docs), + exit cleanly without creating a branch or PR. Output "No documentation changes needed." + + ## Important rules + - Only modify files inside `./_docs/` — never modify pipecat source code + - Follow the conservative editing rules from SKILL.md Step 6 + - Read each doc page fully before editing (SKILL.md Guidelines) + - Use `GH_TOKEN=$DOCS_SYNC_TOKEN` for all `gh` commands targeting pipecat-ai/docs + claude_args: | + --model claude-sonnet-4-5-20250929 + --max-turns 30 + --allowedTools "Read,Write,Edit,Glob,Grep,Bash" From c259a6a73bcc8ad4b571aa974f4f7f078d5380af Mon Sep 17 00:00:00 2001 From: Mark Backman Date: Thu, 26 Feb 2026 19:52:34 -0500 Subject: [PATCH 0661/1060] Deprecate processing metrics (ProcessingMetricsData) MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit Add deprecation warnings to start_processing_metrics() and stop_processing_metrics() on FrameProcessorMetrics and FrameProcessor. Mark ProcessingMetricsData as deprecated in docstring. All existing behavior is preserved — the warnings inform users that these will be removed in a future version. --- changelog/3852.deprecated.md | 1 + src/pipecat/metrics/metrics.py | 4 ++++ src/pipecat/processors/frame_processor.py | 16 ++++++++++++++++ .../metrics/frame_processor_metrics.py | 8 ++++++++ 4 files changed, 29 insertions(+) create mode 100644 changelog/3852.deprecated.md diff --git a/changelog/3852.deprecated.md b/changelog/3852.deprecated.md new file mode 100644 index 000000000..666c7c58a --- /dev/null +++ b/changelog/3852.deprecated.md @@ -0,0 +1 @@ +- Deprecated `ProcessingMetricsData` and `start_processing_metrics()`/`stop_processing_metrics()` on `FrameProcessor` and `FrameProcessorMetrics`. These metrics don't accurately depict a service's performance. Instead, TTFB metrics are recommended. Processing metrics will be removed in the 1.0.0 version. diff --git a/src/pipecat/metrics/metrics.py b/src/pipecat/metrics/metrics.py index 2030306e5..37ab99447 100644 --- a/src/pipecat/metrics/metrics.py +++ b/src/pipecat/metrics/metrics.py @@ -41,6 +41,10 @@ class TTFBMetricsData(MetricsData): class ProcessingMetricsData(MetricsData): """General processing time metrics data. + .. deprecated:: 0.0.104 + Processing metrics are deprecated and will be removed in a future version. + Use TTFB metrics instead. + Parameters: value: Processing time measurement in seconds. """ diff --git a/src/pipecat/processors/frame_processor.py b/src/pipecat/processors/frame_processor.py index baa52cc70..3e90968fe 100644 --- a/src/pipecat/processors/frame_processor.py +++ b/src/pipecat/processors/frame_processor.py @@ -441,19 +441,35 @@ class FrameProcessor(BaseObject): if frame: await self.push_frame(frame) + _processing_metrics_warned = False + async def start_processing_metrics(self, *, start_time: Optional[float] = None): """Start processing metrics collection. + .. deprecated:: 0.0.104 + Processing metrics are deprecated and will be removed in a future version. + Use TTFB metrics instead. + Args: start_time: Optional timestamp to use as the start time. If None, uses the current time. """ if self.can_generate_metrics() and self.metrics_enabled: + if not FrameProcessor._processing_metrics_warned: + FrameProcessor._processing_metrics_warned = True + logger.warning( + "Processing metrics are deprecated and will be removed in a future version. " + "Use TTFB metrics instead." + ) await self._metrics.start_processing_metrics(start_time=start_time) async def stop_processing_metrics(self, *, end_time: Optional[float] = None): """Stop processing metrics collection and push results. + .. deprecated:: 0.0.104 + Processing metrics are deprecated and will be removed in a future version. + Use TTFB metrics instead. + Args: end_time: Optional timestamp to use as the end time. If None, uses the current time. diff --git a/src/pipecat/processors/metrics/frame_processor_metrics.py b/src/pipecat/processors/metrics/frame_processor_metrics.py index 7a52895a2..ef637b5ad 100644 --- a/src/pipecat/processors/metrics/frame_processor_metrics.py +++ b/src/pipecat/processors/metrics/frame_processor_metrics.py @@ -150,6 +150,10 @@ class FrameProcessorMetrics(BaseObject): async def start_processing_metrics(self, *, start_time: Optional[float] = None): """Start measuring processing time. + .. deprecated:: 0.0.104 + Processing metrics are deprecated and will be removed in a future version. + Use TTFB metrics instead. + Args: start_time: Optional timestamp to use as the start time. If None, uses the current time. @@ -159,6 +163,10 @@ class FrameProcessorMetrics(BaseObject): async def stop_processing_metrics(self, *, end_time: Optional[float] = None): """Stop processing time measurement and generate metrics frame. + .. deprecated:: 0.0.104 + Processing metrics are deprecated and will be removed in a future version. + Use TTFB metrics instead. + Args: end_time: Optional timestamp to use as the end time. If None, uses the current time. From deba2515f9706b2d37e7dfeb0f547eb0dc9d2041 Mon Sep 17 00:00:00 2001 From: filipi87 Date: Fri, 27 Feb 2026 11:56:36 -0300 Subject: [PATCH 0662/1060] Added a new LLMAssistantPushAggregationFrame control frame that signals LLMAssistantAggregator to immediately flush its text buffer to the conversation context --- src/pipecat/frames/frames.py | 10 ++++++++++ .../processors/aggregators/llm_response_universal.py | 3 +++ 2 files changed, 13 insertions(+) diff --git a/src/pipecat/frames/frames.py b/src/pipecat/frames/frames.py index 55ae975d1..bbc065969 100644 --- a/src/pipecat/frames/frames.py +++ b/src/pipecat/frames/frames.py @@ -1990,6 +1990,16 @@ class LLMFullResponseEndFrame(ControlFrame): self.skip_tts = None +@dataclass +class LLMAssistantPushAggregationFrame(ControlFrame): + """Frame that forces the LLM assistant aggregator to push its current aggregation to context. + + When received by ``LLMAssistantAggregator``, any text that has been accumulated + in the aggregation buffer is immediately committed to the conversation context as + an assistant message, without waiting for an ``LLMFullResponseEndFrame``. + """ + + @dataclass class LLMContextSummaryRequestFrame(ControlFrame): """Frame requesting context summarization from an LLM service. diff --git a/src/pipecat/processors/aggregators/llm_response_universal.py b/src/pipecat/processors/aggregators/llm_response_universal.py index 4a28b38d5..b255748e0 100644 --- a/src/pipecat/processors/aggregators/llm_response_universal.py +++ b/src/pipecat/processors/aggregators/llm_response_universal.py @@ -35,6 +35,7 @@ from pipecat.frames.frames import ( InputAudioRawFrame, InterimTranscriptionFrame, InterruptionFrame, + LLMAssistantPushAggregationFrame, LLMContextAssistantTimestampFrame, LLMContextFrame, LLMContextSummaryRequestFrame, @@ -879,6 +880,8 @@ class LLMAssistantAggregator(LLMContextAggregator): elif isinstance(frame, (EndFrame, CancelFrame)): await self._handle_end_or_cancel(frame) await self.push_frame(frame, direction) + elif isinstance(frame, LLMAssistantPushAggregationFrame): + await self.push_aggregation() elif isinstance(frame, LLMFullResponseStartFrame): await self._handle_llm_start(frame) elif isinstance(frame, LLMFullResponseEndFrame): From bc6f8e51de242a18743af90126b9ac39c272c86c Mon Sep 17 00:00:00 2001 From: filipi87 Date: Fri, 27 Feb 2026 11:56:44 -0300 Subject: [PATCH 0663/1060] Fixed TTSSpeakFrame not automatically committing spoken text to the conversation context when used outside of an LLM response (e.g., for bot greeting messages or injected speech) --- src/pipecat/services/tts_service.py | 21 +++++++++++++++++++-- 1 file changed, 19 insertions(+), 2 deletions(-) diff --git a/src/pipecat/services/tts_service.py b/src/pipecat/services/tts_service.py index c6d2672d6..4285e14f9 100644 --- a/src/pipecat/services/tts_service.py +++ b/src/pipecat/services/tts_service.py @@ -39,6 +39,7 @@ from pipecat.frames.frames import ( Frame, InterimTranscriptionFrame, InterruptionFrame, + LLMAssistantPushAggregationFrame, LLMFullResponseEndFrame, LLMFullResponseStartFrame, StartFrame, @@ -67,10 +68,16 @@ class TTSContext: """Context information for a TTS request. Attributes: - append_to_context: Whether this TTS output should be appended to the conversation context. + append_to_context: Whether this TTS output should be appended to the + conversation context after it is spoken. + push_assistant_aggregation: Whether to push an + ``LLMAssistantPushAggregationFrame`` after the TTS has finished + speaking, forcing the assistant aggregator to commit its current + text buffer to the conversation context. """ append_to_context: bool = True + push_assistant_aggregation: Optional[bool] = False class TextAggregationMode(str, Enum): @@ -641,10 +648,13 @@ class TTSService(AIService): elif isinstance(frame, TTSSpeakFrame): # Store if we were processing text or not so we can set it back. processing_text = self._processing_text + # If we are not receiving text from the LLM, we can assume that the SpeakFrame should be automatically added to the context + push_assistant_aggregation = frame.append_to_context and not self._llm_response_started # Assumption: text in TTSSpeakFrame does not include inter-frame spaces await self._push_tts_frames( AggregatedTextFrame(frame.text, AggregationType.SENTENCE), append_tts_text_to_context=frame.append_to_context, + push_assistant_aggregation=push_assistant_aggregation, ) # We pause processing incoming frames because we are sending data to # the TTS. We pause to avoid audio overlapping. @@ -809,6 +819,7 @@ class TTSService(AIService): src_frame: AggregatedTextFrame, includes_inter_frame_spaces: Optional[bool] = False, append_tts_text_to_context: Optional[bool] = True, + push_assistant_aggregation: Optional[bool] = False, ): type = src_frame.aggregated_by text = src_frame.text @@ -876,7 +887,8 @@ class TTSService(AIService): self._tts_contexts[context_id] = TTSContext( append_to_context=append_tts_text_to_context if append_tts_text_to_context is not None - else True + else True, + push_assistant_aggregation=push_assistant_aggregation, ) # Apply any final text preparation (e.g., trailing space) @@ -905,6 +917,8 @@ class TTSService(AIService): if append_tts_text_to_context is not None: frame.append_to_context = append_tts_text_to_context await self.push_frame(frame) + if push_assistant_aggregation: + await self.push_frame(LLMAssistantPushAggregationFrame()) async def _stop_frame_handler(self): has_started = False @@ -988,6 +1002,9 @@ class TTSService(AIService): frame = TTSStoppedFrame() frame.pts = last_pts frame.context_id = context_id + if context_id in self._tts_contexts: + if self._tts_contexts[context_id].push_assistant_aggregation: + await self.push_frame(LLMAssistantPushAggregationFrame()) else: # Assumption: word-by-word text frames don't include spaces, so # we can rely on the default includes_inter_frame_spaces=False From 1f45e80f9d6681004865caab9665fb5a5e37fdee Mon Sep 17 00:00:00 2001 From: filipi87 Date: Fri, 27 Feb 2026 11:56:52 -0300 Subject: [PATCH 0664/1060] Updated the 52-live-translation.py example to demonstrate the fix --- examples/foundational/52-live-translation.py | 9 +++++++++ 1 file changed, 9 insertions(+) diff --git a/examples/foundational/52-live-translation.py b/examples/foundational/52-live-translation.py index 30583c1b8..861d23e37 100644 --- a/examples/foundational/52-live-translation.py +++ b/examples/foundational/52-live-translation.py @@ -11,6 +11,7 @@ from dotenv import load_dotenv from loguru import logger from pipecat.audio.vad.silero import SileroVADAnalyzer +from pipecat.frames.frames import TTSSpeakFrame from pipecat.pipeline.pipeline import Pipeline from pipecat.pipeline.runner import PipelineRunner from pipecat.pipeline.task import PipelineParams, PipelineTask @@ -110,6 +111,14 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): @transport.event_handler("on_client_connected") async def on_client_connected(transport, client): logger.info(f"Client connected") + await task.queue_frames( + [ + TTSSpeakFrame( + text="Hello, welcome to live translation. Everything you say will be automatically translated to Spanish. Let's begin!", + append_to_context=True, + ), + ] + ) @transport.event_handler("on_client_disconnected") async def on_client_disconnected(transport, client): From d701c3427c968c963670e8b9dc27c5fc24abb838 Mon Sep 17 00:00:00 2001 From: filipi87 Date: Fri, 27 Feb 2026 11:57:03 -0300 Subject: [PATCH 0665/1060] Changelog entry for the TTSSpeakFrame fix. --- changelog/3845.fixed.md | 1 + 1 file changed, 1 insertion(+) create mode 100644 changelog/3845.fixed.md diff --git a/changelog/3845.fixed.md b/changelog/3845.fixed.md new file mode 100644 index 000000000..423853700 --- /dev/null +++ b/changelog/3845.fixed.md @@ -0,0 +1 @@ +- Fixed `TTSSpeakFrame` not committing spoken text to the conversation context when used outside of an LLM response (e.g., bot greetings or injected speech). \ No newline at end of file From 3b427a47b64685a8f48b19ed80d101d2f57f0e3d Mon Sep 17 00:00:00 2001 From: filipi87 Date: Fri, 27 Feb 2026 11:57:11 -0300 Subject: [PATCH 0666/1060] Fixing Piper test. --- tests/test_piper_tts.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/tests/test_piper_tts.py b/tests/test_piper_tts.py index 0ce14bd85..662b9a40c 100644 --- a/tests/test_piper_tts.py +++ b/tests/test_piper_tts.py @@ -125,7 +125,7 @@ async def test_run_piper_tts_error(aiohttp_client): ) frames_to_send = [ - TTSSpeakFrame(text="Error case."), + TTSSpeakFrame(text="Error case.", append_to_context=False), ] expected_down_frames = [AggregatedTextFrame, TTSStoppedFrame, TTSTextFrame] From 3a32d91c66adbb3b5ea09b70f5f7a7bfbab299c1 Mon Sep 17 00:00:00 2001 From: Mark Backman Date: Fri, 27 Feb 2026 10:21:10 -0500 Subject: [PATCH 0667/1060] Set finalized flag on ElevenLabs Realtime STT transcriptions for manual commit strategy --- src/pipecat/services/elevenlabs/stt.py | 6 ++++++ 1 file changed, 6 insertions(+) diff --git a/src/pipecat/services/elevenlabs/stt.py b/src/pipecat/services/elevenlabs/stt.py index 5422fb193..0cf13121e 100644 --- a/src/pipecat/services/elevenlabs/stt.py +++ b/src/pipecat/services/elevenlabs/stt.py @@ -861,6 +861,8 @@ class ElevenLabsRealtimeSTTService(WebsocketSTTService): await self._handle_transcription(text, True, language) + finalized = self._settings.commit_strategy == CommitStrategy.MANUAL + await self.push_frame( TranscriptionFrame( text, @@ -868,6 +870,7 @@ class ElevenLabsRealtimeSTTService(WebsocketSTTService): time_now_iso8601(), language, result=data, + finalized=finalized, ) ) @@ -902,6 +905,8 @@ class ElevenLabsRealtimeSTTService(WebsocketSTTService): await self._handle_transcription(text, True, language) + finalized = self._settings.commit_strategy == CommitStrategy.MANUAL + # This message is sent after committed_transcript when include_timestamps=true. # It contains the full transcript data including text and word-level timestamps. await self.push_frame( @@ -911,5 +916,6 @@ class ElevenLabsRealtimeSTTService(WebsocketSTTService): time_now_iso8601(), language, result=data, + finalized=finalized, ) ) From 601822e3e5fda2aa6f9de79dda646f88266589c5 Mon Sep 17 00:00:00 2001 From: Mark Backman Date: Fri, 27 Feb 2026 10:25:48 -0500 Subject: [PATCH 0668/1060] Add changelog for PR #3865 --- changelog/3865.changed.md | 1 + 1 file changed, 1 insertion(+) create mode 100644 changelog/3865.changed.md diff --git a/changelog/3865.changed.md b/changelog/3865.changed.md new file mode 100644 index 000000000..7a70eb0d7 --- /dev/null +++ b/changelog/3865.changed.md @@ -0,0 +1 @@ +- `ElevenLabsRealtimeSTTService` now sets `TranscriptionFrame.finalized` to `True` when using `CommitStrategy.MANUAL`. From 41d6470e4aa137ee1fab2a106a5926f387497ba4 Mon Sep 17 00:00:00 2001 From: Mark Backman Date: Fri, 27 Feb 2026 10:39:37 -0500 Subject: [PATCH 0669/1060] Fix docs workflow: add auto-docs label, remove version info --- .github/workflows/update-docs.yml | 10 +--------- 1 file changed, 1 insertion(+), 9 deletions(-) diff --git a/.github/workflows/update-docs.yml b/.github/workflows/update-docs.yml index 03323e87f..27453e74e 100644 --- a/.github/workflows/update-docs.yml +++ b/.github/workflows/update-docs.yml @@ -44,12 +44,6 @@ jobs: token: ${{ secrets.DOCS_SYNC_TOKEN }} path: _docs - - name: Get version info - id: version - run: | - echo "release=$(git describe --tags --abbrev=0 2>/dev/null || echo 'unknown')" >> "$GITHUB_OUTPUT" - echo "dev=$(git describe --tags 2>/dev/null || echo 'unknown')" >> "$GITHUB_OUTPUT" - - name: Resolve PR number id: pr run: | @@ -74,7 +68,6 @@ jobs: 1. Read the skill instructions at `.claude/skills/update-docs/SKILL.md` 2. Read the source-to-doc mapping at `.claude/skills/update-docs/SOURCE_DOC_MAPPING.md` 3. The docs repository is checked out at `./_docs/` - 4. Current pipecat version: ${{ steps.version.outputs.release }} (release), ${{ steps.version.outputs.dev }} (dev) ## Get the diff @@ -119,12 +112,11 @@ jobs: git push -u origin docs/pr-${{ steps.pr.outputs.number }} GH_TOKEN=$DOCS_SYNC_TOKEN gh pr create \ --repo pipecat-ai/docs \ + --label auto-docs \ --title "docs: update for pipecat PR #${{ steps.pr.outputs.number }}" \ --body "$(cat <<'BODY' Automated documentation update for [pipecat PR #${{ steps.pr.outputs.number }}](https://github.com/pipecat-ai/pipecat/pull/${{ steps.pr.outputs.number }}). - Pipecat version: ${{ steps.version.outputs.release }} (${{ steps.version.outputs.dev }}) - ## Changes From aa6d3b38b38793f948c1aa8ac5fb3b1b8d644e5d Mon Sep 17 00:00:00 2001 From: filipi87 Date: Fri, 27 Feb 2026 12:53:25 -0300 Subject: [PATCH 0670/1060] Add explanatory comments for LLMSpecificMessage guards in context summarization, amd fixed the missing guard in LLMContextSummarizer._apply_summary when searching for the first system message. --- .../aggregators/llm_context_summarizer.py | 16 +++++++++++++--- .../utils/context/llm_context_summarization.py | 15 ++++++++++++++- 2 files changed, 27 insertions(+), 4 deletions(-) diff --git a/src/pipecat/processors/aggregators/llm_context_summarizer.py b/src/pipecat/processors/aggregators/llm_context_summarizer.py index a1a613ccc..7886fcf12 100644 --- a/src/pipecat/processors/aggregators/llm_context_summarizer.py +++ b/src/pipecat/processors/aggregators/llm_context_summarizer.py @@ -18,7 +18,7 @@ from pipecat.frames.frames import ( LLMContextSummaryResultFrame, LLMFullResponseStartFrame, ) -from pipecat.processors.aggregators.llm_context import LLMContext +from pipecat.processors.aggregators.llm_context import LLMContext, LLMSpecificMessage from pipecat.utils.asyncio.task_manager import BaseTaskManager from pipecat.utils.base_object import BaseObject from pipecat.utils.context.llm_context_summarization import ( @@ -290,8 +290,18 @@ class LLMContextSummarizer(BaseObject): """ messages = self._context.messages - # Find the first system message to preserve - first_system_msg = next((msg for msg in messages if msg.get("role") == "system"), None) + # Find the first system message to preserve. LLMSpecificMessage instances are excluded + # because they are not dict-like and never represent a system message; they hold + # service-specific metadata (e.g. thinking blocks) that is always paired with a + # standard message. + first_system_msg = next( + ( + msg + for msg in messages + if not isinstance(msg, LLMSpecificMessage) and msg.get("role") == "system" + ), + None, + ) # Get recent messages to keep recent_messages = messages[last_summarized_index + 1 :] diff --git a/src/pipecat/utils/context/llm_context_summarization.py b/src/pipecat/utils/context/llm_context_summarization.py index 06551e3bb..537cc91ab 100644 --- a/src/pipecat/utils/context/llm_context_summarization.py +++ b/src/pipecat/utils/context/llm_context_summarization.py @@ -188,6 +188,8 @@ class LLMContextSummarizationUtil: total = 0 for message in context.messages: + # LLMSpecificMessage holds service-specific data (e.g. thinking blocks, + # thought signatures). Skipping them here for now. if isinstance(message, LLMSpecificMessage): continue @@ -251,6 +253,9 @@ class LLMContextSummarizationUtil: for i in range(start_idx, len(messages)): msg = messages[i] + # LLMSpecificMessage instances (e.g. thinking blocks) never carry tool_call or + # tool_call_id fields, so they cannot affect the pending-call tracking. Skipping + # them avoids an AttributeError. if isinstance(msg, LLMSpecificMessage): continue @@ -302,7 +307,10 @@ class LLMContextSummarizationUtil: if len(messages) <= min_messages_to_keep: return LLMMessagesToSummarize(messages=[], last_summarized_index=-1) - # Find first system message index + # Find first system message index. LLMSpecificMessage instances are excluded because + # they are not dict-like and never represent a system message; they hold + # service-specific metadata (e.g. thinking blocks) that is always paired with a + # standard message. first_system_index = next( ( i @@ -367,6 +375,11 @@ class LLMContextSummarizationUtil: transcript_parts = [] for msg in messages: + # LLMSpecificMessage holds service-specific internal data (e.g. Anthropic thinking + # blocks, Gemini thought signatures). This data is not meaningful as plain text for + # a summarization transcript, and the summarizer LLM would not know how to interpret + # it. The conversational content of those turns is already captured by the + # accompanying standard assistant message. if isinstance(msg, LLMSpecificMessage): continue From 790c434a0833939e950b19ac37c5c7e61835bf89 Mon Sep 17 00:00:00 2001 From: Mark Backman Date: Thu, 26 Feb 2026 20:58:06 -0500 Subject: [PATCH 0671/1060] Update summary message role: use user instead of assistant The context summary is information provided to the assistant, not something the assistant said. --- src/pipecat/processors/aggregators/llm_context_summarizer.py | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/src/pipecat/processors/aggregators/llm_context_summarizer.py b/src/pipecat/processors/aggregators/llm_context_summarizer.py index 7886fcf12..4a32d5397 100644 --- a/src/pipecat/processors/aggregators/llm_context_summarizer.py +++ b/src/pipecat/processors/aggregators/llm_context_summarizer.py @@ -306,8 +306,8 @@ class LLMContextSummarizer(BaseObject): # Get recent messages to keep recent_messages = messages[last_summarized_index + 1 :] - # Create summary message as an assistant message - summary_message = {"role": "assistant", "content": f"Conversation summary: {summary}"} + # Create summary message as an user message + summary_message = {"role": "user", "content": f"Conversation summary: {summary}"} # Reconstruct context new_messages = [] From 945a523eed66536d1ae1330be16e9f710029aa75 Mon Sep 17 00:00:00 2001 From: Mark Backman Date: Thu, 26 Feb 2026 21:03:05 -0500 Subject: [PATCH 0672/1060] Add configurable summary_message_template to LLMContextSummarizationConfig Allows applications to customize how the summary is wrapped when injected into context (e.g., XML tags, custom delimiters) so system prompts can distinguish summaries from live conversation. --- .../processors/aggregators/llm_context_summarizer.py | 6 ++++-- src/pipecat/utils/context/llm_context_summarization.py | 6 ++++++ 2 files changed, 10 insertions(+), 2 deletions(-) diff --git a/src/pipecat/processors/aggregators/llm_context_summarizer.py b/src/pipecat/processors/aggregators/llm_context_summarizer.py index 4a32d5397..a3d65b894 100644 --- a/src/pipecat/processors/aggregators/llm_context_summarizer.py +++ b/src/pipecat/processors/aggregators/llm_context_summarizer.py @@ -306,8 +306,10 @@ class LLMContextSummarizer(BaseObject): # Get recent messages to keep recent_messages = messages[last_summarized_index + 1 :] - # Create summary message as an user message - summary_message = {"role": "user", "content": f"Conversation summary: {summary}"} + # Create summary message as a user message (the summary is context + # provided *to* the assistant, not something the assistant said) + summary_content = self._config.summary_message_template.format(summary=summary) + summary_message = {"role": "user", "content": summary_content} # Reconstruct context new_messages = [] diff --git a/src/pipecat/utils/context/llm_context_summarization.py b/src/pipecat/utils/context/llm_context_summarization.py index 537cc91ab..7cb07a00c 100644 --- a/src/pipecat/utils/context/llm_context_summarization.py +++ b/src/pipecat/utils/context/llm_context_summarization.py @@ -73,6 +73,11 @@ class LLMContextSummarizationConfig: immediate conversational context. summarization_prompt: Custom prompt for the LLM to use when generating summaries. If None, uses DEFAULT_SUMMARIZATION_PROMPT. + summary_message_template: Template for formatting the summary when + injected into context. Must contain ``{summary}`` as a placeholder + for the generated summary text. Allows applications to wrap the + summary in custom delimiters (e.g., XML tags) so that system + prompts can distinguish summaries from live conversation. """ max_context_tokens: int = 8000 @@ -80,6 +85,7 @@ class LLMContextSummarizationConfig: max_unsummarized_messages: int = 20 min_messages_after_summary: int = 4 summarization_prompt: Optional[str] = None + summary_message_template: str = "Conversation summary: {summary}" def __post_init__(self): """Validate configuration parameters.""" From a489bfaf00685eb304bc330e1835070dd9377f2b Mon Sep 17 00:00:00 2001 From: Mark Backman Date: Thu, 26 Feb 2026 21:22:52 -0500 Subject: [PATCH 0673/1060] Add optional dedicated LLM for context summarization Adds an field to LLMContextSummarizationConfig that allows routing summarization to a separate LLM service (e.g., Gemini Flash) instead of the pipeline's primary model. This avoids paying for expensive inference when compressing context in long-running sessions. --- .../aggregators/llm_response_universal.py | 53 +++++++++++++++++-- .../context/llm_context_summarization.py | 11 +++- 2 files changed, 60 insertions(+), 4 deletions(-) diff --git a/src/pipecat/processors/aggregators/llm_response_universal.py b/src/pipecat/processors/aggregators/llm_response_universal.py index b255748e0..217d930e7 100644 --- a/src/pipecat/processors/aggregators/llm_response_universal.py +++ b/src/pipecat/processors/aggregators/llm_response_universal.py @@ -16,7 +16,7 @@ import json import warnings from abc import abstractmethod from dataclasses import dataclass, field -from typing import Any, Dict, List, Literal, Optional, Set, Type +from typing import TYPE_CHECKING, Any, Dict, List, Literal, Optional, Set, Type from loguru import logger @@ -39,6 +39,7 @@ from pipecat.frames.frames import ( LLMContextAssistantTimestampFrame, LLMContextFrame, LLMContextSummaryRequestFrame, + LLMContextSummaryResultFrame, LLMFullResponseEndFrame, LLMFullResponseStartFrame, LLMMessagesAppendFrame, @@ -83,6 +84,9 @@ from pipecat.utils.context.llm_context_summarization import LLMContextSummarizat from pipecat.utils.string import TextPartForConcatenation, concatenate_aggregated_text from pipecat.utils.time import time_now_iso8601 +if TYPE_CHECKING: + from pipecat.services.llm_service import LLMService + @dataclass class LLMUserAggregatorParams: @@ -1248,13 +1252,56 @@ class LLMAssistantAggregator(LLMContextAggregator): ): """Handle summarization request from the summarizer. - Push the request frame UPSTREAM to the LLM service for processing. + If a dedicated summarization LLM is configured, generates the summary + directly and feeds the result to the summarizer. Otherwise, pushes the + request frame upstream to the pipeline's primary LLM service. Args: summarizer: The summarizer that generated the request. frame: The summarization request frame to broadcast. """ - await self.push_frame(frame, FrameDirection.UPSTREAM) + summarization_llm = ( + self._params.context_summarization_config.llm + if self._params.context_summarization_config + else None + ) + + if summarization_llm: + self.create_task(self._generate_summary_with_dedicated_llm(summarization_llm, frame)) + else: + await self.push_frame(frame, FrameDirection.UPSTREAM) + + async def _generate_summary_with_dedicated_llm( + self, llm: "LLMService", frame: LLMContextSummaryRequestFrame + ): + """Generate summary using a dedicated LLM service. + + Calls the dedicated LLM's _generate_summary directly and feeds the + result back to the summarizer, bypassing the pipeline. + + Args: + llm: The dedicated LLM service to use for summarization. + frame: The summarization request frame. + """ + try: + summary, last_index = await llm._generate_summary(frame) + result_frame = LLMContextSummaryResultFrame( + request_id=frame.request_id, + summary=summary, + last_summarized_index=last_index, + ) + except Exception as e: + error = f"Error generating context summary: {e}" + await self.push_error(error, exception=e) + result_frame = LLMContextSummaryResultFrame( + request_id=frame.request_id, + summary="", + last_summarized_index=-1, + error=f"Error generating context summary: {e}", + ) + + if self._summarizer: + await self._summarizer.process_frame(result_frame) class LLMContextAggregatorPair: diff --git a/src/pipecat/utils/context/llm_context_summarization.py b/src/pipecat/utils/context/llm_context_summarization.py index 7cb07a00c..2dcd28fce 100644 --- a/src/pipecat/utils/context/llm_context_summarization.py +++ b/src/pipecat/utils/context/llm_context_summarization.py @@ -11,7 +11,10 @@ context when token limits are reached, enabling efficient long-running conversat """ from dataclasses import dataclass -from typing import List, Optional +from typing import TYPE_CHECKING, List, Optional + +if TYPE_CHECKING: + from pipecat.services.llm_service import LLMService from loguru import logger @@ -78,6 +81,11 @@ class LLMContextSummarizationConfig: for the generated summary text. Allows applications to wrap the summary in custom delimiters (e.g., XML tags) so that system prompts can distinguish summaries from live conversation. + llm: Optional separate LLM service for generating summaries. When set, + summarization requests are sent to this service instead of the + pipeline's primary LLM. Useful for routing summarization to a + cheaper/faster model (e.g., Gemini Flash) while keeping an + expensive model for conversation. If None, uses the pipeline LLM. """ max_context_tokens: int = 8000 @@ -86,6 +94,7 @@ class LLMContextSummarizationConfig: min_messages_after_summary: int = 4 summarization_prompt: Optional[str] = None summary_message_template: str = "Conversation summary: {summary}" + llm: Optional["LLMService"] = None def __post_init__(self): """Validate configuration parameters.""" From 50710e9c3f7c07d4906a32faab9ca57930f6f20e Mon Sep 17 00:00:00 2001 From: Mark Backman Date: Thu, 26 Feb 2026 21:31:04 -0500 Subject: [PATCH 0674/1060] Add summarization timeout to prevent hung LLM calls Adds a configurable summarization_timeout (default 120s) that cancels summary generation if the LLM hangs. On timeout, an error result is returned so _summarization_in_progress resets and future summarizations are unblocked. --- src/pipecat/frames/frames.py | 3 +++ .../aggregators/llm_context_summarizer.py | 1 + .../aggregators/llm_response_universal.py | 25 +++++++++++++++---- src/pipecat/services/llm_service.py | 12 ++++++++- .../context/llm_context_summarization.py | 5 ++++ 5 files changed, 40 insertions(+), 6 deletions(-) diff --git a/src/pipecat/frames/frames.py b/src/pipecat/frames/frames.py index bbc065969..fbb0294a3 100644 --- a/src/pipecat/frames/frames.py +++ b/src/pipecat/frames/frames.py @@ -2019,6 +2019,8 @@ class LLMContextSummaryRequestFrame(ControlFrame): the summary text. summarization_prompt: System prompt instructing the LLM how to generate the summary. + summarization_timeout: Maximum time in seconds for the LLM to generate a + summary. None means no timeout. """ request_id: str @@ -2026,6 +2028,7 @@ class LLMContextSummaryRequestFrame(ControlFrame): min_messages_to_keep: int target_context_tokens: int summarization_prompt: str + summarization_timeout: Optional[float] = None @dataclass diff --git a/src/pipecat/processors/aggregators/llm_context_summarizer.py b/src/pipecat/processors/aggregators/llm_context_summarizer.py index a3d65b894..2618b558b 100644 --- a/src/pipecat/processors/aggregators/llm_context_summarizer.py +++ b/src/pipecat/processors/aggregators/llm_context_summarizer.py @@ -218,6 +218,7 @@ class LLMContextSummarizer(BaseObject): min_messages_to_keep=min_keep, target_context_tokens=self._config.target_context_tokens, summarization_prompt=self._config.summary_prompt, + summarization_timeout=self._config.summarization_timeout, ) # Emit event for aggregator to broadcast diff --git a/src/pipecat/processors/aggregators/llm_response_universal.py b/src/pipecat/processors/aggregators/llm_response_universal.py index 217d930e7..361b2c8a6 100644 --- a/src/pipecat/processors/aggregators/llm_response_universal.py +++ b/src/pipecat/processors/aggregators/llm_response_universal.py @@ -1284,20 +1284,35 @@ class LLMAssistantAggregator(LLMContextAggregator): frame: The summarization request frame. """ try: - summary, last_index = await llm._generate_summary(frame) + if frame.summarization_timeout: + summary, last_index = await asyncio.wait_for( + llm._generate_summary(frame), + timeout=frame.summarization_timeout, + ) + else: + summary, last_index = await llm._generate_summary(frame) result_frame = LLMContextSummaryResultFrame( request_id=frame.request_id, summary=summary, last_summarized_index=last_index, ) - except Exception as e: - error = f"Error generating context summary: {e}" - await self.push_error(error, exception=e) + except asyncio.TimeoutError: + error = f"Context summarization timed out after {frame.summarization_timeout}s" + logger.error(f"{self}: {error}") result_frame = LLMContextSummaryResultFrame( request_id=frame.request_id, summary="", last_summarized_index=-1, - error=f"Error generating context summary: {e}", + error=error, + ) + except Exception as e: + error = f"Error generating context summary: {e}" + await self.push_error(error_msg=error, exception=e) + result_frame = LLMContextSummaryResultFrame( + request_id=frame.request_id, + summary="", + last_summarized_index=-1, + error=error, ) if self._summarizer: diff --git a/src/pipecat/services/llm_service.py b/src/pipecat/services/llm_service.py index a06423754..86048ccbe 100644 --- a/src/pipecat/services/llm_service.py +++ b/src/pipecat/services/llm_service.py @@ -437,7 +437,17 @@ class LLMService(UserTurnCompletionLLMServiceMixin, AIService): error = None try: - summary, last_index = await self._generate_summary(frame) + if frame.summarization_timeout: + summary, last_index = await asyncio.wait_for( + self._generate_summary(frame), + timeout=frame.summarization_timeout, + ) + else: + summary, last_index = await self._generate_summary(frame) + except asyncio.TimeoutError: + await self.push_error( + error_msg=f"Context summarization timed out after {frame.summarization_timeout}s" + ) except Exception as e: error = f"Error generating context summary: {e}" await self.push_error(error, exception=e) diff --git a/src/pipecat/utils/context/llm_context_summarization.py b/src/pipecat/utils/context/llm_context_summarization.py index 2dcd28fce..00dd74fd8 100644 --- a/src/pipecat/utils/context/llm_context_summarization.py +++ b/src/pipecat/utils/context/llm_context_summarization.py @@ -86,6 +86,10 @@ class LLMContextSummarizationConfig: pipeline's primary LLM. Useful for routing summarization to a cheaper/faster model (e.g., Gemini Flash) while keeping an expensive model for conversation. If None, uses the pipeline LLM. + summarization_timeout: Maximum time in seconds to wait for the LLM to + generate a summary. If the call exceeds this timeout, summarization + is aborted with an error and future summarizations are unblocked. + Set to None to disable the timeout. """ max_context_tokens: int = 8000 @@ -95,6 +99,7 @@ class LLMContextSummarizationConfig: summarization_prompt: Optional[str] = None summary_message_template: str = "Conversation summary: {summary}" llm: Optional["LLMService"] = None + summarization_timeout: Optional[float] = 120.0 def __post_init__(self): """Validate configuration parameters.""" From be8ea818c877a2c4319c65749ae719ff876b895b Mon Sep 17 00:00:00 2001 From: Mark Backman Date: Thu, 26 Feb 2026 21:34:01 -0500 Subject: [PATCH 0675/1060] Add on_summary_applied event for observability Emits a SummaryAppliedEvent after context summarization completes, providing message counts so applications can track compression metrics. --- .../aggregators/llm_context_summarizer.py | 47 ++++++++++++++++++- 1 file changed, 45 insertions(+), 2 deletions(-) diff --git a/src/pipecat/processors/aggregators/llm_context_summarizer.py b/src/pipecat/processors/aggregators/llm_context_summarizer.py index 2618b558b..85da9bfa0 100644 --- a/src/pipecat/processors/aggregators/llm_context_summarizer.py +++ b/src/pipecat/processors/aggregators/llm_context_summarizer.py @@ -7,6 +7,7 @@ """This module defines a summarizer for managing LLM context summarization.""" import uuid +from dataclasses import dataclass from typing import Optional from loguru import logger @@ -27,6 +28,25 @@ from pipecat.utils.context.llm_context_summarization import ( ) +@dataclass +class SummaryAppliedEvent: + """Event data emitted when context summarization completes successfully. + + Parameters: + original_message_count: Number of messages before summarization. + new_message_count: Number of messages after summarization. + summarized_message_count: Number of messages that were compressed + into the summary. + preserved_message_count: Number of recent messages preserved + uncompressed. + """ + + original_message_count: int + new_message_count: int + summarized_message_count: int + preserved_message_count: int + + class LLMContextSummarizer(BaseObject): """Summarizer for managing LLM context summarization. @@ -39,6 +59,10 @@ class LLMContextSummarizer(BaseObject): - on_request_summarization: Emitted when summarization should be triggered. The aggregator should broadcast this frame to the LLM service. + - on_summary_applied: Emitted after a summary has been successfully applied + to the context. Receives a SummaryAppliedEvent with metrics about the + compression. + Example:: @summarizer.event_handler("on_request_summarization") @@ -49,6 +73,10 @@ class LLMContextSummarizer(BaseObject): context=frame.context, ... ) + + @summarizer.event_handler("on_summary_applied") + async def on_summary_applied(summarizer, event: SummaryAppliedEvent): + logger.info(f"Compressed {event.original_message_count} -> {event.new_message_count} messages") """ def __init__( @@ -74,6 +102,7 @@ class LLMContextSummarizer(BaseObject): self._pending_summary_request_id: Optional[str] = None self._register_event_handler("on_request_summarization", sync=True) + self._register_event_handler("on_summary_applied") @property def task_manager(self) -> BaseTaskManager: @@ -320,9 +349,23 @@ class LLMContextSummarizer(BaseObject): new_messages.extend(recent_messages) # Update context + original_message_count = len(messages) + num_system_preserved = 1 if first_system_msg else 0 self._context.set_messages(new_messages) + # Messages actually summarized = index range minus the preserved system message + summarized_count = last_summarized_index + 1 - num_system_preserved + logger.info( - f"{self}: Applied context summary, compressed {last_summarized_index + 1} messages " - f"into summary. Context now has {len(new_messages)} messages (was {len(messages)})" + f"{self}: Applied context summary, compressed {summarized_count} messages " + f"into summary. Context now has {len(new_messages)} messages (was {original_message_count})" ) + + # Emit event for observability + event = SummaryAppliedEvent( + original_message_count=original_message_count, + new_message_count=len(new_messages), + summarized_message_count=summarized_count, + preserved_message_count=len(recent_messages) + num_system_preserved, + ) + await self._call_event_handler("on_summary_applied", event) From 712305c5b14fbebd22fc6368309f4f7f13a9373d Mon Sep 17 00:00:00 2001 From: Mark Backman Date: Thu, 26 Feb 2026 21:45:22 -0500 Subject: [PATCH 0676/1060] Add example 54c showing custom context summarization --- .../54-context-summarization-openai.py | 23 +- .../54a-context-summarization-google.py | 23 +- ...54c-context-summarization-dedicated-llm.py | 231 ++++++++++++++++++ 3 files changed, 261 insertions(+), 16 deletions(-) create mode 100644 examples/foundational/54c-context-summarization-dedicated-llm.py diff --git a/examples/foundational/54-context-summarization-openai.py b/examples/foundational/54-context-summarization-openai.py index 652a3af13..45f27854f 100644 --- a/examples/foundational/54-context-summarization-openai.py +++ b/examples/foundational/54-context-summarization-openai.py @@ -20,14 +20,13 @@ from loguru import logger from pipecat.adapters.schemas.function_schema import FunctionSchema from pipecat.adapters.schemas.tools_schema import ToolsSchema -from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3 from pipecat.audio.vad.silero import SileroVADAnalyzer -from pipecat.audio.vad.vad_analyzer import VADParams from pipecat.frames.frames import LLMRunFrame from pipecat.pipeline.pipeline import Pipeline from pipecat.pipeline.runner import PipelineRunner from pipecat.pipeline.task import PipelineParams, PipelineTask from pipecat.processors.aggregators.llm_context import LLMContext +from pipecat.processors.aggregators.llm_context_summarizer import SummaryAppliedEvent from pipecat.processors.aggregators.llm_response_universal import ( LLMAssistantAggregatorParams, LLMContextAggregatorPair, @@ -42,8 +41,6 @@ from pipecat.services.openai.llm import OpenAILLMService from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams -from pipecat.turns.user_stop import TurnAnalyzerUserTurnStopStrategy -from pipecat.turns.user_turn_strategies import UserTurnStrategies from pipecat.utils.context.llm_context_summarization import LLMContextSummarizationConfig load_dotenv(override=True) @@ -120,10 +117,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, user_params=LLMUserAggregatorParams( - user_turn_strategies=UserTurnStrategies( - stop=[TurnAnalyzerUserTurnStopStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3())] - ), - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), + vad_analyzer=SileroVADAnalyzer(), ), assistant_params=LLMAssistantAggregatorParams( enable_context_summarization=True, @@ -138,6 +132,19 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): ), ) + # Listen for summarization events + summarizer = assistant_aggregator._summarizer + if summarizer: + + @summarizer.event_handler("on_summary_applied") + async def on_summary_applied(summarizer, event: SummaryAppliedEvent): + logger.info( + f"Context summarized: {event.original_message_count} messages -> " + f"{event.new_message_count} messages " + f"({event.summarized_message_count} summarized, " + f"{event.preserved_message_count} preserved)" + ) + pipeline = Pipeline( [ transport.input(), # Transport user input diff --git a/examples/foundational/54a-context-summarization-google.py b/examples/foundational/54a-context-summarization-google.py index a7fe4ba5e..2ce29e959 100644 --- a/examples/foundational/54a-context-summarization-google.py +++ b/examples/foundational/54a-context-summarization-google.py @@ -20,14 +20,13 @@ from loguru import logger from pipecat.adapters.schemas.function_schema import FunctionSchema from pipecat.adapters.schemas.tools_schema import ToolsSchema -from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3 from pipecat.audio.vad.silero import SileroVADAnalyzer -from pipecat.audio.vad.vad_analyzer import VADParams from pipecat.frames.frames import LLMRunFrame from pipecat.pipeline.pipeline import Pipeline from pipecat.pipeline.runner import PipelineRunner from pipecat.pipeline.task import PipelineParams, PipelineTask from pipecat.processors.aggregators.llm_context import LLMContext +from pipecat.processors.aggregators.llm_context_summarizer import SummaryAppliedEvent from pipecat.processors.aggregators.llm_response_universal import ( LLMAssistantAggregatorParams, LLMContextAggregatorPair, @@ -42,8 +41,6 @@ from pipecat.services.llm_service import FunctionCallParams from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams -from pipecat.turns.user_stop import TurnAnalyzerUserTurnStopStrategy -from pipecat.turns.user_turn_strategies import UserTurnStrategies from pipecat.utils.context.llm_context_summarization import LLMContextSummarizationConfig load_dotenv(override=True) @@ -120,10 +117,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, user_params=LLMUserAggregatorParams( - user_turn_strategies=UserTurnStrategies( - stop=[TurnAnalyzerUserTurnStopStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3())] - ), - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), + vad_analyzer=SileroVADAnalyzer(), ), assistant_params=LLMAssistantAggregatorParams( enable_context_summarization=True, @@ -138,6 +132,19 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): ), ) + # Listen for summarization events + summarizer = assistant_aggregator._summarizer + if summarizer: + + @summarizer.event_handler("on_summary_applied") + async def on_summary_applied(summarizer, event: SummaryAppliedEvent): + logger.info( + f"Context summarized: {event.original_message_count} messages -> " + f"{event.new_message_count} messages " + f"({event.summarized_message_count} summarized, " + f"{event.preserved_message_count} preserved)" + ) + pipeline = Pipeline( [ transport.input(), # Transport user input diff --git a/examples/foundational/54c-context-summarization-dedicated-llm.py b/examples/foundational/54c-context-summarization-dedicated-llm.py new file mode 100644 index 000000000..3b2195e80 --- /dev/null +++ b/examples/foundational/54c-context-summarization-dedicated-llm.py @@ -0,0 +1,231 @@ +# +# Copyright (c) 2024-2026, Daily +# +# SPDX-License-Identifier: BSD 2-Clause License +# + +"""Example demonstrating advanced context summarization configuration. + +This example shows how to customize context summarization with: +- A dedicated cheap/fast LLM for generating summaries (Gemini Flash) +- A custom summary message template (XML tags) +- A custom summarization prompt +- A summarization timeout +- The on_summary_applied event for observability +""" + +import asyncio +import os + +from dotenv import load_dotenv +from loguru import logger + +from pipecat.adapters.schemas.function_schema import FunctionSchema +from pipecat.adapters.schemas.tools_schema import ToolsSchema +from pipecat.audio.vad.silero import SileroVADAnalyzer +from pipecat.frames.frames import LLMRunFrame +from pipecat.pipeline.pipeline import Pipeline +from pipecat.pipeline.runner import PipelineRunner +from pipecat.pipeline.task import PipelineParams, PipelineTask +from pipecat.processors.aggregators.llm_context import LLMContext +from pipecat.processors.aggregators.llm_context_summarizer import SummaryAppliedEvent +from pipecat.processors.aggregators.llm_response_universal import ( + LLMAssistantAggregatorParams, + LLMContextAggregatorPair, + LLMUserAggregatorParams, +) +from pipecat.runner.types import RunnerArguments +from pipecat.runner.utils import create_transport +from pipecat.services.cartesia.tts import CartesiaTTSService +from pipecat.services.deepgram.stt import DeepgramSTTService +from pipecat.services.google import GoogleLLMService +from pipecat.services.llm_service import FunctionCallParams +from pipecat.services.openai.llm import OpenAILLMService +from pipecat.transports.base_transport import BaseTransport, TransportParams +from pipecat.transports.daily.transport import DailyParams +from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams +from pipecat.utils.context.llm_context_summarization import LLMContextSummarizationConfig + +load_dotenv(override=True) + +# We use lambdas to defer transport parameter creation until the transport +# type is selected at runtime. +transport_params = { + "daily": lambda: DailyParams( + audio_in_enabled=True, + audio_out_enabled=True, + ), + "twilio": lambda: FastAPIWebsocketParams( + audio_in_enabled=True, + audio_out_enabled=True, + ), + "webrtc": lambda: TransportParams( + audio_in_enabled=True, + audio_out_enabled=True, + ), +} + +# Custom summarization prompt tailored to the application +CUSTOM_SUMMARIZATION_PROMPT = """Summarize this conversation, preserving: +- Key decisions and agreements +- Important facts and user preferences +- Any pending action items or unresolved questions + +Be concise. Use clear, factual statements grouped by topic. +Omit greetings, small talk, and resolved tangents.""" + + +# Tool functions for the LLM +async def get_current_weather(params: FunctionCallParams): + """Get the current weather.""" + logger.info("Tool called: get_current_weather") + await asyncio.sleep(1) # Simulate some processing + await params.result_callback({"conditions": "nice", "temperature": "75"}) + + +async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): + logger.info("Starting bot") + + stt = DeepgramSTTService(api_key=os.getenv("DEEPGRAM_API_KEY")) + + tts = CartesiaTTSService( + api_key=os.getenv("CARTESIA_API_KEY"), + voice_id="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady + ) + + # Primary LLM for conversation (could be any provider) + llm = OpenAILLMService(api_key=os.getenv("OPENAI_API_KEY")) + + # Dedicated cheap/fast LLM for summarization only + summarization_llm = GoogleLLMService( + api_key=os.getenv("GOOGLE_API_KEY"), + model="gemini-2.5-flash", + ) + + # Register tool functions + llm.register_function("get_current_weather", get_current_weather) + + weather_function = FunctionSchema( + name="get_current_weather", + description="Get the current weather", + properties={ + "location": { + "type": "string", + "description": "The city and state, e.g. San Francisco, CA", + }, + "format": { + "type": "string", + "enum": ["celsius", "fahrenheit"], + "description": "The temperature unit to use. Infer this from the user's location.", + }, + }, + required=["location", "format"], + ) + tools = ToolsSchema(standard_tools=[weather_function]) + + messages = [ + { + "role": "system", + "content": ( + "You are a helpful LLM in a WebRTC call. Your goal is to demonstrate " + "your capabilities in a succinct way. Your output will be spoken aloud, " + "so avoid special characters that can't easily be spoken. Respond to what " + "the user said in a creative and helpful way. You have access to tools to " + "get the current weather - use them when relevant.\n\n" + "When you see a block, it contains a compressed summary " + "of earlier conversation. Use it as reference but don't mention it to the user." + ), + }, + ] + + context = LLMContext(messages, tools=tools) + + # Create aggregators with custom summarization + user_aggregator, assistant_aggregator = LLMContextAggregatorPair( + context, + user_params=LLMUserAggregatorParams( + vad_analyzer=SileroVADAnalyzer(), + ), + assistant_params=LLMAssistantAggregatorParams( + enable_context_summarization=True, + context_summarization_config=LLMContextSummarizationConfig( + # Trigger thresholds (low values to demonstrate quickly) + max_context_tokens=1000, + max_unsummarized_messages=10, + # Summary generation + target_context_tokens=800, + min_messages_after_summary=2, + summarization_prompt=CUSTOM_SUMMARIZATION_PROMPT, + # Custom summary format - wrap in XML tags so the system + # prompt can identify summaries vs. live conversation + summary_message_template="\n{summary}\n", + # Use a dedicated cheap LLM for summarization instead of + # the primary conversation model + llm=summarization_llm, + # Cancel summarization if it takes longer than 60 seconds + summarization_timeout=60.0, + ), + ), + ) + + # Listen for summarization events + summarizer = assistant_aggregator._summarizer + if summarizer: + + @summarizer.event_handler("on_summary_applied") + async def on_summary_applied(summarizer, event: SummaryAppliedEvent): + logger.info( + f"Context summarized: {event.original_message_count} messages -> " + f"{event.new_message_count} messages " + f"({event.summarized_message_count} summarized, " + f"{event.preserved_message_count} preserved)" + ) + + pipeline = Pipeline( + [ + transport.input(), # Transport user input + stt, + user_aggregator, # User responses + llm, # LLM + tts, # TTS + transport.output(), # Transport bot output + assistant_aggregator, # Assistant spoken responses + ] + ) + + task = PipelineTask( + pipeline, + params=PipelineParams( + enable_metrics=True, + enable_usage_metrics=True, + ), + idle_timeout_secs=runner_args.pipeline_idle_timeout_secs, + ) + + @transport.event_handler("on_client_connected") + async def on_client_connected(transport, client): + logger.info("Client connected") + # Kick off the conversation. + messages.append({"role": "system", "content": "Please introduce yourself to the user."}) + await task.queue_frames([LLMRunFrame()]) + + @transport.event_handler("on_client_disconnected") + async def on_client_disconnected(transport, client): + logger.info("Client disconnected") + await task.cancel() + + runner = PipelineRunner(handle_sigint=runner_args.handle_sigint) + + await runner.run(task) + + +async def bot(runner_args: RunnerArguments): + """Main bot entry point compatible with Pipecat Cloud.""" + transport = await create_transport(runner_args, transport_params) + await run_bot(transport, runner_args) + + +if __name__ == "__main__": + from pipecat.runner.run import main + + main() From ec9ddb31993e05ef0dcc64d962487480a534b941 Mon Sep 17 00:00:00 2001 From: Mark Backman Date: Thu, 26 Feb 2026 22:09:26 -0500 Subject: [PATCH 0677/1060] Add changelog entries for context summarization improvements (#3855) --- changelog/3855.added.2.md | 1 + changelog/3855.added.3.md | 1 + changelog/3855.added.4.md | 1 + changelog/3855.added.md | 1 + changelog/3855.changed.md | 1 + 5 files changed, 5 insertions(+) create mode 100644 changelog/3855.added.2.md create mode 100644 changelog/3855.added.3.md create mode 100644 changelog/3855.added.4.md create mode 100644 changelog/3855.added.md create mode 100644 changelog/3855.changed.md diff --git a/changelog/3855.added.2.md b/changelog/3855.added.2.md new file mode 100644 index 000000000..01cd23efe --- /dev/null +++ b/changelog/3855.added.2.md @@ -0,0 +1 @@ +- Added optional `llm` field to `LLMContextSummarizationConfig` for routing summarization to a dedicated LLM service (e.g., a cheaper/faster model) instead of the pipeline's primary model. diff --git a/changelog/3855.added.3.md b/changelog/3855.added.3.md new file mode 100644 index 000000000..b93fdec60 --- /dev/null +++ b/changelog/3855.added.3.md @@ -0,0 +1 @@ +- Added `summarization_timeout` to `LLMContextSummarizationConfig` (default 120s) to prevent hung LLM calls from permanently blocking future summarizations. diff --git a/changelog/3855.added.4.md b/changelog/3855.added.4.md new file mode 100644 index 000000000..b712b4ac9 --- /dev/null +++ b/changelog/3855.added.4.md @@ -0,0 +1 @@ +- Added `on_summary_applied` event to `LLMContextSummarizer` for observability, providing message counts before and after context summarization. diff --git a/changelog/3855.added.md b/changelog/3855.added.md new file mode 100644 index 000000000..79d37eeba --- /dev/null +++ b/changelog/3855.added.md @@ -0,0 +1 @@ +- Added `summary_message_template` to `LLMContextSummarizationConfig` for customizing how summaries are formatted when injected into context (e.g., wrapping in XML tags). diff --git a/changelog/3855.changed.md b/changelog/3855.changed.md new file mode 100644 index 000000000..2eac6785a --- /dev/null +++ b/changelog/3855.changed.md @@ -0,0 +1 @@ +- Updated context summarization to use `user` role instead of `assistant` for summary messages. From 98e737b4e94b2148f85193a8ddd9bd51deadc9bb Mon Sep 17 00:00:00 2001 From: Mark Backman Date: Thu, 26 Feb 2026 22:56:10 -0500 Subject: [PATCH 0678/1060] Add tests for context summarization improvements Cover summary message role, template, on_summary_applied event, summarization timeout, and dedicated LLM routing/error handling. --- tests/test_context_summarization.py | 300 ++++++++++++++++++++++++++- tests/test_llm_context_summarizer.py | 251 +++++++++++++++++++++- 2 files changed, 548 insertions(+), 3 deletions(-) diff --git a/tests/test_context_summarization.py b/tests/test_context_summarization.py index 3bb1246e9..446bfb8bd 100644 --- a/tests/test_context_summarization.py +++ b/tests/test_context_summarization.py @@ -6,10 +6,11 @@ """Tests for context summarization feature.""" +import asyncio import unittest -from unittest.mock import AsyncMock, MagicMock, patch +from unittest.mock import AsyncMock -from pipecat.frames.frames import LLMContextSummaryRequestFrame +from pipecat.frames.frames import LLMContextSummaryRequestFrame, LLMContextSummaryResultFrame from pipecat.processors.aggregators.llm_context import LLMContext, LLMSpecificMessage from pipecat.services.llm_service import LLMService from pipecat.utils.context.llm_context_summarization import ( @@ -601,6 +602,301 @@ class TestSummaryGenerationExceptions(unittest.IsolatedAsyncioTestCase): self.assertGreater(last_index, -1) self.assertEqual(last_index, 1) # Should be the index of the last summarized message + async def test_generate_summary_task_timeout(self): + """Test that _generate_summary_task handles timeout correctly.""" + llm_service = LLMService() + + # Mock _generate_summary to hang + async def slow_summary(frame): + await asyncio.sleep(10) + return ("summary", 1) + + llm_service._generate_summary = slow_summary + + broadcast_calls = [] + + async def mock_broadcast(frame_class, **kwargs): + broadcast_calls.append((frame_class, kwargs)) + + llm_service.broadcast_frame = mock_broadcast + llm_service.push_error = AsyncMock() + + context = LLMContext() + context.add_message({"role": "user", "content": "Message 1"}) + context.add_message({"role": "assistant", "content": "Response 1"}) + context.add_message({"role": "user", "content": "Message 2"}) + + frame = LLMContextSummaryRequestFrame( + request_id="timeout_test", + context=context, + min_messages_to_keep=1, + target_context_tokens=1000, + summarization_prompt="Summarize this", + summarization_timeout=0.1, # Very short timeout + ) + + await llm_service._generate_summary_task(frame) + + # Should have broadcast an error result + self.assertEqual(len(broadcast_calls), 1) + _, kwargs = broadcast_calls[0] + self.assertEqual(kwargs["request_id"], "timeout_test") + self.assertEqual(kwargs["summary"], "") + self.assertEqual(kwargs["last_summarized_index"], -1) + # error is None for timeout path (push_error is called instead) + self.assertIsNone(kwargs["error"]) + + # push_error should have been called with timeout message + llm_service.push_error.assert_called_once() + call_args = llm_service.push_error.call_args + error_msg = call_args.kwargs.get("error_msg") or call_args.args[0] + self.assertIn("timed out", error_msg) + + +class TestDedicatedLLMSummarization(unittest.IsolatedAsyncioTestCase): + """Tests for dedicated LLM summarization in LLMAssistantAggregator.""" + + def _create_context_and_frame(self): + """Create a context with enough messages and a matching request frame.""" + context = LLMContext() + context.add_message({"role": "user", "content": "Message 1"}) + context.add_message({"role": "assistant", "content": "Response 1"}) + context.add_message({"role": "user", "content": "Message 2"}) + + frame = LLMContextSummaryRequestFrame( + request_id="dedicated_test", + context=context, + min_messages_to_keep=1, + target_context_tokens=1000, + summarization_prompt="Summarize this", + summarization_timeout=5.0, + ) + return context, frame + + async def test_dedicated_llm_success(self): + """Test that dedicated LLM generates summary and feeds result to summarizer.""" + from pipecat.processors.aggregators.llm_context_summarizer import LLMContextSummarizer + from pipecat.processors.aggregators.llm_response_universal import ( + LLMAssistantAggregator, + LLMAssistantAggregatorParams, + ) + from pipecat.utils.asyncio.task_manager import TaskManager, TaskManagerParams + + context, frame = self._create_context_and_frame() + + # Create a mock dedicated LLM + dedicated_llm = LLMService() + dedicated_llm._generate_summary = AsyncMock(return_value=("Dedicated summary", 1)) + + config = LLMContextSummarizationConfig( + max_context_tokens=50, + llm=dedicated_llm, + ) + params = LLMAssistantAggregatorParams( + enable_context_summarization=True, + context_summarization_config=config, + ) + aggregator = LLMAssistantAggregator(context, params=params) + + # Mock summarizer.process_frame to capture the result + result_frames = [] + original_process = aggregator._summarizer.process_frame + + async def capture_process(frame): + result_frames.append(frame) + await original_process(frame) + + aggregator._summarizer.process_frame = capture_process + + # Call the method directly + await aggregator._generate_summary_with_dedicated_llm(dedicated_llm, frame) + + # Verify the dedicated LLM was called + dedicated_llm._generate_summary.assert_called_once_with(frame) + + # Verify result was fed to the summarizer + self.assertEqual(len(result_frames), 1) + result = result_frames[0] + self.assertIsInstance(result, LLMContextSummaryResultFrame) + self.assertEqual(result.request_id, "dedicated_test") + self.assertEqual(result.summary, "Dedicated summary") + self.assertEqual(result.last_summarized_index, 1) + self.assertIsNone(result.error) + + async def test_dedicated_llm_timeout(self): + """Test that dedicated LLM timeout produces error result.""" + from pipecat.processors.aggregators.llm_response_universal import ( + LLMAssistantAggregator, + LLMAssistantAggregatorParams, + ) + + context, _ = self._create_context_and_frame() + + # Create a mock dedicated LLM that hangs + dedicated_llm = LLMService() + + async def slow_summary(frame): + await asyncio.sleep(10) + return ("summary", 1) + + dedicated_llm._generate_summary = slow_summary + + config = LLMContextSummarizationConfig( + max_context_tokens=50, + llm=dedicated_llm, + ) + params = LLMAssistantAggregatorParams( + enable_context_summarization=True, + context_summarization_config=config, + ) + aggregator = LLMAssistantAggregator(context, params=params) + + # Mock summarizer.process_frame to capture the result + result_frames = [] + + async def capture_process(frame): + result_frames.append(frame) + + aggregator._summarizer.process_frame = capture_process + + # Create frame with very short timeout + frame = LLMContextSummaryRequestFrame( + request_id="timeout_test", + context=context, + min_messages_to_keep=1, + target_context_tokens=1000, + summarization_prompt="Summarize this", + summarization_timeout=0.1, + ) + + await aggregator._generate_summary_with_dedicated_llm(dedicated_llm, frame) + + # Verify error result was fed to summarizer + self.assertEqual(len(result_frames), 1) + result = result_frames[0] + self.assertIsInstance(result, LLMContextSummaryResultFrame) + self.assertEqual(result.request_id, "timeout_test") + self.assertEqual(result.summary, "") + self.assertEqual(result.last_summarized_index, -1) + self.assertIn("timed out", result.error) + + async def test_dedicated_llm_exception(self): + """Test that dedicated LLM exceptions produce error result.""" + from pipecat.processors.aggregators.llm_response_universal import ( + LLMAssistantAggregator, + LLMAssistantAggregatorParams, + ) + + context, frame = self._create_context_and_frame() + + # Create a mock dedicated LLM that raises + dedicated_llm = LLMService() + dedicated_llm._generate_summary = AsyncMock( + side_effect=RuntimeError("LLM connection failed") + ) + + config = LLMContextSummarizationConfig( + max_context_tokens=50, + llm=dedicated_llm, + ) + params = LLMAssistantAggregatorParams( + enable_context_summarization=True, + context_summarization_config=config, + ) + aggregator = LLMAssistantAggregator(context, params=params) + aggregator.push_error = AsyncMock() + + # Mock summarizer.process_frame to capture the result + result_frames = [] + + async def capture_process(frame): + result_frames.append(frame) + + aggregator._summarizer.process_frame = capture_process + + await aggregator._generate_summary_with_dedicated_llm(dedicated_llm, frame) + + # Verify error result was fed to summarizer + self.assertEqual(len(result_frames), 1) + result = result_frames[0] + self.assertIsInstance(result, LLMContextSummaryResultFrame) + self.assertEqual(result.request_id, "dedicated_test") + self.assertEqual(result.summary, "") + self.assertEqual(result.last_summarized_index, -1) + self.assertIn("LLM connection failed", result.error) + + # push_error should have been called + aggregator.push_error.assert_called_once() + + async def test_on_request_summarization_routes_to_dedicated_llm(self): + """Test that _on_request_summarization routes to dedicated LLM when configured.""" + from pipecat.processors.aggregators.llm_response_universal import ( + LLMAssistantAggregator, + LLMAssistantAggregatorParams, + ) + + context, frame = self._create_context_and_frame() + + dedicated_llm = LLMService() + dedicated_llm._generate_summary = AsyncMock(return_value=("Summary", 1)) + + config = LLMContextSummarizationConfig( + max_context_tokens=50, + llm=dedicated_llm, + ) + params = LLMAssistantAggregatorParams( + enable_context_summarization=True, + context_summarization_config=config, + ) + aggregator = LLMAssistantAggregator(context, params=params) + aggregator.push_frame = AsyncMock() + + # Track what coroutine is passed to create_task + created_coros = [] + original_create_task = aggregator.create_task + + def mock_create_task(coro, *args, **kwargs): + created_coros.append(coro) + # Actually run the coroutine to avoid "never awaited" warning + task = asyncio.ensure_future(coro) + return task + + aggregator.create_task = mock_create_task + + await aggregator._on_request_summarization(aggregator._summarizer, frame) + + # Should NOT push frame upstream + aggregator.push_frame.assert_not_called() + + # Should have created a task for the dedicated LLM + self.assertEqual(len(created_coros), 1) + + # Wait for the task to complete + await asyncio.sleep(0.05) + + async def test_on_request_summarization_pushes_upstream_without_dedicated_llm(self): + """Test that _on_request_summarization pushes upstream when no dedicated LLM.""" + from pipecat.processors.aggregators.llm_response_universal import ( + LLMAssistantAggregator, + LLMAssistantAggregatorParams, + ) + from pipecat.processors.frame_processor import FrameDirection + + context, frame = self._create_context_and_frame() + + config = LLMContextSummarizationConfig(max_context_tokens=50) + params = LLMAssistantAggregatorParams( + enable_context_summarization=True, + context_summarization_config=config, + ) + aggregator = LLMAssistantAggregator(context, params=params) + aggregator.push_frame = AsyncMock() + + await aggregator._on_request_summarization(aggregator._summarizer, frame) + + # Should push frame upstream + aggregator.push_frame.assert_called_once_with(frame, FrameDirection.UPSTREAM) + class TestLLMSpecificMessageHandling(unittest.TestCase): """Tests that LLMSpecificMessage objects are correctly skipped in summarization.""" diff --git a/tests/test_llm_context_summarizer.py b/tests/test_llm_context_summarizer.py index 7555a8762..0439d403d 100644 --- a/tests/test_llm_context_summarizer.py +++ b/tests/test_llm_context_summarizer.py @@ -14,7 +14,10 @@ from pipecat.frames.frames import ( LLMFullResponseStartFrame, ) from pipecat.processors.aggregators.llm_context import LLMContext -from pipecat.processors.aggregators.llm_context_summarizer import LLMContextSummarizer +from pipecat.processors.aggregators.llm_context_summarizer import ( + LLMContextSummarizer, + SummaryAppliedEvent, +) from pipecat.utils.asyncio.task_manager import TaskManager, TaskManagerParams from pipecat.utils.context.llm_context_summarization import LLMContextSummarizationConfig @@ -291,6 +294,252 @@ class TestLLMContextSummarizer(unittest.IsolatedAsyncioTestCase): await summarizer.cleanup() + async def test_summary_message_role_is_user(self): + """Test that the summary message uses the user role.""" + config = LLMContextSummarizationConfig(max_context_tokens=50, min_messages_after_summary=2) + + summarizer = LLMContextSummarizer(context=self.context, config=config) + await summarizer.setup(self.task_manager) + + # Add messages and trigger summarization + for i in range(10): + self.context.add_message({"role": "user", "content": "Test message."}) + + request_frame = None + + @summarizer.event_handler("on_request_summarization") + async def on_request_summarization(summarizer, frame): + nonlocal request_frame + request_frame = frame + + await summarizer.process_frame(LLMFullResponseStartFrame()) + self.assertIsNotNone(request_frame) + + # Simulate receiving a summary result + summary_result = LLMContextSummaryResultFrame( + request_id=request_frame.request_id, + summary="This is a test summary.", + last_summarized_index=5, + ) + await summarizer.process_frame(summary_result) + + # Find the summary message and verify its role is "user" + summary_msg = next( + (msg for msg in self.context.messages if "summary" in msg.get("content", "").lower()), + None, + ) + self.assertIsNotNone(summary_msg) + self.assertEqual(summary_msg["role"], "user") + + await summarizer.cleanup() + + async def test_summary_message_default_template(self): + """Test that the default summary_message_template is used.""" + config = LLMContextSummarizationConfig(max_context_tokens=50, min_messages_after_summary=2) + + summarizer = LLMContextSummarizer(context=self.context, config=config) + await summarizer.setup(self.task_manager) + + for i in range(10): + self.context.add_message({"role": "user", "content": "Test message."}) + + request_frame = None + + @summarizer.event_handler("on_request_summarization") + async def on_request_summarization(summarizer, frame): + nonlocal request_frame + request_frame = frame + + await summarizer.process_frame(LLMFullResponseStartFrame()) + + summary_result = LLMContextSummaryResultFrame( + request_id=request_frame.request_id, + summary="Key facts from conversation.", + last_summarized_index=5, + ) + await summarizer.process_frame(summary_result) + + # Default template wraps with "Conversation summary: {summary}" + summary_msg = next( + ( + msg + for msg in self.context.messages + if "Conversation summary:" in msg.get("content", "") + ), + None, + ) + self.assertIsNotNone(summary_msg) + self.assertEqual( + summary_msg["content"], "Conversation summary: Key facts from conversation." + ) + + await summarizer.cleanup() + + async def test_summary_message_custom_template(self): + """Test that a custom summary_message_template is applied.""" + config = LLMContextSummarizationConfig( + max_context_tokens=50, + min_messages_after_summary=2, + summary_message_template="\n{summary}\n", + ) + + summarizer = LLMContextSummarizer(context=self.context, config=config) + await summarizer.setup(self.task_manager) + + for i in range(10): + self.context.add_message({"role": "user", "content": "Test message."}) + + request_frame = None + + @summarizer.event_handler("on_request_summarization") + async def on_request_summarization(summarizer, frame): + nonlocal request_frame + request_frame = frame + + await summarizer.process_frame(LLMFullResponseStartFrame()) + + summary_result = LLMContextSummaryResultFrame( + request_id=request_frame.request_id, + summary="Key facts from conversation.", + last_summarized_index=5, + ) + await summarizer.process_frame(summary_result) + + # Custom template wraps with XML tags + summary_msg = next( + (msg for msg in self.context.messages if "" in msg.get("content", "")), + None, + ) + self.assertIsNotNone(summary_msg) + self.assertEqual( + summary_msg["content"], + "\nKey facts from conversation.\n", + ) + + await summarizer.cleanup() + + async def test_on_summary_applied_event(self): + """Test that on_summary_applied event fires with correct data.""" + config = LLMContextSummarizationConfig(max_context_tokens=50, min_messages_after_summary=2) + + summarizer = LLMContextSummarizer(context=self.context, config=config) + await summarizer.setup(self.task_manager) + + # Add messages (1 system + 10 user = 11 total) + for i in range(10): + self.context.add_message({"role": "user", "content": "Test message."}) + + request_frame = None + applied_event = None + + @summarizer.event_handler("on_request_summarization") + async def on_request_summarization(summarizer, frame): + nonlocal request_frame + request_frame = frame + + @summarizer.event_handler("on_summary_applied") + async def on_summary_applied(summarizer, event): + nonlocal applied_event + applied_event = event + + original_count = len(self.context.messages) # 11 + await summarizer.process_frame(LLMFullResponseStartFrame()) + + # Summarize up to index 7 (system=0, user1..user7), keep last 3 (user8, user9, user10) + summary_result = LLMContextSummaryResultFrame( + request_id=request_frame.request_id, + summary="Test summary.", + last_summarized_index=7, + ) + await summarizer.process_frame(summary_result) + + # Allow async event handler to complete + await asyncio.sleep(0.05) + + # Verify event was fired + self.assertIsNotNone(applied_event) + self.assertIsInstance(applied_event, SummaryAppliedEvent) + self.assertEqual(applied_event.original_message_count, original_count) + + # After summarization: system + summary + 3 recent = 5 + self.assertEqual(applied_event.new_message_count, 5) + + # Summarized messages: indices 1-7 = 7 messages (excluding system at index 0) + self.assertEqual(applied_event.summarized_message_count, 7) + + # Preserved: system (1) + recent messages after index 7 (3) = 4 + self.assertEqual(applied_event.preserved_message_count, 4) + + await summarizer.cleanup() + + async def test_on_summary_applied_not_fired_on_error(self): + """Test that on_summary_applied event is NOT fired when summarization fails.""" + config = LLMContextSummarizationConfig(max_context_tokens=50, min_messages_after_summary=2) + + summarizer = LLMContextSummarizer(context=self.context, config=config) + await summarizer.setup(self.task_manager) + + for i in range(10): + self.context.add_message({"role": "user", "content": "Test message."}) + + request_frame = None + applied_event = None + + @summarizer.event_handler("on_request_summarization") + async def on_request_summarization(summarizer, frame): + nonlocal request_frame + request_frame = frame + + @summarizer.event_handler("on_summary_applied") + async def on_summary_applied(summarizer, event): + nonlocal applied_event + applied_event = event + + await summarizer.process_frame(LLMFullResponseStartFrame()) + + # Send a result with an error + error_result = LLMContextSummaryResultFrame( + request_id=request_frame.request_id, + summary="", + last_summarized_index=-1, + error="Summarization timed out", + ) + await summarizer.process_frame(error_result) + + await asyncio.sleep(0.05) + + # Event should NOT have fired + self.assertIsNone(applied_event) + + await summarizer.cleanup() + + async def test_request_frame_includes_timeout(self): + """Test that the request frame includes the configured summarization_timeout.""" + config = LLMContextSummarizationConfig( + max_context_tokens=50, + summarization_timeout=60.0, + ) + + summarizer = LLMContextSummarizer(context=self.context, config=config) + await summarizer.setup(self.task_manager) + + request_frame = None + + @summarizer.event_handler("on_request_summarization") + async def on_request_summarization(summarizer, frame): + nonlocal request_frame + request_frame = frame + + for i in range(10): + self.context.add_message({"role": "user", "content": "Test message to add tokens."}) + + await summarizer.process_frame(LLMFullResponseStartFrame()) + + self.assertIsNotNone(request_frame) + self.assertEqual(request_frame.summarization_timeout, 60.0) + + await summarizer.cleanup() + if __name__ == "__main__": unittest.main() From 82c249608ff9428e1b230828b1f61b2a66f90717 Mon Sep 17 00:00:00 2001 From: Mark Backman Date: Fri, 27 Feb 2026 11:47:55 -0500 Subject: [PATCH 0679/1060] Move dedicated LLM summarization into LLMContextSummarizer The dedicated LLM logic lived in LLMAssistantAggregator, creating two code paths and requiring the aggregator to call a private LLMService method. Move it into the summarizer which already owns the config and summarization lifecycle, keeping the aggregator handler as a single-line upstream push. --- .../aggregators/llm_context_summarizer.py | 69 +++- .../aggregators/llm_response_universal.py | 68 +--- tests/test_context_summarization.py | 305 ++++++++---------- 3 files changed, 194 insertions(+), 248 deletions(-) diff --git a/src/pipecat/processors/aggregators/llm_context_summarizer.py b/src/pipecat/processors/aggregators/llm_context_summarizer.py index 85da9bfa0..44ec985bd 100644 --- a/src/pipecat/processors/aggregators/llm_context_summarizer.py +++ b/src/pipecat/processors/aggregators/llm_context_summarizer.py @@ -6,9 +6,10 @@ """This module defines a summarizer for managing LLM context summarization.""" +import asyncio import uuid from dataclasses import dataclass -from typing import Optional +from typing import TYPE_CHECKING, Optional from loguru import logger @@ -27,6 +28,9 @@ from pipecat.utils.context.llm_context_summarization import ( LLMContextSummarizationUtil, ) +if TYPE_CHECKING: + from pipecat.services.llm_service import LLMService + @dataclass class SummaryAppliedEvent: @@ -227,8 +231,10 @@ class LLMContextSummarizer(BaseObject): async def _request_summarization(self): """Request context summarization from LLM service. - Creates a summarization request frame and emits it via event handler. - Tracks the request ID to match async responses and prevent race conditions. + Creates a summarization request frame and either handles it directly + using a dedicated LLM (if configured) or emits it via event handler + for the pipeline's primary LLM. Tracks the request ID to match async + responses and prevent race conditions. """ # Generate unique request ID request_id = str(uuid.uuid4()) @@ -250,8 +256,61 @@ class LLMContextSummarizer(BaseObject): summarization_timeout=self._config.summarization_timeout, ) - # Emit event for aggregator to broadcast - await self._call_event_handler("on_request_summarization", request_frame) + if self._config.llm: + # Use dedicated LLM directly — no need to involve the pipeline + self.task_manager.create_task( + self._generate_summary_with_dedicated_llm(self._config.llm, request_frame), + f"{self}-dedicated-llm-summary", + ) + else: + # Emit event for aggregator to broadcast to the pipeline LLM + await self._call_event_handler("on_request_summarization", request_frame) + + async def _generate_summary_with_dedicated_llm( + self, llm: "LLMService", frame: LLMContextSummaryRequestFrame + ): + """Generate summary using a dedicated LLM service. + + Calls the dedicated LLM's _generate_summary directly and feeds the + result back through _handle_summary_result, bypassing the pipeline. + + Args: + llm: The dedicated LLM service to use for summarization. + frame: The summarization request frame. + """ + try: + if frame.summarization_timeout: + summary, last_index = await asyncio.wait_for( + llm._generate_summary(frame), + timeout=frame.summarization_timeout, + ) + else: + summary, last_index = await llm._generate_summary(frame) + result_frame = LLMContextSummaryResultFrame( + request_id=frame.request_id, + summary=summary, + last_summarized_index=last_index, + ) + except asyncio.TimeoutError: + error = f"Context summarization timed out after {frame.summarization_timeout}s" + logger.error(f"{self}: {error}") + result_frame = LLMContextSummaryResultFrame( + request_id=frame.request_id, + summary="", + last_summarized_index=-1, + error=error, + ) + except Exception as e: + error = f"Error generating context summary: {e}" + logger.error(f"{self}: {error}") + result_frame = LLMContextSummaryResultFrame( + request_id=frame.request_id, + summary="", + last_summarized_index=-1, + error=error, + ) + + await self._handle_summary_result(result_frame) async def _handle_summary_result(self, frame: LLMContextSummaryResultFrame): """Handle context summarization result from LLM service. diff --git a/src/pipecat/processors/aggregators/llm_response_universal.py b/src/pipecat/processors/aggregators/llm_response_universal.py index 361b2c8a6..b255748e0 100644 --- a/src/pipecat/processors/aggregators/llm_response_universal.py +++ b/src/pipecat/processors/aggregators/llm_response_universal.py @@ -16,7 +16,7 @@ import json import warnings from abc import abstractmethod from dataclasses import dataclass, field -from typing import TYPE_CHECKING, Any, Dict, List, Literal, Optional, Set, Type +from typing import Any, Dict, List, Literal, Optional, Set, Type from loguru import logger @@ -39,7 +39,6 @@ from pipecat.frames.frames import ( LLMContextAssistantTimestampFrame, LLMContextFrame, LLMContextSummaryRequestFrame, - LLMContextSummaryResultFrame, LLMFullResponseEndFrame, LLMFullResponseStartFrame, LLMMessagesAppendFrame, @@ -84,9 +83,6 @@ from pipecat.utils.context.llm_context_summarization import LLMContextSummarizat from pipecat.utils.string import TextPartForConcatenation, concatenate_aggregated_text from pipecat.utils.time import time_now_iso8601 -if TYPE_CHECKING: - from pipecat.services.llm_service import LLMService - @dataclass class LLMUserAggregatorParams: @@ -1252,71 +1248,13 @@ class LLMAssistantAggregator(LLMContextAggregator): ): """Handle summarization request from the summarizer. - If a dedicated summarization LLM is configured, generates the summary - directly and feeds the result to the summarizer. Otherwise, pushes the - request frame upstream to the pipeline's primary LLM service. + Push the request frame UPSTREAM to the LLM service for processing. Args: summarizer: The summarizer that generated the request. frame: The summarization request frame to broadcast. """ - summarization_llm = ( - self._params.context_summarization_config.llm - if self._params.context_summarization_config - else None - ) - - if summarization_llm: - self.create_task(self._generate_summary_with_dedicated_llm(summarization_llm, frame)) - else: - await self.push_frame(frame, FrameDirection.UPSTREAM) - - async def _generate_summary_with_dedicated_llm( - self, llm: "LLMService", frame: LLMContextSummaryRequestFrame - ): - """Generate summary using a dedicated LLM service. - - Calls the dedicated LLM's _generate_summary directly and feeds the - result back to the summarizer, bypassing the pipeline. - - Args: - llm: The dedicated LLM service to use for summarization. - frame: The summarization request frame. - """ - try: - if frame.summarization_timeout: - summary, last_index = await asyncio.wait_for( - llm._generate_summary(frame), - timeout=frame.summarization_timeout, - ) - else: - summary, last_index = await llm._generate_summary(frame) - result_frame = LLMContextSummaryResultFrame( - request_id=frame.request_id, - summary=summary, - last_summarized_index=last_index, - ) - except asyncio.TimeoutError: - error = f"Context summarization timed out after {frame.summarization_timeout}s" - logger.error(f"{self}: {error}") - result_frame = LLMContextSummaryResultFrame( - request_id=frame.request_id, - summary="", - last_summarized_index=-1, - error=error, - ) - except Exception as e: - error = f"Error generating context summary: {e}" - await self.push_error(error_msg=error, exception=e) - result_frame = LLMContextSummaryResultFrame( - request_id=frame.request_id, - summary="", - last_summarized_index=-1, - error=error, - ) - - if self._summarizer: - await self._summarizer.process_frame(result_frame) + await self.push_frame(frame, FrameDirection.UPSTREAM) class LLMContextAggregatorPair: diff --git a/tests/test_context_summarization.py b/tests/test_context_summarization.py index 446bfb8bd..ca56e7a32 100644 --- a/tests/test_context_summarization.py +++ b/tests/test_context_summarization.py @@ -654,85 +654,79 @@ class TestSummaryGenerationExceptions(unittest.IsolatedAsyncioTestCase): class TestDedicatedLLMSummarization(unittest.IsolatedAsyncioTestCase): - """Tests for dedicated LLM summarization in LLMAssistantAggregator.""" + """Tests for dedicated LLM summarization in LLMContextSummarizer.""" - def _create_context_and_frame(self): - """Create a context with enough messages and a matching request frame.""" - context = LLMContext() - context.add_message({"role": "user", "content": "Message 1"}) - context.add_message({"role": "assistant", "content": "Response 1"}) - context.add_message({"role": "user", "content": "Message 2"}) - - frame = LLMContextSummaryRequestFrame( - request_id="dedicated_test", - context=context, - min_messages_to_keep=1, - target_context_tokens=1000, - summarization_prompt="Summarize this", - summarization_timeout=5.0, - ) - return context, frame - - async def test_dedicated_llm_success(self): - """Test that dedicated LLM generates summary and feeds result to summarizer.""" - from pipecat.processors.aggregators.llm_context_summarizer import LLMContextSummarizer - from pipecat.processors.aggregators.llm_response_universal import ( - LLMAssistantAggregator, - LLMAssistantAggregatorParams, - ) + async def asyncSetUp(self): from pipecat.utils.asyncio.task_manager import TaskManager, TaskManagerParams - context, frame = self._create_context_and_frame() + self.task_manager = TaskManager() + self.task_manager.setup(TaskManagerParams(loop=asyncio.get_running_loop())) - # Create a mock dedicated LLM - dedicated_llm = LLMService() - dedicated_llm._generate_summary = AsyncMock(return_value=("Dedicated summary", 1)) + def _create_context_and_config(self, dedicated_llm): + """Create a context with enough messages and a config with a dedicated LLM.""" + context = LLMContext() + for i in range(10): + context.add_message( + {"role": "user", "content": f"Test message {i} that adds tokens to context."} + ) config = LLMContextSummarizationConfig( - max_context_tokens=50, + max_context_tokens=50, # Very low to trigger easily llm=dedicated_llm, + summarization_timeout=5.0, ) - params = LLMAssistantAggregatorParams( - enable_context_summarization=True, - context_summarization_config=config, - ) - aggregator = LLMAssistantAggregator(context, params=params) + return context, config - # Mock summarizer.process_frame to capture the result - result_frames = [] - original_process = aggregator._summarizer.process_frame + async def test_dedicated_llm_success(self): + """Test that dedicated LLM generates summary and applies result.""" + from pipecat.processors.aggregators.llm_context_summarizer import LLMContextSummarizer - async def capture_process(frame): - result_frames.append(frame) - await original_process(frame) + dedicated_llm = LLMService() + dedicated_llm._generate_summary = AsyncMock(return_value=("Dedicated summary", 5)) - aggregator._summarizer.process_frame = capture_process + context, config = self._create_context_and_config(dedicated_llm) + original_message_count = len(context.messages) + summarizer = LLMContextSummarizer(context=context, config=config) + await summarizer.setup(self.task_manager) - # Call the method directly - await aggregator._generate_summary_with_dedicated_llm(dedicated_llm, frame) + # Track whether on_request_summarization event fires (it should NOT) + event_fired = False + + @summarizer.event_handler("on_request_summarization") + async def on_request_summarization(summarizer, frame): + nonlocal event_fired + event_fired = True + + # Trigger summarization via LLM response start + from pipecat.frames.frames import LLMFullResponseStartFrame + + await summarizer.process_frame(LLMFullResponseStartFrame()) + + # Wait for the background task to complete + await asyncio.sleep(0.1) + + # The event should NOT have fired (dedicated LLM handles it internally) + self.assertFalse(event_fired) # Verify the dedicated LLM was called - dedicated_llm._generate_summary.assert_called_once_with(frame) + dedicated_llm._generate_summary.assert_called_once() - # Verify result was fed to the summarizer - self.assertEqual(len(result_frames), 1) - result = result_frames[0] - self.assertIsInstance(result, LLMContextSummaryResultFrame) - self.assertEqual(result.request_id, "dedicated_test") - self.assertEqual(result.summary, "Dedicated summary") - self.assertEqual(result.last_summarized_index, 1) - self.assertIsNone(result.error) + # Verify summary was applied to context (message count should decrease) + self.assertLess(len(context.messages), original_message_count) + + # Verify summary message is present + summary_messages = [ + msg for msg in context.messages if "Conversation summary:" in msg.get("content", "") + ] + self.assertEqual(len(summary_messages), 1) + self.assertIn("Dedicated summary", summary_messages[0]["content"]) + + await summarizer.cleanup() async def test_dedicated_llm_timeout(self): - """Test that dedicated LLM timeout produces error result.""" - from pipecat.processors.aggregators.llm_response_universal import ( - LLMAssistantAggregator, - LLMAssistantAggregatorParams, - ) + """Test that dedicated LLM timeout produces error and clears state.""" + from pipecat.processors.aggregators.llm_context_summarizer import LLMContextSummarizer - context, _ = self._create_context_and_frame() - - # Create a mock dedicated LLM that hangs dedicated_llm = LLMService() async def slow_summary(frame): @@ -741,161 +735,116 @@ class TestDedicatedLLMSummarization(unittest.IsolatedAsyncioTestCase): dedicated_llm._generate_summary = slow_summary - config = LLMContextSummarizationConfig( - max_context_tokens=50, - llm=dedicated_llm, - ) - params = LLMAssistantAggregatorParams( - enable_context_summarization=True, - context_summarization_config=config, - ) - aggregator = LLMAssistantAggregator(context, params=params) + context, config = self._create_context_and_config(dedicated_llm) + config.summarization_timeout = 0.1 # Very short timeout + summarizer = LLMContextSummarizer(context=context, config=config) + await summarizer.setup(self.task_manager) - # Mock summarizer.process_frame to capture the result - result_frames = [] + original_message_count = len(context.messages) - async def capture_process(frame): - result_frames.append(frame) + # Trigger summarization + from pipecat.frames.frames import LLMFullResponseStartFrame - aggregator._summarizer.process_frame = capture_process + await summarizer.process_frame(LLMFullResponseStartFrame()) - # Create frame with very short timeout - frame = LLMContextSummaryRequestFrame( - request_id="timeout_test", - context=context, - min_messages_to_keep=1, - target_context_tokens=1000, - summarization_prompt="Summarize this", - summarization_timeout=0.1, - ) + # Wait for the background task to complete (timeout + some buffer) + await asyncio.sleep(0.3) - await aggregator._generate_summary_with_dedicated_llm(dedicated_llm, frame) + # Context should be unchanged (timeout = error = no summary applied) + self.assertEqual(len(context.messages), original_message_count) - # Verify error result was fed to summarizer - self.assertEqual(len(result_frames), 1) - result = result_frames[0] - self.assertIsInstance(result, LLMContextSummaryResultFrame) - self.assertEqual(result.request_id, "timeout_test") - self.assertEqual(result.summary, "") - self.assertEqual(result.last_summarized_index, -1) - self.assertIn("timed out", result.error) + # Summarization state should be cleared so new requests can be made + self.assertFalse(summarizer._summarization_in_progress) + + await summarizer.cleanup() async def test_dedicated_llm_exception(self): - """Test that dedicated LLM exceptions produce error result.""" - from pipecat.processors.aggregators.llm_response_universal import ( - LLMAssistantAggregator, - LLMAssistantAggregatorParams, - ) + """Test that dedicated LLM exceptions produce error and clear state.""" + from pipecat.processors.aggregators.llm_context_summarizer import LLMContextSummarizer - context, frame = self._create_context_and_frame() - - # Create a mock dedicated LLM that raises dedicated_llm = LLMService() dedicated_llm._generate_summary = AsyncMock( side_effect=RuntimeError("LLM connection failed") ) - config = LLMContextSummarizationConfig( - max_context_tokens=50, - llm=dedicated_llm, - ) - params = LLMAssistantAggregatorParams( - enable_context_summarization=True, - context_summarization_config=config, - ) - aggregator = LLMAssistantAggregator(context, params=params) - aggregator.push_error = AsyncMock() + context, config = self._create_context_and_config(dedicated_llm) + summarizer = LLMContextSummarizer(context=context, config=config) + await summarizer.setup(self.task_manager) - # Mock summarizer.process_frame to capture the result - result_frames = [] + original_message_count = len(context.messages) - async def capture_process(frame): - result_frames.append(frame) + # Trigger summarization + from pipecat.frames.frames import LLMFullResponseStartFrame - aggregator._summarizer.process_frame = capture_process + await summarizer.process_frame(LLMFullResponseStartFrame()) - await aggregator._generate_summary_with_dedicated_llm(dedicated_llm, frame) + # Wait for the background task to complete + await asyncio.sleep(0.1) - # Verify error result was fed to summarizer - self.assertEqual(len(result_frames), 1) - result = result_frames[0] - self.assertIsInstance(result, LLMContextSummaryResultFrame) - self.assertEqual(result.request_id, "dedicated_test") - self.assertEqual(result.summary, "") - self.assertEqual(result.last_summarized_index, -1) - self.assertIn("LLM connection failed", result.error) + # Context should be unchanged (exception = error = no summary applied) + self.assertEqual(len(context.messages), original_message_count) - # push_error should have been called - aggregator.push_error.assert_called_once() + # Summarization state should be cleared + self.assertFalse(summarizer._summarization_in_progress) - async def test_on_request_summarization_routes_to_dedicated_llm(self): - """Test that _on_request_summarization routes to dedicated LLM when configured.""" - from pipecat.processors.aggregators.llm_response_universal import ( - LLMAssistantAggregator, - LLMAssistantAggregatorParams, - ) + await summarizer.cleanup() - context, frame = self._create_context_and_frame() + async def test_dedicated_llm_does_not_emit_event(self): + """Test that summarizer does NOT emit on_request_summarization when dedicated LLM is set.""" + from pipecat.processors.aggregators.llm_context_summarizer import LLMContextSummarizer dedicated_llm = LLMService() dedicated_llm._generate_summary = AsyncMock(return_value=("Summary", 1)) - config = LLMContextSummarizationConfig( - max_context_tokens=50, - llm=dedicated_llm, - ) - params = LLMAssistantAggregatorParams( - enable_context_summarization=True, - context_summarization_config=config, - ) - aggregator = LLMAssistantAggregator(context, params=params) - aggregator.push_frame = AsyncMock() + context, config = self._create_context_and_config(dedicated_llm) + summarizer = LLMContextSummarizer(context=context, config=config) + await summarizer.setup(self.task_manager) - # Track what coroutine is passed to create_task - created_coros = [] - original_create_task = aggregator.create_task + event_fired = False - def mock_create_task(coro, *args, **kwargs): - created_coros.append(coro) - # Actually run the coroutine to avoid "never awaited" warning - task = asyncio.ensure_future(coro) - return task + @summarizer.event_handler("on_request_summarization") + async def on_request_summarization(summarizer, frame): + nonlocal event_fired + event_fired = True - aggregator.create_task = mock_create_task + from pipecat.frames.frames import LLMFullResponseStartFrame - await aggregator._on_request_summarization(aggregator._summarizer, frame) + await summarizer.process_frame(LLMFullResponseStartFrame()) + await asyncio.sleep(0.1) - # Should NOT push frame upstream - aggregator.push_frame.assert_not_called() + self.assertFalse(event_fired) - # Should have created a task for the dedicated LLM - self.assertEqual(len(created_coros), 1) + await summarizer.cleanup() - # Wait for the task to complete - await asyncio.sleep(0.05) + async def test_no_dedicated_llm_emits_event(self): + """Test that summarizer emits on_request_summarization when no dedicated LLM.""" + from pipecat.processors.aggregators.llm_context_summarizer import LLMContextSummarizer - async def test_on_request_summarization_pushes_upstream_without_dedicated_llm(self): - """Test that _on_request_summarization pushes upstream when no dedicated LLM.""" - from pipecat.processors.aggregators.llm_response_universal import ( - LLMAssistantAggregator, - LLMAssistantAggregatorParams, - ) - from pipecat.processors.frame_processor import FrameDirection - - context, frame = self._create_context_and_frame() + context = LLMContext() + for i in range(10): + context.add_message( + {"role": "user", "content": f"Test message {i} that adds tokens to context."} + ) config = LLMContextSummarizationConfig(max_context_tokens=50) - params = LLMAssistantAggregatorParams( - enable_context_summarization=True, - context_summarization_config=config, - ) - aggregator = LLMAssistantAggregator(context, params=params) - aggregator.push_frame = AsyncMock() + summarizer = LLMContextSummarizer(context=context, config=config) + await summarizer.setup(self.task_manager) - await aggregator._on_request_summarization(aggregator._summarizer, frame) + request_frame = None - # Should push frame upstream - aggregator.push_frame.assert_called_once_with(frame, FrameDirection.UPSTREAM) + @summarizer.event_handler("on_request_summarization") + async def on_request_summarization(summarizer, frame): + nonlocal request_frame + request_frame = frame + + from pipecat.frames.frames import LLMFullResponseStartFrame + + await summarizer.process_frame(LLMFullResponseStartFrame()) + + self.assertIsNotNone(request_frame) + self.assertIsInstance(request_frame, LLMContextSummaryRequestFrame) + + await summarizer.cleanup() class TestLLMSpecificMessageHandling(unittest.TestCase): From f74af9b9c7e26cef7db3062c788782ad99140fc6 Mon Sep 17 00:00:00 2001 From: Mark Backman Date: Fri, 27 Feb 2026 11:57:22 -0500 Subject: [PATCH 0680/1060] Always apply a timeout to summarization LLM calls Even when summarization_timeout is explicitly set to None, use a DEFAULT_SUMMARIZATION_TIMEOUT (120s) fallback so the LLM call can never hang indefinitely. Applied in both LLMService and the dedicated LLM path in LLMContextSummarizer. --- src/pipecat/frames/frames.py | 2 +- .../aggregators/llm_context_summarizer.py | 16 ++++++++-------- src/pipecat/services/llm_service.py | 18 ++++++++---------- .../utils/context/llm_context_summarization.py | 6 ++++-- 4 files changed, 21 insertions(+), 21 deletions(-) diff --git a/src/pipecat/frames/frames.py b/src/pipecat/frames/frames.py index fbb0294a3..e1d2c37ff 100644 --- a/src/pipecat/frames/frames.py +++ b/src/pipecat/frames/frames.py @@ -2020,7 +2020,7 @@ class LLMContextSummaryRequestFrame(ControlFrame): summarization_prompt: System prompt instructing the LLM how to generate the summary. summarization_timeout: Maximum time in seconds for the LLM to generate a - summary. None means no timeout. + summary. When None, a default timeout of 120s is applied. """ request_id: str diff --git a/src/pipecat/processors/aggregators/llm_context_summarizer.py b/src/pipecat/processors/aggregators/llm_context_summarizer.py index 44ec985bd..bfdbbceb0 100644 --- a/src/pipecat/processors/aggregators/llm_context_summarizer.py +++ b/src/pipecat/processors/aggregators/llm_context_summarizer.py @@ -24,6 +24,7 @@ from pipecat.processors.aggregators.llm_context import LLMContext, LLMSpecificMe from pipecat.utils.asyncio.task_manager import BaseTaskManager from pipecat.utils.base_object import BaseObject from pipecat.utils.context.llm_context_summarization import ( + DEFAULT_SUMMARIZATION_TIMEOUT, LLMContextSummarizationConfig, LLMContextSummarizationUtil, ) @@ -278,21 +279,20 @@ class LLMContextSummarizer(BaseObject): llm: The dedicated LLM service to use for summarization. frame: The summarization request frame. """ + timeout = frame.summarization_timeout or DEFAULT_SUMMARIZATION_TIMEOUT + try: - if frame.summarization_timeout: - summary, last_index = await asyncio.wait_for( - llm._generate_summary(frame), - timeout=frame.summarization_timeout, - ) - else: - summary, last_index = await llm._generate_summary(frame) + summary, last_index = await asyncio.wait_for( + llm._generate_summary(frame), + timeout=timeout, + ) result_frame = LLMContextSummaryResultFrame( request_id=frame.request_id, summary=summary, last_summarized_index=last_index, ) except asyncio.TimeoutError: - error = f"Context summarization timed out after {frame.summarization_timeout}s" + error = f"Context summarization timed out after {timeout}s" logger.error(f"{self}: {error}") result_frame = LLMContextSummaryResultFrame( request_id=frame.request_id, diff --git a/src/pipecat/services/llm_service.py b/src/pipecat/services/llm_service.py index 86048ccbe..da0d57d66 100644 --- a/src/pipecat/services/llm_service.py +++ b/src/pipecat/services/llm_service.py @@ -62,6 +62,7 @@ from pipecat.services.ai_service import AIService from pipecat.services.settings import LLMSettings from pipecat.turns.user_turn_completion_mixin import UserTurnCompletionLLMServiceMixin from pipecat.utils.context.llm_context_summarization import ( + DEFAULT_SUMMARIZATION_TIMEOUT, LLMContextSummarizationUtil, ) @@ -436,18 +437,15 @@ class LLMService(UserTurnCompletionLLMServiceMixin, AIService): last_index = -1 error = None + timeout = frame.summarization_timeout or DEFAULT_SUMMARIZATION_TIMEOUT + try: - if frame.summarization_timeout: - summary, last_index = await asyncio.wait_for( - self._generate_summary(frame), - timeout=frame.summarization_timeout, - ) - else: - summary, last_index = await self._generate_summary(frame) - except asyncio.TimeoutError: - await self.push_error( - error_msg=f"Context summarization timed out after {frame.summarization_timeout}s" + summary, last_index = await asyncio.wait_for( + self._generate_summary(frame), + timeout=timeout, ) + except asyncio.TimeoutError: + await self.push_error(error_msg=f"Context summarization timed out after {timeout}s") except Exception as e: error = f"Error generating context summary: {e}" await self.push_error(error, exception=e) diff --git a/src/pipecat/utils/context/llm_context_summarization.py b/src/pipecat/utils/context/llm_context_summarization.py index 00dd74fd8..0bdebb3a2 100644 --- a/src/pipecat/utils/context/llm_context_summarization.py +++ b/src/pipecat/utils/context/llm_context_summarization.py @@ -20,6 +20,9 @@ from loguru import logger from pipecat.processors.aggregators.llm_context import LLMContext, LLMSpecificMessage +# Fallback timeout (seconds) used when summarization_timeout is None. +DEFAULT_SUMMARIZATION_TIMEOUT = 120.0 + # Token estimation constants CHARS_PER_TOKEN = 4 # Industry-standard heuristic: 1 token ≈ 4 characters TOKEN_OVERHEAD_PER_MESSAGE = 10 # Estimated structural overhead per message @@ -89,7 +92,6 @@ class LLMContextSummarizationConfig: summarization_timeout: Maximum time in seconds to wait for the LLM to generate a summary. If the call exceeds this timeout, summarization is aborted with an error and future summarizations are unblocked. - Set to None to disable the timeout. """ max_context_tokens: int = 8000 @@ -99,7 +101,7 @@ class LLMContextSummarizationConfig: summarization_prompt: Optional[str] = None summary_message_template: str = "Conversation summary: {summary}" llm: Optional["LLMService"] = None - summarization_timeout: Optional[float] = 120.0 + summarization_timeout: float = DEFAULT_SUMMARIZATION_TIMEOUT def __post_init__(self): """Validate configuration parameters.""" From 6ebfea474614819f5d5e9434f30ff511e20a4518 Mon Sep 17 00:00:00 2001 From: Matt <1610241+wollerman@users.noreply.github.com> Date: Fri, 27 Feb 2026 12:44:31 -0500 Subject: [PATCH 0681/1060] update numba version pin to >= --- pyproject.toml | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/pyproject.toml b/pyproject.toml index 2dea9005c..2cf46c3cd 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -36,7 +36,7 @@ dependencies = [ "soxr~=0.5.0", "openai>=1.74.0,<3", # Pinning numba to resolve package dependencies - "numba==0.61.2", + "numba>=0.61.2", "wait_for2>=0.4.1; python_version<'3.12'", # Required by LocalSmartTurnAnalyzerV3 # Inlined here instead of using a self-referential extra for Poetry compatibility. From acff172bf27a1341348c6acebcfaa21843375a6c Mon Sep 17 00:00:00 2001 From: Matt <1610241+wollerman@users.noreply.github.com> Date: Fri, 27 Feb 2026 14:52:37 -0500 Subject: [PATCH 0682/1060] create changelog entry --- changelog/3868.changed.md | 1 + 1 file changed, 1 insertion(+) create mode 100644 changelog/3868.changed.md diff --git a/changelog/3868.changed.md b/changelog/3868.changed.md new file mode 100644 index 000000000..4f019cca2 --- /dev/null +++ b/changelog/3868.changed.md @@ -0,0 +1 @@ +- Updated numba version pin from == to >=0.61.2 From aa7e9a17d5ecdb3d934833e65dae56570bd8c0ca Mon Sep 17 00:00:00 2001 From: zack Date: Fri, 27 Feb 2026 14:55:22 -0500 Subject: [PATCH 0683/1060] Fix finalization pattern: Use request/confirm in Pipecat mode, finalized flag in STT mode - Add request_finalize() before sending ForceEndpoint in Pipecat mode - Keep confirm_finalize() when receiving formatted finals in Pipecat mode - Remove confirm_finalize() from STT mode (use finalized=True instead) This follows Pipecat's two-step finalization pattern where request_finalize() is called when sending a finalize request to the STT service, and confirm_finalize() is called when receiving confirmation back. --- src/pipecat/services/assemblyai/stt.py | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/src/pipecat/services/assemblyai/stt.py b/src/pipecat/services/assemblyai/stt.py index 9881c145f..90e292ac0 100644 --- a/src/pipecat/services/assemblyai/stt.py +++ b/src/pipecat/services/assemblyai/stt.py @@ -438,6 +438,7 @@ class AssemblyAISTTService(WebsocketSTTService): and self._websocket and self._websocket.state is State.OPEN ): + await self.request_finalize() await self._websocket.send(json.dumps({"type": "ForceEndpoint"})) await self.start_processing_metrics() @@ -761,8 +762,7 @@ class AssemblyAISTTService(WebsocketSTTService): self._user_speaking = True if is_final_turn: - if message.turn_is_formatted: - self.confirm_finalize() + # STT mode: AssemblyAI controls finalization, just mark as finalized await self.push_frame( TranscriptionFrame( transcript_text, From 6ba9f780b08eddbfb6fa2cabe3cce6fe3adc457d Mon Sep 17 00:00:00 2001 From: zack Date: Fri, 27 Feb 2026 15:00:38 -0500 Subject: [PATCH 0684/1060] Remove unnecessary SpeechStarted fallback in STT mode u3-rt-pro guarantees SpeechStarted is always sent before transcripts, so the fallback UserStartedSpeakingFrame broadcast is never needed. This ensures clean pairing of UserStarted/StoppedSpeakingFrame: - Start: Always from _handle_speech_started - Stop: Always from _handle_transcription on final turn --- src/pipecat/services/assemblyai/stt.py | 9 ++------- 1 file changed, 2 insertions(+), 7 deletions(-) diff --git a/src/pipecat/services/assemblyai/stt.py b/src/pipecat/services/assemblyai/stt.py index 90e292ac0..0618a29fe 100644 --- a/src/pipecat/services/assemblyai/stt.py +++ b/src/pipecat/services/assemblyai/stt.py @@ -752,14 +752,9 @@ class AssemblyAISTTService(WebsocketSTTService): ) else: # --- Mode 2: STT turn detection --- - # SpeechStarted handles UserStartedSpeakingFrame + interruption. - # If SpeechStarted hasn't fired yet (shouldn't happen, but guard), - # broadcast here as fallback. + # SpeechStarted always arrives before transcripts with u3-rt-pro, + # so UserStartedSpeakingFrame is guaranteed to be broadcast first. logger.debug(f"{self} Transcript received in STT mode (_user_speaking={self._user_speaking})") - if not self._user_speaking: - logger.warning(f"{self} Transcript arrived before SpeechStarted, broadcasting fallback UserStartedSpeakingFrame") - await self.broadcast_frame(UserStartedSpeakingFrame) - self._user_speaking = True if is_final_turn: # STT mode: AssemblyAI controls finalization, just mark as finalized From 45532a947881817bd1150bd8695a7125b407df04 Mon Sep 17 00:00:00 2001 From: zack Date: Fri, 27 Feb 2026 16:15:49 -0500 Subject: [PATCH 0685/1060] Remove info logs and unused import per PR feedback - Remove unused Mapping import - Remove info logs at initialization (connection params) - Remove info logs in _handle_transcription (transcript details, text sent to LLM) - Remove info logs in _build_ws_url (WebSocket URL and params) - Keep debug logs (less verbose, appropriate for development) --- src/pipecat/services/assemblyai/stt.py | 38 ++------------------------ 1 file changed, 2 insertions(+), 36 deletions(-) diff --git a/src/pipecat/services/assemblyai/stt.py b/src/pipecat/services/assemblyai/stt.py index 0618a29fe..445ab7b73 100644 --- a/src/pipecat/services/assemblyai/stt.py +++ b/src/pipecat/services/assemblyai/stt.py @@ -13,7 +13,7 @@ WebSocket API for streaming audio transcription. import asyncio import json from dataclasses import dataclass, field -from typing import Any, AsyncGenerator, Dict, Mapping, Optional +from typing import Any, AsyncGenerator, Dict, Optional from urllib.parse import urlencode from loguru import logger @@ -211,18 +211,6 @@ class AssemblyAISTTService(WebsocketSTTService): self._user_speaking = False self._vad_speaking = False - # Log final connection params after any modifications - logger.info(f"{self} Final connection params being sent to AssemblyAI:") - logger.info(f" min_end_of_turn_silence_when_confident: {self._settings.connection_params.min_end_of_turn_silence_when_confident}") - logger.info(f" max_turn_silence: {self._settings.connection_params.max_turn_silence}") - - # Warn if min_end_of_turn_silence_when_confident is not 100ms - if self._settings.connection_params.min_end_of_turn_silence_when_confident != 100: - logger.warning( - f"For best latency, set min_end_of_turn_silence_when_confident to 100ms. " - f"Current value: {self._settings.connection_params.min_end_of_turn_silence_when_confident}ms" - ) - def _configure_pipecat_turn_mode( self, connection_params: AssemblyAIConnectionParams, is_u3_pro: bool ) -> AssemblyAIConnectionParams: @@ -461,13 +449,7 @@ class AssemblyAISTTService(WebsocketSTTService): if params: query_string = urlencode(params) - full_url = f"{self._api_endpoint_base_url}?{query_string}" - logger.info(f"{self} WebSocket URL being sent to AssemblyAI:") - logger.info(f" {full_url}") - logger.info(f" Parsed params:") - for k, v in params.items(): - logger.info(f" {k}: {v}") - return full_url + return f"{self._api_endpoint_base_url}?{query_string}" return self._api_endpoint_base_url async def _connect(self): @@ -672,17 +654,6 @@ class AssemblyAISTTService(WebsocketSTTService): - end_of_turn → TranscriptionFrame + UserStoppedSpeakingFrame - else → InterimTranscriptionFrame """ - # Log transcript details - logger.info(f"{self} ===== TRANSCRIPT RECEIVED =====") - logger.info(f" Text: \"{message.transcript}\"") - logger.info(f" end_of_turn: {message.end_of_turn}") - logger.info(f" turn_is_formatted: {message.turn_is_formatted}") - logger.info(f" turn_order: {message.turn_order}") - if message.end_of_turn_confidence is not None: - logger.info(f" end_of_turn_confidence: {message.end_of_turn_confidence}") - logger.info(f" speaker: {message.speaker}") - logger.info(f"===============================") - if not message.transcript: return @@ -709,11 +680,6 @@ class AssemblyAISTTService(WebsocketSTTService): speaker=message.speaker, text=message.transcript ) - logger.info(f"{self} 🤖 TEXT SENT TO LLM (with speaker format): \"{transcript_text}\"") - else: - logger.info(f"{self} 🤖 TEXT SENT TO LLM (speaker {message.speaker}): \"{transcript_text}\"") - else: - logger.info(f"{self} 🤖 TEXT SENT TO LLM: \"{transcript_text}\"") # Determine if this is a final turn from AssemblyAI is_final_turn = message.end_of_turn and ( From 6f33aff0c6c1396b43e63b63c7764afac4dbbdff Mon Sep 17 00:00:00 2001 From: Rupesh Date: Fri, 27 Feb 2026 13:29:01 -0800 Subject: [PATCH 0686/1060] Fix PipelineTask double-inserting RTVIProcessor when custom RTVIObserver is provided When the user places an RTVIProcessor inside their pipeline and provides a custom RTVIObserver subclass in observers, PipelineTask correctly detects both and logs "skipping default ones." However it then unconditionally prepends self._rtvi to the pipeline, causing the processor to appear twice in the frame chain. Track whether the RTVIProcessor was found externally (inside the user pipeline) vs created internally. Only prepend it when created internally. Fixes #3867 --- changelog/3867.fixed.md | 1 + src/pipecat/pipeline/task.py | 10 +++++++++- 2 files changed, 10 insertions(+), 1 deletion(-) create mode 100644 changelog/3867.fixed.md diff --git a/changelog/3867.fixed.md b/changelog/3867.fixed.md new file mode 100644 index 000000000..41ee584a2 --- /dev/null +++ b/changelog/3867.fixed.md @@ -0,0 +1 @@ +- Fixed `PipelineTask` double-inserting `RTVIProcessor` into the frame chain when the user provides both an `RTVIProcessor` in the pipeline and a custom `RTVIObserver` subclass in observers. diff --git a/src/pipecat/pipeline/task.py b/src/pipecat/pipeline/task.py index 2cfe26606..1db23e7d4 100644 --- a/src/pipecat/pipeline/task.py +++ b/src/pipecat/pipeline/task.py @@ -330,6 +330,7 @@ class PipelineTask(BasePipelineTask): # RTVI support self._rtvi = None + self._rtvi_external = False external_rtvi = self._find_processor(pipeline, RTVIProcessor) external_observer_found = any(isinstance(o, RTVIObserver) for o in observers) @@ -349,6 +350,7 @@ class PipelineTask(BasePipelineTask): "They are both added by default, no need to add them yourself." ) self._rtvi = external_rtvi + self._rtvi_external = True elif enable_rtvi: self._rtvi = rtvi_processor or RTVIProcessor() observers.append(self._rtvi.create_rtvi_observer(params=rtvi_observer_params)) @@ -388,7 +390,13 @@ class PipelineTask(BasePipelineTask): # allows us to receive and react to downstream frames. source = PipelineSource(self._source_push_frame, name=f"{self}::Source") sink = PipelineSink(self._sink_push_frame, name=f"{self}::Sink") - processors = [self._rtvi, pipeline] if self._rtvi else [pipeline] + # Only prepend the RTVIProcessor if we created it ourselves. When the + # user already placed it inside their pipeline we must not insert it + # again or it will appear twice in the frame chain. + if self._rtvi and not self._rtvi_external: + processors = [self._rtvi, pipeline] + else: + processors = [pipeline] self._pipeline = Pipeline(processors, source=source, sink=sink) # The task observer acts as a proxy to the provided observers. This way, From 51a3310e78f63a2ade4d99959b00994b3136f44a Mon Sep 17 00:00:00 2001 From: filipi87 Date: Fri, 27 Feb 2026 18:39:57 -0300 Subject: [PATCH 0687/1060] Added LLMSummarizeContextFrame: push this frame anywhere in the pipeline to trigger on-demand context summarization (e.g. from a function call tool). --- src/pipecat/frames/frames.py | 17 +++++++++++++++++ 1 file changed, 17 insertions(+) diff --git a/src/pipecat/frames/frames.py b/src/pipecat/frames/frames.py index e1d2c37ff..126f3c001 100644 --- a/src/pipecat/frames/frames.py +++ b/src/pipecat/frames/frames.py @@ -43,6 +43,7 @@ if TYPE_CHECKING: from pipecat.processors.aggregators.llm_context import LLMContext, NotGiven from pipecat.processors.frame_processor import FrameProcessor from pipecat.services.settings import ServiceSettings + from pipecat.utils.context.llm_context_summarization import LLMContextSummaryConfig from pipecat.utils.tracing.tracing_context import TracingContext @@ -2000,6 +2001,22 @@ class LLMAssistantPushAggregationFrame(ControlFrame): """ +@dataclass +class LLMSummarizeContextFrame(ControlFrame): + """Frame requesting on-demand context summarization. + + Push this frame into the pipeline to trigger a manual context summarization. + + Parameters: + config: Optional per-request override for summary generation settings + (prompt, token budget, messages to keep). If ``None``, the + summarizer's default :class:`~pipecat.utils.context.llm_context_summarization.LLMContextSummaryConfig` + is used. + """ + + config: Optional["LLMContextSummaryConfig"] = None + + @dataclass class LLMContextSummaryRequestFrame(ControlFrame): """Frame requesting context summarization from an LLM service. From f11d4b694415c625f3c651eb907e6d8afd65df2c Mon Sep 17 00:00:00 2001 From: filipi87 Date: Fri, 27 Feb 2026 18:40:41 -0300 Subject: [PATCH 0688/1060] Refactored LLMContextSummarizationConfig into two focused classes, LLMContextSummaryConfig and LLMAutoContextSummarizationConfig. --- .../context/llm_context_summarization.py | 132 ++++++++++++++++-- 1 file changed, 119 insertions(+), 13 deletions(-) diff --git a/src/pipecat/utils/context/llm_context_summarization.py b/src/pipecat/utils/context/llm_context_summarization.py index 0bdebb3a2..e68311942 100644 --- a/src/pipecat/utils/context/llm_context_summarization.py +++ b/src/pipecat/utils/context/llm_context_summarization.py @@ -10,7 +10,8 @@ This module provides reusable functionality for automatically compressing conver context when token limits are reached, enabling efficient long-running conversations. """ -from dataclasses import dataclass +import warnings +from dataclasses import dataclass, field from typing import TYPE_CHECKING, List, Optional if TYPE_CHECKING: @@ -54,26 +55,18 @@ The conversation transcript follows. Generate only the summary, no other text."" @dataclass -class LLMContextSummarizationConfig: - """Configuration for context summarization behavior. +class LLMContextSummaryConfig: + """Configuration for summary generation parameters. - Controls when and how conversation context is automatically compressed - to manage token limits in long-running conversations. + Contains settings that control how a summary is generated. Used by both + automatic and manual summarization modes. Parameters: - max_context_tokens: Maximum allowed context size in tokens. When this - limit is reached, summarization is triggered to compress the context. - The tokens are calculated using the industry-standard approximation - of 1 token ≈ 4 characters. target_context_tokens: Maximum token size for the generated summary. This value is passed directly to the LLM as the max_tokens parameter when generating the summary. Should be sized appropriately to allow the summary plus recent preserved messages to fit within reasonable context limits. - max_unsummarized_messages: Maximum number of new messages that can - accumulate since the last summary before triggering a new - summarization. This ensures regular compression even if token - limits are not reached. min_messages_after_summary: Number of recent messages to preserve uncompressed after each summarization. These messages maintain immediate conversational context. @@ -94,6 +87,94 @@ class LLMContextSummarizationConfig: is aborted with an error and future summarizations are unblocked. """ + target_context_tokens: int = 6000 + min_messages_after_summary: int = 4 + summarization_prompt: Optional[str] = None + summary_message_template: str = "Conversation summary: {summary}" + llm: Optional["LLMService"] = None + summarization_timeout: float = DEFAULT_SUMMARIZATION_TIMEOUT + + def __post_init__(self): + """Validate configuration parameters.""" + if self.target_context_tokens <= 0: + raise ValueError("target_context_tokens must be positive") + if self.min_messages_after_summary < 0: + raise ValueError("min_messages_after_summary must be non-negative") + + @property + def summary_prompt(self) -> str: + """Get the summarization prompt to use. + + Returns: + The custom prompt if set, otherwise the default summarization prompt. + """ + return self.summarization_prompt or DEFAULT_SUMMARIZATION_PROMPT + + +@dataclass +class LLMAutoContextSummarizationConfig: + """Configuration for automatic context summarization. + + Controls when conversation context is automatically compressed and how + that summary is generated. Summarization is triggered when either the + token limit or the unsummarized message count threshold is exceeded. + + Parameters: + max_context_tokens: Maximum allowed context size in tokens. When this + limit is reached, summarization is triggered to compress the context. + The tokens are calculated using the industry-standard approximation + of 1 token ≈ 4 characters. + max_unsummarized_messages: Maximum number of new messages that can + accumulate since the last summary before triggering a new + summarization. This ensures regular compression even if token + limits are not reached. + summary_config: Configuration for summary generation parameters + (prompt, token budget, messages to keep). If not provided, uses + default ``LLMContextSummaryConfig`` values. + """ + + max_context_tokens: int = 8000 + max_unsummarized_messages: int = 20 + summary_config: LLMContextSummaryConfig = field(default_factory=LLMContextSummaryConfig) + + def __post_init__(self): + """Validate configuration parameters.""" + if self.max_context_tokens <= 0: + raise ValueError("max_context_tokens must be positive") + if self.max_unsummarized_messages < 1: + raise ValueError("max_unsummarized_messages must be at least 1") + + # Auto-adjust target_context_tokens if it exceeds max_context_tokens + if self.summary_config.target_context_tokens > self.max_context_tokens: + # Use 80% of max_context_tokens as a reasonable default + self.summary_config.target_context_tokens = int(self.max_context_tokens * 0.8) + + +@dataclass +class LLMContextSummarizationConfig: + """Configuration for context summarization behavior. + + .. deprecated:: + Use :class:`LLMAutoContextSummarizationConfig` with a nested + :class:`LLMContextSummaryConfig` instead:: + + LLMAutoContextSummarizationConfig( + max_context_tokens=8000, + max_unsummarized_messages=20, + summary_config=LLMContextSummaryConfig( + target_context_tokens=6000, + min_messages_after_summary=4, + ), + ) + + Parameters: + max_context_tokens: Maximum allowed context size in tokens. + target_context_tokens: Maximum token size for the generated summary. + max_unsummarized_messages: Maximum new messages before triggering summarization. + min_messages_after_summary: Number of recent messages to preserve. + summarization_prompt: Custom prompt for summary generation. + """ + max_context_tokens: int = 8000 target_context_tokens: int = 6000 max_unsummarized_messages: int = 20 @@ -105,6 +186,12 @@ class LLMContextSummarizationConfig: def __post_init__(self): """Validate configuration parameters.""" + warnings.warn( + "LLMContextSummarizationConfig is deprecated. " + "Use LLMAutoContextSummarizationConfig with a nested LLMContextSummaryConfig instead.", + DeprecationWarning, + stacklevel=2, + ) if self.max_context_tokens <= 0: raise ValueError("max_context_tokens must be positive") if self.target_context_tokens <= 0: @@ -129,6 +216,25 @@ class LLMContextSummarizationConfig: """ return self.summarization_prompt or DEFAULT_SUMMARIZATION_PROMPT + def to_auto_config(self) -> LLMAutoContextSummarizationConfig: + """Convert to the new :class:`LLMAutoContextSummarizationConfig`. + + Returns: + An equivalent ``LLMAutoContextSummarizationConfig`` instance. + """ + return LLMAutoContextSummarizationConfig( + max_context_tokens=self.max_context_tokens, + max_unsummarized_messages=self.max_unsummarized_messages, + summary_config=LLMContextSummaryConfig( + target_context_tokens=self.target_context_tokens, + min_messages_after_summary=self.min_messages_after_summary, + summarization_prompt=self.summarization_prompt, + summary_message_template=self.summary_message_template, + llm=self.llm, + summarization_timeout=self.summarization_timeout, + ), + ) + @dataclass class LLMMessagesToSummarize: From 08d93ce9b662fef96faf64007939741cecc9ebd6 Mon Sep 17 00:00:00 2001 From: filipi87 Date: Fri, 27 Feb 2026 18:41:17 -0300 Subject: [PATCH 0689/1060] Renamed LLMAssistantAggregatorParams fields for clarity. --- .../aggregators/llm_response_universal.py | 77 ++++++++++++++----- 1 file changed, 59 insertions(+), 18 deletions(-) diff --git a/src/pipecat/processors/aggregators/llm_response_universal.py b/src/pipecat/processors/aggregators/llm_response_universal.py index b255748e0..c43cc279d 100644 --- a/src/pipecat/processors/aggregators/llm_response_universal.py +++ b/src/pipecat/processors/aggregators/llm_response_universal.py @@ -79,7 +79,10 @@ from pipecat.turns.user_stop import BaseUserTurnStopStrategy, UserTurnStoppedPar from pipecat.turns.user_turn_completion_mixin import UserTurnCompletionConfig from pipecat.turns.user_turn_controller import UserTurnController from pipecat.turns.user_turn_strategies import ExternalUserTurnStrategies, UserTurnStrategies -from pipecat.utils.context.llm_context_summarization import LLMContextSummarizationConfig +from pipecat.utils.context.llm_context_summarization import ( + LLMAutoContextSummarizationConfig, + LLMContextSummarizationConfig, +) from pipecat.utils.string import TextPartForConcatenation, concatenate_aggregated_text from pipecat.utils.time import time_now_iso8601 @@ -125,18 +128,54 @@ class LLMAssistantAggregatorParams: in text frames by adding spaces between tokens. This parameter is ignored when used with the newer LLMAssistantAggregator, which handles word spacing automatically. - enable_context_summarization: Enable automatic context summarization when token - limits are reached (disabled by default). When enabled, older conversation - messages are automatically compressed into summaries to manage context size. - context_summarization_config: Configuration for context summarization behavior. - Controls thresholds, message preservation, and summarization prompts. If None - and summarization is enabled, uses default configuration values. + enable_auto_context_summarization: Enable automatic context summarization when token + or message-count limits are reached (disabled by default). When enabled, + older conversation messages are automatically compressed into summaries to + manage context size. + auto_context_summarization_config: Configuration for automatic context + summarization. Controls trigger thresholds, message preservation, and + summarization prompts. If None, uses default + ``LLMAutoContextSummarizationConfig`` values. """ expect_stripped_words: bool = True - enable_context_summarization: bool = False + enable_auto_context_summarization: bool = False + auto_context_summarization_config: Optional[LLMAutoContextSummarizationConfig] = None + + # --------------------------------------------------------------------------- + # Deprecated field names — kept for backward compatibility. + # Use enable_auto_context_summarization and auto_context_summarization_config instead. + # --------------------------------------------------------------------------- + enable_context_summarization: Optional[bool] = None context_summarization_config: Optional[LLMContextSummarizationConfig] = None + def __post_init__(self): + if self.enable_context_summarization is not None: + warnings.warn( + "LLMAssistantAggregatorParams.enable_context_summarization is deprecated. " + "Use enable_auto_context_summarization instead.", + DeprecationWarning, + stacklevel=2, + ) + self.enable_auto_context_summarization = self.enable_context_summarization + self.enable_context_summarization = None + + if self.context_summarization_config is not None: + warnings.warn( + "LLMAssistantAggregatorParams.context_summarization_config is deprecated. " + "Use auto_context_summarization_config (LLMAutoContextSummarizationConfig) instead.", + DeprecationWarning, + stacklevel=2, + ) + if isinstance(self.context_summarization_config, LLMContextSummarizationConfig): + self.auto_context_summarization_config = ( + self.context_summarization_config.to_auto_config() + ) + else: + # Accept LLMAutoContextSummarizationConfig passed to the deprecated field + self.auto_context_summarization_config = self.context_summarization_config # type: ignore[assignment] + self.context_summarization_config = None + @dataclass class UserTurnStoppedMessage: @@ -825,16 +864,18 @@ class LLMAssistantAggregator(LLMContextAggregator): self._thought_aggregation: List[TextPartForConcatenation] = [] self._thought_start_time: str = "" - # Context summarization - self._summarizer: Optional[LLMContextSummarizer] = None - if self._params.enable_context_summarization: - self._summarizer = LLMContextSummarizer( - context=self._context, - config=self._params.context_summarization_config, - ) - self._summarizer.add_event_handler( - "on_request_summarization", self._on_request_summarization - ) + # Context summarization — always create the summarizer so that manually + # pushed LLMSummarizeContextFrame frames are always handled. + # Auto-triggering based on thresholds is only enabled when + # enable_auto_context_summarization is True. + self._summarizer: Optional[LLMContextSummarizer] = LLMContextSummarizer( + context=self._context, + config=self._params.auto_context_summarization_config, + auto_trigger=self._params.enable_auto_context_summarization, + ) + self._summarizer.add_event_handler( + "on_request_summarization", self._on_request_summarization + ) self._register_event_handler("on_assistant_turn_started") self._register_event_handler("on_assistant_turn_stopped") From ed7f0a2c08b229996c6d8722591233b9be61e1af Mon Sep 17 00:00:00 2001 From: filipi87 Date: Fri, 27 Feb 2026 18:41:55 -0300 Subject: [PATCH 0690/1060] Adding support for on-demand summarization --- .../aggregators/llm_context_summarizer.py | 107 +++++++++++++----- 1 file changed, 78 insertions(+), 29 deletions(-) diff --git a/src/pipecat/processors/aggregators/llm_context_summarizer.py b/src/pipecat/processors/aggregators/llm_context_summarizer.py index bfdbbceb0..54879a8bb 100644 --- a/src/pipecat/processors/aggregators/llm_context_summarizer.py +++ b/src/pipecat/processors/aggregators/llm_context_summarizer.py @@ -19,14 +19,16 @@ from pipecat.frames.frames import ( LLMContextSummaryRequestFrame, LLMContextSummaryResultFrame, LLMFullResponseStartFrame, + LLMSummarizeContextFrame, ) from pipecat.processors.aggregators.llm_context import LLMContext, LLMSpecificMessage from pipecat.utils.asyncio.task_manager import BaseTaskManager from pipecat.utils.base_object import BaseObject from pipecat.utils.context.llm_context_summarization import ( DEFAULT_SUMMARIZATION_TIMEOUT, - LLMContextSummarizationConfig, + LLMAutoContextSummarizationConfig, LLMContextSummarizationUtil, + LLMContextSummaryConfig, ) if TYPE_CHECKING: @@ -55,9 +57,20 @@ class SummaryAppliedEvent: class LLMContextSummarizer(BaseObject): """Summarizer for managing LLM context summarization. - This class manages automatic context summarization when token or message - limits are reached. It monitors the LLM context size, triggers - summarization requests, and applies the results to compress conversation history. + This class manages context summarization, either automatically when token or + message limits are reached, or on-demand when an ``LLMSummarizeContextFrame`` + is received. It monitors the LLM context size, triggers summarization requests, + and applies the results to compress conversation history. + + When ``auto_trigger=True`` (the default), summarization is triggered + automatically based on the configured thresholds in + ``LLMAutoContextSummarizationConfig``. When ``auto_trigger=False``, + threshold checks are skipped and summarization only happens when an + ``LLMSummarizeContextFrame`` is explicitly pushed into the pipeline. + + Both modes can coexist: set ``auto_trigger=True`` and also push + ``LLMSummarizeContextFrame`` at any time to force an immediate summarization + (subject to the ``_summarization_in_progress`` guard). Event handlers available: @@ -88,18 +101,26 @@ class LLMContextSummarizer(BaseObject): self, *, context: LLMContext, - config: Optional[LLMContextSummarizationConfig] = None, + config: Optional[LLMAutoContextSummarizationConfig] = None, + auto_trigger: bool = True, ): """Initialize the context summarizer. Args: context: The LLM context to monitor and summarize. - config: Configuration for summarization behavior. If None, uses default config. + config: Auto-summarization configuration controlling both trigger + thresholds and default summary generation parameters. If None, + uses default ``LLMAutoContextSummarizationConfig`` values. + auto_trigger: Whether to automatically trigger summarization when + thresholds are reached. When False, summarization only happens + when an ``LLMSummarizeContextFrame`` is pushed into the pipeline. + Defaults to True. """ super().__init__() self._context = context - self._config = config or LLMContextSummarizationConfig() + self._auto_config = config or LLMAutoContextSummarizationConfig() + self._auto_trigger = auto_trigger self._task_manager: Optional[BaseTaskManager] = None @@ -137,6 +158,8 @@ class LLMContextSummarizer(BaseObject): """ if isinstance(frame, LLMFullResponseStartFrame): await self._handle_llm_response_start(frame) + elif isinstance(frame, LLMSummarizeContextFrame): + await self._handle_manual_summarization_request(frame) elif isinstance(frame, LLMContextSummaryResultFrame): await self._handle_summary_result(frame) elif isinstance(frame, InterruptionFrame): @@ -151,12 +174,24 @@ class LLMContextSummarizer(BaseObject): if self._should_summarize(): await self._request_summarization() - async def _handle_interruption(self): - """Handle interruption by canceling summarization in progress. + async def _handle_manual_summarization_request(self, frame: LLMSummarizeContextFrame): + """Handle an explicit on-demand summarization request. + + Reuses the same ``_request_summarization()`` code path as auto mode, + so bookkeeping (``_summarization_in_progress``, + ``_pending_summary_request_id``) is always updated correctly. Args: - frame: The interruption frame. + frame: The manual summarization request frame, optionally carrying + a per-request :class:`~pipecat.utils.context.llm_context_summarization.LLMContextSummaryConfig`. """ + if self._summarization_in_progress: + logger.debug(f"{self}: Summarization already in progress, ignoring manual request") + return + await self._request_summarization(config_override=frame.config) + + async def _handle_interruption(self): + """Handle interruption by canceling summarization in progress.""" # Reset summarization state to allow new requests. This is necessary because # the request frame (LLMContextSummaryRequestFrame) may have been cancelled # during interruption. We preserve _pending_summary_request_id to handle the @@ -179,13 +214,17 @@ class LLMContextSummarizer(BaseObject): Returns: True if all conditions are met: + - ``auto_trigger`` is enabled - No summarization currently in progress - AND either: - - Token count exceeds max_context_tokens - - OR message count exceeds max_unsummarized_messages since last summary + - Token count exceeds ``max_context_tokens`` + - OR message count exceeds ``max_unsummarized_messages`` since last summary """ logger.trace(f"{self}: Checking if context summarization is needed") + if not self._auto_trigger: + return False + if self._summarization_in_progress: logger.debug(f"{self}: Summarization already in progress") return False @@ -195,20 +234,20 @@ class LLMContextSummarizer(BaseObject): num_messages = len(self._context.messages) # Check if we've reached the token limit - token_limit = self._config.max_context_tokens + token_limit = self._auto_config.max_context_tokens token_limit_exceeded = total_tokens >= token_limit # Check if we've exceeded max unsummarized messages messages_since_summary = len(self._context.messages) - 1 message_threshold_exceeded = ( - messages_since_summary >= self._config.max_unsummarized_messages + messages_since_summary >= self._auto_config.max_unsummarized_messages ) logger.trace( f"{self}: Context has {num_messages} messages, " f"~{total_tokens} tokens (limit: {token_limit}), " f"{messages_since_summary} messages since last summary " - f"(message threshold: {self._config.max_unsummarized_messages})" + f"(message threshold: {self._auto_config.max_unsummarized_messages})" ) # Trigger if either limit is exceeded @@ -223,23 +262,30 @@ class LLMContextSummarizer(BaseObject): reason.append(f"~{total_tokens} tokens (>={token_limit} limit)") if message_threshold_exceeded: reason.append( - f"{messages_since_summary} messages (>={self._config.max_unsummarized_messages} threshold)" + f"{messages_since_summary} messages (>={self._auto_config.max_unsummarized_messages} threshold)" ) logger.debug(f"{self}: ✓ Summarization needed - {', '.join(reason)}") return True - async def _request_summarization(self): + async def _request_summarization( + self, config_override: Optional[LLMContextSummaryConfig] = None + ): """Request context summarization from LLM service. Creates a summarization request frame and either handles it directly using a dedicated LLM (if configured) or emits it via event handler - for the pipeline's primary LLM. Tracks the request ID to match async - responses and prevent race conditions. + for the pipeline's primary LLM. + Tracks the request ID to match async responses and prevent race conditions. + + Args: + config_override: Optional per-request summary configuration. If provided, + overrides the default summary generation settings from + ``self._auto_config.summary_config``. """ # Generate unique request ID request_id = str(uuid.uuid4()) - min_keep = self._config.min_messages_after_summary + summary_config = config_override or self._auto_config.summary_config # Mark summarization in progress self._summarization_in_progress = True @@ -251,16 +297,16 @@ class LLMContextSummarizer(BaseObject): request_frame = LLMContextSummaryRequestFrame( request_id=request_id, context=self._context, - min_messages_to_keep=min_keep, - target_context_tokens=self._config.target_context_tokens, - summarization_prompt=self._config.summary_prompt, - summarization_timeout=self._config.summarization_timeout, + min_messages_to_keep=summary_config.min_messages_after_summary, + target_context_tokens=summary_config.target_context_tokens, + summarization_prompt=summary_config.summary_prompt, + summarization_timeout=summary_config.summarization_timeout, ) - if self._config.llm: + if summary_config.llm: # Use dedicated LLM directly — no need to involve the pipeline self.task_manager.create_task( - self._generate_summary_with_dedicated_llm(self._config.llm, request_frame), + self._generate_summary_with_dedicated_llm(summary_config.llm, request_frame), f"{self}-dedicated-llm-summary", ) else: @@ -323,7 +369,9 @@ class LLMContextSummarizer(BaseObject): """ logger.debug(f"{self}: Received summary result (request_id={frame.request_id})") - # Check if this is the result we're waiting for + # Check if this is the result we're waiting for. Both auto and manual + # summarization set _pending_summary_request_id via _request_summarization(), + # so this check always applies. if frame.request_id != self._pending_summary_request_id: logger.debug(f"{self}: Ignoring stale summary result (request_id={frame.request_id})") return @@ -360,7 +408,7 @@ class LLMContextSummarizer(BaseObject): if last_summarized_index >= len(self._context.messages): return False - min_keep = self._config.min_messages_after_summary + min_keep = self._auto_config.summary_config.min_messages_after_summary remaining = len(self._context.messages) - 1 - last_summarized_index if remaining < min_keep: return False @@ -377,6 +425,7 @@ class LLMContextSummarizer(BaseObject): summary: The generated summary text. last_summarized_index: Index of the last message that was summarized. """ + config = self._auto_config.summary_config messages = self._context.messages # Find the first system message to preserve. LLMSpecificMessage instances are excluded @@ -397,7 +446,7 @@ class LLMContextSummarizer(BaseObject): # Create summary message as a user message (the summary is context # provided *to* the assistant, not something the assistant said) - summary_content = self._config.summary_message_template.format(summary=summary) + summary_content = config.summary_message_template.format(summary=summary) summary_message = {"role": "user", "content": summary_content} # Reconstruct context From dfd0a515f320ae47091713c4a9a071c91fa7eafd Mon Sep 17 00:00:00 2001 From: filipi87 Date: Fri, 27 Feb 2026 18:42:13 -0300 Subject: [PATCH 0691/1060] Changelog entries for the context summarization improvements. --- changelog/3863.added.2.md | 1 + changelog/3863.added.md | 1 + changelog/3863.changed.md | 1 + changelog/3863.deprecated.md | 1 + 4 files changed, 4 insertions(+) create mode 100644 changelog/3863.added.2.md create mode 100644 changelog/3863.added.md create mode 100644 changelog/3863.changed.md create mode 100644 changelog/3863.deprecated.md diff --git a/changelog/3863.added.2.md b/changelog/3863.added.2.md new file mode 100644 index 000000000..9c0ab90ba --- /dev/null +++ b/changelog/3863.added.2.md @@ -0,0 +1 @@ +- Added `LLMContextSummaryConfig` (summary generation params: `target_context_tokens`, `min_messages_after_summary`, `summarization_prompt`) and `LLMAutoContextSummarizationConfig` (auto-trigger thresholds: `max_context_tokens`, `max_unsummarized_messages`, plus a nested `summary_config`). These replace the monolithic `LLMContextSummarizationConfig`. diff --git a/changelog/3863.added.md b/changelog/3863.added.md new file mode 100644 index 000000000..d6214aed0 --- /dev/null +++ b/changelog/3863.added.md @@ -0,0 +1 @@ +- Added `LLMSummarizeContextFrame` to trigger on-demand context summarization from anywhere in the pipeline (e.g. a function call tool). Accepts an optional `config: LLMContextSummaryConfig` to override summary generation settings per request. diff --git a/changelog/3863.changed.md b/changelog/3863.changed.md new file mode 100644 index 000000000..faf5712d8 --- /dev/null +++ b/changelog/3863.changed.md @@ -0,0 +1 @@ +- ⚠️ Renamed `LLMAssistantAggregatorParams` fields: `enable_context_summarization` → `enable_auto_context_summarization` and `context_summarization_config` → `auto_context_summarization_config` (now accepts `LLMAutoContextSummarizationConfig`). The old names still work with a `DeprecationWarning` for one release cycle. diff --git a/changelog/3863.deprecated.md b/changelog/3863.deprecated.md new file mode 100644 index 000000000..ba2311fbd --- /dev/null +++ b/changelog/3863.deprecated.md @@ -0,0 +1 @@ +- Deprecated `LLMContextSummarizationConfig`. Use `LLMAutoContextSummarizationConfig` with a nested `LLMContextSummaryConfig` instead. The old class emits a `DeprecationWarning`. From 69414e8a5ab8b9569c4e40b17cba7d186081fbdd Mon Sep 17 00:00:00 2001 From: filipi87 Date: Fri, 27 Feb 2026 18:42:23 -0300 Subject: [PATCH 0692/1060] Added example 54b-context-summarization-manual-openai.py demonstrating on-demand summarization triggered via a function call tool. --- ...54b-context-summarization-manual-openai.py | 179 ++++++++++++++++++ 1 file changed, 179 insertions(+) create mode 100644 examples/foundational/54b-context-summarization-manual-openai.py diff --git a/examples/foundational/54b-context-summarization-manual-openai.py b/examples/foundational/54b-context-summarization-manual-openai.py new file mode 100644 index 000000000..e8acf4bf1 --- /dev/null +++ b/examples/foundational/54b-context-summarization-manual-openai.py @@ -0,0 +1,179 @@ +# +# Copyright (c) 2024-2026, Daily +# +# SPDX-License-Identifier: BSD 2-Clause License +# + +"""Example demonstrating manual context summarization via a function call. + +This example shows how to trigger context summarization on demand rather than +automatically. The user can ask the bot to "summarize the conversation" and the +bot will call a function that pushes an LLMSummarizeContextFrame into the +pipeline, causing the LLM service to compress the conversation history. + +Unlike example 54, automatic summarization is NOT enabled here. Summarization +only happens when the user explicitly requests it through the function call. +""" + +import os + +from dotenv import load_dotenv +from loguru import logger + +from pipecat.adapters.schemas.function_schema import FunctionSchema +from pipecat.adapters.schemas.tools_schema import ToolsSchema +from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3 +from pipecat.audio.vad.silero import SileroVADAnalyzer +from pipecat.audio.vad.vad_analyzer import VADParams +from pipecat.frames.frames import LLMRunFrame, LLMSummarizeContextFrame +from pipecat.pipeline.pipeline import Pipeline +from pipecat.pipeline.runner import PipelineRunner +from pipecat.pipeline.task import PipelineParams, PipelineTask +from pipecat.processors.aggregators.llm_context import LLMContext +from pipecat.processors.aggregators.llm_response_universal import ( + LLMContextAggregatorPair, + LLMUserAggregatorParams, +) +from pipecat.runner.types import RunnerArguments +from pipecat.runner.utils import create_transport +from pipecat.services.cartesia.tts import CartesiaTTSService +from pipecat.services.deepgram.stt import DeepgramSTTService +from pipecat.services.llm_service import FunctionCallParams +from pipecat.services.openai.llm import OpenAILLMService +from pipecat.transports.base_transport import BaseTransport, TransportParams +from pipecat.transports.daily.transport import DailyParams +from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams +from pipecat.turns.user_stop import TurnAnalyzerUserTurnStopStrategy +from pipecat.turns.user_turn_strategies import UserTurnStrategies + +load_dotenv(override=True) + +# We use lambdas to defer transport parameter creation until the transport +# type is selected at runtime. +transport_params = { + "daily": lambda: DailyParams( + audio_in_enabled=True, + audio_out_enabled=True, + ), + "twilio": lambda: FastAPIWebsocketParams( + audio_in_enabled=True, + audio_out_enabled=True, + ), + "webrtc": lambda: TransportParams( + audio_in_enabled=True, + audio_out_enabled=True, + ), +} + + +async def summarize_conversation(params: FunctionCallParams): + """Trigger manual context summarization via a pipeline frame.""" + logger.info("Tool called: summarize_conversation") + await params.result_callback({"status": "summarization_requested"}) + await params.llm.queue_frame(LLMSummarizeContextFrame()) + + +async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): + logger.info("Starting bot") + + stt = DeepgramSTTService(api_key=os.getenv("DEEPGRAM_API_KEY")) + + tts = CartesiaTTSService( + api_key=os.getenv("CARTESIA_API_KEY"), + voice_id="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady + ) + + llm = OpenAILLMService(api_key=os.getenv("OPENAI_API_KEY")) + + llm.register_function("summarize_conversation", summarize_conversation) + + summarize_function = FunctionSchema( + name="summarize_conversation", + description=( + "Summarize and compress the conversation history. " + "Call this when the user asks you to summarize the conversation " + "or when you want to free up context space." + ), + properties={}, + required=[], + ) + tools = ToolsSchema(standard_tools=[summarize_function]) + + messages = [ + { + "role": "system", + "content": ( + "You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your " + "capabilities in a succinct way. Your output will be spoken aloud, so avoid " + "special characters that can't easily be spoken, such as emojis or bullet points. " + "Respond to what the user said in a creative and helpful way. " + "If the user asks you to summarize the conversation, call the " + "summarize_conversation function. After summarization, briefly acknowledge " + "that the conversation history has been compressed." + ), + }, + ] + + context = LLMContext(messages, tools=tools) + + # Automatic summarization is NOT enabled here (enable_auto_context_summarization + # defaults to False). The summarizer is still created internally so that + # LLMSummarizeContextFrame frames pushed via the function call are handled. + user_aggregator, assistant_aggregator = LLMContextAggregatorPair( + context, + user_params=LLMUserAggregatorParams( + user_turn_strategies=UserTurnStrategies( + stop=[TurnAnalyzerUserTurnStopStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3())] + ), + vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), + ), + ) + + pipeline = Pipeline( + [ + transport.input(), # Transport user input + stt, + user_aggregator, # User responses + llm, # LLM + tts, # TTS + transport.output(), # Transport bot output + assistant_aggregator, # Assistant spoken responses + ] + ) + + task = PipelineTask( + pipeline, + params=PipelineParams( + enable_metrics=True, + enable_usage_metrics=True, + ), + idle_timeout_secs=runner_args.pipeline_idle_timeout_secs, + ) + + @transport.event_handler("on_client_connected") + async def on_client_connected(transport, client): + logger.info("Client connected") + # Kick off the conversation. + messages.append({"role": "system", "content": "Please introduce yourself to the user."}) + await task.queue_frames([LLMRunFrame()]) + + @transport.event_handler("on_client_disconnected") + async def on_client_disconnected(transport, client): + logger.info("Client disconnected") + await task.cancel() + + runner = PipelineRunner(handle_sigint=runner_args.handle_sigint) + + await runner.run(task) + + +async def bot(runner_args: RunnerArguments): + """Main bot entry point compatible with Pipecat Cloud.""" + transport = await create_transport(runner_args, transport_params) + await run_bot(transport, runner_args) + + +if __name__ == "__main__": + from pipecat.runner.run import main + + main() From 0839e3813f658998f03ccd750b7084088caecd21 Mon Sep 17 00:00:00 2001 From: filipi87 Date: Fri, 27 Feb 2026 18:42:39 -0300 Subject: [PATCH 0693/1060] Refactoring the examples to use the new context summarization classes. --- .../54-context-summarization-openai.py | 15 +++++--- .../54a-context-summarization-google.py | 15 +++++--- ...54c-context-summarization-dedicated-llm.py | 35 +++++++++++-------- 3 files changed, 40 insertions(+), 25 deletions(-) diff --git a/examples/foundational/54-context-summarization-openai.py b/examples/foundational/54-context-summarization-openai.py index 45f27854f..ff6701bec 100644 --- a/examples/foundational/54-context-summarization-openai.py +++ b/examples/foundational/54-context-summarization-openai.py @@ -41,7 +41,10 @@ from pipecat.services.openai.llm import OpenAILLMService from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams -from pipecat.utils.context.llm_context_summarization import LLMContextSummarizationConfig +from pipecat.utils.context.llm_context_summarization import ( + LLMAutoContextSummarizationConfig, + LLMContextSummaryConfig, +) load_dotenv(override=True) @@ -120,14 +123,16 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): vad_analyzer=SileroVADAnalyzer(), ), assistant_params=LLMAssistantAggregatorParams( - enable_context_summarization=True, + enable_auto_context_summarization=True, # Optional: customize context summarization behavior # Using low limits to demonstrate the feature quickly - context_summarization_config=LLMContextSummarizationConfig( + auto_context_summarization_config=LLMAutoContextSummarizationConfig( max_context_tokens=1000, # Trigger summarization at 1000 tokens - target_context_tokens=800, # Target context size for the summarization max_unsummarized_messages=10, # Or when 10 new messages accumulate - min_messages_after_summary=2, # Keep last 2 messages uncompressed + summary_config=LLMContextSummaryConfig( + target_context_tokens=800, # Target context size for the summarization + min_messages_after_summary=2, # Keep last 2 messages uncompressed + ), ), ), ) diff --git a/examples/foundational/54a-context-summarization-google.py b/examples/foundational/54a-context-summarization-google.py index 2ce29e959..7d2a91310 100644 --- a/examples/foundational/54a-context-summarization-google.py +++ b/examples/foundational/54a-context-summarization-google.py @@ -41,7 +41,10 @@ from pipecat.services.llm_service import FunctionCallParams from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams -from pipecat.utils.context.llm_context_summarization import LLMContextSummarizationConfig +from pipecat.utils.context.llm_context_summarization import ( + LLMAutoContextSummarizationConfig, + LLMContextSummaryConfig, +) load_dotenv(override=True) @@ -120,14 +123,16 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): vad_analyzer=SileroVADAnalyzer(), ), assistant_params=LLMAssistantAggregatorParams( - enable_context_summarization=True, + enable_auto_context_summarization=True, # Optional: customize context summarization behavior # Using low limits to demonstrate the feature quickly - context_summarization_config=LLMContextSummarizationConfig( + auto_context_summarization_config=LLMAutoContextSummarizationConfig( max_context_tokens=1000, # Trigger summarization at 1000 tokens - target_context_tokens=800, # Target context size for the summarization max_unsummarized_messages=10, # Or when 10 new messages accumulate - min_messages_after_summary=2, # Keep last 2 messages uncompressed + summary_config=LLMContextSummaryConfig( + target_context_tokens=800, # Target context size for the summarization + min_messages_after_summary=2, # Keep last 2 messages uncompressed + ), ), ), ) diff --git a/examples/foundational/54c-context-summarization-dedicated-llm.py b/examples/foundational/54c-context-summarization-dedicated-llm.py index 3b2195e80..1dce3890f 100644 --- a/examples/foundational/54c-context-summarization-dedicated-llm.py +++ b/examples/foundational/54c-context-summarization-dedicated-llm.py @@ -44,7 +44,10 @@ from pipecat.services.openai.llm import OpenAILLMService from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams -from pipecat.utils.context.llm_context_summarization import LLMContextSummarizationConfig +from pipecat.utils.context.llm_context_summarization import ( + LLMAutoContextSummarizationConfig, + LLMContextSummaryConfig, +) load_dotenv(override=True) @@ -147,23 +150,25 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): vad_analyzer=SileroVADAnalyzer(), ), assistant_params=LLMAssistantAggregatorParams( - enable_context_summarization=True, - context_summarization_config=LLMContextSummarizationConfig( + enable_auto_context_summarization=True, + auto_context_summarization_config=LLMAutoContextSummarizationConfig( # Trigger thresholds (low values to demonstrate quickly) max_context_tokens=1000, max_unsummarized_messages=10, - # Summary generation - target_context_tokens=800, - min_messages_after_summary=2, - summarization_prompt=CUSTOM_SUMMARIZATION_PROMPT, - # Custom summary format - wrap in XML tags so the system - # prompt can identify summaries vs. live conversation - summary_message_template="\n{summary}\n", - # Use a dedicated cheap LLM for summarization instead of - # the primary conversation model - llm=summarization_llm, - # Cancel summarization if it takes longer than 60 seconds - summarization_timeout=60.0, + summary_config=LLMContextSummaryConfig( + # Summary generation + target_context_tokens=800, + min_messages_after_summary=2, + summarization_prompt=CUSTOM_SUMMARIZATION_PROMPT, + # Custom summary format - wrap in XML tags so the system + # prompt can identify summaries vs. live conversation + summary_message_template="\n{summary}\n", + # Use a dedicated cheap LLM for summarization instead of + # the primary conversation model + llm=summarization_llm, + # Cancel summarization if it takes longer than 60 seconds + summarization_timeout=60.0, + ), ), ), ) From d077a810ae22b4270abb0791e524298e9e99ab00 Mon Sep 17 00:00:00 2001 From: filipi87 Date: Fri, 27 Feb 2026 18:42:50 -0300 Subject: [PATCH 0694/1060] Fixing context summarization tests --- tests/test_context_summarization.py | 104 ++++++++++++++--- tests/test_llm_context_summarizer.py | 162 ++++++++++++++++++++++++--- 2 files changed, 232 insertions(+), 34 deletions(-) diff --git a/tests/test_context_summarization.py b/tests/test_context_summarization.py index ca56e7a32..10223a606 100644 --- a/tests/test_context_summarization.py +++ b/tests/test_context_summarization.py @@ -14,8 +14,10 @@ from pipecat.frames.frames import LLMContextSummaryRequestFrame, LLMContextSumma from pipecat.processors.aggregators.llm_context import LLMContext, LLMSpecificMessage from pipecat.services.llm_service import LLMService from pipecat.utils.context.llm_context_summarization import ( + LLMAutoContextSummarizationConfig, LLMContextSummarizationConfig, LLMContextSummarizationUtil, + LLMContextSummaryConfig, ) @@ -167,43 +169,109 @@ class TestContextSummarizationMixin(unittest.TestCase): self.assertIn("USER: First part Second part", transcript) -class TestLLMContextSummarizationConfig(unittest.TestCase): - """Tests for LLMContextSummarizationConfig.""" +class TestLLMContextSummaryConfig(unittest.TestCase): + """Tests for LLMContextSummaryConfig.""" def test_default_config(self): """Test default configuration values.""" - config = LLMContextSummarizationConfig() + config = LLMContextSummaryConfig() - self.assertEqual(config.max_context_tokens, 8000) - self.assertEqual(config.max_unsummarized_messages, 20) + self.assertEqual(config.target_context_tokens, 6000) self.assertEqual(config.min_messages_after_summary, 4) self.assertIsNone(config.summarization_prompt) def test_custom_config(self): """Test custom configuration.""" - config = LLMContextSummarizationConfig( - max_context_tokens=2500, + config = LLMContextSummaryConfig( target_context_tokens=2000, - max_unsummarized_messages=15, min_messages_after_summary=4, summarization_prompt="Custom prompt", ) - self.assertEqual(config.max_context_tokens, 2500) self.assertEqual(config.target_context_tokens, 2000) - self.assertEqual(config.max_unsummarized_messages, 15) self.assertEqual(config.min_messages_after_summary, 4) self.assertEqual(config.summary_prompt, "Custom prompt") def test_summary_prompt_property(self): """Test summary_prompt property uses default when None.""" - config = LLMContextSummarizationConfig() + config = LLMContextSummaryConfig() self.assertIn("summarizing a conversation", config.summary_prompt.lower()) - config_with_custom = LLMContextSummarizationConfig(summarization_prompt="Custom") + config_with_custom = LLMContextSummaryConfig(summarization_prompt="Custom") self.assertEqual(config_with_custom.summary_prompt, "Custom") +class TestLLMAutoContextSummarizationConfig(unittest.TestCase): + """Tests for LLMAutoContextSummarizationConfig.""" + + def test_default_config(self): + """Test default configuration values.""" + config = LLMAutoContextSummarizationConfig() + + self.assertEqual(config.max_context_tokens, 8000) + self.assertEqual(config.max_unsummarized_messages, 20) + self.assertEqual(config.summary_config.target_context_tokens, 6000) + self.assertEqual(config.summary_config.min_messages_after_summary, 4) + + def test_custom_config(self): + """Test custom configuration.""" + config = LLMAutoContextSummarizationConfig( + max_context_tokens=2500, + max_unsummarized_messages=15, + summary_config=LLMContextSummaryConfig( + target_context_tokens=2000, + min_messages_after_summary=4, + summarization_prompt="Custom prompt", + ), + ) + + self.assertEqual(config.max_context_tokens, 2500) + self.assertEqual(config.max_unsummarized_messages, 15) + self.assertEqual(config.summary_config.target_context_tokens, 2000) + self.assertEqual(config.summary_config.min_messages_after_summary, 4) + self.assertEqual(config.summary_config.summary_prompt, "Custom prompt") + + def test_target_tokens_auto_adjusted(self): + """Test that target_context_tokens is auto-adjusted when it exceeds max.""" + config = LLMAutoContextSummarizationConfig( + max_context_tokens=1000, + summary_config=LLMContextSummaryConfig(target_context_tokens=9000), + ) + self.assertLessEqual(config.summary_config.target_context_tokens, config.max_context_tokens) + + +class TestLLMContextSummarizationConfigDeprecated(unittest.TestCase): + """Tests for deprecated LLMContextSummarizationConfig.""" + + def test_emits_deprecation_warning(self): + """Test that instantiating the deprecated config emits a DeprecationWarning.""" + with self.assertWarns(DeprecationWarning): + LLMContextSummarizationConfig() + + def test_to_auto_config(self): + """Test conversion to the new LLMAutoContextSummarizationConfig.""" + import warnings + + with warnings.catch_warnings(): + warnings.simplefilter("ignore", DeprecationWarning) + old_config = LLMContextSummarizationConfig( + max_context_tokens=2500, + target_context_tokens=2000, + max_unsummarized_messages=15, + min_messages_after_summary=4, + summarization_prompt="Custom", + ) + + new_config = old_config.to_auto_config() + + self.assertIsInstance(new_config, LLMAutoContextSummarizationConfig) + self.assertEqual(new_config.max_context_tokens, 2500) + self.assertEqual(new_config.max_unsummarized_messages, 15) + self.assertEqual(new_config.summary_config.target_context_tokens, 2000) + self.assertEqual(new_config.summary_config.min_messages_after_summary, 4) + self.assertEqual(new_config.summary_config.summarization_prompt, "Custom") + + class TestFunctionCallHandling(unittest.TestCase): """Tests for function call handling in summarization.""" @@ -670,10 +738,12 @@ class TestDedicatedLLMSummarization(unittest.IsolatedAsyncioTestCase): {"role": "user", "content": f"Test message {i} that adds tokens to context."} ) - config = LLMContextSummarizationConfig( + config = LLMAutoContextSummarizationConfig( max_context_tokens=50, # Very low to trigger easily - llm=dedicated_llm, - summarization_timeout=5.0, + summary_config=LLMContextSummaryConfig( + llm=dedicated_llm, + summarization_timeout=5.0, + ), ) return context, config @@ -736,7 +806,7 @@ class TestDedicatedLLMSummarization(unittest.IsolatedAsyncioTestCase): dedicated_llm._generate_summary = slow_summary context, config = self._create_context_and_config(dedicated_llm) - config.summarization_timeout = 0.1 # Very short timeout + config.summary_config.summarization_timeout = 0.1 # Very short timeout summarizer = LLMContextSummarizer(context=context, config=config) await summarizer.setup(self.task_manager) @@ -826,7 +896,7 @@ class TestDedicatedLLMSummarization(unittest.IsolatedAsyncioTestCase): {"role": "user", "content": f"Test message {i} that adds tokens to context."} ) - config = LLMContextSummarizationConfig(max_context_tokens=50) + config = LLMAutoContextSummarizationConfig(max_context_tokens=50) summarizer = LLMContextSummarizer(context=context, config=config) await summarizer.setup(self.task_manager) diff --git a/tests/test_llm_context_summarizer.py b/tests/test_llm_context_summarizer.py index 0439d403d..7e8b326f9 100644 --- a/tests/test_llm_context_summarizer.py +++ b/tests/test_llm_context_summarizer.py @@ -12,6 +12,7 @@ from pipecat.frames.frames import ( LLMContextSummaryRequestFrame, LLMContextSummaryResultFrame, LLMFullResponseStartFrame, + LLMSummarizeContextFrame, ) from pipecat.processors.aggregators.llm_context import LLMContext from pipecat.processors.aggregators.llm_context_summarizer import ( @@ -19,7 +20,10 @@ from pipecat.processors.aggregators.llm_context_summarizer import ( SummaryAppliedEvent, ) from pipecat.utils.asyncio.task_manager import TaskManager, TaskManagerParams -from pipecat.utils.context.llm_context_summarization import LLMContextSummarizationConfig +from pipecat.utils.context.llm_context_summarization import ( + LLMAutoContextSummarizationConfig, + LLMContextSummaryConfig, +) class TestLLMContextSummarizer(unittest.IsolatedAsyncioTestCase): @@ -35,7 +39,7 @@ class TestLLMContextSummarizer(unittest.IsolatedAsyncioTestCase): async def test_summarization_triggered_by_token_limit(self): """Test that summarization is triggered when token limit is reached.""" - config = LLMContextSummarizationConfig( + config = LLMAutoContextSummarizationConfig( max_context_tokens=100, # Very low to trigger easily max_unsummarized_messages=100, # High so it doesn't trigger by message count ) @@ -71,7 +75,7 @@ class TestLLMContextSummarizer(unittest.IsolatedAsyncioTestCase): async def test_summarization_triggered_by_message_count(self): """Test that summarization is triggered when message count threshold is reached.""" - config = LLMContextSummarizationConfig( + config = LLMAutoContextSummarizationConfig( max_context_tokens=100000, # Very high so it doesn't trigger by tokens max_unsummarized_messages=5, # Low to trigger easily ) @@ -101,7 +105,7 @@ class TestLLMContextSummarizer(unittest.IsolatedAsyncioTestCase): async def test_summarization_not_triggered_below_thresholds(self): """Test that summarization is not triggered when below thresholds.""" - config = LLMContextSummarizationConfig( + config = LLMAutoContextSummarizationConfig( max_context_tokens=10000, max_unsummarized_messages=20, ) @@ -130,7 +134,7 @@ class TestLLMContextSummarizer(unittest.IsolatedAsyncioTestCase): async def test_summarization_in_progress_prevents_duplicate(self): """Test that a summarization in progress prevents triggering another.""" - config = LLMContextSummarizationConfig( + config = LLMAutoContextSummarizationConfig( max_context_tokens=50, # Very low max_unsummarized_messages=100, ) @@ -161,7 +165,10 @@ class TestLLMContextSummarizer(unittest.IsolatedAsyncioTestCase): async def test_summary_result_handling(self): """Test that summary results are processed and applied correctly.""" - config = LLMContextSummarizationConfig(max_context_tokens=50, min_messages_after_summary=2) + config = LLMAutoContextSummarizationConfig( + max_context_tokens=50, + summary_config=LLMContextSummaryConfig(min_messages_after_summary=2), + ) summarizer = LLMContextSummarizer(context=self.context, config=config) await summarizer.setup(self.task_manager) @@ -208,7 +215,7 @@ class TestLLMContextSummarizer(unittest.IsolatedAsyncioTestCase): async def test_interruption_cancels_summarization(self): """Test that an interruption cancels pending summarization.""" - config = LLMContextSummarizationConfig(max_context_tokens=50) + config = LLMAutoContextSummarizationConfig(max_context_tokens=50) summarizer = LLMContextSummarizer(context=self.context, config=config) await summarizer.setup(self.task_manager) @@ -238,7 +245,10 @@ class TestLLMContextSummarizer(unittest.IsolatedAsyncioTestCase): async def test_stale_summary_result_ignored(self): """Test that stale summary results are ignored.""" - config = LLMContextSummarizationConfig(max_context_tokens=50, min_messages_after_summary=2) + config = LLMAutoContextSummarizationConfig( + max_context_tokens=50, + summary_config=LLMContextSummaryConfig(min_messages_after_summary=2), + ) summarizer = LLMContextSummarizer(context=self.context, config=config) await summarizer.setup(self.task_manager) @@ -294,9 +304,116 @@ class TestLLMContextSummarizer(unittest.IsolatedAsyncioTestCase): await summarizer.cleanup() + async def test_manual_summarization_via_frame(self): + """Test that LLMSummarizeContextFrame triggers summarization on demand.""" + config = LLMAutoContextSummarizationConfig( + max_context_tokens=100000, # High — auto trigger would never fire + max_unsummarized_messages=100, + ) + + summarizer = LLMContextSummarizer( + context=self.context, + config=config, + auto_trigger=False, # Disable auto; only manual requests should work + ) + await summarizer.setup(self.task_manager) + + request_frame = None + + @summarizer.event_handler("on_request_summarization") + async def on_request_summarization(summarizer, frame): + nonlocal request_frame + request_frame = frame + + # Add messages + for i in range(5): + self.context.add_message({"role": "user", "content": f"Message {i}"}) + + # Auto-trigger should NOT fire even on LLMFullResponseStartFrame + await summarizer.process_frame(LLMFullResponseStartFrame()) + self.assertIsNone(request_frame) + + # Manual trigger via LLMSummarizeContextFrame should fire + await summarizer.process_frame(LLMSummarizeContextFrame()) + self.assertIsNotNone(request_frame) + self.assertIsInstance(request_frame, LLMContextSummaryRequestFrame) + + # The request must have a valid request_id and carry the current context + self.assertTrue(request_frame.request_id) + self.assertEqual(request_frame.context, self.context) + + await summarizer.cleanup() + + async def test_manual_summarization_with_config_override(self): + """Test that LLMSummarizeContextFrame can override default summary config.""" + config = LLMAutoContextSummarizationConfig( + max_context_tokens=100000, + summary_config=LLMContextSummaryConfig( + target_context_tokens=6000, + min_messages_after_summary=4, + ), + ) + + summarizer = LLMContextSummarizer(context=self.context, config=config) + await summarizer.setup(self.task_manager) + + request_frame = None + + @summarizer.event_handler("on_request_summarization") + async def on_request_summarization(summarizer, frame): + nonlocal request_frame + request_frame = frame + + for i in range(5): + self.context.add_message({"role": "user", "content": f"Message {i}"}) + + # Push a manual frame with custom config overrides + custom_config = LLMContextSummaryConfig( + target_context_tokens=500, + min_messages_after_summary=1, + ) + await summarizer.process_frame(LLMSummarizeContextFrame(config=custom_config)) + + self.assertIsNotNone(request_frame) + # The request should use the overridden values + self.assertEqual(request_frame.target_context_tokens, 500) + self.assertEqual(request_frame.min_messages_to_keep, 1) + + await summarizer.cleanup() + + async def test_manual_summarization_blocked_when_in_progress(self): + """Test that a second LLMSummarizeContextFrame is ignored while one is in progress.""" + config = LLMAutoContextSummarizationConfig(max_context_tokens=100000) + + summarizer = LLMContextSummarizer(context=self.context, config=config) + await summarizer.setup(self.task_manager) + + request_count = 0 + + @summarizer.event_handler("on_request_summarization") + async def on_request_summarization(summarizer, frame): + nonlocal request_count + request_count += 1 + + for i in range(5): + self.context.add_message({"role": "user", "content": f"Message {i}"}) + + # First manual request + await summarizer.process_frame(LLMSummarizeContextFrame()) + self.assertEqual(request_count, 1) + + # Second manual request while first is in progress — should be ignored + await summarizer.process_frame(LLMSummarizeContextFrame()) + self.assertEqual(request_count, 1) + + await summarizer.cleanup() + async def test_summary_message_role_is_user(self): """Test that the summary message uses the user role.""" - config = LLMContextSummarizationConfig(max_context_tokens=50, min_messages_after_summary=2) + config = LLMAutoContextSummarizationConfig( + max_context_tokens=50, + summary_config=LLMContextSummaryConfig(min_messages_after_summary=2), + ) summarizer = LLMContextSummarizer(context=self.context, config=config) await summarizer.setup(self.task_manager) @@ -335,7 +452,10 @@ class TestLLMContextSummarizer(unittest.IsolatedAsyncioTestCase): async def test_summary_message_default_template(self): """Test that the default summary_message_template is used.""" - config = LLMContextSummarizationConfig(max_context_tokens=50, min_messages_after_summary=2) + config = LLMAutoContextSummarizationConfig( + max_context_tokens=50, + summary_config=LLMContextSummaryConfig(min_messages_after_summary=2), + ) summarizer = LLMContextSummarizer(context=self.context, config=config) await summarizer.setup(self.task_manager) @@ -377,10 +497,12 @@ class TestLLMContextSummarizer(unittest.IsolatedAsyncioTestCase): async def test_summary_message_custom_template(self): """Test that a custom summary_message_template is applied.""" - config = LLMContextSummarizationConfig( + config = LLMAutoContextSummarizationConfig( max_context_tokens=50, - min_messages_after_summary=2, - summary_message_template="\n{summary}\n", + summary_config=LLMContextSummaryConfig( + min_messages_after_summary=2, + summary_message_template="\n{summary}\n", + ), ) summarizer = LLMContextSummarizer(context=self.context, config=config) @@ -420,7 +542,10 @@ class TestLLMContextSummarizer(unittest.IsolatedAsyncioTestCase): async def test_on_summary_applied_event(self): """Test that on_summary_applied event fires with correct data.""" - config = LLMContextSummarizationConfig(max_context_tokens=50, min_messages_after_summary=2) + config = LLMAutoContextSummarizationConfig( + max_context_tokens=50, + summary_config=LLMContextSummaryConfig(min_messages_after_summary=2), + ) summarizer = LLMContextSummarizer(context=self.context, config=config) await summarizer.setup(self.task_manager) @@ -474,7 +599,10 @@ class TestLLMContextSummarizer(unittest.IsolatedAsyncioTestCase): async def test_on_summary_applied_not_fired_on_error(self): """Test that on_summary_applied event is NOT fired when summarization fails.""" - config = LLMContextSummarizationConfig(max_context_tokens=50, min_messages_after_summary=2) + config = LLMAutoContextSummarizationConfig( + max_context_tokens=50, + summary_config=LLMContextSummaryConfig(min_messages_after_summary=2), + ) summarizer = LLMContextSummarizer(context=self.context, config=config) await summarizer.setup(self.task_manager) @@ -515,9 +643,9 @@ class TestLLMContextSummarizer(unittest.IsolatedAsyncioTestCase): async def test_request_frame_includes_timeout(self): """Test that the request frame includes the configured summarization_timeout.""" - config = LLMContextSummarizationConfig( + config = LLMAutoContextSummarizationConfig( max_context_tokens=50, - summarization_timeout=60.0, + summary_config=LLMContextSummaryConfig(summarization_timeout=60.0), ) summarizer = LLMContextSummarizer(context=self.context, config=config) From 000d38e253776b25fd8693d5fc129a02ec76a413 Mon Sep 17 00:00:00 2001 From: macaki Date: Fri, 27 Feb 2026 15:17:23 -0700 Subject: [PATCH 0695/1060] [Rime] Both mist and arcana now support the speedAlpha parameter. --- src/pipecat/services/rime/tts.py | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/src/pipecat/services/rime/tts.py b/src/pipecat/services/rime/tts.py index d5f97e028..2dbaf2760 100644 --- a/src/pipecat/services/rime/tts.py +++ b/src/pipecat/services/rime/tts.py @@ -301,6 +301,8 @@ class RimeTTSService(AudioContextTTSService): params["lang"] = self._settings.language if self._settings.segment is not None: params["segment"] = self._settings.segment + if self._settings.speedAlpha is not None: + params["speedAlpha"] = self._settings.speedAlpha if self._settings.model == "arcana": if self._settings.repetition_penalty is not None: @@ -310,8 +312,6 @@ class RimeTTSService(AudioContextTTSService): if self._settings.top_p is not None: params["top_p"] = self._settings.top_p else: # mistv2/mist - if self._settings.speedAlpha is not None: - params["speedAlpha"] = self._settings.speedAlpha if self._settings.reduceLatency is not None: params["reduceLatency"] = self._settings.reduceLatency if self._settings.pauseBetweenBrackets is not None: From 56f2564ed10da68d96675e7a482a0f8f29e26561 Mon Sep 17 00:00:00 2001 From: Rupesh Date: Fri, 27 Feb 2026 14:45:37 -0800 Subject: [PATCH 0696/1060] Use local variable instead of instance variable for RTVI prepend decision Replace _rtvi_external instance variable with a local prepend_rtvi flag since it is only used during __init__ to decide whether to prepend the RTVIProcessor to the pipeline. --- src/pipecat/pipeline/task.py | 9 +++------ 1 file changed, 3 insertions(+), 6 deletions(-) diff --git a/src/pipecat/pipeline/task.py b/src/pipecat/pipeline/task.py index 1db23e7d4..eeb39c9b6 100644 --- a/src/pipecat/pipeline/task.py +++ b/src/pipecat/pipeline/task.py @@ -330,7 +330,7 @@ class PipelineTask(BasePipelineTask): # RTVI support self._rtvi = None - self._rtvi_external = False + prepend_rtvi = False external_rtvi = self._find_processor(pipeline, RTVIProcessor) external_observer_found = any(isinstance(o, RTVIObserver) for o in observers) @@ -350,10 +350,10 @@ class PipelineTask(BasePipelineTask): "They are both added by default, no need to add them yourself." ) self._rtvi = external_rtvi - self._rtvi_external = True elif enable_rtvi: self._rtvi = rtvi_processor or RTVIProcessor() observers.append(self._rtvi.create_rtvi_observer(params=rtvi_observer_params)) + prepend_rtvi = True if self._rtvi: # Automatically call RTVIProcessor.set_bot_ready() @@ -393,10 +393,7 @@ class PipelineTask(BasePipelineTask): # Only prepend the RTVIProcessor if we created it ourselves. When the # user already placed it inside their pipeline we must not insert it # again or it will appear twice in the frame chain. - if self._rtvi and not self._rtvi_external: - processors = [self._rtvi, pipeline] - else: - processors = [pipeline] + processors = [self._rtvi, pipeline] if prepend_rtvi else [pipeline] self._pipeline = Pipeline(processors, source=source, sink=sink) # The task observer acts as a proxy to the provided observers. This way, From ef00f27d53a1733e5f94ca31b442edbee102d6f3 Mon Sep 17 00:00:00 2001 From: zack Date: Fri, 27 Feb 2026 17:58:05 -0500 Subject: [PATCH 0697/1060] Fix incorrect await on synchronous request_finalize() method The request_finalize() method in STTService is synchronous (sets a flag), but was being called with await in the VAD turn endpoint handling code. This caused "object NoneType can't be used in 'await' expression" errors. Also includes automatic formatting improvements from ruff. --- src/pipecat/services/assemblyai/models.py | 6 +-- src/pipecat/services/assemblyai/stt.py | 55 ++++++++++++++++------- 2 files changed, 43 insertions(+), 18 deletions(-) diff --git a/src/pipecat/services/assemblyai/models.py b/src/pipecat/services/assemblyai/models.py index fb883ac99..949f2e00e 100644 --- a/src/pipecat/services/assemblyai/models.py +++ b/src/pipecat/services/assemblyai/models.py @@ -152,9 +152,9 @@ class AssemblyAIConnectionParams(BaseModel): max_turn_silence: Optional[int] = None keyterms_prompt: Optional[List[str]] = None prompt: Optional[str] = None - speech_model: Literal["universal-streaming-english", "universal-streaming-multilingual", "u3-rt-pro"] = ( - "u3-rt-pro" - ) + speech_model: Literal[ + "universal-streaming-english", "universal-streaming-multilingual", "u3-rt-pro" + ] = "u3-rt-pro" language_detection: Optional[bool] = None format_turns: bool = True speaker_labels: Optional[bool] = None diff --git a/src/pipecat/services/assemblyai/stt.py b/src/pipecat/services/assemblyai/stt.py index 445ab7b73..b0254d410 100644 --- a/src/pipecat/services/assemblyai/stt.py +++ b/src/pipecat/services/assemblyai/stt.py @@ -73,7 +73,9 @@ def map_language_from_assemblyai(language_code: str) -> Language: # Try to match the language code directly return Language(language_code.lower()) except ValueError: - logger.warning(f"Unknown language code from AssemblyAI: {language_code}, defaulting to English") + logger.warning( + f"Unknown language code from AssemblyAI: {language_code}, defaulting to English" + ) return Language.EN @@ -304,7 +306,11 @@ class AssemblyAISTTService(WebsocketSTTService): return changed # If websocket is connected, send UpdateConfiguration for supported params - if self._websocket and self._websocket.state is State.OPEN and "connection_params" in changed: + if ( + self._websocket + and self._websocket.state is State.OPEN + and "connection_params" in changed + ): # Build UpdateConfiguration message update_config = {"type": "UpdateConfiguration"} conn_params = self._settings.connection_params @@ -314,7 +320,10 @@ class AssemblyAISTTService(WebsocketSTTService): # Check each potentially changed parameter if hasattr(conn_params, "keyterms_prompt"): - if old_conn_params is None or conn_params.keyterms_prompt != old_conn_params.keyterms_prompt: + if ( + old_conn_params is None + or conn_params.keyterms_prompt != old_conn_params.keyterms_prompt + ): if conn_params.keyterms_prompt is not None: update_config["keyterms_prompt"] = conn_params.keyterms_prompt logger.info(f"Updating keyterms_prompt to: {conn_params.keyterms_prompt}") @@ -332,16 +341,29 @@ class AssemblyAISTTService(WebsocketSTTService): logger.info(f"Updating prompt") if hasattr(conn_params, "max_turn_silence"): - if old_conn_params is None or conn_params.max_turn_silence != old_conn_params.max_turn_silence: + if ( + old_conn_params is None + or conn_params.max_turn_silence != old_conn_params.max_turn_silence + ): if conn_params.max_turn_silence is not None: update_config["max_turn_silence"] = conn_params.max_turn_silence - logger.info(f"Updating max_turn_silence to: {conn_params.max_turn_silence}ms") + logger.info( + f"Updating max_turn_silence to: {conn_params.max_turn_silence}ms" + ) if hasattr(conn_params, "min_end_of_turn_silence_when_confident"): - if old_conn_params is None or conn_params.min_end_of_turn_silence_when_confident != old_conn_params.min_end_of_turn_silence_when_confident: + if ( + old_conn_params is None + or conn_params.min_end_of_turn_silence_when_confident + != old_conn_params.min_end_of_turn_silence_when_confident + ): if conn_params.min_end_of_turn_silence_when_confident is not None: - update_config["min_end_of_turn_silence_when_confident"] = conn_params.min_end_of_turn_silence_when_confident - logger.info(f"Updating min_end_of_turn_silence_when_confident to: {conn_params.min_end_of_turn_silence_when_confident}ms") + update_config["min_end_of_turn_silence_when_confident"] = ( + conn_params.min_end_of_turn_silence_when_confident + ) + logger.info( + f"Updating min_end_of_turn_silence_when_confident to: {conn_params.min_end_of_turn_silence_when_confident}ms" + ) # Send update if we have parameters to update if len(update_config) > 1: # More than just "type" @@ -426,7 +448,7 @@ class AssemblyAISTTService(WebsocketSTTService): and self._websocket and self._websocket.state is State.OPEN ): - await self.request_finalize() + self.request_finalize() await self._websocket.send(json.dumps({"type": "ForceEndpoint"})) await self.start_processing_metrics() @@ -616,7 +638,9 @@ class AssemblyAISTTService(WebsocketSTTService): Only applies to Mode 2 (STT turn detection). In Mode 1, VAD + smart turn analyzer handle interruptions via the aggregator. """ - logger.debug(f"{self} SpeechStarted received (vad_force_turn_endpoint={self._vad_force_turn_endpoint})") + logger.debug( + f"{self} SpeechStarted received (vad_force_turn_endpoint={self._vad_force_turn_endpoint})" + ) if self._vad_force_turn_endpoint: logger.debug(f"{self} SpeechStarted ignored in Pipecat mode") return # Mode 1: handled by aggregator @@ -677,8 +701,7 @@ class AssemblyAISTTService(WebsocketSTTService): # Format transcript with speaker labels if format string provided if self._speaker_format: transcript_text = self._speaker_format.format( - speaker=message.speaker, - text=message.transcript + speaker=message.speaker, text=message.transcript ) # Determine if this is a final turn from AssemblyAI @@ -693,7 +716,7 @@ class AssemblyAISTTService(WebsocketSTTService): finalize_confirmed = bool(message.turn_is_formatted) if finalize_confirmed: self.confirm_finalize() - logger.debug(f"{self} Final transcript: \"{transcript_text}\"") + logger.debug(f'{self} Final transcript: "{transcript_text}"') await self.push_frame( TranscriptionFrame( transcript_text, @@ -706,7 +729,7 @@ class AssemblyAISTTService(WebsocketSTTService): await self._trace_transcription(transcript_text, True, language) await self.stop_processing_metrics() else: - logger.debug(f"{self} Interim transcript: \"{transcript_text}\"") + logger.debug(f'{self} Interim transcript: "{transcript_text}"') await self.push_frame( InterimTranscriptionFrame( transcript_text, @@ -720,7 +743,9 @@ class AssemblyAISTTService(WebsocketSTTService): # --- Mode 2: STT turn detection --- # SpeechStarted always arrives before transcripts with u3-rt-pro, # so UserStartedSpeakingFrame is guaranteed to be broadcast first. - logger.debug(f"{self} Transcript received in STT mode (_user_speaking={self._user_speaking})") + logger.debug( + f"{self} Transcript received in STT mode (_user_speaking={self._user_speaking})" + ) if is_final_turn: # STT mode: AssemblyAI controls finalization, just mark as finalized From d7ce1eedd956ea320d7fb980172494cb1aa8c3e2 Mon Sep 17 00:00:00 2001 From: zack Date: Fri, 27 Feb 2026 17:58:18 -0500 Subject: [PATCH 0698/1060] Add foundational examples for AssemblyAI u3-rt-pro - 07o-interruptible-assemblyai.py: Basic example using Pipecat VAD mode - 07o-interruptible-assemblyai-stt.py: Advanced example using STT-controlled turn detection with comprehensive documentation on u3-rt-pro features (turn detection tuning, prompt-based enhancement, speaker diarization) --- .../07o-interruptible-assemblyai-stt.py | 175 ++++++++++++++++++ 1 file changed, 175 insertions(+) create mode 100644 examples/foundational/07o-interruptible-assemblyai-stt.py diff --git a/examples/foundational/07o-interruptible-assemblyai-stt.py b/examples/foundational/07o-interruptible-assemblyai-stt.py new file mode 100644 index 000000000..5deaa82a1 --- /dev/null +++ b/examples/foundational/07o-interruptible-assemblyai-stt.py @@ -0,0 +1,175 @@ +# +# Copyright (c) 2024-2026, Daily +# +# SPDX-License-Identifier: BSD 2-Clause License +# + + +import os + +from dotenv import load_dotenv +from loguru import logger + +from pipecat.frames.frames import LLMRunFrame +from pipecat.pipeline.pipeline import Pipeline +from pipecat.pipeline.runner import PipelineRunner +from pipecat.pipeline.task import PipelineParams, PipelineTask +from pipecat.processors.aggregators.llm_context import LLMContext +from pipecat.processors.aggregators.llm_response_universal import ( + LLMContextAggregatorPair, + LLMUserAggregatorParams, +) +from pipecat.runner.types import RunnerArguments +from pipecat.runner.utils import create_transport +from pipecat.services.assemblyai.models import AssemblyAIConnectionParams +from pipecat.services.assemblyai.stt import AssemblyAISTTService +from pipecat.services.cartesia.tts import CartesiaTTSService +from pipecat.services.openai.llm import OpenAILLMService +from pipecat.transports.base_transport import BaseTransport, TransportParams +from pipecat.transports.daily.transport import DailyParams +from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams +from pipecat.turns.user_turn_strategies import ExternalUserTurnStrategies + +load_dotenv(override=True) + + +# We use lambdas to defer transport parameter creation until the transport +# type is selected at runtime. +transport_params = { + "daily": lambda: DailyParams( + audio_in_enabled=True, + audio_out_enabled=True, + ), + "twilio": lambda: FastAPIWebsocketParams( + audio_in_enabled=True, + audio_out_enabled=True, + ), + "webrtc": lambda: TransportParams( + audio_in_enabled=True, + audio_out_enabled=True, + ), +} + + +async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): + """AssemblyAI u3-rt-pro STT Example with STT-Controlled Turn Detection + + This example demonstrates using AssemblyAI's u3-rt-pro Speech-to-Text model + with STT-controlled turn detection for more natural conversation flow. + + Key features: + + 1. STT-Controlled Turn Detection + - Set `vad_force_turn_endpoint=False` to enable STT mode + - AssemblyAI's model determines when user starts/stops speaking + - Uses `ExternalUserTurnStrategies` instead of Pipecat's VAD + - More natural turn detection based on speech patterns and pauses + + 2. Advanced Turn Detection Tuning (STT Mode) + - `min_end_of_turn_silence_when_confident`: Minimum silence (ms) when confident + about end-of-turn. Lower values = faster responses. Default: 200ms + - `max_turn_silence`: Maximum silence (ms) before forcing end-of-turn. + Prevents long pauses. Default: 1000ms + + 3. Prompt-Based Transcription Enhancement + - Use `prompt` parameter to improve accuracy for specific names/terms + - Particularly useful for proper nouns, technical terms, domain vocabulary + - Example: "Names: Xiomara, Saoirse, Krzystof. Technical terms: API, OAuth." + + 4. Speaker Diarization (Optional) + - Enable with `speaker_labels=True` + - Automatically identifies different speakers in multi-party conversations + - TranscriptionFrame includes speaker_id field (e.g., "Speaker A", "Speaker B") + + 5. Language Detection (Optional, multilingual model only) + - Enable with `language_detection=True` + - Automatically detects spoken language + - Available with universal-streaming-multilingual model + + For more information: https://www.assemblyai.com/docs/speech-to-text/streaming + """ + logger.info(f"Starting bot") + + stt = AssemblyAISTTService( + api_key=os.getenv("ASSEMBLYAI_API_KEY"), + vad_force_turn_endpoint=False, # Enable STT-controlled turn detection + connection_params=AssemblyAIConnectionParams( + speech_model="u3-rt-pro", + # Optional: Tune turn detection timing (defaults shown below) + # min_end_of_turn_silence_when_confident=100, # Default + # max_turn_silence=1000, # Default + # Optional: Boost accuracy for specific names/terms + # prompt="Names: Xiomara, Saoirse, Krzystof. Technical terms: API, OAuth.", + # Optional: Enable speaker diarization + # speaker_labels=True, + ), + ) + + tts = CartesiaTTSService( + api_key=os.getenv("CARTESIA_API_KEY"), + voice_id="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady + ) + + llm = OpenAILLMService(api_key=os.getenv("OPENAI_API_KEY")) + + messages = [ + { + "role": "system", + "content": "You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + }, + ] + + context = LLMContext(messages) + user_aggregator, assistant_aggregator = LLMContextAggregatorPair( + context, + user_params=LLMUserAggregatorParams(user_turn_strategies=ExternalUserTurnStrategies()), + ) + + pipeline = Pipeline( + [ + transport.input(), # Transport user input + stt, # STT + user_aggregator, # User responses + llm, # LLM + tts, # TTS + transport.output(), # Transport bot output + assistant_aggregator, # Assistant spoken responses + ] + ) + + task = PipelineTask( + pipeline, + params=PipelineParams( + enable_metrics=True, + enable_usage_metrics=True, + ), + idle_timeout_secs=runner_args.pipeline_idle_timeout_secs, + ) + + @transport.event_handler("on_client_connected") + async def on_client_connected(transport, client): + logger.info(f"Client connected") + # Kick off the conversation. + messages.append({"role": "system", "content": "Please introduce yourself to the user."}) + await task.queue_frames([LLMRunFrame()]) + + @transport.event_handler("on_client_disconnected") + async def on_client_disconnected(transport, client): + logger.info(f"Client disconnected") + await task.cancel() + + runner = PipelineRunner(handle_sigint=runner_args.handle_sigint) + + await runner.run(task) + + +async def bot(runner_args: RunnerArguments): + """Main bot entry point compatible with Pipecat Cloud.""" + transport = await create_transport(runner_args, transport_params) + await run_bot(transport, runner_args) + + +if __name__ == "__main__": + from pipecat.runner.run import main + + main() From 950a8628dca00583f3f6748c244e19fe36826ed5 Mon Sep 17 00:00:00 2001 From: Mark Backman Date: Fri, 27 Feb 2026 19:49:45 -0500 Subject: [PATCH 0699/1060] Miscellaneous foundational example updates --- .../07c-interruptible-deepgram-flux.py | 6 +++++- .../07g-interruptible-openai-http.py | 1 - ...o-function-calling-gemini-openai-format.py | 20 +++++++++---------- ...54b-context-summarization-manual-openai.py | 9 +-------- uv.lock | 2 +- 5 files changed, 17 insertions(+), 21 deletions(-) diff --git a/examples/foundational/07c-interruptible-deepgram-flux.py b/examples/foundational/07c-interruptible-deepgram-flux.py index e51a30c1b..d2bcceaf7 100644 --- a/examples/foundational/07c-interruptible-deepgram-flux.py +++ b/examples/foundational/07c-interruptible-deepgram-flux.py @@ -10,6 +10,7 @@ import os from dotenv import load_dotenv from loguru import logger +from pipecat.audio.vad.silero import SileroVADAnalyzer from pipecat.frames.frames import LLMRunFrame from pipecat.pipeline.pipeline import Pipeline from pipecat.pipeline.runner import PipelineRunner @@ -72,7 +73,10 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): context = LLMContext(messages) user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, - user_params=LLMUserAggregatorParams(user_turn_strategies=ExternalUserTurnStrategies()), + user_params=LLMUserAggregatorParams( + user_turn_strategies=ExternalUserTurnStrategies(), + vad_analyzer=SileroVADAnalyzer(), + ), ) pipeline = Pipeline( diff --git a/examples/foundational/07g-interruptible-openai-http.py b/examples/foundational/07g-interruptible-openai-http.py index 325fd4ae4..65b2f8b9b 100644 --- a/examples/foundational/07g-interruptible-openai-http.py +++ b/examples/foundational/07g-interruptible-openai-http.py @@ -11,7 +11,6 @@ from dotenv import load_dotenv from loguru import logger from pipecat.audio.vad.silero import SileroVADAnalyzer -from pipecat.audio.vad.vad_analyzer import VADParams from pipecat.frames.frames import LLMRunFrame from pipecat.pipeline.pipeline import Pipeline from pipecat.pipeline.runner import PipelineRunner diff --git a/examples/foundational/14o-function-calling-gemini-openai-format.py b/examples/foundational/14o-function-calling-gemini-openai-format.py index c87c5278e..c3772eb2c 100644 --- a/examples/foundational/14o-function-calling-gemini-openai-format.py +++ b/examples/foundational/14o-function-calling-gemini-openai-format.py @@ -12,12 +12,15 @@ from loguru import logger from pipecat.adapters.schemas.function_schema import FunctionSchema from pipecat.adapters.schemas.tools_schema import ToolsSchema -from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3 from pipecat.audio.vad.silero import SileroVADAnalyzer from pipecat.frames.frames import LLMRunFrame, TTSSpeakFrame from pipecat.pipeline.pipeline import Pipeline from pipecat.pipeline.runner import PipelineRunner from pipecat.pipeline.task import PipelineParams, PipelineTask +from pipecat.processors.aggregators.llm_response_universal import ( + LLMContextAggregatorPair, + LLMUserAggregatorParams, +) from pipecat.processors.aggregators.openai_llm_context import OpenAILLMContext from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport @@ -42,20 +45,14 @@ transport_params = { "daily": lambda: DailyParams( audio_in_enabled=True, audio_out_enabled=True, - vad_analyzer=SileroVADAnalyzer(), - turn_analyzer=LocalSmartTurnAnalyzerV3(), ), "twilio": lambda: FastAPIWebsocketParams( audio_in_enabled=True, audio_out_enabled=True, - vad_analyzer=SileroVADAnalyzer(), - turn_analyzer=LocalSmartTurnAnalyzerV3(), ), "webrtc": lambda: TransportParams( audio_in_enabled=True, audio_out_enabled=True, - vad_analyzer=SileroVADAnalyzer(), - turn_analyzer=LocalSmartTurnAnalyzerV3(), ), } @@ -104,17 +101,20 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): ] context = OpenAILLMContext(messages, tools) - context_aggregator = llm.create_context_aggregator(context) + user_aggregator, assistant_aggregator = LLMContextAggregatorPair( + context, + user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()), + ) pipeline = Pipeline( [ transport.input(), stt, - context_aggregator.user(), + user_aggregator, llm, tts, transport.output(), - context_aggregator.assistant(), + assistant_aggregator, ] ) diff --git a/examples/foundational/54b-context-summarization-manual-openai.py b/examples/foundational/54b-context-summarization-manual-openai.py index e8acf4bf1..c1ff83ef0 100644 --- a/examples/foundational/54b-context-summarization-manual-openai.py +++ b/examples/foundational/54b-context-summarization-manual-openai.py @@ -22,9 +22,7 @@ from loguru import logger from pipecat.adapters.schemas.function_schema import FunctionSchema from pipecat.adapters.schemas.tools_schema import ToolsSchema -from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3 from pipecat.audio.vad.silero import SileroVADAnalyzer -from pipecat.audio.vad.vad_analyzer import VADParams from pipecat.frames.frames import LLMRunFrame, LLMSummarizeContextFrame from pipecat.pipeline.pipeline import Pipeline from pipecat.pipeline.runner import PipelineRunner @@ -121,12 +119,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): # LLMSummarizeContextFrame frames pushed via the function call are handled. user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, - user_params=LLMUserAggregatorParams( - user_turn_strategies=UserTurnStrategies( - stop=[TurnAnalyzerUserTurnStopStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3())] - ), - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), - ), + user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()), ) pipeline = Pipeline( diff --git a/uv.lock b/uv.lock index e368cfc45..a386ee81e 100644 --- a/uv.lock +++ b/uv.lock @@ -4691,7 +4691,7 @@ requires-dist = [ { name = "mlx-whisper", marker = "extra == 'mlx-whisper'", specifier = "~=0.4.2" }, { name = "nltk", specifier = ">=3.9.3,<4" }, { name = "noisereduce", marker = "extra == 'noisereduce'", specifier = "~=3.0.3" }, - { name = "numba", specifier = "==0.61.2" }, + { name = "numba", specifier = ">=0.61.2" }, { name = "numpy", specifier = ">=1.26.4,<3" }, { name = "nvidia-riva-client", marker = "extra == 'nvidia'", specifier = "~=2.21.1" }, { name = "onnxruntime", specifier = "~=1.23.2" }, From 6464230627b47225d31442cf3f95d3beb4718d50 Mon Sep 17 00:00:00 2001 From: Mark Backman Date: Fri, 27 Feb 2026 22:22:35 -0500 Subject: [PATCH 0700/1060] fix: use pull_request_target for docs workflow to access secrets from fork PRs The update-docs workflow intermittently failed with "Input required and not supplied: token" because pull_request events from fork PRs don't have access to repository secrets. Switching to pull_request_target runs the workflow in the base repo's context, ensuring secrets are always available. This is safe since the workflow only runs on already-merged PRs. --- .github/workflows/update-docs.yml | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/.github/workflows/update-docs.yml b/.github/workflows/update-docs.yml index 27453e74e..a9066762d 100644 --- a/.github/workflows/update-docs.yml +++ b/.github/workflows/update-docs.yml @@ -1,7 +1,7 @@ name: Update Documentation on PR Merge on: - pull_request: + pull_request_target: types: [closed] branches: [main] paths: From 9d4955054c53d80b6e005b4bb27af453b3cdcdd0 Mon Sep 17 00:00:00 2001 From: Mark Backman Date: Fri, 27 Feb 2026 22:35:29 -0500 Subject: [PATCH 0701/1060] Fix tracing to use ServiceSettings API instead of dict access The ServiceSettings refactor (PR #3714) changed self._settings from dicts to dataclass subclasses, but tracing code still used .items(), in containment, and subscript access, causing AttributeError on every traced call. Use given_fields() for iteration and attribute access for named fields. --- changelog/3879.changed.md | 1 + .../utils/tracing/service_attributes.py | 14 ++++++++------ .../utils/tracing/service_decorators.py | 19 +++++++------------ 3 files changed, 16 insertions(+), 18 deletions(-) create mode 100644 changelog/3879.changed.md diff --git a/changelog/3879.changed.md b/changelog/3879.changed.md new file mode 100644 index 000000000..2b69f63ce --- /dev/null +++ b/changelog/3879.changed.md @@ -0,0 +1 @@ +- Updated tracing code to use `ServiceSettings` dataclass API (`given_fields()`, attribute access) instead of dict-style access (`.items()`, `in`, subscript). diff --git a/src/pipecat/utils/tracing/service_attributes.py b/src/pipecat/utils/tracing/service_attributes.py index c8471a03b..97ac49d87 100644 --- a/src/pipecat/utils/tracing/service_attributes.py +++ b/src/pipecat/utils/tracing/service_attributes.py @@ -17,6 +17,8 @@ from typing import TYPE_CHECKING, Any, Dict, List, Optional if TYPE_CHECKING: from opentelemetry.trace import Span + from pipecat.services.settings import ServiceSettings + from pipecat.utils.tracing.setup import is_tracing_available if is_tracing_available(): @@ -68,7 +70,7 @@ def add_tts_span_attributes( model: str, voice_id: str, text: Optional[str] = None, - settings: Optional[Dict[str, Any]] = None, + settings: Optional["ServiceSettings"] = None, character_count: Optional[int] = None, operation_name: str = "tts", ttfb: Optional[float] = None, @@ -107,7 +109,7 @@ def add_tts_span_attributes( # Add settings if provided if settings: - for key, value in settings.items(): + for key, value in settings.given_fields().items(): if isinstance(value, (str, int, float, bool)): span.set_attribute(f"settings.{key}", value) @@ -126,7 +128,7 @@ def add_stt_span_attributes( is_final: Optional[bool] = None, language: Optional[str] = None, user_id: Optional[str] = None, - settings: Optional[Dict[str, Any]] = None, + settings: Optional["ServiceSettings"] = None, vad_enabled: bool = False, ttfb: Optional[float] = None, **kwargs, @@ -171,7 +173,7 @@ def add_stt_span_attributes( # Add settings if provided if settings: - for key, value in settings.items(): + for key, value in settings.given_fields().items(): if isinstance(value, (str, int, float, bool)): span.set_attribute(f"settings.{key}", value) @@ -282,7 +284,7 @@ def add_gemini_live_span_attributes( voice_id: Optional[str] = None, language: Optional[str] = None, modalities: Optional[str] = None, - settings: Optional[Dict[str, Any]] = None, + settings: Optional["ServiceSettings"] = None, tools: Optional[List[Dict]] = None, tools_serialized: Optional[str] = None, transcript: Optional[str] = None, @@ -359,7 +361,7 @@ def add_gemini_live_span_attributes( # Add settings if provided if settings: - for key, value in settings.items(): + for key, value in settings.given_fields().items(): if isinstance(value, (str, int, float, bool)): span.set_attribute(f"settings.{key}", value) elif key == "vad" and value: diff --git a/src/pipecat/utils/tracing/service_decorators.py b/src/pipecat/utils/tracing/service_decorators.py index 601cad53d..304ecb5e8 100644 --- a/src/pipecat/utils/tracing/service_decorators.py +++ b/src/pipecat/utils/tracing/service_decorators.py @@ -219,7 +219,7 @@ def traced_tts(func: Optional[Callable] = None, *, name: Optional[str] = None) - tracer = trace.get_tracer("pipecat") with tracer.start_as_current_span(span_name, context=parent_context) as span: try: - settings = getattr(self, "_settings", {}) + settings = getattr(self, "_settings", None) add_tts_span_attributes( span=span, service_name=service_class_name, @@ -338,7 +338,7 @@ def traced_stt(func: Optional[Callable] = None, *, name: Optional[str] = None) - ) # Use settings from the service if available - settings = getattr(self, "_settings", {}) + settings = getattr(self, "_settings", None) add_stt_span_attributes( span=current_span, @@ -510,15 +510,10 @@ def traced_llm(func: Optional[Callable] = None, *, name: Optional[str] = None) - # Get settings from the service params = {} if hasattr(self, "_settings"): - for key, value in self._settings.items(): - if key == "extra": - continue - # Add value directly if it's a basic type + for key, value in self._settings.given_fields().items(): if isinstance(value, (int, float, bool, str)): params[key] = value - elif value is None or ( - hasattr(value, "__name__") and value.__name__ == "NOT_GIVEN" - ): + elif value is None: params[key] = "NOT_GIVEN" # Add all available attributes to the span @@ -627,12 +622,12 @@ def traced_gemini_live(operation: str) -> Callable: model_name = _get_model_name(self) voice_id = getattr(self, "_voice_id", None) language_code = getattr(self, "_language_code", None) - settings = getattr(self, "_settings", {}) + settings = getattr(self, "_settings", None) # Get modalities if available modalities = None - if hasattr(self, "_settings") and "modalities" in self._settings: - modality_obj = self._settings["modalities"] + if settings and hasattr(settings, "modalities"): + modality_obj = settings.modalities if hasattr(modality_obj, "value"): modalities = modality_obj.value else: From f37fd39cdbcbe87ef4c528a2c46304c7bac3b08e Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Aleix=20Conchillo=20Flaqu=C3=A9?= Date: Sat, 28 Feb 2026 17:11:07 -0800 Subject: [PATCH 0702/1060] Add optional direction parameter to PipelineTask.queue_frame() and queue_frames() Allow pushing frames upstream through the pipeline by passing FrameDirection.UPSTREAM. Downstream frames use the existing push queue, while upstream frames are pushed directly from the pipeline sink. --- src/pipecat/pipeline/task.py | 35 ++++++++++---- src/pipecat/processors/frame_processor.py | 2 +- tests/test_pipeline.py | 57 +++++++++++++++++++++++ 3 files changed, 84 insertions(+), 10 deletions(-) diff --git a/src/pipecat/pipeline/task.py b/src/pipecat/pipeline/task.py index eeb39c9b6..deae6290c 100644 --- a/src/pipecat/pipeline/task.py +++ b/src/pipecat/pipeline/task.py @@ -389,12 +389,12 @@ class PipelineTask(BasePipelineTask): # source allows us to receive and react to upstream frames, and the sink # allows us to receive and react to downstream frames. source = PipelineSource(self._source_push_frame, name=f"{self}::Source") - sink = PipelineSink(self._sink_push_frame, name=f"{self}::Sink") + self._sink = PipelineSink(self._sink_push_frame, name=f"{self}::Sink") # Only prepend the RTVIProcessor if we created it ourselves. When the # user already placed it inside their pipeline we must not insert it # again or it will appear twice in the frame chain. processors = [self._rtvi, pipeline] if prepend_rtvi else [pipeline] - self._pipeline = Pipeline(processors, source=source, sink=sink) + self._pipeline = Pipeline(processors, source=source, sink=self._sink) # The task observer acts as a proxy to the provided observers. This way, # we only need to pass a single observer (using the StartFrame) which @@ -625,26 +625,43 @@ class PipelineTask(BasePipelineTask): self._finished = True logger.debug(f"Pipeline task {self} has finished") - async def queue_frame(self, frame: Frame): - """Queue a single frame to be pushed down the pipeline. + async def queue_frame( + self, frame: Frame, direction: FrameDirection = FrameDirection.DOWNSTREAM + ): + """Queue a single frame to be pushed through the pipeline. + + Downstream frames are pushed from the beginning of the pipeline. + Upstream frames are pushed from the end of the pipeline. Args: frame: The frame to be processed. + direction: The direction to push the frame. Defaults to downstream. """ - await self._push_queue.put(frame) + if direction == FrameDirection.DOWNSTREAM: + await self._push_queue.put(frame) + else: + await self._sink.queue_frame(frame, direction) - async def queue_frames(self, frames: Iterable[Frame] | AsyncIterable[Frame]): - """Queues multiple frames to be pushed down the pipeline. + async def queue_frames( + self, + frames: Iterable[Frame] | AsyncIterable[Frame], + direction: FrameDirection = FrameDirection.DOWNSTREAM, + ): + """Queue multiple frames to be pushed through the pipeline. + + Downstream frames are pushed from the beginning of the pipeline. + Upstream frames are pushed from the end of the pipeline. Args: frames: An iterable or async iterable of frames to be processed. + direction: The direction to push the frames. Defaults to downstream. """ if isinstance(frames, AsyncIterable): async for frame in frames: - await self.queue_frame(frame) + await self.queue_frame(frame, direction) elif isinstance(frames, Iterable): for frame in frames: - await self.queue_frame(frame) + await self.queue_frame(frame, direction) async def _cancel(self, *, reason: Optional[str] = None): """Internal cancellation logic for the pipeline task. diff --git a/src/pipecat/processors/frame_processor.py b/src/pipecat/processors/frame_processor.py index 3e90968fe..3e7b48442 100644 --- a/src/pipecat/processors/frame_processor.py +++ b/src/pipecat/processors/frame_processor.py @@ -965,7 +965,7 @@ class FrameProcessor(BaseObject): try: timestamp = self._clock.get_time() if self._clock else 0 if direction == FrameDirection.DOWNSTREAM and self._next: - logger.trace(f"Pushing {frame} from {self} to {self._next}") + logger.trace(f"Pushing {frame} downstream from {self} to {self._next}") if self._observer: data = FramePushed( diff --git a/tests/test_pipeline.py b/tests/test_pipeline.py index 71121a3fc..04601bf14 100644 --- a/tests/test_pipeline.py +++ b/tests/test_pipeline.py @@ -292,6 +292,63 @@ class TestPipelineTask(unittest.IsolatedAsyncioTestCase): assert upstream_received assert downstream_received + async def test_task_queue_frame_upstream(self): + upstream_received = False + + pipeline = Pipeline([IdentityFilter()]) + task = PipelineTask(pipeline, cancel_on_idle_timeout=False) + task.set_reached_upstream_filter((TextFrame,)) + + @task.event_handler("on_frame_reached_upstream") + async def on_frame_reached_upstream(task, frame): + nonlocal upstream_received + if isinstance(frame, TextFrame) and frame.text == "Hello Upstream!": + upstream_received = True + + @task.event_handler("on_pipeline_started") + async def on_pipeline_started(task, frame): + await task.queue_frame(TextFrame(text="Hello Upstream!"), FrameDirection.UPSTREAM) + + try: + await asyncio.wait_for( + task.run(PipelineTaskParams(loop=asyncio.get_event_loop())), + timeout=1.0, + ) + except asyncio.TimeoutError: + pass + + assert upstream_received + + async def test_task_queue_frames_upstream(self): + upstream_texts = [] + + pipeline = Pipeline([IdentityFilter()]) + task = PipelineTask(pipeline, cancel_on_idle_timeout=False) + task.set_reached_upstream_filter((TextFrame,)) + + @task.event_handler("on_frame_reached_upstream") + async def on_frame_reached_upstream(task, frame): + if isinstance(frame, TextFrame): + upstream_texts.append(frame.text) + + @task.event_handler("on_pipeline_started") + async def on_pipeline_started(task, frame): + await task.queue_frames( + [TextFrame(text="First"), TextFrame(text="Second")], + FrameDirection.UPSTREAM, + ) + + try: + await asyncio.wait_for( + task.run(PipelineTaskParams(loop=asyncio.get_event_loop())), + timeout=1.0, + ) + except asyncio.TimeoutError: + pass + + assert "First" in upstream_texts + assert "Second" in upstream_texts + async def test_task_heartbeats(self): heartbeats_counter = 0 From 94a59de4e1d28f8d9af0cd82ff0344fbfe9656a6 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Aleix=20Conchillo=20Flaqu=C3=A9?= Date: Sat, 28 Feb 2026 17:12:06 -0800 Subject: [PATCH 0703/1060] Add changelog for #3883 --- changelog/3883.added.md | 1 + uv.lock | 1221 +++++++++++++++++++++------------------ 2 files changed, 675 insertions(+), 547 deletions(-) create mode 100644 changelog/3883.added.md diff --git a/changelog/3883.added.md b/changelog/3883.added.md new file mode 100644 index 000000000..84360a891 --- /dev/null +++ b/changelog/3883.added.md @@ -0,0 +1 @@ +- Added optional `direction` parameter to `PipelineTask.queue_frame()` and `PipelineTask.queue_frames()`, allowing frames to be pushed upstream from the end of the pipeline. diff --git a/uv.lock b/uv.lock index e368cfc45..49cfa089b 100644 --- a/uv.lock +++ b/uv.lock @@ -15,7 +15,8 @@ version = "1.10.1" source = { registry = "https://pypi.org/simple" } dependencies = [ { name = 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a/src/pipecat/services/grok/realtime/llm.py +++ b/src/pipecat/services/grok/realtime/llm.py @@ -512,7 +512,7 @@ class GrokRealtimeLLMService(LLMService): await self._handle_evt_function_call_arguments_done(evt) elif evt.type == "error": if evt.error.code == "response_cancel_not_active": - logger.warning(f"Non-fatal API error: {evt.error.message}") + logger.debug(f"{self} {evt.error.message}") else: await self._handle_evt_error(evt) return diff --git a/src/pipecat/services/openai/realtime/llm.py b/src/pipecat/services/openai/realtime/llm.py index ebd1fbdbc..57efafbef 100644 --- a/src/pipecat/services/openai/realtime/llm.py +++ b/src/pipecat/services/openai/realtime/llm.py @@ -578,7 +578,7 @@ class OpenAIRealtimeLLMService(LLMService): elif evt.type == "error": if not await self._maybe_handle_evt_retrieve_conversation_item_error(evt): if evt.error.code == "response_cancel_not_active": - logger.warning(f"Non-fatal API error: {evt.error.message}") + logger.debug(f"{self} {evt.error.message}") else: await self._handle_evt_error(evt) # errors are fatal, so exit the receive loop diff --git a/src/pipecat/services/openai_realtime_beta/openai.py b/src/pipecat/services/openai_realtime_beta/openai.py index 808fbb053..ffa1f4207 100644 --- a/src/pipecat/services/openai_realtime_beta/openai.py +++ b/src/pipecat/services/openai_realtime_beta/openai.py @@ -504,7 +504,7 @@ class OpenAIRealtimeBetaLLMService(LLMService): elif evt.type == "error": if not await self._maybe_handle_evt_retrieve_conversation_item_error(evt): if evt.error.code == "response_cancel_not_active": - logger.warning(f"Non-fatal API error: {evt.error.message}") + logger.debug(f"{self} {evt.error.message}") else: await self._handle_evt_error(evt) # errors are fatal, so exit the receive loop From 21a409e447fd23b984e4c4da7e1171c510d0d86f Mon Sep 17 00:00:00 2001 From: zack Date: Sun, 1 Mar 2026 11:17:39 -0500 Subject: [PATCH 0705/1060] Update prompt warning and rename min_end_of_turn_silence_when_confident to min_turn_silence - Add "beta feature" note to custom prompt warning - Rename min_end_of_turn_silence_when_confident parameter to min_turn_silence across all AssemblyAI code - Update documentation, examples, and test files to use new parameter name --- TESTING_CHECKLIST.md | 273 +++++++ TESTING_SETUP.md | 310 ++++++++ .../07o-interruptible-assemblyai-stt.py | 4 +- src/pipecat/services/assemblyai/models.py | 4 +- src/pipecat/services/assemblyai/stt.py | 45 +- test_assemblyai_custom.py | 256 ++++++ test_assemblyai_interactive.py | 750 ++++++++++++++++++ test_assemblyai_u3pro.py | 589 ++++++++++++++ 8 files changed, 2205 insertions(+), 26 deletions(-) create mode 100644 TESTING_CHECKLIST.md create mode 100644 TESTING_SETUP.md create mode 100755 test_assemblyai_custom.py create mode 100755 test_assemblyai_interactive.py create mode 100644 test_assemblyai_u3pro.py diff --git a/TESTING_CHECKLIST.md b/TESTING_CHECKLIST.md new file mode 100644 index 000000000..8d2d147d4 --- /dev/null +++ b/TESTING_CHECKLIST.md @@ -0,0 +1,273 @@ +# AssemblyAI u3-rt-pro Testing Checklist + +## Test Environment Setup +- [ ] Install dependencies: `uv sync --group dev --all-extras` +- [ ] Set up `.env` file with API keys +- [ ] Verify LiveKit connection +- [ ] Run basic voice agent test + +--- + +## Feature Testing Checklist + +### ✅ Basic Configuration Tests + +#### Test 1: Default u3-rt-pro Configuration +- [ ] **Setup:** Create service with default params +- [ ] **Expected:** No errors, uses u3-rt-pro model with 100ms min/max +- [ ] **Verify:** Check logs for connection confirmation + +#### Test 2: Custom min_turn_silence +- [ ] **Setup:** Set `min_turn_silence=200` +- [ ] **Expected:** Both min and max set to 200ms +- [ ] **Verify:** Speak short phrases, observe turn detection timing + +#### Test 3: User sets max_turn_silence (Warning Test) +- [ ] **Setup:** Set `max_turn_silence=500` in connection params +- [ ] **Expected:** Warning logged, value overridden to match min +- [ ] **Verify:** Check logs for warning message + +--- + +### ✅ Prompting Tests + +#### Test 4: No Prompt (Default - Recommended) +- [ ] **Setup:** Don't set prompt parameter +- [ ] **Expected:** Uses default prompt, 88% accuracy, no warnings +- [ ] **Verify:** Transcription quality is good + +#### Test 5: Custom Prompt (Warning Test) +- [ ] **Setup:** Set custom prompt in connection params +- [ ] **Expected:** Warning logged about testing without prompt first +- [ ] **Verify:** Check logs for prompt warning + +#### Test 6: Prompt + Keyterms Conflict (Error Test) +- [ ] **Setup:** Set both `prompt` and `keyterms_prompt` at init +- [ ] **Expected:** ValueError raised with helpful error message +- [ ] **Verify:** Service fails to initialize with clear error + +--- + +### ✅ Keyterms Prompting Tests + +#### Test 7: Basic Keyterms at Init +- [ ] **Setup:** Set `keyterms_prompt=["Pipecat", "AssemblyAI", "Universal-3"]` +- [ ] **Expected:** Terms are boosted in recognition +- [ ] **Verify:** Say the boosted terms, check accuracy + +#### Test 8: Empty Keyterms (No Boosting) +- [ ] **Setup:** Set `keyterms_prompt=[]` +- [ ] **Expected:** No boosting, default behavior +- [ ] **Verify:** Normal transcription + +--- + +### ✅ Diarization Tests + +#### Test 9: Diarization Disabled (Default) +- [ ] **Setup:** Don't set `speaker_labels` parameter +- [ ] **Expected:** No speaker info in transcripts +- [ ] **Verify:** TranscriptionFrame.user_id is default user_id + +#### Test 10: Diarization Enabled (No Formatting) +- [ ] **Setup:** Set `speaker_labels=True` +- [ ] **Expected:** Speaker ID in user_id field, plain text +- [ ] **Verify:** Multiple speakers show different IDs (Speaker A, Speaker B) + +#### Test 11: Diarization with XML Formatting +- [ ] **Setup:** Set `speaker_labels=True`, `speaker_format="<{speaker}>{text}"` +- [ ] **Expected:** Text includes speaker tags: `Hello` +- [ ] **Verify:** Formatted text in transcript, speaker ID in user_id + +#### Test 12: Diarization with Colon Prefix +- [ ] **Setup:** Set `speaker_labels=True`, `speaker_format="{speaker}: {text}"` +- [ ] **Expected:** Text includes prefix: `Speaker A: Hello` +- [ ] **Verify:** Formatted text, multiple speakers distinguishable + +--- + +### ✅ Dynamic Updates Tests + +#### Test 13: Dynamic Keyterms Update (Stage 1 → Stage 2) +- [ ] **Setup:** Start with empty keyterms, update mid-conversation +- [ ] **Expected:** New keyterms take effect immediately +- [ ] **Test Steps:** + 1. Start conversation with no keyterms + 2. Send update frame with `keyterms_prompt=["cardiology", "Dr. Smith"]` + 3. Say the new terms +- [ ] **Verify:** Improved recognition after update + +#### Test 14: Clear Keyterms (Reset Context) +- [ ] **Setup:** Start with keyterms, clear them mid-stream +- [ ] **Expected:** Context biasing removed +- [ ] **Test Steps:** + 1. Start with `keyterms_prompt=["test", "words"]` + 2. Send update frame with `keyterms_prompt=[]` +- [ ] **Verify:** No more boosting after clear + +#### Test 15: Dynamic Silence Parameters +- [ ] **Setup:** Update `max_turn_silence` mid-stream +- [ ] **Expected:** Turn detection timing changes +- [ ] **Test Steps:** + 1. Start with default (1200ms) + 2. Update to `max_turn_silence=5000` (for reading numbers) + 3. Pause longer between words + 4. Update back to `max_turn_silence=1200` +- [ ] **Verify:** Longer pauses tolerated when increased + +#### Test 16: Dynamic Prompt Update +- [ ] **Setup:** Update prompt mid-stream +- [ ] **Expected:** New instructions take effect +- [ ] **Test Steps:** + 1. Start with default prompt + 2. Send update with custom prompt +- [ ] **Verify:** Behavior changes according to new prompt + +#### Test 17: Multiple Parameters at Once +- [ ] **Setup:** Update keyterms, max_turn_silence, and min_end_of_turn together +- [ ] **Expected:** All parameters updated in single WebSocket message +- [ ] **Verify:** Check logs for single UpdateConfiguration message + +#### Test 18: Dynamic Update - Prompt + Keyterms Conflict (Error) +- [ ] **Setup:** Try to update both prompt and keyterms_prompt in same update +- [ ] **Expected:** ValueError raised +- [ ] **Verify:** Update fails with clear error message + +--- + +### ✅ Turn Detection Mode Tests + +#### Test 19: Pipecat Mode (vad_force_turn_endpoint=True) - Default +- [ ] **Setup:** Use default settings (Pipecat mode) +- [ ] **Expected:** + - ForceEndpoint sent on VAD stop + - Smart Turn Analyzer makes decisions + - min=max=100ms for u3-rt-pro +- [ ] **Verify:** Fast finals, Smart Turn handles completeness + +#### Test 20: STT Mode (vad_force_turn_endpoint=False) - u3-rt-pro only +- [ ] **Setup:** Set `vad_force_turn_endpoint=False` with u3-rt-pro +- [ ] **Expected:** + - AssemblyAI controls turn endings + - SpeechStarted message triggers interruptions + - UserStarted/StoppedSpeakingFrame emitted +- [ ] **Verify:** Turn detection from AssemblyAI model + +#### Test 21: STT Mode with universal-streaming (Error Test) +- [ ] **Setup:** Set `vad_force_turn_endpoint=False` with universal-streaming +- [ ] **Expected:** ValueError raised (requires u3-rt-pro) +- [ ] **Verify:** Service fails with clear error + +--- + +### ✅ Language Detection Tests (If Multilingual Model) + +#### Test 22: Language Detection Enabled +- [ ] **Setup:** Use `universal-streaming-multilingual` with `language_detection=True` +- [ ] **Expected:** Language codes in transcripts +- [ ] **Verify:** Speak different languages, check language_code field + +#### Test 23: Language Confidence Threshold +- [ ] **Setup:** Enable language detection +- [ ] **Expected:** High confidence (≥0.7) → detected language, Low → fallback to English +- [ ] **Verify:** Check logs for confidence warnings + +--- + +### ✅ Edge Cases & Error Handling + +#### Test 24: WebSocket Disconnect During Update +- [ ] **Setup:** Simulate disconnect, try update +- [ ] **Expected:** Error logged, update queued for reconnection +- [ ] **Verify:** Graceful handling, no crash + +#### Test 25: Invalid Parameter Types +- [ ] **Setup:** Send update with wrong type (e.g., keyterms_prompt as string) +- [ ] **Expected:** Warning logged, parameter skipped +- [ ] **Verify:** Service continues, invalid param ignored + +#### Test 26: Unknown Parameter in Update +- [ ] **Setup:** Send update with unsupported parameter (e.g., `language`) +- [ ] **Expected:** Warning logged about parameter +- [ ] **Verify:** Other valid params still updated + +--- + +### ✅ Integration Tests + +#### Test 27: Full Voice Agent Flow (Multi-Stage) +- [ ] **Setup:** Complete voice agent with stage transitions +- [ ] **Test Steps:** + 1. Greeting stage (general keyterms) + 2. Name collection stage (name keyterms) + 3. Account number stage (number keyterms, longer silence) + 4. Medical info stage (medical keyterms) + 5. Closing stage (goodbye keyterms) +- [ ] **Verify:** Each stage has appropriate keyterms and timing + +#### Test 28: Diarization + Dynamic Updates +- [ ] **Setup:** Enable diarization, update keyterms mid-stream +- [ ] **Expected:** Both features work together +- [ ] **Verify:** Speaker IDs persist, keyterms update correctly + +#### Test 29: Interruption Handling +- [ ] **Setup:** Bot speaking, user interrupts +- [ ] **Expected:** + - Pipecat mode: VAD + Smart Turn handles + - STT mode: SpeechStarted triggers interrupt +- [ ] **Verify:** Bot stops, user speech processed + +--- + +## Testing Results Template + +``` +| Test # | Feature | Status | Notes | +|--------|---------|--------|-------| +| 1 | Default Config | ✅ PASS | | +| 2 | Custom min_silence | ✅ PASS | | +| 3 | max_silence Warning | ✅ PASS | | +| ... | ... | ... | ... | +``` + +--- + +## Expected Outcomes Summary + +### ✅ Should Work (No Errors) +- Default configuration +- Custom min_turn_silence +- Keyterms prompting +- Diarization with/without formatting +- Dynamic updates (one parameter or multiple) +- Pipecat mode turn detection + +### ⚠️ Should Warn (Logs Warning, Continues) +- Custom prompt set at init +- max_turn_silence set (overridden) +- Invalid parameter types in updates +- Language update attempted +- Prompt used with universal-streaming + +### ❌ Should Error (Raises Exception, Stops) +- prompt + keyterms_prompt at init +- prompt + keyterms_prompt in same update +- vad_force_turn_endpoint=False with universal-streaming + +--- + +## Quick Test Commands + +```bash +# Run basic test +python test_assemblyai_u3pro.py --test basic + +# Run specific test +python test_assemblyai_u3pro.py --test diarization + +# Run all tests +python test_assemblyai_u3pro.py --test all + +# Interactive mode +python test_assemblyai_u3pro.py --interactive +``` diff --git a/TESTING_SETUP.md b/TESTING_SETUP.md new file mode 100644 index 000000000..fa1dca462 --- /dev/null +++ b/TESTING_SETUP.md @@ -0,0 +1,310 @@ +# AssemblyAI u3-rt-pro Testing Setup Guide + +## Quick Start + +### 1. Setup Environment + +```bash +# Copy API keys +cp .env.testing .env + +# Install dependencies +uv sync --group dev --all-extras --no-extra gstreamer --no-extra krisp + +# Make test script executable +chmod +x test_assemblyai_u3pro.py +``` + +### 2. Ensure Audio Devices + +Make sure you have: +- **Microphone** enabled and working +- **Speakers/headphones** connected +- Audio permissions granted (macOS will prompt on first run) + +### 3. Run Tests + +```bash +# Run a specific test +python test_assemblyai_u3pro.py --test basic + +# Interactive mode (choose from menu) +python test_assemblyai_u3pro.py --interactive + +# Run all tests sequentially +python test_assemblyai_u3pro.py --test all +``` + +--- + +## Available Tests + +### Basic Configuration Tests +```bash +# Test 1: Default configuration (min=max=100ms) +python test_assemblyai_u3pro.py --test basic + +# Test 2: Custom min_turn_silence +python test_assemblyai_u3pro.py --test custom_min + +# Test 3: max_turn_silence warning (should be overridden) +python test_assemblyai_u3pro.py --test max_warning +``` + +### Prompting Tests +```bash +# Test 5: Custom prompt warning +python test_assemblyai_u3pro.py --test prompt_warning + +# Test 6: Prompt + keyterms conflict (should error) +python test_assemblyai_u3pro.py --test prompt_keyterms_conflict + +# Test 7: Basic keyterms prompting +python test_assemblyai_u3pro.py --test keyterms +``` + +### Diarization Tests +```bash +# Test 10: Diarization without formatting +python test_assemblyai_u3pro.py --test diarization + +# Test 11: Diarization with XML formatting +python test_assemblyai_u3pro.py --test diarization_xml +``` + +### Dynamic Updates Tests +```bash +# Test 13: Dynamic keyterms (multi-stage) +python test_assemblyai_u3pro.py --test dynamic_keyterms + +# Test 15: Dynamic silence parameters +python test_assemblyai_u3pro.py --test dynamic_silence + +# Test 17: Multiple parameters at once +python test_assemblyai_u3pro.py --test multi_param +``` + +--- + +## Test Execution Flow + +### For Each Test: + +1. **Start the test script** + ```bash + python test_assemblyai_u3pro.py --test + ``` + +2. **Wait for "started" message** indicating the bot is ready + +3. **Speak into your microphone** to test - the bot will: + - Transcribe your speech (you'll see `📝 TRANSCRIPTION:` logs) + - Process through the LLM + - Respond with voice through your speakers + +4. **Observe logs** for: + - ✅ Success indicators + - ⚠️ Warning messages + - ❌ Error messages + - 📝 Transcription output + +5. **Verify expected behavior** against checklist + +6. **Stop test** with Ctrl+C + +--- + +## Expected Test Outcomes + +### Should Pass (✅) +- Basic configuration creates service +- Custom parameters are applied +- Keyterms boost recognition +- Diarization shows speaker IDs +- Dynamic updates work without errors + +### Should Warn (⚠️) +Check logs for warnings: +- "We recommend testing at first with no prompt" +- "max_turn_silence is not used in Pipecat mode" +- "Unknown setting for AssemblyAI STT service" + +### Should Error (❌) +Should raise ValueError and fail to start: +- Both prompt and keyterms_prompt set at init +- Both prompt and keyterms_prompt in same update +- vad_force_turn_endpoint=False with universal-streaming + +--- + +## Debugging Tips + +### Check Logs +```bash +# Run with verbose logging +LOGURU_LEVEL=DEBUG python test_assemblyai_u3pro.py --test +``` + +### Common Issues + +**Issue: "WebSocket connection failed"** +- Check ASSEMBLYAI_API_KEY is correct +- Verify network connection +- Check firewall settings + +**Issue: "No audio input/output"** +- Verify microphone permissions (System Preferences → Security & Privacy → Microphone) +- Check default audio devices in System Preferences → Sound +- Test microphone with another app first +- Make sure no other app is using the microphone + +**Issue: "No transcriptions appearing"** +- Verify microphone permissions +- Check audio levels (speak louder or move closer to mic) +- Speak clearly and wait for VAD to detect +- Check if microphone is muted + +**Issue: "Can't hear bot responses"** +- Check speaker/headphone volume +- Verify correct output device is selected +- Check terminal for TTS errors + +**Issue: "Service fails to start"** +- Check all API keys in .env +- Run `uv sync` to ensure dependencies installed +- Check Python version (3.10+) + +--- + +## Manual Testing Checklist + +After running automated tests, manually verify: + +### ✅ Audio Quality +- [ ] Transcriptions are accurate +- [ ] No distortion or dropouts +- [ ] Latency is acceptable + +### ✅ Turn Detection +- [ ] Bot waits for user to finish speaking +- [ ] No premature cutoffs +- [ ] Handles natural pauses correctly + +### ✅ Interruptions +- [ ] Can interrupt bot mid-sentence +- [ ] Interruption is smooth +- [ ] Bot stops speaking immediately + +### ✅ Diarization (if enabled) +- [ ] Multiple speakers detected correctly +- [ ] Speaker IDs consistent +- [ ] Speaker formatting works + +### ✅ Dynamic Updates +- [ ] Keyterms update without disconnection +- [ ] Turn detection timing changes work +- [ ] Updates logged correctly + +--- + +## Test Results Recording + +### Use this template: + +```markdown +## Test Run: YYYY-MM-DD + +| Test # | Test Name | Status | Notes | +|--------|-----------|--------|-------| +| 1 | basic | ✅ PASS | Transcriptions working | +| 2 | custom_min | ✅ PASS | Turn timing changed | +| 3 | max_warning | ✅ PASS | Warning logged | +| 5 | prompt_warning | ✅ PASS | Warning shown | +| 6 | prompt_keyterms_conflict | ✅ PASS | ValueError raised | +| 7 | keyterms | ✅ PASS | Terms boosted | +| 10 | diarization | ✅ PASS | Speaker IDs correct | +| 11 | diarization_xml | ✅ PASS | XML tags shown | +| 13 | dynamic_keyterms | ✅ PASS | Updates worked | +| 15 | dynamic_silence | ✅ PASS | Timing adjusted | +| 17 | multi_param | ✅ PASS | All params updated | + +### Issues Found: +- None + +### Notes: +- All tests passed successfully +- Latency is excellent (sub-300ms) +- Diarization accuracy is good +``` + +--- + +## Advanced Testing + +### Custom Test Scenarios + +Create custom tests by modifying `test_assemblyai_u3pro.py`: + +```python +async def test_my_custom_scenario(): + """My custom test scenario.""" + logger.info("Testing my specific use case") + + connection_params = AssemblyAIConnectionParams( + speech_model="u3-rt-pro", + # Your custom params here + ) + + task, transport = await create_basic_voice_agent(connection_params) + + # Your test logic here + + runner = PipelineRunner() + await runner.run(task) +``` + +### Stress Testing + +Test with: +- Multiple simultaneous speakers +- Long conversations (30+ minutes) +- Rapid speech +- Heavy accents +- Background noise +- Poor network conditions + +--- + +## Reporting Issues + +When reporting issues, include: + +1. **Test name and number** +2. **Full error message and stack trace** +3. **Relevant log output** (use LOGURU_LEVEL=DEBUG) +4. **Configuration used** (connection_params) +5. **Expected vs actual behavior** +6. **Steps to reproduce** + +--- + +## Next Steps + +After testing: + +1. ✅ Mark completed tests in `TESTING_CHECKLIST.md` +2. 📝 Document any issues found +3. 🐛 Create GitHub issues for bugs +4. ✨ Suggest improvements +5. 📊 Share results with team + +--- + +## Contact + +Questions? Issues? +- Check `TESTING_CHECKLIST.md` for detailed test descriptions +- Review logs with `LOGURU_LEVEL=DEBUG` +- Reach out to the team with your findings + +Happy testing! 🎯 diff --git a/examples/foundational/07o-interruptible-assemblyai-stt.py b/examples/foundational/07o-interruptible-assemblyai-stt.py index 5deaa82a1..ee2994c0e 100644 --- a/examples/foundational/07o-interruptible-assemblyai-stt.py +++ b/examples/foundational/07o-interruptible-assemblyai-stt.py @@ -66,7 +66,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): - More natural turn detection based on speech patterns and pauses 2. Advanced Turn Detection Tuning (STT Mode) - - `min_end_of_turn_silence_when_confident`: Minimum silence (ms) when confident + - `min_turn_silence`: Minimum silence (ms) when confident about end-of-turn. Lower values = faster responses. Default: 200ms - `max_turn_silence`: Maximum silence (ms) before forcing end-of-turn. Prevents long pauses. Default: 1000ms @@ -96,7 +96,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): connection_params=AssemblyAIConnectionParams( speech_model="u3-rt-pro", # Optional: Tune turn detection timing (defaults shown below) - # min_end_of_turn_silence_when_confident=100, # Default + # min_turn_silence=100, # Default # max_turn_silence=1000, # Default # Optional: Boost accuracy for specific names/terms # prompt="Names: Xiomara, Saoirse, Krzystof. Technical terms: API, OAuth.", diff --git a/src/pipecat/services/assemblyai/models.py b/src/pipecat/services/assemblyai/models.py index 949f2e00e..f92b1b8bf 100644 --- a/src/pipecat/services/assemblyai/models.py +++ b/src/pipecat/services/assemblyai/models.py @@ -129,7 +129,7 @@ class AssemblyAIConnectionParams(BaseModel): formatted_finals: Whether to enable transcript formatting. Defaults to True. word_finalization_max_wait_time: Maximum time to wait for word finalization in milliseconds. end_of_turn_confidence_threshold: Confidence threshold for end-of-turn detection. - min_end_of_turn_silence_when_confident: Minimum silence duration when confident about end-of-turn. + min_turn_silence: Minimum silence duration when confident about end-of-turn. max_turn_silence: Maximum silence duration before forcing end-of-turn. keyterms_prompt: List of key terms to guide transcription. Will be JSON serialized before sending. prompt: Optional text prompt to guide the transcription. Only used when speech_model is "u3-rt-pro". @@ -148,7 +148,7 @@ class AssemblyAIConnectionParams(BaseModel): formatted_finals: bool = True word_finalization_max_wait_time: Optional[int] = None end_of_turn_confidence_threshold: Optional[float] = None - min_end_of_turn_silence_when_confident: Optional[int] = None + min_turn_silence: Optional[int] = None max_turn_silence: Optional[int] = None keyterms_prompt: Optional[List[str]] = None prompt: Optional[str] = None diff --git a/src/pipecat/services/assemblyai/stt.py b/src/pipecat/services/assemblyai/stt.py index b0254d410..d82b38a99 100644 --- a/src/pipecat/services/assemblyai/stt.py +++ b/src/pipecat/services/assemblyai/stt.py @@ -127,8 +127,8 @@ class AssemblyAISTTService(WebsocketSTTService): vad_force_turn_endpoint: Controls turn detection mode. When True (Pipecat mode, default): Forces AssemblyAI to return finals ASAP so Pipecat's turn detection (e.g., Smart Turn) decides when the user is done. - - min_end_of_turn_silence_when_confident defaults to 100ms (user can override) - - max_turn_silence is ALWAYS set equal to min_end_of_turn_silence_when_confident + - min_turn_silence defaults to 100ms (user can override) + - max_turn_silence is ALWAYS set equal to min_turn_silence - VAD stop sends ForceEndpoint as ceiling - No UserStarted/StoppedSpeakingFrame emitted from STT When False (STT mode, u3-rt-pro only): AssemblyAI's model controls turn endings. @@ -172,10 +172,11 @@ class AssemblyAISTTService(WebsocketSTTService): # Warn if user sets a custom prompt (recommend testing without one first) if connection_params.prompt is not None: logger.warning( - "Custom prompt detected. We recommend testing with no prompt first, as this " - "will use our optimized default prompt for voice agents. Bad prompts may lead " - "to bad results. If you'd like to create your own prompt, check out our " - "prompting guide at: https://www.assemblyai.com/docs/streaming/prompting" + "Custom prompt detected. Prompting is a beta feature. We recommend testing " + "with no prompt first, as this will use our optimized default prompt for " + "voice agents. Bad prompts may lead to bad results. If you'd like to create " + "your own prompt, check out our prompting guide at: " + "https://www.assemblyai.com/docs/streaming/prompting" ) # When vad_force_turn_endpoint is enabled, configure connection params @@ -223,15 +224,15 @@ class AssemblyAISTTService(WebsocketSTTService): when the user is done speaking. VAD stop is the absolute ceiling. u3-rt-pro: - - min_end_of_turn_silence_when_confident defaults to 100ms (user can override) - - max_turn_silence is ALWAYS set equal to min_end_of_turn_silence_when_confident + - min_turn_silence defaults to 100ms (user can override) + - max_turn_silence is ALWAYS set equal to min_turn_silence to avoid double turn detection (AssemblyAI + Pipecat both analyzing) - If user sets max_turn_silence, it's ignored with a warning - end_of_turn_confidence_threshold: not set (API default) universal-streaming-*: - end_of_turn_confidence_threshold=0.0 (disable semantic turn detection) - - min_end_of_turn_silence_when_confident=160 + - min_turn_silence=160 - max_turn_silence: not set (API default) Args: @@ -244,8 +245,8 @@ class AssemblyAISTTService(WebsocketSTTService): updates = {} if is_u3_pro: - # u3-rt-pro: Synchronize max_turn_silence with min_end_of_turn_silence_when_confident - min_silence = connection_params.min_end_of_turn_silence_when_confident + # u3-rt-pro: Synchronize max_turn_silence with min_turn_silence + min_silence = connection_params.min_turn_silence if min_silence is None: min_silence = 100 @@ -254,20 +255,20 @@ class AssemblyAISTTService(WebsocketSTTService): logger.warning( f"Your max_turn_silence value ({connection_params.max_turn_silence}ms) will be " f"OVERRIDDEN in Pipecat mode (vad_force_turn_endpoint=True). It will be set to " - f"{min_silence}ms (matching min_end_of_turn_silence_when_confident) and SENT to " + f"{min_silence}ms (matching min_turn_silence) and SENT to " f"AssemblyAI to avoid double turn detection. To use your max_turn_silence as-is, " f"switch to STT mode (vad_force_turn_endpoint=False)." ) updates = { - "min_end_of_turn_silence_when_confident": min_silence, + "min_turn_silence": min_silence, "max_turn_silence": min_silence, } else: # universal-streaming: Different configuration (works differently) updates = { "end_of_turn_confidence_threshold": 0.0, - "min_end_of_turn_silence_when_confident": 160, + "min_turn_silence": 160, } # Apply updates if any @@ -292,7 +293,7 @@ class AssemblyAISTTService(WebsocketSTTService): - keyterms_prompt: List of terms to boost (can be empty array to clear) - prompt: Custom prompt text (u3-rt-pro only) - max_turn_silence: Maximum silence before forcing turn end - - min_end_of_turn_silence_when_confident: Silence before EOT check + - min_turn_silence: Silence before EOT check Args: delta: A :class:`STTSettings` (or ``AssemblyAISTTSettings``) delta. @@ -351,18 +352,18 @@ class AssemblyAISTTService(WebsocketSTTService): f"Updating max_turn_silence to: {conn_params.max_turn_silence}ms" ) - if hasattr(conn_params, "min_end_of_turn_silence_when_confident"): + if hasattr(conn_params, "min_turn_silence"): if ( old_conn_params is None - or conn_params.min_end_of_turn_silence_when_confident - != old_conn_params.min_end_of_turn_silence_when_confident + or conn_params.min_turn_silence + != old_conn_params.min_turn_silence ): - if conn_params.min_end_of_turn_silence_when_confident is not None: - update_config["min_end_of_turn_silence_when_confident"] = ( - conn_params.min_end_of_turn_silence_when_confident + if conn_params.min_turn_silence is not None: + update_config["min_turn_silence"] = ( + conn_params.min_turn_silence ) logger.info( - f"Updating min_end_of_turn_silence_when_confident to: {conn_params.min_end_of_turn_silence_when_confident}ms" + f"Updating min_turn_silence to: {conn_params.min_turn_silence}ms" ) # Send update if we have parameters to update diff --git a/test_assemblyai_custom.py b/test_assemblyai_custom.py new file mode 100755 index 000000000..c406918c0 --- /dev/null +++ b/test_assemblyai_custom.py @@ -0,0 +1,256 @@ +#!/usr/bin/env python3 +"""Custom AssemblyAI u3-rt-pro Test Script +Easy parameter tweaking for experimentation + +Edit the CONFIGURATION section below to test different settings! +""" + +import asyncio +import os +import sys + +from dotenv import load_dotenv +from loguru import logger + +from pipecat.audio.vad.silero import SileroVADAnalyzer +from pipecat.frames.frames import LLMRunFrame +from pipecat.pipeline.pipeline import Pipeline +from pipecat.pipeline.runner import PipelineRunner +from pipecat.pipeline.task import PipelineParams, PipelineTask +from pipecat.processors.aggregators.llm_context import LLMContext +from pipecat.processors.aggregators.llm_response_universal import ( + LLMContextAggregatorPair, + LLMUserAggregatorParams, +) +from pipecat.services.assemblyai.models import AssemblyAIConnectionParams +from pipecat.services.assemblyai.stt import AssemblyAISTTService +from pipecat.services.cartesia.tts import CartesiaTTSService +from pipecat.services.openai.llm import OpenAILLMService +from pipecat.transports.local.audio import LocalAudioTransport, LocalAudioTransportParams + +load_dotenv(override=True) + +# ============================================================================ +# CONFIGURATION +# ============================================================================ + +# Log Level: "DEBUG" for detailed logs, "INFO" for normal operation +LOG_LEVEL = "INFO" + +# ============================================================================ +# BOT IMPLEMENTATION +# ============================================================================ + + +async def main(): + """Run the custom test bot with your configured parameters.""" + # Setup logging + logger.remove(0) + logger.add(sys.stderr, level=LOG_LEVEL) + + logger.info("="*80) + logger.info("AssemblyAI u3-rt-pro Custom Test") + logger.info("="*80) + logger.info("Starting bot... Speak after you hear the greeting!") + logger.info("="*80) + + # Create local audio transport + transport = LocalAudioTransport( + LocalAudioTransportParams( + audio_in_enabled=True, + audio_out_enabled=True, + ) + ) + + # ======================================================================== + # EDIT PARAMETERS HERE + # ======================================================================== + + # Build connection params + connection_params = AssemblyAIConnectionParams( + # ==================================================================== + # Model Selection + # ==================================================================== + speech_model="u3-rt-pro", + # speech_model="universal-streaming-english", + # speech_model="universal-streaming-multilingual", + + # ==================================================================== + # Turn Detection Timing + # ==================================================================== + + # Minimum silence when confident about end of turn (milliseconds) + # Default: 100ms | Higher = more patient | Lower = faster responses + # Only used in Pipecat mode (vad_force_turn_endpoint=True) + min_turn_silence=100000, + # min_turn_silence=200, + # min_turn_silence=300, + + # Maximum turn silence (milliseconds) + # WARNING: In Pipecat mode (vad_force_turn_endpoint=True), this is + # automatically set equal to min_turn_silence + # to avoid double turn detection. Only used as-is in STT mode. + max_turn_silence=500, + + # End of turn confidence threshold (0.0 to 1.0) + # Higher = requires more confidence before ending turn + # end_of_turn_confidence_threshold=0.8, + + # ==================================================================== + # Prompting & Boosting + # ==================================================================== + + # Custom Prompt (WARNING: test carefully, default is optimized!) + # None = Use AssemblyAI's optimized default (recommended for 88% accuracy) + prompt=None, + # prompt="Transcribe speech with focus on technical terms.", + # prompt="Context: Medical conversation. Transcribe accurately.", + + # Keyterms Prompting (boosts recognition for specific words) + # NOTE: Cannot use both prompt and keyterms_prompt! + keyterms_prompt=None, + # keyterms_prompt=["Pipecat", "AssemblyAI", "OpenAI", "Cartesia"], + # keyterms_prompt=["Python", "JavaScript", "TypeScript", "API"], + + # ==================================================================== + # Diarization (Speaker Identification) + # ==================================================================== + + # Enable speaker labels (identifies different speakers) + speaker_labels=None, # None or True + # speaker_labels=True, + + # ==================================================================== + # Audio Configuration + # ==================================================================== + + # Audio sample rate (Hz) + # sample_rate=16000, + # sample_rate=8000, + + # Audio encoding format + # encoding="pcm_s16le", # Default: 16-bit PCM + # encoding="pcm_mulaw", # μ-law encoding (telephony) + + # ==================================================================== + # Other Options + # ==================================================================== + + # Format transcript turns (applies formatting rules) + # format_turns=True, # Default + # format_turns=False, + + # Language detection (only for universal-streaming-multilingual) + # language_detection=True, + ) + + # Log connection parameters for debugging + logger.info("="*80) + logger.info("CONNECTION PARAMETERS:") + logger.info(f" speech_model: {connection_params.speech_model}") + logger.info(f" min_turn_silence: {connection_params.min_turn_silence}") + logger.info(f" max_turn_silence: {connection_params.max_turn_silence}") + logger.info(f" sample_rate: {connection_params.sample_rate}") + logger.info(f" encoding: {connection_params.encoding}") + logger.info(f" prompt: {connection_params.prompt}") + logger.info(f" keyterms_prompt: {connection_params.keyterms_prompt}") + logger.info(f" speaker_labels: {connection_params.speaker_labels}") + logger.info(f" format_turns: {connection_params.format_turns}") + logger.info(f" end_of_turn_confidence_threshold: {connection_params.end_of_turn_confidence_threshold}") + logger.info(f" language_detection: {connection_params.language_detection}") + logger.info("="*80) + + # AssemblyAI Speech-to-Text Service + stt = AssemblyAISTTService( + api_key=os.getenv("ASSEMBLYAI_API_KEY"), + connection_params=connection_params, + + # Turn Detection Mode + # True = Pipecat mode (VAD + Smart Turn controls turns) + # False = STT mode (u3-rt-pro model controls turns) + vad_force_turn_endpoint=True, + + # Speaker Formatting (only used if speaker_labels=True) + # None = Just log speaker IDs, don't modify transcript + speaker_format=None, + # speaker_format="{text}", + # speaker_format="{speaker}: {text}", + # speaker_format="[{speaker}] {text}", + + # Additional available parameters (uncomment to use): + # should_interrupt=True, # Only for STT mode + ) + + # ======================================================================== + + # Text-to-Speech + tts = CartesiaTTSService( + api_key=os.getenv("CARTESIA_API_KEY"), + voice_id="a0e99841-438c-4a64-b679-ae501e7d6091", # Conversational English + ) + + # LLM + llm = OpenAILLMService( + api_key=os.getenv("OPENAI_API_KEY"), + model="gpt-4", + ) + + # Conversation context + messages = [ + { + "role": "system", + "content": ( + "You are a helpful voice assistant testing the AssemblyAI u3-rt-pro model. " + "Keep responses very brief (1-2 sentences). " + "Start by introducing yourself briefly and asking the user to speak." + ), + }, + ] + + context = LLMContext(messages) + + # Configure aggregator based on mode + # In STT mode, don't use VAD (model handles turn detection) + # In Pipecat mode, use VAD + Smart Turn + vad_force_turn_endpoint = True # Must match the value in stt configuration above + user_params = None + if vad_force_turn_endpoint: + user_params = LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()) + + user_aggregator, assistant_aggregator = LLMContextAggregatorPair( + context, + user_params=user_params, + ) + + # Pipeline + pipeline = Pipeline( + [ + transport.input(), + stt, + user_aggregator, + llm, + tts, + transport.output(), + assistant_aggregator, + ] + ) + + # Task + task = PipelineTask( + pipeline, + params=PipelineParams( + enable_metrics=True, + enable_usage_metrics=True, + ), + ) + + # Start the conversation + await task.queue_frames([LLMRunFrame()]) + + # Run + runner = PipelineRunner() + await runner.run(task) + + +if __name__ == "__main__": + asyncio.run(main()) diff --git a/test_assemblyai_interactive.py b/test_assemblyai_interactive.py new file mode 100755 index 000000000..ce468ab3d --- /dev/null +++ b/test_assemblyai_interactive.py @@ -0,0 +1,750 @@ +#!/usr/bin/env python3 +"""Interactive AssemblyAI u3-rt-pro Comprehensive Test Suite + +Tests all features with detailed scenarios: +- Basic configuration variations +- Prompting and keyterms with difficult names +- Diarization +- Dynamic parameter updates (single and multiple) +- Mode comparisons +- STT mode timing experiments (testing silence parameters) +- Edge cases + +Usage: + python test_assemblyai_interactive.py +""" + +import asyncio +import os +import sys +from typing import Optional + +from dotenv import load_dotenv +from loguru import logger + +from pipecat.audio.vad.silero import SileroVADAnalyzer +from pipecat.frames.frames import LLMRunFrame, STTUpdateSettingsFrame +from pipecat.pipeline.pipeline import Pipeline +from pipecat.pipeline.runner import PipelineRunner +from pipecat.pipeline.task import PipelineParams, PipelineTask +from pipecat.processors.aggregators.llm_context import LLMContext +from pipecat.processors.aggregators.llm_response_universal import ( + LLMContextAggregatorPair, + LLMUserAggregatorParams, +) +from pipecat.services.assemblyai.models import AssemblyAIConnectionParams +from pipecat.services.assemblyai.stt import AssemblyAISTTService, AssemblyAISTTSettings +from pipecat.services.cartesia.tts import CartesiaTTSService +from pipecat.services.openai.llm import OpenAILLMService +from pipecat.transports.local.audio import LocalAudioTransport, LocalAudioTransportParams + +load_dotenv(override=True) + +logger.remove(0) +logger.add(sys.stderr, level="INFO") + + +async def run_bot( + connection_params: AssemblyAIConnectionParams, + test_name: str, + vad_force_turn_endpoint: bool = True, + speaker_format: Optional[str] = None, + test_dynamic_updates: Optional[callable] = None, +): + """Run the voice bot with specified configuration.""" + logger.info("="*80) + logger.info(f"TEST: {test_name}") + logger.info("="*80) + logger.info("Starting bot... Speak into your microphone after you hear the greeting!") + logger.info("="*80) + + # Create local audio transport + transport = LocalAudioTransport( + LocalAudioTransportParams( + audio_in_enabled=True, + audio_out_enabled=True, + ) + ) + + # AssemblyAI Speech-to-Text + stt = AssemblyAISTTService( + api_key=os.getenv("ASSEMBLYAI_API_KEY"), + connection_params=connection_params, + vad_force_turn_endpoint=vad_force_turn_endpoint, + speaker_format=speaker_format, + ) + + # Text-to-Speech + tts = CartesiaTTSService( + api_key=os.getenv("CARTESIA_API_KEY"), + voice_id="a0e99841-438c-4a64-b679-ae501e7d6091", + ) + + # LLM + llm = OpenAILLMService( + api_key=os.getenv("OPENAI_API_KEY"), + model="gpt-4", + ) + + # Conversation context + messages = [ + { + "role": "system", + "content": ( + "You are a helpful voice assistant testing the AssemblyAI u3-rt-pro model. " + "Keep responses very brief (1-2 sentences). " + "Start by introducing yourself briefly and asking the user to speak." + ), + }, + ] + + context = LLMContext(messages) + + # Configure aggregator based on mode + user_params = None + if vad_force_turn_endpoint: + user_params = LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()) + + user_aggregator, assistant_aggregator = LLMContextAggregatorPair( + context, + user_params=user_params, + ) + + # Pipeline + pipeline = Pipeline( + [ + transport.input(), + stt, + user_aggregator, + llm, + tts, + transport.output(), + assistant_aggregator, + ] + ) + + # Task + task = PipelineTask( + pipeline, + params=PipelineParams( + enable_metrics=True, + enable_usage_metrics=True, + ), + ) + + # Handle dynamic updates if provided + if test_dynamic_updates: + asyncio.create_task(test_dynamic_updates(task)) + + # Start the conversation + await task.queue_frames([LLMRunFrame()]) + + # Run + runner = PipelineRunner() + await runner.run(task) + + +# ============================================================================ +# Test Configurations +# ============================================================================ + +# === BASIC CONFIGURATION (1-3) === + +async def test_01_basic_100ms(): + """Test 1: Basic default configuration (100ms).""" + connection_params = AssemblyAIConnectionParams( + speech_model="u3-rt-pro", + min_turn_silence=100, + ) + await run_bot(connection_params, "Basic Default Configuration (100ms)") + + +async def test_02_custom_200ms(): + """Test 2: Custom min_end_of_turn_silence (200ms).""" + connection_params = AssemblyAIConnectionParams( + speech_model="u3-rt-pro", + min_turn_silence=200, + ) + await run_bot(connection_params, "Custom Turn Silence (200ms)") + + +async def test_03_custom_500ms(): + """Test 3: Longer silence threshold (500ms).""" + connection_params = AssemblyAIConnectionParams( + speech_model="u3-rt-pro", + min_turn_silence=500, + ) + await run_bot(connection_params, "Longer Turn Silence (500ms)") + + +# === PROMPTING & WARNINGS (4-7) === + +async def test_04_max_warning(): + """Test 4: max_turn_silence warning (should be overridden).""" + logger.warning("⚠️ EXPECT WARNING: max_turn_silence will be overridden") + connection_params = AssemblyAIConnectionParams( + speech_model="u3-rt-pro", + max_turn_silence=500, + ) + await run_bot(connection_params, "max_turn_silence Override Warning") + + +async def test_05_prompt_warning(): + """Test 5: Custom prompt warning.""" + logger.warning("⚠️ EXPECT WARNING: Custom prompts should be tested carefully") + connection_params = AssemblyAIConnectionParams( + speech_model="u3-rt-pro", + prompt="Transcribe speech accurately with proper punctuation.", + ) + await run_bot(connection_params, "Custom Prompt Warning Test") + + +async def test_06_prompt_keyterms_conflict(): + """Test 6: Prompt + keyterms conflict (should error).""" + logger.error("❌ EXPECT ERROR: Cannot use both prompt and keyterms_prompt") + try: + connection_params = AssemblyAIConnectionParams( + speech_model="u3-rt-pro", + prompt="Custom prompt", + keyterms_prompt=["test"], + ) + await run_bot(connection_params, "Prompt + Keyterms Conflict (ERROR)") + except ValueError as e: + logger.error(f"✅ EXPECTED ERROR: {e}") + input("\nPress Enter to continue...") + return + + +async def test_07_keyterms_difficult(): + """Test 7: Keyterms with difficult/unusual names.""" + # Use names that STT wouldn't normally get right + keyterms = ["Xiomara", "Saoirse", "Krzystof", "Nguyen", "Pipecat", "AssemblyAI"] + connection_params = AssemblyAIConnectionParams( + speech_model="u3-rt-pro", + keyterms_prompt=keyterms, + ) + logger.info("🎯 Boosted terms: Xiomara, Saoirse, Krzystof, Nguyen, Pipecat, AssemblyAI") + logger.info(" Try saying these difficult names to test boosting!") + await run_bot(connection_params, "Keyterms with Difficult Names") + + +# === DIARIZATION (8-9) === + +async def test_08_diarization_basic(): + """Test 8: Basic diarization (speaker IDs logged).""" + connection_params = AssemblyAIConnectionParams( + speech_model="u3-rt-pro", + speaker_labels=True, + ) + logger.info("🎤 Diarization enabled - speaker IDs will be logged") + logger.info(" Try having multiple people speak!") + await run_bot(connection_params, "Diarization - Basic") + + +async def test_09_diarization_xml(): + """Test 9: Diarization with XML formatting.""" + connection_params = AssemblyAIConnectionParams( + speech_model="u3-rt-pro", + speaker_labels=True, + ) + logger.info("🎤 Diarization with XML tags") + logger.info(" Transcripts will include text") + await run_bot( + connection_params, + "Diarization - XML Formatting", + speaker_format="{text}", + ) + + +# === DYNAMIC UPDATES - SINGLE PARAMETER (10-13) === + +async def test_10_dynamic_keyterms(): + """Test 10: Dynamic keyterms update with difficult names.""" + connection_params = AssemblyAIConnectionParams( + speech_model="u3-rt-pro", + ) + + async def dynamic_update(task): + logger.info("\n" + "="*80) + logger.info("PHASE 1: No keyterms boosting") + logger.info(" Try saying: Xiomara, Saoirse, Krzystof") + logger.info(" (May not transcribe correctly)") + logger.info("="*80) + await asyncio.sleep(15) + + logger.info("\n" + "="*80) + logger.info("🔄 UPDATING: Adding keyterms boost") + logger.info("="*80) + await task.queue_frame( + STTUpdateSettingsFrame( + delta=AssemblyAISTTSettings( + connection_params=AssemblyAIConnectionParams( + keyterms_prompt=["Xiomara", "Saoirse", "Krzystof", "Nguyen"] + ) + ) + ) + ) + logger.info("\n" + "="*80) + logger.info("PHASE 2: Keyterms NOW boosted") + logger.info(" Say the same names again: Xiomara, Saoirse, Krzystof") + logger.info(" (Should transcribe better now!)") + logger.info("="*80) + + logger.info("🔄 This test has 2 phases:") + logger.info(" Phase 1 (15s): No boosting - names may be wrong") + logger.info(" Phase 2: Keyterms added - names should improve") + await run_bot( + connection_params, + "Dynamic Keyterms Update (Before/After)", + test_dynamic_updates=dynamic_update, + ) + + +async def test_11_dynamic_silence(): + """Test 11: Dynamic silence parameter update (dramatic change).""" + connection_params = AssemblyAIConnectionParams( + speech_model="u3-rt-pro", + min_turn_silence=100, + ) + + async def dynamic_update(task): + logger.info("\n" + "="*80) + logger.info("PHASE 1: Quick responses (100ms silence threshold)") + logger.info(" Speak normally - bot responds quickly") + logger.info("="*80) + await asyncio.sleep(10) + + logger.info("\n" + "="*80) + logger.info("🔄 UPDATING: Changing silence from 100ms → 3000ms (3 seconds!)") + logger.info("="*80) + await task.queue_frame( + STTUpdateSettingsFrame( + delta=AssemblyAISTTSettings( + connection_params=AssemblyAIConnectionParams( + min_turn_silence=3000 + ) + ) + ) + ) + logger.info("\n" + "="*80) + logger.info("PHASE 2: Patient responses (3 second silence threshold)") + logger.info(" Bot will wait 3 full seconds before responding") + logger.info(" Try pausing mid-sentence - bot should NOT interrupt") + logger.info("="*80) + + logger.info("🔄 Dramatic change: 100ms → 3000ms after 10 seconds") + await run_bot( + connection_params, + "Dynamic Silence Update (100ms → 3s)", + test_dynamic_updates=dynamic_update, + ) + + +async def test_12_dynamic_prompt(): + """Test 12: Dynamic prompt update with keyterms in prompt.""" + connection_params = AssemblyAIConnectionParams( + speech_model="u3-rt-pro", + ) + + async def dynamic_update(task): + logger.info("\n" + "="*80) + logger.info("PHASE 1: Default prompt (no keyterms)") + logger.info(" Try saying: Xiomara, Saoirse, Krzystof") + logger.info(" (May not transcribe correctly)") + logger.info("="*80) + await asyncio.sleep(15) + + logger.info("\n" + "="*80) + logger.info("🔄 UPDATING: Adding custom prompt with keyterms") + logger.info("="*80) + custom_prompt = """Transcribe verbatim. Rules: +1) Always include punctuation in output. +2) Use period/question mark ONLY for complete sentences. +3) Use comma for mid-sentence pauses. +4) Use no punctuation for incomplete trailing speech. +5) Filler words (um, uh, so, like) indicate speaker will continue. + +Pay special attention to these names and transcribe them exactly: Xiomara, Saoirse, Krzystof, Nguyen.""" + await task.queue_frame( + STTUpdateSettingsFrame( + delta=AssemblyAISTTSettings( + connection_params=AssemblyAIConnectionParams( + prompt=custom_prompt + ) + ) + ) + ) + logger.info("\n" + "="*80) + logger.info("PHASE 2: Prompt with keyterms NOW active") + logger.info(" Say the same names again: Xiomara, Saoirse, Krzystof") + logger.info(" (Should transcribe better now!)") + logger.info("="*80) + + logger.info("🔄 This test has 2 phases:") + logger.info(" Phase 1 (15s): Default prompt - names may be wrong") + logger.info(" Phase 2: Custom prompt with keyterms - names should improve") + await run_bot( + connection_params, + "Dynamic Prompt Update (with keyterms)", + test_dynamic_updates=dynamic_update, + ) + + +async def test_13_dynamic_clear_keyterms(): + """Test 13: Clear keyterms dynamically.""" + connection_params = AssemblyAIConnectionParams( + speech_model="u3-rt-pro", + keyterms_prompt=["Pipecat", "AssemblyAI"], + ) + + async def dynamic_update(task): + await asyncio.sleep(10) + logger.info("🔄 UPDATING: Clearing keyterms (empty array)") + await task.queue_frame( + STTUpdateSettingsFrame( + delta=AssemblyAISTTSettings( + connection_params=AssemblyAIConnectionParams( + keyterms_prompt=[] + ) + ) + ) + ) + + logger.info("🎯 Initial: Pipecat, AssemblyAI boosted") + logger.info("🔄 After 10s: Keyterms will be cleared") + await run_bot( + connection_params, + "Dynamic Clear Keyterms", + test_dynamic_updates=dynamic_update, + ) + + +# === DYNAMIC UPDATES - MULTIPLE PARAMETERS (14-15) === + +async def test_14_multi_param_update(): + """Test 14: Update multiple parameters at once.""" + connection_params = AssemblyAIConnectionParams( + speech_model="u3-rt-pro", + min_turn_silence=100, + ) + + async def dynamic_update(task): + await asyncio.sleep(10) + logger.info("🔄 UPDATING MULTIPLE: keyterms + silence") + await task.queue_frame( + STTUpdateSettingsFrame( + delta=AssemblyAISTTSettings( + connection_params=AssemblyAIConnectionParams( + keyterms_prompt=["Xiomara", "Pipecat"], + min_turn_silence=250, + ) + ) + ) + ) + + logger.info("🔄 After 10s: Will update BOTH keyterms AND silence threshold") + await run_bot( + connection_params, + "Multiple Parameter Update", + test_dynamic_updates=dynamic_update, + ) + + +async def test_15_complex_sequence(): + """Test 15: Complex multi-stage update sequence.""" + connection_params = AssemblyAIConnectionParams( + speech_model="u3-rt-pro", + ) + + async def dynamic_update(task): + logger.info("Stage 1: Initial (10s)") + await asyncio.sleep(10) + + logger.info("🔄 Stage 2: Add keyterms") + await task.queue_frame( + STTUpdateSettingsFrame( + delta=AssemblyAISTTSettings( + connection_params=AssemblyAIConnectionParams( + keyterms_prompt=["Pipecat"] + ) + ) + ) + ) + await asyncio.sleep(10) + + logger.info("🔄 Stage 3: Change silence") + await task.queue_frame( + STTUpdateSettingsFrame( + delta=AssemblyAISTTSettings( + connection_params=AssemblyAIConnectionParams( + min_turn_silence=200 + ) + ) + ) + ) + await asyncio.sleep(10) + + logger.info("🔄 Stage 4: Update both") + await task.queue_frame( + STTUpdateSettingsFrame( + delta=AssemblyAISTTSettings( + connection_params=AssemblyAIConnectionParams( + keyterms_prompt=["AssemblyAI", "OpenAI"], + min_turn_silence=150, + ) + ) + ) + ) + + logger.info("🔄 Multi-stage: 4 configuration changes over 30 seconds") + await run_bot( + connection_params, + "Complex Update Sequence (4 stages)", + test_dynamic_updates=dynamic_update, + ) + + +# === MODE COMPARISON (16-17) === + +async def test_16_pipecat_mode(): + """Test 16: Pipecat mode (VAD + Smart Turn controls turns).""" + connection_params = AssemblyAIConnectionParams( + speech_model="u3-rt-pro", + min_turn_silence=100, + ) + logger.info("🎯 Pipecat Mode: VAD + Smart Turn control turn detection") + logger.info(" Your min_end_of_turn_silence is sent but ForceEndpoint overrides it") + await run_bot( + connection_params, + "Pipecat Mode (VAD + Smart Turn)", + vad_force_turn_endpoint=True, + ) + + +async def test_17_stt_mode(): + """Test 17: STT mode (model controls turns).""" + connection_params = AssemblyAIConnectionParams( + speech_model="u3-rt-pro", + min_turn_silence=100, + ) + logger.info("🎯 STT Mode: u3-rt-pro model controls turn detection") + logger.info(" No ForceEndpoint - parameters are respected") + await run_bot( + connection_params, + "STT Mode (Model Turn Detection)", + vad_force_turn_endpoint=False, + ) + + +# === STT MODE TIMING EXPERIMENTS (18-20) === + +async def test_18_stt_long_max_short_min(): + """Test 18: STT mode - Long max_turn_silence + Short min (5000ms + 100ms).""" + connection_params = AssemblyAIConnectionParams( + speech_model="u3-rt-pro", + min_turn_silence=100, # Short - quick confident turns + max_turn_silence=5000, # Long - allows pauses up to 5 seconds + ) + logger.info("🎯 STT Mode: Testing max/min parameter interaction") + logger.info(" min_turn_silence: 100ms (quick when confident)") + logger.info(" max_turn_silence: 5000ms (allows up to 5 second pauses)") + logger.info(" Try: Quick sentences (should respond fast) + Long pauses mid-thought") + await run_bot( + connection_params, + "STT: Long Max (5s) + Short Min (100ms)", + vad_force_turn_endpoint=False, + ) + + +async def test_19_stt_long_min(): + """Test 19: STT mode - Long min_turn_silence (3000ms).""" + connection_params = AssemblyAIConnectionParams( + speech_model="u3-rt-pro", + min_turn_silence=3000, # 3 seconds + max_turn_silence=5000, # 5 seconds + ) + logger.info("🎯 STT Mode: Testing long minimum silence requirement") + logger.info(" min_turn_silence: 3000ms") + logger.info(" max_turn_silence: 5000ms") + logger.info(" Bot will wait 3 full seconds of silence before responding!") + logger.info(" Try: Speaking with short pauses - bot should NOT interrupt") + await run_bot( + connection_params, + "STT: Long Min (3s)", + vad_force_turn_endpoint=False, + ) + + +async def test_20_stt_both_short(): + """Test 20: STT mode - Both short (max=300ms, min=100ms).""" + connection_params = AssemblyAIConnectionParams( + speech_model="u3-rt-pro", + min_turn_silence=100, # 100ms + max_turn_silence=300, # 300ms + ) + logger.info("🎯 STT Mode: Testing aggressive/quick response timing") + logger.info(" min_turn_silence: 100ms") + logger.info(" max_turn_silence: 300ms") + logger.info(" Bot will respond VERY quickly to any pause!") + logger.info(" Try: Speaking with natural pauses - expect quick responses") + await run_bot( + connection_params, + "STT: Both Short (300ms/100ms)", + vad_force_turn_endpoint=False, + ) + + +# === EDGE CASES (21-23) === + +async def test_21_very_long_silence(): + """Test 21: Very long silence threshold (STT mode only).""" + connection_params = AssemblyAIConnectionParams( + speech_model="u3-rt-pro", + min_turn_silence=10000, # 10 seconds + ) + logger.warning("⚠️ STT Mode with 10 second silence threshold") + logger.info(" Bot will wait 10 seconds of silence before responding!") + await run_bot( + connection_params, + "Very Long Silence (10s) - STT Mode", + vad_force_turn_endpoint=False, + ) + + +async def test_22_very_short_silence(): + """Test 22: Very short silence threshold (50ms).""" + connection_params = AssemblyAIConnectionParams( + speech_model="u3-rt-pro", + min_turn_silence=50, + ) + logger.info("⚡ Very short silence threshold (50ms)") + logger.info(" Bot will respond very quickly!") + await run_bot(connection_params, "Very Short Silence (50ms)") + + +async def test_23_keyterms_plus_diarization(): + """Test 23: Keyterms + Diarization combined.""" + connection_params = AssemblyAIConnectionParams( + speech_model="u3-rt-pro", + keyterms_prompt=["Xiomara", "Saoirse", "Pipecat"], + speaker_labels=True, + ) + logger.info("🎯 Keyterms + 🎤 Diarization both enabled") + logger.info(" Try multiple speakers saying difficult names!") + await run_bot( + connection_params, + "Keyterms + Diarization Combined", + speaker_format="[{speaker}] {text}", + ) + + +# ============================================================================ +# Interactive Menu +# ============================================================================ + + +def show_menu(): + """Display the comprehensive test menu.""" + print("\n" + "="*80) + print("AssemblyAI u3-rt-pro Comprehensive Test Suite") + print("="*80) + print("\n📋 BASIC CONFIGURATION (1-3)") + print(" 1. Basic Default (100ms)") + print(" 2. Custom Silence (200ms)") + print(" 3. Longer Silence (500ms)") + + print("\n⚠️ PROMPTING & WARNINGS (4-7)") + print(" 4. max_turn_silence Warning") + print(" 5. Custom Prompt Warning") + print(" 6. Prompt + Keyterms Conflict (ERROR)") + print(" 7. Keyterms with Difficult Names") + + print("\n🎤 DIARIZATION (8-9)") + print(" 8. Diarization - Basic") + print(" 9. Diarization - XML Formatting") + + print("\n🔄 DYNAMIC UPDATES - SINGLE (10-13)") + print(" 10. Dynamic Keyterms (Before/After with difficult names)") + print(" 11. Dynamic Silence (100ms → 3s DRAMATIC)") + print(" 12. Dynamic Prompt with Keyterms (Before/After)") + print(" 13. Dynamic Clear Keyterms") + + print("\n🔄 DYNAMIC UPDATES - MULTIPLE (14-15)") + print(" 14. Multiple Parameters at Once") + print(" 15. Complex Update Sequence (4 stages)") + + print("\n⚖️ MODE COMPARISON (16-17)") + print(" 16. Pipecat Mode (VAD + Smart Turn)") + print(" 17. STT Mode (Model Turn Detection)") + + print("\n⏱️ STT MODE TIMING EXPERIMENTS (18-20)") + print(" 18. STT: Long Max (5s) + Short Min (100ms)") + print(" 19. STT: Long Min (3s)") + print(" 20. STT: Both Short (300ms/100ms)") + + print("\n🎯 EDGE CASES (21-23)") + print(" 21. Very Long Silence (10s - STT Mode)") + print(" 22. Very Short Silence (50ms)") + print(" 23. Keyterms + Diarization Combined") + + print("\n 0. Exit") + print("\n" + "="*80) + + +async def main(): + """Main interactive menu.""" + tests = { + "1": test_01_basic_100ms, + "2": test_02_custom_200ms, + "3": test_03_custom_500ms, + "4": test_04_max_warning, + "5": test_05_prompt_warning, + "6": test_06_prompt_keyterms_conflict, + "7": test_07_keyterms_difficult, + "8": test_08_diarization_basic, + "9": test_09_diarization_xml, + "10": test_10_dynamic_keyterms, + "11": test_11_dynamic_silence, + "12": test_12_dynamic_prompt, + "13": test_13_dynamic_clear_keyterms, + "14": test_14_multi_param_update, + "15": test_15_complex_sequence, + "16": test_16_pipecat_mode, + "17": test_17_stt_mode, + "18": test_18_stt_long_max_short_min, + "19": test_19_stt_long_min, + "20": test_20_stt_both_short, + "21": test_21_very_long_silence, + "22": test_22_very_short_silence, + "23": test_23_keyterms_plus_diarization, + } + + while True: + show_menu() + choice = input("Enter test number (or 0 to exit): ").strip() + + if choice == "0": + print("\n👋 Goodbye!") + break + + if choice in tests: + try: + await tests[choice]() + except KeyboardInterrupt: + print("\n\n⚠️ Test interrupted by user") + except Exception as e: + logger.error(f"Test failed with error: {e}") + import traceback + traceback.print_exc() + + input("\n\nPress Enter to return to menu...") + else: + print(f"\n❌ Invalid choice: {choice}") + input("Press Enter to continue...") + + +if __name__ == "__main__": + try: + asyncio.run(main()) + except KeyboardInterrupt: + print("\n\n👋 Goodbye!") diff --git a/test_assemblyai_u3pro.py b/test_assemblyai_u3pro.py new file mode 100644 index 000000000..ace700753 --- /dev/null +++ b/test_assemblyai_u3pro.py @@ -0,0 +1,589 @@ +#!/usr/bin/env python3 +"""AssemblyAI u3-rt-pro Comprehensive Test Script + +Tests all features: +- Basic configuration +- Prompting and keyterms +- Diarization +- Dynamic updates +- Turn detection modes + +Usage: + python test_assemblyai_u3pro.py --test + python test_assemblyai_u3pro.py --interactive +""" + +import argparse +import asyncio +import os +import sys +from typing import List + +from dotenv import load_dotenv +from loguru import logger + +# Add src to path +sys.path.insert(0, os.path.join(os.path.dirname(__file__), "src")) + +from pipecat.audio.vad.silero import SileroVADAnalyzer +from pipecat.frames.frames import ( + EndFrame, + Frame, + LLMRunFrame, + STTUpdateSettingsFrame, + TranscriptionFrame, +) +from pipecat.pipeline.pipeline import Pipeline +from pipecat.pipeline.runner import PipelineRunner +from pipecat.pipeline.task import PipelineTask +from pipecat.processors.aggregators.llm_context import LLMContext +from pipecat.processors.aggregators.llm_response_universal import ( + LLMContextAggregatorPair, + LLMUserAggregatorParams, +) +from pipecat.processors.frame_processor import FrameDirection, FrameProcessor +from pipecat.services.assemblyai.models import AssemblyAIConnectionParams +from pipecat.services.assemblyai.stt import AssemblyAISTTService +from pipecat.services.cartesia.tts import CartesiaTTSService +from pipecat.services.openai.llm import OpenAILLMService +from pipecat.transports.local.audio import LocalAudioTransport, LocalAudioTransportParams + +load_dotenv() + +# Test configuration +class TestConfig: + """Centralized test configuration.""" + + ASSEMBLYAI_API_KEY = os.getenv("ASSEMBLYAI_API_KEY") + OPENAI_API_KEY = os.getenv("OPENAI_API_KEY") + CARTESIA_API_KEY = os.getenv("CARTESIA_API_KEY") + + @classmethod + def validate(cls): + """Validate all required API keys are set.""" + missing = [] + if not cls.ASSEMBLYAI_API_KEY: + missing.append("ASSEMBLYAI_API_KEY") + if not cls.OPENAI_API_KEY: + missing.append("OPENAI_API_KEY") + if not cls.CARTESIA_API_KEY: + missing.append("CARTESIA_API_KEY") + + if missing: + logger.error(f"Missing required environment variables: {', '.join(missing)}") + return False + return True + + +class TranscriptionLogger(FrameProcessor): + """Log transcriptions for test verification.""" + + async def process_frame(self, frame: Frame, direction: FrameDirection): + if isinstance(frame, TranscriptionFrame): + logger.info(f"📝 TRANSCRIPTION: {frame.text}") + logger.info(f" Speaker: {frame.user_id}") + logger.info(f" Finalized: {frame.finalized}") + if hasattr(frame, "result") and frame.result: + if hasattr(frame.result, "speaker"): + logger.info(f" Diarization: {frame.result.speaker}") + + await self.push_frame(frame, direction) + + +async def create_basic_voice_agent( + connection_params: AssemblyAIConnectionParams, + vad_force_turn_endpoint: bool = True, + speaker_format: str = None, +) -> tuple[PipelineTask, LocalAudioTransport]: + """Create a basic voice agent for testing. + + Args: + connection_params: AssemblyAI connection parameters + vad_force_turn_endpoint: Turn detection mode + speaker_format: Optional speaker formatting string + + Returns: + Tuple of (PipelineTask, LocalAudioTransport) + """ + # Create local audio transport (uses your microphone and speakers) + transport = LocalAudioTransport( + params=LocalAudioTransportParams( + audio_in_enabled=True, + audio_out_enabled=True, + ) + ) + + # Create STT + stt = AssemblyAISTTService( + api_key=TestConfig.ASSEMBLYAI_API_KEY, + connection_params=connection_params, + vad_force_turn_endpoint=vad_force_turn_endpoint, + speaker_format=speaker_format, + ) + + # Create TTS + tts = CartesiaTTSService( + api_key=TestConfig.CARTESIA_API_KEY, + voice_id="a0e99841-438c-4a64-b679-ae501e7d6091", # Conversational English + ) + + # Create LLM context and service + messages = [ + { + "role": "system", + "content": ( + "You are a helpful voice assistant. Keep responses brief and natural. " + "If you see speaker tags like text, acknowledge " + "that you understand multiple speakers are present." + ), + } + ] + + context = LLMContext(messages) + llm = OpenAILLMService(api_key=TestConfig.OPENAI_API_KEY, model="gpt-4") + + # Create aggregators with VAD + user_aggregator, assistant_aggregator = LLMContextAggregatorPair( + context, + user_params=LLMUserAggregatorParams( + vad_analyzer=SileroVADAnalyzer(), + ), + ) + + # Create transcription logger + transcription_logger = TranscriptionLogger() + + # Create pipeline + pipeline = Pipeline( + [ + transport.input(), + stt, + transcription_logger, + user_aggregator, + llm, + tts, + transport.output(), + assistant_aggregator, + ] + ) + + # Create task + task = PipelineTask(pipeline) + + return task, transport + + +# ============================================================================ +# Test Functions +# ============================================================================ + + +async def test_basic_config(): + """Test 1: Basic default configuration.""" + logger.info("=" * 80) + logger.info("TEST 1: Basic Default Configuration") + logger.info("=" * 80) + + connection_params = AssemblyAIConnectionParams(speech_model="u3-rt-pro") + + task, transport = await create_basic_voice_agent(connection_params) + + logger.info("✅ Service created successfully with default params") + logger.info("Expected: min=max=100ms, u3-rt-pro model") + logger.info("Speak into your microphone to test transcription") + + # Trigger initial bot greeting + await task.queue_frames([LLMRunFrame()]) + + runner = PipelineRunner() + await runner.run(task) + + +async def test_custom_min_silence(): + """Test 2: Custom min_turn_silence.""" + logger.info("=" * 80) + logger.info("TEST 2: Custom min_turn_silence") + logger.info("=" * 80) + + connection_params = AssemblyAIConnectionParams( + speech_model="u3-rt-pro", min_turn_silence=200 + ) + + task, transport = await create_basic_voice_agent(connection_params) + + logger.info("✅ Service created with min=200ms") + logger.info("Expected: Both min and max set to 200ms") + logger.info("Speak short phrases and observe turn detection timing") + + runner = PipelineRunner() + await runner.run(task) + + +async def test_max_silence_warning(): + """Test 3: Setting max_turn_silence should trigger warning.""" + logger.info("=" * 80) + logger.info("TEST 3: max_turn_silence Warning") + logger.info("=" * 80) + + connection_params = AssemblyAIConnectionParams( + speech_model="u3-rt-pro", + min_turn_silence=100, + max_turn_silence=500, # Should trigger warning + ) + + task, transport = await create_basic_voice_agent(connection_params) + + logger.info("⚠️ Check logs above for warning about max_turn_silence being overridden") + logger.info("Expected: Warning logged, max set to 100ms (same as min)") + + runner = PipelineRunner() + await runner.run(task) + + +async def test_custom_prompt_warning(): + """Test 5: Custom prompt should trigger warning.""" + logger.info("=" * 80) + logger.info("TEST 5: Custom Prompt Warning") + logger.info("=" * 80) + + connection_params = AssemblyAIConnectionParams( + speech_model="u3-rt-pro", + prompt="Transcribe verbatim. Always include punctuation.", + ) + + task, transport = await create_basic_voice_agent(connection_params) + + logger.info("⚠️ Check logs above for warning about testing without prompt first") + logger.info("Expected: Warning logged, service continues with custom prompt") + + runner = PipelineRunner() + await runner.run(task) + + +async def test_prompt_keyterms_conflict(): + """Test 6: Prompt + keyterms_prompt should raise error.""" + logger.info("=" * 80) + logger.info("TEST 6: Prompt + Keyterms Conflict (Error)") + logger.info("=" * 80) + + try: + connection_params = AssemblyAIConnectionParams( + speech_model="u3-rt-pro", + prompt="Custom prompt", + keyterms_prompt=["test", "words"], + ) + + task, transport = await create_basic_voice_agent(connection_params) + logger.error("❌ TEST FAILED: Should have raised ValueError") + except ValueError as e: + logger.info(f"✅ TEST PASSED: ValueError raised as expected") + logger.info(f" Error message: {e}") + + +async def test_keyterms_basic(): + """Test 7: Basic keyterms at initialization.""" + logger.info("=" * 80) + logger.info("TEST 7: Basic Keyterms Prompting") + logger.info("=" * 80) + + connection_params = AssemblyAIConnectionParams( + speech_model="u3-rt-pro", + keyterms_prompt=["Pipecat", "AssemblyAI", "Universal-3", "streaming"], + ) + + task, transport = await create_basic_voice_agent(connection_params) + + logger.info("✅ Service created with keyterms: Pipecat, AssemblyAI, Universal-3, streaming") + logger.info("Expected: Boosted recognition for these terms") + logger.info("Try saying: 'I'm testing Pipecat with AssemblyAI Universal-3 for streaming'") + + runner = PipelineRunner() + await runner.run(task) + + +async def test_diarization_no_format(): + """Test 10: Diarization enabled without formatting.""" + logger.info("=" * 80) + logger.info("TEST 10: Diarization Enabled (No Formatting)") + logger.info("=" * 80) + + connection_params = AssemblyAIConnectionParams( + speech_model="u3-rt-pro", speaker_labels=True + ) + + task, transport = await create_basic_voice_agent(connection_params) + + logger.info("✅ Service created with speaker_labels=True") + logger.info("Expected: Speaker IDs in user_id field, plain text in transcript") + logger.info("Have multiple people speak to see different speaker labels") + + runner = PipelineRunner() + await runner.run(task) + + +async def test_diarization_xml_format(): + """Test 11: Diarization with XML formatting.""" + logger.info("=" * 80) + logger.info("TEST 11: Diarization with XML Formatting") + logger.info("=" * 80) + + connection_params = AssemblyAIConnectionParams( + speech_model="u3-rt-pro", speaker_labels=True + ) + + task, transport = await create_basic_voice_agent( + connection_params, speaker_format="<{speaker}>{text}" + ) + + logger.info("✅ Service created with XML speaker formatting") + logger.info("Expected: Text like 'Hello'") + logger.info("Have multiple people speak to see formatted speaker tags") + + runner = PipelineRunner() + await runner.run(task) + + +async def test_dynamic_keyterms(): + """Test 13: Dynamic keyterms updates.""" + logger.info("=" * 80) + logger.info("TEST 13: Dynamic Keyterms Updates") + logger.info("=" * 80) + + connection_params = AssemblyAIConnectionParams(speech_model="u3-rt-pro") + + task, transport = await create_basic_voice_agent(connection_params) + + async def update_keyterms_stages(): + """Simulate multi-stage conversation with keyterms updates.""" + await asyncio.sleep(5) # Wait for connection + + # Stage 1: Greeting + logger.info("🔄 STAGE 1: Greeting (general terms)") + update1 = STTUpdateSettingsFrame( + settings={"keyterms_prompt": ["hello", "hi", "good morning", "welcome"]} + ) + await task.queue_frames([update1]) + + await asyncio.sleep(10) + + # Stage 2: Name collection + logger.info("🔄 STAGE 2: Name Collection") + update2 = STTUpdateSettingsFrame( + settings={ + "keyterms_prompt": [ + "first name", + "last name", + "John", + "Jane", + "Smith", + "Johnson", + ] + } + ) + await task.queue_frames([update2]) + + await asyncio.sleep(10) + + # Stage 3: Medical info + logger.info("🔄 STAGE 3: Medical Information") + update3 = STTUpdateSettingsFrame( + settings={ + "keyterms_prompt": [ + "cardiology", + "echocardiogram", + "blood pressure", + "Dr. Smith", + "metoprolol", + ] + } + ) + await task.queue_frames([update3]) + + await asyncio.sleep(10) + + # Stage 4: Clear keyterms + logger.info("🔄 STAGE 4: Clear Keyterms") + update4 = STTUpdateSettingsFrame(settings={"keyterms_prompt": []}) + await task.queue_frames([update4]) + + # Start update task + asyncio.create_task(update_keyterms_stages()) + + logger.info("✅ Service created, will update keyterms every 10 seconds") + logger.info("Expected: Different keyterms at each stage") + logger.info("Watch logs for 'STAGE X' messages and test relevant terms") + + runner = PipelineRunner() + await runner.run(task) + + +async def test_dynamic_silence_params(): + """Test 15: Dynamic silence parameter updates.""" + logger.info("=" * 80) + logger.info("TEST 15: Dynamic Silence Parameters") + logger.info("=" * 80) + + connection_params = AssemblyAIConnectionParams(speech_model="u3-rt-pro") + + task, transport = await create_basic_voice_agent(connection_params) + + async def update_silence_params(): + """Update silence parameters for different scenarios.""" + await asyncio.sleep(5) + + # Normal conversation + logger.info("🔄 PHASE 1: Normal conversation (default timing)") + await asyncio.sleep(10) + + # Reading credit card + logger.info("🔄 PHASE 2: Reading numbers (longer silence tolerance)") + update1 = STTUpdateSettingsFrame( + settings={ + "max_turn_silence": 5000, + "min_turn_silence": 300, + } + ) + await task.queue_frames([update1]) + + await asyncio.sleep(15) + + # Back to normal + logger.info("🔄 PHASE 3: Back to normal conversation") + update2 = STTUpdateSettingsFrame( + settings={ + "max_turn_silence": 1200, + "min_turn_silence": 100, + } + ) + await task.queue_frames([update2]) + + asyncio.create_task(update_silence_params()) + + logger.info("✅ Service will update silence parameters during conversation") + logger.info("Expected: Longer pauses tolerated in Phase 2") + logger.info("Try pausing between words to test") + + runner = PipelineRunner() + await runner.run(task) + + +async def test_multi_param_update(): + """Test 17: Update multiple parameters at once.""" + logger.info("=" * 80) + logger.info("TEST 17: Multiple Parameter Update") + logger.info("=" * 80) + + connection_params = AssemblyAIConnectionParams(speech_model="u3-rt-pro") + + task, transport = await create_basic_voice_agent(connection_params) + + async def multi_update(): + await asyncio.sleep(5) + + logger.info("🔄 Updating multiple parameters together") + update = STTUpdateSettingsFrame( + settings={ + "keyterms_prompt": ["account", "routing", "number"], + "max_turn_silence": 3000, + "min_turn_silence": 200, + } + ) + await task.queue_frames([update]) + + logger.info("✅ Check logs for single UpdateConfiguration message") + + asyncio.create_task(multi_update()) + + logger.info("Expected: All params updated in single WebSocket message") + + runner = PipelineRunner() + await runner.run(task) + + +# ============================================================================ +# Main Test Runner +# ============================================================================ + + +def main(): + """Main test runner.""" + parser = argparse.ArgumentParser(description="Test AssemblyAI u3-rt-pro integration") + parser.add_argument( + "--test", + type=str, + default="basic", + help="Test to run (basic, custom_min, max_warning, prompt_warning, " + "prompt_keyterms_conflict, keyterms, diarization, diarization_xml, " + "dynamic_keyterms, dynamic_silence, multi_param, all)", + ) + parser.add_argument( + "--interactive", action="store_true", help="Run in interactive mode" + ) + + args = parser.parse_args() + + # Validate environment + if not TestConfig.validate(): + logger.error("Please set all required environment variables in .env") + sys.exit(1) + + # Test mapping + tests = { + "basic": test_basic_config, + "custom_min": test_custom_min_silence, + "max_warning": test_max_silence_warning, + "prompt_warning": test_custom_prompt_warning, + "prompt_keyterms_conflict": test_prompt_keyterms_conflict, + "keyterms": test_keyterms_basic, + "diarization": test_diarization_no_format, + "diarization_xml": test_diarization_xml_format, + "dynamic_keyterms": test_dynamic_keyterms, + "dynamic_silence": test_dynamic_silence_params, + "multi_param": test_multi_param_update, + } + + if args.interactive: + logger.info("Interactive mode - select test to run:") + for i, (name, _) in enumerate(tests.items(), 1): + logger.info(f"{i}. {name}") + logger.info(f"{len(tests) + 1}. Run all tests") + + choice = input("\nEnter test number: ") + try: + choice_num = int(choice) + if choice_num == len(tests) + 1: + args.test = "all" + else: + args.test = list(tests.keys())[choice_num - 1] + except (ValueError, IndexError): + logger.error("Invalid choice") + sys.exit(1) + + # Run test(s) + if args.test == "all": + logger.info("Running all tests sequentially...") + for test_name, test_func in tests.items(): + try: + asyncio.run(test_func()) + except KeyboardInterrupt: + logger.info(f"Test '{test_name}' interrupted") + break + except Exception as e: + logger.error(f"Test '{test_name}' failed: {e}") + else: + if args.test not in tests: + logger.error(f"Unknown test: {args.test}") + logger.info(f"Available tests: {', '.join(tests.keys())}") + sys.exit(1) + + try: + asyncio.run(tests[args.test]()) + except KeyboardInterrupt: + logger.info("Test interrupted") + except Exception as e: + logger.error(f"Test failed: {e}") + raise + + +if __name__ == "__main__": + main() From 07ae4b8d385f3f67b32bc06548382fc1bcade3e2 Mon Sep 17 00:00:00 2001 From: zack Date: Sun, 1 Mar 2026 11:27:31 -0500 Subject: [PATCH 0706/1060] Update AssemblyAI examples to use u3-rt-pro and improve 55d example - Update 13d-assemblyai-transcription.py to explicitly use u3-rt-pro model - Update 55d-update-settings-assemblyai-stt.py to demonstrate keyterms updates instead of language updates - Add helpful logging to show before/after keyterms boosting effect - Use difficult names (Xiomara, Saoirse, Krzystof) to demonstrate boosting effectiveness --- .../13d-assemblyai-transcription.py | 4 +++ .../55d-update-settings-assemblyai-stt.py | 25 ++++++++++++++----- 2 files changed, 23 insertions(+), 6 deletions(-) diff --git a/examples/foundational/13d-assemblyai-transcription.py b/examples/foundational/13d-assemblyai-transcription.py index 06ea52cd5..2dcbaf59b 100644 --- a/examples/foundational/13d-assemblyai-transcription.py +++ b/examples/foundational/13d-assemblyai-transcription.py @@ -16,6 +16,7 @@ from pipecat.pipeline.task import PipelineTask from pipecat.processors.frame_processor import FrameDirection, FrameProcessor from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport +from pipecat.services.assemblyai.models import AssemblyAIConnectionParams from pipecat.services.assemblyai.stt import AssemblyAISTTService from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams @@ -49,6 +50,9 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): stt = AssemblyAISTTService( api_key=os.getenv("ASSEMBLYAI_API_KEY"), + connection_params=AssemblyAIConnectionParams( + speech_model="u3-rt-pro", + ), ) tl = TranscriptionLogger() diff --git a/examples/foundational/55d-update-settings-assemblyai-stt.py b/examples/foundational/55d-update-settings-assemblyai-stt.py index d37c3ec7b..b0d676e25 100644 --- a/examples/foundational/55d-update-settings-assemblyai-stt.py +++ b/examples/foundational/55d-update-settings-assemblyai-stt.py @@ -22,10 +22,10 @@ from pipecat.processors.aggregators.llm_response_universal import ( ) from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport +from pipecat.services.assemblyai.models import AssemblyAIConnectionParams from pipecat.services.assemblyai.stt import AssemblyAISTTService, AssemblyAISTTSettings from pipecat.services.cartesia.tts import CartesiaTTSService from pipecat.services.openai.llm import OpenAILLMService -from pipecat.transcriptions.language import Language from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams @@ -51,7 +51,12 @@ transport_params = { async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): logger.info(f"Starting bot") - stt = AssemblyAISTTService(api_key=os.getenv("ASSEMBLYAI_API_KEY")) + stt = AssemblyAISTTService( + api_key=os.getenv("ASSEMBLYAI_API_KEY"), + connection_params=AssemblyAIConnectionParams( + speech_model="u3-rt-pro", + ), + ) tts = CartesiaTTSService( api_key=os.getenv("CARTESIA_API_KEY"), @@ -63,7 +68,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): messages = [ { "role": "system", - "content": "You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + "content": "You are a helpful LLM in a WebRTC call demonstrating dynamic keyterms updates. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Try saying difficult names like 'Xiomara', 'Saoirse', or 'Krzystof' to test transcription accuracy.", }, ] @@ -97,14 +102,22 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): @transport.event_handler("on_client_connected") async def on_client_connected(transport, client): logger.info(f"Client connected") + logger.info("Phase 1: No keyterms boosting - try saying 'Xiomara', 'Saoirse', or 'Krzystof'") messages.append({"role": "system", "content": "Please introduce yourself to the user."}) await task.queue_frames([LLMRunFrame()]) - await asyncio.sleep(10) - logger.info("Updating AssemblyAI STT settings: language=es") + await asyncio.sleep(15) + logger.info("🔄 Updating keyterms: Adding difficult names for boosting") await task.queue_frame( - STTUpdateSettingsFrame(delta=AssemblyAISTTSettings(language=Language.ES)) + STTUpdateSettingsFrame( + delta=AssemblyAISTTSettings( + connection_params=AssemblyAIConnectionParams( + keyterms_prompt=["Xiomara", "Saoirse", "Krzystof", "Nguyen", "Pipecat"] + ) + ) + ) ) + logger.info("Phase 2: Keyterms active - same names should transcribe better now!") @transport.event_handler("on_client_disconnected") async def on_client_disconnected(transport, client): From 66fca7e3822f75e2042e7cd9e2010c94d0242339 Mon Sep 17 00:00:00 2001 From: zack Date: Sun, 1 Mar 2026 11:33:22 -0500 Subject: [PATCH 0707/1060] Add backward compatibility for min_end_of_turn_silence_when_confident parameter - Keep old parameter name for backward compatibility - Add deprecation warning when old parameter is used - Automatically migrate old parameter value to new min_turn_silence parameter - Exclude deprecated parameter from WebSocket URL to avoid sending it to API - New parameter takes precedence if both are set --- src/pipecat/services/assemblyai/models.py | 20 +++++++++++++++++++- src/pipecat/services/assemblyai/stt.py | 3 +++ 2 files changed, 22 insertions(+), 1 deletion(-) diff --git a/src/pipecat/services/assemblyai/models.py b/src/pipecat/services/assemblyai/models.py index f92b1b8bf..d8df07899 100644 --- a/src/pipecat/services/assemblyai/models.py +++ b/src/pipecat/services/assemblyai/models.py @@ -11,8 +11,9 @@ transcription WebSocket messages and connection configuration. """ from typing import List, Literal, Optional +import warnings -from pydantic import BaseModel, ConfigDict, Field +from pydantic import BaseModel, ConfigDict, Field, model_validator class Word(BaseModel): @@ -130,6 +131,7 @@ class AssemblyAIConnectionParams(BaseModel): word_finalization_max_wait_time: Maximum time to wait for word finalization in milliseconds. end_of_turn_confidence_threshold: Confidence threshold for end-of-turn detection. min_turn_silence: Minimum silence duration when confident about end-of-turn. + min_end_of_turn_silence_when_confident: DEPRECATED. Use min_turn_silence instead. max_turn_silence: Maximum silence duration before forcing end-of-turn. keyterms_prompt: List of key terms to guide transcription. Will be JSON serialized before sending. prompt: Optional text prompt to guide the transcription. Only used when speech_model is "u3-rt-pro". @@ -149,6 +151,7 @@ class AssemblyAIConnectionParams(BaseModel): word_finalization_max_wait_time: Optional[int] = None end_of_turn_confidence_threshold: Optional[float] = None min_turn_silence: Optional[int] = None + min_end_of_turn_silence_when_confident: Optional[int] = None # Deprecated max_turn_silence: Optional[int] = None keyterms_prompt: Optional[List[str]] = None prompt: Optional[str] = None @@ -158,3 +161,18 @@ class AssemblyAIConnectionParams(BaseModel): language_detection: Optional[bool] = None format_turns: bool = True speaker_labels: Optional[bool] = None + + @model_validator(mode="after") + def handle_deprecated_param(self): + """Handle deprecated min_end_of_turn_silence_when_confident parameter.""" + if self.min_end_of_turn_silence_when_confident is not None: + warnings.warn( + "The 'min_end_of_turn_silence_when_confident' parameter is deprecated and will be " + "removed in a future version. Please use 'min_turn_silence' instead.", + DeprecationWarning, + stacklevel=2, + ) + # If min_turn_silence is not set, use the deprecated value + if self.min_turn_silence is None: + self.min_turn_silence = self.min_end_of_turn_silence_when_confident + return self diff --git a/src/pipecat/services/assemblyai/stt.py b/src/pipecat/services/assemblyai/stt.py index d82b38a99..7e2378408 100644 --- a/src/pipecat/services/assemblyai/stt.py +++ b/src/pipecat/services/assemblyai/stt.py @@ -462,6 +462,9 @@ class AssemblyAISTTService(WebsocketSTTService): """Build WebSocket URL with query parameters using urllib.parse.urlencode.""" params = {} for k, v in self._settings.connection_params.model_dump().items(): + # Skip deprecated parameter - it's been migrated to min_turn_silence + if k == "min_end_of_turn_silence_when_confident": + continue if v is not None: if k == "keyterms_prompt": params[k] = json.dumps(v) From d1cbc811083cf2ebfffe2c66c498647b0027fe55 Mon Sep 17 00:00:00 2001 From: zack Date: Sun, 1 Mar 2026 11:36:46 -0500 Subject: [PATCH 0708/1060] Fix 07o example to use new min_turn_silence parameter name in docs and comments --- examples/foundational/07o-interruptible-assemblyai-stt.py | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/examples/foundational/07o-interruptible-assemblyai-stt.py b/examples/foundational/07o-interruptible-assemblyai-stt.py index ee2994c0e..2765f8590 100644 --- a/examples/foundational/07o-interruptible-assemblyai-stt.py +++ b/examples/foundational/07o-interruptible-assemblyai-stt.py @@ -66,8 +66,8 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): - More natural turn detection based on speech patterns and pauses 2. Advanced Turn Detection Tuning (STT Mode) - - `min_turn_silence`: Minimum silence (ms) when confident - about end-of-turn. Lower values = faster responses. Default: 200ms + - `min_turn_silence`: Minimum silence (ms) when confident about end-of-turn. + Lower values = faster responses. Default: 100ms - `max_turn_silence`: Maximum silence (ms) before forcing end-of-turn. Prevents long pauses. Default: 1000ms From 5de495cc989adf7ae2d2624c9e6613978f69b77c Mon Sep 17 00:00:00 2001 From: zack Date: Sun, 1 Mar 2026 11:39:00 -0500 Subject: [PATCH 0709/1060] Use logger.warning instead of warnings.warn for deprecation message - Makes deprecation warning visible in logs without needing Python warning flags - Users will see the warning during normal operation --- src/pipecat/services/assemblyai/models.py | 8 +++----- 1 file changed, 3 insertions(+), 5 deletions(-) diff --git a/src/pipecat/services/assemblyai/models.py b/src/pipecat/services/assemblyai/models.py index d8df07899..3a022dce1 100644 --- a/src/pipecat/services/assemblyai/models.py +++ b/src/pipecat/services/assemblyai/models.py @@ -11,8 +11,8 @@ transcription WebSocket messages and connection configuration. """ from typing import List, Literal, Optional -import warnings +from loguru import logger from pydantic import BaseModel, ConfigDict, Field, model_validator @@ -166,11 +166,9 @@ class AssemblyAIConnectionParams(BaseModel): def handle_deprecated_param(self): """Handle deprecated min_end_of_turn_silence_when_confident parameter.""" if self.min_end_of_turn_silence_when_confident is not None: - warnings.warn( + logger.warning( "The 'min_end_of_turn_silence_when_confident' parameter is deprecated and will be " - "removed in a future version. Please use 'min_turn_silence' instead.", - DeprecationWarning, - stacklevel=2, + "removed in a future version. Please use 'min_turn_silence' instead." ) # If min_turn_silence is not set, use the deprecated value if self.min_turn_silence is None: From 42f91a905613e7b481489cb6437df87821a81e95 Mon Sep 17 00:00:00 2001 From: zack Date: Sun, 1 Mar 2026 11:44:37 -0500 Subject: [PATCH 0710/1060] Apply ruff formatting fixes --- .../55d-update-settings-assemblyai-stt.py | 4 +- src/pipecat/services/assemblyai/stt.py | 7 +- test_assemblyai_custom.py | 32 ++------ test_assemblyai_interactive.py | 77 +++++++++---------- test_assemblyai_u3pro.py | 17 ++-- 5 files changed, 56 insertions(+), 81 deletions(-) diff --git a/examples/foundational/55d-update-settings-assemblyai-stt.py b/examples/foundational/55d-update-settings-assemblyai-stt.py index b0d676e25..f57865588 100644 --- a/examples/foundational/55d-update-settings-assemblyai-stt.py +++ b/examples/foundational/55d-update-settings-assemblyai-stt.py @@ -102,7 +102,9 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): @transport.event_handler("on_client_connected") async def on_client_connected(transport, client): logger.info(f"Client connected") - logger.info("Phase 1: No keyterms boosting - try saying 'Xiomara', 'Saoirse', or 'Krzystof'") + logger.info( + "Phase 1: No keyterms boosting - try saying 'Xiomara', 'Saoirse', or 'Krzystof'" + ) messages.append({"role": "system", "content": "Please introduce yourself to the user."}) await task.queue_frames([LLMRunFrame()]) diff --git a/src/pipecat/services/assemblyai/stt.py b/src/pipecat/services/assemblyai/stt.py index 7e2378408..9938afdee 100644 --- a/src/pipecat/services/assemblyai/stt.py +++ b/src/pipecat/services/assemblyai/stt.py @@ -355,13 +355,10 @@ class AssemblyAISTTService(WebsocketSTTService): if hasattr(conn_params, "min_turn_silence"): if ( old_conn_params is None - or conn_params.min_turn_silence - != old_conn_params.min_turn_silence + or conn_params.min_turn_silence != old_conn_params.min_turn_silence ): if conn_params.min_turn_silence is not None: - update_config["min_turn_silence"] = ( - conn_params.min_turn_silence - ) + update_config["min_turn_silence"] = conn_params.min_turn_silence logger.info( f"Updating min_turn_silence to: {conn_params.min_turn_silence}ms" ) diff --git a/test_assemblyai_custom.py b/test_assemblyai_custom.py index c406918c0..e8e0a28d2 100755 --- a/test_assemblyai_custom.py +++ b/test_assemblyai_custom.py @@ -48,11 +48,11 @@ async def main(): logger.remove(0) logger.add(sys.stderr, level=LOG_LEVEL) - logger.info("="*80) + logger.info("=" * 80) logger.info("AssemblyAI u3-rt-pro Custom Test") - logger.info("="*80) + logger.info("=" * 80) logger.info("Starting bot... Speak after you hear the greeting!") - logger.info("="*80) + logger.info("=" * 80) # Create local audio transport transport = LocalAudioTransport( @@ -74,78 +74,63 @@ async def main(): speech_model="u3-rt-pro", # speech_model="universal-streaming-english", # speech_model="universal-streaming-multilingual", - # ==================================================================== # Turn Detection Timing # ==================================================================== - # Minimum silence when confident about end of turn (milliseconds) # Default: 100ms | Higher = more patient | Lower = faster responses # Only used in Pipecat mode (vad_force_turn_endpoint=True) min_turn_silence=100000, # min_turn_silence=200, # min_turn_silence=300, - # Maximum turn silence (milliseconds) # WARNING: In Pipecat mode (vad_force_turn_endpoint=True), this is # automatically set equal to min_turn_silence # to avoid double turn detection. Only used as-is in STT mode. max_turn_silence=500, - # End of turn confidence threshold (0.0 to 1.0) # Higher = requires more confidence before ending turn # end_of_turn_confidence_threshold=0.8, - # ==================================================================== # Prompting & Boosting # ==================================================================== - # Custom Prompt (WARNING: test carefully, default is optimized!) # None = Use AssemblyAI's optimized default (recommended for 88% accuracy) prompt=None, # prompt="Transcribe speech with focus on technical terms.", # prompt="Context: Medical conversation. Transcribe accurately.", - # Keyterms Prompting (boosts recognition for specific words) # NOTE: Cannot use both prompt and keyterms_prompt! keyterms_prompt=None, # keyterms_prompt=["Pipecat", "AssemblyAI", "OpenAI", "Cartesia"], # keyterms_prompt=["Python", "JavaScript", "TypeScript", "API"], - # ==================================================================== # Diarization (Speaker Identification) # ==================================================================== - # Enable speaker labels (identifies different speakers) speaker_labels=None, # None or True # speaker_labels=True, - # ==================================================================== # Audio Configuration # ==================================================================== - # Audio sample rate (Hz) # sample_rate=16000, # sample_rate=8000, - # Audio encoding format # encoding="pcm_s16le", # Default: 16-bit PCM # encoding="pcm_mulaw", # μ-law encoding (telephony) - # ==================================================================== # Other Options # ==================================================================== - # Format transcript turns (applies formatting rules) # format_turns=True, # Default # format_turns=False, - # Language detection (only for universal-streaming-multilingual) # language_detection=True, ) # Log connection parameters for debugging - logger.info("="*80) + logger.info("=" * 80) logger.info("CONNECTION PARAMETERS:") logger.info(f" speech_model: {connection_params.speech_model}") logger.info(f" min_turn_silence: {connection_params.min_turn_silence}") @@ -156,27 +141,26 @@ async def main(): logger.info(f" keyterms_prompt: {connection_params.keyterms_prompt}") logger.info(f" speaker_labels: {connection_params.speaker_labels}") logger.info(f" format_turns: {connection_params.format_turns}") - logger.info(f" end_of_turn_confidence_threshold: {connection_params.end_of_turn_confidence_threshold}") + logger.info( + f" end_of_turn_confidence_threshold: {connection_params.end_of_turn_confidence_threshold}" + ) logger.info(f" language_detection: {connection_params.language_detection}") - logger.info("="*80) + logger.info("=" * 80) # AssemblyAI Speech-to-Text Service stt = AssemblyAISTTService( api_key=os.getenv("ASSEMBLYAI_API_KEY"), connection_params=connection_params, - # Turn Detection Mode # True = Pipecat mode (VAD + Smart Turn controls turns) # False = STT mode (u3-rt-pro model controls turns) vad_force_turn_endpoint=True, - # Speaker Formatting (only used if speaker_labels=True) # None = Just log speaker IDs, don't modify transcript speaker_format=None, # speaker_format="{text}", # speaker_format="{speaker}: {text}", # speaker_format="[{speaker}] {text}", - # Additional available parameters (uncomment to use): # should_interrupt=True, # Only for STT mode ) diff --git a/test_assemblyai_interactive.py b/test_assemblyai_interactive.py index ce468ab3d..c5ec0b429 100755 --- a/test_assemblyai_interactive.py +++ b/test_assemblyai_interactive.py @@ -52,11 +52,11 @@ async def run_bot( test_dynamic_updates: Optional[callable] = None, ): """Run the voice bot with specified configuration.""" - logger.info("="*80) + logger.info("=" * 80) logger.info(f"TEST: {test_name}") - logger.info("="*80) + logger.info("=" * 80) logger.info("Starting bot... Speak into your microphone after you hear the greeting!") - logger.info("="*80) + logger.info("=" * 80) # Create local audio transport transport = LocalAudioTransport( @@ -150,6 +150,7 @@ async def run_bot( # === BASIC CONFIGURATION (1-3) === + async def test_01_basic_100ms(): """Test 1: Basic default configuration (100ms).""" connection_params = AssemblyAIConnectionParams( @@ -179,6 +180,7 @@ async def test_03_custom_500ms(): # === PROMPTING & WARNINGS (4-7) === + async def test_04_max_warning(): """Test 4: max_turn_silence warning (should be overridden).""" logger.warning("⚠️ EXPECT WARNING: max_turn_silence will be overridden") @@ -230,6 +232,7 @@ async def test_07_keyterms_difficult(): # === DIARIZATION (8-9) === + async def test_08_diarization_basic(): """Test 8: Basic diarization (speaker IDs logged).""" connection_params = AssemblyAIConnectionParams( @@ -258,6 +261,7 @@ async def test_09_diarization_xml(): # === DYNAMIC UPDATES - SINGLE PARAMETER (10-13) === + async def test_10_dynamic_keyterms(): """Test 10: Dynamic keyterms update with difficult names.""" connection_params = AssemblyAIConnectionParams( @@ -265,16 +269,16 @@ async def test_10_dynamic_keyterms(): ) async def dynamic_update(task): - logger.info("\n" + "="*80) + logger.info("\n" + "=" * 80) logger.info("PHASE 1: No keyterms boosting") logger.info(" Try saying: Xiomara, Saoirse, Krzystof") logger.info(" (May not transcribe correctly)") - logger.info("="*80) + logger.info("=" * 80) await asyncio.sleep(15) - logger.info("\n" + "="*80) + logger.info("\n" + "=" * 80) logger.info("🔄 UPDATING: Adding keyterms boost") - logger.info("="*80) + logger.info("=" * 80) await task.queue_frame( STTUpdateSettingsFrame( delta=AssemblyAISTTSettings( @@ -284,11 +288,11 @@ async def test_10_dynamic_keyterms(): ) ) ) - logger.info("\n" + "="*80) + logger.info("\n" + "=" * 80) logger.info("PHASE 2: Keyterms NOW boosted") logger.info(" Say the same names again: Xiomara, Saoirse, Krzystof") logger.info(" (Should transcribe better now!)") - logger.info("="*80) + logger.info("=" * 80) logger.info("🔄 This test has 2 phases:") logger.info(" Phase 1 (15s): No boosting - names may be wrong") @@ -308,29 +312,27 @@ async def test_11_dynamic_silence(): ) async def dynamic_update(task): - logger.info("\n" + "="*80) + logger.info("\n" + "=" * 80) logger.info("PHASE 1: Quick responses (100ms silence threshold)") logger.info(" Speak normally - bot responds quickly") - logger.info("="*80) + logger.info("=" * 80) await asyncio.sleep(10) - logger.info("\n" + "="*80) + logger.info("\n" + "=" * 80) logger.info("🔄 UPDATING: Changing silence from 100ms → 3000ms (3 seconds!)") - logger.info("="*80) + logger.info("=" * 80) await task.queue_frame( STTUpdateSettingsFrame( delta=AssemblyAISTTSettings( - connection_params=AssemblyAIConnectionParams( - min_turn_silence=3000 - ) + connection_params=AssemblyAIConnectionParams(min_turn_silence=3000) ) ) ) - logger.info("\n" + "="*80) + logger.info("\n" + "=" * 80) logger.info("PHASE 2: Patient responses (3 second silence threshold)") logger.info(" Bot will wait 3 full seconds before responding") logger.info(" Try pausing mid-sentence - bot should NOT interrupt") - logger.info("="*80) + logger.info("=" * 80) logger.info("🔄 Dramatic change: 100ms → 3000ms after 10 seconds") await run_bot( @@ -347,16 +349,16 @@ async def test_12_dynamic_prompt(): ) async def dynamic_update(task): - logger.info("\n" + "="*80) + logger.info("\n" + "=" * 80) logger.info("PHASE 1: Default prompt (no keyterms)") logger.info(" Try saying: Xiomara, Saoirse, Krzystof") logger.info(" (May not transcribe correctly)") - logger.info("="*80) + logger.info("=" * 80) await asyncio.sleep(15) - logger.info("\n" + "="*80) + logger.info("\n" + "=" * 80) logger.info("🔄 UPDATING: Adding custom prompt with keyterms") - logger.info("="*80) + logger.info("=" * 80) custom_prompt = """Transcribe verbatim. Rules: 1) Always include punctuation in output. 2) Use period/question mark ONLY for complete sentences. @@ -368,17 +370,15 @@ Pay special attention to these names and transcribe them exactly: Xiomara, Saoir await task.queue_frame( STTUpdateSettingsFrame( delta=AssemblyAISTTSettings( - connection_params=AssemblyAIConnectionParams( - prompt=custom_prompt - ) + connection_params=AssemblyAIConnectionParams(prompt=custom_prompt) ) ) ) - logger.info("\n" + "="*80) + logger.info("\n" + "=" * 80) logger.info("PHASE 2: Prompt with keyterms NOW active") logger.info(" Say the same names again: Xiomara, Saoirse, Krzystof") logger.info(" (Should transcribe better now!)") - logger.info("="*80) + logger.info("=" * 80) logger.info("🔄 This test has 2 phases:") logger.info(" Phase 1 (15s): Default prompt - names may be wrong") @@ -403,9 +403,7 @@ async def test_13_dynamic_clear_keyterms(): await task.queue_frame( STTUpdateSettingsFrame( delta=AssemblyAISTTSettings( - connection_params=AssemblyAIConnectionParams( - keyterms_prompt=[] - ) + connection_params=AssemblyAIConnectionParams(keyterms_prompt=[]) ) ) ) @@ -421,6 +419,7 @@ async def test_13_dynamic_clear_keyterms(): # === DYNAMIC UPDATES - MULTIPLE PARAMETERS (14-15) === + async def test_14_multi_param_update(): """Test 14: Update multiple parameters at once.""" connection_params = AssemblyAIConnectionParams( @@ -464,9 +463,7 @@ async def test_15_complex_sequence(): await task.queue_frame( STTUpdateSettingsFrame( delta=AssemblyAISTTSettings( - connection_params=AssemblyAIConnectionParams( - keyterms_prompt=["Pipecat"] - ) + connection_params=AssemblyAIConnectionParams(keyterms_prompt=["Pipecat"]) ) ) ) @@ -476,9 +473,7 @@ async def test_15_complex_sequence(): await task.queue_frame( STTUpdateSettingsFrame( delta=AssemblyAISTTSettings( - connection_params=AssemblyAIConnectionParams( - min_turn_silence=200 - ) + connection_params=AssemblyAIConnectionParams(min_turn_silence=200) ) ) ) @@ -506,6 +501,7 @@ async def test_15_complex_sequence(): # === MODE COMPARISON (16-17) === + async def test_16_pipecat_mode(): """Test 16: Pipecat mode (VAD + Smart Turn controls turns).""" connection_params = AssemblyAIConnectionParams( @@ -538,6 +534,7 @@ async def test_17_stt_mode(): # === STT MODE TIMING EXPERIMENTS (18-20) === + async def test_18_stt_long_max_short_min(): """Test 18: STT mode - Long max_turn_silence + Short min (5000ms + 100ms).""" connection_params = AssemblyAIConnectionParams( @@ -596,6 +593,7 @@ async def test_20_stt_both_short(): # === EDGE CASES (21-23) === + async def test_21_very_long_silence(): """Test 21: Very long silence threshold (STT mode only).""" connection_params = AssemblyAIConnectionParams( @@ -645,9 +643,9 @@ async def test_23_keyterms_plus_diarization(): def show_menu(): """Display the comprehensive test menu.""" - print("\n" + "="*80) + print("\n" + "=" * 80) print("AssemblyAI u3-rt-pro Comprehensive Test Suite") - print("="*80) + print("=" * 80) print("\n📋 BASIC CONFIGURATION (1-3)") print(" 1. Basic Default (100ms)") print(" 2. Custom Silence (200ms)") @@ -688,7 +686,7 @@ def show_menu(): print(" 23. Keyterms + Diarization Combined") print("\n 0. Exit") - print("\n" + "="*80) + print("\n" + "=" * 80) async def main(): @@ -735,6 +733,7 @@ async def main(): except Exception as e: logger.error(f"Test failed with error: {e}") import traceback + traceback.print_exc() input("\n\nPress Enter to return to menu...") diff --git a/test_assemblyai_u3pro.py b/test_assemblyai_u3pro.py index ace700753..236ab9b50 100644 --- a/test_assemblyai_u3pro.py +++ b/test_assemblyai_u3pro.py @@ -50,6 +50,7 @@ from pipecat.transports.local.audio import LocalAudioTransport, LocalAudioTransp load_dotenv() + # Test configuration class TestConfig: """Centralized test configuration.""" @@ -205,9 +206,7 @@ async def test_custom_min_silence(): logger.info("TEST 2: Custom min_turn_silence") logger.info("=" * 80) - connection_params = AssemblyAIConnectionParams( - speech_model="u3-rt-pro", min_turn_silence=200 - ) + connection_params = AssemblyAIConnectionParams(speech_model="u3-rt-pro", min_turn_silence=200) task, transport = await create_basic_voice_agent(connection_params) @@ -307,9 +306,7 @@ async def test_diarization_no_format(): logger.info("TEST 10: Diarization Enabled (No Formatting)") logger.info("=" * 80) - connection_params = AssemblyAIConnectionParams( - speech_model="u3-rt-pro", speaker_labels=True - ) + connection_params = AssemblyAIConnectionParams(speech_model="u3-rt-pro", speaker_labels=True) task, transport = await create_basic_voice_agent(connection_params) @@ -327,9 +324,7 @@ async def test_diarization_xml_format(): logger.info("TEST 11: Diarization with XML Formatting") logger.info("=" * 80) - connection_params = AssemblyAIConnectionParams( - speech_model="u3-rt-pro", speaker_labels=True - ) + connection_params = AssemblyAIConnectionParams(speech_model="u3-rt-pro", speaker_labels=True) task, transport = await create_basic_voice_agent( connection_params, speaker_format="<{speaker}>{text}" @@ -516,9 +511,7 @@ def main(): "prompt_keyterms_conflict, keyterms, diarization, diarization_xml, " "dynamic_keyterms, dynamic_silence, multi_param, all)", ) - parser.add_argument( - "--interactive", action="store_true", help="Run in interactive mode" - ) + parser.add_argument("--interactive", action="store_true", help="Run in interactive mode") args = parser.parse_args() From 6968d83ccb1a3e9961df693aadaad1cd0e3636ed Mon Sep 17 00:00:00 2001 From: zack Date: Sun, 1 Mar 2026 11:44:51 -0500 Subject: [PATCH 0711/1060] Add changelog entries for PR #3856 --- changelog/3856.added.md | 1 + changelog/3856.changed.md | 1 + changelog/3856.fixed.md | 1 + 3 files changed, 3 insertions(+) create mode 100644 changelog/3856.added.md create mode 100644 changelog/3856.changed.md create mode 100644 changelog/3856.fixed.md diff --git a/changelog/3856.added.md b/changelog/3856.added.md new file mode 100644 index 000000000..0d620a925 --- /dev/null +++ b/changelog/3856.added.md @@ -0,0 +1 @@ +Add AssemblyAI u3-rt-pro model support with STT-controlled turn detection mode diff --git a/changelog/3856.changed.md b/changelog/3856.changed.md new file mode 100644 index 000000000..cb714aeba --- /dev/null +++ b/changelog/3856.changed.md @@ -0,0 +1 @@ +Rename AssemblyAI min_end_of_turn_silence_when_confident parameter to min_turn_silence (old name still supported with deprecation warning) diff --git a/changelog/3856.fixed.md b/changelog/3856.fixed.md new file mode 100644 index 000000000..d9a63a692 --- /dev/null +++ b/changelog/3856.fixed.md @@ -0,0 +1 @@ +Add beta feature warning when using custom prompts with AssemblyAI From 36b9c057309955d241751a8efcdb30897caddd73 Mon Sep 17 00:00:00 2001 From: zack Date: Sun, 1 Mar 2026 11:45:24 -0500 Subject: [PATCH 0712/1060] Fix changelog entries to use proper markdown bullet format --- changelog/3856.added.md | 2 +- changelog/3856.changed.md | 2 +- changelog/3856.fixed.md | 2 +- 3 files changed, 3 insertions(+), 3 deletions(-) diff --git a/changelog/3856.added.md b/changelog/3856.added.md index 0d620a925..95b656058 100644 --- a/changelog/3856.added.md +++ b/changelog/3856.added.md @@ -1 +1 @@ -Add AssemblyAI u3-rt-pro model support with STT-controlled turn detection mode +- Add AssemblyAI u3-rt-pro model support with STT-controlled turn detection mode diff --git a/changelog/3856.changed.md b/changelog/3856.changed.md index cb714aeba..72331c068 100644 --- a/changelog/3856.changed.md +++ b/changelog/3856.changed.md @@ -1 +1 @@ -Rename AssemblyAI min_end_of_turn_silence_when_confident parameter to min_turn_silence (old name still supported with deprecation warning) +- Rename AssemblyAI min_end_of_turn_silence_when_confident parameter to min_turn_silence (old name still supported with deprecation warning) diff --git a/changelog/3856.fixed.md b/changelog/3856.fixed.md index d9a63a692..c31fe8ddf 100644 --- a/changelog/3856.fixed.md +++ b/changelog/3856.fixed.md @@ -1 +1 @@ -Add beta feature warning when using custom prompts with AssemblyAI +- Add beta feature warning when using custom prompts with AssemblyAI From cb7e6127387ee802fcbed9cbaa4a9eabc6bd875f Mon Sep 17 00:00:00 2001 From: zack Date: Sun, 1 Mar 2026 11:51:51 -0500 Subject: [PATCH 0713/1060] Remove test files and testing documentation from PR --- TESTING_CHECKLIST.md | 273 ------------ TESTING_SETUP.md | 310 -------------- test_assemblyai_custom.py | 240 ----------- test_assemblyai_interactive.py | 749 --------------------------------- test_assemblyai_u3pro.py | 582 ------------------------- 5 files changed, 2154 deletions(-) delete mode 100644 TESTING_CHECKLIST.md delete mode 100644 TESTING_SETUP.md delete mode 100755 test_assemblyai_custom.py delete mode 100755 test_assemblyai_interactive.py delete mode 100644 test_assemblyai_u3pro.py diff --git a/TESTING_CHECKLIST.md b/TESTING_CHECKLIST.md deleted file mode 100644 index 8d2d147d4..000000000 --- a/TESTING_CHECKLIST.md +++ /dev/null @@ -1,273 +0,0 @@ -# AssemblyAI u3-rt-pro Testing Checklist - -## Test Environment Setup -- [ ] Install dependencies: `uv sync --group dev --all-extras` -- [ ] Set up `.env` file with API keys -- [ ] Verify LiveKit connection -- [ ] Run basic voice agent test - ---- - -## Feature Testing Checklist - -### ✅ Basic Configuration Tests - -#### Test 1: Default u3-rt-pro Configuration -- [ ] **Setup:** Create service with default params -- [ ] **Expected:** No errors, uses u3-rt-pro model with 100ms min/max -- [ ] **Verify:** Check logs for connection confirmation - -#### Test 2: Custom min_turn_silence -- [ ] **Setup:** Set `min_turn_silence=200` -- [ ] **Expected:** Both min and max set to 200ms -- [ ] **Verify:** Speak short phrases, observe turn detection timing - -#### Test 3: User sets max_turn_silence (Warning Test) -- [ ] **Setup:** Set `max_turn_silence=500` in connection params -- [ ] **Expected:** Warning logged, value overridden to match min -- [ ] **Verify:** Check logs for warning message - ---- - -### ✅ Prompting Tests - -#### Test 4: No Prompt (Default - Recommended) -- [ ] **Setup:** Don't set prompt parameter -- [ ] **Expected:** Uses default prompt, 88% accuracy, no warnings -- [ ] **Verify:** Transcription quality is good - -#### Test 5: Custom Prompt (Warning Test) -- [ ] **Setup:** Set custom prompt in connection params -- [ ] **Expected:** Warning logged about testing without prompt first -- [ ] **Verify:** Check logs for prompt warning - -#### Test 6: Prompt + Keyterms Conflict (Error Test) -- [ ] **Setup:** Set both `prompt` and `keyterms_prompt` at init -- [ ] **Expected:** ValueError raised with helpful error message -- [ ] **Verify:** Service fails to initialize with clear error - ---- - -### ✅ Keyterms Prompting Tests - -#### Test 7: Basic Keyterms at Init -- [ ] **Setup:** Set `keyterms_prompt=["Pipecat", "AssemblyAI", "Universal-3"]` -- [ ] **Expected:** Terms are boosted in recognition -- [ ] **Verify:** Say the boosted terms, check accuracy - -#### Test 8: Empty Keyterms (No Boosting) -- [ ] **Setup:** Set `keyterms_prompt=[]` -- [ ] **Expected:** No boosting, default behavior -- [ ] **Verify:** Normal transcription - ---- - -### ✅ Diarization Tests - -#### Test 9: Diarization Disabled (Default) -- [ ] **Setup:** Don't set `speaker_labels` parameter -- [ ] **Expected:** No speaker info in transcripts -- [ ] **Verify:** TranscriptionFrame.user_id is default user_id - -#### Test 10: Diarization Enabled (No Formatting) -- [ ] **Setup:** Set `speaker_labels=True` -- [ ] **Expected:** Speaker ID in user_id field, plain text -- [ ] **Verify:** Multiple speakers show different IDs (Speaker A, Speaker B) - -#### Test 11: Diarization with XML Formatting -- [ ] **Setup:** Set `speaker_labels=True`, `speaker_format="<{speaker}>{text}"` -- [ ] **Expected:** Text includes speaker tags: `Hello` -- [ ] **Verify:** Formatted text in transcript, speaker ID in user_id - -#### Test 12: Diarization with Colon Prefix -- [ ] **Setup:** Set `speaker_labels=True`, `speaker_format="{speaker}: {text}"` -- [ ] **Expected:** Text includes prefix: `Speaker A: Hello` -- [ ] **Verify:** Formatted text, multiple speakers distinguishable - ---- - -### ✅ Dynamic Updates Tests - -#### Test 13: Dynamic Keyterms Update (Stage 1 → Stage 2) -- [ ] **Setup:** Start with empty keyterms, update mid-conversation -- [ ] **Expected:** New keyterms take effect immediately -- [ ] **Test Steps:** - 1. Start conversation with no keyterms - 2. Send update frame with `keyterms_prompt=["cardiology", "Dr. Smith"]` - 3. Say the new terms -- [ ] **Verify:** Improved recognition after update - -#### Test 14: Clear Keyterms (Reset Context) -- [ ] **Setup:** Start with keyterms, clear them mid-stream -- [ ] **Expected:** Context biasing removed -- [ ] **Test Steps:** - 1. Start with `keyterms_prompt=["test", "words"]` - 2. Send update frame with `keyterms_prompt=[]` -- [ ] **Verify:** No more boosting after clear - -#### Test 15: Dynamic Silence Parameters -- [ ] **Setup:** Update `max_turn_silence` mid-stream -- [ ] **Expected:** Turn detection timing changes -- [ ] **Test Steps:** - 1. Start with default (1200ms) - 2. Update to `max_turn_silence=5000` (for reading numbers) - 3. Pause longer between words - 4. Update back to `max_turn_silence=1200` -- [ ] **Verify:** Longer pauses tolerated when increased - -#### Test 16: Dynamic Prompt Update -- [ ] **Setup:** Update prompt mid-stream -- [ ] **Expected:** New instructions take effect -- [ ] **Test Steps:** - 1. Start with default prompt - 2. Send update with custom prompt -- [ ] **Verify:** Behavior changes according to new prompt - -#### Test 17: Multiple Parameters at Once -- [ ] **Setup:** Update keyterms, max_turn_silence, and min_end_of_turn together -- [ ] **Expected:** All parameters updated in single WebSocket message -- [ ] **Verify:** Check logs for single UpdateConfiguration message - -#### Test 18: Dynamic Update - Prompt + Keyterms Conflict (Error) -- [ ] **Setup:** Try to update both prompt and keyterms_prompt in same update -- [ ] **Expected:** ValueError raised -- [ ] **Verify:** Update fails with clear error message - ---- - -### ✅ Turn Detection Mode Tests - -#### Test 19: Pipecat Mode (vad_force_turn_endpoint=True) - Default -- [ ] **Setup:** Use default settings (Pipecat mode) -- [ ] **Expected:** - - ForceEndpoint sent on VAD stop - - Smart Turn Analyzer makes decisions - - min=max=100ms for u3-rt-pro -- [ ] **Verify:** Fast finals, Smart Turn handles completeness - -#### Test 20: STT Mode (vad_force_turn_endpoint=False) - u3-rt-pro only -- [ ] **Setup:** Set `vad_force_turn_endpoint=False` with u3-rt-pro -- [ ] **Expected:** - - AssemblyAI controls turn endings - - SpeechStarted message triggers interruptions - - UserStarted/StoppedSpeakingFrame emitted -- [ ] **Verify:** Turn detection from AssemblyAI model - -#### Test 21: STT Mode with universal-streaming (Error Test) -- [ ] **Setup:** Set `vad_force_turn_endpoint=False` with universal-streaming -- [ ] **Expected:** ValueError raised (requires u3-rt-pro) -- [ ] **Verify:** Service fails with clear error - ---- - -### ✅ Language Detection Tests (If Multilingual Model) - -#### Test 22: Language Detection Enabled -- [ ] **Setup:** Use `universal-streaming-multilingual` with `language_detection=True` -- [ ] **Expected:** Language codes in transcripts -- [ ] **Verify:** Speak different languages, check language_code field - -#### Test 23: Language Confidence Threshold -- [ ] **Setup:** Enable language detection -- [ ] **Expected:** High confidence (≥0.7) → detected language, Low → fallback to English -- [ ] **Verify:** Check logs for confidence warnings - ---- - -### ✅ Edge Cases & Error Handling - -#### Test 24: WebSocket Disconnect During Update -- [ ] **Setup:** Simulate disconnect, try update -- [ ] **Expected:** Error logged, update queued for reconnection -- [ ] **Verify:** Graceful handling, no crash - -#### Test 25: Invalid Parameter Types -- [ ] **Setup:** Send update with wrong type (e.g., keyterms_prompt as string) -- [ ] **Expected:** Warning logged, parameter skipped -- [ ] **Verify:** Service continues, invalid param ignored - -#### Test 26: Unknown Parameter in Update -- [ ] **Setup:** Send update with unsupported parameter (e.g., `language`) -- [ ] **Expected:** Warning logged about parameter -- [ ] **Verify:** Other valid params still updated - ---- - -### ✅ Integration Tests - -#### Test 27: Full Voice Agent Flow (Multi-Stage) -- [ ] **Setup:** Complete voice agent with stage transitions -- [ ] **Test Steps:** - 1. Greeting stage (general keyterms) - 2. Name collection stage (name keyterms) - 3. Account number stage (number keyterms, longer silence) - 4. Medical info stage (medical keyterms) - 5. Closing stage (goodbye keyterms) -- [ ] **Verify:** Each stage has appropriate keyterms and timing - -#### Test 28: Diarization + Dynamic Updates -- [ ] **Setup:** Enable diarization, update keyterms mid-stream -- [ ] **Expected:** Both features work together -- [ ] **Verify:** Speaker IDs persist, keyterms update correctly - -#### Test 29: Interruption Handling -- [ ] **Setup:** Bot speaking, user interrupts -- [ ] **Expected:** - - Pipecat mode: VAD + Smart Turn handles - - STT mode: SpeechStarted triggers interrupt -- [ ] **Verify:** Bot stops, user speech processed - ---- - -## Testing Results Template - -``` -| Test # | Feature | Status | Notes | -|--------|---------|--------|-------| -| 1 | Default Config | ✅ PASS | | -| 2 | Custom min_silence | ✅ PASS | | -| 3 | max_silence Warning | ✅ PASS | | -| ... | ... | ... | ... | -``` - ---- - -## Expected Outcomes Summary - -### ✅ Should Work (No Errors) -- Default configuration -- Custom min_turn_silence -- Keyterms prompting -- Diarization with/without formatting -- Dynamic updates (one parameter or multiple) -- Pipecat mode turn detection - -### ⚠️ Should Warn (Logs Warning, Continues) -- Custom prompt set at init -- max_turn_silence set (overridden) -- Invalid parameter types in updates -- Language update attempted -- Prompt used with universal-streaming - -### ❌ Should Error (Raises Exception, Stops) -- prompt + keyterms_prompt at init -- prompt + keyterms_prompt in same update -- vad_force_turn_endpoint=False with universal-streaming - ---- - -## Quick Test Commands - -```bash -# Run basic test -python test_assemblyai_u3pro.py --test basic - -# Run specific test -python test_assemblyai_u3pro.py --test diarization - -# Run all tests -python test_assemblyai_u3pro.py --test all - -# Interactive mode -python test_assemblyai_u3pro.py --interactive -``` diff --git a/TESTING_SETUP.md b/TESTING_SETUP.md deleted file mode 100644 index fa1dca462..000000000 --- a/TESTING_SETUP.md +++ /dev/null @@ -1,310 +0,0 @@ -# AssemblyAI u3-rt-pro Testing Setup Guide - -## Quick Start - -### 1. Setup Environment - -```bash -# Copy API keys -cp .env.testing .env - -# Install dependencies -uv sync --group dev --all-extras --no-extra gstreamer --no-extra krisp - -# Make test script executable -chmod +x test_assemblyai_u3pro.py -``` - -### 2. Ensure Audio Devices - -Make sure you have: -- **Microphone** enabled and working -- **Speakers/headphones** connected -- Audio permissions granted (macOS will prompt on first run) - -### 3. Run Tests - -```bash -# Run a specific test -python test_assemblyai_u3pro.py --test basic - -# Interactive mode (choose from menu) -python test_assemblyai_u3pro.py --interactive - -# Run all tests sequentially -python test_assemblyai_u3pro.py --test all -``` - ---- - -## Available Tests - -### Basic Configuration Tests -```bash -# Test 1: Default configuration (min=max=100ms) -python test_assemblyai_u3pro.py --test basic - -# Test 2: Custom min_turn_silence -python test_assemblyai_u3pro.py --test custom_min - -# Test 3: max_turn_silence warning (should be overridden) -python test_assemblyai_u3pro.py --test max_warning -``` - -### Prompting Tests -```bash -# Test 5: Custom prompt warning -python test_assemblyai_u3pro.py --test prompt_warning - -# Test 6: Prompt + keyterms conflict (should error) -python test_assemblyai_u3pro.py --test prompt_keyterms_conflict - -# Test 7: Basic keyterms prompting -python test_assemblyai_u3pro.py --test keyterms -``` - -### Diarization Tests -```bash -# Test 10: Diarization without formatting -python test_assemblyai_u3pro.py --test diarization - -# Test 11: Diarization with XML formatting -python test_assemblyai_u3pro.py --test diarization_xml -``` - -### Dynamic Updates Tests -```bash -# Test 13: Dynamic keyterms (multi-stage) -python test_assemblyai_u3pro.py --test dynamic_keyterms - -# Test 15: Dynamic silence parameters -python test_assemblyai_u3pro.py --test dynamic_silence - -# Test 17: Multiple parameters at once -python test_assemblyai_u3pro.py --test multi_param -``` - ---- - -## Test Execution Flow - -### For Each Test: - -1. **Start the test script** - ```bash - python test_assemblyai_u3pro.py --test - ``` - -2. **Wait for "started" message** indicating the bot is ready - -3. **Speak into your microphone** to test - the bot will: - - Transcribe your speech (you'll see `📝 TRANSCRIPTION:` logs) - - Process through the LLM - - Respond with voice through your speakers - -4. **Observe logs** for: - - ✅ Success indicators - - ⚠️ Warning messages - - ❌ Error messages - - 📝 Transcription output - -5. **Verify expected behavior** against checklist - -6. **Stop test** with Ctrl+C - ---- - -## Expected Test Outcomes - -### Should Pass (✅) -- Basic configuration creates service -- Custom parameters are applied -- Keyterms boost recognition -- Diarization shows speaker IDs -- Dynamic updates work without errors - -### Should Warn (⚠️) -Check logs for warnings: -- "We recommend testing at first with no prompt" -- "max_turn_silence is not used in Pipecat mode" -- "Unknown setting for AssemblyAI STT service" - -### Should Error (❌) -Should raise ValueError and fail to start: -- Both prompt and keyterms_prompt set at init -- Both prompt and keyterms_prompt in same update -- vad_force_turn_endpoint=False with universal-streaming - ---- - -## Debugging Tips - -### Check Logs -```bash -# Run with verbose logging -LOGURU_LEVEL=DEBUG python test_assemblyai_u3pro.py --test -``` - -### Common Issues - -**Issue: "WebSocket connection failed"** -- Check ASSEMBLYAI_API_KEY is correct -- Verify network connection -- Check firewall settings - -**Issue: "No audio input/output"** -- Verify microphone permissions (System Preferences → Security & Privacy → Microphone) -- Check default audio devices in System Preferences → Sound -- Test microphone with another app first -- Make sure no other app is using the microphone - -**Issue: "No transcriptions appearing"** -- Verify microphone permissions -- Check audio levels (speak louder or move closer to mic) -- Speak clearly and wait for VAD to detect -- Check if microphone is muted - -**Issue: "Can't hear bot responses"** -- Check speaker/headphone volume -- Verify correct output device is selected -- Check terminal for TTS errors - -**Issue: "Service fails to start"** -- Check all API keys in .env -- Run `uv sync` to ensure dependencies installed -- Check Python version (3.10+) - ---- - -## Manual Testing Checklist - -After running automated tests, manually verify: - -### ✅ Audio Quality -- [ ] Transcriptions are accurate -- [ ] No distortion or dropouts -- [ ] Latency is acceptable - -### ✅ Turn Detection -- [ ] Bot waits for user to finish speaking -- [ ] No premature cutoffs -- [ ] Handles natural pauses correctly - -### ✅ Interruptions -- [ ] Can interrupt bot mid-sentence -- [ ] Interruption is smooth -- [ ] Bot stops speaking immediately - -### ✅ Diarization (if enabled) -- [ ] Multiple speakers detected correctly -- [ ] Speaker IDs consistent -- [ ] Speaker formatting works - -### ✅ Dynamic Updates -- [ ] Keyterms update without disconnection -- [ ] Turn detection timing changes work -- [ ] Updates logged correctly - ---- - -## Test Results Recording - -### Use this template: - -```markdown -## Test Run: YYYY-MM-DD - -| Test # | Test Name | Status | Notes | -|--------|-----------|--------|-------| -| 1 | basic | ✅ PASS | Transcriptions working | -| 2 | custom_min | ✅ PASS | Turn timing changed | -| 3 | max_warning | ✅ PASS | Warning logged | -| 5 | prompt_warning | ✅ PASS | Warning shown | -| 6 | prompt_keyterms_conflict | ✅ PASS | ValueError raised | -| 7 | keyterms | ✅ PASS | Terms boosted | -| 10 | diarization | ✅ PASS | Speaker IDs correct | -| 11 | diarization_xml | ✅ PASS | XML tags shown | -| 13 | dynamic_keyterms | ✅ PASS | Updates worked | -| 15 | dynamic_silence | ✅ PASS | Timing adjusted | -| 17 | multi_param | ✅ PASS | All params updated | - -### Issues Found: -- None - -### Notes: -- All tests passed successfully -- Latency is excellent (sub-300ms) -- Diarization accuracy is good -``` - ---- - -## Advanced Testing - -### Custom Test Scenarios - -Create custom tests by modifying `test_assemblyai_u3pro.py`: - -```python -async def test_my_custom_scenario(): - """My custom test scenario.""" - logger.info("Testing my specific use case") - - connection_params = AssemblyAIConnectionParams( - speech_model="u3-rt-pro", - # Your custom params here - ) - - task, transport = await create_basic_voice_agent(connection_params) - - # Your test logic here - - runner = PipelineRunner() - await runner.run(task) -``` - -### Stress Testing - -Test with: -- Multiple simultaneous speakers -- Long conversations (30+ minutes) -- Rapid speech -- Heavy accents -- Background noise -- Poor network conditions - ---- - -## Reporting Issues - -When reporting issues, include: - -1. **Test name and number** -2. **Full error message and stack trace** -3. **Relevant log output** (use LOGURU_LEVEL=DEBUG) -4. **Configuration used** (connection_params) -5. **Expected vs actual behavior** -6. **Steps to reproduce** - ---- - -## Next Steps - -After testing: - -1. ✅ Mark completed tests in `TESTING_CHECKLIST.md` -2. 📝 Document any issues found -3. 🐛 Create GitHub issues for bugs -4. ✨ Suggest improvements -5. 📊 Share results with team - ---- - -## Contact - -Questions? Issues? -- Check `TESTING_CHECKLIST.md` for detailed test descriptions -- Review logs with `LOGURU_LEVEL=DEBUG` -- Reach out to the team with your findings - -Happy testing! 🎯 diff --git a/test_assemblyai_custom.py b/test_assemblyai_custom.py deleted file mode 100755 index e8e0a28d2..000000000 --- a/test_assemblyai_custom.py +++ /dev/null @@ -1,240 +0,0 @@ -#!/usr/bin/env python3 -"""Custom AssemblyAI u3-rt-pro Test Script -Easy parameter tweaking for experimentation - -Edit the CONFIGURATION section below to test different settings! -""" - -import asyncio -import os -import sys - -from dotenv import load_dotenv -from loguru import logger - -from pipecat.audio.vad.silero import SileroVADAnalyzer -from pipecat.frames.frames import LLMRunFrame -from pipecat.pipeline.pipeline import Pipeline -from pipecat.pipeline.runner import PipelineRunner -from pipecat.pipeline.task import PipelineParams, PipelineTask -from pipecat.processors.aggregators.llm_context import LLMContext -from pipecat.processors.aggregators.llm_response_universal import ( - LLMContextAggregatorPair, - LLMUserAggregatorParams, -) -from pipecat.services.assemblyai.models import AssemblyAIConnectionParams -from pipecat.services.assemblyai.stt import AssemblyAISTTService -from pipecat.services.cartesia.tts import CartesiaTTSService -from pipecat.services.openai.llm import OpenAILLMService -from pipecat.transports.local.audio import LocalAudioTransport, LocalAudioTransportParams - -load_dotenv(override=True) - -# ============================================================================ -# CONFIGURATION -# ============================================================================ - -# Log Level: "DEBUG" for detailed logs, "INFO" for normal operation -LOG_LEVEL = "INFO" - -# ============================================================================ -# BOT IMPLEMENTATION -# ============================================================================ - - -async def main(): - """Run the custom test bot with your configured parameters.""" - # Setup logging - logger.remove(0) - logger.add(sys.stderr, level=LOG_LEVEL) - - logger.info("=" * 80) - logger.info("AssemblyAI u3-rt-pro Custom Test") - logger.info("=" * 80) - logger.info("Starting bot... Speak after you hear the greeting!") - logger.info("=" * 80) - - # Create local audio transport - transport = LocalAudioTransport( - LocalAudioTransportParams( - audio_in_enabled=True, - audio_out_enabled=True, - ) - ) - - # ======================================================================== - # EDIT PARAMETERS HERE - # ======================================================================== - - # Build connection params - connection_params = AssemblyAIConnectionParams( - # ==================================================================== - # Model Selection - # ==================================================================== - speech_model="u3-rt-pro", - # speech_model="universal-streaming-english", - # speech_model="universal-streaming-multilingual", - # ==================================================================== - # Turn Detection Timing - # ==================================================================== - # Minimum silence when confident about end of turn (milliseconds) - # Default: 100ms | Higher = more patient | Lower = faster responses - # Only used in Pipecat mode (vad_force_turn_endpoint=True) - min_turn_silence=100000, - # min_turn_silence=200, - # min_turn_silence=300, - # Maximum turn silence (milliseconds) - # WARNING: In Pipecat mode (vad_force_turn_endpoint=True), this is - # automatically set equal to min_turn_silence - # to avoid double turn detection. Only used as-is in STT mode. - max_turn_silence=500, - # End of turn confidence threshold (0.0 to 1.0) - # Higher = requires more confidence before ending turn - # end_of_turn_confidence_threshold=0.8, - # ==================================================================== - # Prompting & Boosting - # ==================================================================== - # Custom Prompt (WARNING: test carefully, default is optimized!) - # None = Use AssemblyAI's optimized default (recommended for 88% accuracy) - prompt=None, - # prompt="Transcribe speech with focus on technical terms.", - # prompt="Context: Medical conversation. Transcribe accurately.", - # Keyterms Prompting (boosts recognition for specific words) - # NOTE: Cannot use both prompt and keyterms_prompt! - keyterms_prompt=None, - # keyterms_prompt=["Pipecat", "AssemblyAI", "OpenAI", "Cartesia"], - # keyterms_prompt=["Python", "JavaScript", "TypeScript", "API"], - # ==================================================================== - # Diarization (Speaker Identification) - # ==================================================================== - # Enable speaker labels (identifies different speakers) - speaker_labels=None, # None or True - # speaker_labels=True, - # ==================================================================== - # Audio Configuration - # ==================================================================== - # Audio sample rate (Hz) - # sample_rate=16000, - # sample_rate=8000, - # Audio encoding format - # encoding="pcm_s16le", # Default: 16-bit PCM - # encoding="pcm_mulaw", # μ-law encoding (telephony) - # ==================================================================== - # Other Options - # ==================================================================== - # Format transcript turns (applies formatting rules) - # format_turns=True, # Default - # format_turns=False, - # Language detection (only for universal-streaming-multilingual) - # language_detection=True, - ) - - # Log connection parameters for debugging - logger.info("=" * 80) - logger.info("CONNECTION PARAMETERS:") - logger.info(f" speech_model: {connection_params.speech_model}") - logger.info(f" min_turn_silence: {connection_params.min_turn_silence}") - logger.info(f" max_turn_silence: {connection_params.max_turn_silence}") - logger.info(f" sample_rate: {connection_params.sample_rate}") - logger.info(f" encoding: {connection_params.encoding}") - logger.info(f" prompt: {connection_params.prompt}") - logger.info(f" keyterms_prompt: {connection_params.keyterms_prompt}") - logger.info(f" speaker_labels: {connection_params.speaker_labels}") - logger.info(f" format_turns: {connection_params.format_turns}") - logger.info( - f" end_of_turn_confidence_threshold: {connection_params.end_of_turn_confidence_threshold}" - ) - logger.info(f" language_detection: {connection_params.language_detection}") - logger.info("=" * 80) - - # AssemblyAI Speech-to-Text Service - stt = AssemblyAISTTService( - api_key=os.getenv("ASSEMBLYAI_API_KEY"), - connection_params=connection_params, - # Turn Detection Mode - # True = Pipecat mode (VAD + Smart Turn controls turns) - # False = STT mode (u3-rt-pro model controls turns) - vad_force_turn_endpoint=True, - # Speaker Formatting (only used if speaker_labels=True) - # None = Just log speaker IDs, don't modify transcript - speaker_format=None, - # speaker_format="{text}", - # speaker_format="{speaker}: {text}", - # speaker_format="[{speaker}] {text}", - # Additional available parameters (uncomment to use): - # should_interrupt=True, # Only for STT mode - ) - - # ======================================================================== - - # Text-to-Speech - tts = CartesiaTTSService( - api_key=os.getenv("CARTESIA_API_KEY"), - voice_id="a0e99841-438c-4a64-b679-ae501e7d6091", # Conversational English - ) - - # LLM - llm = OpenAILLMService( - api_key=os.getenv("OPENAI_API_KEY"), - model="gpt-4", - ) - - # Conversation context - messages = [ - { - "role": "system", - "content": ( - "You are a helpful voice assistant testing the AssemblyAI u3-rt-pro model. " - "Keep responses very brief (1-2 sentences). " - "Start by introducing yourself briefly and asking the user to speak." - ), - }, - ] - - context = LLMContext(messages) - - # Configure aggregator based on mode - # In STT mode, don't use VAD (model handles turn detection) - # In Pipecat mode, use VAD + Smart Turn - vad_force_turn_endpoint = True # Must match the value in stt configuration above - user_params = None - if vad_force_turn_endpoint: - user_params = LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()) - - user_aggregator, assistant_aggregator = LLMContextAggregatorPair( - context, - user_params=user_params, - ) - - # Pipeline - pipeline = Pipeline( - [ - transport.input(), - stt, - user_aggregator, - llm, - tts, - transport.output(), - assistant_aggregator, - ] - ) - - # Task - task = PipelineTask( - pipeline, - params=PipelineParams( - enable_metrics=True, - enable_usage_metrics=True, - ), - ) - - # Start the conversation - await task.queue_frames([LLMRunFrame()]) - - # Run - runner = PipelineRunner() - await runner.run(task) - - -if __name__ == "__main__": - asyncio.run(main()) diff --git a/test_assemblyai_interactive.py b/test_assemblyai_interactive.py deleted file mode 100755 index c5ec0b429..000000000 --- a/test_assemblyai_interactive.py +++ /dev/null @@ -1,749 +0,0 @@ -#!/usr/bin/env python3 -"""Interactive AssemblyAI u3-rt-pro Comprehensive Test Suite - -Tests all features with detailed scenarios: -- Basic configuration variations -- Prompting and keyterms with difficult names -- Diarization -- Dynamic parameter updates (single and multiple) -- Mode comparisons -- STT mode timing experiments (testing silence parameters) -- Edge cases - -Usage: - python test_assemblyai_interactive.py -""" - -import asyncio -import os -import sys -from typing import Optional - -from dotenv import load_dotenv -from loguru import logger - -from pipecat.audio.vad.silero import SileroVADAnalyzer -from pipecat.frames.frames import LLMRunFrame, STTUpdateSettingsFrame -from pipecat.pipeline.pipeline import Pipeline -from pipecat.pipeline.runner import PipelineRunner -from pipecat.pipeline.task import PipelineParams, PipelineTask -from pipecat.processors.aggregators.llm_context import LLMContext -from pipecat.processors.aggregators.llm_response_universal import ( - LLMContextAggregatorPair, - LLMUserAggregatorParams, -) -from pipecat.services.assemblyai.models import AssemblyAIConnectionParams -from pipecat.services.assemblyai.stt import AssemblyAISTTService, AssemblyAISTTSettings -from pipecat.services.cartesia.tts import CartesiaTTSService -from pipecat.services.openai.llm import OpenAILLMService -from pipecat.transports.local.audio import LocalAudioTransport, LocalAudioTransportParams - -load_dotenv(override=True) - -logger.remove(0) -logger.add(sys.stderr, level="INFO") - - -async def run_bot( - connection_params: AssemblyAIConnectionParams, - test_name: str, - vad_force_turn_endpoint: bool = True, - speaker_format: Optional[str] = None, - test_dynamic_updates: Optional[callable] = None, -): - """Run the voice bot with specified configuration.""" - logger.info("=" * 80) - logger.info(f"TEST: {test_name}") - logger.info("=" * 80) - logger.info("Starting bot... Speak into your microphone after you hear the greeting!") - logger.info("=" * 80) - - # Create local audio transport - transport = LocalAudioTransport( - LocalAudioTransportParams( - audio_in_enabled=True, - audio_out_enabled=True, - ) - ) - - # AssemblyAI Speech-to-Text - stt = AssemblyAISTTService( - api_key=os.getenv("ASSEMBLYAI_API_KEY"), - connection_params=connection_params, - vad_force_turn_endpoint=vad_force_turn_endpoint, - speaker_format=speaker_format, - ) - - # Text-to-Speech - tts = CartesiaTTSService( - api_key=os.getenv("CARTESIA_API_KEY"), - voice_id="a0e99841-438c-4a64-b679-ae501e7d6091", - ) - - # LLM - llm = OpenAILLMService( - api_key=os.getenv("OPENAI_API_KEY"), - model="gpt-4", - ) - - # Conversation context - messages = [ - { - "role": "system", - "content": ( - "You are a helpful voice assistant testing the AssemblyAI u3-rt-pro model. " - "Keep responses very brief (1-2 sentences). " - "Start by introducing yourself briefly and asking the user to speak." - ), - }, - ] - - context = LLMContext(messages) - - # Configure aggregator based on mode - user_params = None - if vad_force_turn_endpoint: - user_params = LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()) - - user_aggregator, assistant_aggregator = LLMContextAggregatorPair( - context, - user_params=user_params, - ) - - # Pipeline - pipeline = Pipeline( - [ - transport.input(), - stt, - user_aggregator, - llm, - tts, - transport.output(), - assistant_aggregator, - ] - ) - - # Task - task = PipelineTask( - pipeline, - params=PipelineParams( - enable_metrics=True, - enable_usage_metrics=True, - ), - ) - - # Handle dynamic updates if provided - if test_dynamic_updates: - asyncio.create_task(test_dynamic_updates(task)) - - # Start the conversation - await task.queue_frames([LLMRunFrame()]) - - # Run - runner = PipelineRunner() - await runner.run(task) - - -# ============================================================================ -# Test Configurations -# ============================================================================ - -# === BASIC CONFIGURATION (1-3) === - - -async def test_01_basic_100ms(): - """Test 1: Basic default configuration (100ms).""" - connection_params = AssemblyAIConnectionParams( - speech_model="u3-rt-pro", - min_turn_silence=100, - ) - await run_bot(connection_params, "Basic Default Configuration (100ms)") - - -async def test_02_custom_200ms(): - """Test 2: Custom min_end_of_turn_silence (200ms).""" - connection_params = AssemblyAIConnectionParams( - speech_model="u3-rt-pro", - min_turn_silence=200, - ) - await run_bot(connection_params, "Custom Turn Silence (200ms)") - - -async def test_03_custom_500ms(): - """Test 3: Longer silence threshold (500ms).""" - connection_params = AssemblyAIConnectionParams( - speech_model="u3-rt-pro", - min_turn_silence=500, - ) - await run_bot(connection_params, "Longer Turn Silence (500ms)") - - -# === PROMPTING & WARNINGS (4-7) === - - -async def test_04_max_warning(): - """Test 4: max_turn_silence warning (should be overridden).""" - logger.warning("⚠️ EXPECT WARNING: max_turn_silence will be overridden") - connection_params = AssemblyAIConnectionParams( - speech_model="u3-rt-pro", - max_turn_silence=500, - ) - await run_bot(connection_params, "max_turn_silence Override Warning") - - -async def test_05_prompt_warning(): - """Test 5: Custom prompt warning.""" - logger.warning("⚠️ EXPECT WARNING: Custom prompts should be tested carefully") - connection_params = AssemblyAIConnectionParams( - speech_model="u3-rt-pro", - prompt="Transcribe speech accurately with proper punctuation.", - ) - await run_bot(connection_params, "Custom Prompt Warning Test") - - -async def test_06_prompt_keyterms_conflict(): - """Test 6: Prompt + keyterms conflict (should error).""" - logger.error("❌ EXPECT ERROR: Cannot use both prompt and keyterms_prompt") - try: - connection_params = AssemblyAIConnectionParams( - speech_model="u3-rt-pro", - prompt="Custom prompt", - keyterms_prompt=["test"], - ) - await run_bot(connection_params, "Prompt + Keyterms Conflict (ERROR)") - except ValueError as e: - logger.error(f"✅ EXPECTED ERROR: {e}") - input("\nPress Enter to continue...") - return - - -async def test_07_keyterms_difficult(): - """Test 7: Keyterms with difficult/unusual names.""" - # Use names that STT wouldn't normally get right - keyterms = ["Xiomara", "Saoirse", "Krzystof", "Nguyen", "Pipecat", "AssemblyAI"] - connection_params = AssemblyAIConnectionParams( - speech_model="u3-rt-pro", - keyterms_prompt=keyterms, - ) - logger.info("🎯 Boosted terms: Xiomara, Saoirse, Krzystof, Nguyen, Pipecat, AssemblyAI") - logger.info(" Try saying these difficult names to test boosting!") - await run_bot(connection_params, "Keyterms with Difficult Names") - - -# === DIARIZATION (8-9) === - - -async def test_08_diarization_basic(): - """Test 8: Basic diarization (speaker IDs logged).""" - connection_params = AssemblyAIConnectionParams( - speech_model="u3-rt-pro", - speaker_labels=True, - ) - logger.info("🎤 Diarization enabled - speaker IDs will be logged") - logger.info(" Try having multiple people speak!") - await run_bot(connection_params, "Diarization - Basic") - - -async def test_09_diarization_xml(): - """Test 9: Diarization with XML formatting.""" - connection_params = AssemblyAIConnectionParams( - speech_model="u3-rt-pro", - speaker_labels=True, - ) - logger.info("🎤 Diarization with XML tags") - logger.info(" Transcripts will include text") - await run_bot( - connection_params, - "Diarization - XML Formatting", - speaker_format="{text}", - ) - - -# === DYNAMIC UPDATES - SINGLE PARAMETER (10-13) === - - -async def test_10_dynamic_keyterms(): - """Test 10: Dynamic keyterms update with difficult names.""" - connection_params = AssemblyAIConnectionParams( - speech_model="u3-rt-pro", - ) - - async def dynamic_update(task): - logger.info("\n" + "=" * 80) - logger.info("PHASE 1: No keyterms boosting") - logger.info(" Try saying: Xiomara, Saoirse, Krzystof") - logger.info(" (May not transcribe correctly)") - logger.info("=" * 80) - await asyncio.sleep(15) - - logger.info("\n" + "=" * 80) - logger.info("🔄 UPDATING: Adding keyterms boost") - logger.info("=" * 80) - await task.queue_frame( - STTUpdateSettingsFrame( - delta=AssemblyAISTTSettings( - connection_params=AssemblyAIConnectionParams( - keyterms_prompt=["Xiomara", "Saoirse", "Krzystof", "Nguyen"] - ) - ) - ) - ) - logger.info("\n" + "=" * 80) - logger.info("PHASE 2: Keyterms NOW boosted") - logger.info(" Say the same names again: Xiomara, Saoirse, Krzystof") - logger.info(" (Should transcribe better now!)") - logger.info("=" * 80) - - logger.info("🔄 This test has 2 phases:") - logger.info(" Phase 1 (15s): No boosting - names may be wrong") - logger.info(" Phase 2: Keyterms added - names should improve") - await run_bot( - connection_params, - "Dynamic Keyterms Update (Before/After)", - test_dynamic_updates=dynamic_update, - ) - - -async def test_11_dynamic_silence(): - """Test 11: Dynamic silence parameter update (dramatic change).""" - connection_params = AssemblyAIConnectionParams( - speech_model="u3-rt-pro", - min_turn_silence=100, - ) - - async def dynamic_update(task): - logger.info("\n" + "=" * 80) - logger.info("PHASE 1: Quick responses (100ms silence threshold)") - logger.info(" Speak normally - bot responds quickly") - logger.info("=" * 80) - await asyncio.sleep(10) - - logger.info("\n" + "=" * 80) - logger.info("🔄 UPDATING: Changing silence from 100ms → 3000ms (3 seconds!)") - logger.info("=" * 80) - await task.queue_frame( - STTUpdateSettingsFrame( - delta=AssemblyAISTTSettings( - connection_params=AssemblyAIConnectionParams(min_turn_silence=3000) - ) - ) - ) - logger.info("\n" + "=" * 80) - logger.info("PHASE 2: Patient responses (3 second silence threshold)") - logger.info(" Bot will wait 3 full seconds before responding") - logger.info(" Try pausing mid-sentence - bot should NOT interrupt") - logger.info("=" * 80) - - logger.info("🔄 Dramatic change: 100ms → 3000ms after 10 seconds") - await run_bot( - connection_params, - "Dynamic Silence Update (100ms → 3s)", - test_dynamic_updates=dynamic_update, - ) - - -async def test_12_dynamic_prompt(): - """Test 12: Dynamic prompt update with keyterms in prompt.""" - connection_params = AssemblyAIConnectionParams( - speech_model="u3-rt-pro", - ) - - async def dynamic_update(task): - logger.info("\n" + "=" * 80) - logger.info("PHASE 1: Default prompt (no keyterms)") - logger.info(" Try saying: Xiomara, Saoirse, Krzystof") - logger.info(" (May not transcribe correctly)") - logger.info("=" * 80) - await asyncio.sleep(15) - - logger.info("\n" + "=" * 80) - logger.info("🔄 UPDATING: Adding custom prompt with keyterms") - logger.info("=" * 80) - custom_prompt = """Transcribe verbatim. Rules: -1) Always include punctuation in output. -2) Use period/question mark ONLY for complete sentences. -3) Use comma for mid-sentence pauses. -4) Use no punctuation for incomplete trailing speech. -5) Filler words (um, uh, so, like) indicate speaker will continue. - -Pay special attention to these names and transcribe them exactly: Xiomara, Saoirse, Krzystof, Nguyen.""" - await task.queue_frame( - STTUpdateSettingsFrame( - delta=AssemblyAISTTSettings( - connection_params=AssemblyAIConnectionParams(prompt=custom_prompt) - ) - ) - ) - logger.info("\n" + "=" * 80) - logger.info("PHASE 2: Prompt with keyterms NOW active") - logger.info(" Say the same names again: Xiomara, Saoirse, Krzystof") - logger.info(" (Should transcribe better now!)") - logger.info("=" * 80) - - logger.info("🔄 This test has 2 phases:") - logger.info(" Phase 1 (15s): Default prompt - names may be wrong") - logger.info(" Phase 2: Custom prompt with keyterms - names should improve") - await run_bot( - connection_params, - "Dynamic Prompt Update (with keyterms)", - test_dynamic_updates=dynamic_update, - ) - - -async def test_13_dynamic_clear_keyterms(): - """Test 13: Clear keyterms dynamically.""" - connection_params = AssemblyAIConnectionParams( - speech_model="u3-rt-pro", - keyterms_prompt=["Pipecat", "AssemblyAI"], - ) - - async def dynamic_update(task): - await asyncio.sleep(10) - logger.info("🔄 UPDATING: Clearing keyterms (empty array)") - await task.queue_frame( - STTUpdateSettingsFrame( - delta=AssemblyAISTTSettings( - connection_params=AssemblyAIConnectionParams(keyterms_prompt=[]) - ) - ) - ) - - logger.info("🎯 Initial: Pipecat, AssemblyAI boosted") - logger.info("🔄 After 10s: Keyterms will be cleared") - await run_bot( - connection_params, - "Dynamic Clear Keyterms", - test_dynamic_updates=dynamic_update, - ) - - -# === DYNAMIC UPDATES - MULTIPLE PARAMETERS (14-15) === - - -async def test_14_multi_param_update(): - """Test 14: Update multiple parameters at once.""" - connection_params = AssemblyAIConnectionParams( - speech_model="u3-rt-pro", - min_turn_silence=100, - ) - - async def dynamic_update(task): - await asyncio.sleep(10) - logger.info("🔄 UPDATING MULTIPLE: keyterms + silence") - await task.queue_frame( - STTUpdateSettingsFrame( - delta=AssemblyAISTTSettings( - connection_params=AssemblyAIConnectionParams( - keyterms_prompt=["Xiomara", "Pipecat"], - min_turn_silence=250, - ) - ) - ) - ) - - logger.info("🔄 After 10s: Will update BOTH keyterms AND silence threshold") - await run_bot( - connection_params, - "Multiple Parameter Update", - test_dynamic_updates=dynamic_update, - ) - - -async def test_15_complex_sequence(): - """Test 15: Complex multi-stage update sequence.""" - connection_params = AssemblyAIConnectionParams( - speech_model="u3-rt-pro", - ) - - async def dynamic_update(task): - logger.info("Stage 1: Initial (10s)") - await asyncio.sleep(10) - - logger.info("🔄 Stage 2: Add keyterms") - await task.queue_frame( - STTUpdateSettingsFrame( - delta=AssemblyAISTTSettings( - connection_params=AssemblyAIConnectionParams(keyterms_prompt=["Pipecat"]) - ) - ) - ) - await asyncio.sleep(10) - - logger.info("🔄 Stage 3: Change silence") - await task.queue_frame( - STTUpdateSettingsFrame( - delta=AssemblyAISTTSettings( - connection_params=AssemblyAIConnectionParams(min_turn_silence=200) - ) - ) - ) - await asyncio.sleep(10) - - logger.info("🔄 Stage 4: Update both") - await task.queue_frame( - STTUpdateSettingsFrame( - delta=AssemblyAISTTSettings( - connection_params=AssemblyAIConnectionParams( - keyterms_prompt=["AssemblyAI", "OpenAI"], - min_turn_silence=150, - ) - ) - ) - ) - - logger.info("🔄 Multi-stage: 4 configuration changes over 30 seconds") - await run_bot( - connection_params, - "Complex Update Sequence (4 stages)", - test_dynamic_updates=dynamic_update, - ) - - -# === MODE COMPARISON (16-17) === - - -async def test_16_pipecat_mode(): - """Test 16: Pipecat mode (VAD + Smart Turn controls turns).""" - connection_params = AssemblyAIConnectionParams( - speech_model="u3-rt-pro", - min_turn_silence=100, - ) - logger.info("🎯 Pipecat Mode: VAD + Smart Turn control turn detection") - logger.info(" Your min_end_of_turn_silence is sent but ForceEndpoint overrides it") - await run_bot( - connection_params, - "Pipecat Mode (VAD + Smart Turn)", - vad_force_turn_endpoint=True, - ) - - -async def test_17_stt_mode(): - """Test 17: STT mode (model controls turns).""" - connection_params = AssemblyAIConnectionParams( - speech_model="u3-rt-pro", - min_turn_silence=100, - ) - logger.info("🎯 STT Mode: u3-rt-pro model controls turn detection") - logger.info(" No ForceEndpoint - parameters are respected") - await run_bot( - connection_params, - "STT Mode (Model Turn Detection)", - vad_force_turn_endpoint=False, - ) - - -# === STT MODE TIMING EXPERIMENTS (18-20) === - - -async def test_18_stt_long_max_short_min(): - """Test 18: STT mode - Long max_turn_silence + Short min (5000ms + 100ms).""" - connection_params = AssemblyAIConnectionParams( - speech_model="u3-rt-pro", - min_turn_silence=100, # Short - quick confident turns - max_turn_silence=5000, # Long - allows pauses up to 5 seconds - ) - logger.info("🎯 STT Mode: Testing max/min parameter interaction") - logger.info(" min_turn_silence: 100ms (quick when confident)") - logger.info(" max_turn_silence: 5000ms (allows up to 5 second pauses)") - logger.info(" Try: Quick sentences (should respond fast) + Long pauses mid-thought") - await run_bot( - connection_params, - "STT: Long Max (5s) + Short Min (100ms)", - vad_force_turn_endpoint=False, - ) - - -async def test_19_stt_long_min(): - """Test 19: STT mode - Long min_turn_silence (3000ms).""" - connection_params = AssemblyAIConnectionParams( - speech_model="u3-rt-pro", - min_turn_silence=3000, # 3 seconds - max_turn_silence=5000, # 5 seconds - ) - logger.info("🎯 STT Mode: Testing long minimum silence requirement") - logger.info(" min_turn_silence: 3000ms") - logger.info(" max_turn_silence: 5000ms") - logger.info(" Bot will wait 3 full seconds of silence before responding!") - logger.info(" Try: Speaking with short pauses - bot should NOT interrupt") - await run_bot( - connection_params, - "STT: Long Min (3s)", - vad_force_turn_endpoint=False, - ) - - -async def test_20_stt_both_short(): - """Test 20: STT mode - Both short (max=300ms, min=100ms).""" - connection_params = AssemblyAIConnectionParams( - speech_model="u3-rt-pro", - min_turn_silence=100, # 100ms - max_turn_silence=300, # 300ms - ) - logger.info("🎯 STT Mode: Testing aggressive/quick response timing") - logger.info(" min_turn_silence: 100ms") - logger.info(" max_turn_silence: 300ms") - logger.info(" Bot will respond VERY quickly to any pause!") - logger.info(" Try: Speaking with natural pauses - expect quick responses") - await run_bot( - connection_params, - "STT: Both Short (300ms/100ms)", - vad_force_turn_endpoint=False, - ) - - -# === EDGE CASES (21-23) === - - -async def test_21_very_long_silence(): - """Test 21: Very long silence threshold (STT mode only).""" - connection_params = AssemblyAIConnectionParams( - speech_model="u3-rt-pro", - min_turn_silence=10000, # 10 seconds - ) - logger.warning("⚠️ STT Mode with 10 second silence threshold") - logger.info(" Bot will wait 10 seconds of silence before responding!") - await run_bot( - connection_params, - "Very Long Silence (10s) - STT Mode", - vad_force_turn_endpoint=False, - ) - - -async def test_22_very_short_silence(): - """Test 22: Very short silence threshold (50ms).""" - connection_params = AssemblyAIConnectionParams( - speech_model="u3-rt-pro", - min_turn_silence=50, - ) - logger.info("⚡ Very short silence threshold (50ms)") - logger.info(" Bot will respond very quickly!") - await run_bot(connection_params, "Very Short Silence (50ms)") - - -async def test_23_keyterms_plus_diarization(): - """Test 23: Keyterms + Diarization combined.""" - connection_params = AssemblyAIConnectionParams( - speech_model="u3-rt-pro", - keyterms_prompt=["Xiomara", "Saoirse", "Pipecat"], - speaker_labels=True, - ) - logger.info("🎯 Keyterms + 🎤 Diarization both enabled") - logger.info(" Try multiple speakers saying difficult names!") - await run_bot( - connection_params, - "Keyterms + Diarization Combined", - speaker_format="[{speaker}] {text}", - ) - - -# ============================================================================ -# Interactive Menu -# ============================================================================ - - -def show_menu(): - """Display the comprehensive test menu.""" - print("\n" + "=" * 80) - print("AssemblyAI u3-rt-pro Comprehensive Test Suite") - print("=" * 80) - print("\n📋 BASIC CONFIGURATION (1-3)") - print(" 1. Basic Default (100ms)") - print(" 2. Custom Silence (200ms)") - print(" 3. Longer Silence (500ms)") - - print("\n⚠️ PROMPTING & WARNINGS (4-7)") - print(" 4. max_turn_silence Warning") - print(" 5. Custom Prompt Warning") - print(" 6. Prompt + Keyterms Conflict (ERROR)") - print(" 7. Keyterms with Difficult Names") - - print("\n🎤 DIARIZATION (8-9)") - print(" 8. Diarization - Basic") - print(" 9. Diarization - XML Formatting") - - print("\n🔄 DYNAMIC UPDATES - SINGLE (10-13)") - print(" 10. Dynamic Keyterms (Before/After with difficult names)") - print(" 11. Dynamic Silence (100ms → 3s DRAMATIC)") - print(" 12. Dynamic Prompt with Keyterms (Before/After)") - print(" 13. Dynamic Clear Keyterms") - - print("\n🔄 DYNAMIC UPDATES - MULTIPLE (14-15)") - print(" 14. Multiple Parameters at Once") - print(" 15. Complex Update Sequence (4 stages)") - - print("\n⚖️ MODE COMPARISON (16-17)") - print(" 16. Pipecat Mode (VAD + Smart Turn)") - print(" 17. STT Mode (Model Turn Detection)") - - print("\n⏱️ STT MODE TIMING EXPERIMENTS (18-20)") - print(" 18. STT: Long Max (5s) + Short Min (100ms)") - print(" 19. STT: Long Min (3s)") - print(" 20. STT: Both Short (300ms/100ms)") - - print("\n🎯 EDGE CASES (21-23)") - print(" 21. Very Long Silence (10s - STT Mode)") - print(" 22. Very Short Silence (50ms)") - print(" 23. Keyterms + Diarization Combined") - - print("\n 0. Exit") - print("\n" + "=" * 80) - - -async def main(): - """Main interactive menu.""" - tests = { - "1": test_01_basic_100ms, - "2": test_02_custom_200ms, - "3": test_03_custom_500ms, - "4": test_04_max_warning, - "5": test_05_prompt_warning, - "6": test_06_prompt_keyterms_conflict, - "7": test_07_keyterms_difficult, - "8": test_08_diarization_basic, - "9": test_09_diarization_xml, - "10": test_10_dynamic_keyterms, - "11": test_11_dynamic_silence, - "12": test_12_dynamic_prompt, - "13": test_13_dynamic_clear_keyterms, - "14": test_14_multi_param_update, - "15": test_15_complex_sequence, - "16": test_16_pipecat_mode, - "17": test_17_stt_mode, - "18": test_18_stt_long_max_short_min, - "19": test_19_stt_long_min, - "20": test_20_stt_both_short, - "21": test_21_very_long_silence, - "22": test_22_very_short_silence, - "23": test_23_keyterms_plus_diarization, - } - - while True: - show_menu() - choice = input("Enter test number (or 0 to exit): ").strip() - - if choice == "0": - print("\n👋 Goodbye!") - break - - if choice in tests: - try: - await tests[choice]() - except KeyboardInterrupt: - print("\n\n⚠️ Test interrupted by user") - except Exception as e: - logger.error(f"Test failed with error: {e}") - import traceback - - traceback.print_exc() - - input("\n\nPress Enter to return to menu...") - else: - print(f"\n❌ Invalid choice: {choice}") - input("Press Enter to continue...") - - -if __name__ == "__main__": - try: - asyncio.run(main()) - except KeyboardInterrupt: - print("\n\n👋 Goodbye!") diff --git a/test_assemblyai_u3pro.py b/test_assemblyai_u3pro.py deleted file mode 100644 index 236ab9b50..000000000 --- a/test_assemblyai_u3pro.py +++ /dev/null @@ -1,582 +0,0 @@ -#!/usr/bin/env python3 -"""AssemblyAI u3-rt-pro Comprehensive Test Script - -Tests all features: -- Basic configuration -- Prompting and keyterms -- Diarization -- Dynamic updates -- Turn detection modes - -Usage: - python test_assemblyai_u3pro.py --test - python test_assemblyai_u3pro.py --interactive -""" - -import argparse -import asyncio -import os -import sys -from typing import List - -from dotenv import load_dotenv -from loguru import logger - -# Add src to path -sys.path.insert(0, os.path.join(os.path.dirname(__file__), "src")) - -from pipecat.audio.vad.silero import SileroVADAnalyzer -from pipecat.frames.frames import ( - EndFrame, - Frame, - LLMRunFrame, - STTUpdateSettingsFrame, - TranscriptionFrame, -) -from pipecat.pipeline.pipeline import Pipeline -from pipecat.pipeline.runner import PipelineRunner -from pipecat.pipeline.task import PipelineTask -from pipecat.processors.aggregators.llm_context import LLMContext -from pipecat.processors.aggregators.llm_response_universal import ( - LLMContextAggregatorPair, - LLMUserAggregatorParams, -) -from pipecat.processors.frame_processor import FrameDirection, FrameProcessor -from pipecat.services.assemblyai.models import AssemblyAIConnectionParams -from pipecat.services.assemblyai.stt import AssemblyAISTTService -from pipecat.services.cartesia.tts import CartesiaTTSService -from pipecat.services.openai.llm import OpenAILLMService -from pipecat.transports.local.audio import LocalAudioTransport, LocalAudioTransportParams - -load_dotenv() - - -# Test configuration -class TestConfig: - """Centralized test configuration.""" - - ASSEMBLYAI_API_KEY = os.getenv("ASSEMBLYAI_API_KEY") - OPENAI_API_KEY = os.getenv("OPENAI_API_KEY") - CARTESIA_API_KEY = os.getenv("CARTESIA_API_KEY") - - @classmethod - def validate(cls): - """Validate all required API keys are set.""" - missing = [] - if not cls.ASSEMBLYAI_API_KEY: - missing.append("ASSEMBLYAI_API_KEY") - if not cls.OPENAI_API_KEY: - missing.append("OPENAI_API_KEY") - if not cls.CARTESIA_API_KEY: - missing.append("CARTESIA_API_KEY") - - if missing: - logger.error(f"Missing required environment variables: {', '.join(missing)}") - return False - return True - - -class TranscriptionLogger(FrameProcessor): - """Log transcriptions for test verification.""" - - async def process_frame(self, frame: Frame, direction: FrameDirection): - if isinstance(frame, TranscriptionFrame): - logger.info(f"📝 TRANSCRIPTION: {frame.text}") - logger.info(f" Speaker: {frame.user_id}") - logger.info(f" Finalized: {frame.finalized}") - if hasattr(frame, "result") and frame.result: - if hasattr(frame.result, "speaker"): - logger.info(f" Diarization: {frame.result.speaker}") - - await self.push_frame(frame, direction) - - -async def create_basic_voice_agent( - connection_params: AssemblyAIConnectionParams, - vad_force_turn_endpoint: bool = True, - speaker_format: str = None, -) -> tuple[PipelineTask, LocalAudioTransport]: - """Create a basic voice agent for testing. - - Args: - connection_params: AssemblyAI connection parameters - vad_force_turn_endpoint: Turn detection mode - speaker_format: Optional speaker formatting string - - Returns: - Tuple of (PipelineTask, LocalAudioTransport) - """ - # Create local audio transport (uses your microphone and speakers) - transport = LocalAudioTransport( - params=LocalAudioTransportParams( - audio_in_enabled=True, - audio_out_enabled=True, - ) - ) - - # Create STT - stt = AssemblyAISTTService( - api_key=TestConfig.ASSEMBLYAI_API_KEY, - connection_params=connection_params, - vad_force_turn_endpoint=vad_force_turn_endpoint, - speaker_format=speaker_format, - ) - - # Create TTS - tts = CartesiaTTSService( - api_key=TestConfig.CARTESIA_API_KEY, - voice_id="a0e99841-438c-4a64-b679-ae501e7d6091", # Conversational English - ) - - # Create LLM context and service - messages = [ - { - "role": "system", - "content": ( - "You are a helpful voice assistant. Keep responses brief and natural. " - "If you see speaker tags like text, acknowledge " - "that you understand multiple speakers are present." - ), - } - ] - - context = LLMContext(messages) - llm = OpenAILLMService(api_key=TestConfig.OPENAI_API_KEY, model="gpt-4") - - # Create aggregators with VAD - user_aggregator, assistant_aggregator = LLMContextAggregatorPair( - context, - user_params=LLMUserAggregatorParams( - vad_analyzer=SileroVADAnalyzer(), - ), - ) - - # Create transcription logger - transcription_logger = TranscriptionLogger() - - # Create pipeline - pipeline = Pipeline( - [ - transport.input(), - stt, - transcription_logger, - user_aggregator, - llm, - tts, - transport.output(), - assistant_aggregator, - ] - ) - - # Create task - task = PipelineTask(pipeline) - - return task, transport - - -# ============================================================================ -# Test Functions -# ============================================================================ - - -async def test_basic_config(): - """Test 1: Basic default configuration.""" - logger.info("=" * 80) - logger.info("TEST 1: Basic Default Configuration") - logger.info("=" * 80) - - connection_params = AssemblyAIConnectionParams(speech_model="u3-rt-pro") - - task, transport = await create_basic_voice_agent(connection_params) - - logger.info("✅ Service created successfully with default params") - logger.info("Expected: min=max=100ms, u3-rt-pro model") - logger.info("Speak into your microphone to test transcription") - - # Trigger initial bot greeting - await task.queue_frames([LLMRunFrame()]) - - runner = PipelineRunner() - await runner.run(task) - - -async def test_custom_min_silence(): - """Test 2: Custom min_turn_silence.""" - logger.info("=" * 80) - logger.info("TEST 2: Custom min_turn_silence") - logger.info("=" * 80) - - connection_params = AssemblyAIConnectionParams(speech_model="u3-rt-pro", min_turn_silence=200) - - task, transport = await create_basic_voice_agent(connection_params) - - logger.info("✅ Service created with min=200ms") - logger.info("Expected: Both min and max set to 200ms") - logger.info("Speak short phrases and observe turn detection timing") - - runner = PipelineRunner() - await runner.run(task) - - -async def test_max_silence_warning(): - """Test 3: Setting max_turn_silence should trigger warning.""" - logger.info("=" * 80) - logger.info("TEST 3: max_turn_silence Warning") - logger.info("=" * 80) - - connection_params = AssemblyAIConnectionParams( - speech_model="u3-rt-pro", - min_turn_silence=100, - max_turn_silence=500, # Should trigger warning - ) - - task, transport = await create_basic_voice_agent(connection_params) - - logger.info("⚠️ Check logs above for warning about max_turn_silence being overridden") - logger.info("Expected: Warning logged, max set to 100ms (same as min)") - - runner = PipelineRunner() - await runner.run(task) - - -async def test_custom_prompt_warning(): - """Test 5: Custom prompt should trigger warning.""" - logger.info("=" * 80) - logger.info("TEST 5: Custom Prompt Warning") - logger.info("=" * 80) - - connection_params = AssemblyAIConnectionParams( - speech_model="u3-rt-pro", - prompt="Transcribe verbatim. Always include punctuation.", - ) - - task, transport = await create_basic_voice_agent(connection_params) - - logger.info("⚠️ Check logs above for warning about testing without prompt first") - logger.info("Expected: Warning logged, service continues with custom prompt") - - runner = PipelineRunner() - await runner.run(task) - - -async def test_prompt_keyterms_conflict(): - """Test 6: Prompt + keyterms_prompt should raise error.""" - logger.info("=" * 80) - logger.info("TEST 6: Prompt + Keyterms Conflict (Error)") - logger.info("=" * 80) - - try: - connection_params = AssemblyAIConnectionParams( - speech_model="u3-rt-pro", - prompt="Custom prompt", - keyterms_prompt=["test", "words"], - ) - - task, transport = await create_basic_voice_agent(connection_params) - logger.error("❌ TEST FAILED: Should have raised ValueError") - except ValueError as e: - logger.info(f"✅ TEST PASSED: ValueError raised as expected") - logger.info(f" Error message: {e}") - - -async def test_keyterms_basic(): - """Test 7: Basic keyterms at initialization.""" - logger.info("=" * 80) - logger.info("TEST 7: Basic Keyterms Prompting") - logger.info("=" * 80) - - connection_params = AssemblyAIConnectionParams( - speech_model="u3-rt-pro", - keyterms_prompt=["Pipecat", "AssemblyAI", "Universal-3", "streaming"], - ) - - task, transport = await create_basic_voice_agent(connection_params) - - logger.info("✅ Service created with keyterms: Pipecat, AssemblyAI, Universal-3, streaming") - logger.info("Expected: Boosted recognition for these terms") - logger.info("Try saying: 'I'm testing Pipecat with AssemblyAI Universal-3 for streaming'") - - runner = PipelineRunner() - await runner.run(task) - - -async def test_diarization_no_format(): - """Test 10: Diarization enabled without formatting.""" - logger.info("=" * 80) - logger.info("TEST 10: Diarization Enabled (No Formatting)") - logger.info("=" * 80) - - connection_params = AssemblyAIConnectionParams(speech_model="u3-rt-pro", speaker_labels=True) - - task, transport = await create_basic_voice_agent(connection_params) - - logger.info("✅ Service created with speaker_labels=True") - logger.info("Expected: Speaker IDs in user_id field, plain text in transcript") - logger.info("Have multiple people speak to see different speaker labels") - - runner = PipelineRunner() - await runner.run(task) - - -async def test_diarization_xml_format(): - """Test 11: Diarization with XML formatting.""" - logger.info("=" * 80) - logger.info("TEST 11: Diarization with XML Formatting") - logger.info("=" * 80) - - connection_params = AssemblyAIConnectionParams(speech_model="u3-rt-pro", speaker_labels=True) - - task, transport = await create_basic_voice_agent( - connection_params, speaker_format="<{speaker}>{text}" - ) - - logger.info("✅ Service created with XML speaker formatting") - logger.info("Expected: Text like 'Hello'") - logger.info("Have multiple people speak to see formatted speaker tags") - - runner = PipelineRunner() - await runner.run(task) - - -async def test_dynamic_keyterms(): - """Test 13: Dynamic keyterms updates.""" - logger.info("=" * 80) - logger.info("TEST 13: Dynamic Keyterms Updates") - logger.info("=" * 80) - - connection_params = AssemblyAIConnectionParams(speech_model="u3-rt-pro") - - task, transport = await create_basic_voice_agent(connection_params) - - async def update_keyterms_stages(): - """Simulate multi-stage conversation with keyterms updates.""" - await asyncio.sleep(5) # Wait for connection - - # Stage 1: Greeting - logger.info("🔄 STAGE 1: Greeting (general terms)") - update1 = STTUpdateSettingsFrame( - settings={"keyterms_prompt": ["hello", "hi", "good morning", "welcome"]} - ) - await task.queue_frames([update1]) - - await asyncio.sleep(10) - - # Stage 2: Name collection - logger.info("🔄 STAGE 2: Name Collection") - update2 = STTUpdateSettingsFrame( - settings={ - "keyterms_prompt": [ - "first name", - "last name", - "John", - "Jane", - "Smith", - "Johnson", - ] - } - ) - await task.queue_frames([update2]) - - await asyncio.sleep(10) - - # Stage 3: Medical info - logger.info("🔄 STAGE 3: Medical Information") - update3 = STTUpdateSettingsFrame( - settings={ - "keyterms_prompt": [ - "cardiology", - "echocardiogram", - "blood pressure", - "Dr. Smith", - "metoprolol", - ] - } - ) - await task.queue_frames([update3]) - - await asyncio.sleep(10) - - # Stage 4: Clear keyterms - logger.info("🔄 STAGE 4: Clear Keyterms") - update4 = STTUpdateSettingsFrame(settings={"keyterms_prompt": []}) - await task.queue_frames([update4]) - - # Start update task - asyncio.create_task(update_keyterms_stages()) - - logger.info("✅ Service created, will update keyterms every 10 seconds") - logger.info("Expected: Different keyterms at each stage") - logger.info("Watch logs for 'STAGE X' messages and test relevant terms") - - runner = PipelineRunner() - await runner.run(task) - - -async def test_dynamic_silence_params(): - """Test 15: Dynamic silence parameter updates.""" - logger.info("=" * 80) - logger.info("TEST 15: Dynamic Silence Parameters") - logger.info("=" * 80) - - connection_params = AssemblyAIConnectionParams(speech_model="u3-rt-pro") - - task, transport = await create_basic_voice_agent(connection_params) - - async def update_silence_params(): - """Update silence parameters for different scenarios.""" - await asyncio.sleep(5) - - # Normal conversation - logger.info("🔄 PHASE 1: Normal conversation (default timing)") - await asyncio.sleep(10) - - # Reading credit card - logger.info("🔄 PHASE 2: Reading numbers (longer silence tolerance)") - update1 = STTUpdateSettingsFrame( - settings={ - "max_turn_silence": 5000, - "min_turn_silence": 300, - } - ) - await task.queue_frames([update1]) - - await asyncio.sleep(15) - - # Back to normal - logger.info("🔄 PHASE 3: Back to normal conversation") - update2 = STTUpdateSettingsFrame( - settings={ - "max_turn_silence": 1200, - "min_turn_silence": 100, - } - ) - await task.queue_frames([update2]) - - asyncio.create_task(update_silence_params()) - - logger.info("✅ Service will update silence parameters during conversation") - logger.info("Expected: Longer pauses tolerated in Phase 2") - logger.info("Try pausing between words to test") - - runner = PipelineRunner() - await runner.run(task) - - -async def test_multi_param_update(): - """Test 17: Update multiple parameters at once.""" - logger.info("=" * 80) - logger.info("TEST 17: Multiple Parameter Update") - logger.info("=" * 80) - - connection_params = AssemblyAIConnectionParams(speech_model="u3-rt-pro") - - task, transport = await create_basic_voice_agent(connection_params) - - async def multi_update(): - await asyncio.sleep(5) - - logger.info("🔄 Updating multiple parameters together") - update = STTUpdateSettingsFrame( - settings={ - "keyterms_prompt": ["account", "routing", "number"], - "max_turn_silence": 3000, - "min_turn_silence": 200, - } - ) - await task.queue_frames([update]) - - logger.info("✅ Check logs for single UpdateConfiguration message") - - asyncio.create_task(multi_update()) - - logger.info("Expected: All params updated in single WebSocket message") - - runner = PipelineRunner() - await runner.run(task) - - -# ============================================================================ -# Main Test Runner -# ============================================================================ - - -def main(): - """Main test runner.""" - parser = argparse.ArgumentParser(description="Test AssemblyAI u3-rt-pro integration") - parser.add_argument( - "--test", - type=str, - default="basic", - help="Test to run (basic, custom_min, max_warning, prompt_warning, " - "prompt_keyterms_conflict, keyterms, diarization, diarization_xml, " - "dynamic_keyterms, dynamic_silence, multi_param, all)", - ) - parser.add_argument("--interactive", action="store_true", help="Run in interactive mode") - - args = parser.parse_args() - - # Validate environment - if not TestConfig.validate(): - logger.error("Please set all required environment variables in .env") - sys.exit(1) - - # Test mapping - tests = { - "basic": test_basic_config, - "custom_min": test_custom_min_silence, - "max_warning": test_max_silence_warning, - "prompt_warning": test_custom_prompt_warning, - "prompt_keyterms_conflict": test_prompt_keyterms_conflict, - "keyterms": test_keyterms_basic, - "diarization": test_diarization_no_format, - "diarization_xml": test_diarization_xml_format, - "dynamic_keyterms": test_dynamic_keyterms, - "dynamic_silence": test_dynamic_silence_params, - "multi_param": test_multi_param_update, - } - - if args.interactive: - logger.info("Interactive mode - select test to run:") - for i, (name, _) in enumerate(tests.items(), 1): - logger.info(f"{i}. {name}") - logger.info(f"{len(tests) + 1}. Run all tests") - - choice = input("\nEnter test number: ") - try: - choice_num = int(choice) - if choice_num == len(tests) + 1: - args.test = "all" - else: - args.test = list(tests.keys())[choice_num - 1] - except (ValueError, IndexError): - logger.error("Invalid choice") - sys.exit(1) - - # Run test(s) - if args.test == "all": - logger.info("Running all tests sequentially...") - for test_name, test_func in tests.items(): - try: - asyncio.run(test_func()) - except KeyboardInterrupt: - logger.info(f"Test '{test_name}' interrupted") - break - except Exception as e: - logger.error(f"Test '{test_name}' failed: {e}") - else: - if args.test not in tests: - logger.error(f"Unknown test: {args.test}") - logger.info(f"Available tests: {', '.join(tests.keys())}") - sys.exit(1) - - try: - asyncio.run(tests[args.test]()) - except KeyboardInterrupt: - logger.info("Test interrupted") - except Exception as e: - logger.error(f"Test failed: {e}") - raise - - -if __name__ == "__main__": - main() From 91c46ffbf49609bffe07eb5801a97f77b88734a1 Mon Sep 17 00:00:00 2001 From: Mark Backman Date: Sun, 1 Mar 2026 16:30:49 -0500 Subject: [PATCH 0714/1060] Re-inject turn completion instructions after LLM context reset When filter_incomplete_user_turns is enabled and an LLMMessagesUpdateFrame replaces the context via set_messages(), the turn completion instructions system message was lost. This caused the LLM to stop emitting turn completion markers. Re-inject the instructions after set_messages() to fix this. --- changelog/3888.fixed.md | 1 + .../aggregators/llm_response_universal.py | 3 +++ tests/test_context_aggregators_universal.py | 23 +++++++++++++++++++ 3 files changed, 27 insertions(+) create mode 100644 changelog/3888.fixed.md diff --git a/changelog/3888.fixed.md b/changelog/3888.fixed.md new file mode 100644 index 000000000..99e9ad0e0 --- /dev/null +++ b/changelog/3888.fixed.md @@ -0,0 +1 @@ +- Fixed turn completion instructions being lost when `LLMMessagesUpdateFrame` replaces the LLM context. When `filter_incomplete_user_turns` is enabled, the turn completion system message is now re-injected after context replacement. diff --git a/src/pipecat/processors/aggregators/llm_response_universal.py b/src/pipecat/processors/aggregators/llm_response_universal.py index c43cc279d..96f3702be 100644 --- a/src/pipecat/processors/aggregators/llm_response_universal.py +++ b/src/pipecat/processors/aggregators/llm_response_universal.py @@ -642,6 +642,9 @@ class LLMUserAggregator(LLMContextAggregator): async def _handle_llm_messages_update(self, frame: LLMMessagesUpdateFrame): self.set_messages(frame.messages) + if self._params.filter_incomplete_user_turns: + config = self._params.user_turn_completion_config or UserTurnCompletionConfig() + self._context.add_message({"role": "system", "content": config.completion_instructions}) if frame.run_llm: await self.push_context_frame() diff --git a/tests/test_context_aggregators_universal.py b/tests/test_context_aggregators_universal.py index e86905e1c..b22abf6c6 100644 --- a/tests/test_context_aggregators_universal.py +++ b/tests/test_context_aggregators_universal.py @@ -50,6 +50,7 @@ from pipecat.turns.user_mute import ( MuteUntilFirstBotCompleteUserMuteStrategy, ) from pipecat.turns.user_stop import SpeechTimeoutUserTurnStopStrategy +from pipecat.turns.user_turn_completion_mixin import UserTurnCompletionConfig from pipecat.turns.user_turn_strategies import UserTurnStrategies USER_TURN_STOP_TIMEOUT = 0.2 @@ -155,6 +156,28 @@ class TestLLMUserAggregator(unittest.IsolatedAsyncioTestCase): ) assert context.messages[0]["content"] == "Hi there!" + async def test_llm_messages_update_reinjects_turn_completion_instructions(self): + context = LLMContext() + params = LLMUserAggregatorParams(filter_incomplete_user_turns=True) + pipeline = Pipeline([LLMUserAggregator(context, params=params)]) + + new_messages = [ + {"role": "system", "content": "You are a helpful assistant."}, + {"role": "user", "content": "Hello!"}, + ] + frames_to_send = [LLMMessagesUpdateFrame(messages=new_messages)] + await run_test( + pipeline, + frames_to_send=frames_to_send, + ) + config = UserTurnCompletionConfig() + # The context should contain the new messages plus the re-injected instructions + assert len(context.messages) == 3 + assert context.messages[0]["content"] == "You are a helpful assistant." + assert context.messages[1]["content"] == "Hello!" + assert context.messages[2]["role"] == "system" + assert context.messages[2]["content"] == config.completion_instructions + async def test_default_user_turn_strategies(self): context = LLMContext() user_aggregator = LLMUserAggregator( From 16c676a921a3aa77c19162ec3310fa61fff02978 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?G=C3=B6kmen=20G=C3=B6rgen?= Date: Mon, 2 Mar 2026 10:34:50 +0100 Subject: [PATCH 0715/1060] add a test for reproducing the user feedback first. --- tests/test_aic_filter.py | 78 ++++++++++++++++++++++++++++++++++++++++ 1 file changed, 78 insertions(+) diff --git a/tests/test_aic_filter.py b/tests/test_aic_filter.py index 83eca757c..08c702986 100644 --- a/tests/test_aic_filter.py +++ b/tests/test_aic_filter.py @@ -632,6 +632,84 @@ class TestAICFilter(unittest.IsolatedAsyncioTestCase): for result in results: self.assertIsInstance(result, bytes) + async def test_concurrent_filter_no_buffer_resize_error(self): + """Regression: concurrent filter() must not raise BufferError. + + When process_async yields to the event loop, a second filter() call + runs and calls _audio_buffer.extend(). If the first call still holds + a memoryview on the bytearray, extend() raises: + + BufferError: Existing exports of data: object cannot be re-sized + + The fix snapshots the needed data into immutable bytes and trims the + buffer *before* any await, so no memoryview is held across yield + points. + """ + filter_instance = self._create_filter_with_mocks() + + # Make process_async yield to the event loop so concurrent filter() + # calls can interleave and attempt _audio_buffer.extend(). + async def yielding_process_async(audio_array): + await asyncio.sleep(0) + return audio_array.copy() + + self.mock_processor.process_async = yielding_process_async + await self._start_filter_with_mocks(filter_instance) + + samples = np.random.randint(-32768, 32767, size=160, dtype=np.int16) + input_audio = samples.tobytes() + + async def filter_audio(): + return await filter_instance.filter(input_audio) + + # 20 concurrent calls to reliably trigger the interleaving. + tasks = [filter_audio() for _ in range(20)] + results = await asyncio.gather(*tasks) + + for result in results: + self.assertIsInstance(result, bytes) + + async def test_stop_during_filter_no_buffer_resize_error(self): + """Regression: stop() during filter() must not raise BufferError. + + When filter() holds a memoryview on _audio_buffer across an await + (process_async), a concurrent stop() that calls + _audio_buffer.clear() raises: + + BufferError: Existing exports of data: object cannot be re-sized + + This is the exact error path reported in production (line 414). + The fix removes the memoryview by snapshotting data into immutable + bytes before any await. + """ + filter_instance = self._create_filter_with_mocks() + + # Gate so stop() waits until filter() is inside process_async. + processing_started = asyncio.Event() + + async def yielding_process_async(audio_array): + processing_started.set() + await asyncio.sleep(0) # yield — stop() runs here + return audio_array.copy() + + self.mock_processor.process_async = yielding_process_async + await self._start_filter_with_mocks(filter_instance) + + # Exactly one complete frame so the loop runs once. + samples = np.random.randint(-32768, 32767, size=160, dtype=np.int16) + input_audio = samples.tobytes() + + async def stop_after_filter_enters_process_async(): + await processing_started.wait() + await filter_instance.stop() + + # filter() enters process_async → yields → stop() calls clear() + filter_result, _ = await asyncio.gather( + filter_instance.filter(input_audio), + stop_after_filter_enters_process_async(), + ) + self.assertIsInstance(filter_result, bytes) + async def test_buffer_cleared_on_stop(self): """Test that audio buffer is cleared when stopping.""" filter_instance = self._create_filter_with_mocks() From ea59695551894ff2ed4821ef5438b2a77f0caea9 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?G=C3=B6kmen=20G=C3=B6rgen?= Date: Mon, 2 Mar 2026 10:55:25 +0100 Subject: [PATCH 0716/1060] don't use memoryview for concurrency safety. Snapshot the blocks into immutable bytes and trim the buffer BEFORE any await, so no memoryview is held across async yield points. Without this, a concurrent filter() or stop() call could try to extend() or clear() the bytearray while a memoryview still exports it, raising "Existing exports of data: object cannot be re-sized". --- src/pipecat/audio/filters/aic_filter.py | 10 ++++++---- 1 file changed, 6 insertions(+), 4 deletions(-) diff --git a/src/pipecat/audio/filters/aic_filter.py b/src/pipecat/audio/filters/aic_filter.py index 723b3da8f..f0675577e 100644 --- a/src/pipecat/audio/filters/aic_filter.py +++ b/src/pipecat/audio/filters/aic_filter.py @@ -458,13 +458,16 @@ class AICFilter(BaseAudioFilter): if num_blocks == 0: return b"" - filtered_chunks: List[bytes] = [] - mv = memoryview(self._audio_buffer) block_size = self._frames_per_block * self._bytes_per_sample + total_size = num_blocks * block_size + blocks_data = bytes(self._audio_buffer[:total_size]) + self._audio_buffer = self._audio_buffer[total_size:] + + filtered_chunks: List[bytes] = [] for i in range(num_blocks): start = i * block_size - block_i16 = np.frombuffer(mv[start : start + block_size], dtype=self._dtype) + block_i16 = np.frombuffer(blocks_data[start : start + block_size], dtype=self._dtype) # Reuse input buffer, in-place divide np.copyto(self._in_f32[0], block_i16) @@ -479,5 +482,4 @@ class AICFilter(BaseAudioFilter): filtered_chunks.append(self._out_i16.tobytes()) - self._audio_buffer = self._audio_buffer[num_blocks * block_size :] return b"".join(filtered_chunks) From 8ff3e216548d64bd54dc1a639fb52c53d4d2bbac Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?G=C3=B6kmen=20G=C3=B6rgen?= Date: Mon, 2 Mar 2026 11:22:51 +0100 Subject: [PATCH 0717/1060] use new version of vf model. --- examples/foundational/07zd-interruptible-aicoustics.py | 2 +- pyproject.toml | 2 +- 2 files changed, 2 insertions(+), 2 deletions(-) diff --git a/examples/foundational/07zd-interruptible-aicoustics.py b/examples/foundational/07zd-interruptible-aicoustics.py index 61298a706..1a3c626ef 100644 --- a/examples/foundational/07zd-interruptible-aicoustics.py +++ b/examples/foundational/07zd-interruptible-aicoustics.py @@ -40,7 +40,7 @@ def _create_aic_filter() -> AICFilter: return AICFilter( license_key=license_key, - model_id="quail-vf-l-16khz", + model_id="quail-vf-2.0-l-16khz", ) diff --git a/pyproject.toml b/pyproject.toml index 2cf46c3cd..e1a332494 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -52,7 +52,7 @@ Issues = "https://github.com/pipecat-ai/pipecat/issues" Changelog = "https://github.com/pipecat-ai/pipecat/blob/main/CHANGELOG.md" [project.optional-dependencies] -aic = [ "aic-sdk~=2.0.1" ] +aic = [ "aic-sdk~=2.1.0" ] anthropic = [ "anthropic~=0.49.0" ] assemblyai = [ "pipecat-ai[websockets-base]" ] asyncai = [ "pipecat-ai[websockets-base]" ] From d6aab6b52e5ebbc3576254cc86db393c096fab1c Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?G=C3=B6kmen=20G=C3=B6rgen?= Date: Mon, 2 Mar 2026 12:24:52 +0100 Subject: [PATCH 0718/1060] simplify parameter setup in `AICFilter`. ParameterFixedError is deprecated. --- src/pipecat/audio/filters/aic_filter.py | 10 +++------- 1 file changed, 3 insertions(+), 7 deletions(-) diff --git a/src/pipecat/audio/filters/aic_filter.py b/src/pipecat/audio/filters/aic_filter.py index f0675577e..91f0356d0 100644 --- a/src/pipecat/audio/filters/aic_filter.py +++ b/src/pipecat/audio/filters/aic_filter.py @@ -375,12 +375,7 @@ class AICFilter(BaseAudioFilter): self._vad_ctx = self._processor.get_vad_context() # Apply initial parameters - try: - self._processor_ctx.set_parameter( - ProcessorParameter.Bypass, 1.0 if self._bypass else 0.0 - ) - except ParameterFixedError as e: - logger.error(f"AIC parameter update failed: {e}") + self._processor_ctx.set_parameter(ProcessorParameter.Bypass, 1.0 if self._bypass else 0.0) # Log processor information logger.debug(f"ai-coustics filter started:") @@ -389,7 +384,8 @@ class AICFilter(BaseAudioFilter): logger.debug(f" Frames per chunk: {self._frames_per_block}") logger.debug(f" Optimal sample rate: {self._model.get_optimal_sample_rate()} Hz") logger.debug( - f" Optimal number of frames for {self._sample_rate} Hz: {self._model.get_optimal_num_frames(self._sample_rate)}" + f" Optimal number of frames for {self._sample_rate} Hz: " + f"{self._model.get_optimal_num_frames(self._sample_rate)}" ) logger.debug( f" Output delay: {self._processor_ctx.get_output_delay()} samples " From 7575ea7e079c325a2ade25427642e3b106335a6b Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?G=C3=B6kmen=20G=C3=B6rgen?= Date: Mon, 2 Mar 2026 12:47:59 +0100 Subject: [PATCH 0719/1060] add changelog entries for Voice Focus 2.0 support and buffer resize fix in `AICFilter`. --- changelog/3889.changed.md | 3 +++ changelog/3889.fixed.md | 1 + 2 files changed, 4 insertions(+) create mode 100644 changelog/3889.changed.md create mode 100644 changelog/3889.fixed.md diff --git a/changelog/3889.changed.md b/changelog/3889.changed.md new file mode 100644 index 000000000..c04aa0080 --- /dev/null +++ b/changelog/3889.changed.md @@ -0,0 +1,3 @@ +- Support for Voice Focus 2.0 models. + - Updated `aic-sdk` to `~=2.1.0` to support Voice Focus 2.0 models. + - Cleaned unused `ParameterFixedError` exception handling in `AICFilter` parameter setup. diff --git a/changelog/3889.fixed.md b/changelog/3889.fixed.md new file mode 100644 index 000000000..babe3eb35 --- /dev/null +++ b/changelog/3889.fixed.md @@ -0,0 +1 @@ +- Fixed `BufferError: Existing exports of data: object cannot be re-sized` in `AICFilter` caused by holding a `memoryview` on the mutable audio buffer across async yield points. From 55a641e2584d14c2dfff6fe65561331b08229646 Mon Sep 17 00:00:00 2001 From: dhruvladia-sarvam Date: Sun, 1 Mar 2026 22:10:27 +0530 Subject: [PATCH 0720/1060] fix(sarvam): standardize STT/TTS User-Agent headers --- src/pipecat/services/sarvam/stt.py | 34 +++++++++++++++++------------- src/pipecat/services/sarvam/tts.py | 11 ++++++---- 2 files changed, 26 insertions(+), 19 deletions(-) diff --git a/src/pipecat/services/sarvam/stt.py b/src/pipecat/services/sarvam/stt.py index 379473c6f..f4ebf7574 100644 --- a/src/pipecat/services/sarvam/stt.py +++ b/src/pipecat/services/sarvam/stt.py @@ -266,15 +266,10 @@ class SarvamSTTService(STTService): # Initialize Sarvam SDK client self._sdk_headers = sdk_headers() - # NOTE: We avoid passing non-standard kwargs here because different sarvamai - # versions expose different constructor signatures (static type checkers - # complain otherwise). We instead inject headers best-effort below. - self._sarvam_client = AsyncSarvamAI(api_subscription_key=api_key) - for attr in ("default_headers", "_default_headers", "headers", "_headers"): - d = getattr(self._sarvam_client, attr, None) - if isinstance(d, dict): - d.update(self._sdk_headers) - break + # Pass Pipecat SDK headers directly at client construction time so they are + # merged by the Sarvam SDK's client wrapper and consistently applied to + # WebSocket handshake requests. + self._sarvam_client = AsyncSarvamAI(api_subscription_key=api_key, headers=self._sdk_headers) self._websocket_context = None self._socket_client = None self._receive_task = None @@ -517,20 +512,29 @@ class SarvamSTTService(STTService): connect_kwargs["prompt"] = self._settings.prompt def _connect_with_sdk_headers(connect_fn, **kwargs): - # Different SDK versions may use different kwarg names. # If prompt is unsupported at connect-time, retry without it. + # Headers are supplied through request_options because this is a + # documented SDK parameter that survives SDK signature changes. + request_options = {"additional_headers": self._sdk_headers} + logger.debug( + f"Sarvam STT connect request_options.additional_headers: " + f"{request_options['additional_headers']}" + ) attempts = [kwargs] if "prompt" in kwargs: attempts.append({k: v for k, v in kwargs.items() if k != "prompt"}) last_type_error = None for attempt_kwargs in attempts: - for header_kw in ("headers", "additional_headers", "extra_headers"): - try: - return connect_fn(**attempt_kwargs, **{header_kw: self._sdk_headers}) - except TypeError as e: - last_type_error = e try: + return connect_fn( + **attempt_kwargs, + request_options=request_options, + ) + except TypeError as e: + last_type_error = e + try: + # Fallback for SDK builds that don't expose request_options. return connect_fn(**attempt_kwargs) except TypeError as e: last_type_error = e diff --git a/src/pipecat/services/sarvam/tts.py b/src/pipecat/services/sarvam/tts.py index 87604a9f9..e92ade2e5 100644 --- a/src/pipecat/services/sarvam/tts.py +++ b/src/pipecat/services/sarvam/tts.py @@ -1013,12 +1013,15 @@ class SarvamTTSService(InterruptibleTTSService): if self._websocket and self._websocket.state is State.OPEN: return + ws_additional_headers = { + "api-subscription-key": self._api_key, + **sdk_headers(), + } + self._websocket = await websocket_connect( self._websocket_url, - additional_headers={ - "api-subscription-key": self._api_key, - **sdk_headers(), - }, + additional_headers=ws_additional_headers, + user_agent_header=None, ) logger.debug("Connected to Sarvam TTS Websocket") await self._send_config() From 1242f1c10ef0404a03346c0489eceac749548732 Mon Sep 17 00:00:00 2001 From: dhruvladia-sarvam Date: Mon, 2 Mar 2026 17:29:03 +0530 Subject: [PATCH 0721/1060] changelog entry --- changelog/3886.other.md | 1 + 1 file changed, 1 insertion(+) create mode 100644 changelog/3886.other.md diff --git a/changelog/3886.other.md b/changelog/3886.other.md new file mode 100644 index 000000000..0e9fdafed --- /dev/null +++ b/changelog/3886.other.md @@ -0,0 +1 @@ +- Standardized Sarvam STT/TTS User-Agent header handling to consistently send Pipecat SDK identity in websocket requests. \ No newline at end of file From 018ead85514a4cab3de6519e9678ae83f448335b Mon Sep 17 00:00:00 2001 From: Mark Backman Date: Fri, 27 Feb 2026 19:32:08 -0500 Subject: [PATCH 0722/1060] Changelog for PR 3873, docstrings change --- changelog/3873.added.md | 1 + src/pipecat/services/rime/tts.py | 6 +++--- 2 files changed, 4 insertions(+), 3 deletions(-) create mode 100644 changelog/3873.added.md diff --git a/changelog/3873.added.md b/changelog/3873.added.md new file mode 100644 index 000000000..ed01b8e5d --- /dev/null +++ b/changelog/3873.added.md @@ -0,0 +1 @@ +- Added support for the `speed_alpha` parameter to the `arcana` model in `RimeTTSService`. diff --git a/src/pipecat/services/rime/tts.py b/src/pipecat/services/rime/tts.py index 2dbaf2760..944ff4e58 100644 --- a/src/pipecat/services/rime/tts.py +++ b/src/pipecat/services/rime/tts.py @@ -147,10 +147,10 @@ class RimeTTSService(AudioContextTTSService): Parameters: language: Language for synthesis. Defaults to English. segment: Text segmentation mode ("immediate", "bySentence", "never"). + speed_alpha: Speech speed multiplier. repetition_penalty: Token repetition penalty (arcana only). temperature: Sampling temperature (arcana only). top_p: Cumulative probability threshold (arcana only). - speed_alpha: Speech speed multiplier (mistv2 only). reduce_latency: Whether to reduce latency at potential quality cost (mistv2 only). pause_between_brackets: Whether to add pauses between bracketed content (mistv2 only). phonemize_between_brackets: Whether to phonemize bracketed content (mistv2 only). @@ -160,12 +160,12 @@ class RimeTTSService(AudioContextTTSService): language: Optional[Language] = Language.EN segment: Optional[str] = None + speed_alpha: Optional[float] = None # Arcana params repetition_penalty: Optional[float] = None temperature: Optional[float] = None top_p: Optional[float] = None # Mistv2 params - speed_alpha: Optional[float] = None reduce_latency: Optional[bool] = None pause_between_brackets: Optional[bool] = None phonemize_between_brackets: Optional[bool] = None @@ -230,12 +230,12 @@ class RimeTTSService(AudioContextTTSService): else None, segment=params.segment, inlineSpeedAlpha=None, # Not applicable here + speedAlpha=params.speed_alpha, # Arcana params repetition_penalty=params.repetition_penalty, temperature=params.temperature, top_p=params.top_p, # Mistv2 params - speedAlpha=params.speed_alpha, reduceLatency=params.reduce_latency, pauseBetweenBrackets=params.pause_between_brackets, phonemizeBetweenBrackets=params.phonemize_between_brackets, From 442ea6a97e0c3835757f5651f1ea7f37d5485930 Mon Sep 17 00:00:00 2001 From: Rupesh Date: Thu, 26 Feb 2026 19:36:21 -0800 Subject: [PATCH 0723/1060] Fix Smart Turn v3 producing incorrect predictions at non-16kHz sample rates The Whisper-based ONNX model expects 16 kHz audio, but the _predict_endpoint method had five hardcoded references to 16000 without checking the actual pipeline sample rate. When running at 8 kHz (e.g. Twilio telephony), audio was fed to the feature extractor at the wrong rate, causing the model to perceive speech at 2x speed with shifted formant frequencies and produce incorrect end-of-turn predictions. Add automatic resampling via numpy interpolation before feature extraction and replace all hardcoded sample rate values with a _MODEL_SAMPLE_RATE constant. Also fix the WAV debug logger to write files with the correct sample rate header. Fixes #3844 --- .../turn/smart_turn/local_smart_turn_v3.py | 47 +++++++++++++++++-- 1 file changed, 42 insertions(+), 5 deletions(-) diff --git a/src/pipecat/audio/turn/smart_turn/local_smart_turn_v3.py b/src/pipecat/audio/turn/smart_turn/local_smart_turn_v3.py index b9e2a7663..01c3746c8 100644 --- a/src/pipecat/audio/turn/smart_turn/local_smart_turn_v3.py +++ b/src/pipecat/audio/turn/smart_turn/local_smart_turn_v3.py @@ -20,6 +20,9 @@ from transformers import WhisperFeatureExtractor from pipecat.audio.turn.smart_turn.base_smart_turn import BaseSmartTurn from pipecat.utils.env import env_truthy +# The Whisper-based ONNX model expects 16 kHz audio input. +_MODEL_SAMPLE_RATE = 16000 + class LocalSmartTurnAnalyzerV3(BaseSmartTurn): """Local turn analyzer using the smart-turn-v3 ONNX model. @@ -42,6 +45,7 @@ class LocalSmartTurnAnalyzerV3(BaseSmartTurn): super().__init__(**kwargs) self._log_data = env_truthy("PIPECAT_SMART_TURN_LOG_DATA", default=False) + self._resample_warned = False if not smart_turn_model_path: # Load bundled model @@ -77,7 +81,7 @@ class LocalSmartTurnAnalyzerV3(BaseSmartTurn): logger.debug("Loaded Local Smart Turn v3.x") def _write_audio_to_wav( - self, audio_array: np.ndarray, sample_rate: int = 16000, suffix: str = "" + self, audio_array: np.ndarray, sample_rate: int = _MODEL_SAMPLE_RATE, suffix: str = "" ) -> None: """Write audio data to a WAV file in a background thread. @@ -119,10 +123,39 @@ class LocalSmartTurnAnalyzerV3(BaseSmartTurn): thread = threading.Thread(target=write_wav, daemon=True) thread.start() + def _resample_to_model_rate(self, audio_array: np.ndarray) -> np.ndarray: + """Resample audio to the model's expected sample rate (16 kHz). + + Args: + audio_array: Audio data as a float32 numpy array. + + Returns: + Resampled audio array at 16 kHz. + """ + actual_rate = self._sample_rate or _MODEL_SAMPLE_RATE + if actual_rate == _MODEL_SAMPLE_RATE: + return audio_array + + if not self._resample_warned: + logger.warning( + f"Smart Turn v3 model expects {_MODEL_SAMPLE_RATE}Hz audio but received " + f"{actual_rate}Hz. Audio will be resampled automatically." + ) + self._resample_warned = True + + num_output_samples = int(len(audio_array) * _MODEL_SAMPLE_RATE / actual_rate) + return np.interp( + np.linspace(0, len(audio_array), num_output_samples, endpoint=False), + np.arange(len(audio_array)), + audio_array, + ) + def _predict_endpoint(self, audio_array: np.ndarray) -> Dict[str, Any]: """Predict end-of-turn using local ONNX model.""" - def truncate_audio_to_last_n_seconds(audio_array, n_seconds=8, sample_rate=16000): + def truncate_audio_to_last_n_seconds( + audio_array, n_seconds=8, sample_rate=_MODEL_SAMPLE_RATE + ): """Truncate audio to last n seconds or pad with zeros to meet n seconds.""" max_samples = n_seconds * sample_rate if len(audio_array) > max_samples: @@ -134,6 +167,10 @@ class LocalSmartTurnAnalyzerV3(BaseSmartTurn): return audio_array audio_for_logging = audio_array + actual_rate = self._sample_rate or _MODEL_SAMPLE_RATE + + # Resample to 16 kHz if the pipeline uses a different sample rate + audio_array = self._resample_to_model_rate(audio_array) # Truncate to 8 seconds (keeping the end) or pad to 8 seconds audio_array = truncate_audio_to_last_n_seconds(audio_array, n_seconds=8) @@ -141,10 +178,10 @@ class LocalSmartTurnAnalyzerV3(BaseSmartTurn): # Process audio using Whisper's feature extractor inputs = self._feature_extractor( audio_array, - sampling_rate=16000, + sampling_rate=_MODEL_SAMPLE_RATE, return_tensors="np", padding="max_length", - max_length=8 * 16000, + max_length=8 * _MODEL_SAMPLE_RATE, truncation=True, do_normalize=True, ) @@ -164,7 +201,7 @@ class LocalSmartTurnAnalyzerV3(BaseSmartTurn): if self._log_data: suffix = "_complete" if prediction == 1 else "_incomplete" - self._write_audio_to_wav(audio_for_logging, sample_rate=16000, suffix=suffix) + self._write_audio_to_wav(audio_for_logging, sample_rate=actual_rate, suffix=suffix) return { "prediction": prediction, From a7f6db84365e8442df056bdf3540970d0a9225b0 Mon Sep 17 00:00:00 2001 From: Rupesh Date: Thu, 26 Feb 2026 19:36:50 -0800 Subject: [PATCH 0724/1060] Add changelog fragment for #3857 --- changelog/3857.fixed.md | 1 + 1 file changed, 1 insertion(+) create mode 100644 changelog/3857.fixed.md diff --git a/changelog/3857.fixed.md b/changelog/3857.fixed.md new file mode 100644 index 000000000..869c54111 --- /dev/null +++ b/changelog/3857.fixed.md @@ -0,0 +1 @@ +- Fixed `LocalSmartTurnAnalyzerV3` producing incorrect end-of-turn predictions at non-16kHz sample rates (e.g. 8kHz Twilio telephony) by adding automatic resampling to 16kHz before Whisper feature extraction. From 5e8d722bf25ed82560ccb26f5018598313da3100 Mon Sep 17 00:00:00 2001 From: Rupesh Date: Fri, 27 Feb 2026 11:46:39 -0800 Subject: [PATCH 0725/1060] Use soxr for high-quality audio resampling instead of numpy linear interpolation --- src/pipecat/audio/turn/smart_turn/local_smart_turn_v3.py | 8 ++------ 1 file changed, 2 insertions(+), 6 deletions(-) diff --git a/src/pipecat/audio/turn/smart_turn/local_smart_turn_v3.py b/src/pipecat/audio/turn/smart_turn/local_smart_turn_v3.py index 01c3746c8..ffe714641 100644 --- a/src/pipecat/audio/turn/smart_turn/local_smart_turn_v3.py +++ b/src/pipecat/audio/turn/smart_turn/local_smart_turn_v3.py @@ -14,6 +14,7 @@ from typing import Any, Dict, Optional import numpy as np import onnxruntime as ort +import soxr from loguru import logger from transformers import WhisperFeatureExtractor @@ -143,12 +144,7 @@ class LocalSmartTurnAnalyzerV3(BaseSmartTurn): ) self._resample_warned = True - num_output_samples = int(len(audio_array) * _MODEL_SAMPLE_RATE / actual_rate) - return np.interp( - np.linspace(0, len(audio_array), num_output_samples, endpoint=False), - np.arange(len(audio_array)), - audio_array, - ) + return soxr.resample(audio_array, actual_rate, _MODEL_SAMPLE_RATE, quality="VHQ") def _predict_endpoint(self, audio_array: np.ndarray) -> Dict[str, Any]: """Predict end-of-turn using local ONNX model.""" From ad74d19c6ba0178d8b0fa3bdcab27737d5f78c40 Mon Sep 17 00:00:00 2001 From: Rupesh Date: Sun, 1 Mar 2026 13:19:42 -0800 Subject: [PATCH 0726/1060] Remove resampling warning log for consistency with rest of codebase --- src/pipecat/audio/turn/smart_turn/local_smart_turn_v3.py | 8 -------- 1 file changed, 8 deletions(-) diff --git a/src/pipecat/audio/turn/smart_turn/local_smart_turn_v3.py b/src/pipecat/audio/turn/smart_turn/local_smart_turn_v3.py index ffe714641..a8cc249fd 100644 --- a/src/pipecat/audio/turn/smart_turn/local_smart_turn_v3.py +++ b/src/pipecat/audio/turn/smart_turn/local_smart_turn_v3.py @@ -46,7 +46,6 @@ class LocalSmartTurnAnalyzerV3(BaseSmartTurn): super().__init__(**kwargs) self._log_data = env_truthy("PIPECAT_SMART_TURN_LOG_DATA", default=False) - self._resample_warned = False if not smart_turn_model_path: # Load bundled model @@ -137,13 +136,6 @@ class LocalSmartTurnAnalyzerV3(BaseSmartTurn): if actual_rate == _MODEL_SAMPLE_RATE: return audio_array - if not self._resample_warned: - logger.warning( - f"Smart Turn v3 model expects {_MODEL_SAMPLE_RATE}Hz audio but received " - f"{actual_rate}Hz. Audio will be resampled automatically." - ) - self._resample_warned = True - return soxr.resample(audio_array, actual_rate, _MODEL_SAMPLE_RATE, quality="VHQ") def _predict_endpoint(self, audio_array: np.ndarray) -> Dict[str, Any]: From 07ba2550733b21598f5846e392844e649c48f372 Mon Sep 17 00:00:00 2001 From: Mark Backman Date: Mon, 2 Mar 2026 09:20:24 -0500 Subject: [PATCH 0727/1060] Fix update-docs workflow OIDC failure with pull_request_target The switch from pull_request to pull_request_target (for fork PR secret access) broke claude-code-action default OIDC-based GitHub App authentication. Pass github_token explicitly to bypass OIDC. --- .github/workflows/update-docs.yml | 1 + 1 file changed, 1 insertion(+) diff --git a/.github/workflows/update-docs.yml b/.github/workflows/update-docs.yml index a9066762d..d26862766 100644 --- a/.github/workflows/update-docs.yml +++ b/.github/workflows/update-docs.yml @@ -59,6 +59,7 @@ jobs: DOCS_SYNC_TOKEN: ${{ secrets.DOCS_SYNC_TOKEN }} with: anthropic_api_key: ${{ secrets.ANTHROPIC_API_KEY }} + github_token: ${{ secrets.GITHUB_TOKEN }} prompt: | You are updating documentation for the pipecat-ai/docs repository based on changes merged in PR #${{ steps.pr.outputs.number }} of pipecat-ai/pipecat. From 8b09f7bbb4543538582eca5c2fb5ca2d8ea133e3 Mon Sep 17 00:00:00 2001 From: filipi87 Date: Mon, 2 Mar 2026 11:22:33 -0300 Subject: [PATCH 0728/1060] Upgrading Deepgram to version 6. --- changelog/3848.changed.md | 1 + changelog/3848.fixed.md | 1 + pyproject.toml | 2 +- src/pipecat/services/deepgram/stt.py | 632 ++++++++++-------- .../services/deepgram/stt_sagemaker.py | 31 +- tests/test_settings.py | 310 ++++++--- uv.lock | 36 +- 7 files changed, 589 insertions(+), 424 deletions(-) create mode 100644 changelog/3848.changed.md create mode 100644 changelog/3848.fixed.md diff --git a/changelog/3848.changed.md b/changelog/3848.changed.md new file mode 100644 index 000000000..1590e284a --- /dev/null +++ b/changelog/3848.changed.md @@ -0,0 +1 @@ +- ⚠️ Updated `DeepgramSTTService` to use `deepgram-sdk` v6. The `LiveOptions` class was removed from the SDK and is now provided by pipecat directly; import it from `pipecat.services.deepgram.stt` instead of `deepgram`. diff --git a/changelog/3848.fixed.md b/changelog/3848.fixed.md new file mode 100644 index 000000000..a6651b763 --- /dev/null +++ b/changelog/3848.fixed.md @@ -0,0 +1 @@ +- Fixed `DeepgramSTTService` keepalive ping timeout disconnections. The deepgram-sdk v6 removed automatic keepalive; pipecat now sends explicit `KeepAlive` messages every 5 seconds, within the recommended 3–5 second interval before Deepgram's 10-second inactivity timeout. diff --git a/pyproject.toml b/pyproject.toml index 2cf46c3cd..cb1958f62 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -63,7 +63,7 @@ cartesia = [ "cartesia~=2.0.3", "pipecat-ai[websockets-base]" ] camb = [ "camb-sdk>=1.5.4" ] cerebras = [] daily = [ "daily-python~=0.23.0" ] -deepgram = [ "deepgram-sdk~=4.7.0", "pipecat-ai[websockets-base]" ] +deepgram = [ "deepgram-sdk~=6.0.1", "pipecat-ai[websockets-base]" ] deepseek = [] elevenlabs = [ "pipecat-ai[websockets-base]" ] fal = [ "fal-client~=0.5.9" ] diff --git a/src/pipecat/services/deepgram/stt.py b/src/pipecat/services/deepgram/stt.py index 497d6aae1..e8c666d8d 100644 --- a/src/pipecat/services/deepgram/stt.py +++ b/src/pipecat/services/deepgram/stt.py @@ -6,9 +6,9 @@ """Deepgram speech-to-text service implementation.""" -import inspect -from dataclasses import dataclass, field -from typing import Any, AsyncGenerator, Dict, Mapping, Optional, Type +import asyncio +from dataclasses import dataclass, field, fields +from typing import Any, AsyncGenerator, Dict, Optional from loguru import logger @@ -33,14 +33,12 @@ from pipecat.utils.time import time_now_iso8601 from pipecat.utils.tracing.service_decorators import traced_stt try: - from deepgram import ( - AsyncListenWebSocketClient, - DeepgramClient, - DeepgramClientOptions, - ErrorResponse, - LiveOptions, - LiveResultResponse, - LiveTranscriptionEvents, + from deepgram import AsyncDeepgramClient + from deepgram.core.events import EventType + from deepgram.listen.v1.types import ( + ListenV1Results, + ListenV1SpeechStarted, + ListenV1UtteranceEnd, ) except ModuleNotFoundError as e: logger.error(f"Exception: {e}") @@ -48,166 +46,184 @@ except ModuleNotFoundError as e: raise Exception(f"Missing module: {e}") -@dataclass -class _DeepgramSTTSettingsBase(STTSettings): - """Base settings for Deepgram STT services that use ``LiveOptions``. +class LiveOptions: + """Deepgram live transcription options. - Shared by ``DeepgramSTTSettings`` and ``DeepgramSageMakerSTTSettings``. - Not intended for other Deepgram services that don't use ``LiveOptions``. - - Wraps the Deepgram SDK's ``LiveOptions`` in a single ``live_options`` - field and provides delta-merge semantics: when used as a delta (e.g. - via ``STTUpdateSettingsFrame``), only the non-None fields of - ``live_options`` are merged into the stored options rather than - replacing them wholesale. - - ``model`` and ``language`` are kept in sync bidirectionally between - the top-level settings fields and the nested ``live_options``. - - Parameters: - live_options: Deepgram ``LiveOptions`` for STT configuration. - In delta mode only its non-None fields are merged into the - stored options. + Compatibility wrapper that mirrors the ``LiveOptions`` class removed in + deepgram-sdk v6. Pass this to :class:`DeepgramSTTService` via the + ``live_options`` constructor argument. """ - live_options: LiveOptions | _NotGiven = field(default_factory=lambda: NOT_GIVEN) - - # Valid LiveOptions __init__ parameter names (cached at class level). - _live_options_params: set[str] | None = field(default=None, init=False, repr=False) - - @classmethod - def _get_live_options_params(cls) -> set[str]: - """Return the set of valid ``LiveOptions.__init__`` parameter names.""" - if cls._live_options_params is None: - cls._live_options_params = set(inspect.signature(LiveOptions.__init__).parameters) - { - "self" - } - return cls._live_options_params - - def _merge_live_options_delta(self, delta: LiveOptions) -> Dict[str, Any]: - """Merge a ``LiveOptions`` delta into the stored ``live_options``. - - Non-None fields from *delta* overwrite corresponding fields in the - stored ``LiveOptions``. ``model`` and ``language`` are synced to - the top-level settings fields when they change. + def __init__( + self, + *, + callback: Optional[str] = None, + callback_method: Optional[str] = None, + channels: Optional[int] = None, + detect_entities: Optional[bool] = None, + diarize: Optional[bool] = None, + dictation: Optional[bool] = None, + encoding: Optional[str] = None, + endpointing: Optional[Any] = None, + extra: Optional[Any] = None, + interim_results: Optional[bool] = None, + keyterm: Optional[Any] = None, + keywords: Optional[Any] = None, + language: Optional[str] = None, + mip_opt_out: Optional[bool] = None, + model: Optional[str] = None, + multichannel: Optional[bool] = None, + numerals: Optional[bool] = None, + profanity_filter: Optional[bool] = None, + punctuate: Optional[bool] = None, + redact: Optional[Any] = None, + replace: Optional[Any] = None, + sample_rate: Optional[int] = None, + search: Optional[Any] = None, + smart_format: Optional[bool] = None, + tag: Optional[Any] = None, + utterance_end_ms: Optional[int] = None, + vad_events: Optional[bool] = None, + version: Optional[str] = None, + **kwargs, + ): + """Initialize live transcription options. Args: - delta: A ``LiveOptions`` whose non-None fields are the desired - overrides. - - Returns: - Dict mapping each changed key to its **previous** value (same - contract as ``apply_update``). + callback: Callback URL for async transcription delivery. + callback_method: HTTP method to use for the callback (``"GET"`` or ``"POST"``). + channels: Number of audio channels. + detect_entities: Enable named entity detection. + diarize: Enable speaker diarization. + dictation: Enable dictation mode (converts commands to punctuation). + encoding: Audio encoding (e.g. ``"linear16"``). + endpointing: Endpointing sensitivity in ms, or ``False`` to disable. + extra: Additional key-value metadata to attach to the transcription (str or list). + interim_results: Whether to emit interim transcriptions. + keyterm: Keyterms to boost (str or list of str). + keywords: Keywords to boost (str or list of str). + language: BCP-47 language tag (e.g. ``"en-US"``). + mip_opt_out: Opt out of model improvement program. + model: Deepgram model name (e.g. ``"nova-3-general"``). + multichannel: Enable per-channel transcription for multi-channel audio. + numerals: Convert spoken numbers to numerals. + profanity_filter: Filter profanity from transcripts. + punctuate: Add punctuation to transcripts. + redact: Redact sensitive information (str or list of redaction types). + replace: Word replacement rules (str or list). + sample_rate: Audio sample rate in Hz. + search: Search terms to highlight (str or list of str). + smart_format: Apply smart formatting to transcripts. + tag: Custom billing tag (str or list of str). + utterance_end_ms: Silence duration in ms before an utterance-end event. + vad_events: Enable Deepgram VAD speech-started / utterance-end events. + version: Model version (e.g. ``"latest"``). + **kwargs: Any additional Deepgram query parameters. """ - old_dict = self.live_options.to_dict() # type: ignore[union-attr] - delta_dict = delta.to_dict() + self.callback = callback + self.callback_method = callback_method + self.channels = channels + self.detect_entities = detect_entities + self.diarize = diarize + self.dictation = dictation + self.encoding = encoding + self.endpointing = endpointing + self.extra = extra + self.interim_results = interim_results + self.keyterm = keyterm + self.keywords = keywords + self.language = language + self.mip_opt_out = mip_opt_out + self.model = model + self.multichannel = multichannel + self.numerals = numerals + self.profanity_filter = profanity_filter + self.punctuate = punctuate + self.redact = redact + self.replace = replace + self.sample_rate = sample_rate + self.search = search + self.smart_format = smart_format + self.tag = tag + self.utterance_end_ms = utterance_end_ms + self.vad_events = vad_events + self.version = version + self._extra = kwargs - # Deepgram SDK bug: model initialised to the *string* "None". - if delta_dict.get("model") == "None": - del delta_dict["model"] + def __getattr__(self, name: str): + # Fall back to _extra for any params passed as **kwargs. + # __getattr__ is only called when normal attribute lookup fails. + extra = self.__dict__.get("_extra", {}) + try: + return extra[name] + except KeyError: + raise AttributeError(f"'LiveOptions' object has no attribute '{name}'") - if not delta_dict: - return {} - - merged = {**old_dict, **delta_dict} - self.live_options = LiveOptions(**merged) - - # Track what changed. - changed: Dict[str, Any] = {} - for key in delta_dict: - old_val = old_dict.get(key, NOT_GIVEN) - if old_val != delta_dict[key]: - changed[key] = old_val - - # Sync model/language from live_options delta to top-level fields. - if "model" in delta_dict and delta_dict["model"] != self.model: - changed.setdefault("model", self.model) - self.model = delta_dict["model"] - if "language" in delta_dict and delta_dict["language"] != self.language: - changed.setdefault("language", self.language) - self.language = delta_dict["language"] - - return changed - - def apply_update(self: _S, delta: _S) -> Dict[str, Any]: - """Merge a delta into this store, with delta-merge for ``live_options``. - - ``live_options`` is merged field-by-field via - ``_merge_live_options_delta`` rather than being replaced wholesale. - - ``model`` and ``language`` are kept in sync bidirectionally between - the top-level settings fields and ``live_options``. - """ - # Pull live_options out of the delta so super() doesn't replace it. - delta_lo = getattr(delta, "live_options", NOT_GIVEN) - if is_given(delta_lo): - delta.live_options = NOT_GIVEN # type: ignore[assignment] - - # Let the base class handle model, language, extra. - changed = super().apply_update(delta) - - # Sync top-level model/language changes into stored live_options. - if "model" in changed: - self.live_options.model = self.model # type: ignore[union-attr] - if "language" in changed: - self.live_options.language = self.language # type: ignore[union-attr] - - # Merge live_options delta. Top-level model/language take precedence - # over conflicting values in live_options, so write them into the - # delta before merging. - if is_given(delta_lo): - if "model" in changed: - delta_lo.model = self.model - if "language" in changed: - delta_lo.language = self.language - - for key, old_val in self._merge_live_options_delta(delta_lo).items(): - changed.setdefault(key, old_val) - - return changed - - @classmethod - def from_mapping(cls: Type[_S], settings: Mapping[str, Any]) -> _S: - """Build a delta from a plain dict, routing LiveOptions keys correctly. - - Keys that are valid ``LiveOptions.__init__`` parameters (and not - top-level ``STTSettings`` fields like ``model`` / ``language``) are - collected into a ``LiveOptions`` object. ``model`` and ``language`` - are routed to the top-level settings fields. Truly unknown keys go - to ``extra``. - """ - lo_params = cls._get_live_options_params() - stt_field_names = {"model", "language"} - - kwargs: Dict[str, Any] = {} - lo_kwargs: Dict[str, Any] = {} - extra: Dict[str, Any] = {} - - for key, value in settings.items(): - canonical = cls._aliases.get(key, key) - if canonical in stt_field_names: - kwargs[canonical] = value - elif canonical in lo_params: - lo_kwargs[canonical] = value - else: - extra[key] = value - - if lo_kwargs: - kwargs["live_options"] = LiveOptions(**lo_kwargs) - - instance = cls(**kwargs) - instance.extra = extra - return instance + def to_dict(self) -> dict: + """Return a dict of all non-None options.""" + result = {k: v for k, v in vars(self).items() if not k.startswith("_") and v is not None} + result.update({k: v for k, v in self._extra.items() if v is not None}) + return result @dataclass -class DeepgramSTTSettings(_DeepgramSTTSettingsBase): - """Settings for the Deepgram STT service. +class DeepgramSTTSettings(STTSettings): + """Settings for Deepgram STT services. - See ``_DeepgramSTTSettingsBase`` for full documentation. + ``model`` and ``language`` are inherited from ``STTSettings`` / + ``ServiceSettings``. Additional Deepgram connection params may + be passed in through extra ``extra`` (also inherited). + + Parameters: + channels: Number of audio channels. + diarize: Enable speaker diarization. + encoding: Audio encoding (e.g. ``"linear16"``). + endpointing: Endpointing sensitivity in ms, or ``False`` to disable. + interim_results: Whether to emit interim transcriptions. + profanity_filter: Filter profanity from transcripts. + punctuate: Add punctuation to transcripts. + smart_format: Apply smart formatting to transcripts. + vad_events: Enable Deepgram VAD speech-started / utterance-end events. + extra: Additional Deepgram query parameters not covered by the fields above. """ - pass + channels: int | _NotGiven = field(default_factory=lambda: NOT_GIVEN) + diarize: bool | _NotGiven = field(default_factory=lambda: NOT_GIVEN) + encoding: str | _NotGiven = field(default_factory=lambda: NOT_GIVEN) + endpointing: Any | _NotGiven = field(default_factory=lambda: NOT_GIVEN) + interim_results: bool | _NotGiven = field(default_factory=lambda: NOT_GIVEN) + profanity_filter: bool | _NotGiven = field(default_factory=lambda: NOT_GIVEN) + punctuate: bool | _NotGiven = field(default_factory=lambda: NOT_GIVEN) + smart_format: bool | _NotGiven = field(default_factory=lambda: NOT_GIVEN) + vad_events: bool | _NotGiven = field(default_factory=lambda: NOT_GIVEN) + + def _sync_extra_to_fields(self) -> None: + """Sync values from extra dict to declared fields. + + If a key in extra matches a field name and the field is NOT_GIVEN, + promote the extra value to the field. This ensures self._settings + always reflects the "final truth" of values that will be used. + + Keys in extra that match declared fields are always removed from extra + to avoid confusion, even if the field was already set. + """ + if not self.extra: + return + + field_names = { + f.name + for f in fields(self) + if f.name not in ("extra", "model", "language") and not f.name.startswith("_") + } + + for key in list(self.extra.keys()): + if key in field_names: + current_value = getattr(self, key) + if not is_given(current_value): + # Promote extra value to the field + setattr(self, key, self.extra[key]) + # Always remove from extra to avoid ambiguity + del self.extra[key] class DeepgramSTTService(STTService): @@ -254,7 +270,7 @@ class DeepgramSTTService(STTService): base_url: Custom Deepgram API base URL. sample_rate: Audio sample rate. If None, uses default or live_options value. - live_options: Deepgram LiveOptions configuration. Treated as a + live_options: :class: LiveOptions configuration. Treated as a delta from a set of sensible defaults — only the fields you set are overridden; all others keep their default values. addons: Additional Deepgram features to enable. @@ -283,25 +299,29 @@ class DeepgramSTTService(STTService): ) base_url = url - default_options = LiveOptions( - encoding="linear16", - language=Language.EN, + settings = DeepgramSTTSettings( model="nova-3-general", + language=Language.EN, + encoding="linear16", channels=1, interim_results=True, smart_format=False, punctuate=True, profanity_filter=True, vad_events=False, + diarize=False, + endpointing=None, ) - settings = DeepgramSTTSettings( - model=default_options.model, - language=default_options.language, - live_options=default_options, - ) if live_options: - settings._merge_live_options_delta(live_options) + lo_dict = live_options.to_dict() + delta = DeepgramSTTSettings.from_mapping( + {k: v for k, v in lo_dict.items() if k != "sample_rate"} + ) + settings.apply_update(delta) + + # Sync extra to top-level fields so self._settings is unambiguous + settings._sync_extra_to_fields() super().__init__( sample_rate=sample_rate, @@ -313,7 +333,7 @@ class DeepgramSTTService(STTService): self._addons = addons self._should_interrupt = should_interrupt - if self._settings.live_options.vad_events: + if self._settings.vad_events: import warnings with warnings.catch_warnings(): @@ -325,13 +345,29 @@ class DeepgramSTTService(STTService): stacklevel=2, ) - self._client = DeepgramClient( - api_key, - config=DeepgramClientOptions( - url=base_url, - options={"keepalive": "true"}, # verbose=logging.DEBUG - ), - ) + # Build client - support optional custom base URL via DeepgramClientEnvironment + if base_url: + try: + from deepgram import DeepgramClientEnvironment + + ws_url = base_url if base_url.startswith("wss://") else f"wss://{base_url}" + http_url = base_url if base_url.startswith("https://") else f"https://{base_url}" + environment = DeepgramClientEnvironment( + base=http_url, + production=ws_url, + agent=ws_url, + ) + self._client = AsyncDeepgramClient(api_key=api_key, environment=environment) + except Exception: + logger.warning( + f"{self}: Custom base_url configuration failed, falling back to default" + ) + self._client = AsyncDeepgramClient(api_key=api_key) + else: + self._client = AsyncDeepgramClient(api_key=api_key) + + self._connection = None + self._connection_task = None if self.vad_enabled: self._register_event_handler("on_speech_started") @@ -344,7 +380,7 @@ class DeepgramSTTService(STTService): Returns: True if VAD events are enabled in the current settings. """ - return self._settings.live_options.vad_events + return self._settings.vad_events def can_generate_metrics(self) -> bool: """Check if this service can generate processing metrics. @@ -361,6 +397,10 @@ class DeepgramSTTService(STTService): if not changed: return changed + # Sync extra to fields after the update so self._settings stays unambiguous + if isinstance(self._settings, DeepgramSTTSettings): + self._settings._sync_extra_to_fields() + await self._disconnect() await self._connect() @@ -402,79 +442,126 @@ class DeepgramSTTService(STTService): Yields: Frame: None (transcription results come via WebSocket callbacks). """ - await self._connection.send(audio) + if self._connection: + await self._connection.send_media(audio) yield None + def _build_connect_kwargs(self) -> dict: + """Build keyword arguments for ``client.listen.v1.connect()`` from current settings.""" + kwargs = {} + s = self._settings + + # Declared Deepgram-specific fields + for f in fields(s): + if f.name in ("model", "language", "extra") or f.name.startswith("_"): + continue + value = getattr(s, f.name) + if not is_given(value) or value is None: + continue + kwargs[f.name] = str(value).lower() if isinstance(value, bool) else str(value) + + # model and language + if is_given(s.model) and s.model is not None: + kwargs["model"] = str(s.model) + if is_given(s.language) and s.language is not None: + kwargs["language"] = str(s.language) + + # Any remaining values in extra (that didn't map to declared fields) + for key, value in s.extra.items(): + if value is not None: + kwargs[key] = str(value).lower() if isinstance(value, bool) else str(value) + + # Always inject sample_rate from service level. + kwargs["sample_rate"] = str(self.sample_rate) + + if self._addons: + for key, value in self._addons.items(): + kwargs[key] = str(value) + + return kwargs + async def _connect(self): logger.debug("Connecting to Deepgram") - - self._connection: AsyncListenWebSocketClient = self._client.listen.asyncwebsocket.v("1") - - self._connection.on( - LiveTranscriptionEvents(LiveTranscriptionEvents.Transcript), self._on_message - ) - self._connection.on(LiveTranscriptionEvents(LiveTranscriptionEvents.Error), self._on_error) - - if self.vad_enabled: - self._connection.on( - LiveTranscriptionEvents(LiveTranscriptionEvents.SpeechStarted), - self._on_speech_started, - ) - self._connection.on( - LiveTranscriptionEvents(LiveTranscriptionEvents.UtteranceEnd), - self._on_utterance_end, - ) - - live_options = LiveOptions( - **{**self._settings.live_options.to_dict(), "sample_rate": self.sample_rate} - ) - - if not await self._connection.start(options=live_options, addons=self._addons): - await self.push_error(error_msg=f"Unable to connect to Deepgram") - else: - headers = { - k: v - for k, v in self._connection._socket.response.headers.items() - if k.startswith("dg-") - } - logger.debug(f'{self}: Websocket connection initialized: {{"headers": {headers}}}') + self._connection_task = self.create_task(self._connection_handler()) async def _disconnect(self): - if await self._connection.is_connected(): - logger.debug("Disconnecting from Deepgram") - # Deepgram swallows asyncio.CancelledError internally which prevents - # proper cancellation propagation. This issue was found with - # parallel pipelines where `CancelFrame` was not awaited for to - # finish in all branches and it was pushed downstream reaching the - # end of the pipeline, which caused `cleanup()` to be called while - # Deepgram disconnection was still finishing and therefore - # preventing the task cancellation that occurs during `cleanup()`. - # GH issue: https://github.com/deepgram/deepgram-python-sdk/issues/570 - await self._connection.finish() + if not self._connection_task: + return + + logger.debug("Disconnecting from Deepgram") + # Ask Deepgram to close the stream gracefully before cancelling the task. + if self._connection: + await self._connection.send_close_stream() + + await self.cancel_task(self._connection_task) + self._connection_task = None + self._connection = None + + async def _connection_handler(self): + """Manages the full WebSocket lifecycle inside a single async with block. + + Reconnects automatically after transient errors. Exits cleanly when + the task is cancelled (i.e. on stop/cancel). + """ + while True: + connect_kwargs = self._build_connect_kwargs() + try: + async with self._client.listen.v1.connect(**connect_kwargs) as connection: + self._connection = connection + connection.on(EventType.MESSAGE, self._on_message) + connection.on(EventType.ERROR, self._on_error) + + logger.debug(f"{self}: Websocket connection initialized") + + keepalive_task = self.create_task( + self._keepalive_handler(), f"{self}::keepalive" + ) + try: + await connection.start_listening() + finally: + await self.cancel_task(keepalive_task) + except asyncio.CancelledError: + raise + except Exception as e: + logger.warning(f"{self}: Connection lost, will retry: {e}") + finally: + self._connection = None + + async def _keepalive_handler(self): + """Periodically send KeepAlive frames to prevent server-side timeout. + + Deepgram closes inactive connections after 10 seconds (NET-0001 error). + Sending every 5 seconds stays within the recommended 3-5 second interval. + """ + while True: + await asyncio.sleep(5) + if self._connection: + try: + await self._connection.send_keep_alive() + logger.trace(f"{self}: Sent keepalive") + except Exception as e: + logger.warning(f"{self}: Keepalive failed: {e}") async def _start_metrics(self): """Start processing metrics collection for this utterance.""" await self.start_processing_metrics() - async def _on_error(self, *args, **kwargs): - error: ErrorResponse = kwargs["error"] + async def _on_error(self, error): logger.warning(f"{self} connection error, will retry: {error}") await self.push_error(error_msg=f"{error}") await self.stop_all_metrics() - # NOTE(aleix): we don't disconnect (i.e. call finish on the connection) - # because this triggers more errors internally in the Deepgram SDK. So, - # we just forget about the previous connection and create a new one. - await self._connect() + # Reconnection is handled automatically by the retry loop in + # _connection_handler once start_listening() exits after the error. - async def _on_speech_started(self, *args, **kwargs): + async def _on_speech_started(self, message): await self._start_metrics() - await self._call_event_handler("on_speech_started", *args, **kwargs) + await self._call_event_handler("on_speech_started", message) await self.broadcast_frame(UserStartedSpeakingFrame) if self._should_interrupt: await self.push_interruption_task_frame_and_wait() - async def _on_utterance_end(self, *args, **kwargs): - await self._call_event_handler("on_utterance_end", *args, **kwargs) + async def _on_utterance_end(self, message): + await self._call_event_handler("on_utterance_end", message) await self.broadcast_frame(UserStoppedSpeakingFrame) @traced_stt @@ -484,45 +571,51 @@ class DeepgramSTTService(STTService): """Handle a transcription result with tracing.""" pass - async def _on_message(self, *args, **kwargs): - result: LiveResultResponse = kwargs["result"] - if len(result.channel.alternatives) == 0: - return - is_final = result.is_final - transcript = result.channel.alternatives[0].transcript - language = None - if result.channel.alternatives[0].languages: - language = result.channel.alternatives[0].languages[0] - language = Language(language) - if len(transcript) > 0: - if is_final: - # Check if this response is from a finalize() call. - # Only mark as finalized when both we requested it AND Deepgram confirms it. - from_finalize = getattr(result, "from_finalize", False) - if from_finalize: - self.confirm_finalize() - await self.push_frame( - TranscriptionFrame( - transcript, - self._user_id, - time_now_iso8601(), - language, - result=result, + async def _on_message(self, message): + if isinstance(message, ListenV1SpeechStarted): + if self.vad_enabled: + await self._on_speech_started(message) + elif isinstance(message, ListenV1UtteranceEnd): + if self.vad_enabled: + await self._on_utterance_end(message) + elif isinstance(message, ListenV1Results): + if not message.channel or len(message.channel.alternatives) == 0: + return + is_final = message.is_final + transcript = message.channel.alternatives[0].transcript + language = None + if message.channel.alternatives[0].languages: + language = message.channel.alternatives[0].languages[0] + language = Language(language) + if len(transcript) > 0: + if is_final: + # Check if this response is from a finalize() call. + # Only mark as finalized when both we requested it AND Deepgram confirms it. + from_finalize = getattr(message, "from_finalize", False) or False + if from_finalize: + self.confirm_finalize() + await self.push_frame( + TranscriptionFrame( + transcript, + self._user_id, + time_now_iso8601(), + language, + result=message, + ) ) - ) - await self._handle_transcription(transcript, is_final, language) - await self.stop_processing_metrics() - else: - # For interim transcriptions, just push the frame without tracing - await self.push_frame( - InterimTranscriptionFrame( - transcript, - self._user_id, - time_now_iso8601(), - language, - result=result, + await self._handle_transcription(transcript, is_final, language) + await self.stop_processing_metrics() + else: + # For interim transcriptions, just push the frame without tracing + await self.push_frame( + InterimTranscriptionFrame( + transcript, + self._user_id, + time_now_iso8601(), + language, + result=message, + ) ) - ) async def process_frame(self, frame: Frame, direction: FrameDirection): """Process frames with Deepgram-specific handling. @@ -539,6 +632,7 @@ class DeepgramSTTService(STTService): elif isinstance(frame, VADUserStoppedSpeakingFrame): # https://developers.deepgram.com/docs/finalize # Mark that we're awaiting a from_finalize response - self.request_finalize() - await self._connection.finalize() - logger.trace(f"Triggered finalize event on: {frame.name=}, {direction=}") + if self._connection: + self.request_finalize() + await self._connection.send_finalize() + logger.trace(f"Triggered finalize event on: {frame.name=}, {direction=}") diff --git a/src/pipecat/services/deepgram/stt_sagemaker.py b/src/pipecat/services/deepgram/stt_sagemaker.py index ba4b7dfda..0b72b98ab 100644 --- a/src/pipecat/services/deepgram/stt_sagemaker.py +++ b/src/pipecat/services/deepgram/stt_sagemaker.py @@ -32,7 +32,7 @@ from pipecat.frames.frames import ( ) from pipecat.processors.frame_processor import FrameDirection from pipecat.services.aws.sagemaker.bidi_client import SageMakerBidiClient -from pipecat.services.deepgram.stt import _DeepgramSTTSettingsBase +from pipecat.services.deepgram.stt import DeepgramSTTSettings from pipecat.services.settings import STTSettings from pipecat.services.stt_latency import DEEPGRAM_SAGEMAKER_TTFS_P99 from pipecat.services.stt_service import STTService @@ -41,7 +41,7 @@ from pipecat.utils.time import time_now_iso8601 from pipecat.utils.tracing.service_decorators import traced_stt try: - from deepgram import LiveOptions + from pipecat.services.deepgram.stt import LiveOptions except ModuleNotFoundError as e: logger.error(f"Exception: {e}") logger.error( @@ -51,10 +51,10 @@ except ModuleNotFoundError as e: @dataclass -class DeepgramSageMakerSTTSettings(_DeepgramSTTSettingsBase): +class DeepgramSageMakerSTTSettings(DeepgramSTTSettings): """Settings for the Deepgram SageMaker STT service. - See ``_DeepgramSTTSettingsBase`` for full documentation. + See ``DeepgramSTTSettings`` for full documentation. """ pass @@ -117,22 +117,21 @@ class DeepgramSageMakerSTTService(STTService): """ sample_rate = sample_rate or (live_options.sample_rate if live_options else None) - default_options = LiveOptions( - encoding="linear16", - language=Language.EN, + settings = DeepgramSageMakerSTTSettings( model="nova-3", + language=Language.EN, + encoding="linear16", channels=1, interim_results=True, punctuate=True, ) - settings = DeepgramSageMakerSTTSettings( - model=default_options.model, - language=default_options.language, - live_options=default_options, - ) if live_options: - settings._merge_live_options_delta(live_options) + lo_dict = live_options.to_dict() + delta = DeepgramSageMakerSTTSettings.from_mapping( + {k: v for k, v in lo_dict.items() if k != "sample_rate"} + ) + settings.apply_update(delta) super().__init__( sample_rate=sample_rate, @@ -224,9 +223,8 @@ class DeepgramSageMakerSTTService(STTService): """ logger.debug("Connecting to Deepgram on SageMaker...") - live_options = LiveOptions( - **{**self._settings.live_options.to_dict(), "sample_rate": self.sample_rate} - ) + # Reconstruct a LiveOptions from the flat settings to build the query string. + live_options = LiveOptions(**self._settings.given_fields()) # Build query string from live_options, converting booleans to strings query_params = {} @@ -237,6 +235,7 @@ class DeepgramSageMakerSTTService(STTService): query_params[key] = str(value).lower() else: query_params[key] = str(value) + query_params["sample_rate"] = str(self.sample_rate) query_string = "&".join(f"{k}={v}" for k, v in query_params.items()) diff --git a/tests/test_settings.py b/tests/test_settings.py index 47cb6e4cf..ce3e35af0 100644 --- a/tests/test_settings.py +++ b/tests/test_settings.py @@ -6,10 +6,11 @@ """Tests for the typed settings infrastructure in pipecat.services.settings.""" -import pytest -from deepgram import LiveOptions +from unittest.mock import patch -from pipecat.services.deepgram.stt import DeepgramSTTSettings +import pytest + +from pipecat.services.deepgram.stt import DeepgramSTTService, DeepgramSTTSettings from pipecat.services.deepgram.stt_sagemaker import DeepgramSageMakerSTTSettings from pipecat.services.settings import ( NOT_GIVEN, @@ -317,14 +318,16 @@ class TestRoundtrip: # --------------------------------------------------------------------------- -# DeepgramSTTSettings: live_options delta merge +# DeepgramSTTSettings: flat field apply_update # --------------------------------------------------------------------------- class TestDeepgramSTTSettingsApplyUpdate: - def _make_store(self, **lo_kwargs) -> DeepgramSTTSettings: + def _make_store(self, **kwargs) -> DeepgramSTTSettings: """Helper to build a store-mode DeepgramSTTSettings.""" defaults = dict( + model="nova-3-general", + language="en", encoding="linear16", channels=1, interim_results=True, @@ -333,52 +336,25 @@ class TestDeepgramSTTSettingsApplyUpdate: profanity_filter=True, vad_events=False, ) - defaults.update(lo_kwargs) - s = DeepgramSTTSettings( - model="nova-3-general", - language="en", - live_options=LiveOptions(**defaults), - ) - return s + defaults.update(kwargs) + return DeepgramSTTSettings(**defaults) - def test_apply_update_merges_live_options_as_delta(self): - """Only the given fields in the delta LiveOptions are merged.""" + def test_apply_update_merges_flat_fields_as_delta(self): + """Only the given fields in the delta are merged.""" current = self._make_store() - assert current.live_options.punctuate is True + assert current.punctuate is True - delta = DeepgramSTTSettings(live_options=LiveOptions(punctuate=False)) + delta = DeepgramSTTSettings(punctuate=False) changed = current.apply_update(delta) - assert current.live_options.punctuate is False + assert current.punctuate is False assert "punctuate" in changed # Other fields are untouched - assert current.live_options.encoding == "linear16" - assert current.live_options.channels == 1 + assert current.encoding == "linear16" + assert current.channels == 1 - def test_apply_update_syncs_model_from_live_options_to_top_level(self): - """model inside live_options delta should sync to top-level model.""" - current = self._make_store() - assert current.model == "nova-3-general" - - delta = DeepgramSTTSettings(live_options=LiveOptions(model="nova-2")) - changed = current.apply_update(delta) - - assert current.model == "nova-2" - assert "model" in changed - - def test_apply_update_syncs_language_from_live_options_to_top_level(self): - """language inside live_options delta should sync to top-level language.""" - current = self._make_store() - assert current.language == "en" - - delta = DeepgramSTTSettings(live_options=LiveOptions(language="es")) - changed = current.apply_update(delta) - - assert current.language == "es" - assert "language" in changed - - def test_apply_update_syncs_top_level_model_into_live_options(self): - """Top-level model change should propagate into stored live_options.""" + def test_apply_update_model(self): + """model field is updated directly.""" current = self._make_store() assert current.model == "nova-3-general" @@ -386,86 +362,64 @@ class TestDeepgramSTTSettingsApplyUpdate: changed = current.apply_update(delta) assert current.model == "nova-2" - assert current.live_options.model == "nova-2" assert "model" in changed - def test_apply_update_syncs_top_level_language_into_live_options(self): - """Top-level language change should propagate into stored live_options.""" + def test_apply_update_language(self): + """language field is updated directly.""" current = self._make_store() + assert current.language == "en" - delta = DeepgramSTTSettings(language="fr") + delta = DeepgramSTTSettings(language="es") changed = current.apply_update(delta) - assert current.language == "fr" - assert current.live_options.language == "fr" + assert current.language == "es" assert "language" in changed def test_apply_update_no_change(self): """Delta with same values should report no changes.""" current = self._make_store() - delta = DeepgramSTTSettings(live_options=LiveOptions(punctuate=True)) + delta = DeepgramSTTSettings(punctuate=True) changed = current.apply_update(delta) assert changed == {} - def test_apply_update_top_level_model_takes_precedence_over_live_options(self): - """When both top-level model and live_options.model are set, top-level wins.""" + def test_apply_update_multiple_fields(self): + """Multiple flat fields updated at once.""" current = self._make_store() - assert current.model == "nova-3-general" - delta = DeepgramSTTSettings( - model="nova-2", - live_options=LiveOptions(model="nova-3"), - ) + delta = DeepgramSTTSettings(model="nova-2", language="fr", punctuate=False) changed = current.apply_update(delta) assert current.model == "nova-2" - assert current.live_options.model == "nova-2" - assert "model" in changed - - def test_apply_update_top_level_language_takes_precedence_over_live_options(self): - """When both top-level language and live_options.language are set, top-level wins.""" - current = self._make_store() - assert current.language == "en" - - delta = DeepgramSTTSettings( - language="fr", - live_options=LiveOptions(language="es"), - ) - changed = current.apply_update(delta) - assert current.language == "fr" - assert current.live_options.language == "fr" - assert "language" in changed + assert current.punctuate is False + assert changed.keys() == {"model", "language", "punctuate"} class TestDeepgramSTTSettingsFromMapping: - def test_routes_live_options_kwargs(self): - """LiveOptions-valid keys should be collected into live_options.""" - delta = DeepgramSTTSettings.from_mapping({"punctuate": False, "filler_words": True}) - assert is_given(delta.live_options) - assert delta.live_options.punctuate is False - assert delta.live_options.filler_words is True + def test_known_flat_fields_mapped_directly(self): + """Deepgram field names map directly to flat settings fields.""" + delta = DeepgramSTTSettings.from_mapping({"punctuate": False, "diarize": True}) + assert delta.punctuate is False + assert delta.diarize is True - def test_routes_model_and_language_to_top_level(self): - """model and language should be top-level fields, not in live_options.""" + def test_model_and_language_top_level(self): + """model and language are top-level fields.""" delta = DeepgramSTTSettings.from_mapping({"model": "nova-2", "language": "es"}) assert delta.model == "nova-2" assert delta.language == "es" - assert not is_given(delta.live_options) def test_unknown_keys_go_to_extra(self): - """Keys that aren't LiveOptions params or STT fields go to extra.""" + """Keys that aren't declared fields go to extra.""" delta = DeepgramSTTSettings.from_mapping({"unknown_param": 42}) assert delta.extra == {"unknown_param": 42} - assert not is_given(delta.live_options) def test_mixed_keys(self): - """model + LiveOptions keys + unknown keys are routed correctly.""" + """model + known Deepgram fields + unknown keys are routed correctly.""" delta = DeepgramSTTSettings.from_mapping( {"model": "nova-2", "punctuate": False, "unknown": "val"} ) assert delta.model == "nova-2" - assert delta.live_options.punctuate is False + assert delta.punctuate is False assert delta.extra == {"unknown": "val"} def test_roundtrip_from_mapping_apply_update(self): @@ -473,33 +427,32 @@ class TestDeepgramSTTSettingsFromMapping: current = DeepgramSTTSettings( model="nova-3-general", language="en", - live_options=LiveOptions( - encoding="linear16", - channels=1, - interim_results=True, - punctuate=True, - profanity_filter=True, - vad_events=False, - ), + encoding="linear16", + channels=1, + interim_results=True, + punctuate=True, + profanity_filter=True, + vad_events=False, ) - raw = {"punctuate": False, "filler_words": True} + raw = {"punctuate": False, "diarize": True} delta = DeepgramSTTSettings.from_mapping(raw) changed = current.apply_update(delta) - assert current.live_options.punctuate is False - assert current.live_options.filler_words is True + assert current.punctuate is False + assert current.diarize is True # Unchanged fields stay put - assert current.live_options.encoding == "linear16" + assert current.encoding == "linear16" assert current.model == "nova-3-general" assert "punctuate" in changed def test_roundtrip_model_via_dict(self): - """Dict update with model should change top-level and NOT create live_options.""" + """Dict update with model should change top-level model field.""" current = DeepgramSTTSettings( model="nova-3-general", language="en", - live_options=LiveOptions(encoding="linear16", channels=1), + encoding="linear16", + channels=1, ) raw = {"model": "nova-2"} @@ -507,26 +460,167 @@ class TestDeepgramSTTSettingsFromMapping: changed = current.apply_update(delta) assert current.model == "nova-2" - assert current.live_options.model == "nova-2" assert "model" in changed # --------------------------------------------------------------------------- -# DeepgramSageMakerSTTSettings: smoke test that the shared base is inherited +# DeepgramSageMakerSTTSettings: smoke test that flat base is inherited # --------------------------------------------------------------------------- class TestDeepgramSageMakerSTTSettings: - def test_inherits_live_options_behavior(self): - """Smoke test: SageMaker settings inherit the shared base correctly.""" + def test_inherits_flat_settings_behavior(self): + """Smoke test: SageMaker settings inherit the flat base correctly.""" store = DeepgramSageMakerSTTSettings( model="nova-3", language="en", - live_options=LiveOptions(encoding="linear16", channels=1, punctuate=True), + encoding="linear16", + channels=1, + punctuate=True, ) - delta = DeepgramSageMakerSTTSettings(live_options=LiveOptions(punctuate=False)) + delta = DeepgramSageMakerSTTSettings(punctuate=False) changed = store.apply_update(delta) - assert store.live_options.punctuate is False - assert store.live_options.encoding == "linear16" + assert store.punctuate is False + assert store.encoding == "linear16" assert "punctuate" in changed + + +# --------------------------------------------------------------------------- +# DeepgramSTTService: settings initialization with extra syncing +# --------------------------------------------------------------------------- + + +class TestDeepgramSTTSettingsExtraSync: + """Test that settings.extra values are synced to declared fields at init time.""" + + def _make_service(self, **kwargs): + with patch("pipecat.services.deepgram.stt.AsyncDeepgramClient"): + return DeepgramSTTService(api_key="test-key", sample_rate=16000, **kwargs) + + def test_extra_synced_to_declared_field_at_init(self): + """If LiveOptions has unknown params in _extra, they can be synced if they match fields.""" + from pipecat.services.deepgram.stt import LiveOptions + + # Use **kwargs to pass undeclared params + live_options = LiveOptions(numerals=True) # 'numerals' goes into _extra + + svc = self._make_service(live_options=live_options) + + # 'numerals' doesn't match a declared DeepgramSTTSettings field, + # so it should stay in extra + assert svc._settings.extra["numerals"] is True + + def test_declared_field_from_live_options(self): + """LiveOptions fields that match DeepgramSTTSettings fields are applied.""" + from pipecat.services.deepgram.stt import LiveOptions + + live_options = LiveOptions( + punctuate=False, + diarize=True, + ) + + svc = self._make_service(live_options=live_options) + + # These should be in the declared fields + assert svc._settings.punctuate is False + assert svc._settings.diarize is True + + def test_sync_after_from_mapping_with_extra(self): + """If we use from_mapping with keys matching declared fields, they sync.""" + # Simulate a dict-style update with both declared and undeclared keys + raw_dict = { + "diarize": True, # matches declared field + "punctuate": False, # matches declared field + "numerals": True, # doesn't match - stays in extra + } + + delta = DeepgramSTTSettings.from_mapping(raw_dict) + + # After from_mapping, declared fields should be set + assert delta.diarize is True + assert delta.punctuate is False + # Unknown stays in extra + assert delta.extra["numerals"] is True + + # Now simulate syncing (though from_mapping already routes correctly) + delta._sync_extra_to_fields() + + # Still the same - from_mapping already put them in the right place + assert delta.diarize is True + assert delta.punctuate is False + assert delta.extra["numerals"] is True + + def test_sync_promotes_extra_to_field_when_not_given(self): + """_sync_extra_to_fields promotes extra dict entries to declared fields.""" + settings = DeepgramSTTSettings() + # Manually populate extra with a key matching a declared field + settings.extra = {"diarize": True, "punctuate": False, "unknown": "value"} + + # Before sync, fields are NOT_GIVEN + assert not is_given(settings.diarize) + assert not is_given(settings.punctuate) + + # Sync it + settings._sync_extra_to_fields() + + # Now the matching fields should be promoted + assert settings.diarize is True + assert settings.punctuate is False + # And removed from extra + assert "diarize" not in settings.extra + assert "punctuate" not in settings.extra + # Unknown stays + assert settings.extra["unknown"] == "value" + + def test_sync_doesnt_overwrite_already_set_field(self): + """If a field is already set, extra shouldn't overwrite it.""" + settings = DeepgramSTTSettings(punctuate=True) + # Try to put a different value in extra + settings.extra = {"punctuate": False} + + # Sync + settings._sync_extra_to_fields() + + # The already-set field should win + assert settings.punctuate is True + # extra entry should still be removed to avoid confusion + assert "punctuate" not in settings.extra + + def test_build_connect_kwargs_after_sync(self): + """After syncing, _build_connect_kwargs should use the right values.""" + from pipecat.services.deepgram.stt import LiveOptions + + live_options = LiveOptions( + model="nova-2", + language="es", + punctuate=True, + diarize=False, + ) + + svc = self._make_service(live_options=live_options) + kwargs = svc._build_connect_kwargs() + + # All should appear in connect kwargs + assert kwargs["model"] == "nova-2" + assert kwargs["language"] == "es" + assert kwargs["punctuate"] == "true" + assert kwargs["diarize"] == "false" + + def test_unknown_params_stay_in_extra_and_appear_in_kwargs(self): + """Unknown params (not matching fields) stay in extra and get forwarded.""" + from pipecat.services.deepgram.stt import LiveOptions + + # numerals isn't a declared field in DeepgramSTTSettings + live_options = LiveOptions(numerals=True, custom_param="test") + + svc = self._make_service(live_options=live_options) + + # Should be in extra + assert svc._settings.extra["numerals"] is True + assert svc._settings.extra["custom_param"] == "test" + + # And forwarded to kwargs + kwargs = svc._build_connect_kwargs() + assert kwargs["numerals"] == "true" + assert kwargs["custom_param"] == "test" diff --git a/uv.lock b/uv.lock index 49cfa089b..4756deb46 100644 --- a/uv.lock +++ b/uv.lock @@ -28,15 +28,6 @@ wheels = [ { url = "https://files.pythonhosted.org/packages/5f/a0/d9ef19f780f319c21ee90ecfef4431cbeeca95bec7f14071785c17b6029b/accelerate-1.10.1-py3-none-any.whl", hash = "sha256:3621cff60b9a27ce798857ece05e2b9f56fcc71631cfb31ccf71f0359c311f11", size = 374909, upload-time = "2025-08-25T13:57:04.55Z" }, ] -[[package]] -name = "aenum" -version = "3.1.16" -source = { registry = "https://pypi.org/simple" } -sdist = { url = "https://files.pythonhosted.org/packages/09/7a/61ed58e8be9e30c3fe518899cc78c284896d246d51381bab59b5db11e1f3/aenum-3.1.16.tar.gz", hash = "sha256:bfaf9589bdb418ee3a986d85750c7318d9d2839c1b1a1d6fe8fc53ec201cf140", size = 137693, upload-time = "2026-01-12T22:34:38.819Z" } -wheels = [ - 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{ name = "deepgram-sdk", marker = "extra == 'deepgram'", specifier = "~=4.7.0" }, + { name = "deepgram-sdk", marker = "extra == 'deepgram'", specifier = "~=6.0.1" }, { name = "docstring-parser", specifier = "~=0.16" }, { name = "einops", marker = "extra == 'moondream'", specifier = "~=0.8.0" }, { name = "fal-client", marker = "extra == 'fal'", specifier = "~=0.5.9" }, From f386722ef9dfd038ae1fe4100b7671086cd02023 Mon Sep 17 00:00:00 2001 From: dhruvladia-sarvam Date: Mon, 2 Mar 2026 20:38:39 +0530 Subject: [PATCH 0729/1060] removing unnecessary logs --- src/pipecat/services/sarvam/stt.py | 5 +---- src/pipecat/services/sarvam/tts.py | 1 - 2 files changed, 1 insertion(+), 5 deletions(-) diff --git a/src/pipecat/services/sarvam/stt.py b/src/pipecat/services/sarvam/stt.py index f4ebf7574..9e245aece 100644 --- a/src/pipecat/services/sarvam/stt.py +++ b/src/pipecat/services/sarvam/stt.py @@ -516,10 +516,7 @@ class SarvamSTTService(STTService): # Headers are supplied through request_options because this is a # documented SDK parameter that survives SDK signature changes. request_options = {"additional_headers": self._sdk_headers} - logger.debug( - f"Sarvam STT connect request_options.additional_headers: " - f"{request_options['additional_headers']}" - ) + attempts = [kwargs] if "prompt" in kwargs: attempts.append({k: v for k, v in kwargs.items() if k != "prompt"}) diff --git a/src/pipecat/services/sarvam/tts.py b/src/pipecat/services/sarvam/tts.py index e92ade2e5..c18933407 100644 --- a/src/pipecat/services/sarvam/tts.py +++ b/src/pipecat/services/sarvam/tts.py @@ -1021,7 +1021,6 @@ class SarvamTTSService(InterruptibleTTSService): self._websocket = await websocket_connect( self._websocket_url, additional_headers=ws_additional_headers, - user_agent_header=None, ) logger.debug("Connected to Sarvam TTS Websocket") await self._send_config() From c54232bdb40c28c7e28e1600bd3492212ff4b6cc Mon Sep 17 00:00:00 2001 From: Mark Backman Date: Sat, 28 Feb 2026 14:04:21 -0500 Subject: [PATCH 0730/1060] Add StartupTimingObserver for measuring processor start() times Tracks how long each processor start method takes during pipeline startup by measuring StartFrame arrive/leave deltas. Emits a timing report via the on_startup_timing_report event and auto-logs a summary. Internal pipeline processors are excluded from reports by default. --- .../foundational/29-turn-tracking-observer.py | 12 +- .../observers/startup_timing_observer.py | 232 ++++++++++++++++++ tests/test_startup_timing_observer.py | 186 ++++++++++++++ 3 files changed, 427 insertions(+), 3 deletions(-) create mode 100644 src/pipecat/observers/startup_timing_observer.py create mode 100644 tests/test_startup_timing_observer.py diff --git a/examples/foundational/29-turn-tracking-observer.py b/examples/foundational/29-turn-tracking-observer.py index 321197db2..3e85ddfb8 100644 --- a/examples/foundational/29-turn-tracking-observer.py +++ b/examples/foundational/29-turn-tracking-observer.py @@ -12,6 +12,7 @@ from loguru import logger from pipecat.audio.vad.silero import SileroVADAnalyzer from pipecat.frames.frames import LLMRunFrame +from pipecat.observers.startup_timing_observer import StartupTimingObserver from pipecat.observers.user_bot_latency_observer import UserBotLatencyObserver from pipecat.pipeline.pipeline import Pipeline from pipecat.pipeline.runner import PipelineRunner @@ -87,8 +88,8 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): ] ) - # Create latency tracking observer latency_observer = UserBotLatencyObserver() + startup_observer = StartupTimingObserver() task = PipelineTask( pipeline, @@ -97,14 +98,19 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): enable_usage_metrics=True, ), idle_timeout_secs=runner_args.pipeline_idle_timeout_secs, - observers=[latency_observer], + observers=[latency_observer, startup_observer], ) - # Log latency measurements using the event handler @latency_observer.event_handler("on_latency_measured") async def on_latency_measured(observer, latency_seconds): logger.info(f"⏱️ User-to-bot latency: {latency_seconds:.3f}s") + @startup_observer.event_handler("on_startup_timing_report") + async def on_startup_timing_report(observer, report): + logger.info(f"Total startup: {report.total_duration_secs:.3f}s") + for timing in report.processor_timings: + logger.info(f" {timing.processor_name}: {timing.duration_secs:.3f}s") + turn_observer = task.turn_tracking_observer if turn_observer: diff --git a/src/pipecat/observers/startup_timing_observer.py b/src/pipecat/observers/startup_timing_observer.py new file mode 100644 index 000000000..0f3ad0b7a --- /dev/null +++ b/src/pipecat/observers/startup_timing_observer.py @@ -0,0 +1,232 @@ +# +# Copyright (c) 2024-2026, Daily +# +# SPDX-License-Identifier: BSD 2-Clause License +# + +"""Observer for tracking pipeline startup timing. + +This module provides an observer that measures how long each processor's +``start()`` method takes during pipeline startup. It works by tracking +when a ``StartFrame`` arrives at a processor (``on_process_frame``) versus +when it leaves (``on_push_frame``), giving the exact ``start()`` duration +for each processor in the pipeline. + +Example:: + + observer = StartupTimingObserver() + + @observer.event_handler("on_startup_timing_report") + async def on_report(observer, report): + for t in report.processor_timings: + print(f"{t.processor_name}: {t.duration_secs:.3f}s") + + task = PipelineTask(pipeline, observers=[observer]) +""" + +from dataclasses import dataclass, field +from typing import Dict, List, Optional, Tuple, Type + +from loguru import logger + +from pipecat.frames.frames import StartFrame +from pipecat.observers.base_observer import BaseObserver, FrameProcessed, FramePushed +from pipecat.pipeline.base_pipeline import BasePipeline +from pipecat.pipeline.pipeline import PipelineSink, PipelineSource +from pipecat.processors.frame_processor import FrameDirection, FrameProcessor + +# Internal pipeline types excluded from tracking by default. +_INTERNAL_TYPES = (PipelineSink, PipelineSource, BasePipeline) + + +@dataclass +class ProcessorStartupTiming: + """Startup timing for a single processor. + + Parameters: + processor_name: The name of the processor. + duration_secs: How long the processor's start() took, in seconds. + """ + + processor_name: str + duration_secs: float + + +@dataclass +class StartupTimingReport: + """Report of startup timings for all measured processors. + + Parameters: + total_duration_secs: Total wall-clock time from first to last processor start. + processor_timings: Per-processor timing data, in pipeline order. + """ + + total_duration_secs: float + processor_timings: List[ProcessorStartupTiming] = field(default_factory=list) + + +class StartupTimingObserver(BaseObserver): + """Observer that measures processor startup times during pipeline initialization. + + Tracks how long each processor's ``start()`` method takes by measuring the + time between when a ``StartFrame`` arrives at a processor and when it is + pushed downstream. This captures WebSocket connections, API authentication, + model loading, and other initialization work. + + By default, internal pipeline processors (``PipelineSource``, ``PipelineSink``, + ``Pipeline``) are excluded from the report. Pass ``processor_types`` to + measure only specific types. + + Event handlers available: + + - on_startup_timing_report: Called once after startup completes with the full + timing report. + + Example:: + + observer = StartupTimingObserver( + processor_types=(STTService, TTSService) + ) + + @observer.event_handler("on_startup_timing_report") + async def on_report(observer, report): + for t in report.processor_timings: + logger.info(f"{t.processor_name}: {t.duration_secs:.3f}s") + + task = PipelineTask(pipeline, observers=[observer]) + + Args: + processor_types: Optional tuple of processor types to measure. If None, + all non-internal processors are measured. + """ + + def __init__( + self, + *, + processor_types: Optional[Tuple[Type[FrameProcessor], ...]] = None, + **kwargs, + ): + """Initialize the startup timing observer. + + Args: + processor_types: Optional tuple of processor types to measure. + If None, all non-internal processors are measured. + **kwargs: Additional arguments passed to parent class. + """ + super().__init__(**kwargs) + self._processor_types = processor_types + + # Map processor ID -> (processor, arrival_timestamp_ns) + self._arrivals: Dict[int, Tuple[FrameProcessor, int]] = {} + + # Collected timings in pipeline order. + self._timings: List[ProcessorStartupTiming] = [] + + # Lock onto the first StartFrame we see (by frame ID). + self._start_frame_id: Optional[str] = None + + # Whether we've already emitted the report. + self._reported = False + + self._register_event_handler("on_startup_timing_report") + + def _should_track(self, processor: FrameProcessor) -> bool: + """Check if a processor should be tracked for timing. + + Args: + processor: The processor to check. + + Returns: + True if the processor matches the filter or no filter is set. + """ + if self._processor_types is not None: + return isinstance(processor, self._processor_types) + # Default: exclude internal pipeline plumbing. + return not isinstance(processor, _INTERNAL_TYPES) + + async def on_process_frame(self, data: FrameProcessed): + """Record when a StartFrame arrives at a processor. + + When a ``StartFrame`` reaches a ``PipelineSink``, startup is complete + (the frame has traversed the entire pipeline) and the report is emitted. + + Args: + data: The frame processing event data. + """ + if self._reported: + return + + if not isinstance(data.frame, StartFrame): + return + + if data.direction != FrameDirection.DOWNSTREAM: + return + + # Lock onto the first StartFrame. + if self._start_frame_id is None: + self._start_frame_id = data.frame.id + elif data.frame.id != self._start_frame_id: + return + + # When the StartFrame reaches a PipelineSink, all processors have + # completed start(). PipelineSinks use direct mode so the outermost + # sink fires last within the same synchronous call chain. + if isinstance(data.processor, PipelineSink): + if self._timings: + await self._emit_report() + return + + if self._should_track(data.processor): + self._arrivals[data.processor.id] = (data.processor, data.timestamp) + + async def on_push_frame(self, data: FramePushed): + """Record when a StartFrame leaves a processor and compute the delta. + + Args: + data: The frame push event data. + """ + if self._reported: + return + + if not isinstance(data.frame, StartFrame): + return + + if data.direction != FrameDirection.DOWNSTREAM: + return + + if self._start_frame_id is not None and data.frame.id != self._start_frame_id: + return + + arrival = self._arrivals.pop(data.source.id, None) + if arrival is None: + return + + processor, arrival_ts = arrival + duration_ns = data.timestamp - arrival_ts + duration_secs = duration_ns / 1e9 + + self._timings.append( + ProcessorStartupTiming( + processor_name=processor.name, + duration_secs=duration_secs, + ) + ) + + async def _emit_report(self): + """Build and emit the startup timing report.""" + if self._reported: + return + self._reported = True + + total = sum(t.duration_secs for t in self._timings) + + report = StartupTimingReport( + total_duration_secs=total, + processor_timings=self._timings, + ) + + logger.debug(f"Pipeline startup completed in {total:.3f}s") + for t in self._timings: + logger.debug(f" {t.processor_name}: {t.duration_secs:.3f}s") + + await self._call_event_handler("on_startup_timing_report", report) diff --git a/tests/test_startup_timing_observer.py b/tests/test_startup_timing_observer.py new file mode 100644 index 000000000..e3cd7c2b7 --- /dev/null +++ b/tests/test_startup_timing_observer.py @@ -0,0 +1,186 @@ +import asyncio +import unittest + +from pipecat.frames.frames import Frame, StartFrame, TextFrame +from pipecat.observers.startup_timing_observer import ( + StartupTimingObserver, + StartupTimingReport, +) +from pipecat.processors.frame_processor import FrameDirection, FrameProcessor +from pipecat.tests.utils import run_test + + +class SlowStartProcessor(FrameProcessor): + """A processor that sleeps during start to simulate slow initialization.""" + + def __init__(self, delay: float = 0.1, **kwargs): + super().__init__(**kwargs) + self._delay = delay + + async def process_frame(self, frame: Frame, direction: FrameDirection): + await super().process_frame(frame, direction) + if isinstance(frame, StartFrame): + await asyncio.sleep(self._delay) + await self.push_frame(frame, direction) + + +class FastProcessor(FrameProcessor): + """A processor with no start delay.""" + + async def process_frame(self, frame: Frame, direction: FrameDirection): + await super().process_frame(frame, direction) + await self.push_frame(frame, direction) + + +class TestStartupTimingObserver(unittest.IsolatedAsyncioTestCase): + """Tests for StartupTimingObserver.""" + + async def test_timing_reported(self): + """Test that startup timing is measured and reported.""" + observer = StartupTimingObserver() + processor = SlowStartProcessor(delay=0.1) + + reports = [] + + @observer.event_handler("on_startup_timing_report") + async def on_report(obs, report): + reports.append(report) + + frames_to_send = [TextFrame(text="hello")] + + await run_test( + processor, + frames_to_send=frames_to_send, + expected_down_frames=[TextFrame], + observers=[observer], + ) + + self.assertEqual(len(reports), 1) + report = reports[0] + self.assertGreater(report.total_duration_secs, 0) + self.assertGreater(len(report.processor_timings), 0) + + # Find our slow processor in the timings. + slow_timings = [ + t for t in report.processor_timings if "SlowStartProcessor" in t.processor_name + ] + self.assertEqual(len(slow_timings), 1) + self.assertGreaterEqual(slow_timings[0].duration_secs, 0.05) + + async def test_processor_types_filter(self): + """Test that processor_types filter limits which processors appear.""" + observer = StartupTimingObserver(processor_types=(SlowStartProcessor,)) + processor = SlowStartProcessor(delay=0.05) + + reports = [] + + @observer.event_handler("on_startup_timing_report") + async def on_report(obs, report): + reports.append(report) + + frames_to_send = [TextFrame(text="hello")] + + await run_test( + processor, + frames_to_send=frames_to_send, + expected_down_frames=[TextFrame], + observers=[observer], + ) + + self.assertEqual(len(reports), 1) + report = reports[0] + + # Only SlowStartProcessor should be in the timings. + for t in report.processor_timings: + self.assertIn("SlowStartProcessor", t.processor_name) + + async def test_report_emits_once(self): + """Test that the report is emitted only once even with multiple frames.""" + observer = StartupTimingObserver() + processor = FastProcessor() + + reports = [] + + @observer.event_handler("on_startup_timing_report") + async def on_report(obs, report): + reports.append(report) + + frames_to_send = [ + TextFrame(text="first"), + TextFrame(text="second"), + TextFrame(text="third"), + ] + + await run_test( + processor, + frames_to_send=frames_to_send, + expected_down_frames=[TextFrame, TextFrame, TextFrame], + observers=[observer], + ) + + self.assertEqual(len(reports), 1) + + async def test_event_handler_receives_report(self): + """Test that the event handler receives a proper StartupTimingReport.""" + observer = StartupTimingObserver() + processor = SlowStartProcessor(delay=0.05) + + reports = [] + + @observer.event_handler("on_startup_timing_report") + async def on_report(obs, report): + reports.append(report) + + frames_to_send = [TextFrame(text="hello")] + + await run_test( + processor, + frames_to_send=frames_to_send, + expected_down_frames=[TextFrame], + observers=[observer], + ) + + self.assertEqual(len(reports), 1) + report = reports[0] + self.assertIsInstance(report, StartupTimingReport) + self.assertIsInstance(report.total_duration_secs, float) + for timing in report.processor_timings: + self.assertIsInstance(timing.processor_name, str) + self.assertIsInstance(timing.duration_secs, float) + + async def test_excludes_internal_processors(self): + """Test that internal pipeline processors are excluded by default.""" + observer = StartupTimingObserver() + processor = FastProcessor() + + reports = [] + + @observer.event_handler("on_startup_timing_report") + async def on_report(obs, report): + reports.append(report) + + frames_to_send = [TextFrame(text="hello")] + + await run_test( + processor, + frames_to_send=frames_to_send, + expected_down_frames=[TextFrame], + observers=[observer], + ) + + self.assertEqual(len(reports), 1) + report = reports[0] + + # No internal processors (PipelineSource, PipelineSink, Pipeline) in the report. + internal_names = ("Pipeline#", "PipelineTask#") + for t in report.processor_timings: + for prefix in internal_names: + self.assertNotIn( + prefix, + t.processor_name, + f"Internal processor {t.processor_name} should be excluded by default", + ) + + +if __name__ == "__main__": + unittest.main() From e6b9c5c4dccbe5dd46ff9275bac19c136b15fb35 Mon Sep 17 00:00:00 2001 From: Mark Backman Date: Mon, 2 Mar 2026 12:24:10 -0500 Subject: [PATCH 0731/1060] Propagate Azure TTS/STT cancellation errors to the pipeline MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit Azure TTS _handle_canceled was putting None (the normal completion signal) into the audio queue for all cancellation reasons, so run_tts treated errors identically to success—silently producing no audio. Now error cancellations put an Exception marker in the queue, which run_tts converts to an ErrorFrame. Azure STT had no canceled event handler at all, so auth failures, network errors, and rate-limit cancellations were invisible. Added _on_handle_canceled which pushes an ErrorFrame upstream via push_error. Fixes pipecat-ai/pipecat#3892 --- changelog/3893.fixed.md | 1 + src/pipecat/services/azure/stt.py | 12 ++++++++++++ src/pipecat/services/azure/tts.py | 11 +++++++++-- 3 files changed, 22 insertions(+), 2 deletions(-) create mode 100644 changelog/3893.fixed.md diff --git a/changelog/3893.fixed.md b/changelog/3893.fixed.md new file mode 100644 index 000000000..0209571e3 --- /dev/null +++ b/changelog/3893.fixed.md @@ -0,0 +1 @@ +- Fixed Azure TTS and STT services silently swallowing cancellation errors (invalid API key, network failures, rate limiting) instead of propagating them as `ErrorFrame`s to the pipeline. diff --git a/src/pipecat/services/azure/stt.py b/src/pipecat/services/azure/stt.py index c6cb96d2e..5533e350e 100644 --- a/src/pipecat/services/azure/stt.py +++ b/src/pipecat/services/azure/stt.py @@ -35,6 +35,7 @@ from pipecat.utils.tracing.service_decorators import traced_stt try: from azure.cognitiveservices.speech import ( + CancellationReason, ResultReason, SpeechConfig, SpeechRecognizer, @@ -209,6 +210,7 @@ class AzureSTTService(STTService): ) self._speech_recognizer.recognizing.connect(self._on_handle_recognizing) self._speech_recognizer.recognized.connect(self._on_handle_recognized) + self._speech_recognizer.canceled.connect(self._on_handle_canceled) self._speech_recognizer.start_continuous_recognition_async() except Exception as e: await self.push_error( @@ -280,3 +282,13 @@ class AzureSTTService(STTService): result=event, ) asyncio.run_coroutine_threadsafe(self.push_frame(frame), self.get_event_loop()) + + def _on_handle_canceled(self, event): + details = event.result.cancellation_details + if details.reason == CancellationReason.Error: + error_msg = f"Azure STT recognition canceled: {details.reason}" + if details.error_details: + error_msg += f" - {details.error_details}" + asyncio.run_coroutine_threadsafe( + self.push_error(error_msg=error_msg), self.get_event_loop() + ) diff --git a/src/pipecat/services/azure/tts.py b/src/pipecat/services/azure/tts.py index f68694eb5..6e62c73bf 100644 --- a/src/pipecat/services/azure/tts.py +++ b/src/pipecat/services/azure/tts.py @@ -561,9 +561,13 @@ class AzureTTSService(TTSService, AzureBaseTTSService): # User cancellation (from interruption) is expected, not an error if reason == CancellationReason.CancelledByUser: logger.debug(f"{self}: Speech synthesis canceled by user (interruption)") + self._audio_queue.put_nowait(None) else: - logger.warning(f"{self}: Speech synthesis canceled: {reason}") - self._audio_queue.put_nowait(None) + details = evt.result.cancellation_details + error_msg = f"Azure TTS synthesis canceled: {reason}" + if details.error_details: + error_msg += f" - {details.error_details}" + self._audio_queue.put_nowait(Exception(error_msg)) async def push_frame(self, frame: Frame, direction: FrameDirection = FrameDirection.DOWNSTREAM): """Push a frame and handle state changes. @@ -676,6 +680,9 @@ class AzureTTSService(TTSService, AzureBaseTTSService): chunk = await self._audio_queue.get() if chunk is None: # End of stream break + if isinstance(chunk, Exception): # Error from _handle_canceled + yield ErrorFrame(error=str(chunk)) + break if self._first_chunk: await self.stop_ttfb_metrics() From 58aa8e1ba56a4817fcccffd234a8533257ba8cdf Mon Sep 17 00:00:00 2001 From: Mark Backman Date: Sat, 28 Feb 2026 14:05:25 -0500 Subject: [PATCH 0732/1060] Add changelog for #3881 --- changelog/3881.added.md | 1 + 1 file changed, 1 insertion(+) create mode 100644 changelog/3881.added.md diff --git a/changelog/3881.added.md b/changelog/3881.added.md new file mode 100644 index 000000000..694e052ce --- /dev/null +++ b/changelog/3881.added.md @@ -0,0 +1 @@ +- Added `StartupTimingObserver` for measuring how long each processor's `start()` method takes during pipeline startup. Useful for diagnosing cold start slowness and identifying initialization bottlenecks. From 08360668984a9ae158bae566d390c2a67d17b5d5 Mon Sep 17 00:00:00 2001 From: Mark Backman Date: Sun, 1 Mar 2026 08:45:59 -0500 Subject: [PATCH 0733/1060] Add ClientConnectedFrame and transport readiness timing MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit Introduce ClientConnectedFrame (SystemFrame) pushed by all transports when a client connects. StartupTimingObserver uses this to measure transport readiness — the time from StartFrame to first client connection — via a new on_transport_readiness_measured event. --- .../foundational/29-turn-tracking-observer.py | 4 + src/pipecat/frames/frames.py | 11 +++ .../observers/startup_timing_observer.py | 80 ++++++++++++++----- src/pipecat/transports/daily/transport.py | 3 + src/pipecat/transports/heygen/transport.py | 3 + src/pipecat/transports/livekit/transport.py | 3 + .../transports/smallwebrtc/transport.py | 3 + src/pipecat/transports/tavus/transport.py | 3 + src/pipecat/transports/websocket/fastapi.py | 2 + src/pipecat/transports/websocket/server.py | 4 +- tests/test_startup_timing_observer.py | 76 +++++++++++++++++- 11 files changed, 172 insertions(+), 20 deletions(-) diff --git a/examples/foundational/29-turn-tracking-observer.py b/examples/foundational/29-turn-tracking-observer.py index 3e85ddfb8..ad0b448e9 100644 --- a/examples/foundational/29-turn-tracking-observer.py +++ b/examples/foundational/29-turn-tracking-observer.py @@ -111,6 +111,10 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): for timing in report.processor_timings: logger.info(f" {timing.processor_name}: {timing.duration_secs:.3f}s") + @startup_observer.event_handler("on_transport_readiness_measured") + async def on_transport_readiness_measured(observer, report): + logger.info(f"Transport readiness: {report.readiness_secs:.3f}s") + turn_observer = task.turn_tracking_observer if turn_observer: diff --git a/src/pipecat/frames/frames.py b/src/pipecat/frames/frames.py index 126f3c001..b5e368c53 100644 --- a/src/pipecat/frames/frames.py +++ b/src/pipecat/frames/frames.py @@ -1910,6 +1910,17 @@ class StopFrame(ControlFrame, UninterruptibleFrame): pass +@dataclass +class ClientConnectedFrame(SystemFrame): + """Frame indicating that a client has connected to the transport. + + Pushed downstream by the input transport when a client (participant) + connects. Used by observers to measure transport readiness timing. + """ + + pass + + @dataclass class OutputTransportReadyFrame(ControlFrame): """Frame indicating that the output transport is ready. diff --git a/src/pipecat/observers/startup_timing_observer.py b/src/pipecat/observers/startup_timing_observer.py index 0f3ad0b7a..d6b1c8fa9 100644 --- a/src/pipecat/observers/startup_timing_observer.py +++ b/src/pipecat/observers/startup_timing_observer.py @@ -12,6 +12,10 @@ when a ``StartFrame`` arrives at a processor (``on_process_frame``) versus when it leaves (``on_push_frame``), giving the exact ``start()`` duration for each processor in the pipeline. +It also measures transport readiness — the time from ``StartFrame`` to the +first ``ClientConnectedFrame`` — via a separate ``on_transport_readiness_measured`` +event. + Example:: observer = StartupTimingObserver() @@ -21,6 +25,10 @@ Example:: for t in report.processor_timings: print(f"{t.processor_name}: {t.duration_secs:.3f}s") + @observer.event_handler("on_transport_readiness_measured") + async def on_readiness(observer, report): + print(f"Transport ready in {report.readiness_secs:.3f}s") + task = PipelineTask(pipeline, observers=[observer]) """ @@ -29,11 +37,11 @@ from typing import Dict, List, Optional, Tuple, Type from loguru import logger -from pipecat.frames.frames import StartFrame +from pipecat.frames.frames import ClientConnectedFrame, StartFrame from pipecat.observers.base_observer import BaseObserver, FrameProcessed, FramePushed from pipecat.pipeline.base_pipeline import BasePipeline from pipecat.pipeline.pipeline import PipelineSink, PipelineSource -from pipecat.processors.frame_processor import FrameDirection, FrameProcessor +from pipecat.processors.frame_processor import FrameProcessor # Internal pipeline types excluded from tracking by default. _INTERNAL_TYPES = (PipelineSink, PipelineSource, BasePipeline) @@ -65,6 +73,17 @@ class StartupTimingReport: processor_timings: List[ProcessorStartupTiming] = field(default_factory=list) +@dataclass +class TransportReadinessReport: + """Time from pipeline start to first client connection. + + Parameters: + readiness_secs: Seconds from StartFrame to first ClientConnectedFrame. + """ + + readiness_secs: float + + class StartupTimingObserver(BaseObserver): """Observer that measures processor startup times during pipeline initialization. @@ -73,6 +92,10 @@ class StartupTimingObserver(BaseObserver): pushed downstream. This captures WebSocket connections, API authentication, model loading, and other initialization work. + Also measures transport readiness — the time from ``StartFrame`` to the + first ``ClientConnectedFrame`` — indicating how long it takes for a client + to connect after the pipeline starts. + By default, internal pipeline processors (``PipelineSource``, ``PipelineSink``, ``Pipeline``) are excluded from the report. Pass ``processor_types`` to measure only specific types. @@ -81,6 +104,8 @@ class StartupTimingObserver(BaseObserver): - on_startup_timing_report: Called once after startup completes with the full timing report. + - on_transport_readiness_measured: Called once when the first client connects with the + transport readiness timing. Example:: @@ -93,6 +118,10 @@ class StartupTimingObserver(BaseObserver): for t in report.processor_timings: logger.info(f"{t.processor_name}: {t.duration_secs:.3f}s") + @observer.event_handler("on_transport_readiness_measured") + async def on_readiness(observer, report): + logger.info(f"Transport ready in {report.readiness_secs:.3f}s") + task = PipelineTask(pipeline, observers=[observer]) Args: @@ -125,10 +154,17 @@ class StartupTimingObserver(BaseObserver): # Lock onto the first StartFrame we see (by frame ID). self._start_frame_id: Optional[str] = None - # Whether we've already emitted the report. - self._reported = False + # Whether we've already emitted the startup timing report. + self._startup_timing_reported = False + + # Whether we've already measured transport readiness. + self._transport_readiness_measured = False + + # Timestamp (ns) when we first see a StartFrame arrive at a processor. + self._start_frame_arrival_ns: Optional[int] = None self._register_event_handler("on_startup_timing_report") + self._register_event_handler("on_transport_readiness_measured") def _should_track(self, processor: FrameProcessor) -> bool: """Check if a processor should be tracked for timing. @@ -153,18 +189,16 @@ class StartupTimingObserver(BaseObserver): Args: data: The frame processing event data. """ - if self._reported: + if self._startup_timing_reported: return if not isinstance(data.frame, StartFrame): return - if data.direction != FrameDirection.DOWNSTREAM: - return - # Lock onto the first StartFrame. if self._start_frame_id is None: self._start_frame_id = data.frame.id + self._start_frame_arrival_ns = data.timestamp elif data.frame.id != self._start_frame_id: return @@ -182,18 +216,21 @@ class StartupTimingObserver(BaseObserver): async def on_push_frame(self, data: FramePushed): """Record when a StartFrame leaves a processor and compute the delta. + Also handles ``ClientConnectedFrame`` to measure transport readiness. + Args: data: The frame push event data. """ - if self._reported: + if isinstance(data.frame, ClientConnectedFrame): + await self._handle_client_connected(data) + return + + if self._startup_timing_reported: return if not isinstance(data.frame, StartFrame): return - if data.direction != FrameDirection.DOWNSTREAM: - return - if self._start_frame_id is not None and data.frame.id != self._start_frame_id: return @@ -212,11 +249,22 @@ class StartupTimingObserver(BaseObserver): ) ) + async def _handle_client_connected(self, data: FramePushed): + """Measure transport readiness on first client connection.""" + if self._transport_readiness_measured or self._start_frame_arrival_ns is None: + return + + self._transport_readiness_measured = True + delta_ns = data.timestamp - self._start_frame_arrival_ns + readiness_secs = delta_ns / 1e9 + report = TransportReadinessReport(readiness_secs=readiness_secs) + await self._call_event_handler("on_transport_readiness_measured", report) + async def _emit_report(self): """Build and emit the startup timing report.""" - if self._reported: + if self._startup_timing_reported: return - self._reported = True + self._startup_timing_reported = True total = sum(t.duration_secs for t in self._timings) @@ -225,8 +273,4 @@ class StartupTimingObserver(BaseObserver): processor_timings=self._timings, ) - logger.debug(f"Pipeline startup completed in {total:.3f}s") - for t in self._timings: - logger.debug(f" {t.processor_name}: {t.duration_secs:.3f}s") - await self._call_event_handler("on_startup_timing_report", report) diff --git a/src/pipecat/transports/daily/transport.py b/src/pipecat/transports/daily/transport.py index 9575fd51b..cb24b23fa 100644 --- a/src/pipecat/transports/daily/transport.py +++ b/src/pipecat/transports/daily/transport.py @@ -25,6 +25,7 @@ from pydantic import BaseModel from pipecat.audio.vad.vad_analyzer import VADAnalyzer, VADParams from pipecat.frames.frames import ( CancelFrame, + ClientConnectedFrame, DataFrame, EndFrame, Frame, @@ -2716,6 +2717,8 @@ class DailyTransport(BaseTransport): await self._call_event_handler("on_participant_joined", participant) # Also call on_client_connected for compatibility with other transports await self._call_event_handler("on_client_connected", participant) + if self._input: + await self._input.push_frame(ClientConnectedFrame()) async def _on_participant_left(self, participant, reason): """Handle participant left events.""" diff --git a/src/pipecat/transports/heygen/transport.py b/src/pipecat/transports/heygen/transport.py index dbeded3e5..77ccda09f 100644 --- a/src/pipecat/transports/heygen/transport.py +++ b/src/pipecat/transports/heygen/transport.py @@ -26,6 +26,7 @@ from pipecat.frames.frames import ( BotStartedSpeakingFrame, BotStoppedSpeakingFrame, CancelFrame, + ClientConnectedFrame, EndFrame, Frame, InputAudioRawFrame, @@ -387,6 +388,8 @@ class HeyGenTransport(BaseTransport): async def _on_client_connected(self, participant: Any): """Handle client connected events.""" await self._call_event_handler("on_client_connected", participant) + if self._input: + await self._input.push_frame(ClientConnectedFrame()) async def _on_client_disconnected(self, participant: Any): """Handle client disconnected events.""" diff --git a/src/pipecat/transports/livekit/transport.py b/src/pipecat/transports/livekit/transport.py index 1902e7cd3..e4435016c 100644 --- a/src/pipecat/transports/livekit/transport.py +++ b/src/pipecat/transports/livekit/transport.py @@ -24,6 +24,7 @@ from pipecat.audio.vad.vad_analyzer import VADAnalyzer from pipecat.frames.frames import ( AudioRawFrame, CancelFrame, + ClientConnectedFrame, EndFrame, ImageRawFrame, OutputAudioRawFrame, @@ -1143,6 +1144,8 @@ class LiveKitTransport(BaseTransport): async def _on_participant_connected(self, participant_id: str): """Handle participant connected events.""" await self._call_event_handler("on_participant_connected", participant_id) + if self._input: + await self._input.push_frame(ClientConnectedFrame()) async def _on_participant_disconnected(self, participant_id: str): """Handle participant disconnected events.""" diff --git a/src/pipecat/transports/smallwebrtc/transport.py b/src/pipecat/transports/smallwebrtc/transport.py index dc91588a3..36f883278 100644 --- a/src/pipecat/transports/smallwebrtc/transport.py +++ b/src/pipecat/transports/smallwebrtc/transport.py @@ -23,6 +23,7 @@ from pydantic import BaseModel from pipecat.frames.frames import ( CancelFrame, + ClientConnectedFrame, EndFrame, Frame, InputAudioRawFrame, @@ -964,6 +965,8 @@ class SmallWebRTCTransport(BaseTransport): async def _on_client_connected(self, webrtc_connection): """Handle client connection events.""" await self._call_event_handler("on_client_connected", webrtc_connection) + if self._input: + await self._input.push_frame(ClientConnectedFrame()) async def _on_client_disconnected(self, webrtc_connection): """Handle client disconnection events.""" diff --git a/src/pipecat/transports/tavus/transport.py b/src/pipecat/transports/tavus/transport.py index dd63cb790..114f33ca0 100644 --- a/src/pipecat/transports/tavus/transport.py +++ b/src/pipecat/transports/tavus/transport.py @@ -22,6 +22,7 @@ from pydantic import BaseModel from pipecat.frames.frames import ( CancelFrame, + ClientConnectedFrame, EndFrame, Frame, InputAudioRawFrame, @@ -786,6 +787,8 @@ class TavusTransport(BaseTransport): async def _on_client_connected(self, participant: Any): """Handle client connected events.""" await self._call_event_handler("on_client_connected", participant) + if self._input: + await self._input.push_frame(ClientConnectedFrame()) async def _on_client_disconnected(self, participant: Any): """Handle client disconnected events.""" diff --git a/src/pipecat/transports/websocket/fastapi.py b/src/pipecat/transports/websocket/fastapi.py index f52123e52..0fde2b9ae 100644 --- a/src/pipecat/transports/websocket/fastapi.py +++ b/src/pipecat/transports/websocket/fastapi.py @@ -23,6 +23,7 @@ from pydantic import BaseModel from pipecat.frames.frames import ( CancelFrame, + ClientConnectedFrame, EndFrame, Frame, InputAudioRawFrame, @@ -260,6 +261,7 @@ class FastAPIWebsocketInputTransport(BaseInputTransport): if not self._monitor_websocket_task and self._params.session_timeout: self._monitor_websocket_task = self.create_task(self._monitor_websocket()) await self._client.trigger_client_connected() + await self.push_frame(ClientConnectedFrame()) if not self._receive_task: self._receive_task = self.create_task(self._receive_messages()) await self.set_transport_ready(frame) diff --git a/src/pipecat/transports/websocket/server.py b/src/pipecat/transports/websocket/server.py index e5f628fa4..fa3645d37 100644 --- a/src/pipecat/transports/websocket/server.py +++ b/src/pipecat/transports/websocket/server.py @@ -22,11 +22,11 @@ from pydantic import BaseModel from pipecat.frames.frames import ( CancelFrame, + ClientConnectedFrame, EndFrame, Frame, InputAudioRawFrame, InputTransportMessageFrame, - InputTransportMessageUrgentFrame, InterruptionFrame, OutputAudioRawFrame, OutputTransportMessageFrame, @@ -504,6 +504,8 @@ class WebsocketServerTransport(BaseTransport): if self._output: await self._output.set_client_connection(websocket) await self._call_event_handler("on_client_connected", websocket) + if self._input: + await self._input.push_frame(ClientConnectedFrame()) else: logger.error("A WebsocketServerTransport output is missing in the pipeline") diff --git a/tests/test_startup_timing_observer.py b/tests/test_startup_timing_observer.py index e3cd7c2b7..efabf5bc7 100644 --- a/tests/test_startup_timing_observer.py +++ b/tests/test_startup_timing_observer.py @@ -1,10 +1,11 @@ import asyncio import unittest -from pipecat.frames.frames import Frame, StartFrame, TextFrame +from pipecat.frames.frames import ClientConnectedFrame, Frame, StartFrame, TextFrame from pipecat.observers.startup_timing_observer import ( StartupTimingObserver, StartupTimingReport, + TransportReadinessReport, ) from pipecat.processors.frame_processor import FrameDirection, FrameProcessor from pipecat.tests.utils import run_test @@ -181,6 +182,79 @@ class TestStartupTimingObserver(unittest.IsolatedAsyncioTestCase): f"Internal processor {t.processor_name} should be excluded by default", ) + async def test_transport_readiness_measured(self): + """Test that ClientConnectedFrame after startup emits on_transport_readiness_measured.""" + observer = StartupTimingObserver() + processor = FastProcessor() + + readiness_reports = [] + + @observer.event_handler("on_transport_readiness_measured") + async def on_readiness(obs, report): + readiness_reports.append(report) + + frames_to_send = [ClientConnectedFrame(), TextFrame(text="hello")] + + await run_test( + processor, + frames_to_send=frames_to_send, + expected_down_frames=[ClientConnectedFrame, TextFrame], + observers=[observer], + ) + + self.assertEqual(len(readiness_reports), 1) + report = readiness_reports[0] + self.assertIsInstance(report, TransportReadinessReport) + self.assertGreater(report.readiness_secs, 0) + + async def test_transport_readiness_only_first(self): + """Test that only the first ClientConnectedFrame triggers the event.""" + observer = StartupTimingObserver() + processor = FastProcessor() + + readiness_reports = [] + + @observer.event_handler("on_transport_readiness_measured") + async def on_readiness(obs, report): + readiness_reports.append(report) + + frames_to_send = [ + ClientConnectedFrame(), + ClientConnectedFrame(), + TextFrame(text="hello"), + ] + + await run_test( + processor, + frames_to_send=frames_to_send, + expected_down_frames=[ClientConnectedFrame, ClientConnectedFrame, TextFrame], + observers=[observer], + ) + + self.assertEqual(len(readiness_reports), 1) + + async def test_transport_readiness_without_start_frame(self): + """Test that ClientConnectedFrame before StartFrame does not crash.""" + observer = StartupTimingObserver() + + # Directly call on_push_frame with a ClientConnectedFrame before any + # StartFrame has been seen. This should be a no-op (no crash). + from pipecat.observers.base_observer import FramePushed + + processor = FastProcessor() + destination = FastProcessor() + data = FramePushed( + source=processor, + destination=destination, + frame=ClientConnectedFrame(), + direction=FrameDirection.DOWNSTREAM, + timestamp=1000, + ) + await observer.on_push_frame(data) + + # No event should have been emitted. + self.assertFalse(observer._transport_readiness_measured) + if __name__ == "__main__": unittest.main() From de87894778e541b0f174b0be639e50e0825c2887 Mon Sep 17 00:00:00 2001 From: Mark Backman Date: Sun, 1 Mar 2026 08:47:40 -0500 Subject: [PATCH 0734/1060] Update changelog for #3881 --- changelog/3881.added.2.md | 1 + changelog/3881.added.md | 2 +- 2 files changed, 2 insertions(+), 1 deletion(-) create mode 100644 changelog/3881.added.2.md diff --git a/changelog/3881.added.2.md b/changelog/3881.added.2.md new file mode 100644 index 000000000..a5bda94c1 --- /dev/null +++ b/changelog/3881.added.2.md @@ -0,0 +1 @@ +- Added `ClientConnectedFrame`, a new `SystemFrame` pushed by all transports (Daily, LiveKit, FastAPI WebSocket, WebSocket Server, SmallWebRTC, HeyGen, Tavus) when a client connects. Enables observers to track transport readiness timing. diff --git a/changelog/3881.added.md b/changelog/3881.added.md index 694e052ce..cbf6d0293 100644 --- a/changelog/3881.added.md +++ b/changelog/3881.added.md @@ -1 +1 @@ -- Added `StartupTimingObserver` for measuring how long each processor's `start()` method takes during pipeline startup. Useful for diagnosing cold start slowness and identifying initialization bottlenecks. +- Added `StartupTimingObserver` for measuring how long each processor's `start()` method takes during pipeline startup. Also measures transport readiness — the time from `StartFrame` to first client connection — via the `on_transport_readiness_measured` event. Useful for diagnosing cold start slowness and identifying initialization bottlenecks. From 68e8732e72ba5f20ec3b03129f97d4fa2271b190 Mon Sep 17 00:00:00 2001 From: Mark Backman Date: Mon, 2 Mar 2026 10:41:05 -0500 Subject: [PATCH 0735/1060] Add BotConnectedFrame and on_transport_timing_report event Add BotConnectedFrame (SystemFrame) pushed by SFU transports (Daily, LiveKit, HeyGen, Tavus) when the bot joins the room. Replace the on_transport_readiness_measured event with on_transport_timing_report which includes both bot_connected_secs and client_connected_secs. --- changelog/3881.added.3.md | 1 + .../foundational/29-turn-tracking-observer.py | 8 +- src/pipecat/frames/frames.py | 12 ++ .../observers/startup_timing_observer.py | 93 +++++++++----- src/pipecat/services/heygen/client.py | 7 +- src/pipecat/services/heygen/video.py | 5 + src/pipecat/services/tavus/video.py | 5 + src/pipecat/transports/daily/transport.py | 3 + src/pipecat/transports/heygen/transport.py | 9 ++ src/pipecat/transports/livekit/transport.py | 3 + src/pipecat/transports/tavus/transport.py | 12 ++ tests/test_startup_timing_observer.py | 114 +++++++++++++++--- 12 files changed, 215 insertions(+), 57 deletions(-) create mode 100644 changelog/3881.added.3.md diff --git a/changelog/3881.added.3.md b/changelog/3881.added.3.md new file mode 100644 index 000000000..cad26e876 --- /dev/null +++ b/changelog/3881.added.3.md @@ -0,0 +1 @@ +Added `BotConnectedFrame` for SFU transports and `on_transport_timing_report` event to `StartupTimingObserver` with bot and client connection timing. diff --git a/examples/foundational/29-turn-tracking-observer.py b/examples/foundational/29-turn-tracking-observer.py index ad0b448e9..4af28f1ed 100644 --- a/examples/foundational/29-turn-tracking-observer.py +++ b/examples/foundational/29-turn-tracking-observer.py @@ -111,9 +111,11 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): for timing in report.processor_timings: logger.info(f" {timing.processor_name}: {timing.duration_secs:.3f}s") - @startup_observer.event_handler("on_transport_readiness_measured") - async def on_transport_readiness_measured(observer, report): - logger.info(f"Transport readiness: {report.readiness_secs:.3f}s") + @startup_observer.event_handler("on_transport_timing_report") + async def on_transport_timing_report(observer, report): + if report.bot_connected_secs is not None: + logger.info(f"Bot connected: {report.bot_connected_secs:.3f}s") + logger.info(f"Client connected: {report.client_connected_secs:.3f}s") turn_observer = task.turn_tracking_observer if turn_observer: diff --git a/src/pipecat/frames/frames.py b/src/pipecat/frames/frames.py index b5e368c53..86778e564 100644 --- a/src/pipecat/frames/frames.py +++ b/src/pipecat/frames/frames.py @@ -1910,6 +1910,18 @@ class StopFrame(ControlFrame, UninterruptibleFrame): pass +@dataclass +class BotConnectedFrame(SystemFrame): + """Frame indicating the bot has connected to the transport service. + + Pushed downstream by SFU transports (Daily, LiveKit, HeyGen, Tavus) + when the bot successfully joins the room. Non-SFU transports do not + emit this frame. + """ + + pass + + @dataclass class ClientConnectedFrame(SystemFrame): """Frame indicating that a client has connected to the transport. diff --git a/src/pipecat/observers/startup_timing_observer.py b/src/pipecat/observers/startup_timing_observer.py index d6b1c8fa9..555a10cb0 100644 --- a/src/pipecat/observers/startup_timing_observer.py +++ b/src/pipecat/observers/startup_timing_observer.py @@ -12,9 +12,9 @@ when a ``StartFrame`` arrives at a processor (``on_process_frame``) versus when it leaves (``on_push_frame``), giving the exact ``start()`` duration for each processor in the pipeline. -It also measures transport readiness — the time from ``StartFrame`` to the -first ``ClientConnectedFrame`` — via a separate ``on_transport_readiness_measured`` -event. +It also measures transport timing — the time from ``StartFrame`` to the +first ``BotConnectedFrame`` (SFU transports only) and ``ClientConnectedFrame`` +— via a separate ``on_transport_timing_report`` event. Example:: @@ -25,9 +25,11 @@ Example:: for t in report.processor_timings: print(f"{t.processor_name}: {t.duration_secs:.3f}s") - @observer.event_handler("on_transport_readiness_measured") - async def on_readiness(observer, report): - print(f"Transport ready in {report.readiness_secs:.3f}s") + @observer.event_handler("on_transport_timing_report") + async def on_transport(observer, report): + if report.bot_connected_secs is not None: + print(f"Bot connected in {report.bot_connected_secs:.3f}s") + print(f"Client connected in {report.client_connected_secs:.3f}s") task = PipelineTask(pipeline, observers=[observer]) """ @@ -35,9 +37,7 @@ Example:: from dataclasses import dataclass, field from typing import Dict, List, Optional, Tuple, Type -from loguru import logger - -from pipecat.frames.frames import ClientConnectedFrame, StartFrame +from pipecat.frames.frames import BotConnectedFrame, ClientConnectedFrame, StartFrame from pipecat.observers.base_observer import BaseObserver, FrameProcessed, FramePushed from pipecat.pipeline.base_pipeline import BasePipeline from pipecat.pipeline.pipeline import PipelineSink, PipelineSource @@ -74,14 +74,17 @@ class StartupTimingReport: @dataclass -class TransportReadinessReport: - """Time from pipeline start to first client connection. +class TransportTimingReport: + """Time from pipeline start to transport connection milestones. Parameters: - readiness_secs: Seconds from StartFrame to first ClientConnectedFrame. + bot_connected_secs: Seconds from StartFrame to first BotConnectedFrame + (only set for SFU transports). + client_connected_secs: Seconds from StartFrame to first ClientConnectedFrame. """ - readiness_secs: float + bot_connected_secs: Optional[float] = None + client_connected_secs: Optional[float] = None class StartupTimingObserver(BaseObserver): @@ -92,9 +95,13 @@ class StartupTimingObserver(BaseObserver): pushed downstream. This captures WebSocket connections, API authentication, model loading, and other initialization work. - Also measures transport readiness — the time from ``StartFrame`` to the - first ``ClientConnectedFrame`` — indicating how long it takes for a client - to connect after the pipeline starts. + Also measures transport timing, the time from ``StartFrame`` to connection + milestones: + + - ``bot_connected_secs``: When the bot joins the transport room + (SFU transports only, triggered by ``BotConnectedFrame``). + - ``client_connected_secs``: When a remote participant connects + (triggered by ``ClientConnectedFrame``). By default, internal pipeline processors (``PipelineSource``, ``PipelineSink``, ``Pipeline``) are excluded from the report. Pass ``processor_types`` to @@ -104,8 +111,9 @@ class StartupTimingObserver(BaseObserver): - on_startup_timing_report: Called once after startup completes with the full timing report. - - on_transport_readiness_measured: Called once when the first client connects with the - transport readiness timing. + - on_transport_timing_report: Called once when the first client connects with a + TransportTimingReport containing client_connected_secs and bot_connected_secs + (if available). Example:: @@ -118,9 +126,11 @@ class StartupTimingObserver(BaseObserver): for t in report.processor_timings: logger.info(f"{t.processor_name}: {t.duration_secs:.3f}s") - @observer.event_handler("on_transport_readiness_measured") - async def on_readiness(observer, report): - logger.info(f"Transport ready in {report.readiness_secs:.3f}s") + @observer.event_handler("on_transport_timing_report") + async def on_transport(observer, report): + if report.bot_connected_secs is not None: + logger.info(f"Bot connected in {report.bot_connected_secs:.3f}s") + logger.info(f"Client connected in {report.client_connected_secs:.3f}s") task = PipelineTask(pipeline, observers=[observer]) @@ -157,14 +167,17 @@ class StartupTimingObserver(BaseObserver): # Whether we've already emitted the startup timing report. self._startup_timing_reported = False - # Whether we've already measured transport readiness. - self._transport_readiness_measured = False + # Whether we've already measured transport timing. + self._transport_timing_reported = False # Timestamp (ns) when we first see a StartFrame arrive at a processor. self._start_frame_arrival_ns: Optional[int] = None + # Bot connected timing (stored for inclusion in the transport report). + self._bot_connected_secs: Optional[float] = None + self._register_event_handler("on_startup_timing_report") - self._register_event_handler("on_transport_readiness_measured") + self._register_event_handler("on_transport_timing_report") def _should_track(self, processor: FrameProcessor) -> bool: """Check if a processor should be tracked for timing. @@ -216,11 +229,16 @@ class StartupTimingObserver(BaseObserver): async def on_push_frame(self, data: FramePushed): """Record when a StartFrame leaves a processor and compute the delta. - Also handles ``ClientConnectedFrame`` to measure transport readiness. + Also handles ``BotConnectedFrame`` and ``ClientConnectedFrame`` to + measure transport timing. Args: data: The frame push event data. """ + if isinstance(data.frame, BotConnectedFrame): + self._handle_bot_connected(data) + return + if isinstance(data.frame, ClientConnectedFrame): await self._handle_client_connected(data) return @@ -249,16 +267,27 @@ class StartupTimingObserver(BaseObserver): ) ) - async def _handle_client_connected(self, data: FramePushed): - """Measure transport readiness on first client connection.""" - if self._transport_readiness_measured or self._start_frame_arrival_ns is None: + def _handle_bot_connected(self, data: FramePushed): + """Record bot connected timing on first BotConnectedFrame.""" + if self._bot_connected_secs is not None or self._start_frame_arrival_ns is None: return - self._transport_readiness_measured = True delta_ns = data.timestamp - self._start_frame_arrival_ns - readiness_secs = delta_ns / 1e9 - report = TransportReadinessReport(readiness_secs=readiness_secs) - await self._call_event_handler("on_transport_readiness_measured", report) + self._bot_connected_secs = delta_ns / 1e9 + + async def _handle_client_connected(self, data: FramePushed): + """Emit transport timing report on first ClientConnectedFrame.""" + if self._transport_timing_reported or self._start_frame_arrival_ns is None: + return + + self._transport_timing_reported = True + delta_ns = data.timestamp - self._start_frame_arrival_ns + client_connected_secs = delta_ns / 1e9 + report = TransportTimingReport( + bot_connected_secs=self._bot_connected_secs, + client_connected_secs=client_connected_secs, + ) + await self._call_event_handler("on_transport_timing_report", report) async def _emit_report(self): """Build and emit the startup timing report.""" diff --git a/src/pipecat/services/heygen/client.py b/src/pipecat/services/heygen/client.py index 4018d3858..6d45d6114 100644 --- a/src/pipecat/services/heygen/client.py +++ b/src/pipecat/services/heygen/client.py @@ -62,10 +62,12 @@ class HeyGenCallbacks(BaseModel): """Callback handlers for HeyGen events. Parameters: - on_participant_connected: Called when a participant connects - on_participant_disconnected: Called when a participant disconnects + on_connected: Called when the bot connects to the LiveKit room. + on_participant_connected: Called when a participant connects. + on_participant_disconnected: Called when a participant disconnects. """ + on_connected: Callable[[], Awaitable[None]] on_participant_connected: Callable[[str], Awaitable[None]] on_participant_disconnected: Callable[[str], Awaitable[None]] @@ -251,6 +253,7 @@ class HeyGenClient: logger.debug(f"HeyGenClient send_interval: {self._send_interval}") await self._ws_connect() await self._livekit_connect() + self._call_event_callback(self._callbacks.on_connected) async def stop(self) -> None: """Stop the client and terminate all connections. diff --git a/src/pipecat/services/heygen/video.py b/src/pipecat/services/heygen/video.py index b97f4a5ed..7f3624f35 100644 --- a/src/pipecat/services/heygen/video.py +++ b/src/pipecat/services/heygen/video.py @@ -128,6 +128,7 @@ class HeyGenVideoService(AIService): session_request=self._session_request, service_type=self._service_type, callbacks=HeyGenCallbacks( + on_connected=self._on_connected, on_participant_connected=self._on_participant_connected, on_participant_disconnected=self._on_participant_disconnected, ), @@ -144,6 +145,10 @@ class HeyGenVideoService(AIService): await self._client.cleanup() self._client = None + async def _on_connected(self): + """Handle bot connected to LiveKit room.""" + logger.info("HeyGen bot connected to LiveKit room") + async def _on_participant_connected(self, participant_id: str): """Handle participant connected events.""" logger.info(f"Participant connected {participant_id}") diff --git a/src/pipecat/services/tavus/video.py b/src/pipecat/services/tavus/video.py index d9f259797..8c63ff354 100644 --- a/src/pipecat/services/tavus/video.py +++ b/src/pipecat/services/tavus/video.py @@ -94,6 +94,7 @@ class TavusVideoService(AIService): """ await super().setup(setup) callbacks = TavusCallbacks( + on_joined=self._on_joined, on_participant_joined=self._on_participant_joined, on_participant_left=self._on_participant_left, ) @@ -119,6 +120,10 @@ class TavusVideoService(AIService): await self._client.cleanup() self._client = None + async def _on_joined(self, data): + """Handle bot joined the Daily room.""" + logger.info("Tavus bot joined Daily room") + async def _on_participant_left(self, participant, reason): """Handle participant leaving the session.""" participant_id = participant["id"] diff --git a/src/pipecat/transports/daily/transport.py b/src/pipecat/transports/daily/transport.py index cb24b23fa..97aebe915 100644 --- a/src/pipecat/transports/daily/transport.py +++ b/src/pipecat/transports/daily/transport.py @@ -24,6 +24,7 @@ from pydantic import BaseModel from pipecat.audio.vad.vad_analyzer import VADAnalyzer, VADParams from pipecat.frames.frames import ( + BotConnectedFrame, CancelFrame, ClientConnectedFrame, DataFrame, @@ -2579,6 +2580,8 @@ class DailyTransport(BaseTransport): if error: await self._on_error(f"Unable to start transcription: {error}") await self._call_event_handler("on_joined", data) + if self._input: + await self._input.push_frame(BotConnectedFrame()) async def _on_left(self): """Handle room left events.""" diff --git a/src/pipecat/transports/heygen/transport.py b/src/pipecat/transports/heygen/transport.py index 77ccda09f..d79d0080e 100644 --- a/src/pipecat/transports/heygen/transport.py +++ b/src/pipecat/transports/heygen/transport.py @@ -23,6 +23,7 @@ from loguru import logger from pipecat.frames.frames import ( AudioRawFrame, + BotConnectedFrame, BotStartedSpeakingFrame, BotStoppedSpeakingFrame, CancelFrame, @@ -340,6 +341,7 @@ class HeyGenTransport(BaseTransport): session_request=session_request, service_type=service_type, callbacks=HeyGenCallbacks( + on_connected=self._on_connected, on_participant_connected=self._on_participant_connected, on_participant_disconnected=self._on_participant_disconnected, ), @@ -350,9 +352,16 @@ class HeyGenTransport(BaseTransport): # Register supported handlers. The user will only be able to register # these handlers. + self._register_event_handler("on_connected") self._register_event_handler("on_client_connected") self._register_event_handler("on_client_disconnected") + async def _on_connected(self): + """Handle bot connected to LiveKit room.""" + await self._call_event_handler("on_connected") + if self._input: + await self._input.push_frame(BotConnectedFrame()) + async def _on_participant_disconnected(self, participant_id: str): logger.debug(f"HeyGen participant {participant_id} disconnected") if participant_id != "heygen": diff --git a/src/pipecat/transports/livekit/transport.py b/src/pipecat/transports/livekit/transport.py index e4435016c..7e9c1de35 100644 --- a/src/pipecat/transports/livekit/transport.py +++ b/src/pipecat/transports/livekit/transport.py @@ -23,6 +23,7 @@ from pipecat.audio.utils import create_stream_resampler from pipecat.audio.vad.vad_analyzer import VADAnalyzer from pipecat.frames.frames import ( AudioRawFrame, + BotConnectedFrame, CancelFrame, ClientConnectedFrame, EndFrame, @@ -1132,6 +1133,8 @@ class LiveKitTransport(BaseTransport): async def _on_connected(self): """Handle room connected events.""" await self._call_event_handler("on_connected") + if self._input: + await self._input.push_frame(BotConnectedFrame()) async def _on_disconnected(self): """Handle room disconnected events.""" diff --git a/src/pipecat/transports/tavus/transport.py b/src/pipecat/transports/tavus/transport.py index 114f33ca0..6db44d431 100644 --- a/src/pipecat/transports/tavus/transport.py +++ b/src/pipecat/transports/tavus/transport.py @@ -21,6 +21,7 @@ from loguru import logger from pydantic import BaseModel from pipecat.frames.frames import ( + BotConnectedFrame, CancelFrame, ClientConnectedFrame, EndFrame, @@ -133,10 +134,12 @@ class TavusCallbacks(BaseModel): """Callback handlers for Tavus events. Parameters: + on_joined: Called when the bot joins the Daily room. on_participant_joined: Called when a participant joins the conversation. on_participant_left: Called when a participant leaves the conversation. """ + on_joined: Callable[[Mapping[str, Any]], Awaitable[None]] on_participant_joined: Callable[[Mapping[str, Any]], Awaitable[None]] on_participant_left: Callable[[Mapping[str, Any], str], Awaitable[None]] @@ -271,6 +274,7 @@ class TavusTransportClient: async def _on_joined(self, data): """Handle joined event.""" logger.debug("TavusTransportClient joined!") + await self._callbacks.on_joined(data) async def _on_left(self): """Handle left event.""" @@ -703,6 +707,7 @@ class TavusTransport(BaseTransport): self._params = params callbacks = TavusCallbacks( + on_joined=self._on_joined, on_participant_joined=self._on_participant_joined, on_participant_left=self._on_participant_left, ) @@ -721,9 +726,16 @@ class TavusTransport(BaseTransport): # Register supported handlers. The user will only be able to register # these handlers. + self._register_event_handler("on_joined") self._register_event_handler("on_client_connected") self._register_event_handler("on_client_disconnected") + async def _on_joined(self, data): + """Handle bot joined room event.""" + await self._call_event_handler("on_joined", data) + if self._input: + await self._input.push_frame(BotConnectedFrame()) + async def _on_participant_left(self, participant, reason): """Handle participant left events.""" persona_name = await self._client.get_persona_name() diff --git a/tests/test_startup_timing_observer.py b/tests/test_startup_timing_observer.py index efabf5bc7..3c89b9ca3 100644 --- a/tests/test_startup_timing_observer.py +++ b/tests/test_startup_timing_observer.py @@ -1,11 +1,17 @@ import asyncio import unittest -from pipecat.frames.frames import ClientConnectedFrame, Frame, StartFrame, TextFrame +from pipecat.frames.frames import ( + BotConnectedFrame, + ClientConnectedFrame, + Frame, + StartFrame, + TextFrame, +) from pipecat.observers.startup_timing_observer import ( StartupTimingObserver, StartupTimingReport, - TransportReadinessReport, + TransportTimingReport, ) from pipecat.processors.frame_processor import FrameDirection, FrameProcessor from pipecat.tests.utils import run_test @@ -182,16 +188,16 @@ class TestStartupTimingObserver(unittest.IsolatedAsyncioTestCase): f"Internal processor {t.processor_name} should be excluded by default", ) - async def test_transport_readiness_measured(self): - """Test that ClientConnectedFrame after startup emits on_transport_readiness_measured.""" + async def test_transport_timing_client_only(self): + """Test that ClientConnectedFrame emits on_transport_timing_report.""" observer = StartupTimingObserver() processor = FastProcessor() - readiness_reports = [] + transport_reports = [] - @observer.event_handler("on_transport_readiness_measured") - async def on_readiness(obs, report): - readiness_reports.append(report) + @observer.event_handler("on_transport_timing_report") + async def on_transport(obs, report): + transport_reports.append(report) frames_to_send = [ClientConnectedFrame(), TextFrame(text="hello")] @@ -202,21 +208,22 @@ class TestStartupTimingObserver(unittest.IsolatedAsyncioTestCase): observers=[observer], ) - self.assertEqual(len(readiness_reports), 1) - report = readiness_reports[0] - self.assertIsInstance(report, TransportReadinessReport) - self.assertGreater(report.readiness_secs, 0) + self.assertEqual(len(transport_reports), 1) + report = transport_reports[0] + self.assertIsInstance(report, TransportTimingReport) + self.assertGreater(report.client_connected_secs, 0) + self.assertIsNone(report.bot_connected_secs) - async def test_transport_readiness_only_first(self): + async def test_transport_timing_only_first_client(self): """Test that only the first ClientConnectedFrame triggers the event.""" observer = StartupTimingObserver() processor = FastProcessor() - readiness_reports = [] + transport_reports = [] - @observer.event_handler("on_transport_readiness_measured") - async def on_readiness(obs, report): - readiness_reports.append(report) + @observer.event_handler("on_transport_timing_report") + async def on_transport(obs, report): + transport_reports.append(report) frames_to_send = [ ClientConnectedFrame(), @@ -231,9 +238,9 @@ class TestStartupTimingObserver(unittest.IsolatedAsyncioTestCase): observers=[observer], ) - self.assertEqual(len(readiness_reports), 1) + self.assertEqual(len(transport_reports), 1) - async def test_transport_readiness_without_start_frame(self): + async def test_transport_timing_without_start_frame(self): """Test that ClientConnectedFrame before StartFrame does not crash.""" observer = StartupTimingObserver() @@ -253,7 +260,74 @@ class TestStartupTimingObserver(unittest.IsolatedAsyncioTestCase): await observer.on_push_frame(data) # No event should have been emitted. - self.assertFalse(observer._transport_readiness_measured) + self.assertFalse(observer._transport_timing_reported) + + async def test_bot_and_client_connected(self): + """Test that BotConnectedFrame timing is included in the transport report.""" + observer = StartupTimingObserver() + processor = FastProcessor() + + transport_reports = [] + + @observer.event_handler("on_transport_timing_report") + async def on_transport(obs, report): + transport_reports.append(report) + + frames_to_send = [ + BotConnectedFrame(), + ClientConnectedFrame(), + TextFrame(text="hello"), + ] + + await run_test( + processor, + frames_to_send=frames_to_send, + expected_down_frames=[BotConnectedFrame, ClientConnectedFrame, TextFrame], + observers=[observer], + ) + + self.assertEqual(len(transport_reports), 1) + report = transport_reports[0] + self.assertGreater(report.client_connected_secs, 0) + self.assertIsNotNone(report.bot_connected_secs) + self.assertGreater(report.bot_connected_secs, 0) + + # Client connected should be >= bot connected. + self.assertGreaterEqual(report.client_connected_secs, report.bot_connected_secs) + + async def test_bot_connected_only_first(self): + """Test that only the first BotConnectedFrame is recorded.""" + observer = StartupTimingObserver() + processor = FastProcessor() + + transport_reports = [] + + @observer.event_handler("on_transport_timing_report") + async def on_transport(obs, report): + transport_reports.append(report) + + frames_to_send = [ + BotConnectedFrame(), + BotConnectedFrame(), + ClientConnectedFrame(), + TextFrame(text="hello"), + ] + + await run_test( + processor, + frames_to_send=frames_to_send, + expected_down_frames=[ + BotConnectedFrame, + BotConnectedFrame, + ClientConnectedFrame, + TextFrame, + ], + observers=[observer], + ) + + # Only one transport report, with bot timing from first frame. + self.assertEqual(len(transport_reports), 1) + self.assertIsNotNone(transport_reports[0].bot_connected_secs) if __name__ == "__main__": From 75669b12a2a4a07c396932a0e67afa951733db2c Mon Sep 17 00:00:00 2001 From: Mark Backman Date: Mon, 2 Mar 2026 11:01:26 -0500 Subject: [PATCH 0736/1060] Convert observer data models to Pydantic BaseModel with timestamps Switch ProcessorStartupTiming, StartupTimingReport, and TransportTimingReport from dataclasses to Pydantic BaseModel. Add start_time (Unix timestamp) fields and wall clock conversion for monotonic observer timestamps. --- .../observers/startup_timing_observer.py | 37 +++++++++++++++---- tests/test_startup_timing_observer.py | 3 ++ 2 files changed, 32 insertions(+), 8 deletions(-) diff --git a/src/pipecat/observers/startup_timing_observer.py b/src/pipecat/observers/startup_timing_observer.py index 555a10cb0..6dd574cdc 100644 --- a/src/pipecat/observers/startup_timing_observer.py +++ b/src/pipecat/observers/startup_timing_observer.py @@ -34,9 +34,11 @@ Example:: task = PipelineTask(pipeline, observers=[observer]) """ -from dataclasses import dataclass, field +import time from typing import Dict, List, Optional, Tuple, Type +from pydantic import BaseModel, Field + from pipecat.frames.frames import BotConnectedFrame, ClientConnectedFrame, StartFrame from pipecat.observers.base_observer import BaseObserver, FrameProcessed, FramePushed from pipecat.pipeline.base_pipeline import BasePipeline @@ -47,42 +49,45 @@ from pipecat.processors.frame_processor import FrameProcessor _INTERNAL_TYPES = (PipelineSink, PipelineSource, BasePipeline) -@dataclass -class ProcessorStartupTiming: +class ProcessorStartupTiming(BaseModel): """Startup timing for a single processor. Parameters: processor_name: The name of the processor. + start_time: Unix timestamp when the processor's start() began. duration_secs: How long the processor's start() took, in seconds. """ processor_name: str + start_time: float duration_secs: float -@dataclass -class StartupTimingReport: +class StartupTimingReport(BaseModel): """Report of startup timings for all measured processors. Parameters: + start_time: Unix timestamp when the first processor began starting. total_duration_secs: Total wall-clock time from first to last processor start. processor_timings: Per-processor timing data, in pipeline order. """ + start_time: float total_duration_secs: float - processor_timings: List[ProcessorStartupTiming] = field(default_factory=list) + processor_timings: List[ProcessorStartupTiming] = Field(default_factory=list) -@dataclass -class TransportTimingReport: +class TransportTimingReport(BaseModel): """Time from pipeline start to transport connection milestones. Parameters: + start_time: Unix timestamp of the StartFrame (pipeline start). bot_connected_secs: Seconds from StartFrame to first BotConnectedFrame (only set for SFU transports). client_connected_secs: Seconds from StartFrame to first ClientConnectedFrame. """ + start_time: float bot_connected_secs: Optional[float] = None client_connected_secs: Optional[float] = None @@ -176,9 +181,19 @@ class StartupTimingObserver(BaseObserver): # Bot connected timing (stored for inclusion in the transport report). self._bot_connected_secs: Optional[float] = None + # Wall clock reference for converting monotonic ns to Unix timestamps. + self._wall_clock_ref: Optional[float] = None + self._mono_clock_ref_ns: Optional[int] = None + self._register_event_handler("on_startup_timing_report") self._register_event_handler("on_transport_timing_report") + def _mono_to_wall(self, mono_ns: int) -> float: + """Convert a monotonic nanosecond timestamp to a Unix wall clock time.""" + if self._wall_clock_ref is None or self._mono_clock_ref_ns is None: + return 0.0 + return self._wall_clock_ref + (mono_ns - self._mono_clock_ref_ns) / 1e9 + def _should_track(self, processor: FrameProcessor) -> bool: """Check if a processor should be tracked for timing. @@ -212,6 +227,8 @@ class StartupTimingObserver(BaseObserver): if self._start_frame_id is None: self._start_frame_id = data.frame.id self._start_frame_arrival_ns = data.timestamp + self._wall_clock_ref = time.time() + self._mono_clock_ref_ns = data.timestamp elif data.frame.id != self._start_frame_id: return @@ -263,6 +280,7 @@ class StartupTimingObserver(BaseObserver): self._timings.append( ProcessorStartupTiming( processor_name=processor.name, + start_time=self._mono_to_wall(arrival_ts), duration_secs=duration_secs, ) ) @@ -284,6 +302,7 @@ class StartupTimingObserver(BaseObserver): delta_ns = data.timestamp - self._start_frame_arrival_ns client_connected_secs = delta_ns / 1e9 report = TransportTimingReport( + start_time=self._mono_to_wall(self._start_frame_arrival_ns), bot_connected_secs=self._bot_connected_secs, client_connected_secs=client_connected_secs, ) @@ -296,8 +315,10 @@ class StartupTimingObserver(BaseObserver): self._startup_timing_reported = True total = sum(t.duration_secs for t in self._timings) + start_time = self._timings[0].start_time if self._timings else 0.0 report = StartupTimingReport( + start_time=start_time, total_duration_secs=total, processor_timings=self._timings, ) diff --git a/tests/test_startup_timing_observer.py b/tests/test_startup_timing_observer.py index 3c89b9ca3..2bc246754 100644 --- a/tests/test_startup_timing_observer.py +++ b/tests/test_startup_timing_observer.py @@ -151,9 +151,11 @@ class TestStartupTimingObserver(unittest.IsolatedAsyncioTestCase): report = reports[0] self.assertIsInstance(report, StartupTimingReport) self.assertIsInstance(report.total_duration_secs, float) + self.assertGreater(report.start_time, 0) for timing in report.processor_timings: self.assertIsInstance(timing.processor_name, str) self.assertIsInstance(timing.duration_secs, float) + self.assertGreater(timing.start_time, 0) async def test_excludes_internal_processors(self): """Test that internal pipeline processors are excluded by default.""" @@ -211,6 +213,7 @@ class TestStartupTimingObserver(unittest.IsolatedAsyncioTestCase): self.assertEqual(len(transport_reports), 1) report = transport_reports[0] self.assertIsInstance(report, TransportTimingReport) + self.assertGreater(report.start_time, 0) self.assertGreater(report.client_connected_secs, 0) self.assertIsNone(report.bot_connected_secs) From 193f93c2cec5edd91e30a93e04181c86eaabad83 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Aleix=20Conchillo=20Flaqu=C3=A9?= Date: Mon, 2 Mar 2026 10:16:27 -0800 Subject: [PATCH 0737/1060] Update Nvidia example to use llama-3.3-70b-instruct model --- examples/foundational/07r-interruptible-nvidia.py | 3 ++- 1 file changed, 2 insertions(+), 1 deletion(-) diff --git a/examples/foundational/07r-interruptible-nvidia.py b/examples/foundational/07r-interruptible-nvidia.py index 18e0b5d5f..d3e34c61f 100644 --- a/examples/foundational/07r-interruptible-nvidia.py +++ b/examples/foundational/07r-interruptible-nvidia.py @@ -55,7 +55,8 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): stt = NvidiaSTTService(api_key=os.getenv("NVIDIA_API_KEY")) llm = NvidiaLLMService( - api_key=os.getenv("NVIDIA_API_KEY"), model="meta/llama-3.1-405b-instruct" + api_key=os.getenv("NVIDIA_API_KEY"), + model="meta/llama-3.3-70b-instruct", ) tts = NvidiaTTSService(api_key=os.getenv("NVIDIA_API_KEY")) From bbbfdfd32143940726662ca729d5d2a79637286c Mon Sep 17 00:00:00 2001 From: Mark Backman Date: Mon, 2 Mar 2026 14:07:34 -0500 Subject: [PATCH 0738/1060] Replace per-processor start_time with start_offset_secs Use start_offset_secs (offset from StartFrame) on ProcessorStartupTiming instead of a wall-clock timestamp. Reports keep a single start_time anchor for dashboard visualization. Remove _mono_to_wall conversion. --- .../observers/startup_timing_observer.py | 28 ++++++++----------- tests/test_startup_timing_observer.py | 2 +- 2 files changed, 12 insertions(+), 18 deletions(-) diff --git a/src/pipecat/observers/startup_timing_observer.py b/src/pipecat/observers/startup_timing_observer.py index 6dd574cdc..8233ed2b8 100644 --- a/src/pipecat/observers/startup_timing_observer.py +++ b/src/pipecat/observers/startup_timing_observer.py @@ -54,12 +54,13 @@ class ProcessorStartupTiming(BaseModel): Parameters: processor_name: The name of the processor. - start_time: Unix timestamp when the processor's start() began. + start_offset_secs: Offset in seconds from the StartFrame to when this + processor's start() began. duration_secs: How long the processor's start() took, in seconds. """ processor_name: str - start_time: float + start_offset_secs: float duration_secs: float @@ -181,19 +182,12 @@ class StartupTimingObserver(BaseObserver): # Bot connected timing (stored for inclusion in the transport report). self._bot_connected_secs: Optional[float] = None - # Wall clock reference for converting monotonic ns to Unix timestamps. - self._wall_clock_ref: Optional[float] = None - self._mono_clock_ref_ns: Optional[int] = None + # Wall clock time when the StartFrame was first seen. + self._start_wall_clock: Optional[float] = None self._register_event_handler("on_startup_timing_report") self._register_event_handler("on_transport_timing_report") - def _mono_to_wall(self, mono_ns: int) -> float: - """Convert a monotonic nanosecond timestamp to a Unix wall clock time.""" - if self._wall_clock_ref is None or self._mono_clock_ref_ns is None: - return 0.0 - return self._wall_clock_ref + (mono_ns - self._mono_clock_ref_ns) / 1e9 - def _should_track(self, processor: FrameProcessor) -> bool: """Check if a processor should be tracked for timing. @@ -227,8 +221,7 @@ class StartupTimingObserver(BaseObserver): if self._start_frame_id is None: self._start_frame_id = data.frame.id self._start_frame_arrival_ns = data.timestamp - self._wall_clock_ref = time.time() - self._mono_clock_ref_ns = data.timestamp + self._start_wall_clock = time.time() elif data.frame.id != self._start_frame_id: return @@ -277,10 +270,12 @@ class StartupTimingObserver(BaseObserver): duration_ns = data.timestamp - arrival_ts duration_secs = duration_ns / 1e9 + start_offset_secs = (arrival_ts - self._start_frame_arrival_ns) / 1e9 + self._timings.append( ProcessorStartupTiming( processor_name=processor.name, - start_time=self._mono_to_wall(arrival_ts), + start_offset_secs=start_offset_secs, duration_secs=duration_secs, ) ) @@ -302,7 +297,7 @@ class StartupTimingObserver(BaseObserver): delta_ns = data.timestamp - self._start_frame_arrival_ns client_connected_secs = delta_ns / 1e9 report = TransportTimingReport( - start_time=self._mono_to_wall(self._start_frame_arrival_ns), + start_time=self._start_wall_clock or 0.0, bot_connected_secs=self._bot_connected_secs, client_connected_secs=client_connected_secs, ) @@ -315,10 +310,9 @@ class StartupTimingObserver(BaseObserver): self._startup_timing_reported = True total = sum(t.duration_secs for t in self._timings) - start_time = self._timings[0].start_time if self._timings else 0.0 report = StartupTimingReport( - start_time=start_time, + start_time=self._start_wall_clock or 0.0, total_duration_secs=total, processor_timings=self._timings, ) diff --git a/tests/test_startup_timing_observer.py b/tests/test_startup_timing_observer.py index 2bc246754..6355c6081 100644 --- a/tests/test_startup_timing_observer.py +++ b/tests/test_startup_timing_observer.py @@ -155,7 +155,7 @@ class TestStartupTimingObserver(unittest.IsolatedAsyncioTestCase): for timing in report.processor_timings: self.assertIsInstance(timing.processor_name, str) self.assertIsInstance(timing.duration_secs, float) - self.assertGreater(timing.start_time, 0) + self.assertGreaterEqual(timing.start_offset_secs, 0) async def test_excludes_internal_processors(self): """Test that internal pipeline processors are excluded by default.""" From 0cfd953a900f388a09ca40cedf3f49775f6d1cae Mon Sep 17 00:00:00 2001 From: Mark Backman Date: Mon, 2 Mar 2026 14:15:41 -0500 Subject: [PATCH 0739/1060] Use _ArrivalInfo dataclass instead of tuple for arrival tracking --- .../observers/startup_timing_observer.py | 25 +++++++++++++------ 1 file changed, 17 insertions(+), 8 deletions(-) diff --git a/src/pipecat/observers/startup_timing_observer.py b/src/pipecat/observers/startup_timing_observer.py index 8233ed2b8..d4a010d33 100644 --- a/src/pipecat/observers/startup_timing_observer.py +++ b/src/pipecat/observers/startup_timing_observer.py @@ -35,6 +35,7 @@ Example:: """ import time +from dataclasses import dataclass from typing import Dict, List, Optional, Tuple, Type from pydantic import BaseModel, Field @@ -49,6 +50,14 @@ from pipecat.processors.frame_processor import FrameProcessor _INTERNAL_TYPES = (PipelineSink, PipelineSource, BasePipeline) +@dataclass +class _ArrivalInfo: + """Internal record of when a StartFrame arrived at a processor.""" + + processor: FrameProcessor + arrival_ts_ns: int + + class ProcessorStartupTiming(BaseModel): """Startup timing for a single processor. @@ -161,8 +170,8 @@ class StartupTimingObserver(BaseObserver): super().__init__(**kwargs) self._processor_types = processor_types - # Map processor ID -> (processor, arrival_timestamp_ns) - self._arrivals: Dict[int, Tuple[FrameProcessor, int]] = {} + # Map processor ID -> arrival info. + self._arrivals: Dict[int, _ArrivalInfo] = {} # Collected timings in pipeline order. self._timings: List[ProcessorStartupTiming] = [] @@ -234,7 +243,9 @@ class StartupTimingObserver(BaseObserver): return if self._should_track(data.processor): - self._arrivals[data.processor.id] = (data.processor, data.timestamp) + self._arrivals[data.processor.id] = _ArrivalInfo( + processor=data.processor, arrival_ts_ns=data.timestamp + ) async def on_push_frame(self, data: FramePushed): """Record when a StartFrame leaves a processor and compute the delta. @@ -266,15 +277,13 @@ class StartupTimingObserver(BaseObserver): if arrival is None: return - processor, arrival_ts = arrival - duration_ns = data.timestamp - arrival_ts + duration_ns = data.timestamp - arrival.arrival_ts_ns duration_secs = duration_ns / 1e9 - - start_offset_secs = (arrival_ts - self._start_frame_arrival_ns) / 1e9 + start_offset_secs = (arrival.arrival_ts_ns - self._start_frame_arrival_ns) / 1e9 self._timings.append( ProcessorStartupTiming( - processor_name=processor.name, + processor_name=arrival.processor.name, start_offset_secs=start_offset_secs, duration_secs=duration_secs, ) From 389d0c3fb6adbbf7d926a3e3a6fea49a8aaae3d0 Mon Sep 17 00:00:00 2001 From: Mark Backman Date: Mon, 2 Mar 2026 14:33:55 -0500 Subject: [PATCH 0740/1060] Use on_pipeline_started from PipelineTask for startup report Replace the PipelineSink detection in StartupTimingObserver with an on_pipeline_started() callback from PipelineTask via TaskObserver. This fixes premature report emission when using ParallelPipeline, which has its own inner PipelineSinks per branch. --- src/pipecat/observers/base_observer.py | 8 +++++ .../observers/startup_timing_observer.py | 31 +++++++++---------- src/pipecat/pipeline/task.py | 1 + src/pipecat/pipeline/task_observer.py | 14 ++++++++- 4 files changed, 37 insertions(+), 17 deletions(-) diff --git a/src/pipecat/observers/base_observer.py b/src/pipecat/observers/base_observer.py index 78e36fec8..70c79224a 100644 --- a/src/pipecat/observers/base_observer.py +++ b/src/pipecat/observers/base_observer.py @@ -100,3 +100,11 @@ class BaseObserver(BaseObject): data: The event data containing details about the frame transfer. """ pass + + async def on_pipeline_started(self): + """Called when the pipeline has fully started. + + Fired after the ``StartFrame`` has been processed by all processors + in the pipeline, including nested ``ParallelPipeline`` branches. + """ + pass diff --git a/src/pipecat/observers/startup_timing_observer.py b/src/pipecat/observers/startup_timing_observer.py index d4a010d33..a1ea04d47 100644 --- a/src/pipecat/observers/startup_timing_observer.py +++ b/src/pipecat/observers/startup_timing_observer.py @@ -43,11 +43,11 @@ from pydantic import BaseModel, Field from pipecat.frames.frames import BotConnectedFrame, ClientConnectedFrame, StartFrame from pipecat.observers.base_observer import BaseObserver, FrameProcessed, FramePushed from pipecat.pipeline.base_pipeline import BasePipeline -from pipecat.pipeline.pipeline import PipelineSink, PipelineSource +from pipecat.pipeline.pipeline import PipelineSource from pipecat.processors.frame_processor import FrameProcessor # Internal pipeline types excluded from tracking by default. -_INTERNAL_TYPES = (PipelineSink, PipelineSource, BasePipeline) +_INTERNAL_TYPES = (PipelineSource, BasePipeline) @dataclass @@ -118,9 +118,9 @@ class StartupTimingObserver(BaseObserver): - ``client_connected_secs``: When a remote participant connects (triggered by ``ClientConnectedFrame``). - By default, internal pipeline processors (``PipelineSource``, ``PipelineSink``, - ``Pipeline``) are excluded from the report. Pass ``processor_types`` to - measure only specific types. + By default, internal pipeline processors (``PipelineSource``, ``Pipeline``) + are excluded from the report. Pass ``processor_types`` to measure only + specific types. Event handlers available: @@ -211,12 +211,19 @@ class StartupTimingObserver(BaseObserver): # Default: exclude internal pipeline plumbing. return not isinstance(processor, _INTERNAL_TYPES) + async def on_pipeline_started(self): + """Emit the startup timing report when the pipeline has fully started. + + Called by the ``PipelineTask`` after the ``StartFrame`` has been + processed by all processors, including nested ``ParallelPipeline`` + branches. + """ + if self._timings: + await self._emit_report() + async def on_process_frame(self, data: FrameProcessed): """Record when a StartFrame arrives at a processor. - When a ``StartFrame`` reaches a ``PipelineSink``, startup is complete - (the frame has traversed the entire pipeline) and the report is emitted. - Args: data: The frame processing event data. """ @@ -234,14 +241,6 @@ class StartupTimingObserver(BaseObserver): elif data.frame.id != self._start_frame_id: return - # When the StartFrame reaches a PipelineSink, all processors have - # completed start(). PipelineSinks use direct mode so the outermost - # sink fires last within the same synchronous call chain. - if isinstance(data.processor, PipelineSink): - if self._timings: - await self._emit_report() - return - if self._should_track(data.processor): self._arrivals[data.processor.id] = _ArrivalInfo( processor=data.processor, arrival_ts_ns=data.timestamp diff --git a/src/pipecat/pipeline/task.py b/src/pipecat/pipeline/task.py index deae6290c..906d55eb6 100644 --- a/src/pipecat/pipeline/task.py +++ b/src/pipecat/pipeline/task.py @@ -915,6 +915,7 @@ class PipelineTask(BasePipelineTask): if isinstance(frame, StartFrame): await self._call_event_handler("on_pipeline_started", frame) + await self._observer.on_pipeline_started() # Start heartbeat tasks now that StartFrame has been processed # by all processors in the pipeline diff --git a/src/pipecat/pipeline/task_observer.py b/src/pipecat/pipeline/task_observer.py index 4d33fd60e..dc2040e07 100644 --- a/src/pipecat/pipeline/task_observer.py +++ b/src/pipecat/pipeline/task_observer.py @@ -39,6 +39,12 @@ class Proxy: observer: BaseObserver +class _PipelineStartedSignal: + """Internal sentinel queued to observers when the pipeline has started.""" + + pass + + class TaskObserver(BaseObserver): """Proxy observer that manages multiple observers without blocking the pipeline. @@ -129,6 +135,10 @@ class TaskObserver(BaseObserver): for proxy in self._proxies: await proxy.cleanup() + async def on_pipeline_started(self): + """Forward pipeline started signal to all managed observers.""" + await self._send_to_proxy(_PipelineStartedSignal()) + async def on_process_frame(self, data: FrameProcessed): """Queue frame data for all managed observers. @@ -186,7 +196,9 @@ class TaskObserver(BaseObserver): while True: data = await queue.get() - if isinstance(data, FramePushed): + if isinstance(data, _PipelineStartedSignal): + await observer.on_pipeline_started() + elif isinstance(data, FramePushed): if on_push_frame_deprecated: await observer.on_push_frame( data.source, data.destination, data.frame, data.direction, data.timestamp From c1743dcffd16e05785c7c68317981280b299de94 Mon Sep 17 00:00:00 2001 From: Mark Backman Date: Mon, 2 Mar 2026 15:22:44 -0500 Subject: [PATCH 0741/1060] Rename Tavus event, on_connected --- src/pipecat/transports/tavus/transport.py | 13 +++++++------ 1 file changed, 7 insertions(+), 6 deletions(-) diff --git a/src/pipecat/transports/tavus/transport.py b/src/pipecat/transports/tavus/transport.py index 6db44d431..cb6844250 100644 --- a/src/pipecat/transports/tavus/transport.py +++ b/src/pipecat/transports/tavus/transport.py @@ -134,12 +134,12 @@ class TavusCallbacks(BaseModel): """Callback handlers for Tavus events. Parameters: - on_joined: Called when the bot joins the Daily room. + on_connected: Called when the bot connects to the room. on_participant_joined: Called when a participant joins the conversation. on_participant_left: Called when a participant leaves the conversation. """ - on_joined: Callable[[Mapping[str, Any]], Awaitable[None]] + on_connected: Callable[[Mapping[str, Any]], Awaitable[None]] on_participant_joined: Callable[[Mapping[str, Any]], Awaitable[None]] on_participant_left: Callable[[Mapping[str, Any], str], Awaitable[None]] @@ -274,7 +274,7 @@ class TavusTransportClient: async def _on_joined(self, data): """Handle joined event.""" logger.debug("TavusTransportClient joined!") - await self._callbacks.on_joined(data) + await self._callbacks.on_connected(data) async def _on_left(self): """Handle left event.""" @@ -669,6 +669,7 @@ class TavusTransport(BaseTransport): Event handlers available: + - on_connected(transport, data): Bot connected to the room - on_client_connected(transport, participant): Participant connected to the session - on_client_disconnected(transport, participant): Participant disconnected from the session @@ -707,7 +708,7 @@ class TavusTransport(BaseTransport): self._params = params callbacks = TavusCallbacks( - on_joined=self._on_joined, + on_connected=self._on_joined, on_participant_joined=self._on_participant_joined, on_participant_left=self._on_participant_left, ) @@ -726,13 +727,13 @@ class TavusTransport(BaseTransport): # Register supported handlers. The user will only be able to register # these handlers. - self._register_event_handler("on_joined") + self._register_event_handler("on_connected") self._register_event_handler("on_client_connected") self._register_event_handler("on_client_disconnected") async def _on_joined(self, data): """Handle bot joined room event.""" - await self._call_event_handler("on_joined", data) + await self._call_event_handler("on_connected", data) if self._input: await self._input.push_frame(BotConnectedFrame()) From dbdb54ce0f306a38fb0d49f0d8146d5594f9cd39 Mon Sep 17 00:00:00 2001 From: Mark Backman Date: Mon, 2 Mar 2026 15:44:37 -0500 Subject: [PATCH 0742/1060] Add on_connected event handler to DailyTransport for cross-transport consistency --- src/pipecat/transports/daily/transport.py | 5 +++++ 1 file changed, 5 insertions(+) diff --git a/src/pipecat/transports/daily/transport.py b/src/pipecat/transports/daily/transport.py index 97aebe915..dc9868426 100644 --- a/src/pipecat/transports/daily/transport.py +++ b/src/pipecat/transports/daily/transport.py @@ -2072,6 +2072,8 @@ class DailyTransport(BaseTransport): Event handlers available: - on_joined: Called when the bot joins the room. Args: (data: dict) + - on_connected: Called when the bot connects to the room (alias for + on_joined). Args: (data: dict) - on_left: Called when the bot leaves the room. - on_before_leave: [sync] Called just before the bot leaves the room. - on_error: Called when a transport error occurs. Args: (error: str) @@ -2189,6 +2191,7 @@ class DailyTransport(BaseTransport): # Register supported handlers. The user will only be able to register # these handlers. self._register_event_handler("on_active_speaker_changed") + self._register_event_handler("on_connected") self._register_event_handler("on_joined") self._register_event_handler("on_left") self._register_event_handler("on_error") @@ -2580,6 +2583,8 @@ class DailyTransport(BaseTransport): if error: await self._on_error(f"Unable to start transcription: {error}") await self._call_event_handler("on_joined", data) + # Also call on_connected for compatibility with other transports + await self._call_event_handler("on_connected", data) if self._input: await self._input.push_frame(BotConnectedFrame()) From 98bd530574abe8e9b456a24fcb1b38ddbdd84ce7 Mon Sep 17 00:00:00 2001 From: Mark Backman Date: Sat, 28 Feb 2026 14:05:25 -0500 Subject: [PATCH 0743/1060] Add changelog for #3881 --- changelog/3881.added.md | 2 +- .../utils/tracing/service_attributes.py | 14 ++++++-------- .../utils/tracing/service_decorators.py | 19 ++++++++++++------- 3 files changed, 19 insertions(+), 16 deletions(-) diff --git a/changelog/3881.added.md b/changelog/3881.added.md index cbf6d0293..c71475675 100644 --- a/changelog/3881.added.md +++ b/changelog/3881.added.md @@ -1 +1 @@ -- Added `StartupTimingObserver` for measuring how long each processor's `start()` method takes during pipeline startup. Also measures transport readiness — the time from `StartFrame` to first client connection — via the `on_transport_readiness_measured` event. Useful for diagnosing cold start slowness and identifying initialization bottlenecks. +- Added `StartupTimingObserver` for measuring how long each processor's `start()` method takes during pipeline startup. Also measures transport readiness — the time from `StartFrame` to first client connection — via the `on_transport_timing_report` event. diff --git a/src/pipecat/utils/tracing/service_attributes.py b/src/pipecat/utils/tracing/service_attributes.py index 97ac49d87..c8471a03b 100644 --- a/src/pipecat/utils/tracing/service_attributes.py +++ b/src/pipecat/utils/tracing/service_attributes.py @@ -17,8 +17,6 @@ from typing import TYPE_CHECKING, Any, Dict, List, Optional if TYPE_CHECKING: from opentelemetry.trace import Span - from pipecat.services.settings import ServiceSettings - from pipecat.utils.tracing.setup import is_tracing_available if is_tracing_available(): @@ -70,7 +68,7 @@ def add_tts_span_attributes( model: str, voice_id: str, text: Optional[str] = None, - settings: Optional["ServiceSettings"] = None, + settings: Optional[Dict[str, Any]] = None, character_count: Optional[int] = None, operation_name: str = "tts", ttfb: Optional[float] = None, @@ -109,7 +107,7 @@ def add_tts_span_attributes( # Add settings if provided if settings: - for key, value in settings.given_fields().items(): + for key, value in settings.items(): if isinstance(value, (str, int, float, bool)): span.set_attribute(f"settings.{key}", value) @@ -128,7 +126,7 @@ def add_stt_span_attributes( is_final: Optional[bool] = None, language: Optional[str] = None, user_id: Optional[str] = None, - settings: Optional["ServiceSettings"] = None, + settings: Optional[Dict[str, Any]] = None, vad_enabled: bool = False, ttfb: Optional[float] = None, **kwargs, @@ -173,7 +171,7 @@ def add_stt_span_attributes( # Add settings if provided if settings: - for key, value in settings.given_fields().items(): + for key, value in settings.items(): if isinstance(value, (str, int, float, bool)): span.set_attribute(f"settings.{key}", value) @@ -284,7 +282,7 @@ def add_gemini_live_span_attributes( voice_id: Optional[str] = None, language: Optional[str] = None, modalities: Optional[str] = None, - settings: Optional["ServiceSettings"] = None, + settings: Optional[Dict[str, Any]] = None, tools: Optional[List[Dict]] = None, tools_serialized: Optional[str] = None, transcript: Optional[str] = None, @@ -361,7 +359,7 @@ def add_gemini_live_span_attributes( # Add settings if provided if settings: - for key, value in settings.given_fields().items(): + for key, value in settings.items(): if isinstance(value, (str, int, float, bool)): span.set_attribute(f"settings.{key}", value) elif key == "vad" and value: diff --git a/src/pipecat/utils/tracing/service_decorators.py b/src/pipecat/utils/tracing/service_decorators.py index 304ecb5e8..601cad53d 100644 --- a/src/pipecat/utils/tracing/service_decorators.py +++ b/src/pipecat/utils/tracing/service_decorators.py @@ -219,7 +219,7 @@ def traced_tts(func: Optional[Callable] = None, *, name: Optional[str] = None) - tracer = trace.get_tracer("pipecat") with tracer.start_as_current_span(span_name, context=parent_context) as span: try: - settings = getattr(self, "_settings", None) + settings = getattr(self, "_settings", {}) add_tts_span_attributes( span=span, service_name=service_class_name, @@ -338,7 +338,7 @@ def traced_stt(func: Optional[Callable] = None, *, name: Optional[str] = None) - ) # Use settings from the service if available - settings = getattr(self, "_settings", None) + settings = getattr(self, "_settings", {}) add_stt_span_attributes( span=current_span, @@ -510,10 +510,15 @@ def traced_llm(func: Optional[Callable] = None, *, name: Optional[str] = None) - # Get settings from the service params = {} if hasattr(self, "_settings"): - for key, value in self._settings.given_fields().items(): + for key, value in self._settings.items(): + if key == "extra": + continue + # Add value directly if it's a basic type if isinstance(value, (int, float, bool, str)): params[key] = value - elif value is None: + elif value is None or ( + hasattr(value, "__name__") and value.__name__ == "NOT_GIVEN" + ): params[key] = "NOT_GIVEN" # Add all available attributes to the span @@ -622,12 +627,12 @@ def traced_gemini_live(operation: str) -> Callable: model_name = _get_model_name(self) voice_id = getattr(self, "_voice_id", None) language_code = getattr(self, "_language_code", None) - settings = getattr(self, "_settings", None) + settings = getattr(self, "_settings", {}) # Get modalities if available modalities = None - if settings and hasattr(settings, "modalities"): - modality_obj = settings.modalities + if hasattr(self, "_settings") and "modalities" in self._settings: + modality_obj = self._settings["modalities"] if hasattr(modality_obj, "value"): modalities = modality_obj.value else: From ac69b3441e1161120138d43af11ca6cb12aac8c7 Mon Sep 17 00:00:00 2001 From: Mark Backman Date: Fri, 27 Feb 2026 22:35:29 -0500 Subject: [PATCH 0744/1060] Fix tracing to use ServiceSettings API instead of dict access The ServiceSettings refactor (PR #3714) changed self._settings from dicts to dataclass subclasses, but tracing code still used .items(), in containment, and subscript access, causing AttributeError on every traced call. Use given_fields() for iteration and attribute access for named fields. --- .../utils/tracing/service_attributes.py | 14 ++++++++------ .../utils/tracing/service_decorators.py | 19 +++++++------------ 2 files changed, 15 insertions(+), 18 deletions(-) diff --git a/src/pipecat/utils/tracing/service_attributes.py b/src/pipecat/utils/tracing/service_attributes.py index c8471a03b..97ac49d87 100644 --- a/src/pipecat/utils/tracing/service_attributes.py +++ b/src/pipecat/utils/tracing/service_attributes.py @@ -17,6 +17,8 @@ from typing import TYPE_CHECKING, Any, Dict, List, Optional if TYPE_CHECKING: from opentelemetry.trace import Span + from pipecat.services.settings import ServiceSettings + from pipecat.utils.tracing.setup import is_tracing_available if is_tracing_available(): @@ -68,7 +70,7 @@ def add_tts_span_attributes( model: str, voice_id: str, text: Optional[str] = None, - settings: Optional[Dict[str, Any]] = None, + settings: Optional["ServiceSettings"] = None, character_count: Optional[int] = None, operation_name: str = "tts", ttfb: Optional[float] = None, @@ -107,7 +109,7 @@ def add_tts_span_attributes( # Add settings if provided if settings: - for key, value in settings.items(): + for key, value in settings.given_fields().items(): if isinstance(value, (str, int, float, bool)): span.set_attribute(f"settings.{key}", value) @@ -126,7 +128,7 @@ def add_stt_span_attributes( is_final: Optional[bool] = None, language: Optional[str] = None, user_id: Optional[str] = None, - settings: Optional[Dict[str, Any]] = None, + settings: Optional["ServiceSettings"] = None, vad_enabled: bool = False, ttfb: Optional[float] = None, **kwargs, @@ -171,7 +173,7 @@ def add_stt_span_attributes( # Add settings if provided if settings: - for key, value in settings.items(): + for key, value in settings.given_fields().items(): if isinstance(value, (str, int, float, bool)): span.set_attribute(f"settings.{key}", value) @@ -282,7 +284,7 @@ def add_gemini_live_span_attributes( voice_id: Optional[str] = None, language: Optional[str] = None, modalities: Optional[str] = None, - settings: Optional[Dict[str, Any]] = None, + settings: Optional["ServiceSettings"] = None, tools: Optional[List[Dict]] = None, tools_serialized: Optional[str] = None, transcript: Optional[str] = None, @@ -359,7 +361,7 @@ def add_gemini_live_span_attributes( # Add settings if provided if settings: - for key, value in settings.items(): + for key, value in settings.given_fields().items(): if isinstance(value, (str, int, float, bool)): span.set_attribute(f"settings.{key}", value) elif key == "vad" and value: diff --git a/src/pipecat/utils/tracing/service_decorators.py b/src/pipecat/utils/tracing/service_decorators.py index 601cad53d..304ecb5e8 100644 --- a/src/pipecat/utils/tracing/service_decorators.py +++ b/src/pipecat/utils/tracing/service_decorators.py @@ -219,7 +219,7 @@ def traced_tts(func: Optional[Callable] = None, *, name: Optional[str] = None) - tracer = trace.get_tracer("pipecat") with tracer.start_as_current_span(span_name, context=parent_context) as span: try: - settings = getattr(self, "_settings", {}) + settings = getattr(self, "_settings", None) add_tts_span_attributes( span=span, service_name=service_class_name, @@ -338,7 +338,7 @@ def traced_stt(func: Optional[Callable] = None, *, name: Optional[str] = None) - ) # Use settings from the service if available - settings = getattr(self, "_settings", {}) + settings = getattr(self, "_settings", None) add_stt_span_attributes( span=current_span, @@ -510,15 +510,10 @@ def traced_llm(func: Optional[Callable] = None, *, name: Optional[str] = None) - # Get settings from the service params = {} if hasattr(self, "_settings"): - for key, value in self._settings.items(): - if key == "extra": - continue - # Add value directly if it's a basic type + for key, value in self._settings.given_fields().items(): if isinstance(value, (int, float, bool, str)): params[key] = value - elif value is None or ( - hasattr(value, "__name__") and value.__name__ == "NOT_GIVEN" - ): + elif value is None: params[key] = "NOT_GIVEN" # Add all available attributes to the span @@ -627,12 +622,12 @@ def traced_gemini_live(operation: str) -> Callable: model_name = _get_model_name(self) voice_id = getattr(self, "_voice_id", None) language_code = getattr(self, "_language_code", None) - settings = getattr(self, "_settings", {}) + settings = getattr(self, "_settings", None) # Get modalities if available modalities = None - if hasattr(self, "_settings") and "modalities" in self._settings: - modality_obj = self._settings["modalities"] + if settings and hasattr(settings, "modalities"): + modality_obj = settings.modalities if hasattr(modality_obj, "value"): modalities = modality_obj.value else: From 18155b6a633868b35c4a5210d1c0283cd143d6b0 Mon Sep 17 00:00:00 2001 From: Mark Backman Date: Sun, 1 Mar 2026 07:40:02 -0500 Subject: [PATCH 0745/1060] Add latency breakdown to UserBotLatencyObserver MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit Add per-service latency breakdown metrics alongside existing user-to-bot latency measurement. When enable_metrics=True, the observer now emits an on_latency_breakdown event with TTFB, text aggregation, and user turn duration metrics collected between VADUserStoppedSpeakingFrame and BotStartedSpeakingFrame. - Add LatencyBreakdown dataclass with ttfb, text_aggregation, user_turn_secs fields - Accumulate MetricsFrame data during user→bot cycles - Reset accumulators on InterruptionFrame to discard stale metrics - Measure user_turn_secs from actual user silence (VAD timestamp - stop_secs) to turn release (UserStoppedSpeakingFrame) - Filter zero-value TTFB entries from startup metric resets - Add frame deduplication using bounded deque + set pattern - Update example 29 with latency breakdown display --- changelog/3885.added.md | 1 + .../foundational/29-turn-tracking-observer.py | 20 ++ .../observers/user_bot_latency_observer.py | 144 +++++++++-- tests/test_user_bot_latency_observer.py | 230 +++++++++++++++++- 4 files changed, 371 insertions(+), 24 deletions(-) create mode 100644 changelog/3885.added.md diff --git a/changelog/3885.added.md b/changelog/3885.added.md new file mode 100644 index 000000000..0713bbd45 --- /dev/null +++ b/changelog/3885.added.md @@ -0,0 +1 @@ +- Added `LatencyBreakdown` dataclass and `on_latency_breakdown` event to `UserBotLatencyObserver` for per-service latency metrics (TTFB, text aggregation, user turn duration) collected during each user-to-bot response cycle. diff --git a/examples/foundational/29-turn-tracking-observer.py b/examples/foundational/29-turn-tracking-observer.py index 4af28f1ed..736c68c55 100644 --- a/examples/foundational/29-turn-tracking-observer.py +++ b/examples/foundational/29-turn-tracking-observer.py @@ -131,6 +131,26 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): else: logger.info(f"🏁 Turn {turn_number} completed in {duration:.2f}s") + @latency_observer.event_handler("on_latency_breakdown") + async def on_latency_breakdown(observer, breakdown): + # Display a sequential waterfall that roughly adds up to the total. + # User turn is the first stage: user silence → turn release. + # The STT TTFB is shown as context within the user turn since + # it's a component of that time (along with VAD silence and any + # turn analyzer delay). + stt_ttfb = next((t for t in breakdown.ttfb if "STT" in t.processor), None) + if breakdown.user_turn_secs is not None: + stt_note = f" (STT: {stt_ttfb.value:.3f}s)" if stt_ttfb else "" + logger.info(f" User turn: {breakdown.user_turn_secs:.3f}s{stt_note}") + + for ttfb in breakdown.ttfb: + if ttfb is not stt_ttfb: + logger.info(f" {ttfb.processor}: TTFB {ttfb.value:.3f}s") + + if breakdown.text_aggregation: + ta = breakdown.text_aggregation + logger.info(f" {ta.processor}: text aggregation {ta.value:.3f}s") + @transport.event_handler("on_client_connected") async def on_client_connected(transport, client): logger.info(f"Client connected") diff --git a/src/pipecat/observers/user_bot_latency_observer.py b/src/pipecat/observers/user_bot_latency_observer.py index 37d5bc1a0..a7ad579f3 100644 --- a/src/pipecat/observers/user_bot_latency_observer.py +++ b/src/pipecat/observers/user_bot_latency_observer.py @@ -1,22 +1,63 @@ +# +# Copyright (c) 2024-2026, Daily +# +# SPDX-License-Identifier: BSD 2-Clause License +# + """Observer for tracking user-to-bot response latency. This module provides an observer that monitors the time between when a user stops speaking and when the bot starts speaking, emitting events when latency -is measured. +is measured. Optionally collects per-service latency breakdown metrics +(TTFB, text aggregation) when ``enable_metrics=True``. """ import time -from typing import Optional, Set +from collections import deque +from dataclasses import dataclass, field +from typing import List, Optional from pipecat.frames.frames import ( BotStartedSpeakingFrame, + InterruptionFrame, + MetricsFrame, + UserStoppedSpeakingFrame, VADUserStartedSpeakingFrame, VADUserStoppedSpeakingFrame, ) +from pipecat.metrics.metrics import ( + TextAggregationMetricsData, + TTFBMetricsData, +) from pipecat.observers.base_observer import BaseObserver, FramePushed from pipecat.processors.frame_processor import FrameDirection +@dataclass +class LatencyBreakdown: + """Per-service latency breakdown for a single user-to-bot cycle. + + Collected between ``VADUserStoppedSpeakingFrame`` and + ``BotStartedSpeakingFrame`` when ``enable_metrics=True`` in + :class:`~pipecat.pipeline.task.PipelineParams`. + + Parameters: + ttfb: Time-to-first-byte metrics from each service in the pipeline. + text_aggregation: First text aggregation measurement, representing + the latency cost of sentence aggregation in the TTS pipeline. + user_turn_secs: Duration in seconds of the user's turn, measured + from when the user actually stopped speaking to when the turn + was released (``UserStoppedSpeakingFrame``). This includes + VAD silence detection, STT finalization, and any turn analyzer + wait. ``None`` if no ``UserStoppedSpeakingFrame`` was observed + (e.g. no turn analyzer configured). + """ + + ttfb: List[TTFBMetricsData] = field(default_factory=list) + text_aggregation: Optional[TextAggregationMetricsData] = None + user_turn_secs: Optional[float] = None + + class UserBotLatencyObserver(BaseObserver): """Observer that tracks user-to-bot response latency. @@ -25,34 +66,54 @@ class UserBotLatencyObserver(BaseObserver): latency is measured, allowing consumers to log, trace, or otherwise process the latency data. + When ``enable_metrics=True`` in pipeline params, also collects per-service + latency breakdown (TTFB, text aggregation) and emits an + ``on_latency_breakdown`` event alongside the existing latency measurement. + This observer follows the composition pattern used by TurnTrackingObserver, acting as a reusable component for latency measurement. Events: - on_latency_measured(observer, latency_seconds): Emitted when user-to-bot - latency is calculated. Includes the latency value in seconds as a float. + on_latency_measured(observer, latency_seconds): Emitted when + time-to-first-bot-speech is calculated. Measures the time from + when the user stopped speaking to when the bot starts speaking. + on_latency_breakdown(observer, breakdown): Emitted at each + ``BotStartedSpeakingFrame`` with a :class:`LatencyBreakdown` + containing per-service metrics collected during the user→bot cycle. """ - def __init__(self, **kwargs): + def __init__(self, *, max_frames=100, **kwargs): """Initialize the user-bot latency observer. Sets up tracking for processed frames and user speech timing to calculate response latencies. Args: + max_frames: Maximum number of frame IDs to keep in history for + duplicate detection. Defaults to 100. **kwargs: Additional arguments passed to parent class. """ super().__init__(**kwargs) self._user_stopped_time: Optional[float] = None - self._processed_frames: Set[str] = set() + self._user_turn: Optional[float] = None + + # Frame deduplication (bounded deque + set pattern) + self._processed_frames: set = set() + self._frame_history: deque = deque(maxlen=max_frames) + + # Per-cycle metric accumulators + self._ttfb: List[TTFBMetricsData] = [] + self._text_aggregation: Optional[TextAggregationMetricsData] = None self._register_event_handler("on_latency_measured") + self._register_event_handler("on_latency_breakdown") async def on_push_frame(self, data: FramePushed): """Process frames to track speech timing and calculate latency. Tracks VAD events and bot speaking events to measure the time between - user stopping speech and bot starting speech. + user stopping speech and bot starting speech. Also accumulates metrics + from MetricsFrame for the latency breakdown. Args: data: Frame push event containing the frame and direction information. @@ -61,23 +122,78 @@ class UserBotLatencyObserver(BaseObserver): if data.direction != FrameDirection.DOWNSTREAM: return - # Skip already processed frames + # Skip already processed frames (bounded deque + set) if data.frame.id in self._processed_frames: return self._processed_frames.add(data.frame.id) + self._frame_history.append(data.frame.id) - # Track VAD and bot speaking events for latency + if len(self._processed_frames) > len(self._frame_history): + self._processed_frames = set(self._frame_history) + + # Track speech and pipeline events for latency if isinstance(data.frame, VADUserStartedSpeakingFrame): # Reset when user starts speaking self._user_stopped_time = None + self._user_turn = None + self._reset_accumulators() elif isinstance(data.frame, VADUserStoppedSpeakingFrame): # Record the actual time the user stopped speaking, which is # the VAD determination time minus the stop_secs silence duration # that had to elapse before the VAD confirmed speech ended. self._user_stopped_time = data.frame.timestamp - data.frame.stop_secs - elif isinstance(data.frame, BotStartedSpeakingFrame) and self._user_stopped_time: - # Calculate and emit latency - latency = time.time() - self._user_stopped_time - self._user_stopped_time = None - await self._call_event_handler("on_latency_measured", latency) + elif isinstance(data.frame, UserStoppedSpeakingFrame): + # Measure the user turn duration: from actual user silence to + # turn release. Includes VAD silence detection, STT finalization, + # and any turn analyzer wait. + if self._user_stopped_time is not None: + self._user_turn = time.time() - self._user_stopped_time + elif isinstance(data.frame, InterruptionFrame): + # Discard stale metrics from cancelled LLM/TTS cycles + self._reset_accumulators() + elif isinstance(data.frame, MetricsFrame): + self._handle_metrics_frame(data.frame) + elif isinstance(data.frame, BotStartedSpeakingFrame): + await self._handle_bot_started_speaking() + + async def _handle_bot_started_speaking(self): + """Handle BotStartedSpeakingFrame to emit latency and breakdown.""" + if self._user_stopped_time is None: + return + + latency = time.time() - self._user_stopped_time + self._user_stopped_time = None + await self._call_event_handler("on_latency_measured", latency) + + breakdown = LatencyBreakdown( + ttfb=list(self._ttfb), + text_aggregation=self._text_aggregation, + user_turn_secs=self._user_turn, + ) + await self._call_event_handler("on_latency_breakdown", breakdown) + self._reset_accumulators() + + def _handle_metrics_frame(self, frame: MetricsFrame): + """Extract latency metrics from a MetricsFrame. + + Only accumulates metrics when a user→bot measurement is in progress + (after ``VADUserStoppedSpeakingFrame``). + """ + if self._user_stopped_time is None: + return + + for metrics_data in frame.data: + if isinstance(metrics_data, TTFBMetricsData) and metrics_data.value > 0: + self._ttfb.append(metrics_data) + elif isinstance(metrics_data, TextAggregationMetricsData): + # Only keep the first measurement — it's the one that + # impacts the initial speaking latency. + if self._text_aggregation is None: + self._text_aggregation = metrics_data + + def _reset_accumulators(self): + """Clear per-cycle metric accumulators.""" + self._ttfb = [] + self._text_aggregation = None + self._user_turn = None diff --git a/tests/test_user_bot_latency_observer.py b/tests/test_user_bot_latency_observer.py index 1b7325d14..8f8b2893d 100644 --- a/tests/test_user_bot_latency_observer.py +++ b/tests/test_user_bot_latency_observer.py @@ -2,12 +2,19 @@ import unittest from pipecat.frames.frames import ( BotStartedSpeakingFrame, + InterruptionFrame, + MetricsFrame, + UserStoppedSpeakingFrame, VADUserStartedSpeakingFrame, VADUserStoppedSpeakingFrame, ) +from pipecat.metrics.metrics import ( + TextAggregationMetricsData, + TTFBMetricsData, +) from pipecat.observers.user_bot_latency_observer import UserBotLatencyObserver from pipecat.processors.filters.identity_filter import IdentityFilter -from pipecat.tests.utils import run_test +from pipecat.tests.utils import SleepFrame, run_test class TestUserBotLatencyObserver(unittest.IsolatedAsyncioTestCase): @@ -97,22 +104,226 @@ class TestUserBotLatencyObserver(unittest.IsolatedAsyncioTestCase): self.assertGreater(latencies[0], 0) self.assertGreater(latencies[1], 0) - async def test_no_measurement_without_user_stop(self): - """Test that latency is not measured if bot starts without user stopping first.""" - # Create observer + async def test_breakdown_with_metrics(self): + """Test that metrics collected between VADUserStopped and BotStarted appear in breakdown.""" + observer = UserBotLatencyObserver() + processor = IdentityFilter() + + breakdowns = [] + + @observer.event_handler("on_latency_breakdown") + async def on_breakdown(obs, breakdown): + breakdowns.append(breakdown) + + stt_ttfb = TTFBMetricsData(processor="DeepgramSTTService#0", value=0.080) + llm_ttfb = TTFBMetricsData(processor="OpenAILLMService#0", model="gpt-4o", value=0.250) + tts_ttfb = TTFBMetricsData(processor="CartesiaTTSService#0", value=0.070) + text_agg = TextAggregationMetricsData(processor="CartesiaTTSService#0", value=0.030) + + frames_to_send = [ + VADUserStoppedSpeakingFrame(), + MetricsFrame(data=[stt_ttfb]), + MetricsFrame(data=[llm_ttfb, text_agg]), + MetricsFrame(data=[tts_ttfb]), + BotStartedSpeakingFrame(), + ] + + expected_down_frames = [ + VADUserStoppedSpeakingFrame, + MetricsFrame, + MetricsFrame, + MetricsFrame, + BotStartedSpeakingFrame, + ] + + await run_test( + processor, + frames_to_send=frames_to_send, + expected_down_frames=expected_down_frames, + observers=[observer], + ) + + self.assertEqual(len(breakdowns), 1) + bd = breakdowns[0] + self.assertEqual(len(bd.ttfb), 3) + self.assertEqual(bd.ttfb[0].processor, "DeepgramSTTService#0") + self.assertEqual(bd.ttfb[1].processor, "OpenAILLMService#0") + self.assertEqual(bd.ttfb[2].processor, "CartesiaTTSService#0") + self.assertIsNotNone(bd.text_aggregation) + self.assertEqual(bd.text_aggregation.value, 0.030) + + async def test_interruption_resets_accumulators(self): + """Test that InterruptionFrame clears stale metrics from earlier cycles.""" + observer = UserBotLatencyObserver() + processor = IdentityFilter() + + breakdowns = [] + + @observer.event_handler("on_latency_breakdown") + async def on_breakdown(obs, breakdown): + breakdowns.append(breakdown) + + # First cycle metrics (will be interrupted) + stale_llm = TTFBMetricsData(processor="OpenAILLMService#0", value=0.245) + # Second cycle metrics (the ones that matter) + final_llm = TTFBMetricsData(processor="OpenAILLMService#0", value=0.224) + final_tts = TTFBMetricsData(processor="CartesiaTTSService#0", value=0.142) + + frames_to_send = [ + VADUserStoppedSpeakingFrame(), + MetricsFrame(data=[stale_llm]), + InterruptionFrame(), + MetricsFrame(data=[final_llm]), + MetricsFrame(data=[final_tts]), + BotStartedSpeakingFrame(), + ] + + expected_down_frames = [ + VADUserStoppedSpeakingFrame, + MetricsFrame, + InterruptionFrame, + MetricsFrame, + MetricsFrame, + BotStartedSpeakingFrame, + ] + + await run_test( + processor, + frames_to_send=frames_to_send, + expected_down_frames=expected_down_frames, + observers=[observer], + ) + + self.assertEqual(len(breakdowns), 1) + bd = breakdowns[0] + # Only the post-interruption metrics should be present + self.assertEqual(len(bd.ttfb), 2) + self.assertEqual(bd.ttfb[0].processor, "OpenAILLMService#0") + self.assertEqual(bd.ttfb[0].value, 0.224) + self.assertEqual(bd.ttfb[1].processor, "CartesiaTTSService#0") + self.assertEqual(bd.ttfb[1].value, 0.142) + + async def test_only_first_text_aggregation_kept(self): + """Test that only the first text aggregation metric is kept per cycle.""" + observer = UserBotLatencyObserver() + processor = IdentityFilter() + + breakdowns = [] + + @observer.event_handler("on_latency_breakdown") + async def on_breakdown(obs, breakdown): + breakdowns.append(breakdown) + + text_agg_1 = TextAggregationMetricsData(processor="CartesiaTTSService#0", value=0.030) + text_agg_2 = TextAggregationMetricsData(processor="CartesiaTTSService#0", value=0.080) + + frames_to_send = [ + VADUserStoppedSpeakingFrame(), + MetricsFrame(data=[text_agg_1]), + MetricsFrame(data=[text_agg_2]), + BotStartedSpeakingFrame(), + ] + + expected_down_frames = [ + VADUserStoppedSpeakingFrame, + MetricsFrame, + MetricsFrame, + BotStartedSpeakingFrame, + ] + + await run_test( + processor, + frames_to_send=frames_to_send, + expected_down_frames=expected_down_frames, + observers=[observer], + ) + + self.assertEqual(len(breakdowns), 1) + self.assertIsNotNone(breakdowns[0].text_aggregation) + self.assertEqual(breakdowns[0].text_aggregation.value, 0.030) + + async def test_user_turn_measured(self): + """Test that pre-LLM wait from user silence to UserStopped is captured.""" + observer = UserBotLatencyObserver() + processor = IdentityFilter() + + breakdowns = [] + + @observer.event_handler("on_latency_breakdown") + async def on_breakdown(obs, breakdown): + breakdowns.append(breakdown) + + frames_to_send = [ + VADUserStoppedSpeakingFrame(), + SleepFrame(sleep=0.1), # Simulate turn analyzer wait + UserStoppedSpeakingFrame(), + BotStartedSpeakingFrame(), + ] + + expected_down_frames = [ + VADUserStoppedSpeakingFrame, + UserStoppedSpeakingFrame, + BotStartedSpeakingFrame, + ] + + await run_test( + processor, + frames_to_send=frames_to_send, + expected_down_frames=expected_down_frames, + observers=[observer], + ) + + self.assertEqual(len(breakdowns), 1) + self.assertIsNotNone(breakdowns[0].user_turn_secs) + self.assertGreaterEqual(breakdowns[0].user_turn_secs, 0.1) + + async def test_user_turn_none_without_user_stopped(self): + """Test that user_turn is None when no UserStoppedSpeakingFrame arrives.""" + observer = UserBotLatencyObserver() + processor = IdentityFilter() + + breakdowns = [] + + @observer.event_handler("on_latency_breakdown") + async def on_breakdown(obs, breakdown): + breakdowns.append(breakdown) + + frames_to_send = [ + VADUserStoppedSpeakingFrame(), + BotStartedSpeakingFrame(), + ] + + expected_down_frames = [ + VADUserStoppedSpeakingFrame, + BotStartedSpeakingFrame, + ] + + await run_test( + processor, + frames_to_send=frames_to_send, + expected_down_frames=expected_down_frames, + observers=[observer], + ) + + self.assertEqual(len(breakdowns), 1) + self.assertIsNone(breakdowns[0].user_turn_secs) + + async def test_no_measurement_without_user_stop(self): + """Test that BotStartedSpeaking without prior user stop emits nothing.""" observer = UserBotLatencyObserver() - - # Create identity filter processor = IdentityFilter() - # Capture latency events latencies = [] + breakdowns = [] @observer.event_handler("on_latency_measured") async def on_latency(obs, latency_seconds): latencies.append(latency_seconds) - # Define frame sequence - bot starts without user stop + @observer.event_handler("on_latency_breakdown") + async def on_breakdown(obs, breakdown): + breakdowns.append(breakdown) + frames_to_send = [ BotStartedSpeakingFrame(), ] @@ -121,7 +332,6 @@ class TestUserBotLatencyObserver(unittest.IsolatedAsyncioTestCase): BotStartedSpeakingFrame, ] - # Run test await run_test( processor, frames_to_send=frames_to_send, @@ -129,8 +339,8 @@ class TestUserBotLatencyObserver(unittest.IsolatedAsyncioTestCase): observers=[observer], ) - # Verify no latency was measured self.assertEqual(len(latencies), 0) + self.assertEqual(len(breakdowns), 0) if __name__ == "__main__": From ddba1b84a937cceb6ebe602ebd67b42f3a2a374b Mon Sep 17 00:00:00 2001 From: Mark Backman Date: Sun, 1 Mar 2026 09:11:10 -0500 Subject: [PATCH 0746/1060] Add first-bot-speech latency to UserBotLatencyObserver Measure time from ClientConnectedFrame to first BotStartedSpeakingFrame, emitting a one-time on_first_bot_speech_latency event with breakdown. --- changelog/3885.added.2.md | 1 + changelog/3885.added.md | 2 +- .../foundational/29-turn-tracking-observer.py | 4 + .../observers/user_bot_latency_observer.py | 62 ++++++--- tests/test_user_bot_latency_observer.py | 121 ++++++++++++++++++ 5 files changed, 174 insertions(+), 16 deletions(-) create mode 100644 changelog/3885.added.2.md diff --git a/changelog/3885.added.2.md b/changelog/3885.added.2.md new file mode 100644 index 000000000..a9562b883 --- /dev/null +++ b/changelog/3885.added.2.md @@ -0,0 +1 @@ +- Added `on_first_bot_speech_latency` event to `UserBotLatencyObserver` measuring the time from client connection to first bot speech, including a latency breakdown with per-service metrics. diff --git a/changelog/3885.added.md b/changelog/3885.added.md index 0713bbd45..87cbd7824 100644 --- a/changelog/3885.added.md +++ b/changelog/3885.added.md @@ -1 +1 @@ -- Added `LatencyBreakdown` dataclass and `on_latency_breakdown` event to `UserBotLatencyObserver` for per-service latency metrics (TTFB, text aggregation, user turn duration) collected during each user-to-bot response cycle. +- Added `on_latency_breakdown` event to `UserBotLatencyObserver` providing per-service TTFB, text aggregation, and user turn duration metrics for each user-to-bot response cycle. diff --git a/examples/foundational/29-turn-tracking-observer.py b/examples/foundational/29-turn-tracking-observer.py index 736c68c55..2c8ec1f84 100644 --- a/examples/foundational/29-turn-tracking-observer.py +++ b/examples/foundational/29-turn-tracking-observer.py @@ -101,6 +101,10 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): observers=[latency_observer, startup_observer], ) + @latency_observer.event_handler("on_first_bot_speech_latency") + async def on_first_bot_speech_latency(observer, latency_seconds): + logger.info(f"First bot speech: {latency_seconds:.3f}s after client connected") + @latency_observer.event_handler("on_latency_measured") async def on_latency_measured(observer, latency_seconds): logger.info(f"⏱️ User-to-bot latency: {latency_seconds:.3f}s") diff --git a/src/pipecat/observers/user_bot_latency_observer.py b/src/pipecat/observers/user_bot_latency_observer.py index a7ad579f3..cdc7c43d0 100644 --- a/src/pipecat/observers/user_bot_latency_observer.py +++ b/src/pipecat/observers/user_bot_latency_observer.py @@ -19,6 +19,7 @@ from typing import List, Optional from pipecat.frames.frames import ( BotStartedSpeakingFrame, + ClientConnectedFrame, InterruptionFrame, MetricsFrame, UserStoppedSpeakingFrame, @@ -80,6 +81,10 @@ class UserBotLatencyObserver(BaseObserver): on_latency_breakdown(observer, breakdown): Emitted at each ``BotStartedSpeakingFrame`` with a :class:`LatencyBreakdown` containing per-service metrics collected during the user→bot cycle. + on_first_bot_speech_latency(observer, latency_seconds): Emitted once, + the first time ``BotStartedSpeakingFrame`` arrives after + ``ClientConnectedFrame``. Measures the time from client connection + to the first bot speech. """ def __init__(self, *, max_frames=100, **kwargs): @@ -97,6 +102,10 @@ class UserBotLatencyObserver(BaseObserver): self._user_stopped_time: Optional[float] = None self._user_turn: Optional[float] = None + # First bot speech tracking + self._client_connected_time: Optional[float] = None + self._first_bot_speech_measured: bool = False + # Frame deduplication (bounded deque + set pattern) self._processed_frames: set = set() self._frame_history: deque = deque(maxlen=max_frames) @@ -107,6 +116,7 @@ class UserBotLatencyObserver(BaseObserver): self._register_event_handler("on_latency_measured") self._register_event_handler("on_latency_breakdown") + self._register_event_handler("on_first_bot_speech_latency") async def on_push_frame(self, data: FramePushed): """Process frames to track speech timing and calculate latency. @@ -132,12 +142,21 @@ class UserBotLatencyObserver(BaseObserver): if len(self._processed_frames) > len(self._frame_history): self._processed_frames = set(self._frame_history) + # Track client connection (first occurrence only) + if isinstance(data.frame, ClientConnectedFrame): + if self._client_connected_time is None: + self._client_connected_time = time.time() + return + # Track speech and pipeline events for latency if isinstance(data.frame, VADUserStartedSpeakingFrame): # Reset when user starts speaking self._user_stopped_time = None self._user_turn = None self._reset_accumulators() + # If user speaks before the bot's first speech, abandon the + # first-bot-speech measurement — it's only meaningful for greetings. + self._first_bot_speech_measured = True elif isinstance(data.frame, VADUserStoppedSpeakingFrame): # Record the actual time the user stopped speaking, which is # the VAD determination time minus the stop_secs silence duration @@ -159,28 +178,41 @@ class UserBotLatencyObserver(BaseObserver): async def _handle_bot_started_speaking(self): """Handle BotStartedSpeakingFrame to emit latency and breakdown.""" - if self._user_stopped_time is None: - return + emit_breakdown = False - latency = time.time() - self._user_stopped_time - self._user_stopped_time = None - await self._call_event_handler("on_latency_measured", latency) + # One-time first bot speech measurement (client connect → first speech) + if self._client_connected_time is not None and not self._first_bot_speech_measured: + self._first_bot_speech_measured = True + latency = time.time() - self._client_connected_time + await self._call_event_handler("on_first_bot_speech_latency", latency) + emit_breakdown = True - breakdown = LatencyBreakdown( - ttfb=list(self._ttfb), - text_aggregation=self._text_aggregation, - user_turn_secs=self._user_turn, - ) - await self._call_event_handler("on_latency_breakdown", breakdown) - self._reset_accumulators() + if self._user_stopped_time is not None: + latency = time.time() - self._user_stopped_time + self._user_stopped_time = None + await self._call_event_handler("on_latency_measured", latency) + emit_breakdown = True + + if emit_breakdown: + breakdown = LatencyBreakdown( + ttfb=list(self._ttfb), + text_aggregation=self._text_aggregation, + user_turn_secs=self._user_turn, + ) + await self._call_event_handler("on_latency_breakdown", breakdown) + self._reset_accumulators() def _handle_metrics_frame(self, frame: MetricsFrame): """Extract latency metrics from a MetricsFrame. - Only accumulates metrics when a user→bot measurement is in progress - (after ``VADUserStoppedSpeakingFrame``). + Accumulates metrics when a measurement is in progress: either a + user→bot cycle (after ``VADUserStoppedSpeakingFrame``) or the + first-bot-speech window (after ``ClientConnectedFrame``). """ - if self._user_stopped_time is None: + waiting_for_first_speech = ( + self._client_connected_time is not None and not self._first_bot_speech_measured + ) + if self._user_stopped_time is None and not waiting_for_first_speech: return for metrics_data in frame.data: diff --git a/tests/test_user_bot_latency_observer.py b/tests/test_user_bot_latency_observer.py index 8f8b2893d..ab00bfd61 100644 --- a/tests/test_user_bot_latency_observer.py +++ b/tests/test_user_bot_latency_observer.py @@ -2,6 +2,7 @@ import unittest from pipecat.frames.frames import ( BotStartedSpeakingFrame, + ClientConnectedFrame, InterruptionFrame, MetricsFrame, UserStoppedSpeakingFrame, @@ -342,6 +343,126 @@ class TestUserBotLatencyObserver(unittest.IsolatedAsyncioTestCase): self.assertEqual(len(latencies), 0) self.assertEqual(len(breakdowns), 0) + async def test_first_bot_speech_latency(self): + """Test first bot speech latency and breakdown from ClientConnected to BotStartedSpeaking.""" + observer = UserBotLatencyObserver() + processor = IdentityFilter() + + first_speech_latencies = [] + breakdowns = [] + + @observer.event_handler("on_first_bot_speech_latency") + async def on_first_bot_speech(obs, latency_seconds): + first_speech_latencies.append(latency_seconds) + + @observer.event_handler("on_latency_breakdown") + async def on_breakdown(obs, breakdown): + breakdowns.append(breakdown) + + llm_ttfb = TTFBMetricsData(processor="OpenAILLMService#0", value=0.250) + tts_ttfb = TTFBMetricsData(processor="CartesiaTTSService#0", value=0.070) + + frames_to_send = [ + ClientConnectedFrame(), + MetricsFrame(data=[llm_ttfb]), + MetricsFrame(data=[tts_ttfb]), + BotStartedSpeakingFrame(), + ] + + expected_down_frames = [ + ClientConnectedFrame, + MetricsFrame, + MetricsFrame, + BotStartedSpeakingFrame, + ] + + await run_test( + processor, + frames_to_send=frames_to_send, + expected_down_frames=expected_down_frames, + observers=[observer], + ) + + self.assertEqual(len(first_speech_latencies), 1) + self.assertGreater(first_speech_latencies[0], 0) + self.assertLess(first_speech_latencies[0], 1.0) + + # Breakdown should also be emitted with the accumulated metrics + self.assertEqual(len(breakdowns), 1) + self.assertEqual(len(breakdowns[0].ttfb), 2) + self.assertEqual(breakdowns[0].ttfb[0].processor, "OpenAILLMService#0") + self.assertEqual(breakdowns[0].ttfb[1].processor, "CartesiaTTSService#0") + + async def test_first_bot_speech_only_once(self): + """Test that first bot speech latency is only emitted once.""" + observer = UserBotLatencyObserver() + processor = IdentityFilter() + + first_speech_latencies = [] + + @observer.event_handler("on_first_bot_speech_latency") + async def on_first_bot_speech(obs, latency_seconds): + first_speech_latencies.append(latency_seconds) + + frames_to_send = [ + ClientConnectedFrame(), + BotStartedSpeakingFrame(), + # Second bot speech should not trigger the event again + VADUserStoppedSpeakingFrame(), + BotStartedSpeakingFrame(), + ] + + expected_down_frames = [ + ClientConnectedFrame, + BotStartedSpeakingFrame, + VADUserStoppedSpeakingFrame, + BotStartedSpeakingFrame, + ] + + await run_test( + processor, + frames_to_send=frames_to_send, + expected_down_frames=expected_down_frames, + observers=[observer], + ) + + self.assertEqual(len(first_speech_latencies), 1) + + async def test_first_bot_speech_skipped_when_user_speaks_first(self): + """Test that first bot speech event is not emitted when user speaks before the bot.""" + observer = UserBotLatencyObserver() + processor = IdentityFilter() + + first_speech_latencies = [] + + @observer.event_handler("on_first_bot_speech_latency") + async def on_first_bot_speech(obs, latency_seconds): + first_speech_latencies.append(latency_seconds) + + frames_to_send = [ + ClientConnectedFrame(), + # User speaks before bot has a chance to greet + VADUserStartedSpeakingFrame(), + VADUserStoppedSpeakingFrame(), + BotStartedSpeakingFrame(), + ] + + expected_down_frames = [ + ClientConnectedFrame, + VADUserStartedSpeakingFrame, + VADUserStoppedSpeakingFrame, + BotStartedSpeakingFrame, + ] + + await run_test( + processor, + frames_to_send=frames_to_send, + expected_down_frames=expected_down_frames, + observers=[observer], + ) + + self.assertEqual(len(first_speech_latencies), 0) + if __name__ == "__main__": unittest.main() From a738a4d82b44d6b6e0c670376db769127abd41e3 Mon Sep 17 00:00:00 2001 From: Mark Backman Date: Sun, 1 Mar 2026 11:14:17 -0500 Subject: [PATCH 0747/1060] Add function call latency tracking to LatencyBreakdown --- changelog/3885.added.md | 2 +- .../foundational/29-turn-tracking-observer.py | 62 +++++++++++++- .../observers/user_bot_latency_observer.py | 40 ++++++++- tests/test_user_bot_latency_observer.py | 81 +++++++++++++++++++ 4 files changed, 179 insertions(+), 6 deletions(-) diff --git a/changelog/3885.added.md b/changelog/3885.added.md index 87cbd7824..96f8cc2cd 100644 --- a/changelog/3885.added.md +++ b/changelog/3885.added.md @@ -1 +1 @@ -- Added `on_latency_breakdown` event to `UserBotLatencyObserver` providing per-service TTFB, text aggregation, and user turn duration metrics for each user-to-bot response cycle. +- Added `on_latency_breakdown` event to `UserBotLatencyObserver` providing per-service TTFB, text aggregation, user turn duration, and function call latency metrics for each user-to-bot response cycle. diff --git a/examples/foundational/29-turn-tracking-observer.py b/examples/foundational/29-turn-tracking-observer.py index 2c8ec1f84..8bec9e2bc 100644 --- a/examples/foundational/29-turn-tracking-observer.py +++ b/examples/foundational/29-turn-tracking-observer.py @@ -5,11 +5,14 @@ # +import asyncio import os from dotenv import load_dotenv from loguru import logger +from pipecat.adapters.schemas.function_schema import FunctionSchema +from pipecat.adapters.schemas.tools_schema import ToolsSchema from pipecat.audio.vad.silero import SileroVADAnalyzer from pipecat.frames.frames import LLMRunFrame from pipecat.observers.startup_timing_observer import StartupTimingObserver @@ -26,6 +29,7 @@ from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport from pipecat.services.cartesia.tts import CartesiaTTSService from pipecat.services.deepgram.stt import DeepgramSTTService +from pipecat.services.llm_service import FunctionCallParams from pipecat.services.openai.llm import OpenAILLMService from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams @@ -33,6 +37,17 @@ from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams load_dotenv(override=True) + +async def fetch_weather_from_api(params: FunctionCallParams): + await asyncio.sleep(0.25) + await params.result_callback({"conditions": "nice", "temperature": "75"}) + + +async def fetch_restaurant_recommendation(params: FunctionCallParams): + await asyncio.sleep(0.1) + await params.result_callback({"name": "The Golden Dragon"}) + + # We use lambdas to defer transport parameter creation until the transport # type is selected at runtime. transport_params = { @@ -63,6 +78,38 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): llm = OpenAILLMService(api_key=os.getenv("OPENAI_API_KEY")) + llm.register_function("get_current_weather", fetch_weather_from_api) + llm.register_function("get_restaurant_recommendation", fetch_restaurant_recommendation) + + weather_function = FunctionSchema( + name="get_current_weather", + description="Get the current weather", + properties={ + "location": { + "type": "string", + "description": "The city and state, e.g. San Francisco, CA", + }, + "format": { + "type": "string", + "enum": ["celsius", "fahrenheit"], + "description": "The temperature unit to use. Infer this from the user's location.", + }, + }, + required=["location", "format"], + ) + restaurant_function = FunctionSchema( + name="get_restaurant_recommendation", + description="Get a restaurant recommendation", + properties={ + "location": { + "type": "string", + "description": "The city and state, e.g. San Francisco, CA", + }, + }, + required=["location"], + ) + tools = ToolsSchema(standard_tools=[weather_function, restaurant_function]) + messages = [ { "role": "system", @@ -70,7 +117,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): }, ] - context = LLMContext(messages) + context = LLMContext(messages, tools) user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()), @@ -147,9 +194,16 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): stt_note = f" (STT: {stt_ttfb.value:.3f}s)" if stt_ttfb else "" logger.info(f" User turn: {breakdown.user_turn_secs:.3f}s{stt_note}") - for ttfb in breakdown.ttfb: - if ttfb is not stt_ttfb: - logger.info(f" {ttfb.processor}: TTFB {ttfb.value:.3f}s") + # Show non-STT TTFBs, inserting function calls after the first + # LLM TTFB (which triggered the calls) for a chronological waterfall. + non_stt = [t for t in breakdown.ttfb if t is not stt_ttfb] + fc_shown = False + for ttfb in non_stt: + logger.info(f" {ttfb.processor}: TTFB {ttfb.value:.3f}s") + if not fc_shown and breakdown.function_calls: + for fc in breakdown.function_calls: + logger.info(f" {fc.function_name}: {fc.duration_secs:.3f}s") + fc_shown = True if breakdown.text_aggregation: ta = breakdown.text_aggregation diff --git a/src/pipecat/observers/user_bot_latency_observer.py b/src/pipecat/observers/user_bot_latency_observer.py index cdc7c43d0..46dbbd0f1 100644 --- a/src/pipecat/observers/user_bot_latency_observer.py +++ b/src/pipecat/observers/user_bot_latency_observer.py @@ -15,11 +15,13 @@ is measured. Optionally collects per-service latency breakdown metrics import time from collections import deque from dataclasses import dataclass, field -from typing import List, Optional +from typing import Dict, List, Optional from pipecat.frames.frames import ( BotStartedSpeakingFrame, ClientConnectedFrame, + FunctionCallInProgressFrame, + FunctionCallResultFrame, InterruptionFrame, MetricsFrame, UserStoppedSpeakingFrame, @@ -34,6 +36,19 @@ from pipecat.observers.base_observer import BaseObserver, FramePushed from pipecat.processors.frame_processor import FrameDirection +@dataclass +class FunctionCallMetrics: + """Latency for a single function call execution. + + Parameters: + function_name: Name of the function that was called. + duration_secs: Time in seconds from execution start to result. + """ + + function_name: str + duration_secs: float + + @dataclass class LatencyBreakdown: """Per-service latency breakdown for a single user-to-bot cycle. @@ -52,11 +67,14 @@ class LatencyBreakdown: VAD silence detection, STT finalization, and any turn analyzer wait. ``None`` if no ``UserStoppedSpeakingFrame`` was observed (e.g. no turn analyzer configured). + function_calls: Latency for each function call executed during + this cycle. Empty if no function calls occurred. """ ttfb: List[TTFBMetricsData] = field(default_factory=list) text_aggregation: Optional[TextAggregationMetricsData] = None user_turn_secs: Optional[float] = None + function_calls: List[FunctionCallMetrics] = field(default_factory=list) class UserBotLatencyObserver(BaseObserver): @@ -113,6 +131,8 @@ class UserBotLatencyObserver(BaseObserver): # Per-cycle metric accumulators self._ttfb: List[TTFBMetricsData] = [] self._text_aggregation: Optional[TextAggregationMetricsData] = None + self._function_call_starts: Dict[str, tuple[str, float]] = {} + self._function_call_metrics: List[FunctionCallMetrics] = [] self._register_event_handler("on_latency_measured") self._register_event_handler("on_latency_breakdown") @@ -171,6 +191,21 @@ class UserBotLatencyObserver(BaseObserver): elif isinstance(data.frame, InterruptionFrame): # Discard stale metrics from cancelled LLM/TTS cycles self._reset_accumulators() + elif isinstance(data.frame, FunctionCallInProgressFrame): + self._function_call_starts[data.frame.tool_call_id] = ( + data.frame.function_name, + time.time(), + ) + elif isinstance(data.frame, FunctionCallResultFrame): + start = self._function_call_starts.pop(data.frame.tool_call_id, None) + if start is not None: + function_name, start_time = start + self._function_call_metrics.append( + FunctionCallMetrics( + function_name=function_name, + duration_secs=time.time() - start_time, + ) + ) elif isinstance(data.frame, MetricsFrame): self._handle_metrics_frame(data.frame) elif isinstance(data.frame, BotStartedSpeakingFrame): @@ -198,6 +233,7 @@ class UserBotLatencyObserver(BaseObserver): ttfb=list(self._ttfb), text_aggregation=self._text_aggregation, user_turn_secs=self._user_turn, + function_calls=list(self._function_call_metrics), ) await self._call_event_handler("on_latency_breakdown", breakdown) self._reset_accumulators() @@ -229,3 +265,5 @@ class UserBotLatencyObserver(BaseObserver): self._ttfb = [] self._text_aggregation = None self._user_turn = None + self._function_call_starts = {} + self._function_call_metrics = [] diff --git a/tests/test_user_bot_latency_observer.py b/tests/test_user_bot_latency_observer.py index ab00bfd61..8e63647cf 100644 --- a/tests/test_user_bot_latency_observer.py +++ b/tests/test_user_bot_latency_observer.py @@ -3,6 +3,8 @@ import unittest from pipecat.frames.frames import ( BotStartedSpeakingFrame, ClientConnectedFrame, + FunctionCallInProgressFrame, + FunctionCallResultFrame, InterruptionFrame, MetricsFrame, UserStoppedSpeakingFrame, @@ -463,6 +465,85 @@ class TestUserBotLatencyObserver(unittest.IsolatedAsyncioTestCase): self.assertEqual(len(first_speech_latencies), 0) + async def test_function_call_latency_in_breakdown(self): + """Test that function call duration appears in the latency breakdown.""" + observer = UserBotLatencyObserver() + processor = IdentityFilter() + + breakdowns = [] + + @observer.event_handler("on_latency_breakdown") + async def on_breakdown(obs, breakdown): + breakdowns.append(breakdown) + + tool_call_id = "call_abc123" + + frames_to_send = [ + VADUserStoppedSpeakingFrame(), + FunctionCallInProgressFrame( + function_name="get_weather", + tool_call_id=tool_call_id, + arguments={"location": "Atlanta"}, + ), + SleepFrame(sleep=0.1), + FunctionCallResultFrame( + function_name="get_weather", + tool_call_id=tool_call_id, + arguments={"location": "Atlanta"}, + result={"temperature": "75"}, + ), + BotStartedSpeakingFrame(), + ] + + await run_test( + processor, + frames_to_send=frames_to_send, + observers=[observer], + ) + + self.assertEqual(len(breakdowns), 1) + self.assertEqual(len(breakdowns[0].function_calls), 1) + fc = breakdowns[0].function_calls[0] + self.assertEqual(fc.function_name, "get_weather") + self.assertGreaterEqual(fc.duration_secs, 0.1) + + async def test_function_call_reset_on_interruption(self): + """Test that function call metrics are cleared on interruption.""" + observer = UserBotLatencyObserver() + processor = IdentityFilter() + + breakdowns = [] + + @observer.event_handler("on_latency_breakdown") + async def on_breakdown(obs, breakdown): + breakdowns.append(breakdown) + + frames_to_send = [ + VADUserStoppedSpeakingFrame(), + FunctionCallInProgressFrame( + function_name="get_weather", + tool_call_id="call_1", + arguments={}, + ), + FunctionCallResultFrame( + function_name="get_weather", + tool_call_id="call_1", + arguments={}, + result={}, + ), + InterruptionFrame(), + BotStartedSpeakingFrame(), + ] + + await run_test( + processor, + frames_to_send=frames_to_send, + observers=[observer], + ) + + self.assertEqual(len(breakdowns), 1) + self.assertEqual(len(breakdowns[0].function_calls), 0) + if __name__ == "__main__": unittest.main() From ff5b9850096d2d2226b19f5d905f6417958e1af4 Mon Sep 17 00:00:00 2001 From: Mark Backman Date: Sun, 1 Mar 2026 11:51:27 -0500 Subject: [PATCH 0748/1060] Convert observer data models to Pydantic BaseModel with timestamps Enables .model_dump() serialization for Pipecat Cloud collection. All metrics now include start_time (Unix timestamp) for timeline plotting alongside duration_secs. --- .../foundational/29-turn-tracking-observer.py | 6 +- .../observers/user_bot_latency_observer.py | 77 ++++++++++++++++--- tests/test_user_bot_latency_observer.py | 8 +- 3 files changed, 72 insertions(+), 19 deletions(-) diff --git a/examples/foundational/29-turn-tracking-observer.py b/examples/foundational/29-turn-tracking-observer.py index 8bec9e2bc..476dc4612 100644 --- a/examples/foundational/29-turn-tracking-observer.py +++ b/examples/foundational/29-turn-tracking-observer.py @@ -191,7 +191,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): # turn analyzer delay). stt_ttfb = next((t for t in breakdown.ttfb if "STT" in t.processor), None) if breakdown.user_turn_secs is not None: - stt_note = f" (STT: {stt_ttfb.value:.3f}s)" if stt_ttfb else "" + stt_note = f" (STT: {stt_ttfb.duration_secs:.3f}s)" if stt_ttfb else "" logger.info(f" User turn: {breakdown.user_turn_secs:.3f}s{stt_note}") # Show non-STT TTFBs, inserting function calls after the first @@ -199,7 +199,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): non_stt = [t for t in breakdown.ttfb if t is not stt_ttfb] fc_shown = False for ttfb in non_stt: - logger.info(f" {ttfb.processor}: TTFB {ttfb.value:.3f}s") + logger.info(f" {ttfb.processor}: TTFB {ttfb.duration_secs:.3f}s") if not fc_shown and breakdown.function_calls: for fc in breakdown.function_calls: logger.info(f" {fc.function_name}: {fc.duration_secs:.3f}s") @@ -207,7 +207,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): if breakdown.text_aggregation: ta = breakdown.text_aggregation - logger.info(f" {ta.processor}: text aggregation {ta.value:.3f}s") + logger.info(f" {ta.processor}: text aggregation {ta.duration_secs:.3f}s") @transport.event_handler("on_client_connected") async def on_client_connected(transport, client): diff --git a/src/pipecat/observers/user_bot_latency_observer.py b/src/pipecat/observers/user_bot_latency_observer.py index 46dbbd0f1..aa0887e30 100644 --- a/src/pipecat/observers/user_bot_latency_observer.py +++ b/src/pipecat/observers/user_bot_latency_observer.py @@ -14,9 +14,10 @@ is measured. Optionally collects per-service latency breakdown metrics import time from collections import deque -from dataclasses import dataclass, field from typing import Dict, List, Optional +from pydantic import BaseModel, Field + from pipecat.frames.frames import ( BotStartedSpeakingFrame, ClientConnectedFrame, @@ -36,21 +37,51 @@ from pipecat.observers.base_observer import BaseObserver, FramePushed from pipecat.processors.frame_processor import FrameDirection -@dataclass -class FunctionCallMetrics: +class TTFBBreakdownMetrics(BaseModel): + """TTFB measurement with timestamp for timeline placement. + + Parameters: + processor: Name of the processor that reported the TTFB. + model: Optional model name associated with the metric. + start_time: Unix timestamp when the TTFB measurement started. + duration_secs: TTFB duration in seconds. + """ + + processor: str + model: Optional[str] = None + start_time: float + duration_secs: float + + +class TextAggregationBreakdownMetrics(BaseModel): + """Text aggregation measurement with timestamp for timeline placement. + + Parameters: + processor: Name of the processor that reported the metric. + start_time: Unix timestamp when text aggregation started. + duration_secs: Aggregation duration in seconds. + """ + + processor: str + start_time: float + duration_secs: float + + +class FunctionCallMetrics(BaseModel): """Latency for a single function call execution. Parameters: function_name: Name of the function that was called. + start_time: Unix timestamp when execution started. duration_secs: Time in seconds from execution start to result. """ function_name: str + start_time: float duration_secs: float -@dataclass -class LatencyBreakdown: +class LatencyBreakdown(BaseModel): """Per-service latency breakdown for a single user-to-bot cycle. Collected between ``VADUserStoppedSpeakingFrame`` and @@ -61,6 +92,9 @@ class LatencyBreakdown: ttfb: Time-to-first-byte metrics from each service in the pipeline. text_aggregation: First text aggregation measurement, representing the latency cost of sentence aggregation in the TTS pipeline. + user_turn_start_time: Unix timestamp when the user turn started + (actual user silence, adjusted for VAD stop_secs). ``None`` if + no ``VADUserStoppedSpeakingFrame`` was observed. user_turn_secs: Duration in seconds of the user's turn, measured from when the user actually stopped speaking to when the turn was released (``UserStoppedSpeakingFrame``). This includes @@ -71,10 +105,11 @@ class LatencyBreakdown: this cycle. Empty if no function calls occurred. """ - ttfb: List[TTFBMetricsData] = field(default_factory=list) - text_aggregation: Optional[TextAggregationMetricsData] = None + ttfb: List[TTFBBreakdownMetrics] = Field(default_factory=list) + text_aggregation: Optional[TextAggregationBreakdownMetrics] = None + user_turn_start_time: Optional[float] = None user_turn_secs: Optional[float] = None - function_calls: List[FunctionCallMetrics] = field(default_factory=list) + function_calls: List[FunctionCallMetrics] = Field(default_factory=list) class UserBotLatencyObserver(BaseObserver): @@ -118,6 +153,7 @@ class UserBotLatencyObserver(BaseObserver): """ super().__init__(**kwargs) self._user_stopped_time: Optional[float] = None + self._user_turn_start_time: Optional[float] = None self._user_turn: Optional[float] = None # First bot speech tracking @@ -129,8 +165,8 @@ class UserBotLatencyObserver(BaseObserver): self._frame_history: deque = deque(maxlen=max_frames) # Per-cycle metric accumulators - self._ttfb: List[TTFBMetricsData] = [] - self._text_aggregation: Optional[TextAggregationMetricsData] = None + self._ttfb: List[TTFBBreakdownMetrics] = [] + self._text_aggregation: Optional[TextAggregationBreakdownMetrics] = None self._function_call_starts: Dict[str, tuple[str, float]] = {} self._function_call_metrics: List[FunctionCallMetrics] = [] @@ -172,6 +208,7 @@ class UserBotLatencyObserver(BaseObserver): if isinstance(data.frame, VADUserStartedSpeakingFrame): # Reset when user starts speaking self._user_stopped_time = None + self._user_turn_start_time = None self._user_turn = None self._reset_accumulators() # If user speaks before the bot's first speech, abandon the @@ -182,6 +219,7 @@ class UserBotLatencyObserver(BaseObserver): # the VAD determination time minus the stop_secs silence duration # that had to elapse before the VAD confirmed speech ended. self._user_stopped_time = data.frame.timestamp - data.frame.stop_secs + self._user_turn_start_time = self._user_stopped_time elif isinstance(data.frame, UserStoppedSpeakingFrame): # Measure the user turn duration: from actual user silence to # turn release. Includes VAD silence detection, STT finalization, @@ -203,6 +241,7 @@ class UserBotLatencyObserver(BaseObserver): self._function_call_metrics.append( FunctionCallMetrics( function_name=function_name, + start_time=start_time, duration_secs=time.time() - start_time, ) ) @@ -232,6 +271,7 @@ class UserBotLatencyObserver(BaseObserver): breakdown = LatencyBreakdown( ttfb=list(self._ttfb), text_aggregation=self._text_aggregation, + user_turn_start_time=self._user_turn_start_time, user_turn_secs=self._user_turn, function_calls=list(self._function_call_metrics), ) @@ -251,19 +291,32 @@ class UserBotLatencyObserver(BaseObserver): if self._user_stopped_time is None and not waiting_for_first_speech: return + now = time.time() for metrics_data in frame.data: if isinstance(metrics_data, TTFBMetricsData) and metrics_data.value > 0: - self._ttfb.append(metrics_data) + self._ttfb.append( + TTFBBreakdownMetrics( + processor=metrics_data.processor, + model=metrics_data.model, + start_time=now - metrics_data.value, + duration_secs=metrics_data.value, + ) + ) elif isinstance(metrics_data, TextAggregationMetricsData): # Only keep the first measurement — it's the one that # impacts the initial speaking latency. if self._text_aggregation is None: - self._text_aggregation = metrics_data + self._text_aggregation = TextAggregationBreakdownMetrics( + processor=metrics_data.processor, + start_time=now - metrics_data.value, + duration_secs=metrics_data.value, + ) def _reset_accumulators(self): """Clear per-cycle metric accumulators.""" self._ttfb = [] self._text_aggregation = None + self._user_turn_start_time = None self._user_turn = None self._function_call_starts = {} self._function_call_metrics = [] diff --git a/tests/test_user_bot_latency_observer.py b/tests/test_user_bot_latency_observer.py index 8e63647cf..42d5d3367 100644 --- a/tests/test_user_bot_latency_observer.py +++ b/tests/test_user_bot_latency_observer.py @@ -153,7 +153,7 @@ class TestUserBotLatencyObserver(unittest.IsolatedAsyncioTestCase): self.assertEqual(bd.ttfb[1].processor, "OpenAILLMService#0") self.assertEqual(bd.ttfb[2].processor, "CartesiaTTSService#0") self.assertIsNotNone(bd.text_aggregation) - self.assertEqual(bd.text_aggregation.value, 0.030) + self.assertEqual(bd.text_aggregation.duration_secs, 0.030) async def test_interruption_resets_accumulators(self): """Test that InterruptionFrame clears stale metrics from earlier cycles.""" @@ -202,9 +202,9 @@ class TestUserBotLatencyObserver(unittest.IsolatedAsyncioTestCase): # Only the post-interruption metrics should be present self.assertEqual(len(bd.ttfb), 2) self.assertEqual(bd.ttfb[0].processor, "OpenAILLMService#0") - self.assertEqual(bd.ttfb[0].value, 0.224) + self.assertEqual(bd.ttfb[0].duration_secs, 0.224) self.assertEqual(bd.ttfb[1].processor, "CartesiaTTSService#0") - self.assertEqual(bd.ttfb[1].value, 0.142) + self.assertEqual(bd.ttfb[1].duration_secs, 0.142) async def test_only_first_text_aggregation_kept(self): """Test that only the first text aggregation metric is kept per cycle.""" @@ -243,7 +243,7 @@ class TestUserBotLatencyObserver(unittest.IsolatedAsyncioTestCase): self.assertEqual(len(breakdowns), 1) self.assertIsNotNone(breakdowns[0].text_aggregation) - self.assertEqual(breakdowns[0].text_aggregation.value, 0.030) + self.assertEqual(breakdowns[0].text_aggregation.duration_secs, 0.030) async def test_user_turn_measured(self): """Test that pre-LLM wait from user silence to UserStopped is captured.""" From 8f66272de7079818aba54b0ea74804052b030ae4 Mon Sep 17 00:00:00 2001 From: Mark Backman Date: Mon, 2 Mar 2026 16:16:38 -0500 Subject: [PATCH 0749/1060] Update changelog --- changelog/3885.added.2.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/changelog/3885.added.2.md b/changelog/3885.added.2.md index a9562b883..5a6adce12 100644 --- a/changelog/3885.added.2.md +++ b/changelog/3885.added.2.md @@ -1 +1 @@ -- Added `on_first_bot_speech_latency` event to `UserBotLatencyObserver` measuring the time from client connection to first bot speech, including a latency breakdown with per-service metrics. +- Added `on_first_bot_speech_latency` event to `UserBotLatencyObserver` measuring the time from client connection to first bot speech. An `on_latency_breakdown` is also emitted for this first speech event. From d0ecb3c7a8bee801878015f99000d8d8a68403fc Mon Sep 17 00:00:00 2001 From: Mark Backman Date: Mon, 2 Mar 2026 16:24:21 -0500 Subject: [PATCH 0750/1060] Revert "Deprecate processing metrics (ProcessingMetricsData)" (#3852) This reverts commit 127b52bad5309d5e6b3df90a7100f69b49f81c55. --- changelog/3852.deprecated.md | 1 - src/pipecat/metrics/metrics.py | 4 ---- src/pipecat/processors/frame_processor.py | 16 ---------------- .../metrics/frame_processor_metrics.py | 8 -------- 4 files changed, 29 deletions(-) delete mode 100644 changelog/3852.deprecated.md diff --git a/changelog/3852.deprecated.md b/changelog/3852.deprecated.md deleted file mode 100644 index 666c7c58a..000000000 --- a/changelog/3852.deprecated.md +++ /dev/null @@ -1 +0,0 @@ -- Deprecated `ProcessingMetricsData` and `start_processing_metrics()`/`stop_processing_metrics()` on `FrameProcessor` and `FrameProcessorMetrics`. These metrics don't accurately depict a service's performance. Instead, TTFB metrics are recommended. Processing metrics will be removed in the 1.0.0 version. diff --git a/src/pipecat/metrics/metrics.py b/src/pipecat/metrics/metrics.py index 37ab99447..2030306e5 100644 --- a/src/pipecat/metrics/metrics.py +++ b/src/pipecat/metrics/metrics.py @@ -41,10 +41,6 @@ class TTFBMetricsData(MetricsData): class ProcessingMetricsData(MetricsData): """General processing time metrics data. - .. deprecated:: 0.0.104 - Processing metrics are deprecated and will be removed in a future version. - Use TTFB metrics instead. - Parameters: value: Processing time measurement in seconds. """ diff --git a/src/pipecat/processors/frame_processor.py b/src/pipecat/processors/frame_processor.py index 3e7b48442..bfe818696 100644 --- a/src/pipecat/processors/frame_processor.py +++ b/src/pipecat/processors/frame_processor.py @@ -441,35 +441,19 @@ class FrameProcessor(BaseObject): if frame: await self.push_frame(frame) - _processing_metrics_warned = False - async def start_processing_metrics(self, *, start_time: Optional[float] = None): """Start processing metrics collection. - .. deprecated:: 0.0.104 - Processing metrics are deprecated and will be removed in a future version. - Use TTFB metrics instead. - Args: start_time: Optional timestamp to use as the start time. If None, uses the current time. """ if self.can_generate_metrics() and self.metrics_enabled: - if not FrameProcessor._processing_metrics_warned: - FrameProcessor._processing_metrics_warned = True - logger.warning( - "Processing metrics are deprecated and will be removed in a future version. " - "Use TTFB metrics instead." - ) await self._metrics.start_processing_metrics(start_time=start_time) async def stop_processing_metrics(self, *, end_time: Optional[float] = None): """Stop processing metrics collection and push results. - .. deprecated:: 0.0.104 - Processing metrics are deprecated and will be removed in a future version. - Use TTFB metrics instead. - Args: end_time: Optional timestamp to use as the end time. If None, uses the current time. diff --git a/src/pipecat/processors/metrics/frame_processor_metrics.py b/src/pipecat/processors/metrics/frame_processor_metrics.py index ef637b5ad..7a52895a2 100644 --- a/src/pipecat/processors/metrics/frame_processor_metrics.py +++ b/src/pipecat/processors/metrics/frame_processor_metrics.py @@ -150,10 +150,6 @@ class FrameProcessorMetrics(BaseObject): async def start_processing_metrics(self, *, start_time: Optional[float] = None): """Start measuring processing time. - .. deprecated:: 0.0.104 - Processing metrics are deprecated and will be removed in a future version. - Use TTFB metrics instead. - Args: start_time: Optional timestamp to use as the start time. If None, uses the current time. @@ -163,10 +159,6 @@ class FrameProcessorMetrics(BaseObject): async def stop_processing_metrics(self, *, end_time: Optional[float] = None): """Stop processing time measurement and generate metrics frame. - .. deprecated:: 0.0.104 - Processing metrics are deprecated and will be removed in a future version. - Use TTFB metrics instead. - Args: end_time: Optional timestamp to use as the end time. If None, uses the current time. From 4a61d5bfadc55651e921be8bb1ac40affbacd929 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Aleix=20Conchillo=20Flaqu=C3=A9?= Date: Mon, 2 Mar 2026 12:04:51 -0800 Subject: [PATCH 0751/1060] Add broadcast_interruption() to FrameProcessor Replace the round-trip push_interruption_task_frame_and_wait() mechanism with broadcast_interruption(), which pushes an InterruptionFrame both upstream and downstream directly from the calling processor. This eliminates race conditions (transcription arriving before the InterruptionFrame comes back), swallowed-event timeouts (frame blocked before reaching the sink), and the complexity of _wait_for_interruption flag / queue bypass / frame.complete() obligations. - Add broadcast_interruption() to FrameProcessor - Deprecate push_interruption_task_frame_and_wait() (delegates to new method) - Remove event field and complete() from InterruptionFrame/InterruptionTaskFrame - Remove _wait_for_interruption flag and all special-case logic - Remove frame.complete() calls in stt_mute_filter and llm_response_universal - Update all 17 call sites to use broadcast_interruption() - Update tests --- changelog/3900.added.md | 1 + changelog/3900.changed.md | 1 + changelog/3900.deprecated.md | 1 + .../voicemail/voicemail_detector.py | 2 +- src/pipecat/frames/frames.py | 29 +---- src/pipecat/pipeline/task.py | 4 +- .../processors/aggregators/dtmf_aggregator.py | 2 +- .../processors/aggregators/llm_response.py | 2 +- .../aggregators/llm_response_universal.py | 8 +- .../processors/filters/stt_mute_filter.py | 6 - src/pipecat/processors/frame_processor.py | 77 ++++-------- src/pipecat/processors/frameworks/rtvi.py | 2 +- src/pipecat/services/deepgram/flux/stt.py | 2 +- src/pipecat/services/deepgram/stt.py | 2 +- src/pipecat/services/gladia/stt.py | 2 +- .../services/google/gemini_live/llm.py | 2 +- src/pipecat/services/grok/realtime/llm.py | 2 +- src/pipecat/services/openai/realtime/llm.py | 2 +- src/pipecat/services/openai/stt.py | 2 +- .../services/openai_realtime_beta/openai.py | 2 +- src/pipecat/services/sarvam/stt.py | 2 +- src/pipecat/services/speechmatics/stt.py | 2 +- src/pipecat/transports/base_input.py | 2 +- src/pipecat/turns/user_turn_processor.py | 2 +- tests/test_context_aggregators.py | 3 +- tests/test_frame_processor.py | 117 +++--------------- tests/test_stt_mute_filter.py | 13 +- 27 files changed, 68 insertions(+), 224 deletions(-) create mode 100644 changelog/3900.added.md create mode 100644 changelog/3900.changed.md create mode 100644 changelog/3900.deprecated.md diff --git a/changelog/3900.added.md b/changelog/3900.added.md new file mode 100644 index 000000000..08921c004 --- /dev/null +++ b/changelog/3900.added.md @@ -0,0 +1 @@ +- Added `broadcast_interruption()` to `FrameProcessor`. This method pushes an `InterruptionFrame` both upstream and downstream directly from the calling processor, avoiding the round-trip through the pipeline task that `push_interruption_task_frame_and_wait()` required. diff --git a/changelog/3900.changed.md b/changelog/3900.changed.md new file mode 100644 index 000000000..59b4cdb95 --- /dev/null +++ b/changelog/3900.changed.md @@ -0,0 +1 @@ +- Removed `event` field and `complete()` method from `InterruptionFrame`. Removed `event` field from `InterruptionTaskFrame`. These are no longer needed since `broadcast_interruption()` does not require a round-trip completion signal. diff --git a/changelog/3900.deprecated.md b/changelog/3900.deprecated.md new file mode 100644 index 000000000..421e10e92 --- /dev/null +++ b/changelog/3900.deprecated.md @@ -0,0 +1 @@ +- Deprecated `push_interruption_task_frame_and_wait()` in `FrameProcessor`. Use `broadcast_interruption()` instead. The old method now delegates to `broadcast_interruption()` and logs a deprecation warning. diff --git a/src/pipecat/extensions/voicemail/voicemail_detector.py b/src/pipecat/extensions/voicemail/voicemail_detector.py index 7e22e535a..470f5dd54 100644 --- a/src/pipecat/extensions/voicemail/voicemail_detector.py +++ b/src/pipecat/extensions/voicemail/voicemail_detector.py @@ -368,7 +368,7 @@ class ClassificationProcessor(FrameProcessor): await self._voicemail_notifier.notify() # Clear buffered TTS frames # Interrupt the current pipeline to stop any ongoing processing - await self.push_interruption_task_frame_and_wait() + await self.broadcast_interruption() # Set the voicemail event to trigger the voicemail handler self._voicemail_event.clear() diff --git a/src/pipecat/frames/frames.py b/src/pipecat/frames/frames.py index 126f3c001..9d6f78d6c 100644 --- a/src/pipecat/frames/frames.py +++ b/src/pipecat/frames/frames.py @@ -11,7 +11,6 @@ including data frames, system frames, and control frames for audio, video, text, and LLM processing. """ -import asyncio import time from dataclasses import dataclass, field from typing import ( @@ -1141,24 +1140,9 @@ class InterruptionFrame(SystemFrame): This frame is used to interrupt the pipeline. For example, when a user starts speaking to cancel any in-progress bot output. It can also be pushed by any processor. - - Parameters: - event: Optional event set when the frame has fully traversed the - pipeline. - """ - event: Optional[asyncio.Event] = None - - def complete(self): - """Signal that this interruption has been fully processed. - - Called automatically when the frame reaches the pipeline sink, or - manually when the frame is consumed before reaching it (e.g. when - the user is muted). - """ - if self.event: - self.event.set() + pass @dataclass @@ -1825,16 +1809,11 @@ class InterruptionTaskFrame(TaskFrame): """Frame indicating the pipeline should be interrupted. This frame should be pushed upstream to indicate the pipeline should be - interrupted. The pipeline task converts this into an `InterruptionFrame` and - sends it downstream. The `event` is passed to the `InterruptionFrame` so it - can signal when the interruption has fully traversed the pipeline. - - Parameters: - event: Optional event passed to the corresponding `InterruptionFrame`. - + interrupted. The pipeline task converts this into an `InterruptionFrame` + and sends it downstream. """ - event: Optional[asyncio.Event] = None + pass @dataclass diff --git a/src/pipecat/pipeline/task.py b/src/pipecat/pipeline/task.py index deae6290c..291ed5506 100644 --- a/src/pipecat/pipeline/task.py +++ b/src/pipecat/pipeline/task.py @@ -892,7 +892,7 @@ class PipelineTask(BasePipelineTask): # pipeline. This is in case the push task is blocked waiting for a # pipeline-ending frame to finish traversing the pipeline. logger.debug(f"{self}: received interruption task frame {frame}") - await self._pipeline.queue_frame(InterruptionFrame(event=frame.event)) + await self._pipeline.queue_frame(InterruptionFrame()) elif isinstance(frame, ErrorFrame): await self._call_event_handler("on_pipeline_error", frame) if frame.fatal: @@ -931,8 +931,6 @@ class PipelineTask(BasePipelineTask): self._pipeline_end_event.set() elif isinstance(frame, CancelFrame): self._pipeline_end_event.set() - elif isinstance(frame, InterruptionFrame): - frame.complete() elif isinstance(frame, HeartbeatFrame): await self._heartbeat_queue.put(frame) diff --git a/src/pipecat/processors/aggregators/dtmf_aggregator.py b/src/pipecat/processors/aggregators/dtmf_aggregator.py index 1b9c59158..ea56ba6fc 100644 --- a/src/pipecat/processors/aggregators/dtmf_aggregator.py +++ b/src/pipecat/processors/aggregators/dtmf_aggregator.py @@ -104,7 +104,7 @@ class DTMFAggregator(FrameProcessor): # For first digit, schedule interruption. if is_first_digit: - await self.push_interruption_task_frame_and_wait() + await self.broadcast_interruption() # Check for immediate flush conditions if frame.button == self._termination_digit: diff --git a/src/pipecat/processors/aggregators/llm_response.py b/src/pipecat/processors/aggregators/llm_response.py index 44e5ce252..7c246b209 100644 --- a/src/pipecat/processors/aggregators/llm_response.py +++ b/src/pipecat/processors/aggregators/llm_response.py @@ -581,7 +581,7 @@ class LLMUserContextAggregator(LLMContextResponseAggregator): logger.debug( "Interruption conditions met - pushing interruption and aggregation" ) - await self.push_interruption_task_frame_and_wait() + await self.broadcast_interruption() await self._process_aggregation() else: logger.debug("Interruption conditions not met - not pushing aggregation") diff --git a/src/pipecat/processors/aggregators/llm_response_universal.py b/src/pipecat/processors/aggregators/llm_response_universal.py index 96f3702be..cf6c81e5f 100644 --- a/src/pipecat/processors/aggregators/llm_response_universal.py +++ b/src/pipecat/processors/aggregators/llm_response_universal.py @@ -608,12 +608,6 @@ class LLMUserAggregator(LLMContextAggregator): if should_mute_frame: logger.trace(f"{frame.name} suppressed - user currently muted") - # When muted, the InterruptionFrame won't propagate further and - # will never reach the pipeline sink. Complete it here so - # push_interruption_task_frame_and_wait() doesn't hang. - if should_mute_frame and isinstance(frame, InterruptionFrame): - frame.complete() - should_mute_next_time = False for s in self._params.user_mute_strategies: should_mute_next_time |= await s.process_frame(frame) @@ -737,7 +731,7 @@ class LLMUserAggregator(LLMContextAggregator): await self._user_idle_controller.process_frame(UserStartedSpeakingFrame()) if params.enable_interruptions and self._allow_interruptions: - await self.push_interruption_task_frame_and_wait() + await self.broadcast_interruption() await self._call_event_handler("on_user_turn_started", strategy) diff --git a/src/pipecat/processors/filters/stt_mute_filter.py b/src/pipecat/processors/filters/stt_mute_filter.py index f5d008e28..9f522a20d 100644 --- a/src/pipecat/processors/filters/stt_mute_filter.py +++ b/src/pipecat/processors/filters/stt_mute_filter.py @@ -234,12 +234,6 @@ class STTMuteFilter(FrameProcessor): await self.push_frame(frame, direction) else: logger.trace(f"{frame.__class__.__name__} suppressed - STT currently muted") - - # When muted, the InterruptionFrame won't propagate further - # and will never reach the pipeline sink. Complete it here so - # push_interruption_task_frame_and_wait() doesn't hang. - if isinstance(frame, InterruptionFrame): - frame.complete() else: # Pass all other frames through await self.push_frame(frame, direction) diff --git a/src/pipecat/processors/frame_processor.py b/src/pipecat/processors/frame_processor.py index 3e7b48442..69c503e71 100644 --- a/src/pipecat/processors/frame_processor.py +++ b/src/pipecat/processors/frame_processor.py @@ -41,7 +41,6 @@ from pipecat.frames.frames import ( FrameProcessorResumeFrame, FrameProcessorResumeUrgentFrame, InterruptionFrame, - InterruptionTaskFrame, StartFrame, SystemFrame, UninterruptibleFrame, @@ -240,10 +239,6 @@ class FrameProcessor(BaseObject): self.__process_frame_task: Optional[asyncio.Task] = None self.__process_current_frame: Optional[Frame] = None - # Set while awaiting push_interruption_task_frame_and_wait() so that - # _start_interruption() knows not to cancel the process task. - self._wait_for_interruption = False - # Frame processor events. self._register_event_handler("on_before_process_frame", sync=True) self._register_event_handler("on_after_process_frame", sync=True) @@ -329,7 +324,7 @@ class FrameProcessor(BaseObject): warnings.simplefilter("always") warnings.warn( "`FrameProcessor.interruptions_allowed` is deprecated. " - "Use `LLMUserAggregator`'s new `user_mute_strategies` parameter instead.", + "Use `LLMUserAggregator`'s new `user_mute_strategies` parameter instead.", DeprecationWarning, stacklevel=2, ) @@ -647,15 +642,6 @@ class FrameProcessor(BaseObject): if self._cancelling: return - # If we are waiting for an interruption, bypass all queued system frames - # and process the frame right away. This is because a previous system - # frame might be waiting for the interruption frame blocking the input - # task, so this InterruptionFrame would never be dequeued and we'd - # deadlock. - if self._wait_for_interruption and isinstance(frame, InterruptionFrame): - await self.__process_frame(frame, direction, callback) - return - if self._enable_direct_mode: await self.__process_frame(frame, direction, callback) else: @@ -790,43 +776,32 @@ class FrameProcessor(BaseObject): await self._call_event_handler("on_after_push_frame", frame) + async def broadcast_interruption(self): + """Broadcast an `InterruptionFrame` both upstream and downstream.""" + logger.debug(f"{self}: broadcasting interruption") + self.__reset_process_task() + await self.stop_all_metrics() + await self.broadcast_frame(InterruptionFrame) + async def push_interruption_task_frame_and_wait(self, *, timeout: float = 5.0): """Push an interruption task frame upstream and wait for the interruption. - This function sends an `InterruptionTaskFrame` upstream to the - pipeline task. The task creates a corresponding `InterruptionFrame` - and sends it downstream through the pipeline. An `asyncio.Event` is - attached to both frames so the caller can wait until the interruption - has fully traversed the pipeline. The event is set when the - `InterruptionFrame` reaches the pipeline sink. If the frame does - not complete within the given timeout, a warning is logged and the - event is forcibly set so the caller is unblocked. - - Args: - timeout: Maximum seconds to wait for the interruption to complete. + .. deprecated:: 0.0.104 + Use :meth:`broadcast_interruption` instead. This method now + delegates to ``broadcast_interruption()`` and ignores *timeout*. """ - self._wait_for_interruption = True + import warnings - event = asyncio.Event() + with warnings.catch_warnings(): + warnings.simplefilter("always") + warnings.warn( + "`FrameProcessor.push_interruption_task_frame_and_wait()` is deprecated. " + "Use `FrameProcessor.broadcast_interruption()` instead.", + DeprecationWarning, + stacklevel=2, + ) - await self.push_frame(InterruptionTaskFrame(event=event), FrameDirection.UPSTREAM) - - # Wait for the `InterruptionFrame` to complete and log a warning if it - # takes too long. If it does take too long make sure we unblock it, - # otherwise we will hang here forever. - while not event.is_set(): - try: - await asyncio.wait_for(event.wait(), timeout=timeout) - except asyncio.TimeoutError: - logger.warning( - f"{self}: InterruptionFrame has not completed after" - f" {timeout}s. Make sure InterruptionFrame.complete()" - " is being called (e.g. if the frame is being blocked" - " or consumed before reaching the pipeline sink)." - ) - event.set() - - self._wait_for_interruption = False + await self.broadcast_interruption() async def broadcast_frame(self, frame_cls: Type[Frame], **kwargs): """Broadcasts a frame of the specified class upstream and downstream. @@ -933,15 +908,7 @@ class FrameProcessor(BaseObject): async def _start_interruption(self): """Start handling an interruption by cancelling current tasks.""" try: - if self._wait_for_interruption: - # If we get here we know the process task was just waiting for - # an interruption (push_interruption_task_frame_and_wait()), so - # we can't cancel the task because it might still need to do - # more things (e.g. pushing a frame after the - # interruption). Instead we just drain the queue because this is - # an interruption. - self.__reset_process_task() - elif isinstance(self.__process_current_frame, UninterruptibleFrame): + if isinstance(self.__process_current_frame, UninterruptibleFrame): # We don't want to cancel UninterruptibleFrame, so we simply # cleanup the queue. self.__reset_process_queue() diff --git a/src/pipecat/processors/frameworks/rtvi.py b/src/pipecat/processors/frameworks/rtvi.py index e01e95714..eb1e79f3e 100644 --- a/src/pipecat/processors/frameworks/rtvi.py +++ b/src/pipecat/processors/frameworks/rtvi.py @@ -1702,7 +1702,7 @@ class RTVIProcessor(FrameProcessor): async def interrupt_bot(self): """Send a bot interruption frame upstream.""" - await self.push_interruption_task_frame_and_wait() + await self.broadcast_interruption() async def send_server_message(self, data: Any): """Send a server message to the client.""" diff --git a/src/pipecat/services/deepgram/flux/stt.py b/src/pipecat/services/deepgram/flux/stt.py index d509b267e..984906c6c 100644 --- a/src/pipecat/services/deepgram/flux/stt.py +++ b/src/pipecat/services/deepgram/flux/stt.py @@ -675,7 +675,7 @@ class DeepgramFluxSTTService(WebsocketSTTService): self._user_is_speaking = True await self.broadcast_frame(UserStartedSpeakingFrame) if self._should_interrupt: - await self.push_interruption_task_frame_and_wait() + await self.broadcast_interruption() await self.start_metrics() await self._call_event_handler("on_start_of_turn", transcript) if transcript: diff --git a/src/pipecat/services/deepgram/stt.py b/src/pipecat/services/deepgram/stt.py index 497d6aae1..8eb246cf2 100644 --- a/src/pipecat/services/deepgram/stt.py +++ b/src/pipecat/services/deepgram/stt.py @@ -471,7 +471,7 @@ class DeepgramSTTService(STTService): await self._call_event_handler("on_speech_started", *args, **kwargs) await self.broadcast_frame(UserStartedSpeakingFrame) if self._should_interrupt: - await self.push_interruption_task_frame_and_wait() + await self.broadcast_interruption() async def _on_utterance_end(self, *args, **kwargs): await self._call_event_handler("on_utterance_end", *args, **kwargs) diff --git a/src/pipecat/services/gladia/stt.py b/src/pipecat/services/gladia/stt.py index 045a56613..bba554b4a 100644 --- a/src/pipecat/services/gladia/stt.py +++ b/src/pipecat/services/gladia/stt.py @@ -613,7 +613,7 @@ class GladiaSTTService(WebsocketSTTService): await self.broadcast_frame(UserStartedSpeakingFrame) if self._should_interrupt: - await self.push_interruption_task_frame_and_wait() + await self.broadcast_interruption() async def _on_speech_ended(self): """Handle speech end event from Gladia. diff --git a/src/pipecat/services/google/gemini_live/llm.py b/src/pipecat/services/google/gemini_live/llm.py index d06f941c7..2ed11c739 100644 --- a/src/pipecat/services/google/gemini_live/llm.py +++ b/src/pipecat/services/google/gemini_live/llm.py @@ -1265,7 +1265,7 @@ class GeminiLiveLLMService(LLMService): # combination with the context aggregator default # turn strategies. logger.debug("Gemini VAD: interrupted signal received") - await self.push_interruption_task_frame_and_wait() + await self.broadcast_interruption() elif message.server_content and message.server_content.model_turn: await self._handle_msg_model_turn(message) elif ( diff --git a/src/pipecat/services/grok/realtime/llm.py b/src/pipecat/services/grok/realtime/llm.py index 6d148f6d7..7a4e73806 100644 --- a/src/pipecat/services/grok/realtime/llm.py +++ b/src/pipecat/services/grok/realtime/llm.py @@ -734,7 +734,7 @@ class GrokRealtimeLLMService(LLMService): """Handle speech started event from VAD.""" await self._truncate_current_audio_response() await self.broadcast_frame(UserStartedSpeakingFrame) - await self.push_interruption_task_frame_and_wait() + await self.broadcast_interruption() async def _handle_evt_speech_stopped(self, evt): """Handle speech stopped event from VAD.""" diff --git a/src/pipecat/services/openai/realtime/llm.py b/src/pipecat/services/openai/realtime/llm.py index a6667c7c8..07b6aa82b 100644 --- a/src/pipecat/services/openai/realtime/llm.py +++ b/src/pipecat/services/openai/realtime/llm.py @@ -839,7 +839,7 @@ class OpenAIRealtimeLLMService(LLMService): async def _handle_evt_speech_started(self, evt): await self._truncate_current_audio_response() await self.broadcast_frame(UserStartedSpeakingFrame) - await self.push_interruption_task_frame_and_wait() + await self.broadcast_interruption() async def _handle_evt_speech_stopped(self, evt): await self.start_ttfb_metrics() diff --git a/src/pipecat/services/openai/stt.py b/src/pipecat/services/openai/stt.py index 9a52be114..32895f8b5 100644 --- a/src/pipecat/services/openai/stt.py +++ b/src/pipecat/services/openai/stt.py @@ -639,7 +639,7 @@ class OpenAIRealtimeSTTService(WebsocketSTTService): logger.debug("Server VAD: speech started") await self.broadcast_frame(UserStartedSpeakingFrame) if self._should_interrupt: - await self.push_interruption_task_frame_and_wait() + await self.broadcast_interruption() await self.start_processing_metrics() async def _handle_speech_stopped(self, evt: dict): diff --git a/src/pipecat/services/openai_realtime_beta/openai.py b/src/pipecat/services/openai_realtime_beta/openai.py index 8614713ff..c912ed45c 100644 --- a/src/pipecat/services/openai_realtime_beta/openai.py +++ b/src/pipecat/services/openai_realtime_beta/openai.py @@ -709,7 +709,7 @@ class OpenAIRealtimeBetaLLMService(LLMService): async def _handle_evt_speech_started(self, evt): await self._truncate_current_audio_response() await self.broadcast_frame(UserStartedSpeakingFrame) - await self.push_interruption_task_frame_and_wait() + await self.broadcast_interruption() async def _handle_evt_speech_stopped(self, evt): await self.start_ttfb_metrics() diff --git a/src/pipecat/services/sarvam/stt.py b/src/pipecat/services/sarvam/stt.py index 9e245aece..e368ceb02 100644 --- a/src/pipecat/services/sarvam/stt.py +++ b/src/pipecat/services/sarvam/stt.py @@ -644,7 +644,7 @@ class SarvamSTTService(STTService): logger.debug("User started speaking") await self._call_event_handler("on_speech_started") await self.broadcast_frame(UserStartedSpeakingFrame) - await self.push_interruption_task_frame_and_wait() + await self.broadcast_interruption() elif signal == "END_SPEECH": logger.debug("User stopped speaking") diff --git a/src/pipecat/services/speechmatics/stt.py b/src/pipecat/services/speechmatics/stt.py index ac18a36e3..bdeb3b249 100644 --- a/src/pipecat/services/speechmatics/stt.py +++ b/src/pipecat/services/speechmatics/stt.py @@ -836,7 +836,7 @@ class SpeechmaticsSTTService(STTService): # await self.start_processing_metrics() await self.broadcast_frame(UserStartedSpeakingFrame) if self._should_interrupt: - await self.push_interruption_task_frame_and_wait() + await self.broadcast_interruption() async def _handle_end_of_turn(self, message: dict[str, Any]) -> None: """Handle EndOfTurn events. diff --git a/src/pipecat/transports/base_input.py b/src/pipecat/transports/base_input.py index 49c28149a..1da672ab7 100644 --- a/src/pipecat/transports/base_input.py +++ b/src/pipecat/transports/base_input.py @@ -558,7 +558,7 @@ class BaseInputTransport(FrameProcessor): # Make sure we notify about interruptions quickly out-of-band. if should_push_immediate_interruption and self._allow_interruptions: - await self.push_interruption_task_frame_and_wait() + await self.broadcast_interruption() elif self.interruption_strategies and self._bot_speaking: logger.debug( "User started speaking while bot is speaking with interruption config - " diff --git a/src/pipecat/turns/user_turn_processor.py b/src/pipecat/turns/user_turn_processor.py index 7f8995202..85bc658dd 100644 --- a/src/pipecat/turns/user_turn_processor.py +++ b/src/pipecat/turns/user_turn_processor.py @@ -182,7 +182,7 @@ class UserTurnProcessor(FrameProcessor): await self._user_idle_controller.process_frame(UserStartedSpeakingFrame()) if params.enable_interruptions and self._allow_interruptions: - await self.push_interruption_task_frame_and_wait() + await self.broadcast_interruption() await self._call_event_handler("on_user_turn_started", strategy) diff --git a/tests/test_context_aggregators.py b/tests/test_context_aggregators.py index 24dae0b4c..37d36bfef 100644 --- a/tests/test_context_aggregators.py +++ b/tests/test_context_aggregators.py @@ -21,7 +21,6 @@ from pipecat.frames.frames import ( FunctionCallResultProperties, InterimTranscriptionFrame, InterruptionFrame, - InterruptionTaskFrame, LLMContextAssistantTimestampFrame, LLMContextFrame, LLMFullResponseEndFrame, @@ -567,7 +566,7 @@ class BaseTestUserContextAggregator: SleepFrame(), UserStoppedSpeakingFrame(), ] - expected_up_frames = [InterruptionTaskFrame] + expected_up_frames = [InterruptionFrame] expected_down_frames = [ BotStartedSpeakingFrame, UserStartedSpeakingFrame, diff --git a/tests/test_frame_processor.py b/tests/test_frame_processor.py index 138c8e6d8..a875741e3 100644 --- a/tests/test_frame_processor.py +++ b/tests/test_frame_processor.py @@ -9,8 +9,6 @@ import unittest from dataclasses import dataclass, field from typing import List -from loguru import logger - from pipecat.frames.frames import ( DataFrame, EndFrame, @@ -85,50 +83,38 @@ class TestFrameProcessor(unittest.IsolatedAsyncioTestCase): assert before_push_called assert after_push_called - async def test_interruption_and_wait(self): - class DelayFrameProcessor(FrameProcessor): - """This processors just gives time to the event loop to change - between tasks. Otherwise things happen to fast.""" - - async def process_frame(self, frame: Frame, direction: FrameDirection): - await super().process_frame(frame, direction) - await asyncio.sleep(0.1) - await self.push_frame(frame, direction) + async def test_broadcast_interruption(self): + """Test that broadcast_interruption() pushes InterruptionFrame both + directions and allows subsequent code to run.""" class InterruptFrameProcessor(FrameProcessor): async def process_frame(self, frame: Frame, direction: FrameDirection): await super().process_frame(frame, direction) if isinstance(frame, TextFrame): - await self.push_interruption_task_frame_and_wait() + await self.broadcast_interruption() await self.push_frame(OutputTransportMessageUrgentFrame(message=frame.text)) else: await self.push_frame(frame, direction) - pipeline = Pipeline([DelayFrameProcessor(), InterruptFrameProcessor()]) + pipeline = Pipeline([InterruptFrameProcessor()]) frames_to_send = [ - # Just a random interruption to make sure we don't clear anything - # before the actual `InterruptionTaskFrame` interruption. - InterruptionFrame(), - # This will generate an `InterruptionTaskFrame` and will wait for an - # `InterruptionFrame`. TextFrame(text="Hello from Pipecat!"), - # Just give time for everything to complete. SleepFrame(sleep=0.5), - EndFrame(), ] expected_down_frames = [ - InterruptionFrame, InterruptionFrame, OutputTransportMessageUrgentFrame, - EndFrame, + ] + expected_up_frames = [ + InterruptionFrame, ] await run_test( pipeline, frames_to_send=frames_to_send, expected_down_frames=expected_down_frames, - send_end_frame=False, + expected_up_frames=expected_up_frames, ) async def test_interruptible_frames(self): @@ -454,33 +440,20 @@ class TestFrameProcessor(unittest.IsolatedAsyncioTestCase): stop_frames = [f for f in received_frames if isinstance(f, StopFrame)] self.assertEqual(len(stop_frames), 1, "StopFrame should survive interruption") - async def test_interruption_frame_complete_sets_event(self): - """Test that InterruptionFrame.complete() sets the event.""" - event = asyncio.Event() - frame = InterruptionFrame(event=event) - self.assertFalse(event.is_set()) - frame.complete() - self.assertTrue(event.is_set()) - - async def test_interruption_frame_complete_without_event(self): - """Test that InterruptionFrame.complete() is safe without an event.""" - frame = InterruptionFrame() - frame.complete() # Should not raise - - async def test_interruption_event_set_at_pipeline_sink(self): - """Test that the event from push_interruption_task_frame_and_wait() - is set when the InterruptionFrame reaches the pipeline sink.""" - event_was_set = False + async def test_broadcast_interruption_allows_subsequent_code(self): + """Test that broadcast_interruption() returns immediately, allowing the + caller to run code afterwards (e.g. push an urgent frame).""" + code_after_ran = False class InterruptOnTextProcessor(FrameProcessor): async def process_frame(self, frame: Frame, direction: FrameDirection): - nonlocal event_was_set + nonlocal code_after_ran await super().process_frame(frame, direction) if isinstance(frame, TextFrame): - await self.push_interruption_task_frame_and_wait() + await self.broadcast_interruption() - event_was_set = True + code_after_ran = True await self.push_frame(OutputTransportMessageUrgentFrame(message="done")) else: await self.push_frame(frame, direction) @@ -499,63 +472,7 @@ class TestFrameProcessor(unittest.IsolatedAsyncioTestCase): frames_to_send=frames_to_send, expected_down_frames=expected_down_frames, ) - self.assertTrue(event_was_set, "Event should be set after InterruptionFrame completes") - - async def test_interruption_completion_timeout_warning(self): - """Test that a warning is logged when an InterruptionFrame is blocked - and never reaches the pipeline sink.""" - warnings = [] - handler_id = logger.add( - lambda msg: warnings.append(str(msg)), level="WARNING", format="{message}" - ) - - try: - - class BlockInterruptionProcessor(FrameProcessor): - """Blocks InterruptionFrames, completing them after a delay.""" - - async def process_frame(self, frame: Frame, direction: FrameDirection): - await super().process_frame(frame, direction) - if isinstance(frame, InterruptionFrame): - # Complete after the timeout so the warning fires - # but the test doesn't hang. - async def delayed_complete(): - await asyncio.sleep(1.0) - frame.complete() - - asyncio.create_task(delayed_complete()) - return - await self.push_frame(frame, direction) - - class InterruptOnTextProcessor(FrameProcessor): - async def process_frame(self, frame: Frame, direction: FrameDirection): - await super().process_frame(frame, direction) - if isinstance(frame, TextFrame): - await self.push_interruption_task_frame_and_wait(timeout=0.5) - await self.push_frame(OutputTransportMessageUrgentFrame(message="done")) - else: - await self.push_frame(frame, direction) - - pipeline = Pipeline([BlockInterruptionProcessor(), InterruptOnTextProcessor()]) - - frames_to_send = [ - TextFrame(text="trigger"), - ] - expected_down_frames = [ - OutputTransportMessageUrgentFrame, - ] - await run_test( - pipeline, - frames_to_send=frames_to_send, - expected_down_frames=expected_down_frames, - ) - finally: - logger.remove(handler_id) - - self.assertTrue( - any("InterruptionFrame has not completed" in w for w in warnings), - "Expected a timeout warning about InterruptionFrame not completing", - ) + self.assertTrue(code_after_ran, "Code after broadcast_interruption() should execute") if __name__ == "__main__": diff --git a/tests/test_stt_mute_filter.py b/tests/test_stt_mute_filter.py index adf4611df..8f55bdecb 100644 --- a/tests/test_stt_mute_filter.py +++ b/tests/test_stt_mute_filter.py @@ -4,7 +4,6 @@ # SPDX-License-Identifier: BSD 2-Clause License # -import asyncio import unittest from pipecat.frames.frames import ( @@ -329,17 +328,13 @@ class TestSTTMuteFilter(unittest.IsolatedAsyncioTestCase): expected_down_frames=expected_returned_frames, ) - async def test_interruption_frame_completed_when_muted(self): - """Test that InterruptionFrame.complete() is called when the frame is - suppressed due to muting, so push_interruption_task_frame_and_wait() - doesn't hang.""" + async def test_interruption_frame_suppressed_when_muted(self): + """Test that InterruptionFrame is suppressed when the filter is muted.""" filter = STTMuteFilter(config=STTMuteConfig(strategies={STTMuteStrategy.ALWAYS})) - event = asyncio.Event() - frames_to_send = [ BotStartedSpeakingFrame(), - InterruptionFrame(event=event), + InterruptionFrame(), BotStoppedSpeakingFrame(), ] @@ -354,8 +349,6 @@ class TestSTTMuteFilter(unittest.IsolatedAsyncioTestCase): expected_down_frames=expected_returned_frames, ) - self.assertTrue(event.is_set(), "InterruptionFrame.complete() should be called when muted") - if __name__ == "__main__": unittest.main() From 741ff14d3a552a2530aaa2c01afe94c7a3b893df Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Aleix=20Conchillo=20Flaqu=C3=A9?= Date: Mon, 2 Mar 2026 12:06:08 -0800 Subject: [PATCH 0752/1060] Rename changelog files to use PR #3896 and mark breaking change --- changelog/{3900.added.md => 3896.added.md} | 0 changelog/3896.changed.md | 1 + changelog/{3900.deprecated.md => 3896.deprecated.md} | 0 changelog/3900.changed.md | 1 - 4 files changed, 1 insertion(+), 1 deletion(-) rename changelog/{3900.added.md => 3896.added.md} (100%) create mode 100644 changelog/3896.changed.md rename changelog/{3900.deprecated.md => 3896.deprecated.md} (100%) delete mode 100644 changelog/3900.changed.md diff --git a/changelog/3900.added.md b/changelog/3896.added.md similarity index 100% rename from changelog/3900.added.md rename to changelog/3896.added.md diff --git a/changelog/3896.changed.md b/changelog/3896.changed.md new file mode 100644 index 000000000..3b7e4f807 --- /dev/null +++ b/changelog/3896.changed.md @@ -0,0 +1 @@ +- ⚠️ Removed `event` field and `complete()` method from `InterruptionFrame`. Removed `event` field from `InterruptionTaskFrame`. These are no longer needed since `broadcast_interruption()` does not require a round-trip completion signal. diff --git a/changelog/3900.deprecated.md b/changelog/3896.deprecated.md similarity index 100% rename from changelog/3900.deprecated.md rename to changelog/3896.deprecated.md diff --git a/changelog/3900.changed.md b/changelog/3900.changed.md deleted file mode 100644 index 59b4cdb95..000000000 --- a/changelog/3900.changed.md +++ /dev/null @@ -1 +0,0 @@ -- Removed `event` field and `complete()` method from `InterruptionFrame`. Removed `event` field from `InterruptionTaskFrame`. These are no longer needed since `broadcast_interruption()` does not require a round-trip completion signal. From 68d7e98f95b02c9ba925921dfc26ccf727a25a08 Mon Sep 17 00:00:00 2001 From: Mark Backman Date: Mon, 2 Mar 2026 16:33:25 -0500 Subject: [PATCH 0753/1060] Add defensive comment for given_fields() usage in tracing --- src/pipecat/utils/tracing/service_attributes.py | 6 +++--- src/pipecat/utils/tracing/service_decorators.py | 3 ++- 2 files changed, 5 insertions(+), 4 deletions(-) diff --git a/src/pipecat/utils/tracing/service_attributes.py b/src/pipecat/utils/tracing/service_attributes.py index 97ac49d87..21a22341f 100644 --- a/src/pipecat/utils/tracing/service_attributes.py +++ b/src/pipecat/utils/tracing/service_attributes.py @@ -107,7 +107,7 @@ def add_tts_span_attributes( if ttfb is not None: span.set_attribute("metrics.ttfb", ttfb) - # Add settings if provided + # Use given_fields() defensively in case a service doesn't initialize all settings. if settings: for key, value in settings.given_fields().items(): if isinstance(value, (str, int, float, bool)): @@ -171,7 +171,7 @@ def add_stt_span_attributes( if ttfb is not None: span.set_attribute("metrics.ttfb", ttfb) - # Add settings if provided + # Use given_fields() defensively in case a service doesn't initialize all settings. if settings: for key, value in settings.given_fields().items(): if isinstance(value, (str, int, float, bool)): @@ -359,7 +359,7 @@ def add_gemini_live_span_attributes( if tools_serialized: span.set_attribute("tools.definitions", tools_serialized) - # Add settings if provided + # Use given_fields() defensively in case a service doesn't initialize all settings. if settings: for key, value in settings.given_fields().items(): if isinstance(value, (str, int, float, bool)): diff --git a/src/pipecat/utils/tracing/service_decorators.py b/src/pipecat/utils/tracing/service_decorators.py index 304ecb5e8..f4764d248 100644 --- a/src/pipecat/utils/tracing/service_decorators.py +++ b/src/pipecat/utils/tracing/service_decorators.py @@ -507,7 +507,8 @@ def traced_llm(func: Optional[Callable] = None, *, name: Optional[str] = None) - elif hasattr(self, "_system_instruction"): system_message = self._system_instruction - # Get settings from the service + # Use given_fields() defensively in case a service doesn't + # initialize all settings. params = {} if hasattr(self, "_settings"): for key, value in self._settings.given_fields().items(): From 07fdd610ca3f5e82d686ecf37abb29a59c433480 Mon Sep 17 00:00:00 2001 From: filipi87 Date: Mon, 2 Mar 2026 19:02:33 -0300 Subject: [PATCH 0754/1060] Using a default voice in case it is not provided. --- src/pipecat/transports/lemonslice/utils.py | 4 +++- 1 file changed, 3 insertions(+), 1 deletion(-) diff --git a/src/pipecat/transports/lemonslice/utils.py b/src/pipecat/transports/lemonslice/utils.py index 98aac3ccb..cac341d7d 100644 --- a/src/pipecat/transports/lemonslice/utils.py +++ b/src/pipecat/transports/lemonslice/utils.py @@ -64,7 +64,9 @@ class LemonSliceApi: ValueError: If neither agent_id nor agent_image_url is provided. """ if not agent_id and not agent_image_url: - raise ValueError("Provide either agent_id or agent_image_url") + # Fallback to a default agent if none is provided + logger.debug("No agent_id or agent_image_url provided, using default agent") + agent_id = "agent_080308d8b6e99f47" if agent_id and agent_image_url: raise ValueError("Provide exactly one of agent_id or agent_image_url, not both") From 7afd7068b5b57949c5db2d600b34b21714957cbb Mon Sep 17 00:00:00 2001 From: filipi87 Date: Mon, 2 Mar 2026 19:02:51 -0300 Subject: [PATCH 0755/1060] Retrieving the elevenlabs voice ID from environment variable --- examples/foundational/55-lemonslice-transport.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/examples/foundational/55-lemonslice-transport.py b/examples/foundational/55-lemonslice-transport.py index c9f080567..a8e22ede1 100644 --- a/examples/foundational/55-lemonslice-transport.py +++ b/examples/foundational/55-lemonslice-transport.py @@ -53,7 +53,7 @@ async def main(): tts = ElevenLabsTTSService( api_key=os.getenv("ELEVENLABS_API_KEY", ""), - voice_id="ys3XeJJA4ArWMhRpcX1D", + voice_id=os.getenv("ELEVENLABS_VOICE_ID", ""), ) messages = [ From 7648b62e6e50639d4f6607da75fe69e1d4132252 Mon Sep 17 00:00:00 2001 From: zkleb-aai <146127913+zkleb-aai@users.noreply.github.com> Date: Mon, 2 Mar 2026 17:04:17 -0500 Subject: [PATCH 0756/1060] Update src/pipecat/services/assemblyai/stt.py Co-authored-by: Mark Backman --- src/pipecat/services/assemblyai/stt.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/src/pipecat/services/assemblyai/stt.py b/src/pipecat/services/assemblyai/stt.py index 9938afdee..8ef6b5a07 100644 --- a/src/pipecat/services/assemblyai/stt.py +++ b/src/pipecat/services/assemblyai/stt.py @@ -590,7 +590,7 @@ class AssemblyAISTTService(WebsocketSTTService): data = json.loads(message) # Log raw JSON for Turn messages to debug speaker_label if data.get("type") == "Turn": - logger.debug(f"{self} RAW JSON from AssemblyAI: {json.dumps(data, indent=2)}") + logger.trace(f"{self} RAW JSON from AssemblyAI: {json.dumps(data, indent=2)}") await self._handle_message(data) except json.JSONDecodeError: logger.warning(f"Received non-JSON message: {message}") From 6729f4366a68bb56f4b8a11f22b15b1c4ce4a333 Mon Sep 17 00:00:00 2001 From: zkleb-aai <146127913+zkleb-aai@users.noreply.github.com> Date: Mon, 2 Mar 2026 17:04:42 -0500 Subject: [PATCH 0757/1060] Update src/pipecat/services/assemblyai/stt.py Co-authored-by: Mark Backman --- src/pipecat/services/assemblyai/stt.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/src/pipecat/services/assemblyai/stt.py b/src/pipecat/services/assemblyai/stt.py index 8ef6b5a07..bbbdad3f8 100644 --- a/src/pipecat/services/assemblyai/stt.py +++ b/src/pipecat/services/assemblyai/stt.py @@ -717,7 +717,7 @@ class AssemblyAISTTService(WebsocketSTTService): finalize_confirmed = bool(message.turn_is_formatted) if finalize_confirmed: self.confirm_finalize() - logger.debug(f'{self} Final transcript: "{transcript_text}"') + logger.debug(f'{self} Transcript: "{transcript_text}"') await self.push_frame( TranscriptionFrame( transcript_text, From 5c2ca0ce64d41f096bcfb7569dbda6480da31c13 Mon Sep 17 00:00:00 2001 From: zkleb-aai <146127913+zkleb-aai@users.noreply.github.com> Date: Mon, 2 Mar 2026 17:04:54 -0500 Subject: [PATCH 0758/1060] Update changelog/3856.changed.md Co-authored-by: Mark Backman --- changelog/3856.changed.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/changelog/3856.changed.md b/changelog/3856.changed.md index 72331c068..1e7f4c916 100644 --- a/changelog/3856.changed.md +++ b/changelog/3856.changed.md @@ -1 +1 @@ -- Rename AssemblyAI min_end_of_turn_silence_when_confident parameter to min_turn_silence (old name still supported with deprecation warning) +- Rename `AssemblyAISTTService` parameter `min_end_of_turn_silence_when_confident` parameter to `min_turn_silence` (old name still supported with deprecation warning) From ebb794995b6133ec79639356a8eebf6b31b745b5 Mon Sep 17 00:00:00 2001 From: filipi87 Date: Mon, 2 Mar 2026 19:06:13 -0300 Subject: [PATCH 0759/1060] Changing the log levels. --- src/pipecat/transports/lemonslice/transport.py | 8 ++++---- 1 file changed, 4 insertions(+), 4 deletions(-) diff --git a/src/pipecat/transports/lemonslice/transport.py b/src/pipecat/transports/lemonslice/transport.py index 9ef014f79..384921d62 100644 --- a/src/pipecat/transports/lemonslice/transport.py +++ b/src/pipecat/transports/lemonslice/transport.py @@ -329,7 +329,7 @@ class LemonSliceTransportClient: async def send_response_started_message(self) -> None: """Send a response_started message to the LemonSlice session.""" - logger.info("Sending response_started message") + logger.trace("Sending response_started message") transport_frame = OutputTransportMessageUrgentFrame( message={ "event": "response_started", @@ -340,7 +340,7 @@ class LemonSliceTransportClient: async def send_response_finished_message(self) -> None: """Send a response_finished message to the LemonSlice session.""" - logger.debug("Sending response_finished message") + logger.trace("Sending response_finished message") transport_frame = OutputTransportMessageUrgentFrame( message={ "event": "response_finished", @@ -470,7 +470,7 @@ class LemonSliceInputTransport(BaseInputTransport): participant: The participant to capture audio from. """ if self._params.audio_in_enabled: - logger.info( + logger.debug( f"LemonSliceTransportClient start capturing audio for participant {participant['id']}" ) await self._client.capture_participant_audio( @@ -587,7 +587,7 @@ class LemonSliceOutputTransport(BaseOutputTransport): Args: frame: The message frame to send. """ - logger.info(f"LemonSliceTransport sending message {frame}") + logger.trace(f"LemonSliceTransport sending message {frame}") await self._client.send_message(frame) async def push_frame(self, frame: Frame, direction: FrameDirection = FrameDirection.DOWNSTREAM): From daf14f50656b9de046ded01c7f5ab27d9d8dbbd0 Mon Sep 17 00:00:00 2001 From: filipi87 Date: Mon, 2 Mar 2026 19:08:17 -0300 Subject: [PATCH 0760/1060] Renaming LemonSlice utils file to api. --- src/pipecat/transports/lemonslice/{utils.py => api.py} | 0 src/pipecat/transports/lemonslice/transport.py | 2 +- 2 files changed, 1 insertion(+), 1 deletion(-) rename src/pipecat/transports/lemonslice/{utils.py => api.py} (100%) diff --git a/src/pipecat/transports/lemonslice/utils.py b/src/pipecat/transports/lemonslice/api.py similarity index 100% rename from src/pipecat/transports/lemonslice/utils.py rename to src/pipecat/transports/lemonslice/api.py diff --git a/src/pipecat/transports/lemonslice/transport.py b/src/pipecat/transports/lemonslice/transport.py index 384921d62..d649a3fcb 100644 --- a/src/pipecat/transports/lemonslice/transport.py +++ b/src/pipecat/transports/lemonslice/transport.py @@ -40,7 +40,7 @@ from pipecat.transports.daily.transport import ( DailyParams, DailyTransportClient, ) -from pipecat.transports.lemonslice.utils import LemonSliceApi +from pipecat.transports.lemonslice.api import LemonSliceApi class LemonSliceCallbacks(BaseModel): From f07e55a4ed8b42b918ca62d12452d25ddebc0959 Mon Sep 17 00:00:00 2001 From: filipi87 Date: Mon, 2 Mar 2026 19:15:18 -0300 Subject: [PATCH 0761/1060] Wrap LemonSlice session creation params in LemonSliceNewSessionRequest --- .../foundational/55-lemonslice-transport.py | 10 ++- .../transports/lemonslice/transport.py | 87 ++++++++----------- 2 files changed, 46 insertions(+), 51 deletions(-) diff --git a/examples/foundational/55-lemonslice-transport.py b/examples/foundational/55-lemonslice-transport.py index a8e22ede1..8b2e19a6e 100644 --- a/examples/foundational/55-lemonslice-transport.py +++ b/examples/foundational/55-lemonslice-transport.py @@ -25,7 +25,11 @@ from pipecat.processors.aggregators.llm_response_universal import ( from pipecat.services.deepgram.stt import DeepgramSTTService from pipecat.services.elevenlabs.tts import ElevenLabsTTSService from pipecat.services.groq.llm import GroqLLMService -from pipecat.transports.lemonslice.transport import LemonSliceParams, LemonSliceTransport +from pipecat.transports.lemonslice.transport import ( + LemonSliceNewSessionRequest, + LemonSliceParams, + LemonSliceTransport, +) load_dotenv(override=True) @@ -38,8 +42,10 @@ async def main(): transport = LemonSliceTransport( bot_name="Pipecat", api_key=os.getenv("LEMONSLICE_API_KEY"), - agent_id=os.getenv("LEMONSLICE_AGENT_ID"), session=session, + session_request=LemonSliceNewSessionRequest( + agent_id=os.getenv("LEMONSLICE_AGENT_ID"), + ), params=LemonSliceParams( audio_in_enabled=True, audio_out_enabled=True, diff --git a/src/pipecat/transports/lemonslice/transport.py b/src/pipecat/transports/lemonslice/transport.py index d649a3fcb..6a6894167 100644 --- a/src/pipecat/transports/lemonslice/transport.py +++ b/src/pipecat/transports/lemonslice/transport.py @@ -43,6 +43,29 @@ from pipecat.transports.daily.transport import ( from pipecat.transports.lemonslice.api import LemonSliceApi +class LemonSliceNewSessionRequest(BaseModel): + """Request model for creating a new LemonSlice session. + + Parameters: + agent_image_url: URL to an agent image. Provide either agent_id or agent_image_url. + agent_id: ID of a LemonSlice agent. Provide either agent_id or agent_image_url. + agent_prompt: A high-level system prompt that subtly influences the avatar's movements, + expressions, and emotional demeanor. + idle_timeout: Idle timeout in seconds. + daily_room_url: Daily room URL to use for the session. + daily_token: Daily token for authenticating with the room. + lemonslice_properties: Additional properties to pass to the session. + """ + + agent_image_url: Optional[str] = None + agent_id: Optional[str] = None + agent_prompt: Optional[str] = None + idle_timeout: Optional[int] = None + daily_room_url: Optional[str] = None + daily_token: Optional[str] = None + lemonslice_properties: Optional[dict] = None + + class LemonSliceCallbacks(BaseModel): """Callback handlers for LemonSlice events. @@ -87,13 +110,7 @@ class LemonSliceTransportClient: params: LemonSliceParams = LemonSliceParams(), callbacks: LemonSliceCallbacks, api_key: str, - agent_image_url: Optional[str] = None, - agent_id: Optional[str] = None, - agent_prompt: Optional[str] = None, - idle_timeout: Optional[int] = None, - daily_room_url: Optional[str] = None, - daily_token: Optional[str] = None, - lemonslice_properties: Optional[dict] = None, + session_request: Optional[LemonSliceNewSessionRequest] = None, session: aiohttp.ClientSession, ) -> None: """Initialize the LemonSlice transport client. @@ -103,24 +120,13 @@ class LemonSliceTransportClient: params: Optional parameters for LemonSlice operation. callbacks: Callback handlers for LemonSlice-related events. api_key: API key for authenticating with LemonSlice API. - agent_image_url: Optional URL to an agent image. - agent_id: Optional ID of LemonSlice agent. - agent_prompt: Optional system prompt for the avatar. - idle_timeout: Optional idle timeout in seconds. - daily_room_url: Optional Daily room URL to add the LemonSlice avatar to. - daily_token: Optional Daily token for authenticating with the room. - lemonslice_properties: Optional additional properties for the session. + session_request: Optional session creation parameters. If not provided, a default + agent will be used. session: The aiohttp session for making async HTTP requests. """ self._bot_name = bot_name self._api = LemonSliceApi(api_key, session) - self._agent_id = agent_id - self._agent_image_url = agent_image_url - self._agent_prompt = agent_prompt - self._idle_timeout = idle_timeout - self._daily_room_url = daily_room_url - self._daily_token = daily_token - self._lemonslice_properties = lemonslice_properties + self._session_request = session_request or LemonSliceNewSessionRequest() self._session_id: Optional[str] = None self._control_url: Optional[str] = None self._daily_transport_client: Optional[DailyTransportClient] = None @@ -130,13 +136,13 @@ class LemonSliceTransportClient: async def _initialize(self) -> str: """Initialize the conversation and return the room URL.""" response = await self._api.create_session( - agent_image_url=self._agent_image_url, - agent_id=self._agent_id, - agent_prompt=self._agent_prompt, - idle_timeout=self._idle_timeout, - daily_room_url=self._daily_room_url, - daily_token=self._daily_token, - properties=self._lemonslice_properties, + agent_image_url=self._session_request.agent_image_url, + agent_id=self._session_request.agent_id, + agent_prompt=self._session_request.agent_prompt, + idle_timeout=self._session_request.idle_timeout, + daily_room_url=self._session_request.daily_room_url, + daily_token=self._session_request.daily_token, + properties=self._session_request.lemonslice_properties, ) self._session_id = response["session_id"] self._control_url = response["control_url"] @@ -675,16 +681,10 @@ class LemonSliceTransport(BaseTransport): bot_name: str, session: aiohttp.ClientSession, api_key: str, - agent_image_url: Optional[str] = None, - agent_id: Optional[str] = None, - agent_prompt: Optional[str] = None, - idle_timeout: Optional[int] = None, + session_request: Optional[LemonSliceNewSessionRequest] = None, params: LemonSliceParams = LemonSliceParams(), input_name: Optional[str] = None, output_name: Optional[str] = None, - daily_room_url: Optional[str] = None, - daily_token: Optional[str] = None, - lemonslice_properties: Optional[dict] = None, ): """Initialize the LemonSlice transport. @@ -692,16 +692,11 @@ class LemonSliceTransport(BaseTransport): bot_name: The name of the Pipecat bot. session: aiohttp session used for async HTTP requests. api_key: LemonSlice API key for authentication. - agent_image_url: Optional URL to an agent image. - agent_id: Optional ID of the LemonSlice agent. - agent_prompt: Optional system prompt for the avatar. - idle_timeout: Optional idle timeout in seconds. + session_request: Optional session creation parameters. If not provided, a default + agent will be used. params: Optional LemonSlice-specific configuration parameters. input_name: Optional name for the input transport. output_name: Optional name for the output transport. - daily_room_url: Optional Daily room URL to add the LemonSlice avatar to. - daily_token: Optional Daily token for authenticating with the room. - lemonslice_properties: Optional additional properties for the session. """ super().__init__(input_name=input_name, output_name=output_name) self._params = params @@ -714,13 +709,7 @@ class LemonSliceTransport(BaseTransport): bot_name=bot_name, callbacks=callbacks, api_key=api_key, - agent_image_url=agent_image_url, - agent_id=agent_id, - agent_prompt=agent_prompt, - idle_timeout=idle_timeout, - daily_room_url=daily_room_url, - daily_token=daily_token, - lemonslice_properties=lemonslice_properties, + session_request=session_request, session=session, params=params, ) From 11783520c05d20bd7a1e2d8100bf16f6bddaa7ac Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Aleix=20Conchillo=20Flaqu=C3=A9?= Date: Mon, 2 Mar 2026 14:43:34 -0800 Subject: [PATCH 0762/1060] services(deepgram): move stt|tts_sagemaker to sagemaker/stt|tts.py --- src/pipecat/services/deepgram/__init__.py | 1 + .../services/deepgram/{stt_sagemaker.py => sagemaker/stt.py} | 0 .../services/deepgram/{tts_sagemaker.py => sagemaker/tts.py} | 0 3 files changed, 1 insertion(+) rename src/pipecat/services/deepgram/{stt_sagemaker.py => sagemaker/stt.py} (100%) rename src/pipecat/services/deepgram/{tts_sagemaker.py => sagemaker/tts.py} (100%) diff --git a/src/pipecat/services/deepgram/__init__.py b/src/pipecat/services/deepgram/__init__.py index 4e1db3886..f67271abc 100644 --- a/src/pipecat/services/deepgram/__init__.py +++ b/src/pipecat/services/deepgram/__init__.py @@ -9,6 +9,7 @@ import sys from pipecat.services import DeprecatedModuleProxy from .flux import * +from .sagemaker import * from .stt import * from .tts import * diff --git a/src/pipecat/services/deepgram/stt_sagemaker.py b/src/pipecat/services/deepgram/sagemaker/stt.py similarity index 100% rename from src/pipecat/services/deepgram/stt_sagemaker.py rename to src/pipecat/services/deepgram/sagemaker/stt.py diff --git a/src/pipecat/services/deepgram/tts_sagemaker.py b/src/pipecat/services/deepgram/sagemaker/tts.py similarity index 100% rename from src/pipecat/services/deepgram/tts_sagemaker.py rename to src/pipecat/services/deepgram/sagemaker/tts.py From fdeddd7c95d38c3f4f77ccd2cdaa86afd67568ea Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Aleix=20Conchillo=20Flaqu=C3=A9?= Date: Mon, 2 Mar 2026 14:47:17 -0800 Subject: [PATCH 0763/1060] Add deprecation shims for moved stt_sagemaker/tts_sagemaker modules Re-export from the new pipecat.services.deepgram.sagemaker.{stt,tts} paths so existing imports keep working with a deprecation warning. --- src/pipecat/services/deepgram/stt_sagemaker.py | 18 ++++++++++++++++++ src/pipecat/services/deepgram/tts_sagemaker.py | 18 ++++++++++++++++++ 2 files changed, 36 insertions(+) create mode 100644 src/pipecat/services/deepgram/stt_sagemaker.py create mode 100644 src/pipecat/services/deepgram/tts_sagemaker.py diff --git a/src/pipecat/services/deepgram/stt_sagemaker.py b/src/pipecat/services/deepgram/stt_sagemaker.py new file mode 100644 index 000000000..08cd0c5d3 --- /dev/null +++ b/src/pipecat/services/deepgram/stt_sagemaker.py @@ -0,0 +1,18 @@ +# +# Copyright (c) 2024-2026, Daily +# +# SPDX-License-Identifier: BSD 2-Clause License +# + +"""Deprecated: use ``pipecat.services.deepgram.sagemaker.stt`` instead.""" + +import warnings + +warnings.warn( + "Module `pipecat.services.deepgram.stt_sagemaker` is deprecated, " + "use `pipecat.services.deepgram.sagemaker.stt` instead.", + DeprecationWarning, + stacklevel=2, +) + +from pipecat.services.deepgram.sagemaker.stt import * # noqa: E402, F401, F403 diff --git a/src/pipecat/services/deepgram/tts_sagemaker.py b/src/pipecat/services/deepgram/tts_sagemaker.py new file mode 100644 index 000000000..61ca2bceb --- /dev/null +++ b/src/pipecat/services/deepgram/tts_sagemaker.py @@ -0,0 +1,18 @@ +# +# Copyright (c) 2024-2026, Daily +# +# SPDX-License-Identifier: BSD 2-Clause License +# + +"""Deprecated: use ``pipecat.services.deepgram.sagemaker.tts`` instead.""" + +import warnings + +warnings.warn( + "Module `pipecat.services.deepgram.tts_sagemaker` is deprecated, " + "use `pipecat.services.deepgram.sagemaker.tts` instead.", + DeprecationWarning, + stacklevel=2, +) + +from pipecat.services.deepgram.sagemaker.tts import * # noqa: E402, F401, F403 From aae9136df913c5fdfb2d4ee252411fe09b8ac001 Mon Sep 17 00:00:00 2001 From: Mark Backman Date: Mon, 2 Mar 2026 17:44:35 -0500 Subject: [PATCH 0764/1060] Review feedback --- README.md | 2 +- ...slice-transport.py => 56-lemonslice-transport.py} | 0 examples/foundational/README.md | 2 +- uv.lock | 12 +++++++++++- 4 files changed, 13 insertions(+), 3 deletions(-) rename examples/foundational/{55-lemonslice-transport.py => 56-lemonslice-transport.py} (100%) diff --git a/README.md b/README.md index 6a8c8c1fa..881b0ed5e 100644 --- a/README.md +++ b/README.md @@ -89,7 +89,7 @@ Catch new features, interviews, and how-tos on our [Pipecat TV](https://www.yout | Speech-to-Speech | [AWS Nova Sonic](https://docs.pipecat.ai/server/services/s2s/aws), [Gemini Multimodal Live](https://docs.pipecat.ai/server/services/s2s/gemini), [Grok Voice Agent](https://docs.pipecat.ai/server/services/s2s/grok), [OpenAI Realtime](https://docs.pipecat.ai/server/services/s2s/openai), [Ultravox](https://docs.pipecat.ai/server/services/s2s/ultravox), | | Transport | [Daily (WebRTC)](https://docs.pipecat.ai/server/services/transport/daily), [FastAPI Websocket](https://docs.pipecat.ai/server/services/transport/fastapi-websocket), [SmallWebRTCTransport](https://docs.pipecat.ai/server/services/transport/small-webrtc), [WebSocket Server](https://docs.pipecat.ai/server/services/transport/websocket-server), Local | | Serializers | [Exotel](https://docs.pipecat.ai/server/utilities/serializers/exotel), [Plivo](https://docs.pipecat.ai/server/utilities/serializers/plivo), [Twilio](https://docs.pipecat.ai/server/utilities/serializers/twilio), [Telnyx](https://docs.pipecat.ai/server/utilities/serializers/telnyx), [Vonage](https://docs.pipecat.ai/server/utilities/serializers/vonage) | -| Video | [HeyGen](https://docs.pipecat.ai/server/services/video/heygen), [LemonSlice](https://lemonslice.com/docs/self-managed/overview), [Tavus](https://docs.pipecat.ai/server/services/video/tavus), [Simli](https://docs.pipecat.ai/server/services/video/simli) | +| Video | [HeyGen](https://docs.pipecat.ai/server/services/video/heygen), [LemonSlice](https://docs.pipecat.ai/server/services/video/lemonslice), [Tavus](https://docs.pipecat.ai/server/services/video/tavus), [Simli](https://docs.pipecat.ai/server/services/video/simli) | | Memory | [mem0](https://docs.pipecat.ai/server/services/memory/mem0) | | Vision & Image | [fal](https://docs.pipecat.ai/server/services/image-generation/fal), [Google Imagen](https://docs.pipecat.ai/server/services/image-generation/google-imagen), [Moondream](https://docs.pipecat.ai/server/services/vision/moondream) | | Audio Processing | [Silero VAD](https://docs.pipecat.ai/server/utilities/audio/silero-vad-analyzer), [Krisp](https://docs.pipecat.ai/server/utilities/audio/krisp-filter), [Koala](https://docs.pipecat.ai/server/utilities/audio/koala-filter), [ai-coustics](https://docs.pipecat.ai/server/utilities/audio/aic-filter) | diff --git a/examples/foundational/55-lemonslice-transport.py b/examples/foundational/56-lemonslice-transport.py similarity index 100% rename from examples/foundational/55-lemonslice-transport.py rename to examples/foundational/56-lemonslice-transport.py diff --git a/examples/foundational/README.md b/examples/foundational/README.md index 8fb60a0c2..04e88b7e7 100644 --- a/examples/foundational/README.md +++ b/examples/foundational/README.md @@ -121,7 +121,7 @@ uv run 07-interruptible.py -t twilio -x NGROK_HOST_NAME - **[19-openai-realtime-beta.py](./19-openai-realtime-beta.py)**: OpenAI Speech-to-Speech (Direct S2S, Function calls) - **[21-tavus-layer-tavus-transport.py](./21-tavus-layer-tavus-transport.py)**: Tavus digital twin (Avatar integration) - 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== 'fish'", specifier = "~=1.7.0" }, { name = "pillow", specifier = ">=11.1.0,<13" }, + { name = "pipecat-ai", extras = ["daily"], marker = "extra == 'lemonslice'" }, { name = "pipecat-ai", extras = ["nvidia"], marker = "extra == 'riva'" }, { name = "pipecat-ai", extras = ["websockets-base"], marker = "extra == 'assemblyai'" }, { name = "pipecat-ai", extras = ["websockets-base"], marker = "extra == 'asyncai'" }, @@ -4857,7 +4867,7 @@ requires-dist = [ { name = "wait-for2", marker = "python_full_version < '3.12'", specifier = ">=0.4.1" }, { name = "websockets", marker = "extra == 'websockets-base'", specifier = ">=13.1,<16.0" }, ] -provides-extras = ["aic", "anthropic", "assemblyai", "asyncai", "aws", "aws-nova-sonic", "azure", "cartesia", "camb", "cerebras", "daily", "deepgram", "deepseek", "elevenlabs", "fal", "fireworks", "fish", "gladia", "google", "gradium", "grok", "groq", "gstreamer", "heygen", "hume", "inworld", "koala", "kokoro", "krisp", "langchain", "livekit", "lmnt", 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"openrouter", "perplexity", "piper", "qwen", "remote-smart-turn", "resembleai", "rime", "riva", "runner", "sagemaker", "sambanova", "sarvam", "sentry", "silero", "simli", "soniox", "soundfile", "speechmatics", "strands", "tavus", "together", "tracing", "ultravox", "webrtc", "websocket", "websockets-base", "whisper"] [package.metadata.requires-dev] dev = [ From b449515410eac0b577af86d82abf71225bb58460 Mon Sep 17 00:00:00 2001 From: zack Date: Mon, 2 Mar 2026 17:54:31 -0500 Subject: [PATCH 0765/1060] Address PR review feedback: remove debug logs, fix hasattr logic, add VADAnalyzer --- .../07o-interruptible-assemblyai-stt.py | 6 +- src/pipecat/services/assemblyai/stt.py | 86 ++++++++----------- 2 files changed, 40 insertions(+), 52 deletions(-) diff --git a/examples/foundational/07o-interruptible-assemblyai-stt.py b/examples/foundational/07o-interruptible-assemblyai-stt.py index 2765f8590..01d53914d 100644 --- a/examples/foundational/07o-interruptible-assemblyai-stt.py +++ b/examples/foundational/07o-interruptible-assemblyai-stt.py @@ -10,6 +10,7 @@ import os from dotenv import load_dotenv from loguru import logger +from pipecat.audio.vad.silero import SileroVADAnalyzer from pipecat.frames.frames import LLMRunFrame from pipecat.pipeline.pipeline import Pipeline from pipecat.pipeline.runner import PipelineRunner @@ -122,7 +123,10 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): context = LLMContext(messages) user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, - user_params=LLMUserAggregatorParams(user_turn_strategies=ExternalUserTurnStrategies()), + user_params=LLMUserAggregatorParams( + user_turn_strategies=ExternalUserTurnStrategies(), + vad_analyzer=SileroVADAnalyzer(), + ), ) pipeline = Pipeline( diff --git a/src/pipecat/services/assemblyai/stt.py b/src/pipecat/services/assemblyai/stt.py index bbbdad3f8..2e14b1a66 100644 --- a/src/pipecat/services/assemblyai/stt.py +++ b/src/pipecat/services/assemblyai/stt.py @@ -212,7 +212,6 @@ class AssemblyAISTTService(WebsocketSTTService): self._chunk_size_bytes = 0 self._user_speaking = False - self._vad_speaking = False def _configure_pipecat_turn_mode( self, connection_params: AssemblyAIConnectionParams, is_u3_pro: bool @@ -320,48 +319,44 @@ class AssemblyAISTTService(WebsocketSTTService): old_conn_params = changed.get("connection_params") # Check each potentially changed parameter - if hasattr(conn_params, "keyterms_prompt"): - if ( - old_conn_params is None - or conn_params.keyterms_prompt != old_conn_params.keyterms_prompt - ): - if conn_params.keyterms_prompt is not None: - update_config["keyterms_prompt"] = conn_params.keyterms_prompt - logger.info(f"Updating keyterms_prompt to: {conn_params.keyterms_prompt}") + if ( + old_conn_params is None + or conn_params.keyterms_prompt != old_conn_params.keyterms_prompt + ): + if conn_params.keyterms_prompt is not None: + update_config["keyterms_prompt"] = conn_params.keyterms_prompt + logger.info(f"Updating keyterms_prompt to: {conn_params.keyterms_prompt}") - if hasattr(conn_params, "prompt"): - if old_conn_params is None or conn_params.prompt != old_conn_params.prompt: - if conn_params.prompt is not None: - if conn_params.speech_model != "u3-rt-pro": - logger.warning( - f"prompt parameter is only supported with u3-rt-pro model, " - f"current model is {conn_params.speech_model}" - ) - else: - update_config["prompt"] = conn_params.prompt - logger.info(f"Updating prompt") - - if hasattr(conn_params, "max_turn_silence"): - if ( - old_conn_params is None - or conn_params.max_turn_silence != old_conn_params.max_turn_silence - ): - if conn_params.max_turn_silence is not None: - update_config["max_turn_silence"] = conn_params.max_turn_silence - logger.info( - f"Updating max_turn_silence to: {conn_params.max_turn_silence}ms" + if old_conn_params is None or conn_params.prompt != old_conn_params.prompt: + if conn_params.prompt is not None: + if conn_params.speech_model != "u3-rt-pro": + logger.warning( + f"prompt parameter is only supported with u3-rt-pro model, " + f"current model is {conn_params.speech_model}" ) + else: + update_config["prompt"] = conn_params.prompt + logger.info(f"Updating prompt") - if hasattr(conn_params, "min_turn_silence"): - if ( - old_conn_params is None - or conn_params.min_turn_silence != old_conn_params.min_turn_silence - ): - if conn_params.min_turn_silence is not None: - update_config["min_turn_silence"] = conn_params.min_turn_silence - logger.info( - f"Updating min_turn_silence to: {conn_params.min_turn_silence}ms" - ) + if ( + old_conn_params is None + or conn_params.max_turn_silence != old_conn_params.max_turn_silence + ): + if conn_params.max_turn_silence is not None: + update_config["max_turn_silence"] = conn_params.max_turn_silence + logger.info( + f"Updating max_turn_silence to: {conn_params.max_turn_silence}ms" + ) + + if ( + old_conn_params is None + or conn_params.min_turn_silence != old_conn_params.min_turn_silence + ): + if conn_params.min_turn_silence is not None: + update_config["min_turn_silence"] = conn_params.min_turn_silence + logger.info( + f"Updating min_turn_silence to: {conn_params.min_turn_silence}ms" + ) # Send update if we have parameters to update if len(update_config) > 1: # More than just "type" @@ -639,20 +634,14 @@ class AssemblyAISTTService(WebsocketSTTService): Only applies to Mode 2 (STT turn detection). In Mode 1, VAD + smart turn analyzer handle interruptions via the aggregator. """ - logger.debug( - f"{self} SpeechStarted received (vad_force_turn_endpoint={self._vad_force_turn_endpoint})" - ) if self._vad_force_turn_endpoint: - logger.debug(f"{self} SpeechStarted ignored in Pipecat mode") return # Mode 1: handled by aggregator - logger.debug(f"{self} Processing SpeechStarted in STT mode") await self.start_processing_metrics() await self.broadcast_frame(UserStartedSpeakingFrame) if self._should_interrupt: await self.push_interruption_task_frame_and_wait() self._user_speaking = True - logger.debug(f"{self} _user_speaking set to True") async def _handle_termination(self, message: TerminationMessage): """Handle termination message.""" @@ -730,7 +719,6 @@ class AssemblyAISTTService(WebsocketSTTService): await self._trace_transcription(transcript_text, True, language) await self.stop_processing_metrics() else: - logger.debug(f'{self} Interim transcript: "{transcript_text}"') await self.push_frame( InterimTranscriptionFrame( transcript_text, @@ -744,10 +732,6 @@ class AssemblyAISTTService(WebsocketSTTService): # --- Mode 2: STT turn detection --- # SpeechStarted always arrives before transcripts with u3-rt-pro, # so UserStartedSpeakingFrame is guaranteed to be broadcast first. - logger.debug( - f"{self} Transcript received in STT mode (_user_speaking={self._user_speaking})" - ) - if is_final_turn: # STT mode: AssemblyAI controls finalization, just mark as finalized await self.push_frame( From 32773b42d694cddfd7cbdc1d86743781b47d8d4c Mon Sep 17 00:00:00 2001 From: zack Date: Mon, 2 Mar 2026 18:08:46 -0500 Subject: [PATCH 0766/1060] Improve terminology: rename file and replace 'STT mode' with 'AssemblyAI turn detection' - Rename 07o-interruptible-assemblyai-stt.py -> 07o-interruptible-assemblyai-turn-detection.py - Replace 'STT mode' with 'AssemblyAI turn detection mode' throughout codebase - Replace 'Mode 1'/'Mode 2' with descriptive 'Pipecat turn detection'/'AssemblyAI turn detection' - Update changelog to use 'built-in turn detection' terminology - Addresses PR feedback about confusing terminology --- changelog/3856.added.md | 2 +- ...nterruptible-assemblyai-turn-detection.py} | 14 ++++---- src/pipecat/services/assemblyai/stt.py | 33 ++++++++++--------- 3 files changed, 25 insertions(+), 24 deletions(-) rename examples/foundational/{07o-interruptible-assemblyai-stt.py => 07o-interruptible-assemblyai-turn-detection.py} (93%) diff --git a/changelog/3856.added.md b/changelog/3856.added.md index 95b656058..8074a5281 100644 --- a/changelog/3856.added.md +++ b/changelog/3856.added.md @@ -1 +1 @@ -- Add AssemblyAI u3-rt-pro model support with STT-controlled turn detection mode +- Add AssemblyAI u3-rt-pro model support with built-in turn detection mode diff --git a/examples/foundational/07o-interruptible-assemblyai-stt.py b/examples/foundational/07o-interruptible-assemblyai-turn-detection.py similarity index 93% rename from examples/foundational/07o-interruptible-assemblyai-stt.py rename to examples/foundational/07o-interruptible-assemblyai-turn-detection.py index 01d53914d..cf052ada4 100644 --- a/examples/foundational/07o-interruptible-assemblyai-stt.py +++ b/examples/foundational/07o-interruptible-assemblyai-turn-detection.py @@ -53,20 +53,20 @@ transport_params = { async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): - """AssemblyAI u3-rt-pro STT Example with STT-Controlled Turn Detection + """AssemblyAI u3-rt-pro with Built-in Turn Detection This example demonstrates using AssemblyAI's u3-rt-pro Speech-to-Text model - with STT-controlled turn detection for more natural conversation flow. + with AssemblyAI's built-in turn detection for more natural conversation flow. Key features: - 1. STT-Controlled Turn Detection - - Set `vad_force_turn_endpoint=False` to enable STT mode + 1. AssemblyAI Turn Detection + - Set `vad_force_turn_endpoint=False` to use AssemblyAI's built-in turn detection - AssemblyAI's model determines when user starts/stops speaking - - Uses `ExternalUserTurnStrategies` instead of Pipecat's VAD + - Uses `ExternalUserTurnStrategies` to delegate turn control to AssemblyAI - More natural turn detection based on speech patterns and pauses - 2. Advanced Turn Detection Tuning (STT Mode) + 2. Advanced Turn Detection Tuning - `min_turn_silence`: Minimum silence (ms) when confident about end-of-turn. Lower values = faster responses. Default: 100ms - `max_turn_silence`: Maximum silence (ms) before forcing end-of-turn. @@ -93,7 +93,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): stt = AssemblyAISTTService( api_key=os.getenv("ASSEMBLYAI_API_KEY"), - vad_force_turn_endpoint=False, # Enable STT-controlled turn detection + vad_force_turn_endpoint=False, # Use AssemblyAI's built-in turn detection connection_params=AssemblyAIConnectionParams( speech_model="u3-rt-pro", # Optional: Tune turn detection timing (defaults shown below) diff --git a/src/pipecat/services/assemblyai/stt.py b/src/pipecat/services/assemblyai/stt.py index 2e14b1a66..cccd3d8b0 100644 --- a/src/pipecat/services/assemblyai/stt.py +++ b/src/pipecat/services/assemblyai/stt.py @@ -131,14 +131,15 @@ class AssemblyAISTTService(WebsocketSTTService): - max_turn_silence is ALWAYS set equal to min_turn_silence - VAD stop sends ForceEndpoint as ceiling - No UserStarted/StoppedSpeakingFrame emitted from STT - When False (STT mode, u3-rt-pro only): AssemblyAI's model controls turn endings. + When False (AssemblyAI turn detection mode, u3-rt-pro only): AssemblyAI's model + controls turn endings using built-in turn detection. - Uses AssemblyAI API defaults for all parameters (unless user explicitly sets them) - Respects all user-provided connection_params as-is - Emits UserStarted/StoppedSpeakingFrame from STT - No ForceEndpoint on VAD stop should_interrupt: Whether to interrupt the bot when the user starts speaking - in STT mode (vad_force_turn_endpoint=False). Only applies to STT mode. - Defaults to True. + in AssemblyAI turn detection mode (vad_force_turn_endpoint=False). Only applies + when using AssemblyAI's built-in turn detection. Defaults to True. speaker_format: Optional format string for speaker labels when diarization is enabled. Use {speaker} for speaker label and {text} for transcript text. Example: "<{speaker}>{text}" or "{speaker}: {text}" @@ -147,13 +148,13 @@ class AssemblyAISTTService(WebsocketSTTService): Override for your deployment. See https://github.com/pipecat-ai/stt-benchmark **kwargs: Additional arguments passed to parent STTService class. """ - # STT turn detection (vad_force_turn_endpoint=False) requires the + # AssemblyAI turn detection mode (vad_force_turn_endpoint=False) requires the # SpeechStarted event for reliable barge-in. Only u3-rt-pro supports # this. Other models must use Pipecat turn detection. is_u3_pro = connection_params.speech_model == "u3-rt-pro" if not vad_force_turn_endpoint and not is_u3_pro: raise ValueError( - f"STT turn detection (vad_force_turn_endpoint=False) requires " + f"AssemblyAI turn detection mode (vad_force_turn_endpoint=False) requires " f"u3-rt-pro for SpeechStarted support. Either set " f"vad_force_turn_endpoint=True for {connection_params.speech_model}, " f"or use speech_model='u3-rt-pro'." @@ -256,7 +257,7 @@ class AssemblyAISTTService(WebsocketSTTService): f"OVERRIDDEN in Pipecat mode (vad_force_turn_endpoint=True). It will be set to " f"{min_silence}ms (matching min_turn_silence) and SENT to " f"AssemblyAI to avoid double turn detection. To use your max_turn_silence as-is, " - f"switch to STT mode (vad_force_turn_endpoint=False)." + f"switch to AssemblyAI turn detection mode (vad_force_turn_endpoint=False)." ) updates = { @@ -624,18 +625,18 @@ class AssemblyAISTTService(WebsocketSTTService): await self.push_error(error_msg=f"Unknown error occurred: {e}", exception=e) async def _handle_speech_started(self, message: SpeechStartedMessage): - """Handle SpeechStarted event — fast barge-in for Mode 2. + """Handle SpeechStarted event — fast barge-in for AssemblyAI turn detection. Broadcasts UserStartedSpeakingFrame to signal the start of user speech, then pushes an interruption to cancel any bot audio. SpeechStarted fires before any transcript arrives, so the turn is cleanly started before any transcription frames are pushed. - Only applies to Mode 2 (STT turn detection). In Mode 1, VAD + - smart turn analyzer handle interruptions via the aggregator. + Only applies when using AssemblyAI's built-in turn detection. When using + Pipecat turn detection, VAD + smart turn analyzer handle interruptions. """ if self._vad_force_turn_endpoint: - return # Mode 1: handled by aggregator + return # Pipecat mode: handled by aggregator await self.start_processing_metrics() await self.broadcast_frame(UserStartedSpeakingFrame) @@ -655,15 +656,15 @@ class AssemblyAISTTService(WebsocketSTTService): await self.push_frame(EndFrame()) async def _handle_transcription(self, message: TurnMessage): - """Handle transcription results with two-mode turn detection. + """Handle transcription results with two turn detection modes. - Mode 1 (vad_force_turn_endpoint=True, Pipecat turn detection): + Pipecat turn detection (vad_force_turn_endpoint=True): - No UserStarted/StoppedSpeakingFrame from STT - end_of_turn → TranscriptionFrame (finalized set by base class if this is a ForceEndpoint response) - else → InterimTranscriptionFrame - Mode 2 (vad_force_turn_endpoint=False, STT turn detection): + AssemblyAI turn detection (vad_force_turn_endpoint=False): - UserStartedSpeakingFrame on first transcript - end_of_turn → TranscriptionFrame + UserStoppedSpeakingFrame - else → InterimTranscriptionFrame @@ -700,7 +701,7 @@ class AssemblyAISTTService(WebsocketSTTService): ) if self._vad_force_turn_endpoint: - # --- Mode 1: Pipecat turn detection --- + # --- Pipecat turn detection mode --- # No UserStarted/StoppedSpeakingFrame — VAD + smart turn analyzer handle this if is_final_turn: finalize_confirmed = bool(message.turn_is_formatted) @@ -729,11 +730,11 @@ class AssemblyAISTTService(WebsocketSTTService): ) ) else: - # --- Mode 2: STT turn detection --- + # --- AssemblyAI turn detection mode --- # SpeechStarted always arrives before transcripts with u3-rt-pro, # so UserStartedSpeakingFrame is guaranteed to be broadcast first. if is_final_turn: - # STT mode: AssemblyAI controls finalization, just mark as finalized + # AssemblyAI controls finalization, just mark as finalized await self.push_frame( TranscriptionFrame( transcript_text, From 088eb9b01c0706dcc49769ce9c08a0cbbf49b520 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Aleix=20Conchillo=20Flaqu=C3=A9?= Date: Mon, 2 Mar 2026 15:20:22 -0800 Subject: [PATCH 0767/1060] examples: update to new sagemaker packages --- examples/foundational/07c-interruptible-deepgram-sagemaker.py | 4 ++-- .../55a-update-settings-deepgram-sagemaker-stt.py | 2 +- .../55q-update-settings-deepgram-sagemaker-tts.py | 4 ++-- 3 files changed, 5 insertions(+), 5 deletions(-) diff --git a/examples/foundational/07c-interruptible-deepgram-sagemaker.py b/examples/foundational/07c-interruptible-deepgram-sagemaker.py index aced7666f..7a4cd4297 100644 --- a/examples/foundational/07c-interruptible-deepgram-sagemaker.py +++ b/examples/foundational/07c-interruptible-deepgram-sagemaker.py @@ -23,8 +23,8 @@ from pipecat.processors.aggregators.llm_response_universal import ( from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport from pipecat.services.aws.llm import AWSBedrockLLMService -from pipecat.services.deepgram.stt_sagemaker import DeepgramSageMakerSTTService -from pipecat.services.deepgram.tts_sagemaker import DeepgramSageMakerTTSService +from pipecat.services.deepgram.sagemaker.stt import DeepgramSageMakerSTTService +from pipecat.services.deepgram.sagemaker.tts import DeepgramSageMakerTTSService from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams diff --git a/examples/foundational/55a-update-settings-deepgram-sagemaker-stt.py b/examples/foundational/55a-update-settings-deepgram-sagemaker-stt.py index e8094183a..04451e85c 100644 --- a/examples/foundational/55a-update-settings-deepgram-sagemaker-stt.py +++ b/examples/foundational/55a-update-settings-deepgram-sagemaker-stt.py @@ -24,7 +24,7 @@ from pipecat.processors.aggregators.llm_response_universal import ( from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport from pipecat.services.cartesia.tts import CartesiaTTSService -from pipecat.services.deepgram.stt_sagemaker import ( +from pipecat.services.deepgram.sagemaker.stt import ( DeepgramSageMakerSTTService, DeepgramSageMakerSTTSettings, ) diff --git a/examples/foundational/55q-update-settings-deepgram-sagemaker-tts.py b/examples/foundational/55q-update-settings-deepgram-sagemaker-tts.py index 85087d0d2..14958b9d2 100644 --- a/examples/foundational/55q-update-settings-deepgram-sagemaker-tts.py +++ b/examples/foundational/55q-update-settings-deepgram-sagemaker-tts.py @@ -22,11 +22,11 @@ from pipecat.processors.aggregators.llm_response_universal import ( ) from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport -from pipecat.services.deepgram.stt import DeepgramSTTService -from pipecat.services.deepgram.tts_sagemaker import ( +from pipecat.services.deepgram.sagemaker.tts import ( DeepgramSageMakerTTSService, DeepgramSageMakerTTSSettings, ) +from pipecat.services.deepgram.stt import DeepgramSTTService from pipecat.services.openai.llm import OpenAILLMService from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams From 303616599fffffcab61ac0738f38999e3b0012ef Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Aleix=20Conchillo=20Flaqu=C3=A9?= Date: Mon, 2 Mar 2026 14:48:20 -0800 Subject: [PATCH 0768/1060] Add changelog for #3902 --- changelog/3902.changed.md | 1 + 1 file changed, 1 insertion(+) create mode 100644 changelog/3902.changed.md diff --git a/changelog/3902.changed.md b/changelog/3902.changed.md new file mode 100644 index 000000000..95d3d592c --- /dev/null +++ b/changelog/3902.changed.md @@ -0,0 +1 @@ +- Moved `pipecat.services.deepgram.stt_sagemaker` and `pipecat.services.deepgram.tts_sagemaker` to `pipecat.services.deepgram.sagemaker.stt` and `pipecat.services.deepgram.sagemaker.tts`. The old import paths still work but emit a `DeprecationWarning`. From c6c2c5ba05f66d04c0999037603dc75d07fed476 Mon Sep 17 00:00:00 2001 From: zack Date: Mon, 2 Mar 2026 18:25:25 -0500 Subject: [PATCH 0769/1060] Fix end_of_turn_confidence_threshold: set to 1.0 (not 0.0) for universal-streaming - u3-rt-pro: Does not set parameter (not used) - universal-streaming models: Set to 1.0 to maintain fast response - This ensures fast response time matches previous implementation --- src/pipecat/services/assemblyai/stt.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/src/pipecat/services/assemblyai/stt.py b/src/pipecat/services/assemblyai/stt.py index cccd3d8b0..659fa3b4d 100644 --- a/src/pipecat/services/assemblyai/stt.py +++ b/src/pipecat/services/assemblyai/stt.py @@ -267,7 +267,7 @@ class AssemblyAISTTService(WebsocketSTTService): else: # universal-streaming: Different configuration (works differently) updates = { - "end_of_turn_confidence_threshold": 0.0, + "end_of_turn_confidence_threshold": 1.0, "min_turn_silence": 160, } From 7dbb130666acd5ca9177f4a65b82194d60077b52 Mon Sep 17 00:00:00 2001 From: Mark Backman Date: Mon, 2 Mar 2026 19:23:42 -0500 Subject: [PATCH 0770/1060] Add chronological_events utility function to display UserBotLatencyObserver report --- .../foundational/29-turn-tracking-observer.py | 26 +----- .../observers/user_bot_latency_observer.py | 29 +++++++ tests/test_user_bot_latency_observer.py | 84 ++++++++++++++++++- 3 files changed, 114 insertions(+), 25 deletions(-) diff --git a/examples/foundational/29-turn-tracking-observer.py b/examples/foundational/29-turn-tracking-observer.py index 476dc4612..cf85972e1 100644 --- a/examples/foundational/29-turn-tracking-observer.py +++ b/examples/foundational/29-turn-tracking-observer.py @@ -184,30 +184,8 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): @latency_observer.event_handler("on_latency_breakdown") async def on_latency_breakdown(observer, breakdown): - # Display a sequential waterfall that roughly adds up to the total. - # User turn is the first stage: user silence → turn release. - # The STT TTFB is shown as context within the user turn since - # it's a component of that time (along with VAD silence and any - # turn analyzer delay). - stt_ttfb = next((t for t in breakdown.ttfb if "STT" in t.processor), None) - if breakdown.user_turn_secs is not None: - stt_note = f" (STT: {stt_ttfb.duration_secs:.3f}s)" if stt_ttfb else "" - logger.info(f" User turn: {breakdown.user_turn_secs:.3f}s{stt_note}") - - # Show non-STT TTFBs, inserting function calls after the first - # LLM TTFB (which triggered the calls) for a chronological waterfall. - non_stt = [t for t in breakdown.ttfb if t is not stt_ttfb] - fc_shown = False - for ttfb in non_stt: - logger.info(f" {ttfb.processor}: TTFB {ttfb.duration_secs:.3f}s") - if not fc_shown and breakdown.function_calls: - for fc in breakdown.function_calls: - logger.info(f" {fc.function_name}: {fc.duration_secs:.3f}s") - fc_shown = True - - if breakdown.text_aggregation: - ta = breakdown.text_aggregation - logger.info(f" {ta.processor}: text aggregation {ta.duration_secs:.3f}s") + for event in breakdown.chronological_events(): + logger.info(f" {event}") @transport.event_handler("on_client_connected") async def on_client_connected(transport, client): diff --git a/src/pipecat/observers/user_bot_latency_observer.py b/src/pipecat/observers/user_bot_latency_observer.py index aa0887e30..0672b689c 100644 --- a/src/pipecat/observers/user_bot_latency_observer.py +++ b/src/pipecat/observers/user_bot_latency_observer.py @@ -111,6 +111,35 @@ class LatencyBreakdown(BaseModel): user_turn_secs: Optional[float] = None function_calls: List[FunctionCallMetrics] = Field(default_factory=list) + def chronological_events(self) -> List[str]: + """Return human-readable event labels sorted by start time. + + Collects all sub-metrics into a flat list, sorts by ``start_time``, + and returns formatted strings suitable for logging. + + Returns: + List of formatted strings, one per event, in chronological order. + """ + events: List[tuple] = [] + + if self.user_turn_start_time is not None and self.user_turn_secs is not None: + events.append((self.user_turn_start_time, f"User turn: {self.user_turn_secs:.3f}s")) + + for t in self.ttfb: + events.append((t.start_time, f"{t.processor}: TTFB {t.duration_secs:.3f}s")) + + for fc in self.function_calls: + events.append((fc.start_time, f"{fc.function_name}: {fc.duration_secs:.3f}s")) + + if self.text_aggregation: + ta = self.text_aggregation + events.append( + (ta.start_time, f"{ta.processor}: text aggregation {ta.duration_secs:.3f}s") + ) + + events.sort(key=lambda e: e[0]) + return [label for _, label in events] + class UserBotLatencyObserver(BaseObserver): """Observer that tracks user-to-bot response latency. diff --git a/tests/test_user_bot_latency_observer.py b/tests/test_user_bot_latency_observer.py index 42d5d3367..96c24724b 100644 --- a/tests/test_user_bot_latency_observer.py +++ b/tests/test_user_bot_latency_observer.py @@ -15,7 +15,13 @@ from pipecat.metrics.metrics import ( TextAggregationMetricsData, TTFBMetricsData, ) -from pipecat.observers.user_bot_latency_observer import UserBotLatencyObserver +from pipecat.observers.user_bot_latency_observer import ( + FunctionCallMetrics, + LatencyBreakdown, + TextAggregationBreakdownMetrics, + TTFBBreakdownMetrics, + UserBotLatencyObserver, +) from pipecat.processors.filters.identity_filter import IdentityFilter from pipecat.tests.utils import SleepFrame, run_test @@ -545,5 +551,81 @@ class TestUserBotLatencyObserver(unittest.IsolatedAsyncioTestCase): self.assertEqual(len(breakdowns[0].function_calls), 0) +class TestLatencyBreakdownChronologicalEvents(unittest.TestCase): + """Tests for LatencyBreakdown.chronological_events().""" + + def test_events_sorted_by_start_time(self): + """Test that events are returned in chronological order.""" + breakdown = LatencyBreakdown( + user_turn_start_time=100.0, + user_turn_secs=0.150, + ttfb=[ + TTFBBreakdownMetrics( + processor="OpenAILLMService#0", + model="gpt-4o", + start_time=100.200, + duration_secs=0.250, + ), + TTFBBreakdownMetrics( + processor="DeepgramSTTService#0", + start_time=100.050, + duration_secs=0.080, + ), + TTFBBreakdownMetrics( + processor="CartesiaTTSService#0", + start_time=100.500, + duration_secs=0.070, + ), + ], + function_calls=[ + FunctionCallMetrics( + function_name="get_weather", + start_time=100.450, + duration_secs=0.120, + ), + ], + text_aggregation=TextAggregationBreakdownMetrics( + processor="CartesiaTTSService#0", + start_time=100.480, + duration_secs=0.030, + ), + ) + + events = breakdown.chronological_events() + + self.assertEqual(len(events), 6) + self.assertEqual(events[0], "User turn: 0.150s") + self.assertEqual(events[1], "DeepgramSTTService#0: TTFB 0.080s") + self.assertEqual(events[2], "OpenAILLMService#0: TTFB 0.250s") + self.assertEqual(events[3], "get_weather: 0.120s") + self.assertEqual(events[4], "CartesiaTTSService#0: text aggregation 0.030s") + self.assertEqual(events[5], "CartesiaTTSService#0: TTFB 0.070s") + + def test_empty_breakdown(self): + """Test that an empty breakdown returns no events.""" + breakdown = LatencyBreakdown() + self.assertEqual(breakdown.chronological_events(), []) + + def test_user_turn_requires_both_fields(self): + """Test that user turn is only included when both start_time and secs are set.""" + # Only start_time, no duration + breakdown = LatencyBreakdown(user_turn_start_time=100.0) + self.assertEqual(breakdown.chronological_events(), []) + + # Only duration, no start_time + breakdown = LatencyBreakdown(user_turn_secs=0.150) + self.assertEqual(breakdown.chronological_events(), []) + + def test_ttfb_only(self): + """Test breakdown with only TTFB metrics.""" + breakdown = LatencyBreakdown( + ttfb=[ + TTFBBreakdownMetrics(processor="LLM#0", start_time=100.0, duration_secs=0.200), + ], + ) + events = breakdown.chronological_events() + self.assertEqual(events, ["LLM#0: TTFB 0.200s"]) + + if __name__ == "__main__": unittest.main() From 5952ea711c33750b1fd71985f21ac8f30323f50d Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Aleix=20Conchillo=20Flaqu=C3=A9?= Date: Mon, 2 Mar 2026 16:42:58 -0800 Subject: [PATCH 0771/1060] update uv.lock --- uv.lock | 388 +++++++++++++++++++++++++++++--------------------------- 1 file changed, 198 insertions(+), 190 deletions(-) diff --git a/uv.lock b/uv.lock index c8cba1b1b..70bab79c7 100644 --- a/uv.lock +++ b/uv.lock @@ -1755,11 +1755,11 @@ wheels = [ [[package]] name = "filelock" -version = "3.24.3" +version = "3.25.0" source = { registry = "https://pypi.org/simple" } -sdist = { url = "https://files.pythonhosted.org/packages/73/92/a8e2479937ff39185d20dd6a851c1a63e55849e447a55e798cc2e1f49c65/filelock-3.24.3.tar.gz", hash = "sha256:011a5644dc937c22699943ebbfc46e969cdde3e171470a6e40b9533e5a72affa", size = 37935, upload-time = "2026-02-19T00:48:20.543Z" } +sdist = { url = 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logger.info( - f"Updating max_turn_silence to: {conn_params.max_turn_silence}ms" - ) + logger.info(f"Updating max_turn_silence to: {conn_params.max_turn_silence}ms") if ( old_conn_params is None @@ -355,9 +353,7 @@ class AssemblyAISTTService(WebsocketSTTService): ): if conn_params.min_turn_silence is not None: update_config["min_turn_silence"] = conn_params.min_turn_silence - logger.info( - f"Updating min_turn_silence to: {conn_params.min_turn_silence}ms" - ) + logger.info(f"Updating min_turn_silence to: {conn_params.min_turn_silence}ms") # Send update if we have parameters to update if len(update_config) > 1: # More than just "type" From 252f17e1ca3e35acc35c9e0c6db4499f70d6bb59 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Aleix=20Conchillo=20Flaqu=C3=A9?= Date: Mon, 2 Mar 2026 21:06:49 -0800 Subject: [PATCH 0773/1060] transport(tavus): fix on_joined callback --- src/pipecat/transports/tavus/transport.py | 8 ++++---- 1 file changed, 4 insertions(+), 4 deletions(-) diff --git a/src/pipecat/transports/tavus/transport.py b/src/pipecat/transports/tavus/transport.py index cb6844250..79be070c5 100644 --- a/src/pipecat/transports/tavus/transport.py +++ b/src/pipecat/transports/tavus/transport.py @@ -134,12 +134,12 @@ class TavusCallbacks(BaseModel): """Callback handlers for Tavus events. Parameters: - on_connected: Called when the bot connects to the room. + on_joined: Called when the bot joins the Daily room. on_participant_joined: Called when a participant joins the conversation. on_participant_left: Called when a participant leaves the conversation. """ - on_connected: Callable[[Mapping[str, Any]], Awaitable[None]] + on_joined: Callable[[Mapping[str, Any]], Awaitable[None]] on_participant_joined: Callable[[Mapping[str, Any]], Awaitable[None]] on_participant_left: Callable[[Mapping[str, Any], str], Awaitable[None]] @@ -274,7 +274,7 @@ class TavusTransportClient: async def _on_joined(self, data): """Handle joined event.""" logger.debug("TavusTransportClient joined!") - await self._callbacks.on_connected(data) + await self._callbacks.on_joined(data) async def _on_left(self): """Handle left event.""" @@ -708,7 +708,7 @@ class TavusTransport(BaseTransport): self._params = params callbacks = TavusCallbacks( - on_connected=self._on_joined, + on_joined=self._on_joined, on_participant_joined=self._on_participant_joined, on_participant_left=self._on_participant_left, ) From 62260454a27898126a83374ea43f6cbc251da394 Mon Sep 17 00:00:00 2001 From: aconchillo <951761+aconchillo@users.noreply.github.com> Date: Tue, 3 Mar 2026 05:12:42 +0000 Subject: [PATCH 0774/1060] Update changelog for version 0.0.104 --- CHANGELOG.md | 383 +++++++++++++++++++++++++++++++++ changelog/3696.added.md | 1 - changelog/3696.changed.md | 1 - changelog/3696.deprecated.md | 1 - changelog/3714.added.md | 19 -- changelog/3714.changed.md | 1 - changelog/3714.deprecated.2.md | 1 - changelog/3714.deprecated.md | 3 - changelog/3759.performance.md | 1 - changelog/3764.added.md | 1 - changelog/3786.changed.md | 1 - changelog/3786.deprecated.md | 5 - changelog/3791.added.md | 1 - changelog/3794.fixed.md | 1 - changelog/3795.fixed.md | 1 - changelog/3803.fixed.md | 1 - changelog/3803.removed.md | 1 - changelog/3806.added.md | 1 - changelog/3806.changed.2.md | 1 - changelog/3806.changed.md | 1 - changelog/3807.changed.md | 1 - changelog/3808.fixed.md | 1 - changelog/3809.added.md | 1 - changelog/3809.changed.md | 1 - changelog/3809.deprecated.md | 1 - changelog/3811.changed.md | 1 - changelog/3813.fixed.md | 1 - changelog/3814.added.md | 1 - changelog/3814.fixed.md | 1 - changelog/3819.changed.md | 4 - changelog/3822.fixed.md | 1 - changelog/3825.fixed.md | 1 - changelog/3828.fixed.md | 1 - changelog/3837.fixed.md | 1 - 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2026-03-02 + +### Added + +- Added `TextAggregationMetricsData` metric measuring the time from the first + LLM token to the first complete sentence, representing the latency cost of + sentence aggregation in the TTS pipeline. + (PR [#3696](https://github.com/pipecat-ai/pipecat/pull/3696)) + +- Added support for using strongly-typed objects instead of dicts for updating + service settings at runtime. + + Instead of, say: + + ```python + await task.queue_frame( + STTUpdateSettingsFrame(settings={"language": Language.ES}) + ) + ``` + + you'd do: + + ```python + await task.queue_frame( + STTUpdateSettingsFrame(delta=DeepgramSTTSettings(language=Language.ES)) + ) + ``` + + Each service now vends strongly-typed classes like `DeepgramSTTSettings` + representing the service's runtime-updatable settings. + (PR [#3714](https://github.com/pipecat-ai/pipecat/pull/3714)) + +- Added support for specifying private endpoints for Azure Speech-to-Text, + enabling use in private networks behind firewalls. + (PR [#3764](https://github.com/pipecat-ai/pipecat/pull/3764)) + +- Added `LemonSliceTransport` and `LemonSliceApi` to support adding real-time + LemonSlice Avatars to any Daily room. + (PR [#3791](https://github.com/pipecat-ai/pipecat/pull/3791)) + +- Added `output_medium` parameter to `AgentInputParams` and + `OneShotInputParams` in Ultravox service to control initial output medium + (text or voice) at call creation time. + (PR [#3806](https://github.com/pipecat-ai/pipecat/pull/3806)) + +- Added `TurnMetricsData` as a generic metrics class for turn detection, with + e2e processing time measurement. `KrispVivaTurn` now emits `TurnMetricsData` + with `e2e_processing_time_ms` tracking the interval from VAD + speech-to-silence transition to turn completion. + (PR [#3809](https://github.com/pipecat-ai/pipecat/pull/3809)) + +- Added `on_audio_context_interrupted()` and `on_audio_context_completed()` + callbacks to `AudioContextTTSService`. Subclasses can override these to + perform provider-specific cleanup instead of overriding + `_handle_interruption()`. + (PR [#3814](https://github.com/pipecat-ai/pipecat/pull/3814)) + +- Added `on_summary_applied` event to `LLMContextSummarizer` for observability, + providing message counts before and after context summarization. + (PR [#3855](https://github.com/pipecat-ai/pipecat/pull/3855)) + +- Added `summary_message_template` to `LLMContextSummarizationConfig` for + customizing how summaries are formatted when injected into context (e.g., + wrapping in XML tags). + (PR [#3855](https://github.com/pipecat-ai/pipecat/pull/3855)) + +- Added `summarization_timeout` to `LLMContextSummarizationConfig` (default + 120s) to prevent hung LLM calls from permanently blocking future + summarizations. + (PR [#3855](https://github.com/pipecat-ai/pipecat/pull/3855)) + +- Added optional `llm` field to `LLMContextSummarizationConfig` for routing + summarization to a dedicated LLM service (e.g., a cheaper/faster model) + instead of the pipeline's primary model. + (PR [#3855](https://github.com/pipecat-ai/pipecat/pull/3855)) + +- Add AssemblyAI u3-rt-pro model support with built-in turn detection mode + (PR [#3856](https://github.com/pipecat-ai/pipecat/pull/3856)) + +- Added `LLMSummarizeContextFrame` to trigger on-demand context summarization + from anywhere in the pipeline (e.g. a function call tool). Accepts an + optional `config: LLMContextSummaryConfig` to override summary generation + settings per request. + (PR [#3863](https://github.com/pipecat-ai/pipecat/pull/3863)) + +- Added `LLMContextSummaryConfig` (summary generation params: + `target_context_tokens`, `min_messages_after_summary`, + `summarization_prompt`) and `LLMAutoContextSummarizationConfig` (auto-trigger + thresholds: `max_context_tokens`, `max_unsummarized_messages`, plus a nested + `summary_config`). These replace the monolithic + `LLMContextSummarizationConfig`. + (PR [#3863](https://github.com/pipecat-ai/pipecat/pull/3863)) + +- Added support for the `speed_alpha` parameter to the `arcana` model in + `RimeTTSService`. + (PR [#3873](https://github.com/pipecat-ai/pipecat/pull/3873)) + +- Added `ClientConnectedFrame`, a new `SystemFrame` pushed by all transports + (Daily, LiveKit, FastAPI WebSocket, WebSocket Server, SmallWebRTC, HeyGen, + Tavus) when a client connects. Enables observers to track transport readiness + timing. + (PR [#3881](https://github.com/pipecat-ai/pipecat/pull/3881)) + +- Added `StartupTimingObserver` for measuring how long each processor's + `start()` method takes during pipeline startup. Also measures transport + readiness — the time from `StartFrame` to first client connection — via the + `on_transport_timing_report` event. + (PR [#3881](https://github.com/pipecat-ai/pipecat/pull/3881)) + +- Added `BotConnectedFrame` for SFU transports and `on_transport_timing_report` + event to `StartupTimingObserver` with bot and client connection timing. + (PR [#3881](https://github.com/pipecat-ai/pipecat/pull/3881)) + +- Added optional `direction` parameter to `PipelineTask.queue_frame()` and + `PipelineTask.queue_frames()`, allowing frames to be pushed upstream from the + end of the pipeline. + (PR [#3883](https://github.com/pipecat-ai/pipecat/pull/3883)) + +- Added `on_latency_breakdown` event to `UserBotLatencyObserver` providing + per-service TTFB, text aggregation, user turn duration, and function call + latency metrics for each user-to-bot response cycle. + (PR [#3885](https://github.com/pipecat-ai/pipecat/pull/3885)) + +- Added `on_first_bot_speech_latency` event to `UserBotLatencyObserver` + measuring the time from client connection to first bot speech. An + `on_latency_breakdown` is also emitted for this first speech event. + (PR [#3885](https://github.com/pipecat-ai/pipecat/pull/3885)) + +- Added `broadcast_interruption()` to `FrameProcessor`. This method pushes an + `InterruptionFrame` both upstream and downstream directly from the calling + processor, avoiding the round-trip through the pipeline task that + `push_interruption_task_frame_and_wait()` required. + (PR [#3896](https://github.com/pipecat-ai/pipecat/pull/3896)) + +### Changed + +- Added `text_aggregation_mode` parameter to `TTSService` and all TTS + subclasses with a new `TextAggregationMode` enum (`SENTENCE`, `TOKEN`). All + text now flows through text aggregators regardless of mode, enabling pattern + detection and tag handling in TOKEN mode. + (PR [#3696](https://github.com/pipecat-ai/pipecat/pull/3696)) + +- ⚠️ Refactored runtime-updatable service settings to use strongly-typed + classes (`TTSSettings`, `STTSettings`, `LLMSettings`, and service-specific + subclasses) instead of plain dicts. Each service's `_settings` now holds + these strongly-typed objects. For service maintainers, see changes in + COMMUNITY_INTEGRATIONS.md. + (PR [#3714](https://github.com/pipecat-ai/pipecat/pull/3714)) + +- Word timestamp support has been moved from `WordTTSService` into `TTSService` + via a new `supports_word_timestamps` parameter. Services that previously + extended `WordTTSService`, `AudioContextWordTTSService`, or + `WebsocketWordTTSService` now pass `supports_word_timestamps=True` to their + parent `__init__` instead. + (PR [#3786](https://github.com/pipecat-ai/pipecat/pull/3786)) + +- Improved Ultravox TTFB measurement accuracy by using VAD speech end time + instead of `UserStoppedSpeakingFrame` timing. + (PR [#3806](https://github.com/pipecat-ai/pipecat/pull/3806)) + +- Aligned `UltravoxRealtimeLLMService` frame handling with OpenAI/Gemini + realtime services: added `InterruptionFrame` handling with metrics cleanup, + processing metrics at response boundaries, and improved agent transcript + handling for both voice and text output modalities. + (PR [#3806](https://github.com/pipecat-ai/pipecat/pull/3806)) + +- Updated `OpenAIRealtimeLLMService` default model to `gpt-realtime-1.5`. + (PR [#3807](https://github.com/pipecat-ai/pipecat/pull/3807)) + +- Added `api_key` parameter to `KrispVivaSDKManager`, `KrispVivaTurn`, and + `KrispVivaFilter` for Krisp SDK v1.6.1+ licensing. Falls back to + `KRISP_VIVA_API_KEY` environment variable. + (PR [#3809](https://github.com/pipecat-ai/pipecat/pull/3809)) + +- Bumped `nltk` minimum version from 3.9.1 to 3.9.3 to resolve a security + vulnerability. + (PR [#3811](https://github.com/pipecat-ai/pipecat/pull/3811)) + +- `ServiceSettingsUpdateFrame`s are now `UninterruptibleFrame`s. Generally + speaking, you don't want a user interruption to prevent a service setting + change from going into effect. Note that you usually don't use + `ServiceSettingsUpdateFrame` directly, you use one of its subclasses: + - `LLMUpdateSettingsFrame` + - `TTSUpdateSettingsFrame` + - `STTUpdateSettingsFrame` + (PR [#3819](https://github.com/pipecat-ai/pipecat/pull/3819)) + +- Updated context summarization to use `user` role instead of `assistant` for + summary messages. + (PR [#3855](https://github.com/pipecat-ai/pipecat/pull/3855)) + +- Rename `AssemblyAISTTService` parameter + `min_end_of_turn_silence_when_confident` parameter to `min_turn_silence` (old + name still supported with deprecation warning) + (PR [#3856](https://github.com/pipecat-ai/pipecat/pull/3856)) + +- ⚠️ Renamed `LLMAssistantAggregatorParams` fields: + `enable_context_summarization` → `enable_auto_context_summarization` and + `context_summarization_config` → `auto_context_summarization_config` (now + accepts `LLMAutoContextSummarizationConfig`). The old names still work with a + `DeprecationWarning` for one release cycle. + (PR [#3863](https://github.com/pipecat-ai/pipecat/pull/3863)) + +- `ElevenLabsRealtimeSTTService` now sets `TranscriptionFrame.finalized` to + `True` when using `CommitStrategy.MANUAL`. + (PR [#3865](https://github.com/pipecat-ai/pipecat/pull/3865)) + +- Updated numba version pin from == to >=0.61.2 + (PR [#3868](https://github.com/pipecat-ai/pipecat/pull/3868)) + +- Updated tracing code to use `ServiceSettings` dataclass API + (`given_fields()`, attribute access) instead of dict-style access + (`.items()`, `in`, subscript). + (PR [#3879](https://github.com/pipecat-ai/pipecat/pull/3879)) + +- ⚠️ Removed `event` field and `complete()` method from `InterruptionFrame`. + Removed `event` field from `InterruptionTaskFrame`. These are no longer + needed since `broadcast_interruption()` does not require a round-trip + completion signal. + (PR [#3896](https://github.com/pipecat-ai/pipecat/pull/3896)) + +- Moved `pipecat.services.deepgram.stt_sagemaker` and + `pipecat.services.deepgram.tts_sagemaker` to + `pipecat.services.deepgram.sagemaker.stt` and + `pipecat.services.deepgram.sagemaker.tts`. The old import paths still work + but emit a `DeprecationWarning`. + (PR [#3902](https://github.com/pipecat-ai/pipecat/pull/3902)) + +### Deprecated + +- ⚠️ Deprecated `aggregate_sentences` parameter on `TTSService` and all TTS + subclasses. Use `text_aggregation_mode=TextAggregationMode.SENTENCE` or + `text_aggregation_mode=TextAggregationMode.TOKEN` instead. + (PR [#3696](https://github.com/pipecat-ai/pipecat/pull/3696)) + +- Deprecated `set_model()`, `set_voice()`, and `set_language()` on AI services + in favor of runtime updates via `TTSUpdateSettingsFrame`, + `STTUpdateSettingsFrame`, and `LLMUpdateSettingsFrame`. + + ⚠️ Note, too, a subtle behavior change in these deprecated methods. Whereas + previously only `set_language()` caused the service to actually react to the + update (e.g. by reconnecting to a remote service so it an pick up the + change), now all these methods do. This change was made as part of a refactor + making them all work the same way under the hood. + (PR [#3714](https://github.com/pipecat-ai/pipecat/pull/3714)) + +- Dict-based `*UpdateSettingsFrame(settings={...})` is deprecated in favor of + passing typed settings delta objects with + `*UpdateSettingsFrame(delta={...})`. + (PR [#3714](https://github.com/pipecat-ai/pipecat/pull/3714)) + +- Deprecated `WordTTSService`, `WebsocketWordTTSService`, + `AudioContextWordTTSService`, and `InterruptibleWordTTSService`. Use their + non-word counterparts with `supports_word_timestamps=True` instead: + - `WordTTSService` → `TTSService(supports_word_timestamps=True)` + - `WebsocketWordTTSService` → + `WebsocketTTSService(supports_word_timestamps=True)` + - `AudioContextWordTTSService` → + `AudioContextTTSService(supports_word_timestamps=True)` + - `InterruptibleWordTTSService` → + `InterruptibleTTSService(supports_word_timestamps=True)` + (PR [#3786](https://github.com/pipecat-ai/pipecat/pull/3786)) + +- Deprecated `SmartTurnMetricsData` in favor of `TurnMetricsData`. + `BaseSmartTurn` now emits `TurnMetricsData` directly. + (PR [#3809](https://github.com/pipecat-ai/pipecat/pull/3809)) + +- Deprecated `LLMContextSummarizationConfig`. Use + `LLMAutoContextSummarizationConfig` with a nested `LLMContextSummaryConfig` + instead. The old class emits a `DeprecationWarning`. + (PR [#3863](https://github.com/pipecat-ai/pipecat/pull/3863)) + +- Deprecated `push_interruption_task_frame_and_wait()` in `FrameProcessor`. Use + `broadcast_interruption()` instead. The old method now delegates to + `broadcast_interruption()` and logs a deprecation warning. + (PR [#3896](https://github.com/pipecat-ai/pipecat/pull/3896)) + +### Removed + +- Removed `local-smart-turn-v3` optional extra from `pyproject.toml`. The + `transformers` and `onnxruntime` packages are now always installed as core + dependencies since they are required by the default turn stop strategy, + `TurnAnalyzerUserTurnStopStrategy` which uses `LocalSmartTurnAnalyzerV3`. + (PR [#3803](https://github.com/pipecat-ai/pipecat/pull/3803)) + +- ⚠️ Removed `PlayHTTTSService` and `PlayHTHttpTTSService`. PlayHT has been + shut down and is no longer available. + (PR [#3838](https://github.com/pipecat-ai/pipecat/pull/3838)) + +### Fixed + +- Added `LLMSpecificMessage` handling in `LLMContextSummarizationUtil` to skip + provider-specific messages during context summarization. + (PR [#3794](https://github.com/pipecat-ai/pipecat/pull/3794)) + +- Treated `response_cancel_not_active` as a non-fatal error in realtime + services (`OpenAIRealtimeLLMService`, `GrokRealtimeLLMService`, + `OpenAIRealtimeBetaLLMService`) to prevent WebSocket disconnection when + cancelling an inactive response. + (PR [#3795](https://github.com/pipecat-ai/pipecat/pull/3795)) + +- Fixed Poetry compatibility by inlining `local-smart-turn-v3` dependencies + (`transformers`, `onnxruntime`) into core dependencies instead of using a + self-referential extra. + (PR [#3803](https://github.com/pipecat-ai/pipecat/pull/3803)) + +- Fixed `SentryMetrics` method signatures to match updated + `FrameProcessorMetrics` base class, resolving `TypeError` when using + `start_time`/`end_time` keyword arguments. + (PR [#3808](https://github.com/pipecat-ai/pipecat/pull/3808)) + +- Fixed STT TTFB metrics not being reported for `SonioxSTTService` and + `AWSTranscribeSTTService` due to missing `can_generate_metrics()` override. + (PR [#3813](https://github.com/pipecat-ai/pipecat/pull/3813)) + +- Fixed an issue where `AudioContextTTSService`-based providers (AsyncAI, + ElevenLabs, Inworld, Rime) did not close or clean up their server-side audio + contexts after normal speech completion, only on interruption. + (PR [#3814](https://github.com/pipecat-ai/pipecat/pull/3814)) + +- Fixed STT TTFB metrics measuring timeout expiry time instead of actual + transcript arrival time. + (PR [#3822](https://github.com/pipecat-ai/pipecat/pull/3822)) + +- Fixed `InterimTranscriptionFrame` and `TranslationFrame` being + unintentionally pushed downstream in `LLMUserAggregator`. They are now + consumed like `TranscriptionFrame`. + (PR [#3825](https://github.com/pipecat-ai/pipecat/pull/3825)) + +- Fixed misleading "Empty audio frame received for STT service" warnings when + using audio filters (e.g. `RNNoiseFilter`, `KrispVivaFilter`, `AICFilter`) + that buffer audio internally. + (PR [#3828](https://github.com/pipecat-ai/pipecat/pull/3828)) + +- Fixed issues with `RimeNonJsonTTSService` where trailing punctuation is + sometimes vocalized + (PR [#3837](https://github.com/pipecat-ai/pipecat/pull/3837)) + +- Fixed `TTSSpeakFrame` not committing spoken text to the conversation context + when used outside of an LLM response (e.g., bot greetings or injected + speech). + (PR [#3845](https://github.com/pipecat-ai/pipecat/pull/3845)) + +- Removed verbose per-chunk audio logging from `GenesysAudioHookSerializer` + that flooded production logs. + (PR [#3850](https://github.com/pipecat-ai/pipecat/pull/3850)) + +- Add beta feature warning when using custom prompts with AssemblyAI + (PR [#3856](https://github.com/pipecat-ai/pipecat/pull/3856)) + +- Fixed `LocalSmartTurnAnalyzerV3` producing incorrect end-of-turn predictions + at non-16kHz sample rates (e.g. 8kHz Twilio telephony) by adding automatic + resampling to 16kHz before Whisper feature extraction. + (PR [#3857](https://github.com/pipecat-ai/pipecat/pull/3857)) + +- Fixed `PipelineTask` double-inserting `RTVIProcessor` into the frame chain + when the user provides both an `RTVIProcessor` in the pipeline and a custom + `RTVIObserver` subclass in observers. + (PR [#3867](https://github.com/pipecat-ai/pipecat/pull/3867)) + +- Fixed turn completion instructions being lost when `LLMMessagesUpdateFrame` + replaces the LLM context. When `filter_incomplete_user_turns` is enabled, the + turn completion system message is now re-injected after context replacement. + (PR [#3888](https://github.com/pipecat-ai/pipecat/pull/3888)) + +- Fixed Azure TTS and STT services silently swallowing cancellation errors + (invalid API key, network failures, rate limiting) instead of propagating + them as `ErrorFrame`s to the pipeline. + (PR [#3893](https://github.com/pipecat-ai/pipecat/pull/3893)) + +### Performance + +- Switched `GradiumTTSService` from `InterruptibleWordTTSService` to + `AudioContextWordTTSService`, eliminating websocket disconnect/reconnect on + every interruption by using `client_req_id`-based multiplexing. + (PR [#3759](https://github.com/pipecat-ai/pipecat/pull/3759)) + +### Other + +- Standardized Sarvam STT/TTS User-Agent header handling to consistently send + Pipecat SDK identity in websocket requests. + (PR [#3886](https://github.com/pipecat-ai/pipecat/pull/3886)) + ## [0.0.103] - 2026-02-20 ### Added diff --git a/changelog/3696.added.md b/changelog/3696.added.md deleted file mode 100644 index 39726d930..000000000 --- a/changelog/3696.added.md +++ /dev/null @@ -1 +0,0 @@ -- Added `TextAggregationMetricsData` metric measuring the time from the first LLM token to the first complete sentence, representing the latency cost of sentence aggregation in the TTS pipeline. diff --git a/changelog/3696.changed.md b/changelog/3696.changed.md deleted file mode 100644 index a495560ba..000000000 --- a/changelog/3696.changed.md +++ /dev/null @@ -1 +0,0 @@ -- Added `text_aggregation_mode` parameter to `TTSService` and all TTS subclasses with a new `TextAggregationMode` enum (`SENTENCE`, `TOKEN`). All text now flows through text aggregators regardless of mode, enabling pattern detection and tag handling in TOKEN mode. diff --git a/changelog/3696.deprecated.md b/changelog/3696.deprecated.md deleted file mode 100644 index 7b371fc21..000000000 --- a/changelog/3696.deprecated.md +++ /dev/null @@ -1 +0,0 @@ -- ⚠️ Deprecated `aggregate_sentences` parameter on `TTSService` and all TTS subclasses. Use `text_aggregation_mode=TextAggregationMode.SENTENCE` or `text_aggregation_mode=TextAggregationMode.TOKEN` instead. diff --git a/changelog/3714.added.md b/changelog/3714.added.md deleted file mode 100644 index efa54b7d5..000000000 --- a/changelog/3714.added.md +++ /dev/null @@ -1,19 +0,0 @@ -- Added support for using strongly-typed objects instead of dicts for updating service settings at runtime. - - Instead of, say: - - ```python - await task.queue_frame( - STTUpdateSettingsFrame(settings={"language": Language.ES}) - ) - ``` - - you'd do: - - ```python - await task.queue_frame( - STTUpdateSettingsFrame(delta=DeepgramSTTSettings(language=Language.ES)) - ) - ``` - - Each service now vends strongly-typed classes like `DeepgramSTTSettings` representing the service's runtime-updatable settings. diff --git a/changelog/3714.changed.md b/changelog/3714.changed.md deleted file mode 100644 index bcfb5cbf7..000000000 --- a/changelog/3714.changed.md +++ /dev/null @@ -1 +0,0 @@ -- ⚠️ Refactored runtime-updatable service settings to use strongly-typed classes (`TTSSettings`, `STTSettings`, `LLMSettings`, and service-specific subclasses) instead of plain dicts. Each service's `_settings` now holds these strongly-typed objects. For service maintainers, see changes in COMMUNITY_INTEGRATIONS.md. diff --git a/changelog/3714.deprecated.2.md b/changelog/3714.deprecated.2.md deleted file mode 100644 index d386fa5a4..000000000 --- a/changelog/3714.deprecated.2.md +++ /dev/null @@ -1 +0,0 @@ -- Dict-based `*UpdateSettingsFrame(settings={...})` is deprecated in favor of passing typed settings delta objects with `*UpdateSettingsFrame(delta={...})`. diff --git a/changelog/3714.deprecated.md b/changelog/3714.deprecated.md deleted file mode 100644 index 75337a642..000000000 --- a/changelog/3714.deprecated.md +++ /dev/null @@ -1,3 +0,0 @@ -- Deprecated `set_model()`, `set_voice()`, and `set_language()` on AI services in favor of runtime updates via `TTSUpdateSettingsFrame`, `STTUpdateSettingsFrame`, and `LLMUpdateSettingsFrame`. - - ⚠️ Note, too, a subtle behavior change in these deprecated methods. Whereas previously only `set_language()` caused the service to actually react to the update (e.g. by reconnecting to a remote service so it an pick up the change), now all these methods do. This change was made as part of a refactor making them all work the same way under the hood. diff --git a/changelog/3759.performance.md b/changelog/3759.performance.md deleted file mode 100644 index 1bdc17a17..000000000 --- a/changelog/3759.performance.md +++ /dev/null @@ -1 +0,0 @@ -- Switched `GradiumTTSService` from `InterruptibleWordTTSService` to `AudioContextWordTTSService`, eliminating websocket disconnect/reconnect on every interruption by using `client_req_id`-based multiplexing. diff --git a/changelog/3764.added.md b/changelog/3764.added.md deleted file mode 100644 index 5da82f0c1..000000000 --- a/changelog/3764.added.md +++ /dev/null @@ -1 +0,0 @@ -- Added support for specifying private endpoints for Azure Speech-to-Text, enabling use in private networks behind firewalls. \ No newline at end of file diff --git a/changelog/3786.changed.md b/changelog/3786.changed.md deleted file mode 100644 index ed8e7e444..000000000 --- a/changelog/3786.changed.md +++ /dev/null @@ -1 +0,0 @@ -- Word timestamp support has been moved from `WordTTSService` into `TTSService` via a new `supports_word_timestamps` parameter. Services that previously extended `WordTTSService`, `AudioContextWordTTSService`, or `WebsocketWordTTSService` now pass `supports_word_timestamps=True` to their parent `__init__` instead. diff --git a/changelog/3786.deprecated.md b/changelog/3786.deprecated.md deleted file mode 100644 index 7ac5a5b9c..000000000 --- a/changelog/3786.deprecated.md +++ /dev/null @@ -1,5 +0,0 @@ -- Deprecated `WordTTSService`, `WebsocketWordTTSService`, `AudioContextWordTTSService`, and `InterruptibleWordTTSService`. Use their non-word counterparts with `supports_word_timestamps=True` instead: - - `WordTTSService` → `TTSService(supports_word_timestamps=True)` - - `WebsocketWordTTSService` → `WebsocketTTSService(supports_word_timestamps=True)` - - `AudioContextWordTTSService` → `AudioContextTTSService(supports_word_timestamps=True)` - - `InterruptibleWordTTSService` → `InterruptibleTTSService(supports_word_timestamps=True)` diff --git a/changelog/3791.added.md b/changelog/3791.added.md deleted file mode 100644 index 89767de5e..000000000 --- a/changelog/3791.added.md +++ /dev/null @@ -1 +0,0 @@ -- Added `LemonSliceTransport` and `LemonSliceApi` to support adding real-time LemonSlice Avatars to any Daily room. \ No newline at end of file diff --git a/changelog/3794.fixed.md b/changelog/3794.fixed.md deleted file mode 100644 index e2b3c7c00..000000000 --- a/changelog/3794.fixed.md +++ /dev/null @@ -1 +0,0 @@ -- Added `LLMSpecificMessage` handling in `LLMContextSummarizationUtil` to skip provider-specific messages during context summarization. diff --git a/changelog/3795.fixed.md b/changelog/3795.fixed.md deleted file mode 100644 index 8c231abac..000000000 --- a/changelog/3795.fixed.md +++ /dev/null @@ -1 +0,0 @@ -- Treated `response_cancel_not_active` as a non-fatal error in realtime services (`OpenAIRealtimeLLMService`, `GrokRealtimeLLMService`, `OpenAIRealtimeBetaLLMService`) to prevent WebSocket disconnection when cancelling an inactive response. \ No newline at end of file diff --git a/changelog/3803.fixed.md b/changelog/3803.fixed.md deleted file mode 100644 index 73d7c3f19..000000000 --- a/changelog/3803.fixed.md +++ /dev/null @@ -1 +0,0 @@ -- Fixed Poetry compatibility by inlining `local-smart-turn-v3` dependencies (`transformers`, `onnxruntime`) into core dependencies instead of using a self-referential extra. diff --git a/changelog/3803.removed.md b/changelog/3803.removed.md deleted file mode 100644 index 867c3cfcc..000000000 --- a/changelog/3803.removed.md +++ /dev/null @@ -1 +0,0 @@ -- Removed `local-smart-turn-v3` optional extra from `pyproject.toml`. The `transformers` and `onnxruntime` packages are now always installed as core dependencies since they are required by the default turn stop strategy, `TurnAnalyzerUserTurnStopStrategy` which uses `LocalSmartTurnAnalyzerV3`. diff --git a/changelog/3806.added.md b/changelog/3806.added.md deleted file mode 100644 index eeddc9825..000000000 --- a/changelog/3806.added.md +++ /dev/null @@ -1 +0,0 @@ -- Added `output_medium` parameter to `AgentInputParams` and `OneShotInputParams` in Ultravox service to control initial output medium (text or voice) at call creation time. diff --git a/changelog/3806.changed.2.md b/changelog/3806.changed.2.md deleted file mode 100644 index 9d6dfdf76..000000000 --- a/changelog/3806.changed.2.md +++ /dev/null @@ -1 +0,0 @@ -- Improved Ultravox TTFB measurement accuracy by using VAD speech end time instead of `UserStoppedSpeakingFrame` timing. diff --git a/changelog/3806.changed.md b/changelog/3806.changed.md deleted file mode 100644 index c8e2fb68c..000000000 --- a/changelog/3806.changed.md +++ /dev/null @@ -1 +0,0 @@ -- Aligned `UltravoxRealtimeLLMService` frame handling with OpenAI/Gemini realtime services: added `InterruptionFrame` handling with metrics cleanup, processing metrics at response boundaries, and improved agent transcript handling for both voice and text output modalities. diff --git a/changelog/3807.changed.md b/changelog/3807.changed.md deleted file mode 100644 index cc99f29fb..000000000 --- a/changelog/3807.changed.md +++ /dev/null @@ -1 +0,0 @@ -- Updated `OpenAIRealtimeLLMService` default model to `gpt-realtime-1.5`. \ No newline at end of file diff --git a/changelog/3808.fixed.md b/changelog/3808.fixed.md deleted file mode 100644 index 6bf105bf6..000000000 --- a/changelog/3808.fixed.md +++ /dev/null @@ -1 +0,0 @@ -- Fixed `SentryMetrics` method signatures to match updated `FrameProcessorMetrics` base class, resolving `TypeError` when using `start_time`/`end_time` keyword arguments. diff --git a/changelog/3809.added.md b/changelog/3809.added.md deleted file mode 100644 index 99047dc76..000000000 --- a/changelog/3809.added.md +++ /dev/null @@ -1 +0,0 @@ -- Added `TurnMetricsData` as a generic metrics class for turn detection, with e2e processing time measurement. `KrispVivaTurn` now emits `TurnMetricsData` with `e2e_processing_time_ms` tracking the interval from VAD speech-to-silence transition to turn completion. diff --git a/changelog/3809.changed.md b/changelog/3809.changed.md deleted file mode 100644 index 479eaf6ed..000000000 --- a/changelog/3809.changed.md +++ /dev/null @@ -1 +0,0 @@ -- Added `api_key` parameter to `KrispVivaSDKManager`, `KrispVivaTurn`, and `KrispVivaFilter` for Krisp SDK v1.6.1+ licensing. Falls back to `KRISP_VIVA_API_KEY` environment variable. diff --git a/changelog/3809.deprecated.md b/changelog/3809.deprecated.md deleted file mode 100644 index f1498ec0b..000000000 --- a/changelog/3809.deprecated.md +++ /dev/null @@ -1 +0,0 @@ -- Deprecated `SmartTurnMetricsData` in favor of `TurnMetricsData`. `BaseSmartTurn` now emits `TurnMetricsData` directly. diff --git a/changelog/3811.changed.md b/changelog/3811.changed.md deleted file mode 100644 index eb3eb492e..000000000 --- a/changelog/3811.changed.md +++ /dev/null @@ -1 +0,0 @@ -- Bumped `nltk` minimum version from 3.9.1 to 3.9.3 to resolve a security vulnerability. diff --git a/changelog/3813.fixed.md b/changelog/3813.fixed.md deleted file mode 100644 index 9d9115e77..000000000 --- a/changelog/3813.fixed.md +++ /dev/null @@ -1 +0,0 @@ -- Fixed STT TTFB metrics not being reported for `SonioxSTTService` and `AWSTranscribeSTTService` due to missing `can_generate_metrics()` override. diff --git a/changelog/3814.added.md b/changelog/3814.added.md deleted file mode 100644 index b6b2ebbf8..000000000 --- a/changelog/3814.added.md +++ /dev/null @@ -1 +0,0 @@ -- Added `on_audio_context_interrupted()` and `on_audio_context_completed()` callbacks to `AudioContextTTSService`. Subclasses can override these to perform provider-specific cleanup instead of overriding `_handle_interruption()`. diff --git a/changelog/3814.fixed.md b/changelog/3814.fixed.md deleted file mode 100644 index ecd4871f6..000000000 --- a/changelog/3814.fixed.md +++ /dev/null @@ -1 +0,0 @@ -- Fixed an issue where `AudioContextTTSService`-based providers (AsyncAI, ElevenLabs, Inworld, Rime) did not close or clean up their server-side audio contexts after normal speech completion, only on interruption. diff --git a/changelog/3819.changed.md b/changelog/3819.changed.md deleted file mode 100644 index 7b43c399c..000000000 --- a/changelog/3819.changed.md +++ /dev/null @@ -1,4 +0,0 @@ -- `ServiceSettingsUpdateFrame`s are now `UninterruptibleFrame`s. Generally speaking, you don't want a user interruption to prevent a service setting change from going into effect. Note that you usually don't use `ServiceSettingsUpdateFrame` directly, you use one of its subclasses: - - `LLMUpdateSettingsFrame` - - `TTSUpdateSettingsFrame` - - `STTUpdateSettingsFrame` diff --git a/changelog/3822.fixed.md b/changelog/3822.fixed.md deleted file mode 100644 index 48218845f..000000000 --- a/changelog/3822.fixed.md +++ /dev/null @@ -1 +0,0 @@ -- Fixed STT TTFB metrics measuring timeout expiry time instead of actual transcript arrival time. \ No newline at end of file diff --git a/changelog/3825.fixed.md b/changelog/3825.fixed.md deleted file mode 100644 index 7cd9ba508..000000000 --- a/changelog/3825.fixed.md +++ /dev/null @@ -1 +0,0 @@ -- Fixed `InterimTranscriptionFrame` and `TranslationFrame` being unintentionally pushed downstream in `LLMUserAggregator`. They are now consumed like `TranscriptionFrame`. diff --git a/changelog/3828.fixed.md b/changelog/3828.fixed.md deleted file mode 100644 index dd2ee257d..000000000 --- a/changelog/3828.fixed.md +++ /dev/null @@ -1 +0,0 @@ -- Fixed misleading "Empty audio frame received for STT service" warnings when using audio filters (e.g. `RNNoiseFilter`, `KrispVivaFilter`, `AICFilter`) that buffer audio internally. diff --git a/changelog/3837.fixed.md b/changelog/3837.fixed.md deleted file mode 100644 index 767e79f45..000000000 --- a/changelog/3837.fixed.md +++ /dev/null @@ -1 +0,0 @@ -- Fixed issues with `RimeNonJsonTTSService` where trailing punctuation is sometimes vocalized diff --git a/changelog/3838.removed.md b/changelog/3838.removed.md deleted file mode 100644 index fa811cb71..000000000 --- a/changelog/3838.removed.md +++ /dev/null @@ -1 +0,0 @@ -- ⚠️ Removed `PlayHTTTSService` and `PlayHTHttpTTSService`. PlayHT has been shut down and is no longer available. diff --git a/changelog/3845.fixed.md b/changelog/3845.fixed.md deleted file mode 100644 index 423853700..000000000 --- a/changelog/3845.fixed.md +++ /dev/null @@ -1 +0,0 @@ -- Fixed `TTSSpeakFrame` not committing spoken text to the conversation context when used outside of an LLM response (e.g., bot greetings or injected speech). \ No newline at end of file diff --git a/changelog/3850.fixed.md b/changelog/3850.fixed.md deleted file mode 100644 index cfbdc6cf7..000000000 --- a/changelog/3850.fixed.md +++ /dev/null @@ -1 +0,0 @@ -- Removed verbose per-chunk audio logging from `GenesysAudioHookSerializer` that flooded production logs. diff --git a/changelog/3855.added.2.md b/changelog/3855.added.2.md deleted file mode 100644 index 01cd23efe..000000000 --- a/changelog/3855.added.2.md +++ /dev/null @@ -1 +0,0 @@ -- Added optional `llm` field to `LLMContextSummarizationConfig` for routing summarization to a dedicated LLM service (e.g., a cheaper/faster model) instead of the pipeline's primary model. diff --git a/changelog/3855.added.3.md b/changelog/3855.added.3.md deleted file mode 100644 index b93fdec60..000000000 --- a/changelog/3855.added.3.md +++ /dev/null @@ -1 +0,0 @@ -- Added `summarization_timeout` to `LLMContextSummarizationConfig` (default 120s) to prevent hung LLM calls from permanently blocking future summarizations. diff --git a/changelog/3855.added.4.md b/changelog/3855.added.4.md deleted file mode 100644 index b712b4ac9..000000000 --- a/changelog/3855.added.4.md +++ /dev/null @@ -1 +0,0 @@ -- Added `on_summary_applied` event to `LLMContextSummarizer` for observability, providing message counts before and after context summarization. diff --git a/changelog/3855.added.md b/changelog/3855.added.md deleted file mode 100644 index 79d37eeba..000000000 --- a/changelog/3855.added.md +++ /dev/null @@ -1 +0,0 @@ -- Added `summary_message_template` to `LLMContextSummarizationConfig` for customizing how summaries are formatted when injected into context (e.g., wrapping in XML tags). diff --git a/changelog/3855.changed.md b/changelog/3855.changed.md deleted file mode 100644 index 2eac6785a..000000000 --- a/changelog/3855.changed.md +++ /dev/null @@ -1 +0,0 @@ -- Updated context summarization to use `user` role instead of `assistant` for summary messages. diff --git a/changelog/3856.added.md b/changelog/3856.added.md deleted file mode 100644 index 8074a5281..000000000 --- a/changelog/3856.added.md +++ /dev/null @@ -1 +0,0 @@ -- Add AssemblyAI u3-rt-pro model support with built-in turn detection mode diff --git a/changelog/3856.changed.md b/changelog/3856.changed.md deleted file mode 100644 index 1e7f4c916..000000000 --- a/changelog/3856.changed.md +++ /dev/null @@ -1 +0,0 @@ -- Rename `AssemblyAISTTService` parameter `min_end_of_turn_silence_when_confident` parameter to `min_turn_silence` (old name still supported with deprecation warning) diff --git a/changelog/3856.fixed.md b/changelog/3856.fixed.md deleted file mode 100644 index c31fe8ddf..000000000 --- a/changelog/3856.fixed.md +++ /dev/null @@ -1 +0,0 @@ -- Add beta feature warning when using custom prompts with AssemblyAI diff --git a/changelog/3857.fixed.md b/changelog/3857.fixed.md deleted file mode 100644 index 869c54111..000000000 --- a/changelog/3857.fixed.md +++ /dev/null @@ -1 +0,0 @@ -- Fixed `LocalSmartTurnAnalyzerV3` producing incorrect end-of-turn predictions at non-16kHz sample rates (e.g. 8kHz Twilio telephony) by adding automatic resampling to 16kHz before Whisper feature extraction. diff --git a/changelog/3863.added.2.md b/changelog/3863.added.2.md deleted file mode 100644 index 9c0ab90ba..000000000 --- a/changelog/3863.added.2.md +++ /dev/null @@ -1 +0,0 @@ -- Added `LLMContextSummaryConfig` (summary generation params: `target_context_tokens`, `min_messages_after_summary`, `summarization_prompt`) and `LLMAutoContextSummarizationConfig` (auto-trigger thresholds: `max_context_tokens`, `max_unsummarized_messages`, plus a nested `summary_config`). These replace the monolithic `LLMContextSummarizationConfig`. diff --git a/changelog/3863.added.md b/changelog/3863.added.md deleted file mode 100644 index d6214aed0..000000000 --- a/changelog/3863.added.md +++ /dev/null @@ -1 +0,0 @@ -- Added `LLMSummarizeContextFrame` to trigger on-demand context summarization from anywhere in the pipeline (e.g. a function call tool). Accepts an optional `config: LLMContextSummaryConfig` to override summary generation settings per request. diff --git a/changelog/3863.changed.md b/changelog/3863.changed.md deleted file mode 100644 index faf5712d8..000000000 --- a/changelog/3863.changed.md +++ /dev/null @@ -1 +0,0 @@ -- ⚠️ Renamed `LLMAssistantAggregatorParams` fields: `enable_context_summarization` → `enable_auto_context_summarization` and `context_summarization_config` → `auto_context_summarization_config` (now accepts `LLMAutoContextSummarizationConfig`). The old names still work with a `DeprecationWarning` for one release cycle. diff --git a/changelog/3863.deprecated.md b/changelog/3863.deprecated.md deleted file mode 100644 index ba2311fbd..000000000 --- a/changelog/3863.deprecated.md +++ /dev/null @@ -1 +0,0 @@ -- Deprecated `LLMContextSummarizationConfig`. Use `LLMAutoContextSummarizationConfig` with a nested `LLMContextSummaryConfig` instead. The old class emits a `DeprecationWarning`. diff --git a/changelog/3865.changed.md b/changelog/3865.changed.md deleted file mode 100644 index 7a70eb0d7..000000000 --- a/changelog/3865.changed.md +++ /dev/null @@ -1 +0,0 @@ -- `ElevenLabsRealtimeSTTService` now sets `TranscriptionFrame.finalized` to `True` when using `CommitStrategy.MANUAL`. diff --git a/changelog/3867.fixed.md b/changelog/3867.fixed.md deleted file mode 100644 index 41ee584a2..000000000 --- a/changelog/3867.fixed.md +++ /dev/null @@ -1 +0,0 @@ -- Fixed `PipelineTask` double-inserting `RTVIProcessor` into the frame chain when the user provides both an `RTVIProcessor` in the pipeline and a custom `RTVIObserver` subclass in observers. diff --git a/changelog/3868.changed.md b/changelog/3868.changed.md deleted file mode 100644 index 4f019cca2..000000000 --- a/changelog/3868.changed.md +++ /dev/null @@ -1 +0,0 @@ -- Updated numba version pin from == to >=0.61.2 diff --git a/changelog/3873.added.md b/changelog/3873.added.md deleted file mode 100644 index ed01b8e5d..000000000 --- a/changelog/3873.added.md +++ /dev/null @@ -1 +0,0 @@ -- Added support for the `speed_alpha` parameter to the `arcana` model in `RimeTTSService`. diff --git a/changelog/3879.changed.md b/changelog/3879.changed.md deleted file mode 100644 index 2b69f63ce..000000000 --- a/changelog/3879.changed.md +++ /dev/null @@ -1 +0,0 @@ -- Updated tracing code to use `ServiceSettings` dataclass API (`given_fields()`, attribute access) instead of dict-style access (`.items()`, `in`, subscript). diff --git a/changelog/3881.added.2.md b/changelog/3881.added.2.md deleted file mode 100644 index a5bda94c1..000000000 --- a/changelog/3881.added.2.md +++ /dev/null @@ -1 +0,0 @@ -- Added `ClientConnectedFrame`, a new `SystemFrame` pushed by all transports (Daily, LiveKit, FastAPI WebSocket, WebSocket Server, SmallWebRTC, HeyGen, Tavus) when a client connects. Enables observers to track transport readiness timing. diff --git a/changelog/3881.added.3.md b/changelog/3881.added.3.md deleted file mode 100644 index cad26e876..000000000 --- a/changelog/3881.added.3.md +++ /dev/null @@ -1 +0,0 @@ -Added `BotConnectedFrame` for SFU transports and `on_transport_timing_report` event to `StartupTimingObserver` with bot and client connection timing. diff --git a/changelog/3881.added.md b/changelog/3881.added.md deleted file mode 100644 index c71475675..000000000 --- a/changelog/3881.added.md +++ /dev/null @@ -1 +0,0 @@ -- Added `StartupTimingObserver` for measuring how long each processor's `start()` method takes during pipeline startup. Also measures transport readiness — the time from `StartFrame` to first client connection — via the `on_transport_timing_report` event. diff --git a/changelog/3883.added.md b/changelog/3883.added.md deleted file mode 100644 index 84360a891..000000000 --- a/changelog/3883.added.md +++ /dev/null @@ -1 +0,0 @@ -- Added optional `direction` parameter to `PipelineTask.queue_frame()` and `PipelineTask.queue_frames()`, allowing frames to be pushed upstream from the end of the pipeline. diff --git a/changelog/3885.added.2.md b/changelog/3885.added.2.md deleted file mode 100644 index 5a6adce12..000000000 --- a/changelog/3885.added.2.md +++ /dev/null @@ -1 +0,0 @@ -- Added `on_first_bot_speech_latency` event to `UserBotLatencyObserver` measuring the time from client connection to first bot speech. An `on_latency_breakdown` is also emitted for this first speech event. diff --git a/changelog/3885.added.md b/changelog/3885.added.md deleted file mode 100644 index 96f8cc2cd..000000000 --- a/changelog/3885.added.md +++ /dev/null @@ -1 +0,0 @@ -- Added `on_latency_breakdown` event to `UserBotLatencyObserver` providing per-service TTFB, text aggregation, user turn duration, and function call latency metrics for each user-to-bot response cycle. diff --git a/changelog/3886.other.md b/changelog/3886.other.md deleted file mode 100644 index 0e9fdafed..000000000 --- a/changelog/3886.other.md +++ /dev/null @@ -1 +0,0 @@ -- Standardized Sarvam STT/TTS User-Agent header handling to consistently send Pipecat SDK identity in websocket requests. \ No newline at end of file diff --git a/changelog/3888.fixed.md b/changelog/3888.fixed.md deleted file mode 100644 index 99e9ad0e0..000000000 --- a/changelog/3888.fixed.md +++ /dev/null @@ -1 +0,0 @@ -- Fixed turn completion instructions being lost when `LLMMessagesUpdateFrame` replaces the LLM context. When `filter_incomplete_user_turns` is enabled, the turn completion system message is now re-injected after context replacement. diff --git a/changelog/3893.fixed.md b/changelog/3893.fixed.md deleted file mode 100644 index 0209571e3..000000000 --- a/changelog/3893.fixed.md +++ /dev/null @@ -1 +0,0 @@ -- Fixed Azure TTS and STT services silently swallowing cancellation errors (invalid API key, network failures, rate limiting) instead of propagating them as `ErrorFrame`s to the pipeline. diff --git a/changelog/3896.added.md b/changelog/3896.added.md deleted file mode 100644 index 08921c004..000000000 --- a/changelog/3896.added.md +++ /dev/null @@ -1 +0,0 @@ -- Added `broadcast_interruption()` to `FrameProcessor`. This method pushes an `InterruptionFrame` both upstream and downstream directly from the calling processor, avoiding the round-trip through the pipeline task that `push_interruption_task_frame_and_wait()` required. diff --git a/changelog/3896.changed.md b/changelog/3896.changed.md deleted file mode 100644 index 3b7e4f807..000000000 --- a/changelog/3896.changed.md +++ /dev/null @@ -1 +0,0 @@ -- ⚠️ Removed `event` field and `complete()` method from `InterruptionFrame`. Removed `event` field from `InterruptionTaskFrame`. These are no longer needed since `broadcast_interruption()` does not require a round-trip completion signal. diff --git a/changelog/3896.deprecated.md b/changelog/3896.deprecated.md deleted file mode 100644 index 421e10e92..000000000 --- a/changelog/3896.deprecated.md +++ /dev/null @@ -1 +0,0 @@ -- Deprecated `push_interruption_task_frame_and_wait()` in `FrameProcessor`. Use `broadcast_interruption()` instead. The old method now delegates to `broadcast_interruption()` and logs a deprecation warning. diff --git a/changelog/3902.changed.md b/changelog/3902.changed.md deleted file mode 100644 index 95d3d592c..000000000 --- a/changelog/3902.changed.md +++ /dev/null @@ -1 +0,0 @@ -- Moved `pipecat.services.deepgram.stt_sagemaker` and `pipecat.services.deepgram.tts_sagemaker` to `pipecat.services.deepgram.sagemaker.stt` and `pipecat.services.deepgram.sagemaker.tts`. The old import paths still work but emit a `DeprecationWarning`. From aca92745cda832af773e542a1c08eb40c8f890d4 Mon Sep 17 00:00:00 2001 From: Mark Backman Date: Tue, 3 Mar 2026 08:40:12 -0500 Subject: [PATCH 0775/1060] Update update-docs skill to register new services in docs.json and supported-services.mdx When the skill creates a new service documentation page, it now also adds the page to docs.json navigation and the supported-services.mdx table. --- .claude/skills/update-docs/SKILL.md | 58 ++++++++++++++++++++++++++++- 1 file changed, 57 insertions(+), 1 deletion(-) diff --git a/.claude/skills/update-docs/SKILL.md b/.claude/skills/update-docs/SKILL.md index f24d56f00..6ed83abb0 100644 --- a/.claude/skills/update-docs/SKILL.md +++ b/.claude/skills/update-docs/SKILL.md @@ -157,7 +157,11 @@ After processing all mapped pairs, check for two kinds of gaps: **Missing sections**: Mapped doc pages that are missing standard sections compared to the source. For example, a transport page with no Configuration section, or a service page with no InputParams table when the source defines `InputParams(BaseModel)`. Flag these and offer to add the missing sections. -If the user wants a new page, create it using this template structure: +If the user wants a new page, do all three of the following: + +#### 8a: Create the doc page + +Create the new `.mdx` file using this template structure: ``` --- title: "Service Name" @@ -207,6 +211,53 @@ pip install "pipecat-ai[package-name]" [Event table and example code] ``` +#### 8b: Add to docs.json + +Add the new page path to `DOCS_PATH/docs.json` in the correct navigation group. The path format is `server/services/{category}/{provider}` (without the `.mdx` extension). + +Find the matching group in the navigation structure: +- **STT** → `"group": "Speech-to-Text"` under Services +- **TTS** → `"group": "Text-to-Speech"` under Services +- **LLM** → `"group": "LLM"` under Services +- **S2S** → `"group": "Speech-to-Speech"` under Services +- **Transport** → `"group": "Transport"` under Services +- **Serializer** → `"group": "Serializers"` under Services +- **Image generation** → `"group": "Image Generation"` under Services +- **Video** → `"group": "Video"` under Services +- **Memory** → `"group": "Memory"` under Services +- **Vision** → `"group": "Vision"` under Services +- **Analytics** → `"group": "Analytics & Monitoring"` under Services + +Insert the new entry **alphabetically** within the group's `pages` array. For example, adding a new STT service "foo": +```json +{ + "group": "Speech-to-Text", + "pages": [ + "server/services/stt/assemblyai", + "server/services/stt/aws", + ... + "server/services/stt/foo", + ... + ] +} +``` + +#### 8c: Add to supported-services.mdx + +Add a new row to the correct category table in `DOCS_PATH/server/services/supported-services.mdx`. + +Use this format: +``` +| [DisplayName](/server/services/{category}/{provider}) | `pip install "pipecat-ai[package]"` | +``` + +To determine the correct values: +- **DisplayName**: Use the service's human-readable name (e.g., "ElevenLabs", "AWS Polly", "Google Gemini") +- **package**: Look at the service's `pyproject.toml` extras or the import pattern in the source code. For example, if the service is in `src/pipecat/services/foo/`, the package is typically `foo`. +- If no pip dependencies are required, use `No dependencies required` instead. + +Insert the new row **alphabetically** within the table. Match the column alignment of the existing rows. + ### Step 9: Output summary After all edits are complete, print a summary: @@ -221,6 +272,9 @@ After all edits are complete, print a summary: ### Updated guides - `guides/learn/speech-to-text.mdx` — Updated code example (renamed `old_param` → `new_param`) +### New service pages +- `server/services/tts/newprovider.mdx` — Created page, added to docs.json (Text-to-Speech), added to supported-services.mdx + ### Unmapped source files - `src/pipecat/services/newprovider/tts.py` — NewProviderTTSService (no doc page exists) @@ -247,4 +301,6 @@ Before finishing, verify: - [ ] New parameters have accurate types and defaults from source - [ ] Formatting matches the existing page style - [ ] Guides referencing changed APIs were checked and updated +- [ ] New service pages were added to `docs.json` in the correct group, alphabetically +- [ ] New service pages were added to `supported-services.mdx` in the correct table, alphabetically - [ ] Unmapped files were reported to the user From 0fdf7dc16a98d24a1e7d49de6e72bdfb48a9a3a1 Mon Sep 17 00:00:00 2001 From: filipi87 Date: Tue, 3 Mar 2026 11:03:51 -0300 Subject: [PATCH 0776/1060] Fixing sagemaker merge conflicts. --- .../services/deepgram/sagemaker/stt.py | 38 ++++++++++--------- 1 file changed, 21 insertions(+), 17 deletions(-) diff --git a/src/pipecat/services/deepgram/sagemaker/stt.py b/src/pipecat/services/deepgram/sagemaker/stt.py index ba4b7dfda..24a25e5fd 100644 --- a/src/pipecat/services/deepgram/sagemaker/stt.py +++ b/src/pipecat/services/deepgram/sagemaker/stt.py @@ -15,7 +15,7 @@ languages, and various Deepgram features. import asyncio import json from dataclasses import dataclass -from typing import Any, AsyncGenerator, Dict, Optional +from typing import Any, AsyncGenerator, Optional from loguru import logger @@ -32,7 +32,7 @@ from pipecat.frames.frames import ( ) from pipecat.processors.frame_processor import FrameDirection from pipecat.services.aws.sagemaker.bidi_client import SageMakerBidiClient -from pipecat.services.deepgram.stt import _DeepgramSTTSettingsBase +from pipecat.services.deepgram.stt import DeepgramSTTSettings from pipecat.services.settings import STTSettings from pipecat.services.stt_latency import DEEPGRAM_SAGEMAKER_TTFS_P99 from pipecat.services.stt_service import STTService @@ -41,7 +41,7 @@ from pipecat.utils.time import time_now_iso8601 from pipecat.utils.tracing.service_decorators import traced_stt try: - from deepgram import LiveOptions + from pipecat.services.deepgram.stt import LiveOptions except ModuleNotFoundError as e: logger.error(f"Exception: {e}") logger.error( @@ -51,10 +51,10 @@ except ModuleNotFoundError as e: @dataclass -class DeepgramSageMakerSTTSettings(_DeepgramSTTSettingsBase): +class DeepgramSageMakerSTTSettings(DeepgramSTTSettings): """Settings for the Deepgram SageMaker STT service. - See ``_DeepgramSTTSettingsBase`` for full documentation. + See ``DeepgramSTTSettings`` for full documentation. """ pass @@ -117,22 +117,26 @@ class DeepgramSageMakerSTTService(STTService): """ sample_rate = sample_rate or (live_options.sample_rate if live_options else None) - default_options = LiveOptions( - encoding="linear16", - language=Language.EN, + settings = DeepgramSageMakerSTTSettings( model="nova-3", + language=Language.EN, + encoding="linear16", channels=1, interim_results=True, + smart_format=False, punctuate=True, + profanity_filter=True, + vad_events=False, + diarize=False, + endpointing=None, ) - settings = DeepgramSageMakerSTTSettings( - model=default_options.model, - language=default_options.language, - live_options=default_options, - ) if live_options: - settings._merge_live_options_delta(live_options) + lo_dict = live_options.to_dict() + delta = DeepgramSageMakerSTTSettings.from_mapping( + {k: v for k, v in lo_dict.items() if k != "sample_rate"} + ) + settings.apply_update(delta) super().__init__( sample_rate=sample_rate, @@ -224,9 +228,8 @@ class DeepgramSageMakerSTTService(STTService): """ logger.debug("Connecting to Deepgram on SageMaker...") - live_options = LiveOptions( - **{**self._settings.live_options.to_dict(), "sample_rate": self.sample_rate} - ) + # Reconstruct a LiveOptions from the flat settings to build the query string. + live_options = LiveOptions(**self._settings.given_fields()) # Build query string from live_options, converting booleans to strings query_params = {} @@ -237,6 +240,7 @@ class DeepgramSageMakerSTTService(STTService): query_params[key] = str(value).lower() else: query_params[key] = str(value) + query_params["sample_rate"] = str(self.sample_rate) query_string = "&".join(f"{k}={v}" for k, v in query_params.items()) From bdeeacec5169ad640bf1d9ff708fd5f9673ecd33 Mon Sep 17 00:00:00 2001 From: Mark Backman Date: Tue, 3 Mar 2026 10:37:35 -0500 Subject: [PATCH 0777/1060] uv.lock update --- uv.lock | 72 +++++++++++++++++++++++++++++++-------------------------- 1 file changed, 39 insertions(+), 33 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"https://files.pythonhosted.org/packages/6f/e1/50ee92a5db521de8f35075b5eff060dd43d39ebd46c2181a2042f7070385/greenlet-3.3.2-cp314-cp314t-musllinux_1_2_x86_64.whl", hash = "sha256:20154044d9085151bc309e7689d6f7ba10027f8f5a8c0676ad398b951913d89e", size = 1680010, upload-time = "2026-02-20T20:21:13.427Z" }, @@ -4728,7 +4734,7 @@ docs = [ [package.metadata] requires-dist = [ { name = "accelerate", marker = "extra == 'moondream'", specifier = "~=1.10.0" }, - { name = "aic-sdk", marker = "extra == 'aic'", specifier = "~=2.0.1" }, + { name = "aic-sdk", marker = "extra == 'aic'", specifier = "~=2.1.0" }, { name = "aioboto3", marker = "extra == 'aws'", specifier = "~=15.5.0" }, { name = "aiofiles", specifier = ">=24.1.0,<25" }, { name = "aiohttp", specifier = ">=3.11.12,<4" }, From b358657a796223d3025ac0a20cbe4077d7c43dec Mon Sep 17 00:00:00 2001 From: Mark Backman Date: Tue, 3 Mar 2026 20:08:22 -0500 Subject: [PATCH 0778/1060] Make max_context_tokens and max_unsummarized_messages independently optional Allow either threshold to be set to None to cleanly disable that trigger, instead of requiring users to set a very large number as a workaround. At least one of the two must remain set (validated at construction time). --- .../aggregators/llm_context_summarizer.py | 19 ++-- .../context/llm_context_summarization.py | 47 +++++++--- tests/test_context_summarization.py | 37 ++++++++ tests/test_llm_context_summarizer.py | 92 +++++++++++++++++++ 4 files changed, 173 insertions(+), 22 deletions(-) diff --git a/src/pipecat/processors/aggregators/llm_context_summarizer.py b/src/pipecat/processors/aggregators/llm_context_summarizer.py index 54879a8bb..4e55ffaf1 100644 --- a/src/pipecat/processors/aggregators/llm_context_summarizer.py +++ b/src/pipecat/processors/aggregators/llm_context_summarizer.py @@ -211,14 +211,16 @@ class LLMContextSummarizer(BaseObject): Evaluates whether the current context has reached either the token threshold or message count threshold that warrants compression. + Either threshold can be ``None`` to disable that check; at least one + must be set (enforced at config construction time). Returns: True if all conditions are met: - ``auto_trigger`` is enabled - No summarization currently in progress - AND either: - - Token count exceeds ``max_context_tokens`` - - OR message count exceeds ``max_unsummarized_messages`` since last summary + - Token count exceeds ``max_context_tokens`` (when set) + - OR message count exceeds ``max_unsummarized_messages`` since last summary (when set) """ logger.trace(f"{self}: Checking if context summarization is needed") @@ -235,19 +237,20 @@ class LLMContextSummarizer(BaseObject): # Check if we've reached the token limit token_limit = self._auto_config.max_context_tokens - token_limit_exceeded = total_tokens >= token_limit + token_limit_exceeded = token_limit is not None and total_tokens >= token_limit # Check if we've exceeded max unsummarized messages messages_since_summary = len(self._context.messages) - 1 + message_threshold = self._auto_config.max_unsummarized_messages message_threshold_exceeded = ( - messages_since_summary >= self._auto_config.max_unsummarized_messages + message_threshold is not None and messages_since_summary >= message_threshold ) logger.trace( f"{self}: Context has {num_messages} messages, " - f"~{total_tokens} tokens (limit: {token_limit}), " + f"~{total_tokens} tokens (limit: {token_limit if token_limit is not None else 'disabled'}), " f"{messages_since_summary} messages since last summary " - f"(message threshold: {self._auto_config.max_unsummarized_messages})" + f"(message threshold: {message_threshold if message_threshold is not None else 'disabled'})" ) # Trigger if either limit is exceeded @@ -261,9 +264,7 @@ class LLMContextSummarizer(BaseObject): if token_limit_exceeded: reason.append(f"~{total_tokens} tokens (>={token_limit} limit)") if message_threshold_exceeded: - reason.append( - f"{messages_since_summary} messages (>={self._auto_config.max_unsummarized_messages} threshold)" - ) + reason.append(f"{messages_since_summary} messages (>={message_threshold} threshold)") logger.debug(f"{self}: ✓ Summarization needed - {', '.join(reason)}") return True diff --git a/src/pipecat/utils/context/llm_context_summarization.py b/src/pipecat/utils/context/llm_context_summarization.py index e68311942..707d0c32d 100644 --- a/src/pipecat/utils/context/llm_context_summarization.py +++ b/src/pipecat/utils/context/llm_context_summarization.py @@ -119,33 +119,45 @@ class LLMAutoContextSummarizationConfig: that summary is generated. Summarization is triggered when either the token limit or the unsummarized message count threshold is exceeded. + At least one of ``max_context_tokens`` and ``max_unsummarized_messages`` + must be set. Set the other to ``None`` to disable that threshold. + Parameters: max_context_tokens: Maximum allowed context size in tokens. When this limit is reached, summarization is triggered to compress the context. The tokens are calculated using the industry-standard approximation - of 1 token ≈ 4 characters. + of 1 token ≈ 4 characters. Set to ``None`` to disable token-based + triggering. max_unsummarized_messages: Maximum number of new messages that can accumulate since the last summary before triggering a new summarization. This ensures regular compression even if token - limits are not reached. + limits are not reached. Set to ``None`` to disable message-count + triggering. summary_config: Configuration for summary generation parameters (prompt, token budget, messages to keep). If not provided, uses default ``LLMContextSummaryConfig`` values. """ - max_context_tokens: int = 8000 - max_unsummarized_messages: int = 20 + max_context_tokens: Optional[int] = 8000 + max_unsummarized_messages: Optional[int] = 20 summary_config: LLMContextSummaryConfig = field(default_factory=LLMContextSummaryConfig) def __post_init__(self): """Validate configuration parameters.""" - if self.max_context_tokens <= 0: + if self.max_context_tokens is None and self.max_unsummarized_messages is None: + raise ValueError( + "At least one of max_context_tokens and max_unsummarized_messages must be set" + ) + if self.max_context_tokens is not None and self.max_context_tokens <= 0: raise ValueError("max_context_tokens must be positive") - if self.max_unsummarized_messages < 1: + if self.max_unsummarized_messages is not None and self.max_unsummarized_messages < 1: raise ValueError("max_unsummarized_messages must be at least 1") # Auto-adjust target_context_tokens if it exceeds max_context_tokens - if self.summary_config.target_context_tokens > self.max_context_tokens: + if ( + self.max_context_tokens is not None + and self.summary_config.target_context_tokens > self.max_context_tokens + ): # Use 80% of max_context_tokens as a reasonable default self.summary_config.target_context_tokens = int(self.max_context_tokens * 0.8) @@ -154,7 +166,7 @@ class LLMAutoContextSummarizationConfig: class LLMContextSummarizationConfig: """Configuration for context summarization behavior. - .. deprecated:: + .. deprecated:: 0.0.104 Use :class:`LLMAutoContextSummarizationConfig` with a nested :class:`LLMContextSummaryConfig` instead:: @@ -169,15 +181,17 @@ class LLMContextSummarizationConfig: Parameters: max_context_tokens: Maximum allowed context size in tokens. + Set to ``None`` to disable token-based triggering. target_context_tokens: Maximum token size for the generated summary. max_unsummarized_messages: Maximum new messages before triggering summarization. + Set to ``None`` to disable message-count triggering. min_messages_after_summary: Number of recent messages to preserve. summarization_prompt: Custom prompt for summary generation. """ - max_context_tokens: int = 8000 + max_context_tokens: Optional[int] = 8000 target_context_tokens: int = 6000 - max_unsummarized_messages: int = 20 + max_unsummarized_messages: Optional[int] = 20 min_messages_after_summary: int = 4 summarization_prompt: Optional[str] = None summary_message_template: str = "Conversation summary: {summary}" @@ -192,17 +206,24 @@ class LLMContextSummarizationConfig: DeprecationWarning, stacklevel=2, ) - if self.max_context_tokens <= 0: + if self.max_context_tokens is None and self.max_unsummarized_messages is None: + raise ValueError( + "At least one of max_context_tokens and max_unsummarized_messages must be set" + ) + if self.max_context_tokens is not None and self.max_context_tokens <= 0: raise ValueError("max_context_tokens must be positive") if self.target_context_tokens <= 0: raise ValueError("target_context_tokens must be positive") # Auto-adjust target_context_tokens if it exceeds max_context_tokens - if self.target_context_tokens > self.max_context_tokens: + if ( + self.max_context_tokens is not None + and self.target_context_tokens > self.max_context_tokens + ): # Use 80% of max_context_tokens as a reasonable default self.target_context_tokens = int(self.max_context_tokens * 0.8) - if self.max_unsummarized_messages < 1: + if self.max_unsummarized_messages is not None and self.max_unsummarized_messages < 1: raise ValueError("max_unsummarized_messages must be at least 1") if self.min_messages_after_summary < 0: raise ValueError("min_messages_after_summary must be positive") diff --git a/tests/test_context_summarization.py b/tests/test_context_summarization.py index 10223a606..e2666e7fa 100644 --- a/tests/test_context_summarization.py +++ b/tests/test_context_summarization.py @@ -239,6 +239,43 @@ class TestLLMAutoContextSummarizationConfig(unittest.TestCase): ) self.assertLessEqual(config.summary_config.target_context_tokens, config.max_context_tokens) + def test_max_context_tokens_none(self): + """Test that max_context_tokens can be None when max_unsummarized_messages is set.""" + config = LLMAutoContextSummarizationConfig( + max_context_tokens=None, + max_unsummarized_messages=20, + ) + self.assertIsNone(config.max_context_tokens) + self.assertEqual(config.max_unsummarized_messages, 20) + + def test_max_unsummarized_messages_none(self): + """Test that max_unsummarized_messages can be None when max_context_tokens is set.""" + config = LLMAutoContextSummarizationConfig( + max_context_tokens=8000, + max_unsummarized_messages=None, + ) + self.assertEqual(config.max_context_tokens, 8000) + self.assertIsNone(config.max_unsummarized_messages) + + def test_both_none_raises(self): + """Test that setting both thresholds to None raises ValueError.""" + with self.assertRaises(ValueError) as cm: + LLMAutoContextSummarizationConfig( + max_context_tokens=None, + max_unsummarized_messages=None, + ) + self.assertIn("at least one", str(cm.exception).lower()) + + def test_target_tokens_not_auto_adjusted_when_max_none(self): + """Test that target_context_tokens is not auto-adjusted when max_context_tokens is None.""" + config = LLMAutoContextSummarizationConfig( + max_context_tokens=None, + max_unsummarized_messages=10, + summary_config=LLMContextSummaryConfig(target_context_tokens=9000), + ) + # target_context_tokens should remain unchanged since there's no max to compare against + self.assertEqual(config.summary_config.target_context_tokens, 9000) + class TestLLMContextSummarizationConfigDeprecated(unittest.TestCase): """Tests for deprecated LLMContextSummarizationConfig.""" diff --git a/tests/test_llm_context_summarizer.py b/tests/test_llm_context_summarizer.py index 7e8b326f9..bbe8648ef 100644 --- a/tests/test_llm_context_summarizer.py +++ b/tests/test_llm_context_summarizer.py @@ -668,6 +668,98 @@ class TestLLMContextSummarizer(unittest.IsolatedAsyncioTestCase): await summarizer.cleanup() + async def test_token_limit_none_only_message_threshold(self): + """Test that only message threshold triggers when token limit is None.""" + config = LLMAutoContextSummarizationConfig( + max_context_tokens=None, + max_unsummarized_messages=5, + ) + + summarizer = LLMContextSummarizer(context=self.context, config=config) + await summarizer.setup(self.task_manager) + + request_frame = None + + @summarizer.event_handler("on_request_summarization") + async def on_request_summarization(summarizer, frame): + nonlocal request_frame + request_frame = frame + + # Add many tokens but fewer than 5 messages — should NOT trigger + for i in range(3): + self.context.add_message( + {"role": "user", "content": "x" * 10000} # Lots of tokens + ) + + await summarizer.process_frame(LLMFullResponseStartFrame()) + self.assertIsNone(request_frame) + + # Cross the message threshold (5 messages since summary = 6 total including system) + for i in range(3): + self.context.add_message({"role": "user", "content": f"Message {i}"}) + + await summarizer.process_frame(LLMFullResponseStartFrame()) + self.assertIsNotNone(request_frame) + + await summarizer.cleanup() + + async def test_message_limit_none_only_token_threshold(self): + """Test that only token threshold triggers when message limit is None.""" + config = LLMAutoContextSummarizationConfig( + max_context_tokens=100, # Very low + max_unsummarized_messages=None, + ) + + summarizer = LLMContextSummarizer(context=self.context, config=config) + await summarizer.setup(self.task_manager) + + request_frame = None + + @summarizer.event_handler("on_request_summarization") + async def on_request_summarization(summarizer, frame): + nonlocal request_frame + request_frame = frame + + # Add many messages that exceed the token limit + for i in range(10): + self.context.add_message( + {"role": "user", "content": "This is a test message with enough tokens."} + ) + + await summarizer.process_frame(LLMFullResponseStartFrame()) + self.assertIsNotNone(request_frame) + + await summarizer.cleanup() + + async def test_message_limit_none_no_trigger_below_tokens(self): + """Test that many messages don't trigger when message limit is None and tokens are low.""" + config = LLMAutoContextSummarizationConfig( + max_context_tokens=100000, # Very high + max_unsummarized_messages=None, + ) + + summarizer = LLMContextSummarizer(context=self.context, config=config) + await summarizer.setup(self.task_manager) + + request_frame = None + + @summarizer.event_handler("on_request_summarization") + async def on_request_summarization(summarizer, frame): + nonlocal request_frame + request_frame = frame + + # Add many short messages — would exceed any reasonable message count + # but tokens stay well below the limit + for i in range(50): + self.context.add_message({"role": "user", "content": f"Msg {i}"}) + + await summarizer.process_frame(LLMFullResponseStartFrame()) + + # Should NOT trigger because token limit is not exceeded + self.assertIsNone(request_frame) + + await summarizer.cleanup() + if __name__ == "__main__": unittest.main() From 6789aee9e82e4008c42e7cdebb2187335107b001 Mon Sep 17 00:00:00 2001 From: Mark Backman Date: Tue, 3 Mar 2026 20:09:26 -0500 Subject: [PATCH 0779/1060] Add changelog for #3914 --- changelog/3914.changed.md | 1 + 1 file changed, 1 insertion(+) create mode 100644 changelog/3914.changed.md diff --git a/changelog/3914.changed.md b/changelog/3914.changed.md new file mode 100644 index 000000000..22d4ff94e --- /dev/null +++ b/changelog/3914.changed.md @@ -0,0 +1 @@ +- `max_context_tokens` and `max_unsummarized_messages` in `LLMAutoContextSummarizationConfig` (and deprecated `LLMContextSummarizationConfig`) can now be set to `None` independently to disable that summarization threshold. At least one must remain set. From df35ceca2cd83b0f9147074cad81c1651980da3c Mon Sep 17 00:00:00 2001 From: Mark Backman Date: Wed, 4 Mar 2026 09:37:56 -0500 Subject: [PATCH 0780/1060] Add per-tool timeout_secs to register_function and register_direct_function The default function call timeout (10s) causes silent failures for long-running tools. This adds an optional timeout_secs parameter to register_function() and register_direct_function() so individual tools can override the global function_call_timeout_secs. The warning message now mentions both the per-tool and global timeout options. --- src/pipecat/services/llm_service.py | 24 ++++++++++++++++++++++-- 1 file changed, 22 insertions(+), 2 deletions(-) diff --git a/src/pipecat/services/llm_service.py b/src/pipecat/services/llm_service.py index da0d57d66..909b555a2 100644 --- a/src/pipecat/services/llm_service.py +++ b/src/pipecat/services/llm_service.py @@ -120,12 +120,15 @@ class FunctionCallRegistryItem: function_name: The name of the function (None for catch-all handler). handler: The handler for processing function call parameters. cancel_on_interruption: Whether to cancel the call on interruption. + timeout_secs: Optional per-tool timeout in seconds. Overrides the global + ``function_call_timeout_secs`` for this specific function. """ function_name: Optional[str] handler: FunctionCallHandler | "DirectFunctionWrapper" cancel_on_interruption: bool handler_deprecated: bool + timeout_secs: Optional[float] = None @dataclass @@ -540,6 +543,7 @@ class LLMService(UserTurnCompletionLLMServiceMixin, AIService): start_callback=None, *, cancel_on_interruption: bool = True, + timeout_secs: Optional[float] = None, ): """Register a function handler for LLM function calls. @@ -556,6 +560,9 @@ class LLMService(UserTurnCompletionLLMServiceMixin, AIService): cancel_on_interruption: Whether to cancel this function call when an interruption occurs. Defaults to True. + timeout_secs: Optional per-tool timeout in seconds. Overrides the global + ``function_call_timeout_secs`` for this specific function. Defaults to + None, which uses the global timeout. """ signature = inspect.signature(handler) handler_deprecated = len(signature.parameters) > 1 @@ -574,6 +581,7 @@ class LLMService(UserTurnCompletionLLMServiceMixin, AIService): handler=handler, cancel_on_interruption=cancel_on_interruption, handler_deprecated=handler_deprecated, + timeout_secs=timeout_secs, ) # Start callbacks are now deprecated. @@ -592,6 +600,7 @@ class LLMService(UserTurnCompletionLLMServiceMixin, AIService): handler: DirectFunction, *, cancel_on_interruption: bool = True, + timeout_secs: Optional[float] = None, ): """Register a direct function handler for LLM function calls. @@ -603,6 +612,9 @@ class LLMService(UserTurnCompletionLLMServiceMixin, AIService): handler: The direct function to register. Must follow DirectFunction protocol. cancel_on_interruption: Whether to cancel this function call when an interruption occurs. Defaults to True. + timeout_secs: Optional per-tool timeout in seconds. Overrides the global + ``function_call_timeout_secs`` for this specific function. Defaults to + None, which uses the global timeout. """ wrapper = DirectFunctionWrapper(handler) self._functions[wrapper.name] = FunctionCallRegistryItem( @@ -610,6 +622,7 @@ class LLMService(UserTurnCompletionLLMServiceMixin, AIService): handler=wrapper, cancel_on_interruption=cancel_on_interruption, handler_deprecated=False, + timeout_secs=timeout_secs, ) def unregister_function(self, function_name: Optional[str]): @@ -837,9 +850,16 @@ class LLMService(UserTurnCompletionLLMServiceMixin, AIService): # Start a timeout task for deferred function calls async def timeout_handler(): try: - await asyncio.sleep(self._function_call_timeout_secs) + effective_timeout = ( + item.timeout_secs + if item.timeout_secs is not None + else self._function_call_timeout_secs + ) + await asyncio.sleep(effective_timeout) logger.warning( - f"{self} Function call [{runner_item.function_name}:{runner_item.tool_call_id}] timed out after {self._function_call_timeout_secs} seconds" + f"{self} Function call [{runner_item.function_name}:{runner_item.tool_call_id}] timed out after {effective_timeout} seconds." + f" You can increase this timeout by passing `timeout_secs` to `register_function()`," + f" or set a global default via `function_call_timeout_secs` on the LLM constructor." ) await function_call_result_callback(None) except asyncio.CancelledError: From 97e4e7c6473cfb70308aa723ca17e5178f8927bd Mon Sep 17 00:00:00 2001 From: Mark Backman Date: Wed, 4 Mar 2026 09:42:01 -0500 Subject: [PATCH 0781/1060] Add changelog for #3915 --- changelog/3915.added.md | 1 + 1 file changed, 1 insertion(+) create mode 100644 changelog/3915.added.md diff --git a/changelog/3915.added.md b/changelog/3915.added.md new file mode 100644 index 000000000..66d4fb383 --- /dev/null +++ b/changelog/3915.added.md @@ -0,0 +1 @@ +- Added optional `timeout_secs` parameter to `register_function()` and `register_direct_function()` for per-tool function call timeout control, overriding the global `function_call_timeout_secs` default. From 27ae6a03496927ad6feeab68a0007ce026ae3b41 Mon Sep 17 00:00:00 2001 From: Mark Backman Date: Wed, 4 Mar 2026 11:50:37 -0500 Subject: [PATCH 0782/1060] Add missing __init__.py to sagemaker module --- src/pipecat/services/deepgram/sagemaker/__init__.py | 0 1 file changed, 0 insertions(+), 0 deletions(-) create mode 100644 src/pipecat/services/deepgram/sagemaker/__init__.py diff --git a/src/pipecat/services/deepgram/sagemaker/__init__.py b/src/pipecat/services/deepgram/sagemaker/__init__.py new file mode 100644 index 000000000..e69de29bb From 96062972db6a584533872730b798284b0a44b593 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Aleix=20Conchillo=20Flaqu=C3=A9?= Date: Wed, 4 Mar 2026 13:30:43 -0800 Subject: [PATCH 0783/1060] Add logging to Daily transport event handlers Add appropriate log levels to dial-in/dial-out, participant, transcription, and recording event handlers. Move transcription error log from client callback to transport handler to keep logging consistent at the transport level. --- src/pipecat/transports/daily/transport.py | 17 ++++++++++++++++- 1 file changed, 16 insertions(+), 1 deletion(-) diff --git a/src/pipecat/transports/daily/transport.py b/src/pipecat/transports/daily/transport.py index dc9868426..87b46c113 100644 --- a/src/pipecat/transports/daily/transport.py +++ b/src/pipecat/transports/daily/transport.py @@ -1467,7 +1467,6 @@ class DailyTransportClient(EventHandler): Args: message: Error message. """ - logger.error(f"Transcription error: {message}") self._call_event_callback(self._callbacks.on_transcription_error, message) def on_transcription_message(self, message): @@ -2668,44 +2667,54 @@ class DailyTransport(BaseTransport): async def _on_dialin_connected(self, data): """Handle dial-in connected events.""" + logger.debug(f"{self} dial-in connected: {data}") await self._call_event_handler("on_dialin_connected", data) async def _on_dialin_ready(self, sip_endpoint): """Handle dial-in ready events.""" + logger.debug(f"{self} dial-in ready: {sip_endpoint}") if self._params.dialin_settings: await self._handle_dialin_ready(sip_endpoint) await self._call_event_handler("on_dialin_ready", sip_endpoint) async def _on_dialin_stopped(self, data): """Handle dial-in stopped events.""" + logger.debug(f"{self} dial-in stopped: {data}") await self._call_event_handler("on_dialin_stopped", data) async def _on_dialin_error(self, data): """Handle dial-in error events.""" + logger.error(f"{self} dial-in error: {data}") await self._call_event_handler("on_dialin_error", data) async def _on_dialin_warning(self, data): """Handle dial-in warning events.""" + logger.warning(f"{self} dial-in warning: {data}") await self._call_event_handler("on_dialin_warning", data) async def _on_dialout_answered(self, data): """Handle dial-out answered events.""" + logger.debug(f"{self} dial-out answered: {data}") await self._call_event_handler("on_dialout_answered", data) async def _on_dialout_connected(self, data): """Handle dial-out connected events.""" + logger.debug(f"{self} dial-out connected: {data}") await self._call_event_handler("on_dialout_connected", data) async def _on_dialout_stopped(self, data): """Handle dial-out stopped events.""" + logger.debug(f"{self} dial-out stopped: {data}") await self._call_event_handler("on_dialout_stopped", data) async def _on_dialout_error(self, data): """Handle dial-out error events.""" + logger.error(f"{self} dial-out error: {data}") await self._call_event_handler("on_dialout_error", data) async def _on_dialout_warning(self, data): """Handle dial-out warning events.""" + logger.warning(f"{self} dial-out warning: {data}") await self._call_event_handler("on_dialout_warning", data) async def _on_participant_joined(self, participant): @@ -2738,6 +2747,7 @@ class DailyTransport(BaseTransport): async def _on_participant_updated(self, participant): """Handle participant updated events.""" + logger.debug(f"{self} participant updated: {participant}") await self._call_event_handler("on_participant_updated", participant) async def _on_transcription_message(self, message: Mapping[str, Any]) -> None: @@ -2778,20 +2788,25 @@ class DailyTransport(BaseTransport): async def _on_transcription_stopped(self, stopped_by, stopped_by_error): """Handle transcription stopped events.""" + logger.debug(f"{self} transcription stopped by: {stopped_by} (error: {stopped_by_error})") await self._call_event_handler("on_transcription_stopped", stopped_by, stopped_by_error) async def _on_transcription_error(self, message): """Handle transcription error events.""" + logger.error(f"{self} transcription error: {message}") await self._call_event_handler("on_transcription_error", message) async def _on_recording_started(self, status): """Handle recording started events.""" + logger.debug(f"{self} recording started: {status}") await self._call_event_handler("on_recording_started", status) async def _on_recording_stopped(self, stream_id): """Handle recording stopped events.""" + logger.debug(f"{self} recording stopped (id: {stream_id})") await self._call_event_handler("on_recording_stopped", stream_id) async def _on_recording_error(self, stream_id, message): """Handle recording error events.""" + logger.error(f"{self} recording error (id: {stream_id}): {message}") await self._call_event_handler("on_recording_error", stream_id, message) From 9ca900cc4a4a3a48046b19d39cb8d0acb7c1be77 Mon Sep 17 00:00:00 2001 From: vipyne Date: Wed, 4 Mar 2026 09:41:17 -0600 Subject: [PATCH 0784/1060] daily-transport: add cloud-audio-only recording option --- src/pipecat/transports/daily/utils.py | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/src/pipecat/transports/daily/utils.py b/src/pipecat/transports/daily/utils.py index e5bbca8c7..8719cfe7d 100644 --- a/src/pipecat/transports/daily/utils.py +++ b/src/pipecat/transports/daily/utils.py @@ -108,7 +108,7 @@ class DailyRoomProperties(BaseModel): enable_emoji_reactions: bool = False eject_at_room_exp: bool = False enable_dialout: Optional[bool] = None - enable_recording: Optional[Literal["cloud", "local", "raw-tracks"]] = None + enable_recording: Optional[Literal["cloud", "cloud-audio-only", "local", "raw-tracks"]] = None enable_transcription_storage: Optional[bool] = None geo: Optional[str] = None max_participants: Optional[int] = None @@ -202,7 +202,7 @@ class DailyMeetingTokenProperties(BaseModel): enable_screenshare: Optional[bool] = None start_video_off: Optional[bool] = None start_audio_off: Optional[bool] = None - enable_recording: Optional[Literal["cloud", "local", "raw-tracks"]] = None + enable_recording: Optional[Literal["cloud", "cloud-audio-only", "local", "raw-tracks"]] = None enable_prejoin_ui: Optional[bool] = None start_cloud_recording: Optional[bool] = None permissions: Optional[Dict[str, Any]] = None From aa31ced32fba76733c79f84a55f01a87144c77f5 Mon Sep 17 00:00:00 2001 From: vipyne Date: Wed, 4 Mar 2026 09:46:47 -0600 Subject: [PATCH 0785/1060] add changelog for 3916 --- changelog/3916.added.md | 1 + 1 file changed, 1 insertion(+) create mode 100644 changelog/3916.added.md diff --git a/changelog/3916.added.md b/changelog/3916.added.md new file mode 100644 index 000000000..05c3f124f --- /dev/null +++ b/changelog/3916.added.md @@ -0,0 +1 @@ +- Added `cloud-audio-only` recording option to Daily transport's `enable_recording` property. From 01f0caf252a284ef190cd6013941287ab99c0ec6 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Aleix=20Conchillo=20Flaqu=C3=A9?= Date: Wed, 4 Mar 2026 13:25:07 -0800 Subject: [PATCH 0786/1060] wire up system_instruction in OpenAI, Anthropic and AWS Bedrock --- src/pipecat/services/anthropic/llm.py | 12 +++++++++--- src/pipecat/services/aws/llm.py | 12 +++++++++--- src/pipecat/services/openai/base_llm.py | 16 +++++++++++++++- 3 files changed, 33 insertions(+), 7 deletions(-) diff --git a/src/pipecat/services/anthropic/llm.py b/src/pipecat/services/anthropic/llm.py index 03190ef99..755ca6400 100644 --- a/src/pipecat/services/anthropic/llm.py +++ b/src/pipecat/services/anthropic/llm.py @@ -17,7 +17,7 @@ import io import json import re from dataclasses import dataclass, field -from typing import Any, ClassVar, Dict, List, Literal, Optional, Union +from typing import Any, Dict, List, Literal, Optional, Union import httpx from loguru import logger @@ -38,7 +38,6 @@ from pipecat.frames.frames import ( LLMFullResponseEndFrame, LLMFullResponseStartFrame, LLMMessagesFrame, - LLMTextFrame, LLMThoughtEndFrame, LLMThoughtStartFrame, LLMThoughtTextFrame, @@ -219,6 +218,7 @@ class AnthropicLLMService(LLMService): client=None, retry_timeout_secs: Optional[float] = 5.0, retry_on_timeout: Optional[bool] = False, + system_instruction: Optional[str] = None, **kwargs, ): """Initialize the Anthropic LLM service. @@ -230,6 +230,7 @@ class AnthropicLLMService(LLMService): client: Optional custom Anthropic client instance. retry_timeout_secs: Request timeout in seconds for retry logic. retry_on_timeout: Whether to retry the request once if it times out. + system_instruction: Optional system instruction to use as the system prompt. **kwargs: Additional arguments passed to parent LLMService. """ params = params or AnthropicLLMService.InputParams() @@ -265,6 +266,9 @@ class AnthropicLLMService(LLMService): ) # if the client is provided, use it and remove it, otherwise create a new one self._retry_timeout_secs = retry_timeout_secs self._retry_on_timeout = retry_on_timeout + self._system_instruction = system_instruction + if self._system_instruction: + logger.debug(f"{self}: Using system instruction: {self._system_instruction}") def can_generate_metrics(self) -> bool: """Check if this service can generate usage metrics. @@ -395,9 +399,11 @@ class AnthropicLLMService(LLMService): # Universal LLMContext if isinstance(context, LLMContext): adapter: AnthropicLLMAdapter = self.get_llm_adapter() - params = adapter.get_llm_invocation_params( + params: AnthropicLLMInvocationParams = adapter.get_llm_invocation_params( context, enable_prompt_caching=self._settings.enable_prompt_caching ) + if self._system_instruction: + params["system"] = self._system_instruction return params # Anthropic-specific context diff --git a/src/pipecat/services/aws/llm.py b/src/pipecat/services/aws/llm.py index 540ac4a8e..31f8085bc 100644 --- a/src/pipecat/services/aws/llm.py +++ b/src/pipecat/services/aws/llm.py @@ -19,7 +19,7 @@ import json import os import re from dataclasses import dataclass, field -from typing import Any, ClassVar, Dict, List, Optional +from typing import Any, Dict, List, Optional from loguru import logger from PIL import Image @@ -39,7 +39,6 @@ from pipecat.frames.frames import ( LLMFullResponseEndFrame, LLMFullResponseStartFrame, LLMMessagesFrame, - LLMTextFrame, UserImageRawFrame, ) from pipecat.metrics.metrics import LLMTokenUsage @@ -781,6 +780,7 @@ class AWSBedrockLLMService(LLMService): client_config: Optional[Config] = None, retry_timeout_secs: Optional[float] = 5.0, retry_on_timeout: Optional[bool] = False, + system_instruction: Optional[str] = None, **kwargs, ): """Initialize the AWS Bedrock LLM service. @@ -795,6 +795,7 @@ class AWSBedrockLLMService(LLMService): client_config: Custom boto3 client configuration. retry_timeout_secs: Request timeout in seconds for retry logic. retry_on_timeout: Whether to retry the request once if it times out. + system_instruction: Optional system instruction to use as the system prompt. **kwargs: Additional arguments passed to parent LLMService. """ params = params or AWSBedrockLLMService.InputParams() @@ -840,8 +841,11 @@ class AWSBedrockLLMService(LLMService): self._retry_timeout_secs = retry_timeout_secs self._retry_on_timeout = retry_on_timeout + self._system_instruction = system_instruction logger.info(f"Using AWS Bedrock model: {model}") + if self._system_instruction: + logger.debug(f"{self}: Using system instruction: {self._system_instruction}") def can_generate_metrics(self) -> bool: """Check if the service can generate usage metrics. @@ -1019,7 +1023,9 @@ class AWSBedrockLLMService(LLMService): # Universal LLMContext if isinstance(context, LLMContext): adapter: AWSBedrockLLMAdapter = self.get_llm_adapter() - params = adapter.get_llm_invocation_params(context) + params: AWSBedrockLLMInvocationParams = adapter.get_llm_invocation_params(context) + if self._system_instruction: + params["system"] = [{"text": self._system_instruction}] return params # AWS Bedrock-specific context diff --git a/src/pipecat/services/openai/base_llm.py b/src/pipecat/services/openai/base_llm.py index 40a2672f8..ed012d0df 100644 --- a/src/pipecat/services/openai/base_llm.py +++ b/src/pipecat/services/openai/base_llm.py @@ -11,7 +11,7 @@ import base64 import json from contextlib import asynccontextmanager from dataclasses import dataclass, field -from typing import Any, ClassVar, Dict, List, Mapping, Optional +from typing import Any, Dict, List, Mapping, Optional import httpx from loguru import logger @@ -117,6 +117,7 @@ class BaseOpenAILLMService(LLMService): params: Optional[InputParams] = None, retry_timeout_secs: Optional[float] = 5.0, retry_on_timeout: Optional[bool] = False, + system_instruction: Optional[str] = None, **kwargs, ): """Initialize the BaseOpenAILLMService. @@ -131,6 +132,7 @@ class BaseOpenAILLMService(LLMService): params: Input parameters for model configuration and behavior. retry_timeout_secs: Request timeout in seconds. Defaults to 5.0 seconds. retry_on_timeout: Whether to retry the request once if it times out. + system_instruction: Optional system instruction to prepend to messages. **kwargs: Additional arguments passed to the parent LLMService. """ params = params or BaseOpenAILLMService.InputParams() @@ -155,6 +157,7 @@ class BaseOpenAILLMService(LLMService): ) self._retry_timeout_secs = retry_timeout_secs self._retry_on_timeout = retry_on_timeout + self._system_instruction = system_instruction self._full_model_name: str = "" self._client = self.create_client( api_key=api_key, @@ -165,6 +168,9 @@ class BaseOpenAILLMService(LLMService): **kwargs, ) + if self._system_instruction: + logger.debug(f"{self}: Using system instruction: {self._system_instruction}") + def create_client( self, api_key=None, @@ -285,6 +291,14 @@ class BaseOpenAILLMService(LLMService): params.update(params_from_context) params.update(self._settings.extra) + + # Prepend system instruction if set + if self._system_instruction: + messages = params.get("messages", []) + params["messages"] = [ + {"role": "system", "content": self._system_instruction} + ] + messages + return params async def run_inference( From 0004a116d87394d1306a54937d2e8c11fe0e5e81 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Aleix=20Conchillo=20Flaqu=C3=A9?= Date: Wed, 4 Mar 2026 15:36:48 -0800 Subject: [PATCH 0787/1060] examples(foundational): use system_instruction in all examples --- examples/foundational/02-llm-say-one-thing.py | 16 ++++----- .../04-transports-small-webrtc.py | 16 ++++----- examples/foundational/04a-transports-daily.py | 19 +++++------ .../foundational/04b-transports-livekit.py | 17 +++------- .../foundational/06-listen-and-respond.py | 16 ++++----- examples/foundational/06a-image-sync.py | 14 +++----- .../07-interruptible-cartesia-http.py | 16 ++++----- examples/foundational/07-interruptible.py | 16 ++++----- .../07c-interruptible-deepgram-flux.py | 16 ++++----- .../07c-interruptible-deepgram-http.py | 16 ++++----- .../07c-interruptible-deepgram-sagemaker.py | 12 ++----- .../07c-interruptible-deepgram-vad.py | 16 ++++----- .../07c-interruptible-deepgram.py | 16 ++++----- .../07d-interruptible-elevenlabs-http.py | 18 +++++----- .../07d-interruptible-elevenlabs.py | 16 ++++----- .../07f-interruptible-azure-http.py | 12 ++----- .../foundational/07f-interruptible-azure.py | 12 ++----- .../07g-interruptible-openai-http.py | 16 ++++----- .../foundational/07g-interruptible-openai.py | 16 ++++----- .../07h-interruptible-openpipe.py | 12 ++----- .../foundational/07i-interruptible-xtts.py | 18 +++++----- .../foundational/07k-interruptible-lmnt.py | 16 ++++----- .../foundational/07l-interruptible-groq.py | 15 +++----- .../foundational/07m-interruptible-aws.py | 12 ++----- .../07n-interruptible-gemini-image.py | 14 +++----- .../foundational/07n-interruptible-gemini.py | 15 +++----- .../07n-interruptible-google-http.py | 12 ++----- .../foundational/07n-interruptible-google.py | 12 ++----- ...interruptible-assemblyai-turn-detection.py | 16 ++++----- .../07o-interruptible-assemblyai.py | 16 ++++----- .../07p-interruptible-krisp-viva.py | 16 ++++----- .../foundational/07p-interruptible-krisp.py | 16 ++++----- .../07q-interruptible-rime-http.py | 18 +++++----- .../foundational/07q-interruptible-rime.py | 16 ++++----- .../foundational/07r-interruptible-nvidia.py | 12 ++----- .../foundational/07t-interruptible-fish.py | 16 ++++----- .../07v-interruptible-neuphonic-http.py | 18 +++++----- .../07v-interruptible-neuphonic.py | 16 ++++----- .../foundational/07w-interruptible-fal.py | 16 ++++----- .../foundational/07x-interruptible-local.py | 16 ++++----- .../foundational/07y-interruptible-minimax.py | 18 +++++----- .../07z-interruptible-sarvam-http.py | 18 +++++----- .../foundational/07z-interruptible-sarvam.py | 16 ++++----- .../foundational/07za-interruptible-soniox.py | 16 ++++----- .../07zb-interruptible-inworld-http.py | 18 +++++----- .../07zb-interruptible-inworld.py | 16 ++++----- .../07zc-interruptible-asyncai-http.py | 18 +++++----- .../07zc-interruptible-asyncai.py | 16 ++++----- .../07zd-interruptible-aicoustics.py | 16 ++++----- .../foundational/07ze-interruptible-hume.py | 16 ++++----- .../07zf-interruptible-gradium.py | 16 ++++----- .../foundational/07zg-interruptible-camb.py | 18 ++++------ .../07zh-interruptible-hathora.py | 12 ++----- .../foundational/07zi-interruptible-piper.py | 16 ++++----- .../foundational/07zj-interruptible-kokoro.py | 16 ++++----- .../07zk-interruptible-resemble.py | 16 ++++----- .../foundational/08-custom-frame-processor.py | 16 ++++----- examples/foundational/10-wake-phrase.py | 24 +++++++------ examples/foundational/11-sound-effects.py | 14 +++----- .../foundational/12-describe-image-openai.py | 16 ++++----- .../12a-describe-image-anthropic.py | 16 ++++----- .../foundational/12b-describe-image-aws.py | 12 ++----- .../12c-describe-image-gemini-flash.py | 16 ++++----- examples/foundational/14-function-calling.py | 14 +++----- .../14c-function-calling-together.py | 10 ++---- .../14d-function-calling-anthropic-video.py | 16 ++++----- .../14d-function-calling-aws-video.py | 12 ++----- ...14d-function-calling-gemini-flash-video.py | 16 ++++----- .../14d-function-calling-moondream-video.py | 16 ++++----- .../14d-function-calling-openai-video.py | 16 ++++----- .../foundational/14f-function-calling-groq.py | 14 +++----- .../foundational/14g-function-calling-grok.py | 14 +++----- .../14h-function-calling-azure.py | 10 ++---- .../14i-function-calling-fireworks.py | 11 ++---- .../14k-function-calling-cerebras.py | 33 ++++++++---------- .../14l-function-calling-deepseek.py | 34 +++++++++---------- .../14m-function-calling-openrouter.py | 13 +++---- .../foundational/14q-function-calling-qwen.py | 15 ++++---- .../foundational/14r-function-calling-aws.py | 12 ++----- .../14s-function-calling-sambanova.py | 14 +++----- .../14t-function-calling-direct.py | 14 +++----- .../14u-function-calling-ollama.py | 14 +++----- .../14v-function-calling-openai.py | 14 +++----- .../14w-function-calling-mistral.py | 14 +++----- .../14x-function-calling-openpipe.py | 10 ++---- examples/foundational/15-switch-voices.py | 16 ++++----- examples/foundational/15a-switch-languages.py | 16 ++++----- .../16-gpu-container-local-bot.py | 12 ++----- examples/foundational/17-detect-user-idle.py | 16 ++++----- examples/foundational/21-tavus-transport.py | 16 ++++----- .../foundational/21a-tavus-video-service.py | 16 ++++----- .../foundational/23-bot-background-sound.py | 16 ++++----- .../foundational/24-user-mute-strategy.py | 16 ++++----- examples/foundational/27-simli-layer.py | 15 ++++---- .../foundational/28-user-assistant-turns.py | 15 ++++---- .../foundational/29-turn-tracking-observer.py | 16 ++++----- examples/foundational/30-observer.py | 16 ++++----- examples/foundational/34-audio-recording.py | 15 ++++---- .../foundational/36-user-email-gathering.py | 17 +++------- examples/foundational/37-mem0.py | 15 ++++---- examples/foundational/38-smart-turn-fal.py | 16 ++++----- .../38a-smart-turn-local-coreml.py | 16 ++++----- examples/foundational/38b-smart-turn-local.py | 16 ++++----- .../foundational/42-interruption-config.py | 16 ++++----- examples/foundational/43-heygen-transport.py | 16 ++++----- .../foundational/43a-heygen-video-service.py | 16 ++++----- .../foundational/44-voicemail-detection.py | 14 +++----- .../45-before-and-after-events.py | 16 ++++----- examples/foundational/47-sentry-metrics.py | 12 ++----- .../foundational/49a-thinking-anthropic.py | 19 +++-------- examples/foundational/49b-thinking-google.py | 19 +++-------- .../49c-thinking-functions-anthropic.py | 19 +++-------- .../49d-thinking-functions-google.py | 19 +++-------- examples/foundational/52-live-translation.py | 14 +++----- .../54-context-summarization-openai.py | 16 ++++----- .../54a-context-summarization-google.py | 16 ++++----- .../55a-update-settings-deepgram-flux-stt.py | 16 ++++----- ...-update-settings-deepgram-sagemaker-stt.py | 16 ++++----- .../55a-update-settings-deepgram-stt.py | 16 ++++----- .../55b-update-settings-azure-stt.py | 16 ++++----- .../55c-update-settings-google-stt.py | 16 ++++----- .../55d-update-settings-assemblyai-stt.py | 16 ++++----- .../55e-update-settings-gladia-stt.py | 16 ++++----- ...update-settings-elevenlabs-realtime-stt.py | 16 ++++----- .../55g-update-settings-elevenlabs-stt.py | 18 +++++----- .../55h-update-settings-speechmatics-stt.py | 16 ++++----- .../55i-update-settings-whisper-api-stt.py | 16 ++++----- .../55j-update-settings-sarvam-stt.py | 16 ++++----- .../55k-update-settings-soniox-stt.py | 16 ++++----- .../55l-update-settings-aws-transcribe-stt.py | 16 ++++----- .../55m-update-settings-cartesia-stt.py | 16 ++++----- .../55n-update-settings-cartesia-http-tts.py | 16 ++++----- .../55n-update-settings-cartesia-tts.py | 16 ++++----- ...55o-update-settings-elevenlabs-http-tts.py | 18 +++++----- .../55o-update-settings-elevenlabs-tts.py | 16 ++++----- .../55p-update-settings-openai-tts.py | 16 ++++----- .../55q-update-settings-deepgram-http-tts.py | 18 +++++----- ...-update-settings-deepgram-sagemaker-tts.py | 16 ++++----- .../55q-update-settings-deepgram-tts.py | 16 ++++----- .../55r-update-settings-azure-http-tts.py | 16 ++++----- .../55r-update-settings-azure-tts.py | 16 ++++----- .../55s-update-settings-google-http-tts.py | 16 ++++----- .../55s-update-settings-google-stream-tts.py | 16 ++++----- .../55u-update-settings-rime-http-tts.py | 18 +++++----- .../55u-update-settings-rime-tts.py | 16 ++++----- .../55v-update-settings-lmnt-tts.py | 16 ++++----- .../55w-update-settings-fish-tts.py | 16 ++++----- .../55x-update-settings-minimax-tts.py | 18 +++++----- .../55y-update-settings-groq-tts.py | 16 ++++----- .../55z-update-settings-hume-tts.py | 16 ++++----- ...55za-update-settings-neuphonic-http-tts.py | 18 +++++----- .../55za-update-settings-neuphonic-tts.py | 16 ++++----- .../55zb-update-settings-inworld-http-tts.py | 18 +++++----- .../55zb-update-settings-inworld-tts.py | 16 ++++----- .../55zc-update-settings-gemini-tts.py | 16 ++++----- .../55zd-update-settings-aws-polly-tts.py | 16 ++++----- .../55ze-update-settings-sarvam-http-tts.py | 18 +++++----- .../55ze-update-settings-sarvam-tts.py | 16 ++++----- .../55zf-update-settings-camb-tts.py | 16 ++++----- .../55zg-update-settings-hathora-tts.py | 16 ++++----- .../55zh-update-settings-resembleai-tts.py | 16 ++++----- .../55zi-update-settings-azure-llm.py | 12 ++----- .../55zi-update-settings-openai-llm.py | 16 ++++----- .../55zj-update-settings-anthropic-llm.py | 16 ++++----- .../55zk-update-settings-google-llm.py | 16 ++++----- .../55zk-update-settings-google-vertex-llm.py | 12 ++----- .../55zp-update-settings-aws-bedrock-llm.py | 12 ++----- .../55zq-update-settings-fal-stt.py | 16 ++++----- .../55zr-update-settings-gradium-stt.py | 16 ++++----- .../55zs-update-settings-hathora-stt.py | 16 ++++----- ...zt-update-settings-nvidia-segmented-stt.py | 16 ++++----- .../55zt-update-settings-nvidia-stt.py | 16 ++++----- ...5zu-update-settings-openai-realtime-stt.py | 16 ++++----- .../55zv-update-settings-asyncai-http-tts.py | 18 +++++----- .../55zv-update-settings-asyncai-tts.py | 16 ++++----- .../55zw-update-settings-gradium-tts.py | 16 ++++----- .../55zx-update-settings-cerebras-llm.py | 16 ++++----- .../55zy-update-settings-deepseek-llm.py | 16 ++++----- .../55zz-update-settings-fireworks-llm.py | 12 ++----- .../55zza-update-settings-grok-llm.py | 16 ++++----- .../55zzb-update-settings-groq-llm.py | 15 +++----- .../55zzc-update-settings-mistral-llm.py | 16 ++++----- .../55zzd-update-settings-nvidia-llm.py | 15 +++----- .../55zze-update-settings-ollama-llm.py | 16 ++++----- .../55zzf-update-settings-openrouter-llm.py | 16 ++++----- .../55zzh-update-settings-qwen-llm.py | 17 ++++------ .../55zzi-update-settings-sambanova-llm.py | 16 ++++----- .../55zzj-update-settings-together-llm.py | 12 ++----- .../55zzl-update-settings-nvidia-tts.py | 16 ++++----- .../55zzm-update-settings-speechmatics-tts.py | 18 +++++----- .../55zzn-update-settings-groq-stt.py | 16 ++++----- .../foundational/56-lemonslice-transport.py | 16 ++++----- 192 files changed, 1118 insertions(+), 1916 deletions(-) diff --git a/examples/foundational/02-llm-say-one-thing.py b/examples/foundational/02-llm-say-one-thing.py index f4fbfcbe0..9cfd7c39e 100644 --- a/examples/foundational/02-llm-say-one-thing.py +++ b/examples/foundational/02-llm-say-one-thing.py @@ -42,14 +42,10 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): voice_id="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady ) - llm = OpenAILLMService(api_key=os.getenv("OPENAI_API_KEY")) - - messages = [ - { - "role": "system", - "content": "You are an LLM in a WebRTC session, and this is a 'hello world' demo. Say hello to the world.", - } - ] + llm = OpenAILLMService( + api_key=os.getenv("OPENAI_API_KEY"), + system_instruction="You are an LLM in a WebRTC session, and this is a 'hello world' demo.", + ) task = PipelineTask( Pipeline([llm, tts, transport.output()]), @@ -59,7 +55,9 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): # Register an event handler so we can play the audio when the client joins @transport.event_handler("on_client_connected") async def on_client_connected(transport, client): - await task.queue_frames([LLMContextFrame(LLMContext(messages)), EndFrame()]) + context = LLMContext() + context.add_message({"role": "system", "content": "Say hello to the world."}) + await task.queue_frames([LLMContextFrame(context), EndFrame()]) runner = PipelineRunner(handle_sigint=runner_args.handle_sigint) diff --git a/examples/foundational/04-transports-small-webrtc.py b/examples/foundational/04-transports-small-webrtc.py index 7196dbb05..d29171dd2 100644 --- a/examples/foundational/04-transports-small-webrtc.py +++ b/examples/foundational/04-transports-small-webrtc.py @@ -70,16 +70,12 @@ async def run_example(webrtc_connection: SmallWebRTCConnection): voice_id="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady ) - llm = OpenAILLMService(api_key=os.getenv("OPENAI_API_KEY")) + llm = OpenAILLMService( + api_key=os.getenv("OPENAI_API_KEY"), + system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + ) - messages = [ - { - "role": "system", - "content": "You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", - }, - ] - - context = LLMContext(messages) + context = LLMContext() user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()), @@ -109,7 +105,7 @@ async def run_example(webrtc_connection: SmallWebRTCConnection): async def on_client_connected(transport, client): logger.info(f"Client connected") # Kick off the conversation. - messages.append({"role": "system", "content": "Please introduce yourself to the user."}) + context.add_message({"role": "system", "content": "Please introduce yourself to the user."}) await task.queue_frames([LLMRunFrame()]) @transport.event_handler("on_client_disconnected") diff --git a/examples/foundational/04a-transports-daily.py b/examples/foundational/04a-transports-daily.py index d1d88dbec..b0a7958ef 100644 --- a/examples/foundational/04a-transports-daily.py +++ b/examples/foundational/04a-transports-daily.py @@ -53,16 +53,13 @@ async def main(): voice_id="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady ) - llm = OpenAILLMService(api_key=os.getenv("OPENAI_API_KEY"), model="gpt-4o") + llm = OpenAILLMService( + api_key=os.getenv("OPENAI_API_KEY"), + model="gpt-4o", + system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + ) - messages = [ - { - "role": "system", - "content": "You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", - }, - ] - - context = LLMContext(messages) + context = LLMContext() user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()), @@ -91,7 +88,9 @@ async def main(): async def on_first_participant_joined(transport, participant): await transport.capture_participant_transcription(participant["id"]) # Kick off the conversation. - messages.append({"role": "system", "content": "Please introduce yourself to the user."}) + context.add_message( + {"role": "system", "content": "Please introduce yourself to the user."} + ) await task.queue_frames([LLMRunFrame()]) @transport.event_handler("on_participant_left") diff --git a/examples/foundational/04b-transports-livekit.py b/examples/foundational/04b-transports-livekit.py index b577b453e..e05c5ddc3 100644 --- a/examples/foundational/04b-transports-livekit.py +++ b/examples/foundational/04b-transports-livekit.py @@ -55,24 +55,17 @@ async def main(): stt = DeepgramSTTService(api_key=os.getenv("DEEPGRAM_API_KEY")) - llm = OpenAILLMService(api_key=os.getenv("OPENAI_API_KEY")) + llm = OpenAILLMService( + api_key=os.getenv("OPENAI_API_KEY"), + system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + ) tts = CartesiaTTSService( api_key=os.getenv("CARTESIA_API_KEY"), voice_id="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady ) - messages = [ - { - "role": "system", - "content": "You are a helpful LLM in a WebRTC call. " - "Your goal is to demonstrate your capabilities in a succinct way. " - "Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. " - "Respond to what the user said in a creative and helpful way.", - }, - ] - - context = LLMContext(messages) + context = LLMContext() user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()), diff --git a/examples/foundational/06-listen-and-respond.py b/examples/foundational/06-listen-and-respond.py index 14dee63ad..418b3b5af 100644 --- a/examples/foundational/06-listen-and-respond.py +++ b/examples/foundational/06-listen-and-respond.py @@ -86,18 +86,14 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): voice_id="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady ) - llm = OpenAILLMService(api_key=os.getenv("OPENAI_API_KEY")) + llm = OpenAILLMService( + api_key=os.getenv("OPENAI_API_KEY"), + system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + ) ml = MetricsLogger() - messages = [ - { - "role": "system", - "content": "You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", - }, - ] - - context = LLMContext(messages) + context = LLMContext() user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()), @@ -129,7 +125,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): async def on_client_connected(transport, client): logger.info(f"Client connected") # Kick off the conversation. - messages.append({"role": "system", "content": "Please introduce yourself to the user."}) + context.add_message({"role": "system", "content": "Please introduce yourself to the user."}) await task.queue_frames([LLMRunFrame()]) @transport.event_handler("on_client_disconnected") diff --git a/examples/foundational/06a-image-sync.py b/examples/foundational/06a-image-sync.py index be0e4fe78..f963aa339 100644 --- a/examples/foundational/06a-image-sync.py +++ b/examples/foundational/06a-image-sync.py @@ -103,16 +103,12 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): voice_id="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady ) - llm = OpenAILLMService(api_key=os.getenv("OPENAI_API_KEY")) + llm = OpenAILLMService( + api_key=os.getenv("OPENAI_API_KEY"), + system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + ) - messages = [ - { - "role": "system", - "content": "You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", - }, - ] - - context = LLMContext(messages) + context = LLMContext() user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()), diff --git a/examples/foundational/07-interruptible-cartesia-http.py b/examples/foundational/07-interruptible-cartesia-http.py index e65fb3750..558217413 100644 --- a/examples/foundational/07-interruptible-cartesia-http.py +++ b/examples/foundational/07-interruptible-cartesia-http.py @@ -59,16 +59,12 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): voice_id="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady ) - llm = OpenAILLMService(api_key=os.getenv("OPENAI_API_KEY")) + llm = OpenAILLMService( + api_key=os.getenv("OPENAI_API_KEY"), + system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + ) - messages = [ - { - "role": "system", - "content": "You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", - }, - ] - - context = LLMContext(messages) + context = LLMContext() user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()), @@ -99,7 +95,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): async def on_client_connected(transport, client): logger.info(f"Client connected") # Kick off the conversation. - messages.append({"role": "system", "content": "Please introduce yourself to the user."}) + context.add_message({"role": "system", "content": "Please introduce yourself to the user."}) await task.queue_frames([LLMRunFrame()]) @transport.event_handler("on_client_disconnected") diff --git a/examples/foundational/07-interruptible.py b/examples/foundational/07-interruptible.py index 074e091ea..3f97e5028 100644 --- a/examples/foundational/07-interruptible.py +++ b/examples/foundational/07-interruptible.py @@ -62,16 +62,12 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): # text_aggregation_mode=TextAggregationMode.TOKEN, ) - llm = OpenAILLMService(api_key=os.getenv("OPENAI_API_KEY")) + llm = OpenAILLMService( + api_key=os.getenv("OPENAI_API_KEY"), + system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + ) - messages = [ - { - "role": "system", - "content": "You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", - }, - ] - - context = LLMContext(messages) + context = LLMContext() user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()), @@ -102,7 +98,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): async def on_client_connected(transport, client): logger.info(f"Client connected") # Kick off the conversation. - messages.append({"role": "system", "content": "Please introduce yourself to the user."}) + context.add_message({"role": "system", "content": "Please introduce yourself to the user."}) await task.queue_frames([LLMRunFrame()]) @transport.event_handler("on_client_disconnected") diff --git a/examples/foundational/07c-interruptible-deepgram-flux.py b/examples/foundational/07c-interruptible-deepgram-flux.py index d2bcceaf7..3f2d6e28d 100644 --- a/examples/foundational/07c-interruptible-deepgram-flux.py +++ b/examples/foundational/07c-interruptible-deepgram-flux.py @@ -61,16 +61,12 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): tts = DeepgramTTSService(api_key=os.getenv("DEEPGRAM_API_KEY"), voice="aura-2-andromeda-en") - llm = OpenAILLMService(api_key=os.getenv("OPENAI_API_KEY")) + llm = OpenAILLMService( + api_key=os.getenv("OPENAI_API_KEY"), + system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + ) - messages = [ - { - "role": "system", - "content": "You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", - }, - ] - - context = LLMContext(messages) + context = LLMContext() user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, user_params=LLMUserAggregatorParams( @@ -104,7 +100,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): async def on_client_connected(transport, client): logger.info(f"Client connected") # Kick off the conversation. - messages.append({"role": "system", "content": "Please introduce yourself to the user."}) + context.add_message({"role": "system", "content": "Please introduce yourself to the user."}) await task.queue_frames([LLMRunFrame()]) @transport.event_handler("on_client_disconnected") diff --git a/examples/foundational/07c-interruptible-deepgram-http.py b/examples/foundational/07c-interruptible-deepgram-http.py index 53fc77722..6955ccbd1 100644 --- a/examples/foundational/07c-interruptible-deepgram-http.py +++ b/examples/foundational/07c-interruptible-deepgram-http.py @@ -63,14 +63,12 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): aiohttp_session=session, ) - llm = OpenAILLMService(api_key=os.getenv("OPENAI_API_KEY")) + llm = OpenAILLMService( + api_key=os.getenv("OPENAI_API_KEY"), + system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + ) - messages = [ - { - "role": "system", - "content": "You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", - }, - ] + messages = [] context = LLMContext(messages) user_aggregator, assistant_aggregator = LLMContextAggregatorPair( @@ -103,7 +101,9 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): async def on_client_connected(transport, client): logger.info(f"Client connected") # Kick off the conversation. - messages.append({"role": "system", "content": "Please introduce yourself to the user."}) + context.add_message( + {"role": "system", "content": "Please introduce yourself to the user."} + ) await task.queue_frames([LLMRunFrame()]) @transport.event_handler("on_client_disconnected") diff --git a/examples/foundational/07c-interruptible-deepgram-sagemaker.py b/examples/foundational/07c-interruptible-deepgram-sagemaker.py index 7a4cd4297..8c7fc6556 100644 --- a/examples/foundational/07c-interruptible-deepgram-sagemaker.py +++ b/examples/foundational/07c-interruptible-deepgram-sagemaker.py @@ -76,16 +76,10 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): aws_region=os.getenv("AWS_REGION"), model="us.amazon.nova-pro-v1:0", params=AWSBedrockLLMService.InputParams(temperature=0.8), + system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", ) - messages = [ - { - "role": "system", - "content": "You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", - }, - ] - - context = LLMContext(messages) + context = LLMContext() user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()), @@ -116,7 +110,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): async def on_client_connected(transport, client): logger.info(f"Client connected") # Kick off the conversation. - messages.append({"role": "system", "content": "Please introduce yourself to the user."}) + context.add_message({"role": "system", "content": "Please introduce yourself to the user."}) await task.queue_frames([LLMRunFrame()]) @transport.event_handler("on_client_disconnected") diff --git a/examples/foundational/07c-interruptible-deepgram-vad.py b/examples/foundational/07c-interruptible-deepgram-vad.py index 62fb29dff..aaa81fc90 100644 --- a/examples/foundational/07c-interruptible-deepgram-vad.py +++ b/examples/foundational/07c-interruptible-deepgram-vad.py @@ -61,16 +61,12 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): tts = DeepgramTTSService(api_key=os.getenv("DEEPGRAM_API_KEY"), voice="aura-2-andromeda-en") - llm = OpenAILLMService(api_key=os.getenv("OPENAI_API_KEY")) + llm = OpenAILLMService( + api_key=os.getenv("OPENAI_API_KEY"), + system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + ) - messages = [ - { - "role": "system", - "content": "You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", - }, - ] - - context = LLMContext(messages) + context = LLMContext() user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, user_params=LLMUserAggregatorParams(user_turn_strategies=ExternalUserTurnStrategies()), @@ -101,7 +97,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): async def on_client_connected(transport, client): logger.info(f"Client connected") # Kick off the conversation. - messages.append({"role": "system", "content": "Please introduce yourself to the user."}) + context.add_message({"role": "system", "content": "Please introduce yourself to the user."}) await task.queue_frames([LLMRunFrame()]) @transport.event_handler("on_client_disconnected") diff --git a/examples/foundational/07c-interruptible-deepgram.py b/examples/foundational/07c-interruptible-deepgram.py index 0133ad150..1cbfc72cc 100644 --- a/examples/foundational/07c-interruptible-deepgram.py +++ b/examples/foundational/07c-interruptible-deepgram.py @@ -57,16 +57,12 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): tts = DeepgramTTSService(api_key=os.getenv("DEEPGRAM_API_KEY"), voice="aura-2-andromeda-en") - llm = OpenAILLMService(api_key=os.getenv("OPENAI_API_KEY")) + llm = OpenAILLMService( + api_key=os.getenv("OPENAI_API_KEY"), + system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + ) - messages = [ - { - "role": "system", - "content": "You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", - }, - ] - - context = LLMContext(messages) + context = LLMContext() user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()), @@ -97,7 +93,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): async def on_client_connected(transport, client): logger.info(f"Client connected") # Kick off the conversation. - messages.append({"role": "system", "content": "Please introduce yourself to the user."}) + context.add_message({"role": "system", "content": "Please introduce yourself to the user."}) await task.queue_frames([LLMRunFrame()]) @transport.event_handler("on_client_disconnected") diff --git a/examples/foundational/07d-interruptible-elevenlabs-http.py b/examples/foundational/07d-interruptible-elevenlabs-http.py index 0299c1300..85cffc270 100644 --- a/examples/foundational/07d-interruptible-elevenlabs-http.py +++ b/examples/foundational/07d-interruptible-elevenlabs-http.py @@ -67,16 +67,12 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): aiohttp_session=session, ) - llm = OpenAILLMService(api_key=os.getenv("OPENAI_API_KEY")) + llm = OpenAILLMService( + api_key=os.getenv("OPENAI_API_KEY"), + system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + ) - messages = [ - { - "role": "system", - "content": "You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", - }, - ] - - context = LLMContext(messages) + context = LLMContext() user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()), @@ -107,7 +103,9 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): async def on_client_connected(transport, client): logger.info(f"Client connected") # Kick off the conversation. - messages.append({"role": "system", "content": "Please introduce yourself to the user."}) + context.add_message( + {"role": "system", "content": "Please introduce yourself to the user."} + ) await task.queue_frames([LLMRunFrame()]) @transport.event_handler("on_client_disconnected") diff --git a/examples/foundational/07d-interruptible-elevenlabs.py b/examples/foundational/07d-interruptible-elevenlabs.py index feaf41255..b55345f33 100644 --- a/examples/foundational/07d-interruptible-elevenlabs.py +++ b/examples/foundational/07d-interruptible-elevenlabs.py @@ -60,16 +60,12 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): voice_id=os.getenv("ELEVENLABS_VOICE_ID", ""), ) - llm = OpenAILLMService(api_key=os.getenv("OPENAI_API_KEY")) + llm = OpenAILLMService( + api_key=os.getenv("OPENAI_API_KEY"), + system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + ) - messages = [ - { - "role": "system", - "content": "You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", - }, - ] - - context = LLMContext(messages) + context = LLMContext() user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()), @@ -100,7 +96,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): async def on_client_connected(transport, client): logger.info(f"Client connected") # Kick off the conversation. - messages.append({"role": "system", "content": "Please introduce yourself to the user."}) + context.add_message({"role": "system", "content": "Please introduce yourself to the user."}) await task.queue_frames([LLMRunFrame()]) @transport.event_handler("on_client_disconnected") diff --git a/examples/foundational/07f-interruptible-azure-http.py b/examples/foundational/07f-interruptible-azure-http.py index 3d8bdf073..1946f66ee 100644 --- a/examples/foundational/07f-interruptible-azure-http.py +++ b/examples/foundational/07f-interruptible-azure-http.py @@ -66,16 +66,10 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): api_key=os.getenv("AZURE_CHATGPT_API_KEY"), endpoint=os.getenv("AZURE_CHATGPT_ENDPOINT"), model=os.getenv("AZURE_CHATGPT_MODEL"), + system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", ) - messages = [ - { - "role": "system", - "content": "You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", - }, - ] - - context = LLMContext(messages) + context = LLMContext() user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()), @@ -106,7 +100,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): async def on_client_connected(transport, client): logger.info(f"Client connected") # Kick off the conversation. - messages.append({"role": "system", "content": "Please introduce yourself to the user."}) + context.add_message({"role": "system", "content": "Please introduce yourself to the user."}) await task.queue_frames([LLMRunFrame()]) @transport.event_handler("on_client_disconnected") diff --git a/examples/foundational/07f-interruptible-azure.py b/examples/foundational/07f-interruptible-azure.py index 03b399a5a..68f5a72f9 100644 --- a/examples/foundational/07f-interruptible-azure.py +++ b/examples/foundational/07f-interruptible-azure.py @@ -66,16 +66,10 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): api_key=os.getenv("AZURE_CHATGPT_API_KEY"), endpoint=os.getenv("AZURE_CHATGPT_ENDPOINT"), model=os.getenv("AZURE_CHATGPT_MODEL"), + system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", ) - messages = [ - { - "role": "system", - "content": "You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", - }, - ] - - context = LLMContext(messages) + context = LLMContext() user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()), @@ -106,7 +100,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): async def on_client_connected(transport, client): logger.info(f"Client connected") # Kick off the conversation. - messages.append({"role": "system", "content": "Please introduce yourself to the user."}) + context.add_message({"role": "system", "content": "Please introduce yourself to the user."}) await task.queue_frames([LLMRunFrame()]) @transport.event_handler("on_client_disconnected") diff --git a/examples/foundational/07g-interruptible-openai-http.py b/examples/foundational/07g-interruptible-openai-http.py index 65b2f8b9b..05c98ca59 100644 --- a/examples/foundational/07g-interruptible-openai-http.py +++ b/examples/foundational/07g-interruptible-openai-http.py @@ -60,16 +60,12 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): tts = OpenAITTSService(api_key=os.getenv("OPENAI_API_KEY"), voice="ballad") - llm = OpenAILLMService(api_key=os.getenv("OPENAI_API_KEY")) + llm = OpenAILLMService( + api_key=os.getenv("OPENAI_API_KEY"), + system_instruction="You are very knowledgable about dogs. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + ) - messages = [ - { - "role": "system", - "content": "You are very knowledgable about dogs. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", - }, - ] - - context = LLMContext(messages) + context = LLMContext() user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()), @@ -101,7 +97,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): async def on_client_connected(transport, client): logger.info(f"Client connected") # Kick off the conversation. - messages.append({"role": "system", "content": "Please introduce yourself to the user."}) + context.add_message({"role": "system", "content": "Please introduce yourself to the user."}) await task.queue_frames([LLMRunFrame()]) @transport.event_handler("on_client_disconnected") diff --git a/examples/foundational/07g-interruptible-openai.py b/examples/foundational/07g-interruptible-openai.py index 551742a57..a29e8210f 100644 --- a/examples/foundational/07g-interruptible-openai.py +++ b/examples/foundational/07g-interruptible-openai.py @@ -66,16 +66,12 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): tts = OpenAITTSService(api_key=os.getenv("OPENAI_API_KEY"), voice="ballad") - llm = OpenAILLMService(api_key=os.getenv("OPENAI_API_KEY")) + llm = OpenAILLMService( + api_key=os.getenv("OPENAI_API_KEY"), + system_instruction="You are very knowledgable about dogs. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + ) - messages = [ - { - "role": "system", - "content": "You are very knowledgable about dogs. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", - }, - ] - - context = LLMContext(messages) + context = LLMContext() user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()), @@ -107,7 +103,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): async def on_client_connected(transport, client): logger.info(f"Client connected") # Kick off the conversation. - messages.append({"role": "system", "content": "Please introduce yourself to the user."}) + context.add_message({"role": "system", "content": "Please introduce yourself to the user."}) await task.queue_frames([LLMRunFrame()]) @transport.event_handler("on_client_disconnected") diff --git a/examples/foundational/07h-interruptible-openpipe.py b/examples/foundational/07h-interruptible-openpipe.py index 052ddfd14..e3ddc05b8 100644 --- a/examples/foundational/07h-interruptible-openpipe.py +++ b/examples/foundational/07h-interruptible-openpipe.py @@ -65,16 +65,10 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): api_key=os.getenv("OPENAI_API_KEY"), openpipe_api_key=os.getenv("OPENPIPE_API_KEY"), tags={"conversation_id": f"pipecat-{timestamp}"}, + system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", ) - messages = [ - { - "role": "system", - "content": "You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", - }, - ] - - context = LLMContext(messages) + context = LLMContext() user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()), @@ -105,7 +99,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): async def on_client_connected(transport, client): logger.info(f"Client connected") # Kick off the conversation. - messages.append({"role": "system", "content": "Please introduce yourself to the user."}) + context.add_message({"role": "system", "content": "Please introduce yourself to the user."}) await task.queue_frames([LLMRunFrame()]) @transport.event_handler("on_client_disconnected") diff --git a/examples/foundational/07i-interruptible-xtts.py b/examples/foundational/07i-interruptible-xtts.py index 8b2b3d6d5..00883e37f 100644 --- a/examples/foundational/07i-interruptible-xtts.py +++ b/examples/foundational/07i-interruptible-xtts.py @@ -63,16 +63,12 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): base_url="http://localhost:8000", ) - llm = OpenAILLMService(api_key=os.getenv("OPENAI_API_KEY")) + llm = OpenAILLMService( + api_key=os.getenv("OPENAI_API_KEY"), + system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + ) - messages = [ - { - "role": "system", - "content": "You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", - }, - ] - - context = LLMContext(messages) + context = LLMContext() user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()), @@ -103,7 +99,9 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): async def on_client_connected(transport, client): logger.info(f"Client connected") # Kick off the conversation. - messages.append({"role": "system", "content": "Please introduce yourself to the user."}) + context.add_message( + {"role": "system", "content": "Please introduce yourself to the user."} + ) await task.queue_frames([LLMRunFrame()]) @transport.event_handler("on_client_disconnected") diff --git a/examples/foundational/07k-interruptible-lmnt.py b/examples/foundational/07k-interruptible-lmnt.py index a6d1c56b4..246caee19 100644 --- a/examples/foundational/07k-interruptible-lmnt.py +++ b/examples/foundational/07k-interruptible-lmnt.py @@ -56,16 +56,12 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): tts = LmntTTSService(api_key=os.getenv("LMNT_API_KEY"), voice_id="morgan") - llm = OpenAILLMService(api_key=os.getenv("OPENAI_API_KEY")) + llm = OpenAILLMService( + api_key=os.getenv("OPENAI_API_KEY"), + system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + ) - messages = [ - { - "role": "system", - "content": "You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", - }, - ] - - context = LLMContext(messages) + context = LLMContext() user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()), @@ -96,7 +92,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): async def on_client_connected(transport, client): logger.info(f"Client connected") # Kick off the conversation. - messages.append({"role": "system", "content": "Please introduce yourself to the user."}) + context.add_message({"role": "system", "content": "Please introduce yourself to the user."}) await task.queue_frames([LLMRunFrame()]) @transport.event_handler("on_client_disconnected") diff --git a/examples/foundational/07l-interruptible-groq.py b/examples/foundational/07l-interruptible-groq.py index 5c92814e3..5a16d789e 100644 --- a/examples/foundational/07l-interruptible-groq.py +++ b/examples/foundational/07l-interruptible-groq.py @@ -55,19 +55,14 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): stt = GroqSTTService(api_key=os.getenv("GROQ_API_KEY")) llm = GroqLLMService( - api_key=os.getenv("GROQ_API_KEY"), model="meta-llama/llama-4-maverick-17b-128e-instruct" + api_key=os.getenv("GROQ_API_KEY"), + model="meta-llama/llama-4-maverick-17b-128e-instruct", + system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", ) tts = GroqTTSService(api_key=os.getenv("GROQ_API_KEY")) - messages = [ - { - "role": "system", - "content": "You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", - }, - ] - - context = LLMContext(messages) + context = LLMContext() user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()), @@ -98,7 +93,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): async def on_client_connected(transport, client): logger.info(f"Client connected") # Kick off the conversation. - messages.append({"role": "system", "content": "Please introduce yourself to the user."}) + context.add_message({"role": "system", "content": "Please introduce yourself to the user."}) await task.queue_frames([LLMRunFrame()]) @transport.event_handler("on_client_disconnected") diff --git a/examples/foundational/07m-interruptible-aws.py b/examples/foundational/07m-interruptible-aws.py index eac193531..b30220bcd 100644 --- a/examples/foundational/07m-interruptible-aws.py +++ b/examples/foundational/07m-interruptible-aws.py @@ -62,16 +62,10 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): aws_region="us-west-2", model="us.anthropic.claude-haiku-4-5-20251001-v1:0", params=AWSBedrockLLMService.InputParams(temperature=0.8), + system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", ) - messages = [ - { - "role": "system", - "content": "You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", - }, - ] - - context = LLMContext(messages) + context = LLMContext() user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()), @@ -102,7 +96,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): async def on_client_connected(transport, client): logger.info(f"Client connected") # Kick off the conversation. - messages.append({"role": "user", "content": "Please introduce yourself to the user."}) + context.add_message({"role": "user", "content": "Please introduce yourself to the user."}) await task.queue_frames([LLMRunFrame()]) @transport.event_handler("on_client_disconnected") diff --git a/examples/foundational/07n-interruptible-gemini-image.py b/examples/foundational/07n-interruptible-gemini-image.py index 21fea9d1b..b7d3281b9 100644 --- a/examples/foundational/07n-interruptible-gemini-image.py +++ b/examples/foundational/07n-interruptible-gemini-image.py @@ -83,17 +83,11 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): llm = GoogleLLMService( api_key=os.getenv("GOOGLE_API_KEY"), model="gemini-2.5-flash-image", - # model="gemini-3-pro-image-preview", # A more powerful model, but slower + # model="gemini-3-pro-image-preview", # A more powerful model, but slower, + system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", ) - messages = [ - { - "role": "system", - "content": "You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", - }, - ] - - context = LLMContext(messages) + context = LLMContext() user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()), @@ -124,7 +118,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): async def on_client_connected(transport, client): logger.info(f"Client connected") # Kick off the conversation with a styled introduction - messages.append({"role": "system", "content": "Please introduce yourself to the user."}) + context.add_message({"role": "system", "content": "Please introduce yourself to the user."}) await task.queue_frames([LLMRunFrame()]) @transport.event_handler("on_client_disconnected") diff --git a/examples/foundational/07n-interruptible-gemini.py b/examples/foundational/07n-interruptible-gemini.py index 08315fcfa..74f732926 100644 --- a/examples/foundational/07n-interruptible-gemini.py +++ b/examples/foundational/07n-interruptible-gemini.py @@ -71,13 +71,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): llm = GoogleLLMService( api_key=os.getenv("GOOGLE_API_KEY"), model="gemini-2.5-flash", - ) - - # System message that instructs the AI on how to speak - messages = [ - { - "role": "system", - "content": """You are a helpful AI assistant in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. + system_instruction="""You are a helpful AI assistant in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. IMPORTANT: You're using Gemini TTS which supports expressive markup tags. You can use these tags in your responses: - [sigh] - Insert a sigh sound @@ -95,10 +89,9 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): - "The answer is... [long pause] ...42!" Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.""", - }, - ] + ) - context = LLMContext(messages) + context = LLMContext() user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()), @@ -129,7 +122,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): async def on_client_connected(transport, client): logger.info(f"Client connected") # Kick off the conversation - messages.append( + context.add_message( { "role": "system", "content": "You are an AI assistant. You can help with a variety of tasks. Introduce yourself and ask the user what they would like to know.", diff --git a/examples/foundational/07n-interruptible-google-http.py b/examples/foundational/07n-interruptible-google-http.py index e1fd0002f..e5f82ffc5 100644 --- a/examples/foundational/07n-interruptible-google-http.py +++ b/examples/foundational/07n-interruptible-google-http.py @@ -72,16 +72,10 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): # params=GoogleLLMService.InputParams( # thinking=GoogleLLMService.ThinkingConfig(thinking_budget=4096) # ), + system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", ) - messages = [ - { - "role": "system", - "content": "You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", - }, - ] - - context = LLMContext(messages) + context = LLMContext() user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()), @@ -112,7 +106,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): async def on_client_connected(transport, client): logger.info(f"Client connected") # Kick off the conversation. - messages.append({"role": "system", "content": "Please introduce yourself to the user."}) + context.add_message({"role": "system", "content": "Please introduce yourself to the user."}) await task.queue_frames([LLMRunFrame()]) @transport.event_handler("on_client_disconnected") diff --git a/examples/foundational/07n-interruptible-google.py b/examples/foundational/07n-interruptible-google.py index e5c792c12..090fdbbdc 100644 --- a/examples/foundational/07n-interruptible-google.py +++ b/examples/foundational/07n-interruptible-google.py @@ -72,16 +72,10 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): # params=GoogleLLMService.InputParams( # thinking=GoogleLLMService.ThinkingConfig(thinking_budget=4096) # ), + system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", ) - messages = [ - { - "role": "system", - "content": "You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", - }, - ] - - context = LLMContext(messages) + context = LLMContext() user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()), @@ -112,7 +106,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): async def on_client_connected(transport, client): logger.info(f"Client connected") # Kick off the conversation. - messages.append({"role": "system", "content": "Please introduce yourself to the user."}) + context.add_message({"role": "system", "content": "Please introduce yourself to the user."}) await task.queue_frames([LLMRunFrame()]) @transport.event_handler("on_client_disconnected") diff --git a/examples/foundational/07o-interruptible-assemblyai-turn-detection.py b/examples/foundational/07o-interruptible-assemblyai-turn-detection.py index cf052ada4..13f596136 100644 --- a/examples/foundational/07o-interruptible-assemblyai-turn-detection.py +++ b/examples/foundational/07o-interruptible-assemblyai-turn-detection.py @@ -111,16 +111,12 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): voice_id="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady ) - llm = OpenAILLMService(api_key=os.getenv("OPENAI_API_KEY")) + llm = OpenAILLMService( + api_key=os.getenv("OPENAI_API_KEY"), + system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + ) - messages = [ - { - "role": "system", - "content": "You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", - }, - ] - - context = LLMContext(messages) + context = LLMContext() user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, user_params=LLMUserAggregatorParams( @@ -154,7 +150,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): async def on_client_connected(transport, client): logger.info(f"Client connected") # Kick off the conversation. - messages.append({"role": "system", "content": "Please introduce yourself to the user."}) + context.add_message({"role": "system", "content": "Please introduce yourself to the user."}) await task.queue_frames([LLMRunFrame()]) @transport.event_handler("on_client_disconnected") diff --git a/examples/foundational/07o-interruptible-assemblyai.py b/examples/foundational/07o-interruptible-assemblyai.py index b65116b46..8378f7bba 100644 --- a/examples/foundational/07o-interruptible-assemblyai.py +++ b/examples/foundational/07o-interruptible-assemblyai.py @@ -62,16 +62,12 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): voice_id="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady ) - llm = OpenAILLMService(api_key=os.getenv("OPENAI_API_KEY")) + llm = OpenAILLMService( + api_key=os.getenv("OPENAI_API_KEY"), + system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + ) - messages = [ - { - "role": "system", - "content": "You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", - }, - ] - - context = LLMContext(messages) + context = LLMContext() user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()), @@ -102,7 +98,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): async def on_client_connected(transport, client): logger.info(f"Client connected") # Kick off the conversation. - messages.append({"role": "system", "content": "Please introduce yourself to the user."}) + context.add_message({"role": "system", "content": "Please introduce yourself to the user."}) await task.queue_frames([LLMRunFrame()]) @transport.event_handler("on_client_disconnected") diff --git a/examples/foundational/07p-interruptible-krisp-viva.py b/examples/foundational/07p-interruptible-krisp-viva.py index 24929a825..4df652ae0 100644 --- a/examples/foundational/07p-interruptible-krisp-viva.py +++ b/examples/foundational/07p-interruptible-krisp-viva.py @@ -87,16 +87,12 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): api_key=os.getenv("CARTESIA_API_KEY"), voice_id="71a7ad14-091c-4e8e-a314-022ece01c121" ) - llm = OpenAILLMService(api_key=os.getenv("OPENAI_API_KEY")) + llm = OpenAILLMService( + api_key=os.getenv("OPENAI_API_KEY"), + system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + ) - messages = [ - { - "role": "system", - "content": "You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", - }, - ] - - context = LLMContext(messages) + context = LLMContext() user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, user_params=LLMUserAggregatorParams( @@ -133,7 +129,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): async def on_client_connected(transport, client): logger.info(f"Client connected") # Kick off the conversation. - messages.append({"role": "system", "content": "Please introduce yourself to the user."}) + context.add_message({"role": "system", "content": "Please introduce yourself to the user."}) await task.queue_frames([LLMRunFrame()]) @transport.event_handler("on_client_disconnected") diff --git a/examples/foundational/07p-interruptible-krisp.py b/examples/foundational/07p-interruptible-krisp.py index 6a17a57eb..ad737ba05 100644 --- a/examples/foundational/07p-interruptible-krisp.py +++ b/examples/foundational/07p-interruptible-krisp.py @@ -60,16 +60,12 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): tts = DeepgramTTSService(api_key=os.getenv("DEEPGRAM_API_KEY"), voice="aura-helios-en") - llm = OpenAILLMService(api_key=os.getenv("OPENAI_API_KEY")) + llm = OpenAILLMService( + api_key=os.getenv("OPENAI_API_KEY"), + system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + ) - messages = [ - { - "role": "system", - "content": "You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", - }, - ] - - context = LLMContext(messages) + context = LLMContext() user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()), @@ -100,7 +96,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): async def on_client_connected(transport, client): logger.info(f"Client connected") # Kick off the conversation. - messages.append({"role": "system", "content": "Please introduce yourself to the user."}) + context.add_message({"role": "system", "content": "Please introduce yourself to the user."}) await task.queue_frames([LLMRunFrame()]) @transport.event_handler("on_client_disconnected") diff --git a/examples/foundational/07q-interruptible-rime-http.py b/examples/foundational/07q-interruptible-rime-http.py index 902b6b231..4e390b123 100644 --- a/examples/foundational/07q-interruptible-rime-http.py +++ b/examples/foundational/07q-interruptible-rime-http.py @@ -65,16 +65,12 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): aiohttp_session=session, ) - llm = OpenAILLMService(api_key=os.getenv("OPENAI_API_KEY")) + llm = OpenAILLMService( + api_key=os.getenv("OPENAI_API_KEY"), + system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + ) - messages = [ - { - "role": "system", - "content": "You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", - }, - ] - - context = LLMContext(messages) + context = LLMContext() user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()), @@ -105,7 +101,9 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): async def on_client_connected(transport, client): logger.info(f"Client connected") # Kick off the conversation. - messages.append({"role": "system", "content": "Please introduce yourself to the user."}) + context.add_message( + {"role": "system", "content": "Please introduce yourself to the user."} + ) await task.queue_frames([LLMRunFrame()]) @transport.event_handler("on_client_disconnected") diff --git a/examples/foundational/07q-interruptible-rime.py b/examples/foundational/07q-interruptible-rime.py index 27e010273..cebf6bfd0 100644 --- a/examples/foundational/07q-interruptible-rime.py +++ b/examples/foundational/07q-interruptible-rime.py @@ -59,16 +59,12 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): voice_id="luna", ) - llm = OpenAILLMService(api_key=os.getenv("OPENAI_API_KEY")) + llm = OpenAILLMService( + api_key=os.getenv("OPENAI_API_KEY"), + system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + ) - messages = [ - { - "role": "system", - "content": "You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", - }, - ] - - context = LLMContext(messages) + context = LLMContext() user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()), @@ -99,7 +95,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): async def on_client_connected(transport, client): logger.info(f"Client connected") # Kick off the conversation. - messages.append({"role": "system", "content": "Please introduce yourself to the user."}) + context.add_message({"role": "system", "content": "Please introduce yourself to the user."}) await task.queue_frames([LLMRunFrame()]) @transport.event_handler("on_client_disconnected") diff --git a/examples/foundational/07r-interruptible-nvidia.py b/examples/foundational/07r-interruptible-nvidia.py index d3e34c61f..f50667267 100644 --- a/examples/foundational/07r-interruptible-nvidia.py +++ b/examples/foundational/07r-interruptible-nvidia.py @@ -57,18 +57,12 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): llm = NvidiaLLMService( api_key=os.getenv("NVIDIA_API_KEY"), model="meta/llama-3.3-70b-instruct", + system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", ) tts = NvidiaTTSService(api_key=os.getenv("NVIDIA_API_KEY")) - messages = [ - { - "role": "system", - "content": "You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", - }, - ] - - context = LLMContext(messages) + context = LLMContext() user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()), @@ -99,7 +93,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): async def on_client_connected(transport, client): logger.info(f"Client connected") # Kick off the conversation. - messages.append({"role": "system", "content": "Please introduce yourself to the user."}) + context.add_message({"role": "system", "content": "Please introduce yourself to the user."}) await task.queue_frames([LLMRunFrame()]) @transport.event_handler("on_client_disconnected") diff --git a/examples/foundational/07t-interruptible-fish.py b/examples/foundational/07t-interruptible-fish.py index 2df978475..8b4152103 100644 --- a/examples/foundational/07t-interruptible-fish.py +++ b/examples/foundational/07t-interruptible-fish.py @@ -60,16 +60,12 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): model="4ce7e917cedd4bc2bb2e6ff3a46acaa1", # Barack Obama ) - llm = OpenAILLMService(api_key=os.getenv("OPENAI_API_KEY")) + llm = OpenAILLMService( + api_key=os.getenv("OPENAI_API_KEY"), + system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + ) - messages = [ - { - "role": "system", - "content": "You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", - }, - ] - - context = LLMContext(messages) + context = LLMContext() user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()), @@ -100,7 +96,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): async def on_client_connected(transport, client): logger.info(f"Client connected") # Kick off the conversation. - messages.append({"role": "system", "content": "Please introduce yourself to the user."}) + context.add_message({"role": "system", "content": "Please introduce yourself to the user."}) await task.queue_frames([LLMRunFrame()]) @transport.event_handler("on_client_disconnected") diff --git a/examples/foundational/07v-interruptible-neuphonic-http.py b/examples/foundational/07v-interruptible-neuphonic-http.py index d3f27613e..60a08e623 100644 --- a/examples/foundational/07v-interruptible-neuphonic-http.py +++ b/examples/foundational/07v-interruptible-neuphonic-http.py @@ -64,16 +64,12 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): aiohttp_session=session, ) - llm = OpenAILLMService(api_key=os.getenv("OPENAI_API_KEY")) + llm = OpenAILLMService( + api_key=os.getenv("OPENAI_API_KEY"), + system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + ) - messages = [ - { - "role": "system", - "content": "You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", - }, - ] - - context = LLMContext(messages) + context = LLMContext() user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()), @@ -104,7 +100,9 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): async def on_client_connected(transport, client): logger.info(f"Client connected") # Kick off the conversation. - messages.append({"role": "system", "content": "Please introduce yourself to the user."}) + context.add_message( + {"role": "system", "content": "Please introduce yourself to the user."} + ) await task.queue_frames([LLMRunFrame()]) @transport.event_handler("on_client_disconnected") diff --git a/examples/foundational/07v-interruptible-neuphonic.py b/examples/foundational/07v-interruptible-neuphonic.py index c1ee64f3e..02d6862a8 100644 --- a/examples/foundational/07v-interruptible-neuphonic.py +++ b/examples/foundational/07v-interruptible-neuphonic.py @@ -59,16 +59,12 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): voice_id="fc854436-2dac-4d21-aa69-ae17b54e98eb", # Emily ) - llm = OpenAILLMService(api_key=os.getenv("OPENAI_API_KEY")) + llm = OpenAILLMService( + api_key=os.getenv("OPENAI_API_KEY"), + system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + ) - messages = [ - { - "role": "system", - "content": "You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", - }, - ] - - context = LLMContext(messages) + context = LLMContext() user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()), @@ -99,7 +95,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): async def on_client_connected(transport, client): logger.info(f"Client connected") # Kick off the conversation. - messages.append({"role": "system", "content": "Please introduce yourself to the user."}) + context.add_message({"role": "system", "content": "Please introduce yourself to the user."}) await task.queue_frames([LLMRunFrame()]) @transport.event_handler("on_client_disconnected") diff --git a/examples/foundational/07w-interruptible-fal.py b/examples/foundational/07w-interruptible-fal.py index 41fad024a..2d1886ddb 100644 --- a/examples/foundational/07w-interruptible-fal.py +++ b/examples/foundational/07w-interruptible-fal.py @@ -62,16 +62,12 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): voice_id="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady ) - llm = OpenAILLMService(api_key=os.getenv("OPENAI_API_KEY")) + llm = OpenAILLMService( + api_key=os.getenv("OPENAI_API_KEY"), + system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + ) - messages = [ - { - "role": "system", - "content": "You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", - }, - ] - - context = LLMContext(messages) + context = LLMContext() user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()), @@ -102,7 +98,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): async def on_client_connected(transport, client): logger.info(f"Client connected") # Kick off the conversation. - messages.append({"role": "system", "content": "Please introduce yourself to the user."}) + context.add_message({"role": "system", "content": "Please introduce yourself to the user."}) await task.queue_frames([LLMRunFrame()]) @transport.event_handler("on_client_disconnected") diff --git a/examples/foundational/07x-interruptible-local.py b/examples/foundational/07x-interruptible-local.py index 65e5836bc..3465f67b2 100644 --- a/examples/foundational/07x-interruptible-local.py +++ b/examples/foundational/07x-interruptible-local.py @@ -47,16 +47,12 @@ async def main(): voice_id="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady ) - llm = OpenAILLMService(api_key=os.getenv("OPENAI_API_KEY")) + llm = OpenAILLMService( + api_key=os.getenv("OPENAI_API_KEY"), + system_instruction="You are a helpful LLM. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + ) - messages = [ - { - "role": "system", - "content": "You are a helpful LLM. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", - }, - ] - - context = LLMContext(messages) + context = LLMContext() user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()), @@ -82,7 +78,7 @@ async def main(): ), ) - messages.append({"role": "system", "content": "Please introduce yourself to the user."}) + context.add_message({"role": "system", "content": "Please introduce yourself to the user."}) await task.queue_frames([LLMRunFrame()]) runner = PipelineRunner() diff --git a/examples/foundational/07y-interruptible-minimax.py b/examples/foundational/07y-interruptible-minimax.py index 1900b1ba8..f23d86f34 100644 --- a/examples/foundational/07y-interruptible-minimax.py +++ b/examples/foundational/07y-interruptible-minimax.py @@ -66,16 +66,12 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): params=MiniMaxHttpTTSService.InputParams(language=Language.EN), ) - llm = OpenAILLMService(api_key=os.getenv("OPENAI_API_KEY")) + llm = OpenAILLMService( + api_key=os.getenv("OPENAI_API_KEY"), + system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + ) - messages = [ - { - "role": "system", - "content": "You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", - }, - ] - - context = LLMContext(messages) + context = LLMContext() user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()), @@ -106,7 +102,9 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): async def on_client_connected(transport, client): logger.info(f"Client connected") # Kick off the conversation. - messages.append({"role": "system", "content": "Please introduce yourself to the user."}) + context.add_message( + {"role": "system", "content": "Please introduce yourself to the user."} + ) await task.queue_frames([LLMRunFrame()]) @transport.event_handler("on_client_disconnected") diff --git a/examples/foundational/07z-interruptible-sarvam-http.py b/examples/foundational/07z-interruptible-sarvam-http.py index e65be1f8e..1f9a8a4e3 100644 --- a/examples/foundational/07z-interruptible-sarvam-http.py +++ b/examples/foundational/07z-interruptible-sarvam-http.py @@ -68,16 +68,12 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): params=SarvamHttpTTSService.InputParams(language=Language.EN), ) - llm = OpenAILLMService(api_key=os.getenv("OPENAI_API_KEY")) + llm = OpenAILLMService( + api_key=os.getenv("OPENAI_API_KEY"), + system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + ) - messages = [ - { - "role": "system", - "content": "You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", - }, - ] - - context = LLMContext(messages) + context = LLMContext() user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()), @@ -108,7 +104,9 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): async def on_client_connected(transport, client): logger.info(f"Client connected") # Kick off the conversation. - messages.append({"role": "system", "content": "Please introduce yourself to the user."}) + context.add_message( + {"role": "system", "content": "Please introduce yourself to the user."} + ) await task.queue_frames([LLMRunFrame()]) @transport.event_handler("on_client_disconnected") diff --git a/examples/foundational/07z-interruptible-sarvam.py b/examples/foundational/07z-interruptible-sarvam.py index 82e070be2..a9a03e7d4 100644 --- a/examples/foundational/07z-interruptible-sarvam.py +++ b/examples/foundational/07z-interruptible-sarvam.py @@ -62,16 +62,12 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): model="bulbul:v2", voice_id="manisha", ) - llm = OpenAILLMService(api_key=os.getenv("OPENAI_API_KEY")) + llm = OpenAILLMService( + api_key=os.getenv("OPENAI_API_KEY"), + system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + ) - messages = [ - { - "role": "system", - "content": "You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", - }, - ] - - context = LLMContext(messages) + context = LLMContext() user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()), @@ -101,7 +97,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): async def on_client_connected(transport, client): logger.info(f"Client connected") # Kick off the conversation. - messages.append({"role": "system", "content": "Please introduce yourself to the user."}) + context.add_message({"role": "system", "content": "Please introduce yourself to the user."}) await task.queue_frames([LLMRunFrame()]) # Optionally, you can wait for 30 seconds and then change the voice. diff --git a/examples/foundational/07za-interruptible-soniox.py b/examples/foundational/07za-interruptible-soniox.py index a60cfe992..f2d651e5b 100644 --- a/examples/foundational/07za-interruptible-soniox.py +++ b/examples/foundational/07za-interruptible-soniox.py @@ -64,16 +64,12 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): voice_id="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady ) - llm = OpenAILLMService(api_key=os.getenv("OPENAI_API_KEY")) + llm = OpenAILLMService( + api_key=os.getenv("OPENAI_API_KEY"), + system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + ) - messages = [ - { - "role": "system", - "content": "You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", - }, - ] - - context = LLMContext(messages) + context = LLMContext() user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()), @@ -103,7 +99,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): async def on_client_connected(transport, client): logger.info(f"Client connected") # Kick off the conversation. - messages.append({"role": "system", "content": "Please introduce yourself to the user."}) + context.add_message({"role": "system", "content": "Please introduce yourself to the user."}) await task.queue_frames([LLMRunFrame()]) @transport.event_handler("on_client_disconnected") diff --git a/examples/foundational/07zb-interruptible-inworld-http.py b/examples/foundational/07zb-interruptible-inworld-http.py index c6441e1c3..9ef465781 100644 --- a/examples/foundational/07zb-interruptible-inworld-http.py +++ b/examples/foundational/07zb-interruptible-inworld-http.py @@ -64,16 +64,12 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): streaming=True, ) - llm = OpenAILLMService(api_key=os.getenv("OPENAI_API_KEY")) + llm = OpenAILLMService( + api_key=os.getenv("OPENAI_API_KEY"), + system_instruction="You are a helpful AI demonstrating Inworld AI's TTS. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a friendly and helpful way.", + ) - messages = [ - { - "role": "system", - "content": "You are a helpful AI demonstrating Inworld AI's TTS. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a friendly and helpful way.", - }, - ] - - context = LLMContext(messages) + context = LLMContext() user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()), @@ -111,7 +107,9 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): async def on_client_connected(transport, client): logger.info("Client connected") # Kick off the conversation. - messages.append({"role": "system", "content": "Please introduce yourself to the user."}) + context.add_message( + {"role": "system", "content": "Please introduce yourself to the user."} + ) await task.queue_frames([LLMRunFrame()]) @transport.event_handler("on_client_disconnected") diff --git a/examples/foundational/07zb-interruptible-inworld.py b/examples/foundational/07zb-interruptible-inworld.py index 9af1302d3..7cdbfd88a 100644 --- a/examples/foundational/07zb-interruptible-inworld.py +++ b/examples/foundational/07zb-interruptible-inworld.py @@ -61,16 +61,12 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): temperature=1.1, ) - llm = OpenAILLMService(api_key=os.getenv("OPENAI_API_KEY")) + llm = OpenAILLMService( + api_key=os.getenv("OPENAI_API_KEY"), + system_instruction="You are a helpful AI demonstrating Inworld AI's TTS. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a friendly and helpful way.", + ) - messages = [ - { - "role": "system", - "content": "You are a helpful AI demonstrating Inworld AI's TTS. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a friendly and helpful way.", - }, - ] - - context = LLMContext(messages) + context = LLMContext() user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()), @@ -108,7 +104,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): async def on_client_connected(transport, client): logger.info("Client connected") # Kick off the conversation. - messages.append({"role": "system", "content": "Please introduce yourself to the user."}) + context.add_message({"role": "system", "content": "Please introduce yourself to the user."}) await task.queue_frames([LLMRunFrame()]) @transport.event_handler("on_client_disconnected") diff --git a/examples/foundational/07zc-interruptible-asyncai-http.py b/examples/foundational/07zc-interruptible-asyncai-http.py index 3720736bd..17d187ac8 100644 --- a/examples/foundational/07zc-interruptible-asyncai-http.py +++ b/examples/foundational/07zc-interruptible-asyncai-http.py @@ -64,16 +64,12 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): aiohttp_session=session, ) - llm = OpenAILLMService(api_key=os.getenv("OPENAI_API_KEY")) + llm = OpenAILLMService( + api_key=os.getenv("OPENAI_API_KEY"), + system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + ) - messages = [ - { - "role": "system", - "content": "You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", - }, - ] - - context = LLMContext(messages) + context = LLMContext() user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()), @@ -104,7 +100,9 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): async def on_client_connected(transport, client): logger.info(f"Client connected") # Kick off the conversation. - messages.append({"role": "system", "content": "Please introduce yourself to the user."}) + context.add_message( + {"role": "system", "content": "Please introduce yourself to the user."} + ) await task.queue_frames([LLMRunFrame()]) @transport.event_handler("on_client_disconnected") diff --git a/examples/foundational/07zc-interruptible-asyncai.py b/examples/foundational/07zc-interruptible-asyncai.py index 31d8fb437..799842658 100644 --- a/examples/foundational/07zc-interruptible-asyncai.py +++ b/examples/foundational/07zc-interruptible-asyncai.py @@ -60,16 +60,12 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): voice_id=os.getenv("ASYNCAI_VOICE_ID", "e0f39dc4-f691-4e78-bba5-5c636692cc04"), ) - llm = OpenAILLMService(api_key=os.getenv("OPENAI_API_KEY")) + llm = OpenAILLMService( + api_key=os.getenv("OPENAI_API_KEY"), + system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + ) - messages = [ - { - "role": "system", - "content": "You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", - }, - ] - - context = LLMContext(messages) + context = LLMContext() user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()), @@ -100,7 +96,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): async def on_client_connected(transport, client): logger.info(f"Client connected") # Kick off the conversation. - messages.append({"role": "system", "content": "Please introduce yourself to the user."}) + context.add_message({"role": "system", "content": "Please introduce yourself to the user."}) await task.queue_frames([LLMRunFrame()]) @transport.event_handler("on_client_disconnected") diff --git a/examples/foundational/07zd-interruptible-aicoustics.py b/examples/foundational/07zd-interruptible-aicoustics.py index 1a3c626ef..9e9f6ddd6 100644 --- a/examples/foundational/07zd-interruptible-aicoustics.py +++ b/examples/foundational/07zd-interruptible-aicoustics.py @@ -80,16 +80,12 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): voice_id="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady ) - llm = OpenAILLMService(api_key=os.getenv("OPENAI_API_KEY")) + llm = OpenAILLMService( + api_key=os.getenv("OPENAI_API_KEY"), + system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + ) - messages = [ - { - "role": "system", - "content": "You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", - }, - ] - - context = LLMContext(messages) + context = LLMContext() user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, user_params=LLMUserAggregatorParams(vad_analyzer=aic_vad_analyzer), @@ -128,7 +124,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): logger.info(f"Client connected") await audiobuffer.start_recording() # Kick off the conversation. - messages.append({"role": "system", "content": "Please introduce yourself to the user."}) + context.add_message({"role": "system", "content": "Please introduce yourself to the user."}) await task.queue_frames([LLMRunFrame()]) @audiobuffer.event_handler("on_audio_data") diff --git a/examples/foundational/07ze-interruptible-hume.py b/examples/foundational/07ze-interruptible-hume.py index 820e12a73..395aa75d4 100644 --- a/examples/foundational/07ze-interruptible-hume.py +++ b/examples/foundational/07ze-interruptible-hume.py @@ -62,16 +62,12 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): voice_id="f898a92e-685f-43fa-985b-a46920f0650b", ) - llm = OpenAILLMService(api_key=os.getenv("OPENAI_API_KEY")) + llm = OpenAILLMService( + api_key=os.getenv("OPENAI_API_KEY"), + system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + ) - messages = [ - { - "role": "system", - "content": "You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", - }, - ] - - context = LLMContext(messages) + context = LLMContext() user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()), @@ -113,7 +109,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): "💡 Word timestamps are enabled! Watch the console for TTSTextFrame logs showing each word with its PTS." ) # Kick off the conversation. - messages.append({"role": "system", "content": "Please introduce yourself to the user."}) + context.add_message({"role": "system", "content": "Please introduce yourself to the user."}) await task.queue_frames([LLMRunFrame()]) @transport.event_handler("on_client_disconnected") diff --git a/examples/foundational/07zf-interruptible-gradium.py b/examples/foundational/07zf-interruptible-gradium.py index 7c823325f..d76735897 100644 --- a/examples/foundational/07zf-interruptible-gradium.py +++ b/examples/foundational/07zf-interruptible-gradium.py @@ -66,16 +66,12 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): url="wss://us.api.gradium.ai/api/speech/tts", ) - llm = OpenAILLMService(api_key=os.getenv("OPENAI_API_KEY")) + llm = OpenAILLMService( + api_key=os.getenv("OPENAI_API_KEY"), + system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + ) - messages = [ - { - "role": "system", - "content": "You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", - }, - ] - - context = LLMContext(messages) + context = LLMContext() user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()), @@ -106,7 +102,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): async def on_client_connected(transport, client): logger.info(f"Client connected") # Kick off the conversation. - messages.append({"role": "system", "content": "Please introduce yourself to the user."}) + context.add_message({"role": "system", "content": "Please introduce yourself to the user."}) await task.queue_frames([LLMRunFrame()]) @transport.event_handler("on_client_disconnected") diff --git a/examples/foundational/07zg-interruptible-camb.py b/examples/foundational/07zg-interruptible-camb.py index ace1fd8b3..669315603 100644 --- a/examples/foundational/07zg-interruptible-camb.py +++ b/examples/foundational/07zg-interruptible-camb.py @@ -59,18 +59,12 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): model="mars-flash", ) - llm = OpenAILLMService(api_key=os.getenv("OPENAI_API_KEY")) + llm = OpenAILLMService( + api_key=os.getenv("OPENAI_API_KEY"), + system_instruction="You are a helpful voice assistant powered by Camb AI text-to-speech. ", + ) - messages = [ - { - "role": "system", - "content": "You are a helpful voice assistant powered by Camb AI text-to-speech. " - "Keep your responses concise and conversational since they will be spoken aloud. " - "Avoid special characters, emojis, or bullet points.", - }, - ] - - context = LLMContext(messages) + context = LLMContext() user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()), @@ -101,7 +95,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): @transport.event_handler("on_client_connected") async def on_client_connected(transport, client): logger.info("Client connected") - messages.append({"role": "system", "content": "Please introduce yourself to the user."}) + context.add_message({"role": "system", "content": "Please introduce yourself to the user."}) await task.queue_frames([LLMRunFrame()]) @transport.event_handler("on_client_disconnected") diff --git a/examples/foundational/07zh-interruptible-hathora.py b/examples/foundational/07zh-interruptible-hathora.py index 7e903035e..08749bf1a 100644 --- a/examples/foundational/07zh-interruptible-hathora.py +++ b/examples/foundational/07zh-interruptible-hathora.py @@ -64,16 +64,10 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): base_url="https://app-362f7ca1-6975-4e18-a605-ab202bf2c315.app.hathora.dev/v1", api_key=os.getenv("HATHORA_API_KEY"), model=None, + system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", ) - messages = [ - { - "role": "system", - "content": "You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", - }, - ] - - context = LLMContext(messages) + context = LLMContext() context_aggregator = LLMContextAggregatorPair( context, user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()), @@ -104,7 +98,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): async def on_client_connected(transport, client): logger.info(f"Client connected") # Kick off the conversation. - messages.append({"role": "system", "content": "Please introduce yourself to the user."}) + context.add_message({"role": "system", "content": "Please introduce yourself to the user."}) await task.queue_frames([LLMRunFrame()]) @transport.event_handler("on_client_disconnected") diff --git a/examples/foundational/07zi-interruptible-piper.py b/examples/foundational/07zi-interruptible-piper.py index 73b8d0f84..9d07f9cdf 100644 --- a/examples/foundational/07zi-interruptible-piper.py +++ b/examples/foundational/07zi-interruptible-piper.py @@ -56,16 +56,12 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): tts = PiperTTSService(voice_id="en_US-ryan-high") - llm = OpenAILLMService(api_key=os.getenv("OPENAI_API_KEY")) + llm = OpenAILLMService( + api_key=os.getenv("OPENAI_API_KEY"), + system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + ) - messages = [ - { - "role": "system", - "content": "You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", - }, - ] - - context = LLMContext(messages) + context = LLMContext() user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()), @@ -96,7 +92,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): async def on_client_connected(transport, client): logger.info(f"Client connected") # Kick off the conversation. - messages.append({"role": "system", "content": "Please introduce yourself to the user."}) + context.add_message({"role": "system", "content": "Please introduce yourself to the user."}) await task.queue_frames([LLMRunFrame()]) @transport.event_handler("on_client_disconnected") diff --git a/examples/foundational/07zj-interruptible-kokoro.py b/examples/foundational/07zj-interruptible-kokoro.py index 685388813..04ab90145 100644 --- a/examples/foundational/07zj-interruptible-kokoro.py +++ b/examples/foundational/07zj-interruptible-kokoro.py @@ -56,16 +56,12 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): tts = KokoroTTSService(voice_id="af_heart") - llm = OpenAILLMService(api_key=os.getenv("OPENAI_API_KEY")) + llm = OpenAILLMService( + api_key=os.getenv("OPENAI_API_KEY"), + system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + ) - messages = [ - { - "role": "system", - "content": "You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", - }, - ] - - context = LLMContext(messages) + context = LLMContext() user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()), @@ -96,7 +92,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): async def on_client_connected(transport, client): logger.info(f"Client connected") # Kick off the conversation. - messages.append({"role": "system", "content": "Please introduce yourself to the user."}) + context.add_message({"role": "system", "content": "Please introduce yourself to the user."}) await task.queue_frames([LLMRunFrame()]) @transport.event_handler("on_client_disconnected") diff --git a/examples/foundational/07zk-interruptible-resemble.py b/examples/foundational/07zk-interruptible-resemble.py index 3594d5b4f..d9298815d 100644 --- a/examples/foundational/07zk-interruptible-resemble.py +++ b/examples/foundational/07zk-interruptible-resemble.py @@ -62,16 +62,12 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): voice_id=os.getenv("RESEMBLE_VOICE_UUID"), ) - llm = OpenAILLMService(api_key=os.getenv("OPENAI_API_KEY")) + llm = OpenAILLMService( + api_key=os.getenv("OPENAI_API_KEY"), + system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + ) - messages = [ - { - "role": "system", - "content": "You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", - }, - ] - - context = LLMContext(messages) + context = LLMContext() user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()), @@ -102,7 +98,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): async def on_client_connected(transport, client): logger.info(f"Client connected") # Kick off the conversation. - messages.append({"role": "system", "content": "Please introduce yourself to the user."}) + context.add_message({"role": "system", "content": "Please introduce yourself to the user."}) await task.queue_frames([LLMRunFrame()]) @transport.event_handler("on_client_disconnected") diff --git a/examples/foundational/08-custom-frame-processor.py b/examples/foundational/08-custom-frame-processor.py index ba55eec7d..a4b5b2127 100644 --- a/examples/foundational/08-custom-frame-processor.py +++ b/examples/foundational/08-custom-frame-processor.py @@ -98,16 +98,12 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): voice_id="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady ) - llm = OpenAILLMService(api_key=os.getenv("OPENAI_API_KEY")) + llm = OpenAILLMService( + api_key=os.getenv("OPENAI_API_KEY"), + system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + ) - messages = [ - { - "role": "system", - "content": "You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", - }, - ] - - context = LLMContext(messages) + context = LLMContext() user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()), @@ -141,7 +137,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): async def on_client_connected(transport, client): logger.info(f"Client connected: {client}") # Kick off the conversation. - messages.append({"role": "system", "content": "Please introduce yourself to the user."}) + context.add_message({"role": "system", "content": "Please introduce yourself to the user."}) await task.queue_frames([LLMRunFrame()]) @transport.event_handler("on_client_disconnected") diff --git a/examples/foundational/10-wake-phrase.py b/examples/foundational/10-wake-phrase.py index c7f53e496..52a7d1225 100644 --- a/examples/foundational/10-wake-phrase.py +++ b/examples/foundational/10-wake-phrase.py @@ -10,7 +10,7 @@ from dotenv import load_dotenv from loguru import logger from pipecat.audio.vad.silero import SileroVADAnalyzer -from pipecat.frames.frames import TTSSpeakFrame +from pipecat.frames.frames import LLMRunFrame, TTSSpeakFrame from pipecat.pipeline.pipeline import Pipeline from pipecat.pipeline.runner import PipelineRunner from pipecat.pipeline.task import PipelineParams, PipelineTask @@ -59,18 +59,14 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): voice_id="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady ) - llm = OpenAILLMService(api_key=os.getenv("OPENAI_API_KEY")) - - messages = [ - { - "role": "system", - "content": "You are a helpful assistant. Respond to what the user said in a creative and helpful way. Keep your responses brief.", - }, - ] + llm = OpenAILLMService( + api_key=os.getenv("OPENAI_API_KEY"), + system_instruction="You are a helpful assistant. Respond to what the user said in a creative and helpful way. Keep your responses brief.", + ) hey_robot_filter = WakeCheckFilter(["hey robot", "hey, robot"]) - context = LLMContext(messages) + context = LLMContext() user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()), @@ -102,7 +98,13 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): async def on_client_connected(transport, client): logger.info(f"Client connected") # Kick off the conversation. - await task.queue_frame(TTSSpeakFrame("Hi! If you want to talk to me, just say 'Hey Robot'")) + context.add_message( + { + "role": "system", + "content": "Please introduce yourself. Tell the user they should say 'Hey Robot' before talking to you.", + } + ) + await task.queue_frames([LLMRunFrame()]) @transport.event_handler("on_client_disconnected") async def on_client_disconnected(transport, client): diff --git a/examples/foundational/11-sound-effects.py b/examples/foundational/11-sound-effects.py index 156778317..401c36b8e 100644 --- a/examples/foundational/11-sound-effects.py +++ b/examples/foundational/11-sound-effects.py @@ -104,21 +104,17 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): stt = DeepgramSTTService(api_key=os.getenv("DEEPGRAM_API_KEY")) - llm = OpenAILLMService(api_key=os.getenv("OPENAI_API_KEY")) + llm = OpenAILLMService( + api_key=os.getenv("OPENAI_API_KEY"), + system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + ) tts = CartesiaTTSService( api_key=os.getenv("CARTESIA_API_KEY"), voice_id="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady ) - messages = [ - { - "role": "system", - "content": "You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", - }, - ] - - context = LLMContext(messages) + context = LLMContext() user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()), diff --git a/examples/foundational/12-describe-image-openai.py b/examples/foundational/12-describe-image-openai.py index afa334429..dc45451fe 100644 --- a/examples/foundational/12-describe-image-openai.py +++ b/examples/foundational/12-describe-image-openai.py @@ -56,16 +56,12 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): voice_id="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady ) - llm = OpenAILLMService(api_key=os.getenv("OPENAI_API_KEY")) + llm = OpenAILLMService( + api_key=os.getenv("OPENAI_API_KEY"), + system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way. You are also able to describe images.", + ) - messages = [ - { - "role": "system", - "content": "You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way. You are also able to describe images.", - }, - ] - - context = LLMContext(messages) + context = LLMContext() user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()), @@ -114,7 +110,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): size=image.size, text=question, ) - messages.append(message) + context.add_message(message) await task.queue_frames([LLMRunFrame()]) @transport.event_handler("on_client_disconnected") diff --git a/examples/foundational/12a-describe-image-anthropic.py b/examples/foundational/12a-describe-image-anthropic.py index 2b34c6220..a1151ddf9 100644 --- a/examples/foundational/12a-describe-image-anthropic.py +++ b/examples/foundational/12a-describe-image-anthropic.py @@ -56,16 +56,12 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): voice_id="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady ) - llm = AnthropicLLMService(api_key=os.getenv("ANTHROPIC_API_KEY")) + llm = AnthropicLLMService( + api_key=os.getenv("ANTHROPIC_API_KEY"), + system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way. You are also able to describe images.", + ) - messages = [ - { - "role": "system", - "content": "You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way. You are also able to describe images.", - }, - ] - - context = LLMContext(messages) + context = LLMContext() user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()), @@ -114,7 +110,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): size=image.size, text=question, ) - messages.append(message) + context.add_message(message) await task.queue_frames([LLMRunFrame()]) @transport.event_handler("on_client_disconnected") diff --git a/examples/foundational/12b-describe-image-aws.py b/examples/foundational/12b-describe-image-aws.py index 84a391121..43a6ae232 100644 --- a/examples/foundational/12b-describe-image-aws.py +++ b/examples/foundational/12b-describe-image-aws.py @@ -63,16 +63,10 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): # Here we can't because AWS Bedrock doesn't support it for Claude 3.7, # which we need for image input. params=AWSBedrockLLMService.InputParams(temperature=0.8), + system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way. You are also able to describe images.", ) - messages = [ - { - "role": "system", - "content": "You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way. You are also able to describe images.", - }, - ] - - context = LLMContext(messages) + context = LLMContext() user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()), @@ -121,7 +115,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): size=image.size, text=question, ) - messages.append(message) + context.add_message(message) await task.queue_frames([LLMRunFrame()]) @transport.event_handler("on_client_disconnected") diff --git a/examples/foundational/12c-describe-image-gemini-flash.py b/examples/foundational/12c-describe-image-gemini-flash.py index 212dc5b32..9adbe62d2 100644 --- a/examples/foundational/12c-describe-image-gemini-flash.py +++ b/examples/foundational/12c-describe-image-gemini-flash.py @@ -56,16 +56,12 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): voice_id="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady ) - llm = GoogleLLMService(api_key=os.getenv("GOOGLE_API_KEY")) + llm = GoogleLLMService( + api_key=os.getenv("GOOGLE_API_KEY"), + system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way. You are also able to describe images.", + ) - messages = [ - { - "role": "system", - "content": "You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way. You are also able to describe images.", - }, - ] - - context = LLMContext(messages) + context = LLMContext() user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()), @@ -114,7 +110,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): size=image.size, text=question, ) - messages.append(message) + context.add_message(message) await task.queue_frames([LLMRunFrame()]) @transport.event_handler("on_client_disconnected") diff --git a/examples/foundational/14-function-calling.py b/examples/foundational/14-function-calling.py index 27e666d0b..0087af9fc 100644 --- a/examples/foundational/14-function-calling.py +++ b/examples/foundational/14-function-calling.py @@ -70,7 +70,10 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): voice_id="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady ) - llm = OpenAILLMService(api_key=os.getenv("OPENAI_API_KEY")) + llm = OpenAILLMService( + api_key=os.getenv("OPENAI_API_KEY"), + system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + ) # You can also register a function_name of None to get all functions # sent to the same callback with an additional function_name parameter. @@ -110,14 +113,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): ) tools = ToolsSchema(standard_tools=[weather_function, restaurant_function]) - messages = [ - { - "role": "system", - "content": "You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", - }, - ] - - context = LLMContext(messages, tools) + context = LLMContext(tools=tools) user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()), diff --git a/examples/foundational/14c-function-calling-together.py b/examples/foundational/14c-function-calling-together.py index 28dd8c466..214d6f292 100644 --- a/examples/foundational/14c-function-calling-together.py +++ b/examples/foundational/14c-function-calling-together.py @@ -70,6 +70,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): llm = TogetherLLMService( api_key=os.getenv("TOGETHER_API_KEY"), model="meta-llama/Meta-Llama-3.1-70B-Instruct-Turbo", + system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", ) # You can also register a function_name of None to get all functions # sent to the same callback with an additional function_name parameter. @@ -96,14 +97,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): required=["location", "format"], ) tools = ToolsSchema(standard_tools=[weather_function]) - messages = [ - { - "role": "system", - "content": "You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", - }, - ] - - context = LLMContext(messages, tools) + context = LLMContext(tools=tools) user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()), diff --git a/examples/foundational/14d-function-calling-anthropic-video.py b/examples/foundational/14d-function-calling-anthropic-video.py index 630a0aaac..cddde3647 100644 --- a/examples/foundational/14d-function-calling-anthropic-video.py +++ b/examples/foundational/14d-function-calling-anthropic-video.py @@ -94,7 +94,10 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): ) # Anthropic for vision analysis - llm = AnthropicLLMService(api_key=os.getenv("ANTHROPIC_API_KEY")) + llm = AnthropicLLMService( + api_key=os.getenv("ANTHROPIC_API_KEY"), + system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way. You are able to describe images from the user camera.", + ) llm.register_function("fetch_user_image", fetch_user_image) @llm.event_handler("on_function_calls_started") @@ -118,14 +121,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): ) tools = ToolsSchema(standard_tools=[fetch_image_function]) - messages = [ - { - "role": "system", - "content": "You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way. You are able to describe images from the user camera.", - }, - ] - - context = LLMContext(messages, tools) + context = LLMContext(tools=tools) user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()), @@ -162,7 +158,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): client_id = get_transport_client_id(transport, client) # Kick off the conversation. - messages.append( + context.add_message( { "role": "system", "content": f"Please introduce yourself to the user. Use '{client_id}' as the user ID during function calls.", diff --git a/examples/foundational/14d-function-calling-aws-video.py b/examples/foundational/14d-function-calling-aws-video.py index 2b22faada..396ea0a32 100644 --- a/examples/foundational/14d-function-calling-aws-video.py +++ b/examples/foundational/14d-function-calling-aws-video.py @@ -101,6 +101,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): # Here we can't because AWS Bedrock doesn't support it for Claude 3.7, # which we need for image input. params=AWSBedrockLLMService.InputParams(temperature=0.8), + system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way. You are able to describe images from the user camera.", ) llm.register_function("fetch_user_image", fetch_user_image) @@ -125,14 +126,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): ) tools = ToolsSchema(standard_tools=[fetch_image_function]) - messages = [ - { - "role": "system", - "content": "You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way. You are able to describe images from the user camera.", - }, - ] - - context = LLMContext(messages, tools) + context = LLMContext(tools=tools) user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()), @@ -169,7 +163,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): client_id = get_transport_client_id(transport, client) # Kick off the conversation. - messages.append( + context.add_message( { "role": "system", "content": f"Please introduce yourself to the user. Use '{client_id}' as the user ID during function calls.", diff --git a/examples/foundational/14d-function-calling-gemini-flash-video.py b/examples/foundational/14d-function-calling-gemini-flash-video.py index e3d4ca8a4..c59767406 100644 --- a/examples/foundational/14d-function-calling-gemini-flash-video.py +++ b/examples/foundational/14d-function-calling-gemini-flash-video.py @@ -94,7 +94,10 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): ) # Google Gemini model for vision analysis - llm = GoogleLLMService(api_key=os.getenv("GOOGLE_API_KEY")) + llm = GoogleLLMService( + api_key=os.getenv("GOOGLE_API_KEY"), + system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way. You are able to describe images from the user camera.", + ) llm.register_function("fetch_user_image", fetch_user_image) @llm.event_handler("on_function_calls_started") @@ -118,14 +121,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): ) tools = ToolsSchema(standard_tools=[fetch_image_function]) - messages = [ - { - "role": "system", - "content": "You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way. You are able to describe images from the user camera.", - }, - ] - - context = LLMContext(messages, tools) + context = LLMContext(tools=tools) user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()), @@ -162,7 +158,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): client_id = get_transport_client_id(transport, client) # Kick off the conversation. - messages.append( + context.add_message( { "role": "system", "content": f"Please introduce yourself to the user. Use '{client_id}' as the user ID during function calls.", diff --git a/examples/foundational/14d-function-calling-moondream-video.py b/examples/foundational/14d-function-calling-moondream-video.py index 77e9282f4..d0913e3dc 100644 --- a/examples/foundational/14d-function-calling-moondream-video.py +++ b/examples/foundational/14d-function-calling-moondream-video.py @@ -124,7 +124,10 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): voice_id="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady ) - llm = OpenAILLMService(api_key=os.getenv("OPENAI_API_KEY")) + llm = OpenAILLMService( + api_key=os.getenv("OPENAI_API_KEY"), + system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way. You are able to describe images from the user camera.", + ) llm.register_function("fetch_user_image", fetch_user_image) @llm.event_handler("on_function_calls_started") @@ -148,14 +151,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): ) tools = ToolsSchema(standard_tools=[fetch_image_function]) - messages = [ - { - "role": "system", - "content": "You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way. You are able to describe images from the user camera.", - }, - ] - - context = LLMContext(messages, tools) + context = LLMContext(tools=tools) user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()), @@ -200,7 +196,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): client_id = get_transport_client_id(transport, client) # Kick off the conversation. - messages.append( + context.add_message( { "role": "system", "content": f"Please introduce yourself to the user. Use '{client_id}' as the user ID during function calls.", diff --git a/examples/foundational/14d-function-calling-openai-video.py b/examples/foundational/14d-function-calling-openai-video.py index d948e9caa..50365eb29 100644 --- a/examples/foundational/14d-function-calling-openai-video.py +++ b/examples/foundational/14d-function-calling-openai-video.py @@ -94,7 +94,10 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): voice_id="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady ) - llm = OpenAILLMService(api_key=os.getenv("OPENAI_API_KEY")) + llm = OpenAILLMService( + api_key=os.getenv("OPENAI_API_KEY"), + system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way. You are able to describe images from the user camera.", + ) llm.register_function("fetch_user_image", fetch_user_image) @llm.event_handler("on_function_calls_started") @@ -118,14 +121,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): ) tools = ToolsSchema(standard_tools=[fetch_image_function]) - messages = [ - { - "role": "system", - "content": "You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way. You are able to describe images from the user camera.", - }, - ] - - context = LLMContext(messages, tools) + context = LLMContext(tools=tools) user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()), @@ -161,7 +157,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): client_id = get_transport_client_id(transport, client) # Kick off the conversation. - messages.append( + context.add_message( { "role": "system", "content": f"Please introduce yourself to the user. Use '{client_id}' as the user ID during function calls.", diff --git a/examples/foundational/14f-function-calling-groq.py b/examples/foundational/14f-function-calling-groq.py index 2c922d296..e6cfb3659 100644 --- a/examples/foundational/14f-function-calling-groq.py +++ b/examples/foundational/14f-function-calling-groq.py @@ -67,7 +67,10 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): voice_id="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady ) - llm = GroqLLMService(api_key=os.getenv("GROQ_API_KEY")) + llm = GroqLLMService( + api_key=os.getenv("GROQ_API_KEY"), + system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + ) # You can also register a function_name of None to get all functions # sent to the same callback with an additional function_name parameter. llm.register_function("get_current_weather", fetch_weather_from_api) @@ -93,14 +96,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): required=["location"], ) tools = ToolsSchema(standard_tools=[weather_function]) - messages = [ - { - "role": "system", - "content": "You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", - }, - ] - - context = LLMContext(messages, tools) + context = LLMContext(tools=tools) user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()), diff --git a/examples/foundational/14g-function-calling-grok.py b/examples/foundational/14g-function-calling-grok.py index e8529aba5..51435a2a0 100644 --- a/examples/foundational/14g-function-calling-grok.py +++ b/examples/foundational/14g-function-calling-grok.py @@ -67,7 +67,10 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): voice_id="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady ) - llm = GrokLLMService(api_key=os.getenv("GROK_API_KEY")) + llm = GrokLLMService( + api_key=os.getenv("GROK_API_KEY"), + system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + ) # You can also register a function_name of None to get all functions # sent to the same callback with an additional function_name parameter. llm.register_function("get_current_weather", fetch_weather_from_api) @@ -89,14 +92,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): required=["location", "format"], ) tools = ToolsSchema(standard_tools=[weather_function]) - messages = [ - { - "role": "system", - "content": "You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", - }, - ] - - context = LLMContext(messages, tools) + context = LLMContext(tools=tools) user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()), diff --git a/examples/foundational/14h-function-calling-azure.py b/examples/foundational/14h-function-calling-azure.py index fb9407f1a..192cebb92 100644 --- a/examples/foundational/14h-function-calling-azure.py +++ b/examples/foundational/14h-function-calling-azure.py @@ -71,6 +71,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): api_key=os.getenv("AZURE_CHATGPT_API_KEY"), endpoint=os.getenv("AZURE_CHATGPT_ENDPOINT"), model=os.getenv("AZURE_CHATGPT_MODEL"), + system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", ) # You can also register a function_name of None to get all functions # sent to the same callback with an additional function_name parameter. @@ -97,14 +98,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): required=["location", "format"], ) tools = ToolsSchema(standard_tools=[weather_function]) - messages = [ - { - "role": "system", - "content": "You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", - }, - ] - - context = LLMContext(messages, tools) + context = LLMContext(tools=tools) user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()), diff --git a/examples/foundational/14i-function-calling-fireworks.py b/examples/foundational/14i-function-calling-fireworks.py index 7a350f84f..be006e062 100644 --- a/examples/foundational/14i-function-calling-fireworks.py +++ b/examples/foundational/14i-function-calling-fireworks.py @@ -70,6 +70,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): llm = FireworksLLMService( api_key=os.getenv("FIREWORKS_API_KEY"), model="accounts/fireworks/models/gpt-oss-20b", + system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", ) # You can also register a function_name of None to get all functions # sent to the same callback with an additional function_name parameter. @@ -100,14 +101,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): required=["location", "format"], ) tools = ToolsSchema(standard_tools=[weather_function]) - messages = [ - { - "role": "system", - "content": "You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way. Start by saying hello.", - }, - ] - - context = LLMContext(messages, tools) + context = LLMContext(tools=tools) user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()), @@ -138,6 +132,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): async def on_client_connected(transport, client): logger.info(f"Client connected") # Kick off the conversation. + context.add_message({"role": "system", "content": "Please introduce yourself to the user."}) await task.queue_frames([LLMRunFrame()]) @transport.event_handler("on_client_disconnected") diff --git a/examples/foundational/14k-function-calling-cerebras.py b/examples/foundational/14k-function-calling-cerebras.py index ab340c77c..81df8723c 100644 --- a/examples/foundational/14k-function-calling-cerebras.py +++ b/examples/foundational/14k-function-calling-cerebras.py @@ -67,7 +67,20 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): voice_id="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady ) - llm = CerebrasLLMService(api_key=os.getenv("CEREBRAS_API_KEY")) + llm = CerebrasLLMService( + api_key=os.getenv("CEREBRAS_API_KEY"), + system_instruction="""You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. + +You have one functions available: + +1. get_current_weather is used to get current weather information. + +Infer whether to use Fahrenheit or Celsius automatically based on the location, unless the user specifies a preference. + +Start by asking me for my location. Then, use 'get_weather_current' to give me a forecast. + + Respond to what the user said in a creative and helpful way.""", + ) # You can also register a function_name of None to get all functions # sent to the same callback with an additional function_name parameter. llm.register_function("get_current_weather", fetch_weather_from_api) @@ -93,24 +106,8 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): required=["location", "format"], ) tools = ToolsSchema(standard_tools=[weather_function]) - messages = [ - { - "role": "system", - "content": """You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. -You have one functions available: - -1. get_current_weather is used to get current weather information. - -Infer whether to use Fahrenheit or Celsius automatically based on the location, unless the user specifies a preference. - -Start by asking me for my location. Then, use 'get_weather_current' to give me a forecast. - - Respond to what the user said in a creative and helpful way.""", - }, - ] - - context = LLMContext(messages, tools) + context = LLMContext(tools=tools) user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()), diff --git a/examples/foundational/14l-function-calling-deepseek.py b/examples/foundational/14l-function-calling-deepseek.py index 2d54fbe07..93643146a 100644 --- a/examples/foundational/14l-function-calling-deepseek.py +++ b/examples/foundational/14l-function-calling-deepseek.py @@ -67,7 +67,21 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): voice_id="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady ) - llm = DeepSeekLLMService(api_key=os.getenv("DEEPSEEK_API_KEY"), model="deepseek-chat") + llm = DeepSeekLLMService( + api_key=os.getenv("DEEPSEEK_API_KEY"), + model="deepseek-chat", + system_instruction="""You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. + +You have one functions available: + +1. get_current_weather is used to get current weather information. + +Infer whether to use Fahrenheit or Celsius automatically based on the location, unless the user specifies a preference. + +Start by asking me for my location. Then, use 'get_weather_current' to give me a forecast. + + Respond to what the user said in a creative and helpful way.""", + ) # You can also register a function_name of None to get all functions # sent to the same callback with an additional function_name parameter. llm.register_function("get_current_weather", fetch_weather_from_api) @@ -93,24 +107,8 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): required=["location", "format"], ) tools = ToolsSchema(standard_tools=[weather_function]) - messages = [ - { - "role": "system", - "content": """You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. -You have one functions available: - -1. get_current_weather is used to get current weather information. - -Infer whether to use Fahrenheit or Celsius automatically based on the location, unless the user specifies a preference. - -Start by asking me for my location. Then, use 'get_weather_current' to give me a forecast. - - Respond to what the user said in a creative and helpful way.""", - }, - ] - - context = LLMContext(messages, tools) + context = LLMContext(tools=tools) user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()), diff --git a/examples/foundational/14m-function-calling-openrouter.py b/examples/foundational/14m-function-calling-openrouter.py index 5d6589a75..9504021ff 100644 --- a/examples/foundational/14m-function-calling-openrouter.py +++ b/examples/foundational/14m-function-calling-openrouter.py @@ -70,7 +70,9 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): ) llm = OpenRouterLLMService( - api_key=os.getenv("OPENROUTER_API_KEY"), model="openai/gpt-4o-2024-11-20" + api_key=os.getenv("OPENROUTER_API_KEY"), + model="openai/gpt-4o-2024-11-20", + system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", ) # You can also register a function_name of None to get all functions # sent to the same callback with an additional function_name parameter. @@ -97,14 +99,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): required=["location", "format"], ) tools = ToolsSchema(standard_tools=[weather_function]) - messages = [ - { - "role": "system", - "content": "You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", - }, - ] - - context = LLMContext(messages, tools) + context = LLMContext(tools=tools) user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()), diff --git a/examples/foundational/14q-function-calling-qwen.py b/examples/foundational/14q-function-calling-qwen.py index 72130b8fd..32c551b29 100644 --- a/examples/foundational/14q-function-calling-qwen.py +++ b/examples/foundational/14q-function-calling-qwen.py @@ -67,7 +67,11 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): voice_id="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady ) - llm = QwenLLMService(api_key=os.getenv("QWEN_API_KEY"), model="qwen2.5-72b-instruct") + llm = QwenLLMService( + api_key=os.getenv("QWEN_API_KEY"), + model="qwen2.5-72b-instruct", + system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + ) # You can also register a function_name of None to get all functions # sent to the same callback with an additional function_name parameter. @@ -95,14 +99,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): ) tools = ToolsSchema(standard_tools=[weather_function]) - messages = [ - { - "role": "system", - "content": "You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", - }, - ] - - context = LLMContext(messages, tools) + context = LLMContext(tools=tools) user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()), diff --git a/examples/foundational/14r-function-calling-aws.py b/examples/foundational/14r-function-calling-aws.py index 37d29ea7f..1ce5c4220 100644 --- a/examples/foundational/14r-function-calling-aws.py +++ b/examples/foundational/14r-function-calling-aws.py @@ -74,6 +74,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): aws_region="us-west-2", model="us.anthropic.claude-haiku-4-5-20251001-v1:0", params=AWSBedrockLLMService.InputParams(temperature=0.8), + system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", ) # You can also register a function_name of None to get all functions @@ -110,14 +111,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): ) tools = ToolsSchema(standard_tools=[weather_function, restaurant_function]) - messages = [ - { - "role": "system", - "content": "You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", - }, - ] - - context = LLMContext(messages, tools) + context = LLMContext(tools=tools) user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()), @@ -148,7 +142,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): async def on_client_connected(transport, client): logger.info(f"Client connected") # Kick off the conversation. - messages.append({"role": "user", "content": "Please introduce yourself to the user."}) + context.add_message({"role": "user", "content": "Please introduce yourself to the user."}) await task.queue_frames([LLMRunFrame()]) @transport.event_handler("on_client_disconnected") diff --git a/examples/foundational/14s-function-calling-sambanova.py b/examples/foundational/14s-function-calling-sambanova.py index 76eb390c0..1548b2aa1 100644 --- a/examples/foundational/14s-function-calling-sambanova.py +++ b/examples/foundational/14s-function-calling-sambanova.py @@ -70,7 +70,10 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): voice_id="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady ) - llm = SambaNovaLLMService(api_key=os.getenv("SAMBANOVA_API_KEY")) + llm = SambaNovaLLMService( + api_key=os.getenv("SAMBANOVA_API_KEY"), + system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + ) # You can also register a function_name of None to get all functions # sent to the same callback with an additional function_name parameter. llm.register_function("get_current_weather", fetch_weather_from_api) @@ -96,14 +99,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): required=["location"], ) tools = ToolsSchema(standard_tools=[weather_function]) - messages = [ - { - "role": "system", - "content": "You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", - }, - ] - - context = LLMContext(messages, tools) + context = LLMContext(tools=tools) user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()), diff --git a/examples/foundational/14t-function-calling-direct.py b/examples/foundational/14t-function-calling-direct.py index fc12101aa..31efb7ac9 100644 --- a/examples/foundational/14t-function-calling-direct.py +++ b/examples/foundational/14t-function-calling-direct.py @@ -83,7 +83,10 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): voice_id="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady ) - llm = OpenAILLMService(api_key=os.getenv("OPENAI_API_KEY")) + llm = OpenAILLMService( + api_key=os.getenv("OPENAI_API_KEY"), + system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + ) # You can also register a function_name of None to get all functions # sent to the same callback with an additional function_name parameter. @@ -96,14 +99,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): tools = ToolsSchema(standard_tools=[get_current_weather, get_restaurant_recommendation]) - messages = [ - { - "role": "system", - "content": "You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", - }, - ] - - context = LLMContext(messages, tools) + context = LLMContext(tools=tools) user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()), diff --git a/examples/foundational/14u-function-calling-ollama.py b/examples/foundational/14u-function-calling-ollama.py index 7da07b329..b7c65dedf 100644 --- a/examples/foundational/14u-function-calling-ollama.py +++ b/examples/foundational/14u-function-calling-ollama.py @@ -71,7 +71,10 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): voice_id="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady ) - llm = OLLamaLLMService(model="llama3.2") # Update to the model you're running locally + llm = OLLamaLLMService( + model="llama3.2", + system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + ) # Update to the model you're running locally # You can also register a function_name of None to get all functions # sent to the same callback with an additional function_name parameter. @@ -111,14 +114,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): ) tools = ToolsSchema(standard_tools=[weather_function, restaurant_function]) - messages = [ - { - "role": "system", - "content": "You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", - }, - ] - - context = LLMContext(messages, tools) + context = LLMContext(tools=tools) user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()), diff --git a/examples/foundational/14v-function-calling-openai.py b/examples/foundational/14v-function-calling-openai.py index ad4aba063..920275975 100644 --- a/examples/foundational/14v-function-calling-openai.py +++ b/examples/foundational/14v-function-calling-openai.py @@ -78,7 +78,10 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): ) # model choices: gpt-4o, gpt-4.1, etc. - llm = OpenAILLMService(api_key=os.getenv("OPENAI_API_KEY")) + llm = OpenAILLMService( + api_key=os.getenv("OPENAI_API_KEY"), + system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + ) # You can also register a function_name of None to get all functions # sent to the same callback with an additional function_name parameter. @@ -118,14 +121,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): ) tools = ToolsSchema(standard_tools=[weather_function, restaurant_function]) - messages = [ - { - "role": "system", - "content": "You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", - }, - ] - - context = LLMContext(messages, tools) + context = LLMContext(tools=tools) user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()), diff --git a/examples/foundational/14w-function-calling-mistral.py b/examples/foundational/14w-function-calling-mistral.py index c62e8be05..e17d31f72 100644 --- a/examples/foundational/14w-function-calling-mistral.py +++ b/examples/foundational/14w-function-calling-mistral.py @@ -70,7 +70,10 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): voice_id="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady ) - llm = MistralLLMService(api_key=os.getenv("MISTRAL_API_KEY")) + llm = MistralLLMService( + api_key=os.getenv("MISTRAL_API_KEY"), + system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + ) # You can also register a function_name of None to get all functions # sent to the same callback with an additional function_name parameter. @@ -106,14 +109,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): ) tools = ToolsSchema(standard_tools=[weather_function, restaurant_function]) - messages = [ - { - "role": "system", - "content": "You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", - }, - ] - - context = LLMContext(messages, tools) + context = LLMContext(tools=tools) user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()), diff --git a/examples/foundational/14x-function-calling-openpipe.py b/examples/foundational/14x-function-calling-openpipe.py index 576da02a4..8a71a83d7 100644 --- a/examples/foundational/14x-function-calling-openpipe.py +++ b/examples/foundational/14x-function-calling-openpipe.py @@ -76,6 +76,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): api_key=os.getenv("OPENAI_API_KEY"), openpipe_api_key=os.getenv("OPENPIPE_API_KEY"), tags={"conversation_id": f"pipecat-{timestamp}"}, + system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", ) # You can also register a function_name of None to get all functions @@ -116,14 +117,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): ) tools = ToolsSchema(standard_tools=[weather_function, restaurant_function]) - messages = [ - { - "role": "system", - "content": "You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", - }, - ] - - context = LLMContext(messages, tools) + context = LLMContext(tools=tools) user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()), diff --git a/examples/foundational/15-switch-voices.py b/examples/foundational/15-switch-voices.py index 343f9faf1..4478c067b 100644 --- a/examples/foundational/15-switch-voices.py +++ b/examples/foundational/15-switch-voices.py @@ -112,7 +112,10 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): tts = SwitchVoices() - llm = OpenAILLMService(api_key=os.getenv("OPENAI_API_KEY")) + llm = OpenAILLMService( + api_key=os.getenv("OPENAI_API_KEY"), + system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities. Respond to what the user said in a creative and helpful way. Your output should not include non-alphanumeric characters. You can do the following voices: 'News Lady', 'British Lady' and 'Barbershop Man'.", + ) llm.register_function("switch_voice", tts.switch_voice) switch_voice_function = FunctionSchema( @@ -128,14 +131,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): ) tools = ToolsSchema(standard_tools=[switch_voice_function]) - messages = [ - { - "role": "system", - "content": "You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities. Respond to what the user said in a creative and helpful way. Your output should not include non-alphanumeric characters. You can do the following voices: 'News Lady', 'British Lady' and 'Barbershop Man'.", - }, - ] - - context = LLMContext(messages, tools) + context = LLMContext(tools=tools) user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()), @@ -166,7 +162,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): async def on_client_connected(transport, client): logger.info(f"Client connected") # Kick off the conversation. - messages.append( + context.add_message( { "role": "system", "content": f"Please introduce yourself to the user and let them know the voices you can do. Your initial responses should be as if you were a {tts.current_voice}.", diff --git a/examples/foundational/15a-switch-languages.py b/examples/foundational/15a-switch-languages.py index eb25a0511..3ad897077 100644 --- a/examples/foundational/15a-switch-languages.py +++ b/examples/foundational/15a-switch-languages.py @@ -103,7 +103,10 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): tts = SwitchLanguage() - llm = OpenAILLMService(api_key=os.getenv("OPENAI_API_KEY")) + llm = OpenAILLMService( + api_key=os.getenv("OPENAI_API_KEY"), + system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities. Respond to what the user said in a creative and helpful way. Your output should not include non-alphanumeric characters. You can speak the following languages: 'English' and 'Spanish'.", + ) llm.register_function("switch_language", tts.switch_language) switch_language_function = FunctionSchema( @@ -118,14 +121,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): required=["language"], ) tools = ToolsSchema(standard_tools=[switch_language_function]) - messages = [ - { - "role": "system", - "content": "You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities. Respond to what the user said in a creative and helpful way. Your output should not include non-alphanumeric characters. You can speak the following languages: 'English' and 'Spanish'.", - }, - ] - - context = LLMContext(messages, tools) + context = LLMContext(tools=tools) user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()), @@ -156,7 +152,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): async def on_client_connected(transport, client): logger.info(f"Client connected") # Kick off the conversation. - messages.append( + context.add_message( { "role": "system", "content": f"Please introduce yourself to the user and let them know the languages you speak. Your initial responses should be in {tts.current_language}.", diff --git a/examples/foundational/16-gpu-container-local-bot.py b/examples/foundational/16-gpu-container-local-bot.py index 93bd65200..8367e1044 100644 --- a/examples/foundational/16-gpu-container-local-bot.py +++ b/examples/foundational/16-gpu-container-local-bot.py @@ -70,16 +70,10 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): # Or, to use a local vLLM (or similar) api server model="meta-llama/Meta-Llama-3-8B-Instruct", base_url="http://0.0.0.0:8000/v1", + system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", ) - messages = [ - { - "role": "system", - "content": "You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", - }, - ] - - context = LLMContext(messages) + context = LLMContext() user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()), @@ -111,7 +105,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): async def on_client_connected(transport, client): logger.info(f"Client connected") # Kick off the conversation. - messages.append({"role": "system", "content": "Please introduce yourself to the user."}) + context.add_message({"role": "system", "content": "Please introduce yourself to the user."}) await task.queue_frames([LLMRunFrame()]) # Handle "latency-ping" messages. The client will send app messages that look like diff --git a/examples/foundational/17-detect-user-idle.py b/examples/foundational/17-detect-user-idle.py index e6af5a364..217162ea8 100644 --- a/examples/foundational/17-detect-user-idle.py +++ b/examples/foundational/17-detect-user-idle.py @@ -118,7 +118,10 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): voice_id="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady ) - llm = OpenAILLMService(api_key=os.getenv("OPENAI_API_KEY")) + llm = OpenAILLMService( + api_key=os.getenv("OPENAI_API_KEY"), + system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + ) llm.register_function("get_current_weather", fetch_weather_from_api) llm.register_function("get_restaurant_recommendation", fetch_restaurant_recommendation) @@ -156,14 +159,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): ) tools = ToolsSchema(standard_tools=[weather_function, restaurant_function]) - messages = [ - { - "role": "system", - "content": "You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", - }, - ] - - context = LLMContext(messages, tools) + context = LLMContext(tools=tools) user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, user_params=LLMUserAggregatorParams( @@ -209,7 +205,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): async def on_client_connected(transport, client): logger.info(f"Client connected") # Kick off the conversation. - messages.append({"role": "system", "content": "Please introduce yourself to the user."}) + context.add_message({"role": "system", "content": "Please introduce yourself to the user."}) await task.queue_frames([LLMRunFrame()]) await asyncio.sleep(30) logger.info(f"Disabling idle detection") diff --git a/examples/foundational/21-tavus-transport.py b/examples/foundational/21-tavus-transport.py index 925001212..b16ebbf38 100644 --- a/examples/foundational/21-tavus-transport.py +++ b/examples/foundational/21-tavus-transport.py @@ -54,16 +54,12 @@ async def main(): voice_id="a167e0f3-df7e-4d52-a9c3-f949145efdab", ) - llm = GoogleLLMService(api_key=os.getenv("GOOGLE_API_KEY")) + llm = GoogleLLMService( + api_key=os.getenv("GOOGLE_API_KEY"), + system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + ) - messages = [ - { - "role": "system", - "content": "You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", - }, - ] - - context = LLMContext(messages) + context = LLMContext() user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()), @@ -95,7 +91,7 @@ async def main(): async def on_client_connected(transport, participant): logger.info(f"Client connected") # Kick off the conversation. - messages.append( + context.add_message( { "role": "system", "content": "Start by greeting the user and ask how you can help.", diff --git a/examples/foundational/21a-tavus-video-service.py b/examples/foundational/21a-tavus-video-service.py index eff214b3a..7e32579b0 100644 --- a/examples/foundational/21a-tavus-video-service.py +++ b/examples/foundational/21a-tavus-video-service.py @@ -64,7 +64,10 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): voice_id="a167e0f3-df7e-4d52-a9c3-f949145efdab", ) - llm = GoogleLLMService(api_key=os.getenv("GOOGLE_API_KEY")) + llm = GoogleLLMService( + api_key=os.getenv("GOOGLE_API_KEY"), + system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + ) tavus = TavusVideoService( api_key=os.getenv("TAVUS_API_KEY"), @@ -72,14 +75,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): session=session, ) - messages = [ - { - "role": "system", - "content": "You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", - }, - ] - - context = LLMContext(messages) + context = LLMContext() user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()), @@ -113,7 +109,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): async def on_client_connected(transport, client): logger.info(f"Client connected") # Kick off the conversation. - messages.append( + context.add_message( { "role": "system", "content": "Start by greeting the user and ask how you can help.", diff --git a/examples/foundational/23-bot-background-sound.py b/examples/foundational/23-bot-background-sound.py index f2b99af19..a57e8f446 100644 --- a/examples/foundational/23-bot-background-sound.py +++ b/examples/foundational/23-bot-background-sound.py @@ -78,16 +78,12 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): voice_id="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady ) - llm = OpenAILLMService(api_key=os.getenv("OPENAI_API_KEY")) + llm = OpenAILLMService( + api_key=os.getenv("OPENAI_API_KEY"), + system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + ) - messages = [ - { - "role": "system", - "content": "You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", - }, - ] - - context = LLMContext(messages) + context = LLMContext() user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()), @@ -128,7 +124,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): logger.info(f"Re-enabling background sound and starting bot...") await task.queue_frame(MixerEnableFrame(True)) # Kick off the conversation. - messages.append({"role": "system", "content": "Please introduce yourself to the user."}) + context.add_message({"role": "system", "content": "Please introduce yourself to the user."}) await task.queue_frames([LLMRunFrame()]) @transport.event_handler("on_client_disconnected") diff --git a/examples/foundational/24-user-mute-strategy.py b/examples/foundational/24-user-mute-strategy.py index 0a1d2ffde..36b537e6a 100644 --- a/examples/foundational/24-user-mute-strategy.py +++ b/examples/foundational/24-user-mute-strategy.py @@ -73,7 +73,10 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): tts = DeepgramTTSService(api_key=os.getenv("DEEPGRAM_API_KEY"), voice="aura-helios-en") - llm = OpenAILLMService(api_key=os.getenv("OPENAI_API_KEY")) + llm = OpenAILLMService( + api_key=os.getenv("OPENAI_API_KEY"), + system_instruction="You are a helpful assistant who can check the weather. Always check the weather when a location is mentioned. Respond concisely and naturally. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points.", + ) llm.register_function("get_current_weather", fetch_weather_from_api) weather_function = FunctionSchema( @@ -94,14 +97,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): ) tools = ToolsSchema(standard_tools=[weather_function]) - messages = [ - { - "role": "system", - "content": "You are a helpful assistant who can check the weather. Always check the weather when a location is mentioned. Respond concisely and naturally. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points.", - }, - ] - - context = LLMContext(messages, tools) + context = LLMContext(tools=tools) user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, user_params=LLMUserAggregatorParams( @@ -138,7 +134,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): async def on_client_connected(transport, client): logger.info(f"Client connected") # Kick off the conversation with a weather-related prompt - messages.append( + context.add_message( { "role": "system", "content": "Ask the user what city they'd like to know the weather for.", diff --git a/examples/foundational/27-simli-layer.py b/examples/foundational/27-simli-layer.py index 7c44d083a..fb469fbe1 100644 --- a/examples/foundational/27-simli-layer.py +++ b/examples/foundational/27-simli-layer.py @@ -68,16 +68,13 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): face_id="cace3ef7-a4c4-425d-a8cf-a5358eb0c427", ) - llm = OpenAILLMService(api_key=os.getenv("OPENAI_API_KEY"), model="gpt-4o-mini") + llm = OpenAILLMService( + api_key=os.getenv("OPENAI_API_KEY"), + model="gpt-4o-mini", + system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + ) - messages = [ - { - "role": "system", - "content": "You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", - }, - ] - - context = LLMContext(messages) + context = LLMContext() user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()), diff --git a/examples/foundational/28-user-assistant-turns.py b/examples/foundational/28-user-assistant-turns.py index da38a894e..9dd1fa2a1 100644 --- a/examples/foundational/28-user-assistant-turns.py +++ b/examples/foundational/28-user-assistant-turns.py @@ -125,16 +125,12 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): voice_id="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady ) - llm = OpenAILLMService(api_key=os.getenv("OPENAI_API_KEY")) + llm = OpenAILLMService( + api_key=os.getenv("OPENAI_API_KEY"), + system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative, helpful, and brief way.", + ) - messages = [ - { - "role": "system", - "content": "You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative, helpful, and brief way. Say hello.", - }, - ] - - context = LLMContext(messages) + context = LLMContext() user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()), @@ -169,6 +165,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): async def on_client_connected(transport, client): logger.info(f"Client connected") # Start conversation - empty prompt to let LLM follow system instructions + context.add_message({"role": "system", "content": "Please introduce yourself to the user."}) await task.queue_frames([LLMRunFrame()]) @transport.event_handler("on_client_disconnected") diff --git a/examples/foundational/29-turn-tracking-observer.py b/examples/foundational/29-turn-tracking-observer.py index cf85972e1..9ba22dfda 100644 --- a/examples/foundational/29-turn-tracking-observer.py +++ b/examples/foundational/29-turn-tracking-observer.py @@ -76,7 +76,10 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): voice_id="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady ) - llm = OpenAILLMService(api_key=os.getenv("OPENAI_API_KEY")) + llm = OpenAILLMService( + api_key=os.getenv("OPENAI_API_KEY"), + system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + ) llm.register_function("get_current_weather", fetch_weather_from_api) llm.register_function("get_restaurant_recommendation", fetch_restaurant_recommendation) @@ -110,14 +113,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): ) tools = ToolsSchema(standard_tools=[weather_function, restaurant_function]) - messages = [ - { - "role": "system", - "content": "You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", - }, - ] - - context = LLMContext(messages, tools) + context = LLMContext(tools=tools) user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()), @@ -191,7 +187,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): async def on_client_connected(transport, client): logger.info(f"Client connected") # Kick off the conversation. - messages.append({"role": "system", "content": "Please introduce yourself to the user."}) + context.add_message({"role": "system", "content": "Please introduce yourself to the user."}) await task.queue_frames([LLMRunFrame()]) @transport.event_handler("on_client_disconnected") diff --git a/examples/foundational/30-observer.py b/examples/foundational/30-observer.py index 02a609061..4616e0e03 100644 --- a/examples/foundational/30-observer.py +++ b/examples/foundational/30-observer.py @@ -107,16 +107,12 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): voice_id="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady ) - llm = OpenAILLMService(api_key=os.getenv("OPENAI_API_KEY")) + llm = OpenAILLMService( + api_key=os.getenv("OPENAI_API_KEY"), + system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + ) - messages = [ - { - "role": "system", - "content": "You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", - }, - ] - - context = LLMContext(messages) + context = LLMContext() user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()), @@ -158,7 +154,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): async def on_client_connected(transport, client): logger.info(f"Client connected") # Kick off the conversation. - messages.append({"role": "system", "content": "Please introduce yourself to the user."}) + context.add_message({"role": "system", "content": "Please introduce yourself to the user."}) await task.queue_frames([LLMRunFrame()]) @transport.event_handler("on_client_disconnected") diff --git a/examples/foundational/34-audio-recording.py b/examples/foundational/34-audio-recording.py index 46366379f..8435acbde 100644 --- a/examples/foundational/34-audio-recording.py +++ b/examples/foundational/34-audio-recording.py @@ -115,19 +115,16 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): voice_id="71a7ad14-091c-4e8e-a314-022ece01c121", ) - llm = OpenAILLMService(api_key=os.getenv("OPENAI_API_KEY"), model="gpt-4") + llm = OpenAILLMService( + api_key=os.getenv("OPENAI_API_KEY"), + model="gpt-4", + system_instruction="You are a helpful assistant demonstrating audio recording capabilities. Keep your responses brief and clear.", + ) # Create audio buffer processor audiobuffer = AudioBufferProcessor() - messages = [ - { - "role": "system", - "content": "You are a helpful assistant demonstrating audio recording capabilities. Keep your responses brief and clear.", - }, - ] - - context = LLMContext(messages) + context = LLMContext() user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()), diff --git a/examples/foundational/36-user-email-gathering.py b/examples/foundational/36-user-email-gathering.py index 969a63efe..95450c695 100644 --- a/examples/foundational/36-user-email-gathering.py +++ b/examples/foundational/36-user-email-gathering.py @@ -79,7 +79,10 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): # aiohttp_session=session, # ) - llm = OpenAILLMService(api_key=os.getenv("OPENAI_API_KEY")) + llm = OpenAILLMService( + api_key=os.getenv("OPENAI_API_KEY"), + system_instruction="You need to gather a valid email or emails from the user. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. If the user provides one or more email addresses confirm them with the user. Enclose all emails with tags, for example a@a.com.", + ) # You can aslo register a function_name of None to get all functions # sent to the same callback with an additional function_name parameter. llm.register_function("store_user_emails", store_user_emails) @@ -98,17 +101,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): ) tools = ToolsSchema(standard_tools=[store_emails_function]) - messages = [ - { - "role": "system", - # Cartesia - "content": "You need to gather a valid email or emails from the user. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. If the user provides one or more email addresses confirm them with the user. Enclose all emails with tags, for example a@a.com.", - # Rime spell() - # "content": "You need to gather a valid email or emails from the user. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. If the user provides one or more email addresses confirm them with the user. Enclose all emails with spell(), for example spell(a@a.com).", - }, - ] - - context = LLMContext(messages, tools) + context = LLMContext(tools=tools) user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()), diff --git a/examples/foundational/37-mem0.py b/examples/foundational/37-mem0.py index 423695e9c..bfc651f3a 100644 --- a/examples/foundational/37-mem0.py +++ b/examples/foundational/37-mem0.py @@ -221,23 +221,20 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): # ) # Initialize LLM service - llm = OpenAILLMService(api_key=os.getenv("OPENAI_API_KEY"), model="gpt-4o-mini") - - messages = [ - { - "role": "system", - "content": """You are a personal assistant. You can remember things about the person you are talking to. + llm = OpenAILLMService( + api_key=os.getenv("OPENAI_API_KEY"), + model="gpt-4o-mini", + system_instruction="""You are a personal assistant. You can remember things about the person you are talking to. Some Guidelines: - Make sure your responses are friendly yet short and concise. - If the user asks you to remember something, make sure to remember it. - Greet the user by their name if you know about it. """, - }, - ] + ) # Set up conversation context and management # The context_aggregator will automatically collect conversation context - context = LLMContext(messages) + context = LLMContext() user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()), diff --git a/examples/foundational/38-smart-turn-fal.py b/examples/foundational/38-smart-turn-fal.py index ed4bfbae8..fe8992784 100644 --- a/examples/foundational/38-smart-turn-fal.py +++ b/examples/foundational/38-smart-turn-fal.py @@ -64,16 +64,12 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): voice_id="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady ) - llm = OpenAILLMService(api_key=os.getenv("OPENAI_API_KEY")) + llm = OpenAILLMService( + api_key=os.getenv("OPENAI_API_KEY"), + system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + ) - messages = [ - { - "role": "system", - "content": "You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", - }, - ] - - context = LLMContext(messages) + context = LLMContext() user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, user_params=LLMUserAggregatorParams( @@ -116,7 +112,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): async def on_client_connected(transport, client): logger.info(f"Client connected") # Kick off the conversation. - messages.append({"role": "system", "content": "Please introduce yourself to the user."}) + context.add_message({"role": "system", "content": "Please introduce yourself to the user."}) await task.queue_frames([LLMRunFrame()]) @transport.event_handler("on_client_disconnected") diff --git a/examples/foundational/38a-smart-turn-local-coreml.py b/examples/foundational/38a-smart-turn-local-coreml.py index 4284c675c..166fbbe12 100644 --- a/examples/foundational/38a-smart-turn-local-coreml.py +++ b/examples/foundational/38a-smart-turn-local-coreml.py @@ -79,16 +79,12 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): voice_id="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady ) - llm = OpenAILLMService(api_key=os.getenv("OPENAI_API_KEY")) + llm = OpenAILLMService( + api_key=os.getenv("OPENAI_API_KEY"), + system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + ) - messages = [ - { - "role": "system", - "content": "You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", - }, - ] - - context = LLMContext(messages) + context = LLMContext() user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, user_params=LLMUserAggregatorParams( @@ -130,7 +126,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): async def on_client_connected(transport, client): logger.info(f"Client connected") # Kick off the conversation. - messages.append({"role": "system", "content": "Please introduce yourself to the user."}) + context.add_message({"role": "system", "content": "Please introduce yourself to the user."}) await task.queue_frames([LLMRunFrame()]) @transport.event_handler("on_client_disconnected") diff --git a/examples/foundational/38b-smart-turn-local.py b/examples/foundational/38b-smart-turn-local.py index dc62010fb..962b608da 100644 --- a/examples/foundational/38b-smart-turn-local.py +++ b/examples/foundational/38b-smart-turn-local.py @@ -61,16 +61,12 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): voice_id="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady ) - llm = OpenAILLMService(api_key=os.getenv("OPENAI_API_KEY")) + llm = OpenAILLMService( + api_key=os.getenv("OPENAI_API_KEY"), + system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + ) - messages = [ - { - "role": "system", - "content": "You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", - }, - ] - - context = LLMContext(messages) + context = LLMContext() user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()), @@ -102,7 +98,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): async def on_client_connected(transport, client): logger.info(f"Client connected") # Kick off the conversation - messages.append({"role": "system", "content": "Please introduce yourself to the user."}) + context.add_message({"role": "system", "content": "Please introduce yourself to the user."}) await task.queue_frames([LLMRunFrame()]) @transport.event_handler("on_client_disconnected") diff --git a/examples/foundational/42-interruption-config.py b/examples/foundational/42-interruption-config.py index 1310af908..4491f9ee0 100644 --- a/examples/foundational/42-interruption-config.py +++ b/examples/foundational/42-interruption-config.py @@ -62,16 +62,12 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): voice_id="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady ) - llm = OpenAILLMService(api_key=os.getenv("OPENAI_API_KEY")) + llm = OpenAILLMService( + api_key=os.getenv("OPENAI_API_KEY"), + system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + ) - messages = [ - { - "role": "system", - "content": "You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", - }, - ] - - context = LLMContext(messages) + context = LLMContext() user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, user_params=LLMUserAggregatorParams( @@ -108,7 +104,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): async def on_client_connected(transport, client): logger.info(f"Client connected") # Kick off the conversation. - messages.append({"role": "system", "content": "Please introduce yourself to the user."}) + context.add_message({"role": "system", "content": "Please introduce yourself to the user."}) await task.queue_frames([LLMRunFrame()]) @transport.event_handler("on_client_disconnected") diff --git a/examples/foundational/43-heygen-transport.py b/examples/foundational/43-heygen-transport.py index dd31baa02..e38cb7b6e 100644 --- a/examples/foundational/43-heygen-transport.py +++ b/examples/foundational/43-heygen-transport.py @@ -59,16 +59,12 @@ async def main(): voice_id="00967b2f-88a6-4a31-8153-110a92134b9f", ) - llm = GoogleLLMService(api_key=os.getenv("GOOGLE_API_KEY")) + llm = GoogleLLMService( + api_key=os.getenv("GOOGLE_API_KEY"), + system_instruction="You are a helpful assistant. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Be succinct and respond to what the user said in a creative and helpful way.", + ) - messages = [ - { - "role": "system", - "content": "You are a helpful assistant. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Be succinct and respond to what the user said in a creative and helpful way.", - }, - ] - - context = LLMContext(messages) + context = LLMContext() user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()), @@ -98,7 +94,7 @@ async def main(): async def on_client_connected(transport, client): logger.info(f"Client connected") # Kick off the conversation. - messages.append( + context.add_message( { "role": "system", "content": "Start by saying 'Hello' and then a short greeting.", diff --git a/examples/foundational/43a-heygen-video-service.py b/examples/foundational/43a-heygen-video-service.py index ba3d4417d..2b23fe1f8 100644 --- a/examples/foundational/43a-heygen-video-service.py +++ b/examples/foundational/43a-heygen-video-service.py @@ -66,7 +66,10 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): voice_id="00967b2f-88a6-4a31-8153-110a92134b9f", ) - llm = GoogleLLMService(api_key=os.getenv("GOOGLE_API_KEY")) + llm = GoogleLLMService( + api_key=os.getenv("GOOGLE_API_KEY"), + system_instruction="You are a helpful assistant. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Be succinct and respond to what the user said in a creative and helpful way.", + ) heyGen = HeyGenVideoService( api_key=os.getenv("HEYGEN_LIVE_AVATAR_API_KEY"), @@ -80,14 +83,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): ), ) - messages = [ - { - "role": "system", - "content": "You are a helpful assistant. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Be succinct and respond to what the user said in a creative and helpful way.", - }, - ] - - context = LLMContext(messages) + context = LLMContext() user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()), @@ -131,7 +127,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): ) # Kick off the conversation. - messages.append( + context.add_message( { "role": "system", "content": "Start by saying 'Hello' and then a short greeting.", diff --git a/examples/foundational/44-voicemail-detection.py b/examples/foundational/44-voicemail-detection.py index 175cef695..f7cf14f71 100644 --- a/examples/foundational/44-voicemail-detection.py +++ b/examples/foundational/44-voicemail-detection.py @@ -59,19 +59,15 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): voice_id="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady ) - llm = OpenAILLMService(api_key=os.getenv("OPENAI_API_KEY")) + llm = OpenAILLMService( + api_key=os.getenv("OPENAI_API_KEY"), + system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + ) classifier_llm = OpenAILLMService(api_key=os.getenv("OPENAI_API_KEY")) voicemail = VoicemailDetector(llm=classifier_llm) - messages = [ - { - "role": "system", - "content": "You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", - }, - ] - - context = LLMContext(messages) + context = LLMContext() user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()), diff --git a/examples/foundational/45-before-and-after-events.py b/examples/foundational/45-before-and-after-events.py index 52dfbddaf..405af49f3 100644 --- a/examples/foundational/45-before-and-after-events.py +++ b/examples/foundational/45-before-and-after-events.py @@ -70,16 +70,12 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): voice_id="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady ) - llm = OpenAILLMService(api_key=os.getenv("OPENAI_API_KEY")) + llm = OpenAILLMService( + api_key=os.getenv("OPENAI_API_KEY"), + system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + ) - messages = [ - { - "role": "system", - "content": "You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", - }, - ] - - context = LLMContext(messages) + context = LLMContext() user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()), @@ -120,7 +116,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): async def on_client_connected(transport, client): logger.info(f"Client connected") # Kick off the conversation. - messages.append({"role": "system", "content": "Please introduce yourself to the user."}) + context.add_message({"role": "system", "content": "Please introduce yourself to the user."}) # Custom frames are pushed in order so they can be used for synchronization purposes. await task.queue_frames([CustomBeforeProcessFrame(), LLMRunFrame(), CustomAfterPushFrame()]) diff --git a/examples/foundational/47-sentry-metrics.py b/examples/foundational/47-sentry-metrics.py index e0649998d..ef20745e4 100644 --- a/examples/foundational/47-sentry-metrics.py +++ b/examples/foundational/47-sentry-metrics.py @@ -73,16 +73,10 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): llm = OpenAILLMService( api_key=os.getenv("OPENAI_API_KEY"), metrics=SentryMetrics(), + system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", ) - messages = [ - { - "role": "system", - "content": "You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", - }, - ] - - context = LLMContext(messages) + context = LLMContext() user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()), @@ -113,7 +107,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): async def on_client_connected(transport, client): logger.info(f"Client connected") # Kick off the conversation. - messages.append({"role": "system", "content": "Please introduce yourself to the user."}) + context.add_message({"role": "system", "content": "Please introduce yourself to the user."}) await task.queue_frames([LLMRunFrame()]) @transport.event_handler("on_client_disconnected") diff --git a/examples/foundational/49a-thinking-anthropic.py b/examples/foundational/49a-thinking-anthropic.py index 97e82666b..28dd33565 100644 --- a/examples/foundational/49a-thinking-anthropic.py +++ b/examples/foundational/49a-thinking-anthropic.py @@ -64,16 +64,10 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): params=AnthropicLLMService.InputParams( thinking=AnthropicLLMService.ThinkingConfig(type="enabled", budget_tokens=2048) ), + system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", ) - messages = [ - { - "role": "system", - "content": "You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", - }, - ] - - context = LLMContext(messages) + context = LLMContext() user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()), @@ -104,15 +98,10 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): async def on_client_connected(transport, client): logger.info(f"Client connected") # Kick off the conversation. - messages.append( - { - "role": "user", - "content": "Say hello briefly.", - } - ) + context.add_message({"role": "user", "content": "Say hello briefly."}) # Here are some example prompts conducive to demonstrating # thinking (picked from Google and Anthropic docs). - # messages.append( + # context.add_message( # { # "role": "user", # "content": "Analogize photosynthesis and growing up. Keep your answer concise.", diff --git a/examples/foundational/49b-thinking-google.py b/examples/foundational/49b-thinking-google.py index 855347729..32677bcbb 100644 --- a/examples/foundational/49b-thinking-google.py +++ b/examples/foundational/49b-thinking-google.py @@ -69,16 +69,10 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): include_thoughts=True, ) ), + system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", ) - messages = [ - { - "role": "system", - "content": "You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", - }, - ] - - context = LLMContext(messages) + context = LLMContext() user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()), @@ -109,16 +103,11 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): async def on_client_connected(transport, client): logger.info(f"Client connected") # Kick off the conversation. - messages.append( - { - "role": "user", - "content": "Say hello briefly.", - } - ) + context.add_message({"role": "user", "content": "Say hello briefly."}) # Replace the above with one of these example prompts to demonstrate # thinking. # These examples come from Gemini and Anthropic docs. - # messages.append( + # context.add_message( # { # "role": "user", # "content": "Analogize photosynthesis and growing up. Keep your answer concise.", diff --git a/examples/foundational/49c-thinking-functions-anthropic.py b/examples/foundational/49c-thinking-functions-anthropic.py index 6b16a67e1..b070871b1 100644 --- a/examples/foundational/49c-thinking-functions-anthropic.py +++ b/examples/foundational/49c-thinking-functions-anthropic.py @@ -85,6 +85,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): params=AnthropicLLMService.InputParams( thinking=AnthropicLLMService.ThinkingConfig(type="enabled", budget_tokens=2048) ), + system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", ) llm.register_direct_function(check_flight_status) @@ -92,14 +93,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): tools = ToolsSchema(standard_tools=[check_flight_status, book_taxi]) - messages = [ - { - "role": "system", - "content": "You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", - }, - ] - - context = LLMContext(messages, tools) + context = LLMContext(tools=tools) user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()), @@ -130,16 +124,11 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): async def on_client_connected(transport, client): logger.info(f"Client connected") # Kick off the conversation. - messages.append( - { - "role": "user", - "content": "Say hello briefly.", - } - ) + context.add_message({"role": "user", "content": "Say hello briefly."}) # Here is an example prompt conducive to demonstrating thinking and # function calling. # This example comes from Gemini docs. - # messages.append( + # context.add_message( # { # "role": "user", # "content": "Check the status of flight AA100 and, if it's delayed, book me a taxi 2 hours before its departure time.", diff --git a/examples/foundational/49d-thinking-functions-google.py b/examples/foundational/49d-thinking-functions-google.py index a377bf5ef..9b5a333de 100644 --- a/examples/foundational/49d-thinking-functions-google.py +++ b/examples/foundational/49d-thinking-functions-google.py @@ -90,6 +90,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): include_thoughts=True, ) ), + system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", ) llm.register_direct_function(check_flight_status) @@ -97,14 +98,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): tools = ToolsSchema(standard_tools=[check_flight_status, book_taxi]) - messages = [ - { - "role": "system", - "content": "You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", - }, - ] - - context = LLMContext(messages, tools) + context = LLMContext(tools=tools) user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()), @@ -135,16 +129,11 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): async def on_client_connected(transport, client): logger.info(f"Client connected") # Kick off the conversation. - messages.append( - { - "role": "user", - "content": "Say hello briefly.", - } - ) + context.add_message({"role": "user", "content": "Say hello briefly."}) # Replace the above with one of these example prompts to demonstrate # thinking and function calling. # This example comes from Gemini docs. - # messages.append( + # context.add_message( # { # "role": "user", # "content": "Check the status of flight AA100 and, if it's delayed, book me a taxi 2 hours before its departure time.", diff --git a/examples/foundational/52-live-translation.py b/examples/foundational/52-live-translation.py index 861d23e37..6ab0bac18 100644 --- a/examples/foundational/52-live-translation.py +++ b/examples/foundational/52-live-translation.py @@ -62,16 +62,12 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): voice_id="d4db5fb9-f44b-4bd1-85fa-192e0f0d75f9", # Spanish-speaking Lady ) - llm = OpenAILLMService(api_key=os.getenv("OPENAI_API_KEY")) + llm = OpenAILLMService( + api_key=os.getenv("OPENAI_API_KEY"), + system_instruction="You are a live translation assistant. Your sole purpose is to translate English text into Spanish. When you receive English text from the user, immediately translate it into natural, fluent Spanish. Do not add explanations, commentary, or extra information—only provide the Spanish translation of the text you receive.", + ) - messages = [ - { - "role": "system", - "content": "You are a live translation assistant. Your sole purpose is to translate English text into Spanish. When you receive English text from the user, immediately translate it into natural, fluent Spanish. Do not add explanations, commentary, or extra information—only provide the Spanish translation of the text you receive.", - }, - ] - - context = LLMContext(messages) + context = LLMContext() # We use the TranscriptionUserTurnStartStrategy to start a new user turn # every time a transcription is received. We disable interruptions, so the diff --git a/examples/foundational/54-context-summarization-openai.py b/examples/foundational/54-context-summarization-openai.py index ff6701bec..25ea496c3 100644 --- a/examples/foundational/54-context-summarization-openai.py +++ b/examples/foundational/54-context-summarization-openai.py @@ -84,7 +84,10 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): voice_id="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady ) - llm = OpenAILLMService(api_key=os.getenv("OPENAI_API_KEY")) + llm = OpenAILLMService( + api_key=os.getenv("OPENAI_API_KEY"), + system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way. You have access to tools to get the current weather - use them when relevant.", + ) # Register tool functions llm.register_function("get_current_weather", get_current_weather) @@ -107,14 +110,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): ) tools = ToolsSchema(standard_tools=[weather_function]) - messages = [ - { - "role": "system", - "content": "You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way. You have access to tools to get the current weather - use them when relevant.", - }, - ] - - context = LLMContext(messages, tools=tools) + context = LLMContext(tools=tools) # Create aggregators with summarization enabled user_aggregator, assistant_aggregator = LLMContextAggregatorPair( @@ -175,7 +171,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): async def on_client_connected(transport, client): logger.info("Client connected") # Kick off the conversation. - messages.append({"role": "system", "content": "Please introduce yourself to the user."}) + context.add_message({"role": "system", "content": "Please introduce yourself to the user."}) await task.queue_frames([LLMRunFrame()]) @transport.event_handler("on_client_disconnected") diff --git a/examples/foundational/54a-context-summarization-google.py b/examples/foundational/54a-context-summarization-google.py index 7d2a91310..c79e96c3d 100644 --- a/examples/foundational/54a-context-summarization-google.py +++ b/examples/foundational/54a-context-summarization-google.py @@ -84,7 +84,10 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): voice_id="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady ) - llm = GoogleLLMService(api_key=os.getenv("GOOGLE_API_KEY")) + llm = GoogleLLMService( + api_key=os.getenv("GOOGLE_API_KEY"), + system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way. You have access to tools to get the current weather - use them when relevant.", + ) # Register tool functions llm.register_function("get_current_weather", get_current_weather) @@ -107,14 +110,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): ) tools = ToolsSchema(standard_tools=[weather_function]) - messages = [ - { - "role": "system", - "content": "You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way. You have access to tools to get the current weather - use them when relevant.", - }, - ] - - context = LLMContext(messages, tools=tools) + context = LLMContext(tools=tools) # Create aggregators with summarization enabled user_aggregator, assistant_aggregator = LLMContextAggregatorPair( @@ -175,7 +171,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): async def on_client_connected(transport, client): logger.info("Client connected") # Kick off the conversation. - messages.append({"role": "system", "content": "Please introduce yourself to the user."}) + context.add_message({"role": "system", "content": "Please introduce yourself to the user."}) await task.queue_frames([LLMRunFrame()]) @transport.event_handler("on_client_disconnected") diff --git a/examples/foundational/55a-update-settings-deepgram-flux-stt.py b/examples/foundational/55a-update-settings-deepgram-flux-stt.py index a482e513c..ef58fe8fb 100644 --- a/examples/foundational/55a-update-settings-deepgram-flux-stt.py +++ b/examples/foundational/55a-update-settings-deepgram-flux-stt.py @@ -58,16 +58,12 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): voice_id="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady ) - llm = OpenAILLMService(api_key=os.getenv("OPENAI_API_KEY")) + llm = OpenAILLMService( + api_key=os.getenv("OPENAI_API_KEY"), + system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + ) - messages = [ - { - "role": "system", - "content": "You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", - }, - ] - - context = LLMContext(messages) + context = LLMContext() user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()), @@ -97,7 +93,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): @transport.event_handler("on_client_connected") async def on_client_connected(transport, client): logger.info(f"Client connected") - messages.append({"role": "system", "content": "Please introduce yourself to the user."}) + context.add_message({"role": "system", "content": "Please introduce yourself to the user."}) await task.queue_frames([LLMRunFrame()]) await asyncio.sleep(10) diff --git a/examples/foundational/55a-update-settings-deepgram-sagemaker-stt.py b/examples/foundational/55a-update-settings-deepgram-sagemaker-stt.py index 04451e85c..489ea1276 100644 --- a/examples/foundational/55a-update-settings-deepgram-sagemaker-stt.py +++ b/examples/foundational/55a-update-settings-deepgram-sagemaker-stt.py @@ -65,16 +65,12 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): voice_id="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady ) - llm = OpenAILLMService(api_key=os.getenv("OPENAI_API_KEY")) + llm = OpenAILLMService( + api_key=os.getenv("OPENAI_API_KEY"), + system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + ) - messages = [ - { - "role": "system", - "content": "You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", - }, - ] - - context = LLMContext(messages) + context = LLMContext() user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()), @@ -104,7 +100,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): @transport.event_handler("on_client_connected") async def on_client_connected(transport, client): logger.info(f"Client connected") - messages.append({"role": "system", "content": "Please introduce yourself to the user."}) + context.add_message({"role": "system", "content": "Please introduce yourself to the user."}) await task.queue_frames([LLMRunFrame()]) # NOTE: after this change, the bot will only respond if you speak Spanish diff --git a/examples/foundational/55a-update-settings-deepgram-stt.py b/examples/foundational/55a-update-settings-deepgram-stt.py index 8808f6f4c..b0521bb19 100644 --- a/examples/foundational/55a-update-settings-deepgram-stt.py +++ b/examples/foundational/55a-update-settings-deepgram-stt.py @@ -59,16 +59,12 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): voice_id="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady ) - llm = OpenAILLMService(api_key=os.getenv("OPENAI_API_KEY")) + llm = OpenAILLMService( + api_key=os.getenv("OPENAI_API_KEY"), + system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + ) - messages = [ - { - "role": "system", - "content": "You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", - }, - ] - - context = LLMContext(messages) + context = LLMContext() user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()), @@ -98,7 +94,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): @transport.event_handler("on_client_connected") async def on_client_connected(transport, client): logger.info(f"Client connected") - messages.append({"role": "system", "content": "Please introduce yourself to the user."}) + context.add_message({"role": "system", "content": "Please introduce yourself to the user."}) await task.queue_frames([LLMRunFrame()]) # NOTE: after this change, the bot will only respond if you speak Spanish diff --git a/examples/foundational/55b-update-settings-azure-stt.py b/examples/foundational/55b-update-settings-azure-stt.py index 96e4041d0..1d3b3fcee 100644 --- a/examples/foundational/55b-update-settings-azure-stt.py +++ b/examples/foundational/55b-update-settings-azure-stt.py @@ -61,16 +61,12 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): voice_id="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady ) - llm = OpenAILLMService(api_key=os.getenv("OPENAI_API_KEY")) + llm = OpenAILLMService( + api_key=os.getenv("OPENAI_API_KEY"), + system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + ) - messages = [ - { - "role": "system", - "content": "You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", - }, - ] - - context = LLMContext(messages) + context = LLMContext() user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()), @@ -100,7 +96,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): @transport.event_handler("on_client_connected") async def on_client_connected(transport, client): logger.info(f"Client connected") - messages.append({"role": "system", "content": "Please introduce yourself to the user."}) + context.add_message({"role": "system", "content": "Please introduce yourself to the user."}) await task.queue_frames([LLMRunFrame()]) await asyncio.sleep(10) diff --git a/examples/foundational/55c-update-settings-google-stt.py b/examples/foundational/55c-update-settings-google-stt.py index dede5b173..2956b8047 100644 --- a/examples/foundational/55c-update-settings-google-stt.py +++ b/examples/foundational/55c-update-settings-google-stt.py @@ -58,16 +58,12 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): voice_id="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady ) - llm = OpenAILLMService(api_key=os.getenv("OPENAI_API_KEY")) + llm = OpenAILLMService( + api_key=os.getenv("OPENAI_API_KEY"), + system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + ) - messages = [ - { - "role": "system", - "content": "You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", - }, - ] - - context = LLMContext(messages) + context = LLMContext() user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()), @@ -97,7 +93,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): @transport.event_handler("on_client_connected") async def on_client_connected(transport, client): logger.info(f"Client connected") - messages.append({"role": "system", "content": "Please introduce yourself to the user."}) + context.add_message({"role": "system", "content": "Please introduce yourself to the user."}) await task.queue_frames([LLMRunFrame()]) await asyncio.sleep(10) diff --git a/examples/foundational/55d-update-settings-assemblyai-stt.py b/examples/foundational/55d-update-settings-assemblyai-stt.py index f57865588..f8c366a44 100644 --- a/examples/foundational/55d-update-settings-assemblyai-stt.py +++ b/examples/foundational/55d-update-settings-assemblyai-stt.py @@ -63,16 +63,12 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): voice_id="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady ) - llm = OpenAILLMService(api_key=os.getenv("OPENAI_API_KEY")) + llm = OpenAILLMService( + api_key=os.getenv("OPENAI_API_KEY"), + system_instruction="You are a helpful LLM in a WebRTC call demonstrating dynamic keyterms updates. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Try saying difficult names like 'Xiomara', 'Saoirse', or 'Krzystof' to test transcription accuracy.", + ) - messages = [ - { - "role": "system", - "content": "You are a helpful LLM in a WebRTC call demonstrating dynamic keyterms updates. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Try saying difficult names like 'Xiomara', 'Saoirse', or 'Krzystof' to test transcription accuracy.", - }, - ] - - context = LLMContext(messages) + context = LLMContext() user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()), @@ -105,7 +101,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): logger.info( "Phase 1: No keyterms boosting - try saying 'Xiomara', 'Saoirse', or 'Krzystof'" ) - messages.append({"role": "system", "content": "Please introduce yourself to the user."}) + context.add_message({"role": "system", "content": "Please introduce yourself to the user."}) await task.queue_frames([LLMRunFrame()]) await asyncio.sleep(15) diff --git a/examples/foundational/55e-update-settings-gladia-stt.py b/examples/foundational/55e-update-settings-gladia-stt.py index e5bd5486a..5b8283f72 100644 --- a/examples/foundational/55e-update-settings-gladia-stt.py +++ b/examples/foundational/55e-update-settings-gladia-stt.py @@ -58,16 +58,12 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): voice_id="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady ) - llm = OpenAILLMService(api_key=os.getenv("OPENAI_API_KEY")) + llm = OpenAILLMService( + api_key=os.getenv("OPENAI_API_KEY"), + system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + ) - messages = [ - { - "role": "system", - "content": "You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", - }, - ] - - context = LLMContext(messages) + context = LLMContext() user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()), @@ -97,7 +93,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): @transport.event_handler("on_client_connected") async def on_client_connected(transport, client): logger.info(f"Client connected") - messages.append({"role": "system", "content": "Please introduce yourself to the user."}) + context.add_message({"role": "system", "content": "Please introduce yourself to the user."}) await task.queue_frames([LLMRunFrame()]) await asyncio.sleep(10) diff --git a/examples/foundational/55f-update-settings-elevenlabs-realtime-stt.py b/examples/foundational/55f-update-settings-elevenlabs-realtime-stt.py index c3f0a6325..8d2c17778 100644 --- a/examples/foundational/55f-update-settings-elevenlabs-realtime-stt.py +++ b/examples/foundational/55f-update-settings-elevenlabs-realtime-stt.py @@ -61,16 +61,12 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): voice_id="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady ) - llm = OpenAILLMService(api_key=os.getenv("OPENAI_API_KEY")) + llm = OpenAILLMService( + api_key=os.getenv("OPENAI_API_KEY"), + system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + ) - messages = [ - { - "role": "system", - "content": "You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", - }, - ] - - context = LLMContext(messages) + context = LLMContext() user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()), @@ -100,7 +96,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): @transport.event_handler("on_client_connected") async def on_client_connected(transport, client): logger.info(f"Client connected") - messages.append({"role": "system", "content": "Please introduce yourself to the user."}) + context.add_message({"role": "system", "content": "Please introduce yourself to the user."}) await task.queue_frames([LLMRunFrame()]) await asyncio.sleep(10) diff --git a/examples/foundational/55g-update-settings-elevenlabs-stt.py b/examples/foundational/55g-update-settings-elevenlabs-stt.py index 9435bc1ac..0395f273d 100644 --- a/examples/foundational/55g-update-settings-elevenlabs-stt.py +++ b/examples/foundational/55g-update-settings-elevenlabs-stt.py @@ -63,16 +63,12 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): voice_id="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady ) - llm = OpenAILLMService(api_key=os.getenv("OPENAI_API_KEY")) + llm = OpenAILLMService( + api_key=os.getenv("OPENAI_API_KEY"), + system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + ) - messages = [ - { - "role": "system", - "content": "You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", - }, - ] - - context = LLMContext(messages) + context = LLMContext() user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()), @@ -102,7 +98,9 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): @transport.event_handler("on_client_connected") async def on_client_connected(transport, client): logger.info(f"Client connected") - messages.append({"role": "system", "content": "Please introduce yourself to the user."}) + context.add_message( + {"role": "system", "content": "Please introduce yourself to the user."} + ) await task.queue_frames([LLMRunFrame()]) await asyncio.sleep(10) diff --git a/examples/foundational/55h-update-settings-speechmatics-stt.py b/examples/foundational/55h-update-settings-speechmatics-stt.py index c362d2f9f..ba775199a 100644 --- a/examples/foundational/55h-update-settings-speechmatics-stt.py +++ b/examples/foundational/55h-update-settings-speechmatics-stt.py @@ -65,16 +65,12 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): voice_id="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady ) - llm = OpenAILLMService(api_key=os.getenv("OPENAI_API_KEY")) + llm = OpenAILLMService( + api_key=os.getenv("OPENAI_API_KEY"), + system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + ) - messages = [ - { - "role": "system", - "content": "You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", - }, - ] - - context = LLMContext(messages) + context = LLMContext() user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()), @@ -104,7 +100,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): @transport.event_handler("on_client_connected") async def on_client_connected(transport, client): logger.info(f"Client connected") - messages.append({"role": "system", "content": "Please introduce yourself to the user."}) + context.add_message({"role": "system", "content": "Please introduce yourself to the user."}) await task.queue_frames([LLMRunFrame()]) await asyncio.sleep(10) diff --git a/examples/foundational/55i-update-settings-whisper-api-stt.py b/examples/foundational/55i-update-settings-whisper-api-stt.py index 741601c83..962a70485 100644 --- a/examples/foundational/55i-update-settings-whisper-api-stt.py +++ b/examples/foundational/55i-update-settings-whisper-api-stt.py @@ -64,16 +64,12 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): voice_id="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady ) - llm = OpenAILLMService(api_key=os.getenv("OPENAI_API_KEY")) + llm = OpenAILLMService( + api_key=os.getenv("OPENAI_API_KEY"), + system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + ) - messages = [ - { - "role": "system", - "content": "You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", - }, - ] - - context = LLMContext(messages) + context = LLMContext() user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()), @@ -103,7 +99,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): @transport.event_handler("on_client_connected") async def on_client_connected(transport, client): logger.info(f"Client connected") - messages.append({"role": "system", "content": "Please introduce yourself to the user."}) + context.add_message({"role": "system", "content": "Please introduce yourself to the user."}) await task.queue_frames([LLMRunFrame()]) await asyncio.sleep(10) diff --git a/examples/foundational/55j-update-settings-sarvam-stt.py b/examples/foundational/55j-update-settings-sarvam-stt.py index cab9656f8..58f0f80c7 100644 --- a/examples/foundational/55j-update-settings-sarvam-stt.py +++ b/examples/foundational/55j-update-settings-sarvam-stt.py @@ -58,16 +58,12 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): voice_id="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady ) - llm = OpenAILLMService(api_key=os.getenv("OPENAI_API_KEY")) + llm = OpenAILLMService( + api_key=os.getenv("OPENAI_API_KEY"), + system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + ) - messages = [ - { - "role": "system", - "content": "You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", - }, - ] - - context = LLMContext(messages) + context = LLMContext() user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()), @@ -97,7 +93,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): @transport.event_handler("on_client_connected") async def on_client_connected(transport, client): logger.info(f"Client connected") - messages.append({"role": "system", "content": "Please introduce yourself to the user."}) + context.add_message({"role": "system", "content": "Please introduce yourself to the user."}) await task.queue_frames([LLMRunFrame()]) await asyncio.sleep(10) diff --git a/examples/foundational/55k-update-settings-soniox-stt.py b/examples/foundational/55k-update-settings-soniox-stt.py index 85b5d2ba4..b31a0e708 100644 --- a/examples/foundational/55k-update-settings-soniox-stt.py +++ b/examples/foundational/55k-update-settings-soniox-stt.py @@ -58,16 +58,12 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): voice_id="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady ) - llm = OpenAILLMService(api_key=os.getenv("OPENAI_API_KEY")) + llm = OpenAILLMService( + api_key=os.getenv("OPENAI_API_KEY"), + system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + ) - messages = [ - { - "role": "system", - "content": "You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", - }, - ] - - context = LLMContext(messages) + context = LLMContext() user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()), @@ -97,7 +93,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): @transport.event_handler("on_client_connected") async def on_client_connected(transport, client): logger.info(f"Client connected") - messages.append({"role": "system", "content": "Please introduce yourself to the user."}) + context.add_message({"role": "system", "content": "Please introduce yourself to the user."}) await task.queue_frames([LLMRunFrame()]) await asyncio.sleep(10) diff --git a/examples/foundational/55l-update-settings-aws-transcribe-stt.py b/examples/foundational/55l-update-settings-aws-transcribe-stt.py index 3bfeb2faf..910bc66b4 100644 --- a/examples/foundational/55l-update-settings-aws-transcribe-stt.py +++ b/examples/foundational/55l-update-settings-aws-transcribe-stt.py @@ -58,16 +58,12 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): voice_id="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady ) - llm = OpenAILLMService(api_key=os.getenv("OPENAI_API_KEY")) + llm = OpenAILLMService( + api_key=os.getenv("OPENAI_API_KEY"), + system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + ) - messages = [ - { - "role": "system", - "content": "You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", - }, - ] - - context = LLMContext(messages) + context = LLMContext() user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()), @@ -97,7 +93,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): @transport.event_handler("on_client_connected") async def on_client_connected(transport, client): logger.info(f"Client connected") - messages.append({"role": "system", "content": "Please introduce yourself to the user."}) + context.add_message({"role": "system", "content": "Please introduce yourself to the user."}) await task.queue_frames([LLMRunFrame()]) await asyncio.sleep(10) diff --git a/examples/foundational/55m-update-settings-cartesia-stt.py b/examples/foundational/55m-update-settings-cartesia-stt.py index a87847a5a..4956d8d75 100644 --- a/examples/foundational/55m-update-settings-cartesia-stt.py +++ b/examples/foundational/55m-update-settings-cartesia-stt.py @@ -58,16 +58,12 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): voice_id="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady ) - llm = OpenAILLMService(api_key=os.getenv("OPENAI_API_KEY")) + llm = OpenAILLMService( + api_key=os.getenv("OPENAI_API_KEY"), + system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + ) - messages = [ - { - "role": "system", - "content": "You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", - }, - ] - - context = LLMContext(messages) + context = LLMContext() user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()), @@ -97,7 +93,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): @transport.event_handler("on_client_connected") async def on_client_connected(transport, client): logger.info(f"Client connected") - messages.append({"role": "system", "content": "Please introduce yourself to the user."}) + context.add_message({"role": "system", "content": "Please introduce yourself to the user."}) await task.queue_frames([LLMRunFrame()]) await asyncio.sleep(10) diff --git a/examples/foundational/55n-update-settings-cartesia-http-tts.py b/examples/foundational/55n-update-settings-cartesia-http-tts.py index 02d3bca2a..0423d855f 100644 --- a/examples/foundational/55n-update-settings-cartesia-http-tts.py +++ b/examples/foundational/55n-update-settings-cartesia-http-tts.py @@ -61,16 +61,12 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): voice_id="71a7ad14-091c-4e8e-a314-022ece01c121", ) - llm = OpenAILLMService(api_key=os.getenv("OPENAI_API_KEY")) + llm = OpenAILLMService( + api_key=os.getenv("OPENAI_API_KEY"), + system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + ) - messages = [ - { - "role": "system", - "content": "You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", - }, - ] - - context = LLMContext(messages) + context = LLMContext() user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()), @@ -100,7 +96,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): @transport.event_handler("on_client_connected") async def on_client_connected(transport, client): logger.info(f"Client connected") - messages.append({"role": "system", "content": "Please introduce yourself to the user."}) + context.add_message({"role": "system", "content": "Please introduce yourself to the user."}) await task.queue_frames([LLMRunFrame()]) await asyncio.sleep(10) diff --git a/examples/foundational/55n-update-settings-cartesia-tts.py b/examples/foundational/55n-update-settings-cartesia-tts.py index 04e9d8fee..2ee07b830 100644 --- a/examples/foundational/55n-update-settings-cartesia-tts.py +++ b/examples/foundational/55n-update-settings-cartesia-tts.py @@ -59,16 +59,12 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): voice_id="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady ) - llm = OpenAILLMService(api_key=os.getenv("OPENAI_API_KEY")) + llm = OpenAILLMService( + api_key=os.getenv("OPENAI_API_KEY"), + system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + ) - messages = [ - { - "role": "system", - "content": "You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", - }, - ] - - context = LLMContext(messages) + context = LLMContext() user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()), @@ -99,7 +95,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): async def on_client_connected(transport, client): logger.info(f"Client connected") # Kick off the conversation. - messages.append({"role": "system", "content": "Please introduce yourself to the user."}) + context.add_message({"role": "system", "content": "Please introduce yourself to the user."}) await task.queue_frames([LLMRunFrame()]) await asyncio.sleep(10) diff --git a/examples/foundational/55o-update-settings-elevenlabs-http-tts.py b/examples/foundational/55o-update-settings-elevenlabs-http-tts.py index 2ca51730f..7cdf97c25 100644 --- a/examples/foundational/55o-update-settings-elevenlabs-http-tts.py +++ b/examples/foundational/55o-update-settings-elevenlabs-http-tts.py @@ -62,16 +62,12 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): aiohttp_session=session, ) - llm = OpenAILLMService(api_key=os.getenv("OPENAI_API_KEY")) + llm = OpenAILLMService( + api_key=os.getenv("OPENAI_API_KEY"), + system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + ) - messages = [ - { - "role": "system", - "content": "You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", - }, - ] - - context = LLMContext(messages) + context = LLMContext() user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()), @@ -101,7 +97,9 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): @transport.event_handler("on_client_connected") async def on_client_connected(transport, client): logger.info(f"Client connected") - messages.append({"role": "system", "content": "Please introduce yourself to the user."}) + context.add_message( + {"role": "system", "content": "Please introduce yourself to the user."} + ) await task.queue_frames([LLMRunFrame()]) await asyncio.sleep(10) diff --git a/examples/foundational/55o-update-settings-elevenlabs-tts.py b/examples/foundational/55o-update-settings-elevenlabs-tts.py index ddbfd8b8f..6d5d74a17 100644 --- a/examples/foundational/55o-update-settings-elevenlabs-tts.py +++ b/examples/foundational/55o-update-settings-elevenlabs-tts.py @@ -58,16 +58,12 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): voice_id=os.getenv("ELEVENLABS_VOICE_ID"), ) - llm = OpenAILLMService(api_key=os.getenv("OPENAI_API_KEY")) + llm = OpenAILLMService( + api_key=os.getenv("OPENAI_API_KEY"), + system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + ) - messages = [ - { - "role": "system", - "content": "You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", - }, - ] - - context = LLMContext(messages) + context = LLMContext() user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()), @@ -97,7 +93,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): @transport.event_handler("on_client_connected") async def on_client_connected(transport, client): logger.info(f"Client connected") - messages.append({"role": "system", "content": "Please introduce yourself to the user."}) + context.add_message({"role": "system", "content": "Please introduce yourself to the user."}) await task.queue_frames([LLMRunFrame()]) await asyncio.sleep(10) diff --git a/examples/foundational/55p-update-settings-openai-tts.py b/examples/foundational/55p-update-settings-openai-tts.py index fcc24fb76..e108f4949 100644 --- a/examples/foundational/55p-update-settings-openai-tts.py +++ b/examples/foundational/55p-update-settings-openai-tts.py @@ -54,16 +54,12 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): tts = OpenAITTSService(api_key=os.getenv("OPENAI_API_KEY")) - llm = OpenAILLMService(api_key=os.getenv("OPENAI_API_KEY")) + llm = OpenAILLMService( + api_key=os.getenv("OPENAI_API_KEY"), + system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + ) - messages = [ - { - "role": "system", - "content": "You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", - }, - ] - - context = LLMContext(messages) + context = LLMContext() user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()), @@ -94,7 +90,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): @transport.event_handler("on_client_connected") async def on_client_connected(transport, client): logger.info(f"Client connected") - messages.append({"role": "system", "content": "Please introduce yourself to the user."}) + context.add_message({"role": "system", "content": "Please introduce yourself to the user."}) await task.queue_frames([LLMRunFrame()]) await asyncio.sleep(10) diff --git a/examples/foundational/55q-update-settings-deepgram-http-tts.py b/examples/foundational/55q-update-settings-deepgram-http-tts.py index d94bf631a..653e2bd63 100644 --- a/examples/foundational/55q-update-settings-deepgram-http-tts.py +++ b/examples/foundational/55q-update-settings-deepgram-http-tts.py @@ -61,16 +61,12 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): aiohttp_session=session, ) - llm = OpenAILLMService(api_key=os.getenv("OPENAI_API_KEY")) + llm = OpenAILLMService( + api_key=os.getenv("OPENAI_API_KEY"), + system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + ) - messages = [ - { - "role": "system", - "content": "You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", - }, - ] - - context = LLMContext(messages) + context = LLMContext() user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()), @@ -100,7 +96,9 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): @transport.event_handler("on_client_connected") async def on_client_connected(transport, client): logger.info(f"Client connected") - messages.append({"role": "system", "content": "Please introduce yourself to the user."}) + context.add_message( + {"role": "system", "content": "Please introduce yourself to the user."} + ) await task.queue_frames([LLMRunFrame()]) await asyncio.sleep(10) diff --git a/examples/foundational/55q-update-settings-deepgram-sagemaker-tts.py b/examples/foundational/55q-update-settings-deepgram-sagemaker-tts.py index 14958b9d2..6cd396d04 100644 --- a/examples/foundational/55q-update-settings-deepgram-sagemaker-tts.py +++ b/examples/foundational/55q-update-settings-deepgram-sagemaker-tts.py @@ -61,16 +61,12 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): voice="aura-2-helena-en", ) - llm = OpenAILLMService(api_key=os.getenv("OPENAI_API_KEY")) + llm = OpenAILLMService( + api_key=os.getenv("OPENAI_API_KEY"), + system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + ) - messages = [ - { - "role": "system", - "content": "You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", - }, - ] - - context = LLMContext(messages) + context = LLMContext() user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()), @@ -100,7 +96,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): @transport.event_handler("on_client_connected") async def on_client_connected(transport, client): logger.info(f"Client connected") - messages.append({"role": "system", "content": "Please introduce yourself to the user."}) + context.add_message({"role": "system", "content": "Please introduce yourself to the user."}) await task.queue_frames([LLMRunFrame()]) await asyncio.sleep(10) diff --git a/examples/foundational/55q-update-settings-deepgram-tts.py b/examples/foundational/55q-update-settings-deepgram-tts.py index e205ffa73..86d37374a 100644 --- a/examples/foundational/55q-update-settings-deepgram-tts.py +++ b/examples/foundational/55q-update-settings-deepgram-tts.py @@ -54,16 +54,12 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): tts = DeepgramTTSService(api_key=os.getenv("DEEPGRAM_API_KEY")) - llm = OpenAILLMService(api_key=os.getenv("OPENAI_API_KEY")) + llm = OpenAILLMService( + api_key=os.getenv("OPENAI_API_KEY"), + system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + ) - messages = [ - { - "role": "system", - "content": "You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", - }, - ] - - context = LLMContext(messages) + context = LLMContext() user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()), @@ -93,7 +89,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): @transport.event_handler("on_client_connected") async def on_client_connected(transport, client): logger.info(f"Client connected") - messages.append({"role": "system", "content": "Please introduce yourself to the user."}) + context.add_message({"role": "system", "content": "Please introduce yourself to the user."}) await task.queue_frames([LLMRunFrame()]) await asyncio.sleep(10) diff --git a/examples/foundational/55r-update-settings-azure-http-tts.py b/examples/foundational/55r-update-settings-azure-http-tts.py index 0e4df5e7c..d6b870cc7 100644 --- a/examples/foundational/55r-update-settings-azure-http-tts.py +++ b/examples/foundational/55r-update-settings-azure-http-tts.py @@ -57,16 +57,12 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): region=os.getenv("AZURE_SPEECH_REGION"), ) - llm = OpenAILLMService(api_key=os.getenv("OPENAI_API_KEY")) + llm = OpenAILLMService( + api_key=os.getenv("OPENAI_API_KEY"), + system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + ) - messages = [ - { - "role": "system", - "content": "You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", - }, - ] - - context = LLMContext(messages) + context = LLMContext() user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()), @@ -96,7 +92,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): @transport.event_handler("on_client_connected") async def on_client_connected(transport, client): logger.info(f"Client connected") - messages.append({"role": "system", "content": "Please introduce yourself to the user."}) + context.add_message({"role": "system", "content": "Please introduce yourself to the user."}) await task.queue_frames([LLMRunFrame()]) await asyncio.sleep(10) diff --git a/examples/foundational/55r-update-settings-azure-tts.py b/examples/foundational/55r-update-settings-azure-tts.py index a32dad5ed..a564a7267 100644 --- a/examples/foundational/55r-update-settings-azure-tts.py +++ b/examples/foundational/55r-update-settings-azure-tts.py @@ -57,16 +57,12 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): region=os.getenv("AZURE_SPEECH_REGION"), ) - llm = OpenAILLMService(api_key=os.getenv("OPENAI_API_KEY")) + llm = OpenAILLMService( + api_key=os.getenv("OPENAI_API_KEY"), + system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + ) - messages = [ - { - "role": "system", - "content": "You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", - }, - ] - - context = LLMContext(messages) + context = LLMContext() user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()), @@ -96,7 +92,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): @transport.event_handler("on_client_connected") async def on_client_connected(transport, client): logger.info(f"Client connected") - messages.append({"role": "system", "content": "Please introduce yourself to the user."}) + context.add_message({"role": "system", "content": "Please introduce yourself to the user."}) await task.queue_frames([LLMRunFrame()]) await asyncio.sleep(10) diff --git a/examples/foundational/55s-update-settings-google-http-tts.py b/examples/foundational/55s-update-settings-google-http-tts.py index ae3070124..146d5039e 100644 --- a/examples/foundational/55s-update-settings-google-http-tts.py +++ b/examples/foundational/55s-update-settings-google-http-tts.py @@ -54,16 +54,12 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): tts = GoogleHttpTTSService(credentials=os.getenv("GOOGLE_TEST_CREDENTIALS")) - llm = OpenAILLMService(api_key=os.getenv("OPENAI_API_KEY")) + llm = OpenAILLMService( + api_key=os.getenv("OPENAI_API_KEY"), + system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + ) - messages = [ - { - "role": "system", - "content": "You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", - }, - ] - - context = LLMContext(messages) + context = LLMContext() user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()), @@ -93,7 +89,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): @transport.event_handler("on_client_connected") async def on_client_connected(transport, client): logger.info(f"Client connected") - messages.append({"role": "system", "content": "Please introduce yourself to the user."}) + context.add_message({"role": "system", "content": "Please introduce yourself to the user."}) await task.queue_frames([LLMRunFrame()]) await asyncio.sleep(10) diff --git a/examples/foundational/55s-update-settings-google-stream-tts.py b/examples/foundational/55s-update-settings-google-stream-tts.py index 1aba64254..445ab537b 100644 --- a/examples/foundational/55s-update-settings-google-stream-tts.py +++ b/examples/foundational/55s-update-settings-google-stream-tts.py @@ -54,16 +54,12 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): tts = GoogleTTSService(credentials=os.getenv("GOOGLE_TEST_CREDENTIALS")) - llm = OpenAILLMService(api_key=os.getenv("OPENAI_API_KEY")) + llm = OpenAILLMService( + api_key=os.getenv("OPENAI_API_KEY"), + system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + ) - messages = [ - { - "role": "system", - "content": "You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", - }, - ] - - context = LLMContext(messages) + context = LLMContext() user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()), @@ -93,7 +89,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): @transport.event_handler("on_client_connected") async def on_client_connected(transport, client): logger.info(f"Client connected") - messages.append({"role": "system", "content": "Please introduce yourself to the user."}) + context.add_message({"role": "system", "content": "Please introduce yourself to the user."}) await task.queue_frames([LLMRunFrame()]) await asyncio.sleep(10) diff --git a/examples/foundational/55u-update-settings-rime-http-tts.py b/examples/foundational/55u-update-settings-rime-http-tts.py index 28e58ba08..f57d2b83e 100644 --- a/examples/foundational/55u-update-settings-rime-http-tts.py +++ b/examples/foundational/55u-update-settings-rime-http-tts.py @@ -60,16 +60,12 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): api_key=os.getenv("RIME_API_KEY"), voice_id="eva", aiohttp_session=session ) - llm = OpenAILLMService(api_key=os.getenv("OPENAI_API_KEY")) + llm = OpenAILLMService( + api_key=os.getenv("OPENAI_API_KEY"), + system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + ) - messages = [ - { - "role": "system", - "content": "You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", - }, - ] - - context = LLMContext(messages) + context = LLMContext() user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()), @@ -99,7 +95,9 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): @transport.event_handler("on_client_connected") async def on_client_connected(transport, client): logger.info(f"Client connected") - messages.append({"role": "system", "content": "Please introduce yourself to the user."}) + context.add_message( + {"role": "system", "content": "Please introduce yourself to the user."} + ) await task.queue_frames([LLMRunFrame()]) await asyncio.sleep(10) diff --git a/examples/foundational/55u-update-settings-rime-tts.py b/examples/foundational/55u-update-settings-rime-tts.py index 8992cb6db..5c4cdee67 100644 --- a/examples/foundational/55u-update-settings-rime-tts.py +++ b/examples/foundational/55u-update-settings-rime-tts.py @@ -57,16 +57,12 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): voice_id="luna", ) - llm = OpenAILLMService(api_key=os.getenv("OPENAI_API_KEY")) + llm = OpenAILLMService( + api_key=os.getenv("OPENAI_API_KEY"), + system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + ) - messages = [ - { - "role": "system", - "content": "You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", - }, - ] - - context = LLMContext(messages) + context = LLMContext() user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()), @@ -96,7 +92,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): @transport.event_handler("on_client_connected") async def on_client_connected(transport, client): logger.info(f"Client connected") - messages.append({"role": "system", "content": "Please introduce yourself to the user."}) + context.add_message({"role": "system", "content": "Please introduce yourself to the user."}) await task.queue_frames([LLMRunFrame()]) await asyncio.sleep(10) diff --git a/examples/foundational/55v-update-settings-lmnt-tts.py b/examples/foundational/55v-update-settings-lmnt-tts.py index 01bc15ddf..0a2c27401 100644 --- a/examples/foundational/55v-update-settings-lmnt-tts.py +++ b/examples/foundational/55v-update-settings-lmnt-tts.py @@ -57,16 +57,12 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): voice_id="lily", ) - llm = OpenAILLMService(api_key=os.getenv("OPENAI_API_KEY")) + llm = OpenAILLMService( + api_key=os.getenv("OPENAI_API_KEY"), + system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + ) - messages = [ - { - "role": "system", - "content": "You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", - }, - ] - - context = LLMContext(messages) + context = LLMContext() user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()), @@ -96,7 +92,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): @transport.event_handler("on_client_connected") async def on_client_connected(transport, client): logger.info(f"Client connected") - messages.append({"role": "system", "content": "Please introduce yourself to the user."}) + context.add_message({"role": "system", "content": "Please introduce yourself to the user."}) await task.queue_frames([LLMRunFrame()]) await asyncio.sleep(10) diff --git a/examples/foundational/55w-update-settings-fish-tts.py b/examples/foundational/55w-update-settings-fish-tts.py index 72a2160ba..87a4a2072 100644 --- a/examples/foundational/55w-update-settings-fish-tts.py +++ b/examples/foundational/55w-update-settings-fish-tts.py @@ -57,16 +57,12 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): model="4ce7e917cedd4bc2bb2e6ff3a46acaa1", # Barack Obama ) - llm = OpenAILLMService(api_key=os.getenv("OPENAI_API_KEY")) + llm = OpenAILLMService( + api_key=os.getenv("OPENAI_API_KEY"), + system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + ) - messages = [ - { - "role": "system", - "content": "You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", - }, - ] - - context = LLMContext(messages) + context = LLMContext() user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()), @@ -96,7 +92,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): @transport.event_handler("on_client_connected") async def on_client_connected(transport, client): logger.info(f"Client connected") - messages.append({"role": "system", "content": "Please introduce yourself to the user."}) + context.add_message({"role": "system", "content": "Please introduce yourself to the user."}) await task.queue_frames([LLMRunFrame()]) await asyncio.sleep(10) diff --git a/examples/foundational/55x-update-settings-minimax-tts.py b/examples/foundational/55x-update-settings-minimax-tts.py index fdb486415..66ce52071 100644 --- a/examples/foundational/55x-update-settings-minimax-tts.py +++ b/examples/foundational/55x-update-settings-minimax-tts.py @@ -60,16 +60,12 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): aiohttp_session=session, ) - llm = OpenAILLMService(api_key=os.getenv("OPENAI_API_KEY")) + llm = OpenAILLMService( + api_key=os.getenv("OPENAI_API_KEY"), + system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + ) - messages = [ - { - "role": "system", - "content": "You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", - }, - ] - - context = LLMContext(messages) + context = LLMContext() user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()), @@ -99,7 +95,9 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): @transport.event_handler("on_client_connected") async def on_client_connected(transport, client): logger.info(f"Client connected") - messages.append({"role": "system", "content": "Please introduce yourself to the user."}) + context.add_message( + {"role": "system", "content": "Please introduce yourself to the user."} + ) await task.queue_frames([LLMRunFrame()]) await asyncio.sleep(10) diff --git a/examples/foundational/55y-update-settings-groq-tts.py b/examples/foundational/55y-update-settings-groq-tts.py index 3531509f2..73e4ac778 100644 --- a/examples/foundational/55y-update-settings-groq-tts.py +++ b/examples/foundational/55y-update-settings-groq-tts.py @@ -54,16 +54,12 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): tts = GroqTTSService(api_key=os.getenv("GROQ_API_KEY")) - llm = OpenAILLMService(api_key=os.getenv("OPENAI_API_KEY")) + llm = OpenAILLMService( + api_key=os.getenv("OPENAI_API_KEY"), + system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + ) - messages = [ - { - "role": "system", - "content": "You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", - }, - ] - - context = LLMContext(messages) + context = LLMContext() user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()), @@ -93,7 +89,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): @transport.event_handler("on_client_connected") async def on_client_connected(transport, client): logger.info(f"Client connected") - messages.append({"role": "system", "content": "Please introduce yourself to the user."}) + context.add_message({"role": "system", "content": "Please introduce yourself to the user."}) await task.queue_frames([LLMRunFrame()]) await asyncio.sleep(10) diff --git a/examples/foundational/55z-update-settings-hume-tts.py b/examples/foundational/55z-update-settings-hume-tts.py index 493550469..f16745cad 100644 --- a/examples/foundational/55z-update-settings-hume-tts.py +++ b/examples/foundational/55z-update-settings-hume-tts.py @@ -57,16 +57,12 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): voice_id="f898a92e-685f-43fa-985b-a46920f0650b", ) - llm = OpenAILLMService(api_key=os.getenv("OPENAI_API_KEY")) + llm = OpenAILLMService( + api_key=os.getenv("OPENAI_API_KEY"), + system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + ) - messages = [ - { - "role": "system", - "content": "You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", - }, - ] - - context = LLMContext(messages) + context = LLMContext() user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()), @@ -96,7 +92,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): @transport.event_handler("on_client_connected") async def on_client_connected(transport, client): logger.info(f"Client connected") - messages.append({"role": "system", "content": "Please introduce yourself to the user."}) + context.add_message({"role": "system", "content": "Please introduce yourself to the user."}) await task.queue_frames([LLMRunFrame()]) await asyncio.sleep(10) diff --git a/examples/foundational/55za-update-settings-neuphonic-http-tts.py b/examples/foundational/55za-update-settings-neuphonic-http-tts.py index 6e1d18e4a..6c3e510a1 100644 --- a/examples/foundational/55za-update-settings-neuphonic-http-tts.py +++ b/examples/foundational/55za-update-settings-neuphonic-http-tts.py @@ -59,16 +59,12 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): aiohttp_session=session, ) - llm = OpenAILLMService(api_key=os.getenv("OPENAI_API_KEY")) + llm = OpenAILLMService( + api_key=os.getenv("OPENAI_API_KEY"), + system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + ) - messages = [ - { - "role": "system", - "content": "You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", - }, - ] - - context = LLMContext(messages) + context = LLMContext() user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()), @@ -98,7 +94,9 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): @transport.event_handler("on_client_connected") async def on_client_connected(transport, client): logger.info(f"Client connected") - messages.append({"role": "system", "content": "Please introduce yourself to the user."}) + context.add_message( + {"role": "system", "content": "Please introduce yourself to the user."} + ) await task.queue_frames([LLMRunFrame()]) await asyncio.sleep(10) diff --git a/examples/foundational/55za-update-settings-neuphonic-tts.py b/examples/foundational/55za-update-settings-neuphonic-tts.py index 861167a20..e79ac666f 100644 --- a/examples/foundational/55za-update-settings-neuphonic-tts.py +++ b/examples/foundational/55za-update-settings-neuphonic-tts.py @@ -54,16 +54,12 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): tts = NeuphonicTTSService(api_key=os.getenv("NEUPHONIC_API_KEY")) - llm = OpenAILLMService(api_key=os.getenv("OPENAI_API_KEY")) + llm = OpenAILLMService( + api_key=os.getenv("OPENAI_API_KEY"), + system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + ) - messages = [ - { - "role": "system", - "content": "You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", - }, - ] - - context = LLMContext(messages) + context = LLMContext() user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()), @@ -93,7 +89,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): @transport.event_handler("on_client_connected") async def on_client_connected(transport, client): logger.info(f"Client connected") - messages.append({"role": "system", "content": "Please introduce yourself to the user."}) + context.add_message({"role": "system", "content": "Please introduce yourself to the user."}) await task.queue_frames([LLMRunFrame()]) await asyncio.sleep(10) diff --git a/examples/foundational/55zb-update-settings-inworld-http-tts.py b/examples/foundational/55zb-update-settings-inworld-http-tts.py index 99353b87f..ccba1238c 100644 --- a/examples/foundational/55zb-update-settings-inworld-http-tts.py +++ b/examples/foundational/55zb-update-settings-inworld-http-tts.py @@ -58,16 +58,12 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): tts = InworldHttpTTSService(api_key=os.getenv("INWORLD_API_KEY"), aiohttp_session=session) - llm = OpenAILLMService(api_key=os.getenv("OPENAI_API_KEY")) + llm = OpenAILLMService( + api_key=os.getenv("OPENAI_API_KEY"), + system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + ) - messages = [ - { - "role": "system", - "content": "You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", - }, - ] - - context = LLMContext(messages) + context = LLMContext() user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()), @@ -97,7 +93,9 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): @transport.event_handler("on_client_connected") async def on_client_connected(transport, client): logger.info(f"Client connected") - messages.append({"role": "system", "content": "Please introduce yourself to the user."}) + context.add_message( + {"role": "system", "content": "Please introduce yourself to the user."} + ) await task.queue_frames([LLMRunFrame()]) await asyncio.sleep(10) diff --git a/examples/foundational/55zb-update-settings-inworld-tts.py b/examples/foundational/55zb-update-settings-inworld-tts.py index 104001c15..e60e65036 100644 --- a/examples/foundational/55zb-update-settings-inworld-tts.py +++ b/examples/foundational/55zb-update-settings-inworld-tts.py @@ -54,16 +54,12 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): tts = InworldTTSService(api_key=os.getenv("INWORLD_API_KEY")) - llm = OpenAILLMService(api_key=os.getenv("OPENAI_API_KEY")) + llm = OpenAILLMService( + api_key=os.getenv("OPENAI_API_KEY"), + system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + ) - messages = [ - { - "role": "system", - "content": "You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", - }, - ] - - context = LLMContext(messages) + context = LLMContext() user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()), @@ -93,7 +89,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): @transport.event_handler("on_client_connected") async def on_client_connected(transport, client): logger.info(f"Client connected") - messages.append({"role": "system", "content": "Please introduce yourself to the user."}) + context.add_message({"role": "system", "content": "Please introduce yourself to the user."}) await task.queue_frames([LLMRunFrame()]) await asyncio.sleep(10) diff --git a/examples/foundational/55zc-update-settings-gemini-tts.py b/examples/foundational/55zc-update-settings-gemini-tts.py index 21b678047..637ee65a7 100644 --- a/examples/foundational/55zc-update-settings-gemini-tts.py +++ b/examples/foundational/55zc-update-settings-gemini-tts.py @@ -63,16 +63,12 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): ), ) - llm = OpenAILLMService(api_key=os.getenv("OPENAI_API_KEY")) + llm = OpenAILLMService( + api_key=os.getenv("OPENAI_API_KEY"), + system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + ) - messages = [ - { - "role": "system", - "content": "You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", - }, - ] - - context = LLMContext(messages) + context = LLMContext() user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()), @@ -102,7 +98,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): @transport.event_handler("on_client_connected") async def on_client_connected(transport, client): logger.info(f"Client connected") - messages.append({"role": "system", "content": "Please introduce yourself to the user."}) + context.add_message({"role": "system", "content": "Please introduce yourself to the user."}) await task.queue_frames([LLMRunFrame()]) await asyncio.sleep(10) diff --git a/examples/foundational/55zd-update-settings-aws-polly-tts.py b/examples/foundational/55zd-update-settings-aws-polly-tts.py index 4392e7b6f..3b1c1d734 100644 --- a/examples/foundational/55zd-update-settings-aws-polly-tts.py +++ b/examples/foundational/55zd-update-settings-aws-polly-tts.py @@ -54,16 +54,12 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): tts = AWSPollyTTSService() - llm = OpenAILLMService(api_key=os.getenv("OPENAI_API_KEY")) + llm = OpenAILLMService( + api_key=os.getenv("OPENAI_API_KEY"), + system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + ) - messages = [ - { - "role": "system", - "content": "You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", - }, - ] - - context = LLMContext(messages) + context = LLMContext() user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()), @@ -93,7 +89,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): @transport.event_handler("on_client_connected") async def on_client_connected(transport, client): logger.info(f"Client connected") - messages.append({"role": "system", "content": "Please introduce yourself to the user."}) + context.add_message({"role": "system", "content": "Please introduce yourself to the user."}) await task.queue_frames([LLMRunFrame()]) await asyncio.sleep(10) diff --git a/examples/foundational/55ze-update-settings-sarvam-http-tts.py b/examples/foundational/55ze-update-settings-sarvam-http-tts.py index 7832a805a..ffcf086c6 100644 --- a/examples/foundational/55ze-update-settings-sarvam-http-tts.py +++ b/examples/foundational/55ze-update-settings-sarvam-http-tts.py @@ -58,16 +58,12 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): tts = SarvamHttpTTSService(api_key=os.getenv("SARVAM_API_KEY"), aiohttp_session=session) - llm = OpenAILLMService(api_key=os.getenv("OPENAI_API_KEY")) + llm = OpenAILLMService( + api_key=os.getenv("OPENAI_API_KEY"), + system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + ) - messages = [ - { - "role": "system", - "content": "You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", - }, - ] - - context = LLMContext(messages) + context = LLMContext() user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()), @@ -97,7 +93,9 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): @transport.event_handler("on_client_connected") async def on_client_connected(transport, client): logger.info(f"Client connected") - messages.append({"role": "system", "content": "Please introduce yourself to the user."}) + context.add_message( + {"role": "system", "content": "Please introduce yourself to the user."} + ) await task.queue_frames([LLMRunFrame()]) await asyncio.sleep(10) diff --git a/examples/foundational/55ze-update-settings-sarvam-tts.py b/examples/foundational/55ze-update-settings-sarvam-tts.py index e63c6046d..44301578f 100644 --- a/examples/foundational/55ze-update-settings-sarvam-tts.py +++ b/examples/foundational/55ze-update-settings-sarvam-tts.py @@ -54,16 +54,12 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): tts = SarvamTTSService(api_key=os.getenv("SARVAM_API_KEY")) - llm = OpenAILLMService(api_key=os.getenv("OPENAI_API_KEY")) + llm = OpenAILLMService( + api_key=os.getenv("OPENAI_API_KEY"), + system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + ) - messages = [ - { - "role": "system", - "content": "You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", - }, - ] - - context = LLMContext(messages) + context = LLMContext() user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()), @@ -93,7 +89,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): @transport.event_handler("on_client_connected") async def on_client_connected(transport, client): logger.info(f"Client connected") - messages.append({"role": "system", "content": "Please introduce yourself to the user."}) + context.add_message({"role": "system", "content": "Please introduce yourself to the user."}) await task.queue_frames([LLMRunFrame()]) await asyncio.sleep(10) diff --git a/examples/foundational/55zf-update-settings-camb-tts.py b/examples/foundational/55zf-update-settings-camb-tts.py index 82cc4a638..f8058141d 100644 --- a/examples/foundational/55zf-update-settings-camb-tts.py +++ b/examples/foundational/55zf-update-settings-camb-tts.py @@ -55,16 +55,12 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): tts = CambTTSService(api_key=os.getenv("CAMB_API_KEY")) - llm = OpenAILLMService(api_key=os.getenv("OPENAI_API_KEY")) + llm = OpenAILLMService( + api_key=os.getenv("OPENAI_API_KEY"), + system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + ) - messages = [ - { - "role": "system", - "content": "You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", - }, - ] - - context = LLMContext(messages) + context = LLMContext() user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()), @@ -94,7 +90,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): @transport.event_handler("on_client_connected") async def on_client_connected(transport, client): logger.info(f"Client connected") - messages.append({"role": "system", "content": "Please introduce yourself to the user."}) + context.add_message({"role": "system", "content": "Please introduce yourself to the user."}) await task.queue_frames([LLMRunFrame()]) await asyncio.sleep(10) diff --git a/examples/foundational/55zg-update-settings-hathora-tts.py b/examples/foundational/55zg-update-settings-hathora-tts.py index 80b9bfcce..2294809e2 100644 --- a/examples/foundational/55zg-update-settings-hathora-tts.py +++ b/examples/foundational/55zg-update-settings-hathora-tts.py @@ -57,16 +57,12 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): model="hexgrad-kokoro-82m", ) - llm = OpenAILLMService(api_key=os.getenv("OPENAI_API_KEY")) + llm = OpenAILLMService( + api_key=os.getenv("OPENAI_API_KEY"), + system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + ) - messages = [ - { - "role": "system", - "content": "You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", - }, - ] - - context = LLMContext(messages) + context = LLMContext() user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()), @@ -96,7 +92,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): @transport.event_handler("on_client_connected") async def on_client_connected(transport, client): logger.info(f"Client connected") - messages.append({"role": "system", "content": "Please introduce yourself to the user."}) + context.add_message({"role": "system", "content": "Please introduce yourself to the user."}) await task.queue_frames([LLMRunFrame()]) await asyncio.sleep(10) diff --git a/examples/foundational/55zh-update-settings-resembleai-tts.py b/examples/foundational/55zh-update-settings-resembleai-tts.py index 44688ee25..7aba67b1f 100644 --- a/examples/foundational/55zh-update-settings-resembleai-tts.py +++ b/examples/foundational/55zh-update-settings-resembleai-tts.py @@ -57,16 +57,12 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): voice_id=os.getenv("RESEMBLE_VOICE_UUID"), ) - llm = OpenAILLMService(api_key=os.getenv("OPENAI_API_KEY")) + llm = OpenAILLMService( + api_key=os.getenv("OPENAI_API_KEY"), + system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + ) - messages = [ - { - "role": "system", - "content": "You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", - }, - ] - - context = LLMContext(messages) + context = LLMContext() user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()), @@ -96,7 +92,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): @transport.event_handler("on_client_connected") async def on_client_connected(transport, client): logger.info(f"Client connected") - messages.append({"role": "system", "content": "Please introduce yourself to the user."}) + context.add_message({"role": "system", "content": "Please introduce yourself to the user."}) await task.queue_frames([LLMRunFrame()]) await asyncio.sleep(10) diff --git a/examples/foundational/55zi-update-settings-azure-llm.py b/examples/foundational/55zi-update-settings-azure-llm.py index 43161b103..b6e8ccf71 100644 --- a/examples/foundational/55zi-update-settings-azure-llm.py +++ b/examples/foundational/55zi-update-settings-azure-llm.py @@ -62,16 +62,10 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): api_key=os.getenv("AZURE_CHATGPT_API_KEY"), endpoint=os.getenv("AZURE_CHATGPT_ENDPOINT"), model=os.getenv("AZURE_CHATGPT_MODEL"), + system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", ) - messages = [ - { - "role": "system", - "content": "You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", - }, - ] - - context = LLMContext(messages) + context = LLMContext() user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()), @@ -101,7 +95,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): @transport.event_handler("on_client_connected") async def on_client_connected(transport, client): logger.info(f"Client connected") - messages.append({"role": "system", "content": "Please introduce yourself to the user."}) + context.add_message({"role": "system", "content": "Please introduce yourself to the user."}) await task.queue_frames([LLMRunFrame()]) await asyncio.sleep(10) diff --git a/examples/foundational/55zi-update-settings-openai-llm.py b/examples/foundational/55zi-update-settings-openai-llm.py index d84259cc3..c9fb026f3 100644 --- a/examples/foundational/55zi-update-settings-openai-llm.py +++ b/examples/foundational/55zi-update-settings-openai-llm.py @@ -58,16 +58,12 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): voice_id="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady ) - llm = OpenAILLMService(api_key=os.getenv("OPENAI_API_KEY")) + llm = OpenAILLMService( + api_key=os.getenv("OPENAI_API_KEY"), + system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + ) - messages = [ - { - "role": "system", - "content": "You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", - }, - ] - - context = LLMContext(messages) + context = LLMContext() user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()), @@ -97,7 +93,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): @transport.event_handler("on_client_connected") async def on_client_connected(transport, client): logger.info(f"Client connected") - messages.append({"role": "system", "content": "Please introduce yourself to the user."}) + context.add_message({"role": "system", "content": "Please introduce yourself to the user."}) await task.queue_frames([LLMRunFrame()]) await asyncio.sleep(10) diff --git a/examples/foundational/55zj-update-settings-anthropic-llm.py b/examples/foundational/55zj-update-settings-anthropic-llm.py index 354702880..59ac73da6 100644 --- a/examples/foundational/55zj-update-settings-anthropic-llm.py +++ b/examples/foundational/55zj-update-settings-anthropic-llm.py @@ -57,16 +57,12 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): voice_id="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady ) - llm = AnthropicLLMService(api_key=os.getenv("ANTHROPIC_API_KEY")) + llm = AnthropicLLMService( + api_key=os.getenv("ANTHROPIC_API_KEY"), + system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + ) - messages = [ - { - "role": "system", - "content": "You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", - }, - ] - - context = LLMContext(messages) + context = LLMContext() user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()), @@ -96,7 +92,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): @transport.event_handler("on_client_connected") async def on_client_connected(transport, client): logger.info(f"Client connected") - messages.append({"role": "system", "content": "Please introduce yourself to the user."}) + context.add_message({"role": "system", "content": "Please introduce yourself to the user."}) await task.queue_frames([LLMRunFrame()]) await asyncio.sleep(10) diff --git a/examples/foundational/55zk-update-settings-google-llm.py b/examples/foundational/55zk-update-settings-google-llm.py index cd03a34cb..4a0a3de0f 100644 --- a/examples/foundational/55zk-update-settings-google-llm.py +++ b/examples/foundational/55zk-update-settings-google-llm.py @@ -57,16 +57,12 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): voice_id="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady ) - llm = GoogleLLMService(api_key=os.getenv("GOOGLE_API_KEY")) + llm = GoogleLLMService( + api_key=os.getenv("GOOGLE_API_KEY"), + system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + ) - messages = [ - { - "role": "system", - "content": "You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", - }, - ] - - context = LLMContext(messages) + context = LLMContext() user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()), @@ -96,7 +92,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): @transport.event_handler("on_client_connected") async def on_client_connected(transport, client): logger.info(f"Client connected") - messages.append({"role": "system", "content": "Please introduce yourself to the user."}) + context.add_message({"role": "system", "content": "Please introduce yourself to the user."}) await task.queue_frames([LLMRunFrame()]) await asyncio.sleep(10) diff --git a/examples/foundational/55zk-update-settings-google-vertex-llm.py b/examples/foundational/55zk-update-settings-google-vertex-llm.py index 3feba582f..fe8ef808b 100644 --- a/examples/foundational/55zk-update-settings-google-vertex-llm.py +++ b/examples/foundational/55zk-update-settings-google-vertex-llm.py @@ -62,16 +62,10 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): credentials=os.getenv("GOOGLE_VERTEX_TEST_CREDENTIALS"), project_id=os.getenv("GOOGLE_CLOUD_PROJECT_ID"), location=os.getenv("GOOGLE_CLOUD_LOCATION"), + system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", ) - messages = [ - { - "role": "system", - "content": "You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", - }, - ] - - context = LLMContext(messages) + context = LLMContext() user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()), @@ -101,7 +95,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): @transport.event_handler("on_client_connected") async def on_client_connected(transport, client): logger.info(f"Client connected") - messages.append({"role": "system", "content": "Please introduce yourself to the user."}) + context.add_message({"role": "system", "content": "Please introduce yourself to the user."}) await task.queue_frames([LLMRunFrame()]) await asyncio.sleep(10) diff --git a/examples/foundational/55zp-update-settings-aws-bedrock-llm.py b/examples/foundational/55zp-update-settings-aws-bedrock-llm.py index 3d3ee8fb5..72b5ae9be 100644 --- a/examples/foundational/55zp-update-settings-aws-bedrock-llm.py +++ b/examples/foundational/55zp-update-settings-aws-bedrock-llm.py @@ -61,16 +61,10 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): aws_region="us-west-2", model="us.anthropic.claude-haiku-4-5-20251001-v1:0", params=AWSBedrockLLMService.InputParams(temperature=0.8), + system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", ) - messages = [ - { - "role": "system", - "content": "You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", - }, - ] - - context = LLMContext(messages) + context = LLMContext() user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()), @@ -100,7 +94,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): @transport.event_handler("on_client_connected") async def on_client_connected(transport, client): logger.info(f"Client connected") - messages.append({"role": "system", "content": "Please introduce yourself to the user."}) + context.add_message({"role": "system", "content": "Please introduce yourself to the user."}) await task.queue_frames([LLMRunFrame()]) await asyncio.sleep(10) diff --git a/examples/foundational/55zq-update-settings-fal-stt.py b/examples/foundational/55zq-update-settings-fal-stt.py index c0f0a134a..22ee38929 100644 --- a/examples/foundational/55zq-update-settings-fal-stt.py +++ b/examples/foundational/55zq-update-settings-fal-stt.py @@ -57,16 +57,12 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): voice_id="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady ) - llm = OpenAILLMService(api_key=os.getenv("OPENAI_API_KEY")) + llm = OpenAILLMService( + api_key=os.getenv("OPENAI_API_KEY"), + system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + ) - messages = [ - { - "role": "system", - "content": "You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", - }, - ] - - context = LLMContext(messages) + context = LLMContext() user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()), @@ -96,7 +92,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): @transport.event_handler("on_client_connected") async def on_client_connected(transport, client): logger.info(f"Client connected") - messages.append({"role": "system", "content": "Please introduce yourself to the user."}) + context.add_message({"role": "system", "content": "Please introduce yourself to the user."}) await task.queue_frames([LLMRunFrame()]) await asyncio.sleep(10) diff --git a/examples/foundational/55zr-update-settings-gradium-stt.py b/examples/foundational/55zr-update-settings-gradium-stt.py index 636d27bd8..65c70519d 100644 --- a/examples/foundational/55zr-update-settings-gradium-stt.py +++ b/examples/foundational/55zr-update-settings-gradium-stt.py @@ -60,16 +60,12 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): voice_id="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady ) - llm = OpenAILLMService(api_key=os.getenv("OPENAI_API_KEY")) + llm = OpenAILLMService( + api_key=os.getenv("OPENAI_API_KEY"), + system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + ) - messages = [ - { - "role": "system", - "content": "You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", - }, - ] - - context = LLMContext(messages) + context = LLMContext() user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()), @@ -99,7 +95,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): @transport.event_handler("on_client_connected") async def on_client_connected(transport, client): logger.info(f"Client connected") - messages.append({"role": "system", "content": "Please introduce yourself to the user."}) + context.add_message({"role": "system", "content": "Please introduce yourself to the user."}) await task.queue_frames([LLMRunFrame()]) await asyncio.sleep(10) diff --git a/examples/foundational/55zs-update-settings-hathora-stt.py b/examples/foundational/55zs-update-settings-hathora-stt.py index 7a033490a..818772b75 100644 --- a/examples/foundational/55zs-update-settings-hathora-stt.py +++ b/examples/foundational/55zs-update-settings-hathora-stt.py @@ -61,16 +61,12 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): voice_id="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady ) - llm = OpenAILLMService(api_key=os.getenv("OPENAI_API_KEY")) + llm = OpenAILLMService( + api_key=os.getenv("OPENAI_API_KEY"), + system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + ) - messages = [ - { - "role": "system", - "content": "You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", - }, - ] - - context = LLMContext(messages) + context = LLMContext() user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()), @@ -100,7 +96,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): @transport.event_handler("on_client_connected") async def on_client_connected(transport, client): logger.info(f"Client connected") - messages.append({"role": "system", "content": "Please introduce yourself to the user."}) + context.add_message({"role": "system", "content": "Please introduce yourself to the user."}) await task.queue_frames([LLMRunFrame()]) await asyncio.sleep(10) diff --git a/examples/foundational/55zt-update-settings-nvidia-segmented-stt.py b/examples/foundational/55zt-update-settings-nvidia-segmented-stt.py index 60a042c5f..122619aaa 100644 --- a/examples/foundational/55zt-update-settings-nvidia-segmented-stt.py +++ b/examples/foundational/55zt-update-settings-nvidia-segmented-stt.py @@ -57,16 +57,12 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): voice_id="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady ) - llm = OpenAILLMService(api_key=os.getenv("OPENAI_API_KEY")) + llm = OpenAILLMService( + api_key=os.getenv("OPENAI_API_KEY"), + system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + ) - messages = [ - { - "role": "system", - "content": "You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", - }, - ] - - context = LLMContext(messages) + context = LLMContext() user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()), @@ -96,7 +92,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): @transport.event_handler("on_client_connected") async def on_client_connected(transport, client): logger.info(f"Client connected") - messages.append({"role": "system", "content": "Please introduce yourself to the user."}) + context.add_message({"role": "system", "content": "Please introduce yourself to the user."}) await task.queue_frames([LLMRunFrame()]) await asyncio.sleep(10) diff --git a/examples/foundational/55zt-update-settings-nvidia-stt.py b/examples/foundational/55zt-update-settings-nvidia-stt.py index 415f10b12..232db9bf3 100644 --- a/examples/foundational/55zt-update-settings-nvidia-stt.py +++ b/examples/foundational/55zt-update-settings-nvidia-stt.py @@ -58,16 +58,12 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): voice_id="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady ) - llm = OpenAILLMService(api_key=os.getenv("OPENAI_API_KEY")) + llm = OpenAILLMService( + api_key=os.getenv("OPENAI_API_KEY"), + system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + ) - messages = [ - { - "role": "system", - "content": "You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", - }, - ] - - context = LLMContext(messages) + context = LLMContext() user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()), @@ -97,7 +93,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): @transport.event_handler("on_client_connected") async def on_client_connected(transport, client): logger.info(f"Client connected") - messages.append({"role": "system", "content": "Please introduce yourself to the user."}) + context.add_message({"role": "system", "content": "Please introduce yourself to the user."}) await task.queue_frames([LLMRunFrame()]) await asyncio.sleep(10) diff --git a/examples/foundational/55zu-update-settings-openai-realtime-stt.py b/examples/foundational/55zu-update-settings-openai-realtime-stt.py index 2bcd35f52..eb7be5c97 100644 --- a/examples/foundational/55zu-update-settings-openai-realtime-stt.py +++ b/examples/foundational/55zu-update-settings-openai-realtime-stt.py @@ -58,16 +58,12 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): voice_id="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady ) - llm = OpenAILLMService(api_key=os.getenv("OPENAI_API_KEY")) + llm = OpenAILLMService( + api_key=os.getenv("OPENAI_API_KEY"), + system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + ) - messages = [ - { - "role": "system", - "content": "You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", - }, - ] - - context = LLMContext(messages) + context = LLMContext() user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()), @@ -97,7 +93,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): @transport.event_handler("on_client_connected") async def on_client_connected(transport, client): logger.info(f"Client connected") - messages.append({"role": "system", "content": "Please introduce yourself to the user."}) + context.add_message({"role": "system", "content": "Please introduce yourself to the user."}) await task.queue_frames([LLMRunFrame()]) await asyncio.sleep(10) diff --git a/examples/foundational/55zv-update-settings-asyncai-http-tts.py b/examples/foundational/55zv-update-settings-asyncai-http-tts.py index 9688f1bac..79ca4382e 100644 --- a/examples/foundational/55zv-update-settings-asyncai-http-tts.py +++ b/examples/foundational/55zv-update-settings-asyncai-http-tts.py @@ -63,16 +63,12 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): aiohttp_session=session, ) - llm = OpenAILLMService(api_key=os.getenv("OPENAI_API_KEY")) + llm = OpenAILLMService( + api_key=os.getenv("OPENAI_API_KEY"), + system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + ) - messages = [ - { - "role": "system", - "content": "You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", - }, - ] - - context = LLMContext(messages) + context = LLMContext() user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()), @@ -102,7 +98,9 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): @transport.event_handler("on_client_connected") async def on_client_connected(transport, client): logger.info(f"Client connected") - messages.append({"role": "system", "content": "Please introduce yourself to the user."}) + context.add_message( + {"role": "system", "content": "Please introduce yourself to the user."} + ) await task.queue_frames([LLMRunFrame()]) await asyncio.sleep(10) diff --git a/examples/foundational/55zv-update-settings-asyncai-tts.py b/examples/foundational/55zv-update-settings-asyncai-tts.py index fe096b4be..7e5463d2b 100644 --- a/examples/foundational/55zv-update-settings-asyncai-tts.py +++ b/examples/foundational/55zv-update-settings-asyncai-tts.py @@ -58,16 +58,12 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): voice_id=os.getenv("ASYNCAI_VOICE_ID", "e0f39dc4-f691-4e78-bba5-5c636692cc04"), ) - llm = OpenAILLMService(api_key=os.getenv("OPENAI_API_KEY")) + llm = OpenAILLMService( + api_key=os.getenv("OPENAI_API_KEY"), + system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + ) - messages = [ - { - "role": "system", - "content": "You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", - }, - ] - - context = LLMContext(messages) + context = LLMContext() user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()), @@ -97,7 +93,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): @transport.event_handler("on_client_connected") async def on_client_connected(transport, client): logger.info(f"Client connected") - messages.append({"role": "system", "content": "Please introduce yourself to the user."}) + context.add_message({"role": "system", "content": "Please introduce yourself to the user."}) await task.queue_frames([LLMRunFrame()]) await asyncio.sleep(10) diff --git a/examples/foundational/55zw-update-settings-gradium-tts.py b/examples/foundational/55zw-update-settings-gradium-tts.py index d1069bfa4..e12d20dd2 100644 --- a/examples/foundational/55zw-update-settings-gradium-tts.py +++ b/examples/foundational/55zw-update-settings-gradium-tts.py @@ -58,16 +58,12 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): url="wss://us.api.gradium.ai/api/speech/tts", ) - llm = OpenAILLMService(api_key=os.getenv("OPENAI_API_KEY")) + llm = OpenAILLMService( + api_key=os.getenv("OPENAI_API_KEY"), + system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + ) - messages = [ - { - "role": "system", - "content": "You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", - }, - ] - - context = LLMContext(messages) + context = LLMContext() user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()), @@ -97,7 +93,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): @transport.event_handler("on_client_connected") async def on_client_connected(transport, client): logger.info(f"Client connected") - messages.append({"role": "system", "content": "Please introduce yourself to the user."}) + context.add_message({"role": "system", "content": "Please introduce yourself to the user."}) await task.queue_frames([LLMRunFrame()]) await asyncio.sleep(10) diff --git a/examples/foundational/55zx-update-settings-cerebras-llm.py b/examples/foundational/55zx-update-settings-cerebras-llm.py index 6123487a3..3937345e1 100644 --- a/examples/foundational/55zx-update-settings-cerebras-llm.py +++ b/examples/foundational/55zx-update-settings-cerebras-llm.py @@ -58,16 +58,12 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): voice_id="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady ) - llm = CerebrasLLMService(api_key=os.getenv("CEREBRAS_API_KEY")) + llm = CerebrasLLMService( + api_key=os.getenv("CEREBRAS_API_KEY"), + system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + ) - messages = [ - { - "role": "system", - "content": "You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", - }, - ] - - context = LLMContext(messages) + context = LLMContext() user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()), @@ -97,7 +93,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): @transport.event_handler("on_client_connected") async def on_client_connected(transport, client): logger.info(f"Client connected") - messages.append({"role": "system", "content": "Please introduce yourself to the user."}) + context.add_message({"role": "system", "content": "Please introduce yourself to the user."}) await task.queue_frames([LLMRunFrame()]) await asyncio.sleep(10) diff --git a/examples/foundational/55zy-update-settings-deepseek-llm.py b/examples/foundational/55zy-update-settings-deepseek-llm.py index 60cbab30b..c96107c40 100644 --- a/examples/foundational/55zy-update-settings-deepseek-llm.py +++ b/examples/foundational/55zy-update-settings-deepseek-llm.py @@ -58,16 +58,12 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): voice_id="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady ) - llm = DeepSeekLLMService(api_key=os.getenv("DEEPSEEK_API_KEY")) + llm = DeepSeekLLMService( + api_key=os.getenv("DEEPSEEK_API_KEY"), + system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + ) - messages = [ - { - "role": "system", - "content": "You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", - }, - ] - - context = LLMContext(messages) + context = LLMContext() user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()), @@ -97,7 +93,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): @transport.event_handler("on_client_connected") async def on_client_connected(transport, client): logger.info(f"Client connected") - messages.append({"role": "system", "content": "Please introduce yourself to the user."}) + context.add_message({"role": "system", "content": "Please introduce yourself to the user."}) await task.queue_frames([LLMRunFrame()]) await asyncio.sleep(10) diff --git a/examples/foundational/55zz-update-settings-fireworks-llm.py b/examples/foundational/55zz-update-settings-fireworks-llm.py index 97554ae19..8c4388251 100644 --- a/examples/foundational/55zz-update-settings-fireworks-llm.py +++ b/examples/foundational/55zz-update-settings-fireworks-llm.py @@ -61,16 +61,10 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): llm = FireworksLLMService( api_key=os.getenv("FIREWORKS_API_KEY"), model="accounts/fireworks/models/gpt-oss-20b", + system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", ) - messages = [ - { - "role": "system", - "content": "You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", - }, - ] - - context = LLMContext(messages) + context = LLMContext() user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()), @@ -100,7 +94,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): @transport.event_handler("on_client_connected") async def on_client_connected(transport, client): logger.info(f"Client connected") - messages.append({"role": "system", "content": "Please introduce yourself to the user."}) + context.add_message({"role": "system", "content": "Please introduce yourself to the user."}) await task.queue_frames([LLMRunFrame()]) await asyncio.sleep(10) diff --git a/examples/foundational/55zza-update-settings-grok-llm.py b/examples/foundational/55zza-update-settings-grok-llm.py index 8ce081e66..e75c70b5f 100644 --- a/examples/foundational/55zza-update-settings-grok-llm.py +++ b/examples/foundational/55zza-update-settings-grok-llm.py @@ -58,16 +58,12 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): voice_id="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady ) - llm = GrokLLMService(api_key=os.getenv("GROK_API_KEY")) + llm = GrokLLMService( + api_key=os.getenv("GROK_API_KEY"), + system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + ) - messages = [ - { - "role": "system", - "content": "You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", - }, - ] - - context = LLMContext(messages) + context = LLMContext() user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()), @@ -97,7 +93,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): @transport.event_handler("on_client_connected") async def on_client_connected(transport, client): logger.info(f"Client connected") - messages.append({"role": "system", "content": "Please introduce yourself to the user."}) + context.add_message({"role": "system", "content": "Please introduce yourself to the user."}) await task.queue_frames([LLMRunFrame()]) await asyncio.sleep(10) diff --git a/examples/foundational/55zzb-update-settings-groq-llm.py b/examples/foundational/55zzb-update-settings-groq-llm.py index afde4499d..2f7f82bb2 100644 --- a/examples/foundational/55zzb-update-settings-groq-llm.py +++ b/examples/foundational/55zzb-update-settings-groq-llm.py @@ -59,17 +59,12 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): ) llm = GroqLLMService( - api_key=os.getenv("GROQ_API_KEY"), model="meta-llama/llama-4-maverick-17b-128e-instruct" + api_key=os.getenv("GROQ_API_KEY"), + model="meta-llama/llama-4-maverick-17b-128e-instruct", + system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", ) - messages = [ - { - "role": "system", - "content": "You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", - }, - ] - - context = LLMContext(messages) + context = LLMContext() user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()), @@ -99,7 +94,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): @transport.event_handler("on_client_connected") async def on_client_connected(transport, client): logger.info(f"Client connected") - messages.append({"role": "system", "content": "Please introduce yourself to the user."}) + context.add_message({"role": "system", "content": "Please introduce yourself to the user."}) await task.queue_frames([LLMRunFrame()]) await asyncio.sleep(10) diff --git a/examples/foundational/55zzc-update-settings-mistral-llm.py b/examples/foundational/55zzc-update-settings-mistral-llm.py index 7eba98e97..ab3bd4f76 100644 --- a/examples/foundational/55zzc-update-settings-mistral-llm.py +++ b/examples/foundational/55zzc-update-settings-mistral-llm.py @@ -58,16 +58,12 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): voice_id="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady ) - llm = MistralLLMService(api_key=os.getenv("MISTRAL_API_KEY")) + llm = MistralLLMService( + api_key=os.getenv("MISTRAL_API_KEY"), + system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + ) - messages = [ - { - "role": "system", - "content": "You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", - }, - ] - - context = LLMContext(messages) + context = LLMContext() user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()), @@ -97,7 +93,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): @transport.event_handler("on_client_connected") async def on_client_connected(transport, client): logger.info(f"Client connected") - messages.append({"role": "system", "content": "Please introduce yourself to the user."}) + context.add_message({"role": "system", "content": "Please introduce yourself to the user."}) await task.queue_frames([LLMRunFrame()]) await asyncio.sleep(10) diff --git a/examples/foundational/55zzd-update-settings-nvidia-llm.py b/examples/foundational/55zzd-update-settings-nvidia-llm.py index ee57a3a24..a8699c71b 100644 --- a/examples/foundational/55zzd-update-settings-nvidia-llm.py +++ b/examples/foundational/55zzd-update-settings-nvidia-llm.py @@ -59,17 +59,12 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): ) llm = NvidiaLLMService( - api_key=os.getenv("NVIDIA_API_KEY"), model="meta/llama-3.1-405b-instruct" + api_key=os.getenv("NVIDIA_API_KEY"), + model="meta/llama-3.1-405b-instruct", + system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", ) - messages = [ - { - "role": "system", - "content": "You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", - }, - ] - - context = LLMContext(messages) + context = LLMContext() user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()), @@ -99,7 +94,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): @transport.event_handler("on_client_connected") async def on_client_connected(transport, client): logger.info(f"Client connected") - messages.append({"role": "system", "content": "Please introduce yourself to the user."}) + context.add_message({"role": "system", "content": "Please introduce yourself to the user."}) await task.queue_frames([LLMRunFrame()]) await asyncio.sleep(10) diff --git a/examples/foundational/55zze-update-settings-ollama-llm.py b/examples/foundational/55zze-update-settings-ollama-llm.py index e22719ec1..4595604fd 100644 --- a/examples/foundational/55zze-update-settings-ollama-llm.py +++ b/examples/foundational/55zze-update-settings-ollama-llm.py @@ -58,16 +58,12 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): voice_id="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady ) - llm = OLLamaLLMService(model="llama3.2") # Update to the model you're running locally + llm = OLLamaLLMService( + model="llama3.2", + system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + ) # Update to the model you're running locally - messages = [ - { - "role": "system", - "content": "You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", - }, - ] - - context = LLMContext(messages) + context = LLMContext() user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()), @@ -97,7 +93,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): @transport.event_handler("on_client_connected") async def on_client_connected(transport, client): logger.info(f"Client connected") - messages.append({"role": "system", "content": "Please introduce yourself to the user."}) + context.add_message({"role": "system", "content": "Please introduce yourself to the user."}) await task.queue_frames([LLMRunFrame()]) await asyncio.sleep(10) diff --git a/examples/foundational/55zzf-update-settings-openrouter-llm.py b/examples/foundational/55zzf-update-settings-openrouter-llm.py index fc3732192..9a381d88b 100644 --- a/examples/foundational/55zzf-update-settings-openrouter-llm.py +++ b/examples/foundational/55zzf-update-settings-openrouter-llm.py @@ -58,16 +58,12 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): voice_id="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady ) - llm = OpenRouterLLMService(api_key=os.getenv("OPENROUTER_API_KEY")) + llm = OpenRouterLLMService( + api_key=os.getenv("OPENROUTER_API_KEY"), + system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + ) - messages = [ - { - "role": "system", - "content": "You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", - }, - ] - - context = LLMContext(messages) + context = LLMContext() user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()), @@ -97,7 +93,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): @transport.event_handler("on_client_connected") async def on_client_connected(transport, client): logger.info(f"Client connected") - messages.append({"role": "system", "content": "Please introduce yourself to the user."}) + context.add_message({"role": "system", "content": "Please introduce yourself to the user."}) await task.queue_frames([LLMRunFrame()]) await asyncio.sleep(10) diff --git a/examples/foundational/55zzh-update-settings-qwen-llm.py b/examples/foundational/55zzh-update-settings-qwen-llm.py index f31dc05a5..019e916cb 100644 --- a/examples/foundational/55zzh-update-settings-qwen-llm.py +++ b/examples/foundational/55zzh-update-settings-qwen-llm.py @@ -58,16 +58,13 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): voice_id="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady ) - llm = QwenLLMService(api_key=os.getenv("QWEN_API_KEY"), model="qwen2.5-72b-instruct") + llm = QwenLLMService( + api_key=os.getenv("QWEN_API_KEY"), + model="qwen2.5-72b-instruct", + system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + ) - messages = [ - { - "role": "system", - "content": "You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", - }, - ] - - context = LLMContext(messages) + context = LLMContext() user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()), @@ -97,7 +94,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): @transport.event_handler("on_client_connected") async def on_client_connected(transport, client): logger.info(f"Client connected") - messages.append({"role": "system", "content": "Please introduce yourself to the user."}) + context.add_message({"role": "system", "content": "Please introduce yourself to the user."}) await task.queue_frames([LLMRunFrame()]) await asyncio.sleep(10) diff --git a/examples/foundational/55zzi-update-settings-sambanova-llm.py b/examples/foundational/55zzi-update-settings-sambanova-llm.py index 96122cc03..040e95da1 100644 --- a/examples/foundational/55zzi-update-settings-sambanova-llm.py +++ b/examples/foundational/55zzi-update-settings-sambanova-llm.py @@ -58,16 +58,12 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): voice_id="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady ) - llm = SambaNovaLLMService(api_key=os.getenv("SAMBANOVA_API_KEY")) + llm = SambaNovaLLMService( + api_key=os.getenv("SAMBANOVA_API_KEY"), + system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + ) - messages = [ - { - "role": "system", - "content": "You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", - }, - ] - - context = LLMContext(messages) + context = LLMContext() user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()), @@ -97,7 +93,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): @transport.event_handler("on_client_connected") async def on_client_connected(transport, client): logger.info(f"Client connected") - messages.append({"role": "system", "content": "Please introduce yourself to the user."}) + context.add_message({"role": "system", "content": "Please introduce yourself to the user."}) await task.queue_frames([LLMRunFrame()]) await asyncio.sleep(10) diff --git a/examples/foundational/55zzj-update-settings-together-llm.py b/examples/foundational/55zzj-update-settings-together-llm.py index 710ef894a..b1c8c049d 100644 --- a/examples/foundational/55zzj-update-settings-together-llm.py +++ b/examples/foundational/55zzj-update-settings-together-llm.py @@ -61,16 +61,10 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): llm = TogetherLLMService( api_key=os.getenv("TOGETHER_API_KEY"), model="meta-llama/Meta-Llama-3.1-70B-Instruct-Turbo", + system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", ) - messages = [ - { - "role": "system", - "content": "You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", - }, - ] - - context = LLMContext(messages) + context = LLMContext() user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()), @@ -100,7 +94,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): @transport.event_handler("on_client_connected") async def on_client_connected(transport, client): logger.info(f"Client connected") - messages.append({"role": "system", "content": "Please introduce yourself to the user."}) + context.add_message({"role": "system", "content": "Please introduce yourself to the user."}) await task.queue_frames([LLMRunFrame()]) await asyncio.sleep(10) diff --git a/examples/foundational/55zzl-update-settings-nvidia-tts.py b/examples/foundational/55zzl-update-settings-nvidia-tts.py index a8bd50dcd..5bc89bd58 100644 --- a/examples/foundational/55zzl-update-settings-nvidia-tts.py +++ b/examples/foundational/55zzl-update-settings-nvidia-tts.py @@ -55,16 +55,12 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): tts = NvidiaTTSService(api_key=os.getenv("NVIDIA_API_KEY")) - llm = OpenAILLMService(api_key=os.getenv("OPENAI_API_KEY")) + llm = OpenAILLMService( + api_key=os.getenv("OPENAI_API_KEY"), + system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + ) - messages = [ - { - "role": "system", - "content": "You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", - }, - ] - - context = LLMContext(messages) + context = LLMContext() user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()), @@ -94,7 +90,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): @transport.event_handler("on_client_connected") async def on_client_connected(transport, client): logger.info(f"Client connected") - messages.append({"role": "system", "content": "Please introduce yourself to the user."}) + context.add_message({"role": "system", "content": "Please introduce yourself to the user."}) await task.queue_frames([LLMRunFrame()]) await asyncio.sleep(10) diff --git a/examples/foundational/55zzm-update-settings-speechmatics-tts.py b/examples/foundational/55zzm-update-settings-speechmatics-tts.py index 39ed792dd..d9eaaec86 100644 --- a/examples/foundational/55zzm-update-settings-speechmatics-tts.py +++ b/examples/foundational/55zzm-update-settings-speechmatics-tts.py @@ -59,16 +59,12 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): aiohttp_session=session, ) - llm = OpenAILLMService(api_key=os.getenv("OPENAI_API_KEY")) + llm = OpenAILLMService( + api_key=os.getenv("OPENAI_API_KEY"), + system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + ) - messages = [ - { - "role": "system", - "content": "You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", - }, - ] - - context = LLMContext(messages) + context = LLMContext() user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()), @@ -98,7 +94,9 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): @transport.event_handler("on_client_connected") async def on_client_connected(transport, client): logger.info(f"Client connected") - messages.append({"role": "system", "content": "Please introduce yourself to the user."}) + context.add_message( + {"role": "system", "content": "Please introduce yourself to the user."} + ) await task.queue_frames([LLMRunFrame()]) await asyncio.sleep(10) diff --git a/examples/foundational/55zzn-update-settings-groq-stt.py b/examples/foundational/55zzn-update-settings-groq-stt.py index b00ecda81..1d488119c 100644 --- a/examples/foundational/55zzn-update-settings-groq-stt.py +++ b/examples/foundational/55zzn-update-settings-groq-stt.py @@ -60,16 +60,12 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): voice_id="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady ) - llm = OpenAILLMService(api_key=os.getenv("OPENAI_API_KEY")) + llm = OpenAILLMService( + api_key=os.getenv("OPENAI_API_KEY"), + system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + ) - messages = [ - { - "role": "system", - "content": "You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", - }, - ] - - context = LLMContext(messages) + context = LLMContext() user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()), @@ -99,7 +95,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): @transport.event_handler("on_client_connected") async def on_client_connected(transport, client): logger.info(f"Client connected") - messages.append({"role": "system", "content": "Please introduce yourself to the user."}) + context.add_message({"role": "system", "content": "Please introduce yourself to the user."}) await task.queue_frames([LLMRunFrame()]) await asyncio.sleep(10) diff --git a/examples/foundational/56-lemonslice-transport.py b/examples/foundational/56-lemonslice-transport.py index 8b2e19a6e..a3b6b60d3 100644 --- a/examples/foundational/56-lemonslice-transport.py +++ b/examples/foundational/56-lemonslice-transport.py @@ -55,21 +55,17 @@ async def main(): stt = DeepgramSTTService(api_key=os.getenv("DEEPGRAM_API_KEY")) - llm = GroqLLMService(api_key=os.getenv("GROQ_API_KEY")) + llm = GroqLLMService( + api_key=os.getenv("GROQ_API_KEY"), + system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + ) tts = ElevenLabsTTSService( api_key=os.getenv("ELEVENLABS_API_KEY", ""), voice_id=os.getenv("ELEVENLABS_VOICE_ID", ""), ) - messages = [ - { - "role": "system", - "content": "You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", - }, - ] - - context = LLMContext(messages) + context = LLMContext() user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()), @@ -101,7 +97,7 @@ async def main(): async def on_client_connected(transport, participant): logger.info("Client connected") # Kick off the conversation. - messages.append( + context.add_message( { "role": "system", "content": "Start by greeting the user and ask how you can help.", From 3c60b0c8af79fc5e54d8a1576cc1218ad9551eb8 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Aleix=20Conchillo=20Flaqu=C3=A9?= Date: Wed, 4 Mar 2026 13:25:47 -0800 Subject: [PATCH 0788/1060] Add changelog for #3918 --- changelog/3918.added.md | 15 +++++++++++++++ changelog/3918.other.md | 1 + 2 files changed, 16 insertions(+) create mode 100644 changelog/3918.added.md create mode 100644 changelog/3918.other.md diff --git a/changelog/3918.added.md b/changelog/3918.added.md new file mode 100644 index 000000000..6b4d4446f --- /dev/null +++ b/changelog/3918.added.md @@ -0,0 +1,15 @@ +- Wired up `system_instruction` in `BaseOpenAILLMService`, `AnthropicLLMService`, and `AWSBedrockLLMService` so it works as a default system prompt, matching the behavior of the Google services. This enables sharing a single `LLMContext` across multiple LLM services, where each service provides its own system instruction independently. + + ```python + llm = OpenAILLMService( + api_key=os.getenv("OPENAI_API_KEY"), + system_instruction="You are a helpful assistant.", + ) + + context = LLMContext() + + @transport.event_handler("on_client_connected") + async def on_client_connected(transport, client): + context.add_message({"role": "user", "content": "Please introduce yourself."}) + await task.queue_frames([LLMRunFrame()]) + ``` diff --git a/changelog/3918.other.md b/changelog/3918.other.md new file mode 100644 index 000000000..6caa1ba05 --- /dev/null +++ b/changelog/3918.other.md @@ -0,0 +1 @@ +- Updated foundational examples to use `system_instruction` on LLM services instead of adding system messages to `LLMContext`. 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Remove the STT/TTS services, examples, and related references. --- README.md | 26 +-- env.example | 3 - .../07zh-interruptible-hathora.py | 123 ----------- .../55zg-update-settings-hathora-tts.py | 121 ----------- .../55zs-update-settings-hathora-stt.py | 127 ------------ scripts/evals/run-release-evals.py | 1 - src/pipecat/services/hathora/__init__.py | 0 src/pipecat/services/hathora/stt.py | 176 ---------------- src/pipecat/services/hathora/tts.py | 191 ------------------ src/pipecat/services/hathora/utils.py | 22 -- src/pipecat/services/stt_latency.py | 1 - 11 files changed, 13 insertions(+), 778 deletions(-) delete mode 100644 examples/foundational/07zh-interruptible-hathora.py delete mode 100644 examples/foundational/55zg-update-settings-hathora-tts.py delete mode 100644 examples/foundational/55zs-update-settings-hathora-stt.py delete mode 100644 src/pipecat/services/hathora/__init__.py delete mode 100644 src/pipecat/services/hathora/stt.py delete mode 100644 src/pipecat/services/hathora/tts.py delete mode 100644 src/pipecat/services/hathora/utils.py diff --git a/README.md b/README.md index 881b0ed5e..8af4f942c 100644 --- a/README.md +++ b/README.md @@ -81,19 +81,19 @@ Catch new features, interviews, and how-tos on our [Pipecat TV](https://www.yout ## 🧩 Available services -| Category | Services | -| ------------------- | -------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | -| Speech-to-Text | [AssemblyAI](https://docs.pipecat.ai/server/services/stt/assemblyai), [AWS](https://docs.pipecat.ai/server/services/stt/aws), [Azure](https://docs.pipecat.ai/server/services/stt/azure), [Cartesia](https://docs.pipecat.ai/server/services/stt/cartesia), [Deepgram](https://docs.pipecat.ai/server/services/stt/deepgram), [ElevenLabs](https://docs.pipecat.ai/server/services/stt/elevenlabs), [Fal Wizper](https://docs.pipecat.ai/server/services/stt/fal), [Gladia](https://docs.pipecat.ai/server/services/stt/gladia), [Google](https://docs.pipecat.ai/server/services/stt/google), [Gradium](https://docs.pipecat.ai/server/services/stt/gradium), [Groq (Whisper)](https://docs.pipecat.ai/server/services/stt/groq), [Hathora](https://docs.pipecat.ai/server/services/stt/hathora), [NVIDIA Riva](https://docs.pipecat.ai/server/services/stt/riva), [OpenAI (Whisper)](https://docs.pipecat.ai/server/services/stt/openai), [SambaNova (Whisper)](https://docs.pipecat.ai/server/services/stt/sambanova), [Sarvam](https://docs.pipecat.ai/server/services/stt/sarvam), [Soniox](https://docs.pipecat.ai/server/services/stt/soniox), [Speechmatics](https://docs.pipecat.ai/server/services/stt/speechmatics), [Whisper](https://docs.pipecat.ai/server/services/stt/whisper) | -| LLMs | [Anthropic](https://docs.pipecat.ai/server/services/llm/anthropic), [AWS](https://docs.pipecat.ai/server/services/llm/aws), [Azure](https://docs.pipecat.ai/server/services/llm/azure), [Cerebras](https://docs.pipecat.ai/server/services/llm/cerebras), [DeepSeek](https://docs.pipecat.ai/server/services/llm/deepseek), [Fireworks AI](https://docs.pipecat.ai/server/services/llm/fireworks), [Gemini](https://docs.pipecat.ai/server/services/llm/gemini), [Grok](https://docs.pipecat.ai/server/services/llm/grok), [Groq](https://docs.pipecat.ai/server/services/llm/groq), [Mistral](https://docs.pipecat.ai/server/services/llm/mistral), [NVIDIA NIM](https://docs.pipecat.ai/server/services/llm/nim), [Ollama](https://docs.pipecat.ai/server/services/llm/ollama), [OpenAI](https://docs.pipecat.ai/server/services/llm/openai), [OpenRouter](https://docs.pipecat.ai/server/services/llm/openrouter), [Perplexity](https://docs.pipecat.ai/server/services/llm/perplexity), [Qwen](https://docs.pipecat.ai/server/services/llm/qwen), [SambaNova](https://docs.pipecat.ai/server/services/llm/sambanova) [Together AI](https://docs.pipecat.ai/server/services/llm/together) | -| Text-to-Speech | [Async](https://docs.pipecat.ai/server/services/tts/asyncai), [AWS](https://docs.pipecat.ai/server/services/tts/aws), [Azure](https://docs.pipecat.ai/server/services/tts/azure), [Camb AI](https://docs.pipecat.ai/server/services/tts/camb), [Cartesia](https://docs.pipecat.ai/server/services/tts/cartesia), [Deepgram](https://docs.pipecat.ai/server/services/tts/deepgram), [ElevenLabs](https://docs.pipecat.ai/server/services/tts/elevenlabs), [Fish](https://docs.pipecat.ai/server/services/tts/fish), [Google](https://docs.pipecat.ai/server/services/tts/google), [Gradium](https://docs.pipecat.ai/server/services/tts/gradium), [Groq](https://docs.pipecat.ai/server/services/tts/groq), [Hathora](https://docs.pipecat.ai/server/services/tts/hathora), [Hume](https://docs.pipecat.ai/server/services/tts/hume), [Inworld](https://docs.pipecat.ai/server/services/tts/inworld), [LMNT](https://docs.pipecat.ai/server/services/tts/lmnt), [MiniMax](https://docs.pipecat.ai/server/services/tts/minimax), [Neuphonic](https://docs.pipecat.ai/server/services/tts/neuphonic), [NVIDIA Riva](https://docs.pipecat.ai/server/services/tts/riva), [OpenAI](https://docs.pipecat.ai/server/services/tts/openai), [Piper](https://docs.pipecat.ai/server/services/tts/piper), [Resemble](https://docs.pipecat.ai/server/services/tts/resemble), [Rime](https://docs.pipecat.ai/server/services/tts/rime), [Sarvam](https://docs.pipecat.ai/server/services/tts/sarvam), [Speechmatics](https://docs.pipecat.ai/server/services/tts/speechmatics), [XTTS](https://docs.pipecat.ai/server/services/tts/xtts) | -| Speech-to-Speech | [AWS Nova Sonic](https://docs.pipecat.ai/server/services/s2s/aws), [Gemini Multimodal Live](https://docs.pipecat.ai/server/services/s2s/gemini), [Grok Voice Agent](https://docs.pipecat.ai/server/services/s2s/grok), [OpenAI Realtime](https://docs.pipecat.ai/server/services/s2s/openai), [Ultravox](https://docs.pipecat.ai/server/services/s2s/ultravox), | -| Transport | [Daily (WebRTC)](https://docs.pipecat.ai/server/services/transport/daily), [FastAPI Websocket](https://docs.pipecat.ai/server/services/transport/fastapi-websocket), [SmallWebRTCTransport](https://docs.pipecat.ai/server/services/transport/small-webrtc), [WebSocket Server](https://docs.pipecat.ai/server/services/transport/websocket-server), Local | -| Serializers | [Exotel](https://docs.pipecat.ai/server/utilities/serializers/exotel), [Plivo](https://docs.pipecat.ai/server/utilities/serializers/plivo), [Twilio](https://docs.pipecat.ai/server/utilities/serializers/twilio), [Telnyx](https://docs.pipecat.ai/server/utilities/serializers/telnyx), [Vonage](https://docs.pipecat.ai/server/utilities/serializers/vonage) | -| Video | [HeyGen](https://docs.pipecat.ai/server/services/video/heygen), [LemonSlice](https://docs.pipecat.ai/server/services/video/lemonslice), [Tavus](https://docs.pipecat.ai/server/services/video/tavus), [Simli](https://docs.pipecat.ai/server/services/video/simli) | -| Memory | [mem0](https://docs.pipecat.ai/server/services/memory/mem0) | -| Vision & Image | [fal](https://docs.pipecat.ai/server/services/image-generation/fal), [Google Imagen](https://docs.pipecat.ai/server/services/image-generation/google-imagen), [Moondream](https://docs.pipecat.ai/server/services/vision/moondream) | -| Audio Processing | [Silero VAD](https://docs.pipecat.ai/server/utilities/audio/silero-vad-analyzer), [Krisp](https://docs.pipecat.ai/server/utilities/audio/krisp-filter), [Koala](https://docs.pipecat.ai/server/utilities/audio/koala-filter), [ai-coustics](https://docs.pipecat.ai/server/utilities/audio/aic-filter) | -| Analytics & Metrics | [OpenTelemetry](https://docs.pipecat.ai/server/utilities/opentelemetry), [Sentry](https://docs.pipecat.ai/server/services/analytics/sentry) | +| Category | Services | +| ------------------- | ---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | +| Speech-to-Text | [AssemblyAI](https://docs.pipecat.ai/server/services/stt/assemblyai), [AWS](https://docs.pipecat.ai/server/services/stt/aws), [Azure](https://docs.pipecat.ai/server/services/stt/azure), [Cartesia](https://docs.pipecat.ai/server/services/stt/cartesia), [Deepgram](https://docs.pipecat.ai/server/services/stt/deepgram), [ElevenLabs](https://docs.pipecat.ai/server/services/stt/elevenlabs), [Fal Wizper](https://docs.pipecat.ai/server/services/stt/fal), [Gladia](https://docs.pipecat.ai/server/services/stt/gladia), [Google](https://docs.pipecat.ai/server/services/stt/google), [Gradium](https://docs.pipecat.ai/server/services/stt/gradium), [Groq (Whisper)](https://docs.pipecat.ai/server/services/stt/groq), [NVIDIA Riva](https://docs.pipecat.ai/server/services/stt/riva), [OpenAI (Whisper)](https://docs.pipecat.ai/server/services/stt/openai), [SambaNova (Whisper)](https://docs.pipecat.ai/server/services/stt/sambanova), [Sarvam](https://docs.pipecat.ai/server/services/stt/sarvam), [Soniox](https://docs.pipecat.ai/server/services/stt/soniox), [Speechmatics](https://docs.pipecat.ai/server/services/stt/speechmatics), [Whisper](https://docs.pipecat.ai/server/services/stt/whisper) | +| LLMs | [Anthropic](https://docs.pipecat.ai/server/services/llm/anthropic), [AWS](https://docs.pipecat.ai/server/services/llm/aws), [Azure](https://docs.pipecat.ai/server/services/llm/azure), [Cerebras](https://docs.pipecat.ai/server/services/llm/cerebras), [DeepSeek](https://docs.pipecat.ai/server/services/llm/deepseek), [Fireworks AI](https://docs.pipecat.ai/server/services/llm/fireworks), [Gemini](https://docs.pipecat.ai/server/services/llm/gemini), [Grok](https://docs.pipecat.ai/server/services/llm/grok), [Groq](https://docs.pipecat.ai/server/services/llm/groq), [Mistral](https://docs.pipecat.ai/server/services/llm/mistral), [NVIDIA NIM](https://docs.pipecat.ai/server/services/llm/nim), [Ollama](https://docs.pipecat.ai/server/services/llm/ollama), [OpenAI](https://docs.pipecat.ai/server/services/llm/openai), [OpenRouter](https://docs.pipecat.ai/server/services/llm/openrouter), [Perplexity](https://docs.pipecat.ai/server/services/llm/perplexity), [Qwen](https://docs.pipecat.ai/server/services/llm/qwen), [SambaNova](https://docs.pipecat.ai/server/services/llm/sambanova) [Together AI](https://docs.pipecat.ai/server/services/llm/together) | +| Text-to-Speech | [Async](https://docs.pipecat.ai/server/services/tts/asyncai), [AWS](https://docs.pipecat.ai/server/services/tts/aws), [Azure](https://docs.pipecat.ai/server/services/tts/azure), [Camb AI](https://docs.pipecat.ai/server/services/tts/camb), [Cartesia](https://docs.pipecat.ai/server/services/tts/cartesia), [Deepgram](https://docs.pipecat.ai/server/services/tts/deepgram), [ElevenLabs](https://docs.pipecat.ai/server/services/tts/elevenlabs), [Fish](https://docs.pipecat.ai/server/services/tts/fish), [Google](https://docs.pipecat.ai/server/services/tts/google), [Gradium](https://docs.pipecat.ai/server/services/tts/gradium), [Groq](https://docs.pipecat.ai/server/services/tts/groq), [Hume](https://docs.pipecat.ai/server/services/tts/hume), [Inworld](https://docs.pipecat.ai/server/services/tts/inworld), [LMNT](https://docs.pipecat.ai/server/services/tts/lmnt), [MiniMax](https://docs.pipecat.ai/server/services/tts/minimax), [Neuphonic](https://docs.pipecat.ai/server/services/tts/neuphonic), [NVIDIA Riva](https://docs.pipecat.ai/server/services/tts/riva), [OpenAI](https://docs.pipecat.ai/server/services/tts/openai), [Piper](https://docs.pipecat.ai/server/services/tts/piper), [Resemble](https://docs.pipecat.ai/server/services/tts/resemble), [Rime](https://docs.pipecat.ai/server/services/tts/rime), [Sarvam](https://docs.pipecat.ai/server/services/tts/sarvam), [Speechmatics](https://docs.pipecat.ai/server/services/tts/speechmatics), [XTTS](https://docs.pipecat.ai/server/services/tts/xtts) | +| Speech-to-Speech | [AWS Nova Sonic](https://docs.pipecat.ai/server/services/s2s/aws), [Gemini Multimodal Live](https://docs.pipecat.ai/server/services/s2s/gemini), [Grok Voice Agent](https://docs.pipecat.ai/server/services/s2s/grok), [OpenAI Realtime](https://docs.pipecat.ai/server/services/s2s/openai), [Ultravox](https://docs.pipecat.ai/server/services/s2s/ultravox), | +| Transport | [Daily (WebRTC)](https://docs.pipecat.ai/server/services/transport/daily), [FastAPI Websocket](https://docs.pipecat.ai/server/services/transport/fastapi-websocket), [SmallWebRTCTransport](https://docs.pipecat.ai/server/services/transport/small-webrtc), [WebSocket Server](https://docs.pipecat.ai/server/services/transport/websocket-server), Local | +| Serializers | [Exotel](https://docs.pipecat.ai/server/utilities/serializers/exotel), [Plivo](https://docs.pipecat.ai/server/utilities/serializers/plivo), [Twilio](https://docs.pipecat.ai/server/utilities/serializers/twilio), [Telnyx](https://docs.pipecat.ai/server/utilities/serializers/telnyx), [Vonage](https://docs.pipecat.ai/server/utilities/serializers/vonage) | +| Video | [HeyGen](https://docs.pipecat.ai/server/services/video/heygen), [LemonSlice](https://docs.pipecat.ai/server/services/video/lemonslice), [Tavus](https://docs.pipecat.ai/server/services/video/tavus), [Simli](https://docs.pipecat.ai/server/services/video/simli) | +| Memory | [mem0](https://docs.pipecat.ai/server/services/memory/mem0) | +| Vision & Image | [fal](https://docs.pipecat.ai/server/services/image-generation/fal), [Google Imagen](https://docs.pipecat.ai/server/services/image-generation/google-imagen), [Moondream](https://docs.pipecat.ai/server/services/vision/moondream) | +| Audio Processing | [Silero VAD](https://docs.pipecat.ai/server/utilities/audio/silero-vad-analyzer), [Krisp](https://docs.pipecat.ai/server/utilities/audio/krisp-filter), [Koala](https://docs.pipecat.ai/server/utilities/audio/koala-filter), [ai-coustics](https://docs.pipecat.ai/server/utilities/audio/aic-filter) | +| Analytics & Metrics | [OpenTelemetry](https://docs.pipecat.ai/server/utilities/opentelemetry), [Sentry](https://docs.pipecat.ai/server/services/analytics/sentry) | 📚 [View full services documentation →](https://docs.pipecat.ai/server/services/supported-services) diff --git a/env.example b/env.example index 81f3f895d..dda5bb084 100644 --- a/env.example +++ b/env.example @@ -86,9 +86,6 @@ GROK_API_KEY=... # Groq GROQ_API_KEY=... -# Hathora -HATHORA_API_KEY=... - # Heygen HEYGEN_API_KEY=... HEYGEN_LIVE_AVATAR_API_KEY=... diff --git a/examples/foundational/07zh-interruptible-hathora.py b/examples/foundational/07zh-interruptible-hathora.py deleted file mode 100644 index 08749bf1a..000000000 --- a/examples/foundational/07zh-interruptible-hathora.py +++ /dev/null @@ -1,123 +0,0 @@ -# -# Copyright (c) 2024–2026, Daily -# -# SPDX-License-Identifier: BSD 2-Clause License -# - -import os - -from dotenv import load_dotenv -from loguru import logger - -from pipecat.audio.vad.silero import SileroVADAnalyzer -from pipecat.frames.frames import LLMRunFrame -from pipecat.pipeline.pipeline import Pipeline -from pipecat.pipeline.runner import PipelineRunner -from pipecat.pipeline.task import PipelineParams, PipelineTask -from pipecat.processors.aggregators.llm_context import LLMContext -from pipecat.processors.aggregators.llm_response_universal import ( - LLMContextAggregatorPair, - LLMUserAggregatorParams, -) -from pipecat.runner.types import RunnerArguments -from pipecat.runner.utils import create_transport -from pipecat.services.hathora.stt import HathoraSTTService -from pipecat.services.hathora.tts import HathoraTTSService -from pipecat.services.openai.llm import OpenAILLMService -from pipecat.transports.base_transport import BaseTransport, TransportParams -from pipecat.transports.daily.transport import DailyParams -from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams - -load_dotenv(override=True) - -# We use lambdas to defer transport parameter creation until the transport -# type is selected at runtime. -transport_params = { - "daily": lambda: DailyParams( - audio_in_enabled=True, - audio_out_enabled=True, - ), - "twilio": lambda: FastAPIWebsocketParams( - audio_in_enabled=True, - audio_out_enabled=True, - ), - "webrtc": lambda: TransportParams( - audio_in_enabled=True, - audio_out_enabled=True, - ), -} - - -async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): - logger.info(f"Starting bot") - - stt = HathoraSTTService( - model="nvidia-parakeet-tdt-0.6b-v3", - ) - - tts = HathoraTTSService( - model="hexgrad-kokoro-82m", - ) - - # See https://models.hathora.dev/model/qwen3-30b-a3b - llm = OpenAILLMService( - base_url="https://app-362f7ca1-6975-4e18-a605-ab202bf2c315.app.hathora.dev/v1", - api_key=os.getenv("HATHORA_API_KEY"), - model=None, - system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", - ) - - context = LLMContext() - context_aggregator = LLMContextAggregatorPair( - context, - user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()), - ) - - pipeline = Pipeline( - [ - transport.input(), # Transport user input - stt, - context_aggregator.user(), # User responses - llm, # LLM - tts, # TTS - transport.output(), # Transport bot output - context_aggregator.assistant(), # Assistant spoken responses - ] - ) - - task = PipelineTask( - pipeline, - params=PipelineParams( - enable_metrics=True, - enable_usage_metrics=True, - ), - idle_timeout_secs=runner_args.pipeline_idle_timeout_secs, - ) - - @transport.event_handler("on_client_connected") - async def on_client_connected(transport, client): - logger.info(f"Client connected") - # Kick off the conversation. - context.add_message({"role": "system", "content": "Please introduce yourself to the user."}) - await task.queue_frames([LLMRunFrame()]) - - @transport.event_handler("on_client_disconnected") - async def on_client_disconnected(transport, client): - logger.info(f"Client disconnected") - await task.cancel() - - runner = PipelineRunner(handle_sigint=runner_args.handle_sigint) - - await runner.run(task) - - -async def bot(runner_args: RunnerArguments): - """Main bot entry point compatible with Pipecat Cloud.""" - transport = await create_transport(runner_args, transport_params) - await run_bot(transport, runner_args) - - -if __name__ == "__main__": - from pipecat.runner.run import main - - main() diff --git a/examples/foundational/55zg-update-settings-hathora-tts.py b/examples/foundational/55zg-update-settings-hathora-tts.py deleted file mode 100644 index 2294809e2..000000000 --- a/examples/foundational/55zg-update-settings-hathora-tts.py +++ /dev/null @@ -1,121 +0,0 @@ -# -# Copyright (c) 2024-2026, Daily -# -# SPDX-License-Identifier: BSD 2-Clause License -# - -import asyncio -import os - -from dotenv import load_dotenv -from loguru import logger - -from pipecat.audio.vad.silero import SileroVADAnalyzer -from pipecat.frames.frames import LLMRunFrame, TTSUpdateSettingsFrame -from pipecat.pipeline.pipeline import Pipeline -from pipecat.pipeline.runner import PipelineRunner -from pipecat.pipeline.task import PipelineParams, PipelineTask -from pipecat.processors.aggregators.llm_context import LLMContext -from pipecat.processors.aggregators.llm_response_universal import ( - LLMContextAggregatorPair, - LLMUserAggregatorParams, -) -from pipecat.runner.types import RunnerArguments -from pipecat.runner.utils import create_transport -from pipecat.services.deepgram.stt import DeepgramSTTService -from pipecat.services.hathora.tts import HathoraTTSService, HathoraTTSSettings -from pipecat.services.openai.llm import OpenAILLMService -from pipecat.transports.base_transport import BaseTransport, TransportParams -from pipecat.transports.daily.transport import DailyParams -from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams - -load_dotenv(override=True) - -transport_params = { - "daily": lambda: DailyParams( - audio_in_enabled=True, - audio_out_enabled=True, - ), - "twilio": lambda: FastAPIWebsocketParams( - audio_in_enabled=True, - audio_out_enabled=True, - ), - "webrtc": lambda: TransportParams( - audio_in_enabled=True, - audio_out_enabled=True, - ), -} - - -async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): - logger.info(f"Starting bot") - - stt = DeepgramSTTService(api_key=os.getenv("DEEPGRAM_API_KEY")) - - tts = HathoraTTSService( - api_key=os.getenv("HATHORA_API_KEY"), - model="hexgrad-kokoro-82m", - ) - - llm = OpenAILLMService( - api_key=os.getenv("OPENAI_API_KEY"), - system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", - ) - - context = LLMContext() - user_aggregator, assistant_aggregator = LLMContextAggregatorPair( - context, - user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()), - ) - - pipeline = Pipeline( - [ - transport.input(), - stt, - user_aggregator, - llm, - tts, - transport.output(), - assistant_aggregator, - ] - ) - - task = PipelineTask( - pipeline, - params=PipelineParams( - enable_metrics=True, - enable_usage_metrics=True, - ), - idle_timeout_secs=runner_args.pipeline_idle_timeout_secs, - ) - - @transport.event_handler("on_client_connected") - async def on_client_connected(transport, client): - logger.info(f"Client connected") - context.add_message({"role": "system", "content": "Please introduce yourself to the user."}) - await task.queue_frames([LLMRunFrame()]) - - await asyncio.sleep(10) - logger.info("Updating Hathora TTS settings: speed=1.5") - await task.queue_frame(TTSUpdateSettingsFrame(delta=HathoraTTSSettings(speed=1.5))) - - @transport.event_handler("on_client_disconnected") - async def on_client_disconnected(transport, client): - logger.info(f"Client disconnected") - await task.cancel() - - runner = PipelineRunner(handle_sigint=runner_args.handle_sigint) - - await runner.run(task) - - -async def bot(runner_args: RunnerArguments): - """Main bot entry point compatible with Pipecat Cloud.""" - transport = await create_transport(runner_args, transport_params) - await run_bot(transport, runner_args) - - -if __name__ == "__main__": - from pipecat.runner.run import main - - main() diff --git a/examples/foundational/55zs-update-settings-hathora-stt.py b/examples/foundational/55zs-update-settings-hathora-stt.py deleted file mode 100644 index 818772b75..000000000 --- a/examples/foundational/55zs-update-settings-hathora-stt.py +++ /dev/null @@ -1,127 +0,0 @@ -# -# Copyright (c) 2024-2026, Daily -# -# SPDX-License-Identifier: BSD 2-Clause License -# - -import asyncio -import os - -from dotenv import load_dotenv -from loguru import logger - -from pipecat.audio.vad.silero import SileroVADAnalyzer -from pipecat.frames.frames import LLMRunFrame, STTUpdateSettingsFrame -from pipecat.pipeline.pipeline import Pipeline -from pipecat.pipeline.runner import PipelineRunner -from pipecat.pipeline.task import PipelineParams, PipelineTask -from pipecat.processors.aggregators.llm_context import LLMContext -from pipecat.processors.aggregators.llm_response_universal import ( - LLMContextAggregatorPair, - LLMUserAggregatorParams, -) -from pipecat.runner.types import RunnerArguments -from pipecat.runner.utils import create_transport -from pipecat.services.cartesia.tts import CartesiaTTSService -from pipecat.services.hathora.stt import HathoraSTTService, HathoraSTTSettings -from pipecat.services.hathora.utils import ConfigOption -from pipecat.services.openai.llm import OpenAILLMService -from pipecat.transcriptions.language import Language -from pipecat.transports.base_transport import BaseTransport, TransportParams -from pipecat.transports.daily.transport import DailyParams -from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams - -load_dotenv(override=True) - -transport_params = { - "daily": lambda: DailyParams( - audio_in_enabled=True, - audio_out_enabled=True, - ), - "twilio": lambda: FastAPIWebsocketParams( - audio_in_enabled=True, - audio_out_enabled=True, - ), - "webrtc": lambda: TransportParams( - audio_in_enabled=True, - audio_out_enabled=True, - ), -} - - -async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): - logger.info(f"Starting bot") - - stt = HathoraSTTService( - api_key=os.getenv("HATHORA_API_KEY"), model="nvidia-parakeet-tdt-0.6b-v3" - ) - - tts = CartesiaTTSService( - api_key=os.getenv("CARTESIA_API_KEY"), - voice_id="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady - ) - - llm = OpenAILLMService( - api_key=os.getenv("OPENAI_API_KEY"), - system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", - ) - - context = LLMContext() - user_aggregator, assistant_aggregator = LLMContextAggregatorPair( - context, - user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()), - ) - - pipeline = Pipeline( - [ - transport.input(), - stt, - user_aggregator, - llm, - tts, - transport.output(), - assistant_aggregator, - ] - ) - - task = PipelineTask( - pipeline, - params=PipelineParams( - enable_metrics=True, - enable_usage_metrics=True, - ), - idle_timeout_secs=runner_args.pipeline_idle_timeout_secs, - ) - - @transport.event_handler("on_client_connected") - async def on_client_connected(transport, client): - logger.info(f"Client connected") - context.add_message({"role": "system", "content": "Please introduce yourself to the user."}) - await task.queue_frames([LLMRunFrame()]) - - await asyncio.sleep(10) - logger.info("Updating Hathora STT settings: language=es") - await task.queue_frame( - STTUpdateSettingsFrame(delta=HathoraSTTSettings(language=Language.ES)) - ) - - @transport.event_handler("on_client_disconnected") - async def on_client_disconnected(transport, client): - logger.info(f"Client disconnected") - await task.cancel() - - runner = PipelineRunner(handle_sigint=runner_args.handle_sigint) - - await runner.run(task) - - -async def bot(runner_args: RunnerArguments): - """Main bot entry point compatible with Pipecat Cloud.""" - transport = await create_transport(runner_args, transport_params) - await run_bot(transport, runner_args) - - -if __name__ == "__main__": - from pipecat.runner.run import main - - main() diff --git a/scripts/evals/run-release-evals.py b/scripts/evals/run-release-evals.py index 77fc23a33..e473403b8 100644 --- a/scripts/evals/run-release-evals.py +++ b/scripts/evals/run-release-evals.py @@ -144,7 +144,6 @@ TESTS_07 = [ ("07ze-interruptible-hume.py", EVAL_SIMPLE_MATH), ("07zf-interruptible-gradium.py", EVAL_SIMPLE_MATH), ("07zg-interruptible-camb.py", EVAL_SIMPLE_MATH), - ("07zh-interruptible-hathora.py", EVAL_SIMPLE_MATH), ("07zi-interruptible-piper.py", EVAL_SIMPLE_MATH), ("07zj-interruptible-kokoro.py", EVAL_SIMPLE_MATH), # Needs a local XTTS docker instance running. diff --git a/src/pipecat/services/hathora/__init__.py b/src/pipecat/services/hathora/__init__.py deleted file mode 100644 index e69de29bb..000000000 diff --git a/src/pipecat/services/hathora/stt.py b/src/pipecat/services/hathora/stt.py deleted file mode 100644 index 27f1aebfb..000000000 --- a/src/pipecat/services/hathora/stt.py +++ /dev/null @@ -1,176 +0,0 @@ -# -# Copyright (c) 2024–2025, Daily -# -# SPDX-License-Identifier: BSD 2-Clause License -# - -"""[Hathora-hosted](https://models.hathora.dev) speech-to-text services.""" - -import base64 -import os -from dataclasses import dataclass, field -from typing import AsyncGenerator, Optional - -import aiohttp -from pydantic import BaseModel - -from pipecat.frames.frames import ( - ErrorFrame, - Frame, - TranscriptionFrame, -) -from pipecat.services.settings import NOT_GIVEN, STTSettings, _NotGiven -from pipecat.services.stt_latency import HATHORA_TTFS_P99 -from pipecat.services.stt_service import SegmentedSTTService -from pipecat.transcriptions.language import Language -from pipecat.utils.time import time_now_iso8601 -from pipecat.utils.tracing.service_decorators import traced_stt - -from .utils import ConfigOption - - -@dataclass -class HathoraSTTSettings(STTSettings): - """Settings for the Hathora STT service. - - Parameters: - config: Some models support additional config, refer to - `docs `_ for each model to see - what is supported. - """ - - config: list[ConfigOption] | _NotGiven = field(default_factory=lambda: NOT_GIVEN) - - -class HathoraSTTService(SegmentedSTTService): - """This service supports several different speech-to-text models hosted by Hathora. - - [Documentation](https://models.hathora.dev) - """ - - _settings: HathoraSTTSettings - - class InputParams(BaseModel): - """Optional input parameters for Hathora STT configuration. - - Parameters: - language: Language code (if supported by model). - config: Some models support additional config, refer to - [docs](https://models.hathora.dev) for each model to see - what is supported. - """ - - language: Optional[str] = None - config: Optional[list[ConfigOption]] = None - - def __init__( - self, - *, - model: str, - sample_rate: Optional[int] = None, - api_key: Optional[str] = None, - base_url: str = "https://api.models.hathora.dev/inference/v1/stt", - params: Optional[InputParams] = None, - ttfs_p99_latency: Optional[float] = HATHORA_TTFS_P99, - **kwargs, - ): - """Initialize the Hathora STT service. - - Args: - model: Model to use; find available models - [here](https://models.hathora.dev). - sample_rate: The sample rate for audio input. If None, will be determined - from the start frame. - api_key: API key for authentication with the Hathora service; - provision one [here](https://models.hathora.dev/tokens). - base_url: Base API URL for the Hathora STT service. - params: Configuration parameters. - ttfs_p99_latency: P99 latency from speech end to final transcript in seconds. - Override for your deployment. See https://github.com/pipecat-ai/stt-benchmark - **kwargs: Additional arguments passed to the parent class. - """ - params = params or HathoraSTTService.InputParams() - - super().__init__( - sample_rate=sample_rate, - ttfs_p99_latency=ttfs_p99_latency, - settings=HathoraSTTSettings( - model=model, - language=params.language, - config=params.config, - ), - **kwargs, - ) - self._api_key = api_key or os.getenv("HATHORA_API_KEY") - self._base_url = base_url - - def can_generate_metrics(self) -> bool: - """Check if this service can generate processing metrics. - - Returns: - True - """ - return True - - @traced_stt - async def _handle_transcription( - self, transcript: str, is_final: bool, language: Optional[Language] = None - ): - """Handle a transcription result with tracing.""" - pass - - async def run_stt(self, audio: bytes) -> AsyncGenerator[Frame, None]: - """Run speech-to-text on the provided audio data. - - Args: - audio: Raw audio bytes to transcribe. - - Yields: - Frame: Frames containing transcription results (typically TextFrame). - """ - try: - await self.start_processing_metrics() - - url = f"{self._base_url}" - - payload = { - "model": self._settings.model, - } - - if self._settings.language is not None: - payload["language"] = self._settings.language - if self._settings.config is not None: - payload["model_config"] = [ - {"name": option.name, "value": option.value} for option in self._settings.config - ] - - base64_audio = base64.b64encode(audio).decode("utf-8") - payload["audio"] = base64_audio - - async with aiohttp.ClientSession() as session: - async with session.post( - url, - headers={"Authorization": f"Bearer {self._api_key}"}, - json=payload, - ) as resp: - response = await resp.json() - - if response and "text" in response: - text = response["text"].strip() - if text: # Only yield non-empty text - # Hathora's API currently doesn't return language info - # so we default to the requested language or "en" - response_language = self._settings.language or "en" - await self._handle_transcription(text, True, response_language) - yield TranscriptionFrame( - text, - self._user_id, - time_now_iso8601(), - Language(response_language), - result=response, - ) - - await self.stop_processing_metrics() - - except Exception as e: - yield ErrorFrame(error=f"Unknown error occurred: {e}") diff --git a/src/pipecat/services/hathora/tts.py b/src/pipecat/services/hathora/tts.py deleted file mode 100644 index 3fb9e747b..000000000 --- a/src/pipecat/services/hathora/tts.py +++ /dev/null @@ -1,191 +0,0 @@ -# -# Copyright (c) 2024–2025, Daily -# -# SPDX-License-Identifier: BSD 2-Clause License -# - -"""[Hathora-hosted](https://models.hathora.dev) text-to-speech services.""" - -import io -import os -import wave -from dataclasses import dataclass, field -from typing import AsyncGenerator, Optional, Tuple - -import aiohttp -from pydantic import BaseModel - -from pipecat.frames.frames import ( - ErrorFrame, - Frame, - TTSAudioRawFrame, - TTSStartedFrame, - TTSStoppedFrame, -) -from pipecat.services.settings import NOT_GIVEN, TTSSettings, _NotGiven -from pipecat.services.tts_service import TTSService -from pipecat.utils.tracing.service_decorators import traced_tts - -from .utils import ConfigOption - - -def _decode_audio_payload( - audio_bytes: bytes, - *, - fallback_sample_rate: int = 24000, - fallback_channels: int = 1, -) -> Tuple[bytes, int, int]: - """Convert a WAV/PCM payload into raw PCM samples for TTSAudioRawFrame.""" - try: - with wave.open(io.BytesIO(audio_bytes), "rb") as wav_reader: - channels = wav_reader.getnchannels() - sample_rate = wav_reader.getframerate() - frames = wav_reader.readframes(wav_reader.getnframes()) - return frames, sample_rate, channels - except (wave.Error, EOFError): - # If the payload is already raw PCM, just pass it through. - return audio_bytes, fallback_sample_rate, fallback_channels - - -@dataclass -class HathoraTTSSettings(TTSSettings): - """Settings for Hathora TTS service. - - Parameters: - speed: Speech speed multiplier (if supported by model). - config: Some models support additional config, refer to - [docs](https://models.hathora.dev) for each model to see - what is supported. - """ - - speed: float | _NotGiven = field(default_factory=lambda: NOT_GIVEN) - config: list[ConfigOption] | _NotGiven = field(default_factory=lambda: NOT_GIVEN) - - -class HathoraTTSService(TTSService): - """This service supports several different text-to-speech models hosted by Hathora. - - [Documentation](https://models.hathora.dev) - """ - - _settings: HathoraTTSSettings - - class InputParams(BaseModel): - """Optional input parameters for Hathora TTS configuration. - - Parameters: - speed: Speech speed multiplier (if supported by model). - config: Some models support additional config, refer to - [docs](https://models.hathora.dev) for each model to see - what is supported. - """ - - speed: Optional[float] = None - config: Optional[list[ConfigOption]] = None - - def __init__( - self, - *, - model: str, - voice_id: Optional[str] = None, - sample_rate: Optional[int] = None, - api_key: Optional[str] = None, - base_url: str = "https://api.models.hathora.dev/inference/v1/tts", - params: Optional[InputParams] = None, - **kwargs, - ): - """Initialize the Hathora TTS service. - - Args: - model: Model to use; find available models - [here](https://models.hathora.dev). - voice_id: Voice to use for synthesis (if supported by model). - sample_rate: Output sample rate for generated audio. - api_key: API key for authentication with the Hathora service; - provision one [here](https://models.hathora.dev/tokens). - base_url: Base API URL for the Hathora TTS service. - params: Configuration parameters. - **kwargs: Additional arguments passed to the parent class. - """ - params = params or HathoraTTSService.InputParams() - - super().__init__( - sample_rate=sample_rate, - settings=HathoraTTSSettings( - model=model, - voice=voice_id, - language=None, # Not applicable here - speed=params.speed, - config=params.config, - ), - **kwargs, - ) - self._api_key = api_key or os.getenv("HATHORA_API_KEY") - self._base_url = base_url - - def can_generate_metrics(self) -> bool: - """Check if this service can generate processing metrics. - - Returns: - True - """ - return True - - @traced_tts - async def run_tts(self, text: str, context_id: str) -> AsyncGenerator[Frame, None]: - """Run text-to-speech synthesis on the provided text. - - Args: - text: The text to synthesize into speech. - context_id: The context ID for tracking audio frames. - - Yields: - Frame: Audio frames containing the synthesized speech. - """ - try: - await self.start_processing_metrics() - await self.start_ttfb_metrics() - - url = f"{self._base_url}" - - payload = {"model": self._settings.model, "text": text} - - if self._settings.voice is not None: - payload["voice"] = self._settings.voice - if self._settings.speed is not None: - payload["speed"] = self._settings.speed - if self._settings.config is not None: - payload["model_config"] = [ - {"name": option.name, "value": option.value} for option in self._settings.config - ] - - yield TTSStartedFrame(context_id=context_id) - - async with aiohttp.ClientSession() as session: - async with session.post( - url, - headers={"Authorization": f"Bearer {self._api_key}"}, - json=payload, - ) as resp: - audio_data = await resp.read() - - pcm_audio, sample_rate, num_channels = _decode_audio_payload( - audio_data, - fallback_sample_rate=self.sample_rate, - ) - - frame = TTSAudioRawFrame( - audio=pcm_audio, - sample_rate=self.sample_rate, - num_channels=num_channels, - context_id=context_id, - ) - - yield frame - - except Exception as e: - yield ErrorFrame(error=f"Unknown error occurred: {e}") - finally: - await self.stop_ttfb_metrics() - await self.stop_processing_metrics() - yield TTSStoppedFrame(context_id=context_id) diff --git a/src/pipecat/services/hathora/utils.py b/src/pipecat/services/hathora/utils.py deleted file mode 100644 index 6d8eb54b8..000000000 --- a/src/pipecat/services/hathora/utils.py +++ /dev/null @@ -1,22 +0,0 @@ -# -# Copyright (c) 2024–2025, Daily -# -# SPDX-License-Identifier: BSD 2-Clause License -# - -"""Utilities and types for [Hathora-hosted](https://models.hathora.dev) voice services.""" - -from dataclasses import dataclass - - -@dataclass -class ConfigOption: - """Extra configuration option passed into model_config for Hathora (if supported by model). - - Args: - name: Name of the configuration option. - value: Value of the configuration option. - """ - - name: str - value: str diff --git a/src/pipecat/services/stt_latency.py b/src/pipecat/services/stt_latency.py index bf895e1e4..351e041a6 100644 --- a/src/pipecat/services/stt_latency.py +++ b/src/pipecat/services/stt_latency.py @@ -40,7 +40,6 @@ GLADIA_TTFS_P99: float = 1.49 GOOGLE_TTFS_P99: float = 1.57 GRADIUM_TTFS_P99: float = 1.61 GROQ_TTFS_P99: float = 1.54 -HATHORA_TTFS_P99: float = 0.87 OPENAI_TTFS_P99: float = 2.01 OPENAI_REALTIME_TTFS_P99: float = 1.66 SAMBANOVA_TTFS_P99: float = 2.20 From 05fa727c22b63060e085c19713c786aa35be1bfe Mon Sep 17 00:00:00 2001 From: Mark Backman Date: Thu, 5 Mar 2026 13:13:55 -0500 Subject: [PATCH 0791/1060] Update core dependency version ranges for flexibility Widen version ranges for stable packages (aiofiles, docstring_parser, onnxruntime) while adding upper bounds to previously uncapped packages (transformers, numba, wait_for2). Bump soxr to 1.0.0 and pyloudnorm to 0.2.0. Move silero extra to empty since onnxruntime is now a core dep. --- pyproject.toml | 22 ++++----- src/pipecat/audio/vad/silero.py | 2 +- uv.lock | 85 ++++++++++++++++----------------- 3 files changed, 53 insertions(+), 56 deletions(-) diff --git a/pyproject.toml b/pyproject.toml index 0324c311a..5b675ac8c 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -20,10 +20,10 @@ classifiers = [ "Topic :: Scientific/Engineering :: Artificial Intelligence" ] dependencies = [ - "aiofiles>=24.1.0,<25", + "aiofiles>=24.1.0,<27", "aiohttp>=3.11.12,<4", "audioop-lts~=0.2.1; python_version>='3.13'", - "docstring_parser~=0.16", + "docstring_parser>=0.16,<1", "loguru~=0.7.3", "Markdown>=3.7,<4", "nltk>=3.9.3,<4", @@ -31,17 +31,17 @@ dependencies = [ "Pillow>=11.1.0,<13", "protobuf~=5.29.6", "pydantic>=2.10.6,<3", - "pyloudnorm~=0.1.1", + "pyloudnorm~=0.2.0", "resampy~=0.4.3", - "soxr~=0.5.0", + "soxr~=1.0.0", "openai>=1.74.0,<3", # Pinning numba to resolve package dependencies - "numba>=0.61.2", - "wait_for2>=0.4.1; python_version<'3.12'", + "numba>=0.61.2,<1", + "wait_for2>=0.4.1,<1; python_version<'3.12'", # Required by LocalSmartTurnAnalyzerV3 # Inlined here instead of using a self-referential extra for Poetry compatibility. - "transformers", - "onnxruntime~=1.23.2", + "transformers>=4.48.0,<6", + "onnxruntime>=1.23.2,<2", ] [project.urls] @@ -86,12 +86,12 @@ lemonslice = [ "pipecat-ai[daily]" ] livekit = [ "livekit~=1.0.13", "livekit-api~=1.0.5", "tenacity>=8.2.3,<10.0.0", "pyjwt>=2.10.1" ] lmnt = [ "pipecat-ai[websockets-base]" ] local = [ "pyaudio~=0.2.14" ] -local-smart-turn = [ "coremltools>=8.0", "transformers", "torch>=2.5.0,<3", "torchaudio>=2.5.0,<3" ] +local-smart-turn = [ "coremltools>=8.0", "transformers>=4.48.0,<6", "torch>=2.5.0,<3", "torchaudio>=2.5.0,<3" ] mcp = [ "mcp[cli]>=1.11.0,<2" ] mem0 = [ "mem0ai~=0.1.94" ] mistral = [] mlx-whisper = [ "mlx-whisper~=0.4.2" ] -moondream = [ "accelerate~=1.10.0", "einops~=0.8.0", "pyvips[binary]~=3.0.0", "timm~=1.0.13", "transformers>=4.48.0" ] +moondream = [ "accelerate~=1.10.0", "einops~=0.8.0", "pyvips[binary]~=3.0.0", "timm~=1.0.13", "transformers>=4.48.0,<6" ] neuphonic = [ "pipecat-ai[websockets-base]" ] noisereduce = [ "noisereduce~=3.0.3" ] nvidia = [ "nvidia-riva-client~=2.21.1" ] @@ -111,7 +111,7 @@ sagemaker = ["aws_sdk_sagemaker_runtime_http2; python_version>='3.12'"] sambanova = [] sarvam = [ "sarvamai==0.1.26a2", "pipecat-ai[websockets-base]" ] sentry = [ "sentry-sdk>=2.28.0,<3" ] -silero = [ "onnxruntime~=1.23.2" ] +silero = [] simli = [ "simli-ai~=2.0.1"] soniox = [ "pipecat-ai[websockets-base]" ] soundfile = [ "soundfile~=0.13.1" ] diff --git a/src/pipecat/audio/vad/silero.py b/src/pipecat/audio/vad/silero.py index 5b4ad9c0a..c15ba5b90 100644 --- a/src/pipecat/audio/vad/silero.py +++ b/src/pipecat/audio/vad/silero.py @@ -27,7 +27,7 @@ try: except ModuleNotFoundError as e: logger.error(f"Exception: {e}") - logger.error("In order to use Silero VAD, you need to `pip install pipecat-ai[silero]`.") + logger.error("In order to use Silero VAD, you need to `pip install pipecat-ai`.") raise Exception(f"Missing module(s): {e}") diff --git a/uv.lock b/uv.lock index 8c9d3b486..db8f68ade 100644 --- a/uv.lock +++ b/uv.lock @@ -1933,15 +1933,6 @@ wheels = [ { url = "https://files.pythonhosted.org/packages/e6/ab/fb21f4c939bb440104cc2b396d3be1d9b7a9fd3c6c2a53d98c45b3d7c954/fsspec-2026.2.0-py3-none-any.whl", hash = "sha256:98de475b5cb3bd66bedd5c4679e87b4fdfe1a3bf4d707b151b3c07e58c9a2437", size = 202505, upload-time = "2026-02-05T21:50:51.819Z" }, ] -[[package]] -name = "future" -version = "1.0.0" -source = { registry = "https://pypi.org/simple" } -sdist = { url = "https://files.pythonhosted.org/packages/a7/b2/4140c69c6a66432916b26158687e821ba631a4c9273c474343badf84d3ba/future-1.0.0.tar.gz", hash = "sha256:bd2968309307861edae1458a4f8a4f3598c03be43b97521076aebf5d94c07b05", size = 1228490, upload-time = "2024-02-21T11:52:38.461Z" } -wheels = [ - { url = 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Replace CartesiaHttpTTSService's internal use of the Cartesia SDK with direct aiohttp calls, accepting an optional aiohttp_session parameter. Replace fal-client SDK calls in FalSTTService and FalImageGenService with direct HTTP to bypass the SDK's aggressive retry/backoff logic that caused significant latency regressions. --- .../07-interruptible-cartesia-http.py | 95 ++++---- .../07c-interruptible-deepgram-sagemaker.py | 2 +- .../foundational/07w-interruptible-fal.py | 99 ++++---- pyproject.toml | 36 +-- src/pipecat/services/cartesia/tts.py | 31 +-- src/pipecat/services/fal/image.py | 28 ++- src/pipecat/services/fal/stt.py | 50 ++-- uv.lock | 213 +++++------------- 8 files changed, 246 insertions(+), 308 deletions(-) diff --git a/examples/foundational/07-interruptible-cartesia-http.py b/examples/foundational/07-interruptible-cartesia-http.py index 558217413..8ce1ed375 100644 --- a/examples/foundational/07-interruptible-cartesia-http.py +++ b/examples/foundational/07-interruptible-cartesia-http.py @@ -6,6 +6,7 @@ import os +import aiohttp from dotenv import load_dotenv from loguru import logger @@ -52,60 +53,64 @@ transport_params = { async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): logger.info(f"Starting bot") - stt = CartesiaSTTService(api_key=os.getenv("CARTESIA_API_KEY")) + async with aiohttp.ClientSession() as session: + stt = CartesiaSTTService(api_key=os.getenv("CARTESIA_API_KEY")) - tts = CartesiaHttpTTSService( - api_key=os.getenv("CARTESIA_API_KEY"), - voice_id="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady - ) + tts = CartesiaHttpTTSService( + api_key=os.getenv("CARTESIA_API_KEY"), + voice_id="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady + aiohttp_session=session, + ) - llm = OpenAILLMService( - api_key=os.getenv("OPENAI_API_KEY"), - system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", - ) + llm = OpenAILLMService( + api_key=os.getenv("OPENAI_API_KEY"), + system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + ) - context = LLMContext() - user_aggregator, assistant_aggregator = LLMContextAggregatorPair( - context, - user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()), - ) + context = LLMContext() + user_aggregator, assistant_aggregator = LLMContextAggregatorPair( + context, + user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()), + ) - pipeline = Pipeline( - [ - transport.input(), # Transport user input - stt, - user_aggregator, # User responses - llm, # LLM - tts, # TTS - transport.output(), # Transport bot output - assistant_aggregator, # Assistant spoken responses - ] - ) + pipeline = Pipeline( + [ + transport.input(), # Transport user input + stt, + user_aggregator, # User responses + llm, # LLM + tts, # TTS + transport.output(), # Transport bot output + assistant_aggregator, # Assistant spoken responses + ] + ) - task = PipelineTask( - pipeline, - params=PipelineParams( - enable_metrics=True, - enable_usage_metrics=True, - ), - idle_timeout_secs=runner_args.pipeline_idle_timeout_secs, - ) + task = PipelineTask( + pipeline, + params=PipelineParams( + enable_metrics=True, + enable_usage_metrics=True, + ), + idle_timeout_secs=runner_args.pipeline_idle_timeout_secs, + ) - @transport.event_handler("on_client_connected") - async def on_client_connected(transport, client): - logger.info(f"Client connected") - # Kick off the conversation. - context.add_message({"role": "system", "content": "Please introduce yourself to the user."}) - await task.queue_frames([LLMRunFrame()]) + @transport.event_handler("on_client_connected") + async def on_client_connected(transport, client): + logger.info(f"Client connected") + # Kick off the conversation. + context.add_message( + {"role": "system", "content": "Please introduce yourself to the user."} + ) + await task.queue_frames([LLMRunFrame()]) - @transport.event_handler("on_client_disconnected") - async def on_client_disconnected(transport, client): - logger.info(f"Client disconnected") - await task.cancel() + @transport.event_handler("on_client_disconnected") + async def on_client_disconnected(transport, client): + logger.info(f"Client disconnected") + await task.cancel() - runner = PipelineRunner(handle_sigint=runner_args.handle_sigint) + runner = PipelineRunner(handle_sigint=runner_args.handle_sigint) - await runner.run(task) + await runner.run(task) async def bot(runner_args: RunnerArguments): diff --git a/examples/foundational/07c-interruptible-deepgram-sagemaker.py b/examples/foundational/07c-interruptible-deepgram-sagemaker.py index 8c7fc6556..406f95445 100644 --- a/examples/foundational/07c-interruptible-deepgram-sagemaker.py +++ b/examples/foundational/07c-interruptible-deepgram-sagemaker.py @@ -110,7 +110,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): async def on_client_connected(transport, client): logger.info(f"Client connected") # Kick off the conversation. - context.add_message({"role": "system", "content": "Please introduce yourself to the user."}) + context.add_message({"role": "user", "content": "Please introduce yourself to the user."}) await task.queue_frames([LLMRunFrame()]) @transport.event_handler("on_client_disconnected") diff --git a/examples/foundational/07w-interruptible-fal.py b/examples/foundational/07w-interruptible-fal.py index 2d1886ddb..6d88e8624 100644 --- a/examples/foundational/07w-interruptible-fal.py +++ b/examples/foundational/07w-interruptible-fal.py @@ -7,6 +7,7 @@ import os +import aiohttp from dotenv import load_dotenv from loguru import logger @@ -53,62 +54,66 @@ transport_params = { async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): logger.info(f"Starting bot") - stt = FalSTTService( - api_key=os.getenv("FAL_KEY"), - ) + async with aiohttp.ClientSession() as session: + stt = FalSTTService( + api_key=os.getenv("FAL_KEY"), + aiohttp_session=session, + ) - tts = CartesiaTTSService( - api_key=os.getenv("CARTESIA_API_KEY"), - voice_id="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady - ) + tts = CartesiaTTSService( + api_key=os.getenv("CARTESIA_API_KEY"), + voice_id="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady + ) - llm = OpenAILLMService( - api_key=os.getenv("OPENAI_API_KEY"), - system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", - ) + llm = OpenAILLMService( + api_key=os.getenv("OPENAI_API_KEY"), + system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + ) - context = LLMContext() - user_aggregator, assistant_aggregator = LLMContextAggregatorPair( - context, - user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()), - ) + context = LLMContext() + user_aggregator, assistant_aggregator = LLMContextAggregatorPair( + context, + user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()), + ) - pipeline = Pipeline( - [ - transport.input(), # Transport user input - stt, # STT - user_aggregator, # User responses - llm, # LLM - tts, # TTS - transport.output(), # Transport bot output - assistant_aggregator, # Assistant spoken responses - ] - ) + pipeline = Pipeline( + [ + transport.input(), # Transport user input + stt, # STT + user_aggregator, # User responses + llm, # LLM + tts, # TTS + transport.output(), # Transport bot output + assistant_aggregator, # Assistant spoken responses + ] + ) - task = PipelineTask( - pipeline, - params=PipelineParams( - enable_metrics=True, - enable_usage_metrics=True, - ), - idle_timeout_secs=runner_args.pipeline_idle_timeout_secs, - ) + task = PipelineTask( + pipeline, + params=PipelineParams( + enable_metrics=True, + enable_usage_metrics=True, + ), + idle_timeout_secs=runner_args.pipeline_idle_timeout_secs, + ) - @transport.event_handler("on_client_connected") - async def on_client_connected(transport, client): - logger.info(f"Client connected") - # Kick off the conversation. - context.add_message({"role": "system", "content": "Please introduce yourself to the user."}) - await task.queue_frames([LLMRunFrame()]) + @transport.event_handler("on_client_connected") + async def on_client_connected(transport, client): + logger.info(f"Client connected") + # Kick off the conversation. + context.add_message( + {"role": "system", "content": "Please introduce yourself to the user."} + ) + await task.queue_frames([LLMRunFrame()]) - @transport.event_handler("on_client_disconnected") - async def on_client_disconnected(transport, client): - logger.info(f"Client disconnected") - await task.cancel() + @transport.event_handler("on_client_disconnected") + async def on_client_disconnected(transport, client): + logger.info(f"Client disconnected") + await task.cancel() - runner = PipelineRunner(handle_sigint=runner_args.handle_sigint) + runner = PipelineRunner(handle_sigint=runner_args.handle_sigint) - await runner.run(task) + await runner.run(task) async def bot(runner_args: RunnerArguments): diff --git a/pyproject.toml b/pyproject.toml index 5b675ac8c..ec56f0ede 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -53,37 +53,37 @@ Changelog = "https://github.com/pipecat-ai/pipecat/blob/main/CHANGELOG.md" [project.optional-dependencies] aic = [ "aic-sdk~=2.1.0" ] -anthropic = [ "anthropic~=0.49.0" ] +anthropic = [ "anthropic>=0.49.0,<1" ] assemblyai = [ "pipecat-ai[websockets-base]" ] asyncai = [ "pipecat-ai[websockets-base]" ] -aws = [ "aioboto3~=15.5.0", "pipecat-ai[websockets-base]" ] -aws-nova-sonic = [ "aws_sdk_bedrock_runtime~=0.2.0; python_version>='3.12'" ] -azure = [ "azure-cognitiveservices-speech~=1.47.0"] -cartesia = [ "cartesia~=2.0.3", "pipecat-ai[websockets-base]" ] -camb = [ "camb-sdk>=1.5.4" ] +aws = [ "aioboto3>=15.5.0,<16", "pipecat-ai[websockets-base]" ] +aws-nova-sonic = [ "aws_sdk_bedrock_runtime~=0.4.0; python_version>='3.12'" ] +azure = [ "azure-cognitiveservices-speech>=1.47.0,<2"] +cartesia = [ "pipecat-ai[websockets-base]" ] +camb = [ "camb-sdk>=1.5.4,<2" ] cerebras = [] daily = [ "daily-python~=0.23.0" ] -deepgram = [ "deepgram-sdk~=6.0.1", "pipecat-ai[websockets-base]" ] +deepgram = [ "deepgram-sdk>=6.0.1,<7", "pipecat-ai[websockets-base]" ] deepseek = [] elevenlabs = [ "pipecat-ai[websockets-base]" ] -fal = [ "fal-client~=0.5.9" ] +fal = [] fireworks = [] -fish = [ "ormsgpack~=1.7.0", "pipecat-ai[websockets-base]" ] +fish = [ "ormsgpack>=1.7.0,<2", "pipecat-ai[websockets-base]" ] gladia = [ "pipecat-ai[websockets-base]" ] google = [ "google-cloud-speech>=2.33.0,<3", "google-cloud-texttospeech>=2.31.0,<3", "google-genai>=1.57.0,<2", "pipecat-ai[websockets-base]" ] gradium = [ "pipecat-ai[websockets-base]" ] grok = [] -groq = [ "groq~=0.23.0" ] +groq = [ "groq>=0.23.0,<2" ] gstreamer = [ "pygobject~=3.50.0" ] -heygen = [ "livekit>=1.0.13", "pipecat-ai[websockets-base]" ] -hume = [ "hume>=0.11.2" ] +heygen = [ "livekit>=1.0.13,<2", "pipecat-ai[websockets-base]" ] +hume = [ "hume>=0.11.2,<1" ] inworld = [] koala = [ "pvkoala~=2.0.3" ] kokoro = [ "kokoro-onnx>=0.5.0,<1", "requests>=2.32.5,<3" ] krisp = [ "pipecat-ai-krisp~=0.4.0" ] langchain = [ "langchain~=0.3.20", "langchain-community~=0.3.20", "langchain-openai~=0.3.9" ] lemonslice = [ "pipecat-ai[daily]" ] -livekit = [ "livekit~=1.0.13", "livekit-api~=1.0.5", "tenacity>=8.2.3,<10.0.0", "pyjwt>=2.10.1" ] +livekit = [ "livekit>=1.0.13,<2", "livekit-api>=1.0.5,<2", "tenacity>=8.2.3,<10.0.0", "pyjwt>=2.10.1,<3" ] lmnt = [ "pipecat-ai[websockets-base]" ] local = [ "pyaudio~=0.2.14" ] local-smart-turn = [ "coremltools>=8.0", "transformers>=4.48.0,<6", "torch>=2.5.0,<3", "torchaudio>=2.5.0,<3" ] @@ -94,7 +94,7 @@ mlx-whisper = [ "mlx-whisper~=0.4.2" ] moondream = [ "accelerate~=1.10.0", "einops~=0.8.0", "pyvips[binary]~=3.0.0", "timm~=1.0.13", "transformers>=4.48.0,<6" ] neuphonic = [ "pipecat-ai[websockets-base]" ] noisereduce = [ "noisereduce~=3.0.3" ] -nvidia = [ "nvidia-riva-client~=2.21.1" ] +nvidia = [ "nvidia-riva-client>=2.21.1,<3" ] openai = [ "pipecat-ai[websockets-base]" ] rnnoise = [ "pyrnnoise~=0.4.1" ] openpipe = [ "openpipe>=4.50.0,<6" ] @@ -106,7 +106,7 @@ remote-smart-turn = [] resembleai = [ "pipecat-ai[websockets-base]" ] rime = [ "pipecat-ai[websockets-base]" ] riva = [ "pipecat-ai[nvidia]" ] -runner = [ "python-dotenv>=1.0.0,<2.0.0", "uvicorn>=0.32.0,<1.0.0", "fastapi>=0.115.6,<0.128.0", "pipecat-ai-small-webrtc-prebuilt>=2.3.0"] +runner = [ "python-dotenv>=1.0.0,<2.0.0", "uvicorn>=0.32.0,<1.0.0", "fastapi>=0.115.6,<1", "pipecat-ai-small-webrtc-prebuilt>=2.3.0"] sagemaker = ["aws_sdk_sagemaker_runtime_http2; python_version>='3.12'"] sambanova = [] sarvam = [ "sarvamai==0.1.26a2", "pipecat-ai[websockets-base]" ] @@ -119,12 +119,12 @@ speechmatics = [ "speechmatics-voice[smart]~=0.2.8" ] strands = [ "strands-agents>=1.9.1,<2" ] tavus=[] together = [] -tracing = [ "opentelemetry-sdk>=1.33.0", "opentelemetry-api>=1.33.0", "opentelemetry-instrumentation>=0.54b0" ] +tracing = [ "opentelemetry-sdk>=1.33.0,<2", "opentelemetry-api>=1.33.0,<2", "opentelemetry-instrumentation>=0.54b0,<1" ] ultravox = [ "pipecat-ai[websockets-base]" ] webrtc = [ "aiortc>=1.14.0,<2", "opencv-python>=4.11.0.86,<5" ] -websocket = [ "pipecat-ai[websockets-base]", "fastapi>=0.115.6,<0.128.0" ] +websocket = [ "pipecat-ai[websockets-base]", "fastapi>=0.115.6,<1" ] websockets-base = [ "websockets>=13.1,<16.0" ] -whisper = [ "faster-whisper~=1.1.1" ] +whisper = [ "faster-whisper~=1.2.1" ] [dependency-groups] dev = [ diff --git a/src/pipecat/services/cartesia/tts.py b/src/pipecat/services/cartesia/tts.py index 2e637c339..a096a36b3 100644 --- a/src/pipecat/services/cartesia/tts.py +++ b/src/pipecat/services/cartesia/tts.py @@ -13,6 +13,7 @@ from dataclasses import dataclass, field from enum import Enum from typing import Any, AsyncGenerator, List, Literal, Mapping, Optional +import aiohttp from loguru import logger from pydantic import BaseModel, Field @@ -33,13 +34,8 @@ from pipecat.utils.text.base_text_aggregator import BaseTextAggregator from pipecat.utils.text.skip_tags_aggregator import SkipTagsAggregator from pipecat.utils.tracing.service_decorators import traced_tts -# Suppress regex warnings from pydub (used by cartesia) -warnings.filterwarnings("ignore", message="invalid escape sequence", category=SyntaxWarning) - - # See .env.example for Cartesia configuration needed try: - from cartesia import AsyncCartesia from websockets.asyncio.client import connect as websocket_connect from websockets.protocol import State except ModuleNotFoundError as e: @@ -721,6 +717,7 @@ class CartesiaHttpTTSService(TTSService): model: str = "sonic-3", base_url: str = "https://api.cartesia.ai", cartesia_version: str = "2024-11-13", + aiohttp_session: Optional[aiohttp.ClientSession] = None, sample_rate: Optional[int] = None, encoding: str = "pcm_s16le", container: str = "raw", @@ -735,6 +732,8 @@ class CartesiaHttpTTSService(TTSService): model: TTS model to use (e.g., "sonic-3"). base_url: Base URL for Cartesia HTTP API. cartesia_version: API version string for Cartesia service. + aiohttp_session: Optional aiohttp ClientSession for HTTP requests. + If not provided, a session will be created and managed internally. sample_rate: Audio sample rate. If None, uses default. encoding: Audio encoding format. container: Audio container format. @@ -766,10 +765,8 @@ class CartesiaHttpTTSService(TTSService): self._base_url = base_url self._cartesia_version = cartesia_version - self._client = AsyncCartesia( - api_key=api_key, - base_url=base_url, - ) + self._session: aiohttp.ClientSession | None = aiohttp_session + self._owns_session = aiohttp_session is None def can_generate_metrics(self) -> bool: """Check if this service can generate processing metrics. @@ -798,6 +795,14 @@ class CartesiaHttpTTSService(TTSService): """ await super().start(frame) self._settings.output_sample_rate = self.sample_rate + if self._owns_session: + self._session = aiohttp.ClientSession() + + async def _close_session(self): + """Close the HTTP session if we own it.""" + if self._owns_session and self._session: + await self._session.close() + self._session = None async def stop(self, frame: EndFrame): """Stop the Cartesia HTTP TTS service. @@ -806,7 +811,7 @@ class CartesiaHttpTTSService(TTSService): frame: The end frame. """ await super().stop(frame) - await self._client.close() + await self._close_session() async def cancel(self, frame: CancelFrame): """Cancel the Cartesia HTTP TTS service. @@ -815,7 +820,7 @@ class CartesiaHttpTTSService(TTSService): frame: The cancel frame. """ await super().cancel(frame) - await self._client.close() + await self._close_session() @traced_tts async def run_tts(self, text: str, context_id: str) -> AsyncGenerator[Frame, None]: @@ -874,8 +879,6 @@ class CartesiaHttpTTSService(TTSService): yield TTSStartedFrame(context_id=context_id) - session = await self._client._get_session() - headers = { "Cartesia-Version": self._cartesia_version, "X-API-Key": self._api_key, @@ -884,7 +887,7 @@ class CartesiaHttpTTSService(TTSService): url = f"{self._base_url}/tts/bytes" - async with session.post(url, json=payload, headers=headers) as response: + async with self._session.post(url, json=payload, headers=headers) as response: if response.status != 200: error_text = await response.text() yield ErrorFrame(error=f"Cartesia API error: {error_text}") diff --git a/src/pipecat/services/fal/image.py b/src/pipecat/services/fal/image.py index c16d31b43..3de48a984 100644 --- a/src/pipecat/services/fal/image.py +++ b/src/pipecat/services/fal/image.py @@ -25,13 +25,6 @@ from pipecat.frames.frames import ErrorFrame, Frame, URLImageRawFrame from pipecat.services.image_service import ImageGenService from pipecat.services.settings import ImageGenSettings -try: - import fal_client -except ModuleNotFoundError as e: - logger.error(f"Exception: {e}") - logger.error("In order to use Fal, you need to `pip install pipecat-ai[fal]`.") - raise Exception(f"Missing module: {e}") - @dataclass class FalImageGenSettings(ImageGenSettings): @@ -91,6 +84,7 @@ class FalImageGenService(ImageGenService): super().__init__(settings=FalImageGenSettings(model=model), **kwargs) self._params = params self._aiohttp_session = aiohttp_session + self._api_key = key or os.getenv("FAL_KEY", "") if key: os.environ["FAL_KEY"] = key @@ -112,10 +106,22 @@ class FalImageGenService(ImageGenService): logger.debug(f"Generating image from prompt: {prompt}") - response = await fal_client.run_async( - self._settings.model, - arguments={"prompt": prompt, **self._params.model_dump(exclude_none=True)}, - ) + headers = { + "Authorization": f"Key {self._api_key}", + "Content-Type": "application/json", + } + payload = {"prompt": prompt, **self._params.model_dump(exclude_none=True)} + + async with self._aiohttp_session.post( + f"https://fal.run/{self._settings.model}", + json=payload, + headers=headers, + ) as resp: + if resp.status != 200: + error_text = await resp.text() + yield ErrorFrame(error=f"Fal API error ({resp.status}): {error_text}") + return + response = await resp.json() image_url = response["images"][0]["url"] if response else None diff --git a/src/pipecat/services/fal/stt.py b/src/pipecat/services/fal/stt.py index bf70c1c2a..8a82904d7 100644 --- a/src/pipecat/services/fal/stt.py +++ b/src/pipecat/services/fal/stt.py @@ -10,10 +10,12 @@ This module provides integration with Fal's Wizper API for speech-to-text transcription using segmented audio processing. """ +import base64 import os from dataclasses import dataclass, field -from typing import Any, AsyncGenerator, Optional +from typing import AsyncGenerator, Optional +import aiohttp from loguru import logger from pydantic import BaseModel @@ -25,15 +27,6 @@ from pipecat.transcriptions.language import Language, resolve_language from pipecat.utils.time import time_now_iso8601 from pipecat.utils.tracing.service_decorators import traced_stt -try: - import fal_client -except ModuleNotFoundError as e: - logger.error(f"Exception: {e}") - logger.error( - "In order to use Fal, you need to `pip install pipecat-ai[fal]`. Also, set `FAL_KEY` environment variable." - ) - raise Exception(f"Missing module: {e}") - def language_to_fal_language(language: Language) -> Optional[str]: """Convert a Language enum to Fal's Wizper language code. @@ -192,6 +185,7 @@ class FalSTTService(SegmentedSTTService): self, *, api_key: Optional[str] = None, + aiohttp_session: Optional[aiohttp.ClientSession] = None, sample_rate: Optional[int] = None, params: Optional[InputParams] = None, ttfs_p99_latency: Optional[float] = FAL_TTFS_P99, @@ -201,6 +195,8 @@ class FalSTTService(SegmentedSTTService): Args: api_key: Fal API key. If not provided, will check FAL_KEY environment variable. + aiohttp_session: Optional aiohttp ClientSession for HTTP requests. + If not provided, a session will be created and managed internally. sample_rate: Audio sample rate in Hz. If not provided, uses the pipeline's rate. params: Configuration parameters for the Wizper API. ttfs_p99_latency: P99 latency from speech end to final transcript in seconds. @@ -224,14 +220,14 @@ class FalSTTService(SegmentedSTTService): **kwargs, ) - if api_key: - os.environ["FAL_KEY"] = api_key - elif "FAL_KEY" not in os.environ: + self._api_key = api_key or os.getenv("FAL_KEY", "") + if not self._api_key: raise ValueError( "FAL_KEY must be provided either through api_key parameter or environment variable" ) - self._fal_client = fal_client.AsyncClient(key=api_key or os.getenv("FAL_KEY")) + self._session: aiohttp.ClientSession | None = aiohttp_session + self._owns_session = aiohttp_session is None def can_generate_metrics(self) -> bool: """Check if the service can generate processing metrics. @@ -275,12 +271,26 @@ class FalSTTService(SegmentedSTTService): try: await self.start_processing_metrics() - # Send to Fal directly (audio is already in WAV format from base class) - data_uri = fal_client.encode(audio, "audio/x-wav") - response = await self._fal_client.run( - "fal-ai/wizper", - arguments={"audio_url": data_uri, **self._settings.given_fields()}, - ) + if not self._session: + self._session = aiohttp.ClientSession() + + data_uri = f"data:audio/x-wav;base64,{base64.b64encode(audio).decode()}" + payload = {"audio_url": data_uri, **self._settings.given_fields()} + headers = { + "Authorization": f"Key {self._api_key}", + "Content-Type": "application/json", + } + + async with self._session.post( + "https://fal.run/fal-ai/wizper", + json=payload, + headers=headers, + ) as resp: + if resp.status != 200: + error_text = await resp.text() + yield ErrorFrame(error=f"Fal API error ({resp.status}): {error_text}") + return + response = await resp.json() if response and "text" in response: text = response["text"].strip() diff --git a/uv.lock b/uv.lock index db8f68ade..46a8a9a50 100644 --- a/uv.lock +++ b/uv.lock @@ -490,30 +490,30 @@ wheels = [ [[package]] name = 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This parameter allows users to align AssemblyAI's VAD threshold with their external VAD systems (e.g., Silero VAD) to avoid the "dead zone" where AssemblyAI transcribes speech that the external VAD hasn't detected yet, which can delay interruption handling. - Range: 0.0 to 1.0 (lower = more sensitive) - Default: 0.3 (API default when not sent) - Only applicable to u3-rt-pro model - Automatically included in WebSocket query parameters Recommended usage: Set vad_threshold to match your VAD's activation threshold (e.g., both at 0.3) for optimal performance. --- src/pipecat/services/assemblyai/models.py | 17 ++++++++++++----- 1 file changed, 12 insertions(+), 5 deletions(-) diff --git a/src/pipecat/services/assemblyai/models.py b/src/pipecat/services/assemblyai/models.py index 3a022dce1..2c6b3a1dc 100644 --- a/src/pipecat/services/assemblyai/models.py +++ b/src/pipecat/services/assemblyai/models.py @@ -127,8 +127,6 @@ class AssemblyAIConnectionParams(BaseModel): Parameters: sample_rate: Audio sample rate in Hz. Defaults to 16000. encoding: Audio encoding format. Defaults to "pcm_s16le". - formatted_finals: Whether to enable transcript formatting. Defaults to True. - word_finalization_max_wait_time: Maximum time to wait for word finalization in milliseconds. end_of_turn_confidence_threshold: Confidence threshold for end-of-turn detection. min_turn_silence: Minimum silence duration when confident about end-of-turn. min_end_of_turn_silence_when_confident: DEPRECATED. Use min_turn_silence instead. @@ -139,16 +137,24 @@ class AssemblyAIConnectionParams(BaseModel): language_detection: Enable automatic language detection. Only applicable to universal-streaming-multilingual. When enabled, Turn messages include language_code and language_confidence fields. Defaults to None (not sent). - format_turns: Whether to format transcript turns. Defaults to True. + format_turns: Whether to format transcript turns. Only applicable to + universal-streaming-english and universal-streaming-multilingual models. + For u3-rt-pro, formatting is automatic and built-in. Defaults to True. speaker_labels: Enable speaker diarization. When enabled, final transcripts (end_of_turn=True) include a speaker field identifying the speaker (e.g., "Speaker A", "Speaker B"). Defaults to None (not sent). + vad_threshold: Voice activity detection confidence threshold. Only applicable to + u3-rt-pro. The confidence threshold (0.0 to 1.0) for classifying audio frames + as silence. Frames with VAD confidence below this value are considered silent. + Increase for noisy environments to reduce false speech detection. Defaults to + 0.3 (API default). For best performance when using with external VAD (e.g., Silero), + align this value with your VAD's activation threshold to avoid the "dead zone" + where AssemblyAI transcribes speech that your VAD hasn't detected yet. + Defaults to None (not sent). """ sample_rate: int = 16000 encoding: Literal["pcm_s16le", "pcm_mulaw"] = "pcm_s16le" - formatted_finals: bool = True - word_finalization_max_wait_time: Optional[int] = None end_of_turn_confidence_threshold: Optional[float] = None min_turn_silence: Optional[int] = None min_end_of_turn_silence_when_confident: Optional[int] = None # Deprecated @@ -161,6 +167,7 @@ class AssemblyAIConnectionParams(BaseModel): language_detection: Optional[bool] = None format_turns: bool = True speaker_labels: Optional[bool] = None + vad_threshold: Optional[float] = None @model_validator(mode="after") def handle_deprecated_param(self): From 11024ccc2c91eb57fba382d8b3a9880ee78c504c Mon Sep 17 00:00:00 2001 From: zack Date: Thu, 5 Mar 2026 15:32:09 -0500 Subject: [PATCH 0796/1060] Add changelog entries for vad_threshold and parameter cleanup --- changelog/3927.added.md | 1 + changelog/3927.changed.md | 1 + 2 files changed, 2 insertions(+) create mode 100644 changelog/3927.added.md create mode 100644 changelog/3927.changed.md diff --git a/changelog/3927.added.md b/changelog/3927.added.md new file mode 100644 index 000000000..378815fc3 --- /dev/null +++ b/changelog/3927.added.md @@ -0,0 +1 @@ +- Added `vad_threshold` parameter to `AssemblyAIConnectionParams` for configuring voice activity detection sensitivity in U3 Pro. Aligning this with external VAD thresholds (e.g., Silero VAD) prevents the "dead zone" where AssemblyAI transcribes speech that VAD hasn't detected yet. diff --git a/changelog/3927.changed.md b/changelog/3927.changed.md new file mode 100644 index 000000000..b397e86a2 --- /dev/null +++ b/changelog/3927.changed.md @@ -0,0 +1 @@ +- ⚠️ Removed `formatted_finals` and `word_finalization_max_wait_time` from `AssemblyAIConnectionParams` as these were v2 API parameters not supported in v3. Clarified that `format_turns` only applies to Universal-Streaming models; U3 Pro has automatic formatting built-in. From 380726cfd3202287a49277107fddd8ec67b14e81 Mon Sep 17 00:00:00 2001 From: zack Date: Thu, 5 Mar 2026 15:47:54 -0500 Subject: [PATCH 0797/1060] Update AssemblyAI turn detection example to use keyterms_prompt Change the commented example from prompt string format to keyterms_prompt list format for better clarity and consistency with API best practices. --- changelog/3929.other.md | 1 + .../foundational/07o-interruptible-assemblyai-turn-detection.py | 2 +- 2 files changed, 2 insertions(+), 1 deletion(-) create mode 100644 changelog/3929.other.md diff --git a/changelog/3929.other.md b/changelog/3929.other.md new file mode 100644 index 000000000..c1d9f8dda --- /dev/null +++ b/changelog/3929.other.md @@ -0,0 +1 @@ +- Updated AssemblyAI turn detection example to use `keyterms_prompt` list format instead of `prompt` string for improved clarity. diff --git a/examples/foundational/07o-interruptible-assemblyai-turn-detection.py b/examples/foundational/07o-interruptible-assemblyai-turn-detection.py index 13f596136..7a0226277 100644 --- a/examples/foundational/07o-interruptible-assemblyai-turn-detection.py +++ b/examples/foundational/07o-interruptible-assemblyai-turn-detection.py @@ -100,7 +100,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): # min_turn_silence=100, # Default # max_turn_silence=1000, # Default # Optional: Boost accuracy for specific names/terms - # prompt="Names: Xiomara, Saoirse, Krzystof. Technical terms: API, OAuth.", + # keyterms_prompt=["Xiomara", "Saoirse", "Krzystof", "API", "OAuth"], # Optional: Enable speaker diarization # speaker_labels=True, ), From f4b824524106a69c7363ff618aabf87d8ccd2ae2 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Aleix=20Conchillo=20Flaqu=C3=A9?= Date: Thu, 5 Mar 2026 14:55:31 -0800 Subject: [PATCH 0798/1060] Warn when both system_instruction and context system message are set system_instruction from the constructor always takes precedence. A warning is now logged when the context also contains a system message so users can spot the conflict. --- src/pipecat/services/anthropic/llm.py | 5 +++++ src/pipecat/services/aws/llm.py | 5 +++++ src/pipecat/services/openai/base_llm.py | 7 ++++++- 3 files changed, 16 insertions(+), 1 deletion(-) diff --git a/src/pipecat/services/anthropic/llm.py b/src/pipecat/services/anthropic/llm.py index 755ca6400..5981d3e50 100644 --- a/src/pipecat/services/anthropic/llm.py +++ b/src/pipecat/services/anthropic/llm.py @@ -403,6 +403,11 @@ class AnthropicLLMService(LLMService): context, enable_prompt_caching=self._settings.enable_prompt_caching ) if self._system_instruction: + if params["system"] is not NOT_GIVEN: + logger.warning( + f"{self}: Both system_instruction and a system message in context are" + " set. Using system_instruction." + ) params["system"] = self._system_instruction return params diff --git a/src/pipecat/services/aws/llm.py b/src/pipecat/services/aws/llm.py index 31f8085bc..e465ae460 100644 --- a/src/pipecat/services/aws/llm.py +++ b/src/pipecat/services/aws/llm.py @@ -1025,6 +1025,11 @@ class AWSBedrockLLMService(LLMService): adapter: AWSBedrockLLMAdapter = self.get_llm_adapter() params: AWSBedrockLLMInvocationParams = adapter.get_llm_invocation_params(context) if self._system_instruction: + if params["system"]: + logger.warning( + f"{self}: Both system_instruction and a system message in context are" + " set. Using system_instruction." + ) params["system"] = [{"text": self._system_instruction}] return params diff --git a/src/pipecat/services/openai/base_llm.py b/src/pipecat/services/openai/base_llm.py index ed012d0df..dfef1ae90 100644 --- a/src/pipecat/services/openai/base_llm.py +++ b/src/pipecat/services/openai/base_llm.py @@ -292,9 +292,14 @@ class BaseOpenAILLMService(LLMService): params.update(self._settings.extra) - # Prepend system instruction if set + # Prepend system instruction from constructor, replacing any context system message if self._system_instruction: messages = params.get("messages", []) + if messages and messages[0].get("role") == "system": + logger.warning( + f"{self}: Both system_instruction and a system message in context are set." + " Using system_instruction." + ) params["messages"] = [ {"role": "system", "content": self._system_instruction} ] + messages From 789ce2fd5eabd6f361c9ccd3b6679e62a6bc975d Mon Sep 17 00:00:00 2001 From: Daksh Dua Date: Thu, 5 Mar 2026 14:25:31 -0800 Subject: [PATCH 0799/1060] Add param to push empty transcripts --- changelog/3930.added.md | 1 + src/pipecat/services/whisper/base_stt.py | 15 ++++++++++++--- 2 files changed, 13 insertions(+), 3 deletions(-) create mode 100644 changelog/3930.added.md diff --git a/changelog/3930.added.md b/changelog/3930.added.md new file mode 100644 index 000000000..dd799f9ec --- /dev/null +++ b/changelog/3930.added.md @@ -0,0 +1 @@ +- Added `push_empty_transcripts` parameter to `BaseWhisperSTTService` and `OpenAISTTService` to allow empty transcripts to be pushed downstream as `TranscriptionFrame` instead of discarding them (the default behavior). This is intended for situations where VAD fires even though the user did not speak. In these cases, it is useful to know that nothing was transcribed so that the agent can resume speaking, instead of waiting longer for a transcription. \ No newline at end of file diff --git a/src/pipecat/services/whisper/base_stt.py b/src/pipecat/services/whisper/base_stt.py index cf3342f4b..08310831c 100644 --- a/src/pipecat/services/whisper/base_stt.py +++ b/src/pipecat/services/whisper/base_stt.py @@ -136,6 +136,7 @@ class BaseWhisperSTTService(SegmentedSTTService): prompt: Optional[str] = None, temperature: Optional[float] = None, include_prob_metrics: bool = False, + push_empty_transcripts: bool = False, ttfs_p99_latency: Optional[float] = WHISPER_TTFS_P99, **kwargs, ): @@ -151,6 +152,12 @@ class BaseWhisperSTTService(SegmentedSTTService): include_prob_metrics: If True, enables probability metrics in API response. Each service implements this differently (see child classes). Defaults to False. + push_empty_transcripts: - If true, allow empty `TranscriptionFrame` frames to be + pushed downstream instead of discarding them. This is intended for situations + where VAD fires even though the user did not speak. In these cases, it is + useful to know that nothing was transcribed so that the agent can resume + speaking, instead of waiting longer for a transcription. + Defaults to False. ttfs_p99_latency: P99 latency from speech end to final transcript in seconds. Override for your deployment. See https://github.com/pipecat-ai/stt-benchmark **kwargs: Additional arguments passed to SegmentedSTTService. @@ -171,6 +178,7 @@ class BaseWhisperSTTService(SegmentedSTTService): self._prompt = prompt self._temperature = temperature self._include_prob_metrics = include_prob_metrics + self._push_empty_transcripts = push_empty_transcripts def _create_client(self, api_key: Optional[str], base_url: Optional[str]): return AsyncOpenAI(api_key=api_key, base_url=base_url) @@ -237,7 +245,10 @@ class BaseWhisperSTTService(SegmentedSTTService): text = response.text.strip() - if text: + if not text: + logger.warning("Received empty transcription from API") + + if text or self._push_empty_transcripts: await self._handle_transcription(text, True, self._language) logger.debug(f"Transcription: [{text}]") yield TranscriptionFrame( @@ -246,8 +257,6 @@ class BaseWhisperSTTService(SegmentedSTTService): time_now_iso8601(), result=response, ) - else: - logger.warning("Received empty transcription from API") except Exception as e: yield ErrorFrame(error=f"Unknown error occurred: {e}") From fda4cb6732587db938f9870c6c073603ef4b6a95 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Aleix=20Conchillo=20Flaqu=C3=A9?= Date: Thu, 5 Mar 2026 16:16:41 -0800 Subject: [PATCH 0800/1060] Add changelog for #3932 --- changelog/3932.added.md | 1 + 1 file changed, 1 insertion(+) create mode 100644 changelog/3932.added.md diff --git a/changelog/3932.added.md b/changelog/3932.added.md new file mode 100644 index 000000000..e97690d44 --- /dev/null +++ b/changelog/3932.added.md @@ -0,0 +1 @@ +- LLM services (`BaseOpenAILLMService`, `AnthropicLLMService`, `AWSBedrockLLMService`) now log a warning when both `system_instruction` and a system message in the context are set. The constructor's `system_instruction` takes precedence. 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Fix deepgram LiveOptions import in eval script. --- scripts/evals/eval.py | 3 +-- src/pipecat/transports/daily/transport.py | 2 +- 2 files changed, 2 insertions(+), 3 deletions(-) diff --git a/scripts/evals/eval.py b/scripts/evals/eval.py index 91971aee7..16d205825 100644 --- a/scripts/evals/eval.py +++ b/scripts/evals/eval.py @@ -16,7 +16,6 @@ from pathlib import Path from typing import Any, List, Optional, Tuple import aiofiles -from deepgram import LiveOptions from loguru import logger from PIL.ImageFile import ImageFile from utils import ( @@ -50,7 +49,7 @@ from pipecat.processors.audio.audio_buffer_processor import AudioBufferProcessor from pipecat.processors.frame_processor import FrameDirection from pipecat.runner.types import RunnerArguments from pipecat.services.cartesia.tts import CartesiaTTSService -from pipecat.services.deepgram.stt import DeepgramSTTService +from pipecat.services.deepgram.stt import DeepgramSTTService, LiveOptions from pipecat.services.llm_service import FunctionCallParams from pipecat.services.openai.llm import OpenAILLMService from pipecat.transports.daily.transport import DailyParams, DailyTransport diff --git a/src/pipecat/transports/daily/transport.py b/src/pipecat/transports/daily/transport.py index 87b46c113..421e5db8e 100644 --- a/src/pipecat/transports/daily/transport.py +++ b/src/pipecat/transports/daily/transport.py @@ -2747,7 +2747,7 @@ class DailyTransport(BaseTransport): async def _on_participant_updated(self, participant): """Handle participant updated events.""" - logger.debug(f"{self} participant updated: {participant}") + logger.trace(f"{self} participant updated: {participant}") await self._call_event_handler("on_participant_updated", participant) async def _on_transcription_message(self, message: Mapping[str, Any]) -> None: From 3199168d3ec65f9ee93e4e09cb284bac8f39a99b Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Aleix=20Conchillo=20Flaqu=C3=A9?= Date: Thu, 5 Mar 2026 19:14:06 -0800 Subject: [PATCH 0803/1060] scripts(evals): use context.add_message() --- scripts/evals/eval.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/scripts/evals/eval.py b/scripts/evals/eval.py index 16d205825..8084bc3a1 100644 --- a/scripts/evals/eval.py +++ b/scripts/evals/eval.py @@ -361,7 +361,7 @@ async def run_eval_pipeline( # Default behavior is for the bot to speak first # If the eval bot speaks first, we append the prompt to the messages if eval_config.eval_speaks_first: - messages.append( + context.add_message( {"role": "user", "content": f"Start by saying this exactly: '{eval_config.prompt}'"} ) await task.queue_frames([LLMRunFrame()]) From 5dc312ce0c76f503716f05dcdf845a6183a4a917 Mon Sep 17 00:00:00 2001 From: Paul Kompfner Date: Fri, 27 Feb 2026 21:46:03 -0500 Subject: [PATCH 0804/1060] Add `settings` as canonical init arg for all AIService descendants, deprecate redundant `model`/`voice`/`params` args ServiceSettings types were introduced for runtime updates via ServiceUpdateSettingsFrame, but there was tension between init-time and runtime APIs: overlapping-but-different InputParams vs ServiceSettings classes, and runtime-updatable fields like `model` and `voice` scattered as direct init args rather than living in a settings object. This unifies them so developers use the same settings type at both init and runtime, improving ergonomics and consistency. Every concrete AIService subclass (LLM, TTS, STT, ImageGen, Vision, Video) now accepts a `settings` parameter for runtime-updatable config. Old init args (`model`, `voice_id`, `params`/`InputParams`) still work but emit DeprecationWarnings pointing to the new API. When both are provided, `settings` takes precedence. Leaf classes emit warnings; base classes do not, avoiding double warnings in inheritance chains. --- src/pipecat/services/anthropic/llm.py | 87 ++++--- src/pipecat/services/assemblyai/stt.py | 17 +- src/pipecat/services/asyncai/tts.py | 112 ++++++--- src/pipecat/services/aws/llm.py | 72 ++++-- src/pipecat/services/aws/nova_sonic/llm.py | 74 ++++-- src/pipecat/services/aws/stt.py | 53 +++-- src/pipecat/services/aws/tts.py | 53 +++-- src/pipecat/services/azure/image.py | 22 +- src/pipecat/services/azure/llm.py | 24 +- src/pipecat/services/azure/stt.py | 33 ++- src/pipecat/services/azure/tts.py | 117 ++++++--- src/pipecat/services/camb/tts.py | 63 +++-- src/pipecat/services/cartesia/stt.py | 17 +- src/pipecat/services/cartesia/tts.py | 122 +++++++--- src/pipecat/services/cerebras/llm.py | 22 +- src/pipecat/services/deepgram/flux/stt.py | 72 +++--- .../services/deepgram/sagemaker/stt.py | 42 ++-- .../services/deepgram/sagemaker/tts.py | 32 ++- src/pipecat/services/deepgram/stt.py | 15 +- src/pipecat/services/deepgram/tts.py | 62 +++-- src/pipecat/services/deepseek/llm.py | 22 +- src/pipecat/services/elevenlabs/stt.py | 98 ++++++-- src/pipecat/services/elevenlabs/tts.py | 150 +++++++++--- src/pipecat/services/fal/image.py | 20 +- src/pipecat/services/fal/stt.py | 39 ++- src/pipecat/services/fireworks/llm.py | 24 +- src/pipecat/services/fish/tts.py | 68 ++++-- src/pipecat/services/gladia/stt.py | 56 +++-- .../services/google/gemini_live/llm.py | 88 ++++--- .../services/google/gemini_live/llm_vertex.py | 59 ++++- src/pipecat/services/google/image.py | 21 +- src/pipecat/services/google/llm.py | 69 ++++-- src/pipecat/services/google/llm_openai.py | 21 +- src/pipecat/services/google/llm_vertex.py | 44 +++- src/pipecat/services/google/stt.py | 51 ++-- src/pipecat/services/google/tts.py | 163 +++++++++---- src/pipecat/services/gradium/stt.py | 31 ++- src/pipecat/services/gradium/tts.py | 47 +++- src/pipecat/services/grok/llm.py | 21 +- src/pipecat/services/grok/realtime/llm.py | 45 ++-- src/pipecat/services/groq/llm.py | 22 +- src/pipecat/services/groq/stt.py | 63 ++++- src/pipecat/services/groq/tts.py | 57 +++-- src/pipecat/services/heygen/video.py | 10 +- src/pipecat/services/hume/tts.py | 45 +++- src/pipecat/services/inworld/tts.py | 128 +++++++--- src/pipecat/services/kokoro/tts.py | 43 +++- src/pipecat/services/lmnt/tts.py | 40 +++- src/pipecat/services/minimax/tts.py | 123 ++++++---- src/pipecat/services/mistral/llm.py | 22 +- src/pipecat/services/moondream/vision.py | 27 ++- src/pipecat/services/neuphonic/tts.py | 84 +++++-- src/pipecat/services/nvidia/llm.py | 27 ++- src/pipecat/services/nvidia/stt.py | 68 ++++-- src/pipecat/services/nvidia/tts.py | 43 +++- src/pipecat/services/ollama/llm.py | 26 +- src/pipecat/services/openai/base_llm.py | 54 +++-- src/pipecat/services/openai/image.py | 20 +- src/pipecat/services/openai/llm.py | 42 +++- src/pipecat/services/openai/realtime/llm.py | 56 +++-- src/pipecat/services/openai/stt.py | 54 ++++- src/pipecat/services/openai/tts.py | 79 +++++-- .../services/openai_realtime_beta/openai.py | 57 +++-- src/pipecat/services/openpipe/llm.py | 20 +- src/pipecat/services/openrouter/llm.py | 20 +- src/pipecat/services/perplexity/llm.py | 22 +- src/pipecat/services/piper/tts.py | 47 +++- src/pipecat/services/qwen/llm.py | 24 +- src/pipecat/services/resembleai/tts.py | 34 ++- src/pipecat/services/rime/tts.py | 222 ++++++++++++------ src/pipecat/services/sambanova/llm.py | 20 +- src/pipecat/services/sambanova/stt.py | 63 ++++- src/pipecat/services/sarvam/stt.py | 67 ++++-- src/pipecat/services/sarvam/tts.py | 174 +++++++++----- src/pipecat/services/settings.py | 40 ++++ src/pipecat/services/soniox/stt.py | 53 +++-- src/pipecat/services/speechmatics/stt.py | 25 +- src/pipecat/services/speechmatics/tts.py | 43 +++- src/pipecat/services/tavus/video.py | 10 +- src/pipecat/services/together/llm.py | 24 +- src/pipecat/services/ultravox/llm.py | 34 +-- src/pipecat/services/whisper/base_stt.py | 64 +++-- src/pipecat/services/whisper/stt.py | 139 ++++++++--- src/pipecat/services/xtts/tts.py | 30 ++- 84 files changed, 3431 insertions(+), 1182 deletions(-) diff --git a/src/pipecat/services/anthropic/llm.py b/src/pipecat/services/anthropic/llm.py index 5981d3e50..d2a4c300d 100644 --- a/src/pipecat/services/anthropic/llm.py +++ b/src/pipecat/services/anthropic/llm.py @@ -58,7 +58,7 @@ from pipecat.processors.aggregators.openai_llm_context import ( from pipecat.processors.frame_processor import FrameDirection from pipecat.services.llm_service import FunctionCallFromLLM, LLMService from pipecat.services.settings import NOT_GIVEN as _NOT_GIVEN -from pipecat.services.settings import LLMSettings, _NotGiven, is_given +from pipecat.services.settings import LLMSettings, _NotGiven, _warn_deprecated_param, is_given from pipecat.utils.tracing.service_decorators import traced_llm try: @@ -170,6 +170,10 @@ class AnthropicLLMService(LLMService): class InputParams(BaseModel): """Input parameters for Anthropic model inference. + .. deprecated:: + Use ``AnthropicLLMSettings`` instead. Pass settings directly via the + ``settings`` parameter of :class:`AnthropicLLMService`. + Parameters: enable_prompt_caching: Whether to enable the prompt caching feature. enable_prompt_caching_beta (deprecated): Whether to enable the beta prompt caching feature. @@ -213,8 +217,9 @@ class AnthropicLLMService(LLMService): self, *, api_key: str, - model: str = "claude-sonnet-4-6", + model: Optional[str] = None, params: Optional[InputParams] = None, + settings: Optional[AnthropicLLMSettings] = None, client=None, retry_timeout_secs: Optional[float] = 5.0, retry_on_timeout: Optional[bool] = False, @@ -225,42 +230,66 @@ class AnthropicLLMService(LLMService): Args: api_key: Anthropic API key for authentication. - model: Model name to use. Defaults to "claude-sonnet-4-6". + model: Model name to use. + + .. deprecated:: + Use ``settings=AnthropicLLMSettings(model=...)`` instead. + params: Optional model parameters for inference. + + .. deprecated:: + Use ``settings=AnthropicLLMSettings(...)`` instead. + + settings: Runtime-updatable settings for this service. When both + deprecated parameters and *settings* are provided, *settings* + values take precedence. client: Optional custom Anthropic client instance. retry_timeout_secs: Request timeout in seconds for retry logic. retry_on_timeout: Whether to retry the request once if it times out. system_instruction: Optional system instruction to use as the system prompt. **kwargs: Additional arguments passed to parent LLMService. """ - params = params or AnthropicLLMService.InputParams() + if model is not None: + _warn_deprecated_param("model", "AnthropicLLMSettings", "model") + if params is not None: + _warn_deprecated_param("params", "AnthropicLLMSettings") - super().__init__( - settings=AnthropicLLMSettings( - model=model, - max_tokens=params.max_tokens, - enable_prompt_caching=( - params.enable_prompt_caching - if params.enable_prompt_caching is not None - else ( - params.enable_prompt_caching_beta - if params.enable_prompt_caching_beta is not None - else False - ) - ), - temperature=params.temperature, - top_k=params.top_k, - top_p=params.top_p, - frequency_penalty=None, - presence_penalty=None, - seed=None, - filter_incomplete_user_turns=False, - user_turn_completion_config=None, - thinking=params.thinking, - extra=params.extra if isinstance(params.extra, dict) else {}, - ), - **kwargs, + _params = params or AnthropicLLMService.InputParams() + + # Handle existing enable_prompt_caching_beta deprecation + enable_prompt_caching = _params.enable_prompt_caching + if _params.enable_prompt_caching_beta is not None: + import warnings + + with warnings.catch_warnings(): + warnings.simplefilter("always") + warnings.warn( + "enable_prompt_caching_beta is deprecated. Use enable_prompt_caching instead.", + DeprecationWarning, + stacklevel=2, + ) + if enable_prompt_caching is None: + enable_prompt_caching = _params.enable_prompt_caching_beta + + default_settings = AnthropicLLMSettings( + model=model or "claude-sonnet-4-6", + max_tokens=_params.max_tokens, + enable_prompt_caching=enable_prompt_caching or False, + temperature=_params.temperature, + top_k=_params.top_k, + top_p=_params.top_p, + frequency_penalty=None, + presence_penalty=None, + seed=None, + filter_incomplete_user_turns=False, + user_turn_completion_config=None, + thinking=_params.thinking, + extra=_params.extra if isinstance(_params.extra, dict) else {}, ) + if settings is not None: + default_settings.apply_update(settings) + + super().__init__(settings=default_settings, **kwargs) self._client = client or AsyncAnthropic( api_key=api_key ) # if the client is provided, use it and remove it, otherwise create a new one diff --git a/src/pipecat/services/assemblyai/stt.py b/src/pipecat/services/assemblyai/stt.py index c62ae959b..85d4029b7 100644 --- a/src/pipecat/services/assemblyai/stt.py +++ b/src/pipecat/services/assemblyai/stt.py @@ -114,6 +114,7 @@ class AssemblyAISTTService(WebsocketSTTService): vad_force_turn_endpoint: bool = True, should_interrupt: bool = True, speaker_format: Optional[str] = None, + settings: Optional[AssemblyAISTTSettings] = None, ttfs_p99_latency: Optional[float] = ASSEMBLYAI_TTFS_P99, **kwargs, ): @@ -144,6 +145,8 @@ class AssemblyAISTTService(WebsocketSTTService): Use {speaker} for speaker label and {text} for transcript text. Example: "<{speaker}>{text}" or "{speaker}: {text}" If None, transcript text is not modified. Defaults to None. + settings: Runtime-updatable settings. When provided alongside other + parameters, ``settings`` values take precedence. ttfs_p99_latency: P99 latency from speech end to final transcript in seconds. Override for your deployment. See https://github.com/pipecat-ai/stt-benchmark **kwargs: Additional arguments passed to parent STTService class. @@ -185,14 +188,18 @@ class AssemblyAISTTService(WebsocketSTTService): if vad_force_turn_endpoint: connection_params = self._configure_pipecat_turn_mode(connection_params, is_u3_pro) + default_settings = AssemblyAISTTSettings( + model=None, + language=language, + connection_params=connection_params, + ) + if settings is not None: + default_settings.apply_update(settings) + super().__init__( sample_rate=connection_params.sample_rate, ttfs_p99_latency=ttfs_p99_latency, - settings=AssemblyAISTTSettings( - model=None, - language=language, - connection_params=connection_params, - ), + settings=default_settings, **kwargs, ) diff --git a/src/pipecat/services/asyncai/tts.py b/src/pipecat/services/asyncai/tts.py index 4f1fd5a58..245253ac8 100644 --- a/src/pipecat/services/asyncai/tts.py +++ b/src/pipecat/services/asyncai/tts.py @@ -27,7 +27,7 @@ from pipecat.frames.frames import ( TTSStoppedFrame, ) from pipecat.processors.frame_processor import FrameDirection -from pipecat.services.settings import NOT_GIVEN, TTSSettings, _NotGiven +from pipecat.services.settings import NOT_GIVEN, TTSSettings, _NotGiven, _warn_deprecated_param from pipecat.services.tts_service import AudioContextTTSService, TextAggregationMode, TTSService from pipecat.transcriptions.language import Language, resolve_language from pipecat.utils.tracing.service_decorators import traced_tts @@ -110,6 +110,9 @@ class AsyncAITTSService(AudioContextTTSService): class InputParams(BaseModel): """Input parameters for Async TTS configuration. + .. deprecated:: 1.0 + Use ``AsyncAITTSSettings`` directly via the ``settings`` parameter instead. + Parameters: language: Language to use for synthesis. """ @@ -120,14 +123,15 @@ class AsyncAITTSService(AudioContextTTSService): self, *, api_key: str, - voice_id: str, + voice_id: Optional[str] = None, version: str = "v1", url: str = "wss://api.async.com/text_to_speech/websocket/ws", - model: str = "async_flash_v1.0", + model: Optional[str] = None, sample_rate: Optional[int] = None, encoding: str = "pcm_s16le", container: str = "raw", params: Optional[InputParams] = None, + settings: Optional[AsyncAITTSSettings] = None, aggregate_sentences: Optional[bool] = None, text_aggregation_mode: Optional[TextAggregationMode] = None, **kwargs, @@ -138,13 +142,27 @@ class AsyncAITTSService(AudioContextTTSService): api_key: Async API key. voice_id: UUID of the voice to use for synthesis. See docs for a full list: https://docs.async.com/list-voices-16699698e0 + + .. deprecated:: 1.0 + Use ``settings=AsyncAITTSSettings(voice=...)`` instead. + version: Async API version. url: WebSocket URL for Async TTS API. model: TTS model to use (e.g., "async_flash_v1.0"). + + .. deprecated:: 1.0 + Use ``settings=AsyncAITTSSettings(model=...)`` instead. + sample_rate: Audio sample rate. encoding: Audio encoding format. container: Audio container format. params: Additional input parameters for voice customization. + + .. deprecated:: 1.0 + Use ``settings=AsyncAITTSSettings(...)`` instead. + + settings: Runtime-updatable settings. When provided alongside deprecated + parameters, ``settings`` values take precedence. aggregate_sentences: Deprecated. Use text_aggregation_mode instead. .. deprecated:: 0.0.104 @@ -153,7 +171,27 @@ class AsyncAITTSService(AudioContextTTSService): text_aggregation_mode: How to aggregate text before synthesis. **kwargs: Additional arguments passed to the parent service. """ - params = params or AsyncAITTSService.InputParams() + if voice_id is not None: + _warn_deprecated_param("voice_id", "AsyncAITTSSettings", "voice") + if model is not None: + _warn_deprecated_param("model", "AsyncAITTSSettings", "model") + if params is not None: + _warn_deprecated_param("params", "AsyncAITTSSettings") + + _params = params or AsyncAITTSService.InputParams() + + default_settings = AsyncAITTSSettings( + model=model or "async_flash_v1.0", + voice=voice_id, + output_container=container, + output_encoding=encoding, + output_sample_rate=0, + language=self.language_to_service_language(_params.language) + if _params.language + else None, + ) + if settings is not None: + default_settings.apply_update(settings) super().__init__( aggregate_sentences=aggregate_sentences, @@ -161,16 +199,7 @@ class AsyncAITTSService(AudioContextTTSService): pause_frame_processing=True, push_stop_frames=True, sample_rate=sample_rate, - settings=AsyncAITTSSettings( - model=model, - voice=voice_id, - output_container=container, - output_encoding=encoding, - output_sample_rate=0, - language=self.language_to_service_language(params.language) - if params.language - else None, - ), + settings=default_settings, **kwargs, ) @@ -471,6 +500,9 @@ class AsyncAIHttpTTSService(TTSService): class InputParams(BaseModel): """Input parameters for Async API. + .. deprecated:: 1.0 + Use ``AsyncAITTSSettings`` directly via the ``settings`` parameter instead. + Parameters: language: Language to use for synthesis. """ @@ -481,15 +513,16 @@ class AsyncAIHttpTTSService(TTSService): self, *, api_key: str, - voice_id: str, + voice_id: Optional[str] = None, aiohttp_session: aiohttp.ClientSession, - model: str = "async_flash_v1.0", + model: Optional[str] = None, url: str = "https://api.async.com", version: str = "v1", sample_rate: Optional[int] = None, encoding: str = "pcm_s16le", container: str = "raw", params: Optional[InputParams] = None, + settings: Optional[AsyncAITTSSettings] = None, **kwargs, ): """Initialize the Async TTS service. @@ -497,30 +530,55 @@ class AsyncAIHttpTTSService(TTSService): Args: api_key: Async API key. voice_id: ID of the voice to use for synthesis. + + .. deprecated:: 1.0 + Use ``settings=AsyncAITTSSettings(voice=...)`` instead. + aiohttp_session: An aiohttp session for making HTTP requests. model: TTS model to use (e.g., "async_flash_v1.0"). + + .. deprecated:: 1.0 + Use ``settings=AsyncAITTSSettings(model=...)`` instead. + url: Base URL for Async API. version: API version string for Async API. sample_rate: Audio sample rate. encoding: Audio encoding format. container: Audio container format. params: Additional input parameters for voice customization. + + .. deprecated:: 1.0 + Use ``settings=AsyncAITTSSettings(...)`` instead. + + settings: Runtime-updatable settings. When provided alongside deprecated + parameters, ``settings`` values take precedence. **kwargs: Additional arguments passed to the parent TTSService. """ - params = params or AsyncAIHttpTTSService.InputParams() + if voice_id is not None: + _warn_deprecated_param("voice_id", "AsyncAITTSSettings", "voice") + if model is not None: + _warn_deprecated_param("model", "AsyncAITTSSettings", "model") + if params is not None: + _warn_deprecated_param("params", "AsyncAITTSSettings") + + _params = params or AsyncAIHttpTTSService.InputParams() + + default_settings = AsyncAITTSSettings( + model=model or "async_flash_v1.0", + voice=voice_id, + output_container=container, + output_encoding=encoding, + output_sample_rate=0, + language=self.language_to_service_language(_params.language) + if _params.language + else None, + ) + if settings is not None: + default_settings.apply_update(settings) super().__init__( sample_rate=sample_rate, - settings=AsyncAITTSSettings( - model=model, - voice=voice_id, - output_container=container, - output_encoding=encoding, - output_sample_rate=0, - language=self.language_to_service_language(params.language) - if params.language - else None, - ), + settings=default_settings, **kwargs, ) diff --git a/src/pipecat/services/aws/llm.py b/src/pipecat/services/aws/llm.py index e465ae460..b8a92eccb 100644 --- a/src/pipecat/services/aws/llm.py +++ b/src/pipecat/services/aws/llm.py @@ -55,7 +55,7 @@ from pipecat.processors.aggregators.openai_llm_context import ( ) from pipecat.processors.frame_processor import FrameDirection from pipecat.services.llm_service import LLMService -from pipecat.services.settings import NOT_GIVEN, LLMSettings, _NotGiven +from pipecat.services.settings import NOT_GIVEN, LLMSettings, _NotGiven, _warn_deprecated_param from pipecat.utils.tracing.service_decorators import traced_llm try: @@ -752,6 +752,10 @@ class AWSBedrockLLMService(LLMService): class InputParams(BaseModel): """Input parameters for AWS Bedrock LLM service. + .. deprecated:: + Use ``AWSBedrockLLMSettings`` instead. Pass settings directly via the + ``settings`` parameter of :class:`AWSBedrockLLMService`. + Parameters: max_tokens: Maximum number of tokens to generate. temperature: Sampling temperature between 0.0 and 1.0. @@ -771,12 +775,14 @@ class AWSBedrockLLMService(LLMService): def __init__( self, *, - model: str, + model: Optional[str] = None, aws_access_key: Optional[str] = None, aws_secret_key: Optional[str] = None, aws_session_token: Optional[str] = None, aws_region: Optional[str] = None, params: Optional[InputParams] = None, + settings: Optional[AWSBedrockLLMSettings] = None, + stop_sequences: Optional[List[str]] = None, client_config: Optional[Config] = None, retry_timeout_secs: Optional[float] = 5.0, retry_on_timeout: Optional[bool] = False, @@ -787,37 +793,59 @@ class AWSBedrockLLMService(LLMService): Args: model: The AWS Bedrock model identifier to use. + + .. deprecated:: + Use ``settings=AWSBedrockLLMSettings(model=...)`` instead. + aws_access_key: AWS access key ID. If None, uses default credentials. aws_secret_key: AWS secret access key. If None, uses default credentials. aws_session_token: AWS session token for temporary credentials. aws_region: AWS region for the Bedrock service. params: Model parameters and configuration. + + .. deprecated:: + Use ``settings=AWSBedrockLLMSettings(...)`` instead. + + settings: Runtime-updatable settings for this service. When both + deprecated parameters and *settings* are provided, *settings* + values take precedence. + stop_sequences: List of strings that stop generation. client_config: Custom boto3 client configuration. retry_timeout_secs: Request timeout in seconds for retry logic. retry_on_timeout: Whether to retry the request once if it times out. system_instruction: Optional system instruction to use as the system prompt. **kwargs: Additional arguments passed to parent LLMService. """ - params = params or AWSBedrockLLMService.InputParams() + if model is not None: + _warn_deprecated_param("model", "AWSBedrockLLMSettings", "model") + if params is not None: + _warn_deprecated_param("params", "AWSBedrockLLMSettings") - super().__init__( - settings=AWSBedrockLLMSettings( - model=model, - max_tokens=params.max_tokens, - temperature=params.temperature, - top_p=params.top_p, - top_k=None, - frequency_penalty=None, - presence_penalty=None, - seed=None, - filter_incomplete_user_turns=False, - user_turn_completion_config=None, - latency=params.latency, - additional_model_request_fields=params.additional_model_request_fields - if isinstance(params.additional_model_request_fields, dict) - else {}, - ), - **kwargs, + _params = params or AWSBedrockLLMService.InputParams() + + default_settings = AWSBedrockLLMSettings( + model=model or "us.amazon.nova-lite-v1:0", + max_tokens=_params.max_tokens, + temperature=_params.temperature, + top_p=_params.top_p, + top_k=None, + frequency_penalty=None, + presence_penalty=None, + seed=None, + filter_incomplete_user_turns=False, + user_turn_completion_config=None, + latency=_params.latency, + additional_model_request_fields=_params.additional_model_request_fields + if isinstance(_params.additional_model_request_fields, dict) + else {}, + ) + if settings is not None: + default_settings.apply_update(settings) + + super().__init__(settings=default_settings, **kwargs) + + self._stop_sequences = ( + stop_sequences if stop_sequences is not None else (_params.stop_sequences or []) ) # Initialize the AWS Bedrock client @@ -843,7 +871,7 @@ class AWSBedrockLLMService(LLMService): self._retry_on_timeout = retry_on_timeout self._system_instruction = system_instruction - logger.info(f"Using AWS Bedrock model: {model}") + logger.info(f"Using AWS Bedrock model: {self._settings.model}") if self._system_instruction: logger.debug(f"{self}: Using system instruction: {self._system_instruction}") diff --git a/src/pipecat/services/aws/nova_sonic/llm.py b/src/pipecat/services/aws/nova_sonic/llm.py index 29612e593..887c3f46c 100644 --- a/src/pipecat/services/aws/nova_sonic/llm.py +++ b/src/pipecat/services/aws/nova_sonic/llm.py @@ -60,7 +60,7 @@ from pipecat.processors.aggregators.openai_llm_context import ( ) from pipecat.processors.frame_processor import FrameDirection from pipecat.services.llm_service import LLMService -from pipecat.services.settings import NOT_GIVEN, LLMSettings, _NotGiven +from pipecat.services.settings import NOT_GIVEN, LLMSettings, _NotGiven, _warn_deprecated_param from pipecat.utils.time import time_now_iso8601 try: @@ -222,6 +222,7 @@ class AWSNovaSonicLLMService(LLMService): model: str = "amazon.nova-2-sonic-v1:0", voice_id: str = "matthew", params: Optional[Params] = None, + settings: Optional[AWSNovaSonicLLMSettings] = None, system_instruction: Optional[str] = None, tools: Optional[ToolsSchema] = None, send_transcription_frames: bool = True, @@ -238,12 +239,27 @@ class AWSNovaSonicLLMService(LLMService): - Nova 2 Sonic (the default model): "us-east-1", "us-west-2", "ap-northeast-1" - Nova Sonic (the older model): "us-east-1", "ap-northeast-1" model: Model identifier. Defaults to "amazon.nova-2-sonic-v1:0". + + .. deprecated:: + Use ``settings=AWSNovaSonicLLMSettings(model=...)`` instead. + voice_id: Voice ID for speech synthesis. Note that some voices are designed for use with a specific language. Options: - Nova 2 Sonic (the default model): see https://docs.aws.amazon.com/nova/latest/nova2-userguide/sonic-language-support.html - Nova Sonic (the older model): see https://docs.aws.amazon.com/nova/latest/userguide/available-voices.html. + + .. deprecated:: + Use ``settings=AWSNovaSonicLLMSettings(voice_id=...)`` instead. + params: Model parameters for audio configuration and inference. + + .. deprecated:: + Use ``settings=AWSNovaSonicLLMSettings(...)`` instead. + + settings: AWS Nova Sonic LLM settings. If provided together with + deprecated top-level parameters, the ``settings`` values take + precedence. system_instruction: System-level instruction for the model. tools: Available tools/functions for the model to use. send_transcription_frames: Whether to emit transcription frames. @@ -254,23 +270,35 @@ class AWSNovaSonicLLMService(LLMService): **kwargs: Additional arguments passed to the parent LLMService. """ - params = params or Params() + # Check for deprecated parameter usage + if model != "amazon.nova-2-sonic-v1:0": + _warn_deprecated_param("model", "AWSNovaSonicLLMSettings", "model") + if voice_id != "matthew": + _warn_deprecated_param("voice_id", "AWSNovaSonicLLMSettings", "voice_id") + if params is not None: + _warn_deprecated_param("params", "AWSNovaSonicLLMSettings") + + _params = params or Params() + + default_settings = AWSNovaSonicLLMSettings( + model=model, + voice_id=voice_id, + temperature=_params.temperature, + max_tokens=_params.max_tokens, + top_p=_params.top_p, + top_k=None, + frequency_penalty=None, + presence_penalty=None, + seed=None, + filter_incomplete_user_turns=False, + user_turn_completion_config=None, + endpointing_sensitivity=_params.endpointing_sensitivity, + ) + if settings is not None: + default_settings.apply_update(settings) super().__init__( - settings=AWSNovaSonicLLMSettings( - model=model, - voice_id=voice_id, - temperature=params.temperature, - max_tokens=params.max_tokens, - top_p=params.top_p, - top_k=None, - frequency_penalty=None, - presence_penalty=None, - seed=None, - filter_incomplete_user_turns=False, - user_turn_completion_config=None, - endpointing_sensitivity=params.endpointing_sensitivity, - ), + settings=default_settings, **kwargs, ) self._secret_access_key = secret_access_key @@ -280,12 +308,12 @@ class AWSNovaSonicLLMService(LLMService): self._client: Optional[BedrockRuntimeClient] = None # Audio I/O config (hardware settings, not runtime-tunable) - self._input_sample_rate = params.input_sample_rate - self._input_sample_size = params.input_sample_size - self._input_channel_count = params.input_channel_count - self._output_sample_rate = params.output_sample_rate - self._output_sample_size = params.output_sample_size - self._output_channel_count = params.output_channel_count + self._input_sample_rate = _params.input_sample_rate + self._input_sample_size = _params.input_sample_size + self._input_channel_count = _params.input_channel_count + self._output_sample_rate = _params.output_sample_rate + self._output_sample_size = _params.output_sample_size + self._output_channel_count = _params.output_channel_count self._system_instruction = system_instruction self._tools = tools @@ -295,7 +323,7 @@ class AWSNovaSonicLLMService(LLMService): and not self._is_endpointing_sensitivity_supported() ): logger.warning( - f"endpointing_sensitivity is not supported for model '{model}' and will be ignored. " + f"endpointing_sensitivity is not supported for model '{self._settings.model}' and will be ignored. " "This parameter is only supported starting with Nova 2 Sonic (amazon.nova-2-sonic-v1:0)." ) self._settings.endpointing_sensitivity = None diff --git a/src/pipecat/services/aws/stt.py b/src/pipecat/services/aws/stt.py index 7c3fb398e..1cbfa7329 100644 --- a/src/pipecat/services/aws/stt.py +++ b/src/pipecat/services/aws/stt.py @@ -29,7 +29,7 @@ from pipecat.frames.frames import ( TranscriptionFrame, ) from pipecat.services.aws.utils import build_event_message, decode_event, get_presigned_url -from pipecat.services.settings import NOT_GIVEN, STTSettings, _NotGiven +from pipecat.services.settings import NOT_GIVEN, STTSettings, _NotGiven, _warn_deprecated_param from pipecat.services.stt_latency import AWS_TRANSCRIBE_TTFS_P99 from pipecat.services.stt_service import WebsocketSTTService from pipecat.transcriptions.language import Language, resolve_language @@ -81,8 +81,9 @@ class AWSTranscribeSTTService(WebsocketSTTService): aws_access_key_id: Optional[str] = None, aws_session_token: Optional[str] = None, region: Optional[str] = None, - sample_rate: int = 16000, - language: Language = Language.EN, + sample_rate: Optional[int] = None, + language: Optional[Language] = None, + settings: Optional[AWSTranscribeSTTSettings] = None, ttfs_p99_latency: Optional[float] = AWS_TRANSCRIBE_TTFS_P99, **kwargs, ): @@ -93,29 +94,51 @@ class AWSTranscribeSTTService(WebsocketSTTService): aws_access_key_id: AWS access key ID. If None, uses AWS_ACCESS_KEY_ID environment variable. aws_session_token: AWS session token for temporary credentials. If None, uses AWS_SESSION_TOKEN environment variable. region: AWS region for the service. - sample_rate: Audio sample rate in Hz. Must be 8000 or 16000. Defaults to 16000. - language: Language for transcription. Defaults to English. + sample_rate: Audio sample rate in Hz. Must be 8000 or 16000. + + .. deprecated:: 1.0 + Use ``settings=AWSTranscribeSTTSettings(sample_rate=...)`` instead. + + language: Language for transcription. + + .. deprecated:: 1.0 + Use ``settings=AWSTranscribeSTTSettings(language=...)`` instead. + + settings: Runtime-updatable settings. When provided alongside deprecated + parameters, ``settings`` values take precedence. ttfs_p99_latency: P99 latency from speech end to final transcript in seconds. Override for your deployment. See https://github.com/pipecat-ai/stt-benchmark **kwargs: Additional arguments passed to parent STTService class. """ + if sample_rate is not None: + _warn_deprecated_param("sample_rate", "AWSTranscribeSTTSettings", "sample_rate") + if language is not None: + _warn_deprecated_param("language", "AWSTranscribeSTTSettings", "language") + + _sample_rate = sample_rate or 16000 + _language = language or Language.EN + + default_settings = AWSTranscribeSTTSettings( + language=self.language_to_service_language(_language) or "en-US", + sample_rate=_sample_rate, + media_encoding="linear16", + number_of_channels=1, + show_speaker_label=False, + enable_channel_identification=False, + ) + if settings is not None: + default_settings.apply_update(settings) + super().__init__( ttfs_p99_latency=ttfs_p99_latency, - settings=AWSTranscribeSTTSettings( - language=self.language_to_service_language(language) or "en-US", - sample_rate=sample_rate, - media_encoding="linear16", - number_of_channels=1, - show_speaker_label=False, - enable_channel_identification=False, - ), + settings=default_settings, **kwargs, ) # Validate sample rate - AWS Transcribe only supports 8000 Hz or 16000 Hz - if sample_rate not in [8000, 16000]: + if _sample_rate not in [8000, 16000]: logger.warning( - f"AWS Transcribe only supports 8000 Hz or 16000 Hz sample rates. Converting from {sample_rate} Hz to 16000 Hz." + f"AWS Transcribe only supports 8000 Hz or 16000 Hz sample rates. Converting from {_sample_rate} Hz to 16000 Hz." ) self._settings.sample_rate = 16000 diff --git a/src/pipecat/services/aws/tts.py b/src/pipecat/services/aws/tts.py index 017477a7a..8e11cb3cd 100644 --- a/src/pipecat/services/aws/tts.py +++ b/src/pipecat/services/aws/tts.py @@ -25,7 +25,7 @@ from pipecat.frames.frames import ( TTSStartedFrame, TTSStoppedFrame, ) -from pipecat.services.settings import NOT_GIVEN, TTSSettings, _NotGiven +from pipecat.services.settings import NOT_GIVEN, TTSSettings, _NotGiven, _warn_deprecated_param from pipecat.services.tts_service import TTSService from pipecat.transcriptions.language import Language, resolve_language from pipecat.utils.tracing.service_decorators import traced_tts @@ -155,6 +155,9 @@ class AWSPollyTTSService(TTSService): class InputParams(BaseModel): """Input parameters for AWS Polly TTS configuration. + .. deprecated:: 1.0 + Use ``AWSPollyTTSSettings`` directly via the ``settings`` parameter instead. + Parameters: engine: TTS engine to use ('standard', 'neural', etc.). language: Language for synthesis. Defaults to English. @@ -178,9 +181,10 @@ class AWSPollyTTSService(TTSService): aws_access_key_id: Optional[str] = None, aws_session_token: Optional[str] = None, region: Optional[str] = None, - voice_id: str = "Joanna", + voice_id: Optional[str] = None, sample_rate: Optional[int] = None, params: Optional[InputParams] = None, + settings: Optional[AWSPollyTTSSettings] = None, **kwargs, ): """Initializes the AWS Polly TTS service. @@ -191,26 +195,45 @@ class AWSPollyTTSService(TTSService): aws_session_token: AWS session token for temporary credentials. region: AWS region for Polly service. Defaults to 'us-east-1'. voice_id: Voice ID to use for synthesis. Defaults to 'Joanna'. + + .. deprecated:: 1.0 + Use ``settings=AWSPollyTTSSettings(voice=...)`` instead. + sample_rate: Audio sample rate. If None, uses service default. params: Additional input parameters for voice customization. + + .. deprecated:: 1.0 + Use ``settings=AWSPollyTTSSettings(...)`` instead. + + settings: Runtime-updatable settings. When provided alongside deprecated + parameters, ``settings`` values take precedence. **kwargs: Additional arguments passed to parent TTSService class. """ - params = params or AWSPollyTTSService.InputParams() + if voice_id is not None: + _warn_deprecated_param("voice_id", "AWSPollyTTSSettings", "voice") + if params is not None: + _warn_deprecated_param("params", "AWSPollyTTSSettings") + + _params = params or AWSPollyTTSService.InputParams() + + default_settings = AWSPollyTTSSettings( + model=None, + voice=voice_id or "Joanna", + engine=_params.engine, + language=self.language_to_service_language(_params.language) + if _params.language + else "en-US", + pitch=_params.pitch, + rate=_params.rate, + volume=_params.volume, + lexicon_names=_params.lexicon_names, + ) + if settings is not None: + default_settings.apply_update(settings) super().__init__( sample_rate=sample_rate, - settings=AWSPollyTTSSettings( - model=None, - voice=voice_id, - engine=params.engine, - language=self.language_to_service_language(params.language) - if params.language - else "en-US", - pitch=params.pitch, - rate=params.rate, - volume=params.volume, - lexicon_names=params.lexicon_names, - ), + settings=default_settings, **kwargs, ) diff --git a/src/pipecat/services/azure/image.py b/src/pipecat/services/azure/image.py index 66cc28504..e64e5c7d8 100644 --- a/src/pipecat/services/azure/image.py +++ b/src/pipecat/services/azure/image.py @@ -13,14 +13,14 @@ using REST endpoints for creating images from text prompts. import asyncio import io from dataclasses import dataclass -from typing import AsyncGenerator +from typing import AsyncGenerator, Optional import aiohttp from PIL import Image from pipecat.frames.frames import ErrorFrame, Frame, URLImageRawFrame from pipecat.services.image_service import ImageGenService -from pipecat.services.settings import ImageGenSettings +from pipecat.services.settings import ImageGenSettings, _warn_deprecated_param @dataclass @@ -46,9 +46,10 @@ class AzureImageGenServiceREST(ImageGenService): image_size: str, api_key: str, endpoint: str, - model: str, + model: Optional[str] = None, aiohttp_session: aiohttp.ClientSession, api_version="2023-06-01-preview", + settings: Optional[AzureImageGenSettings] = None, ): """Initialize the AzureImageGenServiceREST. @@ -57,10 +58,23 @@ class AzureImageGenServiceREST(ImageGenService): api_key: Azure OpenAI API key for authentication. endpoint: Azure OpenAI endpoint URL. model: The image generation model to use. + + .. deprecated:: 1.0 + Use ``settings=AzureImageGenSettings(model=...)`` instead. + aiohttp_session: Shared aiohttp session for HTTP requests. api_version: Azure API version string. Defaults to "2023-06-01-preview". + settings: Runtime-updatable settings. When provided alongside deprecated + parameters, ``settings`` values take precedence. """ - super().__init__(settings=AzureImageGenSettings(model=model)) + if model is not None: + _warn_deprecated_param("model", "AzureImageGenSettings", "model") + + default_settings = AzureImageGenSettings(model=model) + if settings is not None: + default_settings.apply_update(settings) + + super().__init__(settings=default_settings) self._api_key = api_key self._azure_endpoint = endpoint diff --git a/src/pipecat/services/azure/llm.py b/src/pipecat/services/azure/llm.py index b1807ad13..b828f0e4e 100644 --- a/src/pipecat/services/azure/llm.py +++ b/src/pipecat/services/azure/llm.py @@ -6,10 +6,14 @@ """Azure OpenAI service implementation for the Pipecat AI framework.""" +from typing import Optional + from loguru import logger from openai import AsyncAzureOpenAI +from pipecat.services.openai.base_llm import OpenAILLMSettings from pipecat.services.openai.llm import OpenAILLMService +from pipecat.services.settings import _warn_deprecated_param class AzureLLMService(OpenAILLMService): @@ -24,8 +28,9 @@ class AzureLLMService(OpenAILLMService): *, api_key: str, endpoint: str, - model: str, + model: Optional[str] = None, api_version: str = "2024-09-01-preview", + settings: Optional[OpenAILLMSettings] = None, **kwargs, ): """Initialize the Azure LLM service. @@ -33,15 +38,28 @@ class AzureLLMService(OpenAILLMService): Args: api_key: The API key for accessing Azure OpenAI. endpoint: The Azure endpoint URL. - model: The model identifier to use. + model: The model identifier to use. Defaults to "gpt-4o". + + .. deprecated:: 1.0 + Use ``settings=OpenAILLMSettings(model=...)`` instead. + api_version: Azure API version. Defaults to "2024-09-01-preview". + settings: Runtime-updatable settings. When provided alongside deprecated + parameters, ``settings`` values take precedence. **kwargs: Additional keyword arguments passed to OpenAILLMService. """ + if model is not None: + _warn_deprecated_param("model", "OpenAILLMSettings", "model") + + default_settings = OpenAILLMSettings(model=model or "gpt-4o") + if settings is not None: + default_settings.apply_update(settings) + # Initialize variables before calling parent __init__() because that # will call create_client() and we need those values there. self._endpoint = endpoint self._api_version = api_version - super().__init__(api_key=api_key, model=model, **kwargs) + super().__init__(api_key=api_key, settings=default_settings, **kwargs) def create_client(self, api_key=None, base_url=None, **kwargs): """Create OpenAI-compatible client for Azure OpenAI endpoint. diff --git a/src/pipecat/services/azure/stt.py b/src/pipecat/services/azure/stt.py index 5533e350e..5ab88c8dd 100644 --- a/src/pipecat/services/azure/stt.py +++ b/src/pipecat/services/azure/stt.py @@ -26,7 +26,7 @@ from pipecat.frames.frames import ( TranscriptionFrame, ) from pipecat.services.azure.common import language_to_azure_language -from pipecat.services.settings import NOT_GIVEN, STTSettings, _NotGiven +from pipecat.services.settings import NOT_GIVEN, STTSettings, _NotGiven, _warn_deprecated_param from pipecat.services.stt_latency import AZURE_TTFS_P99 from pipecat.services.stt_service import STTService from pipecat.transcriptions.language import Language @@ -79,10 +79,11 @@ class AzureSTTService(STTService): *, api_key: str, region: str, - language: Language = Language.EN_US, + language: Optional[Language] = Language.EN_US, sample_rate: Optional[int] = None, private_endpoint: Optional[str] = None, endpoint_id: Optional[str] = None, + settings: Optional[AzureSTTSettings] = None, ttfs_p99_latency: Optional[float] = AZURE_TTFS_P99, **kwargs, ): @@ -92,30 +93,44 @@ class AzureSTTService(STTService): api_key: Azure Cognitive Services subscription key. region: Azure region for the Speech service (e.g., 'eastus'). language: Language for speech recognition. Defaults to English (US). + + .. deprecated:: 1.0 + Use ``settings=AzureSTTSettings(language=...)`` instead. + sample_rate: Audio sample rate in Hz. If None, uses service default. private_endpoint: Private endpoint for STT behind firewall. See https://docs.azure.cn/en-us/ai-services/speech-service/speech-services-private-link?tabs=portal endpoint_id: Custom model endpoint id. + settings: Runtime-updatable settings. When provided alongside deprecated + parameters, ``settings`` values take precedence. ttfs_p99_latency: P99 latency from speech end to final transcript in seconds. Override for your deployment. See https://github.com/pipecat-ai/stt-benchmark **kwargs: Additional arguments passed to parent STTService. """ + if language != Language.EN_US: + _warn_deprecated_param("language", "AzureSTTSettings", "language") + + default_settings = AzureSTTSettings( + model=None, + region=region, + language=language_to_azure_language(language) if language else None, + sample_rate=sample_rate, + ) + if settings is not None: + default_settings.apply_update(settings) + super().__init__( sample_rate=sample_rate, ttfs_p99_latency=ttfs_p99_latency, - settings=AzureSTTSettings( - model=None, - region=region, - language=language_to_azure_language(language), - sample_rate=sample_rate, - ), + settings=default_settings, **kwargs, ) self._speech_config = SpeechConfig( subscription=api_key, region=region, - speech_recognition_language=language_to_azure_language(language), + speech_recognition_language=default_settings.language + or language_to_azure_language(Language.EN_US), endpoint=private_endpoint, ) diff --git a/src/pipecat/services/azure/tts.py b/src/pipecat/services/azure/tts.py index 6e62c73bf..d37874825 100644 --- a/src/pipecat/services/azure/tts.py +++ b/src/pipecat/services/azure/tts.py @@ -26,7 +26,7 @@ from pipecat.frames.frames import ( ) from pipecat.processors.frame_processor import FrameDirection from pipecat.services.azure.common import language_to_azure_language -from pipecat.services.settings import NOT_GIVEN, TTSSettings, _NotGiven +from pipecat.services.settings import NOT_GIVEN, TTSSettings, _NotGiven, _warn_deprecated_param from pipecat.services.tts_service import TextAggregationMode, TTSService from pipecat.transcriptions.language import Language from pipecat.utils.tracing.service_decorators import traced_tts @@ -115,6 +115,9 @@ class AzureBaseTTSService: class InputParams(BaseModel): """Input parameters for Azure TTS voice configuration. + .. deprecated:: 1.0 + Use ``settings=AzureTTSSettings(...)`` instead. + Parameters: emphasis: Emphasis level for speech ("strong", "moderate", "reduced"). language: Language for synthesis. Defaults to English (US). @@ -253,9 +256,10 @@ class AzureTTSService(TTSService, AzureBaseTTSService): *, api_key: str, region: str, - voice: str = "en-US-SaraNeural", + voice: Optional[str] = None, sample_rate: Optional[int] = None, params: Optional[AzureBaseTTSService.InputParams] = None, + settings: Optional[AzureTTSSettings] = None, aggregate_sentences: Optional[bool] = None, text_aggregation_mode: Optional[TextAggregationMode] = None, **kwargs, @@ -265,9 +269,19 @@ class AzureTTSService(TTSService, AzureBaseTTSService): Args: api_key: Azure Cognitive Services subscription key. region: Azure region identifier (e.g., "eastus", "westus2"). - voice: Voice name to use for synthesis. Defaults to "en-US-SaraNeural". + voice: Voice name to use for synthesis. + + .. deprecated:: 1.0 + Use ``settings=AzureTTSSettings(voice=...)`` instead. + sample_rate: Audio sample rate in Hz. If None, uses service default. params: Voice and synthesis parameters configuration. + + .. deprecated:: 1.0 + Use ``settings=AzureTTSSettings(...)`` instead. + + settings: Runtime-updatable settings. When provided alongside deprecated + parameters, ``settings`` values take precedence. aggregate_sentences: Deprecated. Use text_aggregation_mode instead. .. deprecated:: 0.0.104 @@ -276,7 +290,29 @@ class AzureTTSService(TTSService, AzureBaseTTSService): text_aggregation_mode: How to aggregate text before synthesis. **kwargs: Additional arguments passed to parent WordTTSService. """ - params = params or AzureBaseTTSService.InputParams() + if voice is not None: + _warn_deprecated_param("voice", "AzureTTSSettings", "voice") + if params is not None: + _warn_deprecated_param("params", "AzureTTSSettings") + + _params = params or AzureBaseTTSService.InputParams() + + default_settings = AzureTTSSettings( + model=None, + emphasis=_params.emphasis, + language=self.language_to_service_language(_params.language) + if _params.language + else "en-US", + pitch=_params.pitch, + rate=_params.rate, + role=_params.role, + style=_params.style, + style_degree=_params.style_degree, + voice=voice or "en-US-SaraNeural", + volume=_params.volume, + ) + if settings is not None: + default_settings.apply_update(settings) super().__init__( aggregate_sentences=aggregate_sentences, @@ -286,25 +322,12 @@ class AzureTTSService(TTSService, AzureBaseTTSService): pause_frame_processing=True, supports_word_timestamps=True, sample_rate=sample_rate, - settings=AzureTTSSettings( - model=None, - emphasis=params.emphasis, - language=self.language_to_service_language(params.language) - if params.language - else "en-US", - pitch=params.pitch, - rate=params.rate, - role=params.role, - style=params.style, - style_degree=params.style_degree, - voice=voice, - volume=params.volume, - ), + settings=default_settings, **kwargs, ) # Initialize Azure-specific functionality from mixin - self._init_azure_base(api_key=api_key, region=region, voice=voice) + self._init_azure_base(api_key=api_key, region=region, voice=default_settings.voice) self._speech_config = None self._speech_synthesizer = None @@ -730,9 +753,10 @@ class AzureHttpTTSService(TTSService, AzureBaseTTSService): *, api_key: str, region: str, - voice: str = "en-US-SaraNeural", + voice: Optional[str] = None, sample_rate: Optional[int] = None, params: Optional[AzureBaseTTSService.InputParams] = None, + settings: Optional[AzureTTSSettings] = None, **kwargs, ): """Initialize the Azure HTTP TTS service. @@ -740,34 +764,53 @@ class AzureHttpTTSService(TTSService, AzureBaseTTSService): Args: api_key: Azure Cognitive Services subscription key. region: Azure region identifier (e.g., "eastus", "westus2"). - voice: Voice name to use for synthesis. Defaults to "en-US-SaraNeural". + voice: Voice name to use for synthesis. + + .. deprecated:: 1.0 + Use ``settings=AzureTTSSettings(voice=...)`` instead. + sample_rate: Audio sample rate in Hz. If None, uses service default. params: Voice and synthesis parameters configuration. + + .. deprecated:: 1.0 + Use ``settings=AzureTTSSettings(...)`` instead. + + settings: Runtime-updatable settings. When provided alongside deprecated + parameters, ``settings`` values take precedence. **kwargs: Additional arguments passed to parent TTSService. """ - params = params or AzureBaseTTSService.InputParams() + if voice is not None: + _warn_deprecated_param("voice", "AzureTTSSettings", "voice") + if params is not None: + _warn_deprecated_param("params", "AzureTTSSettings") + + _params = params or AzureBaseTTSService.InputParams() + + default_settings = AzureTTSSettings( + model=None, + emphasis=_params.emphasis, + language=self.language_to_service_language(_params.language) + if _params.language + else "en-US", + pitch=_params.pitch, + rate=_params.rate, + role=_params.role, + style=_params.style, + style_degree=_params.style_degree, + voice=voice or "en-US-SaraNeural", + volume=_params.volume, + ) + if settings is not None: + default_settings.apply_update(settings) super().__init__( sample_rate=sample_rate, - settings=AzureTTSSettings( - model=None, - emphasis=params.emphasis, - language=self.language_to_service_language(params.language) - if params.language - else "en-US", - pitch=params.pitch, - rate=params.rate, - role=params.role, - style=params.style, - style_degree=params.style_degree, - voice=voice, - volume=params.volume, - ), + settings=default_settings, **kwargs, ) # Initialize Azure-specific functionality from mixin - self._init_azure_base(api_key=api_key, region=region, voice=voice) + self._init_azure_base(api_key=api_key, region=region, voice=default_settings.voice) self._speech_config = None self._speech_synthesizer = None diff --git a/src/pipecat/services/camb/tts.py b/src/pipecat/services/camb/tts.py index 75b299569..4ee2d5171 100644 --- a/src/pipecat/services/camb/tts.py +++ b/src/pipecat/services/camb/tts.py @@ -32,7 +32,7 @@ from pipecat.frames.frames import ( TTSStartedFrame, TTSStoppedFrame, ) -from pipecat.services.settings import NOT_GIVEN, TTSSettings, _NotGiven +from pipecat.services.settings import NOT_GIVEN, TTSSettings, _NotGiven, _warn_deprecated_param from pipecat.services.tts_service import TTSService from pipecat.transcriptions.language import Language, resolve_language from pipecat.utils.tracing.service_decorators import traced_tts @@ -175,6 +175,9 @@ class CambTTSService(TTSService): class InputParams(BaseModel): """Input parameters for Camb.ai TTS configuration. + .. deprecated:: 1.0 + Use ``settings=CambTTSSettings(...)`` instead. + Parameters: language: Language for synthesis (BCP-47 format). Defaults to English. user_instructions: Custom instructions for mars-instruct model only. @@ -193,47 +196,71 @@ class CambTTSService(TTSService): self, *, api_key: str, - voice_id: int = 147320, - model: str = "mars-flash", + voice_id: Optional[int] = None, + model: Optional[str] = None, timeout: float = 60.0, sample_rate: Optional[int] = None, params: Optional[InputParams] = None, + settings: Optional[CambTTSSettings] = None, **kwargs, ): """Initialize the Camb.ai TTS service. Args: api_key: Camb.ai API key for authentication. - voice_id: Voice ID to use. Defaults to 147320. + voice_id: Voice ID to use. + + .. deprecated:: 1.0 + Use ``settings=CambTTSSettings(voice=...)`` instead. + model: TTS model to use. Options: "mars-flash" (fast), "mars-pro" (high quality). - Defaults to "mars-flash". + + .. deprecated:: 1.0 + Use ``settings=CambTTSSettings(model=...)`` instead. + timeout: Request timeout in seconds. Defaults to 60.0 (minimum recommended by Camb.ai). sample_rate: Audio sample rate in Hz. If None, uses model-specific default. params: Additional voice parameters. If None, uses defaults. + + .. deprecated:: 1.0 + Use ``settings=CambTTSSettings(...)`` instead. + + settings: Runtime-updatable settings. When provided alongside deprecated + parameters, ``settings`` values take precedence. **kwargs: Additional arguments passed to parent TTSService. """ - params = params or CambTTSService.InputParams() + if voice_id is not None: + _warn_deprecated_param("voice_id", "CambTTSSettings", "voice") + if model is not None: + _warn_deprecated_param("model", "CambTTSSettings", "model") + if params is not None: + _warn_deprecated_param("params", "CambTTSSettings") + + _params = params or CambTTSService.InputParams() + _model = model or "mars-flash" # Warn if sample rate doesn't match model's supported rate - if sample_rate and sample_rate != MODEL_SAMPLE_RATES.get(model): + if sample_rate and sample_rate != MODEL_SAMPLE_RATES.get(_model): logger.warning( - f"Camb.ai's {model} model only supports {MODEL_SAMPLE_RATES.get(model)}Hz " + f"Camb.ai's {_model} model only supports {MODEL_SAMPLE_RATES.get(_model)}Hz " f"sample rate. Current rate of {sample_rate}Hz may cause issues." ) + default_settings = CambTTSSettings( + model=_model, + voice=voice_id or 147320, + language=( + self.language_to_service_language(_params.language) if _params.language else "en-us" + ), + user_instructions=_params.user_instructions, + ) + if settings is not None: + default_settings.apply_update(settings) + super().__init__( sample_rate=sample_rate, - settings=CambTTSSettings( - model=model, - voice=voice_id, - language=( - self.language_to_service_language(params.language) - if params.language - else "en-us" - ), - user_instructions=params.user_instructions, - ), + settings=default_settings, **kwargs, ) diff --git a/src/pipecat/services/cartesia/stt.py b/src/pipecat/services/cartesia/stt.py index 526fc9116..530f6a4d1 100644 --- a/src/pipecat/services/cartesia/stt.py +++ b/src/pipecat/services/cartesia/stt.py @@ -158,6 +158,7 @@ class CartesiaSTTService(WebsocketSTTService): base_url: str = "", sample_rate: int = 16000, live_options: Optional[CartesiaLiveOptions] = None, + settings: Optional[CartesiaSTTSettings] = None, ttfs_p99_latency: Optional[float] = CARTESIA_TTFS_P99, **kwargs, ): @@ -168,6 +169,8 @@ class CartesiaSTTService(WebsocketSTTService): base_url: Custom API endpoint URL. If empty, uses default. sample_rate: Audio sample rate in Hz. Defaults to 16000. live_options: Configuration options for transcription service. + settings: Runtime-updatable settings. When provided alongside + ``live_options``, ``settings`` values take precedence. ttfs_p99_latency: P99 latency from speech end to final transcript in seconds. Override for your deployment. See https://github.com/pipecat-ai/stt-benchmark **kwargs: Additional arguments passed to parent STTService. @@ -189,16 +192,20 @@ class CartesiaSTTService(WebsocketSTTService): k: v for k, v in merged_options.items() if not isinstance(v, str) or v != "None" } + default_settings = CartesiaSTTSettings( + model=merged_options["model"], + language=merged_options.get("language"), + encoding=merged_options.get("encoding", "pcm_s16le"), + ) + if settings is not None: + default_settings.apply_update(settings) + super().__init__( sample_rate=sample_rate, ttfs_p99_latency=ttfs_p99_latency, keepalive_timeout=120, keepalive_interval=30, - settings=CartesiaSTTSettings( - model=merged_options["model"], - language=merged_options.get("language"), - encoding=merged_options.get("encoding", "pcm_s16le"), - ), + settings=default_settings, **kwargs, ) diff --git a/src/pipecat/services/cartesia/tts.py b/src/pipecat/services/cartesia/tts.py index a096a36b3..bc8b04dfd 100644 --- a/src/pipecat/services/cartesia/tts.py +++ b/src/pipecat/services/cartesia/tts.py @@ -27,7 +27,7 @@ from pipecat.frames.frames import ( TTSStartedFrame, TTSStoppedFrame, ) -from pipecat.services.settings import NOT_GIVEN, TTSSettings, _NotGiven +from pipecat.services.settings import NOT_GIVEN, TTSSettings, _NotGiven, _warn_deprecated_param from pipecat.services.tts_service import AudioContextTTSService, TextAggregationMode, TTSService from pipecat.transcriptions.language import Language, resolve_language from pipecat.utils.text.base_text_aggregator import BaseTextAggregator @@ -259,14 +259,15 @@ class CartesiaTTSService(AudioContextTTSService): self, *, api_key: str, - voice_id: str, + voice_id: Optional[str] = None, cartesia_version: str = "2025-04-16", url: str = "wss://api.cartesia.ai/tts/websocket", - model: str = "sonic-3", + model: Optional[str] = None, sample_rate: Optional[int] = None, encoding: str = "pcm_s16le", container: str = "raw", params: Optional[InputParams] = None, + settings: Optional[CartesiaTTSSettings] = None, text_aggregator: Optional[BaseTextAggregator] = None, text_aggregation_mode: Optional[TextAggregationMode] = None, aggregate_sentences: Optional[bool] = None, @@ -277,13 +278,27 @@ class CartesiaTTSService(AudioContextTTSService): Args: api_key: Cartesia API key for authentication. voice_id: ID of the voice to use for synthesis. + + .. deprecated:: 1.0 + Use ``settings=CartesiaTTSSettings(voice=...)`` instead. + cartesia_version: API version string for Cartesia service. url: WebSocket URL for Cartesia TTS API. model: TTS model to use (e.g., "sonic-3"). + + .. deprecated:: 1.0 + Use ``settings=CartesiaTTSSettings(model=...)`` instead. + sample_rate: Audio sample rate. If None, uses default. encoding: Audio encoding format. container: Audio container format. params: Additional input parameters for voice customization. + + .. deprecated:: 1.0 + Use ``settings=CartesiaTTSSettings(...)`` instead. + + settings: Runtime-updatable settings. When provided alongside deprecated + parameters, ``settings`` values take precedence. text_aggregator: Custom text aggregator for processing input text. .. deprecated:: 0.0.95 @@ -297,6 +312,13 @@ class CartesiaTTSService(AudioContextTTSService): **kwargs: Additional arguments passed to the parent service. """ + if voice_id is not None: + _warn_deprecated_param("voice_id", "CartesiaTTSSettings", "voice") + if model is not None: + _warn_deprecated_param("model", "CartesiaTTSSettings", "model") + if params is not None: + _warn_deprecated_param("params", "CartesiaTTSSettings") + # By default, we aggregate sentences before sending to TTS. This adds # ~200-300ms of latency per sentence (waiting for the sentence-ending # punctuation token from the LLM). Setting @@ -310,7 +332,24 @@ class CartesiaTTSService(AudioContextTTSService): # if we're interrupted. Cartesia gives us word-by-word timestamps. We # can use those to generate text frames ourselves aligned with the # playout timing of the audio! - params = params or CartesiaTTSService.InputParams() + _params = params or CartesiaTTSService.InputParams() + + default_settings = CartesiaTTSSettings( + model=model or "sonic-3", + voice=voice_id, + output_container=container, + output_encoding=encoding, + output_sample_rate=0, + language=( + self.language_to_service_language(_params.language) if _params.language else None + ), + speed=_params.speed, + emotion=_params.emotion, + generation_config=_params.generation_config, + pronunciation_dict_id=_params.pronunciation_dict_id, + ) + if settings is not None: + default_settings.apply_update(settings) super().__init__( text_aggregation_mode=text_aggregation_mode, @@ -320,20 +359,7 @@ class CartesiaTTSService(AudioContextTTSService): supports_word_timestamps=True, sample_rate=sample_rate, text_aggregator=text_aggregator, - settings=CartesiaTTSSettings( - model=model, - output_container=container, - output_encoding=encoding, - output_sample_rate=0, - language=self.language_to_service_language(params.language) - if params.language - else None, - speed=params.speed, - emotion=params.emotion, - generation_config=params.generation_config, - pronunciation_dict_id=params.pronunciation_dict_id, - voice=voice_id, - ), + settings=default_settings, **kwargs, ) @@ -713,8 +739,8 @@ class CartesiaHttpTTSService(TTSService): self, *, api_key: str, - voice_id: str, - model: str = "sonic-3", + voice_id: Optional[str] = None, + model: Optional[str] = None, base_url: str = "https://api.cartesia.ai", cartesia_version: str = "2024-11-13", aiohttp_session: Optional[aiohttp.ClientSession] = None, @@ -722,6 +748,7 @@ class CartesiaHttpTTSService(TTSService): encoding: str = "pcm_s16le", container: str = "raw", params: Optional[InputParams] = None, + settings: Optional[CartesiaTTSSettings] = None, **kwargs, ): """Initialize the Cartesia HTTP TTS service. @@ -729,7 +756,15 @@ class CartesiaHttpTTSService(TTSService): Args: api_key: Cartesia API key for authentication. voice_id: ID of the voice to use for synthesis. + + .. deprecated:: 1.0 + Use ``settings=CartesiaTTSSettings(voice=...)`` instead. + model: TTS model to use (e.g., "sonic-3"). + + .. deprecated:: 1.0 + Use ``settings=CartesiaTTSSettings(model=...)`` instead. + base_url: Base URL for Cartesia HTTP API. cartesia_version: API version string for Cartesia service. aiohttp_session: Optional aiohttp ClientSession for HTTP requests. @@ -738,26 +773,43 @@ class CartesiaHttpTTSService(TTSService): encoding: Audio encoding format. container: Audio container format. params: Additional input parameters for voice customization. + + .. deprecated:: 1.0 + Use ``settings=CartesiaTTSSettings(...)`` instead. + + settings: Runtime-updatable settings. When provided alongside deprecated + parameters, ``settings`` values take precedence. **kwargs: Additional arguments passed to the parent TTSService. """ - params = params or CartesiaHttpTTSService.InputParams() + if voice_id is not None: + _warn_deprecated_param("voice_id", "CartesiaTTSSettings", "voice") + if model is not None: + _warn_deprecated_param("model", "CartesiaTTSSettings", "model") + if params is not None: + _warn_deprecated_param("params", "CartesiaTTSSettings") + + _params = params or CartesiaHttpTTSService.InputParams() + + default_settings = CartesiaTTSSettings( + model=model or "sonic-3", + voice=voice_id, + output_container=container, + output_encoding=encoding, + output_sample_rate=0, + language=( + self.language_to_service_language(_params.language) if _params.language else None + ), + speed=_params.speed, + emotion=_params.emotion, + generation_config=_params.generation_config, + pronunciation_dict_id=_params.pronunciation_dict_id, + ) + if settings is not None: + default_settings.apply_update(settings) super().__init__( sample_rate=sample_rate, - settings=CartesiaTTSSettings( - model=model, - voice=voice_id, - output_container=container, - output_encoding=encoding, - output_sample_rate=0, - language=self.language_to_service_language(params.language) - if params.language - else None, - speed=params.speed, - emotion=params.emotion, - generation_config=params.generation_config, - pronunciation_dict_id=params.pronunciation_dict_id, - ), + settings=default_settings, **kwargs, ) diff --git a/src/pipecat/services/cerebras/llm.py b/src/pipecat/services/cerebras/llm.py index e1ecceef7..ec3c3f09b 100644 --- a/src/pipecat/services/cerebras/llm.py +++ b/src/pipecat/services/cerebras/llm.py @@ -6,10 +6,14 @@ """Cerebras LLM service implementation using OpenAI-compatible interface.""" +from typing import Optional + from loguru import logger from pipecat.adapters.services.open_ai_adapter import OpenAILLMInvocationParams +from pipecat.services.openai.base_llm import OpenAILLMSettings from pipecat.services.openai.llm import OpenAILLMService +from pipecat.services.settings import _warn_deprecated_param class CerebrasLLMService(OpenAILLMService): @@ -24,7 +28,8 @@ class CerebrasLLMService(OpenAILLMService): *, api_key: str, base_url: str = "https://api.cerebras.ai/v1", - model: str = "gpt-oss-120b", + model: Optional[str] = None, + settings: Optional[OpenAILLMSettings] = None, **kwargs, ): """Initialize the Cerebras LLM service. @@ -33,9 +38,22 @@ class CerebrasLLMService(OpenAILLMService): api_key: The API key for accessing Cerebras's API. base_url: The base URL for Cerebras API. Defaults to "https://api.cerebras.ai/v1". model: The model identifier to use. Defaults to "gpt-oss-120b". + + .. deprecated:: 1.0 + Use ``settings=OpenAILLMSettings(model=...)`` instead. + + settings: Runtime-updatable settings. When provided alongside deprecated + parameters, ``settings`` values take precedence. **kwargs: Additional keyword arguments passed to OpenAILLMService. """ - super().__init__(api_key=api_key, base_url=base_url, model=model, **kwargs) + if model is not None: + _warn_deprecated_param("model", "OpenAILLMSettings", "model") + + default_settings = OpenAILLMSettings(model=model or "gpt-oss-120b") + if settings is not None: + default_settings.apply_update(settings) + + super().__init__(api_key=api_key, base_url=base_url, settings=default_settings, **kwargs) def create_client(self, api_key=None, base_url=None, **kwargs): """Create OpenAI-compatible client for Cerebras API endpoint. diff --git a/src/pipecat/services/deepgram/flux/stt.py b/src/pipecat/services/deepgram/flux/stt.py index 984906c6c..fdfd65613 100644 --- a/src/pipecat/services/deepgram/flux/stt.py +++ b/src/pipecat/services/deepgram/flux/stt.py @@ -28,7 +28,7 @@ from pipecat.frames.frames import ( UserStartedSpeakingFrame, UserStoppedSpeakingFrame, ) -from pipecat.services.settings import NOT_GIVEN, STTSettings, _NotGiven +from pipecat.services.settings import NOT_GIVEN, STTSettings, _NotGiven, _warn_deprecated_param from pipecat.services.stt_service import WebsocketSTTService from pipecat.transcriptions.language import Language from pipecat.utils.time import time_now_iso8601 @@ -124,8 +124,8 @@ class DeepgramFluxSTTService(WebsocketSTTService): class InputParams(BaseModel): """Configuration parameters for Deepgram Flux API. - This class defines all available connection parameters for the Deepgram Flux API - based on the official documentation. + .. deprecated:: 1.0 + Use ``settings=DeepgramFluxSTTSettings(...)`` instead. Parameters: eager_eot_threshold: Optional. EagerEndOfTurn/TurnResumed are off by default. @@ -158,10 +158,11 @@ class DeepgramFluxSTTService(WebsocketSTTService): api_key: str, url: str = "wss://api.deepgram.com/v2/listen", sample_rate: Optional[int] = None, - model: str = "flux-general-en", + model: Optional[str] = None, flux_encoding: str = "linear16", params: Optional[InputParams] = None, should_interrupt: bool = True, + settings: Optional[DeepgramFluxSTTSettings] = None, **kwargs, ): """Initialize the Deepgram Flux STT service. @@ -170,12 +171,21 @@ class DeepgramFluxSTTService(WebsocketSTTService): api_key: Deepgram API key for authentication. Required for API access. url: WebSocket URL for the Deepgram Flux API. Defaults to the preview endpoint. sample_rate: Audio sample rate in Hz. If None, uses the rate from params or 16000. - model: Deepgram Flux model to use for transcription. Currently only supports "flux-general-en". + model: Deepgram Flux model to use for transcription. + + .. deprecated:: 1.0 + Use ``settings=DeepgramFluxSTTSettings(model=...)`` instead. + flux_encoding: Audio encoding format required by Flux API. Must be "linear16". Raw signed little-endian 16-bit PCM encoding. params: InputParams instance containing detailed API configuration options. - If None, default parameters will be used. + + .. deprecated:: 1.0 + Use ``settings=DeepgramFluxSTTSettings(...)`` instead. + should_interrupt: Determine whether the bot should be interrupted when Flux detects that the user is speaking. + settings: Runtime-updatable settings. When provided alongside deprecated + parameters, ``settings`` values take precedence. **kwargs: Additional arguments passed to the parent WebsocketSTTService class. Examples: @@ -185,18 +195,21 @@ class DeepgramFluxSTTService(WebsocketSTTService): Advanced usage with custom parameters:: - params = DeepgramFluxSTTService.InputParams( - eager_eot_threshold=0.5, - eot_threshold=0.8, - keyterm=["AI", "machine learning", "neural network"], - tag=["production", "voice-agent"] - ) stt = DeepgramFluxSTTService( api_key="your-api-key", - model="flux-general-en", - params=params + settings=DeepgramFluxSTTSettings( + model="flux-general-en", + eager_eot_threshold=0.5, + eot_threshold=0.8, + keyterm=["AI", "machine learning", "neural network"], + tag=["production", "voice-agent"], + ), ) """ + if model is not None: + _warn_deprecated_param("model", "DeepgramFluxSTTSettings", "model") + if params is not None: + _warn_deprecated_param("params", "DeepgramFluxSTTSettings") # Note: For DeepgramFluxSTTService, differently from other processes, we need to create # the _receive_task inside _connect_websocket, because the websocket should only be # considered connected and ready to send audio once we receive from Flux the message @@ -207,22 +220,27 @@ class DeepgramFluxSTTService(WebsocketSTTService): # was never destroyed. # So we can keep it here as false, because inside the method send_with_retry, it will # already try to reconnect if needed. - params = params or DeepgramFluxSTTService.InputParams() + _params = params or DeepgramFluxSTTService.InputParams() + + default_settings = DeepgramFluxSTTSettings( + model=model or "flux-general-en", + language=Language.EN, + encoding=flux_encoding, + eager_eot_threshold=_params.eager_eot_threshold, + eot_threshold=_params.eot_threshold, + eot_timeout_ms=_params.eot_timeout_ms, + keyterm=_params.keyterm or [], + mip_opt_out=_params.mip_opt_out, + tag=_params.tag or [], + min_confidence=_params.min_confidence, + ) + if settings is not None: + default_settings.apply_update(settings) + super().__init__( sample_rate=sample_rate, reconnect_on_error=False, - settings=DeepgramFluxSTTSettings( - model=model, - language=Language.EN, - encoding=flux_encoding, - eager_eot_threshold=params.eager_eot_threshold, - eot_threshold=params.eot_threshold, - eot_timeout_ms=params.eot_timeout_ms, - keyterm=params.keyterm or [], - mip_opt_out=params.mip_opt_out, - tag=params.tag or [], - min_confidence=params.min_confidence, - ), + settings=default_settings, **kwargs, ) self._api_key = api_key diff --git a/src/pipecat/services/deepgram/sagemaker/stt.py b/src/pipecat/services/deepgram/sagemaker/stt.py index 24a25e5fd..6d813157d 100644 --- a/src/pipecat/services/deepgram/sagemaker/stt.py +++ b/src/pipecat/services/deepgram/sagemaker/stt.py @@ -41,7 +41,7 @@ from pipecat.utils.time import time_now_iso8601 from pipecat.utils.tracing.service_decorators import traced_stt try: - from pipecat.services.deepgram.stt import LiveOptions + from deepgram import LiveOptions except ModuleNotFoundError as e: logger.error(f"Exception: {e}") logger.error( @@ -51,10 +51,10 @@ except ModuleNotFoundError as e: @dataclass -class DeepgramSageMakerSTTSettings(DeepgramSTTSettings): +class DeepgramSageMakerSTTSettings(_DeepgramSTTSettingsBase): """Settings for the Deepgram SageMaker STT service. - See ``DeepgramSTTSettings`` for full documentation. + See ``_DeepgramSTTSettingsBase`` for full documentation. """ pass @@ -97,6 +97,7 @@ class DeepgramSageMakerSTTService(STTService): region: str, sample_rate: Optional[int] = None, live_options: Optional[LiveOptions] = None, + settings: Optional[DeepgramSageMakerSTTSettings] = None, ttfs_p99_latency: Optional[float] = DEEPGRAM_SAGEMAKER_TTFS_P99, **kwargs, ): @@ -111,37 +112,38 @@ class DeepgramSageMakerSTTService(STTService): live_options: Deepgram LiveOptions configuration. Treated as a delta from a set of sensible defaults — only the fields you set are overridden; all others keep their default values. + settings: Runtime-updatable settings. When provided alongside + ``live_options``, ``settings`` values take precedence (applied + after the ``live_options`` merge). ttfs_p99_latency: P99 latency from speech end to final transcript in seconds. Override for your deployment. See https://github.com/pipecat-ai/stt-benchmark **kwargs: Additional arguments passed to the parent STTService. """ sample_rate = sample_rate or (live_options.sample_rate if live_options else None) - settings = DeepgramSageMakerSTTSettings( - model="nova-3", - language=Language.EN, + default_options = LiveOptions( encoding="linear16", + language=Language.EN, + model="nova-3", channels=1, interim_results=True, - smart_format=False, punctuate=True, - profanity_filter=True, - vad_events=False, - diarize=False, - endpointing=None, ) + default_settings = DeepgramSageMakerSTTSettings( + model=default_options.model, + language=default_options.language, + live_options=default_options, + ) if live_options: - lo_dict = live_options.to_dict() - delta = DeepgramSageMakerSTTSettings.from_mapping( - {k: v for k, v in lo_dict.items() if k != "sample_rate"} - ) - settings.apply_update(delta) + default_settings._merge_live_options_delta(live_options) + if settings is not None: + default_settings.apply_update(settings) super().__init__( sample_rate=sample_rate, ttfs_p99_latency=ttfs_p99_latency, - settings=settings, + settings=default_settings, **kwargs, ) @@ -228,8 +230,9 @@ class DeepgramSageMakerSTTService(STTService): """ logger.debug("Connecting to Deepgram on SageMaker...") - # Reconstruct a LiveOptions from the flat settings to build the query string. - live_options = LiveOptions(**self._settings.given_fields()) + live_options = LiveOptions( + **{**self._settings.live_options.to_dict(), "sample_rate": self.sample_rate} + ) # Build query string from live_options, converting booleans to strings query_params = {} @@ -240,7 +243,6 @@ class DeepgramSageMakerSTTService(STTService): query_params[key] = str(value).lower() else: query_params[key] = str(value) - query_params["sample_rate"] = str(self.sample_rate) query_string = "&".join(f"{k}={v}" for k, v in query_params.items()) diff --git a/src/pipecat/services/deepgram/sagemaker/tts.py b/src/pipecat/services/deepgram/sagemaker/tts.py index b583ce76c..0c141bac0 100644 --- a/src/pipecat/services/deepgram/sagemaker/tts.py +++ b/src/pipecat/services/deepgram/sagemaker/tts.py @@ -33,7 +33,7 @@ from pipecat.frames.frames import ( ) from pipecat.processors.frame_processor import FrameDirection from pipecat.services.aws.sagemaker.bidi_client import SageMakerBidiClient -from pipecat.services.settings import NOT_GIVEN, TTSSettings, _NotGiven +from pipecat.services.settings import NOT_GIVEN, TTSSettings, _NotGiven, _warn_deprecated_param from pipecat.services.tts_service import TTSService from pipecat.utils.tracing.service_decorators import traced_tts @@ -78,9 +78,10 @@ class DeepgramSageMakerTTSService(TTSService): *, endpoint_name: str, region: str, - voice: str = "aura-2-helena-en", + voice: Optional[str] = None, sample_rate: Optional[int] = None, encoding: str = "linear16", + settings: Optional[DeepgramSageMakerTTSSettings] = None, **kwargs, ): """Initialize the Deepgram SageMaker TTS service. @@ -90,21 +91,36 @@ class DeepgramSageMakerTTSService(TTSService): deployed (e.g., "my-deepgram-tts-endpoint"). region: AWS region where the endpoint is deployed (e.g., "us-east-2"). voice: Voice model to use for synthesis. Defaults to "aura-2-helena-en". + + .. deprecated:: 1.0 + Use ``settings=DeepgramSageMakerTTSSettings(voice=...)`` instead. + sample_rate: Audio sample rate in Hz. If None, uses the value from StartFrame. encoding: Audio encoding format. Defaults to "linear16". + settings: Runtime-updatable settings. When provided alongside deprecated + parameters, ``settings`` values take precedence. **kwargs: Additional arguments passed to the parent TTSService. """ + if voice is not None: + _warn_deprecated_param("voice", "DeepgramSageMakerTTSSettings", "voice") + + voice = voice or "aura-2-helena-en" + + default_settings = DeepgramSageMakerTTSSettings( + model=voice, + voice=voice, + language=None, + encoding=encoding, + ) + if settings is not None: + default_settings.apply_update(settings) + super().__init__( sample_rate=sample_rate, push_stop_frames=True, pause_frame_processing=True, append_trailing_space=True, - settings=DeepgramSageMakerTTSSettings( - model=voice, - voice=voice, - language=None, - encoding=encoding, - ), + settings=default_settings, **kwargs, ) diff --git a/src/pipecat/services/deepgram/stt.py b/src/pipecat/services/deepgram/stt.py index 343a87e2a..fe3add7cf 100644 --- a/src/pipecat/services/deepgram/stt.py +++ b/src/pipecat/services/deepgram/stt.py @@ -256,6 +256,7 @@ class DeepgramSTTService(STTService): live_options: Optional[LiveOptions] = None, addons: Optional[Dict] = None, should_interrupt: bool = True, + settings: Optional[DeepgramSTTSettings] = None, ttfs_p99_latency: Optional[float] = DEEPGRAM_TTFS_P99, **kwargs, ): @@ -279,6 +280,9 @@ class DeepgramSTTService(STTService): .. deprecated:: 0.0.99 This parameter will be removed along with `vad_events` support. + settings: Runtime-updatable settings. When provided alongside + ``live_options``, ``settings`` values take precedence (applied + after the ``live_options`` merge). ttfs_p99_latency: P99 latency from speech end to final transcript in seconds. Override for your deployment. See https://github.com/pipecat-ai/stt-benchmark **kwargs: Additional arguments passed to the parent STTService. @@ -299,7 +303,7 @@ class DeepgramSTTService(STTService): ) base_url = url - settings = DeepgramSTTSettings( + default_settings = DeepgramSTTSettings( model="nova-3-general", language=Language.EN, encoding="linear16", @@ -318,15 +322,18 @@ class DeepgramSTTService(STTService): delta = DeepgramSTTSettings.from_mapping( {k: v for k, v in lo_dict.items() if k != "sample_rate"} ) - settings.apply_update(delta) + default_settings.apply_update(delta) + + if settings is not None: + default_settings.apply_update(settings) # Sync extra to top-level fields so self._settings is unambiguous - settings._sync_extra_to_fields() + default_settings._sync_extra_to_fields() super().__init__( sample_rate=sample_rate, ttfs_p99_latency=ttfs_p99_latency, - settings=settings, + settings=default_settings, **kwargs, ) diff --git a/src/pipecat/services/deepgram/tts.py b/src/pipecat/services/deepgram/tts.py index c05b90868..4524d17b6 100644 --- a/src/pipecat/services/deepgram/tts.py +++ b/src/pipecat/services/deepgram/tts.py @@ -30,7 +30,7 @@ from pipecat.frames.frames import ( TTSStoppedFrame, ) from pipecat.processors.frame_processor import FrameDirection -from pipecat.services.settings import NOT_GIVEN, TTSSettings, _NotGiven +from pipecat.services.settings import NOT_GIVEN, TTSSettings, _NotGiven, _warn_deprecated_param from pipecat.services.tts_service import TTSService, WebsocketTTSService from pipecat.utils.tracing.service_decorators import traced_tts @@ -72,41 +72,55 @@ class DeepgramTTSService(WebsocketTTSService): self, *, api_key: str, - voice: str = "aura-2-helena-en", + voice: Optional[str] = None, base_url: str = "wss://api.deepgram.com", sample_rate: Optional[int] = None, encoding: str = "linear16", + settings: Optional[DeepgramTTSSettings] = None, **kwargs, ): """Initialize the Deepgram WebSocket TTS service. Args: api_key: Deepgram API key for authentication. - voice: Voice model to use for synthesis. Defaults to "aura-2-helena-en". + voice: Voice model to use for synthesis. + + .. deprecated:: 1.0 + Use ``settings=DeepgramTTSSettings(voice=...)`` instead. + base_url: WebSocket base URL for Deepgram API. Defaults to "wss://api.deepgram.com". sample_rate: Audio sample rate in Hz. If None, uses service default. encoding: Audio encoding format. Defaults to "linear16". Must be one of SUPPORTED_ENCODINGS. + settings: Runtime-updatable settings. When provided alongside deprecated + parameters, ``settings`` values take precedence. **kwargs: Additional arguments passed to parent InterruptibleTTSService class. Raises: ValueError: If encoding is not in SUPPORTED_ENCODINGS. """ + if voice is not None: + _warn_deprecated_param("voice", "DeepgramTTSSettings", "voice") + if encoding.lower() not in self.SUPPORTED_ENCODINGS: raise ValueError( f"Unsupported encoding '{encoding}'. Must be one of {', '.join(self.SUPPORTED_ENCODINGS)} for WebSocket TTS." ) + default_settings = DeepgramTTSSettings( + model=voice or "aura-2-helena-en", + voice=voice or "aura-2-helena-en", + language=None, + encoding=encoding, + ) + if settings is not None: + default_settings.apply_update(settings) + super().__init__( sample_rate=sample_rate, pause_frame_processing=True, push_stop_frames=True, append_trailing_space=True, - settings=DeepgramTTSSettings( - model=voice, - voice=voice, - language=None, - encoding=encoding, - ), + settings=default_settings, **kwargs, ) @@ -375,32 +389,46 @@ class DeepgramHttpTTSService(TTSService): self, *, api_key: str, - voice: str = "aura-2-helena-en", + voice: Optional[str] = None, aiohttp_session: aiohttp.ClientSession, base_url: str = "https://api.deepgram.com", sample_rate: Optional[int] = None, encoding: str = "linear16", + settings: Optional[DeepgramTTSSettings] = None, **kwargs, ): """Initialize the Deepgram TTS service. Args: api_key: Deepgram API key for authentication. - voice: Voice model to use for synthesis. Defaults to "aura-2-helena-en". + voice: Voice model to use for synthesis. + + .. deprecated:: 1.0 + Use ``settings=DeepgramTTSSettings(voice=...)`` instead. + aiohttp_session: Shared aiohttp session for HTTP requests with connection pooling. base_url: Custom base URL for Deepgram API. Defaults to "https://api.deepgram.com". sample_rate: Audio sample rate in Hz. If None, uses service default. encoding: Audio encoding format. Defaults to "linear16". + settings: Runtime-updatable settings. When provided alongside deprecated + parameters, ``settings`` values take precedence. **kwargs: Additional arguments passed to parent TTSService class. """ + if voice is not None: + _warn_deprecated_param("voice", "DeepgramTTSSettings", "voice") + + default_settings = DeepgramTTSSettings( + model=voice or "aura-2-helena-en", + voice=voice or "aura-2-helena-en", + language=None, + encoding=encoding, + ) + if settings is not None: + default_settings.apply_update(settings) + super().__init__( sample_rate=sample_rate, - settings=DeepgramTTSSettings( - model=voice, - voice=voice, - language=None, - encoding=encoding, - ), + settings=default_settings, **kwargs, ) diff --git a/src/pipecat/services/deepseek/llm.py b/src/pipecat/services/deepseek/llm.py index 70318c9ba..2ebc2e6eb 100644 --- a/src/pipecat/services/deepseek/llm.py +++ b/src/pipecat/services/deepseek/llm.py @@ -6,10 +6,14 @@ """DeepSeek LLM service implementation using OpenAI-compatible interface.""" +from typing import Optional + from loguru import logger from pipecat.adapters.services.open_ai_adapter import OpenAILLMInvocationParams +from pipecat.services.openai.base_llm import OpenAILLMSettings from pipecat.services.openai.llm import OpenAILLMService +from pipecat.services.settings import _warn_deprecated_param class DeepSeekLLMService(OpenAILLMService): @@ -24,7 +28,8 @@ class DeepSeekLLMService(OpenAILLMService): *, api_key: str, base_url: str = "https://api.deepseek.com/v1", - model: str = "deepseek-chat", + model: Optional[str] = None, + settings: Optional[OpenAILLMSettings] = None, **kwargs, ): """Initialize the DeepSeek LLM service. @@ -33,9 +38,22 @@ class DeepSeekLLMService(OpenAILLMService): api_key: The API key for accessing DeepSeek's API. base_url: The base URL for DeepSeek API. Defaults to "https://api.deepseek.com/v1". model: The model identifier to use. Defaults to "deepseek-chat". + + .. deprecated:: 1.0 + Use ``settings=OpenAILLMSettings(model=...)`` instead. + + settings: Runtime-updatable settings. When provided alongside deprecated + parameters, ``settings`` values take precedence. **kwargs: Additional keyword arguments passed to OpenAILLMService. """ - super().__init__(api_key=api_key, base_url=base_url, model=model, **kwargs) + if model is not None: + _warn_deprecated_param("model", "OpenAILLMSettings", "model") + + default_settings = OpenAILLMSettings(model=model or "deepseek-chat") + if settings is not None: + default_settings.apply_update(settings) + + super().__init__(api_key=api_key, base_url=base_url, settings=default_settings, **kwargs) def create_client(self, api_key=None, base_url=None, **kwargs): """Create OpenAI-compatible client for DeepSeek API endpoint. diff --git a/src/pipecat/services/elevenlabs/stt.py b/src/pipecat/services/elevenlabs/stt.py index 0cf13121e..d5897b5c5 100644 --- a/src/pipecat/services/elevenlabs/stt.py +++ b/src/pipecat/services/elevenlabs/stt.py @@ -35,7 +35,7 @@ from pipecat.frames.frames import ( VADUserStoppedSpeakingFrame, ) from pipecat.processors.frame_processor import FrameDirection -from pipecat.services.settings import NOT_GIVEN, STTSettings, _NotGiven +from pipecat.services.settings import NOT_GIVEN, STTSettings, _NotGiven, _warn_deprecated_param from pipecat.services.stt_latency import ELEVENLABS_REALTIME_TTFS_P99, ELEVENLABS_TTFS_P99 from pipecat.services.stt_service import SegmentedSTTService, WebsocketSTTService from pipecat.transcriptions.language import Language, resolve_language @@ -228,6 +228,9 @@ class ElevenLabsSTTService(SegmentedSTTService): class InputParams(BaseModel): """Configuration parameters for ElevenLabs STT API. + .. deprecated:: 1.0 + Use ``settings=ElevenLabsSTTSettings(...)`` instead. + Parameters: language: Target language for transcription. tag_audio_events: Whether to include audio events like (laughter), (coughing), in the transcription. @@ -242,9 +245,10 @@ class ElevenLabsSTTService(SegmentedSTTService): api_key: str, aiohttp_session: aiohttp.ClientSession, base_url: str = "https://api.elevenlabs.io", - model: str = "scribe_v2", + model: Optional[str] = None, sample_rate: Optional[int] = None, params: Optional[InputParams] = None, + settings: Optional[ElevenLabsSTTSettings] = None, ttfs_p99_latency: Optional[float] = ELEVENLABS_TTFS_P99, **kwargs, ): @@ -254,25 +258,44 @@ class ElevenLabsSTTService(SegmentedSTTService): api_key: ElevenLabs API key for authentication. aiohttp_session: aiohttp ClientSession for HTTP requests. base_url: Base URL for ElevenLabs API. - model: Model ID for transcription. Defaults to "scribe_v2". + model: Model ID for transcription. + + .. deprecated:: 1.0 + Use ``settings=ElevenLabsSTTSettings(model=...)`` instead. + sample_rate: Audio sample rate in Hz. If not provided, uses the pipeline's rate. params: Configuration parameters for the STT service. + + .. deprecated:: 1.0 + Use ``settings=ElevenLabsSTTSettings(...)`` instead. + + settings: Runtime-updatable settings. When provided alongside deprecated + parameters, ``settings`` values take precedence. ttfs_p99_latency: P99 latency from speech end to final transcript in seconds. Override for your deployment. See https://github.com/pipecat-ai/stt-benchmark **kwargs: Additional arguments passed to SegmentedSTTService. """ - params = params or ElevenLabsSTTService.InputParams() + if model is not None: + _warn_deprecated_param("model", "ElevenLabsSTTSettings", "model") + if params is not None: + _warn_deprecated_param("params", "ElevenLabsSTTSettings") + + _params = params or ElevenLabsSTTService.InputParams() + + default_settings = ElevenLabsSTTSettings( + model=model or "scribe_v2", + language=self.language_to_service_language(_params.language) + if _params.language + else "eng", + tag_audio_events=_params.tag_audio_events, + ) + if settings is not None: + default_settings.apply_update(settings) super().__init__( sample_rate=sample_rate, ttfs_p99_latency=ttfs_p99_latency, - settings=ElevenLabsSTTSettings( - model=model, - language=self.language_to_service_language(params.language) - if params.language - else "eng", - tag_audio_events=params.tag_audio_events, - ), + settings=default_settings, **kwargs, ) @@ -429,6 +452,9 @@ class ElevenLabsRealtimeSTTService(WebsocketSTTService): class InputParams(BaseModel): """Configuration parameters for ElevenLabs Realtime STT API. + .. deprecated:: 1.0 + Use ``settings=ElevenLabsRealtimeSTTSettings(...)`` instead. + Parameters: language_code: ISO-639-1 or ISO-639-3 language code. Leave None for auto-detection. commit_strategy: How to segment speech - manual (Pipecat VAD) or vad (ElevenLabs VAD). @@ -460,9 +486,10 @@ class ElevenLabsRealtimeSTTService(WebsocketSTTService): *, api_key: str, base_url: str = "api.elevenlabs.io", - model: str = "scribe_v2_realtime", + model: Optional[str] = None, sample_rate: Optional[int] = None, params: Optional[InputParams] = None, + settings: Optional[ElevenLabsRealtimeSTTSettings] = None, ttfs_p99_latency: Optional[float] = ELEVENLABS_REALTIME_TTFS_P99, **kwargs, ): @@ -471,32 +498,51 @@ class ElevenLabsRealtimeSTTService(WebsocketSTTService): Args: api_key: ElevenLabs API key for authentication. base_url: Base URL for ElevenLabs WebSocket API. - model: Model ID for transcription. Defaults to "scribe_v2_realtime". + model: Model ID for transcription. + + .. deprecated:: 1.0 + Use ``settings=ElevenLabsRealtimeSTTSettings(model=...)`` instead. + sample_rate: Audio sample rate in Hz. If not provided, uses the pipeline's rate. params: Configuration parameters for the STT service. + + .. deprecated:: 1.0 + Use ``settings=ElevenLabsRealtimeSTTSettings(...)`` instead. + + settings: Runtime-updatable settings. When provided alongside deprecated + parameters, ``settings`` values take precedence. ttfs_p99_latency: P99 latency from speech end to final transcript in seconds. Override for your deployment. See https://github.com/pipecat-ai/stt-benchmark **kwargs: Additional arguments passed to WebsocketSTTService. """ - params = params or ElevenLabsRealtimeSTTService.InputParams() + if model is not None: + _warn_deprecated_param("model", "ElevenLabsRealtimeSTTSettings", "model") + if params is not None: + _warn_deprecated_param("params", "ElevenLabsRealtimeSTTSettings") + + _params = params or ElevenLabsRealtimeSTTService.InputParams() + + default_settings = ElevenLabsRealtimeSTTSettings( + model=model or "scribe_v2_realtime", + language=_params.language_code, + commit_strategy=_params.commit_strategy, + vad_silence_threshold_secs=_params.vad_silence_threshold_secs, + vad_threshold=_params.vad_threshold, + min_speech_duration_ms=_params.min_speech_duration_ms, + min_silence_duration_ms=_params.min_silence_duration_ms, + include_timestamps=_params.include_timestamps, + enable_logging=_params.enable_logging, + include_language_detection=_params.include_language_detection, + ) + if settings is not None: + default_settings.apply_update(settings) super().__init__( sample_rate=sample_rate, ttfs_p99_latency=ttfs_p99_latency, keepalive_timeout=10, keepalive_interval=5, - settings=ElevenLabsRealtimeSTTSettings( - model=model, - language=params.language_code, - commit_strategy=params.commit_strategy, - vad_silence_threshold_secs=params.vad_silence_threshold_secs, - vad_threshold=params.vad_threshold, - min_speech_duration_ms=params.min_speech_duration_ms, - min_silence_duration_ms=params.min_silence_duration_ms, - include_timestamps=params.include_timestamps, - enable_logging=params.enable_logging, - include_language_detection=params.include_language_detection, - ), + settings=default_settings, **kwargs, ) diff --git a/src/pipecat/services/elevenlabs/tts.py b/src/pipecat/services/elevenlabs/tts.py index 1811ed971..b98ce6e1b 100644 --- a/src/pipecat/services/elevenlabs/tts.py +++ b/src/pipecat/services/elevenlabs/tts.py @@ -44,7 +44,7 @@ from pipecat.frames.frames import ( TTSStoppedFrame, ) from pipecat.processors.frame_processor import FrameDirection -from pipecat.services.settings import NOT_GIVEN, TTSSettings, _NotGiven +from pipecat.services.settings import NOT_GIVEN, TTSSettings, _NotGiven, _warn_deprecated_param from pipecat.services.tts_service import ( AudioContextTTSService, TextAggregationMode, @@ -331,6 +331,9 @@ class ElevenLabsTTSService(AudioContextTTSService): class InputParams(BaseModel): """Input parameters for ElevenLabs TTS configuration. + .. deprecated:: 1.0 + Use ``settings=ElevenLabsTTSSettings(...)`` instead. + Parameters: language: Language to use for synthesis. stability: Voice stability control (0.0 to 1.0). @@ -361,11 +364,13 @@ class ElevenLabsTTSService(AudioContextTTSService): self, *, api_key: str, - voice_id: str, - model: str = "eleven_turbo_v2_5", + voice_id: Optional[str] = None, + model: Optional[str] = None, url: str = "wss://api.elevenlabs.io", sample_rate: Optional[int] = None, + pronunciation_dictionary_locators: Optional[List[PronunciationDictionaryLocator]] = None, params: Optional[InputParams] = None, + settings: Optional[ElevenLabsTTSSettings] = None, text_aggregation_mode: Optional[TextAggregationMode] = None, aggregate_sentences: Optional[bool] = None, **kwargs, @@ -375,10 +380,26 @@ class ElevenLabsTTSService(AudioContextTTSService): Args: api_key: ElevenLabs API key for authentication. voice_id: ID of the voice to use for synthesis. + + .. deprecated:: 1.0 + Use ``settings=ElevenLabsTTSSettings(voice=...)`` instead. + model: TTS model to use (e.g., "eleven_turbo_v2_5"). + + .. deprecated:: 1.0 + Use ``settings=ElevenLabsTTSSettings(model=...)`` instead. + url: WebSocket URL for ElevenLabs TTS API. sample_rate: Audio sample rate. If None, uses default. + pronunciation_dictionary_locators: List of pronunciation dictionary + locators to use. params: Additional input parameters for voice customization. + + .. deprecated:: 1.0 + Use ``settings=ElevenLabsTTSSettings(...)`` instead. + + settings: Runtime-updatable settings. When provided alongside deprecated + parameters, ``settings`` values take precedence. text_aggregation_mode: How to aggregate incoming text before synthesis. aggregate_sentences: Whether to aggregate sentences within the TTSService. @@ -387,6 +408,13 @@ class ElevenLabsTTSService(AudioContextTTSService): **kwargs: Additional arguments passed to the parent service. """ + if voice_id is not None: + _warn_deprecated_param("voice_id", "ElevenLabsTTSSettings", "voice") + if model is not None: + _warn_deprecated_param("model", "ElevenLabsTTSSettings", "model") + if params is not None: + _warn_deprecated_param("params", "ElevenLabsTTSSettings") + # By default, we aggregate sentences before sending to TTS. This adds # ~200-300ms of latency per sentence (waiting for the sentence-ending # punctuation token from the LLM). Setting @@ -403,7 +431,26 @@ class ElevenLabsTTSService(AudioContextTTSService): # Finally, ElevenLabs doesn't provide information on when the bot stops # speaking for a while, so we want the parent class to send TTSStopFrame # after a short period not receiving any audio. - params = params or ElevenLabsTTSService.InputParams() + _params = params or ElevenLabsTTSService.InputParams() + + default_settings = ElevenLabsTTSSettings( + model=model or "eleven_turbo_v2_5", + voice=voice_id, + language=( + self.language_to_service_language(_params.language) if _params.language else None + ), + stability=_params.stability, + similarity_boost=_params.similarity_boost, + style=_params.style, + use_speaker_boost=_params.use_speaker_boost, + speed=_params.speed, + auto_mode=str(_params.auto_mode).lower(), + enable_ssml_parsing=_params.enable_ssml_parsing, + enable_logging=_params.enable_logging, + apply_text_normalization=_params.apply_text_normalization, + ) + if settings is not None: + default_settings.apply_update(settings) super().__init__( text_aggregation_mode=text_aggregation_mode, @@ -413,22 +460,7 @@ class ElevenLabsTTSService(AudioContextTTSService): pause_frame_processing=True, supports_word_timestamps=True, sample_rate=sample_rate, - settings=ElevenLabsTTSSettings( - model=model, - voice=voice_id, - language=( - self.language_to_service_language(params.language) if params.language else None - ), - stability=params.stability, - similarity_boost=params.similarity_boost, - style=params.style, - use_speaker_boost=params.use_speaker_boost, - speed=params.speed, - auto_mode=str(params.auto_mode).lower(), - enable_ssml_parsing=params.enable_ssml_parsing, - enable_logging=params.enable_logging, - apply_text_normalization=params.apply_text_normalization, - ), + settings=default_settings, **kwargs, ) @@ -437,7 +469,11 @@ class ElevenLabsTTSService(AudioContextTTSService): self._output_format = "" # initialized in start() self._voice_settings = self._set_voice_settings() - self._pronunciation_dictionary_locators = params.pronunciation_dictionary_locators + self._pronunciation_dictionary_locators = ( + pronunciation_dictionary_locators + if pronunciation_dictionary_locators is not None + else _params.pronunciation_dictionary_locators + ) self._cumulative_time = 0 # Track partial words that span across alignment chunks @@ -871,6 +907,9 @@ class ElevenLabsHttpTTSService(TTSService): class InputParams(BaseModel): """Input parameters for ElevenLabs HTTP TTS configuration. + .. deprecated:: 1.0 + Use ``settings=ElevenLabsHttpTTSSettings(...)`` instead. + Parameters: language: Language to use for synthesis. optimize_streaming_latency: Latency optimization level (0-4). @@ -897,12 +936,14 @@ class ElevenLabsHttpTTSService(TTSService): self, *, api_key: str, - voice_id: str, + voice_id: Optional[str] = None, aiohttp_session: aiohttp.ClientSession, - model: str = "eleven_turbo_v2_5", + model: Optional[str] = None, base_url: str = "https://api.elevenlabs.io", sample_rate: Optional[int] = None, + pronunciation_dictionary_locators: Optional[List[PronunciationDictionaryLocator]] = None, params: Optional[InputParams] = None, + settings: Optional[ElevenLabsHttpTTSSettings] = None, text_aggregation_mode: Optional[TextAggregationMode] = None, aggregate_sentences: Optional[bool] = None, **kwargs, @@ -912,11 +953,27 @@ class ElevenLabsHttpTTSService(TTSService): Args: api_key: ElevenLabs API key for authentication. voice_id: ID of the voice to use for synthesis. + + .. deprecated:: 1.0 + Use ``settings=ElevenLabsHttpTTSSettings(voice=...)`` instead. + aiohttp_session: aiohttp ClientSession for HTTP requests. model: TTS model to use (e.g., "eleven_turbo_v2_5"). + + .. deprecated:: 1.0 + Use ``settings=ElevenLabsHttpTTSSettings(model=...)`` instead. + base_url: Base URL for ElevenLabs HTTP API. sample_rate: Audio sample rate. If None, uses default. + pronunciation_dictionary_locators: List of pronunciation dictionary + locators to use. params: Additional input parameters for voice customization. + + .. deprecated:: 1.0 + Use ``settings=ElevenLabsHttpTTSSettings(...)`` instead. + + settings: Runtime-updatable settings. When provided alongside deprecated + parameters, ``settings`` values take precedence. text_aggregation_mode: How to aggregate incoming text before synthesis. aggregate_sentences: Whether to aggregate sentences within the TTSService. @@ -925,7 +982,31 @@ class ElevenLabsHttpTTSService(TTSService): **kwargs: Additional arguments passed to the parent service. """ - params = params or ElevenLabsHttpTTSService.InputParams() + if voice_id is not None: + _warn_deprecated_param("voice_id", "ElevenLabsHttpTTSSettings", "voice") + if model is not None: + _warn_deprecated_param("model", "ElevenLabsHttpTTSSettings", "model") + if params is not None: + _warn_deprecated_param("params", "ElevenLabsHttpTTSSettings") + + _params = params or ElevenLabsHttpTTSService.InputParams() + + default_settings = ElevenLabsHttpTTSSettings( + model=model or "eleven_turbo_v2_5", + voice=voice_id, + language=( + self.language_to_service_language(_params.language) if _params.language else None + ), + optimize_streaming_latency=_params.optimize_streaming_latency, + stability=_params.stability, + similarity_boost=_params.similarity_boost, + style=_params.style, + use_speaker_boost=_params.use_speaker_boost, + speed=_params.speed, + apply_text_normalization=_params.apply_text_normalization, + ) + if settings is not None: + default_settings.apply_update(settings) super().__init__( text_aggregation_mode=text_aggregation_mode, @@ -934,20 +1015,7 @@ class ElevenLabsHttpTTSService(TTSService): push_stop_frames=True, supports_word_timestamps=True, sample_rate=sample_rate, - settings=ElevenLabsHttpTTSSettings( - model=model, - voice=voice_id, - language=self.language_to_service_language(params.language) - if params.language - else None, - optimize_streaming_latency=params.optimize_streaming_latency, - stability=params.stability, - similarity_boost=params.similarity_boost, - style=params.style, - use_speaker_boost=params.use_speaker_boost, - speed=params.speed, - apply_text_normalization=params.apply_text_normalization, - ), + settings=default_settings, **kwargs, ) @@ -957,7 +1025,11 @@ class ElevenLabsHttpTTSService(TTSService): self._output_format = "" # initialized in start() self._voice_settings = self._set_voice_settings() - self._pronunciation_dictionary_locators = params.pronunciation_dictionary_locators + self._pronunciation_dictionary_locators = ( + pronunciation_dictionary_locators + if pronunciation_dictionary_locators is not None + else _params.pronunciation_dictionary_locators + ) # Track cumulative time to properly sequence word timestamps across utterances self._cumulative_time = 0 diff --git a/src/pipecat/services/fal/image.py b/src/pipecat/services/fal/image.py index 3de48a984..8847e3f24 100644 --- a/src/pipecat/services/fal/image.py +++ b/src/pipecat/services/fal/image.py @@ -23,7 +23,7 @@ from pydantic import BaseModel from pipecat.frames.frames import ErrorFrame, Frame, URLImageRawFrame from pipecat.services.image_service import ImageGenService -from pipecat.services.settings import ImageGenSettings +from pipecat.services.settings import ImageGenSettings, _warn_deprecated_param @dataclass @@ -68,8 +68,9 @@ class FalImageGenService(ImageGenService): *, params: InputParams, aiohttp_session: aiohttp.ClientSession, - model: str = "fal-ai/fast-sdxl", + model: Optional[str] = None, key: Optional[str] = None, + settings: Optional[FalImageGenSettings] = None, **kwargs, ): """Initialize the FalImageGenService. @@ -78,10 +79,23 @@ class FalImageGenService(ImageGenService): params: Input parameters for image generation configuration. aiohttp_session: HTTP client session for downloading generated images. model: The Fal.ai model to use for generation. Defaults to "fal-ai/fast-sdxl". + + .. deprecated:: 1.0 + Use ``settings=FalImageGenSettings(model=...)`` instead. + key: Optional API key for Fal.ai. If provided, sets FAL_KEY environment variable. + settings: Runtime-updatable settings. When provided alongside deprecated + parameters, ``settings`` values take precedence. **kwargs: Additional arguments passed to parent ImageGenService. """ - super().__init__(settings=FalImageGenSettings(model=model), **kwargs) + if model is not None: + _warn_deprecated_param("model", "FalImageGenSettings", "model") + + default_settings = FalImageGenSettings(model=model or "fal-ai/fast-sdxl") + if settings is not None: + default_settings.apply_update(settings) + + super().__init__(settings=default_settings, **kwargs) self._params = params self._aiohttp_session = aiohttp_session self._api_key = key or os.getenv("FAL_KEY", "") diff --git a/src/pipecat/services/fal/stt.py b/src/pipecat/services/fal/stt.py index 8a82904d7..d2c1441d0 100644 --- a/src/pipecat/services/fal/stt.py +++ b/src/pipecat/services/fal/stt.py @@ -20,7 +20,7 @@ from loguru import logger from pydantic import BaseModel from pipecat.frames.frames import ErrorFrame, Frame, TranscriptionFrame -from pipecat.services.settings import NOT_GIVEN, STTSettings, _NotGiven +from pipecat.services.settings import NOT_GIVEN, STTSettings, _NotGiven, _warn_deprecated_param from pipecat.services.stt_latency import FAL_TTFS_P99 from pipecat.services.stt_service import SegmentedSTTService from pipecat.transcriptions.language import Language, resolve_language @@ -169,6 +169,9 @@ class FalSTTService(SegmentedSTTService): class InputParams(BaseModel): """Configuration parameters for Fal's Wizper API. + .. deprecated:: 1.0 + Use ``settings=FalSTTSettings(...)`` instead. + Parameters: language: Language of the audio input. Defaults to English. task: Task to perform ('transcribe' or 'translate'). Defaults to 'transcribe'. @@ -188,6 +191,7 @@ class FalSTTService(SegmentedSTTService): aiohttp_session: Optional[aiohttp.ClientSession] = None, sample_rate: Optional[int] = None, params: Optional[InputParams] = None, + settings: Optional[FalSTTSettings] = None, ttfs_p99_latency: Optional[float] = FAL_TTFS_P99, **kwargs, ): @@ -199,24 +203,37 @@ class FalSTTService(SegmentedSTTService): If not provided, a session will be created and managed internally. sample_rate: Audio sample rate in Hz. If not provided, uses the pipeline's rate. params: Configuration parameters for the Wizper API. + + .. deprecated:: 1.0 + Use ``settings=FalSTTSettings(...)`` instead. + + settings: Runtime-updatable settings. When provided alongside deprecated + parameters, ``settings`` values take precedence. ttfs_p99_latency: P99 latency from speech end to final transcript in seconds. Override for your deployment. See https://github.com/pipecat-ai/stt-benchmark **kwargs: Additional arguments passed to SegmentedSTTService. """ - params = params or FalSTTService.InputParams() + if params is not None: + _warn_deprecated_param("params", "FalSTTSettings") + + _params = params or FalSTTService.InputParams() + + default_settings = FalSTTSettings( + model=None, + language=self.language_to_service_language(_params.language) + if _params.language + else "en", + task=_params.task, + chunk_level=_params.chunk_level, + version=_params.version, + ) + if settings is not None: + default_settings.apply_update(settings) super().__init__( sample_rate=sample_rate, ttfs_p99_latency=ttfs_p99_latency, - settings=FalSTTSettings( - model=None, - language=self.language_to_service_language(params.language) - if params.language - else "en", - task=params.task, - chunk_level=params.chunk_level, - version=params.version, - ), + settings=default_settings, **kwargs, ) diff --git a/src/pipecat/services/fireworks/llm.py b/src/pipecat/services/fireworks/llm.py index 92deb00b9..9fa9e44bd 100644 --- a/src/pipecat/services/fireworks/llm.py +++ b/src/pipecat/services/fireworks/llm.py @@ -6,10 +6,14 @@ """Fireworks AI service implementation using OpenAI-compatible interface.""" +from typing import Optional + from loguru import logger from pipecat.adapters.services.open_ai_adapter import OpenAILLMInvocationParams +from pipecat.services.openai.base_llm import OpenAILLMSettings from pipecat.services.openai.llm import OpenAILLMService +from pipecat.services.settings import _warn_deprecated_param class FireworksLLMService(OpenAILLMService): @@ -23,8 +27,9 @@ class FireworksLLMService(OpenAILLMService): self, *, api_key: str, - model: str = "accounts/fireworks/models/firefunction-v2", + model: Optional[str] = None, base_url: str = "https://api.fireworks.ai/inference/v1", + settings: Optional[OpenAILLMSettings] = None, **kwargs, ): """Initialize the Fireworks LLM service. @@ -32,10 +37,25 @@ class FireworksLLMService(OpenAILLMService): Args: api_key: The API key for accessing Fireworks AI. model: The model identifier to use. Defaults to "accounts/fireworks/models/firefunction-v2". + + .. deprecated:: 1.0 + Use ``settings=OpenAILLMSettings(model=...)`` instead. + base_url: The base URL for Fireworks API. Defaults to "https://api.fireworks.ai/inference/v1". + settings: Runtime-updatable settings. When provided alongside deprecated + parameters, ``settings`` values take precedence. **kwargs: Additional keyword arguments passed to OpenAILLMService. """ - super().__init__(api_key=api_key, base_url=base_url, model=model, **kwargs) + if model is not None: + _warn_deprecated_param("model", "OpenAILLMSettings", "model") + + default_settings = OpenAILLMSettings( + model=model or "accounts/fireworks/models/firefunction-v2" + ) + if settings is not None: + default_settings.apply_update(settings) + + super().__init__(api_key=api_key, base_url=base_url, settings=default_settings, **kwargs) def create_client(self, api_key=None, base_url=None, **kwargs): """Create OpenAI-compatible client for Fireworks API endpoint. diff --git a/src/pipecat/services/fish/tts.py b/src/pipecat/services/fish/tts.py index 9f9d753de..e95cceebd 100644 --- a/src/pipecat/services/fish/tts.py +++ b/src/pipecat/services/fish/tts.py @@ -29,7 +29,7 @@ from pipecat.frames.frames import ( TTSStoppedFrame, ) from pipecat.processors.frame_processor import FrameDirection -from pipecat.services.settings import NOT_GIVEN, TTSSettings, _NotGiven +from pipecat.services.settings import NOT_GIVEN, TTSSettings, _NotGiven, _warn_deprecated_param from pipecat.services.tts_service import InterruptibleTTSService from pipecat.transcriptions.language import Language from pipecat.utils.tracing.service_decorators import traced_tts @@ -95,6 +95,9 @@ class FishAudioTTSService(InterruptibleTTSService): class InputParams(BaseModel): """Input parameters for Fish Audio TTS configuration. + .. deprecated:: 1.0 + Use ``settings=FishAudioTTSSettings(...)`` instead. + Parameters: language: Language for synthesis. Defaults to English. latency: Latency mode ("normal" or "balanced"). Defaults to "normal". @@ -115,10 +118,11 @@ class FishAudioTTSService(InterruptibleTTSService): api_key: str, reference_id: Optional[str] = None, # This is the voice ID model: Optional[str] = None, # Deprecated - model_id: str = "s1", + model_id: Optional[str] = None, output_format: FishAudioOutputFormat = "pcm", sample_rate: Optional[int] = None, params: Optional[InputParams] = None, + settings: Optional[FishAudioTTSSettings] = None, **kwargs, ): """Initialize the Fish Audio TTS service. @@ -126,19 +130,40 @@ class FishAudioTTSService(InterruptibleTTSService): Args: api_key: Fish Audio API key for authentication. reference_id: Reference ID of the voice model to use for synthesis. + + .. deprecated:: 1.0 + Use ``settings=FishAudioTTSSettings(voice=...)`` instead. + model: Deprecated. Reference ID of the voice model to use for synthesis. - .. deprecated:: 0.0.74 - The `model` parameter is deprecated and will be removed in version 0.1.0. - Use `reference_id` instead to specify the voice model. + .. deprecated:: 0.0.74 + The ``model`` parameter is deprecated and will be removed in version 0.1.0. + Use ``reference_id`` instead to specify the voice model. + + model_id: Specify which Fish Audio TTS model to use (e.g. "s1"). + + .. deprecated:: 1.0 + Use ``settings=FishAudioTTSSettings(model=...)`` instead. - model_id: Specify which Fish Audio TTS model to use (e.g. "s1") output_format: Audio output format. Defaults to "pcm". sample_rate: Audio sample rate. If None, uses default. params: Additional input parameters for voice customization. + + .. deprecated:: 1.0 + Use ``settings=FishAudioTTSSettings(...)`` instead. + + settings: Runtime-updatable settings. When provided alongside deprecated + parameters, ``settings`` values take precedence. **kwargs: Additional arguments passed to the parent service. """ - params = params or FishAudioTTSService.InputParams() + if reference_id is not None: + _warn_deprecated_param("reference_id", "FishAudioTTSSettings", "voice") + if model_id is not None: + _warn_deprecated_param("model_id", "FishAudioTTSSettings", "model") + if params is not None: + _warn_deprecated_param("params", "FishAudioTTSSettings") + + _params = params or FishAudioTTSService.InputParams() # Validation for model and reference_id parameters if model and reference_id: @@ -146,9 +171,6 @@ class FishAudioTTSService(InterruptibleTTSService): "Cannot specify both 'model' and 'reference_id'. Use 'reference_id' only." ) - if model is None and reference_id is None: - raise ValueError("Must specify 'reference_id' (or deprecated 'model') parameter.") - if model: import warnings @@ -162,21 +184,25 @@ class FishAudioTTSService(InterruptibleTTSService): ) reference_id = model + default_settings = FishAudioTTSSettings( + model=model_id or "s1", + voice=reference_id, + fish_sample_rate=0, + latency=_params.latency, + format=output_format, + normalize=_params.normalize, + prosody_speed=_params.prosody_speed, + prosody_volume=_params.prosody_volume, + reference_id=reference_id, + ) + if settings is not None: + default_settings.apply_update(settings) + super().__init__( push_stop_frames=True, pause_frame_processing=True, sample_rate=sample_rate, - settings=FishAudioTTSSettings( - model=model_id, - voice=reference_id, - fish_sample_rate=0, - latency=params.latency, - format=output_format, - normalize=params.normalize, - prosody_speed=params.prosody_speed, - prosody_volume=params.prosody_volume, - reference_id=reference_id, - ), + settings=default_settings, **kwargs, ) diff --git a/src/pipecat/services/gladia/stt.py b/src/pipecat/services/gladia/stt.py index bba554b4a..f2376d93e 100644 --- a/src/pipecat/services/gladia/stt.py +++ b/src/pipecat/services/gladia/stt.py @@ -39,7 +39,7 @@ from pipecat.services.gladia.config import ( PreProcessingConfig, RealtimeProcessingConfig, ) -from pipecat.services.settings import NOT_GIVEN, STTSettings, _NotGiven +from pipecat.services.settings import NOT_GIVEN, STTSettings, _NotGiven, _warn_deprecated_param from pipecat.services.stt_latency import GLADIA_TTFS_P99 from pipecat.services.stt_service import WebsocketSTTService from pipecat.transcriptions.language import Language, resolve_language @@ -249,10 +249,11 @@ class GladiaSTTService(WebsocketSTTService): url: str = "https://api.gladia.io/v2/live", confidence: Optional[float] = None, sample_rate: Optional[int] = None, - model: str = "solaria-1", + model: Optional[str] = None, params: Optional[GladiaInputParams] = None, max_buffer_size: int = 1024 * 1024 * 20, # 20MB default buffer should_interrupt: bool = True, + settings: Optional[GladiaSTTSettings] = None, ttfs_p99_latency: Optional[float] = GLADIA_TTFS_P99, **kwargs, ): @@ -269,15 +270,30 @@ class GladiaSTTService(WebsocketSTTService): No confidence threshold is applied. sample_rate: Audio sample rate in Hz. If None, uses service default. - model: Model to use for transcription. Defaults to "solaria-1". + model: Model to use for transcription. + + .. deprecated:: 1.0 + Use ``settings=GladiaSTTSettings(model=...)`` instead. + params: Additional configuration parameters for Gladia service. + + .. deprecated:: 1.0 + Use ``settings=GladiaSTTSettings(...)`` instead. + max_buffer_size: Maximum size of audio buffer in bytes. Defaults to 20MB. should_interrupt: Determine whether the bot should be interrupted when Gladia VAD detects user speech. Defaults to True. + settings: Runtime-updatable settings. When provided alongside deprecated + parameters, ``settings`` values take precedence. ttfs_p99_latency: P99 latency from speech end to final transcript in seconds. Override for your deployment. See https://github.com/pipecat-ai/stt-benchmark **kwargs: Additional arguments passed to the STTService parent class. """ + if model is not None: + _warn_deprecated_param("model", "GladiaSTTSettings", "model") + if params is not None: + _warn_deprecated_param("params", "GladiaSTTSettings") + params = params or GladiaInputParams() if params.language is not None: @@ -307,26 +323,30 @@ class GladiaSTTService(WebsocketSTTService): if language_code: language_config = LanguageConfig(languages=[language_code], code_switching=False) + default_settings = GladiaSTTSettings( + model=model or "solaria-1", + language=None, + encoding=params.encoding, + bit_depth=params.bit_depth, + channels=params.channels, + custom_metadata=params.custom_metadata, + endpointing=params.endpointing, + maximum_duration_without_endpointing=params.maximum_duration_without_endpointing, + language_config=language_config, + pre_processing=params.pre_processing, + realtime_processing=params.realtime_processing, + messages_config=params.messages_config, + enable_vad=params.enable_vad, + ) + if settings is not None: + default_settings.apply_update(settings) + super().__init__( sample_rate=sample_rate, ttfs_p99_latency=ttfs_p99_latency, keepalive_timeout=20, keepalive_interval=5, - settings=GladiaSTTSettings( - model=model, - language=None, - encoding=params.encoding, - bit_depth=params.bit_depth, - channels=params.channels, - custom_metadata=params.custom_metadata, - endpointing=params.endpointing, - maximum_duration_without_endpointing=params.maximum_duration_without_endpointing, - language_config=language_config, - pre_processing=params.pre_processing, - realtime_processing=params.realtime_processing, - messages_config=params.messages_config, - enable_vad=params.enable_vad, - ), + settings=default_settings, **kwargs, ) diff --git a/src/pipecat/services/google/gemini_live/llm.py b/src/pipecat/services/google/gemini_live/llm.py index 2ed11c739..518684dfb 100644 --- a/src/pipecat/services/google/gemini_live/llm.py +++ b/src/pipecat/services/google/gemini_live/llm.py @@ -76,7 +76,7 @@ from pipecat.services.openai.llm import ( OpenAIAssistantContextAggregator, OpenAIUserContextAggregator, ) -from pipecat.services.settings import NOT_GIVEN, LLMSettings, _NotGiven +from pipecat.services.settings import NOT_GIVEN, LLMSettings, _NotGiven, _warn_deprecated_param from pipecat.transcriptions.language import Language, resolve_language from pipecat.utils.string import match_endofsentence from pipecat.utils.time import time_now_iso8601 @@ -552,6 +552,9 @@ class ContextWindowCompressionParams(BaseModel): class InputParams(BaseModel): """Input parameters for Gemini Live generation. + .. deprecated:: + Use ``GeminiLiveLLMSettings`` instead. + Parameters: frequency_penalty: Frequency penalty for generation (0.0-2.0). Defaults to None. max_tokens: Maximum tokens to generate. Must be >= 1. Defaults to 4096. @@ -647,13 +650,14 @@ class GeminiLiveLLMService(LLMService): *, api_key: str, base_url: Optional[str] = None, - model="models/gemini-2.5-flash-native-audio-preview-12-2025", + model: Optional[str] = None, voice_id: str = "Charon", start_audio_paused: bool = False, start_video_paused: bool = False, system_instruction: Optional[str] = None, tools: Optional[Union[List[dict], ToolsSchema]] = None, params: Optional[InputParams] = None, + settings: Optional[GeminiLiveLLMSettings] = None, inference_on_context_initialization: bool = True, file_api_base_url: str = "https://generativelanguage.googleapis.com/v1beta/files", http_options: Optional[HttpOptions] = None, @@ -670,13 +674,23 @@ class GeminiLiveLLMService(LLMService): Please use `http_options` to customize requests made by the API client. - model: Model identifier to use. Defaults to "models/gemini-2.5-flash-native-audio-preview-12-2025". + model: Model identifier to use. + + .. deprecated:: + Use ``settings=GeminiLiveLLMSettings(model=...)`` instead. + voice_id: TTS voice identifier. Defaults to "Charon". start_audio_paused: Whether to start with audio input paused. Defaults to False. start_video_paused: Whether to start with video input paused. Defaults to False. system_instruction: System prompt for the model. Defaults to None. tools: Tools/functions available to the model. Defaults to None. - params: Configuration parameters for the model. Defaults to InputParams(). + params: Configuration parameters for the model. + + .. deprecated:: + Use ``settings=GeminiLiveLLMSettings(...)`` instead. + + settings: Gemini Live LLM settings. If provided together with deprecated + top-level parameters, the ``settings`` values take precedence. inference_on_context_initialization: Whether to generate a response when context is first set. Defaults to True. file_api_base_url: Base URL for the Gemini File API. Defaults to the official endpoint. @@ -694,43 +708,49 @@ class GeminiLiveLLMService(LLMService): DeprecationWarning, stacklevel=2, ) + if model is not None: + _warn_deprecated_param("model", "GeminiLiveLLMSettings", "model") + if params is not None: + _warn_deprecated_param("params", "GeminiLiveLLMSettings") - params = params or InputParams() + _params = params or InputParams() + + default_settings = GeminiLiveLLMSettings( + model=model or "models/gemini-2.5-flash-native-audio-preview-12-2025", + frequency_penalty=_params.frequency_penalty, + max_tokens=_params.max_tokens, + presence_penalty=_params.presence_penalty, + temperature=_params.temperature, + top_k=_params.top_k, + top_p=_params.top_p, + seed=None, + filter_incomplete_user_turns=False, + user_turn_completion_config=None, + modalities=_params.modalities, + language=language_to_gemini_language(_params.language) if _params.language else "en-US", + media_resolution=_params.media_resolution, + vad=_params.vad, + context_window_compression=_params.context_window_compression.model_dump() + if _params.context_window_compression + else {}, + thinking=_params.thinking or {}, + enable_affective_dialog=_params.enable_affective_dialog or False, + proactivity=_params.proactivity or {}, + extra=_params.extra if isinstance(_params.extra, dict) else {}, + ) + if settings is not None: + default_settings.apply_update(settings) super().__init__( base_url=base_url, - settings=GeminiLiveLLMSettings( - model=model, - frequency_penalty=params.frequency_penalty, - max_tokens=params.max_tokens, - presence_penalty=params.presence_penalty, - temperature=params.temperature, - top_k=params.top_k, - top_p=params.top_p, - seed=None, - filter_incomplete_user_turns=False, - user_turn_completion_config=None, - modalities=params.modalities, - language=language_to_gemini_language(params.language) - if params.language - else "en-US", - media_resolution=params.media_resolution, - vad=params.vad, - context_window_compression=params.context_window_compression.model_dump() - if params.context_window_compression - else {}, - thinking=params.thinking or {}, - enable_affective_dialog=params.enable_affective_dialog or False, - proactivity=params.proactivity or {}, - extra=params.extra if isinstance(params.extra, dict) else {}, - ), + settings=default_settings, **kwargs, ) self._last_sent_time = 0 self._base_url = base_url self._voice_id = voice_id - self._language_code = params.language + self._language_code = _params.language self._system_instruction_from_init = system_instruction self._tools_from_init = tools @@ -760,11 +780,11 @@ class GeminiLiveLLMService(LLMService): self._sample_rate = 24000 - self._language = params.language + self._language = _params.language self._language_code = ( - language_to_gemini_language(params.language) if params.language else "en-US" + language_to_gemini_language(_params.language) if _params.language else "en-US" ) - self._vad_params = params.vad + self._vad_params = _params.vad # Reconnection tracking self._consecutive_failures = 0 diff --git a/src/pipecat/services/google/gemini_live/llm_vertex.py b/src/pipecat/services/google/gemini_live/llm_vertex.py index bb61033b3..eadcb66d1 100644 --- a/src/pipecat/services/google/gemini_live/llm_vertex.py +++ b/src/pipecat/services/google/gemini_live/llm_vertex.py @@ -19,9 +19,12 @@ from loguru import logger from pipecat.adapters.schemas.tools_schema import ToolsSchema from pipecat.services.google.gemini_live.llm import ( GeminiLiveLLMService, + GeminiLiveLLMSettings, HttpOptions, InputParams, + language_to_gemini_language, ) +from pipecat.services.settings import _warn_deprecated_param try: from google.auth import default @@ -51,13 +54,14 @@ class GeminiLiveVertexLLMService(GeminiLiveLLMService): credentials_path: Optional[str] = None, location: str, project_id: str, - model="google/gemini-live-2.5-flash-native-audio", + model: Optional[str] = None, voice_id: str = "Charon", start_audio_paused: bool = False, start_video_paused: bool = False, system_instruction: Optional[str] = None, tools: Optional[Union[List[dict], ToolsSchema]] = None, params: Optional[InputParams] = None, + settings: Optional[GeminiLiveLLMSettings] = None, inference_on_context_initialization: bool = True, file_api_base_url: str = "https://generativelanguage.googleapis.com/v1beta/files", http_options: Optional[HttpOptions] = None, @@ -70,7 +74,11 @@ class GeminiLiveVertexLLMService(GeminiLiveLLMService): credentials_path: Path to the service account JSON file. location: GCP region for Vertex AI endpoint (e.g., "us-east4"). project_id: Google Cloud project ID. - model: Model identifier to use. Defaults to "models/gemini-live-2.5-flash-native-audio". + model: Model identifier to use. + + .. deprecated:: + Use ``settings=GeminiLiveLLMSettings(model=...)`` instead. + voice_id: TTS voice identifier. Defaults to "Charon". start_audio_paused: Whether to start with audio input paused. Defaults to False. start_video_paused: Whether to start with video input paused. Defaults to False. @@ -78,6 +86,12 @@ class GeminiLiveVertexLLMService(GeminiLiveLLMService): tools: Tools/functions available to the model. Defaults to None. params: Configuration parameters for the model along with Vertex AI location and project ID. + + .. deprecated:: + Use ``settings=GeminiLiveLLMSettings(...)`` instead. + + settings: Gemini Live LLM settings. If provided together with deprecated + top-level parameters, the ``settings`` values take precedence. inference_on_context_initialization: Whether to generate a response when context is first set. Defaults to True. file_api_base_url: Base URL for the Gemini File API. Defaults to the official endpoint. @@ -95,24 +109,59 @@ class GeminiLiveVertexLLMService(GeminiLiveLLMService): "Invalid parameter 'api_key'. Use 'credentials' or 'credentials_path' for Vertex AI authentication." ) + if model is not None: + _warn_deprecated_param("model", "GeminiLiveLLMSettings", "model") + if params is not None: + _warn_deprecated_param("params", "GeminiLiveLLMSettings") + # These need to be set before calling super().__init__() because # super().__init__() invokes create_client(), which needs these. self._credentials = self._get_credentials(credentials, credentials_path) self._project_id = project_id self._location = location - # Call parent constructor with the obtained API key + # Build default_settings from deprecated args, then apply settings delta. + # We pass settings= to super() instead of model=/params= to avoid + # double deprecation warnings from the parent. + _params = params or InputParams() + + default_settings = GeminiLiveLLMSettings( + model=model or "google/gemini-live-2.5-flash-native-audio", + frequency_penalty=_params.frequency_penalty, + max_tokens=_params.max_tokens, + presence_penalty=_params.presence_penalty, + temperature=_params.temperature, + top_k=_params.top_k, + top_p=_params.top_p, + seed=None, + filter_incomplete_user_turns=False, + user_turn_completion_config=None, + modalities=_params.modalities, + language=language_to_gemini_language(_params.language) if _params.language else "en-US", + media_resolution=_params.media_resolution, + vad=_params.vad, + context_window_compression=_params.context_window_compression.model_dump() + if _params.context_window_compression + else {}, + thinking=_params.thinking or {}, + enable_affective_dialog=_params.enable_affective_dialog or False, + proactivity=_params.proactivity or {}, + extra=_params.extra if isinstance(_params.extra, dict) else {}, + ) + if settings is not None: + default_settings.apply_update(settings) + + # Call parent constructor with the obtained settings super().__init__( # api_key is required by parent class, but actually not used with # Vertex api_key="dummy", - model=model, voice_id=voice_id, start_audio_paused=start_audio_paused, start_video_paused=start_video_paused, system_instruction=system_instruction, tools=tools, - params=params, + settings=default_settings, inference_on_context_initialization=inference_on_context_initialization, file_api_base_url=file_api_base_url, http_options=http_options, diff --git a/src/pipecat/services/google/image.py b/src/pipecat/services/google/image.py index e69faf65e..3d7cf8c94 100644 --- a/src/pipecat/services/google/image.py +++ b/src/pipecat/services/google/image.py @@ -26,7 +26,7 @@ from pydantic import BaseModel, Field from pipecat.frames.frames import ErrorFrame, Frame, URLImageRawFrame from pipecat.services.google.utils import update_google_client_http_options from pipecat.services.image_service import ImageGenService -from pipecat.services.settings import ImageGenSettings +from pipecat.services.settings import ImageGenSettings, _warn_deprecated_param try: from google import genai @@ -73,18 +73,33 @@ class GoogleImageGenService(ImageGenService): api_key: str, params: Optional[InputParams] = None, http_options: Optional[Any] = None, + settings: Optional[GoogleImageGenSettings] = None, **kwargs, ): """Initialize the GoogleImageGenService with API key and parameters. Args: api_key: Google AI API key for authentication. - params: Configuration parameters for image generation. Defaults to InputParams(). + params: Configuration parameters for image generation. + + .. deprecated:: 1.0 + Use ``settings=GoogleImageGenSettings(model=...)`` instead. + http_options: HTTP options for the client. + settings: Runtime-updatable settings. When provided alongside deprecated + parameters, ``settings`` values take precedence. **kwargs: Additional arguments passed to the parent ImageGenService. """ + if params is not None: + _warn_deprecated_param("params", "GoogleImageGenSettings") + params = params or GoogleImageGenService.InputParams() - super().__init__(settings=GoogleImageGenSettings(model=params.model), **kwargs) + + default_settings = GoogleImageGenSettings(model=params.model) + if settings is not None: + default_settings.apply_update(settings) + + super().__init__(settings=default_settings, **kwargs) self._params = params # Add client header diff --git a/src/pipecat/services/google/llm.py b/src/pipecat/services/google/llm.py index 37ccfae9a..5d5a87188 100644 --- a/src/pipecat/services/google/llm.py +++ b/src/pipecat/services/google/llm.py @@ -58,7 +58,13 @@ from pipecat.services.openai.llm import ( OpenAIAssistantContextAggregator, OpenAIUserContextAggregator, ) -from pipecat.services.settings import NOT_GIVEN, LLMSettings, _NotGiven, is_given +from pipecat.services.settings import ( + NOT_GIVEN, + LLMSettings, + _NotGiven, + _warn_deprecated_param, + is_given, +) from pipecat.utils.tracing.service_decorators import traced_llm # Suppress gRPC fork warnings @@ -748,6 +754,9 @@ class GoogleLLMService(LLMService): class InputParams(BaseModel): """Input parameters for Google AI models. + .. deprecated:: + Use ``settings=GoogleLLMSettings(...)`` instead. + Parameters: max_tokens: Maximum number of tokens to generate. temperature: Sampling temperature between 0.0 and 2.0. @@ -773,8 +782,9 @@ class GoogleLLMService(LLMService): self, *, api_key: str, - model: str = "gemini-2.5-flash", + model: Optional[str] = None, params: Optional[InputParams] = None, + settings: Optional[GoogleLLMSettings] = None, system_instruction: Optional[str] = None, tools: Optional[List[Dict[str, Any]]] = None, tool_config: Optional[Dict[str, Any]] = None, @@ -785,33 +795,50 @@ class GoogleLLMService(LLMService): Args: api_key: Google AI API key for authentication. - model: Model name to use. Defaults to "gemini-2.0-flash". - params: Input parameters for the model. + model: Model name to use. + + .. deprecated:: + Use ``settings=GoogleLLMSettings(model=...)`` instead. + + params: Optional model parameters for inference. + + .. deprecated:: + Use ``settings=GoogleLLMSettings(...)`` instead. + + settings: Runtime-updatable settings for this service. When both + deprecated parameters and *settings* are provided, *settings* + values take precedence. system_instruction: System instruction/prompt for the model. tools: List of available tools/functions. tool_config: Configuration for tool usage. http_options: HTTP options for the client. **kwargs: Additional arguments passed to parent class. """ - params = params or GoogleLLMService.InputParams() + if model is not None: + _warn_deprecated_param("model", "GoogleLLMSettings", "model") + if params is not None: + _warn_deprecated_param("params", "GoogleLLMSettings") - super().__init__( - settings=GoogleLLMSettings( - model=model, - max_tokens=params.max_tokens, - temperature=params.temperature, - top_k=params.top_k, - top_p=params.top_p, - frequency_penalty=None, - presence_penalty=None, - seed=None, - filter_incomplete_user_turns=False, - user_turn_completion_config=None, - thinking=params.thinking, - extra=params.extra if isinstance(params.extra, dict) else {}, - ), - **kwargs, + _params = params or GoogleLLMService.InputParams() + + default_settings = GoogleLLMSettings( + model=model or "gemini-2.5-flash", + max_tokens=_params.max_tokens, + temperature=_params.temperature, + top_k=_params.top_k, + top_p=_params.top_p, + frequency_penalty=None, + presence_penalty=None, + seed=None, + filter_incomplete_user_turns=False, + user_turn_completion_config=None, + thinking=_params.thinking, + extra=_params.extra if isinstance(_params.extra, dict) else {}, ) + if settings is not None: + default_settings.apply_update(settings) + + super().__init__(settings=default_settings, **kwargs) self._api_key = api_key self._system_instruction = system_instruction diff --git a/src/pipecat/services/google/llm_openai.py b/src/pipecat/services/google/llm_openai.py index 5d396b583..22703ae55 100644 --- a/src/pipecat/services/google/llm_openai.py +++ b/src/pipecat/services/google/llm_openai.py @@ -12,6 +12,7 @@ API format through Google's Gemini API OpenAI compatibility layer. import json import os +from typing import Optional from openai import AsyncStream from openai.types.chat import ChatCompletionChunk @@ -26,7 +27,9 @@ from loguru import logger from pipecat.frames.frames import LLMTextFrame from pipecat.metrics.metrics import LLMTokenUsage from pipecat.processors.aggregators.openai_llm_context import OpenAILLMContext +from pipecat.services.openai.base_llm import OpenAILLMSettings from pipecat.services.openai.llm import OpenAILLMService +from pipecat.services.settings import _warn_deprecated_param class GoogleLLMOpenAIBetaService(OpenAILLMService): @@ -52,7 +55,8 @@ class GoogleLLMOpenAIBetaService(OpenAILLMService): *, api_key: str, base_url: str = "https://generativelanguage.googleapis.com/v1beta/openai/", - model: str = "gemini-2.0-flash", + model: Optional[str] = None, + settings: Optional[OpenAILLMSettings] = None, **kwargs, ): """Initialize the Google LLM service. @@ -61,6 +65,12 @@ class GoogleLLMOpenAIBetaService(OpenAILLMService): api_key: Google API key for authentication. base_url: Base URL for Google's OpenAI-compatible API. model: Google model name to use (e.g., "gemini-2.0-flash"). + + .. deprecated:: 1.0 + Use ``settings=OpenAILLMSettings(model=...)`` instead. + + settings: Runtime-updatable settings. When provided alongside deprecated + parameters, ``settings`` values take precedence. **kwargs: Additional arguments passed to the parent OpenAILLMService. """ import warnings @@ -74,7 +84,14 @@ class GoogleLLMOpenAIBetaService(OpenAILLMService): stacklevel=2, ) - super().__init__(api_key=api_key, base_url=base_url, model=model, **kwargs) + if model is not None: + _warn_deprecated_param("model", "OpenAILLMSettings", "model") + + default_settings = OpenAILLMSettings(model=model or "gemini-2.0-flash") + if settings is not None: + default_settings.apply_update(settings) + + super().__init__(api_key=api_key, base_url=base_url, settings=default_settings, **kwargs) async def _process_context(self, context: OpenAILLMContext): functions_list = [] diff --git a/src/pipecat/services/google/llm_vertex.py b/src/pipecat/services/google/llm_vertex.py index ef222c97e..9258a4d67 100644 --- a/src/pipecat/services/google/llm_vertex.py +++ b/src/pipecat/services/google/llm_vertex.py @@ -20,7 +20,8 @@ from typing import Optional from loguru import logger -from pipecat.services.google.llm import GoogleLLMService +from pipecat.services.google.llm import GoogleLLMService, GoogleLLMSettings +from pipecat.services.settings import _warn_deprecated_param try: from google.auth import default @@ -99,10 +100,11 @@ class GoogleVertexLLMService(GoogleLLMService): *, credentials: Optional[str] = None, credentials_path: Optional[str] = None, - model: str = "gemini-2.5-flash", + model: Optional[str] = None, location: Optional[str] = None, project_id: Optional[str] = None, params: Optional[GoogleLLMService.InputParams] = None, + settings: Optional[GoogleLLMSettings] = None, system_instruction: Optional[str] = None, tools: Optional[list] = None, tool_config: Optional[dict] = None, @@ -115,9 +117,20 @@ class GoogleVertexLLMService(GoogleLLMService): credentials: JSON string of service account credentials. credentials_path: Path to the service account JSON file. model: Model identifier (e.g., "gemini-2.5-flash"). + + .. deprecated:: + Use ``settings=GoogleLLMSettings(model=...)`` instead. + location: GCP region for Vertex AI endpoint (e.g., "us-east4"). project_id: Google Cloud project ID. params: Input parameters for the model. + + .. deprecated:: + Use ``settings=GoogleLLMSettings(...)`` instead. + + settings: Runtime-updatable settings for this service. When both + deprecated parameters and *settings* are provided, *settings* + values take precedence. system_instruction: System instruction/prompt for the model. tools: List of available tools/functions. tool_config: Configuration for tool usage. @@ -135,6 +148,11 @@ class GoogleVertexLLMService(GoogleLLMService): "Invalid parameter 'api_key'. Use 'credentials' or 'credentials_path' for Vertex AI authentication." ) + if model is not None: + _warn_deprecated_param("model", "GoogleLLMSettings", "model") + if params is not None: + _warn_deprecated_param("params", "GoogleLLMSettings") + # Handle deprecated InputParams fields if params and isinstance(params, GoogleVertexLLMService.InputParams): # Extract location and project_id from params if not provided @@ -170,12 +188,30 @@ class GoogleVertexLLMService(GoogleLLMService): self._project_id = project_id self._location = location + # Build default_settings from deprecated args + _params = params or GoogleLLMService.InputParams() + default_settings = GoogleLLMSettings( + model=model or "gemini-2.5-flash", + max_tokens=_params.max_tokens, + temperature=_params.temperature, + top_k=_params.top_k, + top_p=_params.top_p, + frequency_penalty=None, + presence_penalty=None, + seed=None, + filter_incomplete_user_turns=False, + user_turn_completion_config=None, + thinking=_params.thinking, + extra=_params.extra if isinstance(_params.extra, dict) else {}, + ) + if settings is not None: + default_settings.apply_update(settings) + # Call parent constructor with dummy api_key # (api_key is required by parent class, but not actually used with Vertex) super().__init__( api_key="dummy", - model=model, - params=params, + settings=default_settings, system_instruction=system_instruction, tools=tools, tool_config=tool_config, diff --git a/src/pipecat/services/google/stt.py b/src/pipecat/services/google/stt.py index 95d91d462..818df0214 100644 --- a/src/pipecat/services/google/stt.py +++ b/src/pipecat/services/google/stt.py @@ -36,7 +36,7 @@ from pipecat.frames.frames import ( StartFrame, TranscriptionFrame, ) -from pipecat.services.settings import NOT_GIVEN, STTSettings, _NotGiven +from pipecat.services.settings import NOT_GIVEN, STTSettings, _NotGiven, _warn_deprecated_param from pipecat.services.stt_latency import GOOGLE_TTFS_P99 from pipecat.services.stt_service import STTService from pipecat.transcriptions.language import Language, resolve_language @@ -425,6 +425,9 @@ class GoogleSTTService(STTService): class InputParams(BaseModel): """Configuration parameters for Google Speech-to-Text. + .. deprecated:: 1.0 + Use ``settings=GoogleSTTSettings(...)`` instead. + Parameters: languages: Single language or list of recognition languages. First language is primary. model: Speech recognition model to use. @@ -484,6 +487,7 @@ class GoogleSTTService(STTService): location: str = "global", sample_rate: Optional[int] = None, params: Optional[InputParams] = None, + settings: Optional[GoogleSTTSettings] = None, ttfs_p99_latency: Optional[float] = GOOGLE_TTFS_P99, **kwargs, ): @@ -495,30 +499,43 @@ class GoogleSTTService(STTService): location: Google Cloud location (e.g., "global", "us-central1"). sample_rate: Audio sample rate in Hertz. params: Configuration parameters for the service. + + .. deprecated:: 1.0 + Use ``settings=GoogleSTTSettings(...)`` instead. + + settings: Runtime-updatable settings. When provided alongside deprecated + ``params``, ``settings`` values take precedence. ttfs_p99_latency: P99 latency from speech end to final transcript in seconds. Override for your deployment. See https://github.com/pipecat-ai/stt-benchmark **kwargs: Additional arguments passed to STTService. """ - params = params or GoogleSTTService.InputParams() + if params is not None: + _warn_deprecated_param("params", "GoogleSTTSettings") + + _params = params or GoogleSTTService.InputParams() + + default_settings = GoogleSTTSettings( + language=None, + languages=list(_params.language_list), + language_codes=None, + model=_params.model, + use_separate_recognition_per_channel=_params.use_separate_recognition_per_channel, + enable_automatic_punctuation=_params.enable_automatic_punctuation, + enable_spoken_punctuation=_params.enable_spoken_punctuation, + enable_spoken_emojis=_params.enable_spoken_emojis, + profanity_filter=_params.profanity_filter, + enable_word_time_offsets=_params.enable_word_time_offsets, + enable_word_confidence=_params.enable_word_confidence, + enable_interim_results=_params.enable_interim_results, + enable_voice_activity_events=_params.enable_voice_activity_events, + ) + if settings is not None: + default_settings.apply_update(settings) super().__init__( sample_rate=sample_rate, ttfs_p99_latency=ttfs_p99_latency, - settings=GoogleSTTSettings( - language=None, - languages=list(params.language_list), - language_codes=None, - model=params.model, - use_separate_recognition_per_channel=params.use_separate_recognition_per_channel, - enable_automatic_punctuation=params.enable_automatic_punctuation, - enable_spoken_punctuation=params.enable_spoken_punctuation, - enable_spoken_emojis=params.enable_spoken_emojis, - profanity_filter=params.profanity_filter, - enable_word_time_offsets=params.enable_word_time_offsets, - enable_word_confidence=params.enable_word_confidence, - enable_interim_results=params.enable_interim_results, - enable_voice_activity_events=params.enable_voice_activity_events, - ), + settings=default_settings, **kwargs, ) diff --git a/src/pipecat/services/google/tts.py b/src/pipecat/services/google/tts.py index 6c71977a0..86ec845a5 100644 --- a/src/pipecat/services/google/tts.py +++ b/src/pipecat/services/google/tts.py @@ -37,7 +37,13 @@ from pipecat.frames.frames import ( TTSStartedFrame, TTSStoppedFrame, ) -from pipecat.services.settings import NOT_GIVEN, TTSSettings, _NotGiven, is_given +from pipecat.services.settings import ( + NOT_GIVEN, + TTSSettings, + _NotGiven, + _warn_deprecated_param, + is_given, +) from pipecat.services.tts_service import TTSService from pipecat.transcriptions.language import Language, resolve_language @@ -560,6 +566,9 @@ class GoogleHttpTTSService(TTSService): class InputParams(BaseModel): """Input parameters for Google HTTP TTS voice customization. + .. deprecated:: 1.0 + Use ``GoogleHttpTTSSettings`` directly via the ``settings`` parameter instead. + Parameters: pitch: Voice pitch adjustment (e.g., "+2st", "-50%"). rate: Speaking rate adjustment (e.g., "slow", "fast", "125%"). Used for SSML prosody tags (non-Chirp voices). @@ -586,9 +595,10 @@ class GoogleHttpTTSService(TTSService): credentials: Optional[str] = None, credentials_path: Optional[str] = None, location: Optional[str] = None, - voice_id: str = "en-US-Chirp3-HD-Charon", + voice_id: Optional[str] = None, sample_rate: Optional[int] = None, params: Optional[InputParams] = None, + settings: Optional[GoogleHttpTTSSettings] = None, **kwargs, ): """Initializes the Google HTTP TTS service. @@ -598,28 +608,47 @@ class GoogleHttpTTSService(TTSService): credentials_path: Path to Google Cloud service account JSON file. location: Google Cloud location for regional endpoint (e.g., "us-central1"). voice_id: Google TTS voice identifier (e.g., "en-US-Standard-A"). + + .. deprecated:: 1.0 + Use ``settings=GoogleHttpTTSSettings(voice=...)`` instead. + sample_rate: Audio sample rate in Hz. If None, uses default. params: Voice customization parameters including pitch, rate, volume, etc. + + .. deprecated:: 1.0 + Use ``settings=GoogleHttpTTSSettings(...)`` instead. + + settings: Runtime-updatable settings. When provided alongside deprecated + parameters, ``settings`` values take precedence. **kwargs: Additional arguments passed to parent TTSService. """ - params = params or GoogleHttpTTSService.InputParams() + if voice_id is not None: + _warn_deprecated_param("voice_id", "GoogleHttpTTSSettings", "voice") + if params is not None: + _warn_deprecated_param("params", "GoogleHttpTTSSettings") + + _params = params or GoogleHttpTTSService.InputParams() + + default_settings = GoogleHttpTTSSettings( + model=None, + pitch=_params.pitch, + rate=_params.rate, + speaking_rate=_params.speaking_rate, + volume=_params.volume, + emphasis=_params.emphasis, + language=self.language_to_service_language(_params.language) + if _params.language + else "en-US", + gender=_params.gender, + google_style=_params.google_style, + voice=voice_id or "en-US-Chirp3-HD-Charon", + ) + if settings is not None: + default_settings.apply_update(settings) super().__init__( sample_rate=sample_rate, - settings=GoogleHttpTTSSettings( - model=None, - pitch=params.pitch, - rate=params.rate, - speaking_rate=params.speaking_rate, - volume=params.volume, - emphasis=params.emphasis, - language=self.language_to_service_language(params.language) - if params.language - else "en-US", - gender=params.gender, - google_style=params.google_style, - voice=voice_id, - ), + settings=default_settings, **kwargs, ) @@ -987,6 +1016,9 @@ class GoogleTTSService(GoogleBaseTTSService): class InputParams(BaseModel): """Input parameters for Google streaming TTS configuration. + .. deprecated:: 1.0 + Use ``GoogleStreamTTSSettings`` directly via the ``settings`` parameter instead. + Parameters: language: Language for synthesis. Defaults to English. speaking_rate: The speaking rate, in the range [0.25, 2.0]. @@ -1001,10 +1033,11 @@ class GoogleTTSService(GoogleBaseTTSService): credentials: Optional[str] = None, credentials_path: Optional[str] = None, location: Optional[str] = None, - voice_id: str = "en-US-Chirp3-HD-Charon", + voice_id: Optional[str] = None, voice_cloning_key: Optional[str] = None, sample_rate: Optional[int] = None, - params: InputParams = InputParams(), + params: Optional[InputParams] = None, + settings: Optional[GoogleStreamTTSSettings] = None, **kwargs, ): """Initializes the Google streaming TTS service. @@ -1014,23 +1047,42 @@ class GoogleTTSService(GoogleBaseTTSService): credentials_path: Path to Google Cloud service account JSON file. location: Google Cloud location for regional endpoint (e.g., "us-central1"). voice_id: Google TTS voice identifier (e.g., "en-US-Chirp3-HD-Charon"). + + .. deprecated:: 1.0 + Use ``settings=GoogleStreamTTSSettings(voice=...)`` instead. + voice_cloning_key: The voice cloning key for Chirp 3 custom voices. sample_rate: Audio sample rate in Hz. If None, uses default. params: Language configuration parameters. + + .. deprecated:: 1.0 + Use ``settings=GoogleStreamTTSSettings(...)`` instead. + + settings: Runtime-updatable settings. When provided alongside deprecated + parameters, ``settings`` values take precedence. **kwargs: Additional arguments passed to parent TTSService. """ - params = params or GoogleTTSService.InputParams() + if voice_id is not None: + _warn_deprecated_param("voice_id", "GoogleStreamTTSSettings", "voice") + if params is not None: + _warn_deprecated_param("params", "GoogleStreamTTSSettings") + + _params = params or GoogleTTSService.InputParams() + + default_settings = GoogleStreamTTSSettings( + model=None, + language=self.language_to_service_language(_params.language) + if _params.language + else "en-US", + speaking_rate=_params.speaking_rate, + voice=voice_id or "en-US-Chirp3-HD-Charon", + ) + if settings is not None: + default_settings.apply_update(settings) super().__init__( sample_rate=sample_rate, - settings=GoogleStreamTTSSettings( - model=None, - language=self.language_to_service_language(params.language) - if params.language - else "en-US", - speaking_rate=params.speaking_rate, - voice=voice_id, - ), + settings=default_settings, **kwargs, ) @@ -1170,6 +1222,9 @@ class GeminiTTSService(GoogleBaseTTSService): class InputParams(BaseModel): """Input parameters for Gemini TTS configuration. + .. deprecated:: 1.0 + Use ``GeminiTTSSettings`` directly via the ``settings`` parameter instead. + Parameters: language: Language for synthesis. Defaults to English. prompt: Optional style instructions for how to synthesize the content. @@ -1186,13 +1241,14 @@ class GeminiTTSService(GoogleBaseTTSService): self, *, api_key: Optional[str] = None, - model: str = "gemini-2.5-flash-tts", + model: Optional[str] = None, credentials: Optional[str] = None, credentials_path: Optional[str] = None, location: Optional[str] = None, - voice_id: str = "Kore", + voice_id: Optional[str] = None, sample_rate: Optional[int] = None, params: Optional[InputParams] = None, + settings: Optional[GeminiTTSSettings] = None, **kwargs, ): """Initializes the Gemini TTS service. @@ -1206,12 +1262,26 @@ class GeminiTTSService(GoogleBaseTTSService): model: Gemini TTS model to use. Must be a TTS model like "gemini-2.5-flash-tts" or "gemini-2.5-pro-tts". + + .. deprecated:: 1.0 + Use ``settings=GeminiTTSSettings(model=...)`` instead. + credentials: JSON string containing Google Cloud service account credentials. credentials_path: Path to Google Cloud service account JSON file. location: Google Cloud location for regional endpoint (e.g., "us-central1"). voice_id: Voice name from the available Gemini voices. + + .. deprecated:: 1.0 + Use ``settings=GeminiTTSSettings(voice=...)`` instead. + sample_rate: Audio sample rate in Hz. If None, uses Google's default 24kHz. params: TTS configuration parameters. + + .. deprecated:: 1.0 + Use ``settings=GeminiTTSSettings(...)`` instead. + + settings: Runtime-updatable settings. When provided alongside deprecated + parameters, ``settings`` values take precedence. **kwargs: Additional arguments passed to parent TTSService. """ # Handle deprecated api_key parameter @@ -1222,29 +1292,40 @@ class GeminiTTSService(GoogleBaseTTSService): DeprecationWarning, stacklevel=2, ) + if model is not None: + _warn_deprecated_param("model", "GeminiTTSSettings", "model") + if voice_id is not None: + _warn_deprecated_param("voice_id", "GeminiTTSSettings", "voice") + if params is not None: + _warn_deprecated_param("params", "GeminiTTSSettings") if sample_rate and sample_rate != self.GOOGLE_SAMPLE_RATE: logger.warning( f"Google TTS only supports {self.GOOGLE_SAMPLE_RATE}Hz sample rate. " f"Current rate of {sample_rate}Hz may cause issues." ) - params = params or GeminiTTSService.InputParams() + _params = params or GeminiTTSService.InputParams() + voice_id = voice_id or "Kore" if voice_id not in self.AVAILABLE_VOICES: logger.warning(f"Voice '{voice_id}' not in known voices list. Using anyway.") + default_settings = GeminiTTSSettings( + model=model or "gemini-2.5-flash-tts", + language=self.language_to_service_language(_params.language) + if _params.language + else "en-US", + prompt=_params.prompt, + multi_speaker=_params.multi_speaker, + speaker_configs=_params.speaker_configs, + voice=voice_id, + ) + if settings is not None: + default_settings.apply_update(settings) + super().__init__( sample_rate=sample_rate, - settings=GeminiTTSSettings( - model=model, - language=self.language_to_service_language(params.language) - if params.language - else "en-US", - prompt=params.prompt, - multi_speaker=params.multi_speaker, - speaker_configs=params.speaker_configs, - voice=voice_id, - ), + settings=default_settings, **kwargs, ) diff --git a/src/pipecat/services/gradium/stt.py b/src/pipecat/services/gradium/stt.py index ac35c6e52..e1d2b74d4 100644 --- a/src/pipecat/services/gradium/stt.py +++ b/src/pipecat/services/gradium/stt.py @@ -28,7 +28,7 @@ from pipecat.frames.frames import ( VADUserStoppedSpeakingFrame, ) from pipecat.processors.frame_processor import FrameDirection -from pipecat.services.settings import NOT_GIVEN, STTSettings, _NotGiven +from pipecat.services.settings import NOT_GIVEN, STTSettings, _NotGiven, _warn_deprecated_param from pipecat.services.stt_latency import GRADIUM_TTFS_P99 from pipecat.services.stt_service import WebsocketSTTService from pipecat.transcriptions.language import Language, resolve_language @@ -91,6 +91,9 @@ class GradiumSTTService(WebsocketSTTService): class InputParams(BaseModel): """Configuration parameters for Gradium STT API. + .. deprecated:: 1.0 + Use ``settings=GradiumSTTSettings(...)`` instead. + Parameters: language: Expected language of the audio (e.g., "en", "es", "fr"). This helps ground the model to a specific language and improve @@ -111,6 +114,7 @@ class GradiumSTTService(WebsocketSTTService): api_endpoint_base_url: str = "wss://eu.api.gradium.ai/api/speech/asr", params: Optional[InputParams] = None, json_config: Optional[str] = None, + settings: Optional[GradiumSTTSettings] = None, ttfs_p99_latency: Optional[float] = GRADIUM_TTFS_P99, **kwargs, ): @@ -120,11 +124,17 @@ class GradiumSTTService(WebsocketSTTService): api_key: Gradium API key for authentication. api_endpoint_base_url: WebSocket endpoint URL. Defaults to Gradium's streaming endpoint. params: Configuration parameters for language and delay settings. + + .. deprecated:: 1.0 + Use ``settings=GradiumSTTSettings(...)`` instead. + json_config: Optional JSON configuration string for additional model settings. .. deprecated:: 0.0.101 Use `params` instead for type-safe configuration. + settings: Runtime-updatable settings. When provided alongside deprecated + parameters, ``settings`` values take precedence. ttfs_p99_latency: P99 latency from speech end to final transcript in seconds. Override for your deployment. See https://github.com/pipecat-ai/stt-benchmark **kwargs: Additional arguments passed to parent STTService class. @@ -138,16 +148,23 @@ class GradiumSTTService(WebsocketSTTService): stacklevel=2, ) - params = params or GradiumSTTService.InputParams() + if params is not None: + _warn_deprecated_param("params", "GradiumSTTSettings") + + _params = params or GradiumSTTService.InputParams() + + default_settings = GradiumSTTSettings( + model=None, + language=_params.language, + delay_in_frames=_params.delay_in_frames or None, + ) + if settings is not None: + default_settings.apply_update(settings) super().__init__( sample_rate=SAMPLE_RATE, ttfs_p99_latency=ttfs_p99_latency, - settings=GradiumSTTSettings( - model=None, - language=params.language, - delay_in_frames=params.delay_in_frames or None, - ), + settings=default_settings, **kwargs, ) diff --git a/src/pipecat/services/gradium/tts.py b/src/pipecat/services/gradium/tts.py index c8a83a7f2..75455cf54 100644 --- a/src/pipecat/services/gradium/tts.py +++ b/src/pipecat/services/gradium/tts.py @@ -22,7 +22,7 @@ from pipecat.frames.frames import ( TTSStartedFrame, TTSStoppedFrame, ) -from pipecat.services.settings import NOT_GIVEN, TTSSettings, _NotGiven +from pipecat.services.settings import NOT_GIVEN, TTSSettings, _NotGiven, _warn_deprecated_param from pipecat.services.tts_service import AudioContextTTSService from pipecat.utils.tracing.service_decorators import traced_tts @@ -57,6 +57,9 @@ class GradiumTTSService(AudioContextTTSService): class InputParams(BaseModel): """Configuration parameters for Gradium TTS service. + .. deprecated:: 1.0 + Use ``GradiumTTSSettings`` directly via the ``settings`` parameter instead. + Parameters: temp: Temperature to be used for generation, defaults to 0.6. """ @@ -67,11 +70,12 @@ class GradiumTTSService(AudioContextTTSService): self, *, api_key: str, - voice_id: str = "YTpq7expH9539ERJ", + voice_id: Optional[str] = None, url: str = "wss://eu.api.gradium.ai/api/speech/tts", - model: str = "default", + model: Optional[str] = None, json_config: Optional[str] = None, params: Optional[InputParams] = None, + settings: Optional[GradiumTTSSettings] = None, **kwargs, ): """Initialize the Gradium TTS service. @@ -79,13 +83,41 @@ class GradiumTTSService(AudioContextTTSService): Args: api_key: Gradium API key for authentication. voice_id: the voice identifier. + + .. deprecated:: 1.0 + Use ``settings=GradiumTTSSettings(voice=...)`` instead. + url: Gradium websocket API endpoint. model: Model ID to use for synthesis. + + .. deprecated:: 1.0 + Use ``settings=GradiumTTSSettings(model=...)`` instead. + json_config: Optional JSON configuration string for additional model settings. params: Additional configuration parameters. + + .. deprecated:: 1.0 + Use ``settings=GradiumTTSSettings(...)`` instead. + + settings: Runtime-updatable settings. When provided alongside deprecated + parameters, ``settings`` values take precedence. **kwargs: Additional arguments passed to parent class. """ - params = params or GradiumTTSService.InputParams() + if voice_id is not None: + _warn_deprecated_param("voice_id", "GradiumTTSSettings", "voice") + if model is not None: + _warn_deprecated_param("model", "GradiumTTSSettings", "model") + if params is not None: + _warn_deprecated_param("params", "GradiumTTSSettings") + + default_settings = GradiumTTSSettings( + model=model or "default", + voice=voice_id or "YTpq7expH9539ERJ", + language=None, + output_format="pcm", + ) + if settings is not None: + default_settings.apply_update(settings) super().__init__( push_stop_frames=True, @@ -93,12 +125,7 @@ class GradiumTTSService(AudioContextTTSService): pause_frame_processing=True, supports_word_timestamps=True, sample_rate=SAMPLE_RATE, - settings=GradiumTTSSettings( - model=model, - voice=voice_id, - language=None, - output_format="pcm", - ), + settings=default_settings, **kwargs, ) diff --git a/src/pipecat/services/grok/llm.py b/src/pipecat/services/grok/llm.py index fa905a92c..0ef6d36f2 100644 --- a/src/pipecat/services/grok/llm.py +++ b/src/pipecat/services/grok/llm.py @@ -12,6 +12,7 @@ and context aggregation functionality. """ from dataclasses import dataclass +from typing import Optional from loguru import logger @@ -22,11 +23,13 @@ from pipecat.processors.aggregators.llm_response import ( LLMUserAggregatorParams, ) from pipecat.processors.aggregators.openai_llm_context import OpenAILLMContext +from pipecat.services.openai.base_llm import OpenAILLMSettings from pipecat.services.openai.llm import ( OpenAIAssistantContextAggregator, OpenAILLMService, OpenAIUserContextAggregator, ) +from pipecat.services.settings import _warn_deprecated_param @dataclass @@ -81,7 +84,8 @@ class GrokLLMService(OpenAILLMService): *, api_key: str, base_url: str = "https://api.x.ai/v1", - model: str = "grok-3-beta", + model: Optional[str] = None, + settings: Optional[OpenAILLMSettings] = None, **kwargs, ): """Initialize the GrokLLMService with API key and model. @@ -90,9 +94,22 @@ class GrokLLMService(OpenAILLMService): api_key: The API key for accessing Grok's API. base_url: The base URL for Grok API. Defaults to "https://api.x.ai/v1". model: The model identifier to use. Defaults to "grok-3-beta". + + .. deprecated:: 1.0 + Use ``settings=OpenAILLMSettings(model=...)`` instead. + + settings: Runtime-updatable settings. When provided alongside deprecated + parameters, ``settings`` values take precedence. **kwargs: Additional keyword arguments passed to OpenAILLMService. """ - super().__init__(api_key=api_key, base_url=base_url, model=model, **kwargs) + if model is not None: + _warn_deprecated_param("model", "OpenAILLMSettings", "model") + + default_settings = OpenAILLMSettings(model=model or "grok-3-beta") + if settings is not None: + default_settings.apply_update(settings) + + super().__init__(api_key=api_key, base_url=base_url, settings=default_settings, **kwargs) # Initialize counters for token usage metrics self._prompt_tokens = 0 self._completion_tokens = 0 diff --git a/src/pipecat/services/grok/realtime/llm.py b/src/pipecat/services/grok/realtime/llm.py index 7a4e73806..87f5eaaaa 100644 --- a/src/pipecat/services/grok/realtime/llm.py +++ b/src/pipecat/services/grok/realtime/llm.py @@ -56,7 +56,7 @@ from pipecat.processors.aggregators.llm_response_universal import ( from pipecat.processors.aggregators.openai_llm_context import OpenAILLMContext from pipecat.processors.frame_processor import FrameDirection from pipecat.services.llm_service import FunctionCallFromLLM, LLMService -from pipecat.services.settings import NOT_GIVEN, LLMSettings, _NotGiven +from pipecat.services.settings import NOT_GIVEN, LLMSettings, _NotGiven, _warn_deprecated_param from pipecat.utils.time import time_now_iso8601 from . import events @@ -126,6 +126,7 @@ class GrokRealtimeLLMService(LLMService): api_key: str, base_url: str = "wss://api.x.ai/v1/realtime", session_properties: Optional[events.SessionProperties] = None, + settings: Optional[GrokRealtimeLLMSettings] = None, start_audio_paused: bool = False, **kwargs, ): @@ -136,30 +137,46 @@ class GrokRealtimeLLMService(LLMService): base_url: WebSocket base URL for the realtime API. Defaults to "wss://api.x.ai/v1/realtime". session_properties: Configuration properties for the realtime session. + + .. deprecated:: + Use ``settings=GrokRealtimeLLMSettings(session_properties=...)`` + instead. + If None, uses default SessionProperties with voice "Ara". To set a different voice, configure it in session_properties: session_properties = events.SessionProperties(voice="Rex") Available voices: Ara, Rex, Sal, Eve, Leo. + settings: Grok Realtime LLM settings. If provided together with deprecated + top-level parameters, the ``settings`` values take precedence. start_audio_paused: Whether to start with audio input paused. Defaults to False. **kwargs: Additional arguments passed to parent LLMService. """ + if session_properties is not None: + _warn_deprecated_param( + "session_properties", "GrokRealtimeLLMSettings", "session_properties" + ) + + default_settings = GrokRealtimeLLMSettings( + model=None, + temperature=None, + max_tokens=None, + top_p=None, + top_k=None, + frequency_penalty=None, + presence_penalty=None, + seed=None, + filter_incomplete_user_turns=False, + user_turn_completion_config=None, + session_properties=session_properties or events.SessionProperties(), + ) + if settings is not None: + default_settings.apply_update(settings) + super().__init__( base_url=base_url, - settings=GrokRealtimeLLMSettings( - model=None, - temperature=None, - max_tokens=None, - top_p=None, - top_k=None, - frequency_penalty=None, - presence_penalty=None, - seed=None, - filter_incomplete_user_turns=False, - user_turn_completion_config=None, - session_properties=session_properties or events.SessionProperties(), - ), + settings=default_settings, **kwargs, ) diff --git a/src/pipecat/services/groq/llm.py b/src/pipecat/services/groq/llm.py index 9dae88c31..23cce68a2 100644 --- a/src/pipecat/services/groq/llm.py +++ b/src/pipecat/services/groq/llm.py @@ -6,9 +6,13 @@ """Groq LLM Service implementation using OpenAI-compatible interface.""" +from typing import Optional + from loguru import logger +from pipecat.services.openai.base_llm import OpenAILLMSettings from pipecat.services.openai.llm import OpenAILLMService +from pipecat.services.settings import _warn_deprecated_param class GroqLLMService(OpenAILLMService): @@ -23,7 +27,8 @@ class GroqLLMService(OpenAILLMService): *, api_key: str, base_url: str = "https://api.groq.com/openai/v1", - model: str = "llama-3.3-70b-versatile", + model: Optional[str] = None, + settings: Optional[OpenAILLMSettings] = None, **kwargs, ): """Initialize Groq LLM service. @@ -32,9 +37,22 @@ class GroqLLMService(OpenAILLMService): api_key: The API key for accessing Groq's API. base_url: The base URL for Groq API. Defaults to "https://api.groq.com/openai/v1". model: The model identifier to use. Defaults to "llama-3.3-70b-versatile". + + .. deprecated:: 1.0 + Use ``settings=OpenAILLMSettings(model=...)`` instead. + + settings: Runtime-updatable settings. When provided alongside deprecated + parameters, ``settings`` values take precedence. **kwargs: Additional keyword arguments passed to OpenAILLMService. """ - super().__init__(api_key=api_key, base_url=base_url, model=model, **kwargs) + if model is not None: + _warn_deprecated_param("model", "OpenAILLMSettings", "model") + + default_settings = OpenAILLMSettings(model=model or "llama-3.3-70b-versatile") + if settings is not None: + default_settings.apply_update(settings) + + super().__init__(api_key=api_key, base_url=base_url, settings=default_settings, **kwargs) def create_client(self, api_key=None, base_url=None, **kwargs): """Create OpenAI-compatible client for Groq API endpoint. diff --git a/src/pipecat/services/groq/stt.py b/src/pipecat/services/groq/stt.py index d51e93c68..8018ec702 100644 --- a/src/pipecat/services/groq/stt.py +++ b/src/pipecat/services/groq/stt.py @@ -8,8 +8,13 @@ from typing import Optional +from pipecat.services.settings import _warn_deprecated_param from pipecat.services.stt_latency import GROQ_TTFS_P99 -from pipecat.services.whisper.base_stt import BaseWhisperSTTService, Transcription +from pipecat.services.whisper.base_stt import ( + BaseWhisperSTTService, + BaseWhisperSTTSettings, + Transcription, +) from pipecat.transcriptions.language import Language @@ -23,35 +28,75 @@ class GroqSTTService(BaseWhisperSTTService): def __init__( self, *, - model: str = "whisper-large-v3-turbo", + model: Optional[str] = None, api_key: Optional[str] = None, base_url: str = "https://api.groq.com/openai/v1", - language: Optional[Language] = Language.EN, + language: Optional[Language] = None, prompt: Optional[str] = None, temperature: Optional[float] = None, + settings: Optional[BaseWhisperSTTSettings] = None, ttfs_p99_latency: Optional[float] = GROQ_TTFS_P99, **kwargs, ): """Initialize Groq STT service. Args: - model: Whisper model to use. Defaults to "whisper-large-v3-turbo". + model: Whisper model to use. + + .. deprecated:: 1.0 + Use ``settings=BaseWhisperSTTSettings(model=...)`` instead. + api_key: Groq API key. Defaults to None. base_url: API base URL. Defaults to "https://api.groq.com/openai/v1". - language: Language of the audio input. Defaults to English. + language: Language of the audio input. + + .. deprecated:: 1.0 + Use ``settings=BaseWhisperSTTSettings(language=...)`` instead. + prompt: Optional text to guide the model's style or continue a previous segment. - temperature: Optional sampling temperature between 0 and 1. Defaults to 0.0. + + .. deprecated:: 1.0 + Use ``settings=BaseWhisperSTTSettings(prompt=...)`` instead. + + temperature: Optional sampling temperature between 0 and 1. + + .. deprecated:: 1.0 + Use ``settings=BaseWhisperSTTSettings(temperature=...)`` instead. + + settings: Runtime-updatable settings. When provided alongside deprecated + parameters, ``settings`` values take precedence. ttfs_p99_latency: P99 latency from speech end to final transcript in seconds. Override for your deployment. See https://github.com/pipecat-ai/stt-benchmark **kwargs: Additional arguments passed to BaseWhisperSTTService. """ - super().__init__( + if model is not None: + _warn_deprecated_param("model", "BaseWhisperSTTSettings", "model") + if language is not None: + _warn_deprecated_param("language", "BaseWhisperSTTSettings", "language") + if prompt is not None: + _warn_deprecated_param("prompt", "BaseWhisperSTTSettings", "prompt") + if temperature is not None: + _warn_deprecated_param("temperature", "BaseWhisperSTTSettings", "temperature") + + model = model or "whisper-large-v3-turbo" + language = language or Language.EN + + # Build settings from deprecated params and pass via settings= + # to avoid double deprecation warnings in BaseWhisperSTTService. + default_settings = BaseWhisperSTTSettings( model=model, - api_key=api_key, + language=self.language_to_service_language(language), base_url=base_url, - language=language, prompt=prompt, temperature=temperature, + ) + if settings is not None: + default_settings.apply_update(settings) + + super().__init__( + api_key=api_key, + base_url=base_url, + settings=default_settings, ttfs_p99_latency=ttfs_p99_latency, **kwargs, ) diff --git a/src/pipecat/services/groq/tts.py b/src/pipecat/services/groq/tts.py index 901b786c0..c6cc46e23 100644 --- a/src/pipecat/services/groq/tts.py +++ b/src/pipecat/services/groq/tts.py @@ -21,7 +21,7 @@ from pipecat.frames.frames import ( TTSStartedFrame, TTSStoppedFrame, ) -from pipecat.services.settings import NOT_GIVEN, TTSSettings, _NotGiven +from pipecat.services.settings import NOT_GIVEN, TTSSettings, _NotGiven, _warn_deprecated_param from pipecat.services.tts_service import TTSService from pipecat.transcriptions.language import Language from pipecat.utils.tracing.service_decorators import traced_tts @@ -64,6 +64,9 @@ class GroqTTSService(TTSService): class InputParams(BaseModel): """Input parameters for Groq TTS configuration. + .. deprecated:: 1.0 + Use ``settings=GroqTTSSettings(...)`` instead. + Parameters: language: Language for speech synthesis. Defaults to English. speed: Speech speed multiplier. Defaults to 1.0. @@ -80,9 +83,10 @@ class GroqTTSService(TTSService): api_key: str, output_format: str = "wav", params: Optional[InputParams] = None, - model_name: str = "canopylabs/orpheus-v1-english", - voice_id: str = "autumn", + model_name: Optional[str] = None, + voice_id: Optional[str] = None, sample_rate: Optional[int] = GROQ_SAMPLE_RATE, + settings: Optional[GroqTTSSettings] = None, **kwargs, ): """Initialize Groq TTS service. @@ -91,27 +95,52 @@ class GroqTTSService(TTSService): api_key: Groq API key for authentication. output_format: Audio output format. Defaults to "wav". params: Additional input parameters for voice customization. - model_name: TTS model to use. Defaults to "playai-tts". - voice_id: Voice identifier to use. Defaults to "Celeste-PlayAI". + + .. deprecated:: 1.0 + Use ``settings=GroqTTSSettings(...)`` instead. + + model_name: TTS model to use. + + .. deprecated:: 1.0 + Use ``settings=GroqTTSSettings(model=...)`` instead. + + voice_id: Voice identifier to use. + + .. deprecated:: 1.0 + Use ``settings=GroqTTSSettings(voice=...)`` instead. + sample_rate: Audio sample rate. Must be 48000 Hz for Groq TTS. + settings: Runtime-updatable settings. When provided alongside deprecated + parameters, ``settings`` values take precedence. **kwargs: Additional arguments passed to parent TTSService class. """ + if model_name is not None: + _warn_deprecated_param("model_name", "GroqTTSSettings", "model") + if voice_id is not None: + _warn_deprecated_param("voice_id", "GroqTTSSettings", "voice") + if params is not None: + _warn_deprecated_param("params", "GroqTTSSettings") + if sample_rate != self.GROQ_SAMPLE_RATE: logger.warning(f"Groq TTS only supports {self.GROQ_SAMPLE_RATE}Hz sample rate. ") - params = params or GroqTTSService.InputParams() + _params = params or GroqTTSService.InputParams() + + default_settings = GroqTTSSettings( + model=model_name or "canopylabs/orpheus-v1-english", + voice=voice_id or "autumn", + language=str(_params.language) if _params.language else "en", + output_format=output_format, + speed=_params.speed, + groq_sample_rate=sample_rate, + ) + if settings is not None: + default_settings.apply_update(settings) super().__init__( pause_frame_processing=True, sample_rate=sample_rate, - settings=GroqTTSSettings( - model=model_name, - voice=voice_id, - language=str(params.language) if params.language else "en", - output_format=output_format, - speed=params.speed, - groq_sample_rate=sample_rate, - ), + settings=default_settings, **kwargs, ) diff --git a/src/pipecat/services/heygen/video.py b/src/pipecat/services/heygen/video.py index 7f3624f35..020ecdfcf 100644 --- a/src/pipecat/services/heygen/video.py +++ b/src/pipecat/services/heygen/video.py @@ -45,6 +45,7 @@ from pipecat.services.heygen.client import ( HeyGenClient, ServiceType, ) +from pipecat.services.settings import ServiceSettings from pipecat.transports.base_transport import TransportParams # Using the same values that we do in the BaseOutputTransport @@ -80,6 +81,7 @@ class HeyGenVideoService(AIService): session: aiohttp.ClientSession, session_request: Optional[Union[LiveAvatarNewSessionRequest, NewSessionRequest]] = None, service_type: Optional[ServiceType] = None, + settings: Optional[ServiceSettings] = None, **kwargs, ) -> None: """Initialize the HeyGen video service. @@ -89,9 +91,15 @@ class HeyGenVideoService(AIService): session: HTTP client session for API requests session_request: Configuration for the HeyGen session service_type: Service type for the avatar session + settings: Runtime-updatable settings. HeyGen has no model concept, so this + is primarily used for the ``extra`` dict. **kwargs: Additional arguments passed to parent AIService """ - super().__init__(**kwargs) + default_settings = ServiceSettings(model=None) + if settings is not None: + default_settings.apply_update(settings) + + super().__init__(settings=default_settings, **kwargs) self._api_key = api_key self._session = session self._client: Optional[HeyGenClient] = None diff --git a/src/pipecat/services/hume/tts.py b/src/pipecat/services/hume/tts.py index 2a075ab36..35b6fbbc4 100644 --- a/src/pipecat/services/hume/tts.py +++ b/src/pipecat/services/hume/tts.py @@ -26,7 +26,7 @@ from pipecat.frames.frames import ( TTSStoppedFrame, ) from pipecat.processors.frame_processor import FrameDirection -from pipecat.services.settings import NOT_GIVEN, TTSSettings, _NotGiven +from pipecat.services.settings import NOT_GIVEN, TTSSettings, _NotGiven, _warn_deprecated_param from pipecat.services.tts_service import TTSService from pipecat.utils.tracing.service_decorators import traced_tts @@ -84,6 +84,9 @@ class HumeTTSService(TTSService): class InputParams(BaseModel): """Optional synthesis parameters for Hume TTS. + .. deprecated:: 1.0 + Use ``settings=HumeTTSSettings(...)`` instead. + Parameters: description: Natural-language acting directions (up to 100 characters). speed: Speaking-rate multiplier (0.5-2.0). @@ -98,9 +101,10 @@ class HumeTTSService(TTSService): self, *, api_key: Optional[str] = None, - voice_id: str, + voice_id: Optional[str] = None, params: Optional[InputParams] = None, sample_rate: Optional[int] = HUME_SAMPLE_RATE, + settings: Optional[HumeTTSSettings] = None, **kwargs, ) -> None: """Initialize the HumeTTSService. @@ -108,10 +112,25 @@ class HumeTTSService(TTSService): Args: api_key: Hume API key. If omitted, reads the ``HUME_API_KEY`` environment variable. voice_id: ID of the voice to use. Only voice IDs are supported; voice names are not. + + .. deprecated:: 1.0 + Use ``settings=HumeTTSSettings(voice=...)`` instead. + params: Optional synthesis controls (acting instructions, speed, trailing silence). + + .. deprecated:: 1.0 + Use ``settings=HumeTTSSettings(...)`` instead. + sample_rate: Output sample rate for emitted PCM frames. Defaults to 48_000 (Hume). + settings: Runtime-updatable settings. When provided alongside deprecated + parameters, ``settings`` values take precedence. **kwargs: Additional arguments passed to the parent class. """ + if voice_id is not None: + _warn_deprecated_param("voice_id", "HumeTTSSettings", "voice") + if params is not None: + _warn_deprecated_param("params", "HumeTTSSettings") + api_key = api_key or os.getenv("HUME_API_KEY") if not api_key: raise ValueError("HumeTTSService requires an API key (env HUME_API_KEY or api_key=)") @@ -121,21 +140,25 @@ class HumeTTSService(TTSService): f"Hume TTS streams at {HUME_SAMPLE_RATE} Hz; configured sample_rate={sample_rate}" ) - params = params or HumeTTSService.InputParams() + _params = params or HumeTTSService.InputParams() + + default_settings = HumeTTSSettings( + model=None, + voice=voice_id, + language=None, # Not applicable here + description=_params.description, + speed=_params.speed, + trailing_silence=_params.trailing_silence, + ) + if settings is not None: + default_settings.apply_update(settings) super().__init__( sample_rate=sample_rate, push_text_frames=False, push_stop_frames=True, supports_word_timestamps=True, - settings=HumeTTSSettings( - model=None, - voice=voice_id, - language=None, # Not applicable here - description=params.description, - speed=params.speed, - trailing_silence=params.trailing_silence, - ), + settings=default_settings, **kwargs, ) diff --git a/src/pipecat/services/inworld/tts.py b/src/pipecat/services/inworld/tts.py index d3f64c16f..23c3b36e4 100644 --- a/src/pipecat/services/inworld/tts.py +++ b/src/pipecat/services/inworld/tts.py @@ -29,7 +29,7 @@ from pipecat import version as pipecat_version USER_AGENT = f"pipecat/{pipecat_version()}" from pydantic import BaseModel -from pipecat.services.settings import NOT_GIVEN, TTSSettings, _NotGiven +from pipecat.services.settings import NOT_GIVEN, TTSSettings, _NotGiven, _warn_deprecated_param try: from websockets.asyncio.client import connect as websocket_connect @@ -114,6 +114,9 @@ class InworldHttpTTSService(TTSService): class InputParams(BaseModel): """Input parameters for Inworld TTS configuration. + .. deprecated:: 1.0 + Use ``InworldTTSSettings`` directly via the ``settings`` parameter instead. + Parameters: temperature: Temperature for speech synthesis. speaking_rate: Speaking rate for speech synthesis. @@ -129,12 +132,13 @@ class InworldHttpTTSService(TTSService): *, api_key: str, aiohttp_session: aiohttp.ClientSession, - voice_id: str = "Ashley", - model: str = "inworld-tts-1.5-max", + voice_id: Optional[str] = None, + model: Optional[str] = None, streaming: bool = True, sample_rate: Optional[int] = None, encoding: str = "LINEAR16", - params: InputParams = None, + params: Optional[InputParams] = None, + settings: Optional[InworldTTSSettings] = None, **kwargs, ): """Initialize the Inworld TTS service. @@ -143,32 +147,57 @@ class InworldHttpTTSService(TTSService): api_key: Inworld API key. aiohttp_session: aiohttp ClientSession for HTTP requests. voice_id: ID of the voice to use for synthesis. + + .. deprecated:: 1.0 + Use ``settings=InworldTTSSettings(voice=...)`` instead. + model: ID of the model to use for synthesis. + + .. deprecated:: 1.0 + Use ``settings=InworldTTSSettings(model=...)`` instead. + streaming: Whether to use streaming mode. sample_rate: Audio sample rate in Hz. encoding: Audio encoding format. params: Input parameters for Inworld TTS configuration. + + .. deprecated:: 1.0 + Use ``settings=InworldTTSSettings(...)`` instead. + + settings: Runtime-updatable settings. When provided alongside deprecated + parameters, ``settings`` values take precedence. **kwargs: Additional arguments passed to the parent class. """ - params = params or InworldHttpTTSService.InputParams() + if voice_id is not None: + _warn_deprecated_param("voice_id", "InworldTTSSettings", "voice") + if model is not None: + _warn_deprecated_param("model", "InworldTTSSettings", "model") + if params is not None: + _warn_deprecated_param("params", "InworldTTSSettings") + + _params = params or InworldHttpTTSService.InputParams() + + default_settings = InworldTTSSettings( + model=model or "inworld-tts-1.5-max", + voice=voice_id or "Ashley", + language=None, + audio_encoding=encoding, + audio_sample_rate=0, + speaking_rate=_params.speaking_rate, + temperature=_params.temperature, + timestamp_transport_strategy=_params.timestamp_transport_strategy, + auto_mode=None, # Not applicable for HTTP TTS + apply_text_normalization=None, # Not applicable for HTTP TTS + ) + if settings is not None: + default_settings.apply_update(settings) super().__init__( push_text_frames=False, push_stop_frames=True, supports_word_timestamps=True, sample_rate=sample_rate, - settings=InworldTTSSettings( - model=model, - voice=voice_id, - language=None, - audio_encoding=encoding, - audio_sample_rate=0, - speaking_rate=params.speaking_rate, - temperature=params.temperature, - timestamp_transport_strategy=params.timestamp_transport_strategy, - auto_mode=None, # Not applicable for HTTP TTS - apply_text_normalization=None, # Not applicable for HTTP TTS - ), + settings=default_settings, **kwargs, ) @@ -477,6 +506,9 @@ class InworldTTSService(AudioContextTTSService): class InputParams(BaseModel): """Input parameters for Inworld WebSocket TTS configuration. + .. deprecated:: 1.0 + Use ``InworldTTSSettings`` directly via the ``settings`` parameter instead. + Parameters: temperature: Temperature for speech synthesis. speaking_rate: Speaking rate for speech synthesis. @@ -503,12 +535,13 @@ class InworldTTSService(AudioContextTTSService): self, *, api_key: str, - voice_id: str = "Ashley", - model: str = "inworld-tts-1.5-max", + voice_id: Optional[str] = None, + model: Optional[str] = None, url: str = "wss://api.inworld.ai/tts/v1/voice:streamBidirectional", sample_rate: Optional[int] = None, encoding: str = "LINEAR16", - params: InputParams = None, + params: Optional[InputParams] = None, + settings: Optional[InworldTTSSettings] = None, aggregate_sentences: Optional[bool] = None, text_aggregation_mode: Optional[TextAggregationMode] = None, append_trailing_space: bool = True, @@ -519,11 +552,25 @@ class InworldTTSService(AudioContextTTSService): Args: api_key: Inworld API key. voice_id: ID of the voice to use for synthesis. + + .. deprecated:: 1.0 + Use ``settings=InworldTTSSettings(voice=...)`` instead. + model: ID of the model to use for synthesis. + + .. deprecated:: 1.0 + Use ``settings=InworldTTSSettings(model=...)`` instead. + url: URL of the Inworld WebSocket API. sample_rate: Audio sample rate in Hz. encoding: Audio encoding format. params: Input parameters for Inworld WebSocket TTS configuration. + + .. deprecated:: 1.0 + Use ``settings=InworldTTSSettings(...)`` instead. + + settings: Runtime-updatable settings. When provided alongside deprecated + parameters, ``settings`` values take precedence. aggregate_sentences: Deprecated. Use text_aggregation_mode instead. .. deprecated:: 0.0.104 @@ -533,7 +580,29 @@ class InworldTTSService(AudioContextTTSService): append_trailing_space: Whether to append a trailing space to text before sending to TTS. **kwargs: Additional arguments passed to the parent class. """ - params = params or InworldTTSService.InputParams() + if voice_id is not None: + _warn_deprecated_param("voice_id", "InworldTTSSettings", "voice") + if model is not None: + _warn_deprecated_param("model", "InworldTTSSettings", "model") + if params is not None: + _warn_deprecated_param("params", "InworldTTSSettings") + + _params = params or InworldTTSService.InputParams() + + default_settings = InworldTTSSettings( + model=model or "inworld-tts-1.5-max", + voice=voice_id or "Ashley", + language=None, + audio_encoding=encoding, + audio_sample_rate=0, + speaking_rate=_params.speaking_rate, + temperature=_params.temperature, + apply_text_normalization=_params.apply_text_normalization, + timestamp_transport_strategy=_params.timestamp_transport_strategy, + auto_mode=_params.auto_mode if _params.auto_mode is not None else aggregate_sentences, + ) + if settings is not None: + default_settings.apply_update(settings) super().__init__( push_text_frames=False, @@ -544,18 +613,7 @@ class InworldTTSService(AudioContextTTSService): aggregate_sentences=aggregate_sentences, text_aggregation_mode=text_aggregation_mode, append_trailing_space=append_trailing_space, - settings=InworldTTSSettings( - model=model, - voice=voice_id, - language=None, - audio_encoding=encoding, - audio_sample_rate=0, - speaking_rate=params.speaking_rate, - temperature=params.temperature, - apply_text_normalization=params.apply_text_normalization, - timestamp_transport_strategy=params.timestamp_transport_strategy, - auto_mode=params.auto_mode if params.auto_mode is not None else aggregate_sentences, - ), + settings=default_settings, **kwargs, ) @@ -564,8 +622,8 @@ class InworldTTSService(AudioContextTTSService): self._timestamp_type = "WORD" self._buffer_settings = { - "maxBufferDelayMs": params.max_buffer_delay_ms, - "bufferCharThreshold": params.buffer_char_threshold, + "maxBufferDelayMs": _params.max_buffer_delay_ms, + "bufferCharThreshold": _params.buffer_char_threshold, } self._receive_task = None diff --git a/src/pipecat/services/kokoro/tts.py b/src/pipecat/services/kokoro/tts.py index 4b35fa46d..fed53049c 100644 --- a/src/pipecat/services/kokoro/tts.py +++ b/src/pipecat/services/kokoro/tts.py @@ -23,7 +23,7 @@ from pipecat.frames.frames import ( TTSStartedFrame, TTSStoppedFrame, ) -from pipecat.services.settings import NOT_GIVEN, TTSSettings, _NotGiven +from pipecat.services.settings import NOT_GIVEN, TTSSettings, _NotGiven, _warn_deprecated_param from pipecat.services.tts_service import TTSService from pipecat.transcriptions.language import Language, resolve_language from pipecat.utils.tracing.service_decorators import traced_tts @@ -112,6 +112,9 @@ class KokoroTTSService(TTSService): class InputParams(BaseModel): """Input parameters for Kokoro TTS configuration. + .. deprecated:: 1.0 + Use ``KokoroTTSSettings`` directly via the ``settings`` parameter instead. + Parameters: language: Language to use for synthesis. """ @@ -121,35 +124,55 @@ class KokoroTTSService(TTSService): def __init__( self, *, - voice_id: str, + voice_id: Optional[str] = None, model_path: Optional[str] = None, voices_path: Optional[str] = None, params: Optional[InputParams] = None, + settings: Optional[KokoroTTSSettings] = None, **kwargs, ): """Initialize the Kokoro TTS service. Args: voice_id: Voice identifier to use for synthesis. + + .. deprecated:: 1.0 + Use ``settings=KokoroTTSSettings(voice=...)`` instead. + model_path: Path to the kokoro ONNX model file. Defaults to auto-downloaded file. voices_path: Path to the voices binary file. Defaults to auto-downloaded file. params: Configuration parameters for synthesis. + + .. deprecated:: 1.0 + Use ``settings=KokoroTTSSettings(...)`` instead. + + settings: Runtime-updatable settings. When provided alongside deprecated + parameters, ``settings`` values take precedence. **kwargs: Additional arguments passed to parent `TTSService`. """ - params = params or KokoroTTSService.InputParams() + if voice_id is not None: + _warn_deprecated_param("voice_id", "KokoroTTSSettings", "voice") + if params is not None: + _warn_deprecated_param("params", "KokoroTTSSettings") + + _params = params or KokoroTTSService.InputParams() + + default_settings = KokoroTTSSettings( + model=None, + voice=voice_id, + language=language_to_kokoro_language(_params.language), + lang_code=language_to_kokoro_language(_params.language), + ) + if settings is not None: + default_settings.apply_update(settings) super().__init__( - settings=KokoroTTSSettings( - model=None, - voice=voice_id, - language=language_to_kokoro_language(params.language), - lang_code=language_to_kokoro_language(params.language), - ), + settings=default_settings, **kwargs, ) - self._lang_code = language_to_kokoro_language(params.language) + self._lang_code = language_to_kokoro_language(_params.language) model = Path(model_path) if model_path else KOKORO_CACHE_DIR / "kokoro-v1.0.onnx" voices = Path(voices_path) if voices_path else KOKORO_CACHE_DIR / "voices-v1.0.bin" diff --git a/src/pipecat/services/lmnt/tts.py b/src/pipecat/services/lmnt/tts.py index a2c500ca2..1e7cff994 100644 --- a/src/pipecat/services/lmnt/tts.py +++ b/src/pipecat/services/lmnt/tts.py @@ -24,7 +24,7 @@ from pipecat.frames.frames import ( TTSStoppedFrame, ) from pipecat.processors.frame_processor import FrameDirection -from pipecat.services.settings import NOT_GIVEN, TTSSettings, _NotGiven +from pipecat.services.settings import NOT_GIVEN, TTSSettings, _NotGiven, _warn_deprecated_param from pipecat.services.tts_service import InterruptibleTTSService from pipecat.transcriptions.language import Language, resolve_language from pipecat.utils.tracing.service_decorators import traced_tts @@ -98,10 +98,11 @@ class LmntTTSService(InterruptibleTTSService): self, *, api_key: str, - voice_id: str, + voice_id: Optional[str] = None, sample_rate: Optional[int] = None, language: Language = Language.EN, - model: str = "blizzard", + model: Optional[str] = None, + settings: Optional[LmntTTSSettings] = None, **kwargs, ): """Initialize the LMNT TTS service. @@ -109,21 +110,40 @@ class LmntTTSService(InterruptibleTTSService): Args: api_key: LMNT API key for authentication. voice_id: ID of the voice to use for synthesis. + + .. deprecated:: 1.0 + Use ``settings=LmntTTSSettings(voice=...)`` instead. + sample_rate: Audio sample rate. If None, uses default. language: Language for synthesis. Defaults to English. - model: TTS model to use. Defaults to "blizzard". + model: TTS model to use. + + .. deprecated:: 1.0 + Use ``settings=LmntTTSSettings(model=...)`` instead. + + settings: Runtime-updatable settings. When provided alongside deprecated + parameters, ``settings`` values take precedence. **kwargs: Additional arguments passed to parent InterruptibleTTSService. """ + if voice_id is not None: + _warn_deprecated_param("voice_id", "LmntTTSSettings", "voice") + if model is not None: + _warn_deprecated_param("model", "LmntTTSSettings", "model") + + default_settings = LmntTTSSettings( + model=model or "blizzard", + voice=voice_id, + language=self.language_to_service_language(language), + format="raw", + ) + if settings is not None: + default_settings.apply_update(settings) + super().__init__( push_stop_frames=True, pause_frame_processing=True, sample_rate=sample_rate, - settings=LmntTTSSettings( - model=model, - voice=voice_id, - language=self.language_to_service_language(language), - format="raw", - ), + settings=default_settings, **kwargs, ) diff --git a/src/pipecat/services/minimax/tts.py b/src/pipecat/services/minimax/tts.py index 116d24a34..602654e2f 100644 --- a/src/pipecat/services/minimax/tts.py +++ b/src/pipecat/services/minimax/tts.py @@ -26,7 +26,7 @@ from pipecat.frames.frames import ( TTSStartedFrame, TTSStoppedFrame, ) -from pipecat.services.settings import NOT_GIVEN, TTSSettings, _NotGiven +from pipecat.services.settings import NOT_GIVEN, TTSSettings, _NotGiven, _warn_deprecated_param from pipecat.services.tts_service import TTSService from pipecat.transcriptions.language import Language, resolve_language from pipecat.utils.tracing.service_decorators import traced_tts @@ -166,6 +166,9 @@ class MiniMaxHttpTTSService(TTSService): class InputParams(BaseModel): """Configuration parameters for MiniMax TTS. + .. deprecated:: 1.0 + Use ``MiniMaxTTSSettings`` directly via the ``settings`` parameter instead. + Parameters: language: Language for TTS generation. Supports 40 languages. Note: Filipino, Tamil, and Persian require speech-2.6-* models. @@ -201,11 +204,12 @@ class MiniMaxHttpTTSService(TTSService): api_key: str, base_url: str = "https://api.minimax.io/v1/t2a_v2", group_id: str, - model: str = "speech-02-turbo", - voice_id: str = "Calm_Woman", + model: Optional[str] = None, + voice_id: Optional[str] = None, aiohttp_session: aiohttp.ClientSession, sample_rate: Optional[int] = None, params: Optional[InputParams] = None, + settings: Optional[MiniMaxTTSSettings] = None, **kwargs, ): """Initialize the MiniMax TTS service. @@ -221,50 +225,45 @@ class MiniMaxHttpTTSService(TTSService): "speech-2.6-hd", "speech-2.6-turbo" (latest, supports Filipino/Tamil/Persian), "speech-02-hd", "speech-02-turbo", "speech-01-hd", "speech-01-turbo". + + .. deprecated:: 1.0 + Use ``settings=MiniMaxTTSSettings(model=...)`` instead. + voice_id: Voice identifier. Defaults to "Calm_Woman". + + .. deprecated:: 1.0 + Use ``settings=MiniMaxTTSSettings(voice=...)`` instead. + aiohttp_session: aiohttp.ClientSession for API communication. sample_rate: Output audio sample rate in Hz. If None, uses pipeline default. params: Additional configuration parameters. + + .. deprecated:: 1.0 + Use ``settings=MiniMaxTTSSettings(...)`` instead. + + settings: Runtime-updatable settings. When provided alongside deprecated + parameters, ``settings`` values take precedence. **kwargs: Additional arguments passed to parent TTSService. """ - params = params or MiniMaxHttpTTSService.InputParams() + if model is not None: + _warn_deprecated_param("model", "MiniMaxTTSSettings", "model") + if voice_id is not None: + _warn_deprecated_param("voice_id", "MiniMaxTTSSettings", "voice") + if params is not None: + _warn_deprecated_param("params", "MiniMaxTTSSettings") - super().__init__( - sample_rate=sample_rate, - settings=MiniMaxTTSSettings( - model=model, - voice=voice_id, - language=None, - stream=True, - speed=params.speed, - volume=params.volume, - pitch=params.pitch, - language_boost=None, - emotion=None, - text_normalization=None, - latex_read=None, - audio_bitrate=128000, - audio_format="pcm", - audio_channel=1, - audio_sample_rate=0, - ), - **kwargs, - ) + _params = params or MiniMaxHttpTTSService.InputParams() - self._api_key = api_key - self._group_id = group_id - self._base_url = f"{base_url}?GroupId={group_id}" - self._session = aiohttp_session - - # Add language boost if provided - if params.language: - service_lang = self.language_to_service_language(params.language) + # Resolve language boost + language_boost = None + if _params.language: + service_lang = self.language_to_service_language(_params.language) if service_lang: - self._settings.language_boost = service_lang + language_boost = service_lang - # Add optional emotion if provided - if params.emotion: - # Validate emotion is in the supported list + # Resolve emotion + emotion = None + if _params.emotion: supported_emotions = [ "happy", "sad", @@ -275,15 +274,16 @@ class MiniMaxHttpTTSService(TTSService): "neutral", "fluent", ] - if params.emotion in supported_emotions: - self._settings.emotion = params.emotion + if _params.emotion in supported_emotions: + emotion = _params.emotion else: logger.warning( - f"Unsupported emotion: {params.emotion}. Supported emotions: {supported_emotions}" + f"Unsupported emotion: {_params.emotion}. Supported emotions: {supported_emotions}" ) - # If `english_normalization`, add `text_normalization` and print warning - if params.english_normalization is not None: + # Resolve text_normalization + text_normalization = None + if _params.english_normalization is not None: import warnings with warnings.catch_warnings(): @@ -292,15 +292,40 @@ class MiniMaxHttpTTSService(TTSService): "Parameter `english_normalization` is deprecated and will be removed in a future version. Use `text_normalization` instead.", DeprecationWarning, ) - self._settings.text_normalization = params.english_normalization + text_normalization = _params.english_normalization + if _params.text_normalization is not None: + text_normalization = _params.text_normalization - # Add text_normalization if provided (corrected parameter name) - if params.text_normalization is not None: - self._settings.text_normalization = params.text_normalization + default_settings = MiniMaxTTSSettings( + model=model or "speech-02-turbo", + voice=voice_id or "Calm_Woman", + language=None, + stream=True, + speed=_params.speed, + volume=_params.volume, + pitch=_params.pitch, + language_boost=language_boost, + emotion=emotion, + text_normalization=text_normalization, + latex_read=_params.latex_read, + audio_bitrate=128000, + audio_format="pcm", + audio_channel=1, + audio_sample_rate=0, + ) + if settings is not None: + default_settings.apply_update(settings) - # Add latex_read if provided - if params.latex_read is not None: - self._settings.latex_read = params.latex_read + super().__init__( + sample_rate=sample_rate, + settings=default_settings, + **kwargs, + ) + + self._api_key = api_key + self._group_id = group_id + self._base_url = f"{base_url}?GroupId={group_id}" + self._session = aiohttp_session def can_generate_metrics(self) -> bool: """Check if this service can generate processing metrics. diff --git a/src/pipecat/services/mistral/llm.py b/src/pipecat/services/mistral/llm.py index 984ffb7dd..e4249741e 100644 --- a/src/pipecat/services/mistral/llm.py +++ b/src/pipecat/services/mistral/llm.py @@ -6,14 +6,16 @@ """Mistral LLM service implementation using OpenAI-compatible interface.""" -from typing import List, Sequence +from typing import List, Optional, Sequence from loguru import logger from openai.types.chat import ChatCompletionMessageParam from pipecat.adapters.services.open_ai_adapter import OpenAILLMInvocationParams from pipecat.frames.frames import FunctionCallFromLLM +from pipecat.services.openai.base_llm import OpenAILLMSettings from pipecat.services.openai.llm import OpenAILLMService +from pipecat.services.settings import _warn_deprecated_param class MistralLLMService(OpenAILLMService): @@ -28,7 +30,8 @@ class MistralLLMService(OpenAILLMService): *, api_key: str, base_url: str = "https://api.mistral.ai/v1", - model: str = "mistral-small-latest", + model: Optional[str] = None, + settings: Optional[OpenAILLMSettings] = None, **kwargs, ): """Initialize the Mistral LLM service. @@ -37,9 +40,22 @@ class MistralLLMService(OpenAILLMService): api_key: The API key for accessing Mistral's API. base_url: The base URL for Mistral API. Defaults to "https://api.mistral.ai/v1". model: The model identifier to use. Defaults to "mistral-small-latest". + + .. deprecated:: 1.0 + Use ``settings=OpenAILLMSettings(model=...)`` instead. + + settings: Runtime-updatable settings. When provided alongside deprecated + parameters, ``settings`` values take precedence. **kwargs: Additional keyword arguments passed to OpenAILLMService. """ - super().__init__(api_key=api_key, base_url=base_url, model=model, **kwargs) + if model is not None: + _warn_deprecated_param("model", "OpenAILLMSettings", "model") + + default_settings = OpenAILLMSettings(model=model or "mistral-small-latest") + if settings is not None: + default_settings.apply_update(settings) + + super().__init__(api_key=api_key, base_url=base_url, settings=default_settings, **kwargs) def create_client(self, api_key=None, base_url=None, **kwargs): """Create OpenAI-compatible client for Mistral API endpoint. diff --git a/src/pipecat/services/moondream/vision.py b/src/pipecat/services/moondream/vision.py index 53b98b77a..db449d7ed 100644 --- a/src/pipecat/services/moondream/vision.py +++ b/src/pipecat/services/moondream/vision.py @@ -25,7 +25,7 @@ from pipecat.frames.frames import ( VisionFullResponseStartFrame, VisionTextFrame, ) -from pipecat.services.settings import VisionSettings +from pipecat.services.settings import VisionSettings, _warn_deprecated_param from pipecat.services.vision_service import VisionService try: @@ -80,17 +80,36 @@ class MoondreamService(VisionService): """ def __init__( - self, *, model="vikhyatk/moondream2", revision="2025-01-09", use_cpu=False, **kwargs + self, + *, + model: Optional[str] = None, + revision="2025-01-09", + use_cpu=False, + settings: Optional[MoondreamSettings] = None, + **kwargs, ): """Initialize the Moondream service. Args: model: Hugging Face model identifier for the Moondream model. + + .. deprecated:: 1.0 + Use ``settings=MoondreamSettings(model=...)`` instead. + revision: Specific model revision to use. use_cpu: Whether to force CPU usage instead of hardware acceleration. + settings: Runtime-updatable settings. When provided alongside deprecated + parameters, ``settings`` values take precedence. **kwargs: Additional arguments passed to the parent VisionService. """ - super().__init__(settings=MoondreamSettings(model=model), **kwargs) + if model is not None: + _warn_deprecated_param("model", "MoondreamSettings", "model") + + default_settings = MoondreamSettings(model=model or "vikhyatk/moondream2") + if settings is not None: + default_settings.apply_update(settings) + + super().__init__(settings=default_settings, **kwargs) if not use_cpu: device, dtype = detect_device() @@ -101,7 +120,7 @@ class MoondreamService(VisionService): logger.debug("Loading Moondream model...") self._model = AutoModelForCausalLM.from_pretrained( - model, + self._settings.model, trust_remote_code=True, revision=revision, device_map={"": device}, diff --git a/src/pipecat/services/neuphonic/tts.py b/src/pipecat/services/neuphonic/tts.py index 63411c3eb..21c7b57dd 100644 --- a/src/pipecat/services/neuphonic/tts.py +++ b/src/pipecat/services/neuphonic/tts.py @@ -35,7 +35,7 @@ from pipecat.frames.frames import ( TTSStoppedFrame, ) from pipecat.processors.frame_processor import FrameDirection -from pipecat.services.settings import NOT_GIVEN, TTSSettings, _NotGiven +from pipecat.services.settings import NOT_GIVEN, TTSSettings, _NotGiven, _warn_deprecated_param from pipecat.services.tts_service import InterruptibleTTSService, TextAggregationMode, TTSService from pipecat.transcriptions.language import Language, resolve_language from pipecat.utils.tracing.service_decorators import traced_tts @@ -102,6 +102,9 @@ class NeuphonicTTSService(InterruptibleTTSService): class InputParams(BaseModel): """Input parameters for Neuphonic TTS configuration. + .. deprecated:: 1.0 + Use ``settings=NeuphonicTTSSettings(...)`` instead. + Parameters: language: Language for synthesis. Defaults to English. speed: Speech speed multiplier. Defaults to 1.0. @@ -119,6 +122,7 @@ class NeuphonicTTSService(InterruptibleTTSService): sample_rate: Optional[int] = 22050, encoding: str = "pcm_linear", params: Optional[InputParams] = None, + settings: Optional[NeuphonicTTSSettings] = None, aggregate_sentences: Optional[bool] = None, text_aggregation_mode: Optional[TextAggregationMode] = None, **kwargs, @@ -128,10 +132,20 @@ class NeuphonicTTSService(InterruptibleTTSService): Args: api_key: Neuphonic API key for authentication. voice_id: ID of the voice to use for synthesis. + + .. deprecated:: 1.0 + Use ``settings=NeuphonicTTSSettings(voice=...)`` instead. + url: WebSocket URL for the Neuphonic API. sample_rate: Audio sample rate in Hz. Defaults to 22050. encoding: Audio encoding format. Defaults to "pcm_linear". params: Additional input parameters for TTS configuration. + + .. deprecated:: 1.0 + Use ``settings=NeuphonicTTSSettings(...)`` instead. + + settings: Runtime-updatable settings. When provided alongside deprecated + parameters, ``settings`` values take precedence. aggregate_sentences: Deprecated. Use text_aggregation_mode instead. .. deprecated:: 0.0.104 @@ -140,7 +154,23 @@ class NeuphonicTTSService(InterruptibleTTSService): text_aggregation_mode: How to aggregate text before synthesis. **kwargs: Additional arguments passed to parent InterruptibleTTSService. """ - params = params or NeuphonicTTSService.InputParams() + if voice_id is not None: + _warn_deprecated_param("voice_id", "NeuphonicTTSSettings", "voice") + if params is not None: + _warn_deprecated_param("params", "NeuphonicTTSSettings") + + _params = params or NeuphonicTTSService.InputParams() + + default_settings = NeuphonicTTSSettings( + model=None, + language=self.language_to_service_language(_params.language), + speed=_params.speed, + encoding=encoding, + sampling_rate=sample_rate, + voice=voice_id, + ) + if settings is not None: + default_settings.apply_update(settings) super().__init__( aggregate_sentences=aggregate_sentences, @@ -148,14 +178,7 @@ class NeuphonicTTSService(InterruptibleTTSService): push_stop_frames=True, stop_frame_timeout_s=2.0, sample_rate=sample_rate, - settings=NeuphonicTTSSettings( - model=None, - language=self.language_to_service_language(params.language), - speed=params.speed, - encoding=encoding, - sampling_rate=sample_rate, - voice=voice_id, - ), + settings=default_settings, **kwargs, ) @@ -418,6 +441,9 @@ class NeuphonicHttpTTSService(TTSService): class InputParams(BaseModel): """Input parameters for Neuphonic HTTP TTS configuration. + .. deprecated:: 1.0 + Use ``settings=NeuphonicTTSSettings(...)`` instead. + Parameters: language: Language for synthesis. Defaults to English. speed: Speech speed multiplier. Defaults to 1.0. @@ -436,6 +462,7 @@ class NeuphonicHttpTTSService(TTSService): sample_rate: Optional[int] = 22050, encoding: Optional[str] = "pcm_linear", params: Optional[InputParams] = None, + settings: Optional[NeuphonicTTSSettings] = None, **kwargs, ): """Initialize the Neuphonic HTTP TTS service. @@ -443,25 +470,44 @@ class NeuphonicHttpTTSService(TTSService): Args: api_key: Neuphonic API key for authentication. voice_id: ID of the voice to use for synthesis. + + .. deprecated:: 1.0 + Use ``settings=NeuphonicTTSSettings(voice=...)`` instead. + aiohttp_session: Shared aiohttp session for HTTP requests. url: Base URL for the Neuphonic HTTP API. sample_rate: Audio sample rate in Hz. Defaults to 22050. encoding: Audio encoding format. Defaults to "pcm_linear". params: Additional input parameters for TTS configuration. + + .. deprecated:: 1.0 + Use ``settings=NeuphonicTTSSettings(...)`` instead. + + settings: Runtime-updatable settings. When provided alongside deprecated + parameters, ``settings`` values take precedence. **kwargs: Additional arguments passed to parent TTSService. """ - params = params or NeuphonicHttpTTSService.InputParams() + if voice_id is not None: + _warn_deprecated_param("voice_id", "NeuphonicTTSSettings", "voice") + if params is not None: + _warn_deprecated_param("params", "NeuphonicTTSSettings") + + _params = params or NeuphonicHttpTTSService.InputParams() + + default_settings = NeuphonicTTSSettings( + model=None, + voice=voice_id, + language=self.language_to_service_language(_params.language) or "en", + speed=_params.speed, + encoding=encoding, + sampling_rate=sample_rate, + ) + if settings is not None: + default_settings.apply_update(settings) super().__init__( sample_rate=sample_rate, - settings=NeuphonicTTSSettings( - model=None, - voice=voice_id, - language=self.language_to_service_language(params.language) or "en", - speed=params.speed, - encoding=encoding, - sampling_rate=sample_rate, - ), + settings=default_settings, **kwargs, ) diff --git a/src/pipecat/services/nvidia/llm.py b/src/pipecat/services/nvidia/llm.py index c5db58f31..ef4afe848 100644 --- a/src/pipecat/services/nvidia/llm.py +++ b/src/pipecat/services/nvidia/llm.py @@ -10,10 +10,14 @@ This module provides a service for interacting with NVIDIA's NIM (NVIDIA Inferen Microservice) API while maintaining compatibility with the OpenAI-style interface. """ +from typing import Optional + from pipecat.metrics.metrics import LLMTokenUsage from pipecat.processors.aggregators.llm_context import LLMContext from pipecat.processors.aggregators.openai_llm_context import OpenAILLMContext +from pipecat.services.openai.base_llm import OpenAILLMSettings from pipecat.services.openai.llm import OpenAILLMService +from pipecat.services.settings import _warn_deprecated_param class NvidiaLLMService(OpenAILLMService): @@ -29,7 +33,8 @@ class NvidiaLLMService(OpenAILLMService): *, api_key: str, base_url: str = "https://integrate.api.nvidia.com/v1", - model: str = "nvidia/llama-3.1-nemotron-70b-instruct", + model: Optional[str] = None, + settings: Optional[OpenAILLMSettings] = None, **kwargs, ): """Initialize the NvidiaLLMService. @@ -37,10 +42,26 @@ class NvidiaLLMService(OpenAILLMService): Args: api_key: The API key for accessing NVIDIA's NIM API. base_url: The base URL for NIM API. Defaults to "https://integrate.api.nvidia.com/v1". - model: The model identifier to use. Defaults to "nvidia/llama-3.1-nemotron-70b-instruct". + model: The model identifier to use. Defaults to + "nvidia/llama-3.1-nemotron-70b-instruct". + + .. deprecated:: 1.0 + Use ``settings=OpenAILLMSettings(model=...)`` instead. + + settings: Runtime-updatable settings. When provided alongside deprecated + parameters, ``settings`` values take precedence. **kwargs: Additional keyword arguments passed to OpenAILLMService. """ - super().__init__(api_key=api_key, base_url=base_url, model=model, **kwargs) + if model is not None: + _warn_deprecated_param("model", "OpenAILLMSettings", "model") + + default_settings = OpenAILLMSettings( + model=model or "nvidia/llama-3.1-nemotron-70b-instruct" + ) + if settings is not None: + default_settings.apply_update(settings) + + super().__init__(api_key=api_key, base_url=base_url, settings=default_settings, **kwargs) # Counters for accumulating token usage metrics self._prompt_tokens = 0 self._completion_tokens = 0 diff --git a/src/pipecat/services/nvidia/stt.py b/src/pipecat/services/nvidia/stt.py index 950515096..7f9c28f8f 100644 --- a/src/pipecat/services/nvidia/stt.py +++ b/src/pipecat/services/nvidia/stt.py @@ -23,7 +23,7 @@ from pipecat.frames.frames import ( StartFrame, TranscriptionFrame, ) -from pipecat.services.settings import NOT_GIVEN, STTSettings, _NotGiven +from pipecat.services.settings import NOT_GIVEN, STTSettings, _NotGiven, _warn_deprecated_param from pipecat.services.stt_latency import NVIDIA_TTFS_P99 from pipecat.services.stt_service import SegmentedSTTService, STTService from pipecat.transcriptions.language import Language, resolve_language @@ -130,6 +130,9 @@ class NvidiaSTTService(STTService): class InputParams(BaseModel): """Configuration parameters for NVIDIA Riva STT service. + .. deprecated:: 1.0 + Use ``settings=NvidiaSTTSettings(...)`` instead. + Parameters: language: Target language for transcription. Defaults to EN_US. """ @@ -148,6 +151,7 @@ class NvidiaSTTService(STTService): sample_rate: Optional[int] = None, params: Optional[InputParams] = None, use_ssl: bool = True, + settings: Optional[NvidiaSTTSettings] = None, ttfs_p99_latency: Optional[float] = NVIDIA_TTFS_P99, **kwargs, ): @@ -159,20 +163,33 @@ class NvidiaSTTService(STTService): model_function_map: Mapping containing 'function_id' and 'model_name' for the ASR model. sample_rate: Audio sample rate in Hz. If None, uses pipeline default. params: Additional configuration parameters for NVIDIA Riva. + + .. deprecated:: 1.0 + Use ``settings=NvidiaSTTSettings(...)`` instead. + use_ssl: Whether to use SSL for the NVIDIA Riva server. Defaults to True. + settings: Runtime-updatable settings. When provided alongside deprecated + parameters, ``settings`` values take precedence. ttfs_p99_latency: P99 latency from speech end to final transcript in seconds. Override for your deployment. See https://github.com/pipecat-ai/stt-benchmark **kwargs: Additional arguments passed to STTService. """ - params = params or NvidiaSTTService.InputParams() + if params is not None: + _warn_deprecated_param("params", "NvidiaSTTSettings") + + _params = params or NvidiaSTTService.InputParams() + + default_settings = NvidiaSTTSettings( + model=model_function_map.get("model_name"), + language=_params.language, + ) + if settings is not None: + default_settings.apply_update(settings) super().__init__( sample_rate=sample_rate, ttfs_p99_latency=ttfs_p99_latency, - settings=NvidiaSTTSettings( - model=model_function_map.get("model_name"), - language=params.language, - ), + settings=default_settings, **kwargs, ) @@ -421,6 +438,9 @@ class NvidiaSegmentedSTTService(SegmentedSTTService): class InputParams(BaseModel): """Configuration parameters for NVIDIA Riva segmented STT service. + .. deprecated:: 1.0 + Use ``settings=NvidiaSegmentedSTTSettings(...)`` instead. + Parameters: language: Target language for transcription. Defaults to EN_US. profanity_filter: Whether to filter profanity from results. @@ -449,6 +469,7 @@ class NvidiaSegmentedSTTService(SegmentedSTTService): sample_rate: Optional[int] = None, params: Optional[InputParams] = None, use_ssl: bool = True, + settings: Optional[NvidiaSegmentedSTTSettings] = None, ttfs_p99_latency: Optional[float] = NVIDIA_TTFS_P99, **kwargs, ): @@ -460,26 +481,39 @@ class NvidiaSegmentedSTTService(SegmentedSTTService): model_function_map: Mapping of model name and its corresponding NVIDIA Cloud Function ID sample_rate: Audio sample rate in Hz. If not provided, uses the pipeline's rate params: Additional configuration parameters for NVIDIA Riva + + .. deprecated:: 1.0 + Use ``settings=NvidiaSegmentedSTTSettings(...)`` instead. + use_ssl: Whether to use SSL for the NVIDIA Riva server. Defaults to True. + settings: Runtime-updatable settings. When provided alongside deprecated + parameters, ``settings`` values take precedence. ttfs_p99_latency: P99 latency from speech end to final transcript in seconds. Override for your deployment. See https://github.com/pipecat-ai/stt-benchmark **kwargs: Additional arguments passed to SegmentedSTTService """ - params = params or NvidiaSegmentedSTTService.InputParams() + if params is not None: + _warn_deprecated_param("params", "NvidiaSegmentedSTTSettings") + + _params = params or NvidiaSegmentedSTTService.InputParams() + + default_settings = NvidiaSegmentedSTTSettings( + model=model_function_map.get("model_name"), + language=self.language_to_service_language(_params.language or Language.EN_US) + or "en-US", + profanity_filter=_params.profanity_filter, + automatic_punctuation=_params.automatic_punctuation, + verbatim_transcripts=_params.verbatim_transcripts, + boosted_lm_words=_params.boosted_lm_words, + boosted_lm_score=_params.boosted_lm_score, + ) + if settings is not None: + default_settings.apply_update(settings) super().__init__( sample_rate=sample_rate, ttfs_p99_latency=ttfs_p99_latency, - settings=NvidiaSegmentedSTTSettings( - model=model_function_map.get("model_name"), - language=self.language_to_service_language(params.language or Language.EN_US) - or "en-US", - profanity_filter=params.profanity_filter, - automatic_punctuation=params.automatic_punctuation, - verbatim_transcripts=params.verbatim_transcripts, - boosted_lm_words=params.boosted_lm_words, - boosted_lm_score=params.boosted_lm_score, - ), + settings=default_settings, **kwargs, ) diff --git a/src/pipecat/services/nvidia/tts.py b/src/pipecat/services/nvidia/tts.py index 6785e9631..0f7491645 100644 --- a/src/pipecat/services/nvidia/tts.py +++ b/src/pipecat/services/nvidia/tts.py @@ -31,7 +31,7 @@ from pipecat.frames.frames import ( TTSStartedFrame, TTSStoppedFrame, ) -from pipecat.services.settings import NOT_GIVEN, TTSSettings, _NotGiven +from pipecat.services.settings import NOT_GIVEN, TTSSettings, _NotGiven, _warn_deprecated_param from pipecat.services.tts_service import TTSService from pipecat.transcriptions.language import Language @@ -68,6 +68,9 @@ class NvidiaTTSService(TTSService): class InputParams(BaseModel): """Input parameters for Riva TTS configuration. + .. deprecated:: 1.0 + Use ``NvidiaTTSSettings`` directly via the ``settings`` parameter instead. + Parameters: language: Language code for synthesis. Defaults to US English. quality: Audio quality setting (0-100). Defaults to 20. @@ -81,13 +84,14 @@ class NvidiaTTSService(TTSService): *, api_key: str, server: str = "grpc.nvcf.nvidia.com:443", - voice_id: str = "Magpie-Multilingual.EN-US.Aria", + voice_id: Optional[str] = None, sample_rate: Optional[int] = None, model_function_map: Mapping[str, str] = { "function_id": "877104f7-e885-42b9-8de8-f6e4c6303969", "model_name": "magpie-tts-multilingual", }, params: Optional[InputParams] = None, + settings: Optional[NvidiaTTSSettings] = None, use_ssl: bool = True, **kwargs, ): @@ -96,23 +100,42 @@ class NvidiaTTSService(TTSService): Args: api_key: NVIDIA API key for authentication. server: gRPC server endpoint. Defaults to NVIDIA's cloud endpoint. - voice_id: Voice model identifier. Defaults to multilingual Ray voice. + voice_id: Voice model identifier. Defaults to multilingual Aria voice. + + .. deprecated:: 1.0 + Use ``settings=NvidiaTTSSettings(voice=...)`` instead. + sample_rate: Audio sample rate. If None, uses service default. model_function_map: Dictionary containing function_id and model_name for the TTS model. params: Additional configuration parameters for TTS synthesis. + + .. deprecated:: 1.0 + Use ``settings=NvidiaTTSSettings(...)`` instead. + + settings: Runtime-updatable settings. When provided alongside deprecated + parameters, ``settings`` values take precedence. use_ssl: Whether to use SSL for the NVIDIA Riva server. Defaults to True. **kwargs: Additional arguments passed to parent TTSService. """ - params = params or NvidiaTTSService.InputParams() + if voice_id is not None: + _warn_deprecated_param("voice_id", "NvidiaTTSSettings", "voice") + if params is not None: + _warn_deprecated_param("params", "NvidiaTTSSettings") + + _params = params or NvidiaTTSService.InputParams() + + default_settings = NvidiaTTSSettings( + model=model_function_map.get("model_name"), + voice=voice_id or "Magpie-Multilingual.EN-US.Aria", + language=_params.language, + quality=_params.quality, + ) + if settings is not None: + default_settings.apply_update(settings) super().__init__( sample_rate=sample_rate, - settings=NvidiaTTSSettings( - model=model_function_map.get("model_name"), - voice=voice_id, - language=params.language, - quality=params.quality, - ), + settings=default_settings, **kwargs, ) diff --git a/src/pipecat/services/ollama/llm.py b/src/pipecat/services/ollama/llm.py index 04f22bbae..ecae3fc95 100644 --- a/src/pipecat/services/ollama/llm.py +++ b/src/pipecat/services/ollama/llm.py @@ -6,9 +6,13 @@ """OLLama LLM service implementation for Pipecat AI framework.""" +from typing import Optional + from loguru import logger +from pipecat.services.openai.base_llm import OpenAILLMSettings from pipecat.services.openai.llm import OpenAILLMService +from pipecat.services.settings import _warn_deprecated_param class OLLamaLLMService(OpenAILLMService): @@ -19,17 +23,35 @@ class OLLamaLLMService(OpenAILLMService): """ def __init__( - self, *, model: str = "llama2", base_url: str = "http://localhost:11434/v1", **kwargs + self, + *, + model: Optional[str] = None, + base_url: str = "http://localhost:11434/v1", + settings: Optional[OpenAILLMSettings] = None, + **kwargs, ): """Initialize OLLama LLM service. Args: model: The OLLama model to use. Defaults to "llama2". + + .. deprecated:: 1.0 + Use ``settings=OpenAILLMSettings(model=...)`` instead. + base_url: The base URL for the OLLama API endpoint. Defaults to "http://localhost:11434/v1". + settings: Runtime-updatable settings. When provided alongside deprecated + parameters, ``settings`` values take precedence. **kwargs: Additional keyword arguments passed to OpenAILLMService. """ - super().__init__(model=model, base_url=base_url, api_key="ollama", **kwargs) + if model is not None: + _warn_deprecated_param("model", "OpenAILLMSettings", "model") + + default_settings = OpenAILLMSettings(model=model or "llama2") + if settings is not None: + default_settings.apply_update(settings) + + super().__init__(base_url=base_url, api_key="ollama", settings=default_settings, **kwargs) def create_client(self, base_url=None, **kwargs): """Create OpenAI-compatible client for Ollama. diff --git a/src/pipecat/services/openai/base_llm.py b/src/pipecat/services/openai/base_llm.py index dfef1ae90..9ff3af0ab 100644 --- a/src/pipecat/services/openai/base_llm.py +++ b/src/pipecat/services/openai/base_llm.py @@ -75,6 +75,10 @@ class BaseOpenAILLMService(LLMService): class InputParams(BaseModel): """Input parameters for OpenAI model configuration. + .. deprecated:: 1.0 + Use ``settings=OpenAILLMSettings(...)`` instead of + ``params=InputParams(...)``. + Parameters: frequency_penalty: Penalty for frequent tokens (-2.0 to 2.0). presence_penalty: Penalty for new tokens (-2.0 to 2.0). @@ -108,13 +112,14 @@ class BaseOpenAILLMService(LLMService): def __init__( self, *, - model: str, + model: Optional[str] = None, api_key=None, base_url=None, organization=None, project=None, default_headers: Optional[Mapping[str, str]] = None, params: Optional[InputParams] = None, + settings: Optional[OpenAILLMSettings] = None, retry_timeout_secs: Optional[float] = 5.0, retry_on_timeout: Optional[bool] = False, system_instruction: Optional[str] = None, @@ -124,35 +129,50 @@ class BaseOpenAILLMService(LLMService): Args: model: The OpenAI model name to use (e.g., "gpt-4.1", "gpt-4o"). + + .. deprecated:: 1.0 + Use ``settings=OpenAILLMSettings(model=...)`` instead. + api_key: OpenAI API key. If None, uses environment variable. base_url: Custom base URL for OpenAI API. If None, uses default. organization: OpenAI organization ID. project: OpenAI project ID. default_headers: Additional HTTP headers to include in requests. params: Input parameters for model configuration and behavior. + + .. deprecated:: 1.0 + Use ``settings=OpenAILLMSettings(...)`` instead. + + settings: Runtime-updatable settings. When provided alongside deprecated + parameters, ``settings`` values take precedence. retry_timeout_secs: Request timeout in seconds. Defaults to 5.0 seconds. retry_on_timeout: Whether to retry the request once if it times out. system_instruction: Optional system instruction to prepend to messages. **kwargs: Additional arguments passed to the parent LLMService. """ - params = params or BaseOpenAILLMService.InputParams() + _params = params or BaseOpenAILLMService.InputParams() + + default_settings = OpenAILLMSettings( + model=model or "gpt-4o", + frequency_penalty=_params.frequency_penalty, + presence_penalty=_params.presence_penalty, + seed=_params.seed, + temperature=_params.temperature, + top_p=_params.top_p, + top_k=None, + max_tokens=_params.max_tokens, + max_completion_tokens=_params.max_completion_tokens, + service_tier=_params.service_tier, + filter_incomplete_user_turns=False, + user_turn_completion_config=None, + extra=_params.extra if isinstance(_params.extra, dict) else {}, + ) + + if settings is not None: + default_settings.apply_update(settings) super().__init__( - settings=OpenAILLMSettings( - model=model, - frequency_penalty=params.frequency_penalty, - presence_penalty=params.presence_penalty, - seed=params.seed, - temperature=params.temperature, - top_p=params.top_p, - top_k=None, - max_tokens=params.max_tokens, - max_completion_tokens=params.max_completion_tokens, - service_tier=params.service_tier, - filter_incomplete_user_turns=False, - user_turn_completion_config=None, - extra=params.extra if isinstance(params.extra, dict) else {}, - ), + settings=default_settings, **kwargs, ) self._retry_timeout_secs = retry_timeout_secs diff --git a/src/pipecat/services/openai/image.py b/src/pipecat/services/openai/image.py index f35a5ded8..2dc66876c 100644 --- a/src/pipecat/services/openai/image.py +++ b/src/pipecat/services/openai/image.py @@ -25,7 +25,7 @@ from pipecat.frames.frames import ( URLImageRawFrame, ) from pipecat.services.image_service import ImageGenService -from pipecat.services.settings import ImageGenSettings +from pipecat.services.settings import ImageGenSettings, _warn_deprecated_param @dataclass @@ -52,7 +52,8 @@ class OpenAIImageGenService(ImageGenService): base_url: Optional[str] = None, aiohttp_session: aiohttp.ClientSession, image_size: Literal["256x256", "512x512", "1024x1024", "1792x1024", "1024x1792"], - model: str = "dall-e-3", + model: Optional[str] = None, + settings: Optional[OpenAIImageGenSettings] = None, ): """Initialize the OpenAI image generation service. @@ -62,8 +63,21 @@ class OpenAIImageGenService(ImageGenService): aiohttp_session: HTTP session for downloading generated images. image_size: Target size for generated images. model: DALL-E model to use for generation. Defaults to "dall-e-3". + + .. deprecated:: 1.0 + Use ``settings=OpenAIImageGenSettings(model=...)`` instead. + + settings: Runtime-updatable settings. When provided alongside deprecated + parameters, ``settings`` values take precedence. """ - super().__init__(settings=OpenAIImageGenSettings(model=model)) + if model is not None: + _warn_deprecated_param("model", "OpenAIImageGenSettings", "model") + + default_settings = OpenAIImageGenSettings(model=model or "dall-e-3") + if settings is not None: + default_settings.apply_update(settings) + + super().__init__(settings=default_settings) self._image_size = image_size self._client = AsyncOpenAI(api_key=api_key, base_url=base_url) self._aiohttp_session = aiohttp_session diff --git a/src/pipecat/services/openai/llm.py b/src/pipecat/services/openai/llm.py index b760b0d6e..c259987a8 100644 --- a/src/pipecat/services/openai/llm.py +++ b/src/pipecat/services/openai/llm.py @@ -23,7 +23,8 @@ from pipecat.processors.aggregators.llm_response import ( LLMUserContextAggregator, ) from pipecat.processors.aggregators.openai_llm_context import OpenAILLMContext -from pipecat.services.openai.base_llm import BaseOpenAILLMService +from pipecat.services.openai.base_llm import BaseOpenAILLMService, OpenAILLMSettings +from pipecat.services.settings import _warn_deprecated_param @dataclass @@ -72,18 +73,53 @@ class OpenAILLMService(BaseOpenAILLMService): def __init__( self, *, - model: str = "gpt-4.1", + model: Optional[str] = None, params: Optional[BaseOpenAILLMService.InputParams] = None, + settings: Optional[OpenAILLMSettings] = None, **kwargs, ): """Initialize OpenAI LLM service. Args: model: The OpenAI model name to use. Defaults to "gpt-4.1". + + .. deprecated:: 1.0 + Use ``settings=OpenAILLMSettings(model=...)`` instead. + params: Input parameters for model configuration. + + .. deprecated:: 1.0 + Use ``settings=OpenAILLMSettings(...)`` instead. + + settings: Runtime-updatable settings. When provided alongside deprecated + parameters, ``settings`` values take precedence. **kwargs: Additional arguments passed to the parent BaseOpenAILLMService. """ - super().__init__(model=model, params=params, **kwargs) + if model is not None: + _warn_deprecated_param("model", "OpenAILLMSettings", "model") + if params is not None: + _warn_deprecated_param("params", "OpenAILLMSettings") + + _params = params or BaseOpenAILLMService.InputParams() + default_settings = OpenAILLMSettings( + model=model or "gpt-4.1", + frequency_penalty=_params.frequency_penalty, + presence_penalty=_params.presence_penalty, + seed=_params.seed, + temperature=_params.temperature, + top_p=_params.top_p, + top_k=None, + max_tokens=_params.max_tokens, + max_completion_tokens=_params.max_completion_tokens, + service_tier=_params.service_tier, + filter_incomplete_user_turns=False, + user_turn_completion_config=None, + extra=_params.extra if isinstance(_params.extra, dict) else {}, + ) + if settings is not None: + default_settings.apply_update(settings) + + super().__init__(settings=default_settings, **kwargs) def create_context_aggregator( self, diff --git a/src/pipecat/services/openai/realtime/llm.py b/src/pipecat/services/openai/realtime/llm.py index 07b6aa82b..d6e7a71bd 100644 --- a/src/pipecat/services/openai/realtime/llm.py +++ b/src/pipecat/services/openai/realtime/llm.py @@ -59,7 +59,7 @@ from pipecat.processors.aggregators.openai_llm_context import ( ) from pipecat.processors.frame_processor import FrameDirection from pipecat.services.llm_service import FunctionCallFromLLM, LLMService -from pipecat.services.settings import NOT_GIVEN, LLMSettings, _NotGiven +from pipecat.services.settings import NOT_GIVEN, LLMSettings, _NotGiven, _warn_deprecated_param from pipecat.transcriptions.language import Language from pipecat.utils.time import time_now_iso8601 from pipecat.utils.tracing.service_decorators import traced_openai_realtime, traced_stt @@ -121,9 +121,10 @@ class OpenAIRealtimeLLMService(LLMService): self, *, api_key: str, - model: str = "gpt-realtime-1.5", + model: Optional[str] = None, base_url: str = "wss://api.openai.com/v1/realtime", session_properties: Optional[events.SessionProperties] = None, + settings: Optional[OpenAIRealtimeLLMSettings] = None, start_audio_paused: bool = False, start_video_paused: bool = False, video_frame_detail: str = "auto", @@ -134,14 +135,25 @@ class OpenAIRealtimeLLMService(LLMService): Args: api_key: OpenAI API key for authentication. - model: OpenAI model name. Defaults to "gpt-realtime". + model: OpenAI model name. + + .. deprecated:: + Use ``settings=OpenAIRealtimeLLMSettings(model=...)`` instead. + This is a connection-level parameter set via the WebSocket URL query parameter and cannot be changed during the session. base_url: WebSocket base URL for the realtime API. Defaults to "wss://api.openai.com/v1/realtime". session_properties: Configuration properties for the realtime session. + + .. deprecated:: + Use ``settings=OpenAIRealtimeLLMSettings(session_properties=...)`` + instead. + These are session-level settings that can be updated during the session (except for voice and model). If None, uses default SessionProperties. + settings: Realtime LLM settings. If provided together with deprecated + top-level parameters, the ``settings`` values take precedence. start_audio_paused: Whether to start with audio input paused. Defaults to False. start_video_paused: Whether to start with video input paused. Defaults to False. video_frame_detail: Detail level for video processing. Can be "auto", "low", or "high". @@ -156,6 +168,12 @@ class OpenAIRealtimeLLMService(LLMService): **kwargs: Additional arguments passed to parent LLMService. """ + if model is not None: + _warn_deprecated_param("model", "OpenAIRealtimeLLMSettings", "model") + if session_properties is not None: + _warn_deprecated_param( + "session_properties", "OpenAIRealtimeLLMSettings", "session_properties" + ) if send_transcription_frames is not None: import warnings @@ -168,24 +186,28 @@ class OpenAIRealtimeLLMService(LLMService): stacklevel=2, ) + default_settings = OpenAIRealtimeLLMSettings( + model=model or "gpt-realtime-1.5", + temperature=None, + max_tokens=None, + top_p=None, + top_k=None, + frequency_penalty=None, + presence_penalty=None, + seed=None, + filter_incomplete_user_turns=False, + user_turn_completion_config=None, + session_properties=session_properties or events.SessionProperties(), + ) + if settings is not None: + default_settings.apply_update(settings) + # Build WebSocket URL with model query parameter # Source: https://platform.openai.com/docs/guides/realtime-websocket - full_url = f"{base_url}?model={model}" + full_url = f"{base_url}?model={default_settings.model}" super().__init__( base_url=full_url, - settings=OpenAIRealtimeLLMSettings( - model=model, - temperature=None, - max_tokens=None, - top_p=None, - top_k=None, - frequency_penalty=None, - presence_penalty=None, - seed=None, - filter_incomplete_user_turns=False, - user_turn_completion_config=None, - session_properties=session_properties or events.SessionProperties(), - ), + settings=default_settings, **kwargs, ) diff --git a/src/pipecat/services/openai/stt.py b/src/pipecat/services/openai/stt.py index 32895f8b5..be933cd9a 100644 --- a/src/pipecat/services/openai/stt.py +++ b/src/pipecat/services/openai/stt.py @@ -35,10 +35,14 @@ from pipecat.frames.frames import ( VADUserStoppedSpeakingFrame, ) from pipecat.processors.frame_processor import FrameDirection -from pipecat.services.settings import NOT_GIVEN, STTSettings, _NotGiven +from pipecat.services.settings import NOT_GIVEN, STTSettings, _NotGiven, _warn_deprecated_param from pipecat.services.stt_latency import OPENAI_REALTIME_TTFS_P99, OPENAI_TTFS_P99 from pipecat.services.stt_service import WebsocketSTTService -from pipecat.services.whisper.base_stt import BaseWhisperSTTService, Transcription +from pipecat.services.whisper.base_stt import ( + BaseWhisperSTTService, + BaseWhisperSTTSettings, + Transcription, +) from pipecat.transcriptions.language import Language from pipecat.utils.time import time_now_iso8601 from pipecat.utils.tracing.service_decorators import traced_stt @@ -61,30 +65,40 @@ class OpenAISTTService(BaseWhisperSTTService): def __init__( self, *, - model: str = "gpt-4o-transcribe", + model: Optional[str] = None, api_key: Optional[str] = None, base_url: Optional[str] = None, language: Optional[Language] = Language.EN, prompt: Optional[str] = None, temperature: Optional[float] = None, + settings: Optional[BaseWhisperSTTSettings] = None, ttfs_p99_latency: Optional[float] = OPENAI_TTFS_P99, **kwargs, ): """Initialize OpenAI STT service. Args: - model: Model to use — either gpt-4o or Whisper. Defaults to "gpt-4o-transcribe". + model: Model to use — either gpt-4o or Whisper. + + .. deprecated:: 1.0 + Use ``settings=BaseWhisperSTTSettings(model=...)`` instead. + api_key: OpenAI API key. Defaults to None. base_url: API base URL. Defaults to None. language: Language of the audio input. Defaults to English. prompt: Optional text to guide the model's style or continue a previous segment. temperature: Optional sampling temperature between 0 and 1. Defaults to 0.0. + settings: Runtime-updatable settings. When provided alongside deprecated + parameters, ``settings`` values take precedence. ttfs_p99_latency: P99 latency from speech end to final transcript in seconds. Override for your deployment. See https://github.com/pipecat-ai/stt-benchmark **kwargs: Additional arguments passed to BaseWhisperSTTService. """ + if model is not None: + _warn_deprecated_param("model", "BaseWhisperSTTSettings", "model") + super().__init__( - model=model, + model=model or "gpt-4o-transcribe", api_key=api_key, base_url=base_url, language=language, @@ -94,6 +108,9 @@ class OpenAISTTService(BaseWhisperSTTService): **kwargs, ) + if settings is not None: + self._settings.apply_update(settings) + async def _transcribe(self, audio: bytes) -> Transcription: assert self._language is not None # Assigned in the BaseWhisperSTTService class @@ -175,13 +192,14 @@ class OpenAIRealtimeSTTService(WebsocketSTTService): self, *, api_key: str, - model: str = "gpt-4o-transcribe", + model: Optional[str] = None, base_url: str = "wss://api.openai.com/v1/realtime", language: Optional[Language] = Language.EN, prompt: Optional[str] = None, turn_detection: Optional[Union[dict, Literal[False]]] = False, noise_reduction: Optional[Literal["near_field", "far_field"]] = None, should_interrupt: bool = True, + settings: Optional[OpenAIRealtimeSTTSettings] = None, ttfs_p99_latency: Optional[float] = OPENAI_REALTIME_TTFS_P99, **kwargs, ): @@ -191,7 +209,10 @@ class OpenAIRealtimeSTTService(WebsocketSTTService): api_key: OpenAI API key for authentication. model: Transcription model. Supported values are ``"gpt-4o-transcribe"`` and ``"gpt-4o-mini-transcribe"``. - Defaults to ``"gpt-4o-transcribe"``. + + .. deprecated:: 1.0 + Use ``settings=OpenAIRealtimeSTTSettings(model=...)`` instead. + base_url: WebSocket base URL for the Realtime API. Defaults to ``"wss://api.openai.com/v1/realtime"``. language: Language of the audio input. Defaults to English. @@ -208,6 +229,8 @@ class OpenAIRealtimeSTTService(WebsocketSTTService): should_interrupt: Whether to interrupt bot output when speech is detected by server-side VAD. Only applies when turn detection is enabled. Defaults to True. + settings: Runtime-updatable settings. When provided alongside deprecated + parameters, ``settings`` values take precedence. ttfs_p99_latency: P99 latency from speech end to final transcript in seconds. Override for your deployment. See https://github.com/pipecat-ai/stt-benchmark **kwargs: Additional arguments passed to parent @@ -219,13 +242,20 @@ class OpenAIRealtimeSTTService(WebsocketSTTService): "Install it with: pip install pipecat-ai[openai]" ) + if model is not None: + _warn_deprecated_param("model", "OpenAIRealtimeSTTSettings", "model") + + default_settings = OpenAIRealtimeSTTSettings( + model=model or "gpt-4o-transcribe", + language=language, + prompt=prompt, + ) + if settings is not None: + default_settings.apply_update(settings) + super().__init__( ttfs_p99_latency=ttfs_p99_latency, - settings=OpenAIRealtimeSTTSettings( - model=model, - language=language, - prompt=prompt, - ), + settings=default_settings, **kwargs, ) diff --git a/src/pipecat/services/openai/tts.py b/src/pipecat/services/openai/tts.py index f95d79134..965b8faf7 100644 --- a/src/pipecat/services/openai/tts.py +++ b/src/pipecat/services/openai/tts.py @@ -25,7 +25,7 @@ from pipecat.frames.frames import ( TTSStartedFrame, TTSStoppedFrame, ) -from pipecat.services.settings import NOT_GIVEN, TTSSettings, _NotGiven +from pipecat.services.settings import NOT_GIVEN, TTSSettings, _NotGiven, _warn_deprecated_param from pipecat.services.tts_service import TTSService from pipecat.utils.tracing.service_decorators import traced_tts @@ -90,6 +90,9 @@ class OpenAITTSService(TTSService): class InputParams(BaseModel): """Input parameters for OpenAI TTS configuration. + .. deprecated:: 1.0 + Use ``settings=OpenAITTSSettings(...)`` instead. + Parameters: instructions: Instructions to guide voice synthesis behavior. speed: Voice speed control (0.25 to 4.0, default 1.0). @@ -103,12 +106,13 @@ class OpenAITTSService(TTSService): *, api_key: Optional[str] = None, base_url: Optional[str] = None, - voice: str = "alloy", - model: str = "gpt-4o-mini-tts", + voice: Optional[str] = None, + model: Optional[str] = None, sample_rate: Optional[int] = None, instructions: Optional[str] = None, speed: Optional[float] = None, params: Optional[InputParams] = None, + settings: Optional[OpenAITTSSettings] = None, **kwargs, ): """Initialize OpenAI TTS service. @@ -117,40 +121,69 @@ class OpenAITTSService(TTSService): api_key: OpenAI API key for authentication. If None, uses environment variable. base_url: Custom base URL for OpenAI API. If None, uses default. voice: Voice ID to use for synthesis. Defaults to "alloy". + + .. deprecated:: 1.0 + Use ``settings=OpenAITTSSettings(voice=...)`` instead. + model: TTS model to use. Defaults to "gpt-4o-mini-tts". + + .. deprecated:: 1.0 + Use ``settings=OpenAITTSSettings(model=...)`` instead. + sample_rate: Output audio sample rate in Hz. If None, uses OpenAI's default 24kHz. instructions: Optional instructions to guide voice synthesis behavior. - speed: Voice speed control (0.25 to 4.0, default 1.0). - params: Optional synthesis controls (acting instructions, speed, ...). - **kwargs: Additional keyword arguments passed to TTSService. - .. deprecated:: 0.0.91 - The `instructions` and `speed` parameters are deprecated, use `InputParams` instead. + .. deprecated:: 1.0 + Use ``settings=OpenAITTSSettings(instructions=...)`` instead. + + speed: Voice speed control (0.25 to 4.0, default 1.0). + + .. deprecated:: 1.0 + Use ``settings=OpenAITTSSettings(speed=...)`` instead. + + params: Optional synthesis controls (acting instructions, speed, ...). + + .. deprecated:: 1.0 + Use ``settings=OpenAITTSSettings(...)`` instead. + + settings: Runtime-updatable settings. When provided alongside deprecated + parameters, ``settings`` values take precedence. + **kwargs: Additional keyword arguments passed to TTSService. """ + if voice is not None: + _warn_deprecated_param("voice", "OpenAITTSSettings", "voice") + if model is not None: + _warn_deprecated_param("model", "OpenAITTSSettings", "model") + if instructions is not None: + _warn_deprecated_param("instructions", "OpenAITTSSettings", "instructions") + if speed is not None: + _warn_deprecated_param("speed", "OpenAITTSSettings", "speed") + if params is not None: + _warn_deprecated_param("params", "OpenAITTSSettings") + if sample_rate and sample_rate != self.OPENAI_SAMPLE_RATE: logger.warning( f"OpenAI TTS only supports {self.OPENAI_SAMPLE_RATE}Hz sample rate. " f"Current rate of {sample_rate}Hz may cause issues." ) - if instructions or speed: - import warnings - with warnings.catch_warnings(): - warnings.simplefilter("always") - warnings.warn( - "The `instructions` and `speed` parameters are deprecated, use `InputParams` instead.", - DeprecationWarning, - stacklevel=2, - ) + _params = params or OpenAITTSService.InputParams() + _instructions = instructions if instructions is not None else _params.instructions + _speed = speed if speed is not None else _params.speed + + default_settings = OpenAITTSSettings( + model=model or "gpt-4o-mini-tts", + voice=voice or "alloy", + language=None, + instructions=_instructions, + speed=_speed, + ) + if settings is not None: + default_settings.apply_update(settings) super().__init__( sample_rate=sample_rate, - settings=OpenAITTSSettings( - model=model, - voice=voice, - instructions=params.instructions if params else instructions, - speed=params.speed if params else speed, - ), + settings=default_settings, **kwargs, ) diff --git a/src/pipecat/services/openai_realtime_beta/openai.py b/src/pipecat/services/openai_realtime_beta/openai.py index c912ed45c..cb660ce72 100644 --- a/src/pipecat/services/openai_realtime_beta/openai.py +++ b/src/pipecat/services/openai_realtime_beta/openai.py @@ -54,7 +54,7 @@ from pipecat.processors.aggregators.openai_llm_context import ( from pipecat.processors.frame_processor import FrameDirection from pipecat.services.llm_service import FunctionCallFromLLM, LLMService from pipecat.services.openai.llm import OpenAIContextAggregatorPair -from pipecat.services.settings import NOT_GIVEN, LLMSettings, _NotGiven +from pipecat.services.settings import NOT_GIVEN, LLMSettings, _NotGiven, _warn_deprecated_param from pipecat.transcriptions.language import Language from pipecat.utils.time import time_now_iso8601 from pipecat.utils.tracing.service_decorators import traced_openai_realtime, traced_stt @@ -126,9 +126,10 @@ class OpenAIRealtimeBetaLLMService(LLMService): self, *, api_key: str, - model: str = "gpt-4o-realtime-preview-2025-06-03", + model: Optional[str] = None, base_url: str = "wss://api.openai.com/v1/realtime", session_properties: Optional[events.SessionProperties] = None, + settings: Optional[OpenAIRealtimeBetaLLMSettings] = None, start_audio_paused: bool = False, send_transcription_frames: bool = True, **kwargs, @@ -137,11 +138,22 @@ class OpenAIRealtimeBetaLLMService(LLMService): Args: api_key: OpenAI API key for authentication. - model: OpenAI model name. Defaults to "gpt-4o-realtime-preview-2025-06-03". + model: OpenAI model name. + + .. deprecated:: + Use ``settings=OpenAIRealtimeBetaLLMSettings(model=...)`` instead. + base_url: WebSocket base URL for the realtime API. Defaults to "wss://api.openai.com/v1/realtime". session_properties: Configuration properties for the realtime session. + + .. deprecated:: + Use ``settings=OpenAIRealtimeBetaLLMSettings(session_properties=...)`` + instead. + If None, uses default SessionProperties. + settings: Realtime Beta LLM settings. If provided together with deprecated + top-level parameters, the ``settings`` values take precedence. start_audio_paused: Whether to start with audio input paused. Defaults to False. send_transcription_frames: Whether to emit transcription frames. Defaults to True. **kwargs: Additional arguments passed to parent LLMService. @@ -155,22 +167,33 @@ class OpenAIRealtimeBetaLLMService(LLMService): stacklevel=2, ) - full_url = f"{base_url}?model={model}" + if model is not None: + _warn_deprecated_param("model", "OpenAIRealtimeBetaLLMSettings", "model") + if session_properties is not None: + _warn_deprecated_param( + "session_properties", "OpenAIRealtimeBetaLLMSettings", "session_properties" + ) + + default_settings = OpenAIRealtimeBetaLLMSettings( + model=model or "gpt-4o-realtime-preview-2025-06-03", + temperature=None, + max_tokens=None, + top_p=None, + top_k=None, + frequency_penalty=None, + presence_penalty=None, + seed=None, + filter_incomplete_user_turns=False, + user_turn_completion_config=None, + session_properties=session_properties or events.SessionProperties(), + ) + if settings is not None: + default_settings.apply_update(settings) + + full_url = f"{base_url}?model={default_settings.model}" super().__init__( base_url=full_url, - settings=OpenAIRealtimeBetaLLMSettings( - model=model, - temperature=None, - max_tokens=None, - top_p=None, - top_k=None, - frequency_penalty=None, - presence_penalty=None, - seed=None, - filter_incomplete_user_turns=False, - user_turn_completion_config=None, - session_properties=session_properties or events.SessionProperties(), - ), + settings=default_settings, **kwargs, ) diff --git a/src/pipecat/services/openpipe/llm.py b/src/pipecat/services/openpipe/llm.py index fa53c1554..524eff860 100644 --- a/src/pipecat/services/openpipe/llm.py +++ b/src/pipecat/services/openpipe/llm.py @@ -15,7 +15,9 @@ from typing import Dict, Optional from loguru import logger from pipecat.adapters.services.open_ai_adapter import OpenAILLMInvocationParams +from pipecat.services.openai.base_llm import OpenAILLMSettings from pipecat.services.openai.llm import OpenAILLMService +from pipecat.services.settings import _warn_deprecated_param try: from openpipe import AsyncOpenAI as OpenPipeAI @@ -36,31 +38,45 @@ class OpenPipeLLMService(OpenAILLMService): def __init__( self, *, - model: str = "gpt-4.1", + model: Optional[str] = None, api_key: Optional[str] = None, base_url: Optional[str] = None, openpipe_api_key: Optional[str] = None, openpipe_base_url: str = "https://app.openpipe.ai/api/v1", tags: Optional[Dict[str, str]] = None, + settings: Optional[OpenAILLMSettings] = None, **kwargs, ): """Initialize OpenPipe LLM service. Args: model: The model name to use. Defaults to "gpt-4.1". + + .. deprecated:: 1.0 + Use ``settings=OpenAILLMSettings(model=...)`` instead. + api_key: OpenAI API key for authentication. If None, reads from environment. base_url: Custom OpenAI API endpoint URL. Uses default if None. openpipe_api_key: OpenPipe API key for enhanced features. If None, reads from environment. openpipe_base_url: OpenPipe API endpoint URL. Defaults to "https://app.openpipe.ai/api/v1". tags: Optional dictionary of tags to apply to all requests for tracking. + settings: Runtime-updatable settings. When provided alongside deprecated + parameters, ``settings`` values take precedence. **kwargs: Additional arguments passed to parent OpenAILLMService. """ + if model is not None: + _warn_deprecated_param("model", "OpenAILLMSettings", "model") + + default_settings = OpenAILLMSettings(model=model or "gpt-4.1") + if settings is not None: + default_settings.apply_update(settings) + super().__init__( - model=model, api_key=api_key, base_url=base_url, openpipe_api_key=openpipe_api_key, openpipe_base_url=openpipe_base_url, + settings=default_settings, **kwargs, ) self._tags = tags diff --git a/src/pipecat/services/openrouter/llm.py b/src/pipecat/services/openrouter/llm.py index c33fda2fc..9b202c04d 100644 --- a/src/pipecat/services/openrouter/llm.py +++ b/src/pipecat/services/openrouter/llm.py @@ -14,7 +14,9 @@ from typing import Any, Dict, Optional from loguru import logger +from pipecat.services.openai.base_llm import OpenAILLMSettings from pipecat.services.openai.llm import OpenAILLMService +from pipecat.services.settings import _warn_deprecated_param class OpenRouterLLMService(OpenAILLMService): @@ -28,8 +30,9 @@ class OpenRouterLLMService(OpenAILLMService): self, *, api_key: Optional[str] = None, - model: str = "openai/gpt-4o-2024-11-20", + model: Optional[str] = None, base_url: str = "https://openrouter.ai/api/v1", + settings: Optional[OpenAILLMSettings] = None, **kwargs, ): """Initialize the OpenRouter LLM service. @@ -38,13 +41,26 @@ class OpenRouterLLMService(OpenAILLMService): api_key: The API key for accessing OpenRouter's API. If None, will attempt to read from environment variables. model: The model identifier to use. Defaults to "openai/gpt-4o-2024-11-20". + + .. deprecated:: 1.0 + Use ``settings=OpenAILLMSettings(model=...)`` instead. + base_url: The base URL for OpenRouter API. Defaults to "https://openrouter.ai/api/v1". + settings: Runtime-updatable settings. When provided alongside deprecated + parameters, ``settings`` values take precedence. **kwargs: Additional keyword arguments passed to OpenAILLMService. """ + if model is not None: + _warn_deprecated_param("model", "OpenAILLMSettings", "model") + + default_settings = OpenAILLMSettings(model=model or "openai/gpt-4o-2024-11-20") + if settings is not None: + default_settings.apply_update(settings) + super().__init__( api_key=api_key, base_url=base_url, - model=model, + settings=default_settings, **kwargs, ) diff --git a/src/pipecat/services/perplexity/llm.py b/src/pipecat/services/perplexity/llm.py index e03bace8d..b00f9e974 100644 --- a/src/pipecat/services/perplexity/llm.py +++ b/src/pipecat/services/perplexity/llm.py @@ -11,11 +11,15 @@ an OpenAI-compatible interface. It handles Perplexity's unique token usage reporting patterns while maintaining compatibility with the Pipecat framework. """ +from typing import Optional + from pipecat.adapters.services.open_ai_adapter import OpenAILLMInvocationParams from pipecat.metrics.metrics import LLMTokenUsage from pipecat.processors.aggregators.llm_context import LLMContext from pipecat.processors.aggregators.openai_llm_context import OpenAILLMContext +from pipecat.services.openai.base_llm import OpenAILLMSettings from pipecat.services.openai.llm import OpenAILLMService +from pipecat.services.settings import _warn_deprecated_param class PerplexityLLMService(OpenAILLMService): @@ -31,7 +35,8 @@ class PerplexityLLMService(OpenAILLMService): *, api_key: str, base_url: str = "https://api.perplexity.ai", - model: str = "sonar", + model: Optional[str] = None, + settings: Optional[OpenAILLMSettings] = None, **kwargs, ): """Initialize the Perplexity LLM service. @@ -40,9 +45,22 @@ class PerplexityLLMService(OpenAILLMService): api_key: The API key for accessing Perplexity's API. base_url: The base URL for Perplexity's API. Defaults to "https://api.perplexity.ai". model: The model identifier to use. Defaults to "sonar". + + .. deprecated:: 1.0 + Use ``settings=OpenAILLMSettings(model=...)`` instead. + + settings: Runtime-updatable settings. When provided alongside deprecated + parameters, ``settings`` values take precedence. **kwargs: Additional keyword arguments passed to OpenAILLMService. """ - super().__init__(api_key=api_key, base_url=base_url, model=model, **kwargs) + if model is not None: + _warn_deprecated_param("model", "OpenAILLMSettings", "model") + + default_settings = OpenAILLMSettings(model=model or "sonar") + if settings is not None: + default_settings.apply_update(settings) + + super().__init__(api_key=api_key, base_url=base_url, settings=default_settings, **kwargs) # Counters for accumulating token usage metrics self._prompt_tokens = 0 self._completion_tokens = 0 diff --git a/src/pipecat/services/piper/tts.py b/src/pipecat/services/piper/tts.py index c4831b839..559824b49 100644 --- a/src/pipecat/services/piper/tts.py +++ b/src/pipecat/services/piper/tts.py @@ -20,7 +20,7 @@ from pipecat.frames.frames import ( TTSStartedFrame, TTSStoppedFrame, ) -from pipecat.services.settings import TTSSettings +from pipecat.services.settings import TTSSettings, _warn_deprecated_param from pipecat.services.tts_service import TTSService from pipecat.utils.tracing.service_decorators import traced_tts @@ -53,41 +53,56 @@ class PiperTTSService(TTSService): def __init__( self, *, - voice_id: str, + voice_id: Optional[str] = None, download_dir: Optional[Path] = None, force_redownload: bool = False, use_cuda: bool = False, + settings: Optional[PiperTTSSettings] = None, **kwargs, ): """Initialize the Piper TTS service. Args: voice_id: Piper voice model identifier (e.g. `en_US-ryan-high`). + + .. deprecated:: 1.0 + Use ``settings=PiperTTSSettings(voice=...)`` instead. + download_dir: Directory for storing voice model files. Defaults to the current working directory. force_redownload: Re-download the voice model even if it already exists. use_cuda: Use CUDA for GPU-accelerated inference. + settings: Runtime-updatable settings. When provided alongside deprecated + parameters, ``settings`` values take precedence. **kwargs: Additional arguments passed to the parent `TTSService`. """ + if voice_id is not None: + _warn_deprecated_param("voice_id", "PiperTTSSettings", "voice") + + default_settings = PiperTTSSettings(model=None, voice=voice_id, language=None) + if settings is not None: + default_settings.apply_update(settings) + super().__init__( - settings=PiperTTSSettings(model=None, voice=voice_id, language=None), + settings=default_settings, **kwargs, ) download_dir = download_dir or Path.cwd() - model_file = f"{voice_id}.onnx" + _voice = self._settings.voice + model_file = f"{_voice}.onnx" model_path = Path(download_dir) / model_file if not model_path.exists(): - logger.debug(f"Downloading Piper '{voice_id}' model") - download_voice(voice_id, download_dir, force_redownload=force_redownload) + logger.debug(f"Downloading Piper '{_voice}' model") + download_voice(_voice, download_dir, force_redownload=force_redownload) - logger.debug(f"Loading Piper '{voice_id}' model from {model_path}") + logger.debug(f"Loading Piper '{_voice}' model from {model_path}") self._voice = PiperVoice.load(model_path, use_cuda=use_cuda) - logger.debug(f"Loaded Piper '{voice_id}' model") + logger.debug(f"Loaded Piper '{_voice}' model") def can_generate_metrics(self) -> bool: """Check if this service can generate processing metrics. @@ -190,6 +205,7 @@ class PiperHttpTTSService(TTSService): base_url: str, aiohttp_session: aiohttp.ClientSession, voice_id: Optional[str] = None, + settings: Optional[PiperHttpTTSSettings] = None, **kwargs, ): """Initialize the Piper TTS service. @@ -198,10 +214,23 @@ class PiperHttpTTSService(TTSService): base_url: Base URL for the Piper TTS HTTP server. aiohttp_session: aiohttp ClientSession for making HTTP requests. voice_id: Piper voice model identifier (e.g. `en_US-ryan-high`). + + .. deprecated:: 1.0 + Use ``settings=PiperHttpTTSSettings(voice=...)`` instead. + + settings: Runtime-updatable settings. When provided alongside deprecated + parameters, ``settings`` values take precedence. **kwargs: Additional arguments passed to the parent TTSService. """ + if voice_id is not None: + _warn_deprecated_param("voice_id", "PiperHttpTTSSettings", "voice") + + default_settings = PiperHttpTTSSettings(model=None, voice=voice_id, language=None) + if settings is not None: + default_settings.apply_update(settings) + super().__init__( - settings=PiperHttpTTSSettings(model=None, voice=voice_id, language=None), + settings=default_settings, **kwargs, ) diff --git a/src/pipecat/services/qwen/llm.py b/src/pipecat/services/qwen/llm.py index 6b58faea2..132924662 100644 --- a/src/pipecat/services/qwen/llm.py +++ b/src/pipecat/services/qwen/llm.py @@ -6,9 +6,13 @@ """Qwen LLM service implementation using OpenAI-compatible interface.""" +from typing import Optional + from loguru import logger +from pipecat.services.openai.base_llm import OpenAILLMSettings from pipecat.services.openai.llm import OpenAILLMService +from pipecat.services.settings import _warn_deprecated_param class QwenLLMService(OpenAILLMService): @@ -23,7 +27,8 @@ class QwenLLMService(OpenAILLMService): *, api_key: str, base_url: str = "https://dashscope-intl.aliyuncs.com/compatible-mode/v1", - model: str = "qwen-plus", + model: Optional[str] = None, + settings: Optional[OpenAILLMSettings] = None, **kwargs, ): """Initialize the Qwen LLM service. @@ -32,10 +37,23 @@ class QwenLLMService(OpenAILLMService): api_key: The API key for accessing Qwen's API (DashScope API key). base_url: Base URL for Qwen API. Defaults to "https://dashscope-intl.aliyuncs.com/compatible-mode/v1". model: The model identifier to use. Defaults to "qwen-plus". + + .. deprecated:: 1.0 + Use ``settings=OpenAILLMSettings(model=...)`` instead. + + settings: Runtime-updatable settings. When provided alongside deprecated + parameters, ``settings`` values take precedence. **kwargs: Additional keyword arguments passed to OpenAILLMService. """ - super().__init__(api_key=api_key, base_url=base_url, model=model, **kwargs) - logger.info(f"Initialized Qwen LLM service with model: {model}") + if model is not None: + _warn_deprecated_param("model", "OpenAILLMSettings", "model") + + default_settings = OpenAILLMSettings(model=model or "qwen-plus") + if settings is not None: + default_settings.apply_update(settings) + + super().__init__(api_key=api_key, base_url=base_url, settings=default_settings, **kwargs) + logger.info(f"Initialized Qwen LLM service with model: {self._settings.model}") def create_client(self, api_key=None, base_url=None, **kwargs): """Create OpenAI-compatible client for Qwen API endpoint. diff --git a/src/pipecat/services/resembleai/tts.py b/src/pipecat/services/resembleai/tts.py index 1c2953b72..148dacde2 100644 --- a/src/pipecat/services/resembleai/tts.py +++ b/src/pipecat/services/resembleai/tts.py @@ -23,7 +23,7 @@ from pipecat.frames.frames import ( TTSStartedFrame, TTSStoppedFrame, ) -from pipecat.services.settings import NOT_GIVEN, TTSSettings, _NotGiven +from pipecat.services.settings import NOT_GIVEN, TTSSettings, _NotGiven, _warn_deprecated_param from pipecat.services.tts_service import AudioContextTTSService from pipecat.utils.tracing.service_decorators import traced_tts @@ -70,11 +70,12 @@ class ResembleAITTSService(AudioContextTTSService): self, *, api_key: str, - voice_id: str, + voice_id: Optional[str] = None, url: str = "wss://websocket.cluster.resemble.ai/stream", precision: Optional[str] = "PCM_16", output_format: Optional[str] = "wav", sample_rate: Optional[int] = 22050, + settings: Optional[ResembleAITTSSettings] = None, **kwargs, ): """Initialize the Resemble AI TTS service. @@ -82,24 +83,37 @@ class ResembleAITTSService(AudioContextTTSService): Args: api_key: Resemble AI API key for authentication. voice_id: Voice UUID to use for synthesis. + + .. deprecated:: 1.0 + Use ``settings=ResembleAITTSSettings(voice=...)`` instead. + url: WebSocket URL for Resemble AI TTS API. precision: PCM bit depth (PCM_32, PCM_24, PCM_16, or MULAW). output_format: Audio format (wav or mp3). sample_rate: Audio sample rate (8000, 16000, 22050, 32000, or 44100). Defaults to 22050. + settings: Runtime-updatable settings. When provided alongside deprecated + parameters, ``settings`` values take precedence. **kwargs: Additional arguments passed to the parent service. """ + if voice_id is not None: + _warn_deprecated_param("voice_id", "ResembleAITTSSettings", "voice") + + default_settings = ResembleAITTSSettings( + model=None, + voice=voice_id, + language=None, + precision=precision, + output_format=output_format, + resemble_sample_rate=sample_rate, + ) + if settings is not None: + default_settings.apply_update(settings) + super().__init__( sample_rate=sample_rate, reuse_context_id_within_turn=False, supports_word_timestamps=True, - settings=ResembleAITTSSettings( - model=None, - voice=voice_id, - language=None, - precision=precision, - output_format=output_format, - resemble_sample_rate=sample_rate, - ), + settings=default_settings, **kwargs, ) diff --git a/src/pipecat/services/rime/tts.py b/src/pipecat/services/rime/tts.py index 944ff4e58..a44b738d1 100644 --- a/src/pipecat/services/rime/tts.py +++ b/src/pipecat/services/rime/tts.py @@ -31,7 +31,7 @@ from pipecat.frames.frames import ( TTSStoppedFrame, ) from pipecat.processors.frame_processor import FrameDirection -from pipecat.services.settings import NOT_GIVEN, TTSSettings, _NotGiven +from pipecat.services.settings import NOT_GIVEN, TTSSettings, _NotGiven, _warn_deprecated_param from pipecat.services.tts_service import ( AudioContextTTSService, InterruptibleTTSService, @@ -144,6 +144,9 @@ class RimeTTSService(AudioContextTTSService): class InputParams(BaseModel): """Configuration parameters for Rime TTS service. + .. deprecated:: 1.0 + Use ``settings=RimeTTSSettings(...)`` instead. + Parameters: language: Language for synthesis. Defaults to English. segment: Text segmentation mode ("immediate", "bySentence", "never"). @@ -176,11 +179,12 @@ class RimeTTSService(AudioContextTTSService): self, *, api_key: str, - voice_id: str, + voice_id: Optional[str] = None, url: str = "wss://users-ws.rime.ai/ws3", - model: str = "arcana", + model: Optional[str] = None, sample_rate: Optional[int] = None, params: Optional[InputParams] = None, + settings: Optional[RimeTTSSettings] = None, text_aggregator: Optional[BaseTextAggregator] = None, text_aggregation_mode: Optional[TextAggregationMode] = None, aggregate_sentences: Optional[bool] = None, @@ -191,10 +195,24 @@ class RimeTTSService(AudioContextTTSService): Args: api_key: Rime API key for authentication. voice_id: ID of the voice to use. + + .. deprecated:: 1.0 + Use ``settings=RimeTTSSettings(voice=...)`` instead. + url: Rime websocket API endpoint. model: Model ID to use for synthesis. + + .. deprecated:: 1.0 + Use ``settings=RimeTTSSettings(model=...)`` instead. + sample_rate: Audio sample rate in Hz. params: Additional configuration parameters. + + .. deprecated:: 1.0 + Use ``settings=RimeTTSSettings(...)`` instead. + + settings: Runtime-updatable settings. When provided alongside deprecated + parameters, ``settings`` values take precedence. text_aggregator: Custom text aggregator for processing input text. .. deprecated:: 0.0.95 @@ -208,8 +226,40 @@ class RimeTTSService(AudioContextTTSService): **kwargs: Additional arguments passed to parent class. """ + if voice_id is not None: + _warn_deprecated_param("voice_id", "RimeTTSSettings", "voice") + if model is not None: + _warn_deprecated_param("model", "RimeTTSSettings", "model") + if params is not None: + _warn_deprecated_param("params", "RimeTTSSettings") + # Initialize with parent class settings for proper frame handling - params = params or RimeTTSService.InputParams() + _params = params or RimeTTSService.InputParams() + + default_settings = RimeTTSSettings( + model=model or "arcana", + voice=voice_id, + audioFormat="pcm", + samplingRate=0, # updated in start() + language=self.language_to_service_language(_params.language) + if _params.language + else None, + segment=_params.segment, + inlineSpeedAlpha=None, # Not applicable here + speedAlpha=_params.speed_alpha, + # Arcana params + repetition_penalty=_params.repetition_penalty, + temperature=_params.temperature, + top_p=_params.top_p, + # Mistv2 params + reduceLatency=_params.reduce_latency, + pauseBetweenBrackets=_params.pause_between_brackets, + phonemizeBetweenBrackets=_params.phonemize_between_brackets, + noTextNormalization=_params.no_text_normalization, + saveOovs=_params.save_oovs, + ) + if settings is not None: + default_settings.apply_update(settings) super().__init__( text_aggregation_mode=text_aggregation_mode, @@ -220,28 +270,7 @@ class RimeTTSService(AudioContextTTSService): supports_word_timestamps=True, append_trailing_space=True, sample_rate=sample_rate, - settings=RimeTTSSettings( - model=model, - voice=voice_id, - audioFormat="pcm", - samplingRate=0, # updated in start() - language=self.language_to_service_language(params.language) - if params.language - else None, - segment=params.segment, - inlineSpeedAlpha=None, # Not applicable here - speedAlpha=params.speed_alpha, - # Arcana params - repetition_penalty=params.repetition_penalty, - temperature=params.temperature, - top_p=params.top_p, - # Mistv2 params - reduceLatency=params.reduce_latency, - pauseBetweenBrackets=params.pause_between_brackets, - phonemizeBetweenBrackets=params.phonemize_between_brackets, - noTextNormalization=params.no_text_normalization, - saveOovs=params.save_oovs, - ), + settings=default_settings, **kwargs, ) @@ -628,6 +657,9 @@ class RimeHttpTTSService(TTSService): class InputParams(BaseModel): """Configuration parameters for Rime HTTP TTS service. + .. deprecated:: 1.0 + Use ``settings=RimeTTSSettings(...)`` instead. + Parameters: language: Language for synthesis. Defaults to English. pause_between_brackets: Whether to add pauses between bracketed content. @@ -648,11 +680,12 @@ class RimeHttpTTSService(TTSService): self, *, api_key: str, - voice_id: str, + voice_id: Optional[str] = None, aiohttp_session: aiohttp.ClientSession, - model: str = "mistv2", + model: Optional[str] = None, sample_rate: Optional[int] = None, params: Optional[InputParams] = None, + settings: Optional[RimeTTSSettings] = None, **kwargs, ): """Initialize Rime HTTP TTS service. @@ -660,36 +693,61 @@ class RimeHttpTTSService(TTSService): Args: api_key: Rime API key for authentication. voice_id: ID of the voice to use. + + .. deprecated:: 1.0 + Use ``settings=RimeTTSSettings(voice=...)`` instead. + aiohttp_session: Shared aiohttp session for HTTP requests. model: Model ID to use for synthesis. + + .. deprecated:: 1.0 + Use ``settings=RimeTTSSettings(model=...)`` instead. + sample_rate: Audio sample rate in Hz. params: Additional configuration parameters. + + .. deprecated:: 1.0 + Use ``settings=RimeTTSSettings(...)`` instead. + + settings: Runtime-updatable settings. When provided alongside deprecated + parameters, ``settings`` values take precedence. **kwargs: Additional arguments passed to parent TTSService. """ - params = params or RimeHttpTTSService.InputParams() + if voice_id is not None: + _warn_deprecated_param("voice_id", "RimeTTSSettings", "voice") + if model is not None: + _warn_deprecated_param("model", "RimeTTSSettings", "model") + if params is not None: + _warn_deprecated_param("params", "RimeTTSSettings") + + _params = params or RimeHttpTTSService.InputParams() + + default_settings = RimeTTSSettings( + model=model or "mistv2", + language=self.language_to_service_language(_params.language) + if _params.language + else "eng", + audioFormat="pcm", + samplingRate=0, + segment=None, + speedAlpha=_params.speed_alpha, + reduceLatency=_params.reduce_latency, + pauseBetweenBrackets=_params.pause_between_brackets, + phonemizeBetweenBrackets=_params.phonemize_between_brackets, + noTextNormalization=None, + saveOovs=None, + inlineSpeedAlpha=_params.inline_speed_alpha if _params.inline_speed_alpha else None, + repetition_penalty=None, + temperature=None, + top_p=None, + voice=voice_id, + ) + if settings is not None: + default_settings.apply_update(settings) super().__init__( sample_rate=sample_rate, - settings=RimeTTSSettings( - model=model, - language=self.language_to_service_language(params.language) - if params.language - else "eng", - audioFormat="pcm", - samplingRate=0, - segment=None, - speedAlpha=params.speed_alpha, - reduceLatency=params.reduce_latency, - pauseBetweenBrackets=params.pause_between_brackets, - phonemizeBetweenBrackets=params.phonemize_between_brackets, - noTextNormalization=None, - saveOovs=None, - inlineSpeedAlpha=params.inline_speed_alpha if params.inline_speed_alpha else None, - repetition_penalty=None, - temperature=None, - top_p=None, - voice=voice_id, - ), + settings=default_settings, **kwargs, ) @@ -810,6 +868,9 @@ class RimeNonJsonTTSService(InterruptibleTTSService): class InputParams(BaseModel): """Configuration parameters for Rime Non-JSON WebSocket TTS service. + .. deprecated:: 1.0 + Use ``settings=RimeNonJsonTTSSettings(...)`` instead. + Args: language: Language for synthesis. Defaults to English. segment: Text segmentation mode ("immediate", "bySentence", "never"). @@ -830,12 +891,13 @@ class RimeNonJsonTTSService(InterruptibleTTSService): self, *, api_key: str, - voice_id: str, + voice_id: Optional[str] = None, url: str = "wss://users.rime.ai/ws", - model: str = "arcana", + model: Optional[str] = None, audio_format: str = "pcm", sample_rate: Optional[int] = None, params: Optional[InputParams] = None, + settings: Optional[RimeNonJsonTTSSettings] = None, aggregate_sentences: Optional[bool] = None, text_aggregation_mode: Optional[TextAggregationMode] = None, **kwargs, @@ -845,11 +907,25 @@ class RimeNonJsonTTSService(InterruptibleTTSService): Args: api_key: Rime API key for authentication. voice_id: ID of the voice to use. + + .. deprecated:: 1.0 + Use ``settings=RimeNonJsonTTSSettings(voice=...)`` instead. + url: Rime websocket API endpoint. model: Model ID to use for synthesis. + + .. deprecated:: 1.0 + Use ``settings=RimeNonJsonTTSSettings(model=...)`` instead. + audio_format: Audio format to use. sample_rate: Audio sample rate in Hz. params: Additional configuration parameters. + + .. deprecated:: 1.0 + Use ``settings=RimeNonJsonTTSSettings(...)`` instead. + + settings: Runtime-updatable settings. When provided alongside deprecated + parameters, ``settings`` values take precedence. aggregate_sentences: Deprecated. Use text_aggregation_mode instead. .. deprecated:: 0.0.104 @@ -860,7 +936,31 @@ class RimeNonJsonTTSService(InterruptibleTTSService): text_aggregation_mode: How to aggregate text before synthesis. **kwargs: Additional arguments passed to parent class. """ - params = params or RimeNonJsonTTSService.InputParams() + if voice_id is not None: + _warn_deprecated_param("voice_id", "RimeNonJsonTTSSettings", "voice") + if model is not None: + _warn_deprecated_param("model", "RimeNonJsonTTSSettings", "model") + if params is not None: + _warn_deprecated_param("params", "RimeNonJsonTTSSettings") + + _params = params or RimeNonJsonTTSService.InputParams() + + default_settings = RimeNonJsonTTSSettings( + voice=voice_id, + model=model or "arcana", + audioFormat=audio_format, + samplingRate=sample_rate, + language=self.language_to_service_language(_params.language) + if _params.language + else None, + segment=_params.segment, + repetition_penalty=_params.repetition_penalty, + temperature=_params.temperature, + top_p=_params.top_p, + ) + if settings is not None: + default_settings.apply_update(settings) + super().__init__( sample_rate=sample_rate, aggregate_sentences=aggregate_sentences, @@ -868,26 +968,14 @@ class RimeNonJsonTTSService(InterruptibleTTSService): push_stop_frames=True, pause_frame_processing=True, append_trailing_space=True, - settings=RimeNonJsonTTSSettings( - voice=voice_id, - model=model, - audioFormat=audio_format, - samplingRate=sample_rate, - language=self.language_to_service_language(params.language) - if params.language - else None, - segment=params.segment, - repetition_penalty=params.repetition_penalty, - temperature=params.temperature, - top_p=params.top_p, - ), + settings=default_settings, **kwargs, ) self._api_key = api_key self._url = url # Add any extra parameters for future compatibility - if params.extra: - self._settings.extra.update(params.extra) + if _params.extra: + self._settings.extra.update(_params.extra) self._receive_task = None self._context_id: Optional[str] = None diff --git a/src/pipecat/services/sambanova/llm.py b/src/pipecat/services/sambanova/llm.py index 016e1740d..23d415598 100644 --- a/src/pipecat/services/sambanova/llm.py +++ b/src/pipecat/services/sambanova/llm.py @@ -21,7 +21,9 @@ from pipecat.metrics.metrics import LLMTokenUsage from pipecat.processors.aggregators.llm_context import LLMContext from pipecat.processors.aggregators.openai_llm_context import OpenAILLMContext from pipecat.services.llm_service import FunctionCallFromLLM +from pipecat.services.openai.base_llm import OpenAILLMSettings from pipecat.services.openai.llm import OpenAILLMService +from pipecat.services.settings import _warn_deprecated_param from pipecat.utils.tracing.service_decorators import traced_llm @@ -36,8 +38,9 @@ class SambaNovaLLMService(OpenAILLMService): # type: ignore self, *, api_key: str, - model: str = "Llama-4-Maverick-17B-128E-Instruct", + model: Optional[str] = None, base_url: str = "https://api.sambanova.ai/v1", + settings: Optional[OpenAILLMSettings] = None, **kwargs: Dict[Any, Any], ) -> None: """Initialize SambaNova LLM service. @@ -45,10 +48,23 @@ class SambaNovaLLMService(OpenAILLMService): # type: ignore Args: api_key: The API key for accessing SambaNova API. model: The model identifier to use. Defaults to "Llama-4-Maverick-17B-128E-Instruct". + + .. deprecated:: 1.0 + Use ``settings=OpenAILLMSettings(model=...)`` instead. + base_url: The base URL for SambaNova API. Defaults to "https://api.sambanova.ai/v1". + settings: Runtime-updatable settings. When provided alongside deprecated + parameters, ``settings`` values take precedence. **kwargs: Additional keyword arguments passed to OpenAILLMService. """ - super().__init__(api_key=api_key, base_url=base_url, model=model, **kwargs) + if model is not None: + _warn_deprecated_param("model", "OpenAILLMSettings", "model") + + default_settings = OpenAILLMSettings(model=model or "Llama-4-Maverick-17B-128E-Instruct") + if settings is not None: + default_settings.apply_update(settings) + + super().__init__(api_key=api_key, base_url=base_url, settings=default_settings, **kwargs) def create_client( self, diff --git a/src/pipecat/services/sambanova/stt.py b/src/pipecat/services/sambanova/stt.py index f313f0d7b..4e3c9e01d 100644 --- a/src/pipecat/services/sambanova/stt.py +++ b/src/pipecat/services/sambanova/stt.py @@ -10,8 +10,13 @@ from typing import Any, Optional from loguru import logger +from pipecat.services.settings import _warn_deprecated_param from pipecat.services.stt_latency import SAMBANOVA_TTFS_P99 -from pipecat.services.whisper.base_stt import BaseWhisperSTTService, Transcription +from pipecat.services.whisper.base_stt import ( + BaseWhisperSTTService, + BaseWhisperSTTSettings, + Transcription, +) from pipecat.transcriptions.language import Language @@ -25,35 +30,75 @@ class SambaNovaSTTService(BaseWhisperSTTService): # type: ignore def __init__( self, *, - model: str = "Whisper-Large-v3", + model: Optional[str] = None, api_key: Optional[str] = None, base_url: str = "https://api.sambanova.ai/v1", - language: Optional[Language] = Language.EN, + language: Optional[Language] = None, prompt: Optional[str] = None, temperature: Optional[float] = None, + settings: Optional[BaseWhisperSTTSettings] = None, ttfs_p99_latency: Optional[float] = SAMBANOVA_TTFS_P99, **kwargs: Any, ) -> None: """Initialize SambaNova STT service. Args: - model: Whisper model to use. Defaults to "Whisper-Large-v3". + model: Whisper model to use. + + .. deprecated:: 1.0 + Use ``settings=BaseWhisperSTTSettings(model=...)`` instead. + api_key: SambaNova API key. Defaults to None. base_url: API base URL. Defaults to "https://api.sambanova.ai/v1". - language: Language of the audio input. Defaults to English. + language: Language of the audio input. + + .. deprecated:: 1.0 + Use ``settings=BaseWhisperSTTSettings(language=...)`` instead. + prompt: Optional text to guide the model's style or continue a previous segment. - temperature: Optional sampling temperature between 0 and 1. Defaults to 0.0. + + .. deprecated:: 1.0 + Use ``settings=BaseWhisperSTTSettings(prompt=...)`` instead. + + temperature: Optional sampling temperature between 0 and 1. + + .. deprecated:: 1.0 + Use ``settings=BaseWhisperSTTSettings(temperature=...)`` instead. + + settings: Runtime-updatable settings. When provided alongside deprecated + parameters, ``settings`` values take precedence. ttfs_p99_latency: P99 latency from speech end to final transcript in seconds. Override for your deployment. See https://github.com/pipecat-ai/stt-benchmark **kwargs: Additional arguments passed to `pipecat.services.whisper.base_stt.BaseWhisperSTTService`. """ - super().__init__( + if model is not None: + _warn_deprecated_param("model", "BaseWhisperSTTSettings", "model") + if language is not None: + _warn_deprecated_param("language", "BaseWhisperSTTSettings", "language") + if prompt is not None: + _warn_deprecated_param("prompt", "BaseWhisperSTTSettings", "prompt") + if temperature is not None: + _warn_deprecated_param("temperature", "BaseWhisperSTTSettings", "temperature") + + model = model or "Whisper-Large-v3" + language = language or Language.EN + + # Build settings from deprecated params and pass via settings= + # to avoid double deprecation warnings in BaseWhisperSTTService. + default_settings = BaseWhisperSTTSettings( model=model, - api_key=api_key, + language=self.language_to_service_language(language), base_url=base_url, - language=language, prompt=prompt, temperature=temperature, + ) + if settings is not None: + default_settings.apply_update(settings) + + super().__init__( + api_key=api_key, + base_url=base_url, + settings=default_settings, ttfs_p99_latency=ttfs_p99_latency, **kwargs, ) diff --git a/src/pipecat/services/sarvam/stt.py b/src/pipecat/services/sarvam/stt.py index e368ceb02..b3ac41470 100644 --- a/src/pipecat/services/sarvam/stt.py +++ b/src/pipecat/services/sarvam/stt.py @@ -32,7 +32,13 @@ from pipecat.frames.frames import ( ) from pipecat.processors.frame_processor import FrameDirection from pipecat.services.sarvam._sdk import sdk_headers -from pipecat.services.settings import NOT_GIVEN, STTSettings, _NotGiven, is_given +from pipecat.services.settings import ( + NOT_GIVEN, + STTSettings, + _NotGiven, + _warn_deprecated_param, + is_given, +) from pipecat.services.stt_latency import SARVAM_TTFS_P99 from pipecat.services.stt_service import STTService from pipecat.transcriptions.language import Language, resolve_language @@ -171,6 +177,9 @@ class SarvamSTTService(STTService): class InputParams(BaseModel): """Configuration parameters for Sarvam STT service. + .. deprecated:: 1.0 + Use ``settings=SarvamSTTSettings(...)`` instead. + Parameters: language: Target language for transcription. - saarika:v2.5: Defaults to "unknown" (auto-detect supported) @@ -194,10 +203,11 @@ class SarvamSTTService(STTService): self, *, api_key: str, - model: str = "saarika:v2.5", + model: Optional[str] = None, sample_rate: Optional[int] = None, input_audio_codec: str = "wav", params: Optional[InputParams] = None, + settings: Optional[SarvamSTTSettings] = None, ttfs_p99_latency: Optional[float] = SARVAM_TTFS_P99, keepalive_timeout: Optional[float] = None, keepalive_interval: float = 5.0, @@ -207,13 +217,20 @@ class SarvamSTTService(STTService): Args: api_key: Sarvam API key for authentication. - model: Sarvam model to use for transcription. Allowed values: - - "saarika:v2.5": Standard STT model - - "saaras:v2.5": STT-Translate model (auto-detects language, supports prompts) - - "saaras:v3": Advanced STT model (supports mode) + model: Sarvam model to use for transcription. + + .. deprecated:: 1.0 + Use ``settings=SarvamSTTSettings(model=...)`` instead. + sample_rate: Audio sample rate. Defaults to 16000 if not specified. input_audio_codec: Audio codec/format of the input file. Defaults to "wav". params: Configuration parameters for Sarvam STT service. + + .. deprecated:: 1.0 + Use ``settings=SarvamSTTSettings(...)`` instead. + + settings: Runtime-updatable settings. When provided alongside deprecated + parameters, ``settings`` values take precedence. ttfs_p99_latency: P99 latency from speech end to final transcript in seconds. Override for your deployment. See https://github.com/pipecat-ai/stt-benchmark keepalive_timeout: Seconds of no audio before sending silence to keep the @@ -221,7 +238,13 @@ class SarvamSTTService(STTService): keepalive_interval: Seconds between idle checks when keepalive is enabled. **kwargs: Additional arguments passed to the parent STTService. """ - params = params or SarvamSTTService.InputParams() + if model is not None: + _warn_deprecated_param("model", "SarvamSTTSettings", "model") + if params is not None: + _warn_deprecated_param("params", "SarvamSTTSettings") + + model = model or "saarika:v2.5" + _params = params or SarvamSTTService.InputParams() # Get model configuration (validates model exists) if model not in MODEL_CONFIGS: @@ -231,31 +254,35 @@ class SarvamSTTService(STTService): self._config = MODEL_CONFIGS[model] # Validate parameters against model capabilities - if params.prompt is not None and not self._config.supports_prompt: + if _params.prompt is not None and not self._config.supports_prompt: raise ValueError(f"Model '{model}' does not support prompt parameter.") - if params.mode is not None and not self._config.supports_mode: + if _params.mode is not None and not self._config.supports_mode: raise ValueError(f"Model '{model}' does not support mode parameter.") - if params.language is not None and not self._config.supports_language: + if _params.language is not None and not self._config.supports_language: raise ValueError( f"Model '{model}' does not support language parameter (auto-detects language)." ) # Resolve mode default from model config - mode = params.mode if params.mode is not None else self._config.default_mode + mode = _params.mode if _params.mode is not None else self._config.default_mode + + default_settings = SarvamSTTSettings( + model=model, + language=_params.language, + prompt=_params.prompt, + mode=mode, + vad_signals=_params.vad_signals, + high_vad_sensitivity=_params.high_vad_sensitivity, + ) + if settings is not None: + default_settings.apply_update(settings) super().__init__( sample_rate=sample_rate, ttfs_p99_latency=ttfs_p99_latency, keepalive_timeout=keepalive_timeout, keepalive_interval=keepalive_interval, - settings=SarvamSTTSettings( - model=model, - language=params.language, - prompt=params.prompt, - mode=mode, - vad_signals=params.vad_signals, - high_vad_sensitivity=params.high_vad_sensitivity, - ), + settings=default_settings, **kwargs, ) @@ -274,7 +301,7 @@ class SarvamSTTService(STTService): self._socket_client = None self._receive_task = None - if params.vad_signals: + if _params.vad_signals: self._register_event_handler("on_speech_started") self._register_event_handler("on_speech_stopped") self._register_event_handler("on_utterance_end") diff --git a/src/pipecat/services/sarvam/tts.py b/src/pipecat/services/sarvam/tts.py index c18933407..4d125dfc9 100644 --- a/src/pipecat/services/sarvam/tts.py +++ b/src/pipecat/services/sarvam/tts.py @@ -62,7 +62,7 @@ from pipecat.frames.frames import ( ) from pipecat.processors.frame_processor import FrameDirection from pipecat.services.sarvam._sdk import sdk_headers -from pipecat.services.settings import NOT_GIVEN, TTSSettings, _NotGiven +from pipecat.services.settings import NOT_GIVEN, TTSSettings, _NotGiven, _warn_deprecated_param from pipecat.services.tts_service import InterruptibleTTSService, TextAggregationMode, TTSService from pipecat.transcriptions.language import Language, resolve_language from pipecat.utils.tracing.service_decorators import traced_tts @@ -376,6 +376,9 @@ class SarvamHttpTTSService(TTSService): class InputParams(BaseModel): """Input parameters for Sarvam TTS configuration. + .. deprecated:: 1.0 + Use ``SarvamHttpTTSSettings`` directly via the ``settings`` parameter instead. + Parameters: language: Language for synthesis. Defaults to English (India). pitch: Voice pitch adjustment (-0.75 to 0.75). Defaults to 0.0. @@ -428,10 +431,11 @@ class SarvamHttpTTSService(TTSService): api_key: str, aiohttp_session: aiohttp.ClientSession, voice_id: Optional[str] = None, - model: str = "bulbul:v2", + model: Optional[str] = None, base_url: str = "https://api.sarvam.ai", sample_rate: Optional[int] = None, params: Optional[InputParams] = None, + settings: Optional[SarvamHttpTTSSettings] = None, **kwargs, ): """Initialize the Sarvam TTS service. @@ -440,15 +444,38 @@ class SarvamHttpTTSService(TTSService): api_key: Sarvam AI API subscription key. aiohttp_session: Shared aiohttp session for making requests. voice_id: Speaker voice ID. If None, uses model-appropriate default. + + .. deprecated:: 1.0 + Use ``settings=SarvamHttpTTSSettings(voice=...)`` instead. + model: TTS model to use. Options: - "bulbul:v2" (default): Standard model with pitch/loudness support - "bulbul:v3-beta": Advanced model with temperature control + + .. deprecated:: 1.0 + Use ``settings=SarvamHttpTTSSettings(model=...)`` instead. + base_url: Sarvam AI API base URL. Defaults to "https://api.sarvam.ai". sample_rate: Audio sample rate in Hz (8000, 16000, 22050, 24000). If None, uses model-specific default. params: Additional voice and preprocessing parameters. If None, uses defaults. + + .. deprecated:: 1.0 + Use ``settings=SarvamHttpTTSSettings(...)`` instead. + + settings: Runtime-updatable settings. When provided alongside deprecated + parameters, ``settings`` values take precedence. **kwargs: Additional arguments passed to parent TTSService. """ + if voice_id is not None: + _warn_deprecated_param("voice_id", "SarvamHttpTTSSettings", "voice") + if model is not None: + _warn_deprecated_param("model", "SarvamHttpTTSSettings", "model") + if params is not None: + _warn_deprecated_param("params", "SarvamHttpTTSSettings") + + model = model or "bulbul:v2" + # Get model configuration (validates model exists) if model not in TTS_MODEL_CONFIGS: allowed = ", ".join(sorted(TTS_MODEL_CONFIGS.keys())) @@ -460,39 +487,39 @@ class SarvamHttpTTSService(TTSService): if sample_rate is None: sample_rate = self._config.default_sample_rate - params = params or SarvamHttpTTSService.InputParams() + _params = params or SarvamHttpTTSService.InputParams() # Set default voice based on model if not specified if voice_id is None: voice_id = self._config.default_speaker # Validate and clamp pace to model's valid range - pace = params.pace + pace = _params.pace pace_min, pace_max = self._config.pace_range if pace is not None and (pace < pace_min or pace > pace_max): logger.warning(f"Pace {pace} is outside model range ({pace_min}-{pace_max}). Clamping.") pace = max(pace_min, min(pace_max, pace)) + default_settings = SarvamHttpTTSSettings( + language=( + self.language_to_service_language(_params.language) if _params.language else "en-IN" + ), + enable_preprocessing=( + True if self._config.preprocessing_always_enabled else _params.enable_preprocessing + ), + pace=pace, + pitch=None, + loudness=None, + temperature=None, + model=model, + voice=voice_id, + ) + if settings is not None: + default_settings.apply_update(settings) + super().__init__( sample_rate=sample_rate, - settings=SarvamHttpTTSSettings( - language=( - self.language_to_service_language(params.language) - if params.language - else "en-IN" - ), - enable_preprocessing=( - True - if self._config.preprocessing_always_enabled - else params.enable_preprocessing - ), - pace=pace, - pitch=None, - loudness=None, - temperature=None, - model=model, - voice=voice_id, - ), + settings=default_settings, **kwargs, ) @@ -502,18 +529,18 @@ class SarvamHttpTTSService(TTSService): # Add parameters based on model support if self._config.supports_pitch: - self._settings.pitch = params.pitch - elif params.pitch != 0.0: + self._settings.pitch = _params.pitch + elif _params.pitch != 0.0: logger.warning(f"pitch parameter is ignored for {model}") if self._config.supports_loudness: - self._settings.loudness = params.loudness - elif params.loudness != 1.0: + self._settings.loudness = _params.loudness + elif _params.loudness != 1.0: logger.warning(f"loudness parameter is ignored for {model}") if self._config.supports_temperature: - self._settings.temperature = params.temperature - elif params.temperature != 0.6: + self._settings.temperature = _params.temperature + elif _params.temperature != 0.6: logger.warning(f"temperature parameter is ignored for {model}") def can_generate_metrics(self) -> bool: @@ -697,6 +724,9 @@ class SarvamTTSService(InterruptibleTTSService): class InputParams(BaseModel): """Configuration parameters for Sarvam TTS WebSocket service. + .. deprecated:: 1.0 + Use ``SarvamTTSSettings`` directly via the ``settings`` parameter instead. + Parameters: pitch: Voice pitch adjustment (-0.75 to 0.75). Defaults to 0.0. **Note:** Only supported for bulbul:v2. Ignored for v3 models. @@ -782,13 +812,14 @@ class SarvamTTSService(InterruptibleTTSService): self, *, api_key: str, - model: str = "bulbul:v2", + model: Optional[str] = None, voice_id: Optional[str] = None, url: str = "wss://api.sarvam.ai/text-to-speech/ws", aggregate_sentences: Optional[bool] = None, text_aggregation_mode: Optional[TextAggregationMode] = None, sample_rate: Optional[int] = None, params: Optional[InputParams] = None, + settings: Optional[SarvamTTSSettings] = None, **kwargs, ): """Initialize the Sarvam TTS service with voice and transport configuration. @@ -798,7 +829,15 @@ class SarvamTTSService(InterruptibleTTSService): model: TTS model to use. Options: - "bulbul:v2" (default): Standard model with pitch/loudness support - "bulbul:v3-beta": Advanced model with temperature control + + .. deprecated:: 1.0 + Use ``settings=SarvamTTSSettings(model=...)`` instead. + voice_id: Speaker voice ID. If None, uses model-appropriate default. + + .. deprecated:: 1.0 + Use ``settings=SarvamTTSSettings(voice=...)`` instead. + url: WebSocket URL for the TTS backend (default production URL). aggregate_sentences: Deprecated. Use text_aggregation_mode instead. @@ -809,10 +848,25 @@ class SarvamTTSService(InterruptibleTTSService): sample_rate: Output audio sample rate in Hz (8000, 16000, 22050, 24000). If None, uses model-specific default. params: Optional input parameters to override defaults. + + .. deprecated:: 1.0 + Use ``settings=SarvamTTSSettings(...)`` instead. + + settings: Runtime-updatable settings. When provided alongside deprecated + parameters, ``settings`` values take precedence. **kwargs: Arguments forwarded to InterruptibleTTSService. See https://docs.sarvam.ai/api-reference-docs/text-to-speech/stream """ + if model is not None: + _warn_deprecated_param("model", "SarvamTTSSettings", "model") + if voice_id is not None: + _warn_deprecated_param("voice_id", "SarvamTTSSettings", "voice") + if params is not None: + _warn_deprecated_param("params", "SarvamTTSSettings") + + model = model or "bulbul:v2" + # Get model configuration (validates model exists) if model not in TTS_MODEL_CONFIGS: allowed = ", ".join(sorted(TTS_MODEL_CONFIGS.keys())) @@ -828,15 +882,37 @@ class SarvamTTSService(InterruptibleTTSService): if voice_id is None: voice_id = self._config.default_speaker - params = params or SarvamTTSService.InputParams() + _params = params or SarvamTTSService.InputParams() # Validate and clamp pace to model's valid range - pace = params.pace + pace = _params.pace pace_min, pace_max = self._config.pace_range if pace is not None and (pace < pace_min or pace > pace_max): logger.warning(f"Pace {pace} is outside model range ({pace_min}-{pace_max}). Clamping.") pace = max(pace_min, min(pace_max, pace)) + default_settings = SarvamTTSSettings( + language=( + self.language_to_service_language(_params.language) if _params.language else "en-IN" + ), + speech_sample_rate=str(sample_rate), + enable_preprocessing=( + True if self._config.preprocessing_always_enabled else _params.enable_preprocessing + ), + min_buffer_size=_params.min_buffer_size, + max_chunk_length=_params.max_chunk_length, + output_audio_codec=_params.output_audio_codec, + output_audio_bitrate=_params.output_audio_bitrate, + pace=pace, + pitch=None, + loudness=None, + temperature=None, + model=model, + voice=voice_id, + ) + if settings is not None: + default_settings.apply_update(settings) + # Initialize parent class first super().__init__( aggregate_sentences=aggregate_sentences, @@ -845,29 +921,7 @@ class SarvamTTSService(InterruptibleTTSService): pause_frame_processing=True, push_stop_frames=True, sample_rate=sample_rate, - settings=SarvamTTSSettings( - language=( - self.language_to_service_language(params.language) - if params.language - else "en-IN" - ), - speech_sample_rate=str(sample_rate), - enable_preprocessing=( - True - if self._config.preprocessing_always_enabled - else params.enable_preprocessing - ), - min_buffer_size=params.min_buffer_size, - max_chunk_length=params.max_chunk_length, - output_audio_codec=params.output_audio_codec, - output_audio_bitrate=params.output_audio_bitrate, - pace=pace, - pitch=None, - loudness=None, - temperature=None, - model=model, - voice=voice_id, - ), + settings=default_settings, **kwargs, ) @@ -877,18 +931,18 @@ class SarvamTTSService(InterruptibleTTSService): # Add parameters based on model support if self._config.supports_pitch: - self._settings.pitch = params.pitch - elif params.pitch != 0.0: + self._settings.pitch = _params.pitch + elif _params.pitch != 0.0: logger.warning(f"pitch parameter is ignored for {model}") if self._config.supports_loudness: - self._settings.loudness = params.loudness - elif params.loudness != 1.0: + self._settings.loudness = _params.loudness + elif _params.loudness != 1.0: logger.warning(f"loudness parameter is ignored for {model}") if self._config.supports_temperature: - self._settings.temperature = params.temperature - elif params.temperature != 0.6: + self._settings.temperature = _params.temperature + elif _params.temperature != 0.6: logger.warning(f"temperature parameter is ignored for {model}") self._receive_task = None diff --git a/src/pipecat/services/settings.py b/src/pipecat/services/settings.py index 5d215273f..546104b9a 100644 --- a/src/pipecat/services/settings.py +++ b/src/pipecat/services/settings.py @@ -37,6 +37,7 @@ Key helpers: from __future__ import annotations import copy +import warnings from dataclasses import dataclass, field, fields from typing import TYPE_CHECKING, Any, ClassVar, Dict, Mapping, Optional, Type, TypeVar @@ -47,6 +48,45 @@ from pipecat.transcriptions.language import Language if TYPE_CHECKING: from pipecat.turns.user_turn_completion_mixin import UserTurnCompletionConfig + +# --------------------------------------------------------------------------- +# Deprecation helper +# --------------------------------------------------------------------------- + + +def _warn_deprecated_param( + param_name: str, + settings_class_name: str, + settings_field: str | None = None, + stacklevel: int = 3, +): + """Emit DeprecationWarning for a deprecated init parameter. + + Args: + param_name: Name of the deprecated parameter. + settings_class_name: Name of the settings class to use instead. + settings_field: Specific field on the settings class, if different + from *param_name*. + stacklevel: Stack depth for the warning. Default ``3`` targets + the caller's caller (i.e. user code that instantiated the service). + """ + if settings_field: + msg = ( + f"The `{param_name}` parameter is deprecated. " + f"Use `settings={settings_class_name}({settings_field}=...)` instead. " + f"If both are provided, `settings` takes precedence." + ) + else: + msg = ( + f"The `{param_name}` parameter is deprecated. " + f"Use `settings={settings_class_name}(...)` instead. " + f"If both are provided, `settings` takes precedence." + ) + with warnings.catch_warnings(): + warnings.simplefilter("always") + warnings.warn(msg, DeprecationWarning, stacklevel=stacklevel) + + # --------------------------------------------------------------------------- # NOT_GIVEN sentinel # --------------------------------------------------------------------------- diff --git a/src/pipecat/services/soniox/stt.py b/src/pipecat/services/soniox/stt.py index 32cbee1f4..84c437f36 100644 --- a/src/pipecat/services/soniox/stt.py +++ b/src/pipecat/services/soniox/stt.py @@ -24,7 +24,7 @@ from pipecat.frames.frames import ( VADUserStoppedSpeakingFrame, ) from pipecat.processors.frame_processor import FrameDirection -from pipecat.services.settings import NOT_GIVEN, STTSettings, _NotGiven +from pipecat.services.settings import NOT_GIVEN, STTSettings, _NotGiven, _warn_deprecated_param from pipecat.services.stt_latency import SONIOX_TTFS_P99 from pipecat.services.stt_service import WebsocketSTTService from pipecat.transcriptions.language import Language @@ -79,6 +79,9 @@ class SonioxContextObject(BaseModel): class SonioxInputParams(BaseModel): """Real-time transcription settings. + .. deprecated:: 1.0 + Use ``settings=SonioxSTTSettings(...)`` instead. + See Soniox WebSocket API documentation for more details: https://soniox.com/docs/speech-to-text/api-reference/websocket-api#configuration-parameters @@ -183,8 +186,10 @@ class SonioxSTTService(WebsocketSTTService): api_key: str, url: str = "wss://stt-rt.soniox.com/transcribe-websocket", sample_rate: Optional[int] = None, + model: Optional[str] = None, params: Optional[SonioxInputParams] = None, vad_force_turn_endpoint: bool = True, + settings: Optional[SonioxSTTSettings] = None, ttfs_p99_latency: Optional[float] = SONIOX_TTFS_P99, **kwargs, ): @@ -194,33 +199,53 @@ class SonioxSTTService(WebsocketSTTService): api_key: Soniox API key. url: Soniox WebSocket API URL. sample_rate: Audio sample rate. + model: Soniox model to use for transcription. + + .. deprecated:: 1.0 + Use ``settings=SonioxSTTSettings(model=...)`` instead. + params: Additional configuration parameters, such as language hints, context and speaker diarization. + + .. deprecated:: 1.0 + Use ``settings=SonioxSTTSettings(...)`` instead. + vad_force_turn_endpoint: Listen to `VADUserStoppedSpeakingFrame` to send finalize message to Soniox. If disabled, Soniox will detect the end of the speech. Defaults to True. + settings: Runtime-updatable settings. When provided alongside deprecated + parameters, ``settings`` values take precedence. ttfs_p99_latency: P99 latency from speech end to final transcript in seconds. Override for your deployment. See https://github.com/pipecat-ai/stt-benchmark **kwargs: Additional arguments passed to the STTService. """ - params = params or SonioxInputParams() + if model is not None: + _warn_deprecated_param("model", "SonioxSTTSettings", "model") + if params is not None: + _warn_deprecated_param("params", "SonioxSTTSettings") + + _params = params or SonioxInputParams() + + default_settings = SonioxSTTSettings( + model=model or _params.model, + language=None, + audio_format=_params.audio_format, + num_channels=_params.num_channels, + language_hints=_params.language_hints, + language_hints_strict=_params.language_hints_strict, + context=_params.context, + enable_speaker_diarization=_params.enable_speaker_diarization, + enable_language_identification=_params.enable_language_identification, + client_reference_id=_params.client_reference_id, + ) + if settings is not None: + default_settings.apply_update(settings) super().__init__( sample_rate=sample_rate, ttfs_p99_latency=ttfs_p99_latency, keepalive_timeout=1, keepalive_interval=5, - settings=SonioxSTTSettings( - model=params.model, - language=None, - audio_format=params.audio_format, - num_channels=params.num_channels, - language_hints=params.language_hints, - language_hints_strict=params.language_hints_strict, - context=params.context, - enable_speaker_diarization=params.enable_speaker_diarization, - enable_language_identification=params.enable_language_identification, - client_reference_id=params.client_reference_id, - ), + settings=default_settings, **kwargs, ) diff --git a/src/pipecat/services/speechmatics/stt.py b/src/pipecat/services/speechmatics/stt.py index bdeb3b249..a0ca19f74 100644 --- a/src/pipecat/services/speechmatics/stt.py +++ b/src/pipecat/services/speechmatics/stt.py @@ -33,7 +33,7 @@ from pipecat.frames.frames import ( VADUserStoppedSpeakingFrame, ) from pipecat.processors.frame_processor import FrameDirection -from pipecat.services.settings import NOT_GIVEN, STTSettings, _NotGiven +from pipecat.services.settings import NOT_GIVEN, STTSettings, _NotGiven, _warn_deprecated_param from pipecat.services.stt_latency import SPEECHMATICS_TTFS_P99 from pipecat.services.stt_service import STTService from pipecat.transcriptions.language import Language, resolve_language @@ -381,6 +381,7 @@ class SpeechmaticsSTTService(STTService): sample_rate: int | None = None, params: InputParams | None = None, should_interrupt: bool = True, + settings: SpeechmaticsSTTSettings | None = None, ttfs_p99_latency: float | None = SPEECHMATICS_TTFS_P99, **kwargs, ): @@ -392,8 +393,14 @@ class SpeechmaticsSTTService(STTService): base_url: Base URL for Speechmatics API. Uses environment variable `SPEECHMATICS_RT_URL` or defaults to `wss://eu2.rt.speechmatics.com/v2`. sample_rate: Optional audio sample rate in Hz. - params: Optional[InputParams]: Input parameters for the service. + params: Input parameters for the service. + + .. deprecated:: 1.0 + Use ``settings=SpeechmaticsSTTSettings(...)`` instead. + should_interrupt: Determine whether the bot should be interrupted when Speechmatics turn_detection_mode is configured to detect user speech. + settings: Runtime-updatable settings. When provided alongside deprecated + ``params``, ``settings`` values take precedence. ttfs_p99_latency: P99 latency from speech end to final transcript in seconds. Override for your deployment. See https://github.com/pipecat-ai/stt-benchmark **kwargs: Additional arguments passed to STTService. @@ -410,6 +417,9 @@ class SpeechmaticsSTTService(STTService): if not self._base_url: raise ValueError("Missing Speechmatics base URL") + if params is not None: + _warn_deprecated_param("params", "SpeechmaticsSTTSettings") + # Default params params = params or SpeechmaticsSTTService.InputParams() self._should_interrupt = should_interrupt @@ -426,7 +436,7 @@ class SpeechmaticsSTTService(STTService): speaker_passive_format = params.speaker_passive_format or speaker_active_format # Settings — seeded from InputParams - settings = SpeechmaticsSTTSettings( + default_settings = SpeechmaticsSTTSettings( model=None, # Will be resolved from operating_point after config is built language=params.language, domain=params.domain, @@ -455,13 +465,16 @@ class SpeechmaticsSTTService(STTService): # Build SDK config from settings, then resolve model from operating_point self._client: VoiceAgentClient | None = None - self._config: VoiceAgentConfig = self._build_config(settings) - settings.model = self._config.operating_point.value + self._config: VoiceAgentConfig = self._build_config(default_settings) + default_settings.model = self._config.operating_point.value + + if settings is not None: + default_settings.apply_update(settings) super().__init__( sample_rate=sample_rate, ttfs_p99_latency=ttfs_p99_latency, - settings=settings, + settings=default_settings, **kwargs, ) diff --git a/src/pipecat/services/speechmatics/tts.py b/src/pipecat/services/speechmatics/tts.py index 1ddb895aa..e1260fbe2 100644 --- a/src/pipecat/services/speechmatics/tts.py +++ b/src/pipecat/services/speechmatics/tts.py @@ -22,7 +22,7 @@ from pipecat.frames.frames import ( TTSStartedFrame, TTSStoppedFrame, ) -from pipecat.services.settings import NOT_GIVEN, TTSSettings, _NotGiven +from pipecat.services.settings import NOT_GIVEN, TTSSettings, _NotGiven, _warn_deprecated_param from pipecat.services.tts_service import TTSService from pipecat.utils.network import exponential_backoff_time from pipecat.utils.tracing.service_decorators import traced_tts @@ -62,6 +62,9 @@ class SpeechmaticsTTSService(TTSService): class InputParams(BaseModel): """Optional input parameters for Speechmatics TTS configuration. + .. deprecated:: 1.0 + Use ``settings=SpeechmaticsTTSSettings(...)`` instead. + Parameters: max_retries: Maximum number of retries for TTS requests. Defaults to 5. """ @@ -73,10 +76,11 @@ class SpeechmaticsTTSService(TTSService): *, api_key: str, base_url: str = "https://preview.tts.speechmatics.com", - voice_id: str = "sarah", + voice_id: Optional[str] = None, aiohttp_session: aiohttp.ClientSession, sample_rate: Optional[int] = SPEECHMATICS_SAMPLE_RATE, params: Optional[InputParams] = None, + settings: Optional[SpeechmaticsTTSSettings] = None, **kwargs, ): """Initialize the Speechmatics TTS service. @@ -85,26 +89,45 @@ class SpeechmaticsTTSService(TTSService): api_key: Speechmatics API key for authentication. base_url: Base URL for Speechmatics TTS API. voice_id: Voice model to use for synthesis. + + .. deprecated:: 1.0 + Use ``settings=SpeechmaticsTTSSettings(voice=...)`` instead. + aiohttp_session: Shared aiohttp session for HTTP requests. sample_rate: Audio sample rate in Hz. - params: Optional[InputParams]: Input parameters for the service. + params: Input parameters for the service. + + .. deprecated:: 1.0 + Use ``settings=SpeechmaticsTTSSettings(...)`` instead. + + settings: Runtime-updatable settings. When provided alongside deprecated + parameters, ``settings`` values take precedence. **kwargs: Additional arguments passed to TTSService. """ + if voice_id is not None: + _warn_deprecated_param("voice_id", "SpeechmaticsTTSSettings", "voice") + if params is not None: + _warn_deprecated_param("params", "SpeechmaticsTTSSettings") + if sample_rate and sample_rate != self.SPEECHMATICS_SAMPLE_RATE: logger.warning( f"Speechmatics TTS only supports {self.SPEECHMATICS_SAMPLE_RATE}Hz sample rate. " f"Current rate of {sample_rate}Hz may cause issues." ) - params = params or SpeechmaticsTTSService.InputParams() + _params = params or SpeechmaticsTTSService.InputParams() + + default_settings = SpeechmaticsTTSSettings( + model=None, + voice=voice_id or "sarah", + language=None, + max_retries=_params.max_retries, + ) + if settings is not None: + default_settings.apply_update(settings) super().__init__( sample_rate=sample_rate, - settings=SpeechmaticsTTSSettings( - model=None, - voice=voice_id, - language=None, - max_retries=params.max_retries, - ), + settings=default_settings, **kwargs, ) diff --git a/src/pipecat/services/tavus/video.py b/src/pipecat/services/tavus/video.py index 8c63ff354..e6725fac1 100644 --- a/src/pipecat/services/tavus/video.py +++ b/src/pipecat/services/tavus/video.py @@ -34,6 +34,7 @@ from pipecat.frames.frames import ( ) from pipecat.processors.frame_processor import FrameDirection, FrameProcessorSetup from pipecat.services.ai_service import AIService +from pipecat.services.settings import ServiceSettings from pipecat.transports.tavus.transport import TavusCallbacks, TavusParams, TavusTransportClient @@ -57,6 +58,7 @@ class TavusVideoService(AIService): replica_id: str, persona_id: str = "pipecat-stream", session: aiohttp.ClientSession, + settings: Optional[ServiceSettings] = None, **kwargs, ) -> None: """Initialize the Tavus video service. @@ -66,9 +68,15 @@ class TavusVideoService(AIService): replica_id: ID of the Tavus voice replica to use for speech synthesis. persona_id: ID of the Tavus persona. Defaults to "pipecat-stream" for Pipecat TTS voice. session: Async HTTP session used for communication with Tavus. + settings: Runtime-updatable settings. Tavus has no model concept, so this + is primarily used for the ``extra`` dict. **kwargs: Additional arguments passed to the parent AIService class. """ - super().__init__(**kwargs) + default_settings = ServiceSettings(model=None) + if settings is not None: + default_settings.apply_update(settings) + + super().__init__(settings=default_settings, **kwargs) self._api_key = api_key self._session = session self._replica_id = replica_id diff --git a/src/pipecat/services/together/llm.py b/src/pipecat/services/together/llm.py index 277e8bc9c..b1cb4ffea 100644 --- a/src/pipecat/services/together/llm.py +++ b/src/pipecat/services/together/llm.py @@ -6,9 +6,13 @@ """Together.ai LLM service implementation using OpenAI-compatible interface.""" +from typing import Optional + from loguru import logger +from pipecat.services.openai.base_llm import OpenAILLMSettings from pipecat.services.openai.llm import OpenAILLMService +from pipecat.services.settings import _warn_deprecated_param class TogetherLLMService(OpenAILLMService): @@ -23,7 +27,8 @@ class TogetherLLMService(OpenAILLMService): *, api_key: str, base_url: str = "https://api.together.xyz/v1", - model: str = "meta-llama/Meta-Llama-3.1-8B-Instruct-Turbo", + model: Optional[str] = None, + settings: Optional[OpenAILLMSettings] = None, **kwargs, ): """Initialize Together.ai LLM service. @@ -32,9 +37,24 @@ class TogetherLLMService(OpenAILLMService): api_key: The API key for accessing Together.ai's API. base_url: The base URL for Together.ai API. Defaults to "https://api.together.xyz/v1". model: The model identifier to use. Defaults to "meta-llama/Meta-Llama-3.1-8B-Instruct-Turbo". + + .. deprecated:: 1.0 + Use ``settings=OpenAILLMSettings(model=...)`` instead. + + settings: Runtime-updatable settings. When provided alongside deprecated + parameters, ``settings`` values take precedence. **kwargs: Additional keyword arguments passed to OpenAILLMService. """ - super().__init__(api_key=api_key, base_url=base_url, model=model, **kwargs) + if model is not None: + _warn_deprecated_param("model", "OpenAILLMSettings", "model") + + default_settings = OpenAILLMSettings( + model=model or "meta-llama/Meta-Llama-3.1-8B-Instruct-Turbo" + ) + if settings is not None: + default_settings.apply_update(settings) + + super().__init__(api_key=api_key, base_url=base_url, settings=default_settings, **kwargs) def create_client(self, api_key=None, base_url=None, **kwargs): """Create OpenAI-compatible client for Together.ai API endpoint. diff --git a/src/pipecat/services/ultravox/llm.py b/src/pipecat/services/ultravox/llm.py index 07c3c34fe..933930152 100644 --- a/src/pipecat/services/ultravox/llm.py +++ b/src/pipecat/services/ultravox/llm.py @@ -172,32 +172,38 @@ class UltravoxRealtimeLLMService(LLMService): self, *, params: Union[AgentInputParams, OneShotInputParams, JoinUrlInputParams], + settings: Optional[UltravoxRealtimeLLMSettings] = None, one_shot_selected_tools: Optional[ToolsSchema] = None, **kwargs, ): """Initialize the Ultravox Realtime LLM service. Args: - api_key: Ultravox API key for authentication. params: Configuration parameters for the model. + settings: Ultravox Realtime LLM settings. If provided, the ``settings`` + values take precedence over default values. one_shot_selected_tools: ToolsSchema for tools to use with this call. May only be set with OneShotInputParams. **kwargs: Additional arguments passed to parent LLMService. """ + default_settings = UltravoxRealtimeLLMSettings( + model=None, + temperature=None, + max_tokens=None, + top_p=None, + top_k=None, + frequency_penalty=None, + presence_penalty=None, + seed=None, + filter_incomplete_user_turns=False, + user_turn_completion_config=None, + output_medium=None, + ) + if settings is not None: + default_settings.apply_update(settings) + super().__init__( - settings=UltravoxRealtimeLLMSettings( - model=None, - temperature=None, - max_tokens=None, - top_p=None, - top_k=None, - frequency_penalty=None, - presence_penalty=None, - seed=None, - filter_incomplete_user_turns=False, - user_turn_completion_config=None, - output_medium=None, - ), + settings=default_settings, **kwargs, ) self._params = params diff --git a/src/pipecat/services/whisper/base_stt.py b/src/pipecat/services/whisper/base_stt.py index 08310831c..32dd382e8 100644 --- a/src/pipecat/services/whisper/base_stt.py +++ b/src/pipecat/services/whisper/base_stt.py @@ -18,7 +18,7 @@ from openai import AsyncOpenAI from openai.types.audio import Transcription from pipecat.frames.frames import ErrorFrame, Frame, TranscriptionFrame -from pipecat.services.settings import NOT_GIVEN, STTSettings, _NotGiven +from pipecat.services.settings import NOT_GIVEN, STTSettings, _NotGiven, _warn_deprecated_param from pipecat.services.stt_latency import WHISPER_TTFS_P99 from pipecat.services.stt_service import SegmentedSTTService from pipecat.transcriptions.language import Language, resolve_language @@ -129,14 +129,15 @@ class BaseWhisperSTTService(SegmentedSTTService): def __init__( self, *, - model: str, + model: Optional[str] = None, api_key: Optional[str] = None, base_url: Optional[str] = None, - language: Optional[Language] = Language.EN, + language: Optional[Language] = None, prompt: Optional[str] = None, temperature: Optional[float] = None, include_prob_metrics: bool = False, push_empty_transcripts: bool = False, + settings: Optional[BaseWhisperSTTSettings] = None, ttfs_p99_latency: Optional[float] = WHISPER_TTFS_P99, **kwargs, ): @@ -144,11 +145,27 @@ class BaseWhisperSTTService(SegmentedSTTService): Args: model: Name of the Whisper model to use. + + .. deprecated:: 1.0 + Use ``settings=BaseWhisperSTTSettings(model=...)`` instead. + api_key: Service API key. Defaults to None. base_url: Service API base URL. Defaults to None. - language: Language of the audio input. Defaults to English. + language: Language of the audio input. + + .. deprecated:: 1.0 + Use ``settings=BaseWhisperSTTSettings(language=...)`` instead. + prompt: Optional text to guide the model's style or continue a previous segment. - temperature: Sampling temperature between 0 and 1. Defaults to 0.0. + + .. deprecated:: 1.0 + Use ``settings=BaseWhisperSTTSettings(prompt=...)`` instead. + + temperature: Sampling temperature between 0 and 1. + + .. deprecated:: 1.0 + Use ``settings=BaseWhisperSTTSettings(temperature=...)`` instead. + include_prob_metrics: If True, enables probability metrics in API response. Each service implements this differently (see child classes). Defaults to False. @@ -158,25 +175,44 @@ class BaseWhisperSTTService(SegmentedSTTService): useful to know that nothing was transcribed so that the agent can resume speaking, instead of waiting longer for a transcription. Defaults to False. + settings: Runtime-updatable settings. When provided alongside deprecated + parameters, ``settings`` values take precedence. ttfs_p99_latency: P99 latency from speech end to final transcript in seconds. Override for your deployment. See https://github.com/pipecat-ai/stt-benchmark **kwargs: Additional arguments passed to SegmentedSTTService. """ + if model is not None: + _warn_deprecated_param("model", "BaseWhisperSTTSettings", "model") + if language is not None: + _warn_deprecated_param("language", "BaseWhisperSTTSettings", "language") + if prompt is not None: + _warn_deprecated_param("prompt", "BaseWhisperSTTSettings", "prompt") + if temperature is not None: + _warn_deprecated_param("temperature", "BaseWhisperSTTSettings", "temperature") + + _language = language or Language.EN + + default_settings = BaseWhisperSTTSettings( + model=model, + language=self.language_to_service_language(_language), + base_url=base_url, + prompt=prompt, + temperature=temperature, + ) + if settings is not None: + default_settings.apply_update(settings) + super().__init__( ttfs_p99_latency=ttfs_p99_latency, - settings=BaseWhisperSTTSettings( - model=model, - language=self.language_to_service_language(language or Language.EN), - base_url=base_url, - prompt=prompt, - temperature=temperature, - ), + settings=default_settings, **kwargs, ) self._client = self._create_client(api_key, base_url) self._language = self._settings.language - self._prompt = prompt - self._temperature = temperature + self._prompt = self._settings.prompt if self._settings.prompt else prompt + self._temperature = ( + self._settings.temperature if self._settings.temperature else temperature + ) self._include_prob_metrics = include_prob_metrics self._push_empty_transcripts = push_empty_transcripts diff --git a/src/pipecat/services/whisper/stt.py b/src/pipecat/services/whisper/stt.py index d386d6ed2..2e0a6156a 100644 --- a/src/pipecat/services/whisper/stt.py +++ b/src/pipecat/services/whisper/stt.py @@ -20,7 +20,7 @@ from loguru import logger from typing_extensions import TYPE_CHECKING, override from pipecat.frames.frames import ErrorFrame, Frame, TranscriptionFrame -from pipecat.services.settings import NOT_GIVEN, STTSettings, _NotGiven +from pipecat.services.settings import NOT_GIVEN, STTSettings, _NotGiven, _warn_deprecated_param from pipecat.services.stt_service import SegmentedSTTService from pipecat.transcriptions.language import Language, resolve_language from pipecat.utils.time import time_now_iso8601 @@ -216,36 +216,80 @@ class WhisperSTTService(SegmentedSTTService): def __init__( self, *, - model: str | Model = Model.DISTIL_MEDIUM_EN, - device: str = "auto", - compute_type: str = "default", - no_speech_prob: float = 0.4, - language: Language = Language.EN, + model: Optional[str | Model] = None, + device: Optional[str] = None, + compute_type: Optional[str] = None, + no_speech_prob: Optional[float] = None, + language: Optional[Language] = None, + settings: Optional[WhisperSTTSettings] = None, **kwargs, ): """Initialize the Whisper STT service. Args: model: The Whisper model to use for transcription. Can be a Model enum or string. + + .. deprecated:: 1.0 + Use ``settings=WhisperSTTSettings(model=...)`` instead. + device: The device to run inference on ('cpu', 'cuda', or 'auto'). + + .. deprecated:: 1.0 + Use ``settings=WhisperSTTSettings(device=...)`` instead. + compute_type: The compute type for inference ('default', 'int8', 'int8_float16', etc.). + + .. deprecated:: 1.0 + Use ``settings=WhisperSTTSettings(compute_type=...)`` instead. + no_speech_prob: Probability threshold for filtering out non-speech segments. + + .. deprecated:: 1.0 + Use ``settings=WhisperSTTSettings(no_speech_prob=...)`` instead. + language: The default language for transcription. + + .. deprecated:: 1.0 + Use ``settings=WhisperSTTSettings(language=...)`` instead. + + settings: Runtime-updatable settings. When provided alongside deprecated + parameters, ``settings`` values take precedence. **kwargs: Additional arguments passed to SegmentedSTTService. """ + if model is not None: + _warn_deprecated_param("model", "WhisperSTTSettings", "model") + if device is not None: + _warn_deprecated_param("device", "WhisperSTTSettings", "device") + if compute_type is not None: + _warn_deprecated_param("compute_type", "WhisperSTTSettings", "compute_type") + if no_speech_prob is not None: + _warn_deprecated_param("no_speech_prob", "WhisperSTTSettings", "no_speech_prob") + if language is not None: + _warn_deprecated_param("language", "WhisperSTTSettings", "language") + + _model = model if model is not None else Model.DISTIL_MEDIUM_EN + _device = device or "auto" + _compute_type = compute_type or "default" + _no_speech_prob = no_speech_prob if no_speech_prob is not None else 0.4 + _language = language or Language.EN + + default_settings = WhisperSTTSettings( + model=_model if isinstance(_model, str) else _model.value, + language=_language, + device=_device, + compute_type=_compute_type, + no_speech_prob=_no_speech_prob, + ) + if settings is not None: + default_settings.apply_update(settings) + super().__init__( - settings=WhisperSTTSettings( - model=model if isinstance(model, str) else model.value, - language=language, - device=device, - compute_type=compute_type, - no_speech_prob=no_speech_prob, - ), + settings=default_settings, **kwargs, ) - self._device: str = device - self._compute_type = compute_type - self._no_speech_prob = no_speech_prob + self._device: str = self._settings.device + self._compute_type = self._settings.compute_type + self._no_speech_prob = self._settings.no_speech_prob self._model: Optional[WhisperModel] = None self._load() @@ -352,36 +396,73 @@ class WhisperSTTServiceMLX(WhisperSTTService): def __init__( self, *, - model: str | MLXModel = MLXModel.TINY, - no_speech_prob: float = 0.6, - language: Language = Language.EN, - temperature: float = 0.0, + model: Optional[str | MLXModel] = None, + no_speech_prob: Optional[float] = None, + language: Optional[Language] = None, + temperature: Optional[float] = None, + settings: Optional[WhisperMLXSTTSettings] = None, **kwargs, ): """Initialize the MLX Whisper STT service. Args: model: The MLX Whisper model to use for transcription. Can be an MLXModel enum or string. + + .. deprecated:: 1.0 + Use ``settings=WhisperMLXSTTSettings(model=...)`` instead. + no_speech_prob: Probability threshold for filtering out non-speech segments. + + .. deprecated:: 1.0 + Use ``settings=WhisperMLXSTTSettings(no_speech_prob=...)`` instead. + language: The default language for transcription. + + .. deprecated:: 1.0 + Use ``settings=WhisperMLXSTTSettings(language=...)`` instead. + temperature: Temperature for sampling. Can be a float or tuple of floats. + + .. deprecated:: 1.0 + Use ``settings=WhisperMLXSTTSettings(temperature=...)`` instead. + + settings: Runtime-updatable settings. When provided alongside deprecated + parameters, ``settings`` values take precedence. **kwargs: Additional arguments passed to SegmentedSTTService. """ + if model is not None: + _warn_deprecated_param("model", "WhisperMLXSTTSettings", "model") + if no_speech_prob is not None: + _warn_deprecated_param("no_speech_prob", "WhisperMLXSTTSettings", "no_speech_prob") + if language is not None: + _warn_deprecated_param("language", "WhisperMLXSTTSettings", "language") + if temperature is not None: + _warn_deprecated_param("temperature", "WhisperMLXSTTSettings", "temperature") + + _model = model if model is not None else MLXModel.TINY + _no_speech_prob = no_speech_prob if no_speech_prob is not None else 0.6 + _language = language or Language.EN + _temperature = temperature if temperature is not None else 0.0 + + default_settings = WhisperMLXSTTSettings( + model=_model if isinstance(_model, str) else _model.value, + language=_language, + no_speech_prob=_no_speech_prob, + temperature=_temperature, + engine="mlx", + ) + if settings is not None: + default_settings.apply_update(settings) + # Skip WhisperSTTService.__init__ and call its parent directly SegmentedSTTService.__init__( self, - settings=WhisperMLXSTTSettings( - model=model if isinstance(model, str) else model.value, - language=language, - no_speech_prob=no_speech_prob, - temperature=temperature, - engine="mlx", - ), + settings=default_settings, **kwargs, ) - self._no_speech_prob = no_speech_prob - self._temperature = temperature + self._no_speech_prob = self._settings.no_speech_prob + self._temperature = self._settings.temperature # No need to call _load() as MLX Whisper loads models on demand diff --git a/src/pipecat/services/xtts/tts.py b/src/pipecat/services/xtts/tts.py index 8817c09b5..bba95a400 100644 --- a/src/pipecat/services/xtts/tts.py +++ b/src/pipecat/services/xtts/tts.py @@ -25,7 +25,7 @@ from pipecat.frames.frames import ( TTSStartedFrame, TTSStoppedFrame, ) -from pipecat.services.settings import NOT_GIVEN, TTSSettings, _NotGiven +from pipecat.services.settings import NOT_GIVEN, TTSSettings, _NotGiven, _warn_deprecated_param from pipecat.services.tts_service import TTSService from pipecat.transcriptions.language import Language, resolve_language from pipecat.utils.tracing.service_decorators import traced_tts @@ -94,31 +94,45 @@ class XTTSService(TTSService): def __init__( self, *, - voice_id: str, + voice_id: Optional[str] = None, base_url: str, aiohttp_session: aiohttp.ClientSession, language: Language = Language.EN, sample_rate: Optional[int] = None, + settings: Optional[XTTSTTSSettings] = None, **kwargs, ): """Initialize the XTTS service. Args: voice_id: ID of the voice/speaker to use for synthesis. + + .. deprecated:: 1.0 + Use ``settings=XTTSTTSSettings(voice=...)`` instead. + base_url: Base URL of the XTTS streaming server. aiohttp_session: HTTP session for making requests to the server. language: Language for synthesis. Defaults to English. sample_rate: Audio sample rate. If None, uses default. + settings: Runtime-updatable settings. When provided alongside deprecated + parameters, ``settings`` values take precedence. **kwargs: Additional arguments passed to parent TTSService. """ + if voice_id is not None: + _warn_deprecated_param("voice_id", "XTTSTTSSettings", "voice") + + default_settings = XTTSTTSSettings( + model=None, + voice=voice_id, + language=self.language_to_service_language(language), + base_url=base_url, + ) + if settings is not None: + default_settings.apply_update(settings) + super().__init__( sample_rate=sample_rate, - settings=XTTSTTSSettings( - model=None, - voice=voice_id, - language=self.language_to_service_language(language), - base_url=base_url, - ), + settings=default_settings, **kwargs, ) self._studio_speakers: Optional[Dict[str, Any]] = None From bc2843e30ae2031766d3af665e34df915e65e90e Mon Sep 17 00:00:00 2001 From: Mark Backman Date: Tue, 3 Mar 2026 14:33:16 -0500 Subject: [PATCH 0805/1060] Fix deprecation version --- src/pipecat/services/asyncai/tts.py | 16 ++++++------- src/pipecat/services/aws/stt.py | 4 ++-- src/pipecat/services/aws/tts.py | 6 ++--- src/pipecat/services/azure/image.py | 2 +- src/pipecat/services/azure/llm.py | 2 +- src/pipecat/services/azure/stt.py | 2 +- src/pipecat/services/azure/tts.py | 10 ++++---- src/pipecat/services/camb/tts.py | 8 +++---- src/pipecat/services/cartesia/tts.py | 12 +++++----- src/pipecat/services/cerebras/llm.py | 2 +- src/pipecat/services/deepgram/flux/stt.py | 6 ++--- .../services/deepgram/sagemaker/tts.py | 2 +- src/pipecat/services/deepgram/tts.py | 4 ++-- src/pipecat/services/deepseek/llm.py | 2 +- src/pipecat/services/elevenlabs/stt.py | 12 +++++----- src/pipecat/services/elevenlabs/tts.py | 16 ++++++------- src/pipecat/services/fal/image.py | 2 +- src/pipecat/services/fal/stt.py | 4 ++-- src/pipecat/services/fireworks/llm.py | 2 +- src/pipecat/services/fish/tts.py | 8 +++---- src/pipecat/services/gladia/stt.py | 4 ++-- src/pipecat/services/google/image.py | 2 +- src/pipecat/services/google/llm_openai.py | 2 +- src/pipecat/services/google/stt.py | 4 ++-- src/pipecat/services/google/tts.py | 20 ++++++++-------- src/pipecat/services/gradium/stt.py | 4 ++-- src/pipecat/services/gradium/tts.py | 8 +++---- src/pipecat/services/grok/llm.py | 2 +- src/pipecat/services/groq/llm.py | 2 +- src/pipecat/services/groq/stt.py | 8 +++---- src/pipecat/services/groq/tts.py | 8 +++---- src/pipecat/services/hume/tts.py | 6 ++--- src/pipecat/services/inworld/tts.py | 16 ++++++------- src/pipecat/services/kokoro/tts.py | 6 ++--- src/pipecat/services/lmnt/tts.py | 4 ++-- src/pipecat/services/minimax/tts.py | 8 +++---- src/pipecat/services/mistral/llm.py | 2 +- src/pipecat/services/moondream/vision.py | 2 +- src/pipecat/services/neuphonic/tts.py | 12 +++++----- src/pipecat/services/nvidia/llm.py | 2 +- src/pipecat/services/nvidia/stt.py | 8 +++---- src/pipecat/services/nvidia/tts.py | 6 ++--- src/pipecat/services/ollama/llm.py | 2 +- src/pipecat/services/openai/base_llm.py | 6 ++--- src/pipecat/services/openai/image.py | 2 +- src/pipecat/services/openai/llm.py | 4 ++-- src/pipecat/services/openai/stt.py | 4 ++-- src/pipecat/services/openai/tts.py | 12 +++++----- src/pipecat/services/openpipe/llm.py | 2 +- src/pipecat/services/openrouter/llm.py | 2 +- src/pipecat/services/perplexity/llm.py | 2 +- src/pipecat/services/piper/tts.py | 4 ++-- src/pipecat/services/qwen/llm.py | 2 +- src/pipecat/services/resembleai/tts.py | 2 +- src/pipecat/services/rime/tts.py | 24 +++++++++---------- src/pipecat/services/sambanova/llm.py | 2 +- src/pipecat/services/sambanova/stt.py | 8 +++---- src/pipecat/services/sarvam/stt.py | 6 ++--- src/pipecat/services/sarvam/tts.py | 16 ++++++------- src/pipecat/services/soniox/stt.py | 6 ++--- src/pipecat/services/speechmatics/stt.py | 2 +- src/pipecat/services/speechmatics/tts.py | 6 ++--- src/pipecat/services/together/llm.py | 2 +- src/pipecat/services/whisper/base_stt.py | 8 +++---- src/pipecat/services/whisper/stt.py | 18 +++++++------- src/pipecat/services/xtts/tts.py | 2 +- 66 files changed, 201 insertions(+), 201 deletions(-) diff --git a/src/pipecat/services/asyncai/tts.py b/src/pipecat/services/asyncai/tts.py index 245253ac8..b7ddec2e1 100644 --- a/src/pipecat/services/asyncai/tts.py +++ b/src/pipecat/services/asyncai/tts.py @@ -110,7 +110,7 @@ class AsyncAITTSService(AudioContextTTSService): class InputParams(BaseModel): """Input parameters for Async TTS configuration. - .. deprecated:: 1.0 + .. deprecated:: 1.0.0 Use ``AsyncAITTSSettings`` directly via the ``settings`` parameter instead. Parameters: @@ -143,14 +143,14 @@ class AsyncAITTSService(AudioContextTTSService): voice_id: UUID of the voice to use for synthesis. See docs for a full list: https://docs.async.com/list-voices-16699698e0 - .. deprecated:: 1.0 + .. deprecated:: 1.0.0 Use ``settings=AsyncAITTSSettings(voice=...)`` instead. version: Async API version. url: WebSocket URL for Async TTS API. model: TTS model to use (e.g., "async_flash_v1.0"). - .. deprecated:: 1.0 + .. deprecated:: 1.0.0 Use ``settings=AsyncAITTSSettings(model=...)`` instead. sample_rate: Audio sample rate. @@ -158,7 +158,7 @@ class AsyncAITTSService(AudioContextTTSService): container: Audio container format. params: Additional input parameters for voice customization. - .. deprecated:: 1.0 + .. deprecated:: 1.0.0 Use ``settings=AsyncAITTSSettings(...)`` instead. settings: Runtime-updatable settings. When provided alongside deprecated @@ -500,7 +500,7 @@ class AsyncAIHttpTTSService(TTSService): class InputParams(BaseModel): """Input parameters for Async API. - .. deprecated:: 1.0 + .. deprecated:: 1.0.0 Use ``AsyncAITTSSettings`` directly via the ``settings`` parameter instead. Parameters: @@ -531,13 +531,13 @@ class AsyncAIHttpTTSService(TTSService): api_key: Async API key. voice_id: ID of the voice to use for synthesis. - .. deprecated:: 1.0 + .. deprecated:: 1.0.0 Use ``settings=AsyncAITTSSettings(voice=...)`` instead. aiohttp_session: An aiohttp session for making HTTP requests. model: TTS model to use (e.g., "async_flash_v1.0"). - .. deprecated:: 1.0 + .. deprecated:: 1.0.0 Use ``settings=AsyncAITTSSettings(model=...)`` instead. url: Base URL for Async API. @@ -547,7 +547,7 @@ class AsyncAIHttpTTSService(TTSService): container: Audio container format. params: Additional input parameters for voice customization. - .. deprecated:: 1.0 + .. deprecated:: 1.0.0 Use ``settings=AsyncAITTSSettings(...)`` instead. settings: Runtime-updatable settings. When provided alongside deprecated diff --git a/src/pipecat/services/aws/stt.py b/src/pipecat/services/aws/stt.py index 1cbfa7329..061b17889 100644 --- a/src/pipecat/services/aws/stt.py +++ b/src/pipecat/services/aws/stt.py @@ -96,12 +96,12 @@ class AWSTranscribeSTTService(WebsocketSTTService): region: AWS region for the service. sample_rate: Audio sample rate in Hz. Must be 8000 or 16000. - .. deprecated:: 1.0 + .. deprecated:: 1.0.0 Use ``settings=AWSTranscribeSTTSettings(sample_rate=...)`` instead. language: Language for transcription. - .. deprecated:: 1.0 + .. deprecated:: 1.0.0 Use ``settings=AWSTranscribeSTTSettings(language=...)`` instead. settings: Runtime-updatable settings. When provided alongside deprecated diff --git a/src/pipecat/services/aws/tts.py b/src/pipecat/services/aws/tts.py index 8e11cb3cd..83ef4125c 100644 --- a/src/pipecat/services/aws/tts.py +++ b/src/pipecat/services/aws/tts.py @@ -155,7 +155,7 @@ class AWSPollyTTSService(TTSService): class InputParams(BaseModel): """Input parameters for AWS Polly TTS configuration. - .. deprecated:: 1.0 + .. deprecated:: 1.0.0 Use ``AWSPollyTTSSettings`` directly via the ``settings`` parameter instead. Parameters: @@ -196,13 +196,13 @@ class AWSPollyTTSService(TTSService): region: AWS region for Polly service. Defaults to 'us-east-1'. voice_id: Voice ID to use for synthesis. Defaults to 'Joanna'. - .. deprecated:: 1.0 + .. deprecated:: 1.0.0 Use ``settings=AWSPollyTTSSettings(voice=...)`` instead. sample_rate: Audio sample rate. If None, uses service default. params: Additional input parameters for voice customization. - .. deprecated:: 1.0 + .. deprecated:: 1.0.0 Use ``settings=AWSPollyTTSSettings(...)`` instead. settings: Runtime-updatable settings. When provided alongside deprecated diff --git a/src/pipecat/services/azure/image.py b/src/pipecat/services/azure/image.py index e64e5c7d8..9f5d48c33 100644 --- a/src/pipecat/services/azure/image.py +++ b/src/pipecat/services/azure/image.py @@ -59,7 +59,7 @@ class AzureImageGenServiceREST(ImageGenService): endpoint: Azure OpenAI endpoint URL. model: The image generation model to use. - .. deprecated:: 1.0 + .. deprecated:: 1.0.0 Use ``settings=AzureImageGenSettings(model=...)`` instead. aiohttp_session: Shared aiohttp session for HTTP requests. diff --git a/src/pipecat/services/azure/llm.py b/src/pipecat/services/azure/llm.py index b828f0e4e..3c28e190e 100644 --- a/src/pipecat/services/azure/llm.py +++ b/src/pipecat/services/azure/llm.py @@ -40,7 +40,7 @@ class AzureLLMService(OpenAILLMService): endpoint: The Azure endpoint URL. model: The model identifier to use. Defaults to "gpt-4o". - .. deprecated:: 1.0 + .. deprecated:: 1.0.0 Use ``settings=OpenAILLMSettings(model=...)`` instead. api_version: Azure API version. Defaults to "2024-09-01-preview". diff --git a/src/pipecat/services/azure/stt.py b/src/pipecat/services/azure/stt.py index 5ab88c8dd..02a7ca8ed 100644 --- a/src/pipecat/services/azure/stt.py +++ b/src/pipecat/services/azure/stt.py @@ -94,7 +94,7 @@ class AzureSTTService(STTService): region: Azure region for the Speech service (e.g., 'eastus'). language: Language for speech recognition. Defaults to English (US). - .. deprecated:: 1.0 + .. deprecated:: 1.0.0 Use ``settings=AzureSTTSettings(language=...)`` instead. sample_rate: Audio sample rate in Hz. If None, uses service default. diff --git a/src/pipecat/services/azure/tts.py b/src/pipecat/services/azure/tts.py index d37874825..7e5791f03 100644 --- a/src/pipecat/services/azure/tts.py +++ b/src/pipecat/services/azure/tts.py @@ -115,7 +115,7 @@ class AzureBaseTTSService: class InputParams(BaseModel): """Input parameters for Azure TTS voice configuration. - .. deprecated:: 1.0 + .. deprecated:: 1.0.0 Use ``settings=AzureTTSSettings(...)`` instead. Parameters: @@ -271,13 +271,13 @@ class AzureTTSService(TTSService, AzureBaseTTSService): region: Azure region identifier (e.g., "eastus", "westus2"). voice: Voice name to use for synthesis. - .. deprecated:: 1.0 + .. deprecated:: 1.0.0 Use ``settings=AzureTTSSettings(voice=...)`` instead. sample_rate: Audio sample rate in Hz. If None, uses service default. params: Voice and synthesis parameters configuration. - .. deprecated:: 1.0 + .. deprecated:: 1.0.0 Use ``settings=AzureTTSSettings(...)`` instead. settings: Runtime-updatable settings. When provided alongside deprecated @@ -766,13 +766,13 @@ class AzureHttpTTSService(TTSService, AzureBaseTTSService): region: Azure region identifier (e.g., "eastus", "westus2"). voice: Voice name to use for synthesis. - .. deprecated:: 1.0 + .. deprecated:: 1.0.0 Use ``settings=AzureTTSSettings(voice=...)`` instead. sample_rate: Audio sample rate in Hz. If None, uses service default. params: Voice and synthesis parameters configuration. - .. deprecated:: 1.0 + .. deprecated:: 1.0.0 Use ``settings=AzureTTSSettings(...)`` instead. settings: Runtime-updatable settings. When provided alongside deprecated diff --git a/src/pipecat/services/camb/tts.py b/src/pipecat/services/camb/tts.py index 4ee2d5171..de8b16ab8 100644 --- a/src/pipecat/services/camb/tts.py +++ b/src/pipecat/services/camb/tts.py @@ -175,7 +175,7 @@ class CambTTSService(TTSService): class InputParams(BaseModel): """Input parameters for Camb.ai TTS configuration. - .. deprecated:: 1.0 + .. deprecated:: 1.0.0 Use ``settings=CambTTSSettings(...)`` instead. Parameters: @@ -210,12 +210,12 @@ class CambTTSService(TTSService): api_key: Camb.ai API key for authentication. voice_id: Voice ID to use. - .. deprecated:: 1.0 + .. deprecated:: 1.0.0 Use ``settings=CambTTSSettings(voice=...)`` instead. model: TTS model to use. Options: "mars-flash" (fast), "mars-pro" (high quality). - .. deprecated:: 1.0 + .. deprecated:: 1.0.0 Use ``settings=CambTTSSettings(model=...)`` instead. timeout: Request timeout in seconds. Defaults to 60.0 (minimum recommended @@ -223,7 +223,7 @@ class CambTTSService(TTSService): sample_rate: Audio sample rate in Hz. If None, uses model-specific default. params: Additional voice parameters. If None, uses defaults. - .. deprecated:: 1.0 + .. deprecated:: 1.0.0 Use ``settings=CambTTSSettings(...)`` instead. settings: Runtime-updatable settings. When provided alongside deprecated diff --git a/src/pipecat/services/cartesia/tts.py b/src/pipecat/services/cartesia/tts.py index bc8b04dfd..c2227d00b 100644 --- a/src/pipecat/services/cartesia/tts.py +++ b/src/pipecat/services/cartesia/tts.py @@ -279,14 +279,14 @@ class CartesiaTTSService(AudioContextTTSService): api_key: Cartesia API key for authentication. voice_id: ID of the voice to use for synthesis. - .. deprecated:: 1.0 + .. deprecated:: 1.0.0 Use ``settings=CartesiaTTSSettings(voice=...)`` instead. cartesia_version: API version string for Cartesia service. url: WebSocket URL for Cartesia TTS API. model: TTS model to use (e.g., "sonic-3"). - .. deprecated:: 1.0 + .. deprecated:: 1.0.0 Use ``settings=CartesiaTTSSettings(model=...)`` instead. sample_rate: Audio sample rate. If None, uses default. @@ -294,7 +294,7 @@ class CartesiaTTSService(AudioContextTTSService): container: Audio container format. params: Additional input parameters for voice customization. - .. deprecated:: 1.0 + .. deprecated:: 1.0.0 Use ``settings=CartesiaTTSSettings(...)`` instead. settings: Runtime-updatable settings. When provided alongside deprecated @@ -757,12 +757,12 @@ class CartesiaHttpTTSService(TTSService): api_key: Cartesia API key for authentication. voice_id: ID of the voice to use for synthesis. - .. deprecated:: 1.0 + .. deprecated:: 1.0.0 Use ``settings=CartesiaTTSSettings(voice=...)`` instead. model: TTS model to use (e.g., "sonic-3"). - .. deprecated:: 1.0 + .. deprecated:: 1.0.0 Use ``settings=CartesiaTTSSettings(model=...)`` instead. base_url: Base URL for Cartesia HTTP API. @@ -774,7 +774,7 @@ class CartesiaHttpTTSService(TTSService): container: Audio container format. params: Additional input parameters for voice customization. - .. deprecated:: 1.0 + .. deprecated:: 1.0.0 Use ``settings=CartesiaTTSSettings(...)`` instead. settings: Runtime-updatable settings. When provided alongside deprecated diff --git a/src/pipecat/services/cerebras/llm.py b/src/pipecat/services/cerebras/llm.py index ec3c3f09b..053594083 100644 --- a/src/pipecat/services/cerebras/llm.py +++ b/src/pipecat/services/cerebras/llm.py @@ -39,7 +39,7 @@ class CerebrasLLMService(OpenAILLMService): base_url: The base URL for Cerebras API. Defaults to "https://api.cerebras.ai/v1". model: The model identifier to use. Defaults to "gpt-oss-120b". - .. deprecated:: 1.0 + .. deprecated:: 1.0.0 Use ``settings=OpenAILLMSettings(model=...)`` instead. settings: Runtime-updatable settings. When provided alongside deprecated diff --git a/src/pipecat/services/deepgram/flux/stt.py b/src/pipecat/services/deepgram/flux/stt.py index fdfd65613..04c2f1da3 100644 --- a/src/pipecat/services/deepgram/flux/stt.py +++ b/src/pipecat/services/deepgram/flux/stt.py @@ -124,7 +124,7 @@ class DeepgramFluxSTTService(WebsocketSTTService): class InputParams(BaseModel): """Configuration parameters for Deepgram Flux API. - .. deprecated:: 1.0 + .. deprecated:: 1.0.0 Use ``settings=DeepgramFluxSTTSettings(...)`` instead. Parameters: @@ -173,14 +173,14 @@ class DeepgramFluxSTTService(WebsocketSTTService): sample_rate: Audio sample rate in Hz. If None, uses the rate from params or 16000. model: Deepgram Flux model to use for transcription. - .. deprecated:: 1.0 + .. deprecated:: 1.0.0 Use ``settings=DeepgramFluxSTTSettings(model=...)`` instead. flux_encoding: Audio encoding format required by Flux API. Must be "linear16". Raw signed little-endian 16-bit PCM encoding. params: InputParams instance containing detailed API configuration options. - .. deprecated:: 1.0 + .. deprecated:: 1.0.0 Use ``settings=DeepgramFluxSTTSettings(...)`` instead. should_interrupt: Determine whether the bot should be interrupted when Flux detects that the user is speaking. diff --git a/src/pipecat/services/deepgram/sagemaker/tts.py b/src/pipecat/services/deepgram/sagemaker/tts.py index 0c141bac0..8d03f6eac 100644 --- a/src/pipecat/services/deepgram/sagemaker/tts.py +++ b/src/pipecat/services/deepgram/sagemaker/tts.py @@ -92,7 +92,7 @@ class DeepgramSageMakerTTSService(TTSService): region: AWS region where the endpoint is deployed (e.g., "us-east-2"). voice: Voice model to use for synthesis. Defaults to "aura-2-helena-en". - .. deprecated:: 1.0 + .. deprecated:: 1.0.0 Use ``settings=DeepgramSageMakerTTSSettings(voice=...)`` instead. sample_rate: Audio sample rate in Hz. If None, uses the value from StartFrame. diff --git a/src/pipecat/services/deepgram/tts.py b/src/pipecat/services/deepgram/tts.py index 4524d17b6..7c391490d 100644 --- a/src/pipecat/services/deepgram/tts.py +++ b/src/pipecat/services/deepgram/tts.py @@ -85,7 +85,7 @@ class DeepgramTTSService(WebsocketTTSService): api_key: Deepgram API key for authentication. voice: Voice model to use for synthesis. - .. deprecated:: 1.0 + .. deprecated:: 1.0.0 Use ``settings=DeepgramTTSSettings(voice=...)`` instead. base_url: WebSocket base URL for Deepgram API. Defaults to "wss://api.deepgram.com". @@ -403,7 +403,7 @@ class DeepgramHttpTTSService(TTSService): api_key: Deepgram API key for authentication. voice: Voice model to use for synthesis. - .. deprecated:: 1.0 + .. deprecated:: 1.0.0 Use ``settings=DeepgramTTSSettings(voice=...)`` instead. aiohttp_session: Shared aiohttp session for HTTP requests with connection pooling. diff --git a/src/pipecat/services/deepseek/llm.py b/src/pipecat/services/deepseek/llm.py index 2ebc2e6eb..8cc9ac56e 100644 --- a/src/pipecat/services/deepseek/llm.py +++ b/src/pipecat/services/deepseek/llm.py @@ -39,7 +39,7 @@ class DeepSeekLLMService(OpenAILLMService): base_url: The base URL for DeepSeek API. Defaults to "https://api.deepseek.com/v1". model: The model identifier to use. Defaults to "deepseek-chat". - .. deprecated:: 1.0 + .. deprecated:: 1.0.0 Use ``settings=OpenAILLMSettings(model=...)`` instead. settings: Runtime-updatable settings. When provided alongside deprecated diff --git a/src/pipecat/services/elevenlabs/stt.py b/src/pipecat/services/elevenlabs/stt.py index d5897b5c5..1eebcffde 100644 --- a/src/pipecat/services/elevenlabs/stt.py +++ b/src/pipecat/services/elevenlabs/stt.py @@ -228,7 +228,7 @@ class ElevenLabsSTTService(SegmentedSTTService): class InputParams(BaseModel): """Configuration parameters for ElevenLabs STT API. - .. deprecated:: 1.0 + .. deprecated:: 1.0.0 Use ``settings=ElevenLabsSTTSettings(...)`` instead. Parameters: @@ -260,13 +260,13 @@ class ElevenLabsSTTService(SegmentedSTTService): base_url: Base URL for ElevenLabs API. model: Model ID for transcription. - .. deprecated:: 1.0 + .. deprecated:: 1.0.0 Use ``settings=ElevenLabsSTTSettings(model=...)`` instead. sample_rate: Audio sample rate in Hz. If not provided, uses the pipeline's rate. params: Configuration parameters for the STT service. - .. deprecated:: 1.0 + .. deprecated:: 1.0.0 Use ``settings=ElevenLabsSTTSettings(...)`` instead. settings: Runtime-updatable settings. When provided alongside deprecated @@ -452,7 +452,7 @@ class ElevenLabsRealtimeSTTService(WebsocketSTTService): class InputParams(BaseModel): """Configuration parameters for ElevenLabs Realtime STT API. - .. deprecated:: 1.0 + .. deprecated:: 1.0.0 Use ``settings=ElevenLabsRealtimeSTTSettings(...)`` instead. Parameters: @@ -500,13 +500,13 @@ class ElevenLabsRealtimeSTTService(WebsocketSTTService): base_url: Base URL for ElevenLabs WebSocket API. model: Model ID for transcription. - .. deprecated:: 1.0 + .. deprecated:: 1.0.0 Use ``settings=ElevenLabsRealtimeSTTSettings(model=...)`` instead. sample_rate: Audio sample rate in Hz. If not provided, uses the pipeline's rate. params: Configuration parameters for the STT service. - .. deprecated:: 1.0 + .. deprecated:: 1.0.0 Use ``settings=ElevenLabsRealtimeSTTSettings(...)`` instead. settings: Runtime-updatable settings. When provided alongside deprecated diff --git a/src/pipecat/services/elevenlabs/tts.py b/src/pipecat/services/elevenlabs/tts.py index b98ce6e1b..15c2dbb2e 100644 --- a/src/pipecat/services/elevenlabs/tts.py +++ b/src/pipecat/services/elevenlabs/tts.py @@ -331,7 +331,7 @@ class ElevenLabsTTSService(AudioContextTTSService): class InputParams(BaseModel): """Input parameters for ElevenLabs TTS configuration. - .. deprecated:: 1.0 + .. deprecated:: 1.0.0 Use ``settings=ElevenLabsTTSSettings(...)`` instead. Parameters: @@ -381,12 +381,12 @@ class ElevenLabsTTSService(AudioContextTTSService): api_key: ElevenLabs API key for authentication. voice_id: ID of the voice to use for synthesis. - .. deprecated:: 1.0 + .. deprecated:: 1.0.0 Use ``settings=ElevenLabsTTSSettings(voice=...)`` instead. model: TTS model to use (e.g., "eleven_turbo_v2_5"). - .. deprecated:: 1.0 + .. deprecated:: 1.0.0 Use ``settings=ElevenLabsTTSSettings(model=...)`` instead. url: WebSocket URL for ElevenLabs TTS API. @@ -395,7 +395,7 @@ class ElevenLabsTTSService(AudioContextTTSService): locators to use. params: Additional input parameters for voice customization. - .. deprecated:: 1.0 + .. deprecated:: 1.0.0 Use ``settings=ElevenLabsTTSSettings(...)`` instead. settings: Runtime-updatable settings. When provided alongside deprecated @@ -907,7 +907,7 @@ class ElevenLabsHttpTTSService(TTSService): class InputParams(BaseModel): """Input parameters for ElevenLabs HTTP TTS configuration. - .. deprecated:: 1.0 + .. deprecated:: 1.0.0 Use ``settings=ElevenLabsHttpTTSSettings(...)`` instead. Parameters: @@ -954,13 +954,13 @@ class ElevenLabsHttpTTSService(TTSService): api_key: ElevenLabs API key for authentication. voice_id: ID of the voice to use for synthesis. - .. deprecated:: 1.0 + .. deprecated:: 1.0.0 Use ``settings=ElevenLabsHttpTTSSettings(voice=...)`` instead. aiohttp_session: aiohttp ClientSession for HTTP requests. model: TTS model to use (e.g., "eleven_turbo_v2_5"). - .. deprecated:: 1.0 + .. deprecated:: 1.0.0 Use ``settings=ElevenLabsHttpTTSSettings(model=...)`` instead. base_url: Base URL for ElevenLabs HTTP API. @@ -969,7 +969,7 @@ class ElevenLabsHttpTTSService(TTSService): locators to use. params: Additional input parameters for voice customization. - .. deprecated:: 1.0 + .. deprecated:: 1.0.0 Use ``settings=ElevenLabsHttpTTSSettings(...)`` instead. settings: Runtime-updatable settings. When provided alongside deprecated diff --git a/src/pipecat/services/fal/image.py b/src/pipecat/services/fal/image.py index 8847e3f24..6fd953f13 100644 --- a/src/pipecat/services/fal/image.py +++ b/src/pipecat/services/fal/image.py @@ -80,7 +80,7 @@ class FalImageGenService(ImageGenService): aiohttp_session: HTTP client session for downloading generated images. model: The Fal.ai model to use for generation. Defaults to "fal-ai/fast-sdxl". - .. deprecated:: 1.0 + .. deprecated:: 1.0.0 Use ``settings=FalImageGenSettings(model=...)`` instead. key: Optional API key for Fal.ai. If provided, sets FAL_KEY environment variable. diff --git a/src/pipecat/services/fal/stt.py b/src/pipecat/services/fal/stt.py index d2c1441d0..d80f73a98 100644 --- a/src/pipecat/services/fal/stt.py +++ b/src/pipecat/services/fal/stt.py @@ -169,7 +169,7 @@ class FalSTTService(SegmentedSTTService): class InputParams(BaseModel): """Configuration parameters for Fal's Wizper API. - .. deprecated:: 1.0 + .. deprecated:: 1.0.0 Use ``settings=FalSTTSettings(...)`` instead. Parameters: @@ -204,7 +204,7 @@ class FalSTTService(SegmentedSTTService): sample_rate: Audio sample rate in Hz. If not provided, uses the pipeline's rate. params: Configuration parameters for the Wizper API. - .. deprecated:: 1.0 + .. deprecated:: 1.0.0 Use ``settings=FalSTTSettings(...)`` instead. settings: Runtime-updatable settings. When provided alongside deprecated diff --git a/src/pipecat/services/fireworks/llm.py b/src/pipecat/services/fireworks/llm.py index 9fa9e44bd..33d7d22e2 100644 --- a/src/pipecat/services/fireworks/llm.py +++ b/src/pipecat/services/fireworks/llm.py @@ -38,7 +38,7 @@ class FireworksLLMService(OpenAILLMService): api_key: The API key for accessing Fireworks AI. model: The model identifier to use. Defaults to "accounts/fireworks/models/firefunction-v2". - .. deprecated:: 1.0 + .. deprecated:: 1.0.0 Use ``settings=OpenAILLMSettings(model=...)`` instead. base_url: The base URL for Fireworks API. Defaults to "https://api.fireworks.ai/inference/v1". diff --git a/src/pipecat/services/fish/tts.py b/src/pipecat/services/fish/tts.py index e95cceebd..431b51729 100644 --- a/src/pipecat/services/fish/tts.py +++ b/src/pipecat/services/fish/tts.py @@ -95,7 +95,7 @@ class FishAudioTTSService(InterruptibleTTSService): class InputParams(BaseModel): """Input parameters for Fish Audio TTS configuration. - .. deprecated:: 1.0 + .. deprecated:: 1.0.0 Use ``settings=FishAudioTTSSettings(...)`` instead. Parameters: @@ -131,7 +131,7 @@ class FishAudioTTSService(InterruptibleTTSService): api_key: Fish Audio API key for authentication. reference_id: Reference ID of the voice model to use for synthesis. - .. deprecated:: 1.0 + .. deprecated:: 1.0.0 Use ``settings=FishAudioTTSSettings(voice=...)`` instead. model: Deprecated. Reference ID of the voice model to use for synthesis. @@ -142,14 +142,14 @@ class FishAudioTTSService(InterruptibleTTSService): model_id: Specify which Fish Audio TTS model to use (e.g. "s1"). - .. deprecated:: 1.0 + .. deprecated:: 1.0.0 Use ``settings=FishAudioTTSSettings(model=...)`` instead. output_format: Audio output format. Defaults to "pcm". sample_rate: Audio sample rate. If None, uses default. params: Additional input parameters for voice customization. - .. deprecated:: 1.0 + .. deprecated:: 1.0.0 Use ``settings=FishAudioTTSSettings(...)`` instead. settings: Runtime-updatable settings. When provided alongside deprecated diff --git a/src/pipecat/services/gladia/stt.py b/src/pipecat/services/gladia/stt.py index f2376d93e..e1e0d9276 100644 --- a/src/pipecat/services/gladia/stt.py +++ b/src/pipecat/services/gladia/stt.py @@ -272,12 +272,12 @@ class GladiaSTTService(WebsocketSTTService): sample_rate: Audio sample rate in Hz. If None, uses service default. model: Model to use for transcription. - .. deprecated:: 1.0 + .. deprecated:: 1.0.0 Use ``settings=GladiaSTTSettings(model=...)`` instead. params: Additional configuration parameters for Gladia service. - .. deprecated:: 1.0 + .. deprecated:: 1.0.0 Use ``settings=GladiaSTTSettings(...)`` instead. max_buffer_size: Maximum size of audio buffer in bytes. Defaults to 20MB. diff --git a/src/pipecat/services/google/image.py b/src/pipecat/services/google/image.py index 3d7cf8c94..ce29c0276 100644 --- a/src/pipecat/services/google/image.py +++ b/src/pipecat/services/google/image.py @@ -82,7 +82,7 @@ class GoogleImageGenService(ImageGenService): api_key: Google AI API key for authentication. params: Configuration parameters for image generation. - .. deprecated:: 1.0 + .. deprecated:: 1.0.0 Use ``settings=GoogleImageGenSettings(model=...)`` instead. http_options: HTTP options for the client. diff --git a/src/pipecat/services/google/llm_openai.py b/src/pipecat/services/google/llm_openai.py index 22703ae55..aa8794469 100644 --- a/src/pipecat/services/google/llm_openai.py +++ b/src/pipecat/services/google/llm_openai.py @@ -66,7 +66,7 @@ class GoogleLLMOpenAIBetaService(OpenAILLMService): base_url: Base URL for Google's OpenAI-compatible API. model: Google model name to use (e.g., "gemini-2.0-flash"). - .. deprecated:: 1.0 + .. deprecated:: 1.0.0 Use ``settings=OpenAILLMSettings(model=...)`` instead. settings: Runtime-updatable settings. When provided alongside deprecated diff --git a/src/pipecat/services/google/stt.py b/src/pipecat/services/google/stt.py index 818df0214..23a586b96 100644 --- a/src/pipecat/services/google/stt.py +++ b/src/pipecat/services/google/stt.py @@ -425,7 +425,7 @@ class GoogleSTTService(STTService): class InputParams(BaseModel): """Configuration parameters for Google Speech-to-Text. - .. deprecated:: 1.0 + .. deprecated:: 1.0.0 Use ``settings=GoogleSTTSettings(...)`` instead. Parameters: @@ -500,7 +500,7 @@ class GoogleSTTService(STTService): sample_rate: Audio sample rate in Hertz. params: Configuration parameters for the service. - .. deprecated:: 1.0 + .. deprecated:: 1.0.0 Use ``settings=GoogleSTTSettings(...)`` instead. settings: Runtime-updatable settings. When provided alongside deprecated diff --git a/src/pipecat/services/google/tts.py b/src/pipecat/services/google/tts.py index 86ec845a5..78719f8fa 100644 --- a/src/pipecat/services/google/tts.py +++ b/src/pipecat/services/google/tts.py @@ -566,7 +566,7 @@ class GoogleHttpTTSService(TTSService): class InputParams(BaseModel): """Input parameters for Google HTTP TTS voice customization. - .. deprecated:: 1.0 + .. deprecated:: 1.0.0 Use ``GoogleHttpTTSSettings`` directly via the ``settings`` parameter instead. Parameters: @@ -609,13 +609,13 @@ class GoogleHttpTTSService(TTSService): location: Google Cloud location for regional endpoint (e.g., "us-central1"). voice_id: Google TTS voice identifier (e.g., "en-US-Standard-A"). - .. deprecated:: 1.0 + .. deprecated:: 1.0.0 Use ``settings=GoogleHttpTTSSettings(voice=...)`` instead. sample_rate: Audio sample rate in Hz. If None, uses default. params: Voice customization parameters including pitch, rate, volume, etc. - .. deprecated:: 1.0 + .. deprecated:: 1.0.0 Use ``settings=GoogleHttpTTSSettings(...)`` instead. settings: Runtime-updatable settings. When provided alongside deprecated @@ -1016,7 +1016,7 @@ class GoogleTTSService(GoogleBaseTTSService): class InputParams(BaseModel): """Input parameters for Google streaming TTS configuration. - .. deprecated:: 1.0 + .. deprecated:: 1.0.0 Use ``GoogleStreamTTSSettings`` directly via the ``settings`` parameter instead. Parameters: @@ -1048,14 +1048,14 @@ class GoogleTTSService(GoogleBaseTTSService): location: Google Cloud location for regional endpoint (e.g., "us-central1"). voice_id: Google TTS voice identifier (e.g., "en-US-Chirp3-HD-Charon"). - .. deprecated:: 1.0 + .. deprecated:: 1.0.0 Use ``settings=GoogleStreamTTSSettings(voice=...)`` instead. voice_cloning_key: The voice cloning key for Chirp 3 custom voices. sample_rate: Audio sample rate in Hz. If None, uses default. params: Language configuration parameters. - .. deprecated:: 1.0 + .. deprecated:: 1.0.0 Use ``settings=GoogleStreamTTSSettings(...)`` instead. settings: Runtime-updatable settings. When provided alongside deprecated @@ -1222,7 +1222,7 @@ class GeminiTTSService(GoogleBaseTTSService): class InputParams(BaseModel): """Input parameters for Gemini TTS configuration. - .. deprecated:: 1.0 + .. deprecated:: 1.0.0 Use ``GeminiTTSSettings`` directly via the ``settings`` parameter instead. Parameters: @@ -1263,7 +1263,7 @@ class GeminiTTSService(GoogleBaseTTSService): model: Gemini TTS model to use. Must be a TTS model like "gemini-2.5-flash-tts" or "gemini-2.5-pro-tts". - .. deprecated:: 1.0 + .. deprecated:: 1.0.0 Use ``settings=GeminiTTSSettings(model=...)`` instead. credentials: JSON string containing Google Cloud service account credentials. @@ -1271,13 +1271,13 @@ class GeminiTTSService(GoogleBaseTTSService): location: Google Cloud location for regional endpoint (e.g., "us-central1"). voice_id: Voice name from the available Gemini voices. - .. deprecated:: 1.0 + .. deprecated:: 1.0.0 Use ``settings=GeminiTTSSettings(voice=...)`` instead. sample_rate: Audio sample rate in Hz. If None, uses Google's default 24kHz. params: TTS configuration parameters. - .. deprecated:: 1.0 + .. deprecated:: 1.0.0 Use ``settings=GeminiTTSSettings(...)`` instead. settings: Runtime-updatable settings. When provided alongside deprecated diff --git a/src/pipecat/services/gradium/stt.py b/src/pipecat/services/gradium/stt.py index e1d2b74d4..5974133c0 100644 --- a/src/pipecat/services/gradium/stt.py +++ b/src/pipecat/services/gradium/stt.py @@ -91,7 +91,7 @@ class GradiumSTTService(WebsocketSTTService): class InputParams(BaseModel): """Configuration parameters for Gradium STT API. - .. deprecated:: 1.0 + .. deprecated:: 1.0.0 Use ``settings=GradiumSTTSettings(...)`` instead. Parameters: @@ -125,7 +125,7 @@ class GradiumSTTService(WebsocketSTTService): api_endpoint_base_url: WebSocket endpoint URL. Defaults to Gradium's streaming endpoint. params: Configuration parameters for language and delay settings. - .. deprecated:: 1.0 + .. deprecated:: 1.0.0 Use ``settings=GradiumSTTSettings(...)`` instead. json_config: Optional JSON configuration string for additional model settings. diff --git a/src/pipecat/services/gradium/tts.py b/src/pipecat/services/gradium/tts.py index 75455cf54..6f076f933 100644 --- a/src/pipecat/services/gradium/tts.py +++ b/src/pipecat/services/gradium/tts.py @@ -57,7 +57,7 @@ class GradiumTTSService(AudioContextTTSService): class InputParams(BaseModel): """Configuration parameters for Gradium TTS service. - .. deprecated:: 1.0 + .. deprecated:: 1.0.0 Use ``GradiumTTSSettings`` directly via the ``settings`` parameter instead. Parameters: @@ -84,19 +84,19 @@ class GradiumTTSService(AudioContextTTSService): api_key: Gradium API key for authentication. voice_id: the voice identifier. - .. deprecated:: 1.0 + .. deprecated:: 1.0.0 Use ``settings=GradiumTTSSettings(voice=...)`` instead. url: Gradium websocket API endpoint. model: Model ID to use for synthesis. - .. deprecated:: 1.0 + .. deprecated:: 1.0.0 Use ``settings=GradiumTTSSettings(model=...)`` instead. json_config: Optional JSON configuration string for additional model settings. params: Additional configuration parameters. - .. deprecated:: 1.0 + .. deprecated:: 1.0.0 Use ``settings=GradiumTTSSettings(...)`` instead. settings: Runtime-updatable settings. When provided alongside deprecated diff --git a/src/pipecat/services/grok/llm.py b/src/pipecat/services/grok/llm.py index 0ef6d36f2..2e6a93c4e 100644 --- a/src/pipecat/services/grok/llm.py +++ b/src/pipecat/services/grok/llm.py @@ -95,7 +95,7 @@ class GrokLLMService(OpenAILLMService): base_url: The base URL for Grok API. Defaults to "https://api.x.ai/v1". model: The model identifier to use. Defaults to "grok-3-beta". - .. deprecated:: 1.0 + .. deprecated:: 1.0.0 Use ``settings=OpenAILLMSettings(model=...)`` instead. settings: Runtime-updatable settings. When provided alongside deprecated diff --git a/src/pipecat/services/groq/llm.py b/src/pipecat/services/groq/llm.py index 23cce68a2..0ea3b3f50 100644 --- a/src/pipecat/services/groq/llm.py +++ b/src/pipecat/services/groq/llm.py @@ -38,7 +38,7 @@ class GroqLLMService(OpenAILLMService): base_url: The base URL for Groq API. Defaults to "https://api.groq.com/openai/v1". model: The model identifier to use. Defaults to "llama-3.3-70b-versatile". - .. deprecated:: 1.0 + .. deprecated:: 1.0.0 Use ``settings=OpenAILLMSettings(model=...)`` instead. settings: Runtime-updatable settings. When provided alongside deprecated diff --git a/src/pipecat/services/groq/stt.py b/src/pipecat/services/groq/stt.py index 8018ec702..e6ea42fd8 100644 --- a/src/pipecat/services/groq/stt.py +++ b/src/pipecat/services/groq/stt.py @@ -43,24 +43,24 @@ class GroqSTTService(BaseWhisperSTTService): Args: model: Whisper model to use. - .. deprecated:: 1.0 + .. deprecated:: 1.0.0 Use ``settings=BaseWhisperSTTSettings(model=...)`` instead. api_key: Groq API key. Defaults to None. base_url: API base URL. Defaults to "https://api.groq.com/openai/v1". language: Language of the audio input. - .. deprecated:: 1.0 + .. deprecated:: 1.0.0 Use ``settings=BaseWhisperSTTSettings(language=...)`` instead. prompt: Optional text to guide the model's style or continue a previous segment. - .. deprecated:: 1.0 + .. deprecated:: 1.0.0 Use ``settings=BaseWhisperSTTSettings(prompt=...)`` instead. temperature: Optional sampling temperature between 0 and 1. - .. deprecated:: 1.0 + .. deprecated:: 1.0.0 Use ``settings=BaseWhisperSTTSettings(temperature=...)`` instead. settings: Runtime-updatable settings. When provided alongside deprecated diff --git a/src/pipecat/services/groq/tts.py b/src/pipecat/services/groq/tts.py index c6cc46e23..d16964d8c 100644 --- a/src/pipecat/services/groq/tts.py +++ b/src/pipecat/services/groq/tts.py @@ -64,7 +64,7 @@ class GroqTTSService(TTSService): class InputParams(BaseModel): """Input parameters for Groq TTS configuration. - .. deprecated:: 1.0 + .. deprecated:: 1.0.0 Use ``settings=GroqTTSSettings(...)`` instead. Parameters: @@ -96,17 +96,17 @@ class GroqTTSService(TTSService): output_format: Audio output format. Defaults to "wav". params: Additional input parameters for voice customization. - .. deprecated:: 1.0 + .. deprecated:: 1.0.0 Use ``settings=GroqTTSSettings(...)`` instead. model_name: TTS model to use. - .. deprecated:: 1.0 + .. deprecated:: 1.0.0 Use ``settings=GroqTTSSettings(model=...)`` instead. voice_id: Voice identifier to use. - .. deprecated:: 1.0 + .. deprecated:: 1.0.0 Use ``settings=GroqTTSSettings(voice=...)`` instead. sample_rate: Audio sample rate. Must be 48000 Hz for Groq TTS. diff --git a/src/pipecat/services/hume/tts.py b/src/pipecat/services/hume/tts.py index 35b6fbbc4..5b7300816 100644 --- a/src/pipecat/services/hume/tts.py +++ b/src/pipecat/services/hume/tts.py @@ -84,7 +84,7 @@ class HumeTTSService(TTSService): class InputParams(BaseModel): """Optional synthesis parameters for Hume TTS. - .. deprecated:: 1.0 + .. deprecated:: 1.0.0 Use ``settings=HumeTTSSettings(...)`` instead. Parameters: @@ -113,12 +113,12 @@ class HumeTTSService(TTSService): api_key: Hume API key. If omitted, reads the ``HUME_API_KEY`` environment variable. voice_id: ID of the voice to use. Only voice IDs are supported; voice names are not. - .. deprecated:: 1.0 + .. deprecated:: 1.0.0 Use ``settings=HumeTTSSettings(voice=...)`` instead. params: Optional synthesis controls (acting instructions, speed, trailing silence). - .. deprecated:: 1.0 + .. deprecated:: 1.0.0 Use ``settings=HumeTTSSettings(...)`` instead. sample_rate: Output sample rate for emitted PCM frames. Defaults to 48_000 (Hume). diff --git a/src/pipecat/services/inworld/tts.py b/src/pipecat/services/inworld/tts.py index 23c3b36e4..f1797ad55 100644 --- a/src/pipecat/services/inworld/tts.py +++ b/src/pipecat/services/inworld/tts.py @@ -114,7 +114,7 @@ class InworldHttpTTSService(TTSService): class InputParams(BaseModel): """Input parameters for Inworld TTS configuration. - .. deprecated:: 1.0 + .. deprecated:: 1.0.0 Use ``InworldTTSSettings`` directly via the ``settings`` parameter instead. Parameters: @@ -148,12 +148,12 @@ class InworldHttpTTSService(TTSService): aiohttp_session: aiohttp ClientSession for HTTP requests. voice_id: ID of the voice to use for synthesis. - .. deprecated:: 1.0 + .. deprecated:: 1.0.0 Use ``settings=InworldTTSSettings(voice=...)`` instead. model: ID of the model to use for synthesis. - .. deprecated:: 1.0 + .. deprecated:: 1.0.0 Use ``settings=InworldTTSSettings(model=...)`` instead. streaming: Whether to use streaming mode. @@ -161,7 +161,7 @@ class InworldHttpTTSService(TTSService): encoding: Audio encoding format. params: Input parameters for Inworld TTS configuration. - .. deprecated:: 1.0 + .. deprecated:: 1.0.0 Use ``settings=InworldTTSSettings(...)`` instead. settings: Runtime-updatable settings. When provided alongside deprecated @@ -506,7 +506,7 @@ class InworldTTSService(AudioContextTTSService): class InputParams(BaseModel): """Input parameters for Inworld WebSocket TTS configuration. - .. deprecated:: 1.0 + .. deprecated:: 1.0.0 Use ``InworldTTSSettings`` directly via the ``settings`` parameter instead. Parameters: @@ -553,12 +553,12 @@ class InworldTTSService(AudioContextTTSService): api_key: Inworld API key. voice_id: ID of the voice to use for synthesis. - .. deprecated:: 1.0 + .. deprecated:: 1.0.0 Use ``settings=InworldTTSSettings(voice=...)`` instead. model: ID of the model to use for synthesis. - .. deprecated:: 1.0 + .. deprecated:: 1.0.0 Use ``settings=InworldTTSSettings(model=...)`` instead. url: URL of the Inworld WebSocket API. @@ -566,7 +566,7 @@ class InworldTTSService(AudioContextTTSService): encoding: Audio encoding format. params: Input parameters for Inworld WebSocket TTS configuration. - .. deprecated:: 1.0 + .. deprecated:: 1.0.0 Use ``settings=InworldTTSSettings(...)`` instead. settings: Runtime-updatable settings. When provided alongside deprecated diff --git a/src/pipecat/services/kokoro/tts.py b/src/pipecat/services/kokoro/tts.py index fed53049c..8bab78f93 100644 --- a/src/pipecat/services/kokoro/tts.py +++ b/src/pipecat/services/kokoro/tts.py @@ -112,7 +112,7 @@ class KokoroTTSService(TTSService): class InputParams(BaseModel): """Input parameters for Kokoro TTS configuration. - .. deprecated:: 1.0 + .. deprecated:: 1.0.0 Use ``KokoroTTSSettings`` directly via the ``settings`` parameter instead. Parameters: @@ -136,14 +136,14 @@ class KokoroTTSService(TTSService): Args: voice_id: Voice identifier to use for synthesis. - .. deprecated:: 1.0 + .. deprecated:: 1.0.0 Use ``settings=KokoroTTSSettings(voice=...)`` instead. model_path: Path to the kokoro ONNX model file. Defaults to auto-downloaded file. voices_path: Path to the voices binary file. Defaults to auto-downloaded file. params: Configuration parameters for synthesis. - .. deprecated:: 1.0 + .. deprecated:: 1.0.0 Use ``settings=KokoroTTSSettings(...)`` instead. settings: Runtime-updatable settings. When provided alongside deprecated diff --git a/src/pipecat/services/lmnt/tts.py b/src/pipecat/services/lmnt/tts.py index 1e7cff994..a8ccec358 100644 --- a/src/pipecat/services/lmnt/tts.py +++ b/src/pipecat/services/lmnt/tts.py @@ -111,14 +111,14 @@ class LmntTTSService(InterruptibleTTSService): api_key: LMNT API key for authentication. voice_id: ID of the voice to use for synthesis. - .. deprecated:: 1.0 + .. deprecated:: 1.0.0 Use ``settings=LmntTTSSettings(voice=...)`` instead. sample_rate: Audio sample rate. If None, uses default. language: Language for synthesis. Defaults to English. model: TTS model to use. - .. deprecated:: 1.0 + .. deprecated:: 1.0.0 Use ``settings=LmntTTSSettings(model=...)`` instead. settings: Runtime-updatable settings. When provided alongside deprecated diff --git a/src/pipecat/services/minimax/tts.py b/src/pipecat/services/minimax/tts.py index 602654e2f..9e520f763 100644 --- a/src/pipecat/services/minimax/tts.py +++ b/src/pipecat/services/minimax/tts.py @@ -166,7 +166,7 @@ class MiniMaxHttpTTSService(TTSService): class InputParams(BaseModel): """Configuration parameters for MiniMax TTS. - .. deprecated:: 1.0 + .. deprecated:: 1.0.0 Use ``MiniMaxTTSSettings`` directly via the ``settings`` parameter instead. Parameters: @@ -226,19 +226,19 @@ class MiniMaxHttpTTSService(TTSService): "speech-02-hd", "speech-02-turbo", "speech-01-hd", "speech-01-turbo". - .. deprecated:: 1.0 + .. deprecated:: 1.0.0 Use ``settings=MiniMaxTTSSettings(model=...)`` instead. voice_id: Voice identifier. Defaults to "Calm_Woman". - .. deprecated:: 1.0 + .. deprecated:: 1.0.0 Use ``settings=MiniMaxTTSSettings(voice=...)`` instead. aiohttp_session: aiohttp.ClientSession for API communication. sample_rate: Output audio sample rate in Hz. If None, uses pipeline default. params: Additional configuration parameters. - .. deprecated:: 1.0 + .. deprecated:: 1.0.0 Use ``settings=MiniMaxTTSSettings(...)`` instead. settings: Runtime-updatable settings. When provided alongside deprecated diff --git a/src/pipecat/services/mistral/llm.py b/src/pipecat/services/mistral/llm.py index e4249741e..da1f612c9 100644 --- a/src/pipecat/services/mistral/llm.py +++ b/src/pipecat/services/mistral/llm.py @@ -41,7 +41,7 @@ class MistralLLMService(OpenAILLMService): base_url: The base URL for Mistral API. Defaults to "https://api.mistral.ai/v1". model: The model identifier to use. Defaults to "mistral-small-latest". - .. deprecated:: 1.0 + .. deprecated:: 1.0.0 Use ``settings=OpenAILLMSettings(model=...)`` instead. settings: Runtime-updatable settings. When provided alongside deprecated diff --git a/src/pipecat/services/moondream/vision.py b/src/pipecat/services/moondream/vision.py index db449d7ed..b80928a43 100644 --- a/src/pipecat/services/moondream/vision.py +++ b/src/pipecat/services/moondream/vision.py @@ -93,7 +93,7 @@ class MoondreamService(VisionService): Args: model: Hugging Face model identifier for the Moondream model. - .. deprecated:: 1.0 + .. deprecated:: 1.0.0 Use ``settings=MoondreamSettings(model=...)`` instead. revision: Specific model revision to use. diff --git a/src/pipecat/services/neuphonic/tts.py b/src/pipecat/services/neuphonic/tts.py index 21c7b57dd..e1efee96b 100644 --- a/src/pipecat/services/neuphonic/tts.py +++ b/src/pipecat/services/neuphonic/tts.py @@ -102,7 +102,7 @@ class NeuphonicTTSService(InterruptibleTTSService): class InputParams(BaseModel): """Input parameters for Neuphonic TTS configuration. - .. deprecated:: 1.0 + .. deprecated:: 1.0.0 Use ``settings=NeuphonicTTSSettings(...)`` instead. Parameters: @@ -133,7 +133,7 @@ class NeuphonicTTSService(InterruptibleTTSService): api_key: Neuphonic API key for authentication. voice_id: ID of the voice to use for synthesis. - .. deprecated:: 1.0 + .. deprecated:: 1.0.0 Use ``settings=NeuphonicTTSSettings(voice=...)`` instead. url: WebSocket URL for the Neuphonic API. @@ -141,7 +141,7 @@ class NeuphonicTTSService(InterruptibleTTSService): encoding: Audio encoding format. Defaults to "pcm_linear". params: Additional input parameters for TTS configuration. - .. deprecated:: 1.0 + .. deprecated:: 1.0.0 Use ``settings=NeuphonicTTSSettings(...)`` instead. settings: Runtime-updatable settings. When provided alongside deprecated @@ -441,7 +441,7 @@ class NeuphonicHttpTTSService(TTSService): class InputParams(BaseModel): """Input parameters for Neuphonic HTTP TTS configuration. - .. deprecated:: 1.0 + .. deprecated:: 1.0.0 Use ``settings=NeuphonicTTSSettings(...)`` instead. Parameters: @@ -471,7 +471,7 @@ class NeuphonicHttpTTSService(TTSService): api_key: Neuphonic API key for authentication. voice_id: ID of the voice to use for synthesis. - .. deprecated:: 1.0 + .. deprecated:: 1.0.0 Use ``settings=NeuphonicTTSSettings(voice=...)`` instead. aiohttp_session: Shared aiohttp session for HTTP requests. @@ -480,7 +480,7 @@ class NeuphonicHttpTTSService(TTSService): encoding: Audio encoding format. Defaults to "pcm_linear". params: Additional input parameters for TTS configuration. - .. deprecated:: 1.0 + .. deprecated:: 1.0.0 Use ``settings=NeuphonicTTSSettings(...)`` instead. settings: Runtime-updatable settings. When provided alongside deprecated diff --git a/src/pipecat/services/nvidia/llm.py b/src/pipecat/services/nvidia/llm.py index ef4afe848..1667457b9 100644 --- a/src/pipecat/services/nvidia/llm.py +++ b/src/pipecat/services/nvidia/llm.py @@ -45,7 +45,7 @@ class NvidiaLLMService(OpenAILLMService): model: The model identifier to use. Defaults to "nvidia/llama-3.1-nemotron-70b-instruct". - .. deprecated:: 1.0 + .. deprecated:: 1.0.0 Use ``settings=OpenAILLMSettings(model=...)`` instead. settings: Runtime-updatable settings. When provided alongside deprecated diff --git a/src/pipecat/services/nvidia/stt.py b/src/pipecat/services/nvidia/stt.py index 7f9c28f8f..63e901005 100644 --- a/src/pipecat/services/nvidia/stt.py +++ b/src/pipecat/services/nvidia/stt.py @@ -130,7 +130,7 @@ class NvidiaSTTService(STTService): class InputParams(BaseModel): """Configuration parameters for NVIDIA Riva STT service. - .. deprecated:: 1.0 + .. deprecated:: 1.0.0 Use ``settings=NvidiaSTTSettings(...)`` instead. Parameters: @@ -164,7 +164,7 @@ class NvidiaSTTService(STTService): sample_rate: Audio sample rate in Hz. If None, uses pipeline default. params: Additional configuration parameters for NVIDIA Riva. - .. deprecated:: 1.0 + .. deprecated:: 1.0.0 Use ``settings=NvidiaSTTSettings(...)`` instead. use_ssl: Whether to use SSL for the NVIDIA Riva server. Defaults to True. @@ -438,7 +438,7 @@ class NvidiaSegmentedSTTService(SegmentedSTTService): class InputParams(BaseModel): """Configuration parameters for NVIDIA Riva segmented STT service. - .. deprecated:: 1.0 + .. deprecated:: 1.0.0 Use ``settings=NvidiaSegmentedSTTSettings(...)`` instead. Parameters: @@ -482,7 +482,7 @@ class NvidiaSegmentedSTTService(SegmentedSTTService): sample_rate: Audio sample rate in Hz. If not provided, uses the pipeline's rate params: Additional configuration parameters for NVIDIA Riva - .. deprecated:: 1.0 + .. deprecated:: 1.0.0 Use ``settings=NvidiaSegmentedSTTSettings(...)`` instead. use_ssl: Whether to use SSL for the NVIDIA Riva server. Defaults to True. diff --git a/src/pipecat/services/nvidia/tts.py b/src/pipecat/services/nvidia/tts.py index 0f7491645..75caa27e4 100644 --- a/src/pipecat/services/nvidia/tts.py +++ b/src/pipecat/services/nvidia/tts.py @@ -68,7 +68,7 @@ class NvidiaTTSService(TTSService): class InputParams(BaseModel): """Input parameters for Riva TTS configuration. - .. deprecated:: 1.0 + .. deprecated:: 1.0.0 Use ``NvidiaTTSSettings`` directly via the ``settings`` parameter instead. Parameters: @@ -102,14 +102,14 @@ class NvidiaTTSService(TTSService): server: gRPC server endpoint. Defaults to NVIDIA's cloud endpoint. voice_id: Voice model identifier. Defaults to multilingual Aria voice. - .. deprecated:: 1.0 + .. deprecated:: 1.0.0 Use ``settings=NvidiaTTSSettings(voice=...)`` instead. sample_rate: Audio sample rate. If None, uses service default. model_function_map: Dictionary containing function_id and model_name for the TTS model. params: Additional configuration parameters for TTS synthesis. - .. deprecated:: 1.0 + .. deprecated:: 1.0.0 Use ``settings=NvidiaTTSSettings(...)`` instead. settings: Runtime-updatable settings. When provided alongside deprecated diff --git a/src/pipecat/services/ollama/llm.py b/src/pipecat/services/ollama/llm.py index ecae3fc95..8fc94985d 100644 --- a/src/pipecat/services/ollama/llm.py +++ b/src/pipecat/services/ollama/llm.py @@ -35,7 +35,7 @@ class OLLamaLLMService(OpenAILLMService): Args: model: The OLLama model to use. Defaults to "llama2". - .. deprecated:: 1.0 + .. deprecated:: 1.0.0 Use ``settings=OpenAILLMSettings(model=...)`` instead. base_url: The base URL for the OLLama API endpoint. diff --git a/src/pipecat/services/openai/base_llm.py b/src/pipecat/services/openai/base_llm.py index 9ff3af0ab..0b4c3dec7 100644 --- a/src/pipecat/services/openai/base_llm.py +++ b/src/pipecat/services/openai/base_llm.py @@ -75,7 +75,7 @@ class BaseOpenAILLMService(LLMService): class InputParams(BaseModel): """Input parameters for OpenAI model configuration. - .. deprecated:: 1.0 + .. deprecated:: 1.0.0 Use ``settings=OpenAILLMSettings(...)`` instead of ``params=InputParams(...)``. @@ -130,7 +130,7 @@ class BaseOpenAILLMService(LLMService): Args: model: The OpenAI model name to use (e.g., "gpt-4.1", "gpt-4o"). - .. deprecated:: 1.0 + .. deprecated:: 1.0.0 Use ``settings=OpenAILLMSettings(model=...)`` instead. api_key: OpenAI API key. If None, uses environment variable. @@ -140,7 +140,7 @@ class BaseOpenAILLMService(LLMService): default_headers: Additional HTTP headers to include in requests. params: Input parameters for model configuration and behavior. - .. deprecated:: 1.0 + .. deprecated:: 1.0.0 Use ``settings=OpenAILLMSettings(...)`` instead. settings: Runtime-updatable settings. When provided alongside deprecated diff --git a/src/pipecat/services/openai/image.py b/src/pipecat/services/openai/image.py index 2dc66876c..a145df6e5 100644 --- a/src/pipecat/services/openai/image.py +++ b/src/pipecat/services/openai/image.py @@ -64,7 +64,7 @@ class OpenAIImageGenService(ImageGenService): image_size: Target size for generated images. model: DALL-E model to use for generation. Defaults to "dall-e-3". - .. deprecated:: 1.0 + .. deprecated:: 1.0.0 Use ``settings=OpenAIImageGenSettings(model=...)`` instead. settings: Runtime-updatable settings. When provided alongside deprecated diff --git a/src/pipecat/services/openai/llm.py b/src/pipecat/services/openai/llm.py index c259987a8..a8ab760c4 100644 --- a/src/pipecat/services/openai/llm.py +++ b/src/pipecat/services/openai/llm.py @@ -83,12 +83,12 @@ class OpenAILLMService(BaseOpenAILLMService): Args: model: The OpenAI model name to use. Defaults to "gpt-4.1". - .. deprecated:: 1.0 + .. deprecated:: 1.0.0 Use ``settings=OpenAILLMSettings(model=...)`` instead. params: Input parameters for model configuration. - .. deprecated:: 1.0 + .. deprecated:: 1.0.0 Use ``settings=OpenAILLMSettings(...)`` instead. settings: Runtime-updatable settings. When provided alongside deprecated diff --git a/src/pipecat/services/openai/stt.py b/src/pipecat/services/openai/stt.py index be933cd9a..5c31d3f02 100644 --- a/src/pipecat/services/openai/stt.py +++ b/src/pipecat/services/openai/stt.py @@ -80,7 +80,7 @@ class OpenAISTTService(BaseWhisperSTTService): Args: model: Model to use — either gpt-4o or Whisper. - .. deprecated:: 1.0 + .. deprecated:: 1.0.0 Use ``settings=BaseWhisperSTTSettings(model=...)`` instead. api_key: OpenAI API key. Defaults to None. @@ -210,7 +210,7 @@ class OpenAIRealtimeSTTService(WebsocketSTTService): model: Transcription model. Supported values are ``"gpt-4o-transcribe"`` and ``"gpt-4o-mini-transcribe"``. - .. deprecated:: 1.0 + .. deprecated:: 1.0.0 Use ``settings=OpenAIRealtimeSTTSettings(model=...)`` instead. base_url: WebSocket base URL for the Realtime API. diff --git a/src/pipecat/services/openai/tts.py b/src/pipecat/services/openai/tts.py index 965b8faf7..42c963808 100644 --- a/src/pipecat/services/openai/tts.py +++ b/src/pipecat/services/openai/tts.py @@ -90,7 +90,7 @@ class OpenAITTSService(TTSService): class InputParams(BaseModel): """Input parameters for OpenAI TTS configuration. - .. deprecated:: 1.0 + .. deprecated:: 1.0.0 Use ``settings=OpenAITTSSettings(...)`` instead. Parameters: @@ -122,28 +122,28 @@ class OpenAITTSService(TTSService): base_url: Custom base URL for OpenAI API. If None, uses default. voice: Voice ID to use for synthesis. Defaults to "alloy". - .. deprecated:: 1.0 + .. deprecated:: 1.0.0 Use ``settings=OpenAITTSSettings(voice=...)`` instead. model: TTS model to use. Defaults to "gpt-4o-mini-tts". - .. deprecated:: 1.0 + .. deprecated:: 1.0.0 Use ``settings=OpenAITTSSettings(model=...)`` instead. sample_rate: Output audio sample rate in Hz. If None, uses OpenAI's default 24kHz. instructions: Optional instructions to guide voice synthesis behavior. - .. deprecated:: 1.0 + .. deprecated:: 1.0.0 Use ``settings=OpenAITTSSettings(instructions=...)`` instead. speed: Voice speed control (0.25 to 4.0, default 1.0). - .. deprecated:: 1.0 + .. deprecated:: 1.0.0 Use ``settings=OpenAITTSSettings(speed=...)`` instead. params: Optional synthesis controls (acting instructions, speed, ...). - .. deprecated:: 1.0 + .. deprecated:: 1.0.0 Use ``settings=OpenAITTSSettings(...)`` instead. settings: Runtime-updatable settings. When provided alongside deprecated diff --git a/src/pipecat/services/openpipe/llm.py b/src/pipecat/services/openpipe/llm.py index 524eff860..7fb4ebd2d 100644 --- a/src/pipecat/services/openpipe/llm.py +++ b/src/pipecat/services/openpipe/llm.py @@ -52,7 +52,7 @@ class OpenPipeLLMService(OpenAILLMService): Args: model: The model name to use. Defaults to "gpt-4.1". - .. deprecated:: 1.0 + .. deprecated:: 1.0.0 Use ``settings=OpenAILLMSettings(model=...)`` instead. api_key: OpenAI API key for authentication. If None, reads from environment. diff --git a/src/pipecat/services/openrouter/llm.py b/src/pipecat/services/openrouter/llm.py index 9b202c04d..ea307aaee 100644 --- a/src/pipecat/services/openrouter/llm.py +++ b/src/pipecat/services/openrouter/llm.py @@ -42,7 +42,7 @@ class OpenRouterLLMService(OpenAILLMService): to read from environment variables. model: The model identifier to use. Defaults to "openai/gpt-4o-2024-11-20". - .. deprecated:: 1.0 + .. deprecated:: 1.0.0 Use ``settings=OpenAILLMSettings(model=...)`` instead. base_url: The base URL for OpenRouter API. Defaults to "https://openrouter.ai/api/v1". diff --git a/src/pipecat/services/perplexity/llm.py b/src/pipecat/services/perplexity/llm.py index b00f9e974..1fbf763f3 100644 --- a/src/pipecat/services/perplexity/llm.py +++ b/src/pipecat/services/perplexity/llm.py @@ -46,7 +46,7 @@ class PerplexityLLMService(OpenAILLMService): base_url: The base URL for Perplexity's API. Defaults to "https://api.perplexity.ai". model: The model identifier to use. Defaults to "sonar". - .. deprecated:: 1.0 + .. deprecated:: 1.0.0 Use ``settings=OpenAILLMSettings(model=...)`` instead. settings: Runtime-updatable settings. When provided alongside deprecated diff --git a/src/pipecat/services/piper/tts.py b/src/pipecat/services/piper/tts.py index 559824b49..73c555c9d 100644 --- a/src/pipecat/services/piper/tts.py +++ b/src/pipecat/services/piper/tts.py @@ -65,7 +65,7 @@ class PiperTTSService(TTSService): Args: voice_id: Piper voice model identifier (e.g. `en_US-ryan-high`). - .. deprecated:: 1.0 + .. deprecated:: 1.0.0 Use ``settings=PiperTTSSettings(voice=...)`` instead. download_dir: Directory for storing voice model files. Defaults to @@ -215,7 +215,7 @@ class PiperHttpTTSService(TTSService): aiohttp_session: aiohttp ClientSession for making HTTP requests. voice_id: Piper voice model identifier (e.g. `en_US-ryan-high`). - .. deprecated:: 1.0 + .. deprecated:: 1.0.0 Use ``settings=PiperHttpTTSSettings(voice=...)`` instead. settings: Runtime-updatable settings. When provided alongside deprecated diff --git a/src/pipecat/services/qwen/llm.py b/src/pipecat/services/qwen/llm.py index 132924662..db407f880 100644 --- a/src/pipecat/services/qwen/llm.py +++ b/src/pipecat/services/qwen/llm.py @@ -38,7 +38,7 @@ class QwenLLMService(OpenAILLMService): base_url: Base URL for Qwen API. Defaults to "https://dashscope-intl.aliyuncs.com/compatible-mode/v1". model: The model identifier to use. Defaults to "qwen-plus". - .. deprecated:: 1.0 + .. deprecated:: 1.0.0 Use ``settings=OpenAILLMSettings(model=...)`` instead. settings: Runtime-updatable settings. When provided alongside deprecated diff --git a/src/pipecat/services/resembleai/tts.py b/src/pipecat/services/resembleai/tts.py index 148dacde2..ade4361e0 100644 --- a/src/pipecat/services/resembleai/tts.py +++ b/src/pipecat/services/resembleai/tts.py @@ -84,7 +84,7 @@ class ResembleAITTSService(AudioContextTTSService): api_key: Resemble AI API key for authentication. voice_id: Voice UUID to use for synthesis. - .. deprecated:: 1.0 + .. deprecated:: 1.0.0 Use ``settings=ResembleAITTSSettings(voice=...)`` instead. url: WebSocket URL for Resemble AI TTS API. diff --git a/src/pipecat/services/rime/tts.py b/src/pipecat/services/rime/tts.py index a44b738d1..c607a2e06 100644 --- a/src/pipecat/services/rime/tts.py +++ b/src/pipecat/services/rime/tts.py @@ -144,7 +144,7 @@ class RimeTTSService(AudioContextTTSService): class InputParams(BaseModel): """Configuration parameters for Rime TTS service. - .. deprecated:: 1.0 + .. deprecated:: 1.0.0 Use ``settings=RimeTTSSettings(...)`` instead. Parameters: @@ -196,19 +196,19 @@ class RimeTTSService(AudioContextTTSService): api_key: Rime API key for authentication. voice_id: ID of the voice to use. - .. deprecated:: 1.0 + .. deprecated:: 1.0.0 Use ``settings=RimeTTSSettings(voice=...)`` instead. url: Rime websocket API endpoint. model: Model ID to use for synthesis. - .. deprecated:: 1.0 + .. deprecated:: 1.0.0 Use ``settings=RimeTTSSettings(model=...)`` instead. sample_rate: Audio sample rate in Hz. params: Additional configuration parameters. - .. deprecated:: 1.0 + .. deprecated:: 1.0.0 Use ``settings=RimeTTSSettings(...)`` instead. settings: Runtime-updatable settings. When provided alongside deprecated @@ -657,7 +657,7 @@ class RimeHttpTTSService(TTSService): class InputParams(BaseModel): """Configuration parameters for Rime HTTP TTS service. - .. deprecated:: 1.0 + .. deprecated:: 1.0.0 Use ``settings=RimeTTSSettings(...)`` instead. Parameters: @@ -694,19 +694,19 @@ class RimeHttpTTSService(TTSService): api_key: Rime API key for authentication. voice_id: ID of the voice to use. - .. deprecated:: 1.0 + .. deprecated:: 1.0.0 Use ``settings=RimeTTSSettings(voice=...)`` instead. aiohttp_session: Shared aiohttp session for HTTP requests. model: Model ID to use for synthesis. - .. deprecated:: 1.0 + .. deprecated:: 1.0.0 Use ``settings=RimeTTSSettings(model=...)`` instead. sample_rate: Audio sample rate in Hz. params: Additional configuration parameters. - .. deprecated:: 1.0 + .. deprecated:: 1.0.0 Use ``settings=RimeTTSSettings(...)`` instead. settings: Runtime-updatable settings. When provided alongside deprecated @@ -868,7 +868,7 @@ class RimeNonJsonTTSService(InterruptibleTTSService): class InputParams(BaseModel): """Configuration parameters for Rime Non-JSON WebSocket TTS service. - .. deprecated:: 1.0 + .. deprecated:: 1.0.0 Use ``settings=RimeNonJsonTTSSettings(...)`` instead. Args: @@ -908,20 +908,20 @@ class RimeNonJsonTTSService(InterruptibleTTSService): api_key: Rime API key for authentication. voice_id: ID of the voice to use. - .. deprecated:: 1.0 + .. deprecated:: 1.0.0 Use ``settings=RimeNonJsonTTSSettings(voice=...)`` instead. url: Rime websocket API endpoint. model: Model ID to use for synthesis. - .. deprecated:: 1.0 + .. deprecated:: 1.0.0 Use ``settings=RimeNonJsonTTSSettings(model=...)`` instead. audio_format: Audio format to use. sample_rate: Audio sample rate in Hz. params: Additional configuration parameters. - .. deprecated:: 1.0 + .. deprecated:: 1.0.0 Use ``settings=RimeNonJsonTTSSettings(...)`` instead. settings: Runtime-updatable settings. When provided alongside deprecated diff --git a/src/pipecat/services/sambanova/llm.py b/src/pipecat/services/sambanova/llm.py index 23d415598..5114297a8 100644 --- a/src/pipecat/services/sambanova/llm.py +++ b/src/pipecat/services/sambanova/llm.py @@ -49,7 +49,7 @@ class SambaNovaLLMService(OpenAILLMService): # type: ignore api_key: The API key for accessing SambaNova API. model: The model identifier to use. Defaults to "Llama-4-Maverick-17B-128E-Instruct". - .. deprecated:: 1.0 + .. deprecated:: 1.0.0 Use ``settings=OpenAILLMSettings(model=...)`` instead. base_url: The base URL for SambaNova API. Defaults to "https://api.sambanova.ai/v1". diff --git a/src/pipecat/services/sambanova/stt.py b/src/pipecat/services/sambanova/stt.py index 4e3c9e01d..4ca156b88 100644 --- a/src/pipecat/services/sambanova/stt.py +++ b/src/pipecat/services/sambanova/stt.py @@ -45,24 +45,24 @@ class SambaNovaSTTService(BaseWhisperSTTService): # type: ignore Args: model: Whisper model to use. - .. deprecated:: 1.0 + .. deprecated:: 1.0.0 Use ``settings=BaseWhisperSTTSettings(model=...)`` instead. api_key: SambaNova API key. Defaults to None. base_url: API base URL. Defaults to "https://api.sambanova.ai/v1". language: Language of the audio input. - .. deprecated:: 1.0 + .. deprecated:: 1.0.0 Use ``settings=BaseWhisperSTTSettings(language=...)`` instead. prompt: Optional text to guide the model's style or continue a previous segment. - .. deprecated:: 1.0 + .. deprecated:: 1.0.0 Use ``settings=BaseWhisperSTTSettings(prompt=...)`` instead. temperature: Optional sampling temperature between 0 and 1. - .. deprecated:: 1.0 + .. deprecated:: 1.0.0 Use ``settings=BaseWhisperSTTSettings(temperature=...)`` instead. settings: Runtime-updatable settings. When provided alongside deprecated diff --git a/src/pipecat/services/sarvam/stt.py b/src/pipecat/services/sarvam/stt.py index b3ac41470..97c8d1ccc 100644 --- a/src/pipecat/services/sarvam/stt.py +++ b/src/pipecat/services/sarvam/stt.py @@ -177,7 +177,7 @@ class SarvamSTTService(STTService): class InputParams(BaseModel): """Configuration parameters for Sarvam STT service. - .. deprecated:: 1.0 + .. deprecated:: 1.0.0 Use ``settings=SarvamSTTSettings(...)`` instead. Parameters: @@ -219,14 +219,14 @@ class SarvamSTTService(STTService): api_key: Sarvam API key for authentication. model: Sarvam model to use for transcription. - .. deprecated:: 1.0 + .. deprecated:: 1.0.0 Use ``settings=SarvamSTTSettings(model=...)`` instead. sample_rate: Audio sample rate. Defaults to 16000 if not specified. input_audio_codec: Audio codec/format of the input file. Defaults to "wav". params: Configuration parameters for Sarvam STT service. - .. deprecated:: 1.0 + .. deprecated:: 1.0.0 Use ``settings=SarvamSTTSettings(...)`` instead. settings: Runtime-updatable settings. When provided alongside deprecated diff --git a/src/pipecat/services/sarvam/tts.py b/src/pipecat/services/sarvam/tts.py index 4d125dfc9..14386d743 100644 --- a/src/pipecat/services/sarvam/tts.py +++ b/src/pipecat/services/sarvam/tts.py @@ -376,7 +376,7 @@ class SarvamHttpTTSService(TTSService): class InputParams(BaseModel): """Input parameters for Sarvam TTS configuration. - .. deprecated:: 1.0 + .. deprecated:: 1.0.0 Use ``SarvamHttpTTSSettings`` directly via the ``settings`` parameter instead. Parameters: @@ -445,14 +445,14 @@ class SarvamHttpTTSService(TTSService): aiohttp_session: Shared aiohttp session for making requests. voice_id: Speaker voice ID. If None, uses model-appropriate default. - .. deprecated:: 1.0 + .. deprecated:: 1.0.0 Use ``settings=SarvamHttpTTSSettings(voice=...)`` instead. model: TTS model to use. Options: - "bulbul:v2" (default): Standard model with pitch/loudness support - "bulbul:v3-beta": Advanced model with temperature control - .. deprecated:: 1.0 + .. deprecated:: 1.0.0 Use ``settings=SarvamHttpTTSSettings(model=...)`` instead. base_url: Sarvam AI API base URL. Defaults to "https://api.sarvam.ai". @@ -460,7 +460,7 @@ class SarvamHttpTTSService(TTSService): If None, uses model-specific default. params: Additional voice and preprocessing parameters. If None, uses defaults. - .. deprecated:: 1.0 + .. deprecated:: 1.0.0 Use ``settings=SarvamHttpTTSSettings(...)`` instead. settings: Runtime-updatable settings. When provided alongside deprecated @@ -724,7 +724,7 @@ class SarvamTTSService(InterruptibleTTSService): class InputParams(BaseModel): """Configuration parameters for Sarvam TTS WebSocket service. - .. deprecated:: 1.0 + .. deprecated:: 1.0.0 Use ``SarvamTTSSettings`` directly via the ``settings`` parameter instead. Parameters: @@ -830,12 +830,12 @@ class SarvamTTSService(InterruptibleTTSService): - "bulbul:v2" (default): Standard model with pitch/loudness support - "bulbul:v3-beta": Advanced model with temperature control - .. deprecated:: 1.0 + .. deprecated:: 1.0.0 Use ``settings=SarvamTTSSettings(model=...)`` instead. voice_id: Speaker voice ID. If None, uses model-appropriate default. - .. deprecated:: 1.0 + .. deprecated:: 1.0.0 Use ``settings=SarvamTTSSettings(voice=...)`` instead. url: WebSocket URL for the TTS backend (default production URL). @@ -849,7 +849,7 @@ class SarvamTTSService(InterruptibleTTSService): If None, uses model-specific default. params: Optional input parameters to override defaults. - .. deprecated:: 1.0 + .. deprecated:: 1.0.0 Use ``settings=SarvamTTSSettings(...)`` instead. settings: Runtime-updatable settings. When provided alongside deprecated diff --git a/src/pipecat/services/soniox/stt.py b/src/pipecat/services/soniox/stt.py index 84c437f36..c9b3fb7c9 100644 --- a/src/pipecat/services/soniox/stt.py +++ b/src/pipecat/services/soniox/stt.py @@ -79,7 +79,7 @@ class SonioxContextObject(BaseModel): class SonioxInputParams(BaseModel): """Real-time transcription settings. - .. deprecated:: 1.0 + .. deprecated:: 1.0.0 Use ``settings=SonioxSTTSettings(...)`` instead. See Soniox WebSocket API documentation for more details: @@ -201,13 +201,13 @@ class SonioxSTTService(WebsocketSTTService): sample_rate: Audio sample rate. model: Soniox model to use for transcription. - .. deprecated:: 1.0 + .. deprecated:: 1.0.0 Use ``settings=SonioxSTTSettings(model=...)`` instead. params: Additional configuration parameters, such as language hints, context and speaker diarization. - .. deprecated:: 1.0 + .. deprecated:: 1.0.0 Use ``settings=SonioxSTTSettings(...)`` instead. vad_force_turn_endpoint: Listen to `VADUserStoppedSpeakingFrame` to send finalize message to Soniox. diff --git a/src/pipecat/services/speechmatics/stt.py b/src/pipecat/services/speechmatics/stt.py index a0ca19f74..2d3e90896 100644 --- a/src/pipecat/services/speechmatics/stt.py +++ b/src/pipecat/services/speechmatics/stt.py @@ -395,7 +395,7 @@ class SpeechmaticsSTTService(STTService): sample_rate: Optional audio sample rate in Hz. params: Input parameters for the service. - .. deprecated:: 1.0 + .. deprecated:: 1.0.0 Use ``settings=SpeechmaticsSTTSettings(...)`` instead. should_interrupt: Determine whether the bot should be interrupted when Speechmatics turn_detection_mode is configured to detect user speech. diff --git a/src/pipecat/services/speechmatics/tts.py b/src/pipecat/services/speechmatics/tts.py index e1260fbe2..8ce6ae2ef 100644 --- a/src/pipecat/services/speechmatics/tts.py +++ b/src/pipecat/services/speechmatics/tts.py @@ -62,7 +62,7 @@ class SpeechmaticsTTSService(TTSService): class InputParams(BaseModel): """Optional input parameters for Speechmatics TTS configuration. - .. deprecated:: 1.0 + .. deprecated:: 1.0.0 Use ``settings=SpeechmaticsTTSSettings(...)`` instead. Parameters: @@ -90,14 +90,14 @@ class SpeechmaticsTTSService(TTSService): base_url: Base URL for Speechmatics TTS API. voice_id: Voice model to use for synthesis. - .. deprecated:: 1.0 + .. deprecated:: 1.0.0 Use ``settings=SpeechmaticsTTSSettings(voice=...)`` instead. aiohttp_session: Shared aiohttp session for HTTP requests. sample_rate: Audio sample rate in Hz. params: Input parameters for the service. - .. deprecated:: 1.0 + .. deprecated:: 1.0.0 Use ``settings=SpeechmaticsTTSSettings(...)`` instead. settings: Runtime-updatable settings. When provided alongside deprecated diff --git a/src/pipecat/services/together/llm.py b/src/pipecat/services/together/llm.py index b1cb4ffea..48e15ae5c 100644 --- a/src/pipecat/services/together/llm.py +++ b/src/pipecat/services/together/llm.py @@ -38,7 +38,7 @@ class TogetherLLMService(OpenAILLMService): base_url: The base URL for Together.ai API. Defaults to "https://api.together.xyz/v1". model: The model identifier to use. Defaults to "meta-llama/Meta-Llama-3.1-8B-Instruct-Turbo". - .. deprecated:: 1.0 + .. deprecated:: 1.0.0 Use ``settings=OpenAILLMSettings(model=...)`` instead. settings: Runtime-updatable settings. When provided alongside deprecated diff --git a/src/pipecat/services/whisper/base_stt.py b/src/pipecat/services/whisper/base_stt.py index 32dd382e8..a54da0c05 100644 --- a/src/pipecat/services/whisper/base_stt.py +++ b/src/pipecat/services/whisper/base_stt.py @@ -146,24 +146,24 @@ class BaseWhisperSTTService(SegmentedSTTService): Args: model: Name of the Whisper model to use. - .. deprecated:: 1.0 + .. deprecated:: 1.0.0 Use ``settings=BaseWhisperSTTSettings(model=...)`` instead. api_key: Service API key. Defaults to None. base_url: Service API base URL. Defaults to None. language: Language of the audio input. - .. deprecated:: 1.0 + .. deprecated:: 1.0.0 Use ``settings=BaseWhisperSTTSettings(language=...)`` instead. prompt: Optional text to guide the model's style or continue a previous segment. - .. deprecated:: 1.0 + .. deprecated:: 1.0.0 Use ``settings=BaseWhisperSTTSettings(prompt=...)`` instead. temperature: Sampling temperature between 0 and 1. - .. deprecated:: 1.0 + .. deprecated:: 1.0.0 Use ``settings=BaseWhisperSTTSettings(temperature=...)`` instead. include_prob_metrics: If True, enables probability metrics in API response. diff --git a/src/pipecat/services/whisper/stt.py b/src/pipecat/services/whisper/stt.py index 2e0a6156a..38fd287fa 100644 --- a/src/pipecat/services/whisper/stt.py +++ b/src/pipecat/services/whisper/stt.py @@ -229,27 +229,27 @@ class WhisperSTTService(SegmentedSTTService): Args: model: The Whisper model to use for transcription. Can be a Model enum or string. - .. deprecated:: 1.0 + .. deprecated:: 1.0.0 Use ``settings=WhisperSTTSettings(model=...)`` instead. device: The device to run inference on ('cpu', 'cuda', or 'auto'). - .. deprecated:: 1.0 + .. deprecated:: 1.0.0 Use ``settings=WhisperSTTSettings(device=...)`` instead. compute_type: The compute type for inference ('default', 'int8', 'int8_float16', etc.). - .. deprecated:: 1.0 + .. deprecated:: 1.0.0 Use ``settings=WhisperSTTSettings(compute_type=...)`` instead. no_speech_prob: Probability threshold for filtering out non-speech segments. - .. deprecated:: 1.0 + .. deprecated:: 1.0.0 Use ``settings=WhisperSTTSettings(no_speech_prob=...)`` instead. language: The default language for transcription. - .. deprecated:: 1.0 + .. deprecated:: 1.0.0 Use ``settings=WhisperSTTSettings(language=...)`` instead. settings: Runtime-updatable settings. When provided alongside deprecated @@ -408,22 +408,22 @@ class WhisperSTTServiceMLX(WhisperSTTService): Args: model: The MLX Whisper model to use for transcription. Can be an MLXModel enum or string. - .. deprecated:: 1.0 + .. deprecated:: 1.0.0 Use ``settings=WhisperMLXSTTSettings(model=...)`` instead. no_speech_prob: Probability threshold for filtering out non-speech segments. - .. deprecated:: 1.0 + .. deprecated:: 1.0.0 Use ``settings=WhisperMLXSTTSettings(no_speech_prob=...)`` instead. language: The default language for transcription. - .. deprecated:: 1.0 + .. deprecated:: 1.0.0 Use ``settings=WhisperMLXSTTSettings(language=...)`` instead. temperature: Temperature for sampling. Can be a float or tuple of floats. - .. deprecated:: 1.0 + .. deprecated:: 1.0.0 Use ``settings=WhisperMLXSTTSettings(temperature=...)`` instead. settings: Runtime-updatable settings. When provided alongside deprecated diff --git a/src/pipecat/services/xtts/tts.py b/src/pipecat/services/xtts/tts.py index bba95a400..88137172f 100644 --- a/src/pipecat/services/xtts/tts.py +++ b/src/pipecat/services/xtts/tts.py @@ -107,7 +107,7 @@ class XTTSService(TTSService): Args: voice_id: ID of the voice/speaker to use for synthesis. - .. deprecated:: 1.0 + .. deprecated:: 1.0.0 Use ``settings=XTTSTTSSettings(voice=...)`` instead. base_url: Base URL of the XTTS streaming server. From 07f1d0cd966ceafabb875664149eebfa1b7021fe Mon Sep 17 00:00:00 2001 From: Mark Backman Date: Tue, 3 Mar 2026 19:52:09 -0500 Subject: [PATCH 0806/1060] Change `_warn_deprecated_param` to accept type references instead of strings Update all ~192 call sites across 84 service files to pass class references (e.g. `CartesiaTTSSettings`) instead of string names (`"CartesiaTTSSettings"`) to `_warn_deprecated_param()`. This enables better IDE refactoring support. Also fix `from_mapping` return type annotations in 5 settings subclasses to use `typing.Self` instead of forward reference strings. --- src/pipecat/services/anthropic/llm.py | 74 ++--- src/pipecat/services/assemblyai/stt.py | 39 ++- src/pipecat/services/asyncai/tts.py | 76 +++--- src/pipecat/services/aws/llm.py | 52 ++-- src/pipecat/services/aws/nova_sonic/llm.py | 55 ++-- src/pipecat/services/aws/stt.py | 29 +- src/pipecat/services/aws/tts.py | 46 ++-- src/pipecat/services/azure/image.py | 2 +- src/pipecat/services/azure/llm.py | 11 +- src/pipecat/services/azure/stt.py | 15 +- src/pipecat/services/azure/tts.py | 104 ++++--- src/pipecat/services/camb/tts.py | 49 ++-- src/pipecat/services/cartesia/stt.py | 38 +-- src/pipecat/services/cartesia/tts.py | 93 ++++--- src/pipecat/services/cerebras/llm.py | 11 +- src/pipecat/services/deepgram/flux/stt.py | 41 ++- .../services/deepgram/sagemaker/stt.py | 36 ++- .../services/deepgram/sagemaker/tts.py | 2 +- src/pipecat/services/deepgram/stt.py | 28 +- src/pipecat/services/deepgram/tts.py | 32 ++- src/pipecat/services/deepseek/llm.py | 11 +- src/pipecat/services/elevenlabs/stt.py | 82 ++++-- src/pipecat/services/elevenlabs/tts.py | 131 +++++---- src/pipecat/services/fal/image.py | 11 +- src/pipecat/services/fal/stt.py | 31 ++- src/pipecat/services/fireworks/llm.py | 13 +- src/pipecat/services/fish/tts.py | 52 ++-- src/pipecat/services/gladia/stt.py | 91 ++++--- .../services/google/gemini_live/llm.py | 77 ++++-- .../services/google/gemini_live/llm_vertex.py | 77 ++++-- src/pipecat/services/google/image.py | 14 +- src/pipecat/services/google/llm.py | 41 ++- src/pipecat/services/google/llm_openai.py | 11 +- src/pipecat/services/google/llm_vertex.py | 46 ++-- src/pipecat/services/google/stt.py | 50 ++-- src/pipecat/services/google/tts.py | 131 +++++---- src/pipecat/services/gradium/stt.py | 21 +- src/pipecat/services/gradium/tts.py | 27 +- src/pipecat/services/grok/llm.py | 11 +- src/pipecat/services/grok/realtime/llm.py | 17 +- src/pipecat/services/groq/llm.py | 11 +- src/pipecat/services/groq/stt.py | 39 +-- src/pipecat/services/groq/tts.py | 35 ++- src/pipecat/services/hume/tts.py | 31 ++- src/pipecat/services/inworld/tts.py | 117 +++++--- src/pipecat/services/kokoro/tts.py | 37 ++- src/pipecat/services/lmnt/tts.py | 22 +- src/pipecat/services/minimax/tts.py | 132 ++++----- src/pipecat/services/mistral/llm.py | 11 +- src/pipecat/services/moondream/vision.py | 11 +- src/pipecat/services/neuphonic/tts.py | 62 +++-- src/pipecat/services/nvidia/llm.py | 13 +- src/pipecat/services/nvidia/stt.py | 54 ++-- src/pipecat/services/nvidia/tts.py | 30 ++- src/pipecat/services/ollama/llm.py | 11 +- src/pipecat/services/openai/base_llm.py | 41 ++- src/pipecat/services/openai/image.py | 11 +- src/pipecat/services/openai/llm.py | 51 ++-- src/pipecat/services/openai/realtime/llm.py | 23 +- src/pipecat/services/openai/stt.py | 49 ++-- src/pipecat/services/openai/tts.py | 47 ++-- .../services/openai_realtime_beta/openai.py | 24 +- src/pipecat/services/openpipe/llm.py | 11 +- src/pipecat/services/openrouter/llm.py | 11 +- src/pipecat/services/perplexity/llm.py | 11 +- src/pipecat/services/piper/tts.py | 34 ++- src/pipecat/services/qwen/llm.py | 11 +- src/pipecat/services/resembleai/tts.py | 27 +- src/pipecat/services/rime/tts.py | 176 +++++++----- src/pipecat/services/sambanova/llm.py | 11 +- src/pipecat/services/sambanova/stt.py | 39 +-- src/pipecat/services/sarvam/stt.py | 66 +++-- src/pipecat/services/sarvam/tts.py | 255 ++++++++++-------- src/pipecat/services/settings.py | 5 +- src/pipecat/services/soniox/stt.py | 49 ++-- src/pipecat/services/speechmatics/stt.py | 109 +++++--- src/pipecat/services/speechmatics/tts.py | 24 +- src/pipecat/services/together/llm.py | 13 +- src/pipecat/services/ultravox/llm.py | 5 + src/pipecat/services/whisper/base_stt.py | 42 +-- src/pipecat/services/whisper/stt.py | 90 ++++--- src/pipecat/services/xtts/tts.py | 13 +- 82 files changed, 2321 insertions(+), 1321 deletions(-) diff --git a/src/pipecat/services/anthropic/llm.py b/src/pipecat/services/anthropic/llm.py index d2a4c300d..170c7e425 100644 --- a/src/pipecat/services/anthropic/llm.py +++ b/src/pipecat/services/anthropic/llm.py @@ -249,43 +249,57 @@ class AnthropicLLMService(LLMService): system_instruction: Optional system instruction to use as the system prompt. **kwargs: Additional arguments passed to parent LLMService. """ - if model is not None: - _warn_deprecated_param("model", "AnthropicLLMSettings", "model") - if params is not None: - _warn_deprecated_param("params", "AnthropicLLMSettings") - - _params = params or AnthropicLLMService.InputParams() - - # Handle existing enable_prompt_caching_beta deprecation - enable_prompt_caching = _params.enable_prompt_caching - if _params.enable_prompt_caching_beta is not None: - import warnings - - with warnings.catch_warnings(): - warnings.simplefilter("always") - warnings.warn( - "enable_prompt_caching_beta is deprecated. Use enable_prompt_caching instead.", - DeprecationWarning, - stacklevel=2, - ) - if enable_prompt_caching is None: - enable_prompt_caching = _params.enable_prompt_caching_beta - + # 1. Initialize default_settings with hardcoded defaults default_settings = AnthropicLLMSettings( - model=model or "claude-sonnet-4-6", - max_tokens=_params.max_tokens, - enable_prompt_caching=enable_prompt_caching or False, - temperature=_params.temperature, - top_k=_params.top_k, - top_p=_params.top_p, + model="claude-sonnet-4-6", + max_tokens=4096, + enable_prompt_caching=False, + temperature=NOT_GIVEN, + top_k=NOT_GIVEN, + top_p=NOT_GIVEN, frequency_penalty=None, presence_penalty=None, seed=None, filter_incomplete_user_turns=False, user_turn_completion_config=None, - thinking=_params.thinking, - extra=_params.extra if isinstance(_params.extra, dict) else {}, + thinking=NOT_GIVEN, + extra={}, ) + + # 2. Apply direct init arg overrides (deprecated) + if model is not None: + _warn_deprecated_param("model", AnthropicLLMSettings, "model") + default_settings.model = model + + # 3. Apply params overrides — only if settings not provided + if params is not None: + _warn_deprecated_param("params", AnthropicLLMSettings) + if not settings: + default_settings.max_tokens = params.max_tokens + default_settings.temperature = params.temperature + default_settings.top_k = params.top_k + default_settings.top_p = params.top_p + default_settings.thinking = params.thinking + if isinstance(params.extra, dict): + default_settings.extra = params.extra + # Handle enable_prompt_caching / enable_prompt_caching_beta + enable_prompt_caching = params.enable_prompt_caching + if params.enable_prompt_caching_beta is not None: + import warnings + + with warnings.catch_warnings(): + warnings.simplefilter("always") + warnings.warn( + "enable_prompt_caching_beta is deprecated. " + "Use enable_prompt_caching instead.", + DeprecationWarning, + stacklevel=2, + ) + if enable_prompt_caching is None: + enable_prompt_caching = params.enable_prompt_caching_beta + default_settings.enable_prompt_caching = enable_prompt_caching or False + + # 4. Apply settings delta (canonical API, always wins) if settings is not None: default_settings.apply_update(settings) diff --git a/src/pipecat/services/assemblyai/stt.py b/src/pipecat/services/assemblyai/stt.py index 85d4029b7..e140f7543 100644 --- a/src/pipecat/services/assemblyai/stt.py +++ b/src/pipecat/services/assemblyai/stt.py @@ -32,7 +32,7 @@ from pipecat.frames.frames import ( VADUserStoppedSpeakingFrame, ) from pipecat.processors.frame_processor import FrameDirection -from pipecat.services.settings import NOT_GIVEN, STTSettings, _NotGiven +from pipecat.services.settings import NOT_GIVEN, STTSettings, _NotGiven, _warn_deprecated_param from pipecat.services.stt_latency import ASSEMBLYAI_TTFS_P99 from pipecat.services.stt_service import WebsocketSTTService from pipecat.transcriptions.language import Language @@ -108,9 +108,9 @@ class AssemblyAISTTService(WebsocketSTTService): self, *, api_key: str, - language: Language = Language.EN, # AssemblyAI only supports English + language: Optional[Language] = None, api_endpoint_base_url: str = "wss://streaming.assemblyai.com/v3/ws", - connection_params: AssemblyAIConnectionParams = AssemblyAIConnectionParams(), + connection_params: Optional[AssemblyAIConnectionParams] = None, vad_force_turn_endpoint: bool = True, should_interrupt: bool = True, speaker_format: Optional[str] = None, @@ -151,20 +151,23 @@ class AssemblyAISTTService(WebsocketSTTService): Override for your deployment. See https://github.com/pipecat-ai/stt-benchmark **kwargs: Additional arguments passed to parent STTService class. """ + # Resolve connection_params early — needed for validation and turn mode config + _connection_params = connection_params or AssemblyAIConnectionParams() + # AssemblyAI turn detection mode (vad_force_turn_endpoint=False) requires the # SpeechStarted event for reliable barge-in. Only u3-rt-pro supports # this. Other models must use Pipecat turn detection. - is_u3_pro = connection_params.speech_model == "u3-rt-pro" + is_u3_pro = _connection_params.speech_model == "u3-rt-pro" if not vad_force_turn_endpoint and not is_u3_pro: raise ValueError( f"AssemblyAI turn detection mode (vad_force_turn_endpoint=False) requires " f"u3-rt-pro for SpeechStarted support. Either set " - f"vad_force_turn_endpoint=True for {connection_params.speech_model}, " + f"vad_force_turn_endpoint=True for {_connection_params.speech_model}, " f"or use speech_model='u3-rt-pro'." ) # Validate that prompt and keyterms_prompt are not both set - if connection_params.prompt is not None and connection_params.keyterms_prompt is not None: + if _connection_params.prompt is not None and _connection_params.keyterms_prompt is not None: raise ValueError( "The prompt and keyterms_prompt parameters cannot be used in the same request. " "Please choose either one or the other based on your use case. When you use " @@ -174,7 +177,7 @@ class AssemblyAISTTService(WebsocketSTTService): ) # Warn if user sets a custom prompt (recommend testing without one first) - if connection_params.prompt is not None: + if _connection_params.prompt is not None: logger.warning( "Custom prompt detected. Prompting is a beta feature. We recommend testing " "with no prompt first, as this will use our optimized default prompt for " @@ -186,18 +189,32 @@ class AssemblyAISTTService(WebsocketSTTService): # When vad_force_turn_endpoint is enabled, configure connection params # for Pipecat turn detection mode (fast finals for smart turn analyzer) if vad_force_turn_endpoint: - connection_params = self._configure_pipecat_turn_mode(connection_params, is_u3_pro) + _connection_params = self._configure_pipecat_turn_mode(_connection_params, is_u3_pro) + # 1. Initialize default_settings with hardcoded defaults default_settings = AssemblyAISTTSettings( model=None, - language=language, - connection_params=connection_params, + language=Language.EN, + connection_params=AssemblyAIConnectionParams(), ) + + # 2. Apply direct init arg overrides (deprecated) + if language is not None: + _warn_deprecated_param("language", AssemblyAISTTSettings, "language") + default_settings.language = language + + # 3. Apply connection_params overrides — only if settings not provided + if connection_params is not None: + _warn_deprecated_param("connection_params", AssemblyAISTTSettings) + if not settings: + default_settings.connection_params = _connection_params + + # 4. Apply settings delta (canonical API, always wins) if settings is not None: default_settings.apply_update(settings) super().__init__( - sample_rate=connection_params.sample_rate, + sample_rate=_connection_params.sample_rate, ttfs_p99_latency=ttfs_p99_latency, settings=default_settings, **kwargs, diff --git a/src/pipecat/services/asyncai/tts.py b/src/pipecat/services/asyncai/tts.py index b7ddec2e1..ef5c95bfe 100644 --- a/src/pipecat/services/asyncai/tts.py +++ b/src/pipecat/services/asyncai/tts.py @@ -10,7 +10,7 @@ import asyncio import base64 import json from dataclasses import dataclass, field -from typing import Any, AsyncGenerator, Mapping, Optional +from typing import Any, AsyncGenerator, Mapping, Optional, Self import aiohttp from loguru import logger @@ -88,7 +88,7 @@ class AsyncAITTSSettings(TTSSettings): output_sample_rate: int | _NotGiven = field(default_factory=lambda: NOT_GIVEN) @classmethod - def from_mapping(cls, settings: Mapping[str, Any]) -> "AsyncAITTSSettings": + def from_mapping(cls, settings: Mapping[str, Any]) -> Self: """Construct settings from a plain dict, destructuring legacy nested ``output_format``.""" flat = dict(settings) nested = flat.pop("output_format", None) @@ -171,25 +171,33 @@ class AsyncAITTSService(AudioContextTTSService): text_aggregation_mode: How to aggregate text before synthesis. **kwargs: Additional arguments passed to the parent service. """ - if voice_id is not None: - _warn_deprecated_param("voice_id", "AsyncAITTSSettings", "voice") - if model is not None: - _warn_deprecated_param("model", "AsyncAITTSSettings", "model") - if params is not None: - _warn_deprecated_param("params", "AsyncAITTSSettings") - - _params = params or AsyncAITTSService.InputParams() - + # 1. Initialize default_settings with hardcoded defaults default_settings = AsyncAITTSSettings( - model=model or "async_flash_v1.0", - voice=voice_id, + model="async_flash_v1.0", + voice=None, + language=None, output_container=container, output_encoding=encoding, output_sample_rate=0, - language=self.language_to_service_language(_params.language) - if _params.language - else None, ) + + # 2. Apply direct init arg overrides (deprecated) + if voice_id is not None: + _warn_deprecated_param("voice_id", AsyncAITTSSettings, "voice") + default_settings.voice = voice_id + if model is not None: + _warn_deprecated_param("model", AsyncAITTSSettings, "model") + default_settings.model = model + + # 3. Apply params overrides — only if settings not provided + if params is not None: + _warn_deprecated_param("params", AsyncAITTSSettings) + if not settings: + default_settings.language = ( + self.language_to_service_language(params.language) if params.language else None + ) + + # 4. Apply settings delta (canonical API, always wins) if settings is not None: default_settings.apply_update(settings) @@ -554,25 +562,33 @@ class AsyncAIHttpTTSService(TTSService): parameters, ``settings`` values take precedence. **kwargs: Additional arguments passed to the parent TTSService. """ - if voice_id is not None: - _warn_deprecated_param("voice_id", "AsyncAITTSSettings", "voice") - if model is not None: - _warn_deprecated_param("model", "AsyncAITTSSettings", "model") - if params is not None: - _warn_deprecated_param("params", "AsyncAITTSSettings") - - _params = params or AsyncAIHttpTTSService.InputParams() - + # 1. Initialize default_settings with hardcoded defaults default_settings = AsyncAITTSSettings( - model=model or "async_flash_v1.0", - voice=voice_id, + model="async_flash_v1.0", + voice=None, + language=None, output_container=container, output_encoding=encoding, output_sample_rate=0, - language=self.language_to_service_language(_params.language) - if _params.language - else None, ) + + # 2. Apply direct init arg overrides (deprecated) + if voice_id is not None: + _warn_deprecated_param("voice_id", AsyncAITTSSettings, "voice") + default_settings.voice = voice_id + if model is not None: + _warn_deprecated_param("model", AsyncAITTSSettings, "model") + default_settings.model = model + + # 3. Apply params overrides — only if settings not provided + if params is not None: + _warn_deprecated_param("params", AsyncAITTSSettings) + if not settings: + default_settings.language = ( + self.language_to_service_language(params.language) if params.language else None + ) + + # 4. Apply settings delta (canonical API, always wins) if settings is not None: default_settings.apply_update(settings) diff --git a/src/pipecat/services/aws/llm.py b/src/pipecat/services/aws/llm.py index b8a92eccb..d688b6114 100644 --- a/src/pipecat/services/aws/llm.py +++ b/src/pipecat/services/aws/llm.py @@ -816,37 +816,53 @@ class AWSBedrockLLMService(LLMService): system_instruction: Optional system instruction to use as the system prompt. **kwargs: Additional arguments passed to parent LLMService. """ - if model is not None: - _warn_deprecated_param("model", "AWSBedrockLLMSettings", "model") - if params is not None: - _warn_deprecated_param("params", "AWSBedrockLLMSettings") - - _params = params or AWSBedrockLLMService.InputParams() - + # 1. Initialize default_settings with hardcoded defaults default_settings = AWSBedrockLLMSettings( - model=model or "us.amazon.nova-lite-v1:0", - max_tokens=_params.max_tokens, - temperature=_params.temperature, - top_p=_params.top_p, + model="us.amazon.nova-lite-v1:0", + max_tokens=None, + temperature=None, + top_p=None, top_k=None, frequency_penalty=None, presence_penalty=None, seed=None, filter_incomplete_user_turns=False, user_turn_completion_config=None, - latency=_params.latency, - additional_model_request_fields=_params.additional_model_request_fields - if isinstance(_params.additional_model_request_fields, dict) - else {}, + latency=None, + additional_model_request_fields={}, ) + + # 2. Apply direct init arg overrides (deprecated) + if model is not None: + _warn_deprecated_param("model", AWSBedrockLLMSettings, "model") + default_settings.model = model + + # 3. Apply params overrides — only if settings not provided + if params is not None: + _warn_deprecated_param("params", AWSBedrockLLMSettings) + if not settings: + default_settings.max_tokens = params.max_tokens + default_settings.temperature = params.temperature + default_settings.top_p = params.top_p + default_settings.latency = params.latency + if isinstance(params.additional_model_request_fields, dict): + default_settings.additional_model_request_fields = ( + params.additional_model_request_fields + ) + + # 4. Apply settings delta (canonical API, always wins) if settings is not None: default_settings.apply_update(settings) super().__init__(settings=default_settings, **kwargs) - self._stop_sequences = ( - stop_sequences if stop_sequences is not None else (_params.stop_sequences or []) - ) + # Handle stop_sequences (not a settings field) + if stop_sequences is not None: + self._stop_sequences = stop_sequences + elif params is not None: + self._stop_sequences = params.stop_sequences or [] + else: + self._stop_sequences = [] # Initialize the AWS Bedrock client if not client_config: diff --git a/src/pipecat/services/aws/nova_sonic/llm.py b/src/pipecat/services/aws/nova_sonic/llm.py index 887c3f46c..7fec1c73c 100644 --- a/src/pipecat/services/aws/nova_sonic/llm.py +++ b/src/pipecat/services/aws/nova_sonic/llm.py @@ -270,30 +270,40 @@ class AWSNovaSonicLLMService(LLMService): **kwargs: Additional arguments passed to the parent LLMService. """ - # Check for deprecated parameter usage - if model != "amazon.nova-2-sonic-v1:0": - _warn_deprecated_param("model", "AWSNovaSonicLLMSettings", "model") - if voice_id != "matthew": - _warn_deprecated_param("voice_id", "AWSNovaSonicLLMSettings", "voice_id") - if params is not None: - _warn_deprecated_param("params", "AWSNovaSonicLLMSettings") - - _params = params or Params() - + # 1. Initialize default_settings with hardcoded defaults default_settings = AWSNovaSonicLLMSettings( - model=model, - voice_id=voice_id, - temperature=_params.temperature, - max_tokens=_params.max_tokens, - top_p=_params.top_p, + model="amazon.nova-2-sonic-v1:0", + voice_id="matthew", + temperature=0.7, + max_tokens=1024, + top_p=0.9, top_k=None, frequency_penalty=None, presence_penalty=None, seed=None, filter_incomplete_user_turns=False, user_turn_completion_config=None, - endpointing_sensitivity=_params.endpointing_sensitivity, + endpointing_sensitivity=None, ) + + # 2. Apply direct init arg overrides (deprecated) + if model != "amazon.nova-2-sonic-v1:0": + _warn_deprecated_param("model", AWSNovaSonicLLMSettings, "model") + default_settings.model = model + if voice_id != "matthew": + _warn_deprecated_param("voice_id", AWSNovaSonicLLMSettings, "voice_id") + default_settings.voice_id = voice_id + + # 3. Apply params overrides — only if settings not provided + if params is not None: + _warn_deprecated_param("params", AWSNovaSonicLLMSettings) + if not settings: + default_settings.temperature = params.temperature + default_settings.max_tokens = params.max_tokens + default_settings.top_p = params.top_p + default_settings.endpointing_sensitivity = params.endpointing_sensitivity + + # 4. Apply settings delta (canonical API, always wins) if settings is not None: default_settings.apply_update(settings) @@ -308,12 +318,13 @@ class AWSNovaSonicLLMService(LLMService): self._client: Optional[BedrockRuntimeClient] = None # Audio I/O config (hardware settings, not runtime-tunable) - self._input_sample_rate = _params.input_sample_rate - self._input_sample_size = _params.input_sample_size - self._input_channel_count = _params.input_channel_count - self._output_sample_rate = _params.output_sample_rate - self._output_sample_size = _params.output_sample_size - self._output_channel_count = _params.output_channel_count + _audio_params = params or Params() + self._input_sample_rate = _audio_params.input_sample_rate + self._input_sample_size = _audio_params.input_sample_size + self._input_channel_count = _audio_params.input_channel_count + self._output_sample_rate = _audio_params.output_sample_rate + self._output_sample_size = _audio_params.output_sample_size + self._output_channel_count = _audio_params.output_channel_count self._system_instruction = system_instruction self._tools = tools diff --git a/src/pipecat/services/aws/stt.py b/src/pipecat/services/aws/stt.py index 061b17889..950624fbf 100644 --- a/src/pipecat/services/aws/stt.py +++ b/src/pipecat/services/aws/stt.py @@ -110,22 +110,27 @@ class AWSTranscribeSTTService(WebsocketSTTService): Override for your deployment. See https://github.com/pipecat-ai/stt-benchmark **kwargs: Additional arguments passed to parent STTService class. """ - if sample_rate is not None: - _warn_deprecated_param("sample_rate", "AWSTranscribeSTTSettings", "sample_rate") - if language is not None: - _warn_deprecated_param("language", "AWSTranscribeSTTSettings", "language") - - _sample_rate = sample_rate or 16000 - _language = language or Language.EN - + # 1. Initialize default_settings with hardcoded defaults default_settings = AWSTranscribeSTTSettings( - language=self.language_to_service_language(_language) or "en-US", - sample_rate=_sample_rate, + language=self.language_to_service_language(Language.EN) or "en-US", + sample_rate=16000, media_encoding="linear16", number_of_channels=1, show_speaker_label=False, enable_channel_identification=False, ) + + # 2. Apply direct init arg overrides (deprecated) + if sample_rate is not None: + _warn_deprecated_param("sample_rate", AWSTranscribeSTTSettings, "sample_rate") + default_settings.sample_rate = sample_rate + if language is not None: + _warn_deprecated_param("language", AWSTranscribeSTTSettings, "language") + default_settings.language = self.language_to_service_language(language) or "en-US" + + # 3. No params to apply + + # 4. Apply settings delta (canonical API, always wins) if settings is not None: default_settings.apply_update(settings) @@ -136,9 +141,9 @@ class AWSTranscribeSTTService(WebsocketSTTService): ) # Validate sample rate - AWS Transcribe only supports 8000 Hz or 16000 Hz - if _sample_rate not in [8000, 16000]: + if default_settings.sample_rate not in [8000, 16000]: logger.warning( - f"AWS Transcribe only supports 8000 Hz or 16000 Hz sample rates. Converting from {_sample_rate} Hz to 16000 Hz." + f"AWS Transcribe only supports 8000 Hz or 16000 Hz sample rates. Converting from {default_settings.sample_rate} Hz to 16000 Hz." ) self._settings.sample_rate = 16000 diff --git a/src/pipecat/services/aws/tts.py b/src/pipecat/services/aws/tts.py index 83ef4125c..f248db27a 100644 --- a/src/pipecat/services/aws/tts.py +++ b/src/pipecat/services/aws/tts.py @@ -209,25 +209,39 @@ class AWSPollyTTSService(TTSService): parameters, ``settings`` values take precedence. **kwargs: Additional arguments passed to parent TTSService class. """ - if voice_id is not None: - _warn_deprecated_param("voice_id", "AWSPollyTTSSettings", "voice") - if params is not None: - _warn_deprecated_param("params", "AWSPollyTTSSettings") - - _params = params or AWSPollyTTSService.InputParams() - + # 1. Initialize default_settings with hardcoded defaults default_settings = AWSPollyTTSSettings( model=None, - voice=voice_id or "Joanna", - engine=_params.engine, - language=self.language_to_service_language(_params.language) - if _params.language - else "en-US", - pitch=_params.pitch, - rate=_params.rate, - volume=_params.volume, - lexicon_names=_params.lexicon_names, + voice="Joanna", + language="en-US", + engine=None, + pitch=None, + rate=None, + volume=None, + lexicon_names=None, ) + + # 2. Apply direct init arg overrides (deprecated) + if voice_id is not None: + _warn_deprecated_param("voice_id", AWSPollyTTSSettings, "voice") + default_settings.voice = voice_id + + # 3. Apply params overrides — only if settings not provided + if params is not None: + _warn_deprecated_param("params", AWSPollyTTSSettings) + if not settings: + default_settings.engine = params.engine + default_settings.language = ( + self.language_to_service_language(params.language) + if params.language + else "en-US" + ) + default_settings.pitch = params.pitch + default_settings.rate = params.rate + default_settings.volume = params.volume + default_settings.lexicon_names = params.lexicon_names + + # 4. Apply settings delta (canonical API, always wins) if settings is not None: default_settings.apply_update(settings) diff --git a/src/pipecat/services/azure/image.py b/src/pipecat/services/azure/image.py index 9f5d48c33..ca58644f2 100644 --- a/src/pipecat/services/azure/image.py +++ b/src/pipecat/services/azure/image.py @@ -68,7 +68,7 @@ class AzureImageGenServiceREST(ImageGenService): parameters, ``settings`` values take precedence. """ if model is not None: - _warn_deprecated_param("model", "AzureImageGenSettings", "model") + _warn_deprecated_param("model", AzureImageGenSettings, "model") default_settings = AzureImageGenSettings(model=model) if settings is not None: diff --git a/src/pipecat/services/azure/llm.py b/src/pipecat/services/azure/llm.py index 3c28e190e..734a0bacf 100644 --- a/src/pipecat/services/azure/llm.py +++ b/src/pipecat/services/azure/llm.py @@ -48,10 +48,15 @@ class AzureLLMService(OpenAILLMService): parameters, ``settings`` values take precedence. **kwargs: Additional keyword arguments passed to OpenAILLMService. """ - if model is not None: - _warn_deprecated_param("model", "OpenAILLMSettings", "model") + # 1. Initialize default_settings with hardcoded defaults + default_settings = OpenAILLMSettings(model="gpt-4o") - default_settings = OpenAILLMSettings(model=model or "gpt-4o") + # 2. Apply direct init arg overrides (deprecated) + if model is not None: + _warn_deprecated_param("model", OpenAILLMSettings, "model") + default_settings.model = model + + # 4. Apply settings delta (canonical API, always wins) if settings is not None: default_settings.apply_update(settings) diff --git a/src/pipecat/services/azure/stt.py b/src/pipecat/services/azure/stt.py index 02a7ca8ed..66f871ad3 100644 --- a/src/pipecat/services/azure/stt.py +++ b/src/pipecat/services/azure/stt.py @@ -107,15 +107,22 @@ class AzureSTTService(STTService): Override for your deployment. See https://github.com/pipecat-ai/stt-benchmark **kwargs: Additional arguments passed to parent STTService. """ - if language != Language.EN_US: - _warn_deprecated_param("language", "AzureSTTSettings", "language") - + # 1. Initialize default_settings with hardcoded defaults default_settings = AzureSTTSettings( model=None, region=region, - language=language_to_azure_language(language) if language else None, + language=language_to_azure_language(Language.EN_US), sample_rate=sample_rate, ) + + # 2. Apply direct init arg overrides (deprecated) + if language is not None and language != Language.EN_US: + _warn_deprecated_param("language", AzureSTTSettings, "language") + default_settings.language = language_to_azure_language(language) + + # 3. No params to apply + + # 4. Apply settings delta (canonical API, always wins) if settings is not None: default_settings.apply_update(settings) diff --git a/src/pipecat/services/azure/tts.py b/src/pipecat/services/azure/tts.py index 7e5791f03..3a67cb2ff 100644 --- a/src/pipecat/services/azure/tts.py +++ b/src/pipecat/services/azure/tts.py @@ -290,27 +290,43 @@ class AzureTTSService(TTSService, AzureBaseTTSService): text_aggregation_mode: How to aggregate text before synthesis. **kwargs: Additional arguments passed to parent WordTTSService. """ - if voice is not None: - _warn_deprecated_param("voice", "AzureTTSSettings", "voice") - if params is not None: - _warn_deprecated_param("params", "AzureTTSSettings") - - _params = params or AzureBaseTTSService.InputParams() - + # 1. Initialize default_settings with hardcoded defaults default_settings = AzureTTSSettings( model=None, - emphasis=_params.emphasis, - language=self.language_to_service_language(_params.language) - if _params.language - else "en-US", - pitch=_params.pitch, - rate=_params.rate, - role=_params.role, - style=_params.style, - style_degree=_params.style_degree, - voice=voice or "en-US-SaraNeural", - volume=_params.volume, + voice="en-US-SaraNeural", + language="en-US", + emphasis=None, + pitch=None, + rate=None, + role=None, + style=None, + style_degree=None, + volume=None, ) + + # 2. Apply direct init arg overrides (deprecated) + if voice is not None: + _warn_deprecated_param("voice", AzureTTSSettings, "voice") + default_settings.voice = voice + + # 3. Apply params overrides — only if settings not provided + if params is not None: + _warn_deprecated_param("params", AzureTTSSettings) + if not settings: + default_settings.emphasis = params.emphasis + default_settings.language = ( + self.language_to_service_language(params.language) + if params.language + else "en-US" + ) + default_settings.pitch = params.pitch + default_settings.rate = params.rate + default_settings.role = params.role + default_settings.style = params.style + default_settings.style_degree = params.style_degree + default_settings.volume = params.volume + + # 4. Apply settings delta (canonical API, always wins) if settings is not None: default_settings.apply_update(settings) @@ -779,27 +795,43 @@ class AzureHttpTTSService(TTSService, AzureBaseTTSService): parameters, ``settings`` values take precedence. **kwargs: Additional arguments passed to parent TTSService. """ - if voice is not None: - _warn_deprecated_param("voice", "AzureTTSSettings", "voice") - if params is not None: - _warn_deprecated_param("params", "AzureTTSSettings") - - _params = params or AzureBaseTTSService.InputParams() - + # 1. Initialize default_settings with hardcoded defaults default_settings = AzureTTSSettings( model=None, - emphasis=_params.emphasis, - language=self.language_to_service_language(_params.language) - if _params.language - else "en-US", - pitch=_params.pitch, - rate=_params.rate, - role=_params.role, - style=_params.style, - style_degree=_params.style_degree, - voice=voice or "en-US-SaraNeural", - volume=_params.volume, + voice="en-US-SaraNeural", + language="en-US", + emphasis=None, + pitch=None, + rate=None, + role=None, + style=None, + style_degree=None, + volume=None, ) + + # 2. Apply direct init arg overrides (deprecated) + if voice is not None: + _warn_deprecated_param("voice", AzureTTSSettings, "voice") + default_settings.voice = voice + + # 3. Apply params overrides — only if settings not provided + if params is not None: + _warn_deprecated_param("params", AzureTTSSettings) + if not settings: + default_settings.emphasis = params.emphasis + default_settings.language = ( + self.language_to_service_language(params.language) + if params.language + else "en-US" + ) + default_settings.pitch = params.pitch + default_settings.rate = params.rate + default_settings.role = params.role + default_settings.style = params.style + default_settings.style_degree = params.style_degree + default_settings.volume = params.volume + + # 4. Apply settings delta (canonical API, always wins) if settings is not None: default_settings.apply_update(settings) diff --git a/src/pipecat/services/camb/tts.py b/src/pipecat/services/camb/tts.py index de8b16ab8..9a1b753a6 100644 --- a/src/pipecat/services/camb/tts.py +++ b/src/pipecat/services/camb/tts.py @@ -230,34 +230,45 @@ class CambTTSService(TTSService): parameters, ``settings`` values take precedence. **kwargs: Additional arguments passed to parent TTSService. """ - if voice_id is not None: - _warn_deprecated_param("voice_id", "CambTTSSettings", "voice") - if model is not None: - _warn_deprecated_param("model", "CambTTSSettings", "model") - if params is not None: - _warn_deprecated_param("params", "CambTTSSettings") + # 1. Initialize default_settings with hardcoded defaults + default_settings = CambTTSSettings( + model="mars-flash", + voice=147320, + language="en-us", + user_instructions=None, + ) - _params = params or CambTTSService.InputParams() - _model = model or "mars-flash" + # 2. Apply direct init arg overrides (deprecated) + if model is not None: + _warn_deprecated_param("model", CambTTSSettings, "model") + default_settings.model = model + if voice_id is not None: + _warn_deprecated_param("voice_id", CambTTSSettings, "voice") + default_settings.voice = voice_id + + # 3. Apply params overrides — only if settings not provided + if params is not None: + _warn_deprecated_param("params", CambTTSSettings) + if not settings: + if params.language is not None: + default_settings.language = ( + self.language_to_service_language(params.language) or "en-us" + ) + if params.user_instructions is not None: + default_settings.user_instructions = params.user_instructions + + # 4. Apply settings delta (canonical API, always wins) + if settings is not None: + default_settings.apply_update(settings) # Warn if sample rate doesn't match model's supported rate + _model = default_settings.model if sample_rate and sample_rate != MODEL_SAMPLE_RATES.get(_model): logger.warning( f"Camb.ai's {_model} model only supports {MODEL_SAMPLE_RATES.get(_model)}Hz " f"sample rate. Current rate of {sample_rate}Hz may cause issues." ) - default_settings = CambTTSSettings( - model=_model, - voice=voice_id or 147320, - language=( - self.language_to_service_language(_params.language) if _params.language else "en-us" - ), - user_instructions=_params.user_instructions, - ) - if settings is not None: - default_settings.apply_update(settings) - super().__init__( sample_rate=sample_rate, settings=default_settings, diff --git a/src/pipecat/services/cartesia/stt.py b/src/pipecat/services/cartesia/stt.py index 530f6a4d1..aa66b102e 100644 --- a/src/pipecat/services/cartesia/stt.py +++ b/src/pipecat/services/cartesia/stt.py @@ -28,7 +28,7 @@ from pipecat.frames.frames import ( VADUserStoppedSpeakingFrame, ) from pipecat.processors.frame_processor import FrameDirection -from pipecat.services.settings import NOT_GIVEN, STTSettings, _NotGiven +from pipecat.services.settings import NOT_GIVEN, STTSettings, _NotGiven, _warn_deprecated_param from pipecat.services.stt_latency import CARTESIA_TTFS_P99 from pipecat.services.stt_service import WebsocketSTTService from pipecat.transcriptions.language import Language @@ -177,26 +177,34 @@ class CartesiaSTTService(WebsocketSTTService): """ sample_rate = sample_rate or (live_options.sample_rate if live_options else None) - default_options = CartesiaLiveOptions( + # 1. Initialize default_settings with hardcoded defaults + default_settings = CartesiaSTTSettings( model="ink-whisper", language=Language.EN.value, encoding="pcm_s16le", - sample_rate=sample_rate, ) - merged_options = default_options.to_dict() - if live_options: - merged_options.update(live_options.to_dict()) - # Filter out "None" string values - merged_options = { - k: v for k, v in merged_options.items() if not isinstance(v, str) or v != "None" - } + # 2. (no deprecated direct args for this service) - default_settings = CartesiaSTTSettings( - model=merged_options["model"], - language=merged_options.get("language"), - encoding=merged_options.get("encoding", "pcm_s16le"), - ) + # 3. Apply live_options overrides — only if settings not provided + if live_options is not None: + _warn_deprecated_param("live_options", CartesiaSTTSettings) + if not settings: + lo_dict = live_options.to_dict() + # Filter out "None" string values + lo_dict = { + k: v + for k, v in lo_dict.items() + if (not isinstance(v, str) or v != "None") and k != "sample_rate" + } + if "model" in lo_dict: + default_settings.model = lo_dict["model"] + if "language" in lo_dict: + default_settings.language = lo_dict["language"] + if "encoding" in lo_dict: + default_settings.encoding = lo_dict["encoding"] + + # 4. Apply settings delta (canonical API, always wins) if settings is not None: default_settings.apply_update(settings) diff --git a/src/pipecat/services/cartesia/tts.py b/src/pipecat/services/cartesia/tts.py index c2227d00b..2aeeefda2 100644 --- a/src/pipecat/services/cartesia/tts.py +++ b/src/pipecat/services/cartesia/tts.py @@ -11,7 +11,7 @@ import json import warnings from dataclasses import dataclass, field from enum import Enum -from typing import Any, AsyncGenerator, List, Literal, Mapping, Optional +from typing import Any, AsyncGenerator, List, Literal, Mapping, Optional, Self import aiohttp from loguru import logger @@ -212,7 +212,7 @@ class CartesiaTTSSettings(TTSSettings): pronunciation_dict_id: str | _NotGiven = field(default_factory=lambda: NOT_GIVEN) @classmethod - def from_mapping(cls, settings: Mapping[str, Any]) -> "CartesiaTTSSettings": + def from_mapping(cls, settings: Mapping[str, Any]) -> Self: """Construct settings from a plain dict, destructuring legacy nested ``output_format``.""" flat = dict(settings) nested = flat.pop("output_format", None) @@ -312,13 +312,6 @@ class CartesiaTTSService(AudioContextTTSService): **kwargs: Additional arguments passed to the parent service. """ - if voice_id is not None: - _warn_deprecated_param("voice_id", "CartesiaTTSSettings", "voice") - if model is not None: - _warn_deprecated_param("model", "CartesiaTTSSettings", "model") - if params is not None: - _warn_deprecated_param("params", "CartesiaTTSSettings") - # By default, we aggregate sentences before sending to TTS. This adds # ~200-300ms of latency per sentence (waiting for the sentence-ending # punctuation token from the LLM). Setting @@ -332,22 +325,39 @@ class CartesiaTTSService(AudioContextTTSService): # if we're interrupted. Cartesia gives us word-by-word timestamps. We # can use those to generate text frames ourselves aligned with the # playout timing of the audio! - _params = params or CartesiaTTSService.InputParams() + # 1. Initialize default_settings with hardcoded defaults default_settings = CartesiaTTSSettings( - model=model or "sonic-3", - voice=voice_id, + model="sonic-3", output_container=container, output_encoding=encoding, output_sample_rate=0, - language=( - self.language_to_service_language(_params.language) if _params.language else None - ), - speed=_params.speed, - emotion=_params.emotion, - generation_config=_params.generation_config, - pronunciation_dict_id=_params.pronunciation_dict_id, ) + + # 2. Apply direct init arg overrides (deprecated) + if voice_id is not None: + _warn_deprecated_param("voice_id", CartesiaTTSSettings, "voice") + default_settings.voice = voice_id + if model is not None: + _warn_deprecated_param("model", CartesiaTTSSettings, "model") + default_settings.model = model + + # 3. Apply params overrides — only if settings not provided + if params is not None: + _warn_deprecated_param("params", CartesiaTTSSettings) + if not settings: + if params.language is not None: + default_settings.language = self.language_to_service_language(params.language) + if params.speed is not None: + default_settings.speed = params.speed + if params.emotion is not None: + default_settings.emotion = params.emotion + if params.generation_config is not None: + default_settings.generation_config = params.generation_config + if params.pronunciation_dict_id is not None: + default_settings.pronunciation_dict_id = params.pronunciation_dict_id + + # 4. Apply settings delta (canonical API, always wins) if settings is not None: default_settings.apply_update(settings) @@ -781,29 +791,38 @@ class CartesiaHttpTTSService(TTSService): parameters, ``settings`` values take precedence. **kwargs: Additional arguments passed to the parent TTSService. """ - if voice_id is not None: - _warn_deprecated_param("voice_id", "CartesiaTTSSettings", "voice") - if model is not None: - _warn_deprecated_param("model", "CartesiaTTSSettings", "model") - if params is not None: - _warn_deprecated_param("params", "CartesiaTTSSettings") - - _params = params or CartesiaHttpTTSService.InputParams() - + # 1. Initialize default_settings with hardcoded defaults default_settings = CartesiaTTSSettings( - model=model or "sonic-3", - voice=voice_id, + model="sonic-3", output_container=container, output_encoding=encoding, output_sample_rate=0, - language=( - self.language_to_service_language(_params.language) if _params.language else None - ), - speed=_params.speed, - emotion=_params.emotion, - generation_config=_params.generation_config, - pronunciation_dict_id=_params.pronunciation_dict_id, ) + + # 2. Apply direct init arg overrides (deprecated) + if voice_id is not None: + _warn_deprecated_param("voice_id", CartesiaTTSSettings, "voice") + default_settings.voice = voice_id + if model is not None: + _warn_deprecated_param("model", CartesiaTTSSettings, "model") + default_settings.model = model + + # 3. Apply params overrides — only if settings not provided + if params is not None: + _warn_deprecated_param("params", CartesiaTTSSettings) + if not settings: + if params.language is not None: + default_settings.language = self.language_to_service_language(params.language) + if params.speed is not None: + default_settings.speed = params.speed + if params.emotion is not None: + default_settings.emotion = params.emotion + if params.generation_config is not None: + default_settings.generation_config = params.generation_config + if params.pronunciation_dict_id is not None: + default_settings.pronunciation_dict_id = params.pronunciation_dict_id + + # 4. Apply settings delta (canonical API, always wins) if settings is not None: default_settings.apply_update(settings) diff --git a/src/pipecat/services/cerebras/llm.py b/src/pipecat/services/cerebras/llm.py index 053594083..98fbfe0e3 100644 --- a/src/pipecat/services/cerebras/llm.py +++ b/src/pipecat/services/cerebras/llm.py @@ -46,10 +46,15 @@ class CerebrasLLMService(OpenAILLMService): parameters, ``settings`` values take precedence. **kwargs: Additional keyword arguments passed to OpenAILLMService. """ - if model is not None: - _warn_deprecated_param("model", "OpenAILLMSettings", "model") + # 1. Initialize default_settings with hardcoded defaults + default_settings = OpenAILLMSettings(model="gpt-oss-120b") - default_settings = OpenAILLMSettings(model=model or "gpt-oss-120b") + # 2. Apply direct init arg overrides (deprecated) + if model is not None: + _warn_deprecated_param("model", OpenAILLMSettings, "model") + default_settings.model = model + + # 4. Apply settings delta (canonical API, always wins) if settings is not None: default_settings.apply_update(settings) diff --git a/src/pipecat/services/deepgram/flux/stt.py b/src/pipecat/services/deepgram/flux/stt.py index 04c2f1da3..8ddd2ef0d 100644 --- a/src/pipecat/services/deepgram/flux/stt.py +++ b/src/pipecat/services/deepgram/flux/stt.py @@ -206,10 +206,6 @@ class DeepgramFluxSTTService(WebsocketSTTService): ), ) """ - if model is not None: - _warn_deprecated_param("model", "DeepgramFluxSTTSettings", "model") - if params is not None: - _warn_deprecated_param("params", "DeepgramFluxSTTSettings") # Note: For DeepgramFluxSTTService, differently from other processes, we need to create # the _receive_task inside _connect_websocket, because the websocket should only be # considered connected and ready to send audio once we receive from Flux the message @@ -220,20 +216,39 @@ class DeepgramFluxSTTService(WebsocketSTTService): # was never destroyed. # So we can keep it here as false, because inside the method send_with_retry, it will # already try to reconnect if needed. - _params = params or DeepgramFluxSTTService.InputParams() + # 1. Initialize default_settings with hardcoded defaults default_settings = DeepgramFluxSTTSettings( - model=model or "flux-general-en", + model="flux-general-en", language=Language.EN, encoding=flux_encoding, - eager_eot_threshold=_params.eager_eot_threshold, - eot_threshold=_params.eot_threshold, - eot_timeout_ms=_params.eot_timeout_ms, - keyterm=_params.keyterm or [], - mip_opt_out=_params.mip_opt_out, - tag=_params.tag or [], - min_confidence=_params.min_confidence, + eager_eot_threshold=None, + eot_threshold=None, + eot_timeout_ms=None, + keyterm=[], + mip_opt_out=None, + tag=[], + min_confidence=None, ) + + # 2. Apply direct init arg overrides (deprecated) + if model is not None: + _warn_deprecated_param("model", DeepgramFluxSTTSettings, "model") + default_settings.model = model + + # 3. Apply params overrides — only if settings not provided + if params is not None: + _warn_deprecated_param("params", DeepgramFluxSTTSettings) + if not settings: + default_settings.eager_eot_threshold = params.eager_eot_threshold + default_settings.eot_threshold = params.eot_threshold + default_settings.eot_timeout_ms = params.eot_timeout_ms + default_settings.keyterm = params.keyterm or [] + default_settings.mip_opt_out = params.mip_opt_out + default_settings.tag = params.tag or [] + default_settings.min_confidence = params.min_confidence + + # 4. Apply settings delta (canonical API, always wins) if settings is not None: default_settings.apply_update(settings) diff --git a/src/pipecat/services/deepgram/sagemaker/stt.py b/src/pipecat/services/deepgram/sagemaker/stt.py index 6d813157d..d7a867e38 100644 --- a/src/pipecat/services/deepgram/sagemaker/stt.py +++ b/src/pipecat/services/deepgram/sagemaker/stt.py @@ -14,7 +14,7 @@ languages, and various Deepgram features. import asyncio import json -from dataclasses import dataclass +from dataclasses import dataclass, field from typing import Any, AsyncGenerator, Optional from loguru import logger @@ -32,8 +32,7 @@ from pipecat.frames.frames import ( ) from pipecat.processors.frame_processor import FrameDirection from pipecat.services.aws.sagemaker.bidi_client import SageMakerBidiClient -from pipecat.services.deepgram.stt import DeepgramSTTSettings -from pipecat.services.settings import STTSettings +from pipecat.services.settings import NOT_GIVEN, STTSettings, _NotGiven, _warn_deprecated_param from pipecat.services.stt_latency import DEEPGRAM_SAGEMAKER_TTFS_P99 from pipecat.services.stt_service import STTService from pipecat.transcriptions.language import Language @@ -51,13 +50,14 @@ except ModuleNotFoundError as e: @dataclass -class DeepgramSageMakerSTTSettings(_DeepgramSTTSettingsBase): +class DeepgramSageMakerSTTSettings(STTSettings): """Settings for the Deepgram SageMaker STT service. - See ``_DeepgramSTTSettingsBase`` for full documentation. + Parameters: + live_options: Deepgram LiveOptions for the SageMaker connection. """ - pass + live_options: Any | _NotGiven = field(default_factory=lambda: NOT_GIVEN) class DeepgramSageMakerSTTService(STTService): @@ -130,13 +130,29 @@ class DeepgramSageMakerSTTService(STTService): punctuate=True, ) + # 1. Initialize default_settings with hardcoded defaults default_settings = DeepgramSageMakerSTTSettings( - model=default_options.model, - language=default_options.language, + model="nova-3", + language=Language.EN, live_options=default_options, ) - if live_options: - default_settings._merge_live_options_delta(live_options) + + # 2. (no deprecated direct args like model= for this service) + + # 3. Apply live_options overrides — only if settings not provided + if live_options is not None: + _warn_deprecated_param("live_options", DeepgramSageMakerSTTSettings) + if not settings: + # Merge user live_options onto defaults + merged_dict = {**default_options.to_dict(), **live_options.to_dict()} + merged_live_options = LiveOptions(**merged_dict) + default_settings.live_options = merged_live_options + if hasattr(live_options, "model") and live_options.model is not None: + default_settings.model = live_options.model + if hasattr(live_options, "language") and live_options.language is not None: + default_settings.language = live_options.language + + # 4. Apply settings delta (canonical API, always wins) if settings is not None: default_settings.apply_update(settings) diff --git a/src/pipecat/services/deepgram/sagemaker/tts.py b/src/pipecat/services/deepgram/sagemaker/tts.py index 8d03f6eac..62cd25188 100644 --- a/src/pipecat/services/deepgram/sagemaker/tts.py +++ b/src/pipecat/services/deepgram/sagemaker/tts.py @@ -102,7 +102,7 @@ class DeepgramSageMakerTTSService(TTSService): **kwargs: Additional arguments passed to the parent TTSService. """ if voice is not None: - _warn_deprecated_param("voice", "DeepgramSageMakerTTSSettings", "voice") + _warn_deprecated_param("voice", DeepgramSageMakerTTSSettings, "voice") voice = voice or "aura-2-helena-en" diff --git a/src/pipecat/services/deepgram/stt.py b/src/pipecat/services/deepgram/stt.py index fe3add7cf..f311567aa 100644 --- a/src/pipecat/services/deepgram/stt.py +++ b/src/pipecat/services/deepgram/stt.py @@ -25,7 +25,14 @@ from pipecat.frames.frames import ( VADUserStoppedSpeakingFrame, ) from pipecat.processors.frame_processor import FrameDirection -from pipecat.services.settings import _S, NOT_GIVEN, STTSettings, _NotGiven, is_given +from pipecat.services.settings import ( + _S, + NOT_GIVEN, + STTSettings, + _NotGiven, + _warn_deprecated_param, + is_given, +) from pipecat.services.stt_latency import DEEPGRAM_TTFS_P99 from pipecat.services.stt_service import STTService from pipecat.transcriptions.language import Language @@ -303,6 +310,7 @@ class DeepgramSTTService(STTService): ) base_url = url + # 1. Initialize default_settings with hardcoded defaults default_settings = DeepgramSTTSettings( model="nova-3-general", language=Language.EN, @@ -317,13 +325,19 @@ class DeepgramSTTService(STTService): endpointing=None, ) - if live_options: - lo_dict = live_options.to_dict() - delta = DeepgramSTTSettings.from_mapping( - {k: v for k, v in lo_dict.items() if k != "sample_rate"} - ) - default_settings.apply_update(delta) + # 2. (no deprecated direct args like model= for this service) + # 3. Apply live_options overrides — only if settings not provided + if live_options is not None: + _warn_deprecated_param("live_options", DeepgramSTTSettings) + if not settings: + lo_dict = live_options.to_dict() + delta = DeepgramSTTSettings.from_mapping( + {k: v for k, v in lo_dict.items() if k != "sample_rate"} + ) + default_settings.apply_update(delta) + + # 4. Apply settings delta (canonical API, always wins) if settings is not None: default_settings.apply_update(settings) diff --git a/src/pipecat/services/deepgram/tts.py b/src/pipecat/services/deepgram/tts.py index 7c391490d..98a615f9b 100644 --- a/src/pipecat/services/deepgram/tts.py +++ b/src/pipecat/services/deepgram/tts.py @@ -98,20 +98,26 @@ class DeepgramTTSService(WebsocketTTSService): Raises: ValueError: If encoding is not in SUPPORTED_ENCODINGS. """ - if voice is not None: - _warn_deprecated_param("voice", "DeepgramTTSSettings", "voice") - if encoding.lower() not in self.SUPPORTED_ENCODINGS: raise ValueError( f"Unsupported encoding '{encoding}'. Must be one of {', '.join(self.SUPPORTED_ENCODINGS)} for WebSocket TTS." ) + # 1. Initialize default_settings with hardcoded defaults default_settings = DeepgramTTSSettings( - model=voice or "aura-2-helena-en", - voice=voice or "aura-2-helena-en", + model="aura-2-helena-en", + voice="aura-2-helena-en", language=None, encoding=encoding, ) + + # 2. Apply direct init arg overrides (deprecated) + if voice is not None: + _warn_deprecated_param("voice", DeepgramTTSSettings, "voice") + default_settings.model = voice + default_settings.voice = voice + + # 4. Apply settings delta (canonical API, always wins) if settings is not None: default_settings.apply_update(settings) @@ -414,15 +420,21 @@ class DeepgramHttpTTSService(TTSService): parameters, ``settings`` values take precedence. **kwargs: Additional arguments passed to parent TTSService class. """ - if voice is not None: - _warn_deprecated_param("voice", "DeepgramTTSSettings", "voice") - + # 1. Initialize default_settings with hardcoded defaults default_settings = DeepgramTTSSettings( - model=voice or "aura-2-helena-en", - voice=voice or "aura-2-helena-en", + model="aura-2-helena-en", + voice="aura-2-helena-en", language=None, encoding=encoding, ) + + # 2. Apply direct init arg overrides (deprecated) + if voice is not None: + _warn_deprecated_param("voice", DeepgramTTSSettings, "voice") + default_settings.model = voice + default_settings.voice = voice + + # 4. Apply settings delta (canonical API, always wins) if settings is not None: default_settings.apply_update(settings) diff --git a/src/pipecat/services/deepseek/llm.py b/src/pipecat/services/deepseek/llm.py index 8cc9ac56e..c383f5609 100644 --- a/src/pipecat/services/deepseek/llm.py +++ b/src/pipecat/services/deepseek/llm.py @@ -46,10 +46,15 @@ class DeepSeekLLMService(OpenAILLMService): parameters, ``settings`` values take precedence. **kwargs: Additional keyword arguments passed to OpenAILLMService. """ - if model is not None: - _warn_deprecated_param("model", "OpenAILLMSettings", "model") + # 1. Initialize default_settings with hardcoded defaults + default_settings = OpenAILLMSettings(model="deepseek-chat") - default_settings = OpenAILLMSettings(model=model or "deepseek-chat") + # 2. Apply direct init arg overrides (deprecated) + if model is not None: + _warn_deprecated_param("model", OpenAILLMSettings, "model") + default_settings.model = model + + # 4. Apply settings delta (canonical API, always wins) if settings is not None: default_settings.apply_update(settings) diff --git a/src/pipecat/services/elevenlabs/stt.py b/src/pipecat/services/elevenlabs/stt.py index 1eebcffde..d93f95332 100644 --- a/src/pipecat/services/elevenlabs/stt.py +++ b/src/pipecat/services/elevenlabs/stt.py @@ -275,20 +275,29 @@ class ElevenLabsSTTService(SegmentedSTTService): Override for your deployment. See https://github.com/pipecat-ai/stt-benchmark **kwargs: Additional arguments passed to SegmentedSTTService. """ - if model is not None: - _warn_deprecated_param("model", "ElevenLabsSTTSettings", "model") - if params is not None: - _warn_deprecated_param("params", "ElevenLabsSTTSettings") - - _params = params or ElevenLabsSTTService.InputParams() - + # 1. Initialize default_settings with hardcoded defaults default_settings = ElevenLabsSTTSettings( - model=model or "scribe_v2", - language=self.language_to_service_language(_params.language) - if _params.language - else "eng", - tag_audio_events=_params.tag_audio_events, + model="scribe_v2", + language="eng", + tag_audio_events=True, ) + + # 2. Apply direct init arg overrides (deprecated) + if model is not None: + _warn_deprecated_param("model", ElevenLabsSTTSettings, "model") + default_settings.model = model + + # 3. Apply params overrides — only if settings not provided + if params is not None: + _warn_deprecated_param("params", ElevenLabsSTTSettings) + if not settings: + if params.language is not None: + default_settings.language = ( + self.language_to_service_language(params.language) or "eng" + ) + default_settings.tag_audio_events = params.tag_audio_events + + # 4. Apply settings delta (canonical API, always wins) if settings is not None: default_settings.apply_update(settings) @@ -515,25 +524,40 @@ class ElevenLabsRealtimeSTTService(WebsocketSTTService): Override for your deployment. See https://github.com/pipecat-ai/stt-benchmark **kwargs: Additional arguments passed to WebsocketSTTService. """ - if model is not None: - _warn_deprecated_param("model", "ElevenLabsRealtimeSTTSettings", "model") - if params is not None: - _warn_deprecated_param("params", "ElevenLabsRealtimeSTTSettings") - - _params = params or ElevenLabsRealtimeSTTService.InputParams() - + # 1. Initialize default_settings with hardcoded defaults default_settings = ElevenLabsRealtimeSTTSettings( - model=model or "scribe_v2_realtime", - language=_params.language_code, - commit_strategy=_params.commit_strategy, - vad_silence_threshold_secs=_params.vad_silence_threshold_secs, - vad_threshold=_params.vad_threshold, - min_speech_duration_ms=_params.min_speech_duration_ms, - min_silence_duration_ms=_params.min_silence_duration_ms, - include_timestamps=_params.include_timestamps, - enable_logging=_params.enable_logging, - include_language_detection=_params.include_language_detection, + model="scribe_v2_realtime", + language=None, + commit_strategy=CommitStrategy.MANUAL, + vad_silence_threshold_secs=None, + vad_threshold=None, + min_speech_duration_ms=None, + min_silence_duration_ms=None, + include_timestamps=False, + enable_logging=False, + include_language_detection=False, ) + + # 2. Apply direct init arg overrides (deprecated) + if model is not None: + _warn_deprecated_param("model", ElevenLabsRealtimeSTTSettings, "model") + default_settings.model = model + + # 3. Apply params overrides — only if settings not provided + if params is not None: + _warn_deprecated_param("params", ElevenLabsRealtimeSTTSettings) + if not settings: + default_settings.language = params.language_code + default_settings.commit_strategy = params.commit_strategy + default_settings.vad_silence_threshold_secs = params.vad_silence_threshold_secs + default_settings.vad_threshold = params.vad_threshold + default_settings.min_speech_duration_ms = params.min_speech_duration_ms + default_settings.min_silence_duration_ms = params.min_silence_duration_ms + default_settings.include_timestamps = params.include_timestamps + default_settings.enable_logging = params.enable_logging + default_settings.include_language_detection = params.include_language_detection + + # 4. Apply settings delta (canonical API, always wins) if settings is not None: default_settings.apply_update(settings) diff --git a/src/pipecat/services/elevenlabs/tts.py b/src/pipecat/services/elevenlabs/tts.py index 15c2dbb2e..3cec12431 100644 --- a/src/pipecat/services/elevenlabs/tts.py +++ b/src/pipecat/services/elevenlabs/tts.py @@ -408,13 +408,6 @@ class ElevenLabsTTSService(AudioContextTTSService): **kwargs: Additional arguments passed to the parent service. """ - if voice_id is not None: - _warn_deprecated_param("voice_id", "ElevenLabsTTSSettings", "voice") - if model is not None: - _warn_deprecated_param("model", "ElevenLabsTTSSettings", "model") - if params is not None: - _warn_deprecated_param("params", "ElevenLabsTTSSettings") - # By default, we aggregate sentences before sending to TTS. This adds # ~200-300ms of latency per sentence (waiting for the sentence-ending # punctuation token from the LLM). Setting @@ -431,24 +424,49 @@ class ElevenLabsTTSService(AudioContextTTSService): # Finally, ElevenLabs doesn't provide information on when the bot stops # speaking for a while, so we want the parent class to send TTSStopFrame # after a short period not receiving any audio. - _params = params or ElevenLabsTTSService.InputParams() + # 1. Initialize default_settings with hardcoded defaults default_settings = ElevenLabsTTSSettings( - model=model or "eleven_turbo_v2_5", - voice=voice_id, - language=( - self.language_to_service_language(_params.language) if _params.language else None - ), - stability=_params.stability, - similarity_boost=_params.similarity_boost, - style=_params.style, - use_speaker_boost=_params.use_speaker_boost, - speed=_params.speed, - auto_mode=str(_params.auto_mode).lower(), - enable_ssml_parsing=_params.enable_ssml_parsing, - enable_logging=_params.enable_logging, - apply_text_normalization=_params.apply_text_normalization, + model="eleven_turbo_v2_5", ) + + # 2. Apply direct init arg overrides (deprecated) + if voice_id is not None: + _warn_deprecated_param("voice_id", ElevenLabsTTSSettings, "voice") + default_settings.voice = voice_id + if model is not None: + _warn_deprecated_param("model", ElevenLabsTTSSettings, "model") + default_settings.model = model + + # 3. Apply params overrides — only if settings not provided + _pronunciation_dictionary_locators = pronunciation_dictionary_locators + if params is not None: + _warn_deprecated_param("params", ElevenLabsTTSSettings) + if not settings: + if params.language is not None: + default_settings.language = self.language_to_service_language(params.language) + if params.stability is not None: + default_settings.stability = params.stability + if params.similarity_boost is not None: + default_settings.similarity_boost = params.similarity_boost + if params.style is not None: + default_settings.style = params.style + if params.use_speaker_boost is not None: + default_settings.use_speaker_boost = params.use_speaker_boost + if params.speed is not None: + default_settings.speed = params.speed + if params.auto_mode is not None: + default_settings.auto_mode = str(params.auto_mode).lower() + if params.enable_ssml_parsing is not None: + default_settings.enable_ssml_parsing = params.enable_ssml_parsing + if params.enable_logging is not None: + default_settings.enable_logging = params.enable_logging + if params.apply_text_normalization is not None: + default_settings.apply_text_normalization = params.apply_text_normalization + if _pronunciation_dictionary_locators is None: + _pronunciation_dictionary_locators = params.pronunciation_dictionary_locators + + # 4. Apply settings delta (canonical API, always wins) if settings is not None: default_settings.apply_update(settings) @@ -469,11 +487,7 @@ class ElevenLabsTTSService(AudioContextTTSService): self._output_format = "" # initialized in start() self._voice_settings = self._set_voice_settings() - self._pronunciation_dictionary_locators = ( - pronunciation_dictionary_locators - if pronunciation_dictionary_locators is not None - else _params.pronunciation_dictionary_locators - ) + self._pronunciation_dictionary_locators = _pronunciation_dictionary_locators self._cumulative_time = 0 # Track partial words that span across alignment chunks @@ -982,29 +996,44 @@ class ElevenLabsHttpTTSService(TTSService): **kwargs: Additional arguments passed to the parent service. """ - if voice_id is not None: - _warn_deprecated_param("voice_id", "ElevenLabsHttpTTSSettings", "voice") - if model is not None: - _warn_deprecated_param("model", "ElevenLabsHttpTTSSettings", "model") - if params is not None: - _warn_deprecated_param("params", "ElevenLabsHttpTTSSettings") - - _params = params or ElevenLabsHttpTTSService.InputParams() - + # 1. Initialize default_settings with hardcoded defaults default_settings = ElevenLabsHttpTTSSettings( - model=model or "eleven_turbo_v2_5", - voice=voice_id, - language=( - self.language_to_service_language(_params.language) if _params.language else None - ), - optimize_streaming_latency=_params.optimize_streaming_latency, - stability=_params.stability, - similarity_boost=_params.similarity_boost, - style=_params.style, - use_speaker_boost=_params.use_speaker_boost, - speed=_params.speed, - apply_text_normalization=_params.apply_text_normalization, + model="eleven_turbo_v2_5", ) + + # 2. Apply direct init arg overrides (deprecated) + if voice_id is not None: + _warn_deprecated_param("voice_id", ElevenLabsHttpTTSSettings, "voice") + default_settings.voice = voice_id + if model is not None: + _warn_deprecated_param("model", ElevenLabsHttpTTSSettings, "model") + default_settings.model = model + + # 3. Apply params overrides — only if settings not provided + _pronunciation_dictionary_locators = pronunciation_dictionary_locators + if params is not None: + _warn_deprecated_param("params", ElevenLabsHttpTTSSettings) + if not settings: + if params.language is not None: + default_settings.language = self.language_to_service_language(params.language) + if params.optimize_streaming_latency is not None: + default_settings.optimize_streaming_latency = params.optimize_streaming_latency + if params.stability is not None: + default_settings.stability = params.stability + if params.similarity_boost is not None: + default_settings.similarity_boost = params.similarity_boost + if params.style is not None: + default_settings.style = params.style + if params.use_speaker_boost is not None: + default_settings.use_speaker_boost = params.use_speaker_boost + if params.speed is not None: + default_settings.speed = params.speed + if params.apply_text_normalization is not None: + default_settings.apply_text_normalization = params.apply_text_normalization + if _pronunciation_dictionary_locators is None: + _pronunciation_dictionary_locators = params.pronunciation_dictionary_locators + + # 4. Apply settings delta (canonical API, always wins) if settings is not None: default_settings.apply_update(settings) @@ -1025,11 +1054,7 @@ class ElevenLabsHttpTTSService(TTSService): self._output_format = "" # initialized in start() self._voice_settings = self._set_voice_settings() - self._pronunciation_dictionary_locators = ( - pronunciation_dictionary_locators - if pronunciation_dictionary_locators is not None - else _params.pronunciation_dictionary_locators - ) + self._pronunciation_dictionary_locators = _pronunciation_dictionary_locators # Track cumulative time to properly sequence word timestamps across utterances self._cumulative_time = 0 diff --git a/src/pipecat/services/fal/image.py b/src/pipecat/services/fal/image.py index 6fd953f13..2c36c2208 100644 --- a/src/pipecat/services/fal/image.py +++ b/src/pipecat/services/fal/image.py @@ -88,10 +88,15 @@ class FalImageGenService(ImageGenService): parameters, ``settings`` values take precedence. **kwargs: Additional arguments passed to parent ImageGenService. """ - if model is not None: - _warn_deprecated_param("model", "FalImageGenSettings", "model") + # 1. Initialize default_settings with hardcoded defaults + default_settings = FalImageGenSettings(model="fal-ai/fast-sdxl") - default_settings = FalImageGenSettings(model=model or "fal-ai/fast-sdxl") + # 2. Apply direct init arg overrides (deprecated) + if model is not None: + _warn_deprecated_param("model", FalImageGenSettings, "model") + default_settings.model = model + + # 4. Apply settings delta (canonical API, always wins) if settings is not None: default_settings.apply_update(settings) diff --git a/src/pipecat/services/fal/stt.py b/src/pipecat/services/fal/stt.py index d80f73a98..ea9f69a18 100644 --- a/src/pipecat/services/fal/stt.py +++ b/src/pipecat/services/fal/stt.py @@ -213,20 +213,29 @@ class FalSTTService(SegmentedSTTService): Override for your deployment. See https://github.com/pipecat-ai/stt-benchmark **kwargs: Additional arguments passed to SegmentedSTTService. """ - if params is not None: - _warn_deprecated_param("params", "FalSTTSettings") - - _params = params or FalSTTService.InputParams() - + # 1. Initialize default_settings with hardcoded defaults default_settings = FalSTTSettings( model=None, - language=self.language_to_service_language(_params.language) - if _params.language - else "en", - task=_params.task, - chunk_level=_params.chunk_level, - version=_params.version, + language=language_to_fal_language(Language.EN) or "en", + task="transcribe", + chunk_level="segment", + version="3", ) + + # 2. (no deprecated direct args for this service) + + # 3. Apply params overrides — only if settings not provided + if params is not None: + _warn_deprecated_param("params", FalSTTSettings) + if not settings: + default_settings.language = ( + language_to_fal_language(params.language) if params.language else "en" + ) + default_settings.task = params.task + default_settings.chunk_level = params.chunk_level + default_settings.version = params.version + + # 4. Apply settings delta (canonical API, always wins) if settings is not None: default_settings.apply_update(settings) diff --git a/src/pipecat/services/fireworks/llm.py b/src/pipecat/services/fireworks/llm.py index 33d7d22e2..cb5a0cf39 100644 --- a/src/pipecat/services/fireworks/llm.py +++ b/src/pipecat/services/fireworks/llm.py @@ -46,12 +46,15 @@ class FireworksLLMService(OpenAILLMService): parameters, ``settings`` values take precedence. **kwargs: Additional keyword arguments passed to OpenAILLMService. """ - if model is not None: - _warn_deprecated_param("model", "OpenAILLMSettings", "model") + # 1. Initialize default_settings with hardcoded defaults + default_settings = OpenAILLMSettings(model="accounts/fireworks/models/firefunction-v2") - default_settings = OpenAILLMSettings( - model=model or "accounts/fireworks/models/firefunction-v2" - ) + # 2. Apply direct init arg overrides (deprecated) + if model is not None: + _warn_deprecated_param("model", OpenAILLMSettings, "model") + default_settings.model = model + + # 4. Apply settings delta (canonical API, always wins) if settings is not None: default_settings.apply_update(settings) diff --git a/src/pipecat/services/fish/tts.py b/src/pipecat/services/fish/tts.py index 431b51729..3d4412186 100644 --- a/src/pipecat/services/fish/tts.py +++ b/src/pipecat/services/fish/tts.py @@ -12,7 +12,7 @@ for streaming text-to-speech synthesis with customizable voice parameters. import uuid from dataclasses import dataclass, field -from typing import Any, AsyncGenerator, ClassVar, Dict, Literal, Mapping, Optional +from typing import Any, AsyncGenerator, ClassVar, Dict, Literal, Mapping, Optional, Self from loguru import logger from pydantic import BaseModel @@ -72,7 +72,7 @@ class FishAudioTTSSettings(TTSSettings): _aliases: ClassVar[Dict[str, str]] = {"voice_id": "voice", "sample_rate": "fish_sample_rate"} @classmethod - def from_mapping(cls, settings: Mapping[str, Any]) -> "FishAudioTTSSettings": + def from_mapping(cls, settings: Mapping[str, Any]) -> Self: """Construct settings from a plain dict, destructuring legacy nested ``prosody``.""" flat = dict(settings) nested = flat.pop("prosody", None) @@ -156,15 +156,6 @@ class FishAudioTTSService(InterruptibleTTSService): parameters, ``settings`` values take precedence. **kwargs: Additional arguments passed to the parent service. """ - if reference_id is not None: - _warn_deprecated_param("reference_id", "FishAudioTTSSettings", "voice") - if model_id is not None: - _warn_deprecated_param("model_id", "FishAudioTTSSettings", "model") - if params is not None: - _warn_deprecated_param("params", "FishAudioTTSSettings") - - _params = params or FishAudioTTSService.InputParams() - # Validation for model and reference_id parameters if model and reference_id: raise ValueError( @@ -184,17 +175,42 @@ class FishAudioTTSService(InterruptibleTTSService): ) reference_id = model + # 1. Initialize default_settings with hardcoded defaults default_settings = FishAudioTTSSettings( - model=model_id or "s1", - voice=reference_id, + model="s1", + voice=None, fish_sample_rate=0, - latency=_params.latency, + latency="normal", format=output_format, - normalize=_params.normalize, - prosody_speed=_params.prosody_speed, - prosody_volume=_params.prosody_volume, - reference_id=reference_id, + normalize=True, + prosody_speed=1.0, + prosody_volume=0, + reference_id=None, ) + + # 2. Apply direct init arg overrides (deprecated) + if reference_id is not None: + _warn_deprecated_param("reference_id", FishAudioTTSSettings, "voice") + default_settings.voice = reference_id + default_settings.reference_id = reference_id + if model_id is not None: + _warn_deprecated_param("model_id", FishAudioTTSSettings, "model") + default_settings.model = model_id + + # 3. Apply params overrides — only if settings not provided + if params is not None: + _warn_deprecated_param("params", FishAudioTTSSettings) + if not settings: + if params.latency is not None: + default_settings.latency = params.latency + if params.normalize is not None: + default_settings.normalize = params.normalize + if params.prosody_speed is not None: + default_settings.prosody_speed = params.prosody_speed + if params.prosody_volume is not None: + default_settings.prosody_volume = params.prosody_volume + + # 4. Apply settings delta (canonical API, always wins) if settings is not None: default_settings.apply_update(settings) diff --git a/src/pipecat/services/gladia/stt.py b/src/pipecat/services/gladia/stt.py index e1e0d9276..a12829b0d 100644 --- a/src/pipecat/services/gladia/stt.py +++ b/src/pipecat/services/gladia/stt.py @@ -289,23 +289,6 @@ class GladiaSTTService(WebsocketSTTService): Override for your deployment. See https://github.com/pipecat-ai/stt-benchmark **kwargs: Additional arguments passed to the STTService parent class. """ - if model is not None: - _warn_deprecated_param("model", "GladiaSTTSettings", "model") - if params is not None: - _warn_deprecated_param("params", "GladiaSTTSettings") - - params = params or GladiaInputParams() - - if params.language is not None: - with warnings.catch_warnings(): - warnings.simplefilter("always") - warnings.warn( - "The 'language' parameter is deprecated and will be removed in a future version. " - "Use 'language_config' instead.", - DeprecationWarning, - stacklevel=2, - ) - if confidence: with warnings.catch_warnings(): warnings.simplefilter("always") @@ -316,28 +299,64 @@ class GladiaSTTService(WebsocketSTTService): stacklevel=2, ) - # Resolve deprecated language → language_config at init time - language_config = params.language_config - if not language_config and params.language: - language_code = self.language_to_service_language(params.language) - if language_code: - language_config = LanguageConfig(languages=[language_code], code_switching=False) - + # 1. Initialize default_settings with hardcoded defaults default_settings = GladiaSTTSettings( - model=model or "solaria-1", + model="solaria-1", language=None, - encoding=params.encoding, - bit_depth=params.bit_depth, - channels=params.channels, - custom_metadata=params.custom_metadata, - endpointing=params.endpointing, - maximum_duration_without_endpointing=params.maximum_duration_without_endpointing, - language_config=language_config, - pre_processing=params.pre_processing, - realtime_processing=params.realtime_processing, - messages_config=params.messages_config, - enable_vad=params.enable_vad, + encoding="wav/pcm", + bit_depth=16, + channels=1, + custom_metadata=None, + endpointing=None, + maximum_duration_without_endpointing=5, + language_config=None, + pre_processing=None, + realtime_processing=None, + messages_config=None, + enable_vad=False, ) + + # 2. Apply direct init arg overrides (deprecated) + if model is not None: + _warn_deprecated_param("model", GladiaSTTSettings, "model") + default_settings.model = model + + # 3. Apply params overrides — only if settings not provided + if params is not None: + _warn_deprecated_param("params", GladiaSTTSettings) + if params.language is not None: + with warnings.catch_warnings(): + warnings.simplefilter("always") + warnings.warn( + "The 'language' parameter is deprecated and will be removed in a future " + "version. Use 'language_config' instead.", + DeprecationWarning, + stacklevel=2, + ) + if not settings: + default_settings.encoding = params.encoding + default_settings.bit_depth = params.bit_depth + default_settings.channels = params.channels + default_settings.custom_metadata = params.custom_metadata + default_settings.endpointing = params.endpointing + default_settings.maximum_duration_without_endpointing = ( + params.maximum_duration_without_endpointing + ) + default_settings.pre_processing = params.pre_processing + default_settings.realtime_processing = params.realtime_processing + default_settings.messages_config = params.messages_config + default_settings.enable_vad = params.enable_vad + # Resolve deprecated language → language_config at init time + language_config = params.language_config + if not language_config and params.language: + language_code = self.language_to_service_language(params.language) + if language_code: + language_config = LanguageConfig( + languages=[language_code], code_switching=False + ) + default_settings.language_config = language_config + + # 4. Apply settings delta (canonical API, always wins) if settings is not None: default_settings.apply_update(settings) diff --git a/src/pipecat/services/google/gemini_live/llm.py b/src/pipecat/services/google/gemini_live/llm.py index 518684dfb..6e7a8f8a1 100644 --- a/src/pipecat/services/google/gemini_live/llm.py +++ b/src/pipecat/services/google/gemini_live/llm.py @@ -708,36 +708,63 @@ class GeminiLiveLLMService(LLMService): DeprecationWarning, stacklevel=2, ) - if model is not None: - _warn_deprecated_param("model", "GeminiLiveLLMSettings", "model") - if params is not None: - _warn_deprecated_param("params", "GeminiLiveLLMSettings") - - _params = params or InputParams() + # 1. Initialize default_settings with hardcoded defaults default_settings = GeminiLiveLLMSettings( - model=model or "models/gemini-2.5-flash-native-audio-preview-12-2025", - frequency_penalty=_params.frequency_penalty, - max_tokens=_params.max_tokens, - presence_penalty=_params.presence_penalty, - temperature=_params.temperature, - top_k=_params.top_k, - top_p=_params.top_p, + model="models/gemini-2.5-flash-native-audio-preview-12-2025", + frequency_penalty=None, + max_tokens=4096, + presence_penalty=None, + temperature=None, + top_k=None, + top_p=None, seed=None, filter_incomplete_user_turns=False, user_turn_completion_config=None, - modalities=_params.modalities, - language=language_to_gemini_language(_params.language) if _params.language else "en-US", - media_resolution=_params.media_resolution, - vad=_params.vad, - context_window_compression=_params.context_window_compression.model_dump() - if _params.context_window_compression - else {}, - thinking=_params.thinking or {}, - enable_affective_dialog=_params.enable_affective_dialog or False, - proactivity=_params.proactivity or {}, - extra=_params.extra if isinstance(_params.extra, dict) else {}, + modalities=GeminiModalities.AUDIO, + language="en-US", + media_resolution=GeminiMediaResolution.UNSPECIFIED, + vad=None, + context_window_compression={}, + thinking={}, + enable_affective_dialog=False, + proactivity={}, + extra={}, ) + + # 2. Apply direct init arg overrides (deprecated) + if model is not None: + _warn_deprecated_param("model", GeminiLiveLLMSettings, "model") + default_settings.model = model + + # 3. Apply params overrides — only if settings not provided + if params is not None: + _warn_deprecated_param("params", GeminiLiveLLMSettings) + if not settings: + default_settings.frequency_penalty = params.frequency_penalty + default_settings.max_tokens = params.max_tokens + default_settings.presence_penalty = params.presence_penalty + default_settings.temperature = params.temperature + default_settings.top_k = params.top_k + default_settings.top_p = params.top_p + default_settings.modalities = params.modalities + default_settings.language = ( + language_to_gemini_language(params.language) if params.language else "en-US" + ) + default_settings.media_resolution = params.media_resolution + default_settings.vad = params.vad + default_settings.context_window_compression = ( + params.context_window_compression.model_dump() + if params.context_window_compression + else {} + ) + default_settings.thinking = params.thinking or {} + default_settings.enable_affective_dialog = params.enable_affective_dialog or False + default_settings.proactivity = params.proactivity or {} + if isinstance(params.extra, dict): + default_settings.extra = params.extra + + # 4. Apply settings delta (canonical API, always wins) if settings is not None: default_settings.apply_update(settings) @@ -750,7 +777,7 @@ class GeminiLiveLLMService(LLMService): self._last_sent_time = 0 self._base_url = base_url self._voice_id = voice_id - self._language_code = _params.language + self._language_code = params.language if params is not None else Language.EN_US self._system_instruction_from_init = system_instruction self._tools_from_init = tools diff --git a/src/pipecat/services/google/gemini_live/llm_vertex.py b/src/pipecat/services/google/gemini_live/llm_vertex.py index eadcb66d1..5d63251d9 100644 --- a/src/pipecat/services/google/gemini_live/llm_vertex.py +++ b/src/pipecat/services/google/gemini_live/llm_vertex.py @@ -20,6 +20,8 @@ from pipecat.adapters.schemas.tools_schema import ToolsSchema from pipecat.services.google.gemini_live.llm import ( GeminiLiveLLMService, GeminiLiveLLMSettings, + GeminiMediaResolution, + GeminiModalities, HttpOptions, InputParams, language_to_gemini_language, @@ -109,11 +111,6 @@ class GeminiLiveVertexLLMService(GeminiLiveLLMService): "Invalid parameter 'api_key'. Use 'credentials' or 'credentials_path' for Vertex AI authentication." ) - if model is not None: - _warn_deprecated_param("model", "GeminiLiveLLMSettings", "model") - if params is not None: - _warn_deprecated_param("params", "GeminiLiveLLMSettings") - # These need to be set before calling super().__init__() because # super().__init__() invokes create_client(), which needs these. self._credentials = self._get_credentials(credentials, credentials_path) @@ -123,31 +120,63 @@ class GeminiLiveVertexLLMService(GeminiLiveLLMService): # Build default_settings from deprecated args, then apply settings delta. # We pass settings= to super() instead of model=/params= to avoid # double deprecation warnings from the parent. - _params = params or InputParams() + # 1. Initialize default_settings with hardcoded defaults default_settings = GeminiLiveLLMSettings( - model=model or "google/gemini-live-2.5-flash-native-audio", - frequency_penalty=_params.frequency_penalty, - max_tokens=_params.max_tokens, - presence_penalty=_params.presence_penalty, - temperature=_params.temperature, - top_k=_params.top_k, - top_p=_params.top_p, + model="google/gemini-live-2.5-flash-native-audio", + frequency_penalty=None, + max_tokens=4096, + presence_penalty=None, + temperature=None, + top_k=None, + top_p=None, seed=None, filter_incomplete_user_turns=False, user_turn_completion_config=None, - modalities=_params.modalities, - language=language_to_gemini_language(_params.language) if _params.language else "en-US", - media_resolution=_params.media_resolution, - vad=_params.vad, - context_window_compression=_params.context_window_compression.model_dump() - if _params.context_window_compression - else {}, - thinking=_params.thinking or {}, - enable_affective_dialog=_params.enable_affective_dialog or False, - proactivity=_params.proactivity or {}, - extra=_params.extra if isinstance(_params.extra, dict) else {}, + modalities=GeminiModalities.AUDIO, + language="en-US", + media_resolution=GeminiMediaResolution.UNSPECIFIED, + vad=None, + context_window_compression={}, + thinking={}, + enable_affective_dialog=False, + proactivity={}, + extra={}, ) + + # 2. Apply direct init arg overrides (deprecated) + if model is not None: + _warn_deprecated_param("model", GeminiLiveLLMSettings, "model") + default_settings.model = model + + # 3. Apply params overrides — only if settings not provided + if params is not None: + _warn_deprecated_param("params", GeminiLiveLLMSettings) + if not settings: + default_settings.frequency_penalty = params.frequency_penalty + default_settings.max_tokens = params.max_tokens + default_settings.presence_penalty = params.presence_penalty + default_settings.temperature = params.temperature + default_settings.top_k = params.top_k + default_settings.top_p = params.top_p + default_settings.modalities = params.modalities + default_settings.language = ( + language_to_gemini_language(params.language) if params.language else "en-US" + ) + default_settings.media_resolution = params.media_resolution + default_settings.vad = params.vad + default_settings.context_window_compression = ( + params.context_window_compression.model_dump() + if params.context_window_compression + else {} + ) + default_settings.thinking = params.thinking or {} + default_settings.enable_affective_dialog = params.enable_affective_dialog or False + default_settings.proactivity = params.proactivity or {} + if isinstance(params.extra, dict): + default_settings.extra = params.extra + + # 4. Apply settings delta (canonical API, always wins) if settings is not None: default_settings.apply_update(settings) diff --git a/src/pipecat/services/google/image.py b/src/pipecat/services/google/image.py index ce29c0276..09ec61554 100644 --- a/src/pipecat/services/google/image.py +++ b/src/pipecat/services/google/image.py @@ -90,17 +90,21 @@ class GoogleImageGenService(ImageGenService): parameters, ``settings`` values take precedence. **kwargs: Additional arguments passed to the parent ImageGenService. """ + # 1. Initialize default_settings with hardcoded defaults + default_settings = GoogleImageGenSettings(model="imagen-3.0-generate-002") + + # 3. Apply params overrides — only if settings not provided if params is not None: - _warn_deprecated_param("params", "GoogleImageGenSettings") + _warn_deprecated_param("params", GoogleImageGenSettings) + if not settings: + default_settings.model = params.model - params = params or GoogleImageGenService.InputParams() - - default_settings = GoogleImageGenSettings(model=params.model) + # 4. Apply settings delta (canonical API, always wins) if settings is not None: default_settings.apply_update(settings) super().__init__(settings=default_settings, **kwargs) - self._params = params + self._params = params or GoogleImageGenService.InputParams() # Add client header http_options = update_google_client_http_options(http_options) diff --git a/src/pipecat/services/google/llm.py b/src/pipecat/services/google/llm.py index 5d5a87188..49e6d2366 100644 --- a/src/pipecat/services/google/llm.py +++ b/src/pipecat/services/google/llm.py @@ -814,27 +814,40 @@ class GoogleLLMService(LLMService): http_options: HTTP options for the client. **kwargs: Additional arguments passed to parent class. """ - if model is not None: - _warn_deprecated_param("model", "GoogleLLMSettings", "model") - if params is not None: - _warn_deprecated_param("params", "GoogleLLMSettings") - - _params = params or GoogleLLMService.InputParams() - + # 1. Initialize default_settings with hardcoded defaults default_settings = GoogleLLMSettings( - model=model or "gemini-2.5-flash", - max_tokens=_params.max_tokens, - temperature=_params.temperature, - top_k=_params.top_k, - top_p=_params.top_p, + model="gemini-2.5-flash", + max_tokens=4096, + temperature=None, + top_k=None, + top_p=None, frequency_penalty=None, presence_penalty=None, seed=None, filter_incomplete_user_turns=False, user_turn_completion_config=None, - thinking=_params.thinking, - extra=_params.extra if isinstance(_params.extra, dict) else {}, + thinking=None, + extra={}, ) + + # 2. Apply direct init arg overrides (deprecated) + if model is not None: + _warn_deprecated_param("model", GoogleLLMSettings, "model") + default_settings.model = model + + # 3. Apply params overrides — only if settings not provided + if params is not None: + _warn_deprecated_param("params", GoogleLLMSettings) + if not settings: + default_settings.max_tokens = params.max_tokens + default_settings.temperature = params.temperature + default_settings.top_k = params.top_k + default_settings.top_p = params.top_p + default_settings.thinking = params.thinking + if isinstance(params.extra, dict): + default_settings.extra = params.extra + + # 4. Apply settings delta (canonical API, always wins) if settings is not None: default_settings.apply_update(settings) diff --git a/src/pipecat/services/google/llm_openai.py b/src/pipecat/services/google/llm_openai.py index aa8794469..4705e8f68 100644 --- a/src/pipecat/services/google/llm_openai.py +++ b/src/pipecat/services/google/llm_openai.py @@ -84,10 +84,15 @@ class GoogleLLMOpenAIBetaService(OpenAILLMService): stacklevel=2, ) - if model is not None: - _warn_deprecated_param("model", "OpenAILLMSettings", "model") + # 1. Initialize default_settings with hardcoded defaults + default_settings = OpenAILLMSettings(model="gemini-2.0-flash") - default_settings = OpenAILLMSettings(model=model or "gemini-2.0-flash") + # 2. Apply direct init arg overrides (deprecated) + if model is not None: + _warn_deprecated_param("model", OpenAILLMSettings, "model") + default_settings.model = model + + # 4. Apply settings delta (canonical API, always wins) if settings is not None: default_settings.apply_update(settings) diff --git a/src/pipecat/services/google/llm_vertex.py b/src/pipecat/services/google/llm_vertex.py index 9258a4d67..b1a9de584 100644 --- a/src/pipecat/services/google/llm_vertex.py +++ b/src/pipecat/services/google/llm_vertex.py @@ -148,15 +148,9 @@ class GoogleVertexLLMService(GoogleLLMService): "Invalid parameter 'api_key'. Use 'credentials' or 'credentials_path' for Vertex AI authentication." ) - if model is not None: - _warn_deprecated_param("model", "GoogleLLMSettings", "model") - if params is not None: - _warn_deprecated_param("params", "GoogleLLMSettings") - - # Handle deprecated InputParams fields + # Handle deprecated InputParams fields (location/project_id extraction + # must happen before validation, regardless of settings) if params and isinstance(params, GoogleVertexLLMService.InputParams): - # Extract location and project_id from params if not provided - # directly, for backward compatibility if project_id is None: project_id = params.project_id if location is None: @@ -188,22 +182,40 @@ class GoogleVertexLLMService(GoogleLLMService): self._project_id = project_id self._location = location - # Build default_settings from deprecated args - _params = params or GoogleLLMService.InputParams() + # 1. Initialize default_settings with hardcoded defaults default_settings = GoogleLLMSettings( - model=model or "gemini-2.5-flash", - max_tokens=_params.max_tokens, - temperature=_params.temperature, - top_k=_params.top_k, - top_p=_params.top_p, + model="gemini-2.5-flash", + max_tokens=4096, + temperature=None, + top_k=None, + top_p=None, frequency_penalty=None, presence_penalty=None, seed=None, filter_incomplete_user_turns=False, user_turn_completion_config=None, - thinking=_params.thinking, - extra=_params.extra if isinstance(_params.extra, dict) else {}, + thinking=None, + extra={}, ) + + # 2. Apply direct init arg overrides (deprecated) + if model is not None: + _warn_deprecated_param("model", GoogleLLMSettings, "model") + default_settings.model = model + + # 3. Apply params overrides — only if settings not provided + if params is not None: + _warn_deprecated_param("params", GoogleLLMSettings) + if not settings: + default_settings.max_tokens = params.max_tokens + default_settings.temperature = params.temperature + default_settings.top_k = params.top_k + default_settings.top_p = params.top_p + default_settings.thinking = params.thinking + if isinstance(params.extra, dict): + default_settings.extra = params.extra + + # 4. Apply settings delta (canonical API, always wins) if settings is not None: default_settings.apply_update(settings) diff --git a/src/pipecat/services/google/stt.py b/src/pipecat/services/google/stt.py index 23a586b96..5415a5403 100644 --- a/src/pipecat/services/google/stt.py +++ b/src/pipecat/services/google/stt.py @@ -509,26 +509,44 @@ class GoogleSTTService(STTService): Override for your deployment. See https://github.com/pipecat-ai/stt-benchmark **kwargs: Additional arguments passed to STTService. """ - if params is not None: - _warn_deprecated_param("params", "GoogleSTTSettings") - - _params = params or GoogleSTTService.InputParams() - + # 1. Initialize default_settings with hardcoded defaults default_settings = GoogleSTTSettings( language=None, - languages=list(_params.language_list), + languages=[Language.EN_US], language_codes=None, - model=_params.model, - use_separate_recognition_per_channel=_params.use_separate_recognition_per_channel, - enable_automatic_punctuation=_params.enable_automatic_punctuation, - enable_spoken_punctuation=_params.enable_spoken_punctuation, - enable_spoken_emojis=_params.enable_spoken_emojis, - profanity_filter=_params.profanity_filter, - enable_word_time_offsets=_params.enable_word_time_offsets, - enable_word_confidence=_params.enable_word_confidence, - enable_interim_results=_params.enable_interim_results, - enable_voice_activity_events=_params.enable_voice_activity_events, + model="latest_long", + use_separate_recognition_per_channel=False, + enable_automatic_punctuation=True, + enable_spoken_punctuation=False, + enable_spoken_emojis=False, + profanity_filter=False, + enable_word_time_offsets=False, + enable_word_confidence=False, + enable_interim_results=True, + enable_voice_activity_events=False, ) + + # 2. No direct init arg overrides + + # 3. Apply params overrides — only if settings not provided + if params is not None: + _warn_deprecated_param("params", GoogleSTTSettings) + if not settings: + default_settings.languages = list(params.language_list) + default_settings.model = params.model + default_settings.use_separate_recognition_per_channel = ( + params.use_separate_recognition_per_channel + ) + default_settings.enable_automatic_punctuation = params.enable_automatic_punctuation + default_settings.enable_spoken_punctuation = params.enable_spoken_punctuation + default_settings.enable_spoken_emojis = params.enable_spoken_emojis + default_settings.profanity_filter = params.profanity_filter + default_settings.enable_word_time_offsets = params.enable_word_time_offsets + default_settings.enable_word_confidence = params.enable_word_confidence + default_settings.enable_interim_results = params.enable_interim_results + default_settings.enable_voice_activity_events = params.enable_voice_activity_events + + # 4. Apply settings delta (canonical API, always wins) if settings is not None: default_settings.apply_update(settings) diff --git a/src/pipecat/services/google/tts.py b/src/pipecat/services/google/tts.py index 78719f8fa..6b17caed5 100644 --- a/src/pipecat/services/google/tts.py +++ b/src/pipecat/services/google/tts.py @@ -622,27 +622,40 @@ class GoogleHttpTTSService(TTSService): parameters, ``settings`` values take precedence. **kwargs: Additional arguments passed to parent TTSService. """ - if voice_id is not None: - _warn_deprecated_param("voice_id", "GoogleHttpTTSSettings", "voice") - if params is not None: - _warn_deprecated_param("params", "GoogleHttpTTSSettings") - - _params = params or GoogleHttpTTSService.InputParams() - + # 1. Initialize default_settings with hardcoded defaults default_settings = GoogleHttpTTSSettings( model=None, - pitch=_params.pitch, - rate=_params.rate, - speaking_rate=_params.speaking_rate, - volume=_params.volume, - emphasis=_params.emphasis, - language=self.language_to_service_language(_params.language) - if _params.language - else "en-US", - gender=_params.gender, - google_style=_params.google_style, - voice=voice_id or "en-US-Chirp3-HD-Charon", + voice="en-US-Chirp3-HD-Charon", + language="en-US", ) + + # 2. Apply direct init arg overrides (deprecated) + if voice_id is not None: + _warn_deprecated_param("voice_id", GoogleHttpTTSSettings, "voice") + default_settings.voice = voice_id + + # 3. Apply params overrides — only if settings not provided + if params is not None: + _warn_deprecated_param("params", GoogleHttpTTSSettings) + if not settings: + if params.pitch is not None: + default_settings.pitch = params.pitch + if params.rate is not None: + default_settings.rate = params.rate + if params.speaking_rate is not None: + default_settings.speaking_rate = params.speaking_rate + if params.volume is not None: + default_settings.volume = params.volume + if params.emphasis is not None: + default_settings.emphasis = params.emphasis + if params.language is not None: + default_settings.language = self.language_to_service_language(params.language) + if params.gender is not None: + default_settings.gender = params.gender + if params.google_style is not None: + default_settings.google_style = params.google_style + + # 4. Apply settings delta (canonical API, always wins) if settings is not None: default_settings.apply_update(settings) @@ -1062,21 +1075,28 @@ class GoogleTTSService(GoogleBaseTTSService): parameters, ``settings`` values take precedence. **kwargs: Additional arguments passed to parent TTSService. """ - if voice_id is not None: - _warn_deprecated_param("voice_id", "GoogleStreamTTSSettings", "voice") - if params is not None: - _warn_deprecated_param("params", "GoogleStreamTTSSettings") - - _params = params or GoogleTTSService.InputParams() - + # 1. Initialize default_settings with hardcoded defaults default_settings = GoogleStreamTTSSettings( model=None, - language=self.language_to_service_language(_params.language) - if _params.language - else "en-US", - speaking_rate=_params.speaking_rate, - voice=voice_id or "en-US-Chirp3-HD-Charon", + voice="en-US-Chirp3-HD-Charon", + language="en-US", ) + + # 2. Apply direct init arg overrides (deprecated) + if voice_id is not None: + _warn_deprecated_param("voice_id", GoogleStreamTTSSettings, "voice") + default_settings.voice = voice_id + + # 3. Apply params overrides — only if settings not provided + if params is not None: + _warn_deprecated_param("params", GoogleStreamTTSSettings) + if not settings: + if params.language is not None: + default_settings.language = self.language_to_service_language(params.language) + if params.speaking_rate is not None: + default_settings.speaking_rate = params.speaking_rate + + # 4. Apply settings delta (canonical API, always wins) if settings is not None: default_settings.apply_update(settings) @@ -1292,34 +1312,47 @@ class GeminiTTSService(GoogleBaseTTSService): DeprecationWarning, stacklevel=2, ) - if model is not None: - _warn_deprecated_param("model", "GeminiTTSSettings", "model") - if voice_id is not None: - _warn_deprecated_param("voice_id", "GeminiTTSSettings", "voice") - if params is not None: - _warn_deprecated_param("params", "GeminiTTSSettings") if sample_rate and sample_rate != self.GOOGLE_SAMPLE_RATE: logger.warning( f"Google TTS only supports {self.GOOGLE_SAMPLE_RATE}Hz sample rate. " f"Current rate of {sample_rate}Hz may cause issues." ) - _params = params or GeminiTTSService.InputParams() - - voice_id = voice_id or "Kore" - if voice_id not in self.AVAILABLE_VOICES: - logger.warning(f"Voice '{voice_id}' not in known voices list. Using anyway.") + # 1. Initialize default_settings with hardcoded defaults default_settings = GeminiTTSSettings( - model=model or "gemini-2.5-flash-tts", - language=self.language_to_service_language(_params.language) - if _params.language - else "en-US", - prompt=_params.prompt, - multi_speaker=_params.multi_speaker, - speaker_configs=_params.speaker_configs, - voice=voice_id, + model="gemini-2.5-flash-tts", + voice="Kore", + language="en-US", ) + + # 2. Apply direct init arg overrides (deprecated) + if model is not None: + _warn_deprecated_param("model", GeminiTTSSettings, "model") + default_settings.model = model + if voice_id is not None: + _warn_deprecated_param("voice_id", GeminiTTSSettings, "voice") + default_settings.voice = voice_id + + if default_settings.voice not in self.AVAILABLE_VOICES: + logger.warning( + f"Voice '{default_settings.voice}' not in known voices list. Using anyway." + ) + + # 3. Apply params overrides — only if settings not provided + if params is not None: + _warn_deprecated_param("params", GeminiTTSSettings) + if not settings: + if params.language is not None: + default_settings.language = self.language_to_service_language(params.language) + if params.prompt is not None: + default_settings.prompt = params.prompt + if params.multi_speaker is not None: + default_settings.multi_speaker = params.multi_speaker + if params.speaker_configs is not None: + default_settings.speaker_configs = params.speaker_configs + + # 4. Apply settings delta (canonical API, always wins) if settings is not None: default_settings.apply_update(settings) diff --git a/src/pipecat/services/gradium/stt.py b/src/pipecat/services/gradium/stt.py index 5974133c0..51ac8a7cd 100644 --- a/src/pipecat/services/gradium/stt.py +++ b/src/pipecat/services/gradium/stt.py @@ -148,16 +148,23 @@ class GradiumSTTService(WebsocketSTTService): stacklevel=2, ) - if params is not None: - _warn_deprecated_param("params", "GradiumSTTSettings") - - _params = params or GradiumSTTService.InputParams() - + # 1. Initialize default_settings with hardcoded defaults default_settings = GradiumSTTSettings( model=None, - language=_params.language, - delay_in_frames=_params.delay_in_frames or None, + language=None, + delay_in_frames=None, ) + + # 2. (no deprecated direct args for this service) + + # 3. Apply params overrides — only if settings not provided + if params is not None: + _warn_deprecated_param("params", GradiumSTTSettings) + if not settings: + default_settings.language = params.language + default_settings.delay_in_frames = params.delay_in_frames + + # 4. Apply settings delta (canonical API, always wins) if settings is not None: default_settings.apply_update(settings) diff --git a/src/pipecat/services/gradium/tts.py b/src/pipecat/services/gradium/tts.py index 6f076f933..b3b9b50ca 100644 --- a/src/pipecat/services/gradium/tts.py +++ b/src/pipecat/services/gradium/tts.py @@ -103,19 +103,28 @@ class GradiumTTSService(AudioContextTTSService): parameters, ``settings`` values take precedence. **kwargs: Additional arguments passed to parent class. """ - if voice_id is not None: - _warn_deprecated_param("voice_id", "GradiumTTSSettings", "voice") - if model is not None: - _warn_deprecated_param("model", "GradiumTTSSettings", "model") - if params is not None: - _warn_deprecated_param("params", "GradiumTTSSettings") - + # 1. Initialize default_settings with hardcoded defaults default_settings = GradiumTTSSettings( - model=model or "default", - voice=voice_id or "YTpq7expH9539ERJ", + model="default", + voice="YTpq7expH9539ERJ", language=None, output_format="pcm", ) + + # 2. Apply direct init arg overrides (deprecated) + if model is not None: + _warn_deprecated_param("model", GradiumTTSSettings, "model") + default_settings.model = model + if voice_id is not None: + _warn_deprecated_param("voice_id", GradiumTTSSettings, "voice") + default_settings.voice = voice_id + + # 3. Apply params overrides — only if settings not provided + if params is not None: + _warn_deprecated_param("params", GradiumTTSSettings) + # Note: params.temp has no corresponding settings field + + # 4. Apply settings delta (canonical API, always wins) if settings is not None: default_settings.apply_update(settings) diff --git a/src/pipecat/services/grok/llm.py b/src/pipecat/services/grok/llm.py index 2e6a93c4e..f552f059a 100644 --- a/src/pipecat/services/grok/llm.py +++ b/src/pipecat/services/grok/llm.py @@ -102,10 +102,15 @@ class GrokLLMService(OpenAILLMService): parameters, ``settings`` values take precedence. **kwargs: Additional keyword arguments passed to OpenAILLMService. """ - if model is not None: - _warn_deprecated_param("model", "OpenAILLMSettings", "model") + # 1. Initialize default_settings with hardcoded defaults + default_settings = OpenAILLMSettings(model="grok-3-beta") - default_settings = OpenAILLMSettings(model=model or "grok-3-beta") + # 2. Apply direct init arg overrides (deprecated) + if model is not None: + _warn_deprecated_param("model", OpenAILLMSettings, "model") + default_settings.model = model + + # 4. Apply settings delta (canonical API, always wins) if settings is not None: default_settings.apply_update(settings) diff --git a/src/pipecat/services/grok/realtime/llm.py b/src/pipecat/services/grok/realtime/llm.py index 87f5eaaaa..2f2df1b45 100644 --- a/src/pipecat/services/grok/realtime/llm.py +++ b/src/pipecat/services/grok/realtime/llm.py @@ -153,11 +153,7 @@ class GrokRealtimeLLMService(LLMService): start_audio_paused: Whether to start with audio input paused. Defaults to False. **kwargs: Additional arguments passed to parent LLMService. """ - if session_properties is not None: - _warn_deprecated_param( - "session_properties", "GrokRealtimeLLMSettings", "session_properties" - ) - + # 1. Initialize default_settings with hardcoded defaults default_settings = GrokRealtimeLLMSettings( model=None, temperature=None, @@ -169,8 +165,17 @@ class GrokRealtimeLLMService(LLMService): seed=None, filter_incomplete_user_turns=False, user_turn_completion_config=None, - session_properties=session_properties or events.SessionProperties(), + session_properties=events.SessionProperties(), ) + + # 2. Apply direct init arg overrides (deprecated) + if session_properties is not None: + _warn_deprecated_param( + "session_properties", GrokRealtimeLLMSettings, "session_properties" + ) + default_settings.session_properties = session_properties + + # 4. Apply settings delta (canonical API, always wins) if settings is not None: default_settings.apply_update(settings) diff --git a/src/pipecat/services/groq/llm.py b/src/pipecat/services/groq/llm.py index 0ea3b3f50..f88d5a877 100644 --- a/src/pipecat/services/groq/llm.py +++ b/src/pipecat/services/groq/llm.py @@ -45,10 +45,15 @@ class GroqLLMService(OpenAILLMService): parameters, ``settings`` values take precedence. **kwargs: Additional keyword arguments passed to OpenAILLMService. """ - if model is not None: - _warn_deprecated_param("model", "OpenAILLMSettings", "model") + # 1. Initialize default_settings with hardcoded defaults + default_settings = OpenAILLMSettings(model="llama-3.3-70b-versatile") - default_settings = OpenAILLMSettings(model=model or "llama-3.3-70b-versatile") + # 2. Apply direct init arg overrides (deprecated) + if model is not None: + _warn_deprecated_param("model", OpenAILLMSettings, "model") + default_settings.model = model + + # 4. Apply settings delta (canonical API, always wins) if settings is not None: default_settings.apply_update(settings) diff --git a/src/pipecat/services/groq/stt.py b/src/pipecat/services/groq/stt.py index e6ea42fd8..ac6a4325c 100644 --- a/src/pipecat/services/groq/stt.py +++ b/src/pipecat/services/groq/stt.py @@ -69,27 +69,30 @@ class GroqSTTService(BaseWhisperSTTService): Override for your deployment. See https://github.com/pipecat-ai/stt-benchmark **kwargs: Additional arguments passed to BaseWhisperSTTService. """ - if model is not None: - _warn_deprecated_param("model", "BaseWhisperSTTSettings", "model") - if language is not None: - _warn_deprecated_param("language", "BaseWhisperSTTSettings", "language") - if prompt is not None: - _warn_deprecated_param("prompt", "BaseWhisperSTTSettings", "prompt") - if temperature is not None: - _warn_deprecated_param("temperature", "BaseWhisperSTTSettings", "temperature") - - model = model or "whisper-large-v3-turbo" - language = language or Language.EN - - # Build settings from deprecated params and pass via settings= - # to avoid double deprecation warnings in BaseWhisperSTTService. + # --- 1. Hardcoded defaults --- default_settings = BaseWhisperSTTSettings( - model=model, - language=self.language_to_service_language(language), + model="whisper-large-v3-turbo", + language=self.language_to_service_language(Language.EN), base_url=base_url, - prompt=prompt, - temperature=temperature, ) + + # --- 2. Deprecated direct-arg overrides --- + if model is not None: + _warn_deprecated_param("model", BaseWhisperSTTSettings, "model") + default_settings.model = model + if language is not None: + _warn_deprecated_param("language", BaseWhisperSTTSettings, "language") + default_settings.language = self.language_to_service_language(language) + if prompt is not None: + _warn_deprecated_param("prompt", BaseWhisperSTTSettings, "prompt") + default_settings.prompt = prompt + if temperature is not None: + _warn_deprecated_param("temperature", BaseWhisperSTTSettings, "temperature") + default_settings.temperature = temperature + + # --- 3. (no params object for this service) --- + + # --- 4. Settings delta (canonical API, always wins) --- if settings is not None: default_settings.apply_update(settings) diff --git a/src/pipecat/services/groq/tts.py b/src/pipecat/services/groq/tts.py index d16964d8c..b1c546713 100644 --- a/src/pipecat/services/groq/tts.py +++ b/src/pipecat/services/groq/tts.py @@ -114,26 +114,35 @@ class GroqTTSService(TTSService): parameters, ``settings`` values take precedence. **kwargs: Additional arguments passed to parent TTSService class. """ - if model_name is not None: - _warn_deprecated_param("model_name", "GroqTTSSettings", "model") - if voice_id is not None: - _warn_deprecated_param("voice_id", "GroqTTSSettings", "voice") - if params is not None: - _warn_deprecated_param("params", "GroqTTSSettings") - if sample_rate != self.GROQ_SAMPLE_RATE: logger.warning(f"Groq TTS only supports {self.GROQ_SAMPLE_RATE}Hz sample rate. ") - _params = params or GroqTTSService.InputParams() - + # 1. Initialize default_settings with hardcoded defaults default_settings = GroqTTSSettings( - model=model_name or "canopylabs/orpheus-v1-english", - voice=voice_id or "autumn", - language=str(_params.language) if _params.language else "en", + model="canopylabs/orpheus-v1-english", + voice="autumn", + language="en", output_format=output_format, - speed=_params.speed, + speed=1.0, groq_sample_rate=sample_rate, ) + + # 2. Apply direct init arg overrides (deprecated) + if model_name is not None: + _warn_deprecated_param("model_name", GroqTTSSettings, "model") + default_settings.model = model_name + if voice_id is not None: + _warn_deprecated_param("voice_id", GroqTTSSettings, "voice") + default_settings.voice = voice_id + + # 3. Apply params overrides — only if settings not provided + if params is not None: + _warn_deprecated_param("params", GroqTTSSettings) + if not settings: + default_settings.language = str(params.language) if params.language else "en" + default_settings.speed = params.speed + + # 4. Apply settings delta (canonical API, always wins) if settings is not None: default_settings.apply_update(settings) diff --git a/src/pipecat/services/hume/tts.py b/src/pipecat/services/hume/tts.py index 5b7300816..7b0ecd0c8 100644 --- a/src/pipecat/services/hume/tts.py +++ b/src/pipecat/services/hume/tts.py @@ -126,11 +126,6 @@ class HumeTTSService(TTSService): parameters, ``settings`` values take precedence. **kwargs: Additional arguments passed to the parent class. """ - if voice_id is not None: - _warn_deprecated_param("voice_id", "HumeTTSSettings", "voice") - if params is not None: - _warn_deprecated_param("params", "HumeTTSSettings") - api_key = api_key or os.getenv("HUME_API_KEY") if not api_key: raise ValueError("HumeTTSService requires an API key (env HUME_API_KEY or api_key=)") @@ -140,16 +135,30 @@ class HumeTTSService(TTSService): f"Hume TTS streams at {HUME_SAMPLE_RATE} Hz; configured sample_rate={sample_rate}" ) - _params = params or HumeTTSService.InputParams() - + # 1. Initialize default_settings with hardcoded defaults default_settings = HumeTTSSettings( model=None, - voice=voice_id, + voice=None, language=None, # Not applicable here - description=_params.description, - speed=_params.speed, - trailing_silence=_params.trailing_silence, + description=None, + speed=None, + trailing_silence=None, ) + + # 2. Apply direct init arg overrides (deprecated) + if voice_id is not None: + _warn_deprecated_param("voice_id", HumeTTSSettings, "voice") + default_settings.voice = voice_id + + # 3. Apply params overrides — only if settings not provided + if params is not None: + _warn_deprecated_param("params", HumeTTSSettings) + if not settings: + default_settings.description = params.description + default_settings.speed = params.speed + default_settings.trailing_silence = params.trailing_silence + + # 4. Apply settings delta (canonical API, always wins) if settings is not None: default_settings.apply_update(settings) diff --git a/src/pipecat/services/inworld/tts.py b/src/pipecat/services/inworld/tts.py index f1797ad55..688ba542a 100644 --- a/src/pipecat/services/inworld/tts.py +++ b/src/pipecat/services/inworld/tts.py @@ -18,7 +18,18 @@ import base64 import json import uuid from dataclasses import dataclass, field -from typing import Any, AsyncGenerator, ClassVar, Dict, List, Literal, Mapping, Optional, Tuple +from typing import ( + Any, + AsyncGenerator, + ClassVar, + Dict, + List, + Literal, + Mapping, + Optional, + Self, + Tuple, +) import aiohttp import websockets @@ -91,7 +102,7 @@ class InworldTTSSettings(TTSSettings): } @classmethod - def from_mapping(cls, settings: Mapping[str, Any]) -> "InworldTTSSettings": + def from_mapping(cls, settings: Mapping[str, Any]) -> Self: """Construct settings from a plain dict, destructuring legacy nested ``audioConfig``.""" flat = dict(settings) nested = flat.pop("audioConfig", None) @@ -168,27 +179,42 @@ class InworldHttpTTSService(TTSService): parameters, ``settings`` values take precedence. **kwargs: Additional arguments passed to the parent class. """ - if voice_id is not None: - _warn_deprecated_param("voice_id", "InworldTTSSettings", "voice") - if model is not None: - _warn_deprecated_param("model", "InworldTTSSettings", "model") - if params is not None: - _warn_deprecated_param("params", "InworldTTSSettings") - - _params = params or InworldHttpTTSService.InputParams() - + # 1. Initialize default_settings with hardcoded defaults default_settings = InworldTTSSettings( - model=model or "inworld-tts-1.5-max", - voice=voice_id or "Ashley", + model="inworld-tts-1.5-max", + voice="Ashley", language=None, audio_encoding=encoding, audio_sample_rate=0, - speaking_rate=_params.speaking_rate, - temperature=_params.temperature, - timestamp_transport_strategy=_params.timestamp_transport_strategy, + speaking_rate=None, + temperature=None, + timestamp_transport_strategy="ASYNC", auto_mode=None, # Not applicable for HTTP TTS apply_text_normalization=None, # Not applicable for HTTP TTS ) + + # 2. Apply direct init arg overrides (deprecated) + if voice_id is not None: + _warn_deprecated_param("voice_id", InworldTTSSettings, "voice") + default_settings.voice = voice_id + if model is not None: + _warn_deprecated_param("model", InworldTTSSettings, "model") + default_settings.model = model + + # 3. Apply params overrides — only if settings not provided + if params is not None: + _warn_deprecated_param("params", InworldTTSSettings) + if not settings: + if params.speaking_rate is not None: + default_settings.speaking_rate = params.speaking_rate + if params.temperature is not None: + default_settings.temperature = params.temperature + if params.timestamp_transport_strategy is not None: + default_settings.timestamp_transport_strategy = ( + params.timestamp_transport_strategy + ) + + # 4. Apply settings delta (canonical API, always wins) if settings is not None: default_settings.apply_update(settings) @@ -580,27 +606,50 @@ class InworldTTSService(AudioContextTTSService): append_trailing_space: Whether to append a trailing space to text before sending to TTS. **kwargs: Additional arguments passed to the parent class. """ - if voice_id is not None: - _warn_deprecated_param("voice_id", "InworldTTSSettings", "voice") - if model is not None: - _warn_deprecated_param("model", "InworldTTSSettings", "model") - if params is not None: - _warn_deprecated_param("params", "InworldTTSSettings") - - _params = params or InworldTTSService.InputParams() - + # 1. Initialize default_settings with hardcoded defaults default_settings = InworldTTSSettings( - model=model or "inworld-tts-1.5-max", - voice=voice_id or "Ashley", + model="inworld-tts-1.5-max", + voice="Ashley", language=None, audio_encoding=encoding, audio_sample_rate=0, - speaking_rate=_params.speaking_rate, - temperature=_params.temperature, - apply_text_normalization=_params.apply_text_normalization, - timestamp_transport_strategy=_params.timestamp_transport_strategy, - auto_mode=_params.auto_mode if _params.auto_mode is not None else aggregate_sentences, + speaking_rate=None, + temperature=None, + apply_text_normalization=None, + timestamp_transport_strategy="ASYNC", + auto_mode=True if aggregate_sentences is None else aggregate_sentences, ) + + # 2. Apply direct init arg overrides (deprecated) + if voice_id is not None: + _warn_deprecated_param("voice_id", InworldTTSSettings, "voice") + default_settings.voice = voice_id + if model is not None: + _warn_deprecated_param("model", InworldTTSSettings, "model") + default_settings.model = model + + # 3. Apply params overrides — only if settings not provided + _buffer_max_delay_ms = None + _buffer_char_threshold = None + if params is not None: + _warn_deprecated_param("params", InworldTTSSettings) + if not settings: + if params.speaking_rate is not None: + default_settings.speaking_rate = params.speaking_rate + if params.temperature is not None: + default_settings.temperature = params.temperature + if params.apply_text_normalization is not None: + default_settings.apply_text_normalization = params.apply_text_normalization + if params.timestamp_transport_strategy is not None: + default_settings.timestamp_transport_strategy = ( + params.timestamp_transport_strategy + ) + if params.auto_mode is not None: + default_settings.auto_mode = params.auto_mode + _buffer_max_delay_ms = params.max_buffer_delay_ms + _buffer_char_threshold = params.buffer_char_threshold + + # 4. Apply settings delta (canonical API, always wins) if settings is not None: default_settings.apply_update(settings) @@ -622,8 +671,8 @@ class InworldTTSService(AudioContextTTSService): self._timestamp_type = "WORD" self._buffer_settings = { - "maxBufferDelayMs": _params.max_buffer_delay_ms, - "bufferCharThreshold": _params.buffer_char_threshold, + "maxBufferDelayMs": _buffer_max_delay_ms, + "bufferCharThreshold": _buffer_char_threshold, } self._receive_task = None diff --git a/src/pipecat/services/kokoro/tts.py b/src/pipecat/services/kokoro/tts.py index 8bab78f93..7e53060da 100644 --- a/src/pipecat/services/kokoro/tts.py +++ b/src/pipecat/services/kokoro/tts.py @@ -151,19 +151,28 @@ class KokoroTTSService(TTSService): **kwargs: Additional arguments passed to parent `TTSService`. """ - if voice_id is not None: - _warn_deprecated_param("voice_id", "KokoroTTSSettings", "voice") - if params is not None: - _warn_deprecated_param("params", "KokoroTTSSettings") - - _params = params or KokoroTTSService.InputParams() - + # 1. Initialize default_settings with hardcoded defaults default_settings = KokoroTTSSettings( model=None, - voice=voice_id, - language=language_to_kokoro_language(_params.language), - lang_code=language_to_kokoro_language(_params.language), + voice=None, + language=language_to_kokoro_language(Language.EN), + lang_code=language_to_kokoro_language(Language.EN), ) + + # 2. Apply direct init arg overrides (deprecated) + if voice_id is not None: + _warn_deprecated_param("voice_id", KokoroTTSSettings, "voice") + default_settings.voice = voice_id + + # 3. Apply params overrides — only if settings not provided + if params is not None: + _warn_deprecated_param("params", KokoroTTSSettings) + if not settings: + lang_code = language_to_kokoro_language(params.language) + default_settings.language = lang_code + default_settings.lang_code = lang_code + + # 4. Apply settings delta (canonical API, always wins) if settings is not None: default_settings.apply_update(settings) @@ -172,14 +181,14 @@ class KokoroTTSService(TTSService): **kwargs, ) - self._lang_code = language_to_kokoro_language(_params.language) + self._lang_code = default_settings.lang_code - model = Path(model_path) if model_path else KOKORO_CACHE_DIR / "kokoro-v1.0.onnx" + model_file = Path(model_path) if model_path else KOKORO_CACHE_DIR / "kokoro-v1.0.onnx" voices = Path(voices_path) if voices_path else KOKORO_CACHE_DIR / "voices-v1.0.bin" - _ensure_model_files(model, voices) + _ensure_model_files(model_file, voices) - self._kokoro = Kokoro(str(model), str(voices)) + self._kokoro = Kokoro(str(model_file), str(voices)) self._resampler = create_stream_resampler() diff --git a/src/pipecat/services/lmnt/tts.py b/src/pipecat/services/lmnt/tts.py index a8ccec358..c69eadfef 100644 --- a/src/pipecat/services/lmnt/tts.py +++ b/src/pipecat/services/lmnt/tts.py @@ -125,17 +125,25 @@ class LmntTTSService(InterruptibleTTSService): parameters, ``settings`` values take precedence. **kwargs: Additional arguments passed to parent InterruptibleTTSService. """ - if voice_id is not None: - _warn_deprecated_param("voice_id", "LmntTTSSettings", "voice") - if model is not None: - _warn_deprecated_param("model", "LmntTTSSettings", "model") - + # 1. Initialize default_settings with hardcoded defaults default_settings = LmntTTSSettings( - model=model or "blizzard", - voice=voice_id, + model="blizzard", + voice=None, language=self.language_to_service_language(language), format="raw", ) + + # 2. Apply direct init arg overrides (deprecated) + if voice_id is not None: + _warn_deprecated_param("voice_id", LmntTTSSettings, "voice") + default_settings.voice = voice_id + if model is not None: + _warn_deprecated_param("model", LmntTTSSettings, "model") + default_settings.model = model + + # 3. No params for this service + + # 4. Apply settings delta (canonical API, always wins) if settings is not None: default_settings.apply_update(settings) diff --git a/src/pipecat/services/minimax/tts.py b/src/pipecat/services/minimax/tts.py index 9e520f763..2d9f49636 100644 --- a/src/pipecat/services/minimax/tts.py +++ b/src/pipecat/services/minimax/tts.py @@ -12,7 +12,7 @@ for streaming text-to-speech synthesis. import json from dataclasses import dataclass, field -from typing import Any, AsyncGenerator, ClassVar, Dict, Mapping, Optional +from typing import Any, AsyncGenerator, ClassVar, Dict, Mapping, Optional, Self import aiohttp from loguru import logger @@ -123,7 +123,7 @@ class MiniMaxTTSSettings(TTSSettings): _aliases: ClassVar[Dict[str, str]] = {"voice_id": "voice"} @classmethod - def from_mapping(cls, settings: Mapping[str, Any]) -> "MiniMaxTTSSettings": + def from_mapping(cls, settings: Mapping[str, Any]) -> Self: """Construct settings from a plain dict, destructuring legacy nested dicts. Handles ``voice_setting`` (with ``vol`` → ``volume`` rename) and @@ -245,74 +245,82 @@ class MiniMaxHttpTTSService(TTSService): parameters, ``settings`` values take precedence. **kwargs: Additional arguments passed to parent TTSService. """ - if model is not None: - _warn_deprecated_param("model", "MiniMaxTTSSettings", "model") - if voice_id is not None: - _warn_deprecated_param("voice_id", "MiniMaxTTSSettings", "voice") - if params is not None: - _warn_deprecated_param("params", "MiniMaxTTSSettings") - - _params = params or MiniMaxHttpTTSService.InputParams() - - # Resolve language boost - language_boost = None - if _params.language: - service_lang = self.language_to_service_language(_params.language) - if service_lang: - language_boost = service_lang - - # Resolve emotion - emotion = None - if _params.emotion: - supported_emotions = [ - "happy", - "sad", - "angry", - "fearful", - "disgusted", - "surprised", - "neutral", - "fluent", - ] - if _params.emotion in supported_emotions: - emotion = _params.emotion - else: - logger.warning( - f"Unsupported emotion: {_params.emotion}. Supported emotions: {supported_emotions}" - ) - - # Resolve text_normalization - text_normalization = None - if _params.english_normalization is not None: - import warnings - - with warnings.catch_warnings(): - warnings.simplefilter("always") - warnings.warn( - "Parameter `english_normalization` is deprecated and will be removed in a future version. Use `text_normalization` instead.", - DeprecationWarning, - ) - text_normalization = _params.english_normalization - if _params.text_normalization is not None: - text_normalization = _params.text_normalization - + # 1. Initialize default_settings with hardcoded defaults default_settings = MiniMaxTTSSettings( - model=model or "speech-02-turbo", - voice=voice_id or "Calm_Woman", + model="speech-02-turbo", + voice="Calm_Woman", language=None, stream=True, - speed=_params.speed, - volume=_params.volume, - pitch=_params.pitch, - language_boost=language_boost, - emotion=emotion, - text_normalization=text_normalization, - latex_read=_params.latex_read, + speed=1.0, + volume=1.0, + pitch=0, + language_boost=None, + emotion=None, + text_normalization=None, + latex_read=None, audio_bitrate=128000, audio_format="pcm", audio_channel=1, audio_sample_rate=0, ) + + # 2. Apply direct init arg overrides (deprecated) + if model is not None: + _warn_deprecated_param("model", MiniMaxTTSSettings, "model") + default_settings.model = model + if voice_id is not None: + _warn_deprecated_param("voice_id", MiniMaxTTSSettings, "voice") + default_settings.voice = voice_id + + # 3. Apply params overrides — only if settings not provided + if params is not None: + _warn_deprecated_param("params", MiniMaxTTSSettings) + if not settings: + default_settings.speed = params.speed + default_settings.volume = params.volume + default_settings.pitch = params.pitch + default_settings.latex_read = params.latex_read + + # Resolve language boost + if params.language: + service_lang = self.language_to_service_language(params.language) + if service_lang: + default_settings.language_boost = service_lang + + # Resolve emotion + if params.emotion: + supported_emotions = [ + "happy", + "sad", + "angry", + "fearful", + "disgusted", + "surprised", + "neutral", + "fluent", + ] + if params.emotion in supported_emotions: + default_settings.emotion = params.emotion + else: + logger.warning( + f"Unsupported emotion: {params.emotion}. Supported emotions: {supported_emotions}" + ) + + # Resolve text_normalization + if params.english_normalization is not None: + import warnings + + with warnings.catch_warnings(): + warnings.simplefilter("always") + warnings.warn( + "Parameter `english_normalization` is deprecated and will be removed in a future version. Use `text_normalization` instead.", + DeprecationWarning, + ) + default_settings.text_normalization = params.english_normalization + if params.text_normalization is not None: + default_settings.text_normalization = params.text_normalization + + # 4. Apply settings delta (canonical API, always wins) if settings is not None: default_settings.apply_update(settings) diff --git a/src/pipecat/services/mistral/llm.py b/src/pipecat/services/mistral/llm.py index da1f612c9..ca72cde37 100644 --- a/src/pipecat/services/mistral/llm.py +++ b/src/pipecat/services/mistral/llm.py @@ -48,10 +48,15 @@ class MistralLLMService(OpenAILLMService): parameters, ``settings`` values take precedence. **kwargs: Additional keyword arguments passed to OpenAILLMService. """ - if model is not None: - _warn_deprecated_param("model", "OpenAILLMSettings", "model") + # 1. Initialize default_settings with hardcoded defaults + default_settings = OpenAILLMSettings(model="mistral-small-latest") - default_settings = OpenAILLMSettings(model=model or "mistral-small-latest") + # 2. Apply direct init arg overrides (deprecated) + if model is not None: + _warn_deprecated_param("model", OpenAILLMSettings, "model") + default_settings.model = model + + # 4. Apply settings delta (canonical API, always wins) if settings is not None: default_settings.apply_update(settings) diff --git a/src/pipecat/services/moondream/vision.py b/src/pipecat/services/moondream/vision.py index b80928a43..3f0701c80 100644 --- a/src/pipecat/services/moondream/vision.py +++ b/src/pipecat/services/moondream/vision.py @@ -102,10 +102,15 @@ class MoondreamService(VisionService): parameters, ``settings`` values take precedence. **kwargs: Additional arguments passed to the parent VisionService. """ - if model is not None: - _warn_deprecated_param("model", "MoondreamSettings", "model") + # 1. Initialize default_settings with hardcoded defaults + default_settings = MoondreamSettings(model="vikhyatk/moondream2") - default_settings = MoondreamSettings(model=model or "vikhyatk/moondream2") + # 2. Apply direct init arg overrides (deprecated) + if model is not None: + _warn_deprecated_param("model", MoondreamSettings, "model") + default_settings.model = model + + # 4. Apply settings delta (canonical API, always wins) if settings is not None: default_settings.apply_update(settings) diff --git a/src/pipecat/services/neuphonic/tts.py b/src/pipecat/services/neuphonic/tts.py index e1efee96b..ae85c3ab5 100644 --- a/src/pipecat/services/neuphonic/tts.py +++ b/src/pipecat/services/neuphonic/tts.py @@ -154,21 +154,31 @@ class NeuphonicTTSService(InterruptibleTTSService): text_aggregation_mode: How to aggregate text before synthesis. **kwargs: Additional arguments passed to parent InterruptibleTTSService. """ - if voice_id is not None: - _warn_deprecated_param("voice_id", "NeuphonicTTSSettings", "voice") - if params is not None: - _warn_deprecated_param("params", "NeuphonicTTSSettings") - - _params = params or NeuphonicTTSService.InputParams() - + # 1. Initialize default_settings with hardcoded defaults default_settings = NeuphonicTTSSettings( model=None, - language=self.language_to_service_language(_params.language), - speed=_params.speed, + voice=None, + language=self.language_to_service_language(Language.EN), + speed=1.0, encoding=encoding, sampling_rate=sample_rate, - voice=voice_id, ) + + # 2. Apply direct init arg overrides (deprecated) + if voice_id is not None: + _warn_deprecated_param("voice_id", NeuphonicTTSSettings, "voice") + default_settings.voice = voice_id + + # 3. Apply params overrides — only if settings not provided + if params is not None: + _warn_deprecated_param("params", NeuphonicTTSSettings) + if not settings: + if params.language is not None: + default_settings.language = self.language_to_service_language(params.language) + if params.speed is not None: + default_settings.speed = params.speed + + # 4. Apply settings delta (canonical API, always wins) if settings is not None: default_settings.apply_update(settings) @@ -487,21 +497,33 @@ class NeuphonicHttpTTSService(TTSService): parameters, ``settings`` values take precedence. **kwargs: Additional arguments passed to parent TTSService. """ - if voice_id is not None: - _warn_deprecated_param("voice_id", "NeuphonicTTSSettings", "voice") - if params is not None: - _warn_deprecated_param("params", "NeuphonicTTSSettings") - - _params = params or NeuphonicHttpTTSService.InputParams() - + # 1. Initialize default_settings with hardcoded defaults default_settings = NeuphonicTTSSettings( model=None, - voice=voice_id, - language=self.language_to_service_language(_params.language) or "en", - speed=_params.speed, + voice=None, + language=self.language_to_service_language(Language.EN) or "en", + speed=1.0, encoding=encoding, sampling_rate=sample_rate, ) + + # 2. Apply direct init arg overrides (deprecated) + if voice_id is not None: + _warn_deprecated_param("voice_id", NeuphonicTTSSettings, "voice") + default_settings.voice = voice_id + + # 3. Apply params overrides — only if settings not provided + if params is not None: + _warn_deprecated_param("params", NeuphonicTTSSettings) + if not settings: + if params.language is not None: + default_settings.language = ( + self.language_to_service_language(params.language) or "en" + ) + if params.speed is not None: + default_settings.speed = params.speed + + # 4. Apply settings delta (canonical API, always wins) if settings is not None: default_settings.apply_update(settings) diff --git a/src/pipecat/services/nvidia/llm.py b/src/pipecat/services/nvidia/llm.py index 1667457b9..f09db54fa 100644 --- a/src/pipecat/services/nvidia/llm.py +++ b/src/pipecat/services/nvidia/llm.py @@ -52,12 +52,15 @@ class NvidiaLLMService(OpenAILLMService): parameters, ``settings`` values take precedence. **kwargs: Additional keyword arguments passed to OpenAILLMService. """ - if model is not None: - _warn_deprecated_param("model", "OpenAILLMSettings", "model") + # 1. Initialize default_settings with hardcoded defaults + default_settings = OpenAILLMSettings(model="nvidia/llama-3.1-nemotron-70b-instruct") - default_settings = OpenAILLMSettings( - model=model or "nvidia/llama-3.1-nemotron-70b-instruct" - ) + # 2. Apply direct init arg overrides (deprecated) + if model is not None: + _warn_deprecated_param("model", OpenAILLMSettings, "model") + default_settings.model = model + + # 4. Apply settings delta (canonical API, always wins) if settings is not None: default_settings.apply_update(settings) diff --git a/src/pipecat/services/nvidia/stt.py b/src/pipecat/services/nvidia/stt.py index 63e901005..3ceaf45fa 100644 --- a/src/pipecat/services/nvidia/stt.py +++ b/src/pipecat/services/nvidia/stt.py @@ -174,15 +174,21 @@ class NvidiaSTTService(STTService): Override for your deployment. See https://github.com/pipecat-ai/stt-benchmark **kwargs: Additional arguments passed to STTService. """ - if params is not None: - _warn_deprecated_param("params", "NvidiaSTTSettings") - - _params = params or NvidiaSTTService.InputParams() - + # 1. Initialize default_settings with hardcoded defaults default_settings = NvidiaSTTSettings( model=model_function_map.get("model_name"), - language=_params.language, + language=Language.EN_US, ) + + # 2. (no deprecated direct args for this service) + + # 3. Apply params overrides — only if settings not provided + if params is not None: + _warn_deprecated_param("params", NvidiaSTTSettings) + if not settings: + default_settings.language = params.language + + # 4. Apply settings delta (canonical API, always wins) if settings is not None: default_settings.apply_update(settings) @@ -492,21 +498,33 @@ class NvidiaSegmentedSTTService(SegmentedSTTService): Override for your deployment. See https://github.com/pipecat-ai/stt-benchmark **kwargs: Additional arguments passed to SegmentedSTTService """ - if params is not None: - _warn_deprecated_param("params", "NvidiaSegmentedSTTSettings") - - _params = params or NvidiaSegmentedSTTService.InputParams() - + # 1. Initialize default_settings with hardcoded defaults default_settings = NvidiaSegmentedSTTSettings( model=model_function_map.get("model_name"), - language=self.language_to_service_language(_params.language or Language.EN_US) - or "en-US", - profanity_filter=_params.profanity_filter, - automatic_punctuation=_params.automatic_punctuation, - verbatim_transcripts=_params.verbatim_transcripts, - boosted_lm_words=_params.boosted_lm_words, - boosted_lm_score=_params.boosted_lm_score, + language=language_to_nvidia_riva_language(Language.EN_US) or "en-US", + profanity_filter=False, + automatic_punctuation=True, + verbatim_transcripts=False, + boosted_lm_words=None, + boosted_lm_score=4.0, ) + + # 2. (no deprecated direct args for this service) + + # 3. Apply params overrides — only if settings not provided + if params is not None: + _warn_deprecated_param("params", NvidiaSegmentedSTTSettings) + if not settings: + default_settings.language = ( + language_to_nvidia_riva_language(params.language or Language.EN_US) or "en-US" + ) + default_settings.profanity_filter = params.profanity_filter + default_settings.automatic_punctuation = params.automatic_punctuation + default_settings.verbatim_transcripts = params.verbatim_transcripts + default_settings.boosted_lm_words = params.boosted_lm_words + default_settings.boosted_lm_score = params.boosted_lm_score + + # 4. Apply settings delta (canonical API, always wins) if settings is not None: default_settings.apply_update(settings) diff --git a/src/pipecat/services/nvidia/tts.py b/src/pipecat/services/nvidia/tts.py index 75caa27e4..be0b90071 100644 --- a/src/pipecat/services/nvidia/tts.py +++ b/src/pipecat/services/nvidia/tts.py @@ -117,19 +117,29 @@ class NvidiaTTSService(TTSService): use_ssl: Whether to use SSL for the NVIDIA Riva server. Defaults to True. **kwargs: Additional arguments passed to parent TTSService. """ - if voice_id is not None: - _warn_deprecated_param("voice_id", "NvidiaTTSSettings", "voice") - if params is not None: - _warn_deprecated_param("params", "NvidiaTTSSettings") - - _params = params or NvidiaTTSService.InputParams() - + # 1. Initialize default_settings with hardcoded defaults default_settings = NvidiaTTSSettings( model=model_function_map.get("model_name"), - voice=voice_id or "Magpie-Multilingual.EN-US.Aria", - language=_params.language, - quality=_params.quality, + voice="Magpie-Multilingual.EN-US.Aria", + language=Language.EN_US, + quality=20, ) + + # 2. Apply direct init arg overrides (deprecated) + if voice_id is not None: + _warn_deprecated_param("voice_id", NvidiaTTSSettings, "voice") + default_settings.voice = voice_id + + # 3. Apply params overrides — only if settings not provided + if params is not None: + _warn_deprecated_param("params", NvidiaTTSSettings) + if not settings: + if params.language is not None: + default_settings.language = params.language + if params.quality is not None: + default_settings.quality = params.quality + + # 4. Apply settings delta (canonical API, always wins) if settings is not None: default_settings.apply_update(settings) diff --git a/src/pipecat/services/ollama/llm.py b/src/pipecat/services/ollama/llm.py index 8fc94985d..2a4a3e78f 100644 --- a/src/pipecat/services/ollama/llm.py +++ b/src/pipecat/services/ollama/llm.py @@ -44,10 +44,15 @@ class OLLamaLLMService(OpenAILLMService): parameters, ``settings`` values take precedence. **kwargs: Additional keyword arguments passed to OpenAILLMService. """ - if model is not None: - _warn_deprecated_param("model", "OpenAILLMSettings", "model") + # 1. Initialize default_settings with hardcoded defaults + default_settings = OpenAILLMSettings(model="llama2") - default_settings = OpenAILLMSettings(model=model or "llama2") + # 2. Apply direct init arg overrides (deprecated) + if model is not None: + _warn_deprecated_param("model", OpenAILLMSettings, "model") + default_settings.model = model + + # 4. Apply settings delta (canonical API, always wins) if settings is not None: default_settings.apply_update(settings) diff --git a/src/pipecat/services/openai/base_llm.py b/src/pipecat/services/openai/base_llm.py index 0b4c3dec7..6c27fbe37 100644 --- a/src/pipecat/services/openai/base_llm.py +++ b/src/pipecat/services/openai/base_llm.py @@ -150,24 +150,41 @@ class BaseOpenAILLMService(LLMService): system_instruction: Optional system instruction to prepend to messages. **kwargs: Additional arguments passed to the parent LLMService. """ - _params = params or BaseOpenAILLMService.InputParams() - + # 1. Initialize default_settings with hardcoded defaults default_settings = OpenAILLMSettings( - model=model or "gpt-4o", - frequency_penalty=_params.frequency_penalty, - presence_penalty=_params.presence_penalty, - seed=_params.seed, - temperature=_params.temperature, - top_p=_params.top_p, + model="gpt-4o", + frequency_penalty=NOT_GIVEN, + presence_penalty=NOT_GIVEN, + seed=NOT_GIVEN, + temperature=NOT_GIVEN, + top_p=NOT_GIVEN, top_k=None, - max_tokens=_params.max_tokens, - max_completion_tokens=_params.max_completion_tokens, - service_tier=_params.service_tier, + max_tokens=NOT_GIVEN, + max_completion_tokens=NOT_GIVEN, + service_tier=NOT_GIVEN, filter_incomplete_user_turns=False, user_turn_completion_config=None, - extra=_params.extra if isinstance(_params.extra, dict) else {}, + extra={}, ) + # 2. Apply direct init arg overrides (no warnings in base class) + if model is not None: + default_settings.model = model + + # 3. Apply params overrides — only if settings not provided + if params is not None and not settings: + default_settings.frequency_penalty = params.frequency_penalty + default_settings.presence_penalty = params.presence_penalty + default_settings.seed = params.seed + default_settings.temperature = params.temperature + default_settings.top_p = params.top_p + default_settings.max_tokens = params.max_tokens + default_settings.max_completion_tokens = params.max_completion_tokens + default_settings.service_tier = params.service_tier + if isinstance(params.extra, dict): + default_settings.extra = params.extra + + # 4. Apply settings delta (canonical API, always wins) if settings is not None: default_settings.apply_update(settings) diff --git a/src/pipecat/services/openai/image.py b/src/pipecat/services/openai/image.py index a145df6e5..fd9bd0ba8 100644 --- a/src/pipecat/services/openai/image.py +++ b/src/pipecat/services/openai/image.py @@ -70,10 +70,15 @@ class OpenAIImageGenService(ImageGenService): settings: Runtime-updatable settings. When provided alongside deprecated parameters, ``settings`` values take precedence. """ - if model is not None: - _warn_deprecated_param("model", "OpenAIImageGenSettings", "model") + # 1. Initialize default_settings with hardcoded defaults + default_settings = OpenAIImageGenSettings(model="dall-e-3") - default_settings = OpenAIImageGenSettings(model=model or "dall-e-3") + # 2. Apply direct init arg overrides (deprecated) + if model is not None: + _warn_deprecated_param("model", OpenAIImageGenSettings, "model") + default_settings.model = model + + # 4. Apply settings delta (canonical API, always wins) if settings is not None: default_settings.apply_update(settings) diff --git a/src/pipecat/services/openai/llm.py b/src/pipecat/services/openai/llm.py index a8ab760c4..56515ce89 100644 --- a/src/pipecat/services/openai/llm.py +++ b/src/pipecat/services/openai/llm.py @@ -10,6 +10,8 @@ import json from dataclasses import dataclass from typing import Any, Optional +from openai import NOT_GIVEN + from pipecat.frames.frames import ( FunctionCallCancelFrame, FunctionCallInProgressFrame, @@ -95,27 +97,44 @@ class OpenAILLMService(BaseOpenAILLMService): parameters, ``settings`` values take precedence. **kwargs: Additional arguments passed to the parent BaseOpenAILLMService. """ - if model is not None: - _warn_deprecated_param("model", "OpenAILLMSettings", "model") - if params is not None: - _warn_deprecated_param("params", "OpenAILLMSettings") - - _params = params or BaseOpenAILLMService.InputParams() + # 1. Initialize default_settings with hardcoded defaults default_settings = OpenAILLMSettings( - model=model or "gpt-4.1", - frequency_penalty=_params.frequency_penalty, - presence_penalty=_params.presence_penalty, - seed=_params.seed, - temperature=_params.temperature, - top_p=_params.top_p, + model="gpt-4.1", + frequency_penalty=NOT_GIVEN, + presence_penalty=NOT_GIVEN, + seed=NOT_GIVEN, + temperature=NOT_GIVEN, + top_p=NOT_GIVEN, top_k=None, - max_tokens=_params.max_tokens, - max_completion_tokens=_params.max_completion_tokens, - service_tier=_params.service_tier, + max_tokens=NOT_GIVEN, + max_completion_tokens=NOT_GIVEN, + service_tier=NOT_GIVEN, filter_incomplete_user_turns=False, user_turn_completion_config=None, - extra=_params.extra if isinstance(_params.extra, dict) else {}, + extra={}, ) + + # 2. Apply direct init arg overrides (deprecated) + if model is not None: + _warn_deprecated_param("model", OpenAILLMSettings, "model") + default_settings.model = model + + # 3. Apply params overrides — only if settings not provided + if params is not None: + _warn_deprecated_param("params", OpenAILLMSettings) + if not settings: + default_settings.frequency_penalty = params.frequency_penalty + default_settings.presence_penalty = params.presence_penalty + default_settings.seed = params.seed + default_settings.temperature = params.temperature + default_settings.top_p = params.top_p + default_settings.max_tokens = params.max_tokens + default_settings.max_completion_tokens = params.max_completion_tokens + default_settings.service_tier = params.service_tier + if isinstance(params.extra, dict): + default_settings.extra = params.extra + + # 4. Apply settings delta (canonical API, always wins) if settings is not None: default_settings.apply_update(settings) diff --git a/src/pipecat/services/openai/realtime/llm.py b/src/pipecat/services/openai/realtime/llm.py index d6e7a71bd..1230ed2db 100644 --- a/src/pipecat/services/openai/realtime/llm.py +++ b/src/pipecat/services/openai/realtime/llm.py @@ -168,12 +168,6 @@ class OpenAIRealtimeLLMService(LLMService): **kwargs: Additional arguments passed to parent LLMService. """ - if model is not None: - _warn_deprecated_param("model", "OpenAIRealtimeLLMSettings", "model") - if session_properties is not None: - _warn_deprecated_param( - "session_properties", "OpenAIRealtimeLLMSettings", "session_properties" - ) if send_transcription_frames is not None: import warnings @@ -186,8 +180,9 @@ class OpenAIRealtimeLLMService(LLMService): stacklevel=2, ) + # 1. Initialize default_settings with hardcoded defaults default_settings = OpenAIRealtimeLLMSettings( - model=model or "gpt-realtime-1.5", + model="gpt-realtime-1.5", temperature=None, max_tokens=None, top_p=None, @@ -197,8 +192,20 @@ class OpenAIRealtimeLLMService(LLMService): seed=None, filter_incomplete_user_turns=False, user_turn_completion_config=None, - session_properties=session_properties or events.SessionProperties(), + session_properties=events.SessionProperties(), ) + + # 2. Apply direct init arg overrides (deprecated) + if model is not None: + _warn_deprecated_param("model", OpenAIRealtimeLLMSettings, "model") + default_settings.model = model + if session_properties is not None: + _warn_deprecated_param( + "session_properties", OpenAIRealtimeLLMSettings, "session_properties" + ) + default_settings.session_properties = session_properties + + # 4. Apply settings delta (canonical API, always wins) if settings is not None: default_settings.apply_update(settings) diff --git a/src/pipecat/services/openai/stt.py b/src/pipecat/services/openai/stt.py index 5c31d3f02..ea2814619 100644 --- a/src/pipecat/services/openai/stt.py +++ b/src/pipecat/services/openai/stt.py @@ -94,23 +94,35 @@ class OpenAISTTService(BaseWhisperSTTService): Override for your deployment. See https://github.com/pipecat-ai/stt-benchmark **kwargs: Additional arguments passed to BaseWhisperSTTService. """ - if model is not None: - _warn_deprecated_param("model", "BaseWhisperSTTSettings", "model") - - super().__init__( - model=model or "gpt-4o-transcribe", - api_key=api_key, + # --- 1. Hardcoded defaults --- + _language = language or Language.EN + default_settings = BaseWhisperSTTSettings( + model="gpt-4o-transcribe", + language=self.language_to_service_language(_language), base_url=base_url, - language=language, prompt=prompt, temperature=temperature, + ) + + # --- 2. Deprecated direct-arg overrides --- + if model is not None: + _warn_deprecated_param("model", BaseWhisperSTTSettings, "model") + default_settings.model = model + + # --- 3. (no params object for this service) --- + + # --- 4. Settings delta (canonical API, always wins) --- + if settings is not None: + default_settings.apply_update(settings) + + super().__init__( + api_key=api_key, + base_url=base_url, + settings=default_settings, ttfs_p99_latency=ttfs_p99_latency, **kwargs, ) - if settings is not None: - self._settings.apply_update(settings) - async def _transcribe(self, audio: bytes) -> Transcription: assert self._language is not None # Assigned in the BaseWhisperSTTService class @@ -242,14 +254,21 @@ class OpenAIRealtimeSTTService(WebsocketSTTService): "Install it with: pip install pipecat-ai[openai]" ) - if model is not None: - _warn_deprecated_param("model", "OpenAIRealtimeSTTSettings", "model") - + # --- 1. Hardcoded defaults --- default_settings = OpenAIRealtimeSTTSettings( - model=model or "gpt-4o-transcribe", + model="gpt-4o-transcribe", language=language, prompt=prompt, ) + + # --- 2. Deprecated direct-arg overrides --- + if model is not None: + _warn_deprecated_param("model", OpenAIRealtimeSTTSettings, "model") + default_settings.model = model + + # --- 3. (no params object for this service) --- + + # --- 4. Settings delta (canonical API, always wins) --- if settings is not None: default_settings.apply_update(settings) @@ -262,7 +281,7 @@ class OpenAIRealtimeSTTService(WebsocketSTTService): self._api_key = api_key self._base_url = base_url - self._prompt = prompt + self._prompt = self._settings.prompt self._turn_detection = turn_detection self._noise_reduction = noise_reduction self._should_interrupt = should_interrupt diff --git a/src/pipecat/services/openai/tts.py b/src/pipecat/services/openai/tts.py index 42c963808..a119c3d14 100644 --- a/src/pipecat/services/openai/tts.py +++ b/src/pipecat/services/openai/tts.py @@ -150,34 +150,43 @@ class OpenAITTSService(TTSService): parameters, ``settings`` values take precedence. **kwargs: Additional keyword arguments passed to TTSService. """ - if voice is not None: - _warn_deprecated_param("voice", "OpenAITTSSettings", "voice") - if model is not None: - _warn_deprecated_param("model", "OpenAITTSSettings", "model") - if instructions is not None: - _warn_deprecated_param("instructions", "OpenAITTSSettings", "instructions") - if speed is not None: - _warn_deprecated_param("speed", "OpenAITTSSettings", "speed") - if params is not None: - _warn_deprecated_param("params", "OpenAITTSSettings") - if sample_rate and sample_rate != self.OPENAI_SAMPLE_RATE: logger.warning( f"OpenAI TTS only supports {self.OPENAI_SAMPLE_RATE}Hz sample rate. " f"Current rate of {sample_rate}Hz may cause issues." ) - _params = params or OpenAITTSService.InputParams() - _instructions = instructions if instructions is not None else _params.instructions - _speed = speed if speed is not None else _params.speed - + # 1. Initialize default_settings with hardcoded defaults default_settings = OpenAITTSSettings( - model=model or "gpt-4o-mini-tts", - voice=voice or "alloy", + model="gpt-4o-mini-tts", + voice="alloy", language=None, - instructions=_instructions, - speed=_speed, ) + + # 2. Apply direct init arg overrides (deprecated) + if voice is not None: + _warn_deprecated_param("voice", OpenAITTSSettings, "voice") + default_settings.voice = voice + if model is not None: + _warn_deprecated_param("model", OpenAITTSSettings, "model") + default_settings.model = model + if instructions is not None: + _warn_deprecated_param("instructions", OpenAITTSSettings, "instructions") + default_settings.instructions = instructions + if speed is not None: + _warn_deprecated_param("speed", OpenAITTSSettings, "speed") + default_settings.speed = speed + + # 3. Apply params overrides — only if settings not provided + if params is not None: + _warn_deprecated_param("params", OpenAITTSSettings) + if not settings: + if params.instructions is not None: + default_settings.instructions = params.instructions + if params.speed is not None: + default_settings.speed = params.speed + + # 4. Apply settings delta (canonical API, always wins) if settings is not None: default_settings.apply_update(settings) diff --git a/src/pipecat/services/openai_realtime_beta/openai.py b/src/pipecat/services/openai_realtime_beta/openai.py index cb660ce72..11b60c3b9 100644 --- a/src/pipecat/services/openai_realtime_beta/openai.py +++ b/src/pipecat/services/openai_realtime_beta/openai.py @@ -167,15 +167,9 @@ class OpenAIRealtimeBetaLLMService(LLMService): stacklevel=2, ) - if model is not None: - _warn_deprecated_param("model", "OpenAIRealtimeBetaLLMSettings", "model") - if session_properties is not None: - _warn_deprecated_param( - "session_properties", "OpenAIRealtimeBetaLLMSettings", "session_properties" - ) - + # 1. Initialize default_settings with hardcoded defaults default_settings = OpenAIRealtimeBetaLLMSettings( - model=model or "gpt-4o-realtime-preview-2025-06-03", + model="gpt-4o-realtime-preview-2025-06-03", temperature=None, max_tokens=None, top_p=None, @@ -185,8 +179,20 @@ class OpenAIRealtimeBetaLLMService(LLMService): seed=None, filter_incomplete_user_turns=False, user_turn_completion_config=None, - session_properties=session_properties or events.SessionProperties(), + session_properties=events.SessionProperties(), ) + + # 2. Apply direct init arg overrides (deprecated) + if model is not None: + _warn_deprecated_param("model", OpenAIRealtimeBetaLLMSettings, "model") + default_settings.model = model + if session_properties is not None: + _warn_deprecated_param( + "session_properties", OpenAIRealtimeBetaLLMSettings, "session_properties" + ) + default_settings.session_properties = session_properties + + # 4. Apply settings delta (canonical API, always wins) if settings is not None: default_settings.apply_update(settings) diff --git a/src/pipecat/services/openpipe/llm.py b/src/pipecat/services/openpipe/llm.py index 7fb4ebd2d..9724c0a3f 100644 --- a/src/pipecat/services/openpipe/llm.py +++ b/src/pipecat/services/openpipe/llm.py @@ -64,10 +64,15 @@ class OpenPipeLLMService(OpenAILLMService): parameters, ``settings`` values take precedence. **kwargs: Additional arguments passed to parent OpenAILLMService. """ - if model is not None: - _warn_deprecated_param("model", "OpenAILLMSettings", "model") + # 1. Initialize default_settings with hardcoded defaults + default_settings = OpenAILLMSettings(model="gpt-4.1") - default_settings = OpenAILLMSettings(model=model or "gpt-4.1") + # 2. Apply direct init arg overrides (deprecated) + if model is not None: + _warn_deprecated_param("model", OpenAILLMSettings, "model") + default_settings.model = model + + # 4. Apply settings delta (canonical API, always wins) if settings is not None: default_settings.apply_update(settings) diff --git a/src/pipecat/services/openrouter/llm.py b/src/pipecat/services/openrouter/llm.py index ea307aaee..42f01c77d 100644 --- a/src/pipecat/services/openrouter/llm.py +++ b/src/pipecat/services/openrouter/llm.py @@ -50,10 +50,15 @@ class OpenRouterLLMService(OpenAILLMService): parameters, ``settings`` values take precedence. **kwargs: Additional keyword arguments passed to OpenAILLMService. """ - if model is not None: - _warn_deprecated_param("model", "OpenAILLMSettings", "model") + # 1. Initialize default_settings with hardcoded defaults + default_settings = OpenAILLMSettings(model="openai/gpt-4o-2024-11-20") - default_settings = OpenAILLMSettings(model=model or "openai/gpt-4o-2024-11-20") + # 2. Apply direct init arg overrides (deprecated) + if model is not None: + _warn_deprecated_param("model", OpenAILLMSettings, "model") + default_settings.model = model + + # 4. Apply settings delta (canonical API, always wins) if settings is not None: default_settings.apply_update(settings) diff --git a/src/pipecat/services/perplexity/llm.py b/src/pipecat/services/perplexity/llm.py index 1fbf763f3..2d350b736 100644 --- a/src/pipecat/services/perplexity/llm.py +++ b/src/pipecat/services/perplexity/llm.py @@ -53,10 +53,15 @@ class PerplexityLLMService(OpenAILLMService): parameters, ``settings`` values take precedence. **kwargs: Additional keyword arguments passed to OpenAILLMService. """ - if model is not None: - _warn_deprecated_param("model", "OpenAILLMSettings", "model") + # 1. Initialize default_settings with hardcoded defaults + default_settings = OpenAILLMSettings(model="sonar") - default_settings = OpenAILLMSettings(model=model or "sonar") + # 2. Apply direct init arg overrides (deprecated) + if model is not None: + _warn_deprecated_param("model", OpenAILLMSettings, "model") + default_settings.model = model + + # 4. Apply settings delta (canonical API, always wins) if settings is not None: default_settings.apply_update(settings) diff --git a/src/pipecat/services/piper/tts.py b/src/pipecat/services/piper/tts.py index 73c555c9d..fd6b0bf16 100644 --- a/src/pipecat/services/piper/tts.py +++ b/src/pipecat/services/piper/tts.py @@ -76,10 +76,17 @@ class PiperTTSService(TTSService): parameters, ``settings`` values take precedence. **kwargs: Additional arguments passed to the parent `TTSService`. """ - if voice_id is not None: - _warn_deprecated_param("voice_id", "PiperTTSSettings", "voice") + # 1. Initialize default_settings with hardcoded defaults + default_settings = PiperTTSSettings(model=None, voice=None, language=None) - default_settings = PiperTTSSettings(model=None, voice=voice_id, language=None) + # 2. Apply direct init arg overrides (deprecated) + if voice_id is not None: + _warn_deprecated_param("voice_id", PiperTTSSettings, "voice") + default_settings.voice = voice_id + + # 3. No params for this service + + # 4. Apply settings delta (canonical API, always wins) if settings is not None: default_settings.apply_update(settings) @@ -92,15 +99,15 @@ class PiperTTSService(TTSService): _voice = self._settings.voice model_file = f"{_voice}.onnx" - model_path = Path(download_dir) / model_file + model_path_resolved = Path(download_dir) / model_file - if not model_path.exists(): + if not model_path_resolved.exists(): logger.debug(f"Downloading Piper '{_voice}' model") download_voice(_voice, download_dir, force_redownload=force_redownload) - logger.debug(f"Loading Piper '{_voice}' model from {model_path}") + logger.debug(f"Loading Piper '{_voice}' model from {model_path_resolved}") - self._voice = PiperVoice.load(model_path, use_cuda=use_cuda) + self._voice = PiperVoice.load(model_path_resolved, use_cuda=use_cuda) logger.debug(f"Loaded Piper '{_voice}' model") @@ -222,10 +229,17 @@ class PiperHttpTTSService(TTSService): parameters, ``settings`` values take precedence. **kwargs: Additional arguments passed to the parent TTSService. """ - if voice_id is not None: - _warn_deprecated_param("voice_id", "PiperHttpTTSSettings", "voice") + # 1. Initialize default_settings with hardcoded defaults + default_settings = PiperHttpTTSSettings(model=None, voice=None, language=None) - default_settings = PiperHttpTTSSettings(model=None, voice=voice_id, language=None) + # 2. Apply direct init arg overrides (deprecated) + if voice_id is not None: + _warn_deprecated_param("voice_id", PiperHttpTTSSettings, "voice") + default_settings.voice = voice_id + + # 3. No params for this service + + # 4. Apply settings delta (canonical API, always wins) if settings is not None: default_settings.apply_update(settings) diff --git a/src/pipecat/services/qwen/llm.py b/src/pipecat/services/qwen/llm.py index db407f880..92d24fa76 100644 --- a/src/pipecat/services/qwen/llm.py +++ b/src/pipecat/services/qwen/llm.py @@ -45,10 +45,15 @@ class QwenLLMService(OpenAILLMService): parameters, ``settings`` values take precedence. **kwargs: Additional keyword arguments passed to OpenAILLMService. """ - if model is not None: - _warn_deprecated_param("model", "OpenAILLMSettings", "model") + # 1. Initialize default_settings with hardcoded defaults + default_settings = OpenAILLMSettings(model="qwen-plus") - default_settings = OpenAILLMSettings(model=model or "qwen-plus") + # 2. Apply direct init arg overrides (deprecated) + if model is not None: + _warn_deprecated_param("model", OpenAILLMSettings, "model") + default_settings.model = model + + # 4. Apply settings delta (canonical API, always wins) if settings is not None: default_settings.apply_update(settings) diff --git a/src/pipecat/services/resembleai/tts.py b/src/pipecat/services/resembleai/tts.py index ade4361e0..28ec8a522 100644 --- a/src/pipecat/services/resembleai/tts.py +++ b/src/pipecat/services/resembleai/tts.py @@ -95,17 +95,30 @@ class ResembleAITTSService(AudioContextTTSService): parameters, ``settings`` values take precedence. **kwargs: Additional arguments passed to the parent service. """ - if voice_id is not None: - _warn_deprecated_param("voice_id", "ResembleAITTSSettings", "voice") - + # 1. Initialize default_settings with hardcoded defaults default_settings = ResembleAITTSSettings( model=None, - voice=voice_id, + voice=None, language=None, - precision=precision, - output_format=output_format, - resemble_sample_rate=sample_rate, + precision="PCM_16", + output_format="wav", + resemble_sample_rate=22050, ) + + # 2. Apply direct init arg overrides (deprecated) + if voice_id is not None: + _warn_deprecated_param("voice_id", ResembleAITTSSettings, "voice") + default_settings.voice = voice_id + if precision is not None: + default_settings.precision = precision + if output_format is not None: + default_settings.output_format = output_format + if sample_rate is not None: + default_settings.resemble_sample_rate = sample_rate + + # 3. No params for this service + + # 4. Apply settings delta (canonical API, always wins) if settings is not None: default_settings.apply_update(settings) diff --git a/src/pipecat/services/rime/tts.py b/src/pipecat/services/rime/tts.py index c607a2e06..1de4087de 100644 --- a/src/pipecat/services/rime/tts.py +++ b/src/pipecat/services/rime/tts.py @@ -226,38 +226,57 @@ class RimeTTSService(AudioContextTTSService): **kwargs: Additional arguments passed to parent class. """ - if voice_id is not None: - _warn_deprecated_param("voice_id", "RimeTTSSettings", "voice") - if model is not None: - _warn_deprecated_param("model", "RimeTTSSettings", "model") - if params is not None: - _warn_deprecated_param("params", "RimeTTSSettings") - - # Initialize with parent class settings for proper frame handling - _params = params or RimeTTSService.InputParams() - + # 1. Initialize default_settings with hardcoded defaults default_settings = RimeTTSSettings( - model=model or "arcana", - voice=voice_id, + model="arcana", + voice=None, audioFormat="pcm", samplingRate=0, # updated in start() - language=self.language_to_service_language(_params.language) - if _params.language - else None, - segment=_params.segment, - inlineSpeedAlpha=None, # Not applicable here - speedAlpha=_params.speed_alpha, + language=None, + segment=None, + inlineSpeedAlpha=None, + speedAlpha=None, # Arcana params - repetition_penalty=_params.repetition_penalty, - temperature=_params.temperature, - top_p=_params.top_p, + repetition_penalty=None, + temperature=None, + top_p=None, # Mistv2 params - reduceLatency=_params.reduce_latency, - pauseBetweenBrackets=_params.pause_between_brackets, - phonemizeBetweenBrackets=_params.phonemize_between_brackets, - noTextNormalization=_params.no_text_normalization, - saveOovs=_params.save_oovs, + reduceLatency=None, + pauseBetweenBrackets=None, + phonemizeBetweenBrackets=None, + noTextNormalization=None, + saveOovs=None, ) + + # 2. Apply direct init arg overrides (deprecated) + if voice_id is not None: + _warn_deprecated_param("voice_id", RimeTTSSettings, "voice") + default_settings.voice = voice_id + if model is not None: + _warn_deprecated_param("model", RimeTTSSettings, "model") + default_settings.model = model + + # 3. Apply params overrides — only if settings not provided + if params is not None: + _warn_deprecated_param("params", RimeTTSSettings) + if not settings: + default_settings.language = ( + self.language_to_service_language(params.language) if params.language else None + ) + default_settings.segment = params.segment + default_settings.speedAlpha = params.speed_alpha + # Arcana params + default_settings.repetition_penalty = params.repetition_penalty + default_settings.temperature = params.temperature + default_settings.top_p = params.top_p + # Mistv2 params + default_settings.reduceLatency = params.reduce_latency + default_settings.pauseBetweenBrackets = params.pause_between_brackets + default_settings.phonemizeBetweenBrackets = params.phonemize_between_brackets + default_settings.noTextNormalization = params.no_text_normalization + default_settings.saveOovs = params.save_oovs + + # 4. Apply settings delta (canonical API, always wins) if settings is not None: default_settings.apply_update(settings) @@ -713,35 +732,50 @@ class RimeHttpTTSService(TTSService): parameters, ``settings`` values take precedence. **kwargs: Additional arguments passed to parent TTSService. """ - if voice_id is not None: - _warn_deprecated_param("voice_id", "RimeTTSSettings", "voice") - if model is not None: - _warn_deprecated_param("model", "RimeTTSSettings", "model") - if params is not None: - _warn_deprecated_param("params", "RimeTTSSettings") - - _params = params or RimeHttpTTSService.InputParams() - + # 1. Initialize default_settings with hardcoded defaults default_settings = RimeTTSSettings( - model=model or "mistv2", - language=self.language_to_service_language(_params.language) - if _params.language - else "eng", + model="mistv2", + voice=None, + language="eng", audioFormat="pcm", samplingRate=0, segment=None, - speedAlpha=_params.speed_alpha, - reduceLatency=_params.reduce_latency, - pauseBetweenBrackets=_params.pause_between_brackets, - phonemizeBetweenBrackets=_params.phonemize_between_brackets, + speedAlpha=None, + reduceLatency=None, + pauseBetweenBrackets=None, + phonemizeBetweenBrackets=None, noTextNormalization=None, saveOovs=None, - inlineSpeedAlpha=_params.inline_speed_alpha if _params.inline_speed_alpha else None, + inlineSpeedAlpha=None, repetition_penalty=None, temperature=None, top_p=None, - voice=voice_id, ) + + # 2. Apply direct init arg overrides (deprecated) + if voice_id is not None: + _warn_deprecated_param("voice_id", RimeTTSSettings, "voice") + default_settings.voice = voice_id + if model is not None: + _warn_deprecated_param("model", RimeTTSSettings, "model") + default_settings.model = model + + # 3. Apply params overrides — only if settings not provided + if params is not None: + _warn_deprecated_param("params", RimeTTSSettings) + if not settings: + default_settings.language = ( + self.language_to_service_language(params.language) if params.language else "eng" + ) + default_settings.speedAlpha = params.speed_alpha + default_settings.reduceLatency = params.reduce_latency + default_settings.pauseBetweenBrackets = params.pause_between_brackets + default_settings.phonemizeBetweenBrackets = params.phonemize_between_brackets + default_settings.inlineSpeedAlpha = ( + params.inline_speed_alpha if params.inline_speed_alpha else None + ) + + # 4. Apply settings delta (canonical API, always wins) if settings is not None: default_settings.apply_update(settings) @@ -936,28 +970,40 @@ class RimeNonJsonTTSService(InterruptibleTTSService): text_aggregation_mode: How to aggregate text before synthesis. **kwargs: Additional arguments passed to parent class. """ - if voice_id is not None: - _warn_deprecated_param("voice_id", "RimeNonJsonTTSSettings", "voice") - if model is not None: - _warn_deprecated_param("model", "RimeNonJsonTTSSettings", "model") - if params is not None: - _warn_deprecated_param("params", "RimeNonJsonTTSSettings") - - _params = params or RimeNonJsonTTSService.InputParams() - + # 1. Initialize default_settings with hardcoded defaults default_settings = RimeNonJsonTTSSettings( - voice=voice_id, - model=model or "arcana", + voice=None, + model="arcana", audioFormat=audio_format, samplingRate=sample_rate, - language=self.language_to_service_language(_params.language) - if _params.language - else None, - segment=_params.segment, - repetition_penalty=_params.repetition_penalty, - temperature=_params.temperature, - top_p=_params.top_p, + language=None, + segment=None, + repetition_penalty=None, + temperature=None, + top_p=None, ) + + # 2. Apply direct init arg overrides (deprecated) + if voice_id is not None: + _warn_deprecated_param("voice_id", RimeNonJsonTTSSettings, "voice") + default_settings.voice = voice_id + if model is not None: + _warn_deprecated_param("model", RimeNonJsonTTSSettings, "model") + default_settings.model = model + + # 3. Apply params overrides — only if settings not provided + if params is not None: + _warn_deprecated_param("params", RimeNonJsonTTSSettings) + if not settings: + default_settings.language = ( + self.language_to_service_language(params.language) if params.language else None + ) + default_settings.segment = params.segment + default_settings.repetition_penalty = params.repetition_penalty + default_settings.temperature = params.temperature + default_settings.top_p = params.top_p + + # 4. Apply settings delta (canonical API, always wins) if settings is not None: default_settings.apply_update(settings) @@ -974,8 +1020,8 @@ class RimeNonJsonTTSService(InterruptibleTTSService): self._api_key = api_key self._url = url # Add any extra parameters for future compatibility - if _params.extra: - self._settings.extra.update(_params.extra) + if params and params.extra: + self._settings.extra.update(params.extra) self._receive_task = None self._context_id: Optional[str] = None diff --git a/src/pipecat/services/sambanova/llm.py b/src/pipecat/services/sambanova/llm.py index 5114297a8..f9b7b1380 100644 --- a/src/pipecat/services/sambanova/llm.py +++ b/src/pipecat/services/sambanova/llm.py @@ -57,10 +57,15 @@ class SambaNovaLLMService(OpenAILLMService): # type: ignore parameters, ``settings`` values take precedence. **kwargs: Additional keyword arguments passed to OpenAILLMService. """ - if model is not None: - _warn_deprecated_param("model", "OpenAILLMSettings", "model") + # 1. Initialize default_settings with hardcoded defaults + default_settings = OpenAILLMSettings(model="Llama-4-Maverick-17B-128E-Instruct") - default_settings = OpenAILLMSettings(model=model or "Llama-4-Maverick-17B-128E-Instruct") + # 2. Apply direct init arg overrides (deprecated) + if model is not None: + _warn_deprecated_param("model", OpenAILLMSettings, "model") + default_settings.model = model + + # 4. Apply settings delta (canonical API, always wins) if settings is not None: default_settings.apply_update(settings) diff --git a/src/pipecat/services/sambanova/stt.py b/src/pipecat/services/sambanova/stt.py index 4ca156b88..0c2d77e36 100644 --- a/src/pipecat/services/sambanova/stt.py +++ b/src/pipecat/services/sambanova/stt.py @@ -71,27 +71,30 @@ class SambaNovaSTTService(BaseWhisperSTTService): # type: ignore Override for your deployment. See https://github.com/pipecat-ai/stt-benchmark **kwargs: Additional arguments passed to `pipecat.services.whisper.base_stt.BaseWhisperSTTService`. """ - if model is not None: - _warn_deprecated_param("model", "BaseWhisperSTTSettings", "model") - if language is not None: - _warn_deprecated_param("language", "BaseWhisperSTTSettings", "language") - if prompt is not None: - _warn_deprecated_param("prompt", "BaseWhisperSTTSettings", "prompt") - if temperature is not None: - _warn_deprecated_param("temperature", "BaseWhisperSTTSettings", "temperature") - - model = model or "Whisper-Large-v3" - language = language or Language.EN - - # Build settings from deprecated params and pass via settings= - # to avoid double deprecation warnings in BaseWhisperSTTService. + # --- 1. Hardcoded defaults --- default_settings = BaseWhisperSTTSettings( - model=model, - language=self.language_to_service_language(language), + model="Whisper-Large-v3", + language=self.language_to_service_language(Language.EN), base_url=base_url, - prompt=prompt, - temperature=temperature, ) + + # --- 2. Deprecated direct-arg overrides --- + if model is not None: + _warn_deprecated_param("model", BaseWhisperSTTSettings, "model") + default_settings.model = model + if language is not None: + _warn_deprecated_param("language", BaseWhisperSTTSettings, "language") + default_settings.language = self.language_to_service_language(language) + if prompt is not None: + _warn_deprecated_param("prompt", BaseWhisperSTTSettings, "prompt") + default_settings.prompt = prompt + if temperature is not None: + _warn_deprecated_param("temperature", BaseWhisperSTTSettings, "temperature") + default_settings.temperature = temperature + + # --- 3. (no params object for this service) --- + + # --- 4. Settings delta (canonical API, always wins) --- if settings is not None: default_settings.apply_update(settings) diff --git a/src/pipecat/services/sarvam/stt.py b/src/pipecat/services/sarvam/stt.py index 97c8d1ccc..fd9a55f14 100644 --- a/src/pipecat/services/sarvam/stt.py +++ b/src/pipecat/services/sarvam/stt.py @@ -238,44 +238,56 @@ class SarvamSTTService(STTService): keepalive_interval: Seconds between idle checks when keepalive is enabled. **kwargs: Additional arguments passed to the parent STTService. """ + # 1. Initialize default_settings with hardcoded defaults + default_settings = SarvamSTTSettings( + model="saarika:v2.5", + language=None, + prompt=None, + mode=None, + vad_signals=None, + high_vad_sensitivity=None, + ) + + # 2. Apply direct init arg overrides (deprecated) if model is not None: - _warn_deprecated_param("model", "SarvamSTTSettings", "model") + _warn_deprecated_param("model", SarvamSTTSettings, "model") + default_settings.model = model + + # 3. Apply params overrides — only if settings not provided if params is not None: - _warn_deprecated_param("params", "SarvamSTTSettings") + _warn_deprecated_param("params", SarvamSTTSettings) + if not settings: + default_settings.language = params.language + default_settings.prompt = params.prompt + default_settings.mode = params.mode + default_settings.vad_signals = params.vad_signals + default_settings.high_vad_sensitivity = params.high_vad_sensitivity - model = model or "saarika:v2.5" - _params = params or SarvamSTTService.InputParams() + # 4. Apply settings delta (canonical API, always wins) + if settings is not None: + default_settings.apply_update(settings) - # Get model configuration (validates model exists) - if model not in MODEL_CONFIGS: + # Resolve model config and validate (after all overrides) + resolved_model = default_settings.model + if resolved_model not in MODEL_CONFIGS: allowed = ", ".join(sorted(MODEL_CONFIGS.keys())) - raise ValueError(f"Unsupported model '{model}'. Allowed values: {allowed}.") + raise ValueError(f"Unsupported model '{resolved_model}'. Allowed values: {allowed}.") - self._config = MODEL_CONFIGS[model] + self._config = MODEL_CONFIGS[resolved_model] # Validate parameters against model capabilities - if _params.prompt is not None and not self._config.supports_prompt: - raise ValueError(f"Model '{model}' does not support prompt parameter.") - if _params.mode is not None and not self._config.supports_mode: - raise ValueError(f"Model '{model}' does not support mode parameter.") - if _params.language is not None and not self._config.supports_language: + if default_settings.prompt is not None and not self._config.supports_prompt: + raise ValueError(f"Model '{resolved_model}' does not support prompt parameter.") + if default_settings.mode is not None and not self._config.supports_mode: + raise ValueError(f"Model '{resolved_model}' does not support mode parameter.") + if default_settings.language is not None and not self._config.supports_language: raise ValueError( - f"Model '{model}' does not support language parameter (auto-detects language)." + f"Model '{resolved_model}' does not support language parameter (auto-detects language)." ) # Resolve mode default from model config - mode = _params.mode if _params.mode is not None else self._config.default_mode - - default_settings = SarvamSTTSettings( - model=model, - language=_params.language, - prompt=_params.prompt, - mode=mode, - vad_signals=_params.vad_signals, - high_vad_sensitivity=_params.high_vad_sensitivity, - ) - if settings is not None: - default_settings.apply_update(settings) + if default_settings.mode is None: + default_settings.mode = self._config.default_mode super().__init__( sample_rate=sample_rate, @@ -301,7 +313,7 @@ class SarvamSTTService(STTService): self._socket_client = None self._receive_task = None - if _params.vad_signals: + if default_settings.vad_signals: self._register_event_handler("on_speech_started") self._register_event_handler("on_speech_stopped") self._register_event_handler("on_utterance_end") diff --git a/src/pipecat/services/sarvam/tts.py b/src/pipecat/services/sarvam/tts.py index 14386d743..8c76e0ec9 100644 --- a/src/pipecat/services/sarvam/tts.py +++ b/src/pipecat/services/sarvam/tts.py @@ -467,55 +467,89 @@ class SarvamHttpTTSService(TTSService): parameters, ``settings`` values take precedence. **kwargs: Additional arguments passed to parent TTSService. """ - if voice_id is not None: - _warn_deprecated_param("voice_id", "SarvamHttpTTSSettings", "voice") - if model is not None: - _warn_deprecated_param("model", "SarvamHttpTTSSettings", "model") - if params is not None: - _warn_deprecated_param("params", "SarvamHttpTTSSettings") + # 1. Initialize default_settings with hardcoded defaults + default_settings = SarvamHttpTTSSettings( + model="bulbul:v2", + voice="anushka", + language="en-IN", + enable_preprocessing=False, + pace=1.0, + pitch=None, + loudness=None, + temperature=None, + ) - model = model or "bulbul:v2" + # 2. Apply direct init arg overrides (deprecated) + if model is not None: + _warn_deprecated_param("model", SarvamHttpTTSSettings, "model") + default_settings.model = model + if voice_id is not None: + _warn_deprecated_param("voice_id", SarvamHttpTTSSettings, "voice") + default_settings.voice = voice_id + + # 3. Apply params overrides — only if settings not provided + if params is not None: + _warn_deprecated_param("params", SarvamHttpTTSSettings) + if not settings: + if params.language is not None: + default_settings.language = ( + self.language_to_service_language(params.language) or "en-IN" + ) + if params.enable_preprocessing is not None: + default_settings.enable_preprocessing = params.enable_preprocessing + if params.pace is not None: + default_settings.pace = params.pace + if params.pitch is not None: + default_settings.pitch = params.pitch + if params.loudness is not None: + default_settings.loudness = params.loudness + if params.temperature is not None: + default_settings.temperature = params.temperature + + # 4. Apply settings delta (canonical API, always wins) + if settings is not None: + default_settings.apply_update(settings) # Get model configuration (validates model exists) - if model not in TTS_MODEL_CONFIGS: + resolved_model = default_settings.model + if resolved_model not in TTS_MODEL_CONFIGS: allowed = ", ".join(sorted(TTS_MODEL_CONFIGS.keys())) - raise ValueError(f"Unsupported model '{model}'. Allowed values: {allowed}.") + raise ValueError(f"Unsupported model '{resolved_model}'. Allowed values: {allowed}.") - self._config = TTS_MODEL_CONFIGS[model] + self._config = TTS_MODEL_CONFIGS[resolved_model] # Set default sample rate based on model if not specified if sample_rate is None: sample_rate = self._config.default_sample_rate - _params = params or SarvamHttpTTSService.InputParams() - - # Set default voice based on model if not specified - if voice_id is None: - voice_id = self._config.default_speaker + # Set default voice based on model if not specified via any mechanism + if voice_id is None and (settings is None or settings.voice is NOT_GIVEN): + default_settings.voice = self._config.default_speaker # Validate and clamp pace to model's valid range - pace = _params.pace + pace = default_settings.pace pace_min, pace_max = self._config.pace_range if pace is not None and (pace < pace_min or pace > pace_max): logger.warning(f"Pace {pace} is outside model range ({pace_min}-{pace_max}). Clamping.") - pace = max(pace_min, min(pace_max, pace)) + default_settings.pace = max(pace_min, min(pace_max, pace)) - default_settings = SarvamHttpTTSSettings( - language=( - self.language_to_service_language(_params.language) if _params.language else "en-IN" - ), - enable_preprocessing=( - True if self._config.preprocessing_always_enabled else _params.enable_preprocessing - ), - pace=pace, - pitch=None, - loudness=None, - temperature=None, - model=model, - voice=voice_id, - ) - if settings is not None: - default_settings.apply_update(settings) + # Force preprocessing for models that require it + if self._config.preprocessing_always_enabled: + default_settings.enable_preprocessing = True + + # Warn about unsupported model-specific parameters + if not self._config.supports_pitch and default_settings.pitch not in (None, 0.0): + logger.warning(f"pitch parameter is ignored for {resolved_model}") + default_settings.pitch = None + if not self._config.supports_loudness and default_settings.loudness not in (None, 1.0): + logger.warning(f"loudness parameter is ignored for {resolved_model}") + default_settings.loudness = None + if not self._config.supports_temperature and default_settings.temperature not in ( + None, + 0.6, + ): + logger.warning(f"temperature parameter is ignored for {resolved_model}") + default_settings.temperature = None super().__init__( sample_rate=sample_rate, @@ -527,22 +561,6 @@ class SarvamHttpTTSService(TTSService): self._base_url = base_url self._session = aiohttp_session - # Add parameters based on model support - if self._config.supports_pitch: - self._settings.pitch = _params.pitch - elif _params.pitch != 0.0: - logger.warning(f"pitch parameter is ignored for {model}") - - if self._config.supports_loudness: - self._settings.loudness = _params.loudness - elif _params.loudness != 1.0: - logger.warning(f"loudness parameter is ignored for {model}") - - if self._config.supports_temperature: - self._settings.temperature = _params.temperature - elif _params.temperature != 0.6: - logger.warning(f"temperature parameter is ignored for {model}") - def can_generate_metrics(self) -> bool: """Check if this service can generate processing metrics. @@ -858,62 +876,105 @@ class SarvamTTSService(InterruptibleTTSService): See https://docs.sarvam.ai/api-reference-docs/text-to-speech/stream """ - if model is not None: - _warn_deprecated_param("model", "SarvamTTSSettings", "model") - if voice_id is not None: - _warn_deprecated_param("voice_id", "SarvamTTSSettings", "voice") - if params is not None: - _warn_deprecated_param("params", "SarvamTTSSettings") + # 1. Initialize default_settings with hardcoded defaults + default_settings = SarvamTTSSettings( + model="bulbul:v2", + voice="anushka", + language="en-IN", + speech_sample_rate="22050", + enable_preprocessing=False, + min_buffer_size=50, + max_chunk_length=150, + output_audio_codec="linear16", + output_audio_bitrate="128k", + pace=1.0, + pitch=None, + loudness=None, + temperature=None, + ) - model = model or "bulbul:v2" + # 2. Apply direct init arg overrides (deprecated) + if model is not None: + _warn_deprecated_param("model", SarvamTTSSettings, "model") + default_settings.model = model + if voice_id is not None: + _warn_deprecated_param("voice_id", SarvamTTSSettings, "voice") + default_settings.voice = voice_id + + # 3. Apply params overrides — only if settings not provided + if params is not None: + _warn_deprecated_param("params", SarvamTTSSettings) + if not settings: + if params.language is not None: + default_settings.language = ( + self.language_to_service_language(params.language) or "en-IN" + ) + if params.enable_preprocessing is not None: + default_settings.enable_preprocessing = params.enable_preprocessing + if params.min_buffer_size is not None: + default_settings.min_buffer_size = params.min_buffer_size + if params.max_chunk_length is not None: + default_settings.max_chunk_length = params.max_chunk_length + if params.output_audio_codec is not None: + default_settings.output_audio_codec = params.output_audio_codec + if params.output_audio_bitrate is not None: + default_settings.output_audio_bitrate = params.output_audio_bitrate + if params.pace is not None: + default_settings.pace = params.pace + if params.pitch is not None: + default_settings.pitch = params.pitch + if params.loudness is not None: + default_settings.loudness = params.loudness + if params.temperature is not None: + default_settings.temperature = params.temperature + + # 4. Apply settings delta (canonical API, always wins) + if settings is not None: + default_settings.apply_update(settings) # Get model configuration (validates model exists) - if model not in TTS_MODEL_CONFIGS: + resolved_model = default_settings.model + if resolved_model not in TTS_MODEL_CONFIGS: allowed = ", ".join(sorted(TTS_MODEL_CONFIGS.keys())) - raise ValueError(f"Unsupported model '{model}'. Allowed values: {allowed}.") + raise ValueError(f"Unsupported model '{resolved_model}'. Allowed values: {allowed}.") - self._config = TTS_MODEL_CONFIGS[model] + self._config = TTS_MODEL_CONFIGS[resolved_model] # Set default sample rate based on model if not specified if sample_rate is None: sample_rate = self._config.default_sample_rate + default_settings.speech_sample_rate = str(sample_rate) - # Set default voice based on model if not specified - if voice_id is None: - voice_id = self._config.default_speaker - - _params = params or SarvamTTSService.InputParams() + # Set default voice based on model if not specified via any mechanism + if voice_id is None and (settings is None or settings.voice is NOT_GIVEN): + default_settings.voice = self._config.default_speaker # Validate and clamp pace to model's valid range - pace = _params.pace + pace = default_settings.pace pace_min, pace_max = self._config.pace_range if pace is not None and (pace < pace_min or pace > pace_max): logger.warning(f"Pace {pace} is outside model range ({pace_min}-{pace_max}). Clamping.") - pace = max(pace_min, min(pace_max, pace)) + default_settings.pace = max(pace_min, min(pace_max, pace)) - default_settings = SarvamTTSSettings( - language=( - self.language_to_service_language(_params.language) if _params.language else "en-IN" - ), - speech_sample_rate=str(sample_rate), - enable_preprocessing=( - True if self._config.preprocessing_always_enabled else _params.enable_preprocessing - ), - min_buffer_size=_params.min_buffer_size, - max_chunk_length=_params.max_chunk_length, - output_audio_codec=_params.output_audio_codec, - output_audio_bitrate=_params.output_audio_bitrate, - pace=pace, - pitch=None, - loudness=None, - temperature=None, - model=model, - voice=voice_id, - ) - if settings is not None: - default_settings.apply_update(settings) + # Force preprocessing for models that require it + if self._config.preprocessing_always_enabled: + default_settings.enable_preprocessing = True - # Initialize parent class first + # Warn about unsupported model-specific parameters + if not self._config.supports_pitch and default_settings.pitch not in (None, 0.0): + logger.warning(f"pitch parameter is ignored for {resolved_model}") + default_settings.pitch = None + if not self._config.supports_loudness and default_settings.loudness not in (None, 1.0): + logger.warning(f"loudness parameter is ignored for {resolved_model}") + default_settings.loudness = None + if not self._config.supports_temperature and default_settings.temperature not in ( + None, + 0.6, + ): + logger.warning(f"temperature parameter is ignored for {resolved_model}") + default_settings.temperature = None + + # Initialize parent class super().__init__( aggregate_sentences=aggregate_sentences, text_aggregation_mode=text_aggregation_mode, @@ -926,25 +987,9 @@ class SarvamTTSService(InterruptibleTTSService): ) # WebSocket endpoint URL with model query parameter - self._websocket_url = f"{url}?model={model}" + self._websocket_url = f"{url}?model={resolved_model}" self._api_key = api_key - # Add parameters based on model support - if self._config.supports_pitch: - self._settings.pitch = _params.pitch - elif _params.pitch != 0.0: - logger.warning(f"pitch parameter is ignored for {model}") - - if self._config.supports_loudness: - self._settings.loudness = _params.loudness - elif _params.loudness != 1.0: - logger.warning(f"loudness parameter is ignored for {model}") - - if self._config.supports_temperature: - self._settings.temperature = _params.temperature - elif _params.temperature != 0.6: - logger.warning(f"temperature parameter is ignored for {model}") - self._receive_task = None self._keepalive_task = None self._context_id: Optional[str] = None diff --git a/src/pipecat/services/settings.py b/src/pipecat/services/settings.py index 546104b9a..d9ec5bc7b 100644 --- a/src/pipecat/services/settings.py +++ b/src/pipecat/services/settings.py @@ -56,7 +56,7 @@ if TYPE_CHECKING: def _warn_deprecated_param( param_name: str, - settings_class_name: str, + settings_class: type, settings_field: str | None = None, stacklevel: int = 3, ): @@ -64,12 +64,13 @@ def _warn_deprecated_param( Args: param_name: Name of the deprecated parameter. - settings_class_name: Name of the settings class to use instead. + settings_class: The settings class to use instead. settings_field: Specific field on the settings class, if different from *param_name*. stacklevel: Stack depth for the warning. Default ``3`` targets the caller's caller (i.e. user code that instantiated the service). """ + settings_class_name = settings_class.__name__ if settings_field: msg = ( f"The `{param_name}` parameter is deprecated. " diff --git a/src/pipecat/services/soniox/stt.py b/src/pipecat/services/soniox/stt.py index c9b3fb7c9..b37a76b0f 100644 --- a/src/pipecat/services/soniox/stt.py +++ b/src/pipecat/services/soniox/stt.py @@ -218,25 +218,42 @@ class SonioxSTTService(WebsocketSTTService): Override for your deployment. See https://github.com/pipecat-ai/stt-benchmark **kwargs: Additional arguments passed to the STTService. """ - if model is not None: - _warn_deprecated_param("model", "SonioxSTTSettings", "model") - if params is not None: - _warn_deprecated_param("params", "SonioxSTTSettings") - - _params = params or SonioxInputParams() - + # 1. Initialize default_settings with hardcoded defaults default_settings = SonioxSTTSettings( - model=model or _params.model, + model="stt-rt-v4", language=None, - audio_format=_params.audio_format, - num_channels=_params.num_channels, - language_hints=_params.language_hints, - language_hints_strict=_params.language_hints_strict, - context=_params.context, - enable_speaker_diarization=_params.enable_speaker_diarization, - enable_language_identification=_params.enable_language_identification, - client_reference_id=_params.client_reference_id, + audio_format="pcm_s16le", + num_channels=1, + language_hints=None, + language_hints_strict=None, + context=None, + enable_speaker_diarization=False, + enable_language_identification=False, + client_reference_id=None, ) + + # 2. Apply direct init arg overrides (deprecated) + if model is not None: + _warn_deprecated_param("model", SonioxSTTSettings, "model") + default_settings.model = model + + # 3. Apply params overrides — only if settings not provided + if params is not None: + _warn_deprecated_param("params", SonioxSTTSettings) + if not settings: + default_settings.model = params.model + default_settings.audio_format = params.audio_format + default_settings.num_channels = params.num_channels + default_settings.language_hints = params.language_hints + default_settings.language_hints_strict = params.language_hints_strict + default_settings.context = params.context + default_settings.enable_speaker_diarization = params.enable_speaker_diarization + default_settings.enable_language_identification = ( + params.enable_language_identification + ) + default_settings.client_reference_id = params.client_reference_id + + # 4. Apply settings delta (canonical API, always wins) if settings is not None: default_settings.apply_update(settings) diff --git a/src/pipecat/services/speechmatics/stt.py b/src/pipecat/services/speechmatics/stt.py index 2d3e90896..620646d31 100644 --- a/src/pipecat/services/speechmatics/stt.py +++ b/src/pipecat/services/speechmatics/stt.py @@ -417,57 +417,86 @@ class SpeechmaticsSTTService(STTService): if not self._base_url: raise ValueError("Missing Speechmatics base URL") - if params is not None: - _warn_deprecated_param("params", "SpeechmaticsSTTSettings") - - # Default params - params = params or SpeechmaticsSTTService.InputParams() self._should_interrupt = should_interrupt - # Deprecation check - self._check_deprecated_args(kwargs, params) + # Deprecation check (mutates params in-place for legacy kwargs migration) + _params = params or SpeechmaticsSTTService.InputParams() + self._check_deprecated_args(kwargs, _params) - # Output formatting defaults - speaker_active_format = params.speaker_active_format - if speaker_active_format is None: - speaker_active_format = ( - "@{speaker_id}: {text}" if params.enable_diarization else "{text}" - ) - speaker_passive_format = params.speaker_passive_format or speaker_active_format - - # Settings — seeded from InputParams + # 1. Initialize default_settings with hardcoded defaults default_settings = SpeechmaticsSTTSettings( model=None, # Will be resolved from operating_point after config is built - language=params.language, - domain=params.domain, - turn_detection_mode=params.turn_detection_mode, - speaker_active_format=speaker_active_format, - speaker_passive_format=speaker_passive_format, - focus_speakers=params.focus_speakers, - ignore_speakers=params.ignore_speakers, - focus_mode=params.focus_mode, - known_speakers=params.known_speakers, - additional_vocab=params.additional_vocab, - audio_encoding=params.audio_encoding, - operating_point=params.operating_point, - max_delay=params.max_delay, - end_of_utterance_silence_trigger=params.end_of_utterance_silence_trigger, - end_of_utterance_max_delay=params.end_of_utterance_max_delay, - punctuation_overrides=params.punctuation_overrides, - include_partials=params.include_partials, - split_sentences=params.split_sentences, - enable_diarization=params.enable_diarization, - speaker_sensitivity=params.speaker_sensitivity, - max_speakers=params.max_speakers, - prefer_current_speaker=params.prefer_current_speaker, - extra_params=params.extra_params, + language=Language.EN, + domain=None, + turn_detection_mode=TurnDetectionMode.EXTERNAL, + speaker_active_format="{text}", + speaker_passive_format="{text}", + focus_speakers=[], + ignore_speakers=[], + focus_mode=SpeakerFocusMode.RETAIN, + known_speakers=[], + additional_vocab=[], + audio_encoding=AudioEncoding.PCM_S16LE, + operating_point=None, + max_delay=None, + end_of_utterance_silence_trigger=None, + end_of_utterance_max_delay=None, + punctuation_overrides=None, + include_partials=None, + split_sentences=None, + enable_diarization=None, + speaker_sensitivity=None, + max_speakers=None, + prefer_current_speaker=None, + extra_params=None, ) + # 2. No direct init arg overrides + + # 3. Apply params overrides — only if settings not provided + if params is not None: + _warn_deprecated_param("params", SpeechmaticsSTTSettings) + if not settings: + default_settings.language = _params.language + default_settings.domain = _params.domain + default_settings.turn_detection_mode = _params.turn_detection_mode + # Output formatting defaults + speaker_active_format = _params.speaker_active_format + if speaker_active_format is None: + speaker_active_format = ( + "@{speaker_id}: {text}" if _params.enable_diarization else "{text}" + ) + default_settings.speaker_active_format = speaker_active_format + default_settings.speaker_passive_format = ( + _params.speaker_passive_format or speaker_active_format + ) + default_settings.focus_speakers = _params.focus_speakers + default_settings.ignore_speakers = _params.ignore_speakers + default_settings.focus_mode = _params.focus_mode + default_settings.known_speakers = _params.known_speakers + default_settings.additional_vocab = _params.additional_vocab + default_settings.audio_encoding = _params.audio_encoding + default_settings.operating_point = _params.operating_point + default_settings.max_delay = _params.max_delay + default_settings.end_of_utterance_silence_trigger = ( + _params.end_of_utterance_silence_trigger + ) + default_settings.end_of_utterance_max_delay = _params.end_of_utterance_max_delay + default_settings.punctuation_overrides = _params.punctuation_overrides + default_settings.include_partials = _params.include_partials + default_settings.split_sentences = _params.split_sentences + default_settings.enable_diarization = _params.enable_diarization + default_settings.speaker_sensitivity = _params.speaker_sensitivity + default_settings.max_speakers = _params.max_speakers + default_settings.prefer_current_speaker = _params.prefer_current_speaker + default_settings.extra_params = _params.extra_params + # Build SDK config from settings, then resolve model from operating_point self._client: VoiceAgentClient | None = None self._config: VoiceAgentConfig = self._build_config(default_settings) default_settings.model = self._config.operating_point.value + # 4. Apply settings delta (canonical API, always wins) if settings is not None: default_settings.apply_update(settings) @@ -496,7 +525,7 @@ class SpeechmaticsSTTService(STTService): self._bot_speaking: bool = False # Event handlers - if params.enable_diarization: + if default_settings.enable_diarization: self._register_event_handler("on_speakers_result") # ============================================================================ diff --git a/src/pipecat/services/speechmatics/tts.py b/src/pipecat/services/speechmatics/tts.py index 8ce6ae2ef..dff3e5f0f 100644 --- a/src/pipecat/services/speechmatics/tts.py +++ b/src/pipecat/services/speechmatics/tts.py @@ -104,24 +104,32 @@ class SpeechmaticsTTSService(TTSService): parameters, ``settings`` values take precedence. **kwargs: Additional arguments passed to TTSService. """ - if voice_id is not None: - _warn_deprecated_param("voice_id", "SpeechmaticsTTSSettings", "voice") - if params is not None: - _warn_deprecated_param("params", "SpeechmaticsTTSSettings") - if sample_rate and sample_rate != self.SPEECHMATICS_SAMPLE_RATE: logger.warning( f"Speechmatics TTS only supports {self.SPEECHMATICS_SAMPLE_RATE}Hz sample rate. " f"Current rate of {sample_rate}Hz may cause issues." ) - _params = params or SpeechmaticsTTSService.InputParams() + # 1. Initialize default_settings with hardcoded defaults default_settings = SpeechmaticsTTSSettings( model=None, - voice=voice_id or "sarah", + voice="sarah", language=None, - max_retries=_params.max_retries, + max_retries=5, ) + + # 2. Apply direct init arg overrides (deprecated) + if voice_id is not None: + _warn_deprecated_param("voice_id", SpeechmaticsTTSSettings, "voice") + default_settings.voice = voice_id + + # 3. Apply params overrides — only if settings not provided + if params is not None: + _warn_deprecated_param("params", SpeechmaticsTTSSettings) + if not settings: + default_settings.max_retries = params.max_retries + + # 4. Apply settings delta (canonical API, always wins) if settings is not None: default_settings.apply_update(settings) diff --git a/src/pipecat/services/together/llm.py b/src/pipecat/services/together/llm.py index 48e15ae5c..0fd8b637b 100644 --- a/src/pipecat/services/together/llm.py +++ b/src/pipecat/services/together/llm.py @@ -45,12 +45,15 @@ class TogetherLLMService(OpenAILLMService): parameters, ``settings`` values take precedence. **kwargs: Additional keyword arguments passed to OpenAILLMService. """ - if model is not None: - _warn_deprecated_param("model", "OpenAILLMSettings", "model") + # 1. Initialize default_settings with hardcoded defaults + default_settings = OpenAILLMSettings(model="meta-llama/Meta-Llama-3.1-8B-Instruct-Turbo") - default_settings = OpenAILLMSettings( - model=model or "meta-llama/Meta-Llama-3.1-8B-Instruct-Turbo" - ) + # 2. Apply direct init arg overrides (deprecated) + if model is not None: + _warn_deprecated_param("model", OpenAILLMSettings, "model") + default_settings.model = model + + # 4. Apply settings delta (canonical API, always wins) if settings is not None: default_settings.apply_update(settings) diff --git a/src/pipecat/services/ultravox/llm.py b/src/pipecat/services/ultravox/llm.py index 933930152..094d22827 100644 --- a/src/pipecat/services/ultravox/llm.py +++ b/src/pipecat/services/ultravox/llm.py @@ -186,6 +186,7 @@ class UltravoxRealtimeLLMService(LLMService): May only be set with OneShotInputParams. **kwargs: Additional arguments passed to parent LLMService. """ + # 1. Initialize default_settings with hardcoded defaults default_settings = UltravoxRealtimeLLMSettings( model=None, temperature=None, @@ -199,6 +200,10 @@ class UltravoxRealtimeLLMService(LLMService): user_turn_completion_config=None, output_medium=None, ) + + # (No step 2/3 — params is required and not deprecated) + + # 4. Apply settings delta (canonical API, always wins) if settings is not None: default_settings.apply_update(settings) diff --git a/src/pipecat/services/whisper/base_stt.py b/src/pipecat/services/whisper/base_stt.py index a54da0c05..b6c19ab5a 100644 --- a/src/pipecat/services/whisper/base_stt.py +++ b/src/pipecat/services/whisper/base_stt.py @@ -181,24 +181,30 @@ class BaseWhisperSTTService(SegmentedSTTService): Override for your deployment. See https://github.com/pipecat-ai/stt-benchmark **kwargs: Additional arguments passed to SegmentedSTTService. """ - if model is not None: - _warn_deprecated_param("model", "BaseWhisperSTTSettings", "model") - if language is not None: - _warn_deprecated_param("language", "BaseWhisperSTTSettings", "language") - if prompt is not None: - _warn_deprecated_param("prompt", "BaseWhisperSTTSettings", "prompt") - if temperature is not None: - _warn_deprecated_param("temperature", "BaseWhisperSTTSettings", "temperature") - - _language = language or Language.EN - + # --- 1. Hardcoded defaults --- default_settings = BaseWhisperSTTSettings( - model=model, - language=self.language_to_service_language(_language), + model=None, + language=None, base_url=base_url, - prompt=prompt, - temperature=temperature, ) + + # --- 2. Deprecated direct-arg overrides --- + if model is not None: + _warn_deprecated_param("model", BaseWhisperSTTSettings, "model") + default_settings.model = model + if language is not None: + _warn_deprecated_param("language", BaseWhisperSTTSettings, "language") + default_settings.language = self.language_to_service_language(language) + if prompt is not None: + _warn_deprecated_param("prompt", BaseWhisperSTTSettings, "prompt") + default_settings.prompt = prompt + if temperature is not None: + _warn_deprecated_param("temperature", BaseWhisperSTTSettings, "temperature") + default_settings.temperature = temperature + + # --- 3. (no params object for this service) --- + + # --- 4. Settings delta (canonical API, always wins) --- if settings is not None: default_settings.apply_update(settings) @@ -209,10 +215,8 @@ class BaseWhisperSTTService(SegmentedSTTService): ) self._client = self._create_client(api_key, base_url) self._language = self._settings.language - self._prompt = self._settings.prompt if self._settings.prompt else prompt - self._temperature = ( - self._settings.temperature if self._settings.temperature else temperature - ) + self._prompt = self._settings.prompt + self._temperature = self._settings.temperature self._include_prob_metrics = include_prob_metrics self._push_empty_transcripts = push_empty_transcripts diff --git a/src/pipecat/services/whisper/stt.py b/src/pipecat/services/whisper/stt.py index 38fd287fa..17fe24c2d 100644 --- a/src/pipecat/services/whisper/stt.py +++ b/src/pipecat/services/whisper/stt.py @@ -256,30 +256,35 @@ class WhisperSTTService(SegmentedSTTService): parameters, ``settings`` values take precedence. **kwargs: Additional arguments passed to SegmentedSTTService. """ - if model is not None: - _warn_deprecated_param("model", "WhisperSTTSettings", "model") - if device is not None: - _warn_deprecated_param("device", "WhisperSTTSettings", "device") - if compute_type is not None: - _warn_deprecated_param("compute_type", "WhisperSTTSettings", "compute_type") - if no_speech_prob is not None: - _warn_deprecated_param("no_speech_prob", "WhisperSTTSettings", "no_speech_prob") - if language is not None: - _warn_deprecated_param("language", "WhisperSTTSettings", "language") - - _model = model if model is not None else Model.DISTIL_MEDIUM_EN - _device = device or "auto" - _compute_type = compute_type or "default" - _no_speech_prob = no_speech_prob if no_speech_prob is not None else 0.4 - _language = language or Language.EN - + # --- 1. Hardcoded defaults --- default_settings = WhisperSTTSettings( - model=_model if isinstance(_model, str) else _model.value, - language=_language, - device=_device, - compute_type=_compute_type, - no_speech_prob=_no_speech_prob, + model=Model.DISTIL_MEDIUM_EN.value, + language=Language.EN, + device="auto", + compute_type="default", + no_speech_prob=0.4, ) + + # --- 2. Deprecated direct-arg overrides --- + if model is not None: + _warn_deprecated_param("model", WhisperSTTSettings, "model") + default_settings.model = model if isinstance(model, str) else model.value + if device is not None: + _warn_deprecated_param("device", WhisperSTTSettings, "device") + default_settings.device = device + if compute_type is not None: + _warn_deprecated_param("compute_type", WhisperSTTSettings, "compute_type") + default_settings.compute_type = compute_type + if no_speech_prob is not None: + _warn_deprecated_param("no_speech_prob", WhisperSTTSettings, "no_speech_prob") + default_settings.no_speech_prob = no_speech_prob + if language is not None: + _warn_deprecated_param("language", WhisperSTTSettings, "language") + default_settings.language = language + + # --- 3. (no params object for this service) --- + + # --- 4. Settings delta (canonical API, always wins) --- if settings is not None: default_settings.apply_update(settings) @@ -430,27 +435,32 @@ class WhisperSTTServiceMLX(WhisperSTTService): parameters, ``settings`` values take precedence. **kwargs: Additional arguments passed to SegmentedSTTService. """ - if model is not None: - _warn_deprecated_param("model", "WhisperMLXSTTSettings", "model") - if no_speech_prob is not None: - _warn_deprecated_param("no_speech_prob", "WhisperMLXSTTSettings", "no_speech_prob") - if language is not None: - _warn_deprecated_param("language", "WhisperMLXSTTSettings", "language") - if temperature is not None: - _warn_deprecated_param("temperature", "WhisperMLXSTTSettings", "temperature") - - _model = model if model is not None else MLXModel.TINY - _no_speech_prob = no_speech_prob if no_speech_prob is not None else 0.6 - _language = language or Language.EN - _temperature = temperature if temperature is not None else 0.0 - + # --- 1. Hardcoded defaults --- default_settings = WhisperMLXSTTSettings( - model=_model if isinstance(_model, str) else _model.value, - language=_language, - no_speech_prob=_no_speech_prob, - temperature=_temperature, + model=MLXModel.TINY.value, + language=Language.EN, + no_speech_prob=0.6, + temperature=0.0, engine="mlx", ) + + # --- 2. Deprecated direct-arg overrides --- + if model is not None: + _warn_deprecated_param("model", WhisperMLXSTTSettings, "model") + default_settings.model = model if isinstance(model, str) else model.value + if no_speech_prob is not None: + _warn_deprecated_param("no_speech_prob", WhisperMLXSTTSettings, "no_speech_prob") + default_settings.no_speech_prob = no_speech_prob + if language is not None: + _warn_deprecated_param("language", WhisperMLXSTTSettings, "language") + default_settings.language = language + if temperature is not None: + _warn_deprecated_param("temperature", WhisperMLXSTTSettings, "temperature") + default_settings.temperature = temperature + + # --- 3. (no params object for this service) --- + + # --- 4. Settings delta (canonical API, always wins) --- if settings is not None: default_settings.apply_update(settings) diff --git a/src/pipecat/services/xtts/tts.py b/src/pipecat/services/xtts/tts.py index 88137172f..c5bfe629e 100644 --- a/src/pipecat/services/xtts/tts.py +++ b/src/pipecat/services/xtts/tts.py @@ -118,15 +118,20 @@ class XTTSService(TTSService): parameters, ``settings`` values take precedence. **kwargs: Additional arguments passed to parent TTSService. """ - if voice_id is not None: - _warn_deprecated_param("voice_id", "XTTSTTSSettings", "voice") - + # 1. Initialize default_settings with hardcoded defaults default_settings = XTTSTTSSettings( model=None, - voice=voice_id, + voice=None, language=self.language_to_service_language(language), base_url=base_url, ) + + # 2. Apply direct init arg overrides (deprecated) + if voice_id is not None: + _warn_deprecated_param("voice_id", XTTSTTSSettings, "voice") + default_settings.voice = voice_id + + # 4. Apply settings delta (canonical API, always wins) if settings is not None: default_settings.apply_update(settings) From f31bfcf4ece659a1be7267250ccd6d41c396a51a Mon Sep 17 00:00:00 2001 From: Mark Backman Date: Tue, 3 Mar 2026 20:29:35 -0500 Subject: [PATCH 0807/1060] Clean up CartesiaTTSSettings: separate init-only vs runtime-updatable fields Move output_container, output_encoding, output_sample_rate out of CartesiaTTSSettings into plain instance attributes since they cannot change at runtime without breaking the audio pipeline. Remove deprecated speed/emotion fields and their dead references in _build_msg() and run_tts(). Remove the from_mapping override that only existed to destructure those now-removed output format fields. --- src/pipecat/services/cartesia/tts.py | 135 ++++++++------------------- 1 file changed, 37 insertions(+), 98 deletions(-) diff --git a/src/pipecat/services/cartesia/tts.py b/src/pipecat/services/cartesia/tts.py index 2aeeefda2..71017074b 100644 --- a/src/pipecat/services/cartesia/tts.py +++ b/src/pipecat/services/cartesia/tts.py @@ -8,14 +8,13 @@ import base64 import json -import warnings from dataclasses import dataclass, field from enum import Enum -from typing import Any, AsyncGenerator, List, Literal, Mapping, Optional, Self +from typing import AsyncGenerator, List, Optional import aiohttp from loguru import logger -from pydantic import BaseModel, Field +from pydantic import BaseModel from pipecat.frames.frames import ( CancelFrame, @@ -192,35 +191,16 @@ class CartesiaTTSSettings(TTSSettings): """Settings for Cartesia TTS services. Parameters: - output_container: Audio container format (e.g. "raw"). - output_encoding: Audio encoding format (e.g. "pcm_s16le"). - output_sample_rate: Audio sample rate in Hz. - speed: Voice speed control for non-Sonic-3 models (literal values). - emotion: List of emotion controls for non-Sonic-3 models. generation_config: Generation configuration for Sonic-3 models. Includes volume, speed (numeric), and emotion (string) parameters. pronunciation_dict_id: The ID of the pronunciation dictionary to use for custom pronunciations. """ - output_container: str | _NotGiven = field(default_factory=lambda: NOT_GIVEN) - output_encoding: str | _NotGiven = field(default_factory=lambda: NOT_GIVEN) - output_sample_rate: int | _NotGiven = field(default_factory=lambda: NOT_GIVEN) - speed: Literal["slow", "normal", "fast"] | _NotGiven = field(default_factory=lambda: NOT_GIVEN) - emotion: List[str] | _NotGiven = field(default_factory=lambda: NOT_GIVEN) - generation_config: GenerationConfig | _NotGiven = field(default_factory=lambda: NOT_GIVEN) - pronunciation_dict_id: str | _NotGiven = field(default_factory=lambda: NOT_GIVEN) - - @classmethod - def from_mapping(cls, settings: Mapping[str, Any]) -> Self: - """Construct settings from a plain dict, destructuring legacy nested ``output_format``.""" - flat = dict(settings) - nested = flat.pop("output_format", None) - if isinstance(nested, dict): - flat.setdefault("output_container", nested.get("container")) - flat.setdefault("output_encoding", nested.get("encoding")) - flat.setdefault("output_sample_rate", nested.get("sample_rate")) - return super().from_mapping(flat) + generation_config: GenerationConfig | None | _NotGiven = field( + default_factory=lambda: NOT_GIVEN + ) + pronunciation_dict_id: str | None | _NotGiven = field(default_factory=lambda: NOT_GIVEN) class CartesiaTTSService(AudioContextTTSService): @@ -228,7 +208,7 @@ class CartesiaTTSService(AudioContextTTSService): Provides text-to-speech using Cartesia's streaming WebSocket API. Supports word-level timestamps, audio context management, and various voice - customization options including speed and emotion controls. + customization options including generation configuration. """ _settings: CartesiaTTSSettings @@ -238,20 +218,12 @@ class CartesiaTTSService(AudioContextTTSService): Parameters: language: Language to use for synthesis. - speed: Voice speed control for non-Sonic-3 models (literal values). - emotion: List of emotion controls for non-Sonic-3 models. - - .. deprecated:: 0.0.68 - The `emotion` parameter is deprecated and will be removed in a future version. - generation_config: Generation configuration for Sonic-3 models. Includes volume, speed (numeric), and emotion (string) parameters. pronunciation_dict_id: The ID of the pronunciation dictionary to use for custom pronunciations. """ language: Optional[Language] = Language.EN - speed: Optional[Literal["slow", "normal", "fast"]] = None - emotion: Optional[List[str]] = [] generation_config: Optional[GenerationConfig] = None pronunciation_dict_id: Optional[str] = None @@ -279,14 +251,14 @@ class CartesiaTTSService(AudioContextTTSService): api_key: Cartesia API key for authentication. voice_id: ID of the voice to use for synthesis. - .. deprecated:: 1.0.0 + .. deprecated:: 0.0.105 Use ``settings=CartesiaTTSSettings(voice=...)`` instead. cartesia_version: API version string for Cartesia service. url: WebSocket URL for Cartesia TTS API. model: TTS model to use (e.g., "sonic-3"). - .. deprecated:: 1.0.0 + .. deprecated:: 0.0.105 Use ``settings=CartesiaTTSSettings(model=...)`` instead. sample_rate: Audio sample rate. If None, uses default. @@ -294,7 +266,7 @@ class CartesiaTTSService(AudioContextTTSService): container: Audio container format. params: Additional input parameters for voice customization. - .. deprecated:: 1.0.0 + .. deprecated:: 0.0.105 Use ``settings=CartesiaTTSSettings(...)`` instead. settings: Runtime-updatable settings. When provided alongside deprecated @@ -329,9 +301,9 @@ class CartesiaTTSService(AudioContextTTSService): # 1. Initialize default_settings with hardcoded defaults default_settings = CartesiaTTSSettings( model="sonic-3", - output_container=container, - output_encoding=encoding, - output_sample_rate=0, + language=language_to_cartesia_language(Language.EN), + generation_config=None, + pronunciation_dict_id=None, ) # 2. Apply direct init arg overrides (deprecated) @@ -348,10 +320,6 @@ class CartesiaTTSService(AudioContextTTSService): if not settings: if params.language is not None: default_settings.language = self.language_to_service_language(params.language) - if params.speed is not None: - default_settings.speed = params.speed - if params.emotion is not None: - default_settings.emotion = params.emotion if params.generation_config is not None: default_settings.generation_config = params.generation_config if params.pronunciation_dict_id is not None: @@ -387,6 +355,11 @@ class CartesiaTTSService(AudioContextTTSService): self._cartesia_version = cartesia_version self._url = url + # Audio output format — init-only, not runtime-updatable + self._output_container = container + self._output_encoding = encoding + self._output_sample_rate = 0 # Set in start() from self.sample_rate + self._receive_task = None def can_generate_metrics(self) -> bool: @@ -484,17 +457,6 @@ class CartesiaTTSService(AudioContextTTSService): voice_config["mode"] = "id" voice_config["id"] = self._settings.voice - if self._settings.emotion: - with warnings.catch_warnings(): - warnings.simplefilter("always") - warnings.warn( - "The 'emotion' parameter in __experimental_controls is deprecated and will be removed in a future version.", - DeprecationWarning, - stacklevel=2, - ) - voice_config["__experimental_controls"] = {} - voice_config["__experimental_controls"]["emotion"] = self._settings.emotion - msg = { "transcript": text, "continue": continue_transcript, @@ -502,9 +464,9 @@ class CartesiaTTSService(AudioContextTTSService): "model_id": self._settings.model, "voice": voice_config, "output_format": { - "container": self._settings.output_container, - "encoding": self._settings.output_encoding, - "sample_rate": self._settings.output_sample_rate, + "container": self._output_container, + "encoding": self._output_encoding, + "sample_rate": self._output_sample_rate, }, "add_timestamps": add_timestamps, "use_original_timestamps": False if self._settings.model == "sonic" else True, @@ -513,9 +475,6 @@ class CartesiaTTSService(AudioContextTTSService): if self._settings.language: msg["language"] = self._settings.language - if self._settings.speed: - msg["speed"] = self._settings.speed - if self._settings.generation_config: msg["generation_config"] = self._settings.generation_config.model_dump( exclude_none=True @@ -533,7 +492,7 @@ class CartesiaTTSService(AudioContextTTSService): frame: The start frame containing initialization parameters. """ await super().start(frame) - self._settings.output_sample_rate = self.sample_rate + self._output_sample_rate = self.sample_rate await self._connect() async def stop(self, frame: EndFrame): @@ -728,20 +687,12 @@ class CartesiaHttpTTSService(TTSService): Parameters: language: Language to use for synthesis. - speed: Voice speed control for non-Sonic-3 models (literal values). - emotion: List of emotion controls for non-Sonic-3 models. - - .. deprecated:: 0.0.68 - The `emotion` parameter is deprecated and will be removed in a future version. - generation_config: Generation configuration for Sonic-3 models. Includes volume, speed (numeric), and emotion (string) parameters. pronunciation_dict_id: The ID of the pronunciation dictionary to use for custom pronunciations. """ language: Optional[Language] = Language.EN - speed: Optional[Literal["slow", "normal", "fast"]] = None - emotion: Optional[List[str]] = Field(default_factory=list) generation_config: Optional[GenerationConfig] = None pronunciation_dict_id: Optional[str] = None @@ -767,12 +718,12 @@ class CartesiaHttpTTSService(TTSService): api_key: Cartesia API key for authentication. voice_id: ID of the voice to use for synthesis. - .. deprecated:: 1.0.0 + .. deprecated:: 0.0.105 Use ``settings=CartesiaTTSSettings(voice=...)`` instead. model: TTS model to use (e.g., "sonic-3"). - .. deprecated:: 1.0.0 + .. deprecated:: 0.0.105 Use ``settings=CartesiaTTSSettings(model=...)`` instead. base_url: Base URL for Cartesia HTTP API. @@ -784,7 +735,7 @@ class CartesiaHttpTTSService(TTSService): container: Audio container format. params: Additional input parameters for voice customization. - .. deprecated:: 1.0.0 + .. deprecated:: 0.0.105 Use ``settings=CartesiaTTSSettings(...)`` instead. settings: Runtime-updatable settings. When provided alongside deprecated @@ -794,9 +745,9 @@ class CartesiaHttpTTSService(TTSService): # 1. Initialize default_settings with hardcoded defaults default_settings = CartesiaTTSSettings( model="sonic-3", - output_container=container, - output_encoding=encoding, - output_sample_rate=0, + language=language_to_cartesia_language(Language.EN), + generation_config=None, + pronunciation_dict_id=None, ) # 2. Apply direct init arg overrides (deprecated) @@ -813,10 +764,6 @@ class CartesiaHttpTTSService(TTSService): if not settings: if params.language is not None: default_settings.language = self.language_to_service_language(params.language) - if params.speed is not None: - default_settings.speed = params.speed - if params.emotion is not None: - default_settings.emotion = params.emotion if params.generation_config is not None: default_settings.generation_config = params.generation_config if params.pronunciation_dict_id is not None: @@ -836,6 +783,11 @@ class CartesiaHttpTTSService(TTSService): self._base_url = base_url self._cartesia_version = cartesia_version + # Audio output format — init-only, not runtime-updatable + self._output_container = container + self._output_encoding = encoding + self._output_sample_rate = 0 # Set in start() from self.sample_rate + self._session: aiohttp.ClientSession | None = aiohttp_session self._owns_session = aiohttp_session is None @@ -865,7 +817,7 @@ class CartesiaHttpTTSService(TTSService): frame: The start frame containing initialization parameters. """ await super().start(frame) - self._settings.output_sample_rate = self.sample_rate + self._output_sample_rate = self.sample_rate if self._owns_session: self._session = aiohttp.ClientSession() @@ -909,22 +861,12 @@ class CartesiaHttpTTSService(TTSService): try: voice_config = {"mode": "id", "id": self._settings.voice} - if self._settings.emotion: - with warnings.catch_warnings(): - warnings.simplefilter("always") - warnings.warn( - "The 'emotion' parameter in voice.__experimental_controls is deprecated and will be removed in a future version.", - DeprecationWarning, - stacklevel=2, - ) - voice_config["__experimental_controls"] = {"emotion": self._settings.emotion} - await self.start_ttfb_metrics() output_format = { - "container": self._settings.output_container, - "encoding": self._settings.output_encoding, - "sample_rate": self._settings.output_sample_rate, + "container": self._output_container, + "encoding": self._output_encoding, + "sample_rate": self._output_sample_rate, } payload = { @@ -937,9 +879,6 @@ class CartesiaHttpTTSService(TTSService): if self._settings.language: payload["language"] = self._settings.language - if self._settings.speed: - payload["speed"] = self._settings.speed - if self._settings.generation_config: payload["generation_config"] = self._settings.generation_config.model_dump( exclude_none=True From 1274bb2c5588f35dc69871cb21153a889d365227 Mon Sep 17 00:00:00 2001 From: Mark Backman Date: Tue, 3 Mar 2026 20:31:08 -0500 Subject: [PATCH 0808/1060] Update deprecation version to 0.0.105 --- examples/foundational/07-interruptible.py | 9 ++++--- src/pipecat/services/asyncai/tts.py | 16 ++++++------- src/pipecat/services/aws/stt.py | 4 ++-- src/pipecat/services/aws/tts.py | 6 ++--- src/pipecat/services/azure/image.py | 2 +- src/pipecat/services/azure/llm.py | 2 +- src/pipecat/services/azure/stt.py | 2 +- src/pipecat/services/azure/tts.py | 10 ++++---- src/pipecat/services/camb/tts.py | 8 +++---- src/pipecat/services/cerebras/llm.py | 2 +- src/pipecat/services/deepgram/flux/stt.py | 6 ++--- .../services/deepgram/sagemaker/tts.py | 2 +- src/pipecat/services/deepgram/tts.py | 4 ++-- src/pipecat/services/deepseek/llm.py | 2 +- src/pipecat/services/elevenlabs/stt.py | 12 +++++----- src/pipecat/services/elevenlabs/tts.py | 16 ++++++------- src/pipecat/services/fal/image.py | 2 +- src/pipecat/services/fal/stt.py | 4 ++-- src/pipecat/services/fireworks/llm.py | 2 +- src/pipecat/services/fish/tts.py | 8 +++---- src/pipecat/services/gladia/stt.py | 4 ++-- src/pipecat/services/google/image.py | 2 +- src/pipecat/services/google/llm_openai.py | 2 +- src/pipecat/services/google/stt.py | 4 ++-- src/pipecat/services/google/tts.py | 20 ++++++++-------- src/pipecat/services/gradium/stt.py | 4 ++-- src/pipecat/services/gradium/tts.py | 8 +++---- src/pipecat/services/grok/llm.py | 2 +- src/pipecat/services/groq/llm.py | 2 +- src/pipecat/services/groq/stt.py | 8 +++---- src/pipecat/services/groq/tts.py | 8 +++---- src/pipecat/services/hume/tts.py | 6 ++--- src/pipecat/services/inworld/tts.py | 16 ++++++------- src/pipecat/services/kokoro/tts.py | 6 ++--- src/pipecat/services/lmnt/tts.py | 4 ++-- src/pipecat/services/minimax/tts.py | 8 +++---- src/pipecat/services/mistral/llm.py | 2 +- src/pipecat/services/moondream/vision.py | 2 +- src/pipecat/services/neuphonic/tts.py | 12 +++++----- src/pipecat/services/nvidia/llm.py | 2 +- src/pipecat/services/nvidia/stt.py | 8 +++---- src/pipecat/services/nvidia/tts.py | 6 ++--- src/pipecat/services/ollama/llm.py | 2 +- src/pipecat/services/openai/base_llm.py | 6 ++--- src/pipecat/services/openai/image.py | 2 +- src/pipecat/services/openai/llm.py | 4 ++-- src/pipecat/services/openai/stt.py | 4 ++-- src/pipecat/services/openai/tts.py | 12 +++++----- src/pipecat/services/openpipe/llm.py | 2 +- src/pipecat/services/openrouter/llm.py | 2 +- src/pipecat/services/perplexity/llm.py | 2 +- src/pipecat/services/piper/tts.py | 4 ++-- src/pipecat/services/qwen/llm.py | 2 +- src/pipecat/services/resembleai/tts.py | 2 +- src/pipecat/services/rime/tts.py | 24 +++++++++---------- src/pipecat/services/sambanova/llm.py | 2 +- src/pipecat/services/sambanova/stt.py | 8 +++---- src/pipecat/services/sarvam/stt.py | 6 ++--- src/pipecat/services/sarvam/tts.py | 16 ++++++------- src/pipecat/services/soniox/stt.py | 6 ++--- src/pipecat/services/speechmatics/stt.py | 2 +- src/pipecat/services/speechmatics/tts.py | 6 ++--- src/pipecat/services/together/llm.py | 2 +- src/pipecat/services/whisper/base_stt.py | 8 +++---- src/pipecat/services/whisper/stt.py | 18 +++++++------- src/pipecat/services/xtts/tts.py | 2 +- 66 files changed, 199 insertions(+), 200 deletions(-) diff --git a/examples/foundational/07-interruptible.py b/examples/foundational/07-interruptible.py index 3f97e5028..b8a334ec0 100644 --- a/examples/foundational/07-interruptible.py +++ b/examples/foundational/07-interruptible.py @@ -21,7 +21,7 @@ from pipecat.processors.aggregators.llm_response_universal import ( ) from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport -from pipecat.services.cartesia.tts import CartesiaTTSService +from pipecat.services.cartesia.tts import CartesiaTTSService, CartesiaTTSSettings from pipecat.services.deepgram.stt import DeepgramSTTService from pipecat.services.openai.llm import OpenAILLMService from pipecat.services.tts_service import TextAggregationMode @@ -56,10 +56,9 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): tts = CartesiaTTSService( api_key=os.getenv("CARTESIA_API_KEY"), - voice_id="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady - # Alternatively, you can use TextAggregationMode.TOKEN to stream tokens instead of - # sentencesfor faster response times. - # text_aggregation_mode=TextAggregationMode.TOKEN, + settings=CartesiaTTSSettings( + voice="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady + ), ) llm = OpenAILLMService( diff --git a/src/pipecat/services/asyncai/tts.py b/src/pipecat/services/asyncai/tts.py index ef5c95bfe..d4e2eabdc 100644 --- a/src/pipecat/services/asyncai/tts.py +++ b/src/pipecat/services/asyncai/tts.py @@ -110,7 +110,7 @@ class AsyncAITTSService(AudioContextTTSService): class InputParams(BaseModel): """Input parameters for Async TTS configuration. - .. deprecated:: 1.0.0 + .. deprecated:: 0.0.105 Use ``AsyncAITTSSettings`` directly via the ``settings`` parameter instead. Parameters: @@ -143,14 +143,14 @@ class AsyncAITTSService(AudioContextTTSService): voice_id: UUID of the voice to use for synthesis. See docs for a full list: https://docs.async.com/list-voices-16699698e0 - .. deprecated:: 1.0.0 + .. deprecated:: 0.0.105 Use ``settings=AsyncAITTSSettings(voice=...)`` instead. version: Async API version. url: WebSocket URL for Async TTS API. model: TTS model to use (e.g., "async_flash_v1.0"). - .. deprecated:: 1.0.0 + .. deprecated:: 0.0.105 Use ``settings=AsyncAITTSSettings(model=...)`` instead. sample_rate: Audio sample rate. @@ -158,7 +158,7 @@ class AsyncAITTSService(AudioContextTTSService): container: Audio container format. params: Additional input parameters for voice customization. - .. deprecated:: 1.0.0 + .. deprecated:: 0.0.105 Use ``settings=AsyncAITTSSettings(...)`` instead. settings: Runtime-updatable settings. When provided alongside deprecated @@ -508,7 +508,7 @@ class AsyncAIHttpTTSService(TTSService): class InputParams(BaseModel): """Input parameters for Async API. - .. deprecated:: 1.0.0 + .. deprecated:: 0.0.105 Use ``AsyncAITTSSettings`` directly via the ``settings`` parameter instead. Parameters: @@ -539,13 +539,13 @@ class AsyncAIHttpTTSService(TTSService): api_key: Async API key. voice_id: ID of the voice to use for synthesis. - .. deprecated:: 1.0.0 + .. deprecated:: 0.0.105 Use ``settings=AsyncAITTSSettings(voice=...)`` instead. aiohttp_session: An aiohttp session for making HTTP requests. model: TTS model to use (e.g., "async_flash_v1.0"). - .. deprecated:: 1.0.0 + .. deprecated:: 0.0.105 Use ``settings=AsyncAITTSSettings(model=...)`` instead. url: Base URL for Async API. @@ -555,7 +555,7 @@ class AsyncAIHttpTTSService(TTSService): container: Audio container format. params: Additional input parameters for voice customization. - .. deprecated:: 1.0.0 + .. deprecated:: 0.0.105 Use ``settings=AsyncAITTSSettings(...)`` instead. settings: Runtime-updatable settings. When provided alongside deprecated diff --git a/src/pipecat/services/aws/stt.py b/src/pipecat/services/aws/stt.py index 950624fbf..451c8a695 100644 --- a/src/pipecat/services/aws/stt.py +++ b/src/pipecat/services/aws/stt.py @@ -96,12 +96,12 @@ class AWSTranscribeSTTService(WebsocketSTTService): region: AWS region for the service. sample_rate: Audio sample rate in Hz. Must be 8000 or 16000. - .. deprecated:: 1.0.0 + .. deprecated:: 0.0.105 Use ``settings=AWSTranscribeSTTSettings(sample_rate=...)`` instead. language: Language for transcription. - .. deprecated:: 1.0.0 + .. deprecated:: 0.0.105 Use ``settings=AWSTranscribeSTTSettings(language=...)`` instead. settings: Runtime-updatable settings. When provided alongside deprecated diff --git a/src/pipecat/services/aws/tts.py b/src/pipecat/services/aws/tts.py index f248db27a..043fc264e 100644 --- a/src/pipecat/services/aws/tts.py +++ b/src/pipecat/services/aws/tts.py @@ -155,7 +155,7 @@ class AWSPollyTTSService(TTSService): class InputParams(BaseModel): """Input parameters for AWS Polly TTS configuration. - .. deprecated:: 1.0.0 + .. deprecated:: 0.0.105 Use ``AWSPollyTTSSettings`` directly via the ``settings`` parameter instead. Parameters: @@ -196,13 +196,13 @@ class AWSPollyTTSService(TTSService): region: AWS region for Polly service. Defaults to 'us-east-1'. voice_id: Voice ID to use for synthesis. Defaults to 'Joanna'. - .. deprecated:: 1.0.0 + .. deprecated:: 0.0.105 Use ``settings=AWSPollyTTSSettings(voice=...)`` instead. sample_rate: Audio sample rate. If None, uses service default. params: Additional input parameters for voice customization. - .. deprecated:: 1.0.0 + .. deprecated:: 0.0.105 Use ``settings=AWSPollyTTSSettings(...)`` instead. settings: Runtime-updatable settings. When provided alongside deprecated diff --git a/src/pipecat/services/azure/image.py b/src/pipecat/services/azure/image.py index ca58644f2..2a1286c78 100644 --- a/src/pipecat/services/azure/image.py +++ b/src/pipecat/services/azure/image.py @@ -59,7 +59,7 @@ class AzureImageGenServiceREST(ImageGenService): endpoint: Azure OpenAI endpoint URL. model: The image generation model to use. - .. deprecated:: 1.0.0 + .. deprecated:: 0.0.105 Use ``settings=AzureImageGenSettings(model=...)`` instead. aiohttp_session: Shared aiohttp session for HTTP requests. diff --git a/src/pipecat/services/azure/llm.py b/src/pipecat/services/azure/llm.py index 734a0bacf..19a31320e 100644 --- a/src/pipecat/services/azure/llm.py +++ b/src/pipecat/services/azure/llm.py @@ -40,7 +40,7 @@ class AzureLLMService(OpenAILLMService): endpoint: The Azure endpoint URL. model: The model identifier to use. Defaults to "gpt-4o". - .. deprecated:: 1.0.0 + .. deprecated:: 0.0.105 Use ``settings=OpenAILLMSettings(model=...)`` instead. api_version: Azure API version. Defaults to "2024-09-01-preview". diff --git a/src/pipecat/services/azure/stt.py b/src/pipecat/services/azure/stt.py index 66f871ad3..2527f0bb0 100644 --- a/src/pipecat/services/azure/stt.py +++ b/src/pipecat/services/azure/stt.py @@ -94,7 +94,7 @@ class AzureSTTService(STTService): region: Azure region for the Speech service (e.g., 'eastus'). language: Language for speech recognition. Defaults to English (US). - .. deprecated:: 1.0.0 + .. deprecated:: 0.0.105 Use ``settings=AzureSTTSettings(language=...)`` instead. sample_rate: Audio sample rate in Hz. If None, uses service default. diff --git a/src/pipecat/services/azure/tts.py b/src/pipecat/services/azure/tts.py index 3a67cb2ff..f4aa85dbc 100644 --- a/src/pipecat/services/azure/tts.py +++ b/src/pipecat/services/azure/tts.py @@ -115,7 +115,7 @@ class AzureBaseTTSService: class InputParams(BaseModel): """Input parameters for Azure TTS voice configuration. - .. deprecated:: 1.0.0 + .. deprecated:: 0.0.105 Use ``settings=AzureTTSSettings(...)`` instead. Parameters: @@ -271,13 +271,13 @@ class AzureTTSService(TTSService, AzureBaseTTSService): region: Azure region identifier (e.g., "eastus", "westus2"). voice: Voice name to use for synthesis. - .. deprecated:: 1.0.0 + .. deprecated:: 0.0.105 Use ``settings=AzureTTSSettings(voice=...)`` instead. sample_rate: Audio sample rate in Hz. If None, uses service default. params: Voice and synthesis parameters configuration. - .. deprecated:: 1.0.0 + .. deprecated:: 0.0.105 Use ``settings=AzureTTSSettings(...)`` instead. settings: Runtime-updatable settings. When provided alongside deprecated @@ -782,13 +782,13 @@ class AzureHttpTTSService(TTSService, AzureBaseTTSService): region: Azure region identifier (e.g., "eastus", "westus2"). voice: Voice name to use for synthesis. - .. deprecated:: 1.0.0 + .. deprecated:: 0.0.105 Use ``settings=AzureTTSSettings(voice=...)`` instead. sample_rate: Audio sample rate in Hz. If None, uses service default. params: Voice and synthesis parameters configuration. - .. deprecated:: 1.0.0 + .. deprecated:: 0.0.105 Use ``settings=AzureTTSSettings(...)`` instead. settings: Runtime-updatable settings. When provided alongside deprecated diff --git a/src/pipecat/services/camb/tts.py b/src/pipecat/services/camb/tts.py index 9a1b753a6..ef007181e 100644 --- a/src/pipecat/services/camb/tts.py +++ b/src/pipecat/services/camb/tts.py @@ -175,7 +175,7 @@ class CambTTSService(TTSService): class InputParams(BaseModel): """Input parameters for Camb.ai TTS configuration. - .. deprecated:: 1.0.0 + .. deprecated:: 0.0.105 Use ``settings=CambTTSSettings(...)`` instead. Parameters: @@ -210,12 +210,12 @@ class CambTTSService(TTSService): api_key: Camb.ai API key for authentication. voice_id: Voice ID to use. - .. deprecated:: 1.0.0 + .. deprecated:: 0.0.105 Use ``settings=CambTTSSettings(voice=...)`` instead. model: TTS model to use. Options: "mars-flash" (fast), "mars-pro" (high quality). - .. deprecated:: 1.0.0 + .. deprecated:: 0.0.105 Use ``settings=CambTTSSettings(model=...)`` instead. timeout: Request timeout in seconds. Defaults to 60.0 (minimum recommended @@ -223,7 +223,7 @@ class CambTTSService(TTSService): sample_rate: Audio sample rate in Hz. If None, uses model-specific default. params: Additional voice parameters. If None, uses defaults. - .. deprecated:: 1.0.0 + .. deprecated:: 0.0.105 Use ``settings=CambTTSSettings(...)`` instead. settings: Runtime-updatable settings. When provided alongside deprecated diff --git a/src/pipecat/services/cerebras/llm.py b/src/pipecat/services/cerebras/llm.py index 98fbfe0e3..c952b9552 100644 --- a/src/pipecat/services/cerebras/llm.py +++ b/src/pipecat/services/cerebras/llm.py @@ -39,7 +39,7 @@ class CerebrasLLMService(OpenAILLMService): base_url: The base URL for Cerebras API. Defaults to "https://api.cerebras.ai/v1". model: The model identifier to use. Defaults to "gpt-oss-120b". - .. deprecated:: 1.0.0 + .. deprecated:: 0.0.105 Use ``settings=OpenAILLMSettings(model=...)`` instead. settings: Runtime-updatable settings. When provided alongside deprecated diff --git a/src/pipecat/services/deepgram/flux/stt.py b/src/pipecat/services/deepgram/flux/stt.py index 8ddd2ef0d..ae5364f60 100644 --- a/src/pipecat/services/deepgram/flux/stt.py +++ b/src/pipecat/services/deepgram/flux/stt.py @@ -124,7 +124,7 @@ class DeepgramFluxSTTService(WebsocketSTTService): class InputParams(BaseModel): """Configuration parameters for Deepgram Flux API. - .. deprecated:: 1.0.0 + .. deprecated:: 0.0.105 Use ``settings=DeepgramFluxSTTSettings(...)`` instead. Parameters: @@ -173,14 +173,14 @@ class DeepgramFluxSTTService(WebsocketSTTService): sample_rate: Audio sample rate in Hz. If None, uses the rate from params or 16000. model: Deepgram Flux model to use for transcription. - .. deprecated:: 1.0.0 + .. deprecated:: 0.0.105 Use ``settings=DeepgramFluxSTTSettings(model=...)`` instead. flux_encoding: Audio encoding format required by Flux API. Must be "linear16". Raw signed little-endian 16-bit PCM encoding. params: InputParams instance containing detailed API configuration options. - .. deprecated:: 1.0.0 + .. deprecated:: 0.0.105 Use ``settings=DeepgramFluxSTTSettings(...)`` instead. should_interrupt: Determine whether the bot should be interrupted when Flux detects that the user is speaking. diff --git a/src/pipecat/services/deepgram/sagemaker/tts.py b/src/pipecat/services/deepgram/sagemaker/tts.py index 62cd25188..9457cc1db 100644 --- a/src/pipecat/services/deepgram/sagemaker/tts.py +++ b/src/pipecat/services/deepgram/sagemaker/tts.py @@ -92,7 +92,7 @@ class DeepgramSageMakerTTSService(TTSService): region: AWS region where the endpoint is deployed (e.g., "us-east-2"). voice: Voice model to use for synthesis. Defaults to "aura-2-helena-en". - .. deprecated:: 1.0.0 + .. deprecated:: 0.0.105 Use ``settings=DeepgramSageMakerTTSSettings(voice=...)`` instead. sample_rate: Audio sample rate in Hz. If None, uses the value from StartFrame. diff --git a/src/pipecat/services/deepgram/tts.py b/src/pipecat/services/deepgram/tts.py index 98a615f9b..b54cd23dc 100644 --- a/src/pipecat/services/deepgram/tts.py +++ b/src/pipecat/services/deepgram/tts.py @@ -85,7 +85,7 @@ class DeepgramTTSService(WebsocketTTSService): api_key: Deepgram API key for authentication. voice: Voice model to use for synthesis. - .. deprecated:: 1.0.0 + .. deprecated:: 0.0.105 Use ``settings=DeepgramTTSSettings(voice=...)`` instead. base_url: WebSocket base URL for Deepgram API. Defaults to "wss://api.deepgram.com". @@ -409,7 +409,7 @@ class DeepgramHttpTTSService(TTSService): api_key: Deepgram API key for authentication. voice: Voice model to use for synthesis. - .. deprecated:: 1.0.0 + .. deprecated:: 0.0.105 Use ``settings=DeepgramTTSSettings(voice=...)`` instead. aiohttp_session: Shared aiohttp session for HTTP requests with connection pooling. diff --git a/src/pipecat/services/deepseek/llm.py b/src/pipecat/services/deepseek/llm.py index c383f5609..3d7c67e2a 100644 --- a/src/pipecat/services/deepseek/llm.py +++ b/src/pipecat/services/deepseek/llm.py @@ -39,7 +39,7 @@ class DeepSeekLLMService(OpenAILLMService): base_url: The base URL for DeepSeek API. Defaults to "https://api.deepseek.com/v1". model: The model identifier to use. Defaults to "deepseek-chat". - .. deprecated:: 1.0.0 + .. deprecated:: 0.0.105 Use ``settings=OpenAILLMSettings(model=...)`` instead. settings: Runtime-updatable settings. When provided alongside deprecated diff --git a/src/pipecat/services/elevenlabs/stt.py b/src/pipecat/services/elevenlabs/stt.py index d93f95332..2d75abff9 100644 --- a/src/pipecat/services/elevenlabs/stt.py +++ b/src/pipecat/services/elevenlabs/stt.py @@ -228,7 +228,7 @@ class ElevenLabsSTTService(SegmentedSTTService): class InputParams(BaseModel): """Configuration parameters for ElevenLabs STT API. - .. deprecated:: 1.0.0 + .. deprecated:: 0.0.105 Use ``settings=ElevenLabsSTTSettings(...)`` instead. Parameters: @@ -260,13 +260,13 @@ class ElevenLabsSTTService(SegmentedSTTService): base_url: Base URL for ElevenLabs API. model: Model ID for transcription. - .. deprecated:: 1.0.0 + .. deprecated:: 0.0.105 Use ``settings=ElevenLabsSTTSettings(model=...)`` instead. sample_rate: Audio sample rate in Hz. If not provided, uses the pipeline's rate. params: Configuration parameters for the STT service. - .. deprecated:: 1.0.0 + .. deprecated:: 0.0.105 Use ``settings=ElevenLabsSTTSettings(...)`` instead. settings: Runtime-updatable settings. When provided alongside deprecated @@ -461,7 +461,7 @@ class ElevenLabsRealtimeSTTService(WebsocketSTTService): class InputParams(BaseModel): """Configuration parameters for ElevenLabs Realtime STT API. - .. deprecated:: 1.0.0 + .. deprecated:: 0.0.105 Use ``settings=ElevenLabsRealtimeSTTSettings(...)`` instead. Parameters: @@ -509,13 +509,13 @@ class ElevenLabsRealtimeSTTService(WebsocketSTTService): base_url: Base URL for ElevenLabs WebSocket API. model: Model ID for transcription. - .. deprecated:: 1.0.0 + .. deprecated:: 0.0.105 Use ``settings=ElevenLabsRealtimeSTTSettings(model=...)`` instead. sample_rate: Audio sample rate in Hz. If not provided, uses the pipeline's rate. params: Configuration parameters for the STT service. - .. deprecated:: 1.0.0 + .. deprecated:: 0.0.105 Use ``settings=ElevenLabsRealtimeSTTSettings(...)`` instead. settings: Runtime-updatable settings. When provided alongside deprecated diff --git a/src/pipecat/services/elevenlabs/tts.py b/src/pipecat/services/elevenlabs/tts.py index 3cec12431..2447427ab 100644 --- a/src/pipecat/services/elevenlabs/tts.py +++ b/src/pipecat/services/elevenlabs/tts.py @@ -331,7 +331,7 @@ class ElevenLabsTTSService(AudioContextTTSService): class InputParams(BaseModel): """Input parameters for ElevenLabs TTS configuration. - .. deprecated:: 1.0.0 + .. deprecated:: 0.0.105 Use ``settings=ElevenLabsTTSSettings(...)`` instead. Parameters: @@ -381,12 +381,12 @@ class ElevenLabsTTSService(AudioContextTTSService): api_key: ElevenLabs API key for authentication. voice_id: ID of the voice to use for synthesis. - .. deprecated:: 1.0.0 + .. deprecated:: 0.0.105 Use ``settings=ElevenLabsTTSSettings(voice=...)`` instead. model: TTS model to use (e.g., "eleven_turbo_v2_5"). - .. deprecated:: 1.0.0 + .. deprecated:: 0.0.105 Use ``settings=ElevenLabsTTSSettings(model=...)`` instead. url: WebSocket URL for ElevenLabs TTS API. @@ -395,7 +395,7 @@ class ElevenLabsTTSService(AudioContextTTSService): locators to use. params: Additional input parameters for voice customization. - .. deprecated:: 1.0.0 + .. deprecated:: 0.0.105 Use ``settings=ElevenLabsTTSSettings(...)`` instead. settings: Runtime-updatable settings. When provided alongside deprecated @@ -921,7 +921,7 @@ class ElevenLabsHttpTTSService(TTSService): class InputParams(BaseModel): """Input parameters for ElevenLabs HTTP TTS configuration. - .. deprecated:: 1.0.0 + .. deprecated:: 0.0.105 Use ``settings=ElevenLabsHttpTTSSettings(...)`` instead. Parameters: @@ -968,13 +968,13 @@ class ElevenLabsHttpTTSService(TTSService): api_key: ElevenLabs API key for authentication. voice_id: ID of the voice to use for synthesis. - .. deprecated:: 1.0.0 + .. deprecated:: 0.0.105 Use ``settings=ElevenLabsHttpTTSSettings(voice=...)`` instead. aiohttp_session: aiohttp ClientSession for HTTP requests. model: TTS model to use (e.g., "eleven_turbo_v2_5"). - .. deprecated:: 1.0.0 + .. deprecated:: 0.0.105 Use ``settings=ElevenLabsHttpTTSSettings(model=...)`` instead. base_url: Base URL for ElevenLabs HTTP API. @@ -983,7 +983,7 @@ class ElevenLabsHttpTTSService(TTSService): locators to use. params: Additional input parameters for voice customization. - .. deprecated:: 1.0.0 + .. deprecated:: 0.0.105 Use ``settings=ElevenLabsHttpTTSSettings(...)`` instead. settings: Runtime-updatable settings. When provided alongside deprecated diff --git a/src/pipecat/services/fal/image.py b/src/pipecat/services/fal/image.py index 2c36c2208..342aaa4a9 100644 --- a/src/pipecat/services/fal/image.py +++ b/src/pipecat/services/fal/image.py @@ -80,7 +80,7 @@ class FalImageGenService(ImageGenService): aiohttp_session: HTTP client session for downloading generated images. model: The Fal.ai model to use for generation. Defaults to "fal-ai/fast-sdxl". - .. deprecated:: 1.0.0 + .. deprecated:: 0.0.105 Use ``settings=FalImageGenSettings(model=...)`` instead. key: Optional API key for Fal.ai. If provided, sets FAL_KEY environment variable. diff --git a/src/pipecat/services/fal/stt.py b/src/pipecat/services/fal/stt.py index ea9f69a18..4428599b1 100644 --- a/src/pipecat/services/fal/stt.py +++ b/src/pipecat/services/fal/stt.py @@ -169,7 +169,7 @@ class FalSTTService(SegmentedSTTService): class InputParams(BaseModel): """Configuration parameters for Fal's Wizper API. - .. deprecated:: 1.0.0 + .. deprecated:: 0.0.105 Use ``settings=FalSTTSettings(...)`` instead. Parameters: @@ -204,7 +204,7 @@ class FalSTTService(SegmentedSTTService): sample_rate: Audio sample rate in Hz. If not provided, uses the pipeline's rate. params: Configuration parameters for the Wizper API. - .. deprecated:: 1.0.0 + .. deprecated:: 0.0.105 Use ``settings=FalSTTSettings(...)`` instead. settings: Runtime-updatable settings. When provided alongside deprecated diff --git a/src/pipecat/services/fireworks/llm.py b/src/pipecat/services/fireworks/llm.py index cb5a0cf39..e7866c55d 100644 --- a/src/pipecat/services/fireworks/llm.py +++ b/src/pipecat/services/fireworks/llm.py @@ -38,7 +38,7 @@ class FireworksLLMService(OpenAILLMService): api_key: The API key for accessing Fireworks AI. model: The model identifier to use. Defaults to "accounts/fireworks/models/firefunction-v2". - .. deprecated:: 1.0.0 + .. deprecated:: 0.0.105 Use ``settings=OpenAILLMSettings(model=...)`` instead. base_url: The base URL for Fireworks API. Defaults to "https://api.fireworks.ai/inference/v1". diff --git a/src/pipecat/services/fish/tts.py b/src/pipecat/services/fish/tts.py index 3d4412186..af02b4e99 100644 --- a/src/pipecat/services/fish/tts.py +++ b/src/pipecat/services/fish/tts.py @@ -95,7 +95,7 @@ class FishAudioTTSService(InterruptibleTTSService): class InputParams(BaseModel): """Input parameters for Fish Audio TTS configuration. - .. deprecated:: 1.0.0 + .. deprecated:: 0.0.105 Use ``settings=FishAudioTTSSettings(...)`` instead. Parameters: @@ -131,7 +131,7 @@ class FishAudioTTSService(InterruptibleTTSService): api_key: Fish Audio API key for authentication. reference_id: Reference ID of the voice model to use for synthesis. - .. deprecated:: 1.0.0 + .. deprecated:: 0.0.105 Use ``settings=FishAudioTTSSettings(voice=...)`` instead. model: Deprecated. Reference ID of the voice model to use for synthesis. @@ -142,14 +142,14 @@ class FishAudioTTSService(InterruptibleTTSService): model_id: Specify which Fish Audio TTS model to use (e.g. "s1"). - .. deprecated:: 1.0.0 + .. deprecated:: 0.0.105 Use ``settings=FishAudioTTSSettings(model=...)`` instead. output_format: Audio output format. Defaults to "pcm". sample_rate: Audio sample rate. If None, uses default. params: Additional input parameters for voice customization. - .. deprecated:: 1.0.0 + .. deprecated:: 0.0.105 Use ``settings=FishAudioTTSSettings(...)`` instead. settings: Runtime-updatable settings. When provided alongside deprecated diff --git a/src/pipecat/services/gladia/stt.py b/src/pipecat/services/gladia/stt.py index a12829b0d..44e5bbd9c 100644 --- a/src/pipecat/services/gladia/stt.py +++ b/src/pipecat/services/gladia/stt.py @@ -272,12 +272,12 @@ class GladiaSTTService(WebsocketSTTService): sample_rate: Audio sample rate in Hz. If None, uses service default. model: Model to use for transcription. - .. deprecated:: 1.0.0 + .. deprecated:: 0.0.105 Use ``settings=GladiaSTTSettings(model=...)`` instead. params: Additional configuration parameters for Gladia service. - .. deprecated:: 1.0.0 + .. deprecated:: 0.0.105 Use ``settings=GladiaSTTSettings(...)`` instead. max_buffer_size: Maximum size of audio buffer in bytes. Defaults to 20MB. diff --git a/src/pipecat/services/google/image.py b/src/pipecat/services/google/image.py index 09ec61554..d15d5d0ed 100644 --- a/src/pipecat/services/google/image.py +++ b/src/pipecat/services/google/image.py @@ -82,7 +82,7 @@ class GoogleImageGenService(ImageGenService): api_key: Google AI API key for authentication. params: Configuration parameters for image generation. - .. deprecated:: 1.0.0 + .. deprecated:: 0.0.105 Use ``settings=GoogleImageGenSettings(model=...)`` instead. http_options: HTTP options for the client. diff --git a/src/pipecat/services/google/llm_openai.py b/src/pipecat/services/google/llm_openai.py index 4705e8f68..b33eefd9a 100644 --- a/src/pipecat/services/google/llm_openai.py +++ b/src/pipecat/services/google/llm_openai.py @@ -66,7 +66,7 @@ class GoogleLLMOpenAIBetaService(OpenAILLMService): base_url: Base URL for Google's OpenAI-compatible API. model: Google model name to use (e.g., "gemini-2.0-flash"). - .. deprecated:: 1.0.0 + .. deprecated:: 0.0.105 Use ``settings=OpenAILLMSettings(model=...)`` instead. settings: Runtime-updatable settings. When provided alongside deprecated diff --git a/src/pipecat/services/google/stt.py b/src/pipecat/services/google/stt.py index 5415a5403..376e74a6d 100644 --- a/src/pipecat/services/google/stt.py +++ b/src/pipecat/services/google/stt.py @@ -425,7 +425,7 @@ class GoogleSTTService(STTService): class InputParams(BaseModel): """Configuration parameters for Google Speech-to-Text. - .. deprecated:: 1.0.0 + .. deprecated:: 0.0.105 Use ``settings=GoogleSTTSettings(...)`` instead. Parameters: @@ -500,7 +500,7 @@ class GoogleSTTService(STTService): sample_rate: Audio sample rate in Hertz. params: Configuration parameters for the service. - .. deprecated:: 1.0.0 + .. deprecated:: 0.0.105 Use ``settings=GoogleSTTSettings(...)`` instead. settings: Runtime-updatable settings. When provided alongside deprecated diff --git a/src/pipecat/services/google/tts.py b/src/pipecat/services/google/tts.py index 6b17caed5..22ba47821 100644 --- a/src/pipecat/services/google/tts.py +++ b/src/pipecat/services/google/tts.py @@ -566,7 +566,7 @@ class GoogleHttpTTSService(TTSService): class InputParams(BaseModel): """Input parameters for Google HTTP TTS voice customization. - .. deprecated:: 1.0.0 + .. deprecated:: 0.0.105 Use ``GoogleHttpTTSSettings`` directly via the ``settings`` parameter instead. Parameters: @@ -609,13 +609,13 @@ class GoogleHttpTTSService(TTSService): location: Google Cloud location for regional endpoint (e.g., "us-central1"). voice_id: Google TTS voice identifier (e.g., "en-US-Standard-A"). - .. deprecated:: 1.0.0 + .. deprecated:: 0.0.105 Use ``settings=GoogleHttpTTSSettings(voice=...)`` instead. sample_rate: Audio sample rate in Hz. If None, uses default. params: Voice customization parameters including pitch, rate, volume, etc. - .. deprecated:: 1.0.0 + .. deprecated:: 0.0.105 Use ``settings=GoogleHttpTTSSettings(...)`` instead. settings: Runtime-updatable settings. When provided alongside deprecated @@ -1029,7 +1029,7 @@ class GoogleTTSService(GoogleBaseTTSService): class InputParams(BaseModel): """Input parameters for Google streaming TTS configuration. - .. deprecated:: 1.0.0 + .. deprecated:: 0.0.105 Use ``GoogleStreamTTSSettings`` directly via the ``settings`` parameter instead. Parameters: @@ -1061,14 +1061,14 @@ class GoogleTTSService(GoogleBaseTTSService): location: Google Cloud location for regional endpoint (e.g., "us-central1"). voice_id: Google TTS voice identifier (e.g., "en-US-Chirp3-HD-Charon"). - .. deprecated:: 1.0.0 + .. deprecated:: 0.0.105 Use ``settings=GoogleStreamTTSSettings(voice=...)`` instead. voice_cloning_key: The voice cloning key for Chirp 3 custom voices. sample_rate: Audio sample rate in Hz. If None, uses default. params: Language configuration parameters. - .. deprecated:: 1.0.0 + .. deprecated:: 0.0.105 Use ``settings=GoogleStreamTTSSettings(...)`` instead. settings: Runtime-updatable settings. When provided alongside deprecated @@ -1242,7 +1242,7 @@ class GeminiTTSService(GoogleBaseTTSService): class InputParams(BaseModel): """Input parameters for Gemini TTS configuration. - .. deprecated:: 1.0.0 + .. deprecated:: 0.0.105 Use ``GeminiTTSSettings`` directly via the ``settings`` parameter instead. Parameters: @@ -1283,7 +1283,7 @@ class GeminiTTSService(GoogleBaseTTSService): model: Gemini TTS model to use. Must be a TTS model like "gemini-2.5-flash-tts" or "gemini-2.5-pro-tts". - .. deprecated:: 1.0.0 + .. deprecated:: 0.0.105 Use ``settings=GeminiTTSSettings(model=...)`` instead. credentials: JSON string containing Google Cloud service account credentials. @@ -1291,13 +1291,13 @@ class GeminiTTSService(GoogleBaseTTSService): location: Google Cloud location for regional endpoint (e.g., "us-central1"). voice_id: Voice name from the available Gemini voices. - .. deprecated:: 1.0.0 + .. deprecated:: 0.0.105 Use ``settings=GeminiTTSSettings(voice=...)`` instead. sample_rate: Audio sample rate in Hz. If None, uses Google's default 24kHz. params: TTS configuration parameters. - .. deprecated:: 1.0.0 + .. deprecated:: 0.0.105 Use ``settings=GeminiTTSSettings(...)`` instead. settings: Runtime-updatable settings. When provided alongside deprecated diff --git a/src/pipecat/services/gradium/stt.py b/src/pipecat/services/gradium/stt.py index 51ac8a7cd..fff58d87a 100644 --- a/src/pipecat/services/gradium/stt.py +++ b/src/pipecat/services/gradium/stt.py @@ -91,7 +91,7 @@ class GradiumSTTService(WebsocketSTTService): class InputParams(BaseModel): """Configuration parameters for Gradium STT API. - .. deprecated:: 1.0.0 + .. deprecated:: 0.0.105 Use ``settings=GradiumSTTSettings(...)`` instead. Parameters: @@ -125,7 +125,7 @@ class GradiumSTTService(WebsocketSTTService): api_endpoint_base_url: WebSocket endpoint URL. Defaults to Gradium's streaming endpoint. params: Configuration parameters for language and delay settings. - .. deprecated:: 1.0.0 + .. deprecated:: 0.0.105 Use ``settings=GradiumSTTSettings(...)`` instead. json_config: Optional JSON configuration string for additional model settings. diff --git a/src/pipecat/services/gradium/tts.py b/src/pipecat/services/gradium/tts.py index b3b9b50ca..3befb4505 100644 --- a/src/pipecat/services/gradium/tts.py +++ b/src/pipecat/services/gradium/tts.py @@ -57,7 +57,7 @@ class GradiumTTSService(AudioContextTTSService): class InputParams(BaseModel): """Configuration parameters for Gradium TTS service. - .. deprecated:: 1.0.0 + .. deprecated:: 0.0.105 Use ``GradiumTTSSettings`` directly via the ``settings`` parameter instead. Parameters: @@ -84,19 +84,19 @@ class GradiumTTSService(AudioContextTTSService): api_key: Gradium API key for authentication. voice_id: the voice identifier. - .. deprecated:: 1.0.0 + .. deprecated:: 0.0.105 Use ``settings=GradiumTTSSettings(voice=...)`` instead. url: Gradium websocket API endpoint. model: Model ID to use for synthesis. - .. deprecated:: 1.0.0 + .. deprecated:: 0.0.105 Use ``settings=GradiumTTSSettings(model=...)`` instead. json_config: Optional JSON configuration string for additional model settings. params: Additional configuration parameters. - .. deprecated:: 1.0.0 + .. deprecated:: 0.0.105 Use ``settings=GradiumTTSSettings(...)`` instead. settings: Runtime-updatable settings. When provided alongside deprecated diff --git a/src/pipecat/services/grok/llm.py b/src/pipecat/services/grok/llm.py index f552f059a..98c925ac5 100644 --- a/src/pipecat/services/grok/llm.py +++ b/src/pipecat/services/grok/llm.py @@ -95,7 +95,7 @@ class GrokLLMService(OpenAILLMService): base_url: The base URL for Grok API. Defaults to "https://api.x.ai/v1". model: The model identifier to use. Defaults to "grok-3-beta". - .. deprecated:: 1.0.0 + .. deprecated:: 0.0.105 Use ``settings=OpenAILLMSettings(model=...)`` instead. settings: Runtime-updatable settings. When provided alongside deprecated diff --git a/src/pipecat/services/groq/llm.py b/src/pipecat/services/groq/llm.py index f88d5a877..c69776ad0 100644 --- a/src/pipecat/services/groq/llm.py +++ b/src/pipecat/services/groq/llm.py @@ -38,7 +38,7 @@ class GroqLLMService(OpenAILLMService): base_url: The base URL for Groq API. Defaults to "https://api.groq.com/openai/v1". model: The model identifier to use. Defaults to "llama-3.3-70b-versatile". - .. deprecated:: 1.0.0 + .. deprecated:: 0.0.105 Use ``settings=OpenAILLMSettings(model=...)`` instead. settings: Runtime-updatable settings. When provided alongside deprecated diff --git a/src/pipecat/services/groq/stt.py b/src/pipecat/services/groq/stt.py index ac6a4325c..b875f63d4 100644 --- a/src/pipecat/services/groq/stt.py +++ b/src/pipecat/services/groq/stt.py @@ -43,24 +43,24 @@ class GroqSTTService(BaseWhisperSTTService): Args: model: Whisper model to use. - .. deprecated:: 1.0.0 + .. deprecated:: 0.0.105 Use ``settings=BaseWhisperSTTSettings(model=...)`` instead. api_key: Groq API key. Defaults to None. base_url: API base URL. Defaults to "https://api.groq.com/openai/v1". language: Language of the audio input. - .. deprecated:: 1.0.0 + .. deprecated:: 0.0.105 Use ``settings=BaseWhisperSTTSettings(language=...)`` instead. prompt: Optional text to guide the model's style or continue a previous segment. - .. deprecated:: 1.0.0 + .. deprecated:: 0.0.105 Use ``settings=BaseWhisperSTTSettings(prompt=...)`` instead. temperature: Optional sampling temperature between 0 and 1. - .. deprecated:: 1.0.0 + .. deprecated:: 0.0.105 Use ``settings=BaseWhisperSTTSettings(temperature=...)`` instead. settings: Runtime-updatable settings. When provided alongside deprecated diff --git a/src/pipecat/services/groq/tts.py b/src/pipecat/services/groq/tts.py index b1c546713..6f9a610e2 100644 --- a/src/pipecat/services/groq/tts.py +++ b/src/pipecat/services/groq/tts.py @@ -64,7 +64,7 @@ class GroqTTSService(TTSService): class InputParams(BaseModel): """Input parameters for Groq TTS configuration. - .. deprecated:: 1.0.0 + .. deprecated:: 0.0.105 Use ``settings=GroqTTSSettings(...)`` instead. Parameters: @@ -96,17 +96,17 @@ class GroqTTSService(TTSService): output_format: Audio output format. Defaults to "wav". params: Additional input parameters for voice customization. - .. deprecated:: 1.0.0 + .. deprecated:: 0.0.105 Use ``settings=GroqTTSSettings(...)`` instead. model_name: TTS model to use. - .. deprecated:: 1.0.0 + .. deprecated:: 0.0.105 Use ``settings=GroqTTSSettings(model=...)`` instead. voice_id: Voice identifier to use. - .. deprecated:: 1.0.0 + .. deprecated:: 0.0.105 Use ``settings=GroqTTSSettings(voice=...)`` instead. sample_rate: Audio sample rate. Must be 48000 Hz for Groq TTS. diff --git a/src/pipecat/services/hume/tts.py b/src/pipecat/services/hume/tts.py index 7b0ecd0c8..052d1cd0a 100644 --- a/src/pipecat/services/hume/tts.py +++ b/src/pipecat/services/hume/tts.py @@ -84,7 +84,7 @@ class HumeTTSService(TTSService): class InputParams(BaseModel): """Optional synthesis parameters for Hume TTS. - .. deprecated:: 1.0.0 + .. deprecated:: 0.0.105 Use ``settings=HumeTTSSettings(...)`` instead. Parameters: @@ -113,12 +113,12 @@ class HumeTTSService(TTSService): api_key: Hume API key. If omitted, reads the ``HUME_API_KEY`` environment variable. voice_id: ID of the voice to use. Only voice IDs are supported; voice names are not. - .. deprecated:: 1.0.0 + .. deprecated:: 0.0.105 Use ``settings=HumeTTSSettings(voice=...)`` instead. params: Optional synthesis controls (acting instructions, speed, trailing silence). - .. deprecated:: 1.0.0 + .. deprecated:: 0.0.105 Use ``settings=HumeTTSSettings(...)`` instead. sample_rate: Output sample rate for emitted PCM frames. Defaults to 48_000 (Hume). diff --git a/src/pipecat/services/inworld/tts.py b/src/pipecat/services/inworld/tts.py index 688ba542a..f650ce620 100644 --- a/src/pipecat/services/inworld/tts.py +++ b/src/pipecat/services/inworld/tts.py @@ -125,7 +125,7 @@ class InworldHttpTTSService(TTSService): class InputParams(BaseModel): """Input parameters for Inworld TTS configuration. - .. deprecated:: 1.0.0 + .. deprecated:: 0.0.105 Use ``InworldTTSSettings`` directly via the ``settings`` parameter instead. Parameters: @@ -159,12 +159,12 @@ class InworldHttpTTSService(TTSService): aiohttp_session: aiohttp ClientSession for HTTP requests. voice_id: ID of the voice to use for synthesis. - .. deprecated:: 1.0.0 + .. deprecated:: 0.0.105 Use ``settings=InworldTTSSettings(voice=...)`` instead. model: ID of the model to use for synthesis. - .. deprecated:: 1.0.0 + .. deprecated:: 0.0.105 Use ``settings=InworldTTSSettings(model=...)`` instead. streaming: Whether to use streaming mode. @@ -172,7 +172,7 @@ class InworldHttpTTSService(TTSService): encoding: Audio encoding format. params: Input parameters for Inworld TTS configuration. - .. deprecated:: 1.0.0 + .. deprecated:: 0.0.105 Use ``settings=InworldTTSSettings(...)`` instead. settings: Runtime-updatable settings. When provided alongside deprecated @@ -532,7 +532,7 @@ class InworldTTSService(AudioContextTTSService): class InputParams(BaseModel): """Input parameters for Inworld WebSocket TTS configuration. - .. deprecated:: 1.0.0 + .. deprecated:: 0.0.105 Use ``InworldTTSSettings`` directly via the ``settings`` parameter instead. Parameters: @@ -579,12 +579,12 @@ class InworldTTSService(AudioContextTTSService): api_key: Inworld API key. voice_id: ID of the voice to use for synthesis. - .. deprecated:: 1.0.0 + .. deprecated:: 0.0.105 Use ``settings=InworldTTSSettings(voice=...)`` instead. model: ID of the model to use for synthesis. - .. deprecated:: 1.0.0 + .. deprecated:: 0.0.105 Use ``settings=InworldTTSSettings(model=...)`` instead. url: URL of the Inworld WebSocket API. @@ -592,7 +592,7 @@ class InworldTTSService(AudioContextTTSService): encoding: Audio encoding format. params: Input parameters for Inworld WebSocket TTS configuration. - .. deprecated:: 1.0.0 + .. deprecated:: 0.0.105 Use ``settings=InworldTTSSettings(...)`` instead. settings: Runtime-updatable settings. When provided alongside deprecated diff --git a/src/pipecat/services/kokoro/tts.py b/src/pipecat/services/kokoro/tts.py index 7e53060da..60dfb65ce 100644 --- a/src/pipecat/services/kokoro/tts.py +++ b/src/pipecat/services/kokoro/tts.py @@ -112,7 +112,7 @@ class KokoroTTSService(TTSService): class InputParams(BaseModel): """Input parameters for Kokoro TTS configuration. - .. deprecated:: 1.0.0 + .. deprecated:: 0.0.105 Use ``KokoroTTSSettings`` directly via the ``settings`` parameter instead. Parameters: @@ -136,14 +136,14 @@ class KokoroTTSService(TTSService): Args: voice_id: Voice identifier to use for synthesis. - .. deprecated:: 1.0.0 + .. deprecated:: 0.0.105 Use ``settings=KokoroTTSSettings(voice=...)`` instead. model_path: Path to the kokoro ONNX model file. Defaults to auto-downloaded file. voices_path: Path to the voices binary file. Defaults to auto-downloaded file. params: Configuration parameters for synthesis. - .. deprecated:: 1.0.0 + .. deprecated:: 0.0.105 Use ``settings=KokoroTTSSettings(...)`` instead. settings: Runtime-updatable settings. When provided alongside deprecated diff --git a/src/pipecat/services/lmnt/tts.py b/src/pipecat/services/lmnt/tts.py index c69eadfef..58468bc00 100644 --- a/src/pipecat/services/lmnt/tts.py +++ b/src/pipecat/services/lmnt/tts.py @@ -111,14 +111,14 @@ class LmntTTSService(InterruptibleTTSService): api_key: LMNT API key for authentication. voice_id: ID of the voice to use for synthesis. - .. deprecated:: 1.0.0 + .. deprecated:: 0.0.105 Use ``settings=LmntTTSSettings(voice=...)`` instead. sample_rate: Audio sample rate. If None, uses default. language: Language for synthesis. Defaults to English. model: TTS model to use. - .. deprecated:: 1.0.0 + .. deprecated:: 0.0.105 Use ``settings=LmntTTSSettings(model=...)`` instead. settings: Runtime-updatable settings. When provided alongside deprecated diff --git a/src/pipecat/services/minimax/tts.py b/src/pipecat/services/minimax/tts.py index 2d9f49636..2be25aef9 100644 --- a/src/pipecat/services/minimax/tts.py +++ b/src/pipecat/services/minimax/tts.py @@ -166,7 +166,7 @@ class MiniMaxHttpTTSService(TTSService): class InputParams(BaseModel): """Configuration parameters for MiniMax TTS. - .. deprecated:: 1.0.0 + .. deprecated:: 0.0.105 Use ``MiniMaxTTSSettings`` directly via the ``settings`` parameter instead. Parameters: @@ -226,19 +226,19 @@ class MiniMaxHttpTTSService(TTSService): "speech-02-hd", "speech-02-turbo", "speech-01-hd", "speech-01-turbo". - .. deprecated:: 1.0.0 + .. deprecated:: 0.0.105 Use ``settings=MiniMaxTTSSettings(model=...)`` instead. voice_id: Voice identifier. Defaults to "Calm_Woman". - .. deprecated:: 1.0.0 + .. deprecated:: 0.0.105 Use ``settings=MiniMaxTTSSettings(voice=...)`` instead. aiohttp_session: aiohttp.ClientSession for API communication. sample_rate: Output audio sample rate in Hz. If None, uses pipeline default. params: Additional configuration parameters. - .. deprecated:: 1.0.0 + .. deprecated:: 0.0.105 Use ``settings=MiniMaxTTSSettings(...)`` instead. settings: Runtime-updatable settings. When provided alongside deprecated diff --git a/src/pipecat/services/mistral/llm.py b/src/pipecat/services/mistral/llm.py index ca72cde37..57ab45d6f 100644 --- a/src/pipecat/services/mistral/llm.py +++ b/src/pipecat/services/mistral/llm.py @@ -41,7 +41,7 @@ class MistralLLMService(OpenAILLMService): base_url: The base URL for Mistral API. Defaults to "https://api.mistral.ai/v1". model: The model identifier to use. Defaults to "mistral-small-latest". - .. deprecated:: 1.0.0 + .. deprecated:: 0.0.105 Use ``settings=OpenAILLMSettings(model=...)`` instead. settings: Runtime-updatable settings. When provided alongside deprecated diff --git a/src/pipecat/services/moondream/vision.py b/src/pipecat/services/moondream/vision.py index 3f0701c80..32b592061 100644 --- a/src/pipecat/services/moondream/vision.py +++ b/src/pipecat/services/moondream/vision.py @@ -93,7 +93,7 @@ class MoondreamService(VisionService): Args: model: Hugging Face model identifier for the Moondream model. - .. deprecated:: 1.0.0 + .. deprecated:: 0.0.105 Use ``settings=MoondreamSettings(model=...)`` instead. revision: Specific model revision to use. diff --git a/src/pipecat/services/neuphonic/tts.py b/src/pipecat/services/neuphonic/tts.py index ae85c3ab5..f6cc6bf68 100644 --- a/src/pipecat/services/neuphonic/tts.py +++ b/src/pipecat/services/neuphonic/tts.py @@ -102,7 +102,7 @@ class NeuphonicTTSService(InterruptibleTTSService): class InputParams(BaseModel): """Input parameters for Neuphonic TTS configuration. - .. deprecated:: 1.0.0 + .. deprecated:: 0.0.105 Use ``settings=NeuphonicTTSSettings(...)`` instead. Parameters: @@ -133,7 +133,7 @@ class NeuphonicTTSService(InterruptibleTTSService): api_key: Neuphonic API key for authentication. voice_id: ID of the voice to use for synthesis. - .. deprecated:: 1.0.0 + .. deprecated:: 0.0.105 Use ``settings=NeuphonicTTSSettings(voice=...)`` instead. url: WebSocket URL for the Neuphonic API. @@ -141,7 +141,7 @@ class NeuphonicTTSService(InterruptibleTTSService): encoding: Audio encoding format. Defaults to "pcm_linear". params: Additional input parameters for TTS configuration. - .. deprecated:: 1.0.0 + .. deprecated:: 0.0.105 Use ``settings=NeuphonicTTSSettings(...)`` instead. settings: Runtime-updatable settings. When provided alongside deprecated @@ -451,7 +451,7 @@ class NeuphonicHttpTTSService(TTSService): class InputParams(BaseModel): """Input parameters for Neuphonic HTTP TTS configuration. - .. deprecated:: 1.0.0 + .. deprecated:: 0.0.105 Use ``settings=NeuphonicTTSSettings(...)`` instead. Parameters: @@ -481,7 +481,7 @@ class NeuphonicHttpTTSService(TTSService): api_key: Neuphonic API key for authentication. voice_id: ID of the voice to use for synthesis. - .. deprecated:: 1.0.0 + .. deprecated:: 0.0.105 Use ``settings=NeuphonicTTSSettings(voice=...)`` instead. aiohttp_session: Shared aiohttp session for HTTP requests. @@ -490,7 +490,7 @@ class NeuphonicHttpTTSService(TTSService): encoding: Audio encoding format. Defaults to "pcm_linear". params: Additional input parameters for TTS configuration. - .. deprecated:: 1.0.0 + .. deprecated:: 0.0.105 Use ``settings=NeuphonicTTSSettings(...)`` instead. settings: Runtime-updatable settings. When provided alongside deprecated diff --git a/src/pipecat/services/nvidia/llm.py b/src/pipecat/services/nvidia/llm.py index f09db54fa..88245464e 100644 --- a/src/pipecat/services/nvidia/llm.py +++ b/src/pipecat/services/nvidia/llm.py @@ -45,7 +45,7 @@ class NvidiaLLMService(OpenAILLMService): model: The model identifier to use. Defaults to "nvidia/llama-3.1-nemotron-70b-instruct". - .. deprecated:: 1.0.0 + .. deprecated:: 0.0.105 Use ``settings=OpenAILLMSettings(model=...)`` instead. settings: Runtime-updatable settings. When provided alongside deprecated diff --git a/src/pipecat/services/nvidia/stt.py b/src/pipecat/services/nvidia/stt.py index 3ceaf45fa..df785e25c 100644 --- a/src/pipecat/services/nvidia/stt.py +++ b/src/pipecat/services/nvidia/stt.py @@ -130,7 +130,7 @@ class NvidiaSTTService(STTService): class InputParams(BaseModel): """Configuration parameters for NVIDIA Riva STT service. - .. deprecated:: 1.0.0 + .. deprecated:: 0.0.105 Use ``settings=NvidiaSTTSettings(...)`` instead. Parameters: @@ -164,7 +164,7 @@ class NvidiaSTTService(STTService): sample_rate: Audio sample rate in Hz. If None, uses pipeline default. params: Additional configuration parameters for NVIDIA Riva. - .. deprecated:: 1.0.0 + .. deprecated:: 0.0.105 Use ``settings=NvidiaSTTSettings(...)`` instead. use_ssl: Whether to use SSL for the NVIDIA Riva server. Defaults to True. @@ -444,7 +444,7 @@ class NvidiaSegmentedSTTService(SegmentedSTTService): class InputParams(BaseModel): """Configuration parameters for NVIDIA Riva segmented STT service. - .. deprecated:: 1.0.0 + .. deprecated:: 0.0.105 Use ``settings=NvidiaSegmentedSTTSettings(...)`` instead. Parameters: @@ -488,7 +488,7 @@ class NvidiaSegmentedSTTService(SegmentedSTTService): sample_rate: Audio sample rate in Hz. If not provided, uses the pipeline's rate params: Additional configuration parameters for NVIDIA Riva - .. deprecated:: 1.0.0 + .. deprecated:: 0.0.105 Use ``settings=NvidiaSegmentedSTTSettings(...)`` instead. use_ssl: Whether to use SSL for the NVIDIA Riva server. Defaults to True. diff --git a/src/pipecat/services/nvidia/tts.py b/src/pipecat/services/nvidia/tts.py index be0b90071..6e3298a75 100644 --- a/src/pipecat/services/nvidia/tts.py +++ b/src/pipecat/services/nvidia/tts.py @@ -68,7 +68,7 @@ class NvidiaTTSService(TTSService): class InputParams(BaseModel): """Input parameters for Riva TTS configuration. - .. deprecated:: 1.0.0 + .. deprecated:: 0.0.105 Use ``NvidiaTTSSettings`` directly via the ``settings`` parameter instead. Parameters: @@ -102,14 +102,14 @@ class NvidiaTTSService(TTSService): server: gRPC server endpoint. Defaults to NVIDIA's cloud endpoint. voice_id: Voice model identifier. Defaults to multilingual Aria voice. - .. deprecated:: 1.0.0 + .. deprecated:: 0.0.105 Use ``settings=NvidiaTTSSettings(voice=...)`` instead. sample_rate: Audio sample rate. If None, uses service default. model_function_map: Dictionary containing function_id and model_name for the TTS model. params: Additional configuration parameters for TTS synthesis. - .. deprecated:: 1.0.0 + .. deprecated:: 0.0.105 Use ``settings=NvidiaTTSSettings(...)`` instead. settings: Runtime-updatable settings. When provided alongside deprecated diff --git a/src/pipecat/services/ollama/llm.py b/src/pipecat/services/ollama/llm.py index 2a4a3e78f..477a80b5f 100644 --- a/src/pipecat/services/ollama/llm.py +++ b/src/pipecat/services/ollama/llm.py @@ -35,7 +35,7 @@ class OLLamaLLMService(OpenAILLMService): Args: model: The OLLama model to use. Defaults to "llama2". - .. deprecated:: 1.0.0 + .. deprecated:: 0.0.105 Use ``settings=OpenAILLMSettings(model=...)`` instead. base_url: The base URL for the OLLama API endpoint. diff --git a/src/pipecat/services/openai/base_llm.py b/src/pipecat/services/openai/base_llm.py index 6c27fbe37..d44fbcf41 100644 --- a/src/pipecat/services/openai/base_llm.py +++ b/src/pipecat/services/openai/base_llm.py @@ -75,7 +75,7 @@ class BaseOpenAILLMService(LLMService): class InputParams(BaseModel): """Input parameters for OpenAI model configuration. - .. deprecated:: 1.0.0 + .. deprecated:: 0.0.105 Use ``settings=OpenAILLMSettings(...)`` instead of ``params=InputParams(...)``. @@ -130,7 +130,7 @@ class BaseOpenAILLMService(LLMService): Args: model: The OpenAI model name to use (e.g., "gpt-4.1", "gpt-4o"). - .. deprecated:: 1.0.0 + .. deprecated:: 0.0.105 Use ``settings=OpenAILLMSettings(model=...)`` instead. api_key: OpenAI API key. If None, uses environment variable. @@ -140,7 +140,7 @@ class BaseOpenAILLMService(LLMService): default_headers: Additional HTTP headers to include in requests. params: Input parameters for model configuration and behavior. - .. deprecated:: 1.0.0 + .. deprecated:: 0.0.105 Use ``settings=OpenAILLMSettings(...)`` instead. settings: Runtime-updatable settings. When provided alongside deprecated diff --git a/src/pipecat/services/openai/image.py b/src/pipecat/services/openai/image.py index fd9bd0ba8..4120db8c6 100644 --- a/src/pipecat/services/openai/image.py +++ b/src/pipecat/services/openai/image.py @@ -64,7 +64,7 @@ class OpenAIImageGenService(ImageGenService): image_size: Target size for generated images. model: DALL-E model to use for generation. Defaults to "dall-e-3". - .. deprecated:: 1.0.0 + .. deprecated:: 0.0.105 Use ``settings=OpenAIImageGenSettings(model=...)`` instead. settings: Runtime-updatable settings. When provided alongside deprecated diff --git a/src/pipecat/services/openai/llm.py b/src/pipecat/services/openai/llm.py index 56515ce89..a81d3dc29 100644 --- a/src/pipecat/services/openai/llm.py +++ b/src/pipecat/services/openai/llm.py @@ -85,12 +85,12 @@ class OpenAILLMService(BaseOpenAILLMService): Args: model: The OpenAI model name to use. Defaults to "gpt-4.1". - .. deprecated:: 1.0.0 + .. deprecated:: 0.0.105 Use ``settings=OpenAILLMSettings(model=...)`` instead. params: Input parameters for model configuration. - .. deprecated:: 1.0.0 + .. deprecated:: 0.0.105 Use ``settings=OpenAILLMSettings(...)`` instead. settings: Runtime-updatable settings. When provided alongside deprecated diff --git a/src/pipecat/services/openai/stt.py b/src/pipecat/services/openai/stt.py index ea2814619..7692deee5 100644 --- a/src/pipecat/services/openai/stt.py +++ b/src/pipecat/services/openai/stt.py @@ -80,7 +80,7 @@ class OpenAISTTService(BaseWhisperSTTService): Args: model: Model to use — either gpt-4o or Whisper. - .. deprecated:: 1.0.0 + .. deprecated:: 0.0.105 Use ``settings=BaseWhisperSTTSettings(model=...)`` instead. api_key: OpenAI API key. Defaults to None. @@ -222,7 +222,7 @@ class OpenAIRealtimeSTTService(WebsocketSTTService): model: Transcription model. Supported values are ``"gpt-4o-transcribe"`` and ``"gpt-4o-mini-transcribe"``. - .. deprecated:: 1.0.0 + .. deprecated:: 0.0.105 Use ``settings=OpenAIRealtimeSTTSettings(model=...)`` instead. base_url: WebSocket base URL for the Realtime API. diff --git a/src/pipecat/services/openai/tts.py b/src/pipecat/services/openai/tts.py index a119c3d14..feb6453c7 100644 --- a/src/pipecat/services/openai/tts.py +++ b/src/pipecat/services/openai/tts.py @@ -90,7 +90,7 @@ class OpenAITTSService(TTSService): class InputParams(BaseModel): """Input parameters for OpenAI TTS configuration. - .. deprecated:: 1.0.0 + .. deprecated:: 0.0.105 Use ``settings=OpenAITTSSettings(...)`` instead. Parameters: @@ -122,28 +122,28 @@ class OpenAITTSService(TTSService): base_url: Custom base URL for OpenAI API. If None, uses default. voice: Voice ID to use for synthesis. Defaults to "alloy". - .. deprecated:: 1.0.0 + .. deprecated:: 0.0.105 Use ``settings=OpenAITTSSettings(voice=...)`` instead. model: TTS model to use. Defaults to "gpt-4o-mini-tts". - .. deprecated:: 1.0.0 + .. deprecated:: 0.0.105 Use ``settings=OpenAITTSSettings(model=...)`` instead. sample_rate: Output audio sample rate in Hz. If None, uses OpenAI's default 24kHz. instructions: Optional instructions to guide voice synthesis behavior. - .. deprecated:: 1.0.0 + .. deprecated:: 0.0.105 Use ``settings=OpenAITTSSettings(instructions=...)`` instead. speed: Voice speed control (0.25 to 4.0, default 1.0). - .. deprecated:: 1.0.0 + .. deprecated:: 0.0.105 Use ``settings=OpenAITTSSettings(speed=...)`` instead. params: Optional synthesis controls (acting instructions, speed, ...). - .. deprecated:: 1.0.0 + .. deprecated:: 0.0.105 Use ``settings=OpenAITTSSettings(...)`` instead. settings: Runtime-updatable settings. When provided alongside deprecated diff --git a/src/pipecat/services/openpipe/llm.py b/src/pipecat/services/openpipe/llm.py index 9724c0a3f..431de832d 100644 --- a/src/pipecat/services/openpipe/llm.py +++ b/src/pipecat/services/openpipe/llm.py @@ -52,7 +52,7 @@ class OpenPipeLLMService(OpenAILLMService): Args: model: The model name to use. Defaults to "gpt-4.1". - .. deprecated:: 1.0.0 + .. deprecated:: 0.0.105 Use ``settings=OpenAILLMSettings(model=...)`` instead. api_key: OpenAI API key for authentication. If None, reads from environment. diff --git a/src/pipecat/services/openrouter/llm.py b/src/pipecat/services/openrouter/llm.py index 42f01c77d..8c42069d8 100644 --- a/src/pipecat/services/openrouter/llm.py +++ b/src/pipecat/services/openrouter/llm.py @@ -42,7 +42,7 @@ class OpenRouterLLMService(OpenAILLMService): to read from environment variables. model: The model identifier to use. Defaults to "openai/gpt-4o-2024-11-20". - .. deprecated:: 1.0.0 + .. deprecated:: 0.0.105 Use ``settings=OpenAILLMSettings(model=...)`` instead. base_url: The base URL for OpenRouter API. Defaults to "https://openrouter.ai/api/v1". diff --git a/src/pipecat/services/perplexity/llm.py b/src/pipecat/services/perplexity/llm.py index 2d350b736..8195dd50e 100644 --- a/src/pipecat/services/perplexity/llm.py +++ b/src/pipecat/services/perplexity/llm.py @@ -46,7 +46,7 @@ class PerplexityLLMService(OpenAILLMService): base_url: The base URL for Perplexity's API. Defaults to "https://api.perplexity.ai". model: The model identifier to use. Defaults to "sonar". - .. deprecated:: 1.0.0 + .. deprecated:: 0.0.105 Use ``settings=OpenAILLMSettings(model=...)`` instead. settings: Runtime-updatable settings. When provided alongside deprecated diff --git a/src/pipecat/services/piper/tts.py b/src/pipecat/services/piper/tts.py index fd6b0bf16..46bf98cd1 100644 --- a/src/pipecat/services/piper/tts.py +++ b/src/pipecat/services/piper/tts.py @@ -65,7 +65,7 @@ class PiperTTSService(TTSService): Args: voice_id: Piper voice model identifier (e.g. `en_US-ryan-high`). - .. deprecated:: 1.0.0 + .. deprecated:: 0.0.105 Use ``settings=PiperTTSSettings(voice=...)`` instead. download_dir: Directory for storing voice model files. Defaults to @@ -222,7 +222,7 @@ class PiperHttpTTSService(TTSService): aiohttp_session: aiohttp ClientSession for making HTTP requests. voice_id: Piper voice model identifier (e.g. `en_US-ryan-high`). - .. deprecated:: 1.0.0 + .. deprecated:: 0.0.105 Use ``settings=PiperHttpTTSSettings(voice=...)`` instead. settings: Runtime-updatable settings. When provided alongside deprecated diff --git a/src/pipecat/services/qwen/llm.py b/src/pipecat/services/qwen/llm.py index 92d24fa76..b983e00cd 100644 --- a/src/pipecat/services/qwen/llm.py +++ b/src/pipecat/services/qwen/llm.py @@ -38,7 +38,7 @@ class QwenLLMService(OpenAILLMService): base_url: Base URL for Qwen API. Defaults to "https://dashscope-intl.aliyuncs.com/compatible-mode/v1". model: The model identifier to use. Defaults to "qwen-plus". - .. deprecated:: 1.0.0 + .. deprecated:: 0.0.105 Use ``settings=OpenAILLMSettings(model=...)`` instead. settings: Runtime-updatable settings. When provided alongside deprecated diff --git a/src/pipecat/services/resembleai/tts.py b/src/pipecat/services/resembleai/tts.py index 28ec8a522..f0a8a988a 100644 --- a/src/pipecat/services/resembleai/tts.py +++ b/src/pipecat/services/resembleai/tts.py @@ -84,7 +84,7 @@ class ResembleAITTSService(AudioContextTTSService): api_key: Resemble AI API key for authentication. voice_id: Voice UUID to use for synthesis. - .. deprecated:: 1.0.0 + .. deprecated:: 0.0.105 Use ``settings=ResembleAITTSSettings(voice=...)`` instead. url: WebSocket URL for Resemble AI TTS API. diff --git a/src/pipecat/services/rime/tts.py b/src/pipecat/services/rime/tts.py index 1de4087de..613d58f3a 100644 --- a/src/pipecat/services/rime/tts.py +++ b/src/pipecat/services/rime/tts.py @@ -144,7 +144,7 @@ class RimeTTSService(AudioContextTTSService): class InputParams(BaseModel): """Configuration parameters for Rime TTS service. - .. deprecated:: 1.0.0 + .. deprecated:: 0.0.105 Use ``settings=RimeTTSSettings(...)`` instead. Parameters: @@ -196,19 +196,19 @@ class RimeTTSService(AudioContextTTSService): api_key: Rime API key for authentication. voice_id: ID of the voice to use. - .. deprecated:: 1.0.0 + .. deprecated:: 0.0.105 Use ``settings=RimeTTSSettings(voice=...)`` instead. url: Rime websocket API endpoint. model: Model ID to use for synthesis. - .. deprecated:: 1.0.0 + .. deprecated:: 0.0.105 Use ``settings=RimeTTSSettings(model=...)`` instead. sample_rate: Audio sample rate in Hz. params: Additional configuration parameters. - .. deprecated:: 1.0.0 + .. deprecated:: 0.0.105 Use ``settings=RimeTTSSettings(...)`` instead. settings: Runtime-updatable settings. When provided alongside deprecated @@ -676,7 +676,7 @@ class RimeHttpTTSService(TTSService): class InputParams(BaseModel): """Configuration parameters for Rime HTTP TTS service. - .. deprecated:: 1.0.0 + .. deprecated:: 0.0.105 Use ``settings=RimeTTSSettings(...)`` instead. Parameters: @@ -713,19 +713,19 @@ class RimeHttpTTSService(TTSService): api_key: Rime API key for authentication. voice_id: ID of the voice to use. - .. deprecated:: 1.0.0 + .. deprecated:: 0.0.105 Use ``settings=RimeTTSSettings(voice=...)`` instead. aiohttp_session: Shared aiohttp session for HTTP requests. model: Model ID to use for synthesis. - .. deprecated:: 1.0.0 + .. deprecated:: 0.0.105 Use ``settings=RimeTTSSettings(model=...)`` instead. sample_rate: Audio sample rate in Hz. params: Additional configuration parameters. - .. deprecated:: 1.0.0 + .. deprecated:: 0.0.105 Use ``settings=RimeTTSSettings(...)`` instead. settings: Runtime-updatable settings. When provided alongside deprecated @@ -902,7 +902,7 @@ class RimeNonJsonTTSService(InterruptibleTTSService): class InputParams(BaseModel): """Configuration parameters for Rime Non-JSON WebSocket TTS service. - .. deprecated:: 1.0.0 + .. deprecated:: 0.0.105 Use ``settings=RimeNonJsonTTSSettings(...)`` instead. Args: @@ -942,20 +942,20 @@ class RimeNonJsonTTSService(InterruptibleTTSService): api_key: Rime API key for authentication. voice_id: ID of the voice to use. - .. deprecated:: 1.0.0 + .. deprecated:: 0.0.105 Use ``settings=RimeNonJsonTTSSettings(voice=...)`` instead. url: Rime websocket API endpoint. model: Model ID to use for synthesis. - .. deprecated:: 1.0.0 + .. deprecated:: 0.0.105 Use ``settings=RimeNonJsonTTSSettings(model=...)`` instead. audio_format: Audio format to use. sample_rate: Audio sample rate in Hz. params: Additional configuration parameters. - .. deprecated:: 1.0.0 + .. deprecated:: 0.0.105 Use ``settings=RimeNonJsonTTSSettings(...)`` instead. settings: Runtime-updatable settings. When provided alongside deprecated diff --git a/src/pipecat/services/sambanova/llm.py b/src/pipecat/services/sambanova/llm.py index f9b7b1380..2468dad13 100644 --- a/src/pipecat/services/sambanova/llm.py +++ b/src/pipecat/services/sambanova/llm.py @@ -49,7 +49,7 @@ class SambaNovaLLMService(OpenAILLMService): # type: ignore api_key: The API key for accessing SambaNova API. model: The model identifier to use. Defaults to "Llama-4-Maverick-17B-128E-Instruct". - .. deprecated:: 1.0.0 + .. deprecated:: 0.0.105 Use ``settings=OpenAILLMSettings(model=...)`` instead. base_url: The base URL for SambaNova API. Defaults to "https://api.sambanova.ai/v1". diff --git a/src/pipecat/services/sambanova/stt.py b/src/pipecat/services/sambanova/stt.py index 0c2d77e36..60f638897 100644 --- a/src/pipecat/services/sambanova/stt.py +++ b/src/pipecat/services/sambanova/stt.py @@ -45,24 +45,24 @@ class SambaNovaSTTService(BaseWhisperSTTService): # type: ignore Args: model: Whisper model to use. - .. deprecated:: 1.0.0 + .. deprecated:: 0.0.105 Use ``settings=BaseWhisperSTTSettings(model=...)`` instead. api_key: SambaNova API key. Defaults to None. base_url: API base URL. Defaults to "https://api.sambanova.ai/v1". language: Language of the audio input. - .. deprecated:: 1.0.0 + .. deprecated:: 0.0.105 Use ``settings=BaseWhisperSTTSettings(language=...)`` instead. prompt: Optional text to guide the model's style or continue a previous segment. - .. deprecated:: 1.0.0 + .. deprecated:: 0.0.105 Use ``settings=BaseWhisperSTTSettings(prompt=...)`` instead. temperature: Optional sampling temperature between 0 and 1. - .. deprecated:: 1.0.0 + .. deprecated:: 0.0.105 Use ``settings=BaseWhisperSTTSettings(temperature=...)`` instead. settings: Runtime-updatable settings. When provided alongside deprecated diff --git a/src/pipecat/services/sarvam/stt.py b/src/pipecat/services/sarvam/stt.py index fd9a55f14..f255619bb 100644 --- a/src/pipecat/services/sarvam/stt.py +++ b/src/pipecat/services/sarvam/stt.py @@ -177,7 +177,7 @@ class SarvamSTTService(STTService): class InputParams(BaseModel): """Configuration parameters for Sarvam STT service. - .. deprecated:: 1.0.0 + .. deprecated:: 0.0.105 Use ``settings=SarvamSTTSettings(...)`` instead. Parameters: @@ -219,14 +219,14 @@ class SarvamSTTService(STTService): api_key: Sarvam API key for authentication. model: Sarvam model to use for transcription. - .. deprecated:: 1.0.0 + .. deprecated:: 0.0.105 Use ``settings=SarvamSTTSettings(model=...)`` instead. sample_rate: Audio sample rate. Defaults to 16000 if not specified. input_audio_codec: Audio codec/format of the input file. Defaults to "wav". params: Configuration parameters for Sarvam STT service. - .. deprecated:: 1.0.0 + .. deprecated:: 0.0.105 Use ``settings=SarvamSTTSettings(...)`` instead. settings: Runtime-updatable settings. When provided alongside deprecated diff --git a/src/pipecat/services/sarvam/tts.py b/src/pipecat/services/sarvam/tts.py index 8c76e0ec9..cf00dd8c7 100644 --- a/src/pipecat/services/sarvam/tts.py +++ b/src/pipecat/services/sarvam/tts.py @@ -376,7 +376,7 @@ class SarvamHttpTTSService(TTSService): class InputParams(BaseModel): """Input parameters for Sarvam TTS configuration. - .. deprecated:: 1.0.0 + .. deprecated:: 0.0.105 Use ``SarvamHttpTTSSettings`` directly via the ``settings`` parameter instead. Parameters: @@ -445,14 +445,14 @@ class SarvamHttpTTSService(TTSService): aiohttp_session: Shared aiohttp session for making requests. voice_id: Speaker voice ID. If None, uses model-appropriate default. - .. deprecated:: 1.0.0 + .. deprecated:: 0.0.105 Use ``settings=SarvamHttpTTSSettings(voice=...)`` instead. model: TTS model to use. Options: - "bulbul:v2" (default): Standard model with pitch/loudness support - "bulbul:v3-beta": Advanced model with temperature control - .. deprecated:: 1.0.0 + .. deprecated:: 0.0.105 Use ``settings=SarvamHttpTTSSettings(model=...)`` instead. base_url: Sarvam AI API base URL. Defaults to "https://api.sarvam.ai". @@ -460,7 +460,7 @@ class SarvamHttpTTSService(TTSService): If None, uses model-specific default. params: Additional voice and preprocessing parameters. If None, uses defaults. - .. deprecated:: 1.0.0 + .. deprecated:: 0.0.105 Use ``settings=SarvamHttpTTSSettings(...)`` instead. settings: Runtime-updatable settings. When provided alongside deprecated @@ -742,7 +742,7 @@ class SarvamTTSService(InterruptibleTTSService): class InputParams(BaseModel): """Configuration parameters for Sarvam TTS WebSocket service. - .. deprecated:: 1.0.0 + .. deprecated:: 0.0.105 Use ``SarvamTTSSettings`` directly via the ``settings`` parameter instead. Parameters: @@ -848,12 +848,12 @@ class SarvamTTSService(InterruptibleTTSService): - "bulbul:v2" (default): Standard model with pitch/loudness support - "bulbul:v3-beta": Advanced model with temperature control - .. deprecated:: 1.0.0 + .. deprecated:: 0.0.105 Use ``settings=SarvamTTSSettings(model=...)`` instead. voice_id: Speaker voice ID. If None, uses model-appropriate default. - .. deprecated:: 1.0.0 + .. deprecated:: 0.0.105 Use ``settings=SarvamTTSSettings(voice=...)`` instead. url: WebSocket URL for the TTS backend (default production URL). @@ -867,7 +867,7 @@ class SarvamTTSService(InterruptibleTTSService): If None, uses model-specific default. params: Optional input parameters to override defaults. - .. deprecated:: 1.0.0 + .. deprecated:: 0.0.105 Use ``settings=SarvamTTSSettings(...)`` instead. settings: Runtime-updatable settings. When provided alongside deprecated diff --git a/src/pipecat/services/soniox/stt.py b/src/pipecat/services/soniox/stt.py index b37a76b0f..beadabf1b 100644 --- a/src/pipecat/services/soniox/stt.py +++ b/src/pipecat/services/soniox/stt.py @@ -79,7 +79,7 @@ class SonioxContextObject(BaseModel): class SonioxInputParams(BaseModel): """Real-time transcription settings. - .. deprecated:: 1.0.0 + .. deprecated:: 0.0.105 Use ``settings=SonioxSTTSettings(...)`` instead. See Soniox WebSocket API documentation for more details: @@ -201,13 +201,13 @@ class SonioxSTTService(WebsocketSTTService): sample_rate: Audio sample rate. model: Soniox model to use for transcription. - .. deprecated:: 1.0.0 + .. deprecated:: 0.0.105 Use ``settings=SonioxSTTSettings(model=...)`` instead. params: Additional configuration parameters, such as language hints, context and speaker diarization. - .. deprecated:: 1.0.0 + .. deprecated:: 0.0.105 Use ``settings=SonioxSTTSettings(...)`` instead. vad_force_turn_endpoint: Listen to `VADUserStoppedSpeakingFrame` to send finalize message to Soniox. diff --git a/src/pipecat/services/speechmatics/stt.py b/src/pipecat/services/speechmatics/stt.py index 620646d31..a0a5c8b64 100644 --- a/src/pipecat/services/speechmatics/stt.py +++ b/src/pipecat/services/speechmatics/stt.py @@ -395,7 +395,7 @@ class SpeechmaticsSTTService(STTService): sample_rate: Optional audio sample rate in Hz. params: Input parameters for the service. - .. deprecated:: 1.0.0 + .. deprecated:: 0.0.105 Use ``settings=SpeechmaticsSTTSettings(...)`` instead. should_interrupt: Determine whether the bot should be interrupted when Speechmatics turn_detection_mode is configured to detect user speech. diff --git a/src/pipecat/services/speechmatics/tts.py b/src/pipecat/services/speechmatics/tts.py index dff3e5f0f..55ded437e 100644 --- a/src/pipecat/services/speechmatics/tts.py +++ b/src/pipecat/services/speechmatics/tts.py @@ -62,7 +62,7 @@ class SpeechmaticsTTSService(TTSService): class InputParams(BaseModel): """Optional input parameters for Speechmatics TTS configuration. - .. deprecated:: 1.0.0 + .. deprecated:: 0.0.105 Use ``settings=SpeechmaticsTTSSettings(...)`` instead. Parameters: @@ -90,14 +90,14 @@ class SpeechmaticsTTSService(TTSService): base_url: Base URL for Speechmatics TTS API. voice_id: Voice model to use for synthesis. - .. deprecated:: 1.0.0 + .. deprecated:: 0.0.105 Use ``settings=SpeechmaticsTTSSettings(voice=...)`` instead. aiohttp_session: Shared aiohttp session for HTTP requests. sample_rate: Audio sample rate in Hz. params: Input parameters for the service. - .. deprecated:: 1.0.0 + .. deprecated:: 0.0.105 Use ``settings=SpeechmaticsTTSSettings(...)`` instead. settings: Runtime-updatable settings. When provided alongside deprecated diff --git a/src/pipecat/services/together/llm.py b/src/pipecat/services/together/llm.py index 0fd8b637b..9ec8e9fc2 100644 --- a/src/pipecat/services/together/llm.py +++ b/src/pipecat/services/together/llm.py @@ -38,7 +38,7 @@ class TogetherLLMService(OpenAILLMService): base_url: The base URL for Together.ai API. Defaults to "https://api.together.xyz/v1". model: The model identifier to use. Defaults to "meta-llama/Meta-Llama-3.1-8B-Instruct-Turbo". - .. deprecated:: 1.0.0 + .. deprecated:: 0.0.105 Use ``settings=OpenAILLMSettings(model=...)`` instead. settings: Runtime-updatable settings. When provided alongside deprecated diff --git a/src/pipecat/services/whisper/base_stt.py b/src/pipecat/services/whisper/base_stt.py index b6c19ab5a..c2dde8acc 100644 --- a/src/pipecat/services/whisper/base_stt.py +++ b/src/pipecat/services/whisper/base_stt.py @@ -146,24 +146,24 @@ class BaseWhisperSTTService(SegmentedSTTService): Args: model: Name of the Whisper model to use. - .. deprecated:: 1.0.0 + .. deprecated:: 0.0.105 Use ``settings=BaseWhisperSTTSettings(model=...)`` instead. api_key: Service API key. Defaults to None. base_url: Service API base URL. Defaults to None. language: Language of the audio input. - .. deprecated:: 1.0.0 + .. deprecated:: 0.0.105 Use ``settings=BaseWhisperSTTSettings(language=...)`` instead. prompt: Optional text to guide the model's style or continue a previous segment. - .. deprecated:: 1.0.0 + .. deprecated:: 0.0.105 Use ``settings=BaseWhisperSTTSettings(prompt=...)`` instead. temperature: Sampling temperature between 0 and 1. - .. deprecated:: 1.0.0 + .. deprecated:: 0.0.105 Use ``settings=BaseWhisperSTTSettings(temperature=...)`` instead. include_prob_metrics: If True, enables probability metrics in API response. diff --git a/src/pipecat/services/whisper/stt.py b/src/pipecat/services/whisper/stt.py index 17fe24c2d..f3ac0c948 100644 --- a/src/pipecat/services/whisper/stt.py +++ b/src/pipecat/services/whisper/stt.py @@ -229,27 +229,27 @@ class WhisperSTTService(SegmentedSTTService): Args: model: The Whisper model to use for transcription. Can be a Model enum or string. - .. deprecated:: 1.0.0 + .. deprecated:: 0.0.105 Use ``settings=WhisperSTTSettings(model=...)`` instead. device: The device to run inference on ('cpu', 'cuda', or 'auto'). - .. deprecated:: 1.0.0 + .. deprecated:: 0.0.105 Use ``settings=WhisperSTTSettings(device=...)`` instead. compute_type: The compute type for inference ('default', 'int8', 'int8_float16', etc.). - .. deprecated:: 1.0.0 + .. deprecated:: 0.0.105 Use ``settings=WhisperSTTSettings(compute_type=...)`` instead. no_speech_prob: Probability threshold for filtering out non-speech segments. - .. deprecated:: 1.0.0 + .. deprecated:: 0.0.105 Use ``settings=WhisperSTTSettings(no_speech_prob=...)`` instead. language: The default language for transcription. - .. deprecated:: 1.0.0 + .. deprecated:: 0.0.105 Use ``settings=WhisperSTTSettings(language=...)`` instead. settings: Runtime-updatable settings. When provided alongside deprecated @@ -413,22 +413,22 @@ class WhisperSTTServiceMLX(WhisperSTTService): Args: model: The MLX Whisper model to use for transcription. Can be an MLXModel enum or string. - .. deprecated:: 1.0.0 + .. deprecated:: 0.0.105 Use ``settings=WhisperMLXSTTSettings(model=...)`` instead. no_speech_prob: Probability threshold for filtering out non-speech segments. - .. deprecated:: 1.0.0 + .. deprecated:: 0.0.105 Use ``settings=WhisperMLXSTTSettings(no_speech_prob=...)`` instead. language: The default language for transcription. - .. deprecated:: 1.0.0 + .. deprecated:: 0.0.105 Use ``settings=WhisperMLXSTTSettings(language=...)`` instead. temperature: Temperature for sampling. Can be a float or tuple of floats. - .. deprecated:: 1.0.0 + .. deprecated:: 0.0.105 Use ``settings=WhisperMLXSTTSettings(temperature=...)`` instead. settings: Runtime-updatable settings. When provided alongside deprecated diff --git a/src/pipecat/services/xtts/tts.py b/src/pipecat/services/xtts/tts.py index c5bfe629e..adf11da6a 100644 --- a/src/pipecat/services/xtts/tts.py +++ b/src/pipecat/services/xtts/tts.py @@ -107,7 +107,7 @@ class XTTSService(TTSService): Args: voice_id: ID of the voice/speaker to use for synthesis. - .. deprecated:: 1.0.0 + .. deprecated:: 0.0.105 Use ``settings=XTTSTTSSettings(voice=...)`` instead. base_url: Base URL of the XTTS streaming server. From 3cb792a80167beabf54c32cf008c705846149ef3 Mon Sep 17 00:00:00 2001 From: Mark Backman Date: Tue, 3 Mar 2026 23:02:55 -0500 Subject: [PATCH 0809/1060] Update TTS service settings --- src/pipecat/services/asyncai/tts.py | 61 +++++++------------ src/pipecat/services/azure/tts.py | 8 +-- .../services/deepgram/sagemaker/tts.py | 16 ++--- src/pipecat/services/deepgram/tts.py | 24 +++----- src/pipecat/services/elevenlabs/tts.py | 51 ++++++---------- src/pipecat/services/fish/tts.py | 18 +++--- src/pipecat/services/google/tts.py | 6 -- src/pipecat/services/gradium/tts.py | 13 ++-- src/pipecat/services/groq/tts.py | 10 +-- src/pipecat/services/inworld/tts.py | 31 +++++----- src/pipecat/services/kokoro/tts.py | 32 +++++----- src/pipecat/services/lmnt/tts.py | 17 ++---- src/pipecat/services/minimax/tts.py | 39 ++++-------- src/pipecat/services/neuphonic/tts.py | 17 ++---- src/pipecat/services/resembleai/tts.py | 45 +++++--------- src/pipecat/services/rime/tts.py | 38 ++++++------ src/pipecat/services/sarvam/tts.py | 40 +++++------- src/pipecat/services/xtts/tts.py | 21 +++---- 18 files changed, 184 insertions(+), 303 deletions(-) diff --git a/src/pipecat/services/asyncai/tts.py b/src/pipecat/services/asyncai/tts.py index d4e2eabdc..3b1296752 100644 --- a/src/pipecat/services/asyncai/tts.py +++ b/src/pipecat/services/asyncai/tts.py @@ -9,8 +9,8 @@ import asyncio import base64 import json -from dataclasses import dataclass, field -from typing import Any, AsyncGenerator, Mapping, Optional, Self +from dataclasses import dataclass +from typing import Any, AsyncGenerator, Optional import aiohttp from loguru import logger @@ -27,7 +27,7 @@ from pipecat.frames.frames import ( TTSStoppedFrame, ) from pipecat.processors.frame_processor import FrameDirection -from pipecat.services.settings import NOT_GIVEN, TTSSettings, _NotGiven, _warn_deprecated_param +from pipecat.services.settings import TTSSettings, _warn_deprecated_param from pipecat.services.tts_service import AudioContextTTSService, TextAggregationMode, TTSService from pipecat.transcriptions.language import Language, resolve_language from pipecat.utils.tracing.service_decorators import traced_tts @@ -75,28 +75,9 @@ def language_to_async_language(language: Language) -> Optional[str]: @dataclass class AsyncAITTSSettings(TTSSettings): - """Settings for Async AI TTS services. + """Settings for Async AI TTS services.""" - Parameters: - output_container: Audio container format (e.g. "raw"). - output_encoding: Audio encoding format (e.g. "pcm_s16le"). - output_sample_rate: Audio sample rate in Hz. - """ - - output_container: str | _NotGiven = field(default_factory=lambda: NOT_GIVEN) - output_encoding: str | _NotGiven = field(default_factory=lambda: NOT_GIVEN) - output_sample_rate: int | _NotGiven = field(default_factory=lambda: NOT_GIVEN) - - @classmethod - def from_mapping(cls, settings: Mapping[str, Any]) -> Self: - """Construct settings from a plain dict, destructuring legacy nested ``output_format``.""" - flat = dict(settings) - nested = flat.pop("output_format", None) - if isinstance(nested, dict): - flat.setdefault("output_container", nested.get("container")) - flat.setdefault("output_encoding", nested.get("encoding")) - flat.setdefault("output_sample_rate", nested.get("sample_rate")) - return super().from_mapping(flat) + pass class AsyncAITTSService(AudioContextTTSService): @@ -176,9 +157,6 @@ class AsyncAITTSService(AudioContextTTSService): model="async_flash_v1.0", voice=None, language=None, - output_container=container, - output_encoding=encoding, - output_sample_rate=0, ) # 2. Apply direct init arg overrides (deprecated) @@ -215,6 +193,11 @@ class AsyncAITTSService(AudioContextTTSService): self._api_version = version self._url = url + # Init-only audio format config (not runtime-updatable). + self._output_container = container + self._output_encoding = encoding + self._output_sample_rate = 0 # Set in start() + self._receive_task = None self._keepalive_task = None @@ -262,7 +245,7 @@ class AsyncAITTSService(AudioContextTTSService): frame: The start frame containing initialization parameters. """ await super().start(frame) - self._settings.output_sample_rate = self.sample_rate + self._output_sample_rate = self.sample_rate await self._connect() async def stop(self, frame: EndFrame): @@ -319,9 +302,9 @@ class AsyncAITTSService(AudioContextTTSService): "model_id": self._settings.model, "voice": {"mode": "id", "id": self._settings.voice}, "output_format": { - "container": self._settings.output_container, - "encoding": self._settings.output_encoding, - "sample_rate": self._settings.output_sample_rate, + "container": self._output_container, + "encoding": self._output_encoding, + "sample_rate": self._output_sample_rate, }, "language": self._settings.language, } @@ -567,9 +550,6 @@ class AsyncAIHttpTTSService(TTSService): model="async_flash_v1.0", voice=None, language=None, - output_container=container, - output_encoding=encoding, - output_sample_rate=0, ) # 2. Apply direct init arg overrides (deprecated) @@ -602,6 +582,11 @@ class AsyncAIHttpTTSService(TTSService): self._base_url = url self._api_version = version + # Init-only audio format config (not runtime-updatable). + self._output_container = container + self._output_encoding = encoding + self._output_sample_rate = 0 # Set in start() + self._session = aiohttp_session def can_generate_metrics(self) -> bool: @@ -630,7 +615,7 @@ class AsyncAIHttpTTSService(TTSService): frame: The start frame containing initialization parameters. """ await super().start(frame) - self._settings.output_sample_rate = self.sample_rate + self._output_sample_rate = self.sample_rate @traced_tts async def run_tts(self, text: str, context_id: str) -> AsyncGenerator[Frame, None]: @@ -653,9 +638,9 @@ class AsyncAIHttpTTSService(TTSService): "transcript": text, "voice": voice_config, "output_format": { - "container": self._settings.output_container, - "encoding": self._settings.output_encoding, - "sample_rate": self._settings.output_sample_rate, + "container": self._output_container, + "encoding": self._output_encoding, + "sample_rate": self._output_sample_rate, }, "language": self._settings.language, } diff --git a/src/pipecat/services/azure/tts.py b/src/pipecat/services/azure/tts.py index f4aa85dbc..112459c5a 100644 --- a/src/pipecat/services/azure/tts.py +++ b/src/pipecat/services/azure/tts.py @@ -73,7 +73,6 @@ class AzureTTSSettings(TTSSettings): Parameters: emphasis: Emphasis level for speech ("strong", "moderate", "reduced"). - language: Language for synthesis. Defaults to English (US). pitch: Voice pitch adjustment (e.g., "+10%", "-5Hz", "high"). rate: Speech rate adjustment (e.g., "1.0", "1.25", "slow", "fast"). role: Voice role for expression (e.g., "YoungAdultFemale"). @@ -83,7 +82,6 @@ class AzureTTSSettings(TTSSettings): """ emphasis: str | _NotGiven = field(default_factory=lambda: NOT_GIVEN) - language: str | _NotGiven = field(default_factory=lambda: NOT_GIVEN) pitch: str | _NotGiven = field(default_factory=lambda: NOT_GIVEN) rate: str | _NotGiven = field(default_factory=lambda: NOT_GIVEN) role: str | _NotGiven = field(default_factory=lambda: NOT_GIVEN) @@ -143,7 +141,6 @@ class AzureBaseTTSService: *, api_key: str, region: str, - voice: str = "en-US-SaraNeural", ): """Initialize Azure-specific configuration. @@ -152,7 +149,6 @@ class AzureBaseTTSService: Args: api_key: Azure Cognitive Services subscription key. region: Azure region identifier (e.g., "eastus", "westus2"). - voice: Voice name to use for synthesis. Defaults to "en-US-SaraNeural". """ self._api_key = api_key self._region = region @@ -343,7 +339,7 @@ class AzureTTSService(TTSService, AzureBaseTTSService): ) # Initialize Azure-specific functionality from mixin - self._init_azure_base(api_key=api_key, region=region, voice=default_settings.voice) + self._init_azure_base(api_key=api_key, region=region) self._speech_config = None self._speech_synthesizer = None @@ -842,7 +838,7 @@ class AzureHttpTTSService(TTSService, AzureBaseTTSService): ) # Initialize Azure-specific functionality from mixin - self._init_azure_base(api_key=api_key, region=region, voice=default_settings.voice) + self._init_azure_base(api_key=api_key, region=region) self._speech_config = None self._speech_synthesizer = None diff --git a/src/pipecat/services/deepgram/sagemaker/tts.py b/src/pipecat/services/deepgram/sagemaker/tts.py index 9457cc1db..0129abedb 100644 --- a/src/pipecat/services/deepgram/sagemaker/tts.py +++ b/src/pipecat/services/deepgram/sagemaker/tts.py @@ -14,7 +14,7 @@ streaming audio output. import asyncio import json -from dataclasses import dataclass, field +from dataclasses import dataclass from typing import Any, AsyncGenerator, Optional from loguru import logger @@ -33,20 +33,16 @@ from pipecat.frames.frames import ( ) from pipecat.processors.frame_processor import FrameDirection from pipecat.services.aws.sagemaker.bidi_client import SageMakerBidiClient -from pipecat.services.settings import NOT_GIVEN, TTSSettings, _NotGiven, _warn_deprecated_param +from pipecat.services.settings import TTSSettings, _warn_deprecated_param from pipecat.services.tts_service import TTSService from pipecat.utils.tracing.service_decorators import traced_tts @dataclass class DeepgramSageMakerTTSSettings(TTSSettings): - """Settings for Deepgram SageMaker TTS service. + """Settings for Deepgram SageMaker TTS service.""" - Parameters: - encoding: Audio encoding format (e.g. "linear16"). - """ - - encoding: str | _NotGiven = field(default_factory=lambda: NOT_GIVEN) + pass class DeepgramSageMakerTTSService(TTSService): @@ -107,10 +103,9 @@ class DeepgramSageMakerTTSService(TTSService): voice = voice or "aura-2-helena-en" default_settings = DeepgramSageMakerTTSSettings( - model=voice, + model=None, voice=voice, language=None, - encoding=encoding, ) if settings is not None: default_settings.apply_update(settings) @@ -126,6 +121,7 @@ class DeepgramSageMakerTTSService(TTSService): self._endpoint_name = endpoint_name self._region = region + self._encoding = encoding self._client: Optional[SageMakerBidiClient] = None self._response_task: Optional[asyncio.Task] = None diff --git a/src/pipecat/services/deepgram/tts.py b/src/pipecat/services/deepgram/tts.py index b54cd23dc..95db998e2 100644 --- a/src/pipecat/services/deepgram/tts.py +++ b/src/pipecat/services/deepgram/tts.py @@ -11,7 +11,7 @@ for generating speech from text using various voice models. """ import json -from dataclasses import dataclass, field +from dataclasses import dataclass from typing import Any, AsyncGenerator, Optional import aiohttp @@ -30,7 +30,7 @@ from pipecat.frames.frames import ( TTSStoppedFrame, ) from pipecat.processors.frame_processor import FrameDirection -from pipecat.services.settings import NOT_GIVEN, TTSSettings, _NotGiven, _warn_deprecated_param +from pipecat.services.settings import TTSSettings, _warn_deprecated_param from pipecat.services.tts_service import TTSService, WebsocketTTSService from pipecat.utils.tracing.service_decorators import traced_tts @@ -47,13 +47,9 @@ except ModuleNotFoundError as e: @dataclass class DeepgramTTSSettings(TTSSettings): - """Settings for Deepgram TTS service. + """Settings for Deepgram TTS service.""" - Parameters: - encoding: Audio encoding format (linear16, mulaw, alaw). - """ - - encoding: str | _NotGiven = field(default_factory=lambda: NOT_GIVEN) + pass class DeepgramTTSService(WebsocketTTSService): @@ -105,10 +101,9 @@ class DeepgramTTSService(WebsocketTTSService): # 1. Initialize default_settings with hardcoded defaults default_settings = DeepgramTTSSettings( - model="aura-2-helena-en", + model=None, voice="aura-2-helena-en", language=None, - encoding=encoding, ) # 2. Apply direct init arg overrides (deprecated) @@ -132,6 +127,7 @@ class DeepgramTTSService(WebsocketTTSService): self._api_key = api_key self._base_url = base_url + self._encoding = encoding self._receive_task = None self._context_id: Optional[str] = None @@ -236,7 +232,7 @@ class DeepgramTTSService(WebsocketTTSService): # Build WebSocket URL with query parameters params = [] params.append(f"model={self._settings.voice}") - params.append(f"encoding={self._settings.encoding}") + params.append(f"encoding={self._encoding}") params.append(f"sample_rate={self.sample_rate}") url = f"{self._base_url}/v1/speak?{'&'.join(params)}" @@ -422,10 +418,9 @@ class DeepgramHttpTTSService(TTSService): """ # 1. Initialize default_settings with hardcoded defaults default_settings = DeepgramTTSSettings( - model="aura-2-helena-en", + model=None, voice="aura-2-helena-en", language=None, - encoding=encoding, ) # 2. Apply direct init arg overrides (deprecated) @@ -447,6 +442,7 @@ class DeepgramHttpTTSService(TTSService): self._api_key = api_key self._session = aiohttp_session self._base_url = base_url + self._encoding = encoding def can_generate_metrics(self) -> bool: """Check if the service can generate metrics. @@ -476,7 +472,7 @@ class DeepgramHttpTTSService(TTSService): params = { "model": self._settings.voice, - "encoding": self._settings.encoding, + "encoding": self._encoding, "sample_rate": self.sample_rate, "container": "none", } diff --git a/src/pipecat/services/elevenlabs/tts.py b/src/pipecat/services/elevenlabs/tts.py index 2447427ab..c22455e7a 100644 --- a/src/pipecat/services/elevenlabs/tts.py +++ b/src/pipecat/services/elevenlabs/tts.py @@ -201,9 +201,6 @@ class ElevenLabsTTSSettings(TTSSettings): style: Style control for voice expression (0.0 to 1.0). use_speaker_boost: Whether to use speaker boost enhancement. speed: Voice speed control (0.7 to 1.2). - auto_mode: Whether to enable automatic mode optimization. - enable_ssml_parsing: Whether to parse SSML tags in text. - enable_logging: Whether to enable ElevenLabs logging. apply_text_normalization: Text normalization mode ("auto", "on", "off"). """ @@ -212,9 +209,6 @@ class ElevenLabsTTSSettings(TTSSettings): style: float | None | _NotGiven = field(default_factory=lambda: NOT_GIVEN) use_speaker_boost: bool | None | _NotGiven = field(default_factory=lambda: NOT_GIVEN) speed: float | None | _NotGiven = field(default_factory=lambda: NOT_GIVEN) - auto_mode: bool | None | _NotGiven = field(default_factory=lambda: NOT_GIVEN) - enable_ssml_parsing: bool | None | _NotGiven = field(default_factory=lambda: NOT_GIVEN) - enable_logging: bool | None | _NotGiven = field(default_factory=lambda: NOT_GIVEN) apply_text_normalization: Literal["auto", "on", "off"] | None | _NotGiven = field( default_factory=lambda: NOT_GIVEN ) @@ -228,8 +222,6 @@ class ElevenLabsTTSSettings(TTSSettings): {"stability", "similarity_boost", "style", "use_speaker_boost", "speed"} ) - _aliases: ClassVar[Dict[str, str]] = {"voice_id": "voice"} - @dataclass class ElevenLabsHttpTTSSettings(TTSSettings): @@ -255,8 +247,6 @@ class ElevenLabsHttpTTSSettings(TTSSettings): default_factory=lambda: NOT_GIVEN ) - _aliases: ClassVar[Dict[str, str]] = {"voice_id": "voice"} - def calculate_word_times( alignment_info: Mapping[str, Any], @@ -430,6 +420,11 @@ class ElevenLabsTTSService(AudioContextTTSService): model="eleven_turbo_v2_5", ) + # Track init-only URL params through the override chain + _auto_mode = True + _enable_ssml_parsing = None + _enable_logging = None + # 2. Apply direct init arg overrides (deprecated) if voice_id is not None: _warn_deprecated_param("voice_id", ElevenLabsTTSSettings, "voice") @@ -456,11 +451,11 @@ class ElevenLabsTTSService(AudioContextTTSService): if params.speed is not None: default_settings.speed = params.speed if params.auto_mode is not None: - default_settings.auto_mode = str(params.auto_mode).lower() + _auto_mode = str(params.auto_mode).lower() if params.enable_ssml_parsing is not None: - default_settings.enable_ssml_parsing = params.enable_ssml_parsing + _enable_ssml_parsing = params.enable_ssml_parsing if params.enable_logging is not None: - default_settings.enable_logging = params.enable_logging + _enable_logging = params.enable_logging if params.apply_text_normalization is not None: default_settings.apply_text_normalization = params.apply_text_normalization if _pronunciation_dictionary_locators is None: @@ -485,6 +480,11 @@ class ElevenLabsTTSService(AudioContextTTSService): self._api_key = api_key self._url = url + # Init-only WebSocket URL params (not runtime-updatable). + self._auto_mode = _auto_mode + self._enable_ssml_parsing = _enable_ssml_parsing + self._enable_logging = _enable_logging + self._output_format = "" # initialized in start() self._voice_settings = self._set_voice_settings() self._pronunciation_dictionary_locators = _pronunciation_dictionary_locators @@ -518,20 +518,7 @@ class ElevenLabsTTSService(AudioContextTTSService): return language_to_elevenlabs_language(language) def _set_voice_settings(self): - ts = self._settings - voice_setting_keys = [ - "stability", - "similarity_boost", - "style", - "use_speaker_boost", - "speed", - ] - voice_settings = {} - for key in voice_setting_keys: - val = getattr(ts, key, None) - if val is not None: - voice_settings[key] = val - return voice_settings or None + return build_elevenlabs_voice_settings(self._settings) async def _update_settings(self, delta: TTSSettings) -> dict[str, Any]: """Apply a settings delta, reconnecting as needed. @@ -670,13 +657,13 @@ class ElevenLabsTTSService(AudioContextTTSService): voice_id = self._settings.voice model = self._settings.model output_format = self._output_format - url = f"{self._url}/v1/text-to-speech/{voice_id}/multi-stream-input?model_id={model}&output_format={output_format}&auto_mode={self._settings.auto_mode}" + url = f"{self._url}/v1/text-to-speech/{voice_id}/multi-stream-input?model_id={model}&output_format={output_format}&auto_mode={self._auto_mode}" - if self._settings.enable_ssml_parsing: - url += f"&enable_ssml_parsing={self._settings.enable_ssml_parsing}" + if self._enable_ssml_parsing: + url += f"&enable_ssml_parsing={self._enable_ssml_parsing}" - if self._settings.enable_logging: - url += f"&enable_logging={self._settings.enable_logging}" + if self._enable_logging: + url += f"&enable_logging={self._enable_logging}" if self._settings.apply_text_normalization is not None: url += f"&apply_text_normalization={self._settings.apply_text_normalization}" diff --git a/src/pipecat/services/fish/tts.py b/src/pipecat/services/fish/tts.py index af02b4e99..78b021c51 100644 --- a/src/pipecat/services/fish/tts.py +++ b/src/pipecat/services/fish/tts.py @@ -52,25 +52,19 @@ class FishAudioTTSSettings(TTSSettings): """Settings for Fish Audio TTS service. Parameters: - fish_sample_rate: Audio sample rate sent to the API. latency: Latency mode ("normal" or "balanced"). Defaults to "normal". - format: Audio output format. normalize: Whether to normalize audio output. Defaults to True. prosody_speed: Speech speed multiplier (0.5-2.0). Defaults to 1.0. prosody_volume: Volume adjustment in dB. Defaults to 0. reference_id: Reference ID of the voice model. """ - fish_sample_rate: int | _NotGiven = field(default_factory=lambda: NOT_GIVEN) latency: str | None | _NotGiven = field(default_factory=lambda: NOT_GIVEN) - format: str | _NotGiven = field(default_factory=lambda: NOT_GIVEN) normalize: bool | None | _NotGiven = field(default_factory=lambda: NOT_GIVEN) prosody_speed: float | None | _NotGiven = field(default_factory=lambda: NOT_GIVEN) prosody_volume: int | None | _NotGiven = field(default_factory=lambda: NOT_GIVEN) reference_id: str | None | _NotGiven = field(default_factory=lambda: NOT_GIVEN) - _aliases: ClassVar[Dict[str, str]] = {"voice_id": "voice", "sample_rate": "fish_sample_rate"} - @classmethod def from_mapping(cls, settings: Mapping[str, Any]) -> Self: """Construct settings from a plain dict, destructuring legacy nested ``prosody``.""" @@ -179,9 +173,7 @@ class FishAudioTTSService(InterruptibleTTSService): default_settings = FishAudioTTSSettings( model="s1", voice=None, - fish_sample_rate=0, latency="normal", - format=output_format, normalize=True, prosody_speed=1.0, prosody_volume=0, @@ -228,6 +220,10 @@ class FishAudioTTSService(InterruptibleTTSService): self._receive_task = None self._request_id = None + # Init-only audio format config (not runtime-updatable). + self._fish_sample_rate = 0 # Set in start() + self._output_format = output_format + def can_generate_metrics(self) -> bool: """Check if this service can generate processing metrics. @@ -262,7 +258,7 @@ class FishAudioTTSService(InterruptibleTTSService): frame: The start frame containing initialization parameters. """ await super().start(frame) - self._settings.fish_sample_rate = self.sample_rate + self._fish_sample_rate = self.sample_rate await self._connect() async def stop(self, frame: EndFrame): @@ -312,9 +308,9 @@ class FishAudioTTSService(InterruptibleTTSService): # Send initial start message with ormsgpack request_settings = { - "sample_rate": self._settings.fish_sample_rate, + "sample_rate": self._fish_sample_rate, "latency": self._settings.latency, - "format": self._settings.format, + "format": self._output_format, "normalize": self._settings.normalize, "prosody": { "speed": self._settings.prosody_speed, diff --git a/src/pipecat/services/google/tts.py b/src/pipecat/services/google/tts.py index 22ba47821..7cf2ee996 100644 --- a/src/pipecat/services/google/tts.py +++ b/src/pipecat/services/google/tts.py @@ -494,7 +494,6 @@ class GoogleHttpTTSSettings(TTSSettings): Range [0.25, 2.0]. volume: Volume adjustment (e.g., "loud", "soft", "+6dB"). emphasis: Emphasis level for the text. - language: Language for synthesis. Defaults to English. gender: Voice gender preference. google_style: Google-specific voice style. """ @@ -506,7 +505,6 @@ class GoogleHttpTTSSettings(TTSSettings): emphasis: Literal["strong", "moderate", "reduced", "none"] | None | _NotGiven = field( default_factory=lambda: NOT_GIVEN ) - language: str | None | _NotGiven = field(default_factory=lambda: NOT_GIVEN) gender: Literal["male", "female", "neutral"] | None | _NotGiven = field( default_factory=lambda: NOT_GIVEN ) @@ -520,11 +518,9 @@ class GoogleStreamTTSSettings(TTSSettings): """Settings for Google streaming TTS service. Parameters: - language: Language for synthesis. Defaults to English. speaking_rate: The speaking rate, in the range [0.25, 2.0]. """ - language: str | None | _NotGiven = field(default_factory=lambda: NOT_GIVEN) speaking_rate: float | None | _NotGiven = field(default_factory=lambda: NOT_GIVEN) @@ -533,13 +529,11 @@ class GeminiTTSSettings(TTSSettings): """Settings for Gemini TTS service. Parameters: - language: Language for synthesis. Defaults to English. prompt: Optional style instructions for how to synthesize the content. multi_speaker: Whether to enable multi-speaker support. speaker_configs: List of speaker configurations for multi-speaker mode. """ - language: str | None | _NotGiven = field(default_factory=lambda: NOT_GIVEN) prompt: str | None | _NotGiven = field(default_factory=lambda: NOT_GIVEN) multi_speaker: bool | _NotGiven = field(default_factory=lambda: NOT_GIVEN) speaker_configs: list[dict[str, Any]] | None | _NotGiven = field( diff --git a/src/pipecat/services/gradium/tts.py b/src/pipecat/services/gradium/tts.py index 3befb4505..2ade14367 100644 --- a/src/pipecat/services/gradium/tts.py +++ b/src/pipecat/services/gradium/tts.py @@ -6,7 +6,7 @@ import base64 import json -from dataclasses import dataclass, field +from dataclasses import dataclass from typing import Any, AsyncGenerator, Optional from loguru import logger @@ -22,7 +22,7 @@ from pipecat.frames.frames import ( TTSStartedFrame, TTSStoppedFrame, ) -from pipecat.services.settings import NOT_GIVEN, TTSSettings, _NotGiven, _warn_deprecated_param +from pipecat.services.settings import TTSSettings, _warn_deprecated_param from pipecat.services.tts_service import AudioContextTTSService from pipecat.utils.tracing.service_decorators import traced_tts @@ -40,13 +40,9 @@ SAMPLE_RATE = 48000 @dataclass class GradiumTTSSettings(TTSSettings): - """Settings for the Gradium TTS service. + """Settings for the Gradium TTS service.""" - Parameters: - output_format: Audio output format. - """ - - output_format: str | _NotGiven = field(default_factory=lambda: NOT_GIVEN) + pass class GradiumTTSService(AudioContextTTSService): @@ -108,7 +104,6 @@ class GradiumTTSService(AudioContextTTSService): model="default", voice="YTpq7expH9539ERJ", language=None, - output_format="pcm", ) # 2. Apply direct init arg overrides (deprecated) diff --git a/src/pipecat/services/groq/tts.py b/src/pipecat/services/groq/tts.py index 6f9a610e2..18b623fc8 100644 --- a/src/pipecat/services/groq/tts.py +++ b/src/pipecat/services/groq/tts.py @@ -9,7 +9,7 @@ import io import wave from dataclasses import dataclass, field -from typing import AsyncGenerator, ClassVar, Dict, Optional +from typing import AsyncGenerator, Optional from loguru import logger from pydantic import BaseModel @@ -39,16 +39,10 @@ class GroqTTSSettings(TTSSettings): """Settings for the Groq TTS service. Parameters: - output_format: Audio output format. speed: Speech speed multiplier. Defaults to 1.0. - groq_sample_rate: Audio sample rate. """ - output_format: str | _NotGiven = field(default_factory=lambda: NOT_GIVEN) speed: float | None | _NotGiven = field(default_factory=lambda: NOT_GIVEN) - groq_sample_rate: int | _NotGiven = field(default_factory=lambda: NOT_GIVEN) - - _aliases: ClassVar[Dict[str, str]] = {"voice_id": "voice", "sample_rate": "groq_sample_rate"} class GroqTTSService(TTSService): @@ -122,9 +116,7 @@ class GroqTTSService(TTSService): model="canopylabs/orpheus-v1-english", voice="autumn", language="en", - output_format=output_format, speed=1.0, - groq_sample_rate=sample_rate, ) # 2. Apply direct init arg overrides (deprecated) diff --git a/src/pipecat/services/inworld/tts.py b/src/pipecat/services/inworld/tts.py index f650ce620..a1421b2ab 100644 --- a/src/pipecat/services/inworld/tts.py +++ b/src/pipecat/services/inworld/tts.py @@ -71,8 +71,6 @@ class InworldTTSSettings(TTSSettings): """Settings for Inworld TTS services. Parameters: - audio_encoding: Audio encoding format (e.g. LINEAR16). - audio_sample_rate: Audio sample rate in Hz. speaking_rate: Speaking rate for speech synthesis. temperature: Temperature for speech synthesis. auto_mode: Whether to use auto mode. Recommended when texts are sent @@ -84,8 +82,6 @@ class InworldTTSSettings(TTSSettings): timestamp_transport_strategy: Strategy for timestamp transport ("ASYNC" or "SYNC"). """ - audio_encoding: str | _NotGiven = field(default_factory=lambda: NOT_GIVEN) - audio_sample_rate: int | _NotGiven = field(default_factory=lambda: NOT_GIVEN) speaking_rate: float | _NotGiven = field(default_factory=lambda: NOT_GIVEN) temperature: float | _NotGiven = field(default_factory=lambda: NOT_GIVEN) auto_mode: bool | _NotGiven = field(default_factory=lambda: NOT_GIVEN) @@ -93,7 +89,6 @@ class InworldTTSSettings(TTSSettings): timestamp_transport_strategy: str | None | _NotGiven = field(default_factory=lambda: NOT_GIVEN) _aliases: ClassVar[Dict[str, str]] = { - "voice_id": "voice", "voiceId": "voice", "modelId": "model", "applyTextNormalization": "apply_text_normalization", @@ -107,8 +102,6 @@ class InworldTTSSettings(TTSSettings): flat = dict(settings) nested = flat.pop("audioConfig", None) if isinstance(nested, dict): - flat.setdefault("audio_encoding", nested.get("audioEncoding")) - flat.setdefault("audio_sample_rate", nested.get("sampleRateHertz")) flat.setdefault("speaking_rate", nested.get("speakingRate")) return super().from_mapping(flat) @@ -184,8 +177,6 @@ class InworldHttpTTSService(TTSService): model="inworld-tts-1.5-max", voice="Ashley", language=None, - audio_encoding=encoding, - audio_sample_rate=0, speaking_rate=None, temperature=None, timestamp_transport_strategy="ASYNC", @@ -239,6 +230,10 @@ class InworldHttpTTSService(TTSService): self._cumulative_time = 0.0 + # Init-only audio format config (not runtime-updatable). + self._audio_encoding = encoding + self._audio_sample_rate = 0 # Set in start() + def can_generate_metrics(self) -> bool: """Check if this service can generate processing metrics. @@ -254,7 +249,7 @@ class InworldHttpTTSService(TTSService): frame: The start frame. """ await super().start(frame) - self._settings.audio_sample_rate = self.sample_rate + self._audio_sample_rate = self.sample_rate async def stop(self, frame: EndFrame): """Stop the Inworld TTS service. @@ -334,8 +329,8 @@ class InworldHttpTTSService(TTSService): logger.debug(f"{self}: Generating TTS [{text}] (streaming={self._streaming})") audio_config = { - "audioEncoding": self._settings.audio_encoding, - "sampleRateHertz": self._settings.audio_sample_rate, + "audioEncoding": self._audio_encoding, + "sampleRateHertz": self._audio_sample_rate, } if self._settings.speaking_rate is not None: audio_config["speakingRate"] = self._settings.speaking_rate @@ -611,8 +606,6 @@ class InworldTTSService(AudioContextTTSService): model="inworld-tts-1.5-max", voice="Ashley", language=None, - audio_encoding=encoding, - audio_sample_rate=0, speaking_rate=None, temperature=None, apply_text_normalization=None, @@ -686,6 +679,10 @@ class InworldTTSService(AudioContextTTSService): # Track the end time of the last word in the current generation self._generation_end_time = 0.0 + # Init-only audio format config (not runtime-updatable). + self._audio_encoding = encoding + self._audio_sample_rate = 0 # Set in start() + def can_generate_metrics(self) -> bool: """Check if this service can generate processing metrics. @@ -701,7 +698,7 @@ class InworldTTSService(AudioContextTTSService): frame: The start frame. """ await super().start(frame) - self._settings.audio_sample_rate = self.sample_rate + self._audio_sample_rate = self.sample_rate await self._connect() async def stop(self, frame: EndFrame): @@ -1051,8 +1048,8 @@ class InworldTTSService(AudioContextTTSService): context_id: The context ID. """ audio_config = { - "audioEncoding": self._settings.audio_encoding, - "sampleRateHertz": self._settings.audio_sample_rate, + "audioEncoding": self._audio_encoding, + "sampleRateHertz": self._audio_sample_rate, } if self._settings.speaking_rate is not None: audio_config["speakingRate"] = self._settings.speaking_rate diff --git a/src/pipecat/services/kokoro/tts.py b/src/pipecat/services/kokoro/tts.py index 60dfb65ce..0646923f3 100644 --- a/src/pipecat/services/kokoro/tts.py +++ b/src/pipecat/services/kokoro/tts.py @@ -7,7 +7,7 @@ """Kokoro TTS service implementation using kokoro-onnx.""" import os -from dataclasses import dataclass, field +from dataclasses import dataclass from pathlib import Path from typing import AsyncGenerator, Optional @@ -23,7 +23,7 @@ from pipecat.frames.frames import ( TTSStartedFrame, TTSStoppedFrame, ) -from pipecat.services.settings import NOT_GIVEN, TTSSettings, _NotGiven, _warn_deprecated_param +from pipecat.services.settings import TTSSettings, _warn_deprecated_param from pipecat.services.tts_service import TTSService from pipecat.transcriptions.language import Language, resolve_language from pipecat.utils.tracing.service_decorators import traced_tts @@ -91,13 +91,9 @@ def language_to_kokoro_language(language: Language) -> str: @dataclass class KokoroTTSSettings(TTSSettings): - """Settings for the Kokoro TTS service. + """Settings for the Kokoro TTS service.""" - Parameters: - lang_code: Kokoro language code for synthesis. - """ - - lang_code: str | _NotGiven = field(default_factory=lambda: NOT_GIVEN) + pass class KokoroTTSService(TTSService): @@ -156,7 +152,6 @@ class KokoroTTSService(TTSService): model=None, voice=None, language=language_to_kokoro_language(Language.EN), - lang_code=language_to_kokoro_language(Language.EN), ) # 2. Apply direct init arg overrides (deprecated) @@ -168,9 +163,7 @@ class KokoroTTSService(TTSService): if params is not None: _warn_deprecated_param("params", KokoroTTSSettings) if not settings: - lang_code = language_to_kokoro_language(params.language) - default_settings.language = lang_code - default_settings.lang_code = lang_code + default_settings.language = language_to_kokoro_language(params.language) # 4. Apply settings delta (canonical API, always wins) if settings is not None: @@ -181,8 +174,6 @@ class KokoroTTSService(TTSService): **kwargs, ) - self._lang_code = default_settings.lang_code - model_file = Path(model_path) if model_path else KOKORO_CACHE_DIR / "kokoro-v1.0.onnx" voices = Path(voices_path) if voices_path else KOKORO_CACHE_DIR / "voices-v1.0.bin" @@ -196,6 +187,17 @@ class KokoroTTSService(TTSService): """Indicate that this service supports TTFB and usage metrics.""" return True + def language_to_service_language(self, language: Language) -> str: + """Convert a Language enum to kokoro-onnx language format. + + Args: + language: The language to convert. + + Returns: + The kokoro-onnx language code. + """ + return language_to_kokoro_language(language) + @traced_tts async def run_tts(self, text: str, context_id: str) -> AsyncGenerator[Frame, None]: """Synthesize speech from text using kokoro-onnx. @@ -215,7 +217,7 @@ class KokoroTTSService(TTSService): yield TTSStartedFrame(context_id=context_id) stream = self._kokoro.create_stream( - text, voice=self._settings.voice, lang=self._lang_code, speed=1.0 + text, voice=self._settings.voice, lang=self._settings.language, speed=1.0 ) async for samples, sample_rate in stream: diff --git a/src/pipecat/services/lmnt/tts.py b/src/pipecat/services/lmnt/tts.py index 58468bc00..9ee6d8d60 100644 --- a/src/pipecat/services/lmnt/tts.py +++ b/src/pipecat/services/lmnt/tts.py @@ -7,7 +7,7 @@ """LMNT text-to-speech service implementation.""" import json -from dataclasses import dataclass, field +from dataclasses import dataclass from typing import Any, AsyncGenerator, Optional from loguru import logger @@ -17,14 +17,13 @@ from pipecat.frames.frames import ( EndFrame, ErrorFrame, Frame, - InterruptionFrame, StartFrame, TTSAudioRawFrame, TTSStartedFrame, TTSStoppedFrame, ) from pipecat.processors.frame_processor import FrameDirection -from pipecat.services.settings import NOT_GIVEN, TTSSettings, _NotGiven, _warn_deprecated_param +from pipecat.services.settings import TTSSettings, _warn_deprecated_param from pipecat.services.tts_service import InterruptibleTTSService from pipecat.transcriptions.language import Language, resolve_language from pipecat.utils.tracing.service_decorators import traced_tts @@ -75,13 +74,9 @@ def language_to_lmnt_language(language: Language) -> Optional[str]: @dataclass class LmntTTSSettings(TTSSettings): - """Settings for LMNT TTS service. + """Settings for LMNT TTS service.""" - Parameters: - format: Audio output format. Defaults to "raw". - """ - - format: str | _NotGiven = field(default_factory=lambda: NOT_GIVEN) + pass class LmntTTSService(InterruptibleTTSService): @@ -130,7 +125,6 @@ class LmntTTSService(InterruptibleTTSService): model="blizzard", voice=None, language=self.language_to_service_language(language), - format="raw", ) # 2. Apply direct init arg overrides (deprecated) @@ -156,6 +150,7 @@ class LmntTTSService(InterruptibleTTSService): ) self._api_key = api_key + self._output_format = "raw" self._receive_task = None self._context_id: Optional[str] = None @@ -262,7 +257,7 @@ class LmntTTSService(InterruptibleTTSService): init_msg = { "X-API-Key": self._api_key, "voice": self._settings.voice, - "format": self._settings.format, + "format": self._output_format, "sample_rate": self.sample_rate, "language": self._settings.language, "model": self._settings.model, diff --git a/src/pipecat/services/minimax/tts.py b/src/pipecat/services/minimax/tts.py index 2be25aef9..efe8c1fd9 100644 --- a/src/pipecat/services/minimax/tts.py +++ b/src/pipecat/services/minimax/tts.py @@ -12,7 +12,7 @@ for streaming text-to-speech synthesis. import json from dataclasses import dataclass, field -from typing import Any, AsyncGenerator, ClassVar, Dict, Mapping, Optional, Self +from typing import Any, AsyncGenerator, Mapping, Optional, Self import aiohttp from loguru import logger @@ -100,10 +100,6 @@ class MiniMaxTTSSettings(TTSSettings): "disgusted", "surprised", "calm", "fluent"). text_normalization: Enable text normalization (Chinese/English). latex_read: Enable LaTeX formula reading. - audio_bitrate: Audio bitrate in bps. - audio_format: Audio output format. - audio_channel: Number of audio channels. - audio_sample_rate: Audio sample rate in Hz. language_boost: Language boost string for multilingual support. """ @@ -114,14 +110,8 @@ class MiniMaxTTSSettings(TTSSettings): emotion: str | None | _NotGiven = field(default_factory=lambda: NOT_GIVEN) text_normalization: bool | None | _NotGiven = field(default_factory=lambda: NOT_GIVEN) latex_read: bool | None | _NotGiven = field(default_factory=lambda: NOT_GIVEN) - audio_bitrate: int | _NotGiven = field(default_factory=lambda: NOT_GIVEN) - audio_format: str | _NotGiven = field(default_factory=lambda: NOT_GIVEN) - audio_channel: int | _NotGiven = field(default_factory=lambda: NOT_GIVEN) - audio_sample_rate: int | _NotGiven = field(default_factory=lambda: NOT_GIVEN) language_boost: str | None | _NotGiven = field(default_factory=lambda: NOT_GIVEN) - _aliases: ClassVar[Dict[str, str]] = {"voice_id": "voice"} - @classmethod def from_mapping(cls, settings: Mapping[str, Any]) -> Self: """Construct settings from a plain dict, destructuring legacy nested dicts. @@ -140,13 +130,6 @@ class MiniMaxTTSSettings(TTSSettings): flat.setdefault("text_normalization", voice.get("text_normalization")) flat.setdefault("latex_read", voice.get("latex_read")) - audio = flat.pop("audio_setting", None) - if isinstance(audio, dict): - flat.setdefault("audio_bitrate", audio.get("bitrate")) - flat.setdefault("audio_format", audio.get("format")) - flat.setdefault("audio_channel", audio.get("channel")) - flat.setdefault("audio_sample_rate", audio.get("sample_rate")) - return super().from_mapping(flat) @@ -258,10 +241,6 @@ class MiniMaxHttpTTSService(TTSService): emotion=None, text_normalization=None, latex_read=None, - audio_bitrate=128000, - audio_format="pcm", - audio_channel=1, - audio_sample_rate=0, ) # 2. Apply direct init arg overrides (deprecated) @@ -335,6 +314,12 @@ class MiniMaxHttpTTSService(TTSService): self._base_url = f"{base_url}?GroupId={group_id}" self._session = aiohttp_session + # Init-only audio format config + self._audio_bitrate = 128000 + self._audio_format = "pcm" + self._audio_channel = 1 + self._audio_sample_rate = 0 # Set in start() + def can_generate_metrics(self) -> bool: """Check if this service can generate processing metrics. @@ -361,7 +346,7 @@ class MiniMaxHttpTTSService(TTSService): frame: The start frame containing initialization parameters. """ await super().start(frame) - self._settings.audio_sample_rate = self.sample_rate + self._audio_sample_rate = self.sample_rate logger.debug(f"MiniMax TTS initialized with sample_rate: {self.sample_rate}") @traced_tts @@ -399,10 +384,10 @@ class MiniMaxHttpTTSService(TTSService): # Build audio_setting dict for API audio_setting = { - "bitrate": self._settings.audio_bitrate, - "format": self._settings.audio_format, - "channel": self._settings.audio_channel, - "sample_rate": self._settings.audio_sample_rate, + "bitrate": self._audio_bitrate, + "format": self._audio_format, + "channel": self._audio_channel, + "sample_rate": self._audio_sample_rate, } # Create payload from settings diff --git a/src/pipecat/services/neuphonic/tts.py b/src/pipecat/services/neuphonic/tts.py index f6cc6bf68..da14ec2e5 100644 --- a/src/pipecat/services/neuphonic/tts.py +++ b/src/pipecat/services/neuphonic/tts.py @@ -80,13 +80,9 @@ class NeuphonicTTSSettings(TTSSettings): Parameters: speed: Speech speed multiplier. Defaults to 1.0. - encoding: Audio encoding format. - sampling_rate: Audio sample rate. """ speed: float | _NotGiven = field(default_factory=lambda: NOT_GIVEN) - encoding: str | _NotGiven = field(default_factory=lambda: NOT_GIVEN) - sampling_rate: int | _NotGiven = field(default_factory=lambda: NOT_GIVEN) class NeuphonicTTSService(InterruptibleTTSService): @@ -160,8 +156,6 @@ class NeuphonicTTSService(InterruptibleTTSService): voice=None, language=self.language_to_service_language(Language.EN), speed=1.0, - encoding=encoding, - sampling_rate=sample_rate, ) # 2. Apply direct init arg overrides (deprecated) @@ -200,6 +194,8 @@ class NeuphonicTTSService(InterruptibleTTSService): self._receive_task = None self._keepalive_task = None self._context_id: Optional[str] = None + self._encoding = encoding + self._sampling_rate = sample_rate def can_generate_metrics(self) -> bool: """Check if this service can generate processing metrics. @@ -327,8 +323,8 @@ class NeuphonicTTSService(InterruptibleTTSService): tts_config = { "lang_code": self._settings.language, "speed": self._settings.speed, - "encoding": self._settings.encoding, - "sampling_rate": self._settings.sampling_rate, + "encoding": self._encoding, + "sampling_rate": self._sampling_rate, "voice_id": self._settings.voice, } @@ -503,8 +499,6 @@ class NeuphonicHttpTTSService(TTSService): voice=None, language=self.language_to_service_language(Language.EN) or "en", speed=1.0, - encoding=encoding, - sampling_rate=sample_rate, ) # 2. Apply direct init arg overrides (deprecated) @@ -536,6 +530,7 @@ class NeuphonicHttpTTSService(TTSService): self._api_key = api_key self._session = aiohttp_session self._base_url = url.rstrip("/") + self._encoding = encoding def can_generate_metrics(self) -> bool: """Check if this service can generate processing metrics. @@ -629,7 +624,7 @@ class NeuphonicHttpTTSService(TTSService): payload = { "text": text, "lang_code": self._settings.language, - "encoding": self._settings.encoding, + "encoding": self._encoding, "sampling_rate": self.sample_rate, "speed": self._settings.speed, } diff --git a/src/pipecat/services/resembleai/tts.py b/src/pipecat/services/resembleai/tts.py index f0a8a988a..e1c1cf68a 100644 --- a/src/pipecat/services/resembleai/tts.py +++ b/src/pipecat/services/resembleai/tts.py @@ -8,8 +8,8 @@ import base64 import json -from dataclasses import dataclass, field -from typing import AsyncGenerator, ClassVar, Dict, Optional +from dataclasses import dataclass +from typing import AsyncGenerator, Optional from loguru import logger @@ -23,7 +23,7 @@ from pipecat.frames.frames import ( TTSStartedFrame, TTSStoppedFrame, ) -from pipecat.services.settings import NOT_GIVEN, TTSSettings, _NotGiven, _warn_deprecated_param +from pipecat.services.settings import TTSSettings, _warn_deprecated_param from pipecat.services.tts_service import AudioContextTTSService from pipecat.utils.tracing.service_decorators import traced_tts @@ -38,22 +38,9 @@ except ModuleNotFoundError as e: @dataclass class ResembleAITTSSettings(TTSSettings): - """Settings for Resemble AI TTS service. + """Settings for Resemble AI TTS service.""" - Parameters: - precision: PCM bit depth (PCM_32, PCM_24, PCM_16, or MULAW). - output_format: Audio format (wav or mp3). - resemble_sample_rate: Audio sample rate sent to the API. - """ - - precision: str | None | _NotGiven = field(default_factory=lambda: NOT_GIVEN) - output_format: str | None | _NotGiven = field(default_factory=lambda: NOT_GIVEN) - resemble_sample_rate: int | None | _NotGiven = field(default_factory=lambda: NOT_GIVEN) - - _aliases: ClassVar[Dict[str, str]] = { - "voice_id": "voice", - "sample_rate": "resemble_sample_rate", - } + pass class ResembleAITTSService(AudioContextTTSService): @@ -100,21 +87,12 @@ class ResembleAITTSService(AudioContextTTSService): model=None, voice=None, language=None, - precision="PCM_16", - output_format="wav", - resemble_sample_rate=22050, ) # 2. Apply direct init arg overrides (deprecated) if voice_id is not None: _warn_deprecated_param("voice_id", ResembleAITTSSettings, "voice") default_settings.voice = voice_id - if precision is not None: - default_settings.precision = precision - if output_format is not None: - default_settings.output_format = output_format - if sample_rate is not None: - default_settings.resemble_sample_rate = sample_rate # 3. No params for this service @@ -133,6 +111,11 @@ class ResembleAITTSService(AudioContextTTSService): self._api_key = api_key self._url = url + # Init-only audio format config (not runtime-updatable). + self._precision = precision or "PCM_16" + self._output_format = output_format or "wav" + self._resemble_sample_rate = 0 # Set in start() + self._websocket = None self._request_id_counter = 0 self._receive_task = None @@ -174,9 +157,9 @@ class ResembleAITTSService(AudioContextTTSService): "data": text, "binary_response": False, # Use JSON frames to get timestamps "request_id": self._request_id_counter, # ResembleAI only accepts number - "output_format": self._settings.output_format, - "sample_rate": self._settings.resemble_sample_rate, - "precision": self._settings.precision, + "output_format": self._output_format, + "sample_rate": self._resemble_sample_rate, + "precision": self._precision, "no_audio_header": True, } @@ -190,7 +173,7 @@ class ResembleAITTSService(AudioContextTTSService): frame: The start frame containing initialization parameters. """ await super().start(frame) - self._settings.resemble_sample_rate = self.sample_rate + self._resemble_sample_rate = self.sample_rate await self._connect() async def stop(self, frame: EndFrame): diff --git a/src/pipecat/services/rime/tts.py b/src/pipecat/services/rime/tts.py index 613d58f3a..04ebcd5fc 100644 --- a/src/pipecat/services/rime/tts.py +++ b/src/pipecat/services/rime/tts.py @@ -76,8 +76,6 @@ class RimeTTSSettings(TTSSettings): """Settings for Rime WS JSON and HTTP TTS services. Parameters: - audioFormat: Audio output format. - samplingRate: Audio sample rate. segment: Text segmentation mode ("immediate", "bySentence", "never"). speedAlpha: Speech speed multiplier (mistv2 only). reduceLatency: Whether to reduce latency at potential quality cost (mistv2 only). @@ -91,8 +89,6 @@ class RimeTTSSettings(TTSSettings): top_p: Cumulative probability threshold (arcana only, 0.0-1.0). """ - audioFormat: str | _NotGiven = field(default_factory=lambda: NOT_GIVEN) - samplingRate: int | _NotGiven = field(default_factory=lambda: NOT_GIVEN) segment: str | None | _NotGiven = field(default_factory=lambda: NOT_GIVEN) speedAlpha: float | None | _NotGiven = field(default_factory=lambda: NOT_GIVEN) reduceLatency: bool | None | _NotGiven = field(default_factory=lambda: NOT_GIVEN) @@ -113,16 +109,12 @@ class RimeNonJsonTTSSettings(TTSSettings): """Settings for Rime non-JSON WS TTS service. Parameters: - audioFormat: Audio output format. - samplingRate: Audio sample rate. segment: Text segmentation mode ("immediate", "bySentence", "never"). repetition_penalty: Token repetition penalty (1.0-2.0). temperature: Sampling temperature (0.0-1.0). top_p: Cumulative probability threshold (0.0-1.0). """ - audioFormat: str | _NotGiven = field(default_factory=lambda: NOT_GIVEN) - samplingRate: int | _NotGiven = field(default_factory=lambda: NOT_GIVEN) segment: str | None | _NotGiven = field(default_factory=lambda: NOT_GIVEN) repetition_penalty: float | None | _NotGiven = field(default_factory=lambda: NOT_GIVEN) temperature: float | None | _NotGiven = field(default_factory=lambda: NOT_GIVEN) @@ -230,8 +222,6 @@ class RimeTTSService(AudioContextTTSService): default_settings = RimeTTSSettings( model="arcana", voice=None, - audioFormat="pcm", - samplingRate=0, # updated in start() language=None, segment=None, inlineSpeedAlpha=None, @@ -293,6 +283,10 @@ class RimeTTSService(AudioContextTTSService): **kwargs, ) + # Init-only audio format fields (not runtime-updatable) + self._audio_format = "pcm" + self._sampling_rate = 0 # updated in start() + if not text_aggregator: # Always skip tags added for spelled-out text # Note: This is primarily to support backwards compatibility. @@ -342,8 +336,8 @@ class RimeTTSService(AudioContextTTSService): params: dict[str, Any] = { "speaker": self._settings.voice, "modelId": self._settings.model, - "audioFormat": self._settings.audioFormat, - "samplingRate": self._settings.samplingRate, + "audioFormat": self._audio_format, + "samplingRate": self._sampling_rate, } if self._settings.language is not None: params["lang"] = self._settings.language @@ -437,7 +431,7 @@ class RimeTTSService(AudioContextTTSService): frame: The start frame containing initialization parameters. """ await super().start(frame) - self._settings.samplingRate = self.sample_rate + self._sampling_rate = self.sample_rate await self._connect() async def stop(self, frame: EndFrame): @@ -737,8 +731,6 @@ class RimeHttpTTSService(TTSService): model="mistv2", voice=None, language="eng", - audioFormat="pcm", - samplingRate=0, segment=None, speedAlpha=None, reduceLatency=None, @@ -789,6 +781,9 @@ class RimeHttpTTSService(TTSService): self._session = aiohttp_session self._base_url = "https://users.rime.ai/v1/rime-tts" + # Init-only audio format fields (not runtime-updatable) + self._audio_format = "pcm" + def can_generate_metrics(self) -> bool: """Check if this service can generate processing metrics. @@ -974,8 +969,6 @@ class RimeNonJsonTTSService(InterruptibleTTSService): default_settings = RimeNonJsonTTSSettings( voice=None, model="arcana", - audioFormat=audio_format, - samplingRate=sample_rate, language=None, segment=None, repetition_penalty=None, @@ -1017,6 +1010,11 @@ class RimeNonJsonTTSService(InterruptibleTTSService): settings=default_settings, **kwargs, ) + + # Init-only audio format fields (not runtime-updatable) + self._audio_format = audio_format + self._sampling_rate = sample_rate + self._api_key = api_key self._url = url # Add any extra parameters for future compatibility @@ -1053,7 +1051,7 @@ class RimeNonJsonTTSService(InterruptibleTTSService): frame: The start frame containing initialization parameters. """ await super().start(frame) - self._settings.samplingRate = self.sample_rate + self._sampling_rate = self.sample_rate await self._connect() async def stop(self, frame: EndFrame): @@ -1101,8 +1099,8 @@ class RimeNonJsonTTSService(InterruptibleTTSService): settings_dict = { "speaker": self._settings.voice, "modelId": self._settings.model, - "audioFormat": self._settings.audioFormat, - "samplingRate": self._settings.samplingRate, + "audioFormat": self._audio_format, + "samplingRate": self._sampling_rate, } if self._settings.language is not None: settings_dict["lang"] = self._settings.language diff --git a/src/pipecat/services/sarvam/tts.py b/src/pipecat/services/sarvam/tts.py index cf00dd8c7..659a58bdd 100644 --- a/src/pipecat/services/sarvam/tts.py +++ b/src/pipecat/services/sarvam/tts.py @@ -250,7 +250,6 @@ class SarvamHttpTTSSettings(TTSSettings): """Settings for Sarvam HTTP TTS service. Parameters: - language: Sarvam language code. enable_preprocessing: Whether to enable text preprocessing. Defaults to False. **Note:** Always enabled for bulbul:v3-beta (cannot be disabled). pace: Speech pace multiplier. Defaults to 1.0. @@ -263,16 +262,13 @@ class SarvamHttpTTSSettings(TTSSettings): temperature: Controls output randomness for bulbul:v3-beta (0.01 to 1.0). Lower values = more deterministic, higher = more random. Defaults to 0.6. **Note:** Only supported for bulbul:v3-beta. Ignored for v2. - sample_rate: Audio sample rate. """ - language: str | None | _NotGiven = field(default_factory=lambda: NOT_GIVEN) enable_preprocessing: bool | None | _NotGiven = field(default_factory=lambda: NOT_GIVEN) pace: float | None | _NotGiven = field(default_factory=lambda: NOT_GIVEN) pitch: float | None | _NotGiven = field(default_factory=lambda: NOT_GIVEN) loudness: float | None | _NotGiven = field(default_factory=lambda: NOT_GIVEN) temperature: float | None | _NotGiven = field(default_factory=lambda: NOT_GIVEN) - sarvam_sample_rate: int | _NotGiven = field(default_factory=lambda: NOT_GIVEN) @dataclass @@ -280,19 +276,12 @@ class SarvamTTSSettings(TTSSettings): """Settings for Sarvam WebSocket TTS service. Parameters: - language: Sarvam language code (e.g. ``"hi-IN"``). Uses the standard - ``TTSSettings.language`` field. - speech_sample_rate: Audio sample rate as string. enable_preprocessing: Enable text preprocessing. Defaults to False. **Note:** Always enabled for bulbul:v3-beta. min_buffer_size: Minimum characters to buffer before generating audio. Lower values reduce latency but may affect quality. Defaults to 50. max_chunk_length: Maximum characters processed in a single chunk. Controls memory usage and processing efficiency. Defaults to 150. - output_audio_codec: Audio codec format. Options: linear16, mulaw, alaw, - opus, flac, aac, wav, mp3. Defaults to "linear16". - output_audio_bitrate: Audio bitrate (32k, 64k, 96k, 128k, 192k). - Defaults to "128k". pace: Speech pace multiplier. Defaults to 1.0. - bulbul:v2: Range 0.3 to 3.0 - bulbul:v3-beta: Range 0.5 to 2.0 @@ -307,12 +296,9 @@ class SarvamTTSSettings(TTSSettings): _aliases: ClassVar[Dict[str, str]] = {"target_language_code": "language"} - speech_sample_rate: str | _NotGiven = field(default_factory=lambda: NOT_GIVEN) enable_preprocessing: bool | None | _NotGiven = field(default_factory=lambda: NOT_GIVEN) min_buffer_size: int | None | _NotGiven = field(default_factory=lambda: NOT_GIVEN) max_chunk_length: int | None | _NotGiven = field(default_factory=lambda: NOT_GIVEN) - output_audio_codec: str | None | _NotGiven = field(default_factory=lambda: NOT_GIVEN) - output_audio_bitrate: str | None | _NotGiven = field(default_factory=lambda: NOT_GIVEN) pace: float | None | _NotGiven = field(default_factory=lambda: NOT_GIVEN) pitch: float | None | _NotGiven = field(default_factory=lambda: NOT_GIVEN) loudness: float | None | _NotGiven = field(default_factory=lambda: NOT_GIVEN) @@ -587,7 +573,6 @@ class SarvamHttpTTSService(TTSService): frame: The start frame containing initialization parameters. """ await super().start(frame) - self._settings.sarvam_sample_rate = self.sample_rate @traced_tts async def run_tts(self, text: str, context_id: str) -> AsyncGenerator[Frame, None]: @@ -881,12 +866,9 @@ class SarvamTTSService(InterruptibleTTSService): model="bulbul:v2", voice="anushka", language="en-IN", - speech_sample_rate="22050", enable_preprocessing=False, min_buffer_size=50, max_chunk_length=150, - output_audio_codec="linear16", - output_audio_bitrate="128k", pace=1.0, pitch=None, loudness=None, @@ -901,6 +883,10 @@ class SarvamTTSService(InterruptibleTTSService): _warn_deprecated_param("voice_id", SarvamTTSSettings, "voice") default_settings.voice = voice_id + # Init-only audio format fields (not runtime-updatable) + output_audio_codec = "linear16" + output_audio_bitrate = "128k" + # 3. Apply params overrides — only if settings not provided if params is not None: _warn_deprecated_param("params", SarvamTTSSettings) @@ -916,9 +902,9 @@ class SarvamTTSService(InterruptibleTTSService): if params.max_chunk_length is not None: default_settings.max_chunk_length = params.max_chunk_length if params.output_audio_codec is not None: - default_settings.output_audio_codec = params.output_audio_codec + output_audio_codec = params.output_audio_codec if params.output_audio_bitrate is not None: - default_settings.output_audio_bitrate = params.output_audio_bitrate + output_audio_bitrate = params.output_audio_bitrate if params.pace is not None: default_settings.pace = params.pace if params.pitch is not None: @@ -943,7 +929,6 @@ class SarvamTTSService(InterruptibleTTSService): # Set default sample rate based on model if not specified if sample_rate is None: sample_rate = self._config.default_sample_rate - default_settings.speech_sample_rate = str(sample_rate) # Set default voice based on model if not specified via any mechanism if voice_id is None and (settings is None or settings.voice is NOT_GIVEN): @@ -986,6 +971,11 @@ class SarvamTTSService(InterruptibleTTSService): **kwargs, ) + # Init-only audio format fields (not runtime-updatable) + self._speech_sample_rate = str(sample_rate) + self._output_audio_codec = output_audio_codec + self._output_audio_bitrate = output_audio_bitrate + # WebSocket endpoint URL with model query parameter self._websocket_url = f"{url}?model={resolved_model}" self._api_key = api_key @@ -1022,7 +1012,7 @@ class SarvamTTSService(InterruptibleTTSService): await super().start(frame) # WebSocket API expects sample rate as string - self._settings.speech_sample_rate = str(self.sample_rate) + self._speech_sample_rate = str(self.sample_rate) await self._connect() async def stop(self, frame: EndFrame): @@ -1140,12 +1130,12 @@ class SarvamTTSService(InterruptibleTTSService): config_data = { "target_language_code": self._settings.language, "speaker": self._settings.voice, - "speech_sample_rate": self._settings.speech_sample_rate, + "speech_sample_rate": self._speech_sample_rate, "enable_preprocessing": self._settings.enable_preprocessing, "min_buffer_size": self._settings.min_buffer_size, "max_chunk_length": self._settings.max_chunk_length, - "output_audio_codec": self._settings.output_audio_codec, - "output_audio_bitrate": self._settings.output_audio_bitrate, + "output_audio_codec": self._output_audio_codec, + "output_audio_bitrate": self._output_audio_bitrate, "pace": self._settings.pace, "model": self._settings.model, } diff --git a/src/pipecat/services/xtts/tts.py b/src/pipecat/services/xtts/tts.py index adf11da6a..ea7cb0b8b 100644 --- a/src/pipecat/services/xtts/tts.py +++ b/src/pipecat/services/xtts/tts.py @@ -10,7 +10,7 @@ This module provides integration with Coqui XTTS streaming server for text-to-speech synthesis using local Docker deployment. """ -from dataclasses import dataclass, field +from dataclasses import dataclass from typing import AsyncGenerator, Dict, Optional import aiohttp @@ -25,7 +25,7 @@ from pipecat.frames.frames import ( TTSStartedFrame, TTSStoppedFrame, ) -from pipecat.services.settings import NOT_GIVEN, TTSSettings, _NotGiven, _warn_deprecated_param +from pipecat.services.settings import TTSSettings, _warn_deprecated_param from pipecat.services.tts_service import TTSService from pipecat.transcriptions.language import Language, resolve_language from pipecat.utils.tracing.service_decorators import traced_tts @@ -72,13 +72,9 @@ def language_to_xtts_language(language: Language) -> Optional[str]: @dataclass class XTTSTTSSettings(TTSSettings): - """Settings for XTTS TTS service. + """Settings for XTTS TTS service.""" - Parameters: - base_url: Base URL of the XTTS streaming server. - """ - - base_url: str | _NotGiven = field(default_factory=lambda: NOT_GIVEN) + pass class XTTSService(TTSService): @@ -123,7 +119,6 @@ class XTTSService(TTSService): model=None, voice=None, language=self.language_to_service_language(language), - base_url=base_url, ) # 2. Apply direct init arg overrides (deprecated) @@ -140,6 +135,10 @@ class XTTSService(TTSService): settings=default_settings, **kwargs, ) + + # Init-only fields (not runtime-updatable) + self._base_url = base_url + self._studio_speakers: Optional[Dict[str, Any]] = None self._aiohttp_session = aiohttp_session @@ -175,7 +174,7 @@ class XTTSService(TTSService): if self._studio_speakers: return - async with self._aiohttp_session.get(self._settings.base_url + "/studio_speakers") as r: + async with self._aiohttp_session.get(self._base_url + "/studio_speakers") as r: if r.status != 200: text = await r.text() await self.push_error( @@ -203,7 +202,7 @@ class XTTSService(TTSService): embeddings = self._studio_speakers[self._settings.voice] - url = self._settings.base_url + "/tts_stream" + url = self._base_url + "/tts_stream" payload = { "text": text.replace(".", "").replace("*", ""), From 034e81ff1840a980085f6ed2856dafa6ad8100ef Mon Sep 17 00:00:00 2001 From: Mark Backman Date: Wed, 4 Mar 2026 16:09:10 -0500 Subject: [PATCH 0810/1060] Update STT service settings --- .../07c-interruptible-deepgram-sagemaker.py | 17 +- .../07g-interruptible-openai-http.py | 17 +- src/pipecat/services/assemblyai/models.py | 3 + src/pipecat/services/assemblyai/stt.py | 308 +++++++++--------- src/pipecat/services/aws/stt.py | 67 ++-- src/pipecat/services/azure/stt.py | 16 +- src/pipecat/services/cartesia/stt.py | 69 ++-- src/pipecat/services/deepgram/flux/stt.py | 23 +- .../services/deepgram/sagemaker/stt.py | 178 ++++++---- .../services/deepgram/sagemaker/tts.py | 3 +- src/pipecat/services/deepgram/stt.py | 156 +++++++-- src/pipecat/services/elevenlabs/stt.py | 26 +- src/pipecat/services/fal/stt.py | 53 +-- src/pipecat/services/gladia/config.py | 4 + src/pipecat/services/gladia/stt.py | 61 ++-- src/pipecat/services/gradium/stt.py | 26 +- src/pipecat/services/groq/stt.py | 49 ++- src/pipecat/services/nvidia/stt.py | 27 +- src/pipecat/services/openai/stt.py | 82 +++-- src/pipecat/services/openai/tts.py | 2 + src/pipecat/services/sambanova/stt.py | 43 ++- src/pipecat/services/sarvam/stt.py | 72 ++-- src/pipecat/services/soniox/stt.py | 32 +- src/pipecat/services/speechmatics/stt.py | 25 +- src/pipecat/services/whisper/base_stt.py | 35 +- src/pipecat/services/whisper/stt.py | 45 +-- tests/test_settings.py | 49 ++- 27 files changed, 829 insertions(+), 659 deletions(-) diff --git a/examples/foundational/07c-interruptible-deepgram-sagemaker.py b/examples/foundational/07c-interruptible-deepgram-sagemaker.py index 406f95445..2f51bda8d 100644 --- a/examples/foundational/07c-interruptible-deepgram-sagemaker.py +++ b/examples/foundational/07c-interruptible-deepgram-sagemaker.py @@ -22,9 +22,12 @@ from pipecat.processors.aggregators.llm_response_universal import ( ) from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport -from pipecat.services.aws.llm import AWSBedrockLLMService +from pipecat.services.aws.llm import AWSBedrockLLMService, AWSBedrockLLMSettings from pipecat.services.deepgram.sagemaker.stt import DeepgramSageMakerSTTService -from pipecat.services.deepgram.sagemaker.tts import DeepgramSageMakerTTSService +from pipecat.services.deepgram.sagemaker.tts import ( + DeepgramSageMakerTTSService, + DeepgramSageMakerTTSSettings, +) from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams @@ -69,14 +72,18 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): tts = DeepgramSageMakerTTSService( endpoint_name=os.getenv("SAGEMAKER_TTS_ENDPOINT_NAME"), region=os.getenv("AWS_REGION"), - voice="aura-2-andromeda-en", + settings=DeepgramSageMakerTTSSettings( + voice="aura-2-andromeda-en", + ), ) llm = AWSBedrockLLMService( aws_region=os.getenv("AWS_REGION"), - model="us.amazon.nova-pro-v1:0", - params=AWSBedrockLLMService.InputParams(temperature=0.8), system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + settings=AWSBedrockLLMSettings( + model="us.amazon.nova-pro-v1:0", + temperature=0.8, + ), ) context = LLMContext() diff --git a/examples/foundational/07g-interruptible-openai-http.py b/examples/foundational/07g-interruptible-openai-http.py index 05c98ca59..721d1795f 100644 --- a/examples/foundational/07g-interruptible-openai-http.py +++ b/examples/foundational/07g-interruptible-openai-http.py @@ -23,8 +23,8 @@ from pipecat.processors.aggregators.llm_response_universal import ( from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport from pipecat.services.openai.llm import OpenAILLMService -from pipecat.services.openai.stt import OpenAISTTService -from pipecat.services.openai.tts import OpenAITTSService +from pipecat.services.openai.stt import OpenAISTTService, OpenAISTTSettings +from pipecat.services.openai.tts import OpenAITTSService, OpenAITTSSettings from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams @@ -54,11 +54,18 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): stt = OpenAISTTService( api_key=os.getenv("OPENAI_API_KEY"), - model="gpt-4o-transcribe", - prompt="Expect words related to dogs, such as breed names.", + settings=OpenAISTTSettings( + model="gpt-4o-transcribe", + prompt="Expect words related to dogs, such as breed names.", + ), ) - tts = OpenAITTSService(api_key=os.getenv("OPENAI_API_KEY"), voice="ballad") + tts = OpenAITTSService( + api_key=os.getenv("OPENAI_API_KEY"), + settings=OpenAITTSSettings( + voice="ballad", + ), + ) llm = OpenAILLMService( api_key=os.getenv("OPENAI_API_KEY"), diff --git a/src/pipecat/services/assemblyai/models.py b/src/pipecat/services/assemblyai/models.py index 2c6b3a1dc..efc13d482 100644 --- a/src/pipecat/services/assemblyai/models.py +++ b/src/pipecat/services/assemblyai/models.py @@ -124,6 +124,9 @@ AnyMessage = BeginMessage | TurnMessage | SpeechStartedMessage | TerminationMess class AssemblyAIConnectionParams(BaseModel): """Configuration parameters for AssemblyAI WebSocket connection. + .. deprecated:: 0.0.105 + Use ``settings=AssemblyAISTTSettings(foo=...)`` instead. + Parameters: sample_rate: Audio sample rate in Hz. Defaults to 16000. encoding: Audio encoding format. Defaults to "pcm_s16le". diff --git a/src/pipecat/services/assemblyai/stt.py b/src/pipecat/services/assemblyai/stt.py index e140f7543..ec4130ea5 100644 --- a/src/pipecat/services/assemblyai/stt.py +++ b/src/pipecat/services/assemblyai/stt.py @@ -13,7 +13,7 @@ WebSocket API for streaming audio transcription. import asyncio import json from dataclasses import dataclass, field -from typing import Any, AsyncGenerator, Dict, Optional +from typing import Any, AsyncGenerator, Dict, List, Optional from urllib.parse import urlencode from loguru import logger @@ -83,15 +83,38 @@ def map_language_from_assemblyai(language_code: str) -> Language: class AssemblyAISTTSettings(STTSettings): """Settings for the AssemblyAI STT service. - See :class:`AssemblyAIConnectionParams` for detailed parameter descriptions. - Parameters: - connection_params: Connection configuration parameters. + formatted_finals: Whether to enable transcript formatting. + word_finalization_max_wait_time: Maximum time to wait for word + finalization in milliseconds. + end_of_turn_confidence_threshold: Confidence threshold for + end-of-turn detection. + min_turn_silence: Minimum silence duration when confident about + end-of-turn. + max_turn_silence: Maximum silence duration before forcing + end-of-turn. + keyterms_prompt: List of key terms to guide transcription. + prompt: Optional text prompt to guide the transcription. Only + used when model is "u3-rt-pro". + language_detection: Enable automatic language detection. + format_turns: Whether to format transcript turns. + speaker_labels: Enable speaker diarization. """ - connection_params: AssemblyAIConnectionParams | _NotGiven = field( + formatted_finals: bool | _NotGiven = field(default_factory=lambda: NOT_GIVEN) + word_finalization_max_wait_time: int | None | _NotGiven = field( default_factory=lambda: NOT_GIVEN ) + end_of_turn_confidence_threshold: float | None | _NotGiven = field( + default_factory=lambda: NOT_GIVEN + ) + min_turn_silence: int | None | _NotGiven = field(default_factory=lambda: NOT_GIVEN) + max_turn_silence: int | None | _NotGiven = field(default_factory=lambda: NOT_GIVEN) + keyterms_prompt: List[str] | None | _NotGiven = field(default_factory=lambda: NOT_GIVEN) + prompt: str | None | _NotGiven = field(default_factory=lambda: NOT_GIVEN) + language_detection: bool | None | _NotGiven = field(default_factory=lambda: NOT_GIVEN) + format_turns: bool | _NotGiven = field(default_factory=lambda: NOT_GIVEN) + speaker_labels: bool | None | _NotGiven = field(default_factory=lambda: NOT_GIVEN) class AssemblyAISTTService(WebsocketSTTService): @@ -110,6 +133,8 @@ class AssemblyAISTTService(WebsocketSTTService): api_key: str, language: Optional[Language] = None, api_endpoint_base_url: str = "wss://streaming.assemblyai.com/v3/ws", + sample_rate: int = 16000, + encoding: str = "pcm_s16le", connection_params: Optional[AssemblyAIConnectionParams] = None, vad_force_turn_endpoint: bool = True, should_interrupt: bool = True, @@ -123,8 +148,18 @@ class AssemblyAISTTService(WebsocketSTTService): Args: api_key: AssemblyAI API key for authentication. language: Language code for transcription. Defaults to English (Language.EN). + + .. deprecated:: 0.0.105 + Use ``settings=AssemblyAISTTSettings(language=...)`` instead. + api_endpoint_base_url: WebSocket endpoint URL. Defaults to AssemblyAI's streaming endpoint. - connection_params: Connection configuration parameters. Defaults to AssemblyAIConnectionParams(). + sample_rate: Audio sample rate in Hz. Defaults to 16000. + encoding: Audio encoding format. Defaults to "pcm_s16le". + connection_params: Connection configuration parameters. + + .. deprecated:: 0.0.105 + Use ``settings=AssemblyAISTTSettings(...)`` instead. + vad_force_turn_endpoint: Controls turn detection mode. When True (Pipecat mode, default): Forces AssemblyAI to return finals ASAP so Pipecat's turn detection (e.g., Smart Turn) decides when the user is done. @@ -135,7 +170,6 @@ class AssemblyAISTTService(WebsocketSTTService): When False (AssemblyAI turn detection mode, u3-rt-pro only): AssemblyAI's model controls turn endings using built-in turn detection. - Uses AssemblyAI API defaults for all parameters (unless user explicitly sets them) - - Respects all user-provided connection_params as-is - Emits UserStarted/StoppedSpeakingFrame from STT - No ForceEndpoint on VAD stop should_interrupt: Whether to interrupt the bot when the user starts speaking @@ -145,39 +179,80 @@ class AssemblyAISTTService(WebsocketSTTService): Use {speaker} for speaker label and {text} for transcript text. Example: "<{speaker}>{text}" or "{speaker}: {text}" If None, transcript text is not modified. Defaults to None. - settings: Runtime-updatable settings. When provided alongside other + settings: Runtime-updatable settings. When provided alongside deprecated parameters, ``settings`` values take precedence. ttfs_p99_latency: P99 latency from speech end to final transcript in seconds. Override for your deployment. See https://github.com/pipecat-ai/stt-benchmark **kwargs: Additional arguments passed to parent STTService class. """ - # Resolve connection_params early — needed for validation and turn mode config - _connection_params = connection_params or AssemblyAIConnectionParams() + # 1. Initialize default_settings with hardcoded defaults + default_settings = AssemblyAISTTSettings( + model="u3-rt-pro", + language=Language.EN, + formatted_finals=True, + word_finalization_max_wait_time=None, + end_of_turn_confidence_threshold=None, + min_turn_silence=None, + max_turn_silence=None, + keyterms_prompt=None, + prompt=None, + language_detection=None, + format_turns=True, + speaker_labels=None, + ) - # AssemblyAI turn detection mode (vad_force_turn_endpoint=False) requires the - # SpeechStarted event for reliable barge-in. Only u3-rt-pro supports - # this. Other models must use Pipecat turn detection. - is_u3_pro = _connection_params.speech_model == "u3-rt-pro" + # 2. Apply direct init arg overrides (deprecated) + if language is not None: + _warn_deprecated_param("language", AssemblyAISTTSettings, "language") + default_settings.language = language + + # 3. Apply connection_params overrides (deprecated) — only if settings not provided + if connection_params is not None: + _warn_deprecated_param("connection_params", AssemblyAISTTSettings) + if not settings: + sample_rate = connection_params.sample_rate + encoding = connection_params.encoding + default_settings.model = connection_params.speech_model + default_settings.formatted_finals = connection_params.formatted_finals + default_settings.word_finalization_max_wait_time = ( + connection_params.word_finalization_max_wait_time + ) + default_settings.end_of_turn_confidence_threshold = ( + connection_params.end_of_turn_confidence_threshold + ) + default_settings.min_turn_silence = connection_params.min_turn_silence + default_settings.max_turn_silence = connection_params.max_turn_silence + default_settings.keyterms_prompt = connection_params.keyterms_prompt + default_settings.prompt = connection_params.prompt + default_settings.language_detection = connection_params.language_detection + default_settings.format_turns = connection_params.format_turns + default_settings.speaker_labels = connection_params.speaker_labels + + # 4. Apply settings delta (canonical API, always wins) + if settings is not None: + default_settings.apply_update(settings) + + # 5. Validate final settings + is_u3_pro = default_settings.model == "u3-rt-pro" if not vad_force_turn_endpoint and not is_u3_pro: raise ValueError( f"AssemblyAI turn detection mode (vad_force_turn_endpoint=False) requires " f"u3-rt-pro for SpeechStarted support. Either set " - f"vad_force_turn_endpoint=True for {_connection_params.speech_model}, " - f"or use speech_model='u3-rt-pro'." + f"vad_force_turn_endpoint=True for {default_settings.model}, " + f"or use model='u3-rt-pro'." ) - # Validate that prompt and keyterms_prompt are not both set - if _connection_params.prompt is not None and _connection_params.keyterms_prompt is not None: + if default_settings.prompt is not None and default_settings.keyterms_prompt is not None: raise ValueError( "The prompt and keyterms_prompt parameters cannot be used in the same request. " "Please choose either one or the other based on your use case. When you use " "keyterms_prompt, your boosted words are appended to the default prompt automatically. " - "Or to boost within prompt: + Make sure to boost the words in the audio. " + "Or to boost within prompt: + Make sure to boost the words " + "in the audio. " "For more info go to: https://www.assemblyai.com/docs/streaming/universal-3-pro" ) - # Warn if user sets a custom prompt (recommend testing without one first) - if _connection_params.prompt is not None: + if default_settings.prompt is not None: logger.warning( "Custom prompt detected. Prompting is a beta feature. We recommend testing " "with no prompt first, as this will use our optimized default prompt for " @@ -186,35 +261,12 @@ class AssemblyAISTTService(WebsocketSTTService): "https://www.assemblyai.com/docs/streaming/prompting" ) - # When vad_force_turn_endpoint is enabled, configure connection params - # for Pipecat turn detection mode (fast finals for smart turn analyzer) + # 6. Configure pipecat turn mode (mutates default_settings) if vad_force_turn_endpoint: - _connection_params = self._configure_pipecat_turn_mode(_connection_params, is_u3_pro) - - # 1. Initialize default_settings with hardcoded defaults - default_settings = AssemblyAISTTSettings( - model=None, - language=Language.EN, - connection_params=AssemblyAIConnectionParams(), - ) - - # 2. Apply direct init arg overrides (deprecated) - if language is not None: - _warn_deprecated_param("language", AssemblyAISTTSettings, "language") - default_settings.language = language - - # 3. Apply connection_params overrides — only if settings not provided - if connection_params is not None: - _warn_deprecated_param("connection_params", AssemblyAISTTSettings) - if not settings: - default_settings.connection_params = _connection_params - - # 4. Apply settings delta (canonical API, always wins) - if settings is not None: - default_settings.apply_update(settings) + self._configure_pipecat_turn_mode(default_settings, is_u3_pro) super().__init__( - sample_rate=_connection_params.sample_rate, + sample_rate=sample_rate, ttfs_p99_latency=ttfs_p99_latency, settings=default_settings, **kwargs, @@ -226,6 +278,9 @@ class AssemblyAISTTService(WebsocketSTTService): self._should_interrupt = should_interrupt self._speaker_format = speaker_format + # Init-only audio config (not runtime-updatable) + self._encoding = encoding + self._termination_event = asyncio.Event() self._received_termination = False self._connected = False @@ -238,10 +293,8 @@ class AssemblyAISTTService(WebsocketSTTService): self._user_speaking = False - def _configure_pipecat_turn_mode( - self, connection_params: AssemblyAIConnectionParams, is_u3_pro: bool - ) -> AssemblyAIConnectionParams: - """Configure connection params for Pipecat turn detection mode. + def _configure_pipecat_turn_mode(self, settings: AssemblyAISTTSettings, is_u3_pro: bool): + """Configure settings for Pipecat turn detection mode. When vad_force_turn_endpoint is enabled, force AssemblyAI to return finals as fast as possible so Pipecat's smart turn analyzer can decide @@ -260,46 +313,31 @@ class AssemblyAISTTService(WebsocketSTTService): - max_turn_silence: not set (API default) Args: - connection_params: The user-provided connection parameters. + settings: The settings to configure in place. is_u3_pro: Whether using u3-rt-pro model. - - Returns: - Updated connection parameters configured for Pipecat turn mode. """ - updates = {} - if is_u3_pro: # u3-rt-pro: Synchronize max_turn_silence with min_turn_silence - min_silence = connection_params.min_turn_silence + min_silence = settings.min_turn_silence if min_silence is None: min_silence = 100 # Warn if user set max_turn_silence (will be overridden) - if connection_params.max_turn_silence is not None: + if settings.max_turn_silence is not None: logger.warning( - f"Your max_turn_silence value ({connection_params.max_turn_silence}ms) will be " + f"Your max_turn_silence value ({settings.max_turn_silence}ms) will be " f"OVERRIDDEN in Pipecat mode (vad_force_turn_endpoint=True). It will be set to " f"{min_silence}ms (matching min_turn_silence) and SENT to " f"AssemblyAI to avoid double turn detection. To use your max_turn_silence as-is, " f"switch to AssemblyAI turn detection mode (vad_force_turn_endpoint=False)." ) - updates = { - "min_turn_silence": min_silence, - "max_turn_silence": min_silence, - } + settings.min_turn_silence = min_silence + settings.max_turn_silence = min_silence else: # universal-streaming: Different configuration (works differently) - updates = { - "end_of_turn_confidence_threshold": 1.0, - "min_turn_silence": 160, - } - - # Apply updates if any - if updates: - connection_params = connection_params.model_copy(update=updates) - - return connection_params + settings.end_of_turn_confidence_threshold = 1.0 + settings.min_turn_silence = 160 def can_generate_metrics(self) -> bool: """Check if the service can generate metrics. @@ -309,18 +347,11 @@ class AssemblyAISTTService(WebsocketSTTService): """ return True - async def _update_settings(self, delta: STTSettings) -> dict[str, Any]: - """Apply a settings delta and send UpdateConfiguration if connected. - - Stores settings changes and sends UpdateConfiguration message to AssemblyAI - without reconnecting. Supports updating: - - keyterms_prompt: List of terms to boost (can be empty array to clear) - - prompt: Custom prompt text (u3-rt-pro only) - - max_turn_silence: Maximum silence before forcing turn end - - min_turn_silence: Silence before EOT check + async def _update_settings(self, delta: AssemblyAISTTSettings) -> dict[str, Any]: + """Apply a settings delta and reconnect to apply changes. Args: - delta: A :class:`STTSettings` (or ``AssemblyAISTTSettings``) delta. + delta: A settings delta with updated values. Returns: Dict mapping changed field names to their previous values. @@ -330,72 +361,9 @@ class AssemblyAISTTService(WebsocketSTTService): if not changed: return changed - # If websocket is connected, send UpdateConfiguration for supported params - if ( - self._websocket - and self._websocket.state is State.OPEN - and "connection_params" in changed - ): - # Build UpdateConfiguration message - update_config = {"type": "UpdateConfiguration"} - conn_params = self._settings.connection_params - - # Get the old connection_params to see what changed - old_conn_params = changed.get("connection_params") - - # Check each potentially changed parameter - if ( - old_conn_params is None - or conn_params.keyterms_prompt != old_conn_params.keyterms_prompt - ): - if conn_params.keyterms_prompt is not None: - update_config["keyterms_prompt"] = conn_params.keyterms_prompt - logger.info(f"Updating keyterms_prompt to: {conn_params.keyterms_prompt}") - - if old_conn_params is None or conn_params.prompt != old_conn_params.prompt: - if conn_params.prompt is not None: - if conn_params.speech_model != "u3-rt-pro": - logger.warning( - f"prompt parameter is only supported with u3-rt-pro model, " - f"current model is {conn_params.speech_model}" - ) - else: - update_config["prompt"] = conn_params.prompt - logger.info(f"Updating prompt") - - if ( - old_conn_params is None - or conn_params.max_turn_silence != old_conn_params.max_turn_silence - ): - if conn_params.max_turn_silence is not None: - update_config["max_turn_silence"] = conn_params.max_turn_silence - logger.info(f"Updating max_turn_silence to: {conn_params.max_turn_silence}ms") - - if ( - old_conn_params is None - or conn_params.min_turn_silence != old_conn_params.min_turn_silence - ): - if conn_params.min_turn_silence is not None: - update_config["min_turn_silence"] = conn_params.min_turn_silence - logger.info(f"Updating min_turn_silence to: {conn_params.min_turn_silence}ms") - - # Send update if we have parameters to update - if len(update_config) > 1: # More than just "type" - try: - await self._websocket.send(json.dumps(update_config)) - logger.info(f"Sent UpdateConfiguration: {update_config}") - except Exception as e: - logger.error(f"Failed to send UpdateConfiguration: {e}") - elif "connection_params" in changed: - logger.warning( - "Connection params changed but WebSocket not connected. " - "Settings will be applied on next connection." - ) - - # Warn about other settings that can't be changed dynamically - other_changes = {k: v for k, v in changed.items() if k not in ["connection_params"]} - if other_changes: - self._warn_unhandled_updated_settings(other_changes) + # Reconnect to apply updated settings (they become WS query params) + await self._disconnect() + await self._connect() return changed @@ -473,19 +441,41 @@ class AssemblyAISTTService(WebsocketSTTService): def _build_ws_url(self) -> str: """Build WebSocket URL with query parameters using urllib.parse.urlencode.""" - params = {} - for k, v in self._settings.connection_params.model_dump().items(): - # Skip deprecated parameter - it's been migrated to min_turn_silence - if k == "min_end_of_turn_silence_when_confident": - continue + s = self._settings + params: dict[str, Any] = {} + + # Init-only audio config + params["sample_rate"] = self.sample_rate + params["encoding"] = self._encoding + + # Map model → speech_model (AssemblyAI API naming) + if s.model is not None: + params["speech_model"] = s.model + + # Settings fields (skip None values) + optional_fields = { + "formatted_finals": s.formatted_finals, + "word_finalization_max_wait_time": s.word_finalization_max_wait_time, + "end_of_turn_confidence_threshold": s.end_of_turn_confidence_threshold, + "min_turn_silence": s.min_turn_silence, + "max_turn_silence": s.max_turn_silence, + "prompt": s.prompt, + "language_detection": s.language_detection, + "format_turns": s.format_turns, + "speaker_labels": s.speaker_labels, + } + + for k, v in optional_fields.items(): if v is not None: - if k == "keyterms_prompt": - params[k] = json.dumps(v) - elif isinstance(v, bool): + if isinstance(v, bool): params[k] = str(v).lower() else: params[k] = v + # Special handling for keyterms_prompt (needs JSON encoding) + if s.keyterms_prompt is not None: + params["keyterms_prompt"] = json.dumps(s.keyterms_prompt) + if params: query_string = urlencode(params) return f"{self._api_endpoint_base_url}?{query_string}" @@ -717,7 +707,7 @@ class AssemblyAISTTService(WebsocketSTTService): # Determine if this is a final turn from AssemblyAI is_final_turn = message.end_of_turn and ( - not self._settings.connection_params.format_turns or message.turn_is_formatted + not self._settings.format_turns or message.turn_is_formatted ) if self._vad_force_turn_endpoint: diff --git a/src/pipecat/services/aws/stt.py b/src/pipecat/services/aws/stt.py index 451c8a695..dd2f2f97b 100644 --- a/src/pipecat/services/aws/stt.py +++ b/src/pipecat/services/aws/stt.py @@ -14,7 +14,7 @@ import json import os import random import string -from dataclasses import dataclass, field +from dataclasses import dataclass from typing import Any, AsyncGenerator, Optional from loguru import logger @@ -29,7 +29,7 @@ from pipecat.frames.frames import ( TranscriptionFrame, ) from pipecat.services.aws.utils import build_event_message, decode_event, get_presigned_url -from pipecat.services.settings import NOT_GIVEN, STTSettings, _NotGiven, _warn_deprecated_param +from pipecat.services.settings import STTSettings, _warn_deprecated_param from pipecat.services.stt_latency import AWS_TRANSCRIBE_TTFS_P99 from pipecat.services.stt_service import WebsocketSTTService from pipecat.transcriptions.language import Language, resolve_language @@ -47,21 +47,9 @@ except ModuleNotFoundError as e: @dataclass class AWSTranscribeSTTSettings(STTSettings): - """Settings for the AWS Transcribe STT service. + """Settings for the AWS Transcribe STT service.""" - Parameters: - sample_rate: Audio sample rate in Hz (8000 or 16000). - media_encoding: Audio encoding format (e.g. "linear16"). - number_of_channels: Number of audio channels. - show_speaker_label: Whether to show speaker labels. - enable_channel_identification: Whether to enable channel identification. - """ - - sample_rate: int | _NotGiven = field(default_factory=lambda: NOT_GIVEN) - media_encoding: str | _NotGiven = field(default_factory=lambda: NOT_GIVEN) - number_of_channels: int | _NotGiven = field(default_factory=lambda: NOT_GIVEN) - show_speaker_label: bool | _NotGiven = field(default_factory=lambda: NOT_GIVEN) - enable_channel_identification: bool | _NotGiven = field(default_factory=lambda: NOT_GIVEN) + pass class AWSTranscribeSTTService(WebsocketSTTService): @@ -94,11 +82,9 @@ class AWSTranscribeSTTService(WebsocketSTTService): aws_access_key_id: AWS access key ID. If None, uses AWS_ACCESS_KEY_ID environment variable. aws_session_token: AWS session token for temporary credentials. If None, uses AWS_SESSION_TOKEN environment variable. region: AWS region for the service. - sample_rate: Audio sample rate in Hz. Must be 8000 or 16000. - - .. deprecated:: 0.0.105 - Use ``settings=AWSTranscribeSTTSettings(sample_rate=...)`` instead. - + sample_rate: Audio sample rate in Hz. If None, uses the pipeline sample rate. + AWS Transcribe only supports 8000 or 16000 Hz; other values are + clamped to 16000 Hz at connect time. language: Language for transcription. .. deprecated:: 0.0.105 @@ -113,17 +99,9 @@ class AWSTranscribeSTTService(WebsocketSTTService): # 1. Initialize default_settings with hardcoded defaults default_settings = AWSTranscribeSTTSettings( language=self.language_to_service_language(Language.EN) or "en-US", - sample_rate=16000, - media_encoding="linear16", - number_of_channels=1, - show_speaker_label=False, - enable_channel_identification=False, ) # 2. Apply direct init arg overrides (deprecated) - if sample_rate is not None: - _warn_deprecated_param("sample_rate", AWSTranscribeSTTSettings, "sample_rate") - default_settings.sample_rate = sample_rate if language is not None: _warn_deprecated_param("language", AWSTranscribeSTTSettings, "language") default_settings.language = self.language_to_service_language(language) or "en-US" @@ -135,17 +113,17 @@ class AWSTranscribeSTTService(WebsocketSTTService): default_settings.apply_update(settings) super().__init__( + sample_rate=sample_rate, ttfs_p99_latency=ttfs_p99_latency, settings=default_settings, **kwargs, ) - # Validate sample rate - AWS Transcribe only supports 8000 Hz or 16000 Hz - if default_settings.sample_rate not in [8000, 16000]: - logger.warning( - f"AWS Transcribe only supports 8000 Hz or 16000 Hz sample rates. Converting from {default_settings.sample_rate} Hz to 16000 Hz." - ) - self._settings.sample_rate = 16000 + # Init-only connection config (not runtime-updatable). + self._media_encoding = "linear16" + self._number_of_channels = 1 + self._show_speaker_label = False + self._enable_channel_identification = False self._credentials = { "aws_access_key_id": aws_access_key_id or os.getenv("AWS_ACCESS_KEY_ID"), @@ -293,6 +271,15 @@ class AWSTranscribeSTTService(WebsocketSTTService): if not language_code: raise ValueError(f"Unsupported language: {language_code}") + # Validate sample rate — AWS Transcribe only supports 8000 or 16000 Hz + connect_sample_rate = self.sample_rate + if connect_sample_rate not in (8000, 16000): + logger.warning( + f"AWS Transcribe only supports 8000 Hz or 16000 Hz sample rates. " + f"Converting from {connect_sample_rate} Hz to 16000 Hz." + ) + connect_sample_rate = 16000 + # Generate random websocket key websocket_key = "".join( random.choices( @@ -318,14 +305,14 @@ class AWSTranscribeSTTService(WebsocketSTTService): }, language_code=language_code, media_encoding=self.get_service_encoding( - self._settings.media_encoding + self._media_encoding ), # Convert to AWS format - sample_rate=self._settings.sample_rate, - number_of_channels=self._settings.number_of_channels, + sample_rate=connect_sample_rate, + number_of_channels=self._number_of_channels, enable_partial_results_stabilization=True, partial_results_stability="high", - show_speaker_label=self._settings.show_speaker_label, - enable_channel_identification=self._settings.enable_channel_identification, + show_speaker_label=self._show_speaker_label, + enable_channel_identification=self._enable_channel_identification, ) logger.debug(f"{self} Connecting to WebSocket with URL: {presigned_url[:100]}...") diff --git a/src/pipecat/services/azure/stt.py b/src/pipecat/services/azure/stt.py index 2527f0bb0..8e6204c5e 100644 --- a/src/pipecat/services/azure/stt.py +++ b/src/pipecat/services/azure/stt.py @@ -11,7 +11,7 @@ Speech SDK for real-time audio transcription. """ import asyncio -from dataclasses import dataclass, field +from dataclasses import dataclass from typing import Any, AsyncGenerator, Optional from loguru import logger @@ -26,7 +26,7 @@ from pipecat.frames.frames import ( TranscriptionFrame, ) from pipecat.services.azure.common import language_to_azure_language -from pipecat.services.settings import NOT_GIVEN, STTSettings, _NotGiven, _warn_deprecated_param +from pipecat.services.settings import STTSettings, _warn_deprecated_param from pipecat.services.stt_latency import AZURE_TTFS_P99 from pipecat.services.stt_service import STTService from pipecat.transcriptions.language import Language @@ -53,15 +53,9 @@ except ModuleNotFoundError as e: @dataclass class AzureSTTSettings(STTSettings): - """Settings for the Azure STT service. + """Settings for the Azure STT service.""" - Parameters: - region: Azure region for the Speech service. - sample_rate: Audio sample rate in Hz. - """ - - region: str | _NotGiven = field(default_factory=lambda: NOT_GIVEN) - sample_rate: int | None | _NotGiven = field(default_factory=lambda: NOT_GIVEN) + pass class AzureSTTService(STTService): @@ -110,9 +104,7 @@ class AzureSTTService(STTService): # 1. Initialize default_settings with hardcoded defaults default_settings = AzureSTTSettings( model=None, - region=region, language=language_to_azure_language(Language.EN_US), - sample_rate=sample_rate, ) # 2. Apply direct init arg overrides (deprecated) diff --git a/src/pipecat/services/cartesia/stt.py b/src/pipecat/services/cartesia/stt.py index aa66b102e..67416016e 100644 --- a/src/pipecat/services/cartesia/stt.py +++ b/src/pipecat/services/cartesia/stt.py @@ -12,7 +12,7 @@ the Cartesia Live transcription API for real-time speech recognition. import json import urllib.parse -from dataclasses import dataclass, field +from dataclasses import dataclass from typing import Any, AsyncGenerator, Optional from loguru import logger @@ -28,7 +28,7 @@ from pipecat.frames.frames import ( VADUserStoppedSpeakingFrame, ) from pipecat.processors.frame_processor import FrameDirection -from pipecat.services.settings import NOT_GIVEN, STTSettings, _NotGiven, _warn_deprecated_param +from pipecat.services.settings import STTSettings, _warn_deprecated_param from pipecat.services.stt_latency import CARTESIA_TTFS_P99 from pipecat.services.stt_service import WebsocketSTTService from pipecat.transcriptions.language import Language @@ -46,20 +46,17 @@ except ModuleNotFoundError as e: @dataclass class CartesiaSTTSettings(STTSettings): - """Settings for the Cartesia STT service. + """Settings for the Cartesia STT service.""" - Parameters: - encoding: Audio encoding format (e.g. ``"pcm_s16le"``). - """ - - encoding: str | _NotGiven = field(default_factory=lambda: NOT_GIVEN) + pass class CartesiaLiveOptions: """Configuration options for Cartesia Live STT service. - Manages transcription parameters including model selection, language, - audio encoding format, and sample rate settings. + .. deprecated:: 0.0.105 + Use ``settings=CartesiaSTTSettings(...)`` for model/language and + direct ``__init__`` parameters for encoding/sample_rate instead. """ def __init__( @@ -156,7 +153,8 @@ class CartesiaSTTService(WebsocketSTTService): *, api_key: str, base_url: str = "", - sample_rate: int = 16000, + encoding: str = "pcm_s16le", + sample_rate: Optional[int] = None, live_options: Optional[CartesiaLiveOptions] = None, settings: Optional[CartesiaSTTSettings] = None, ttfs_p99_latency: Optional[float] = CARTESIA_TTFS_P99, @@ -167,44 +165,42 @@ class CartesiaSTTService(WebsocketSTTService): Args: api_key: Authentication key for Cartesia API. base_url: Custom API endpoint URL. If empty, uses default. - sample_rate: Audio sample rate in Hz. Defaults to 16000. + encoding: Audio encoding format. Defaults to "pcm_s16le". + sample_rate: Audio sample rate in Hz. If None, uses the pipeline + sample rate. live_options: Configuration options for transcription service. - settings: Runtime-updatable settings. When provided alongside - ``live_options``, ``settings`` values take precedence. + + .. deprecated:: 0.0.105 + Use ``settings=CartesiaSTTSettings(...)`` for model/language + and direct init parameters for encoding/sample_rate instead. + + settings: Runtime-updatable settings. When provided alongside deprecated + parameters, ``settings`` values take precedence. ttfs_p99_latency: P99 latency from speech end to final transcript in seconds. Override for your deployment. See https://github.com/pipecat-ai/stt-benchmark **kwargs: Additional arguments passed to parent STTService. """ - sample_rate = sample_rate or (live_options.sample_rate if live_options else None) - # 1. Initialize default_settings with hardcoded defaults default_settings = CartesiaSTTSettings( model="ink-whisper", language=Language.EN.value, - encoding="pcm_s16le", ) - # 2. (no deprecated direct args for this service) - - # 3. Apply live_options overrides — only if settings not provided + # 2. Apply live_options overrides — only if settings not provided if live_options is not None: _warn_deprecated_param("live_options", CartesiaSTTSettings) if not settings: - lo_dict = live_options.to_dict() - # Filter out "None" string values - lo_dict = { - k: v - for k, v in lo_dict.items() - if (not isinstance(v, str) or v != "None") and k != "sample_rate" - } - if "model" in lo_dict: - default_settings.model = lo_dict["model"] - if "language" in lo_dict: - default_settings.language = lo_dict["language"] - if "encoding" in lo_dict: - default_settings.encoding = lo_dict["encoding"] + if live_options.sample_rate and sample_rate is None: + sample_rate = live_options.sample_rate + if live_options.encoding: + encoding = live_options.encoding + if live_options.model: + default_settings.model = live_options.model + if live_options.language: + lang = live_options.language + default_settings.language = lang.value if isinstance(lang, Language) else lang - # 4. Apply settings delta (canonical API, always wins) + # 3. Apply settings delta (canonical API, always wins) if settings is not None: default_settings.apply_update(settings) @@ -221,6 +217,9 @@ class CartesiaSTTService(WebsocketSTTService): self._base_url = base_url or "api.cartesia.ai" self._receive_task = None + # Init-only audio config (not runtime-updatable). + self._encoding = encoding + def can_generate_metrics(self) -> bool: """Check if the service can generate processing metrics. @@ -339,7 +338,7 @@ class CartesiaSTTService(WebsocketSTTService): params = { "model": self._settings.model, "language": self._settings.language, - "encoding": self._settings.encoding, + "encoding": self._encoding, "sample_rate": str(self.sample_rate), } ws_url = f"wss://{self._base_url}/stt/websocket?{urllib.parse.urlencode(params)}" diff --git a/src/pipecat/services/deepgram/flux/stt.py b/src/pipecat/services/deepgram/flux/stt.py index ae5364f60..1e7f135b2 100644 --- a/src/pipecat/services/deepgram/flux/stt.py +++ b/src/pipecat/services/deepgram/flux/stt.py @@ -81,20 +81,16 @@ class DeepgramFluxSTTSettings(STTSettings): eot_timeout_ms: Time in ms after speech to finish a turn regardless of EOT confidence (default 5000). keyterm: Keyterms to boost recognition accuracy for specialized terminology. - mip_opt_out: Opt out of the Deepgram Model Improvement Program (default False). tag: Tags to label requests for identification during usage reporting. min_confidence: Minimum confidence required to create a TranscriptionFrame. - encoding: Audio encoding format (e.g. ``"linear16"``). """ eager_eot_threshold: float | None | _NotGiven = field(default_factory=lambda: NOT_GIVEN) eot_threshold: float | None | _NotGiven = field(default_factory=lambda: NOT_GIVEN) eot_timeout_ms: int | None | _NotGiven = field(default_factory=lambda: NOT_GIVEN) keyterm: list | _NotGiven = field(default_factory=lambda: NOT_GIVEN) - mip_opt_out: bool | None | _NotGiven = field(default_factory=lambda: NOT_GIVEN) tag: list | _NotGiven = field(default_factory=lambda: NOT_GIVEN) min_confidence: float | None | _NotGiven = field(default_factory=lambda: NOT_GIVEN) - encoding: str | _NotGiven = field(default_factory=lambda: NOT_GIVEN) class DeepgramFluxSTTService(WebsocketSTTService): @@ -158,6 +154,7 @@ class DeepgramFluxSTTService(WebsocketSTTService): api_key: str, url: str = "wss://api.deepgram.com/v2/listen", sample_rate: Optional[int] = None, + mip_opt_out: Optional[bool] = None, model: Optional[str] = None, flux_encoding: str = "linear16", params: Optional[InputParams] = None, @@ -170,7 +167,9 @@ class DeepgramFluxSTTService(WebsocketSTTService): Args: api_key: Deepgram API key for authentication. Required for API access. url: WebSocket URL for the Deepgram Flux API. Defaults to the preview endpoint. - sample_rate: Audio sample rate in Hz. If None, uses the rate from params or 16000. + sample_rate: Audio sample rate in Hz. If None, uses the pipeline + sample rate. + mip_opt_out: Opt out of the Deepgram Model Improvement Program. model: Deepgram Flux model to use for transcription. .. deprecated:: 0.0.105 @@ -221,12 +220,10 @@ class DeepgramFluxSTTService(WebsocketSTTService): default_settings = DeepgramFluxSTTSettings( model="flux-general-en", language=Language.EN, - encoding=flux_encoding, eager_eot_threshold=None, eot_threshold=None, eot_timeout_ms=None, keyterm=[], - mip_opt_out=None, tag=[], min_confidence=None, ) @@ -244,9 +241,10 @@ class DeepgramFluxSTTService(WebsocketSTTService): default_settings.eot_threshold = params.eot_threshold default_settings.eot_timeout_ms = params.eot_timeout_ms default_settings.keyterm = params.keyterm or [] - default_settings.mip_opt_out = params.mip_opt_out default_settings.tag = params.tag or [] default_settings.min_confidence = params.min_confidence + if params.mip_opt_out is not None: + mip_opt_out = params.mip_opt_out # 4. Apply settings delta (canonical API, always wins) if settings is not None: @@ -261,8 +259,11 @@ class DeepgramFluxSTTService(WebsocketSTTService): self._api_key = api_key self._url = url self._should_interrupt = should_interrupt + self._encoding = flux_encoding + self._mip_opt_out = mip_opt_out self._websocket_url = None self._receive_task = None + # Flux event handlers self._register_event_handler("on_start_of_turn") self._register_event_handler("on_turn_resumed") @@ -448,7 +449,7 @@ class DeepgramFluxSTTService(WebsocketSTTService): url_params = [ f"model={self._settings.model}", f"sample_rate={self.sample_rate}", - f"encoding={self._settings.encoding}", + f"encoding={self._encoding}", ] if self._settings.eager_eot_threshold is not None: @@ -460,8 +461,8 @@ class DeepgramFluxSTTService(WebsocketSTTService): if self._settings.eot_timeout_ms is not None: url_params.append(f"eot_timeout_ms={self._settings.eot_timeout_ms}") - if self._settings.mip_opt_out is not None: - url_params.append(f"mip_opt_out={str(self._settings.mip_opt_out).lower()}") + if self._mip_opt_out is not None: + url_params.append(f"mip_opt_out={str(self._mip_opt_out).lower()}") # Add keyterm parameters (can have multiple) for keyterm in self._settings.keyterm: diff --git a/src/pipecat/services/deepgram/sagemaker/stt.py b/src/pipecat/services/deepgram/sagemaker/stt.py index d7a867e38..4f29b227f 100644 --- a/src/pipecat/services/deepgram/sagemaker/stt.py +++ b/src/pipecat/services/deepgram/sagemaker/stt.py @@ -14,7 +14,7 @@ languages, and various Deepgram features. import asyncio import json -from dataclasses import dataclass, field +from dataclasses import dataclass, fields from typing import Any, AsyncGenerator, Optional from loguru import logger @@ -32,32 +32,23 @@ from pipecat.frames.frames import ( ) from pipecat.processors.frame_processor import FrameDirection from pipecat.services.aws.sagemaker.bidi_client import SageMakerBidiClient -from pipecat.services.settings import NOT_GIVEN, STTSettings, _NotGiven, _warn_deprecated_param +from pipecat.services.deepgram.stt import DeepgramSTTSettings, LiveOptions +from pipecat.services.settings import STTSettings, _warn_deprecated_param, is_given from pipecat.services.stt_latency import DEEPGRAM_SAGEMAKER_TTFS_P99 from pipecat.services.stt_service import STTService from pipecat.transcriptions.language import Language from pipecat.utils.time import time_now_iso8601 from pipecat.utils.tracing.service_decorators import traced_stt -try: - from deepgram import LiveOptions -except ModuleNotFoundError as e: - logger.error(f"Exception: {e}") - logger.error( - "In order to use DeepgramSageMakerSTTService, you need to `pip install pipecat-ai[deepgram,sagemaker]`." - ) - raise Exception(f"Missing module: {e}") - @dataclass -class DeepgramSageMakerSTTSettings(STTSettings): +class DeepgramSageMakerSTTSettings(DeepgramSTTSettings): """Settings for the Deepgram SageMaker STT service. - Parameters: - live_options: Deepgram LiveOptions for the SageMaker connection. + Inherits all fields from :class:`DeepgramSTTSettings`. """ - live_options: Any | _NotGiven = field(default_factory=lambda: NOT_GIVEN) + pass class DeepgramSageMakerSTTService(STTService): @@ -72,14 +63,13 @@ class DeepgramSageMakerSTTService(STTService): - AWS credentials configured (via environment variables, AWS CLI, or instance metadata) - A deployed SageMaker endpoint with Deepgram model: https://developers.deepgram.com/docs/deploy-amazon-sagemaker - - Deepgram SDK for LiveOptions configuration Example:: stt = DeepgramSageMakerSTTService( endpoint_name="my-deepgram-endpoint", region="us-east-2", - live_options=LiveOptions( + settings=DeepgramSageMakerSTTSettings( model="nova-3", language="en", interim_results=True, @@ -95,7 +85,11 @@ class DeepgramSageMakerSTTService(STTService): *, endpoint_name: str, region: str, + encoding: str = "linear16", + channels: int = 1, + multichannel: bool = False, sample_rate: Optional[int] = None, + mip_opt_out: Optional[bool] = None, live_options: Optional[LiveOptions] = None, settings: Optional[DeepgramSageMakerSTTSettings] = None, ttfs_p99_latency: Optional[float] = DEEPGRAM_SAGEMAKER_TTFS_P99, @@ -107,11 +101,20 @@ class DeepgramSageMakerSTTService(STTService): endpoint_name: Name of the SageMaker endpoint with Deepgram model deployed (e.g., "my-deepgram-nova-3-endpoint"). region: AWS region where the endpoint is deployed (e.g., "us-east-2"). - sample_rate: Audio sample rate in Hz. If None, uses value from - live_options or defaults to the value from StartFrame. - live_options: Deepgram LiveOptions configuration. Treated as a - delta from a set of sensible defaults — only the fields you - set are overridden; all others keep their default values. + encoding: Audio encoding format. Defaults to "linear16". + channels: Number of audio channels. Defaults to 1. + multichannel: Transcribe each audio channel independently. + Defaults to False. + sample_rate: Audio sample rate in Hz. If None, uses the pipeline + sample rate. + mip_opt_out: Opt out of Deepgram model improvement program. + live_options: Legacy configuration options. + + .. deprecated:: 0.0.105 + Use ``settings=DeepgramSageMakerSTTSettings(...)`` for + runtime-updatable fields and direct init parameters for + connection-level config. + settings: Runtime-updatable settings. When provided alongside ``live_options``, ``settings`` values take precedence (applied after the ``live_options`` merge). @@ -119,43 +122,63 @@ class DeepgramSageMakerSTTService(STTService): Override for your deployment. See https://github.com/pipecat-ai/stt-benchmark **kwargs: Additional arguments passed to the parent STTService. """ - sample_rate = sample_rate or (live_options.sample_rate if live_options else None) - - default_options = LiveOptions( - encoding="linear16", - language=Language.EN, - model="nova-3", - channels=1, - interim_results=True, - punctuate=True, - ) - # 1. Initialize default_settings with hardcoded defaults default_settings = DeepgramSageMakerSTTSettings( model="nova-3", language=Language.EN, - live_options=default_options, + detect_entities=False, + diarize=False, + dictation=False, + endpointing=None, + interim_results=True, + keyterm=None, + keywords=None, + numerals=False, + profanity_filter=True, + punctuate=True, + redact=None, + replace=None, + search=None, + smart_format=False, + utterance_end_ms=None, + vad_events=False, ) - # 2. (no deprecated direct args like model= for this service) - - # 3. Apply live_options overrides — only if settings not provided + # 2. Apply live_options overrides — only if settings not provided if live_options is not None: _warn_deprecated_param("live_options", DeepgramSageMakerSTTSettings) if not settings: - # Merge user live_options onto defaults - merged_dict = {**default_options.to_dict(), **live_options.to_dict()} - merged_live_options = LiveOptions(**merged_dict) - default_settings.live_options = merged_live_options - if hasattr(live_options, "model") and live_options.model is not None: - default_settings.model = live_options.model - if hasattr(live_options, "language") and live_options.language is not None: - default_settings.language = live_options.language + # Extract init-only fields from live_options + if live_options.sample_rate is not None and sample_rate is None: + sample_rate = live_options.sample_rate + if live_options.encoding is not None: + encoding = live_options.encoding + if live_options.channels is not None: + channels = live_options.channels + if live_options.multichannel is not None: + multichannel = live_options.multichannel + if live_options.mip_opt_out is not None: + mip_opt_out = live_options.mip_opt_out - # 4. Apply settings delta (canonical API, always wins) + # Build settings delta from remaining fields + init_only = { + "sample_rate", + "encoding", + "channels", + "multichannel", + "mip_opt_out", + } + lo_dict = {k: v for k, v in live_options.to_dict().items() if k not in init_only} + delta = DeepgramSageMakerSTTSettings.from_mapping(lo_dict) + default_settings.apply_update(delta) + + # 3. Apply settings delta (canonical API, always wins) if settings is not None: default_settings.apply_update(settings) + # Sync extra to top-level fields so self._settings is unambiguous + default_settings._sync_extra_to_fields() + super().__init__( sample_rate=sample_rate, ttfs_p99_latency=ttfs_p99_latency, @@ -166,6 +189,12 @@ class DeepgramSageMakerSTTService(STTService): self._endpoint_name = endpoint_name self._region = region + # Init-only connection config (not runtime-updatable). + self._encoding = encoding + self._channels = channels + self._multichannel = multichannel + self._mip_opt_out = mip_opt_out + self._client: Optional[SageMakerBidiClient] = None self._response_task: Optional[asyncio.Task] = None self._keepalive_task: Optional[asyncio.Task] = None @@ -185,6 +214,10 @@ class DeepgramSageMakerSTTService(STTService): if not changed: return changed + # Sync extra to fields after the update so self._settings stays unambiguous + if isinstance(self._settings, DeepgramSTTSettings): + self._settings._sync_extra_to_fields() + # TODO: someday we could reconnect here to apply updated settings. # Code might look something like the below: # await self._disconnect() @@ -237,6 +270,43 @@ class DeepgramSageMakerSTTService(STTService): yield ErrorFrame(error=f"Unknown error occurred: {e}") yield None + def _build_query_string(self) -> str: + """Build query string from current settings and init-only connection config.""" + params = {} + s = self._settings + + # Declared Deepgram-specific fields from settings + for f in fields(s): + if f.name in ("model", "language", "extra") or f.name.startswith("_"): + continue + value = getattr(s, f.name) + if not is_given(value) or value is None: + continue + params[f.name] = str(value).lower() if isinstance(value, bool) else str(value) + + # model and language + if is_given(s.model) and s.model is not None: + params["model"] = str(s.model) + if is_given(s.language) and s.language is not None: + params["language"] = str(s.language) + + # Init-only connection config + params["encoding"] = self._encoding + params["channels"] = str(self._channels) + params["multichannel"] = str(self._multichannel).lower() + params["sample_rate"] = str(self.sample_rate) + + if self._mip_opt_out is not None: + params["mip_opt_out"] = str(self._mip_opt_out).lower() + + # Any remaining values in extra + if s.extra: + for key, value in s.extra.items(): + if value is not None: + params[key] = str(value).lower() if isinstance(value, bool) else str(value) + + return "&".join(f"{k}={v}" for k, v in params.items()) + async def _connect(self): """Connect to the SageMaker endpoint and start the BiDi session. @@ -246,21 +316,7 @@ class DeepgramSageMakerSTTService(STTService): """ logger.debug("Connecting to Deepgram on SageMaker...") - live_options = LiveOptions( - **{**self._settings.live_options.to_dict(), "sample_rate": self.sample_rate} - ) - - # Build query string from live_options, converting booleans to strings - query_params = {} - for key, value in live_options.to_dict().items(): - if value is not None: - # Convert boolean values to lowercase strings for Deepgram API - if isinstance(value, bool): - query_params[key] = str(value).lower() - else: - query_params[key] = str(value) - - query_string = "&".join(f"{k}={v}" for k, v in query_params.items()) + query_string = self._build_query_string() # Create BiDi client self._client = SageMakerBidiClient( diff --git a/src/pipecat/services/deepgram/sagemaker/tts.py b/src/pipecat/services/deepgram/sagemaker/tts.py index 0129abedb..3693178a1 100644 --- a/src/pipecat/services/deepgram/sagemaker/tts.py +++ b/src/pipecat/services/deepgram/sagemaker/tts.py @@ -187,8 +187,7 @@ class DeepgramSageMakerTTSService(TTSService): logger.debug("Connecting to Deepgram TTS on SageMaker...") query_string = ( - f"model={self._settings.voice}&encoding={self._settings.encoding}" - f"&sample_rate={self.sample_rate}" + f"model={self._settings.voice}&encoding={self._encoding}&sample_rate={self.sample_rate}" ) self._client = SageMakerBidiClient( diff --git a/src/pipecat/services/deepgram/stt.py b/src/pipecat/services/deepgram/stt.py index f311567aa..d377fe69a 100644 --- a/src/pipecat/services/deepgram/stt.py +++ b/src/pipecat/services/deepgram/stt.py @@ -8,7 +8,7 @@ import asyncio from dataclasses import dataclass, field, fields -from typing import Any, AsyncGenerator, Dict, Optional +from typing import Any, AsyncGenerator, Optional from loguru import logger @@ -26,7 +26,6 @@ from pipecat.frames.frames import ( ) from pipecat.processors.frame_processor import FrameDirection from pipecat.services.settings import ( - _S, NOT_GIVEN, STTSettings, _NotGiven, @@ -57,8 +56,11 @@ class LiveOptions: """Deepgram live transcription options. Compatibility wrapper that mirrors the ``LiveOptions`` class removed in - deepgram-sdk v6. Pass this to :class:`DeepgramSTTService` via the - ``live_options`` constructor argument. + deepgram-sdk v6. + + .. deprecated:: 0.0.105 + Use ``settings=DeepgramSTTSettings(...)`` for runtime-updatable fields + and direct ``__init__`` parameters for connection-level config instead. """ def __init__( @@ -179,29 +181,42 @@ class DeepgramSTTSettings(STTSettings): ``model`` and ``language`` are inherited from ``STTSettings`` / ``ServiceSettings``. Additional Deepgram connection params may - be passed in through extra ``extra`` (also inherited). + be passed in through ``extra`` (also inherited). Parameters: - channels: Number of audio channels. + detect_entities: Enable named entity detection. diarize: Enable speaker diarization. - encoding: Audio encoding (e.g. ``"linear16"``). + dictation: Enable dictation mode (converts commands to punctuation). endpointing: Endpointing sensitivity in ms, or ``False`` to disable. interim_results: Whether to emit interim transcriptions. + keyterm: Keyterms to boost (str or list of str). + keywords: Keywords to boost (str or list of str). + numerals: Convert spoken numbers to numerals. profanity_filter: Filter profanity from transcripts. punctuate: Add punctuation to transcripts. + redact: Redact sensitive information (str or list of redaction types). + replace: Word replacement rules (str or list). + search: Search terms to highlight (str or list of str). smart_format: Apply smart formatting to transcripts. + utterance_end_ms: Silence duration in ms before an utterance-end event. vad_events: Enable Deepgram VAD speech-started / utterance-end events. - extra: Additional Deepgram query parameters not covered by the fields above. """ - channels: int | _NotGiven = field(default_factory=lambda: NOT_GIVEN) + detect_entities: bool | _NotGiven = field(default_factory=lambda: NOT_GIVEN) diarize: bool | _NotGiven = field(default_factory=lambda: NOT_GIVEN) - encoding: str | _NotGiven = field(default_factory=lambda: NOT_GIVEN) + dictation: bool | _NotGiven = field(default_factory=lambda: NOT_GIVEN) endpointing: Any | _NotGiven = field(default_factory=lambda: NOT_GIVEN) interim_results: bool | _NotGiven = field(default_factory=lambda: NOT_GIVEN) + keyterm: Any | _NotGiven = field(default_factory=lambda: NOT_GIVEN) + keywords: Any | _NotGiven = field(default_factory=lambda: NOT_GIVEN) + numerals: bool | _NotGiven = field(default_factory=lambda: NOT_GIVEN) profanity_filter: bool | _NotGiven = field(default_factory=lambda: NOT_GIVEN) punctuate: bool | _NotGiven = field(default_factory=lambda: NOT_GIVEN) + redact: Any | _NotGiven = field(default_factory=lambda: NOT_GIVEN) + replace: Any | _NotGiven = field(default_factory=lambda: NOT_GIVEN) + search: Any | _NotGiven = field(default_factory=lambda: NOT_GIVEN) smart_format: bool | _NotGiven = field(default_factory=lambda: NOT_GIVEN) + utterance_end_ms: int | None | _NotGiven = field(default_factory=lambda: NOT_GIVEN) vad_events: bool | _NotGiven = field(default_factory=lambda: NOT_GIVEN) def _sync_extra_to_fields(self) -> None: @@ -259,9 +274,16 @@ class DeepgramSTTService(STTService): api_key: str, url: str = "", base_url: str = "", + encoding: str = "linear16", + channels: int = 1, + multichannel: bool = False, sample_rate: Optional[int] = None, + callback: Optional[str] = None, + callback_method: Optional[str] = None, + tag: Optional[Any] = None, + mip_opt_out: Optional[bool] = None, live_options: Optional[LiveOptions] = None, - addons: Optional[Dict] = None, + addons: Optional[dict] = None, should_interrupt: bool = True, settings: Optional[DeepgramSTTSettings] = None, ttfs_p99_latency: Optional[float] = DEEPGRAM_TTFS_P99, @@ -277,12 +299,25 @@ class DeepgramSTTService(STTService): Parameter `url` is deprecated, use `base_url` instead. base_url: Custom Deepgram API base URL. - sample_rate: Audio sample rate. If None, uses default or live_options value. - live_options: :class: LiveOptions configuration. Treated as a - delta from a set of sensible defaults — only the fields you - set are overridden; all others keep their default values. + encoding: Audio encoding format. Defaults to "linear16". + channels: Number of audio channels. Defaults to 1. + multichannel: Transcribe each audio channel independently. + Defaults to False. + sample_rate: Audio sample rate in Hz. If None, uses the pipeline + sample rate. + callback: Callback URL for async transcription delivery. + callback_method: HTTP method for the callback (``"GET"`` or ``"POST"``). + tag: Custom billing tag. + mip_opt_out: Opt out of Deepgram model improvement program. + live_options: Legacy configuration options. + + .. deprecated:: 0.0.105 + Use ``settings=DeepgramSTTSettings(...)`` for runtime-updatable + fields and direct init parameters for connection-level config. + addons: Additional Deepgram features to enable. - should_interrupt: Determine whether the bot should be interrupted when Deepgram VAD events are enabled and the system detects that the user is speaking. + should_interrupt: Whether to interrupt the bot when Deepgram VAD + detects the user is speaking. .. deprecated:: 0.0.99 This parameter will be removed along with `vad_events` support. @@ -297,8 +332,6 @@ class DeepgramSTTService(STTService): Note: The `vad_events` option in LiveOptions is deprecated as of version 0.0.99 and will be removed in a future version. Please use the Silero VAD instead. """ - sample_rate = sample_rate or (live_options.sample_rate if live_options else None) - if url: import warnings @@ -314,30 +347,62 @@ class DeepgramSTTService(STTService): default_settings = DeepgramSTTSettings( model="nova-3-general", language=Language.EN, - encoding="linear16", - channels=1, - interim_results=True, - smart_format=False, - punctuate=True, - profanity_filter=True, - vad_events=False, + detect_entities=False, diarize=False, + dictation=False, endpointing=None, + interim_results=True, + keyterm=None, + keywords=None, + numerals=False, + profanity_filter=True, + punctuate=True, + redact=None, + replace=None, + search=None, + smart_format=False, + utterance_end_ms=None, + vad_events=False, ) - # 2. (no deprecated direct args like model= for this service) - - # 3. Apply live_options overrides — only if settings not provided + # 2. Apply live_options overrides — only if settings not provided if live_options is not None: _warn_deprecated_param("live_options", DeepgramSTTSettings) if not settings: - lo_dict = live_options.to_dict() - delta = DeepgramSTTSettings.from_mapping( - {k: v for k, v in lo_dict.items() if k != "sample_rate"} - ) + # Extract init-only fields from live_options + if live_options.sample_rate is not None and sample_rate is None: + sample_rate = live_options.sample_rate + if live_options.encoding is not None: + encoding = live_options.encoding + if live_options.channels is not None: + channels = live_options.channels + if live_options.callback is not None: + callback = live_options.callback + if live_options.callback_method is not None: + callback_method = live_options.callback_method + if live_options.tag is not None: + tag = live_options.tag + if live_options.mip_opt_out is not None: + mip_opt_out = live_options.mip_opt_out + if live_options.multichannel is not None: + multichannel = live_options.multichannel + + # Build settings delta from remaining fields + init_only = { + "sample_rate", + "encoding", + "channels", + "multichannel", + "callback", + "callback_method", + "tag", + "mip_opt_out", + } + lo_dict = {k: v for k, v in live_options.to_dict().items() if k not in init_only} + delta = DeepgramSTTSettings.from_mapping(lo_dict) default_settings.apply_update(delta) - # 4. Apply settings delta (canonical API, always wins) + # 3. Apply settings delta (canonical API, always wins) if settings is not None: default_settings.apply_update(settings) @@ -353,6 +418,13 @@ class DeepgramSTTService(STTService): self._addons = addons self._should_interrupt = should_interrupt + self._encoding = encoding + self._channels = channels + self._multichannel = multichannel + self._callback = callback + self._callback_method = callback_method + self._tag = tag + self._mip_opt_out = mip_opt_out if self._settings.vad_events: import warnings @@ -487,14 +559,26 @@ class DeepgramSTTService(STTService): if is_given(s.language) and s.language is not None: kwargs["language"] = str(s.language) + # Init-only connection config + kwargs["encoding"] = self._encoding + kwargs["channels"] = str(self._channels) + kwargs["multichannel"] = str(self._multichannel).lower() + kwargs["sample_rate"] = str(self.sample_rate) + + if self._callback is not None: + kwargs["callback"] = self._callback + if self._callback_method is not None: + kwargs["callback_method"] = self._callback_method + if self._tag is not None: + kwargs["tag"] = str(self._tag) + if self._mip_opt_out is not None: + kwargs["mip_opt_out"] = str(self._mip_opt_out).lower() + # Any remaining values in extra (that didn't map to declared fields) for key, value in s.extra.items(): if value is not None: kwargs[key] = str(value).lower() if isinstance(value, bool) else str(value) - # Always inject sample_rate from service level. - kwargs["sample_rate"] = str(self.sample_rate) - if self._addons: for key, value in self._addons.items(): kwargs[key] = str(value) diff --git a/src/pipecat/services/elevenlabs/stt.py b/src/pipecat/services/elevenlabs/stt.py index 2d75abff9..f9899f7f1 100644 --- a/src/pipecat/services/elevenlabs/stt.py +++ b/src/pipecat/services/elevenlabs/stt.py @@ -182,7 +182,8 @@ class ElevenLabsSTTSettings(STTSettings): """Settings for the ElevenLabs file-based STT service. Parameters: - tag_audio_events: Whether to include audio event tags in transcription. + tag_audio_events: Whether to include audio events like (laughter), + (coughing) in the transcription. """ tag_audio_events: bool | _NotGiven = field(default_factory=lambda: NOT_GIVEN) @@ -195,7 +196,6 @@ class ElevenLabsRealtimeSTTSettings(STTSettings): See ``ElevenLabsRealtimeSTTService.InputParams`` for detailed descriptions. Parameters: - commit_strategy: How to segment speech - manual (Pipecat VAD) or vad (ElevenLabs VAD). vad_silence_threshold_secs: Seconds of silence before VAD commits (0.3-3.0). vad_threshold: VAD sensitivity (0.1-0.9, lower is more sensitive). min_speech_duration_ms: Minimum speech duration for VAD (50-2000ms). @@ -205,7 +205,6 @@ class ElevenLabsRealtimeSTTSettings(STTSettings): include_language_detection: Whether to include language detection in transcripts. """ - commit_strategy: CommitStrategy | _NotGiven = field(default_factory=lambda: NOT_GIVEN) vad_silence_threshold_secs: float | None | _NotGiven = field(default_factory=lambda: NOT_GIVEN) vad_threshold: float | None | _NotGiven = field(default_factory=lambda: NOT_GIVEN) min_speech_duration_ms: int | None | _NotGiven = field(default_factory=lambda: NOT_GIVEN) @@ -495,6 +494,7 @@ class ElevenLabsRealtimeSTTService(WebsocketSTTService): *, api_key: str, base_url: str = "api.elevenlabs.io", + commit_strategy: CommitStrategy = CommitStrategy.MANUAL, model: Optional[str] = None, sample_rate: Optional[int] = None, params: Optional[InputParams] = None, @@ -507,6 +507,9 @@ class ElevenLabsRealtimeSTTService(WebsocketSTTService): Args: api_key: ElevenLabs API key for authentication. base_url: Base URL for ElevenLabs WebSocket API. + commit_strategy: How to segment speech — ``CommitStrategy.MANUAL`` + (Pipecat VAD) or ``CommitStrategy.VAD`` (ElevenLabs VAD). + Defaults to ``CommitStrategy.MANUAL``. model: Model ID for transcription. .. deprecated:: 0.0.105 @@ -528,7 +531,6 @@ class ElevenLabsRealtimeSTTService(WebsocketSTTService): default_settings = ElevenLabsRealtimeSTTSettings( model="scribe_v2_realtime", language=None, - commit_strategy=CommitStrategy.MANUAL, vad_silence_threshold_secs=None, vad_threshold=None, min_speech_duration_ms=None, @@ -548,7 +550,8 @@ class ElevenLabsRealtimeSTTService(WebsocketSTTService): _warn_deprecated_param("params", ElevenLabsRealtimeSTTSettings) if not settings: default_settings.language = params.language_code - default_settings.commit_strategy = params.commit_strategy + if params.commit_strategy != CommitStrategy.MANUAL: + commit_strategy = params.commit_strategy default_settings.vad_silence_threshold_secs = params.vad_silence_threshold_secs default_settings.vad_threshold = params.vad_threshold default_settings.min_speech_duration_ms = params.min_speech_duration_ms @@ -575,6 +578,9 @@ class ElevenLabsRealtimeSTTService(WebsocketSTTService): self._audio_format = "" # initialized in start() self._receive_task = None + # Init-only config (not runtime-updatable). + self._commit_strategy = commit_strategy + self._connected_event = asyncio.Event() self._connected_event.set() @@ -651,7 +657,7 @@ class ElevenLabsRealtimeSTTService(WebsocketSTTService): await self._start_metrics() elif isinstance(frame, VADUserStoppedSpeakingFrame): # Send commit when user stops speaking (manual commit mode) - if self._settings.commit_strategy == CommitStrategy.MANUAL: + if self._commit_strategy == CommitStrategy.MANUAL: if self._websocket and self._websocket.state is State.OPEN: try: commit_message = { @@ -754,7 +760,7 @@ class ElevenLabsRealtimeSTTService(WebsocketSTTService): params.append(f"language_code={self._settings.language}") params.append(f"audio_format={self._audio_format}") - params.append(f"commit_strategy={self._settings.commit_strategy.value}") + params.append(f"commit_strategy={self._commit_strategy.value}") # Add optional parameters if self._settings.include_timestamps: @@ -771,7 +777,7 @@ class ElevenLabsRealtimeSTTService(WebsocketSTTService): ) # Add VAD parameters if using VAD commit strategy and values are specified - if self._settings.commit_strategy == CommitStrategy.VAD: + if self._commit_strategy == CommitStrategy.VAD: if self._settings.vad_silence_threshold_secs is not None: params.append( f"vad_silence_threshold_secs={self._settings.vad_silence_threshold_secs}" @@ -931,7 +937,7 @@ class ElevenLabsRealtimeSTTService(WebsocketSTTService): await self._handle_transcription(text, True, language) - finalized = self._settings.commit_strategy == CommitStrategy.MANUAL + finalized = self._commit_strategy == CommitStrategy.MANUAL await self.push_frame( TranscriptionFrame( @@ -975,7 +981,7 @@ class ElevenLabsRealtimeSTTService(WebsocketSTTService): await self._handle_transcription(text, True, language) - finalized = self._settings.commit_strategy == CommitStrategy.MANUAL + finalized = self._commit_strategy == CommitStrategy.MANUAL # This message is sent after committed_transcript when include_timestamps=true. # It contains the full transcript data including text and word-level timestamps. diff --git a/src/pipecat/services/fal/stt.py b/src/pipecat/services/fal/stt.py index 4428599b1..18b8ed85c 100644 --- a/src/pipecat/services/fal/stt.py +++ b/src/pipecat/services/fal/stt.py @@ -12,7 +12,7 @@ transcription using segmented audio processing. import base64 import os -from dataclasses import dataclass, field +from dataclasses import dataclass from typing import AsyncGenerator, Optional import aiohttp @@ -20,7 +20,7 @@ from loguru import logger from pydantic import BaseModel from pipecat.frames.frames import ErrorFrame, Frame, TranscriptionFrame -from pipecat.services.settings import NOT_GIVEN, STTSettings, _NotGiven, _warn_deprecated_param +from pipecat.services.settings import STTSettings, _warn_deprecated_param from pipecat.services.stt_latency import FAL_TTFS_P99 from pipecat.services.stt_service import SegmentedSTTService from pipecat.transcriptions.language import Language, resolve_language @@ -143,18 +143,9 @@ def language_to_fal_language(language: Language) -> Optional[str]: @dataclass class FalSTTSettings(STTSettings): - """Settings for the Fal Wizper STT service. + """Settings for the Fal Wizper STT service.""" - Parameters: - task: Task to perform ('transcribe' or 'translate'). Defaults to - 'transcribe'. - chunk_level: Level of chunking ('segment'). Defaults to 'segment'. - version: Version of Wizper model to use. Defaults to '3'. - """ - - task: str | _NotGiven = field(default_factory=lambda: NOT_GIVEN) - chunk_level: str | _NotGiven = field(default_factory=lambda: NOT_GIVEN) - version: str | _NotGiven = field(default_factory=lambda: NOT_GIVEN) + pass class FalSTTService(SegmentedSTTService): @@ -189,6 +180,9 @@ class FalSTTService(SegmentedSTTService): *, api_key: Optional[str] = None, aiohttp_session: Optional[aiohttp.ClientSession] = None, + task: str = "transcribe", + chunk_level: str = "segment", + version: str = "3", sample_rate: Optional[int] = None, params: Optional[InputParams] = None, settings: Optional[FalSTTSettings] = None, @@ -201,11 +195,16 @@ class FalSTTService(SegmentedSTTService): api_key: Fal API key. If not provided, will check FAL_KEY environment variable. aiohttp_session: Optional aiohttp ClientSession for HTTP requests. If not provided, a session will be created and managed internally. + task: Task to perform (``"transcribe"`` or ``"translate"``). + Defaults to ``"transcribe"``. + chunk_level: Level of chunking (``"segment"``). Defaults to ``"segment"``. + version: Version of Wizper model to use. Defaults to ``"3"``. sample_rate: Audio sample rate in Hz. If not provided, uses the pipeline's rate. params: Configuration parameters for the Wizper API. .. deprecated:: 0.0.105 - Use ``settings=FalSTTSettings(...)`` instead. + Use ``settings=FalSTTSettings(...)`` for model/language and + direct init parameters for task/chunk_level/version instead. settings: Runtime-updatable settings. When provided alongside deprecated parameters, ``settings`` values take precedence. @@ -217,9 +216,6 @@ class FalSTTService(SegmentedSTTService): default_settings = FalSTTSettings( model=None, language=language_to_fal_language(Language.EN) or "en", - task="transcribe", - chunk_level="segment", - version="3", ) # 2. (no deprecated direct args for this service) @@ -231,9 +227,12 @@ class FalSTTService(SegmentedSTTService): default_settings.language = ( language_to_fal_language(params.language) if params.language else "en" ) - default_settings.task = params.task - default_settings.chunk_level = params.chunk_level - default_settings.version = params.version + if params.task != "transcribe": + task = params.task + if params.chunk_level != "segment": + chunk_level = params.chunk_level + if params.version != "3": + version = params.version # 4. Apply settings delta (canonical API, always wins) if settings is not None: @@ -246,6 +245,10 @@ class FalSTTService(SegmentedSTTService): **kwargs, ) + self._task = task + self._chunk_level = chunk_level + self._version = version + self._api_key = api_key or os.getenv("FAL_KEY", "") if not self._api_key: raise ValueError( @@ -301,7 +304,15 @@ class FalSTTService(SegmentedSTTService): self._session = aiohttp.ClientSession() data_uri = f"data:audio/x-wav;base64,{base64.b64encode(audio).decode()}" - payload = {"audio_url": data_uri, **self._settings.given_fields()} + payload: dict = {"audio_url": data_uri} + if self._settings.language is not None: + payload["language"] = self._settings.language + if self._task is not None: + payload["task"] = self._task + if self._chunk_level is not None: + payload["chunk_level"] = self._chunk_level + if self._version is not None: + payload["version"] = self._version headers = { "Authorization": f"Key {self._api_key}", "Content-Type": "application/json", diff --git a/src/pipecat/services/gladia/config.py b/src/pipecat/services/gladia/config.py index 5fd5bfdac..ec8997d7c 100644 --- a/src/pipecat/services/gladia/config.py +++ b/src/pipecat/services/gladia/config.py @@ -152,6 +152,10 @@ class MessagesConfig(BaseModel): class GladiaInputParams(BaseModel): """Configuration parameters for the Gladia STT service. + .. deprecated:: 0.0.105 + Use ``settings=GladiaSTTSettings(...)`` for runtime-updatable + fields and direct init parameters for encoding/bit_depth/channels. + Parameters: encoding: Audio encoding format bit_depth: Audio bit depth diff --git a/src/pipecat/services/gladia/stt.py b/src/pipecat/services/gladia/stt.py index 44e5bbd9c..f1eca2dc2 100644 --- a/src/pipecat/services/gladia/stt.py +++ b/src/pipecat/services/gladia/stt.py @@ -15,7 +15,7 @@ import base64 import json import warnings from dataclasses import dataclass, field -from typing import Any, AsyncGenerator, Dict, Literal, Optional +from typing import Any, AsyncGenerator, Literal, Optional import aiohttp from loguru import logger @@ -191,28 +191,22 @@ class GladiaSTTSettings(STTSettings): """Settings for Gladia STT service. Parameters: - encoding: Audio encoding format. - bit_depth: Audio bit depth. - channels: Number of audio channels. + language_config: Language detection and handling configuration. custom_metadata: Additional metadata to include with requests. endpointing: Silence duration in seconds to mark end of speech. maximum_duration_without_endpointing: Maximum utterance duration without silence. - language_config: Detailed language configuration. pre_processing: Audio pre-processing options. realtime_processing: Real-time processing features. messages_config: WebSocket message filtering options. enable_vad: Enable VAD to trigger end of utterance detection. """ - encoding: str | None | _NotGiven = field(default_factory=lambda: NOT_GIVEN) - bit_depth: int | None | _NotGiven = field(default_factory=lambda: NOT_GIVEN) - channels: int | None | _NotGiven = field(default_factory=lambda: NOT_GIVEN) - custom_metadata: Dict[str, Any] | None | _NotGiven = field(default_factory=lambda: NOT_GIVEN) + language_config: LanguageConfig | None | _NotGiven = field(default_factory=lambda: NOT_GIVEN) + custom_metadata: dict[str, Any] | None | _NotGiven = field(default_factory=lambda: NOT_GIVEN) endpointing: float | None | _NotGiven = field(default_factory=lambda: NOT_GIVEN) maximum_duration_without_endpointing: int | None | _NotGiven = field( default_factory=lambda: NOT_GIVEN ) - language_config: LanguageConfig | None | _NotGiven = field(default_factory=lambda: NOT_GIVEN) pre_processing: PreProcessingConfig | None | _NotGiven = field( default_factory=lambda: NOT_GIVEN ) @@ -247,6 +241,9 @@ class GladiaSTTService(WebsocketSTTService): api_key: str, region: Literal["us-west", "eu-west"] | None = None, url: str = "https://api.gladia.io/v2/live", + encoding: str = "wav/pcm", + bit_depth: int = 16, + channels: int = 1, confidence: Optional[float] = None, sample_rate: Optional[int] = None, model: Optional[str] = None, @@ -263,6 +260,9 @@ class GladiaSTTService(WebsocketSTTService): api_key: Gladia API key for authentication. region: Region used to process audio. eu-west or us-west. Defaults to eu-west. url: Gladia API URL. Defaults to "https://api.gladia.io/v2/live". + encoding: Audio encoding format. Defaults to ``"wav/pcm"``. + bit_depth: Audio bit depth. Defaults to 16. + channels: Number of audio channels. Defaults to 1. confidence: Minimum confidence threshold for transcriptions (0.0-1.0). .. deprecated:: 0.0.86 @@ -278,7 +278,8 @@ class GladiaSTTService(WebsocketSTTService): params: Additional configuration parameters for Gladia service. .. deprecated:: 0.0.105 - Use ``settings=GladiaSTTSettings(...)`` instead. + Use ``settings=GladiaSTTSettings(...)`` for runtime-updatable + fields and direct init parameters for encoding/bit_depth/channels. max_buffer_size: Maximum size of audio buffer in bytes. Defaults to 20MB. should_interrupt: Determine whether the bot should be interrupted when @@ -303,13 +304,10 @@ class GladiaSTTService(WebsocketSTTService): default_settings = GladiaSTTSettings( model="solaria-1", language=None, - encoding="wav/pcm", - bit_depth=16, - channels=1, + language_config=None, custom_metadata=None, endpointing=None, maximum_duration_without_endpointing=5, - language_config=None, pre_processing=None, realtime_processing=None, messages_config=None, @@ -334,9 +332,13 @@ class GladiaSTTService(WebsocketSTTService): stacklevel=2, ) if not settings: - default_settings.encoding = params.encoding - default_settings.bit_depth = params.bit_depth - default_settings.channels = params.channels + # Extract init-only fields from params + if params.encoding is not None: + encoding = params.encoding + if params.bit_depth is not None: + bit_depth = params.bit_depth + if params.channels is not None: + channels = params.channels default_settings.custom_metadata = params.custom_metadata default_settings.endpointing = params.endpointing default_settings.maximum_duration_without_endpointing = ( @@ -347,14 +349,14 @@ class GladiaSTTService(WebsocketSTTService): default_settings.messages_config = params.messages_config default_settings.enable_vad = params.enable_vad # Resolve deprecated language → language_config at init time - language_config = params.language_config - if not language_config and params.language: + if params.language_config: + default_settings.language_config = params.language_config + elif params.language: language_code = self.language_to_service_language(params.language) if language_code: - language_config = LanguageConfig( + default_settings.language_config = LanguageConfig( languages=[language_code], code_switching=False ) - default_settings.language_config = language_config # 4. Apply settings delta (canonical API, always wins) if settings is not None: @@ -374,6 +376,11 @@ class GladiaSTTService(WebsocketSTTService): self._url = url self._receive_task = None + # Init-only connection config + self._encoding = encoding + self._bit_depth = bit_depth + self._channels = channels + # Session management self._session_url = None self._session_id = None @@ -411,14 +418,14 @@ class GladiaSTTService(WebsocketSTTService): """ return language_to_gladia_language(language) - def _prepare_settings(self) -> Dict[str, Any]: + def _prepare_settings(self) -> dict[str, Any]: s = self._settings settings = { - "encoding": s.encoding or "wav/pcm", - "bit_depth": s.bit_depth or 16, + "encoding": self._encoding or "wav/pcm", + "bit_depth": self._bit_depth or 16, "sample_rate": self.sample_rate, - "channels": s.channels or 1, + "channels": self._channels or 1, "model": s.model, } @@ -610,7 +617,7 @@ class GladiaSTTService(WebsocketSTTService): self._websocket = None await self._call_event_handler("on_disconnected") - async def _setup_gladia(self, settings: Dict[str, Any]): + async def _setup_gladia(self, settings: dict[str, Any]): async with aiohttp.ClientSession() as session: params = {} if self._region: diff --git a/src/pipecat/services/gradium/stt.py b/src/pipecat/services/gradium/stt.py index fff58d87a..e8ab072d0 100644 --- a/src/pipecat/services/gradium/stt.py +++ b/src/pipecat/services/gradium/stt.py @@ -12,7 +12,7 @@ WebSocket API for streaming audio transcription. import base64 import json -from dataclasses import dataclass, field +from dataclasses import dataclass from typing import Any, AsyncGenerator, Optional from loguru import logger @@ -28,7 +28,7 @@ from pipecat.frames.frames import ( VADUserStoppedSpeakingFrame, ) from pipecat.processors.frame_processor import FrameDirection -from pipecat.services.settings import NOT_GIVEN, STTSettings, _NotGiven, _warn_deprecated_param +from pipecat.services.settings import STTSettings, _warn_deprecated_param from pipecat.services.stt_latency import GRADIUM_TTFS_P99 from pipecat.services.stt_service import WebsocketSTTService from pipecat.transcriptions.language import Language, resolve_language @@ -68,14 +68,9 @@ def language_to_gradium_language(language: Language) -> Optional[str]: @dataclass class GradiumSTTSettings(STTSettings): - """Settings for the Gradium STT service. + """Settings for the Gradium STT service.""" - Parameters: - delay_in_frames: Delay in audio frames (80ms each) before text is - generated. Higher delays allow more context but increase latency. - """ - - delay_in_frames: int | _NotGiven = field(default_factory=lambda: NOT_GIVEN) + pass class GradiumSTTService(WebsocketSTTService): @@ -112,6 +107,7 @@ class GradiumSTTService(WebsocketSTTService): *, api_key: str, api_endpoint_base_url: str = "wss://eu.api.gradium.ai/api/speech/asr", + delay_in_frames: Optional[int] = None, params: Optional[InputParams] = None, json_config: Optional[str] = None, settings: Optional[GradiumSTTSettings] = None, @@ -123,6 +119,9 @@ class GradiumSTTService(WebsocketSTTService): Args: api_key: Gradium API key for authentication. api_endpoint_base_url: WebSocket endpoint URL. Defaults to Gradium's streaming endpoint. + delay_in_frames: Delay in audio frames (80ms each) before text is + generated. Higher delays allow more context but increase latency. + Allowed values: 7, 8, 10, 12, 14, 16, 20, 24, 36, 48. params: Configuration parameters for language and delay settings. .. deprecated:: 0.0.105 @@ -152,7 +151,6 @@ class GradiumSTTService(WebsocketSTTService): default_settings = GradiumSTTSettings( model=None, language=None, - delay_in_frames=None, ) # 2. (no deprecated direct args for this service) @@ -162,7 +160,8 @@ class GradiumSTTService(WebsocketSTTService): _warn_deprecated_param("params", GradiumSTTSettings) if not settings: default_settings.language = params.language - default_settings.delay_in_frames = params.delay_in_frames + if params.delay_in_frames is not None: + delay_in_frames = params.delay_in_frames # 4. Apply settings delta (canonical API, always wins) if settings is not None: @@ -179,6 +178,7 @@ class GradiumSTTService(WebsocketSTTService): self._api_endpoint_base_url = api_endpoint_base_url self._websocket = None self._json_config = json_config + self._config_delay_in_frames = delay_in_frames self._receive_task = None @@ -358,8 +358,8 @@ class GradiumSTTService(WebsocketSTTService): gradium_language = language_to_gradium_language(self._settings.language) if gradium_language: json_config["language"] = gradium_language - if self._settings.delay_in_frames: - json_config["delay_in_frames"] = self._settings.delay_in_frames + if self._config_delay_in_frames: + json_config["delay_in_frames"] = self._config_delay_in_frames if json_config: setup_msg["json_config"] = json_config await self._websocket.send(json.dumps(setup_msg)) diff --git a/src/pipecat/services/groq/stt.py b/src/pipecat/services/groq/stt.py index b875f63d4..1733831c8 100644 --- a/src/pipecat/services/groq/stt.py +++ b/src/pipecat/services/groq/stt.py @@ -6,6 +6,7 @@ """Groq speech-to-text service implementation using Whisper models.""" +from dataclasses import dataclass from typing import Optional from pipecat.services.settings import _warn_deprecated_param @@ -18,6 +19,17 @@ from pipecat.services.whisper.base_stt import ( from pipecat.transcriptions.language import Language +@dataclass +class GroqSTTSettings(BaseWhisperSTTSettings): + """Settings for the Groq STT service. + + Parameters: + prompt: Optional prompt text to guide transcription style. + """ + + pass + + class GroqSTTService(BaseWhisperSTTService): """Groq Whisper speech-to-text service. @@ -25,6 +37,8 @@ class GroqSTTService(BaseWhisperSTTService): set via the api_key parameter or GROQ_API_KEY environment variable. """ + _settings: GroqSTTSettings + def __init__( self, *, @@ -34,7 +48,7 @@ class GroqSTTService(BaseWhisperSTTService): language: Optional[Language] = None, prompt: Optional[str] = None, temperature: Optional[float] = None, - settings: Optional[BaseWhisperSTTSettings] = None, + settings: Optional[GroqSTTSettings] = None, ttfs_p99_latency: Optional[float] = GROQ_TTFS_P99, **kwargs, ): @@ -44,24 +58,24 @@ class GroqSTTService(BaseWhisperSTTService): model: Whisper model to use. .. deprecated:: 0.0.105 - Use ``settings=BaseWhisperSTTSettings(model=...)`` instead. + Use ``settings=GroqSTTSettings(model=...)`` instead. api_key: Groq API key. Defaults to None. base_url: API base URL. Defaults to "https://api.groq.com/openai/v1". language: Language of the audio input. .. deprecated:: 0.0.105 - Use ``settings=BaseWhisperSTTSettings(language=...)`` instead. + Use ``settings=GroqSTTSettings(language=...)`` instead. prompt: Optional text to guide the model's style or continue a previous segment. .. deprecated:: 0.0.105 - Use ``settings=BaseWhisperSTTSettings(prompt=...)`` instead. + Use ``settings=GroqSTTSettings(prompt=...)`` instead. temperature: Optional sampling temperature between 0 and 1. .. deprecated:: 0.0.105 - Use ``settings=BaseWhisperSTTSettings(temperature=...)`` instead. + Use ``settings=GroqSTTSettings(temperature=...)`` instead. settings: Runtime-updatable settings. When provided alongside deprecated parameters, ``settings`` values take precedence. @@ -70,24 +84,25 @@ class GroqSTTService(BaseWhisperSTTService): **kwargs: Additional arguments passed to BaseWhisperSTTService. """ # --- 1. Hardcoded defaults --- - default_settings = BaseWhisperSTTSettings( + default_settings = GroqSTTSettings( model="whisper-large-v3-turbo", language=self.language_to_service_language(Language.EN), - base_url=base_url, + prompt=None, + temperature=None, ) # --- 2. Deprecated direct-arg overrides --- if model is not None: - _warn_deprecated_param("model", BaseWhisperSTTSettings, "model") + _warn_deprecated_param("model", GroqSTTSettings, "model") default_settings.model = model if language is not None: - _warn_deprecated_param("language", BaseWhisperSTTSettings, "language") + _warn_deprecated_param("language", GroqSTTSettings, "language") default_settings.language = self.language_to_service_language(language) if prompt is not None: - _warn_deprecated_param("prompt", BaseWhisperSTTSettings, "prompt") + _warn_deprecated_param("prompt", GroqSTTSettings, "prompt") default_settings.prompt = prompt if temperature is not None: - _warn_deprecated_param("temperature", BaseWhisperSTTSettings, "temperature") + _warn_deprecated_param("temperature", GroqSTTSettings, "temperature") default_settings.temperature = temperature # --- 3. (no params object for this service) --- @@ -105,7 +120,7 @@ class GroqSTTService(BaseWhisperSTTService): ) async def _transcribe(self, audio: bytes) -> Transcription: - assert self._language is not None # Assigned in the BaseWhisperSTTService class + assert self._settings.language is not None # Build kwargs dict with only set parameters kwargs = { @@ -113,13 +128,13 @@ class GroqSTTService(BaseWhisperSTTService): "model": self._settings.model, # Use verbose_json to get probability metrics "response_format": "verbose_json" if self._include_prob_metrics else "json", - "language": self._language, + "language": self._settings.language, } - if self._prompt is not None: - kwargs["prompt"] = self._prompt + if self._settings.prompt is not None: + kwargs["prompt"] = self._settings.prompt - if self._temperature is not None: - kwargs["temperature"] = self._temperature + if self._settings.temperature is not None: + kwargs["temperature"] = self._settings.temperature return await self._client.audio.transcriptions.create(**kwargs) diff --git a/src/pipecat/services/nvidia/stt.py b/src/pipecat/services/nvidia/stt.py index df785e25c..9b9b2bcf9 100644 --- a/src/pipecat/services/nvidia/stt.py +++ b/src/pipecat/services/nvidia/stt.py @@ -8,7 +8,7 @@ import asyncio from concurrent.futures import CancelledError as FuturesCancelledError -from dataclasses import dataclass, field +from dataclasses import dataclass from typing import Any, AsyncGenerator, List, Mapping, Optional from loguru import logger @@ -23,7 +23,7 @@ from pipecat.frames.frames import ( StartFrame, TranscriptionFrame, ) -from pipecat.services.settings import NOT_GIVEN, STTSettings, _NotGiven, _warn_deprecated_param +from pipecat.services.settings import STTSettings, _warn_deprecated_param from pipecat.services.stt_latency import NVIDIA_TTFS_P99 from pipecat.services.stt_service import SegmentedSTTService, STTService from pipecat.transcriptions.language import Language, resolve_language @@ -110,11 +110,11 @@ class NvidiaSegmentedSTTSettings(STTSettings): boosted_lm_score: Score boost for specified words. """ - profanity_filter: bool | _NotGiven = field(default_factory=lambda: NOT_GIVEN) - automatic_punctuation: bool | _NotGiven = field(default_factory=lambda: NOT_GIVEN) - verbatim_transcripts: bool | _NotGiven = field(default_factory=lambda: NOT_GIVEN) - boosted_lm_words: List[str] | _NotGiven = field(default_factory=lambda: NOT_GIVEN) - boosted_lm_score: float | _NotGiven = field(default_factory=lambda: NOT_GIVEN) + profanity_filter: bool = False + automatic_punctuation: bool = True + verbatim_transcripts: bool = False + boosted_lm_words: Optional[List[str]] = None + boosted_lm_score: float = 4.0 class NvidiaSTTService(STTService): @@ -586,19 +586,18 @@ class NvidiaSegmentedSTTService(SegmentedSTTService): def _create_recognition_config(self): """Create the NVIDIA Riva ASR recognition configuration.""" # Create base configuration + s = self._settings config = riva.client.RecognitionConfig( language_code=self._get_language_code(), max_alternatives=1, - profanity_filter=self._settings.profanity_filter, - enable_automatic_punctuation=self._settings.automatic_punctuation, - verbatim_transcripts=self._settings.verbatim_transcripts, + profanity_filter=s.profanity_filter, + enable_automatic_punctuation=s.automatic_punctuation, + verbatim_transcripts=s.verbatim_transcripts, ) # Add word boosting if specified - if self._settings.boosted_lm_words: - riva.client.add_word_boosting_to_config( - config, self._settings.boosted_lm_words, self._settings.boosted_lm_score - ) + if s.boosted_lm_words: + riva.client.add_word_boosting_to_config(config, s.boosted_lm_words, s.boosted_lm_score) # Add voice activity detection parameters riva.client.add_endpoint_parameters_to_config( diff --git a/src/pipecat/services/openai/stt.py b/src/pipecat/services/openai/stt.py index 7692deee5..fbd372523 100644 --- a/src/pipecat/services/openai/stt.py +++ b/src/pipecat/services/openai/stt.py @@ -16,7 +16,7 @@ Provides two STT services: import base64 import json -from dataclasses import dataclass, field +from dataclasses import dataclass from typing import Any, AsyncGenerator, Literal, Optional, Union from loguru import logger @@ -35,7 +35,7 @@ from pipecat.frames.frames import ( VADUserStoppedSpeakingFrame, ) from pipecat.processors.frame_processor import FrameDirection -from pipecat.services.settings import NOT_GIVEN, STTSettings, _NotGiven, _warn_deprecated_param +from pipecat.services.settings import STTSettings, _NotGiven, _warn_deprecated_param from pipecat.services.stt_latency import OPENAI_REALTIME_TTFS_P99, OPENAI_TTFS_P99 from pipecat.services.stt_service import WebsocketSTTService from pipecat.services.whisper.base_stt import ( @@ -55,6 +55,13 @@ except ModuleNotFoundError: State = None +@dataclass +class OpenAISTTSettings(BaseWhisperSTTSettings): + """Settings for the OpenAI STT service.""" + + pass + + class OpenAISTTService(BaseWhisperSTTService): """OpenAI Speech-to-Text service that generates text from audio. @@ -62,6 +69,8 @@ class OpenAISTTService(BaseWhisperSTTService): set via the api_key parameter or OPENAI_API_KEY environment variable. """ + _settings: OpenAISTTSettings + def __init__( self, *, @@ -71,7 +80,7 @@ class OpenAISTTService(BaseWhisperSTTService): language: Optional[Language] = Language.EN, prompt: Optional[str] = None, temperature: Optional[float] = None, - settings: Optional[BaseWhisperSTTSettings] = None, + settings: Optional[OpenAISTTSettings] = None, ttfs_p99_latency: Optional[float] = OPENAI_TTFS_P99, **kwargs, ): @@ -81,13 +90,25 @@ class OpenAISTTService(BaseWhisperSTTService): model: Model to use — either gpt-4o or Whisper. .. deprecated:: 0.0.105 - Use ``settings=BaseWhisperSTTSettings(model=...)`` instead. + Use ``settings=OpenAISTTSettings(model=...)`` instead. api_key: OpenAI API key. Defaults to None. base_url: API base URL. Defaults to None. language: Language of the audio input. Defaults to English. + + .. deprecated:: 0.0.105 + Use ``settings=OpenAISTTSettings(language=...)`` instead. + prompt: Optional text to guide the model's style or continue a previous segment. + + .. deprecated:: 0.0.105 + Use ``settings=OpenAISTTSettings(prompt=...)`` instead. + temperature: Optional sampling temperature between 0 and 1. Defaults to 0.0. + + .. deprecated:: 0.0.105 + Use ``settings=OpenAISTTSettings(temperature=...)`` instead. + settings: Runtime-updatable settings. When provided alongside deprecated parameters, ``settings`` values take precedence. ttfs_p99_latency: P99 latency from speech end to final transcript in seconds. @@ -96,18 +117,23 @@ class OpenAISTTService(BaseWhisperSTTService): """ # --- 1. Hardcoded defaults --- _language = language or Language.EN - default_settings = BaseWhisperSTTSettings( + default_settings = OpenAISTTSettings( model="gpt-4o-transcribe", language=self.language_to_service_language(_language), - base_url=base_url, - prompt=prompt, - temperature=temperature, + prompt=None, + temperature=None, ) # --- 2. Deprecated direct-arg overrides --- if model is not None: - _warn_deprecated_param("model", BaseWhisperSTTSettings, "model") + _warn_deprecated_param("model", OpenAISTTSettings, "model") default_settings.model = model + if prompt is not None: + _warn_deprecated_param("prompt", OpenAISTTSettings, "prompt") + default_settings.prompt = prompt + if temperature is not None: + _warn_deprecated_param("temperature", OpenAISTTSettings, "temperature") + default_settings.temperature = temperature # --- 3. (no params object for this service) --- @@ -124,7 +150,7 @@ class OpenAISTTService(BaseWhisperSTTService): ) async def _transcribe(self, audio: bytes) -> Transcription: - assert self._language is not None # Assigned in the BaseWhisperSTTService class + assert self._settings.language is not None # Build kwargs dict with only set parameters kwargs = { @@ -162,7 +188,7 @@ class OpenAIRealtimeSTTSettings(STTSettings): prompt: Optional prompt text to guide transcription style. """ - prompt: str | _NotGiven = field(default_factory=lambda: NOT_GIVEN) + prompt: str | None | _NotGiven = None class OpenAIRealtimeSTTService(WebsocketSTTService): @@ -228,8 +254,16 @@ class OpenAIRealtimeSTTService(WebsocketSTTService): base_url: WebSocket base URL for the Realtime API. Defaults to ``"wss://api.openai.com/v1/realtime"``. language: Language of the audio input. Defaults to English. + + .. deprecated:: 0.0.105 + Use ``settings=OpenAIRealtimeSTTSettings(language=...)`` instead. + prompt: Optional prompt text to guide transcription style or provide keyword hints. + + .. deprecated:: 0.0.105 + Use ``settings=OpenAIRealtimeSTTSettings(prompt=...)`` instead. + turn_detection: Server-side VAD configuration. Defaults to ``False`` (disabled), which relies on a local VAD processor in the pipeline. Pass ``None`` to use server @@ -257,14 +291,20 @@ class OpenAIRealtimeSTTService(WebsocketSTTService): # --- 1. Hardcoded defaults --- default_settings = OpenAIRealtimeSTTSettings( model="gpt-4o-transcribe", - language=language, - prompt=prompt, + language=Language.EN, + prompt=None, ) # --- 2. Deprecated direct-arg overrides --- if model is not None: _warn_deprecated_param("model", OpenAIRealtimeSTTSettings, "model") default_settings.model = model + if language is not None and language != Language.EN: + _warn_deprecated_param("language", OpenAIRealtimeSTTSettings, "language") + default_settings.language = language + if prompt is not None: + _warn_deprecated_param("prompt", OpenAIRealtimeSTTSettings, "prompt") + default_settings.prompt = prompt # --- 3. (no params object for this service) --- @@ -281,7 +321,6 @@ class OpenAIRealtimeSTTService(WebsocketSTTService): self._api_key = api_key self._base_url = base_url - self._prompt = self._settings.prompt self._turn_detection = turn_detection self._noise_reduction = noise_reduction self._should_interrupt = should_interrupt @@ -318,8 +357,7 @@ class OpenAIRealtimeSTTService(WebsocketSTTService): async def _update_settings(self, delta: STTSettings) -> dict[str, Any]: """Apply a settings delta and send session update if needed. - Keeps ``_language_code`` and ``_prompt`` in sync with settings - and sends a ``session.update`` to the server when the session is active. + Sends a ``session.update`` to the server when the session is active. Args: delta: A :class:`STTSettings` (or ``OpenAIRealtimeSTTSettings``) delta. @@ -329,13 +367,7 @@ class OpenAIRealtimeSTTService(WebsocketSTTService): """ changed = await super()._update_settings(delta) - if not changed: - return changed - - if "prompt" in changed and isinstance(self._settings, OpenAIRealtimeSTTSettings): - self._prompt = self._settings.prompt - - if self._session_ready: + if changed and self._session_ready: await self._send_session_update() return changed @@ -492,8 +524,8 @@ class OpenAIRealtimeSTTService(WebsocketSTTService): if language_code: transcription["language"] = language_code - if self._prompt: - transcription["prompt"] = self._prompt + if self._settings.prompt: + transcription["prompt"] = self._settings.prompt input_audio: dict = { "format": { diff --git a/src/pipecat/services/openai/tts.py b/src/pipecat/services/openai/tts.py index feb6453c7..b4933ae9f 100644 --- a/src/pipecat/services/openai/tts.py +++ b/src/pipecat/services/openai/tts.py @@ -161,6 +161,8 @@ class OpenAITTSService(TTSService): model="gpt-4o-mini-tts", voice="alloy", language=None, + instructions=None, + speed=None, ) # 2. Apply direct init arg overrides (deprecated) diff --git a/src/pipecat/services/sambanova/stt.py b/src/pipecat/services/sambanova/stt.py index 60f638897..822c44da9 100644 --- a/src/pipecat/services/sambanova/stt.py +++ b/src/pipecat/services/sambanova/stt.py @@ -6,6 +6,7 @@ """SambaNova's Speech-to-Text service implementation for real-time transcription.""" +from dataclasses import dataclass from typing import Any, Optional from loguru import logger @@ -20,6 +21,13 @@ from pipecat.services.whisper.base_stt import ( from pipecat.transcriptions.language import Language +@dataclass +class SambaNovaSTTSettings(BaseWhisperSTTSettings): + """Settings for the SambaNova STT service.""" + + pass + + class SambaNovaSTTService(BaseWhisperSTTService): # type: ignore """SambaNova Whisper speech-to-text service. @@ -36,7 +44,7 @@ class SambaNovaSTTService(BaseWhisperSTTService): # type: ignore language: Optional[Language] = None, prompt: Optional[str] = None, temperature: Optional[float] = None, - settings: Optional[BaseWhisperSTTSettings] = None, + settings: Optional[SambaNovaSTTSettings] = None, ttfs_p99_latency: Optional[float] = SAMBANOVA_TTFS_P99, **kwargs: Any, ) -> None: @@ -46,24 +54,24 @@ class SambaNovaSTTService(BaseWhisperSTTService): # type: ignore model: Whisper model to use. .. deprecated:: 0.0.105 - Use ``settings=BaseWhisperSTTSettings(model=...)`` instead. + Use ``settings=SambaNovaSTTSettings(model=...)`` instead. api_key: SambaNova API key. Defaults to None. base_url: API base URL. Defaults to "https://api.sambanova.ai/v1". language: Language of the audio input. .. deprecated:: 0.0.105 - Use ``settings=BaseWhisperSTTSettings(language=...)`` instead. + Use ``settings=SambaNovaSTTSettings(language=...)`` instead. prompt: Optional text to guide the model's style or continue a previous segment. .. deprecated:: 0.0.105 - Use ``settings=BaseWhisperSTTSettings(prompt=...)`` instead. + Use ``settings=SambaNovaSTTSettings(prompt=...)`` instead. temperature: Optional sampling temperature between 0 and 1. .. deprecated:: 0.0.105 - Use ``settings=BaseWhisperSTTSettings(temperature=...)`` instead. + Use ``settings=SambaNovaSTTSettings(temperature=...)`` instead. settings: Runtime-updatable settings. When provided alongside deprecated parameters, ``settings`` values take precedence. @@ -72,24 +80,25 @@ class SambaNovaSTTService(BaseWhisperSTTService): # type: ignore **kwargs: Additional arguments passed to `pipecat.services.whisper.base_stt.BaseWhisperSTTService`. """ # --- 1. Hardcoded defaults --- - default_settings = BaseWhisperSTTSettings( + default_settings = SambaNovaSTTSettings( model="Whisper-Large-v3", language=self.language_to_service_language(Language.EN), - base_url=base_url, + prompt=None, + temperature=None, ) # --- 2. Deprecated direct-arg overrides --- if model is not None: - _warn_deprecated_param("model", BaseWhisperSTTSettings, "model") + _warn_deprecated_param("model", SambaNovaSTTSettings, "model") default_settings.model = model if language is not None: - _warn_deprecated_param("language", BaseWhisperSTTSettings, "language") + _warn_deprecated_param("language", SambaNovaSTTSettings, "language") default_settings.language = self.language_to_service_language(language) if prompt is not None: - _warn_deprecated_param("prompt", BaseWhisperSTTSettings, "prompt") + _warn_deprecated_param("prompt", SambaNovaSTTSettings, "prompt") default_settings.prompt = prompt if temperature is not None: - _warn_deprecated_param("temperature", BaseWhisperSTTSettings, "temperature") + _warn_deprecated_param("temperature", SambaNovaSTTSettings, "temperature") default_settings.temperature = temperature # --- 3. (no params object for this service) --- @@ -107,7 +116,7 @@ class SambaNovaSTTService(BaseWhisperSTTService): # type: ignore ) async def _transcribe(self, audio: bytes) -> Transcription: - assert self._language is not None # Assigned in the BaseWhisperSTTService class + assert self._settings.language is not None if self._include_prob_metrics: # https://docs.sambanova.ai/docs/en/features/audio#request-parameters @@ -122,13 +131,13 @@ class SambaNovaSTTService(BaseWhisperSTTService): # type: ignore "file": ("audio.wav", audio, "audio/wav"), "model": self._settings.model, "response_format": "json", - "language": self._language, + "language": self._settings.language, } - if self._prompt is not None: - kwargs["prompt"] = self._prompt + if self._settings.prompt is not None: + kwargs["prompt"] = self._settings.prompt - if self._temperature is not None: - kwargs["temperature"] = self._temperature + if self._settings.temperature is not None: + kwargs["temperature"] = self._settings.temperature return await self._client.audio.transcriptions.create(**kwargs) diff --git a/src/pipecat/services/sarvam/stt.py b/src/pipecat/services/sarvam/stt.py index f255619bb..d8659a6e7 100644 --- a/src/pipecat/services/sarvam/stt.py +++ b/src/pipecat/services/sarvam/stt.py @@ -142,14 +142,13 @@ class SarvamSTTSettings(STTSettings): """Settings for the Sarvam STT service. Parameters: - prompt: Optional prompt to guide transcription/translation style. - mode: Mode of operation (transcribe, translate, verbatim, etc.). + prompt: Optional prompt to guide transcription/translation style/context. + Only applicable to models that support prompts (e.g., saaras:v2.5). vad_signals: Enable VAD signals in response. high_vad_sensitivity: Enable high VAD sensitivity. """ prompt: str | None | _NotGiven = field(default_factory=lambda: NOT_GIVEN) - mode: str | None | _NotGiven = field(default_factory=lambda: NOT_GIVEN) vad_signals: bool | None | _NotGiven = field(default_factory=lambda: NOT_GIVEN) high_vad_sensitivity: bool | None | _NotGiven = field(default_factory=lambda: NOT_GIVEN) @@ -204,6 +203,9 @@ class SarvamSTTService(STTService): *, api_key: str, model: Optional[str] = None, + mode: Optional[ + Literal["transcribe", "translate", "verbatim", "translit", "codemix"] + ] = None, sample_rate: Optional[int] = None, input_audio_codec: str = "wav", params: Optional[InputParams] = None, @@ -222,6 +224,9 @@ class SarvamSTTService(STTService): .. deprecated:: 0.0.105 Use ``settings=SarvamSTTSettings(model=...)`` instead. + mode: Mode of operation. Options: transcribe, translate, verbatim, + translit, codemix. Only applicable to models that support it + (e.g., saaras:v3). Defaults to the model's default mode. sample_rate: Audio sample rate. Defaults to 16000 if not specified. input_audio_codec: Audio codec/format of the input file. Defaults to "wav". params: Configuration parameters for Sarvam STT service. @@ -238,32 +243,32 @@ class SarvamSTTService(STTService): keepalive_interval: Seconds between idle checks when keepalive is enabled. **kwargs: Additional arguments passed to the parent STTService. """ - # 1. Initialize default_settings with hardcoded defaults + # --- 1. Hardcoded defaults --- default_settings = SarvamSTTSettings( model="saarika:v2.5", language=None, prompt=None, - mode=None, vad_signals=None, high_vad_sensitivity=None, ) - # 2. Apply direct init arg overrides (deprecated) + # --- 2. Deprecated direct-arg overrides --- if model is not None: _warn_deprecated_param("model", SarvamSTTSettings, "model") default_settings.model = model - # 3. Apply params overrides — only if settings not provided + # --- 3. Deprecated params overrides --- if params is not None: _warn_deprecated_param("params", SarvamSTTSettings) if not settings: default_settings.language = params.language default_settings.prompt = params.prompt - default_settings.mode = params.mode + if params.mode is not None: + mode = params.mode default_settings.vad_signals = params.vad_signals default_settings.high_vad_sensitivity = params.high_vad_sensitivity - # 4. Apply settings delta (canonical API, always wins) + # --- 4. Settings delta (canonical API, always wins) --- if settings is not None: default_settings.apply_update(settings) @@ -278,7 +283,7 @@ class SarvamSTTService(STTService): # Validate parameters against model capabilities if default_settings.prompt is not None and not self._config.supports_prompt: raise ValueError(f"Model '{resolved_model}' does not support prompt parameter.") - if default_settings.mode is not None and not self._config.supports_mode: + if mode is not None and not self._config.supports_mode: raise ValueError(f"Model '{resolved_model}' does not support mode parameter.") if default_settings.language is not None and not self._config.supports_language: raise ValueError( @@ -286,8 +291,8 @@ class SarvamSTTService(STTService): ) # Resolve mode default from model config - if default_settings.mode is None: - default_settings.mode = self._config.default_mode + if mode is None: + mode = self._config.default_mode super().__init__( sample_rate=sample_rate, @@ -300,6 +305,9 @@ class SarvamSTTService(STTService): self._api_key = api_key + # Init-only connection config (not runtime-updatable) + self._mode = mode + # Store connection parameters self._input_audio_codec = input_audio_codec @@ -380,30 +388,26 @@ class SarvamSTTService(STTService): f"Model '{self._settings.model}' does not support language parameter " "(auto-detects language)." ) - - if isinstance(delta, SarvamSTTSettings): - if is_given(delta.prompt) and delta.prompt is not None: - if not self._config.supports_prompt: - raise ValueError( - f"Model '{self._settings.model}' does not support prompt parameter." - ) - if is_given(delta.mode) and delta.mode is not None: - if not self._config.supports_mode: - raise ValueError( - f"Model '{self._settings.model}' does not support mode parameter." - ) + if ( + isinstance(delta, SarvamSTTSettings) + and is_given(delta.prompt) + and delta.prompt is not None + ): + if not self._config.supports_prompt: + raise ValueError( + f"Model '{self._settings.model}' does not support prompt parameter." + ) changed = await super()._update_settings(delta) - # TODO: someday we could reconnect here to apply updated settings. - # Code might look something like the below: - # if not changed: - # return changed + # Prompt is a WebSocket connect-time parameter; reconnect to apply. + if "prompt" in changed: + await self._disconnect() + await self._connect() - # await self._disconnect() - # await self._connect() - - self._warn_unhandled_updated_settings(changed) + unhandled = {k: v for k, v in changed.items() if k != "prompt"} + if unhandled: + self._warn_unhandled_updated_settings(unhandled) return changed @@ -542,8 +546,8 @@ class SarvamSTTService(STTService): connect_kwargs["language_code"] = language_string # Add mode for models that support it - if self._config.supports_mode and self._settings.mode is not None: - connect_kwargs["mode"] = self._settings.mode + if self._config.supports_mode and self._mode is not None: + connect_kwargs["mode"] = self._mode # Prompt support differs across sarvamai versions. Prefer connect-time prompt # when available and gracefully degrade if the SDK doesn't accept it. diff --git a/src/pipecat/services/soniox/stt.py b/src/pipecat/services/soniox/stt.py index beadabf1b..483cad062 100644 --- a/src/pipecat/services/soniox/stt.py +++ b/src/pipecat/services/soniox/stt.py @@ -144,8 +144,6 @@ class SonioxSTTSettings(STTSettings): """Settings for Soniox STT service. Parameters: - audio_format: Audio format to use for transcription. - num_channels: Number of channels to use for transcription. language_hints: List of language hints to use for transcription. language_hints_strict: If true, strictly enforce language hints. context: Customization for transcription. String for models with @@ -156,8 +154,6 @@ class SonioxSTTSettings(STTSettings): client_reference_id: Client reference ID to use for transcription. """ - audio_format: str | None | _NotGiven = field(default_factory=lambda: NOT_GIVEN) - num_channels: int | None | _NotGiven = field(default_factory=lambda: NOT_GIVEN) language_hints: List[Language] | None | _NotGiven = field(default_factory=lambda: NOT_GIVEN) language_hints_strict: bool | None | _NotGiven = field(default_factory=lambda: NOT_GIVEN) context: SonioxContextObject | str | None | _NotGiven = field(default_factory=lambda: NOT_GIVEN) @@ -187,6 +183,8 @@ class SonioxSTTService(WebsocketSTTService): url: str = "wss://stt-rt.soniox.com/transcribe-websocket", sample_rate: Optional[int] = None, model: Optional[str] = None, + audio_format: str = "pcm_s16le", + num_channels: int = 1, params: Optional[SonioxInputParams] = None, vad_force_turn_endpoint: bool = True, settings: Optional[SonioxSTTSettings] = None, @@ -204,6 +202,8 @@ class SonioxSTTService(WebsocketSTTService): .. deprecated:: 0.0.105 Use ``settings=SonioxSTTSettings(model=...)`` instead. + audio_format: Audio format for transcription. Defaults to ``"pcm_s16le"``. + num_channels: Number of audio channels. Defaults to 1. params: Additional configuration parameters, such as language hints, context and speaker diarization. @@ -218,12 +218,10 @@ class SonioxSTTService(WebsocketSTTService): Override for your deployment. See https://github.com/pipecat-ai/stt-benchmark **kwargs: Additional arguments passed to the STTService. """ - # 1. Initialize default_settings with hardcoded defaults + # --- 1. Hardcoded defaults --- default_settings = SonioxSTTSettings( model="stt-rt-v4", language=None, - audio_format="pcm_s16le", - num_channels=1, language_hints=None, language_hints_strict=None, context=None, @@ -232,18 +230,20 @@ class SonioxSTTService(WebsocketSTTService): client_reference_id=None, ) - # 2. Apply direct init arg overrides (deprecated) + # --- 2. Deprecated direct-arg overrides --- if model is not None: _warn_deprecated_param("model", SonioxSTTSettings, "model") default_settings.model = model - # 3. Apply params overrides — only if settings not provided + # --- 3. Deprecated params overrides --- if params is not None: _warn_deprecated_param("params", SonioxSTTSettings) if not settings: default_settings.model = params.model - default_settings.audio_format = params.audio_format - default_settings.num_channels = params.num_channels + if params.audio_format is not None: + audio_format = params.audio_format + if params.num_channels is not None: + num_channels = params.num_channels default_settings.language_hints = params.language_hints default_settings.language_hints_strict = params.language_hints_strict default_settings.context = params.context @@ -253,7 +253,7 @@ class SonioxSTTService(WebsocketSTTService): ) default_settings.client_reference_id = params.client_reference_id - # 4. Apply settings delta (canonical API, always wins) + # --- 4. Settings delta (canonical API, always wins) --- if settings is not None: default_settings.apply_update(settings) @@ -270,6 +270,10 @@ class SonioxSTTService(WebsocketSTTService): self._url = url self._vad_force_turn_endpoint = vad_force_turn_endpoint + # Init-only audio config + self._audio_format = audio_format + self._num_channels = num_channels + self._final_transcription_buffer = [] self._last_tokens_received: Optional[float] = None @@ -438,8 +442,8 @@ class SonioxSTTService(WebsocketSTTService): config = { "api_key": self._api_key, "model": s.model, - "audio_format": s.audio_format, - "num_channels": s.num_channels or 1, + "audio_format": self._audio_format, + "num_channels": self._num_channels, "enable_endpoint_detection": enable_endpoint_detection, "sample_rate": self.sample_rate, "language_hints": _prepare_language_hints(s.language_hints), diff --git a/src/pipecat/services/speechmatics/stt.py b/src/pipecat/services/speechmatics/stt.py index a0a5c8b64..b3ded9255 100644 --- a/src/pipecat/services/speechmatics/stt.py +++ b/src/pipecat/services/speechmatics/stt.py @@ -100,7 +100,6 @@ class SpeechmaticsSTTSettings(STTSettings): focus_mode: Speaker focus mode for diarization. known_speakers: List of known speaker labels and identifiers. additional_vocab: List of additional vocabulary entries. - audio_encoding: Audio encoding format. operating_point: Operating point for accuracy vs. latency. max_delay: Maximum delay in seconds for transcription. end_of_utterance_silence_trigger: Maximum delay for end of utterance trigger. @@ -126,7 +125,6 @@ class SpeechmaticsSTTSettings(STTSettings): additional_vocab: list[AdditionalVocabEntry] | _NotGiven = field( default_factory=lambda: NOT_GIVEN ) - audio_encoding: AudioEncoding | _NotGiven = field(default_factory=lambda: NOT_GIVEN) operating_point: OperatingPoint | _NotGiven = field(default_factory=lambda: NOT_GIVEN) max_delay: float | _NotGiven = field(default_factory=lambda: NOT_GIVEN) end_of_utterance_silence_trigger: float | _NotGiven = field(default_factory=lambda: NOT_GIVEN) @@ -344,8 +342,8 @@ class SpeechmaticsSTTService(STTService): class UpdateParams(BaseModel): """Update parameters for Speechmatics STT service. - These are the only parameters that can be changed once a session has started. If you need to - change the language, etc., then you must create a new instance of the service. + .. deprecated:: 0.0.104 + Use ``SpeechmaticsSTTSettings`` with ``STTUpdateSettingsFrame`` instead. Parameters: focus_speakers: List of speaker IDs to focus on. When enabled, only these speakers are @@ -379,6 +377,7 @@ class SpeechmaticsSTTService(STTService): api_key: str | None = None, base_url: str | None = None, sample_rate: int | None = None, + encoding: AudioEncoding = AudioEncoding.PCM_S16LE, params: InputParams | None = None, should_interrupt: bool = True, settings: SpeechmaticsSTTSettings | None = None, @@ -393,6 +392,7 @@ class SpeechmaticsSTTService(STTService): base_url: Base URL for Speechmatics API. Uses environment variable `SPEECHMATICS_RT_URL` or defaults to `wss://eu2.rt.speechmatics.com/v2`. sample_rate: Optional audio sample rate in Hz. + encoding: Audio encoding format. Defaults to ``AudioEncoding.PCM_S16LE``. params: Input parameters for the service. .. deprecated:: 0.0.105 @@ -423,7 +423,7 @@ class SpeechmaticsSTTService(STTService): _params = params or SpeechmaticsSTTService.InputParams() self._check_deprecated_args(kwargs, _params) - # 1. Initialize default_settings with hardcoded defaults + # --- 1. Hardcoded defaults --- default_settings = SpeechmaticsSTTSettings( model=None, # Will be resolved from operating_point after config is built language=Language.EN, @@ -436,7 +436,6 @@ class SpeechmaticsSTTService(STTService): focus_mode=SpeakerFocusMode.RETAIN, known_speakers=[], additional_vocab=[], - audio_encoding=AudioEncoding.PCM_S16LE, operating_point=None, max_delay=None, end_of_utterance_silence_trigger=None, @@ -451,9 +450,9 @@ class SpeechmaticsSTTService(STTService): extra_params=None, ) - # 2. No direct init arg overrides + # --- 2. No direct init arg overrides --- - # 3. Apply params overrides — only if settings not provided + # --- 3. Deprecated params overrides --- if params is not None: _warn_deprecated_param("params", SpeechmaticsSTTSettings) if not settings: @@ -475,7 +474,7 @@ class SpeechmaticsSTTService(STTService): default_settings.focus_mode = _params.focus_mode default_settings.known_speakers = _params.known_speakers default_settings.additional_vocab = _params.additional_vocab - default_settings.audio_encoding = _params.audio_encoding + encoding = _params.audio_encoding default_settings.operating_point = _params.operating_point default_settings.max_delay = _params.max_delay default_settings.end_of_utterance_silence_trigger = ( @@ -493,10 +492,11 @@ class SpeechmaticsSTTService(STTService): # Build SDK config from settings, then resolve model from operating_point self._client: VoiceAgentClient | None = None + self._audio_encoding = encoding self._config: VoiceAgentConfig = self._build_config(default_settings) default_settings.model = self._config.operating_point.value - # 4. Apply settings delta (canonical API, always wins) + # --- 4. Settings delta (canonical API, always wins) --- if settings is not None: default_settings.apply_update(settings) @@ -720,6 +720,9 @@ class SpeechmaticsSTTService(STTService): # Preset from turn detection mode config = VoiceAgentConfigPreset.load(s.turn_detection_mode.value) + # Audio encoding (init-only, stored as instance attribute) + config.audio_encoding = self._audio_encoding + # Language + domain language = s.language config.language = self._language_to_speechmatics_language(language) @@ -773,7 +776,7 @@ class SpeechmaticsSTTService(STTService): ) -> None: """Updates the speaker configuration. - .. deprecated:: + .. deprecated:: 0.0.104 Use ``STTUpdateSettingsFrame`` with ``SpeechmaticsSTTSettings(...)`` instead. diff --git a/src/pipecat/services/whisper/base_stt.py b/src/pipecat/services/whisper/base_stt.py index c2dde8acc..f89d7f5d0 100644 --- a/src/pipecat/services/whisper/base_stt.py +++ b/src/pipecat/services/whisper/base_stt.py @@ -10,15 +10,15 @@ This module provides common functionality for services implementing the Whisper interface, including language mapping, metrics generation, and error handling. """ -from dataclasses import dataclass, field -from typing import Any, AsyncGenerator, Optional +from dataclasses import dataclass +from typing import AsyncGenerator, Optional from loguru import logger from openai import AsyncOpenAI from openai.types.audio import Transcription from pipecat.frames.frames import ErrorFrame, Frame, TranscriptionFrame -from pipecat.services.settings import NOT_GIVEN, STTSettings, _NotGiven, _warn_deprecated_param +from pipecat.services.settings import STTSettings, _NotGiven, _warn_deprecated_param from pipecat.services.stt_latency import WHISPER_TTFS_P99 from pipecat.services.stt_service import SegmentedSTTService from pipecat.transcriptions.language import Language, resolve_language @@ -31,15 +31,13 @@ class BaseWhisperSTTSettings(STTSettings): """Settings for Whisper API-based STT services. Parameters: - base_url: API base URL. prompt: Optional text to guide the model's style or continue a previous segment. temperature: Sampling temperature between 0 and 1. """ - base_url: str | _NotGiven = field(default_factory=lambda: NOT_GIVEN) - prompt: str | _NotGiven = field(default_factory=lambda: NOT_GIVEN) - temperature: float | _NotGiven = field(default_factory=lambda: NOT_GIVEN) + prompt: str | None | _NotGiven = None + temperature: float | None | _NotGiven = None def language_to_whisper_language(language: Language) -> Optional[str]: @@ -185,7 +183,6 @@ class BaseWhisperSTTService(SegmentedSTTService): default_settings = BaseWhisperSTTSettings( model=None, language=None, - base_url=base_url, ) # --- 2. Deprecated direct-arg overrides --- @@ -214,32 +211,12 @@ class BaseWhisperSTTService(SegmentedSTTService): **kwargs, ) self._client = self._create_client(api_key, base_url) - self._language = self._settings.language - self._prompt = self._settings.prompt - self._temperature = self._settings.temperature self._include_prob_metrics = include_prob_metrics self._push_empty_transcripts = push_empty_transcripts def _create_client(self, api_key: Optional[str], base_url: Optional[str]): return AsyncOpenAI(api_key=api_key, base_url=base_url) - async def _update_settings(self, delta: STTSettings) -> dict[str, Any]: - """Apply a settings delta, syncing instance variables. - - Keeps ``_language``, ``_prompt``, and ``_temperature`` in sync with - the settings fields. - """ - changed = await super()._update_settings(delta) - - if "language" in changed: - self._language = self._settings.language - if "prompt" in changed: - self._prompt = self._settings.prompt - if "temperature" in changed: - self._temperature = self._settings.temperature - - return changed - def can_generate_metrics(self) -> bool: """Whether this service can generate processing metrics. @@ -289,7 +266,7 @@ class BaseWhisperSTTService(SegmentedSTTService): logger.warning("Received empty transcription from API") if text or self._push_empty_transcripts: - await self._handle_transcription(text, True, self._language) + await self._handle_transcription(text, True, self._settings.language) logger.debug(f"Transcription: [{text}]") yield TranscriptionFrame( text, diff --git a/src/pipecat/services/whisper/stt.py b/src/pipecat/services/whisper/stt.py index f3ac0c948..af96f92c0 100644 --- a/src/pipecat/services/whisper/stt.py +++ b/src/pipecat/services/whisper/stt.py @@ -179,13 +179,9 @@ class WhisperSTTSettings(STTSettings): """Settings for the local Whisper (Faster Whisper) STT service. Parameters: - device: Inference device ('cpu', 'cuda', or 'auto'). - compute_type: Compute type for inference ('default', 'int8', etc.). no_speech_prob: Probability threshold for filtering non-speech segments. """ - device: str | _NotGiven = field(default_factory=lambda: NOT_GIVEN) - compute_type: str | _NotGiven = field(default_factory=lambda: NOT_GIVEN) no_speech_prob: float | _NotGiven = field(default_factory=lambda: NOT_GIVEN) @@ -217,8 +213,8 @@ class WhisperSTTService(SegmentedSTTService): self, *, model: Optional[str | Model] = None, - device: Optional[str] = None, - compute_type: Optional[str] = None, + device: str = "auto", + compute_type: str = "default", no_speech_prob: Optional[float] = None, language: Optional[Language] = None, settings: Optional[WhisperSTTSettings] = None, @@ -233,15 +229,9 @@ class WhisperSTTService(SegmentedSTTService): Use ``settings=WhisperSTTSettings(model=...)`` instead. device: The device to run inference on ('cpu', 'cuda', or 'auto'). - - .. deprecated:: 0.0.105 - Use ``settings=WhisperSTTSettings(device=...)`` instead. - - compute_type: The compute type for inference ('default', 'int8', 'int8_float16', etc.). - - .. deprecated:: 0.0.105 - Use ``settings=WhisperSTTSettings(compute_type=...)`` instead. - + Defaults to ``"auto"``. + compute_type: The compute type for inference ('default', 'int8', + 'int8_float16', etc.). Defaults to ``"default"``. no_speech_prob: Probability threshold for filtering out non-speech segments. .. deprecated:: 0.0.105 @@ -260,8 +250,6 @@ class WhisperSTTService(SegmentedSTTService): default_settings = WhisperSTTSettings( model=Model.DISTIL_MEDIUM_EN.value, language=Language.EN, - device="auto", - compute_type="default", no_speech_prob=0.4, ) @@ -269,12 +257,6 @@ class WhisperSTTService(SegmentedSTTService): if model is not None: _warn_deprecated_param("model", WhisperSTTSettings, "model") default_settings.model = model if isinstance(model, str) else model.value - if device is not None: - _warn_deprecated_param("device", WhisperSTTSettings, "device") - default_settings.device = device - if compute_type is not None: - _warn_deprecated_param("compute_type", WhisperSTTSettings, "compute_type") - default_settings.compute_type = compute_type if no_speech_prob is not None: _warn_deprecated_param("no_speech_prob", WhisperSTTSettings, "no_speech_prob") default_settings.no_speech_prob = no_speech_prob @@ -292,9 +274,11 @@ class WhisperSTTService(SegmentedSTTService): settings=default_settings, **kwargs, ) - self._device: str = self._settings.device - self._compute_type = self._settings.compute_type - self._no_speech_prob = self._settings.no_speech_prob + + # Init-only inference config + self._device = device + self._compute_type = compute_type + self._model: Optional[WhisperModel] = None self._load() @@ -373,7 +357,7 @@ class WhisperSTTService(SegmentedSTTService): ) text: str = "" for segment in segments: - if segment.no_speech_prob < self._no_speech_prob: + if segment.no_speech_prob < self._settings.no_speech_prob: text += f"{segment.text} " await self.stop_processing_metrics() @@ -471,9 +455,6 @@ class WhisperSTTServiceMLX(WhisperSTTService): **kwargs, ) - self._no_speech_prob = self._settings.no_speech_prob - self._temperature = self._settings.temperature - # No need to call _load() as MLX Whisper loads models on demand @override @@ -514,7 +495,7 @@ class WhisperSTTServiceMLX(WhisperSTTService): mlx_whisper.transcribe, audio_float, path_or_hf_repo=self._settings.model, - temperature=self._temperature, + temperature=self._settings.temperature, language=self._settings.language, ) text: str = "" @@ -523,7 +504,7 @@ class WhisperSTTServiceMLX(WhisperSTTService): if segment.get("compression_ratio", None) == 0.5555555555555556: continue - if segment.get("no_speech_prob", 0.0) < self._no_speech_prob: + if segment.get("no_speech_prob", 0.0) < self._settings.no_speech_prob: text += f"{segment.get('text', '')} " if len(text.strip()) == 0: diff --git a/tests/test_settings.py b/tests/test_settings.py index ce3e35af0..201e85745 100644 --- a/tests/test_settings.py +++ b/tests/test_settings.py @@ -328,8 +328,6 @@ class TestDeepgramSTTSettingsApplyUpdate: defaults = dict( model="nova-3-general", language="en", - encoding="linear16", - channels=1, interim_results=True, smart_format=False, punctuate=True, @@ -350,8 +348,8 @@ class TestDeepgramSTTSettingsApplyUpdate: assert current.punctuate is False assert "punctuate" in changed # Other fields are untouched - assert current.encoding == "linear16" - assert current.channels == 1 + assert current.model == "nova-3-general" + assert current.language == "en" def test_apply_update_model(self): """model field is updated directly.""" @@ -427,8 +425,6 @@ class TestDeepgramSTTSettingsFromMapping: current = DeepgramSTTSettings( model="nova-3-general", language="en", - encoding="linear16", - channels=1, interim_results=True, punctuate=True, profanity_filter=True, @@ -442,7 +438,6 @@ class TestDeepgramSTTSettingsFromMapping: assert current.punctuate is False assert current.diarize is True # Unchanged fields stay put - assert current.encoding == "linear16" assert current.model == "nova-3-general" assert "punctuate" in changed @@ -451,8 +446,6 @@ class TestDeepgramSTTSettingsFromMapping: current = DeepgramSTTSettings( model="nova-3-general", language="en", - encoding="linear16", - channels=1, ) raw = {"model": "nova-2"} @@ -474,16 +467,13 @@ class TestDeepgramSageMakerSTTSettings: store = DeepgramSageMakerSTTSettings( model="nova-3", language="en", - encoding="linear16", - channels=1, - punctuate=True, ) - delta = DeepgramSageMakerSTTSettings(punctuate=False) + delta = DeepgramSageMakerSTTSettings(model="nova-2") changed = store.apply_update(delta) - assert store.punctuate is False - assert store.encoding == "linear16" - assert "punctuate" in changed + assert store.model == "nova-2" + assert store.language == "en" + assert "model" in changed # --------------------------------------------------------------------------- @@ -499,17 +489,17 @@ class TestDeepgramSTTSettingsExtraSync: return DeepgramSTTService(api_key="test-key", sample_rate=16000, **kwargs) def test_extra_synced_to_declared_field_at_init(self): - """If LiveOptions has unknown params in _extra, they can be synced if they match fields.""" + """LiveOptions params that match declared fields are synced at init.""" from pipecat.services.deepgram.stt import LiveOptions - # Use **kwargs to pass undeclared params - live_options = LiveOptions(numerals=True) # 'numerals' goes into _extra + live_options = LiveOptions(numerals=True) svc = self._make_service(live_options=live_options) - # 'numerals' doesn't match a declared DeepgramSTTSettings field, - # so it should stay in extra - assert svc._settings.extra["numerals"] is True + # 'numerals' is a declared DeepgramSTTSettings field, + # so it should be promoted from extra to the declared field + assert svc._settings.numerals is True + assert "numerals" not in svc._settings.extra def test_declared_field_from_live_options(self): """LiveOptions fields that match DeepgramSTTSettings fields are applied.""" @@ -532,7 +522,7 @@ class TestDeepgramSTTSettingsExtraSync: raw_dict = { "diarize": True, # matches declared field "punctuate": False, # matches declared field - "numerals": True, # doesn't match - stays in extra + "custom_param": "value", # doesn't match - stays in extra } delta = DeepgramSTTSettings.from_mapping(raw_dict) @@ -541,7 +531,7 @@ class TestDeepgramSTTSettingsExtraSync: assert delta.diarize is True assert delta.punctuate is False # Unknown stays in extra - assert delta.extra["numerals"] is True + assert delta.extra["custom_param"] == "value" # Now simulate syncing (though from_mapping already routes correctly) delta._sync_extra_to_fields() @@ -549,7 +539,7 @@ class TestDeepgramSTTSettingsExtraSync: # Still the same - from_mapping already put them in the right place assert delta.diarize is True assert delta.punctuate is False - assert delta.extra["numerals"] is True + assert delta.extra["custom_param"] == "value" def test_sync_promotes_extra_to_field_when_not_given(self): """_sync_extra_to_fields promotes extra dict entries to declared fields.""" @@ -611,16 +601,17 @@ class TestDeepgramSTTSettingsExtraSync: """Unknown params (not matching fields) stay in extra and get forwarded.""" from pipecat.services.deepgram.stt import LiveOptions - # numerals isn't a declared field in DeepgramSTTSettings + # 'numerals' is now a declared field; 'custom_param' is not live_options = LiveOptions(numerals=True, custom_param="test") svc = self._make_service(live_options=live_options) - # Should be in extra - assert svc._settings.extra["numerals"] is True + # 'numerals' is a declared field, so it should be promoted + assert svc._settings.numerals is True + # 'custom_param' is unknown, so it stays in extra assert svc._settings.extra["custom_param"] == "test" - # And forwarded to kwargs + # Both forwarded to kwargs kwargs = svc._build_connect_kwargs() assert kwargs["numerals"] == "true" assert kwargs["custom_param"] == "test" From a4375274b29c4cc4a0ecfc4e88cdda97b3017783 Mon Sep 17 00:00:00 2001 From: Mark Backman Date: Wed, 4 Mar 2026 18:04:59 -0500 Subject: [PATCH 0811/1060] Add Settings subclasses to all services and auto-discovered init tests - Add dedicated Settings subclasses to 20 LLM services that were borrowing parent Settings classes (e.g. AzureLLMSettings, GroqLLMSettings) so users don't need cross-module imports - Fix field defaults to NOT_GIVEN in BaseWhisperSTTSettings, OpenAIRealtimeSTTSettings, and NvidiaSegmentedSTTSettings for delta-mode safety - Fix incomplete default_settings in AWS, Cartesia, ElevenLabs, Fish, and Whisper services so validate_complete() passes - Add auto-discovered tests that verify all Settings classes default to NOT_GIVEN (delta safety) and all services initialize with complete settings (store completeness) --- src/pipecat/services/aws/stt.py | 1 + src/pipecat/services/azure/llm.py | 14 +- src/pipecat/services/azure/realtime/llm.py | 11 +- src/pipecat/services/cartesia/tts.py | 2 + src/pipecat/services/cerebras/llm.py | 14 +- src/pipecat/services/deepseek/llm.py | 14 +- src/pipecat/services/elevenlabs/tts.py | 17 ++ src/pipecat/services/fireworks/llm.py | 14 +- src/pipecat/services/fish/tts.py | 1 + .../services/google/gemini_live/llm_vertex.py | 16 +- src/pipecat/services/google/llm_openai.py | 14 +- src/pipecat/services/google/llm_vertex.py | 16 +- src/pipecat/services/grok/llm.py | 13 +- src/pipecat/services/groq/llm.py | 14 +- src/pipecat/services/mistral/llm.py | 14 +- src/pipecat/services/nvidia/llm.py | 14 +- src/pipecat/services/nvidia/stt.py | 14 +- src/pipecat/services/ollama/llm.py | 14 +- src/pipecat/services/openai/stt.py | 6 +- .../services/openai_realtime_beta/azure.py | 10 +- src/pipecat/services/openpipe/llm.py | 14 +- src/pipecat/services/openrouter/llm.py | 14 +- src/pipecat/services/perplexity/llm.py | 14 +- src/pipecat/services/qwen/llm.py | 14 +- src/pipecat/services/sambanova/llm.py | 14 +- src/pipecat/services/together/llm.py | 14 +- src/pipecat/services/whisper/base_stt.py | 10 +- tests/test_service_init.py | 181 ++++++++++++++++++ 28 files changed, 436 insertions(+), 72 deletions(-) create mode 100644 tests/test_service_init.py diff --git a/src/pipecat/services/aws/stt.py b/src/pipecat/services/aws/stt.py index dd2f2f97b..f46f5259c 100644 --- a/src/pipecat/services/aws/stt.py +++ b/src/pipecat/services/aws/stt.py @@ -98,6 +98,7 @@ class AWSTranscribeSTTService(WebsocketSTTService): """ # 1. Initialize default_settings with hardcoded defaults default_settings = AWSTranscribeSTTSettings( + model=None, language=self.language_to_service_language(Language.EN) or "en-US", ) diff --git a/src/pipecat/services/azure/llm.py b/src/pipecat/services/azure/llm.py index 19a31320e..5f1ce2698 100644 --- a/src/pipecat/services/azure/llm.py +++ b/src/pipecat/services/azure/llm.py @@ -6,6 +6,7 @@ """Azure OpenAI service implementation for the Pipecat AI framework.""" +from dataclasses import dataclass from typing import Optional from loguru import logger @@ -16,6 +17,13 @@ from pipecat.services.openai.llm import OpenAILLMService from pipecat.services.settings import _warn_deprecated_param +@dataclass +class AzureLLMSettings(OpenAILLMSettings): + """Settings for Azure OpenAI LLM service.""" + + pass + + class AzureLLMService(OpenAILLMService): """A service for interacting with Azure OpenAI using the OpenAI-compatible interface. @@ -30,7 +38,7 @@ class AzureLLMService(OpenAILLMService): endpoint: str, model: Optional[str] = None, api_version: str = "2024-09-01-preview", - settings: Optional[OpenAILLMSettings] = None, + settings: Optional[AzureLLMSettings] = None, **kwargs, ): """Initialize the Azure LLM service. @@ -49,11 +57,11 @@ class AzureLLMService(OpenAILLMService): **kwargs: Additional keyword arguments passed to OpenAILLMService. """ # 1. Initialize default_settings with hardcoded defaults - default_settings = OpenAILLMSettings(model="gpt-4o") + default_settings = AzureLLMSettings(model="gpt-4o") # 2. Apply direct init arg overrides (deprecated) if model is not None: - _warn_deprecated_param("model", OpenAILLMSettings, "model") + _warn_deprecated_param("model", AzureLLMSettings, "model") default_settings.model = model # 4. Apply settings delta (canonical API, always wins) diff --git a/src/pipecat/services/azure/realtime/llm.py b/src/pipecat/services/azure/realtime/llm.py index 39c9bd707..fa645d8c1 100644 --- a/src/pipecat/services/azure/realtime/llm.py +++ b/src/pipecat/services/azure/realtime/llm.py @@ -6,9 +6,11 @@ """Azure OpenAI Realtime LLM service implementation.""" +from dataclasses import dataclass + from loguru import logger -from pipecat.services.openai.realtime.llm import OpenAIRealtimeLLMService +from pipecat.services.openai.realtime.llm import OpenAIRealtimeLLMService, OpenAIRealtimeLLMSettings try: from websockets.asyncio.client import connect as websocket_connect @@ -18,6 +20,13 @@ except ModuleNotFoundError as e: raise Exception(f"Missing module: {e}") +@dataclass +class AzureRealtimeLLMSettings(OpenAIRealtimeLLMSettings): + """Settings for Azure Realtime LLM service.""" + + pass + + class AzureRealtimeLLMService(OpenAIRealtimeLLMService): """Azure OpenAI Realtime LLM service with Azure-specific authentication. diff --git a/src/pipecat/services/cartesia/tts.py b/src/pipecat/services/cartesia/tts.py index 71017074b..166aa70af 100644 --- a/src/pipecat/services/cartesia/tts.py +++ b/src/pipecat/services/cartesia/tts.py @@ -301,6 +301,7 @@ class CartesiaTTSService(AudioContextTTSService): # 1. Initialize default_settings with hardcoded defaults default_settings = CartesiaTTSSettings( model="sonic-3", + voice=None, language=language_to_cartesia_language(Language.EN), generation_config=None, pronunciation_dict_id=None, @@ -745,6 +746,7 @@ class CartesiaHttpTTSService(TTSService): # 1. Initialize default_settings with hardcoded defaults default_settings = CartesiaTTSSettings( model="sonic-3", + voice=None, language=language_to_cartesia_language(Language.EN), generation_config=None, pronunciation_dict_id=None, diff --git a/src/pipecat/services/cerebras/llm.py b/src/pipecat/services/cerebras/llm.py index c952b9552..40862f252 100644 --- a/src/pipecat/services/cerebras/llm.py +++ b/src/pipecat/services/cerebras/llm.py @@ -6,6 +6,7 @@ """Cerebras LLM service implementation using OpenAI-compatible interface.""" +from dataclasses import dataclass from typing import Optional from loguru import logger @@ -16,6 +17,13 @@ from pipecat.services.openai.llm import OpenAILLMService from pipecat.services.settings import _warn_deprecated_param +@dataclass +class CerebrasLLMSettings(OpenAILLMSettings): + """Settings for Cerebras LLM service.""" + + pass + + class CerebrasLLMService(OpenAILLMService): """A service for interacting with Cerebras's API using the OpenAI-compatible interface. @@ -29,7 +37,7 @@ class CerebrasLLMService(OpenAILLMService): api_key: str, base_url: str = "https://api.cerebras.ai/v1", model: Optional[str] = None, - settings: Optional[OpenAILLMSettings] = None, + settings: Optional[CerebrasLLMSettings] = None, **kwargs, ): """Initialize the Cerebras LLM service. @@ -47,11 +55,11 @@ class CerebrasLLMService(OpenAILLMService): **kwargs: Additional keyword arguments passed to OpenAILLMService. """ # 1. Initialize default_settings with hardcoded defaults - default_settings = OpenAILLMSettings(model="gpt-oss-120b") + default_settings = CerebrasLLMSettings(model="gpt-oss-120b") # 2. Apply direct init arg overrides (deprecated) if model is not None: - _warn_deprecated_param("model", OpenAILLMSettings, "model") + _warn_deprecated_param("model", CerebrasLLMSettings, "model") default_settings.model = model # 4. Apply settings delta (canonical API, always wins) diff --git a/src/pipecat/services/deepseek/llm.py b/src/pipecat/services/deepseek/llm.py index 3d7c67e2a..d778639ef 100644 --- a/src/pipecat/services/deepseek/llm.py +++ b/src/pipecat/services/deepseek/llm.py @@ -6,6 +6,7 @@ """DeepSeek LLM service implementation using OpenAI-compatible interface.""" +from dataclasses import dataclass from typing import Optional from loguru import logger @@ -16,6 +17,13 @@ from pipecat.services.openai.llm import OpenAILLMService from pipecat.services.settings import _warn_deprecated_param +@dataclass +class DeepSeekLLMSettings(OpenAILLMSettings): + """Settings for DeepSeek LLM service.""" + + pass + + class DeepSeekLLMService(OpenAILLMService): """A service for interacting with DeepSeek's API using the OpenAI-compatible interface. @@ -29,7 +37,7 @@ class DeepSeekLLMService(OpenAILLMService): api_key: str, base_url: str = "https://api.deepseek.com/v1", model: Optional[str] = None, - settings: Optional[OpenAILLMSettings] = None, + settings: Optional[DeepSeekLLMSettings] = None, **kwargs, ): """Initialize the DeepSeek LLM service. @@ -47,11 +55,11 @@ class DeepSeekLLMService(OpenAILLMService): **kwargs: Additional keyword arguments passed to OpenAILLMService. """ # 1. Initialize default_settings with hardcoded defaults - default_settings = OpenAILLMSettings(model="deepseek-chat") + default_settings = DeepSeekLLMSettings(model="deepseek-chat") # 2. Apply direct init arg overrides (deprecated) if model is not None: - _warn_deprecated_param("model", OpenAILLMSettings, "model") + _warn_deprecated_param("model", DeepSeekLLMSettings, "model") default_settings.model = model # 4. Apply settings delta (canonical API, always wins) diff --git a/src/pipecat/services/elevenlabs/tts.py b/src/pipecat/services/elevenlabs/tts.py index c22455e7a..cfb08eb6d 100644 --- a/src/pipecat/services/elevenlabs/tts.py +++ b/src/pipecat/services/elevenlabs/tts.py @@ -418,6 +418,14 @@ class ElevenLabsTTSService(AudioContextTTSService): # 1. Initialize default_settings with hardcoded defaults default_settings = ElevenLabsTTSSettings( model="eleven_turbo_v2_5", + voice=None, + language=None, + stability=None, + similarity_boost=None, + style=None, + use_speaker_boost=None, + speed=None, + apply_text_normalization=None, ) # Track init-only URL params through the override chain @@ -986,6 +994,15 @@ class ElevenLabsHttpTTSService(TTSService): # 1. Initialize default_settings with hardcoded defaults default_settings = ElevenLabsHttpTTSSettings( model="eleven_turbo_v2_5", + voice=None, + language=None, + optimize_streaming_latency=None, + stability=None, + similarity_boost=None, + style=None, + use_speaker_boost=None, + speed=None, + apply_text_normalization=None, ) # 2. Apply direct init arg overrides (deprecated) diff --git a/src/pipecat/services/fireworks/llm.py b/src/pipecat/services/fireworks/llm.py index e7866c55d..7ba3f9eac 100644 --- a/src/pipecat/services/fireworks/llm.py +++ b/src/pipecat/services/fireworks/llm.py @@ -6,6 +6,7 @@ """Fireworks AI service implementation using OpenAI-compatible interface.""" +from dataclasses import dataclass from typing import Optional from loguru import logger @@ -16,6 +17,13 @@ from pipecat.services.openai.llm import OpenAILLMService from pipecat.services.settings import _warn_deprecated_param +@dataclass +class FireworksLLMSettings(OpenAILLMSettings): + """Settings for Fireworks LLM service.""" + + pass + + class FireworksLLMService(OpenAILLMService): """A service for interacting with Fireworks AI using the OpenAI-compatible interface. @@ -29,7 +37,7 @@ class FireworksLLMService(OpenAILLMService): api_key: str, model: Optional[str] = None, base_url: str = "https://api.fireworks.ai/inference/v1", - settings: Optional[OpenAILLMSettings] = None, + settings: Optional[FireworksLLMSettings] = None, **kwargs, ): """Initialize the Fireworks LLM service. @@ -47,11 +55,11 @@ class FireworksLLMService(OpenAILLMService): **kwargs: Additional keyword arguments passed to OpenAILLMService. """ # 1. Initialize default_settings with hardcoded defaults - default_settings = OpenAILLMSettings(model="accounts/fireworks/models/firefunction-v2") + default_settings = FireworksLLMSettings(model="accounts/fireworks/models/firefunction-v2") # 2. Apply direct init arg overrides (deprecated) if model is not None: - _warn_deprecated_param("model", OpenAILLMSettings, "model") + _warn_deprecated_param("model", FireworksLLMSettings, "model") default_settings.model = model # 4. Apply settings delta (canonical API, always wins) diff --git a/src/pipecat/services/fish/tts.py b/src/pipecat/services/fish/tts.py index 78b021c51..9ea749546 100644 --- a/src/pipecat/services/fish/tts.py +++ b/src/pipecat/services/fish/tts.py @@ -173,6 +173,7 @@ class FishAudioTTSService(InterruptibleTTSService): default_settings = FishAudioTTSSettings( model="s1", voice=None, + language=None, latency="normal", normalize=True, prosody_speed=1.0, diff --git a/src/pipecat/services/google/gemini_live/llm_vertex.py b/src/pipecat/services/google/gemini_live/llm_vertex.py index 5d63251d9..43d3ab207 100644 --- a/src/pipecat/services/google/gemini_live/llm_vertex.py +++ b/src/pipecat/services/google/gemini_live/llm_vertex.py @@ -12,6 +12,7 @@ streaming responses, and tool usage. """ import json +from dataclasses import dataclass from typing import List, Optional, Union from loguru import logger @@ -41,6 +42,13 @@ except ModuleNotFoundError as e: raise Exception(f"Missing module: {e}") +@dataclass +class GeminiLiveVertexLLMSettings(GeminiLiveLLMSettings): + """Settings for Gemini Live Vertex LLM service.""" + + pass + + class GeminiLiveVertexLLMService(GeminiLiveLLMService): """Provides access to Google's Gemini Live model via Vertex AI. @@ -63,7 +71,7 @@ class GeminiLiveVertexLLMService(GeminiLiveLLMService): system_instruction: Optional[str] = None, tools: Optional[Union[List[dict], ToolsSchema]] = None, params: Optional[InputParams] = None, - settings: Optional[GeminiLiveLLMSettings] = None, + settings: Optional[GeminiLiveVertexLLMSettings] = None, inference_on_context_initialization: bool = True, file_api_base_url: str = "https://generativelanguage.googleapis.com/v1beta/files", http_options: Optional[HttpOptions] = None, @@ -122,7 +130,7 @@ class GeminiLiveVertexLLMService(GeminiLiveLLMService): # double deprecation warnings from the parent. # 1. Initialize default_settings with hardcoded defaults - default_settings = GeminiLiveLLMSettings( + default_settings = GeminiLiveVertexLLMSettings( model="google/gemini-live-2.5-flash-native-audio", frequency_penalty=None, max_tokens=4096, @@ -146,12 +154,12 @@ class GeminiLiveVertexLLMService(GeminiLiveLLMService): # 2. Apply direct init arg overrides (deprecated) if model is not None: - _warn_deprecated_param("model", GeminiLiveLLMSettings, "model") + _warn_deprecated_param("model", GeminiLiveVertexLLMSettings, "model") default_settings.model = model # 3. Apply params overrides — only if settings not provided if params is not None: - _warn_deprecated_param("params", GeminiLiveLLMSettings) + _warn_deprecated_param("params", GeminiLiveVertexLLMSettings) if not settings: default_settings.frequency_penalty = params.frequency_penalty default_settings.max_tokens = params.max_tokens diff --git a/src/pipecat/services/google/llm_openai.py b/src/pipecat/services/google/llm_openai.py index b33eefd9a..1d7ae6bc4 100644 --- a/src/pipecat/services/google/llm_openai.py +++ b/src/pipecat/services/google/llm_openai.py @@ -12,6 +12,7 @@ API format through Google's Gemini API OpenAI compatibility layer. import json import os +from dataclasses import dataclass from typing import Optional from openai import AsyncStream @@ -32,6 +33,13 @@ from pipecat.services.openai.llm import OpenAILLMService from pipecat.services.settings import _warn_deprecated_param +@dataclass +class GoogleOpenAILLMSettings(OpenAILLMSettings): + """Settings for Google OpenAI-compatible LLM service.""" + + pass + + class GoogleLLMOpenAIBetaService(OpenAILLMService): """Google LLM service using OpenAI-compatible API format. @@ -56,7 +64,7 @@ class GoogleLLMOpenAIBetaService(OpenAILLMService): api_key: str, base_url: str = "https://generativelanguage.googleapis.com/v1beta/openai/", model: Optional[str] = None, - settings: Optional[OpenAILLMSettings] = None, + settings: Optional[GoogleOpenAILLMSettings] = None, **kwargs, ): """Initialize the Google LLM service. @@ -85,11 +93,11 @@ class GoogleLLMOpenAIBetaService(OpenAILLMService): ) # 1. Initialize default_settings with hardcoded defaults - default_settings = OpenAILLMSettings(model="gemini-2.0-flash") + default_settings = GoogleOpenAILLMSettings(model="gemini-2.0-flash") # 2. Apply direct init arg overrides (deprecated) if model is not None: - _warn_deprecated_param("model", OpenAILLMSettings, "model") + _warn_deprecated_param("model", GoogleOpenAILLMSettings, "model") default_settings.model = model # 4. Apply settings delta (canonical API, always wins) diff --git a/src/pipecat/services/google/llm_vertex.py b/src/pipecat/services/google/llm_vertex.py index b1a9de584..e21341614 100644 --- a/src/pipecat/services/google/llm_vertex.py +++ b/src/pipecat/services/google/llm_vertex.py @@ -12,6 +12,7 @@ extending the GoogleLLMService with Vertex AI authentication. import json import os +from dataclasses import dataclass # Suppress gRPC fork warnings os.environ["GRPC_ENABLE_FORK_SUPPORT"] = "false" @@ -39,6 +40,13 @@ except ModuleNotFoundError as e: raise Exception(f"Missing module: {e}") +@dataclass +class GoogleVertexLLMSettings(GoogleLLMSettings): + """Settings for Google Vertex LLM service.""" + + pass + + class GoogleVertexLLMService(GoogleLLMService): """Google Vertex AI LLM service extending GoogleLLMService. @@ -104,7 +112,7 @@ class GoogleVertexLLMService(GoogleLLMService): location: Optional[str] = None, project_id: Optional[str] = None, params: Optional[GoogleLLMService.InputParams] = None, - settings: Optional[GoogleLLMSettings] = None, + settings: Optional[GoogleVertexLLMSettings] = None, system_instruction: Optional[str] = None, tools: Optional[list] = None, tool_config: Optional[dict] = None, @@ -183,7 +191,7 @@ class GoogleVertexLLMService(GoogleLLMService): self._location = location # 1. Initialize default_settings with hardcoded defaults - default_settings = GoogleLLMSettings( + default_settings = GoogleVertexLLMSettings( model="gemini-2.5-flash", max_tokens=4096, temperature=None, @@ -200,12 +208,12 @@ class GoogleVertexLLMService(GoogleLLMService): # 2. Apply direct init arg overrides (deprecated) if model is not None: - _warn_deprecated_param("model", GoogleLLMSettings, "model") + _warn_deprecated_param("model", GoogleVertexLLMSettings, "model") default_settings.model = model # 3. Apply params overrides — only if settings not provided if params is not None: - _warn_deprecated_param("params", GoogleLLMSettings) + _warn_deprecated_param("params", GoogleVertexLLMSettings) if not settings: default_settings.max_tokens = params.max_tokens default_settings.temperature = params.temperature diff --git a/src/pipecat/services/grok/llm.py b/src/pipecat/services/grok/llm.py index 98c925ac5..7f9ac643b 100644 --- a/src/pipecat/services/grok/llm.py +++ b/src/pipecat/services/grok/llm.py @@ -70,6 +70,13 @@ class GrokContextAggregatorPair: return self._assistant +@dataclass +class GrokLLMSettings(OpenAILLMSettings): + """Settings for Grok LLM service.""" + + pass + + class GrokLLMService(OpenAILLMService): """A service for interacting with Grok's API using the OpenAI-compatible interface. @@ -85,7 +92,7 @@ class GrokLLMService(OpenAILLMService): api_key: str, base_url: str = "https://api.x.ai/v1", model: Optional[str] = None, - settings: Optional[OpenAILLMSettings] = None, + settings: Optional[GrokLLMSettings] = None, **kwargs, ): """Initialize the GrokLLMService with API key and model. @@ -103,11 +110,11 @@ class GrokLLMService(OpenAILLMService): **kwargs: Additional keyword arguments passed to OpenAILLMService. """ # 1. Initialize default_settings with hardcoded defaults - default_settings = OpenAILLMSettings(model="grok-3-beta") + default_settings = GrokLLMSettings(model="grok-3-beta") # 2. Apply direct init arg overrides (deprecated) if model is not None: - _warn_deprecated_param("model", OpenAILLMSettings, "model") + _warn_deprecated_param("model", GrokLLMSettings, "model") default_settings.model = model # 4. Apply settings delta (canonical API, always wins) diff --git a/src/pipecat/services/groq/llm.py b/src/pipecat/services/groq/llm.py index c69776ad0..5b81a4c7d 100644 --- a/src/pipecat/services/groq/llm.py +++ b/src/pipecat/services/groq/llm.py @@ -6,6 +6,7 @@ """Groq LLM Service implementation using OpenAI-compatible interface.""" +from dataclasses import dataclass from typing import Optional from loguru import logger @@ -15,6 +16,13 @@ from pipecat.services.openai.llm import OpenAILLMService from pipecat.services.settings import _warn_deprecated_param +@dataclass +class GroqLLMSettings(OpenAILLMSettings): + """Settings for Groq LLM service.""" + + pass + + class GroqLLMService(OpenAILLMService): """A service for interacting with Groq's API using the OpenAI-compatible interface. @@ -28,7 +36,7 @@ class GroqLLMService(OpenAILLMService): api_key: str, base_url: str = "https://api.groq.com/openai/v1", model: Optional[str] = None, - settings: Optional[OpenAILLMSettings] = None, + settings: Optional[GroqLLMSettings] = None, **kwargs, ): """Initialize Groq LLM service. @@ -46,11 +54,11 @@ class GroqLLMService(OpenAILLMService): **kwargs: Additional keyword arguments passed to OpenAILLMService. """ # 1. Initialize default_settings with hardcoded defaults - default_settings = OpenAILLMSettings(model="llama-3.3-70b-versatile") + default_settings = GroqLLMSettings(model="llama-3.3-70b-versatile") # 2. Apply direct init arg overrides (deprecated) if model is not None: - _warn_deprecated_param("model", OpenAILLMSettings, "model") + _warn_deprecated_param("model", GroqLLMSettings, "model") default_settings.model = model # 4. Apply settings delta (canonical API, always wins) diff --git a/src/pipecat/services/mistral/llm.py b/src/pipecat/services/mistral/llm.py index 57ab45d6f..c4deab4c3 100644 --- a/src/pipecat/services/mistral/llm.py +++ b/src/pipecat/services/mistral/llm.py @@ -6,6 +6,7 @@ """Mistral LLM service implementation using OpenAI-compatible interface.""" +from dataclasses import dataclass from typing import List, Optional, Sequence from loguru import logger @@ -18,6 +19,13 @@ from pipecat.services.openai.llm import OpenAILLMService from pipecat.services.settings import _warn_deprecated_param +@dataclass +class MistralLLMSettings(OpenAILLMSettings): + """Settings for Mistral LLM service.""" + + pass + + class MistralLLMService(OpenAILLMService): """A service for interacting with Mistral's API using the OpenAI-compatible interface. @@ -31,7 +39,7 @@ class MistralLLMService(OpenAILLMService): api_key: str, base_url: str = "https://api.mistral.ai/v1", model: Optional[str] = None, - settings: Optional[OpenAILLMSettings] = None, + settings: Optional[MistralLLMSettings] = None, **kwargs, ): """Initialize the Mistral LLM service. @@ -49,11 +57,11 @@ class MistralLLMService(OpenAILLMService): **kwargs: Additional keyword arguments passed to OpenAILLMService. """ # 1. Initialize default_settings with hardcoded defaults - default_settings = OpenAILLMSettings(model="mistral-small-latest") + default_settings = MistralLLMSettings(model="mistral-small-latest") # 2. Apply direct init arg overrides (deprecated) if model is not None: - _warn_deprecated_param("model", OpenAILLMSettings, "model") + _warn_deprecated_param("model", MistralLLMSettings, "model") default_settings.model = model # 4. Apply settings delta (canonical API, always wins) diff --git a/src/pipecat/services/nvidia/llm.py b/src/pipecat/services/nvidia/llm.py index 88245464e..4ebfac0d8 100644 --- a/src/pipecat/services/nvidia/llm.py +++ b/src/pipecat/services/nvidia/llm.py @@ -10,6 +10,7 @@ This module provides a service for interacting with NVIDIA's NIM (NVIDIA Inferen Microservice) API while maintaining compatibility with the OpenAI-style interface. """ +from dataclasses import dataclass from typing import Optional from pipecat.metrics.metrics import LLMTokenUsage @@ -20,6 +21,13 @@ from pipecat.services.openai.llm import OpenAILLMService from pipecat.services.settings import _warn_deprecated_param +@dataclass +class NvidiaLLMSettings(OpenAILLMSettings): + """Settings for NVIDIA LLM service.""" + + pass + + class NvidiaLLMService(OpenAILLMService): """A service for interacting with NVIDIA's NIM (NVIDIA Inference Microservice) API. @@ -34,7 +42,7 @@ class NvidiaLLMService(OpenAILLMService): api_key: str, base_url: str = "https://integrate.api.nvidia.com/v1", model: Optional[str] = None, - settings: Optional[OpenAILLMSettings] = None, + settings: Optional[NvidiaLLMSettings] = None, **kwargs, ): """Initialize the NvidiaLLMService. @@ -53,11 +61,11 @@ class NvidiaLLMService(OpenAILLMService): **kwargs: Additional keyword arguments passed to OpenAILLMService. """ # 1. Initialize default_settings with hardcoded defaults - default_settings = OpenAILLMSettings(model="nvidia/llama-3.1-nemotron-70b-instruct") + default_settings = NvidiaLLMSettings(model="nvidia/llama-3.1-nemotron-70b-instruct") # 2. Apply direct init arg overrides (deprecated) if model is not None: - _warn_deprecated_param("model", OpenAILLMSettings, "model") + _warn_deprecated_param("model", NvidiaLLMSettings, "model") default_settings.model = model # 4. Apply settings delta (canonical API, always wins) diff --git a/src/pipecat/services/nvidia/stt.py b/src/pipecat/services/nvidia/stt.py index 9b9b2bcf9..6823965a9 100644 --- a/src/pipecat/services/nvidia/stt.py +++ b/src/pipecat/services/nvidia/stt.py @@ -8,7 +8,7 @@ import asyncio from concurrent.futures import CancelledError as FuturesCancelledError -from dataclasses import dataclass +from dataclasses import dataclass, field from typing import Any, AsyncGenerator, List, Mapping, Optional from loguru import logger @@ -23,7 +23,7 @@ from pipecat.frames.frames import ( StartFrame, TranscriptionFrame, ) -from pipecat.services.settings import STTSettings, _warn_deprecated_param +from pipecat.services.settings import NOT_GIVEN, STTSettings, _NotGiven, _warn_deprecated_param from pipecat.services.stt_latency import NVIDIA_TTFS_P99 from pipecat.services.stt_service import SegmentedSTTService, STTService from pipecat.transcriptions.language import Language, resolve_language @@ -110,11 +110,11 @@ class NvidiaSegmentedSTTSettings(STTSettings): boosted_lm_score: Score boost for specified words. """ - profanity_filter: bool = False - automatic_punctuation: bool = True - verbatim_transcripts: bool = False - boosted_lm_words: Optional[List[str]] = None - boosted_lm_score: float = 4.0 + profanity_filter: bool | _NotGiven = field(default_factory=lambda: NOT_GIVEN) + automatic_punctuation: bool | _NotGiven = field(default_factory=lambda: NOT_GIVEN) + verbatim_transcripts: bool | _NotGiven = field(default_factory=lambda: NOT_GIVEN) + boosted_lm_words: List[str] | None | _NotGiven = field(default_factory=lambda: NOT_GIVEN) + boosted_lm_score: float | _NotGiven = field(default_factory=lambda: NOT_GIVEN) class NvidiaSTTService(STTService): diff --git a/src/pipecat/services/ollama/llm.py b/src/pipecat/services/ollama/llm.py index 477a80b5f..cd0c68099 100644 --- a/src/pipecat/services/ollama/llm.py +++ b/src/pipecat/services/ollama/llm.py @@ -6,6 +6,7 @@ """OLLama LLM service implementation for Pipecat AI framework.""" +from dataclasses import dataclass from typing import Optional from loguru import logger @@ -15,6 +16,13 @@ from pipecat.services.openai.llm import OpenAILLMService from pipecat.services.settings import _warn_deprecated_param +@dataclass +class OllamaLLMSettings(OpenAILLMSettings): + """Settings for Ollama LLM service.""" + + pass + + class OLLamaLLMService(OpenAILLMService): """OLLama LLM service that provides local language model capabilities. @@ -27,7 +35,7 @@ class OLLamaLLMService(OpenAILLMService): *, model: Optional[str] = None, base_url: str = "http://localhost:11434/v1", - settings: Optional[OpenAILLMSettings] = None, + settings: Optional[OllamaLLMSettings] = None, **kwargs, ): """Initialize OLLama LLM service. @@ -45,11 +53,11 @@ class OLLamaLLMService(OpenAILLMService): **kwargs: Additional keyword arguments passed to OpenAILLMService. """ # 1. Initialize default_settings with hardcoded defaults - default_settings = OpenAILLMSettings(model="llama2") + default_settings = OllamaLLMSettings(model="llama2") # 2. Apply direct init arg overrides (deprecated) if model is not None: - _warn_deprecated_param("model", OpenAILLMSettings, "model") + _warn_deprecated_param("model", OllamaLLMSettings, "model") default_settings.model = model # 4. Apply settings delta (canonical API, always wins) diff --git a/src/pipecat/services/openai/stt.py b/src/pipecat/services/openai/stt.py index fbd372523..0e1e4f594 100644 --- a/src/pipecat/services/openai/stt.py +++ b/src/pipecat/services/openai/stt.py @@ -16,7 +16,7 @@ Provides two STT services: import base64 import json -from dataclasses import dataclass +from dataclasses import dataclass, field from typing import Any, AsyncGenerator, Literal, Optional, Union from loguru import logger @@ -35,7 +35,7 @@ from pipecat.frames.frames import ( VADUserStoppedSpeakingFrame, ) from pipecat.processors.frame_processor import FrameDirection -from pipecat.services.settings import STTSettings, _NotGiven, _warn_deprecated_param +from pipecat.services.settings import NOT_GIVEN, STTSettings, _NotGiven, _warn_deprecated_param from pipecat.services.stt_latency import OPENAI_REALTIME_TTFS_P99, OPENAI_TTFS_P99 from pipecat.services.stt_service import WebsocketSTTService from pipecat.services.whisper.base_stt import ( @@ -188,7 +188,7 @@ class OpenAIRealtimeSTTSettings(STTSettings): prompt: Optional prompt text to guide transcription style. """ - prompt: str | None | _NotGiven = None + prompt: str | None | _NotGiven = field(default_factory=lambda: NOT_GIVEN) class OpenAIRealtimeSTTService(WebsocketSTTService): diff --git a/src/pipecat/services/openai_realtime_beta/azure.py b/src/pipecat/services/openai_realtime_beta/azure.py index 6370ac0f4..fb85b1e79 100644 --- a/src/pipecat/services/openai_realtime_beta/azure.py +++ b/src/pipecat/services/openai_realtime_beta/azure.py @@ -7,10 +7,11 @@ """Azure OpenAI Realtime Beta LLM service implementation.""" import warnings +from dataclasses import dataclass from loguru import logger -from .openai import OpenAIRealtimeBetaLLMService +from .openai import OpenAIRealtimeBetaLLMService, OpenAIRealtimeBetaLLMSettings try: from websockets.asyncio.client import connect as websocket_connect @@ -22,6 +23,13 @@ except ModuleNotFoundError as e: raise Exception(f"Missing module: {e}") +@dataclass +class AzureRealtimeBetaLLMSettings(OpenAIRealtimeBetaLLMSettings): + """Settings for Azure Realtime Beta LLM service.""" + + pass + + class AzureRealtimeBetaLLMService(OpenAIRealtimeBetaLLMService): """Azure OpenAI Realtime Beta LLM service with Azure-specific authentication. diff --git a/src/pipecat/services/openpipe/llm.py b/src/pipecat/services/openpipe/llm.py index 431de832d..b2e953e64 100644 --- a/src/pipecat/services/openpipe/llm.py +++ b/src/pipecat/services/openpipe/llm.py @@ -10,6 +10,7 @@ This module provides an OpenPipe-specific implementation of the OpenAI LLM servi enabling integration with OpenPipe's fine-tuning and monitoring capabilities. """ +from dataclasses import dataclass from typing import Dict, Optional from loguru import logger @@ -27,6 +28,13 @@ except ModuleNotFoundError as e: raise Exception(f"Missing module: {e}") +@dataclass +class OpenPipeLLMSettings(OpenAILLMSettings): + """Settings for OpenPipe LLM service.""" + + pass + + class OpenPipeLLMService(OpenAILLMService): """OpenPipe-powered Large Language Model service. @@ -44,7 +52,7 @@ class OpenPipeLLMService(OpenAILLMService): openpipe_api_key: Optional[str] = None, openpipe_base_url: str = "https://app.openpipe.ai/api/v1", tags: Optional[Dict[str, str]] = None, - settings: Optional[OpenAILLMSettings] = None, + settings: Optional[OpenPipeLLMSettings] = None, **kwargs, ): """Initialize OpenPipe LLM service. @@ -65,11 +73,11 @@ class OpenPipeLLMService(OpenAILLMService): **kwargs: Additional arguments passed to parent OpenAILLMService. """ # 1. Initialize default_settings with hardcoded defaults - default_settings = OpenAILLMSettings(model="gpt-4.1") + default_settings = OpenPipeLLMSettings(model="gpt-4.1") # 2. Apply direct init arg overrides (deprecated) if model is not None: - _warn_deprecated_param("model", OpenAILLMSettings, "model") + _warn_deprecated_param("model", OpenPipeLLMSettings, "model") default_settings.model = model # 4. Apply settings delta (canonical API, always wins) diff --git a/src/pipecat/services/openrouter/llm.py b/src/pipecat/services/openrouter/llm.py index 8c42069d8..fa2f170ee 100644 --- a/src/pipecat/services/openrouter/llm.py +++ b/src/pipecat/services/openrouter/llm.py @@ -10,6 +10,7 @@ This module provides an OpenAI-compatible interface for interacting with OpenRou extending the base OpenAI LLM service functionality. """ +from dataclasses import dataclass from typing import Any, Dict, Optional from loguru import logger @@ -19,6 +20,13 @@ from pipecat.services.openai.llm import OpenAILLMService from pipecat.services.settings import _warn_deprecated_param +@dataclass +class OpenRouterLLMSettings(OpenAILLMSettings): + """Settings for OpenRouter LLM service.""" + + pass + + class OpenRouterLLMService(OpenAILLMService): """A service for interacting with OpenRouter's API using the OpenAI-compatible interface. @@ -32,7 +40,7 @@ class OpenRouterLLMService(OpenAILLMService): api_key: Optional[str] = None, model: Optional[str] = None, base_url: str = "https://openrouter.ai/api/v1", - settings: Optional[OpenAILLMSettings] = None, + settings: Optional[OpenRouterLLMSettings] = None, **kwargs, ): """Initialize the OpenRouter LLM service. @@ -51,11 +59,11 @@ class OpenRouterLLMService(OpenAILLMService): **kwargs: Additional keyword arguments passed to OpenAILLMService. """ # 1. Initialize default_settings with hardcoded defaults - default_settings = OpenAILLMSettings(model="openai/gpt-4o-2024-11-20") + default_settings = OpenRouterLLMSettings(model="openai/gpt-4o-2024-11-20") # 2. Apply direct init arg overrides (deprecated) if model is not None: - _warn_deprecated_param("model", OpenAILLMSettings, "model") + _warn_deprecated_param("model", OpenRouterLLMSettings, "model") default_settings.model = model # 4. Apply settings delta (canonical API, always wins) diff --git a/src/pipecat/services/perplexity/llm.py b/src/pipecat/services/perplexity/llm.py index 8195dd50e..d90aea6a4 100644 --- a/src/pipecat/services/perplexity/llm.py +++ b/src/pipecat/services/perplexity/llm.py @@ -11,6 +11,7 @@ an OpenAI-compatible interface. It handles Perplexity's unique token usage reporting patterns while maintaining compatibility with the Pipecat framework. """ +from dataclasses import dataclass from typing import Optional from pipecat.adapters.services.open_ai_adapter import OpenAILLMInvocationParams @@ -22,6 +23,13 @@ from pipecat.services.openai.llm import OpenAILLMService from pipecat.services.settings import _warn_deprecated_param +@dataclass +class PerplexityLLMSettings(OpenAILLMSettings): + """Settings for Perplexity LLM service.""" + + pass + + class PerplexityLLMService(OpenAILLMService): """A service for interacting with Perplexity's API. @@ -36,7 +44,7 @@ class PerplexityLLMService(OpenAILLMService): api_key: str, base_url: str = "https://api.perplexity.ai", model: Optional[str] = None, - settings: Optional[OpenAILLMSettings] = None, + settings: Optional[PerplexityLLMSettings] = None, **kwargs, ): """Initialize the Perplexity LLM service. @@ -54,11 +62,11 @@ class PerplexityLLMService(OpenAILLMService): **kwargs: Additional keyword arguments passed to OpenAILLMService. """ # 1. Initialize default_settings with hardcoded defaults - default_settings = OpenAILLMSettings(model="sonar") + default_settings = PerplexityLLMSettings(model="sonar") # 2. Apply direct init arg overrides (deprecated) if model is not None: - _warn_deprecated_param("model", OpenAILLMSettings, "model") + _warn_deprecated_param("model", PerplexityLLMSettings, "model") default_settings.model = model # 4. Apply settings delta (canonical API, always wins) diff --git a/src/pipecat/services/qwen/llm.py b/src/pipecat/services/qwen/llm.py index b983e00cd..6d9abeefe 100644 --- a/src/pipecat/services/qwen/llm.py +++ b/src/pipecat/services/qwen/llm.py @@ -6,6 +6,7 @@ """Qwen LLM service implementation using OpenAI-compatible interface.""" +from dataclasses import dataclass from typing import Optional from loguru import logger @@ -15,6 +16,13 @@ from pipecat.services.openai.llm import OpenAILLMService from pipecat.services.settings import _warn_deprecated_param +@dataclass +class QwenLLMSettings(OpenAILLMSettings): + """Settings for Qwen LLM service.""" + + pass + + class QwenLLMService(OpenAILLMService): """A service for interacting with Alibaba Cloud's Qwen LLM API using the OpenAI-compatible interface. @@ -28,7 +36,7 @@ class QwenLLMService(OpenAILLMService): api_key: str, base_url: str = "https://dashscope-intl.aliyuncs.com/compatible-mode/v1", model: Optional[str] = None, - settings: Optional[OpenAILLMSettings] = None, + settings: Optional[QwenLLMSettings] = None, **kwargs, ): """Initialize the Qwen LLM service. @@ -46,11 +54,11 @@ class QwenLLMService(OpenAILLMService): **kwargs: Additional keyword arguments passed to OpenAILLMService. """ # 1. Initialize default_settings with hardcoded defaults - default_settings = OpenAILLMSettings(model="qwen-plus") + default_settings = QwenLLMSettings(model="qwen-plus") # 2. Apply direct init arg overrides (deprecated) if model is not None: - _warn_deprecated_param("model", OpenAILLMSettings, "model") + _warn_deprecated_param("model", QwenLLMSettings, "model") default_settings.model = model # 4. Apply settings delta (canonical API, always wins) diff --git a/src/pipecat/services/sambanova/llm.py b/src/pipecat/services/sambanova/llm.py index 2468dad13..f87b432cc 100644 --- a/src/pipecat/services/sambanova/llm.py +++ b/src/pipecat/services/sambanova/llm.py @@ -7,6 +7,7 @@ """SambaNova LLM service implementation using OpenAI-compatible interface.""" import json +from dataclasses import dataclass from typing import Any, Dict, Optional from loguru import logger @@ -27,6 +28,13 @@ from pipecat.services.settings import _warn_deprecated_param from pipecat.utils.tracing.service_decorators import traced_llm +@dataclass +class SambaNovaLLMSettings(OpenAILLMSettings): + """Settings for SambaNova LLM service.""" + + pass + + class SambaNovaLLMService(OpenAILLMService): # type: ignore """A service for interacting with SambaNova using the OpenAI-compatible interface. @@ -40,7 +48,7 @@ class SambaNovaLLMService(OpenAILLMService): # type: ignore api_key: str, model: Optional[str] = None, base_url: str = "https://api.sambanova.ai/v1", - settings: Optional[OpenAILLMSettings] = None, + settings: Optional[SambaNovaLLMSettings] = None, **kwargs: Dict[Any, Any], ) -> None: """Initialize SambaNova LLM service. @@ -58,11 +66,11 @@ class SambaNovaLLMService(OpenAILLMService): # type: ignore **kwargs: Additional keyword arguments passed to OpenAILLMService. """ # 1. Initialize default_settings with hardcoded defaults - default_settings = OpenAILLMSettings(model="Llama-4-Maverick-17B-128E-Instruct") + default_settings = SambaNovaLLMSettings(model="Llama-4-Maverick-17B-128E-Instruct") # 2. Apply direct init arg overrides (deprecated) if model is not None: - _warn_deprecated_param("model", OpenAILLMSettings, "model") + _warn_deprecated_param("model", SambaNovaLLMSettings, "model") default_settings.model = model # 4. Apply settings delta (canonical API, always wins) diff --git a/src/pipecat/services/together/llm.py b/src/pipecat/services/together/llm.py index 9ec8e9fc2..23e38f752 100644 --- a/src/pipecat/services/together/llm.py +++ b/src/pipecat/services/together/llm.py @@ -6,6 +6,7 @@ """Together.ai LLM service implementation using OpenAI-compatible interface.""" +from dataclasses import dataclass from typing import Optional from loguru import logger @@ -15,6 +16,13 @@ from pipecat.services.openai.llm import OpenAILLMService from pipecat.services.settings import _warn_deprecated_param +@dataclass +class TogetherLLMSettings(OpenAILLMSettings): + """Settings for Together LLM service.""" + + pass + + class TogetherLLMService(OpenAILLMService): """A service for interacting with Together.ai's API using the OpenAI-compatible interface. @@ -28,7 +36,7 @@ class TogetherLLMService(OpenAILLMService): api_key: str, base_url: str = "https://api.together.xyz/v1", model: Optional[str] = None, - settings: Optional[OpenAILLMSettings] = None, + settings: Optional[TogetherLLMSettings] = None, **kwargs, ): """Initialize Together.ai LLM service. @@ -46,11 +54,11 @@ class TogetherLLMService(OpenAILLMService): **kwargs: Additional keyword arguments passed to OpenAILLMService. """ # 1. Initialize default_settings with hardcoded defaults - default_settings = OpenAILLMSettings(model="meta-llama/Meta-Llama-3.1-8B-Instruct-Turbo") + default_settings = TogetherLLMSettings(model="meta-llama/Meta-Llama-3.1-8B-Instruct-Turbo") # 2. Apply direct init arg overrides (deprecated) if model is not None: - _warn_deprecated_param("model", OpenAILLMSettings, "model") + _warn_deprecated_param("model", TogetherLLMSettings, "model") default_settings.model = model # 4. Apply settings delta (canonical API, always wins) diff --git a/src/pipecat/services/whisper/base_stt.py b/src/pipecat/services/whisper/base_stt.py index f89d7f5d0..13de0f251 100644 --- a/src/pipecat/services/whisper/base_stt.py +++ b/src/pipecat/services/whisper/base_stt.py @@ -10,7 +10,7 @@ This module provides common functionality for services implementing the Whisper interface, including language mapping, metrics generation, and error handling. """ -from dataclasses import dataclass +from dataclasses import dataclass, field from typing import AsyncGenerator, Optional from loguru import logger @@ -18,7 +18,7 @@ from openai import AsyncOpenAI from openai.types.audio import Transcription from pipecat.frames.frames import ErrorFrame, Frame, TranscriptionFrame -from pipecat.services.settings import STTSettings, _NotGiven, _warn_deprecated_param +from pipecat.services.settings import NOT_GIVEN, STTSettings, _NotGiven, _warn_deprecated_param from pipecat.services.stt_latency import WHISPER_TTFS_P99 from pipecat.services.stt_service import SegmentedSTTService from pipecat.transcriptions.language import Language, resolve_language @@ -36,8 +36,8 @@ class BaseWhisperSTTSettings(STTSettings): temperature: Sampling temperature between 0 and 1. """ - prompt: str | None | _NotGiven = None - temperature: float | None | _NotGiven = None + prompt: str | None | _NotGiven = field(default_factory=lambda: NOT_GIVEN) + temperature: float | None | _NotGiven = field(default_factory=lambda: NOT_GIVEN) def language_to_whisper_language(language: Language) -> Optional[str]: @@ -183,6 +183,8 @@ class BaseWhisperSTTService(SegmentedSTTService): default_settings = BaseWhisperSTTSettings( model=None, language=None, + prompt=None, + temperature=None, ) # --- 2. Deprecated direct-arg overrides --- diff --git a/tests/test_service_init.py b/tests/test_service_init.py new file mode 100644 index 000000000..73cb6a337 --- /dev/null +++ b/tests/test_service_init.py @@ -0,0 +1,181 @@ +# +# Copyright (c) 2024-2026, Daily +# +# SPDX-License-Identifier: BSD 2-Clause License +# + +"""Tests for service settings and initialization patterns. + +Settings objects operate in two modes: + +- **Store mode** (``self._settings``): the live state inside a service. + Every field must hold a real value (``None`` is fine, ``NOT_GIVEN`` is not). +- **Delta mode** (``FooSettings()`` with no args): a sparse update. + Every field must default to ``NOT_GIVEN`` so ``apply_update()`` skips + untouched fields and doesn't accidentally overwrite the store. + +These tests verify both sides of that contract automatically: + +1. **Delta defaults** — Instantiate every ``ServiceSettings`` subclass with + no arguments and assert that every field is ``NOT_GIVEN``. Catches the + bug where a field defaults to ``None`` instead of ``NOT_GIVEN``, which + would cause partial deltas to silently overwrite unrelated store values. + +2. **Store completeness** — Instantiate every concrete service with dummy + args and assert that ``_settings`` contains no ``NOT_GIVEN`` values. + This is the same check that ``validate_complete()`` runs in ``start()``, + but caught here at unit-test time without needing a running pipeline. + Catches services that forget to initialize a field in ``default_settings``. + +All Settings and Service classes are auto-discovered via ``pkgutil``; +new services are covered automatically with no per-service maintenance. +""" + +import importlib +import inspect +import pkgutil +import warnings +from dataclasses import fields + +import pytest + +import pipecat.services +from pipecat.services.ai_service import AIService +from pipecat.services.settings import ServiceSettings, is_given + +# Modules that define abstract base service classes (not concrete services). +_BASE_MODULES = frozenset( + { + "pipecat.services.ai_service", + "pipecat.services.llm_service", + "pipecat.services.stt_service", + "pipecat.services.tts_service", + "pipecat.services.image_gen_service", + "pipecat.services.vision_service", + } +) + + +# --------------------------------------------------------------------------- +# Auto-discovery +# --------------------------------------------------------------------------- + + +def _all_subclasses(cls): + result = set() + for sub in cls.__subclasses__(): + result.add(sub) + result.update(_all_subclasses(sub)) + return result + + +def _import_all_service_modules(): + """Import every module under pipecat.services (skipping missing deps).""" + package = pipecat.services + for _importer, modname, _ispkg in pkgutil.walk_packages( + package.__path__, prefix=package.__name__ + "." + ): + try: + importlib.import_module(modname) + except Exception: + continue + + +_import_all_service_modules() + +ALL_SETTINGS_CLASSES = sorted(_all_subclasses(ServiceSettings), key=lambda c: c.__qualname__) +assert ALL_SETTINGS_CLASSES, "No settings classes discovered" + + +# --------------------------------------------------------------------------- +# Service instantiation helpers +# --------------------------------------------------------------------------- + + +def _try_instantiate(cls): + """Try to instantiate a service with dummy values for required args. + + Inspects the __init__ signature and passes "test" for every required + keyword-only parameter. Services that need non-string required args + or fail for other reasons will raise and be skipped by the test. + """ + sig = inspect.signature(cls.__init__) + kwargs = {} + for name, param in sig.parameters.items(): + if name == "self": + continue + if param.kind in (param.VAR_POSITIONAL, param.VAR_KEYWORD): + continue + if param.default is not param.empty: + continue + # Required parameter — pass a dummy string + kwargs[name] = "test" + return cls(**kwargs) + + +def _discover_service_classes(): + """Return concrete service classes that can be instantiated with dummy args.""" + result = [] + for cls in sorted(_all_subclasses(AIService), key=lambda c: c.__qualname__): + # Skip abstract base classes defined in framework modules. + if cls.__module__ in _BASE_MODULES: + continue + try: + svc = _try_instantiate(cls) + except Exception: + continue + if hasattr(svc, "_settings"): + result.append(cls) + return result + + +ALL_SERVICE_CLASSES = _discover_service_classes() +assert ALL_SERVICE_CLASSES, "No service classes could be instantiated" + + +# --------------------------------------------------------------------------- +# 1. Settings defaults: delta-mode safety +# --------------------------------------------------------------------------- + + +@pytest.mark.parametrize("settings_cls", ALL_SETTINGS_CLASSES, ids=lambda c: c.__qualname__) +def test_delta_defaults_are_not_given(settings_cls): + """Every field must default to NOT_GIVEN so empty deltas are no-ops. + + A field that defaults to None instead of NOT_GIVEN will cause + apply_update() to overwrite the corresponding store value whenever + a partial delta is applied. + """ + instance = settings_cls() + for f in fields(instance): + if f.name == "extra": + continue + val = getattr(instance, f.name) + assert not is_given(val), ( + f"{settings_cls.__qualname__}.{f.name} defaults to {val!r}, expected NOT_GIVEN" + ) + + +# --------------------------------------------------------------------------- +# 2. Service construction: store-mode completeness +# --------------------------------------------------------------------------- + + +@pytest.mark.parametrize("service_cls", ALL_SERVICE_CLASSES, ids=lambda c: c.__qualname__) +def test_service_settings_complete(service_cls): + """After construction, _settings must have no NOT_GIVEN values. + + This is what validate_complete() checks in start(). Catching it + here means we don't need a running pipeline to find missing defaults. + """ + try: + svc = _try_instantiate(service_cls) + except Exception: + pytest.skip("Cannot re-instantiate (environment issue)") + for f in fields(svc._settings): + if f.name == "extra": + continue + val = getattr(svc._settings, f.name) + assert is_given(val), ( + f"{service_cls.__qualname__}._settings.{f.name} is NOT_GIVEN after construction" + ) From 939d753c2b350b894fc760ae8f1afa7ade91e98b Mon Sep 17 00:00:00 2001 From: Mark Backman Date: Wed, 4 Mar 2026 21:12:44 -0500 Subject: [PATCH 0812/1060] Update LLMs --- src/pipecat/services/aws/llm.py | 22 ++++-- src/pipecat/services/aws/nova_sonic/llm.py | 14 ++-- src/pipecat/services/azure/realtime/llm.py | 2 + src/pipecat/services/cerebras/llm.py | 2 + src/pipecat/services/deepseek/llm.py | 2 + src/pipecat/services/fireworks/llm.py | 2 + .../services/google/gemini_live/llm.py | 12 ++- .../services/google/gemini_live/llm_vertex.py | 10 ++- src/pipecat/services/google/llm_openai.py | 2 + src/pipecat/services/google/llm_vertex.py | 2 + src/pipecat/services/grok/llm.py | 2 + src/pipecat/services/grok/realtime/llm.py | 73 ++++++------------- src/pipecat/services/groq/llm.py | 2 + src/pipecat/services/mistral/llm.py | 2 + src/pipecat/services/nvidia/llm.py | 2 + src/pipecat/services/ollama/llm.py | 2 + src/pipecat/services/openai/base_llm.py | 9 +-- src/pipecat/services/openai/llm.py | 10 ++- src/pipecat/services/openai/realtime/llm.py | 60 +++++---------- .../services/openai_realtime_beta/azure.py | 2 + .../services/openai_realtime_beta/openai.py | 49 ++++--------- src/pipecat/services/openpipe/llm.py | 2 + src/pipecat/services/openrouter/llm.py | 2 + src/pipecat/services/perplexity/llm.py | 2 + src/pipecat/services/qwen/llm.py | 2 + src/pipecat/services/sambanova/llm.py | 2 + src/pipecat/services/together/llm.py | 2 + 27 files changed, 144 insertions(+), 151 deletions(-) diff --git a/src/pipecat/services/aws/llm.py b/src/pipecat/services/aws/llm.py index d688b6114..3b0392a0e 100644 --- a/src/pipecat/services/aws/llm.py +++ b/src/pipecat/services/aws/llm.py @@ -75,10 +75,12 @@ class AWSBedrockLLMSettings(LLMSettings): """Settings for AWS Bedrock LLM services. Parameters: + stop_sequences: List of strings that stop generation. latency: Performance mode - "standard" or "optimized". additional_model_request_fields: Additional model-specific parameters. """ + stop_sequences: List[str] | None | _NotGiven = field(default_factory=lambda: NOT_GIVEN) latency: str | _NotGiven = field(default_factory=lambda: NOT_GIVEN) additional_model_request_fields: Dict[str, Any] | _NotGiven = field( default_factory=lambda: NOT_GIVEN @@ -810,6 +812,10 @@ class AWSBedrockLLMService(LLMService): deprecated parameters and *settings* are provided, *settings* values take precedence. stop_sequences: List of strings that stop generation. + + .. deprecated:: 0.0.105 + Use ``settings=AWSBedrockLLMSettings(stop_sequences=...)`` instead. + client_config: Custom boto3 client configuration. retry_timeout_secs: Request timeout in seconds for retry logic. retry_on_timeout: Whether to retry the request once if it times out. @@ -828,6 +834,7 @@ class AWSBedrockLLMService(LLMService): seed=None, filter_incomplete_user_turns=False, user_turn_completion_config=None, + stop_sequences=None, latency=None, additional_model_request_fields={}, ) @@ -836,6 +843,9 @@ class AWSBedrockLLMService(LLMService): if model is not None: _warn_deprecated_param("model", AWSBedrockLLMSettings, "model") default_settings.model = model + if stop_sequences is not None: + _warn_deprecated_param("stop_sequences", AWSBedrockLLMSettings, "stop_sequences") + default_settings.stop_sequences = stop_sequences # 3. Apply params overrides — only if settings not provided if params is not None: @@ -844,6 +854,8 @@ class AWSBedrockLLMService(LLMService): default_settings.max_tokens = params.max_tokens default_settings.temperature = params.temperature default_settings.top_p = params.top_p + if params.stop_sequences: + default_settings.stop_sequences = params.stop_sequences default_settings.latency = params.latency if isinstance(params.additional_model_request_fields, dict): default_settings.additional_model_request_fields = ( @@ -856,14 +868,6 @@ class AWSBedrockLLMService(LLMService): super().__init__(settings=default_settings, **kwargs) - # Handle stop_sequences (not a settings field) - if stop_sequences is not None: - self._stop_sequences = stop_sequences - elif params is not None: - self._stop_sequences = params.stop_sequences or [] - else: - self._stop_sequences = [] - # Initialize the AWS Bedrock client if not client_config: client_config = Config( @@ -915,6 +919,8 @@ class AWSBedrockLLMService(LLMService): inference_config["temperature"] = self._settings.temperature if self._settings.top_p is not None: inference_config["topP"] = self._settings.top_p + if self._settings.stop_sequences: + inference_config["stopSequences"] = self._settings.stop_sequences return inference_config async def run_inference( diff --git a/src/pipecat/services/aws/nova_sonic/llm.py b/src/pipecat/services/aws/nova_sonic/llm.py index 7fec1c73c..9103ebdfd 100644 --- a/src/pipecat/services/aws/nova_sonic/llm.py +++ b/src/pipecat/services/aws/nova_sonic/llm.py @@ -191,12 +191,12 @@ class AWSNovaSonicLLMSettings(LLMSettings): """Settings for AWS Nova Sonic LLM service. Parameters: - voice_id: Voice for speech synthesis. + voice: Voice identifier for speech synthesis. endpointing_sensitivity: Controls how quickly Nova Sonic decides the user has stopped speaking. Can be "LOW", "MEDIUM", or "HIGH". """ - voice_id: str | _NotGiven = field(default_factory=lambda: NOT_GIVEN) + voice: str | _NotGiven = field(default_factory=lambda: NOT_GIVEN) endpointing_sensitivity: str | None | _NotGiven = field(default_factory=lambda: NOT_GIVEN) @@ -250,7 +250,7 @@ class AWSNovaSonicLLMService(LLMService): - Nova Sonic (the older model): see https://docs.aws.amazon.com/nova/latest/userguide/available-voices.html. .. deprecated:: - Use ``settings=AWSNovaSonicLLMSettings(voice_id=...)`` instead. + Use ``settings=AWSNovaSonicLLMSettings(voice=...)`` instead. params: Model parameters for audio configuration and inference. @@ -273,7 +273,7 @@ class AWSNovaSonicLLMService(LLMService): # 1. Initialize default_settings with hardcoded defaults default_settings = AWSNovaSonicLLMSettings( model="amazon.nova-2-sonic-v1:0", - voice_id="matthew", + voice="matthew", temperature=0.7, max_tokens=1024, top_p=0.9, @@ -291,8 +291,8 @@ class AWSNovaSonicLLMService(LLMService): _warn_deprecated_param("model", AWSNovaSonicLLMSettings, "model") default_settings.model = model if voice_id != "matthew": - _warn_deprecated_param("voice_id", AWSNovaSonicLLMSettings, "voice_id") - default_settings.voice_id = voice_id + _warn_deprecated_param("voice_id", AWSNovaSonicLLMSettings, "voice") + default_settings.voice = voice_id # 3. Apply params overrides — only if settings not provided if params is not None: @@ -811,7 +811,7 @@ class AWSNovaSonicLLMService(LLMService): "sampleRateHertz": {self._output_sample_rate}, "sampleSizeBits": {self._output_sample_size}, "channelCount": {self._output_channel_count}, - "voiceId": "{self._settings.voice_id}", + "voiceId": "{self._settings.voice}", "encoding": "base64", "audioType": "SPEECH" }}{tools_config} diff --git a/src/pipecat/services/azure/realtime/llm.py b/src/pipecat/services/azure/realtime/llm.py index fa645d8c1..0de2217d8 100644 --- a/src/pipecat/services/azure/realtime/llm.py +++ b/src/pipecat/services/azure/realtime/llm.py @@ -35,6 +35,8 @@ class AzureRealtimeLLMService(OpenAIRealtimeLLMService): real-time audio and text communication capabilities as the base OpenAI service. """ + _settings: AzureRealtimeLLMSettings + def __init__( self, *, diff --git a/src/pipecat/services/cerebras/llm.py b/src/pipecat/services/cerebras/llm.py index 40862f252..d98a2d7a4 100644 --- a/src/pipecat/services/cerebras/llm.py +++ b/src/pipecat/services/cerebras/llm.py @@ -31,6 +31,8 @@ class CerebrasLLMService(OpenAILLMService): maintaining full compatibility with OpenAI's interface and functionality. """ + _settings: CerebrasLLMSettings + def __init__( self, *, diff --git a/src/pipecat/services/deepseek/llm.py b/src/pipecat/services/deepseek/llm.py index d778639ef..684e971ca 100644 --- a/src/pipecat/services/deepseek/llm.py +++ b/src/pipecat/services/deepseek/llm.py @@ -31,6 +31,8 @@ class DeepSeekLLMService(OpenAILLMService): maintaining full compatibility with OpenAI's interface and functionality. """ + _settings: DeepSeekLLMSettings + def __init__( self, *, diff --git a/src/pipecat/services/fireworks/llm.py b/src/pipecat/services/fireworks/llm.py index 7ba3f9eac..86665cc48 100644 --- a/src/pipecat/services/fireworks/llm.py +++ b/src/pipecat/services/fireworks/llm.py @@ -31,6 +31,8 @@ class FireworksLLMService(OpenAILLMService): maintaining full compatibility with OpenAI's interface and functionality. """ + _settings: FireworksLLMSettings + def __init__( self, *, diff --git a/src/pipecat/services/google/gemini_live/llm.py b/src/pipecat/services/google/gemini_live/llm.py index 6e7a8f8a1..146a0fcc4 100644 --- a/src/pipecat/services/google/gemini_live/llm.py +++ b/src/pipecat/services/google/gemini_live/llm.py @@ -610,6 +610,7 @@ class GeminiLiveLLMSettings(LLMSettings): """Settings for Gemini Live LLM services. Parameters: + voice: TTS voice identifier (e.g. ``"Charon"``). modalities: Response modalities. language: Language for generation. media_resolution: Media resolution setting. @@ -620,6 +621,7 @@ class GeminiLiveLLMSettings(LLMSettings): proactivity: Proactivity configuration. """ + voice: str | _NotGiven = field(default_factory=lambda: NOT_GIVEN) modalities: GeminiModalities | _NotGiven = field(default_factory=lambda: NOT_GIVEN) language: Language | str | _NotGiven = field(default_factory=lambda: NOT_GIVEN) media_resolution: GeminiMediaResolution | _NotGiven = field(default_factory=lambda: NOT_GIVEN) @@ -680,6 +682,9 @@ class GeminiLiveLLMService(LLMService): Use ``settings=GeminiLiveLLMSettings(model=...)`` instead. voice_id: TTS voice identifier. Defaults to "Charon". + + .. deprecated:: 0.0.105 + Use ``settings=GeminiLiveLLMSettings(voice=...)`` instead. start_audio_paused: Whether to start with audio input paused. Defaults to False. start_video_paused: Whether to start with video input paused. Defaults to False. system_instruction: System prompt for the model. Defaults to None. @@ -712,6 +717,7 @@ class GeminiLiveLLMService(LLMService): # 1. Initialize default_settings with hardcoded defaults default_settings = GeminiLiveLLMSettings( model="models/gemini-2.5-flash-native-audio-preview-12-2025", + voice="Charon", frequency_penalty=None, max_tokens=4096, presence_penalty=None, @@ -736,6 +742,9 @@ class GeminiLiveLLMService(LLMService): if model is not None: _warn_deprecated_param("model", GeminiLiveLLMSettings, "model") default_settings.model = model + if voice_id != "Charon": + _warn_deprecated_param("voice_id", GeminiLiveLLMSettings, "voice") + default_settings.voice = voice_id # 3. Apply params overrides — only if settings not provided if params is not None: @@ -776,7 +785,6 @@ class GeminiLiveLLMService(LLMService): self._last_sent_time = 0 self._base_url = base_url - self._voice_id = voice_id self._language_code = params.language if params is not None else Language.EN_US self._system_instruction_from_init = system_instruction @@ -1184,7 +1192,7 @@ class GeminiLiveLLMService(LLMService): response_modalities=[Modality(self._settings.modalities.value)], speech_config=SpeechConfig( voice_config=VoiceConfig( - prebuilt_voice_config={"voice_name": self._voice_id} + prebuilt_voice_config={"voice_name": self._settings.voice} ), language_code=self._settings.language, ), diff --git a/src/pipecat/services/google/gemini_live/llm_vertex.py b/src/pipecat/services/google/gemini_live/llm_vertex.py index 43d3ab207..6264ea285 100644 --- a/src/pipecat/services/google/gemini_live/llm_vertex.py +++ b/src/pipecat/services/google/gemini_live/llm_vertex.py @@ -57,6 +57,8 @@ class GeminiLiveVertexLLMService(GeminiLiveLLMService): responses, and tool usage. """ + _settings: GeminiLiveVertexLLMSettings + def __init__( self, *, @@ -90,6 +92,9 @@ class GeminiLiveVertexLLMService(GeminiLiveLLMService): Use ``settings=GeminiLiveLLMSettings(model=...)`` instead. voice_id: TTS voice identifier. Defaults to "Charon". + + .. deprecated:: 0.0.105 + Use ``settings=GeminiLiveVertexLLMSettings(voice=...)`` instead. start_audio_paused: Whether to start with audio input paused. Defaults to False. start_video_paused: Whether to start with video input paused. Defaults to False. system_instruction: System prompt for the model. Defaults to None. @@ -132,6 +137,7 @@ class GeminiLiveVertexLLMService(GeminiLiveLLMService): # 1. Initialize default_settings with hardcoded defaults default_settings = GeminiLiveVertexLLMSettings( model="google/gemini-live-2.5-flash-native-audio", + voice="Charon", frequency_penalty=None, max_tokens=4096, presence_penalty=None, @@ -156,6 +162,9 @@ class GeminiLiveVertexLLMService(GeminiLiveLLMService): if model is not None: _warn_deprecated_param("model", GeminiLiveVertexLLMSettings, "model") default_settings.model = model + if voice_id != "Charon": + _warn_deprecated_param("voice_id", GeminiLiveVertexLLMSettings, "voice") + default_settings.voice = voice_id # 3. Apply params overrides — only if settings not provided if params is not None: @@ -193,7 +202,6 @@ class GeminiLiveVertexLLMService(GeminiLiveLLMService): # api_key is required by parent class, but actually not used with # Vertex api_key="dummy", - voice_id=voice_id, start_audio_paused=start_audio_paused, start_video_paused=start_video_paused, system_instruction=system_instruction, diff --git a/src/pipecat/services/google/llm_openai.py b/src/pipecat/services/google/llm_openai.py index 1d7ae6bc4..96e208fcb 100644 --- a/src/pipecat/services/google/llm_openai.py +++ b/src/pipecat/services/google/llm_openai.py @@ -58,6 +58,8 @@ class GoogleLLMOpenAIBetaService(OpenAILLMService): https://ai.google.dev/gemini-api/docs/openai """ + _settings: GoogleOpenAILLMSettings + def __init__( self, *, diff --git a/src/pipecat/services/google/llm_vertex.py b/src/pipecat/services/google/llm_vertex.py index e21341614..27f168042 100644 --- a/src/pipecat/services/google/llm_vertex.py +++ b/src/pipecat/services/google/llm_vertex.py @@ -59,6 +59,8 @@ class GoogleVertexLLMService(GoogleLLMService): https://cloud.google.com/vertex-ai/generative-ai/docs/model-reference/inference """ + _settings: GoogleVertexLLMSettings + class InputParams(GoogleLLMService.InputParams): """Input parameters specific to Vertex AI. diff --git a/src/pipecat/services/grok/llm.py b/src/pipecat/services/grok/llm.py index 7f9ac643b..59741cf9a 100644 --- a/src/pipecat/services/grok/llm.py +++ b/src/pipecat/services/grok/llm.py @@ -86,6 +86,8 @@ class GrokLLMService(OpenAILLMService): processing and reports final totals. """ + _settings: GrokLLMSettings + def __init__( self, *, diff --git a/src/pipecat/services/grok/realtime/llm.py b/src/pipecat/services/grok/realtime/llm.py index 2f2df1b45..638477b5e 100644 --- a/src/pipecat/services/grok/realtime/llm.py +++ b/src/pipecat/services/grok/realtime/llm.py @@ -13,7 +13,7 @@ https://docs.x.ai/docs/guides/voice/agent import base64 import json import time -from dataclasses import dataclass, field +from dataclasses import dataclass from typing import Any, Optional from loguru import logger @@ -56,7 +56,7 @@ from pipecat.processors.aggregators.llm_response_universal import ( from pipecat.processors.aggregators.openai_llm_context import OpenAILLMContext from pipecat.processors.frame_processor import FrameDirection from pipecat.services.llm_service import FunctionCallFromLLM, LLMService -from pipecat.services.settings import NOT_GIVEN, LLMSettings, _NotGiven, _warn_deprecated_param +from pipecat.services.settings import LLMSettings from pipecat.utils.time import time_now_iso8601 from . import events @@ -88,15 +88,9 @@ class CurrentAudioResponse: @dataclass class GrokRealtimeLLMSettings(LLMSettings): - """Settings for Grok Realtime LLM services. + """Settings for Grok Realtime LLM services.""" - Parameters: - session_properties: Grok Realtime session configuration. - """ - - session_properties: events.SessionProperties | _NotGiven = field( - default_factory=lambda: NOT_GIVEN - ) + pass class GrokRealtimeLLMService(LLMService): @@ -137,19 +131,13 @@ class GrokRealtimeLLMService(LLMService): base_url: WebSocket base URL for the realtime API. Defaults to "wss://api.x.ai/v1/realtime". session_properties: Configuration properties for the realtime session. - - .. deprecated:: - Use ``settings=GrokRealtimeLLMSettings(session_properties=...)`` - instead. - If None, uses default SessionProperties with voice "Ara". To set a different voice, configure it in session_properties: session_properties = events.SessionProperties(voice="Rex") Available voices: Ara, Rex, Sal, Eve, Leo. - settings: Grok Realtime LLM settings. If provided together with deprecated - top-level parameters, the ``settings`` values take precedence. + settings: Runtime-updatable settings for this service. start_audio_paused: Whether to start with audio input paused. Defaults to False. **kwargs: Additional arguments passed to parent LLMService. """ @@ -165,17 +153,9 @@ class GrokRealtimeLLMService(LLMService): seed=None, filter_incomplete_user_turns=False, user_turn_completion_config=None, - session_properties=events.SessionProperties(), ) - # 2. Apply direct init arg overrides (deprecated) - if session_properties is not None: - _warn_deprecated_param( - "session_properties", GrokRealtimeLLMSettings, "session_properties" - ) - default_settings.session_properties = session_properties - - # 4. Apply settings delta (canonical API, always wins) + # 2. Apply settings delta (canonical API, always wins) if settings is not None: default_settings.apply_update(settings) @@ -187,6 +167,7 @@ class GrokRealtimeLLMService(LLMService): self.api_key = api_key self.base_url = base_url + self._session_properties = session_properties or events.SessionProperties() self._audio_input_paused = start_audio_paused self._websocket = None @@ -235,13 +216,13 @@ class GrokRealtimeLLMService(LLMService): Configured sample rate or None if not manually configured. For PCMU/PCMA formats, returns 8000 Hz (G.711 standard). """ - if not self._settings.session_properties.audio: + if not self._session_properties.audio: return None audio_config = ( - self._settings.session_properties.audio.input + self._session_properties.audio.input if direction == "input" - else self._settings.session_properties.audio.output + else self._session_properties.audio.output ) if audio_config and audio_config.format: @@ -271,8 +252,8 @@ class GrokRealtimeLLMService(LLMService): def _is_turn_detection_enabled(self) -> bool: """Check if server-side VAD is enabled.""" - if self._settings.session_properties.turn_detection: - return self._settings.session_properties.turn_detection.type == "server_vad" + if self._session_properties.turn_detection: + return self._session_properties.turn_detection.type == "server_vad" return False async def _handle_interruption(self): @@ -339,7 +320,7 @@ class GrokRealtimeLLMService(LLMService): input_sample_rate: Sample rate for audio input (Hz). output_sample_rate: Sample rate for audio output (Hz). """ - props = self._settings.session_properties + props = self._session_properties if not props.audio: props.audio = events.AudioConfiguration() if not props.audio.input: @@ -395,7 +376,12 @@ class GrokRealtimeLLMService(LLMService): # directly. The frame.delta path falls through to super, which calls # _update_settings → our override handles the rest. if isinstance(frame, LLMUpdateSettingsFrame) and frame.delta is None: - self._settings.session_properties = events.SessionProperties(**frame.settings) + # Capture current audio config before replacing session properties. + input_rate = self._get_configured_sample_rate("input") + output_rate = self._get_configured_sample_rate("output") + self._session_properties = events.SessionProperties(**frame.settings) + if input_rate and output_rate: + self._ensure_audio_config(input_rate, output_rate) await self._send_session_update() await self.push_frame(frame, direction) return @@ -498,29 +484,14 @@ class GrokRealtimeLLMService(LLMService): await self.push_error(error_msg=f"Error sending client event: {e}", exception=e) async def _update_settings(self, delta): - """Apply a settings delta, sending a session update if needed.""" - # Capture current sample rates before the update replaces them. - input_rate = self._get_configured_sample_rate("input") - output_rate = self._get_configured_sample_rate("output") - + """Apply a settings delta.""" changed = await super()._update_settings(delta) - - if "session_properties" in changed: - if input_rate and output_rate: - self._ensure_audio_config(input_rate, output_rate) - else: - logger.warning( - "Attempting to apply session properties update without configured sample rates. " - "Audio configuration may be incomplete." - ) - await self._send_session_update() - - self._warn_unhandled_updated_settings(changed.keys() - {"session_properties"}) + self._warn_unhandled_updated_settings(changed.keys()) return changed async def _send_session_update(self): """Update session settings on the server.""" - settings = self._settings.session_properties + settings = self._session_properties adapter: GrokRealtimeLLMAdapter = self.get_llm_adapter() if self._context: diff --git a/src/pipecat/services/groq/llm.py b/src/pipecat/services/groq/llm.py index 5b81a4c7d..d7fc7f939 100644 --- a/src/pipecat/services/groq/llm.py +++ b/src/pipecat/services/groq/llm.py @@ -30,6 +30,8 @@ class GroqLLMService(OpenAILLMService): maintaining full compatibility with OpenAI's interface and functionality. """ + _settings: GroqLLMSettings + def __init__( self, *, diff --git a/src/pipecat/services/mistral/llm.py b/src/pipecat/services/mistral/llm.py index c4deab4c3..801c02f9e 100644 --- a/src/pipecat/services/mistral/llm.py +++ b/src/pipecat/services/mistral/llm.py @@ -33,6 +33,8 @@ class MistralLLMService(OpenAILLMService): maintaining full compatibility with OpenAI's interface and functionality. """ + _settings: MistralLLMSettings + def __init__( self, *, diff --git a/src/pipecat/services/nvidia/llm.py b/src/pipecat/services/nvidia/llm.py index 4ebfac0d8..48ccbaaf4 100644 --- a/src/pipecat/services/nvidia/llm.py +++ b/src/pipecat/services/nvidia/llm.py @@ -36,6 +36,8 @@ class NvidiaLLMService(OpenAILLMService): in token usage reporting between NIM (incremental) and OpenAI (final summary). """ + _settings: NvidiaLLMSettings + def __init__( self, *, diff --git a/src/pipecat/services/ollama/llm.py b/src/pipecat/services/ollama/llm.py index cd0c68099..d1c0eeebd 100644 --- a/src/pipecat/services/ollama/llm.py +++ b/src/pipecat/services/ollama/llm.py @@ -30,6 +30,8 @@ class OLLamaLLMService(OpenAILLMService): providing a compatible interface for running large language models locally. """ + _settings: OllamaLLMSettings + def __init__( self, *, diff --git a/src/pipecat/services/openai/base_llm.py b/src/pipecat/services/openai/base_llm.py index d44fbcf41..52fb451c3 100644 --- a/src/pipecat/services/openai/base_llm.py +++ b/src/pipecat/services/openai/base_llm.py @@ -53,11 +53,9 @@ class OpenAILLMSettings(LLMSettings): Parameters: max_completion_tokens: Maximum completion tokens to generate. - service_tier: Service tier to use (e.g., "auto", "flex", "priority"). """ max_completion_tokens: int | _NotGiven = field(default_factory=lambda: _NOT_GIVEN) - service_tier: str | _NotGiven = field(default_factory=lambda: _NOT_GIVEN) class BaseOpenAILLMService(LLMService): @@ -118,6 +116,7 @@ class BaseOpenAILLMService(LLMService): organization=None, project=None, default_headers: Optional[Mapping[str, str]] = None, + service_tier: Optional[str] = None, params: Optional[InputParams] = None, settings: Optional[OpenAILLMSettings] = None, retry_timeout_secs: Optional[float] = 5.0, @@ -138,6 +137,7 @@ class BaseOpenAILLMService(LLMService): organization: OpenAI organization ID. project: OpenAI project ID. default_headers: Additional HTTP headers to include in requests. + service_tier: Service tier to use (e.g., "auto", "flex", "priority"). params: Input parameters for model configuration and behavior. .. deprecated:: 0.0.105 @@ -161,7 +161,6 @@ class BaseOpenAILLMService(LLMService): top_k=None, max_tokens=NOT_GIVEN, max_completion_tokens=NOT_GIVEN, - service_tier=NOT_GIVEN, filter_incomplete_user_turns=False, user_turn_completion_config=None, extra={}, @@ -180,7 +179,6 @@ class BaseOpenAILLMService(LLMService): default_settings.top_p = params.top_p default_settings.max_tokens = params.max_tokens default_settings.max_completion_tokens = params.max_completion_tokens - default_settings.service_tier = params.service_tier if isinstance(params.extra, dict): default_settings.extra = params.extra @@ -192,6 +190,7 @@ class BaseOpenAILLMService(LLMService): settings=default_settings, **kwargs, ) + self._service_tier = service_tier self._retry_timeout_secs = retry_timeout_secs self._retry_on_timeout = retry_on_timeout self._system_instruction = system_instruction @@ -321,7 +320,7 @@ class BaseOpenAILLMService(LLMService): "top_p": self._settings.top_p, "max_tokens": self._settings.max_tokens, "max_completion_tokens": self._settings.max_completion_tokens, - "service_tier": self._settings.service_tier, + "service_tier": self._service_tier, } # Messages, tools, tool_choice diff --git a/src/pipecat/services/openai/llm.py b/src/pipecat/services/openai/llm.py index a81d3dc29..f2e3ad00a 100644 --- a/src/pipecat/services/openai/llm.py +++ b/src/pipecat/services/openai/llm.py @@ -76,6 +76,7 @@ class OpenAILLMService(BaseOpenAILLMService): self, *, model: Optional[str] = None, + service_tier: Optional[str] = None, params: Optional[BaseOpenAILLMService.InputParams] = None, settings: Optional[OpenAILLMSettings] = None, **kwargs, @@ -88,6 +89,7 @@ class OpenAILLMService(BaseOpenAILLMService): .. deprecated:: 0.0.105 Use ``settings=OpenAILLMSettings(model=...)`` instead. + service_tier: Service tier to use (e.g., "auto", "flex", "priority"). params: Input parameters for model configuration. .. deprecated:: 0.0.105 @@ -108,7 +110,6 @@ class OpenAILLMService(BaseOpenAILLMService): top_k=None, max_tokens=NOT_GIVEN, max_completion_tokens=NOT_GIVEN, - service_tier=NOT_GIVEN, filter_incomplete_user_turns=False, user_turn_completion_config=None, extra={}, @@ -119,6 +120,10 @@ class OpenAILLMService(BaseOpenAILLMService): _warn_deprecated_param("model", OpenAILLMSettings, "model") default_settings.model = model + # Handle service_tier from deprecated params + if params is not None and not settings and params.service_tier is not NOT_GIVEN: + service_tier = service_tier or params.service_tier + # 3. Apply params overrides — only if settings not provided if params is not None: _warn_deprecated_param("params", OpenAILLMSettings) @@ -130,7 +135,6 @@ class OpenAILLMService(BaseOpenAILLMService): default_settings.top_p = params.top_p default_settings.max_tokens = params.max_tokens default_settings.max_completion_tokens = params.max_completion_tokens - default_settings.service_tier = params.service_tier if isinstance(params.extra, dict): default_settings.extra = params.extra @@ -138,7 +142,7 @@ class OpenAILLMService(BaseOpenAILLMService): if settings is not None: default_settings.apply_update(settings) - super().__init__(settings=default_settings, **kwargs) + super().__init__(service_tier=service_tier, settings=default_settings, **kwargs) def create_context_aggregator( self, diff --git a/src/pipecat/services/openai/realtime/llm.py b/src/pipecat/services/openai/realtime/llm.py index 1230ed2db..761d7244b 100644 --- a/src/pipecat/services/openai/realtime/llm.py +++ b/src/pipecat/services/openai/realtime/llm.py @@ -10,7 +10,7 @@ import base64 import io import json import time -from dataclasses import dataclass, field +from dataclasses import dataclass from typing import Any, Optional from loguru import logger @@ -59,7 +59,7 @@ from pipecat.processors.aggregators.openai_llm_context import ( ) from pipecat.processors.frame_processor import FrameDirection from pipecat.services.llm_service import FunctionCallFromLLM, LLMService -from pipecat.services.settings import NOT_GIVEN, LLMSettings, _NotGiven, _warn_deprecated_param +from pipecat.services.settings import LLMSettings, _warn_deprecated_param from pipecat.transcriptions.language import Language from pipecat.utils.time import time_now_iso8601 from pipecat.utils.tracing.service_decorators import traced_openai_realtime, traced_stt @@ -93,15 +93,9 @@ class CurrentAudioResponse: @dataclass class OpenAIRealtimeLLMSettings(LLMSettings): - """Settings for OpenAI Realtime LLM services. + """Settings for OpenAI Realtime LLM services.""" - Parameters: - session_properties: OpenAI Realtime session configuration. - """ - - session_properties: events.SessionProperties | _NotGiven = field( - default_factory=lambda: NOT_GIVEN - ) + pass class OpenAIRealtimeLLMService(LLMService): @@ -145,15 +139,8 @@ class OpenAIRealtimeLLMService(LLMService): base_url: WebSocket base URL for the realtime API. Defaults to "wss://api.openai.com/v1/realtime". session_properties: Configuration properties for the realtime session. - - .. deprecated:: - Use ``settings=OpenAIRealtimeLLMSettings(session_properties=...)`` - instead. - - These are session-level settings that can be updated during the session - (except for voice and model). If None, uses default SessionProperties. - settings: Realtime LLM settings. If provided together with deprecated - top-level parameters, the ``settings`` values take precedence. + If None, uses default SessionProperties. + settings: Runtime-updatable settings for this service. start_audio_paused: Whether to start with audio input paused. Defaults to False. start_video_paused: Whether to start with video input paused. Defaults to False. video_frame_detail: Detail level for video processing. Can be "auto", "low", or "high". @@ -192,20 +179,14 @@ class OpenAIRealtimeLLMService(LLMService): seed=None, filter_incomplete_user_turns=False, user_turn_completion_config=None, - session_properties=events.SessionProperties(), ) # 2. Apply direct init arg overrides (deprecated) if model is not None: _warn_deprecated_param("model", OpenAIRealtimeLLMSettings, "model") default_settings.model = model - if session_properties is not None: - _warn_deprecated_param( - "session_properties", OpenAIRealtimeLLMSettings, "session_properties" - ) - default_settings.session_properties = session_properties - # 4. Apply settings delta (canonical API, always wins) + # 3. Apply settings delta (canonical API, always wins) if settings is not None: default_settings.apply_update(settings) @@ -220,6 +201,7 @@ class OpenAIRealtimeLLMService(LLMService): self.api_key = api_key self.base_url = full_url + self._session_properties = session_properties or events.SessionProperties() self._audio_input_paused = start_audio_paused self._video_input_paused = start_video_paused self._video_frame_detail = video_frame_detail @@ -282,12 +264,12 @@ class OpenAIRealtimeLLMService(LLMService): def _is_modality_enabled(self, modality: str) -> bool: """Check if a specific modality is enabled, "text" or "audio".""" - modalities = self._settings.session_properties.output_modalities or ["audio", "text"] + modalities = self._session_properties.output_modalities or ["audio", "text"] return modality in modalities def _get_enabled_modalities(self) -> list[str]: """Get the list of enabled modalities.""" - modalities = self._settings.session_properties.output_modalities or ["audio", "text"] + modalities = self._session_properties.output_modalities or ["audio", "text"] # API only supports single modality responses: either ["text"] or ["audio"] if "audio" in modalities: return ["audio"] @@ -360,9 +342,9 @@ class OpenAIRealtimeLLMService(LLMService): # None and False are different. Check for False. None means we're using OpenAI's # built-in turn detection defaults. turn_detection_disabled = ( - self._settings.session_properties.audio - and self._settings.session_properties.audio.input - and self._settings.session_properties.audio.input.turn_detection is False + self._session_properties.audio + and self._session_properties.audio.input + and self._session_properties.audio.input.turn_detection is False ) if turn_detection_disabled: await self.send_client_event(events.InputAudioBufferClearEvent()) @@ -382,9 +364,9 @@ class OpenAIRealtimeLLMService(LLMService): # None and False are different. Check for False. None means we're using OpenAI's # built-in turn detection defaults. turn_detection_disabled = ( - self._settings.session_properties.audio - and self._settings.session_properties.audio.input - and self._settings.session_properties.audio.input.turn_detection is False + self._session_properties.audio + and self._session_properties.audio.input + and self._session_properties.audio.input.turn_detection is False ) if turn_detection_disabled: await self.send_client_event(events.InputAudioBufferCommitEvent()) @@ -457,7 +439,7 @@ class OpenAIRealtimeLLMService(LLMService): # directly. The frame.delta path falls through to super, which calls # _update_settings → our override handles the rest. if isinstance(frame, LLMUpdateSettingsFrame) and frame.delta is None: - self._settings.session_properties = events.SessionProperties(**frame.settings) + self._session_properties = events.SessionProperties(**frame.settings) await self._send_session_update() await self.push_frame(frame, direction) return @@ -576,15 +558,13 @@ class OpenAIRealtimeLLMService(LLMService): await self.push_error(error_msg=f"Error sending client event: {e}", exception=e) async def _update_settings(self, delta): - """Apply a settings delta, sending a session update if needed.""" + """Apply a settings delta.""" changed = await super()._update_settings(delta) - if "session_properties" in changed: - await self._send_session_update() - self._warn_unhandled_updated_settings(changed.keys() - {"session_properties"}) + self._warn_unhandled_updated_settings(changed.keys()) return changed async def _send_session_update(self): - settings = self._settings.session_properties + settings = self._session_properties adapter: OpenAIRealtimeLLMAdapter = self.get_llm_adapter() if self._context: diff --git a/src/pipecat/services/openai_realtime_beta/azure.py b/src/pipecat/services/openai_realtime_beta/azure.py index fb85b1e79..72a1201f7 100644 --- a/src/pipecat/services/openai_realtime_beta/azure.py +++ b/src/pipecat/services/openai_realtime_beta/azure.py @@ -42,6 +42,8 @@ class AzureRealtimeBetaLLMService(OpenAIRealtimeBetaLLMService): real-time audio and text communication capabilities as the base OpenAI service. """ + _settings: AzureRealtimeBetaLLMSettings + def __init__( self, *, diff --git a/src/pipecat/services/openai_realtime_beta/openai.py b/src/pipecat/services/openai_realtime_beta/openai.py index 11b60c3b9..67a892e6f 100644 --- a/src/pipecat/services/openai_realtime_beta/openai.py +++ b/src/pipecat/services/openai_realtime_beta/openai.py @@ -10,7 +10,7 @@ import base64 import json import time import warnings -from dataclasses import dataclass, field +from dataclasses import dataclass from typing import Optional from loguru import logger @@ -54,7 +54,7 @@ from pipecat.processors.aggregators.openai_llm_context import ( from pipecat.processors.frame_processor import FrameDirection from pipecat.services.llm_service import FunctionCallFromLLM, LLMService from pipecat.services.openai.llm import OpenAIContextAggregatorPair -from pipecat.services.settings import NOT_GIVEN, LLMSettings, _NotGiven, _warn_deprecated_param +from pipecat.services.settings import LLMSettings, _warn_deprecated_param from pipecat.transcriptions.language import Language from pipecat.utils.time import time_now_iso8601 from pipecat.utils.tracing.service_decorators import traced_openai_realtime, traced_stt @@ -94,15 +94,9 @@ class CurrentAudioResponse: @dataclass class OpenAIRealtimeBetaLLMSettings(LLMSettings): - """Settings for OpenAI Realtime Beta LLM services. + """Settings for OpenAI Realtime Beta LLM services.""" - Parameters: - session_properties: OpenAI Realtime session configuration. - """ - - session_properties: events.SessionProperties | _NotGiven = field( - default_factory=lambda: NOT_GIVEN - ) + pass class OpenAIRealtimeBetaLLMService(LLMService): @@ -146,14 +140,8 @@ class OpenAIRealtimeBetaLLMService(LLMService): base_url: WebSocket base URL for the realtime API. Defaults to "wss://api.openai.com/v1/realtime". session_properties: Configuration properties for the realtime session. - - .. deprecated:: - Use ``settings=OpenAIRealtimeBetaLLMSettings(session_properties=...)`` - instead. - If None, uses default SessionProperties. - settings: Realtime Beta LLM settings. If provided together with deprecated - top-level parameters, the ``settings`` values take precedence. + settings: Runtime-updatable settings for this service. start_audio_paused: Whether to start with audio input paused. Defaults to False. send_transcription_frames: Whether to emit transcription frames. Defaults to True. **kwargs: Additional arguments passed to parent LLMService. @@ -179,20 +167,13 @@ class OpenAIRealtimeBetaLLMService(LLMService): seed=None, filter_incomplete_user_turns=False, user_turn_completion_config=None, - session_properties=events.SessionProperties(), ) # 2. Apply direct init arg overrides (deprecated) if model is not None: _warn_deprecated_param("model", OpenAIRealtimeBetaLLMSettings, "model") default_settings.model = model - if session_properties is not None: - _warn_deprecated_param( - "session_properties", OpenAIRealtimeBetaLLMSettings, "session_properties" - ) - default_settings.session_properties = session_properties - - # 4. Apply settings delta (canonical API, always wins) + # 3. Apply settings delta (canonical API, always wins) if settings is not None: default_settings.apply_update(settings) @@ -205,6 +186,7 @@ class OpenAIRealtimeBetaLLMService(LLMService): self.api_key = api_key self.base_url = full_url + self._session_properties = session_properties or events.SessionProperties() self._audio_input_paused = start_audio_paused self._send_transcription_frames = send_transcription_frames self._websocket = None @@ -243,12 +225,12 @@ class OpenAIRealtimeBetaLLMService(LLMService): def _is_modality_enabled(self, modality: str) -> bool: """Check if a specific modality is enabled, "text" or "audio".""" - modalities = self._settings.session_properties.modalities or ["audio", "text"] + modalities = self._session_properties.modalities or ["audio", "text"] return modality in modalities def _get_enabled_modalities(self) -> list[str]: """Get the list of enabled modalities.""" - return self._settings.session_properties.modalities or ["audio", "text"] + return self._session_properties.modalities or ["audio", "text"] async def retrieve_conversation_item(self, item_id: str): """Retrieve a conversation item by ID from the server. @@ -315,7 +297,7 @@ class OpenAIRealtimeBetaLLMService(LLMService): async def _handle_interruption(self): # None and False are different. Check for False. None means we're using OpenAI's # built-in turn detection defaults. - if self._settings.session_properties.turn_detection is False: + if self._session_properties.turn_detection is False: await self.send_client_event(events.InputAudioBufferClearEvent()) await self.send_client_event(events.ResponseCancelEvent()) await self._truncate_current_audio_response() @@ -332,7 +314,7 @@ class OpenAIRealtimeBetaLLMService(LLMService): async def _handle_user_stopped_speaking(self, frame): # None and False are different. Check for False. None means we're using OpenAI's # built-in turn detection defaults. - if self._settings.session_properties.turn_detection is False: + if self._session_properties.turn_detection is False: await self.send_client_event(events.InputAudioBufferCommitEvent()) await self.send_client_event(events.ResponseCreateEvent()) @@ -403,7 +385,7 @@ class OpenAIRealtimeBetaLLMService(LLMService): # directly. The frame.delta path falls through to super, which calls # _update_settings → our override handles the rest. if isinstance(frame, LLMUpdateSettingsFrame) and frame.delta is None: - self._settings.session_properties = events.SessionProperties(**frame.settings) + self._session_properties = events.SessionProperties(**frame.settings) await self._send_session_update() await self.push_frame(frame, direction) return @@ -520,14 +502,13 @@ class OpenAIRealtimeBetaLLMService(LLMService): await self.push_error(error_msg=f"Error sending client event: {e}", exception=e) async def _update_settings(self, delta): - """Apply a settings delta, sending a session update if needed.""" + """Apply a settings delta.""" changed = await super()._update_settings(delta) - if "session_properties" in changed: - await self._send_session_update() + self._warn_unhandled_updated_settings(changed.keys()) return changed async def _send_session_update(self): - settings = self._settings.session_properties + settings = self._session_properties # tools given in the context override the tools in the session properties if self._context and self._context.tools: settings.tools = self._context.tools diff --git a/src/pipecat/services/openpipe/llm.py b/src/pipecat/services/openpipe/llm.py index b2e953e64..f6437feef 100644 --- a/src/pipecat/services/openpipe/llm.py +++ b/src/pipecat/services/openpipe/llm.py @@ -43,6 +43,8 @@ class OpenPipeLLMService(OpenAILLMService): for model training and evaluation. """ + _settings: OpenPipeLLMSettings + def __init__( self, *, diff --git a/src/pipecat/services/openrouter/llm.py b/src/pipecat/services/openrouter/llm.py index fa2f170ee..03591de46 100644 --- a/src/pipecat/services/openrouter/llm.py +++ b/src/pipecat/services/openrouter/llm.py @@ -34,6 +34,8 @@ class OpenRouterLLMService(OpenAILLMService): maintaining full compatibility with OpenAI's interface and functionality. """ + _settings: OpenRouterLLMSettings + def __init__( self, *, diff --git a/src/pipecat/services/perplexity/llm.py b/src/pipecat/services/perplexity/llm.py index d90aea6a4..9969020c5 100644 --- a/src/pipecat/services/perplexity/llm.py +++ b/src/pipecat/services/perplexity/llm.py @@ -38,6 +38,8 @@ class PerplexityLLMService(OpenAILLMService): in token usage reporting between Perplexity (incremental) and OpenAI (final summary). """ + _settings: PerplexityLLMSettings + def __init__( self, *, diff --git a/src/pipecat/services/qwen/llm.py b/src/pipecat/services/qwen/llm.py index 6d9abeefe..e08566418 100644 --- a/src/pipecat/services/qwen/llm.py +++ b/src/pipecat/services/qwen/llm.py @@ -30,6 +30,8 @@ class QwenLLMService(OpenAILLMService): maintaining full compatibility with OpenAI's interface and functionality. """ + _settings: QwenLLMSettings + def __init__( self, *, diff --git a/src/pipecat/services/sambanova/llm.py b/src/pipecat/services/sambanova/llm.py index f87b432cc..cdd2139da 100644 --- a/src/pipecat/services/sambanova/llm.py +++ b/src/pipecat/services/sambanova/llm.py @@ -42,6 +42,8 @@ class SambaNovaLLMService(OpenAILLMService): # type: ignore maintaining full compatibility with OpenAI's interface and functionality. """ + _settings: SambaNovaLLMSettings + def __init__( self, *, diff --git a/src/pipecat/services/together/llm.py b/src/pipecat/services/together/llm.py index 23e38f752..2fa952a95 100644 --- a/src/pipecat/services/together/llm.py +++ b/src/pipecat/services/together/llm.py @@ -30,6 +30,8 @@ class TogetherLLMService(OpenAILLMService): maintaining full compatibility with OpenAI's interface and functionality. """ + _settings: TogetherLLMSettings + def __init__( self, *, From 14c3a88f02332615e900b76af4ca614c48c1e733 Mon Sep 17 00:00:00 2001 From: Mark Backman Date: Wed, 4 Mar 2026 21:20:54 -0500 Subject: [PATCH 0813/1060] Fix tests --- tests/test_service_init.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/tests/test_service_init.py b/tests/test_service_init.py index 73cb6a337..67dcbb324 100644 --- a/tests/test_service_init.py +++ b/tests/test_service_init.py @@ -73,7 +73,7 @@ def _import_all_service_modules(): """Import every module under pipecat.services (skipping missing deps).""" package = pipecat.services for _importer, modname, _ispkg in pkgutil.walk_packages( - package.__path__, prefix=package.__name__ + "." + package.__path__, prefix=package.__name__ + ".", onerror=lambda _name: None ): try: importlib.import_module(modname) From 62554a2390088164a589bb5599a28627c8c4ac56 Mon Sep 17 00:00:00 2001 From: Mark Backman Date: Wed, 4 Mar 2026 22:55:51 -0500 Subject: [PATCH 0814/1060] Update examples --- .../foundational/01-say-one-thing-piper.py | 4 +- .../foundational/01-say-one-thing-rime.py | 6 +- examples/foundational/01-say-one-thing.py | 6 +- examples/foundational/01a-local-audio.py | 6 +- examples/foundational/01b-livekit-audio.py | 6 +- examples/foundational/02-llm-say-one-thing.py | 6 +- .../04-transports-small-webrtc.py | 6 +- examples/foundational/04a-transports-daily.py | 12 ++-- .../foundational/04b-transports-livekit.py | 6 +- .../foundational/05-sync-speech-and-image.py | 6 +- .../05a-local-sync-speech-and-image.py | 6 +- .../foundational/06-listen-and-respond.py | 6 +- examples/foundational/06a-image-sync.py | 6 +- .../07-interruptible-cartesia-http.py | 6 +- .../07a-interruptible-speechmatics-vad.py | 37 +++++------- .../07a-interruptible-speechmatics.py | 36 +++++------- .../07b-interruptible-langchain.py | 6 +- .../07c-interruptible-deepgram-flux.py | 15 +++-- .../07c-interruptible-deepgram-http.py | 10 ++-- .../07c-interruptible-deepgram-vad.py | 17 ++++-- .../07c-interruptible-deepgram.py | 9 ++- .../07d-interruptible-elevenlabs-http.py | 6 +- .../07d-interruptible-elevenlabs.py | 6 +- .../foundational/07g-interruptible-openai.py | 23 ++++---- .../07h-interruptible-openpipe.py | 6 +- .../foundational/07i-interruptible-xtts.py | 6 +- .../07j-interruptible-gladia-vad.py | 28 +++++---- .../foundational/07j-interruptible-gladia.py | 28 +++++---- .../foundational/07k-interruptible-lmnt.py | 9 ++- .../foundational/07l-interruptible-groq.py | 6 +- .../07m-interruptible-aws-strands.py | 9 ++- .../foundational/07m-interruptible-aws.py | 9 ++- .../07n-interruptible-gemini-image.py | 22 ++++--- .../foundational/07n-interruptible-gemini.py | 14 +++-- .../07n-interruptible-google-http.py | 27 +++++---- .../foundational/07n-interruptible-google.py | 27 +++++---- ...interruptible-assemblyai-turn-detection.py | 11 ++-- .../07o-interruptible-assemblyai.py | 6 +- .../07p-interruptible-krisp-viva.py | 7 ++- .../foundational/07p-interruptible-krisp.py | 9 ++- .../07q-interruptible-rime-http.py | 7 ++- .../foundational/07q-interruptible-rime.py | 6 +- .../foundational/07r-interruptible-nvidia.py | 6 +- .../07s-interruptible-google-audio-in.py | 13 +++-- .../foundational/07t-interruptible-fish.py | 6 +- .../07v-interruptible-neuphonic-http.py | 6 +- .../07v-interruptible-neuphonic.py | 6 +- .../foundational/07w-interruptible-fal.py | 6 +- .../foundational/07x-interruptible-local.py | 6 +- .../foundational/07y-interruptible-minimax.py | 6 +- .../07z-interruptible-sarvam-http.py | 6 +- .../foundational/07z-interruptible-sarvam.py | 14 +++-- .../foundational/07za-interruptible-soniox.py | 20 ++++--- .../07zb-interruptible-inworld-http.py | 10 ++-- .../07zb-interruptible-inworld.py | 10 ++-- .../07zc-interruptible-asyncai-http.py | 6 +- .../07zc-interruptible-asyncai.py | 6 +- .../07zd-interruptible-aicoustics.py | 6 +- .../foundational/07ze-interruptible-hume.py | 6 +- .../07zf-interruptible-gradium.py | 10 ++-- .../foundational/07zg-interruptible-camb.py | 6 +- .../foundational/07zi-interruptible-piper.py | 8 ++- .../foundational/07zj-interruptible-kokoro.py | 8 ++- .../07zk-interruptible-resemble.py | 6 +- .../foundational/08-custom-frame-processor.py | 6 +- examples/foundational/10-wake-phrase.py | 6 +- examples/foundational/11-sound-effects.py | 6 +- .../foundational/12-describe-image-openai.py | 6 +- .../12a-describe-image-anthropic.py | 6 +- .../foundational/12b-describe-image-aws.py | 20 ++++--- .../12c-describe-image-gemini-flash.py | 6 +- .../12d-describe-image-moondream.py | 6 +- .../13b-deepgram-transcription.py | 6 +- .../foundational/13c-gladia-transcription.py | 6 +- .../foundational/13c-gladia-translation.py | 12 ++-- .../13d-assemblyai-transcription.py | 7 +-- examples/foundational/13e-whisper-mlx.py | 8 ++- .../13g-sambanova-transcription.py | 6 +- .../13h-speechmatics-transcription.py | 4 +- .../foundational/13l-gradium-transcription.py | 7 ++- .../foundational/13m-openai-transcription.py | 8 ++- examples/foundational/14-function-calling.py | 6 +- .../14a-function-calling-anthropic.py | 22 +++---- .../14c-function-calling-together.py | 12 ++-- .../14d-function-calling-anthropic-video.py | 6 +- .../14d-function-calling-aws-video.py | 20 ++++--- ...14d-function-calling-gemini-flash-video.py | 6 +- .../14d-function-calling-moondream-video.py | 6 +- .../14d-function-calling-openai-video.py | 6 +- .../14e-function-calling-google.py | 58 ++++++++++--------- .../foundational/14f-function-calling-groq.py | 6 +- .../foundational/14g-function-calling-grok.py | 6 +- .../14h-function-calling-azure.py | 12 ++-- .../14i-function-calling-fireworks.py | 12 ++-- .../14j-function-calling-nvidia.py | 29 ++++------ .../14k-function-calling-cerebras.py | 6 +- .../14l-function-calling-deepseek.py | 12 ++-- .../14m-function-calling-openrouter.py | 16 +++-- .../14n-function-calling-perplexity.py | 20 +++---- ...o-function-calling-gemini-openai-format.py | 11 +++- .../14p-function-calling-gemini-vertex-ai.py | 7 ++- .../foundational/14q-function-calling-qwen.py | 6 +- .../foundational/14r-function-calling-aws.py | 17 ++++-- .../14s-function-calling-sambanova.py | 6 +- .../14t-function-calling-direct.py | 6 +- .../14u-function-calling-ollama.py | 12 ++-- .../14v-function-calling-openai.py | 16 ++--- .../14w-function-calling-mistral.py | 6 +- .../14x-function-calling-openpipe.py | 6 +- examples/foundational/15-switch-voices.py | 14 +++-- examples/foundational/15a-switch-languages.py | 10 +++- .../16-gpu-container-local-bot.py | 12 ++-- examples/foundational/17-detect-user-idle.py | 6 +- .../19b-openai-realtime-beta-text.py | 6 +- .../foundational/19b-openai-realtime-text.py | 6 +- .../20a-persistent-context-openai.py | 6 +- .../20c-persistent-context-anthropic.py | 10 ++-- .../20d-persistent-context-gemini.py | 6 +- examples/foundational/21-tavus-transport.py | 6 +- .../foundational/21a-tavus-video-service.py | 6 +- .../22-filter-incomplete-turns.py | 24 ++++---- .../foundational/23-bot-background-sound.py | 6 +- .../foundational/24-user-mute-strategy.py | 9 ++- examples/foundational/25-google-audio-in.py | 18 +++--- examples/foundational/26d-gemini-live-text.py | 2 +- examples/foundational/27-simli-layer.py | 12 ++-- .../foundational/28-user-assistant-turns.py | 6 +- .../foundational/29-turn-tracking-observer.py | 6 +- examples/foundational/30-observer.py | 6 +- .../32-gemini-grounding-metadata.py | 6 +- examples/foundational/33-gemini-rag.py | 29 ++++++---- examples/foundational/34-audio-recording.py | 7 ++- .../35-pattern-pair-voice-switching.py | 23 ++++---- .../foundational/36-user-email-gathering.py | 6 +- examples/foundational/37-mem0.py | 12 ++-- examples/foundational/38-smart-turn-fal.py | 6 +- .../38a-smart-turn-local-coreml.py | 6 +- examples/foundational/38b-smart-turn-local.py | 6 +- examples/foundational/39-mcp-stdio.py | 40 ++++++------- .../foundational/39a-mcp-streamable-http.py | 6 +- .../39b-mcp-streamable-http-gemini-live.py | 6 +- examples/foundational/39c-multiple-mcp.py | 14 ++--- .../foundational/42-interruption-config.py | 6 +- examples/foundational/43-heygen-transport.py | 6 +- .../foundational/43a-heygen-video-service.py | 6 +- .../foundational/44-voicemail-detection.py | 6 +- .../45-before-and-after-events.py | 6 +- examples/foundational/47-sentry-metrics.py | 6 +- examples/foundational/48-service-switcher.py | 31 +++++----- .../foundational/49a-thinking-anthropic.py | 19 ++++-- examples/foundational/49b-thinking-google.py | 15 ++--- .../49c-thinking-functions-anthropic.py | 19 ++++-- .../49d-thinking-functions-google.py | 15 ++--- examples/foundational/52-live-translation.py | 6 +- .../53-concurrent-llm-evaluation.py | 43 ++++++-------- .../53-concurrent-llm-rtvi-ignored-sources.py | 43 +++++--------- .../54-context-summarization-openai.py | 6 +- .../54a-context-summarization-google.py | 6 +- ...54b-context-summarization-manual-openai.py | 36 +++++------- ...54c-context-summarization-dedicated-llm.py | 42 +++++++------- .../55a-update-settings-deepgram-flux-stt.py | 6 +- ...-update-settings-deepgram-sagemaker-stt.py | 6 +- .../55a-update-settings-deepgram-stt.py | 6 +- .../55b-update-settings-azure-stt.py | 6 +- .../55c-update-settings-google-stt.py | 6 +- .../55d-update-settings-assemblyai-stt.py | 6 +- .../55e-update-settings-gladia-stt.py | 6 +- ...update-settings-elevenlabs-realtime-stt.py | 6 +- .../55g-update-settings-elevenlabs-stt.py | 6 +- .../55h-update-settings-speechmatics-stt.py | 6 +- .../55i-update-settings-whisper-api-stt.py | 6 +- .../55j-update-settings-sarvam-stt.py | 6 +- .../55k-update-settings-soniox-stt.py | 6 +- .../55l-update-settings-aws-transcribe-stt.py | 6 +- .../55m-update-settings-cartesia-stt.py | 6 +- .../55n-update-settings-cartesia-http-tts.py | 4 +- .../55n-update-settings-cartesia-tts.py | 4 +- .../55zi-update-settings-azure-llm.py | 6 +- .../55zi-update-settings-openai-llm.py | 6 +- .../55zj-update-settings-anthropic-llm.py | 6 +- .../55zk-update-settings-google-llm.py | 6 +- .../55zk-update-settings-google-vertex-llm.py | 6 +- .../55zp-update-settings-aws-bedrock-llm.py | 6 +- .../55zq-update-settings-fal-stt.py | 6 +- .../55zr-update-settings-gradium-stt.py | 6 +- ...zt-update-settings-nvidia-segmented-stt.py | 6 +- .../55zt-update-settings-nvidia-stt.py | 6 +- ...5zu-update-settings-openai-realtime-stt.py | 6 +- .../55zx-update-settings-cerebras-llm.py | 6 +- .../55zy-update-settings-deepseek-llm.py | 6 +- .../55zz-update-settings-fireworks-llm.py | 6 +- .../55zza-update-settings-grok-llm.py | 6 +- .../55zzb-update-settings-groq-llm.py | 6 +- .../55zzc-update-settings-mistral-llm.py | 6 +- .../55zzd-update-settings-nvidia-llm.py | 6 +- .../55zze-update-settings-ollama-llm.py | 6 +- .../55zzf-update-settings-openrouter-llm.py | 6 +- .../55zzg-update-settings-perplexity-llm.py | 6 +- .../55zzh-update-settings-qwen-llm.py | 6 +- .../55zzi-update-settings-sambanova-llm.py | 6 +- .../55zzj-update-settings-together-llm.py | 6 +- .../55zzn-update-settings-groq-stt.py | 6 +- .../foundational/56-lemonslice-transport.py | 6 +- examples/quickstart/bot.py | 6 +- scripts/evals/eval.py | 2 +- src/pipecat/services/openai/base_llm.py | 2 +- src/pipecat/services/sarvam/tts.py | 21 +------ 207 files changed, 1241 insertions(+), 852 deletions(-) diff --git a/examples/foundational/01-say-one-thing-piper.py b/examples/foundational/01-say-one-thing-piper.py index cace8dbeb..6c4e1836e 100644 --- a/examples/foundational/01-say-one-thing-piper.py +++ b/examples/foundational/01-say-one-thing-piper.py @@ -39,7 +39,9 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): # Create an HTTP session async with aiohttp.ClientSession() as session: tts = PiperHttpTTSService( - base_url=os.getenv("PIPER_BASE_URL"), aiohttp_session=session, sample_rate=24000 + base_url=os.getenv("PIPER_BASE_URL"), + aiohttp_session=session, + sample_rate=24000, ) task = PipelineTask( diff --git a/examples/foundational/01-say-one-thing-rime.py b/examples/foundational/01-say-one-thing-rime.py index 2a31efa68..63667fac8 100644 --- a/examples/foundational/01-say-one-thing-rime.py +++ b/examples/foundational/01-say-one-thing-rime.py @@ -16,7 +16,7 @@ from pipecat.pipeline.runner import PipelineRunner from pipecat.pipeline.task import PipelineTask from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport -from pipecat.services.rime.tts import RimeHttpTTSService +from pipecat.services.rime.tts import RimeHttpTTSService, RimeTTSSettings from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams @@ -39,8 +39,10 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): async with aiohttp.ClientSession() as session: tts = RimeHttpTTSService( api_key=os.getenv("RIME_API_KEY", ""), - voice_id="rex", aiohttp_session=session, + settings=RimeTTSSettings( + voice="rex", + ), ) task = PipelineTask( diff --git a/examples/foundational/01-say-one-thing.py b/examples/foundational/01-say-one-thing.py index 7df26701c..bfcf829cc 100644 --- a/examples/foundational/01-say-one-thing.py +++ b/examples/foundational/01-say-one-thing.py @@ -15,7 +15,7 @@ from pipecat.pipeline.runner import PipelineRunner from pipecat.pipeline.task import PipelineTask from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport -from pipecat.services.cartesia.tts import CartesiaTTSService +from pipecat.services.cartesia.tts import CartesiaTTSService, CartesiaTTSSettings from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams @@ -37,7 +37,9 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): tts = CartesiaTTSService( api_key=os.getenv("CARTESIA_API_KEY"), - voice_id="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady + settings=CartesiaTTSSettings( + voice="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady + ), ) task = PipelineTask( diff --git a/examples/foundational/01a-local-audio.py b/examples/foundational/01a-local-audio.py index 432880203..77565dffe 100644 --- a/examples/foundational/01a-local-audio.py +++ b/examples/foundational/01a-local-audio.py @@ -15,7 +15,7 @@ from pipecat.frames.frames import EndFrame, TTSSpeakFrame from pipecat.pipeline.pipeline import Pipeline from pipecat.pipeline.runner import PipelineRunner from pipecat.pipeline.task import PipelineTask -from pipecat.services.cartesia.tts import CartesiaTTSService +from pipecat.services.cartesia.tts import CartesiaTTSService, CartesiaTTSSettings from pipecat.transports.local.audio import LocalAudioTransport, LocalAudioTransportParams load_dotenv(override=True) @@ -29,7 +29,9 @@ async def main(): tts = CartesiaTTSService( api_key=os.getenv("CARTESIA_API_KEY"), - voice_id="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady + settings=CartesiaTTSSettings( + voice="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady + ), ) pipeline = Pipeline([tts, transport.output()]) diff --git a/examples/foundational/01b-livekit-audio.py b/examples/foundational/01b-livekit-audio.py index a7697646e..ad4c785eb 100644 --- a/examples/foundational/01b-livekit-audio.py +++ b/examples/foundational/01b-livekit-audio.py @@ -16,7 +16,7 @@ from pipecat.pipeline.pipeline import Pipeline from pipecat.pipeline.runner import PipelineRunner from pipecat.pipeline.task import PipelineTask from pipecat.runner.livekit import configure -from pipecat.services.cartesia.tts import CartesiaTTSService +from pipecat.services.cartesia.tts import CartesiaTTSService, CartesiaTTSSettings from pipecat.transports.livekit.transport import LiveKitParams, LiveKitTransport load_dotenv(override=True) @@ -37,7 +37,9 @@ async def main(): tts = CartesiaTTSService( api_key=os.getenv("CARTESIA_API_KEY"), - voice_id="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady + settings=CartesiaTTSSettings( + voice="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady + ), ) runner = PipelineRunner() diff --git a/examples/foundational/02-llm-say-one-thing.py b/examples/foundational/02-llm-say-one-thing.py index 9cfd7c39e..3ee536a64 100644 --- a/examples/foundational/02-llm-say-one-thing.py +++ b/examples/foundational/02-llm-say-one-thing.py @@ -16,7 +16,7 @@ from pipecat.pipeline.task import PipelineTask from pipecat.processors.aggregators.llm_context import LLMContext from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport -from pipecat.services.cartesia.tts import CartesiaTTSService +from pipecat.services.cartesia.tts import CartesiaTTSService, CartesiaTTSSettings from pipecat.services.openai.llm import OpenAILLMService from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams @@ -39,7 +39,9 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): tts = CartesiaTTSService( api_key=os.getenv("CARTESIA_API_KEY"), - voice_id="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady + settings=CartesiaTTSSettings( + voice="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady + ), ) llm = OpenAILLMService( diff --git a/examples/foundational/04-transports-small-webrtc.py b/examples/foundational/04-transports-small-webrtc.py index d29171dd2..6cf32a285 100644 --- a/examples/foundational/04-transports-small-webrtc.py +++ b/examples/foundational/04-transports-small-webrtc.py @@ -27,7 +27,7 @@ from pipecat.processors.aggregators.llm_response_universal import ( LLMContextAggregatorPair, LLMUserAggregatorParams, ) -from pipecat.services.cartesia.tts import CartesiaTTSService +from pipecat.services.cartesia.tts import CartesiaTTSService, CartesiaTTSSettings from pipecat.services.deepgram.stt import DeepgramSTTService from pipecat.services.openai.llm import OpenAILLMService from pipecat.transports.base_transport import TransportParams @@ -67,7 +67,9 @@ async def run_example(webrtc_connection: SmallWebRTCConnection): tts = CartesiaTTSService( api_key=os.getenv("CARTESIA_API_KEY"), - voice_id="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady + settings=CartesiaTTSSettings( + voice="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady + ), ) llm = OpenAILLMService( diff --git a/examples/foundational/04a-transports-daily.py b/examples/foundational/04a-transports-daily.py index b0a7958ef..8b23cb69e 100644 --- a/examples/foundational/04a-transports-daily.py +++ b/examples/foundational/04a-transports-daily.py @@ -23,8 +23,8 @@ from pipecat.processors.aggregators.llm_response_universal import ( LLMUserAggregatorParams, ) from pipecat.runner.daily import configure -from pipecat.services.cartesia.tts import CartesiaTTSService -from pipecat.services.openai.llm import OpenAILLMService +from pipecat.services.cartesia.tts import CartesiaTTSService, CartesiaTTSSettings +from pipecat.services.openai.llm import OpenAILLMService, OpenAILLMSettings from pipecat.transports.daily.transport import DailyParams, DailyTransport load_dotenv(override=True) @@ -50,12 +50,16 @@ async def main(): tts = CartesiaTTSService( api_key=os.getenv("CARTESIA_API_KEY"), - voice_id="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady + settings=CartesiaTTSSettings( + voice="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady + ), ) llm = OpenAILLMService( api_key=os.getenv("OPENAI_API_KEY"), - model="gpt-4o", + settings=OpenAILLMSettings( + model="gpt-4o", + ), system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", ) diff --git a/examples/foundational/04b-transports-livekit.py b/examples/foundational/04b-transports-livekit.py index e05c5ddc3..f55f106c1 100644 --- a/examples/foundational/04b-transports-livekit.py +++ b/examples/foundational/04b-transports-livekit.py @@ -29,7 +29,7 @@ from pipecat.processors.aggregators.llm_response_universal import ( LLMUserAggregatorParams, ) from pipecat.runner.livekit import configure -from pipecat.services.cartesia.tts import CartesiaTTSService +from pipecat.services.cartesia.tts import CartesiaTTSService, CartesiaTTSSettings from pipecat.services.deepgram.stt import DeepgramSTTService from pipecat.services.openai.llm import OpenAILLMService from pipecat.transports.livekit.transport import LiveKitParams, LiveKitTransport @@ -62,7 +62,9 @@ async def main(): tts = CartesiaTTSService( api_key=os.getenv("CARTESIA_API_KEY"), - voice_id="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady + settings=CartesiaTTSSettings( + voice="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady + ), ) context = LLMContext() diff --git a/examples/foundational/05-sync-speech-and-image.py b/examples/foundational/05-sync-speech-and-image.py index c1b142670..95de1143b 100644 --- a/examples/foundational/05-sync-speech-and-image.py +++ b/examples/foundational/05-sync-speech-and-image.py @@ -27,7 +27,7 @@ from pipecat.processors.aggregators.sentence import SentenceAggregator from pipecat.processors.frame_processor import FrameDirection, FrameProcessor from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport -from pipecat.services.cartesia.tts import CartesiaHttpTTSService +from pipecat.services.cartesia.tts import CartesiaHttpTTSService, CartesiaTTSSettings from pipecat.services.fal.image import FalImageGenService from pipecat.services.openai.llm import OpenAILLMService from pipecat.transports.base_transport import BaseTransport, TransportParams @@ -98,7 +98,9 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): tts = CartesiaHttpTTSService( api_key=os.getenv("CARTESIA_API_KEY"), - voice_id="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady + settings=CartesiaTTSSettings( + voice="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady + ), ) imagegen = FalImageGenService( diff --git a/examples/foundational/05a-local-sync-speech-and-image.py b/examples/foundational/05a-local-sync-speech-and-image.py index 56309c0a5..03b690c11 100644 --- a/examples/foundational/05a-local-sync-speech-and-image.py +++ b/examples/foundational/05a-local-sync-speech-and-image.py @@ -28,7 +28,7 @@ from pipecat.pipeline.task import PipelineTask from pipecat.processors.aggregators.llm_context import LLMContext from pipecat.processors.aggregators.sentence import SentenceAggregator from pipecat.processors.frame_processor import FrameDirection, FrameProcessor -from pipecat.services.cartesia.tts import CartesiaHttpTTSService +from pipecat.services.cartesia.tts import CartesiaHttpTTSService, CartesiaTTSSettings from pipecat.services.fal.image import FalImageGenService from pipecat.services.openai.llm import OpenAILLMService from pipecat.transports.local.tk import TkLocalTransport, TkTransportParams @@ -98,7 +98,9 @@ async def main(): tts = CartesiaHttpTTSService( api_key=os.getenv("CARTESIA_API_KEY"), - voice_id="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady + settings=CartesiaTTSSettings( + voice="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady + ), ) imagegen = FalImageGenService( diff --git a/examples/foundational/06-listen-and-respond.py b/examples/foundational/06-listen-and-respond.py index 418b3b5af..c90d79c4e 100644 --- a/examples/foundational/06-listen-and-respond.py +++ b/examples/foundational/06-listen-and-respond.py @@ -28,7 +28,7 @@ from pipecat.processors.aggregators.llm_response_universal import ( from pipecat.processors.frame_processor import FrameDirection, FrameProcessor from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport -from pipecat.services.cartesia.tts import CartesiaTTSService +from pipecat.services.cartesia.tts import CartesiaTTSService, CartesiaTTSSettings from pipecat.services.deepgram.stt import DeepgramSTTService from pipecat.services.openai.llm import OpenAILLMService from pipecat.transports.base_transport import BaseTransport, TransportParams @@ -83,7 +83,9 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): tts = CartesiaTTSService( api_key=os.getenv("CARTESIA_API_KEY"), - voice_id="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady + settings=CartesiaTTSSettings( + voice="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady + ), ) llm = OpenAILLMService( diff --git a/examples/foundational/06a-image-sync.py b/examples/foundational/06a-image-sync.py index f963aa339..666f4739c 100644 --- a/examples/foundational/06a-image-sync.py +++ b/examples/foundational/06a-image-sync.py @@ -29,7 +29,7 @@ from pipecat.processors.aggregators.llm_response_universal import ( from pipecat.processors.frame_processor import FrameDirection, FrameProcessor from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport -from pipecat.services.cartesia.tts import CartesiaTTSService +from pipecat.services.cartesia.tts import CartesiaTTSService, CartesiaTTSSettings from pipecat.services.deepgram.stt import DeepgramSTTService from pipecat.services.openai.llm import OpenAILLMService from pipecat.transports.base_transport import BaseTransport, TransportParams @@ -100,7 +100,9 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): tts = CartesiaTTSService( api_key=os.getenv("CARTESIA_API_KEY"), - voice_id="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady + settings=CartesiaTTSSettings( + voice="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady + ), ) llm = OpenAILLMService( diff --git a/examples/foundational/07-interruptible-cartesia-http.py b/examples/foundational/07-interruptible-cartesia-http.py index 8ce1ed375..b20289ce2 100644 --- a/examples/foundational/07-interruptible-cartesia-http.py +++ b/examples/foundational/07-interruptible-cartesia-http.py @@ -23,7 +23,7 @@ from pipecat.processors.aggregators.llm_response_universal import ( from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport from pipecat.services.cartesia.stt import CartesiaSTTService -from pipecat.services.cartesia.tts import CartesiaHttpTTSService +from pipecat.services.cartesia.tts import CartesiaHttpTTSService, CartesiaTTSSettings from pipecat.services.openai.llm import OpenAILLMService from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams @@ -58,8 +58,10 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): tts = CartesiaHttpTTSService( api_key=os.getenv("CARTESIA_API_KEY"), - voice_id="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady aiohttp_session=session, + settings=CartesiaTTSSettings( + voice="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady + ), ) llm = OpenAILLMService( diff --git a/examples/foundational/07a-interruptible-speechmatics-vad.py b/examples/foundational/07a-interruptible-speechmatics-vad.py index d75ae2b1f..5bb8459e2 100644 --- a/examples/foundational/07a-interruptible-speechmatics-vad.py +++ b/examples/foundational/07a-interruptible-speechmatics-vad.py @@ -21,10 +21,10 @@ from pipecat.processors.aggregators.llm_response_universal import ( ) from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport -from pipecat.services.openai.base_llm import BaseOpenAILLMService +from pipecat.services.openai.base_llm import OpenAILLMSettings from pipecat.services.openai.llm import OpenAILLMService -from pipecat.services.speechmatics.stt import SpeechmaticsSTTService -from pipecat.services.speechmatics.tts import SpeechmaticsTTSService +from pipecat.services.speechmatics.stt import SpeechmaticsSTTService, SpeechmaticsSTTSettings +from pipecat.services.speechmatics.tts import SpeechmaticsTTSService, SpeechmaticsTTSSettings from pipecat.transcriptions.language import Language from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams @@ -93,7 +93,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): async with aiohttp.ClientSession() as session: stt = SpeechmaticsSTTService( api_key=os.getenv("SPEECHMATICS_API_KEY"), - params=SpeechmaticsSTTService.InputParams( + settings=SpeechmaticsSTTSettings( language=Language.EN, turn_detection_mode=SpeechmaticsSTTService.TurnDetectionMode.ADAPTIVE, # focus_speakers=["S1"], @@ -104,32 +104,21 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): tts = SpeechmaticsTTSService( api_key=os.getenv("SPEECHMATICS_API_KEY"), - voice_id="sarah", + settings=SpeechmaticsTTSSettings( + voice="sarah", + ), aiohttp_session=session, ) llm = OpenAILLMService( api_key=os.getenv("OPENAI_API_KEY"), - params=BaseOpenAILLMService.InputParams(temperature=0.75), + settings=OpenAILLMSettings( + temperature=0.75, + ), + system_instruction="You are a helpful British assistant called Sarah. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Always include punctuation in your responses. Give very short replies - do not give longer replies unless strictly necessary. Respond to what the user said in a concise, funny, creative and helpful way. Use `` tags to identify different speakers - do not use tags in your replies. Do not respond to speakers within `` tags unless explicitly asked to.", ) - messages = [ - { - "role": "system", - "content": ( - "You are a helpful British assistant called Sarah. " - "Your goal is to demonstrate your capabilities in a succinct way. " - "Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. " - "Always include punctuation in your responses. " - "Give very short replies - do not give longer replies unless strictly necessary. " - "Respond to what the user said in a concise, funny, creative and helpful way. " - "Use `` tags to identify different speakers - do not use tags in your replies. " - "Do not respond to speakers within `` tags unless explicitly asked to. " - ), - }, - ] - - context = LLMContext(messages) + context = LLMContext() user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, user_params=LLMUserAggregatorParams(user_turn_strategies=ExternalUserTurnStrategies()), @@ -160,7 +149,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): async def on_client_connected(transport, client): logger.info(f"Client connected") # Kick off the conversation. - messages.append({"role": "system", "content": "Say a short hello to the user."}) + context.add_message({"role": "system", "content": "Say a short hello to the user."}) await task.queue_frames([LLMRunFrame()]) @transport.event_handler("on_client_disconnected") diff --git a/examples/foundational/07a-interruptible-speechmatics.py b/examples/foundational/07a-interruptible-speechmatics.py index f8b4cdf19..caecb74be 100644 --- a/examples/foundational/07a-interruptible-speechmatics.py +++ b/examples/foundational/07a-interruptible-speechmatics.py @@ -22,10 +22,10 @@ from pipecat.processors.aggregators.llm_response_universal import ( ) from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport -from pipecat.services.openai.base_llm import BaseOpenAILLMService +from pipecat.services.openai.base_llm import OpenAILLMSettings from pipecat.services.openai.llm import OpenAILLMService -from pipecat.services.speechmatics.stt import SpeechmaticsSTTService -from pipecat.services.speechmatics.tts import SpeechmaticsTTSService +from pipecat.services.speechmatics.stt import SpeechmaticsSTTService, SpeechmaticsSTTSettings +from pipecat.services.speechmatics.tts import SpeechmaticsTTSService, SpeechmaticsTTSSettings from pipecat.transcriptions.language import Language from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams @@ -76,7 +76,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): async with aiohttp.ClientSession() as session: stt = SpeechmaticsSTTService( api_key=os.getenv("SPEECHMATICS_API_KEY"), - params=SpeechmaticsSTTService.InputParams( + settings=SpeechmaticsSTTSettings( language=Language.EN, speaker_active_format="<{speaker_id}>{text}", ), @@ -84,31 +84,21 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): tts = SpeechmaticsTTSService( api_key=os.getenv("SPEECHMATICS_API_KEY"), - voice_id="sarah", + settings=SpeechmaticsTTSSettings( + voice="sarah", + ), aiohttp_session=session, ) llm = OpenAILLMService( api_key=os.getenv("OPENAI_API_KEY"), - params=BaseOpenAILLMService.InputParams(temperature=0.75), + settings=OpenAILLMSettings( + temperature=0.75, + ), + system_instruction="You are a helpful British assistant called Sarah. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Always include punctuation in your responses. Give very short replies - do not give longer replies unless strictly necessary. Respond to what the user said in a concise, funny, creative and helpful way. Use `` tags to identify different speakers - do not use tags in your replies. Do not respond to speakers within `` tags unless explicitly asked to.", ) - messages = [ - { - "role": "system", - "content": ( - "You are a helpful British assistant called Sarah. " - "Your goal is to demonstrate your capabilities in a succinct way. " - "Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. " - "Always include punctuation in your responses. " - "Give very short replies - do not give longer replies unless strictly necessary. " - "Respond to what the user said in a concise, funny, creative and helpful way. " - "Use `` tags to identify different speakers - do not use tags in your replies." - ), - }, - ] - - context = LLMContext(messages) + context = LLMContext() user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()), @@ -139,7 +129,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): async def on_client_connected(transport, client): logger.info(f"Client connected") # Kick off the conversation. - messages.append({"role": "system", "content": "Say a short hello to the user."}) + context.add_message({"role": "system", "content": "Say a short hello to the user."}) await task.queue_frames([LLMRunFrame()]) @transport.event_handler("on_client_disconnected") diff --git a/examples/foundational/07b-interruptible-langchain.py b/examples/foundational/07b-interruptible-langchain.py index 21290b576..e7a5dc1b8 100644 --- a/examples/foundational/07b-interruptible-langchain.py +++ b/examples/foundational/07b-interruptible-langchain.py @@ -28,7 +28,7 @@ from pipecat.processors.aggregators.llm_response_universal import ( from pipecat.processors.frameworks.langchain import LangchainProcessor from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport -from pipecat.services.cartesia.tts import CartesiaTTSService +from pipecat.services.cartesia.tts import CartesiaTTSService, CartesiaTTSSettings from pipecat.services.deepgram.stt import DeepgramSTTService from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams @@ -71,7 +71,9 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): tts = CartesiaTTSService( api_key=os.getenv("CARTESIA_API_KEY"), - voice_id="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady + settings=CartesiaTTSSettings( + voice="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady + ), ) prompt = ChatPromptTemplate.from_messages( diff --git a/examples/foundational/07c-interruptible-deepgram-flux.py b/examples/foundational/07c-interruptible-deepgram-flux.py index 3f2d6e28d..4eafc24a7 100644 --- a/examples/foundational/07c-interruptible-deepgram-flux.py +++ b/examples/foundational/07c-interruptible-deepgram-flux.py @@ -22,8 +22,8 @@ from pipecat.processors.aggregators.llm_response_universal import ( ) from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport -from pipecat.services.deepgram.flux.stt import DeepgramFluxSTTService -from pipecat.services.deepgram.tts import DeepgramTTSService +from pipecat.services.deepgram.flux.stt import DeepgramFluxSTTService, DeepgramFluxSTTSettings +from pipecat.services.deepgram.tts import DeepgramTTSService, DeepgramTTSSettings from pipecat.services.openai.llm import OpenAILLMService from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams @@ -56,10 +56,17 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): stt = DeepgramFluxSTTService( api_key=os.getenv("DEEPGRAM_API_KEY"), - params=DeepgramFluxSTTService.InputParams(min_confidence=0.3), + settings=DeepgramFluxSTTSettings( + min_confidence=0.3, + ), ) - tts = DeepgramTTSService(api_key=os.getenv("DEEPGRAM_API_KEY"), voice="aura-2-andromeda-en") + tts = DeepgramTTSService( + api_key=os.getenv("DEEPGRAM_API_KEY"), + settings=DeepgramTTSSettings( + voice="aura-2-andromeda-en", + ), + ) llm = OpenAILLMService( api_key=os.getenv("OPENAI_API_KEY"), diff --git a/examples/foundational/07c-interruptible-deepgram-http.py b/examples/foundational/07c-interruptible-deepgram-http.py index 6955ccbd1..e6281fbc5 100644 --- a/examples/foundational/07c-interruptible-deepgram-http.py +++ b/examples/foundational/07c-interruptible-deepgram-http.py @@ -24,7 +24,7 @@ from pipecat.processors.aggregators.llm_response_universal import ( from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport from pipecat.services.deepgram.stt import DeepgramSTTService -from pipecat.services.deepgram.tts import DeepgramHttpTTSService +from pipecat.services.deepgram.tts import DeepgramHttpTTSService, DeepgramTTSSettings from pipecat.services.openai.llm import OpenAILLMService from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams @@ -59,7 +59,9 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): tts = DeepgramHttpTTSService( api_key=os.getenv("DEEPGRAM_API_KEY"), - voice="aura-2-andromeda-en", + settings=DeepgramTTSSettings( + voice="aura-2-andromeda-en", + ), aiohttp_session=session, ) @@ -68,9 +70,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", ) - messages = [] - - context = LLMContext(messages) + context = LLMContext() user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()), diff --git a/examples/foundational/07c-interruptible-deepgram-vad.py b/examples/foundational/07c-interruptible-deepgram-vad.py index aaa81fc90..81acad665 100644 --- a/examples/foundational/07c-interruptible-deepgram-vad.py +++ b/examples/foundational/07c-interruptible-deepgram-vad.py @@ -7,7 +7,6 @@ import os -from deepgram import LiveOptions from dotenv import load_dotenv from loguru import logger @@ -22,8 +21,8 @@ from pipecat.processors.aggregators.llm_response_universal import ( ) from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport -from pipecat.services.deepgram.stt import DeepgramSTTService -from pipecat.services.deepgram.tts import DeepgramTTSService +from pipecat.services.deepgram.stt import DeepgramSTTService, DeepgramSTTSettings +from pipecat.services.deepgram.tts import DeepgramTTSService, DeepgramTTSSettings from pipecat.services.openai.llm import OpenAILLMService from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams @@ -56,10 +55,18 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): stt = DeepgramSTTService( api_key=os.getenv("DEEPGRAM_API_KEY"), - live_options=LiveOptions(vad_events=True, utterance_end_ms="1000"), + settings=DeepgramSTTSettings( + vad_events=True, + utterance_end_ms="1000", + ), ) - tts = DeepgramTTSService(api_key=os.getenv("DEEPGRAM_API_KEY"), voice="aura-2-andromeda-en") + tts = DeepgramTTSService( + api_key=os.getenv("DEEPGRAM_API_KEY"), + settings=DeepgramTTSSettings( + voice="aura-2-andromeda-en", + ), + ) llm = OpenAILLMService( api_key=os.getenv("OPENAI_API_KEY"), diff --git a/examples/foundational/07c-interruptible-deepgram.py b/examples/foundational/07c-interruptible-deepgram.py index 1cbfc72cc..d33a19d56 100644 --- a/examples/foundational/07c-interruptible-deepgram.py +++ b/examples/foundational/07c-interruptible-deepgram.py @@ -23,7 +23,7 @@ from pipecat.processors.aggregators.llm_response_universal import ( from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport from pipecat.services.deepgram.stt import DeepgramSTTService -from pipecat.services.deepgram.tts import DeepgramTTSService +from pipecat.services.deepgram.tts import DeepgramTTSService, DeepgramTTSSettings from pipecat.services.openai.llm import OpenAILLMService from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams @@ -55,7 +55,12 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): stt = DeepgramSTTService(api_key=os.getenv("DEEPGRAM_API_KEY")) - tts = DeepgramTTSService(api_key=os.getenv("DEEPGRAM_API_KEY"), voice="aura-2-andromeda-en") + tts = DeepgramTTSService( + api_key=os.getenv("DEEPGRAM_API_KEY"), + settings=DeepgramTTSSettings( + voice="aura-2-andromeda-en", + ), + ) llm = OpenAILLMService( api_key=os.getenv("OPENAI_API_KEY"), diff --git a/examples/foundational/07d-interruptible-elevenlabs-http.py b/examples/foundational/07d-interruptible-elevenlabs-http.py index 85cffc270..0dd95900c 100644 --- a/examples/foundational/07d-interruptible-elevenlabs-http.py +++ b/examples/foundational/07d-interruptible-elevenlabs-http.py @@ -24,7 +24,7 @@ from pipecat.processors.aggregators.llm_response_universal import ( from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport from pipecat.services.elevenlabs.stt import ElevenLabsSTTService -from pipecat.services.elevenlabs.tts import ElevenLabsHttpTTSService +from pipecat.services.elevenlabs.tts import ElevenLabsHttpTTSService, ElevenLabsHttpTTSSettings from pipecat.services.openai.llm import OpenAILLMService from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams @@ -63,8 +63,10 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): tts = ElevenLabsHttpTTSService( api_key=os.getenv("ELEVENLABS_API_KEY", ""), - voice_id=os.getenv("ELEVENLABS_VOICE_ID", ""), aiohttp_session=session, + settings=ElevenLabsHttpTTSSettings( + voice=os.getenv("ELEVENLABS_VOICE_ID", ""), + ), ) llm = OpenAILLMService( diff --git a/examples/foundational/07d-interruptible-elevenlabs.py b/examples/foundational/07d-interruptible-elevenlabs.py index b55345f33..c4f31ac9b 100644 --- a/examples/foundational/07d-interruptible-elevenlabs.py +++ b/examples/foundational/07d-interruptible-elevenlabs.py @@ -23,7 +23,7 @@ from pipecat.processors.aggregators.llm_response_universal import ( from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport from pipecat.services.elevenlabs.stt import ElevenLabsRealtimeSTTService -from pipecat.services.elevenlabs.tts import ElevenLabsTTSService +from pipecat.services.elevenlabs.tts import ElevenLabsTTSService, ElevenLabsTTSSettings from pipecat.services.openai.llm import OpenAILLMService from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams @@ -57,7 +57,9 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): tts = ElevenLabsTTSService( api_key=os.getenv("ELEVENLABS_API_KEY", ""), - voice_id=os.getenv("ELEVENLABS_VOICE_ID", ""), + settings=ElevenLabsTTSSettings( + voice=os.getenv("ELEVENLABS_VOICE_ID", ""), + ), ) llm = OpenAILLMService( diff --git a/examples/foundational/07g-interruptible-openai.py b/examples/foundational/07g-interruptible-openai.py index a29e8210f..86b6c9267 100644 --- a/examples/foundational/07g-interruptible-openai.py +++ b/examples/foundational/07g-interruptible-openai.py @@ -23,8 +23,8 @@ from pipecat.processors.aggregators.llm_response_universal import ( from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport from pipecat.services.openai.llm import OpenAILLMService -from pipecat.services.openai.stt import OpenAIRealtimeSTTService -from pipecat.services.openai.tts import OpenAITTSService +from pipecat.services.openai.stt import OpenAIRealtimeSTTService, OpenAIRealtimeSTTSettings +from pipecat.services.openai.tts import OpenAITTSService, OpenAITTSSettings from pipecat.transcriptions.language import Language from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams @@ -55,16 +55,19 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): stt = OpenAIRealtimeSTTService( api_key=os.getenv("OPENAI_API_KEY"), - model="gpt-4o-transcribe", - prompt="Expect words related to dogs, such as breed names.", - language=Language.EN, - # Uses local VAD by default. - # To enable server-side VAD, set turn_detection=None or - # a dict with server_vad settings. - # turn_detection={"type": "server_vad", "threshold": 0.5}, + settings=OpenAIRealtimeSTTSettings( + model="gpt-4o-transcribe", + prompt="Expect words related to dogs, such as breed names.", + language=Language.EN, + ), ) - tts = OpenAITTSService(api_key=os.getenv("OPENAI_API_KEY"), voice="ballad") + tts = OpenAITTSService( + api_key=os.getenv("OPENAI_API_KEY"), + settings=OpenAITTSSettings( + voice="ballad", + ), + ) llm = OpenAILLMService( api_key=os.getenv("OPENAI_API_KEY"), diff --git a/examples/foundational/07h-interruptible-openpipe.py b/examples/foundational/07h-interruptible-openpipe.py index e3ddc05b8..6dbf04296 100644 --- a/examples/foundational/07h-interruptible-openpipe.py +++ b/examples/foundational/07h-interruptible-openpipe.py @@ -23,7 +23,7 @@ from pipecat.processors.aggregators.llm_response_universal import ( ) from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport -from pipecat.services.cartesia.tts import CartesiaTTSService +from pipecat.services.cartesia.tts import CartesiaTTSService, CartesiaTTSSettings from pipecat.services.deepgram.stt import DeepgramSTTService from pipecat.services.openpipe.llm import OpenPipeLLMService from pipecat.transports.base_transport import BaseTransport, TransportParams @@ -57,7 +57,9 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): tts = CartesiaTTSService( api_key=os.getenv("CARTESIA_API_KEY"), - voice_id="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady + settings=CartesiaTTSSettings( + voice="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady + ), ) timestamp = int(time.time()) diff --git a/examples/foundational/07i-interruptible-xtts.py b/examples/foundational/07i-interruptible-xtts.py index 00883e37f..6837917aa 100644 --- a/examples/foundational/07i-interruptible-xtts.py +++ b/examples/foundational/07i-interruptible-xtts.py @@ -25,7 +25,7 @@ from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport from pipecat.services.deepgram.stt import DeepgramSTTService from pipecat.services.openai.llm import OpenAILLMService -from pipecat.services.xtts.tts import XTTSService +from pipecat.services.xtts.tts import XTTSService, XTTSSettings from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams @@ -59,7 +59,9 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): tts = XTTSService( aiohttp_session=session, - voice_id="Claribel Dervla", + settings=XTTSSettings( + voice="Claribel Dervla", + ), base_url="http://localhost:8000", ) diff --git a/examples/foundational/07j-interruptible-gladia-vad.py b/examples/foundational/07j-interruptible-gladia-vad.py index f0874f0f3..2983e1605 100644 --- a/examples/foundational/07j-interruptible-gladia-vad.py +++ b/examples/foundational/07j-interruptible-gladia-vad.py @@ -22,9 +22,9 @@ from pipecat.processors.aggregators.llm_response_universal import ( ) from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport -from pipecat.services.cartesia.tts import CartesiaTTSService -from pipecat.services.gladia.config import GladiaInputParams, LanguageConfig -from pipecat.services.gladia.stt import GladiaSTTService +from pipecat.services.cartesia.tts import CartesiaTTSService, CartesiaTTSSettings +from pipecat.services.gladia.config import LanguageConfig +from pipecat.services.gladia.stt import GladiaSTTService, GladiaSTTSettings from pipecat.services.openai.llm import OpenAILLMService from pipecat.transcriptions.language import Language from pipecat.transports.base_transport import BaseTransport, TransportParams @@ -58,7 +58,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): stt = GladiaSTTService( api_key=os.getenv("GLADIA_API_KEY", ""), region=os.getenv("GLADIA_REGION"), - params=GladiaInputParams( + settings=GladiaSTTSettings( language_config=LanguageConfig( languages=[Language.EN], ), @@ -68,19 +68,17 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): tts = CartesiaTTSService( api_key=os.getenv("CARTESIA_API_KEY", ""), - voice_id="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady + settings=CartesiaTTSSettings( + voice="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady + ), ) - llm = OpenAILLMService(api_key=os.getenv("OPENAI_API_KEY", "")) + llm = OpenAILLMService( + api_key=os.getenv("OPENAI_API_KEY", ""), + system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + ) - messages = [ - { - "role": "system", - "content": f"You are a helpful LLM. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", - }, - ] - - context = LLMContext(messages) + context = LLMContext() user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, user_params=LLMUserAggregatorParams( @@ -114,7 +112,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): async def on_client_connected(transport, client): logger.info(f"Client connected") # Kick off the conversation. - messages.append({"role": "system", "content": "Please introduce yourself to the user."}) + context.add_message({"role": "system", "content": "Please introduce yourself to the user."}) await task.queue_frames([LLMRunFrame()]) @transport.event_handler("on_client_disconnected") diff --git a/examples/foundational/07j-interruptible-gladia.py b/examples/foundational/07j-interruptible-gladia.py index 4bebffce7..5dca15834 100644 --- a/examples/foundational/07j-interruptible-gladia.py +++ b/examples/foundational/07j-interruptible-gladia.py @@ -22,9 +22,9 @@ from pipecat.processors.aggregators.llm_response_universal import ( ) from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport -from pipecat.services.cartesia.tts import CartesiaTTSService -from pipecat.services.gladia.config import GladiaInputParams, LanguageConfig -from pipecat.services.gladia.stt import GladiaSTTService +from pipecat.services.cartesia.tts import CartesiaTTSService, CartesiaTTSSettings +from pipecat.services.gladia.config import LanguageConfig +from pipecat.services.gladia.stt import GladiaSTTService, GladiaSTTSettings from pipecat.services.openai.llm import OpenAILLMService from pipecat.transcriptions.language import Language from pipecat.transports.base_transport import BaseTransport, TransportParams @@ -57,7 +57,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): stt = GladiaSTTService( api_key=os.getenv("GLADIA_API_KEY", ""), region=os.getenv("GLADIA_REGION"), - params=GladiaInputParams( + settings=GladiaSTTSettings( language_config=LanguageConfig( languages=[Language.EN], ) @@ -66,19 +66,17 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): tts = CartesiaTTSService( api_key=os.getenv("CARTESIA_API_KEY", ""), - voice_id="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady + settings=CartesiaTTSSettings( + voice="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady + ), ) - llm = OpenAILLMService(api_key=os.getenv("OPENAI_API_KEY", "")) + llm = OpenAILLMService( + api_key=os.getenv("OPENAI_API_KEY", ""), + system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + ) - messages = [ - { - "role": "system", - "content": f"You are a helpful LLM. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", - }, - ] - - context = LLMContext(messages) + context = LLMContext() user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()), @@ -109,7 +107,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): async def on_client_connected(transport, client): logger.info(f"Client connected") # Kick off the conversation. - messages.append({"role": "system", "content": "Please introduce yourself to the user."}) + context.add_message({"role": "system", "content": "Please introduce yourself to the user."}) await task.queue_frames([LLMRunFrame()]) @transport.event_handler("on_client_disconnected") diff --git a/examples/foundational/07k-interruptible-lmnt.py b/examples/foundational/07k-interruptible-lmnt.py index 246caee19..debf186b1 100644 --- a/examples/foundational/07k-interruptible-lmnt.py +++ b/examples/foundational/07k-interruptible-lmnt.py @@ -23,7 +23,7 @@ from pipecat.processors.aggregators.llm_response_universal import ( from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport from pipecat.services.deepgram.stt import DeepgramSTTService -from pipecat.services.lmnt.tts import LmntTTSService +from pipecat.services.lmnt.tts import LmntTTSService, LmntTTSSettings from pipecat.services.openai.llm import OpenAILLMService from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams @@ -54,7 +54,12 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): stt = DeepgramSTTService(api_key=os.getenv("DEEPGRAM_API_KEY")) - tts = LmntTTSService(api_key=os.getenv("LMNT_API_KEY"), voice_id="morgan") + tts = LmntTTSService( + api_key=os.getenv("LMNT_API_KEY"), + settings=LmntTTSSettings( + voice="morgan", + ), + ) llm = OpenAILLMService( api_key=os.getenv("OPENAI_API_KEY"), diff --git a/examples/foundational/07l-interruptible-groq.py b/examples/foundational/07l-interruptible-groq.py index 5a16d789e..dd532b71c 100644 --- a/examples/foundational/07l-interruptible-groq.py +++ b/examples/foundational/07l-interruptible-groq.py @@ -22,7 +22,7 @@ from pipecat.processors.aggregators.llm_response_universal import ( ) from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport -from pipecat.services.groq.llm import GroqLLMService +from pipecat.services.groq.llm import GroqLLMService, GroqLLMSettings from pipecat.services.groq.stt import GroqSTTService from pipecat.services.groq.tts import GroqTTSService from pipecat.transports.base_transport import BaseTransport, TransportParams @@ -56,7 +56,9 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): llm = GroqLLMService( api_key=os.getenv("GROQ_API_KEY"), - model="meta-llama/llama-4-maverick-17b-128e-instruct", + settings=GroqLLMSettings( + model="meta-llama/llama-4-maverick-17b-128e-instruct", + ), system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", ) diff --git a/examples/foundational/07m-interruptible-aws-strands.py b/examples/foundational/07m-interruptible-aws-strands.py index 2e0fc18d8..c65709a7b 100644 --- a/examples/foundational/07m-interruptible-aws-strands.py +++ b/examples/foundational/07m-interruptible-aws-strands.py @@ -22,7 +22,7 @@ from pipecat.processors.frameworks.strands_agents import StrandsAgentsProcessor from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport from pipecat.services.aws.stt import AWSTranscribeSTTService -from pipecat.services.aws.tts import AWSPollyTTSService +from pipecat.services.aws.tts import AWSPollyTTSService, AWSPollyTTSSettings from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams @@ -95,8 +95,11 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): tts = AWSPollyTTSService( region="us-west-2", # only specific regions support generative TTS - voice_id="Joanna", - params=AWSPollyTTSService.InputParams(engine="generative", rate="1.1"), + settings=AWSPollyTTSSettings( + voice="Joanna", + engine="generative", + rate="1.1", + ), ) # Create Strands agent processor diff --git a/examples/foundational/07m-interruptible-aws.py b/examples/foundational/07m-interruptible-aws.py index b30220bcd..48a632a35 100644 --- a/examples/foundational/07m-interruptible-aws.py +++ b/examples/foundational/07m-interruptible-aws.py @@ -22,7 +22,7 @@ from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport from pipecat.services.aws.llm import AWSBedrockLLMService from pipecat.services.aws.stt import AWSTranscribeSTTService -from pipecat.services.aws.tts import AWSPollyTTSService +from pipecat.services.aws.tts import AWSPollyTTSService, AWSPollyTTSSettings from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams @@ -54,8 +54,11 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): tts = AWSPollyTTSService( region="us-west-2", # only specific regions support generative TTS - voice_id="Joanna", - params=AWSPollyTTSService.InputParams(engine="generative", rate="1.1"), + settings=AWSPollyTTSSettings( + voice="Joanna", + engine="generative", + rate="1.1", + ), ) llm = AWSBedrockLLMService( diff --git a/examples/foundational/07n-interruptible-gemini-image.py b/examples/foundational/07n-interruptible-gemini-image.py index b7d3281b9..2b1d191c4 100644 --- a/examples/foundational/07n-interruptible-gemini-image.py +++ b/examples/foundational/07n-interruptible-gemini-image.py @@ -37,9 +37,9 @@ from pipecat.processors.aggregators.llm_response_universal import ( ) from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport -from pipecat.services.google.llm import GoogleLLMService -from pipecat.services.google.stt import GoogleSTTService -from pipecat.services.google.tts import GoogleTTSService +from pipecat.services.google.llm import GoogleLLMService, GoogleLLMSettings +from pipecat.services.google.stt import GoogleSTTService, GoogleSTTSettings +from pipecat.services.google.tts import GoogleTTSService, GoogleTTSSettings from pipecat.transcriptions.language import Language from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams @@ -70,20 +70,26 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): logger.info(f"Starting bot") stt = GoogleSTTService( - params=GoogleSTTService.InputParams(languages=Language.EN_US), credentials=os.getenv("GOOGLE_TEST_CREDENTIALS"), + settings=GoogleSTTSettings( + languages=Language.EN_US, + ), ) tts = GoogleTTSService( - voice_id="en-US-Chirp3-HD-Charon", - params=GoogleTTSService.InputParams(language=Language.EN_US), credentials=os.getenv("GOOGLE_TEST_CREDENTIALS"), + settings=GoogleTTSSettings( + voice="en-US-Chirp3-HD-Charon", + language=Language.EN_US, + ), ) llm = GoogleLLMService( api_key=os.getenv("GOOGLE_API_KEY"), - model="gemini-2.5-flash-image", - # model="gemini-3-pro-image-preview", # A more powerful model, but slower, + settings=GoogleLLMSettings( + model="gemini-2.5-flash-image", + # model="gemini-3-pro-image-preview", # A more powerful model, but slower, + ), system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", ) diff --git a/examples/foundational/07n-interruptible-gemini.py b/examples/foundational/07n-interruptible-gemini.py index 74f732926..7a631f473 100644 --- a/examples/foundational/07n-interruptible-gemini.py +++ b/examples/foundational/07n-interruptible-gemini.py @@ -23,8 +23,8 @@ from pipecat.processors.aggregators.llm_response_universal import ( from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport from pipecat.services.google.llm import GoogleLLMService -from pipecat.services.google.stt import GoogleSTTService -from pipecat.services.google.tts import GeminiTTSService +from pipecat.services.google.stt import GoogleSTTService, GoogleSTTSettings +from pipecat.services.google.tts import GeminiTTSService, GeminiTTSSettings from pipecat.transcriptions.language import Language from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams @@ -54,15 +54,17 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): logger.info(f"Starting bot with Gemini TTS") stt = GoogleSTTService( - params=GoogleSTTService.InputParams(languages=Language.EN_US), + settings=GoogleSTTSettings( + languages=Language.EN_US, + ), credentials=os.getenv("GOOGLE_TEST_CREDENTIALS"), ) tts = GeminiTTSService( credentials=os.getenv("GOOGLE_TEST_CREDENTIALS"), - model="gemini-2.5-flash-tts", - voice_id="Charon", - params=GeminiTTSService.InputParams( + settings=GeminiTTSSettings( + model="gemini-2.5-flash-tts", + voice="Charon", language=Language.EN_US, prompt="You are a helpful AI assistant. Speak in a natural, conversational tone.", ), diff --git a/examples/foundational/07n-interruptible-google-http.py b/examples/foundational/07n-interruptible-google-http.py index e5f82ffc5..1f570366a 100644 --- a/examples/foundational/07n-interruptible-google-http.py +++ b/examples/foundational/07n-interruptible-google-http.py @@ -22,9 +22,9 @@ from pipecat.processors.aggregators.llm_response_universal import ( ) from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport -from pipecat.services.google.llm import GoogleLLMService -from pipecat.services.google.stt import GoogleSTTService -from pipecat.services.google.tts import GoogleHttpTTSService +from pipecat.services.google.llm import GoogleLLMService, GoogleLLMSettings +from pipecat.services.google.stt import GoogleSTTService, GoogleSTTSettings +from pipecat.services.google.tts import GoogleHttpTTSService, GoogleHttpTTSSettings from pipecat.transcriptions.language import Language from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams @@ -54,24 +54,29 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): logger.info(f"Starting bot") stt = GoogleSTTService( - params=GoogleSTTService.InputParams(languages=Language.EN_US, model="chirp_3"), + settings=GoogleSTTSettings( + languages=Language.EN_US, + model="chirp_3", + ), credentials=os.getenv("GOOGLE_TEST_CREDENTIALS"), location="us", ) tts = GoogleHttpTTSService( - voice_id="en-US-Chirp3-HD-Charon", - params=GoogleHttpTTSService.InputParams(language=Language.EN_US), + settings=GoogleHttpTTSSettings( + voice="en-US-Chirp3-HD-Charon", + language=Language.EN_US, + ), credentials=os.getenv("GOOGLE_TEST_CREDENTIALS"), ) llm = GoogleLLMService( api_key=os.getenv("GOOGLE_API_KEY"), - model="gemini-2.5-flash", - # force a certain amount of thinking if you want it - # params=GoogleLLMService.InputParams( - # thinking=GoogleLLMService.ThinkingConfig(thinking_budget=4096) - # ), + settings=GoogleLLMSettings( + model="gemini-2.5-flash", + # force a certain amount of thinking if you want it + # thinking=GoogleLLMService.ThinkingConfig(thinking_budget=4096) + ), system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", ) diff --git a/examples/foundational/07n-interruptible-google.py b/examples/foundational/07n-interruptible-google.py index 090fdbbdc..439676238 100644 --- a/examples/foundational/07n-interruptible-google.py +++ b/examples/foundational/07n-interruptible-google.py @@ -22,9 +22,9 @@ from pipecat.processors.aggregators.llm_response_universal import ( ) from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport -from pipecat.services.google.llm import GoogleLLMService -from pipecat.services.google.stt import GoogleSTTService -from pipecat.services.google.tts import GoogleTTSService +from pipecat.services.google.llm import GoogleLLMService, GoogleLLMSettings +from pipecat.services.google.stt import GoogleSTTService, GoogleSTTSettings +from pipecat.services.google.tts import GoogleTTSService, GoogleTTSSettings from pipecat.transcriptions.language import Language from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams @@ -54,24 +54,29 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): logger.info(f"Starting bot") stt = GoogleSTTService( - params=GoogleSTTService.InputParams(languages=Language.EN_US, model="chirp_3"), + settings=GoogleSTTSettings( + languages=Language.EN_US, + model="chirp_3", + ), credentials=os.getenv("GOOGLE_TEST_CREDENTIALS"), location="us", ) tts = GoogleTTSService( - voice_id="en-US-Chirp3-HD-Charon", - params=GoogleTTSService.InputParams(language=Language.EN_US), + settings=GoogleTTSSettings( + voice="en-US-Chirp3-HD-Charon", + language=Language.EN_US, + ), credentials=os.getenv("GOOGLE_TEST_CREDENTIALS"), ) llm = GoogleLLMService( api_key=os.getenv("GOOGLE_API_KEY"), - model="gemini-2.5-flash", - # force a certain amount of thinking if you want it - # params=GoogleLLMService.InputParams( - # thinking=GoogleLLMService.ThinkingConfig(thinking_budget=4096) - # ), + settings=GoogleLLMSettings( + model="gemini-2.5-flash", + # force a certain amount of thinking if you want it + # thinking=GoogleLLMService.ThinkingConfig(thinking_budget=4096), + ), system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", ) diff --git a/examples/foundational/07o-interruptible-assemblyai-turn-detection.py b/examples/foundational/07o-interruptible-assemblyai-turn-detection.py index 7a0226277..6f2ec36f2 100644 --- a/examples/foundational/07o-interruptible-assemblyai-turn-detection.py +++ b/examples/foundational/07o-interruptible-assemblyai-turn-detection.py @@ -22,9 +22,8 @@ from pipecat.processors.aggregators.llm_response_universal import ( ) from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport -from pipecat.services.assemblyai.models import AssemblyAIConnectionParams -from pipecat.services.assemblyai.stt import AssemblyAISTTService -from pipecat.services.cartesia.tts import CartesiaTTSService +from pipecat.services.assemblyai.stt import AssemblyAISTTService, AssemblyAISTTSettings +from pipecat.services.cartesia.tts import CartesiaTTSService, CartesiaTTSSettings from pipecat.services.openai.llm import OpenAILLMService from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams @@ -94,7 +93,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): stt = AssemblyAISTTService( api_key=os.getenv("ASSEMBLYAI_API_KEY"), vad_force_turn_endpoint=False, # Use AssemblyAI's built-in turn detection - connection_params=AssemblyAIConnectionParams( + settings=AssemblyAISTTSettings( speech_model="u3-rt-pro", # Optional: Tune turn detection timing (defaults shown below) # min_turn_silence=100, # Default @@ -108,7 +107,9 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): tts = CartesiaTTSService( api_key=os.getenv("CARTESIA_API_KEY"), - voice_id="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady + settings=CartesiaTTSSettings( + voice="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady + ), ) llm = OpenAILLMService( diff --git a/examples/foundational/07o-interruptible-assemblyai.py b/examples/foundational/07o-interruptible-assemblyai.py index 8378f7bba..10d6a8cd4 100644 --- a/examples/foundational/07o-interruptible-assemblyai.py +++ b/examples/foundational/07o-interruptible-assemblyai.py @@ -23,7 +23,7 @@ from pipecat.processors.aggregators.llm_response_universal import ( from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport from pipecat.services.assemblyai.stt import AssemblyAISTTService -from pipecat.services.cartesia.tts import CartesiaTTSService +from pipecat.services.cartesia.tts import CartesiaTTSService, CartesiaTTSSettings from pipecat.services.openai.llm import OpenAILLMService from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams @@ -59,7 +59,9 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): tts = CartesiaTTSService( api_key=os.getenv("CARTESIA_API_KEY"), - voice_id="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady + settings=CartesiaTTSSettings( + voice="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady + ), ) llm = OpenAILLMService( diff --git a/examples/foundational/07p-interruptible-krisp-viva.py b/examples/foundational/07p-interruptible-krisp-viva.py index 4df652ae0..1b10202f3 100644 --- a/examples/foundational/07p-interruptible-krisp-viva.py +++ b/examples/foundational/07p-interruptible-krisp-viva.py @@ -43,7 +43,7 @@ from pipecat.processors.aggregators.llm_response_universal import ( ) from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport -from pipecat.services.cartesia.tts import CartesiaTTSService +from pipecat.services.cartesia.tts import CartesiaTTSService, CartesiaTTSSettings from pipecat.services.deepgram.stt import DeepgramSTTService from pipecat.services.openai.llm import OpenAILLMService from pipecat.transports.base_transport import BaseTransport, TransportParams @@ -84,7 +84,10 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): stt = DeepgramSTTService(api_key=os.getenv("DEEPGRAM_API_KEY")) tts = CartesiaTTSService( - api_key=os.getenv("CARTESIA_API_KEY"), voice_id="71a7ad14-091c-4e8e-a314-022ece01c121" + api_key=os.getenv("CARTESIA_API_KEY"), + settings=CartesiaTTSSettings( + voice="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady + ), ) llm = OpenAILLMService( diff --git a/examples/foundational/07p-interruptible-krisp.py b/examples/foundational/07p-interruptible-krisp.py index ad737ba05..54d88d32a 100644 --- a/examples/foundational/07p-interruptible-krisp.py +++ b/examples/foundational/07p-interruptible-krisp.py @@ -24,7 +24,7 @@ from pipecat.processors.aggregators.llm_response_universal import ( from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport from pipecat.services.deepgram.stt import DeepgramSTTService -from pipecat.services.deepgram.tts import DeepgramTTSService +from pipecat.services.deepgram.tts import DeepgramTTSService, DeepgramTTSSettings from pipecat.services.openai.llm import OpenAILLMService from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams @@ -58,7 +58,12 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): stt = DeepgramSTTService(api_key=os.getenv("DEEPGRAM_API_KEY")) - tts = DeepgramTTSService(api_key=os.getenv("DEEPGRAM_API_KEY"), voice="aura-helios-en") + tts = DeepgramTTSService( + api_key=os.getenv("DEEPGRAM_API_KEY"), + settings=DeepgramTTSSettings( + voice="aura-helios-en", + ), + ) llm = OpenAILLMService( api_key=os.getenv("OPENAI_API_KEY"), diff --git a/examples/foundational/07q-interruptible-rime-http.py b/examples/foundational/07q-interruptible-rime-http.py index 4e390b123..c735e39c9 100644 --- a/examples/foundational/07q-interruptible-rime-http.py +++ b/examples/foundational/07q-interruptible-rime-http.py @@ -25,7 +25,7 @@ from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport from pipecat.services.deepgram.stt import DeepgramSTTService from pipecat.services.openai.llm import OpenAILLMService -from pipecat.services.rime.tts import RimeHttpTTSService +from pipecat.services.rime.tts import RimeHttpTTSService, RimeTTSSettings from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams @@ -60,7 +60,10 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): tts = RimeHttpTTSService( api_key=os.getenv("RIME_API_KEY", ""), - voice_id="luna", + settings=RimeTTSSettings( + voice="luna", + model="arcana", + ), model="arcana", aiohttp_session=session, ) diff --git a/examples/foundational/07q-interruptible-rime.py b/examples/foundational/07q-interruptible-rime.py index cebf6bfd0..dbc6b91e6 100644 --- a/examples/foundational/07q-interruptible-rime.py +++ b/examples/foundational/07q-interruptible-rime.py @@ -24,7 +24,7 @@ from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport from pipecat.services.deepgram.stt import DeepgramSTTService from pipecat.services.openai.llm import OpenAILLMService -from pipecat.services.rime.tts import RimeTTSService +from pipecat.services.rime.tts import RimeTTSService, RimeTTSSettings from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams @@ -56,7 +56,9 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): tts = RimeTTSService( api_key=os.getenv("RIME_API_KEY", ""), - voice_id="luna", + settings=RimeTTSSettings( + voice="luna", + ), ) llm = OpenAILLMService( diff --git a/examples/foundational/07r-interruptible-nvidia.py b/examples/foundational/07r-interruptible-nvidia.py index f50667267..69a5fbc15 100644 --- a/examples/foundational/07r-interruptible-nvidia.py +++ b/examples/foundational/07r-interruptible-nvidia.py @@ -22,7 +22,7 @@ from pipecat.processors.aggregators.llm_response_universal import ( ) from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport -from pipecat.services.nvidia.llm import NvidiaLLMService +from pipecat.services.nvidia.llm import NvidiaLLMService, NvidiaLLMSettings from pipecat.services.nvidia.stt import NvidiaSTTService from pipecat.services.nvidia.tts import NvidiaTTSService from pipecat.transports.base_transport import BaseTransport, TransportParams @@ -56,7 +56,9 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): llm = NvidiaLLMService( api_key=os.getenv("NVIDIA_API_KEY"), - model="meta/llama-3.3-70b-instruct", + settings=NvidiaLLMSettings( + model="meta/llama-3.3-70b-instruct", + ), system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", ) diff --git a/examples/foundational/07s-interruptible-google-audio-in.py b/examples/foundational/07s-interruptible-google-audio-in.py index 1de374a3f..d4067b620 100644 --- a/examples/foundational/07s-interruptible-google-audio-in.py +++ b/examples/foundational/07s-interruptible-google-audio-in.py @@ -36,8 +36,8 @@ from pipecat.processors.aggregators.llm_response_universal import ( from pipecat.processors.frame_processor import FrameProcessor from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport -from pipecat.services.google.llm import GoogleLLMService -from pipecat.services.google.tts import GoogleTTSService +from pipecat.services.google.llm import GoogleLLMService, GoogleLLMSettings +from pipecat.services.google.tts import GoogleTTSService, GoogleTTSSettings from pipecat.transcriptions.language import Language from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams @@ -216,7 +216,9 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): llm = GoogleLLMService( api_key=os.getenv("GOOGLE_API_KEY"), - model="gemini-2.5-flash", + settings=GoogleLLMSettings( + model="gemini-2.5-flash", + ), # force a certain amount of thinking if you want it # params=GoogleLLMService.InputParams( # thinking=GoogleLLMService.ThinkingConfig(thinking_budget=4096) @@ -224,7 +226,10 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): ) tts = GoogleTTSService( - voice_id="en-US-Chirp3-HD-Charon", + settings=GoogleTTSSettings( + voice="en-US-Chirp3-HD-Charon", + language=Language.EN_US, + ), params=GoogleTTSService.InputParams(language=Language.EN_US), credentials=os.getenv("GOOGLE_TEST_CREDENTIALS"), ) diff --git a/examples/foundational/07t-interruptible-fish.py b/examples/foundational/07t-interruptible-fish.py index 8b4152103..d54d34c1c 100644 --- a/examples/foundational/07t-interruptible-fish.py +++ b/examples/foundational/07t-interruptible-fish.py @@ -23,7 +23,7 @@ from pipecat.processors.aggregators.llm_response_universal import ( from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport from pipecat.services.deepgram.stt import DeepgramSTTService -from pipecat.services.fish.tts import FishAudioTTSService +from pipecat.services.fish.tts import FishAudioTTSService, FishAudioTTSSettings from pipecat.services.openai.llm import OpenAILLMService from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams @@ -57,7 +57,9 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): tts = FishAudioTTSService( api_key=os.getenv("FISH_API_KEY"), - model="4ce7e917cedd4bc2bb2e6ff3a46acaa1", # Barack Obama + settings=FishAudioTTSSettings( + model="4ce7e917cedd4bc2bb2e6ff3a46acaa1", # Barack Obama + ), ) llm = OpenAILLMService( diff --git a/examples/foundational/07v-interruptible-neuphonic-http.py b/examples/foundational/07v-interruptible-neuphonic-http.py index 60a08e623..081d9d6cc 100644 --- a/examples/foundational/07v-interruptible-neuphonic-http.py +++ b/examples/foundational/07v-interruptible-neuphonic-http.py @@ -24,7 +24,7 @@ from pipecat.processors.aggregators.llm_response_universal import ( from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport from pipecat.services.deepgram.stt import DeepgramSTTService -from pipecat.services.neuphonic.tts import NeuphonicHttpTTSService +from pipecat.services.neuphonic.tts import NeuphonicHttpTTSService, NeuphonicTTSSettings from pipecat.services.openai.llm import OpenAILLMService from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams @@ -60,7 +60,9 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): tts = NeuphonicHttpTTSService( api_key=os.getenv("NEUPHONIC_API_KEY"), - voice_id="fc854436-2dac-4d21-aa69-ae17b54e98eb", # Emily + settings=NeuphonicTTSSettings( + voice="fc854436-2dac-4d21-aa69-ae17b54e98eb", # Emily + ), aiohttp_session=session, ) diff --git a/examples/foundational/07v-interruptible-neuphonic.py b/examples/foundational/07v-interruptible-neuphonic.py index 02d6862a8..3f30ab9c7 100644 --- a/examples/foundational/07v-interruptible-neuphonic.py +++ b/examples/foundational/07v-interruptible-neuphonic.py @@ -23,7 +23,7 @@ from pipecat.processors.aggregators.llm_response_universal import ( from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport from pipecat.services.deepgram.stt import DeepgramSTTService -from pipecat.services.neuphonic.tts import NeuphonicTTSService +from pipecat.services.neuphonic.tts import NeuphonicTTSService, NeuphonicTTSSettings from pipecat.services.openai.llm import OpenAILLMService from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams @@ -56,7 +56,9 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): tts = NeuphonicTTSService( api_key=os.getenv("NEUPHONIC_API_KEY"), - voice_id="fc854436-2dac-4d21-aa69-ae17b54e98eb", # Emily + settings=NeuphonicTTSSettings( + voice="fc854436-2dac-4d21-aa69-ae17b54e98eb", # Emily + ), ) llm = OpenAILLMService( diff --git a/examples/foundational/07w-interruptible-fal.py b/examples/foundational/07w-interruptible-fal.py index 6d88e8624..7e0e53bc9 100644 --- a/examples/foundational/07w-interruptible-fal.py +++ b/examples/foundational/07w-interruptible-fal.py @@ -23,7 +23,7 @@ from pipecat.processors.aggregators.llm_response_universal import ( ) from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport -from pipecat.services.cartesia.tts import CartesiaTTSService +from pipecat.services.cartesia.tts import CartesiaTTSService, CartesiaTTSSettings from pipecat.services.fal.stt import FalSTTService from pipecat.services.openai.llm import OpenAILLMService from pipecat.transports.base_transport import BaseTransport, TransportParams @@ -62,7 +62,9 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): tts = CartesiaTTSService( api_key=os.getenv("CARTESIA_API_KEY"), - voice_id="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady + settings=CartesiaTTSSettings( + voice="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady + ), ) llm = OpenAILLMService( diff --git a/examples/foundational/07x-interruptible-local.py b/examples/foundational/07x-interruptible-local.py index 3465f67b2..63cf2bbb1 100644 --- a/examples/foundational/07x-interruptible-local.py +++ b/examples/foundational/07x-interruptible-local.py @@ -21,7 +21,7 @@ from pipecat.processors.aggregators.llm_response_universal import ( LLMContextAggregatorPair, LLMUserAggregatorParams, ) -from pipecat.services.cartesia.tts import CartesiaTTSService +from pipecat.services.cartesia.tts import CartesiaTTSService, CartesiaTTSSettings from pipecat.services.deepgram.stt import DeepgramSTTService from pipecat.services.openai.llm import OpenAILLMService from pipecat.transports.local.audio import LocalAudioTransport, LocalAudioTransportParams @@ -44,7 +44,9 @@ async def main(): tts = CartesiaTTSService( api_key=os.getenv("CARTESIA_API_KEY"), - voice_id="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady + settings=CartesiaTTSSettings( + voice="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady + ), ) llm = OpenAILLMService( diff --git a/examples/foundational/07y-interruptible-minimax.py b/examples/foundational/07y-interruptible-minimax.py index f23d86f34..690c35178 100644 --- a/examples/foundational/07y-interruptible-minimax.py +++ b/examples/foundational/07y-interruptible-minimax.py @@ -24,7 +24,7 @@ from pipecat.processors.aggregators.llm_response_universal import ( from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport from pipecat.services.deepgram.stt import DeepgramSTTService -from pipecat.services.minimax.tts import MiniMaxHttpTTSService +from pipecat.services.minimax.tts import MiniMaxHttpTTSService, MiniMaxTTSSettings from pipecat.services.openai.llm import OpenAILLMService from pipecat.transcriptions.language import Language from pipecat.transports.base_transport import BaseTransport, TransportParams @@ -63,7 +63,9 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): api_key=os.getenv("MINIMAX_API_KEY", ""), group_id=os.getenv("MINIMAX_GROUP_ID", ""), aiohttp_session=session, - params=MiniMaxHttpTTSService.InputParams(language=Language.EN), + settings=MiniMaxTTSSettings( + language=Language.EN, + ), ) llm = OpenAILLMService( diff --git a/examples/foundational/07z-interruptible-sarvam-http.py b/examples/foundational/07z-interruptible-sarvam-http.py index 1f9a8a4e3..33f1277e6 100644 --- a/examples/foundational/07z-interruptible-sarvam-http.py +++ b/examples/foundational/07z-interruptible-sarvam-http.py @@ -25,7 +25,7 @@ from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport from pipecat.services.openai.llm import OpenAILLMService from pipecat.services.sarvam.stt import SarvamSTTService -from pipecat.services.sarvam.tts import SarvamHttpTTSService +from pipecat.services.sarvam.tts import SarvamHttpTTSService, SarvamHttpTTSSettings from pipecat.transcriptions.language import Language from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams @@ -65,7 +65,9 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): tts = SarvamHttpTTSService( api_key=os.getenv("SARVAM_API_KEY"), aiohttp_session=session, - params=SarvamHttpTTSService.InputParams(language=Language.EN), + settings=SarvamHttpTTSSettings( + language=Language.EN, + ), ) llm = OpenAILLMService( diff --git a/examples/foundational/07z-interruptible-sarvam.py b/examples/foundational/07z-interruptible-sarvam.py index a9a03e7d4..60b5bcc8b 100644 --- a/examples/foundational/07z-interruptible-sarvam.py +++ b/examples/foundational/07z-interruptible-sarvam.py @@ -22,8 +22,8 @@ from pipecat.processors.aggregators.llm_response_universal import ( from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport from pipecat.services.openai.llm import OpenAILLMService -from pipecat.services.sarvam.stt import SarvamSTTService -from pipecat.services.sarvam.tts import SarvamTTSService +from pipecat.services.sarvam.stt import SarvamSTTService, SarvamSTTSettings +from pipecat.services.sarvam.tts import SarvamTTSService, SarvamTTSSettings from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams @@ -54,13 +54,17 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): stt = SarvamSTTService( api_key=os.getenv("SARVAM_API_KEY"), - model="saarika:v2.5", + settings=SarvamSTTSettings( + model="saarika:v2.5", + ), ) tts = SarvamTTSService( api_key=os.getenv("SARVAM_API_KEY"), - model="bulbul:v2", - voice_id="manisha", + settings=SarvamTTSSettings( + model="bulbul:v2", + voice="manisha", + ), ) llm = OpenAILLMService( api_key=os.getenv("OPENAI_API_KEY"), diff --git a/examples/foundational/07za-interruptible-soniox.py b/examples/foundational/07za-interruptible-soniox.py index f2d651e5b..56b2dee1e 100644 --- a/examples/foundational/07za-interruptible-soniox.py +++ b/examples/foundational/07za-interruptible-soniox.py @@ -22,9 +22,9 @@ from pipecat.processors.aggregators.llm_response_universal import ( ) from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport -from pipecat.services.cartesia.tts import CartesiaTTSService +from pipecat.services.cartesia.tts import CartesiaTTSService, CartesiaTTSSettings from pipecat.services.openai.llm import OpenAILLMService -from pipecat.services.soniox.stt import SonioxInputParams, SonioxSTTService +from pipecat.services.soniox.stt import SonioxSTTService, SonioxSTTSettings from pipecat.transcriptions.language import Language from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams @@ -51,17 +51,21 @@ transport_params = { async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): logger.info(f"Starting bot") - stt = SonioxSTTService( - api_key=os.getenv("SONIOX_API_KEY"), - params=SonioxInputParams( - language_hints=[Language.EN], - language_hints_strict=True, + stt = ( + SonioxSTTService( + api_key=os.getenv("SONIOX_API_KEY"), + settings=SonioxSTTSettings( + language_hints=[Language.EN], + language_hints_strict=True, + ), ), ) tts = CartesiaTTSService( api_key=os.getenv("CARTESIA_API_KEY"), - voice_id="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady + settings=CartesiaTTSSettings( + voice="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady + ), ) llm = OpenAILLMService( diff --git a/examples/foundational/07zb-interruptible-inworld-http.py b/examples/foundational/07zb-interruptible-inworld-http.py index 9ef465781..ffbdbb444 100644 --- a/examples/foundational/07zb-interruptible-inworld-http.py +++ b/examples/foundational/07zb-interruptible-inworld-http.py @@ -24,7 +24,7 @@ from pipecat.processors.aggregators.llm_response_universal import ( from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport from pipecat.services.deepgram.stt import DeepgramSTTService -from pipecat.services.inworld.tts import InworldHttpTTSService +from pipecat.services.inworld.tts import InworldHttpTTSService, InworldTTSSettings from pipecat.services.openai.llm import OpenAILLMService from pipecat.transports.base_output import BaseOutputTransport from pipecat.transports.base_transport import BaseTransport, TransportParams @@ -58,10 +58,12 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): tts = InworldHttpTTSService( api_key=os.getenv("INWORLD_API_KEY", ""), aiohttp_session=session, - voice_id="Ashley", - model="inworld-tts-1", - # Set to False for non-streaming mode or True for streaming mode. streaming=True, + settings=InworldTTSSettings( + voice="Ashley", + model="inworld-tts-1", + ), + # Set to False for non-streaming mode or True for streaming mode. ) llm = OpenAILLMService( diff --git a/examples/foundational/07zb-interruptible-inworld.py b/examples/foundational/07zb-interruptible-inworld.py index 7cdbfd88a..6c8b53706 100644 --- a/examples/foundational/07zb-interruptible-inworld.py +++ b/examples/foundational/07zb-interruptible-inworld.py @@ -23,7 +23,7 @@ from pipecat.processors.aggregators.llm_response_universal import ( from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport from pipecat.services.deepgram.stt import DeepgramSTTService -from pipecat.services.inworld.tts import InworldTTSService +from pipecat.services.inworld.tts import InworldTTSService, InworldTTSSettings from pipecat.services.openai.llm import OpenAILLMService from pipecat.transports.base_output import BaseOutputTransport from pipecat.transports.base_transport import BaseTransport, TransportParams @@ -56,9 +56,11 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): tts = InworldTTSService( api_key=os.getenv("INWORLD_API_KEY", ""), - voice_id="Ashley", - model="inworld-tts-1", - temperature=1.1, + settings=InworldTTSSettings( + voice="Ashley", + model="inworld-tts-1", + temperature=1.1, + ), ) llm = OpenAILLMService( diff --git a/examples/foundational/07zc-interruptible-asyncai-http.py b/examples/foundational/07zc-interruptible-asyncai-http.py index 17d187ac8..3246feac4 100644 --- a/examples/foundational/07zc-interruptible-asyncai-http.py +++ b/examples/foundational/07zc-interruptible-asyncai-http.py @@ -23,7 +23,7 @@ from pipecat.processors.aggregators.llm_response_universal import ( ) from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport -from pipecat.services.asyncai.tts import AsyncAIHttpTTSService +from pipecat.services.asyncai.tts import AsyncAIHttpTTSService, AsyncAITTSSettings from pipecat.services.deepgram.stt import DeepgramSTTService from pipecat.services.openai.llm import OpenAILLMService from pipecat.transports.base_transport import BaseTransport, TransportParams @@ -60,7 +60,9 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): tts = AsyncAIHttpTTSService( api_key=os.getenv("ASYNCAI_API_KEY", ""), - voice_id=os.getenv("ASYNCAI_VOICE_ID", "e0f39dc4-f691-4e78-bba5-5c636692cc04"), + settings=AsyncAITTSSettings( + voice="e0f39dc4-f691-4e78-bba5-5c636692cc04", + ), aiohttp_session=session, ) diff --git a/examples/foundational/07zc-interruptible-asyncai.py b/examples/foundational/07zc-interruptible-asyncai.py index 799842658..093f03ccb 100644 --- a/examples/foundational/07zc-interruptible-asyncai.py +++ b/examples/foundational/07zc-interruptible-asyncai.py @@ -22,7 +22,7 @@ from pipecat.processors.aggregators.llm_response_universal import ( ) from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport -from pipecat.services.asyncai.tts import AsyncAITTSService +from pipecat.services.asyncai.tts import AsyncAITTSService, AsyncAITTSSettings from pipecat.services.deepgram.stt import DeepgramSTTService from pipecat.services.openai.llm import OpenAILLMService from pipecat.transports.base_transport import BaseTransport, TransportParams @@ -57,7 +57,9 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): tts = AsyncAITTSService( api_key=os.getenv("ASYNCAI_API_KEY", ""), - voice_id=os.getenv("ASYNCAI_VOICE_ID", "e0f39dc4-f691-4e78-bba5-5c636692cc04"), + settings=AsyncAITTSSettings( + voice="e0f39dc4-f691-4e78-bba5-5c636692cc04", + ), ) llm = OpenAILLMService( diff --git a/examples/foundational/07zd-interruptible-aicoustics.py b/examples/foundational/07zd-interruptible-aicoustics.py index 9e9f6ddd6..cedb95a9e 100644 --- a/examples/foundational/07zd-interruptible-aicoustics.py +++ b/examples/foundational/07zd-interruptible-aicoustics.py @@ -25,7 +25,7 @@ from pipecat.processors.aggregators.llm_response_universal import ( from pipecat.processors.audio.audio_buffer_processor import AudioBufferProcessor from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport -from pipecat.services.cartesia.tts import CartesiaTTSService +from pipecat.services.cartesia.tts import CartesiaTTSService, CartesiaTTSSettings from pipecat.services.deepgram.stt import DeepgramSTTService from pipecat.services.openai.llm import OpenAILLMService from pipecat.transports.base_transport import BaseTransport, TransportParams @@ -77,7 +77,9 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): tts = CartesiaTTSService( api_key=os.getenv("CARTESIA_API_KEY"), - voice_id="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady + settings=CartesiaTTSSettings( + voice="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady + ), ) llm = OpenAILLMService( diff --git a/examples/foundational/07ze-interruptible-hume.py b/examples/foundational/07ze-interruptible-hume.py index 395aa75d4..70ace62e9 100644 --- a/examples/foundational/07ze-interruptible-hume.py +++ b/examples/foundational/07ze-interruptible-hume.py @@ -23,7 +23,7 @@ from pipecat.processors.aggregators.llm_response_universal import ( from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport from pipecat.services.deepgram.stt import DeepgramSTTService -from pipecat.services.hume.tts import HUME_SAMPLE_RATE, HumeTTSService +from pipecat.services.hume.tts import HUME_SAMPLE_RATE, HumeTTSService, HumeTTSSettings from pipecat.services.openai.llm import OpenAILLMService from pipecat.transports.base_output import BaseOutputTransport from pipecat.transports.base_transport import BaseTransport, TransportParams @@ -59,7 +59,9 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): tts = HumeTTSService( api_key=os.getenv("HUME_API_KEY"), # Replace with your Hume voice ID - voice_id="f898a92e-685f-43fa-985b-a46920f0650b", + settings=HumeTTSSettings( + voice="f898a92e-685f-43fa-985b-a46920f0650b", + ), ) llm = OpenAILLMService( diff --git a/examples/foundational/07zf-interruptible-gradium.py b/examples/foundational/07zf-interruptible-gradium.py index d76735897..ff164c790 100644 --- a/examples/foundational/07zf-interruptible-gradium.py +++ b/examples/foundational/07zf-interruptible-gradium.py @@ -21,8 +21,8 @@ from pipecat.processors.aggregators.llm_response_universal import ( ) from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport -from pipecat.services.gradium.stt import GradiumSTTService -from pipecat.services.gradium.tts import GradiumTTSService +from pipecat.services.gradium.stt import GradiumSTTService, GradiumSTTSettings +from pipecat.services.gradium.tts import GradiumTTSService, GradiumTTSSettings from pipecat.services.openai.llm import OpenAILLMService from pipecat.transcriptions.language import Language from pipecat.transports.base_transport import BaseTransport, TransportParams @@ -55,15 +55,17 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): stt = GradiumSTTService( api_key=os.getenv("GRADIUM_API_KEY"), api_endpoint_base_url="wss://us.api.gradium.ai/api/speech/asr", - params=GradiumSTTService.InputParams( + settings=GradiumSTTSettings( language=Language.EN, ), ) tts = GradiumTTSService( api_key=os.getenv("GRADIUM_API_KEY"), - voice_id="YTpq7expH9539ERJ", url="wss://us.api.gradium.ai/api/speech/tts", + settings=GradiumTTSSettings( + voice="YTpq7expH9539ERJ", + ), ) llm = OpenAILLMService( diff --git a/examples/foundational/07zg-interruptible-camb.py b/examples/foundational/07zg-interruptible-camb.py index 669315603..f98303b26 100644 --- a/examples/foundational/07zg-interruptible-camb.py +++ b/examples/foundational/07zg-interruptible-camb.py @@ -21,7 +21,7 @@ from pipecat.processors.aggregators.llm_response_universal import ( ) from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport -from pipecat.services.camb.tts import CambTTSService +from pipecat.services.camb.tts import CambTTSService, CambTTSSettings from pipecat.services.deepgram.stt import DeepgramSTTService from pipecat.services.openai.llm import OpenAILLMService from pipecat.transports.base_transport import BaseTransport, TransportParams @@ -56,7 +56,9 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): tts = CambTTSService( api_key=os.getenv("CAMB_API_KEY"), - model="mars-flash", + settings=CambTTSSettings( + model="mars-flash", + ), ) llm = OpenAILLMService( diff --git a/examples/foundational/07zi-interruptible-piper.py b/examples/foundational/07zi-interruptible-piper.py index 9d07f9cdf..fb38cba6a 100644 --- a/examples/foundational/07zi-interruptible-piper.py +++ b/examples/foundational/07zi-interruptible-piper.py @@ -23,7 +23,7 @@ from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport from pipecat.services.deepgram.stt import DeepgramSTTService from pipecat.services.openai.llm import OpenAILLMService -from pipecat.services.piper.tts import PiperTTSService +from pipecat.services.piper.tts import PiperTTSService, PiperTTSSettings from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams @@ -54,7 +54,11 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): stt = DeepgramSTTService(api_key=os.getenv("DEEPGRAM_API_KEY")) - tts = PiperTTSService(voice_id="en_US-ryan-high") + tts = PiperTTSService( + settings=PiperTTSSettings( + voice="en_US-ryan-high", + ), + ) llm = OpenAILLMService( api_key=os.getenv("OPENAI_API_KEY"), diff --git a/examples/foundational/07zj-interruptible-kokoro.py b/examples/foundational/07zj-interruptible-kokoro.py index 04ab90145..7271ef42d 100644 --- a/examples/foundational/07zj-interruptible-kokoro.py +++ b/examples/foundational/07zj-interruptible-kokoro.py @@ -22,7 +22,7 @@ from pipecat.processors.aggregators.llm_response_universal import ( from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport from pipecat.services.deepgram.stt import DeepgramSTTService -from pipecat.services.kokoro.tts import KokoroTTSService +from pipecat.services.kokoro.tts import KokoroTTSService, KokoroTTSSettings from pipecat.services.openai.llm import OpenAILLMService from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams @@ -54,7 +54,11 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): stt = DeepgramSTTService(api_key=os.getenv("DEEPGRAM_API_KEY")) - tts = KokoroTTSService(voice_id="af_heart") + tts = KokoroTTSService( + settings=KokoroTTSSettings( + voice="af_heart", + ), + ) llm = OpenAILLMService( api_key=os.getenv("OPENAI_API_KEY"), diff --git a/examples/foundational/07zk-interruptible-resemble.py b/examples/foundational/07zk-interruptible-resemble.py index d9298815d..5e89eaa6e 100644 --- a/examples/foundational/07zk-interruptible-resemble.py +++ b/examples/foundational/07zk-interruptible-resemble.py @@ -23,7 +23,7 @@ from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport from pipecat.services.deepgram.stt import DeepgramSTTService from pipecat.services.openai.llm import OpenAILLMService -from pipecat.services.resembleai.tts import ResembleAITTSService +from pipecat.services.resembleai.tts import ResembleAITTSService, ResembleAITTSSettings from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams @@ -59,7 +59,9 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): tts = ResembleAITTSService( api_key=os.getenv("RESEMBLE_API_KEY"), - voice_id=os.getenv("RESEMBLE_VOICE_UUID"), + settings=ResembleAITTSSettings( + voice=os.getenv("RESEMBLE_VOICE_UUID"), + ), ) llm = OpenAILLMService( diff --git a/examples/foundational/08-custom-frame-processor.py b/examples/foundational/08-custom-frame-processor.py index a4b5b2127..cfab184cb 100644 --- a/examples/foundational/08-custom-frame-processor.py +++ b/examples/foundational/08-custom-frame-processor.py @@ -26,7 +26,7 @@ from pipecat.processors.aggregators.llm_response_universal import ( from pipecat.processors.frame_processor import FrameDirection, FrameProcessor from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport -from pipecat.services.cartesia.tts import CartesiaTTSService +from pipecat.services.cartesia.tts import CartesiaTTSService, CartesiaTTSSettings from pipecat.services.deepgram.stt import DeepgramSTTService from pipecat.services.openai.llm import OpenAILLMService from pipecat.transports.base_transport import BaseTransport, TransportParams @@ -95,7 +95,9 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): tts = CartesiaTTSService( api_key=os.getenv("CARTESIA_API_KEY"), - voice_id="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady + settings=CartesiaTTSSettings( + voice="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady + ), ) llm = OpenAILLMService( diff --git a/examples/foundational/10-wake-phrase.py b/examples/foundational/10-wake-phrase.py index 52a7d1225..a57ef6f96 100644 --- a/examples/foundational/10-wake-phrase.py +++ b/examples/foundational/10-wake-phrase.py @@ -22,7 +22,7 @@ from pipecat.processors.aggregators.llm_response_universal import ( from pipecat.processors.filters.wake_check_filter import WakeCheckFilter from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport -from pipecat.services.cartesia.tts import CartesiaTTSService +from pipecat.services.cartesia.tts import CartesiaTTSService, CartesiaTTSSettings from pipecat.services.deepgram.stt import DeepgramSTTService from pipecat.services.openai.llm import OpenAILLMService from pipecat.transports.base_transport import BaseTransport, TransportParams @@ -56,7 +56,9 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): tts = CartesiaTTSService( api_key=os.getenv("CARTESIA_API_KEY"), - voice_id="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady + settings=CartesiaTTSSettings( + voice="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady + ), ) llm = OpenAILLMService( diff --git a/examples/foundational/11-sound-effects.py b/examples/foundational/11-sound-effects.py index 401c36b8e..332c1536a 100644 --- a/examples/foundational/11-sound-effects.py +++ b/examples/foundational/11-sound-effects.py @@ -30,7 +30,7 @@ from pipecat.processors.frame_processor import FrameDirection, FrameProcessor from pipecat.processors.logger import FrameLogger from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport -from pipecat.services.cartesia.tts import CartesiaTTSService +from pipecat.services.cartesia.tts import CartesiaTTSService, CartesiaTTSSettings from pipecat.services.deepgram.stt import DeepgramSTTService from pipecat.services.openai.llm import OpenAILLMService from pipecat.transports.base_transport import BaseTransport, TransportParams @@ -111,7 +111,9 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): tts = CartesiaTTSService( api_key=os.getenv("CARTESIA_API_KEY"), - voice_id="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady + settings=CartesiaTTSSettings( + voice="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady + ), ) context = LLMContext() diff --git a/examples/foundational/12-describe-image-openai.py b/examples/foundational/12-describe-image-openai.py index dc45451fe..4d22e4046 100644 --- a/examples/foundational/12-describe-image-openai.py +++ b/examples/foundational/12-describe-image-openai.py @@ -23,7 +23,7 @@ from pipecat.processors.aggregators.llm_response_universal import ( ) from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport -from pipecat.services.cartesia.tts import CartesiaTTSService +from pipecat.services.cartesia.tts import CartesiaTTSService, CartesiaTTSSettings from pipecat.services.deepgram.stt import DeepgramSTTService from pipecat.services.openai.llm import OpenAILLMService from pipecat.transports.base_transport import BaseTransport, TransportParams @@ -53,7 +53,9 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): tts = CartesiaTTSService( api_key=os.getenv("CARTESIA_API_KEY"), - voice_id="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady + settings=CartesiaTTSSettings( + voice="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady + ), ) llm = OpenAILLMService( diff --git a/examples/foundational/12a-describe-image-anthropic.py b/examples/foundational/12a-describe-image-anthropic.py index a1151ddf9..79e4460a2 100644 --- a/examples/foundational/12a-describe-image-anthropic.py +++ b/examples/foundational/12a-describe-image-anthropic.py @@ -24,7 +24,7 @@ from pipecat.processors.aggregators.llm_response_universal import ( from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport from pipecat.services.anthropic.llm import AnthropicLLMService -from pipecat.services.cartesia.tts import CartesiaTTSService +from pipecat.services.cartesia.tts import CartesiaTTSService, CartesiaTTSSettings from pipecat.services.deepgram.stt import DeepgramSTTService from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams @@ -53,7 +53,9 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): tts = CartesiaTTSService( api_key=os.getenv("CARTESIA_API_KEY"), - voice_id="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady + settings=CartesiaTTSSettings( + voice="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady + ), ) llm = AnthropicLLMService( diff --git a/examples/foundational/12b-describe-image-aws.py b/examples/foundational/12b-describe-image-aws.py index 43a6ae232..b4db59409 100644 --- a/examples/foundational/12b-describe-image-aws.py +++ b/examples/foundational/12b-describe-image-aws.py @@ -23,8 +23,8 @@ from pipecat.processors.aggregators.llm_response_universal import ( ) from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport -from pipecat.services.aws.llm import AWSBedrockLLMService -from pipecat.services.cartesia.tts import CartesiaTTSService +from pipecat.services.aws.llm import AWSBedrockLLMService, AWSBedrockLLMSettings +from pipecat.services.cartesia.tts import CartesiaTTSService, CartesiaTTSSettings from pipecat.services.deepgram.stt import DeepgramSTTService from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams @@ -53,16 +53,20 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): tts = CartesiaTTSService( api_key=os.getenv("CARTESIA_API_KEY"), - voice_id="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady + settings=CartesiaTTSSettings( + voice="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady + ), ) llm = AWSBedrockLLMService( aws_region="us-west-2", - model="us.anthropic.claude-3-7-sonnet-20250219-v1:0", - # Note: usually, prefer providing latency="optimized" param. - # Here we can't because AWS Bedrock doesn't support it for Claude 3.7, - # which we need for image input. - params=AWSBedrockLLMService.InputParams(temperature=0.8), + settings=AWSBedrockLLMSettings( + model="us.anthropic.claude-3-7-sonnet-20250219-v1:0", + # Note: usually, prefer providing latency="optimized" param. + # Here we can't because AWS Bedrock doesn't support it for Claude 3.7, + # which we need for image input. + params=AWSBedrockLLMService.InputParams(temperature=0.8), + ), system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way. You are also able to describe images.", ) diff --git a/examples/foundational/12c-describe-image-gemini-flash.py b/examples/foundational/12c-describe-image-gemini-flash.py index 9adbe62d2..1f550dd6f 100644 --- a/examples/foundational/12c-describe-image-gemini-flash.py +++ b/examples/foundational/12c-describe-image-gemini-flash.py @@ -23,7 +23,7 @@ from pipecat.processors.aggregators.llm_response_universal import ( ) from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport -from pipecat.services.cartesia.tts import CartesiaTTSService +from pipecat.services.cartesia.tts import CartesiaTTSService, CartesiaTTSSettings from pipecat.services.deepgram.stt import DeepgramSTTService from pipecat.services.google.llm import GoogleLLMService from pipecat.transports.base_transport import BaseTransport, TransportParams @@ -53,7 +53,9 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): tts = CartesiaTTSService( api_key=os.getenv("CARTESIA_API_KEY"), - voice_id="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady + settings=CartesiaTTSSettings( + voice="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady + ), ) llm = GoogleLLMService( diff --git a/examples/foundational/12d-describe-image-moondream.py b/examples/foundational/12d-describe-image-moondream.py index 070b004a1..21fc79ed5 100644 --- a/examples/foundational/12d-describe-image-moondream.py +++ b/examples/foundational/12d-describe-image-moondream.py @@ -17,7 +17,7 @@ from pipecat.pipeline.runner import PipelineRunner from pipecat.pipeline.task import PipelineParams, PipelineTask from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport -from pipecat.services.cartesia.tts import CartesiaTTSService +from pipecat.services.cartesia.tts import CartesiaTTSService, CartesiaTTSSettings from pipecat.services.moondream.vision import MoondreamService from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams @@ -42,7 +42,9 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): tts = CartesiaTTSService( api_key=os.getenv("CARTESIA_API_KEY"), - voice_id="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady + settings=CartesiaTTSSettings( + voice="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady + ), ) vision = MoondreamService() diff --git a/examples/foundational/13b-deepgram-transcription.py b/examples/foundational/13b-deepgram-transcription.py index ed83bd1d5..61ba5c266 100644 --- a/examples/foundational/13b-deepgram-transcription.py +++ b/examples/foundational/13b-deepgram-transcription.py @@ -16,7 +16,7 @@ from pipecat.pipeline.task import PipelineTask from pipecat.processors.frame_processor import FrameDirection, FrameProcessor from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport -from pipecat.services.deepgram.stt import DeepgramSTTService, Language, LiveOptions +from pipecat.services.deepgram.stt import DeepgramSTTService, DeepgramSTTSettings, Language from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams @@ -49,7 +49,9 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): stt = DeepgramSTTService( api_key=os.getenv("DEEPGRAM_API_KEY"), - live_options=LiveOptions(language=Language.EN), + settings=DeepgramSTTSettings( + language=Language.EN, + ), ) tl = TranscriptionLogger() diff --git a/examples/foundational/13c-gladia-transcription.py b/examples/foundational/13c-gladia-transcription.py index c98fda727..8771cb8d4 100644 --- a/examples/foundational/13c-gladia-transcription.py +++ b/examples/foundational/13c-gladia-transcription.py @@ -50,7 +50,11 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): stt = GladiaSTTService( api_key=os.getenv("GLADIA_API_KEY"), region=os.getenv("GLADIA_REGION"), - # live_options=LiveOptions(language=Language.FR), + # settings=GladiaSTTSettings( + # language_config=LanguageConfig( + # languages=[Language.FR], + # ), + # ), ) tl = TranscriptionLogger() diff --git a/examples/foundational/13c-gladia-translation.py b/examples/foundational/13c-gladia-translation.py index edc294858..9f7b6a6da 100644 --- a/examples/foundational/13c-gladia-translation.py +++ b/examples/foundational/13c-gladia-translation.py @@ -22,7 +22,7 @@ from pipecat.services.gladia.config import ( RealtimeProcessingConfig, TranslationConfig, ) -from pipecat.services.gladia.stt import GladiaSTTService +from pipecat.services.gladia.stt import GladiaSTTService, GladiaSTTSettings from pipecat.transcriptions.language import Language from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams @@ -59,16 +59,16 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): stt = GladiaSTTService( api_key=os.getenv("GLADIA_API_KEY"), region=os.getenv("GLADIA_REGION"), - params=GladiaInputParams( + settings=GladiaSTTSettings( language_config=LanguageConfig( - languages=[Language.EN], # Input in English + languages=[Language.EN], code_switching=False, ), realtime_processing=RealtimeProcessingConfig( - translation=True, # Enable translation + translation=True, translation_config=TranslationConfig( - target_languages=[Language.ES], # Translate to Spanish - model="enhanced", # Use the enhanced translation model + target_languages=[Language.ES], + model="enhanced", ), ), ), diff --git a/examples/foundational/13d-assemblyai-transcription.py b/examples/foundational/13d-assemblyai-transcription.py index 2dcbaf59b..c4ca9cd6b 100644 --- a/examples/foundational/13d-assemblyai-transcription.py +++ b/examples/foundational/13d-assemblyai-transcription.py @@ -16,8 +16,7 @@ from pipecat.pipeline.task import PipelineTask from pipecat.processors.frame_processor import FrameDirection, FrameProcessor from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport -from pipecat.services.assemblyai.models import AssemblyAIConnectionParams -from pipecat.services.assemblyai.stt import AssemblyAISTTService +from pipecat.services.assemblyai.stt import AssemblyAISTTService, AssemblyAISTTSettings from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams @@ -50,8 +49,8 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): stt = AssemblyAISTTService( api_key=os.getenv("ASSEMBLYAI_API_KEY"), - connection_params=AssemblyAIConnectionParams( - speech_model="u3-rt-pro", + settings=AssemblyAISTTSettings( + model="u3-rt-pro", ), ) diff --git a/examples/foundational/13e-whisper-mlx.py b/examples/foundational/13e-whisper-mlx.py index ba90d0850..0f11d4397 100644 --- a/examples/foundational/13e-whisper-mlx.py +++ b/examples/foundational/13e-whisper-mlx.py @@ -18,7 +18,7 @@ from pipecat.pipeline.task import PipelineParams, PipelineTask from pipecat.processors.frame_processor import FrameDirection, FrameProcessor from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport -from pipecat.services.whisper.stt import MLXModel, WhisperSTTServiceMLX +from pipecat.services.whisper.stt import MLXModel, WhisperMLXSTTSettings, WhisperSTTServiceMLX from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams @@ -77,7 +77,11 @@ transport_params = { async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): logger.info(f"Starting bot") - stt = WhisperSTTServiceMLX(model=MLXModel.LARGE_V3_TURBO) + stt = WhisperSTTServiceMLX( + settings=WhisperMLXSTTSettings( + model=MLXModel.LARGE_V3_TURBO, + ), + ) tl = TranscriptionLogger() diff --git a/examples/foundational/13g-sambanova-transcription.py b/examples/foundational/13g-sambanova-transcription.py index cebeea615..1e399c38f 100644 --- a/examples/foundational/13g-sambanova-transcription.py +++ b/examples/foundational/13g-sambanova-transcription.py @@ -19,7 +19,7 @@ from pipecat.pipeline.task import PipelineParams, PipelineTask from pipecat.processors.frame_processor import FrameDirection, FrameProcessor from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport -from pipecat.services.sambanova.stt import SambaNovaSTTService +from pipecat.services.sambanova.stt import SambaNovaSTTService, SambaNovaSTTSettings from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams @@ -79,7 +79,9 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): logger.info(f"Starting bot") stt = SambaNovaSTTService( - model="Whisper-Large-v3", + settings=SambaNovaSTTSettings( + model="Whisper-Large-v3", + ), api_key=os.getenv("SAMBANOVA_API_KEY"), ) diff --git a/examples/foundational/13h-speechmatics-transcription.py b/examples/foundational/13h-speechmatics-transcription.py index f1d1d93c6..d013357f6 100644 --- a/examples/foundational/13h-speechmatics-transcription.py +++ b/examples/foundational/13h-speechmatics-transcription.py @@ -16,7 +16,7 @@ from pipecat.pipeline.task import PipelineTask from pipecat.processors.frame_processor import FrameDirection, FrameProcessor from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport -from pipecat.services.speechmatics.stt import SpeechmaticsSTTService +from pipecat.services.speechmatics.stt import SpeechmaticsSTTService, SpeechmaticsSTTSettings from pipecat.transcriptions.language import Language from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams @@ -65,7 +65,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): stt = SpeechmaticsSTTService( api_key=os.getenv("SPEECHMATICS_API_KEY"), - params=SpeechmaticsSTTService.InputParams( + settings=SpeechmaticsSTTSettings( language=Language.EN, speaker_active_format="<{speaker_id}>{text}", ), diff --git a/examples/foundational/13l-gradium-transcription.py b/examples/foundational/13l-gradium-transcription.py index 38709dff7..84b23017c 100644 --- a/examples/foundational/13l-gradium-transcription.py +++ b/examples/foundational/13l-gradium-transcription.py @@ -16,7 +16,7 @@ from pipecat.pipeline.task import PipelineTask from pipecat.processors.frame_processor import FrameDirection, FrameProcessor from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport -from pipecat.services.gradium.stt import GradiumSTTService +from pipecat.services.gradium.stt import GradiumSTTService, GradiumSTTSettings from pipecat.transcriptions.language import Language from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams @@ -52,7 +52,10 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): stt = GradiumSTTService( api_key=os.getenv("GRADIUM_API_KEY"), api_endpoint_base_url="wss://us.api.gradium.ai/api/speech/asr", - params=GradiumSTTService.InputParams(language=Language.EN, delay_in_frames=8), + settings=GradiumSTTSettings( + language=Language.EN, + delay_in_frames=8, + ), ) tl = TranscriptionLogger() diff --git a/examples/foundational/13m-openai-transcription.py b/examples/foundational/13m-openai-transcription.py index 2ef35cb3f..8dc9e0101 100644 --- a/examples/foundational/13m-openai-transcription.py +++ b/examples/foundational/13m-openai-transcription.py @@ -18,7 +18,7 @@ from pipecat.pipeline.task import PipelineTask from pipecat.processors.frame_processor import FrameDirection, FrameProcessor from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport -from pipecat.services.openai.stt import OpenAIRealtimeSTTService +from pipecat.services.openai.stt import OpenAIRealtimeSTTService, OpenAIRealtimeSTTSettings from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams @@ -53,8 +53,10 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): stt = OpenAIRealtimeSTTService( api_key=os.getenv("OPENAI_API_KEY"), - model="gpt-4o-transcribe", - prompt="Expect words related to dogs, such as breed names.", + settings=OpenAIRealtimeSTTSettings( + model="gpt-4o-transcribe", + prompt="Expect words related to dogs, such as breed names.", + ), ) tl = TranscriptionLogger() diff --git a/examples/foundational/14-function-calling.py b/examples/foundational/14-function-calling.py index 0087af9fc..2a3206dbc 100644 --- a/examples/foundational/14-function-calling.py +++ b/examples/foundational/14-function-calling.py @@ -23,7 +23,7 @@ from pipecat.processors.aggregators.llm_response_universal import ( ) from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport -from pipecat.services.cartesia.tts import CartesiaTTSService +from pipecat.services.cartesia.tts import CartesiaTTSService, CartesiaTTSSettings from pipecat.services.deepgram.stt import DeepgramSTTService from pipecat.services.llm_service import FunctionCallParams from pipecat.services.openai.llm import OpenAILLMService @@ -67,7 +67,9 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): tts = CartesiaTTSService( api_key=os.getenv("CARTESIA_API_KEY"), - voice_id="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady + settings=CartesiaTTSSettings( + voice="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady + ), ) llm = OpenAILLMService( diff --git a/examples/foundational/14a-function-calling-anthropic.py b/examples/foundational/14a-function-calling-anthropic.py index 36030bc2b..0fd40af4f 100644 --- a/examples/foundational/14a-function-calling-anthropic.py +++ b/examples/foundational/14a-function-calling-anthropic.py @@ -25,7 +25,7 @@ from pipecat.processors.aggregators.llm_response_universal import ( from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport from pipecat.services.anthropic.llm import AnthropicLLMService -from pipecat.services.cartesia.tts import CartesiaTTSService +from pipecat.services.cartesia.tts import CartesiaTTSService, CartesiaTTSSettings from pipecat.services.deepgram.stt import DeepgramSTTService from pipecat.services.llm_service import FunctionCallParams from pipecat.transports.base_transport import BaseTransport, TransportParams @@ -69,10 +69,15 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): tts = CartesiaTTSService( api_key=os.getenv("CARTESIA_API_KEY"), - voice_id="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady + settings=CartesiaTTSSettings( + voice="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady + ), ) - llm = AnthropicLLMService(api_key=os.getenv("ANTHROPIC_API_KEY")) + llm = AnthropicLLMService( + api_key=os.getenv("ANTHROPIC_API_KEY"), + system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + ) llm.register_function("get_weather", get_weather) llm.register_function("get_restaurant_recommendation", fetch_restaurant_recommendation) @@ -100,16 +105,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): ) tools = ToolsSchema(standard_tools=[weather_function, restaurant_function]) - # todo: test with very short initial user message - - # messages = [{"role": "system", - # "content": "You are a helpful assistant who can report the weather in any location in the universe. Respond concisely. Your response will be turned into speech so use only simple words and punctuation."}, - # {"role": "user", - # "content": " Start the conversation by introducing yourself."}] - - messages = [{"role": "user", "content": "Say 'hello' to start the conversation."}] - - context = LLMContext(messages, tools) + context = LLMContext(tools=tools) user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()), diff --git a/examples/foundational/14c-function-calling-together.py b/examples/foundational/14c-function-calling-together.py index 214d6f292..6362e1ea6 100644 --- a/examples/foundational/14c-function-calling-together.py +++ b/examples/foundational/14c-function-calling-together.py @@ -24,10 +24,10 @@ from pipecat.processors.aggregators.llm_response_universal import ( ) from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport -from pipecat.services.cartesia.tts import CartesiaTTSService +from pipecat.services.cartesia.tts import CartesiaTTSService, CartesiaTTSSettings from pipecat.services.deepgram.stt import DeepgramSTTService from pipecat.services.llm_service import FunctionCallParams -from pipecat.services.together.llm import TogetherLLMService +from pipecat.services.together.llm import TogetherLLMService, TogetherLLMSettings from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams @@ -64,12 +64,16 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): tts = CartesiaTTSService( api_key=os.getenv("CARTESIA_API_KEY"), - voice_id="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady + settings=CartesiaTTSSettings( + voice="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady + ), ) llm = TogetherLLMService( api_key=os.getenv("TOGETHER_API_KEY"), - model="meta-llama/Meta-Llama-3.1-70B-Instruct-Turbo", + settings=TogetherLLMSettings( + model="meta-llama/Meta-Llama-3.1-70B-Instruct-Turbo", + ), system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", ) # You can also register a function_name of None to get all functions diff --git a/examples/foundational/14d-function-calling-anthropic-video.py b/examples/foundational/14d-function-calling-anthropic-video.py index cddde3647..fee17734c 100644 --- a/examples/foundational/14d-function-calling-anthropic-video.py +++ b/examples/foundational/14d-function-calling-anthropic-video.py @@ -29,7 +29,7 @@ from pipecat.runner.utils import ( maybe_capture_participant_camera, ) from pipecat.services.anthropic.llm import AnthropicLLMService -from pipecat.services.cartesia.tts import CartesiaTTSService +from pipecat.services.cartesia.tts import CartesiaTTSService, CartesiaTTSSettings from pipecat.services.deepgram.stt import DeepgramSTTService from pipecat.services.llm_service import FunctionCallParams from pipecat.transports.base_transport import BaseTransport, TransportParams @@ -90,7 +90,9 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): tts = CartesiaTTSService( api_key=os.getenv("CARTESIA_API_KEY"), - voice_id="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady + settings=CartesiaTTSSettings( + voice="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady + ), ) # Anthropic for vision analysis diff --git a/examples/foundational/14d-function-calling-aws-video.py b/examples/foundational/14d-function-calling-aws-video.py index 396ea0a32..234552d92 100644 --- a/examples/foundational/14d-function-calling-aws-video.py +++ b/examples/foundational/14d-function-calling-aws-video.py @@ -28,8 +28,8 @@ from pipecat.runner.utils import ( get_transport_client_id, maybe_capture_participant_camera, ) -from pipecat.services.aws.llm import AWSBedrockLLMService -from pipecat.services.cartesia.tts import CartesiaTTSService +from pipecat.services.aws.llm import AWSBedrockLLMService, AWSBedrockLLMSettings +from pipecat.services.cartesia.tts import CartesiaTTSService, CartesiaTTSSettings from pipecat.services.deepgram.stt import DeepgramSTTService from pipecat.services.llm_service import FunctionCallParams from pipecat.transports.base_transport import BaseTransport, TransportParams @@ -90,17 +90,21 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): tts = CartesiaTTSService( api_key=os.getenv("CARTESIA_API_KEY"), - voice_id="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady + settings=CartesiaTTSSettings( + voice="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady + ), ) # AWS for vision analysis llm = AWSBedrockLLMService( aws_region="us-west-2", - model="us.anthropic.claude-3-7-sonnet-20250219-v1:0", - # Note: usually, prefer providing latency="optimized" param. - # Here we can't because AWS Bedrock doesn't support it for Claude 3.7, - # which we need for image input. - params=AWSBedrockLLMService.InputParams(temperature=0.8), + settings=AWSBedrockLLMSettings( + model="us.anthropic.claude-3-7-sonnet-20250219-v1:0", + # Note: usually, prefer providing latency="optimized" param. + # Here we can't because AWS Bedrock doesn't support it for Claude 3.7, + # which we need for image input. + temperature=0.8, + ), system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way. You are able to describe images from the user camera.", ) llm.register_function("fetch_user_image", fetch_user_image) diff --git a/examples/foundational/14d-function-calling-gemini-flash-video.py b/examples/foundational/14d-function-calling-gemini-flash-video.py index c59767406..f1255d287 100644 --- a/examples/foundational/14d-function-calling-gemini-flash-video.py +++ b/examples/foundational/14d-function-calling-gemini-flash-video.py @@ -28,7 +28,7 @@ from pipecat.runner.utils import ( get_transport_client_id, maybe_capture_participant_camera, ) -from pipecat.services.cartesia.tts import CartesiaTTSService +from pipecat.services.cartesia.tts import CartesiaTTSService, CartesiaTTSSettings from pipecat.services.deepgram.stt import DeepgramSTTService from pipecat.services.google.llm import GoogleLLMService from pipecat.services.llm_service import FunctionCallParams @@ -90,7 +90,9 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): tts = CartesiaTTSService( api_key=os.getenv("CARTESIA_API_KEY"), - voice_id="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady + settings=CartesiaTTSSettings( + voice="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady + ), ) # Google Gemini model for vision analysis diff --git a/examples/foundational/14d-function-calling-moondream-video.py b/examples/foundational/14d-function-calling-moondream-video.py index d0913e3dc..6ffb10213 100644 --- a/examples/foundational/14d-function-calling-moondream-video.py +++ b/examples/foundational/14d-function-calling-moondream-video.py @@ -37,7 +37,7 @@ from pipecat.runner.utils import ( get_transport_client_id, maybe_capture_participant_camera, ) -from pipecat.services.cartesia.tts import CartesiaTTSService +from pipecat.services.cartesia.tts import CartesiaTTSService, CartesiaTTSSettings from pipecat.services.deepgram.stt import DeepgramSTTService from pipecat.services.llm_service import FunctionCallParams from pipecat.services.moondream.vision import MoondreamService @@ -121,7 +121,9 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): tts = CartesiaTTSService( api_key=os.getenv("CARTESIA_API_KEY"), - voice_id="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady + settings=CartesiaTTSSettings( + voice="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady + ), ) llm = OpenAILLMService( diff --git a/examples/foundational/14d-function-calling-openai-video.py b/examples/foundational/14d-function-calling-openai-video.py index 50365eb29..235815a5c 100644 --- a/examples/foundational/14d-function-calling-openai-video.py +++ b/examples/foundational/14d-function-calling-openai-video.py @@ -29,7 +29,7 @@ from pipecat.runner.utils import ( get_transport_client_id, maybe_capture_participant_camera, ) -from pipecat.services.cartesia.tts import CartesiaTTSService +from pipecat.services.cartesia.tts import CartesiaTTSService, CartesiaTTSSettings from pipecat.services.deepgram.stt import DeepgramSTTService from pipecat.services.llm_service import FunctionCallParams from pipecat.services.openai.llm import OpenAILLMService @@ -91,7 +91,9 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): tts = CartesiaTTSService( api_key=os.getenv("CARTESIA_API_KEY"), - voice_id="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady + settings=CartesiaTTSSettings( + voice="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady + ), ) llm = OpenAILLMService( diff --git a/examples/foundational/14e-function-calling-google.py b/examples/foundational/14e-function-calling-google.py index cae32146e..08308dee3 100644 --- a/examples/foundational/14e-function-calling-google.py +++ b/examples/foundational/14e-function-calling-google.py @@ -29,7 +29,7 @@ from pipecat.runner.utils import ( get_transport_client_id, maybe_capture_participant_camera, ) -from pipecat.services.cartesia.tts import CartesiaTTSService +from pipecat.services.cartesia.tts import CartesiaTTSService, CartesiaTTSSettings from pipecat.services.deepgram.stt import DeepgramSTTService from pipecat.services.google.llm import GoogleLLMService from pipecat.services.llm_service import FunctionCallParams @@ -100,10 +100,34 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): tts = CartesiaTTSService( api_key=os.getenv("CARTESIA_API_KEY"), - voice_id="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady + settings=CartesiaTTSSettings( + voice="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady + ), ) - llm = GoogleLLMService(api_key=os.getenv("GOOGLE_API_KEY")) + system_prompt = """\ +You are a helpful assistant who converses with a user and answers questions. Respond concisely to general questions. + +Your response will be turned into speech so use only simple words and punctuation. + +You have access to three tools: get_weather, get_restaurant_recommendation, and get_image. + +You can respond to questions about the weather using the get_weather tool. + +You can answer questions about the user's video stream using the get_image tool. Some examples of phrases that \ +indicate you should use the get_image tool are: +- What do you see? +- What's in the video? +- Can you describe the video? +- Tell me about what you see. +- Tell me something interesting about what you see. +- What's happening in the video? +""" + + llm = GoogleLLMService( + api_key=os.getenv("GOOGLE_API_KEY"), + system_instruction=system_prompt, + ) llm.register_function("get_weather", get_weather) llm.register_function("get_image", get_image) llm.register_function("get_restaurant_recommendation", fetch_restaurant_recommendation) @@ -156,29 +180,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): ) tools = ToolsSchema(standard_tools=[weather_function, get_image_function, restaurant_function]) - system_prompt = """\ -You are a helpful assistant who converses with a user and answers questions. Respond concisely to general questions. - -Your response will be turned into speech so use only simple words and punctuation. - -You have access to three tools: get_weather, get_restaurant_recommendation, and get_image. - -You can respond to questions about the weather using the get_weather tool. - -You can answer questions about the user's video stream using the get_image tool. Some examples of phrases that \ -indicate you should use the get_image tool are: -- What do you see? -- What's in the video? -- Can you describe the video? -- Tell me about what you see. -- Tell me something interesting about what you see. -- What's happening in the video? -""" - messages = [ - {"role": "system", "content": system_prompt}, - ] - - context = LLMContext(messages, tools) + context = LLMContext(tools=tools) user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()), @@ -214,9 +216,9 @@ indicate you should use the get_image tool are: client_id = get_transport_client_id(transport, client) # Kick off the conversation. - messages.append( + context.add_message( { - "role": "system", + "role": "user", "content": f"Please introduce yourself to the user. Use '{client_id}' as the user ID during function calls.", } ) diff --git a/examples/foundational/14f-function-calling-groq.py b/examples/foundational/14f-function-calling-groq.py index e6cfb3659..11bbda12d 100644 --- a/examples/foundational/14f-function-calling-groq.py +++ b/examples/foundational/14f-function-calling-groq.py @@ -24,7 +24,7 @@ from pipecat.processors.aggregators.llm_response_universal import ( ) from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport -from pipecat.services.cartesia.tts import CartesiaTTSService +from pipecat.services.cartesia.tts import CartesiaTTSService, CartesiaTTSSettings from pipecat.services.groq.llm import GroqLLMService from pipecat.services.groq.stt import GroqSTTService from pipecat.services.llm_service import FunctionCallParams @@ -64,7 +64,9 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): tts = CartesiaTTSService( api_key=os.getenv("CARTESIA_API_KEY"), - voice_id="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady + settings=CartesiaTTSSettings( + voice="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady + ), ) llm = GroqLLMService( diff --git a/examples/foundational/14g-function-calling-grok.py b/examples/foundational/14g-function-calling-grok.py index 51435a2a0..7ff89658d 100644 --- a/examples/foundational/14g-function-calling-grok.py +++ b/examples/foundational/14g-function-calling-grok.py @@ -24,7 +24,7 @@ from pipecat.processors.aggregators.llm_response_universal import ( ) from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport -from pipecat.services.cartesia.tts import CartesiaTTSService +from pipecat.services.cartesia.tts import CartesiaTTSService, CartesiaTTSSettings from pipecat.services.deepgram.stt import DeepgramSTTService from pipecat.services.grok.llm import GrokLLMService from pipecat.services.llm_service import FunctionCallParams @@ -64,7 +64,9 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): tts = CartesiaTTSService( api_key=os.getenv("CARTESIA_API_KEY"), - voice_id="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady + settings=CartesiaTTSSettings( + voice="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady + ), ) llm = GrokLLMService( diff --git a/examples/foundational/14h-function-calling-azure.py b/examples/foundational/14h-function-calling-azure.py index 192cebb92..9df6abeef 100644 --- a/examples/foundational/14h-function-calling-azure.py +++ b/examples/foundational/14h-function-calling-azure.py @@ -24,8 +24,8 @@ from pipecat.processors.aggregators.llm_response_universal import ( ) from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport -from pipecat.services.azure.llm import AzureLLMService -from pipecat.services.cartesia.tts import CartesiaTTSService +from pipecat.services.azure.llm import AzureLLMService, AzureLLMSettings +from pipecat.services.cartesia.tts import CartesiaTTSService, CartesiaTTSSettings from pipecat.services.deepgram.stt import DeepgramSTTService from pipecat.services.llm_service import FunctionCallParams from pipecat.transports.base_transport import BaseTransport, TransportParams @@ -64,13 +64,17 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): tts = CartesiaTTSService( api_key=os.getenv("CARTESIA_API_KEY"), - voice_id="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady + settings=CartesiaTTSSettings( + voice="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady + ), ) llm = AzureLLMService( api_key=os.getenv("AZURE_CHATGPT_API_KEY"), endpoint=os.getenv("AZURE_CHATGPT_ENDPOINT"), - model=os.getenv("AZURE_CHATGPT_MODEL"), + settings=AzureLLMSettings( + model=os.getenv("AZURE_CHATGPT_MODEL"), + ), system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", ) # You can also register a function_name of None to get all functions diff --git a/examples/foundational/14i-function-calling-fireworks.py b/examples/foundational/14i-function-calling-fireworks.py index be006e062..6a274c09f 100644 --- a/examples/foundational/14i-function-calling-fireworks.py +++ b/examples/foundational/14i-function-calling-fireworks.py @@ -24,9 +24,9 @@ from pipecat.processors.aggregators.llm_response_universal import ( ) from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport -from pipecat.services.cartesia.tts import CartesiaTTSService +from pipecat.services.cartesia.tts import CartesiaTTSService, CartesiaTTSSettings from pipecat.services.deepgram.stt import DeepgramSTTService -from pipecat.services.fireworks.llm import FireworksLLMService +from pipecat.services.fireworks.llm import FireworksLLMService, FireworksLLMSettings from pipecat.services.llm_service import FunctionCallParams from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams @@ -64,12 +64,16 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): tts = CartesiaTTSService( api_key=os.getenv("CARTESIA_API_KEY"), - voice_id="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady + settings=CartesiaTTSSettings( + voice="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady + ), ) llm = FireworksLLMService( api_key=os.getenv("FIREWORKS_API_KEY"), - model="accounts/fireworks/models/gpt-oss-20b", + settings=FireworksLLMSettings( + model="accounts/fireworks/models/gpt-oss-20b", + ), system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", ) # You can also register a function_name of None to get all functions diff --git a/examples/foundational/14j-function-calling-nvidia.py b/examples/foundational/14j-function-calling-nvidia.py index e079c228f..680952d75 100644 --- a/examples/foundational/14j-function-calling-nvidia.py +++ b/examples/foundational/14j-function-calling-nvidia.py @@ -24,10 +24,10 @@ from pipecat.processors.aggregators.llm_response_universal import ( ) from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport -from pipecat.services.cartesia.tts import CartesiaTTSService +from pipecat.services.cartesia.tts import CartesiaTTSService, CartesiaTTSSettings from pipecat.services.deepgram.stt import DeepgramSTTService from pipecat.services.llm_service import FunctionCallParams -from pipecat.services.nvidia.llm import NvidiaLLMService +from pipecat.services.nvidia.llm import NvidiaLLMService, NvidiaLLMSettings from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams @@ -64,15 +64,19 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): tts = CartesiaTTSService( api_key=os.getenv("CARTESIA_API_KEY"), - voice_id="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady - # text_filters=[MarkdownTextFilter()], + settings=CartesiaTTSSettings( + voice="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady + ), ) llm = NvidiaLLMService( api_key=os.getenv("NVIDIA_API_KEY"), - model="nvidia/llama-3.3-nemotron-super-49b-v1.5", - # Recommended when turning thinking off - params=NvidiaLLMService.InputParams(temperature=0.0), + settings=NvidiaLLMSettings( + model="nvidia/llama-3.3-nemotron-super-49b-v1.5", + # Recommended when turning thinking off + temperature=0.0, + ), + system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", ) # You can also register a function_name of None to get all functions # sent to the same callback with an additional function_name parameter. @@ -99,17 +103,8 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): required=["location", "format"], ) tools = ToolsSchema(standard_tools=[weather_function]) - messages = [ - # Disable thinking by sending this message first - # Check the model for the corresponding "no thinking" message - {"role": "system", "content": "/no_think"}, - { - "role": "system", - "content": "You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", - }, - ] - context = LLMContext(messages, tools) + context = LLMContext(tools=tools) user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()), diff --git a/examples/foundational/14k-function-calling-cerebras.py b/examples/foundational/14k-function-calling-cerebras.py index 81df8723c..118062769 100644 --- a/examples/foundational/14k-function-calling-cerebras.py +++ b/examples/foundational/14k-function-calling-cerebras.py @@ -24,7 +24,7 @@ from pipecat.processors.aggregators.llm_response_universal import ( ) from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport -from pipecat.services.cartesia.tts import CartesiaTTSService +from pipecat.services.cartesia.tts import CartesiaTTSService, CartesiaTTSSettings from pipecat.services.cerebras.llm import CerebrasLLMService from pipecat.services.deepgram.stt import DeepgramSTTService from pipecat.services.llm_service import FunctionCallParams @@ -64,7 +64,9 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): tts = CartesiaTTSService( api_key=os.getenv("CARTESIA_API_KEY"), - voice_id="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady + settings=CartesiaTTSSettings( + voice="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady + ), ) llm = CerebrasLLMService( diff --git a/examples/foundational/14l-function-calling-deepseek.py b/examples/foundational/14l-function-calling-deepseek.py index 93643146a..9c2068236 100644 --- a/examples/foundational/14l-function-calling-deepseek.py +++ b/examples/foundational/14l-function-calling-deepseek.py @@ -24,9 +24,9 @@ from pipecat.processors.aggregators.llm_response_universal import ( ) from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport -from pipecat.services.cartesia.tts import CartesiaTTSService +from pipecat.services.cartesia.tts import CartesiaTTSService, CartesiaTTSSettings from pipecat.services.deepgram.stt import DeepgramSTTService -from pipecat.services.deepseek.llm import DeepSeekLLMService +from pipecat.services.deepseek.llm import DeepSeekLLMService, DeepSeekLLMSettings from pipecat.services.llm_service import FunctionCallParams from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams @@ -64,12 +64,16 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): tts = CartesiaTTSService( api_key=os.getenv("CARTESIA_API_KEY"), - voice_id="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady + settings=CartesiaTTSSettings( + voice="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady + ), ) llm = DeepSeekLLMService( api_key=os.getenv("DEEPSEEK_API_KEY"), - model="deepseek-chat", + settings=DeepSeekLLMSettings( + model="deepseek-chat", + ), system_instruction="""You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. You have one functions available: diff --git a/examples/foundational/14m-function-calling-openrouter.py b/examples/foundational/14m-function-calling-openrouter.py index 9504021ff..dbcd1813f 100644 --- a/examples/foundational/14m-function-calling-openrouter.py +++ b/examples/foundational/14m-function-calling-openrouter.py @@ -24,10 +24,10 @@ from pipecat.processors.aggregators.llm_response_universal import ( ) from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport -from pipecat.services.azure.tts import AzureTTSService +from pipecat.services.azure.tts import AzureTTSService, AzureTTSSettings from pipecat.services.deepgram.stt import DeepgramSTTService from pipecat.services.llm_service import FunctionCallParams -from pipecat.services.openrouter.llm import OpenRouterLLMService +from pipecat.services.openrouter.llm import OpenRouterLLMService, OpenRouterLLMSettings from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams @@ -65,13 +65,19 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): tts = AzureTTSService( api_key=os.getenv("AZURE_SPEECH_API_KEY"), region=os.getenv("AZURE_SPEECH_REGION"), - voice="en-US-JennyNeural", - params=AzureTTSService.InputParams(language="en-US", rate="1.1", style="cheerful"), + settings=AzureTTSSettings( + voice="en-US-JennyNeural", + language="en-US", + rate="1.1", + style="cheerful", + ), ) llm = OpenRouterLLMService( api_key=os.getenv("OPENROUTER_API_KEY"), - model="openai/gpt-4o-2024-11-20", + settings=OpenRouterLLMSettings( + model="openai/gpt-4o-2024-11-20", + ), system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", ) # You can also register a function_name of None to get all functions diff --git a/examples/foundational/14n-function-calling-perplexity.py b/examples/foundational/14n-function-calling-perplexity.py index 2f1a18d52..4857b614f 100644 --- a/examples/foundational/14n-function-calling-perplexity.py +++ b/examples/foundational/14n-function-calling-perplexity.py @@ -28,7 +28,7 @@ from pipecat.processors.aggregators.llm_response_universal import ( ) from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport -from pipecat.services.cartesia.tts import CartesiaTTSService +from pipecat.services.cartesia.tts import CartesiaTTSService, CartesiaTTSSettings from pipecat.services.deepgram.stt import DeepgramSTTService from pipecat.services.perplexity.llm import PerplexityLLMService from pipecat.transports.base_transport import BaseTransport, TransportParams @@ -62,19 +62,17 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): tts = CartesiaTTSService( api_key=os.getenv("CARTESIA_API_KEY"), - voice_id="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady + settings=CartesiaTTSSettings( + voice="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady + ), ) - llm = PerplexityLLMService(api_key=os.getenv("PERPLEXITY_API_KEY")) + llm = PerplexityLLMService( + api_key=os.getenv("PERPLEXITY_API_KEY"), + system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way, but try to be brief.", + ) - messages = [ - { - "role": "user", - "content": "You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way, but try to be brief.", - }, - ] - - context = LLMContext(messages) + context = LLMContext() user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()), diff --git a/examples/foundational/14o-function-calling-gemini-openai-format.py b/examples/foundational/14o-function-calling-gemini-openai-format.py index c3772eb2c..4a752586f 100644 --- a/examples/foundational/14o-function-calling-gemini-openai-format.py +++ b/examples/foundational/14o-function-calling-gemini-openai-format.py @@ -25,7 +25,7 @@ from pipecat.processors.aggregators.openai_llm_context import OpenAILLMContext from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport from pipecat.services.deepgram.stt import DeepgramSTTService -from pipecat.services.elevenlabs.tts import ElevenLabsTTSService +from pipecat.services.elevenlabs.tts import ElevenLabsTTSService, ElevenLabsTTSSettings from pipecat.services.google.llm_openai import GoogleLLMOpenAIBetaService from pipecat.services.llm_service import FunctionCallParams from pipecat.transports.base_transport import BaseTransport, TransportParams @@ -64,10 +64,15 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): tts = ElevenLabsTTSService( api_key=os.getenv("ELEVENLABS_API_KEY", ""), - voice_id=os.getenv("ELEVENLABS_VOICE_ID", ""), + settings=ElevenLabsTTSSettings( + voice_id=os.getenv("ELEVENLABS_VOICE_ID", ""), + ), ) - llm = GoogleLLMOpenAIBetaService(api_key=os.getenv("GOOGLE_API_KEY")) + llm = GoogleLLMOpenAIBetaService( + api_key=os.getenv("GOOGLE_API_KEY"), + system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + ) # You can aslo register a function_name of None to get all functions # sent to the same callback with an additional function_name parameter. llm.register_function("get_current_weather", fetch_weather_from_api) diff --git a/examples/foundational/14p-function-calling-gemini-vertex-ai.py b/examples/foundational/14p-function-calling-gemini-vertex-ai.py index a71f3c8d1..3ff062201 100644 --- a/examples/foundational/14p-function-calling-gemini-vertex-ai.py +++ b/examples/foundational/14p-function-calling-gemini-vertex-ai.py @@ -25,7 +25,7 @@ from pipecat.processors.aggregators.llm_response_universal import ( from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport from pipecat.services.deepgram.stt import DeepgramSTTService -from pipecat.services.elevenlabs.tts import ElevenLabsTTSService +from pipecat.services.elevenlabs.tts import ElevenLabsTTSService, ElevenLabsTTSSettings from pipecat.services.google.llm_vertex import GoogleVertexLLMService from pipecat.services.llm_service import FunctionCallParams from pipecat.transports.base_transport import BaseTransport, TransportParams @@ -64,13 +64,16 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): tts = ElevenLabsTTSService( api_key=os.getenv("ELEVENLABS_API_KEY", ""), - voice_id=os.getenv("ELEVENLABS_VOICE_ID", ""), + settings=ElevenLabsTTSSettings( + voice_id=os.getenv("ELEVENLABS_VOICE_ID", ""), + ), ) llm = GoogleVertexLLMService( credentials=os.getenv("GOOGLE_VERTEX_TEST_CREDENTIALS"), project_id=os.getenv("GOOGLE_CLOUD_PROJECT_ID"), location=os.getenv("GOOGLE_CLOUD_LOCATION"), + system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", ) # You can aslo register a function_name of None to get all functions # sent to the same callback with an additional function_name parameter. diff --git a/examples/foundational/14q-function-calling-qwen.py b/examples/foundational/14q-function-calling-qwen.py index 32c551b29..58d34a3e1 100644 --- a/examples/foundational/14q-function-calling-qwen.py +++ b/examples/foundational/14q-function-calling-qwen.py @@ -24,7 +24,7 @@ from pipecat.processors.aggregators.llm_response_universal import ( ) from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport -from pipecat.services.cartesia.tts import CartesiaTTSService +from pipecat.services.cartesia.tts import CartesiaTTSService, CartesiaTTSSettings from pipecat.services.deepgram.stt import DeepgramSTTService from pipecat.services.llm_service import FunctionCallParams from pipecat.services.qwen.llm import QwenLLMService @@ -64,7 +64,9 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): tts = CartesiaTTSService( api_key=os.getenv("CARTESIA_API_KEY"), - voice_id="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady + settings=CartesiaTTSSettings( + voice="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady + ), ) llm = QwenLLMService( diff --git a/examples/foundational/14r-function-calling-aws.py b/examples/foundational/14r-function-calling-aws.py index 1ce5c4220..9e8e9836f 100644 --- a/examples/foundational/14r-function-calling-aws.py +++ b/examples/foundational/14r-function-calling-aws.py @@ -22,9 +22,9 @@ from pipecat.processors.aggregators.llm_response_universal import ( ) from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport -from pipecat.services.aws.llm import AWSBedrockLLMService +from pipecat.services.aws.llm import AWSBedrockLLMService, AWSBedrockLLMSettings from pipecat.services.aws.stt import AWSTranscribeSTTService -from pipecat.services.aws.tts import AWSPollyTTSService +from pipecat.services.aws.tts import AWSPollyTTSService, AWSPollyTTSSettings from pipecat.services.llm_service import FunctionCallParams from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams @@ -66,14 +66,19 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): tts = AWSPollyTTSService( region="us-west-2", # only specific regions support generative TTS - voice_id="Joanna", - params=AWSPollyTTSService.InputParams(engine="generative", rate="1.1"), + settings=AWSPollyTTSSettings( + voice_id="Joanna", + engine="generative", + rate="1.1", + ), ) llm = AWSBedrockLLMService( aws_region="us-west-2", - model="us.anthropic.claude-haiku-4-5-20251001-v1:0", - params=AWSBedrockLLMService.InputParams(temperature=0.8), + settings=AWSBedrockLLMSettings( + model="us.anthropic.claude-haiku-4-5-20251001-v1:0", + temperature=0.8, + ), system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", ) diff --git a/examples/foundational/14s-function-calling-sambanova.py b/examples/foundational/14s-function-calling-sambanova.py index 1548b2aa1..8cb007691 100644 --- a/examples/foundational/14s-function-calling-sambanova.py +++ b/examples/foundational/14s-function-calling-sambanova.py @@ -24,7 +24,7 @@ from pipecat.processors.aggregators.llm_response_universal import ( ) from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport -from pipecat.services.cartesia.tts import CartesiaTTSService +from pipecat.services.cartesia.tts import CartesiaTTSService, CartesiaTTSSettings from pipecat.services.llm_service import FunctionCallParams from pipecat.services.sambanova.llm import SambaNovaLLMService from pipecat.services.sambanova.stt import SambaNovaSTTService @@ -67,7 +67,9 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): tts = CartesiaTTSService( api_key=os.getenv("CARTESIA_API_KEY"), - voice_id="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady + settings=CartesiaTTSSettings( + voice="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady + ), ) llm = SambaNovaLLMService( diff --git a/examples/foundational/14t-function-calling-direct.py b/examples/foundational/14t-function-calling-direct.py index 31efb7ac9..b2912b91a 100644 --- a/examples/foundational/14t-function-calling-direct.py +++ b/examples/foundational/14t-function-calling-direct.py @@ -23,7 +23,7 @@ from pipecat.processors.aggregators.llm_response_universal import ( ) from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport -from pipecat.services.cartesia.tts import CartesiaTTSService +from pipecat.services.cartesia.tts import CartesiaTTSService, CartesiaTTSSettings from pipecat.services.deepgram.stt import DeepgramSTTService from pipecat.services.llm_service import FunctionCallParams from pipecat.services.openai.llm import OpenAILLMService @@ -80,7 +80,9 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): tts = CartesiaTTSService( api_key=os.getenv("CARTESIA_API_KEY"), - voice_id="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady + settings=CartesiaTTSSettings( + voice="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady + ), ) llm = OpenAILLMService( diff --git a/examples/foundational/14u-function-calling-ollama.py b/examples/foundational/14u-function-calling-ollama.py index b7c65dedf..53b81402d 100644 --- a/examples/foundational/14u-function-calling-ollama.py +++ b/examples/foundational/14u-function-calling-ollama.py @@ -24,10 +24,10 @@ from pipecat.processors.aggregators.llm_response_universal import ( ) from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport -from pipecat.services.cartesia.tts import CartesiaTTSService +from pipecat.services.cartesia.tts import CartesiaTTSService, CartesiaTTSSettings from pipecat.services.deepgram.stt import DeepgramSTTService from pipecat.services.llm_service import FunctionCallParams -from pipecat.services.ollama.llm import OLLamaLLMService +from pipecat.services.ollama.llm import OLLamaLLMService, OLLamaLLMSettings from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams @@ -68,11 +68,15 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): tts = CartesiaTTSService( api_key=os.getenv("CARTESIA_API_KEY"), - voice_id="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady + settings=CartesiaTTSSettings( + voice="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady + ), ) llm = OLLamaLLMService( - model="llama3.2", + settings=OLLamaLLMSettings( + model="llama3.2", + ), system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", ) # Update to the model you're running locally diff --git a/examples/foundational/14v-function-calling-openai.py b/examples/foundational/14v-function-calling-openai.py index 920275975..77bacc091 100644 --- a/examples/foundational/14v-function-calling-openai.py +++ b/examples/foundational/14v-function-calling-openai.py @@ -25,8 +25,8 @@ from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport from pipecat.services.llm_service import FunctionCallParams from pipecat.services.openai.llm import OpenAILLMService -from pipecat.services.openai.stt import OpenAISTTService -from pipecat.services.openai.tts import OpenAITTSService +from pipecat.services.openai.stt import OpenAISTTService, OpenAISTTSettings +from pipecat.services.openai.tts import OpenAITTSService, OpenAITTSSettings from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams @@ -65,15 +65,17 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): stt = OpenAISTTService( api_key=os.getenv("OPENAI_API_KEY"), - model="gpt-4o-transcribe", - prompt="Expect words related weather, such as temperature and conditions. And restaurant names.", + settings=OpenAISTTSettings( + model="gpt-4o-transcribe", + prompt="Expect words related weather, such as temperature and conditions. And restaurant names.", + ), ) - # voice choices: ash, ballad, or any other voice available in the OpenAI TTS API - # see https://www.openai.fm/ tts = OpenAITTSService( api_key=os.getenv("OPENAI_API_KEY"), - voice="ballad", + settings=OpenAITTSSettings( + voice="ballad", + ), instructions="Please speak clearly and at a moderate pace.", ) diff --git a/examples/foundational/14w-function-calling-mistral.py b/examples/foundational/14w-function-calling-mistral.py index e17d31f72..fa809414b 100644 --- a/examples/foundational/14w-function-calling-mistral.py +++ b/examples/foundational/14w-function-calling-mistral.py @@ -23,7 +23,7 @@ from pipecat.processors.aggregators.llm_response_universal import ( ) from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport -from pipecat.services.cartesia.tts import CartesiaTTSService +from pipecat.services.cartesia.tts import CartesiaTTSService, CartesiaTTSSettings from pipecat.services.deepgram.stt import DeepgramSTTService from pipecat.services.llm_service import FunctionCallParams from pipecat.services.mistral.llm import MistralLLMService @@ -67,7 +67,9 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): tts = CartesiaTTSService( api_key=os.getenv("CARTESIA_API_KEY"), - voice_id="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady + settings=CartesiaTTSSettings( + voice="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady + ), ) llm = MistralLLMService( diff --git a/examples/foundational/14x-function-calling-openpipe.py b/examples/foundational/14x-function-calling-openpipe.py index 8a71a83d7..61382c435 100644 --- a/examples/foundational/14x-function-calling-openpipe.py +++ b/examples/foundational/14x-function-calling-openpipe.py @@ -24,7 +24,7 @@ from pipecat.processors.aggregators.llm_response_universal import ( ) from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport -from pipecat.services.cartesia.tts import CartesiaTTSService +from pipecat.services.cartesia.tts import CartesiaTTSService, CartesiaTTSSettings from pipecat.services.deepgram.stt import DeepgramSTTService from pipecat.services.llm_service import FunctionCallParams from pipecat.services.openpipe.llm import OpenPipeLLMService @@ -68,7 +68,9 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): tts = CartesiaTTSService( api_key=os.getenv("CARTESIA_API_KEY"), - voice_id="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady + settings=CartesiaTTSSettings( + voice="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady + ), ) timestamp = int(time.time()) diff --git a/examples/foundational/15-switch-voices.py b/examples/foundational/15-switch-voices.py index 4478c067b..f749a03c7 100644 --- a/examples/foundational/15-switch-voices.py +++ b/examples/foundational/15-switch-voices.py @@ -26,7 +26,7 @@ from pipecat.processors.aggregators.llm_response_universal import ( from pipecat.processors.filters.function_filter import FunctionFilter from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport -from pipecat.services.cartesia.tts import CartesiaTTSService +from pipecat.services.cartesia.tts import CartesiaTTSService, CartesiaTTSSettings from pipecat.services.deepgram.stt import DeepgramSTTService from pipecat.services.llm_service import FunctionCallParams from pipecat.services.openai.llm import OpenAILLMService @@ -43,17 +43,23 @@ class SwitchVoices(ParallelPipeline): news_lady = CartesiaTTSService( api_key=os.getenv("CARTESIA_API_KEY"), - voice_id="bf991597-6c13-47e4-8411-91ec2de5c466", # Newslady + settings=CartesiaTTSSettings( + voice="bf991597-6c13-47e4-8411-91ec2de5c466", # Newslady + ), ) british_lady = CartesiaTTSService( api_key=os.getenv("CARTESIA_API_KEY"), - voice_id="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady + settings=CartesiaTTSSettings( + voice="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady + ), ) barbershop_man = CartesiaTTSService( api_key=os.getenv("CARTESIA_API_KEY"), - voice_id="a0e99841-438c-4a64-b679-ae501e7d6091", # Barbershop Man + settings=CartesiaTTSSettings( + voice="a0e99841-438c-4a64-b679-ae501e7d6091", # Barbershop Man + ), ) super().__init__( diff --git a/examples/foundational/15a-switch-languages.py b/examples/foundational/15a-switch-languages.py index 3ad897077..dad7e0ee3 100644 --- a/examples/foundational/15a-switch-languages.py +++ b/examples/foundational/15a-switch-languages.py @@ -27,7 +27,7 @@ from pipecat.processors.aggregators.llm_response_universal import ( from pipecat.processors.filters.function_filter import FunctionFilter from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport -from pipecat.services.cartesia.tts import CartesiaTTSService +from pipecat.services.cartesia.tts import CartesiaTTSService, CartesiaTTSSettings from pipecat.services.deepgram.stt import DeepgramSTTService from pipecat.services.llm_service import FunctionCallParams from pipecat.services.openai.llm import OpenAILLMService @@ -44,12 +44,16 @@ class SwitchLanguage(ParallelPipeline): english_tts = CartesiaTTSService( api_key=os.getenv("CARTESIA_API_KEY"), - voice_id="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady + settings=CartesiaTTSSettings( + voice="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady + ), ) spanish_tts = CartesiaTTSService( api_key=os.getenv("CARTESIA_API_KEY"), - voice_id="d4db5fb9-f44b-4bd1-85fa-192e0f0d75f9", # Spanish-speaking Lady + settings=CartesiaTTSSettings( + voice="d4db5fb9-f44b-4bd1-85fa-192e0f0d75f9", # Spanish-speaking Lady + ), ) super().__init__( diff --git a/examples/foundational/16-gpu-container-local-bot.py b/examples/foundational/16-gpu-container-local-bot.py index 8367e1044..cf02b37ce 100644 --- a/examples/foundational/16-gpu-container-local-bot.py +++ b/examples/foundational/16-gpu-container-local-bot.py @@ -23,8 +23,8 @@ from pipecat.processors.aggregators.llm_response_universal import ( from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport from pipecat.services.deepgram.stt import DeepgramSTTService -from pipecat.services.deepgram.tts import DeepgramTTSService -from pipecat.services.openai.llm import OpenAILLMService +from pipecat.services.deepgram.tts import DeepgramTTSService, DeepgramTTSSettings +from pipecat.services.openai.llm import OpenAILLMService, OpenAILLMSettings from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import ( DailyOutputTransportMessageFrame, @@ -60,7 +60,9 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): tts = DeepgramTTSService( api_key=os.getenv("DEEPGRAM_API_KEY"), - voice="aura-asteria-en", + settings=DeepgramTTSSettings( + voice="aura-asteria-en", + ), base_url="http://0.0.0.0:8080", ) @@ -68,7 +70,9 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): # To use OpenAI # api_key=os.getenv("OPENAI_API_KEY"), # Or, to use a local vLLM (or similar) api server - model="meta-llama/Meta-Llama-3-8B-Instruct", + settings=OpenAILLMSettings( + model="meta-llama/Meta-Llama-3-8B-Instruct", + ), base_url="http://0.0.0.0:8000/v1", system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", ) diff --git a/examples/foundational/17-detect-user-idle.py b/examples/foundational/17-detect-user-idle.py index 217162ea8..9da863bc9 100644 --- a/examples/foundational/17-detect-user-idle.py +++ b/examples/foundational/17-detect-user-idle.py @@ -32,7 +32,7 @@ from pipecat.processors.aggregators.llm_response_universal import ( from pipecat.processors.frame_processor import FrameDirection from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport -from pipecat.services.cartesia.tts import CartesiaTTSService +from pipecat.services.cartesia.tts import CartesiaTTSService, CartesiaTTSSettings from pipecat.services.deepgram.stt import DeepgramSTTService from pipecat.services.llm_service import FunctionCallParams from pipecat.services.openai.llm import OpenAILLMService @@ -115,7 +115,9 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): tts = CartesiaTTSService( api_key=os.getenv("CARTESIA_API_KEY"), - voice_id="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady + settings=CartesiaTTSSettings( + voice="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady + ), ) llm = OpenAILLMService( diff --git a/examples/foundational/19b-openai-realtime-beta-text.py b/examples/foundational/19b-openai-realtime-beta-text.py index 83e1563a0..7a4ad3469 100644 --- a/examples/foundational/19b-openai-realtime-beta-text.py +++ b/examples/foundational/19b-openai-realtime-beta-text.py @@ -21,7 +21,7 @@ from pipecat.pipeline.task import PipelineParams, PipelineTask from pipecat.processors.aggregators.openai_llm_context import OpenAILLMContext from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport -from pipecat.services.cartesia.tts import CartesiaTTSService +from pipecat.services.cartesia.tts import CartesiaTTSService, CartesiaTTSSettings from pipecat.services.llm_service import FunctionCallParams from pipecat.services.openai_realtime_beta import ( InputAudioNoiseReduction, @@ -147,7 +147,9 @@ Remember, your responses should be short. Just one or two sentences, usually. Re tts = CartesiaTTSService( api_key=os.getenv("CARTESIA_API_KEY"), - voice_id="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady + settings=CartesiaTTSSettings( + voice="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady + ), ) # you can either register a single function for all function calls, or specific functions diff --git a/examples/foundational/19b-openai-realtime-text.py b/examples/foundational/19b-openai-realtime-text.py index 38731d72a..98dc81c3b 100644 --- a/examples/foundational/19b-openai-realtime-text.py +++ b/examples/foundational/19b-openai-realtime-text.py @@ -22,7 +22,7 @@ from pipecat.processors.aggregators.llm_context import LLMContext from pipecat.processors.aggregators.llm_response_universal import LLMContextAggregatorPair from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport -from pipecat.services.cartesia.tts import CartesiaTTSService +from pipecat.services.cartesia.tts import CartesiaTTSService, CartesiaTTSSettings from pipecat.services.llm_service import FunctionCallParams from pipecat.services.openai.realtime.events import ( AudioConfiguration, @@ -154,7 +154,9 @@ Remember, your responses should be short. Just one or two sentences, usually. Re tts = CartesiaTTSService( api_key=os.getenv("CARTESIA_API_KEY"), - voice_id="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady + settings=CartesiaTTSSettings( + voice="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady + ), ) # you can either register a single function for all function calls, or specific functions diff --git a/examples/foundational/20a-persistent-context-openai.py b/examples/foundational/20a-persistent-context-openai.py index be40add52..acdcefb92 100644 --- a/examples/foundational/20a-persistent-context-openai.py +++ b/examples/foundational/20a-persistent-context-openai.py @@ -26,7 +26,7 @@ from pipecat.processors.aggregators.llm_response_universal import ( ) from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport -from pipecat.services.cartesia.tts import CartesiaTTSService +from pipecat.services.cartesia.tts import CartesiaTTSService, CartesiaTTSSettings from pipecat.services.deepgram.stt import DeepgramSTTService from pipecat.services.llm_service import FunctionCallParams from pipecat.services.openai.llm import OpenAILLMService @@ -180,7 +180,9 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): tts = CartesiaTTSService( api_key=os.getenv("CARTESIA_API_KEY"), - voice_id="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady + settings=CartesiaTTSSettings( + voice="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady + ), ) llm = OpenAILLMService(api_key=os.getenv("OPENAI_API_KEY")) diff --git a/examples/foundational/20c-persistent-context-anthropic.py b/examples/foundational/20c-persistent-context-anthropic.py index d99f4debf..5f2a3f317 100644 --- a/examples/foundational/20c-persistent-context-anthropic.py +++ b/examples/foundational/20c-persistent-context-anthropic.py @@ -27,7 +27,7 @@ from pipecat.processors.aggregators.llm_response_universal import ( from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport from pipecat.services.anthropic.llm import AnthropicLLMService -from pipecat.services.cartesia.tts import CartesiaTTSService +from pipecat.services.cartesia.tts import CartesiaTTSService, CartesiaTTSSettings from pipecat.services.deepgram.stt import DeepgramSTTService from pipecat.services.llm_service import FunctionCallParams from pipecat.transports.base_transport import BaseTransport, TransportParams @@ -189,12 +189,12 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): tts = CartesiaTTSService( api_key=os.getenv("CARTESIA_API_KEY"), - voice_id="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady + settings=CartesiaTTSSettings( + voice="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady + ), ) - llm = AnthropicLLMService( - api_key=os.getenv("ANTHROPIC_API_KEY"), model="claude-3-5-sonnet-latest" - ) + llm = AnthropicLLMService(api_key=os.getenv("ANTHROPIC_API_KEY")) # you can either register a single function for all function calls, or specific functions # llm.register_function(None, fetch_weather_from_api) diff --git a/examples/foundational/20d-persistent-context-gemini.py b/examples/foundational/20d-persistent-context-gemini.py index 3bcd3c106..ca5186532 100644 --- a/examples/foundational/20d-persistent-context-gemini.py +++ b/examples/foundational/20d-persistent-context-gemini.py @@ -31,7 +31,7 @@ from pipecat.runner.utils import ( get_transport_client_id, maybe_capture_participant_camera, ) -from pipecat.services.cartesia.tts import CartesiaTTSService +from pipecat.services.cartesia.tts import CartesiaTTSService, CartesiaTTSSettings from pipecat.services.deepgram.stt import DeepgramSTTService from pipecat.services.google.llm import GoogleLLMService from pipecat.services.llm_service import FunctionCallParams @@ -257,7 +257,9 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): tts = CartesiaTTSService( api_key=os.getenv("CARTESIA_API_KEY"), - voice_id="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady + settings=CartesiaTTSSettings( + voice="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady + ), ) llm = GoogleLLMService(api_key=os.getenv("GOOGLE_API_KEY")) diff --git a/examples/foundational/21-tavus-transport.py b/examples/foundational/21-tavus-transport.py index b16ebbf38..06d904c21 100644 --- a/examples/foundational/21-tavus-transport.py +++ b/examples/foundational/21-tavus-transport.py @@ -22,7 +22,7 @@ from pipecat.processors.aggregators.llm_response_universal import ( LLMContextAggregatorPair, LLMUserAggregatorParams, ) -from pipecat.services.cartesia.tts import CartesiaTTSService +from pipecat.services.cartesia.tts import CartesiaTTSService, CartesiaTTSSettings from pipecat.services.deepgram.stt import DeepgramSTTService from pipecat.services.google.llm import GoogleLLMService from pipecat.transports.tavus.transport import TavusParams, TavusTransport @@ -51,7 +51,9 @@ async def main(): tts = CartesiaTTSService( api_key=os.getenv("CARTESIA_API_KEY"), - voice_id="a167e0f3-df7e-4d52-a9c3-f949145efdab", + settings=CartesiaTTSSettings( + voice="a167e0f3-df7e-4d52-a9c3-f949145efdab", + ), ) llm = GoogleLLMService( diff --git a/examples/foundational/21a-tavus-video-service.py b/examples/foundational/21a-tavus-video-service.py index 7e32579b0..c756a7821 100644 --- a/examples/foundational/21a-tavus-video-service.py +++ b/examples/foundational/21a-tavus-video-service.py @@ -23,7 +23,7 @@ from pipecat.processors.aggregators.llm_response_universal import ( ) from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport -from pipecat.services.cartesia.tts import CartesiaTTSService +from pipecat.services.cartesia.tts import CartesiaTTSService, CartesiaTTSSettings from pipecat.services.deepgram.stt import DeepgramSTTService from pipecat.services.google.llm import GoogleLLMService from pipecat.services.tavus.video import TavusVideoService @@ -61,7 +61,9 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): tts = CartesiaTTSService( api_key=os.getenv("CARTESIA_API_KEY"), - voice_id="a167e0f3-df7e-4d52-a9c3-f949145efdab", + settings=CartesiaTTSSettings( + voice="a167e0f3-df7e-4d52-a9c3-f949145efdab", + ), ) llm = GoogleLLMService( diff --git a/examples/foundational/22-filter-incomplete-turns.py b/examples/foundational/22-filter-incomplete-turns.py index b7d094d1e..876999bcd 100644 --- a/examples/foundational/22-filter-incomplete-turns.py +++ b/examples/foundational/22-filter-incomplete-turns.py @@ -35,7 +35,7 @@ from pipecat.processors.aggregators.llm_response_universal import ( ) from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport -from pipecat.services.cartesia.tts import CartesiaTTSService +from pipecat.services.cartesia.tts import CartesiaTTSService, CartesiaTTSSettings from pipecat.services.deepgram.stt import DeepgramSTTService from pipecat.services.openai.llm import OpenAILLMService from pipecat.transports.base_transport import BaseTransport, TransportParams @@ -68,21 +68,19 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): stt = DeepgramSTTService(api_key=os.getenv("DEEPGRAM_API_KEY")) - llm = OpenAILLMService(api_key=os.getenv("OPENAI_API_KEY")) + llm = OpenAILLMService( + api_key=os.getenv("OPENAI_API_KEY"), + system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + ) tts = CartesiaTTSService( api_key=os.getenv("CARTESIA_API_KEY"), - voice_id="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady + settings=CartesiaTTSSettings( + voice="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady + ), ) - messages = [ - { - "role": "system", - "content": f"""You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.""", - } - ] - - context = LLMContext(messages) + context = LLMContext() user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, user_params=LLMUserAggregatorParams( @@ -128,9 +126,9 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): async def on_client_connected(transport, client): logger.info(f"Client connected") # Kick off the conversation. - messages.append( + context.add_message( { - "role": "system", + "role": "user", "content": "Please introduce yourself to the user, asking them a question that will require a complete response. To start, say 'Let me start with a fun one. If you could travel anywhere in the world right now, where would you go and why?'", } ) diff --git a/examples/foundational/23-bot-background-sound.py b/examples/foundational/23-bot-background-sound.py index a57e8f446..a88ebc9bc 100644 --- a/examples/foundational/23-bot-background-sound.py +++ b/examples/foundational/23-bot-background-sound.py @@ -24,7 +24,7 @@ from pipecat.processors.aggregators.llm_response_universal import ( ) from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport -from pipecat.services.cartesia.tts import CartesiaTTSService +from pipecat.services.cartesia.tts import CartesiaTTSService, CartesiaTTSSettings from pipecat.services.deepgram.stt import DeepgramSTTService from pipecat.services.openai.llm import OpenAILLMService from pipecat.transports.base_transport import BaseTransport, TransportParams @@ -75,7 +75,9 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): tts = CartesiaTTSService( api_key=os.getenv("CARTESIA_API_KEY"), - voice_id="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady + settings=CartesiaTTSSettings( + voice="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady + ), ) llm = OpenAILLMService( diff --git a/examples/foundational/24-user-mute-strategy.py b/examples/foundational/24-user-mute-strategy.py index 36b537e6a..d4276f04a 100644 --- a/examples/foundational/24-user-mute-strategy.py +++ b/examples/foundational/24-user-mute-strategy.py @@ -26,7 +26,7 @@ from pipecat.processors.aggregators.llm_response_universal import ( from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport from pipecat.services.deepgram.stt import DeepgramSTTService -from pipecat.services.deepgram.tts import DeepgramTTSService +from pipecat.services.deepgram.tts import DeepgramTTSService, DeepgramTTSSettings from pipecat.services.llm_service import FunctionCallParams from pipecat.services.openai.llm import OpenAILLMService from pipecat.transports.base_transport import BaseTransport, TransportParams @@ -71,7 +71,12 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): stt = DeepgramSTTService(api_key=os.getenv("DEEPGRAM_API_KEY")) - tts = DeepgramTTSService(api_key=os.getenv("DEEPGRAM_API_KEY"), voice="aura-helios-en") + tts = DeepgramTTSService( + api_key=os.getenv("DEEPGRAM_API_KEY"), + settings=DeepgramTTSSettings( + voice="aura-2-helena-en", + ), + ) llm = OpenAILLMService( api_key=os.getenv("OPENAI_API_KEY"), diff --git a/examples/foundational/25-google-audio-in.py b/examples/foundational/25-google-audio-in.py index 40903e1d5..a278ea4b3 100644 --- a/examples/foundational/25-google-audio-in.py +++ b/examples/foundational/25-google-audio-in.py @@ -32,8 +32,8 @@ from pipecat.processors.aggregators.llm_response_universal import LLMContextAggr from pipecat.processors.frame_processor import FrameProcessor from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport -from pipecat.services.cartesia.tts import CartesiaTTSService -from pipecat.services.google.llm import GoogleLLMService +from pipecat.services.cartesia.tts import CartesiaTTSService, CartesiaTTSSettings +from pipecat.services.google.llm import GoogleLLMService, GoogleLLMSettings from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams @@ -290,13 +290,16 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): tts = CartesiaTTSService( api_key=os.getenv("CARTESIA_API_KEY"), - voice_id="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady + settings=CartesiaTTSSettings( + voice="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady + ), ) conversation_llm = GoogleLLMService( name="Conversation", - model="gemini-2.0-flash-001", - # model="gemini-exp-1121", + settings=GoogleLLMSettings( + model="gemini-2.5-flash", + ), api_key=os.getenv("GOOGLE_API_KEY"), # we can give the GoogleLLMService a system instruction to use directly # in the GenerativeModel constructor. Let's do that rather than put @@ -306,8 +309,9 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): input_transcription_llm = GoogleLLMService( name="Transcription", - model="gemini-2.0-flash-001", - # model="gemini-exp-1121", + settings=GoogleLLMSettings( + model="gemini-2.5-flash", + ), api_key=os.getenv("GOOGLE_API_KEY"), system_instruction=transcriber_system_message, ) diff --git a/examples/foundational/26d-gemini-live-text.py b/examples/foundational/26d-gemini-live-text.py index 1b3845fa3..eebe9874d 100644 --- a/examples/foundational/26d-gemini-live-text.py +++ b/examples/foundational/26d-gemini-live-text.py @@ -23,7 +23,7 @@ from pipecat.processors.aggregators.llm_response_universal import ( ) from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport -from pipecat.services.cartesia.tts import CartesiaTTSService +from pipecat.services.cartesia.tts import CartesiaTTSService, CartesiaTTSSettings from pipecat.services.google.gemini_live.llm import ( GeminiLiveLLMService, GeminiModalities, diff --git a/examples/foundational/27-simli-layer.py b/examples/foundational/27-simli-layer.py index fb469fbe1..05d0649d6 100644 --- a/examples/foundational/27-simli-layer.py +++ b/examples/foundational/27-simli-layer.py @@ -22,9 +22,9 @@ from pipecat.processors.aggregators.llm_response_universal import ( ) from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport -from pipecat.services.cartesia.tts import CartesiaTTSService +from pipecat.services.cartesia.tts import CartesiaTTSService, CartesiaTTSSettings from pipecat.services.deepgram.stt import DeepgramSTTService -from pipecat.services.openai.llm import OpenAILLMService +from pipecat.services.openai.llm import OpenAILLMService, OpenAILLMSettings from pipecat.services.simli.video import SimliVideoService from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams @@ -60,7 +60,9 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): tts = CartesiaTTSService( api_key=os.getenv("CARTESIA_API_KEY"), - voice_id="71a7ad14-091c-4e8e-a314-022ece01c121", + settings=CartesiaTTSSettings( + voice="71a7ad14-091c-4e8e-a314-022ece01c121", + ), ) simli_ai = SimliVideoService( @@ -70,7 +72,9 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): llm = OpenAILLMService( api_key=os.getenv("OPENAI_API_KEY"), - model="gpt-4o-mini", + settings=OpenAILLMSettings( + model="gpt-4o-mini", + ), system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", ) diff --git a/examples/foundational/28-user-assistant-turns.py b/examples/foundational/28-user-assistant-turns.py index 9dd1fa2a1..d59ad3870 100644 --- a/examples/foundational/28-user-assistant-turns.py +++ b/examples/foundational/28-user-assistant-turns.py @@ -24,7 +24,7 @@ from pipecat.processors.aggregators.llm_response_universal import ( ) from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport -from pipecat.services.cartesia.tts import CartesiaTTSService +from pipecat.services.cartesia.tts import CartesiaTTSService, CartesiaTTSSettings from pipecat.services.deepgram.stt import DeepgramSTTService from pipecat.services.openai.llm import OpenAILLMService from pipecat.transports.base_transport import BaseTransport, TransportParams @@ -122,7 +122,9 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): tts = CartesiaTTSService( api_key=os.getenv("CARTESIA_API_KEY"), - voice_id="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady + settings=CartesiaTTSSettings( + voice="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady + ), ) llm = OpenAILLMService( diff --git a/examples/foundational/29-turn-tracking-observer.py b/examples/foundational/29-turn-tracking-observer.py index 9ba22dfda..0dd164bd0 100644 --- a/examples/foundational/29-turn-tracking-observer.py +++ b/examples/foundational/29-turn-tracking-observer.py @@ -27,7 +27,7 @@ from pipecat.processors.aggregators.llm_response_universal import ( ) from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport -from pipecat.services.cartesia.tts import CartesiaTTSService +from pipecat.services.cartesia.tts import CartesiaTTSService, CartesiaTTSSettings from pipecat.services.deepgram.stt import DeepgramSTTService from pipecat.services.llm_service import FunctionCallParams from pipecat.services.openai.llm import OpenAILLMService @@ -73,7 +73,9 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): tts = CartesiaTTSService( api_key=os.getenv("CARTESIA_API_KEY"), - voice_id="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady + settings=CartesiaTTSSettings( + voice="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady + ), ) llm = OpenAILLMService( diff --git a/examples/foundational/30-observer.py b/examples/foundational/30-observer.py index 4616e0e03..5ee0bdaed 100644 --- a/examples/foundational/30-observer.py +++ b/examples/foundational/30-observer.py @@ -34,7 +34,7 @@ from pipecat.processors.aggregators.llm_response_universal import ( from pipecat.processors.frame_processor import FrameDirection from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport -from pipecat.services.cartesia.tts import CartesiaTTSService +from pipecat.services.cartesia.tts import CartesiaTTSService, CartesiaTTSSettings from pipecat.services.deepgram.stt import DeepgramSTTService from pipecat.services.openai.llm import OpenAILLMService from pipecat.transports.base_input import BaseInputTransport @@ -104,7 +104,9 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): tts = CartesiaTTSService( api_key=os.getenv("CARTESIA_API_KEY"), - voice_id="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady + settings=CartesiaTTSSettings( + voice="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady + ), ) llm = OpenAILLMService( diff --git a/examples/foundational/32-gemini-grounding-metadata.py b/examples/foundational/32-gemini-grounding-metadata.py index 19844b1fa..2977e19bc 100644 --- a/examples/foundational/32-gemini-grounding-metadata.py +++ b/examples/foundational/32-gemini-grounding-metadata.py @@ -25,7 +25,7 @@ from pipecat.processors.aggregators.llm_response_universal import ( ) from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport -from pipecat.services.cartesia.tts import CartesiaTTSService +from pipecat.services.cartesia.tts import CartesiaTTSService, CartesiaTTSSettings from pipecat.services.deepgram.stt import DeepgramSTTService from pipecat.services.google.llm import GoogleLLMService, LLMSearchResponseFrame from pipecat.services.llm_service import LLMService @@ -99,7 +99,9 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): tts = CartesiaTTSService( api_key=os.getenv("CARTESIA_API_KEY"), - voice_id="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady + settings=CartesiaTTSSettings( + voice="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady + ), ) # Initialize the Gemini Multimodal Live model diff --git a/examples/foundational/33-gemini-rag.py b/examples/foundational/33-gemini-rag.py index ae95ce117..c34a9c83e 100644 --- a/examples/foundational/33-gemini-rag.py +++ b/examples/foundational/33-gemini-rag.py @@ -69,9 +69,9 @@ from pipecat.processors.aggregators.llm_response_universal import ( ) from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport -from pipecat.services.cartesia.tts import CartesiaTTSService +from pipecat.services.cartesia.tts import CartesiaTTSService, CartesiaTTSSettings from pipecat.services.deepgram.stt import DeepgramSTTService -from pipecat.services.google.llm import GoogleLLMService +from pipecat.services.google.llm import GoogleLLMService, GoogleLLMSettings from pipecat.services.llm_service import FunctionCallParams from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams @@ -183,11 +183,24 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): tts = CartesiaTTSService( api_key=os.getenv("CARTESIA_API_KEY"), - voice_id="f9836c6e-a0bd-460e-9d3c-f7299fa60f94", # Southern Lady + settings=CartesiaTTSSettings( + voice="f9836c6e-a0bd-460e-9d3c-f7299fa60f94", # Southern Lady + ), ) + system_prompt = """\ +You are a helpful assistant who converses with a user and answers questions. + +You have access to the tool, query_knowledge_base, that allows you to query the knowledge base for the answer to the user's question. + +Your response will be turned into speech so use only simple words and punctuation. +""" + llm = GoogleLLMService( - model=VOICE_MODEL, + settings=GoogleLLMSettings( + model=VOICE_MODEL, + ), + system_instruction=system_prompt, api_key=os.getenv("GOOGLE_API_KEY"), ) llm.register_function("query_knowledge_base", query_knowledge_base) @@ -205,15 +218,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): ) tools = ToolsSchema(standard_tools=[query_function]) - system_prompt = """\ -You are a helpful assistant who converses with a user and answers questions. - -You have access to the tool, query_knowledge_base, that allows you to query the knowledge base for the answer to the user's question. - -Your response will be turned into speech so use only simple words and punctuation. -""" messages = [ - {"role": "system", "content": system_prompt}, {"role": "user", "content": "Greet the user."}, ] diff --git a/examples/foundational/34-audio-recording.py b/examples/foundational/34-audio-recording.py index 8435acbde..aa52c213a 100644 --- a/examples/foundational/34-audio-recording.py +++ b/examples/foundational/34-audio-recording.py @@ -63,7 +63,7 @@ from pipecat.processors.aggregators.llm_response_universal import ( from pipecat.processors.audio.audio_buffer_processor import AudioBufferProcessor from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport -from pipecat.services.cartesia.tts import CartesiaTTSService +from pipecat.services.cartesia.tts import CartesiaTTSService, CartesiaTTSSettings from pipecat.services.deepgram.stt import DeepgramSTTService from pipecat.services.openai.llm import OpenAILLMService from pipecat.transports.base_transport import BaseTransport, TransportParams @@ -112,12 +112,13 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): tts = CartesiaTTSService( api_key=os.getenv("CARTESIA_API_KEY"), - voice_id="71a7ad14-091c-4e8e-a314-022ece01c121", + settings=CartesiaTTSSettings( + voice="71a7ad14-091c-4e8e-a314-022ece01c121", + ), ) llm = OpenAILLMService( api_key=os.getenv("OPENAI_API_KEY"), - model="gpt-4", system_instruction="You are a helpful assistant demonstrating audio recording capabilities. Keep your responses brief and clear.", ) diff --git a/examples/foundational/35-pattern-pair-voice-switching.py b/examples/foundational/35-pattern-pair-voice-switching.py index cacc04459..c10e185b0 100644 --- a/examples/foundational/35-pattern-pair-voice-switching.py +++ b/examples/foundational/35-pattern-pair-voice-switching.py @@ -56,7 +56,7 @@ from pipecat.processors.aggregators.llm_response_universal import ( ) from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport -from pipecat.services.cartesia.tts import CartesiaTTSService +from pipecat.services.cartesia.tts import CartesiaTTSService, CartesiaTTSSettings from pipecat.services.deepgram.stt import DeepgramSTTService from pipecat.services.openai.llm import OpenAILLMService from pipecat.transports.base_transport import BaseTransport, TransportParams @@ -129,13 +129,12 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): # Initialize TTS with narrator voice as default tts = CartesiaTTSService( api_key=os.getenv("CARTESIA_API_KEY"), - voice_id=VOICE_IDS["narrator"], + settings=CartesiaTTSSettings( + voice=VOICE_IDS["narrator"], + ), text_aggregator=pattern_aggregator, ) - # Initialize LLM - llm = OpenAILLMService(api_key=os.getenv("OPENAI_API_KEY")) - # System prompt for storytelling with voice switching system_prompt = """You are an engaging storyteller that uses different voices to bring stories to life. @@ -184,15 +183,13 @@ FOLLOW THESE RULES: Remember: Use narrator voice for EVERYTHING except the actual quoted dialogue.""" - # Set up LLM context - messages = [ - { - "role": "system", - "content": system_prompt, - }, - ] + # Initialize LLM + llm = OpenAILLMService( + api_key=os.getenv("OPENAI_API_KEY"), + system_instruction=system_prompt, + ) - context = LLMContext(messages) + context = LLMContext() user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()), diff --git a/examples/foundational/36-user-email-gathering.py b/examples/foundational/36-user-email-gathering.py index 95450c695..9c4bdd4ac 100644 --- a/examples/foundational/36-user-email-gathering.py +++ b/examples/foundational/36-user-email-gathering.py @@ -24,7 +24,7 @@ from pipecat.processors.aggregators.llm_response_universal import ( ) from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport -from pipecat.services.cartesia.tts import CartesiaTTSService +from pipecat.services.cartesia.tts import CartesiaTTSService, CartesiaTTSSettings from pipecat.services.deepgram.stt import DeepgramSTTService from pipecat.services.llm_service import FunctionCallParams from pipecat.services.openai.llm import OpenAILLMService @@ -67,7 +67,9 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): # (see https://docs.cartesia.ai/build-with-sonic/formatting-text-for-sonic/spelling-out-input-text) tts = CartesiaTTSService( api_key=os.getenv("CARTESIA_API_KEY"), - voice_id="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady + settings=CartesiaTTSSettings( + voice="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady + ), ) # Rime offers a function `spell()` that we can use to ask the user diff --git a/examples/foundational/37-mem0.py b/examples/foundational/37-mem0.py index bfc651f3a..e02d86915 100644 --- a/examples/foundational/37-mem0.py +++ b/examples/foundational/37-mem0.py @@ -60,9 +60,9 @@ from pipecat.processors.aggregators.llm_response_universal import ( from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport from pipecat.services.deepgram.stt import DeepgramSTTService -from pipecat.services.elevenlabs.tts import ElevenLabsTTSService +from pipecat.services.elevenlabs.tts import ElevenLabsTTSService, ElevenLabsTTSSettings from pipecat.services.mem0.memory import Mem0MemoryService -from pipecat.services.openai.llm import OpenAILLMService +from pipecat.services.openai.llm import OpenAILLMService, OpenAILLMSettings from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams @@ -166,7 +166,9 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): # Initialize text-to-speech service tts = ElevenLabsTTSService( api_key=os.getenv("ELEVENLABS_API_KEY"), - voice_id="pNInz6obpgDQGcFmaJgB", + settings=ElevenLabsTTSSettings( + voice="pNInz6obpgDQGcFmaJgB", + ), ) # ===================================================================== @@ -223,7 +225,9 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): # Initialize LLM service llm = OpenAILLMService( api_key=os.getenv("OPENAI_API_KEY"), - model="gpt-4o-mini", + settings=OpenAILLMSettings( + model="gpt-4o-mini", + ), system_instruction="""You are a personal assistant. You can remember things about the person you are talking to. Some Guidelines: - Make sure your responses are friendly yet short and concise. diff --git a/examples/foundational/38-smart-turn-fal.py b/examples/foundational/38-smart-turn-fal.py index fe8992784..384652b29 100644 --- a/examples/foundational/38-smart-turn-fal.py +++ b/examples/foundational/38-smart-turn-fal.py @@ -24,7 +24,7 @@ from pipecat.processors.aggregators.llm_response_universal import ( ) from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport -from pipecat.services.cartesia.tts import CartesiaTTSService +from pipecat.services.cartesia.tts import CartesiaTTSService, CartesiaTTSSettings from pipecat.services.deepgram.stt import DeepgramSTTService from pipecat.services.openai.llm import OpenAILLMService from pipecat.transports.base_transport import BaseTransport, TransportParams @@ -61,7 +61,9 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): tts = CartesiaTTSService( api_key=os.getenv("CARTESIA_API_KEY"), - voice_id="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady + settings=CartesiaTTSSettings( + voice="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady + ), ) llm = OpenAILLMService( diff --git a/examples/foundational/38a-smart-turn-local-coreml.py b/examples/foundational/38a-smart-turn-local-coreml.py index 166fbbe12..01585982d 100644 --- a/examples/foundational/38a-smart-turn-local-coreml.py +++ b/examples/foundational/38a-smart-turn-local-coreml.py @@ -23,7 +23,7 @@ from pipecat.processors.aggregators.llm_response_universal import ( ) from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport -from pipecat.services.cartesia.tts import CartesiaTTSService +from pipecat.services.cartesia.tts import CartesiaTTSService, CartesiaTTSSettings from pipecat.services.deepgram.stt import DeepgramSTTService from pipecat.services.openai.llm import OpenAILLMService from pipecat.transports.base_transport import BaseTransport, TransportParams @@ -76,7 +76,9 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): tts = CartesiaTTSService( api_key=os.getenv("CARTESIA_API_KEY"), - voice_id="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady + settings=CartesiaTTSSettings( + voice="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady + ), ) llm = OpenAILLMService( diff --git a/examples/foundational/38b-smart-turn-local.py b/examples/foundational/38b-smart-turn-local.py index 962b608da..aceff9bc9 100644 --- a/examples/foundational/38b-smart-turn-local.py +++ b/examples/foundational/38b-smart-turn-local.py @@ -24,7 +24,7 @@ from pipecat.processors.aggregators.llm_response_universal import ( ) from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport -from pipecat.services.cartesia.tts import CartesiaTTSService +from pipecat.services.cartesia.tts import CartesiaTTSService, CartesiaTTSSettings from pipecat.services.deepgram.stt import DeepgramSTTService from pipecat.services.openai.llm import OpenAILLMService from pipecat.transports.base_transport import BaseTransport, TransportParams @@ -58,7 +58,9 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): tts = CartesiaTTSService( api_key=os.getenv("CARTESIA_API_KEY"), - voice_id="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady + settings=CartesiaTTSSettings( + voice="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady + ), ) llm = OpenAILLMService( diff --git a/examples/foundational/39-mcp-stdio.py b/examples/foundational/39-mcp-stdio.py index 2daf21626..0919e2fb0 100644 --- a/examples/foundational/39-mcp-stdio.py +++ b/examples/foundational/39-mcp-stdio.py @@ -36,7 +36,7 @@ from pipecat.processors.frame_processor import FrameDirection, FrameProcessor from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport from pipecat.services.anthropic.llm import AnthropicLLMService -from pipecat.services.cartesia.tts import CartesiaTTSService +from pipecat.services.cartesia.tts import CartesiaTTSService, CartesiaTTSSettings from pipecat.services.deepgram.stt import DeepgramSTTService from pipecat.services.mcp_service import MCPClient from pipecat.transports.base_transport import BaseTransport, TransportParams @@ -137,12 +137,25 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): tts = CartesiaTTSService( api_key=os.getenv("CARTESIA_API_KEY"), - voice_id="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady + settings=CartesiaTTSSettings( + voice="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady + ), ) - llm = AnthropicLLMService( - api_key=os.getenv("ANTHROPIC_API_KEY"), model="claude-3-7-sonnet-latest" - ) + system = f""" + You are a helpful LLM in a WebRTC call. + Your goal is to demonstrate your capabilities in a succinct way. + You have access to tools to search the Rijksmuseum collection. + Offer, for example, to show a floral still life, use the `search_artwork` tool. + The tool may respond with a JSON object with an `artworks` array. Choose the art from that array. + Once the tool has responded, tell the user the title and use the `open_image_in_browser` tool. + Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. + Respond to what the user said in a creative and helpful way. + Don't overexplain what you are doing. + Just respond with short sentences when you are carrying out tool calls. + """ + + llm = AnthropicLLMService(api_key=os.getenv("ANTHROPIC_API_KEY"), system_instruction=system) try: mcp = MCPClient( @@ -169,22 +182,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): logger.error(f"error registering tools") logger.exception("error trace:") - system = f""" - You are a helpful LLM in a WebRTC call. - Your goal is to demonstrate your capabilities in a succinct way. - You have access to tools to search the Rijksmuseum collection. - Offer, for example, to show a floral still life, use the `search_artwork` tool. - The tool may respond with a JSON object with an `artworks` array. Choose the art from that array. - Once the tool has responded, tell the user the title and use the `open_image_in_browser` tool. - Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. - Respond to what the user said in a creative and helpful way. - Don't overexplain what you are doing. - Just respond with short sentences when you are carrying out tool calls. - """ - - messages = [{"role": "system", "content": system}] - - context = LLMContext(messages, tools) + context = LLMContext(tools=tools) user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()), diff --git a/examples/foundational/39a-mcp-streamable-http.py b/examples/foundational/39a-mcp-streamable-http.py index 2af2ba9cb..870556073 100644 --- a/examples/foundational/39a-mcp-streamable-http.py +++ b/examples/foundational/39a-mcp-streamable-http.py @@ -23,7 +23,7 @@ from pipecat.processors.aggregators.llm_response_universal import ( ) from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport -from pipecat.services.cartesia.tts import CartesiaTTSService +from pipecat.services.cartesia.tts import CartesiaTTSService, CartesiaTTSSettings from pipecat.services.deepgram.stt import DeepgramSTTService from pipecat.services.google.llm import GoogleLLMService from pipecat.services.mcp_service import MCPClient @@ -58,7 +58,9 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): tts = CartesiaTTSService( api_key=os.getenv("CARTESIA_API_KEY"), - voice_id="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady + settings=CartesiaTTSSettings( + voice="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady + ), ) llm = GoogleLLMService(api_key=os.getenv("GOOGLE_API_KEY"), model="gemini-2.0-flash") diff --git a/examples/foundational/39b-mcp-streamable-http-gemini-live.py b/examples/foundational/39b-mcp-streamable-http-gemini-live.py index c4c427bd8..8a0ea57fd 100644 --- a/examples/foundational/39b-mcp-streamable-http-gemini-live.py +++ b/examples/foundational/39b-mcp-streamable-http-gemini-live.py @@ -23,7 +23,7 @@ from pipecat.processors.aggregators.llm_response_universal import ( ) from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport -from pipecat.services.cartesia.tts import CartesiaTTSService +from pipecat.services.cartesia.tts import CartesiaTTSService, CartesiaTTSSettings from pipecat.services.deepgram.stt import DeepgramSTTService from pipecat.services.google.gemini_live.llm import GeminiLiveLLMService from pipecat.services.mcp_service import MCPClient @@ -58,7 +58,9 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): tts = CartesiaTTSService( api_key=os.getenv("CARTESIA_API_KEY"), - voice_id="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady + settings=CartesiaTTSSettings( + voice="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady + ), ) try: diff --git a/examples/foundational/39c-multiple-mcp.py b/examples/foundational/39c-multiple-mcp.py index 5f662cdb8..dcda884ec 100644 --- a/examples/foundational/39c-multiple-mcp.py +++ b/examples/foundational/39c-multiple-mcp.py @@ -38,7 +38,7 @@ from pipecat.processors.frame_processor import FrameDirection, FrameProcessor from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport from pipecat.services.anthropic.llm import AnthropicLLMService -from pipecat.services.cartesia.tts import CartesiaTTSService +from pipecat.services.cartesia.tts import CartesiaTTSService, CartesiaTTSSettings from pipecat.services.deepgram.stt import DeepgramSTTService from pipecat.services.mcp_service import MCPClient from pipecat.transports.base_transport import BaseTransport, TransportParams @@ -120,11 +120,9 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): tts = CartesiaTTSService( api_key=os.getenv("CARTESIA_API_KEY"), - voice_id="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady - ) - - llm = AnthropicLLMService( - api_key=os.getenv("ANTHROPIC_API_KEY"), model="claude-3-7-sonnet-latest" + settings=CartesiaTTSSettings( + voice="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady + ), ) system = f""" @@ -141,7 +139,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): Just respond with short sentences when you are carrying out tool calls. """ - messages = [{"role": "system", "content": system}] + llm = AnthropicLLMService(api_key=os.getenv("ANTHROPIC_API_KEY"), system_instruction=system) try: rijksmuseum_mcp = MCPClient( @@ -184,7 +182,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): all_standard_tools = rijksmuseum_tools.standard_tools + github_tools.standard_tools all_tools = ToolsSchema(standard_tools=all_standard_tools) - context = LLMContext(messages, all_tools) + context = LLMContext(tools=all_tools) user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()), diff --git a/examples/foundational/42-interruption-config.py b/examples/foundational/42-interruption-config.py index 4491f9ee0..f8add9019 100644 --- a/examples/foundational/42-interruption-config.py +++ b/examples/foundational/42-interruption-config.py @@ -22,7 +22,7 @@ from pipecat.processors.aggregators.llm_response_universal import ( ) from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport -from pipecat.services.cartesia.tts import CartesiaTTSService +from pipecat.services.cartesia.tts import CartesiaTTSService, CartesiaTTSSettings from pipecat.services.deepgram.stt import DeepgramSTTService from pipecat.services.openai.llm import OpenAILLMService from pipecat.transports.base_transport import BaseTransport, TransportParams @@ -59,7 +59,9 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): tts = CartesiaTTSService( api_key=os.getenv("CARTESIA_API_KEY"), - voice_id="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady + settings=CartesiaTTSSettings( + voice="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady + ), ) llm = OpenAILLMService( diff --git a/examples/foundational/43-heygen-transport.py b/examples/foundational/43-heygen-transport.py index e38cb7b6e..5797aeb25 100644 --- a/examples/foundational/43-heygen-transport.py +++ b/examples/foundational/43-heygen-transport.py @@ -22,7 +22,7 @@ from pipecat.processors.aggregators.llm_response_universal import ( LLMContextAggregatorPair, LLMUserAggregatorParams, ) -from pipecat.services.cartesia.tts import CartesiaTTSService +from pipecat.services.cartesia.tts import CartesiaTTSService, CartesiaTTSSettings from pipecat.services.deepgram.stt import DeepgramSTTService from pipecat.services.google.llm import GoogleLLMService from pipecat.services.heygen.api_liveavatar import LiveAvatarNewSessionRequest @@ -56,7 +56,9 @@ async def main(): tts = CartesiaTTSService( api_key=os.getenv("CARTESIA_API_KEY"), - voice_id="00967b2f-88a6-4a31-8153-110a92134b9f", + settings=CartesiaTTSSettings( + voice="00967b2f-88a6-4a31-8153-110a92134b9f", + ), ) llm = GoogleLLMService( diff --git a/examples/foundational/43a-heygen-video-service.py b/examples/foundational/43a-heygen-video-service.py index 2b23fe1f8..5be8f1caa 100644 --- a/examples/foundational/43a-heygen-video-service.py +++ b/examples/foundational/43a-heygen-video-service.py @@ -22,7 +22,7 @@ from pipecat.processors.aggregators.llm_response_universal import ( ) from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport -from pipecat.services.cartesia.tts import CartesiaTTSService +from pipecat.services.cartesia.tts import CartesiaTTSService, CartesiaTTSSettings from pipecat.services.deepgram.stt import DeepgramSTTService from pipecat.services.google.llm import GoogleLLMService from pipecat.services.heygen.api_liveavatar import LiveAvatarNewSessionRequest @@ -63,7 +63,9 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): tts = CartesiaTTSService( api_key=os.getenv("CARTESIA_API_KEY"), - voice_id="00967b2f-88a6-4a31-8153-110a92134b9f", + settings=CartesiaTTSSettings( + voice="00967b2f-88a6-4a31-8153-110a92134b9f", + ), ) llm = GoogleLLMService( diff --git a/examples/foundational/44-voicemail-detection.py b/examples/foundational/44-voicemail-detection.py index f7cf14f71..e46c59cc0 100644 --- a/examples/foundational/44-voicemail-detection.py +++ b/examples/foundational/44-voicemail-detection.py @@ -22,7 +22,7 @@ from pipecat.processors.aggregators.llm_response_universal import ( ) from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport -from pipecat.services.cartesia.tts import CartesiaTTSService +from pipecat.services.cartesia.tts import CartesiaTTSService, CartesiaTTSSettings from pipecat.services.deepgram.stt import DeepgramSTTService from pipecat.services.openai.llm import OpenAILLMService from pipecat.transports.base_transport import BaseTransport, TransportParams @@ -56,7 +56,9 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): tts = CartesiaTTSService( api_key=os.getenv("CARTESIA_API_KEY"), - voice_id="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady + settings=CartesiaTTSSettings( + voice="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady + ), ) llm = OpenAILLMService( diff --git a/examples/foundational/45-before-and-after-events.py b/examples/foundational/45-before-and-after-events.py index 405af49f3..db71e283d 100644 --- a/examples/foundational/45-before-and-after-events.py +++ b/examples/foundational/45-before-and-after-events.py @@ -22,7 +22,7 @@ from pipecat.processors.aggregators.llm_response_universal import ( ) from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport -from pipecat.services.cartesia.tts import CartesiaTTSService +from pipecat.services.cartesia.tts import CartesiaTTSService, CartesiaTTSSettings from pipecat.services.deepgram.stt import DeepgramSTTService from pipecat.services.openai.llm import OpenAILLMService from pipecat.transports.base_transport import BaseTransport, TransportParams @@ -67,7 +67,9 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): tts = CartesiaTTSService( api_key=os.getenv("CARTESIA_API_KEY"), - voice_id="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady + settings=CartesiaTTSSettings( + voice="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady + ), ) llm = OpenAILLMService( diff --git a/examples/foundational/47-sentry-metrics.py b/examples/foundational/47-sentry-metrics.py index ef20745e4..f9983c46f 100644 --- a/examples/foundational/47-sentry-metrics.py +++ b/examples/foundational/47-sentry-metrics.py @@ -23,7 +23,7 @@ from pipecat.processors.aggregators.llm_response_universal import ( from pipecat.processors.metrics.sentry import SentryMetrics from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport -from pipecat.services.cartesia.tts import CartesiaTTSService +from pipecat.services.cartesia.tts import CartesiaTTSService, CartesiaTTSSettings from pipecat.services.deepgram.stt import DeepgramSTTService from pipecat.services.openai.llm import OpenAILLMService from pipecat.transports.base_transport import BaseTransport, TransportParams @@ -66,7 +66,9 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): tts = CartesiaTTSService( api_key=os.getenv("CARTESIA_API_KEY"), - voice_id="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady + settings=CartesiaTTSSettings( + voice="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady + ), metrics=SentryMetrics(), ) diff --git a/examples/foundational/48-service-switcher.py b/examples/foundational/48-service-switcher.py index 4aaafa508..dd7d9ec82 100644 --- a/examples/foundational/48-service-switcher.py +++ b/examples/foundational/48-service-switcher.py @@ -27,9 +27,9 @@ from pipecat.processors.aggregators.llm_response_universal import ( from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport from pipecat.services.cartesia.stt import CartesiaSTTService -from pipecat.services.cartesia.tts import CartesiaTTSService +from pipecat.services.cartesia.tts import CartesiaTTSService, CartesiaTTSSettings from pipecat.services.deepgram.stt import DeepgramSTTService -from pipecat.services.deepgram.tts import DeepgramTTSService +from pipecat.services.deepgram.tts import DeepgramTTSService, DeepgramTTSSettings from pipecat.services.google.llm import GoogleLLMService from pipecat.services.llm_service import FunctionCallParams from pipecat.services.openai.llm import OpenAILLMService @@ -102,15 +102,24 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): tts_cartesia = CartesiaTTSService( api_key=os.getenv("CARTESIA_API_KEY"), - voice_id="71a7ad14-091c-4e8e-a314-022ece01c121", + settings=CartesiaTTSSettings( + voice="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady + ), + ) + tts_deepgram = DeepgramTTSService( + api_key=os.getenv("DEEPGRAM_API_KEY"), + settings=DeepgramTTSSettings( + voice="aura-2-helena-en", + ), ) - tts_deepgram = DeepgramTTSService(api_key=os.getenv("DEEPGRAM_API_KEY")) tts_switcher = ServiceSwitcher( services=[tts_cartesia, tts_deepgram], strategy_type=ServiceSwitcherStrategyManual ) - llm_openai = OpenAILLMService(api_key=os.getenv("OPENAI_API_KEY")) - llm_google = GoogleLLMService(api_key=os.getenv("GOOGLE_API_KEY")) + system = "You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way." + + llm_openai = OpenAILLMService(api_key=os.getenv("OPENAI_API_KEY"), system_instruction=system) + llm_google = GoogleLLMService(api_key=os.getenv("GOOGLE_API_KEY"), system_instruction=system) llm_switcher = LLMSwitcher( llms=[llm_openai, llm_google], strategy_type=ServiceSwitcherStrategyManual ) @@ -119,15 +128,9 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): # Register a "direct" function llm_switcher.register_direct_function(get_restaurant_recommendation) - messages = [ - { - "role": "system", - "content": "You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", - }, - ] tools = ToolsSchema(standard_tools=[weather_function, get_restaurant_recommendation]) - context = LLMContext(messages, tools) + context = LLMContext(tools=tools) user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()), @@ -158,7 +161,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): async def on_client_connected(transport, client): logger.info(f"Client connected") # Kick off the conversation. - messages.append({"role": "system", "content": "Please introduce yourself to the user."}) + context.add_message({"role": "user", "content": "Please introduce yourself to the user."}) await task.queue_frames([LLMRunFrame()]) await asyncio.sleep(15) print(f"Switching to {stt_deepgram}") diff --git a/examples/foundational/49a-thinking-anthropic.py b/examples/foundational/49a-thinking-anthropic.py index 28dd33565..fa84e7c6c 100644 --- a/examples/foundational/49a-thinking-anthropic.py +++ b/examples/foundational/49a-thinking-anthropic.py @@ -22,8 +22,12 @@ from pipecat.processors.aggregators.llm_response_universal import ( ) from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport -from pipecat.services.anthropic.llm import AnthropicLLMService -from pipecat.services.cartesia.tts import CartesiaTTSService +from pipecat.services.anthropic.llm import ( + AnthropicLLMService, + AnthropicLLMSettings, + AnthropicThinkingConfig, +) +from pipecat.services.cartesia.tts import CartesiaTTSService, CartesiaTTSSettings from pipecat.services.deepgram.stt import DeepgramSTTService from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams @@ -56,13 +60,18 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): tts = CartesiaTTSService( api_key=os.getenv("CARTESIA_API_KEY"), - voice_id="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady + settings=CartesiaTTSSettings( + voice="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady + ), ) llm = AnthropicLLMService( api_key=os.getenv("ANTHROPIC_API_KEY"), - params=AnthropicLLMService.InputParams( - thinking=AnthropicLLMService.ThinkingConfig(type="enabled", budget_tokens=2048) + settings=AnthropicLLMSettings( + thinking=AnthropicThinkingConfig( + type="enabled", + budget_tokens=2048, + ), ), system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", ) diff --git a/examples/foundational/49b-thinking-google.py b/examples/foundational/49b-thinking-google.py index 32677bcbb..0fb0a30f0 100644 --- a/examples/foundational/49b-thinking-google.py +++ b/examples/foundational/49b-thinking-google.py @@ -22,9 +22,9 @@ from pipecat.processors.aggregators.llm_response_universal import ( ) from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport -from pipecat.services.cartesia.tts import CartesiaTTSService +from pipecat.services.cartesia.tts import CartesiaTTSService, CartesiaTTSSettings from pipecat.services.deepgram.stt import DeepgramSTTService -from pipecat.services.google.llm import GoogleLLMService +from pipecat.services.google.llm import GoogleLLMService, GoogleLLMSettings, GoogleThinkingConfig from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams @@ -56,18 +56,19 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): tts = CartesiaTTSService( api_key=os.getenv("CARTESIA_API_KEY"), - voice_id="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady + settings=CartesiaTTSSettings( + voice="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady + ), ) llm = GoogleLLMService( api_key=os.getenv("GOOGLE_API_KEY"), # model="gemini-3-pro-preview", # A more powerful reasoning model, but slower - params=GoogleLLMService.InputParams( - thinking=GoogleLLMService.ThinkingConfig( - # thinking_level="low", # Use this field instead of thinking_budget for Gemini 3 Pro. Defaults to "high". + settings=GoogleLLMSettings( + thinking=GoogleThinkingConfig( thinking_budget=-1, # Dynamic thinking include_thoughts=True, - ) + ), ), system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", ) diff --git a/examples/foundational/49c-thinking-functions-anthropic.py b/examples/foundational/49c-thinking-functions-anthropic.py index b070871b1..4fb66470d 100644 --- a/examples/foundational/49c-thinking-functions-anthropic.py +++ b/examples/foundational/49c-thinking-functions-anthropic.py @@ -23,8 +23,12 @@ from pipecat.processors.aggregators.llm_response_universal import ( ) from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport -from pipecat.services.anthropic.llm import AnthropicLLMService -from pipecat.services.cartesia.tts import CartesiaTTSService +from pipecat.services.anthropic.llm import ( + AnthropicLLMService, + AnthropicLLMSettings, + AnthropicThinkingConfig, +) +from pipecat.services.cartesia.tts import CartesiaTTSService, CartesiaTTSSettings from pipecat.services.deepgram.stt import DeepgramSTTService from pipecat.services.llm_service import FunctionCallParams from pipecat.transports.base_transport import BaseTransport, TransportParams @@ -77,13 +81,18 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): tts = CartesiaTTSService( api_key=os.getenv("CARTESIA_API_KEY"), - voice_id="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady + settings=CartesiaTTSSettings( + voice="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady + ), ) llm = AnthropicLLMService( api_key=os.getenv("ANTHROPIC_API_KEY"), - params=AnthropicLLMService.InputParams( - thinking=AnthropicLLMService.ThinkingConfig(type="enabled", budget_tokens=2048) + settings=AnthropicLLMSettings( + thinking=AnthropicThinkingConfig( + type="enabled", + budget_tokens=2048, + ), ), system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", ) diff --git a/examples/foundational/49d-thinking-functions-google.py b/examples/foundational/49d-thinking-functions-google.py index 9b5a333de..3963fc387 100644 --- a/examples/foundational/49d-thinking-functions-google.py +++ b/examples/foundational/49d-thinking-functions-google.py @@ -23,9 +23,9 @@ from pipecat.processors.aggregators.llm_response_universal import ( ) from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport -from pipecat.services.cartesia.tts import CartesiaTTSService +from pipecat.services.cartesia.tts import CartesiaTTSService, CartesiaTTSSettings from pipecat.services.deepgram.stt import DeepgramSTTService -from pipecat.services.google.llm import GoogleLLMService +from pipecat.services.google.llm import GoogleLLMService, GoogleLLMSettings, GoogleThinkingConfig from pipecat.services.llm_service import FunctionCallParams from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams @@ -77,18 +77,19 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): tts = CartesiaTTSService( api_key=os.getenv("CARTESIA_API_KEY"), - voice_id="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady + settings=CartesiaTTSSettings( + voice="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady + ), ) llm = GoogleLLMService( api_key=os.getenv("GOOGLE_API_KEY"), # model="gemini-3-pro-preview", # A more powerful reasoning model, but slower - params=GoogleLLMService.InputParams( - thinking=GoogleLLMService.ThinkingConfig( - # thinking_level="low", # Use this field instead of thinking_budget for Gemini 3 Pro. Defaults to "high". + settings=GoogleLLMSettings( + thinking=GoogleThinkingConfig( thinking_budget=-1, # Dynamic thinking include_thoughts=True, - ) + ), ), system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", ) diff --git a/examples/foundational/52-live-translation.py b/examples/foundational/52-live-translation.py index 6ab0bac18..15598667f 100644 --- a/examples/foundational/52-live-translation.py +++ b/examples/foundational/52-live-translation.py @@ -22,7 +22,7 @@ from pipecat.processors.aggregators.llm_response_universal import ( ) from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport -from pipecat.services.cartesia.tts import CartesiaTTSService +from pipecat.services.cartesia.tts import CartesiaTTSService, CartesiaTTSSettings from pipecat.services.deepgram.stt import DeepgramSTTService from pipecat.services.openai.llm import OpenAILLMService from pipecat.transports.base_transport import BaseTransport, TransportParams @@ -59,7 +59,9 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): tts = CartesiaTTSService( api_key=os.getenv("CARTESIA_API_KEY"), - voice_id="d4db5fb9-f44b-4bd1-85fa-192e0f0d75f9", # Spanish-speaking Lady + settings=CartesiaTTSSettings( + voice="d4db5fb9-f44b-4bd1-85fa-192e0f0d75f9", # Spanish-speaking Lady + ), ) llm = OpenAILLMService( diff --git a/examples/foundational/53-concurrent-llm-evaluation.py b/examples/foundational/53-concurrent-llm-evaluation.py index 9fb44a44f..a93ca2ada 100644 --- a/examples/foundational/53-concurrent-llm-evaluation.py +++ b/examples/foundational/53-concurrent-llm-evaluation.py @@ -24,9 +24,9 @@ from pipecat.processors.aggregators.llm_response_universal import ( from pipecat.processors.audio.vad_processor import VADProcessor from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport -from pipecat.services.cartesia.tts import CartesiaTTSService +from pipecat.services.cartesia.tts import CartesiaTTSService, CartesiaTTSSettings from pipecat.services.deepgram.stt import DeepgramSTTService -from pipecat.services.groq.llm import GroqLLMService +from pipecat.services.groq.llm import GroqLLMService, GroqLLMSettings from pipecat.services.openai.llm import OpenAILLMService from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams @@ -62,31 +62,24 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): tts = CartesiaTTSService( api_key=os.getenv("CARTESIA_API_KEY"), - voice_id="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady + settings=CartesiaTTSSettings( + voice="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady + ), ) - openai_llm = OpenAILLMService(api_key=os.getenv("OPENAI_API_KEY")) - - openai_messages = [ - { - "role": "system", - "content": "You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", - }, - ] + openai_llm = OpenAILLMService( + api_key=os.getenv("OPENAI_API_KEY"), + system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + ) groq_llm = GroqLLMService( - api_key=os.getenv("GROQ_API_KEY"), model="meta-llama/llama-4-maverick-17b-128e-instruct" + api_key=os.getenv("GROQ_API_KEY"), + settings=GroqLLMSettings(model="meta-llama/llama-4-maverick-17b-128e-instruct"), + system_instruction="You are a very helpful assistant. Your goal is to demonstrate your capabilities in detail in a creative and helpful way.", ) - groq_messages = [ - { - "role": "system", - "content": "You are a very helpful assistant. Your goal is to demonstrate your capabilities in detail in a creative and helpful way.", - }, - ] - - openai_context = LLMContext(openai_messages) - groq_context = LLMContext(groq_messages) + openai_context = LLMContext() + groq_context = LLMContext() # We use an external VADProcessor because the UserTurnProcessor is shared # across multiple parallel aggregators. The VADProcessor emits @@ -147,11 +140,11 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): async def on_client_connected(transport, client): logger.info(f"Client connected") # Kick off the conversation. - openai_messages.append( - {"role": "system", "content": "Please introduce yourself to the user."} + openai_context.add_message( + {"role": "user", "content": "Please introduce yourself to the user."} ) - groq_messages.append( - {"role": "system", "content": "Please introduce yourself to the user."} + groq_context.add_message( + {"role": "user", "content": "Please introduce yourself to the user."} ) await task.queue_frames([LLMRunFrame()]) diff --git a/examples/foundational/53-concurrent-llm-rtvi-ignored-sources.py b/examples/foundational/53-concurrent-llm-rtvi-ignored-sources.py index b16f8831f..f449269e9 100644 --- a/examples/foundational/53-concurrent-llm-rtvi-ignored-sources.py +++ b/examples/foundational/53-concurrent-llm-rtvi-ignored-sources.py @@ -31,7 +31,7 @@ from pipecat.processors.audio.vad_processor import VADProcessor from pipecat.processors.frameworks.rtvi import RTVIObserverParams from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport -from pipecat.services.cartesia.tts import CartesiaTTSService +from pipecat.services.cartesia.tts import CartesiaTTSService, CartesiaTTSSettings from pipecat.services.deepgram.stt import DeepgramSTTService from pipecat.services.openai.llm import OpenAILLMService from pipecat.transports.base_transport import BaseTransport, TransportParams @@ -67,40 +67,27 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): tts = CartesiaTTSService( api_key=os.getenv("CARTESIA_API_KEY"), - voice_id="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady + settings=CartesiaTTSSettings( + voice="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady + ), ) # Main LLM — drives the conversation. Its RTVI events reach the client. - main_llm = OpenAILLMService(api_key=os.getenv("OPENAI_API_KEY")) - - main_messages = [ - { - "role": "system", - "content": "You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", - }, - ] + main_llm = OpenAILLMService( + api_key=os.getenv("OPENAI_API_KEY"), + system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + ) # Evaluator LLM — silently grades the user's message in the background. # Its RTVI events will be suppressed so the client is unaware of this branch. evaluator_llm = OpenAILLMService( api_key=os.getenv("OPENAI_API_KEY"), name="EvaluatorLLM", + system_instruction="You are a silent quality evaluator. When given a user message, respond with a single JSON object: {'score': <1-5>, 'reason': ''}. Do not respond conversationally.", ) - evaluator_messages = [ - { - "role": "system", - "content": ( - "You are a silent quality evaluator. When given a user message, " - "respond with a single JSON object: " - '{"score": <1-5>, "reason": ""}. ' - "Do not respond conversationally." - ), - }, - ] - - main_context = LLMContext(main_messages) - evaluator_context = LLMContext(evaluator_messages) + main_context = LLMContext() + evaluator_context = LLMContext() # We use an external VADProcessor because the UserTurnProcessor is shared # across multiple parallel aggregators. The VADProcessor emits @@ -163,10 +150,12 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): @transport.event_handler("on_client_connected") async def on_client_connected(transport, client): logger.info("Client connected") - main_messages.append( - {"role": "system", "content": "Please introduce yourself to the user."} + main_context.add_message( + {"role": "user", "content": "Please introduce yourself to the user."} + ) + evaluator_context.add_message( + {"role": "user", "content": "Ready to evaluate user messages."} ) - evaluator_messages.append({"role": "system", "content": "Ready to evaluate user messages."}) await task.queue_frames([LLMRunFrame()]) @transport.event_handler("on_client_disconnected") diff --git a/examples/foundational/54-context-summarization-openai.py b/examples/foundational/54-context-summarization-openai.py index 25ea496c3..8c7c38d62 100644 --- a/examples/foundational/54-context-summarization-openai.py +++ b/examples/foundational/54-context-summarization-openai.py @@ -34,7 +34,7 @@ from pipecat.processors.aggregators.llm_response_universal import ( ) from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport -from pipecat.services.cartesia.tts import CartesiaTTSService +from pipecat.services.cartesia.tts import CartesiaTTSService, CartesiaTTSSettings from pipecat.services.deepgram.stt import DeepgramSTTService from pipecat.services.llm_service import FunctionCallParams from pipecat.services.openai.llm import OpenAILLMService @@ -81,7 +81,9 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): tts = CartesiaTTSService( api_key=os.getenv("CARTESIA_API_KEY"), - voice_id="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady + settings=CartesiaTTSSettings( + voice="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady + ), ) llm = OpenAILLMService( diff --git a/examples/foundational/54a-context-summarization-google.py b/examples/foundational/54a-context-summarization-google.py index c79e96c3d..21e2ef459 100644 --- a/examples/foundational/54a-context-summarization-google.py +++ b/examples/foundational/54a-context-summarization-google.py @@ -34,7 +34,7 @@ from pipecat.processors.aggregators.llm_response_universal import ( ) from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport -from pipecat.services.cartesia.tts import CartesiaTTSService +from pipecat.services.cartesia.tts import CartesiaTTSService, CartesiaTTSSettings from pipecat.services.deepgram.stt import DeepgramSTTService from pipecat.services.google import GoogleLLMService from pipecat.services.llm_service import FunctionCallParams @@ -81,7 +81,9 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): tts = CartesiaTTSService( api_key=os.getenv("CARTESIA_API_KEY"), - voice_id="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady + settings=CartesiaTTSSettings( + voice="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady + ), ) llm = GoogleLLMService( diff --git a/examples/foundational/54b-context-summarization-manual-openai.py b/examples/foundational/54b-context-summarization-manual-openai.py index c1ff83ef0..0fd2c0bd7 100644 --- a/examples/foundational/54b-context-summarization-manual-openai.py +++ b/examples/foundational/54b-context-summarization-manual-openai.py @@ -34,7 +34,7 @@ from pipecat.processors.aggregators.llm_response_universal import ( ) from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport -from pipecat.services.cartesia.tts import CartesiaTTSService +from pipecat.services.cartesia.tts import CartesiaTTSService, CartesiaTTSSettings from pipecat.services.deepgram.stt import DeepgramSTTService from pipecat.services.llm_service import FunctionCallParams from pipecat.services.openai.llm import OpenAILLMService @@ -78,10 +78,21 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): tts = CartesiaTTSService( api_key=os.getenv("CARTESIA_API_KEY"), - voice_id="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady + settings=CartesiaTTSSettings( + voice="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady + ), ) - llm = OpenAILLMService(api_key=os.getenv("OPENAI_API_KEY")) + system_prompt = """You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your + capabilities in a succinct way. Your output will be spoken aloud, so avoid + special characters that can't easily be spoken, such as emojis or bullet points. + Respond to what the user said in a creative and helpful way. + If the user asks you to summarize the conversation, call the + summarize_conversation function. After summarization, briefly acknowledge + that the conversation history has been compressed. + """ + + llm = OpenAILLMService(api_key=os.getenv("OPENAI_API_KEY"), system_instruction=system_prompt) llm.register_function("summarize_conversation", summarize_conversation) @@ -97,22 +108,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): ) tools = ToolsSchema(standard_tools=[summarize_function]) - messages = [ - { - "role": "system", - "content": ( - "You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your " - "capabilities in a succinct way. Your output will be spoken aloud, so avoid " - "special characters that can't easily be spoken, such as emojis or bullet points. " - "Respond to what the user said in a creative and helpful way. " - "If the user asks you to summarize the conversation, call the " - "summarize_conversation function. After summarization, briefly acknowledge " - "that the conversation history has been compressed." - ), - }, - ] - - context = LLMContext(messages, tools=tools) + context = LLMContext(tools=tools) # Automatic summarization is NOT enabled here (enable_auto_context_summarization # defaults to False). The summarizer is still created internally so that @@ -147,7 +143,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): async def on_client_connected(transport, client): logger.info("Client connected") # Kick off the conversation. - messages.append({"role": "system", "content": "Please introduce yourself to the user."}) + context.add_message({"role": "user", "content": "Please introduce yourself to the user."}) await task.queue_frames([LLMRunFrame()]) @transport.event_handler("on_client_disconnected") diff --git a/examples/foundational/54c-context-summarization-dedicated-llm.py b/examples/foundational/54c-context-summarization-dedicated-llm.py index 1dce3890f..ce0f7658f 100644 --- a/examples/foundational/54c-context-summarization-dedicated-llm.py +++ b/examples/foundational/54c-context-summarization-dedicated-llm.py @@ -36,9 +36,9 @@ from pipecat.processors.aggregators.llm_response_universal import ( ) from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport -from pipecat.services.cartesia.tts import CartesiaTTSService +from pipecat.services.cartesia.tts import CartesiaTTSService, CartesiaTTSSettings from pipecat.services.deepgram.stt import DeepgramSTTService -from pipecat.services.google import GoogleLLMService +from pipecat.services.google.llm import GoogleLLMService, GoogleLLMSettings from pipecat.services.llm_service import FunctionCallParams from pipecat.services.openai.llm import OpenAILLMService from pipecat.transports.base_transport import BaseTransport, TransportParams @@ -93,16 +93,29 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): tts = CartesiaTTSService( api_key=os.getenv("CARTESIA_API_KEY"), - voice_id="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady + settings=CartesiaTTSSettings( + voice="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady + ), ) + system_prompt = """You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your + capabilities in a succinct way. Your output will be spoken aloud, so avoid + special characters that can't easily be spoken, such as emojis or bullet points. + Respond to what the user said in a creative and helpful way. + You have access to tools to get the current weather - use them when relevant. + When you see a block, it contains a compressed summary + of earlier conversation. Use it as reference but don't mention it to the user. + """ + # Primary LLM for conversation (could be any provider) - llm = OpenAILLMService(api_key=os.getenv("OPENAI_API_KEY")) + llm = OpenAILLMService(api_key=os.getenv("OPENAI_API_KEY"), system_instruction=system_prompt) # Dedicated cheap/fast LLM for summarization only summarization_llm = GoogleLLMService( api_key=os.getenv("GOOGLE_API_KEY"), - model="gemini-2.5-flash", + settings=GoogleLLMSettings( + model="gemini-2.5-flash", + ), ) # Register tool functions @@ -126,22 +139,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): ) tools = ToolsSchema(standard_tools=[weather_function]) - messages = [ - { - "role": "system", - "content": ( - "You are a helpful LLM in a WebRTC call. Your goal is to demonstrate " - "your capabilities in a succinct way. Your output will be spoken aloud, " - "so avoid special characters that can't easily be spoken. Respond to what " - "the user said in a creative and helpful way. You have access to tools to " - "get the current weather - use them when relevant.\n\n" - "When you see a block, it contains a compressed summary " - "of earlier conversation. Use it as reference but don't mention it to the user." - ), - }, - ] - - context = LLMContext(messages, tools=tools) + context = LLMContext(tools=tools) # Create aggregators with custom summarization user_aggregator, assistant_aggregator = LLMContextAggregatorPair( @@ -211,7 +209,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): async def on_client_connected(transport, client): logger.info("Client connected") # Kick off the conversation. - messages.append({"role": "system", "content": "Please introduce yourself to the user."}) + context.add_message({"role": "user", "content": "Please introduce yourself to the user."}) await task.queue_frames([LLMRunFrame()]) @transport.event_handler("on_client_disconnected") diff --git a/examples/foundational/55a-update-settings-deepgram-flux-stt.py b/examples/foundational/55a-update-settings-deepgram-flux-stt.py index ef58fe8fb..0a507aaed 100644 --- a/examples/foundational/55a-update-settings-deepgram-flux-stt.py +++ b/examples/foundational/55a-update-settings-deepgram-flux-stt.py @@ -22,7 +22,7 @@ from pipecat.processors.aggregators.llm_response_universal import ( ) from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport -from pipecat.services.cartesia.tts import CartesiaTTSService +from pipecat.services.cartesia.tts import CartesiaTTSService, CartesiaTTSSettings from pipecat.services.deepgram.flux.stt import DeepgramFluxSTTService, DeepgramFluxSTTSettings from pipecat.services.openai.llm import OpenAILLMService from pipecat.transcriptions.language import Language @@ -55,7 +55,9 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): tts = CartesiaTTSService( api_key=os.getenv("CARTESIA_API_KEY"), - voice_id="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady + settings=CartesiaTTSSettings( + voice="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady + ), ) llm = OpenAILLMService( diff --git a/examples/foundational/55a-update-settings-deepgram-sagemaker-stt.py b/examples/foundational/55a-update-settings-deepgram-sagemaker-stt.py index 489ea1276..b6f2142bc 100644 --- a/examples/foundational/55a-update-settings-deepgram-sagemaker-stt.py +++ b/examples/foundational/55a-update-settings-deepgram-sagemaker-stt.py @@ -23,7 +23,7 @@ from pipecat.processors.aggregators.llm_response_universal import ( ) from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport -from pipecat.services.cartesia.tts import CartesiaTTSService +from pipecat.services.cartesia.tts import CartesiaTTSService, CartesiaTTSSettings from pipecat.services.deepgram.sagemaker.stt import ( DeepgramSageMakerSTTService, DeepgramSageMakerSTTSettings, @@ -62,7 +62,9 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): tts = CartesiaTTSService( api_key=os.getenv("CARTESIA_API_KEY"), - voice_id="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady + settings=CartesiaTTSSettings( + voice="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady + ), ) llm = OpenAILLMService( diff --git a/examples/foundational/55a-update-settings-deepgram-stt.py b/examples/foundational/55a-update-settings-deepgram-stt.py index b0521bb19..b914d8085 100644 --- a/examples/foundational/55a-update-settings-deepgram-stt.py +++ b/examples/foundational/55a-update-settings-deepgram-stt.py @@ -23,7 +23,7 @@ from pipecat.processors.aggregators.llm_response_universal import ( ) from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport -from pipecat.services.cartesia.tts import CartesiaTTSService +from pipecat.services.cartesia.tts import CartesiaTTSService, CartesiaTTSSettings from pipecat.services.deepgram.stt import DeepgramSTTService, DeepgramSTTSettings from pipecat.services.openai.llm import OpenAILLMService from pipecat.transcriptions.language import Language @@ -56,7 +56,9 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): tts = CartesiaTTSService( api_key=os.getenv("CARTESIA_API_KEY"), - voice_id="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady + settings=CartesiaTTSSettings( + voice="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady + ), ) llm = OpenAILLMService( diff --git a/examples/foundational/55b-update-settings-azure-stt.py b/examples/foundational/55b-update-settings-azure-stt.py index 1d3b3fcee..c54b1a0d8 100644 --- a/examples/foundational/55b-update-settings-azure-stt.py +++ b/examples/foundational/55b-update-settings-azure-stt.py @@ -23,7 +23,7 @@ from pipecat.processors.aggregators.llm_response_universal import ( from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport from pipecat.services.azure.stt import AzureSTTService, AzureSTTSettings -from pipecat.services.cartesia.tts import CartesiaTTSService +from pipecat.services.cartesia.tts import CartesiaTTSService, CartesiaTTSSettings from pipecat.services.openai.llm import OpenAILLMService from pipecat.transcriptions.language import Language from pipecat.transports.base_transport import BaseTransport, TransportParams @@ -58,7 +58,9 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): tts = CartesiaTTSService( api_key=os.getenv("CARTESIA_API_KEY"), - voice_id="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady + settings=CartesiaTTSSettings( + voice="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady + ), ) llm = OpenAILLMService( diff --git a/examples/foundational/55c-update-settings-google-stt.py b/examples/foundational/55c-update-settings-google-stt.py index 2956b8047..23b312f5f 100644 --- a/examples/foundational/55c-update-settings-google-stt.py +++ b/examples/foundational/55c-update-settings-google-stt.py @@ -22,7 +22,7 @@ from pipecat.processors.aggregators.llm_response_universal import ( ) from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport -from pipecat.services.cartesia.tts import CartesiaTTSService +from pipecat.services.cartesia.tts import CartesiaTTSService, CartesiaTTSSettings from pipecat.services.google.stt import GoogleSTTService, GoogleSTTSettings from pipecat.services.openai.llm import OpenAILLMService from pipecat.transcriptions.language import Language @@ -55,7 +55,9 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): tts = CartesiaTTSService( api_key=os.getenv("CARTESIA_API_KEY"), - voice_id="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady + settings=CartesiaTTSSettings( + voice="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady + ), ) llm = OpenAILLMService( diff --git a/examples/foundational/55d-update-settings-assemblyai-stt.py b/examples/foundational/55d-update-settings-assemblyai-stt.py index f8c366a44..e6d10d04f 100644 --- a/examples/foundational/55d-update-settings-assemblyai-stt.py +++ b/examples/foundational/55d-update-settings-assemblyai-stt.py @@ -24,7 +24,7 @@ from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport from pipecat.services.assemblyai.models import AssemblyAIConnectionParams from pipecat.services.assemblyai.stt import AssemblyAISTTService, AssemblyAISTTSettings -from pipecat.services.cartesia.tts import CartesiaTTSService +from pipecat.services.cartesia.tts import CartesiaTTSService, CartesiaTTSSettings from pipecat.services.openai.llm import OpenAILLMService from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams @@ -60,7 +60,9 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): tts = CartesiaTTSService( api_key=os.getenv("CARTESIA_API_KEY"), - voice_id="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady + settings=CartesiaTTSSettings( + voice="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady + ), ) llm = OpenAILLMService( diff --git a/examples/foundational/55e-update-settings-gladia-stt.py b/examples/foundational/55e-update-settings-gladia-stt.py index 5b8283f72..6cc3fc92a 100644 --- a/examples/foundational/55e-update-settings-gladia-stt.py +++ b/examples/foundational/55e-update-settings-gladia-stt.py @@ -22,7 +22,7 @@ from pipecat.processors.aggregators.llm_response_universal import ( ) from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport -from pipecat.services.cartesia.tts import CartesiaTTSService +from pipecat.services.cartesia.tts import CartesiaTTSService, CartesiaTTSSettings from pipecat.services.gladia.stt import GladiaSTTService, GladiaSTTSettings from pipecat.services.openai.llm import OpenAILLMService from pipecat.transcriptions.language import Language @@ -55,7 +55,9 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): tts = CartesiaTTSService( api_key=os.getenv("CARTESIA_API_KEY"), - voice_id="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady + settings=CartesiaTTSSettings( + voice="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady + ), ) llm = OpenAILLMService( diff --git a/examples/foundational/55f-update-settings-elevenlabs-realtime-stt.py b/examples/foundational/55f-update-settings-elevenlabs-realtime-stt.py index 8d2c17778..ef1e44b61 100644 --- a/examples/foundational/55f-update-settings-elevenlabs-realtime-stt.py +++ b/examples/foundational/55f-update-settings-elevenlabs-realtime-stt.py @@ -22,7 +22,7 @@ from pipecat.processors.aggregators.llm_response_universal import ( ) from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport -from pipecat.services.cartesia.tts import CartesiaTTSService +from pipecat.services.cartesia.tts import CartesiaTTSService, CartesiaTTSSettings from pipecat.services.elevenlabs.stt import ( ElevenLabsRealtimeSTTService, ElevenLabsRealtimeSTTSettings, @@ -58,7 +58,9 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): tts = CartesiaTTSService( api_key=os.getenv("CARTESIA_API_KEY"), - voice_id="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady + settings=CartesiaTTSSettings( + voice="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady + ), ) llm = OpenAILLMService( diff --git a/examples/foundational/55g-update-settings-elevenlabs-stt.py b/examples/foundational/55g-update-settings-elevenlabs-stt.py index 0395f273d..c3fb9eac9 100644 --- a/examples/foundational/55g-update-settings-elevenlabs-stt.py +++ b/examples/foundational/55g-update-settings-elevenlabs-stt.py @@ -23,7 +23,7 @@ from pipecat.processors.aggregators.llm_response_universal import ( ) from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport -from pipecat.services.cartesia.tts import CartesiaTTSService +from pipecat.services.cartesia.tts import CartesiaTTSService, CartesiaTTSSettings from pipecat.services.elevenlabs.stt import ElevenLabsSTTService, ElevenLabsSTTSettings from pipecat.services.openai.llm import OpenAILLMService from pipecat.transcriptions.language import Language @@ -60,7 +60,9 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): tts = CartesiaTTSService( api_key=os.getenv("CARTESIA_API_KEY"), - voice_id="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady + settings=CartesiaTTSSettings( + voice="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady + ), ) llm = OpenAILLMService( diff --git a/examples/foundational/55h-update-settings-speechmatics-stt.py b/examples/foundational/55h-update-settings-speechmatics-stt.py index ba775199a..1471f7ef2 100644 --- a/examples/foundational/55h-update-settings-speechmatics-stt.py +++ b/examples/foundational/55h-update-settings-speechmatics-stt.py @@ -22,7 +22,7 @@ from pipecat.processors.aggregators.llm_response_universal import ( ) from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport -from pipecat.services.cartesia.tts import CartesiaTTSService +from pipecat.services.cartesia.tts import CartesiaTTSService, CartesiaTTSSettings from pipecat.services.openai.llm import OpenAILLMService from pipecat.services.speechmatics.stt import SpeechmaticsSTTService, SpeechmaticsSTTSettings from pipecat.transcriptions.language import Language @@ -62,7 +62,9 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): tts = CartesiaTTSService( api_key=os.getenv("CARTESIA_API_KEY"), - voice_id="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady + settings=CartesiaTTSSettings( + voice="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady + ), ) llm = OpenAILLMService( diff --git a/examples/foundational/55i-update-settings-whisper-api-stt.py b/examples/foundational/55i-update-settings-whisper-api-stt.py index 962a70485..6b957a0be 100644 --- a/examples/foundational/55i-update-settings-whisper-api-stt.py +++ b/examples/foundational/55i-update-settings-whisper-api-stt.py @@ -22,7 +22,7 @@ from pipecat.processors.aggregators.llm_response_universal import ( ) from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport -from pipecat.services.cartesia.tts import CartesiaTTSService +from pipecat.services.cartesia.tts import CartesiaTTSService, CartesiaTTSSettings from pipecat.services.openai.llm import OpenAILLMService from pipecat.services.openai.stt import OpenAISTTService from pipecat.services.whisper.base_stt import BaseWhisperSTTSettings @@ -61,7 +61,9 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): tts = CartesiaTTSService( api_key=os.getenv("CARTESIA_API_KEY"), - voice_id="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady + settings=CartesiaTTSSettings( + voice="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady + ), ) llm = OpenAILLMService( diff --git a/examples/foundational/55j-update-settings-sarvam-stt.py b/examples/foundational/55j-update-settings-sarvam-stt.py index 58f0f80c7..57ebccab5 100644 --- a/examples/foundational/55j-update-settings-sarvam-stt.py +++ b/examples/foundational/55j-update-settings-sarvam-stt.py @@ -22,7 +22,7 @@ from pipecat.processors.aggregators.llm_response_universal import ( ) from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport -from pipecat.services.cartesia.tts import CartesiaTTSService +from pipecat.services.cartesia.tts import CartesiaTTSService, CartesiaTTSSettings from pipecat.services.openai.llm import OpenAILLMService from pipecat.services.sarvam.stt import SarvamSTTService, SarvamSTTSettings from pipecat.transcriptions.language import Language @@ -55,7 +55,9 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): tts = CartesiaTTSService( api_key=os.getenv("CARTESIA_API_KEY"), - voice_id="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady + settings=CartesiaTTSSettings( + voice="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady + ), ) llm = OpenAILLMService( diff --git a/examples/foundational/55k-update-settings-soniox-stt.py b/examples/foundational/55k-update-settings-soniox-stt.py index b31a0e708..ac339e3c1 100644 --- a/examples/foundational/55k-update-settings-soniox-stt.py +++ b/examples/foundational/55k-update-settings-soniox-stt.py @@ -22,7 +22,7 @@ from pipecat.processors.aggregators.llm_response_universal import ( ) from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport -from pipecat.services.cartesia.tts import CartesiaTTSService +from pipecat.services.cartesia.tts import CartesiaTTSService, CartesiaTTSSettings from pipecat.services.openai.llm import OpenAILLMService from pipecat.services.soniox.stt import SonioxSTTService, SonioxSTTSettings from pipecat.transcriptions.language import Language @@ -55,7 +55,9 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): tts = CartesiaTTSService( api_key=os.getenv("CARTESIA_API_KEY"), - voice_id="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady + settings=CartesiaTTSSettings( + voice="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady + ), ) llm = OpenAILLMService( diff --git a/examples/foundational/55l-update-settings-aws-transcribe-stt.py b/examples/foundational/55l-update-settings-aws-transcribe-stt.py index 910bc66b4..5594f21d9 100644 --- a/examples/foundational/55l-update-settings-aws-transcribe-stt.py +++ b/examples/foundational/55l-update-settings-aws-transcribe-stt.py @@ -23,7 +23,7 @@ from pipecat.processors.aggregators.llm_response_universal import ( from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport from pipecat.services.aws.stt import AWSTranscribeSTTService, AWSTranscribeSTTSettings -from pipecat.services.cartesia.tts import CartesiaTTSService +from pipecat.services.cartesia.tts import CartesiaTTSService, CartesiaTTSSettings from pipecat.services.openai.llm import OpenAILLMService from pipecat.transcriptions.language import Language from pipecat.transports.base_transport import BaseTransport, TransportParams @@ -55,7 +55,9 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): tts = CartesiaTTSService( api_key=os.getenv("CARTESIA_API_KEY"), - voice_id="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady + settings=CartesiaTTSSettings( + voice="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady + ), ) llm = OpenAILLMService( diff --git a/examples/foundational/55m-update-settings-cartesia-stt.py b/examples/foundational/55m-update-settings-cartesia-stt.py index 4956d8d75..f1a984d9b 100644 --- a/examples/foundational/55m-update-settings-cartesia-stt.py +++ b/examples/foundational/55m-update-settings-cartesia-stt.py @@ -23,7 +23,7 @@ from pipecat.processors.aggregators.llm_response_universal import ( from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport from pipecat.services.cartesia.stt import CartesiaSTTService, CartesiaSTTSettings -from pipecat.services.cartesia.tts import CartesiaTTSService +from pipecat.services.cartesia.tts import CartesiaTTSService, CartesiaTTSSettings from pipecat.services.openai.llm import OpenAILLMService from pipecat.transcriptions.language import Language from pipecat.transports.base_transport import BaseTransport, TransportParams @@ -55,7 +55,9 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): tts = CartesiaTTSService( api_key=os.getenv("CARTESIA_API_KEY"), - voice_id="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady + settings=CartesiaTTSSettings( + voice="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady + ), ) llm = OpenAILLMService( diff --git a/examples/foundational/55n-update-settings-cartesia-http-tts.py b/examples/foundational/55n-update-settings-cartesia-http-tts.py index 0423d855f..a58a8a778 100644 --- a/examples/foundational/55n-update-settings-cartesia-http-tts.py +++ b/examples/foundational/55n-update-settings-cartesia-http-tts.py @@ -58,7 +58,9 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): tts = CartesiaHttpTTSService( api_key=os.getenv("CARTESIA_API_KEY"), - voice_id="71a7ad14-091c-4e8e-a314-022ece01c121", + settings=CartesiaTTSSettings( + voice="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady + ), ) llm = OpenAILLMService( diff --git a/examples/foundational/55n-update-settings-cartesia-tts.py b/examples/foundational/55n-update-settings-cartesia-tts.py index 2ee07b830..e729c53f2 100644 --- a/examples/foundational/55n-update-settings-cartesia-tts.py +++ b/examples/foundational/55n-update-settings-cartesia-tts.py @@ -56,7 +56,9 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): tts = CartesiaTTSService( api_key=os.getenv("CARTESIA_API_KEY"), - voice_id="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady + settings=CartesiaTTSSettings( + voice="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady + ), ) llm = OpenAILLMService( diff --git a/examples/foundational/55zi-update-settings-azure-llm.py b/examples/foundational/55zi-update-settings-azure-llm.py index b6e8ccf71..29748491b 100644 --- a/examples/foundational/55zi-update-settings-azure-llm.py +++ b/examples/foundational/55zi-update-settings-azure-llm.py @@ -23,7 +23,7 @@ from pipecat.processors.aggregators.llm_response_universal import ( from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport from pipecat.services.azure.llm import AzureLLMService -from pipecat.services.cartesia.tts import CartesiaTTSService +from pipecat.services.cartesia.tts import CartesiaTTSService, CartesiaTTSSettings from pipecat.services.deepgram.stt import DeepgramSTTService from pipecat.services.openai.base_llm import OpenAILLMSettings from pipecat.transports.base_transport import BaseTransport, TransportParams @@ -55,7 +55,9 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): tts = CartesiaTTSService( api_key=os.getenv("CARTESIA_API_KEY"), - voice_id="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady + settings=CartesiaTTSSettings( + voice="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady + ), ) llm = AzureLLMService( diff --git a/examples/foundational/55zi-update-settings-openai-llm.py b/examples/foundational/55zi-update-settings-openai-llm.py index c9fb026f3..123fc7a04 100644 --- a/examples/foundational/55zi-update-settings-openai-llm.py +++ b/examples/foundational/55zi-update-settings-openai-llm.py @@ -22,7 +22,7 @@ from pipecat.processors.aggregators.llm_response_universal import ( ) from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport -from pipecat.services.cartesia.tts import CartesiaTTSService +from pipecat.services.cartesia.tts import CartesiaTTSService, CartesiaTTSSettings from pipecat.services.deepgram.stt import DeepgramSTTService from pipecat.services.openai.base_llm import OpenAILLMSettings from pipecat.services.openai.llm import OpenAILLMService @@ -55,7 +55,9 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): tts = CartesiaTTSService( api_key=os.getenv("CARTESIA_API_KEY"), - voice_id="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady + settings=CartesiaTTSSettings( + voice="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady + ), ) llm = OpenAILLMService( diff --git a/examples/foundational/55zj-update-settings-anthropic-llm.py b/examples/foundational/55zj-update-settings-anthropic-llm.py index 59ac73da6..d44102f2d 100644 --- a/examples/foundational/55zj-update-settings-anthropic-llm.py +++ b/examples/foundational/55zj-update-settings-anthropic-llm.py @@ -23,7 +23,7 @@ from pipecat.processors.aggregators.llm_response_universal import ( from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport from pipecat.services.anthropic.llm import AnthropicLLMService, AnthropicLLMSettings -from pipecat.services.cartesia.tts import CartesiaTTSService +from pipecat.services.cartesia.tts import CartesiaTTSService, CartesiaTTSSettings from pipecat.services.deepgram.stt import DeepgramSTTService from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams @@ -54,7 +54,9 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): tts = CartesiaTTSService( api_key=os.getenv("CARTESIA_API_KEY"), - voice_id="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady + settings=CartesiaTTSSettings( + voice="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady + ), ) llm = AnthropicLLMService( diff --git a/examples/foundational/55zk-update-settings-google-llm.py b/examples/foundational/55zk-update-settings-google-llm.py index 4a0a3de0f..d1222e422 100644 --- a/examples/foundational/55zk-update-settings-google-llm.py +++ b/examples/foundational/55zk-update-settings-google-llm.py @@ -22,7 +22,7 @@ from pipecat.processors.aggregators.llm_response_universal import ( ) from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport -from pipecat.services.cartesia.tts import CartesiaTTSService +from pipecat.services.cartesia.tts import CartesiaTTSService, CartesiaTTSSettings from pipecat.services.deepgram.stt import DeepgramSTTService from pipecat.services.google.llm import GoogleLLMService, GoogleLLMSettings from pipecat.transports.base_transport import BaseTransport, TransportParams @@ -54,7 +54,9 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): tts = CartesiaTTSService( api_key=os.getenv("CARTESIA_API_KEY"), - voice_id="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady + settings=CartesiaTTSSettings( + voice="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady + ), ) llm = GoogleLLMService( diff --git a/examples/foundational/55zk-update-settings-google-vertex-llm.py b/examples/foundational/55zk-update-settings-google-vertex-llm.py index fe8ef808b..aa9452d09 100644 --- a/examples/foundational/55zk-update-settings-google-vertex-llm.py +++ b/examples/foundational/55zk-update-settings-google-vertex-llm.py @@ -22,7 +22,7 @@ from pipecat.processors.aggregators.llm_response_universal import ( ) from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport -from pipecat.services.cartesia.tts import CartesiaTTSService +from pipecat.services.cartesia.tts import CartesiaTTSService, CartesiaTTSSettings from pipecat.services.deepgram.stt import DeepgramSTTService from pipecat.services.google.llm import GoogleLLMSettings from pipecat.services.google.llm_vertex import GoogleVertexLLMService @@ -55,7 +55,9 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): tts = CartesiaTTSService( api_key=os.getenv("CARTESIA_API_KEY"), - voice_id="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady + settings=CartesiaTTSSettings( + voice="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady + ), ) llm = GoogleVertexLLMService( diff --git a/examples/foundational/55zp-update-settings-aws-bedrock-llm.py b/examples/foundational/55zp-update-settings-aws-bedrock-llm.py index 72b5ae9be..c543ef50c 100644 --- a/examples/foundational/55zp-update-settings-aws-bedrock-llm.py +++ b/examples/foundational/55zp-update-settings-aws-bedrock-llm.py @@ -23,7 +23,7 @@ from pipecat.processors.aggregators.llm_response_universal import ( from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport from pipecat.services.aws.llm import AWSBedrockLLMService, AWSBedrockLLMSettings -from pipecat.services.cartesia.tts import CartesiaTTSService +from pipecat.services.cartesia.tts import CartesiaTTSService, CartesiaTTSSettings from pipecat.services.deepgram.stt import DeepgramSTTService from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams @@ -54,7 +54,9 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): tts = CartesiaTTSService( api_key=os.getenv("CARTESIA_API_KEY"), - voice_id="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady + settings=CartesiaTTSSettings( + voice="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady + ), ) llm = AWSBedrockLLMService( diff --git a/examples/foundational/55zq-update-settings-fal-stt.py b/examples/foundational/55zq-update-settings-fal-stt.py index 22ee38929..96f916d81 100644 --- a/examples/foundational/55zq-update-settings-fal-stt.py +++ b/examples/foundational/55zq-update-settings-fal-stt.py @@ -22,7 +22,7 @@ from pipecat.processors.aggregators.llm_response_universal import ( ) from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport -from pipecat.services.cartesia.tts import CartesiaTTSService +from pipecat.services.cartesia.tts import CartesiaTTSService, CartesiaTTSSettings from pipecat.services.fal.stt import FalSTTService, FalSTTSettings from pipecat.services.openai.llm import OpenAILLMService from pipecat.transports.base_transport import BaseTransport, TransportParams @@ -54,7 +54,9 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): tts = CartesiaTTSService( api_key=os.getenv("CARTESIA_API_KEY"), - voice_id="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady + settings=CartesiaTTSSettings( + voice="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady + ), ) llm = OpenAILLMService( diff --git a/examples/foundational/55zr-update-settings-gradium-stt.py b/examples/foundational/55zr-update-settings-gradium-stt.py index 65c70519d..0b3085125 100644 --- a/examples/foundational/55zr-update-settings-gradium-stt.py +++ b/examples/foundational/55zr-update-settings-gradium-stt.py @@ -22,7 +22,7 @@ from pipecat.processors.aggregators.llm_response_universal import ( ) from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport -from pipecat.services.cartesia.tts import CartesiaTTSService +from pipecat.services.cartesia.tts import CartesiaTTSService, CartesiaTTSSettings from pipecat.services.gradium.stt import GradiumSTTService, GradiumSTTSettings from pipecat.services.openai.llm import OpenAILLMService from pipecat.transports.base_transport import BaseTransport, TransportParams @@ -57,7 +57,9 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): tts = CartesiaTTSService( api_key=os.getenv("CARTESIA_API_KEY"), - voice_id="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady + settings=CartesiaTTSSettings( + voice="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady + ), ) llm = OpenAILLMService( diff --git a/examples/foundational/55zt-update-settings-nvidia-segmented-stt.py b/examples/foundational/55zt-update-settings-nvidia-segmented-stt.py index 122619aaa..55a6719be 100644 --- a/examples/foundational/55zt-update-settings-nvidia-segmented-stt.py +++ b/examples/foundational/55zt-update-settings-nvidia-segmented-stt.py @@ -22,7 +22,7 @@ from pipecat.processors.aggregators.llm_response_universal import ( ) from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport -from pipecat.services.cartesia.tts import CartesiaTTSService +from pipecat.services.cartesia.tts import CartesiaTTSService, CartesiaTTSSettings from pipecat.services.nvidia.stt import NvidiaSegmentedSTTService, NvidiaSegmentedSTTSettings from pipecat.services.openai.llm import OpenAILLMService from pipecat.transports.base_transport import BaseTransport, TransportParams @@ -54,7 +54,9 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): tts = CartesiaTTSService( api_key=os.getenv("CARTESIA_API_KEY"), - voice_id="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady + settings=CartesiaTTSSettings( + voice="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady + ), ) llm = OpenAILLMService( diff --git a/examples/foundational/55zt-update-settings-nvidia-stt.py b/examples/foundational/55zt-update-settings-nvidia-stt.py index 232db9bf3..2f15895d2 100644 --- a/examples/foundational/55zt-update-settings-nvidia-stt.py +++ b/examples/foundational/55zt-update-settings-nvidia-stt.py @@ -22,7 +22,7 @@ from pipecat.processors.aggregators.llm_response_universal import ( ) from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport -from pipecat.services.cartesia.tts import CartesiaTTSService +from pipecat.services.cartesia.tts import CartesiaTTSService, CartesiaTTSSettings from pipecat.services.nvidia.stt import NvidiaSTTService, NvidiaSTTSettings from pipecat.services.openai.llm import OpenAILLMService from pipecat.transcriptions.language import Language @@ -55,7 +55,9 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): tts = CartesiaTTSService( api_key=os.getenv("CARTESIA_API_KEY"), - voice_id="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady + settings=CartesiaTTSSettings( + voice="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady + ), ) llm = OpenAILLMService( diff --git a/examples/foundational/55zu-update-settings-openai-realtime-stt.py b/examples/foundational/55zu-update-settings-openai-realtime-stt.py index eb7be5c97..7cc31085b 100644 --- a/examples/foundational/55zu-update-settings-openai-realtime-stt.py +++ b/examples/foundational/55zu-update-settings-openai-realtime-stt.py @@ -22,7 +22,7 @@ from pipecat.processors.aggregators.llm_response_universal import ( ) from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport -from pipecat.services.cartesia.tts import CartesiaTTSService +from pipecat.services.cartesia.tts import CartesiaTTSService, CartesiaTTSSettings from pipecat.services.openai.llm import OpenAILLMService from pipecat.services.openai.stt import OpenAIRealtimeSTTService, OpenAIRealtimeSTTSettings from pipecat.transcriptions.language import Language @@ -55,7 +55,9 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): tts = CartesiaTTSService( api_key=os.getenv("CARTESIA_API_KEY"), - voice_id="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady + settings=CartesiaTTSSettings( + voice="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady + ), ) llm = OpenAILLMService( diff --git a/examples/foundational/55zx-update-settings-cerebras-llm.py b/examples/foundational/55zx-update-settings-cerebras-llm.py index 3937345e1..dc09cdae7 100644 --- a/examples/foundational/55zx-update-settings-cerebras-llm.py +++ b/examples/foundational/55zx-update-settings-cerebras-llm.py @@ -22,7 +22,7 @@ from pipecat.processors.aggregators.llm_response_universal import ( ) from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport -from pipecat.services.cartesia.tts import CartesiaTTSService +from pipecat.services.cartesia.tts import CartesiaTTSService, CartesiaTTSSettings from pipecat.services.cerebras.llm import CerebrasLLMService from pipecat.services.deepgram.stt import DeepgramSTTService from pipecat.services.openai.base_llm import OpenAILLMSettings @@ -55,7 +55,9 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): tts = CartesiaTTSService( api_key=os.getenv("CARTESIA_API_KEY"), - voice_id="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady + settings=CartesiaTTSSettings( + voice="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady + ), ) llm = CerebrasLLMService( diff --git a/examples/foundational/55zy-update-settings-deepseek-llm.py b/examples/foundational/55zy-update-settings-deepseek-llm.py index c96107c40..fe6e18185 100644 --- a/examples/foundational/55zy-update-settings-deepseek-llm.py +++ b/examples/foundational/55zy-update-settings-deepseek-llm.py @@ -22,7 +22,7 @@ from pipecat.processors.aggregators.llm_response_universal import ( ) from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport -from pipecat.services.cartesia.tts import CartesiaTTSService +from pipecat.services.cartesia.tts import CartesiaTTSService, CartesiaTTSSettings from pipecat.services.deepgram.stt import DeepgramSTTService from pipecat.services.deepseek.llm import DeepSeekLLMService from pipecat.services.openai.base_llm import OpenAILLMSettings @@ -55,7 +55,9 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): tts = CartesiaTTSService( api_key=os.getenv("CARTESIA_API_KEY"), - voice_id="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady + settings=CartesiaTTSSettings( + voice="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady + ), ) llm = DeepSeekLLMService( diff --git a/examples/foundational/55zz-update-settings-fireworks-llm.py b/examples/foundational/55zz-update-settings-fireworks-llm.py index 8c4388251..19b9276e6 100644 --- a/examples/foundational/55zz-update-settings-fireworks-llm.py +++ b/examples/foundational/55zz-update-settings-fireworks-llm.py @@ -22,7 +22,7 @@ from pipecat.processors.aggregators.llm_response_universal import ( ) from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport -from pipecat.services.cartesia.tts import CartesiaTTSService +from pipecat.services.cartesia.tts import CartesiaTTSService, CartesiaTTSSettings from pipecat.services.deepgram.stt import DeepgramSTTService from pipecat.services.fireworks.llm import FireworksLLMService from pipecat.services.openai.base_llm import OpenAILLMSettings @@ -55,7 +55,9 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): tts = CartesiaTTSService( api_key=os.getenv("CARTESIA_API_KEY"), - voice_id="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady + settings=CartesiaTTSSettings( + voice="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady + ), ) llm = FireworksLLMService( diff --git a/examples/foundational/55zza-update-settings-grok-llm.py b/examples/foundational/55zza-update-settings-grok-llm.py index e75c70b5f..c40f40ac6 100644 --- a/examples/foundational/55zza-update-settings-grok-llm.py +++ b/examples/foundational/55zza-update-settings-grok-llm.py @@ -22,7 +22,7 @@ from pipecat.processors.aggregators.llm_response_universal import ( ) from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport -from pipecat.services.cartesia.tts import CartesiaTTSService +from pipecat.services.cartesia.tts import CartesiaTTSService, CartesiaTTSSettings from pipecat.services.deepgram.stt import DeepgramSTTService from pipecat.services.grok.llm import GrokLLMService from pipecat.services.openai.base_llm import OpenAILLMSettings @@ -55,7 +55,9 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): tts = CartesiaTTSService( api_key=os.getenv("CARTESIA_API_KEY"), - voice_id="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady + settings=CartesiaTTSSettings( + voice="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady + ), ) llm = GrokLLMService( diff --git a/examples/foundational/55zzb-update-settings-groq-llm.py b/examples/foundational/55zzb-update-settings-groq-llm.py index 2f7f82bb2..be5467b8a 100644 --- a/examples/foundational/55zzb-update-settings-groq-llm.py +++ b/examples/foundational/55zzb-update-settings-groq-llm.py @@ -22,7 +22,7 @@ from pipecat.processors.aggregators.llm_response_universal import ( ) from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport -from pipecat.services.cartesia.tts import CartesiaTTSService +from pipecat.services.cartesia.tts import CartesiaTTSService, CartesiaTTSSettings from pipecat.services.deepgram.stt import DeepgramSTTService from pipecat.services.groq.llm import GroqLLMService from pipecat.services.openai.base_llm import OpenAILLMSettings @@ -55,7 +55,9 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): tts = CartesiaTTSService( api_key=os.getenv("CARTESIA_API_KEY"), - voice_id="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady + settings=CartesiaTTSSettings( + voice="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady + ), ) llm = GroqLLMService( diff --git a/examples/foundational/55zzc-update-settings-mistral-llm.py b/examples/foundational/55zzc-update-settings-mistral-llm.py index ab3bd4f76..f6fa824d4 100644 --- a/examples/foundational/55zzc-update-settings-mistral-llm.py +++ b/examples/foundational/55zzc-update-settings-mistral-llm.py @@ -22,7 +22,7 @@ from pipecat.processors.aggregators.llm_response_universal import ( ) from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport -from pipecat.services.cartesia.tts import CartesiaTTSService +from pipecat.services.cartesia.tts import CartesiaTTSService, CartesiaTTSSettings from pipecat.services.deepgram.stt import DeepgramSTTService from pipecat.services.mistral.llm import MistralLLMService from pipecat.services.openai.base_llm import OpenAILLMSettings @@ -55,7 +55,9 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): tts = CartesiaTTSService( api_key=os.getenv("CARTESIA_API_KEY"), - voice_id="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady + settings=CartesiaTTSSettings( + voice="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady + ), ) llm = MistralLLMService( diff --git a/examples/foundational/55zzd-update-settings-nvidia-llm.py b/examples/foundational/55zzd-update-settings-nvidia-llm.py index a8699c71b..5e26e8213 100644 --- a/examples/foundational/55zzd-update-settings-nvidia-llm.py +++ b/examples/foundational/55zzd-update-settings-nvidia-llm.py @@ -22,7 +22,7 @@ from pipecat.processors.aggregators.llm_response_universal import ( ) from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport -from pipecat.services.cartesia.tts import CartesiaTTSService +from pipecat.services.cartesia.tts import CartesiaTTSService, CartesiaTTSSettings from pipecat.services.deepgram.stt import DeepgramSTTService from pipecat.services.nvidia.llm import NvidiaLLMService from pipecat.services.openai.base_llm import OpenAILLMSettings @@ -55,7 +55,9 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): tts = CartesiaTTSService( api_key=os.getenv("CARTESIA_API_KEY"), - voice_id="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady + settings=CartesiaTTSSettings( + voice="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady + ), ) llm = NvidiaLLMService( diff --git a/examples/foundational/55zze-update-settings-ollama-llm.py b/examples/foundational/55zze-update-settings-ollama-llm.py index 4595604fd..7e3fa02de 100644 --- a/examples/foundational/55zze-update-settings-ollama-llm.py +++ b/examples/foundational/55zze-update-settings-ollama-llm.py @@ -22,7 +22,7 @@ from pipecat.processors.aggregators.llm_response_universal import ( ) from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport -from pipecat.services.cartesia.tts import CartesiaTTSService +from pipecat.services.cartesia.tts import CartesiaTTSService, CartesiaTTSSettings from pipecat.services.deepgram.stt import DeepgramSTTService from pipecat.services.ollama.llm import OLLamaLLMService from pipecat.services.openai.base_llm import OpenAILLMSettings @@ -55,7 +55,9 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): tts = CartesiaTTSService( api_key=os.getenv("CARTESIA_API_KEY"), - voice_id="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady + settings=CartesiaTTSSettings( + voice="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady + ), ) llm = OLLamaLLMService( diff --git a/examples/foundational/55zzf-update-settings-openrouter-llm.py b/examples/foundational/55zzf-update-settings-openrouter-llm.py index 9a381d88b..c31a7c43c 100644 --- a/examples/foundational/55zzf-update-settings-openrouter-llm.py +++ b/examples/foundational/55zzf-update-settings-openrouter-llm.py @@ -22,7 +22,7 @@ from pipecat.processors.aggregators.llm_response_universal import ( ) from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport -from pipecat.services.cartesia.tts import CartesiaTTSService +from pipecat.services.cartesia.tts import CartesiaTTSService, CartesiaTTSSettings from pipecat.services.deepgram.stt import DeepgramSTTService from pipecat.services.openai.base_llm import OpenAILLMSettings from pipecat.services.openrouter.llm import OpenRouterLLMService @@ -55,7 +55,9 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): tts = CartesiaTTSService( api_key=os.getenv("CARTESIA_API_KEY"), - voice_id="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady + settings=CartesiaTTSSettings( + voice="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady + ), ) llm = OpenRouterLLMService( diff --git a/examples/foundational/55zzg-update-settings-perplexity-llm.py b/examples/foundational/55zzg-update-settings-perplexity-llm.py index f55975685..5227c6063 100644 --- a/examples/foundational/55zzg-update-settings-perplexity-llm.py +++ b/examples/foundational/55zzg-update-settings-perplexity-llm.py @@ -22,7 +22,7 @@ from pipecat.processors.aggregators.llm_response_universal import ( ) from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport -from pipecat.services.cartesia.tts import CartesiaTTSService +from pipecat.services.cartesia.tts import CartesiaTTSService, CartesiaTTSSettings from pipecat.services.deepgram.stt import DeepgramSTTService from pipecat.services.openai.base_llm import OpenAILLMSettings from pipecat.services.perplexity.llm import PerplexityLLMService @@ -55,7 +55,9 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): tts = CartesiaTTSService( api_key=os.getenv("CARTESIA_API_KEY"), - voice_id="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady + settings=CartesiaTTSSettings( + voice="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady + ), ) llm = PerplexityLLMService(api_key=os.getenv("PERPLEXITY_API_KEY")) diff --git a/examples/foundational/55zzh-update-settings-qwen-llm.py b/examples/foundational/55zzh-update-settings-qwen-llm.py index 019e916cb..5c6d17d1d 100644 --- a/examples/foundational/55zzh-update-settings-qwen-llm.py +++ b/examples/foundational/55zzh-update-settings-qwen-llm.py @@ -22,7 +22,7 @@ from pipecat.processors.aggregators.llm_response_universal import ( ) from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport -from pipecat.services.cartesia.tts import CartesiaTTSService +from pipecat.services.cartesia.tts import CartesiaTTSService, CartesiaTTSSettings from pipecat.services.deepgram.stt import DeepgramSTTService from pipecat.services.openai.base_llm import OpenAILLMSettings from pipecat.services.qwen.llm import QwenLLMService @@ -55,7 +55,9 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): tts = CartesiaTTSService( api_key=os.getenv("CARTESIA_API_KEY"), - voice_id="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady + settings=CartesiaTTSSettings( + voice="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady + ), ) llm = QwenLLMService( diff --git a/examples/foundational/55zzi-update-settings-sambanova-llm.py b/examples/foundational/55zzi-update-settings-sambanova-llm.py index 040e95da1..cececc078 100644 --- a/examples/foundational/55zzi-update-settings-sambanova-llm.py +++ b/examples/foundational/55zzi-update-settings-sambanova-llm.py @@ -22,7 +22,7 @@ from pipecat.processors.aggregators.llm_response_universal import ( ) from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport -from pipecat.services.cartesia.tts import CartesiaTTSService +from pipecat.services.cartesia.tts import CartesiaTTSService, CartesiaTTSSettings from pipecat.services.deepgram.stt import DeepgramSTTService from pipecat.services.openai.base_llm import OpenAILLMSettings from pipecat.services.sambanova.llm import SambaNovaLLMService @@ -55,7 +55,9 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): tts = CartesiaTTSService( api_key=os.getenv("CARTESIA_API_KEY"), - voice_id="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady + settings=CartesiaTTSSettings( + voice="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady + ), ) llm = SambaNovaLLMService( diff --git a/examples/foundational/55zzj-update-settings-together-llm.py b/examples/foundational/55zzj-update-settings-together-llm.py index b1c8c049d..4e1c9732f 100644 --- a/examples/foundational/55zzj-update-settings-together-llm.py +++ b/examples/foundational/55zzj-update-settings-together-llm.py @@ -22,7 +22,7 @@ from pipecat.processors.aggregators.llm_response_universal import ( ) from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport -from pipecat.services.cartesia.tts import CartesiaTTSService +from pipecat.services.cartesia.tts import CartesiaTTSService, CartesiaTTSSettings from pipecat.services.deepgram.stt import DeepgramSTTService from pipecat.services.openai.base_llm import OpenAILLMSettings from pipecat.services.together.llm import TogetherLLMService @@ -55,7 +55,9 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): tts = CartesiaTTSService( api_key=os.getenv("CARTESIA_API_KEY"), - voice_id="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady + settings=CartesiaTTSSettings( + voice="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady + ), ) llm = TogetherLLMService( diff --git a/examples/foundational/55zzn-update-settings-groq-stt.py b/examples/foundational/55zzn-update-settings-groq-stt.py index 1d488119c..7a8551be2 100644 --- a/examples/foundational/55zzn-update-settings-groq-stt.py +++ b/examples/foundational/55zzn-update-settings-groq-stt.py @@ -22,7 +22,7 @@ from pipecat.processors.aggregators.llm_response_universal import ( ) from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport -from pipecat.services.cartesia.tts import CartesiaTTSService +from pipecat.services.cartesia.tts import CartesiaTTSService, CartesiaTTSSettings from pipecat.services.groq.stt import GroqSTTService from pipecat.services.openai.llm import OpenAILLMService from pipecat.services.whisper.base_stt import BaseWhisperSTTSettings @@ -57,7 +57,9 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): tts = CartesiaTTSService( api_key=os.getenv("CARTESIA_API_KEY"), - voice_id="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady + settings=CartesiaTTSSettings( + voice="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady + ), ) llm = OpenAILLMService( diff --git a/examples/foundational/56-lemonslice-transport.py b/examples/foundational/56-lemonslice-transport.py index a3b6b60d3..6085f3b00 100644 --- a/examples/foundational/56-lemonslice-transport.py +++ b/examples/foundational/56-lemonslice-transport.py @@ -23,7 +23,7 @@ from pipecat.processors.aggregators.llm_response_universal import ( LLMUserAggregatorParams, ) from pipecat.services.deepgram.stt import DeepgramSTTService -from pipecat.services.elevenlabs.tts import ElevenLabsTTSService +from pipecat.services.elevenlabs.tts import ElevenLabsTTSService, ElevenLabsTTSSettings from pipecat.services.groq.llm import GroqLLMService from pipecat.transports.lemonslice.transport import ( LemonSliceNewSessionRequest, @@ -62,7 +62,9 @@ async def main(): tts = ElevenLabsTTSService( api_key=os.getenv("ELEVENLABS_API_KEY", ""), - voice_id=os.getenv("ELEVENLABS_VOICE_ID", ""), + settings=ElevenLabsTTSSettings( + voice="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady + ), ) context = LLMContext() diff --git a/examples/quickstart/bot.py b/examples/quickstart/bot.py index fbe27d783..956331d50 100644 --- a/examples/quickstart/bot.py +++ b/examples/quickstart/bot.py @@ -45,7 +45,7 @@ from pipecat.processors.aggregators.llm_response_universal import ( ) from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport -from pipecat.services.cartesia.tts import CartesiaTTSService +from pipecat.services.cartesia.tts import CartesiaTTSService, CartesiaTTSSettings from pipecat.services.deepgram.stt import DeepgramSTTService from pipecat.services.openai.llm import OpenAILLMService from pipecat.transports.base_transport import BaseTransport, TransportParams @@ -63,7 +63,9 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): tts = CartesiaTTSService( api_key=os.getenv("CARTESIA_API_KEY"), - voice_id="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady + settings=CartesiaTTSSettings( + voice="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady + ), ) llm = OpenAILLMService(api_key=os.getenv("OPENAI_API_KEY")) diff --git a/scripts/evals/eval.py b/scripts/evals/eval.py index 8084bc3a1..d45e6343b 100644 --- a/scripts/evals/eval.py +++ b/scripts/evals/eval.py @@ -48,7 +48,7 @@ from pipecat.processors.aggregators.llm_response_universal import ( from pipecat.processors.audio.audio_buffer_processor import AudioBufferProcessor from pipecat.processors.frame_processor import FrameDirection from pipecat.runner.types import RunnerArguments -from pipecat.services.cartesia.tts import CartesiaTTSService +from pipecat.services.cartesia.tts import CartesiaTTSService, CartesiaTTSSettings from pipecat.services.deepgram.stt import DeepgramSTTService, LiveOptions from pipecat.services.llm_service import FunctionCallParams from pipecat.services.openai.llm import OpenAILLMService diff --git a/src/pipecat/services/openai/base_llm.py b/src/pipecat/services/openai/base_llm.py index 52fb451c3..cf4101305 100644 --- a/src/pipecat/services/openai/base_llm.py +++ b/src/pipecat/services/openai/base_llm.py @@ -320,7 +320,7 @@ class BaseOpenAILLMService(LLMService): "top_p": self._settings.top_p, "max_tokens": self._settings.max_tokens, "max_completion_tokens": self._settings.max_completion_tokens, - "service_tier": self._service_tier, + "service_tier": self._service_tier if self._service_tier is not None else NOT_GIVEN, } # Messages, tools, tool_choice diff --git a/src/pipecat/services/sarvam/tts.py b/src/pipecat/services/sarvam/tts.py index 659a58bdd..0d605fc6b 100644 --- a/src/pipecat/services/sarvam/tts.py +++ b/src/pipecat/services/sarvam/tts.py @@ -272,37 +272,22 @@ class SarvamHttpTTSSettings(TTSSettings): @dataclass -class SarvamTTSSettings(TTSSettings): +class SarvamTTSSettings(SarvamHttpTTSSettings): """Settings for Sarvam WebSocket TTS service. + Extends :class:`SarvamHttpTTSSettings` with WebSocket-specific buffering parameters. + Parameters: - enable_preprocessing: Enable text preprocessing. Defaults to False. - **Note:** Always enabled for bulbul:v3-beta. min_buffer_size: Minimum characters to buffer before generating audio. Lower values reduce latency but may affect quality. Defaults to 50. max_chunk_length: Maximum characters processed in a single chunk. Controls memory usage and processing efficiency. Defaults to 150. - pace: Speech pace multiplier. Defaults to 1.0. - - bulbul:v2: Range 0.3 to 3.0 - - bulbul:v3-beta: Range 0.5 to 2.0 - pitch: Voice pitch adjustment (-0.75 to 0.75). Defaults to 0.0. - **Note:** Only supported for bulbul:v2. Ignored for v3 models. - loudness: Volume multiplier (0.3 to 3.0). Defaults to 1.0. - **Note:** Only supported for bulbul:v2. Ignored for v3 models. - temperature: Controls output randomness for bulbul:v3-beta (0.01 to 1.0). - Lower = more deterministic, higher = more random. Defaults to 0.6. - **Note:** Only supported for bulbul:v3-beta. Ignored for v2. """ _aliases: ClassVar[Dict[str, str]] = {"target_language_code": "language"} - enable_preprocessing: bool | None | _NotGiven = field(default_factory=lambda: NOT_GIVEN) min_buffer_size: int | None | _NotGiven = field(default_factory=lambda: NOT_GIVEN) max_chunk_length: int | None | _NotGiven = field(default_factory=lambda: NOT_GIVEN) - pace: float | None | _NotGiven = field(default_factory=lambda: NOT_GIVEN) - pitch: float | None | _NotGiven = field(default_factory=lambda: NOT_GIVEN) - loudness: float | None | _NotGiven = field(default_factory=lambda: NOT_GIVEN) - temperature: float | None | _NotGiven = field(default_factory=lambda: NOT_GIVEN) class SarvamHttpTTSService(TTSService): From 8a203dd98feafd8dd662f85ae580040da5cf1b62 Mon Sep 17 00:00:00 2001 From: Mark Backman Date: Wed, 4 Mar 2026 23:29:50 -0500 Subject: [PATCH 0815/1060] Update more examples, misc services --- examples/foundational/03-still-frame.py | 6 +- .../foundational/03a-local-still-frame.py | 6 +- .../foundational/05-sync-speech-and-image.py | 6 +- .../05a-local-sync-speech-and-image.py | 6 +- ...o-function-calling-gemini-openai-format.py | 2 +- .../14p-function-calling-gemini-vertex-ai.py | 2 +- .../foundational/14r-function-calling-aws.py | 2 +- .../foundational/36-user-email-gathering.py | 4 +- .../55d-update-settings-assemblyai-stt.py | 9 +-- .../55h-update-settings-speechmatics-stt.py | 2 +- ...55o-update-settings-elevenlabs-http-tts.py | 2 +- .../55o-update-settings-elevenlabs-tts.py | 2 +- .../55u-update-settings-rime-http-tts.py | 4 +- .../55u-update-settings-rime-tts.py | 2 +- .../55v-update-settings-lmnt-tts.py | 2 +- .../55w-update-settings-fish-tts.py | 2 +- .../55z-update-settings-hume-tts.py | 2 +- .../55zc-update-settings-gemini-tts.py | 6 +- .../55zh-update-settings-resembleai-tts.py | 2 +- .../55zi-update-settings-azure-llm.py | 4 +- .../55zp-update-settings-aws-bedrock-llm.py | 6 +- .../55zv-update-settings-asyncai-http-tts.py | 4 +- .../55zv-update-settings-asyncai-tts.py | 4 +- .../55zw-update-settings-gradium-tts.py | 2 +- .../55zz-update-settings-fireworks-llm.py | 4 +- .../55zzb-update-settings-groq-llm.py | 4 +- .../55zzd-update-settings-nvidia-llm.py | 4 +- .../55zze-update-settings-ollama-llm.py | 4 +- .../55zzh-update-settings-qwen-llm.py | 4 +- .../55zzj-update-settings-together-llm.py | 4 +- src/pipecat/services/azure/image.py | 35 ++++++++-- src/pipecat/services/fal/image.py | 70 +++++++++++++++++-- src/pipecat/services/google/image.py | 33 ++++++--- src/pipecat/services/heygen/video.py | 10 ++- src/pipecat/services/openai/image.py | 31 ++++++-- src/pipecat/services/tavus/video.py | 10 ++- 36 files changed, 221 insertions(+), 81 deletions(-) diff --git a/examples/foundational/03-still-frame.py b/examples/foundational/03-still-frame.py index def125165..a98a53637 100644 --- a/examples/foundational/03-still-frame.py +++ b/examples/foundational/03-still-frame.py @@ -16,7 +16,7 @@ from pipecat.pipeline.runner import PipelineRunner from pipecat.pipeline.task import PipelineTask from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport -from pipecat.services.fal.image import FalImageGenService +from pipecat.services.fal.image import FalImageGenService, FalImageGenSettings from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams @@ -45,7 +45,9 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): # Create an HTTP session async with aiohttp.ClientSession() as session: imagegen = FalImageGenService( - params=FalImageGenService.InputParams(image_size="square_hd"), + settings=FalImageGenSettings( + image_size="square_hd", + ), aiohttp_session=session, key=os.getenv("FAL_KEY"), ) diff --git a/examples/foundational/03a-local-still-frame.py b/examples/foundational/03a-local-still-frame.py index b25c51c4a..db67848e8 100644 --- a/examples/foundational/03a-local-still-frame.py +++ b/examples/foundational/03a-local-still-frame.py @@ -17,7 +17,7 @@ from pipecat.frames.frames import TextFrame from pipecat.pipeline.pipeline import Pipeline from pipecat.pipeline.runner import PipelineRunner from pipecat.pipeline.task import PipelineTask -from pipecat.services.fal.image import FalImageGenService +from pipecat.services.fal.image import FalImageGenService, FalImageGenSettings from pipecat.transports.local.tk import TkLocalTransport, TkTransportParams load_dotenv(override=True) @@ -37,7 +37,9 @@ async def main(): ) imagegen = FalImageGenService( - params=FalImageGenService.InputParams(image_size="square_hd"), + settings=FalImageGenSettings( + image_size="square_hd", + ), aiohttp_session=session, key=os.getenv("FAL_KEY"), ) diff --git a/examples/foundational/05-sync-speech-and-image.py b/examples/foundational/05-sync-speech-and-image.py index 95de1143b..b77ff1612 100644 --- a/examples/foundational/05-sync-speech-and-image.py +++ b/examples/foundational/05-sync-speech-and-image.py @@ -28,7 +28,7 @@ from pipecat.processors.frame_processor import FrameDirection, FrameProcessor from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport from pipecat.services.cartesia.tts import CartesiaHttpTTSService, CartesiaTTSSettings -from pipecat.services.fal.image import FalImageGenService +from pipecat.services.fal.image import FalImageGenService, FalImageGenSettings from pipecat.services.openai.llm import OpenAILLMService from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams @@ -104,7 +104,9 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): ) imagegen = FalImageGenService( - params=FalImageGenService.InputParams(image_size="square_hd"), + settings=FalImageGenSettings( + image_size="square_hd", + ), aiohttp_session=session, key=os.getenv("FAL_KEY"), ) diff --git a/examples/foundational/05a-local-sync-speech-and-image.py b/examples/foundational/05a-local-sync-speech-and-image.py index 03b690c11..993e8eb07 100644 --- a/examples/foundational/05a-local-sync-speech-and-image.py +++ b/examples/foundational/05a-local-sync-speech-and-image.py @@ -29,7 +29,7 @@ from pipecat.processors.aggregators.llm_context import LLMContext from pipecat.processors.aggregators.sentence import SentenceAggregator from pipecat.processors.frame_processor import FrameDirection, FrameProcessor from pipecat.services.cartesia.tts import CartesiaHttpTTSService, CartesiaTTSSettings -from pipecat.services.fal.image import FalImageGenService +from pipecat.services.fal.image import FalImageGenService, FalImageGenSettings from pipecat.services.openai.llm import OpenAILLMService from pipecat.transports.local.tk import TkLocalTransport, TkTransportParams @@ -104,7 +104,9 @@ async def main(): ) imagegen = FalImageGenService( - params=FalImageGenService.InputParams(image_size="square_hd"), + settings=FalImageGenSettings( + image_size="square_hd", + ), aiohttp_session=session, key=os.getenv("FAL_KEY"), ) diff --git a/examples/foundational/14o-function-calling-gemini-openai-format.py b/examples/foundational/14o-function-calling-gemini-openai-format.py index 4a752586f..5eb8ff89d 100644 --- a/examples/foundational/14o-function-calling-gemini-openai-format.py +++ b/examples/foundational/14o-function-calling-gemini-openai-format.py @@ -65,7 +65,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): tts = ElevenLabsTTSService( api_key=os.getenv("ELEVENLABS_API_KEY", ""), settings=ElevenLabsTTSSettings( - voice_id=os.getenv("ELEVENLABS_VOICE_ID", ""), + voice=os.getenv("ELEVENLABS_VOICE_ID", ""), ), ) diff --git a/examples/foundational/14p-function-calling-gemini-vertex-ai.py b/examples/foundational/14p-function-calling-gemini-vertex-ai.py index 3ff062201..bf7b9458d 100644 --- a/examples/foundational/14p-function-calling-gemini-vertex-ai.py +++ b/examples/foundational/14p-function-calling-gemini-vertex-ai.py @@ -65,7 +65,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): tts = ElevenLabsTTSService( api_key=os.getenv("ELEVENLABS_API_KEY", ""), settings=ElevenLabsTTSSettings( - voice_id=os.getenv("ELEVENLABS_VOICE_ID", ""), + voice=os.getenv("ELEVENLABS_VOICE_ID", ""), ), ) diff --git a/examples/foundational/14r-function-calling-aws.py b/examples/foundational/14r-function-calling-aws.py index 9e8e9836f..9d7e4e7a1 100644 --- a/examples/foundational/14r-function-calling-aws.py +++ b/examples/foundational/14r-function-calling-aws.py @@ -67,7 +67,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): tts = AWSPollyTTSService( region="us-west-2", # only specific regions support generative TTS settings=AWSPollyTTSSettings( - voice_id="Joanna", + voice="Joanna", engine="generative", rate="1.1", ), diff --git a/examples/foundational/36-user-email-gathering.py b/examples/foundational/36-user-email-gathering.py index 9c4bdd4ac..5bdb937d0 100644 --- a/examples/foundational/36-user-email-gathering.py +++ b/examples/foundational/36-user-email-gathering.py @@ -77,7 +77,9 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): # (see https://docs.rime.ai/api-reference/spell) # tts = RimeHttpTTSService( # api_key=os.getenv("RIME_API_KEY", ""), - # voice_id="eva", + # settings=RimeTTSSettings( + # voice="eva", + # ), # aiohttp_session=session, # ) diff --git a/examples/foundational/55d-update-settings-assemblyai-stt.py b/examples/foundational/55d-update-settings-assemblyai-stt.py index e6d10d04f..9cd5641fd 100644 --- a/examples/foundational/55d-update-settings-assemblyai-stt.py +++ b/examples/foundational/55d-update-settings-assemblyai-stt.py @@ -22,7 +22,6 @@ from pipecat.processors.aggregators.llm_response_universal import ( ) from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport -from pipecat.services.assemblyai.models import AssemblyAIConnectionParams from pipecat.services.assemblyai.stt import AssemblyAISTTService, AssemblyAISTTSettings from pipecat.services.cartesia.tts import CartesiaTTSService, CartesiaTTSSettings from pipecat.services.openai.llm import OpenAILLMService @@ -53,8 +52,8 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): stt = AssemblyAISTTService( api_key=os.getenv("ASSEMBLYAI_API_KEY"), - connection_params=AssemblyAIConnectionParams( - speech_model="u3-rt-pro", + settings=AssemblyAISTTSettings( + model="u3-rt-pro", ), ) @@ -111,9 +110,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): await task.queue_frame( STTUpdateSettingsFrame( delta=AssemblyAISTTSettings( - connection_params=AssemblyAIConnectionParams( - keyterms_prompt=["Xiomara", "Saoirse", "Krzystof", "Nguyen", "Pipecat"] - ) + keyterms_prompt=["Xiomara", "Saoirse", "Krzystof", "Nguyen", "Pipecat"] ) ) ) diff --git a/examples/foundational/55h-update-settings-speechmatics-stt.py b/examples/foundational/55h-update-settings-speechmatics-stt.py index 1471f7ef2..7a0f493a8 100644 --- a/examples/foundational/55h-update-settings-speechmatics-stt.py +++ b/examples/foundational/55h-update-settings-speechmatics-stt.py @@ -53,7 +53,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): stt = SpeechmaticsSTTService( api_key=os.getenv("SPEECHMATICS_API_KEY"), - params=SpeechmaticsSTTService.InputParams( + settings=SpeechmaticsSTTSettings( enable_diarization=True, speaker_active_format="<{speaker_id}>{text}", speaker_passive_format="<{speaker_id}>{text}", diff --git a/examples/foundational/55o-update-settings-elevenlabs-http-tts.py b/examples/foundational/55o-update-settings-elevenlabs-http-tts.py index 7cdf97c25..c6160d1c2 100644 --- a/examples/foundational/55o-update-settings-elevenlabs-http-tts.py +++ b/examples/foundational/55o-update-settings-elevenlabs-http-tts.py @@ -58,7 +58,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): tts = ElevenLabsHttpTTSService( api_key=os.getenv("ELEVENLABS_API_KEY"), - voice_id=os.getenv("ELEVENLABS_VOICE_ID"), + settings=ElevenLabsHttpTTSSettings(voice=os.getenv("ELEVENLABS_VOICE_ID")), aiohttp_session=session, ) diff --git a/examples/foundational/55o-update-settings-elevenlabs-tts.py b/examples/foundational/55o-update-settings-elevenlabs-tts.py index 6d5d74a17..104dd314f 100644 --- a/examples/foundational/55o-update-settings-elevenlabs-tts.py +++ b/examples/foundational/55o-update-settings-elevenlabs-tts.py @@ -55,7 +55,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): tts = ElevenLabsTTSService( api_key=os.getenv("ELEVENLABS_API_KEY"), - voice_id=os.getenv("ELEVENLABS_VOICE_ID"), + settings=ElevenLabsTTSSettings(voice=os.getenv("ELEVENLABS_VOICE_ID")), ) llm = OpenAILLMService( diff --git a/examples/foundational/55u-update-settings-rime-http-tts.py b/examples/foundational/55u-update-settings-rime-http-tts.py index f57d2b83e..8515b796e 100644 --- a/examples/foundational/55u-update-settings-rime-http-tts.py +++ b/examples/foundational/55u-update-settings-rime-http-tts.py @@ -57,7 +57,9 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): stt = DeepgramSTTService(api_key=os.getenv("DEEPGRAM_API_KEY")) tts = RimeHttpTTSService( - api_key=os.getenv("RIME_API_KEY"), voice_id="eva", aiohttp_session=session + api_key=os.getenv("RIME_API_KEY"), + settings=RimeTTSSettings(voice="eva"), + aiohttp_session=session, ) llm = OpenAILLMService( diff --git a/examples/foundational/55u-update-settings-rime-tts.py b/examples/foundational/55u-update-settings-rime-tts.py index 5c4cdee67..72c63af8c 100644 --- a/examples/foundational/55u-update-settings-rime-tts.py +++ b/examples/foundational/55u-update-settings-rime-tts.py @@ -54,7 +54,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): tts = RimeTTSService( api_key=os.getenv("RIME_API_KEY"), - voice_id="luna", + settings=RimeTTSSettings(voice="luna"), ) llm = OpenAILLMService( diff --git a/examples/foundational/55v-update-settings-lmnt-tts.py b/examples/foundational/55v-update-settings-lmnt-tts.py index 0a2c27401..d0651c84e 100644 --- a/examples/foundational/55v-update-settings-lmnt-tts.py +++ b/examples/foundational/55v-update-settings-lmnt-tts.py @@ -54,7 +54,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): tts = LmntTTSService( api_key=os.getenv("LMNT_API_KEY"), - voice_id="lily", + settings=LmntTTSSettings(voice="lily"), ) llm = OpenAILLMService( diff --git a/examples/foundational/55w-update-settings-fish-tts.py b/examples/foundational/55w-update-settings-fish-tts.py index 87a4a2072..ff95838f7 100644 --- a/examples/foundational/55w-update-settings-fish-tts.py +++ b/examples/foundational/55w-update-settings-fish-tts.py @@ -54,7 +54,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): tts = FishAudioTTSService( api_key=os.getenv("FISH_API_KEY"), - model="4ce7e917cedd4bc2bb2e6ff3a46acaa1", # Barack Obama + settings=FishAudioTTSSettings(voice="4ce7e917cedd4bc2bb2e6ff3a46acaa1"), # Barack Obama ) llm = OpenAILLMService( diff --git a/examples/foundational/55z-update-settings-hume-tts.py b/examples/foundational/55z-update-settings-hume-tts.py index f16745cad..d01dc78bf 100644 --- a/examples/foundational/55z-update-settings-hume-tts.py +++ b/examples/foundational/55z-update-settings-hume-tts.py @@ -54,7 +54,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): tts = HumeTTSService( api_key=os.getenv("HUME_API_KEY"), - voice_id="f898a92e-685f-43fa-985b-a46920f0650b", + settings=HumeTTSSettings(voice="f898a92e-685f-43fa-985b-a46920f0650b"), ) llm = OpenAILLMService( diff --git a/examples/foundational/55zc-update-settings-gemini-tts.py b/examples/foundational/55zc-update-settings-gemini-tts.py index 637ee65a7..99a91d176 100644 --- a/examples/foundational/55zc-update-settings-gemini-tts.py +++ b/examples/foundational/55zc-update-settings-gemini-tts.py @@ -55,9 +55,9 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): tts = GeminiTTSService( credentials=os.getenv("GOOGLE_TEST_CREDENTIALS"), - model="gemini-2.5-flash-tts", - voice_id="Charon", - params=GeminiTTSService.InputParams( + settings=GeminiTTSSettings( + model="gemini-2.5-flash-tts", + voice="Charon", language=Language.EN_US, prompt="You are a helpful AI assistant. Speak in a natural, conversational tone.", ), diff --git a/examples/foundational/55zh-update-settings-resembleai-tts.py b/examples/foundational/55zh-update-settings-resembleai-tts.py index 7aba67b1f..8428357b5 100644 --- a/examples/foundational/55zh-update-settings-resembleai-tts.py +++ b/examples/foundational/55zh-update-settings-resembleai-tts.py @@ -54,7 +54,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): tts = ResembleAITTSService( api_key=os.getenv("RESEMBLE_API_KEY"), - voice_id=os.getenv("RESEMBLE_VOICE_UUID"), + settings=ResembleAITTSSettings(voice=os.getenv("RESEMBLE_VOICE_UUID")), ) llm = OpenAILLMService( diff --git a/examples/foundational/55zi-update-settings-azure-llm.py b/examples/foundational/55zi-update-settings-azure-llm.py index 29748491b..b7fe5d745 100644 --- a/examples/foundational/55zi-update-settings-azure-llm.py +++ b/examples/foundational/55zi-update-settings-azure-llm.py @@ -22,7 +22,7 @@ from pipecat.processors.aggregators.llm_response_universal import ( ) from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport -from pipecat.services.azure.llm import AzureLLMService +from pipecat.services.azure.llm import AzureLLMService, AzureLLMSettings from pipecat.services.cartesia.tts import CartesiaTTSService, CartesiaTTSSettings from pipecat.services.deepgram.stt import DeepgramSTTService from pipecat.services.openai.base_llm import OpenAILLMSettings @@ -63,7 +63,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): llm = AzureLLMService( api_key=os.getenv("AZURE_CHATGPT_API_KEY"), endpoint=os.getenv("AZURE_CHATGPT_ENDPOINT"), - model=os.getenv("AZURE_CHATGPT_MODEL"), + settings=AzureLLMSettings(model=os.getenv("AZURE_CHATGPT_MODEL")), system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", ) diff --git a/examples/foundational/55zp-update-settings-aws-bedrock-llm.py b/examples/foundational/55zp-update-settings-aws-bedrock-llm.py index c543ef50c..3d5d93b6a 100644 --- a/examples/foundational/55zp-update-settings-aws-bedrock-llm.py +++ b/examples/foundational/55zp-update-settings-aws-bedrock-llm.py @@ -61,8 +61,10 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): llm = AWSBedrockLLMService( aws_region="us-west-2", - model="us.anthropic.claude-haiku-4-5-20251001-v1:0", - params=AWSBedrockLLMService.InputParams(temperature=0.8), + settings=AWSBedrockLLMSettings( + model="us.anthropic.claude-haiku-4-5-20251001-v1:0", + temperature=0.8, + ), system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", ) diff --git a/examples/foundational/55zv-update-settings-asyncai-http-tts.py b/examples/foundational/55zv-update-settings-asyncai-http-tts.py index 79ca4382e..2063cda3a 100644 --- a/examples/foundational/55zv-update-settings-asyncai-http-tts.py +++ b/examples/foundational/55zv-update-settings-asyncai-http-tts.py @@ -59,7 +59,9 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): tts = AsyncAIHttpTTSService( api_key=os.getenv("ASYNCAI_API_KEY", ""), - voice_id=os.getenv("ASYNCAI_VOICE_ID", "e0f39dc4-f691-4e78-bba5-5c636692cc04"), + settings=AsyncAITTSSettings( + voice=os.getenv("ASYNCAI_VOICE_ID", "e0f39dc4-f691-4e78-bba5-5c636692cc04") + ), aiohttp_session=session, ) diff --git a/examples/foundational/55zv-update-settings-asyncai-tts.py b/examples/foundational/55zv-update-settings-asyncai-tts.py index 7e5463d2b..10cace018 100644 --- a/examples/foundational/55zv-update-settings-asyncai-tts.py +++ b/examples/foundational/55zv-update-settings-asyncai-tts.py @@ -55,7 +55,9 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): tts = AsyncAITTSService( api_key=os.getenv("ASYNCAI_API_KEY", ""), - voice_id=os.getenv("ASYNCAI_VOICE_ID", "e0f39dc4-f691-4e78-bba5-5c636692cc04"), + settings=AsyncAITTSSettings( + voice=os.getenv("ASYNCAI_VOICE_ID", "e0f39dc4-f691-4e78-bba5-5c636692cc04") + ), ) llm = OpenAILLMService( diff --git a/examples/foundational/55zw-update-settings-gradium-tts.py b/examples/foundational/55zw-update-settings-gradium-tts.py index e12d20dd2..5c33e090a 100644 --- a/examples/foundational/55zw-update-settings-gradium-tts.py +++ b/examples/foundational/55zw-update-settings-gradium-tts.py @@ -54,7 +54,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): tts = GradiumTTSService( api_key=os.getenv("GRADIUM_API_KEY"), - voice_id="YTpq7expH9539ERJ", + settings=GradiumTTSSettings(voice="YTpq7expH9539ERJ"), url="wss://us.api.gradium.ai/api/speech/tts", ) diff --git a/examples/foundational/55zz-update-settings-fireworks-llm.py b/examples/foundational/55zz-update-settings-fireworks-llm.py index 19b9276e6..56d29cfac 100644 --- a/examples/foundational/55zz-update-settings-fireworks-llm.py +++ b/examples/foundational/55zz-update-settings-fireworks-llm.py @@ -24,7 +24,7 @@ from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport from pipecat.services.cartesia.tts import CartesiaTTSService, CartesiaTTSSettings from pipecat.services.deepgram.stt import DeepgramSTTService -from pipecat.services.fireworks.llm import FireworksLLMService +from pipecat.services.fireworks.llm import FireworksLLMService, FireworksLLMSettings from pipecat.services.openai.base_llm import OpenAILLMSettings from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams @@ -62,7 +62,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): llm = FireworksLLMService( api_key=os.getenv("FIREWORKS_API_KEY"), - model="accounts/fireworks/models/gpt-oss-20b", + settings=FireworksLLMSettings(model="accounts/fireworks/models/gpt-oss-20b"), system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", ) diff --git a/examples/foundational/55zzb-update-settings-groq-llm.py b/examples/foundational/55zzb-update-settings-groq-llm.py index be5467b8a..35cec306f 100644 --- a/examples/foundational/55zzb-update-settings-groq-llm.py +++ b/examples/foundational/55zzb-update-settings-groq-llm.py @@ -24,7 +24,7 @@ from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport from pipecat.services.cartesia.tts import CartesiaTTSService, CartesiaTTSSettings from pipecat.services.deepgram.stt import DeepgramSTTService -from pipecat.services.groq.llm import GroqLLMService +from pipecat.services.groq.llm import GroqLLMService, GroqLLMSettings from pipecat.services.openai.base_llm import OpenAILLMSettings from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams @@ -62,7 +62,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): llm = GroqLLMService( api_key=os.getenv("GROQ_API_KEY"), - model="meta-llama/llama-4-maverick-17b-128e-instruct", + settings=GroqLLMSettings(model="meta-llama/llama-4-maverick-17b-128e-instruct"), system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", ) diff --git a/examples/foundational/55zzd-update-settings-nvidia-llm.py b/examples/foundational/55zzd-update-settings-nvidia-llm.py index 5e26e8213..68d168461 100644 --- a/examples/foundational/55zzd-update-settings-nvidia-llm.py +++ b/examples/foundational/55zzd-update-settings-nvidia-llm.py @@ -24,7 +24,7 @@ from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport from pipecat.services.cartesia.tts import CartesiaTTSService, CartesiaTTSSettings from pipecat.services.deepgram.stt import DeepgramSTTService -from pipecat.services.nvidia.llm import NvidiaLLMService +from pipecat.services.nvidia.llm import NvidiaLLMService, NvidiaLLMSettings from pipecat.services.openai.base_llm import OpenAILLMSettings from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams @@ -62,7 +62,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): llm = NvidiaLLMService( api_key=os.getenv("NVIDIA_API_KEY"), - model="meta/llama-3.1-405b-instruct", + settings=NvidiaLLMSettings(model="meta/llama-3.1-405b-instruct"), system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", ) diff --git a/examples/foundational/55zze-update-settings-ollama-llm.py b/examples/foundational/55zze-update-settings-ollama-llm.py index 7e3fa02de..8a3a5f973 100644 --- a/examples/foundational/55zze-update-settings-ollama-llm.py +++ b/examples/foundational/55zze-update-settings-ollama-llm.py @@ -24,7 +24,7 @@ from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport from pipecat.services.cartesia.tts import CartesiaTTSService, CartesiaTTSSettings from pipecat.services.deepgram.stt import DeepgramSTTService -from pipecat.services.ollama.llm import OLLamaLLMService +from pipecat.services.ollama.llm import OLLamaLLMService, OllamaLLMSettings from pipecat.services.openai.base_llm import OpenAILLMSettings from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams @@ -61,7 +61,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): ) llm = OLLamaLLMService( - model="llama3.2", + settings=OllamaLLMSettings(model="llama3.2"), system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", ) # Update to the model you're running locally diff --git a/examples/foundational/55zzh-update-settings-qwen-llm.py b/examples/foundational/55zzh-update-settings-qwen-llm.py index 5c6d17d1d..dd95308ec 100644 --- a/examples/foundational/55zzh-update-settings-qwen-llm.py +++ b/examples/foundational/55zzh-update-settings-qwen-llm.py @@ -25,7 +25,7 @@ from pipecat.runner.utils import create_transport from pipecat.services.cartesia.tts import CartesiaTTSService, CartesiaTTSSettings from pipecat.services.deepgram.stt import DeepgramSTTService from pipecat.services.openai.base_llm import OpenAILLMSettings -from pipecat.services.qwen.llm import QwenLLMService +from pipecat.services.qwen.llm import QwenLLMService, QwenLLMSettings from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams @@ -62,7 +62,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): llm = QwenLLMService( api_key=os.getenv("QWEN_API_KEY"), - model="qwen2.5-72b-instruct", + settings=QwenLLMSettings(model="qwen2.5-72b-instruct"), system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", ) diff --git a/examples/foundational/55zzj-update-settings-together-llm.py b/examples/foundational/55zzj-update-settings-together-llm.py index 4e1c9732f..c3cfafea2 100644 --- a/examples/foundational/55zzj-update-settings-together-llm.py +++ b/examples/foundational/55zzj-update-settings-together-llm.py @@ -25,7 +25,7 @@ from pipecat.runner.utils import create_transport from pipecat.services.cartesia.tts import CartesiaTTSService, CartesiaTTSSettings from pipecat.services.deepgram.stt import DeepgramSTTService from pipecat.services.openai.base_llm import OpenAILLMSettings -from pipecat.services.together.llm import TogetherLLMService +from pipecat.services.together.llm import TogetherLLMService, TogetherLLMSettings from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams @@ -62,7 +62,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): llm = TogetherLLMService( api_key=os.getenv("TOGETHER_API_KEY"), - model="meta-llama/Meta-Llama-3.1-70B-Instruct-Turbo", + settings=TogetherLLMSettings(model="meta-llama/Meta-Llama-3.1-70B-Instruct-Turbo"), system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", ) diff --git a/src/pipecat/services/azure/image.py b/src/pipecat/services/azure/image.py index 2a1286c78..28ac68bf9 100644 --- a/src/pipecat/services/azure/image.py +++ b/src/pipecat/services/azure/image.py @@ -12,7 +12,7 @@ using REST endpoints for creating images from text prompts. import asyncio import io -from dataclasses import dataclass +from dataclasses import dataclass, field from typing import AsyncGenerator, Optional import aiohttp @@ -20,7 +20,7 @@ from PIL import Image from pipecat.frames.frames import ErrorFrame, Frame, URLImageRawFrame from pipecat.services.image_service import ImageGenService -from pipecat.services.settings import ImageGenSettings, _warn_deprecated_param +from pipecat.services.settings import NOT_GIVEN, ImageGenSettings, _NotGiven, _warn_deprecated_param @dataclass @@ -29,8 +29,11 @@ class AzureImageGenSettings(ImageGenSettings): Parameters: model: Azure image generation model identifier. + image_size: Target size for generated images. """ + image_size: str | None | _NotGiven = field(default_factory=lambda: NOT_GIVEN) + class AzureImageGenServiceREST(ImageGenService): """Azure OpenAI REST-based image generation service. @@ -40,10 +43,12 @@ class AzureImageGenServiceREST(ImageGenService): and automatic image download and processing. """ + _settings: AzureImageGenSettings + def __init__( self, *, - image_size: str, + image_size: Optional[str] = None, api_key: str, endpoint: str, model: Optional[str] = None, @@ -55,6 +60,10 @@ class AzureImageGenServiceREST(ImageGenService): Args: image_size: Size specification for generated images (e.g., "1024x1024"). + + .. deprecated:: 0.0.105 + Use ``settings=AzureImageGenSettings(image_size=...)`` instead. + api_key: Azure OpenAI API key for authentication. endpoint: Azure OpenAI endpoint URL. model: The image generation model to use. @@ -67,10 +76,22 @@ class AzureImageGenServiceREST(ImageGenService): settings: Runtime-updatable settings. When provided alongside deprecated parameters, ``settings`` values take precedence. """ + # 1. Initialize default_settings with hardcoded defaults + default_settings = AzureImageGenSettings( + model=None, + image_size=None, + ) + + # 2. Apply direct init arg overrides (deprecated) if model is not None: _warn_deprecated_param("model", AzureImageGenSettings, "model") + default_settings.model = model - default_settings = AzureImageGenSettings(model=model) + if image_size is not None: + _warn_deprecated_param("image_size", AzureImageGenSettings, "image_size") + default_settings.image_size = image_size + + # 4. Apply settings delta (canonical API, always wins) if settings is not None: default_settings.apply_update(settings) @@ -79,7 +100,6 @@ class AzureImageGenServiceREST(ImageGenService): self._api_key = api_key self._azure_endpoint = endpoint self._api_version = api_version - self._image_size = image_size self._aiohttp_session = aiohttp_session async def run_image_gen(self, prompt: str) -> AsyncGenerator[Frame, None]: @@ -97,12 +117,13 @@ class AzureImageGenServiceREST(ImageGenService): headers = {"api-key": self._api_key, "Content-Type": "application/json"} body = { - # Enter your prompt text here "prompt": prompt, - "size": self._image_size, "n": 1, } + if self._settings.image_size is not None: + body["size"] = self._settings.image_size + async with self._aiohttp_session.post(url, headers=headers, json=body) as submission: # We never get past this line, because this header isn't # defined on a 429 response, but something is eating our diff --git a/src/pipecat/services/fal/image.py b/src/pipecat/services/fal/image.py index 342aaa4a9..c6fb81003 100644 --- a/src/pipecat/services/fal/image.py +++ b/src/pipecat/services/fal/image.py @@ -13,8 +13,8 @@ for creating images from text prompts using various AI models. import asyncio import io import os -from dataclasses import dataclass -from typing import AsyncGenerator, Dict, Optional, Union +from dataclasses import dataclass, field +from typing import Any, AsyncGenerator, Dict, Optional, Union import aiohttp from loguru import logger @@ -23,7 +23,7 @@ from pydantic import BaseModel from pipecat.frames.frames import ErrorFrame, Frame, URLImageRawFrame from pipecat.services.image_service import ImageGenService -from pipecat.services.settings import ImageGenSettings, _warn_deprecated_param +from pipecat.services.settings import NOT_GIVEN, ImageGenSettings, _NotGiven, _warn_deprecated_param @dataclass @@ -32,8 +32,36 @@ class FalImageGenSettings(ImageGenSettings): Parameters: model: Fal.ai model identifier. + seed: Random seed for reproducible generation. ``None`` uses a random seed. + num_inference_steps: Number of inference steps for generation. + num_images: Number of images to generate. + image_size: Image dimensions as a string preset or dict with width/height. + expand_prompt: Whether to automatically expand/enhance the prompt. + enable_safety_checker: Whether to enable content safety filtering. + format: Output image format. """ + seed: int | None | _NotGiven = field(default_factory=lambda: NOT_GIVEN) + num_inference_steps: int | _NotGiven = field(default_factory=lambda: NOT_GIVEN) + num_images: int | _NotGiven = field(default_factory=lambda: NOT_GIVEN) + image_size: str | Dict[str, int] | _NotGiven = field(default_factory=lambda: NOT_GIVEN) + expand_prompt: bool | _NotGiven = field(default_factory=lambda: NOT_GIVEN) + enable_safety_checker: bool | _NotGiven = field(default_factory=lambda: NOT_GIVEN) + format: str | _NotGiven = field(default_factory=lambda: NOT_GIVEN) + + def to_api_arguments(self) -> Dict[str, Any]: + """Build the Fal API arguments dict from settings, excluding None values.""" + args: Dict[str, Any] = {} + if self.seed is not None: + args["seed"] = self.seed + args["num_inference_steps"] = self.num_inference_steps + args["num_images"] = self.num_images + args["image_size"] = self.image_size + args["expand_prompt"] = self.expand_prompt + args["enable_safety_checker"] = self.enable_safety_checker + args["format"] = self.format + return args + class FalImageGenService(ImageGenService): """Fal's image generation service. @@ -45,6 +73,9 @@ class FalImageGenService(ImageGenService): class InputParams(BaseModel): """Input parameters for Fal.ai image generation. + .. deprecated:: 0.0.105 + Use ``settings=FalImageGenSettings(...)`` instead. + Parameters: seed: Random seed for reproducible generation. If None, uses random seed. num_inference_steps: Number of inference steps for generation. Defaults to 8. @@ -63,10 +94,12 @@ class FalImageGenService(ImageGenService): enable_safety_checker: bool = True format: str = "png" + _settings: FalImageGenSettings + def __init__( self, *, - params: InputParams, + params: Optional[InputParams] = None, aiohttp_session: aiohttp.ClientSession, model: Optional[str] = None, key: Optional[str] = None, @@ -77,6 +110,10 @@ class FalImageGenService(ImageGenService): Args: params: Input parameters for image generation configuration. + + .. deprecated:: 0.0.105 + Use ``settings=FalImageGenSettings(...)`` instead. + aiohttp_session: HTTP client session for downloading generated images. model: The Fal.ai model to use for generation. Defaults to "fal-ai/fast-sdxl". @@ -89,19 +126,38 @@ class FalImageGenService(ImageGenService): **kwargs: Additional arguments passed to parent ImageGenService. """ # 1. Initialize default_settings with hardcoded defaults - default_settings = FalImageGenSettings(model="fal-ai/fast-sdxl") + default_settings = FalImageGenSettings( + model="fal-ai/fast-sdxl", + seed=None, + num_inference_steps=8, + num_images=1, + image_size="square_hd", + expand_prompt=False, + enable_safety_checker=True, + format="png", + ) # 2. Apply direct init arg overrides (deprecated) if model is not None: _warn_deprecated_param("model", FalImageGenSettings, "model") default_settings.model = model + if params is not None: + _warn_deprecated_param("params", FalImageGenSettings) + if not settings: + default_settings.seed = params.seed + default_settings.num_inference_steps = params.num_inference_steps + default_settings.num_images = params.num_images + default_settings.image_size = params.image_size + default_settings.expand_prompt = params.expand_prompt + default_settings.enable_safety_checker = params.enable_safety_checker + default_settings.format = params.format + # 4. Apply settings delta (canonical API, always wins) if settings is not None: default_settings.apply_update(settings) super().__init__(settings=default_settings, **kwargs) - self._params = params self._aiohttp_session = aiohttp_session self._api_key = key or os.getenv("FAL_KEY", "") if key: @@ -129,7 +185,7 @@ class FalImageGenService(ImageGenService): "Authorization": f"Key {self._api_key}", "Content-Type": "application/json", } - payload = {"prompt": prompt, **self._params.model_dump(exclude_none=True)} + payload = {"prompt": prompt, **self._settings.to_api_arguments()} async with self._aiohttp_session.post( f"https://fal.run/{self._settings.model}", diff --git a/src/pipecat/services/google/image.py b/src/pipecat/services/google/image.py index d15d5d0ed..4c351cc6e 100644 --- a/src/pipecat/services/google/image.py +++ b/src/pipecat/services/google/image.py @@ -16,7 +16,7 @@ import os # Suppress gRPC fork warnings os.environ["GRPC_ENABLE_FORK_SUPPORT"] = "false" -from dataclasses import dataclass +from dataclasses import dataclass, field from typing import Any, AsyncGenerator, Optional from loguru import logger @@ -26,7 +26,7 @@ from pydantic import BaseModel, Field from pipecat.frames.frames import ErrorFrame, Frame, URLImageRawFrame from pipecat.services.google.utils import update_google_client_http_options from pipecat.services.image_service import ImageGenService -from pipecat.services.settings import ImageGenSettings, _warn_deprecated_param +from pipecat.services.settings import NOT_GIVEN, ImageGenSettings, _NotGiven, _warn_deprecated_param try: from google import genai @@ -43,8 +43,13 @@ class GoogleImageGenSettings(ImageGenSettings): Parameters: model: Google Imagen model identifier. + number_of_images: Number of images to generate per request. + negative_prompt: Text describing what not to include in generated images. """ + number_of_images: int | _NotGiven = field(default_factory=lambda: NOT_GIVEN) + negative_prompt: str | None | _NotGiven = field(default_factory=lambda: NOT_GIVEN) + class GoogleImageGenService(ImageGenService): """Google AI image generation service using Imagen models. @@ -57,6 +62,9 @@ class GoogleImageGenService(ImageGenService): class InputParams(BaseModel): """Configuration parameters for Google image generation. + .. deprecated:: 0.0.105 + Use ``settings=GoogleImageGenSettings(...)`` instead. + Parameters: number_of_images: Number of images to generate (1-8). Defaults to 1. model: Google Imagen model to use. Defaults to "imagen-3.0-generate-002". @@ -67,6 +75,8 @@ class GoogleImageGenService(ImageGenService): model: str = Field(default="imagen-3.0-generate-002") negative_prompt: Optional[str] = Field(default=None) + _settings: GoogleImageGenSettings + def __init__( self, *, @@ -83,7 +93,7 @@ class GoogleImageGenService(ImageGenService): params: Configuration parameters for image generation. .. deprecated:: 0.0.105 - Use ``settings=GoogleImageGenSettings(model=...)`` instead. + Use ``settings=GoogleImageGenSettings(...)`` instead. http_options: HTTP options for the client. settings: Runtime-updatable settings. When provided alongside deprecated @@ -91,20 +101,25 @@ class GoogleImageGenService(ImageGenService): **kwargs: Additional arguments passed to the parent ImageGenService. """ # 1. Initialize default_settings with hardcoded defaults - default_settings = GoogleImageGenSettings(model="imagen-3.0-generate-002") + default_settings = GoogleImageGenSettings( + model="imagen-3.0-generate-002", + number_of_images=1, + negative_prompt=None, + ) - # 3. Apply params overrides — only if settings not provided + # 2. Apply params overrides (deprecated) if params is not None: _warn_deprecated_param("params", GoogleImageGenSettings) if not settings: default_settings.model = params.model + default_settings.number_of_images = params.number_of_images + default_settings.negative_prompt = params.negative_prompt # 4. Apply settings delta (canonical API, always wins) if settings is not None: default_settings.apply_update(settings) super().__init__(settings=default_settings, **kwargs) - self._params = params or GoogleImageGenService.InputParams() # Add client header http_options = update_google_client_http_options(http_options) @@ -137,11 +152,11 @@ class GoogleImageGenService(ImageGenService): try: response = await self._client.aio.models.generate_images( - model=self._params.model, + model=self._settings.model, prompt=prompt, config=types.GenerateImagesConfig( - number_of_images=self._params.number_of_images, - negative_prompt=self._params.negative_prompt, + number_of_images=self._settings.number_of_images, + negative_prompt=self._settings.negative_prompt, ), ) await self.stop_ttfb_metrics() diff --git a/src/pipecat/services/heygen/video.py b/src/pipecat/services/heygen/video.py index 020ecdfcf..18df8ac60 100644 --- a/src/pipecat/services/heygen/video.py +++ b/src/pipecat/services/heygen/video.py @@ -12,6 +12,7 @@ audio/video streaming capabilities through the HeyGen API. """ import asyncio +from dataclasses import dataclass from typing import Optional, Union import aiohttp @@ -52,6 +53,13 @@ from pipecat.transports.base_transport import TransportParams AVATAR_VAD_STOP_SECS = 0.35 +@dataclass +class HeyGenVideoSettings(ServiceSettings): + """Settings for the HeyGen video service.""" + + pass + + class HeyGenVideoService(AIService): """A service that integrates HeyGen's interactive avatar capabilities into the pipeline. @@ -81,7 +89,7 @@ class HeyGenVideoService(AIService): session: aiohttp.ClientSession, session_request: Optional[Union[LiveAvatarNewSessionRequest, NewSessionRequest]] = None, service_type: Optional[ServiceType] = None, - settings: Optional[ServiceSettings] = None, + settings: Optional[HeyGenVideoSettings] = None, **kwargs, ) -> None: """Initialize the HeyGen video service. diff --git a/src/pipecat/services/openai/image.py b/src/pipecat/services/openai/image.py index 4120db8c6..397d8c3d2 100644 --- a/src/pipecat/services/openai/image.py +++ b/src/pipecat/services/openai/image.py @@ -11,7 +11,7 @@ for creating images from text prompts. """ import io -from dataclasses import dataclass +from dataclasses import dataclass, field from typing import AsyncGenerator, Literal, Optional import aiohttp @@ -25,7 +25,7 @@ from pipecat.frames.frames import ( URLImageRawFrame, ) from pipecat.services.image_service import ImageGenService -from pipecat.services.settings import ImageGenSettings, _warn_deprecated_param +from pipecat.services.settings import NOT_GIVEN, ImageGenSettings, _NotGiven, _warn_deprecated_param @dataclass @@ -34,8 +34,11 @@ class OpenAIImageGenSettings(ImageGenSettings): Parameters: model: DALL-E model identifier. + image_size: Target size for generated images. """ + image_size: str | None | _NotGiven = field(default_factory=lambda: NOT_GIVEN) + class OpenAIImageGenService(ImageGenService): """OpenAI DALL-E image generation service. @@ -45,13 +48,17 @@ class OpenAIImageGenService(ImageGenService): with configurable quality and style parameters. """ + _settings: OpenAIImageGenSettings + def __init__( self, *, api_key: str, base_url: Optional[str] = None, aiohttp_session: aiohttp.ClientSession, - image_size: Literal["256x256", "512x512", "1024x1024", "1792x1024", "1024x1792"], + image_size: Optional[ + Literal["256x256", "512x512", "1024x1024", "1792x1024", "1024x1792"] + ] = None, model: Optional[str] = None, settings: Optional[OpenAIImageGenSettings] = None, ): @@ -61,7 +68,11 @@ class OpenAIImageGenService(ImageGenService): api_key: OpenAI API key for authentication. base_url: Custom base URL for OpenAI API. If None, uses default. aiohttp_session: HTTP session for downloading generated images. - image_size: Target size for generated images. + image_size: Target size for generated images. Defaults to "1024x1024". + + .. deprecated:: 0.0.105 + Use ``settings=OpenAIImageGenSettings(image_size=...)`` instead. + model: DALL-E model to use for generation. Defaults to "dall-e-3". .. deprecated:: 0.0.105 @@ -71,19 +82,25 @@ class OpenAIImageGenService(ImageGenService): parameters, ``settings`` values take precedence. """ # 1. Initialize default_settings with hardcoded defaults - default_settings = OpenAIImageGenSettings(model="dall-e-3") + default_settings = OpenAIImageGenSettings( + model="dall-e-3", + image_size=None, + ) # 2. Apply direct init arg overrides (deprecated) if model is not None: _warn_deprecated_param("model", OpenAIImageGenSettings, "model") default_settings.model = model + if image_size is not None: + _warn_deprecated_param("image_size", OpenAIImageGenSettings, "image_size") + default_settings.image_size = image_size + # 4. Apply settings delta (canonical API, always wins) if settings is not None: default_settings.apply_update(settings) super().__init__(settings=default_settings) - self._image_size = image_size self._client = AsyncOpenAI(api_key=api_key, base_url=base_url) self._aiohttp_session = aiohttp_session @@ -99,7 +116,7 @@ class OpenAIImageGenService(ImageGenService): logger.debug(f"Generating image from prompt: {prompt}") image = await self._client.images.generate( - prompt=prompt, model=self._settings.model, n=1, size=self._image_size + prompt=prompt, model=self._settings.model, n=1, size=self._settings.image_size ) image_url = image.data[0].url diff --git a/src/pipecat/services/tavus/video.py b/src/pipecat/services/tavus/video.py index e6725fac1..4a7211033 100644 --- a/src/pipecat/services/tavus/video.py +++ b/src/pipecat/services/tavus/video.py @@ -11,6 +11,7 @@ avatar functionality through Tavus's streaming API. """ import asyncio +from dataclasses import dataclass from typing import Optional import aiohttp @@ -38,6 +39,13 @@ from pipecat.services.settings import ServiceSettings from pipecat.transports.tavus.transport import TavusCallbacks, TavusParams, TavusTransportClient +@dataclass +class TavusVideoSettings(ServiceSettings): + """Settings for the Tavus video service.""" + + pass + + class TavusVideoService(AIService): """Service that proxies audio to Tavus and receives audio and video in return. @@ -58,7 +66,7 @@ class TavusVideoService(AIService): replica_id: str, persona_id: str = "pipecat-stream", session: aiohttp.ClientSession, - settings: Optional[ServiceSettings] = None, + settings: Optional[TavusVideoSettings] = None, **kwargs, ) -> None: """Initialize the Tavus video service. From ab371852084b47ff540623383324286cb496733a Mon Sep 17 00:00:00 2001 From: Mark Backman Date: Fri, 6 Mar 2026 08:32:59 -0500 Subject: [PATCH 0816/1060] Update run_eval_pipeline with the latest settings, system_instruction patterns --- scripts/evals/eval.py | 59 ++++++++++++++++++++----------------------- 1 file changed, 27 insertions(+), 32 deletions(-) diff --git a/scripts/evals/eval.py b/scripts/evals/eval.py index d45e6343b..c2316e123 100644 --- a/scripts/evals/eval.py +++ b/scripts/evals/eval.py @@ -49,7 +49,7 @@ from pipecat.processors.audio.audio_buffer_processor import AudioBufferProcessor from pipecat.processors.frame_processor import FrameDirection from pipecat.runner.types import RunnerArguments from pipecat.services.cartesia.tts import CartesiaTTSService, CartesiaTTSSettings -from pipecat.services.deepgram.stt import DeepgramSTTService, LiveOptions +from pipecat.services.deepgram.stt import DeepgramSTTService, DeepgramSTTSettings from pipecat.services.llm_service import FunctionCallParams from pipecat.services.openai.llm import OpenAILLMService from pipecat.transports.daily.transport import DailyParams, DailyTransport @@ -243,7 +243,7 @@ async def run_eval_pipeline( # 5" (in audio) this can be converted to "32 is 5". stt = DeepgramSTTService( api_key=os.getenv("DEEPGRAM_API_KEY"), - live_options=LiveOptions( + settings=DeepgramSTTSettings( language="multi", smart_format=False, ), @@ -251,10 +251,32 @@ async def run_eval_pipeline( tts = CartesiaTTSService( api_key=os.getenv("CARTESIA_API_KEY"), - voice_id="97f4b8fb-f2fe-444b-bb9a-c109783a857a", # Nathan + settings=CartesiaTTSSettings( + voice="97f4b8fb-f2fe-444b-bb9a-c109783a857a", # Nathan + ), ) - llm = OpenAILLMService(api_key=os.getenv("OPENAI_API_KEY")) + # Load example prompt depending on image. + example_prompt = "" + example_image: Optional[ImageFile] = None + if isinstance(eval_config.prompt, str): + example_prompt = eval_config.prompt + elif isinstance(eval_config.prompt, tuple): + example_prompt, example_image = eval_config.prompt + + common_system_prompt = ( + "You should only call the eval function if:\n" + "- The user explicitly attempts to answer the question, AND\n" + f"- Their answer can be cleanly evaluated using: {eval_config.eval}\n" + "Ignore greetings, comments, non-answers, or requests for clarification.\n" + "Numerical word answers are allowed (e.g., 'five' is the same as '5').\n" + ) + if eval_config.eval_speaks_first: + system_prompt = f"You are an evaluation agent, be extremly brief. You will start the conversation by saying: '{example_prompt}'. {common_system_prompt}" + else: + system_prompt = f"You are an evaluation agent, be extremly brief. First, ask one question: {example_prompt}. {common_system_prompt}" + + llm = OpenAILLMService(api_key=os.getenv("OPENAI_API_KEY"), system_instruction=system_prompt) llm.register_function("eval_function", eval_runner.function_assert_eval) @@ -281,34 +303,7 @@ async def run_eval_pipeline( ) tools = ToolsSchema(standard_tools=[eval_function]) - # Load example prompt depending on image. - example_prompt = "" - example_image: Optional[ImageFile] = None - if isinstance(eval_config.prompt, str): - example_prompt = eval_config.prompt - elif isinstance(eval_config.prompt, tuple): - example_prompt, example_image = eval_config.prompt - - common_system_prompt = ( - "You should only call the eval function if:\n" - "- The user explicitly attempts to answer the question, AND\n" - f"- Their answer can be cleanly evaluated using: {eval_config.eval}\n" - "Ignore greetings, comments, non-answers, or requests for clarification.\n" - "Numerical word answers are allowed (e.g., 'five' is the same as '5').\n" - ) - if eval_config.eval_speaks_first: - system_prompt = f"You are an evaluation agent, be extremly brief. You will start the conversation by saying: '{example_prompt}'. {common_system_prompt}" - else: - system_prompt = f"You are an evaluation agent, be extremly brief. First, ask one question: {example_prompt}. {common_system_prompt}" - - messages = [ - { - "role": "system", - "content": system_prompt, - }, - ] - - context = LLMContext(messages, tools) + context = LLMContext(tools=tools) context_aggregator = LLMContextAggregatorPair( context, user_params=LLMUserAggregatorParams( From ee2895a783a8d07bad8637939a37d88be51dd366 Mon Sep 17 00:00:00 2001 From: Mark Backman Date: Fri, 6 Mar 2026 08:44:15 -0500 Subject: [PATCH 0817/1060] Update COMMUNITY_INTEGRATIONS.md with full Service Settings guidance Broaden the "Dynamic Settings Updates" section into "Service Settings" covering the complete settings pattern: defining a Settings subclass, wiring it into __init__ with defaults + apply_update, and distinguishing init-only config from runtime-updatable fields. --- COMMUNITY_INTEGRATIONS.md | 95 ++++++++++++++++++++++++++++++--------- 1 file changed, 74 insertions(+), 21 deletions(-) diff --git a/COMMUNITY_INTEGRATIONS.md b/COMMUNITY_INTEGRATIONS.md index ff8d08ea5..5dd9e5764 100644 --- a/COMMUNITY_INTEGRATIONS.md +++ b/COMMUNITY_INTEGRATIONS.md @@ -231,49 +231,102 @@ def can_generate_metrics(self) -> bool: return True ``` -### Dynamic Settings Updates +### Service Settings -STT, LLM, and TTS services support runtime configuration changes via `*UpdateSettingsFrame`s (e.g. `STTUpdateSettingsFrame`, `TTSUpdateSettingsFrame`, `LLMUpdateSettingsFrame`). +Every STT, LLM, TTS, and image-generation service exposes a **Settings dataclass** that serves two roles: -Each service declares a settings dataclass that extends the appropriate base (`STTSettings`, `TTSSettings`, `LLMSettings`). Fields default to `NOT_GIVEN` so that update objects can represent sparse deltas: +1. **Store mode** — the service's `self._settings` holds the current value of every runtime-updatable field. +2. **Delta mode** — an update frame carries only the fields that changed; unset fields remain `NOT_GIVEN`. + +#### Defining your Settings class + +Extend `STTSettings`, `TTSSettings`, `LLMSettings`, or `ImageGenSettings`. The base classes already provide common fields (e.g. `model`, `voice`, `language`). You only need to add **service-specific knobs that should be runtime-updatable**: ```python from dataclasses import dataclass, field -from pipecat.services.settings import STTSettings, NOT_GIVEN +from pipecat.services.settings import TTSSettings, NOT_GIVEN @dataclass -class MySTTSettings(STTSettings): - """Settings for my STT service. +class MyTTSSettings(TTSSettings): + """Settings for MyTTS service. Parameters: - region: Cloud region for the service. + speaking_rate: Speed multiplier (0.5–2.0). """ - region: str = field(default_factory=lambda: NOT_GIVEN) + speaking_rate: float | None = field(default_factory=lambda: NOT_GIVEN) ``` -The service stores its current settings in `self._settings` and declares the type with a class-level annotation for editor support: +**What goes in Settings vs. `__init__` params:** + +| Belongs in Settings | Stays as `__init__` params | +| -------------------------------------------------------- | ----------------------------------------- | +| Model name, voice, language | API keys, auth tokens | +| Service-specific tuning knobs (rate, pitch, temperature) | Base URLs, endpoint overrides | +| Anything users may want to change mid-session | Audio encoding, sample format | +| | Connection parameters (timeouts, retries) | + +The rule of thumb: if a caller might send an update frame to change it at runtime, it belongs in Settings. Everything else is init-only config stored as `self._xxx`. + +#### Wiring settings into `__init__` + +Accept an **optional** `settings` parameter. Build a `default_settings` object with all fields set to real values, then merge any caller overrides with `apply_update`: ```python -class MySTTService(STTService): - _settings: MySTTSettings +from typing import Optional - def __init__(self, *, model: str, language: str, region: str, **kwargs): - # An initial value should be provided for every settings field. - # This will be validated at service start. - # (If you track sample_rate, it can be a placeholder value like 0; see - # "Sample Rate Handling"). - super().__init__( - settings=MySTTSettings(model=model, language=language, region=region), **kwargs +class MyTTSService(TTSService): + _settings: MyTTSSettings + + def __init__( + self, + *, + api_key: str, + settings: Optional[MyTTSSettings] = None, + **kwargs, + ): + # 1. Defaults — every field has a real value (store mode). + default_settings = MyTTSSettings( + model="my-model-v1", + voice="default-voice", + language="en", + speaking_rate=1.0, ) + + # 2. Merge caller overrides (only given fields win). + if settings is not None: + default_settings.apply_update(settings) + + # 3. Pass the fully-populated settings to the base class. + super().__init__(settings=default_settings, **kwargs) + + # 4. Init-only config stored separately. + self._api_key = api_key ``` +This pattern lets callers override only what they care about: + +```python +# Uses all defaults +svc = MyTTSService(api_key="sk-xxx") + +# Overrides just the voice +svc = MyTTSService( + api_key="sk-xxx", + settings=MyTTSSettings(voice="custom-voice"), +) +``` + +#### Reacting to runtime changes + +STT, LLM, and TTS services support runtime configuration changes via `*UpdateSettingsFrame`s (e.g. `STTUpdateSettingsFrame`, `TTSUpdateSettingsFrame`, `LLMUpdateSettingsFrame`). + To react to runtime setting changes, override `_update_settings`. The base implementation applies the delta to `self._settings` and returns a `dict` mapping each changed field name to its **pre-update** value. Your override should call `super()` first, then act on the changed fields. A common implementation might look like: ```python -async def _update_settings(self, update: STTSettings) -> dict[str, Any]: - """Apply a settings update, reconfiguring the recognizer if needed.""" +async def _update_settings(self, update: TTSSettings) -> dict[str, Any]: + """Apply a settings update, reconfiguring the connection if needed.""" changed = await super()._update_settings(update) if not changed: @@ -292,7 +345,7 @@ Note that, in this example, the service requires a reconnect to apply the new la If your service can't yet apply certain settings at runtime, call `self._warn_unhandled_updated_settings(changed)` with any unhandled field names so users get a clear log message: ```python -async def _update_settings(self, update: STTSettings) -> dict[str, Any]: +async def _update_settings(self, update: TTSSettings) -> dict[str, Any]: changed = await super()._update_settings(update) if not changed: From 4ef3b52c722fafae1d8540583bfd0b6b8fdccca3 Mon Sep 17 00:00:00 2001 From: filipi87 Date: Fri, 6 Mar 2026 11:40:27 -0300 Subject: [PATCH 0818/1060] Fix context summarization leaving orphaned tool responses in kept context. --- .../context/llm_context_summarization.py | 22 ++- tests/test_context_summarization.py | 150 +++++++++++++++++- 2 files changed, 164 insertions(+), 8 deletions(-) diff --git a/src/pipecat/utils/context/llm_context_summarization.py b/src/pipecat/utils/context/llm_context_summarization.py index 707d0c32d..f7536cbaf 100644 --- a/src/pipecat/utils/context/llm_context_summarization.py +++ b/src/pipecat/utils/context/llm_context_summarization.py @@ -382,25 +382,33 @@ class LLMContextSummarizationUtil: return total @staticmethod - def _get_function_calls_in_progress_index(messages: List[dict], start_idx: int) -> int: + def _get_function_calls_in_progress_index( + messages: List[dict], start_idx: int, summary_end: int + ) -> int: """Find the earliest message index with incomplete function calls. - Scans messages to identify function/tool calls that haven't received - their results yet. This prevents summarizing incomplete tool interactions - which would break the request-response pairing. + Scans messages from ``start_idx`` up to (but not including) + ``summary_end`` to identify tool calls whose responses either don't + exist yet or fall in the kept portion of the context (>= summary_end). + This prevents summarizing tool call requests when their responses would + remain in the kept context as orphans, which the OpenAI API rejects. Args: messages: List of messages to check. start_idx: Index to start checking from. + summary_end: Exclusive upper bound for the scan (the first kept + message index). Only tool responses within this range count as + completing a call; responses beyond it are treated as absent, + leaving the call "in progress". Returns: Index of first message with function call in progress, or -1 if all - function calls are complete. + function calls are complete within the scanned range. """ # Track tool call IDs mapped to their message index pending_tool_calls: dict[str, int] = {} - for i in range(start_idx, len(messages)): + for i in range(start_idx, summary_end): msg = messages[i] # LLMSpecificMessage instances (e.g. thinking blocks) never carry tool_call or # tool_call_id fields, so they cannot affect the pending-call tracking. Skipping @@ -484,7 +492,7 @@ class LLMContextSummarizationUtil: # Check for function calls in progress in the range we want to summarize function_call_start = LLMContextSummarizationUtil._get_function_calls_in_progress_index( - messages, summary_start + messages, summary_start, summary_end ) if function_call_start >= 0 and function_call_start < summary_end: # Stop summarization before the function call diff --git a/tests/test_context_summarization.py b/tests/test_context_summarization.py index e2666e7fa..454535bc0 100644 --- a/tests/test_context_summarization.py +++ b/tests/test_context_summarization.py @@ -954,6 +954,152 @@ class TestDedicatedLLMSummarization(unittest.IsolatedAsyncioTestCase): await summarizer.cleanup() +class TestOrphanedToolResponseDetection(unittest.TestCase): + """Tests that tool responses in the kept range are treated as orphans. + + The scan in _get_function_calls_in_progress_index is bounded by summary_end, + so a tool response that falls in the kept portion (>= summary_end) never + resolves its matching tool call. This ensures the assistant+tool_calls + message and all its responses stay together in the kept range. + """ + + def test_tool_response_in_kept_range_is_treated_as_orphan(self): + """Tool response in the kept range causes the tool call to be kept too.""" + context = LLMContext() + context.add_message({"role": "system", "content": "System prompt"}) # idx 0 + context.add_message({"role": "user", "content": "Hello"}) # idx 1 + context.add_message( # idx 2: assistant with tool_call + { + "role": "assistant", + "content": "", + "tool_calls": [ + { + "id": "call_1", + "type": "function", + "function": {"name": "fn", "arguments": "{}"}, + } + ], + } + ) + context.add_message( + {"role": "tool", "tool_call_id": "call_1", "content": "result"} + ) # idx 3 (kept) + context.add_message({"role": "user", "content": "Thanks"}) # idx 4 (kept) + + # Keep 2: summary_end=3. The tool response at idx 3 is outside the scan + # range → call_1 stays pending → boundary moves back to idx 2. + result = LLMContextSummarizationUtil.get_messages_to_summarize(context, 2) + self.assertEqual(result.last_summarized_index, 1) + self.assertEqual(result.messages[-1]["content"], "Hello") + + def test_tool_response_in_summarized_range_is_not_orphan(self): + """Tool response within the summarized range correctly resolves its call.""" + context = LLMContext() + context.add_message({"role": "system", "content": "System prompt"}) # idx 0 + context.add_message({"role": "user", "content": "Hello"}) # idx 1 + context.add_message( # idx 2: assistant with tool_call + { + "role": "assistant", + "content": "", + "tool_calls": [ + { + "id": "call_1", + "type": "function", + "function": {"name": "fn", "arguments": "{}"}, + } + ], + } + ) + context.add_message( + {"role": "tool", "tool_call_id": "call_1", "content": "result"} + ) # idx 3 + context.add_message({"role": "assistant", "content": "Done"}) # idx 4 + context.add_message({"role": "user", "content": "Thanks"}) # idx 5 (kept) + + # Keep 1: summary_end=5. Both the tool call (idx 2) and its response + # (idx 3) are within the scan range → resolved → no adjustment. + result = LLMContextSummarizationUtil.get_messages_to_summarize(context, 1) + self.assertEqual(result.last_summarized_index, 4) + self.assertEqual(len(result.messages), 4) + + def test_partial_responses_in_kept_range_moves_back(self): + """When only some tool responses are in the kept range the whole group is kept.""" + context = LLMContext() + context.add_message({"role": "system", "content": "System prompt"}) # idx 0 + context.add_message({"role": "user", "content": "Hello"}) # idx 1 + context.add_message( # idx 2: assistant with two tool_calls + { + "role": "assistant", + "content": "", + "tool_calls": [ + { + "id": "call_a", + "type": "function", + "function": {"name": "fn_a", "arguments": "{}"}, + }, + { + "id": "call_b", + "type": "function", + "function": {"name": "fn_b", "arguments": "{}"}, + }, + ], + } + ) + context.add_message( + {"role": "tool", "tool_call_id": "call_a", "content": "result_a"} + ) # idx 3 + context.add_message( + {"role": "tool", "tool_call_id": "call_b", "content": "result_b"} + ) # idx 4 (kept) + context.add_message({"role": "user", "content": "Thanks"}) # idx 5 (kept) + + # Keep 2: summary_end=4. call_a is resolved (idx 3 is in scan range) but + # call_b's response (idx 4) is outside → call_b stays pending → + # function_call_start=2 → boundary moves back to idx 2. + result = LLMContextSummarizationUtil.get_messages_to_summarize(context, 2) + self.assertEqual(result.last_summarized_index, 1) + self.assertEqual(result.messages[-1]["content"], "Hello") + + def test_non_adjacent_orphan_in_kept_range_moves_back(self): + """Orphaned tool response deeper in the kept range (not at the boundary) is detected.""" + context = LLMContext() + context.add_message({"role": "system", "content": "System prompt"}) # idx 0 + context.add_message({"role": "user", "content": "Hello"}) # idx 1 + context.add_message( # idx 2: assistant with two tool_calls + { + "role": "assistant", + "content": "", + "tool_calls": [ + { + "id": "call_a", + "type": "function", + "function": {"name": "fn_a", "arguments": "{}"}, + }, + { + "id": "call_b", + "type": "function", + "function": {"name": "fn_b", "arguments": "{}"}, + }, + ], + } + ) + context.add_message( + {"role": "tool", "tool_call_id": "call_a", "content": "result_a"} + ) # idx 3 + context.add_message({"role": "user", "content": "Intermediate"}) # idx 4 (kept) + context.add_message( + {"role": "tool", "tool_call_id": "call_b", "content": "result_b"} + ) # idx 5 (kept) — NOT adjacent to the boundary + context.add_message({"role": "user", "content": "Latest"}) # idx 6 (kept) + + # Keep 3: summary_end=4. call_b's response is at idx 5, two hops into + # the kept range. The scan stops at idx 4, so call_b is never resolved → + # function_call_start=2 → boundary moves back to idx 2. + result = LLMContextSummarizationUtil.get_messages_to_summarize(context, 3) + self.assertEqual(result.last_summarized_index, 1) + self.assertEqual(result.messages[-1]["content"], "Hello") + + class TestLLMSpecificMessageHandling(unittest.TestCase): """Tests that LLMSpecificMessage objects are correctly skipped in summarization.""" @@ -1022,7 +1168,9 @@ class TestLLMSpecificMessageHandling(unittest.TestCase): {"role": "tool", "tool_call_id": "call_123", "content": '{"time": "10:30 AM"}'}, ] - result = LLMContextSummarizationUtil._get_function_calls_in_progress_index(messages, 0) + result = LLMContextSummarizationUtil._get_function_calls_in_progress_index( + messages, 0, len(messages) + ) self.assertEqual(result, -1) From 524b87f087f039f396050abcdfcc9aba5d269b9d Mon Sep 17 00:00:00 2001 From: filipi87 Date: Fri, 6 Mar 2026 11:45:20 -0300 Subject: [PATCH 0819/1060] Adding changelog entry for the summarization fix. --- changelog/3937.fixed.md | 1 + 1 file changed, 1 insertion(+) create mode 100644 changelog/3937.fixed.md diff --git a/changelog/3937.fixed.md b/changelog/3937.fixed.md new file mode 100644 index 000000000..eda9d27f6 --- /dev/null +++ b/changelog/3937.fixed.md @@ -0,0 +1 @@ +- Fixed context summarization leaving orphaned tool responses in the kept context when tool calls were moved to the summarized portion. From 78deaa735d69e08a07b1385651b6de6367757dd1 Mon Sep 17 00:00:00 2001 From: Paul Kompfner Date: Thu, 5 Mar 2026 14:03:32 -0500 Subject: [PATCH 0820/1060] Move `system_instruction` into `LLMSettings` Add `system_instruction` field to `LLMSettings` so it is runtime-updatable via settings. For Google (GoogleLLMService, GoogleVertexLLMService), deprecate the init-time arg since it was already shipped. For Anthropic, AWS Bedrock, and OpenAI, remove the init-time arg entirely since it was never shipped. Still need to handle realtime services (OpenAI Realtime, Grok Realtime, Gemini Live). --- examples/foundational/02-llm-say-one-thing.py | 6 ++++-- .../foundational/04-transports-small-webrtc.py | 6 ++++-- examples/foundational/04a-transports-daily.py | 2 +- examples/foundational/04b-transports-livekit.py | 6 ++++-- examples/foundational/06-listen-and-respond.py | 6 ++++-- examples/foundational/06a-image-sync.py | 6 ++++-- .../07-interruptible-cartesia-http.py | 6 ++++-- examples/foundational/07-interruptible.py | 6 ++++-- .../07a-interruptible-speechmatics-vad.py | 2 +- .../07a-interruptible-speechmatics.py | 2 +- .../07c-interruptible-deepgram-flux.py | 6 ++++-- .../07c-interruptible-deepgram-http.py | 6 ++++-- .../07c-interruptible-deepgram-sagemaker.py | 2 +- .../07c-interruptible-deepgram-vad.py | 6 ++++-- .../foundational/07c-interruptible-deepgram.py | 6 ++++-- .../07d-interruptible-elevenlabs-http.py | 6 ++++-- .../foundational/07d-interruptible-elevenlabs.py | 6 ++++-- .../foundational/07f-interruptible-azure-http.py | 6 ++++-- examples/foundational/07f-interruptible-azure.py | 6 ++++-- .../07g-interruptible-openai-http.py | 6 ++++-- .../foundational/07g-interruptible-openai.py | 6 ++++-- .../foundational/07h-interruptible-openpipe.py | 6 ++++-- examples/foundational/07i-interruptible-xtts.py | 6 ++++-- .../foundational/07j-interruptible-gladia-vad.py | 6 ++++-- .../foundational/07j-interruptible-gladia.py | 6 ++++-- examples/foundational/07k-interruptible-lmnt.py | 6 ++++-- examples/foundational/07l-interruptible-groq.py | 2 +- examples/foundational/07m-interruptible-aws.py | 6 ++++-- .../07n-interruptible-gemini-image.py | 2 +- .../foundational/07n-interruptible-gemini.py | 6 ++++-- .../07n-interruptible-google-http.py | 2 +- .../foundational/07n-interruptible-google.py | 2 +- ...7o-interruptible-assemblyai-turn-detection.py | 6 ++++-- .../foundational/07o-interruptible-assemblyai.py | 6 ++++-- .../foundational/07p-interruptible-krisp-viva.py | 6 ++++-- examples/foundational/07p-interruptible-krisp.py | 6 ++++-- .../foundational/07q-interruptible-rime-http.py | 6 ++++-- examples/foundational/07q-interruptible-rime.py | 6 ++++-- .../foundational/07r-interruptible-nvidia.py | 2 +- examples/foundational/07t-interruptible-fish.py | 6 ++++-- .../07v-interruptible-neuphonic-http.py | 6 ++++-- .../foundational/07v-interruptible-neuphonic.py | 6 ++++-- examples/foundational/07w-interruptible-fal.py | 6 ++++-- examples/foundational/07x-interruptible-local.py | 6 ++++-- .../foundational/07y-interruptible-minimax.py | 6 ++++-- .../07z-interruptible-sarvam-http.py | 6 ++++-- .../foundational/07z-interruptible-sarvam.py | 6 ++++-- .../foundational/07za-interruptible-soniox.py | 6 ++++-- .../07zb-interruptible-inworld-http.py | 6 ++++-- .../foundational/07zb-interruptible-inworld.py | 6 ++++-- .../07zc-interruptible-asyncai-http.py | 6 ++++-- .../foundational/07zc-interruptible-asyncai.py | 6 ++++-- .../07zd-interruptible-aicoustics.py | 6 ++++-- examples/foundational/07ze-interruptible-hume.py | 6 ++++-- .../foundational/07zf-interruptible-gradium.py | 6 ++++-- examples/foundational/07zg-interruptible-camb.py | 6 ++++-- .../foundational/07zi-interruptible-piper.py | 6 ++++-- .../foundational/07zj-interruptible-kokoro.py | 6 ++++-- .../foundational/07zk-interruptible-resemble.py | 6 ++++-- .../foundational/08-custom-frame-processor.py | 6 ++++-- examples/foundational/10-wake-phrase.py | 6 ++++-- examples/foundational/11-sound-effects.py | 6 ++++-- .../foundational/12-describe-image-openai.py | 6 ++++-- .../foundational/12a-describe-image-anthropic.py | 6 ++++-- examples/foundational/12b-describe-image-aws.py | 2 +- .../12c-describe-image-gemini-flash.py | 6 ++++-- examples/foundational/14-function-calling.py | 6 ++++-- .../14a-function-calling-anthropic.py | 6 ++++-- .../14c-function-calling-together.py | 2 +- .../14d-function-calling-anthropic-video.py | 6 ++++-- .../14d-function-calling-aws-video.py | 2 +- .../14d-function-calling-gemini-flash-video.py | 6 ++++-- .../14d-function-calling-moondream-video.py | 6 ++++-- .../14d-function-calling-openai-video.py | 6 ++++-- .../foundational/14e-function-calling-google.py | 6 ++++-- .../foundational/14f-function-calling-groq.py | 6 ++++-- .../foundational/14g-function-calling-grok.py | 6 ++++-- .../foundational/14h-function-calling-azure.py | 2 +- .../14i-function-calling-fireworks.py | 2 +- .../foundational/14j-function-calling-nvidia.py | 2 +- .../14k-function-calling-cerebras.py | 6 ++++-- .../14l-function-calling-deepseek.py | 4 ++-- .../14m-function-calling-openrouter.py | 2 +- .../14n-function-calling-perplexity.py | 7 +++++-- .../14o-function-calling-gemini-openai-format.py | 6 ++++-- .../14p-function-calling-gemini-vertex-ai.py | 6 ++++-- .../foundational/14q-function-calling-qwen.py | 6 ++++-- .../foundational/14r-function-calling-aws.py | 2 +- .../14s-function-calling-sambanova.py | 6 ++++-- .../foundational/14t-function-calling-direct.py | 6 ++++-- .../foundational/14u-function-calling-ollama.py | 2 +- .../foundational/14v-function-calling-openai.py | 6 ++++-- .../foundational/14w-function-calling-mistral.py | 6 ++++-- .../14x-function-calling-openpipe.py | 6 ++++-- examples/foundational/15-switch-voices.py | 6 ++++-- examples/foundational/15a-switch-languages.py | 6 ++++-- .../foundational/16-gpu-container-local-bot.py | 2 +- examples/foundational/17-detect-user-idle.py | 6 ++++-- examples/foundational/21-tavus-transport.py | 6 ++++-- examples/foundational/21a-tavus-video-service.py | 6 ++++-- .../foundational/22-filter-incomplete-turns.py | 6 ++++-- examples/foundational/23-bot-background-sound.py | 6 ++++-- examples/foundational/24-user-mute-strategy.py | 6 ++++-- examples/foundational/25-google-audio-in.py | 4 ++-- examples/foundational/27-simli-layer.py | 2 +- examples/foundational/28-user-assistant-turns.py | 6 ++++-- .../foundational/29-turn-tracking-observer.py | 6 ++++-- examples/foundational/30-observer.py | 6 ++++-- .../foundational/32-gemini-grounding-metadata.py | 6 ++++-- examples/foundational/33-gemini-rag.py | 2 +- examples/foundational/34-audio-recording.py | 6 ++++-- .../35-pattern-pair-voice-switching.py | 6 ++++-- examples/foundational/36-user-email-gathering.py | 6 ++++-- examples/foundational/37-mem0.py | 4 ++-- examples/foundational/38-smart-turn-fal.py | 6 ++++-- .../foundational/38a-smart-turn-local-coreml.py | 6 ++++-- examples/foundational/38b-smart-turn-local.py | 6 ++++-- examples/foundational/39-mcp-stdio.py | 9 +++++++-- examples/foundational/39c-multiple-mcp.py | 9 +++++++-- examples/foundational/42-interruption-config.py | 6 ++++-- examples/foundational/43-heygen-transport.py | 6 ++++-- .../foundational/43a-heygen-video-service.py | 6 ++++-- examples/foundational/44-voicemail-detection.py | 6 ++++-- .../foundational/45-before-and-after-events.py | 6 ++++-- examples/foundational/47-sentry-metrics.py | 6 ++++-- examples/foundational/48-service-switcher.py | 14 ++++++++++---- examples/foundational/49a-thinking-anthropic.py | 2 +- examples/foundational/49b-thinking-google.py | 2 +- .../49c-thinking-functions-anthropic.py | 2 +- .../49d-thinking-functions-google.py | 2 +- examples/foundational/52-live-translation.py | 6 ++++-- .../foundational/53-concurrent-llm-evaluation.py | 12 ++++++++---- .../53-concurrent-llm-rtvi-ignored-sources.py | 10 +++++++--- .../54-context-summarization-openai.py | 6 ++++-- .../54a-context-summarization-google.py | 6 ++++-- .../54b-context-summarization-manual-openai.py | 9 +++++++-- .../54c-context-summarization-dedicated-llm.py | 9 +++++++-- .../55a-update-settings-deepgram-flux-stt.py | 6 ++++-- ...55a-update-settings-deepgram-sagemaker-stt.py | 6 ++++-- .../55a-update-settings-deepgram-stt.py | 6 ++++-- .../55b-update-settings-azure-stt.py | 6 ++++-- .../55c-update-settings-google-stt.py | 6 ++++-- .../55d-update-settings-assemblyai-stt.py | 6 ++++-- .../55e-update-settings-gladia-stt.py | 6 ++++-- ...5f-update-settings-elevenlabs-realtime-stt.py | 6 ++++-- .../55g-update-settings-elevenlabs-stt.py | 6 ++++-- .../55h-update-settings-speechmatics-stt.py | 6 ++++-- .../55i-update-settings-whisper-api-stt.py | 6 ++++-- .../55j-update-settings-sarvam-stt.py | 6 ++++-- .../55k-update-settings-soniox-stt.py | 6 ++++-- .../55l-update-settings-aws-transcribe-stt.py | 6 ++++-- .../55m-update-settings-cartesia-stt.py | 6 ++++-- .../55n-update-settings-cartesia-http-tts.py | 6 ++++-- .../55n-update-settings-cartesia-tts.py | 6 ++++-- .../55o-update-settings-elevenlabs-http-tts.py | 6 ++++-- .../55o-update-settings-elevenlabs-tts.py | 6 ++++-- .../55p-update-settings-openai-tts.py | 6 ++++-- .../55q-update-settings-deepgram-http-tts.py | 6 ++++-- ...55q-update-settings-deepgram-sagemaker-tts.py | 6 ++++-- .../55q-update-settings-deepgram-tts.py | 6 ++++-- .../55r-update-settings-azure-http-tts.py | 6 ++++-- .../55r-update-settings-azure-tts.py | 6 ++++-- .../55s-update-settings-google-http-tts.py | 6 ++++-- .../55s-update-settings-google-stream-tts.py | 6 ++++-- .../55u-update-settings-rime-http-tts.py | 6 ++++-- .../foundational/55u-update-settings-rime-tts.py | 6 ++++-- .../foundational/55v-update-settings-lmnt-tts.py | 6 ++++-- .../foundational/55w-update-settings-fish-tts.py | 6 ++++-- .../55x-update-settings-minimax-tts.py | 6 ++++-- .../foundational/55y-update-settings-groq-tts.py | 6 ++++-- .../foundational/55z-update-settings-hume-tts.py | 6 ++++-- .../55za-update-settings-neuphonic-http-tts.py | 6 ++++-- .../55za-update-settings-neuphonic-tts.py | 6 ++++-- .../55zb-update-settings-inworld-http-tts.py | 6 ++++-- .../55zb-update-settings-inworld-tts.py | 6 ++++-- .../55zc-update-settings-gemini-tts.py | 6 ++++-- .../55zd-update-settings-aws-polly-tts.py | 6 ++++-- .../55ze-update-settings-sarvam-http-tts.py | 6 ++++-- .../55ze-update-settings-sarvam-tts.py | 6 ++++-- .../55zf-update-settings-camb-tts.py | 6 ++++-- .../55zh-update-settings-resembleai-tts.py | 6 ++++-- .../55zi-update-settings-azure-llm.py | 6 ++++-- .../55zi-update-settings-openai-llm.py | 4 +++- .../55zj-update-settings-anthropic-llm.py | 4 +++- .../55zk-update-settings-google-llm.py | 4 +++- .../55zk-update-settings-google-vertex-llm.py | 6 ++++-- .../55zp-update-settings-aws-bedrock-llm.py | 2 +- .../foundational/55zq-update-settings-fal-stt.py | 6 ++++-- .../55zr-update-settings-gradium-stt.py | 6 ++++-- .../55zt-update-settings-nvidia-segmented-stt.py | 6 ++++-- .../55zt-update-settings-nvidia-stt.py | 6 ++++-- .../55zu-update-settings-openai-realtime-stt.py | 6 ++++-- .../55zv-update-settings-asyncai-http-tts.py | 6 ++++-- .../55zv-update-settings-asyncai-tts.py | 6 ++++-- .../55zw-update-settings-gradium-tts.py | 6 ++++-- .../55zx-update-settings-cerebras-llm.py | 6 ++++-- .../55zy-update-settings-deepseek-llm.py | 6 ++++-- .../55zz-update-settings-fireworks-llm.py | 6 ++++-- .../55zza-update-settings-grok-llm.py | 6 ++++-- .../55zzb-update-settings-groq-llm.py | 6 ++++-- .../55zzc-update-settings-mistral-llm.py | 6 ++++-- .../55zzd-update-settings-nvidia-llm.py | 6 ++++-- .../55zze-update-settings-ollama-llm.py | 6 ++++-- .../55zzf-update-settings-openrouter-llm.py | 6 ++++-- .../55zzh-update-settings-qwen-llm.py | 6 ++++-- .../55zzi-update-settings-sambanova-llm.py | 6 ++++-- .../55zzj-update-settings-together-llm.py | 6 ++++-- .../55zzl-update-settings-nvidia-tts.py | 6 ++++-- .../55zzm-update-settings-speechmatics-tts.py | 6 ++++-- .../55zzn-update-settings-groq-stt.py | 6 ++++-- examples/foundational/56-lemonslice-transport.py | 6 ++++-- src/pipecat/services/anthropic/llm.py | 12 +++++------- src/pipecat/services/aws/llm.py | 12 +++++------- src/pipecat/services/cerebras/llm.py | 8 ++++++++ src/pipecat/services/fireworks/llm.py | 8 ++++++++ src/pipecat/services/google/llm.py | 16 ++++++++++++---- src/pipecat/services/google/llm_vertex.py | 10 +++++++++- src/pipecat/services/mistral/llm.py | 7 +++++++ src/pipecat/services/openai/base_llm.py | 12 +++++------- src/pipecat/services/openai/llm.py | 1 + src/pipecat/services/perplexity/llm.py | 7 +++++++ src/pipecat/services/sambanova/llm.py | 8 ++++++++ src/pipecat/services/settings.py | 2 ++ 223 files changed, 860 insertions(+), 424 deletions(-) diff --git a/examples/foundational/02-llm-say-one-thing.py b/examples/foundational/02-llm-say-one-thing.py index 3ee536a64..988ff634f 100644 --- a/examples/foundational/02-llm-say-one-thing.py +++ b/examples/foundational/02-llm-say-one-thing.py @@ -17,7 +17,7 @@ from pipecat.processors.aggregators.llm_context import LLMContext from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport from pipecat.services.cartesia.tts import CartesiaTTSService, CartesiaTTSSettings -from pipecat.services.openai.llm import OpenAILLMService +from pipecat.services.openai.llm import OpenAILLMService, OpenAILLMSettings from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams @@ -46,7 +46,9 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): llm = OpenAILLMService( api_key=os.getenv("OPENAI_API_KEY"), - system_instruction="You are an LLM in a WebRTC session, and this is a 'hello world' demo.", + settings=OpenAILLMSettings( + system_instruction="You are an LLM in a WebRTC session, and this is a 'hello world' demo.", + ), ) task = PipelineTask( diff --git a/examples/foundational/04-transports-small-webrtc.py b/examples/foundational/04-transports-small-webrtc.py index 6cf32a285..a26fdf5c0 100644 --- a/examples/foundational/04-transports-small-webrtc.py +++ b/examples/foundational/04-transports-small-webrtc.py @@ -29,7 +29,7 @@ from pipecat.processors.aggregators.llm_response_universal import ( ) from pipecat.services.cartesia.tts import CartesiaTTSService, CartesiaTTSSettings from pipecat.services.deepgram.stt import DeepgramSTTService -from pipecat.services.openai.llm import OpenAILLMService +from pipecat.services.openai.llm import OpenAILLMService, OpenAILLMSettings from pipecat.transports.base_transport import TransportParams from pipecat.transports.smallwebrtc.connection import IceServer, SmallWebRTCConnection from pipecat.transports.smallwebrtc.transport import SmallWebRTCTransport @@ -74,7 +74,9 @@ async def run_example(webrtc_connection: SmallWebRTCConnection): llm = OpenAILLMService( api_key=os.getenv("OPENAI_API_KEY"), - system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + settings=OpenAILLMSettings( + system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + ), ) context = LLMContext() diff --git a/examples/foundational/04a-transports-daily.py b/examples/foundational/04a-transports-daily.py index 8b23cb69e..15b5e20e2 100644 --- a/examples/foundational/04a-transports-daily.py +++ b/examples/foundational/04a-transports-daily.py @@ -59,8 +59,8 @@ async def main(): api_key=os.getenv("OPENAI_API_KEY"), settings=OpenAILLMSettings( model="gpt-4o", + system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", ), - system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", ) context = LLMContext() diff --git a/examples/foundational/04b-transports-livekit.py b/examples/foundational/04b-transports-livekit.py index f55f106c1..1f4709b0b 100644 --- a/examples/foundational/04b-transports-livekit.py +++ b/examples/foundational/04b-transports-livekit.py @@ -31,7 +31,7 @@ from pipecat.processors.aggregators.llm_response_universal import ( from pipecat.runner.livekit import configure from pipecat.services.cartesia.tts import CartesiaTTSService, CartesiaTTSSettings from pipecat.services.deepgram.stt import DeepgramSTTService -from pipecat.services.openai.llm import OpenAILLMService +from pipecat.services.openai.llm import OpenAILLMService, OpenAILLMSettings from pipecat.transports.livekit.transport import LiveKitParams, LiveKitTransport load_dotenv(override=True) @@ -57,7 +57,9 @@ async def main(): llm = OpenAILLMService( api_key=os.getenv("OPENAI_API_KEY"), - system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + settings=OpenAILLMSettings( + system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + ), ) tts = CartesiaTTSService( diff --git a/examples/foundational/06-listen-and-respond.py b/examples/foundational/06-listen-and-respond.py index c90d79c4e..1e2f88a93 100644 --- a/examples/foundational/06-listen-and-respond.py +++ b/examples/foundational/06-listen-and-respond.py @@ -30,7 +30,7 @@ from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport from pipecat.services.cartesia.tts import CartesiaTTSService, CartesiaTTSSettings from pipecat.services.deepgram.stt import DeepgramSTTService -from pipecat.services.openai.llm import OpenAILLMService +from pipecat.services.openai.llm import OpenAILLMService, OpenAILLMSettings from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams @@ -90,7 +90,9 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): llm = OpenAILLMService( api_key=os.getenv("OPENAI_API_KEY"), - system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + settings=OpenAILLMSettings( + system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + ), ) ml = MetricsLogger() diff --git a/examples/foundational/06a-image-sync.py b/examples/foundational/06a-image-sync.py index 666f4739c..007a41143 100644 --- a/examples/foundational/06a-image-sync.py +++ b/examples/foundational/06a-image-sync.py @@ -31,7 +31,7 @@ from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport from pipecat.services.cartesia.tts import CartesiaTTSService, CartesiaTTSSettings from pipecat.services.deepgram.stt import DeepgramSTTService -from pipecat.services.openai.llm import OpenAILLMService +from pipecat.services.openai.llm import OpenAILLMService, OpenAILLMSettings from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams @@ -107,7 +107,9 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): llm = OpenAILLMService( api_key=os.getenv("OPENAI_API_KEY"), - system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + settings=OpenAILLMSettings( + system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + ), ) context = LLMContext() diff --git a/examples/foundational/07-interruptible-cartesia-http.py b/examples/foundational/07-interruptible-cartesia-http.py index b20289ce2..ac409f55d 100644 --- a/examples/foundational/07-interruptible-cartesia-http.py +++ b/examples/foundational/07-interruptible-cartesia-http.py @@ -24,7 +24,7 @@ from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport from pipecat.services.cartesia.stt import CartesiaSTTService from pipecat.services.cartesia.tts import CartesiaHttpTTSService, CartesiaTTSSettings -from pipecat.services.openai.llm import OpenAILLMService +from pipecat.services.openai.llm import OpenAILLMService, OpenAILLMSettings from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams @@ -66,7 +66,9 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): llm = OpenAILLMService( api_key=os.getenv("OPENAI_API_KEY"), - system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + settings=OpenAILLMSettings( + system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + ), ) context = LLMContext() diff --git a/examples/foundational/07-interruptible.py b/examples/foundational/07-interruptible.py index b8a334ec0..05a751a68 100644 --- a/examples/foundational/07-interruptible.py +++ b/examples/foundational/07-interruptible.py @@ -23,7 +23,7 @@ from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport from pipecat.services.cartesia.tts import CartesiaTTSService, CartesiaTTSSettings from pipecat.services.deepgram.stt import DeepgramSTTService -from pipecat.services.openai.llm import OpenAILLMService +from pipecat.services.openai.llm import OpenAILLMService, OpenAILLMSettings from pipecat.services.tts_service import TextAggregationMode from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams @@ -63,7 +63,9 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): llm = OpenAILLMService( api_key=os.getenv("OPENAI_API_KEY"), - system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + settings=OpenAILLMSettings( + system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + ), ) context = LLMContext() diff --git a/examples/foundational/07a-interruptible-speechmatics-vad.py b/examples/foundational/07a-interruptible-speechmatics-vad.py index 5bb8459e2..a6a287f83 100644 --- a/examples/foundational/07a-interruptible-speechmatics-vad.py +++ b/examples/foundational/07a-interruptible-speechmatics-vad.py @@ -114,8 +114,8 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): api_key=os.getenv("OPENAI_API_KEY"), settings=OpenAILLMSettings( temperature=0.75, + system_instruction="You are a helpful British assistant called Sarah. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Always include punctuation in your responses. Give very short replies - do not give longer replies unless strictly necessary. Respond to what the user said in a concise, funny, creative and helpful way. Use `` tags to identify different speakers - do not use tags in your replies. Do not respond to speakers within `` tags unless explicitly asked to.", ), - system_instruction="You are a helpful British assistant called Sarah. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Always include punctuation in your responses. Give very short replies - do not give longer replies unless strictly necessary. Respond to what the user said in a concise, funny, creative and helpful way. Use `` tags to identify different speakers - do not use tags in your replies. Do not respond to speakers within `` tags unless explicitly asked to.", ) context = LLMContext() diff --git a/examples/foundational/07a-interruptible-speechmatics.py b/examples/foundational/07a-interruptible-speechmatics.py index caecb74be..d4e4dc638 100644 --- a/examples/foundational/07a-interruptible-speechmatics.py +++ b/examples/foundational/07a-interruptible-speechmatics.py @@ -94,8 +94,8 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): api_key=os.getenv("OPENAI_API_KEY"), settings=OpenAILLMSettings( temperature=0.75, + system_instruction="You are a helpful British assistant called Sarah. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Always include punctuation in your responses. Give very short replies - do not give longer replies unless strictly necessary. Respond to what the user said in a concise, funny, creative and helpful way. Use `` tags to identify different speakers - do not use tags in your replies. Do not respond to speakers within `` tags unless explicitly asked to.", ), - system_instruction="You are a helpful British assistant called Sarah. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Always include punctuation in your responses. Give very short replies - do not give longer replies unless strictly necessary. Respond to what the user said in a concise, funny, creative and helpful way. Use `` tags to identify different speakers - do not use tags in your replies. Do not respond to speakers within `` tags unless explicitly asked to.", ) context = LLMContext() diff --git a/examples/foundational/07c-interruptible-deepgram-flux.py b/examples/foundational/07c-interruptible-deepgram-flux.py index 4eafc24a7..c205c5141 100644 --- a/examples/foundational/07c-interruptible-deepgram-flux.py +++ b/examples/foundational/07c-interruptible-deepgram-flux.py @@ -24,7 +24,7 @@ from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport from pipecat.services.deepgram.flux.stt import DeepgramFluxSTTService, DeepgramFluxSTTSettings from pipecat.services.deepgram.tts import DeepgramTTSService, DeepgramTTSSettings -from pipecat.services.openai.llm import OpenAILLMService +from pipecat.services.openai.llm import OpenAILLMService, OpenAILLMSettings from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams @@ -70,7 +70,9 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): llm = OpenAILLMService( api_key=os.getenv("OPENAI_API_KEY"), - system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + settings=OpenAILLMSettings( + system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + ), ) context = LLMContext() diff --git a/examples/foundational/07c-interruptible-deepgram-http.py b/examples/foundational/07c-interruptible-deepgram-http.py index e6281fbc5..b4d829e96 100644 --- a/examples/foundational/07c-interruptible-deepgram-http.py +++ b/examples/foundational/07c-interruptible-deepgram-http.py @@ -25,7 +25,7 @@ from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport from pipecat.services.deepgram.stt import DeepgramSTTService from pipecat.services.deepgram.tts import DeepgramHttpTTSService, DeepgramTTSSettings -from pipecat.services.openai.llm import OpenAILLMService +from pipecat.services.openai.llm import OpenAILLMService, OpenAILLMSettings from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams @@ -67,7 +67,9 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): llm = OpenAILLMService( api_key=os.getenv("OPENAI_API_KEY"), - system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + settings=OpenAILLMSettings( + system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + ), ) context = LLMContext() diff --git a/examples/foundational/07c-interruptible-deepgram-sagemaker.py b/examples/foundational/07c-interruptible-deepgram-sagemaker.py index 2f51bda8d..b1c54a27e 100644 --- a/examples/foundational/07c-interruptible-deepgram-sagemaker.py +++ b/examples/foundational/07c-interruptible-deepgram-sagemaker.py @@ -79,10 +79,10 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): llm = AWSBedrockLLMService( aws_region=os.getenv("AWS_REGION"), - system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", settings=AWSBedrockLLMSettings( model="us.amazon.nova-pro-v1:0", temperature=0.8, + system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", ), ) diff --git a/examples/foundational/07c-interruptible-deepgram-vad.py b/examples/foundational/07c-interruptible-deepgram-vad.py index 81acad665..4af1b0c72 100644 --- a/examples/foundational/07c-interruptible-deepgram-vad.py +++ b/examples/foundational/07c-interruptible-deepgram-vad.py @@ -23,7 +23,7 @@ from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport from pipecat.services.deepgram.stt import DeepgramSTTService, DeepgramSTTSettings from pipecat.services.deepgram.tts import DeepgramTTSService, DeepgramTTSSettings -from pipecat.services.openai.llm import OpenAILLMService +from pipecat.services.openai.llm import OpenAILLMService, OpenAILLMSettings from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams @@ -70,7 +70,9 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): llm = OpenAILLMService( api_key=os.getenv("OPENAI_API_KEY"), - system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + settings=OpenAILLMSettings( + system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + ), ) context = LLMContext() diff --git a/examples/foundational/07c-interruptible-deepgram.py b/examples/foundational/07c-interruptible-deepgram.py index d33a19d56..1a10c0b28 100644 --- a/examples/foundational/07c-interruptible-deepgram.py +++ b/examples/foundational/07c-interruptible-deepgram.py @@ -24,7 +24,7 @@ from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport from pipecat.services.deepgram.stt import DeepgramSTTService from pipecat.services.deepgram.tts import DeepgramTTSService, DeepgramTTSSettings -from pipecat.services.openai.llm import OpenAILLMService +from pipecat.services.openai.llm import OpenAILLMService, OpenAILLMSettings from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams @@ -64,7 +64,9 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): llm = OpenAILLMService( api_key=os.getenv("OPENAI_API_KEY"), - system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + settings=OpenAILLMSettings( + system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + ), ) context = LLMContext() diff --git a/examples/foundational/07d-interruptible-elevenlabs-http.py b/examples/foundational/07d-interruptible-elevenlabs-http.py index 0dd95900c..a7f68a599 100644 --- a/examples/foundational/07d-interruptible-elevenlabs-http.py +++ b/examples/foundational/07d-interruptible-elevenlabs-http.py @@ -25,7 +25,7 @@ from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport from pipecat.services.elevenlabs.stt import ElevenLabsSTTService from pipecat.services.elevenlabs.tts import ElevenLabsHttpTTSService, ElevenLabsHttpTTSSettings -from pipecat.services.openai.llm import OpenAILLMService +from pipecat.services.openai.llm import OpenAILLMService, OpenAILLMSettings from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams @@ -71,7 +71,9 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): llm = OpenAILLMService( api_key=os.getenv("OPENAI_API_KEY"), - system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + settings=OpenAILLMSettings( + system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + ), ) context = LLMContext() diff --git a/examples/foundational/07d-interruptible-elevenlabs.py b/examples/foundational/07d-interruptible-elevenlabs.py index c4f31ac9b..ec62eac4d 100644 --- a/examples/foundational/07d-interruptible-elevenlabs.py +++ b/examples/foundational/07d-interruptible-elevenlabs.py @@ -24,7 +24,7 @@ from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport from pipecat.services.elevenlabs.stt import ElevenLabsRealtimeSTTService from pipecat.services.elevenlabs.tts import ElevenLabsTTSService, ElevenLabsTTSSettings -from pipecat.services.openai.llm import OpenAILLMService +from pipecat.services.openai.llm import OpenAILLMService, OpenAILLMSettings from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams @@ -64,7 +64,9 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): llm = OpenAILLMService( api_key=os.getenv("OPENAI_API_KEY"), - system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + settings=OpenAILLMSettings( + system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + ), ) context = LLMContext() diff --git a/examples/foundational/07f-interruptible-azure-http.py b/examples/foundational/07f-interruptible-azure-http.py index 1946f66ee..38b840d6a 100644 --- a/examples/foundational/07f-interruptible-azure-http.py +++ b/examples/foundational/07f-interruptible-azure-http.py @@ -22,7 +22,7 @@ from pipecat.processors.aggregators.llm_response_universal import ( ) from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport -from pipecat.services.azure.llm import AzureLLMService +from pipecat.services.azure.llm import AzureLLMService, AzureLLMSettings from pipecat.services.azure.stt import AzureSTTService from pipecat.services.azure.tts import AzureHttpTTSService from pipecat.transports.base_transport import BaseTransport, TransportParams @@ -66,7 +66,9 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): api_key=os.getenv("AZURE_CHATGPT_API_KEY"), endpoint=os.getenv("AZURE_CHATGPT_ENDPOINT"), model=os.getenv("AZURE_CHATGPT_MODEL"), - system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + settings=AzureLLMSettings( + system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + ), ) context = LLMContext() diff --git a/examples/foundational/07f-interruptible-azure.py b/examples/foundational/07f-interruptible-azure.py index 68f5a72f9..7dafd8e1e 100644 --- a/examples/foundational/07f-interruptible-azure.py +++ b/examples/foundational/07f-interruptible-azure.py @@ -22,7 +22,7 @@ from pipecat.processors.aggregators.llm_response_universal import ( ) from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport -from pipecat.services.azure.llm import AzureLLMService +from pipecat.services.azure.llm import AzureLLMService, AzureLLMSettings from pipecat.services.azure.stt import AzureSTTService from pipecat.services.azure.tts import AzureTTSService from pipecat.transports.base_transport import BaseTransport, TransportParams @@ -66,7 +66,9 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): api_key=os.getenv("AZURE_CHATGPT_API_KEY"), endpoint=os.getenv("AZURE_CHATGPT_ENDPOINT"), model=os.getenv("AZURE_CHATGPT_MODEL"), - system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + settings=AzureLLMSettings( + system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + ), ) context = LLMContext() diff --git a/examples/foundational/07g-interruptible-openai-http.py b/examples/foundational/07g-interruptible-openai-http.py index 721d1795f..2b841be6a 100644 --- a/examples/foundational/07g-interruptible-openai-http.py +++ b/examples/foundational/07g-interruptible-openai-http.py @@ -22,7 +22,7 @@ from pipecat.processors.aggregators.llm_response_universal import ( ) from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport -from pipecat.services.openai.llm import OpenAILLMService +from pipecat.services.openai.llm import OpenAILLMService, OpenAILLMSettings from pipecat.services.openai.stt import OpenAISTTService, OpenAISTTSettings from pipecat.services.openai.tts import OpenAITTSService, OpenAITTSSettings from pipecat.transports.base_transport import BaseTransport, TransportParams @@ -69,7 +69,9 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): llm = OpenAILLMService( api_key=os.getenv("OPENAI_API_KEY"), - system_instruction="You are very knowledgable about dogs. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + settings=OpenAILLMSettings( + system_instruction="You are very knowledgable about dogs. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + ), ) context = LLMContext() diff --git a/examples/foundational/07g-interruptible-openai.py b/examples/foundational/07g-interruptible-openai.py index 86b6c9267..776feeb17 100644 --- a/examples/foundational/07g-interruptible-openai.py +++ b/examples/foundational/07g-interruptible-openai.py @@ -22,7 +22,7 @@ from pipecat.processors.aggregators.llm_response_universal import ( ) from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport -from pipecat.services.openai.llm import OpenAILLMService +from pipecat.services.openai.llm import OpenAILLMService, OpenAILLMSettings from pipecat.services.openai.stt import OpenAIRealtimeSTTService, OpenAIRealtimeSTTSettings from pipecat.services.openai.tts import OpenAITTSService, OpenAITTSSettings from pipecat.transcriptions.language import Language @@ -71,7 +71,9 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): llm = OpenAILLMService( api_key=os.getenv("OPENAI_API_KEY"), - system_instruction="You are very knowledgable about dogs. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + settings=OpenAILLMSettings( + system_instruction="You are very knowledgable about dogs. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + ), ) context = LLMContext() diff --git a/examples/foundational/07h-interruptible-openpipe.py b/examples/foundational/07h-interruptible-openpipe.py index 6dbf04296..f7cd4d7d9 100644 --- a/examples/foundational/07h-interruptible-openpipe.py +++ b/examples/foundational/07h-interruptible-openpipe.py @@ -25,7 +25,7 @@ from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport from pipecat.services.cartesia.tts import CartesiaTTSService, CartesiaTTSSettings from pipecat.services.deepgram.stt import DeepgramSTTService -from pipecat.services.openpipe.llm import OpenPipeLLMService +from pipecat.services.openpipe.llm import OpenPipeLLMService, OpenPipeLLMSettings from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams @@ -67,7 +67,9 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): api_key=os.getenv("OPENAI_API_KEY"), openpipe_api_key=os.getenv("OPENPIPE_API_KEY"), tags={"conversation_id": f"pipecat-{timestamp}"}, - system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + settings=OpenPipeLLMSettings( + system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + ), ) context = LLMContext() diff --git a/examples/foundational/07i-interruptible-xtts.py b/examples/foundational/07i-interruptible-xtts.py index 6837917aa..76f139cbf 100644 --- a/examples/foundational/07i-interruptible-xtts.py +++ b/examples/foundational/07i-interruptible-xtts.py @@ -24,7 +24,7 @@ from pipecat.processors.aggregators.llm_response_universal import ( from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport from pipecat.services.deepgram.stt import DeepgramSTTService -from pipecat.services.openai.llm import OpenAILLMService +from pipecat.services.openai.llm import OpenAILLMService, OpenAILLMSettings from pipecat.services.xtts.tts import XTTSService, XTTSSettings from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams @@ -67,7 +67,9 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): llm = OpenAILLMService( api_key=os.getenv("OPENAI_API_KEY"), - system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + settings=OpenAILLMSettings( + system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + ), ) context = LLMContext() diff --git a/examples/foundational/07j-interruptible-gladia-vad.py b/examples/foundational/07j-interruptible-gladia-vad.py index 2983e1605..3bc0c0404 100644 --- a/examples/foundational/07j-interruptible-gladia-vad.py +++ b/examples/foundational/07j-interruptible-gladia-vad.py @@ -25,7 +25,7 @@ from pipecat.runner.utils import create_transport from pipecat.services.cartesia.tts import CartesiaTTSService, CartesiaTTSSettings from pipecat.services.gladia.config import LanguageConfig from pipecat.services.gladia.stt import GladiaSTTService, GladiaSTTSettings -from pipecat.services.openai.llm import OpenAILLMService +from pipecat.services.openai.llm import OpenAILLMService, OpenAILLMSettings from pipecat.transcriptions.language import Language from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams @@ -75,7 +75,9 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): llm = OpenAILLMService( api_key=os.getenv("OPENAI_API_KEY", ""), - system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + settings=OpenAILLMSettings( + system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + ), ) context = LLMContext() diff --git a/examples/foundational/07j-interruptible-gladia.py b/examples/foundational/07j-interruptible-gladia.py index 5dca15834..781e20942 100644 --- a/examples/foundational/07j-interruptible-gladia.py +++ b/examples/foundational/07j-interruptible-gladia.py @@ -25,7 +25,7 @@ from pipecat.runner.utils import create_transport from pipecat.services.cartesia.tts import CartesiaTTSService, CartesiaTTSSettings from pipecat.services.gladia.config import LanguageConfig from pipecat.services.gladia.stt import GladiaSTTService, GladiaSTTSettings -from pipecat.services.openai.llm import OpenAILLMService +from pipecat.services.openai.llm import OpenAILLMService, OpenAILLMSettings from pipecat.transcriptions.language import Language from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams @@ -73,7 +73,9 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): llm = OpenAILLMService( api_key=os.getenv("OPENAI_API_KEY", ""), - system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + settings=OpenAILLMSettings( + system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + ), ) context = LLMContext() diff --git a/examples/foundational/07k-interruptible-lmnt.py b/examples/foundational/07k-interruptible-lmnt.py index debf186b1..cab1bca81 100644 --- a/examples/foundational/07k-interruptible-lmnt.py +++ b/examples/foundational/07k-interruptible-lmnt.py @@ -24,7 +24,7 @@ from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport from pipecat.services.deepgram.stt import DeepgramSTTService from pipecat.services.lmnt.tts import LmntTTSService, LmntTTSSettings -from pipecat.services.openai.llm import OpenAILLMService +from pipecat.services.openai.llm import OpenAILLMService, OpenAILLMSettings from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams @@ -63,7 +63,9 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): llm = OpenAILLMService( api_key=os.getenv("OPENAI_API_KEY"), - system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + settings=OpenAILLMSettings( + system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + ), ) context = LLMContext() diff --git a/examples/foundational/07l-interruptible-groq.py b/examples/foundational/07l-interruptible-groq.py index dd532b71c..3fe64a460 100644 --- a/examples/foundational/07l-interruptible-groq.py +++ b/examples/foundational/07l-interruptible-groq.py @@ -58,8 +58,8 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): api_key=os.getenv("GROQ_API_KEY"), settings=GroqLLMSettings( model="meta-llama/llama-4-maverick-17b-128e-instruct", + system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", ), - system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", ) tts = GroqTTSService(api_key=os.getenv("GROQ_API_KEY")) diff --git a/examples/foundational/07m-interruptible-aws.py b/examples/foundational/07m-interruptible-aws.py index 48a632a35..8b7c0c29e 100644 --- a/examples/foundational/07m-interruptible-aws.py +++ b/examples/foundational/07m-interruptible-aws.py @@ -20,7 +20,7 @@ from pipecat.processors.aggregators.llm_response_universal import ( ) from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport -from pipecat.services.aws.llm import AWSBedrockLLMService +from pipecat.services.aws.llm import AWSBedrockLLMService, AWSBedrockLLMSettings from pipecat.services.aws.stt import AWSTranscribeSTTService from pipecat.services.aws.tts import AWSPollyTTSService, AWSPollyTTSSettings from pipecat.transports.base_transport import BaseTransport, TransportParams @@ -65,7 +65,9 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): aws_region="us-west-2", model="us.anthropic.claude-haiku-4-5-20251001-v1:0", params=AWSBedrockLLMService.InputParams(temperature=0.8), - system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + settings=AWSBedrockLLMSettings( + system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + ), ) context = LLMContext() diff --git a/examples/foundational/07n-interruptible-gemini-image.py b/examples/foundational/07n-interruptible-gemini-image.py index 2b1d191c4..072998fa9 100644 --- a/examples/foundational/07n-interruptible-gemini-image.py +++ b/examples/foundational/07n-interruptible-gemini-image.py @@ -89,8 +89,8 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): settings=GoogleLLMSettings( model="gemini-2.5-flash-image", # model="gemini-3-pro-image-preview", # A more powerful model, but slower, + system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", ), - system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", ) context = LLMContext() diff --git a/examples/foundational/07n-interruptible-gemini.py b/examples/foundational/07n-interruptible-gemini.py index 7a631f473..a48efefad 100644 --- a/examples/foundational/07n-interruptible-gemini.py +++ b/examples/foundational/07n-interruptible-gemini.py @@ -22,7 +22,7 @@ from pipecat.processors.aggregators.llm_response_universal import ( ) from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport -from pipecat.services.google.llm import GoogleLLMService +from pipecat.services.google.llm import GoogleLLMService, GoogleLLMSettings from pipecat.services.google.stt import GoogleSTTService, GoogleSTTSettings from pipecat.services.google.tts import GeminiTTSService, GeminiTTSSettings from pipecat.transcriptions.language import Language @@ -73,7 +73,8 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): llm = GoogleLLMService( api_key=os.getenv("GOOGLE_API_KEY"), model="gemini-2.5-flash", - system_instruction="""You are a helpful AI assistant in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. + settings=GoogleLLMSettings( + system_instruction="""You are a helpful AI assistant in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. IMPORTANT: You're using Gemini TTS which supports expressive markup tags. You can use these tags in your responses: - [sigh] - Insert a sigh sound @@ -91,6 +92,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): - "The answer is... [long pause] ...42!" Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.""", + ), ) context = LLMContext() diff --git a/examples/foundational/07n-interruptible-google-http.py b/examples/foundational/07n-interruptible-google-http.py index 1f570366a..0a6280618 100644 --- a/examples/foundational/07n-interruptible-google-http.py +++ b/examples/foundational/07n-interruptible-google-http.py @@ -76,8 +76,8 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): model="gemini-2.5-flash", # force a certain amount of thinking if you want it # thinking=GoogleLLMService.ThinkingConfig(thinking_budget=4096) + system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", ), - system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", ) context = LLMContext() diff --git a/examples/foundational/07n-interruptible-google.py b/examples/foundational/07n-interruptible-google.py index 439676238..d6c57b548 100644 --- a/examples/foundational/07n-interruptible-google.py +++ b/examples/foundational/07n-interruptible-google.py @@ -76,8 +76,8 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): model="gemini-2.5-flash", # force a certain amount of thinking if you want it # thinking=GoogleLLMService.ThinkingConfig(thinking_budget=4096), + system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", ), - system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", ) context = LLMContext() diff --git a/examples/foundational/07o-interruptible-assemblyai-turn-detection.py b/examples/foundational/07o-interruptible-assemblyai-turn-detection.py index 6f2ec36f2..b15e3038f 100644 --- a/examples/foundational/07o-interruptible-assemblyai-turn-detection.py +++ b/examples/foundational/07o-interruptible-assemblyai-turn-detection.py @@ -24,7 +24,7 @@ from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport from pipecat.services.assemblyai.stt import AssemblyAISTTService, AssemblyAISTTSettings from pipecat.services.cartesia.tts import CartesiaTTSService, CartesiaTTSSettings -from pipecat.services.openai.llm import OpenAILLMService +from pipecat.services.openai.llm import OpenAILLMService, OpenAILLMSettings from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams @@ -114,7 +114,9 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): llm = OpenAILLMService( api_key=os.getenv("OPENAI_API_KEY"), - system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + settings=OpenAILLMSettings( + system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + ), ) context = LLMContext() diff --git a/examples/foundational/07o-interruptible-assemblyai.py b/examples/foundational/07o-interruptible-assemblyai.py index 10d6a8cd4..8e58ddbf3 100644 --- a/examples/foundational/07o-interruptible-assemblyai.py +++ b/examples/foundational/07o-interruptible-assemblyai.py @@ -24,7 +24,7 @@ from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport from pipecat.services.assemblyai.stt import AssemblyAISTTService from pipecat.services.cartesia.tts import CartesiaTTSService, CartesiaTTSSettings -from pipecat.services.openai.llm import OpenAILLMService +from pipecat.services.openai.llm import OpenAILLMService, OpenAILLMSettings from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams @@ -66,7 +66,9 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): llm = OpenAILLMService( api_key=os.getenv("OPENAI_API_KEY"), - system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + settings=OpenAILLMSettings( + system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + ), ) context = LLMContext() diff --git a/examples/foundational/07p-interruptible-krisp-viva.py b/examples/foundational/07p-interruptible-krisp-viva.py index 1b10202f3..056a2f6cc 100644 --- a/examples/foundational/07p-interruptible-krisp-viva.py +++ b/examples/foundational/07p-interruptible-krisp-viva.py @@ -45,7 +45,7 @@ from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport from pipecat.services.cartesia.tts import CartesiaTTSService, CartesiaTTSSettings from pipecat.services.deepgram.stt import DeepgramSTTService -from pipecat.services.openai.llm import OpenAILLMService +from pipecat.services.openai.llm import OpenAILLMService, OpenAILLMSettings from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams @@ -92,7 +92,9 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): llm = OpenAILLMService( api_key=os.getenv("OPENAI_API_KEY"), - system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + settings=OpenAILLMSettings( + system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + ), ) context = LLMContext() diff --git a/examples/foundational/07p-interruptible-krisp.py b/examples/foundational/07p-interruptible-krisp.py index 54d88d32a..b3ccfb30e 100644 --- a/examples/foundational/07p-interruptible-krisp.py +++ b/examples/foundational/07p-interruptible-krisp.py @@ -25,7 +25,7 @@ from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport from pipecat.services.deepgram.stt import DeepgramSTTService from pipecat.services.deepgram.tts import DeepgramTTSService, DeepgramTTSSettings -from pipecat.services.openai.llm import OpenAILLMService +from pipecat.services.openai.llm import OpenAILLMService, OpenAILLMSettings from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams @@ -67,7 +67,9 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): llm = OpenAILLMService( api_key=os.getenv("OPENAI_API_KEY"), - system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + settings=OpenAILLMSettings( + system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + ), ) context = LLMContext() diff --git a/examples/foundational/07q-interruptible-rime-http.py b/examples/foundational/07q-interruptible-rime-http.py index c735e39c9..ebbdc6946 100644 --- a/examples/foundational/07q-interruptible-rime-http.py +++ b/examples/foundational/07q-interruptible-rime-http.py @@ -24,7 +24,7 @@ from pipecat.processors.aggregators.llm_response_universal import ( from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport from pipecat.services.deepgram.stt import DeepgramSTTService -from pipecat.services.openai.llm import OpenAILLMService +from pipecat.services.openai.llm import OpenAILLMService, OpenAILLMSettings from pipecat.services.rime.tts import RimeHttpTTSService, RimeTTSSettings from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams @@ -70,7 +70,9 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): llm = OpenAILLMService( api_key=os.getenv("OPENAI_API_KEY"), - system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + settings=OpenAILLMSettings( + system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + ), ) context = LLMContext() diff --git a/examples/foundational/07q-interruptible-rime.py b/examples/foundational/07q-interruptible-rime.py index dbc6b91e6..bfcf5da41 100644 --- a/examples/foundational/07q-interruptible-rime.py +++ b/examples/foundational/07q-interruptible-rime.py @@ -23,7 +23,7 @@ from pipecat.processors.aggregators.llm_response_universal import ( from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport from pipecat.services.deepgram.stt import DeepgramSTTService -from pipecat.services.openai.llm import OpenAILLMService +from pipecat.services.openai.llm import OpenAILLMService, OpenAILLMSettings from pipecat.services.rime.tts import RimeTTSService, RimeTTSSettings from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams @@ -63,7 +63,9 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): llm = OpenAILLMService( api_key=os.getenv("OPENAI_API_KEY"), - system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + settings=OpenAILLMSettings( + system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + ), ) context = LLMContext() diff --git a/examples/foundational/07r-interruptible-nvidia.py b/examples/foundational/07r-interruptible-nvidia.py index 69a5fbc15..a5a477ba0 100644 --- a/examples/foundational/07r-interruptible-nvidia.py +++ b/examples/foundational/07r-interruptible-nvidia.py @@ -58,8 +58,8 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): api_key=os.getenv("NVIDIA_API_KEY"), settings=NvidiaLLMSettings( model="meta/llama-3.3-70b-instruct", + system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", ), - system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", ) tts = NvidiaTTSService(api_key=os.getenv("NVIDIA_API_KEY")) diff --git a/examples/foundational/07t-interruptible-fish.py b/examples/foundational/07t-interruptible-fish.py index d54d34c1c..4825c3110 100644 --- a/examples/foundational/07t-interruptible-fish.py +++ b/examples/foundational/07t-interruptible-fish.py @@ -24,7 +24,7 @@ from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport from pipecat.services.deepgram.stt import DeepgramSTTService from pipecat.services.fish.tts import FishAudioTTSService, FishAudioTTSSettings -from pipecat.services.openai.llm import OpenAILLMService +from pipecat.services.openai.llm import OpenAILLMService, OpenAILLMSettings from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams @@ -64,7 +64,9 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): llm = OpenAILLMService( api_key=os.getenv("OPENAI_API_KEY"), - system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + settings=OpenAILLMSettings( + system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + ), ) context = LLMContext() diff --git a/examples/foundational/07v-interruptible-neuphonic-http.py b/examples/foundational/07v-interruptible-neuphonic-http.py index 081d9d6cc..5c2934fcd 100644 --- a/examples/foundational/07v-interruptible-neuphonic-http.py +++ b/examples/foundational/07v-interruptible-neuphonic-http.py @@ -25,7 +25,7 @@ from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport from pipecat.services.deepgram.stt import DeepgramSTTService from pipecat.services.neuphonic.tts import NeuphonicHttpTTSService, NeuphonicTTSSettings -from pipecat.services.openai.llm import OpenAILLMService +from pipecat.services.openai.llm import OpenAILLMService, OpenAILLMSettings from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams @@ -68,7 +68,9 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): llm = OpenAILLMService( api_key=os.getenv("OPENAI_API_KEY"), - system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + settings=OpenAILLMSettings( + system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + ), ) context = LLMContext() diff --git a/examples/foundational/07v-interruptible-neuphonic.py b/examples/foundational/07v-interruptible-neuphonic.py index 3f30ab9c7..d70b187a7 100644 --- a/examples/foundational/07v-interruptible-neuphonic.py +++ b/examples/foundational/07v-interruptible-neuphonic.py @@ -24,7 +24,7 @@ from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport from pipecat.services.deepgram.stt import DeepgramSTTService from pipecat.services.neuphonic.tts import NeuphonicTTSService, NeuphonicTTSSettings -from pipecat.services.openai.llm import OpenAILLMService +from pipecat.services.openai.llm import OpenAILLMService, OpenAILLMSettings from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams @@ -63,7 +63,9 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): llm = OpenAILLMService( api_key=os.getenv("OPENAI_API_KEY"), - system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + settings=OpenAILLMSettings( + system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + ), ) context = LLMContext() diff --git a/examples/foundational/07w-interruptible-fal.py b/examples/foundational/07w-interruptible-fal.py index 7e0e53bc9..6539cbfc9 100644 --- a/examples/foundational/07w-interruptible-fal.py +++ b/examples/foundational/07w-interruptible-fal.py @@ -25,7 +25,7 @@ from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport from pipecat.services.cartesia.tts import CartesiaTTSService, CartesiaTTSSettings from pipecat.services.fal.stt import FalSTTService -from pipecat.services.openai.llm import OpenAILLMService +from pipecat.services.openai.llm import OpenAILLMService, OpenAILLMSettings from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams @@ -69,7 +69,9 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): llm = OpenAILLMService( api_key=os.getenv("OPENAI_API_KEY"), - system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + settings=OpenAILLMSettings( + system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + ), ) context = LLMContext() diff --git a/examples/foundational/07x-interruptible-local.py b/examples/foundational/07x-interruptible-local.py index 63cf2bbb1..e0eeee03b 100644 --- a/examples/foundational/07x-interruptible-local.py +++ b/examples/foundational/07x-interruptible-local.py @@ -23,7 +23,7 @@ from pipecat.processors.aggregators.llm_response_universal import ( ) from pipecat.services.cartesia.tts import CartesiaTTSService, CartesiaTTSSettings from pipecat.services.deepgram.stt import DeepgramSTTService -from pipecat.services.openai.llm import OpenAILLMService +from pipecat.services.openai.llm import OpenAILLMService, OpenAILLMSettings from pipecat.transports.local.audio import LocalAudioTransport, LocalAudioTransportParams load_dotenv(override=True) @@ -51,7 +51,9 @@ async def main(): llm = OpenAILLMService( api_key=os.getenv("OPENAI_API_KEY"), - system_instruction="You are a helpful LLM. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + settings=OpenAILLMSettings( + system_instruction="You are a helpful LLM. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + ), ) context = LLMContext() diff --git a/examples/foundational/07y-interruptible-minimax.py b/examples/foundational/07y-interruptible-minimax.py index 690c35178..1213291e0 100644 --- a/examples/foundational/07y-interruptible-minimax.py +++ b/examples/foundational/07y-interruptible-minimax.py @@ -25,7 +25,7 @@ from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport from pipecat.services.deepgram.stt import DeepgramSTTService from pipecat.services.minimax.tts import MiniMaxHttpTTSService, MiniMaxTTSSettings -from pipecat.services.openai.llm import OpenAILLMService +from pipecat.services.openai.llm import OpenAILLMService, OpenAILLMSettings from pipecat.transcriptions.language import Language from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams @@ -70,7 +70,9 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): llm = OpenAILLMService( api_key=os.getenv("OPENAI_API_KEY"), - system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + settings=OpenAILLMSettings( + system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + ), ) context = LLMContext() diff --git a/examples/foundational/07z-interruptible-sarvam-http.py b/examples/foundational/07z-interruptible-sarvam-http.py index 33f1277e6..566cea75a 100644 --- a/examples/foundational/07z-interruptible-sarvam-http.py +++ b/examples/foundational/07z-interruptible-sarvam-http.py @@ -23,7 +23,7 @@ from pipecat.processors.aggregators.llm_response_universal import ( ) from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport -from pipecat.services.openai.llm import OpenAILLMService +from pipecat.services.openai.llm import OpenAILLMService, OpenAILLMSettings from pipecat.services.sarvam.stt import SarvamSTTService from pipecat.services.sarvam.tts import SarvamHttpTTSService, SarvamHttpTTSSettings from pipecat.transcriptions.language import Language @@ -72,7 +72,9 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): llm = OpenAILLMService( api_key=os.getenv("OPENAI_API_KEY"), - system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + settings=OpenAILLMSettings( + system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + ), ) context = LLMContext() diff --git a/examples/foundational/07z-interruptible-sarvam.py b/examples/foundational/07z-interruptible-sarvam.py index 60b5bcc8b..827ce947f 100644 --- a/examples/foundational/07z-interruptible-sarvam.py +++ b/examples/foundational/07z-interruptible-sarvam.py @@ -21,7 +21,7 @@ from pipecat.processors.aggregators.llm_response_universal import ( ) from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport -from pipecat.services.openai.llm import OpenAILLMService +from pipecat.services.openai.llm import OpenAILLMService, OpenAILLMSettings from pipecat.services.sarvam.stt import SarvamSTTService, SarvamSTTSettings from pipecat.services.sarvam.tts import SarvamTTSService, SarvamTTSSettings from pipecat.transports.base_transport import BaseTransport, TransportParams @@ -68,7 +68,9 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): ) llm = OpenAILLMService( api_key=os.getenv("OPENAI_API_KEY"), - system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + settings=OpenAILLMSettings( + system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + ), ) context = LLMContext() diff --git a/examples/foundational/07za-interruptible-soniox.py b/examples/foundational/07za-interruptible-soniox.py index 56b2dee1e..380033a11 100644 --- a/examples/foundational/07za-interruptible-soniox.py +++ b/examples/foundational/07za-interruptible-soniox.py @@ -23,7 +23,7 @@ from pipecat.processors.aggregators.llm_response_universal import ( from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport from pipecat.services.cartesia.tts import CartesiaTTSService, CartesiaTTSSettings -from pipecat.services.openai.llm import OpenAILLMService +from pipecat.services.openai.llm import OpenAILLMService, OpenAILLMSettings from pipecat.services.soniox.stt import SonioxSTTService, SonioxSTTSettings from pipecat.transcriptions.language import Language from pipecat.transports.base_transport import BaseTransport, TransportParams @@ -70,7 +70,9 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): llm = OpenAILLMService( api_key=os.getenv("OPENAI_API_KEY"), - system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + settings=OpenAILLMSettings( + system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + ), ) context = LLMContext() diff --git a/examples/foundational/07zb-interruptible-inworld-http.py b/examples/foundational/07zb-interruptible-inworld-http.py index ffbdbb444..1376ab8da 100644 --- a/examples/foundational/07zb-interruptible-inworld-http.py +++ b/examples/foundational/07zb-interruptible-inworld-http.py @@ -25,7 +25,7 @@ from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport from pipecat.services.deepgram.stt import DeepgramSTTService from pipecat.services.inworld.tts import InworldHttpTTSService, InworldTTSSettings -from pipecat.services.openai.llm import OpenAILLMService +from pipecat.services.openai.llm import OpenAILLMService, OpenAILLMSettings from pipecat.transports.base_output import BaseOutputTransport from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams @@ -68,7 +68,9 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): llm = OpenAILLMService( api_key=os.getenv("OPENAI_API_KEY"), - system_instruction="You are a helpful AI demonstrating Inworld AI's TTS. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a friendly and helpful way.", + settings=OpenAILLMSettings( + system_instruction="You are a helpful AI demonstrating Inworld AI's TTS. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a friendly and helpful way.", + ), ) context = LLMContext() diff --git a/examples/foundational/07zb-interruptible-inworld.py b/examples/foundational/07zb-interruptible-inworld.py index 6c8b53706..9c9895ca9 100644 --- a/examples/foundational/07zb-interruptible-inworld.py +++ b/examples/foundational/07zb-interruptible-inworld.py @@ -24,7 +24,7 @@ from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport from pipecat.services.deepgram.stt import DeepgramSTTService from pipecat.services.inworld.tts import InworldTTSService, InworldTTSSettings -from pipecat.services.openai.llm import OpenAILLMService +from pipecat.services.openai.llm import OpenAILLMService, OpenAILLMSettings from pipecat.transports.base_output import BaseOutputTransport from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams @@ -65,7 +65,9 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): llm = OpenAILLMService( api_key=os.getenv("OPENAI_API_KEY"), - system_instruction="You are a helpful AI demonstrating Inworld AI's TTS. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a friendly and helpful way.", + settings=OpenAILLMSettings( + system_instruction="You are a helpful AI demonstrating Inworld AI's TTS. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a friendly and helpful way.", + ), ) context = LLMContext() diff --git a/examples/foundational/07zc-interruptible-asyncai-http.py b/examples/foundational/07zc-interruptible-asyncai-http.py index 3246feac4..b3f46f671 100644 --- a/examples/foundational/07zc-interruptible-asyncai-http.py +++ b/examples/foundational/07zc-interruptible-asyncai-http.py @@ -25,7 +25,7 @@ from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport from pipecat.services.asyncai.tts import AsyncAIHttpTTSService, AsyncAITTSSettings from pipecat.services.deepgram.stt import DeepgramSTTService -from pipecat.services.openai.llm import OpenAILLMService +from pipecat.services.openai.llm import OpenAILLMService, OpenAILLMSettings from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams @@ -68,7 +68,9 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): llm = OpenAILLMService( api_key=os.getenv("OPENAI_API_KEY"), - system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + settings=OpenAILLMSettings( + system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + ), ) context = LLMContext() diff --git a/examples/foundational/07zc-interruptible-asyncai.py b/examples/foundational/07zc-interruptible-asyncai.py index 093f03ccb..b95a55ddb 100644 --- a/examples/foundational/07zc-interruptible-asyncai.py +++ b/examples/foundational/07zc-interruptible-asyncai.py @@ -24,7 +24,7 @@ from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport from pipecat.services.asyncai.tts import AsyncAITTSService, AsyncAITTSSettings from pipecat.services.deepgram.stt import DeepgramSTTService -from pipecat.services.openai.llm import OpenAILLMService +from pipecat.services.openai.llm import OpenAILLMService, OpenAILLMSettings from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams @@ -64,7 +64,9 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): llm = OpenAILLMService( api_key=os.getenv("OPENAI_API_KEY"), - system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + settings=OpenAILLMSettings( + system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + ), ) context = LLMContext() diff --git a/examples/foundational/07zd-interruptible-aicoustics.py b/examples/foundational/07zd-interruptible-aicoustics.py index cedb95a9e..481e098a2 100644 --- a/examples/foundational/07zd-interruptible-aicoustics.py +++ b/examples/foundational/07zd-interruptible-aicoustics.py @@ -27,7 +27,7 @@ from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport from pipecat.services.cartesia.tts import CartesiaTTSService, CartesiaTTSSettings from pipecat.services.deepgram.stt import DeepgramSTTService -from pipecat.services.openai.llm import OpenAILLMService +from pipecat.services.openai.llm import OpenAILLMService, OpenAILLMSettings from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams @@ -84,7 +84,9 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): llm = OpenAILLMService( api_key=os.getenv("OPENAI_API_KEY"), - system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + settings=OpenAILLMSettings( + system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + ), ) context = LLMContext() diff --git a/examples/foundational/07ze-interruptible-hume.py b/examples/foundational/07ze-interruptible-hume.py index 70ace62e9..c5c352232 100644 --- a/examples/foundational/07ze-interruptible-hume.py +++ b/examples/foundational/07ze-interruptible-hume.py @@ -24,7 +24,7 @@ from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport from pipecat.services.deepgram.stt import DeepgramSTTService from pipecat.services.hume.tts import HUME_SAMPLE_RATE, HumeTTSService, HumeTTSSettings -from pipecat.services.openai.llm import OpenAILLMService +from pipecat.services.openai.llm import OpenAILLMService, OpenAILLMSettings from pipecat.transports.base_output import BaseOutputTransport from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams @@ -66,7 +66,9 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): llm = OpenAILLMService( api_key=os.getenv("OPENAI_API_KEY"), - system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + settings=OpenAILLMSettings( + system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + ), ) context = LLMContext() diff --git a/examples/foundational/07zf-interruptible-gradium.py b/examples/foundational/07zf-interruptible-gradium.py index ff164c790..acf168f13 100644 --- a/examples/foundational/07zf-interruptible-gradium.py +++ b/examples/foundational/07zf-interruptible-gradium.py @@ -23,7 +23,7 @@ from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport from pipecat.services.gradium.stt import GradiumSTTService, GradiumSTTSettings from pipecat.services.gradium.tts import GradiumTTSService, GradiumTTSSettings -from pipecat.services.openai.llm import OpenAILLMService +from pipecat.services.openai.llm import OpenAILLMService, OpenAILLMSettings from pipecat.transcriptions.language import Language from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams @@ -70,7 +70,9 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): llm = OpenAILLMService( api_key=os.getenv("OPENAI_API_KEY"), - system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + settings=OpenAILLMSettings( + system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + ), ) context = LLMContext() diff --git a/examples/foundational/07zg-interruptible-camb.py b/examples/foundational/07zg-interruptible-camb.py index f98303b26..e8d5011e2 100644 --- a/examples/foundational/07zg-interruptible-camb.py +++ b/examples/foundational/07zg-interruptible-camb.py @@ -23,7 +23,7 @@ from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport from pipecat.services.camb.tts import CambTTSService, CambTTSSettings from pipecat.services.deepgram.stt import DeepgramSTTService -from pipecat.services.openai.llm import OpenAILLMService +from pipecat.services.openai.llm import OpenAILLMService, OpenAILLMSettings from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams @@ -63,7 +63,9 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): llm = OpenAILLMService( api_key=os.getenv("OPENAI_API_KEY"), - system_instruction="You are a helpful voice assistant powered by Camb AI text-to-speech. ", + settings=OpenAILLMSettings( + system_instruction="You are a helpful voice assistant powered by Camb AI text-to-speech. ", + ), ) context = LLMContext() diff --git a/examples/foundational/07zi-interruptible-piper.py b/examples/foundational/07zi-interruptible-piper.py index fb38cba6a..9ac672fc2 100644 --- a/examples/foundational/07zi-interruptible-piper.py +++ b/examples/foundational/07zi-interruptible-piper.py @@ -22,7 +22,7 @@ from pipecat.processors.aggregators.llm_response_universal import ( from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport from pipecat.services.deepgram.stt import DeepgramSTTService -from pipecat.services.openai.llm import OpenAILLMService +from pipecat.services.openai.llm import OpenAILLMService, OpenAILLMSettings from pipecat.services.piper.tts import PiperTTSService, PiperTTSSettings from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams @@ -62,7 +62,9 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): llm = OpenAILLMService( api_key=os.getenv("OPENAI_API_KEY"), - system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + settings=OpenAILLMSettings( + system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + ), ) context = LLMContext() diff --git a/examples/foundational/07zj-interruptible-kokoro.py b/examples/foundational/07zj-interruptible-kokoro.py index 7271ef42d..66a225d35 100644 --- a/examples/foundational/07zj-interruptible-kokoro.py +++ b/examples/foundational/07zj-interruptible-kokoro.py @@ -23,7 +23,7 @@ from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport from pipecat.services.deepgram.stt import DeepgramSTTService from pipecat.services.kokoro.tts import KokoroTTSService, KokoroTTSSettings -from pipecat.services.openai.llm import OpenAILLMService +from pipecat.services.openai.llm import OpenAILLMService, OpenAILLMSettings from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams @@ -62,7 +62,9 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): llm = OpenAILLMService( api_key=os.getenv("OPENAI_API_KEY"), - system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + settings=OpenAILLMSettings( + system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + ), ) context = LLMContext() diff --git a/examples/foundational/07zk-interruptible-resemble.py b/examples/foundational/07zk-interruptible-resemble.py index 5e89eaa6e..2212fa80f 100644 --- a/examples/foundational/07zk-interruptible-resemble.py +++ b/examples/foundational/07zk-interruptible-resemble.py @@ -22,7 +22,7 @@ from pipecat.processors.aggregators.llm_response_universal import ( from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport from pipecat.services.deepgram.stt import DeepgramSTTService -from pipecat.services.openai.llm import OpenAILLMService +from pipecat.services.openai.llm import OpenAILLMService, OpenAILLMSettings from pipecat.services.resembleai.tts import ResembleAITTSService, ResembleAITTSSettings from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams @@ -66,7 +66,9 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): llm = OpenAILLMService( api_key=os.getenv("OPENAI_API_KEY"), - system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + settings=OpenAILLMSettings( + system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + ), ) context = LLMContext() diff --git a/examples/foundational/08-custom-frame-processor.py b/examples/foundational/08-custom-frame-processor.py index cfab184cb..820659207 100644 --- a/examples/foundational/08-custom-frame-processor.py +++ b/examples/foundational/08-custom-frame-processor.py @@ -28,7 +28,7 @@ from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport from pipecat.services.cartesia.tts import CartesiaTTSService, CartesiaTTSSettings from pipecat.services.deepgram.stt import DeepgramSTTService -from pipecat.services.openai.llm import OpenAILLMService +from pipecat.services.openai.llm import OpenAILLMService, OpenAILLMSettings from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams @@ -102,7 +102,9 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): llm = OpenAILLMService( api_key=os.getenv("OPENAI_API_KEY"), - system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + settings=OpenAILLMSettings( + system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + ), ) context = LLMContext() diff --git a/examples/foundational/10-wake-phrase.py b/examples/foundational/10-wake-phrase.py index a57ef6f96..de237659a 100644 --- a/examples/foundational/10-wake-phrase.py +++ b/examples/foundational/10-wake-phrase.py @@ -24,7 +24,7 @@ from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport from pipecat.services.cartesia.tts import CartesiaTTSService, CartesiaTTSSettings from pipecat.services.deepgram.stt import DeepgramSTTService -from pipecat.services.openai.llm import OpenAILLMService +from pipecat.services.openai.llm import OpenAILLMService, OpenAILLMSettings from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams @@ -63,7 +63,9 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): llm = OpenAILLMService( api_key=os.getenv("OPENAI_API_KEY"), - system_instruction="You are a helpful assistant. Respond to what the user said in a creative and helpful way. Keep your responses brief.", + settings=OpenAILLMSettings( + system_instruction="You are a helpful assistant. Respond to what the user said in a creative and helpful way. Keep your responses brief.", + ), ) hey_robot_filter = WakeCheckFilter(["hey robot", "hey, robot"]) diff --git a/examples/foundational/11-sound-effects.py b/examples/foundational/11-sound-effects.py index 332c1536a..664bd122c 100644 --- a/examples/foundational/11-sound-effects.py +++ b/examples/foundational/11-sound-effects.py @@ -32,7 +32,7 @@ from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport from pipecat.services.cartesia.tts import CartesiaTTSService, CartesiaTTSSettings from pipecat.services.deepgram.stt import DeepgramSTTService -from pipecat.services.openai.llm import OpenAILLMService +from pipecat.services.openai.llm import OpenAILLMService, OpenAILLMSettings from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams @@ -106,7 +106,9 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): llm = OpenAILLMService( api_key=os.getenv("OPENAI_API_KEY"), - system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + settings=OpenAILLMSettings( + system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + ), ) tts = CartesiaTTSService( diff --git a/examples/foundational/12-describe-image-openai.py b/examples/foundational/12-describe-image-openai.py index 4d22e4046..d9b0be871 100644 --- a/examples/foundational/12-describe-image-openai.py +++ b/examples/foundational/12-describe-image-openai.py @@ -25,7 +25,7 @@ from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport from pipecat.services.cartesia.tts import CartesiaTTSService, CartesiaTTSSettings from pipecat.services.deepgram.stt import DeepgramSTTService -from pipecat.services.openai.llm import OpenAILLMService +from pipecat.services.openai.llm import OpenAILLMService, OpenAILLMSettings from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams @@ -60,7 +60,9 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): llm = OpenAILLMService( api_key=os.getenv("OPENAI_API_KEY"), - system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way. You are also able to describe images.", + settings=OpenAILLMSettings( + system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way. You are also able to describe images.", + ), ) context = LLMContext() diff --git a/examples/foundational/12a-describe-image-anthropic.py b/examples/foundational/12a-describe-image-anthropic.py index 79e4460a2..5a10f24a5 100644 --- a/examples/foundational/12a-describe-image-anthropic.py +++ b/examples/foundational/12a-describe-image-anthropic.py @@ -23,7 +23,7 @@ from pipecat.processors.aggregators.llm_response_universal import ( ) from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport -from pipecat.services.anthropic.llm import AnthropicLLMService +from pipecat.services.anthropic.llm import AnthropicLLMService, AnthropicLLMSettings from pipecat.services.cartesia.tts import CartesiaTTSService, CartesiaTTSSettings from pipecat.services.deepgram.stt import DeepgramSTTService from pipecat.transports.base_transport import BaseTransport, TransportParams @@ -60,7 +60,9 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): llm = AnthropicLLMService( api_key=os.getenv("ANTHROPIC_API_KEY"), - system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way. You are also able to describe images.", + settings=AnthropicLLMSettings( + system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way. You are also able to describe images.", + ), ) context = LLMContext() diff --git a/examples/foundational/12b-describe-image-aws.py b/examples/foundational/12b-describe-image-aws.py index b4db59409..eaa5e3d19 100644 --- a/examples/foundational/12b-describe-image-aws.py +++ b/examples/foundational/12b-describe-image-aws.py @@ -66,8 +66,8 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): # Here we can't because AWS Bedrock doesn't support it for Claude 3.7, # which we need for image input. params=AWSBedrockLLMService.InputParams(temperature=0.8), + system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way. You are also able to describe images.", ), - system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way. You are also able to describe images.", ) context = LLMContext() diff --git a/examples/foundational/12c-describe-image-gemini-flash.py b/examples/foundational/12c-describe-image-gemini-flash.py index 1f550dd6f..2e76eff19 100644 --- a/examples/foundational/12c-describe-image-gemini-flash.py +++ b/examples/foundational/12c-describe-image-gemini-flash.py @@ -25,7 +25,7 @@ from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport from pipecat.services.cartesia.tts import CartesiaTTSService, CartesiaTTSSettings from pipecat.services.deepgram.stt import DeepgramSTTService -from pipecat.services.google.llm import GoogleLLMService +from pipecat.services.google.llm import GoogleLLMService, GoogleLLMSettings from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams @@ -60,7 +60,9 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): llm = GoogleLLMService( api_key=os.getenv("GOOGLE_API_KEY"), - system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way. You are also able to describe images.", + settings=GoogleLLMSettings( + system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way. You are also able to describe images.", + ), ) context = LLMContext() diff --git a/examples/foundational/14-function-calling.py b/examples/foundational/14-function-calling.py index 2a3206dbc..81cddec90 100644 --- a/examples/foundational/14-function-calling.py +++ b/examples/foundational/14-function-calling.py @@ -26,7 +26,7 @@ from pipecat.runner.utils import create_transport from pipecat.services.cartesia.tts import CartesiaTTSService, CartesiaTTSSettings from pipecat.services.deepgram.stt import DeepgramSTTService from pipecat.services.llm_service import FunctionCallParams -from pipecat.services.openai.llm import OpenAILLMService +from pipecat.services.openai.llm import OpenAILLMService, OpenAILLMSettings from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams @@ -74,7 +74,9 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): llm = OpenAILLMService( api_key=os.getenv("OPENAI_API_KEY"), - system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + settings=OpenAILLMSettings( + system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + ), ) # You can also register a function_name of None to get all functions diff --git a/examples/foundational/14a-function-calling-anthropic.py b/examples/foundational/14a-function-calling-anthropic.py index 0fd40af4f..19bc314b8 100644 --- a/examples/foundational/14a-function-calling-anthropic.py +++ b/examples/foundational/14a-function-calling-anthropic.py @@ -24,7 +24,7 @@ from pipecat.processors.aggregators.llm_response_universal import ( ) from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport -from pipecat.services.anthropic.llm import AnthropicLLMService +from pipecat.services.anthropic.llm import AnthropicLLMService, AnthropicLLMSettings from pipecat.services.cartesia.tts import CartesiaTTSService, CartesiaTTSSettings from pipecat.services.deepgram.stt import DeepgramSTTService from pipecat.services.llm_service import FunctionCallParams @@ -76,7 +76,9 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): llm = AnthropicLLMService( api_key=os.getenv("ANTHROPIC_API_KEY"), - system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + settings=AnthropicLLMSettings( + system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + ), ) llm.register_function("get_weather", get_weather) llm.register_function("get_restaurant_recommendation", fetch_restaurant_recommendation) diff --git a/examples/foundational/14c-function-calling-together.py b/examples/foundational/14c-function-calling-together.py index 6362e1ea6..66ed02c15 100644 --- a/examples/foundational/14c-function-calling-together.py +++ b/examples/foundational/14c-function-calling-together.py @@ -73,8 +73,8 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): api_key=os.getenv("TOGETHER_API_KEY"), settings=TogetherLLMSettings( model="meta-llama/Meta-Llama-3.1-70B-Instruct-Turbo", + system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", ), - system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", ) # You can also register a function_name of None to get all functions # sent to the same callback with an additional function_name parameter. diff --git a/examples/foundational/14d-function-calling-anthropic-video.py b/examples/foundational/14d-function-calling-anthropic-video.py index fee17734c..f1e097902 100644 --- a/examples/foundational/14d-function-calling-anthropic-video.py +++ b/examples/foundational/14d-function-calling-anthropic-video.py @@ -28,7 +28,7 @@ from pipecat.runner.utils import ( get_transport_client_id, maybe_capture_participant_camera, ) -from pipecat.services.anthropic.llm import AnthropicLLMService +from pipecat.services.anthropic.llm import AnthropicLLMService, AnthropicLLMSettings from pipecat.services.cartesia.tts import CartesiaTTSService, CartesiaTTSSettings from pipecat.services.deepgram.stt import DeepgramSTTService from pipecat.services.llm_service import FunctionCallParams @@ -98,7 +98,9 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): # Anthropic for vision analysis llm = AnthropicLLMService( api_key=os.getenv("ANTHROPIC_API_KEY"), - system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way. You are able to describe images from the user camera.", + settings=AnthropicLLMSettings( + system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way. You are able to describe images from the user camera.", + ), ) llm.register_function("fetch_user_image", fetch_user_image) diff --git a/examples/foundational/14d-function-calling-aws-video.py b/examples/foundational/14d-function-calling-aws-video.py index 234552d92..09ceaedd4 100644 --- a/examples/foundational/14d-function-calling-aws-video.py +++ b/examples/foundational/14d-function-calling-aws-video.py @@ -104,8 +104,8 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): # Here we can't because AWS Bedrock doesn't support it for Claude 3.7, # which we need for image input. temperature=0.8, + system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way. You are able to describe images from the user camera.", ), - system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way. You are able to describe images from the user camera.", ) llm.register_function("fetch_user_image", fetch_user_image) diff --git a/examples/foundational/14d-function-calling-gemini-flash-video.py b/examples/foundational/14d-function-calling-gemini-flash-video.py index f1255d287..a56349f96 100644 --- a/examples/foundational/14d-function-calling-gemini-flash-video.py +++ b/examples/foundational/14d-function-calling-gemini-flash-video.py @@ -30,7 +30,7 @@ from pipecat.runner.utils import ( ) from pipecat.services.cartesia.tts import CartesiaTTSService, CartesiaTTSSettings from pipecat.services.deepgram.stt import DeepgramSTTService -from pipecat.services.google.llm import GoogleLLMService +from pipecat.services.google.llm import GoogleLLMService, GoogleLLMSettings from pipecat.services.llm_service import FunctionCallParams from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams @@ -98,7 +98,9 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): # Google Gemini model for vision analysis llm = GoogleLLMService( api_key=os.getenv("GOOGLE_API_KEY"), - system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way. You are able to describe images from the user camera.", + settings=GoogleLLMSettings( + system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way. You are able to describe images from the user camera.", + ), ) llm.register_function("fetch_user_image", fetch_user_image) diff --git a/examples/foundational/14d-function-calling-moondream-video.py b/examples/foundational/14d-function-calling-moondream-video.py index 6ffb10213..c32bf3549 100644 --- a/examples/foundational/14d-function-calling-moondream-video.py +++ b/examples/foundational/14d-function-calling-moondream-video.py @@ -41,7 +41,7 @@ from pipecat.services.cartesia.tts import CartesiaTTSService, CartesiaTTSSetting from pipecat.services.deepgram.stt import DeepgramSTTService from pipecat.services.llm_service import FunctionCallParams from pipecat.services.moondream.vision import MoondreamService -from pipecat.services.openai.llm import OpenAILLMService +from pipecat.services.openai.llm import OpenAILLMService, OpenAILLMSettings from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams @@ -128,7 +128,9 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): llm = OpenAILLMService( api_key=os.getenv("OPENAI_API_KEY"), - system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way. You are able to describe images from the user camera.", + settings=OpenAILLMSettings( + system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way. You are able to describe images from the user camera.", + ), ) llm.register_function("fetch_user_image", fetch_user_image) diff --git a/examples/foundational/14d-function-calling-openai-video.py b/examples/foundational/14d-function-calling-openai-video.py index 235815a5c..5bfa336aa 100644 --- a/examples/foundational/14d-function-calling-openai-video.py +++ b/examples/foundational/14d-function-calling-openai-video.py @@ -32,7 +32,7 @@ from pipecat.runner.utils import ( from pipecat.services.cartesia.tts import CartesiaTTSService, CartesiaTTSSettings from pipecat.services.deepgram.stt import DeepgramSTTService from pipecat.services.llm_service import FunctionCallParams -from pipecat.services.openai.llm import OpenAILLMService +from pipecat.services.openai.llm import OpenAILLMService, OpenAILLMSettings from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams @@ -98,7 +98,9 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): llm = OpenAILLMService( api_key=os.getenv("OPENAI_API_KEY"), - system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way. You are able to describe images from the user camera.", + settings=OpenAILLMSettings( + system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way. You are able to describe images from the user camera.", + ), ) llm.register_function("fetch_user_image", fetch_user_image) diff --git a/examples/foundational/14e-function-calling-google.py b/examples/foundational/14e-function-calling-google.py index 08308dee3..19a0392b9 100644 --- a/examples/foundational/14e-function-calling-google.py +++ b/examples/foundational/14e-function-calling-google.py @@ -31,7 +31,7 @@ from pipecat.runner.utils import ( ) from pipecat.services.cartesia.tts import CartesiaTTSService, CartesiaTTSSettings from pipecat.services.deepgram.stt import DeepgramSTTService -from pipecat.services.google.llm import GoogleLLMService +from pipecat.services.google.llm import GoogleLLMService, GoogleLLMSettings from pipecat.services.llm_service import FunctionCallParams from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams @@ -126,7 +126,9 @@ indicate you should use the get_image tool are: llm = GoogleLLMService( api_key=os.getenv("GOOGLE_API_KEY"), - system_instruction=system_prompt, + settings=GoogleLLMSettings( + system_instruction=system_prompt, + ), ) llm.register_function("get_weather", get_weather) llm.register_function("get_image", get_image) diff --git a/examples/foundational/14f-function-calling-groq.py b/examples/foundational/14f-function-calling-groq.py index 11bbda12d..1b66e7e90 100644 --- a/examples/foundational/14f-function-calling-groq.py +++ b/examples/foundational/14f-function-calling-groq.py @@ -25,7 +25,7 @@ from pipecat.processors.aggregators.llm_response_universal import ( from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport from pipecat.services.cartesia.tts import CartesiaTTSService, CartesiaTTSSettings -from pipecat.services.groq.llm import GroqLLMService +from pipecat.services.groq.llm import GroqLLMService, GroqLLMSettings from pipecat.services.groq.stt import GroqSTTService from pipecat.services.llm_service import FunctionCallParams from pipecat.transports.base_transport import BaseTransport, TransportParams @@ -71,7 +71,9 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): llm = GroqLLMService( api_key=os.getenv("GROQ_API_KEY"), - system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + settings=GroqLLMSettings( + system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + ), ) # You can also register a function_name of None to get all functions # sent to the same callback with an additional function_name parameter. diff --git a/examples/foundational/14g-function-calling-grok.py b/examples/foundational/14g-function-calling-grok.py index 7ff89658d..eb607a5b8 100644 --- a/examples/foundational/14g-function-calling-grok.py +++ b/examples/foundational/14g-function-calling-grok.py @@ -26,7 +26,7 @@ from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport from pipecat.services.cartesia.tts import CartesiaTTSService, CartesiaTTSSettings from pipecat.services.deepgram.stt import DeepgramSTTService -from pipecat.services.grok.llm import GrokLLMService +from pipecat.services.grok.llm import GrokLLMService, GrokLLMSettings from pipecat.services.llm_service import FunctionCallParams from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams @@ -71,7 +71,9 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): llm = GrokLLMService( api_key=os.getenv("GROK_API_KEY"), - system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + settings=GrokLLMSettings( + system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + ), ) # You can also register a function_name of None to get all functions # sent to the same callback with an additional function_name parameter. diff --git a/examples/foundational/14h-function-calling-azure.py b/examples/foundational/14h-function-calling-azure.py index 9df6abeef..7eb3cb9de 100644 --- a/examples/foundational/14h-function-calling-azure.py +++ b/examples/foundational/14h-function-calling-azure.py @@ -74,8 +74,8 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): endpoint=os.getenv("AZURE_CHATGPT_ENDPOINT"), settings=AzureLLMSettings( model=os.getenv("AZURE_CHATGPT_MODEL"), + system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", ), - system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", ) # You can also register a function_name of None to get all functions # sent to the same callback with an additional function_name parameter. diff --git a/examples/foundational/14i-function-calling-fireworks.py b/examples/foundational/14i-function-calling-fireworks.py index 6a274c09f..aad4b6ecf 100644 --- a/examples/foundational/14i-function-calling-fireworks.py +++ b/examples/foundational/14i-function-calling-fireworks.py @@ -73,8 +73,8 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): api_key=os.getenv("FIREWORKS_API_KEY"), settings=FireworksLLMSettings( model="accounts/fireworks/models/gpt-oss-20b", + system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", ), - system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", ) # You can also register a function_name of None to get all functions # sent to the same callback with an additional function_name parameter. diff --git a/examples/foundational/14j-function-calling-nvidia.py b/examples/foundational/14j-function-calling-nvidia.py index 680952d75..87c6812e8 100644 --- a/examples/foundational/14j-function-calling-nvidia.py +++ b/examples/foundational/14j-function-calling-nvidia.py @@ -75,8 +75,8 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): model="nvidia/llama-3.3-nemotron-super-49b-v1.5", # Recommended when turning thinking off temperature=0.0, + system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", ), - system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", ) # You can also register a function_name of None to get all functions # sent to the same callback with an additional function_name parameter. diff --git a/examples/foundational/14k-function-calling-cerebras.py b/examples/foundational/14k-function-calling-cerebras.py index 118062769..4bbcf3f8e 100644 --- a/examples/foundational/14k-function-calling-cerebras.py +++ b/examples/foundational/14k-function-calling-cerebras.py @@ -25,7 +25,7 @@ from pipecat.processors.aggregators.llm_response_universal import ( from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport from pipecat.services.cartesia.tts import CartesiaTTSService, CartesiaTTSSettings -from pipecat.services.cerebras.llm import CerebrasLLMService +from pipecat.services.cerebras.llm import CerebrasLLMService, CerebrasLLMSettings from pipecat.services.deepgram.stt import DeepgramSTTService from pipecat.services.llm_service import FunctionCallParams from pipecat.transports.base_transport import BaseTransport, TransportParams @@ -71,7 +71,8 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): llm = CerebrasLLMService( api_key=os.getenv("CEREBRAS_API_KEY"), - system_instruction="""You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. + settings=CerebrasLLMSettings( + system_instruction="""You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. You have one functions available: @@ -82,6 +83,7 @@ Infer whether to use Fahrenheit or Celsius automatically based on the location, Start by asking me for my location. Then, use 'get_weather_current' to give me a forecast. Respond to what the user said in a creative and helpful way.""", + ), ) # You can also register a function_name of None to get all functions # sent to the same callback with an additional function_name parameter. diff --git a/examples/foundational/14l-function-calling-deepseek.py b/examples/foundational/14l-function-calling-deepseek.py index 9c2068236..425a58ec6 100644 --- a/examples/foundational/14l-function-calling-deepseek.py +++ b/examples/foundational/14l-function-calling-deepseek.py @@ -73,8 +73,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): api_key=os.getenv("DEEPSEEK_API_KEY"), settings=DeepSeekLLMSettings( model="deepseek-chat", - ), - system_instruction="""You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. + system_instruction="""You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. You have one functions available: @@ -85,6 +84,7 @@ Infer whether to use Fahrenheit or Celsius automatically based on the location, Start by asking me for my location. Then, use 'get_weather_current' to give me a forecast. Respond to what the user said in a creative and helpful way.""", + ), ) # You can also register a function_name of None to get all functions # sent to the same callback with an additional function_name parameter. diff --git a/examples/foundational/14m-function-calling-openrouter.py b/examples/foundational/14m-function-calling-openrouter.py index dbcd1813f..fd39ef7af 100644 --- a/examples/foundational/14m-function-calling-openrouter.py +++ b/examples/foundational/14m-function-calling-openrouter.py @@ -77,8 +77,8 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): api_key=os.getenv("OPENROUTER_API_KEY"), settings=OpenRouterLLMSettings( model="openai/gpt-4o-2024-11-20", + system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", ), - system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", ) # You can also register a function_name of None to get all functions # sent to the same callback with an additional function_name parameter. diff --git a/examples/foundational/14n-function-calling-perplexity.py b/examples/foundational/14n-function-calling-perplexity.py index 4857b614f..78d397656 100644 --- a/examples/foundational/14n-function-calling-perplexity.py +++ b/examples/foundational/14n-function-calling-perplexity.py @@ -30,7 +30,7 @@ from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport from pipecat.services.cartesia.tts import CartesiaTTSService, CartesiaTTSSettings from pipecat.services.deepgram.stt import DeepgramSTTService -from pipecat.services.perplexity.llm import PerplexityLLMService +from pipecat.services.perplexity.llm import PerplexityLLMService, PerplexityLLMSettings from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams @@ -69,7 +69,9 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): llm = PerplexityLLMService( api_key=os.getenv("PERPLEXITY_API_KEY"), - system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way, but try to be brief.", + settings=PerplexityLLMSettings( + system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way, but try to be brief.", + ), ) context = LLMContext() @@ -103,6 +105,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): async def on_client_connected(transport, client): logger.info(f"Client connected") # Kick off the conversation. + context.add_message({"role": "user", "content": "Please introduce yourself to the user."}) await task.queue_frames([LLMRunFrame()]) @transport.event_handler("on_client_disconnected") diff --git a/examples/foundational/14o-function-calling-gemini-openai-format.py b/examples/foundational/14o-function-calling-gemini-openai-format.py index 5eb8ff89d..82a77e4bb 100644 --- a/examples/foundational/14o-function-calling-gemini-openai-format.py +++ b/examples/foundational/14o-function-calling-gemini-openai-format.py @@ -26,7 +26,7 @@ from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport from pipecat.services.deepgram.stt import DeepgramSTTService from pipecat.services.elevenlabs.tts import ElevenLabsTTSService, ElevenLabsTTSSettings -from pipecat.services.google.llm_openai import GoogleLLMOpenAIBetaService +from pipecat.services.google.llm_openai import GoogleLLMOpenAIBetaService, OpenAILLMSettings from pipecat.services.llm_service import FunctionCallParams from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams @@ -71,7 +71,9 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): llm = GoogleLLMOpenAIBetaService( api_key=os.getenv("GOOGLE_API_KEY"), - system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + settings=OpenAILLMSettings( + system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + ), ) # You can aslo register a function_name of None to get all functions # sent to the same callback with an additional function_name parameter. diff --git a/examples/foundational/14p-function-calling-gemini-vertex-ai.py b/examples/foundational/14p-function-calling-gemini-vertex-ai.py index bf7b9458d..026e41e59 100644 --- a/examples/foundational/14p-function-calling-gemini-vertex-ai.py +++ b/examples/foundational/14p-function-calling-gemini-vertex-ai.py @@ -26,7 +26,7 @@ from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport from pipecat.services.deepgram.stt import DeepgramSTTService from pipecat.services.elevenlabs.tts import ElevenLabsTTSService, ElevenLabsTTSSettings -from pipecat.services.google.llm_vertex import GoogleVertexLLMService +from pipecat.services.google.llm_vertex import GoogleVertexLLMService, GoogleVertexLLMSettings from pipecat.services.llm_service import FunctionCallParams from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams @@ -73,7 +73,9 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): credentials=os.getenv("GOOGLE_VERTEX_TEST_CREDENTIALS"), project_id=os.getenv("GOOGLE_CLOUD_PROJECT_ID"), location=os.getenv("GOOGLE_CLOUD_LOCATION"), - system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + settings=GoogleVertexLLMSettings( + system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + ), ) # You can aslo register a function_name of None to get all functions # sent to the same callback with an additional function_name parameter. diff --git a/examples/foundational/14q-function-calling-qwen.py b/examples/foundational/14q-function-calling-qwen.py index 58d34a3e1..9aa1c3b91 100644 --- a/examples/foundational/14q-function-calling-qwen.py +++ b/examples/foundational/14q-function-calling-qwen.py @@ -27,7 +27,7 @@ from pipecat.runner.utils import create_transport from pipecat.services.cartesia.tts import CartesiaTTSService, CartesiaTTSSettings from pipecat.services.deepgram.stt import DeepgramSTTService from pipecat.services.llm_service import FunctionCallParams -from pipecat.services.qwen.llm import QwenLLMService +from pipecat.services.qwen.llm import QwenLLMService, QwenLLMSettings from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams @@ -72,7 +72,9 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): llm = QwenLLMService( api_key=os.getenv("QWEN_API_KEY"), model="qwen2.5-72b-instruct", - system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + settings=QwenLLMSettings( + system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + ), ) # You can also register a function_name of None to get all functions diff --git a/examples/foundational/14r-function-calling-aws.py b/examples/foundational/14r-function-calling-aws.py index 9d7e4e7a1..3693cba6c 100644 --- a/examples/foundational/14r-function-calling-aws.py +++ b/examples/foundational/14r-function-calling-aws.py @@ -78,8 +78,8 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): settings=AWSBedrockLLMSettings( model="us.anthropic.claude-haiku-4-5-20251001-v1:0", temperature=0.8, + system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", ), - system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", ) # You can also register a function_name of None to get all functions diff --git a/examples/foundational/14s-function-calling-sambanova.py b/examples/foundational/14s-function-calling-sambanova.py index 8cb007691..46ae742f3 100644 --- a/examples/foundational/14s-function-calling-sambanova.py +++ b/examples/foundational/14s-function-calling-sambanova.py @@ -26,7 +26,7 @@ from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport from pipecat.services.cartesia.tts import CartesiaTTSService, CartesiaTTSSettings from pipecat.services.llm_service import FunctionCallParams -from pipecat.services.sambanova.llm import SambaNovaLLMService +from pipecat.services.sambanova.llm import SambaNovaLLMService, SambaNovaLLMSettings from pipecat.services.sambanova.stt import SambaNovaSTTService from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams @@ -74,7 +74,9 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): llm = SambaNovaLLMService( api_key=os.getenv("SAMBANOVA_API_KEY"), - system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + settings=SambaNovaLLMSettings( + system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + ), ) # You can also register a function_name of None to get all functions # sent to the same callback with an additional function_name parameter. diff --git a/examples/foundational/14t-function-calling-direct.py b/examples/foundational/14t-function-calling-direct.py index b2912b91a..86a8d61b2 100644 --- a/examples/foundational/14t-function-calling-direct.py +++ b/examples/foundational/14t-function-calling-direct.py @@ -26,7 +26,7 @@ from pipecat.runner.utils import create_transport from pipecat.services.cartesia.tts import CartesiaTTSService, CartesiaTTSSettings from pipecat.services.deepgram.stt import DeepgramSTTService from pipecat.services.llm_service import FunctionCallParams -from pipecat.services.openai.llm import OpenAILLMService +from pipecat.services.openai.llm import OpenAILLMService, OpenAILLMSettings from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams @@ -87,7 +87,9 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): llm = OpenAILLMService( api_key=os.getenv("OPENAI_API_KEY"), - system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + settings=OpenAILLMSettings( + system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + ), ) # You can also register a function_name of None to get all functions diff --git a/examples/foundational/14u-function-calling-ollama.py b/examples/foundational/14u-function-calling-ollama.py index 53b81402d..761bab4a4 100644 --- a/examples/foundational/14u-function-calling-ollama.py +++ b/examples/foundational/14u-function-calling-ollama.py @@ -76,8 +76,8 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): llm = OLLamaLLMService( settings=OLLamaLLMSettings( model="llama3.2", + system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", ), - system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", ) # Update to the model you're running locally # You can also register a function_name of None to get all functions diff --git a/examples/foundational/14v-function-calling-openai.py b/examples/foundational/14v-function-calling-openai.py index 77bacc091..5e86632ec 100644 --- a/examples/foundational/14v-function-calling-openai.py +++ b/examples/foundational/14v-function-calling-openai.py @@ -24,7 +24,7 @@ from pipecat.processors.aggregators.llm_response_universal import ( from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport from pipecat.services.llm_service import FunctionCallParams -from pipecat.services.openai.llm import OpenAILLMService +from pipecat.services.openai.llm import OpenAILLMService, OpenAILLMSettings from pipecat.services.openai.stt import OpenAISTTService, OpenAISTTSettings from pipecat.services.openai.tts import OpenAITTSService, OpenAITTSSettings from pipecat.transports.base_transport import BaseTransport, TransportParams @@ -82,7 +82,9 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): # model choices: gpt-4o, gpt-4.1, etc. llm = OpenAILLMService( api_key=os.getenv("OPENAI_API_KEY"), - system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + settings=OpenAILLMSettings( + system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + ), ) # You can also register a function_name of None to get all functions diff --git a/examples/foundational/14w-function-calling-mistral.py b/examples/foundational/14w-function-calling-mistral.py index fa809414b..ce535c3ef 100644 --- a/examples/foundational/14w-function-calling-mistral.py +++ b/examples/foundational/14w-function-calling-mistral.py @@ -26,7 +26,7 @@ from pipecat.runner.utils import create_transport from pipecat.services.cartesia.tts import CartesiaTTSService, CartesiaTTSSettings from pipecat.services.deepgram.stt import DeepgramSTTService from pipecat.services.llm_service import FunctionCallParams -from pipecat.services.mistral.llm import MistralLLMService +from pipecat.services.mistral.llm import MistralLLMService, MistralLLMSettings from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams @@ -74,7 +74,9 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): llm = MistralLLMService( api_key=os.getenv("MISTRAL_API_KEY"), - system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + settings=MistralLLMSettings( + system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + ), ) # You can also register a function_name of None to get all functions diff --git a/examples/foundational/14x-function-calling-openpipe.py b/examples/foundational/14x-function-calling-openpipe.py index 61382c435..4f6898f5c 100644 --- a/examples/foundational/14x-function-calling-openpipe.py +++ b/examples/foundational/14x-function-calling-openpipe.py @@ -27,7 +27,7 @@ from pipecat.runner.utils import create_transport from pipecat.services.cartesia.tts import CartesiaTTSService, CartesiaTTSSettings from pipecat.services.deepgram.stt import DeepgramSTTService from pipecat.services.llm_service import FunctionCallParams -from pipecat.services.openpipe.llm import OpenPipeLLMService +from pipecat.services.openpipe.llm import OpenPipeLLMService, OpenPipeLLMSettings from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams @@ -78,7 +78,9 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): api_key=os.getenv("OPENAI_API_KEY"), openpipe_api_key=os.getenv("OPENPIPE_API_KEY"), tags={"conversation_id": f"pipecat-{timestamp}"}, - system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + settings=OpenPipeLLMSettings( + system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + ), ) # You can also register a function_name of None to get all functions diff --git a/examples/foundational/15-switch-voices.py b/examples/foundational/15-switch-voices.py index f749a03c7..c298aaf0f 100644 --- a/examples/foundational/15-switch-voices.py +++ b/examples/foundational/15-switch-voices.py @@ -29,7 +29,7 @@ from pipecat.runner.utils import create_transport from pipecat.services.cartesia.tts import CartesiaTTSService, CartesiaTTSSettings from pipecat.services.deepgram.stt import DeepgramSTTService from pipecat.services.llm_service import FunctionCallParams -from pipecat.services.openai.llm import OpenAILLMService +from pipecat.services.openai.llm import OpenAILLMService, OpenAILLMSettings from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams @@ -120,7 +120,9 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): llm = OpenAILLMService( api_key=os.getenv("OPENAI_API_KEY"), - system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities. Respond to what the user said in a creative and helpful way. Your output should not include non-alphanumeric characters. You can do the following voices: 'News Lady', 'British Lady' and 'Barbershop Man'.", + settings=OpenAILLMSettings( + system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities. Respond to what the user said in a creative and helpful way. Your output should not include non-alphanumeric characters. You can do the following voices: 'News Lady', 'British Lady' and 'Barbershop Man'.", + ), ) llm.register_function("switch_voice", tts.switch_voice) diff --git a/examples/foundational/15a-switch-languages.py b/examples/foundational/15a-switch-languages.py index dad7e0ee3..c19038ea2 100644 --- a/examples/foundational/15a-switch-languages.py +++ b/examples/foundational/15a-switch-languages.py @@ -30,7 +30,7 @@ from pipecat.runner.utils import create_transport from pipecat.services.cartesia.tts import CartesiaTTSService, CartesiaTTSSettings from pipecat.services.deepgram.stt import DeepgramSTTService from pipecat.services.llm_service import FunctionCallParams -from pipecat.services.openai.llm import OpenAILLMService +from pipecat.services.openai.llm import OpenAILLMService, OpenAILLMSettings from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams @@ -109,7 +109,9 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): llm = OpenAILLMService( api_key=os.getenv("OPENAI_API_KEY"), - system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities. Respond to what the user said in a creative and helpful way. Your output should not include non-alphanumeric characters. You can speak the following languages: 'English' and 'Spanish'.", + settings=OpenAILLMSettings( + system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities. Respond to what the user said in a creative and helpful way. Your output should not include non-alphanumeric characters. You can speak the following languages: 'English' and 'Spanish'.", + ), ) llm.register_function("switch_language", tts.switch_language) diff --git a/examples/foundational/16-gpu-container-local-bot.py b/examples/foundational/16-gpu-container-local-bot.py index cf02b37ce..103b5216f 100644 --- a/examples/foundational/16-gpu-container-local-bot.py +++ b/examples/foundational/16-gpu-container-local-bot.py @@ -72,9 +72,9 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): # Or, to use a local vLLM (or similar) api server settings=OpenAILLMSettings( model="meta-llama/Meta-Llama-3-8B-Instruct", + system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", ), base_url="http://0.0.0.0:8000/v1", - system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", ) context = LLMContext() diff --git a/examples/foundational/17-detect-user-idle.py b/examples/foundational/17-detect-user-idle.py index 9da863bc9..ecb7ceea1 100644 --- a/examples/foundational/17-detect-user-idle.py +++ b/examples/foundational/17-detect-user-idle.py @@ -35,7 +35,7 @@ from pipecat.runner.utils import create_transport from pipecat.services.cartesia.tts import CartesiaTTSService, CartesiaTTSSettings from pipecat.services.deepgram.stt import DeepgramSTTService from pipecat.services.llm_service import FunctionCallParams -from pipecat.services.openai.llm import OpenAILLMService +from pipecat.services.openai.llm import OpenAILLMService, OpenAILLMSettings from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams @@ -122,7 +122,9 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): llm = OpenAILLMService( api_key=os.getenv("OPENAI_API_KEY"), - system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + settings=OpenAILLMSettings( + system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + ), ) llm.register_function("get_current_weather", fetch_weather_from_api) diff --git a/examples/foundational/21-tavus-transport.py b/examples/foundational/21-tavus-transport.py index 06d904c21..7936a4555 100644 --- a/examples/foundational/21-tavus-transport.py +++ b/examples/foundational/21-tavus-transport.py @@ -24,7 +24,7 @@ from pipecat.processors.aggregators.llm_response_universal import ( ) from pipecat.services.cartesia.tts import CartesiaTTSService, CartesiaTTSSettings from pipecat.services.deepgram.stt import DeepgramSTTService -from pipecat.services.google.llm import GoogleLLMService +from pipecat.services.google.llm import GoogleLLMService, GoogleLLMSettings from pipecat.transports.tavus.transport import TavusParams, TavusTransport load_dotenv(override=True) @@ -58,7 +58,9 @@ async def main(): llm = GoogleLLMService( api_key=os.getenv("GOOGLE_API_KEY"), - system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + settings=GoogleLLMSettings( + system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + ), ) context = LLMContext() diff --git a/examples/foundational/21a-tavus-video-service.py b/examples/foundational/21a-tavus-video-service.py index c756a7821..fd2ff5880 100644 --- a/examples/foundational/21a-tavus-video-service.py +++ b/examples/foundational/21a-tavus-video-service.py @@ -25,7 +25,7 @@ from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport from pipecat.services.cartesia.tts import CartesiaTTSService, CartesiaTTSSettings from pipecat.services.deepgram.stt import DeepgramSTTService -from pipecat.services.google.llm import GoogleLLMService +from pipecat.services.google.llm import GoogleLLMService, GoogleLLMSettings from pipecat.services.tavus.video import TavusVideoService from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams @@ -68,7 +68,9 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): llm = GoogleLLMService( api_key=os.getenv("GOOGLE_API_KEY"), - system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + settings=GoogleLLMSettings( + system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + ), ) tavus = TavusVideoService( diff --git a/examples/foundational/22-filter-incomplete-turns.py b/examples/foundational/22-filter-incomplete-turns.py index 876999bcd..6d5af6be8 100644 --- a/examples/foundational/22-filter-incomplete-turns.py +++ b/examples/foundational/22-filter-incomplete-turns.py @@ -37,7 +37,7 @@ from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport from pipecat.services.cartesia.tts import CartesiaTTSService, CartesiaTTSSettings from pipecat.services.deepgram.stt import DeepgramSTTService -from pipecat.services.openai.llm import OpenAILLMService +from pipecat.services.openai.llm import OpenAILLMService, OpenAILLMSettings from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams @@ -70,7 +70,9 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): llm = OpenAILLMService( api_key=os.getenv("OPENAI_API_KEY"), - system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + settings=OpenAILLMSettings( + system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + ), ) tts = CartesiaTTSService( diff --git a/examples/foundational/23-bot-background-sound.py b/examples/foundational/23-bot-background-sound.py index a88ebc9bc..ad82ab8c3 100644 --- a/examples/foundational/23-bot-background-sound.py +++ b/examples/foundational/23-bot-background-sound.py @@ -26,7 +26,7 @@ from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport from pipecat.services.cartesia.tts import CartesiaTTSService, CartesiaTTSSettings from pipecat.services.deepgram.stt import DeepgramSTTService -from pipecat.services.openai.llm import OpenAILLMService +from pipecat.services.openai.llm import OpenAILLMService, OpenAILLMSettings from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams @@ -82,7 +82,9 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): llm = OpenAILLMService( api_key=os.getenv("OPENAI_API_KEY"), - system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + settings=OpenAILLMSettings( + system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + ), ) context = LLMContext() diff --git a/examples/foundational/24-user-mute-strategy.py b/examples/foundational/24-user-mute-strategy.py index d4276f04a..ab206de73 100644 --- a/examples/foundational/24-user-mute-strategy.py +++ b/examples/foundational/24-user-mute-strategy.py @@ -28,7 +28,7 @@ from pipecat.runner.utils import create_transport from pipecat.services.deepgram.stt import DeepgramSTTService from pipecat.services.deepgram.tts import DeepgramTTSService, DeepgramTTSSettings from pipecat.services.llm_service import FunctionCallParams -from pipecat.services.openai.llm import OpenAILLMService +from pipecat.services.openai.llm import OpenAILLMService, OpenAILLMSettings from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams @@ -80,7 +80,9 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): llm = OpenAILLMService( api_key=os.getenv("OPENAI_API_KEY"), - system_instruction="You are a helpful assistant who can check the weather. Always check the weather when a location is mentioned. Respond concisely and naturally. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points.", + settings=OpenAILLMSettings( + system_instruction="You are a helpful assistant who can check the weather. Always check the weather when a location is mentioned. Respond concisely and naturally. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points.", + ), ) llm.register_function("get_current_weather", fetch_weather_from_api) diff --git a/examples/foundational/25-google-audio-in.py b/examples/foundational/25-google-audio-in.py index a278ea4b3..1a8d203cd 100644 --- a/examples/foundational/25-google-audio-in.py +++ b/examples/foundational/25-google-audio-in.py @@ -299,21 +299,21 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): name="Conversation", settings=GoogleLLMSettings( model="gemini-2.5-flash", + system_instruction=conversation_system_message, ), api_key=os.getenv("GOOGLE_API_KEY"), # we can give the GoogleLLMService a system instruction to use directly # in the GenerativeModel constructor. Let's do that rather than put # our system message in the messages list. - system_instruction=conversation_system_message, ) input_transcription_llm = GoogleLLMService( name="Transcription", settings=GoogleLLMSettings( model="gemini-2.5-flash", + system_instruction=transcriber_system_message, ), api_key=os.getenv("GOOGLE_API_KEY"), - system_instruction=transcriber_system_message, ) messages = [ diff --git a/examples/foundational/27-simli-layer.py b/examples/foundational/27-simli-layer.py index 05d0649d6..3120a1280 100644 --- a/examples/foundational/27-simli-layer.py +++ b/examples/foundational/27-simli-layer.py @@ -74,8 +74,8 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): api_key=os.getenv("OPENAI_API_KEY"), settings=OpenAILLMSettings( model="gpt-4o-mini", + system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", ), - system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", ) context = LLMContext() diff --git a/examples/foundational/28-user-assistant-turns.py b/examples/foundational/28-user-assistant-turns.py index d59ad3870..2a7cce980 100644 --- a/examples/foundational/28-user-assistant-turns.py +++ b/examples/foundational/28-user-assistant-turns.py @@ -26,7 +26,7 @@ from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport from pipecat.services.cartesia.tts import CartesiaTTSService, CartesiaTTSSettings from pipecat.services.deepgram.stt import DeepgramSTTService -from pipecat.services.openai.llm import OpenAILLMService +from pipecat.services.openai.llm import OpenAILLMService, OpenAILLMSettings from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams @@ -129,7 +129,9 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): llm = OpenAILLMService( api_key=os.getenv("OPENAI_API_KEY"), - system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative, helpful, and brief way.", + settings=OpenAILLMSettings( + system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative, helpful, and brief way.", + ), ) context = LLMContext() diff --git a/examples/foundational/29-turn-tracking-observer.py b/examples/foundational/29-turn-tracking-observer.py index 0dd164bd0..d83442456 100644 --- a/examples/foundational/29-turn-tracking-observer.py +++ b/examples/foundational/29-turn-tracking-observer.py @@ -30,7 +30,7 @@ from pipecat.runner.utils import create_transport from pipecat.services.cartesia.tts import CartesiaTTSService, CartesiaTTSSettings from pipecat.services.deepgram.stt import DeepgramSTTService from pipecat.services.llm_service import FunctionCallParams -from pipecat.services.openai.llm import OpenAILLMService +from pipecat.services.openai.llm import OpenAILLMService, OpenAILLMSettings from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams @@ -80,7 +80,9 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): llm = OpenAILLMService( api_key=os.getenv("OPENAI_API_KEY"), - system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + settings=OpenAILLMSettings( + system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + ), ) llm.register_function("get_current_weather", fetch_weather_from_api) diff --git a/examples/foundational/30-observer.py b/examples/foundational/30-observer.py index 5ee0bdaed..c730a2993 100644 --- a/examples/foundational/30-observer.py +++ b/examples/foundational/30-observer.py @@ -36,7 +36,7 @@ from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport from pipecat.services.cartesia.tts import CartesiaTTSService, CartesiaTTSSettings from pipecat.services.deepgram.stt import DeepgramSTTService -from pipecat.services.openai.llm import OpenAILLMService +from pipecat.services.openai.llm import OpenAILLMService, OpenAILLMSettings from pipecat.transports.base_input import BaseInputTransport from pipecat.transports.base_output import BaseOutputTransport from pipecat.transports.base_transport import BaseTransport, TransportParams @@ -111,7 +111,9 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): llm = OpenAILLMService( api_key=os.getenv("OPENAI_API_KEY"), - system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + settings=OpenAILLMSettings( + system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + ), ) context = LLMContext() diff --git a/examples/foundational/32-gemini-grounding-metadata.py b/examples/foundational/32-gemini-grounding-metadata.py index 2977e19bc..6c2b182f7 100644 --- a/examples/foundational/32-gemini-grounding-metadata.py +++ b/examples/foundational/32-gemini-grounding-metadata.py @@ -27,7 +27,7 @@ from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport from pipecat.services.cartesia.tts import CartesiaTTSService, CartesiaTTSSettings from pipecat.services.deepgram.stt import DeepgramSTTService -from pipecat.services.google.llm import GoogleLLMService, LLMSearchResponseFrame +from pipecat.services.google.llm import GoogleLLMService, GoogleLLMSettings, LLMSearchResponseFrame from pipecat.services.llm_service import LLMService from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams @@ -107,7 +107,9 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): # Initialize the Gemini Multimodal Live model llm = GoogleLLMService( api_key=os.getenv("GOOGLE_API_KEY"), - system_instruction=system_instruction, + settings=GoogleLLMSettings( + system_instruction=system_instruction, + ), tools=tools, ) diff --git a/examples/foundational/33-gemini-rag.py b/examples/foundational/33-gemini-rag.py index c34a9c83e..3b1ba6bb9 100644 --- a/examples/foundational/33-gemini-rag.py +++ b/examples/foundational/33-gemini-rag.py @@ -199,8 +199,8 @@ Your response will be turned into speech so use only simple words and punctuatio llm = GoogleLLMService( settings=GoogleLLMSettings( model=VOICE_MODEL, + system_instruction=system_prompt, ), - system_instruction=system_prompt, api_key=os.getenv("GOOGLE_API_KEY"), ) llm.register_function("query_knowledge_base", query_knowledge_base) diff --git a/examples/foundational/34-audio-recording.py b/examples/foundational/34-audio-recording.py index aa52c213a..2bc413ec2 100644 --- a/examples/foundational/34-audio-recording.py +++ b/examples/foundational/34-audio-recording.py @@ -65,7 +65,7 @@ from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport from pipecat.services.cartesia.tts import CartesiaTTSService, CartesiaTTSSettings from pipecat.services.deepgram.stt import DeepgramSTTService -from pipecat.services.openai.llm import OpenAILLMService +from pipecat.services.openai.llm import OpenAILLMService, OpenAILLMSettings from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams @@ -119,7 +119,9 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): llm = OpenAILLMService( api_key=os.getenv("OPENAI_API_KEY"), - system_instruction="You are a helpful assistant demonstrating audio recording capabilities. Keep your responses brief and clear.", + settings=OpenAILLMSettings( + system_instruction="You are a helpful assistant demonstrating audio recording capabilities. Keep your responses brief and clear.", + ), ) # Create audio buffer processor diff --git a/examples/foundational/35-pattern-pair-voice-switching.py b/examples/foundational/35-pattern-pair-voice-switching.py index c10e185b0..0c5c6256c 100644 --- a/examples/foundational/35-pattern-pair-voice-switching.py +++ b/examples/foundational/35-pattern-pair-voice-switching.py @@ -58,7 +58,7 @@ from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport from pipecat.services.cartesia.tts import CartesiaTTSService, CartesiaTTSSettings from pipecat.services.deepgram.stt import DeepgramSTTService -from pipecat.services.openai.llm import OpenAILLMService +from pipecat.services.openai.llm import OpenAILLMService, OpenAILLMSettings from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams @@ -186,7 +186,9 @@ Remember: Use narrator voice for EVERYTHING except the actual quoted dialogue."" # Initialize LLM llm = OpenAILLMService( api_key=os.getenv("OPENAI_API_KEY"), - system_instruction=system_prompt, + settings=OpenAILLMSettings( + system_instruction=system_prompt, + ), ) context = LLMContext() diff --git a/examples/foundational/36-user-email-gathering.py b/examples/foundational/36-user-email-gathering.py index 5bdb937d0..2f9c04fd8 100644 --- a/examples/foundational/36-user-email-gathering.py +++ b/examples/foundational/36-user-email-gathering.py @@ -27,7 +27,7 @@ from pipecat.runner.utils import create_transport from pipecat.services.cartesia.tts import CartesiaTTSService, CartesiaTTSSettings from pipecat.services.deepgram.stt import DeepgramSTTService from pipecat.services.llm_service import FunctionCallParams -from pipecat.services.openai.llm import OpenAILLMService +from pipecat.services.openai.llm import OpenAILLMService, OpenAILLMSettings from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams @@ -85,7 +85,9 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): llm = OpenAILLMService( api_key=os.getenv("OPENAI_API_KEY"), - system_instruction="You need to gather a valid email or emails from the user. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. If the user provides one or more email addresses confirm them with the user. Enclose all emails with tags, for example a@a.com.", + settings=OpenAILLMSettings( + system_instruction="You need to gather a valid email or emails from the user. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. If the user provides one or more email addresses confirm them with the user. Enclose all emails with tags, for example a@a.com.", + ), ) # You can aslo register a function_name of None to get all functions # sent to the same callback with an additional function_name parameter. diff --git a/examples/foundational/37-mem0.py b/examples/foundational/37-mem0.py index e02d86915..5e9dc351d 100644 --- a/examples/foundational/37-mem0.py +++ b/examples/foundational/37-mem0.py @@ -227,13 +227,13 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): api_key=os.getenv("OPENAI_API_KEY"), settings=OpenAILLMSettings( model="gpt-4o-mini", - ), - system_instruction="""You are a personal assistant. You can remember things about the person you are talking to. + system_instruction="""You are a personal assistant. You can remember things about the person you are talking to. Some Guidelines: - Make sure your responses are friendly yet short and concise. - If the user asks you to remember something, make sure to remember it. - Greet the user by their name if you know about it. """, + ), ) # Set up conversation context and management diff --git a/examples/foundational/38-smart-turn-fal.py b/examples/foundational/38-smart-turn-fal.py index 384652b29..2eafe6297 100644 --- a/examples/foundational/38-smart-turn-fal.py +++ b/examples/foundational/38-smart-turn-fal.py @@ -26,7 +26,7 @@ from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport from pipecat.services.cartesia.tts import CartesiaTTSService, CartesiaTTSSettings from pipecat.services.deepgram.stt import DeepgramSTTService -from pipecat.services.openai.llm import OpenAILLMService +from pipecat.services.openai.llm import OpenAILLMService, OpenAILLMSettings from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams @@ -68,7 +68,9 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): llm = OpenAILLMService( api_key=os.getenv("OPENAI_API_KEY"), - system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + settings=OpenAILLMSettings( + system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + ), ) context = LLMContext() diff --git a/examples/foundational/38a-smart-turn-local-coreml.py b/examples/foundational/38a-smart-turn-local-coreml.py index 01585982d..4ed17642b 100644 --- a/examples/foundational/38a-smart-turn-local-coreml.py +++ b/examples/foundational/38a-smart-turn-local-coreml.py @@ -25,7 +25,7 @@ from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport from pipecat.services.cartesia.tts import CartesiaTTSService, CartesiaTTSSettings from pipecat.services.deepgram.stt import DeepgramSTTService -from pipecat.services.openai.llm import OpenAILLMService +from pipecat.services.openai.llm import OpenAILLMService, OpenAILLMSettings from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams @@ -83,7 +83,9 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): llm = OpenAILLMService( api_key=os.getenv("OPENAI_API_KEY"), - system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + settings=OpenAILLMSettings( + system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + ), ) context = LLMContext() diff --git a/examples/foundational/38b-smart-turn-local.py b/examples/foundational/38b-smart-turn-local.py index aceff9bc9..361889a5b 100644 --- a/examples/foundational/38b-smart-turn-local.py +++ b/examples/foundational/38b-smart-turn-local.py @@ -26,7 +26,7 @@ from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport from pipecat.services.cartesia.tts import CartesiaTTSService, CartesiaTTSSettings from pipecat.services.deepgram.stt import DeepgramSTTService -from pipecat.services.openai.llm import OpenAILLMService +from pipecat.services.openai.llm import OpenAILLMService, OpenAILLMSettings from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams @@ -65,7 +65,9 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): llm = OpenAILLMService( api_key=os.getenv("OPENAI_API_KEY"), - system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + settings=OpenAILLMSettings( + system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + ), ) context = LLMContext() diff --git a/examples/foundational/39-mcp-stdio.py b/examples/foundational/39-mcp-stdio.py index 0919e2fb0..7e648cfd7 100644 --- a/examples/foundational/39-mcp-stdio.py +++ b/examples/foundational/39-mcp-stdio.py @@ -35,7 +35,7 @@ from pipecat.processors.aggregators.llm_response_universal import ( from pipecat.processors.frame_processor import FrameDirection, FrameProcessor from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport -from pipecat.services.anthropic.llm import AnthropicLLMService +from pipecat.services.anthropic.llm import AnthropicLLMService, AnthropicLLMSettings from pipecat.services.cartesia.tts import CartesiaTTSService, CartesiaTTSSettings from pipecat.services.deepgram.stt import DeepgramSTTService from pipecat.services.mcp_service import MCPClient @@ -155,7 +155,12 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): Just respond with short sentences when you are carrying out tool calls. """ - llm = AnthropicLLMService(api_key=os.getenv("ANTHROPIC_API_KEY"), system_instruction=system) + llm = AnthropicLLMService( + api_key=os.getenv("ANTHROPIC_API_KEY"), + settings=AnthropicLLMSettings( + system_instruction=system, + ), + ) try: mcp = MCPClient( diff --git a/examples/foundational/39c-multiple-mcp.py b/examples/foundational/39c-multiple-mcp.py index dcda884ec..e4612efa4 100644 --- a/examples/foundational/39c-multiple-mcp.py +++ b/examples/foundational/39c-multiple-mcp.py @@ -37,7 +37,7 @@ from pipecat.processors.aggregators.llm_response_universal import ( from pipecat.processors.frame_processor import FrameDirection, FrameProcessor from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport -from pipecat.services.anthropic.llm import AnthropicLLMService +from pipecat.services.anthropic.llm import AnthropicLLMService, AnthropicLLMSettings from pipecat.services.cartesia.tts import CartesiaTTSService, CartesiaTTSSettings from pipecat.services.deepgram.stt import DeepgramSTTService from pipecat.services.mcp_service import MCPClient @@ -139,7 +139,12 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): Just respond with short sentences when you are carrying out tool calls. """ - llm = AnthropicLLMService(api_key=os.getenv("ANTHROPIC_API_KEY"), system_instruction=system) + llm = AnthropicLLMService( + api_key=os.getenv("ANTHROPIC_API_KEY"), + settings=AnthropicLLMSettings( + system_instruction=system, + ), + ) try: rijksmuseum_mcp = MCPClient( diff --git a/examples/foundational/42-interruption-config.py b/examples/foundational/42-interruption-config.py index f8add9019..4c8e3ba23 100644 --- a/examples/foundational/42-interruption-config.py +++ b/examples/foundational/42-interruption-config.py @@ -24,7 +24,7 @@ from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport from pipecat.services.cartesia.tts import CartesiaTTSService, CartesiaTTSSettings from pipecat.services.deepgram.stt import DeepgramSTTService -from pipecat.services.openai.llm import OpenAILLMService +from pipecat.services.openai.llm import OpenAILLMService, OpenAILLMSettings from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams @@ -66,7 +66,9 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): llm = OpenAILLMService( api_key=os.getenv("OPENAI_API_KEY"), - system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + settings=OpenAILLMSettings( + system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + ), ) context = LLMContext() diff --git a/examples/foundational/43-heygen-transport.py b/examples/foundational/43-heygen-transport.py index 5797aeb25..ad0e20764 100644 --- a/examples/foundational/43-heygen-transport.py +++ b/examples/foundational/43-heygen-transport.py @@ -24,7 +24,7 @@ from pipecat.processors.aggregators.llm_response_universal import ( ) from pipecat.services.cartesia.tts import CartesiaTTSService, CartesiaTTSSettings from pipecat.services.deepgram.stt import DeepgramSTTService -from pipecat.services.google.llm import GoogleLLMService +from pipecat.services.google.llm import GoogleLLMService, GoogleLLMSettings from pipecat.services.heygen.api_liveavatar import LiveAvatarNewSessionRequest from pipecat.transports.heygen.transport import HeyGenParams, HeyGenTransport, ServiceType @@ -63,7 +63,9 @@ async def main(): llm = GoogleLLMService( api_key=os.getenv("GOOGLE_API_KEY"), - system_instruction="You are a helpful assistant. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Be succinct and respond to what the user said in a creative and helpful way.", + settings=GoogleLLMSettings( + system_instruction="You are a helpful assistant. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Be succinct and respond to what the user said in a creative and helpful way.", + ), ) context = LLMContext() diff --git a/examples/foundational/43a-heygen-video-service.py b/examples/foundational/43a-heygen-video-service.py index 5be8f1caa..e4bd0e460 100644 --- a/examples/foundational/43a-heygen-video-service.py +++ b/examples/foundational/43a-heygen-video-service.py @@ -24,7 +24,7 @@ from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport from pipecat.services.cartesia.tts import CartesiaTTSService, CartesiaTTSSettings from pipecat.services.deepgram.stt import DeepgramSTTService -from pipecat.services.google.llm import GoogleLLMService +from pipecat.services.google.llm import GoogleLLMService, GoogleLLMSettings from pipecat.services.heygen.api_liveavatar import LiveAvatarNewSessionRequest from pipecat.services.heygen.client import ServiceType from pipecat.services.heygen.video import HeyGenVideoService @@ -70,7 +70,9 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): llm = GoogleLLMService( api_key=os.getenv("GOOGLE_API_KEY"), - system_instruction="You are a helpful assistant. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Be succinct and respond to what the user said in a creative and helpful way.", + settings=GoogleLLMSettings( + system_instruction="You are a helpful assistant. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Be succinct and respond to what the user said in a creative and helpful way.", + ), ) heyGen = HeyGenVideoService( diff --git a/examples/foundational/44-voicemail-detection.py b/examples/foundational/44-voicemail-detection.py index e46c59cc0..ef7d73b38 100644 --- a/examples/foundational/44-voicemail-detection.py +++ b/examples/foundational/44-voicemail-detection.py @@ -24,7 +24,7 @@ from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport from pipecat.services.cartesia.tts import CartesiaTTSService, CartesiaTTSSettings from pipecat.services.deepgram.stt import DeepgramSTTService -from pipecat.services.openai.llm import OpenAILLMService +from pipecat.services.openai.llm import OpenAILLMService, OpenAILLMSettings from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams @@ -63,7 +63,9 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): llm = OpenAILLMService( api_key=os.getenv("OPENAI_API_KEY"), - system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + settings=OpenAILLMSettings( + system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + ), ) classifier_llm = OpenAILLMService(api_key=os.getenv("OPENAI_API_KEY")) diff --git a/examples/foundational/45-before-and-after-events.py b/examples/foundational/45-before-and-after-events.py index db71e283d..c06837a4b 100644 --- a/examples/foundational/45-before-and-after-events.py +++ b/examples/foundational/45-before-and-after-events.py @@ -24,7 +24,7 @@ from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport from pipecat.services.cartesia.tts import CartesiaTTSService, CartesiaTTSSettings from pipecat.services.deepgram.stt import DeepgramSTTService -from pipecat.services.openai.llm import OpenAILLMService +from pipecat.services.openai.llm import OpenAILLMService, OpenAILLMSettings from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams @@ -74,7 +74,9 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): llm = OpenAILLMService( api_key=os.getenv("OPENAI_API_KEY"), - system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + settings=OpenAILLMSettings( + system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + ), ) context = LLMContext() diff --git a/examples/foundational/47-sentry-metrics.py b/examples/foundational/47-sentry-metrics.py index f9983c46f..d024ed73a 100644 --- a/examples/foundational/47-sentry-metrics.py +++ b/examples/foundational/47-sentry-metrics.py @@ -25,7 +25,7 @@ from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport from pipecat.services.cartesia.tts import CartesiaTTSService, CartesiaTTSSettings from pipecat.services.deepgram.stt import DeepgramSTTService -from pipecat.services.openai.llm import OpenAILLMService +from pipecat.services.openai.llm import OpenAILLMService, OpenAILLMSettings from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams @@ -75,7 +75,9 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): llm = OpenAILLMService( api_key=os.getenv("OPENAI_API_KEY"), metrics=SentryMetrics(), - system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + settings=OpenAILLMSettings( + system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + ), ) context = LLMContext() diff --git a/examples/foundational/48-service-switcher.py b/examples/foundational/48-service-switcher.py index dd7d9ec82..d0e3f09ec 100644 --- a/examples/foundational/48-service-switcher.py +++ b/examples/foundational/48-service-switcher.py @@ -30,9 +30,9 @@ from pipecat.services.cartesia.stt import CartesiaSTTService from pipecat.services.cartesia.tts import CartesiaTTSService, CartesiaTTSSettings from pipecat.services.deepgram.stt import DeepgramSTTService from pipecat.services.deepgram.tts import DeepgramTTSService, DeepgramTTSSettings -from pipecat.services.google.llm import GoogleLLMService +from pipecat.services.google.llm import GoogleLLMService, GoogleLLMSettings from pipecat.services.llm_service import FunctionCallParams -from pipecat.services.openai.llm import OpenAILLMService +from pipecat.services.openai.llm import OpenAILLMService, OpenAILLMSettings from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams @@ -118,8 +118,14 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): system = "You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way." - llm_openai = OpenAILLMService(api_key=os.getenv("OPENAI_API_KEY"), system_instruction=system) - llm_google = GoogleLLMService(api_key=os.getenv("GOOGLE_API_KEY"), system_instruction=system) + llm_openai = OpenAILLMService( + api_key=os.getenv("OPENAI_API_KEY"), + settings=OpenAILLMSettings(system_instruction=system), + ) + llm_google = GoogleLLMService( + api_key=os.getenv("GOOGLE_API_KEY"), + settings=GoogleLLMSettings(system_instruction=system), + ) llm_switcher = LLMSwitcher( llms=[llm_openai, llm_google], strategy_type=ServiceSwitcherStrategyManual ) diff --git a/examples/foundational/49a-thinking-anthropic.py b/examples/foundational/49a-thinking-anthropic.py index fa84e7c6c..a222ad19f 100644 --- a/examples/foundational/49a-thinking-anthropic.py +++ b/examples/foundational/49a-thinking-anthropic.py @@ -72,8 +72,8 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): type="enabled", budget_tokens=2048, ), + system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", ), - system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", ) context = LLMContext() diff --git a/examples/foundational/49b-thinking-google.py b/examples/foundational/49b-thinking-google.py index 0fb0a30f0..05ec76f4c 100644 --- a/examples/foundational/49b-thinking-google.py +++ b/examples/foundational/49b-thinking-google.py @@ -69,8 +69,8 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): thinking_budget=-1, # Dynamic thinking include_thoughts=True, ), + system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", ), - system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", ) context = LLMContext() diff --git a/examples/foundational/49c-thinking-functions-anthropic.py b/examples/foundational/49c-thinking-functions-anthropic.py index 4fb66470d..977b49800 100644 --- a/examples/foundational/49c-thinking-functions-anthropic.py +++ b/examples/foundational/49c-thinking-functions-anthropic.py @@ -93,8 +93,8 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): type="enabled", budget_tokens=2048, ), + system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", ), - system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", ) llm.register_direct_function(check_flight_status) diff --git a/examples/foundational/49d-thinking-functions-google.py b/examples/foundational/49d-thinking-functions-google.py index 3963fc387..81b01f744 100644 --- a/examples/foundational/49d-thinking-functions-google.py +++ b/examples/foundational/49d-thinking-functions-google.py @@ -90,8 +90,8 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): thinking_budget=-1, # Dynamic thinking include_thoughts=True, ), + system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", ), - system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", ) llm.register_direct_function(check_flight_status) diff --git a/examples/foundational/52-live-translation.py b/examples/foundational/52-live-translation.py index 15598667f..a90eb3ce4 100644 --- a/examples/foundational/52-live-translation.py +++ b/examples/foundational/52-live-translation.py @@ -24,7 +24,7 @@ from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport from pipecat.services.cartesia.tts import CartesiaTTSService, CartesiaTTSSettings from pipecat.services.deepgram.stt import DeepgramSTTService -from pipecat.services.openai.llm import OpenAILLMService +from pipecat.services.openai.llm import OpenAILLMService, OpenAILLMSettings from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams @@ -66,7 +66,9 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): llm = OpenAILLMService( api_key=os.getenv("OPENAI_API_KEY"), - system_instruction="You are a live translation assistant. Your sole purpose is to translate English text into Spanish. When you receive English text from the user, immediately translate it into natural, fluent Spanish. Do not add explanations, commentary, or extra information—only provide the Spanish translation of the text you receive.", + settings=OpenAILLMSettings( + system_instruction="You are a live translation assistant. Your sole purpose is to translate English text into Spanish. When you receive English text from the user, immediately translate it into natural, fluent Spanish. Do not add explanations, commentary, or extra information—only provide the Spanish translation of the text you receive.", + ), ) context = LLMContext() diff --git a/examples/foundational/53-concurrent-llm-evaluation.py b/examples/foundational/53-concurrent-llm-evaluation.py index a93ca2ada..0ae0afa18 100644 --- a/examples/foundational/53-concurrent-llm-evaluation.py +++ b/examples/foundational/53-concurrent-llm-evaluation.py @@ -27,7 +27,7 @@ from pipecat.runner.utils import create_transport from pipecat.services.cartesia.tts import CartesiaTTSService, CartesiaTTSSettings from pipecat.services.deepgram.stt import DeepgramSTTService from pipecat.services.groq.llm import GroqLLMService, GroqLLMSettings -from pipecat.services.openai.llm import OpenAILLMService +from pipecat.services.openai.llm import OpenAILLMService, OpenAILLMSettings from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams @@ -69,13 +69,17 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): openai_llm = OpenAILLMService( api_key=os.getenv("OPENAI_API_KEY"), - system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + settings=OpenAILLMSettings( + system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + ), ) groq_llm = GroqLLMService( api_key=os.getenv("GROQ_API_KEY"), - settings=GroqLLMSettings(model="meta-llama/llama-4-maverick-17b-128e-instruct"), - system_instruction="You are a very helpful assistant. Your goal is to demonstrate your capabilities in detail in a creative and helpful way.", + settings=GroqLLMSettings( + model="meta-llama/llama-4-maverick-17b-128e-instruct", + system_instruction="You are a very helpful assistant. Your goal is to demonstrate your capabilities in detail in a creative and helpful way.", + ), ) openai_context = LLMContext() diff --git a/examples/foundational/53-concurrent-llm-rtvi-ignored-sources.py b/examples/foundational/53-concurrent-llm-rtvi-ignored-sources.py index f449269e9..d6b3feac3 100644 --- a/examples/foundational/53-concurrent-llm-rtvi-ignored-sources.py +++ b/examples/foundational/53-concurrent-llm-rtvi-ignored-sources.py @@ -33,7 +33,7 @@ from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport from pipecat.services.cartesia.tts import CartesiaTTSService, CartesiaTTSSettings from pipecat.services.deepgram.stt import DeepgramSTTService -from pipecat.services.openai.llm import OpenAILLMService +from pipecat.services.openai.llm import OpenAILLMService, OpenAILLMSettings from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams @@ -75,7 +75,9 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): # Main LLM — drives the conversation. Its RTVI events reach the client. main_llm = OpenAILLMService( api_key=os.getenv("OPENAI_API_KEY"), - system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + settings=OpenAILLMSettings( + system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + ), ) # Evaluator LLM — silently grades the user's message in the background. @@ -83,7 +85,9 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): evaluator_llm = OpenAILLMService( api_key=os.getenv("OPENAI_API_KEY"), name="EvaluatorLLM", - system_instruction="You are a silent quality evaluator. When given a user message, respond with a single JSON object: {'score': <1-5>, 'reason': ''}. Do not respond conversationally.", + settings=OpenAILLMSettings( + system_instruction="You are a silent quality evaluator. When given a user message, respond with a single JSON object: {'score': <1-5>, 'reason': ''}. Do not respond conversationally.", + ), ) main_context = LLMContext() diff --git a/examples/foundational/54-context-summarization-openai.py b/examples/foundational/54-context-summarization-openai.py index 8c7c38d62..897ed171f 100644 --- a/examples/foundational/54-context-summarization-openai.py +++ b/examples/foundational/54-context-summarization-openai.py @@ -37,7 +37,7 @@ from pipecat.runner.utils import create_transport from pipecat.services.cartesia.tts import CartesiaTTSService, CartesiaTTSSettings from pipecat.services.deepgram.stt import DeepgramSTTService from pipecat.services.llm_service import FunctionCallParams -from pipecat.services.openai.llm import OpenAILLMService +from pipecat.services.openai.llm import OpenAILLMService, OpenAILLMSettings from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams @@ -88,7 +88,9 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): llm = OpenAILLMService( api_key=os.getenv("OPENAI_API_KEY"), - system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way. You have access to tools to get the current weather - use them when relevant.", + settings=OpenAILLMSettings( + system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way. You have access to tools to get the current weather - use them when relevant.", + ), ) # Register tool functions diff --git a/examples/foundational/54a-context-summarization-google.py b/examples/foundational/54a-context-summarization-google.py index 21e2ef459..8242ea879 100644 --- a/examples/foundational/54a-context-summarization-google.py +++ b/examples/foundational/54a-context-summarization-google.py @@ -36,7 +36,7 @@ from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport from pipecat.services.cartesia.tts import CartesiaTTSService, CartesiaTTSSettings from pipecat.services.deepgram.stt import DeepgramSTTService -from pipecat.services.google import GoogleLLMService +from pipecat.services.google import GoogleLLMService, GoogleLLMSettings from pipecat.services.llm_service import FunctionCallParams from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams @@ -88,7 +88,9 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): llm = GoogleLLMService( api_key=os.getenv("GOOGLE_API_KEY"), - system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way. You have access to tools to get the current weather - use them when relevant.", + settings=GoogleLLMSettings( + system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way. You have access to tools to get the current weather - use them when relevant.", + ), ) # Register tool functions diff --git a/examples/foundational/54b-context-summarization-manual-openai.py b/examples/foundational/54b-context-summarization-manual-openai.py index 0fd2c0bd7..ae1e9bf14 100644 --- a/examples/foundational/54b-context-summarization-manual-openai.py +++ b/examples/foundational/54b-context-summarization-manual-openai.py @@ -37,7 +37,7 @@ from pipecat.runner.utils import create_transport from pipecat.services.cartesia.tts import CartesiaTTSService, CartesiaTTSSettings from pipecat.services.deepgram.stt import DeepgramSTTService from pipecat.services.llm_service import FunctionCallParams -from pipecat.services.openai.llm import OpenAILLMService +from pipecat.services.openai.llm import OpenAILLMService, OpenAILLMSettings from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams @@ -92,7 +92,12 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): that the conversation history has been compressed. """ - llm = OpenAILLMService(api_key=os.getenv("OPENAI_API_KEY"), system_instruction=system_prompt) + llm = OpenAILLMService( + api_key=os.getenv("OPENAI_API_KEY"), + settings=OpenAILLMSettings( + system_instruction=system_prompt, + ), + ) llm.register_function("summarize_conversation", summarize_conversation) diff --git a/examples/foundational/54c-context-summarization-dedicated-llm.py b/examples/foundational/54c-context-summarization-dedicated-llm.py index ce0f7658f..c3c4a0c2e 100644 --- a/examples/foundational/54c-context-summarization-dedicated-llm.py +++ b/examples/foundational/54c-context-summarization-dedicated-llm.py @@ -40,7 +40,7 @@ from pipecat.services.cartesia.tts import CartesiaTTSService, CartesiaTTSSetting from pipecat.services.deepgram.stt import DeepgramSTTService from pipecat.services.google.llm import GoogleLLMService, GoogleLLMSettings from pipecat.services.llm_service import FunctionCallParams -from pipecat.services.openai.llm import OpenAILLMService +from pipecat.services.openai.llm import OpenAILLMService, OpenAILLMSettings from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams @@ -108,7 +108,12 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): """ # Primary LLM for conversation (could be any provider) - llm = OpenAILLMService(api_key=os.getenv("OPENAI_API_KEY"), system_instruction=system_prompt) + llm = OpenAILLMService( + api_key=os.getenv("OPENAI_API_KEY"), + settings=OpenAILLMSettings( + system_instruction=system_prompt, + ), + ) # Dedicated cheap/fast LLM for summarization only summarization_llm = GoogleLLMService( diff --git a/examples/foundational/55a-update-settings-deepgram-flux-stt.py b/examples/foundational/55a-update-settings-deepgram-flux-stt.py index 0a507aaed..cd55f3e37 100644 --- a/examples/foundational/55a-update-settings-deepgram-flux-stt.py +++ b/examples/foundational/55a-update-settings-deepgram-flux-stt.py @@ -24,7 +24,7 @@ from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport from pipecat.services.cartesia.tts import CartesiaTTSService, CartesiaTTSSettings from pipecat.services.deepgram.flux.stt import DeepgramFluxSTTService, DeepgramFluxSTTSettings -from pipecat.services.openai.llm import OpenAILLMService +from pipecat.services.openai.llm import OpenAILLMService, OpenAILLMSettings from pipecat.transcriptions.language import Language from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams @@ -62,7 +62,9 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): llm = OpenAILLMService( api_key=os.getenv("OPENAI_API_KEY"), - system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + settings=OpenAILLMSettings( + system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + ), ) context = LLMContext() diff --git a/examples/foundational/55a-update-settings-deepgram-sagemaker-stt.py b/examples/foundational/55a-update-settings-deepgram-sagemaker-stt.py index b6f2142bc..af080e9db 100644 --- a/examples/foundational/55a-update-settings-deepgram-sagemaker-stt.py +++ b/examples/foundational/55a-update-settings-deepgram-sagemaker-stt.py @@ -28,7 +28,7 @@ from pipecat.services.deepgram.sagemaker.stt import ( DeepgramSageMakerSTTService, DeepgramSageMakerSTTSettings, ) -from pipecat.services.openai.llm import OpenAILLMService +from pipecat.services.openai.llm import OpenAILLMService, OpenAILLMSettings from pipecat.transcriptions.language import Language from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams @@ -69,7 +69,9 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): llm = OpenAILLMService( api_key=os.getenv("OPENAI_API_KEY"), - system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + settings=OpenAILLMSettings( + system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + ), ) context = LLMContext() diff --git a/examples/foundational/55a-update-settings-deepgram-stt.py b/examples/foundational/55a-update-settings-deepgram-stt.py index b914d8085..0519799f0 100644 --- a/examples/foundational/55a-update-settings-deepgram-stt.py +++ b/examples/foundational/55a-update-settings-deepgram-stt.py @@ -25,7 +25,7 @@ from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport from pipecat.services.cartesia.tts import CartesiaTTSService, CartesiaTTSSettings from pipecat.services.deepgram.stt import DeepgramSTTService, DeepgramSTTSettings -from pipecat.services.openai.llm import OpenAILLMService +from pipecat.services.openai.llm import OpenAILLMService, OpenAILLMSettings from pipecat.transcriptions.language import Language from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams @@ -63,7 +63,9 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): llm = OpenAILLMService( api_key=os.getenv("OPENAI_API_KEY"), - system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + settings=OpenAILLMSettings( + system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + ), ) context = LLMContext() diff --git a/examples/foundational/55b-update-settings-azure-stt.py b/examples/foundational/55b-update-settings-azure-stt.py index c54b1a0d8..c10f79de4 100644 --- a/examples/foundational/55b-update-settings-azure-stt.py +++ b/examples/foundational/55b-update-settings-azure-stt.py @@ -24,7 +24,7 @@ from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport from pipecat.services.azure.stt import AzureSTTService, AzureSTTSettings from pipecat.services.cartesia.tts import CartesiaTTSService, CartesiaTTSSettings -from pipecat.services.openai.llm import OpenAILLMService +from pipecat.services.openai.llm import OpenAILLMService, OpenAILLMSettings from pipecat.transcriptions.language import Language from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams @@ -65,7 +65,9 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): llm = OpenAILLMService( api_key=os.getenv("OPENAI_API_KEY"), - system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + settings=OpenAILLMSettings( + system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + ), ) context = LLMContext() diff --git a/examples/foundational/55c-update-settings-google-stt.py b/examples/foundational/55c-update-settings-google-stt.py index 23b312f5f..9c67a8039 100644 --- a/examples/foundational/55c-update-settings-google-stt.py +++ b/examples/foundational/55c-update-settings-google-stt.py @@ -24,7 +24,7 @@ from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport from pipecat.services.cartesia.tts import CartesiaTTSService, CartesiaTTSSettings from pipecat.services.google.stt import GoogleSTTService, GoogleSTTSettings -from pipecat.services.openai.llm import OpenAILLMService +from pipecat.services.openai.llm import OpenAILLMService, OpenAILLMSettings from pipecat.transcriptions.language import Language from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams @@ -62,7 +62,9 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): llm = OpenAILLMService( api_key=os.getenv("OPENAI_API_KEY"), - system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + settings=OpenAILLMSettings( + system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + ), ) context = LLMContext() diff --git a/examples/foundational/55d-update-settings-assemblyai-stt.py b/examples/foundational/55d-update-settings-assemblyai-stt.py index 9cd5641fd..1b8ca5eda 100644 --- a/examples/foundational/55d-update-settings-assemblyai-stt.py +++ b/examples/foundational/55d-update-settings-assemblyai-stt.py @@ -24,7 +24,7 @@ from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport from pipecat.services.assemblyai.stt import AssemblyAISTTService, AssemblyAISTTSettings from pipecat.services.cartesia.tts import CartesiaTTSService, CartesiaTTSSettings -from pipecat.services.openai.llm import OpenAILLMService +from pipecat.services.openai.llm import OpenAILLMService, OpenAILLMSettings from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams @@ -66,7 +66,9 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): llm = OpenAILLMService( api_key=os.getenv("OPENAI_API_KEY"), - system_instruction="You are a helpful LLM in a WebRTC call demonstrating dynamic keyterms updates. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Try saying difficult names like 'Xiomara', 'Saoirse', or 'Krzystof' to test transcription accuracy.", + settings=OpenAILLMSettings( + system_instruction="You are a helpful LLM in a WebRTC call demonstrating dynamic keyterms updates. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Try saying difficult names like 'Xiomara', 'Saoirse', or 'Krzystof' to test transcription accuracy.", + ), ) context = LLMContext() diff --git a/examples/foundational/55e-update-settings-gladia-stt.py b/examples/foundational/55e-update-settings-gladia-stt.py index 6cc3fc92a..24e0dfa6f 100644 --- a/examples/foundational/55e-update-settings-gladia-stt.py +++ b/examples/foundational/55e-update-settings-gladia-stt.py @@ -24,7 +24,7 @@ from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport from pipecat.services.cartesia.tts import CartesiaTTSService, CartesiaTTSSettings from pipecat.services.gladia.stt import GladiaSTTService, GladiaSTTSettings -from pipecat.services.openai.llm import OpenAILLMService +from pipecat.services.openai.llm import OpenAILLMService, OpenAILLMSettings from pipecat.transcriptions.language import Language from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams @@ -62,7 +62,9 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): llm = OpenAILLMService( api_key=os.getenv("OPENAI_API_KEY"), - system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + settings=OpenAILLMSettings( + system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + ), ) context = LLMContext() diff --git a/examples/foundational/55f-update-settings-elevenlabs-realtime-stt.py b/examples/foundational/55f-update-settings-elevenlabs-realtime-stt.py index ef1e44b61..b1f35de13 100644 --- a/examples/foundational/55f-update-settings-elevenlabs-realtime-stt.py +++ b/examples/foundational/55f-update-settings-elevenlabs-realtime-stt.py @@ -27,7 +27,7 @@ from pipecat.services.elevenlabs.stt import ( ElevenLabsRealtimeSTTService, ElevenLabsRealtimeSTTSettings, ) -from pipecat.services.openai.llm import OpenAILLMService +from pipecat.services.openai.llm import OpenAILLMService, OpenAILLMSettings from pipecat.transcriptions.language import Language from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams @@ -65,7 +65,9 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): llm = OpenAILLMService( api_key=os.getenv("OPENAI_API_KEY"), - system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + settings=OpenAILLMSettings( + system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + ), ) context = LLMContext() diff --git a/examples/foundational/55g-update-settings-elevenlabs-stt.py b/examples/foundational/55g-update-settings-elevenlabs-stt.py index c3fb9eac9..9896a1652 100644 --- a/examples/foundational/55g-update-settings-elevenlabs-stt.py +++ b/examples/foundational/55g-update-settings-elevenlabs-stt.py @@ -25,7 +25,7 @@ from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport from pipecat.services.cartesia.tts import CartesiaTTSService, CartesiaTTSSettings from pipecat.services.elevenlabs.stt import ElevenLabsSTTService, ElevenLabsSTTSettings -from pipecat.services.openai.llm import OpenAILLMService +from pipecat.services.openai.llm import OpenAILLMService, OpenAILLMSettings from pipecat.transcriptions.language import Language from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams @@ -67,7 +67,9 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): llm = OpenAILLMService( api_key=os.getenv("OPENAI_API_KEY"), - system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + settings=OpenAILLMSettings( + system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + ), ) context = LLMContext() diff --git a/examples/foundational/55h-update-settings-speechmatics-stt.py b/examples/foundational/55h-update-settings-speechmatics-stt.py index 7a0f493a8..01f653c7e 100644 --- a/examples/foundational/55h-update-settings-speechmatics-stt.py +++ b/examples/foundational/55h-update-settings-speechmatics-stt.py @@ -23,7 +23,7 @@ from pipecat.processors.aggregators.llm_response_universal import ( from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport from pipecat.services.cartesia.tts import CartesiaTTSService, CartesiaTTSSettings -from pipecat.services.openai.llm import OpenAILLMService +from pipecat.services.openai.llm import OpenAILLMService, OpenAILLMSettings from pipecat.services.speechmatics.stt import SpeechmaticsSTTService, SpeechmaticsSTTSettings from pipecat.transcriptions.language import Language from pipecat.transports.base_transport import BaseTransport, TransportParams @@ -69,7 +69,9 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): llm = OpenAILLMService( api_key=os.getenv("OPENAI_API_KEY"), - system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + settings=OpenAILLMSettings( + system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + ), ) context = LLMContext() diff --git a/examples/foundational/55i-update-settings-whisper-api-stt.py b/examples/foundational/55i-update-settings-whisper-api-stt.py index 6b957a0be..d2c81b0bc 100644 --- a/examples/foundational/55i-update-settings-whisper-api-stt.py +++ b/examples/foundational/55i-update-settings-whisper-api-stt.py @@ -23,7 +23,7 @@ from pipecat.processors.aggregators.llm_response_universal import ( from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport from pipecat.services.cartesia.tts import CartesiaTTSService, CartesiaTTSSettings -from pipecat.services.openai.llm import OpenAILLMService +from pipecat.services.openai.llm import OpenAILLMService, OpenAILLMSettings from pipecat.services.openai.stt import OpenAISTTService from pipecat.services.whisper.base_stt import BaseWhisperSTTSettings from pipecat.transports.base_transport import BaseTransport, TransportParams @@ -68,7 +68,9 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): llm = OpenAILLMService( api_key=os.getenv("OPENAI_API_KEY"), - system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + settings=OpenAILLMSettings( + system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + ), ) context = LLMContext() diff --git a/examples/foundational/55j-update-settings-sarvam-stt.py b/examples/foundational/55j-update-settings-sarvam-stt.py index 57ebccab5..982b22b57 100644 --- a/examples/foundational/55j-update-settings-sarvam-stt.py +++ b/examples/foundational/55j-update-settings-sarvam-stt.py @@ -23,7 +23,7 @@ from pipecat.processors.aggregators.llm_response_universal import ( from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport from pipecat.services.cartesia.tts import CartesiaTTSService, CartesiaTTSSettings -from pipecat.services.openai.llm import OpenAILLMService +from pipecat.services.openai.llm import OpenAILLMService, OpenAILLMSettings from pipecat.services.sarvam.stt import SarvamSTTService, SarvamSTTSettings from pipecat.transcriptions.language import Language from pipecat.transports.base_transport import BaseTransport, TransportParams @@ -62,7 +62,9 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): llm = OpenAILLMService( api_key=os.getenv("OPENAI_API_KEY"), - system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + settings=OpenAILLMSettings( + system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + ), ) context = LLMContext() diff --git a/examples/foundational/55k-update-settings-soniox-stt.py b/examples/foundational/55k-update-settings-soniox-stt.py index ac339e3c1..5fdf0fd82 100644 --- a/examples/foundational/55k-update-settings-soniox-stt.py +++ b/examples/foundational/55k-update-settings-soniox-stt.py @@ -23,7 +23,7 @@ from pipecat.processors.aggregators.llm_response_universal import ( from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport from pipecat.services.cartesia.tts import CartesiaTTSService, CartesiaTTSSettings -from pipecat.services.openai.llm import OpenAILLMService +from pipecat.services.openai.llm import OpenAILLMService, OpenAILLMSettings from pipecat.services.soniox.stt import SonioxSTTService, SonioxSTTSettings from pipecat.transcriptions.language import Language from pipecat.transports.base_transport import BaseTransport, TransportParams @@ -62,7 +62,9 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): llm = OpenAILLMService( api_key=os.getenv("OPENAI_API_KEY"), - system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + settings=OpenAILLMSettings( + system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + ), ) context = LLMContext() diff --git a/examples/foundational/55l-update-settings-aws-transcribe-stt.py b/examples/foundational/55l-update-settings-aws-transcribe-stt.py index 5594f21d9..07a923616 100644 --- a/examples/foundational/55l-update-settings-aws-transcribe-stt.py +++ b/examples/foundational/55l-update-settings-aws-transcribe-stt.py @@ -24,7 +24,7 @@ from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport from pipecat.services.aws.stt import AWSTranscribeSTTService, AWSTranscribeSTTSettings from pipecat.services.cartesia.tts import CartesiaTTSService, CartesiaTTSSettings -from pipecat.services.openai.llm import OpenAILLMService +from pipecat.services.openai.llm import OpenAILLMService, OpenAILLMSettings from pipecat.transcriptions.language import Language from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams @@ -62,7 +62,9 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): llm = OpenAILLMService( api_key=os.getenv("OPENAI_API_KEY"), - system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + settings=OpenAILLMSettings( + system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + ), ) context = LLMContext() diff --git a/examples/foundational/55m-update-settings-cartesia-stt.py b/examples/foundational/55m-update-settings-cartesia-stt.py index f1a984d9b..e8fc79e94 100644 --- a/examples/foundational/55m-update-settings-cartesia-stt.py +++ b/examples/foundational/55m-update-settings-cartesia-stt.py @@ -24,7 +24,7 @@ from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport from pipecat.services.cartesia.stt import CartesiaSTTService, CartesiaSTTSettings from pipecat.services.cartesia.tts import CartesiaTTSService, CartesiaTTSSettings -from pipecat.services.openai.llm import OpenAILLMService +from pipecat.services.openai.llm import OpenAILLMService, OpenAILLMSettings from pipecat.transcriptions.language import Language from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams @@ -62,7 +62,9 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): llm = OpenAILLMService( api_key=os.getenv("OPENAI_API_KEY"), - system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + settings=OpenAILLMSettings( + system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + ), ) context = LLMContext() diff --git a/examples/foundational/55n-update-settings-cartesia-http-tts.py b/examples/foundational/55n-update-settings-cartesia-http-tts.py index a58a8a778..9cd935692 100644 --- a/examples/foundational/55n-update-settings-cartesia-http-tts.py +++ b/examples/foundational/55n-update-settings-cartesia-http-tts.py @@ -28,7 +28,7 @@ from pipecat.services.cartesia.tts import ( GenerationConfig, ) from pipecat.services.deepgram.stt import DeepgramSTTService -from pipecat.services.openai.llm import OpenAILLMService +from pipecat.services.openai.llm import OpenAILLMService, OpenAILLMSettings from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams @@ -65,7 +65,9 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): llm = OpenAILLMService( api_key=os.getenv("OPENAI_API_KEY"), - system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + settings=OpenAILLMSettings( + system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + ), ) context = LLMContext() diff --git a/examples/foundational/55n-update-settings-cartesia-tts.py b/examples/foundational/55n-update-settings-cartesia-tts.py index e729c53f2..37ec2e903 100644 --- a/examples/foundational/55n-update-settings-cartesia-tts.py +++ b/examples/foundational/55n-update-settings-cartesia-tts.py @@ -24,7 +24,7 @@ from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport from pipecat.services.cartesia.tts import CartesiaTTSService, CartesiaTTSSettings, GenerationConfig from pipecat.services.deepgram.stt import DeepgramSTTService -from pipecat.services.openai.llm import OpenAILLMService +from pipecat.services.openai.llm import OpenAILLMService, OpenAILLMSettings from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams @@ -63,7 +63,9 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): llm = OpenAILLMService( api_key=os.getenv("OPENAI_API_KEY"), - system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + settings=OpenAILLMSettings( + system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + ), ) context = LLMContext() diff --git a/examples/foundational/55o-update-settings-elevenlabs-http-tts.py b/examples/foundational/55o-update-settings-elevenlabs-http-tts.py index c6160d1c2..c8c2af4ab 100644 --- a/examples/foundational/55o-update-settings-elevenlabs-http-tts.py +++ b/examples/foundational/55o-update-settings-elevenlabs-http-tts.py @@ -26,7 +26,7 @@ from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport from pipecat.services.deepgram.stt import DeepgramSTTService from pipecat.services.elevenlabs.tts import ElevenLabsHttpTTSService, ElevenLabsHttpTTSSettings -from pipecat.services.openai.llm import OpenAILLMService +from pipecat.services.openai.llm import OpenAILLMService, OpenAILLMSettings from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams @@ -64,7 +64,9 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): llm = OpenAILLMService( api_key=os.getenv("OPENAI_API_KEY"), - system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + settings=OpenAILLMSettings( + system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + ), ) context = LLMContext() diff --git a/examples/foundational/55o-update-settings-elevenlabs-tts.py b/examples/foundational/55o-update-settings-elevenlabs-tts.py index 104dd314f..71ff8c0af 100644 --- a/examples/foundational/55o-update-settings-elevenlabs-tts.py +++ b/examples/foundational/55o-update-settings-elevenlabs-tts.py @@ -24,7 +24,7 @@ from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport from pipecat.services.deepgram.stt import DeepgramSTTService from pipecat.services.elevenlabs.tts import ElevenLabsTTSService, ElevenLabsTTSSettings -from pipecat.services.openai.llm import OpenAILLMService +from pipecat.services.openai.llm import OpenAILLMService, OpenAILLMSettings from pipecat.transcriptions.language import Language from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams @@ -60,7 +60,9 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): llm = OpenAILLMService( api_key=os.getenv("OPENAI_API_KEY"), - system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + settings=OpenAILLMSettings( + system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + ), ) context = LLMContext() diff --git a/examples/foundational/55p-update-settings-openai-tts.py b/examples/foundational/55p-update-settings-openai-tts.py index e108f4949..9a1402a1c 100644 --- a/examples/foundational/55p-update-settings-openai-tts.py +++ b/examples/foundational/55p-update-settings-openai-tts.py @@ -23,7 +23,7 @@ from pipecat.processors.aggregators.llm_response_universal import ( from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport from pipecat.services.deepgram.stt import DeepgramSTTService -from pipecat.services.openai.llm import OpenAILLMService +from pipecat.services.openai.llm import OpenAILLMService, OpenAILLMSettings from pipecat.services.openai.tts import OpenAITTSService, OpenAITTSSettings from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams @@ -56,7 +56,9 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): llm = OpenAILLMService( api_key=os.getenv("OPENAI_API_KEY"), - system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + settings=OpenAILLMSettings( + system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + ), ) context = LLMContext() diff --git a/examples/foundational/55q-update-settings-deepgram-http-tts.py b/examples/foundational/55q-update-settings-deepgram-http-tts.py index 653e2bd63..dd5220c3f 100644 --- a/examples/foundational/55q-update-settings-deepgram-http-tts.py +++ b/examples/foundational/55q-update-settings-deepgram-http-tts.py @@ -26,7 +26,7 @@ from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport from pipecat.services.deepgram.stt import DeepgramSTTService from pipecat.services.deepgram.tts import DeepgramHttpTTSService, DeepgramTTSSettings -from pipecat.services.openai.llm import OpenAILLMService +from pipecat.services.openai.llm import OpenAILLMService, OpenAILLMSettings from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams @@ -63,7 +63,9 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): llm = OpenAILLMService( api_key=os.getenv("OPENAI_API_KEY"), - system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + settings=OpenAILLMSettings( + system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + ), ) context = LLMContext() diff --git a/examples/foundational/55q-update-settings-deepgram-sagemaker-tts.py b/examples/foundational/55q-update-settings-deepgram-sagemaker-tts.py index 6cd396d04..b913375bb 100644 --- a/examples/foundational/55q-update-settings-deepgram-sagemaker-tts.py +++ b/examples/foundational/55q-update-settings-deepgram-sagemaker-tts.py @@ -27,7 +27,7 @@ from pipecat.services.deepgram.sagemaker.tts import ( DeepgramSageMakerTTSSettings, ) from pipecat.services.deepgram.stt import DeepgramSTTService -from pipecat.services.openai.llm import OpenAILLMService +from pipecat.services.openai.llm import OpenAILLMService, OpenAILLMSettings from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams @@ -63,7 +63,9 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): llm = OpenAILLMService( api_key=os.getenv("OPENAI_API_KEY"), - system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + settings=OpenAILLMSettings( + system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + ), ) context = LLMContext() diff --git a/examples/foundational/55q-update-settings-deepgram-tts.py b/examples/foundational/55q-update-settings-deepgram-tts.py index 86d37374a..7164c7b58 100644 --- a/examples/foundational/55q-update-settings-deepgram-tts.py +++ b/examples/foundational/55q-update-settings-deepgram-tts.py @@ -24,7 +24,7 @@ from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport from pipecat.services.deepgram.stt import DeepgramSTTService from pipecat.services.deepgram.tts import DeepgramTTSService, DeepgramTTSSettings -from pipecat.services.openai.llm import OpenAILLMService +from pipecat.services.openai.llm import OpenAILLMService, OpenAILLMSettings from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams @@ -56,7 +56,9 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): llm = OpenAILLMService( api_key=os.getenv("OPENAI_API_KEY"), - system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + settings=OpenAILLMSettings( + system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + ), ) context = LLMContext() diff --git a/examples/foundational/55r-update-settings-azure-http-tts.py b/examples/foundational/55r-update-settings-azure-http-tts.py index d6b870cc7..148e97f1a 100644 --- a/examples/foundational/55r-update-settings-azure-http-tts.py +++ b/examples/foundational/55r-update-settings-azure-http-tts.py @@ -24,7 +24,7 @@ from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport from pipecat.services.azure.tts import AzureHttpTTSService, AzureTTSSettings from pipecat.services.deepgram.stt import DeepgramSTTService -from pipecat.services.openai.llm import OpenAILLMService +from pipecat.services.openai.llm import OpenAILLMService, OpenAILLMSettings from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams @@ -59,7 +59,9 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): llm = OpenAILLMService( api_key=os.getenv("OPENAI_API_KEY"), - system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + settings=OpenAILLMSettings( + system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + ), ) context = LLMContext() diff --git a/examples/foundational/55r-update-settings-azure-tts.py b/examples/foundational/55r-update-settings-azure-tts.py index a564a7267..d23d41a89 100644 --- a/examples/foundational/55r-update-settings-azure-tts.py +++ b/examples/foundational/55r-update-settings-azure-tts.py @@ -24,7 +24,7 @@ from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport from pipecat.services.azure.tts import AzureTTSService, AzureTTSSettings from pipecat.services.deepgram.stt import DeepgramSTTService -from pipecat.services.openai.llm import OpenAILLMService +from pipecat.services.openai.llm import OpenAILLMService, OpenAILLMSettings from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams @@ -59,7 +59,9 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): llm = OpenAILLMService( api_key=os.getenv("OPENAI_API_KEY"), - system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + settings=OpenAILLMSettings( + system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + ), ) context = LLMContext() diff --git a/examples/foundational/55s-update-settings-google-http-tts.py b/examples/foundational/55s-update-settings-google-http-tts.py index 146d5039e..c573bee6f 100644 --- a/examples/foundational/55s-update-settings-google-http-tts.py +++ b/examples/foundational/55s-update-settings-google-http-tts.py @@ -24,7 +24,7 @@ from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport from pipecat.services.deepgram.stt import DeepgramSTTService from pipecat.services.google.tts import GoogleHttpTTSService, GoogleHttpTTSSettings -from pipecat.services.openai.llm import OpenAILLMService +from pipecat.services.openai.llm import OpenAILLMService, OpenAILLMSettings from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams @@ -56,7 +56,9 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): llm = OpenAILLMService( api_key=os.getenv("OPENAI_API_KEY"), - system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + settings=OpenAILLMSettings( + system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + ), ) context = LLMContext() diff --git a/examples/foundational/55s-update-settings-google-stream-tts.py b/examples/foundational/55s-update-settings-google-stream-tts.py index 445ab537b..b13cbd063 100644 --- a/examples/foundational/55s-update-settings-google-stream-tts.py +++ b/examples/foundational/55s-update-settings-google-stream-tts.py @@ -24,7 +24,7 @@ from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport from pipecat.services.deepgram.stt import DeepgramSTTService from pipecat.services.google.tts import GoogleStreamTTSSettings, GoogleTTSService -from pipecat.services.openai.llm import OpenAILLMService +from pipecat.services.openai.llm import OpenAILLMService, OpenAILLMSettings from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams @@ -56,7 +56,9 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): llm = OpenAILLMService( api_key=os.getenv("OPENAI_API_KEY"), - system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + settings=OpenAILLMSettings( + system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + ), ) context = LLMContext() diff --git a/examples/foundational/55u-update-settings-rime-http-tts.py b/examples/foundational/55u-update-settings-rime-http-tts.py index 8515b796e..0c00913e7 100644 --- a/examples/foundational/55u-update-settings-rime-http-tts.py +++ b/examples/foundational/55u-update-settings-rime-http-tts.py @@ -25,7 +25,7 @@ from pipecat.processors.aggregators.llm_response_universal import ( from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport from pipecat.services.deepgram.stt import DeepgramSTTService -from pipecat.services.openai.llm import OpenAILLMService +from pipecat.services.openai.llm import OpenAILLMService, OpenAILLMSettings from pipecat.services.rime.tts import RimeHttpTTSService, RimeTTSSettings from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams @@ -64,7 +64,9 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): llm = OpenAILLMService( api_key=os.getenv("OPENAI_API_KEY"), - system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + settings=OpenAILLMSettings( + system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + ), ) context = LLMContext() diff --git a/examples/foundational/55u-update-settings-rime-tts.py b/examples/foundational/55u-update-settings-rime-tts.py index 72c63af8c..cb8e09876 100644 --- a/examples/foundational/55u-update-settings-rime-tts.py +++ b/examples/foundational/55u-update-settings-rime-tts.py @@ -23,7 +23,7 @@ from pipecat.processors.aggregators.llm_response_universal import ( from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport from pipecat.services.deepgram.stt import DeepgramSTTService -from pipecat.services.openai.llm import OpenAILLMService +from pipecat.services.openai.llm import OpenAILLMService, OpenAILLMSettings from pipecat.services.rime.tts import RimeTTSService, RimeTTSSettings from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams @@ -59,7 +59,9 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): llm = OpenAILLMService( api_key=os.getenv("OPENAI_API_KEY"), - system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + settings=OpenAILLMSettings( + system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + ), ) context = LLMContext() diff --git a/examples/foundational/55v-update-settings-lmnt-tts.py b/examples/foundational/55v-update-settings-lmnt-tts.py index d0651c84e..48b0f8d43 100644 --- a/examples/foundational/55v-update-settings-lmnt-tts.py +++ b/examples/foundational/55v-update-settings-lmnt-tts.py @@ -24,7 +24,7 @@ from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport from pipecat.services.deepgram.stt import DeepgramSTTService from pipecat.services.lmnt.tts import LmntTTSService, LmntTTSSettings -from pipecat.services.openai.llm import OpenAILLMService +from pipecat.services.openai.llm import OpenAILLMService, OpenAILLMSettings from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams @@ -59,7 +59,9 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): llm = OpenAILLMService( api_key=os.getenv("OPENAI_API_KEY"), - system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + settings=OpenAILLMSettings( + system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + ), ) context = LLMContext() diff --git a/examples/foundational/55w-update-settings-fish-tts.py b/examples/foundational/55w-update-settings-fish-tts.py index ff95838f7..8243f82f2 100644 --- a/examples/foundational/55w-update-settings-fish-tts.py +++ b/examples/foundational/55w-update-settings-fish-tts.py @@ -24,7 +24,7 @@ from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport from pipecat.services.deepgram.stt import DeepgramSTTService from pipecat.services.fish.tts import FishAudioTTSService, FishAudioTTSSettings -from pipecat.services.openai.llm import OpenAILLMService +from pipecat.services.openai.llm import OpenAILLMService, OpenAILLMSettings from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams @@ -59,7 +59,9 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): llm = OpenAILLMService( api_key=os.getenv("OPENAI_API_KEY"), - system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + settings=OpenAILLMSettings( + system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + ), ) context = LLMContext() diff --git a/examples/foundational/55x-update-settings-minimax-tts.py b/examples/foundational/55x-update-settings-minimax-tts.py index 66ce52071..fc74bca4c 100644 --- a/examples/foundational/55x-update-settings-minimax-tts.py +++ b/examples/foundational/55x-update-settings-minimax-tts.py @@ -25,7 +25,7 @@ from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport from pipecat.services.deepgram.stt import DeepgramSTTService from pipecat.services.minimax.tts import MiniMaxHttpTTSService, MiniMaxTTSSettings -from pipecat.services.openai.llm import OpenAILLMService +from pipecat.services.openai.llm import OpenAILLMService, OpenAILLMSettings from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams @@ -62,7 +62,9 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): llm = OpenAILLMService( api_key=os.getenv("OPENAI_API_KEY"), - system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + settings=OpenAILLMSettings( + system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + ), ) context = LLMContext() diff --git a/examples/foundational/55y-update-settings-groq-tts.py b/examples/foundational/55y-update-settings-groq-tts.py index 73e4ac778..632907eaf 100644 --- a/examples/foundational/55y-update-settings-groq-tts.py +++ b/examples/foundational/55y-update-settings-groq-tts.py @@ -24,7 +24,7 @@ from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport from pipecat.services.deepgram.stt import DeepgramSTTService from pipecat.services.groq.tts import GroqTTSService, GroqTTSSettings -from pipecat.services.openai.llm import OpenAILLMService +from pipecat.services.openai.llm import OpenAILLMService, OpenAILLMSettings from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams @@ -56,7 +56,9 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): llm = OpenAILLMService( api_key=os.getenv("OPENAI_API_KEY"), - system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + settings=OpenAILLMSettings( + system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + ), ) context = LLMContext() diff --git a/examples/foundational/55z-update-settings-hume-tts.py b/examples/foundational/55z-update-settings-hume-tts.py index d01dc78bf..855610b6b 100644 --- a/examples/foundational/55z-update-settings-hume-tts.py +++ b/examples/foundational/55z-update-settings-hume-tts.py @@ -24,7 +24,7 @@ from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport from pipecat.services.deepgram.stt import DeepgramSTTService from pipecat.services.hume.tts import HumeTTSService, HumeTTSSettings -from pipecat.services.openai.llm import OpenAILLMService +from pipecat.services.openai.llm import OpenAILLMService, OpenAILLMSettings from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams @@ -59,7 +59,9 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): llm = OpenAILLMService( api_key=os.getenv("OPENAI_API_KEY"), - system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + settings=OpenAILLMSettings( + system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + ), ) context = LLMContext() diff --git a/examples/foundational/55za-update-settings-neuphonic-http-tts.py b/examples/foundational/55za-update-settings-neuphonic-http-tts.py index 6c3e510a1..7435b135d 100644 --- a/examples/foundational/55za-update-settings-neuphonic-http-tts.py +++ b/examples/foundational/55za-update-settings-neuphonic-http-tts.py @@ -25,7 +25,7 @@ from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport from pipecat.services.deepgram.stt import DeepgramSTTService from pipecat.services.neuphonic.tts import NeuphonicHttpTTSService, NeuphonicTTSSettings -from pipecat.services.openai.llm import OpenAILLMService +from pipecat.services.openai.llm import OpenAILLMService, OpenAILLMSettings from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams @@ -61,7 +61,9 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): llm = OpenAILLMService( api_key=os.getenv("OPENAI_API_KEY"), - system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + settings=OpenAILLMSettings( + system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + ), ) context = LLMContext() diff --git a/examples/foundational/55za-update-settings-neuphonic-tts.py b/examples/foundational/55za-update-settings-neuphonic-tts.py index e79ac666f..c0566e86b 100644 --- a/examples/foundational/55za-update-settings-neuphonic-tts.py +++ b/examples/foundational/55za-update-settings-neuphonic-tts.py @@ -24,7 +24,7 @@ from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport from pipecat.services.deepgram.stt import DeepgramSTTService from pipecat.services.neuphonic.tts import NeuphonicTTSService, NeuphonicTTSSettings -from pipecat.services.openai.llm import OpenAILLMService +from pipecat.services.openai.llm import OpenAILLMService, OpenAILLMSettings from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams @@ -56,7 +56,9 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): llm = OpenAILLMService( api_key=os.getenv("OPENAI_API_KEY"), - system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + settings=OpenAILLMSettings( + system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + ), ) context = LLMContext() diff --git a/examples/foundational/55zb-update-settings-inworld-http-tts.py b/examples/foundational/55zb-update-settings-inworld-http-tts.py index ccba1238c..4a2e2a2bc 100644 --- a/examples/foundational/55zb-update-settings-inworld-http-tts.py +++ b/examples/foundational/55zb-update-settings-inworld-http-tts.py @@ -26,7 +26,7 @@ from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport from pipecat.services.deepgram.stt import DeepgramSTTService from pipecat.services.inworld.tts import InworldHttpTTSService, InworldTTSSettings -from pipecat.services.openai.llm import OpenAILLMService +from pipecat.services.openai.llm import OpenAILLMService, OpenAILLMSettings from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams @@ -60,7 +60,9 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): llm = OpenAILLMService( api_key=os.getenv("OPENAI_API_KEY"), - system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + settings=OpenAILLMSettings( + system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + ), ) context = LLMContext() diff --git a/examples/foundational/55zb-update-settings-inworld-tts.py b/examples/foundational/55zb-update-settings-inworld-tts.py index e60e65036..7fcaf67bd 100644 --- a/examples/foundational/55zb-update-settings-inworld-tts.py +++ b/examples/foundational/55zb-update-settings-inworld-tts.py @@ -24,7 +24,7 @@ from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport from pipecat.services.deepgram.stt import DeepgramSTTService from pipecat.services.inworld.tts import InworldTTSService, InworldTTSSettings -from pipecat.services.openai.llm import OpenAILLMService +from pipecat.services.openai.llm import OpenAILLMService, OpenAILLMSettings from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams @@ -56,7 +56,9 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): llm = OpenAILLMService( api_key=os.getenv("OPENAI_API_KEY"), - system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + settings=OpenAILLMSettings( + system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + ), ) context = LLMContext() diff --git a/examples/foundational/55zc-update-settings-gemini-tts.py b/examples/foundational/55zc-update-settings-gemini-tts.py index 99a91d176..2d2f15cda 100644 --- a/examples/foundational/55zc-update-settings-gemini-tts.py +++ b/examples/foundational/55zc-update-settings-gemini-tts.py @@ -24,7 +24,7 @@ from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport from pipecat.services.deepgram.stt import DeepgramSTTService from pipecat.services.google.tts import GeminiTTSService, GeminiTTSSettings -from pipecat.services.openai.llm import OpenAILLMService +from pipecat.services.openai.llm import OpenAILLMService, OpenAILLMSettings from pipecat.transcriptions.language import Language from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams @@ -65,7 +65,9 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): llm = OpenAILLMService( api_key=os.getenv("OPENAI_API_KEY"), - system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + settings=OpenAILLMSettings( + system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + ), ) context = LLMContext() diff --git a/examples/foundational/55zd-update-settings-aws-polly-tts.py b/examples/foundational/55zd-update-settings-aws-polly-tts.py index 3b1c1d734..1f6ce56b2 100644 --- a/examples/foundational/55zd-update-settings-aws-polly-tts.py +++ b/examples/foundational/55zd-update-settings-aws-polly-tts.py @@ -24,7 +24,7 @@ from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport from pipecat.services.aws.tts import AWSPollyTTSService, AWSPollyTTSSettings from pipecat.services.deepgram.stt import DeepgramSTTService -from pipecat.services.openai.llm import OpenAILLMService +from pipecat.services.openai.llm import OpenAILLMService, OpenAILLMSettings from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams @@ -56,7 +56,9 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): llm = OpenAILLMService( api_key=os.getenv("OPENAI_API_KEY"), - system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + settings=OpenAILLMSettings( + system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + ), ) context = LLMContext() diff --git a/examples/foundational/55ze-update-settings-sarvam-http-tts.py b/examples/foundational/55ze-update-settings-sarvam-http-tts.py index ffcf086c6..811ffceb8 100644 --- a/examples/foundational/55ze-update-settings-sarvam-http-tts.py +++ b/examples/foundational/55ze-update-settings-sarvam-http-tts.py @@ -25,7 +25,7 @@ from pipecat.processors.aggregators.llm_response_universal import ( from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport from pipecat.services.deepgram.stt import DeepgramSTTService -from pipecat.services.openai.llm import OpenAILLMService +from pipecat.services.openai.llm import OpenAILLMService, OpenAILLMSettings from pipecat.services.sarvam.tts import SarvamHttpTTSService, SarvamHttpTTSSettings from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams @@ -60,7 +60,9 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): llm = OpenAILLMService( api_key=os.getenv("OPENAI_API_KEY"), - system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + settings=OpenAILLMSettings( + system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + ), ) context = LLMContext() diff --git a/examples/foundational/55ze-update-settings-sarvam-tts.py b/examples/foundational/55ze-update-settings-sarvam-tts.py index 44301578f..b36e6f81f 100644 --- a/examples/foundational/55ze-update-settings-sarvam-tts.py +++ b/examples/foundational/55ze-update-settings-sarvam-tts.py @@ -23,7 +23,7 @@ from pipecat.processors.aggregators.llm_response_universal import ( from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport from pipecat.services.deepgram.stt import DeepgramSTTService -from pipecat.services.openai.llm import OpenAILLMService +from pipecat.services.openai.llm import OpenAILLMService, OpenAILLMSettings from pipecat.services.sarvam.tts import SarvamTTSService, SarvamTTSSettings from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams @@ -56,7 +56,9 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): llm = OpenAILLMService( api_key=os.getenv("OPENAI_API_KEY"), - system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + settings=OpenAILLMSettings( + system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + ), ) context = LLMContext() diff --git a/examples/foundational/55zf-update-settings-camb-tts.py b/examples/foundational/55zf-update-settings-camb-tts.py index f8058141d..493ad0917 100644 --- a/examples/foundational/55zf-update-settings-camb-tts.py +++ b/examples/foundational/55zf-update-settings-camb-tts.py @@ -24,7 +24,7 @@ from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport from pipecat.services.camb.tts import CambTTSService, CambTTSSettings from pipecat.services.deepgram.stt import DeepgramSTTService -from pipecat.services.openai.llm import OpenAILLMService +from pipecat.services.openai.llm import OpenAILLMService, OpenAILLMSettings from pipecat.transcriptions.language import Language from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams @@ -57,7 +57,9 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): llm = OpenAILLMService( api_key=os.getenv("OPENAI_API_KEY"), - system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + settings=OpenAILLMSettings( + system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + ), ) context = LLMContext() diff --git a/examples/foundational/55zh-update-settings-resembleai-tts.py b/examples/foundational/55zh-update-settings-resembleai-tts.py index 8428357b5..2c5ef3b25 100644 --- a/examples/foundational/55zh-update-settings-resembleai-tts.py +++ b/examples/foundational/55zh-update-settings-resembleai-tts.py @@ -23,7 +23,7 @@ from pipecat.processors.aggregators.llm_response_universal import ( from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport from pipecat.services.deepgram.stt import DeepgramSTTService -from pipecat.services.openai.llm import OpenAILLMService +from pipecat.services.openai.llm import OpenAILLMService, OpenAILLMSettings from pipecat.services.resembleai.tts import ResembleAITTSService, ResembleAITTSSettings from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams @@ -59,7 +59,9 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): llm = OpenAILLMService( api_key=os.getenv("OPENAI_API_KEY"), - system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + settings=OpenAILLMSettings( + system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + ), ) context = LLMContext() diff --git a/examples/foundational/55zi-update-settings-azure-llm.py b/examples/foundational/55zi-update-settings-azure-llm.py index b7fe5d745..5093ba560 100644 --- a/examples/foundational/55zi-update-settings-azure-llm.py +++ b/examples/foundational/55zi-update-settings-azure-llm.py @@ -63,8 +63,10 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): llm = AzureLLMService( api_key=os.getenv("AZURE_CHATGPT_API_KEY"), endpoint=os.getenv("AZURE_CHATGPT_ENDPOINT"), - settings=AzureLLMSettings(model=os.getenv("AZURE_CHATGPT_MODEL")), - system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + settings=AzureLLMSettings( + model=os.getenv("AZURE_CHATGPT_MODEL"), + system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + ), ) context = LLMContext() diff --git a/examples/foundational/55zi-update-settings-openai-llm.py b/examples/foundational/55zi-update-settings-openai-llm.py index 123fc7a04..6af897217 100644 --- a/examples/foundational/55zi-update-settings-openai-llm.py +++ b/examples/foundational/55zi-update-settings-openai-llm.py @@ -62,7 +62,9 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): llm = OpenAILLMService( api_key=os.getenv("OPENAI_API_KEY"), - system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + settings=OpenAILLMSettings( + system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + ), ) context = LLMContext() diff --git a/examples/foundational/55zj-update-settings-anthropic-llm.py b/examples/foundational/55zj-update-settings-anthropic-llm.py index d44102f2d..8417d0dcd 100644 --- a/examples/foundational/55zj-update-settings-anthropic-llm.py +++ b/examples/foundational/55zj-update-settings-anthropic-llm.py @@ -61,7 +61,9 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): llm = AnthropicLLMService( api_key=os.getenv("ANTHROPIC_API_KEY"), - system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + settings=AnthropicLLMSettings( + system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + ), ) context = LLMContext() diff --git a/examples/foundational/55zk-update-settings-google-llm.py b/examples/foundational/55zk-update-settings-google-llm.py index d1222e422..94b15c886 100644 --- a/examples/foundational/55zk-update-settings-google-llm.py +++ b/examples/foundational/55zk-update-settings-google-llm.py @@ -61,7 +61,9 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): llm = GoogleLLMService( api_key=os.getenv("GOOGLE_API_KEY"), - system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + settings=GoogleLLMSettings( + system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + ), ) context = LLMContext() diff --git a/examples/foundational/55zk-update-settings-google-vertex-llm.py b/examples/foundational/55zk-update-settings-google-vertex-llm.py index aa9452d09..1158c4635 100644 --- a/examples/foundational/55zk-update-settings-google-vertex-llm.py +++ b/examples/foundational/55zk-update-settings-google-vertex-llm.py @@ -25,7 +25,7 @@ from pipecat.runner.utils import create_transport from pipecat.services.cartesia.tts import CartesiaTTSService, CartesiaTTSSettings from pipecat.services.deepgram.stt import DeepgramSTTService from pipecat.services.google.llm import GoogleLLMSettings -from pipecat.services.google.llm_vertex import GoogleVertexLLMService +from pipecat.services.google.llm_vertex import GoogleVertexLLMService, GoogleVertexLLMSettings from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams @@ -64,7 +64,9 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): credentials=os.getenv("GOOGLE_VERTEX_TEST_CREDENTIALS"), project_id=os.getenv("GOOGLE_CLOUD_PROJECT_ID"), location=os.getenv("GOOGLE_CLOUD_LOCATION"), - system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + settings=GoogleVertexLLMSettings( + system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + ), ) context = LLMContext() diff --git a/examples/foundational/55zp-update-settings-aws-bedrock-llm.py b/examples/foundational/55zp-update-settings-aws-bedrock-llm.py index 3d5d93b6a..f4f8f8815 100644 --- a/examples/foundational/55zp-update-settings-aws-bedrock-llm.py +++ b/examples/foundational/55zp-update-settings-aws-bedrock-llm.py @@ -64,8 +64,8 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): settings=AWSBedrockLLMSettings( model="us.anthropic.claude-haiku-4-5-20251001-v1:0", temperature=0.8, + system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", ), - system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", ) context = LLMContext() diff --git a/examples/foundational/55zq-update-settings-fal-stt.py b/examples/foundational/55zq-update-settings-fal-stt.py index 96f916d81..0811523f0 100644 --- a/examples/foundational/55zq-update-settings-fal-stt.py +++ b/examples/foundational/55zq-update-settings-fal-stt.py @@ -24,7 +24,7 @@ from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport from pipecat.services.cartesia.tts import CartesiaTTSService, CartesiaTTSSettings from pipecat.services.fal.stt import FalSTTService, FalSTTSettings -from pipecat.services.openai.llm import OpenAILLMService +from pipecat.services.openai.llm import OpenAILLMService, OpenAILLMSettings from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams @@ -61,7 +61,9 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): llm = OpenAILLMService( api_key=os.getenv("OPENAI_API_KEY"), - system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + settings=OpenAILLMSettings( + system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + ), ) context = LLMContext() diff --git a/examples/foundational/55zr-update-settings-gradium-stt.py b/examples/foundational/55zr-update-settings-gradium-stt.py index 0b3085125..952f2bb26 100644 --- a/examples/foundational/55zr-update-settings-gradium-stt.py +++ b/examples/foundational/55zr-update-settings-gradium-stt.py @@ -24,7 +24,7 @@ from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport from pipecat.services.cartesia.tts import CartesiaTTSService, CartesiaTTSSettings from pipecat.services.gradium.stt import GradiumSTTService, GradiumSTTSettings -from pipecat.services.openai.llm import OpenAILLMService +from pipecat.services.openai.llm import OpenAILLMService, OpenAILLMSettings from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams @@ -64,7 +64,9 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): llm = OpenAILLMService( api_key=os.getenv("OPENAI_API_KEY"), - system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + settings=OpenAILLMSettings( + system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + ), ) context = LLMContext() diff --git a/examples/foundational/55zt-update-settings-nvidia-segmented-stt.py b/examples/foundational/55zt-update-settings-nvidia-segmented-stt.py index 55a6719be..b46096e0b 100644 --- a/examples/foundational/55zt-update-settings-nvidia-segmented-stt.py +++ b/examples/foundational/55zt-update-settings-nvidia-segmented-stt.py @@ -24,7 +24,7 @@ from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport from pipecat.services.cartesia.tts import CartesiaTTSService, CartesiaTTSSettings from pipecat.services.nvidia.stt import NvidiaSegmentedSTTService, NvidiaSegmentedSTTSettings -from pipecat.services.openai.llm import OpenAILLMService +from pipecat.services.openai.llm import OpenAILLMService, OpenAILLMSettings from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams @@ -61,7 +61,9 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): llm = OpenAILLMService( api_key=os.getenv("OPENAI_API_KEY"), - system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + settings=OpenAILLMSettings( + system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + ), ) context = LLMContext() diff --git a/examples/foundational/55zt-update-settings-nvidia-stt.py b/examples/foundational/55zt-update-settings-nvidia-stt.py index 2f15895d2..2efa824c3 100644 --- a/examples/foundational/55zt-update-settings-nvidia-stt.py +++ b/examples/foundational/55zt-update-settings-nvidia-stt.py @@ -24,7 +24,7 @@ from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport from pipecat.services.cartesia.tts import CartesiaTTSService, CartesiaTTSSettings from pipecat.services.nvidia.stt import NvidiaSTTService, NvidiaSTTSettings -from pipecat.services.openai.llm import OpenAILLMService +from pipecat.services.openai.llm import OpenAILLMService, OpenAILLMSettings from pipecat.transcriptions.language import Language from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams @@ -62,7 +62,9 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): llm = OpenAILLMService( api_key=os.getenv("OPENAI_API_KEY"), - system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + settings=OpenAILLMSettings( + system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + ), ) context = LLMContext() diff --git a/examples/foundational/55zu-update-settings-openai-realtime-stt.py b/examples/foundational/55zu-update-settings-openai-realtime-stt.py index 7cc31085b..9f0e1dc89 100644 --- a/examples/foundational/55zu-update-settings-openai-realtime-stt.py +++ b/examples/foundational/55zu-update-settings-openai-realtime-stt.py @@ -23,7 +23,7 @@ from pipecat.processors.aggregators.llm_response_universal import ( from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport from pipecat.services.cartesia.tts import CartesiaTTSService, CartesiaTTSSettings -from pipecat.services.openai.llm import OpenAILLMService +from pipecat.services.openai.llm import OpenAILLMService, OpenAILLMSettings from pipecat.services.openai.stt import OpenAIRealtimeSTTService, OpenAIRealtimeSTTSettings from pipecat.transcriptions.language import Language from pipecat.transports.base_transport import BaseTransport, TransportParams @@ -62,7 +62,9 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): llm = OpenAILLMService( api_key=os.getenv("OPENAI_API_KEY"), - system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + settings=OpenAILLMSettings( + system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + ), ) context = LLMContext() diff --git a/examples/foundational/55zv-update-settings-asyncai-http-tts.py b/examples/foundational/55zv-update-settings-asyncai-http-tts.py index 2063cda3a..29a774fae 100644 --- a/examples/foundational/55zv-update-settings-asyncai-http-tts.py +++ b/examples/foundational/55zv-update-settings-asyncai-http-tts.py @@ -26,7 +26,7 @@ from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport from pipecat.services.asyncai.tts import AsyncAIHttpTTSService, AsyncAITTSSettings from pipecat.services.deepgram.stt import DeepgramSTTService -from pipecat.services.openai.llm import OpenAILLMService +from pipecat.services.openai.llm import OpenAILLMService, OpenAILLMSettings from pipecat.transcriptions.language import Language from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams @@ -67,7 +67,9 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): llm = OpenAILLMService( api_key=os.getenv("OPENAI_API_KEY"), - system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + settings=OpenAILLMSettings( + system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + ), ) context = LLMContext() diff --git a/examples/foundational/55zv-update-settings-asyncai-tts.py b/examples/foundational/55zv-update-settings-asyncai-tts.py index 10cace018..b9c35ebbd 100644 --- a/examples/foundational/55zv-update-settings-asyncai-tts.py +++ b/examples/foundational/55zv-update-settings-asyncai-tts.py @@ -24,7 +24,7 @@ from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport from pipecat.services.asyncai.tts import AsyncAITTSService, AsyncAITTSSettings from pipecat.services.deepgram.stt import DeepgramSTTService -from pipecat.services.openai.llm import OpenAILLMService +from pipecat.services.openai.llm import OpenAILLMService, OpenAILLMSettings from pipecat.transcriptions.language import Language from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams @@ -62,7 +62,9 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): llm = OpenAILLMService( api_key=os.getenv("OPENAI_API_KEY"), - system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + settings=OpenAILLMSettings( + system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + ), ) context = LLMContext() diff --git a/examples/foundational/55zw-update-settings-gradium-tts.py b/examples/foundational/55zw-update-settings-gradium-tts.py index 5c33e090a..52f7c73c5 100644 --- a/examples/foundational/55zw-update-settings-gradium-tts.py +++ b/examples/foundational/55zw-update-settings-gradium-tts.py @@ -24,7 +24,7 @@ from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport from pipecat.services.deepgram.stt import DeepgramSTTService from pipecat.services.gradium.tts import GradiumTTSService, GradiumTTSSettings -from pipecat.services.openai.llm import OpenAILLMService +from pipecat.services.openai.llm import OpenAILLMService, OpenAILLMSettings from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams @@ -60,7 +60,9 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): llm = OpenAILLMService( api_key=os.getenv("OPENAI_API_KEY"), - system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + settings=OpenAILLMSettings( + system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + ), ) context = LLMContext() diff --git a/examples/foundational/55zx-update-settings-cerebras-llm.py b/examples/foundational/55zx-update-settings-cerebras-llm.py index dc09cdae7..c6d27d8e5 100644 --- a/examples/foundational/55zx-update-settings-cerebras-llm.py +++ b/examples/foundational/55zx-update-settings-cerebras-llm.py @@ -23,7 +23,7 @@ from pipecat.processors.aggregators.llm_response_universal import ( from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport from pipecat.services.cartesia.tts import CartesiaTTSService, CartesiaTTSSettings -from pipecat.services.cerebras.llm import CerebrasLLMService +from pipecat.services.cerebras.llm import CerebrasLLMService, CerebrasLLMSettings from pipecat.services.deepgram.stt import DeepgramSTTService from pipecat.services.openai.base_llm import OpenAILLMSettings from pipecat.transports.base_transport import BaseTransport, TransportParams @@ -62,7 +62,9 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): llm = CerebrasLLMService( api_key=os.getenv("CEREBRAS_API_KEY"), - system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + settings=CerebrasLLMSettings( + system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + ), ) context = LLMContext() diff --git a/examples/foundational/55zy-update-settings-deepseek-llm.py b/examples/foundational/55zy-update-settings-deepseek-llm.py index fe6e18185..23e314f8b 100644 --- a/examples/foundational/55zy-update-settings-deepseek-llm.py +++ b/examples/foundational/55zy-update-settings-deepseek-llm.py @@ -24,7 +24,7 @@ from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport from pipecat.services.cartesia.tts import CartesiaTTSService, CartesiaTTSSettings from pipecat.services.deepgram.stt import DeepgramSTTService -from pipecat.services.deepseek.llm import DeepSeekLLMService +from pipecat.services.deepseek.llm import DeepSeekLLMService, DeepSeekLLMSettings from pipecat.services.openai.base_llm import OpenAILLMSettings from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams @@ -62,7 +62,9 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): llm = DeepSeekLLMService( api_key=os.getenv("DEEPSEEK_API_KEY"), - system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + settings=DeepSeekLLMSettings( + system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + ), ) context = LLMContext() diff --git a/examples/foundational/55zz-update-settings-fireworks-llm.py b/examples/foundational/55zz-update-settings-fireworks-llm.py index 56d29cfac..9ea0c9343 100644 --- a/examples/foundational/55zz-update-settings-fireworks-llm.py +++ b/examples/foundational/55zz-update-settings-fireworks-llm.py @@ -62,8 +62,10 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): llm = FireworksLLMService( api_key=os.getenv("FIREWORKS_API_KEY"), - settings=FireworksLLMSettings(model="accounts/fireworks/models/gpt-oss-20b"), - system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + settings=FireworksLLMSettings( + model="accounts/fireworks/models/gpt-oss-20b", + system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + ), ) context = LLMContext() diff --git a/examples/foundational/55zza-update-settings-grok-llm.py b/examples/foundational/55zza-update-settings-grok-llm.py index c40f40ac6..ca537a705 100644 --- a/examples/foundational/55zza-update-settings-grok-llm.py +++ b/examples/foundational/55zza-update-settings-grok-llm.py @@ -24,7 +24,7 @@ from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport from pipecat.services.cartesia.tts import CartesiaTTSService, CartesiaTTSSettings from pipecat.services.deepgram.stt import DeepgramSTTService -from pipecat.services.grok.llm import GrokLLMService +from pipecat.services.grok.llm import GrokLLMService, GrokLLMSettings from pipecat.services.openai.base_llm import OpenAILLMSettings from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams @@ -62,7 +62,9 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): llm = GrokLLMService( api_key=os.getenv("GROK_API_KEY"), - system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + settings=GrokLLMSettings( + system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + ), ) context = LLMContext() diff --git a/examples/foundational/55zzb-update-settings-groq-llm.py b/examples/foundational/55zzb-update-settings-groq-llm.py index 35cec306f..3f2ffdb79 100644 --- a/examples/foundational/55zzb-update-settings-groq-llm.py +++ b/examples/foundational/55zzb-update-settings-groq-llm.py @@ -62,8 +62,10 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): llm = GroqLLMService( api_key=os.getenv("GROQ_API_KEY"), - settings=GroqLLMSettings(model="meta-llama/llama-4-maverick-17b-128e-instruct"), - system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + settings=GroqLLMSettings( + model="meta-llama/llama-4-maverick-17b-128e-instruct", + system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + ), ) context = LLMContext() diff --git a/examples/foundational/55zzc-update-settings-mistral-llm.py b/examples/foundational/55zzc-update-settings-mistral-llm.py index f6fa824d4..b9d591146 100644 --- a/examples/foundational/55zzc-update-settings-mistral-llm.py +++ b/examples/foundational/55zzc-update-settings-mistral-llm.py @@ -24,7 +24,7 @@ from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport from pipecat.services.cartesia.tts import CartesiaTTSService, CartesiaTTSSettings from pipecat.services.deepgram.stt import DeepgramSTTService -from pipecat.services.mistral.llm import MistralLLMService +from pipecat.services.mistral.llm import MistralLLMService, MistralLLMSettings from pipecat.services.openai.base_llm import OpenAILLMSettings from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams @@ -62,7 +62,9 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): llm = MistralLLMService( api_key=os.getenv("MISTRAL_API_KEY"), - system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + settings=MistralLLMSettings( + system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + ), ) context = LLMContext() diff --git a/examples/foundational/55zzd-update-settings-nvidia-llm.py b/examples/foundational/55zzd-update-settings-nvidia-llm.py index 68d168461..389b51f06 100644 --- a/examples/foundational/55zzd-update-settings-nvidia-llm.py +++ b/examples/foundational/55zzd-update-settings-nvidia-llm.py @@ -62,8 +62,10 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): llm = NvidiaLLMService( api_key=os.getenv("NVIDIA_API_KEY"), - settings=NvidiaLLMSettings(model="meta/llama-3.1-405b-instruct"), - system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + settings=NvidiaLLMSettings( + model="meta/llama-3.1-405b-instruct", + system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + ), ) context = LLMContext() diff --git a/examples/foundational/55zze-update-settings-ollama-llm.py b/examples/foundational/55zze-update-settings-ollama-llm.py index 8a3a5f973..d413267a3 100644 --- a/examples/foundational/55zze-update-settings-ollama-llm.py +++ b/examples/foundational/55zze-update-settings-ollama-llm.py @@ -61,8 +61,10 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): ) llm = OLLamaLLMService( - settings=OllamaLLMSettings(model="llama3.2"), - system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + settings=OllamaLLMSettings( + model="llama3.2", + system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + ), ) # Update to the model you're running locally context = LLMContext() diff --git a/examples/foundational/55zzf-update-settings-openrouter-llm.py b/examples/foundational/55zzf-update-settings-openrouter-llm.py index c31a7c43c..c34d885f1 100644 --- a/examples/foundational/55zzf-update-settings-openrouter-llm.py +++ b/examples/foundational/55zzf-update-settings-openrouter-llm.py @@ -25,7 +25,7 @@ from pipecat.runner.utils import create_transport from pipecat.services.cartesia.tts import CartesiaTTSService, CartesiaTTSSettings from pipecat.services.deepgram.stt import DeepgramSTTService from pipecat.services.openai.base_llm import OpenAILLMSettings -from pipecat.services.openrouter.llm import OpenRouterLLMService +from pipecat.services.openrouter.llm import OpenRouterLLMService, OpenRouterLLMSettings from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams @@ -62,7 +62,9 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): llm = OpenRouterLLMService( api_key=os.getenv("OPENROUTER_API_KEY"), - system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + settings=OpenRouterLLMSettings( + system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + ), ) context = LLMContext() diff --git a/examples/foundational/55zzh-update-settings-qwen-llm.py b/examples/foundational/55zzh-update-settings-qwen-llm.py index dd95308ec..584cb23ea 100644 --- a/examples/foundational/55zzh-update-settings-qwen-llm.py +++ b/examples/foundational/55zzh-update-settings-qwen-llm.py @@ -62,8 +62,10 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): llm = QwenLLMService( api_key=os.getenv("QWEN_API_KEY"), - settings=QwenLLMSettings(model="qwen2.5-72b-instruct"), - system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + settings=QwenLLMSettings( + model="qwen2.5-72b-instruct", + system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + ), ) context = LLMContext() diff --git a/examples/foundational/55zzi-update-settings-sambanova-llm.py b/examples/foundational/55zzi-update-settings-sambanova-llm.py index cececc078..dc246f2cd 100644 --- a/examples/foundational/55zzi-update-settings-sambanova-llm.py +++ b/examples/foundational/55zzi-update-settings-sambanova-llm.py @@ -25,7 +25,7 @@ from pipecat.runner.utils import create_transport from pipecat.services.cartesia.tts import CartesiaTTSService, CartesiaTTSSettings from pipecat.services.deepgram.stt import DeepgramSTTService from pipecat.services.openai.base_llm import OpenAILLMSettings -from pipecat.services.sambanova.llm import SambaNovaLLMService +from pipecat.services.sambanova.llm import SambaNovaLLMService, SambaNovaLLMSettings from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams @@ -62,7 +62,9 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): llm = SambaNovaLLMService( api_key=os.getenv("SAMBANOVA_API_KEY"), - system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + settings=SambaNovaLLMSettings( + system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + ), ) context = LLMContext() diff --git a/examples/foundational/55zzj-update-settings-together-llm.py b/examples/foundational/55zzj-update-settings-together-llm.py index c3cfafea2..bd855bcff 100644 --- a/examples/foundational/55zzj-update-settings-together-llm.py +++ b/examples/foundational/55zzj-update-settings-together-llm.py @@ -62,8 +62,10 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): llm = TogetherLLMService( api_key=os.getenv("TOGETHER_API_KEY"), - settings=TogetherLLMSettings(model="meta-llama/Meta-Llama-3.1-70B-Instruct-Turbo"), - system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + settings=TogetherLLMSettings( + model="meta-llama/Meta-Llama-3.1-70B-Instruct-Turbo", + system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + ), ) context = LLMContext() diff --git a/examples/foundational/55zzl-update-settings-nvidia-tts.py b/examples/foundational/55zzl-update-settings-nvidia-tts.py index 5bc89bd58..e667a9ca3 100644 --- a/examples/foundational/55zzl-update-settings-nvidia-tts.py +++ b/examples/foundational/55zzl-update-settings-nvidia-tts.py @@ -24,7 +24,7 @@ from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport from pipecat.services.deepgram.stt import DeepgramSTTService from pipecat.services.nvidia.tts import NvidiaTTSService, NvidiaTTSSettings -from pipecat.services.openai.llm import OpenAILLMService +from pipecat.services.openai.llm import OpenAILLMService, OpenAILLMSettings from pipecat.transcriptions.language import Language from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams @@ -57,7 +57,9 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): llm = OpenAILLMService( api_key=os.getenv("OPENAI_API_KEY"), - system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + settings=OpenAILLMSettings( + system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + ), ) context = LLMContext() diff --git a/examples/foundational/55zzm-update-settings-speechmatics-tts.py b/examples/foundational/55zzm-update-settings-speechmatics-tts.py index d9eaaec86..2e8bb46a6 100644 --- a/examples/foundational/55zzm-update-settings-speechmatics-tts.py +++ b/examples/foundational/55zzm-update-settings-speechmatics-tts.py @@ -24,7 +24,7 @@ from pipecat.processors.aggregators.llm_response_universal import ( from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport from pipecat.services.deepgram.stt import DeepgramSTTService -from pipecat.services.openai.llm import OpenAILLMService +from pipecat.services.openai.llm import OpenAILLMService, OpenAILLMSettings from pipecat.services.speechmatics.tts import SpeechmaticsTTSService, SpeechmaticsTTSSettings from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams @@ -61,7 +61,9 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): llm = OpenAILLMService( api_key=os.getenv("OPENAI_API_KEY"), - system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + settings=OpenAILLMSettings( + system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + ), ) context = LLMContext() diff --git a/examples/foundational/55zzn-update-settings-groq-stt.py b/examples/foundational/55zzn-update-settings-groq-stt.py index 7a8551be2..d6dac9e1f 100644 --- a/examples/foundational/55zzn-update-settings-groq-stt.py +++ b/examples/foundational/55zzn-update-settings-groq-stt.py @@ -24,7 +24,7 @@ from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport from pipecat.services.cartesia.tts import CartesiaTTSService, CartesiaTTSSettings from pipecat.services.groq.stt import GroqSTTService -from pipecat.services.openai.llm import OpenAILLMService +from pipecat.services.openai.llm import OpenAILLMService, OpenAILLMSettings from pipecat.services.whisper.base_stt import BaseWhisperSTTSettings from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams @@ -64,7 +64,9 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): llm = OpenAILLMService( api_key=os.getenv("OPENAI_API_KEY"), - system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + settings=OpenAILLMSettings( + system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + ), ) context = LLMContext() diff --git a/examples/foundational/56-lemonslice-transport.py b/examples/foundational/56-lemonslice-transport.py index 6085f3b00..8dc400841 100644 --- a/examples/foundational/56-lemonslice-transport.py +++ b/examples/foundational/56-lemonslice-transport.py @@ -24,7 +24,7 @@ from pipecat.processors.aggregators.llm_response_universal import ( ) from pipecat.services.deepgram.stt import DeepgramSTTService from pipecat.services.elevenlabs.tts import ElevenLabsTTSService, ElevenLabsTTSSettings -from pipecat.services.groq.llm import GroqLLMService +from pipecat.services.groq.llm import GroqLLMService, GroqLLMSettings from pipecat.transports.lemonslice.transport import ( LemonSliceNewSessionRequest, LemonSliceParams, @@ -57,7 +57,9 @@ async def main(): llm = GroqLLMService( api_key=os.getenv("GROQ_API_KEY"), - system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + settings=GroqLLMSettings( + system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + ), ) tts = ElevenLabsTTSService( diff --git a/src/pipecat/services/anthropic/llm.py b/src/pipecat/services/anthropic/llm.py index 170c7e425..369c2a4ed 100644 --- a/src/pipecat/services/anthropic/llm.py +++ b/src/pipecat/services/anthropic/llm.py @@ -223,7 +223,6 @@ class AnthropicLLMService(LLMService): client=None, retry_timeout_secs: Optional[float] = 5.0, retry_on_timeout: Optional[bool] = False, - system_instruction: Optional[str] = None, **kwargs, ): """Initialize the Anthropic LLM service. @@ -246,12 +245,12 @@ class AnthropicLLMService(LLMService): client: Optional custom Anthropic client instance. retry_timeout_secs: Request timeout in seconds for retry logic. retry_on_timeout: Whether to retry the request once if it times out. - system_instruction: Optional system instruction to use as the system prompt. **kwargs: Additional arguments passed to parent LLMService. """ # 1. Initialize default_settings with hardcoded defaults default_settings = AnthropicLLMSettings( model="claude-sonnet-4-6", + system_instruction=None, max_tokens=4096, enable_prompt_caching=False, temperature=NOT_GIVEN, @@ -309,9 +308,8 @@ class AnthropicLLMService(LLMService): ) # if the client is provided, use it and remove it, otherwise create a new one self._retry_timeout_secs = retry_timeout_secs self._retry_on_timeout = retry_on_timeout - self._system_instruction = system_instruction - if self._system_instruction: - logger.debug(f"{self}: Using system instruction: {self._system_instruction}") + if self._settings.system_instruction: + logger.debug(f"{self}: Using system instruction: {self._settings.system_instruction}") def can_generate_metrics(self) -> bool: """Check if this service can generate usage metrics. @@ -445,13 +443,13 @@ class AnthropicLLMService(LLMService): params: AnthropicLLMInvocationParams = adapter.get_llm_invocation_params( context, enable_prompt_caching=self._settings.enable_prompt_caching ) - if self._system_instruction: + if self._settings.system_instruction: if params["system"] is not NOT_GIVEN: logger.warning( f"{self}: Both system_instruction and a system message in context are" " set. Using system_instruction." ) - params["system"] = self._system_instruction + params["system"] = self._settings.system_instruction return params # Anthropic-specific context diff --git a/src/pipecat/services/aws/llm.py b/src/pipecat/services/aws/llm.py index 3b0392a0e..34a0dd780 100644 --- a/src/pipecat/services/aws/llm.py +++ b/src/pipecat/services/aws/llm.py @@ -788,7 +788,6 @@ class AWSBedrockLLMService(LLMService): client_config: Optional[Config] = None, retry_timeout_secs: Optional[float] = 5.0, retry_on_timeout: Optional[bool] = False, - system_instruction: Optional[str] = None, **kwargs, ): """Initialize the AWS Bedrock LLM service. @@ -819,12 +818,12 @@ class AWSBedrockLLMService(LLMService): client_config: Custom boto3 client configuration. retry_timeout_secs: Request timeout in seconds for retry logic. retry_on_timeout: Whether to retry the request once if it times out. - system_instruction: Optional system instruction to use as the system prompt. **kwargs: Additional arguments passed to parent LLMService. """ # 1. Initialize default_settings with hardcoded defaults default_settings = AWSBedrockLLMSettings( model="us.amazon.nova-lite-v1:0", + system_instruction=None, max_tokens=None, temperature=None, top_p=None, @@ -889,11 +888,10 @@ class AWSBedrockLLMService(LLMService): self._retry_timeout_secs = retry_timeout_secs self._retry_on_timeout = retry_on_timeout - self._system_instruction = system_instruction logger.info(f"Using AWS Bedrock model: {self._settings.model}") - if self._system_instruction: - logger.debug(f"{self}: Using system instruction: {self._system_instruction}") + if self._settings.system_instruction: + logger.debug(f"{self}: Using system instruction: {self._settings.system_instruction}") def can_generate_metrics(self) -> bool: """Check if the service can generate usage metrics. @@ -1074,13 +1072,13 @@ class AWSBedrockLLMService(LLMService): if isinstance(context, LLMContext): adapter: AWSBedrockLLMAdapter = self.get_llm_adapter() params: AWSBedrockLLMInvocationParams = adapter.get_llm_invocation_params(context) - if self._system_instruction: + if self._settings.system_instruction: if params["system"]: logger.warning( f"{self}: Both system_instruction and a system message in context are" " set. Using system_instruction." ) - params["system"] = [{"text": self._system_instruction}] + params["system"] = [{"text": self._settings.system_instruction}] return params # AWS Bedrock-specific context diff --git a/src/pipecat/services/cerebras/llm.py b/src/pipecat/services/cerebras/llm.py index d98a2d7a4..c3b56ff29 100644 --- a/src/pipecat/services/cerebras/llm.py +++ b/src/pipecat/services/cerebras/llm.py @@ -111,4 +111,12 @@ class CerebrasLLMService(OpenAILLMService): params.update(params_from_context) params.update(self._settings.extra) + + # Prepend system instruction if set + if self._settings.system_instruction: + messages = params.get("messages", []) + params["messages"] = [ + {"role": "system", "content": self._settings.system_instruction} + ] + messages + return params diff --git a/src/pipecat/services/fireworks/llm.py b/src/pipecat/services/fireworks/llm.py index 86665cc48..ccc9107f6 100644 --- a/src/pipecat/services/fireworks/llm.py +++ b/src/pipecat/services/fireworks/llm.py @@ -112,4 +112,12 @@ class FireworksLLMService(OpenAILLMService): params.update(params_from_context) params.update(self._settings.extra) + + # Prepend system instruction if set + if self._settings.system_instruction: + messages = params.get("messages", []) + params["messages"] = [ + {"role": "system", "content": self._settings.system_instruction} + ] + messages + return params diff --git a/src/pipecat/services/google/llm.py b/src/pipecat/services/google/llm.py index 49e6d2366..980d2d576 100644 --- a/src/pipecat/services/google/llm.py +++ b/src/pipecat/services/google/llm.py @@ -809,6 +809,9 @@ class GoogleLLMService(LLMService): deprecated parameters and *settings* are provided, *settings* values take precedence. system_instruction: System instruction/prompt for the model. + + .. deprecated:: 0.0.105 + Use ``settings=GoogleLLMSettings(system_instruction=...)`` instead. tools: List of available tools/functions. tool_config: Configuration for tool usage. http_options: HTTP options for the client. @@ -817,6 +820,7 @@ class GoogleLLMService(LLMService): # 1. Initialize default_settings with hardcoded defaults default_settings = GoogleLLMSettings( model="gemini-2.5-flash", + system_instruction=None, max_tokens=4096, temperature=None, top_k=None, @@ -834,6 +838,9 @@ class GoogleLLMService(LLMService): if model is not None: _warn_deprecated_param("model", GoogleLLMSettings, "model") default_settings.model = model + if system_instruction is not None: + _warn_deprecated_param("system_instruction", GoogleLLMSettings, "system_instruction") + default_settings.system_instruction = system_instruction # 3. Apply params overrides — only if settings not provided if params is not None: @@ -854,7 +861,6 @@ class GoogleLLMService(LLMService): super().__init__(settings=default_settings, **kwargs) self._api_key = api_key - self._system_instruction = system_instruction self._http_options = update_google_client_http_options(http_options) self._tools = tools self._tool_config = tool_config @@ -993,10 +999,10 @@ class GoogleLLMService(LLMService): messages = params_from_context["messages"] if ( params_from_context["system_instruction"] - and self._system_instruction != params_from_context["system_instruction"] + and self._settings.system_instruction != params_from_context["system_instruction"] ): logger.debug(f"System instruction changed: {params_from_context['system_instruction']}") - self._system_instruction = params_from_context["system_instruction"] + self._settings.system_instruction = params_from_context["system_instruction"] tools = [] if params_from_context["tools"]: @@ -1009,7 +1015,9 @@ class GoogleLLMService(LLMService): # Build generation parameters generation_params = self._build_generation_params( - system_instruction=self._system_instruction, tools=tools, tool_config=tool_config + system_instruction=self._settings.system_instruction, + tools=tools, + tool_config=tool_config, ) # possibly modify generation_params (in place) to set thinking to off by default diff --git a/src/pipecat/services/google/llm_vertex.py b/src/pipecat/services/google/llm_vertex.py index 27f168042..42d96333c 100644 --- a/src/pipecat/services/google/llm_vertex.py +++ b/src/pipecat/services/google/llm_vertex.py @@ -142,6 +142,9 @@ class GoogleVertexLLMService(GoogleLLMService): deprecated parameters and *settings* are provided, *settings* values take precedence. system_instruction: System instruction/prompt for the model. + + .. deprecated:: 0.0.105 + Use ``settings=GoogleVertexLLMSettings(system_instruction=...)`` instead. tools: List of available tools/functions. tool_config: Configuration for tool usage. http_options: HTTP options for the client. @@ -195,6 +198,7 @@ class GoogleVertexLLMService(GoogleLLMService): # 1. Initialize default_settings with hardcoded defaults default_settings = GoogleVertexLLMSettings( model="gemini-2.5-flash", + system_instruction=None, max_tokens=4096, temperature=None, top_k=None, @@ -212,6 +216,11 @@ class GoogleVertexLLMService(GoogleLLMService): if model is not None: _warn_deprecated_param("model", GoogleVertexLLMSettings, "model") default_settings.model = model + if system_instruction is not None: + _warn_deprecated_param( + "system_instruction", GoogleVertexLLMSettings, "system_instruction" + ) + default_settings.system_instruction = system_instruction # 3. Apply params overrides — only if settings not provided if params is not None: @@ -234,7 +243,6 @@ class GoogleVertexLLMService(GoogleLLMService): super().__init__( api_key="dummy", settings=default_settings, - system_instruction=system_instruction, tools=tools, tool_config=tool_config, http_options=http_options, diff --git a/src/pipecat/services/mistral/llm.py b/src/pipecat/services/mistral/llm.py index 801c02f9e..647a56bca 100644 --- a/src/pipecat/services/mistral/llm.py +++ b/src/pipecat/services/mistral/llm.py @@ -231,4 +231,11 @@ class MistralLLMService(OpenAILLMService): # Add any extra parameters params.update(self._settings.extra) + # Prepend system instruction if set + if self._settings.system_instruction: + messages = params.get("messages", []) + params["messages"] = [ + {"role": "system", "content": self._settings.system_instruction} + ] + messages + return params diff --git a/src/pipecat/services/openai/base_llm.py b/src/pipecat/services/openai/base_llm.py index cf4101305..5e59a5129 100644 --- a/src/pipecat/services/openai/base_llm.py +++ b/src/pipecat/services/openai/base_llm.py @@ -121,7 +121,6 @@ class BaseOpenAILLMService(LLMService): settings: Optional[OpenAILLMSettings] = None, retry_timeout_secs: Optional[float] = 5.0, retry_on_timeout: Optional[bool] = False, - system_instruction: Optional[str] = None, **kwargs, ): """Initialize the BaseOpenAILLMService. @@ -147,12 +146,12 @@ class BaseOpenAILLMService(LLMService): parameters, ``settings`` values take precedence. retry_timeout_secs: Request timeout in seconds. Defaults to 5.0 seconds. retry_on_timeout: Whether to retry the request once if it times out. - system_instruction: Optional system instruction to prepend to messages. **kwargs: Additional arguments passed to the parent LLMService. """ # 1. Initialize default_settings with hardcoded defaults default_settings = OpenAILLMSettings( model="gpt-4o", + system_instruction=None, frequency_penalty=NOT_GIVEN, presence_penalty=NOT_GIVEN, seed=NOT_GIVEN, @@ -193,7 +192,6 @@ class BaseOpenAILLMService(LLMService): self._service_tier = service_tier self._retry_timeout_secs = retry_timeout_secs self._retry_on_timeout = retry_on_timeout - self._system_instruction = system_instruction self._full_model_name: str = "" self._client = self.create_client( api_key=api_key, @@ -204,8 +202,8 @@ class BaseOpenAILLMService(LLMService): **kwargs, ) - if self._system_instruction: - logger.debug(f"{self}: Using system instruction: {self._system_instruction}") + if self._settings.system_instruction: + logger.debug(f"{self}: Using system instruction: {self._settings.system_instruction}") def create_client( self, @@ -329,7 +327,7 @@ class BaseOpenAILLMService(LLMService): params.update(self._settings.extra) # Prepend system instruction from constructor, replacing any context system message - if self._system_instruction: + if self._settings.system_instruction: messages = params.get("messages", []) if messages and messages[0].get("role") == "system": logger.warning( @@ -337,7 +335,7 @@ class BaseOpenAILLMService(LLMService): " Using system_instruction." ) params["messages"] = [ - {"role": "system", "content": self._system_instruction} + {"role": "system", "content": self._settings.system_instruction} ] + messages return params diff --git a/src/pipecat/services/openai/llm.py b/src/pipecat/services/openai/llm.py index f2e3ad00a..ab1384a4c 100644 --- a/src/pipecat/services/openai/llm.py +++ b/src/pipecat/services/openai/llm.py @@ -102,6 +102,7 @@ class OpenAILLMService(BaseOpenAILLMService): # 1. Initialize default_settings with hardcoded defaults default_settings = OpenAILLMSettings( model="gpt-4.1", + system_instruction=None, frequency_penalty=NOT_GIVEN, presence_penalty=NOT_GIVEN, seed=NOT_GIVEN, diff --git a/src/pipecat/services/perplexity/llm.py b/src/pipecat/services/perplexity/llm.py index 9969020c5..137fdeeb9 100644 --- a/src/pipecat/services/perplexity/llm.py +++ b/src/pipecat/services/perplexity/llm.py @@ -114,6 +114,13 @@ class PerplexityLLMService(OpenAILLMService): if self._settings.max_tokens is not None: params["max_tokens"] = self._settings.max_tokens + # Prepend system instruction if set + if self._settings.system_instruction: + messages = params.get("messages", []) + params["messages"] = [ + {"role": "system", "content": self._settings.system_instruction} + ] + messages + return params async def _process_context(self, context: OpenAILLMContext | LLMContext): diff --git a/src/pipecat/services/sambanova/llm.py b/src/pipecat/services/sambanova/llm.py index cdd2139da..0c92db098 100644 --- a/src/pipecat/services/sambanova/llm.py +++ b/src/pipecat/services/sambanova/llm.py @@ -128,6 +128,14 @@ class SambaNovaLLMService(OpenAILLMService): # type: ignore params.update(params_from_context) params.update(self._settings.extra) + + # Prepend system instruction if set + if self._settings.system_instruction: + messages = params.get("messages", []) + params["messages"] = [ + {"role": "system", "content": self._settings.system_instruction} + ] + messages + return params @traced_llm # type: ignore diff --git a/src/pipecat/services/settings.py b/src/pipecat/services/settings.py index d9ec5bc7b..c9a120972 100644 --- a/src/pipecat/services/settings.py +++ b/src/pipecat/services/settings.py @@ -395,6 +395,7 @@ class LLMSettings(ServiceSettings): Parameters: model: LLM model identifier. + system_instruction: System instruction/prompt for the model. temperature: Sampling temperature. max_tokens: Maximum tokens to generate. top_p: Nucleus sampling probability. @@ -411,6 +412,7 @@ class LLMSettings(ServiceSettings): and prompts for incomplete turns. """ + system_instruction: str | None | _NotGiven = field(default_factory=lambda: NOT_GIVEN) temperature: float | None | _NotGiven = field(default_factory=lambda: NOT_GIVEN) max_tokens: int | None | _NotGiven = field(default_factory=lambda: NOT_GIVEN) top_p: float | None | _NotGiven = field(default_factory=lambda: NOT_GIVEN) From a1641f37625a6a85af5a9ee2a51f51b5296bcb52 Mon Sep 17 00:00:00 2001 From: Paul Kompfner Date: Thu, 5 Mar 2026 15:33:41 -0500 Subject: [PATCH 0821/1060] Add `system_instruction` to realtime service settings Add `system_instruction=None` to `default_settings` for OpenAIRealtimeLLMService, GrokRealtimeLLMService, UltravoxRealtimeLLMService, AWSNovaSonicLLMService (Azure inherits from OpenAI), and OpenAIRealtimeBetaLLMService (Azure Beta inherits from OpenAI Beta). Deprecate `system_instruction` init arg in AWSNovaSonicLLMService in favor of `settings=AWSNovaSonicLLMSettings(system_instruction=...)`. Use `self._settings.system_instruction` directly instead of storing a separate `self._system_instruction`. Deprecation of `params` and `session_properties` in favor of `settings` for realtime services will be tackled in future work. --- src/pipecat/services/aws/nova_sonic/llm.py | 14 +++++++++++--- src/pipecat/services/grok/realtime/llm.py | 1 + src/pipecat/services/openai/realtime/llm.py | 1 + .../services/openai_realtime_beta/openai.py | 1 + src/pipecat/services/ultravox/llm.py | 1 + 5 files changed, 15 insertions(+), 3 deletions(-) diff --git a/src/pipecat/services/aws/nova_sonic/llm.py b/src/pipecat/services/aws/nova_sonic/llm.py index 9103ebdfd..fd13fe56e 100644 --- a/src/pipecat/services/aws/nova_sonic/llm.py +++ b/src/pipecat/services/aws/nova_sonic/llm.py @@ -261,6 +261,9 @@ class AWSNovaSonicLLMService(LLMService): deprecated top-level parameters, the ``settings`` values take precedence. system_instruction: System-level instruction for the model. + + .. deprecated:: 0.0.105 + Use ``settings=AWSNovaSonicLLMSettings(system_instruction=...)`` instead. tools: Available tools/functions for the model to use. send_transcription_frames: Whether to emit transcription frames. @@ -273,6 +276,7 @@ class AWSNovaSonicLLMService(LLMService): # 1. Initialize default_settings with hardcoded defaults default_settings = AWSNovaSonicLLMSettings( model="amazon.nova-2-sonic-v1:0", + system_instruction=None, voice="matthew", temperature=0.7, max_tokens=1024, @@ -293,6 +297,11 @@ class AWSNovaSonicLLMService(LLMService): if voice_id != "matthew": _warn_deprecated_param("voice_id", AWSNovaSonicLLMSettings, "voice") default_settings.voice = voice_id + if system_instruction is not None: + _warn_deprecated_param( + "system_instruction", AWSNovaSonicLLMSettings, "system_instruction" + ) + default_settings.system_instruction = system_instruction # 3. Apply params overrides — only if settings not provided if params is not None: @@ -325,7 +334,6 @@ class AWSNovaSonicLLMService(LLMService): self._output_sample_rate = _audio_params.output_sample_rate self._output_sample_size = _audio_params.output_sample_size self._output_channel_count = _audio_params.output_channel_count - self._system_instruction = system_instruction self._tools = tools # Validate endpointing_sensitivity parameter @@ -625,11 +633,11 @@ class AWSNovaSonicLLMService(LLMService): await self._send_prompt_start_event(tools) # Send system instruction. - # Instruction from context takes priority over self._system_instruction. + # Instruction from context takes priority over self._settings.system_instruction. system_instruction = ( llm_connection_params["system_instruction"] if llm_connection_params["system_instruction"] - else self._system_instruction + else self._settings.system_instruction ) logger.debug(f"Using system instruction: {system_instruction}") if system_instruction: diff --git a/src/pipecat/services/grok/realtime/llm.py b/src/pipecat/services/grok/realtime/llm.py index 638477b5e..074b44c5d 100644 --- a/src/pipecat/services/grok/realtime/llm.py +++ b/src/pipecat/services/grok/realtime/llm.py @@ -144,6 +144,7 @@ class GrokRealtimeLLMService(LLMService): # 1. Initialize default_settings with hardcoded defaults default_settings = GrokRealtimeLLMSettings( model=None, + system_instruction=None, temperature=None, max_tokens=None, top_p=None, diff --git a/src/pipecat/services/openai/realtime/llm.py b/src/pipecat/services/openai/realtime/llm.py index 761d7244b..b5d9dc8e2 100644 --- a/src/pipecat/services/openai/realtime/llm.py +++ b/src/pipecat/services/openai/realtime/llm.py @@ -170,6 +170,7 @@ class OpenAIRealtimeLLMService(LLMService): # 1. Initialize default_settings with hardcoded defaults default_settings = OpenAIRealtimeLLMSettings( model="gpt-realtime-1.5", + system_instruction=None, temperature=None, max_tokens=None, top_p=None, diff --git a/src/pipecat/services/openai_realtime_beta/openai.py b/src/pipecat/services/openai_realtime_beta/openai.py index 67a892e6f..a3f8e47fc 100644 --- a/src/pipecat/services/openai_realtime_beta/openai.py +++ b/src/pipecat/services/openai_realtime_beta/openai.py @@ -158,6 +158,7 @@ class OpenAIRealtimeBetaLLMService(LLMService): # 1. Initialize default_settings with hardcoded defaults default_settings = OpenAIRealtimeBetaLLMSettings( model="gpt-4o-realtime-preview-2025-06-03", + system_instruction=None, temperature=None, max_tokens=None, top_p=None, diff --git a/src/pipecat/services/ultravox/llm.py b/src/pipecat/services/ultravox/llm.py index 094d22827..eccc1a864 100644 --- a/src/pipecat/services/ultravox/llm.py +++ b/src/pipecat/services/ultravox/llm.py @@ -189,6 +189,7 @@ class UltravoxRealtimeLLMService(LLMService): # 1. Initialize default_settings with hardcoded defaults default_settings = UltravoxRealtimeLLMSettings( model=None, + system_instruction=None, temperature=None, max_tokens=None, top_p=None, From 5b270fec8e1cdcf4001c4b7060a118129308fc5a Mon Sep 17 00:00:00 2001 From: Paul Kompfner Date: Thu, 5 Mar 2026 16:09:24 -0500 Subject: [PATCH 0822/1060] In AWS Nova Sonic examples, migrate to newer pattern of passing in `settings` with `voice` and `system_instruction`, in favor of passing in `voice_id` as a direct init arg and the system instruction as the first message in the context --- .../20e-persistent-context-aws-nova-sonic.py | 10 +++++----- examples/foundational/40-aws-nova-sonic.py | 10 +++++----- 2 files changed, 10 insertions(+), 10 deletions(-) diff --git a/examples/foundational/20e-persistent-context-aws-nova-sonic.py b/examples/foundational/20e-persistent-context-aws-nova-sonic.py index 69ffb86b6..7efa2678c 100644 --- a/examples/foundational/20e-persistent-context-aws-nova-sonic.py +++ b/examples/foundational/20e-persistent-context-aws-nova-sonic.py @@ -24,7 +24,7 @@ from pipecat.processors.aggregators.llm_context import LLMContext from pipecat.processors.aggregators.llm_response_universal import LLMContextAggregatorPair from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport -from pipecat.services.aws.nova_sonic.llm import AWSNovaSonicLLMService +from pipecat.services.aws.nova_sonic.llm import AWSNovaSonicLLMService, AWSNovaSonicLLMSettings from pipecat.services.llm_service import FunctionCallParams from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams @@ -222,9 +222,10 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): secret_access_key=os.getenv("AWS_SECRET_ACCESS_KEY"), access_key_id=os.getenv("AWS_ACCESS_KEY_ID"), region=os.getenv("AWS_REGION"), # as of 2025-05-06, us-east-1 is the only supported region - voice_id="tiffany", # matthew, tiffany, amy - # you could choose to pass instruction here rather than via context - # system_instruction=system_instruction, + settings=AWSNovaSonicLLMSettings( + voice="tiffany", # matthew, tiffany, amy + system_instruction=system_instruction, + ), # you could choose to pass tools here rather than via context # tools=tools ) @@ -236,7 +237,6 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): context = LLMContext( messages=[ - {"role": "system", "content": f"{system_instruction}"}, {"role": "user", "content": "Hello!"}, ], tools=tools, diff --git a/examples/foundational/40-aws-nova-sonic.py b/examples/foundational/40-aws-nova-sonic.py index 1bfa6063e..0bb670d4b 100644 --- a/examples/foundational/40-aws-nova-sonic.py +++ b/examples/foundational/40-aws-nova-sonic.py @@ -28,7 +28,7 @@ from pipecat.processors.aggregators.llm_response_universal import ( ) from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport -from pipecat.services.aws.nova_sonic.llm import AWSNovaSonicLLMService +from pipecat.services.aws.nova_sonic.llm import AWSNovaSonicLLMService, AWSNovaSonicLLMSettings from pipecat.services.llm_service import FunctionCallParams from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams @@ -130,9 +130,10 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): # - ap-northeast-1 region=os.getenv("AWS_REGION"), session_token=os.getenv("AWS_SESSION_TOKEN"), - voice_id="tiffany", - # you could choose to pass instruction here rather than via context - # system_instruction=system_instruction + settings=AWSNovaSonicLLMSettings( + voice="tiffany", + system_instruction=system_instruction, + ), # you could choose to pass tools here rather than via context # tools=tools ) @@ -147,7 +148,6 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): # Set up context and context management. context = LLMContext( messages=[ - {"role": "system", "content": f"{system_instruction}"}, { "role": "user", "content": "Tell me a fun fact!", From 848f35f5dff94963d45dadcf891bcf6776c0eb2b Mon Sep 17 00:00:00 2001 From: kigland Date: Fri, 6 Mar 2026 23:05:02 +0800 Subject: [PATCH 0823/1060] fix: replace bare except handlers with specific exception types --- examples/foundational/39-mcp-stdio.py | 2 +- examples/foundational/39c-multiple-mcp.py | 2 +- src/pipecat/adapters/services/bedrock_adapter.py | 2 +- src/pipecat/serializers/telnyx.py | 2 +- src/pipecat/serializers/twilio.py | 2 +- src/pipecat/services/aws/llm.py | 2 +- src/pipecat/services/mcp_service.py | 2 +- 7 files changed, 7 insertions(+), 7 deletions(-) diff --git a/examples/foundational/39-mcp-stdio.py b/examples/foundational/39-mcp-stdio.py index 2daf21626..51a15d68c 100644 --- a/examples/foundational/39-mcp-stdio.py +++ b/examples/foundational/39-mcp-stdio.py @@ -70,7 +70,7 @@ class UrlToImageProcessor(FrameProcessor): return data["artObject"]["webImage"]["url"] if "artworks" in data and len(data["artworks"]): return data["artworks"][0]["webImage"]["url"] - except: + except (json.JSONDecodeError, KeyError, TypeError): pass return None diff --git a/examples/foundational/39c-multiple-mcp.py b/examples/foundational/39c-multiple-mcp.py index 5f662cdb8..3349e04e6 100644 --- a/examples/foundational/39c-multiple-mcp.py +++ b/examples/foundational/39c-multiple-mcp.py @@ -72,7 +72,7 @@ class UrlToImageProcessor(FrameProcessor): return data["artObject"]["webImage"]["url"] if "artworks" in data and len(data["artworks"]): return data["artworks"][0]["webImage"]["url"] - except: + except (json.JSONDecodeError, KeyError, TypeError): pass async def run_image_process(self, image_url: str): diff --git a/src/pipecat/adapters/services/bedrock_adapter.py b/src/pipecat/adapters/services/bedrock_adapter.py index ccbbe5e2e..8fd474cb6 100644 --- a/src/pipecat/adapters/services/bedrock_adapter.py +++ b/src/pipecat/adapters/services/bedrock_adapter.py @@ -209,7 +209,7 @@ class AWSBedrockLLMAdapter(BaseLLMAdapter[AWSBedrockLLMInvocationParams]): tool_result_content = [{"json": content_json}] else: tool_result_content = [{"text": message["content"]}] - except: + except (json.JSONDecodeError, ValueError): tool_result_content = [{"text": message["content"]}] return { diff --git a/src/pipecat/serializers/telnyx.py b/src/pipecat/serializers/telnyx.py index 769244f93..1c0405ade 100644 --- a/src/pipecat/serializers/telnyx.py +++ b/src/pipecat/serializers/telnyx.py @@ -198,7 +198,7 @@ class TelnyxFrameSerializer(FrameSerializer): f"Telnyx call {call_control_id} was already terminated" ) return - except: + except Exception: pass # Fall through to log the raw error # Log other 422 errors diff --git a/src/pipecat/serializers/twilio.py b/src/pipecat/serializers/twilio.py index 72fec4f28..bf92a9043 100644 --- a/src/pipecat/serializers/twilio.py +++ b/src/pipecat/serializers/twilio.py @@ -212,7 +212,7 @@ class TwilioFrameSerializer(FrameSerializer): if error_data.get("code") == 20404: logger.debug(f"Twilio call {call_sid} was already terminated") return - except: + except Exception: pass # Fall through to log the raw error # Log other 404 errors diff --git a/src/pipecat/services/aws/llm.py b/src/pipecat/services/aws/llm.py index e465ae460..8f614cf8f 100644 --- a/src/pipecat/services/aws/llm.py +++ b/src/pipecat/services/aws/llm.py @@ -369,7 +369,7 @@ class AWSBedrockLLMContext(OpenAILLMContext): tool_result_content = [{"json": content_json}] else: tool_result_content = [{"text": message["content"]}] - except: + except (json.JSONDecodeError, ValueError): tool_result_content = [{"text": message["content"]}] return { diff --git a/src/pipecat/services/mcp_service.py b/src/pipecat/services/mcp_service.py index 936e210d2..302185719 100644 --- a/src/pipecat/services/mcp_service.py +++ b/src/pipecat/services/mcp_service.py @@ -298,7 +298,7 @@ class MCPClient(BaseObject): try: logger.debug(f"Found {len(available_tools)} available tools") - except: + except Exception: pass for tool in available_tools.tools: From bd4229ea9dd81e639e74be94680e80cea741efe1 Mon Sep 17 00:00:00 2001 From: Paul Kompfner Date: Fri, 6 Mar 2026 11:43:55 -0500 Subject: [PATCH 0824/1060] Adopt the `settings` pattern for OpenAI Realtime session properties MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit Move `session_properties` into `OpenAIRealtimeLLMSettings`, making `settings` the canonical way to configure OpenAI Realtime — matching the pattern used across the rest of the codebase. The `session_properties` init arg is now deprecated in favor of `settings=OpenAIRealtimeLLMSettings(session_properties=...)`. `model` and `system_instruction` are synced bidirectionally between the top-level settings fields and `session_properties.model`/`.instructions`, with top-level taking precedence on conflict. --- src/pipecat/services/openai/realtime/llm.py | 173 ++++++++++++++--- tests/test_settings.py | 200 ++++++++++++++++++++ 2 files changed, 346 insertions(+), 27 deletions(-) diff --git a/src/pipecat/services/openai/realtime/llm.py b/src/pipecat/services/openai/realtime/llm.py index b5d9dc8e2..36c6d8fae 100644 --- a/src/pipecat/services/openai/realtime/llm.py +++ b/src/pipecat/services/openai/realtime/llm.py @@ -10,8 +10,9 @@ import base64 import io import json import time -from dataclasses import dataclass -from typing import Any, Optional +from dataclasses import dataclass, field +from dataclasses import fields as dataclass_fields +from typing import Any, Dict, Mapping, Optional, Type from loguru import logger from PIL import Image @@ -59,7 +60,13 @@ from pipecat.processors.aggregators.openai_llm_context import ( ) from pipecat.processors.frame_processor import FrameDirection from pipecat.services.llm_service import FunctionCallFromLLM, LLMService -from pipecat.services.settings import LLMSettings, _warn_deprecated_param +from pipecat.services.settings import ( + NOT_GIVEN, + LLMSettings, + _NotGiven, + _warn_deprecated_param, + is_given, +) from pipecat.transcriptions.language import Language from pipecat.utils.time import time_now_iso8601 from pipecat.utils.tracing.service_decorators import traced_openai_realtime, traced_stt @@ -93,9 +100,107 @@ class CurrentAudioResponse: @dataclass class OpenAIRealtimeLLMSettings(LLMSettings): - """Settings for OpenAI Realtime LLM services.""" + """Settings for OpenAI Realtime LLM services. - pass + Parameters: + session_properties: OpenAI Realtime session properties (modalities, + audio config, tools, etc.). ``model`` and ``instructions`` are + synced bidirectionally with the top-level ``model`` and + ``system_instruction`` fields. + """ + + session_properties: events.SessionProperties | _NotGiven = field( + default_factory=lambda: NOT_GIVEN + ) + + # -- Bidirectional sync helpers ------------------------------------------ + + @staticmethod + def _sync_top_level_to_sp(settings: "OpenAIRealtimeLLMSettings"): + """Push top-level ``model``/``system_instruction`` into ``session_properties``.""" + if not is_given(settings.session_properties): + return + sp = settings.session_properties + if is_given(settings.model) and settings.model is not None: + sp.model = settings.model + if is_given(settings.system_instruction): + sp.instructions = settings.system_instruction + + # -- apply_update override ----------------------------------------------- + + def apply_update(self, delta: "OpenAIRealtimeLLMSettings") -> Dict[str, Any]: + """Merge a delta, keeping ``model``/``system_instruction`` in sync with SP. + + When the delta contains ``session_properties``, it **replaces** the + stored SP wholesale (matching legacy behaviour). Top-level field + values always take precedence over conflicting SP values. + """ + # 1. Let the base class handle all fields including session_properties + # (wholesale replacement when given). + changed = super().apply_update(delta) + + # 2. SP → top-level: if the SP was just replaced and carries + # model/instructions that the delta didn't set at top level, + # pull them up. + if "session_properties" in changed and is_given(self.session_properties): + sp = self.session_properties + if "model" not in changed and sp.model is not None: + old_model = self.model + self.model = sp.model + if old_model != self.model: + changed["model"] = old_model + if "system_instruction" not in changed and sp.instructions is not None: + old_si = self.system_instruction + self.system_instruction = sp.instructions + if old_si != self.system_instruction: + changed["system_instruction"] = old_si + + # 3. Top-level → SP: ensure SP mirrors the authoritative top-level + # values. Covers all cases: top-level-only delta, SP-only delta, + # and mixed deltas where top-level takes precedence. + self._sync_top_level_to_sp(self) + + return changed + + # -- from_mapping override ----------------------------------------------- + + @classmethod + def from_mapping( + cls: Type["OpenAIRealtimeLLMSettings"], settings: Mapping[str, Any] + ) -> "OpenAIRealtimeLLMSettings": + """Build a delta from a plain dict, routing SP keys into ``session_properties``. + + Keys that correspond to ``SessionProperties`` fields (except ``model``) + are collected into a nested ``session_properties`` value. ``model`` is + always routed to the top-level field. Unknown keys go to ``extra``. + """ + # Determine which keys belong to our own dataclass fields. + own_field_names = {f.name for f in dataclass_fields(cls)} - {"extra"} + + top: Dict[str, Any] = {} + sp_dict: Dict[str, Any] = {} + extra: Dict[str, Any] = {} + + # Build the SP field set without instantiating (avoid __post_init__ + # cost for every from_mapping call). + sp_keys = set(events.SessionProperties.model_fields.keys()) - {"model"} + + for key, value in settings.items(): + # Resolve aliases first + canonical = cls._aliases.get(key, key) + if canonical in own_field_names: + top[canonical] = value + elif canonical in sp_keys: + sp_dict[canonical] = value + else: + extra[key] = value + + if sp_dict: + top["session_properties"] = events.SessionProperties(**sp_dict) + + instance = cls(**top) + instance.extra = extra + return instance class OpenAIRealtimeLLMService(LLMService): @@ -140,6 +245,10 @@ class OpenAIRealtimeLLMService(LLMService): Defaults to "wss://api.openai.com/v1/realtime". session_properties: Configuration properties for the realtime session. If None, uses default SessionProperties. + + .. deprecated:: + Use ``settings=OpenAIRealtimeLLMSettings(session_properties=...)`` + instead. settings: Runtime-updatable settings for this service. start_audio_paused: Whether to start with audio input paused. Defaults to False. start_video_paused: Whether to start with video input paused. Defaults to False. @@ -180,6 +289,7 @@ class OpenAIRealtimeLLMService(LLMService): seed=None, filter_incomplete_user_turns=False, user_turn_completion_config=None, + session_properties=events.SessionProperties(), ) # 2. Apply direct init arg overrides (deprecated) @@ -187,6 +297,23 @@ class OpenAIRealtimeLLMService(LLMService): _warn_deprecated_param("model", OpenAIRealtimeLLMSettings, "model") default_settings.model = model + if session_properties is not None: + _warn_deprecated_param( + "session_properties", + OpenAIRealtimeLLMSettings, + "session_properties", + ) + default_settings.session_properties = session_properties + # Sync model/instructions from the deprecated SP arg to top-level, + # but only if the deprecated `model` arg didn't already set it. + if model is None and session_properties.model is not None: + default_settings.model = session_properties.model + if session_properties.instructions is not None: + default_settings.system_instruction = session_properties.instructions + + # Sync top-level model back into session_properties + OpenAIRealtimeLLMSettings._sync_top_level_to_sp(default_settings) + # 3. Apply settings delta (canonical API, always wins) if settings is not None: default_settings.apply_update(settings) @@ -202,7 +329,6 @@ class OpenAIRealtimeLLMService(LLMService): self.api_key = api_key self.base_url = full_url - self._session_properties = session_properties or events.SessionProperties() self._audio_input_paused = start_audio_paused self._video_input_paused = start_video_paused self._video_frame_detail = video_frame_detail @@ -265,12 +391,12 @@ class OpenAIRealtimeLLMService(LLMService): def _is_modality_enabled(self, modality: str) -> bool: """Check if a specific modality is enabled, "text" or "audio".""" - modalities = self._session_properties.output_modalities or ["audio", "text"] + modalities = self._settings.session_properties.output_modalities or ["audio", "text"] return modality in modalities def _get_enabled_modalities(self) -> list[str]: """Get the list of enabled modalities.""" - modalities = self._session_properties.output_modalities or ["audio", "text"] + modalities = self._settings.session_properties.output_modalities or ["audio", "text"] # API only supports single modality responses: either ["text"] or ["audio"] if "audio" in modalities: return ["audio"] @@ -343,9 +469,9 @@ class OpenAIRealtimeLLMService(LLMService): # None and False are different. Check for False. None means we're using OpenAI's # built-in turn detection defaults. turn_detection_disabled = ( - self._session_properties.audio - and self._session_properties.audio.input - and self._session_properties.audio.input.turn_detection is False + self._settings.session_properties.audio + and self._settings.session_properties.audio.input + and self._settings.session_properties.audio.input.turn_detection is False ) if turn_detection_disabled: await self.send_client_event(events.InputAudioBufferClearEvent()) @@ -365,9 +491,9 @@ class OpenAIRealtimeLLMService(LLMService): # None and False are different. Check for False. None means we're using OpenAI's # built-in turn detection defaults. turn_detection_disabled = ( - self._session_properties.audio - and self._session_properties.audio.input - and self._session_properties.audio.input.turn_detection is False + self._settings.session_properties.audio + and self._settings.session_properties.audio.input + and self._settings.session_properties.audio.input.turn_detection is False ) if turn_detection_disabled: await self.send_client_event(events.InputAudioBufferCommitEvent()) @@ -435,16 +561,6 @@ class OpenAIRealtimeLLMService(LLMService): frame: The frame to process. direction: The direction of frame flow in the pipeline. """ - # Backward-compatible dict path: frame.settings contains SessionProperties - # fields, not our Settings fields, so we construct SessionProperties - # directly. The frame.delta path falls through to super, which calls - # _update_settings → our override handles the rest. - if isinstance(frame, LLMUpdateSettingsFrame) and frame.delta is None: - self._session_properties = events.SessionProperties(**frame.settings) - await self._send_session_update() - await self.push_frame(frame, direction) - return - await super().process_frame(frame, direction) if isinstance(frame, TranscriptionFrame): @@ -559,13 +675,16 @@ class OpenAIRealtimeLLMService(LLMService): await self.push_error(error_msg=f"Error sending client event: {e}", exception=e) async def _update_settings(self, delta): - """Apply a settings delta.""" + """Apply a settings delta, sending a session update when needed.""" changed = await super()._update_settings(delta) - self._warn_unhandled_updated_settings(changed.keys()) + handled = {"session_properties", "system_instruction"} + if changed.keys() & handled: + await self._send_session_update() + self._warn_unhandled_updated_settings(changed.keys() - handled) return changed async def _send_session_update(self): - settings = self._session_properties + settings = self._settings.session_properties adapter: OpenAIRealtimeLLMAdapter = self.get_llm_adapter() if self._context: diff --git a/tests/test_settings.py b/tests/test_settings.py index 201e85745..875ccf067 100644 --- a/tests/test_settings.py +++ b/tests/test_settings.py @@ -12,6 +12,8 @@ import pytest from pipecat.services.deepgram.stt import DeepgramSTTService, DeepgramSTTSettings from pipecat.services.deepgram.stt_sagemaker import DeepgramSageMakerSTTSettings +from pipecat.services.openai.realtime import events +from pipecat.services.openai.realtime.llm import OpenAIRealtimeLLMSettings from pipecat.services.settings import ( NOT_GIVEN, LLMSettings, @@ -615,3 +617,201 @@ class TestDeepgramSTTSettingsExtraSync: kwargs = svc._build_connect_kwargs() assert kwargs["numerals"] == "true" assert kwargs["custom_param"] == "test" + + +# --------------------------------------------------------------------------- +# OpenAIRealtimeLLMSettings: apply_update with bidirectional sync +# --------------------------------------------------------------------------- + + +class TestOpenAIRealtimeSettingsApplyUpdate: + def _make_store(self, **kwargs) -> OpenAIRealtimeLLMSettings: + """Helper to build a store-mode OpenAIRealtimeLLMSettings.""" + defaults = dict( + model="gpt-realtime-1.5", + system_instruction=None, + temperature=None, + max_tokens=None, + top_p=None, + top_k=None, + frequency_penalty=None, + presence_penalty=None, + seed=None, + filter_incomplete_user_turns=False, + user_turn_completion_config=None, + session_properties=events.SessionProperties(), + ) + defaults.update(kwargs) + return OpenAIRealtimeLLMSettings(**defaults) + + def test_top_level_model_syncs_to_sp(self): + """Updating top-level model should propagate to session_properties.model.""" + store = self._make_store() + delta = OpenAIRealtimeLLMSettings(model="gpt-realtime-2.0") + changed = store.apply_update(delta) + + assert "model" in changed + assert store.model == "gpt-realtime-2.0" + assert store.session_properties.model == "gpt-realtime-2.0" + + def test_top_level_system_instruction_syncs_to_sp(self): + """Updating top-level system_instruction should propagate to session_properties.instructions.""" + store = self._make_store() + delta = OpenAIRealtimeLLMSettings(system_instruction="Be helpful.") + changed = store.apply_update(delta) + + assert "system_instruction" in changed + assert store.system_instruction == "Be helpful." + assert store.session_properties.instructions == "Be helpful." + + def test_sp_replaces_wholesale(self): + """session_properties in delta replaces the entire stored SP.""" + store = self._make_store( + session_properties=events.SessionProperties( + output_modalities=["audio", "text"], + instructions="Old instructions.", + ), + system_instruction="Old instructions.", + ) + + new_sp = events.SessionProperties(output_modalities=["text"]) + delta = OpenAIRealtimeLLMSettings(session_properties=new_sp) + changed = store.apply_update(delta) + + assert "session_properties" in changed + assert store.session_properties.output_modalities == ["text"] + # Fields not in the new SP become None (wholesale replacement) + # But model is synced from top-level + assert store.session_properties.model == "gpt-realtime-1.5" + + def test_sp_model_syncs_to_top_level(self): + """session_properties.model should sync to top-level model.""" + store = self._make_store() + new_sp = events.SessionProperties(model="gpt-realtime-2.0") + delta = OpenAIRealtimeLLMSettings(session_properties=new_sp) + changed = store.apply_update(delta) + + assert "model" in changed + assert store.model == "gpt-realtime-2.0" + assert store.session_properties.model == "gpt-realtime-2.0" + + def test_sp_instructions_syncs_to_top_level(self): + """session_properties.instructions should sync to top-level system_instruction.""" + store = self._make_store() + new_sp = events.SessionProperties(instructions="New instructions.") + delta = OpenAIRealtimeLLMSettings(session_properties=new_sp) + changed = store.apply_update(delta) + + assert "system_instruction" in changed + assert store.system_instruction == "New instructions." + assert store.session_properties.instructions == "New instructions." + + def test_top_level_model_takes_precedence_over_sp_model(self): + """When both model and session_properties.model are in the delta, top-level wins.""" + store = self._make_store() + new_sp = events.SessionProperties(model="sp-model") + delta = OpenAIRealtimeLLMSettings(model="top-model", session_properties=new_sp) + store.apply_update(delta) + + assert store.model == "top-model" + assert store.session_properties.model == "top-model" + + def test_top_level_si_takes_precedence_over_sp_instructions(self): + """When both system_instruction and SP.instructions are in delta, top-level wins.""" + store = self._make_store() + new_sp = events.SessionProperties(instructions="sp instructions") + delta = OpenAIRealtimeLLMSettings( + system_instruction="top instructions", + session_properties=new_sp, + ) + store.apply_update(delta) + + assert store.system_instruction == "top instructions" + assert store.session_properties.instructions == "top instructions" + + def test_non_synced_field_update_does_not_affect_sp(self): + """Updating a non-synced field like temperature shouldn't touch session_properties.""" + store = self._make_store( + session_properties=events.SessionProperties(instructions="Keep me."), + system_instruction="Keep me.", + ) + original_sp = store.session_properties + + delta = OpenAIRealtimeLLMSettings(temperature=0.5) + changed = store.apply_update(delta) + + assert "temperature" in changed + assert store.temperature == 0.5 + # SP should be untouched (same object) + assert store.session_properties is original_sp + assert store.session_properties.instructions == "Keep me." + + +# --------------------------------------------------------------------------- +# OpenAIRealtimeLLMSettings: from_mapping +# --------------------------------------------------------------------------- + + +class TestOpenAIRealtimeSettingsFromMapping: + def test_sp_keys_route_to_session_properties(self): + """SessionProperties fields (instructions, audio, etc.) route into nested SP.""" + delta = OpenAIRealtimeLLMSettings.from_mapping( + {"instructions": "Be concise.", "output_modalities": ["text"]} + ) + assert is_given(delta.session_properties) + assert delta.session_properties.instructions == "Be concise." + assert delta.session_properties.output_modalities == ["text"] + + def test_model_routes_to_top_level(self): + """model should go to the top-level field, not session_properties.""" + delta = OpenAIRealtimeLLMSettings.from_mapping({"model": "gpt-realtime-2.0"}) + assert delta.model == "gpt-realtime-2.0" + # No session_properties should be created since no SP keys were present + assert not is_given(delta.session_properties) + + def test_unknown_keys_go_to_extra(self): + """Unrecognized keys should land in extra.""" + delta = OpenAIRealtimeLLMSettings.from_mapping({"unknown_param": 42}) + assert not is_given(delta.model) + assert not is_given(delta.session_properties) + assert delta.extra == {"unknown_param": 42} + + def test_mixed_keys(self): + """model + SP keys + unknown keys are routed correctly.""" + delta = OpenAIRealtimeLLMSettings.from_mapping( + { + "model": "gpt-realtime-2.0", + "instructions": "Be helpful.", + "unknown": "val", + } + ) + assert delta.model == "gpt-realtime-2.0" + assert is_given(delta.session_properties) + assert delta.session_properties.instructions == "Be helpful." + assert delta.extra == {"unknown": "val"} + + def test_roundtrip_from_mapping_apply_update(self): + """Simulate dict-style update: from_mapping -> apply_update.""" + store = OpenAIRealtimeLLMSettings( + model="gpt-realtime-1.5", + system_instruction=None, + temperature=None, + max_tokens=None, + top_p=None, + top_k=None, + frequency_penalty=None, + presence_penalty=None, + seed=None, + filter_incomplete_user_turns=False, + user_turn_completion_config=None, + session_properties=events.SessionProperties(), + ) + + raw = {"instructions": "Be concise.", "output_modalities": ["text"]} + delta = OpenAIRealtimeLLMSettings.from_mapping(raw) + changed = store.apply_update(delta) + + assert "session_properties" in changed + assert store.session_properties.instructions == "Be concise." + assert store.session_properties.output_modalities == ["text"] + assert store.system_instruction == "Be concise." From 158424aa28da58de0c775f530d2f3213267dcfc8 Mon Sep 17 00:00:00 2001 From: mattie ruth backman Date: Mon, 22 Dec 2025 15:39:47 -0500 Subject: [PATCH 0825/1060] Convert RTVI framework into a structured package Replace the monolithic rtvi.py with a proper package split by concern protocol version: - models_v0.py: deprecated pre-1.0 Pydantic models - models_v1.py: current RTVI protocol v1 message models - frames.py: RTVI pipeline frame dataclasses - observer.py: RTVIObserver and RTVIObserverParams - processor.py: RTVIProcessor (now lean, imports from submodules) - __init__.py: re-exports full public API for backward compatability --- src/pipecat/processors/frameworks/rtvi.py | 2169 ----------------- .../processors/frameworks/rtvi/__init__.py | 73 + .../processors/frameworks/rtvi/frames.py | 74 + .../processors/frameworks/rtvi/models_v0.py | 334 +++ .../processors/frameworks/rtvi/models_v1.py | 581 +++++ .../processors/frameworks/rtvi/observer.py | 664 +++++ .../processors/frameworks/rtvi/processor.py | 653 +++++ src/pipecat/serializers/base_serializer.py | 4 +- 8 files changed, 2381 insertions(+), 2171 deletions(-) delete mode 100644 src/pipecat/processors/frameworks/rtvi.py create mode 100644 src/pipecat/processors/frameworks/rtvi/__init__.py create mode 100644 src/pipecat/processors/frameworks/rtvi/frames.py create mode 100644 src/pipecat/processors/frameworks/rtvi/models_v0.py create mode 100644 src/pipecat/processors/frameworks/rtvi/models_v1.py create mode 100644 src/pipecat/processors/frameworks/rtvi/observer.py create mode 100644 src/pipecat/processors/frameworks/rtvi/processor.py diff --git a/src/pipecat/processors/frameworks/rtvi.py b/src/pipecat/processors/frameworks/rtvi.py deleted file mode 100644 index eb1e79f3e..000000000 --- a/src/pipecat/processors/frameworks/rtvi.py +++ /dev/null @@ -1,2169 +0,0 @@ -# -# Copyright (c) 2024-2026, Daily -# -# SPDX-License-Identifier: BSD 2-Clause License -# - -"""RTVI (Real-Time Voice Interface) protocol implementation for Pipecat. - -This module provides the RTVI protocol implementation for real-time voice interactions -between clients and AI agents. It includes message handling, action processing, -and frame observation for the RTVI protocol. -""" - -import asyncio -import base64 -import time -from dataclasses import dataclass, field -from enum import Enum -from typing import ( - Any, - Awaitable, - Callable, - Dict, - List, - Literal, - Mapping, - Optional, - Set, - Tuple, - Union, -) - -from loguru import logger -from pydantic import BaseModel, Field, PrivateAttr, ValidationError - -from pipecat import version as pipecat_version -from pipecat.audio.utils import calculate_audio_volume -from pipecat.frames.frames import ( - AggregatedTextFrame, - AggregationType, - BotStartedSpeakingFrame, - BotStoppedSpeakingFrame, - CancelFrame, - DataFrame, - EndFrame, - EndTaskFrame, - ErrorFrame, - Frame, - FunctionCallCancelFrame, - FunctionCallInProgressFrame, - FunctionCallResultFrame, - FunctionCallsStartedFrame, - InputAudioRawFrame, - InputTransportMessageFrame, - InterimTranscriptionFrame, - LLMConfigureOutputFrame, - LLMContextFrame, - LLMFullResponseEndFrame, - LLMFullResponseStartFrame, - LLMMessagesAppendFrame, - LLMTextFrame, - MetricsFrame, - OutputTransportMessageUrgentFrame, - StartFrame, - SystemFrame, - TranscriptionFrame, - TTSAudioRawFrame, - TTSStartedFrame, - TTSStoppedFrame, - TTSTextFrame, - UserMuteStartedFrame, - UserMuteStoppedFrame, - UserStartedSpeakingFrame, - UserStoppedSpeakingFrame, -) -from pipecat.metrics.metrics import ( - LLMUsageMetricsData, - ProcessingMetricsData, - TTFBMetricsData, - TTSUsageMetricsData, -) -from pipecat.observers.base_observer import BaseObserver, FramePushed -from pipecat.processors.aggregators.openai_llm_context import OpenAILLMContextFrame -from pipecat.processors.frame_processor import FrameDirection, FrameProcessor -from pipecat.services.llm_service import ( - FunctionCallParams, # TODO(aleix): we shouldn't import `services` from `processors` -) -from pipecat.transports.base_input import BaseInputTransport -from pipecat.transports.base_output import BaseOutputTransport -from pipecat.transports.base_transport import BaseTransport -from pipecat.utils.string import match_endofsentence - -RTVI_PROTOCOL_VERSION = "1.2.0" - -RTVI_MESSAGE_LABEL = "rtvi-ai" -RTVIMessageLiteral = Literal["rtvi-ai"] - -ActionResult = Union[bool, int, float, str, list, dict] - - -class RTVIServiceOption(BaseModel): - """Configuration option for an RTVI service. - - Defines a configurable option that can be set for an RTVI service, - including its name, type, and handler function. - - .. deprecated:: 0.0.75 - Pipeline Configuration has been removed as part of the RTVI protocol 1.0.0. - Use custom client and server messages instead. - """ - - name: str - type: Literal["bool", "number", "string", "array", "object"] - handler: Callable[["RTVIProcessor", str, "RTVIServiceOptionConfig"], Awaitable[None]] = Field( - exclude=True - ) - - -class RTVIService(BaseModel): - """An RTVI service definition. - - Represents a service that can be configured and used within the RTVI protocol, - containing a name and list of configurable options. - - .. deprecated:: 0.0.75 - Pipeline Configuration has been removed as part of the RTVI protocol 1.0.0. - Use custom client and server messages instead. - """ - - name: str - options: List[RTVIServiceOption] - _options_dict: Dict[str, RTVIServiceOption] = PrivateAttr(default={}) - - def model_post_init(self, __context: Any) -> None: - """Initialize the options dictionary after model creation.""" - self._options_dict = {} - for option in self.options: - self._options_dict[option.name] = option - return super().model_post_init(__context) - - -class RTVIActionArgumentData(BaseModel): - """Data for an RTVI action argument. - - Contains the name and value of an argument passed to an RTVI action. - - .. deprecated:: 0.0.75 - Actions have been removed as part of the RTVI protocol 1.0.0. - Use custom client and server messages instead. - """ - - name: str - value: Any - - -class RTVIActionArgument(BaseModel): - """Definition of an RTVI action argument. - - Specifies the name and expected type of an argument for an RTVI action. - - .. deprecated:: 0.0.75 - Actions have been removed as part of the RTVI protocol 1.0.0. - Use custom client and server messages instead. - """ - - name: str - type: Literal["bool", "number", "string", "array", "object"] - - -class RTVIAction(BaseModel): - """An RTVI action definition. - - Represents an action that can be executed within the RTVI protocol, - including its service, name, arguments, and handler function. - - .. deprecated:: 0.0.75 - Actions have been removed as part of the RTVI protocol 1.0.0. - Use custom client and server messages instead. - """ - - service: str - action: str - arguments: List[RTVIActionArgument] = Field(default_factory=list) - result: Literal["bool", "number", "string", "array", "object"] - handler: Callable[["RTVIProcessor", str, Dict[str, Any]], Awaitable[ActionResult]] = Field( - exclude=True - ) - _arguments_dict: Dict[str, RTVIActionArgument] = PrivateAttr(default={}) - - def model_post_init(self, __context: Any) -> None: - """Initialize the arguments dictionary after model creation.""" - self._arguments_dict = {} - for arg in self.arguments: - self._arguments_dict[arg.name] = arg - return super().model_post_init(__context) - - -class RTVIServiceOptionConfig(BaseModel): - """Configuration value for an RTVI service option. - - Contains the name and value to set for a specific service option. - - .. deprecated:: 0.0.75 - Pipeline Configuration has been removed as part of the RTVI protocol 1.0.0. - Use custom client and server messages instead. - """ - - name: str - value: Any - - -class RTVIServiceConfig(BaseModel): - """Configuration for an RTVI service. - - Contains the service name and list of option configurations to apply. - - .. deprecated:: 0.0.75 - Pipeline Configuration has been removed as part of the RTVI protocol 1.0.0. - Use custom client and server messages instead. - """ - - service: str - options: List[RTVIServiceOptionConfig] - - -class RTVIConfig(BaseModel): - """Complete RTVI configuration. - - Contains the full configuration for all RTVI services. - - .. deprecated:: 0.0.75 - Pipeline Configuration has been removed as part of the RTVI protocol 1.0.0. - Use custom client and server messages instead. - """ - - config: List[RTVIServiceConfig] - - -# -# Client -> Pipecat messages. -# - - -# deprecated -class RTVIUpdateConfig(BaseModel): - """Request to update RTVI configuration. - - Contains new configuration settings and whether to interrupt the bot. - - .. deprecated:: 0.0.75 - Pipeline Configuration has been removed as part of the RTVI protocol 1.0.0. - Use custom client and server messages instead. - """ - - config: List[RTVIServiceConfig] - interrupt: bool = False - - -class RTVIActionRunArgument(BaseModel): - """Argument for running an RTVI action. - - Contains the name and value of an argument to pass to an action. - - .. deprecated:: 0.0.75 - Actions have been removed as part of the RTVI protocol 1.0.0. - Use custom client and server messages instead. - """ - - name: str - value: Any - - -class RTVIActionRun(BaseModel): - """Request to run an RTVI action. - - Contains the service, action name, and optional arguments. - - .. deprecated:: 0.0.75 - Actions have been removed as part of the RTVI protocol 1.0.0. - Use custom client and server messages instead. - """ - - service: str - action: str - arguments: Optional[List[RTVIActionRunArgument]] = None - - -@dataclass -class RTVIActionFrame(DataFrame): - """Frame containing an RTVI action to execute. - - Parameters: - rtvi_action_run: The action to execute. - message_id: Optional message ID for response correlation. - - .. deprecated:: 0.0.75 - Actions have been removed as part of the RTVI protocol 1.0.0. - Use custom client and server messages instead. - """ - - rtvi_action_run: RTVIActionRun - message_id: Optional[str] = None - - -class RTVIRawClientMessageData(BaseModel): - """Data structure expected from client messages sent to the RTVI server.""" - - t: str - d: Optional[Any] = None - - -class RTVIClientMessage(BaseModel): - """Cleansed data structure for client messages for handling.""" - - msg_id: str - type: str - data: Optional[Any] = None - - -@dataclass -class RTVIClientMessageFrame(SystemFrame): - """A frame for sending messages from the client to the RTVI server. - - This frame is meant for custom messaging from the client to the server - and expects a server-response message. - """ - - msg_id: str - type: str - data: Optional[Any] = None - - -@dataclass -class RTVIServerResponseFrame(SystemFrame): - """A frame for responding to a client RTVI message. - - This frame should be sent in response to an RTVIClientMessageFrame - and include the original RTVIClientMessageFrame to ensure the response - is properly attributed to the original request. To respond with an error, - set the `error` field to a string describing the error. This will result - in the client receiving a `response-error` message instead of a - `server-response` message. - """ - - client_msg: RTVIClientMessageFrame - data: Optional[Any] = None - error: Optional[str] = None - - -class RTVIRawServerResponseData(BaseModel): - """Data structure for server responses to client messages.""" - - t: str - d: Optional[Any] = None - - -class RTVIServerResponse(BaseModel): - """The RTVI-formatted message response from the server to the client. - - This message is used to respond to custom messages sent by the client. - """ - - label: RTVIMessageLiteral = RTVI_MESSAGE_LABEL - type: Literal["server-response"] = "server-response" - id: str - data: RTVIRawServerResponseData - - -class RTVIMessage(BaseModel): - """Base RTVI message structure. - - Represents the standard format for RTVI protocol messages. - """ - - label: RTVIMessageLiteral = RTVI_MESSAGE_LABEL - type: str - id: str - data: Optional[Dict[str, Any]] = None - - -# -# Pipecat -> Client responses and messages. -# - - -class RTVIErrorResponseData(BaseModel): - """Data for an RTVI error response. - - Contains the error message to send back to the client. - """ - - error: str - - -class RTVIErrorResponse(BaseModel): - """RTVI error response message. - - RTVI Formatted error response message for relaying failed client requests. - """ - - label: RTVIMessageLiteral = RTVI_MESSAGE_LABEL - type: Literal["error-response"] = "error-response" - id: str - data: RTVIErrorResponseData - - -class RTVIErrorData(BaseModel): - """Data for an RTVI error event. - - Contains error information including whether it's fatal. - """ - - error: str - fatal: bool # Indicates the pipeline has stopped due to this error - - -class RTVIError(BaseModel): - """RTVI error event message. - - RTVI Formatted error message for relaying errors in the pipeline. - """ - - label: RTVIMessageLiteral = RTVI_MESSAGE_LABEL - type: Literal["error"] = "error" - data: RTVIErrorData - - -class RTVIDescribeConfigData(BaseModel): - """Data for describing available RTVI configuration. - - Contains the list of available services and their options. - - .. deprecated:: 0.0.75 - Pipeline Configuration has been removed as part of the RTVI protocol 1.0.0. - Use custom client and server messages instead. - """ - - config: List[RTVIService] - - -class RTVIDescribeConfig(BaseModel): - """Message describing available RTVI configuration. - - Sent in response to a describe-config request. - - .. deprecated:: 0.0.75 - Pipeline Configuration has been removed as part of the RTVI protocol 1.0.0. - Use custom client and server messages instead. - """ - - label: RTVIMessageLiteral = RTVI_MESSAGE_LABEL - type: Literal["config-available"] = "config-available" - id: str - data: RTVIDescribeConfigData - - -class RTVIDescribeActionsData(BaseModel): - """Data for describing available RTVI actions. - - Contains the list of available actions that can be executed. - - .. deprecated:: 0.0.75 - Actions have been removed as part of the RTVI protocol 1.0.0. - Use custom client and server messages instead. - """ - - actions: List[RTVIAction] - - -class RTVIDescribeActions(BaseModel): - """Message describing available RTVI actions. - - Sent in response to a describe-actions request. - - .. deprecated:: 0.0.75 - Actions have been removed as part of the RTVI protocol 1.0.0. - Use custom client and server messages instead. - """ - - label: RTVIMessageLiteral = RTVI_MESSAGE_LABEL - type: Literal["actions-available"] = "actions-available" - id: str - data: RTVIDescribeActionsData - - -class RTVIConfigResponse(BaseModel): - """Response containing current RTVI configuration. - - Sent in response to a get-config request. - - .. deprecated:: 0.0.75 - Pipeline Configuration has been removed as part of the RTVI protocol 1.0.0. - Use custom client and server messages instead. - """ - - label: RTVIMessageLiteral = RTVI_MESSAGE_LABEL - type: Literal["config"] = "config" - id: str - data: RTVIConfig - - -class RTVIActionResponseData(BaseModel): - """Data for an RTVI action response. - - Contains the result of executing an action. - - .. deprecated:: 0.0.75 - Actions have been removed as part of the RTVI protocol 1.0.0. - Use custom client and server messages instead. - """ - - result: ActionResult - - -class RTVIActionResponse(BaseModel): - """Response to an RTVI action execution. - - Sent after successfully executing an action. - - .. deprecated:: 0.0.75 - Actions have been removed as part of the RTVI protocol 1.0.0. - Use custom client and server messages instead. - """ - - label: RTVIMessageLiteral = RTVI_MESSAGE_LABEL - type: Literal["action-response"] = "action-response" - id: str - data: RTVIActionResponseData - - -class AboutClientData(BaseModel): - """Data about the RTVI client. - - Contains information about the client, including which RTVI library it - is using, what platform it is on and any additional details, if available. - """ - - library: str - library_version: Optional[str] = None - platform: Optional[str] = None - platform_version: Optional[str] = None - platform_details: Optional[Any] = None - - -class RTVIClientReadyData(BaseModel): - """Data format of client ready messages. - - Contains the RTVIprotocol version and client information. - """ - - version: str - about: AboutClientData - - -class RTVIBotReadyData(BaseModel): - """Data for bot ready notification. - - Contains protocol version and initial configuration. - """ - - version: str - # The config field is deprecated and will not be included if - # the client's rtvi version is 1.0.0 or higher. - config: Optional[List[RTVIServiceConfig]] = None - about: Optional[Mapping[str, Any]] = None - - -class RTVIBotReady(BaseModel): - """Message indicating bot is ready for interaction. - - Sent after bot initialization is complete. - """ - - label: RTVIMessageLiteral = RTVI_MESSAGE_LABEL - type: Literal["bot-ready"] = "bot-ready" - id: str - data: RTVIBotReadyData - - -class RTVILLMFunctionCallMessageData(BaseModel): - """Data for LLM function call notification. - - Contains function call details including name, ID, and arguments. - - .. deprecated:: 0.0.102 - Use ``RTVILLMFunctionCallInProgressMessageData`` instead. - """ - - function_name: str - tool_call_id: str - args: Mapping[str, Any] - - -class RTVILLMFunctionCallMessage(BaseModel): - """Message notifying of an LLM function call. - - Sent when the LLM makes a function call. - - .. deprecated:: 0.0.102 - Use ``RTVILLMFunctionCallInProgressMessage`` with the - ``llm-function-call-in-progress`` event type instead. - """ - - label: RTVIMessageLiteral = RTVI_MESSAGE_LABEL - type: Literal["llm-function-call"] = "llm-function-call" - data: RTVILLMFunctionCallMessageData - - -class RTVISendTextOptions(BaseModel): - """Options for sending text input to the LLM. - - Contains options for how the pipeline should process the text input. - """ - - run_immediately: bool = True - audio_response: bool = True - - -class RTVISendTextData(BaseModel): - """Data format for sending text input to the LLM. - - Contains the text content to send and any options for how the pipeline should process it. - - """ - - content: str - options: Optional[RTVISendTextOptions] = None - - -class RTVIAppendToContextData(BaseModel): - """Data format for appending messages to the context. - - Contains the role, content, and whether to run the message immediately. - - .. deprecated:: 0.0.85 - The RTVI message, append-to-context, has been deprecated. Use send-text - or custom client and server messages instead. - """ - - role: Literal["user", "assistant"] | str - content: Any - run_immediately: bool = False - - -class RTVIAppendToContext(BaseModel): - """RTVI Message format to append content to the LLM context.""" - - label: RTVIMessageLiteral = RTVI_MESSAGE_LABEL - type: Literal["append-to-context"] = "append-to-context" - data: RTVIAppendToContextData - - -class RTVILLMFunctionCallStartMessageData(BaseModel): - """Data for LLM function call start notification. - - Contains the function name being called. Fields may be omitted based on - the configured function_call_report_level for security. - """ - - function_name: Optional[str] = None - - -class RTVILLMFunctionCallStartMessage(BaseModel): - """Message notifying that an LLM function call has started. - - Sent when the LLM begins a function call. - """ - - label: RTVIMessageLiteral = RTVI_MESSAGE_LABEL - type: Literal["llm-function-call-started"] = "llm-function-call-started" - data: RTVILLMFunctionCallStartMessageData - - -class RTVILLMFunctionCallResultData(BaseModel): - """Data for LLM function call result. - - Contains function call details and result. - """ - - function_name: str - tool_call_id: str - arguments: dict - result: dict | str - - -class RTVILLMFunctionCallInProgressMessageData(BaseModel): - """Data for LLM function call in-progress notification. - - Contains function call details including name, ID, and arguments. - Fields may be omitted based on the configured function_call_report_level for security. - """ - - tool_call_id: str - function_name: Optional[str] = None - arguments: Optional[Mapping[str, Any]] = None - - -class RTVILLMFunctionCallInProgressMessage(BaseModel): - """Message notifying that an LLM function call is in progress. - - Sent when the LLM function call execution begins. - """ - - label: RTVIMessageLiteral = RTVI_MESSAGE_LABEL - type: Literal["llm-function-call-in-progress"] = "llm-function-call-in-progress" - data: RTVILLMFunctionCallInProgressMessageData - - -class RTVILLMFunctionCallStoppedMessageData(BaseModel): - """Data for LLM function call stopped notification. - - Contains details about the function call that stopped, including - whether it was cancelled or completed with a result. - Fields may be omitted based on the configured function_call_report_level for security. - """ - - tool_call_id: str - cancelled: bool - function_name: Optional[str] = None - result: Optional[Any] = None - - -class RTVILLMFunctionCallStoppedMessage(BaseModel): - """Message notifying that an LLM function call has stopped. - - Sent when a function call completes (with result) or is cancelled. - """ - - label: RTVIMessageLiteral = RTVI_MESSAGE_LABEL - type: Literal["llm-function-call-stopped"] = "llm-function-call-stopped" - data: RTVILLMFunctionCallStoppedMessageData - - -class RTVIBotLLMStartedMessage(BaseModel): - """Message indicating bot LLM processing has started.""" - - label: RTVIMessageLiteral = RTVI_MESSAGE_LABEL - type: Literal["bot-llm-started"] = "bot-llm-started" - - -class RTVIBotLLMStoppedMessage(BaseModel): - """Message indicating bot LLM processing has stopped.""" - - label: RTVIMessageLiteral = RTVI_MESSAGE_LABEL - type: Literal["bot-llm-stopped"] = "bot-llm-stopped" - - -class RTVIBotTTSStartedMessage(BaseModel): - """Message indicating bot TTS processing has started.""" - - label: RTVIMessageLiteral = RTVI_MESSAGE_LABEL - type: Literal["bot-tts-started"] = "bot-tts-started" - - -class RTVIBotTTSStoppedMessage(BaseModel): - """Message indicating bot TTS processing has stopped.""" - - label: RTVIMessageLiteral = RTVI_MESSAGE_LABEL - type: Literal["bot-tts-stopped"] = "bot-tts-stopped" - - -class RTVITextMessageData(BaseModel): - """Data for text-based RTVI messages. - - Contains text content. - """ - - text: str - - -class RTVIBotOutputMessageData(RTVITextMessageData): - """Data for bot output RTVI messages. - - Extends RTVITextMessageData to include metadata about the output. - """ - - spoken: bool = False # Indicates if the text has been spoken by TTS - aggregated_by: AggregationType | str - # Indicates what form the text is in (e.g., by word, sentence, etc.) - - -class RTVIBotOutputMessage(BaseModel): - """Message containing bot output text. - - An event meant to holistically represent what the bot is outputting, - along with metadata about the output and if it has been spoken. - """ - - label: RTVIMessageLiteral = RTVI_MESSAGE_LABEL - type: Literal["bot-output"] = "bot-output" - data: RTVIBotOutputMessageData - - -class RTVIBotTranscriptionMessage(BaseModel): - """Message containing bot transcription text. - - Sent when the bot's speech is transcribed. - """ - - label: RTVIMessageLiteral = RTVI_MESSAGE_LABEL - type: Literal["bot-transcription"] = "bot-transcription" - data: RTVITextMessageData - - -class RTVIBotLLMTextMessage(BaseModel): - """Message containing bot LLM text output. - - Sent when the bot's LLM generates text. - """ - - label: RTVIMessageLiteral = RTVI_MESSAGE_LABEL - type: Literal["bot-llm-text"] = "bot-llm-text" - data: RTVITextMessageData - - -class RTVIBotTTSTextMessage(BaseModel): - """Message containing bot TTS text output. - - Sent when text is being processed by TTS. - """ - - label: RTVIMessageLiteral = RTVI_MESSAGE_LABEL - type: Literal["bot-tts-text"] = "bot-tts-text" - data: RTVITextMessageData - - -class RTVIAudioMessageData(BaseModel): - """Data for audio-based RTVI messages. - - Contains audio data and metadata. - """ - - audio: str - sample_rate: int - num_channels: int - - -class RTVIBotTTSAudioMessage(BaseModel): - """Message containing bot TTS audio output. - - Sent when the bot's TTS generates audio. - """ - - label: RTVIMessageLiteral = RTVI_MESSAGE_LABEL - type: Literal["bot-tts-audio"] = "bot-tts-audio" - data: RTVIAudioMessageData - - -class RTVIUserTranscriptionMessageData(BaseModel): - """Data for user transcription messages. - - Contains transcription text and metadata. - """ - - text: str - user_id: str - timestamp: str - final: bool - - -class RTVIUserTranscriptionMessage(BaseModel): - """Message containing user transcription. - - Sent when user speech is transcribed. - """ - - label: RTVIMessageLiteral = RTVI_MESSAGE_LABEL - type: Literal["user-transcription"] = "user-transcription" - data: RTVIUserTranscriptionMessageData - - -class RTVIUserLLMTextMessage(BaseModel): - """Message containing user text input for LLM. - - Sent when user text is processed by the LLM. - """ - - label: RTVIMessageLiteral = RTVI_MESSAGE_LABEL - type: Literal["user-llm-text"] = "user-llm-text" - data: RTVITextMessageData - - -class RTVIUserStartedSpeakingMessage(BaseModel): - """Message indicating user has started speaking.""" - - label: RTVIMessageLiteral = RTVI_MESSAGE_LABEL - type: Literal["user-started-speaking"] = "user-started-speaking" - - -class RTVIUserStoppedSpeakingMessage(BaseModel): - """Message indicating user has stopped speaking.""" - - label: RTVIMessageLiteral = RTVI_MESSAGE_LABEL - type: Literal["user-stopped-speaking"] = "user-stopped-speaking" - - -class RTVIUserMuteStartedMessage(BaseModel): - """Message indicating user has been muted.""" - - label: RTVIMessageLiteral = RTVI_MESSAGE_LABEL - type: Literal["user-mute-started"] = "user-mute-started" - - -class RTVIUserMuteStoppedMessage(BaseModel): - """Message indicating user has been unmuted.""" - - label: RTVIMessageLiteral = RTVI_MESSAGE_LABEL - type: Literal["user-mute-stopped"] = "user-mute-stopped" - - -class RTVIBotStartedSpeakingMessage(BaseModel): - """Message indicating bot has started speaking.""" - - label: RTVIMessageLiteral = RTVI_MESSAGE_LABEL - type: Literal["bot-started-speaking"] = "bot-started-speaking" - - -class RTVIBotStoppedSpeakingMessage(BaseModel): - """Message indicating bot has stopped speaking.""" - - label: RTVIMessageLiteral = RTVI_MESSAGE_LABEL - type: Literal["bot-stopped-speaking"] = "bot-stopped-speaking" - - -class RTVIMetricsMessage(BaseModel): - """Message containing performance metrics. - - Sent to provide performance and usage metrics. - """ - - label: RTVIMessageLiteral = RTVI_MESSAGE_LABEL - type: Literal["metrics"] = "metrics" - data: Mapping[str, Any] - - -class RTVIServerMessage(BaseModel): - """Generic server message. - - Used for custom server-to-client messages. - """ - - label: RTVIMessageLiteral = RTVI_MESSAGE_LABEL - type: Literal["server-message"] = "server-message" - data: Any - - -class RTVIAudioLevelMessageData(BaseModel): - """Data format for sending audio levels.""" - - value: float - - -class RTVIUserAudioLevelMessage(BaseModel): - """Message indicating user audio level.""" - - label: RTVIMessageLiteral = RTVI_MESSAGE_LABEL - type: Literal["user-audio-level"] = "user-audio-level" - data: RTVIAudioLevelMessageData - - -class RTVIBotAudioLevelMessage(BaseModel): - """Message indicating bot audio level.""" - - label: RTVIMessageLiteral = RTVI_MESSAGE_LABEL - type: Literal["bot-audio-level"] = "bot-audio-level" - data: RTVIAudioLevelMessageData - - -class RTVISystemLogMessage(BaseModel): - """Message including a system log.""" - - label: RTVIMessageLiteral = RTVI_MESSAGE_LABEL - type: Literal["system-log"] = "system-log" - data: RTVITextMessageData - - -@dataclass -class RTVIServerMessageFrame(SystemFrame): - """A frame for sending server messages to the client. - - Parameters: - data: The message data to send to the client. - """ - - data: Any - - def __str__(self): - """String representation of the RTVI server message frame.""" - return f"{self.name}(data: {self.data})" - - -class RTVIFunctionCallReportLevel(str, Enum): - """Level of detail to include in function call RTVI events. - - Controls what information is exposed in function call events for security. - - Values: - DISABLED: No events emitted for this function call. - NONE: Events only with tool_call_id, no function name or metadata (most secure). - NAME: Events with function name, no arguments or results. - FULL: Events with function name, arguments, and results. - """ - - DISABLED = "disabled" - NONE = "none" - NAME = "name" - FULL = "full" - - -@dataclass -class RTVIObserverParams: - """Parameters for configuring RTVI Observer behavior. - - .. deprecated:: 0.0.87 - Parameter `errors_enabled` is deprecated. Error messages are always enabled. - - Parameters: - bot_output_enabled: Indicates if bot output messages should be sent. - bot_llm_enabled: Indicates if the bot's LLM messages should be sent. - bot_tts_enabled: Indicates if the bot's TTS messages should be sent. - bot_speaking_enabled: Indicates if the bot's started/stopped speaking messages should be sent. - bot_audio_level_enabled: Indicates if bot's audio level messages should be sent. - user_llm_enabled: Indicates if the user's LLM input messages should be sent. - user_speaking_enabled: Indicates if the user's started/stopped speaking messages should be sent. - user_transcription_enabled: Indicates if user's transcription messages should be sent. - user_audio_level_enabled: Indicates if user's audio level messages should be sent. - metrics_enabled: Indicates if metrics messages should be sent. - system_logs_enabled: Indicates if system logs should be sent. - errors_enabled: [Deprecated] Indicates if errors messages should be sent. - ignored_sources: List of frame processors whose frames should be silently ignored - by this observer. Useful for suppressing RTVI messages from secondary pipeline - branches (e.g. a silent evaluation LLM) that should not be visible to clients. - Sources can also be added and removed dynamically via ``add_ignored_source()`` - and ``remove_ignored_source()``. - skip_aggregator_types: List of aggregation types to skip sending as tts/output messages. - Note: if using this to avoid sending secure information, be sure to also disable - bot_llm_enabled to avoid leaking through LLM messages. - bot_output_transforms: A list of callables to transform text before just before sending it - to TTS. Each callable takes the aggregated text and its type, and returns the - transformed text. To register, provide a list of tuples of - (aggregation_type | '*', transform_function). - audio_level_period_secs: How often audio levels should be sent if enabled. - function_call_report_level: Controls what information is exposed in function call - events for security. A dict mapping function names to levels, where ``"*"`` - sets the default level for unlisted functions:: - - function_call_report_level={ - "*": RTVIFunctionCallReportLevel.NONE, # Default: events with no metadata - "get_weather": RTVIFunctionCallReportLevel.FULL, # Expose everything - } - - Levels: - - DISABLED: No events emitted for this function. - - NONE: Events with tool_call_id only (most secure when events needed). - - NAME: Adds function name to events. - - FULL: Adds function name, arguments, and results. - - Defaults to ``{"*": RTVIFunctionCallReportLevel.NONE}``. - """ - - bot_output_enabled: bool = True - bot_llm_enabled: bool = True - bot_tts_enabled: bool = True - bot_speaking_enabled: bool = True - bot_audio_level_enabled: bool = False - user_llm_enabled: bool = True - user_speaking_enabled: bool = True - user_mute_enabled: bool = True - user_transcription_enabled: bool = True - user_audio_level_enabled: bool = False - metrics_enabled: bool = True - system_logs_enabled: bool = False - errors_enabled: Optional[bool] = None - ignored_sources: List[FrameProcessor] = field(default_factory=list) - skip_aggregator_types: Optional[List[AggregationType | str]] = None - bot_output_transforms: Optional[ - List[ - Tuple[ - AggregationType | str, - Callable[[str, AggregationType | str], Awaitable[str]], - ] - ] - ] = None - audio_level_period_secs: float = 0.15 - function_call_report_level: Dict[str, RTVIFunctionCallReportLevel] = field( - default_factory=lambda: {"*": RTVIFunctionCallReportLevel.NONE} - ) - - -class RTVIObserver(BaseObserver): - """Pipeline frame observer for RTVI server message handling. - - This observer monitors pipeline frames and converts them into appropriate RTVI messages - for client communication. It handles various frame types including speech events, - transcriptions, LLM responses, and TTS events. - - Note: - This observer only handles outgoing messages. Incoming RTVI client messages - are handled by the RTVIProcessor. - """ - - def __init__( - self, - rtvi: Optional["RTVIProcessor"] = None, - *, - params: Optional[RTVIObserverParams] = None, - **kwargs, - ): - """Initialize the RTVI observer. - - Args: - rtvi: The RTVI processor to push frames to. - params: Settings to enable/disable specific messages. - **kwargs: Additional arguments passed to parent class. - """ - super().__init__(**kwargs) - self._rtvi = rtvi - self._params = params or RTVIObserverParams() - - self._ignored_sources: Set[FrameProcessor] = set(self._params.ignored_sources) - self._frames_seen = set() - - self._bot_transcription = "" - self._last_user_audio_level = 0 - self._last_bot_audio_level = 0 - - # Track bot speaking state for queuing aggregated text frames - self._bot_is_speaking = False - self._queued_aggregated_text_frames: List[AggregatedTextFrame] = [] - - if self._params.system_logs_enabled: - self._system_logger_id = logger.add(self._logger_sink) - - if self._params.errors_enabled is not None: - import warnings - - with warnings.catch_warnings(): - warnings.simplefilter("always") - warnings.warn( - "Parameter `errors_enabled` is deprecated. Error messages are always enabled.", - DeprecationWarning, - ) - - self._aggregation_transforms: List[ - Tuple[AggregationType | str, Callable[[str, AggregationType | str], Awaitable[str]]] - ] = self._params.bot_output_transforms or [] - - def add_bot_output_transformer( - self, - transform_function: Callable[[str, AggregationType | str], Awaitable[str]], - aggregation_type: AggregationType | str = "*", - ): - """Transform text for a specific aggregation type before sending as Bot Output or TTS. - - Args: - transform_function: The function to apply for transformation. This function should take - the text and aggregation type as input and return the transformed text. - Ex.: async def my_transform(text: str, aggregation_type: str) -> str: - aggregation_type: The type of aggregation to transform. This value defaults to "*" to - handle all text before sending to the client. - """ - self._aggregation_transforms.append((aggregation_type, transform_function)) - - def remove_bot_output_transformer( - self, - transform_function: Callable[[str, AggregationType | str], Awaitable[str]], - aggregation_type: AggregationType | str = "*", - ): - """Remove a text transformer for a specific aggregation type. - - Args: - transform_function: The function to remove. - aggregation_type: The type of aggregation to remove the transformer for. - """ - self._aggregation_transforms = [ - (agg_type, func) - for agg_type, func in self._aggregation_transforms - if not (agg_type == aggregation_type and func == transform_function) - ] - - def add_ignored_source(self, source: FrameProcessor): - """Ignore all frames pushed by the given processor. - - Any frame whose source matches ``source`` will be silently skipped, - preventing RTVI messages from being emitted for activity in that - processor. Useful for suppressing events from secondary pipeline - branches (e.g. a silent evaluation LLM) that should not be visible - to clients. - - Args: - source: The frame processor to ignore. - """ - self._ignored_sources.add(source) - - def remove_ignored_source(self, source: FrameProcessor): - """Stop ignoring frames pushed by the given processor. - - Reverses a previous call to ``add_ignored_source()``. If ``source`` - was not previously ignored this is a no-op. - - Args: - source: The frame processor to stop ignoring. - """ - self._ignored_sources.discard(source) - - def _get_function_call_report_level(self, function_name: str) -> RTVIFunctionCallReportLevel: - """Get the report level for a specific function call. - - Args: - function_name: The name of the function to get the report level for. - - Returns: - The report level for the function. Looks up the function name first, - then falls back to "*" key, then NONE. - """ - levels = self._params.function_call_report_level - if function_name in levels: - return levels[function_name] - return levels.get("*", RTVIFunctionCallReportLevel.NONE) - - async def _logger_sink(self, message): - """Logger sink so we can send system logs to RTVI clients.""" - message = RTVISystemLogMessage(data=RTVITextMessageData(text=message)) - await self.send_rtvi_message(message) - - async def cleanup(self): - """Cleanup RTVI observer resources.""" - await super().cleanup() - if self._params.system_logs_enabled: - logger.remove(self._system_logger_id) - - async def send_rtvi_message(self, model: BaseModel, exclude_none: bool = True): - """Send an RTVI message. - - By default, we push a transport frame. But this function can be - overriden by subclass to send RTVI messages in different ways. - - Args: - model: The message to send. - exclude_none: Whether to exclude None values from the model dump. - - """ - if self._rtvi: - await self._rtvi.push_transport_message(model, exclude_none) - - async def on_push_frame(self, data: FramePushed): - """Process a frame being pushed through the pipeline. - - Args: - data: Frame push event data containing source, frame, direction, and timestamp. - """ - src = data.source - frame = data.frame - direction = data.direction - - # Frames from explicitly ignored sources are always skipped. - if self._ignored_sources and src in self._ignored_sources: - return - - # For broadcast frames (pushed in both directions), only process - # the downstream copy to avoid sending duplicate RTVI messages. - if frame.broadcast_sibling_id is not None and direction != FrameDirection.DOWNSTREAM: - return - - # If we have already seen this frame, let's skip it. - if frame.id in self._frames_seen: - return - - # This tells whether the frame is already processed. If false, we will try - # again the next time we see the frame. - mark_as_seen = True - - if ( - isinstance(frame, (UserStartedSpeakingFrame, UserStoppedSpeakingFrame)) - and self._params.user_speaking_enabled - ): - await self._handle_interruptions(frame) - elif ( - isinstance(frame, (UserMuteStartedFrame, UserMuteStoppedFrame)) - and self._params.user_mute_enabled - ): - await self._handle_user_mute(frame) - elif ( - isinstance(frame, (BotStartedSpeakingFrame, BotStoppedSpeakingFrame)) - and self._params.bot_speaking_enabled - ): - await self._handle_bot_speaking(frame) - elif ( - isinstance(frame, (TranscriptionFrame, InterimTranscriptionFrame)) - and self._params.user_transcription_enabled - ): - await self._handle_user_transcriptions(frame) - elif ( - isinstance(frame, (OpenAILLMContextFrame, LLMContextFrame)) - and self._params.user_llm_enabled - ): - await self._handle_context(frame) - elif isinstance(frame, LLMFullResponseStartFrame) and self._params.bot_llm_enabled: - await self.send_rtvi_message(RTVIBotLLMStartedMessage()) - elif isinstance(frame, LLMFullResponseEndFrame) and self._params.bot_llm_enabled: - await self.send_rtvi_message(RTVIBotLLMStoppedMessage()) - elif isinstance(frame, LLMTextFrame) and self._params.bot_llm_enabled: - await self._handle_llm_text_frame(frame) - elif isinstance(frame, TTSStartedFrame) and self._params.bot_tts_enabled: - await self.send_rtvi_message(RTVIBotTTSStartedMessage()) - elif isinstance(frame, TTSStoppedFrame) and self._params.bot_tts_enabled: - await self.send_rtvi_message(RTVIBotTTSStoppedMessage()) - elif isinstance(frame, AggregatedTextFrame) and ( - self._params.bot_output_enabled or self._params.bot_tts_enabled - ): - if isinstance(frame, TTSTextFrame) and not isinstance(src, BaseOutputTransport): - # This check is to make sure we handle the frame when it has gone - # through the transport and has correct timing. - mark_as_seen = False - else: - await self._handle_aggregated_llm_text(frame) - elif isinstance(frame, MetricsFrame) and self._params.metrics_enabled: - await self._handle_metrics(frame) - elif isinstance(frame, FunctionCallsStartedFrame): - for function_call in frame.function_calls: - report_level = self._get_function_call_report_level(function_call.function_name) - if report_level == RTVIFunctionCallReportLevel.DISABLED: - continue - data = RTVILLMFunctionCallStartMessageData() - if report_level in ( - RTVIFunctionCallReportLevel.NAME, - RTVIFunctionCallReportLevel.FULL, - ): - data.function_name = function_call.function_name - message = RTVILLMFunctionCallStartMessage(data=data) - await self.send_rtvi_message(message) - elif isinstance(frame, FunctionCallInProgressFrame): - report_level = self._get_function_call_report_level(frame.function_name) - if report_level != RTVIFunctionCallReportLevel.DISABLED: - data = RTVILLMFunctionCallInProgressMessageData(tool_call_id=frame.tool_call_id) - if report_level in ( - RTVIFunctionCallReportLevel.NAME, - RTVIFunctionCallReportLevel.FULL, - ): - data.function_name = frame.function_name - if report_level == RTVIFunctionCallReportLevel.FULL: - data.arguments = frame.arguments - message = RTVILLMFunctionCallInProgressMessage(data=data) - await self.send_rtvi_message(message) - elif isinstance(frame, FunctionCallCancelFrame): - report_level = self._get_function_call_report_level(frame.function_name) - if report_level != RTVIFunctionCallReportLevel.DISABLED: - data = RTVILLMFunctionCallStoppedMessageData( - tool_call_id=frame.tool_call_id, - cancelled=True, - ) - if report_level in ( - RTVIFunctionCallReportLevel.NAME, - RTVIFunctionCallReportLevel.FULL, - ): - data.function_name = frame.function_name - message = RTVILLMFunctionCallStoppedMessage(data=data) - await self.send_rtvi_message(message) - elif isinstance(frame, FunctionCallResultFrame): - report_level = self._get_function_call_report_level(frame.function_name) - if report_level != RTVIFunctionCallReportLevel.DISABLED: - data = RTVILLMFunctionCallStoppedMessageData( - tool_call_id=frame.tool_call_id, - cancelled=False, - ) - if report_level in ( - RTVIFunctionCallReportLevel.NAME, - RTVIFunctionCallReportLevel.FULL, - ): - data.function_name = frame.function_name - if report_level == RTVIFunctionCallReportLevel.FULL: - data.result = frame.result if frame.result else None - message = RTVILLMFunctionCallStoppedMessage(data=data) - await self.send_rtvi_message(message) - elif isinstance(frame, RTVIServerMessageFrame): - message = RTVIServerMessage(data=frame.data) - await self.send_rtvi_message(message) - elif isinstance(frame, RTVIServerResponseFrame): - if frame.error is not None: - await self._send_error_response(frame) - else: - await self._send_server_response(frame) - elif isinstance(frame, InputAudioRawFrame) and self._params.user_audio_level_enabled: - curr_time = time.time() - diff_time = curr_time - self._last_user_audio_level - if diff_time > self._params.audio_level_period_secs: - level = calculate_audio_volume(frame.audio, frame.sample_rate) - message = RTVIUserAudioLevelMessage(data=RTVIAudioLevelMessageData(value=level)) - await self.send_rtvi_message(message) - self._last_user_audio_level = curr_time - elif isinstance(frame, TTSAudioRawFrame) and self._params.bot_audio_level_enabled: - curr_time = time.time() - diff_time = curr_time - self._last_bot_audio_level - if diff_time > self._params.audio_level_period_secs: - level = calculate_audio_volume(frame.audio, frame.sample_rate) - message = RTVIBotAudioLevelMessage(data=RTVIAudioLevelMessageData(value=level)) - await self.send_rtvi_message(message) - self._last_bot_audio_level = curr_time - - if mark_as_seen: - self._frames_seen.add(frame.id) - - async def _handle_interruptions(self, frame: Frame): - """Handle user speaking interruption frames.""" - message = None - if isinstance(frame, UserStartedSpeakingFrame): - message = RTVIUserStartedSpeakingMessage() - elif isinstance(frame, UserStoppedSpeakingFrame): - message = RTVIUserStoppedSpeakingMessage() - - if message: - await self.send_rtvi_message(message) - - async def _handle_user_mute(self, frame: Frame): - """Handle user mute/unmute frames.""" - message = None - if isinstance(frame, UserMuteStartedFrame): - message = RTVIUserMuteStartedMessage() - elif isinstance(frame, UserMuteStoppedFrame): - message = RTVIUserMuteStoppedMessage() - - if message: - await self.send_rtvi_message(message) - - async def _handle_bot_speaking(self, frame: Frame): - """Handle bot speaking event frames.""" - if isinstance(frame, BotStartedSpeakingFrame): - message = RTVIBotStartedSpeakingMessage() - await self.send_rtvi_message(message) - # Flush any queued aggregated text frames - for queued_frame in self._queued_aggregated_text_frames: - await self._send_aggregated_llm_text(queued_frame) - self._queued_aggregated_text_frames.clear() - self._bot_is_speaking = True - elif isinstance(frame, BotStoppedSpeakingFrame): - message = RTVIBotStoppedSpeakingMessage() - await self.send_rtvi_message(message) - self._bot_is_speaking = False - - async def _handle_aggregated_llm_text(self, frame: AggregatedTextFrame): - """Handle aggregated LLM text output frames.""" - if self._bot_is_speaking: - # Bot has already started speaking, send directly - await self._send_aggregated_llm_text(frame) - else: - # Bot hasn't started speaking yet, queue the frame - self._queued_aggregated_text_frames.append(frame) - - async def _send_aggregated_llm_text(self, frame: AggregatedTextFrame): - """Send aggregated LLM text messages.""" - # Skip certain aggregator types if configured to do so. - if ( - self._params.skip_aggregator_types - and frame.aggregated_by in self._params.skip_aggregator_types - ): - return - - text = frame.text - type = frame.aggregated_by - for aggregation_type, transform in self._aggregation_transforms: - if aggregation_type == type or aggregation_type == "*": - text = await transform(text, type) - - isTTS = isinstance(frame, TTSTextFrame) - if self._params.bot_output_enabled: - message = RTVIBotOutputMessage( - data=RTVIBotOutputMessageData(text=text, spoken=isTTS, aggregated_by=type) - ) - await self.send_rtvi_message(message) - - if isTTS and self._params.bot_tts_enabled: - tts_message = RTVIBotTTSTextMessage(data=RTVITextMessageData(text=text)) - await self.send_rtvi_message(tts_message) - - async def _handle_llm_text_frame(self, frame: LLMTextFrame): - """Handle LLM text output frames.""" - message = RTVIBotLLMTextMessage(data=RTVITextMessageData(text=frame.text)) - await self.send_rtvi_message(message) - - # TODO (mrkb): Remove all this logic when we fully deprecate bot-transcription messages. - self._bot_transcription += frame.text - - if match_endofsentence(self._bot_transcription) and len(self._bot_transcription) > 0: - await self.send_rtvi_message( - RTVIBotTranscriptionMessage(data=RTVITextMessageData(text=self._bot_transcription)) - ) - self._bot_transcription = "" - - async def _handle_user_transcriptions(self, frame: Frame): - """Handle user transcription frames.""" - message = None - if isinstance(frame, TranscriptionFrame): - message = RTVIUserTranscriptionMessage( - data=RTVIUserTranscriptionMessageData( - text=frame.text, user_id=frame.user_id, timestamp=frame.timestamp, final=True - ) - ) - elif isinstance(frame, InterimTranscriptionFrame): - message = RTVIUserTranscriptionMessage( - data=RTVIUserTranscriptionMessageData( - text=frame.text, user_id=frame.user_id, timestamp=frame.timestamp, final=False - ) - ) - - if message: - await self.send_rtvi_message(message) - - async def _handle_context(self, frame: OpenAILLMContextFrame | LLMContextFrame): - """Process LLM context frames to extract user messages for the RTVI client.""" - try: - if isinstance(frame, OpenAILLMContextFrame): - messages = frame.context.messages - else: - messages = frame.context.get_messages() - if not messages: - return - - message = messages[-1] - - # Handle Google LLM format (protobuf objects with attributes) - # Note: not possible if frame is a universal LLMContextFrame - if hasattr(message, "role") and message.role == "user" and hasattr(message, "parts"): - text = "".join(part.text for part in message.parts if hasattr(part, "text")) - if text: - rtvi_message = RTVIUserLLMTextMessage(data=RTVITextMessageData(text=text)) - await self.send_rtvi_message(rtvi_message) - - # Handle OpenAI format (original implementation) - elif isinstance(message, dict): - if message["role"] == "user": - content = message["content"] - if isinstance(content, list): - text = " ".join(item["text"] for item in content if "text" in item) - else: - text = content - rtvi_message = RTVIUserLLMTextMessage(data=RTVITextMessageData(text=text)) - await self.send_rtvi_message(rtvi_message) - - except Exception as e: - logger.warning(f"Caught an error while trying to handle context: {e}") - - async def _handle_metrics(self, frame: MetricsFrame): - """Handle metrics frames and convert to RTVI metrics messages.""" - metrics = {} - for d in frame.data: - if isinstance(d, TTFBMetricsData): - if "ttfb" not in metrics: - metrics["ttfb"] = [] - metrics["ttfb"].append(d.model_dump(exclude_none=True)) - elif isinstance(d, ProcessingMetricsData): - if "processing" not in metrics: - metrics["processing"] = [] - metrics["processing"].append(d.model_dump(exclude_none=True)) - elif isinstance(d, LLMUsageMetricsData): - if "tokens" not in metrics: - metrics["tokens"] = [] - metrics["tokens"].append(d.value.model_dump(exclude_none=True)) - elif isinstance(d, TTSUsageMetricsData): - if "characters" not in metrics: - metrics["characters"] = [] - metrics["characters"].append(d.model_dump(exclude_none=True)) - - message = RTVIMetricsMessage(data=metrics) - await self.send_rtvi_message(message) - - async def _send_server_response(self, frame: RTVIServerResponseFrame): - """Send a response to the client for a specific request.""" - message = RTVIServerResponse( - id=str(frame.client_msg.msg_id), - data=RTVIRawServerResponseData(t=frame.client_msg.type, d=frame.data), - ) - await self.send_rtvi_message(message) - - async def _send_error_response(self, frame: RTVIServerResponseFrame): - """Send a response to the client for a specific request.""" - message = RTVIErrorResponse( - id=str(frame.client_msg.msg_id), data=RTVIErrorResponseData(error=frame.error) - ) - await self.send_rtvi_message(message) - - -class RTVIProcessor(FrameProcessor): - """Main processor for handling RTVI protocol messages and actions. - - This processor manages the RTVI protocol communication including client-server - handshaking, configuration management, action execution, and message routing. - It serves as the central hub for RTVI protocol operations. - """ - - def __init__( - self, - *, - config: Optional[RTVIConfig] = None, - transport: Optional[BaseTransport] = None, - **kwargs, - ): - """Initialize the RTVI processor. - - Args: - config: Initial RTVI configuration. - transport: Transport layer for communication. - **kwargs: Additional arguments passed to parent class. - """ - super().__init__(**kwargs) - self._config = config or RTVIConfig(config=[]) - - self._bot_ready = False - self._client_ready = False - self._client_ready_id = "" - # Default to 0.3.0 which is the last version before actually having a - # "client-version". - self._client_version = [0, 3, 0] - self._llm_skip_tts: bool = False # Keep in sync with llm_service.py's configuration. - - self._registered_actions: Dict[str, RTVIAction] = {} - self._registered_services: Dict[str, RTVIService] = {} - - # A task to process incoming action frames. - self._action_task: Optional[asyncio.Task] = None - - # A task to process incoming transport messages. - self._message_task: Optional[asyncio.Task] = None - - self._register_event_handler("on_bot_started") - self._register_event_handler("on_client_ready") - self._register_event_handler("on_client_message") - - self._input_transport = None - self._transport = transport - if self._transport: - input_transport = self._transport.input() - if isinstance(input_transport, BaseInputTransport): - self._input_transport = input_transport - self._input_transport.enable_audio_in_stream_on_start(False) - - def register_action(self, action: RTVIAction): - """Register an action that can be executed via RTVI. - - Args: - action: The action to register. - """ - import warnings - - with warnings.catch_warnings(): - warnings.simplefilter("always") - warnings.warn( - "The actions API is deprecated, use server and client messages instead.", - DeprecationWarning, - ) - - id = self._action_id(action.service, action.action) - self._registered_actions[id] = action - - def register_service(self, service: RTVIService): - """Register a service that can be configured via RTVI. - - Args: - service: The service to register. - """ - import warnings - - with warnings.catch_warnings(): - warnings.simplefilter("always") - warnings.warn( - "The actions API is deprecated, use server and client messages instead.", - DeprecationWarning, - ) - - self._registered_services[service.name] = service - - def create_rtvi_observer(self, *, params: Optional[RTVIObserverParams] = None, **kwargs): - """Creates a new RTVI Observer. - - Args: - params: Settings to enable/disable specific messages. - **kwargs: Additional arguments passed to the observer. - - Returns: - A new RTVI observer. - """ - return RTVIObserver(self, params=params, **kwargs) - - async def set_client_ready(self): - """Mark the client as ready and trigger the ready event.""" - self._client_ready = True - await self._call_event_handler("on_client_ready") - - async def set_bot_ready(self, about: Mapping[str, Any] = None): - """Mark the bot as ready and send the bot-ready message. - - Args: - about: Optional information about the bot to include in the ready message. - If left as None, the Pipecat library and version will be used. - """ - self._bot_ready = True - # Only call the (deprecated) _update_config method if the we're using a - # config (which is deprecated). Otherwise we'd always print an - # unnecessary deprecation warning. - if self._config.config: - await self._update_config(self._config, False) - await self._send_bot_ready(about=about) - - async def interrupt_bot(self): - """Send a bot interruption frame upstream.""" - await self.broadcast_interruption() - - async def send_server_message(self, data: Any): - """Send a server message to the client.""" - message = RTVIServerMessage(data=data) - await self._send_server_message(message) - - async def send_server_response(self, client_msg: RTVIClientMessage, data: Any): - """Send a server response for a given client message.""" - message = RTVIServerResponse( - id=client_msg.msg_id, data=RTVIRawServerResponseData(t=client_msg.type, d=data) - ) - await self._send_server_message(message) - - async def send_error_response(self, client_msg: RTVIClientMessage, error: str): - """Send an error response for a given client message.""" - await self._send_error_response(id=client_msg.msg_id, error=error) - - async def send_error(self, error: str): - """Send an error message to the client. - - Args: - error: The error message to send. - """ - await self._send_error_frame(ErrorFrame(error=error)) - - async def push_transport_message(self, model: BaseModel, exclude_none: bool = True): - """Push a transport message frame.""" - frame = OutputTransportMessageUrgentFrame( - message=model.model_dump(exclude_none=exclude_none) - ) - await self.push_frame(frame) - - async def handle_message(self, message: RTVIMessage): - """Handle an incoming RTVI message. - - Args: - message: The RTVI message to handle. - """ - await self._message_queue.put(message) - - async def handle_function_call(self, params: FunctionCallParams): - """Handle a function call from the LLM. - - Args: - params: The function call parameters. - - .. deprecated:: 0.0.102 - This method is deprecated. Function call events are now automatically - sent by ``RTVIObserver`` using the ``llm-function-call-in-progress`` event. - Configure reporting level via ``RTVIObserverParams.function_call_report_level``. - """ - import warnings - - warnings.warn( - "handle_function_call is deprecated. Function call events are now " - "automatically sent by RTVIObserver using llm-function-call-in-progress.", - DeprecationWarning, - stacklevel=2, - ) - fn = RTVILLMFunctionCallMessageData( - function_name=params.function_name, - tool_call_id=params.tool_call_id, - args=params.arguments, - ) - message = RTVILLMFunctionCallMessage(data=fn) - await self.push_transport_message(message, exclude_none=False) - - async def process_frame(self, frame: Frame, direction: FrameDirection): - """Process incoming frames through the RTVI processor. - - Args: - frame: The frame to process. - direction: The direction of frame flow. - """ - await super().process_frame(frame, direction) - - # Specific system frames - if isinstance(frame, StartFrame): - # Push StartFrame before start(), because we want StartFrame to be - # processed by every processor before any other frame is processed. - await self.push_frame(frame, direction) - await self._start(frame) - elif isinstance(frame, CancelFrame): - await self._cancel(frame) - await self.push_frame(frame, direction) - elif isinstance(frame, ErrorFrame): - await self._send_error_frame(frame) - await self.push_frame(frame, direction) - elif isinstance(frame, InputTransportMessageFrame): - await self._handle_transport_message(frame) - # All other system frames - elif isinstance(frame, SystemFrame): - await self.push_frame(frame, direction) - # Control frames - elif isinstance(frame, EndFrame): - # Push EndFrame before stop(), because stop() waits on the task to - # finish and the task finishes when EndFrame is processed. - await self.push_frame(frame, direction) - await self._stop(frame) - # Data frames - elif isinstance(frame, RTVIActionFrame): - await self._action_queue.put(frame) - elif isinstance(frame, LLMConfigureOutputFrame): - self._llm_skip_tts = frame.skip_tts - await self.push_frame(frame, direction) - # Other frames - else: - await self.push_frame(frame, direction) - - async def _start(self, frame: StartFrame): - """Start the RTVI processor tasks.""" - if not self._action_task: - self._action_queue = asyncio.Queue() - self._action_task = self.create_task(self._action_task_handler()) - if not self._message_task: - self._message_queue = asyncio.Queue() - self._message_task = self.create_task(self._message_task_handler()) - await self._call_event_handler("on_bot_started") - - async def _stop(self, frame: EndFrame): - """Stop the RTVI processor tasks.""" - await self._cancel_tasks() - - async def _cancel(self, frame: CancelFrame): - """Cancel the RTVI processor tasks.""" - await self._cancel_tasks() - - async def _cancel_tasks(self): - """Cancel all running tasks.""" - if self._action_task: - await self.cancel_task(self._action_task) - self._action_task = None - - if self._message_task: - await self.cancel_task(self._message_task) - self._message_task = None - - async def _action_task_handler(self): - """Handle incoming action frames.""" - while True: - frame = await self._action_queue.get() - await self._handle_action(frame.message_id, frame.rtvi_action_run) - self._action_queue.task_done() - - async def _message_task_handler(self): - """Handle incoming transport messages.""" - while True: - message = await self._message_queue.get() - await self._handle_message(message) - self._message_queue.task_done() - - async def _handle_transport_message(self, frame: InputTransportMessageFrame): - """Handle an incoming transport message frame.""" - try: - transport_message = frame.message - if transport_message.get("label") != RTVI_MESSAGE_LABEL: - logger.warning(f"Ignoring not RTVI message: {transport_message}") - return - message = RTVIMessage.model_validate(transport_message) - await self._message_queue.put(message) - except ValidationError as e: - await self.send_error(f"Invalid RTVI transport message: {e}") - logger.warning(f"Invalid RTVI transport message: {e}") - - async def _handle_message(self, message: RTVIMessage): - """Handle a parsed RTVI message.""" - try: - match message.type: - case "client-ready": - data = None - try: - data = RTVIClientReadyData.model_validate(message.data) - except ValidationError: - # Not all clients have been updated to RTVI 1.0.0. - # For now, that's okay, we just log their info as unknown. - data = None - pass - await self._handle_client_ready(message.id, data) - case "describe-actions": - await self._handle_describe_actions(message.id) - case "describe-config": - await self._handle_describe_config(message.id) - case "get-config": - await self._handle_get_config(message.id) - case "update-config": - update_config = RTVIUpdateConfig.model_validate(message.data) - await self._handle_update_config(message.id, update_config) - case "disconnect-bot": - await self.push_frame(EndTaskFrame(), FrameDirection.UPSTREAM) - case "client-message": - data = RTVIRawClientMessageData.model_validate(message.data) - await self._handle_client_message(message.id, data) - case "action": - action = RTVIActionRun.model_validate(message.data) - action_frame = RTVIActionFrame(message_id=message.id, rtvi_action_run=action) - await self._action_queue.put(action_frame) - case "llm-function-call-result": - data = RTVILLMFunctionCallResultData.model_validate(message.data) - await self._handle_function_call_result(data) - case "send-text": - data = RTVISendTextData.model_validate(message.data) - await self._handle_send_text(data) - case "append-to-context": - logger.warning( - f"The append-to-context message is deprecated, use send-text instead." - ) - data = RTVIAppendToContextData.model_validate(message.data) - await self._handle_update_context(data) - case "raw-audio" | "raw-audio-batch": - await self._handle_audio_buffer(message.data) - - case _: - await self._send_error_response(message.id, f"Unsupported type {message.type}") - - except ValidationError as e: - await self._send_error_response(message.id, f"Invalid message: {e}") - logger.warning(f"Invalid message: {e}") - except Exception as e: - await self._send_error_response(message.id, f"Exception processing message: {e}") - logger.warning(f"Exception processing message: {e}") - - async def _handle_client_ready(self, request_id: str, data: RTVIClientReadyData | None): - """Handle the client-ready message from the client.""" - version = data.version if data else None - logger.debug(f"Received client-ready: version {version}") - if version: - try: - self._client_version = [int(v) for v in version.split(".")] - except ValueError: - logger.warning(f"Invalid client version format: {version}") - about = data.about if data else {"library": "unknown"} - logger.debug(f"Client Details: {about}") - if self._input_transport: - await self._input_transport.start_audio_in_streaming() - - self._client_ready_id = request_id - await self.set_client_ready() - - async def _handle_audio_buffer(self, data): - """Handle incoming audio buffer data.""" - if not self._input_transport: - return - - # Extract audio batch ensuring it's a list - audio_list = data.get("base64AudioBatch") or [data.get("base64Audio")] - - try: - for base64_audio in filter(None, audio_list): # Filter out None values - pcm_bytes = base64.b64decode(base64_audio) - frame = InputAudioRawFrame( - audio=pcm_bytes, - sample_rate=data["sampleRate"], - num_channels=data["numChannels"], - ) - await self._input_transport.push_audio_frame(frame) - - except (KeyError, TypeError, ValueError) as e: - # Handle missing keys, decoding errors, and invalid types - logger.error(f"Error processing audio buffer: {e}") - - async def _handle_describe_config(self, request_id: str): - """Handle a describe-config request.""" - import warnings - - with warnings.catch_warnings(): - warnings.simplefilter("always") - warnings.warn( - "Configuration helpers are deprecated. If your application needs this behavior, use custom server and client messages.", - DeprecationWarning, - ) - - services = list(self._registered_services.values()) - message = RTVIDescribeConfig(id=request_id, data=RTVIDescribeConfigData(config=services)) - await self.push_transport_message(message) - - async def _handle_describe_actions(self, request_id: str): - """Handle a describe-actions request.""" - import warnings - - with warnings.catch_warnings(): - warnings.simplefilter("always") - warnings.warn( - "The Actions API is deprecated, use custom server and client messages instead.", - DeprecationWarning, - ) - - actions = list(self._registered_actions.values()) - message = RTVIDescribeActions(id=request_id, data=RTVIDescribeActionsData(actions=actions)) - await self.push_transport_message(message) - - async def _handle_get_config(self, request_id: str): - """Handle a get-config request.""" - import warnings - - with warnings.catch_warnings(): - warnings.simplefilter("always") - warnings.warn( - "Configuration helpers are deprecated. If your application needs this behavior, use custom server and client messages.", - DeprecationWarning, - ) - - message = RTVIConfigResponse(id=request_id, data=self._config) - await self.push_transport_message(message) - - def _update_config_option(self, service: str, config: RTVIServiceOptionConfig): - """Update a specific configuration option.""" - for service_config in self._config.config: - if service_config.service == service: - for option_config in service_config.options: - if option_config.name == config.name: - option_config.value = config.value - return - # If we couldn't find a value for this config, we simply need to - # add it. - service_config.options.append(config) - - async def _update_service_config(self, config: RTVIServiceConfig): - """Update configuration for a specific service.""" - import warnings - - with warnings.catch_warnings(): - warnings.simplefilter("always") - warnings.warn( - "Configuration helpers are deprecated. If your application needs this behavior, use custom server and client messages.", - DeprecationWarning, - ) - - service = self._registered_services[config.service] - for option in config.options: - handler = service._options_dict[option.name].handler - await handler(self, service.name, option) - self._update_config_option(service.name, option) - - async def _update_config(self, data: RTVIConfig, interrupt: bool): - """Update the RTVI configuration.""" - import warnings - - with warnings.catch_warnings(): - warnings.simplefilter("always") - warnings.warn( - "Configuration helpers are deprecated. If your application needs this behavior, use custom server and client messages.", - DeprecationWarning, - ) - - if interrupt: - await self.interrupt_bot() - for service_config in data.config: - await self._update_service_config(service_config) - - async def _handle_update_config(self, request_id: str, data: RTVIUpdateConfig): - """Handle an update-config request.""" - await self._update_config(RTVIConfig(config=data.config), data.interrupt) - await self._handle_get_config(request_id) - - async def _handle_send_text(self, data: RTVISendTextData): - """Handle a send-text message from the client.""" - opts = data.options if data.options is not None else RTVISendTextOptions() - if opts.run_immediately: - await self.interrupt_bot() - cur_llm_skip_tts = self._llm_skip_tts - should_skip_tts = not opts.audio_response - toggle_skip_tts = cur_llm_skip_tts != should_skip_tts - if toggle_skip_tts: - output_frame = LLMConfigureOutputFrame(skip_tts=should_skip_tts) - await self.push_frame(output_frame) - text_frame = LLMMessagesAppendFrame( - messages=[{"role": "user", "content": data.content}], - run_llm=opts.run_immediately, - ) - await self.push_frame(text_frame) - if toggle_skip_tts: - output_frame = LLMConfigureOutputFrame(skip_tts=cur_llm_skip_tts) - await self.push_frame(output_frame) - - async def _handle_update_context(self, data: RTVIAppendToContextData): - if data.run_immediately: - await self.interrupt_bot() - frame = LLMMessagesAppendFrame( - messages=[{"role": data.role, "content": data.content}], - run_llm=data.run_immediately, - ) - await self.push_frame(frame) - - async def _handle_client_message(self, msg_id: str, data: RTVIRawClientMessageData): - """Handle a client message frame.""" - if not data: - await self._send_error_response(msg_id, "Malformed client message") - return - - # Create a RTVIClientMessageFrame to push the message - frame = RTVIClientMessageFrame(msg_id=msg_id, type=data.t, data=data.d) - await self.push_frame(frame) - await self._call_event_handler( - "on_client_message", - RTVIClientMessage( - msg_id=msg_id, - type=data.t, - data=data.d, - ), - ) - - async def _handle_function_call_result(self, data): - """Handle a function call result from the client.""" - frame = FunctionCallResultFrame( - function_name=data.function_name, - tool_call_id=data.tool_call_id, - arguments=data.arguments, - result=data.result, - ) - await self.push_frame(frame) - - async def _handle_action(self, request_id: Optional[str], data: RTVIActionRun): - """Handle an action execution request.""" - action_id = self._action_id(data.service, data.action) - if action_id not in self._registered_actions: - await self._send_error_response(request_id, f"Action {action_id} not registered") - return - action = self._registered_actions[action_id] - arguments = {} - if data.arguments: - for arg in data.arguments: - arguments[arg.name] = arg.value - result = await action.handler(self, action.service, arguments) - # Only send a response if request_id is present. Things that don't care about - # action responses (such as webhooks) don't set a request_id - if request_id: - message = RTVIActionResponse(id=request_id, data=RTVIActionResponseData(result=result)) - await self.push_transport_message(message) - - async def _send_bot_ready(self, about: Mapping[str, Any] = None): - """Send the bot-ready message to the client. - - Args: - about: Optional information about the bot to include in the ready message. - If left as None, the pipecat library and version will be used. - """ - config = None - if self._client_version and self._client_version[0] < 1: - config = self._config.config - if not about: - about = {"library": "pipecat-ai", "library_version": f"{pipecat_version()}"} - message = RTVIBotReady( - id=self._client_ready_id, - data=RTVIBotReadyData(version=RTVI_PROTOCOL_VERSION, about=about, config=config), - ) - await self.push_transport_message(message) - - async def _send_server_message(self, message: RTVIServerMessage | RTVIServerResponse): - """Send a message or response to the client.""" - await self.push_transport_message(message) - - async def _send_error_frame(self, frame: ErrorFrame): - """Send an error frame as an RTVI error message.""" - message = RTVIError(data=RTVIErrorData(error=frame.error, fatal=frame.fatal)) - await self.push_transport_message(message) - - async def _send_error_response(self, id: str, error: str): - """Send an error response message.""" - message = RTVIErrorResponse(id=id, data=RTVIErrorResponseData(error=error)) - await self.push_transport_message(message) - - def _action_id(self, service: str, action: str) -> str: - """Generate an action ID from service and action names.""" - return f"{service}:{action}" diff --git a/src/pipecat/processors/frameworks/rtvi/__init__.py b/src/pipecat/processors/frameworks/rtvi/__init__.py new file mode 100644 index 000000000..12f6022ee --- /dev/null +++ b/src/pipecat/processors/frameworks/rtvi/__init__.py @@ -0,0 +1,73 @@ +# +# Copyright (c) 2024-2026, Daily +# +# SPDX-License-Identifier: BSD 2-Clause License +# + +"""RTVI (Real-Time Voice Interface) protocol implementation for Pipecat.""" + +from pipecat.processors.frameworks.rtvi.frames import ( + RTVIActionFrame, + RTVIClientMessageFrame, + RTVIServerMessageFrame, + RTVIServerResponseFrame, +) +from pipecat.processors.frameworks.rtvi.models_v0 import ( + ActionResult, + RTVIAction, + RTVIActionArgument, + RTVIActionArgumentData, + RTVIActionResponse, + RTVIActionResponseData, + RTVIActionRun, + RTVIActionRunArgument, + RTVIBotReadyDataDeprecated, + RTVIConfig, + RTVIConfigResponse, + RTVIDescribeActions, + RTVIDescribeActionsData, + RTVIDescribeConfig, + RTVIDescribeConfigData, + RTVIService, + RTVIServiceConfig, + RTVIServiceOption, + RTVIServiceOptionConfig, + RTVIUpdateConfig, +) +from pipecat.processors.frameworks.rtvi.observer import ( + RTVIFunctionCallReportLevel, + RTVIObserver, + RTVIObserverParams, +) +from pipecat.processors.frameworks.rtvi.processor import RTVIProcessor + +__all__ = [ + "ActionResult", + "RTVIAction", + "RTVIActionArgument", + "RTVIActionArgumentData", + "RTVIActionFrame", + "RTVIActionResponse", + "RTVIActionResponseData", + "RTVIActionRun", + "RTVIActionRunArgument", + "RTVIBotReadyDataDeprecated", + "RTVIClientMessageFrame", + "RTVIConfig", + "RTVIConfigResponse", + "RTVIDescribeActions", + "RTVIDescribeActionsData", + "RTVIDescribeConfig", + "RTVIDescribeConfigData", + "RTVIFunctionCallReportLevel", + "RTVIObserver", + "RTVIObserverParams", + "RTVIProcessor", + "RTVIServerMessageFrame", + "RTVIServerResponseFrame", + "RTVIService", + "RTVIServiceConfig", + "RTVIServiceOption", + "RTVIServiceOptionConfig", + "RTVIUpdateConfig", +] diff --git a/src/pipecat/processors/frameworks/rtvi/frames.py b/src/pipecat/processors/frameworks/rtvi/frames.py new file mode 100644 index 000000000..37d25c764 --- /dev/null +++ b/src/pipecat/processors/frameworks/rtvi/frames.py @@ -0,0 +1,74 @@ +# +# Copyright (c) 2024-2026, Daily +# +# SPDX-License-Identifier: BSD 2-Clause License +# + +"""RTVI pipeline frame definitions.""" + +from dataclasses import dataclass +from typing import Any, Optional + +from pipecat.frames.frames import DataFrame, SystemFrame + + +@dataclass +class RTVIActionFrame(DataFrame): + """Frame containing an RTVI action to execute. + + Parameters: + rtvi_action_run: The action to execute. + message_id: Optional message ID for response correlation. + + .. deprecated:: 0.0.75 + Actions have been removed as part of the RTVI protocol 1.0.0. + Use custom client and server messages instead. + """ + + rtvi_action_run: Any + message_id: Optional[str] = None + + +@dataclass +class RTVIServerMessageFrame(SystemFrame): + """A frame for sending server messages to the client. + + Parameters: + data: The message data to send to the client. + """ + + data: Any + + def __str__(self): + """String representation of the RTVI server message frame.""" + return f"{self.name}(data: {self.data})" + + +@dataclass +class RTVIClientMessageFrame(SystemFrame): + """A frame for sending messages from the client to the RTVI server. + + This frame is meant for custom messaging from the client to the server + and expects a server-response message. + """ + + msg_id: str + type: str + data: Optional[Any] = None + + +@dataclass +class RTVIServerResponseFrame(SystemFrame): + """A frame for responding to a client RTVI message. + + This frame should be sent in response to an RTVIClientMessageFrame + and include the original RTVIClientMessageFrame to ensure the response + is properly attributed to the original request. To respond with an error, + set the `error` field to a string describing the error. This will result + in the client receiving a `response-error` message instead of a + `server-response` message. + """ + + client_msg: RTVIClientMessageFrame + data: Optional[Any] = None + error: Optional[str] = None diff --git a/src/pipecat/processors/frameworks/rtvi/models_v0.py b/src/pipecat/processors/frameworks/rtvi/models_v0.py new file mode 100644 index 000000000..b3826902e --- /dev/null +++ b/src/pipecat/processors/frameworks/rtvi/models_v0.py @@ -0,0 +1,334 @@ +# +# Copyright (c) 2024-2026, Daily +# +# SPDX-License-Identifier: BSD 2-Clause License +# + +"""RTVI pre-1.0 protocol models (deprecated). + +All classes here are kept for backward compatibility only. Pipeline configuration +and the actions API were removed in RTVI protocol 1.0.0. Use custom client and +server messages instead. +""" + +from typing import ( + Any, + Awaitable, + Callable, + Dict, + List, + Literal, + Optional, + Union, +) + +from pydantic import BaseModel, Field, PrivateAttr + +import pipecat.processors.frameworks.rtvi.models_v1 as RTVI + +ActionResult = Union[bool, int, float, str, list, dict] + + +class RTVIServiceOption(BaseModel): + """Configuration option for an RTVI service. + + Defines a configurable option that can be set for an RTVI service, + including its name, type, and handler function. + + .. deprecated:: 0.0.75 + Pipeline Configuration has been removed as part of the RTVI protocol 1.0.0. + Use custom client and server messages instead. + """ + + name: str + type: Literal["bool", "number", "string", "array", "object"] + handler: Callable[["RTVIProcessor", str, "RTVIServiceOptionConfig"], Awaitable[None]] = Field( + exclude=True + ) + + +class RTVIService(BaseModel): + """An RTVI service definition. + + Represents a service that can be configured and used within the RTVI protocol, + containing a name and list of configurable options. + + .. deprecated:: 0.0.75 + Pipeline Configuration has been removed as part of the RTVI protocol 1.0.0. + Use custom client and server messages instead. + """ + + name: str + options: List[RTVIServiceOption] + _options_dict: Dict[str, RTVIServiceOption] = PrivateAttr(default={}) + + def model_post_init(self, __context: Any) -> None: + """Initialize the options dictionary after model creation.""" + self._options_dict = {} + for option in self.options: + self._options_dict[option.name] = option + return super().model_post_init(__context) + + +class RTVIActionArgumentData(BaseModel): + """Data for an RTVI action argument. + + Contains the name and value of an argument passed to an RTVI action. + + .. deprecated:: 0.0.75 + Actions have been removed as part of the RTVI protocol 1.0.0. + Use custom client and server messages instead. + """ + + name: str + value: Any + + +class RTVIActionArgument(BaseModel): + """Definition of an RTVI action argument. + + Specifies the name and expected type of an argument for an RTVI action. + + .. deprecated:: 0.0.75 + Actions have been removed as part of the RTVI protocol 1.0.0. + Use custom client and server messages instead. + """ + + name: str + type: Literal["bool", "number", "string", "array", "object"] + + +class RTVIAction(BaseModel): + """An RTVI action definition. + + Represents an action that can be executed within the RTVI protocol, + including its service, name, arguments, and handler function. + + .. deprecated:: 0.0.75 + Actions have been removed as part of the RTVI protocol 1.0.0. + Use custom client and server messages instead. + """ + + service: str + action: str + arguments: List[RTVIActionArgument] = Field(default_factory=list) + result: Literal["bool", "number", "string", "array", "object"] + handler: Callable[["RTVIProcessor", str, Dict[str, Any]], Awaitable[ActionResult]] = Field( + exclude=True + ) + _arguments_dict: Dict[str, RTVIActionArgument] = PrivateAttr(default={}) + + def model_post_init(self, __context: Any) -> None: + """Initialize the arguments dictionary after model creation.""" + self._arguments_dict = {} + for arg in self.arguments: + self._arguments_dict[arg.name] = arg + return super().model_post_init(__context) + + +class RTVIServiceOptionConfig(BaseModel): + """Configuration value for an RTVI service option. + + Contains the name and value to set for a specific service option. + + .. deprecated:: 0.0.75 + Pipeline Configuration has been removed as part of the RTVI protocol 1.0.0. + Use custom client and server messages instead. + """ + + name: str + value: Any + + +class RTVIServiceConfig(BaseModel): + """Configuration for an RTVI service. + + Contains the service name and list of option configurations to apply. + + .. deprecated:: 0.0.75 + Pipeline Configuration has been removed as part of the RTVI protocol 1.0.0. + Use custom client and server messages instead. + """ + + service: str + options: List[RTVIServiceOptionConfig] + + +class RTVIConfig(BaseModel): + """Complete RTVI configuration. + + Contains the full configuration for all RTVI services. + + .. deprecated:: 0.0.75 + Pipeline Configuration has been removed as part of the RTVI protocol 1.0.0. + Use custom client and server messages instead. + """ + + config: List[RTVIServiceConfig] + + +# +# Client -> Pipecat messages. +# + + +class RTVIUpdateConfig(BaseModel): + """Request to update RTVI configuration. + + Contains new configuration settings and whether to interrupt the bot. + + .. deprecated:: 0.0.75 + Pipeline Configuration has been removed as part of the RTVI protocol 1.0.0. + Use custom client and server messages instead. + """ + + config: List[RTVIServiceConfig] + interrupt: bool = False + + +class RTVIActionRunArgument(BaseModel): + """Argument for running an RTVI action. + + Contains the name and value of an argument to pass to an action. + + .. deprecated:: 0.0.75 + Actions have been removed as part of the RTVI protocol 1.0.0. + Use custom client and server messages instead. + """ + + name: str + value: Any + + +class RTVIActionRun(BaseModel): + """Request to run an RTVI action. + + Contains the service, action name, and optional arguments. + + .. deprecated:: 0.0.75 + Actions have been removed as part of the RTVI protocol 1.0.0. + Use custom client and server messages instead. + """ + + service: str + action: str + arguments: Optional[List[RTVIActionRunArgument]] = None + + +# +# Pipecat -> Client responses and messages. +# + + +class RTVIBotReadyDataDeprecated(RTVI.BotReadyData): + """Data for bot ready notification. + + Contains protocol version and initial configuration. + """ + + # The config field is deprecated and will not be included if + # the client's rtvi version is 1.0.0 or higher. + config: Optional[List[RTVIServiceConfig]] = None + + +class RTVIDescribeConfigData(BaseModel): + """Data for describing available RTVI configuration. + + Contains the list of available services and their options. + + .. deprecated:: 0.0.75 + Pipeline Configuration has been removed as part of the RTVI protocol 1.0.0. + Use custom client and server messages instead. + """ + + config: List[RTVIService] + + +class RTVIDescribeConfig(BaseModel): + """Message describing available RTVI configuration. + + Sent in response to a describe-config request. + + .. deprecated:: 0.0.75 + Pipeline Configuration has been removed as part of the RTVI protocol 1.0.0. + Use custom client and server messages instead. + """ + + label: RTVI.MessageLiteral = RTVI.MESSAGE_LABEL + type: Literal["config-available"] = "config-available" + id: str + data: RTVIDescribeConfigData + + +class RTVIDescribeActionsData(BaseModel): + """Data for describing available RTVI actions. + + Contains the list of available actions that can be executed. + + .. deprecated:: 0.0.75 + Actions have been removed as part of the RTVI protocol 1.0.0. + Use custom client and server messages instead. + """ + + actions: List[RTVIAction] + + +class RTVIDescribeActions(BaseModel): + """Message describing available RTVI actions. + + Sent in response to a describe-actions request. + + .. deprecated:: 0.0.75 + Actions have been removed as part of the RTVI protocol 1.0.0. + Use custom client and server messages instead. + """ + + label: RTVI.MessageLiteral = RTVI.MESSAGE_LABEL + type: Literal["actions-available"] = "actions-available" + id: str + data: RTVIDescribeActionsData + + +class RTVIConfigResponse(BaseModel): + """Response containing current RTVI configuration. + + Sent in response to a get-config request. + + .. deprecated:: 0.0.75 + Pipeline Configuration has been removed as part of the RTVI protocol 1.0.0. + Use custom client and server messages instead. + """ + + label: RTVI.MessageLiteral = RTVI.MESSAGE_LABEL + type: Literal["config"] = "config" + id: str + data: RTVIConfig + + +class RTVIActionResponseData(BaseModel): + """Data for an RTVI action response. + + Contains the result of executing an action. + + .. deprecated:: 0.0.75 + Actions have been removed as part of the RTVI protocol 1.0.0. + Use custom client and server messages instead. + """ + + result: ActionResult + + +class RTVIActionResponse(BaseModel): + """Response to an RTVI action execution. + + Sent after successfully executing an action. + + .. deprecated:: 0.0.75 + Actions have been removed as part of the RTVI protocol 1.0.0. + Use custom client and server messages instead. + """ + + label: RTVI.MessageLiteral = RTVI.MESSAGE_LABEL + type: Literal["action-response"] = "action-response" + id: str + data: RTVIActionResponseData diff --git a/src/pipecat/processors/frameworks/rtvi/models_v1.py b/src/pipecat/processors/frameworks/rtvi/models_v1.py new file mode 100644 index 000000000..f38986cb0 --- /dev/null +++ b/src/pipecat/processors/frameworks/rtvi/models_v1.py @@ -0,0 +1,581 @@ +# +# Copyright (c) 2024–2025, Daily +# +# SPDX-License-Identifier: BSD 2-Clause License +# + +"""RTVI protocol v1 message models. + +Contains all RTVI protocol v1 message definitions and data structures. +Import this module under the ``RTVI`` alias to use as a namespace:: + + import pipecat.processors.frameworks.rtvi.models_v1 as RTVI + + msg = RTVI.BotReady(id="1", data=RTVI.BotReadyData(version=RTVI.PROTOCOL_VERSION)) +""" + +from typing import ( + Any, + Dict, + Literal, + Mapping, + Optional, +) + +from pydantic import BaseModel + +from pipecat.frames.frames import ( + AggregationType, +) + +# -- Constants -- +PROTOCOL_VERSION = "1.2.0" + +MESSAGE_LABEL = "rtvi-ai" +MessageLiteral = Literal["rtvi-ai"] + +# -- Base Message Structure -- + + +class Message(BaseModel): + """Base RTVI message structure. + + Represents the standard format for RTVI protocol messages. + """ + + label: MessageLiteral = MESSAGE_LABEL + type: str + id: str + data: Optional[Dict[str, Any]] = None + + +# -- Client -> Pipecat messages. + + +class RawClientMessageData(BaseModel): + """Data structure expected from client messages sent to the RTVI server.""" + + t: str + d: Optional[Any] = None + + +class ClientMessage(BaseModel): + """Cleansed data structure for client messages for handling.""" + + msg_id: str + type: str + data: Optional[Any] = None + + +class RawServerResponseData(BaseModel): + """Data structure for server responses to client messages.""" + + t: str + d: Optional[Any] = None + + +class ServerResponse(BaseModel): + """The RTVI-formatted message response from the server to the client. + + This message is used to respond to custom messages sent by the client. + """ + + label: MessageLiteral = MESSAGE_LABEL + type: Literal["server-response"] = "server-response" + id: str + data: RawServerResponseData + + +class AboutClientData(BaseModel): + """Data about the RTVI client. + + Contains information about the client, including which RTVI library it + is using, what platform it is on and any additional details, if available. + """ + + library: str + library_version: Optional[str] = None + platform: Optional[str] = None + platform_version: Optional[str] = None + platform_details: Optional[Any] = None + + +class ClientReadyData(BaseModel): + """Data format of client ready messages. + + Contains the RTVI protocol version and client information. + """ + + version: str + about: AboutClientData + + +# -- Pipecat -> Client errors + + +class ErrorResponseData(BaseModel): + """Data for an RTVI error response. + + Contains the error message to send back to the client. + """ + + error: str + + +class ErrorResponse(BaseModel): + """RTVI error response message. + + RTVI formatted error response message for relaying failed client requests. + """ + + label: MessageLiteral = MESSAGE_LABEL + type: Literal["error-response"] = "error-response" + id: str + data: ErrorResponseData + + +class ErrorData(BaseModel): + """Data for an RTVI error event. + + Contains error information including whether it's fatal. + """ + + error: str + fatal: bool # Indicates the pipeline has stopped due to this error + + +class Error(BaseModel): + """RTVI error event message. + + RTVI formatted error message for relaying errors in the pipeline. + """ + + label: MessageLiteral = MESSAGE_LABEL + type: Literal["error"] = "error" + data: ErrorData + + +# -- Pipecat -> Client responses and messages. + + +class BotReadyData(BaseModel): + """Data for bot ready notification. + + Contains protocol version and initial configuration. + """ + + version: str + about: Optional[Mapping[str, Any]] = None + + +class BotReady(BaseModel): + """Message indicating bot is ready for interaction. + + Sent after bot initialization is complete. + """ + + label: MessageLiteral = MESSAGE_LABEL + type: Literal["bot-ready"] = "bot-ready" + id: str + data: BotReadyData + + +class LLMFunctionCallMessageData(BaseModel): + """Data for LLM function call notification. + + Contains function call details including name, ID, and arguments. + + .. deprecated:: 0.0.102 + Use ``LLMFunctionCallInProgressMessageData`` instead. + """ + + function_name: str + tool_call_id: str + args: Mapping[str, Any] + + +class LLMFunctionCallMessage(BaseModel): + """Message notifying of an LLM function call. + + Sent when the LLM makes a function call. + + .. deprecated:: 0.0.102 + Use ``LLMFunctionCallInProgressMessage`` with the + ``llm-function-call-in-progress`` event type instead. + """ + + label: MessageLiteral = MESSAGE_LABEL + type: Literal["llm-function-call"] = "llm-function-call" + data: LLMFunctionCallMessageData + + +class SendTextOptions(BaseModel): + """Options for sending text input to the LLM. + + Contains options for how the pipeline should process the text input. + """ + + run_immediately: bool = True + audio_response: bool = True + + +class SendTextData(BaseModel): + """Data format for sending text input to the LLM. + + Contains the text content to send and any options for how the pipeline should process it. + """ + + content: str + options: Optional[SendTextOptions] = None + + +class AppendToContextData(BaseModel): + """Data format for appending messages to the context. + + Contains the role, content, and whether to run the message immediately. + + .. deprecated:: 0.0.85 + The RTVI message, append-to-context, has been deprecated. Use send-text + or custom client and server messages instead. + """ + + role: Literal["user", "assistant"] | str + content: Any + run_immediately: bool = False + + +class AppendToContext(BaseModel): + """RTVI message format to append content to the LLM context. + + .. deprecated:: 0.0.85 + The RTVI message, append-to-context, has been deprecated. Use send-text + or custom client and server messages instead. + """ + + label: MessageLiteral = MESSAGE_LABEL + type: Literal["append-to-context"] = "append-to-context" + data: AppendToContextData + + +class LLMFunctionCallStartMessageData(BaseModel): + """Data for LLM function call start notification. + + Contains the function name being called. Fields may be omitted based on + the configured function_call_report_level for security. + """ + + function_name: Optional[str] = None + + +class LLMFunctionCallStartMessage(BaseModel): + """Message notifying that an LLM function call has started. + + Sent when the LLM begins a function call. + """ + + label: MessageLiteral = MESSAGE_LABEL + type: Literal["llm-function-call-started"] = "llm-function-call-started" + data: LLMFunctionCallStartMessageData + + +class LLMFunctionCallResultData(BaseModel): + """Data for LLM function call result. + + Contains function call details and result. + """ + + function_name: str + tool_call_id: str + arguments: dict + result: dict | str + + +class LLMFunctionCallInProgressMessageData(BaseModel): + """Data for LLM function call in-progress notification. + + Contains function call details including name, ID, and arguments. + Fields may be omitted based on the configured function_call_report_level for security. + """ + + tool_call_id: str + function_name: Optional[str] = None + arguments: Optional[Mapping[str, Any]] = None + + +class LLMFunctionCallInProgressMessage(BaseModel): + """Message notifying that an LLM function call is in progress. + + Sent when the LLM function call execution begins. + """ + + label: MessageLiteral = MESSAGE_LABEL + type: Literal["llm-function-call-in-progress"] = "llm-function-call-in-progress" + data: LLMFunctionCallInProgressMessageData + + +class LLMFunctionCallStoppedMessageData(BaseModel): + """Data for LLM function call stopped notification. + + Contains details about the function call that stopped, including + whether it was cancelled or completed with a result. + Fields may be omitted based on the configured function_call_report_level for security. + """ + + tool_call_id: str + cancelled: bool + function_name: Optional[str] = None + result: Optional[Any] = None + + +class LLMFunctionCallStoppedMessage(BaseModel): + """Message notifying that an LLM function call has stopped. + + Sent when a function call completes (with result) or is cancelled. + """ + + label: MessageLiteral = MESSAGE_LABEL + type: Literal["llm-function-call-stopped"] = "llm-function-call-stopped" + data: LLMFunctionCallStoppedMessageData + + +class BotLLMStartedMessage(BaseModel): + """Message indicating bot LLM processing has started.""" + + label: MessageLiteral = MESSAGE_LABEL + type: Literal["bot-llm-started"] = "bot-llm-started" + + +class BotLLMStoppedMessage(BaseModel): + """Message indicating bot LLM processing has stopped.""" + + label: MessageLiteral = MESSAGE_LABEL + type: Literal["bot-llm-stopped"] = "bot-llm-stopped" + + +class BotTTSStartedMessage(BaseModel): + """Message indicating bot TTS processing has started.""" + + label: MessageLiteral = MESSAGE_LABEL + type: Literal["bot-tts-started"] = "bot-tts-started" + + +class BotTTSStoppedMessage(BaseModel): + """Message indicating bot TTS processing has stopped.""" + + label: MessageLiteral = MESSAGE_LABEL + type: Literal["bot-tts-stopped"] = "bot-tts-stopped" + + +class TextMessageData(BaseModel): + """Data for text-based RTVI messages. + + Contains text content. + """ + + text: str + + +class BotOutputMessageData(TextMessageData): + """Data for bot output RTVI messages. + + Extends TextMessageData to include metadata about the output. + """ + + spoken: bool = False # Indicates if the text has been spoken by TTS + aggregated_by: AggregationType | str + # Indicates what form the text is in (e.g., by word, sentence, etc.) + + +class BotOutputMessage(BaseModel): + """Message containing bot output text. + + An event meant to holistically represent what the bot is outputting, + along with metadata about the output and if it has been spoken. + """ + + label: MessageLiteral = MESSAGE_LABEL + type: Literal["bot-output"] = "bot-output" + data: BotOutputMessageData + + +class BotTranscriptionMessage(BaseModel): + """Message containing bot transcription text. + + Sent when the bot's speech is transcribed. + """ + + label: MessageLiteral = MESSAGE_LABEL + type: Literal["bot-transcription"] = "bot-transcription" + data: TextMessageData + + +class BotLLMTextMessage(BaseModel): + """Message containing bot LLM text output. + + Sent when the bot's LLM generates text. + """ + + label: MessageLiteral = MESSAGE_LABEL + type: Literal["bot-llm-text"] = "bot-llm-text" + data: TextMessageData + + +class BotTTSTextMessage(BaseModel): + """Message containing bot TTS text output. + + Sent when text is being processed by TTS. + """ + + label: MessageLiteral = MESSAGE_LABEL + type: Literal["bot-tts-text"] = "bot-tts-text" + data: TextMessageData + + +class AudioMessageData(BaseModel): + """Data for audio-based RTVI messages. + + Contains audio data and metadata. + """ + + audio: str + sample_rate: int + num_channels: int + + +class BotTTSAudioMessage(BaseModel): + """Message containing bot TTS audio output. + + Sent when the bot's TTS generates audio. + """ + + label: MessageLiteral = MESSAGE_LABEL + type: Literal["bot-tts-audio"] = "bot-tts-audio" + data: AudioMessageData + + +class UserTranscriptionMessageData(BaseModel): + """Data for user transcription messages. + + Contains transcription text and metadata. + """ + + text: str + user_id: str + timestamp: str + final: bool + + +class UserTranscriptionMessage(BaseModel): + """Message containing user transcription. + + Sent when user speech is transcribed. + """ + + label: MessageLiteral = MESSAGE_LABEL + type: Literal["user-transcription"] = "user-transcription" + data: UserTranscriptionMessageData + + +class UserLLMTextMessage(BaseModel): + """Message containing user text input for LLM. + + Sent when user text is processed by the LLM. + """ + + label: MessageLiteral = MESSAGE_LABEL + type: Literal["user-llm-text"] = "user-llm-text" + data: TextMessageData + + +class UserStartedSpeakingMessage(BaseModel): + """Message indicating user has started speaking.""" + + label: MessageLiteral = MESSAGE_LABEL + type: Literal["user-started-speaking"] = "user-started-speaking" + + +class UserStoppedSpeakingMessage(BaseModel): + """Message indicating user has stopped speaking.""" + + label: MessageLiteral = MESSAGE_LABEL + type: Literal["user-stopped-speaking"] = "user-stopped-speaking" + + +class UserMuteStartedMessage(BaseModel): + """Message indicating user has been muted.""" + + label: MessageLiteral = MESSAGE_LABEL + type: Literal["user-mute-started"] = "user-mute-started" + + +class UserMuteStoppedMessage(BaseModel): + """Message indicating user has been unmuted.""" + + label: MessageLiteral = MESSAGE_LABEL + type: Literal["user-mute-stopped"] = "user-mute-stopped" + + +class BotStartedSpeakingMessage(BaseModel): + """Message indicating bot has started speaking.""" + + label: MessageLiteral = MESSAGE_LABEL + type: Literal["bot-started-speaking"] = "bot-started-speaking" + + +class BotStoppedSpeakingMessage(BaseModel): + """Message indicating bot has stopped speaking.""" + + label: MessageLiteral = MESSAGE_LABEL + type: Literal["bot-stopped-speaking"] = "bot-stopped-speaking" + + +class MetricsMessage(BaseModel): + """Message containing performance metrics. + + Sent to provide performance and usage metrics. + """ + + label: MessageLiteral = MESSAGE_LABEL + type: Literal["metrics"] = "metrics" + data: Mapping[str, Any] + + +class ServerMessage(BaseModel): + """Generic server message. + + Used for custom server-to-client messages. + """ + + label: MessageLiteral = MESSAGE_LABEL + type: Literal["server-message"] = "server-message" + data: Any + + +class AudioLevelMessageData(BaseModel): + """Data format for sending audio levels.""" + + value: float + + +class UserAudioLevelMessage(BaseModel): + """Message indicating user audio level.""" + + label: MessageLiteral = MESSAGE_LABEL + type: Literal["user-audio-level"] = "user-audio-level" + data: AudioLevelMessageData + + +class BotAudioLevelMessage(BaseModel): + """Message indicating bot audio level.""" + + label: MessageLiteral = MESSAGE_LABEL + type: Literal["bot-audio-level"] = "bot-audio-level" + data: AudioLevelMessageData + + +class SystemLogMessage(BaseModel): + """Message including a system log.""" + + label: MessageLiteral = MESSAGE_LABEL + type: Literal["system-log"] = "system-log" + data: TextMessageData diff --git a/src/pipecat/processors/frameworks/rtvi/observer.py b/src/pipecat/processors/frameworks/rtvi/observer.py new file mode 100644 index 000000000..83837ad6e --- /dev/null +++ b/src/pipecat/processors/frameworks/rtvi/observer.py @@ -0,0 +1,664 @@ +# +# Copyright (c) 2024-2026, Daily +# +# SPDX-License-Identifier: BSD 2-Clause License +# + +"""RTVI observer for converting pipeline frames to outgoing RTVI messages.""" + +import time +from dataclasses import dataclass, field +from enum import Enum +from typing import ( + TYPE_CHECKING, + Awaitable, + Callable, + Dict, + List, + Optional, + Set, + Tuple, +) + +from loguru import logger +from pydantic import BaseModel + +import pipecat.processors.frameworks.rtvi.models_v1 as RTVI +from pipecat.audio.utils import calculate_audio_volume +from pipecat.frames.frames import ( + AggregatedTextFrame, + AggregationType, + BotStartedSpeakingFrame, + BotStoppedSpeakingFrame, + Frame, + FunctionCallCancelFrame, + FunctionCallInProgressFrame, + FunctionCallResultFrame, + FunctionCallsStartedFrame, + InputAudioRawFrame, + InterimTranscriptionFrame, + LLMContextFrame, + LLMFullResponseEndFrame, + LLMFullResponseStartFrame, + LLMTextFrame, + MetricsFrame, + TranscriptionFrame, + TTSAudioRawFrame, + TTSStartedFrame, + TTSStoppedFrame, + TTSTextFrame, + UserMuteStartedFrame, + UserMuteStoppedFrame, + UserStartedSpeakingFrame, + UserStoppedSpeakingFrame, +) +from pipecat.metrics.metrics import ( + LLMUsageMetricsData, + ProcessingMetricsData, + TTFBMetricsData, + TTSUsageMetricsData, +) +from pipecat.observers.base_observer import BaseObserver, FramePushed +from pipecat.processors.aggregators.openai_llm_context import OpenAILLMContextFrame +from pipecat.processors.frame_processor import FrameDirection, FrameProcessor +from pipecat.processors.frameworks.rtvi.frames import ( + RTVIServerMessageFrame, + RTVIServerResponseFrame, +) +from pipecat.transports.base_output import BaseOutputTransport +from pipecat.utils.string import match_endofsentence + +if TYPE_CHECKING: + from pipecat.processors.frameworks.rtvi.processor import RTVIProcessor + + +class RTVIFunctionCallReportLevel(str, Enum): + """Level of detail to include in function call RTVI events. + + Controls what information is exposed in function call events for security. + + Values: + DISABLED: No events emitted for this function call. + NONE: Events only with tool_call_id, no function name or metadata (most secure). + NAME: Events with function name, no arguments or results. + FULL: Events with function name, arguments, and results. + """ + + DISABLED = "disabled" + NONE = "none" + NAME = "name" + FULL = "full" + + +@dataclass +class RTVIObserverParams: + """Parameters for configuring RTVI Observer behavior. + + .. deprecated:: 0.0.87 + Parameter `errors_enabled` is deprecated. Error messages are always enabled. + + Parameters: + bot_output_enabled: Indicates if bot output messages should be sent. + bot_llm_enabled: Indicates if the bot's LLM messages should be sent. + bot_tts_enabled: Indicates if the bot's TTS messages should be sent. + bot_speaking_enabled: Indicates if the bot's started/stopped speaking messages should be sent. + bot_audio_level_enabled: Indicates if bot's audio level messages should be sent. + user_llm_enabled: Indicates if the user's LLM input messages should be sent. + user_speaking_enabled: Indicates if the user's started/stopped speaking messages should be sent. + user_transcription_enabled: Indicates if user's transcription messages should be sent. + user_audio_level_enabled: Indicates if user's audio level messages should be sent. + metrics_enabled: Indicates if metrics messages should be sent. + system_logs_enabled: Indicates if system logs should be sent. + errors_enabled: [Deprecated] Indicates if errors messages should be sent. + ignored_sources: List of frame processors whose frames should be silently ignored + by this observer. Useful for suppressing RTVI messages from secondary pipeline + branches (e.g. a silent evaluation LLM) that should not be visible to clients. + Sources can also be added and removed dynamically via ``add_ignored_source()`` + and ``remove_ignored_source()``. + skip_aggregator_types: List of aggregation types to skip sending as tts/output messages. + Note: if using this to avoid sending secure information, be sure to also disable + bot_llm_enabled to avoid leaking through LLM messages. + bot_output_transforms: A list of callables to transform text before just before sending it + to TTS. Each callable takes the aggregated text and its type, and returns the + transformed text. To register, provide a list of tuples of + (aggregation_type | '*', transform_function). + audio_level_period_secs: How often audio levels should be sent if enabled. + function_call_report_level: Controls what information is exposed in function call + events for security. A dict mapping function names to levels, where ``"*"`` + sets the default level for unlisted functions:: + + function_call_report_level={ + "*": RTVIFunctionCallReportLevel.NONE, # Default: events with no metadata + "get_weather": RTVIFunctionCallReportLevel.FULL, # Expose everything + } + + Levels: + - DISABLED: No events emitted for this function. + - NONE: Events with tool_call_id only (most secure when events needed). + - NAME: Adds function name to events. + - FULL: Adds function name, arguments, and results. + + Defaults to ``{"*": RTVIFunctionCallReportLevel.NONE}``. + """ + + bot_output_enabled: bool = True + bot_llm_enabled: bool = True + bot_tts_enabled: bool = True + bot_speaking_enabled: bool = True + bot_audio_level_enabled: bool = False + user_llm_enabled: bool = True + user_speaking_enabled: bool = True + user_mute_enabled: bool = True + user_transcription_enabled: bool = True + user_audio_level_enabled: bool = False + metrics_enabled: bool = True + system_logs_enabled: bool = False + errors_enabled: Optional[bool] = None + ignored_sources: List[FrameProcessor] = field(default_factory=list) + skip_aggregator_types: Optional[List[AggregationType | str]] = None + bot_output_transforms: Optional[ + List[ + Tuple[ + AggregationType | str, + Callable[[str, AggregationType | str], Awaitable[str]], + ] + ] + ] = None + audio_level_period_secs: float = 0.15 + function_call_report_level: Dict[str, RTVIFunctionCallReportLevel] = field( + default_factory=lambda: {"*": RTVIFunctionCallReportLevel.NONE} + ) + + +class RTVIObserver(BaseObserver): + """Pipeline frame observer for RTVI server message handling. + + This observer monitors pipeline frames and converts them into appropriate RTVI messages + for client communication. It handles various frame types including speech events, + transcriptions, LLM responses, and TTS events. + + Note: + This observer only handles outgoing messages. Incoming RTVI client messages + are handled by the RTVIProcessor. + """ + + def __init__( + self, + rtvi: Optional["RTVIProcessor"] = None, + *, + params: Optional[RTVIObserverParams] = None, + **kwargs, + ): + """Initialize the RTVI observer. + + Args: + rtvi: The RTVI processor to push frames to. + params: Settings to enable/disable specific messages. + **kwargs: Additional arguments passed to parent class. + """ + super().__init__(**kwargs) + self._rtvi = rtvi + self._params = params or RTVIObserverParams() + + self._ignored_sources: Set[FrameProcessor] = set(self._params.ignored_sources) + self._frames_seen = set() + + self._bot_transcription = "" + self._last_user_audio_level = 0 + self._last_bot_audio_level = 0 + + # Track bot speaking state for queuing aggregated text frames + self._bot_is_speaking = False + self._queued_aggregated_text_frames: List[AggregatedTextFrame] = [] + + if self._params.system_logs_enabled: + self._system_logger_id = logger.add(self._logger_sink) + + if self._params.errors_enabled is not None: + import warnings + + with warnings.catch_warnings(): + warnings.simplefilter("always") + warnings.warn( + "Parameter `errors_enabled` is deprecated. Error messages are always enabled.", + DeprecationWarning, + ) + + self._aggregation_transforms: List[ + Tuple[AggregationType | str, Callable[[str, AggregationType | str], Awaitable[str]]] + ] = self._params.bot_output_transforms or [] + + def add_bot_output_transformer( + self, + transform_function: Callable[[str, AggregationType | str], Awaitable[str]], + aggregation_type: AggregationType | str = "*", + ): + """Transform text for a specific aggregation type before sending as Bot Output or TTS. + + Args: + transform_function: The function to apply for transformation. This function should take + the text and aggregation type as input and return the transformed text. + Ex.: async def my_transform(text: str, aggregation_type: str) -> str: + aggregation_type: The type of aggregation to transform. This value defaults to "*" to + handle all text before sending to the client. + """ + self._aggregation_transforms.append((aggregation_type, transform_function)) + + def remove_bot_output_transformer( + self, + transform_function: Callable[[str, AggregationType | str], Awaitable[str]], + aggregation_type: AggregationType | str = "*", + ): + """Remove a text transformer for a specific aggregation type. + + Args: + transform_function: The function to remove. + aggregation_type: The type of aggregation to remove the transformer for. + """ + self._aggregation_transforms = [ + (agg_type, func) + for agg_type, func in self._aggregation_transforms + if not (agg_type == aggregation_type and func == transform_function) + ] + + def add_ignored_source(self, source: FrameProcessor): + """Ignore all frames pushed by the given processor. + + Any frame whose source matches ``source`` will be silently skipped, + preventing RTVI messages from being emitted for activity in that + processor. Useful for suppressing events from secondary pipeline + branches (e.g. a silent evaluation LLM) that should not be visible + to clients. + + Args: + source: The frame processor to ignore. + """ + self._ignored_sources.add(source) + + def remove_ignored_source(self, source: FrameProcessor): + """Stop ignoring frames pushed by the given processor. + + Reverses a previous call to ``add_ignored_source()``. If ``source`` + was not previously ignored this is a no-op. + + Args: + source: The frame processor to stop ignoring. + """ + self._ignored_sources.discard(source) + + def _get_function_call_report_level(self, function_name: str) -> RTVIFunctionCallReportLevel: + """Get the report level for a specific function call. + + Args: + function_name: The name of the function to get the report level for. + + Returns: + The report level for the function. Looks up the function name first, + then falls back to "*" key, then NONE. + """ + levels = self._params.function_call_report_level + if function_name in levels: + return levels[function_name] + return levels.get("*", RTVIFunctionCallReportLevel.NONE) + + async def _logger_sink(self, message): + """Logger sink so we can send system logs to RTVI clients.""" + message = RTVI.SystemLogMessage(data=RTVI.TextMessageData(text=message)) + await self.send_rtvi_message(message) + + async def cleanup(self): + """Cleanup RTVI observer resources.""" + await super().cleanup() + if self._params.system_logs_enabled: + logger.remove(self._system_logger_id) + + async def send_rtvi_message(self, model: BaseModel, exclude_none: bool = True): + """Send an RTVI message. + + By default, we push a transport frame. But this function can be + overriden by subclass to send RTVI messages in different ways. + + Args: + model: The message to send. + exclude_none: Whether to exclude None values from the model dump. + + """ + if self._rtvi: + await self._rtvi.push_transport_message(model, exclude_none) + + async def on_push_frame(self, data: FramePushed): + """Process a frame being pushed through the pipeline. + + Args: + data: Frame push event data containing source, frame, direction, and timestamp. + """ + src = data.source + frame = data.frame + direction = data.direction + + # Frames from explicitly ignored sources are always skipped. + if self._ignored_sources and src in self._ignored_sources: + return + + # For broadcast frames (pushed in both directions), only process + # the downstream copy to avoid sending duplicate RTVI messages. + if frame.broadcast_sibling_id is not None and direction != FrameDirection.DOWNSTREAM: + return + + # If we have already seen this frame, let's skip it. + if frame.id in self._frames_seen: + return + + # This tells whether the frame is already processed. If false, we will try + # again the next time we see the frame. + mark_as_seen = True + + if ( + isinstance(frame, (UserStartedSpeakingFrame, UserStoppedSpeakingFrame)) + and self._params.user_speaking_enabled + ): + await self._handle_interruptions(frame) + elif ( + isinstance(frame, (UserMuteStartedFrame, UserMuteStoppedFrame)) + and self._params.user_mute_enabled + ): + await self._handle_user_mute(frame) + elif ( + isinstance(frame, (BotStartedSpeakingFrame, BotStoppedSpeakingFrame)) + and self._params.bot_speaking_enabled + ): + await self._handle_bot_speaking(frame) + elif ( + isinstance(frame, (TranscriptionFrame, InterimTranscriptionFrame)) + and self._params.user_transcription_enabled + ): + await self._handle_user_transcriptions(frame) + elif ( + isinstance(frame, (OpenAILLMContextFrame, LLMContextFrame)) + and self._params.user_llm_enabled + ): + await self._handle_context(frame) + elif isinstance(frame, LLMFullResponseStartFrame) and self._params.bot_llm_enabled: + await self.send_rtvi_message(RTVI.BotLLMStartedMessage()) + elif isinstance(frame, LLMFullResponseEndFrame) and self._params.bot_llm_enabled: + await self.send_rtvi_message(RTVI.BotLLMStoppedMessage()) + elif isinstance(frame, LLMTextFrame) and self._params.bot_llm_enabled: + await self._handle_llm_text_frame(frame) + elif isinstance(frame, TTSStartedFrame) and self._params.bot_tts_enabled: + await self.send_rtvi_message(RTVI.BotTTSStartedMessage()) + elif isinstance(frame, TTSStoppedFrame) and self._params.bot_tts_enabled: + await self.send_rtvi_message(RTVI.BotTTSStoppedMessage()) + elif isinstance(frame, AggregatedTextFrame) and ( + self._params.bot_output_enabled or self._params.bot_tts_enabled + ): + if isinstance(frame, TTSTextFrame) and not isinstance(src, BaseOutputTransport): + # This check is to make sure we handle the frame when it has gone + # through the transport and has correct timing. + mark_as_seen = False + else: + await self._handle_aggregated_llm_text(frame) + elif isinstance(frame, MetricsFrame) and self._params.metrics_enabled: + await self._handle_metrics(frame) + elif isinstance(frame, FunctionCallsStartedFrame): + for function_call in frame.function_calls: + report_level = self._get_function_call_report_level(function_call.function_name) + if report_level == RTVIFunctionCallReportLevel.DISABLED: + continue + data = RTVI.LLMFunctionCallStartMessageData() + if report_level in ( + RTVIFunctionCallReportLevel.NAME, + RTVIFunctionCallReportLevel.FULL, + ): + data.function_name = function_call.function_name + message = RTVI.LLMFunctionCallStartMessage(data=data) + await self.send_rtvi_message(message) + elif isinstance(frame, FunctionCallInProgressFrame): + report_level = self._get_function_call_report_level(frame.function_name) + if report_level != RTVIFunctionCallReportLevel.DISABLED: + data = RTVI.LLMFunctionCallInProgressMessageData(tool_call_id=frame.tool_call_id) + if report_level in ( + RTVIFunctionCallReportLevel.NAME, + RTVIFunctionCallReportLevel.FULL, + ): + data.function_name = frame.function_name + if report_level == RTVIFunctionCallReportLevel.FULL: + data.arguments = frame.arguments + message = RTVI.LLMFunctionCallInProgressMessage(data=data) + await self.send_rtvi_message(message) + elif isinstance(frame, FunctionCallCancelFrame): + report_level = self._get_function_call_report_level(frame.function_name) + if report_level != RTVIFunctionCallReportLevel.DISABLED: + data = RTVI.LLMFunctionCallStoppedMessageData( + tool_call_id=frame.tool_call_id, + cancelled=True, + ) + if report_level in ( + RTVIFunctionCallReportLevel.NAME, + RTVIFunctionCallReportLevel.FULL, + ): + data.function_name = frame.function_name + message = RTVI.LLMFunctionCallStoppedMessage(data=data) + await self.send_rtvi_message(message) + elif isinstance(frame, FunctionCallResultFrame): + report_level = self._get_function_call_report_level(frame.function_name) + if report_level != RTVIFunctionCallReportLevel.DISABLED: + data = RTVI.LLMFunctionCallStoppedMessageData( + tool_call_id=frame.tool_call_id, + cancelled=False, + ) + if report_level in ( + RTVIFunctionCallReportLevel.NAME, + RTVIFunctionCallReportLevel.FULL, + ): + data.function_name = frame.function_name + if report_level == RTVIFunctionCallReportLevel.FULL: + data.result = frame.result if frame.result else None + message = RTVI.LLMFunctionCallStoppedMessage(data=data) + await self.send_rtvi_message(message) + elif isinstance(frame, RTVIServerMessageFrame): + message = RTVI.ServerMessage(data=frame.data) + await self.send_rtvi_message(message) + elif isinstance(frame, RTVIServerResponseFrame): + if frame.error is not None: + await self._send_error_response(frame) + else: + await self._send_server_response(frame) + elif isinstance(frame, InputAudioRawFrame) and self._params.user_audio_level_enabled: + curr_time = time.time() + diff_time = curr_time - self._last_user_audio_level + if diff_time > self._params.audio_level_period_secs: + level = calculate_audio_volume(frame.audio, frame.sample_rate) + message = RTVI.UserAudioLevelMessage(data=RTVI.AudioLevelMessageData(value=level)) + await self.send_rtvi_message(message) + self._last_user_audio_level = curr_time + elif isinstance(frame, TTSAudioRawFrame) and self._params.bot_audio_level_enabled: + curr_time = time.time() + diff_time = curr_time - self._last_bot_audio_level + if diff_time > self._params.audio_level_period_secs: + level = calculate_audio_volume(frame.audio, frame.sample_rate) + message = RTVI.BotAudioLevelMessage(data=RTVI.AudioLevelMessageData(value=level)) + await self.send_rtvi_message(message) + self._last_bot_audio_level = curr_time + + if mark_as_seen: + self._frames_seen.add(frame.id) + + async def _handle_interruptions(self, frame: Frame): + """Handle user speaking interruption frames.""" + message = None + if isinstance(frame, UserStartedSpeakingFrame): + message = RTVI.UserStartedSpeakingMessage() + elif isinstance(frame, UserStoppedSpeakingFrame): + message = RTVI.UserStoppedSpeakingMessage() + + if message: + await self.send_rtvi_message(message) + + async def _handle_user_mute(self, frame: Frame): + """Handle user mute/unmute frames.""" + message = None + if isinstance(frame, UserMuteStartedFrame): + message = RTVI.UserMuteStartedMessage() + elif isinstance(frame, UserMuteStoppedFrame): + message = RTVI.UserMuteStoppedMessage() + + if message: + await self.send_rtvi_message(message) + + async def _handle_bot_speaking(self, frame: Frame): + """Handle bot speaking event frames.""" + if isinstance(frame, BotStartedSpeakingFrame): + message = RTVI.BotStartedSpeakingMessage() + await self.send_rtvi_message(message) + # Flush any queued aggregated text frames + for queued_frame in self._queued_aggregated_text_frames: + await self._send_aggregated_llm_text(queued_frame) + self._queued_aggregated_text_frames.clear() + self._bot_is_speaking = True + elif isinstance(frame, BotStoppedSpeakingFrame): + message = RTVI.BotStoppedSpeakingMessage() + await self.send_rtvi_message(message) + self._bot_is_speaking = False + + async def _handle_aggregated_llm_text(self, frame: AggregatedTextFrame): + """Handle aggregated LLM text output frames.""" + if self._bot_is_speaking: + # Bot has already started speaking, send directly + await self._send_aggregated_llm_text(frame) + else: + # Bot hasn't started speaking yet, queue the frame + self._queued_aggregated_text_frames.append(frame) + + async def _send_aggregated_llm_text(self, frame: AggregatedTextFrame): + """Send aggregated LLM text messages.""" + # Skip certain aggregator types if configured to do so. + if ( + self._params.skip_aggregator_types + and frame.aggregated_by in self._params.skip_aggregator_types + ): + return + + text = frame.text + type = frame.aggregated_by + for aggregation_type, transform in self._aggregation_transforms: + if aggregation_type == type or aggregation_type == "*": + text = await transform(text, type) + + isTTS = isinstance(frame, TTSTextFrame) + if self._params.bot_output_enabled: + message = RTVI.BotOutputMessage( + data=RTVI.BotOutputMessageData(text=text, spoken=isTTS, aggregated_by=type) + ) + await self.send_rtvi_message(message) + + if isTTS and self._params.bot_tts_enabled: + tts_message = RTVI.BotTTSTextMessage(data=RTVI.TextMessageData(text=text)) + await self.send_rtvi_message(tts_message) + + async def _handle_llm_text_frame(self, frame: LLMTextFrame): + """Handle LLM text output frames.""" + message = RTVI.BotLLMTextMessage(data=RTVI.TextMessageData(text=frame.text)) + await self.send_rtvi_message(message) + + # TODO (mrkb): Remove all this logic when we fully deprecate bot-transcription messages. + self._bot_transcription += frame.text + + if match_endofsentence(self._bot_transcription) and len(self._bot_transcription) > 0: + await self.send_rtvi_message( + RTVI.BotTranscriptionMessage( + data=RTVI.TextMessageData(text=self._bot_transcription) + ) + ) + self._bot_transcription = "" + + async def _handle_user_transcriptions(self, frame: Frame): + """Handle user transcription frames.""" + message = None + if isinstance(frame, TranscriptionFrame): + message = RTVI.UserTranscriptionMessage( + data=RTVI.UserTranscriptionMessageData( + text=frame.text, user_id=frame.user_id, timestamp=frame.timestamp, final=True + ) + ) + elif isinstance(frame, InterimTranscriptionFrame): + message = RTVI.UserTranscriptionMessage( + data=RTVI.UserTranscriptionMessageData( + text=frame.text, user_id=frame.user_id, timestamp=frame.timestamp, final=False + ) + ) + + if message: + await self.send_rtvi_message(message) + + async def _handle_context(self, frame: OpenAILLMContextFrame | LLMContextFrame): + """Process LLM context frames to extract user messages for the RTVI client.""" + try: + if isinstance(frame, OpenAILLMContextFrame): + messages = frame.context.messages + else: + messages = frame.context.get_messages() + if not messages: + return + + message = messages[-1] + + # Handle Google LLM format (protobuf objects with attributes) + # Note: not possible if frame is a universal LLMContextFrame + if hasattr(message, "role") and message.role == "user" and hasattr(message, "parts"): + text = "".join(part.text for part in message.parts if hasattr(part, "text")) + if text: + rtvi_message = RTVI.UserLLMTextMessage(data=RTVI.TextMessageData(text=text)) + await self.send_rtvi_message(rtvi_message) + + # Handle OpenAI format (original implementation) + elif isinstance(message, dict): + if message["role"] == "user": + content = message["content"] + if isinstance(content, list): + text = " ".join(item["text"] for item in content if "text" in item) + else: + text = content + rtvi_message = RTVI.UserLLMTextMessage(data=RTVI.TextMessageData(text=text)) + await self.send_rtvi_message(rtvi_message) + + except Exception as e: + logger.warning(f"Caught an error while trying to handle context: {e}") + + async def _handle_metrics(self, frame: MetricsFrame): + """Handle metrics frames and convert to RTVI metrics messages.""" + metrics = {} + for d in frame.data: + if isinstance(d, TTFBMetricsData): + if "ttfb" not in metrics: + metrics["ttfb"] = [] + metrics["ttfb"].append(d.model_dump(exclude_none=True)) + elif isinstance(d, ProcessingMetricsData): + if "processing" not in metrics: + metrics["processing"] = [] + metrics["processing"].append(d.model_dump(exclude_none=True)) + elif isinstance(d, LLMUsageMetricsData): + if "tokens" not in metrics: + metrics["tokens"] = [] + metrics["tokens"].append(d.value.model_dump(exclude_none=True)) + elif isinstance(d, TTSUsageMetricsData): + if "characters" not in metrics: + metrics["characters"] = [] + metrics["characters"].append(d.model_dump(exclude_none=True)) + + message = RTVI.MetricsMessage(data=metrics) + await self.send_rtvi_message(message) + + async def _send_server_response(self, frame: RTVIServerResponseFrame): + """Send a response to the client for a specific request.""" + message = RTVI.ServerResponse( + id=str(frame.client_msg.msg_id), + data=RTVI.RawServerResponseData(t=frame.client_msg.type, d=frame.data), + ) + await self.send_rtvi_message(message) + + async def _send_error_response(self, frame: RTVIServerResponseFrame): + """Send a response to the client for a specific request.""" + message = RTVI.ErrorResponse( + id=str(frame.client_msg.msg_id), data=RTVI.ErrorResponseData(error=frame.error) + ) + await self.send_rtvi_message(message) diff --git a/src/pipecat/processors/frameworks/rtvi/processor.py b/src/pipecat/processors/frameworks/rtvi/processor.py new file mode 100644 index 000000000..345dcb8c4 --- /dev/null +++ b/src/pipecat/processors/frameworks/rtvi/processor.py @@ -0,0 +1,653 @@ +# +# Copyright (c) 2024-2026, Daily +# +# SPDX-License-Identifier: BSD 2-Clause License +# + +"""RTVIProcessor: main RTVI protocol processor.""" + +import asyncio +import base64 +from typing import Any, Dict, Mapping, Optional + +from loguru import logger +from pydantic import BaseModel, ValidationError + +import pipecat.processors.frameworks.rtvi.models_v1 as RTVI +from pipecat import version as pipecat_version +from pipecat.frames.frames import ( + CancelFrame, + EndFrame, + EndTaskFrame, + ErrorFrame, + Frame, + FunctionCallResultFrame, + InputAudioRawFrame, + InputTransportMessageFrame, + LLMConfigureOutputFrame, + LLMMessagesAppendFrame, + OutputTransportMessageUrgentFrame, + StartFrame, + SystemFrame, +) +from pipecat.processors.frame_processor import FrameDirection, FrameProcessor +from pipecat.processors.frameworks.rtvi.frames import RTVIActionFrame, RTVIClientMessageFrame +from pipecat.processors.frameworks.rtvi.models_v0 import ( + RTVIAction, + RTVIActionResponse, + RTVIActionResponseData, + RTVIActionRun, + RTVIBotReadyDataDeprecated, + RTVIConfig, + RTVIConfigResponse, + RTVIDescribeActions, + RTVIDescribeActionsData, + RTVIDescribeConfig, + RTVIDescribeConfigData, + RTVIService, + RTVIServiceConfig, + RTVIServiceOptionConfig, + RTVIUpdateConfig, +) +from pipecat.processors.frameworks.rtvi.observer import RTVIObserver, RTVIObserverParams +from pipecat.services.llm_service import ( + FunctionCallParams, # TODO(aleix): we shouldn't import `services` from `processors` +) +from pipecat.transports.base_input import BaseInputTransport +from pipecat.transports.base_transport import BaseTransport + + +class RTVIProcessor(FrameProcessor): + """Main processor for handling RTVI protocol messages and actions. + + This processor manages the RTVI protocol communication including client-server + handshaking, configuration management, action execution, and message routing. + It serves as the central hub for RTVI protocol operations. + """ + + def __init__( + self, + *, + config: Optional[RTVIConfig] = None, + transport: Optional[BaseTransport] = None, + **kwargs, + ): + """Initialize the RTVI processor. + + Args: + config: Initial RTVI configuration. + transport: Transport layer for communication. + **kwargs: Additional arguments passed to parent class. + """ + super().__init__(**kwargs) + self._config = config or RTVIConfig(config=[]) + + self._bot_ready = False + self._client_ready = False + self._client_ready_id = "" + # Default to 0.3.0 which is the last version before actually having a + # "client-version". + self._client_version = [0, 3, 0] + self._llm_skip_tts: bool = False # Keep in sync with llm_service.py's configuration. + + self._registered_actions: Dict[str, RTVIAction] = {} + self._registered_services: Dict[str, RTVIService] = {} + + # A task to process incoming action frames. + self._action_task: Optional[asyncio.Task] = None + + # A task to process incoming transport messages. + self._message_task: Optional[asyncio.Task] = None + + self._register_event_handler("on_bot_started") + self._register_event_handler("on_client_ready") + self._register_event_handler("on_client_message") + + self._input_transport = None + self._transport = transport + if self._transport: + input_transport = self._transport.input() + if isinstance(input_transport, BaseInputTransport): + self._input_transport = input_transport + self._input_transport.enable_audio_in_stream_on_start(False) + + def register_action(self, action: RTVIAction): + """Register an action that can be executed via RTVI. + + Args: + action: The action to register. + """ + import warnings + + with warnings.catch_warnings(): + warnings.simplefilter("always") + warnings.warn( + "The actions API is deprecated, use server and client messages instead.", + DeprecationWarning, + ) + + id = self._action_id(action.service, action.action) + self._registered_actions[id] = action + + def register_service(self, service: RTVIService): + """Register a service that can be configured via RTVI. + + Args: + service: The service to register. + """ + import warnings + + with warnings.catch_warnings(): + warnings.simplefilter("always") + warnings.warn( + "The actions API is deprecated, use server and client messages instead.", + DeprecationWarning, + ) + + self._registered_services[service.name] = service + + def create_rtvi_observer(self, *, params: Optional[RTVIObserverParams] = None, **kwargs): + """Creates a new RTVI Observer. + + Args: + params: Settings to enable/disable specific messages. + **kwargs: Additional arguments passed to the observer. + + Returns: + A new RTVI observer. + """ + return RTVIObserver(self, params=params, **kwargs) + + async def set_client_ready(self): + """Mark the client as ready and trigger the ready event.""" + self._client_ready = True + await self._call_event_handler("on_client_ready") + + async def set_bot_ready(self, about: Mapping[str, Any] = None): + """Mark the bot as ready and send the bot-ready message. + + Args: + about: Optional information about the bot to include in the ready message. + If left as None, the Pipecat library and version will be used. + """ + self._bot_ready = True + # Only call the (deprecated) _update_config method if the we're using a + # config (which is deprecated). Otherwise we'd always print an + # unnecessary deprecation warning. + if self._config.config: + await self._update_config(self._config, False) + await self._send_bot_ready(about=about) + + async def interrupt_bot(self): + """Send a bot interruption frame upstream.""" + await self.broadcast_interruption() + + async def send_server_message(self, data: Any): + """Send a server message to the client.""" + message = RTVI.ServerMessage(data=data) + await self._send_server_message(message) + + async def send_server_response(self, client_msg: RTVI.ClientMessage, data: Any): + """Send a server response for a given client message.""" + message = RTVI.ServerResponse( + id=client_msg.msg_id, data=RTVI.RawServerResponseData(t=client_msg.type, d=data) + ) + await self._send_server_message(message) + + async def send_error_response(self, client_msg: RTVI.ClientMessage, error: str): + """Send an error response for a given client message.""" + await self._send_error_response(id=client_msg.msg_id, error=error) + + async def send_error(self, error: str): + """Send an error message to the client. + + Args: + error: The error message to send. + """ + await self._send_error_frame(ErrorFrame(error=error)) + + async def push_transport_message(self, model: BaseModel, exclude_none: bool = True): + """Push a transport message frame.""" + frame = OutputTransportMessageUrgentFrame( + message=model.model_dump(exclude_none=exclude_none) + ) + await self.push_frame(frame) + + async def handle_message(self, message: RTVI.Message): + """Handle an incoming RTVI message. + + Args: + message: The RTVI message to handle. + """ + await self._message_queue.put(message) + + async def handle_function_call(self, params: FunctionCallParams): + """Handle a function call from the LLM. + + Args: + params: The function call parameters. + + .. deprecated:: 0.0.102 + This method is deprecated. Function call events are now automatically + sent by ``RTVIObserver`` using the ``llm-function-call-in-progress`` event. + Configure reporting level via ``RTVIObserverParams.function_call_report_level``. + """ + import warnings + + warnings.warn( + "handle_function_call is deprecated. Function call events are now " + "automatically sent by RTVIObserver using llm-function-call-in-progress.", + DeprecationWarning, + stacklevel=2, + ) + fn = RTVI.LLMFunctionCallMessageData( + function_name=params.function_name, + tool_call_id=params.tool_call_id, + args=params.arguments, + ) + message = RTVI.LLMFunctionCallMessage(data=fn) + await self.push_transport_message(message, exclude_none=False) + + async def process_frame(self, frame: Frame, direction: FrameDirection): + """Process incoming frames through the RTVI processor. + + Args: + frame: The frame to process. + direction: The direction of frame flow. + """ + await super().process_frame(frame, direction) + + # Specific system frames + if isinstance(frame, StartFrame): + # Push StartFrame before start(), because we want StartFrame to be + # processed by every processor before any other frame is processed. + await self.push_frame(frame, direction) + await self._start(frame) + elif isinstance(frame, CancelFrame): + await self._cancel(frame) + await self.push_frame(frame, direction) + elif isinstance(frame, ErrorFrame): + await self._send_error_frame(frame) + await self.push_frame(frame, direction) + elif isinstance(frame, InputTransportMessageFrame): + await self._handle_transport_message(frame) + # All other system frames + elif isinstance(frame, SystemFrame): + await self.push_frame(frame, direction) + # Control frames + elif isinstance(frame, EndFrame): + # Push EndFrame before stop(), because stop() waits on the task to + # finish and the task finishes when EndFrame is processed. + await self.push_frame(frame, direction) + await self._stop(frame) + # Data frames + elif isinstance(frame, RTVIActionFrame): + await self._action_queue.put(frame) + elif isinstance(frame, LLMConfigureOutputFrame): + self._llm_skip_tts = frame.skip_tts + await self.push_frame(frame, direction) + # Other frames + else: + await self.push_frame(frame, direction) + + async def _start(self, frame: StartFrame): + """Start the RTVI processor tasks.""" + if not self._action_task: + self._action_queue = asyncio.Queue() + self._action_task = self.create_task(self._action_task_handler()) + if not self._message_task: + self._message_queue = asyncio.Queue() + self._message_task = self.create_task(self._message_task_handler()) + await self._call_event_handler("on_bot_started") + + async def _stop(self, frame: EndFrame): + """Stop the RTVI processor tasks.""" + await self._cancel_tasks() + + async def _cancel(self, frame: CancelFrame): + """Cancel the RTVI processor tasks.""" + await self._cancel_tasks() + + async def _cancel_tasks(self): + """Cancel all running tasks.""" + if self._action_task: + await self.cancel_task(self._action_task) + self._action_task = None + + if self._message_task: + await self.cancel_task(self._message_task) + self._message_task = None + + async def _action_task_handler(self): + """Handle incoming action frames.""" + while True: + frame = await self._action_queue.get() + await self._handle_action(frame.message_id, frame.rtvi_action_run) + self._action_queue.task_done() + + async def _message_task_handler(self): + """Handle incoming transport messages.""" + while True: + message = await self._message_queue.get() + await self._handle_message(message) + self._message_queue.task_done() + + async def _handle_transport_message(self, frame: InputTransportMessageFrame): + """Handle an incoming transport message frame.""" + try: + transport_message = frame.message + if transport_message.get("label") != RTVI.MESSAGE_LABEL: + logger.warning(f"Ignoring not RTVI message: {transport_message}") + return + message = RTVI.Message.model_validate(transport_message) + await self._message_queue.put(message) + except ValidationError as e: + await self.send_error(f"Invalid RTVI transport message: {e}") + logger.warning(f"Invalid RTVI transport message: {e}") + + async def _handle_message(self, message: RTVI.Message): + """Handle a parsed RTVI message.""" + try: + match message.type: + case "client-ready": + data = None + try: + data = RTVI.ClientReadyData.model_validate(message.data) + except ValidationError: + # Not all clients have been updated to RTVI 1.0.0. + # For now, that's okay, we just log their info as unknown. + data = None + pass + await self._handle_client_ready(message.id, data) + case "describe-actions": + await self._handle_describe_actions(message.id) + case "describe-config": + await self._handle_describe_config(message.id) + case "get-config": + await self._handle_get_config(message.id) + case "update-config": + update_config = RTVIUpdateConfig.model_validate(message.data) + await self._handle_update_config(message.id, update_config) + case "disconnect-bot": + await self.push_frame(EndTaskFrame(), FrameDirection.UPSTREAM) + case "client-message": + data = RTVI.RawClientMessageData.model_validate(message.data) + await self._handle_client_message(message.id, data) + case "action": + action = RTVIActionRun.model_validate(message.data) + action_frame = RTVIActionFrame(message_id=message.id, rtvi_action_run=action) + await self._action_queue.put(action_frame) + case "llm-function-call-result": + data = RTVI.LLMFunctionCallResultData.model_validate(message.data) + await self._handle_function_call_result(data) + case "send-text": + data = RTVI.SendTextData.model_validate(message.data) + await self._handle_send_text(data) + case "append-to-context": + logger.warning( + f"The append-to-context message is deprecated, use send-text instead." + ) + data = RTVI.AppendToContextData.model_validate(message.data) + await self._handle_update_context(data) + case "raw-audio" | "raw-audio-batch": + await self._handle_audio_buffer(message.data) + + case _: + await self._send_error_response(message.id, f"Unsupported type {message.type}") + + except ValidationError as e: + await self._send_error_response(message.id, f"Invalid message: {e}") + logger.warning(f"Invalid message: {e}") + except Exception as e: + await self._send_error_response(message.id, f"Exception processing message: {e}") + logger.warning(f"Exception processing message: {e}") + + async def _handle_client_ready(self, request_id: str, data: RTVI.ClientReadyData | None): + """Handle the client-ready message from the client.""" + version = data.version if data else None + logger.debug(f"Received client-ready: version {version}") + if version: + try: + self._client_version = [int(v) for v in version.split(".")] + except ValueError: + logger.warning(f"Invalid client version format: {version}") + about = data.about if data else {"library": "unknown"} + logger.debug(f"Client Details: {about}") + if self._input_transport: + await self._input_transport.start_audio_in_streaming() + + self._client_ready_id = request_id + await self.set_client_ready() + + async def _handle_audio_buffer(self, data): + """Handle incoming audio buffer data.""" + if not self._input_transport: + return + + # Extract audio batch ensuring it's a list + audio_list = data.get("base64AudioBatch") or [data.get("base64Audio")] + + try: + for base64_audio in filter(None, audio_list): # Filter out None values + pcm_bytes = base64.b64decode(base64_audio) + frame = InputAudioRawFrame( + audio=pcm_bytes, + sample_rate=data["sampleRate"], + num_channels=data["numChannels"], + ) + await self._input_transport.push_audio_frame(frame) + + except (KeyError, TypeError, ValueError) as e: + # Handle missing keys, decoding errors, and invalid types + logger.error(f"Error processing audio buffer: {e}") + + async def _handle_describe_config(self, request_id: str): + """Handle a describe-config request.""" + import warnings + + with warnings.catch_warnings(): + warnings.simplefilter("always") + warnings.warn( + "Configuration helpers are deprecated. If your application needs this behavior, use custom server and client messages.", + DeprecationWarning, + ) + + services = list(self._registered_services.values()) + message = RTVIDescribeConfig(id=request_id, data=RTVIDescribeConfigData(config=services)) + await self.push_transport_message(message) + + async def _handle_describe_actions(self, request_id: str): + """Handle a describe-actions request.""" + import warnings + + with warnings.catch_warnings(): + warnings.simplefilter("always") + warnings.warn( + "The Actions API is deprecated, use custom server and client messages instead.", + DeprecationWarning, + ) + + actions = list(self._registered_actions.values()) + message = RTVIDescribeActions(id=request_id, data=RTVIDescribeActionsData(actions=actions)) + await self.push_transport_message(message) + + async def _handle_get_config(self, request_id: str): + """Handle a get-config request.""" + import warnings + + with warnings.catch_warnings(): + warnings.simplefilter("always") + warnings.warn( + "Configuration helpers are deprecated. If your application needs this behavior, use custom server and client messages.", + DeprecationWarning, + ) + + message = RTVIConfigResponse(id=request_id, data=self._config) + await self.push_transport_message(message) + + def _update_config_option(self, service: str, config: RTVIServiceOptionConfig): + """Update a specific configuration option.""" + for service_config in self._config.config: + if service_config.service == service: + for option_config in service_config.options: + if option_config.name == config.name: + option_config.value = config.value + return + # If we couldn't find a value for this config, we simply need to + # add it. + service_config.options.append(config) + + async def _update_service_config(self, config: RTVIServiceConfig): + """Update configuration for a specific service.""" + import warnings + + with warnings.catch_warnings(): + warnings.simplefilter("always") + warnings.warn( + "Configuration helpers are deprecated. If your application needs this behavior, use custom server and client messages.", + DeprecationWarning, + ) + + service = self._registered_services[config.service] + for option in config.options: + handler = service._options_dict[option.name].handler + await handler(self, service.name, option) + self._update_config_option(service.name, option) + + async def _update_config(self, data: RTVIConfig, interrupt: bool): + """Update the RTVI configuration.""" + import warnings + + with warnings.catch_warnings(): + warnings.simplefilter("always") + warnings.warn( + "Configuration helpers are deprecated. If your application needs this behavior, use custom server and client messages.", + DeprecationWarning, + ) + + if interrupt: + await self.interrupt_bot() + for service_config in data.config: + await self._update_service_config(service_config) + + async def _handle_update_config(self, request_id: str, data: RTVIUpdateConfig): + """Handle an update-config request.""" + await self._update_config(RTVIConfig(config=data.config), data.interrupt) + await self._handle_get_config(request_id) + + async def _handle_send_text(self, data: RTVI.SendTextData): + """Handle a send-text message from the client.""" + opts = data.options if data.options is not None else RTVI.SendTextOptions() + if opts.run_immediately: + await self.interrupt_bot() + cur_llm_skip_tts = self._llm_skip_tts + should_skip_tts = not opts.audio_response + toggle_skip_tts = cur_llm_skip_tts != should_skip_tts + if toggle_skip_tts: + output_frame = LLMConfigureOutputFrame(skip_tts=should_skip_tts) + await self.push_frame(output_frame) + text_frame = LLMMessagesAppendFrame( + messages=[{"role": "user", "content": data.content}], + run_llm=opts.run_immediately, + ) + await self.push_frame(text_frame) + if toggle_skip_tts: + output_frame = LLMConfigureOutputFrame(skip_tts=cur_llm_skip_tts) + await self.push_frame(output_frame) + + async def _handle_update_context(self, data: RTVI.AppendToContextData): + if data.run_immediately: + await self.interrupt_bot() + frame = LLMMessagesAppendFrame( + messages=[{"role": data.role, "content": data.content}], + run_llm=data.run_immediately, + ) + await self.push_frame(frame) + + async def _handle_client_message(self, msg_id: str, data: RTVI.RawClientMessageData): + """Handle a client message frame.""" + if not data: + await self._send_error_response(msg_id, "Malformed client message") + return + + # Create a RTVIClientMessageFrame to push the message + frame = RTVIClientMessageFrame(msg_id=msg_id, type=data.t, data=data.d) + await self.push_frame(frame) + await self._call_event_handler( + "on_client_message", + RTVI.ClientMessage( + msg_id=msg_id, + type=data.t, + data=data.d, + ), + ) + + async def _handle_function_call_result(self, data): + """Handle a function call result from the client.""" + frame = FunctionCallResultFrame( + function_name=data.function_name, + tool_call_id=data.tool_call_id, + arguments=data.arguments, + result=data.result, + ) + await self.push_frame(frame) + + async def _handle_action(self, request_id: Optional[str], data: RTVIActionRun): + """Handle an action execution request.""" + action_id = self._action_id(data.service, data.action) + if action_id not in self._registered_actions: + await self._send_error_response(request_id, f"Action {action_id} not registered") + return + action = self._registered_actions[action_id] + arguments = {} + if data.arguments: + for arg in data.arguments: + arguments[arg.name] = arg.value + result = await action.handler(self, action.service, arguments) + # Only send a response if request_id is present. Things that don't care about + # action responses (such as webhooks) don't set a request_id + if request_id: + message = RTVIActionResponse(id=request_id, data=RTVIActionResponseData(result=result)) + await self.push_transport_message(message) + + async def _send_bot_ready(self, about: Mapping[str, Any] = None): + """Send the bot-ready message to the client. + + Args: + about: Optional information about the bot to include in the ready message. + If left as None, the pipecat library and version will be used. + """ + if not about: + about = {"library": "pipecat-ai", "library_version": f"{pipecat_version()}"} + if self._client_version and self._client_version[0] < 1: + config = self._config.config + message = RTVI.BotReady( + id=self._client_ready_id, + data=RTVIBotReadyDataDeprecated( + version=RTVI.PROTOCOL_VERSION, about=about, config=config + ), + ) + else: + message = RTVI.BotReady( + id=self._client_ready_id, + data=RTVI.BotReadyData(version=RTVI.PROTOCOL_VERSION, about=about), + ) + await self.push_transport_message(message) + + async def _send_server_message(self, message: RTVI.ServerMessage | RTVI.ServerResponse): + """Send a message or response to the client.""" + await self.push_transport_message(message) + + async def _send_error_frame(self, frame: ErrorFrame): + """Send an error frame as an RTVI error message.""" + message = RTVI.Error(data=RTVI.ErrorData(error=frame.error, fatal=frame.fatal)) + await self.push_transport_message(message) + + async def _send_error_response(self, id: str, error: str): + """Send an error response message.""" + message = RTVI.ErrorResponse(id=id, data=RTVI.ErrorResponseData(error=error)) + await self.push_transport_message(message) + + def _action_id(self, service: str, action: str) -> str: + """Generate an action ID from service and action names.""" + return f"{service}:{action}" diff --git a/src/pipecat/serializers/base_serializer.py b/src/pipecat/serializers/base_serializer.py index edf005a81..4807f8606 100644 --- a/src/pipecat/serializers/base_serializer.py +++ b/src/pipecat/serializers/base_serializer.py @@ -11,13 +11,13 @@ from typing import Optional from pydantic import BaseModel +import pipecat.processors.frameworks.rtvi.models_v1 as RTVI from pipecat.frames.frames import ( Frame, OutputTransportMessageFrame, OutputTransportMessageUrgentFrame, StartFrame, ) -from pipecat.processors.frameworks.rtvi import RTVI_MESSAGE_LABEL from pipecat.utils.base_object import BaseObject @@ -64,7 +64,7 @@ class FrameSerializer(BaseObject): if ( self._params.ignore_rtvi_messages and isinstance(frame, (OutputTransportMessageFrame, OutputTransportMessageUrgentFrame)) - and frame.message.get("label") == RTVI_MESSAGE_LABEL + and frame.message.get("label") == RTVI.MESSAGE_LABEL ): return True return False From 49fba5209c1bfa1938ba99648933dcdc21f10304 Mon Sep 17 00:00:00 2001 From: mattie ruth backman Date: Wed, 4 Mar 2026 14:15:25 -0500 Subject: [PATCH 0826/1060] copilot feedback --- src/pipecat/processors/frameworks/rtvi/frames.py | 2 +- src/pipecat/processors/frameworks/rtvi/models_v0.py | 4 ++++ src/pipecat/processors/frameworks/rtvi/observer.py | 10 +++++----- src/pipecat/processors/frameworks/rtvi/processor.py | 4 ---- 4 files changed, 10 insertions(+), 10 deletions(-) diff --git a/src/pipecat/processors/frameworks/rtvi/frames.py b/src/pipecat/processors/frameworks/rtvi/frames.py index 37d25c764..6a771f7e4 100644 --- a/src/pipecat/processors/frameworks/rtvi/frames.py +++ b/src/pipecat/processors/frameworks/rtvi/frames.py @@ -65,7 +65,7 @@ class RTVIServerResponseFrame(SystemFrame): and include the original RTVIClientMessageFrame to ensure the response is properly attributed to the original request. To respond with an error, set the `error` field to a string describing the error. This will result - in the client receiving a `response-error` message instead of a + in the client receiving an `error-response` message instead of a `server-response` message. """ diff --git a/src/pipecat/processors/frameworks/rtvi/models_v0.py b/src/pipecat/processors/frameworks/rtvi/models_v0.py index b3826902e..e1d0c8aa4 100644 --- a/src/pipecat/processors/frameworks/rtvi/models_v0.py +++ b/src/pipecat/processors/frameworks/rtvi/models_v0.py @@ -12,6 +12,7 @@ server messages instead. """ from typing import ( + TYPE_CHECKING, Any, Awaitable, Callable, @@ -26,6 +27,9 @@ from pydantic import BaseModel, Field, PrivateAttr import pipecat.processors.frameworks.rtvi.models_v1 as RTVI +if TYPE_CHECKING: + from pipecat.processors.frameworks.rtvi.processor import RTVIProcessor + ActionResult = Union[bool, int, float, str, list, dict] diff --git a/src/pipecat/processors/frameworks/rtvi/observer.py b/src/pipecat/processors/frameworks/rtvi/observer.py index 83837ad6e..2f097b0ac 100644 --- a/src/pipecat/processors/frameworks/rtvi/observer.py +++ b/src/pipecat/processors/frameworks/rtvi/observer.py @@ -316,7 +316,7 @@ class RTVIObserver(BaseObserver): """Send an RTVI message. By default, we push a transport frame. But this function can be - overriden by subclass to send RTVI messages in different ways. + overridden by subclass to send RTVI messages in different ways. Args: model: The message to send. @@ -539,15 +539,15 @@ class RTVIObserver(BaseObserver): return text = frame.text - type = frame.aggregated_by + agg_type = frame.aggregated_by for aggregation_type, transform in self._aggregation_transforms: - if aggregation_type == type or aggregation_type == "*": - text = await transform(text, type) + if aggregation_type == agg_type or aggregation_type == "*": + text = await transform(text, agg_type) isTTS = isinstance(frame, TTSTextFrame) if self._params.bot_output_enabled: message = RTVI.BotOutputMessage( - data=RTVI.BotOutputMessageData(text=text, spoken=isTTS, aggregated_by=type) + data=RTVI.BotOutputMessageData(text=text, spoken=isTTS, aggregated_by=agg_type) ) await self.send_rtvi_message(message) diff --git a/src/pipecat/processors/frameworks/rtvi/processor.py b/src/pipecat/processors/frameworks/rtvi/processor.py index 345dcb8c4..4b4ea2123 100644 --- a/src/pipecat/processors/frameworks/rtvi/processor.py +++ b/src/pipecat/processors/frameworks/rtvi/processor.py @@ -566,10 +566,6 @@ class RTVIProcessor(FrameProcessor): async def _handle_client_message(self, msg_id: str, data: RTVI.RawClientMessageData): """Handle a client message frame.""" - if not data: - await self._send_error_response(msg_id, "Malformed client message") - return - # Create a RTVIClientMessageFrame to push the message frame = RTVIClientMessageFrame(msg_id=msg_id, type=data.t, data=data.d) await self.push_frame(frame) From da0975a4e04a0c2721042ebef34ec29c8d84c8bf Mon Sep 17 00:00:00 2001 From: mattie ruth backman Date: Wed, 4 Mar 2026 16:35:30 -0500 Subject: [PATCH 0827/1060] Fix forward reference --- src/pipecat/processors/frameworks/rtvi/models_v0.py | 12 ++---------- 1 file changed, 2 insertions(+), 10 deletions(-) diff --git a/src/pipecat/processors/frameworks/rtvi/models_v0.py b/src/pipecat/processors/frameworks/rtvi/models_v0.py index e1d0c8aa4..af2c54300 100644 --- a/src/pipecat/processors/frameworks/rtvi/models_v0.py +++ b/src/pipecat/processors/frameworks/rtvi/models_v0.py @@ -12,7 +12,6 @@ server messages instead. """ from typing import ( - TYPE_CHECKING, Any, Awaitable, Callable, @@ -27,9 +26,6 @@ from pydantic import BaseModel, Field, PrivateAttr import pipecat.processors.frameworks.rtvi.models_v1 as RTVI -if TYPE_CHECKING: - from pipecat.processors.frameworks.rtvi.processor import RTVIProcessor - ActionResult = Union[bool, int, float, str, list, dict] @@ -46,9 +42,7 @@ class RTVIServiceOption(BaseModel): name: str type: Literal["bool", "number", "string", "array", "object"] - handler: Callable[["RTVIProcessor", str, "RTVIServiceOptionConfig"], Awaitable[None]] = Field( - exclude=True - ) + handler: Callable[..., Awaitable[None]] = Field(exclude=True) class RTVIService(BaseModel): @@ -117,9 +111,7 @@ class RTVIAction(BaseModel): action: str arguments: List[RTVIActionArgument] = Field(default_factory=list) result: Literal["bool", "number", "string", "array", "object"] - handler: Callable[["RTVIProcessor", str, Dict[str, Any]], Awaitable[ActionResult]] = Field( - exclude=True - ) + handler: Callable[..., Awaitable[ActionResult]] = Field(exclude=True) _arguments_dict: Dict[str, RTVIActionArgument] = PrivateAttr(default={}) def model_post_init(self, __context: Any) -> None: From 18494658c351aac83794c5f168361e7aa0619c09 Mon Sep 17 00:00:00 2001 From: mattie ruth backman Date: Fri, 6 Mar 2026 11:24:34 -0500 Subject: [PATCH 0828/1060] rename models_vX to models.py and models_deprecated.py --- src/pipecat/processors/frameworks/rtvi/__init__.py | 2 +- .../processors/frameworks/rtvi/{models_v1.py => models.py} | 2 +- .../frameworks/rtvi/{models_v0.py => models_deprecated.py} | 2 +- src/pipecat/processors/frameworks/rtvi/observer.py | 2 +- src/pipecat/processors/frameworks/rtvi/processor.py | 4 ++-- src/pipecat/serializers/base_serializer.py | 2 +- 6 files changed, 7 insertions(+), 7 deletions(-) rename src/pipecat/processors/frameworks/rtvi/{models_v1.py => models.py} (99%) rename src/pipecat/processors/frameworks/rtvi/{models_v0.py => models_deprecated.py} (99%) diff --git a/src/pipecat/processors/frameworks/rtvi/__init__.py b/src/pipecat/processors/frameworks/rtvi/__init__.py index 12f6022ee..eed90ed09 100644 --- a/src/pipecat/processors/frameworks/rtvi/__init__.py +++ b/src/pipecat/processors/frameworks/rtvi/__init__.py @@ -12,7 +12,7 @@ from pipecat.processors.frameworks.rtvi.frames import ( RTVIServerMessageFrame, RTVIServerResponseFrame, ) -from pipecat.processors.frameworks.rtvi.models_v0 import ( +from pipecat.processors.frameworks.rtvi.models_deprecated import ( ActionResult, RTVIAction, RTVIActionArgument, diff --git a/src/pipecat/processors/frameworks/rtvi/models_v1.py b/src/pipecat/processors/frameworks/rtvi/models.py similarity index 99% rename from src/pipecat/processors/frameworks/rtvi/models_v1.py rename to src/pipecat/processors/frameworks/rtvi/models.py index f38986cb0..7a9d4e633 100644 --- a/src/pipecat/processors/frameworks/rtvi/models_v1.py +++ b/src/pipecat/processors/frameworks/rtvi/models.py @@ -9,7 +9,7 @@ Contains all RTVI protocol v1 message definitions and data structures. Import this module under the ``RTVI`` alias to use as a namespace:: - import pipecat.processors.frameworks.rtvi.models_v1 as RTVI + import pipecat.processors.frameworks.rtvi.models as RTVI msg = RTVI.BotReady(id="1", data=RTVI.BotReadyData(version=RTVI.PROTOCOL_VERSION)) """ diff --git a/src/pipecat/processors/frameworks/rtvi/models_v0.py b/src/pipecat/processors/frameworks/rtvi/models_deprecated.py similarity index 99% rename from src/pipecat/processors/frameworks/rtvi/models_v0.py rename to src/pipecat/processors/frameworks/rtvi/models_deprecated.py index af2c54300..07c998f6f 100644 --- a/src/pipecat/processors/frameworks/rtvi/models_v0.py +++ b/src/pipecat/processors/frameworks/rtvi/models_deprecated.py @@ -24,7 +24,7 @@ from typing import ( from pydantic import BaseModel, Field, PrivateAttr -import pipecat.processors.frameworks.rtvi.models_v1 as RTVI +import pipecat.processors.frameworks.rtvi.models as RTVI ActionResult = Union[bool, int, float, str, list, dict] diff --git a/src/pipecat/processors/frameworks/rtvi/observer.py b/src/pipecat/processors/frameworks/rtvi/observer.py index 2f097b0ac..3e4553b2f 100644 --- a/src/pipecat/processors/frameworks/rtvi/observer.py +++ b/src/pipecat/processors/frameworks/rtvi/observer.py @@ -23,7 +23,7 @@ from typing import ( from loguru import logger from pydantic import BaseModel -import pipecat.processors.frameworks.rtvi.models_v1 as RTVI +import pipecat.processors.frameworks.rtvi.models as RTVI from pipecat.audio.utils import calculate_audio_volume from pipecat.frames.frames import ( AggregatedTextFrame, diff --git a/src/pipecat/processors/frameworks/rtvi/processor.py b/src/pipecat/processors/frameworks/rtvi/processor.py index 4b4ea2123..b750bd70b 100644 --- a/src/pipecat/processors/frameworks/rtvi/processor.py +++ b/src/pipecat/processors/frameworks/rtvi/processor.py @@ -13,7 +13,7 @@ from typing import Any, Dict, Mapping, Optional from loguru import logger from pydantic import BaseModel, ValidationError -import pipecat.processors.frameworks.rtvi.models_v1 as RTVI +import pipecat.processors.frameworks.rtvi.models as RTVI from pipecat import version as pipecat_version from pipecat.frames.frames import ( CancelFrame, @@ -32,7 +32,7 @@ from pipecat.frames.frames import ( ) from pipecat.processors.frame_processor import FrameDirection, FrameProcessor from pipecat.processors.frameworks.rtvi.frames import RTVIActionFrame, RTVIClientMessageFrame -from pipecat.processors.frameworks.rtvi.models_v0 import ( +from pipecat.processors.frameworks.rtvi.models_deprecated import ( RTVIAction, RTVIActionResponse, RTVIActionResponseData, diff --git a/src/pipecat/serializers/base_serializer.py b/src/pipecat/serializers/base_serializer.py index 4807f8606..c7b32dccc 100644 --- a/src/pipecat/serializers/base_serializer.py +++ b/src/pipecat/serializers/base_serializer.py @@ -11,7 +11,7 @@ from typing import Optional from pydantic import BaseModel -import pipecat.processors.frameworks.rtvi.models_v1 as RTVI +import pipecat.processors.frameworks.rtvi.models as RTVI from pipecat.frames.frames import ( Frame, OutputTransportMessageFrame, From 2b8a6d9ca4cae18343f46239bce60feb79712bcd Mon Sep 17 00:00:00 2001 From: Paul Kompfner Date: Fri, 6 Mar 2026 12:00:41 -0500 Subject: [PATCH 0829/1060] In OpenAI/Azure Realtime examples, migrate to `settings=OpenAIRealtimeLLMSettings(...)` pattern Move `session_properties` and `system_instruction` into the `settings` arg, matching the canonical pattern used across the codebase. --- examples/foundational/19-openai-realtime.py | 47 ++++++++++--------- examples/foundational/19a-azure-realtime.py | 39 +++++++-------- .../foundational/19b-openai-realtime-text.py | 45 +++++++++--------- .../19c-openai-realtime-live-video.py | 47 ++++++++++--------- .../20b-persistent-context-openai-realtime.py | 41 ++++++++-------- 5 files changed, 116 insertions(+), 103 deletions(-) diff --git a/examples/foundational/19-openai-realtime.py b/examples/foundational/19-openai-realtime.py index 0d59782f1..d10fbc129 100644 --- a/examples/foundational/19-openai-realtime.py +++ b/examples/foundational/19-openai-realtime.py @@ -37,7 +37,10 @@ from pipecat.services.openai.realtime.events import ( SemanticTurnDetection, SessionProperties, ) -from pipecat.services.openai.realtime.llm import OpenAIRealtimeLLMService +from pipecat.services.openai.realtime.llm import ( + OpenAIRealtimeLLMService, + OpenAIRealtimeLLMSettings, +) from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams @@ -137,22 +140,10 @@ transport_params = { async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): logger.info(f"Starting bot") - session_properties = SessionProperties( - audio=AudioConfiguration( - input=AudioInput( - transcription=InputAudioTranscription(), - # Set openai TurnDetection parameters. Not setting this at all will turn it - # on by default - turn_detection=SemanticTurnDetection(), - # Or set to False to disable openai turn detection and use transport VAD - # turn_detection=False, - noise_reduction=InputAudioNoiseReduction(type="near_field"), - ) - ), - # In this example we provide tools through the context, but you could - # alternatively provide them here. - # tools=tools, - instructions="""You are a helpful and friendly AI. + llm = OpenAIRealtimeLLMService( + api_key=os.getenv("OPENAI_API_KEY"), + settings=OpenAIRealtimeLLMSettings( + system_instruction="""You are a helpful and friendly AI. Act like a human, but remember that you aren't a human and that you can't do human things in the real world. Your voice and personality should be warm and engaging, with a lively and @@ -166,11 +157,23 @@ You are participating in a voice conversation. Keep your responses concise, shor unless specifically asked to elaborate on a topic. Remember, your responses should be short. Just one or two sentences, usually. Respond in English.""", - ) - - llm = OpenAIRealtimeLLMService( - api_key=os.getenv("OPENAI_API_KEY"), - session_properties=session_properties, + session_properties=SessionProperties( + audio=AudioConfiguration( + input=AudioInput( + transcription=InputAudioTranscription(), + # Set openai TurnDetection parameters. Not setting this at all will turn it + # on by default + turn_detection=SemanticTurnDetection(), + # Or set to False to disable openai turn detection and use transport VAD + # turn_detection=False, + noise_reduction=InputAudioNoiseReduction(type="near_field"), + ) + ), + # In this example we provide tools through the context, but you could + # alternatively provide them here. + # tools=tools, + ), + ), ) # you can either register a single function for all function calls, or specific functions diff --git a/examples/foundational/19a-azure-realtime.py b/examples/foundational/19a-azure-realtime.py index 6883a1f09..8d52a1c12 100644 --- a/examples/foundational/19a-azure-realtime.py +++ b/examples/foundational/19a-azure-realtime.py @@ -30,6 +30,7 @@ from pipecat.services.openai.realtime.events import ( InputAudioTranscription, SessionProperties, ) +from pipecat.services.openai.realtime.llm import OpenAIRealtimeLLMSettings from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams @@ -111,19 +112,11 @@ transport_params = { async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): logger.info(f"Starting bot") - session_properties = SessionProperties( - audio=AudioConfiguration( - input=AudioInput( - transcription=InputAudioTranscription(model="whisper-1"), - # Set openai TurnDetection parameters. Not setting this at all will turn it - # on by default - # turn_detection=TurnDetection(silence_duration_ms=1000), - # Or set to False to disable openai turn detection and use transport VAD - # turn_detection=False, - ) - ), - # tools=tools, - instructions="""You are a helpful and friendly AI. + llm = AzureRealtimeLLMService( + api_key=os.getenv("AZURE_REALTIME_API_KEY"), + base_url=os.getenv("AZURE_REALTIME_BASE_URL"), + settings=OpenAIRealtimeLLMSettings( + system_instruction="""You are a helpful and friendly AI. Act like a human, but remember that you aren't a human and that you can't do human things in the real world. Your voice and personality should be warm and engaging, with a lively and @@ -141,12 +134,20 @@ You have access to the following tools: - get_restaurant_recommendation: Get a restaurant recommendation for a given location. Remember, your responses should be short. Just one or two sentences, usually. Respond in English.""", - ) - - llm = AzureRealtimeLLMService( - api_key=os.getenv("AZURE_REALTIME_API_KEY"), - base_url=os.getenv("AZURE_REALTIME_BASE_URL"), - session_properties=session_properties, + session_properties=SessionProperties( + audio=AudioConfiguration( + input=AudioInput( + transcription=InputAudioTranscription(model="whisper-1"), + # Set openai TurnDetection parameters. Not setting this at all will turn it + # on by default + # turn_detection=TurnDetection(silence_duration_ms=1000), + # Or set to False to disable openai turn detection and use transport VAD + # turn_detection=False, + ) + ), + # tools=tools, + ), + ), ) # you can either register a single function for all function calls, or specific functions diff --git a/examples/foundational/19b-openai-realtime-text.py b/examples/foundational/19b-openai-realtime-text.py index 98dc81c3b..e03381642 100644 --- a/examples/foundational/19b-openai-realtime-text.py +++ b/examples/foundational/19b-openai-realtime-text.py @@ -32,7 +32,10 @@ from pipecat.services.openai.realtime.events import ( SemanticTurnDetection, SessionProperties, ) -from pipecat.services.openai.realtime.llm import OpenAIRealtimeLLMService +from pipecat.services.openai.realtime.llm import ( + OpenAIRealtimeLLMService, + OpenAIRealtimeLLMSettings, +) from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams @@ -113,21 +116,10 @@ transport_params = { async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): logger.info(f"Starting bot") - session_properties = SessionProperties( - audio=AudioConfiguration( - input=AudioInput( - transcription=InputAudioTranscription(), - # Set openai TurnDetection parameters. Not setting this at all will turn it - # on by default - turn_detection=SemanticTurnDetection(), - # Or set to False to disable openai turn detection and use transport VAD - # turn_detection=False, - noise_reduction=InputAudioNoiseReduction(type="near_field"), - ) - ), - output_modalities=["text"], - # tools=tools, - instructions="""You are a helpful and friendly AI. + llm = OpenAIRealtimeLLMService( + api_key=os.getenv("OPENAI_API_KEY"), + settings=OpenAIRealtimeLLMSettings( + system_instruction="""You are a helpful and friendly AI. Act like a human, but remember that you aren't a human and that you can't do human things in the real world. Your voice and personality should be warm and engaging, with a lively and @@ -145,11 +137,22 @@ You have access to the following tools: - get_restaurant_recommendation: Get a restaurant recommendation for a given location. Remember, your responses should be short. Just one or two sentences, usually. Respond in English.""", - ) - - llm = OpenAIRealtimeLLMService( - api_key=os.getenv("OPENAI_API_KEY"), - session_properties=session_properties, + session_properties=SessionProperties( + audio=AudioConfiguration( + input=AudioInput( + transcription=InputAudioTranscription(), + # Set openai TurnDetection parameters. Not setting this at all will turn it + # on by default + turn_detection=SemanticTurnDetection(), + # Or set to False to disable openai turn detection and use transport VAD + # turn_detection=False, + noise_reduction=InputAudioNoiseReduction(type="near_field"), + ) + ), + output_modalities=["text"], + # tools=tools, + ), + ), ) tts = CartesiaTTSService( diff --git a/examples/foundational/19c-openai-realtime-live-video.py b/examples/foundational/19c-openai-realtime-live-video.py index 3f091f712..31088ff0f 100644 --- a/examples/foundational/19c-openai-realtime-live-video.py +++ b/examples/foundational/19c-openai-realtime-live-video.py @@ -32,7 +32,10 @@ from pipecat.services.openai.realtime.events import ( SemanticTurnDetection, SessionProperties, ) -from pipecat.services.openai.realtime.llm import OpenAIRealtimeLLMService +from pipecat.services.openai.realtime.llm import ( + OpenAIRealtimeLLMService, + OpenAIRealtimeLLMSettings, +) from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams @@ -60,22 +63,10 @@ transport_params = { async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): logger.info(f"Starting bot") - session_properties = SessionProperties( - audio=AudioConfiguration( - input=AudioInput( - transcription=InputAudioTranscription(), - # Set openai TurnDetection parameters. Not setting this at all will turn it - # on by default - turn_detection=SemanticTurnDetection(), - # Or set to False to disable openai turn detection and use transport VAD - # turn_detection=False, - noise_reduction=InputAudioNoiseReduction(type="near_field"), - ) - ), - # In this example we provide tools through the context, but you could - # alternatively provide them here. - # tools=tools, - instructions="""You are a helpful and friendly AI. + llm = OpenAIRealtimeLLMService( + api_key=os.getenv("OPENAI_API_KEY"), + settings=OpenAIRealtimeLLMSettings( + system_instruction="""You are a helpful and friendly AI. Act like a human, but remember that you aren't a human and that you can't do human things in the real world. Your voice and personality should be warm and engaging, with a lively and @@ -89,11 +80,23 @@ You are participating in a voice conversation. Keep your responses concise, shor unless specifically asked to elaborate on a topic. Remember, your responses should be short. Just one or two sentences, usually. Respond in English.""", - ) - - llm = OpenAIRealtimeLLMService( - api_key=os.getenv("OPENAI_API_KEY"), - session_properties=session_properties, + session_properties=SessionProperties( + audio=AudioConfiguration( + input=AudioInput( + transcription=InputAudioTranscription(), + # Set openai TurnDetection parameters. Not setting this at all will turn it + # on by default + turn_detection=SemanticTurnDetection(), + # Or set to False to disable openai turn detection and use transport VAD + # turn_detection=False, + noise_reduction=InputAudioNoiseReduction(type="near_field"), + ) + ), + # In this example we provide tools through the context, but you could + # alternatively provide them here. + # tools=tools, + ), + ), ) # Create a standard OpenAI LLM context object using the normal messages format. The diff --git a/examples/foundational/20b-persistent-context-openai-realtime.py b/examples/foundational/20b-persistent-context-openai-realtime.py index a24ff39e5..b85f8c319 100644 --- a/examples/foundational/20b-persistent-context-openai-realtime.py +++ b/examples/foundational/20b-persistent-context-openai-realtime.py @@ -33,7 +33,10 @@ from pipecat.services.openai.realtime.events import ( SessionProperties, TurnDetection, ) -from pipecat.services.openai.realtime.llm import OpenAIRealtimeLLMService +from pipecat.services.openai.realtime.llm import ( + OpenAIRealtimeLLMService, + OpenAIRealtimeLLMSettings, +) from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams @@ -173,19 +176,10 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): stt = DeepgramSTTService(api_key=os.getenv("DEEPGRAM_API_KEY")) - session_properties = SessionProperties( - audio=AudioConfiguration( - input=AudioInput( - transcription=InputAudioTranscription(), - # Set openai TurnDetection parameters. Not setting this at all will turn it - # on by default - turn_detection=TurnDetection(silence_duration_ms=1000), - # Or set to False to disable openai turn detection and use transport VAD - # turn_detection=False, - ) - ), - # tools=tools, - instructions="""Your knowledge cutoff is 2023-10. You are a helpful and friendly AI. + llm = OpenAIRealtimeLLMService( + api_key=os.getenv("OPENAI_API_KEY"), + settings=OpenAIRealtimeLLMSettings( + system_instruction="""Your knowledge cutoff is 2023-10. You are a helpful and friendly AI. Act like a human, but remember that you aren't a human and that you can't do human things in the real world. Your voice and personality should be warm and engaging, with a lively and @@ -199,11 +193,20 @@ You are participating in a voice conversation. Keep your responses concise, shor unless specifically asked to elaborate on a topic. Remember, your responses should be short. Just one or two sentences, usually.""", - ) - - llm = OpenAIRealtimeLLMService( - api_key=os.getenv("OPENAI_API_KEY"), - session_properties=session_properties, + session_properties=SessionProperties( + audio=AudioConfiguration( + input=AudioInput( + transcription=InputAudioTranscription(), + # Set openai TurnDetection parameters. Not setting this at all will turn it + # on by default + turn_detection=TurnDetection(silence_duration_ms=1000), + # Or set to False to disable openai turn detection and use transport VAD + # turn_detection=False, + ) + ), + # tools=tools, + ), + ), ) # you can either register a single function for all function calls, or specific functions From f4c039048c608d858fa92bcb6ccbea7f9be5a7d3 Mon Sep 17 00:00:00 2001 From: Paul Kompfner Date: Fri, 6 Mar 2026 12:48:10 -0500 Subject: [PATCH 0830/1060] Adopt the `settings` pattern for Grok Realtime session properties MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit Move `session_properties` into `GrokRealtimeLLMSettings`, making `settings` the canonical way to configure Grok Realtime — matching the pattern used across the rest of the codebase. The `session_properties` init arg is now deprecated in favor of `settings=GrokRealtimeLLMSettings(session_properties=...)`. `system_instruction` is synced bidirectionally between the top-level settings field and `session_properties.instructions`, with top-level taking precedence on conflict. (Unlike OpenAI Realtime, Grok's `SessionProperties` has no `model` field, so no model sync is needed.) --- src/pipecat/services/grok/realtime/llm.py | 175 ++++++++++++++++---- src/pipecat/services/openai/realtime/llm.py | 4 +- tests/test_settings.py | 168 +++++++++++++++++++ 3 files changed, 313 insertions(+), 34 deletions(-) diff --git a/src/pipecat/services/grok/realtime/llm.py b/src/pipecat/services/grok/realtime/llm.py index 074b44c5d..f0fb170d4 100644 --- a/src/pipecat/services/grok/realtime/llm.py +++ b/src/pipecat/services/grok/realtime/llm.py @@ -13,8 +13,9 @@ https://docs.x.ai/docs/guides/voice/agent import base64 import json import time -from dataclasses import dataclass -from typing import Any, Optional +from dataclasses import dataclass, field +from dataclasses import fields as dataclass_fields +from typing import Any, Dict, Mapping, Optional, Type from loguru import logger @@ -34,7 +35,6 @@ from pipecat.frames.frames import ( LLMMessagesAppendFrame, LLMSetToolsFrame, LLMTextFrame, - LLMUpdateSettingsFrame, StartFrame, TranscriptionFrame, TTSAudioRawFrame, @@ -56,7 +56,13 @@ from pipecat.processors.aggregators.llm_response_universal import ( from pipecat.processors.aggregators.openai_llm_context import OpenAILLMContext from pipecat.processors.frame_processor import FrameDirection from pipecat.services.llm_service import FunctionCallFromLLM, LLMService -from pipecat.services.settings import LLMSettings +from pipecat.services.settings import ( + NOT_GIVEN, + LLMSettings, + _NotGiven, + _warn_deprecated_param, + is_given, +) from pipecat.utils.time import time_now_iso8601 from . import events @@ -88,9 +94,96 @@ class CurrentAudioResponse: @dataclass class GrokRealtimeLLMSettings(LLMSettings): - """Settings for Grok Realtime LLM services.""" + """Settings for Grok Realtime LLM services. - pass + Parameters: + session_properties: Grok Realtime session properties (voice, audio config, + tools, etc.). ``instructions`` is synced bidirectionally with the + top-level ``system_instruction`` field. + """ + + session_properties: events.SessionProperties | _NotGiven = field( + default_factory=lambda: NOT_GIVEN + ) + + # -- Bidirectional sync helpers ------------------------------------------ + + @staticmethod + def _sync_top_level_to_sp(settings: "GrokRealtimeLLMSettings"): + """Push top-level ``system_instruction`` into ``session_properties``.""" + if not is_given(settings.session_properties): + return + sp = settings.session_properties + if is_given(settings.system_instruction): + sp.instructions = settings.system_instruction + + # -- apply_update override ----------------------------------------------- + + def apply_update(self, delta: "GrokRealtimeLLMSettings") -> Dict[str, Any]: + """Merge a delta, keeping ``system_instruction`` in sync with SP. + + When the delta contains ``session_properties``, it **replaces** the + stored SP wholesale (matching legacy behaviour). Top-level field + values always take precedence over conflicting SP values. + """ + # 1. Let the base class handle all fields including session_properties + # (wholesale replacement when given). + changed = super().apply_update(delta) + + # 2. SP → top-level: if the SP was just replaced and carries + # instructions that the delta didn't set at top level, pull it up. + if "session_properties" in changed and is_given(self.session_properties): + sp = self.session_properties + if "system_instruction" not in changed and sp.instructions is not None: + old_si = self.system_instruction + self.system_instruction = sp.instructions + if old_si != self.system_instruction: + changed["system_instruction"] = old_si + + # 3. Top-level → SP: ensure SP mirrors the authoritative top-level + # values. Covers all cases: top-level-only delta, SP-only delta, + # and mixed deltas where top-level takes precedence. + self._sync_top_level_to_sp(self) + + return changed + + # -- from_mapping override ----------------------------------------------- + + @classmethod + def from_mapping( + cls: Type["GrokRealtimeLLMSettings"], settings: Mapping[str, Any] + ) -> "GrokRealtimeLLMSettings": + """Build a delta from a plain dict, routing SP keys into ``session_properties``. + + Keys that correspond to ``SessionProperties`` fields are collected into + a nested ``session_properties`` value. ``model`` is always routed to + the top-level field. Unknown keys go to ``extra``. + """ + # Determine which keys belong to our own dataclass fields. + own_field_names = {f.name for f in dataclass_fields(cls)} - {"extra"} + + top: Dict[str, Any] = {} + sp_dict: Dict[str, Any] = {} + extra: Dict[str, Any] = {} + + sp_keys = set(events.SessionProperties.model_fields.keys()) + + for key, value in settings.items(): + # Resolve aliases first + canonical = cls._aliases.get(key, key) + if canonical in own_field_names: + top[canonical] = value + elif canonical in sp_keys: + sp_dict[canonical] = value + else: + extra[key] = value + + if sp_dict: + top["session_properties"] = events.SessionProperties(**sp_dict) + + instance = cls(**top) + instance.extra = extra + return instance class GrokRealtimeLLMService(LLMService): @@ -132,6 +225,11 @@ class GrokRealtimeLLMService(LLMService): Defaults to "wss://api.x.ai/v1/realtime". session_properties: Configuration properties for the realtime session. If None, uses default SessionProperties with voice "Ara". + + .. deprecated:: 0.0.105 + Use ``settings=GrokRealtimeLLMSettings(session_properties=...)`` + instead. + To set a different voice, configure it in session_properties: session_properties = events.SessionProperties(voice="Rex") @@ -154,9 +252,25 @@ class GrokRealtimeLLMService(LLMService): seed=None, filter_incomplete_user_turns=False, user_turn_completion_config=None, + session_properties=events.SessionProperties(), ) - # 2. Apply settings delta (canonical API, always wins) + # 2. Apply direct init arg overrides (deprecated) + if session_properties is not None: + _warn_deprecated_param( + "session_properties", + GrokRealtimeLLMSettings, + "session_properties", + ) + default_settings.session_properties = session_properties + # Sync instructions from the deprecated SP arg to top-level + if session_properties.instructions is not None: + default_settings.system_instruction = session_properties.instructions + + # Sync top-level system_instruction back into session_properties + GrokRealtimeLLMSettings._sync_top_level_to_sp(default_settings) + + # 3. Apply settings delta (canonical API, always wins) if settings is not None: default_settings.apply_update(settings) @@ -168,7 +282,6 @@ class GrokRealtimeLLMService(LLMService): self.api_key = api_key self.base_url = base_url - self._session_properties = session_properties or events.SessionProperties() self._audio_input_paused = start_audio_paused self._websocket = None @@ -217,13 +330,13 @@ class GrokRealtimeLLMService(LLMService): Configured sample rate or None if not manually configured. For PCMU/PCMA formats, returns 8000 Hz (G.711 standard). """ - if not self._session_properties.audio: + if not self._settings.session_properties.audio: return None audio_config = ( - self._session_properties.audio.input + self._settings.session_properties.audio.input if direction == "input" - else self._session_properties.audio.output + else self._settings.session_properties.audio.output ) if audio_config and audio_config.format: @@ -253,8 +366,8 @@ class GrokRealtimeLLMService(LLMService): def _is_turn_detection_enabled(self) -> bool: """Check if server-side VAD is enabled.""" - if self._session_properties.turn_detection: - return self._session_properties.turn_detection.type == "server_vad" + if self._settings.session_properties.turn_detection: + return self._settings.session_properties.turn_detection.type == "server_vad" return False async def _handle_interruption(self): @@ -321,7 +434,7 @@ class GrokRealtimeLLMService(LLMService): input_sample_rate: Sample rate for audio input (Hz). output_sample_rate: Sample rate for audio output (Hz). """ - props = self._session_properties + props = self._settings.session_properties if not props.audio: props.audio = events.AudioConfiguration() if not props.audio.input: @@ -372,21 +485,6 @@ class GrokRealtimeLLMService(LLMService): frame: The frame to process. direction: The direction of frame flow in the pipeline. """ - # Backward-compatible dict path: frame.settings contains SessionProperties - # fields, not our Settings fields, so we construct SessionProperties - # directly. The frame.delta path falls through to super, which calls - # _update_settings → our override handles the rest. - if isinstance(frame, LLMUpdateSettingsFrame) and frame.delta is None: - # Capture current audio config before replacing session properties. - input_rate = self._get_configured_sample_rate("input") - output_rate = self._get_configured_sample_rate("output") - self._session_properties = events.SessionProperties(**frame.settings) - if input_rate and output_rate: - self._ensure_audio_config(input_rate, output_rate) - await self._send_session_update() - await self.push_frame(frame, direction) - return - await super().process_frame(frame, direction) if isinstance(frame, TranscriptionFrame): @@ -485,14 +583,27 @@ class GrokRealtimeLLMService(LLMService): await self.push_error(error_msg=f"Error sending client event: {e}", exception=e) async def _update_settings(self, delta): - """Apply a settings delta.""" + """Apply a settings delta, sending a session update when needed.""" + # Capture audio config before the update — a wholesale SP replacement + # would lose it since the new SP likely has audio=None. + input_rate = self._get_configured_sample_rate("input") + output_rate = self._get_configured_sample_rate("output") + changed = await super()._update_settings(delta) - self._warn_unhandled_updated_settings(changed.keys()) + + # Re-establish audio config if it was lost during SP replacement. + if "session_properties" in changed and input_rate and output_rate: + self._ensure_audio_config(input_rate, output_rate) + + handled = {"session_properties", "system_instruction"} + if changed.keys() & handled: + await self._send_session_update() + self._warn_unhandled_updated_settings(changed.keys() - handled) return changed async def _send_session_update(self): """Update session settings on the server.""" - settings = self._session_properties + settings = self._settings.session_properties adapter: GrokRealtimeLLMAdapter = self.get_llm_adapter() if self._context: diff --git a/src/pipecat/services/openai/realtime/llm.py b/src/pipecat/services/openai/realtime/llm.py index 36c6d8fae..faaae2cd9 100644 --- a/src/pipecat/services/openai/realtime/llm.py +++ b/src/pipecat/services/openai/realtime/llm.py @@ -236,7 +236,7 @@ class OpenAIRealtimeLLMService(LLMService): api_key: OpenAI API key for authentication. model: OpenAI model name. - .. deprecated:: + .. deprecated:: 0.0.105 Use ``settings=OpenAIRealtimeLLMSettings(model=...)`` instead. This is a connection-level parameter set via the WebSocket URL query @@ -246,7 +246,7 @@ class OpenAIRealtimeLLMService(LLMService): session_properties: Configuration properties for the realtime session. If None, uses default SessionProperties. - .. deprecated:: + .. deprecated:: 0.0.105 Use ``settings=OpenAIRealtimeLLMSettings(session_properties=...)`` instead. settings: Runtime-updatable settings for this service. diff --git a/tests/test_settings.py b/tests/test_settings.py index 875ccf067..973dd7815 100644 --- a/tests/test_settings.py +++ b/tests/test_settings.py @@ -12,6 +12,8 @@ import pytest from pipecat.services.deepgram.stt import DeepgramSTTService, DeepgramSTTSettings from pipecat.services.deepgram.stt_sagemaker import DeepgramSageMakerSTTSettings +from pipecat.services.grok.realtime import events as grok_events +from pipecat.services.grok.realtime.llm import GrokRealtimeLLMSettings from pipecat.services.openai.realtime import events from pipecat.services.openai.realtime.llm import OpenAIRealtimeLLMSettings from pipecat.services.settings import ( @@ -815,3 +817,169 @@ class TestOpenAIRealtimeSettingsFromMapping: assert store.session_properties.instructions == "Be concise." assert store.session_properties.output_modalities == ["text"] assert store.system_instruction == "Be concise." + + +# --------------------------------------------------------------------------- +# GrokRealtimeLLMSettings: apply_update +# --------------------------------------------------------------------------- + + +class TestGrokRealtimeSettingsApplyUpdate: + def _make_store(self, **kwargs) -> GrokRealtimeLLMSettings: + """Helper to build a store-mode GrokRealtimeLLMSettings.""" + defaults = dict( + model=None, + system_instruction=None, + temperature=None, + max_tokens=None, + top_p=None, + top_k=None, + frequency_penalty=None, + presence_penalty=None, + seed=None, + filter_incomplete_user_turns=False, + user_turn_completion_config=None, + session_properties=grok_events.SessionProperties(), + ) + defaults.update(kwargs) + return GrokRealtimeLLMSettings(**defaults) + + def test_top_level_system_instruction_syncs_to_sp(self): + """Updating top-level system_instruction should propagate to session_properties.instructions.""" + store = self._make_store() + delta = GrokRealtimeLLMSettings(system_instruction="Be helpful.") + changed = store.apply_update(delta) + + assert "system_instruction" in changed + assert store.system_instruction == "Be helpful." + assert store.session_properties.instructions == "Be helpful." + + def test_sp_replaces_wholesale(self): + """session_properties in delta replaces the entire stored SP.""" + store = self._make_store( + session_properties=grok_events.SessionProperties( + voice="Rex", + instructions="Old instructions.", + ), + system_instruction="Old instructions.", + ) + + new_sp = grok_events.SessionProperties(voice="Sal") + delta = GrokRealtimeLLMSettings(session_properties=new_sp) + changed = store.apply_update(delta) + + assert "session_properties" in changed + assert store.session_properties.voice == "Sal" + # instructions is synced from top-level system_instruction + assert store.session_properties.instructions == "Old instructions." + + def test_sp_instructions_syncs_to_top_level(self): + """session_properties.instructions should sync to top-level system_instruction.""" + store = self._make_store() + new_sp = grok_events.SessionProperties(instructions="New instructions.") + delta = GrokRealtimeLLMSettings(session_properties=new_sp) + changed = store.apply_update(delta) + + assert "system_instruction" in changed + assert store.system_instruction == "New instructions." + assert store.session_properties.instructions == "New instructions." + + def test_top_level_si_takes_precedence_over_sp_instructions(self): + """When both system_instruction and SP.instructions are in delta, top-level wins.""" + store = self._make_store() + new_sp = grok_events.SessionProperties(instructions="sp instructions") + delta = GrokRealtimeLLMSettings( + system_instruction="top instructions", + session_properties=new_sp, + ) + store.apply_update(delta) + + assert store.system_instruction == "top instructions" + assert store.session_properties.instructions == "top instructions" + + def test_non_synced_field_update_does_not_affect_sp(self): + """Updating a non-synced field like temperature shouldn't touch session_properties.""" + store = self._make_store( + session_properties=grok_events.SessionProperties(instructions="Keep me."), + system_instruction="Keep me.", + ) + original_sp = store.session_properties + + delta = GrokRealtimeLLMSettings(temperature=0.5) + changed = store.apply_update(delta) + + assert "temperature" in changed + assert store.temperature == 0.5 + # SP should be untouched (same object) + assert store.session_properties is original_sp + assert store.session_properties.instructions == "Keep me." + + +# --------------------------------------------------------------------------- +# GrokRealtimeLLMSettings: from_mapping +# --------------------------------------------------------------------------- + + +class TestGrokRealtimeSettingsFromMapping: + def test_sp_keys_route_to_session_properties(self): + """SessionProperties fields (instructions, voice, etc.) route into nested SP.""" + delta = GrokRealtimeLLMSettings.from_mapping( + {"instructions": "Be concise.", "voice": "Rex"} + ) + assert is_given(delta.session_properties) + assert delta.session_properties.instructions == "Be concise." + assert delta.session_properties.voice == "Rex" + + def test_model_routes_to_top_level(self): + """model should go to the top-level field, not session_properties.""" + delta = GrokRealtimeLLMSettings.from_mapping({"model": "some-model"}) + assert delta.model == "some-model" + # No session_properties should be created since no SP keys were present + assert not is_given(delta.session_properties) + + def test_unknown_keys_go_to_extra(self): + """Unrecognized keys should land in extra.""" + delta = GrokRealtimeLLMSettings.from_mapping({"unknown_param": 42}) + assert not is_given(delta.model) + assert not is_given(delta.session_properties) + assert delta.extra == {"unknown_param": 42} + + def test_mixed_keys(self): + """model + SP keys + unknown keys are routed correctly.""" + delta = GrokRealtimeLLMSettings.from_mapping( + { + "model": "some-model", + "instructions": "Be helpful.", + "unknown": "val", + } + ) + assert delta.model == "some-model" + assert is_given(delta.session_properties) + assert delta.session_properties.instructions == "Be helpful." + assert delta.extra == {"unknown": "val"} + + def test_roundtrip_from_mapping_apply_update(self): + """Simulate dict-style update: from_mapping -> apply_update.""" + store = GrokRealtimeLLMSettings( + model=None, + system_instruction=None, + temperature=None, + max_tokens=None, + top_p=None, + top_k=None, + frequency_penalty=None, + presence_penalty=None, + seed=None, + filter_incomplete_user_turns=False, + user_turn_completion_config=None, + session_properties=grok_events.SessionProperties(), + ) + + raw = {"instructions": "Be concise.", "voice": "Eve"} + delta = GrokRealtimeLLMSettings.from_mapping(raw) + changed = store.apply_update(delta) + + assert "session_properties" in changed + assert store.session_properties.instructions == "Be concise." + assert store.session_properties.voice == "Eve" + assert store.system_instruction == "Be concise." From 593b75bc8b328aac8334ecc727df09e6e9cd246f Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Aleix=20Conchillo=20Flaqu=C3=A9?= Date: Thu, 5 Mar 2026 16:17:32 -0800 Subject: [PATCH 0831/1060] Update foundational examples to use "user" role Use system_instruction on LLM service constructors instead of adding system messages to LLMContext. Messages added to context now use "user" role. --- changelog/3931.other.md | 1 + examples/foundational/02-llm-say-one-thing.py | 2 +- .../04-transports-small-webrtc.py | 2 +- examples/foundational/04a-transports-daily.py | 2 +- .../foundational/05-sync-speech-and-image.py | 2 +- .../05a-local-sync-speech-and-image.py | 2 +- .../foundational/06-listen-and-respond.py | 2 +- .../07-interruptible-cartesia-http.py | 2 +- examples/foundational/07-interruptible.py | 2 +- .../07a-interruptible-speechmatics-vad.py | 2 +- .../07a-interruptible-speechmatics.py | 2 +- .../07c-interruptible-deepgram-flux.py | 2 +- .../07c-interruptible-deepgram-http.py | 2 +- .../07c-interruptible-deepgram-vad.py | 2 +- .../07c-interruptible-deepgram.py | 2 +- .../07d-interruptible-elevenlabs-http.py | 2 +- .../07d-interruptible-elevenlabs.py | 2 +- .../07f-interruptible-azure-http.py | 2 +- .../foundational/07f-interruptible-azure.py | 2 +- .../07g-interruptible-openai-http.py | 2 +- .../foundational/07g-interruptible-openai.py | 2 +- .../07h-interruptible-openpipe.py | 2 +- .../foundational/07i-interruptible-xtts.py | 2 +- .../07j-interruptible-gladia-vad.py | 2 +- .../foundational/07j-interruptible-gladia.py | 2 +- .../foundational/07k-interruptible-lmnt.py | 2 +- .../foundational/07l-interruptible-groq.py | 2 +- .../07n-interruptible-gemini-image.py | 2 +- .../foundational/07n-interruptible-gemini.py | 2 +- .../07n-interruptible-google-http.py | 2 +- .../foundational/07n-interruptible-google.py | 2 +- ...interruptible-assemblyai-turn-detection.py | 2 +- .../07o-interruptible-assemblyai.py | 2 +- .../07p-interruptible-krisp-viva.py | 2 +- .../foundational/07p-interruptible-krisp.py | 2 +- .../07q-interruptible-rime-http.py | 2 +- .../foundational/07q-interruptible-rime.py | 2 +- .../foundational/07r-interruptible-nvidia.py | 2 +- .../07s-interruptible-google-audio-in.py | 22 ++------ .../foundational/07t-interruptible-fish.py | 2 +- .../07v-interruptible-neuphonic-http.py | 2 +- .../07v-interruptible-neuphonic.py | 2 +- .../foundational/07w-interruptible-fal.py | 2 +- .../foundational/07x-interruptible-local.py | 2 +- .../foundational/07y-interruptible-minimax.py | 2 +- .../07z-interruptible-sarvam-http.py | 2 +- .../foundational/07z-interruptible-sarvam.py | 2 +- .../foundational/07za-interruptible-soniox.py | 2 +- .../07zb-interruptible-inworld-http.py | 2 +- .../07zb-interruptible-inworld.py | 2 +- .../07zc-interruptible-asyncai-http.py | 2 +- .../07zc-interruptible-asyncai.py | 2 +- .../07zd-interruptible-aicoustics.py | 2 +- .../foundational/07ze-interruptible-hume.py | 2 +- .../07zf-interruptible-gradium.py | 2 +- .../foundational/07zg-interruptible-camb.py | 2 +- .../foundational/07zi-interruptible-piper.py | 2 +- .../foundational/07zj-interruptible-kokoro.py | 2 +- .../07zk-interruptible-resemble.py | 2 +- .../foundational/08-custom-frame-processor.py | 2 +- examples/foundational/10-wake-phrase.py | 2 +- .../14a-function-calling-anthropic.py | 1 + .../14d-function-calling-anthropic-video.py | 2 +- .../14d-function-calling-aws-video.py | 2 +- ...14d-function-calling-gemini-flash-video.py | 2 +- .../14d-function-calling-moondream-video.py | 2 +- .../14d-function-calling-openai-video.py | 2 +- .../14i-function-calling-fireworks.py | 2 +- examples/foundational/15-switch-voices.py | 2 +- examples/foundational/15a-switch-languages.py | 2 +- .../16-gpu-container-local-bot.py | 2 +- examples/foundational/17-detect-user-idle.py | 6 +-- .../20a-persistent-context-openai.py | 14 +++-- ...persistent-context-openai-realtime-beta.py | 17 +++--- .../20c-persistent-context-anthropic.py | 32 +++++------- .../20d-persistent-context-gemini.py | 25 ++++----- .../20e-persistent-context-aws-nova-sonic.py | 8 +-- examples/foundational/21-tavus-transport.py | 2 +- .../foundational/21a-tavus-video-service.py | 2 +- .../foundational/23-bot-background-sound.py | 2 +- .../foundational/24-user-mute-strategy.py | 2 +- .../26b-gemini-live-function-calling.py | 9 +--- .../foundational/28-user-assistant-turns.py | 2 +- .../foundational/29-turn-tracking-observer.py | 2 +- examples/foundational/30-observer.py | 2 +- examples/foundational/33-gemini-rag.py | 9 ++-- examples/foundational/38-smart-turn-fal.py | 2 +- .../38a-smart-turn-local-coreml.py | 2 +- examples/foundational/38b-smart-turn-local.py | 2 +- examples/foundational/39-mcp-stdio.py | 4 +- .../foundational/39a-mcp-streamable-http.py | 27 +++++----- examples/foundational/39c-multiple-mcp.py | 4 +- examples/foundational/40-aws-nova-sonic.py | 11 +--- .../foundational/42-interruption-config.py | 2 +- examples/foundational/43-heygen-transport.py | 2 +- .../foundational/43a-heygen-video-service.py | 2 +- .../45-before-and-after-events.py | 2 +- examples/foundational/47-sentry-metrics.py | 2 +- examples/foundational/48-service-switcher.py | 6 +-- .../54-context-summarization-openai.py | 2 +- .../54a-context-summarization-google.py | 2 +- .../55a-update-settings-deepgram-flux-stt.py | 2 +- ...-update-settings-deepgram-sagemaker-stt.py | 2 +- .../55a-update-settings-deepgram-stt.py | 2 +- .../55b-update-settings-azure-stt.py | 2 +- .../55c-update-settings-google-stt.py | 2 +- .../55d-update-settings-assemblyai-stt.py | 2 +- .../55e-update-settings-gladia-stt.py | 2 +- ...update-settings-elevenlabs-realtime-stt.py | 2 +- .../55g-update-settings-elevenlabs-stt.py | 2 +- .../55h-update-settings-speechmatics-stt.py | 2 +- .../55i-update-settings-whisper-api-stt.py | 2 +- .../55j-update-settings-sarvam-stt.py | 2 +- .../55k-update-settings-soniox-stt.py | 2 +- .../55l-update-settings-aws-transcribe-stt.py | 2 +- .../55m-update-settings-cartesia-stt.py | 2 +- .../55n-update-settings-cartesia-http-tts.py | 2 +- .../55n-update-settings-cartesia-tts.py | 2 +- ...55o-update-settings-elevenlabs-http-tts.py | 2 +- .../55o-update-settings-elevenlabs-tts.py | 2 +- .../55p-update-settings-openai-tts.py | 2 +- .../55q-update-settings-deepgram-http-tts.py | 2 +- ...-update-settings-deepgram-sagemaker-tts.py | 2 +- .../55q-update-settings-deepgram-tts.py | 2 +- .../55r-update-settings-azure-http-tts.py | 2 +- .../55r-update-settings-azure-tts.py | 2 +- .../55s-update-settings-google-http-tts.py | 2 +- .../55s-update-settings-google-stream-tts.py | 2 +- .../55u-update-settings-rime-http-tts.py | 2 +- .../55u-update-settings-rime-tts.py | 2 +- .../55v-update-settings-lmnt-tts.py | 2 +- .../55w-update-settings-fish-tts.py | 2 +- .../55x-update-settings-minimax-tts.py | 2 +- .../55y-update-settings-groq-tts.py | 2 +- .../55z-update-settings-hume-tts.py | 2 +- ...55za-update-settings-neuphonic-http-tts.py | 2 +- .../55za-update-settings-neuphonic-tts.py | 2 +- .../55zb-update-settings-inworld-http-tts.py | 2 +- .../55zb-update-settings-inworld-tts.py | 2 +- .../55zc-update-settings-gemini-tts.py | 2 +- .../55zd-update-settings-aws-polly-tts.py | 2 +- .../55ze-update-settings-sarvam-http-tts.py | 2 +- .../55ze-update-settings-sarvam-tts.py | 2 +- .../55zf-update-settings-camb-tts.py | 2 +- .../55zh-update-settings-resembleai-tts.py | 2 +- .../55zi-update-settings-azure-llm.py | 2 +- .../55zi-update-settings-openai-llm.py | 2 +- .../55zj-update-settings-anthropic-llm.py | 2 +- .../55zk-update-settings-google-llm.py | 2 +- .../55zk-update-settings-google-vertex-llm.py | 2 +- ...55zm-update-settings-gemini-live-vertex.py | 10 +--- .../55zm-update-settings-gemini-live.py | 14 ++--- .../55zp-update-settings-aws-bedrock-llm.py | 2 +- .../55zq-update-settings-fal-stt.py | 2 +- .../55zr-update-settings-gradium-stt.py | 2 +- ...zt-update-settings-nvidia-segmented-stt.py | 2 +- .../55zt-update-settings-nvidia-stt.py | 2 +- ...5zu-update-settings-openai-realtime-stt.py | 2 +- .../55zv-update-settings-asyncai-http-tts.py | 2 +- .../55zv-update-settings-asyncai-tts.py | 2 +- .../55zw-update-settings-gradium-tts.py | 2 +- .../55zx-update-settings-cerebras-llm.py | 2 +- .../55zy-update-settings-deepseek-llm.py | 2 +- .../55zz-update-settings-fireworks-llm.py | 2 +- .../55zza-update-settings-grok-llm.py | 2 +- .../55zzb-update-settings-groq-llm.py | 2 +- .../55zzc-update-settings-mistral-llm.py | 2 +- .../55zzd-update-settings-nvidia-llm.py | 2 +- .../55zze-update-settings-ollama-llm.py | 2 +- .../55zzf-update-settings-openrouter-llm.py | 2 +- .../55zzh-update-settings-qwen-llm.py | 2 +- .../55zzi-update-settings-sambanova-llm.py | 2 +- .../55zzj-update-settings-together-llm.py | 2 +- ...5zzk-update-settings-aws-nova-sonic-llm.py | 16 ++---- .../55zzl-update-settings-nvidia-tts.py | 2 +- .../55zzm-update-settings-speechmatics-tts.py | 2 +- .../55zzn-update-settings-groq-stt.py | 2 +- .../foundational/56-lemonslice-transport.py | 2 +- scripts/evals/eval.py | 52 ++++++++++--------- 179 files changed, 271 insertions(+), 335 deletions(-) create mode 100644 changelog/3931.other.md diff --git a/changelog/3931.other.md b/changelog/3931.other.md new file mode 100644 index 000000000..a1ebef414 --- /dev/null +++ b/changelog/3931.other.md @@ -0,0 +1 @@ +- Updated foundational examples and eval scripts to use `"user"` role instead of `"system"` when adding messages to `LLMContext`, since system prompts should be set via `system_instruction` on the LLM service. diff --git a/examples/foundational/02-llm-say-one-thing.py b/examples/foundational/02-llm-say-one-thing.py index 988ff634f..f59a2216d 100644 --- a/examples/foundational/02-llm-say-one-thing.py +++ b/examples/foundational/02-llm-say-one-thing.py @@ -60,7 +60,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): @transport.event_handler("on_client_connected") async def on_client_connected(transport, client): context = LLMContext() - context.add_message({"role": "system", "content": "Say hello to the world."}) + context.add_message({"role": "user", "content": "Say hello to the world."}) await task.queue_frames([LLMContextFrame(context), EndFrame()]) runner = PipelineRunner(handle_sigint=runner_args.handle_sigint) diff --git a/examples/foundational/04-transports-small-webrtc.py b/examples/foundational/04-transports-small-webrtc.py index a26fdf5c0..d8b6422db 100644 --- a/examples/foundational/04-transports-small-webrtc.py +++ b/examples/foundational/04-transports-small-webrtc.py @@ -109,7 +109,7 @@ async def run_example(webrtc_connection: SmallWebRTCConnection): async def on_client_connected(transport, client): logger.info(f"Client connected") # Kick off the conversation. - context.add_message({"role": "system", "content": "Please introduce yourself to the user."}) + context.add_message({"role": "user", "content": "Please introduce yourself to the user."}) await task.queue_frames([LLMRunFrame()]) @transport.event_handler("on_client_disconnected") diff --git a/examples/foundational/04a-transports-daily.py b/examples/foundational/04a-transports-daily.py index 15b5e20e2..aaf8a3f0f 100644 --- a/examples/foundational/04a-transports-daily.py +++ b/examples/foundational/04a-transports-daily.py @@ -93,7 +93,7 @@ async def main(): await transport.capture_participant_transcription(participant["id"]) # Kick off the conversation. context.add_message( - {"role": "system", "content": "Please introduce yourself to the user."} + {"role": "user", "content": "Please introduce yourself to the user."} ) await task.queue_frames([LLMRunFrame()]) diff --git a/examples/foundational/05-sync-speech-and-image.py b/examples/foundational/05-sync-speech-and-image.py index b77ff1612..276d3a14a 100644 --- a/examples/foundational/05-sync-speech-and-image.py +++ b/examples/foundational/05-sync-speech-and-image.py @@ -152,7 +152,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): ]: messages = [ { - "role": "system", + "role": "user", "content": f"Describe a nature photograph suitable for use in a calendar, for the month of {month}. Include only the image description with no preamble. Limit the description to one sentence, please.", } ] diff --git a/examples/foundational/05a-local-sync-speech-and-image.py b/examples/foundational/05a-local-sync-speech-and-image.py index 993e8eb07..b06a2a8b0 100644 --- a/examples/foundational/05a-local-sync-speech-and-image.py +++ b/examples/foundational/05a-local-sync-speech-and-image.py @@ -49,7 +49,7 @@ async def main(): async def get_month_data(month): messages = [ { - "role": "system", + "role": "user", "content": f"Describe a nature photograph suitable for use in a calendar, for the month of {month}. Include only the image description with no preamble. Limit the description to one sentence, please.", } ] diff --git a/examples/foundational/06-listen-and-respond.py b/examples/foundational/06-listen-and-respond.py index 1e2f88a93..d2daff3fb 100644 --- a/examples/foundational/06-listen-and-respond.py +++ b/examples/foundational/06-listen-and-respond.py @@ -129,7 +129,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): async def on_client_connected(transport, client): logger.info(f"Client connected") # Kick off the conversation. - context.add_message({"role": "system", "content": "Please introduce yourself to the user."}) + context.add_message({"role": "user", "content": "Please introduce yourself to the user."}) await task.queue_frames([LLMRunFrame()]) @transport.event_handler("on_client_disconnected") diff --git a/examples/foundational/07-interruptible-cartesia-http.py b/examples/foundational/07-interruptible-cartesia-http.py index ac409f55d..56a06f2e9 100644 --- a/examples/foundational/07-interruptible-cartesia-http.py +++ b/examples/foundational/07-interruptible-cartesia-http.py @@ -103,7 +103,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): logger.info(f"Client connected") # Kick off the conversation. context.add_message( - {"role": "system", "content": "Please introduce yourself to the user."} + {"role": "user", "content": "Please introduce yourself to the user."} ) await task.queue_frames([LLMRunFrame()]) diff --git a/examples/foundational/07-interruptible.py b/examples/foundational/07-interruptible.py index 05a751a68..cf9c5af96 100644 --- a/examples/foundational/07-interruptible.py +++ b/examples/foundational/07-interruptible.py @@ -99,7 +99,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): async def on_client_connected(transport, client): logger.info(f"Client connected") # Kick off the conversation. - context.add_message({"role": "system", "content": "Please introduce yourself to the user."}) + context.add_message({"role": "user", "content": "Please introduce yourself to the user."}) await task.queue_frames([LLMRunFrame()]) @transport.event_handler("on_client_disconnected") diff --git a/examples/foundational/07a-interruptible-speechmatics-vad.py b/examples/foundational/07a-interruptible-speechmatics-vad.py index a6a287f83..2ede06e4f 100644 --- a/examples/foundational/07a-interruptible-speechmatics-vad.py +++ b/examples/foundational/07a-interruptible-speechmatics-vad.py @@ -149,7 +149,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): async def on_client_connected(transport, client): logger.info(f"Client connected") # Kick off the conversation. - context.add_message({"role": "system", "content": "Say a short hello to the user."}) + context.add_message({"role": "user", "content": "Say a short hello to the user."}) await task.queue_frames([LLMRunFrame()]) @transport.event_handler("on_client_disconnected") diff --git a/examples/foundational/07a-interruptible-speechmatics.py b/examples/foundational/07a-interruptible-speechmatics.py index d4e4dc638..bee3410e3 100644 --- a/examples/foundational/07a-interruptible-speechmatics.py +++ b/examples/foundational/07a-interruptible-speechmatics.py @@ -129,7 +129,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): async def on_client_connected(transport, client): logger.info(f"Client connected") # Kick off the conversation. - context.add_message({"role": "system", "content": "Say a short hello to the user."}) + context.add_message({"role": "user", "content": "Say a short hello to the user."}) await task.queue_frames([LLMRunFrame()]) @transport.event_handler("on_client_disconnected") diff --git a/examples/foundational/07c-interruptible-deepgram-flux.py b/examples/foundational/07c-interruptible-deepgram-flux.py index c205c5141..a356a81cc 100644 --- a/examples/foundational/07c-interruptible-deepgram-flux.py +++ b/examples/foundational/07c-interruptible-deepgram-flux.py @@ -109,7 +109,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): async def on_client_connected(transport, client): logger.info(f"Client connected") # Kick off the conversation. - context.add_message({"role": "system", "content": "Please introduce yourself to the user."}) + context.add_message({"role": "user", "content": "Please introduce yourself to the user."}) await task.queue_frames([LLMRunFrame()]) @transport.event_handler("on_client_disconnected") diff --git a/examples/foundational/07c-interruptible-deepgram-http.py b/examples/foundational/07c-interruptible-deepgram-http.py index b4d829e96..fa8b6712c 100644 --- a/examples/foundational/07c-interruptible-deepgram-http.py +++ b/examples/foundational/07c-interruptible-deepgram-http.py @@ -104,7 +104,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): logger.info(f"Client connected") # Kick off the conversation. context.add_message( - {"role": "system", "content": "Please introduce yourself to the user."} + {"role": "user", "content": "Please introduce yourself to the user."} ) await task.queue_frames([LLMRunFrame()]) diff --git a/examples/foundational/07c-interruptible-deepgram-vad.py b/examples/foundational/07c-interruptible-deepgram-vad.py index 4af1b0c72..7a0ccb441 100644 --- a/examples/foundational/07c-interruptible-deepgram-vad.py +++ b/examples/foundational/07c-interruptible-deepgram-vad.py @@ -106,7 +106,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): async def on_client_connected(transport, client): logger.info(f"Client connected") # Kick off the conversation. - context.add_message({"role": "system", "content": "Please introduce yourself to the user."}) + context.add_message({"role": "user", "content": "Please introduce yourself to the user."}) await task.queue_frames([LLMRunFrame()]) @transport.event_handler("on_client_disconnected") diff --git a/examples/foundational/07c-interruptible-deepgram.py b/examples/foundational/07c-interruptible-deepgram.py index 1a10c0b28..521890f68 100644 --- a/examples/foundational/07c-interruptible-deepgram.py +++ b/examples/foundational/07c-interruptible-deepgram.py @@ -100,7 +100,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): async def on_client_connected(transport, client): logger.info(f"Client connected") # Kick off the conversation. - context.add_message({"role": "system", "content": "Please introduce yourself to the user."}) + context.add_message({"role": "user", "content": "Please introduce yourself to the user."}) await task.queue_frames([LLMRunFrame()]) @transport.event_handler("on_client_disconnected") diff --git a/examples/foundational/07d-interruptible-elevenlabs-http.py b/examples/foundational/07d-interruptible-elevenlabs-http.py index a7f68a599..279f6c8a2 100644 --- a/examples/foundational/07d-interruptible-elevenlabs-http.py +++ b/examples/foundational/07d-interruptible-elevenlabs-http.py @@ -108,7 +108,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): logger.info(f"Client connected") # Kick off the conversation. context.add_message( - {"role": "system", "content": "Please introduce yourself to the user."} + {"role": "user", "content": "Please introduce yourself to the user."} ) await task.queue_frames([LLMRunFrame()]) diff --git a/examples/foundational/07d-interruptible-elevenlabs.py b/examples/foundational/07d-interruptible-elevenlabs.py index ec62eac4d..14e21e851 100644 --- a/examples/foundational/07d-interruptible-elevenlabs.py +++ b/examples/foundational/07d-interruptible-elevenlabs.py @@ -100,7 +100,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): async def on_client_connected(transport, client): logger.info(f"Client connected") # Kick off the conversation. - context.add_message({"role": "system", "content": "Please introduce yourself to the user."}) + context.add_message({"role": "user", "content": "Please introduce yourself to the user."}) await task.queue_frames([LLMRunFrame()]) @transport.event_handler("on_client_disconnected") diff --git a/examples/foundational/07f-interruptible-azure-http.py b/examples/foundational/07f-interruptible-azure-http.py index 38b840d6a..407022f75 100644 --- a/examples/foundational/07f-interruptible-azure-http.py +++ b/examples/foundational/07f-interruptible-azure-http.py @@ -102,7 +102,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): async def on_client_connected(transport, client): logger.info(f"Client connected") # Kick off the conversation. - context.add_message({"role": "system", "content": "Please introduce yourself to the user."}) + context.add_message({"role": "user", "content": "Please introduce yourself to the user."}) await task.queue_frames([LLMRunFrame()]) @transport.event_handler("on_client_disconnected") diff --git a/examples/foundational/07f-interruptible-azure.py b/examples/foundational/07f-interruptible-azure.py index 7dafd8e1e..7e47e1c3e 100644 --- a/examples/foundational/07f-interruptible-azure.py +++ b/examples/foundational/07f-interruptible-azure.py @@ -102,7 +102,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): async def on_client_connected(transport, client): logger.info(f"Client connected") # Kick off the conversation. - context.add_message({"role": "system", "content": "Please introduce yourself to the user."}) + context.add_message({"role": "user", "content": "Please introduce yourself to the user."}) await task.queue_frames([LLMRunFrame()]) @transport.event_handler("on_client_disconnected") diff --git a/examples/foundational/07g-interruptible-openai-http.py b/examples/foundational/07g-interruptible-openai-http.py index 2b841be6a..ee0071bcb 100644 --- a/examples/foundational/07g-interruptible-openai-http.py +++ b/examples/foundational/07g-interruptible-openai-http.py @@ -106,7 +106,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): async def on_client_connected(transport, client): logger.info(f"Client connected") # Kick off the conversation. - context.add_message({"role": "system", "content": "Please introduce yourself to the user."}) + context.add_message({"role": "user", "content": "Please introduce yourself to the user."}) await task.queue_frames([LLMRunFrame()]) @transport.event_handler("on_client_disconnected") diff --git a/examples/foundational/07g-interruptible-openai.py b/examples/foundational/07g-interruptible-openai.py index 776feeb17..89d57fa70 100644 --- a/examples/foundational/07g-interruptible-openai.py +++ b/examples/foundational/07g-interruptible-openai.py @@ -108,7 +108,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): async def on_client_connected(transport, client): logger.info(f"Client connected") # Kick off the conversation. - context.add_message({"role": "system", "content": "Please introduce yourself to the user."}) + context.add_message({"role": "user", "content": "Please introduce yourself to the user."}) await task.queue_frames([LLMRunFrame()]) @transport.event_handler("on_client_disconnected") diff --git a/examples/foundational/07h-interruptible-openpipe.py b/examples/foundational/07h-interruptible-openpipe.py index f7cd4d7d9..f744fee4e 100644 --- a/examples/foundational/07h-interruptible-openpipe.py +++ b/examples/foundational/07h-interruptible-openpipe.py @@ -103,7 +103,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): async def on_client_connected(transport, client): logger.info(f"Client connected") # Kick off the conversation. - context.add_message({"role": "system", "content": "Please introduce yourself to the user."}) + context.add_message({"role": "user", "content": "Please introduce yourself to the user."}) await task.queue_frames([LLMRunFrame()]) @transport.event_handler("on_client_disconnected") diff --git a/examples/foundational/07i-interruptible-xtts.py b/examples/foundational/07i-interruptible-xtts.py index 76f139cbf..40845fac0 100644 --- a/examples/foundational/07i-interruptible-xtts.py +++ b/examples/foundational/07i-interruptible-xtts.py @@ -104,7 +104,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): logger.info(f"Client connected") # Kick off the conversation. context.add_message( - {"role": "system", "content": "Please introduce yourself to the user."} + {"role": "user", "content": "Please introduce yourself to the user."} ) await task.queue_frames([LLMRunFrame()]) diff --git a/examples/foundational/07j-interruptible-gladia-vad.py b/examples/foundational/07j-interruptible-gladia-vad.py index 3bc0c0404..ca2687d43 100644 --- a/examples/foundational/07j-interruptible-gladia-vad.py +++ b/examples/foundational/07j-interruptible-gladia-vad.py @@ -114,7 +114,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): async def on_client_connected(transport, client): logger.info(f"Client connected") # Kick off the conversation. - context.add_message({"role": "system", "content": "Please introduce yourself to the user."}) + context.add_message({"role": "user", "content": "Please introduce yourself to the user."}) await task.queue_frames([LLMRunFrame()]) @transport.event_handler("on_client_disconnected") diff --git a/examples/foundational/07j-interruptible-gladia.py b/examples/foundational/07j-interruptible-gladia.py index 781e20942..42ee1b1cc 100644 --- a/examples/foundational/07j-interruptible-gladia.py +++ b/examples/foundational/07j-interruptible-gladia.py @@ -109,7 +109,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): async def on_client_connected(transport, client): logger.info(f"Client connected") # Kick off the conversation. - context.add_message({"role": "system", "content": "Please introduce yourself to the user."}) + context.add_message({"role": "user", "content": "Please introduce yourself to the user."}) await task.queue_frames([LLMRunFrame()]) @transport.event_handler("on_client_disconnected") diff --git a/examples/foundational/07k-interruptible-lmnt.py b/examples/foundational/07k-interruptible-lmnt.py index cab1bca81..091b72499 100644 --- a/examples/foundational/07k-interruptible-lmnt.py +++ b/examples/foundational/07k-interruptible-lmnt.py @@ -99,7 +99,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): async def on_client_connected(transport, client): logger.info(f"Client connected") # Kick off the conversation. - context.add_message({"role": "system", "content": "Please introduce yourself to the user."}) + context.add_message({"role": "user", "content": "Please introduce yourself to the user."}) await task.queue_frames([LLMRunFrame()]) @transport.event_handler("on_client_disconnected") diff --git a/examples/foundational/07l-interruptible-groq.py b/examples/foundational/07l-interruptible-groq.py index 3fe64a460..8d2125546 100644 --- a/examples/foundational/07l-interruptible-groq.py +++ b/examples/foundational/07l-interruptible-groq.py @@ -95,7 +95,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): async def on_client_connected(transport, client): logger.info(f"Client connected") # Kick off the conversation. - context.add_message({"role": "system", "content": "Please introduce yourself to the user."}) + context.add_message({"role": "user", "content": "Please introduce yourself to the user."}) await task.queue_frames([LLMRunFrame()]) @transport.event_handler("on_client_disconnected") diff --git a/examples/foundational/07n-interruptible-gemini-image.py b/examples/foundational/07n-interruptible-gemini-image.py index 072998fa9..96c7cfd47 100644 --- a/examples/foundational/07n-interruptible-gemini-image.py +++ b/examples/foundational/07n-interruptible-gemini-image.py @@ -124,7 +124,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): async def on_client_connected(transport, client): logger.info(f"Client connected") # Kick off the conversation with a styled introduction - context.add_message({"role": "system", "content": "Please introduce yourself to the user."}) + context.add_message({"role": "user", "content": "Please introduce yourself to the user."}) await task.queue_frames([LLMRunFrame()]) @transport.event_handler("on_client_disconnected") diff --git a/examples/foundational/07n-interruptible-gemini.py b/examples/foundational/07n-interruptible-gemini.py index a48efefad..a1d58a1cd 100644 --- a/examples/foundational/07n-interruptible-gemini.py +++ b/examples/foundational/07n-interruptible-gemini.py @@ -128,7 +128,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): # Kick off the conversation context.add_message( { - "role": "system", + "role": "user", "content": "You are an AI assistant. You can help with a variety of tasks. Introduce yourself and ask the user what they would like to know.", } ) diff --git a/examples/foundational/07n-interruptible-google-http.py b/examples/foundational/07n-interruptible-google-http.py index 0a6280618..a607653f7 100644 --- a/examples/foundational/07n-interruptible-google-http.py +++ b/examples/foundational/07n-interruptible-google-http.py @@ -111,7 +111,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): async def on_client_connected(transport, client): logger.info(f"Client connected") # Kick off the conversation. - context.add_message({"role": "system", "content": "Please introduce yourself to the user."}) + context.add_message({"role": "user", "content": "Please introduce yourself to the user."}) await task.queue_frames([LLMRunFrame()]) @transport.event_handler("on_client_disconnected") diff --git a/examples/foundational/07n-interruptible-google.py b/examples/foundational/07n-interruptible-google.py index d6c57b548..522d168e1 100644 --- a/examples/foundational/07n-interruptible-google.py +++ b/examples/foundational/07n-interruptible-google.py @@ -111,7 +111,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): async def on_client_connected(transport, client): logger.info(f"Client connected") # Kick off the conversation. - context.add_message({"role": "system", "content": "Please introduce yourself to the user."}) + context.add_message({"role": "user", "content": "Please introduce yourself to the user."}) await task.queue_frames([LLMRunFrame()]) @transport.event_handler("on_client_disconnected") diff --git a/examples/foundational/07o-interruptible-assemblyai-turn-detection.py b/examples/foundational/07o-interruptible-assemblyai-turn-detection.py index b15e3038f..114c6f263 100644 --- a/examples/foundational/07o-interruptible-assemblyai-turn-detection.py +++ b/examples/foundational/07o-interruptible-assemblyai-turn-detection.py @@ -153,7 +153,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): async def on_client_connected(transport, client): logger.info(f"Client connected") # Kick off the conversation. - context.add_message({"role": "system", "content": "Please introduce yourself to the user."}) + context.add_message({"role": "user", "content": "Please introduce yourself to the user."}) await task.queue_frames([LLMRunFrame()]) @transport.event_handler("on_client_disconnected") diff --git a/examples/foundational/07o-interruptible-assemblyai.py b/examples/foundational/07o-interruptible-assemblyai.py index 8e58ddbf3..9b60f3e98 100644 --- a/examples/foundational/07o-interruptible-assemblyai.py +++ b/examples/foundational/07o-interruptible-assemblyai.py @@ -102,7 +102,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): async def on_client_connected(transport, client): logger.info(f"Client connected") # Kick off the conversation. - context.add_message({"role": "system", "content": "Please introduce yourself to the user."}) + context.add_message({"role": "user", "content": "Please introduce yourself to the user."}) await task.queue_frames([LLMRunFrame()]) @transport.event_handler("on_client_disconnected") diff --git a/examples/foundational/07p-interruptible-krisp-viva.py b/examples/foundational/07p-interruptible-krisp-viva.py index 056a2f6cc..67a29bd89 100644 --- a/examples/foundational/07p-interruptible-krisp-viva.py +++ b/examples/foundational/07p-interruptible-krisp-viva.py @@ -134,7 +134,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): async def on_client_connected(transport, client): logger.info(f"Client connected") # Kick off the conversation. - context.add_message({"role": "system", "content": "Please introduce yourself to the user."}) + context.add_message({"role": "user", "content": "Please introduce yourself to the user."}) await task.queue_frames([LLMRunFrame()]) @transport.event_handler("on_client_disconnected") diff --git a/examples/foundational/07p-interruptible-krisp.py b/examples/foundational/07p-interruptible-krisp.py index b3ccfb30e..5b760e768 100644 --- a/examples/foundational/07p-interruptible-krisp.py +++ b/examples/foundational/07p-interruptible-krisp.py @@ -103,7 +103,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): async def on_client_connected(transport, client): logger.info(f"Client connected") # Kick off the conversation. - context.add_message({"role": "system", "content": "Please introduce yourself to the user."}) + context.add_message({"role": "user", "content": "Please introduce yourself to the user."}) await task.queue_frames([LLMRunFrame()]) @transport.event_handler("on_client_disconnected") diff --git a/examples/foundational/07q-interruptible-rime-http.py b/examples/foundational/07q-interruptible-rime-http.py index ebbdc6946..8324d546e 100644 --- a/examples/foundational/07q-interruptible-rime-http.py +++ b/examples/foundational/07q-interruptible-rime-http.py @@ -107,7 +107,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): logger.info(f"Client connected") # Kick off the conversation. context.add_message( - {"role": "system", "content": "Please introduce yourself to the user."} + {"role": "user", "content": "Please introduce yourself to the user."} ) await task.queue_frames([LLMRunFrame()]) diff --git a/examples/foundational/07q-interruptible-rime.py b/examples/foundational/07q-interruptible-rime.py index bfcf5da41..5379e9914 100644 --- a/examples/foundational/07q-interruptible-rime.py +++ b/examples/foundational/07q-interruptible-rime.py @@ -99,7 +99,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): async def on_client_connected(transport, client): logger.info(f"Client connected") # Kick off the conversation. - context.add_message({"role": "system", "content": "Please introduce yourself to the user."}) + context.add_message({"role": "user", "content": "Please introduce yourself to the user."}) await task.queue_frames([LLMRunFrame()]) @transport.event_handler("on_client_disconnected") diff --git a/examples/foundational/07r-interruptible-nvidia.py b/examples/foundational/07r-interruptible-nvidia.py index a5a477ba0..70c151f11 100644 --- a/examples/foundational/07r-interruptible-nvidia.py +++ b/examples/foundational/07r-interruptible-nvidia.py @@ -95,7 +95,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): async def on_client_connected(transport, client): logger.info(f"Client connected") # Kick off the conversation. - context.add_message({"role": "system", "content": "Please introduce yourself to the user."}) + context.add_message({"role": "user", "content": "Please introduce yourself to the user."}) await task.queue_frames([LLMRunFrame()]) @transport.event_handler("on_client_disconnected") diff --git a/examples/foundational/07s-interruptible-google-audio-in.py b/examples/foundational/07s-interruptible-google-audio-in.py index d4067b620..31bfbcc35 100644 --- a/examples/foundational/07s-interruptible-google-audio-in.py +++ b/examples/foundational/07s-interruptible-google-audio-in.py @@ -218,11 +218,10 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): api_key=os.getenv("GOOGLE_API_KEY"), settings=GoogleLLMSettings( model="gemini-2.5-flash", + system_instruction=system_message, + # force a certain amount of thinking if you want it + # thinking=GoogleLLMService.ThinkingConfig(thinking_budget=4096) ), - # force a certain amount of thinking if you want it - # params=GoogleLLMService.InputParams( - # thinking=GoogleLLMService.ThinkingConfig(thinking_budget=4096) - # ), ) tts = GoogleTTSService( @@ -234,18 +233,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): credentials=os.getenv("GOOGLE_TEST_CREDENTIALS"), ) - messages = [ - { - "role": "system", - "content": system_message, - }, - { - "role": "user", - "content": "Start by saying hello.", - }, - ] - - context = LLMContext(messages) + context = LLMContext() user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()), @@ -281,7 +269,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): async def on_client_connected(transport, client): logger.info(f"Client connected") # Kick off the conversation. - messages.append({"role": "system", "content": "Please introduce yourself to the user."}) + context.add_message({"role": "user", "content": "Please introduce yourself to the user."}) await task.queue_frames([LLMRunFrame()]) @transport.event_handler("on_client_disconnected") diff --git a/examples/foundational/07t-interruptible-fish.py b/examples/foundational/07t-interruptible-fish.py index 4825c3110..e7aeb993b 100644 --- a/examples/foundational/07t-interruptible-fish.py +++ b/examples/foundational/07t-interruptible-fish.py @@ -100,7 +100,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): async def on_client_connected(transport, client): logger.info(f"Client connected") # Kick off the conversation. - context.add_message({"role": "system", "content": "Please introduce yourself to the user."}) + context.add_message({"role": "user", "content": "Please introduce yourself to the user."}) await task.queue_frames([LLMRunFrame()]) @transport.event_handler("on_client_disconnected") diff --git a/examples/foundational/07v-interruptible-neuphonic-http.py b/examples/foundational/07v-interruptible-neuphonic-http.py index 5c2934fcd..8ebfe9002 100644 --- a/examples/foundational/07v-interruptible-neuphonic-http.py +++ b/examples/foundational/07v-interruptible-neuphonic-http.py @@ -105,7 +105,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): logger.info(f"Client connected") # Kick off the conversation. context.add_message( - {"role": "system", "content": "Please introduce yourself to the user."} + {"role": "user", "content": "Please introduce yourself to the user."} ) await task.queue_frames([LLMRunFrame()]) diff --git a/examples/foundational/07v-interruptible-neuphonic.py b/examples/foundational/07v-interruptible-neuphonic.py index d70b187a7..8eee009f3 100644 --- a/examples/foundational/07v-interruptible-neuphonic.py +++ b/examples/foundational/07v-interruptible-neuphonic.py @@ -99,7 +99,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): async def on_client_connected(transport, client): logger.info(f"Client connected") # Kick off the conversation. - context.add_message({"role": "system", "content": "Please introduce yourself to the user."}) + context.add_message({"role": "user", "content": "Please introduce yourself to the user."}) await task.queue_frames([LLMRunFrame()]) @transport.event_handler("on_client_disconnected") diff --git a/examples/foundational/07w-interruptible-fal.py b/examples/foundational/07w-interruptible-fal.py index 6539cbfc9..81045df5f 100644 --- a/examples/foundational/07w-interruptible-fal.py +++ b/examples/foundational/07w-interruptible-fal.py @@ -106,7 +106,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): logger.info(f"Client connected") # Kick off the conversation. context.add_message( - {"role": "system", "content": "Please introduce yourself to the user."} + {"role": "user", "content": "Please introduce yourself to the user."} ) await task.queue_frames([LLMRunFrame()]) diff --git a/examples/foundational/07x-interruptible-local.py b/examples/foundational/07x-interruptible-local.py index e0eeee03b..0e5107890 100644 --- a/examples/foundational/07x-interruptible-local.py +++ b/examples/foundational/07x-interruptible-local.py @@ -82,7 +82,7 @@ async def main(): ), ) - context.add_message({"role": "system", "content": "Please introduce yourself to the user."}) + context.add_message({"role": "user", "content": "Please introduce yourself to the user."}) await task.queue_frames([LLMRunFrame()]) runner = PipelineRunner() diff --git a/examples/foundational/07y-interruptible-minimax.py b/examples/foundational/07y-interruptible-minimax.py index 1213291e0..64fe7da06 100644 --- a/examples/foundational/07y-interruptible-minimax.py +++ b/examples/foundational/07y-interruptible-minimax.py @@ -107,7 +107,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): logger.info(f"Client connected") # Kick off the conversation. context.add_message( - {"role": "system", "content": "Please introduce yourself to the user."} + {"role": "user", "content": "Please introduce yourself to the user."} ) await task.queue_frames([LLMRunFrame()]) diff --git a/examples/foundational/07z-interruptible-sarvam-http.py b/examples/foundational/07z-interruptible-sarvam-http.py index 566cea75a..4a0baa65c 100644 --- a/examples/foundational/07z-interruptible-sarvam-http.py +++ b/examples/foundational/07z-interruptible-sarvam-http.py @@ -109,7 +109,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): logger.info(f"Client connected") # Kick off the conversation. context.add_message( - {"role": "system", "content": "Please introduce yourself to the user."} + {"role": "user", "content": "Please introduce yourself to the user."} ) await task.queue_frames([LLMRunFrame()]) diff --git a/examples/foundational/07z-interruptible-sarvam.py b/examples/foundational/07z-interruptible-sarvam.py index 827ce947f..e366b4d31 100644 --- a/examples/foundational/07z-interruptible-sarvam.py +++ b/examples/foundational/07z-interruptible-sarvam.py @@ -103,7 +103,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): async def on_client_connected(transport, client): logger.info(f"Client connected") # Kick off the conversation. - context.add_message({"role": "system", "content": "Please introduce yourself to the user."}) + context.add_message({"role": "user", "content": "Please introduce yourself to the user."}) await task.queue_frames([LLMRunFrame()]) # Optionally, you can wait for 30 seconds and then change the voice. diff --git a/examples/foundational/07za-interruptible-soniox.py b/examples/foundational/07za-interruptible-soniox.py index 380033a11..78e3ac873 100644 --- a/examples/foundational/07za-interruptible-soniox.py +++ b/examples/foundational/07za-interruptible-soniox.py @@ -105,7 +105,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): async def on_client_connected(transport, client): logger.info(f"Client connected") # Kick off the conversation. - context.add_message({"role": "system", "content": "Please introduce yourself to the user."}) + context.add_message({"role": "user", "content": "Please introduce yourself to the user."}) await task.queue_frames([LLMRunFrame()]) @transport.event_handler("on_client_disconnected") diff --git a/examples/foundational/07zb-interruptible-inworld-http.py b/examples/foundational/07zb-interruptible-inworld-http.py index 1376ab8da..6e57fbb56 100644 --- a/examples/foundational/07zb-interruptible-inworld-http.py +++ b/examples/foundational/07zb-interruptible-inworld-http.py @@ -112,7 +112,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): logger.info("Client connected") # Kick off the conversation. context.add_message( - {"role": "system", "content": "Please introduce yourself to the user."} + {"role": "user", "content": "Please introduce yourself to the user."} ) await task.queue_frames([LLMRunFrame()]) diff --git a/examples/foundational/07zb-interruptible-inworld.py b/examples/foundational/07zb-interruptible-inworld.py index 9c9895ca9..0865a4e92 100644 --- a/examples/foundational/07zb-interruptible-inworld.py +++ b/examples/foundational/07zb-interruptible-inworld.py @@ -108,7 +108,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): async def on_client_connected(transport, client): logger.info("Client connected") # Kick off the conversation. - context.add_message({"role": "system", "content": "Please introduce yourself to the user."}) + context.add_message({"role": "user", "content": "Please introduce yourself to the user."}) await task.queue_frames([LLMRunFrame()]) @transport.event_handler("on_client_disconnected") diff --git a/examples/foundational/07zc-interruptible-asyncai-http.py b/examples/foundational/07zc-interruptible-asyncai-http.py index b3f46f671..1fe69c38b 100644 --- a/examples/foundational/07zc-interruptible-asyncai-http.py +++ b/examples/foundational/07zc-interruptible-asyncai-http.py @@ -105,7 +105,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): logger.info(f"Client connected") # Kick off the conversation. context.add_message( - {"role": "system", "content": "Please introduce yourself to the user."} + {"role": "user", "content": "Please introduce yourself to the user."} ) await task.queue_frames([LLMRunFrame()]) diff --git a/examples/foundational/07zc-interruptible-asyncai.py b/examples/foundational/07zc-interruptible-asyncai.py index b95a55ddb..05113cdb9 100644 --- a/examples/foundational/07zc-interruptible-asyncai.py +++ b/examples/foundational/07zc-interruptible-asyncai.py @@ -100,7 +100,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): async def on_client_connected(transport, client): logger.info(f"Client connected") # Kick off the conversation. - context.add_message({"role": "system", "content": "Please introduce yourself to the user."}) + context.add_message({"role": "user", "content": "Please introduce yourself to the user."}) await task.queue_frames([LLMRunFrame()]) @transport.event_handler("on_client_disconnected") diff --git a/examples/foundational/07zd-interruptible-aicoustics.py b/examples/foundational/07zd-interruptible-aicoustics.py index 481e098a2..e8f55e4e0 100644 --- a/examples/foundational/07zd-interruptible-aicoustics.py +++ b/examples/foundational/07zd-interruptible-aicoustics.py @@ -128,7 +128,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): logger.info(f"Client connected") await audiobuffer.start_recording() # Kick off the conversation. - context.add_message({"role": "system", "content": "Please introduce yourself to the user."}) + context.add_message({"role": "user", "content": "Please introduce yourself to the user."}) await task.queue_frames([LLMRunFrame()]) @audiobuffer.event_handler("on_audio_data") diff --git a/examples/foundational/07ze-interruptible-hume.py b/examples/foundational/07ze-interruptible-hume.py index c5c352232..fbe752a7d 100644 --- a/examples/foundational/07ze-interruptible-hume.py +++ b/examples/foundational/07ze-interruptible-hume.py @@ -113,7 +113,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): "💡 Word timestamps are enabled! Watch the console for TTSTextFrame logs showing each word with its PTS." ) # Kick off the conversation. - context.add_message({"role": "system", "content": "Please introduce yourself to the user."}) + context.add_message({"role": "user", "content": "Please introduce yourself to the user."}) await task.queue_frames([LLMRunFrame()]) @transport.event_handler("on_client_disconnected") diff --git a/examples/foundational/07zf-interruptible-gradium.py b/examples/foundational/07zf-interruptible-gradium.py index acf168f13..41cdcd799 100644 --- a/examples/foundational/07zf-interruptible-gradium.py +++ b/examples/foundational/07zf-interruptible-gradium.py @@ -106,7 +106,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): async def on_client_connected(transport, client): logger.info(f"Client connected") # Kick off the conversation. - context.add_message({"role": "system", "content": "Please introduce yourself to the user."}) + context.add_message({"role": "user", "content": "Please introduce yourself to the user."}) await task.queue_frames([LLMRunFrame()]) @transport.event_handler("on_client_disconnected") diff --git a/examples/foundational/07zg-interruptible-camb.py b/examples/foundational/07zg-interruptible-camb.py index e8d5011e2..20bc8b665 100644 --- a/examples/foundational/07zg-interruptible-camb.py +++ b/examples/foundational/07zg-interruptible-camb.py @@ -99,7 +99,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): @transport.event_handler("on_client_connected") async def on_client_connected(transport, client): logger.info("Client connected") - context.add_message({"role": "system", "content": "Please introduce yourself to the user."}) + context.add_message({"role": "user", "content": "Please introduce yourself to the user."}) await task.queue_frames([LLMRunFrame()]) @transport.event_handler("on_client_disconnected") diff --git a/examples/foundational/07zi-interruptible-piper.py b/examples/foundational/07zi-interruptible-piper.py index 9ac672fc2..f6d9bfeea 100644 --- a/examples/foundational/07zi-interruptible-piper.py +++ b/examples/foundational/07zi-interruptible-piper.py @@ -98,7 +98,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): async def on_client_connected(transport, client): logger.info(f"Client connected") # Kick off the conversation. - context.add_message({"role": "system", "content": "Please introduce yourself to the user."}) + context.add_message({"role": "user", "content": "Please introduce yourself to the user."}) await task.queue_frames([LLMRunFrame()]) @transport.event_handler("on_client_disconnected") diff --git a/examples/foundational/07zj-interruptible-kokoro.py b/examples/foundational/07zj-interruptible-kokoro.py index 66a225d35..da35b5d5c 100644 --- a/examples/foundational/07zj-interruptible-kokoro.py +++ b/examples/foundational/07zj-interruptible-kokoro.py @@ -98,7 +98,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): async def on_client_connected(transport, client): logger.info(f"Client connected") # Kick off the conversation. - context.add_message({"role": "system", "content": "Please introduce yourself to the user."}) + context.add_message({"role": "user", "content": "Please introduce yourself to the user."}) await task.queue_frames([LLMRunFrame()]) @transport.event_handler("on_client_disconnected") diff --git a/examples/foundational/07zk-interruptible-resemble.py b/examples/foundational/07zk-interruptible-resemble.py index 2212fa80f..c186db6be 100644 --- a/examples/foundational/07zk-interruptible-resemble.py +++ b/examples/foundational/07zk-interruptible-resemble.py @@ -102,7 +102,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): async def on_client_connected(transport, client): logger.info(f"Client connected") # Kick off the conversation. - context.add_message({"role": "system", "content": "Please introduce yourself to the user."}) + context.add_message({"role": "user", "content": "Please introduce yourself to the user."}) await task.queue_frames([LLMRunFrame()]) @transport.event_handler("on_client_disconnected") diff --git a/examples/foundational/08-custom-frame-processor.py b/examples/foundational/08-custom-frame-processor.py index 820659207..507de6d41 100644 --- a/examples/foundational/08-custom-frame-processor.py +++ b/examples/foundational/08-custom-frame-processor.py @@ -141,7 +141,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): async def on_client_connected(transport, client): logger.info(f"Client connected: {client}") # Kick off the conversation. - context.add_message({"role": "system", "content": "Please introduce yourself to the user."}) + context.add_message({"role": "user", "content": "Please introduce yourself to the user."}) await task.queue_frames([LLMRunFrame()]) @transport.event_handler("on_client_disconnected") diff --git a/examples/foundational/10-wake-phrase.py b/examples/foundational/10-wake-phrase.py index de237659a..04a1e40b8 100644 --- a/examples/foundational/10-wake-phrase.py +++ b/examples/foundational/10-wake-phrase.py @@ -104,7 +104,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): # Kick off the conversation. context.add_message( { - "role": "system", + "role": "user", "content": "Please introduce yourself. Tell the user they should say 'Hey Robot' before talking to you.", } ) diff --git a/examples/foundational/14a-function-calling-anthropic.py b/examples/foundational/14a-function-calling-anthropic.py index 19bc314b8..efcaba47e 100644 --- a/examples/foundational/14a-function-calling-anthropic.py +++ b/examples/foundational/14a-function-calling-anthropic.py @@ -138,6 +138,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): async def on_client_connected(transport, client): logger.info(f"Client connected") # Kick off the conversation. + context.add_message({"role": "user", "content": "Please introduce yourself to the user."}) await task.queue_frames([LLMRunFrame()]) @transport.event_handler("on_client_disconnected") diff --git a/examples/foundational/14d-function-calling-anthropic-video.py b/examples/foundational/14d-function-calling-anthropic-video.py index f1e097902..136a7f110 100644 --- a/examples/foundational/14d-function-calling-anthropic-video.py +++ b/examples/foundational/14d-function-calling-anthropic-video.py @@ -164,7 +164,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): # Kick off the conversation. context.add_message( { - "role": "system", + "role": "user", "content": f"Please introduce yourself to the user. Use '{client_id}' as the user ID during function calls.", } ) diff --git a/examples/foundational/14d-function-calling-aws-video.py b/examples/foundational/14d-function-calling-aws-video.py index 09ceaedd4..358c6f7f0 100644 --- a/examples/foundational/14d-function-calling-aws-video.py +++ b/examples/foundational/14d-function-calling-aws-video.py @@ -169,7 +169,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): # Kick off the conversation. context.add_message( { - "role": "system", + "role": "user", "content": f"Please introduce yourself to the user. Use '{client_id}' as the user ID during function calls.", } ) diff --git a/examples/foundational/14d-function-calling-gemini-flash-video.py b/examples/foundational/14d-function-calling-gemini-flash-video.py index a56349f96..b261a8922 100644 --- a/examples/foundational/14d-function-calling-gemini-flash-video.py +++ b/examples/foundational/14d-function-calling-gemini-flash-video.py @@ -164,7 +164,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): # Kick off the conversation. context.add_message( { - "role": "system", + "role": "user", "content": f"Please introduce yourself to the user. Use '{client_id}' as the user ID during function calls.", } ) diff --git a/examples/foundational/14d-function-calling-moondream-video.py b/examples/foundational/14d-function-calling-moondream-video.py index c32bf3549..9de08ce05 100644 --- a/examples/foundational/14d-function-calling-moondream-video.py +++ b/examples/foundational/14d-function-calling-moondream-video.py @@ -202,7 +202,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): # Kick off the conversation. context.add_message( { - "role": "system", + "role": "user", "content": f"Please introduce yourself to the user. Use '{client_id}' as the user ID during function calls.", } ) diff --git a/examples/foundational/14d-function-calling-openai-video.py b/examples/foundational/14d-function-calling-openai-video.py index 5bfa336aa..8c6416617 100644 --- a/examples/foundational/14d-function-calling-openai-video.py +++ b/examples/foundational/14d-function-calling-openai-video.py @@ -163,7 +163,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): # Kick off the conversation. context.add_message( { - "role": "system", + "role": "user", "content": f"Please introduce yourself to the user. Use '{client_id}' as the user ID during function calls.", } ) diff --git a/examples/foundational/14i-function-calling-fireworks.py b/examples/foundational/14i-function-calling-fireworks.py index aad4b6ecf..23d971324 100644 --- a/examples/foundational/14i-function-calling-fireworks.py +++ b/examples/foundational/14i-function-calling-fireworks.py @@ -136,7 +136,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): async def on_client_connected(transport, client): logger.info(f"Client connected") # Kick off the conversation. - context.add_message({"role": "system", "content": "Please introduce yourself to the user."}) + context.add_message({"role": "user", "content": "Please introduce yourself to the user."}) await task.queue_frames([LLMRunFrame()]) @transport.event_handler("on_client_disconnected") diff --git a/examples/foundational/15-switch-voices.py b/examples/foundational/15-switch-voices.py index c298aaf0f..40f2202de 100644 --- a/examples/foundational/15-switch-voices.py +++ b/examples/foundational/15-switch-voices.py @@ -172,7 +172,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): # Kick off the conversation. context.add_message( { - "role": "system", + "role": "user", "content": f"Please introduce yourself to the user and let them know the voices you can do. Your initial responses should be as if you were a {tts.current_voice}.", } ) diff --git a/examples/foundational/15a-switch-languages.py b/examples/foundational/15a-switch-languages.py index c19038ea2..c514d9a5d 100644 --- a/examples/foundational/15a-switch-languages.py +++ b/examples/foundational/15a-switch-languages.py @@ -160,7 +160,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): # Kick off the conversation. context.add_message( { - "role": "system", + "role": "user", "content": f"Please introduce yourself to the user and let them know the languages you speak. Your initial responses should be in {tts.current_language}.", } ) diff --git a/examples/foundational/16-gpu-container-local-bot.py b/examples/foundational/16-gpu-container-local-bot.py index 103b5216f..c1d267df3 100644 --- a/examples/foundational/16-gpu-container-local-bot.py +++ b/examples/foundational/16-gpu-container-local-bot.py @@ -109,7 +109,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): async def on_client_connected(transport, client): logger.info(f"Client connected") # Kick off the conversation. - context.add_message({"role": "system", "content": "Please introduce yourself to the user."}) + context.add_message({"role": "user", "content": "Please introduce yourself to the user."}) await task.queue_frames([LLMRunFrame()]) # Handle "latency-ping" messages. The client will send app messages that look like diff --git a/examples/foundational/17-detect-user-idle.py b/examples/foundational/17-detect-user-idle.py index ecb7ceea1..90434c77b 100644 --- a/examples/foundational/17-detect-user-idle.py +++ b/examples/foundational/17-detect-user-idle.py @@ -60,14 +60,14 @@ class IdleHandler: if self._retry_count == 1: # First attempt: Add a gentle prompt to the conversation message = { - "role": "system", + "role": "user", "content": "The user has been quiet. Politely and briefly ask if they're still there.", } await aggregator.push_frame(LLMMessagesAppendFrame([message], run_llm=True)) elif self._retry_count == 2: # Second attempt: More direct prompt message = { - "role": "system", + "role": "user", "content": "The user is still inactive. Ask if they'd like to continue our conversation.", } await aggregator.push_frame(LLMMessagesAppendFrame([message], run_llm=True)) @@ -209,7 +209,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): async def on_client_connected(transport, client): logger.info(f"Client connected") # Kick off the conversation. - context.add_message({"role": "system", "content": "Please introduce yourself to the user."}) + context.add_message({"role": "user", "content": "Please introduce yourself to the user."}) await task.queue_frames([LLMRunFrame()]) await asyncio.sleep(30) logger.info(f"Disabling idle detection") diff --git a/examples/foundational/20a-persistent-context-openai.py b/examples/foundational/20a-persistent-context-openai.py index acdcefb92..691893336 100644 --- a/examples/foundational/20a-persistent-context-openai.py +++ b/examples/foundational/20a-persistent-context-openai.py @@ -95,12 +95,7 @@ async def load_conversation(params: FunctionCallParams): await params.result_callback({"success": False, "error": str(e)}) -messages = [ - { - "role": "system", - "content": "You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", - }, -] +system_instruction = "You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way." weather_function = FunctionSchema( name="get_current_weather", @@ -185,7 +180,10 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): ), ) - llm = OpenAILLMService(api_key=os.getenv("OPENAI_API_KEY")) + llm = OpenAILLMService( + api_key=os.getenv("OPENAI_API_KEY"), + system_instruction=system_instruction, + ) # you can either register a single function for all function calls, or specific functions # llm.register_function(None, fetch_weather_from_api) @@ -194,7 +192,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): llm.register_function("get_saved_conversation_filenames", get_saved_conversation_filenames) llm.register_function("load_conversation", load_conversation) - context = LLMContext(messages, tools) + context = LLMContext(tools=tools) user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()), diff --git a/examples/foundational/20b-persistent-context-openai-realtime-beta.py b/examples/foundational/20b-persistent-context-openai-realtime-beta.py index cb4ffa642..fa59e1674 100644 --- a/examples/foundational/20b-persistent-context-openai-realtime-beta.py +++ b/examples/foundational/20b-persistent-context-openai-realtime-beta.py @@ -31,7 +31,6 @@ from pipecat.services.openai_realtime_beta import ( SessionProperties, TurnDetection, ) -from pipecat.services.openai_realtime_beta.events import AudioConfiguration, AudioInput from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams @@ -182,16 +181,12 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): stt = DeepgramSTTService(api_key=os.getenv("DEEPGRAM_API_KEY")) session_properties = SessionProperties( - audio=AudioConfiguration( - input=AudioInput( - transcription=InputAudioTranscription(), - # Set openai TurnDetection parameters. Not setting this at all will turn it - # on by default - turn_detection=TurnDetection(silence_duration_ms=1000), - # Or set to False to disable openai turn detection and use transport VAD - # turn_detection=False, - ) - ), + input_audio_transcription=InputAudioTranscription(), + # Set openai TurnDetection parameters. Not setting this at all will turn + # it on by default + turn_detection=TurnDetection(silence_duration_ms=1000), + # Or set to False to disable openai turn detection and use transport VAD + # turn_detection=False, # tools=tools, instructions="""Your knowledge cutoff is 2023-10. You are a helpful and friendly AI. diff --git a/examples/foundational/20c-persistent-context-anthropic.py b/examples/foundational/20c-persistent-context-anthropic.py index 5f2a3f317..78ab3a7bc 100644 --- a/examples/foundational/20c-persistent-context-anthropic.py +++ b/examples/foundational/20c-persistent-context-anthropic.py @@ -26,7 +26,7 @@ from pipecat.processors.aggregators.llm_response_universal import ( ) from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport -from pipecat.services.anthropic.llm import AnthropicLLMService +from pipecat.services.anthropic.llm import AnthropicLLMService, AnthropicLLMSettings from pipecat.services.cartesia.tts import CartesiaTTSService, CartesiaTTSSettings from pipecat.services.deepgram.stt import DeepgramSTTService from pipecat.services.llm_service import FunctionCallParams @@ -38,7 +38,6 @@ load_dotenv(override=True) BASE_FILENAME = "/tmp/pipecat_conversation_" -tts = None async def fetch_weather_from_api(params: FunctionCallParams): @@ -82,7 +81,6 @@ async def save_conversation(params: FunctionCallParams): async def load_conversation(params: FunctionCallParams): - global tts filename = params.arguments["filename"] logger.debug(f"loading conversation from {filename}") try: @@ -96,18 +94,7 @@ async def load_conversation(params: FunctionCallParams): await params.result_callback({"success": False, "error": str(e)}) -# Test message munging ... -messages = [ - { - "role": "system", - "content": "You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a succinct, creative and helpful way. Prefer responses that are one sentence long unless you are asked for a longer or more detailed response.", - }, - {"role": "user", "content": "Start the call by saying the word 'hello'. Say only that word."}, - # {"role": "user", "content": ""}, - # {"role": "assistant", "content": []}, - # {"role": "user", "content": "Tell me"}, - # {"role": "user", "content": "a joke"}, -] +system_instruction = "You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a succinct, creative and helpful way. Prefer responses that are one sentence long unless you are asked for a longer or more detailed response." weather_function = FunctionSchema( name="get_current_weather", @@ -183,8 +170,6 @@ transport_params = { async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): logger.info(f"Starting bot") - global tts - stt = DeepgramSTTService(api_key=os.getenv("DEEPGRAM_API_KEY")) tts = CartesiaTTSService( @@ -194,7 +179,10 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): ), ) - llm = AnthropicLLMService(api_key=os.getenv("ANTHROPIC_API_KEY")) + llm = AnthropicLLMService( + api_key=os.getenv("ANTHROPIC_API_KEY"), + settings=AnthropicLLMSettings(system_instruction=system_instruction), + ) # you can either register a single function for all function calls, or specific functions # llm.register_function(None, fetch_weather_from_api) @@ -203,7 +191,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): llm.register_function("get_saved_conversation_filenames", get_saved_conversation_filenames) llm.register_function("load_conversation", load_conversation) - context = LLMContext(messages, tools) + context = LLMContext(tools=tools) user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()), @@ -234,6 +222,12 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): async def on_client_connected(transport, client): logger.info(f"Client connected") # Kick off the conversation. + context.add_message( + { + "role": "user", + "content": "Start the call by saying the word 'hello'. Say only that word.", + } + ) await task.queue_frames([LLMRunFrame()]) @transport.event_handler("on_client_disconnected") diff --git a/examples/foundational/20d-persistent-context-gemini.py b/examples/foundational/20d-persistent-context-gemini.py index ca5186532..082e5f07f 100644 --- a/examples/foundational/20d-persistent-context-gemini.py +++ b/examples/foundational/20d-persistent-context-gemini.py @@ -122,11 +122,7 @@ async def load_conversation(params: FunctionCallParams): await params.result_callback({"success": False, "error": str(e)}) -# Test message munging ... -messages = [ - { - "role": "system", - "content": """You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your +system_instruction = """You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way. @@ -151,13 +147,7 @@ indicate you should use the get_image tool are: - Tell me about what you see. - Tell me something interesting about what you see. - What's happening in the video? - """, - }, - # {"role": "user", "content": ""}, - # {"role": "assistant", "content": []}, - # {"role": "user", "content": "Tell me"}, - # {"role": "user", "content": "a joke"}, -] +""" weather_function = FunctionSchema( name="get_current_weather", @@ -262,7 +252,10 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): ), ) - llm = GoogleLLMService(api_key=os.getenv("GOOGLE_API_KEY")) + llm = GoogleLLMService( + api_key=os.getenv("GOOGLE_API_KEY"), + system_instruction=system_instruction, + ) # you can either register a single function for all function calls, or specific functions # llm.register_function(None, fetch_weather_from_api) @@ -272,7 +265,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): llm.register_function("load_conversation", load_conversation) llm.register_function("get_image", get_image) - context = LLMContext(messages, tools) + context = LLMContext(tools=tools) user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()), @@ -308,9 +301,9 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): client_id = get_transport_client_id(transport, client) # Kick off the conversation. - messages.append( + context.add_message( { - "role": "system", + "role": "user", "content": f"Please introduce yourself to the user. Use '{client_id}' as the user ID during function calls.", } ) diff --git a/examples/foundational/20e-persistent-context-aws-nova-sonic.py b/examples/foundational/20e-persistent-context-aws-nova-sonic.py index 7efa2678c..16e00d4c2 100644 --- a/examples/foundational/20e-persistent-context-aws-nova-sonic.py +++ b/examples/foundational/20e-persistent-context-aws-nova-sonic.py @@ -235,12 +235,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): llm.register_function("get_saved_conversation_filenames", get_saved_conversation_filenames) llm.register_function("load_conversation", load_conversation) - context = LLMContext( - messages=[ - {"role": "user", "content": "Hello!"}, - ], - tools=tools, - ) + context = LLMContext(tools=tools) user_aggregator, assistant_aggregator = LLMContextAggregatorPair(context) pipeline = Pipeline( @@ -266,6 +261,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): async def on_client_connected(transport, client): logger.info(f"Client connected") # Kick off the conversation. + context.add_message({"role": "user", "content": "Please introduce yourself to the user."}) await task.queue_frames([LLMRunFrame()]) # HACK: if using the older Nova Sonic (pre-2) model, you need this special way of # triggering the first assistant response. Note that this trigger requires a special diff --git a/examples/foundational/21-tavus-transport.py b/examples/foundational/21-tavus-transport.py index 7936a4555..2da83463d 100644 --- a/examples/foundational/21-tavus-transport.py +++ b/examples/foundational/21-tavus-transport.py @@ -97,7 +97,7 @@ async def main(): # Kick off the conversation. context.add_message( { - "role": "system", + "role": "user", "content": "Start by greeting the user and ask how you can help.", } ) diff --git a/examples/foundational/21a-tavus-video-service.py b/examples/foundational/21a-tavus-video-service.py index fd2ff5880..0b26961c2 100644 --- a/examples/foundational/21a-tavus-video-service.py +++ b/examples/foundational/21a-tavus-video-service.py @@ -115,7 +115,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): # Kick off the conversation. context.add_message( { - "role": "system", + "role": "user", "content": "Start by greeting the user and ask how you can help.", } ) diff --git a/examples/foundational/23-bot-background-sound.py b/examples/foundational/23-bot-background-sound.py index ad82ab8c3..53544fdf6 100644 --- a/examples/foundational/23-bot-background-sound.py +++ b/examples/foundational/23-bot-background-sound.py @@ -128,7 +128,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): logger.info(f"Re-enabling background sound and starting bot...") await task.queue_frame(MixerEnableFrame(True)) # Kick off the conversation. - context.add_message({"role": "system", "content": "Please introduce yourself to the user."}) + context.add_message({"role": "user", "content": "Please introduce yourself to the user."}) await task.queue_frames([LLMRunFrame()]) @transport.event_handler("on_client_disconnected") diff --git a/examples/foundational/24-user-mute-strategy.py b/examples/foundational/24-user-mute-strategy.py index ab206de73..fac86dae4 100644 --- a/examples/foundational/24-user-mute-strategy.py +++ b/examples/foundational/24-user-mute-strategy.py @@ -143,7 +143,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): # Kick off the conversation with a weather-related prompt context.add_message( { - "role": "system", + "role": "user", "content": "Ask the user what city they'd like to know the weather for.", } ) diff --git a/examples/foundational/26b-gemini-live-function-calling.py b/examples/foundational/26b-gemini-live-function-calling.py index 7aea43036..0ffceecd1 100644 --- a/examples/foundational/26b-gemini-live-function-calling.py +++ b/examples/foundational/26b-gemini-live-function-calling.py @@ -131,13 +131,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): # than as arguments to GeminiLiveLLMService, but note that doing so will # trigger a (fast) reconnection when the GeminiLiveLLMService first # receives the context (i.e. when we send the LLMRunFrame below). - context = LLMContext( - [ - # {"role": "system", "content": system_instruction}, - {"role": "user", "content": "Say hello."}, - ], - # tools, - ) + context = LLMContext() user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, user_params=LLMUserAggregatorParams( @@ -172,6 +166,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): async def on_client_connected(transport, client): logger.info(f"Client connected") # Kick off the conversation. + context.add_message({"role": "user", "content": "Please introduce yourself to the user."}) await task.queue_frames([LLMRunFrame()]) @transport.event_handler("on_client_disconnected") diff --git a/examples/foundational/28-user-assistant-turns.py b/examples/foundational/28-user-assistant-turns.py index 2a7cce980..6ff7ca9ec 100644 --- a/examples/foundational/28-user-assistant-turns.py +++ b/examples/foundational/28-user-assistant-turns.py @@ -169,7 +169,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): async def on_client_connected(transport, client): logger.info(f"Client connected") # Start conversation - empty prompt to let LLM follow system instructions - context.add_message({"role": "system", "content": "Please introduce yourself to the user."}) + context.add_message({"role": "user", "content": "Please introduce yourself to the user."}) await task.queue_frames([LLMRunFrame()]) @transport.event_handler("on_client_disconnected") diff --git a/examples/foundational/29-turn-tracking-observer.py b/examples/foundational/29-turn-tracking-observer.py index d83442456..a73126936 100644 --- a/examples/foundational/29-turn-tracking-observer.py +++ b/examples/foundational/29-turn-tracking-observer.py @@ -191,7 +191,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): async def on_client_connected(transport, client): logger.info(f"Client connected") # Kick off the conversation. - context.add_message({"role": "system", "content": "Please introduce yourself to the user."}) + context.add_message({"role": "user", "content": "Please introduce yourself to the user."}) await task.queue_frames([LLMRunFrame()]) @transport.event_handler("on_client_disconnected") diff --git a/examples/foundational/30-observer.py b/examples/foundational/30-observer.py index c730a2993..28a76059d 100644 --- a/examples/foundational/30-observer.py +++ b/examples/foundational/30-observer.py @@ -158,7 +158,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): async def on_client_connected(transport, client): logger.info(f"Client connected") # Kick off the conversation. - context.add_message({"role": "system", "content": "Please introduce yourself to the user."}) + context.add_message({"role": "user", "content": "Please introduce yourself to the user."}) await task.queue_frames([LLMRunFrame()]) @transport.event_handler("on_client_disconnected") diff --git a/examples/foundational/33-gemini-rag.py b/examples/foundational/33-gemini-rag.py index 3b1ba6bb9..cadb3fd92 100644 --- a/examples/foundational/33-gemini-rag.py +++ b/examples/foundational/33-gemini-rag.py @@ -197,11 +197,11 @@ Your response will be turned into speech so use only simple words and punctuatio """ llm = GoogleLLMService( + api_key=os.getenv("GOOGLE_API_KEY"), settings=GoogleLLMSettings( model=VOICE_MODEL, system_instruction=system_prompt, ), - api_key=os.getenv("GOOGLE_API_KEY"), ) llm.register_function("query_knowledge_base", query_knowledge_base) @@ -218,11 +218,7 @@ Your response will be turned into speech so use only simple words and punctuatio ) tools = ToolsSchema(standard_tools=[query_function]) - messages = [ - {"role": "user", "content": "Greet the user."}, - ] - - context = LLMContext(messages, tools) + context = LLMContext(tools=tools) user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()), @@ -252,6 +248,7 @@ Your response will be turned into speech so use only simple words and punctuatio async def on_client_connected(transport, client): logger.info(f"Client connected") # Start conversation - empty prompt to let LLM follow system instructions + context.add_message({"role": "user", "content": "Please introduce yourself to the user."}) await task.queue_frames([LLMRunFrame()]) @transport.event_handler("on_client_disconnected") diff --git a/examples/foundational/38-smart-turn-fal.py b/examples/foundational/38-smart-turn-fal.py index 2eafe6297..6ecc444f9 100644 --- a/examples/foundational/38-smart-turn-fal.py +++ b/examples/foundational/38-smart-turn-fal.py @@ -116,7 +116,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): async def on_client_connected(transport, client): logger.info(f"Client connected") # Kick off the conversation. - context.add_message({"role": "system", "content": "Please introduce yourself to the user."}) + context.add_message({"role": "user", "content": "Please introduce yourself to the user."}) await task.queue_frames([LLMRunFrame()]) @transport.event_handler("on_client_disconnected") diff --git a/examples/foundational/38a-smart-turn-local-coreml.py b/examples/foundational/38a-smart-turn-local-coreml.py index 4ed17642b..32cd507b8 100644 --- a/examples/foundational/38a-smart-turn-local-coreml.py +++ b/examples/foundational/38a-smart-turn-local-coreml.py @@ -130,7 +130,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): async def on_client_connected(transport, client): logger.info(f"Client connected") # Kick off the conversation. - context.add_message({"role": "system", "content": "Please introduce yourself to the user."}) + context.add_message({"role": "user", "content": "Please introduce yourself to the user."}) await task.queue_frames([LLMRunFrame()]) @transport.event_handler("on_client_disconnected") diff --git a/examples/foundational/38b-smart-turn-local.py b/examples/foundational/38b-smart-turn-local.py index 361889a5b..30849a71d 100644 --- a/examples/foundational/38b-smart-turn-local.py +++ b/examples/foundational/38b-smart-turn-local.py @@ -102,7 +102,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): async def on_client_connected(transport, client): logger.info(f"Client connected") # Kick off the conversation - context.add_message({"role": "system", "content": "Please introduce yourself to the user."}) + context.add_message({"role": "user", "content": "Please introduce yourself to the user."}) await task.queue_frames([LLMRunFrame()]) @transport.event_handler("on_client_disconnected") diff --git a/examples/foundational/39-mcp-stdio.py b/examples/foundational/39-mcp-stdio.py index 7e648cfd7..b6f111044 100644 --- a/examples/foundational/39-mcp-stdio.py +++ b/examples/foundational/39-mcp-stdio.py @@ -142,7 +142,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): ), ) - system = f""" + system_prompt = f""" You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. You have access to tools to search the Rijksmuseum collection. @@ -158,7 +158,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): llm = AnthropicLLMService( api_key=os.getenv("ANTHROPIC_API_KEY"), settings=AnthropicLLMSettings( - system_instruction=system, + system_instruction=system_prompt, ), ) diff --git a/examples/foundational/39a-mcp-streamable-http.py b/examples/foundational/39a-mcp-streamable-http.py index 870556073..38f52ff1c 100644 --- a/examples/foundational/39a-mcp-streamable-http.py +++ b/examples/foundational/39a-mcp-streamable-http.py @@ -63,7 +63,19 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): ), ) - llm = GoogleLLMService(api_key=os.getenv("GOOGLE_API_KEY"), model="gemini-2.0-flash") + system_prompt = f""" + You are a helpful LLM in a WebRTC call. + Your goal is to answer questions about the user's GitHub repositories and account. + You have access to a number of tools provided by Github. Use any and all tools to help users. + Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. + Don't overexplain what you are doing. + Just respond with short sentences when you are carrying out tool calls. + """ + + llm = GoogleLLMService( + api_key=os.getenv("GOOGLE_API_KEY"), + system_instruction=system_prompt, + ) try: # Github MCP docs: https://github.com/github/github-mcp-server @@ -87,18 +99,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): logger.error(f"error registering tools") logger.exception("error trace:") - system = f""" - You are a helpful LLM in a WebRTC call. - Your goal is to answer questions about the user's GitHub repositories and account. - You have access to a number of tools provided by Github. Use any and all tools to help users. - Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. - Don't overexplain what you are doing. - Just respond with short sentences when you are carrying out tool calls. - """ - - messages = [{"role": "system", "content": system}] - - context = LLMContext(messages, tools) + context = LLMContext(tools=tools) user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()), diff --git a/examples/foundational/39c-multiple-mcp.py b/examples/foundational/39c-multiple-mcp.py index e4612efa4..4c7bc27d9 100644 --- a/examples/foundational/39c-multiple-mcp.py +++ b/examples/foundational/39c-multiple-mcp.py @@ -125,7 +125,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): ), ) - system = f""" + system_prompt = f""" You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. You have access to tools to search the Rijksmuseum collection and the user's GitHub repositories and account. @@ -142,7 +142,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): llm = AnthropicLLMService( api_key=os.getenv("ANTHROPIC_API_KEY"), settings=AnthropicLLMSettings( - system_instruction=system, + system_instruction=system_prompt, ), ) diff --git a/examples/foundational/40-aws-nova-sonic.py b/examples/foundational/40-aws-nova-sonic.py index 0bb670d4b..327efaac5 100644 --- a/examples/foundational/40-aws-nova-sonic.py +++ b/examples/foundational/40-aws-nova-sonic.py @@ -146,15 +146,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): ) # Set up context and context management. - context = LLMContext( - messages=[ - { - "role": "user", - "content": "Tell me a fun fact!", - }, - ], - tools=tools, - ) + context = LLMContext(tools=tools) user_aggregator, assistant_aggregator = LLMContextAggregatorPair(context) # Build the pipeline @@ -183,6 +175,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): async def on_client_connected(transport, client): logger.info(f"Client connected") # Kick off the conversation. + context.add_message({"role": "user", "content": "Please introduce yourself to the user."}) await task.queue_frames([LLMRunFrame()]) # HACK: if using the older Nova Sonic (pre-2) model, you need this special way of # triggering the first assistant response. Note that this trigger requires a special diff --git a/examples/foundational/42-interruption-config.py b/examples/foundational/42-interruption-config.py index 4c8e3ba23..a74b5cc7b 100644 --- a/examples/foundational/42-interruption-config.py +++ b/examples/foundational/42-interruption-config.py @@ -108,7 +108,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): async def on_client_connected(transport, client): logger.info(f"Client connected") # Kick off the conversation. - context.add_message({"role": "system", "content": "Please introduce yourself to the user."}) + context.add_message({"role": "user", "content": "Please introduce yourself to the user."}) await task.queue_frames([LLMRunFrame()]) @transport.event_handler("on_client_disconnected") diff --git a/examples/foundational/43-heygen-transport.py b/examples/foundational/43-heygen-transport.py index ad0e20764..23b87a5bb 100644 --- a/examples/foundational/43-heygen-transport.py +++ b/examples/foundational/43-heygen-transport.py @@ -100,7 +100,7 @@ async def main(): # Kick off the conversation. context.add_message( { - "role": "system", + "role": "user", "content": "Start by saying 'Hello' and then a short greeting.", } ) diff --git a/examples/foundational/43a-heygen-video-service.py b/examples/foundational/43a-heygen-video-service.py index e4bd0e460..5edeb6bc3 100644 --- a/examples/foundational/43a-heygen-video-service.py +++ b/examples/foundational/43a-heygen-video-service.py @@ -133,7 +133,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): # Kick off the conversation. context.add_message( { - "role": "system", + "role": "user", "content": "Start by saying 'Hello' and then a short greeting.", } ) diff --git a/examples/foundational/45-before-and-after-events.py b/examples/foundational/45-before-and-after-events.py index c06837a4b..e0e5604c6 100644 --- a/examples/foundational/45-before-and-after-events.py +++ b/examples/foundational/45-before-and-after-events.py @@ -120,7 +120,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): async def on_client_connected(transport, client): logger.info(f"Client connected") # Kick off the conversation. - context.add_message({"role": "system", "content": "Please introduce yourself to the user."}) + context.add_message({"role": "user", "content": "Please introduce yourself to the user."}) # Custom frames are pushed in order so they can be used for synchronization purposes. await task.queue_frames([CustomBeforeProcessFrame(), LLMRunFrame(), CustomAfterPushFrame()]) diff --git a/examples/foundational/47-sentry-metrics.py b/examples/foundational/47-sentry-metrics.py index d024ed73a..a415fd975 100644 --- a/examples/foundational/47-sentry-metrics.py +++ b/examples/foundational/47-sentry-metrics.py @@ -111,7 +111,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): async def on_client_connected(transport, client): logger.info(f"Client connected") # Kick off the conversation. - context.add_message({"role": "system", "content": "Please introduce yourself to the user."}) + context.add_message({"role": "user", "content": "Please introduce yourself to the user."}) await task.queue_frames([LLMRunFrame()]) @transport.event_handler("on_client_disconnected") diff --git a/examples/foundational/48-service-switcher.py b/examples/foundational/48-service-switcher.py index d0e3f09ec..970e14839 100644 --- a/examples/foundational/48-service-switcher.py +++ b/examples/foundational/48-service-switcher.py @@ -116,15 +116,15 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): services=[tts_cartesia, tts_deepgram], strategy_type=ServiceSwitcherStrategyManual ) - system = "You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way." + system_prompt = "You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way." llm_openai = OpenAILLMService( api_key=os.getenv("OPENAI_API_KEY"), - settings=OpenAILLMSettings(system_instruction=system), + settings=OpenAILLMSettings(system_instruction=system_prompt), ) llm_google = GoogleLLMService( api_key=os.getenv("GOOGLE_API_KEY"), - settings=GoogleLLMSettings(system_instruction=system), + settings=GoogleLLMSettings(system_instruction=system_prompt), ) llm_switcher = LLMSwitcher( llms=[llm_openai, llm_google], strategy_type=ServiceSwitcherStrategyManual diff --git a/examples/foundational/54-context-summarization-openai.py b/examples/foundational/54-context-summarization-openai.py index 897ed171f..9c3f75fa5 100644 --- a/examples/foundational/54-context-summarization-openai.py +++ b/examples/foundational/54-context-summarization-openai.py @@ -175,7 +175,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): async def on_client_connected(transport, client): logger.info("Client connected") # Kick off the conversation. - context.add_message({"role": "system", "content": "Please introduce yourself to the user."}) + context.add_message({"role": "user", "content": "Please introduce yourself to the user."}) await task.queue_frames([LLMRunFrame()]) @transport.event_handler("on_client_disconnected") diff --git a/examples/foundational/54a-context-summarization-google.py b/examples/foundational/54a-context-summarization-google.py index 8242ea879..b9ce3d7c7 100644 --- a/examples/foundational/54a-context-summarization-google.py +++ b/examples/foundational/54a-context-summarization-google.py @@ -175,7 +175,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): async def on_client_connected(transport, client): logger.info("Client connected") # Kick off the conversation. - context.add_message({"role": "system", "content": "Please introduce yourself to the user."}) + context.add_message({"role": "user", "content": "Please introduce yourself to the user."}) await task.queue_frames([LLMRunFrame()]) @transport.event_handler("on_client_disconnected") diff --git a/examples/foundational/55a-update-settings-deepgram-flux-stt.py b/examples/foundational/55a-update-settings-deepgram-flux-stt.py index cd55f3e37..72d9b5638 100644 --- a/examples/foundational/55a-update-settings-deepgram-flux-stt.py +++ b/examples/foundational/55a-update-settings-deepgram-flux-stt.py @@ -97,7 +97,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): @transport.event_handler("on_client_connected") async def on_client_connected(transport, client): logger.info(f"Client connected") - context.add_message({"role": "system", "content": "Please introduce yourself to the user."}) + context.add_message({"role": "user", "content": "Please introduce yourself to the user."}) await task.queue_frames([LLMRunFrame()]) await asyncio.sleep(10) diff --git a/examples/foundational/55a-update-settings-deepgram-sagemaker-stt.py b/examples/foundational/55a-update-settings-deepgram-sagemaker-stt.py index af080e9db..21604829f 100644 --- a/examples/foundational/55a-update-settings-deepgram-sagemaker-stt.py +++ b/examples/foundational/55a-update-settings-deepgram-sagemaker-stt.py @@ -104,7 +104,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): @transport.event_handler("on_client_connected") async def on_client_connected(transport, client): logger.info(f"Client connected") - context.add_message({"role": "system", "content": "Please introduce yourself to the user."}) + context.add_message({"role": "user", "content": "Please introduce yourself to the user."}) await task.queue_frames([LLMRunFrame()]) # NOTE: after this change, the bot will only respond if you speak Spanish diff --git a/examples/foundational/55a-update-settings-deepgram-stt.py b/examples/foundational/55a-update-settings-deepgram-stt.py index 0519799f0..c7442549c 100644 --- a/examples/foundational/55a-update-settings-deepgram-stt.py +++ b/examples/foundational/55a-update-settings-deepgram-stt.py @@ -98,7 +98,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): @transport.event_handler("on_client_connected") async def on_client_connected(transport, client): logger.info(f"Client connected") - context.add_message({"role": "system", "content": "Please introduce yourself to the user."}) + context.add_message({"role": "user", "content": "Please introduce yourself to the user."}) await task.queue_frames([LLMRunFrame()]) # NOTE: after this change, the bot will only respond if you speak Spanish diff --git a/examples/foundational/55b-update-settings-azure-stt.py b/examples/foundational/55b-update-settings-azure-stt.py index c10f79de4..f93f907e7 100644 --- a/examples/foundational/55b-update-settings-azure-stt.py +++ b/examples/foundational/55b-update-settings-azure-stt.py @@ -100,7 +100,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): @transport.event_handler("on_client_connected") async def on_client_connected(transport, client): logger.info(f"Client connected") - context.add_message({"role": "system", "content": "Please introduce yourself to the user."}) + context.add_message({"role": "user", "content": "Please introduce yourself to the user."}) await task.queue_frames([LLMRunFrame()]) await asyncio.sleep(10) diff --git a/examples/foundational/55c-update-settings-google-stt.py b/examples/foundational/55c-update-settings-google-stt.py index 9c67a8039..e2b844c2e 100644 --- a/examples/foundational/55c-update-settings-google-stt.py +++ b/examples/foundational/55c-update-settings-google-stt.py @@ -97,7 +97,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): @transport.event_handler("on_client_connected") async def on_client_connected(transport, client): logger.info(f"Client connected") - context.add_message({"role": "system", "content": "Please introduce yourself to the user."}) + context.add_message({"role": "user", "content": "Please introduce yourself to the user."}) await task.queue_frames([LLMRunFrame()]) await asyncio.sleep(10) diff --git a/examples/foundational/55d-update-settings-assemblyai-stt.py b/examples/foundational/55d-update-settings-assemblyai-stt.py index 1b8ca5eda..2a49da3e2 100644 --- a/examples/foundational/55d-update-settings-assemblyai-stt.py +++ b/examples/foundational/55d-update-settings-assemblyai-stt.py @@ -104,7 +104,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): logger.info( "Phase 1: No keyterms boosting - try saying 'Xiomara', 'Saoirse', or 'Krzystof'" ) - context.add_message({"role": "system", "content": "Please introduce yourself to the user."}) + context.add_message({"role": "user", "content": "Please introduce yourself to the user."}) await task.queue_frames([LLMRunFrame()]) await asyncio.sleep(15) diff --git a/examples/foundational/55e-update-settings-gladia-stt.py b/examples/foundational/55e-update-settings-gladia-stt.py index 24e0dfa6f..885c78030 100644 --- a/examples/foundational/55e-update-settings-gladia-stt.py +++ b/examples/foundational/55e-update-settings-gladia-stt.py @@ -97,7 +97,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): @transport.event_handler("on_client_connected") async def on_client_connected(transport, client): logger.info(f"Client connected") - context.add_message({"role": "system", "content": "Please introduce yourself to the user."}) + context.add_message({"role": "user", "content": "Please introduce yourself to the user."}) await task.queue_frames([LLMRunFrame()]) await asyncio.sleep(10) diff --git a/examples/foundational/55f-update-settings-elevenlabs-realtime-stt.py b/examples/foundational/55f-update-settings-elevenlabs-realtime-stt.py index b1f35de13..6598240cb 100644 --- a/examples/foundational/55f-update-settings-elevenlabs-realtime-stt.py +++ b/examples/foundational/55f-update-settings-elevenlabs-realtime-stt.py @@ -100,7 +100,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): @transport.event_handler("on_client_connected") async def on_client_connected(transport, client): logger.info(f"Client connected") - context.add_message({"role": "system", "content": "Please introduce yourself to the user."}) + context.add_message({"role": "user", "content": "Please introduce yourself to the user."}) await task.queue_frames([LLMRunFrame()]) await asyncio.sleep(10) diff --git a/examples/foundational/55g-update-settings-elevenlabs-stt.py b/examples/foundational/55g-update-settings-elevenlabs-stt.py index 9896a1652..50a160b2b 100644 --- a/examples/foundational/55g-update-settings-elevenlabs-stt.py +++ b/examples/foundational/55g-update-settings-elevenlabs-stt.py @@ -103,7 +103,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): async def on_client_connected(transport, client): logger.info(f"Client connected") context.add_message( - {"role": "system", "content": "Please introduce yourself to the user."} + {"role": "user", "content": "Please introduce yourself to the user."} ) await task.queue_frames([LLMRunFrame()]) diff --git a/examples/foundational/55h-update-settings-speechmatics-stt.py b/examples/foundational/55h-update-settings-speechmatics-stt.py index 01f653c7e..89b15c94c 100644 --- a/examples/foundational/55h-update-settings-speechmatics-stt.py +++ b/examples/foundational/55h-update-settings-speechmatics-stt.py @@ -104,7 +104,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): @transport.event_handler("on_client_connected") async def on_client_connected(transport, client): logger.info(f"Client connected") - context.add_message({"role": "system", "content": "Please introduce yourself to the user."}) + context.add_message({"role": "user", "content": "Please introduce yourself to the user."}) await task.queue_frames([LLMRunFrame()]) await asyncio.sleep(10) diff --git a/examples/foundational/55i-update-settings-whisper-api-stt.py b/examples/foundational/55i-update-settings-whisper-api-stt.py index d2c81b0bc..72674d7dd 100644 --- a/examples/foundational/55i-update-settings-whisper-api-stt.py +++ b/examples/foundational/55i-update-settings-whisper-api-stt.py @@ -103,7 +103,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): @transport.event_handler("on_client_connected") async def on_client_connected(transport, client): logger.info(f"Client connected") - context.add_message({"role": "system", "content": "Please introduce yourself to the user."}) + context.add_message({"role": "user", "content": "Please introduce yourself to the user."}) await task.queue_frames([LLMRunFrame()]) await asyncio.sleep(10) diff --git a/examples/foundational/55j-update-settings-sarvam-stt.py b/examples/foundational/55j-update-settings-sarvam-stt.py index 982b22b57..b882c8a2b 100644 --- a/examples/foundational/55j-update-settings-sarvam-stt.py +++ b/examples/foundational/55j-update-settings-sarvam-stt.py @@ -97,7 +97,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): @transport.event_handler("on_client_connected") async def on_client_connected(transport, client): logger.info(f"Client connected") - context.add_message({"role": "system", "content": "Please introduce yourself to the user."}) + context.add_message({"role": "user", "content": "Please introduce yourself to the user."}) await task.queue_frames([LLMRunFrame()]) await asyncio.sleep(10) diff --git a/examples/foundational/55k-update-settings-soniox-stt.py b/examples/foundational/55k-update-settings-soniox-stt.py index 5fdf0fd82..bf395aefc 100644 --- a/examples/foundational/55k-update-settings-soniox-stt.py +++ b/examples/foundational/55k-update-settings-soniox-stt.py @@ -97,7 +97,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): @transport.event_handler("on_client_connected") async def on_client_connected(transport, client): logger.info(f"Client connected") - context.add_message({"role": "system", "content": "Please introduce yourself to the user."}) + context.add_message({"role": "user", "content": "Please introduce yourself to the user."}) await task.queue_frames([LLMRunFrame()]) await asyncio.sleep(10) diff --git a/examples/foundational/55l-update-settings-aws-transcribe-stt.py b/examples/foundational/55l-update-settings-aws-transcribe-stt.py index 07a923616..9c37da430 100644 --- a/examples/foundational/55l-update-settings-aws-transcribe-stt.py +++ b/examples/foundational/55l-update-settings-aws-transcribe-stt.py @@ -97,7 +97,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): @transport.event_handler("on_client_connected") async def on_client_connected(transport, client): logger.info(f"Client connected") - context.add_message({"role": "system", "content": "Please introduce yourself to the user."}) + context.add_message({"role": "user", "content": "Please introduce yourself to the user."}) await task.queue_frames([LLMRunFrame()]) await asyncio.sleep(10) diff --git a/examples/foundational/55m-update-settings-cartesia-stt.py b/examples/foundational/55m-update-settings-cartesia-stt.py index e8fc79e94..97d18f6fe 100644 --- a/examples/foundational/55m-update-settings-cartesia-stt.py +++ b/examples/foundational/55m-update-settings-cartesia-stt.py @@ -97,7 +97,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): @transport.event_handler("on_client_connected") async def on_client_connected(transport, client): logger.info(f"Client connected") - context.add_message({"role": "system", "content": "Please introduce yourself to the user."}) + context.add_message({"role": "user", "content": "Please introduce yourself to the user."}) await task.queue_frames([LLMRunFrame()]) await asyncio.sleep(10) diff --git a/examples/foundational/55n-update-settings-cartesia-http-tts.py b/examples/foundational/55n-update-settings-cartesia-http-tts.py index 9cd935692..7ec4155da 100644 --- a/examples/foundational/55n-update-settings-cartesia-http-tts.py +++ b/examples/foundational/55n-update-settings-cartesia-http-tts.py @@ -100,7 +100,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): @transport.event_handler("on_client_connected") async def on_client_connected(transport, client): logger.info(f"Client connected") - context.add_message({"role": "system", "content": "Please introduce yourself to the user."}) + context.add_message({"role": "user", "content": "Please introduce yourself to the user."}) await task.queue_frames([LLMRunFrame()]) await asyncio.sleep(10) diff --git a/examples/foundational/55n-update-settings-cartesia-tts.py b/examples/foundational/55n-update-settings-cartesia-tts.py index 37ec2e903..3ecf6ba5a 100644 --- a/examples/foundational/55n-update-settings-cartesia-tts.py +++ b/examples/foundational/55n-update-settings-cartesia-tts.py @@ -99,7 +99,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): async def on_client_connected(transport, client): logger.info(f"Client connected") # Kick off the conversation. - context.add_message({"role": "system", "content": "Please introduce yourself to the user."}) + context.add_message({"role": "user", "content": "Please introduce yourself to the user."}) await task.queue_frames([LLMRunFrame()]) await asyncio.sleep(10) diff --git a/examples/foundational/55o-update-settings-elevenlabs-http-tts.py b/examples/foundational/55o-update-settings-elevenlabs-http-tts.py index c8c2af4ab..58ef44010 100644 --- a/examples/foundational/55o-update-settings-elevenlabs-http-tts.py +++ b/examples/foundational/55o-update-settings-elevenlabs-http-tts.py @@ -100,7 +100,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): async def on_client_connected(transport, client): logger.info(f"Client connected") context.add_message( - {"role": "system", "content": "Please introduce yourself to the user."} + {"role": "user", "content": "Please introduce yourself to the user."} ) await task.queue_frames([LLMRunFrame()]) diff --git a/examples/foundational/55o-update-settings-elevenlabs-tts.py b/examples/foundational/55o-update-settings-elevenlabs-tts.py index 71ff8c0af..dcab84af4 100644 --- a/examples/foundational/55o-update-settings-elevenlabs-tts.py +++ b/examples/foundational/55o-update-settings-elevenlabs-tts.py @@ -95,7 +95,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): @transport.event_handler("on_client_connected") async def on_client_connected(transport, client): logger.info(f"Client connected") - context.add_message({"role": "system", "content": "Please introduce yourself to the user."}) + context.add_message({"role": "user", "content": "Please introduce yourself to the user."}) await task.queue_frames([LLMRunFrame()]) await asyncio.sleep(10) diff --git a/examples/foundational/55p-update-settings-openai-tts.py b/examples/foundational/55p-update-settings-openai-tts.py index 9a1402a1c..0a8c35cc2 100644 --- a/examples/foundational/55p-update-settings-openai-tts.py +++ b/examples/foundational/55p-update-settings-openai-tts.py @@ -92,7 +92,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): @transport.event_handler("on_client_connected") async def on_client_connected(transport, client): logger.info(f"Client connected") - context.add_message({"role": "system", "content": "Please introduce yourself to the user."}) + context.add_message({"role": "user", "content": "Please introduce yourself to the user."}) await task.queue_frames([LLMRunFrame()]) await asyncio.sleep(10) diff --git a/examples/foundational/55q-update-settings-deepgram-http-tts.py b/examples/foundational/55q-update-settings-deepgram-http-tts.py index dd5220c3f..bed83dfc3 100644 --- a/examples/foundational/55q-update-settings-deepgram-http-tts.py +++ b/examples/foundational/55q-update-settings-deepgram-http-tts.py @@ -99,7 +99,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): async def on_client_connected(transport, client): logger.info(f"Client connected") context.add_message( - {"role": "system", "content": "Please introduce yourself to the user."} + {"role": "user", "content": "Please introduce yourself to the user."} ) await task.queue_frames([LLMRunFrame()]) diff --git a/examples/foundational/55q-update-settings-deepgram-sagemaker-tts.py b/examples/foundational/55q-update-settings-deepgram-sagemaker-tts.py index b913375bb..73a4ae365 100644 --- a/examples/foundational/55q-update-settings-deepgram-sagemaker-tts.py +++ b/examples/foundational/55q-update-settings-deepgram-sagemaker-tts.py @@ -98,7 +98,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): @transport.event_handler("on_client_connected") async def on_client_connected(transport, client): logger.info(f"Client connected") - context.add_message({"role": "system", "content": "Please introduce yourself to the user."}) + context.add_message({"role": "user", "content": "Please introduce yourself to the user."}) await task.queue_frames([LLMRunFrame()]) await asyncio.sleep(10) diff --git a/examples/foundational/55q-update-settings-deepgram-tts.py b/examples/foundational/55q-update-settings-deepgram-tts.py index 7164c7b58..f151f3d3f 100644 --- a/examples/foundational/55q-update-settings-deepgram-tts.py +++ b/examples/foundational/55q-update-settings-deepgram-tts.py @@ -91,7 +91,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): @transport.event_handler("on_client_connected") async def on_client_connected(transport, client): logger.info(f"Client connected") - context.add_message({"role": "system", "content": "Please introduce yourself to the user."}) + context.add_message({"role": "user", "content": "Please introduce yourself to the user."}) await task.queue_frames([LLMRunFrame()]) await asyncio.sleep(10) diff --git a/examples/foundational/55r-update-settings-azure-http-tts.py b/examples/foundational/55r-update-settings-azure-http-tts.py index 148e97f1a..56d144718 100644 --- a/examples/foundational/55r-update-settings-azure-http-tts.py +++ b/examples/foundational/55r-update-settings-azure-http-tts.py @@ -94,7 +94,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): @transport.event_handler("on_client_connected") async def on_client_connected(transport, client): logger.info(f"Client connected") - context.add_message({"role": "system", "content": "Please introduce yourself to the user."}) + context.add_message({"role": "user", "content": "Please introduce yourself to the user."}) await task.queue_frames([LLMRunFrame()]) await asyncio.sleep(10) diff --git a/examples/foundational/55r-update-settings-azure-tts.py b/examples/foundational/55r-update-settings-azure-tts.py index d23d41a89..de234fec9 100644 --- a/examples/foundational/55r-update-settings-azure-tts.py +++ b/examples/foundational/55r-update-settings-azure-tts.py @@ -94,7 +94,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): @transport.event_handler("on_client_connected") async def on_client_connected(transport, client): logger.info(f"Client connected") - context.add_message({"role": "system", "content": "Please introduce yourself to the user."}) + context.add_message({"role": "user", "content": "Please introduce yourself to the user."}) await task.queue_frames([LLMRunFrame()]) await asyncio.sleep(10) diff --git a/examples/foundational/55s-update-settings-google-http-tts.py b/examples/foundational/55s-update-settings-google-http-tts.py index c573bee6f..79d3a3d42 100644 --- a/examples/foundational/55s-update-settings-google-http-tts.py +++ b/examples/foundational/55s-update-settings-google-http-tts.py @@ -91,7 +91,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): @transport.event_handler("on_client_connected") async def on_client_connected(transport, client): logger.info(f"Client connected") - context.add_message({"role": "system", "content": "Please introduce yourself to the user."}) + context.add_message({"role": "user", "content": "Please introduce yourself to the user."}) await task.queue_frames([LLMRunFrame()]) await asyncio.sleep(10) diff --git a/examples/foundational/55s-update-settings-google-stream-tts.py b/examples/foundational/55s-update-settings-google-stream-tts.py index b13cbd063..ca7e696af 100644 --- a/examples/foundational/55s-update-settings-google-stream-tts.py +++ b/examples/foundational/55s-update-settings-google-stream-tts.py @@ -91,7 +91,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): @transport.event_handler("on_client_connected") async def on_client_connected(transport, client): logger.info(f"Client connected") - context.add_message({"role": "system", "content": "Please introduce yourself to the user."}) + context.add_message({"role": "user", "content": "Please introduce yourself to the user."}) await task.queue_frames([LLMRunFrame()]) await asyncio.sleep(10) diff --git a/examples/foundational/55u-update-settings-rime-http-tts.py b/examples/foundational/55u-update-settings-rime-http-tts.py index 0c00913e7..6ecf61fce 100644 --- a/examples/foundational/55u-update-settings-rime-http-tts.py +++ b/examples/foundational/55u-update-settings-rime-http-tts.py @@ -100,7 +100,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): async def on_client_connected(transport, client): logger.info(f"Client connected") context.add_message( - {"role": "system", "content": "Please introduce yourself to the user."} + {"role": "user", "content": "Please introduce yourself to the user."} ) await task.queue_frames([LLMRunFrame()]) diff --git a/examples/foundational/55u-update-settings-rime-tts.py b/examples/foundational/55u-update-settings-rime-tts.py index cb8e09876..e8652d311 100644 --- a/examples/foundational/55u-update-settings-rime-tts.py +++ b/examples/foundational/55u-update-settings-rime-tts.py @@ -94,7 +94,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): @transport.event_handler("on_client_connected") async def on_client_connected(transport, client): logger.info(f"Client connected") - context.add_message({"role": "system", "content": "Please introduce yourself to the user."}) + context.add_message({"role": "user", "content": "Please introduce yourself to the user."}) await task.queue_frames([LLMRunFrame()]) await asyncio.sleep(10) diff --git a/examples/foundational/55v-update-settings-lmnt-tts.py b/examples/foundational/55v-update-settings-lmnt-tts.py index 48b0f8d43..55ab18a16 100644 --- a/examples/foundational/55v-update-settings-lmnt-tts.py +++ b/examples/foundational/55v-update-settings-lmnt-tts.py @@ -94,7 +94,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): @transport.event_handler("on_client_connected") async def on_client_connected(transport, client): logger.info(f"Client connected") - context.add_message({"role": "system", "content": "Please introduce yourself to the user."}) + context.add_message({"role": "user", "content": "Please introduce yourself to the user."}) await task.queue_frames([LLMRunFrame()]) await asyncio.sleep(10) diff --git a/examples/foundational/55w-update-settings-fish-tts.py b/examples/foundational/55w-update-settings-fish-tts.py index 8243f82f2..306f3e34d 100644 --- a/examples/foundational/55w-update-settings-fish-tts.py +++ b/examples/foundational/55w-update-settings-fish-tts.py @@ -94,7 +94,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): @transport.event_handler("on_client_connected") async def on_client_connected(transport, client): logger.info(f"Client connected") - context.add_message({"role": "system", "content": "Please introduce yourself to the user."}) + context.add_message({"role": "user", "content": "Please introduce yourself to the user."}) await task.queue_frames([LLMRunFrame()]) await asyncio.sleep(10) diff --git a/examples/foundational/55x-update-settings-minimax-tts.py b/examples/foundational/55x-update-settings-minimax-tts.py index fc74bca4c..44ae6339d 100644 --- a/examples/foundational/55x-update-settings-minimax-tts.py +++ b/examples/foundational/55x-update-settings-minimax-tts.py @@ -98,7 +98,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): async def on_client_connected(transport, client): logger.info(f"Client connected") context.add_message( - {"role": "system", "content": "Please introduce yourself to the user."} + {"role": "user", "content": "Please introduce yourself to the user."} ) await task.queue_frames([LLMRunFrame()]) diff --git a/examples/foundational/55y-update-settings-groq-tts.py b/examples/foundational/55y-update-settings-groq-tts.py index 632907eaf..161c73ef0 100644 --- a/examples/foundational/55y-update-settings-groq-tts.py +++ b/examples/foundational/55y-update-settings-groq-tts.py @@ -91,7 +91,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): @transport.event_handler("on_client_connected") async def on_client_connected(transport, client): logger.info(f"Client connected") - context.add_message({"role": "system", "content": "Please introduce yourself to the user."}) + context.add_message({"role": "user", "content": "Please introduce yourself to the user."}) await task.queue_frames([LLMRunFrame()]) await asyncio.sleep(10) diff --git a/examples/foundational/55z-update-settings-hume-tts.py b/examples/foundational/55z-update-settings-hume-tts.py index 855610b6b..ea8f3b316 100644 --- a/examples/foundational/55z-update-settings-hume-tts.py +++ b/examples/foundational/55z-update-settings-hume-tts.py @@ -94,7 +94,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): @transport.event_handler("on_client_connected") async def on_client_connected(transport, client): logger.info(f"Client connected") - context.add_message({"role": "system", "content": "Please introduce yourself to the user."}) + context.add_message({"role": "user", "content": "Please introduce yourself to the user."}) await task.queue_frames([LLMRunFrame()]) await asyncio.sleep(10) diff --git a/examples/foundational/55za-update-settings-neuphonic-http-tts.py b/examples/foundational/55za-update-settings-neuphonic-http-tts.py index 7435b135d..29de5281e 100644 --- a/examples/foundational/55za-update-settings-neuphonic-http-tts.py +++ b/examples/foundational/55za-update-settings-neuphonic-http-tts.py @@ -97,7 +97,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): async def on_client_connected(transport, client): logger.info(f"Client connected") context.add_message( - {"role": "system", "content": "Please introduce yourself to the user."} + {"role": "user", "content": "Please introduce yourself to the user."} ) await task.queue_frames([LLMRunFrame()]) diff --git a/examples/foundational/55za-update-settings-neuphonic-tts.py b/examples/foundational/55za-update-settings-neuphonic-tts.py index c0566e86b..58532eba0 100644 --- a/examples/foundational/55za-update-settings-neuphonic-tts.py +++ b/examples/foundational/55za-update-settings-neuphonic-tts.py @@ -91,7 +91,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): @transport.event_handler("on_client_connected") async def on_client_connected(transport, client): logger.info(f"Client connected") - context.add_message({"role": "system", "content": "Please introduce yourself to the user."}) + context.add_message({"role": "user", "content": "Please introduce yourself to the user."}) await task.queue_frames([LLMRunFrame()]) await asyncio.sleep(10) diff --git a/examples/foundational/55zb-update-settings-inworld-http-tts.py b/examples/foundational/55zb-update-settings-inworld-http-tts.py index 4a2e2a2bc..dc11afac5 100644 --- a/examples/foundational/55zb-update-settings-inworld-http-tts.py +++ b/examples/foundational/55zb-update-settings-inworld-http-tts.py @@ -96,7 +96,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): async def on_client_connected(transport, client): logger.info(f"Client connected") context.add_message( - {"role": "system", "content": "Please introduce yourself to the user."} + {"role": "user", "content": "Please introduce yourself to the user."} ) await task.queue_frames([LLMRunFrame()]) diff --git a/examples/foundational/55zb-update-settings-inworld-tts.py b/examples/foundational/55zb-update-settings-inworld-tts.py index 7fcaf67bd..a1fb3a9f4 100644 --- a/examples/foundational/55zb-update-settings-inworld-tts.py +++ b/examples/foundational/55zb-update-settings-inworld-tts.py @@ -91,7 +91,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): @transport.event_handler("on_client_connected") async def on_client_connected(transport, client): logger.info(f"Client connected") - context.add_message({"role": "system", "content": "Please introduce yourself to the user."}) + context.add_message({"role": "user", "content": "Please introduce yourself to the user."}) await task.queue_frames([LLMRunFrame()]) await asyncio.sleep(10) diff --git a/examples/foundational/55zc-update-settings-gemini-tts.py b/examples/foundational/55zc-update-settings-gemini-tts.py index 2d2f15cda..41c7dfd8b 100644 --- a/examples/foundational/55zc-update-settings-gemini-tts.py +++ b/examples/foundational/55zc-update-settings-gemini-tts.py @@ -100,7 +100,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): @transport.event_handler("on_client_connected") async def on_client_connected(transport, client): logger.info(f"Client connected") - context.add_message({"role": "system", "content": "Please introduce yourself to the user."}) + context.add_message({"role": "user", "content": "Please introduce yourself to the user."}) await task.queue_frames([LLMRunFrame()]) await asyncio.sleep(10) diff --git a/examples/foundational/55zd-update-settings-aws-polly-tts.py b/examples/foundational/55zd-update-settings-aws-polly-tts.py index 1f6ce56b2..b1c632958 100644 --- a/examples/foundational/55zd-update-settings-aws-polly-tts.py +++ b/examples/foundational/55zd-update-settings-aws-polly-tts.py @@ -91,7 +91,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): @transport.event_handler("on_client_connected") async def on_client_connected(transport, client): logger.info(f"Client connected") - context.add_message({"role": "system", "content": "Please introduce yourself to the user."}) + context.add_message({"role": "user", "content": "Please introduce yourself to the user."}) await task.queue_frames([LLMRunFrame()]) await asyncio.sleep(10) diff --git a/examples/foundational/55ze-update-settings-sarvam-http-tts.py b/examples/foundational/55ze-update-settings-sarvam-http-tts.py index 811ffceb8..1bbd0886e 100644 --- a/examples/foundational/55ze-update-settings-sarvam-http-tts.py +++ b/examples/foundational/55ze-update-settings-sarvam-http-tts.py @@ -96,7 +96,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): async def on_client_connected(transport, client): logger.info(f"Client connected") context.add_message( - {"role": "system", "content": "Please introduce yourself to the user."} + {"role": "user", "content": "Please introduce yourself to the user."} ) await task.queue_frames([LLMRunFrame()]) diff --git a/examples/foundational/55ze-update-settings-sarvam-tts.py b/examples/foundational/55ze-update-settings-sarvam-tts.py index b36e6f81f..52876c595 100644 --- a/examples/foundational/55ze-update-settings-sarvam-tts.py +++ b/examples/foundational/55ze-update-settings-sarvam-tts.py @@ -91,7 +91,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): @transport.event_handler("on_client_connected") async def on_client_connected(transport, client): logger.info(f"Client connected") - context.add_message({"role": "system", "content": "Please introduce yourself to the user."}) + context.add_message({"role": "user", "content": "Please introduce yourself to the user."}) await task.queue_frames([LLMRunFrame()]) await asyncio.sleep(10) diff --git a/examples/foundational/55zf-update-settings-camb-tts.py b/examples/foundational/55zf-update-settings-camb-tts.py index 493ad0917..5c9987dc9 100644 --- a/examples/foundational/55zf-update-settings-camb-tts.py +++ b/examples/foundational/55zf-update-settings-camb-tts.py @@ -92,7 +92,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): @transport.event_handler("on_client_connected") async def on_client_connected(transport, client): logger.info(f"Client connected") - context.add_message({"role": "system", "content": "Please introduce yourself to the user."}) + context.add_message({"role": "user", "content": "Please introduce yourself to the user."}) await task.queue_frames([LLMRunFrame()]) await asyncio.sleep(10) diff --git a/examples/foundational/55zh-update-settings-resembleai-tts.py b/examples/foundational/55zh-update-settings-resembleai-tts.py index 2c5ef3b25..192e5d868 100644 --- a/examples/foundational/55zh-update-settings-resembleai-tts.py +++ b/examples/foundational/55zh-update-settings-resembleai-tts.py @@ -94,7 +94,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): @transport.event_handler("on_client_connected") async def on_client_connected(transport, client): logger.info(f"Client connected") - context.add_message({"role": "system", "content": "Please introduce yourself to the user."}) + context.add_message({"role": "user", "content": "Please introduce yourself to the user."}) await task.queue_frames([LLMRunFrame()]) await asyncio.sleep(10) diff --git a/examples/foundational/55zi-update-settings-azure-llm.py b/examples/foundational/55zi-update-settings-azure-llm.py index 5093ba560..21f65eabb 100644 --- a/examples/foundational/55zi-update-settings-azure-llm.py +++ b/examples/foundational/55zi-update-settings-azure-llm.py @@ -99,7 +99,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): @transport.event_handler("on_client_connected") async def on_client_connected(transport, client): logger.info(f"Client connected") - context.add_message({"role": "system", "content": "Please introduce yourself to the user."}) + context.add_message({"role": "user", "content": "Please introduce yourself to the user."}) await task.queue_frames([LLMRunFrame()]) await asyncio.sleep(10) diff --git a/examples/foundational/55zi-update-settings-openai-llm.py b/examples/foundational/55zi-update-settings-openai-llm.py index 6af897217..1eddc6bb4 100644 --- a/examples/foundational/55zi-update-settings-openai-llm.py +++ b/examples/foundational/55zi-update-settings-openai-llm.py @@ -97,7 +97,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): @transport.event_handler("on_client_connected") async def on_client_connected(transport, client): logger.info(f"Client connected") - context.add_message({"role": "system", "content": "Please introduce yourself to the user."}) + context.add_message({"role": "user", "content": "Please introduce yourself to the user."}) await task.queue_frames([LLMRunFrame()]) await asyncio.sleep(10) diff --git a/examples/foundational/55zj-update-settings-anthropic-llm.py b/examples/foundational/55zj-update-settings-anthropic-llm.py index 8417d0dcd..c36ee758d 100644 --- a/examples/foundational/55zj-update-settings-anthropic-llm.py +++ b/examples/foundational/55zj-update-settings-anthropic-llm.py @@ -96,7 +96,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): @transport.event_handler("on_client_connected") async def on_client_connected(transport, client): logger.info(f"Client connected") - context.add_message({"role": "system", "content": "Please introduce yourself to the user."}) + context.add_message({"role": "user", "content": "Please introduce yourself to the user."}) await task.queue_frames([LLMRunFrame()]) await asyncio.sleep(10) diff --git a/examples/foundational/55zk-update-settings-google-llm.py b/examples/foundational/55zk-update-settings-google-llm.py index 94b15c886..0eaa89d10 100644 --- a/examples/foundational/55zk-update-settings-google-llm.py +++ b/examples/foundational/55zk-update-settings-google-llm.py @@ -96,7 +96,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): @transport.event_handler("on_client_connected") async def on_client_connected(transport, client): logger.info(f"Client connected") - context.add_message({"role": "system", "content": "Please introduce yourself to the user."}) + context.add_message({"role": "user", "content": "Please introduce yourself to the user."}) await task.queue_frames([LLMRunFrame()]) await asyncio.sleep(10) diff --git a/examples/foundational/55zk-update-settings-google-vertex-llm.py b/examples/foundational/55zk-update-settings-google-vertex-llm.py index 1158c4635..95e84fec5 100644 --- a/examples/foundational/55zk-update-settings-google-vertex-llm.py +++ b/examples/foundational/55zk-update-settings-google-vertex-llm.py @@ -99,7 +99,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): @transport.event_handler("on_client_connected") async def on_client_connected(transport, client): logger.info(f"Client connected") - context.add_message({"role": "system", "content": "Please introduce yourself to the user."}) + context.add_message({"role": "user", "content": "Please introduce yourself to the user."}) await task.queue_frames([LLMRunFrame()]) await asyncio.sleep(10) diff --git a/examples/foundational/55zm-update-settings-gemini-live-vertex.py b/examples/foundational/55zm-update-settings-gemini-live-vertex.py index 96bd7a1c6..7e01fdf52 100644 --- a/examples/foundational/55zm-update-settings-gemini-live-vertex.py +++ b/examples/foundational/55zm-update-settings-gemini-live-vertex.py @@ -53,16 +53,10 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): credentials=os.getenv("GOOGLE_VERTEX_TEST_CREDENTIALS"), project_id=os.getenv("GOOGLE_CLOUD_PROJECT_ID"), location=os.getenv("GOOGLE_CLOUD_LOCATION"), + system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", ) - messages = [ - { - "role": "system", - "content": "You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", - }, - ] - - context = LLMContext(messages) + context = LLMContext() user_aggregator, assistant_aggregator = LLMContextAggregatorPair(context) pipeline = Pipeline( diff --git a/examples/foundational/55zm-update-settings-gemini-live.py b/examples/foundational/55zm-update-settings-gemini-live.py index a00343ac3..5d8f4e845 100644 --- a/examples/foundational/55zm-update-settings-gemini-live.py +++ b/examples/foundational/55zm-update-settings-gemini-live.py @@ -51,16 +51,12 @@ transport_params = { async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): logger.info(f"Starting bot") - llm = GeminiLiveLLMService(api_key=os.getenv("GOOGLE_API_KEY")) + llm = GeminiLiveLLMService( + api_key=os.getenv("GOOGLE_API_KEY"), + system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + ) - messages = [ - { - "role": "system", - "content": "You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", - }, - ] - - context = LLMContext(messages) + context = LLMContext() user_aggregator, assistant_aggregator = LLMContextAggregatorPair(context) pipeline = Pipeline( diff --git a/examples/foundational/55zp-update-settings-aws-bedrock-llm.py b/examples/foundational/55zp-update-settings-aws-bedrock-llm.py index f4f8f8815..0ae2e0c57 100644 --- a/examples/foundational/55zp-update-settings-aws-bedrock-llm.py +++ b/examples/foundational/55zp-update-settings-aws-bedrock-llm.py @@ -98,7 +98,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): @transport.event_handler("on_client_connected") async def on_client_connected(transport, client): logger.info(f"Client connected") - context.add_message({"role": "system", "content": "Please introduce yourself to the user."}) + context.add_message({"role": "user", "content": "Please introduce yourself to the user."}) await task.queue_frames([LLMRunFrame()]) await asyncio.sleep(10) diff --git a/examples/foundational/55zq-update-settings-fal-stt.py b/examples/foundational/55zq-update-settings-fal-stt.py index 0811523f0..910b4d348 100644 --- a/examples/foundational/55zq-update-settings-fal-stt.py +++ b/examples/foundational/55zq-update-settings-fal-stt.py @@ -96,7 +96,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): @transport.event_handler("on_client_connected") async def on_client_connected(transport, client): logger.info(f"Client connected") - context.add_message({"role": "system", "content": "Please introduce yourself to the user."}) + context.add_message({"role": "user", "content": "Please introduce yourself to the user."}) await task.queue_frames([LLMRunFrame()]) await asyncio.sleep(10) diff --git a/examples/foundational/55zr-update-settings-gradium-stt.py b/examples/foundational/55zr-update-settings-gradium-stt.py index 952f2bb26..7b40638a5 100644 --- a/examples/foundational/55zr-update-settings-gradium-stt.py +++ b/examples/foundational/55zr-update-settings-gradium-stt.py @@ -99,7 +99,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): @transport.event_handler("on_client_connected") async def on_client_connected(transport, client): logger.info(f"Client connected") - context.add_message({"role": "system", "content": "Please introduce yourself to the user."}) + context.add_message({"role": "user", "content": "Please introduce yourself to the user."}) await task.queue_frames([LLMRunFrame()]) await asyncio.sleep(10) diff --git a/examples/foundational/55zt-update-settings-nvidia-segmented-stt.py b/examples/foundational/55zt-update-settings-nvidia-segmented-stt.py index b46096e0b..abec5cb7a 100644 --- a/examples/foundational/55zt-update-settings-nvidia-segmented-stt.py +++ b/examples/foundational/55zt-update-settings-nvidia-segmented-stt.py @@ -96,7 +96,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): @transport.event_handler("on_client_connected") async def on_client_connected(transport, client): logger.info(f"Client connected") - context.add_message({"role": "system", "content": "Please introduce yourself to the user."}) + context.add_message({"role": "user", "content": "Please introduce yourself to the user."}) await task.queue_frames([LLMRunFrame()]) await asyncio.sleep(10) diff --git a/examples/foundational/55zt-update-settings-nvidia-stt.py b/examples/foundational/55zt-update-settings-nvidia-stt.py index 2efa824c3..116035aa2 100644 --- a/examples/foundational/55zt-update-settings-nvidia-stt.py +++ b/examples/foundational/55zt-update-settings-nvidia-stt.py @@ -97,7 +97,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): @transport.event_handler("on_client_connected") async def on_client_connected(transport, client): logger.info(f"Client connected") - context.add_message({"role": "system", "content": "Please introduce yourself to the user."}) + context.add_message({"role": "user", "content": "Please introduce yourself to the user."}) await task.queue_frames([LLMRunFrame()]) await asyncio.sleep(10) diff --git a/examples/foundational/55zu-update-settings-openai-realtime-stt.py b/examples/foundational/55zu-update-settings-openai-realtime-stt.py index 9f0e1dc89..846775cd4 100644 --- a/examples/foundational/55zu-update-settings-openai-realtime-stt.py +++ b/examples/foundational/55zu-update-settings-openai-realtime-stt.py @@ -97,7 +97,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): @transport.event_handler("on_client_connected") async def on_client_connected(transport, client): logger.info(f"Client connected") - context.add_message({"role": "system", "content": "Please introduce yourself to the user."}) + context.add_message({"role": "user", "content": "Please introduce yourself to the user."}) await task.queue_frames([LLMRunFrame()]) await asyncio.sleep(10) diff --git a/examples/foundational/55zv-update-settings-asyncai-http-tts.py b/examples/foundational/55zv-update-settings-asyncai-http-tts.py index 29a774fae..cea5ab72f 100644 --- a/examples/foundational/55zv-update-settings-asyncai-http-tts.py +++ b/examples/foundational/55zv-update-settings-asyncai-http-tts.py @@ -103,7 +103,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): async def on_client_connected(transport, client): logger.info(f"Client connected") context.add_message( - {"role": "system", "content": "Please introduce yourself to the user."} + {"role": "user", "content": "Please introduce yourself to the user."} ) await task.queue_frames([LLMRunFrame()]) diff --git a/examples/foundational/55zv-update-settings-asyncai-tts.py b/examples/foundational/55zv-update-settings-asyncai-tts.py index b9c35ebbd..947b5c852 100644 --- a/examples/foundational/55zv-update-settings-asyncai-tts.py +++ b/examples/foundational/55zv-update-settings-asyncai-tts.py @@ -97,7 +97,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): @transport.event_handler("on_client_connected") async def on_client_connected(transport, client): logger.info(f"Client connected") - context.add_message({"role": "system", "content": "Please introduce yourself to the user."}) + context.add_message({"role": "user", "content": "Please introduce yourself to the user."}) await task.queue_frames([LLMRunFrame()]) await asyncio.sleep(10) diff --git a/examples/foundational/55zw-update-settings-gradium-tts.py b/examples/foundational/55zw-update-settings-gradium-tts.py index 52f7c73c5..f81267d1c 100644 --- a/examples/foundational/55zw-update-settings-gradium-tts.py +++ b/examples/foundational/55zw-update-settings-gradium-tts.py @@ -95,7 +95,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): @transport.event_handler("on_client_connected") async def on_client_connected(transport, client): logger.info(f"Client connected") - context.add_message({"role": "system", "content": "Please introduce yourself to the user."}) + context.add_message({"role": "user", "content": "Please introduce yourself to the user."}) await task.queue_frames([LLMRunFrame()]) await asyncio.sleep(10) diff --git a/examples/foundational/55zx-update-settings-cerebras-llm.py b/examples/foundational/55zx-update-settings-cerebras-llm.py index c6d27d8e5..3a9bf5510 100644 --- a/examples/foundational/55zx-update-settings-cerebras-llm.py +++ b/examples/foundational/55zx-update-settings-cerebras-llm.py @@ -97,7 +97,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): @transport.event_handler("on_client_connected") async def on_client_connected(transport, client): logger.info(f"Client connected") - context.add_message({"role": "system", "content": "Please introduce yourself to the user."}) + context.add_message({"role": "user", "content": "Please introduce yourself to the user."}) await task.queue_frames([LLMRunFrame()]) await asyncio.sleep(10) diff --git a/examples/foundational/55zy-update-settings-deepseek-llm.py b/examples/foundational/55zy-update-settings-deepseek-llm.py index 23e314f8b..3a2dd38a8 100644 --- a/examples/foundational/55zy-update-settings-deepseek-llm.py +++ b/examples/foundational/55zy-update-settings-deepseek-llm.py @@ -97,7 +97,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): @transport.event_handler("on_client_connected") async def on_client_connected(transport, client): logger.info(f"Client connected") - context.add_message({"role": "system", "content": "Please introduce yourself to the user."}) + context.add_message({"role": "user", "content": "Please introduce yourself to the user."}) await task.queue_frames([LLMRunFrame()]) await asyncio.sleep(10) diff --git a/examples/foundational/55zz-update-settings-fireworks-llm.py b/examples/foundational/55zz-update-settings-fireworks-llm.py index 9ea0c9343..fceaadbc2 100644 --- a/examples/foundational/55zz-update-settings-fireworks-llm.py +++ b/examples/foundational/55zz-update-settings-fireworks-llm.py @@ -98,7 +98,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): @transport.event_handler("on_client_connected") async def on_client_connected(transport, client): logger.info(f"Client connected") - context.add_message({"role": "system", "content": "Please introduce yourself to the user."}) + context.add_message({"role": "user", "content": "Please introduce yourself to the user."}) await task.queue_frames([LLMRunFrame()]) await asyncio.sleep(10) diff --git a/examples/foundational/55zza-update-settings-grok-llm.py b/examples/foundational/55zza-update-settings-grok-llm.py index ca537a705..6ea0cd3c3 100644 --- a/examples/foundational/55zza-update-settings-grok-llm.py +++ b/examples/foundational/55zza-update-settings-grok-llm.py @@ -97,7 +97,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): @transport.event_handler("on_client_connected") async def on_client_connected(transport, client): logger.info(f"Client connected") - context.add_message({"role": "system", "content": "Please introduce yourself to the user."}) + context.add_message({"role": "user", "content": "Please introduce yourself to the user."}) await task.queue_frames([LLMRunFrame()]) await asyncio.sleep(10) diff --git a/examples/foundational/55zzb-update-settings-groq-llm.py b/examples/foundational/55zzb-update-settings-groq-llm.py index 3f2ffdb79..9f655f7fc 100644 --- a/examples/foundational/55zzb-update-settings-groq-llm.py +++ b/examples/foundational/55zzb-update-settings-groq-llm.py @@ -98,7 +98,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): @transport.event_handler("on_client_connected") async def on_client_connected(transport, client): logger.info(f"Client connected") - context.add_message({"role": "system", "content": "Please introduce yourself to the user."}) + context.add_message({"role": "user", "content": "Please introduce yourself to the user."}) await task.queue_frames([LLMRunFrame()]) await asyncio.sleep(10) diff --git a/examples/foundational/55zzc-update-settings-mistral-llm.py b/examples/foundational/55zzc-update-settings-mistral-llm.py index b9d591146..a7cb56446 100644 --- a/examples/foundational/55zzc-update-settings-mistral-llm.py +++ b/examples/foundational/55zzc-update-settings-mistral-llm.py @@ -97,7 +97,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): @transport.event_handler("on_client_connected") async def on_client_connected(transport, client): logger.info(f"Client connected") - context.add_message({"role": "system", "content": "Please introduce yourself to the user."}) + context.add_message({"role": "user", "content": "Please introduce yourself to the user."}) await task.queue_frames([LLMRunFrame()]) await asyncio.sleep(10) diff --git a/examples/foundational/55zzd-update-settings-nvidia-llm.py b/examples/foundational/55zzd-update-settings-nvidia-llm.py index 389b51f06..13593b57b 100644 --- a/examples/foundational/55zzd-update-settings-nvidia-llm.py +++ b/examples/foundational/55zzd-update-settings-nvidia-llm.py @@ -98,7 +98,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): @transport.event_handler("on_client_connected") async def on_client_connected(transport, client): logger.info(f"Client connected") - context.add_message({"role": "system", "content": "Please introduce yourself to the user."}) + context.add_message({"role": "user", "content": "Please introduce yourself to the user."}) await task.queue_frames([LLMRunFrame()]) await asyncio.sleep(10) diff --git a/examples/foundational/55zze-update-settings-ollama-llm.py b/examples/foundational/55zze-update-settings-ollama-llm.py index d413267a3..a6904895b 100644 --- a/examples/foundational/55zze-update-settings-ollama-llm.py +++ b/examples/foundational/55zze-update-settings-ollama-llm.py @@ -97,7 +97,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): @transport.event_handler("on_client_connected") async def on_client_connected(transport, client): logger.info(f"Client connected") - context.add_message({"role": "system", "content": "Please introduce yourself to the user."}) + context.add_message({"role": "user", "content": "Please introduce yourself to the user."}) await task.queue_frames([LLMRunFrame()]) await asyncio.sleep(10) diff --git a/examples/foundational/55zzf-update-settings-openrouter-llm.py b/examples/foundational/55zzf-update-settings-openrouter-llm.py index c34d885f1..124e5f04a 100644 --- a/examples/foundational/55zzf-update-settings-openrouter-llm.py +++ b/examples/foundational/55zzf-update-settings-openrouter-llm.py @@ -97,7 +97,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): @transport.event_handler("on_client_connected") async def on_client_connected(transport, client): logger.info(f"Client connected") - context.add_message({"role": "system", "content": "Please introduce yourself to the user."}) + context.add_message({"role": "user", "content": "Please introduce yourself to the user."}) await task.queue_frames([LLMRunFrame()]) await asyncio.sleep(10) diff --git a/examples/foundational/55zzh-update-settings-qwen-llm.py b/examples/foundational/55zzh-update-settings-qwen-llm.py index 584cb23ea..7a35fd124 100644 --- a/examples/foundational/55zzh-update-settings-qwen-llm.py +++ b/examples/foundational/55zzh-update-settings-qwen-llm.py @@ -98,7 +98,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): @transport.event_handler("on_client_connected") async def on_client_connected(transport, client): logger.info(f"Client connected") - context.add_message({"role": "system", "content": "Please introduce yourself to the user."}) + context.add_message({"role": "user", "content": "Please introduce yourself to the user."}) await task.queue_frames([LLMRunFrame()]) await asyncio.sleep(10) diff --git a/examples/foundational/55zzi-update-settings-sambanova-llm.py b/examples/foundational/55zzi-update-settings-sambanova-llm.py index dc246f2cd..73f3316db 100644 --- a/examples/foundational/55zzi-update-settings-sambanova-llm.py +++ b/examples/foundational/55zzi-update-settings-sambanova-llm.py @@ -97,7 +97,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): @transport.event_handler("on_client_connected") async def on_client_connected(transport, client): logger.info(f"Client connected") - context.add_message({"role": "system", "content": "Please introduce yourself to the user."}) + context.add_message({"role": "user", "content": "Please introduce yourself to the user."}) await task.queue_frames([LLMRunFrame()]) await asyncio.sleep(10) diff --git a/examples/foundational/55zzj-update-settings-together-llm.py b/examples/foundational/55zzj-update-settings-together-llm.py index bd855bcff..314b81223 100644 --- a/examples/foundational/55zzj-update-settings-together-llm.py +++ b/examples/foundational/55zzj-update-settings-together-llm.py @@ -98,7 +98,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): @transport.event_handler("on_client_connected") async def on_client_connected(transport, client): logger.info(f"Client connected") - context.add_message({"role": "system", "content": "Please introduce yourself to the user."}) + context.add_message({"role": "user", "content": "Please introduce yourself to the user."}) await task.queue_frames([LLMRunFrame()]) await asyncio.sleep(10) diff --git a/examples/foundational/55zzk-update-settings-aws-nova-sonic-llm.py b/examples/foundational/55zzk-update-settings-aws-nova-sonic-llm.py index 301270797..c6789a521 100644 --- a/examples/foundational/55zzk-update-settings-aws-nova-sonic-llm.py +++ b/examples/foundational/55zzk-update-settings-aws-nova-sonic-llm.py @@ -52,20 +52,10 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): secret_access_key=os.getenv("AWS_SECRET_ACCESS_KEY"), access_key_id=os.getenv("AWS_ACCESS_KEY_ID"), region=os.getenv("AWS_REGION"), + system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", ) - messages = [ - { - "role": "system", - "content": "You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", - }, - { - "role": "user", - "content": "Tell me a fun fact!", - }, - ] - - context = LLMContext(messages) + context = LLMContext() user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()), @@ -93,7 +83,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): @transport.event_handler("on_client_connected") async def on_client_connected(transport, client): logger.info(f"Client connected") - messages.append({"role": "system", "content": "Please introduce yourself to the user."}) + context.add_message({"role": "user", "content": "Tell me a fun fact."}) await task.queue_frames([LLMRunFrame()]) await asyncio.sleep(10) diff --git a/examples/foundational/55zzl-update-settings-nvidia-tts.py b/examples/foundational/55zzl-update-settings-nvidia-tts.py index e667a9ca3..a6d26542a 100644 --- a/examples/foundational/55zzl-update-settings-nvidia-tts.py +++ b/examples/foundational/55zzl-update-settings-nvidia-tts.py @@ -92,7 +92,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): @transport.event_handler("on_client_connected") async def on_client_connected(transport, client): logger.info(f"Client connected") - context.add_message({"role": "system", "content": "Please introduce yourself to the user."}) + context.add_message({"role": "user", "content": "Please introduce yourself to the user."}) await task.queue_frames([LLMRunFrame()]) await asyncio.sleep(10) diff --git a/examples/foundational/55zzm-update-settings-speechmatics-tts.py b/examples/foundational/55zzm-update-settings-speechmatics-tts.py index 2e8bb46a6..2cce46ebb 100644 --- a/examples/foundational/55zzm-update-settings-speechmatics-tts.py +++ b/examples/foundational/55zzm-update-settings-speechmatics-tts.py @@ -97,7 +97,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): async def on_client_connected(transport, client): logger.info(f"Client connected") context.add_message( - {"role": "system", "content": "Please introduce yourself to the user."} + {"role": "user", "content": "Please introduce yourself to the user."} ) await task.queue_frames([LLMRunFrame()]) diff --git a/examples/foundational/55zzn-update-settings-groq-stt.py b/examples/foundational/55zzn-update-settings-groq-stt.py index d6dac9e1f..f3f3ffa01 100644 --- a/examples/foundational/55zzn-update-settings-groq-stt.py +++ b/examples/foundational/55zzn-update-settings-groq-stt.py @@ -99,7 +99,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): @transport.event_handler("on_client_connected") async def on_client_connected(transport, client): logger.info(f"Client connected") - context.add_message({"role": "system", "content": "Please introduce yourself to the user."}) + context.add_message({"user": "system", "content": "Please introduce yourself to the user."}) await task.queue_frames([LLMRunFrame()]) await asyncio.sleep(10) diff --git a/examples/foundational/56-lemonslice-transport.py b/examples/foundational/56-lemonslice-transport.py index 8dc400841..aefa533e4 100644 --- a/examples/foundational/56-lemonslice-transport.py +++ b/examples/foundational/56-lemonslice-transport.py @@ -103,7 +103,7 @@ async def main(): # Kick off the conversation. context.add_message( { - "role": "system", + "role": "user", "content": "Start by greeting the user and ask how you can help.", } ) diff --git a/scripts/evals/eval.py b/scripts/evals/eval.py index c2316e123..992eb43c7 100644 --- a/scripts/evals/eval.py +++ b/scripts/evals/eval.py @@ -51,6 +51,7 @@ from pipecat.runner.types import RunnerArguments from pipecat.services.cartesia.tts import CartesiaTTSService, CartesiaTTSSettings from pipecat.services.deepgram.stt import DeepgramSTTService, DeepgramSTTSettings from pipecat.services.llm_service import FunctionCallParams +from pipecat.services.openai.base_llm import OpenAILLMSettings from pipecat.services.openai.llm import OpenAILLMService from pipecat.transports.daily.transport import DailyParams, DailyTransport @@ -256,30 +257,6 @@ async def run_eval_pipeline( ), ) - # Load example prompt depending on image. - example_prompt = "" - example_image: Optional[ImageFile] = None - if isinstance(eval_config.prompt, str): - example_prompt = eval_config.prompt - elif isinstance(eval_config.prompt, tuple): - example_prompt, example_image = eval_config.prompt - - common_system_prompt = ( - "You should only call the eval function if:\n" - "- The user explicitly attempts to answer the question, AND\n" - f"- Their answer can be cleanly evaluated using: {eval_config.eval}\n" - "Ignore greetings, comments, non-answers, or requests for clarification.\n" - "Numerical word answers are allowed (e.g., 'five' is the same as '5').\n" - ) - if eval_config.eval_speaks_first: - system_prompt = f"You are an evaluation agent, be extremly brief. You will start the conversation by saying: '{example_prompt}'. {common_system_prompt}" - else: - system_prompt = f"You are an evaluation agent, be extremly brief. First, ask one question: {example_prompt}. {common_system_prompt}" - - llm = OpenAILLMService(api_key=os.getenv("OPENAI_API_KEY"), system_instruction=system_prompt) - - llm.register_function("eval_function", eval_runner.function_assert_eval) - eval_function = FunctionSchema( name="eval_function", description=( @@ -303,6 +280,33 @@ async def run_eval_pipeline( ) tools = ToolsSchema(standard_tools=[eval_function]) + # Load example prompt depending on image. + example_prompt = "" + example_image: Optional[ImageFile] = None + if isinstance(eval_config.prompt, str): + example_prompt = eval_config.prompt + elif isinstance(eval_config.prompt, tuple): + example_prompt, example_image = eval_config.prompt + + common_system_prompt = ( + "You should only call the eval function if:\n" + "- The user explicitly attempts to answer the question, AND\n" + f"- Their answer can be cleanly evaluated using: {eval_config.eval}\n" + "Ignore greetings, comments, non-answers, or requests for clarification.\n" + "Numerical word answers are allowed (e.g., 'five' is the same as '5').\n" + ) + if eval_config.eval_speaks_first: + system_prompt = f"You are an evaluation agent, be extremly brief. You will start the conversation by saying: '{example_prompt}'. {common_system_prompt}" + else: + system_prompt = f"You are an evaluation agent, be extremly brief. First, ask one question: {example_prompt}. {common_system_prompt}" + + llm = OpenAILLMService( + api_key=os.getenv("OPENAI_API_KEY"), + settings=OpenAILLMSettings(system_instruction=system_prompt), + ) + + llm.register_function("eval_function", eval_runner.function_assert_eval) + context = LLMContext(tools=tools) context_aggregator = LLMContextAggregatorPair( context, From c243850cf106784b9d9062181d931c3f492a50bc Mon Sep 17 00:00:00 2001 From: filipi87 Date: Fri, 6 Mar 2026 16:14:23 -0300 Subject: [PATCH 0832/1060] Removing observer from the inworld example. --- examples/foundational/07zb-interruptible-inworld.py | 11 +---------- 1 file changed, 1 insertion(+), 10 deletions(-) diff --git a/examples/foundational/07zb-interruptible-inworld.py b/examples/foundational/07zb-interruptible-inworld.py index 0865a4e92..6e2cd7aed 100644 --- a/examples/foundational/07zb-interruptible-inworld.py +++ b/examples/foundational/07zb-interruptible-inworld.py @@ -10,8 +10,7 @@ from dotenv import load_dotenv from loguru import logger from pipecat.audio.vad.silero import SileroVADAnalyzer -from pipecat.frames.frames import LLMRunFrame, TTSTextFrame -from pipecat.observers.loggers.debug_log_observer import DebugLogObserver, FrameEndpoint +from pipecat.frames.frames import LLMRunFrame from pipecat.pipeline.pipeline import Pipeline from pipecat.pipeline.runner import PipelineRunner from pipecat.pipeline.task import PipelineParams, PipelineTask @@ -25,7 +24,6 @@ from pipecat.runner.utils import create_transport from pipecat.services.deepgram.stt import DeepgramSTTService from pipecat.services.inworld.tts import InworldTTSService, InworldTTSSettings from pipecat.services.openai.llm import OpenAILLMService, OpenAILLMSettings -from pipecat.transports.base_output import BaseOutputTransport from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams @@ -94,13 +92,6 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): enable_metrics=True, enable_usage_metrics=True, ), - observers=[ - DebugLogObserver( - frame_types={ - TTSTextFrame: (BaseOutputTransport, FrameEndpoint.SOURCE), - } - ), - ], idle_timeout_secs=runner_args.pipeline_idle_timeout_secs, ) From 921e9e1fc904dd0f4ada3300ede1964bbbad14f3 Mon Sep 17 00:00:00 2001 From: filipi87 Date: Fri, 6 Mar 2026 16:15:10 -0300 Subject: [PATCH 0833/1060] Refactoring TTS services to allow concurrent audio contexts. --- src/pipecat/services/tts_service.py | 794 ++++++++++++++++------------ 1 file changed, 453 insertions(+), 341 deletions(-) diff --git a/src/pipecat/services/tts_service.py b/src/pipecat/services/tts_service.py index 4285e14f9..db695fd52 100644 --- a/src/pipecat/services/tts_service.py +++ b/src/pipecat/services/tts_service.py @@ -97,6 +97,15 @@ class TextAggregationMode(str, Enum): return self.value +@dataclass +class _WordTimestampEntry: + """Internal: word timestamp routed through an audio context queue.""" + + word: str + timestamp: float + context_id: str + + class TTSService(AIService): """Base class for text-to-speech services. @@ -131,6 +140,8 @@ class TTSService(AIService): _settings: TTSSettings + _CONTEXT_KEEPALIVE = object() + def __init__( self, *, @@ -141,6 +152,8 @@ class TTSService(AIService): push_text_frames: bool = True, # if True, TTSService will push TTSStoppedFrames, otherwise subclass must do it push_stop_frames: bool = False, + # if True, TTSService will push TTSStartedFrames and create audio contexts automatically + push_start_frame: bool = False, # if push_stop_frames is True, wait for this idle period before pushing TTSStoppedFrame stop_frame_timeout_s: float = 2.0, # if True, TTSService will push silence audio frames after TTSStoppedFrame @@ -154,8 +167,6 @@ class TTSService(AIService): append_trailing_space: bool = False, # TTS output sample rate sample_rate: Optional[int] = None, - # if True, enables word-level timestamp tracking and synchronization - supports_word_timestamps: bool = False, # Text aggregator to aggregate incoming tokens and decide when to push to the TTS. text_aggregator: Optional[BaseTextAggregator] = None, # Types of text aggregations that should not be spoken. @@ -174,6 +185,8 @@ class TTSService(AIService): # Audio transport destination of the generated frames. transport_destination: Optional[str] = None, settings: Optional[TTSSettings] = None, + # if True, the context ID is reused within an LLM turn + reuse_context_id_within_turn: bool = True, **kwargs, ): """Initialize the TTS service. @@ -191,6 +204,9 @@ class TTSService(AIService): push_text_frames: Whether to push TextFrames and LLMFullResponseEndFrames. push_stop_frames: Whether to automatically push TTSStoppedFrames. + push_start_frame: Whether to automatically create audio contexts and push TTSStartedFrames. + When True, the base class handles ``create_audio_context`` and yields ``TTSStartedFrame`` + before each synthesis call, so ``run_tts`` implementations do not need to. stop_frame_timeout_s: Idle time before pushing TTSStoppedFrame when push_stop_frames is True. push_silence_after_stop: Whether to push silence audio after TTSStoppedFrame. silence_time_s: Duration of silence to push when push_silence_after_stop is True. @@ -198,9 +214,6 @@ class TTSService(AIService): append_trailing_space: Whether to append a trailing space to text before sending to TTS. This helps prevent some TTS services from vocalizing trailing punctuation (e.g., "dot"). sample_rate: Output sample rate for generated audio. - supports_word_timestamps: Whether this service supports word-level timestamp tracking. - When True, enables synchronization of audio with spoken words so only spoken words - are added to the conversation context. text_aggregator: Custom text aggregator for processing incoming text. .. deprecated:: 0.0.95 @@ -220,6 +233,8 @@ class TTSService(AIService): transport_destination: Destination for generated audio frames. settings: The runtime-updatable settings for the TTS service. + reuse_context_id_within_turn: Whether the service should reuse context IDs within the + same turn. **kwargs: Additional arguments passed to the parent AIService. """ super().__init__( @@ -256,6 +271,7 @@ class TTSService(AIService): self._text_aggregation_mode: TextAggregationMode = text_aggregation_mode self._push_text_frames: bool = push_text_frames self._push_stop_frames: bool = push_stop_frames + self._push_start_frame: bool = push_start_frame self._stop_frame_timeout_s: float = stop_frame_timeout_s self._push_silence_after_stop: bool = push_silence_after_stop self._silence_time_s: float = silence_time_s @@ -304,18 +320,43 @@ class TTSService(AIService): self._streamed_text: str = "" self._text_aggregation_metrics_started: bool = False - # Word timestamp state (active when supports_word_timestamps=True) - self._supports_word_timestamps: bool = supports_word_timestamps + # Word timestamp state self._initial_word_timestamp: int = -1 self._initial_word_times: List[Tuple[str, float, Optional[str]]] = [] - self._words_task: Optional[asyncio.Task] = None + # PTS of the last word frame pushed via _add_word_timestamps, used to assign + # correct PTS to sentinel frames ("TTSStoppedFrame", "Reset") that follow. + self._word_last_pts: int = 0 self._llm_response_started: bool = False + self._reuse_context_id_within_turn: bool = reuse_context_id_within_turn + + # _turn_context_id: + # Set on LLMFullResponseStartFrame and cleared after LLMFullResponseEndFrame + # is processed (i.e. after flush). All sentences within one LLM turn share + # this ID so the TTS service groups them into a single audio context. + # Temporarily set to None for TTSSpeakFrame utterances, which are standalone. + # + # _playing_context_id (playback-side cursor): + # Set by _audio_context_task_handler as it dequeues contexts for playback. + # Cleared by reset_active_audio_context() on interruption. Used by + # has_active_audio_context() and get_active_audio_context_id(). + # + # Both fields may hold the same value during a turn, but + # they clear at different times: _turn_context_id is cleared when the LLM turn + # ends (synthesis done) while _playing_context_id remains set until the audio + # finishes playing. Merging them would null out the playback cursor prematurely. + self._playing_context_id: Optional[str] = None + self._turn_context_id: Optional[str] = None + self._audio_contexts: Dict[str, asyncio.Queue] = {} + self._audio_context_task: Optional[asyncio.Task] = None self._register_event_handler("on_connected") self._register_event_handler("on_disconnected") self._register_event_handler("on_connection_error") self._register_event_handler("on_tts_request") + # Whether the TTS process is currently yielding audio frames synchronously. + self._is_yielding_frames_synchronously = False + @property def _is_streaming_tokens(self) -> bool: """Whether the service is streaming tokens directly without sentence aggregation.""" @@ -417,13 +458,14 @@ class TTSService(AIService): await self._update_settings(settings_cls(voice=voice)) def create_context_id(self) -> str: - """Generate a unique context ID for a TTS request. - - This method can be overridden by subclasses to provide custom context ID generation. + """Generate or reuse a context ID based on concurrent TTS support. Returns: - A unique string identifier for the TTS context. + A context ID string for the TTS request. """ + if self._reuse_context_id_within_turn and self._turn_context_id: + self._refresh_audio_context(self._turn_context_id) + return self._turn_context_id return str(uuid.uuid4()) # Converts the text to audio. @@ -466,8 +508,13 @@ class TTSService(AIService): return text + " " return text - async def flush_audio(self): - """Flush any buffered audio data.""" + async def flush_audio(self, context_id: Optional[str] = None): + """Flush any buffered audio data. + + Args: + context_id: The specific context to flush. If None, falls back to the + currently active context (for non-concurrent services). + """ pass async def start(self, frame: StartFrame): @@ -480,8 +527,7 @@ class TTSService(AIService): self._sample_rate = self._init_sample_rate or frame.audio_out_sample_rate if self._push_stop_frames and not self._stop_frame_task: self._stop_frame_task = self.create_task(self._stop_frame_handler()) - if self._supports_word_timestamps: - self._create_words_task() + self._create_audio_context_task() async def stop(self, frame: EndFrame): """Stop the TTS service. @@ -493,8 +539,12 @@ class TTSService(AIService): if self._stop_frame_task: await self.cancel_task(self._stop_frame_task) self._stop_frame_task = None - if self._words_task: - await self._stop_words_task() + if self._audio_context_task: + # Indicate no more audio contexts are available; this will end the + # task cleanly after all contexts have been processed. + await self._contexts_queue.put(None) + await self._audio_context_task + self._audio_context_task = None async def cancel(self, frame: CancelFrame): """Cancel the TTS service. @@ -506,8 +556,7 @@ class TTSService(AIService): if self._stop_frame_task: await self.cancel_task(self._stop_frame_task) self._stop_frame_task = None - if self._words_task: - await self._stop_words_task() + await self._stop_audio_context_task() def add_text_transformer( self, @@ -584,6 +633,25 @@ class TTSService(AIService): await self.queue_frame(TTSSpeakFrame(text)) + async def on_turn_context_completed(self): + """Handle the completion of a turn.""" + # For HTTP services they emit the frames synchronously, so close the audio context here + # once all frames (including TTSTextFrame above) have been enqueued. + if self._is_yielding_frames_synchronously and self.audio_context_available( + self._turn_context_id + ): + if self._push_stop_frames: + await self.append_to_audio_context( + self._turn_context_id, TTSStoppedFrame(context_id=self._turn_context_id) + ) + await self.remove_audio_context(self._turn_context_id) + + # Flush any pending audio so the TTS service closes the current context. + await self.flush_audio(context_id=self._turn_context_id) + + # Reset the turn context ID + self._turn_context_id = None + async def process_frame(self, frame: Frame, direction: FrameDirection): """Process frames for text-to-speech conversion. @@ -615,6 +683,8 @@ class TTSService(AIService): await self.push_frame(frame, direction) elif isinstance(frame, LLMFullResponseStartFrame): self._llm_response_started = True + # New LLM turn → assign a fresh context ID shared by all sentences + self._turn_context_id = self.create_context_id() await self.push_frame(frame, direction) elif isinstance(frame, (LLMFullResponseEndFrame, EndFrame)): # We pause processing incoming frames if the LLM response included @@ -642,12 +712,17 @@ class TTSService(AIService): await self.push_frame(frame, direction) else: await self.push_frame(frame, direction) - # Flush any pending audio so the TTS service closes the current context. - if self._supports_word_timestamps: - await self.flush_audio() + + await self.on_turn_context_completed() elif isinstance(frame, TTSSpeakFrame): # Store if we were processing text or not so we can set it back. processing_text = self._processing_text + # TTSSpeakFrame is independent — temporarily clear the turn context + # so create_context_id() generates a fresh UUID for this utterance. + saved_turn_context_id = self._turn_context_id + self._turn_context_id = None + # Creating a new context_id for the TTS request. + self._turn_context_id = self.create_context_id() # If we are not receiving text from the LLM, we can assume that the SpeakFrame should be automatically added to the context push_assistant_aggregation = frame.append_to_context and not self._llm_response_started # Assumption: text in TTSSpeakFrame does not include inter-frame spaces @@ -656,10 +731,11 @@ class TTSService(AIService): append_tts_text_to_context=frame.append_to_context, push_assistant_aggregation=push_assistant_aggregation, ) + await self.on_turn_context_completed() # We pause processing incoming frames because we are sending data to # the TTS. We pause to avoid audio overlapping. await self._maybe_pause_frame_processing() - await self.flush_audio() + self._turn_context_id = saved_turn_context_id self._processing_text = processing_text elif isinstance(frame, TTSUpdateSettingsFrame): if frame.delta is not None: @@ -789,8 +865,17 @@ class TTSService(AIService): self._llm_response_started = False self._streamed_text = "" self._text_aggregation_metrics_started = False - if self._supports_word_timestamps: - await self.reset_word_timestamps() + await self.reset_word_timestamps() + + await self._stop_audio_context_task() + audio_contexts = self.get_audio_contexts() + if audio_contexts: + for ctx_id in audio_contexts: + await self.on_audio_context_interrupted(context_id=ctx_id) + self.reset_active_audio_context() + self._turn_context_id = None + self._word_last_pts = 0 + self._create_audio_context_task() async def _maybe_pause_frame_processing(self): if self._processing_text and self._pause_frame_processing: @@ -897,7 +982,12 @@ class TTSService(AIService): # Trigger event before starting TTS await self._call_event_handler("on_tts_request", context_id, prepared_text) - await self.process_generator(self.run_tts(prepared_text, context_id)) + if self._push_start_frame and not self.audio_context_available(context_id): + await self.create_audio_context(context_id) + await self.start_ttfb_metrics() + await self.append_to_audio_context(context_id, TTSStartedFrame(context_id=context_id)) + + await self.tts_process_generator(context_id, self.run_tts(prepared_text, context_id)) if not self._is_streaming_tokens: await self.stop_processing_metrics() @@ -916,9 +1006,44 @@ class TTSService(AIService): # Only override append_to_context if explicitly set if append_tts_text_to_context is not None: frame.append_to_context = append_tts_text_to_context - await self.push_frame(frame) - if push_assistant_aggregation: - await self.push_frame(LLMAssistantPushAggregationFrame()) + # For services using the audio context we are appending to the context, so it preserves the ordering. + if self.audio_context_available(context_id): + await self.append_to_audio_context(context_id, frame) + if push_assistant_aggregation: + await self.append_to_audio_context( + context_id, LLMAssistantPushAggregationFrame() + ) + else: + await self.push_frame(frame) + if push_assistant_aggregation: + await self.push_frame(LLMAssistantPushAggregationFrame()) + + async def tts_process_generator( + self, context_id: str, generator: AsyncGenerator[Frame | None, None] + ) -> bool: + """Process frames from an async generator, routing them through the audio context. + + All non-None frames yielded by the generator are appended to the audio context + identified by context_id. The audio context must be created by run_tts (via + create_audio_context) before the first frame is yielded. + + WebSocket services yield None to signal that audio will arrive via a separate + receive loop; those services manage context lifetime themselves (via remove_audio_context + in the receive loop on "done"). HTTP services never yield None and do NOT call + remove_audio_context in run_tts — the caller (_synthesize_text) closes the context + after appending any remaining frames (e.g. TTSTextFrame). + + Args: + context_id: The audio context to route frames to. + generator: An async generator yielding Frame objects or None. + + """ + is_yielding_frames = False + async for frame in generator: + if frame: + await self.append_to_audio_context(context_id, frame) + is_yielding_frames = True + self._is_yielding_frames_synchronously = is_yielding_frames async def _stop_frame_handler(self): has_started = False @@ -937,18 +1062,25 @@ class TTSService(AIService): has_started = False # - # Word timestamp methods (active when supports_word_timestamps=True) + # Word timestamp methods # async def start_word_timestamps(self): """Start tracking word timestamps from the current time.""" if self._initial_word_timestamp == -1: - self._initial_word_timestamp = self.get_clock().get_time() + current_time = self.get_clock().get_time() + # Initialize word timestamp tracking. Use the last emitted timestamp if it's ahead + # of current time to maintain continuity across overlapping audio contexts. + self._initial_word_timestamp = ( + self._word_last_pts if self._word_last_pts > current_time else current_time + ) # If we cached some initial word times (because we didn't receive # audio), let's add them now. if self._initial_word_times: - await self._add_word_timestamps(self._initial_word_times) + cached = self._initial_word_times.copy() self._initial_word_times = [] + for word, timestamp_seconds, ctx_id in cached: + await self._add_word_timestamps([(word, timestamp_seconds)], ctx_id) async def reset_word_timestamps(self): """Reset word timestamp tracking.""" @@ -957,75 +1089,281 @@ class TTSService(AIService): async def add_word_timestamps( self, word_times: List[Tuple[str, float]], context_id: Optional[str] = None ): - """Add word timestamps to the processing queue. + """Add word timestamps for processing. + + When an audio context exists for this context_id, timestamps are routed into the + per-context audio queue alongside audio frames so they are processed in strict + playback order by _handle_audio_context. Otherwise they are processed immediately + via _add_word_timestamps. Args: word_times: List of (word, timestamp) tuples where timestamp is in seconds. context_id: Unique identifier for the TTS context. """ - # Transform to include context_id in each tuple - word_times_with_context = [(word, timestamp, context_id) for word, timestamp in word_times] - - if self._initial_word_timestamp == -1: - # Cache word timestamps and don't add them until we have started - # (i.e. we have some audio). - self._initial_word_times.extend(word_times_with_context) + if context_id and self.audio_context_available(context_id): + for word, timestamp in word_times: + await self._audio_contexts[context_id].put( + _WordTimestampEntry( + word=word, + timestamp=timestamp, + context_id=context_id, + ) + ) else: - await self._add_word_timestamps(word_times_with_context) + await self._add_word_timestamps(word_times=word_times, context_id=context_id) - def _create_words_task(self): - if not self._words_task: - self._words_queue: asyncio.Queue = asyncio.Queue() - self._words_task = self.create_task(self._words_task_handler()) + async def _add_word_timestamps( + self, word_times: List[Tuple[str, float]], context_id: Optional[str] = None + ): + """Process word timestamps directly, building and pushing frames inline. - async def _stop_words_task(self): - if self._words_task: - await self.cancel_task(self._words_task) - self._words_task = None + This is the single processing path for all word timestamp events, used both + from _handle_audio_context (via _WordTimestampEntry) and from services that + do not use audio contexts. Sentinel entries drive control-frame emission: - async def _add_word_timestamps(self, word_times_with_context: List[Tuple[str, float, str]]): - for word, timestamp, context_id in word_times_with_context: - await self._words_queue.put((word, seconds_to_nanoseconds(timestamp), context_id)) + - ("Reset", 0): reset timestamp baseline; emit LLMFullResponseEndFrame if needed. + - ("TTSStoppedFrame", 0): emit TTSStoppedFrame. + - Any other entry: emit TTSTextFrame with a PTS relative to the baseline. - async def _words_task_handler(self): - last_pts = 0 - while True: - frame = None - (word, timestamp, context_id) = await self._words_queue.get() + When the baseline (_initial_word_timestamp) is not yet set, regular word entries + are cached in _initial_word_times and flushed once start_word_timestamps() is + called (i.e. when the first audio chunk is received). + """ + for word, timestamp in word_times: if word == "Reset" and timestamp == 0: await self.reset_word_timestamps() if self._llm_response_started: self._llm_response_started = False frame = LLMFullResponseEndFrame() - frame.pts = last_pts + frame.pts = self._word_last_pts + await self.push_frame(frame) elif word == "TTSStoppedFrame" and timestamp == 0: - frame = TTSStoppedFrame() - frame.pts = last_pts + frame = TTSStoppedFrame(context_id=context_id) + frame.pts = self._word_last_pts frame.context_id = context_id + await self.push_frame(frame) if context_id in self._tts_contexts: if self._tts_contexts[context_id].push_assistant_aggregation: await self.push_frame(LLMAssistantPushAggregationFrame()) else: - # Assumption: word-by-word text frames don't include spaces, so - # we can rely on the default includes_inter_frame_spaces=False - frame = TTSTextFrame(word, aggregated_by=AggregationType.WORD) - frame.pts = self._initial_word_timestamp + timestamp - frame.context_id = context_id - # Look up append_to_context from context metadata - if context_id in self._tts_contexts: - frame.append_to_context = self._tts_contexts[context_id].append_to_context - if frame: - last_pts = frame.pts - await self.push_frame(frame) - self._words_queue.task_done() + ts_ns = seconds_to_nanoseconds(timestamp) + if self._initial_word_timestamp == -1: + # Cache until we have audio and can compute PTS. + self._initial_word_times.append((word, timestamp, context_id)) + else: + # Assumption: word-by-word text frames don't include spaces, so + # we can rely on the default includes_inter_frame_spaces=False + frame = TTSTextFrame(word, aggregated_by=AggregationType.WORD) + frame.pts = self._initial_word_timestamp + ts_ns + frame.context_id = context_id + if context_id in self._tts_contexts: + frame.append_to_context = self._tts_contexts[context_id].append_to_context + self._word_last_pts = frame.pts + await self.push_frame(frame) + + # + # Audio context methods (active when using websocket-based TTS with context management) + # + + async def create_audio_context(self, context_id: str): + """Create a new audio context for grouping related audio. + + Args: + context_id: Unique identifier for the audio context. + """ + await self._contexts_queue.put(context_id) + self._audio_contexts[context_id] = asyncio.Queue() + logger.trace(f"{self} created audio context {context_id}") + + async def append_to_audio_context(self, context_id: str, frame: Frame): + """Append audio or control frame to an existing context. + + Args: + context_id: The context to append audio to. + frame: The audio or control frame to append. + """ + if self.audio_context_available(context_id): + logger.trace(f"{self} appending audio {frame} to audio context {context_id}") + await self._audio_contexts[context_id].put(frame) + elif context_id == self._turn_context_id: + # Sometimes the HTTP service can take more than 3 seconds without sending any audio + # So we are now recreating the context id while we are in the same turn + logger.debug(f"{self} recreating audio context {context_id}") + await self.create_audio_context(context_id) + logger.trace(f"{self} appending audio {frame} to audio context {context_id}") + await self._audio_contexts[context_id].put(frame) + else: + logger.warning(f"{self} unable to append audio to context {context_id}") + + async def remove_audio_context(self, context_id: str): + """Remove an existing audio context. + + Args: + context_id: The context to remove. + """ + if self.audio_context_available(context_id): + # We just mark the audio context for deletion by appending + # None. Once we reach None while handling audio we know we can + # safely remove the context. + logger.trace(f"{self} marking audio context {context_id} for deletion") + await self._audio_contexts[context_id].put(None) + else: + logger.warning(f"{self} unable to remove context {context_id}") + + def has_active_audio_context(self) -> bool: + """Check if there is an active audio context. + + Returns: + True if an active audio context exists, False otherwise. + """ + return self._playing_context_id is not None and self.audio_context_available( + self._playing_context_id + ) + + def get_audio_contexts(self) -> List[str]: + """Get a list of all available audio contexts.""" + return list(self._audio_contexts.keys()) + + def get_active_audio_context_id(self) -> Optional[str]: + """Get the active audio context ID. + + Returns: + The active context ID, or None if no context is active. + """ + return self._playing_context_id + + async def remove_active_audio_context(self): + """Remove the active audio context.""" + if self._playing_context_id: + await self.remove_audio_context(self._playing_context_id) + self.reset_active_audio_context() + + def reset_active_audio_context(self): + """Reset the active audio context.""" + self._playing_context_id = None + + def audio_context_available(self, context_id: str) -> bool: + """Check whether the given audio context is registered. + + Args: + context_id: The context ID to check. + + Returns: + True if the context exists and is available. + """ + return context_id in self._audio_contexts + + def _refresh_audio_context(self, context_id: str): + """Signal that the audio context is still in use, resetting the timeout.""" + if self.audio_context_available(context_id): + self._audio_contexts[context_id].put_nowait(TTSService._CONTEXT_KEEPALIVE) + + def _create_audio_context_task(self): + if not self._audio_context_task: + self._contexts_queue: asyncio.Queue = asyncio.Queue() + self._audio_contexts: Dict[str, asyncio.Queue] = {} + self._audio_context_task = self.create_task(self._audio_context_task_handler()) + + async def _stop_audio_context_task(self): + if self._audio_context_task: + await self.cancel_task(self._audio_context_task) + self._audio_context_task = None + + async def _audio_context_task_handler(self): + """In this task we process audio contexts in order.""" + running = True + while running: + context_id = await self._contexts_queue.get() + self._playing_context_id = context_id + + if context_id: + # Process the audio context until the context doesn't have more + # audio available (i.e. we find None). + await self._handle_audio_context(context_id) + + # We just finished processing the context, so we can safely remove it. + del self._audio_contexts[context_id] + await self.on_audio_context_completed(context_id=context_id) + self.reset_active_audio_context() + else: + running = False + + self._contexts_queue.task_done() + + async def _handle_audio_context(self, context_id: str): + """Process items from an audio context queue until it is exhausted.""" + AUDIO_CONTEXT_TIMEOUT = 3.0 + queue = self._audio_contexts[context_id] + running = True + timestamps_started = False + while running: + try: + frame = await asyncio.wait_for(queue.get(), timeout=AUDIO_CONTEXT_TIMEOUT) + if frame is TTSService._CONTEXT_KEEPALIVE: + # Context is still in use, reset the timeout. + continue + elif frame is None: + running = False + elif isinstance(frame, _WordTimestampEntry): + # _add_word_timestamps is the single processing path: it handles + # sentinel entries ("Reset", "TTSStoppedFrame") and regular words + # inline, keeping all word-frame logic in one place. + await self._add_word_timestamps( + [(frame.word, frame.timestamp)], frame.context_id + ) + continue + elif isinstance(frame, TTSAudioRawFrame): + # Set the word-timestamp baseline once, on the first audio chunk. + if not timestamps_started: + await self.stop_ttfb_metrics() + await self.start_word_timestamps() + timestamps_started = True + + if frame: + if isinstance(frame, ErrorFrame): + await self.push_error_frame(frame) + else: + await self.push_frame(frame) + except asyncio.TimeoutError: + # We didn't get audio, so let's consider this context finished. + logger.trace(f"{self} time out on audio context {context_id}") + break + + async def on_audio_context_interrupted(self, context_id: str): + """Called when an audio context is cancelled due to an interruption. + + Override this in a subclass to perform provider-specific cleanup (e.g. + sending a cancel/close message over the WebSocket) when the bot is + interrupted mid-speech. The audio context task has already been stopped + and the active context has **not** yet been reset when this is called, + so ``context_id`` reflects the context that was cut short. + + Args: + context_id: The ID of the audio context that was interrupted, or + ``None`` if no context was active at the time. + """ + pass + + async def on_audio_context_completed(self, context_id: str): + """Called after an audio context has finished playing all of its audio. + + Override this in a subclass to perform provider-specific cleanup (e.g. + sending a close-context message to free server-side resources) once an + audio context has been fully processed. The context entry has already + been removed from the internal context map, and the active context has + **not** yet been reset when this is called. + + Args: + context_id: The ID of the audio context that finished processing. + """ + pass class WordTTSService(TTSService): - """Deprecated. Use TTSService with supports_word_timestamps=True instead. + """Deprecated. Use TTSService directly instead. - .. deprecated:: 0.0.104 - Word timestamp functionality has been moved to TTSService. Pass - ``supports_word_timestamps=True`` to TTSService (or any subclass) instead. + .. deprecated:: 0.0.105 + Word timestamp functionality is now always active in TTSService. """ def __init__(self, **kwargs): @@ -1034,7 +1372,7 @@ class WordTTSService(TTSService): Args: **kwargs: Additional arguments passed to the parent TTSService. """ - super().__init__(supports_word_timestamps=True, **kwargs) + super().__init__(**kwargs) class WebsocketTTSService(TTSService, WebsocketService): @@ -1110,11 +1448,10 @@ class InterruptibleTTSService(WebsocketTTSService): class WebsocketWordTTSService(WebsocketTTSService): - """Deprecated. Use WebsocketTTSService with supports_word_timestamps=True instead. + """Deprecated. Use WebsocketTTSService directly instead. - .. deprecated:: 0.0.104 - Word timestamp functionality has been moved to TTSService. Pass - ``supports_word_timestamps=True`` to WebsocketTTSService instead. + .. deprecated:: 0.0.105 + Word timestamp functionality is now always active in TTSService. """ def __init__(self, *, reconnect_on_error: bool = True, **kwargs): @@ -1124,17 +1461,14 @@ class WebsocketWordTTSService(WebsocketTTSService): reconnect_on_error: Whether to automatically reconnect on websocket errors. **kwargs: Additional arguments passed to parent classes. """ - super().__init__( - supports_word_timestamps=True, reconnect_on_error=reconnect_on_error, **kwargs - ) + super().__init__(reconnect_on_error=reconnect_on_error, **kwargs) class InterruptibleWordTTSService(InterruptibleTTSService): - """Deprecated. Use InterruptibleTTSService with supports_word_timestamps=True instead. + """Deprecated. Use InterruptibleTTSService directly instead. - .. deprecated:: 0.0.104 - Word timestamp functionality has been moved to TTSService. Pass - ``supports_word_timestamps=True`` to InterruptibleTTSService instead. + .. deprecated:: 0.0.105 + Word timestamp functionality is now always active in TTSService. """ def __init__(self, **kwargs): @@ -1143,26 +1477,21 @@ class InterruptibleWordTTSService(InterruptibleTTSService): Args: **kwargs: Additional arguments passed to the parent InterruptibleTTSService. """ - super().__init__(supports_word_timestamps=True, **kwargs) + super().__init__(**kwargs) class AudioContextTTSService(WebsocketTTSService): - """Base class for websocket-based TTS services with audio context management. + """Deprecated. Inherit from WebsocketTTSService directly instead. - This is a base class for websocket-based TTS services that allow correlating - the generated audio with the requested text through audio contexts. + Audio context management (previously the main purpose of this class) is now + built into TTSService. This class is kept only for backwards compatibility. - Each request could be multiple sentences long which are grouped by - context. For this to work, the TTS service needs to support handling - multiple requests at once (i.e. multiple simultaneous contexts). - - The audio received from the TTS will be played in context order. That is, if - we requested audio for a context "A" and then audio for context "B", the - audio from context ID "A" will be played first. + .. deprecated:: 0.0.105 + Subclass :class:`WebsocketTTSService` directly and pass + ``reuse_context_id_within_turn`` as + keyword arguments to its ``__init__``. """ - _CONTEXT_KEEPALIVE = object() - def __init__( self, *, @@ -1177,248 +1506,26 @@ class AudioContextTTSService(WebsocketTTSService): reconnect_on_error: Whether to automatically reconnect on websocket errors. **kwargs: Additional arguments passed to the parent WebsocketTTSService. """ - super().__init__(reconnect_on_error=reconnect_on_error, **kwargs) - self._reuse_context_id_within_turn = reuse_context_id_within_turn - self._context_id = None - self._contexts: Dict[str, asyncio.Queue] = {} - self._audio_context_task = None + import warnings - async def create_audio_context(self, context_id: str): - """Create a new audio context for grouping related audio. - - Args: - context_id: Unique identifier for the audio context. - """ - # Set the context ID if not already set - if not self._context_id: - self._context_id = context_id - - await self._contexts_queue.put(context_id) - self._contexts[context_id] = asyncio.Queue() - logger.trace(f"{self} created audio context {context_id}") - - async def append_to_audio_context(self, context_id: str, frame: TTSAudioRawFrame): - """Append audio to an existing context. - - Args: - context_id: The context to append audio to. - frame: The audio frame to append. - """ - if self.audio_context_available(context_id): - logger.trace(f"{self} appending audio {frame} to audio context {context_id}") - await self._contexts[context_id].put(frame) - else: - logger.warning(f"{self} unable to append audio to context {context_id}") - - async def remove_audio_context(self, context_id: str): - """Remove an existing audio context. - - Args: - context_id: The context to remove. - """ - if self.audio_context_available(context_id): - # We just mark the audio context for deletion by appending - # None. Once we reach None while handling audio we know we can - # safely remove the context. - logger.trace(f"{self} marking audio context {context_id} for deletion") - await self._contexts[context_id].put(None) - else: - logger.warning(f"{self} unable to remove context {context_id}") - - def has_active_audio_context(self) -> bool: - """Check if there is an active audio context. - - Returns: - True if an active audio context exists, False otherwise. - """ - return self._context_id is not None and self.audio_context_available(self._context_id) - - def get_active_audio_context_id(self) -> Optional[str]: - """Get the active audio context ID. - - Returns: - The active context ID, or None if no context is active. - """ - return self._context_id - - async def remove_active_audio_context(self): - """Remove the active audio context.""" - if self._context_id: - await self.remove_audio_context(self._context_id) - self.reset_active_audio_context() - - def reset_active_audio_context(self): - """Reset the active audio context.""" - self._context_id = None - - def audio_context_available(self, context_id: str) -> bool: - """Check whether the given audio context is registered. - - Args: - context_id: The context ID to check. - - Returns: - True if the context exists and is available. - """ - return context_id in self._contexts - - def create_context_id(self) -> str: - """Generate or reuse a context ID based on concurrent TTS support. - - If _reuse_context_id_within_turn is False and a context already exists, - the existing context ID is returned. Otherwise, a new unique context - ID is generated. - - Returns: - A context ID string for the TTS request. - """ - if self._reuse_context_id_within_turn and self._context_id: - self._refresh_active_audio_context() - return self._context_id - return super().create_context_id() - - def _refresh_active_audio_context(self): - """Signal that the audio context is still in use, resetting the timeout.""" - if self.has_active_audio_context(): - self._contexts[self._context_id].put_nowait(AudioContextTTSService._CONTEXT_KEEPALIVE) - - async def start(self, frame: StartFrame): - """Start the audio context TTS service. - - Args: - frame: The start frame containing initialization parameters. - """ - await super().start(frame) - self._create_audio_context_task() - - async def stop(self, frame: EndFrame): - """Stop the audio context TTS service. - - Args: - frame: The end frame. - """ - await super().stop(frame) - if self._audio_context_task: - # Indicate no more audio contexts are available. this will end the - # task cleanly after all contexts have been processed. - await self._contexts_queue.put(None) - await self._audio_context_task - self._audio_context_task = None - - async def cancel(self, frame: CancelFrame): - """Cancel the audio context TTS service. - - Args: - frame: The cancel frame. - """ - await super().cancel(frame) - await self._stop_audio_context_task() - - async def _handle_interruption(self, frame: InterruptionFrame, direction: FrameDirection): - await super()._handle_interruption(frame, direction) - await self._stop_audio_context_task() - await self.on_audio_context_interrupted(context_id=self._context_id) - self.reset_active_audio_context() - self._create_audio_context_task() - - def _create_audio_context_task(self): - if not self._audio_context_task: - self._contexts_queue = asyncio.Queue() - self._contexts: Dict[str, asyncio.Queue] = {} - self._audio_context_task = self.create_task(self._audio_context_task_handler()) - - async def _stop_audio_context_task(self): - if self._audio_context_task: - await self.cancel_task(self._audio_context_task) - self._audio_context_task = None - - async def _audio_context_task_handler(self): - """In this task we process audio contexts in order.""" - running = True - while running: - context_id = await self._contexts_queue.get() - self._context_id = context_id - - if context_id: - # Process the audio context until the context doesn't have more - # audio available (i.e. we find None). - await self._handle_audio_context(context_id) - - # We just finished processing the context, so we can safely remove it. - del self._contexts[context_id] - await self.on_audio_context_completed(context_id=context_id) - self.reset_active_audio_context() - - # Append some silence between sentences. - silence = b"\x00" * self.sample_rate - frame = TTSAudioRawFrame( - audio=silence, - sample_rate=self.sample_rate, - num_channels=1, - context_id=context_id, - ) - await self.push_frame(frame) - else: - running = False - - self._contexts_queue.task_done() - - async def _handle_audio_context(self, context_id: str): - # If we don't receive any audio during this time, we consider the context finished. - AUDIO_CONTEXT_TIMEOUT = 3.0 - queue = self._contexts[context_id] - running = True - while running: - try: - frame = await asyncio.wait_for(queue.get(), timeout=AUDIO_CONTEXT_TIMEOUT) - if frame is AudioContextTTSService._CONTEXT_KEEPALIVE: - # Context is still in use, reset the timeout. - continue - - if frame: - await self.push_frame(frame) - running = frame is not None - except asyncio.TimeoutError: - # We didn't get audio, so let's consider this context finished. - logger.trace(f"{self} time out on audio context {context_id}") - break - - async def on_audio_context_interrupted(self, context_id: str): - """Called when an audio context is cancelled due to an interruption. - - Override this in a subclass to perform provider-specific cleanup (e.g. - sending a cancel/close message over the WebSocket) when the bot is - interrupted mid-speech. The audio context task has already been stopped - and the active context has **not** yet been reset when this is called, - so ``context_id`` reflects the context that was cut short. - - Args: - context_id: The ID of the audio context that was interrupted, or - ``None`` if no context was active at the time. - """ - pass - - async def on_audio_context_completed(self, context_id: str): - """Called after an audio context has finished playing all of its audio. - - Override this in a subclass to perform provider-specific cleanup (e.g. - sending a close-context message to free server-side resources) once an - audio context has been fully processed. The context entry has already - been removed from the internal context map, and the active context has - **not** yet been reset when this is called. - - Args: - context_id: The ID of the audio context that finished processing. - """ - pass + warnings.warn( + "AudioContextTTSService is deprecated. Inherit from WebsocketTTSService directly " + "and pass reuse_context_id_within_turn as kwargs.", + DeprecationWarning, + stacklevel=2, + ) + super().__init__( + reuse_context_id_within_turn=reuse_context_id_within_turn, + reconnect_on_error=reconnect_on_error, + **kwargs, + ) class AudioContextWordTTSService(AudioContextTTSService): - """Deprecated. Use AudioContextTTSService with supports_word_timestamps=True instead. + """Deprecated. Use WebsocketTTSService directly instead. - .. deprecated:: 0.0.104 - Word timestamp functionality has been moved to TTSService. Pass - ``supports_word_timestamps=True`` to AudioContextTTSService instead. + .. deprecated:: 0.0.105 + Subclass :class:`WebsocketTTSService` directly. """ def __init__(self, *, reconnect_on_error: bool = True, **kwargs): @@ -1428,6 +1535,11 @@ class AudioContextWordTTSService(AudioContextTTSService): reconnect_on_error: Whether to automatically reconnect on websocket errors. **kwargs: Additional arguments passed to parent classes. """ - super().__init__( - supports_word_timestamps=True, reconnect_on_error=reconnect_on_error, **kwargs + import warnings + + warnings.warn( + "AudioContextWordTTSService is deprecated. Inherit from WebsocketTTSService directly.", + DeprecationWarning, + stacklevel=2, ) + super().__init__(reconnect_on_error=reconnect_on_error, **kwargs) From 24430d8d4561176b44c3ed3dabdebae9f0d0054d Mon Sep 17 00:00:00 2001 From: filipi87 Date: Fri, 6 Mar 2026 16:15:26 -0300 Subject: [PATCH 0834/1060] Fixing Piper test. --- src/pipecat/tests/utils.py | 22 ++++++++++---------- tests/test_piper_tts.py | 42 +++++++++++++++++++++++--------------- 2 files changed, 36 insertions(+), 28 deletions(-) diff --git a/src/pipecat/tests/utils.py b/src/pipecat/tests/utils.py index 356fb8545..ca18c4c4d 100644 --- a/src/pipecat/tests/utils.py +++ b/src/pipecat/tests/utils.py @@ -199,13 +199,13 @@ async def run_test( # # Down frames # - received_down_frames: Sequence[Frame] = [] - if expected_down_frames is not None: - while not received_down.empty(): - frame = await received_down.get() - if not isinstance(frame, EndFrame) or not send_end_frame: - received_down_frames.append(frame) + received_down_frames: list[Frame] = [] + while not received_down.empty(): + frame = await received_down.get() + if not isinstance(frame, EndFrame) or not send_end_frame: + received_down_frames.append(frame) + if expected_down_frames is not None: down_frames_printed = "[" for frame in received_down_frames: down_frames_printed += f"{frame.__class__.__name__}, " @@ -225,12 +225,12 @@ async def run_test( # # Up frames # - received_up_frames: Sequence[Frame] = [] - if expected_up_frames is not None: - while not received_up.empty(): - frame = await received_up.get() - received_up_frames.append(frame) + received_up_frames: list[Frame] = [] + while not received_up.empty(): + frame = await received_up.get() + received_up_frames.append(frame) + if expected_up_frames is not None: print("received UP frames =", received_up_frames) print("expected UP frames =", expected_up_frames) diff --git a/tests/test_piper_tts.py b/tests/test_piper_tts.py index 662b9a40c..2b1dae577 100644 --- a/tests/test_piper_tts.py +++ b/tests/test_piper_tts.py @@ -77,28 +77,36 @@ async def test_run_piper_tts_success(aiohttp_client): TTSSpeakFrame(text="Hello world."), ] - expected_returned_frames = [ - AggregatedTextFrame, - TTSStartedFrame, - TTSAudioRawFrame, - TTSAudioRawFrame, - TTSAudioRawFrame, - TTSAudioRawFrame, - TTSAudioRawFrame, - TTSAudioRawFrame, - TTSAudioRawFrame, - TTSAudioRawFrame, - TTSStoppedFrame, - TTSTextFrame, - ] - frames_received = await run_test( tts_service, frames_to_send=frames_to_send, - expected_down_frames=expected_returned_frames, ) down_frames = frames_received[0] + frame_types = [type(f) for f in down_frames] + + # Verify key frames are present + assert AggregatedTextFrame in frame_types + assert TTSStartedFrame in frame_types + assert TTSStoppedFrame in frame_types + assert TTSTextFrame in frame_types + + # Verify ordering: Started → audio → Stopped → Text + started_idx = frame_types.index(TTSStartedFrame) + stopped_idx = frame_types.index(TTSStoppedFrame) + text_idx = frame_types.index(TTSTextFrame) + assert started_idx < text_idx < stopped_idx, ( + "Expected: TTSStartedFrame < TTSTextFrame < TTSStoppedFrame" + ) + + # Frames between Started and Stopped must all be audio or text + for i in range(started_idx + 1, stopped_idx): + assert frame_types[i] in (TTSAudioRawFrame, TTSTextFrame), ( + f"Unexpected frame type between Started and Stopped: {frame_types[i]}" + ) + + # All audio frames have correct sample rate audio_frames = [f for f in down_frames if isinstance(f, TTSAudioRawFrame)] + assert len(audio_frames) >= 1, "Expected at least one audio frame" for a_frame in audio_frames: assert a_frame.sample_rate == 24000, "Sample rate should match the default (24000)" @@ -128,7 +136,7 @@ async def test_run_piper_tts_error(aiohttp_client): TTSSpeakFrame(text="Error case.", append_to_context=False), ] - expected_down_frames = [AggregatedTextFrame, TTSStoppedFrame, TTSTextFrame] + expected_down_frames = [AggregatedTextFrame, TTSStartedFrame, TTSTextFrame, TTSStoppedFrame] expected_up_frames = [ErrorFrame] From 88ff7c451ba757dc25e898c626b0b476f4d9aa5b Mon Sep 17 00:00:00 2001 From: filipi87 Date: Fri, 6 Mar 2026 16:15:59 -0300 Subject: [PATCH 0835/1060] Refactored all 25+ TTS service implementations to use the new push_start_frame=True pattern --- src/pipecat/services/asyncai/tts.py | 36 +++++----- src/pipecat/services/aws/tts.py | 12 +--- src/pipecat/services/azure/tts.py | 21 ++---- src/pipecat/services/camb/tts.py | 9 +-- src/pipecat/services/cartesia/tts.py | 48 +++++++------- .../services/deepgram/sagemaker/tts.py | 14 ++-- src/pipecat/services/deepgram/tts.py | 21 ++---- src/pipecat/services/elevenlabs/tts.py | 63 +++++++----------- src/pipecat/services/fish/tts.py | 12 +--- src/pipecat/services/google/tts.py | 22 ++----- src/pipecat/services/gradium/tts.py | 32 +++------ src/pipecat/services/groq/tts.py | 9 +-- src/pipecat/services/hume/tts.py | 13 +--- src/pipecat/services/inworld/tts.py | 66 ++++++------------- src/pipecat/services/kokoro/tts.py | 7 +- src/pipecat/services/lmnt/tts.py | 12 +--- src/pipecat/services/minimax/tts.py | 8 +-- src/pipecat/services/neuphonic/tts.py | 24 ++----- src/pipecat/services/nvidia/tts.py | 8 +-- src/pipecat/services/openai/tts.py | 8 +-- src/pipecat/services/piper/tts.py | 16 ++--- src/pipecat/services/resembleai/tts.py | 18 ++--- src/pipecat/services/rime/tts.py | 42 +++++------- src/pipecat/services/sarvam/tts.py | 18 ++--- src/pipecat/services/speechmatics/tts.py | 13 +--- src/pipecat/services/xtts/tts.py | 12 +--- 26 files changed, 182 insertions(+), 382 deletions(-) diff --git a/src/pipecat/services/asyncai/tts.py b/src/pipecat/services/asyncai/tts.py index 3b1296752..56a7d0e82 100644 --- a/src/pipecat/services/asyncai/tts.py +++ b/src/pipecat/services/asyncai/tts.py @@ -23,12 +23,11 @@ from pipecat.frames.frames import ( Frame, StartFrame, TTSAudioRawFrame, - TTSStartedFrame, TTSStoppedFrame, ) from pipecat.processors.frame_processor import FrameDirection from pipecat.services.settings import TTSSettings, _warn_deprecated_param -from pipecat.services.tts_service import AudioContextTTSService, TextAggregationMode, TTSService +from pipecat.services.tts_service import TextAggregationMode, TTSService, WebsocketTTSService from pipecat.transcriptions.language import Language, resolve_language from pipecat.utils.tracing.service_decorators import traced_tts @@ -80,7 +79,7 @@ class AsyncAITTSSettings(TTSSettings): pass -class AsyncAITTSService(AudioContextTTSService): +class AsyncAITTSService(WebsocketTTSService): """Async TTS service with WebSocket streaming. Provides text-to-speech using Async's streaming WebSocket API. @@ -183,8 +182,9 @@ class AsyncAITTSService(AudioContextTTSService): aggregate_sentences=aggregate_sentences, text_aggregation_mode=text_aggregation_mode, pause_frame_processing=True, - push_stop_frames=True, sample_rate=sample_rate, + push_start_frame=True, + push_stop_frames=True, settings=default_settings, **kwargs, ) @@ -340,13 +340,18 @@ class AsyncAITTSService(AudioContextTTSService): return self._websocket raise Exception("Websocket not connected") - async def flush_audio(self): - """Flush any pending audio.""" - context_id = self.get_active_audio_context_id() - if not context_id or not self._websocket: + async def flush_audio(self, context_id: Optional[str] = None): + """Flush any pending audio. + + Args: + context_id: The specific context to flush. If None, falls back to the + currently active context. + """ + flush_id = context_id or self.get_active_audio_context_id() + if not flush_id or not self._websocket: return logger.trace(f"{self}: flushing audio") - msg = self._build_msg(text=" ", context_id=context_id, force=True) + msg = self._build_msg(text=" ", context_id=flush_id, force=True) await self._websocket.send(msg) async def push_frame(self, frame: Frame, direction: FrameDirection = FrameDirection.DOWNSTREAM): @@ -459,12 +464,6 @@ class AsyncAITTSService(AudioContextTTSService): await self._connect() try: - if not self.has_active_audio_context(): - await self.start_ttfb_metrics() - yield TTSStartedFrame(context_id=context_id) - if not self.audio_context_available(context_id): - await self.create_audio_context(context_id) - msg = self._build_msg(text=text, force=True, context_id=context_id) await self._get_websocket().send(msg) await self.start_tts_usage_metrics(text) @@ -574,6 +573,8 @@ class AsyncAIHttpTTSService(TTSService): super().__init__( sample_rate=sample_rate, + push_start_frame=True, + push_stop_frames=True, settings=default_settings, **kwargs, ) @@ -632,7 +633,7 @@ class AsyncAIHttpTTSService(TTSService): try: voice_config = {"mode": "id", "id": self._settings.voice} - await self.start_ttfb_metrics() + payload = { "model_id": self._settings.model, "transcript": text, @@ -644,7 +645,7 @@ class AsyncAIHttpTTSService(TTSService): }, "language": self._settings.language, } - yield TTSStartedFrame(context_id=context_id) + headers = { "version": self._api_version, "x-api-key": self._api_key, @@ -682,4 +683,3 @@ class AsyncAIHttpTTSService(TTSService): await self.push_error(error_msg=f"Unknown error occurred: {e}", exception=e) finally: await self.stop_ttfb_metrics() - yield TTSStoppedFrame(context_id=context_id) diff --git a/src/pipecat/services/aws/tts.py b/src/pipecat/services/aws/tts.py index 043fc264e..285026bca 100644 --- a/src/pipecat/services/aws/tts.py +++ b/src/pipecat/services/aws/tts.py @@ -22,8 +22,6 @@ from pipecat.frames.frames import ( ErrorFrame, Frame, TTSAudioRawFrame, - TTSStartedFrame, - TTSStoppedFrame, ) from pipecat.services.settings import NOT_GIVEN, TTSSettings, _NotGiven, _warn_deprecated_param from pipecat.services.tts_service import TTSService @@ -247,6 +245,8 @@ class AWSPollyTTSService(TTSService): super().__init__( sample_rate=sample_rate, + push_start_frame=True, + push_stop_frames=True, settings=default_settings, **kwargs, ) @@ -329,8 +329,6 @@ class AWSPollyTTSService(TTSService): logger.debug(f"{self}: Generating TTS [{text}]") try: - await self.start_ttfb_metrics() - # Construct the parameters dictionary ssml = self._construct_ssml(text) @@ -362,8 +360,6 @@ class AWSPollyTTSService(TTSService): await self.start_tts_usage_metrics(text) - yield TTSStartedFrame(context_id=context_id) - CHUNK_SIZE = self.chunk_size for i in range(0, len(audio_data), CHUNK_SIZE): @@ -373,14 +369,10 @@ class AWSPollyTTSService(TTSService): frame = TTSAudioRawFrame(chunk, self.sample_rate, 1, context_id=context_id) yield frame - yield TTSStoppedFrame(context_id=context_id) except (BotoCoreError, ClientError) as error: error_message = f"AWS Polly TTS error: {str(error)}" yield ErrorFrame(error=error_message) - finally: - yield TTSStoppedFrame(context_id=context_id) - class PollyTTSService(AWSPollyTTSService): """Deprecated alias for AWSPollyTTSService. diff --git a/src/pipecat/services/azure/tts.py b/src/pipecat/services/azure/tts.py index 112459c5a..f710482e9 100644 --- a/src/pipecat/services/azure/tts.py +++ b/src/pipecat/services/azure/tts.py @@ -21,7 +21,6 @@ from pipecat.frames.frames import ( InterruptionFrame, StartFrame, TTSAudioRawFrame, - TTSStartedFrame, TTSStoppedFrame, ) from pipecat.processors.frame_processor import FrameDirection @@ -331,8 +330,8 @@ class AzureTTSService(TTSService, AzureBaseTTSService): text_aggregation_mode=text_aggregation_mode, push_text_frames=False, # We'll push text frames based on word timestamps push_stop_frames=True, + push_start_frame=True, pause_frame_processing=True, - supports_word_timestamps=True, sample_rate=sample_rate, settings=default_settings, **kwargs, @@ -346,7 +345,6 @@ class AzureTTSService(TTSService, AzureBaseTTSService): self._audio_queue = asyncio.Queue() self._word_boundary_queue = asyncio.Queue() self._word_processor_task = None - self._first_chunk = True self._cumulative_audio_offset: float = 0.0 # Cumulative audio duration in seconds self._current_sentence_base_offset: float = 0.0 # Base offset for current sentence self._current_sentence_duration: float = 0.0 # Duration from Azure callback @@ -619,7 +617,6 @@ class AzureTTSService(TTSService, AzureBaseTTSService): def _reset_state(self): """Reset TTS state between turns.""" - self._first_chunk = True self._cumulative_audio_offset = 0.0 self._current_sentence_base_offset = 0.0 self._current_sentence_duration = 0.0 @@ -628,7 +625,7 @@ class AzureTTSService(TTSService, AzureBaseTTSService): self._last_timestamp = None self._current_context_id = None - async def flush_audio(self): + async def flush_audio(self, context_id: Optional[str] = None): """Flush any pending audio data.""" logger.trace(f"{self}: flushing audio") @@ -694,9 +691,6 @@ class AzureTTSService(TTSService, AzureBaseTTSService): return try: - await self.start_ttfb_metrics() - yield TTSStartedFrame(context_id=context_id) - self._first_chunk = True self._current_context_id = context_id # Capture base offset BEFORE starting synthesis to avoid race conditions @@ -719,11 +713,6 @@ class AzureTTSService(TTSService, AzureBaseTTSService): yield ErrorFrame(error=str(chunk)) break - if self._first_chunk: - await self.stop_ttfb_metrics() - await self.start_word_timestamps() - self._first_chunk = False - frame = TTSAudioRawFrame( audio=chunk, sample_rate=self.sample_rate, @@ -833,6 +822,8 @@ class AzureHttpTTSService(TTSService, AzureBaseTTSService): super().__init__( sample_rate=sample_rate, + push_start_frame=True, + push_stop_frames=True, settings=default_settings, **kwargs, ) @@ -887,8 +878,6 @@ class AzureHttpTTSService(TTSService, AzureBaseTTSService): """ logger.debug(f"{self}: Generating TTS [{text}]") - await self.start_ttfb_metrics() - ssml = self._construct_ssml(text) result = await asyncio.to_thread(self._speech_synthesizer.speak_ssml, ssml) @@ -896,7 +885,6 @@ class AzureHttpTTSService(TTSService, AzureBaseTTSService): if result.reason == ResultReason.SynthesizingAudioCompleted: await self.start_tts_usage_metrics(text) await self.stop_ttfb_metrics() - yield TTSStartedFrame(context_id=context_id) # Azure always sends a 44-byte header. Strip it off. yield TTSAudioRawFrame( audio=result.audio_data[44:], @@ -904,7 +892,6 @@ class AzureHttpTTSService(TTSService, AzureBaseTTSService): num_channels=1, context_id=context_id, ) - yield TTSStoppedFrame(context_id=context_id) elif result.reason == ResultReason.Canceled: cancellation_details = result.cancellation_details logger.warning(f"Speech synthesis canceled: {cancellation_details.reason}") diff --git a/src/pipecat/services/camb/tts.py b/src/pipecat/services/camb/tts.py index ef007181e..b30726fda 100644 --- a/src/pipecat/services/camb/tts.py +++ b/src/pipecat/services/camb/tts.py @@ -29,8 +29,6 @@ from pipecat.frames.frames import ( Frame, StartFrame, TTSAudioRawFrame, - TTSStartedFrame, - TTSStoppedFrame, ) from pipecat.services.settings import NOT_GIVEN, TTSSettings, _NotGiven, _warn_deprecated_param from pipecat.services.tts_service import TTSService @@ -271,6 +269,8 @@ class CambTTSService(TTSService): super().__init__( sample_rate=sample_rate, + push_start_frame=True, + push_stop_frames=True, settings=default_settings, **kwargs, ) @@ -332,8 +332,6 @@ class CambTTSService(TTSService): text = text[:3000] try: - await self.start_ttfb_metrics() - # Build SDK parameters tts_kwargs: Dict[str, Any] = { "text": text, @@ -348,7 +346,6 @@ class CambTTSService(TTSService): tts_kwargs["user_instructions"] = self._settings.user_instructions await self.start_tts_usage_metrics(text) - yield TTSStartedFrame(context_id=context_id) assert self._client is not None, "Camb.ai TTS service not initialized" @@ -384,5 +381,3 @@ class CambTTSService(TTSService): except Exception as e: yield ErrorFrame(error=f"Camb.ai TTS error: {e}") - finally: - yield TTSStoppedFrame(context_id=context_id) diff --git a/src/pipecat/services/cartesia/tts.py b/src/pipecat/services/cartesia/tts.py index 166aa70af..3f708d06f 100644 --- a/src/pipecat/services/cartesia/tts.py +++ b/src/pipecat/services/cartesia/tts.py @@ -27,7 +27,7 @@ from pipecat.frames.frames import ( TTSStoppedFrame, ) from pipecat.services.settings import NOT_GIVEN, TTSSettings, _NotGiven, _warn_deprecated_param -from pipecat.services.tts_service import AudioContextTTSService, TextAggregationMode, TTSService +from pipecat.services.tts_service import TextAggregationMode, TTSService, WebsocketTTSService from pipecat.transcriptions.language import Language, resolve_language from pipecat.utils.text.base_text_aggregator import BaseTextAggregator from pipecat.utils.text.skip_tags_aggregator import SkipTagsAggregator @@ -203,7 +203,7 @@ class CartesiaTTSSettings(TTSSettings): pronunciation_dict_id: str | None | _NotGiven = field(default_factory=lambda: NOT_GIVEN) -class CartesiaTTSService(AudioContextTTSService): +class CartesiaTTSService(WebsocketTTSService): """Cartesia TTS service with WebSocket streaming and word timestamps. Provides text-to-speech using Cartesia's streaming WebSocket API. @@ -334,9 +334,9 @@ class CartesiaTTSService(AudioContextTTSService): text_aggregation_mode=text_aggregation_mode, aggregate_sentences=aggregate_sentences, push_text_frames=False, - pause_frame_processing=True, - supports_word_timestamps=True, + pause_frame_processing=False, sample_rate=sample_rate, + push_start_frame=True, text_aggregator=text_aggregator, settings=default_settings, **kwargs, @@ -452,7 +452,11 @@ class CartesiaTTSService(AudioContextTTSService): return list(zip(words, starts)) def _build_msg( - self, text: str = "", continue_transcript: bool = True, add_timestamps: bool = True + self, + text: str = "", + continue_transcript: bool = True, + add_timestamps: bool = True, + context_id: str = "", ): voice_config = {} voice_config["mode"] = "id" @@ -461,7 +465,7 @@ class CartesiaTTSService(AudioContextTTSService): msg = { "transcript": text, "continue": continue_transcript, - "context_id": self.get_active_audio_context_id(), + "context_id": context_id, "model_id": self._settings.model, "voice": voice_config, "output_format": { @@ -580,15 +584,19 @@ class CartesiaTTSService(AudioContextTTSService): """ pass - async def flush_audio(self): - """Flush any pending audio and finalize the current context.""" - context_id = self.get_active_audio_context_id() - if not context_id or not self._websocket: + async def flush_audio(self, context_id: Optional[str] = None): + """Flush any pending audio and finalize the current context. + + Args: + context_id: The specific context to flush. If None, falls back to the + currently active context. + """ + flush_id = context_id or self.get_active_audio_context_id() + if not flush_id or not self._websocket: return logger.trace(f"{self}: flushing audio") - msg = self._build_msg(text="", continue_transcript=False) + msg = self._build_msg(text="", continue_transcript=False, context_id=flush_id) await self._websocket.send(msg) - self.reset_active_audio_context() async def _process_messages(self): async for message in self._get_websocket(): @@ -607,8 +615,6 @@ class CartesiaTTSService(AudioContextTTSService): ) await self.add_word_timestamps(processed_timestamps, ctx_id) elif msg["type"] == "chunk": - await self.stop_ttfb_metrics() - await self.start_word_timestamps() frame = TTSAudioRawFrame( audio=base64.b64decode(msg["data"]), sample_rate=self.sample_rate, @@ -652,12 +658,7 @@ class CartesiaTTSService(AudioContextTTSService): if not self._websocket or self._websocket.state is State.CLOSED: await self._connect() - if not self.has_active_audio_context(): - await self.start_ttfb_metrics() - yield TTSStartedFrame(context_id=context_id) - await self.create_audio_context(context_id) - - msg = self._build_msg(text=text) + msg = self._build_msg(text=text, context_id=context_id) try: await self._get_websocket().send(msg) @@ -777,6 +778,8 @@ class CartesiaHttpTTSService(TTSService): super().__init__( sample_rate=sample_rate, + push_start_frame=True, + push_stop_frames=True, settings=default_settings, **kwargs, ) @@ -863,8 +866,6 @@ class CartesiaHttpTTSService(TTSService): try: voice_config = {"mode": "id", "id": self._settings.voice} - await self.start_ttfb_metrics() - output_format = { "container": self._output_container, "encoding": self._output_encoding, @@ -889,8 +890,6 @@ class CartesiaHttpTTSService(TTSService): if self._settings.pronunciation_dict_id: payload["pronunciation_dict_id"] = self._settings.pronunciation_dict_id - yield TTSStartedFrame(context_id=context_id) - headers = { "Cartesia-Version": self._cartesia_version, "X-API-Key": self._api_key, @@ -922,4 +921,3 @@ class CartesiaHttpTTSService(TTSService): yield ErrorFrame(error=f"Unknown error occurred: {e}") finally: await self.stop_ttfb_metrics() - yield TTSStoppedFrame(context_id=context_id) diff --git a/src/pipecat/services/deepgram/sagemaker/tts.py b/src/pipecat/services/deepgram/sagemaker/tts.py index 3693178a1..9e8c30ad7 100644 --- a/src/pipecat/services/deepgram/sagemaker/tts.py +++ b/src/pipecat/services/deepgram/sagemaker/tts.py @@ -328,7 +328,7 @@ class DeepgramSageMakerTTSService(TTSService): except Exception as e: logger.error(f"{self} error sending Clear message: {e}") - async def flush_audio(self): + async def flush_audio(self, context_id: Optional[str] = None): """Flush any pending audio synthesis by sending Flush command. This should be called when the LLM finishes a complete response to force @@ -355,12 +355,12 @@ class DeepgramSageMakerTTSService(TTSService): logger.debug(f"{self}: Generating TTS [{text}]") try: - if not self._ttfb_started: - await self.start_ttfb_metrics() - self._ttfb_started = True - await self.start_tts_usage_metrics(text) - - yield TTSStartedFrame(context_id=context_id) + if not self.audio_context_available(context_id): + await self.create_audio_context(context_id) + if not self._ttfb_started: + await self.start_ttfb_metrics() + self._ttfb_started = True + yield TTSStartedFrame(context_id=context_id) self._context_id = context_id await self._client.send_json({"type": "Speak", "text": text}) diff --git a/src/pipecat/services/deepgram/tts.py b/src/pipecat/services/deepgram/tts.py index 95db998e2..6c8685bee 100644 --- a/src/pipecat/services/deepgram/tts.py +++ b/src/pipecat/services/deepgram/tts.py @@ -26,8 +26,6 @@ from pipecat.frames.frames import ( LLMFullResponseEndFrame, StartFrame, TTSAudioRawFrame, - TTSStartedFrame, - TTSStoppedFrame, ) from pipecat.processors.frame_processor import FrameDirection from pipecat.services.settings import TTSSettings, _warn_deprecated_param @@ -120,6 +118,7 @@ class DeepgramTTSService(WebsocketTTSService): sample_rate=sample_rate, pause_frame_processing=True, push_stop_frames=True, + push_start_frame=True, append_trailing_space=True, settings=default_settings, **kwargs, @@ -130,7 +129,6 @@ class DeepgramTTSService(WebsocketTTSService): self._encoding = encoding self._receive_task = None - self._context_id: Optional[str] = None def can_generate_metrics(self) -> bool: """Check if the service can generate metrics. @@ -267,7 +265,6 @@ class DeepgramTTSService(WebsocketTTSService): logger.error(f"{self} exception: {e}") await self.push_error(ErrorFrame(error=f"{self} error: {e}")) finally: - self._context_id = None self._websocket = None await self._call_event_handler("on_disconnected") @@ -299,7 +296,9 @@ class DeepgramTTSService(WebsocketTTSService): if isinstance(message, bytes): # Binary message contains audio data await self.stop_ttfb_metrics() - frame = TTSAudioRawFrame(message, self.sample_rate, 1, context_id=self._context_id) + frame = TTSAudioRawFrame( + message, self.sample_rate, 1, context_id=self.get_active_audio_context_id() + ) await self.push_frame(frame) elif isinstance(message, str): # Text message contains metadata or control messages @@ -326,7 +325,7 @@ class DeepgramTTSService(WebsocketTTSService): except json.JSONDecodeError: logger.error(f"Invalid JSON message: {message}") - async def flush_audio(self): + async def flush_audio(self, context_id: Optional[str] = None): """Flush any pending audio synthesis by sending Flush command. This should be called when the LLM finishes a complete response to force @@ -357,13 +356,8 @@ class DeepgramTTSService(WebsocketTTSService): if not self._websocket or self._websocket.state is State.CLOSED: await self._connect() - await self.start_ttfb_metrics() await self.start_tts_usage_metrics(text) - yield TTSStartedFrame(context_id=context_id) - # Store context_id for use in _receive_messages - self._context_id = context_id - # Send text message to Deepgram # Note: We don't send Flush here - that should only be sent when the # LLM finishes a complete response via flush_audio() @@ -435,6 +429,8 @@ class DeepgramHttpTTSService(TTSService): super().__init__( sample_rate=sample_rate, + push_start_frame=True, + push_stop_frames=True, settings=default_settings, **kwargs, ) @@ -492,7 +488,6 @@ class DeepgramHttpTTSService(TTSService): raise Exception(f"HTTP {response.status}: {error_text}") await self.start_tts_usage_metrics(text) - yield TTSStartedFrame(context_id=context_id) CHUNK_SIZE = self.chunk_size @@ -510,7 +505,5 @@ class DeepgramHttpTTSService(TTSService): context_id=context_id, ) - yield TTSStoppedFrame(context_id=context_id) - except Exception as e: yield ErrorFrame(f"Error getting audio: {str(e)}") diff --git a/src/pipecat/services/elevenlabs/tts.py b/src/pipecat/services/elevenlabs/tts.py index cfb08eb6d..de930d1f2 100644 --- a/src/pipecat/services/elevenlabs/tts.py +++ b/src/pipecat/services/elevenlabs/tts.py @@ -46,9 +46,9 @@ from pipecat.frames.frames import ( from pipecat.processors.frame_processor import FrameDirection from pipecat.services.settings import NOT_GIVEN, TTSSettings, _NotGiven, _warn_deprecated_param from pipecat.services.tts_service import ( - AudioContextTTSService, TextAggregationMode, TTSService, + WebsocketTTSService, ) from pipecat.transcriptions.language import Language, resolve_language from pipecat.utils.tracing.service_decorators import traced_tts @@ -308,7 +308,7 @@ def calculate_word_times( return (word_times, new_partial_word, new_partial_word_start_time) -class ElevenLabsTTSService(AudioContextTTSService): +class ElevenLabsTTSService(WebsocketTTSService): """ElevenLabs WebSocket-based TTS service with word timestamps. Provides real-time text-to-speech using ElevenLabs' WebSocket streaming API. @@ -479,7 +479,6 @@ class ElevenLabsTTSService(AudioContextTTSService): push_text_frames=False, push_stop_frames=True, pause_frame_processing=True, - supports_word_timestamps=True, sample_rate=sample_rate, settings=default_settings, **kwargs, @@ -559,20 +558,15 @@ class ElevenLabsTTSService(AudioContextTTSService): ) await self._disconnect() await self._connect() - elif voice_settings_changed and self.has_active_audio_context(): + elif voice_settings_changed: logger.debug( f"Voice settings changed ({changed.keys() & ElevenLabsTTSSettings.VOICE_SETTINGS_FIELDS}), " f"closing current context to apply changes" ) - context_id = self.get_active_audio_context_id() - try: - if self._websocket: - await self._websocket.send( - json.dumps({"context_id": context_id, "close_context": True}) - ) - except Exception as e: - await self.push_error(error_msg=f"Unknown error occurred: {e}", exception=e) - self.reset_active_audio_context() + audio_contexts = self.get_audio_contexts() + if audio_contexts: + for ctx_id in audio_contexts: + await self._close_context(ctx_id) if not url_changed: # Reconnect applies all settings; only warn about fields not handled @@ -610,13 +604,18 @@ class ElevenLabsTTSService(AudioContextTTSService): await super().cancel(frame) await self._disconnect() - async def flush_audio(self): - """Flush any pending audio and finalize the current context.""" - context_id = self.get_active_audio_context_id() - if not context_id or not self._websocket: + async def flush_audio(self, context_id: Optional[str] = None): + """Flush any pending audio and finalize the current context. + + Args: + context_id: The specific context to flush. If None, falls back to the + currently active context. + """ + flush_id = context_id or self.get_active_audio_context_id() + if not flush_id or not self._websocket: return logger.trace(f"{self}: flushing audio") - msg = {"context_id": context_id, "flush": True} + msg = {"context_id": flush_id, "flush": True} await self._websocket.send(json.dumps(msg)) async def push_frame(self, frame: Frame, direction: FrameDirection = FrameDirection.DOWNSTREAM): @@ -703,9 +702,7 @@ class ElevenLabsTTSService(AudioContextTTSService): if self._websocket: logger.debug("Disconnecting from ElevenLabs") - # Close all contexts and the socket - if self.has_active_audio_context(): - await self._websocket.send(json.dumps({"close_socket": True})) + await self._websocket.send(json.dumps({"close_socket": True})) await self._websocket.close() logger.debug("Disconnected from ElevenLabs") except Exception as e: @@ -737,6 +734,7 @@ class ElevenLabsTTSService(AudioContextTTSService): ) except Exception as e: await self.push_error(error_msg=f"Unknown error occurred: {e}", exception=e) + self._cumulative_time = 0.0 self._partial_word = "" self._partial_word_start_time = 0.0 @@ -782,9 +780,6 @@ class ElevenLabsTTSService(AudioContextTTSService): continue if msg.get("audio"): - await self.stop_ttfb_metrics() - await self.start_word_timestamps() - audio = base64.b64decode(msg["audio"]) frame = TTSAudioRawFrame(audio, self.sample_rate, 1, context_id=received_ctx_id) await self.append_to_audio_context(received_ctx_id, frame) @@ -845,9 +840,8 @@ class ElevenLabsTTSService(AudioContextTTSService): logger.warning(f"{self} keepalive error: {e}") break - async def _send_text(self, text: str): + async def _send_text(self, text: str, context_id: str): """Send text to the WebSocket for synthesis.""" - context_id = self.get_active_audio_context_id() if self._websocket and context_id: msg = {"text": text, "context_id": context_id} await self._websocket.send(json.dumps(msg)) @@ -870,16 +864,14 @@ class ElevenLabsTTSService(AudioContextTTSService): await self._connect() try: - if not self.has_active_audio_context(): + if not self.audio_context_available(context_id): + await self.create_audio_context(context_id) await self.start_ttfb_metrics() yield TTSStartedFrame(context_id=context_id) self._cumulative_time = 0 self._partial_word = "" self._partial_word_start_time = 0.0 - if not self.audio_context_available(context_id): - await self.create_audio_context(context_id) - # Initialize context with voice settings and pronunciation dictionaries msg = {"text": " ", "context_id": context_id} if self._voice_settings: @@ -892,7 +884,7 @@ class ElevenLabsTTSService(AudioContextTTSService): await self._websocket.send(json.dumps(msg)) logger.trace(f"Created new context {context_id}") - await self._send_text(text) + await self._send_text(text, context_id) await self.start_tts_usage_metrics(text) except Exception as e: yield TTSStoppedFrame(context_id=context_id) @@ -1046,7 +1038,7 @@ class ElevenLabsHttpTTSService(TTSService): aggregate_sentences=aggregate_sentences, push_text_frames=False, push_stop_frames=True, - supports_word_timestamps=True, + push_start_frame=True, sample_rate=sample_rate, settings=default_settings, **kwargs, @@ -1266,8 +1258,6 @@ class ElevenLabsHttpTTSService(TTSService): params["optimize_streaming_latency"] = self._settings.optimize_streaming_latency try: - await self.start_ttfb_metrics() - async with self._session.post( url, json=payload, headers=headers, params=params ) as response: @@ -1278,10 +1268,6 @@ class ElevenLabsHttpTTSService(TTSService): await self.start_tts_usage_metrics(text) - # Start TTS sequence - await self.start_word_timestamps() - yield TTSStartedFrame(context_id=context_id) - # Track the duration of this utterance based on the last character's end time utterance_duration = 0 async for line in response.content: @@ -1347,4 +1333,3 @@ class ElevenLabsHttpTTSService(TTSService): yield ErrorFrame(error=f"Unknown error occurred: {e}") finally: await self.stop_ttfb_metrics() - # Let the parent class handle TTSStoppedFrame diff --git a/src/pipecat/services/fish/tts.py b/src/pipecat/services/fish/tts.py index 9ea749546..64c3bccd9 100644 --- a/src/pipecat/services/fish/tts.py +++ b/src/pipecat/services/fish/tts.py @@ -209,6 +209,7 @@ class FishAudioTTSService(InterruptibleTTSService): super().__init__( push_stop_frames=True, + push_start_frame=True, pause_frame_processing=True, sample_rate=sample_rate, settings=default_settings, @@ -219,7 +220,6 @@ class FishAudioTTSService(InterruptibleTTSService): self._base_url = "wss://api.fish.audio/v1/tts/live" self._websocket = None self._receive_task = None - self._request_id = None # Init-only audio format config (not runtime-updatable). self._fish_sample_rate = 0 # Set in start() @@ -341,11 +341,10 @@ class FishAudioTTSService(InterruptibleTTSService): except Exception as e: await self.push_error(error_msg=f"Unknown error occurred: {e}", exception=e) finally: - self._request_id = None self._websocket = None await self._call_event_handler("on_disconnected") - async def flush_audio(self): + async def flush_audio(self, context_id: Optional[str] = None): """Flush any buffered audio by sending a flush event to Fish Audio.""" logger.trace(f"{self}: Flushing audio buffers") if not self._websocket or self._websocket.state is State.CLOSED: @@ -361,7 +360,6 @@ class FishAudioTTSService(InterruptibleTTSService): async def _handle_interruption(self, frame: InterruptionFrame, direction: FrameDirection): await super()._handle_interruption(frame, direction) await self.stop_all_metrics() - self._request_id = None async def _receive_messages(self): async for message in self._get_websocket(): @@ -398,12 +396,6 @@ class FishAudioTTSService(InterruptibleTTSService): if not self._websocket or self._websocket.state is State.CLOSED: await self._connect() - if not self._request_id: - await self.start_ttfb_metrics() - await self.start_tts_usage_metrics(text) - yield TTSStartedFrame(context_id=context_id) - self._request_id = str(uuid.uuid4()) - # Send the text text_message = { "event": "text", diff --git a/src/pipecat/services/google/tts.py b/src/pipecat/services/google/tts.py index 7cf2ee996..071d731b1 100644 --- a/src/pipecat/services/google/tts.py +++ b/src/pipecat/services/google/tts.py @@ -34,8 +34,6 @@ from pipecat.frames.frames import ( Frame, StartFrame, TTSAudioRawFrame, - TTSStartedFrame, - TTSStoppedFrame, ) from pipecat.services.settings import ( NOT_GIVEN, @@ -655,6 +653,8 @@ class GoogleHttpTTSService(TTSService): super().__init__( sample_rate=sample_rate, + push_start_frame=True, + push_stop_frames=True, settings=default_settings, **kwargs, ) @@ -803,8 +803,6 @@ class GoogleHttpTTSService(TTSService): logger.debug(f"{self}: Generating TTS [{text}]") try: - await self.start_ttfb_metrics() - # Check if the voice is a Chirp voice (including Chirp 3) or Journey voice is_chirp_voice = "chirp" in self._settings.voice.lower() is_journey_voice = "journey" in self._settings.voice.lower() @@ -840,8 +838,6 @@ class GoogleHttpTTSService(TTSService): await self.start_tts_usage_metrics(text) - yield TTSStartedFrame(context_id=context_id) - # Skip the first 44 bytes to remove the WAV header audio_content = response.audio_content[44:] @@ -855,8 +851,6 @@ class GoogleHttpTTSService(TTSService): frame = TTSAudioRawFrame(chunk, self.sample_rate, 1, context_id=context_id) yield frame - yield TTSStoppedFrame(context_id=context_id) - except Exception as e: error_message = f"TTS generation error: {str(e)}" yield ErrorFrame(error=error_message) @@ -967,8 +961,6 @@ class GoogleBaseTTSService(TTSService): streaming_responses = await self._client.streaming_synthesize(request_generator()) await self.start_tts_usage_metrics(text) - yield TTSStartedFrame(context_id=context_id) - audio_buffer = b"" first_chunk_for_ttfb = False @@ -992,8 +984,6 @@ class GoogleBaseTTSService(TTSService): if audio_buffer: yield TTSAudioRawFrame(audio_buffer, self.sample_rate, 1, context_id=context_id) - yield TTSStoppedFrame(context_id=context_id) - class GoogleTTSService(GoogleBaseTTSService): """Google Cloud Text-to-Speech streaming service. @@ -1096,6 +1086,8 @@ class GoogleTTSService(GoogleBaseTTSService): super().__init__( sample_rate=sample_rate, + push_start_frame=True, + push_stop_frames=True, settings=default_settings, **kwargs, ) @@ -1135,8 +1127,6 @@ class GoogleTTSService(GoogleBaseTTSService): logger.debug(f"{self}: Generating TTS [{text}]") try: - await self.start_ttfb_metrics() - # Build voice selection params if self._voice_cloning_key: voice_clone_params = texttospeech_v1.VoiceCloneParams( @@ -1352,6 +1342,8 @@ class GeminiTTSService(GoogleBaseTTSService): super().__init__( sample_rate=sample_rate, + push_start_frame=True, + push_stop_frames=True, settings=default_settings, **kwargs, ) @@ -1414,8 +1406,6 @@ class GeminiTTSService(GoogleBaseTTSService): logger.debug(f"{self}: Generating TTS [{text}]") try: - await self.start_ttfb_metrics() - # Build voice selection params if self._settings.multi_speaker and self._settings.speaker_configs: # Multi-speaker mode diff --git a/src/pipecat/services/gradium/tts.py b/src/pipecat/services/gradium/tts.py index 2ade14367..745a77f56 100644 --- a/src/pipecat/services/gradium/tts.py +++ b/src/pipecat/services/gradium/tts.py @@ -19,11 +19,10 @@ from pipecat.frames.frames import ( Frame, StartFrame, TTSAudioRawFrame, - TTSStartedFrame, TTSStoppedFrame, ) from pipecat.services.settings import TTSSettings, _warn_deprecated_param -from pipecat.services.tts_service import AudioContextTTSService +from pipecat.services.tts_service import WebsocketTTSService from pipecat.utils.tracing.service_decorators import traced_tts try: @@ -45,7 +44,7 @@ class GradiumTTSSettings(TTSSettings): pass -class GradiumTTSService(AudioContextTTSService): +class GradiumTTSService(WebsocketTTSService): """Text-to-Speech service using Gradium's websocket API.""" _settings: GradiumTTSSettings @@ -125,9 +124,9 @@ class GradiumTTSService(AudioContextTTSService): super().__init__( push_stop_frames=True, + push_start_frame=True, push_text_frames=False, pause_frame_processing=True, - supports_word_timestamps=True, sample_rate=SAMPLE_RATE, settings=default_settings, **kwargs, @@ -166,12 +165,9 @@ class GradiumTTSService(AudioContextTTSService): self._warn_unhandled_updated_settings(changed) return changed - def _build_msg(self, text: str = "") -> dict: + def _build_msg(self, text: str = "", context_id: str = "") -> dict: """Build JSON message for Gradium API.""" - msg = {"text": text, "type": "text"} - context_id = self.get_active_audio_context_id() - if context_id: - msg["client_req_id"] = context_id + msg = {"text": text, "type": "text", "client_req_id": context_id} return msg async def start(self, frame: StartFrame): @@ -280,15 +276,14 @@ class GradiumTTSService(AudioContextTTSService): return self._websocket raise Exception("Websocket not connected") - async def flush_audio(self): + async def flush_audio(self, context_id: Optional[str] = None): """Flush any pending audio synthesis.""" - context_id = self.get_active_audio_context_id() - if not context_id or not self._websocket: + flush_id = context_id or self.get_active_audio_context_id() + if not flush_id or not self._websocket: return try: - msg = {"type": "end_of_stream", "client_req_id": context_id} + msg = {"type": "end_of_stream", "client_req_id": flush_id} await self._websocket.send(json.dumps(msg)) - self.reset_active_audio_context() except ConnectionClosedOK: logger.debug(f"{self}: connection closed normally during flush") except Exception as e: @@ -326,8 +321,6 @@ class GradiumTTSService(AudioContextTTSService): if msg["type"] == "audio": if not ctx_id or not self.audio_context_available(ctx_id): continue - await self.stop_ttfb_metrics() - await self.start_word_timestamps() frame = TTSAudioRawFrame( audio=base64.b64decode(msg["audio"]), sample_rate=self.sample_rate, @@ -369,12 +362,7 @@ class GradiumTTSService(AudioContextTTSService): await self._connect() try: - if not self.has_active_audio_context(): - await self.start_ttfb_metrics() - yield TTSStartedFrame(context_id=context_id) - await self.create_audio_context(context_id) - - msg = self._build_msg(text=text) + msg = self._build_msg(text=text, context_id=context_id) await self._get_websocket().send(json.dumps(msg)) await self.start_tts_usage_metrics(text) except Exception as e: diff --git a/src/pipecat/services/groq/tts.py b/src/pipecat/services/groq/tts.py index 18b623fc8..139816834 100644 --- a/src/pipecat/services/groq/tts.py +++ b/src/pipecat/services/groq/tts.py @@ -18,8 +18,6 @@ from pipecat.frames.frames import ( ErrorFrame, Frame, TTSAudioRawFrame, - TTSStartedFrame, - TTSStoppedFrame, ) from pipecat.services.settings import NOT_GIVEN, TTSSettings, _NotGiven, _warn_deprecated_param from pipecat.services.tts_service import TTSService @@ -140,6 +138,8 @@ class GroqTTSService(TTSService): super().__init__( pause_frame_processing=True, + push_start_frame=True, + push_stop_frames=True, sample_rate=sample_rate, settings=default_settings, **kwargs, @@ -171,9 +171,6 @@ class GroqTTSService(TTSService): """ logger.debug(f"{self}: Generating TTS [{text}]") measuring_ttfb = True - await self.start_ttfb_metrics() - yield TTSStartedFrame(context_id=context_id) - try: response = await self._client.audio.speech.create( model=self._settings.model, @@ -198,5 +195,3 @@ class GroqTTSService(TTSService): yield TTSAudioRawFrame(bytes, frame_rate, channels, context_id=context_id) except Exception as e: yield ErrorFrame(error=f"Unknown error occurred: {e}") - - yield TTSStoppedFrame(context_id=context_id) diff --git a/src/pipecat/services/hume/tts.py b/src/pipecat/services/hume/tts.py index 052d1cd0a..ff5eb7522 100644 --- a/src/pipecat/services/hume/tts.py +++ b/src/pipecat/services/hume/tts.py @@ -22,7 +22,6 @@ from pipecat.frames.frames import ( InterruptionFrame, StartFrame, TTSAudioRawFrame, - TTSStartedFrame, TTSStoppedFrame, ) from pipecat.processors.frame_processor import FrameDirection @@ -166,7 +165,7 @@ class HumeTTSService(TTSService): sample_rate=sample_rate, push_text_frames=False, push_stop_frames=True, - supports_word_timestamps=True, + push_start_frame=True, settings=default_settings, **kwargs, ) @@ -181,7 +180,6 @@ class HumeTTSService(TTSService): # Track cumulative time for word timestamps across utterances self._cumulative_time = 0.0 - self._started = False def can_generate_metrics(self) -> bool: """Can generate metrics. @@ -203,7 +201,6 @@ class HumeTTSService(TTSService): def _reset_state(self): """Reset internal state variables.""" self._cumulative_time = 0.0 - self._started = False async def stop(self, frame: EndFrame) -> None: """Stop the service and cleanup resources. @@ -310,15 +307,8 @@ class HumeTTSService(TTSService): # Request raw PCM chunks in the streaming JSON pcm_fmt = FormatPcm(type="pcm") - await self.start_ttfb_metrics() await self.start_tts_usage_metrics(text) - # Start TTS sequence if not already started - if not self._started: - await self.start_word_timestamps() - yield TTSStartedFrame(context_id=context_id) - self._started = True - try: # Instant mode is always enabled here (not user-configurable) # Hume emits mono PCM at 48 kHz; downstream can resample if needed. @@ -395,4 +385,3 @@ class HumeTTSService(TTSService): finally: # Ensure TTFB timer is stopped even on early failures await self.stop_ttfb_metrics() - # Let the parent class handle TTSStoppedFrame via push_stop_frames diff --git a/src/pipecat/services/inworld/tts.py b/src/pipecat/services/inworld/tts.py index a1421b2ab..d602efb52 100644 --- a/src/pipecat/services/inworld/tts.py +++ b/src/pipecat/services/inworld/tts.py @@ -62,7 +62,7 @@ from pipecat.frames.frames import ( TTSStoppedFrame, ) from pipecat.processors.frame_processor import FrameDirection -from pipecat.services.tts_service import AudioContextTTSService, TextAggregationMode, TTSService +from pipecat.services.tts_service import TextAggregationMode, TTSService, WebsocketTTSService from pipecat.utils.tracing.service_decorators import traced_tts @@ -212,7 +212,7 @@ class InworldHttpTTSService(TTSService): super().__init__( push_text_frames=False, push_stop_frames=True, - supports_word_timestamps=True, + push_start_frame=True, sample_rate=sample_rate, settings=default_settings, **kwargs, @@ -359,11 +359,6 @@ class InworldHttpTTSService(TTSService): } try: - await self.start_ttfb_metrics() - - await self.start_word_timestamps() - yield TTSStartedFrame(context_id=context_id) - async with self._session.post( self._base_url, json=payload, headers=headers ) as response: @@ -514,7 +509,7 @@ class InworldHttpTTSService(TTSService): ) -class InworldTTSService(AudioContextTTSService): +class InworldTTSService(WebsocketTTSService): """Inworld AI WebSocket-based TTS service. Uses bidirectional WebSocket for lower latency streaming. Supports multiple @@ -650,7 +645,6 @@ class InworldTTSService(AudioContextTTSService): push_text_frames=False, push_stop_frames=True, pause_frame_processing=True, - supports_word_timestamps=True, sample_rate=sample_rate, aggregate_sentences=aggregate_sentences, text_aggregation_mode=text_aggregation_mode, @@ -719,17 +713,17 @@ class InworldTTSService(AudioContextTTSService): await super().cancel(frame) await self._disconnect() - async def flush_audio(self): + async def flush_audio(self, context_id: Optional[str] = None): """Flush any pending audio without closing the context. This triggers synthesis of all accumulated text in the buffer while keeping the context open for subsequent text. The context is only closed on interruption, disconnect, or end of session. """ - context_id = self.get_active_audio_context_id() - if context_id and self._websocket: - logger.trace(f"Flushing audio for context {context_id}") - await self._send_flush(context_id) + flush_id = context_id or self.get_active_audio_context_id() + if flush_id and self._websocket: + logger.trace(f"Flushing audio for context {flush_id}") + await self._send_flush(flush_id) async def push_frame(self, frame: Frame, direction: FrameDirection = FrameDirection.DOWNSTREAM): """Push a frame and handle state changes. @@ -899,12 +893,10 @@ class InworldTTSService(AudioContextTTSService): if self._websocket: logger.debug("Disconnecting from Inworld WebSocket TTS") - context_id = self.get_active_audio_context_id() - if context_id: - try: - await self._send_close_context(context_id) - except Exception: - pass + audio_contexts = self.get_audio_contexts() + if audio_contexts: + for ctx_id in audio_contexts: + await self._send_close_context(ctx_id) await self._websocket.close() logger.debug("Disconnected from Inworld WebSocket TTS") except Exception as e: @@ -934,10 +926,7 @@ class InworldTTSService(AudioContextTTSService): for k in ["contextCreated", "audioChunk", "flushCompleted", "contextClosed"] if k in result ] - logger.debug( - f"{self}: Received message types={msg_types}, ctx_id={ctx_id}, " - f"current_ctx={self.get_active_audio_context_id()}, available={self.audio_context_available(ctx_id) if ctx_id else 'N/A'}" - ) + logger.debug(f"{self}: Received message types={msg_types}, ctx_id={ctx_id}") # Check for errors status = result.get("status", {}) @@ -948,9 +937,7 @@ class InworldTTSService(AudioContextTTSService): # Handle "Context not found" error (code 5) # This can happen when a keepalive message is sent but no context is available. if error_code == 5 and "not found" in error_msg.lower(): - logger.debug( - f"{self}: Context {ctx_id or self.get_active_audio_context_id()} not found." - ) + logger.debug(f"{self}: Context {ctx_id} not found.") continue # For other errors, push error frame @@ -961,17 +948,10 @@ class InworldTTSService(AudioContextTTSService): await self.push_error(error_msg=str(msg["error"])) continue - # Check if this message belongs to an available context. - # If the context isn't available but matches our current context ID, - # recreate it (handles race conditions during interruption recovery). + # If the context isn't available recreate it (handles race conditions during interruption recovery). if ctx_id and not self.audio_context_available(ctx_id): - if self.get_active_audio_context_id() == ctx_id: - logger.trace(f"{self}: Recreating audio context for current context: {ctx_id}") - await self.create_audio_context(ctx_id) - else: - # This is a message from an old/closed context - skip it - logger.trace(f"{self}: Skipping message from unavailable context: {ctx_id}") - continue + logger.trace(f"{self}: Recreating audio context for current context: {ctx_id}") + await self.create_audio_context(ctx_id) # Process audio chunk audio_chunk = result.get("audioChunk", {}) @@ -979,8 +959,6 @@ class InworldTTSService(AudioContextTTSService): if audio_b64: logger.trace(f"{self}: Processing audio chunk for context {ctx_id}") - await self.stop_ttfb_metrics() - await self.start_word_timestamps() audio = base64.b64decode(audio_b64) if len(audio) > 44 and audio.startswith(b"RIFF"): audio = audio[44:] @@ -1012,12 +990,8 @@ class InworldTTSService(AudioContextTTSService): if "contextClosed" in result: logger.trace(f"{self}: Context closed on server: {ctx_id}") await self.stop_ttfb_metrics() - # Only reset if this is our current context - if ctx_id == self.get_active_audio_context_id(): - self.reset_active_audio_context() - if ctx_id and self.audio_context_available(ctx_id): - await self.remove_audio_context(ctx_id) await self.add_word_timestamps([("TTSStoppedFrame", 0), ("Reset", 0)], ctx_id) + await self.remove_audio_context(ctx_id) async def _keepalive_task_handler(self): """Send periodic keepalive messages to maintain WebSocket connection.""" @@ -1128,10 +1102,10 @@ class InworldTTSService(AudioContextTTSService): await self._connect() try: - if not self.has_active_audio_context(): + if not self.audio_context_available(context_id): + await self.create_audio_context(context_id) await self.start_ttfb_metrics() yield TTSStartedFrame(context_id=context_id) - await self.create_audio_context(context_id) await self._send_context(context_id) await self._send_text(context_id, text) diff --git a/src/pipecat/services/kokoro/tts.py b/src/pipecat/services/kokoro/tts.py index 0646923f3..e69ef7a67 100644 --- a/src/pipecat/services/kokoro/tts.py +++ b/src/pipecat/services/kokoro/tts.py @@ -20,8 +20,6 @@ from pipecat.frames.frames import ( ErrorFrame, Frame, TTSAudioRawFrame, - TTSStartedFrame, - TTSStoppedFrame, ) from pipecat.services.settings import TTSSettings, _warn_deprecated_param from pipecat.services.tts_service import TTSService @@ -170,6 +168,8 @@ class KokoroTTSService(TTSService): default_settings.apply_update(settings) super().__init__( + push_start_frame=True, + push_stop_frames=True, settings=default_settings, **kwargs, ) @@ -212,9 +212,7 @@ class KokoroTTSService(TTSService): logger.debug(f"{self}: Generating TTS [{text}]") try: - await self.start_ttfb_metrics() await self.start_tts_usage_metrics(text) - yield TTSStartedFrame(context_id=context_id) stream = self._kokoro.create_stream( text, voice=self._settings.voice, lang=self._settings.language, speed=1.0 @@ -238,4 +236,3 @@ class KokoroTTSService(TTSService): yield ErrorFrame(error=f"Unknown error occurred: {e}") finally: await self.stop_ttfb_metrics() - yield TTSStoppedFrame(context_id=context_id) diff --git a/src/pipecat/services/lmnt/tts.py b/src/pipecat/services/lmnt/tts.py index 9ee6d8d60..c8bfcaf55 100644 --- a/src/pipecat/services/lmnt/tts.py +++ b/src/pipecat/services/lmnt/tts.py @@ -143,6 +143,7 @@ class LmntTTSService(InterruptibleTTSService): super().__init__( push_stop_frames=True, + push_start_frame=True, pause_frame_processing=True, sample_rate=sample_rate, settings=default_settings, @@ -152,7 +153,6 @@ class LmntTTSService(InterruptibleTTSService): self._api_key = api_key self._output_format = "raw" self._receive_task = None - self._context_id: Optional[str] = None def can_generate_metrics(self) -> bool: """Check if this service can generate processing metrics. @@ -289,7 +289,6 @@ class LmntTTSService(InterruptibleTTSService): except Exception as e: await self.push_error(error_msg=f"Error disconnecting from LMNT: {e}", exception=e) finally: - self._context_id = None self._websocket = None await self._call_event_handler("on_disconnected") @@ -299,7 +298,7 @@ class LmntTTSService(InterruptibleTTSService): return self._websocket raise Exception("Websocket not connected") - async def flush_audio(self): + async def flush_audio(self, context_id: Optional[str] = None): """Flush any pending audio synthesis.""" if not self._websocket or self._websocket.state is State.CLOSED: return @@ -315,7 +314,7 @@ class LmntTTSService(InterruptibleTTSService): audio=message, sample_rate=self.sample_rate, num_channels=1, - context_id=self._context_id, + context_id=self.get_active_audio_context_id(), ) await self.push_frame(frame) else: @@ -347,11 +346,6 @@ class LmntTTSService(InterruptibleTTSService): await self._connect() try: - await self.start_ttfb_metrics() - # Store context_id for use in _receive_messages - self._context_id = context_id - yield TTSStartedFrame(context_id=context_id) - # Send text to LMNT await self._get_websocket().send(json.dumps({"text": text})) # Force synthesis diff --git a/src/pipecat/services/minimax/tts.py b/src/pipecat/services/minimax/tts.py index efe8c1fd9..33e0669e1 100644 --- a/src/pipecat/services/minimax/tts.py +++ b/src/pipecat/services/minimax/tts.py @@ -23,8 +23,6 @@ from pipecat.frames.frames import ( Frame, StartFrame, TTSAudioRawFrame, - TTSStartedFrame, - TTSStoppedFrame, ) from pipecat.services.settings import NOT_GIVEN, TTSSettings, _NotGiven, _warn_deprecated_param from pipecat.services.tts_service import TTSService @@ -305,6 +303,8 @@ class MiniMaxHttpTTSService(TTSService): super().__init__( sample_rate=sample_rate, + push_start_frame=True, + push_stop_frames=True, settings=default_settings, **kwargs, ) @@ -402,8 +402,6 @@ class MiniMaxHttpTTSService(TTSService): payload["language_boost"] = self._settings.language_boost try: - await self.start_ttfb_metrics() - async with self._session.post( self._base_url, headers=headers, json=payload ) as response: @@ -413,7 +411,6 @@ class MiniMaxHttpTTSService(TTSService): return await self.start_tts_usage_metrics(text) - yield TTSStartedFrame(context_id=context_id) # Process the streaming response buffer = bytearray() @@ -490,4 +487,3 @@ class MiniMaxHttpTTSService(TTSService): yield ErrorFrame(error=f"Unknown error occurred: {e}", exception=e) finally: await self.stop_ttfb_metrics() - yield TTSStoppedFrame(context_id=context_id) diff --git a/src/pipecat/services/neuphonic/tts.py b/src/pipecat/services/neuphonic/tts.py index da14ec2e5..c1916414e 100644 --- a/src/pipecat/services/neuphonic/tts.py +++ b/src/pipecat/services/neuphonic/tts.py @@ -180,6 +180,7 @@ class NeuphonicTTSService(InterruptibleTTSService): aggregate_sentences=aggregate_sentences, text_aggregation_mode=text_aggregation_mode, push_stop_frames=True, + push_start_frame=True, stop_frame_timeout_s=2.0, sample_rate=sample_rate, settings=default_settings, @@ -188,12 +189,8 @@ class NeuphonicTTSService(InterruptibleTTSService): self._api_key = api_key self._url = url - - self._cumulative_time = 0 - self._receive_task = None self._keepalive_task = None - self._context_id: Optional[str] = None self._encoding = encoding self._sampling_rate = sample_rate @@ -252,7 +249,7 @@ class NeuphonicTTSService(InterruptibleTTSService): await super().cancel(frame) await self._disconnect() - async def flush_audio(self): + async def flush_audio(self, context_id: Optional[str] = None): """Flush any pending audio synthesis by sending stop command.""" if self._websocket: msg = {"text": ""} @@ -358,7 +355,6 @@ class NeuphonicTTSService(InterruptibleTTSService): except Exception as e: await self.push_error(error_msg=f"Unknown error occurred: {e}", exception=e) finally: - self._context_id = None self._websocket = None await self._call_event_handler("on_disconnected") @@ -372,7 +368,7 @@ class NeuphonicTTSService(InterruptibleTTSService): audio = base64.b64decode(msg["data"]["audio"]) frame = TTSAudioRawFrame( - audio, self.sample_rate, 1, context_id=self._context_id + audio, self.sample_rate, 1, context_id=self.get_active_audio_context_id() ) await self.push_frame(frame) @@ -415,12 +411,6 @@ class NeuphonicTTSService(InterruptibleTTSService): await self._connect() try: - await self.start_ttfb_metrics() - # Store context_id for use in _receive_messages - self._context_id = context_id - yield TTSStartedFrame(context_id=context_id) - self._cumulative_time = 0 - await self._send_text(text) await self.start_tts_usage_metrics(text) except Exception as e: @@ -523,6 +513,8 @@ class NeuphonicHttpTTSService(TTSService): super().__init__( sample_rate=sample_rate, + push_stop_frames=True, + push_start_frame=True, settings=default_settings, **kwargs, ) @@ -559,7 +551,7 @@ class NeuphonicHttpTTSService(TTSService): """ await super().start(frame) - async def flush_audio(self): + async def flush_audio(self, context_id: Optional[str] = None): """Flush any pending audio synthesis. Note: @@ -633,8 +625,6 @@ class NeuphonicHttpTTSService(TTSService): payload["voice_id"] = self._settings.voice try: - await self.start_ttfb_metrics() - async with self._session.post(url, json=payload, headers=headers) as response: if response.status != 200: error_text = await response.text() @@ -643,7 +633,6 @@ class NeuphonicHttpTTSService(TTSService): return await self.start_tts_usage_metrics(text) - yield TTSStartedFrame(context_id=context_id) # Process SSE stream line by line async for line in response.content: @@ -681,4 +670,3 @@ class NeuphonicHttpTTSService(TTSService): yield ErrorFrame(error=f"Unknown error occurred: {e}") finally: await self.stop_ttfb_metrics() - yield TTSStoppedFrame(context_id=context_id) diff --git a/src/pipecat/services/nvidia/tts.py b/src/pipecat/services/nvidia/tts.py index 6e3298a75..7f7638f5f 100644 --- a/src/pipecat/services/nvidia/tts.py +++ b/src/pipecat/services/nvidia/tts.py @@ -28,8 +28,6 @@ from pipecat.frames.frames import ( Frame, StartFrame, TTSAudioRawFrame, - TTSStartedFrame, - TTSStoppedFrame, ) from pipecat.services.settings import NOT_GIVEN, TTSSettings, _NotGiven, _warn_deprecated_param from pipecat.services.tts_service import TTSService @@ -145,6 +143,8 @@ class NvidiaTTSService(TTSService): super().__init__( sample_rate=sample_rate, + push_start_frame=True, + push_stop_frames=True, settings=default_settings, **kwargs, ) @@ -271,9 +271,6 @@ class NvidiaTTSService(TTSService): assert self._service is not None, "TTS service not initialized" assert self._config is not None, "Synthesis configuration not created" - await self.start_ttfb_metrics() - yield TTSStartedFrame(context_id=context_id) - logger.debug(f"{self}: Generating TTS [{text}]") responses = await asyncio.to_thread(read_audio_responses) @@ -289,7 +286,6 @@ class NvidiaTTSService(TTSService): yield frame await self.start_tts_usage_metrics(text) - yield TTSStoppedFrame(context_id=context_id) except asyncio.TimeoutError as e: logger.error(f"{self} timeout waiting for audio response") yield ErrorFrame(error=f"{self} error: {e}") diff --git a/src/pipecat/services/openai/tts.py b/src/pipecat/services/openai/tts.py index b4933ae9f..a50129349 100644 --- a/src/pipecat/services/openai/tts.py +++ b/src/pipecat/services/openai/tts.py @@ -22,8 +22,6 @@ from pipecat.frames.frames import ( Frame, StartFrame, TTSAudioRawFrame, - TTSStartedFrame, - TTSStoppedFrame, ) from pipecat.services.settings import NOT_GIVEN, TTSSettings, _NotGiven, _warn_deprecated_param from pipecat.services.tts_service import TTSService @@ -194,6 +192,8 @@ class OpenAITTSService(TTSService): super().__init__( sample_rate=sample_rate, + push_start_frame=True, + push_stop_frames=True, settings=default_settings, **kwargs, ) @@ -234,8 +234,6 @@ class OpenAITTSService(TTSService): """ logger.debug(f"{self}: Generating TTS [{text}]") try: - await self.start_ttfb_metrics() - # Setup API parameters create_params = { "input": text, @@ -267,12 +265,10 @@ class OpenAITTSService(TTSService): CHUNK_SIZE = self.chunk_size - yield TTSStartedFrame(context_id=context_id) async for chunk in r.iter_bytes(CHUNK_SIZE): if len(chunk) > 0: await self.stop_ttfb_metrics() frame = TTSAudioRawFrame(chunk, self.sample_rate, 1, context_id=context_id) yield frame - yield TTSStoppedFrame(context_id=context_id) except BadRequestError as e: yield ErrorFrame(error=f"Unknown error occurred: {e}") diff --git a/src/pipecat/services/piper/tts.py b/src/pipecat/services/piper/tts.py index 46bf98cd1..f0343947b 100644 --- a/src/pipecat/services/piper/tts.py +++ b/src/pipecat/services/piper/tts.py @@ -17,8 +17,6 @@ from loguru import logger from pipecat.frames.frames import ( ErrorFrame, Frame, - TTSStartedFrame, - TTSStoppedFrame, ) from pipecat.services.settings import TTSSettings, _warn_deprecated_param from pipecat.services.tts_service import TTSService @@ -91,6 +89,8 @@ class PiperTTSService(TTSService): default_settings.apply_update(settings) super().__init__( + push_start_frame=True, + push_stop_frames=True, settings=default_settings, **kwargs, ) @@ -159,12 +159,8 @@ class PiperTTSService(TTSService): logger.debug(f"{self}: Generating TTS [{text}]") try: - await self.start_ttfb_metrics() - await self.start_tts_usage_metrics(text) - yield TTSStartedFrame(context_id=context_id) - async for frame in self._stream_audio_frames_from_iterator( async_iterator(self._voice.synthesize(text)), in_sample_rate=self._voice.config.sample_rate, @@ -178,7 +174,6 @@ class PiperTTSService(TTSService): finally: logger.debug(f"{self}: Finished TTS [{text}]") await self.stop_ttfb_metrics() - yield TTSStoppedFrame(context_id=context_id) # This assumes a running TTS service running: @@ -244,6 +239,8 @@ class PiperHttpTTSService(TTSService): default_settings.apply_update(settings) super().__init__( + push_start_frame=True, + push_stop_frames=True, settings=default_settings, **kwargs, ) @@ -279,8 +276,6 @@ class PiperHttpTTSService(TTSService): "Content-Type": "application/json", } try: - await self.start_ttfb_metrics() - data = { "text": text, "voice": self._settings.voice, @@ -296,8 +291,6 @@ class PiperHttpTTSService(TTSService): await self.start_tts_usage_metrics(text) - yield TTSStartedFrame(context_id=context_id) - CHUNK_SIZE = self.chunk_size async for frame in self._stream_audio_frames_from_iterator( @@ -311,4 +304,3 @@ class PiperHttpTTSService(TTSService): yield ErrorFrame(error=f"Unknown error occurred: {e}") finally: await self.stop_ttfb_metrics() - yield TTSStoppedFrame(context_id=context_id) diff --git a/src/pipecat/services/resembleai/tts.py b/src/pipecat/services/resembleai/tts.py index e1c1cf68a..45f8fc229 100644 --- a/src/pipecat/services/resembleai/tts.py +++ b/src/pipecat/services/resembleai/tts.py @@ -24,7 +24,7 @@ from pipecat.frames.frames import ( TTSStoppedFrame, ) from pipecat.services.settings import TTSSettings, _warn_deprecated_param -from pipecat.services.tts_service import AudioContextTTSService +from pipecat.services.tts_service import WebsocketTTSService from pipecat.utils.tracing.service_decorators import traced_tts try: @@ -43,7 +43,7 @@ class ResembleAITTSSettings(TTSSettings): pass -class ResembleAITTSService(AudioContextTTSService): +class ResembleAITTSService(WebsocketTTSService): """Resemble AI TTS service with WebSocket streaming and word timestamps. Provides text-to-speech using Resemble AI's streaming WebSocket API. @@ -103,7 +103,6 @@ class ResembleAITTSService(AudioContextTTSService): super().__init__( sample_rate=sample_rate, reuse_context_id_within_turn=False, - supports_word_timestamps=True, settings=default_settings, **kwargs, ) @@ -268,7 +267,7 @@ class ResembleAITTSService(AudioContextTTSService): """ pass - async def flush_audio(self): + async def flush_audio(self, context_id: Optional[str] = None): """Flush any pending audio and finalize the current context.""" logger.trace(f"{self}: flushing audio") # For Resemble AI, we just wait for the audio_end message @@ -297,9 +296,6 @@ class ResembleAITTSService(AudioContextTTSService): continue if msg_type == "audio": - await self.stop_ttfb_metrics() - await self.start_word_timestamps() - # Decode base64 audio content audio_content = msg.get("audio_content", "") if not audio_content: @@ -447,14 +443,14 @@ class ResembleAITTSService(AudioContextTTSService): if not self._websocket or self._websocket.state is State.CLOSED: await self._connect() - await self.start_ttfb_metrics() - yield TTSStartedFrame(context_id=context_id) + if not self.audio_context_available(context_id): + await self.create_audio_context(context_id) + await self.start_ttfb_metrics() + yield TTSStartedFrame(context_id=context_id) # Map request_id to context_id for tracking self._request_id_to_context[self._request_id_counter] = context_id - await self.create_audio_context(context_id) - msg = self._build_msg(text=text) try: diff --git a/src/pipecat/services/rime/tts.py b/src/pipecat/services/rime/tts.py index 04ebcd5fc..27580504b 100644 --- a/src/pipecat/services/rime/tts.py +++ b/src/pipecat/services/rime/tts.py @@ -33,10 +33,10 @@ from pipecat.frames.frames import ( from pipecat.processors.frame_processor import FrameDirection from pipecat.services.settings import NOT_GIVEN, TTSSettings, _NotGiven, _warn_deprecated_param from pipecat.services.tts_service import ( - AudioContextTTSService, InterruptibleTTSService, TextAggregationMode, TTSService, + WebsocketTTSService, ) from pipecat.transcriptions.language import Language, resolve_language from pipecat.utils.text.base_text_aggregator import BaseTextAggregator @@ -123,7 +123,7 @@ class RimeNonJsonTTSSettings(TTSSettings): _aliases: ClassVar[Dict[str, str]] = {"speaker": "voice"} -class RimeTTSService(AudioContextTTSService): +class RimeTTSService(WebsocketTTSService): """Text-to-Speech service using Rime's websocket API. Uses Rime's websocket JSON API to convert text to speech with word-level timing @@ -276,7 +276,6 @@ class RimeTTSService(AudioContextTTSService): push_text_frames=False, push_stop_frames=True, pause_frame_processing=True, - supports_word_timestamps=True, append_trailing_space=True, sample_rate=sample_rate, settings=default_settings, @@ -408,9 +407,9 @@ class RimeTTSService(AudioContextTTSService): return changed - def _build_msg(self, text: str = "") -> dict: + def _build_msg(self, text: str = "", context_id: str = "") -> dict: """Build JSON message for Rime API.""" - msg = {"text": text, "contextId": self.get_active_audio_context_id()} + msg = {"text": text, "contextId": context_id} if self._extra_msg_fields: msg |= self._extra_msg_fields self._extra_msg_fields = {} @@ -557,15 +556,14 @@ class RimeTTSService(AudioContextTTSService): return word_pairs - async def flush_audio(self): + async def flush_audio(self, context_id: Optional[str] = None): """Flush any pending audio synthesis.""" - context_id = self.get_active_audio_context_id() - if not context_id or not self._websocket: + flush_id = context_id or self.get_active_audio_context_id() + if not flush_id or not self._websocket: return logger.trace(f"{self}: flushing audio") await self._get_websocket().send(json.dumps({"operation": "flush"})) - self.reset_active_audio_context() async def _receive_messages(self): """Process incoming websocket messages.""" @@ -578,8 +576,6 @@ class RimeTTSService(AudioContextTTSService): context_id = msg["contextId"] if msg["type"] == "chunk": # Process audio chunk - await self.stop_ttfb_metrics() - await self.start_word_timestamps() frame = TTSAudioRawFrame( audio=base64.b64decode(msg["data"]), sample_rate=self.sample_rate, @@ -638,13 +634,13 @@ class RimeTTSService(AudioContextTTSService): await self._connect() try: - if not self.has_active_audio_context(): + if not self.audio_context_available(context_id): + await self.create_audio_context(context_id) await self.start_ttfb_metrics() yield TTSStartedFrame(context_id=context_id) self._cumulative_time = 0 - await self.create_audio_context(context_id) - msg = self._build_msg(text=text) + msg = self._build_msg(text=text, context_id=context_id) await self._get_websocket().send(json.dumps(msg)) await self.start_tts_usage_metrics(text) except Exception as e: @@ -773,6 +769,8 @@ class RimeHttpTTSService(TTSService): super().__init__( sample_rate=sample_rate, + push_stop_frames=True, + push_start_frame=True, settings=default_settings, **kwargs, ) @@ -844,8 +842,6 @@ class RimeHttpTTSService(TTSService): need_to_strip_wav_header = False try: - await self.start_ttfb_metrics() - async with self._session.post( self._base_url, json=payload, headers=headers ) as response: @@ -856,8 +852,6 @@ class RimeHttpTTSService(TTSService): await self.start_tts_usage_metrics(text) - yield TTSStartedFrame(context_id=context_id) - CHUNK_SIZE = self.chunk_size async for frame in self._stream_audio_frames_from_iterator( @@ -872,7 +866,6 @@ class RimeHttpTTSService(TTSService): yield ErrorFrame(error=f"Unknown error occurred: {e}") finally: await self.stop_ttfb_metrics() - yield TTSStoppedFrame(context_id=context_id) class RimeNonJsonTTSService(InterruptibleTTSService): @@ -1005,6 +998,7 @@ class RimeNonJsonTTSService(InterruptibleTTSService): aggregate_sentences=aggregate_sentences, text_aggregation_mode=text_aggregation_mode, push_stop_frames=True, + push_start_frame=True, pause_frame_processing=True, append_trailing_space=True, settings=default_settings, @@ -1022,7 +1016,6 @@ class RimeNonJsonTTSService(InterruptibleTTSService): self._settings.extra.update(params.extra) self._receive_task = None - self._context_id: Optional[str] = None def can_generate_metrics(self) -> bool: """Check if this service can generate processing metrics. @@ -1138,7 +1131,6 @@ class RimeNonJsonTTSService(InterruptibleTTSService): except Exception as e: await self.push_error(error_msg=f"Unknown error occurred: {e}", exception=e) finally: - self._context_id = None self._websocket = None await self._call_event_handler("on_disconnected") @@ -1148,7 +1140,7 @@ class RimeNonJsonTTSService(InterruptibleTTSService): return self._websocket raise Exception("Websocket not connected") - async def flush_audio(self): + async def flush_audio(self, context_id: Optional[str] = None): """Flush any pending audio synthesis.""" if not self._websocket: return @@ -1168,7 +1160,7 @@ class RimeNonJsonTTSService(InterruptibleTTSService): audio=message, sample_rate=self.sample_rate, num_channels=1, - context_id=self._context_id, + context_id=self.get_active_audio_context_id(), ) await self.push_frame(frame) except Exception as e: @@ -1190,10 +1182,6 @@ class RimeNonJsonTTSService(InterruptibleTTSService): if not self._websocket or self._websocket.state is State.CLOSED: await self._connect() try: - await self.start_ttfb_metrics() - # Store context_id for use in _receive_messages - self._context_id = context_id - yield TTSStartedFrame(context_id=context_id) # Send bare text (not JSON) await self._get_websocket().send(text) await self.start_tts_usage_metrics(text) diff --git a/src/pipecat/services/sarvam/tts.py b/src/pipecat/services/sarvam/tts.py index 0d605fc6b..6bf38bb24 100644 --- a/src/pipecat/services/sarvam/tts.py +++ b/src/pipecat/services/sarvam/tts.py @@ -524,6 +524,8 @@ class SarvamHttpTTSService(TTSService): super().__init__( sample_rate=sample_rate, + push_stop_frames=True, + push_start_frame=True, settings=default_settings, **kwargs, ) @@ -573,8 +575,6 @@ class SarvamHttpTTSService(TTSService): logger.debug(f"{self}: Generating TTS [{text}]") try: - await self.start_ttfb_metrics() - # Build payload with common parameters payload = { "text": text, @@ -606,8 +606,6 @@ class SarvamHttpTTSService(TTSService): url = f"{self._base_url}/text-to-speech" - yield TTSStartedFrame(context_id=context_id) - async with self._session.post(url, json=payload, headers=headers) as response: if response.status != 200: error_text = await response.text() @@ -645,7 +643,6 @@ class SarvamHttpTTSService(TTSService): yield ErrorFrame(error=f"Error generating TTS: {e}", exception=e) finally: await self.stop_ttfb_metrics() - yield TTSStoppedFrame(context_id=context_id) class SarvamTTSService(InterruptibleTTSService): @@ -951,6 +948,7 @@ class SarvamTTSService(InterruptibleTTSService): push_text_frames=True, pause_frame_processing=True, push_stop_frames=True, + push_start_frame=True, sample_rate=sample_rate, settings=default_settings, **kwargs, @@ -967,7 +965,6 @@ class SarvamTTSService(InterruptibleTTSService): self._receive_task = None self._keepalive_task = None - self._context_id: Optional[str] = None def can_generate_metrics(self) -> bool: """Check if this service can generate processing metrics. @@ -1018,7 +1015,7 @@ class SarvamTTSService(InterruptibleTTSService): await super().cancel(frame) await self._disconnect() - async def flush_audio(self): + async def flush_audio(self, context_id: Optional[str] = None): """Flush any pending audio synthesis by sending flush command.""" try: if self._websocket: @@ -1151,7 +1148,6 @@ class SarvamTTSService(InterruptibleTTSService): except Exception as e: await self.push_error(error_msg=f"Error closing websocket: {e}", exception=e) finally: - self._context_id = None self._websocket = None await self._call_event_handler("on_disconnected") @@ -1170,7 +1166,7 @@ class SarvamTTSService(InterruptibleTTSService): await self.stop_ttfb_metrics() audio = base64.b64decode(msg["data"]["audio"]) frame = TTSAudioRawFrame( - audio, self.sample_rate, 1, context_id=self._context_id + audio, self.sample_rate, 1, context_id=self.get_active_audio_context_id() ) await self.push_frame(frame) elif msg.get("type") == "error": @@ -1224,10 +1220,6 @@ class SarvamTTSService(InterruptibleTTSService): await self._connect() try: - await self.start_ttfb_metrics() - # Store context_id for use in _receive_messages - self._context_id = context_id - yield TTSStartedFrame(context_id=context_id) await self._send_text(text) await self.start_tts_usage_metrics(text) except Exception as e: diff --git a/src/pipecat/services/speechmatics/tts.py b/src/pipecat/services/speechmatics/tts.py index 55ded437e..22b47f3fc 100644 --- a/src/pipecat/services/speechmatics/tts.py +++ b/src/pipecat/services/speechmatics/tts.py @@ -19,8 +19,6 @@ from pipecat.frames.frames import ( ErrorFrame, Frame, TTSAudioRawFrame, - TTSStartedFrame, - TTSStoppedFrame, ) from pipecat.services.settings import NOT_GIVEN, TTSSettings, _NotGiven, _warn_deprecated_param from pipecat.services.tts_service import TTSService @@ -135,6 +133,8 @@ class SpeechmaticsTTSService(TTSService): super().__init__( sample_rate=sample_rate, + push_start_frame=True, + push_stop_frames=True, settings=default_settings, **kwargs, ) @@ -185,9 +185,6 @@ class SpeechmaticsTTSService(TTSService): url = _get_endpoint_url(self._base_url, self._settings.voice, self.sample_rate) try: - # Start TTS TTFB metrics - await self.start_ttfb_metrics() - # Track attempt attempt = 0 @@ -238,9 +235,6 @@ class SpeechmaticsTTSService(TTSService): # Update Pipecat metrics await self.start_tts_usage_metrics(text) - # Emit the TTS started frame - yield TTSStartedFrame(context_id=context_id) - # Process the response in streaming chunks first_chunk = True buffer = b"" @@ -277,8 +271,7 @@ class SpeechmaticsTTSService(TTSService): except Exception as e: yield ErrorFrame(error=f"Error generating TTS: {e}") finally: - # Emit the TTS stopped frame - yield TTSStoppedFrame(context_id=context_id) + await self.stop_ttfb_metrics() def _get_endpoint_url(base_url: str, voice: str, sample_rate: int) -> str: diff --git a/src/pipecat/services/xtts/tts.py b/src/pipecat/services/xtts/tts.py index ea7cb0b8b..539ddc88c 100644 --- a/src/pipecat/services/xtts/tts.py +++ b/src/pipecat/services/xtts/tts.py @@ -11,7 +11,7 @@ text-to-speech synthesis using local Docker deployment. """ from dataclasses import dataclass -from typing import AsyncGenerator, Dict, Optional +from typing import Any, AsyncGenerator, Dict, Optional import aiohttp from loguru import logger @@ -22,8 +22,6 @@ from pipecat.frames.frames import ( Frame, StartFrame, TTSAudioRawFrame, - TTSStartedFrame, - TTSStoppedFrame, ) from pipecat.services.settings import TTSSettings, _warn_deprecated_param from pipecat.services.tts_service import TTSService @@ -132,6 +130,8 @@ class XTTSService(TTSService): super().__init__( sample_rate=sample_rate, + push_start_frame=True, + push_stop_frames=True, settings=default_settings, **kwargs, ) @@ -213,8 +213,6 @@ class XTTSService(TTSService): "stream_chunk_size": 20, } - await self.start_ttfb_metrics() - async with self._aiohttp_session.post(url, json=payload) as r: if r.status != 200: text = await r.text() @@ -223,8 +221,6 @@ class XTTSService(TTSService): await self.start_tts_usage_metrics(text) - yield TTSStartedFrame(context_id=context_id) - CHUNK_SIZE = self.chunk_size buffer = bytearray() @@ -262,5 +258,3 @@ class XTTSService(TTSService): resampled_audio, self.sample_rate, 1, context_id=context_id ) yield frame - - yield TTSStoppedFrame(context_id=context_id) From 07abd3d60fe63f970f878fb7fb0662973e2fbc7c Mon Sep 17 00:00:00 2001 From: filipi87 Date: Fri, 6 Mar 2026 16:16:11 -0300 Subject: [PATCH 0836/1060] Fixed BotStoppedSpeakingFrame emission: now emitted as soon as TTSStoppedFrame is received, with a fallback silence-based timeout increased to reduce false positives --- src/pipecat/transports/base_output.py | 25 +++++++++++++++++++++---- 1 file changed, 21 insertions(+), 4 deletions(-) diff --git a/src/pipecat/transports/base_output.py b/src/pipecat/transports/base_output.py index 15eb99f3a..e14ae3828 100644 --- a/src/pipecat/transports/base_output.py +++ b/src/pipecat/transports/base_output.py @@ -44,12 +44,15 @@ from pipecat.frames.frames import ( StartFrame, SystemFrame, TTSAudioRawFrame, + TTSStoppedFrame, ) from pipecat.processors.frame_processor import FrameDirection, FrameProcessor from pipecat.transports.base_transport import TransportParams from pipecat.utils.time import nanoseconds_to_seconds BOT_VAD_STOP_SECS = 0.35 +# Only used as a fallback +BOT_VAD_STOP_FALLBACK_SECS = 3 class BaseOutputTransport(FrameProcessor): @@ -354,6 +357,8 @@ class BaseOutputTransport(FrameProcessor): await sender.handle_sync_frame(frame) elif isinstance(frame, MixerControlFrame): await sender.handle_mixer_control_frame(frame) + elif isinstance(frame, TTSStoppedFrame): + await sender.handle_sync_frame(frame) elif frame.pts: await sender.handle_timed_frame(frame) else: @@ -412,6 +417,8 @@ class BaseOutputTransport(FrameProcessor): # Indicates if the bot is currently speaking. self._bot_speaking = False + # Indicates if TTS audio has been received since the last stop. + self._tts_audio_received = False # Last time a BotSpeakingFrame was pushed. self._bot_speaking_frame_time = 0 # How often a BotSpeakingFrame should be pushed (value should be @@ -639,6 +646,7 @@ class BaseOutputTransport(FrameProcessor): return self._bot_speaking = False + self._tts_audio_received = False # Clean audio buffer (there could be tiny left overs if not multiple # to our output chunk size). @@ -682,6 +690,9 @@ class BaseOutputTransport(FrameProcessor): async def _handle_bot_speech(self, frame: Frame): # TTS case. if isinstance(frame, TTSAudioRawFrame): + # We will only trigger bot stopped speaking based on the TTSStoppedFrame, + # if we have received audio from TTS + self._tts_audio_received = True await self._bot_currently_speaking() # Speech stream case. elif isinstance(frame, SpeechOutputAudioRawFrame): @@ -703,6 +714,12 @@ class BaseOutputTransport(FrameProcessor): await self._transport.send_message(frame) elif isinstance(frame, OutputDTMFFrame): await self._transport.write_dtmf(frame) + elif isinstance(frame, TTSStoppedFrame): + # We will only trigger bot stopped speaking based on the TTSStoppedFrame, + # if we have received audio from TTS + if self._tts_audio_received: + logger.debug("Bot stopped speaking based on TTSStoppedFrame") + await self._bot_stopped_speaking() else: await self._transport.write_transport_frame(frame) @@ -722,7 +739,7 @@ class BaseOutputTransport(FrameProcessor): yield frame self._audio_queue.task_done() except asyncio.TimeoutError: - # Notify the bot stopped speaking upstream if necessary. + # Fallback: notify the bot stopped speaking upstream if necessary based on timeout. await self._bot_stopped_speaking() async def with_mixer(vad_stop_secs: float) -> AsyncGenerator[Frame, None]: @@ -737,7 +754,7 @@ class BaseOutputTransport(FrameProcessor): yield frame self._audio_queue.task_done() except asyncio.QueueEmpty: - # Notify the bot stopped speaking upstream if necessary. + # Fallback: notify the bot stopped speaking upstream if necessary based on timeout. diff_time = time.time() - last_frame_time if diff_time > vad_stop_secs: await self._bot_stopped_speaking() @@ -755,9 +772,9 @@ class BaseOutputTransport(FrameProcessor): await asyncio.sleep(0) if self._mixer: - return with_mixer(BOT_VAD_STOP_SECS) + return with_mixer(BOT_VAD_STOP_FALLBACK_SECS) else: - return without_mixer(BOT_VAD_STOP_SECS) + return without_mixer(BOT_VAD_STOP_FALLBACK_SECS) async def _send_silence(self, secs: int): if secs <= 0: From 3000037dec4c8078813d42229d824e04eee80b4a Mon Sep 17 00:00:00 2001 From: filipi87 Date: Fri, 6 Mar 2026 16:16:25 -0300 Subject: [PATCH 0837/1060] Changelog entries for the TTS improvements and fixes. --- changelog/3804.added.md | 1 + changelog/3804.changed.md | 1 + changelog/3804.deprecated.md | 2 ++ changelog/3804.removed.md | 1 + 4 files changed, 5 insertions(+) create mode 100644 changelog/3804.added.md create mode 100644 changelog/3804.changed.md create mode 100644 changelog/3804.deprecated.md create mode 100644 changelog/3804.removed.md diff --git a/changelog/3804.added.md b/changelog/3804.added.md new file mode 100644 index 000000000..0ad7676c9 --- /dev/null +++ b/changelog/3804.added.md @@ -0,0 +1 @@ +- Added concurrent audio context support: `CartesiaTTSService` can now synthesize the next sentence while the previous one is still playing, by setting `pause_frame_processing=False` and routing each sentence through its own audio context queue. diff --git a/changelog/3804.changed.md b/changelog/3804.changed.md new file mode 100644 index 000000000..9caae491f --- /dev/null +++ b/changelog/3804.changed.md @@ -0,0 +1 @@ +- Audio context management (previously in `AudioContextTTSService`) is now built into `TTSService`. All WebSocket providers (`cartesia`, `elevenlabs`, `asyncai`, `inworld`, `rime`, `gradium`, `resembleai`) now inherit from `WebsocketTTSService` directly. Word-timestamp baseline is set automatically on the first audio chunk of each context instead of requiring each provider to call `start_word_timestamps()` in their receive loop. diff --git a/changelog/3804.deprecated.md b/changelog/3804.deprecated.md new file mode 100644 index 000000000..0babfe7d4 --- /dev/null +++ b/changelog/3804.deprecated.md @@ -0,0 +1,2 @@ +- Deprecated `AudioContextTTSService` and `AudioContextWordTTSService`. Subclass `WebsocketTTSService` directly instead; audio context management is now part of the base `TTSService`. +- Deprecated `WordTTSService`, `WebsocketWordTTSService`, and `InterruptibleWordTTSService`. Word timestamp logic is now always active in `TTSService` and no longer needs to be opted into via a subclass. diff --git a/changelog/3804.removed.md b/changelog/3804.removed.md new file mode 100644 index 000000000..1813b5999 --- /dev/null +++ b/changelog/3804.removed.md @@ -0,0 +1 @@ +- ⚠️ Removed `supports_word_timestamps` parameter from `TTSService.__init__()`. Word timestamp logic is now always active. Remove this argument from any custom subclass `super().__init__()` calls. From 9b7a86bb12fc9bea7a285a14059b80b6eb29a5f2 Mon Sep 17 00:00:00 2001 From: Paul Kompfner Date: Fri, 6 Mar 2026 14:29:59 -0500 Subject: [PATCH 0838/1060] Add AudioConfig class to AWSNovaSonicLLMService for non-deprecated audio configuration The audio fields (sample rates, sample sizes, channel counts) on the deprecated `Params` class had no non-deprecated equivalent. This adds an `AudioConfig` class and `audio_config` init arg so users can specify audio configuration without relying on the deprecated `params` parameter. --- ...5zzk-update-settings-aws-nova-sonic-llm.py | 4 +- src/pipecat/services/aws/nova_sonic/llm.py | 95 +++++++++++++++---- 2 files changed, 77 insertions(+), 22 deletions(-) diff --git a/examples/foundational/55zzk-update-settings-aws-nova-sonic-llm.py b/examples/foundational/55zzk-update-settings-aws-nova-sonic-llm.py index c6789a521..de516baa8 100644 --- a/examples/foundational/55zzk-update-settings-aws-nova-sonic-llm.py +++ b/examples/foundational/55zzk-update-settings-aws-nova-sonic-llm.py @@ -52,7 +52,9 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): secret_access_key=os.getenv("AWS_SECRET_ACCESS_KEY"), access_key_id=os.getenv("AWS_ACCESS_KEY_ID"), region=os.getenv("AWS_REGION"), - system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + settings=AWSNovaSonicLLMSettings( + system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + ), ) context = LLMContext() diff --git a/src/pipecat/services/aws/nova_sonic/llm.py b/src/pipecat/services/aws/nova_sonic/llm.py index fd13fe56e..3948ae1eb 100644 --- a/src/pipecat/services/aws/nova_sonic/llm.py +++ b/src/pipecat/services/aws/nova_sonic/llm.py @@ -149,6 +149,10 @@ class CurrentContent: class Params(BaseModel): """Configuration parameters for AWS Nova Sonic. + .. deprecated:: 0.0.105 + Use ``settings=AWSNovaSonicLLMSettings(...)`` for inference settings + and ``audio_config=AudioConfig(...)`` for audio configuration. + Parameters: input_sample_rate: Audio input sample rate in Hz. input_sample_size: Audio input sample size in bits. @@ -185,6 +189,41 @@ class Params(BaseModel): # Turn-taking endpointing_sensitivity: Optional[str] = Field(default=None) + @property + def audio_config(self) -> "AudioConfig": + """Return an ``AudioConfig`` populated from this instance's audio fields.""" + return AudioConfig( + input_sample_rate=self.input_sample_rate, + input_sample_size=self.input_sample_size, + input_channel_count=self.input_channel_count, + output_sample_rate=self.output_sample_rate, + output_sample_size=self.output_sample_size, + output_channel_count=self.output_channel_count, + ) + + +class AudioConfig(BaseModel): + """Audio configuration for AWS Nova Sonic. + + Parameters: + input_sample_rate: Audio input sample rate in Hz. + input_sample_size: Audio input sample size in bits. + input_channel_count: Number of input audio channels. + output_sample_rate: Audio output sample rate in Hz. + output_sample_size: Audio output sample size in bits. + output_channel_count: Number of output audio channels. + """ + + # Input + input_sample_rate: Optional[int] = Field(default=16000) + input_sample_size: Optional[int] = Field(default=16) + input_channel_count: Optional[int] = Field(default=1) + + # Output + output_sample_rate: Optional[int] = Field(default=24000) + output_sample_size: Optional[int] = Field(default=16) + output_channel_count: Optional[int] = Field(default=1) + @dataclass class AWSNovaSonicLLMSettings(LLMSettings): @@ -222,6 +261,7 @@ class AWSNovaSonicLLMService(LLMService): model: str = "amazon.nova-2-sonic-v1:0", voice_id: str = "matthew", params: Optional[Params] = None, + audio_config: Optional[AudioConfig] = None, settings: Optional[AWSNovaSonicLLMSettings] = None, system_instruction: Optional[str] = None, tools: Optional[ToolsSchema] = None, @@ -254,9 +294,13 @@ class AWSNovaSonicLLMService(LLMService): params: Model parameters for audio configuration and inference. - .. deprecated:: - Use ``settings=AWSNovaSonicLLMSettings(...)`` instead. + .. deprecated:: 0.0.105 + Use ``settings=AWSNovaSonicLLMSettings(...)`` for inference + settings and ``audio_config=AudioConfig(...)`` for audio + configuration. + audio_config: Audio configuration (sample rates, sample sizes, + channel counts). If not provided, defaults are used. settings: AWS Nova Sonic LLM settings. If provided together with deprecated top-level parameters, the ``settings`` values take precedence. @@ -305,7 +349,19 @@ class AWSNovaSonicLLMService(LLMService): # 3. Apply params overrides — only if settings not provided if params is not None: - _warn_deprecated_param("params", AWSNovaSonicLLMSettings) + import warnings + + with warnings.catch_warnings(): + warnings.simplefilter("always") + warnings.warn( + "The `params` parameter is deprecated. " + "Use `settings=AWSNovaSonicLLMSettings(...)` for inference settings " + "(temperature, max_tokens, top_p, endpointing_sensitivity) " + "and `audio_config=AudioConfig(...)` for audio configuration " + "(sample rates, sample sizes, channel counts).", + DeprecationWarning, + stacklevel=2, + ) if not settings: default_settings.temperature = params.temperature default_settings.max_tokens = params.max_tokens @@ -327,13 +383,10 @@ class AWSNovaSonicLLMService(LLMService): self._client: Optional[BedrockRuntimeClient] = None # Audio I/O config (hardware settings, not runtime-tunable) - _audio_params = params or Params() - self._input_sample_rate = _audio_params.input_sample_rate - self._input_sample_size = _audio_params.input_sample_size - self._input_channel_count = _audio_params.input_channel_count - self._output_sample_rate = _audio_params.output_sample_rate - self._output_sample_size = _audio_params.output_sample_size - self._output_channel_count = _audio_params.output_channel_count + # Priority: audio_config > params (deprecated) > defaults + self._audio_config = audio_config or ( + params.audio_config if params is not None else AudioConfig() + ) self._tools = tools # Validate endpointing_sensitivity parameter @@ -816,9 +869,9 @@ class AWSNovaSonicLLMService(LLMService): }}, "audioOutputConfiguration": {{ "mediaType": "audio/lpcm", - "sampleRateHertz": {self._output_sample_rate}, - "sampleSizeBits": {self._output_sample_size}, - "channelCount": {self._output_channel_count}, + "sampleRateHertz": {self._audio_config.output_sample_rate}, + "sampleSizeBits": {self._audio_config.output_sample_size}, + "channelCount": {self._audio_config.output_channel_count}, "voiceId": "{self._settings.voice}", "encoding": "base64", "audioType": "SPEECH" @@ -844,9 +897,9 @@ class AWSNovaSonicLLMService(LLMService): "role": "USER", "audioInputConfiguration": {{ "mediaType": "audio/lpcm", - "sampleRateHertz": {self._input_sample_rate}, - "sampleSizeBits": {self._input_sample_size}, - "channelCount": {self._input_channel_count}, + "sampleRateHertz": {self._audio_config.input_sample_rate}, + "sampleSizeBits": {self._audio_config.input_sample_size}, + "channelCount": {self._audio_config.input_channel_count}, "audioType": "SPEECH", "encoding": "base64" }} @@ -1129,8 +1182,8 @@ class AWSNovaSonicLLMService(LLMService): audio = base64.b64decode(audio_content) frame = TTSAudioRawFrame( audio=audio, - sample_rate=self._output_sample_rate, - num_channels=self._output_channel_count, + sample_rate=self._audio_config.output_sample_rate, + num_channels=self._audio_config.output_channel_count, ) await self.push_frame(frame) @@ -1442,9 +1495,9 @@ class AWSNovaSonicLLMService(LLMService): chunk_duration = 0.02 # what we might get from InputAudioRawFrame chunk_size = int( chunk_duration - * self._input_sample_rate - * self._input_channel_count - * (self._input_sample_size / 8) + * self._audio_config.input_sample_rate + * self._audio_config.input_channel_count + * (self._audio_config.input_sample_size / 8) ) # e.g. 0.02 seconds of 16-bit (2-byte) PCM mono audio at 16kHz is 640 bytes # Lead with a bit of blank audio, if needed. From 696e431e961bba7d79726fb81f77d4f4b32f5f01 Mon Sep 17 00:00:00 2001 From: Mark Backman Date: Fri, 6 Mar 2026 10:48:39 -0500 Subject: [PATCH 0839/1060] Broaden Service Settings docs to cover all AI service types Use "AI service" language instead of listing specific types, add ServiceSettings as a fallback for direct AIService subclasses, and clarify delta mode description with a concrete frame example. --- COMMUNITY_INTEGRATIONS.md | 8 ++++---- 1 file changed, 4 insertions(+), 4 deletions(-) diff --git a/COMMUNITY_INTEGRATIONS.md b/COMMUNITY_INTEGRATIONS.md index 5dd9e5764..e17c72bc7 100644 --- a/COMMUNITY_INTEGRATIONS.md +++ b/COMMUNITY_INTEGRATIONS.md @@ -233,14 +233,14 @@ def can_generate_metrics(self) -> bool: ### Service Settings -Every STT, LLM, TTS, and image-generation service exposes a **Settings dataclass** that serves two roles: +Every AI service (STT, LLM, TTS, image generation, etc.) exposes a **Settings dataclass** that serves two roles: 1. **Store mode** — the service's `self._settings` holds the current value of every runtime-updatable field. -2. **Delta mode** — an update frame carries only the fields that changed; unset fields remain `NOT_GIVEN`. +2. **Delta mode** — an update frame (e.g. `TTSUpdateSettingsFrame`) specifies only the fields that should change; unspecified fields remain `NOT_GIVEN`. #### Defining your Settings class -Extend `STTSettings`, `TTSSettings`, `LLMSettings`, or `ImageGenSettings`. The base classes already provide common fields (e.g. `model`, `voice`, `language`). You only need to add **service-specific knobs that should be runtime-updatable**: +Extend `STTSettings`, `TTSSettings`, `LLMSettings`, or `ImageGenSettings` (or, if your service directly subclasses `AIService`, `ServiceSettings`). The base classes already provide common fields (e.g. `model`, `voice`, `language`). You only need to add **service-specific knobs that should be runtime-updatable**: ```python from dataclasses import dataclass, field @@ -320,7 +320,7 @@ svc = MyTTSService( #### Reacting to runtime changes -STT, LLM, and TTS services support runtime configuration changes via `*UpdateSettingsFrame`s (e.g. `STTUpdateSettingsFrame`, `TTSUpdateSettingsFrame`, `LLMUpdateSettingsFrame`). +AI services support runtime configuration changes via `*UpdateSettingsFrame`s (e.g. `STTUpdateSettingsFrame`, `TTSUpdateSettingsFrame`, `LLMUpdateSettingsFrame`). To react to runtime setting changes, override `_update_settings`. The base implementation applies the delta to `self._settings` and returns a `dict` mapping each changed field name to its **pre-update** value. Your override should call `super()` first, then act on the changed fields. A common implementation might look like: From 940da9eeebeb2eb8b1c662b6b764dfa62e253d1b Mon Sep 17 00:00:00 2001 From: Mark Backman Date: Fri, 6 Mar 2026 10:50:49 -0500 Subject: [PATCH 0840/1060] Add vad_threshold to AssemblyAISTTSettings Wire vad_threshold through Settings, default_settings, the deprecated connection_params path, and _build_ws_url query params. --- src/pipecat/services/assemblyai/stt.py | 6 ++++++ 1 file changed, 6 insertions(+) diff --git a/src/pipecat/services/assemblyai/stt.py b/src/pipecat/services/assemblyai/stt.py index ec4130ea5..3c4803708 100644 --- a/src/pipecat/services/assemblyai/stt.py +++ b/src/pipecat/services/assemblyai/stt.py @@ -99,6 +99,8 @@ class AssemblyAISTTSettings(STTSettings): language_detection: Enable automatic language detection. format_turns: Whether to format transcript turns. speaker_labels: Enable speaker diarization. + vad_threshold: VAD confidence threshold (0.0–1.0) for classifying + audio frames as silence. Only applicable to u3-rt-pro. """ formatted_finals: bool | _NotGiven = field(default_factory=lambda: NOT_GIVEN) @@ -115,6 +117,7 @@ class AssemblyAISTTSettings(STTSettings): language_detection: bool | None | _NotGiven = field(default_factory=lambda: NOT_GIVEN) format_turns: bool | _NotGiven = field(default_factory=lambda: NOT_GIVEN) speaker_labels: bool | None | _NotGiven = field(default_factory=lambda: NOT_GIVEN) + vad_threshold: float | None | _NotGiven = field(default_factory=lambda: NOT_GIVEN) class AssemblyAISTTService(WebsocketSTTService): @@ -199,6 +202,7 @@ class AssemblyAISTTService(WebsocketSTTService): language_detection=None, format_turns=True, speaker_labels=None, + vad_threshold=None, ) # 2. Apply direct init arg overrides (deprecated) @@ -227,6 +231,7 @@ class AssemblyAISTTService(WebsocketSTTService): default_settings.language_detection = connection_params.language_detection default_settings.format_turns = connection_params.format_turns default_settings.speaker_labels = connection_params.speaker_labels + default_settings.vad_threshold = connection_params.vad_threshold # 4. Apply settings delta (canonical API, always wins) if settings is not None: @@ -463,6 +468,7 @@ class AssemblyAISTTService(WebsocketSTTService): "language_detection": s.language_detection, "format_turns": s.format_turns, "speaker_labels": s.speaker_labels, + "vad_threshold": s.vad_threshold, } for k, v in optional_fields.items(): From c3794956efea708948b43bb9eb253f7fdef91c20 Mon Sep 17 00:00:00 2001 From: Mark Backman Date: Fri, 6 Mar 2026 12:47:26 -0500 Subject: [PATCH 0841/1060] Add deprecation version, fix foundational example double system message --- examples/foundational/07f-interruptible-azure-http.py | 2 +- examples/foundational/07f-interruptible-azure.py | 2 +- examples/foundational/07m-interruptible-aws.py | 4 ++-- .../07o-interruptible-assemblyai-turn-detection.py | 2 +- examples/foundational/14d-function-calling-aws-video.py | 4 ++-- examples/foundational/55zzn-update-settings-groq-stt.py | 2 +- src/pipecat/processors/aggregators/llm_context.py | 2 +- src/pipecat/processors/user_idle_processor.py | 2 +- src/pipecat/services/anthropic/llm.py | 6 +++--- src/pipecat/services/assemblyai/stt.py | 2 +- src/pipecat/services/aws/llm.py | 6 +++--- src/pipecat/services/aws/nova_sonic/llm.py | 4 ++-- src/pipecat/services/aws/stt.py | 4 ++-- src/pipecat/services/google/gemini_live/llm.py | 6 +++--- src/pipecat/services/google/gemini_live/llm_vertex.py | 4 ++-- src/pipecat/services/google/llm.py | 6 +++--- src/pipecat/services/google/llm_vertex.py | 4 ++-- src/pipecat/services/google/stt.py | 2 +- src/pipecat/services/openai_realtime_beta/openai.py | 2 +- src/pipecat/services/sarvam/stt.py | 2 +- 20 files changed, 34 insertions(+), 34 deletions(-) diff --git a/examples/foundational/07f-interruptible-azure-http.py b/examples/foundational/07f-interruptible-azure-http.py index 407022f75..ec5068b25 100644 --- a/examples/foundational/07f-interruptible-azure-http.py +++ b/examples/foundational/07f-interruptible-azure-http.py @@ -65,8 +65,8 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): llm = AzureLLMService( api_key=os.getenv("AZURE_CHATGPT_API_KEY"), endpoint=os.getenv("AZURE_CHATGPT_ENDPOINT"), - model=os.getenv("AZURE_CHATGPT_MODEL"), settings=AzureLLMSettings( + model=os.getenv("AZURE_CHATGPT_MODEL"), system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", ), ) diff --git a/examples/foundational/07f-interruptible-azure.py b/examples/foundational/07f-interruptible-azure.py index 7e47e1c3e..d905d59bb 100644 --- a/examples/foundational/07f-interruptible-azure.py +++ b/examples/foundational/07f-interruptible-azure.py @@ -65,8 +65,8 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): llm = AzureLLMService( api_key=os.getenv("AZURE_CHATGPT_API_KEY"), endpoint=os.getenv("AZURE_CHATGPT_ENDPOINT"), - model=os.getenv("AZURE_CHATGPT_MODEL"), settings=AzureLLMSettings( + model=os.getenv("AZURE_CHATGPT_MODEL"), system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", ), ) diff --git a/examples/foundational/07m-interruptible-aws.py b/examples/foundational/07m-interruptible-aws.py index 8b7c0c29e..9cea445c9 100644 --- a/examples/foundational/07m-interruptible-aws.py +++ b/examples/foundational/07m-interruptible-aws.py @@ -63,9 +63,9 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): llm = AWSBedrockLLMService( aws_region="us-west-2", - model="us.anthropic.claude-haiku-4-5-20251001-v1:0", - params=AWSBedrockLLMService.InputParams(temperature=0.8), settings=AWSBedrockLLMSettings( + model="us.anthropic.claude-haiku-4-5-20251001-v1:0", + temperature=0.8, system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", ), ) diff --git a/examples/foundational/07o-interruptible-assemblyai-turn-detection.py b/examples/foundational/07o-interruptible-assemblyai-turn-detection.py index 114c6f263..2c2ca5419 100644 --- a/examples/foundational/07o-interruptible-assemblyai-turn-detection.py +++ b/examples/foundational/07o-interruptible-assemblyai-turn-detection.py @@ -94,7 +94,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): api_key=os.getenv("ASSEMBLYAI_API_KEY"), vad_force_turn_endpoint=False, # Use AssemblyAI's built-in turn detection settings=AssemblyAISTTSettings( - speech_model="u3-rt-pro", + model="u3-rt-pro", # Optional: Tune turn detection timing (defaults shown below) # min_turn_silence=100, # Default # max_turn_silence=1000, # Default diff --git a/examples/foundational/14d-function-calling-aws-video.py b/examples/foundational/14d-function-calling-aws-video.py index 358c6f7f0..75235bc01 100644 --- a/examples/foundational/14d-function-calling-aws-video.py +++ b/examples/foundational/14d-function-calling-aws-video.py @@ -99,7 +99,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): llm = AWSBedrockLLMService( aws_region="us-west-2", settings=AWSBedrockLLMSettings( - model="us.anthropic.claude-3-7-sonnet-20250219-v1:0", + model="us.anthropic.claude-sonnet-4-6", # Note: usually, prefer providing latency="optimized" param. # Here we can't because AWS Bedrock doesn't support it for Claude 3.7, # which we need for image input. @@ -170,7 +170,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): context.add_message( { "role": "user", - "content": f"Please introduce yourself to the user. Use '{client_id}' as the user ID during function calls.", + "content": f"Please introduce yourself to the user briefly; don't mention the camera. Use '{client_id}' as the user ID during function calls.", } ) await task.queue_frames([LLMRunFrame()]) diff --git a/examples/foundational/55zzn-update-settings-groq-stt.py b/examples/foundational/55zzn-update-settings-groq-stt.py index f3f3ffa01..dc7ba6d23 100644 --- a/examples/foundational/55zzn-update-settings-groq-stt.py +++ b/examples/foundational/55zzn-update-settings-groq-stt.py @@ -99,7 +99,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): @transport.event_handler("on_client_connected") async def on_client_connected(transport, client): logger.info(f"Client connected") - context.add_message({"user": "system", "content": "Please introduce yourself to the user."}) + context.add_message({"role": "user", "content": "Please introduce yourself to the user."}) await task.queue_frames([LLMRunFrame()]) await asyncio.sleep(10) diff --git a/src/pipecat/processors/aggregators/llm_context.py b/src/pipecat/processors/aggregators/llm_context.py index 4b0e95aa7..1375b8297 100644 --- a/src/pipecat/processors/aggregators/llm_context.py +++ b/src/pipecat/processors/aggregators/llm_context.py @@ -255,7 +255,7 @@ class LLMContext: this method, which is part of the public API of OpenAILLMContext but doesn't need to be for LLMContext. - .. deprecated:: + .. deprecated:: 0.0.92 Use `get_messages()` instead. Returns: diff --git a/src/pipecat/processors/user_idle_processor.py b/src/pipecat/processors/user_idle_processor.py index 67c41ab13..f7ea48599 100644 --- a/src/pipecat/processors/user_idle_processor.py +++ b/src/pipecat/processors/user_idle_processor.py @@ -27,7 +27,7 @@ from pipecat.processors.frame_processor import FrameDirection, FrameProcessor class UserIdleProcessor(FrameProcessor): """Monitors user inactivity and triggers callbacks after timeout periods. - .. deprecated:: + .. deprecated:: 0.0.100 UserIdleProcessor is deprecated in 0.0.100 and will be removed in a future version. Use LLMUserAggregator with user_idle_timeout parameter instead. diff --git a/src/pipecat/services/anthropic/llm.py b/src/pipecat/services/anthropic/llm.py index 369c2a4ed..49f7f58b4 100644 --- a/src/pipecat/services/anthropic/llm.py +++ b/src/pipecat/services/anthropic/llm.py @@ -170,7 +170,7 @@ class AnthropicLLMService(LLMService): class InputParams(BaseModel): """Input parameters for Anthropic model inference. - .. deprecated:: + .. deprecated:: 0.0.105 Use ``AnthropicLLMSettings`` instead. Pass settings directly via the ``settings`` parameter of :class:`AnthropicLLMService`. @@ -231,12 +231,12 @@ class AnthropicLLMService(LLMService): api_key: Anthropic API key for authentication. model: Model name to use. - .. deprecated:: + .. deprecated:: 0.0.105 Use ``settings=AnthropicLLMSettings(model=...)`` instead. params: Optional model parameters for inference. - .. deprecated:: + .. deprecated:: 0.0.105 Use ``settings=AnthropicLLMSettings(...)`` instead. settings: Runtime-updatable settings for this service. When both diff --git a/src/pipecat/services/assemblyai/stt.py b/src/pipecat/services/assemblyai/stt.py index 3c4803708..a75327300 100644 --- a/src/pipecat/services/assemblyai/stt.py +++ b/src/pipecat/services/assemblyai/stt.py @@ -657,7 +657,7 @@ class AssemblyAISTTService(WebsocketSTTService): await self.start_processing_metrics() await self.broadcast_frame(UserStartedSpeakingFrame) if self._should_interrupt: - await self.push_interruption_task_frame_and_wait() + await self.broadcast_interruption() self._user_speaking = True async def _handle_termination(self, message: TerminationMessage): diff --git a/src/pipecat/services/aws/llm.py b/src/pipecat/services/aws/llm.py index 34a0dd780..5b8c80996 100644 --- a/src/pipecat/services/aws/llm.py +++ b/src/pipecat/services/aws/llm.py @@ -754,7 +754,7 @@ class AWSBedrockLLMService(LLMService): class InputParams(BaseModel): """Input parameters for AWS Bedrock LLM service. - .. deprecated:: + .. deprecated:: 0.0.105 Use ``AWSBedrockLLMSettings`` instead. Pass settings directly via the ``settings`` parameter of :class:`AWSBedrockLLMService`. @@ -795,7 +795,7 @@ class AWSBedrockLLMService(LLMService): Args: model: The AWS Bedrock model identifier to use. - .. deprecated:: + .. deprecated:: 0.0.105 Use ``settings=AWSBedrockLLMSettings(model=...)`` instead. aws_access_key: AWS access key ID. If None, uses default credentials. @@ -804,7 +804,7 @@ class AWSBedrockLLMService(LLMService): aws_region: AWS region for the Bedrock service. params: Model parameters and configuration. - .. deprecated:: + .. deprecated:: 0.0.105 Use ``settings=AWSBedrockLLMSettings(...)`` instead. settings: Runtime-updatable settings for this service. When both diff --git a/src/pipecat/services/aws/nova_sonic/llm.py b/src/pipecat/services/aws/nova_sonic/llm.py index 3948ae1eb..3acc1d0fc 100644 --- a/src/pipecat/services/aws/nova_sonic/llm.py +++ b/src/pipecat/services/aws/nova_sonic/llm.py @@ -280,7 +280,7 @@ class AWSNovaSonicLLMService(LLMService): - Nova Sonic (the older model): "us-east-1", "ap-northeast-1" model: Model identifier. Defaults to "amazon.nova-2-sonic-v1:0". - .. deprecated:: + .. deprecated:: 0.0.105 Use ``settings=AWSNovaSonicLLMSettings(model=...)`` instead. voice_id: Voice ID for speech synthesis. @@ -289,7 +289,7 @@ class AWSNovaSonicLLMService(LLMService): - Nova 2 Sonic (the default model): see https://docs.aws.amazon.com/nova/latest/nova2-userguide/sonic-language-support.html - Nova Sonic (the older model): see https://docs.aws.amazon.com/nova/latest/userguide/available-voices.html. - .. deprecated:: + .. deprecated:: 0.0.105 Use ``settings=AWSNovaSonicLLMSettings(voice=...)`` instead. params: Model parameters for audio configuration and inference. diff --git a/src/pipecat/services/aws/stt.py b/src/pipecat/services/aws/stt.py index f46f5259c..f2ce79c29 100644 --- a/src/pipecat/services/aws/stt.py +++ b/src/pipecat/services/aws/stt.py @@ -99,13 +99,13 @@ class AWSTranscribeSTTService(WebsocketSTTService): # 1. Initialize default_settings with hardcoded defaults default_settings = AWSTranscribeSTTSettings( model=None, - language=self.language_to_service_language(Language.EN) or "en-US", + language=self.language_to_service_language(Language.EN), ) # 2. Apply direct init arg overrides (deprecated) if language is not None: _warn_deprecated_param("language", AWSTranscribeSTTSettings, "language") - default_settings.language = self.language_to_service_language(language) or "en-US" + default_settings.language = self.language_to_service_language(language) # 3. No params to apply diff --git a/src/pipecat/services/google/gemini_live/llm.py b/src/pipecat/services/google/gemini_live/llm.py index 146a0fcc4..9f65f57a1 100644 --- a/src/pipecat/services/google/gemini_live/llm.py +++ b/src/pipecat/services/google/gemini_live/llm.py @@ -552,7 +552,7 @@ class ContextWindowCompressionParams(BaseModel): class InputParams(BaseModel): """Input parameters for Gemini Live generation. - .. deprecated:: + .. deprecated:: 0.0.105 Use ``GeminiLiveLLMSettings`` instead. Parameters: @@ -678,7 +678,7 @@ class GeminiLiveLLMService(LLMService): model: Model identifier to use. - .. deprecated:: + .. deprecated:: 0.0.105 Use ``settings=GeminiLiveLLMSettings(model=...)`` instead. voice_id: TTS voice identifier. Defaults to "Charon". @@ -691,7 +691,7 @@ class GeminiLiveLLMService(LLMService): tools: Tools/functions available to the model. Defaults to None. params: Configuration parameters for the model. - .. deprecated:: + .. deprecated:: 0.0.105 Use ``settings=GeminiLiveLLMSettings(...)`` instead. settings: Gemini Live LLM settings. If provided together with deprecated diff --git a/src/pipecat/services/google/gemini_live/llm_vertex.py b/src/pipecat/services/google/gemini_live/llm_vertex.py index 6264ea285..9edd73e61 100644 --- a/src/pipecat/services/google/gemini_live/llm_vertex.py +++ b/src/pipecat/services/google/gemini_live/llm_vertex.py @@ -88,7 +88,7 @@ class GeminiLiveVertexLLMService(GeminiLiveLLMService): project_id: Google Cloud project ID. model: Model identifier to use. - .. deprecated:: + .. deprecated:: 0.0.105 Use ``settings=GeminiLiveLLMSettings(model=...)`` instead. voice_id: TTS voice identifier. Defaults to "Charon". @@ -102,7 +102,7 @@ class GeminiLiveVertexLLMService(GeminiLiveLLMService): params: Configuration parameters for the model along with Vertex AI location and project ID. - .. deprecated:: + .. deprecated:: 0.0.105 Use ``settings=GeminiLiveLLMSettings(...)`` instead. settings: Gemini Live LLM settings. If provided together with deprecated diff --git a/src/pipecat/services/google/llm.py b/src/pipecat/services/google/llm.py index 980d2d576..d5f025bcd 100644 --- a/src/pipecat/services/google/llm.py +++ b/src/pipecat/services/google/llm.py @@ -754,7 +754,7 @@ class GoogleLLMService(LLMService): class InputParams(BaseModel): """Input parameters for Google AI models. - .. deprecated:: + .. deprecated:: 0.0.105 Use ``settings=GoogleLLMSettings(...)`` instead. Parameters: @@ -797,12 +797,12 @@ class GoogleLLMService(LLMService): api_key: Google AI API key for authentication. model: Model name to use. - .. deprecated:: + .. deprecated:: 0.0.105 Use ``settings=GoogleLLMSettings(model=...)`` instead. params: Optional model parameters for inference. - .. deprecated:: + .. deprecated:: 0.0.105 Use ``settings=GoogleLLMSettings(...)`` instead. settings: Runtime-updatable settings for this service. When both diff --git a/src/pipecat/services/google/llm_vertex.py b/src/pipecat/services/google/llm_vertex.py index 42d96333c..cbad30c48 100644 --- a/src/pipecat/services/google/llm_vertex.py +++ b/src/pipecat/services/google/llm_vertex.py @@ -128,14 +128,14 @@ class GoogleVertexLLMService(GoogleLLMService): credentials_path: Path to the service account JSON file. model: Model identifier (e.g., "gemini-2.5-flash"). - .. deprecated:: + .. deprecated:: 0.0.105 Use ``settings=GoogleLLMSettings(model=...)`` instead. location: GCP region for Vertex AI endpoint (e.g., "us-east4"). project_id: Google Cloud project ID. params: Input parameters for the model. - .. deprecated:: + .. deprecated:: 0.0.105 Use ``settings=GoogleLLMSettings(...)`` instead. settings: Runtime-updatable settings for this service. When both diff --git a/src/pipecat/services/google/stt.py b/src/pipecat/services/google/stt.py index 376e74a6d..6ac0d6440 100644 --- a/src/pipecat/services/google/stt.py +++ b/src/pipecat/services/google/stt.py @@ -653,7 +653,7 @@ class GoogleSTTService(STTService): async def set_languages(self, languages: List[Language]): """Update the service's recognition languages. - .. deprecated:: + .. deprecated:: 0.0.104 Use ``STTUpdateSettingsFrame`` with ``GoogleSTTSettings(languages=...)`` instead. diff --git a/src/pipecat/services/openai_realtime_beta/openai.py b/src/pipecat/services/openai_realtime_beta/openai.py index a3f8e47fc..bd9dc29b0 100644 --- a/src/pipecat/services/openai_realtime_beta/openai.py +++ b/src/pipecat/services/openai_realtime_beta/openai.py @@ -134,7 +134,7 @@ class OpenAIRealtimeBetaLLMService(LLMService): api_key: OpenAI API key for authentication. model: OpenAI model name. - .. deprecated:: + .. deprecated:: 0.0.105 Use ``settings=OpenAIRealtimeBetaLLMSettings(model=...)`` instead. base_url: WebSocket base URL for the realtime API. diff --git a/src/pipecat/services/sarvam/stt.py b/src/pipecat/services/sarvam/stt.py index d8659a6e7..8581a7463 100644 --- a/src/pipecat/services/sarvam/stt.py +++ b/src/pipecat/services/sarvam/stt.py @@ -414,7 +414,7 @@ class SarvamSTTService(STTService): async def set_prompt(self, prompt: Optional[str]): """Set the transcription/translation prompt and reconnect. - .. deprecated:: + .. deprecated:: 0.0.104 Use ``STTUpdateSettingsFrame(SarvamSTTSettings(prompt=...))`` instead. Args: From 6431ad8e2aa626ed7df42c2a322a0bdbacfef704 Mon Sep 17 00:00:00 2001 From: Mark Backman Date: Fri, 6 Mar 2026 13:51:48 -0500 Subject: [PATCH 0842/1060] Fix service settings init ordering and example bugs - Speechmatics: move config build after super().__init__ and settings delta so turn_detection_mode (e.g. ADAPTIVE) takes effect - Google STT: fix example passing bare Language enum instead of list - Google TTS: add missing explicit defaults for all custom settings fields - Soniox: fix accidental tuple wrapping of STT service in example - Speechmatics examples: fix system->user role in kick-off messages - Deepgram Flux: move tag from settings to __init__ (billing metadata) - ElevenLabs STT: default tag_audio_events to None (use API default) - Fal STT: simplify language default handling - Google TTS: rename GoogleStreamTTSSettings to GoogleTTSSettings --- .../foundational/07n-interruptible-google.py | 5 +-- .../foundational/07za-interruptible-soniox.py | 14 ++++----- src/pipecat/services/deepgram/flux/stt.py | 11 ++++--- src/pipecat/services/elevenlabs/stt.py | 15 +++++---- src/pipecat/services/fal/stt.py | 7 ++--- src/pipecat/services/google/tts.py | 31 +++++++++++++------ src/pipecat/services/speechmatics/stt.py | 14 ++++----- 7 files changed, 54 insertions(+), 43 deletions(-) diff --git a/examples/foundational/07n-interruptible-google.py b/examples/foundational/07n-interruptible-google.py index 522d168e1..4f5409085 100644 --- a/examples/foundational/07n-interruptible-google.py +++ b/examples/foundational/07n-interruptible-google.py @@ -55,8 +55,9 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): stt = GoogleSTTService( settings=GoogleSTTSettings( - languages=Language.EN_US, - model="chirp_3", + languages=[Language.EN_US], + # Add model to use a specific model + # model="chirp_3", ), credentials=os.getenv("GOOGLE_TEST_CREDENTIALS"), location="us", diff --git a/examples/foundational/07za-interruptible-soniox.py b/examples/foundational/07za-interruptible-soniox.py index 78e3ac873..71011c5d9 100644 --- a/examples/foundational/07za-interruptible-soniox.py +++ b/examples/foundational/07za-interruptible-soniox.py @@ -51,13 +51,13 @@ transport_params = { async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): logger.info(f"Starting bot") - stt = ( - SonioxSTTService( - api_key=os.getenv("SONIOX_API_KEY"), - settings=SonioxSTTSettings( - language_hints=[Language.EN], - language_hints_strict=True, - ), + stt = SonioxSTTService( + api_key=os.getenv("SONIOX_API_KEY"), + settings=SonioxSTTSettings( + # Add language hints to use a specific language + # Add strict mode to enforce the language hints + language_hints=[Language.EN], + language_hints_strict=True, ), ) diff --git a/src/pipecat/services/deepgram/flux/stt.py b/src/pipecat/services/deepgram/flux/stt.py index 1e7f135b2..678d373b4 100644 --- a/src/pipecat/services/deepgram/flux/stt.py +++ b/src/pipecat/services/deepgram/flux/stt.py @@ -81,7 +81,6 @@ class DeepgramFluxSTTSettings(STTSettings): eot_timeout_ms: Time in ms after speech to finish a turn regardless of EOT confidence (default 5000). keyterm: Keyterms to boost recognition accuracy for specialized terminology. - tag: Tags to label requests for identification during usage reporting. min_confidence: Minimum confidence required to create a TranscriptionFrame. """ @@ -89,7 +88,6 @@ class DeepgramFluxSTTSettings(STTSettings): eot_threshold: float | None | _NotGiven = field(default_factory=lambda: NOT_GIVEN) eot_timeout_ms: int | None | _NotGiven = field(default_factory=lambda: NOT_GIVEN) keyterm: list | _NotGiven = field(default_factory=lambda: NOT_GIVEN) - tag: list | _NotGiven = field(default_factory=lambda: NOT_GIVEN) min_confidence: float | None | _NotGiven = field(default_factory=lambda: NOT_GIVEN) @@ -157,6 +155,7 @@ class DeepgramFluxSTTService(WebsocketSTTService): mip_opt_out: Optional[bool] = None, model: Optional[str] = None, flux_encoding: str = "linear16", + tag: Optional[list] = None, params: Optional[InputParams] = None, should_interrupt: bool = True, settings: Optional[DeepgramFluxSTTSettings] = None, @@ -177,6 +176,7 @@ class DeepgramFluxSTTService(WebsocketSTTService): flux_encoding: Audio encoding format required by Flux API. Must be "linear16". Raw signed little-endian 16-bit PCM encoding. + tag: Tags to label requests for identification during usage reporting. params: InputParams instance containing detailed API configuration options. .. deprecated:: 0.0.105 @@ -224,7 +224,6 @@ class DeepgramFluxSTTService(WebsocketSTTService): eot_threshold=None, eot_timeout_ms=None, keyterm=[], - tag=[], min_confidence=None, ) @@ -241,7 +240,8 @@ class DeepgramFluxSTTService(WebsocketSTTService): default_settings.eot_threshold = params.eot_threshold default_settings.eot_timeout_ms = params.eot_timeout_ms default_settings.keyterm = params.keyterm or [] - default_settings.tag = params.tag or [] + if params.tag and tag is None: + tag = params.tag default_settings.min_confidence = params.min_confidence if params.mip_opt_out is not None: mip_opt_out = params.mip_opt_out @@ -261,6 +261,7 @@ class DeepgramFluxSTTService(WebsocketSTTService): self._should_interrupt = should_interrupt self._encoding = flux_encoding self._mip_opt_out = mip_opt_out + self._tag = tag or [] self._websocket_url = None self._receive_task = None @@ -469,7 +470,7 @@ class DeepgramFluxSTTService(WebsocketSTTService): url_params.append(urlencode({"keyterm": keyterm})) # Add tag parameters (can have multiple) - for tag_value in self._settings.tag: + for tag_value in self._tag: url_params.append(urlencode({"tag": tag_value})) self._websocket_url = f"{self._url}?{'&'.join(url_params)}" diff --git a/src/pipecat/services/elevenlabs/stt.py b/src/pipecat/services/elevenlabs/stt.py index f9899f7f1..6c21a9d20 100644 --- a/src/pipecat/services/elevenlabs/stt.py +++ b/src/pipecat/services/elevenlabs/stt.py @@ -186,7 +186,7 @@ class ElevenLabsSTTSettings(STTSettings): (coughing) in the transcription. """ - tag_audio_events: bool | _NotGiven = field(default_factory=lambda: NOT_GIVEN) + tag_audio_events: bool | None | _NotGiven = field(default_factory=lambda: NOT_GIVEN) @dataclass @@ -277,8 +277,8 @@ class ElevenLabsSTTService(SegmentedSTTService): # 1. Initialize default_settings with hardcoded defaults default_settings = ElevenLabsSTTSettings( model="scribe_v2", - language="eng", - tag_audio_events=True, + language=language_to_elevenlabs_language(Language.EN), + tag_audio_events=None, ) # 2. Apply direct init arg overrides (deprecated) @@ -291,9 +291,7 @@ class ElevenLabsSTTService(SegmentedSTTService): _warn_deprecated_param("params", ElevenLabsSTTSettings) if not settings: if params.language is not None: - default_settings.language = ( - self.language_to_service_language(params.language) or "eng" - ) + default_settings.language = language_to_elevenlabs_language(params.language) default_settings.tag_audio_events = params.tag_audio_events # 4. Apply settings delta (canonical API, always wins) @@ -354,10 +352,11 @@ class ElevenLabsSTTService(SegmentedSTTService): content_type="audio/x-wav", ) - # Add required model_id, language_code, and tag_audio_events + # Add required model_id and language_code data.add_field("model_id", self._settings.model) data.add_field("language_code", self._settings.language) - data.add_field("tag_audio_events", str(self._settings.tag_audio_events).lower()) + if self._settings.tag_audio_events is not None: + data.add_field("tag_audio_events", str(self._settings.tag_audio_events).lower()) async with self._session.post(url, data=data, headers=headers) as response: if response.status != 200: diff --git a/src/pipecat/services/fal/stt.py b/src/pipecat/services/fal/stt.py index 18b8ed85c..54aa750b4 100644 --- a/src/pipecat/services/fal/stt.py +++ b/src/pipecat/services/fal/stt.py @@ -215,7 +215,7 @@ class FalSTTService(SegmentedSTTService): # 1. Initialize default_settings with hardcoded defaults default_settings = FalSTTSettings( model=None, - language=language_to_fal_language(Language.EN) or "en", + language=language_to_fal_language(Language.EN), ) # 2. (no deprecated direct args for this service) @@ -224,9 +224,8 @@ class FalSTTService(SegmentedSTTService): if params is not None: _warn_deprecated_param("params", FalSTTSettings) if not settings: - default_settings.language = ( - language_to_fal_language(params.language) if params.language else "en" - ) + if params.language is not None: + default_settings.language = language_to_fal_language(params.language) if params.task != "transcribe": task = params.task if params.chunk_level != "segment": diff --git a/src/pipecat/services/google/tts.py b/src/pipecat/services/google/tts.py index 071d731b1..a937e2588 100644 --- a/src/pipecat/services/google/tts.py +++ b/src/pipecat/services/google/tts.py @@ -512,7 +512,7 @@ class GoogleHttpTTSSettings(TTSSettings): @dataclass -class GoogleStreamTTSSettings(TTSSettings): +class GoogleTTSSettings(TTSSettings): """Settings for Google streaming TTS service. Parameters: @@ -619,6 +619,13 @@ class GoogleHttpTTSService(TTSService): model=None, voice="en-US-Chirp3-HD-Charon", language="en-US", + pitch=None, + rate=None, + speaking_rate=None, + volume=None, + emphasis=None, + gender=None, + google_style=None, ) # 2. Apply direct init arg overrides (deprecated) @@ -1008,13 +1015,13 @@ class GoogleTTSService(GoogleBaseTTSService): ) """ - _settings: GoogleStreamTTSSettings + _settings: GoogleTTSSettings class InputParams(BaseModel): """Input parameters for Google streaming TTS configuration. .. deprecated:: 0.0.105 - Use ``GoogleStreamTTSSettings`` directly via the ``settings`` parameter instead. + Use ``GoogleTTSSettings`` directly via the ``settings`` parameter instead. Parameters: language: Language for synthesis. Defaults to English. @@ -1034,7 +1041,7 @@ class GoogleTTSService(GoogleBaseTTSService): voice_cloning_key: Optional[str] = None, sample_rate: Optional[int] = None, params: Optional[InputParams] = None, - settings: Optional[GoogleStreamTTSSettings] = None, + settings: Optional[GoogleTTSSettings] = None, **kwargs, ): """Initializes the Google streaming TTS service. @@ -1046,34 +1053,35 @@ class GoogleTTSService(GoogleBaseTTSService): voice_id: Google TTS voice identifier (e.g., "en-US-Chirp3-HD-Charon"). .. deprecated:: 0.0.105 - Use ``settings=GoogleStreamTTSSettings(voice=...)`` instead. + Use ``settings=GoogleTTSSettings(voice=...)`` instead. voice_cloning_key: The voice cloning key for Chirp 3 custom voices. sample_rate: Audio sample rate in Hz. If None, uses default. params: Language configuration parameters. .. deprecated:: 0.0.105 - Use ``settings=GoogleStreamTTSSettings(...)`` instead. + Use ``settings=GoogleTTSSettings(...)`` instead. settings: Runtime-updatable settings. When provided alongside deprecated parameters, ``settings`` values take precedence. **kwargs: Additional arguments passed to parent TTSService. """ # 1. Initialize default_settings with hardcoded defaults - default_settings = GoogleStreamTTSSettings( + default_settings = GoogleTTSSettings( model=None, voice="en-US-Chirp3-HD-Charon", language="en-US", + speaking_rate=None, ) # 2. Apply direct init arg overrides (deprecated) if voice_id is not None: - _warn_deprecated_param("voice_id", GoogleStreamTTSSettings, "voice") + _warn_deprecated_param("voice_id", GoogleTTSSettings, "voice") default_settings.voice = voice_id # 3. Apply params overrides — only if settings not provided if params is not None: - _warn_deprecated_param("params", GoogleStreamTTSSettings) + _warn_deprecated_param("params", GoogleTTSSettings) if not settings: if params.language is not None: default_settings.language = self.language_to_service_language(params.language) @@ -1104,7 +1112,7 @@ class GoogleTTSService(GoogleBaseTTSService): Args: delta: Settings delta. Can include 'speaking_rate' (float). """ - if isinstance(delta, GoogleStreamTTSSettings) and is_given(delta.speaking_rate): + if isinstance(delta, GoogleTTSSettings) and is_given(delta.speaking_rate): rate_value = float(delta.speaking_rate) if not (0.25 <= rate_value <= 2.0): logger.warning( @@ -1308,6 +1316,9 @@ class GeminiTTSService(GoogleBaseTTSService): model="gemini-2.5-flash-tts", voice="Kore", language="en-US", + prompt=None, + multi_speaker=False, + speaker_configs=None, ) # 2. Apply direct init arg overrides (deprecated) diff --git a/src/pipecat/services/speechmatics/stt.py b/src/pipecat/services/speechmatics/stt.py index b3ded9255..2500dd712 100644 --- a/src/pipecat/services/speechmatics/stt.py +++ b/src/pipecat/services/speechmatics/stt.py @@ -90,7 +90,6 @@ class SpeechmaticsSTTSettings(STTSettings): See ``SpeechmaticsSTTService.InputParams`` for detailed descriptions of each field. Parameters: - model: The operating point / model name. domain: Domain for Speechmatics API. turn_detection_mode: Endpoint handling mode. speaker_active_format: Formatter for active speaker ID. @@ -490,12 +489,6 @@ class SpeechmaticsSTTService(STTService): default_settings.prefer_current_speaker = _params.prefer_current_speaker default_settings.extra_params = _params.extra_params - # Build SDK config from settings, then resolve model from operating_point - self._client: VoiceAgentClient | None = None - self._audio_encoding = encoding - self._config: VoiceAgentConfig = self._build_config(default_settings) - default_settings.model = self._config.operating_point.value - # --- 4. Settings delta (canonical API, always wins) --- if settings is not None: default_settings.apply_update(settings) @@ -507,6 +500,13 @@ class SpeechmaticsSTTService(STTService): **kwargs, ) + # Build SDK config from settings, then resolve model from operating_point + self._client: VoiceAgentClient | None = None + self._audio_encoding = encoding + self._config: VoiceAgentConfig = self._build_config(self._settings) + self._settings.model = self._config.operating_point.value + self._sync_model_name_to_metrics() + # Outbound frame queue self._outbound_frames: asyncio.Queue[Frame] = asyncio.Queue() From 7d41049b3582e59de9fe595e81580647e2c538b4 Mon Sep 17 00:00:00 2001 From: Mark Backman Date: Fri, 6 Mar 2026 15:14:54 -0500 Subject: [PATCH 0843/1060] Review feedback, clarify corresponding class in STTSettings docstrings --- src/pipecat/services/assemblyai/stt.py | 2 +- src/pipecat/services/aws/stt.py | 2 +- src/pipecat/services/azure/stt.py | 2 +- src/pipecat/services/cartesia/stt.py | 2 +- src/pipecat/services/deepgram/flux/stt.py | 2 +- src/pipecat/services/deepgram/stt.py | 2 +- src/pipecat/services/elevenlabs/stt.py | 4 ++-- src/pipecat/services/fal/stt.py | 2 +- src/pipecat/services/gladia/stt.py | 2 +- src/pipecat/services/google/stt.py | 2 +- src/pipecat/services/google/tts.py | 11 ++++++++--- src/pipecat/services/gradium/stt.py | 2 +- src/pipecat/services/nvidia/stt.py | 4 ++-- src/pipecat/services/openai/stt.py | 2 +- src/pipecat/services/sarvam/stt.py | 2 +- src/pipecat/services/soniox/stt.py | 2 +- src/pipecat/services/speechmatics/stt.py | 15 +++++++-------- src/pipecat/services/whisper/base_stt.py | 2 +- src/pipecat/services/whisper/stt.py | 4 ++-- 19 files changed, 35 insertions(+), 31 deletions(-) diff --git a/src/pipecat/services/assemblyai/stt.py b/src/pipecat/services/assemblyai/stt.py index a75327300..3d10c970f 100644 --- a/src/pipecat/services/assemblyai/stt.py +++ b/src/pipecat/services/assemblyai/stt.py @@ -81,7 +81,7 @@ def map_language_from_assemblyai(language_code: str) -> Language: @dataclass class AssemblyAISTTSettings(STTSettings): - """Settings for the AssemblyAI STT service. + """Settings for AssemblyAISTTService. Parameters: formatted_finals: Whether to enable transcript formatting. diff --git a/src/pipecat/services/aws/stt.py b/src/pipecat/services/aws/stt.py index f2ce79c29..879fa99ab 100644 --- a/src/pipecat/services/aws/stt.py +++ b/src/pipecat/services/aws/stt.py @@ -47,7 +47,7 @@ except ModuleNotFoundError as e: @dataclass class AWSTranscribeSTTSettings(STTSettings): - """Settings for the AWS Transcribe STT service.""" + """Settings for AWSTranscribeSTTService.""" pass diff --git a/src/pipecat/services/azure/stt.py b/src/pipecat/services/azure/stt.py index 8e6204c5e..c1db76b82 100644 --- a/src/pipecat/services/azure/stt.py +++ b/src/pipecat/services/azure/stt.py @@ -53,7 +53,7 @@ except ModuleNotFoundError as e: @dataclass class AzureSTTSettings(STTSettings): - """Settings for the Azure STT service.""" + """Settings for AzureSTTService.""" pass diff --git a/src/pipecat/services/cartesia/stt.py b/src/pipecat/services/cartesia/stt.py index 67416016e..cdf46d50a 100644 --- a/src/pipecat/services/cartesia/stt.py +++ b/src/pipecat/services/cartesia/stt.py @@ -46,7 +46,7 @@ except ModuleNotFoundError as e: @dataclass class CartesiaSTTSettings(STTSettings): - """Settings for the Cartesia STT service.""" + """Settings for CartesiaSTTService.""" pass diff --git a/src/pipecat/services/deepgram/flux/stt.py b/src/pipecat/services/deepgram/flux/stt.py index 678d373b4..1ed28a749 100644 --- a/src/pipecat/services/deepgram/flux/stt.py +++ b/src/pipecat/services/deepgram/flux/stt.py @@ -71,7 +71,7 @@ class FluxEventType(str, Enum): @dataclass class DeepgramFluxSTTSettings(STTSettings): - """Settings for the Deepgram Flux STT service. + """Settings for DeepgramFluxSTTService. Parameters: eager_eot_threshold: EagerEndOfTurn/TurnResumed threshold. Off by default. diff --git a/src/pipecat/services/deepgram/stt.py b/src/pipecat/services/deepgram/stt.py index d377fe69a..caa6233b3 100644 --- a/src/pipecat/services/deepgram/stt.py +++ b/src/pipecat/services/deepgram/stt.py @@ -177,7 +177,7 @@ class LiveOptions: @dataclass class DeepgramSTTSettings(STTSettings): - """Settings for Deepgram STT services. + """Settings for DeepgramSTTService. ``model`` and ``language`` are inherited from ``STTSettings`` / ``ServiceSettings``. Additional Deepgram connection params may diff --git a/src/pipecat/services/elevenlabs/stt.py b/src/pipecat/services/elevenlabs/stt.py index 6c21a9d20..230e8a368 100644 --- a/src/pipecat/services/elevenlabs/stt.py +++ b/src/pipecat/services/elevenlabs/stt.py @@ -179,7 +179,7 @@ class CommitStrategy(str, Enum): @dataclass class ElevenLabsSTTSettings(STTSettings): - """Settings for the ElevenLabs file-based STT service. + """Settings for ElevenLabsSTTService. Parameters: tag_audio_events: Whether to include audio events like (laughter), @@ -191,7 +191,7 @@ class ElevenLabsSTTSettings(STTSettings): @dataclass class ElevenLabsRealtimeSTTSettings(STTSettings): - """Settings for the ElevenLabs Realtime STT service. + """Settings for ElevenLabsRealtimeSTTService. See ``ElevenLabsRealtimeSTTService.InputParams`` for detailed descriptions. diff --git a/src/pipecat/services/fal/stt.py b/src/pipecat/services/fal/stt.py index 54aa750b4..92e97d381 100644 --- a/src/pipecat/services/fal/stt.py +++ b/src/pipecat/services/fal/stt.py @@ -143,7 +143,7 @@ def language_to_fal_language(language: Language) -> Optional[str]: @dataclass class FalSTTSettings(STTSettings): - """Settings for the Fal Wizper STT service.""" + """Settings for FalSTTService.""" pass diff --git a/src/pipecat/services/gladia/stt.py b/src/pipecat/services/gladia/stt.py index f1eca2dc2..144f37fb2 100644 --- a/src/pipecat/services/gladia/stt.py +++ b/src/pipecat/services/gladia/stt.py @@ -188,7 +188,7 @@ class _InputParamsDescriptor: @dataclass class GladiaSTTSettings(STTSettings): - """Settings for Gladia STT service. + """Settings for GladiaSTTService. Parameters: language_config: Language detection and handling configuration. diff --git a/src/pipecat/services/google/stt.py b/src/pipecat/services/google/stt.py index 6ac0d6440..131d0e9d1 100644 --- a/src/pipecat/services/google/stt.py +++ b/src/pipecat/services/google/stt.py @@ -360,7 +360,7 @@ def language_to_google_stt_language(language: Language) -> Optional[str]: @dataclass class GoogleSTTSettings(STTSettings): - """Settings for Google Cloud Speech-to-Text V2. + """Settings for GoogleSTTService. Parameters: languages: List of ``Language`` enums for recognition diff --git a/src/pipecat/services/google/tts.py b/src/pipecat/services/google/tts.py index a937e2588..984989fa5 100644 --- a/src/pipecat/services/google/tts.py +++ b/src/pipecat/services/google/tts.py @@ -482,7 +482,7 @@ def language_to_gemini_tts_language(language: Language) -> Optional[str]: @dataclass class GoogleHttpTTSSettings(TTSSettings): - """Settings for Google HTTP TTS service. + """Settings for GoogleHttpTTSService. Parameters: pitch: Voice pitch adjustment (e.g., "+2st", "-50%"). @@ -513,7 +513,7 @@ class GoogleHttpTTSSettings(TTSSettings): @dataclass class GoogleTTSSettings(TTSSettings): - """Settings for Google streaming TTS service. + """Settings for GoogleTTSService. Parameters: speaking_rate: The speaking rate, in the range [0.25, 2.0]. @@ -522,9 +522,14 @@ class GoogleTTSSettings(TTSSettings): speaking_rate: float | None | _NotGiven = field(default_factory=lambda: NOT_GIVEN) +#: .. deprecated:: 0.0.105 +#: Use ``GoogleTTSSettings`` instead. +GoogleStreamTTSSettings = GoogleTTSSettings + + @dataclass class GeminiTTSSettings(TTSSettings): - """Settings for Gemini TTS service. + """Settings for GeminiTTSService. Parameters: prompt: Optional style instructions for how to synthesize the content. diff --git a/src/pipecat/services/gradium/stt.py b/src/pipecat/services/gradium/stt.py index e8ab072d0..2a912c355 100644 --- a/src/pipecat/services/gradium/stt.py +++ b/src/pipecat/services/gradium/stt.py @@ -68,7 +68,7 @@ def language_to_gradium_language(language: Language) -> Optional[str]: @dataclass class GradiumSTTSettings(STTSettings): - """Settings for the Gradium STT service.""" + """Settings for GradiumSTTService.""" pass diff --git a/src/pipecat/services/nvidia/stt.py b/src/pipecat/services/nvidia/stt.py index 6823965a9..3d6d2391e 100644 --- a/src/pipecat/services/nvidia/stt.py +++ b/src/pipecat/services/nvidia/stt.py @@ -93,14 +93,14 @@ def language_to_nvidia_riva_language(language: Language) -> Optional[str]: @dataclass class NvidiaSTTSettings(STTSettings): - """Settings for the NVIDIA Riva streaming STT service.""" + """Settings for NvidiaSTTService.""" pass @dataclass class NvidiaSegmentedSTTSettings(STTSettings): - """Settings for the NVIDIA Riva segmented STT service. + """Settings for NvidiaSegmentedSTTService. Parameters: profanity_filter: Whether to filter profanity from results. diff --git a/src/pipecat/services/openai/stt.py b/src/pipecat/services/openai/stt.py index 0e1e4f594..a6d7beb0c 100644 --- a/src/pipecat/services/openai/stt.py +++ b/src/pipecat/services/openai/stt.py @@ -182,7 +182,7 @@ _OPENAI_SAMPLE_RATE = 24000 @dataclass class OpenAIRealtimeSTTSettings(STTSettings): - """Settings for the OpenAI Realtime STT service. + """Settings for OpenAIRealtimeSTTService. Parameters: prompt: Optional prompt text to guide transcription style. diff --git a/src/pipecat/services/sarvam/stt.py b/src/pipecat/services/sarvam/stt.py index 8581a7463..3e4136c41 100644 --- a/src/pipecat/services/sarvam/stt.py +++ b/src/pipecat/services/sarvam/stt.py @@ -139,7 +139,7 @@ MODEL_CONFIGS: Dict[str, ModelConfig] = { @dataclass class SarvamSTTSettings(STTSettings): - """Settings for the Sarvam STT service. + """Settings for SarvamSTTService. Parameters: prompt: Optional prompt to guide transcription/translation style/context. diff --git a/src/pipecat/services/soniox/stt.py b/src/pipecat/services/soniox/stt.py index 483cad062..85277a41b 100644 --- a/src/pipecat/services/soniox/stt.py +++ b/src/pipecat/services/soniox/stt.py @@ -141,7 +141,7 @@ def _prepare_language_hints( @dataclass class SonioxSTTSettings(STTSettings): - """Settings for Soniox STT service. + """Settings for SonioxSTTService. Parameters: language_hints: List of language hints to use for transcription. diff --git a/src/pipecat/services/speechmatics/stt.py b/src/pipecat/services/speechmatics/stt.py index 2500dd712..e3100a2ad 100644 --- a/src/pipecat/services/speechmatics/stt.py +++ b/src/pipecat/services/speechmatics/stt.py @@ -85,7 +85,7 @@ class TurnDetectionMode(str, Enum): @dataclass class SpeechmaticsSTTSettings(STTSettings): - """Settings for Speechmatics STT service. + """Settings for SpeechmaticsSTTService. See ``SpeechmaticsSTTService.InputParams`` for detailed descriptions of each field. @@ -493,6 +493,12 @@ class SpeechmaticsSTTService(STTService): if settings is not None: default_settings.apply_update(settings) + # Build SDK config from settings, set model name before calling super + self._client: VoiceAgentClient | None = None + self._audio_encoding = encoding + self._config: VoiceAgentConfig = self._build_config(default_settings) + default_settings.model = self._config.operating_point.value + super().__init__( sample_rate=sample_rate, ttfs_p99_latency=ttfs_p99_latency, @@ -500,13 +506,6 @@ class SpeechmaticsSTTService(STTService): **kwargs, ) - # Build SDK config from settings, then resolve model from operating_point - self._client: VoiceAgentClient | None = None - self._audio_encoding = encoding - self._config: VoiceAgentConfig = self._build_config(self._settings) - self._settings.model = self._config.operating_point.value - self._sync_model_name_to_metrics() - # Outbound frame queue self._outbound_frames: asyncio.Queue[Frame] = asyncio.Queue() diff --git a/src/pipecat/services/whisper/base_stt.py b/src/pipecat/services/whisper/base_stt.py index 13de0f251..a3bb98548 100644 --- a/src/pipecat/services/whisper/base_stt.py +++ b/src/pipecat/services/whisper/base_stt.py @@ -28,7 +28,7 @@ from pipecat.utils.tracing.service_decorators import traced_stt @dataclass class BaseWhisperSTTSettings(STTSettings): - """Settings for Whisper API-based STT services. + """Settings for BaseWhisperSTTService. Parameters: prompt: Optional text to guide the model's style or continue diff --git a/src/pipecat/services/whisper/stt.py b/src/pipecat/services/whisper/stt.py index af96f92c0..ab5354e2c 100644 --- a/src/pipecat/services/whisper/stt.py +++ b/src/pipecat/services/whisper/stt.py @@ -176,7 +176,7 @@ def language_to_whisper_language(language: Language) -> Optional[str]: @dataclass class WhisperSTTSettings(STTSettings): - """Settings for the local Whisper (Faster Whisper) STT service. + """Settings for WhisperSTTService. Parameters: no_speech_prob: Probability threshold for filtering non-speech segments. @@ -187,7 +187,7 @@ class WhisperSTTSettings(STTSettings): @dataclass class WhisperMLXSTTSettings(STTSettings): - """Settings for the MLX Whisper STT service. + """Settings for WhisperMLXSTTService. Parameters: no_speech_prob: Probability threshold for filtering non-speech segments. From 4ed3480e4b0ef3388c3476f1228979275ffb141d Mon Sep 17 00:00:00 2001 From: Mark Backman Date: Fri, 6 Mar 2026 16:40:38 -0500 Subject: [PATCH 0844/1060] Update TTSSettings docstrings with the corresponding class name(s) --- src/pipecat/services/asyncai/tts.py | 2 +- src/pipecat/services/aws/tts.py | 2 +- src/pipecat/services/azure/tts.py | 2 +- src/pipecat/services/camb/tts.py | 2 +- src/pipecat/services/cartesia/tts.py | 2 +- src/pipecat/services/deepgram/sagemaker/tts.py | 2 +- src/pipecat/services/deepgram/tts.py | 2 +- src/pipecat/services/elevenlabs/tts.py | 4 ++-- src/pipecat/services/fish/tts.py | 2 +- src/pipecat/services/gradium/tts.py | 2 +- src/pipecat/services/groq/tts.py | 2 +- src/pipecat/services/hume/tts.py | 2 +- src/pipecat/services/inworld/tts.py | 2 +- src/pipecat/services/kokoro/tts.py | 2 +- src/pipecat/services/lmnt/tts.py | 2 +- src/pipecat/services/minimax/tts.py | 2 +- src/pipecat/services/neuphonic/tts.py | 2 +- src/pipecat/services/nvidia/tts.py | 2 +- src/pipecat/services/openai/tts.py | 2 +- src/pipecat/services/piper/tts.py | 4 ++-- src/pipecat/services/resembleai/tts.py | 2 +- src/pipecat/services/rime/tts.py | 4 ++-- src/pipecat/services/sarvam/tts.py | 4 ++-- src/pipecat/services/speechmatics/tts.py | 2 +- src/pipecat/services/xtts/tts.py | 2 +- 25 files changed, 29 insertions(+), 29 deletions(-) diff --git a/src/pipecat/services/asyncai/tts.py b/src/pipecat/services/asyncai/tts.py index 56a7d0e82..7bcc1fdb1 100644 --- a/src/pipecat/services/asyncai/tts.py +++ b/src/pipecat/services/asyncai/tts.py @@ -74,7 +74,7 @@ def language_to_async_language(language: Language) -> Optional[str]: @dataclass class AsyncAITTSSettings(TTSSettings): - """Settings for Async AI TTS services.""" + """Settings for AsyncAITTSService and AsyncAIHttpTTSService.""" pass diff --git a/src/pipecat/services/aws/tts.py b/src/pipecat/services/aws/tts.py index 285026bca..12eab245c 100644 --- a/src/pipecat/services/aws/tts.py +++ b/src/pipecat/services/aws/tts.py @@ -123,7 +123,7 @@ def language_to_aws_language(language: Language) -> Optional[str]: @dataclass class AWSPollyTTSSettings(TTSSettings): - """Settings for AWS Polly TTS service. + """Settings for AWSPollyTTSService. Parameters: engine: TTS engine to use ('standard', 'neural', etc.). diff --git a/src/pipecat/services/azure/tts.py b/src/pipecat/services/azure/tts.py index f710482e9..c2884b860 100644 --- a/src/pipecat/services/azure/tts.py +++ b/src/pipecat/services/azure/tts.py @@ -68,7 +68,7 @@ def sample_rate_to_output_format(sample_rate: int) -> SpeechSynthesisOutputForma @dataclass class AzureTTSSettings(TTSSettings): - """Settings for Azure TTS services. + """Settings for AzureTTSService and AzureHttpTTSService. Parameters: emphasis: Emphasis level for speech ("strong", "moderate", "reduced"). diff --git a/src/pipecat/services/camb/tts.py b/src/pipecat/services/camb/tts.py index b30726fda..12b33974e 100644 --- a/src/pipecat/services/camb/tts.py +++ b/src/pipecat/services/camb/tts.py @@ -135,7 +135,7 @@ def _get_aligned_audio(buffer: bytes) -> tuple[bytes, bytes]: @dataclass class CambTTSSettings(TTSSettings): - """Settings for Camb.ai TTS service. + """Settings for CambTTSService. Parameters: user_instructions: Custom instructions for mars-instruct model only. diff --git a/src/pipecat/services/cartesia/tts.py b/src/pipecat/services/cartesia/tts.py index 3f708d06f..e5135aacb 100644 --- a/src/pipecat/services/cartesia/tts.py +++ b/src/pipecat/services/cartesia/tts.py @@ -188,7 +188,7 @@ class CartesiaEmotion(str, Enum): @dataclass class CartesiaTTSSettings(TTSSettings): - """Settings for Cartesia TTS services. + """Settings for CartesiaTTSService and CartesiaHttpTTSService. Parameters: generation_config: Generation configuration for Sonic-3 models. Includes volume, diff --git a/src/pipecat/services/deepgram/sagemaker/tts.py b/src/pipecat/services/deepgram/sagemaker/tts.py index 9e8c30ad7..fa5b1cebd 100644 --- a/src/pipecat/services/deepgram/sagemaker/tts.py +++ b/src/pipecat/services/deepgram/sagemaker/tts.py @@ -40,7 +40,7 @@ from pipecat.utils.tracing.service_decorators import traced_tts @dataclass class DeepgramSageMakerTTSSettings(TTSSettings): - """Settings for Deepgram SageMaker TTS service.""" + """Settings for DeepgramSageMakerTTSService.""" pass diff --git a/src/pipecat/services/deepgram/tts.py b/src/pipecat/services/deepgram/tts.py index 6c8685bee..7749fc370 100644 --- a/src/pipecat/services/deepgram/tts.py +++ b/src/pipecat/services/deepgram/tts.py @@ -45,7 +45,7 @@ except ModuleNotFoundError as e: @dataclass class DeepgramTTSSettings(TTSSettings): - """Settings for Deepgram TTS service.""" + """Settings for DeepgramTTSService and DeepgramHttpTTSService.""" pass diff --git a/src/pipecat/services/elevenlabs/tts.py b/src/pipecat/services/elevenlabs/tts.py index de930d1f2..2d961258b 100644 --- a/src/pipecat/services/elevenlabs/tts.py +++ b/src/pipecat/services/elevenlabs/tts.py @@ -187,7 +187,7 @@ class PronunciationDictionaryLocator(BaseModel): @dataclass class ElevenLabsTTSSettings(TTSSettings): - """Settings for the ElevenLabs WebSocket TTS service. + """Settings for ElevenLabsTTSService. Fields that appear in the WebSocket URL (``voice``, ``model``, ``language``) require a full reconnect when changed. Fields that @@ -225,7 +225,7 @@ class ElevenLabsTTSSettings(TTSSettings): @dataclass class ElevenLabsHttpTTSSettings(TTSSettings): - """Settings for the ElevenLabs HTTP TTS service. + """Settings for ElevenLabsHttpTTSService. Parameters: optimize_streaming_latency: Latency optimization level (0-4). diff --git a/src/pipecat/services/fish/tts.py b/src/pipecat/services/fish/tts.py index 64c3bccd9..fce28c746 100644 --- a/src/pipecat/services/fish/tts.py +++ b/src/pipecat/services/fish/tts.py @@ -49,7 +49,7 @@ FishAudioOutputFormat = Literal["opus", "mp3", "pcm", "wav"] @dataclass class FishAudioTTSSettings(TTSSettings): - """Settings for Fish Audio TTS service. + """Settings for FishAudioTTSService. Parameters: latency: Latency mode ("normal" or "balanced"). Defaults to "normal". diff --git a/src/pipecat/services/gradium/tts.py b/src/pipecat/services/gradium/tts.py index 745a77f56..3dd663185 100644 --- a/src/pipecat/services/gradium/tts.py +++ b/src/pipecat/services/gradium/tts.py @@ -39,7 +39,7 @@ SAMPLE_RATE = 48000 @dataclass class GradiumTTSSettings(TTSSettings): - """Settings for the Gradium TTS service.""" + """Settings for GradiumTTSService.""" pass diff --git a/src/pipecat/services/groq/tts.py b/src/pipecat/services/groq/tts.py index 139816834..4e56312e5 100644 --- a/src/pipecat/services/groq/tts.py +++ b/src/pipecat/services/groq/tts.py @@ -34,7 +34,7 @@ except ModuleNotFoundError as e: @dataclass class GroqTTSSettings(TTSSettings): - """Settings for the Groq TTS service. + """Settings for GroqTTSService. Parameters: speed: Speech speed multiplier. Defaults to 1.0. diff --git a/src/pipecat/services/hume/tts.py b/src/pipecat/services/hume/tts.py index ff5eb7522..135806da7 100644 --- a/src/pipecat/services/hume/tts.py +++ b/src/pipecat/services/hume/tts.py @@ -50,7 +50,7 @@ DEFAULT_HEADERS = { @dataclass class HumeTTSSettings(TTSSettings): - """Settings for Hume TTS service. + """Settings for HumeTTSService. Parameters: description: Natural-language acting directions (up to 100 characters). diff --git a/src/pipecat/services/inworld/tts.py b/src/pipecat/services/inworld/tts.py index d602efb52..8c89b200f 100644 --- a/src/pipecat/services/inworld/tts.py +++ b/src/pipecat/services/inworld/tts.py @@ -68,7 +68,7 @@ from pipecat.utils.tracing.service_decorators import traced_tts @dataclass class InworldTTSSettings(TTSSettings): - """Settings for Inworld TTS services. + """Settings for InworldTTSService and InworldHttpTTSService. Parameters: speaking_rate: Speaking rate for speech synthesis. diff --git a/src/pipecat/services/kokoro/tts.py b/src/pipecat/services/kokoro/tts.py index e69ef7a67..bfc39daed 100644 --- a/src/pipecat/services/kokoro/tts.py +++ b/src/pipecat/services/kokoro/tts.py @@ -89,7 +89,7 @@ def language_to_kokoro_language(language: Language) -> str: @dataclass class KokoroTTSSettings(TTSSettings): - """Settings for the Kokoro TTS service.""" + """Settings for KokoroTTSService.""" pass diff --git a/src/pipecat/services/lmnt/tts.py b/src/pipecat/services/lmnt/tts.py index c8bfcaf55..e9362c4d8 100644 --- a/src/pipecat/services/lmnt/tts.py +++ b/src/pipecat/services/lmnt/tts.py @@ -74,7 +74,7 @@ def language_to_lmnt_language(language: Language) -> Optional[str]: @dataclass class LmntTTSSettings(TTSSettings): - """Settings for LMNT TTS service.""" + """Settings for LmntTTSService.""" pass diff --git a/src/pipecat/services/minimax/tts.py b/src/pipecat/services/minimax/tts.py index 33e0669e1..768e877b9 100644 --- a/src/pipecat/services/minimax/tts.py +++ b/src/pipecat/services/minimax/tts.py @@ -87,7 +87,7 @@ def language_to_minimax_language(language: Language) -> Optional[str]: @dataclass class MiniMaxTTSSettings(TTSSettings): - """Settings for MiniMax TTS service. + """Settings for MiniMaxHttpTTSService. Parameters: stream: Whether to use streaming mode. diff --git a/src/pipecat/services/neuphonic/tts.py b/src/pipecat/services/neuphonic/tts.py index c1916414e..202262355 100644 --- a/src/pipecat/services/neuphonic/tts.py +++ b/src/pipecat/services/neuphonic/tts.py @@ -76,7 +76,7 @@ def language_to_neuphonic_lang_code(language: Language) -> Optional[str]: @dataclass class NeuphonicTTSSettings(TTSSettings): - """Settings for Neuphonic TTS service. + """Settings for NeuphonicTTSService and NeuphonicHttpTTSService. Parameters: speed: Speech speed multiplier. Defaults to 1.0. diff --git a/src/pipecat/services/nvidia/tts.py b/src/pipecat/services/nvidia/tts.py index 7f7638f5f..fb701185c 100644 --- a/src/pipecat/services/nvidia/tts.py +++ b/src/pipecat/services/nvidia/tts.py @@ -44,7 +44,7 @@ except ModuleNotFoundError as e: @dataclass class NvidiaTTSSettings(TTSSettings): - """Settings for NVIDIA Riva TTS service. + """Settings for NvidiaTTSService. Parameters: quality: Audio quality setting (0-100). diff --git a/src/pipecat/services/openai/tts.py b/src/pipecat/services/openai/tts.py index a50129349..71c04c59f 100644 --- a/src/pipecat/services/openai/tts.py +++ b/src/pipecat/services/openai/tts.py @@ -62,7 +62,7 @@ VALID_VOICES: Dict[str, ValidVoice] = { @dataclass class OpenAITTSSettings(TTSSettings): - """Settings for OpenAI TTS service. + """Settings for OpenAITTSService. Parameters: instructions: Instructions to guide voice synthesis behavior. diff --git a/src/pipecat/services/piper/tts.py b/src/pipecat/services/piper/tts.py index f0343947b..337dcd00c 100644 --- a/src/pipecat/services/piper/tts.py +++ b/src/pipecat/services/piper/tts.py @@ -33,7 +33,7 @@ except ModuleNotFoundError as e: @dataclass class PiperTTSSettings(TTSSettings): - """Settings for Piper TTS service.""" + """Settings for PiperTTSService.""" pass @@ -186,7 +186,7 @@ class PiperTTSService(TTSService): # @dataclass class PiperHttpTTSSettings(TTSSettings): - """Settings for Piper HTTP TTS service.""" + """Settings for PiperHttpTTSService.""" pass diff --git a/src/pipecat/services/resembleai/tts.py b/src/pipecat/services/resembleai/tts.py index 45f8fc229..f0a93a182 100644 --- a/src/pipecat/services/resembleai/tts.py +++ b/src/pipecat/services/resembleai/tts.py @@ -38,7 +38,7 @@ except ModuleNotFoundError as e: @dataclass class ResembleAITTSSettings(TTSSettings): - """Settings for Resemble AI TTS service.""" + """Settings for ResembleAITTSService.""" pass diff --git a/src/pipecat/services/rime/tts.py b/src/pipecat/services/rime/tts.py index 27580504b..8a9186c59 100644 --- a/src/pipecat/services/rime/tts.py +++ b/src/pipecat/services/rime/tts.py @@ -73,7 +73,7 @@ def language_to_rime_language(language: Language) -> str: @dataclass class RimeTTSSettings(TTSSettings): - """Settings for Rime WS JSON and HTTP TTS services. + """Settings for RimeTTSService and RimeHttpTTSService. Parameters: segment: Text segmentation mode ("immediate", "bySentence", "never"). @@ -106,7 +106,7 @@ class RimeTTSSettings(TTSSettings): @dataclass class RimeNonJsonTTSSettings(TTSSettings): - """Settings for Rime non-JSON WS TTS service. + """Settings for RimeNonJsonTTSService. Parameters: segment: Text segmentation mode ("immediate", "bySentence", "never"). diff --git a/src/pipecat/services/sarvam/tts.py b/src/pipecat/services/sarvam/tts.py index 6bf38bb24..008c53be1 100644 --- a/src/pipecat/services/sarvam/tts.py +++ b/src/pipecat/services/sarvam/tts.py @@ -247,7 +247,7 @@ def language_to_sarvam_language(language: Language) -> Optional[str]: @dataclass class SarvamHttpTTSSettings(TTSSettings): - """Settings for Sarvam HTTP TTS service. + """Settings for SarvamHttpTTSService. Parameters: enable_preprocessing: Whether to enable text preprocessing. Defaults to False. @@ -273,7 +273,7 @@ class SarvamHttpTTSSettings(TTSSettings): @dataclass class SarvamTTSSettings(SarvamHttpTTSSettings): - """Settings for Sarvam WebSocket TTS service. + """Settings for SarvamTTSService. Extends :class:`SarvamHttpTTSSettings` with WebSocket-specific buffering parameters. diff --git a/src/pipecat/services/speechmatics/tts.py b/src/pipecat/services/speechmatics/tts.py index 22b47f3fc..a93d9c78a 100644 --- a/src/pipecat/services/speechmatics/tts.py +++ b/src/pipecat/services/speechmatics/tts.py @@ -37,7 +37,7 @@ except ModuleNotFoundError as e: @dataclass class SpeechmaticsTTSSettings(TTSSettings): - """Settings for Speechmatics TTS service. + """Settings for SpeechmaticsTTSService. Parameters: max_retries: Maximum number of retries for HTTP requests. diff --git a/src/pipecat/services/xtts/tts.py b/src/pipecat/services/xtts/tts.py index 539ddc88c..42f13887c 100644 --- a/src/pipecat/services/xtts/tts.py +++ b/src/pipecat/services/xtts/tts.py @@ -70,7 +70,7 @@ def language_to_xtts_language(language: Language) -> Optional[str]: @dataclass class XTTSTTSSettings(TTSSettings): - """Settings for XTTS TTS service.""" + """Settings for XTTSTTSService.""" pass From a97a086dbd9675e0811fade9728c38fe1053c9b4 Mon Sep 17 00:00:00 2001 From: Mark Backman Date: Fri, 6 Mar 2026 18:41:54 -0500 Subject: [PATCH 0845/1060] Fix GeminiLiveLLMService init referencing undefined _params variable Replace references to undefined `_params` with `self._settings` for language and VAD config. Add missing `system_instruction` to default settings to satisfy validate_complete(). Remove redundant line that read language from the deprecated `params` arg. --- src/pipecat/services/google/gemini_live/llm.py | 12 +++++++----- 1 file changed, 7 insertions(+), 5 deletions(-) diff --git a/src/pipecat/services/google/gemini_live/llm.py b/src/pipecat/services/google/gemini_live/llm.py index 9f65f57a1..d6fbe7ebe 100644 --- a/src/pipecat/services/google/gemini_live/llm.py +++ b/src/pipecat/services/google/gemini_live/llm.py @@ -607,7 +607,7 @@ class InputParams(BaseModel): @dataclass class GeminiLiveLLMSettings(LLMSettings): - """Settings for Gemini Live LLM services. + """Settings for GeminiLiveLLMService and GeminiLiveVertexLLMService. Parameters: voice: TTS voice identifier (e.g. ``"Charon"``). @@ -717,6 +717,7 @@ class GeminiLiveLLMService(LLMService): # 1. Initialize default_settings with hardcoded defaults default_settings = GeminiLiveLLMSettings( model="models/gemini-2.5-flash-native-audio-preview-12-2025", + system_instruction=system_instruction, voice="Charon", frequency_penalty=None, max_tokens=4096, @@ -785,7 +786,6 @@ class GeminiLiveLLMService(LLMService): self._last_sent_time = 0 self._base_url = base_url - self._language_code = params.language if params is not None else Language.EN_US self._system_instruction_from_init = system_instruction self._tools_from_init = tools @@ -815,11 +815,13 @@ class GeminiLiveLLMService(LLMService): self._sample_rate = 24000 - self._language = _params.language + self._language = self._settings.language self._language_code = ( - language_to_gemini_language(_params.language) if _params.language else "en-US" + language_to_gemini_language(self._settings.language) + if self._settings.language + else "en-US" ) - self._vad_params = _params.vad + self._vad_params = self._settings.vad # Reconnection tracking self._consecutive_failures = 0 From 2c85d2056cc043552e315d5f382ae7e39d32a851 Mon Sep 17 00:00:00 2001 From: Mark Backman Date: Fri, 6 Mar 2026 18:42:22 -0500 Subject: [PATCH 0846/1060] Examples fixes for Gemini Live --- examples/foundational/26-gemini-live.py | 8 +++++--- examples/foundational/26a-gemini-live-transcription.py | 10 ---------- .../foundational/26b-gemini-live-function-calling.py | 6 ++++-- examples/foundational/26c-gemini-live-video.py | 8 +++++--- examples/foundational/26d-gemini-live-text.py | 7 +++++-- examples/foundational/26e-gemini-live-google-search.py | 8 +++++--- examples/foundational/26f-gemini-live-files-api.py | 9 +++++---- .../foundational/26g-gemini-live-groundingMetadata.py | 9 +++++---- .../26h-gemini-live-vertex-function-calling.py | 7 +++++-- examples/foundational/26i-gemini-live-graceful-end.py | 6 ++++-- .../55zm-update-settings-gemini-live-vertex.py | 5 ++++- .../foundational/55zm-update-settings-gemini-live.py | 10 +++++----- 12 files changed, 52 insertions(+), 41 deletions(-) diff --git a/examples/foundational/26-gemini-live.py b/examples/foundational/26-gemini-live.py index 9a705fac1..76287236c 100644 --- a/examples/foundational/26-gemini-live.py +++ b/examples/foundational/26-gemini-live.py @@ -18,7 +18,7 @@ from pipecat.pipeline.task import PipelineParams, PipelineTask from pipecat.processors.audio.vad_processor import VADProcessor from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport -from pipecat.services.google.gemini_live.llm import GeminiLiveLLMService +from pipecat.services.google.gemini_live.llm import GeminiLiveLLMService, GeminiLiveLLMSettings from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams @@ -64,8 +64,10 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): llm = GeminiLiveLLMService( api_key=os.getenv("GOOGLE_API_KEY"), - system_instruction=system_instruction, - voice_id="Puck", # Aoede, Charon, Fenrir, Kore, Puck + settings=GeminiLiveLLMSettings( + system_instruction=system_instruction, + voice="Puck", # Aoede, Charon, Fenrir, Kore, Puck + ), ) vad_processor = VADProcessor(vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.5))) diff --git a/examples/foundational/26a-gemini-live-transcription.py b/examples/foundational/26a-gemini-live-transcription.py index 96a719b10..eda8dde8b 100644 --- a/examples/foundational/26a-gemini-live-transcription.py +++ b/examples/foundational/26a-gemini-live-transcription.py @@ -67,16 +67,6 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): "role": "user", "content": "Say hello. Then ask if I want to hear a joke.", }, - # {"role": "assistant", "content": "Hello! Why don't scientists trust atoms?"}, - # { - # "role": "user", - # "content": [ - # { - # "type": "text", - # "text": "Oh, I know this one: because they make up everything.", - # } - # ], - # }, ], ) user_aggregator, assistant_aggregator = LLMContextAggregatorPair( diff --git a/examples/foundational/26b-gemini-live-function-calling.py b/examples/foundational/26b-gemini-live-function-calling.py index 0ffceecd1..850327924 100644 --- a/examples/foundational/26b-gemini-live-function-calling.py +++ b/examples/foundational/26b-gemini-live-function-calling.py @@ -26,7 +26,7 @@ from pipecat.processors.aggregators.llm_response_universal import ( ) from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport -from pipecat.services.google.gemini_live.llm import GeminiLiveLLMService +from pipecat.services.google.gemini_live.llm import GeminiLiveLLMService, GeminiLiveLLMSettings from pipecat.services.llm_service import FunctionCallParams from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams @@ -120,7 +120,9 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): llm = GeminiLiveLLMService( api_key=os.getenv("GOOGLE_API_KEY"), - system_instruction=system_instruction, + settings=GeminiLiveLLMSettings( + system_instruction=system_instruction, + ), tools=tools, ) diff --git a/examples/foundational/26c-gemini-live-video.py b/examples/foundational/26c-gemini-live-video.py index 4243f50d9..5cde4d214 100644 --- a/examples/foundational/26c-gemini-live-video.py +++ b/examples/foundational/26c-gemini-live-video.py @@ -28,7 +28,7 @@ from pipecat.runner.utils import ( maybe_capture_participant_camera, maybe_capture_participant_screen, ) -from pipecat.services.google.gemini_live.llm import GeminiLiveLLMService +from pipecat.services.google.gemini_live.llm import GeminiLiveLLMService, GeminiLiveLLMSettings from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams @@ -53,8 +53,10 @@ transport_params = { async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): llm = GeminiLiveLLMService( api_key=os.getenv("GOOGLE_API_KEY"), - voice_id="Aoede", # Puck, Charon, Kore, Fenrir, Aoede - # system_instruction="Talk like a pirate." + settings=GeminiLiveLLMSettings( + voice="Aoede", # Puck, Charon, Kore, Fenrir, Aoede + # system_instruction="Talk like a pirate." + ), # inference_on_context_initialization=False, ) diff --git a/examples/foundational/26d-gemini-live-text.py b/examples/foundational/26d-gemini-live-text.py index eebe9874d..dcaf617ac 100644 --- a/examples/foundational/26d-gemini-live-text.py +++ b/examples/foundational/26d-gemini-live-text.py @@ -26,6 +26,7 @@ from pipecat.runner.utils import create_transport from pipecat.services.cartesia.tts import CartesiaTTSService, CartesiaTTSSettings from pipecat.services.google.gemini_live.llm import ( GeminiLiveLLMService, + GeminiLiveLLMSettings, GeminiModalities, InputParams, ) @@ -74,9 +75,11 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): # https://cloud.google.com/vertex-ai/generative-ai/docs/live-api/tools#native-audio). llm = GeminiLiveLLMService( api_key=os.getenv("GOOGLE_API_KEY"), - system_instruction=SYSTEM_INSTRUCTION, + settings=GeminiLiveLLMSettings( + system_instruction=SYSTEM_INSTRUCTION, + modalities=GeminiModalities.TEXT, + ), tools=[{"google_search": {}}, {"code_execution": {}}], - params=InputParams(modalities=GeminiModalities.TEXT), ) # Optionally, you can set the response modalities via a function diff --git a/examples/foundational/26e-gemini-live-google-search.py b/examples/foundational/26e-gemini-live-google-search.py index 64ab1962a..07c3a517d 100644 --- a/examples/foundational/26e-gemini-live-google-search.py +++ b/examples/foundational/26e-gemini-live-google-search.py @@ -23,7 +23,7 @@ from pipecat.processors.aggregators.llm_response_universal import ( ) from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport -from pipecat.services.google.gemini_live.llm import GeminiLiveLLMService +from pipecat.services.google.gemini_live.llm import GeminiLiveLLMService, GeminiLiveLLMSettings from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams @@ -73,8 +73,10 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): # Initialize the Gemini Multimodal Live model llm = GeminiLiveLLMService( api_key=os.getenv("GOOGLE_API_KEY"), - voice_id="Puck", # Aoede, Charon, Fenrir, Kore, Puck - system_instruction=system_instruction, + settings=GeminiLiveLLMSettings( + voice="Puck", # Aoede, Charon, Fenrir, Kore, Puck + system_instruction=system_instruction, + ), tools=tools, ) diff --git a/examples/foundational/26f-gemini-live-files-api.py b/examples/foundational/26f-gemini-live-files-api.py index 4dcf2c10a..a35265e86 100644 --- a/examples/foundational/26f-gemini-live-files-api.py +++ b/examples/foundational/26f-gemini-live-files-api.py @@ -23,7 +23,7 @@ from pipecat.processors.aggregators.llm_response_universal import ( ) from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport -from pipecat.services.google.gemini_live.llm import GeminiLiveLLMService +from pipecat.services.google.gemini_live.llm import GeminiLiveLLMService, GeminiLiveLLMSettings from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams @@ -110,9 +110,10 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): # Initialize Gemini service with File API support llm = GeminiLiveLLMService( api_key=os.getenv("GOOGLE_API_KEY"), - system_instruction=system_instruction, - voice_id="Charon", # Aoede, Charon, Fenrir, Kore, Puck - transcribe_user_audio=True, + settings=GeminiLiveLLMSettings( + system_instruction=system_instruction, + voice="Charon", # Aoede, Charon, Fenrir, Kore, Puck + ), ) # Upload the sample file to Gemini File API diff --git a/examples/foundational/26g-gemini-live-groundingMetadata.py b/examples/foundational/26g-gemini-live-groundingMetadata.py index 2868bfebc..1dede44f2 100644 --- a/examples/foundational/26g-gemini-live-groundingMetadata.py +++ b/examples/foundational/26g-gemini-live-groundingMetadata.py @@ -19,7 +19,7 @@ from pipecat.processors.frame_processor import FrameDirection, FrameProcessor from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport from pipecat.services.google.frames import LLMSearchResponseFrame -from pipecat.services.google.gemini_live.llm import GeminiLiveLLMService +from pipecat.services.google.gemini_live.llm import GeminiLiveLLMService, GeminiLiveLLMSettings from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams @@ -107,9 +107,10 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): llm = GeminiLiveLLMService( api_key=os.getenv("GOOGLE_API_KEY"), - system_instruction=SYSTEM_INSTRUCTION, - voice_id="Charon", # Aoede, Charon, Fenrir, Kore, Puck - transcribe_user_audio=True, + settings=GeminiLiveLLMSettings( + system_instruction=SYSTEM_INSTRUCTION, + voice="Charon", # Aoede, Charon, Fenrir, Kore, Puck + ), tools=tools, ) diff --git a/examples/foundational/26h-gemini-live-vertex-function-calling.py b/examples/foundational/26h-gemini-live-vertex-function-calling.py index eb1db7934..ba27bbc9d 100644 --- a/examples/foundational/26h-gemini-live-vertex-function-calling.py +++ b/examples/foundational/26h-gemini-live-vertex-function-calling.py @@ -26,6 +26,7 @@ from pipecat.processors.aggregators.llm_response_universal import ( ) from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport +from pipecat.services.google.gemini_live.llm import GeminiLiveLLMSettings from pipecat.services.google.gemini_live.llm_vertex import GeminiLiveVertexLLMService from pipecat.services.llm_service import FunctionCallParams from pipecat.transports.base_transport import BaseTransport, TransportParams @@ -117,8 +118,10 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): credentials=os.getenv("GOOGLE_VERTEX_TEST_CREDENTIALS"), project_id=os.getenv("GOOGLE_CLOUD_PROJECT_ID"), location=os.getenv("GOOGLE_CLOUD_LOCATION"), - system_instruction=system_instruction, - voice_id="Puck", # Aoede, Charon, Fenrir, Kore, Puck + settings=GeminiLiveLLMSettings( + system_instruction=system_instruction, + voice="Puck", # Aoede, Charon, Fenrir, Kore, Puck + ), tools=tools, ) diff --git a/examples/foundational/26i-gemini-live-graceful-end.py b/examples/foundational/26i-gemini-live-graceful-end.py index 54c8f0dfd..cfc09e19d 100644 --- a/examples/foundational/26i-gemini-live-graceful-end.py +++ b/examples/foundational/26i-gemini-live-graceful-end.py @@ -26,7 +26,7 @@ from pipecat.processors.aggregators.llm_response_universal import ( from pipecat.processors.frame_processor import FrameDirection from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport -from pipecat.services.google.gemini_live.llm import GeminiLiveLLMService +from pipecat.services.google.gemini_live.llm import GeminiLiveLLMService, GeminiLiveLLMSettings from pipecat.services.llm_service import FunctionCallParams from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams @@ -132,7 +132,9 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): llm = GeminiLiveLLMService( api_key=os.getenv("GOOGLE_API_KEY"), - system_instruction=system_instruction, + settings=GeminiLiveLLMSettings( + system_instruction=system_instruction, + ), tools=tools, ) diff --git a/examples/foundational/55zm-update-settings-gemini-live-vertex.py b/examples/foundational/55zm-update-settings-gemini-live-vertex.py index 7e01fdf52..715834f71 100644 --- a/examples/foundational/55zm-update-settings-gemini-live-vertex.py +++ b/examples/foundational/55zm-update-settings-gemini-live-vertex.py @@ -53,7 +53,9 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): credentials=os.getenv("GOOGLE_VERTEX_TEST_CREDENTIALS"), project_id=os.getenv("GOOGLE_CLOUD_PROJECT_ID"), location=os.getenv("GOOGLE_CLOUD_LOCATION"), - system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + settings=GeminiLiveLLMSettings( + system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + ), ) context = LLMContext() @@ -81,6 +83,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): @transport.event_handler("on_client_connected") async def on_client_connected(transport, client): logger.info(f"Client connected") + context.add_message({"role": "user", "content": "Please introduce yourself to the user."}) await task.queue_frames([LLMRunFrame()]) await asyncio.sleep(10) diff --git a/examples/foundational/55zm-update-settings-gemini-live.py b/examples/foundational/55zm-update-settings-gemini-live.py index 5d8f4e845..172daae7c 100644 --- a/examples/foundational/55zm-update-settings-gemini-live.py +++ b/examples/foundational/55zm-update-settings-gemini-live.py @@ -19,10 +19,7 @@ from pipecat.processors.aggregators.llm_context import LLMContext from pipecat.processors.aggregators.llm_response_universal import LLMContextAggregatorPair from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport -from pipecat.services.google.gemini_live.llm import ( - GeminiLiveLLMService, - GeminiLiveLLMSettings, -) +from pipecat.services.google.gemini_live.llm import GeminiLiveLLMService, GeminiLiveLLMSettings from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams @@ -53,7 +50,9 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): llm = GeminiLiveLLMService( api_key=os.getenv("GOOGLE_API_KEY"), - system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + settings=GeminiLiveLLMSettings( + system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + ), ) context = LLMContext() @@ -81,6 +80,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): @transport.event_handler("on_client_connected") async def on_client_connected(transport, client): logger.info(f"Client connected") + context.add_message({"role": "user", "content": "Please introduce yourself to the user."}) await task.queue_frames([LLMRunFrame()]) await asyncio.sleep(10) From 671e9a68468b763bacef51ac0b2bb2bf8993865c Mon Sep 17 00:00:00 2001 From: Mark Backman Date: Fri, 6 Mar 2026 20:39:00 -0500 Subject: [PATCH 0847/1060] TTS service and example updates --- .../foundational/07i-interruptible-xtts.py | 4 +- .../07n-interruptible-gemini-image.py | 2 +- .../foundational/07n-interruptible-gemini.py | 2 +- .../07n-interruptible-google-http.py | 5 +- .../foundational/07t-interruptible-fish.py | 2 +- .../07z-interruptible-sarvam-http.py | 8 +- examples/foundational/15a-switch-languages.py | 8 +- scripts/evals/run-release-evals.py | 1 + src/pipecat/services/cartesia/tts.py | 3 +- src/pipecat/services/elevenlabs/stt.py | 40 ++++----- src/pipecat/services/elevenlabs/tts.py | 25 +++--- src/pipecat/services/fish/tts.py | 35 +++++--- src/pipecat/services/inworld/tts.py | 89 +++++++------------ src/pipecat/services/lmnt/tts.py | 10 ++- src/pipecat/services/minimax/tts.py | 8 +- src/pipecat/services/neuphonic/tts.py | 8 +- src/pipecat/services/sarvam/tts.py | 21 ++++- src/pipecat/services/xtts/tts.py | 2 +- 18 files changed, 142 insertions(+), 131 deletions(-) diff --git a/examples/foundational/07i-interruptible-xtts.py b/examples/foundational/07i-interruptible-xtts.py index 40845fac0..c5bb61419 100644 --- a/examples/foundational/07i-interruptible-xtts.py +++ b/examples/foundational/07i-interruptible-xtts.py @@ -25,7 +25,7 @@ from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport from pipecat.services.deepgram.stt import DeepgramSTTService from pipecat.services.openai.llm import OpenAILLMService, OpenAILLMSettings -from pipecat.services.xtts.tts import XTTSService, XTTSSettings +from pipecat.services.xtts.tts import XTTSService, XTTSTTSSettings from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams @@ -59,7 +59,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): tts = XTTSService( aiohttp_session=session, - settings=XTTSSettings( + settings=XTTSTTSSettings( voice="Claribel Dervla", ), base_url="http://localhost:8000", diff --git a/examples/foundational/07n-interruptible-gemini-image.py b/examples/foundational/07n-interruptible-gemini-image.py index 96c7cfd47..8369f1de6 100644 --- a/examples/foundational/07n-interruptible-gemini-image.py +++ b/examples/foundational/07n-interruptible-gemini-image.py @@ -72,7 +72,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): stt = GoogleSTTService( credentials=os.getenv("GOOGLE_TEST_CREDENTIALS"), settings=GoogleSTTSettings( - languages=Language.EN_US, + languages=[Language.EN_US], ), ) diff --git a/examples/foundational/07n-interruptible-gemini.py b/examples/foundational/07n-interruptible-gemini.py index a1d58a1cd..92220bce5 100644 --- a/examples/foundational/07n-interruptible-gemini.py +++ b/examples/foundational/07n-interruptible-gemini.py @@ -55,7 +55,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): stt = GoogleSTTService( settings=GoogleSTTSettings( - languages=Language.EN_US, + languages=[Language.EN_US], ), credentials=os.getenv("GOOGLE_TEST_CREDENTIALS"), ) diff --git a/examples/foundational/07n-interruptible-google-http.py b/examples/foundational/07n-interruptible-google-http.py index a607653f7..b137bcd7f 100644 --- a/examples/foundational/07n-interruptible-google-http.py +++ b/examples/foundational/07n-interruptible-google-http.py @@ -55,8 +55,9 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): stt = GoogleSTTService( settings=GoogleSTTSettings( - languages=Language.EN_US, - model="chirp_3", + languages=[Language.EN_US], + # Add model to use a specific model + # model="chirp_3", ), credentials=os.getenv("GOOGLE_TEST_CREDENTIALS"), location="us", diff --git a/examples/foundational/07t-interruptible-fish.py b/examples/foundational/07t-interruptible-fish.py index e7aeb993b..caeab20c6 100644 --- a/examples/foundational/07t-interruptible-fish.py +++ b/examples/foundational/07t-interruptible-fish.py @@ -58,7 +58,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): tts = FishAudioTTSService( api_key=os.getenv("FISH_API_KEY"), settings=FishAudioTTSSettings( - model="4ce7e917cedd4bc2bb2e6ff3a46acaa1", # Barack Obama + voice="4ce7e917cedd4bc2bb2e6ff3a46acaa1", # Barack Obama ), ) diff --git a/examples/foundational/07z-interruptible-sarvam-http.py b/examples/foundational/07z-interruptible-sarvam-http.py index 4a0baa65c..ac6ece100 100644 --- a/examples/foundational/07z-interruptible-sarvam-http.py +++ b/examples/foundational/07z-interruptible-sarvam-http.py @@ -24,7 +24,7 @@ from pipecat.processors.aggregators.llm_response_universal import ( from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport from pipecat.services.openai.llm import OpenAILLMService, OpenAILLMSettings -from pipecat.services.sarvam.stt import SarvamSTTService +from pipecat.services.sarvam.stt import SarvamSTTService, SarvamSTTSettings from pipecat.services.sarvam.tts import SarvamHttpTTSService, SarvamHttpTTSSettings from pipecat.transcriptions.language import Language from pipecat.transports.base_transport import BaseTransport, TransportParams @@ -59,14 +59,16 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): async with aiohttp.ClientSession() as session: stt = SarvamSTTService( api_key=os.getenv("SARVAM_API_KEY"), - model="saarika:v2.5", + settings=SarvamSTTSettings( + model="saarika:v2.5", + ), ) tts = SarvamHttpTTSService( api_key=os.getenv("SARVAM_API_KEY"), aiohttp_session=session, settings=SarvamHttpTTSSettings( - language=Language.EN, + language=Language.EN_IN, ), ) diff --git a/examples/foundational/15a-switch-languages.py b/examples/foundational/15a-switch-languages.py index c514d9a5d..d1bfc2289 100644 --- a/examples/foundational/15a-switch-languages.py +++ b/examples/foundational/15a-switch-languages.py @@ -7,7 +7,6 @@ import os -from deepgram import LiveOptions from dotenv import load_dotenv from loguru import logger @@ -28,7 +27,7 @@ from pipecat.processors.filters.function_filter import FunctionFilter from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport from pipecat.services.cartesia.tts import CartesiaTTSService, CartesiaTTSSettings -from pipecat.services.deepgram.stt import DeepgramSTTService +from pipecat.services.deepgram.stt import DeepgramSTTService, DeepgramSTTSettings from pipecat.services.llm_service import FunctionCallParams from pipecat.services.openai.llm import OpenAILLMService, OpenAILLMSettings from pipecat.transports.base_transport import BaseTransport, TransportParams @@ -102,7 +101,10 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): logger.info(f"Starting bot") stt = DeepgramSTTService( - api_key=os.getenv("DEEPGRAM_API_KEY"), live_options=LiveOptions(language="multi") + api_key=os.getenv("DEEPGRAM_API_KEY"), + settings=DeepgramSTTSettings( + language="multi", + ), ) tts = SwitchLanguage() diff --git a/scripts/evals/run-release-evals.py b/scripts/evals/run-release-evals.py index e473403b8..625f33564 100644 --- a/scripts/evals/run-release-evals.py +++ b/scripts/evals/run-release-evals.py @@ -146,6 +146,7 @@ TESTS_07 = [ ("07zg-interruptible-camb.py", EVAL_SIMPLE_MATH), ("07zi-interruptible-piper.py", EVAL_SIMPLE_MATH), ("07zj-interruptible-kokoro.py", EVAL_SIMPLE_MATH), + ("07zk-interruptible-resembleai.py", EVAL_SIMPLE_MATH), # Needs a local XTTS docker instance running. # ("07i-interruptible-xtts.py", EVAL_SIMPLE_MATH), ] diff --git a/src/pipecat/services/cartesia/tts.py b/src/pipecat/services/cartesia/tts.py index e5135aacb..c71a84f41 100644 --- a/src/pipecat/services/cartesia/tts.py +++ b/src/pipecat/services/cartesia/tts.py @@ -23,7 +23,6 @@ from pipecat.frames.frames import ( Frame, StartFrame, TTSAudioRawFrame, - TTSStartedFrame, TTSStoppedFrame, ) from pipecat.services.settings import NOT_GIVEN, TTSSettings, _NotGiven, _warn_deprecated_param @@ -705,7 +704,7 @@ class CartesiaHttpTTSService(TTSService): voice_id: Optional[str] = None, model: Optional[str] = None, base_url: str = "https://api.cartesia.ai", - cartesia_version: str = "2024-11-13", + cartesia_version: str = "2026-03-01", aiohttp_session: Optional[aiohttp.ClientSession] = None, sample_rate: Optional[int] = None, encoding: str = "pcm_s16le", diff --git a/src/pipecat/services/elevenlabs/stt.py b/src/pipecat/services/elevenlabs/stt.py index 230e8a368..1802bb095 100644 --- a/src/pipecat/services/elevenlabs/stt.py +++ b/src/pipecat/services/elevenlabs/stt.py @@ -200,18 +200,12 @@ class ElevenLabsRealtimeSTTSettings(STTSettings): vad_threshold: VAD sensitivity (0.1-0.9, lower is more sensitive). min_speech_duration_ms: Minimum speech duration for VAD (50-2000ms). min_silence_duration_ms: Minimum silence duration for VAD (50-2000ms). - include_timestamps: Whether to include word-level timestamps in transcripts. - enable_logging: Whether to enable logging on ElevenLabs' side. - include_language_detection: Whether to include language detection in transcripts. """ vad_silence_threshold_secs: float | None | _NotGiven = field(default_factory=lambda: NOT_GIVEN) vad_threshold: float | None | _NotGiven = field(default_factory=lambda: NOT_GIVEN) min_speech_duration_ms: int | None | _NotGiven = field(default_factory=lambda: NOT_GIVEN) min_silence_duration_ms: int | None | _NotGiven = field(default_factory=lambda: NOT_GIVEN) - include_timestamps: bool | _NotGiven = field(default_factory=lambda: NOT_GIVEN) - enable_logging: bool | _NotGiven = field(default_factory=lambda: NOT_GIVEN) - include_language_detection: bool | _NotGiven = field(default_factory=lambda: NOT_GIVEN) class ElevenLabsSTTService(SegmentedSTTService): @@ -496,6 +490,9 @@ class ElevenLabsRealtimeSTTService(WebsocketSTTService): commit_strategy: CommitStrategy = CommitStrategy.MANUAL, model: Optional[str] = None, sample_rate: Optional[int] = None, + include_timestamps: bool = False, + enable_logging: bool = False, + include_language_detection: bool = False, params: Optional[InputParams] = None, settings: Optional[ElevenLabsRealtimeSTTSettings] = None, ttfs_p99_latency: Optional[float] = ELEVENLABS_REALTIME_TTFS_P99, @@ -515,6 +512,9 @@ class ElevenLabsRealtimeSTTService(WebsocketSTTService): Use ``settings=ElevenLabsRealtimeSTTSettings(model=...)`` instead. sample_rate: Audio sample rate in Hz. If not provided, uses the pipeline's rate. + include_timestamps: Whether to include word-level timestamps in transcripts. + enable_logging: Whether to enable logging on ElevenLabs' side. + include_language_detection: Whether to include language detection in transcripts. params: Configuration parameters for the STT service. .. deprecated:: 0.0.105 @@ -534,9 +534,6 @@ class ElevenLabsRealtimeSTTService(WebsocketSTTService): vad_threshold=None, min_speech_duration_ms=None, min_silence_duration_ms=None, - include_timestamps=False, - enable_logging=False, - include_language_detection=False, ) # 2. Apply direct init arg overrides (deprecated) @@ -555,9 +552,9 @@ class ElevenLabsRealtimeSTTService(WebsocketSTTService): default_settings.vad_threshold = params.vad_threshold default_settings.min_speech_duration_ms = params.min_speech_duration_ms default_settings.min_silence_duration_ms = params.min_silence_duration_ms - default_settings.include_timestamps = params.include_timestamps - default_settings.enable_logging = params.enable_logging - default_settings.include_language_detection = params.include_language_detection + include_timestamps = params.include_timestamps + enable_logging = params.enable_logging + include_language_detection = params.include_language_detection # 4. Apply settings delta (canonical API, always wins) if settings is not None: @@ -579,6 +576,9 @@ class ElevenLabsRealtimeSTTService(WebsocketSTTService): # Init-only config (not runtime-updatable). self._commit_strategy = commit_strategy + self._include_timestamps = include_timestamps + self._enable_logging = enable_logging + self._include_language_detection = include_language_detection self._connected_event = asyncio.Event() self._connected_event.set() @@ -762,17 +762,15 @@ class ElevenLabsRealtimeSTTService(WebsocketSTTService): params.append(f"commit_strategy={self._commit_strategy.value}") # Add optional parameters - if self._settings.include_timestamps: - params.append( - f"include_timestamps={str(self._settings.include_timestamps).lower()}" - ) + if self._include_timestamps: + params.append(f"include_timestamps={str(self._include_timestamps).lower()}") - if self._settings.enable_logging: - params.append(f"enable_logging={str(self._settings.enable_logging).lower()}") + if self._enable_logging: + params.append(f"enable_logging={str(self._enable_logging).lower()}") - if self._settings.include_language_detection: + if self._include_language_detection: params.append( - f"include_language_detection={str(self._settings.include_language_detection).lower()}" + f"include_language_detection={str(self._include_language_detection).lower()}" ) # Add VAD parameters if using VAD commit strategy and values are specified @@ -920,7 +918,7 @@ class ElevenLabsRealtimeSTTService(WebsocketSTTService): """ # If timestamps are enabled, skip this message and wait for the # committed_transcript_with_timestamps message which contains all the data - if self._settings.include_timestamps: + if self._include_timestamps: return text = data.get("text", "").strip() diff --git a/src/pipecat/services/elevenlabs/tts.py b/src/pipecat/services/elevenlabs/tts.py index 2d961258b..ae413fd3b 100644 --- a/src/pipecat/services/elevenlabs/tts.py +++ b/src/pipecat/services/elevenlabs/tts.py @@ -358,6 +358,9 @@ class ElevenLabsTTSService(WebsocketTTSService): model: Optional[str] = None, url: str = "wss://api.elevenlabs.io", sample_rate: Optional[int] = None, + auto_mode: bool = True, + enable_ssml_parsing: Optional[bool] = None, + enable_logging: Optional[bool] = None, pronunciation_dictionary_locators: Optional[List[PronunciationDictionaryLocator]] = None, params: Optional[InputParams] = None, settings: Optional[ElevenLabsTTSSettings] = None, @@ -381,6 +384,9 @@ class ElevenLabsTTSService(WebsocketTTSService): url: WebSocket URL for ElevenLabs TTS API. sample_rate: Audio sample rate. If None, uses default. + auto_mode: Whether to enable automatic mode optimization. + enable_ssml_parsing: Whether to parse SSML tags in text. + enable_logging: Whether to enable ElevenLabs server-side logging. pronunciation_dictionary_locators: List of pronunciation dictionary locators to use. params: Additional input parameters for voice customization. @@ -428,11 +434,6 @@ class ElevenLabsTTSService(WebsocketTTSService): apply_text_normalization=None, ) - # Track init-only URL params through the override chain - _auto_mode = True - _enable_ssml_parsing = None - _enable_logging = None - # 2. Apply direct init arg overrides (deprecated) if voice_id is not None: _warn_deprecated_param("voice_id", ElevenLabsTTSSettings, "voice") @@ -459,11 +460,11 @@ class ElevenLabsTTSService(WebsocketTTSService): if params.speed is not None: default_settings.speed = params.speed if params.auto_mode is not None: - _auto_mode = str(params.auto_mode).lower() + auto_mode = params.auto_mode if params.enable_ssml_parsing is not None: - _enable_ssml_parsing = params.enable_ssml_parsing + enable_ssml_parsing = params.enable_ssml_parsing if params.enable_logging is not None: - _enable_logging = params.enable_logging + enable_logging = params.enable_logging if params.apply_text_normalization is not None: default_settings.apply_text_normalization = params.apply_text_normalization if _pronunciation_dictionary_locators is None: @@ -488,9 +489,9 @@ class ElevenLabsTTSService(WebsocketTTSService): self._url = url # Init-only WebSocket URL params (not runtime-updatable). - self._auto_mode = _auto_mode - self._enable_ssml_parsing = _enable_ssml_parsing - self._enable_logging = _enable_logging + self._auto_mode = auto_mode + self._enable_ssml_parsing = enable_ssml_parsing + self._enable_logging = enable_logging self._output_format = "" # initialized in start() self._voice_settings = self._set_voice_settings() @@ -664,7 +665,7 @@ class ElevenLabsTTSService(WebsocketTTSService): voice_id = self._settings.voice model = self._settings.model output_format = self._output_format - url = f"{self._url}/v1/text-to-speech/{voice_id}/multi-stream-input?model_id={model}&output_format={output_format}&auto_mode={self._auto_mode}" + url = f"{self._url}/v1/text-to-speech/{voice_id}/multi-stream-input?model_id={model}&output_format={output_format}&auto_mode={str(self._auto_mode).lower()}" if self._enable_ssml_parsing: url += f"&enable_ssml_parsing={self._enable_ssml_parsing}" diff --git a/src/pipecat/services/fish/tts.py b/src/pipecat/services/fish/tts.py index fce28c746..88e0cc8dd 100644 --- a/src/pipecat/services/fish/tts.py +++ b/src/pipecat/services/fish/tts.py @@ -10,9 +10,8 @@ This module provides integration with Fish Audio's real-time TTS WebSocket API for streaming text-to-speech synthesis with customizable voice parameters. """ -import uuid from dataclasses import dataclass, field -from typing import Any, AsyncGenerator, ClassVar, Dict, Literal, Mapping, Optional, Self +from typing import Any, AsyncGenerator, Literal, Mapping, Optional, Self from loguru import logger from pydantic import BaseModel @@ -25,7 +24,6 @@ from pipecat.frames.frames import ( InterruptionFrame, StartFrame, TTSAudioRawFrame, - TTSStartedFrame, TTSStoppedFrame, ) from pipecat.processors.frame_processor import FrameDirection @@ -52,18 +50,20 @@ class FishAudioTTSSettings(TTSSettings): """Settings for FishAudioTTSService. Parameters: - latency: Latency mode ("normal" or "balanced"). Defaults to "normal". + latency: Latency mode ("normal" or "balanced"). Defaults to "balanced". normalize: Whether to normalize audio output. Defaults to True. + temperature: Controls randomness in speech generation (0.0-1.0). + top_p: Controls diversity via nucleus sampling (0.0-1.0). prosody_speed: Speech speed multiplier (0.5-2.0). Defaults to 1.0. - prosody_volume: Volume adjustment in dB. Defaults to 0. - reference_id: Reference ID of the voice model. + prosody_volume: Volume adjustment in dB (-20 to 20). Defaults to 0. """ latency: str | None | _NotGiven = field(default_factory=lambda: NOT_GIVEN) normalize: bool | None | _NotGiven = field(default_factory=lambda: NOT_GIVEN) + temperature: float | None | _NotGiven = field(default_factory=lambda: NOT_GIVEN) + top_p: float | None | _NotGiven = field(default_factory=lambda: NOT_GIVEN) prosody_speed: float | None | _NotGiven = field(default_factory=lambda: NOT_GIVEN) prosody_volume: int | None | _NotGiven = field(default_factory=lambda: NOT_GIVEN) - reference_id: str | None | _NotGiven = field(default_factory=lambda: NOT_GIVEN) @classmethod def from_mapping(cls, settings: Mapping[str, Any]) -> Self: @@ -174,18 +174,18 @@ class FishAudioTTSService(InterruptibleTTSService): model="s1", voice=None, language=None, - latency="normal", + latency="balanced", normalize=True, + temperature=None, + top_p=None, prosody_speed=1.0, prosody_volume=0, - reference_id=None, ) # 2. Apply direct init arg overrides (deprecated) if reference_id is not None: _warn_deprecated_param("reference_id", FishAudioTTSSettings, "voice") default_settings.voice = reference_id - default_settings.reference_id = reference_id if model_id is not None: _warn_deprecated_param("model_id", FishAudioTTSSettings, "model") default_settings.model = model_id @@ -317,8 +317,12 @@ class FishAudioTTSService(InterruptibleTTSService): "speed": self._settings.prosody_speed, "volume": self._settings.prosody_volume, }, - "reference_id": self._settings.reference_id, + "reference_id": self._settings.voice, } + if self._settings.temperature is not None: + request_settings["temperature"] = self._settings.temperature + if self._settings.top_p is not None: + request_settings["top_p"] = self._settings.top_p start_message = {"event": "start", "request": {"text": "", **request_settings}} await self._websocket.send(ormsgpack.packb(start_message)) logger.debug("Sent start message to Fish Audio") @@ -375,7 +379,14 @@ class FishAudioTTSService(InterruptibleTTSService): frame = TTSAudioRawFrame(audio_data, self.sample_rate, 1) await self.push_frame(frame) await self.stop_ttfb_metrics() - continue + elif event == "finish": + reason = msg.get("reason", "unknown") + if reason == "error": + await self.push_error( + error_msg="Fish Audio server error during synthesis" + ) + else: + logger.debug(f"Fish Audio session finished: {reason}") except Exception as e: await self.push_error(error_msg=f"Unknown error occurred: {e}", exception=e) diff --git a/src/pipecat/services/inworld/tts.py b/src/pipecat/services/inworld/tts.py index 8c89b200f..789efa274 100644 --- a/src/pipecat/services/inworld/tts.py +++ b/src/pipecat/services/inworld/tts.py @@ -73,27 +73,14 @@ class InworldTTSSettings(TTSSettings): Parameters: speaking_rate: Speaking rate for speech synthesis. temperature: Temperature for speech synthesis. - auto_mode: Whether to use auto mode. Recommended when texts are sent - in full sentences/phrases. When enabled, the server controls - flushing of buffered text to achieve minimal latency while - maintaining high quality audio output. If None (default), - automatically set based on aggregate_sentences. - apply_text_normalization: Whether to apply text normalization. - timestamp_transport_strategy: Strategy for timestamp transport ("ASYNC" or "SYNC"). """ speaking_rate: float | _NotGiven = field(default_factory=lambda: NOT_GIVEN) temperature: float | _NotGiven = field(default_factory=lambda: NOT_GIVEN) - auto_mode: bool | _NotGiven = field(default_factory=lambda: NOT_GIVEN) - apply_text_normalization: str | _NotGiven = field(default_factory=lambda: NOT_GIVEN) - timestamp_transport_strategy: str | None | _NotGiven = field(default_factory=lambda: NOT_GIVEN) _aliases: ClassVar[Dict[str, str]] = { "voiceId": "voice", "modelId": "model", - "applyTextNormalization": "apply_text_normalization", - "autoMode": "auto_mode", - "timestampTransportStrategy": "timestamp_transport_strategy", } @classmethod @@ -141,6 +128,7 @@ class InworldHttpTTSService(TTSService): streaming: bool = True, sample_rate: Optional[int] = None, encoding: str = "LINEAR16", + timestamp_transport_strategy: Optional[Literal["ASYNC", "SYNC"]] = "ASYNC", params: Optional[InputParams] = None, settings: Optional[InworldTTSSettings] = None, **kwargs, @@ -163,6 +151,8 @@ class InworldHttpTTSService(TTSService): streaming: Whether to use streaming mode. sample_rate: Audio sample rate in Hz. encoding: Audio encoding format. + timestamp_transport_strategy: Strategy for timestamp transport + ("ASYNC" or "SYNC"). Defaults to "ASYNC". params: Input parameters for Inworld TTS configuration. .. deprecated:: 0.0.105 @@ -179,9 +169,6 @@ class InworldHttpTTSService(TTSService): language=None, speaking_rate=None, temperature=None, - timestamp_transport_strategy="ASYNC", - auto_mode=None, # Not applicable for HTTP TTS - apply_text_normalization=None, # Not applicable for HTTP TTS ) # 2. Apply direct init arg overrides (deprecated) @@ -201,9 +188,7 @@ class InworldHttpTTSService(TTSService): if params.temperature is not None: default_settings.temperature = params.temperature if params.timestamp_transport_strategy is not None: - default_settings.timestamp_transport_strategy = ( - params.timestamp_transport_strategy - ) + timestamp_transport_strategy = params.timestamp_transport_strategy # 4. Apply settings delta (canonical API, always wins) if settings is not None: @@ -230,9 +215,10 @@ class InworldHttpTTSService(TTSService): self._cumulative_time = 0.0 - # Init-only audio format config (not runtime-updatable). + # Init-only config (not runtime-updatable). self._audio_encoding = encoding self._audio_sample_rate = 0 # Set in start() + self._timestamp_transport_strategy = timestamp_transport_strategy def can_generate_metrics(self) -> bool: """Check if this service can generate processing metrics. @@ -251,22 +237,6 @@ class InworldHttpTTSService(TTSService): await super().start(frame) self._audio_sample_rate = self.sample_rate - async def stop(self, frame: EndFrame): - """Stop the Inworld TTS service. - - Args: - frame: The end frame. - """ - await super().stop(frame) - - async def cancel(self, frame: CancelFrame): - """Cancel the Inworld TTS service. - - Args: - frame: The cancel frame. - """ - await super().cancel(frame) - async def push_frame(self, frame: Frame, direction: FrameDirection = FrameDirection.DOWNSTREAM): """Push a frame and handle state changes. @@ -347,8 +317,8 @@ class InworldHttpTTSService(TTSService): # Use WORD timestamps for simplicity and correct spacing/capitalization payload["timestampType"] = self._timestamp_type - if self._settings.timestamp_transport_strategy is not None: - payload["timestampTransportStrategy"] = self._settings.timestamp_transport_strategy + if self._timestamp_transport_strategy is not None: + payload["timestampTransportStrategy"] = self._timestamp_transport_strategy request_id = str(uuid.uuid4()) headers = { @@ -556,6 +526,9 @@ class InworldTTSService(WebsocketTTSService): url: str = "wss://api.inworld.ai/tts/v1/voice:streamBidirectional", sample_rate: Optional[int] = None, encoding: str = "LINEAR16", + auto_mode: Optional[bool] = None, + apply_text_normalization: Optional[str] = None, + timestamp_transport_strategy: Optional[Literal["ASYNC", "SYNC"]] = "ASYNC", params: Optional[InputParams] = None, settings: Optional[InworldTTSSettings] = None, aggregate_sentences: Optional[bool] = None, @@ -580,6 +553,12 @@ class InworldTTSService(WebsocketTTSService): url: URL of the Inworld WebSocket API. sample_rate: Audio sample rate in Hz. encoding: Audio encoding format. + auto_mode: Whether to use auto mode. When enabled, the server + controls flushing of buffered text. If None (default), + automatically set based on ``aggregate_sentences``. + apply_text_normalization: Whether to apply text normalization. + timestamp_transport_strategy: Strategy for timestamp transport + ("ASYNC" or "SYNC"). Defaults to "ASYNC". params: Input parameters for Inworld WebSocket TTS configuration. .. deprecated:: 0.0.105 @@ -596,6 +575,10 @@ class InworldTTSService(WebsocketTTSService): append_trailing_space: Whether to append a trailing space to text before sending to TTS. **kwargs: Additional arguments passed to the parent class. """ + # Derive auto_mode from aggregate_sentences if not explicitly set + if auto_mode is None: + auto_mode = True if aggregate_sentences is None else aggregate_sentences + # 1. Initialize default_settings with hardcoded defaults default_settings = InworldTTSSettings( model="inworld-tts-1.5-max", @@ -603,9 +586,6 @@ class InworldTTSService(WebsocketTTSService): language=None, speaking_rate=None, temperature=None, - apply_text_normalization=None, - timestamp_transport_strategy="ASYNC", - auto_mode=True if aggregate_sentences is None else aggregate_sentences, ) # 2. Apply direct init arg overrides (deprecated) @@ -627,13 +607,11 @@ class InworldTTSService(WebsocketTTSService): if params.temperature is not None: default_settings.temperature = params.temperature if params.apply_text_normalization is not None: - default_settings.apply_text_normalization = params.apply_text_normalization + apply_text_normalization = params.apply_text_normalization if params.timestamp_transport_strategy is not None: - default_settings.timestamp_transport_strategy = ( - params.timestamp_transport_strategy - ) + timestamp_transport_strategy = params.timestamp_transport_strategy if params.auto_mode is not None: - default_settings.auto_mode = params.auto_mode + auto_mode = params.auto_mode _buffer_max_delay_ms = params.max_buffer_delay_ms _buffer_char_threshold = params.buffer_char_threshold @@ -673,9 +651,12 @@ class InworldTTSService(WebsocketTTSService): # Track the end time of the last word in the current generation self._generation_end_time = 0.0 - # Init-only audio format config (not runtime-updatable). + # Init-only config (not runtime-updatable). self._audio_encoding = encoding self._audio_sample_rate = 0 # Set in start() + self._auto_mode = auto_mode + self._apply_text_normalization = apply_text_normalization + self._timestamp_transport_strategy = timestamp_transport_strategy def can_generate_metrics(self) -> bool: """Check if this service can generate processing metrics. @@ -1036,14 +1017,12 @@ class InworldTTSService(WebsocketTTSService): if self._settings.temperature is not None: create_config["temperature"] = self._settings.temperature - if self._settings.apply_text_normalization is not None: - create_config["applyTextNormalization"] = self._settings.apply_text_normalization - if self._settings.auto_mode is not None: - create_config["autoMode"] = self._settings.auto_mode - if self._settings.timestamp_transport_strategy is not None: - create_config["timestampTransportStrategy"] = ( - self._settings.timestamp_transport_strategy - ) + if self._apply_text_normalization is not None: + create_config["applyTextNormalization"] = self._apply_text_normalization + if self._auto_mode is not None: + create_config["autoMode"] = self._auto_mode + if self._timestamp_transport_strategy is not None: + create_config["timestampTransportStrategy"] = self._timestamp_transport_strategy # Set buffer settings for timely audio generation. # Use provided values or defaults that work well for streaming LLM output. diff --git a/src/pipecat/services/lmnt/tts.py b/src/pipecat/services/lmnt/tts.py index e9362c4d8..3cc6778af 100644 --- a/src/pipecat/services/lmnt/tts.py +++ b/src/pipecat/services/lmnt/tts.py @@ -19,7 +19,6 @@ from pipecat.frames.frames import ( Frame, StartFrame, TTSAudioRawFrame, - TTSStartedFrame, TTSStoppedFrame, ) from pipecat.processors.frame_processor import FrameDirection @@ -48,6 +47,7 @@ def language_to_lmnt_language(language: Language) -> Optional[str]: The corresponding LMNT language code, or None if not supported. """ LANGUAGE_MAP = { + Language.AR: "ar", Language.DE: "de", Language.EN: "en", Language.ES: "es", @@ -65,6 +65,7 @@ def language_to_lmnt_language(language: Language) -> Optional[str]: Language.TH: "th", Language.TR: "tr", Language.UK: "uk", + Language.UR: "ur", Language.VI: "vi", Language.ZH: "zh", } @@ -96,6 +97,7 @@ class LmntTTSService(InterruptibleTTSService): voice_id: Optional[str] = None, sample_rate: Optional[int] = None, language: Language = Language.EN, + output_format: str = "pcm_s16le", model: Optional[str] = None, settings: Optional[LmntTTSSettings] = None, **kwargs, @@ -111,6 +113,8 @@ class LmntTTSService(InterruptibleTTSService): sample_rate: Audio sample rate. If None, uses default. language: Language for synthesis. Defaults to English. + output_format: Audio output format. One of "pcm_s16le", "pcm_f32le", + "mp3", "ulaw", "webm". Defaults to "pcm_s16le". model: TTS model to use. .. deprecated:: 0.0.105 @@ -122,7 +126,7 @@ class LmntTTSService(InterruptibleTTSService): """ # 1. Initialize default_settings with hardcoded defaults default_settings = LmntTTSSettings( - model="blizzard", + model="aurora", voice=None, language=self.language_to_service_language(language), ) @@ -151,7 +155,7 @@ class LmntTTSService(InterruptibleTTSService): ) self._api_key = api_key - self._output_format = "raw" + self._output_format = output_format self._receive_task = None def can_generate_metrics(self) -> bool: diff --git a/src/pipecat/services/minimax/tts.py b/src/pipecat/services/minimax/tts.py index 768e877b9..1edd8bf78 100644 --- a/src/pipecat/services/minimax/tts.py +++ b/src/pipecat/services/minimax/tts.py @@ -90,7 +90,6 @@ class MiniMaxTTSSettings(TTSSettings): """Settings for MiniMaxHttpTTSService. Parameters: - stream: Whether to use streaming mode. speed: Speech speed (range: 0.5 to 2.0). volume: Speech volume (range: 0 to 10). pitch: Pitch adjustment (range: -12 to 12). @@ -101,7 +100,6 @@ class MiniMaxTTSSettings(TTSSettings): language_boost: Language boost string for multilingual support. """ - stream: bool | _NotGiven = field(default_factory=lambda: NOT_GIVEN) speed: float | None | _NotGiven = field(default_factory=lambda: NOT_GIVEN) volume: float | None | _NotGiven = field(default_factory=lambda: NOT_GIVEN) pitch: int | None | _NotGiven = field(default_factory=lambda: NOT_GIVEN) @@ -189,6 +187,7 @@ class MiniMaxHttpTTSService(TTSService): voice_id: Optional[str] = None, aiohttp_session: aiohttp.ClientSession, sample_rate: Optional[int] = None, + stream: bool = True, params: Optional[InputParams] = None, settings: Optional[MiniMaxTTSSettings] = None, **kwargs, @@ -217,6 +216,7 @@ class MiniMaxHttpTTSService(TTSService): aiohttp_session: aiohttp.ClientSession for API communication. sample_rate: Output audio sample rate in Hz. If None, uses pipeline default. + stream: Whether to use streaming mode. Defaults to True. params: Additional configuration parameters. .. deprecated:: 0.0.105 @@ -231,7 +231,6 @@ class MiniMaxHttpTTSService(TTSService): model="speech-02-turbo", voice="Calm_Woman", language=None, - stream=True, speed=1.0, volume=1.0, pitch=0, @@ -311,6 +310,7 @@ class MiniMaxHttpTTSService(TTSService): self._api_key = api_key self._group_id = group_id + self._stream = stream self._base_url = f"{base_url}?GroupId={group_id}" self._session = aiohttp_session @@ -392,7 +392,7 @@ class MiniMaxHttpTTSService(TTSService): # Create payload from settings payload = { - "stream": self._settings.stream, + "stream": self._stream, "voice_setting": voice_setting, "audio_setting": audio_setting, "model": self._settings.model, diff --git a/src/pipecat/services/neuphonic/tts.py b/src/pipecat/services/neuphonic/tts.py index 202262355..441d222ea 100644 --- a/src/pipecat/services/neuphonic/tts.py +++ b/src/pipecat/services/neuphonic/tts.py @@ -26,12 +26,10 @@ from pipecat.frames.frames import ( EndFrame, ErrorFrame, Frame, - InterruptionFrame, LLMFullResponseEndFrame, StartFrame, TTSAudioRawFrame, TTSSpeakFrame, - TTSStartedFrame, TTSStoppedFrame, ) from pipecat.processors.frame_processor import FrameDirection @@ -487,7 +485,7 @@ class NeuphonicHttpTTSService(TTSService): default_settings = NeuphonicTTSSettings( model=None, voice=None, - language=self.language_to_service_language(Language.EN) or "en", + language=self.language_to_service_language(Language.EN), speed=1.0, ) @@ -501,9 +499,7 @@ class NeuphonicHttpTTSService(TTSService): _warn_deprecated_param("params", NeuphonicTTSSettings) if not settings: if params.language is not None: - default_settings.language = ( - self.language_to_service_language(params.language) or "en" - ) + default_settings.language = self.language_to_service_language(params.language) if params.speed is not None: default_settings.speed = params.speed diff --git a/src/pipecat/services/sarvam/tts.py b/src/pipecat/services/sarvam/tts.py index 008c53be1..c0a74b198 100644 --- a/src/pipecat/services/sarvam/tts.py +++ b/src/pipecat/services/sarvam/tts.py @@ -53,11 +53,9 @@ from pipecat.frames.frames import ( EndFrame, ErrorFrame, Frame, - InterruptionFrame, LLMFullResponseEndFrame, StartFrame, TTSAudioRawFrame, - TTSStartedFrame, TTSStoppedFrame, ) from pipecat.processors.frame_processor import FrameDirection @@ -230,16 +228,27 @@ def language_to_sarvam_language(language: Language) -> Optional[str]: """ LANGUAGE_MAP = { Language.BN: "bn-IN", # Bengali + Language.BN_IN: "bn-IN", Language.EN: "en-IN", # English (India) + Language.EN_IN: "en-IN", Language.GU: "gu-IN", # Gujarati + Language.GU_IN: "gu-IN", Language.HI: "hi-IN", # Hindi + Language.HI_IN: "hi-IN", Language.KN: "kn-IN", # Kannada + Language.KN_IN: "kn-IN", Language.ML: "ml-IN", # Malayalam + Language.ML_IN: "ml-IN", Language.MR: "mr-IN", # Marathi + Language.MR_IN: "mr-IN", Language.OR: "od-IN", # Odia + Language.OR_IN: "od-IN", Language.PA: "pa-IN", # Punjabi + Language.PA_IN: "pa-IN", Language.TA: "ta-IN", # Tamil + Language.TA_IN: "ta-IN", Language.TE: "te-IN", # Telugu + Language.TE_IN: "te-IN", } return resolve_language(language, LANGUAGE_MAP, use_base_code=False) @@ -481,6 +490,10 @@ class SarvamHttpTTSService(TTSService): if settings is not None: default_settings.apply_update(settings) + # Convert Language enum to service-specific string + if isinstance(default_settings.language, Language): + default_settings.language = self.language_to_service_language(default_settings.language) + # Get model configuration (validates model exists) resolved_model = default_settings.model if resolved_model not in TTS_MODEL_CONFIGS: @@ -900,6 +913,10 @@ class SarvamTTSService(InterruptibleTTSService): if settings is not None: default_settings.apply_update(settings) + # Convert Language enum to service-specific string + if isinstance(default_settings.language, Language): + default_settings.language = self.language_to_service_language(default_settings.language) + # Get model configuration (validates model exists) resolved_model = default_settings.model if resolved_model not in TTS_MODEL_CONFIGS: diff --git a/src/pipecat/services/xtts/tts.py b/src/pipecat/services/xtts/tts.py index 42f13887c..4da8db72a 100644 --- a/src/pipecat/services/xtts/tts.py +++ b/src/pipecat/services/xtts/tts.py @@ -70,7 +70,7 @@ def language_to_xtts_language(language: Language) -> Optional[str]: @dataclass class XTTSTTSSettings(TTSSettings): - """Settings for XTTSTTSService.""" + """Settings for XTTSService.""" pass From 750b87dc24ee1f3ee0e0afd734697b48b70a629e Mon Sep 17 00:00:00 2001 From: Mark Backman Date: Fri, 6 Mar 2026 20:48:26 -0500 Subject: [PATCH 0848/1060] Fix AWS examples, update to sonnet 4.6 --- examples/foundational/07m-interruptible-aws-strands.py | 4 ++-- examples/foundational/07m-interruptible-aws.py | 2 +- examples/foundational/12b-describe-image-aws.py | 7 ++----- examples/foundational/14r-function-calling-aws.py | 2 +- .../foundational/55zp-update-settings-aws-bedrock-llm.py | 2 +- 5 files changed, 7 insertions(+), 10 deletions(-) diff --git a/examples/foundational/07m-interruptible-aws-strands.py b/examples/foundational/07m-interruptible-aws-strands.py index c65709a7b..e5c6f6f01 100644 --- a/examples/foundational/07m-interruptible-aws-strands.py +++ b/examples/foundational/07m-interruptible-aws-strands.py @@ -104,7 +104,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): # Create Strands agent processor try: - agent = build_agent(model_id="us.anthropic.claude-3-5-haiku-20241022-v1:0", max_tokens=8000) + agent = build_agent(model_id="us.anthropic.claude-sonnet-4-6", max_tokens=8000) llm = StrandsAgentsProcessor(agent=agent) logger.info("Successfully created Strands agent for NAB customer service coaching") except Exception as e: @@ -152,7 +152,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): messages=[ { "role": "user", - "content": f"Greet the user and introduce yourself.", + "content": f"Greet the user and introduce yourself. Don't use emojis.", } ], run_llm=True, diff --git a/examples/foundational/07m-interruptible-aws.py b/examples/foundational/07m-interruptible-aws.py index 9cea445c9..8ddec82ef 100644 --- a/examples/foundational/07m-interruptible-aws.py +++ b/examples/foundational/07m-interruptible-aws.py @@ -64,7 +64,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): llm = AWSBedrockLLMService( aws_region="us-west-2", settings=AWSBedrockLLMSettings( - model="us.anthropic.claude-haiku-4-5-20251001-v1:0", + model="us.anthropic.claude-sonnet-4-6", temperature=0.8, system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", ), diff --git a/examples/foundational/12b-describe-image-aws.py b/examples/foundational/12b-describe-image-aws.py index eaa5e3d19..86ec2e66d 100644 --- a/examples/foundational/12b-describe-image-aws.py +++ b/examples/foundational/12b-describe-image-aws.py @@ -61,11 +61,8 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): llm = AWSBedrockLLMService( aws_region="us-west-2", settings=AWSBedrockLLMSettings( - model="us.anthropic.claude-3-7-sonnet-20250219-v1:0", - # Note: usually, prefer providing latency="optimized" param. - # Here we can't because AWS Bedrock doesn't support it for Claude 3.7, - # which we need for image input. - params=AWSBedrockLLMService.InputParams(temperature=0.8), + model="us.anthropic.claude-sonnet-4-6", + temperature=0.8, system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way. You are also able to describe images.", ), ) diff --git a/examples/foundational/14r-function-calling-aws.py b/examples/foundational/14r-function-calling-aws.py index 3693cba6c..2414e06f0 100644 --- a/examples/foundational/14r-function-calling-aws.py +++ b/examples/foundational/14r-function-calling-aws.py @@ -76,7 +76,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): llm = AWSBedrockLLMService( aws_region="us-west-2", settings=AWSBedrockLLMSettings( - model="us.anthropic.claude-haiku-4-5-20251001-v1:0", + model="us.anthropic.claude-sonnet-4-6", temperature=0.8, system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", ), diff --git a/examples/foundational/55zp-update-settings-aws-bedrock-llm.py b/examples/foundational/55zp-update-settings-aws-bedrock-llm.py index 0ae2e0c57..06a131814 100644 --- a/examples/foundational/55zp-update-settings-aws-bedrock-llm.py +++ b/examples/foundational/55zp-update-settings-aws-bedrock-llm.py @@ -62,7 +62,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): llm = AWSBedrockLLMService( aws_region="us-west-2", settings=AWSBedrockLLMSettings( - model="us.anthropic.claude-haiku-4-5-20251001-v1:0", + model="us.anthropic.claude-sonnet-4-6", temperature=0.8, system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", ), From 536f1e178a5b008344ba5723239f331dc3e770fc Mon Sep 17 00:00:00 2001 From: Mark Backman Date: Fri, 6 Mar 2026 21:01:31 -0500 Subject: [PATCH 0849/1060] Fix race condition in Deepgram STT disconnect causing error flood Clear self._connection before sending close stream so run_stt stops sending audio immediately during the WebSocket close handshake. --- src/pipecat/services/deepgram/stt.py | 11 +++++++---- 1 file changed, 7 insertions(+), 4 deletions(-) diff --git a/src/pipecat/services/deepgram/stt.py b/src/pipecat/services/deepgram/stt.py index caa6233b3..17570911a 100644 --- a/src/pipecat/services/deepgram/stt.py +++ b/src/pipecat/services/deepgram/stt.py @@ -594,13 +594,16 @@ class DeepgramSTTService(STTService): return logger.debug("Disconnecting from Deepgram") - # Ask Deepgram to close the stream gracefully before cancelling the task. - if self._connection: - await self._connection.send_close_stream() + # Clear self._connection first to prevent run_stt from sending audio + # during the close handshake, then close gracefully on the saved ref. + connection = self._connection + self._connection = None + + if connection: + await connection.send_close_stream() await self.cancel_task(self._connection_task) self._connection_task = None - self._connection = None async def _connection_handler(self): """Manages the full WebSocket lifecycle inside a single async with block. From 9c42d27f4d2f6ecaa2c1b572940d7ea7edcb6fba Mon Sep 17 00:00:00 2001 From: Mark Backman Date: Fri, 6 Mar 2026 21:07:03 -0500 Subject: [PATCH 0850/1060] Support runtime language updates in Azure STT Extract recognizer setup/teardown into _connect/_disconnect so _update_settings can reconnect when language changes at runtime. --- src/pipecat/services/azure/stt.py | 76 +++++++++++++------------------ 1 file changed, 32 insertions(+), 44 deletions(-) diff --git a/src/pipecat/services/azure/stt.py b/src/pipecat/services/azure/stt.py index c1db76b82..f66cfeb42 100644 --- a/src/pipecat/services/azure/stt.py +++ b/src/pipecat/services/azure/stt.py @@ -159,23 +159,15 @@ class AzureSTTService(STTService): return language_to_azure_language(language) async def _update_settings(self, delta: STTSettings) -> dict[str, Any]: - """Apply a settings delta. - - Settings are stored but not applied to the active recognizer. - """ + """Apply a settings delta and reconnect if language changed.""" changed = await super()._update_settings(delta) - # TODO: someday we could reconnect here to apply updated settings. - # Code might look something like the below: - # if "language" in changed: - # self._speech_config.speech_recognition_language = self._settings.language - # if self._speech_recognizer: - # # Requires refactoring to set up and tear down recognizer, as - # # language is applied at recognizer initialization - # await self._disconnect() - # await self._connect() - - self._warn_unhandled_updated_settings(changed) + if "language" in changed: + self._speech_config.speech_recognition_language = ( + self._settings.language or language_to_azure_language(Language.EN_US) + ) + await self._disconnect() + await self._connect() return changed @@ -202,14 +194,32 @@ class AzureSTTService(STTService): async def start(self, frame: StartFrame): """Start the speech recognition service. - Initializes the Azure speech recognizer with audio stream configuration - and begins continuous speech recognition. - Args: frame: Frame indicating the start of processing. """ await super().start(frame) + await self._connect() + async def stop(self, frame: EndFrame): + """Stop the speech recognition service. + + Args: + frame: Frame indicating the end of processing. + """ + await super().stop(frame) + await self._disconnect() + + async def cancel(self, frame: CancelFrame): + """Cancel the speech recognition service. + + Args: + frame: Frame indicating cancellation. + """ + await super().cancel(frame) + await self._disconnect() + + async def _connect(self): + """Initialize the Azure speech recognizer and begin continuous recognition.""" if self._audio_stream: return @@ -231,37 +241,15 @@ class AzureSTTService(STTService): error_msg=f"Uncaught exception during initialization: {e}", exception=e ) - async def stop(self, frame: EndFrame): - """Stop the speech recognition service. - - Cleanly shuts down the Azure speech recognizer and closes audio streams. - - Args: - frame: Frame indicating the end of processing. - """ - await super().stop(frame) - - if self._speech_recognizer: - self._speech_recognizer.stop_continuous_recognition_async() - - if self._audio_stream: - self._audio_stream.close() - - async def cancel(self, frame: CancelFrame): - """Cancel the speech recognition service. - - Immediately stops recognition and closes resources. - - Args: - frame: Frame indicating cancellation. - """ - await super().cancel(frame) - + async def _disconnect(self): + """Stop recognition and close audio streams.""" if self._speech_recognizer: self._speech_recognizer.stop_continuous_recognition_async() + self._speech_recognizer = None if self._audio_stream: self._audio_stream.close() + self._audio_stream = None @traced_stt async def _handle_transcription( From ec93cd1d510fd4f2f377661f3c07e6a8dc2909ef Mon Sep 17 00:00:00 2001 From: Mark Backman Date: Fri, 6 Mar 2026 21:52:45 -0500 Subject: [PATCH 0851/1060] Fix settings update handling in additional STT services --- ...-update-settings-deepgram-sagemaker-stt.py | 3 +- .../55a-update-settings-deepgram-stt.py | 3 +- .../55zr-update-settings-gradium-stt.py | 2 +- src/pipecat/services/aws/stt.py | 18 +++--------- src/pipecat/services/gradium/stt.py | 29 ++++++++++--------- src/pipecat/services/inworld/tts.py | 2 +- src/pipecat/services/sarvam/stt.py | 22 ++++++++------ src/pipecat/services/soniox/stt.py | 16 +++------- 8 files changed, 40 insertions(+), 55 deletions(-) diff --git a/examples/foundational/55a-update-settings-deepgram-sagemaker-stt.py b/examples/foundational/55a-update-settings-deepgram-sagemaker-stt.py index 21604829f..30ce506a7 100644 --- a/examples/foundational/55a-update-settings-deepgram-sagemaker-stt.py +++ b/examples/foundational/55a-update-settings-deepgram-sagemaker-stt.py @@ -7,7 +7,6 @@ import asyncio import os -from deepgram import LiveOptions from dotenv import load_dotenv from loguru import logger @@ -114,7 +113,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): STTUpdateSettingsFrame( delta=DeepgramSageMakerSTTSettings( language=Language.ES, - live_options=LiveOptions(punctuate=False), + punctuate=False, ) ) ) diff --git a/examples/foundational/55a-update-settings-deepgram-stt.py b/examples/foundational/55a-update-settings-deepgram-stt.py index c7442549c..100887f80 100644 --- a/examples/foundational/55a-update-settings-deepgram-stt.py +++ b/examples/foundational/55a-update-settings-deepgram-stt.py @@ -7,7 +7,6 @@ import asyncio import os -from deepgram import LiveOptions from dotenv import load_dotenv from loguru import logger @@ -108,7 +107,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): STTUpdateSettingsFrame( delta=DeepgramSTTSettings( language=Language.ES, - live_options=LiveOptions(punctuate=False), + punctuate=False, ) ) ) diff --git a/examples/foundational/55zr-update-settings-gradium-stt.py b/examples/foundational/55zr-update-settings-gradium-stt.py index 7b40638a5..9e76d3bec 100644 --- a/examples/foundational/55zr-update-settings-gradium-stt.py +++ b/examples/foundational/55zr-update-settings-gradium-stt.py @@ -104,7 +104,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): await asyncio.sleep(10) logger.info("Updating Gradium STT settings: delay_in_frames=5") - await task.queue_frame(STTUpdateSettingsFrame(delta=GradiumSTTSettings(delay_in_frames=5))) + await task.queue_frame(STTUpdateSettingsFrame(delta=GradiumSTTSettings(delay_in_frames=16))) @transport.event_handler("on_client_disconnected") async def on_client_disconnected(transport, client): diff --git a/src/pipecat/services/aws/stt.py b/src/pipecat/services/aws/stt.py index 879fa99ab..ca3b0140c 100644 --- a/src/pipecat/services/aws/stt.py +++ b/src/pipecat/services/aws/stt.py @@ -158,22 +158,12 @@ class AWSTranscribeSTTService(WebsocketSTTService): return encoding_map.get(encoding, encoding) async def _update_settings(self, delta: STTSettings) -> dict[str, Any]: - """Apply a settings delta. - - Settings are stored but not applied to the active connection. - """ + """Apply a settings delta and reconnect if anything changed.""" changed = await super()._update_settings(delta) - if not changed: - return changed - - # TODO: someday we could reconnect here to apply updated settings. - # Code might look something like the below: - # if changed and self._websocket: - # await self._disconnect() - # await self._connect() - - self._warn_unhandled_updated_settings(changed) + if changed: + await self._disconnect() + await self._connect() return changed diff --git a/src/pipecat/services/gradium/stt.py b/src/pipecat/services/gradium/stt.py index 2a912c355..05a6bb8b5 100644 --- a/src/pipecat/services/gradium/stt.py +++ b/src/pipecat/services/gradium/stt.py @@ -68,9 +68,16 @@ def language_to_gradium_language(language: Language) -> Optional[str]: @dataclass class GradiumSTTSettings(STTSettings): - """Settings for GradiumSTTService.""" + """Settings for GradiumSTTService. - pass + Parameters: + delay_in_frames: Delay in audio frames (80ms each) before text is + generated. Higher delays allow more context but increase latency. + Allowed values: 7, 8, 10, 12, 14, 16, 20, 24, 36, 48. + Default is 10 (800ms). Lower values like 7-8 give faster response. + """ + + delay_in_frames: Optional[int] = None class GradiumSTTService(WebsocketSTTService): @@ -107,7 +114,6 @@ class GradiumSTTService(WebsocketSTTService): *, api_key: str, api_endpoint_base_url: str = "wss://eu.api.gradium.ai/api/speech/asr", - delay_in_frames: Optional[int] = None, params: Optional[InputParams] = None, json_config: Optional[str] = None, settings: Optional[GradiumSTTSettings] = None, @@ -119,9 +125,6 @@ class GradiumSTTService(WebsocketSTTService): Args: api_key: Gradium API key for authentication. api_endpoint_base_url: WebSocket endpoint URL. Defaults to Gradium's streaming endpoint. - delay_in_frames: Delay in audio frames (80ms each) before text is - generated. Higher delays allow more context but increase latency. - Allowed values: 7, 8, 10, 12, 14, 16, 20, 24, 36, 48. params: Configuration parameters for language and delay settings. .. deprecated:: 0.0.105 @@ -151,19 +154,18 @@ class GradiumSTTService(WebsocketSTTService): default_settings = GradiumSTTSettings( model=None, language=None, + delay_in_frames=None, ) - # 2. (no deprecated direct args for this service) - - # 3. Apply params overrides — only if settings not provided + # 2. Apply params overrides — only if settings not provided if params is not None: _warn_deprecated_param("params", GradiumSTTSettings) if not settings: default_settings.language = params.language if params.delay_in_frames is not None: - delay_in_frames = params.delay_in_frames + default_settings.delay_in_frames = params.delay_in_frames - # 4. Apply settings delta (canonical API, always wins) + # 3. Apply settings delta (canonical API, always wins) if settings is not None: default_settings.apply_update(settings) @@ -178,7 +180,6 @@ class GradiumSTTService(WebsocketSTTService): self._api_endpoint_base_url = api_endpoint_base_url self._websocket = None self._json_config = json_config - self._config_delay_in_frames = delay_in_frames self._receive_task = None @@ -358,8 +359,8 @@ class GradiumSTTService(WebsocketSTTService): gradium_language = language_to_gradium_language(self._settings.language) if gradium_language: json_config["language"] = gradium_language - if self._config_delay_in_frames: - json_config["delay_in_frames"] = self._config_delay_in_frames + if self._settings.delay_in_frames: + json_config["delay_in_frames"] = self._settings.delay_in_frames if json_config: setup_msg["json_config"] = json_config await self._websocket.send(json.dumps(setup_msg)) diff --git a/src/pipecat/services/inworld/tts.py b/src/pipecat/services/inworld/tts.py index 789efa274..17a0e8040 100644 --- a/src/pipecat/services/inworld/tts.py +++ b/src/pipecat/services/inworld/tts.py @@ -907,7 +907,7 @@ class InworldTTSService(WebsocketTTSService): for k in ["contextCreated", "audioChunk", "flushCompleted", "contextClosed"] if k in result ] - logger.debug(f"{self}: Received message types={msg_types}, ctx_id={ctx_id}") + logger.trace(f"{self}: Received message types={msg_types}, ctx_id={ctx_id}") # Check for errors status = result.get("status", {}) diff --git a/src/pipecat/services/sarvam/stt.py b/src/pipecat/services/sarvam/stt.py index 3e4136c41..cd6d19ac0 100644 --- a/src/pipecat/services/sarvam/stt.py +++ b/src/pipecat/services/sarvam/stt.py @@ -400,12 +400,13 @@ class SarvamSTTService(STTService): changed = await super()._update_settings(delta) - # Prompt is a WebSocket connect-time parameter; reconnect to apply. - if "prompt" in changed: + # Language and prompt are WebSocket connect-time parameters; reconnect to apply. + reconnect_fields = {"language", "prompt"} + if changed.keys() & reconnect_fields: await self._disconnect() await self._connect() - unhandled = {k: v for k, v in changed.items() if k != "prompt"} + unhandled = {k: v for k, v in changed.items() if k not in reconnect_fields} if unhandled: self._warn_unhandled_updated_settings(unhandled) @@ -483,7 +484,6 @@ class SarvamSTTService(STTService): Frame: None (transcription results come via WebSocket callbacks). """ if not self._socket_client: - logger.warning("WebSocket not connected, cannot process audio") yield None return @@ -636,18 +636,22 @@ class SarvamSTTService(STTService): await self.cancel_task(self._receive_task) self._receive_task = None - if self._websocket_context and self._socket_client: + # Clear references first to prevent run_stt from sending audio + # during the close handshake. + socket_client = self._socket_client + websocket_context = self._websocket_context + self._socket_client = None + self._websocket_context = None + + if websocket_context and socket_client: try: - # Exit the async context manager - await self._websocket_context.__aexit__(None, None, None) + await websocket_context.__aexit__(None, None, None) except Exception as e: await self.push_error( error_msg=f"Error closing WebSocket connection: {e}", exception=e ) finally: logger.debug("Disconnected from Sarvam WebSocket") - self._socket_client = None - self._websocket_context = None async def _receive_task_handler(self): """Handle incoming messages from Sarvam WebSocket. diff --git a/src/pipecat/services/soniox/stt.py b/src/pipecat/services/soniox/stt.py index 85277a41b..613e35a28 100644 --- a/src/pipecat/services/soniox/stt.py +++ b/src/pipecat/services/soniox/stt.py @@ -297,9 +297,7 @@ class SonioxSTTService(WebsocketSTTService): await self._connect() async def _update_settings(self, delta: SonioxSTTSettings) -> dict[str, Any]: - """Apply settings delta. - - Settings are stored but not applied to the active connection. + """Apply settings delta and reconnect if anything changed. Args: delta: A settings delta. @@ -309,15 +307,9 @@ class SonioxSTTService(WebsocketSTTService): """ changed = await super()._update_settings(delta) - if not changed: - return changed - - # TODO: someday we could reconnect here to apply updated settings. - # Code might look something like the below: - # await self._disconnect() - # await self._connect() - - self._warn_unhandled_updated_settings(changed) + if changed: + await self._disconnect() + await self._connect() return changed From 256c8f87b4b107482a1685fa7126f3e999bd62aa Mon Sep 17 00:00:00 2001 From: Paul Kompfner Date: Fri, 6 Mar 2026 17:01:29 -0500 Subject: [PATCH 0852/1060] Add missing step 3 comment to LLM service init methods Adds the explicit "no params object" step 3 comment to all LLM services that skip from step 2 to step 4 in their settings initialization sequence, matching the pattern established in services that do have a params object. --- src/pipecat/services/azure/llm.py | 2 ++ src/pipecat/services/cerebras/llm.py | 2 ++ src/pipecat/services/deepseek/llm.py | 2 ++ src/pipecat/services/fireworks/llm.py | 2 ++ src/pipecat/services/google/llm_openai.py | 2 ++ src/pipecat/services/grok/llm.py | 2 ++ src/pipecat/services/groq/llm.py | 2 ++ src/pipecat/services/mistral/llm.py | 2 ++ src/pipecat/services/nvidia/llm.py | 2 ++ src/pipecat/services/ollama/llm.py | 2 ++ src/pipecat/services/openpipe/llm.py | 2 ++ src/pipecat/services/openrouter/llm.py | 2 ++ src/pipecat/services/perplexity/llm.py | 2 ++ src/pipecat/services/qwen/llm.py | 2 ++ src/pipecat/services/sambanova/llm.py | 2 ++ src/pipecat/services/together/llm.py | 2 ++ 16 files changed, 32 insertions(+) diff --git a/src/pipecat/services/azure/llm.py b/src/pipecat/services/azure/llm.py index 5f1ce2698..ce98d151a 100644 --- a/src/pipecat/services/azure/llm.py +++ b/src/pipecat/services/azure/llm.py @@ -64,6 +64,8 @@ class AzureLLMService(OpenAILLMService): _warn_deprecated_param("model", AzureLLMSettings, "model") default_settings.model = model + # 3. (No step 3, as there's no params object to apply) + # 4. Apply settings delta (canonical API, always wins) if settings is not None: default_settings.apply_update(settings) diff --git a/src/pipecat/services/cerebras/llm.py b/src/pipecat/services/cerebras/llm.py index c3b56ff29..0fe19bd75 100644 --- a/src/pipecat/services/cerebras/llm.py +++ b/src/pipecat/services/cerebras/llm.py @@ -64,6 +64,8 @@ class CerebrasLLMService(OpenAILLMService): _warn_deprecated_param("model", CerebrasLLMSettings, "model") default_settings.model = model + # 3. (No step 3, as there's no params object to apply) + # 4. Apply settings delta (canonical API, always wins) if settings is not None: default_settings.apply_update(settings) diff --git a/src/pipecat/services/deepseek/llm.py b/src/pipecat/services/deepseek/llm.py index 684e971ca..b91a2f443 100644 --- a/src/pipecat/services/deepseek/llm.py +++ b/src/pipecat/services/deepseek/llm.py @@ -64,6 +64,8 @@ class DeepSeekLLMService(OpenAILLMService): _warn_deprecated_param("model", DeepSeekLLMSettings, "model") default_settings.model = model + # 3. (No step 3, as there's no params object to apply) + # 4. Apply settings delta (canonical API, always wins) if settings is not None: default_settings.apply_update(settings) diff --git a/src/pipecat/services/fireworks/llm.py b/src/pipecat/services/fireworks/llm.py index ccc9107f6..b576462cb 100644 --- a/src/pipecat/services/fireworks/llm.py +++ b/src/pipecat/services/fireworks/llm.py @@ -64,6 +64,8 @@ class FireworksLLMService(OpenAILLMService): _warn_deprecated_param("model", FireworksLLMSettings, "model") default_settings.model = model + # 3. (No step 3, as there's no params object to apply) + # 4. Apply settings delta (canonical API, always wins) if settings is not None: default_settings.apply_update(settings) diff --git a/src/pipecat/services/google/llm_openai.py b/src/pipecat/services/google/llm_openai.py index 96e208fcb..cf89fa3a4 100644 --- a/src/pipecat/services/google/llm_openai.py +++ b/src/pipecat/services/google/llm_openai.py @@ -102,6 +102,8 @@ class GoogleLLMOpenAIBetaService(OpenAILLMService): _warn_deprecated_param("model", GoogleOpenAILLMSettings, "model") default_settings.model = model + # 3. (No step 3, as there's no params object to apply) + # 4. Apply settings delta (canonical API, always wins) if settings is not None: default_settings.apply_update(settings) diff --git a/src/pipecat/services/grok/llm.py b/src/pipecat/services/grok/llm.py index 59741cf9a..c95dd190f 100644 --- a/src/pipecat/services/grok/llm.py +++ b/src/pipecat/services/grok/llm.py @@ -119,6 +119,8 @@ class GrokLLMService(OpenAILLMService): _warn_deprecated_param("model", GrokLLMSettings, "model") default_settings.model = model + # 3. (No step 3, as there's no params object to apply) + # 4. Apply settings delta (canonical API, always wins) if settings is not None: default_settings.apply_update(settings) diff --git a/src/pipecat/services/groq/llm.py b/src/pipecat/services/groq/llm.py index d7fc7f939..eff88226a 100644 --- a/src/pipecat/services/groq/llm.py +++ b/src/pipecat/services/groq/llm.py @@ -63,6 +63,8 @@ class GroqLLMService(OpenAILLMService): _warn_deprecated_param("model", GroqLLMSettings, "model") default_settings.model = model + # 3. (No step 3, as there's no params object to apply) + # 4. Apply settings delta (canonical API, always wins) if settings is not None: default_settings.apply_update(settings) diff --git a/src/pipecat/services/mistral/llm.py b/src/pipecat/services/mistral/llm.py index 647a56bca..8e977ff7b 100644 --- a/src/pipecat/services/mistral/llm.py +++ b/src/pipecat/services/mistral/llm.py @@ -66,6 +66,8 @@ class MistralLLMService(OpenAILLMService): _warn_deprecated_param("model", MistralLLMSettings, "model") default_settings.model = model + # 3. (No step 3, as there's no params object to apply) + # 4. Apply settings delta (canonical API, always wins) if settings is not None: default_settings.apply_update(settings) diff --git a/src/pipecat/services/nvidia/llm.py b/src/pipecat/services/nvidia/llm.py index 48ccbaaf4..16b3a78c4 100644 --- a/src/pipecat/services/nvidia/llm.py +++ b/src/pipecat/services/nvidia/llm.py @@ -70,6 +70,8 @@ class NvidiaLLMService(OpenAILLMService): _warn_deprecated_param("model", NvidiaLLMSettings, "model") default_settings.model = model + # 3. (No step 3, as there's no params object to apply) + # 4. Apply settings delta (canonical API, always wins) if settings is not None: default_settings.apply_update(settings) diff --git a/src/pipecat/services/ollama/llm.py b/src/pipecat/services/ollama/llm.py index d1c0eeebd..4662d741b 100644 --- a/src/pipecat/services/ollama/llm.py +++ b/src/pipecat/services/ollama/llm.py @@ -62,6 +62,8 @@ class OLLamaLLMService(OpenAILLMService): _warn_deprecated_param("model", OllamaLLMSettings, "model") default_settings.model = model + # 3. (No step 3, as there's no params object to apply) + # 4. Apply settings delta (canonical API, always wins) if settings is not None: default_settings.apply_update(settings) diff --git a/src/pipecat/services/openpipe/llm.py b/src/pipecat/services/openpipe/llm.py index f6437feef..ee4fe611b 100644 --- a/src/pipecat/services/openpipe/llm.py +++ b/src/pipecat/services/openpipe/llm.py @@ -82,6 +82,8 @@ class OpenPipeLLMService(OpenAILLMService): _warn_deprecated_param("model", OpenPipeLLMSettings, "model") default_settings.model = model + # 3. (No step 3, as there's no params object to apply) + # 4. Apply settings delta (canonical API, always wins) if settings is not None: default_settings.apply_update(settings) diff --git a/src/pipecat/services/openrouter/llm.py b/src/pipecat/services/openrouter/llm.py index 03591de46..f9ac13d22 100644 --- a/src/pipecat/services/openrouter/llm.py +++ b/src/pipecat/services/openrouter/llm.py @@ -68,6 +68,8 @@ class OpenRouterLLMService(OpenAILLMService): _warn_deprecated_param("model", OpenRouterLLMSettings, "model") default_settings.model = model + # 3. (No step 3, as there's no params object to apply) + # 4. Apply settings delta (canonical API, always wins) if settings is not None: default_settings.apply_update(settings) diff --git a/src/pipecat/services/perplexity/llm.py b/src/pipecat/services/perplexity/llm.py index 137fdeeb9..7fe414023 100644 --- a/src/pipecat/services/perplexity/llm.py +++ b/src/pipecat/services/perplexity/llm.py @@ -71,6 +71,8 @@ class PerplexityLLMService(OpenAILLMService): _warn_deprecated_param("model", PerplexityLLMSettings, "model") default_settings.model = model + # 3. (No step 3, as there's no params object to apply) + # 4. Apply settings delta (canonical API, always wins) if settings is not None: default_settings.apply_update(settings) diff --git a/src/pipecat/services/qwen/llm.py b/src/pipecat/services/qwen/llm.py index e08566418..656b223b2 100644 --- a/src/pipecat/services/qwen/llm.py +++ b/src/pipecat/services/qwen/llm.py @@ -63,6 +63,8 @@ class QwenLLMService(OpenAILLMService): _warn_deprecated_param("model", QwenLLMSettings, "model") default_settings.model = model + # 3. (No step 3, as there's no params object to apply) + # 4. Apply settings delta (canonical API, always wins) if settings is not None: default_settings.apply_update(settings) diff --git a/src/pipecat/services/sambanova/llm.py b/src/pipecat/services/sambanova/llm.py index 0c92db098..0a0c53eaa 100644 --- a/src/pipecat/services/sambanova/llm.py +++ b/src/pipecat/services/sambanova/llm.py @@ -75,6 +75,8 @@ class SambaNovaLLMService(OpenAILLMService): # type: ignore _warn_deprecated_param("model", SambaNovaLLMSettings, "model") default_settings.model = model + # 3. (No step 3, as there's no params object to apply) + # 4. Apply settings delta (canonical API, always wins) if settings is not None: default_settings.apply_update(settings) diff --git a/src/pipecat/services/together/llm.py b/src/pipecat/services/together/llm.py index 2fa952a95..d39eb8ce6 100644 --- a/src/pipecat/services/together/llm.py +++ b/src/pipecat/services/together/llm.py @@ -63,6 +63,8 @@ class TogetherLLMService(OpenAILLMService): _warn_deprecated_param("model", TogetherLLMSettings, "model") default_settings.model = model + # 3. (No step 3, as there's no params object to apply) + # 4. Apply settings delta (canonical API, always wins) if settings is not None: default_settings.apply_update(settings) From 6088e6eb52303f8254b06554bcb15831cf35551a Mon Sep 17 00:00:00 2001 From: Paul Kompfner Date: Fri, 6 Mar 2026 17:25:07 -0500 Subject: [PATCH 0853/1060] Make budget_tokens optional in AnthropicThinkingConfig budget_tokens is required when type is "enabled" and rejected when type is "disabled" (this is validated by the server) --- src/pipecat/services/anthropic/llm.py | 8 ++++---- 1 file changed, 4 insertions(+), 4 deletions(-) diff --git a/src/pipecat/services/anthropic/llm.py b/src/pipecat/services/anthropic/llm.py index 49f7f58b4..a11ec9b3e 100644 --- a/src/pipecat/services/anthropic/llm.py +++ b/src/pipecat/services/anthropic/llm.py @@ -76,16 +76,16 @@ class AnthropicThinkingConfig(BaseModel): type: Type of thinking mode (currently only "enabled" or "disabled"). budget_tokens: Maximum number of tokens for thinking. With today's models, the minimum is 1024. - Only allowed if type is "enabled". + Currently required when type is "enabled", not allowed when "disabled". """ # Why `| str` here? To not break compatibility in case Anthropic adds # more types in the future. type: Literal["enabled", "disabled"] | str - # Why not enforce minimnum of 1024 here? To not break compatibility in - # case Anthropic changes this requirement in the future. - budget_tokens: int + # No client-side validation on budget_tokens — we let the server + # enforce the rules so we stay forward-compatible if they change. + budget_tokens: Optional[int] = None @dataclass From 622d9279cbaeb1276de7c820b448a0d2a74ccc58 Mon Sep 17 00:00:00 2001 From: Paul Kompfner Date: Fri, 6 Mar 2026 22:30:15 -0500 Subject: [PATCH 0854/1060] Use exact service class names in LLMSettings docstrings --- src/pipecat/services/anthropic/llm.py | 2 +- src/pipecat/services/aws/llm.py | 2 +- src/pipecat/services/aws/nova_sonic/llm.py | 2 +- src/pipecat/services/azure/llm.py | 2 +- src/pipecat/services/azure/realtime/llm.py | 2 +- src/pipecat/services/cerebras/llm.py | 2 +- src/pipecat/services/deepseek/llm.py | 2 +- src/pipecat/services/fireworks/llm.py | 2 +- src/pipecat/services/google/gemini_live/llm.py | 2 +- src/pipecat/services/google/gemini_live/llm_vertex.py | 2 +- src/pipecat/services/google/llm.py | 2 +- src/pipecat/services/google/llm_openai.py | 2 +- src/pipecat/services/google/llm_vertex.py | 2 +- src/pipecat/services/grok/llm.py | 2 +- src/pipecat/services/grok/realtime/llm.py | 2 +- src/pipecat/services/groq/llm.py | 2 +- src/pipecat/services/mistral/llm.py | 2 +- src/pipecat/services/nvidia/llm.py | 2 +- src/pipecat/services/ollama/llm.py | 2 +- src/pipecat/services/openai/base_llm.py | 2 +- src/pipecat/services/openai/realtime/llm.py | 2 +- src/pipecat/services/openai_realtime_beta/azure.py | 2 +- src/pipecat/services/openai_realtime_beta/openai.py | 2 +- src/pipecat/services/openpipe/llm.py | 2 +- src/pipecat/services/openrouter/llm.py | 2 +- src/pipecat/services/perplexity/llm.py | 2 +- src/pipecat/services/qwen/llm.py | 2 +- src/pipecat/services/sambanova/llm.py | 2 +- src/pipecat/services/together/llm.py | 2 +- 29 files changed, 29 insertions(+), 29 deletions(-) diff --git a/src/pipecat/services/anthropic/llm.py b/src/pipecat/services/anthropic/llm.py index a11ec9b3e..f687b56c5 100644 --- a/src/pipecat/services/anthropic/llm.py +++ b/src/pipecat/services/anthropic/llm.py @@ -90,7 +90,7 @@ class AnthropicThinkingConfig(BaseModel): @dataclass class AnthropicLLMSettings(LLMSettings): - """Settings for Anthropic LLM services. + """Settings for AnthropicLLMService. Parameters: enable_prompt_caching: Whether to enable prompt caching. diff --git a/src/pipecat/services/aws/llm.py b/src/pipecat/services/aws/llm.py index 5b8c80996..bcc5028c4 100644 --- a/src/pipecat/services/aws/llm.py +++ b/src/pipecat/services/aws/llm.py @@ -72,7 +72,7 @@ except ModuleNotFoundError as e: @dataclass class AWSBedrockLLMSettings(LLMSettings): - """Settings for AWS Bedrock LLM services. + """Settings for AWSBedrockLLMService. Parameters: stop_sequences: List of strings that stop generation. diff --git a/src/pipecat/services/aws/nova_sonic/llm.py b/src/pipecat/services/aws/nova_sonic/llm.py index 3acc1d0fc..fa69a9c8a 100644 --- a/src/pipecat/services/aws/nova_sonic/llm.py +++ b/src/pipecat/services/aws/nova_sonic/llm.py @@ -227,7 +227,7 @@ class AudioConfig(BaseModel): @dataclass class AWSNovaSonicLLMSettings(LLMSettings): - """Settings for AWS Nova Sonic LLM service. + """Settings for AWSNovaSonicLLMService. Parameters: voice: Voice identifier for speech synthesis. diff --git a/src/pipecat/services/azure/llm.py b/src/pipecat/services/azure/llm.py index ce98d151a..1c9960e8a 100644 --- a/src/pipecat/services/azure/llm.py +++ b/src/pipecat/services/azure/llm.py @@ -19,7 +19,7 @@ from pipecat.services.settings import _warn_deprecated_param @dataclass class AzureLLMSettings(OpenAILLMSettings): - """Settings for Azure OpenAI LLM service.""" + """Settings for AzureLLMService.""" pass diff --git a/src/pipecat/services/azure/realtime/llm.py b/src/pipecat/services/azure/realtime/llm.py index 0de2217d8..bf91d484e 100644 --- a/src/pipecat/services/azure/realtime/llm.py +++ b/src/pipecat/services/azure/realtime/llm.py @@ -22,7 +22,7 @@ except ModuleNotFoundError as e: @dataclass class AzureRealtimeLLMSettings(OpenAIRealtimeLLMSettings): - """Settings for Azure Realtime LLM service.""" + """Settings for AzureRealtimeLLMService.""" pass diff --git a/src/pipecat/services/cerebras/llm.py b/src/pipecat/services/cerebras/llm.py index 0fe19bd75..d8dcf3d08 100644 --- a/src/pipecat/services/cerebras/llm.py +++ b/src/pipecat/services/cerebras/llm.py @@ -19,7 +19,7 @@ from pipecat.services.settings import _warn_deprecated_param @dataclass class CerebrasLLMSettings(OpenAILLMSettings): - """Settings for Cerebras LLM service.""" + """Settings for CerebrasLLMService.""" pass diff --git a/src/pipecat/services/deepseek/llm.py b/src/pipecat/services/deepseek/llm.py index b91a2f443..2286a98b2 100644 --- a/src/pipecat/services/deepseek/llm.py +++ b/src/pipecat/services/deepseek/llm.py @@ -19,7 +19,7 @@ from pipecat.services.settings import _warn_deprecated_param @dataclass class DeepSeekLLMSettings(OpenAILLMSettings): - """Settings for DeepSeek LLM service.""" + """Settings for DeepSeekLLMService.""" pass diff --git a/src/pipecat/services/fireworks/llm.py b/src/pipecat/services/fireworks/llm.py index b576462cb..cd7e91504 100644 --- a/src/pipecat/services/fireworks/llm.py +++ b/src/pipecat/services/fireworks/llm.py @@ -19,7 +19,7 @@ from pipecat.services.settings import _warn_deprecated_param @dataclass class FireworksLLMSettings(OpenAILLMSettings): - """Settings for Fireworks LLM service.""" + """Settings for FireworksLLMService.""" pass diff --git a/src/pipecat/services/google/gemini_live/llm.py b/src/pipecat/services/google/gemini_live/llm.py index d6fbe7ebe..58dcd2da8 100644 --- a/src/pipecat/services/google/gemini_live/llm.py +++ b/src/pipecat/services/google/gemini_live/llm.py @@ -607,7 +607,7 @@ class InputParams(BaseModel): @dataclass class GeminiLiveLLMSettings(LLMSettings): - """Settings for GeminiLiveLLMService and GeminiLiveVertexLLMService. + """Settings for GeminiLiveLLMService. Parameters: voice: TTS voice identifier (e.g. ``"Charon"``). diff --git a/src/pipecat/services/google/gemini_live/llm_vertex.py b/src/pipecat/services/google/gemini_live/llm_vertex.py index 9edd73e61..09aaeebbb 100644 --- a/src/pipecat/services/google/gemini_live/llm_vertex.py +++ b/src/pipecat/services/google/gemini_live/llm_vertex.py @@ -44,7 +44,7 @@ except ModuleNotFoundError as e: @dataclass class GeminiLiveVertexLLMSettings(GeminiLiveLLMSettings): - """Settings for Gemini Live Vertex LLM service.""" + """Settings for GeminiLiveVertexLLMService.""" pass diff --git a/src/pipecat/services/google/llm.py b/src/pipecat/services/google/llm.py index d5f025bcd..06f47bc2e 100644 --- a/src/pipecat/services/google/llm.py +++ b/src/pipecat/services/google/llm.py @@ -714,7 +714,7 @@ class GoogleThinkingConfig(BaseModel): @dataclass class GoogleLLMSettings(LLMSettings): - """Settings for Google LLM services. + """Settings for GoogleLLMService. Parameters: thinking: Thinking configuration. diff --git a/src/pipecat/services/google/llm_openai.py b/src/pipecat/services/google/llm_openai.py index cf89fa3a4..75fc6c54c 100644 --- a/src/pipecat/services/google/llm_openai.py +++ b/src/pipecat/services/google/llm_openai.py @@ -35,7 +35,7 @@ from pipecat.services.settings import _warn_deprecated_param @dataclass class GoogleOpenAILLMSettings(OpenAILLMSettings): - """Settings for Google OpenAI-compatible LLM service.""" + """Settings for GoogleLLMOpenAIBetaService.""" pass diff --git a/src/pipecat/services/google/llm_vertex.py b/src/pipecat/services/google/llm_vertex.py index cbad30c48..e40f15de6 100644 --- a/src/pipecat/services/google/llm_vertex.py +++ b/src/pipecat/services/google/llm_vertex.py @@ -42,7 +42,7 @@ except ModuleNotFoundError as e: @dataclass class GoogleVertexLLMSettings(GoogleLLMSettings): - """Settings for Google Vertex LLM service.""" + """Settings for GoogleVertexLLMService.""" pass diff --git a/src/pipecat/services/grok/llm.py b/src/pipecat/services/grok/llm.py index c95dd190f..144d91a16 100644 --- a/src/pipecat/services/grok/llm.py +++ b/src/pipecat/services/grok/llm.py @@ -72,7 +72,7 @@ class GrokContextAggregatorPair: @dataclass class GrokLLMSettings(OpenAILLMSettings): - """Settings for Grok LLM service.""" + """Settings for GrokLLMService.""" pass diff --git a/src/pipecat/services/grok/realtime/llm.py b/src/pipecat/services/grok/realtime/llm.py index f0fb170d4..7e252ebf5 100644 --- a/src/pipecat/services/grok/realtime/llm.py +++ b/src/pipecat/services/grok/realtime/llm.py @@ -94,7 +94,7 @@ class CurrentAudioResponse: @dataclass class GrokRealtimeLLMSettings(LLMSettings): - """Settings for Grok Realtime LLM services. + """Settings for GrokRealtimeLLMService. Parameters: session_properties: Grok Realtime session properties (voice, audio config, diff --git a/src/pipecat/services/groq/llm.py b/src/pipecat/services/groq/llm.py index eff88226a..e86c59391 100644 --- a/src/pipecat/services/groq/llm.py +++ b/src/pipecat/services/groq/llm.py @@ -18,7 +18,7 @@ from pipecat.services.settings import _warn_deprecated_param @dataclass class GroqLLMSettings(OpenAILLMSettings): - """Settings for Groq LLM service.""" + """Settings for GroqLLMService.""" pass diff --git a/src/pipecat/services/mistral/llm.py b/src/pipecat/services/mistral/llm.py index 8e977ff7b..8389613e0 100644 --- a/src/pipecat/services/mistral/llm.py +++ b/src/pipecat/services/mistral/llm.py @@ -21,7 +21,7 @@ from pipecat.services.settings import _warn_deprecated_param @dataclass class MistralLLMSettings(OpenAILLMSettings): - """Settings for Mistral LLM service.""" + """Settings for MistralLLMService.""" pass diff --git a/src/pipecat/services/nvidia/llm.py b/src/pipecat/services/nvidia/llm.py index 16b3a78c4..65c0880e4 100644 --- a/src/pipecat/services/nvidia/llm.py +++ b/src/pipecat/services/nvidia/llm.py @@ -23,7 +23,7 @@ from pipecat.services.settings import _warn_deprecated_param @dataclass class NvidiaLLMSettings(OpenAILLMSettings): - """Settings for NVIDIA LLM service.""" + """Settings for NvidiaLLMService.""" pass diff --git a/src/pipecat/services/ollama/llm.py b/src/pipecat/services/ollama/llm.py index 4662d741b..42b5b00b1 100644 --- a/src/pipecat/services/ollama/llm.py +++ b/src/pipecat/services/ollama/llm.py @@ -18,7 +18,7 @@ from pipecat.services.settings import _warn_deprecated_param @dataclass class OllamaLLMSettings(OpenAILLMSettings): - """Settings for Ollama LLM service.""" + """Settings for OLLamaLLMService.""" pass diff --git a/src/pipecat/services/openai/base_llm.py b/src/pipecat/services/openai/base_llm.py index 5e59a5129..bfeae62a1 100644 --- a/src/pipecat/services/openai/base_llm.py +++ b/src/pipecat/services/openai/base_llm.py @@ -49,7 +49,7 @@ from pipecat.utils.tracing.service_decorators import traced_llm @dataclass class OpenAILLMSettings(LLMSettings): - """Settings for OpenAI-compatible LLM services. + """Settings for BaseOpenAILLMService. Parameters: max_completion_tokens: Maximum completion tokens to generate. diff --git a/src/pipecat/services/openai/realtime/llm.py b/src/pipecat/services/openai/realtime/llm.py index faaae2cd9..c25181dd1 100644 --- a/src/pipecat/services/openai/realtime/llm.py +++ b/src/pipecat/services/openai/realtime/llm.py @@ -100,7 +100,7 @@ class CurrentAudioResponse: @dataclass class OpenAIRealtimeLLMSettings(LLMSettings): - """Settings for OpenAI Realtime LLM services. + """Settings for OpenAIRealtimeLLMService. Parameters: session_properties: OpenAI Realtime session properties (modalities, diff --git a/src/pipecat/services/openai_realtime_beta/azure.py b/src/pipecat/services/openai_realtime_beta/azure.py index 72a1201f7..55fb7744d 100644 --- a/src/pipecat/services/openai_realtime_beta/azure.py +++ b/src/pipecat/services/openai_realtime_beta/azure.py @@ -25,7 +25,7 @@ except ModuleNotFoundError as e: @dataclass class AzureRealtimeBetaLLMSettings(OpenAIRealtimeBetaLLMSettings): - """Settings for Azure Realtime Beta LLM service.""" + """Settings for AzureRealtimeBetaLLMService.""" pass diff --git a/src/pipecat/services/openai_realtime_beta/openai.py b/src/pipecat/services/openai_realtime_beta/openai.py index bd9dc29b0..689ca91a5 100644 --- a/src/pipecat/services/openai_realtime_beta/openai.py +++ b/src/pipecat/services/openai_realtime_beta/openai.py @@ -94,7 +94,7 @@ class CurrentAudioResponse: @dataclass class OpenAIRealtimeBetaLLMSettings(LLMSettings): - """Settings for OpenAI Realtime Beta LLM services.""" + """Settings for OpenAIRealtimeBetaLLMService.""" pass diff --git a/src/pipecat/services/openpipe/llm.py b/src/pipecat/services/openpipe/llm.py index ee4fe611b..58840c40d 100644 --- a/src/pipecat/services/openpipe/llm.py +++ b/src/pipecat/services/openpipe/llm.py @@ -30,7 +30,7 @@ except ModuleNotFoundError as e: @dataclass class OpenPipeLLMSettings(OpenAILLMSettings): - """Settings for OpenPipe LLM service.""" + """Settings for OpenPipeLLMService.""" pass diff --git a/src/pipecat/services/openrouter/llm.py b/src/pipecat/services/openrouter/llm.py index f9ac13d22..411eca91e 100644 --- a/src/pipecat/services/openrouter/llm.py +++ b/src/pipecat/services/openrouter/llm.py @@ -22,7 +22,7 @@ from pipecat.services.settings import _warn_deprecated_param @dataclass class OpenRouterLLMSettings(OpenAILLMSettings): - """Settings for OpenRouter LLM service.""" + """Settings for OpenRouterLLMService.""" pass diff --git a/src/pipecat/services/perplexity/llm.py b/src/pipecat/services/perplexity/llm.py index 7fe414023..614e6ad9b 100644 --- a/src/pipecat/services/perplexity/llm.py +++ b/src/pipecat/services/perplexity/llm.py @@ -25,7 +25,7 @@ from pipecat.services.settings import _warn_deprecated_param @dataclass class PerplexityLLMSettings(OpenAILLMSettings): - """Settings for Perplexity LLM service.""" + """Settings for PerplexityLLMService.""" pass diff --git a/src/pipecat/services/qwen/llm.py b/src/pipecat/services/qwen/llm.py index 656b223b2..ba2b734c7 100644 --- a/src/pipecat/services/qwen/llm.py +++ b/src/pipecat/services/qwen/llm.py @@ -18,7 +18,7 @@ from pipecat.services.settings import _warn_deprecated_param @dataclass class QwenLLMSettings(OpenAILLMSettings): - """Settings for Qwen LLM service.""" + """Settings for QwenLLMService.""" pass diff --git a/src/pipecat/services/sambanova/llm.py b/src/pipecat/services/sambanova/llm.py index 0a0c53eaa..e56f2576b 100644 --- a/src/pipecat/services/sambanova/llm.py +++ b/src/pipecat/services/sambanova/llm.py @@ -30,7 +30,7 @@ from pipecat.utils.tracing.service_decorators import traced_llm @dataclass class SambaNovaLLMSettings(OpenAILLMSettings): - """Settings for SambaNova LLM service.""" + """Settings for SambaNovaLLMService.""" pass diff --git a/src/pipecat/services/together/llm.py b/src/pipecat/services/together/llm.py index d39eb8ce6..38089addc 100644 --- a/src/pipecat/services/together/llm.py +++ b/src/pipecat/services/together/llm.py @@ -18,7 +18,7 @@ from pipecat.services.settings import _warn_deprecated_param @dataclass class TogetherLLMSettings(OpenAILLMSettings): - """Settings for Together LLM service.""" + """Settings for TogetherLLMService.""" pass From 1cfaea20077d70b01ef480f16043bdd94e8bc54d Mon Sep 17 00:00:00 2001 From: Mark Backman Date: Sat, 7 Mar 2026 07:36:47 -0500 Subject: [PATCH 0855/1060] Address code review feedback --- changelog/3946.added.md | 1 + src/pipecat/services/aws/stt.py | 4 ++-- src/pipecat/services/azure/stt.py | 7 ++++--- src/pipecat/services/deepgram/stt.py | 11 +++++++---- src/pipecat/services/deepgram/tts.py | 4 ++++ src/pipecat/services/elevenlabs/stt.py | 5 +++-- src/pipecat/services/gradium/stt.py | 17 ++++++++++------- src/pipecat/services/lmnt/tts.py | 2 +- src/pipecat/services/piper/tts.py | 4 ++-- src/pipecat/services/resembleai/tts.py | 2 +- src/pipecat/services/xtts/tts.py | 2 ++ tests/test_service_init.py | 1 - 12 files changed, 37 insertions(+), 23 deletions(-) create mode 100644 changelog/3946.added.md diff --git a/changelog/3946.added.md b/changelog/3946.added.md new file mode 100644 index 000000000..6aabfefb2 --- /dev/null +++ b/changelog/3946.added.md @@ -0,0 +1 @@ +- Runtime settings updates (via `STTUpdateSettingsFrame`) now work for AWS Transcribe, Azure, Cartesia, Deepgram, ElevenLabs Realtime, Gradium, and Soniox STT services. Previously, changing settings at runtime only stored the new values without reconnecting. diff --git a/src/pipecat/services/aws/stt.py b/src/pipecat/services/aws/stt.py index ca3b0140c..7355bb1b7 100644 --- a/src/pipecat/services/aws/stt.py +++ b/src/pipecat/services/aws/stt.py @@ -107,7 +107,7 @@ class AWSTranscribeSTTService(WebsocketSTTService): _warn_deprecated_param("language", AWSTranscribeSTTSettings, "language") default_settings.language = self.language_to_service_language(language) - # 3. No params to apply + # 3. (No step 3, as there's no params object to apply) # 4. Apply settings delta (canonical API, always wins) if settings is not None: @@ -161,7 +161,7 @@ class AWSTranscribeSTTService(WebsocketSTTService): """Apply a settings delta and reconnect if anything changed.""" changed = await super()._update_settings(delta) - if changed: + if changed and self._websocket: await self._disconnect() await self._connect() diff --git a/src/pipecat/services/azure/stt.py b/src/pipecat/services/azure/stt.py index f66cfeb42..f940ea9c0 100644 --- a/src/pipecat/services/azure/stt.py +++ b/src/pipecat/services/azure/stt.py @@ -112,7 +112,7 @@ class AzureSTTService(STTService): _warn_deprecated_param("language", AzureSTTSettings, "language") default_settings.language = language_to_azure_language(language) - # 3. No params to apply + # 3. (No step 3, as there's no params object to apply) # 4. Apply settings delta (canonical API, always wins) if settings is not None: @@ -166,8 +166,9 @@ class AzureSTTService(STTService): self._speech_config.speech_recognition_language = ( self._settings.language or language_to_azure_language(Language.EN_US) ) - await self._disconnect() - await self._connect() + if self._audio_stream: + await self._disconnect() + await self._connect() return changed diff --git a/src/pipecat/services/deepgram/stt.py b/src/pipecat/services/deepgram/stt.py index 17570911a..14020631b 100644 --- a/src/pipecat/services/deepgram/stt.py +++ b/src/pipecat/services/deepgram/stt.py @@ -365,7 +365,9 @@ class DeepgramSTTService(STTService): vad_events=False, ) - # 2. Apply live_options overrides — only if settings not provided + # 2. (No step 2, as there are no deprecated direct args) + + # 3. Apply live_options overrides — only if settings not provided if live_options is not None: _warn_deprecated_param("live_options", DeepgramSTTSettings) if not settings: @@ -402,7 +404,7 @@ class DeepgramSTTService(STTService): delta = DeepgramSTTSettings.from_mapping(lo_dict) default_settings.apply_update(delta) - # 3. Apply settings delta (canonical API, always wins) + # 4. Apply settings delta (canonical API, always wins) if settings is not None: default_settings.apply_update(settings) @@ -494,8 +496,9 @@ class DeepgramSTTService(STTService): if isinstance(self._settings, DeepgramSTTSettings): self._settings._sync_extra_to_fields() - await self._disconnect() - await self._connect() + if self._connection: + await self._disconnect() + await self._connect() return changed diff --git a/src/pipecat/services/deepgram/tts.py b/src/pipecat/services/deepgram/tts.py index 7749fc370..5d6e5ffdc 100644 --- a/src/pipecat/services/deepgram/tts.py +++ b/src/pipecat/services/deepgram/tts.py @@ -110,6 +110,8 @@ class DeepgramTTSService(WebsocketTTSService): default_settings.model = voice default_settings.voice = voice + # 3. (No step 3, as there's no params object to apply) + # 4. Apply settings delta (canonical API, always wins) if settings is not None: default_settings.apply_update(settings) @@ -423,6 +425,8 @@ class DeepgramHttpTTSService(TTSService): default_settings.model = voice default_settings.voice = voice + # 3. (No step 3, as there's no params object to apply) + # 4. Apply settings delta (canonical API, always wins) if settings is not None: default_settings.apply_update(settings) diff --git a/src/pipecat/services/elevenlabs/stt.py b/src/pipecat/services/elevenlabs/stt.py index 1802bb095..dff501d22 100644 --- a/src/pipecat/services/elevenlabs/stt.py +++ b/src/pipecat/services/elevenlabs/stt.py @@ -605,8 +605,9 @@ class ElevenLabsRealtimeSTTService(WebsocketSTTService): if not changed: return changed - await self._disconnect() - await self._connect() + if self._websocket: + await self._disconnect() + await self._connect() return changed diff --git a/src/pipecat/services/gradium/stt.py b/src/pipecat/services/gradium/stt.py index 05a6bb8b5..814d478e4 100644 --- a/src/pipecat/services/gradium/stt.py +++ b/src/pipecat/services/gradium/stt.py @@ -12,7 +12,7 @@ WebSocket API for streaming audio transcription. import base64 import json -from dataclasses import dataclass +from dataclasses import dataclass, field from typing import Any, AsyncGenerator, Optional from loguru import logger @@ -28,7 +28,7 @@ from pipecat.frames.frames import ( VADUserStoppedSpeakingFrame, ) from pipecat.processors.frame_processor import FrameDirection -from pipecat.services.settings import STTSettings, _warn_deprecated_param +from pipecat.services.settings import NOT_GIVEN, STTSettings, _NotGiven, _warn_deprecated_param from pipecat.services.stt_latency import GRADIUM_TTFS_P99 from pipecat.services.stt_service import WebsocketSTTService from pipecat.transcriptions.language import Language, resolve_language @@ -77,7 +77,7 @@ class GradiumSTTSettings(STTSettings): Default is 10 (800ms). Lower values like 7-8 give faster response. """ - delay_in_frames: Optional[int] = None + delay_in_frames: Optional[int] | _NotGiven = field(default_factory=lambda: NOT_GIVEN) class GradiumSTTService(WebsocketSTTService): @@ -157,7 +157,9 @@ class GradiumSTTService(WebsocketSTTService): delay_in_frames=None, ) - # 2. Apply params overrides — only if settings not provided + # 2. (No step 2, as there are no deprecated direct args) + + # 3. Apply params overrides — only if settings not provided if params is not None: _warn_deprecated_param("params", GradiumSTTSettings) if not settings: @@ -165,7 +167,7 @@ class GradiumSTTService(WebsocketSTTService): if params.delay_in_frames is not None: default_settings.delay_in_frames = params.delay_in_frames - # 3. Apply settings delta (canonical API, always wins) + # 4. Apply settings delta (canonical API, always wins) if settings is not None: default_settings.apply_update(settings) @@ -213,8 +215,9 @@ class GradiumSTTService(WebsocketSTTService): if not changed: return changed - await self._disconnect() - await self._connect() + if self._websocket: + await self._disconnect() + await self._connect() return changed async def start(self, frame: StartFrame): diff --git a/src/pipecat/services/lmnt/tts.py b/src/pipecat/services/lmnt/tts.py index 3cc6778af..f6bf46649 100644 --- a/src/pipecat/services/lmnt/tts.py +++ b/src/pipecat/services/lmnt/tts.py @@ -139,7 +139,7 @@ class LmntTTSService(InterruptibleTTSService): _warn_deprecated_param("model", LmntTTSSettings, "model") default_settings.model = model - # 3. No params for this service + # 3. (No step 3, as there's no params object to apply) # 4. Apply settings delta (canonical API, always wins) if settings is not None: diff --git a/src/pipecat/services/piper/tts.py b/src/pipecat/services/piper/tts.py index 337dcd00c..fb7b627cd 100644 --- a/src/pipecat/services/piper/tts.py +++ b/src/pipecat/services/piper/tts.py @@ -82,7 +82,7 @@ class PiperTTSService(TTSService): _warn_deprecated_param("voice_id", PiperTTSSettings, "voice") default_settings.voice = voice_id - # 3. No params for this service + # 3. (No step 3, as there's no params object to apply) # 4. Apply settings delta (canonical API, always wins) if settings is not None: @@ -232,7 +232,7 @@ class PiperHttpTTSService(TTSService): _warn_deprecated_param("voice_id", PiperHttpTTSSettings, "voice") default_settings.voice = voice_id - # 3. No params for this service + # 3. (No step 3, as there's no params object to apply) # 4. Apply settings delta (canonical API, always wins) if settings is not None: diff --git a/src/pipecat/services/resembleai/tts.py b/src/pipecat/services/resembleai/tts.py index f0a93a182..9713cea44 100644 --- a/src/pipecat/services/resembleai/tts.py +++ b/src/pipecat/services/resembleai/tts.py @@ -94,7 +94,7 @@ class ResembleAITTSService(WebsocketTTSService): _warn_deprecated_param("voice_id", ResembleAITTSSettings, "voice") default_settings.voice = voice_id - # 3. No params for this service + # 3. (No step 3, as there's no params object to apply) # 4. Apply settings delta (canonical API, always wins) if settings is not None: diff --git a/src/pipecat/services/xtts/tts.py b/src/pipecat/services/xtts/tts.py index 4da8db72a..78ac6dfb8 100644 --- a/src/pipecat/services/xtts/tts.py +++ b/src/pipecat/services/xtts/tts.py @@ -124,6 +124,8 @@ class XTTSService(TTSService): _warn_deprecated_param("voice_id", XTTSTTSSettings, "voice") default_settings.voice = voice_id + # 3. (No step 3, as there's no params object to apply) + # 4. Apply settings delta (canonical API, always wins) if settings is not None: default_settings.apply_update(settings) diff --git a/tests/test_service_init.py b/tests/test_service_init.py index 67dcbb324..377300f64 100644 --- a/tests/test_service_init.py +++ b/tests/test_service_init.py @@ -34,7 +34,6 @@ new services are covered automatically with no per-service maintenance. import importlib import inspect import pkgutil -import warnings from dataclasses import fields import pytest From 26631a9c31771849cfde62489888189dbe5e6dcf Mon Sep 17 00:00:00 2001 From: Mark Backman Date: Sat, 7 Mar 2026 08:17:40 -0500 Subject: [PATCH 0856/1060] Add Settings class attribute alias to all service classes Add a `Settings` class-level alias on every STT, LLM, TTS, image, vision, and video service class pointing to its settings dataclass. This lets developers discover the right settings class via the service class itself (e.g. `GoogleSTTService.Settings(...)`) without needing to know or import the separate settings class name. --- src/pipecat/services/anthropic/llm.py | 1 + src/pipecat/services/assemblyai/stt.py | 1 + src/pipecat/services/asyncai/tts.py | 2 ++ src/pipecat/services/aws/llm.py | 1 + src/pipecat/services/aws/nova_sonic/llm.py | 1 + src/pipecat/services/aws/stt.py | 1 + src/pipecat/services/aws/tts.py | 3 +++ src/pipecat/services/azure/image.py | 1 + src/pipecat/services/azure/llm.py | 2 ++ src/pipecat/services/azure/realtime/llm.py | 1 + src/pipecat/services/azure/stt.py | 1 + src/pipecat/services/azure/tts.py | 4 ++++ src/pipecat/services/camb/tts.py | 1 + src/pipecat/services/cartesia/stt.py | 1 + src/pipecat/services/cartesia/tts.py | 2 ++ src/pipecat/services/cerebras/llm.py | 1 + src/pipecat/services/deepgram/flux/stt.py | 1 + src/pipecat/services/deepgram/sagemaker/stt.py | 1 + src/pipecat/services/deepgram/sagemaker/tts.py | 1 + src/pipecat/services/deepgram/stt.py | 1 + src/pipecat/services/deepgram/tts.py | 2 ++ src/pipecat/services/deepseek/llm.py | 1 + src/pipecat/services/elevenlabs/stt.py | 2 ++ src/pipecat/services/elevenlabs/tts.py | 2 ++ src/pipecat/services/fal/image.py | 3 +++ src/pipecat/services/fal/stt.py | 1 + src/pipecat/services/fireworks/llm.py | 1 + src/pipecat/services/fish/tts.py | 1 + src/pipecat/services/gladia/stt.py | 1 + src/pipecat/services/google/gemini_live/llm.py | 1 + src/pipecat/services/google/gemini_live/llm_vertex.py | 1 + src/pipecat/services/google/image.py | 5 +++-- src/pipecat/services/google/llm.py | 1 + src/pipecat/services/google/llm_openai.py | 1 + src/pipecat/services/google/llm_vertex.py | 1 + src/pipecat/services/google/stt.py | 1 + src/pipecat/services/google/tts.py | 3 +++ src/pipecat/services/gradium/stt.py | 1 + src/pipecat/services/gradium/tts.py | 1 + src/pipecat/services/grok/llm.py | 1 + src/pipecat/services/grok/realtime/llm.py | 1 + src/pipecat/services/groq/llm.py | 1 + src/pipecat/services/groq/stt.py | 1 + src/pipecat/services/groq/tts.py | 1 + src/pipecat/services/heygen/video.py | 3 +++ src/pipecat/services/hume/tts.py | 1 + src/pipecat/services/inworld/tts.py | 2 ++ src/pipecat/services/kokoro/tts.py | 1 + src/pipecat/services/lmnt/tts.py | 1 + src/pipecat/services/minimax/tts.py | 1 + src/pipecat/services/mistral/llm.py | 1 + src/pipecat/services/moondream/vision.py | 3 +++ src/pipecat/services/neuphonic/tts.py | 2 ++ src/pipecat/services/nvidia/llm.py | 1 + src/pipecat/services/nvidia/stt.py | 2 ++ src/pipecat/services/nvidia/tts.py | 1 + src/pipecat/services/ollama/llm.py | 1 + src/pipecat/services/openai/base_llm.py | 1 + src/pipecat/services/openai/image.py | 1 + src/pipecat/services/openai/realtime/llm.py | 1 + src/pipecat/services/openai/stt.py | 2 ++ src/pipecat/services/openai/tts.py | 1 + src/pipecat/services/openai_realtime_beta/azure.py | 1 + src/pipecat/services/openai_realtime_beta/openai.py | 1 + src/pipecat/services/openpipe/llm.py | 1 + src/pipecat/services/openrouter/llm.py | 1 + src/pipecat/services/perplexity/llm.py | 1 + src/pipecat/services/piper/tts.py | 2 ++ src/pipecat/services/qwen/llm.py | 1 + src/pipecat/services/resembleai/tts.py | 1 + src/pipecat/services/rime/tts.py | 3 +++ src/pipecat/services/sambanova/llm.py | 1 + src/pipecat/services/sambanova/stt.py | 2 ++ src/pipecat/services/sarvam/stt.py | 1 + src/pipecat/services/sarvam/tts.py | 2 ++ src/pipecat/services/soniox/stt.py | 1 + src/pipecat/services/speechmatics/stt.py | 1 + src/pipecat/services/speechmatics/tts.py | 1 + src/pipecat/services/tavus/video.py | 3 +++ src/pipecat/services/together/llm.py | 1 + src/pipecat/services/ultravox/llm.py | 1 + src/pipecat/services/whisper/base_stt.py | 1 + src/pipecat/services/whisper/stt.py | 2 ++ src/pipecat/services/xtts/tts.py | 1 + 84 files changed, 117 insertions(+), 2 deletions(-) diff --git a/src/pipecat/services/anthropic/llm.py b/src/pipecat/services/anthropic/llm.py index f687b56c5..7abcec3e0 100644 --- a/src/pipecat/services/anthropic/llm.py +++ b/src/pipecat/services/anthropic/llm.py @@ -159,6 +159,7 @@ class AnthropicLLMService(LLMService): Can use custom clients like AsyncAnthropicBedrock and AsyncAnthropicVertex. """ + Settings = AnthropicLLMSettings _settings: AnthropicLLMSettings # Overriding the default adapter to use the Anthropic one. diff --git a/src/pipecat/services/assemblyai/stt.py b/src/pipecat/services/assemblyai/stt.py index 3d10c970f..ddfcb4a47 100644 --- a/src/pipecat/services/assemblyai/stt.py +++ b/src/pipecat/services/assemblyai/stt.py @@ -128,6 +128,7 @@ class AssemblyAISTTService(WebsocketSTTService): for audio processing and connection management. """ + Settings = AssemblyAISTTSettings _settings: AssemblyAISTTSettings def __init__( diff --git a/src/pipecat/services/asyncai/tts.py b/src/pipecat/services/asyncai/tts.py index 7bcc1fdb1..67f79dbfd 100644 --- a/src/pipecat/services/asyncai/tts.py +++ b/src/pipecat/services/asyncai/tts.py @@ -85,6 +85,7 @@ class AsyncAITTSService(WebsocketTTSService): Provides text-to-speech using Async's streaming WebSocket API. """ + Settings = AsyncAITTSSettings _settings: AsyncAITTSSettings class InputParams(BaseModel): @@ -485,6 +486,7 @@ class AsyncAIHttpTTSService(TTSService): connection is not required or desired. """ + Settings = AsyncAITTSSettings _settings: AsyncAITTSSettings class InputParams(BaseModel): diff --git a/src/pipecat/services/aws/llm.py b/src/pipecat/services/aws/llm.py index bcc5028c4..168a2a98f 100644 --- a/src/pipecat/services/aws/llm.py +++ b/src/pipecat/services/aws/llm.py @@ -746,6 +746,7 @@ class AWSBedrockLLMService(LLMService): vision capabilities. """ + Settings = AWSBedrockLLMSettings _settings: AWSBedrockLLMSettings # Overriding the default adapter to use the Anthropic one. diff --git a/src/pipecat/services/aws/nova_sonic/llm.py b/src/pipecat/services/aws/nova_sonic/llm.py index fa69a9c8a..8e4633544 100644 --- a/src/pipecat/services/aws/nova_sonic/llm.py +++ b/src/pipecat/services/aws/nova_sonic/llm.py @@ -246,6 +246,7 @@ class AWSNovaSonicLLMService(LLMService): and function calling capabilities using AWS Nova Sonic model. """ + Settings = AWSNovaSonicLLMSettings _settings: AWSNovaSonicLLMSettings # Override the default adapter to use the AWSNovaSonicLLMAdapter one diff --git a/src/pipecat/services/aws/stt.py b/src/pipecat/services/aws/stt.py index 7355bb1b7..8b28c006a 100644 --- a/src/pipecat/services/aws/stt.py +++ b/src/pipecat/services/aws/stt.py @@ -60,6 +60,7 @@ class AWSTranscribeSTTService(WebsocketSTTService): final transcription results. """ + Settings = AWSTranscribeSTTSettings _settings: AWSTranscribeSTTSettings def __init__( diff --git a/src/pipecat/services/aws/tts.py b/src/pipecat/services/aws/tts.py index 12eab245c..47b12429a 100644 --- a/src/pipecat/services/aws/tts.py +++ b/src/pipecat/services/aws/tts.py @@ -148,6 +148,7 @@ class AWSPollyTTSService(TTSService): options including prosody controls. """ + Settings = AWSPollyTTSSettings _settings: AWSPollyTTSSettings class InputParams(BaseModel): @@ -382,6 +383,8 @@ class PollyTTSService(AWSPollyTTSService): """ + Settings = AWSPollyTTSSettings + def __init__(self, **kwargs): """Initialize the deprecated PollyTTSService. diff --git a/src/pipecat/services/azure/image.py b/src/pipecat/services/azure/image.py index 28ac68bf9..1b62fbfe4 100644 --- a/src/pipecat/services/azure/image.py +++ b/src/pipecat/services/azure/image.py @@ -43,6 +43,7 @@ class AzureImageGenServiceREST(ImageGenService): and automatic image download and processing. """ + Settings = AzureImageGenSettings _settings: AzureImageGenSettings def __init__( diff --git a/src/pipecat/services/azure/llm.py b/src/pipecat/services/azure/llm.py index 1c9960e8a..322ff0b3e 100644 --- a/src/pipecat/services/azure/llm.py +++ b/src/pipecat/services/azure/llm.py @@ -31,6 +31,8 @@ class AzureLLMService(OpenAILLMService): maintaining full compatibility with OpenAI's interface and functionality. """ + Settings = AzureLLMSettings + def __init__( self, *, diff --git a/src/pipecat/services/azure/realtime/llm.py b/src/pipecat/services/azure/realtime/llm.py index bf91d484e..c791af94d 100644 --- a/src/pipecat/services/azure/realtime/llm.py +++ b/src/pipecat/services/azure/realtime/llm.py @@ -35,6 +35,7 @@ class AzureRealtimeLLMService(OpenAIRealtimeLLMService): real-time audio and text communication capabilities as the base OpenAI service. """ + Settings = AzureRealtimeLLMSettings _settings: AzureRealtimeLLMSettings def __init__( diff --git a/src/pipecat/services/azure/stt.py b/src/pipecat/services/azure/stt.py index f940ea9c0..0588cc6cc 100644 --- a/src/pipecat/services/azure/stt.py +++ b/src/pipecat/services/azure/stt.py @@ -66,6 +66,7 @@ class AzureSTTService(STTService): provides real-time transcription results with timing information. """ + Settings = AzureSTTSettings _settings: AzureSTTSettings def __init__( diff --git a/src/pipecat/services/azure/tts.py b/src/pipecat/services/azure/tts.py index c2884b860..1c74c7655 100644 --- a/src/pipecat/services/azure/tts.py +++ b/src/pipecat/services/azure/tts.py @@ -246,6 +246,8 @@ class AzureTTSService(TTSService, AzureBaseTTSService): available for lower latency playback and accurate word-level synchronization. """ + Settings = AzureTTSSettings + def __init__( self, *, @@ -749,6 +751,8 @@ class AzureHttpTTSService(TTSService, AzureBaseTTSService): required and simpler integration is preferred. """ + Settings = AzureTTSSettings + def __init__( self, *, diff --git a/src/pipecat/services/camb/tts.py b/src/pipecat/services/camb/tts.py index 12b33974e..9918b2320 100644 --- a/src/pipecat/services/camb/tts.py +++ b/src/pipecat/services/camb/tts.py @@ -168,6 +168,7 @@ class CambTTSService(TTSService): ) """ + Settings = CambTTSSettings _settings: CambTTSSettings class InputParams(BaseModel): diff --git a/src/pipecat/services/cartesia/stt.py b/src/pipecat/services/cartesia/stt.py index cdf46d50a..9c0924827 100644 --- a/src/pipecat/services/cartesia/stt.py +++ b/src/pipecat/services/cartesia/stt.py @@ -146,6 +146,7 @@ class CartesiaSTTService(WebsocketSTTService): See: https://docs.cartesia.ai/api-reference/stt/stt """ + Settings = CartesiaSTTSettings _settings: CartesiaSTTSettings def __init__( diff --git a/src/pipecat/services/cartesia/tts.py b/src/pipecat/services/cartesia/tts.py index c71a84f41..d41f341ca 100644 --- a/src/pipecat/services/cartesia/tts.py +++ b/src/pipecat/services/cartesia/tts.py @@ -210,6 +210,7 @@ class CartesiaTTSService(WebsocketTTSService): customization options including generation configuration. """ + Settings = CartesiaTTSSettings _settings: CartesiaTTSSettings class InputParams(BaseModel): @@ -681,6 +682,7 @@ class CartesiaHttpTTSService(TTSService): integration is preferred. """ + Settings = CartesiaTTSSettings _settings: CartesiaTTSSettings class InputParams(BaseModel): diff --git a/src/pipecat/services/cerebras/llm.py b/src/pipecat/services/cerebras/llm.py index d8dcf3d08..5d4bc2d14 100644 --- a/src/pipecat/services/cerebras/llm.py +++ b/src/pipecat/services/cerebras/llm.py @@ -31,6 +31,7 @@ class CerebrasLLMService(OpenAILLMService): maintaining full compatibility with OpenAI's interface and functionality. """ + Settings = CerebrasLLMSettings _settings: CerebrasLLMSettings def __init__( diff --git a/src/pipecat/services/deepgram/flux/stt.py b/src/pipecat/services/deepgram/flux/stt.py index 1ed28a749..d31c42d9b 100644 --- a/src/pipecat/services/deepgram/flux/stt.py +++ b/src/pipecat/services/deepgram/flux/stt.py @@ -113,6 +113,7 @@ class DeepgramFluxSTTService(WebsocketSTTService): ... """ + Settings = DeepgramFluxSTTSettings _settings: DeepgramFluxSTTSettings class InputParams(BaseModel): diff --git a/src/pipecat/services/deepgram/sagemaker/stt.py b/src/pipecat/services/deepgram/sagemaker/stt.py index 4f29b227f..812a2701e 100644 --- a/src/pipecat/services/deepgram/sagemaker/stt.py +++ b/src/pipecat/services/deepgram/sagemaker/stt.py @@ -78,6 +78,7 @@ class DeepgramSageMakerSTTService(STTService): ) """ + Settings = DeepgramSageMakerSTTSettings _settings: DeepgramSageMakerSTTSettings def __init__( diff --git a/src/pipecat/services/deepgram/sagemaker/tts.py b/src/pipecat/services/deepgram/sagemaker/tts.py index fa5b1cebd..a40f56713 100644 --- a/src/pipecat/services/deepgram/sagemaker/tts.py +++ b/src/pipecat/services/deepgram/sagemaker/tts.py @@ -67,6 +67,7 @@ class DeepgramSageMakerTTSService(TTSService): ) """ + Settings = DeepgramSageMakerTTSSettings _settings: DeepgramSageMakerTTSSettings def __init__( diff --git a/src/pipecat/services/deepgram/stt.py b/src/pipecat/services/deepgram/stt.py index 14020631b..d8f782f5d 100644 --- a/src/pipecat/services/deepgram/stt.py +++ b/src/pipecat/services/deepgram/stt.py @@ -266,6 +266,7 @@ class DeepgramSTTService(STTService): ... """ + Settings = DeepgramSTTSettings _settings: DeepgramSTTSettings def __init__( diff --git a/src/pipecat/services/deepgram/tts.py b/src/pipecat/services/deepgram/tts.py index 5d6e5ffdc..89bc9ae97 100644 --- a/src/pipecat/services/deepgram/tts.py +++ b/src/pipecat/services/deepgram/tts.py @@ -58,6 +58,7 @@ class DeepgramTTSService(WebsocketTTSService): message for conversational AI use cases. """ + Settings = DeepgramTTSSettings _settings: DeepgramTTSSettings SUPPORTED_ENCODINGS = ("linear16", "mulaw", "alaw") @@ -381,6 +382,7 @@ class DeepgramHttpTTSService(TTSService): configurable sample rates and quality settings. """ + Settings = DeepgramTTSSettings _settings: DeepgramTTSSettings def __init__( diff --git a/src/pipecat/services/deepseek/llm.py b/src/pipecat/services/deepseek/llm.py index 2286a98b2..8fc4b5db8 100644 --- a/src/pipecat/services/deepseek/llm.py +++ b/src/pipecat/services/deepseek/llm.py @@ -31,6 +31,7 @@ class DeepSeekLLMService(OpenAILLMService): maintaining full compatibility with OpenAI's interface and functionality. """ + Settings = DeepSeekLLMSettings _settings: DeepSeekLLMSettings def __init__( diff --git a/src/pipecat/services/elevenlabs/stt.py b/src/pipecat/services/elevenlabs/stt.py index dff501d22..76e854ade 100644 --- a/src/pipecat/services/elevenlabs/stt.py +++ b/src/pipecat/services/elevenlabs/stt.py @@ -216,6 +216,7 @@ class ElevenLabsSTTService(SegmentedSTTService): The service uploads audio files to ElevenLabs and receives transcription results directly. """ + Settings = ElevenLabsSTTSettings _settings: ElevenLabsSTTSettings class InputParams(BaseModel): @@ -448,6 +449,7 @@ class ElevenLabsRealtimeSTTService(WebsocketSTTService): commit transcript segments, providing consistency with other STT services. """ + Settings = ElevenLabsRealtimeSTTSettings _settings: ElevenLabsRealtimeSTTSettings class InputParams(BaseModel): diff --git a/src/pipecat/services/elevenlabs/tts.py b/src/pipecat/services/elevenlabs/tts.py index ae413fd3b..01f3cd516 100644 --- a/src/pipecat/services/elevenlabs/tts.py +++ b/src/pipecat/services/elevenlabs/tts.py @@ -316,6 +316,7 @@ class ElevenLabsTTSService(WebsocketTTSService): customization options including stability, similarity boost, and speed controls. """ + Settings = ElevenLabsTTSSettings _settings: ElevenLabsTTSSettings class InputParams(BaseModel): @@ -904,6 +905,7 @@ class ElevenLabsHttpTTSService(TTSService): connection is not required or desired. """ + Settings = ElevenLabsHttpTTSSettings _settings: ElevenLabsHttpTTSSettings class InputParams(BaseModel): diff --git a/src/pipecat/services/fal/image.py b/src/pipecat/services/fal/image.py index c6fb81003..cb4d646ba 100644 --- a/src/pipecat/services/fal/image.py +++ b/src/pipecat/services/fal/image.py @@ -70,6 +70,9 @@ class FalImageGenService(ImageGenService): parameters for image quality, safety, and format options. """ + Settings = FalImageGenSettings + _settings: FalImageGenSettings + class InputParams(BaseModel): """Input parameters for Fal.ai image generation. diff --git a/src/pipecat/services/fal/stt.py b/src/pipecat/services/fal/stt.py index 92e97d381..692878bf6 100644 --- a/src/pipecat/services/fal/stt.py +++ b/src/pipecat/services/fal/stt.py @@ -155,6 +155,7 @@ class FalSTTService(SegmentedSTTService): segments. It inherits from SegmentedSTTService to handle audio buffering and speech detection. """ + Settings = FalSTTSettings _settings: FalSTTSettings class InputParams(BaseModel): diff --git a/src/pipecat/services/fireworks/llm.py b/src/pipecat/services/fireworks/llm.py index cd7e91504..118090be9 100644 --- a/src/pipecat/services/fireworks/llm.py +++ b/src/pipecat/services/fireworks/llm.py @@ -31,6 +31,7 @@ class FireworksLLMService(OpenAILLMService): maintaining full compatibility with OpenAI's interface and functionality. """ + Settings = FireworksLLMSettings _settings: FireworksLLMSettings def __init__( diff --git a/src/pipecat/services/fish/tts.py b/src/pipecat/services/fish/tts.py index 88e0cc8dd..4974dfa37 100644 --- a/src/pipecat/services/fish/tts.py +++ b/src/pipecat/services/fish/tts.py @@ -84,6 +84,7 @@ class FishAudioTTSService(InterruptibleTTSService): audio generation with interruption handling. """ + Settings = FishAudioTTSSettings _settings: FishAudioTTSSettings class InputParams(BaseModel): diff --git a/src/pipecat/services/gladia/stt.py b/src/pipecat/services/gladia/stt.py index 144f37fb2..fc09d94fc 100644 --- a/src/pipecat/services/gladia/stt.py +++ b/src/pipecat/services/gladia/stt.py @@ -230,6 +230,7 @@ class GladiaSTTService(WebsocketSTTService): Use :class:`~pipecat.services.gladia.config.GladiaInputParams` directly instead. """ + Settings = GladiaSTTSettings _settings: GladiaSTTSettings # Maintain backward compatibility diff --git a/src/pipecat/services/google/gemini_live/llm.py b/src/pipecat/services/google/gemini_live/llm.py index 58dcd2da8..c25caafdd 100644 --- a/src/pipecat/services/google/gemini_live/llm.py +++ b/src/pipecat/services/google/gemini_live/llm.py @@ -642,6 +642,7 @@ class GeminiLiveLLMService(LLMService): responses, and tool usage. """ + Settings = GeminiLiveLLMSettings _settings: GeminiLiveLLMSettings # Overriding the default adapter to use the Gemini one. diff --git a/src/pipecat/services/google/gemini_live/llm_vertex.py b/src/pipecat/services/google/gemini_live/llm_vertex.py index 09aaeebbb..cdfde1660 100644 --- a/src/pipecat/services/google/gemini_live/llm_vertex.py +++ b/src/pipecat/services/google/gemini_live/llm_vertex.py @@ -57,6 +57,7 @@ class GeminiLiveVertexLLMService(GeminiLiveLLMService): responses, and tool usage. """ + Settings = GeminiLiveVertexLLMSettings _settings: GeminiLiveVertexLLMSettings def __init__( diff --git a/src/pipecat/services/google/image.py b/src/pipecat/services/google/image.py index 4c351cc6e..5cf37aa4e 100644 --- a/src/pipecat/services/google/image.py +++ b/src/pipecat/services/google/image.py @@ -59,6 +59,9 @@ class GoogleImageGenService(ImageGenService): prompting for enhanced control over generated content. """ + Settings = GoogleImageGenSettings + _settings: GoogleImageGenSettings + class InputParams(BaseModel): """Configuration parameters for Google image generation. @@ -75,8 +78,6 @@ class GoogleImageGenService(ImageGenService): model: str = Field(default="imagen-3.0-generate-002") negative_prompt: Optional[str] = Field(default=None) - _settings: GoogleImageGenSettings - def __init__( self, *, diff --git a/src/pipecat/services/google/llm.py b/src/pipecat/services/google/llm.py index 06f47bc2e..198e612f0 100644 --- a/src/pipecat/services/google/llm.py +++ b/src/pipecat/services/google/llm.py @@ -743,6 +743,7 @@ class GoogleLLMService(LLMService): expected by the Google AI model. """ + Settings = GoogleLLMSettings _settings: GoogleLLMSettings # Overriding the default adapter to use the Gemini one. diff --git a/src/pipecat/services/google/llm_openai.py b/src/pipecat/services/google/llm_openai.py index 75fc6c54c..cd5e0f060 100644 --- a/src/pipecat/services/google/llm_openai.py +++ b/src/pipecat/services/google/llm_openai.py @@ -58,6 +58,7 @@ class GoogleLLMOpenAIBetaService(OpenAILLMService): https://ai.google.dev/gemini-api/docs/openai """ + Settings = GoogleOpenAILLMSettings _settings: GoogleOpenAILLMSettings def __init__( diff --git a/src/pipecat/services/google/llm_vertex.py b/src/pipecat/services/google/llm_vertex.py index e40f15de6..3901b5d50 100644 --- a/src/pipecat/services/google/llm_vertex.py +++ b/src/pipecat/services/google/llm_vertex.py @@ -59,6 +59,7 @@ class GoogleVertexLLMService(GoogleLLMService): https://cloud.google.com/vertex-ai/generative-ai/docs/model-reference/inference """ + Settings = GoogleVertexLLMSettings _settings: GoogleVertexLLMSettings class InputParams(GoogleLLMService.InputParams): diff --git a/src/pipecat/services/google/stt.py b/src/pipecat/services/google/stt.py index 131d0e9d1..70e51ac3c 100644 --- a/src/pipecat/services/google/stt.py +++ b/src/pipecat/services/google/stt.py @@ -414,6 +414,7 @@ class GoogleSTTService(STTService): ValueError: If project ID is not found in credentials. """ + Settings = GoogleSTTSettings _settings: GoogleSTTSettings # Google Cloud's STT service has a connection time limit of 5 minutes per stream. diff --git a/src/pipecat/services/google/tts.py b/src/pipecat/services/google/tts.py index 984989fa5..d3f7879ad 100644 --- a/src/pipecat/services/google/tts.py +++ b/src/pipecat/services/google/tts.py @@ -558,6 +558,7 @@ class GoogleHttpTTSService(TTSService): Chirp and Journey voices don't support SSML and will use plain text input. """ + Settings = GoogleHttpTTSSettings _settings: GoogleHttpTTSSettings class InputParams(BaseModel): @@ -1020,6 +1021,7 @@ class GoogleTTSService(GoogleBaseTTSService): ) """ + Settings = GoogleTTSSettings _settings: GoogleTTSSettings class InputParams(BaseModel): @@ -1198,6 +1200,7 @@ class GeminiTTSService(GoogleBaseTTSService): ) """ + Settings = GeminiTTSSettings _settings: GeminiTTSSettings GOOGLE_SAMPLE_RATE = 24000 # Google TTS always outputs at 24kHz diff --git a/src/pipecat/services/gradium/stt.py b/src/pipecat/services/gradium/stt.py index 814d478e4..3fddf0470 100644 --- a/src/pipecat/services/gradium/stt.py +++ b/src/pipecat/services/gradium/stt.py @@ -88,6 +88,7 @@ class GradiumSTTService(WebsocketSTTService): for audio processing and connection management. """ + Settings = GradiumSTTSettings _settings: GradiumSTTSettings class InputParams(BaseModel): diff --git a/src/pipecat/services/gradium/tts.py b/src/pipecat/services/gradium/tts.py index 3dd663185..03b4d7008 100644 --- a/src/pipecat/services/gradium/tts.py +++ b/src/pipecat/services/gradium/tts.py @@ -47,6 +47,7 @@ class GradiumTTSSettings(TTSSettings): class GradiumTTSService(WebsocketTTSService): """Text-to-Speech service using Gradium's websocket API.""" + Settings = GradiumTTSSettings _settings: GradiumTTSSettings class InputParams(BaseModel): diff --git a/src/pipecat/services/grok/llm.py b/src/pipecat/services/grok/llm.py index 144d91a16..255ee2cf5 100644 --- a/src/pipecat/services/grok/llm.py +++ b/src/pipecat/services/grok/llm.py @@ -86,6 +86,7 @@ class GrokLLMService(OpenAILLMService): processing and reports final totals. """ + Settings = GrokLLMSettings _settings: GrokLLMSettings def __init__( diff --git a/src/pipecat/services/grok/realtime/llm.py b/src/pipecat/services/grok/realtime/llm.py index 7e252ebf5..30061af4a 100644 --- a/src/pipecat/services/grok/realtime/llm.py +++ b/src/pipecat/services/grok/realtime/llm.py @@ -202,6 +202,7 @@ class GrokRealtimeLLMService(LLMService): - Server-side VAD (Voice Activity Detection) """ + Settings = GrokRealtimeLLMSettings _settings: GrokRealtimeLLMSettings # Use the Grok-specific adapter diff --git a/src/pipecat/services/groq/llm.py b/src/pipecat/services/groq/llm.py index e86c59391..6669c385a 100644 --- a/src/pipecat/services/groq/llm.py +++ b/src/pipecat/services/groq/llm.py @@ -30,6 +30,7 @@ class GroqLLMService(OpenAILLMService): maintaining full compatibility with OpenAI's interface and functionality. """ + Settings = GroqLLMSettings _settings: GroqLLMSettings def __init__( diff --git a/src/pipecat/services/groq/stt.py b/src/pipecat/services/groq/stt.py index 1733831c8..b5d59181a 100644 --- a/src/pipecat/services/groq/stt.py +++ b/src/pipecat/services/groq/stt.py @@ -37,6 +37,7 @@ class GroqSTTService(BaseWhisperSTTService): set via the api_key parameter or GROQ_API_KEY environment variable. """ + Settings = GroqSTTSettings _settings: GroqSTTSettings def __init__( diff --git a/src/pipecat/services/groq/tts.py b/src/pipecat/services/groq/tts.py index 4e56312e5..bb39a9067 100644 --- a/src/pipecat/services/groq/tts.py +++ b/src/pipecat/services/groq/tts.py @@ -51,6 +51,7 @@ class GroqTTSService(TTSService): and output formats. """ + Settings = GroqTTSSettings _settings: GroqTTSSettings class InputParams(BaseModel): diff --git a/src/pipecat/services/heygen/video.py b/src/pipecat/services/heygen/video.py index 18df8ac60..2c42dfc6b 100644 --- a/src/pipecat/services/heygen/video.py +++ b/src/pipecat/services/heygen/video.py @@ -82,6 +82,9 @@ class HeyGenVideoService(AIService): Defaults to using the "Shawn_Therapist_public" avatar with "v2" version. """ + Settings = HeyGenVideoSettings + _settings: HeyGenVideoSettings + def __init__( self, *, diff --git a/src/pipecat/services/hume/tts.py b/src/pipecat/services/hume/tts.py index 135806da7..5eb2db646 100644 --- a/src/pipecat/services/hume/tts.py +++ b/src/pipecat/services/hume/tts.py @@ -78,6 +78,7 @@ class HumeTTSService(TTSService): - Provides metrics for Time To First Byte (TTFB) and TTS usage. """ + Settings = HumeTTSSettings _settings: HumeTTSSettings class InputParams(BaseModel): diff --git a/src/pipecat/services/inworld/tts.py b/src/pipecat/services/inworld/tts.py index 17a0e8040..dc09c0481 100644 --- a/src/pipecat/services/inworld/tts.py +++ b/src/pipecat/services/inworld/tts.py @@ -100,6 +100,7 @@ class InworldHttpTTSService(TTSService): Outputs LINEAR16 audio at configurable sample rates with word-level timestamps. """ + Settings = InworldTTSSettings _settings: InworldTTSSettings class InputParams(BaseModel): @@ -487,6 +488,7 @@ class InworldTTSService(WebsocketTTSService): with word-level timestamps. """ + Settings = InworldTTSSettings _settings: InworldTTSSettings class InputParams(BaseModel): diff --git a/src/pipecat/services/kokoro/tts.py b/src/pipecat/services/kokoro/tts.py index bfc39daed..98f181c6f 100644 --- a/src/pipecat/services/kokoro/tts.py +++ b/src/pipecat/services/kokoro/tts.py @@ -101,6 +101,7 @@ class KokoroTTSService(TTSService): Automatically downloads model files on first use. """ + Settings = KokoroTTSSettings _settings: KokoroTTSSettings class InputParams(BaseModel): diff --git a/src/pipecat/services/lmnt/tts.py b/src/pipecat/services/lmnt/tts.py index f6bf46649..46e5e4697 100644 --- a/src/pipecat/services/lmnt/tts.py +++ b/src/pipecat/services/lmnt/tts.py @@ -88,6 +88,7 @@ class LmntTTSService(InterruptibleTTSService): language settings. """ + Settings = LmntTTSSettings _settings: LmntTTSSettings def __init__( diff --git a/src/pipecat/services/minimax/tts.py b/src/pipecat/services/minimax/tts.py index 1edd8bf78..f62e8d46b 100644 --- a/src/pipecat/services/minimax/tts.py +++ b/src/pipecat/services/minimax/tts.py @@ -140,6 +140,7 @@ class MiniMaxHttpTTSService(TTSService): https://www.minimax.io/platform/document/T2A%20V2?key=66719005a427f0c8a5701643 """ + Settings = MiniMaxTTSSettings _settings: MiniMaxTTSSettings class InputParams(BaseModel): diff --git a/src/pipecat/services/mistral/llm.py b/src/pipecat/services/mistral/llm.py index 8389613e0..9e01a76b5 100644 --- a/src/pipecat/services/mistral/llm.py +++ b/src/pipecat/services/mistral/llm.py @@ -33,6 +33,7 @@ class MistralLLMService(OpenAILLMService): maintaining full compatibility with OpenAI's interface and functionality. """ + Settings = MistralLLMSettings _settings: MistralLLMSettings def __init__( diff --git a/src/pipecat/services/moondream/vision.py b/src/pipecat/services/moondream/vision.py index 32b592061..abc344fc5 100644 --- a/src/pipecat/services/moondream/vision.py +++ b/src/pipecat/services/moondream/vision.py @@ -79,6 +79,9 @@ class MoondreamService(VisionService): including CUDA, MPS, and Intel XPU. """ + Settings = MoondreamSettings + _settings: MoondreamSettings + def __init__( self, *, diff --git a/src/pipecat/services/neuphonic/tts.py b/src/pipecat/services/neuphonic/tts.py index 441d222ea..abc33c37e 100644 --- a/src/pipecat/services/neuphonic/tts.py +++ b/src/pipecat/services/neuphonic/tts.py @@ -91,6 +91,7 @@ class NeuphonicTTSService(InterruptibleTTSService): parameters for high-quality speech generation. """ + Settings = NeuphonicTTSSettings _settings: NeuphonicTTSSettings class InputParams(BaseModel): @@ -430,6 +431,7 @@ class NeuphonicHttpTTSService(TTSService): HTTP-based communication over WebSocket connections. """ + Settings = NeuphonicTTSSettings _settings: NeuphonicTTSSettings class InputParams(BaseModel): diff --git a/src/pipecat/services/nvidia/llm.py b/src/pipecat/services/nvidia/llm.py index 65c0880e4..17490f513 100644 --- a/src/pipecat/services/nvidia/llm.py +++ b/src/pipecat/services/nvidia/llm.py @@ -36,6 +36,7 @@ class NvidiaLLMService(OpenAILLMService): in token usage reporting between NIM (incremental) and OpenAI (final summary). """ + Settings = NvidiaLLMSettings _settings: NvidiaLLMSettings def __init__( diff --git a/src/pipecat/services/nvidia/stt.py b/src/pipecat/services/nvidia/stt.py index 3d6d2391e..5935e7846 100644 --- a/src/pipecat/services/nvidia/stt.py +++ b/src/pipecat/services/nvidia/stt.py @@ -125,6 +125,7 @@ class NvidiaSTTService(STTService): processing for low-latency applications. """ + Settings = NvidiaSTTSettings _settings: NvidiaSTTSettings class InputParams(BaseModel): @@ -439,6 +440,7 @@ class NvidiaSegmentedSTTService(SegmentedSTTService): audio buffering and speech detection. """ + Settings = NvidiaSegmentedSTTSettings _settings: NvidiaSegmentedSTTSettings class InputParams(BaseModel): diff --git a/src/pipecat/services/nvidia/tts.py b/src/pipecat/services/nvidia/tts.py index fb701185c..ad39d505b 100644 --- a/src/pipecat/services/nvidia/tts.py +++ b/src/pipecat/services/nvidia/tts.py @@ -61,6 +61,7 @@ class NvidiaTTSService(TTSService): configurable quality settings. """ + Settings = NvidiaTTSSettings _settings: NvidiaTTSSettings class InputParams(BaseModel): diff --git a/src/pipecat/services/ollama/llm.py b/src/pipecat/services/ollama/llm.py index 42b5b00b1..f4d138d78 100644 --- a/src/pipecat/services/ollama/llm.py +++ b/src/pipecat/services/ollama/llm.py @@ -30,6 +30,7 @@ class OLLamaLLMService(OpenAILLMService): providing a compatible interface for running large language models locally. """ + Settings = OllamaLLMSettings _settings: OllamaLLMSettings def __init__( diff --git a/src/pipecat/services/openai/base_llm.py b/src/pipecat/services/openai/base_llm.py index bfeae62a1..5466c75a5 100644 --- a/src/pipecat/services/openai/base_llm.py +++ b/src/pipecat/services/openai/base_llm.py @@ -68,6 +68,7 @@ class BaseOpenAILLMService(LLMService): configurations. """ + Settings = OpenAILLMSettings _settings: OpenAILLMSettings class InputParams(BaseModel): diff --git a/src/pipecat/services/openai/image.py b/src/pipecat/services/openai/image.py index 397d8c3d2..6091863f3 100644 --- a/src/pipecat/services/openai/image.py +++ b/src/pipecat/services/openai/image.py @@ -48,6 +48,7 @@ class OpenAIImageGenService(ImageGenService): with configurable quality and style parameters. """ + Settings = OpenAIImageGenSettings _settings: OpenAIImageGenSettings def __init__( diff --git a/src/pipecat/services/openai/realtime/llm.py b/src/pipecat/services/openai/realtime/llm.py index c25181dd1..4fa3ab604 100644 --- a/src/pipecat/services/openai/realtime/llm.py +++ b/src/pipecat/services/openai/realtime/llm.py @@ -211,6 +211,7 @@ class OpenAIRealtimeLLMService(LLMService): management, and real-time transcription. """ + Settings = OpenAIRealtimeLLMSettings _settings: OpenAIRealtimeLLMSettings # Overriding the default adapter to use the OpenAIRealtimeLLMAdapter one. diff --git a/src/pipecat/services/openai/stt.py b/src/pipecat/services/openai/stt.py index a6d7beb0c..e2f9ec0ee 100644 --- a/src/pipecat/services/openai/stt.py +++ b/src/pipecat/services/openai/stt.py @@ -69,6 +69,7 @@ class OpenAISTTService(BaseWhisperSTTService): set via the api_key parameter or OPENAI_API_KEY environment variable. """ + Settings = OpenAISTTSettings _settings: OpenAISTTSettings def __init__( @@ -224,6 +225,7 @@ class OpenAIRealtimeSTTService(WebsocketSTTService): ) """ + Settings = OpenAIRealtimeSTTSettings _settings: OpenAIRealtimeSTTSettings def __init__( diff --git a/src/pipecat/services/openai/tts.py b/src/pipecat/services/openai/tts.py index 71c04c59f..264475113 100644 --- a/src/pipecat/services/openai/tts.py +++ b/src/pipecat/services/openai/tts.py @@ -81,6 +81,7 @@ class OpenAITTSService(TTSService): speech synthesis with streaming audio output. """ + Settings = OpenAITTSSettings _settings: OpenAITTSSettings OPENAI_SAMPLE_RATE = 24000 # OpenAI TTS always outputs at 24kHz diff --git a/src/pipecat/services/openai_realtime_beta/azure.py b/src/pipecat/services/openai_realtime_beta/azure.py index 55fb7744d..6497e1266 100644 --- a/src/pipecat/services/openai_realtime_beta/azure.py +++ b/src/pipecat/services/openai_realtime_beta/azure.py @@ -42,6 +42,7 @@ class AzureRealtimeBetaLLMService(OpenAIRealtimeBetaLLMService): real-time audio and text communication capabilities as the base OpenAI service. """ + Settings = AzureRealtimeBetaLLMSettings _settings: AzureRealtimeBetaLLMSettings def __init__( diff --git a/src/pipecat/services/openai_realtime_beta/openai.py b/src/pipecat/services/openai_realtime_beta/openai.py index 689ca91a5..51fcc2720 100644 --- a/src/pipecat/services/openai_realtime_beta/openai.py +++ b/src/pipecat/services/openai_realtime_beta/openai.py @@ -111,6 +111,7 @@ class OpenAIRealtimeBetaLLMService(LLMService): management, and real-time transcription. """ + Settings = OpenAIRealtimeBetaLLMSettings _settings: OpenAIRealtimeBetaLLMSettings # Overriding the default adapter to use the OpenAIRealtimeLLMAdapter one. diff --git a/src/pipecat/services/openpipe/llm.py b/src/pipecat/services/openpipe/llm.py index 58840c40d..3fef1e3af 100644 --- a/src/pipecat/services/openpipe/llm.py +++ b/src/pipecat/services/openpipe/llm.py @@ -43,6 +43,7 @@ class OpenPipeLLMService(OpenAILLMService): for model training and evaluation. """ + Settings = OpenPipeLLMSettings _settings: OpenPipeLLMSettings def __init__( diff --git a/src/pipecat/services/openrouter/llm.py b/src/pipecat/services/openrouter/llm.py index 411eca91e..d57c5cf24 100644 --- a/src/pipecat/services/openrouter/llm.py +++ b/src/pipecat/services/openrouter/llm.py @@ -34,6 +34,7 @@ class OpenRouterLLMService(OpenAILLMService): maintaining full compatibility with OpenAI's interface and functionality. """ + Settings = OpenRouterLLMSettings _settings: OpenRouterLLMSettings def __init__( diff --git a/src/pipecat/services/perplexity/llm.py b/src/pipecat/services/perplexity/llm.py index 614e6ad9b..b13fb20f0 100644 --- a/src/pipecat/services/perplexity/llm.py +++ b/src/pipecat/services/perplexity/llm.py @@ -38,6 +38,7 @@ class PerplexityLLMService(OpenAILLMService): in token usage reporting between Perplexity (incremental) and OpenAI (final summary). """ + Settings = PerplexityLLMSettings _settings: PerplexityLLMSettings def __init__( diff --git a/src/pipecat/services/piper/tts.py b/src/pipecat/services/piper/tts.py index fb7b627cd..9a44b8e21 100644 --- a/src/pipecat/services/piper/tts.py +++ b/src/pipecat/services/piper/tts.py @@ -46,6 +46,7 @@ class PiperTTSService(TTSService): match the configured sample rate. """ + Settings = PiperTTSSettings _settings: PiperTTSSettings def __init__( @@ -199,6 +200,7 @@ class PiperHttpTTSService(TTSService): rates and automatic WAV header removal. """ + Settings = PiperHttpTTSSettings _settings: PiperHttpTTSSettings def __init__( diff --git a/src/pipecat/services/qwen/llm.py b/src/pipecat/services/qwen/llm.py index ba2b734c7..d145f8339 100644 --- a/src/pipecat/services/qwen/llm.py +++ b/src/pipecat/services/qwen/llm.py @@ -30,6 +30,7 @@ class QwenLLMService(OpenAILLMService): maintaining full compatibility with OpenAI's interface and functionality. """ + Settings = QwenLLMSettings _settings: QwenLLMSettings def __init__( diff --git a/src/pipecat/services/resembleai/tts.py b/src/pipecat/services/resembleai/tts.py index 9713cea44..31977ca0b 100644 --- a/src/pipecat/services/resembleai/tts.py +++ b/src/pipecat/services/resembleai/tts.py @@ -51,6 +51,7 @@ class ResembleAITTSService(WebsocketTTSService): multiple simultaneous synthesis requests with proper interruption support. """ + Settings = ResembleAITTSSettings _settings: ResembleAITTSSettings def __init__( diff --git a/src/pipecat/services/rime/tts.py b/src/pipecat/services/rime/tts.py index 8a9186c59..15cc8b88a 100644 --- a/src/pipecat/services/rime/tts.py +++ b/src/pipecat/services/rime/tts.py @@ -131,6 +131,7 @@ class RimeTTSService(WebsocketTTSService): within a turn. """ + Settings = RimeTTSSettings _settings: RimeTTSSettings class InputParams(BaseModel): @@ -661,6 +662,7 @@ class RimeHttpTTSService(TTSService): Suitable for use cases where streaming is not required. """ + Settings = RimeTTSSettings _settings: RimeTTSSettings class InputParams(BaseModel): @@ -885,6 +887,7 @@ class RimeNonJsonTTSService(InterruptibleTTSService): accepts and returns non-JSON messages. """ + Settings = RimeNonJsonTTSSettings _settings: RimeNonJsonTTSSettings class InputParams(BaseModel): diff --git a/src/pipecat/services/sambanova/llm.py b/src/pipecat/services/sambanova/llm.py index e56f2576b..629c3d4c5 100644 --- a/src/pipecat/services/sambanova/llm.py +++ b/src/pipecat/services/sambanova/llm.py @@ -42,6 +42,7 @@ class SambaNovaLLMService(OpenAILLMService): # type: ignore maintaining full compatibility with OpenAI's interface and functionality. """ + Settings = SambaNovaLLMSettings _settings: SambaNovaLLMSettings def __init__( diff --git a/src/pipecat/services/sambanova/stt.py b/src/pipecat/services/sambanova/stt.py index 822c44da9..c273b67eb 100644 --- a/src/pipecat/services/sambanova/stt.py +++ b/src/pipecat/services/sambanova/stt.py @@ -35,6 +35,8 @@ class SambaNovaSTTService(BaseWhisperSTTService): # type: ignore Requires a SambaNova API key set via the api_key parameter or SAMBANOVA_API_KEY environment variable. """ + Settings = SambaNovaSTTSettings + def __init__( self, *, diff --git a/src/pipecat/services/sarvam/stt.py b/src/pipecat/services/sarvam/stt.py index cd6d19ac0..429973838 100644 --- a/src/pipecat/services/sarvam/stt.py +++ b/src/pipecat/services/sarvam/stt.py @@ -171,6 +171,7 @@ class SarvamSTTService(STTService): ... """ + Settings = SarvamSTTSettings _settings: SarvamSTTSettings class InputParams(BaseModel): diff --git a/src/pipecat/services/sarvam/tts.py b/src/pipecat/services/sarvam/tts.py index c0a74b198..639a860ac 100644 --- a/src/pipecat/services/sarvam/tts.py +++ b/src/pipecat/services/sarvam/tts.py @@ -351,6 +351,7 @@ class SarvamHttpTTSService(TTSService): ) """ + Settings = SarvamHttpTTSSettings _settings: SarvamHttpTTSSettings class InputParams(BaseModel): @@ -717,6 +718,7 @@ class SarvamTTSService(InterruptibleTTSService): See https://docs.sarvam.ai/api-reference-docs/text-to-speech/stream for API details. """ + Settings = SarvamTTSSettings _settings: SarvamTTSSettings class InputParams(BaseModel): diff --git a/src/pipecat/services/soniox/stt.py b/src/pipecat/services/soniox/stt.py index 613e35a28..6e5a8f62c 100644 --- a/src/pipecat/services/soniox/stt.py +++ b/src/pipecat/services/soniox/stt.py @@ -174,6 +174,7 @@ class SonioxSTTService(WebsocketSTTService): For complete API documentation, see: https://soniox.com/docs/speech-to-text/api-reference/websocket-api """ + Settings = SonioxSTTSettings _settings: SonioxSTTSettings def __init__( diff --git a/src/pipecat/services/speechmatics/stt.py b/src/pipecat/services/speechmatics/stt.py index e3100a2ad..aaff90900 100644 --- a/src/pipecat/services/speechmatics/stt.py +++ b/src/pipecat/services/speechmatics/stt.py @@ -175,6 +175,7 @@ class SpeechmaticsSTTService(STTService): ... """ + Settings = SpeechmaticsSTTSettings _settings: SpeechmaticsSTTSettings # Export related classes as class attributes diff --git a/src/pipecat/services/speechmatics/tts.py b/src/pipecat/services/speechmatics/tts.py index a93d9c78a..5f0aed7f3 100644 --- a/src/pipecat/services/speechmatics/tts.py +++ b/src/pipecat/services/speechmatics/tts.py @@ -53,6 +53,7 @@ class SpeechmaticsTTSService(TTSService): It converts text to speech and returns raw PCM audio data for real-time playback. """ + Settings = SpeechmaticsTTSSettings _settings: SpeechmaticsTTSSettings SPEECHMATICS_SAMPLE_RATE = 16000 diff --git a/src/pipecat/services/tavus/video.py b/src/pipecat/services/tavus/video.py index 4a7211033..3d5946e54 100644 --- a/src/pipecat/services/tavus/video.py +++ b/src/pipecat/services/tavus/video.py @@ -59,6 +59,9 @@ class TavusVideoService(AIService): - User room: Contains the Pipecat Bot and the user """ + Settings = TavusVideoSettings + _settings: TavusVideoSettings + def __init__( self, *, diff --git a/src/pipecat/services/together/llm.py b/src/pipecat/services/together/llm.py index 38089addc..21663206e 100644 --- a/src/pipecat/services/together/llm.py +++ b/src/pipecat/services/together/llm.py @@ -30,6 +30,7 @@ class TogetherLLMService(OpenAILLMService): maintaining full compatibility with OpenAI's interface and functionality. """ + Settings = TogetherLLMSettings _settings: TogetherLLMSettings def __init__( diff --git a/src/pipecat/services/ultravox/llm.py b/src/pipecat/services/ultravox/llm.py index eccc1a864..bfd34ceae 100644 --- a/src/pipecat/services/ultravox/llm.py +++ b/src/pipecat/services/ultravox/llm.py @@ -166,6 +166,7 @@ class UltravoxRealtimeLLMService(LLMService): by the model and may not always align with its understanding of user input. """ + Settings = UltravoxRealtimeLLMSettings _settings: UltravoxRealtimeLLMSettings def __init__( diff --git a/src/pipecat/services/whisper/base_stt.py b/src/pipecat/services/whisper/base_stt.py index a3bb98548..869f92a55 100644 --- a/src/pipecat/services/whisper/base_stt.py +++ b/src/pipecat/services/whisper/base_stt.py @@ -122,6 +122,7 @@ class BaseWhisperSTTService(SegmentedSTTService): including metrics generation and error handling. """ + Settings = BaseWhisperSTTSettings _settings: BaseWhisperSTTSettings def __init__( diff --git a/src/pipecat/services/whisper/stt.py b/src/pipecat/services/whisper/stt.py index ab5354e2c..b5971ce9a 100644 --- a/src/pipecat/services/whisper/stt.py +++ b/src/pipecat/services/whisper/stt.py @@ -207,6 +207,7 @@ class WhisperSTTService(SegmentedSTTService): segments. It supports multiple languages and various model sizes. """ + Settings = WhisperSTTSettings _settings: WhisperSTTSettings def __init__( @@ -380,6 +381,7 @@ class WhisperSTTServiceMLX(WhisperSTTService): segments. It's optimized for Apple Silicon and supports multiple languages and quantizations. """ + Settings = WhisperMLXSTTSettings _settings: WhisperMLXSTTSettings def __init__( diff --git a/src/pipecat/services/xtts/tts.py b/src/pipecat/services/xtts/tts.py index 78ac6dfb8..32c2781f2 100644 --- a/src/pipecat/services/xtts/tts.py +++ b/src/pipecat/services/xtts/tts.py @@ -83,6 +83,7 @@ class XTTSService(TTSService): studio speakers configuration. """ + Settings = XTTSTTSSettings _settings: XTTSTTSSettings def __init__( From c5da3cf2bdaf79e76d3d905803836a30701b4631 Mon Sep 17 00:00:00 2001 From: Mark Backman Date: Sat, 7 Mar 2026 08:37:27 -0500 Subject: [PATCH 0857/1060] Add on-the-fly Configure support for Deepgram Flux STT Wire up the existing settings update infrastructure to send a Configure WebSocket message when keyterm, eot_threshold, eager_eot_threshold, or eot_timeout_ms change mid-stream, avoiding a full reconnect. --- .../55a-update-settings-deepgram-flux-stt.py | 13 +++++ src/pipecat/services/deepgram/flux/stt.py | 51 ++++++++++++++++--- 2 files changed, 58 insertions(+), 6 deletions(-) diff --git a/examples/foundational/55a-update-settings-deepgram-flux-stt.py b/examples/foundational/55a-update-settings-deepgram-flux-stt.py index 72d9b5638..11254127d 100644 --- a/examples/foundational/55a-update-settings-deepgram-flux-stt.py +++ b/examples/foundational/55a-update-settings-deepgram-flux-stt.py @@ -100,6 +100,19 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): context.add_message({"role": "user", "content": "Please introduce yourself to the user."}) await task.queue_frames([LLMRunFrame()]) + # Update configure-able fields mid-stream (sent via Configure message, + # no reconnect needed). + await asyncio.sleep(10) + logger.info("Updating Deepgram Flux STT settings: eot_threshold, keyterm") + await task.queue_frame( + STTUpdateSettingsFrame( + delta=DeepgramFluxSTTSettings( + eot_threshold=0.8, + keyterm=["Pipecat", "Deepgram"], + ) + ) + ) + await asyncio.sleep(10) logger.info("Updating Deepgram Flux STT settings: language=es") await task.queue_frame( diff --git a/src/pipecat/services/deepgram/flux/stt.py b/src/pipecat/services/deepgram/flux/stt.py index 1ed28a749..e87bfc2d7 100644 --- a/src/pipecat/services/deepgram/flux/stt.py +++ b/src/pipecat/services/deepgram/flux/stt.py @@ -53,6 +53,8 @@ class FluxMessageType(str, Enum): RECEIVE_CONNECTED = "Connected" RECEIVE_FATAL_ERROR = "Error" TURN_INFO = "TurnInfo" + CONFIGURE_SUCCESS = "ConfigureSuccess" + CONFIGURE_FAILURE = "ConfigureFailure" class FluxEventType(str, Enum): @@ -114,6 +116,7 @@ class DeepgramFluxSTTService(WebsocketSTTService): """ _settings: DeepgramFluxSTTSettings + _CONFIGURE_FIELDS = {"keyterm", "eot_threshold", "eager_eot_threshold", "eot_timeout_ms"} class InputParams(BaseModel): """Configuration parameters for Deepgram Flux API. @@ -409,6 +412,33 @@ class DeepgramFluxSTTService(WebsocketSTTService): except Exception as e: await self.push_error(error_msg=f"Error sending closeStream: {e}", exception=e) + async def _send_configure(self, fields: set[str]): + """Send a Configure control message to update settings mid-stream. + + Builds a Configure JSON message containing only the fields that changed + and sends it over the existing WebSocket connection. + + Args: + fields: Set of changed field names to include in the message. + """ + message: dict[str, Any] = {"type": "Configure"} + + if "keyterm" in fields: + message["keyterms"] = self._settings.keyterm + + thresholds: dict[str, Any] = {} + if "eot_threshold" in fields: + thresholds["eot_threshold"] = self._settings.eot_threshold + if "eager_eot_threshold" in fields: + thresholds["eager_eot_threshold"] = self._settings.eager_eot_threshold + if "eot_timeout_ms" in fields: + thresholds["eot_timeout_ms"] = self._settings.eot_timeout_ms + if thresholds: + message["thresholds"] = thresholds + + logger.debug(f"{self}: sending Configure message: {message}") + await self._websocket.send(json.dumps(message)) + def can_generate_metrics(self) -> bool: """Check if this service can generate processing metrics. @@ -420,19 +450,20 @@ class DeepgramFluxSTTService(WebsocketSTTService): async def _update_settings(self, delta: DeepgramFluxSTTSettings) -> dict[str, Any]: """Apply a settings delta. - Settings are stored but not applied to the active connection. + Configure-able fields (keyterm, eot_threshold, eager_eot_threshold, + eot_timeout_ms) are sent to Deepgram via a Configure WebSocket message. + Other fields are stored but cannot be applied to the active connection. """ changed = await super()._update_settings(delta) if not changed: return changed - # TODO: someday we could reconnect here to apply updated settings. - # Code might look something like the below: - # await self._disconnect() - # await self._connect() + configure_fields = changed.keys() & self._CONFIGURE_FIELDS + if configure_fields and self._websocket and self._websocket.state is State.OPEN: + await self._send_configure(configure_fields) - self._warn_unhandled_updated_settings(changed) + self._warn_unhandled_updated_settings(changed.keys() - self._CONFIGURE_FIELDS) return changed @@ -629,6 +660,14 @@ class DeepgramFluxSTTService(WebsocketSTTService): await self._handle_fatal_error(data) case FluxMessageType.TURN_INFO: await self._handle_turn_info(data) + case FluxMessageType.CONFIGURE_SUCCESS: + logger.info(f"{self}: Configure accepted: {data}") + case FluxMessageType.CONFIGURE_FAILURE: + error_code = data.get("error_code", "unknown") + description = data.get("description", "no description") + error_msg = f"Configure rejected: [{error_code}] {description}" + logger.warning(f"{self}: {error_msg}") + await self.push_error(error_msg=error_msg) async def _handle_connection_established(self): """Handle successful connection establishment to Deepgram Flux. From 4ebdacdea23ab95949d79e43c79f6064586ac229 Mon Sep 17 00:00:00 2001 From: Mark Backman Date: Sat, 7 Mar 2026 08:48:11 -0500 Subject: [PATCH 0858/1060] Add changelog for #3953 --- changelog/3953.added.md | 1 + 1 file changed, 1 insertion(+) create mode 100644 changelog/3953.added.md diff --git a/changelog/3953.added.md b/changelog/3953.added.md new file mode 100644 index 000000000..d540ff125 --- /dev/null +++ b/changelog/3953.added.md @@ -0,0 +1 @@ +- Added on-the-fly `Configure` support for `DeepgramFluxSTTService`. The `keyterm`, `eot_threshold`, `eager_eot_threshold`, and `eot_timeout_ms` settings can now be updated mid-stream via `STTUpdateSettingsFrame` without requiring a WebSocket reconnect. From cd28c82de3e8541ff456858a605283962e92e280 Mon Sep 17 00:00:00 2001 From: Mark Backman Date: Sat, 7 Mar 2026 09:15:24 -0500 Subject: [PATCH 0859/1060] Update examples to use the class Settings alias --- examples/foundational/01-say-one-thing-rime.py | 4 ++-- examples/foundational/01-say-one-thing.py | 4 ++-- examples/foundational/01a-local-audio.py | 4 ++-- examples/foundational/01b-livekit-audio.py | 4 ++-- examples/foundational/02-llm-say-one-thing.py | 8 ++++---- examples/foundational/03-still-frame.py | 4 ++-- examples/foundational/03a-local-still-frame.py | 4 ++-- .../foundational/04-transports-small-webrtc.py | 8 ++++---- examples/foundational/04a-transports-daily.py | 8 ++++---- .../foundational/04b-transports-livekit.py | 8 ++++---- .../foundational/05-sync-speech-and-image.py | 8 ++++---- .../05a-local-sync-speech-and-image.py | 8 ++++---- examples/foundational/06-listen-and-respond.py | 8 ++++---- examples/foundational/06a-image-sync.py | 8 ++++---- .../07-interruptible-cartesia-http.py | 8 ++++---- examples/foundational/07-interruptible.py | 8 ++++---- .../07a-interruptible-speechmatics-vad.py | 11 +++++------ .../07a-interruptible-speechmatics.py | 11 +++++------ .../07b-interruptible-langchain.py | 4 ++-- .../07c-interruptible-deepgram-flux.py | 12 ++++++------ .../07c-interruptible-deepgram-http.py | 8 ++++---- .../07c-interruptible-deepgram-sagemaker.py | 7 ++----- .../07c-interruptible-deepgram-vad.py | 12 ++++++------ .../foundational/07c-interruptible-deepgram.py | 8 ++++---- .../07d-interruptible-elevenlabs-http.py | 8 ++++---- .../07d-interruptible-elevenlabs.py | 8 ++++---- .../07f-interruptible-azure-http.py | 4 ++-- .../foundational/07f-interruptible-azure.py | 4 ++-- .../07g-interruptible-openai-http.py | 12 ++++++------ .../foundational/07g-interruptible-openai.py | 12 ++++++------ .../foundational/07h-interruptible-openpipe.py | 8 ++++---- .../foundational/07i-interruptible-xtts.py | 8 ++++---- .../07j-interruptible-gladia-vad.py | 12 ++++++------ .../foundational/07j-interruptible-gladia.py | 12 ++++++------ .../foundational/07k-interruptible-lmnt.py | 8 ++++---- .../foundational/07l-interruptible-groq.py | 4 ++-- .../07m-interruptible-aws-strands.py | 4 ++-- examples/foundational/07m-interruptible-aws.py | 8 ++++---- .../07n-interruptible-gemini-image.py | 12 ++++++------ .../foundational/07n-interruptible-gemini.py | 12 ++++++------ .../07n-interruptible-google-http.py | 12 ++++++------ .../foundational/07n-interruptible-google.py | 12 ++++++------ ...-interruptible-assemblyai-turn-detection.py | 12 ++++++------ .../07o-interruptible-assemblyai.py | 8 ++++---- .../07p-interruptible-krisp-viva.py | 8 ++++---- .../foundational/07p-interruptible-krisp.py | 8 ++++---- .../07q-interruptible-rime-http.py | 8 ++++---- .../foundational/07q-interruptible-rime.py | 8 ++++---- .../foundational/07r-interruptible-nvidia.py | 4 ++-- .../07s-interruptible-google-audio-in.py | 8 ++++---- .../foundational/07t-interruptible-fish.py | 8 ++++---- .../07v-interruptible-neuphonic-http.py | 8 ++++---- .../07v-interruptible-neuphonic.py | 8 ++++---- examples/foundational/07w-interruptible-fal.py | 8 ++++---- .../foundational/07x-interruptible-local.py | 8 ++++---- .../foundational/07y-interruptible-minimax.py | 8 ++++---- .../07z-interruptible-sarvam-http.py | 12 ++++++------ .../foundational/07z-interruptible-sarvam.py | 12 ++++++------ .../foundational/07za-interruptible-soniox.py | 12 ++++++------ .../07zb-interruptible-inworld-http.py | 8 ++++---- .../foundational/07zb-interruptible-inworld.py | 8 ++++---- .../07zc-interruptible-asyncai-http.py | 8 ++++---- .../foundational/07zc-interruptible-asyncai.py | 8 ++++---- .../07zd-interruptible-aicoustics.py | 8 ++++---- .../foundational/07ze-interruptible-hume.py | 8 ++++---- .../foundational/07zf-interruptible-gradium.py | 12 ++++++------ .../foundational/07zg-interruptible-camb.py | 8 ++++---- .../foundational/07zi-interruptible-piper.py | 8 ++++---- .../foundational/07zj-interruptible-kokoro.py | 8 ++++---- .../07zk-interruptible-resemble.py | 8 ++++---- .../foundational/08-custom-frame-processor.py | 8 ++++---- examples/foundational/10-wake-phrase.py | 8 ++++---- examples/foundational/11-sound-effects.py | 8 ++++---- .../foundational/12-describe-image-openai.py | 8 ++++---- .../12a-describe-image-anthropic.py | 8 ++++---- .../foundational/12b-describe-image-aws.py | 8 ++++---- .../12c-describe-image-gemini-flash.py | 8 ++++---- .../12d-describe-image-moondream.py | 4 ++-- .../foundational/13b-deepgram-transcription.py | 4 ++-- .../foundational/13c-gladia-translation.py | 5 ++--- .../13d-assemblyai-transcription.py | 4 ++-- examples/foundational/13e-whisper-mlx.py | 4 ++-- .../13g-sambanova-transcription.py | 4 ++-- .../13h-speechmatics-transcription.py | 4 ++-- .../foundational/13l-gradium-transcription.py | 4 ++-- .../foundational/13m-openai-transcription.py | 4 ++-- examples/foundational/14-function-calling.py | 8 ++++---- .../14a-function-calling-anthropic.py | 8 ++++---- .../14c-function-calling-together.py | 8 ++++---- .../14d-function-calling-anthropic-video.py | 8 ++++---- .../14d-function-calling-aws-video.py | 8 ++++---- .../14d-function-calling-gemini-flash-video.py | 8 ++++---- .../14d-function-calling-moondream-video.py | 8 ++++---- .../14d-function-calling-openai-video.py | 8 ++++---- .../14e-function-calling-google.py | 8 ++++---- .../foundational/14f-function-calling-groq.py | 8 ++++---- .../foundational/14g-function-calling-grok.py | 8 ++++---- .../foundational/14h-function-calling-azure.py | 8 ++++---- .../14i-function-calling-fireworks.py | 8 ++++---- .../14j-function-calling-nvidia.py | 8 ++++---- .../14k-function-calling-cerebras.py | 8 ++++---- .../14l-function-calling-deepseek.py | 8 ++++---- .../14m-function-calling-openrouter.py | 8 ++++---- .../14n-function-calling-perplexity.py | 8 ++++---- ...4o-function-calling-gemini-openai-format.py | 8 ++++---- .../14p-function-calling-gemini-vertex-ai.py | 8 ++++---- .../foundational/14q-function-calling-qwen.py | 8 ++++---- .../foundational/14r-function-calling-aws.py | 8 ++++---- .../14s-function-calling-sambanova.py | 8 ++++---- .../14t-function-calling-direct.py | 8 ++++---- .../14u-function-calling-ollama.py | 8 ++++---- .../14v-function-calling-openai.py | 12 ++++++------ .../14w-function-calling-mistral.py | 8 ++++---- .../14x-function-calling-openpipe.py | 8 ++++---- examples/foundational/15-switch-voices.py | 12 ++++++------ examples/foundational/15a-switch-languages.py | 14 +++++++------- .../foundational/16-gpu-container-local-bot.py | 8 ++++---- examples/foundational/17-detect-user-idle.py | 8 ++++---- examples/foundational/19-openai-realtime.py | 7 ++----- examples/foundational/19a-azure-realtime.py | 3 +-- .../19b-openai-realtime-beta-text.py | 4 ++-- .../foundational/19b-openai-realtime-text.py | 4 ++-- .../19c-openai-realtime-live-video.py | 7 ++----- .../20a-persistent-context-openai.py | 4 ++-- .../20b-persistent-context-openai-realtime.py | 7 ++----- .../20c-persistent-context-anthropic.py | 10 ++++++---- .../20d-persistent-context-gemini.py | 4 ++-- .../20e-persistent-context-aws-nova-sonic.py | 4 ++-- examples/foundational/21-tavus-transport.py | 8 ++++---- .../foundational/21a-tavus-video-service.py | 8 ++++---- .../foundational/22-filter-incomplete-turns.py | 8 ++++---- .../foundational/23-bot-background-sound.py | 8 ++++---- examples/foundational/24-user-mute-strategy.py | 8 ++++---- examples/foundational/25-google-audio-in.py | 10 +++++----- examples/foundational/26-gemini-live.py | 4 ++-- .../26a-gemini-live-transcription.py | 8 +++++--- .../26b-gemini-live-function-calling.py | 4 ++-- examples/foundational/26c-gemini-live-video.py | 4 ++-- examples/foundational/26d-gemini-live-text.py | 11 +++-------- .../26e-gemini-live-google-search.py | 4 ++-- .../foundational/26f-gemini-live-files-api.py | 4 ++-- .../26g-gemini-live-groundingMetadata.py | 4 ++-- .../26h-gemini-live-vertex-function-calling.py | 3 +-- .../26i-gemini-live-graceful-end.py | 4 ++-- examples/foundational/27-simli-layer.py | 8 ++++---- .../foundational/28-user-assistant-turns.py | 8 ++++---- .../foundational/29-turn-tracking-observer.py | 8 ++++---- examples/foundational/30-observer.py | 8 ++++---- .../32-gemini-grounding-metadata.py | 8 ++++---- examples/foundational/33-gemini-rag.py | 8 ++++---- examples/foundational/34-audio-recording.py | 8 ++++---- .../35-pattern-pair-voice-switching.py | 8 ++++---- .../foundational/36-user-email-gathering.py | 8 ++++---- examples/foundational/37-mem0.py | 8 ++++---- examples/foundational/38-smart-turn-fal.py | 8 ++++---- .../38a-smart-turn-local-coreml.py | 8 ++++---- examples/foundational/38b-smart-turn-local.py | 8 ++++---- examples/foundational/39-mcp-stdio.py | 8 ++++---- .../foundational/39a-mcp-streamable-http.py | 4 ++-- .../39b-mcp-streamable-http-gemini-live.py | 4 ++-- examples/foundational/39c-multiple-mcp.py | 8 ++++---- examples/foundational/40-aws-nova-sonic.py | 4 ++-- .../foundational/42-interruption-config.py | 8 ++++---- examples/foundational/43-heygen-transport.py | 8 ++++---- .../foundational/43a-heygen-video-service.py | 8 ++++---- .../foundational/44-voicemail-detection.py | 8 ++++---- .../foundational/45-before-and-after-events.py | 8 ++++---- examples/foundational/47-sentry-metrics.py | 8 ++++---- examples/foundational/48-service-switcher.py | 16 ++++++++-------- .../foundational/49a-thinking-anthropic.py | 12 ++++-------- examples/foundational/49b-thinking-google.py | 8 ++++---- .../49c-thinking-functions-anthropic.py | 12 ++++-------- .../49d-thinking-functions-google.py | 8 ++++---- examples/foundational/51-grok-realtime.py | 4 +++- examples/foundational/52-live-translation.py | 8 ++++---- .../53-concurrent-llm-evaluation.py | 12 ++++++------ .../53-concurrent-llm-rtvi-ignored-sources.py | 10 +++++----- .../54-context-summarization-openai.py | 8 ++++---- .../54a-context-summarization-google.py | 8 ++++---- .../54b-context-summarization-manual-openai.py | 10 ++++------ .../54c-context-summarization-dedicated-llm.py | 12 ++++++------ .../55a-update-settings-deepgram-flux-stt.py | 12 ++++++------ ...a-update-settings-deepgram-sagemaker-stt.py | 15 ++++++--------- .../55a-update-settings-deepgram-stt.py | 12 ++++++------ .../55b-update-settings-azure-stt.py | 14 ++++++++------ .../55c-update-settings-google-stt.py | 12 ++++++------ .../55d-update-settings-assemblyai-stt.py | 14 +++++++------- .../55e-update-settings-gladia-stt.py | 12 ++++++------ ...-update-settings-elevenlabs-realtime-stt.py | 17 ++++++++--------- .../55g-update-settings-elevenlabs-stt.py | 12 ++++++------ .../55h-update-settings-speechmatics-stt.py | 18 +++++++++--------- .../55i-update-settings-whisper-api-stt.py | 8 ++++---- .../55j-update-settings-sarvam-stt.py | 12 ++++++------ .../55k-update-settings-soniox-stt.py | 12 ++++++------ .../55l-update-settings-aws-transcribe-stt.py | 12 ++++++------ .../55m-update-settings-cartesia-stt.py | 12 ++++++------ .../55n-update-settings-cartesia-http-tts.py | 14 +++++--------- .../55n-update-settings-cartesia-tts.py | 10 +++++----- .../55o-update-settings-elevenlabs-http-tts.py | 10 +++++----- .../55o-update-settings-elevenlabs-tts.py | 15 ++++++++------- .../55p-update-settings-openai-tts.py | 8 ++++---- .../55q-update-settings-deepgram-http-tts.py | 14 +++++++++----- ...q-update-settings-deepgram-sagemaker-tts.py | 17 +++++++++-------- .../55q-update-settings-deepgram-tts.py | 10 +++++----- .../55r-update-settings-azure-http-tts.py | 8 ++++---- .../55r-update-settings-azure-tts.py | 8 ++++---- .../55s-update-settings-google-http-tts.py | 8 ++++---- .../55s-update-settings-google-stream-tts.py | 8 ++++---- .../55u-update-settings-rime-http-tts.py | 12 +++++++----- .../55u-update-settings-rime-tts.py | 10 +++++----- .../55v-update-settings-lmnt-tts.py | 10 +++++----- .../55w-update-settings-fish-tts.py | 12 +++++++----- .../55x-update-settings-minimax-tts.py | 10 ++++++---- .../55y-update-settings-groq-tts.py | 8 ++++---- .../55z-update-settings-hume-tts.py | 10 +++++----- .../55za-update-settings-neuphonic-http-tts.py | 10 ++++++---- .../55za-update-settings-neuphonic-tts.py | 10 ++++++---- .../55zb-update-settings-inworld-http-tts.py | 10 ++++++---- .../55zb-update-settings-inworld-tts.py | 10 ++++++---- .../55zc-update-settings-gemini-tts.py | 12 +++++++----- .../55zd-update-settings-aws-polly-tts.py | 10 ++++++---- .../55ze-update-settings-sarvam-http-tts.py | 10 ++++++---- .../55ze-update-settings-sarvam-tts.py | 8 ++++---- .../55zf-update-settings-camb-tts.py | 10 ++++++---- .../55zh-update-settings-resembleai-tts.py | 10 +++++----- .../55zi-update-settings-azure-llm.py | 13 +++++++------ .../55zi-update-settings-openai-llm.py | 11 ++++++----- .../55zj-update-settings-anthropic-llm.py | 12 +++++++----- .../55zk-update-settings-google-llm.py | 12 +++++++----- .../55zk-update-settings-google-vertex-llm.py | 12 +++++++----- .../55zl-update-settings-azure-realtime.py | 5 ++--- .../55zl-update-settings-openai-realtime.py | 9 +++------ .../55zm-update-settings-gemini-live-vertex.py | 7 ++++--- .../55zm-update-settings-gemini-live.py | 8 +++++--- .../55zn-update-settings-ultravox-realtime.py | 10 +++------- .../55zo-update-settings-grok-realtime.py | 7 ++----- .../55zp-update-settings-aws-bedrock-llm.py | 12 +++++++----- .../55zq-update-settings-fal-stt.py | 14 ++++++++------ .../55zr-update-settings-gradium-stt.py | 14 ++++++++------ ...5zt-update-settings-nvidia-segmented-stt.py | 12 ++++++------ .../55zt-update-settings-nvidia-stt.py | 12 ++++++------ ...55zu-update-settings-openai-realtime-stt.py | 12 ++++++------ .../55zv-update-settings-asyncai-http-tts.py | 10 +++++----- .../55zv-update-settings-asyncai-tts.py | 10 +++++----- .../55zw-update-settings-gradium-tts.py | 10 +++++----- .../55zx-update-settings-cerebras-llm.py | 13 +++++++------ .../55zy-update-settings-deepseek-llm.py | 13 +++++++------ .../55zz-update-settings-fireworks-llm.py | 13 +++++++------ .../55zza-update-settings-grok-llm.py | 13 +++++++------ .../55zzb-update-settings-groq-llm.py | 13 +++++++------ .../55zzc-update-settings-mistral-llm.py | 12 +++++++----- .../55zzd-update-settings-nvidia-llm.py | 13 +++++++------ .../55zze-update-settings-ollama-llm.py | 13 +++++++------ .../55zzf-update-settings-openrouter-llm.py | 13 +++++++------ .../55zzg-update-settings-perplexity-llm.py | 9 +++++---- .../55zzh-update-settings-qwen-llm.py | 13 +++++++------ .../55zzi-update-settings-sambanova-llm.py | 13 +++++++------ .../55zzj-update-settings-together-llm.py | 13 +++++++------ ...55zzk-update-settings-aws-nova-sonic-llm.py | 6 +++--- .../55zzl-update-settings-nvidia-tts.py | 8 ++++---- .../55zzm-update-settings-speechmatics-tts.py | 8 ++++---- .../55zzn-update-settings-groq-stt.py | 11 +++++------ .../foundational/56-lemonslice-transport.py | 8 ++++---- scripts/evals/eval.py | 12 +++++++----- 264 files changed, 1172 insertions(+), 1155 deletions(-) diff --git a/examples/foundational/01-say-one-thing-rime.py b/examples/foundational/01-say-one-thing-rime.py index 63667fac8..a9df51f7f 100644 --- a/examples/foundational/01-say-one-thing-rime.py +++ b/examples/foundational/01-say-one-thing-rime.py @@ -16,7 +16,7 @@ from pipecat.pipeline.runner import PipelineRunner from pipecat.pipeline.task import PipelineTask from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport -from pipecat.services.rime.tts import RimeHttpTTSService, RimeTTSSettings +from pipecat.services.rime.tts import RimeHttpTTSService from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams @@ -40,7 +40,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): tts = RimeHttpTTSService( api_key=os.getenv("RIME_API_KEY", ""), aiohttp_session=session, - settings=RimeTTSSettings( + settings=RimeHttpTTSService.Settings( voice="rex", ), ) diff --git a/examples/foundational/01-say-one-thing.py b/examples/foundational/01-say-one-thing.py index bfcf829cc..fdfecde6c 100644 --- a/examples/foundational/01-say-one-thing.py +++ b/examples/foundational/01-say-one-thing.py @@ -15,7 +15,7 @@ from pipecat.pipeline.runner import PipelineRunner from pipecat.pipeline.task import PipelineTask from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport -from pipecat.services.cartesia.tts import CartesiaTTSService, CartesiaTTSSettings +from pipecat.services.cartesia.tts import CartesiaTTSService from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams @@ -37,7 +37,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): tts = CartesiaTTSService( api_key=os.getenv("CARTESIA_API_KEY"), - settings=CartesiaTTSSettings( + settings=CartesiaTTSService.Settings( voice="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady ), ) diff --git a/examples/foundational/01a-local-audio.py b/examples/foundational/01a-local-audio.py index 77565dffe..1e18b4b03 100644 --- a/examples/foundational/01a-local-audio.py +++ b/examples/foundational/01a-local-audio.py @@ -15,7 +15,7 @@ from pipecat.frames.frames import EndFrame, TTSSpeakFrame from pipecat.pipeline.pipeline import Pipeline from pipecat.pipeline.runner import PipelineRunner from pipecat.pipeline.task import PipelineTask -from pipecat.services.cartesia.tts import CartesiaTTSService, CartesiaTTSSettings +from pipecat.services.cartesia.tts import CartesiaTTSService from pipecat.transports.local.audio import LocalAudioTransport, LocalAudioTransportParams load_dotenv(override=True) @@ -29,7 +29,7 @@ async def main(): tts = CartesiaTTSService( api_key=os.getenv("CARTESIA_API_KEY"), - settings=CartesiaTTSSettings( + settings=CartesiaTTSService.Settings( voice="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady ), ) diff --git a/examples/foundational/01b-livekit-audio.py b/examples/foundational/01b-livekit-audio.py index ad4c785eb..5f64a29ed 100644 --- a/examples/foundational/01b-livekit-audio.py +++ b/examples/foundational/01b-livekit-audio.py @@ -16,7 +16,7 @@ from pipecat.pipeline.pipeline import Pipeline from pipecat.pipeline.runner import PipelineRunner from pipecat.pipeline.task import PipelineTask from pipecat.runner.livekit import configure -from pipecat.services.cartesia.tts import CartesiaTTSService, CartesiaTTSSettings +from pipecat.services.cartesia.tts import CartesiaTTSService from pipecat.transports.livekit.transport import LiveKitParams, LiveKitTransport load_dotenv(override=True) @@ -37,7 +37,7 @@ async def main(): tts = CartesiaTTSService( api_key=os.getenv("CARTESIA_API_KEY"), - settings=CartesiaTTSSettings( + settings=CartesiaTTSService.Settings( voice="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady ), ) diff --git a/examples/foundational/02-llm-say-one-thing.py b/examples/foundational/02-llm-say-one-thing.py index f59a2216d..cebea9dcf 100644 --- a/examples/foundational/02-llm-say-one-thing.py +++ b/examples/foundational/02-llm-say-one-thing.py @@ -16,8 +16,8 @@ from pipecat.pipeline.task import PipelineTask from pipecat.processors.aggregators.llm_context import LLMContext from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport -from pipecat.services.cartesia.tts import CartesiaTTSService, CartesiaTTSSettings -from pipecat.services.openai.llm import OpenAILLMService, OpenAILLMSettings +from pipecat.services.cartesia.tts import CartesiaTTSService +from pipecat.services.openai.llm import OpenAILLMService from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams @@ -39,14 +39,14 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): tts = CartesiaTTSService( api_key=os.getenv("CARTESIA_API_KEY"), - settings=CartesiaTTSSettings( + settings=CartesiaTTSService.Settings( voice="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady ), ) llm = OpenAILLMService( api_key=os.getenv("OPENAI_API_KEY"), - settings=OpenAILLMSettings( + settings=OpenAILLMService.Settings( system_instruction="You are an LLM in a WebRTC session, and this is a 'hello world' demo.", ), ) diff --git a/examples/foundational/03-still-frame.py b/examples/foundational/03-still-frame.py index a98a53637..dc1bf4c5f 100644 --- a/examples/foundational/03-still-frame.py +++ b/examples/foundational/03-still-frame.py @@ -16,7 +16,7 @@ from pipecat.pipeline.runner import PipelineRunner from pipecat.pipeline.task import PipelineTask from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport -from pipecat.services.fal.image import FalImageGenService, FalImageGenSettings +from pipecat.services.fal.image import FalImageGenService from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams @@ -45,7 +45,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): # Create an HTTP session async with aiohttp.ClientSession() as session: imagegen = FalImageGenService( - settings=FalImageGenSettings( + settings=FalImageGenService.Settings( image_size="square_hd", ), aiohttp_session=session, diff --git a/examples/foundational/03a-local-still-frame.py b/examples/foundational/03a-local-still-frame.py index db67848e8..0b70e2297 100644 --- a/examples/foundational/03a-local-still-frame.py +++ b/examples/foundational/03a-local-still-frame.py @@ -17,7 +17,7 @@ from pipecat.frames.frames import TextFrame from pipecat.pipeline.pipeline import Pipeline from pipecat.pipeline.runner import PipelineRunner from pipecat.pipeline.task import PipelineTask -from pipecat.services.fal.image import FalImageGenService, FalImageGenSettings +from pipecat.services.fal.image import FalImageGenService from pipecat.transports.local.tk import TkLocalTransport, TkTransportParams load_dotenv(override=True) @@ -37,7 +37,7 @@ async def main(): ) imagegen = FalImageGenService( - settings=FalImageGenSettings( + settings=FalImageGenService.Settings( image_size="square_hd", ), aiohttp_session=session, diff --git a/examples/foundational/04-transports-small-webrtc.py b/examples/foundational/04-transports-small-webrtc.py index d8b6422db..ba4749919 100644 --- a/examples/foundational/04-transports-small-webrtc.py +++ b/examples/foundational/04-transports-small-webrtc.py @@ -27,9 +27,9 @@ from pipecat.processors.aggregators.llm_response_universal import ( LLMContextAggregatorPair, LLMUserAggregatorParams, ) -from pipecat.services.cartesia.tts import CartesiaTTSService, CartesiaTTSSettings +from pipecat.services.cartesia.tts import CartesiaTTSService from pipecat.services.deepgram.stt import DeepgramSTTService -from pipecat.services.openai.llm import OpenAILLMService, OpenAILLMSettings +from pipecat.services.openai.llm import OpenAILLMService from pipecat.transports.base_transport import TransportParams from pipecat.transports.smallwebrtc.connection import IceServer, SmallWebRTCConnection from pipecat.transports.smallwebrtc.transport import SmallWebRTCTransport @@ -67,14 +67,14 @@ async def run_example(webrtc_connection: SmallWebRTCConnection): tts = CartesiaTTSService( api_key=os.getenv("CARTESIA_API_KEY"), - settings=CartesiaTTSSettings( + settings=CartesiaTTSService.Settings( voice="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady ), ) llm = OpenAILLMService( api_key=os.getenv("OPENAI_API_KEY"), - settings=OpenAILLMSettings( + settings=OpenAILLMService.Settings( system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", ), ) diff --git a/examples/foundational/04a-transports-daily.py b/examples/foundational/04a-transports-daily.py index aaf8a3f0f..ab986c22f 100644 --- a/examples/foundational/04a-transports-daily.py +++ b/examples/foundational/04a-transports-daily.py @@ -23,8 +23,8 @@ from pipecat.processors.aggregators.llm_response_universal import ( LLMUserAggregatorParams, ) from pipecat.runner.daily import configure -from pipecat.services.cartesia.tts import CartesiaTTSService, CartesiaTTSSettings -from pipecat.services.openai.llm import OpenAILLMService, OpenAILLMSettings +from pipecat.services.cartesia.tts import CartesiaTTSService +from pipecat.services.openai.llm import OpenAILLMService from pipecat.transports.daily.transport import DailyParams, DailyTransport load_dotenv(override=True) @@ -50,14 +50,14 @@ async def main(): tts = CartesiaTTSService( api_key=os.getenv("CARTESIA_API_KEY"), - settings=CartesiaTTSSettings( + settings=CartesiaTTSService.Settings( voice="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady ), ) llm = OpenAILLMService( api_key=os.getenv("OPENAI_API_KEY"), - settings=OpenAILLMSettings( + settings=OpenAILLMService.Settings( model="gpt-4o", system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", ), diff --git a/examples/foundational/04b-transports-livekit.py b/examples/foundational/04b-transports-livekit.py index 1f4709b0b..09262f767 100644 --- a/examples/foundational/04b-transports-livekit.py +++ b/examples/foundational/04b-transports-livekit.py @@ -29,9 +29,9 @@ from pipecat.processors.aggregators.llm_response_universal import ( LLMUserAggregatorParams, ) from pipecat.runner.livekit import configure -from pipecat.services.cartesia.tts import CartesiaTTSService, CartesiaTTSSettings +from pipecat.services.cartesia.tts import CartesiaTTSService from pipecat.services.deepgram.stt import DeepgramSTTService -from pipecat.services.openai.llm import OpenAILLMService, OpenAILLMSettings +from pipecat.services.openai.llm import OpenAILLMService from pipecat.transports.livekit.transport import LiveKitParams, LiveKitTransport load_dotenv(override=True) @@ -57,14 +57,14 @@ async def main(): llm = OpenAILLMService( api_key=os.getenv("OPENAI_API_KEY"), - settings=OpenAILLMSettings( + settings=OpenAILLMService.Settings( system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", ), ) tts = CartesiaTTSService( api_key=os.getenv("CARTESIA_API_KEY"), - settings=CartesiaTTSSettings( + settings=CartesiaTTSService.Settings( voice="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady ), ) diff --git a/examples/foundational/05-sync-speech-and-image.py b/examples/foundational/05-sync-speech-and-image.py index 276d3a14a..1e4cf34a4 100644 --- a/examples/foundational/05-sync-speech-and-image.py +++ b/examples/foundational/05-sync-speech-and-image.py @@ -27,8 +27,8 @@ from pipecat.processors.aggregators.sentence import SentenceAggregator from pipecat.processors.frame_processor import FrameDirection, FrameProcessor from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport -from pipecat.services.cartesia.tts import CartesiaHttpTTSService, CartesiaTTSSettings -from pipecat.services.fal.image import FalImageGenService, FalImageGenSettings +from pipecat.services.cartesia.tts import CartesiaHttpTTSService +from pipecat.services.fal.image import FalImageGenService from pipecat.services.openai.llm import OpenAILLMService from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams @@ -98,13 +98,13 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): tts = CartesiaHttpTTSService( api_key=os.getenv("CARTESIA_API_KEY"), - settings=CartesiaTTSSettings( + settings=CartesiaHttpTTSService.Settings( voice="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady ), ) imagegen = FalImageGenService( - settings=FalImageGenSettings( + settings=FalImageGenService.Settings( image_size="square_hd", ), aiohttp_session=session, diff --git a/examples/foundational/05a-local-sync-speech-and-image.py b/examples/foundational/05a-local-sync-speech-and-image.py index b06a2a8b0..d0c5a103a 100644 --- a/examples/foundational/05a-local-sync-speech-and-image.py +++ b/examples/foundational/05a-local-sync-speech-and-image.py @@ -28,8 +28,8 @@ from pipecat.pipeline.task import PipelineTask from pipecat.processors.aggregators.llm_context import LLMContext from pipecat.processors.aggregators.sentence import SentenceAggregator from pipecat.processors.frame_processor import FrameDirection, FrameProcessor -from pipecat.services.cartesia.tts import CartesiaHttpTTSService, CartesiaTTSSettings -from pipecat.services.fal.image import FalImageGenService, FalImageGenSettings +from pipecat.services.cartesia.tts import CartesiaHttpTTSService +from pipecat.services.fal.image import FalImageGenService from pipecat.services.openai.llm import OpenAILLMService from pipecat.transports.local.tk import TkLocalTransport, TkTransportParams @@ -98,13 +98,13 @@ async def main(): tts = CartesiaHttpTTSService( api_key=os.getenv("CARTESIA_API_KEY"), - settings=CartesiaTTSSettings( + settings=CartesiaHttpTTSService.Settings( voice="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady ), ) imagegen = FalImageGenService( - settings=FalImageGenSettings( + settings=FalImageGenService.Settings( image_size="square_hd", ), aiohttp_session=session, diff --git a/examples/foundational/06-listen-and-respond.py b/examples/foundational/06-listen-and-respond.py index d2daff3fb..7a73ad876 100644 --- a/examples/foundational/06-listen-and-respond.py +++ b/examples/foundational/06-listen-and-respond.py @@ -28,9 +28,9 @@ from pipecat.processors.aggregators.llm_response_universal import ( from pipecat.processors.frame_processor import FrameDirection, FrameProcessor from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport -from pipecat.services.cartesia.tts import CartesiaTTSService, CartesiaTTSSettings +from pipecat.services.cartesia.tts import CartesiaTTSService from pipecat.services.deepgram.stt import DeepgramSTTService -from pipecat.services.openai.llm import OpenAILLMService, OpenAILLMSettings +from pipecat.services.openai.llm import OpenAILLMService from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams @@ -83,14 +83,14 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): tts = CartesiaTTSService( api_key=os.getenv("CARTESIA_API_KEY"), - settings=CartesiaTTSSettings( + settings=CartesiaTTSService.Settings( voice="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady ), ) llm = OpenAILLMService( api_key=os.getenv("OPENAI_API_KEY"), - settings=OpenAILLMSettings( + settings=OpenAILLMService.Settings( system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", ), ) diff --git a/examples/foundational/06a-image-sync.py b/examples/foundational/06a-image-sync.py index 007a41143..3f80380dc 100644 --- a/examples/foundational/06a-image-sync.py +++ b/examples/foundational/06a-image-sync.py @@ -29,9 +29,9 @@ from pipecat.processors.aggregators.llm_response_universal import ( from pipecat.processors.frame_processor import FrameDirection, FrameProcessor from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport -from pipecat.services.cartesia.tts import CartesiaTTSService, CartesiaTTSSettings +from pipecat.services.cartesia.tts import CartesiaTTSService from pipecat.services.deepgram.stt import DeepgramSTTService -from pipecat.services.openai.llm import OpenAILLMService, OpenAILLMSettings +from pipecat.services.openai.llm import OpenAILLMService from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams @@ -100,14 +100,14 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): tts = CartesiaTTSService( api_key=os.getenv("CARTESIA_API_KEY"), - settings=CartesiaTTSSettings( + settings=CartesiaTTSService.Settings( voice="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady ), ) llm = OpenAILLMService( api_key=os.getenv("OPENAI_API_KEY"), - settings=OpenAILLMSettings( + settings=OpenAILLMService.Settings( system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", ), ) diff --git a/examples/foundational/07-interruptible-cartesia-http.py b/examples/foundational/07-interruptible-cartesia-http.py index 56a06f2e9..be6bc07a6 100644 --- a/examples/foundational/07-interruptible-cartesia-http.py +++ b/examples/foundational/07-interruptible-cartesia-http.py @@ -23,8 +23,8 @@ from pipecat.processors.aggregators.llm_response_universal import ( from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport from pipecat.services.cartesia.stt import CartesiaSTTService -from pipecat.services.cartesia.tts import CartesiaHttpTTSService, CartesiaTTSSettings -from pipecat.services.openai.llm import OpenAILLMService, OpenAILLMSettings +from pipecat.services.cartesia.tts import CartesiaHttpTTSService +from pipecat.services.openai.llm import OpenAILLMService from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams @@ -59,14 +59,14 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): tts = CartesiaHttpTTSService( api_key=os.getenv("CARTESIA_API_KEY"), aiohttp_session=session, - settings=CartesiaTTSSettings( + settings=CartesiaHttpTTSService.Settings( voice="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady ), ) llm = OpenAILLMService( api_key=os.getenv("OPENAI_API_KEY"), - settings=OpenAILLMSettings( + settings=OpenAILLMService.Settings( system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", ), ) diff --git a/examples/foundational/07-interruptible.py b/examples/foundational/07-interruptible.py index cf9c5af96..6fa80d838 100644 --- a/examples/foundational/07-interruptible.py +++ b/examples/foundational/07-interruptible.py @@ -21,9 +21,9 @@ from pipecat.processors.aggregators.llm_response_universal import ( ) from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport -from pipecat.services.cartesia.tts import CartesiaTTSService, CartesiaTTSSettings +from pipecat.services.cartesia.tts import CartesiaTTSService from pipecat.services.deepgram.stt import DeepgramSTTService -from pipecat.services.openai.llm import OpenAILLMService, OpenAILLMSettings +from pipecat.services.openai.llm import OpenAILLMService from pipecat.services.tts_service import TextAggregationMode from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams @@ -56,14 +56,14 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): tts = CartesiaTTSService( api_key=os.getenv("CARTESIA_API_KEY"), - settings=CartesiaTTSSettings( + settings=CartesiaTTSService.Settings( voice="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady ), ) llm = OpenAILLMService( api_key=os.getenv("OPENAI_API_KEY"), - settings=OpenAILLMSettings( + settings=OpenAILLMService.Settings( system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", ), ) diff --git a/examples/foundational/07a-interruptible-speechmatics-vad.py b/examples/foundational/07a-interruptible-speechmatics-vad.py index 2ede06e4f..cece246d8 100644 --- a/examples/foundational/07a-interruptible-speechmatics-vad.py +++ b/examples/foundational/07a-interruptible-speechmatics-vad.py @@ -21,10 +21,9 @@ from pipecat.processors.aggregators.llm_response_universal import ( ) from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport -from pipecat.services.openai.base_llm import OpenAILLMSettings from pipecat.services.openai.llm import OpenAILLMService -from pipecat.services.speechmatics.stt import SpeechmaticsSTTService, SpeechmaticsSTTSettings -from pipecat.services.speechmatics.tts import SpeechmaticsTTSService, SpeechmaticsTTSSettings +from pipecat.services.speechmatics.stt import SpeechmaticsSTTService +from pipecat.services.speechmatics.tts import SpeechmaticsTTSService from pipecat.transcriptions.language import Language from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams @@ -93,7 +92,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): async with aiohttp.ClientSession() as session: stt = SpeechmaticsSTTService( api_key=os.getenv("SPEECHMATICS_API_KEY"), - settings=SpeechmaticsSTTSettings( + settings=SpeechmaticsSTTService.Settings( language=Language.EN, turn_detection_mode=SpeechmaticsSTTService.TurnDetectionMode.ADAPTIVE, # focus_speakers=["S1"], @@ -104,7 +103,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): tts = SpeechmaticsTTSService( api_key=os.getenv("SPEECHMATICS_API_KEY"), - settings=SpeechmaticsTTSSettings( + settings=SpeechmaticsTTSService.Settings( voice="sarah", ), aiohttp_session=session, @@ -112,7 +111,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): llm = OpenAILLMService( api_key=os.getenv("OPENAI_API_KEY"), - settings=OpenAILLMSettings( + settings=OpenAILLMService.Settings( temperature=0.75, system_instruction="You are a helpful British assistant called Sarah. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Always include punctuation in your responses. Give very short replies - do not give longer replies unless strictly necessary. Respond to what the user said in a concise, funny, creative and helpful way. Use `` tags to identify different speakers - do not use tags in your replies. Do not respond to speakers within `` tags unless explicitly asked to.", ), diff --git a/examples/foundational/07a-interruptible-speechmatics.py b/examples/foundational/07a-interruptible-speechmatics.py index bee3410e3..3d6395f73 100644 --- a/examples/foundational/07a-interruptible-speechmatics.py +++ b/examples/foundational/07a-interruptible-speechmatics.py @@ -22,10 +22,9 @@ from pipecat.processors.aggregators.llm_response_universal import ( ) from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport -from pipecat.services.openai.base_llm import OpenAILLMSettings from pipecat.services.openai.llm import OpenAILLMService -from pipecat.services.speechmatics.stt import SpeechmaticsSTTService, SpeechmaticsSTTSettings -from pipecat.services.speechmatics.tts import SpeechmaticsTTSService, SpeechmaticsTTSSettings +from pipecat.services.speechmatics.stt import SpeechmaticsSTTService +from pipecat.services.speechmatics.tts import SpeechmaticsTTSService from pipecat.transcriptions.language import Language from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams @@ -76,7 +75,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): async with aiohttp.ClientSession() as session: stt = SpeechmaticsSTTService( api_key=os.getenv("SPEECHMATICS_API_KEY"), - settings=SpeechmaticsSTTSettings( + settings=SpeechmaticsSTTService.Settings( language=Language.EN, speaker_active_format="<{speaker_id}>{text}", ), @@ -84,7 +83,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): tts = SpeechmaticsTTSService( api_key=os.getenv("SPEECHMATICS_API_KEY"), - settings=SpeechmaticsTTSSettings( + settings=SpeechmaticsTTSService.Settings( voice="sarah", ), aiohttp_session=session, @@ -92,7 +91,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): llm = OpenAILLMService( api_key=os.getenv("OPENAI_API_KEY"), - settings=OpenAILLMSettings( + settings=OpenAILLMService.Settings( temperature=0.75, system_instruction="You are a helpful British assistant called Sarah. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Always include punctuation in your responses. Give very short replies - do not give longer replies unless strictly necessary. Respond to what the user said in a concise, funny, creative and helpful way. Use `` tags to identify different speakers - do not use tags in your replies. Do not respond to speakers within `` tags unless explicitly asked to.", ), diff --git a/examples/foundational/07b-interruptible-langchain.py b/examples/foundational/07b-interruptible-langchain.py index e7a5dc1b8..1a85bf7ad 100644 --- a/examples/foundational/07b-interruptible-langchain.py +++ b/examples/foundational/07b-interruptible-langchain.py @@ -28,7 +28,7 @@ from pipecat.processors.aggregators.llm_response_universal import ( from pipecat.processors.frameworks.langchain import LangchainProcessor from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport -from pipecat.services.cartesia.tts import CartesiaTTSService, CartesiaTTSSettings +from pipecat.services.cartesia.tts import CartesiaTTSService from pipecat.services.deepgram.stt import DeepgramSTTService from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams @@ -71,7 +71,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): tts = CartesiaTTSService( api_key=os.getenv("CARTESIA_API_KEY"), - settings=CartesiaTTSSettings( + settings=CartesiaTTSService.Settings( voice="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady ), ) diff --git a/examples/foundational/07c-interruptible-deepgram-flux.py b/examples/foundational/07c-interruptible-deepgram-flux.py index a356a81cc..da027b4f8 100644 --- a/examples/foundational/07c-interruptible-deepgram-flux.py +++ b/examples/foundational/07c-interruptible-deepgram-flux.py @@ -22,9 +22,9 @@ from pipecat.processors.aggregators.llm_response_universal import ( ) from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport -from pipecat.services.deepgram.flux.stt import DeepgramFluxSTTService, DeepgramFluxSTTSettings -from pipecat.services.deepgram.tts import DeepgramTTSService, DeepgramTTSSettings -from pipecat.services.openai.llm import OpenAILLMService, OpenAILLMSettings +from pipecat.services.deepgram.flux.stt import DeepgramFluxSTTService +from pipecat.services.deepgram.tts import DeepgramTTSService +from pipecat.services.openai.llm import OpenAILLMService from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams @@ -56,21 +56,21 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): stt = DeepgramFluxSTTService( api_key=os.getenv("DEEPGRAM_API_KEY"), - settings=DeepgramFluxSTTSettings( + settings=DeepgramFluxSTTService.Settings( min_confidence=0.3, ), ) tts = DeepgramTTSService( api_key=os.getenv("DEEPGRAM_API_KEY"), - settings=DeepgramTTSSettings( + settings=DeepgramTTSService.Settings( voice="aura-2-andromeda-en", ), ) llm = OpenAILLMService( api_key=os.getenv("OPENAI_API_KEY"), - settings=OpenAILLMSettings( + settings=OpenAILLMService.Settings( system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", ), ) diff --git a/examples/foundational/07c-interruptible-deepgram-http.py b/examples/foundational/07c-interruptible-deepgram-http.py index fa8b6712c..ee6733165 100644 --- a/examples/foundational/07c-interruptible-deepgram-http.py +++ b/examples/foundational/07c-interruptible-deepgram-http.py @@ -24,8 +24,8 @@ from pipecat.processors.aggregators.llm_response_universal import ( from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport from pipecat.services.deepgram.stt import DeepgramSTTService -from pipecat.services.deepgram.tts import DeepgramHttpTTSService, DeepgramTTSSettings -from pipecat.services.openai.llm import OpenAILLMService, OpenAILLMSettings +from pipecat.services.deepgram.tts import DeepgramHttpTTSService +from pipecat.services.openai.llm import OpenAILLMService from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams @@ -59,7 +59,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): tts = DeepgramHttpTTSService( api_key=os.getenv("DEEPGRAM_API_KEY"), - settings=DeepgramTTSSettings( + settings=DeepgramHttpTTSService.Settings( voice="aura-2-andromeda-en", ), aiohttp_session=session, @@ -67,7 +67,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): llm = OpenAILLMService( api_key=os.getenv("OPENAI_API_KEY"), - settings=OpenAILLMSettings( + settings=OpenAILLMService.Settings( system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", ), ) diff --git a/examples/foundational/07c-interruptible-deepgram-sagemaker.py b/examples/foundational/07c-interruptible-deepgram-sagemaker.py index b1c54a27e..91b1c95aa 100644 --- a/examples/foundational/07c-interruptible-deepgram-sagemaker.py +++ b/examples/foundational/07c-interruptible-deepgram-sagemaker.py @@ -24,10 +24,7 @@ from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport from pipecat.services.aws.llm import AWSBedrockLLMService, AWSBedrockLLMSettings from pipecat.services.deepgram.sagemaker.stt import DeepgramSageMakerSTTService -from pipecat.services.deepgram.sagemaker.tts import ( - DeepgramSageMakerTTSService, - DeepgramSageMakerTTSSettings, -) +from pipecat.services.deepgram.sagemaker.tts import DeepgramSageMakerTTSService from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams @@ -72,7 +69,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): tts = DeepgramSageMakerTTSService( endpoint_name=os.getenv("SAGEMAKER_TTS_ENDPOINT_NAME"), region=os.getenv("AWS_REGION"), - settings=DeepgramSageMakerTTSSettings( + settings=DeepgramSageMakerTTSService.Settings( voice="aura-2-andromeda-en", ), ) diff --git a/examples/foundational/07c-interruptible-deepgram-vad.py b/examples/foundational/07c-interruptible-deepgram-vad.py index 7a0ccb441..0a4dc0125 100644 --- a/examples/foundational/07c-interruptible-deepgram-vad.py +++ b/examples/foundational/07c-interruptible-deepgram-vad.py @@ -21,9 +21,9 @@ from pipecat.processors.aggregators.llm_response_universal import ( ) from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport -from pipecat.services.deepgram.stt import DeepgramSTTService, DeepgramSTTSettings -from pipecat.services.deepgram.tts import DeepgramTTSService, DeepgramTTSSettings -from pipecat.services.openai.llm import OpenAILLMService, OpenAILLMSettings +from pipecat.services.deepgram.stt import DeepgramSTTService +from pipecat.services.deepgram.tts import DeepgramTTSService +from pipecat.services.openai.llm import OpenAILLMService from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams @@ -55,7 +55,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): stt = DeepgramSTTService( api_key=os.getenv("DEEPGRAM_API_KEY"), - settings=DeepgramSTTSettings( + settings=DeepgramSTTService.Settings( vad_events=True, utterance_end_ms="1000", ), @@ -63,14 +63,14 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): tts = DeepgramTTSService( api_key=os.getenv("DEEPGRAM_API_KEY"), - settings=DeepgramTTSSettings( + settings=DeepgramTTSService.Settings( voice="aura-2-andromeda-en", ), ) llm = OpenAILLMService( api_key=os.getenv("OPENAI_API_KEY"), - settings=OpenAILLMSettings( + settings=OpenAILLMService.Settings( system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", ), ) diff --git a/examples/foundational/07c-interruptible-deepgram.py b/examples/foundational/07c-interruptible-deepgram.py index 521890f68..e00a9f191 100644 --- a/examples/foundational/07c-interruptible-deepgram.py +++ b/examples/foundational/07c-interruptible-deepgram.py @@ -23,8 +23,8 @@ from pipecat.processors.aggregators.llm_response_universal import ( from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport from pipecat.services.deepgram.stt import DeepgramSTTService -from pipecat.services.deepgram.tts import DeepgramTTSService, DeepgramTTSSettings -from pipecat.services.openai.llm import OpenAILLMService, OpenAILLMSettings +from pipecat.services.deepgram.tts import DeepgramTTSService +from pipecat.services.openai.llm import OpenAILLMService from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams @@ -57,14 +57,14 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): tts = DeepgramTTSService( api_key=os.getenv("DEEPGRAM_API_KEY"), - settings=DeepgramTTSSettings( + settings=DeepgramTTSService.Settings( voice="aura-2-andromeda-en", ), ) llm = OpenAILLMService( api_key=os.getenv("OPENAI_API_KEY"), - settings=OpenAILLMSettings( + settings=OpenAILLMService.Settings( system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", ), ) diff --git a/examples/foundational/07d-interruptible-elevenlabs-http.py b/examples/foundational/07d-interruptible-elevenlabs-http.py index 279f6c8a2..cf60ac3e7 100644 --- a/examples/foundational/07d-interruptible-elevenlabs-http.py +++ b/examples/foundational/07d-interruptible-elevenlabs-http.py @@ -24,8 +24,8 @@ from pipecat.processors.aggregators.llm_response_universal import ( from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport from pipecat.services.elevenlabs.stt import ElevenLabsSTTService -from pipecat.services.elevenlabs.tts import ElevenLabsHttpTTSService, ElevenLabsHttpTTSSettings -from pipecat.services.openai.llm import OpenAILLMService, OpenAILLMSettings +from pipecat.services.elevenlabs.tts import ElevenLabsHttpTTSService +from pipecat.services.openai.llm import OpenAILLMService from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams @@ -64,14 +64,14 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): tts = ElevenLabsHttpTTSService( api_key=os.getenv("ELEVENLABS_API_KEY", ""), aiohttp_session=session, - settings=ElevenLabsHttpTTSSettings( + settings=ElevenLabsHttpTTSService.Settings( voice=os.getenv("ELEVENLABS_VOICE_ID", ""), ), ) llm = OpenAILLMService( api_key=os.getenv("OPENAI_API_KEY"), - settings=OpenAILLMSettings( + settings=OpenAILLMService.Settings( system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", ), ) diff --git a/examples/foundational/07d-interruptible-elevenlabs.py b/examples/foundational/07d-interruptible-elevenlabs.py index 14e21e851..d14bc71cd 100644 --- a/examples/foundational/07d-interruptible-elevenlabs.py +++ b/examples/foundational/07d-interruptible-elevenlabs.py @@ -23,8 +23,8 @@ from pipecat.processors.aggregators.llm_response_universal import ( from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport from pipecat.services.elevenlabs.stt import ElevenLabsRealtimeSTTService -from pipecat.services.elevenlabs.tts import ElevenLabsTTSService, ElevenLabsTTSSettings -from pipecat.services.openai.llm import OpenAILLMService, OpenAILLMSettings +from pipecat.services.elevenlabs.tts import ElevenLabsTTSService +from pipecat.services.openai.llm import OpenAILLMService from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams @@ -57,14 +57,14 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): tts = ElevenLabsTTSService( api_key=os.getenv("ELEVENLABS_API_KEY", ""), - settings=ElevenLabsTTSSettings( + settings=ElevenLabsTTSService.Settings( voice=os.getenv("ELEVENLABS_VOICE_ID", ""), ), ) llm = OpenAILLMService( api_key=os.getenv("OPENAI_API_KEY"), - settings=OpenAILLMSettings( + settings=OpenAILLMService.Settings( system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", ), ) diff --git a/examples/foundational/07f-interruptible-azure-http.py b/examples/foundational/07f-interruptible-azure-http.py index ec5068b25..38a2410fc 100644 --- a/examples/foundational/07f-interruptible-azure-http.py +++ b/examples/foundational/07f-interruptible-azure-http.py @@ -22,7 +22,7 @@ from pipecat.processors.aggregators.llm_response_universal import ( ) from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport -from pipecat.services.azure.llm import AzureLLMService, AzureLLMSettings +from pipecat.services.azure.llm import AzureLLMService from pipecat.services.azure.stt import AzureSTTService from pipecat.services.azure.tts import AzureHttpTTSService from pipecat.transports.base_transport import BaseTransport, TransportParams @@ -65,7 +65,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): llm = AzureLLMService( api_key=os.getenv("AZURE_CHATGPT_API_KEY"), endpoint=os.getenv("AZURE_CHATGPT_ENDPOINT"), - settings=AzureLLMSettings( + settings=AzureLLMService.Settings( model=os.getenv("AZURE_CHATGPT_MODEL"), system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", ), diff --git a/examples/foundational/07f-interruptible-azure.py b/examples/foundational/07f-interruptible-azure.py index d905d59bb..b7ace8548 100644 --- a/examples/foundational/07f-interruptible-azure.py +++ b/examples/foundational/07f-interruptible-azure.py @@ -22,7 +22,7 @@ from pipecat.processors.aggregators.llm_response_universal import ( ) from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport -from pipecat.services.azure.llm import AzureLLMService, AzureLLMSettings +from pipecat.services.azure.llm import AzureLLMService from pipecat.services.azure.stt import AzureSTTService from pipecat.services.azure.tts import AzureTTSService from pipecat.transports.base_transport import BaseTransport, TransportParams @@ -65,7 +65,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): llm = AzureLLMService( api_key=os.getenv("AZURE_CHATGPT_API_KEY"), endpoint=os.getenv("AZURE_CHATGPT_ENDPOINT"), - settings=AzureLLMSettings( + settings=AzureLLMService.Settings( model=os.getenv("AZURE_CHATGPT_MODEL"), system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", ), diff --git a/examples/foundational/07g-interruptible-openai-http.py b/examples/foundational/07g-interruptible-openai-http.py index ee0071bcb..127b9b0c0 100644 --- a/examples/foundational/07g-interruptible-openai-http.py +++ b/examples/foundational/07g-interruptible-openai-http.py @@ -22,9 +22,9 @@ from pipecat.processors.aggregators.llm_response_universal import ( ) from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport -from pipecat.services.openai.llm import OpenAILLMService, OpenAILLMSettings -from pipecat.services.openai.stt import OpenAISTTService, OpenAISTTSettings -from pipecat.services.openai.tts import OpenAITTSService, OpenAITTSSettings +from pipecat.services.openai.llm import OpenAILLMService +from pipecat.services.openai.stt import OpenAISTTService +from pipecat.services.openai.tts import OpenAITTSService from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams @@ -54,7 +54,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): stt = OpenAISTTService( api_key=os.getenv("OPENAI_API_KEY"), - settings=OpenAISTTSettings( + settings=OpenAISTTService.Settings( model="gpt-4o-transcribe", prompt="Expect words related to dogs, such as breed names.", ), @@ -62,14 +62,14 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): tts = OpenAITTSService( api_key=os.getenv("OPENAI_API_KEY"), - settings=OpenAITTSSettings( + settings=OpenAITTSService.Settings( voice="ballad", ), ) llm = OpenAILLMService( api_key=os.getenv("OPENAI_API_KEY"), - settings=OpenAILLMSettings( + settings=OpenAILLMService.Settings( system_instruction="You are very knowledgable about dogs. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", ), ) diff --git a/examples/foundational/07g-interruptible-openai.py b/examples/foundational/07g-interruptible-openai.py index 89d57fa70..9b8fbea09 100644 --- a/examples/foundational/07g-interruptible-openai.py +++ b/examples/foundational/07g-interruptible-openai.py @@ -22,9 +22,9 @@ from pipecat.processors.aggregators.llm_response_universal import ( ) from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport -from pipecat.services.openai.llm import OpenAILLMService, OpenAILLMSettings -from pipecat.services.openai.stt import OpenAIRealtimeSTTService, OpenAIRealtimeSTTSettings -from pipecat.services.openai.tts import OpenAITTSService, OpenAITTSSettings +from pipecat.services.openai.llm import OpenAILLMService +from pipecat.services.openai.stt import OpenAIRealtimeSTTService +from pipecat.services.openai.tts import OpenAITTSService from pipecat.transcriptions.language import Language from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams @@ -55,7 +55,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): stt = OpenAIRealtimeSTTService( api_key=os.getenv("OPENAI_API_KEY"), - settings=OpenAIRealtimeSTTSettings( + settings=OpenAIRealtimeSTTService.Settings( model="gpt-4o-transcribe", prompt="Expect words related to dogs, such as breed names.", language=Language.EN, @@ -64,14 +64,14 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): tts = OpenAITTSService( api_key=os.getenv("OPENAI_API_KEY"), - settings=OpenAITTSSettings( + settings=OpenAITTSService.Settings( voice="ballad", ), ) llm = OpenAILLMService( api_key=os.getenv("OPENAI_API_KEY"), - settings=OpenAILLMSettings( + settings=OpenAILLMService.Settings( system_instruction="You are very knowledgable about dogs. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", ), ) diff --git a/examples/foundational/07h-interruptible-openpipe.py b/examples/foundational/07h-interruptible-openpipe.py index f744fee4e..eaaa6fedd 100644 --- a/examples/foundational/07h-interruptible-openpipe.py +++ b/examples/foundational/07h-interruptible-openpipe.py @@ -23,9 +23,9 @@ from pipecat.processors.aggregators.llm_response_universal import ( ) from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport -from pipecat.services.cartesia.tts import CartesiaTTSService, CartesiaTTSSettings +from pipecat.services.cartesia.tts import CartesiaTTSService from pipecat.services.deepgram.stt import DeepgramSTTService -from pipecat.services.openpipe.llm import OpenPipeLLMService, OpenPipeLLMSettings +from pipecat.services.openpipe.llm import OpenPipeLLMService from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams @@ -57,7 +57,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): tts = CartesiaTTSService( api_key=os.getenv("CARTESIA_API_KEY"), - settings=CartesiaTTSSettings( + settings=CartesiaTTSService.Settings( voice="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady ), ) @@ -67,7 +67,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): api_key=os.getenv("OPENAI_API_KEY"), openpipe_api_key=os.getenv("OPENPIPE_API_KEY"), tags={"conversation_id": f"pipecat-{timestamp}"}, - settings=OpenPipeLLMSettings( + settings=OpenPipeLLMService.Settings( system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", ), ) diff --git a/examples/foundational/07i-interruptible-xtts.py b/examples/foundational/07i-interruptible-xtts.py index c5bb61419..3246d5da9 100644 --- a/examples/foundational/07i-interruptible-xtts.py +++ b/examples/foundational/07i-interruptible-xtts.py @@ -24,8 +24,8 @@ from pipecat.processors.aggregators.llm_response_universal import ( from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport from pipecat.services.deepgram.stt import DeepgramSTTService -from pipecat.services.openai.llm import OpenAILLMService, OpenAILLMSettings -from pipecat.services.xtts.tts import XTTSService, XTTSTTSSettings +from pipecat.services.openai.llm import OpenAILLMService +from pipecat.services.xtts.tts import XTTSService from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams @@ -59,7 +59,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): tts = XTTSService( aiohttp_session=session, - settings=XTTSTTSSettings( + settings=XTTSService.Settings( voice="Claribel Dervla", ), base_url="http://localhost:8000", @@ -67,7 +67,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): llm = OpenAILLMService( api_key=os.getenv("OPENAI_API_KEY"), - settings=OpenAILLMSettings( + settings=OpenAILLMService.Settings( system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", ), ) diff --git a/examples/foundational/07j-interruptible-gladia-vad.py b/examples/foundational/07j-interruptible-gladia-vad.py index ca2687d43..b25ab7275 100644 --- a/examples/foundational/07j-interruptible-gladia-vad.py +++ b/examples/foundational/07j-interruptible-gladia-vad.py @@ -22,10 +22,10 @@ from pipecat.processors.aggregators.llm_response_universal import ( ) from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport -from pipecat.services.cartesia.tts import CartesiaTTSService, CartesiaTTSSettings +from pipecat.services.cartesia.tts import CartesiaTTSService from pipecat.services.gladia.config import LanguageConfig -from pipecat.services.gladia.stt import GladiaSTTService, GladiaSTTSettings -from pipecat.services.openai.llm import OpenAILLMService, OpenAILLMSettings +from pipecat.services.gladia.stt import GladiaSTTService +from pipecat.services.openai.llm import OpenAILLMService from pipecat.transcriptions.language import Language from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams @@ -58,7 +58,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): stt = GladiaSTTService( api_key=os.getenv("GLADIA_API_KEY", ""), region=os.getenv("GLADIA_REGION"), - settings=GladiaSTTSettings( + settings=GladiaSTTService.Settings( language_config=LanguageConfig( languages=[Language.EN], ), @@ -68,14 +68,14 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): tts = CartesiaTTSService( api_key=os.getenv("CARTESIA_API_KEY", ""), - settings=CartesiaTTSSettings( + settings=CartesiaTTSService.Settings( voice="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady ), ) llm = OpenAILLMService( api_key=os.getenv("OPENAI_API_KEY", ""), - settings=OpenAILLMSettings( + settings=OpenAILLMService.Settings( system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", ), ) diff --git a/examples/foundational/07j-interruptible-gladia.py b/examples/foundational/07j-interruptible-gladia.py index 42ee1b1cc..d1fee759b 100644 --- a/examples/foundational/07j-interruptible-gladia.py +++ b/examples/foundational/07j-interruptible-gladia.py @@ -22,10 +22,10 @@ from pipecat.processors.aggregators.llm_response_universal import ( ) from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport -from pipecat.services.cartesia.tts import CartesiaTTSService, CartesiaTTSSettings +from pipecat.services.cartesia.tts import CartesiaTTSService from pipecat.services.gladia.config import LanguageConfig -from pipecat.services.gladia.stt import GladiaSTTService, GladiaSTTSettings -from pipecat.services.openai.llm import OpenAILLMService, OpenAILLMSettings +from pipecat.services.gladia.stt import GladiaSTTService +from pipecat.services.openai.llm import OpenAILLMService from pipecat.transcriptions.language import Language from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams @@ -57,7 +57,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): stt = GladiaSTTService( api_key=os.getenv("GLADIA_API_KEY", ""), region=os.getenv("GLADIA_REGION"), - settings=GladiaSTTSettings( + settings=GladiaSTTService.Settings( language_config=LanguageConfig( languages=[Language.EN], ) @@ -66,14 +66,14 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): tts = CartesiaTTSService( api_key=os.getenv("CARTESIA_API_KEY", ""), - settings=CartesiaTTSSettings( + settings=CartesiaTTSService.Settings( voice="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady ), ) llm = OpenAILLMService( api_key=os.getenv("OPENAI_API_KEY", ""), - settings=OpenAILLMSettings( + settings=OpenAILLMService.Settings( system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", ), ) diff --git a/examples/foundational/07k-interruptible-lmnt.py b/examples/foundational/07k-interruptible-lmnt.py index 091b72499..a41f1ae2e 100644 --- a/examples/foundational/07k-interruptible-lmnt.py +++ b/examples/foundational/07k-interruptible-lmnt.py @@ -23,8 +23,8 @@ from pipecat.processors.aggregators.llm_response_universal import ( from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport from pipecat.services.deepgram.stt import DeepgramSTTService -from pipecat.services.lmnt.tts import LmntTTSService, LmntTTSSettings -from pipecat.services.openai.llm import OpenAILLMService, OpenAILLMSettings +from pipecat.services.lmnt.tts import LmntTTSService +from pipecat.services.openai.llm import OpenAILLMService from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams @@ -56,14 +56,14 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): tts = LmntTTSService( api_key=os.getenv("LMNT_API_KEY"), - settings=LmntTTSSettings( + settings=LmntTTSService.Settings( voice="morgan", ), ) llm = OpenAILLMService( api_key=os.getenv("OPENAI_API_KEY"), - settings=OpenAILLMSettings( + settings=OpenAILLMService.Settings( system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", ), ) diff --git a/examples/foundational/07l-interruptible-groq.py b/examples/foundational/07l-interruptible-groq.py index 8d2125546..208d39c2d 100644 --- a/examples/foundational/07l-interruptible-groq.py +++ b/examples/foundational/07l-interruptible-groq.py @@ -22,7 +22,7 @@ from pipecat.processors.aggregators.llm_response_universal import ( ) from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport -from pipecat.services.groq.llm import GroqLLMService, GroqLLMSettings +from pipecat.services.groq.llm import GroqLLMService from pipecat.services.groq.stt import GroqSTTService from pipecat.services.groq.tts import GroqTTSService from pipecat.transports.base_transport import BaseTransport, TransportParams @@ -56,7 +56,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): llm = GroqLLMService( api_key=os.getenv("GROQ_API_KEY"), - settings=GroqLLMSettings( + settings=GroqLLMService.Settings( model="meta-llama/llama-4-maverick-17b-128e-instruct", system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", ), diff --git a/examples/foundational/07m-interruptible-aws-strands.py b/examples/foundational/07m-interruptible-aws-strands.py index e5c6f6f01..5d7b5fc8e 100644 --- a/examples/foundational/07m-interruptible-aws-strands.py +++ b/examples/foundational/07m-interruptible-aws-strands.py @@ -22,7 +22,7 @@ from pipecat.processors.frameworks.strands_agents import StrandsAgentsProcessor from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport from pipecat.services.aws.stt import AWSTranscribeSTTService -from pipecat.services.aws.tts import AWSPollyTTSService, AWSPollyTTSSettings +from pipecat.services.aws.tts import AWSPollyTTSService from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams @@ -95,7 +95,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): tts = AWSPollyTTSService( region="us-west-2", # only specific regions support generative TTS - settings=AWSPollyTTSSettings( + settings=AWSPollyTTSService.Settings( voice="Joanna", engine="generative", rate="1.1", diff --git a/examples/foundational/07m-interruptible-aws.py b/examples/foundational/07m-interruptible-aws.py index 8ddec82ef..ff3b6a789 100644 --- a/examples/foundational/07m-interruptible-aws.py +++ b/examples/foundational/07m-interruptible-aws.py @@ -20,9 +20,9 @@ from pipecat.processors.aggregators.llm_response_universal import ( ) from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport -from pipecat.services.aws.llm import AWSBedrockLLMService, AWSBedrockLLMSettings +from pipecat.services.aws.llm import AWSBedrockLLMService from pipecat.services.aws.stt import AWSTranscribeSTTService -from pipecat.services.aws.tts import AWSPollyTTSService, AWSPollyTTSSettings +from pipecat.services.aws.tts import AWSPollyTTSService from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams @@ -54,7 +54,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): tts = AWSPollyTTSService( region="us-west-2", # only specific regions support generative TTS - settings=AWSPollyTTSSettings( + settings=AWSPollyTTSService.Settings( voice="Joanna", engine="generative", rate="1.1", @@ -63,7 +63,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): llm = AWSBedrockLLMService( aws_region="us-west-2", - settings=AWSBedrockLLMSettings( + settings=AWSBedrockLLMService.Settings( model="us.anthropic.claude-sonnet-4-6", temperature=0.8, system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", diff --git a/examples/foundational/07n-interruptible-gemini-image.py b/examples/foundational/07n-interruptible-gemini-image.py index 8369f1de6..ad292ab03 100644 --- a/examples/foundational/07n-interruptible-gemini-image.py +++ b/examples/foundational/07n-interruptible-gemini-image.py @@ -37,9 +37,9 @@ from pipecat.processors.aggregators.llm_response_universal import ( ) from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport -from pipecat.services.google.llm import GoogleLLMService, GoogleLLMSettings -from pipecat.services.google.stt import GoogleSTTService, GoogleSTTSettings -from pipecat.services.google.tts import GoogleTTSService, GoogleTTSSettings +from pipecat.services.google.llm import GoogleLLMService +from pipecat.services.google.stt import GoogleSTTService +from pipecat.services.google.tts import GoogleTTSService from pipecat.transcriptions.language import Language from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams @@ -71,14 +71,14 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): stt = GoogleSTTService( credentials=os.getenv("GOOGLE_TEST_CREDENTIALS"), - settings=GoogleSTTSettings( + settings=GoogleSTTService.Settings( languages=[Language.EN_US], ), ) tts = GoogleTTSService( credentials=os.getenv("GOOGLE_TEST_CREDENTIALS"), - settings=GoogleTTSSettings( + settings=GoogleTTSService.Settings( voice="en-US-Chirp3-HD-Charon", language=Language.EN_US, ), @@ -86,7 +86,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): llm = GoogleLLMService( api_key=os.getenv("GOOGLE_API_KEY"), - settings=GoogleLLMSettings( + settings=GoogleLLMService.Settings( model="gemini-2.5-flash-image", # model="gemini-3-pro-image-preview", # A more powerful model, but slower, system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", diff --git a/examples/foundational/07n-interruptible-gemini.py b/examples/foundational/07n-interruptible-gemini.py index 92220bce5..3d8857708 100644 --- a/examples/foundational/07n-interruptible-gemini.py +++ b/examples/foundational/07n-interruptible-gemini.py @@ -22,9 +22,9 @@ from pipecat.processors.aggregators.llm_response_universal import ( ) from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport -from pipecat.services.google.llm import GoogleLLMService, GoogleLLMSettings -from pipecat.services.google.stt import GoogleSTTService, GoogleSTTSettings -from pipecat.services.google.tts import GeminiTTSService, GeminiTTSSettings +from pipecat.services.google.llm import GoogleLLMService +from pipecat.services.google.stt import GoogleSTTService +from pipecat.services.google.tts import GeminiTTSService from pipecat.transcriptions.language import Language from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams @@ -54,7 +54,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): logger.info(f"Starting bot with Gemini TTS") stt = GoogleSTTService( - settings=GoogleSTTSettings( + settings=GoogleSTTService.Settings( languages=[Language.EN_US], ), credentials=os.getenv("GOOGLE_TEST_CREDENTIALS"), @@ -62,7 +62,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): tts = GeminiTTSService( credentials=os.getenv("GOOGLE_TEST_CREDENTIALS"), - settings=GeminiTTSSettings( + settings=GeminiTTSService.Settings( model="gemini-2.5-flash-tts", voice="Charon", language=Language.EN_US, @@ -73,7 +73,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): llm = GoogleLLMService( api_key=os.getenv("GOOGLE_API_KEY"), model="gemini-2.5-flash", - settings=GoogleLLMSettings( + settings=GoogleLLMService.Settings( system_instruction="""You are a helpful AI assistant in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. IMPORTANT: You're using Gemini TTS which supports expressive markup tags. You can use these tags in your responses: diff --git a/examples/foundational/07n-interruptible-google-http.py b/examples/foundational/07n-interruptible-google-http.py index b137bcd7f..91e822ec0 100644 --- a/examples/foundational/07n-interruptible-google-http.py +++ b/examples/foundational/07n-interruptible-google-http.py @@ -22,9 +22,9 @@ from pipecat.processors.aggregators.llm_response_universal import ( ) from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport -from pipecat.services.google.llm import GoogleLLMService, GoogleLLMSettings -from pipecat.services.google.stt import GoogleSTTService, GoogleSTTSettings -from pipecat.services.google.tts import GoogleHttpTTSService, GoogleHttpTTSSettings +from pipecat.services.google.llm import GoogleLLMService +from pipecat.services.google.stt import GoogleSTTService +from pipecat.services.google.tts import GoogleHttpTTSService from pipecat.transcriptions.language import Language from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams @@ -54,7 +54,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): logger.info(f"Starting bot") stt = GoogleSTTService( - settings=GoogleSTTSettings( + settings=GoogleSTTService.Settings( languages=[Language.EN_US], # Add model to use a specific model # model="chirp_3", @@ -64,7 +64,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): ) tts = GoogleHttpTTSService( - settings=GoogleHttpTTSSettings( + settings=GoogleHttpTTSService.Settings( voice="en-US-Chirp3-HD-Charon", language=Language.EN_US, ), @@ -73,7 +73,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): llm = GoogleLLMService( api_key=os.getenv("GOOGLE_API_KEY"), - settings=GoogleLLMSettings( + settings=GoogleLLMService.GoogleLLMSettings( model="gemini-2.5-flash", # force a certain amount of thinking if you want it # thinking=GoogleLLMService.ThinkingConfig(thinking_budget=4096) diff --git a/examples/foundational/07n-interruptible-google.py b/examples/foundational/07n-interruptible-google.py index 4f5409085..2f148bb13 100644 --- a/examples/foundational/07n-interruptible-google.py +++ b/examples/foundational/07n-interruptible-google.py @@ -22,9 +22,9 @@ from pipecat.processors.aggregators.llm_response_universal import ( ) from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport -from pipecat.services.google.llm import GoogleLLMService, GoogleLLMSettings -from pipecat.services.google.stt import GoogleSTTService, GoogleSTTSettings -from pipecat.services.google.tts import GoogleTTSService, GoogleTTSSettings +from pipecat.services.google.llm import GoogleLLMService +from pipecat.services.google.stt import GoogleSTTService +from pipecat.services.google.tts import GoogleTTSService from pipecat.transcriptions.language import Language from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams @@ -54,7 +54,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): logger.info(f"Starting bot") stt = GoogleSTTService( - settings=GoogleSTTSettings( + settings=GoogleSTTService.Settings( languages=[Language.EN_US], # Add model to use a specific model # model="chirp_3", @@ -64,7 +64,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): ) tts = GoogleTTSService( - settings=GoogleTTSSettings( + settings=GoogleTTSService.Settings( voice="en-US-Chirp3-HD-Charon", language=Language.EN_US, ), @@ -73,7 +73,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): llm = GoogleLLMService( api_key=os.getenv("GOOGLE_API_KEY"), - settings=GoogleLLMSettings( + settings=GoogleLLMService.Settings( model="gemini-2.5-flash", # force a certain amount of thinking if you want it # thinking=GoogleLLMService.ThinkingConfig(thinking_budget=4096), diff --git a/examples/foundational/07o-interruptible-assemblyai-turn-detection.py b/examples/foundational/07o-interruptible-assemblyai-turn-detection.py index 2c2ca5419..7f8c8169e 100644 --- a/examples/foundational/07o-interruptible-assemblyai-turn-detection.py +++ b/examples/foundational/07o-interruptible-assemblyai-turn-detection.py @@ -22,9 +22,9 @@ from pipecat.processors.aggregators.llm_response_universal import ( ) from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport -from pipecat.services.assemblyai.stt import AssemblyAISTTService, AssemblyAISTTSettings -from pipecat.services.cartesia.tts import CartesiaTTSService, CartesiaTTSSettings -from pipecat.services.openai.llm import OpenAILLMService, OpenAILLMSettings +from pipecat.services.assemblyai.stt import AssemblyAISTTService +from pipecat.services.cartesia.tts import CartesiaTTSService +from pipecat.services.openai.llm import OpenAILLMService from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams @@ -93,7 +93,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): stt = AssemblyAISTTService( api_key=os.getenv("ASSEMBLYAI_API_KEY"), vad_force_turn_endpoint=False, # Use AssemblyAI's built-in turn detection - settings=AssemblyAISTTSettings( + settings=AssemblyAISTTService.Settings( model="u3-rt-pro", # Optional: Tune turn detection timing (defaults shown below) # min_turn_silence=100, # Default @@ -107,14 +107,14 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): tts = CartesiaTTSService( api_key=os.getenv("CARTESIA_API_KEY"), - settings=CartesiaTTSSettings( + settings=CartesiaTTSService.Settings( voice="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady ), ) llm = OpenAILLMService( api_key=os.getenv("OPENAI_API_KEY"), - settings=OpenAILLMSettings( + settings=OpenAILLMService.Settings( system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", ), ) diff --git a/examples/foundational/07o-interruptible-assemblyai.py b/examples/foundational/07o-interruptible-assemblyai.py index 9b60f3e98..700ec404e 100644 --- a/examples/foundational/07o-interruptible-assemblyai.py +++ b/examples/foundational/07o-interruptible-assemblyai.py @@ -23,8 +23,8 @@ from pipecat.processors.aggregators.llm_response_universal import ( from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport from pipecat.services.assemblyai.stt import AssemblyAISTTService -from pipecat.services.cartesia.tts import CartesiaTTSService, CartesiaTTSSettings -from pipecat.services.openai.llm import OpenAILLMService, OpenAILLMSettings +from pipecat.services.cartesia.tts import CartesiaTTSService +from pipecat.services.openai.llm import OpenAILLMService from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams @@ -59,14 +59,14 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): tts = CartesiaTTSService( api_key=os.getenv("CARTESIA_API_KEY"), - settings=CartesiaTTSSettings( + settings=CartesiaTTSService.Settings( voice="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady ), ) llm = OpenAILLMService( api_key=os.getenv("OPENAI_API_KEY"), - settings=OpenAILLMSettings( + settings=OpenAILLMService.Settings( system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", ), ) diff --git a/examples/foundational/07p-interruptible-krisp-viva.py b/examples/foundational/07p-interruptible-krisp-viva.py index 67a29bd89..b9eda804c 100644 --- a/examples/foundational/07p-interruptible-krisp-viva.py +++ b/examples/foundational/07p-interruptible-krisp-viva.py @@ -43,9 +43,9 @@ from pipecat.processors.aggregators.llm_response_universal import ( ) from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport -from pipecat.services.cartesia.tts import CartesiaTTSService, CartesiaTTSSettings +from pipecat.services.cartesia.tts import CartesiaTTSService from pipecat.services.deepgram.stt import DeepgramSTTService -from pipecat.services.openai.llm import OpenAILLMService, OpenAILLMSettings +from pipecat.services.openai.llm import OpenAILLMService from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams @@ -85,14 +85,14 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): tts = CartesiaTTSService( api_key=os.getenv("CARTESIA_API_KEY"), - settings=CartesiaTTSSettings( + settings=CartesiaTTSService.Settings( voice="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady ), ) llm = OpenAILLMService( api_key=os.getenv("OPENAI_API_KEY"), - settings=OpenAILLMSettings( + settings=OpenAILLMService.Settings( system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", ), ) diff --git a/examples/foundational/07p-interruptible-krisp.py b/examples/foundational/07p-interruptible-krisp.py index 5b760e768..800bc6fbc 100644 --- a/examples/foundational/07p-interruptible-krisp.py +++ b/examples/foundational/07p-interruptible-krisp.py @@ -24,8 +24,8 @@ from pipecat.processors.aggregators.llm_response_universal import ( from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport from pipecat.services.deepgram.stt import DeepgramSTTService -from pipecat.services.deepgram.tts import DeepgramTTSService, DeepgramTTSSettings -from pipecat.services.openai.llm import OpenAILLMService, OpenAILLMSettings +from pipecat.services.deepgram.tts import DeepgramTTSService +from pipecat.services.openai.llm import OpenAILLMService from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams @@ -60,14 +60,14 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): tts = DeepgramTTSService( api_key=os.getenv("DEEPGRAM_API_KEY"), - settings=DeepgramTTSSettings( + settings=DeepgramTTSService.Settings( voice="aura-helios-en", ), ) llm = OpenAILLMService( api_key=os.getenv("OPENAI_API_KEY"), - settings=OpenAILLMSettings( + settings=OpenAILLMService.Settings( system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", ), ) diff --git a/examples/foundational/07q-interruptible-rime-http.py b/examples/foundational/07q-interruptible-rime-http.py index 8324d546e..f143ee287 100644 --- a/examples/foundational/07q-interruptible-rime-http.py +++ b/examples/foundational/07q-interruptible-rime-http.py @@ -24,8 +24,8 @@ from pipecat.processors.aggregators.llm_response_universal import ( from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport from pipecat.services.deepgram.stt import DeepgramSTTService -from pipecat.services.openai.llm import OpenAILLMService, OpenAILLMSettings -from pipecat.services.rime.tts import RimeHttpTTSService, RimeTTSSettings +from pipecat.services.openai.llm import OpenAILLMService +from pipecat.services.rime.tts import RimeHttpTTSService from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams @@ -60,7 +60,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): tts = RimeHttpTTSService( api_key=os.getenv("RIME_API_KEY", ""), - settings=RimeTTSSettings( + settings=RimeHttpTTSService.Settings( voice="luna", model="arcana", ), @@ -70,7 +70,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): llm = OpenAILLMService( api_key=os.getenv("OPENAI_API_KEY"), - settings=OpenAILLMSettings( + settings=OpenAILLMService.Settings( system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", ), ) diff --git a/examples/foundational/07q-interruptible-rime.py b/examples/foundational/07q-interruptible-rime.py index 5379e9914..dde507ee1 100644 --- a/examples/foundational/07q-interruptible-rime.py +++ b/examples/foundational/07q-interruptible-rime.py @@ -23,8 +23,8 @@ from pipecat.processors.aggregators.llm_response_universal import ( from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport from pipecat.services.deepgram.stt import DeepgramSTTService -from pipecat.services.openai.llm import OpenAILLMService, OpenAILLMSettings -from pipecat.services.rime.tts import RimeTTSService, RimeTTSSettings +from pipecat.services.openai.llm import OpenAILLMService +from pipecat.services.rime.tts import RimeTTSService from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams @@ -56,14 +56,14 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): tts = RimeTTSService( api_key=os.getenv("RIME_API_KEY", ""), - settings=RimeTTSSettings( + settings=RimeTTSService.Settings( voice="luna", ), ) llm = OpenAILLMService( api_key=os.getenv("OPENAI_API_KEY"), - settings=OpenAILLMSettings( + settings=OpenAILLMService.Settings( system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", ), ) diff --git a/examples/foundational/07r-interruptible-nvidia.py b/examples/foundational/07r-interruptible-nvidia.py index 70c151f11..2e69dd50f 100644 --- a/examples/foundational/07r-interruptible-nvidia.py +++ b/examples/foundational/07r-interruptible-nvidia.py @@ -22,7 +22,7 @@ from pipecat.processors.aggregators.llm_response_universal import ( ) from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport -from pipecat.services.nvidia.llm import NvidiaLLMService, NvidiaLLMSettings +from pipecat.services.nvidia.llm import NvidiaLLMService from pipecat.services.nvidia.stt import NvidiaSTTService from pipecat.services.nvidia.tts import NvidiaTTSService from pipecat.transports.base_transport import BaseTransport, TransportParams @@ -56,7 +56,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): llm = NvidiaLLMService( api_key=os.getenv("NVIDIA_API_KEY"), - settings=NvidiaLLMSettings( + settings=NvidiaLLMService.Settings( model="meta/llama-3.3-70b-instruct", system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", ), diff --git a/examples/foundational/07s-interruptible-google-audio-in.py b/examples/foundational/07s-interruptible-google-audio-in.py index 31bfbcc35..6de7e1966 100644 --- a/examples/foundational/07s-interruptible-google-audio-in.py +++ b/examples/foundational/07s-interruptible-google-audio-in.py @@ -36,8 +36,8 @@ from pipecat.processors.aggregators.llm_response_universal import ( from pipecat.processors.frame_processor import FrameProcessor from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport -from pipecat.services.google.llm import GoogleLLMService, GoogleLLMSettings -from pipecat.services.google.tts import GoogleTTSService, GoogleTTSSettings +from pipecat.services.google.llm import GoogleLLMService +from pipecat.services.google.tts import GoogleTTSService from pipecat.transcriptions.language import Language from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams @@ -216,7 +216,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): llm = GoogleLLMService( api_key=os.getenv("GOOGLE_API_KEY"), - settings=GoogleLLMSettings( + settings=GoogleLLMService.Settings( model="gemini-2.5-flash", system_instruction=system_message, # force a certain amount of thinking if you want it @@ -225,7 +225,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): ) tts = GoogleTTSService( - settings=GoogleTTSSettings( + settings=GoogleTTSService.Settings( voice="en-US-Chirp3-HD-Charon", language=Language.EN_US, ), diff --git a/examples/foundational/07t-interruptible-fish.py b/examples/foundational/07t-interruptible-fish.py index caeab20c6..d51e3a71e 100644 --- a/examples/foundational/07t-interruptible-fish.py +++ b/examples/foundational/07t-interruptible-fish.py @@ -23,8 +23,8 @@ from pipecat.processors.aggregators.llm_response_universal import ( from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport from pipecat.services.deepgram.stt import DeepgramSTTService -from pipecat.services.fish.tts import FishAudioTTSService, FishAudioTTSSettings -from pipecat.services.openai.llm import OpenAILLMService, OpenAILLMSettings +from pipecat.services.fish.tts import FishAudioTTSService +from pipecat.services.openai.llm import OpenAILLMService from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams @@ -57,14 +57,14 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): tts = FishAudioTTSService( api_key=os.getenv("FISH_API_KEY"), - settings=FishAudioTTSSettings( + settings=FishAudioTTSService.Settings( voice="4ce7e917cedd4bc2bb2e6ff3a46acaa1", # Barack Obama ), ) llm = OpenAILLMService( api_key=os.getenv("OPENAI_API_KEY"), - settings=OpenAILLMSettings( + settings=OpenAILLMService.Settings( system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", ), ) diff --git a/examples/foundational/07v-interruptible-neuphonic-http.py b/examples/foundational/07v-interruptible-neuphonic-http.py index 8ebfe9002..bc2bbe983 100644 --- a/examples/foundational/07v-interruptible-neuphonic-http.py +++ b/examples/foundational/07v-interruptible-neuphonic-http.py @@ -24,8 +24,8 @@ from pipecat.processors.aggregators.llm_response_universal import ( from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport from pipecat.services.deepgram.stt import DeepgramSTTService -from pipecat.services.neuphonic.tts import NeuphonicHttpTTSService, NeuphonicTTSSettings -from pipecat.services.openai.llm import OpenAILLMService, OpenAILLMSettings +from pipecat.services.neuphonic.tts import NeuphonicHttpTTSService +from pipecat.services.openai.llm import OpenAILLMService from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams @@ -60,7 +60,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): tts = NeuphonicHttpTTSService( api_key=os.getenv("NEUPHONIC_API_KEY"), - settings=NeuphonicTTSSettings( + settings=NeuphonicHttpTTSService.Settings( voice="fc854436-2dac-4d21-aa69-ae17b54e98eb", # Emily ), aiohttp_session=session, @@ -68,7 +68,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): llm = OpenAILLMService( api_key=os.getenv("OPENAI_API_KEY"), - settings=OpenAILLMSettings( + settings=OpenAILLMService.Settings( system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", ), ) diff --git a/examples/foundational/07v-interruptible-neuphonic.py b/examples/foundational/07v-interruptible-neuphonic.py index 8eee009f3..b44632286 100644 --- a/examples/foundational/07v-interruptible-neuphonic.py +++ b/examples/foundational/07v-interruptible-neuphonic.py @@ -23,8 +23,8 @@ from pipecat.processors.aggregators.llm_response_universal import ( from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport from pipecat.services.deepgram.stt import DeepgramSTTService -from pipecat.services.neuphonic.tts import NeuphonicTTSService, NeuphonicTTSSettings -from pipecat.services.openai.llm import OpenAILLMService, OpenAILLMSettings +from pipecat.services.neuphonic.tts import NeuphonicTTSService +from pipecat.services.openai.llm import OpenAILLMService from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams @@ -56,14 +56,14 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): tts = NeuphonicTTSService( api_key=os.getenv("NEUPHONIC_API_KEY"), - settings=NeuphonicTTSSettings( + settings=NeuphonicTTSService.Settings( voice="fc854436-2dac-4d21-aa69-ae17b54e98eb", # Emily ), ) llm = OpenAILLMService( api_key=os.getenv("OPENAI_API_KEY"), - settings=OpenAILLMSettings( + settings=OpenAILLMService.Settings( system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", ), ) diff --git a/examples/foundational/07w-interruptible-fal.py b/examples/foundational/07w-interruptible-fal.py index 81045df5f..89a38d23c 100644 --- a/examples/foundational/07w-interruptible-fal.py +++ b/examples/foundational/07w-interruptible-fal.py @@ -23,9 +23,9 @@ from pipecat.processors.aggregators.llm_response_universal import ( ) from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport -from pipecat.services.cartesia.tts import CartesiaTTSService, CartesiaTTSSettings +from pipecat.services.cartesia.tts import CartesiaTTSService from pipecat.services.fal.stt import FalSTTService -from pipecat.services.openai.llm import OpenAILLMService, OpenAILLMSettings +from pipecat.services.openai.llm import OpenAILLMService from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams @@ -62,14 +62,14 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): tts = CartesiaTTSService( api_key=os.getenv("CARTESIA_API_KEY"), - settings=CartesiaTTSSettings( + settings=CartesiaTTSService.Settings( voice="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady ), ) llm = OpenAILLMService( api_key=os.getenv("OPENAI_API_KEY"), - settings=OpenAILLMSettings( + settings=OpenAILLMService.Settings( system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", ), ) diff --git a/examples/foundational/07x-interruptible-local.py b/examples/foundational/07x-interruptible-local.py index 0e5107890..e0ace854b 100644 --- a/examples/foundational/07x-interruptible-local.py +++ b/examples/foundational/07x-interruptible-local.py @@ -21,9 +21,9 @@ from pipecat.processors.aggregators.llm_response_universal import ( LLMContextAggregatorPair, LLMUserAggregatorParams, ) -from pipecat.services.cartesia.tts import CartesiaTTSService, CartesiaTTSSettings +from pipecat.services.cartesia.tts import CartesiaTTSService from pipecat.services.deepgram.stt import DeepgramSTTService -from pipecat.services.openai.llm import OpenAILLMService, OpenAILLMSettings +from pipecat.services.openai.llm import OpenAILLMService from pipecat.transports.local.audio import LocalAudioTransport, LocalAudioTransportParams load_dotenv(override=True) @@ -44,14 +44,14 @@ async def main(): tts = CartesiaTTSService( api_key=os.getenv("CARTESIA_API_KEY"), - settings=CartesiaTTSSettings( + settings=CartesiaTTSService.Settings( voice="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady ), ) llm = OpenAILLMService( api_key=os.getenv("OPENAI_API_KEY"), - settings=OpenAILLMSettings( + settings=OpenAILLMService.Settings( system_instruction="You are a helpful LLM. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", ), ) diff --git a/examples/foundational/07y-interruptible-minimax.py b/examples/foundational/07y-interruptible-minimax.py index 64fe7da06..d9bcef371 100644 --- a/examples/foundational/07y-interruptible-minimax.py +++ b/examples/foundational/07y-interruptible-minimax.py @@ -24,8 +24,8 @@ from pipecat.processors.aggregators.llm_response_universal import ( from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport from pipecat.services.deepgram.stt import DeepgramSTTService -from pipecat.services.minimax.tts import MiniMaxHttpTTSService, MiniMaxTTSSettings -from pipecat.services.openai.llm import OpenAILLMService, OpenAILLMSettings +from pipecat.services.minimax.tts import MiniMaxHttpTTSService +from pipecat.services.openai.llm import OpenAILLMService from pipecat.transcriptions.language import Language from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams @@ -63,14 +63,14 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): api_key=os.getenv("MINIMAX_API_KEY", ""), group_id=os.getenv("MINIMAX_GROUP_ID", ""), aiohttp_session=session, - settings=MiniMaxTTSSettings( + settings=MiniMaxHttpTTSService.Settings( language=Language.EN, ), ) llm = OpenAILLMService( api_key=os.getenv("OPENAI_API_KEY"), - settings=OpenAILLMSettings( + settings=OpenAILLMService.Settings( system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", ), ) diff --git a/examples/foundational/07z-interruptible-sarvam-http.py b/examples/foundational/07z-interruptible-sarvam-http.py index ac6ece100..76c892fd9 100644 --- a/examples/foundational/07z-interruptible-sarvam-http.py +++ b/examples/foundational/07z-interruptible-sarvam-http.py @@ -23,9 +23,9 @@ from pipecat.processors.aggregators.llm_response_universal import ( ) from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport -from pipecat.services.openai.llm import OpenAILLMService, OpenAILLMSettings -from pipecat.services.sarvam.stt import SarvamSTTService, SarvamSTTSettings -from pipecat.services.sarvam.tts import SarvamHttpTTSService, SarvamHttpTTSSettings +from pipecat.services.openai.llm import OpenAILLMService +from pipecat.services.sarvam.stt import SarvamSTTService +from pipecat.services.sarvam.tts import SarvamHttpTTSService from pipecat.transcriptions.language import Language from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams @@ -59,7 +59,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): async with aiohttp.ClientSession() as session: stt = SarvamSTTService( api_key=os.getenv("SARVAM_API_KEY"), - settings=SarvamSTTSettings( + settings=SarvamSTTService.Settings( model="saarika:v2.5", ), ) @@ -67,14 +67,14 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): tts = SarvamHttpTTSService( api_key=os.getenv("SARVAM_API_KEY"), aiohttp_session=session, - settings=SarvamHttpTTSSettings( + settings=SarvamHttpTTSService.Settings( language=Language.EN_IN, ), ) llm = OpenAILLMService( api_key=os.getenv("OPENAI_API_KEY"), - settings=OpenAILLMSettings( + settings=OpenAILLMService.Settings( system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", ), ) diff --git a/examples/foundational/07z-interruptible-sarvam.py b/examples/foundational/07z-interruptible-sarvam.py index e366b4d31..915ea2c3d 100644 --- a/examples/foundational/07z-interruptible-sarvam.py +++ b/examples/foundational/07z-interruptible-sarvam.py @@ -21,9 +21,9 @@ from pipecat.processors.aggregators.llm_response_universal import ( ) from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport -from pipecat.services.openai.llm import OpenAILLMService, OpenAILLMSettings -from pipecat.services.sarvam.stt import SarvamSTTService, SarvamSTTSettings -from pipecat.services.sarvam.tts import SarvamTTSService, SarvamTTSSettings +from pipecat.services.openai.llm import OpenAILLMService +from pipecat.services.sarvam.stt import SarvamSTTService +from pipecat.services.sarvam.tts import SarvamTTSService from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams @@ -54,21 +54,21 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): stt = SarvamSTTService( api_key=os.getenv("SARVAM_API_KEY"), - settings=SarvamSTTSettings( + settings=SarvamSTTService.Settings( model="saarika:v2.5", ), ) tts = SarvamTTSService( api_key=os.getenv("SARVAM_API_KEY"), - settings=SarvamTTSSettings( + settings=SarvamTTSService.Settings( model="bulbul:v2", voice="manisha", ), ) llm = OpenAILLMService( api_key=os.getenv("OPENAI_API_KEY"), - settings=OpenAILLMSettings( + settings=OpenAILLMService.Settings( system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", ), ) diff --git a/examples/foundational/07za-interruptible-soniox.py b/examples/foundational/07za-interruptible-soniox.py index 71011c5d9..d425be966 100644 --- a/examples/foundational/07za-interruptible-soniox.py +++ b/examples/foundational/07za-interruptible-soniox.py @@ -22,9 +22,9 @@ from pipecat.processors.aggregators.llm_response_universal import ( ) from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport -from pipecat.services.cartesia.tts import CartesiaTTSService, CartesiaTTSSettings -from pipecat.services.openai.llm import OpenAILLMService, OpenAILLMSettings -from pipecat.services.soniox.stt import SonioxSTTService, SonioxSTTSettings +from pipecat.services.cartesia.tts import CartesiaTTSService +from pipecat.services.openai.llm import OpenAILLMService +from pipecat.services.soniox.stt import SonioxSTTService from pipecat.transcriptions.language import Language from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams @@ -53,7 +53,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): stt = SonioxSTTService( api_key=os.getenv("SONIOX_API_KEY"), - settings=SonioxSTTSettings( + settings=SonioxSTTService.Settings( # Add language hints to use a specific language # Add strict mode to enforce the language hints language_hints=[Language.EN], @@ -63,14 +63,14 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): tts = CartesiaTTSService( api_key=os.getenv("CARTESIA_API_KEY"), - settings=CartesiaTTSSettings( + settings=CartesiaTTSService.Settings( voice="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady ), ) llm = OpenAILLMService( api_key=os.getenv("OPENAI_API_KEY"), - settings=OpenAILLMSettings( + settings=OpenAILLMService.Settings( system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", ), ) diff --git a/examples/foundational/07zb-interruptible-inworld-http.py b/examples/foundational/07zb-interruptible-inworld-http.py index 6e57fbb56..9f0027b42 100644 --- a/examples/foundational/07zb-interruptible-inworld-http.py +++ b/examples/foundational/07zb-interruptible-inworld-http.py @@ -24,8 +24,8 @@ from pipecat.processors.aggregators.llm_response_universal import ( from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport from pipecat.services.deepgram.stt import DeepgramSTTService -from pipecat.services.inworld.tts import InworldHttpTTSService, InworldTTSSettings -from pipecat.services.openai.llm import OpenAILLMService, OpenAILLMSettings +from pipecat.services.inworld.tts import InworldHttpTTSService +from pipecat.services.openai.llm import OpenAILLMService from pipecat.transports.base_output import BaseOutputTransport from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams @@ -59,7 +59,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): api_key=os.getenv("INWORLD_API_KEY", ""), aiohttp_session=session, streaming=True, - settings=InworldTTSSettings( + settings=InworldHttpTTSService.Settings( voice="Ashley", model="inworld-tts-1", ), @@ -68,7 +68,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): llm = OpenAILLMService( api_key=os.getenv("OPENAI_API_KEY"), - settings=OpenAILLMSettings( + settings=OpenAILLMService.Settings( system_instruction="You are a helpful AI demonstrating Inworld AI's TTS. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a friendly and helpful way.", ), ) diff --git a/examples/foundational/07zb-interruptible-inworld.py b/examples/foundational/07zb-interruptible-inworld.py index 6e2cd7aed..9f9384554 100644 --- a/examples/foundational/07zb-interruptible-inworld.py +++ b/examples/foundational/07zb-interruptible-inworld.py @@ -22,8 +22,8 @@ from pipecat.processors.aggregators.llm_response_universal import ( from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport from pipecat.services.deepgram.stt import DeepgramSTTService -from pipecat.services.inworld.tts import InworldTTSService, InworldTTSSettings -from pipecat.services.openai.llm import OpenAILLMService, OpenAILLMSettings +from pipecat.services.inworld.tts import InworldTTSService +from pipecat.services.openai.llm import OpenAILLMService from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams @@ -54,7 +54,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): tts = InworldTTSService( api_key=os.getenv("INWORLD_API_KEY", ""), - settings=InworldTTSSettings( + settings=InworldTTSService.Settings( voice="Ashley", model="inworld-tts-1", temperature=1.1, @@ -63,7 +63,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): llm = OpenAILLMService( api_key=os.getenv("OPENAI_API_KEY"), - settings=OpenAILLMSettings( + settings=OpenAILLMService.Settings( system_instruction="You are a helpful AI demonstrating Inworld AI's TTS. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a friendly and helpful way.", ), ) diff --git a/examples/foundational/07zc-interruptible-asyncai-http.py b/examples/foundational/07zc-interruptible-asyncai-http.py index 1fe69c38b..e95bd60b2 100644 --- a/examples/foundational/07zc-interruptible-asyncai-http.py +++ b/examples/foundational/07zc-interruptible-asyncai-http.py @@ -23,9 +23,9 @@ from pipecat.processors.aggregators.llm_response_universal import ( ) from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport -from pipecat.services.asyncai.tts import AsyncAIHttpTTSService, AsyncAITTSSettings +from pipecat.services.asyncai.tts import AsyncAIHttpTTSService from pipecat.services.deepgram.stt import DeepgramSTTService -from pipecat.services.openai.llm import OpenAILLMService, OpenAILLMSettings +from pipecat.services.openai.llm import OpenAILLMService from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams @@ -60,7 +60,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): tts = AsyncAIHttpTTSService( api_key=os.getenv("ASYNCAI_API_KEY", ""), - settings=AsyncAITTSSettings( + settings=AsyncAIHttpTTSService.Settings( voice="e0f39dc4-f691-4e78-bba5-5c636692cc04", ), aiohttp_session=session, @@ -68,7 +68,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): llm = OpenAILLMService( api_key=os.getenv("OPENAI_API_KEY"), - settings=OpenAILLMSettings( + settings=OpenAILLMService.Settings( system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", ), ) diff --git a/examples/foundational/07zc-interruptible-asyncai.py b/examples/foundational/07zc-interruptible-asyncai.py index 05113cdb9..40cdcf7ab 100644 --- a/examples/foundational/07zc-interruptible-asyncai.py +++ b/examples/foundational/07zc-interruptible-asyncai.py @@ -22,9 +22,9 @@ from pipecat.processors.aggregators.llm_response_universal import ( ) from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport -from pipecat.services.asyncai.tts import AsyncAITTSService, AsyncAITTSSettings +from pipecat.services.asyncai.tts import AsyncAITTSService from pipecat.services.deepgram.stt import DeepgramSTTService -from pipecat.services.openai.llm import OpenAILLMService, OpenAILLMSettings +from pipecat.services.openai.llm import OpenAILLMService from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams @@ -57,14 +57,14 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): tts = AsyncAITTSService( api_key=os.getenv("ASYNCAI_API_KEY", ""), - settings=AsyncAITTSSettings( + settings=AsyncAITTSService.Settings( voice="e0f39dc4-f691-4e78-bba5-5c636692cc04", ), ) llm = OpenAILLMService( api_key=os.getenv("OPENAI_API_KEY"), - settings=OpenAILLMSettings( + settings=OpenAILLMService.Settings( system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", ), ) diff --git a/examples/foundational/07zd-interruptible-aicoustics.py b/examples/foundational/07zd-interruptible-aicoustics.py index e8f55e4e0..923530943 100644 --- a/examples/foundational/07zd-interruptible-aicoustics.py +++ b/examples/foundational/07zd-interruptible-aicoustics.py @@ -25,9 +25,9 @@ from pipecat.processors.aggregators.llm_response_universal import ( from pipecat.processors.audio.audio_buffer_processor import AudioBufferProcessor from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport -from pipecat.services.cartesia.tts import CartesiaTTSService, CartesiaTTSSettings +from pipecat.services.cartesia.tts import CartesiaTTSService from pipecat.services.deepgram.stt import DeepgramSTTService -from pipecat.services.openai.llm import OpenAILLMService, OpenAILLMSettings +from pipecat.services.openai.llm import OpenAILLMService from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams @@ -77,14 +77,14 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): tts = CartesiaTTSService( api_key=os.getenv("CARTESIA_API_KEY"), - settings=CartesiaTTSSettings( + settings=CartesiaTTSService.Settings( voice="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady ), ) llm = OpenAILLMService( api_key=os.getenv("OPENAI_API_KEY"), - settings=OpenAILLMSettings( + settings=OpenAILLMService.Settings( system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", ), ) diff --git a/examples/foundational/07ze-interruptible-hume.py b/examples/foundational/07ze-interruptible-hume.py index fbe752a7d..ef19e3619 100644 --- a/examples/foundational/07ze-interruptible-hume.py +++ b/examples/foundational/07ze-interruptible-hume.py @@ -23,8 +23,8 @@ from pipecat.processors.aggregators.llm_response_universal import ( from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport from pipecat.services.deepgram.stt import DeepgramSTTService -from pipecat.services.hume.tts import HUME_SAMPLE_RATE, HumeTTSService, HumeTTSSettings -from pipecat.services.openai.llm import OpenAILLMService, OpenAILLMSettings +from pipecat.services.hume.tts import HUME_SAMPLE_RATE, HumeTTSService +from pipecat.services.openai.llm import OpenAILLMService from pipecat.transports.base_output import BaseOutputTransport from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams @@ -59,14 +59,14 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): tts = HumeTTSService( api_key=os.getenv("HUME_API_KEY"), # Replace with your Hume voice ID - settings=HumeTTSSettings( + settings=HumeTTSService.Settings( voice="f898a92e-685f-43fa-985b-a46920f0650b", ), ) llm = OpenAILLMService( api_key=os.getenv("OPENAI_API_KEY"), - settings=OpenAILLMSettings( + settings=OpenAILLMService.Settings( system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", ), ) diff --git a/examples/foundational/07zf-interruptible-gradium.py b/examples/foundational/07zf-interruptible-gradium.py index 41cdcd799..4b7e2f32b 100644 --- a/examples/foundational/07zf-interruptible-gradium.py +++ b/examples/foundational/07zf-interruptible-gradium.py @@ -21,9 +21,9 @@ from pipecat.processors.aggregators.llm_response_universal import ( ) from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport -from pipecat.services.gradium.stt import GradiumSTTService, GradiumSTTSettings -from pipecat.services.gradium.tts import GradiumTTSService, GradiumTTSSettings -from pipecat.services.openai.llm import OpenAILLMService, OpenAILLMSettings +from pipecat.services.gradium.stt import GradiumSTTService +from pipecat.services.gradium.tts import GradiumTTSService +from pipecat.services.openai.llm import OpenAILLMService from pipecat.transcriptions.language import Language from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams @@ -55,7 +55,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): stt = GradiumSTTService( api_key=os.getenv("GRADIUM_API_KEY"), api_endpoint_base_url="wss://us.api.gradium.ai/api/speech/asr", - settings=GradiumSTTSettings( + settings=GradiumSTTService.Settings( language=Language.EN, ), ) @@ -63,14 +63,14 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): tts = GradiumTTSService( api_key=os.getenv("GRADIUM_API_KEY"), url="wss://us.api.gradium.ai/api/speech/tts", - settings=GradiumTTSSettings( + settings=GradiumTTSService.Settings( voice="YTpq7expH9539ERJ", ), ) llm = OpenAILLMService( api_key=os.getenv("OPENAI_API_KEY"), - settings=OpenAILLMSettings( + settings=OpenAILLMService.Settings( system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", ), ) diff --git a/examples/foundational/07zg-interruptible-camb.py b/examples/foundational/07zg-interruptible-camb.py index 20bc8b665..e0f764f4e 100644 --- a/examples/foundational/07zg-interruptible-camb.py +++ b/examples/foundational/07zg-interruptible-camb.py @@ -21,9 +21,9 @@ from pipecat.processors.aggregators.llm_response_universal import ( ) from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport -from pipecat.services.camb.tts import CambTTSService, CambTTSSettings +from pipecat.services.camb.tts import CambTTSService from pipecat.services.deepgram.stt import DeepgramSTTService -from pipecat.services.openai.llm import OpenAILLMService, OpenAILLMSettings +from pipecat.services.openai.llm import OpenAILLMService from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams @@ -56,14 +56,14 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): tts = CambTTSService( api_key=os.getenv("CAMB_API_KEY"), - settings=CambTTSSettings( + settings=CambTTSService.Settings( model="mars-flash", ), ) llm = OpenAILLMService( api_key=os.getenv("OPENAI_API_KEY"), - settings=OpenAILLMSettings( + settings=OpenAILLMService.Settings( system_instruction="You are a helpful voice assistant powered by Camb AI text-to-speech. ", ), ) diff --git a/examples/foundational/07zi-interruptible-piper.py b/examples/foundational/07zi-interruptible-piper.py index f6d9bfeea..44b7d0efd 100644 --- a/examples/foundational/07zi-interruptible-piper.py +++ b/examples/foundational/07zi-interruptible-piper.py @@ -22,8 +22,8 @@ from pipecat.processors.aggregators.llm_response_universal import ( from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport from pipecat.services.deepgram.stt import DeepgramSTTService -from pipecat.services.openai.llm import OpenAILLMService, OpenAILLMSettings -from pipecat.services.piper.tts import PiperTTSService, PiperTTSSettings +from pipecat.services.openai.llm import OpenAILLMService +from pipecat.services.piper.tts import PiperTTSService from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams @@ -55,14 +55,14 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): stt = DeepgramSTTService(api_key=os.getenv("DEEPGRAM_API_KEY")) tts = PiperTTSService( - settings=PiperTTSSettings( + settings=PiperTTSService.Settings( voice="en_US-ryan-high", ), ) llm = OpenAILLMService( api_key=os.getenv("OPENAI_API_KEY"), - settings=OpenAILLMSettings( + settings=OpenAILLMService.Settings( system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", ), ) diff --git a/examples/foundational/07zj-interruptible-kokoro.py b/examples/foundational/07zj-interruptible-kokoro.py index da35b5d5c..0978ba720 100644 --- a/examples/foundational/07zj-interruptible-kokoro.py +++ b/examples/foundational/07zj-interruptible-kokoro.py @@ -22,8 +22,8 @@ from pipecat.processors.aggregators.llm_response_universal import ( from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport from pipecat.services.deepgram.stt import DeepgramSTTService -from pipecat.services.kokoro.tts import KokoroTTSService, KokoroTTSSettings -from pipecat.services.openai.llm import OpenAILLMService, OpenAILLMSettings +from pipecat.services.kokoro.tts import KokoroTTSService +from pipecat.services.openai.llm import OpenAILLMService from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams @@ -55,14 +55,14 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): stt = DeepgramSTTService(api_key=os.getenv("DEEPGRAM_API_KEY")) tts = KokoroTTSService( - settings=KokoroTTSSettings( + settings=KokoroTTSService.Settings( voice="af_heart", ), ) llm = OpenAILLMService( api_key=os.getenv("OPENAI_API_KEY"), - settings=OpenAILLMSettings( + settings=OpenAILLMService.Settings( system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", ), ) diff --git a/examples/foundational/07zk-interruptible-resemble.py b/examples/foundational/07zk-interruptible-resemble.py index c186db6be..88bcb724e 100644 --- a/examples/foundational/07zk-interruptible-resemble.py +++ b/examples/foundational/07zk-interruptible-resemble.py @@ -22,8 +22,8 @@ from pipecat.processors.aggregators.llm_response_universal import ( from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport from pipecat.services.deepgram.stt import DeepgramSTTService -from pipecat.services.openai.llm import OpenAILLMService, OpenAILLMSettings -from pipecat.services.resembleai.tts import ResembleAITTSService, ResembleAITTSSettings +from pipecat.services.openai.llm import OpenAILLMService +from pipecat.services.resembleai.tts import ResembleAITTSService from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams @@ -59,14 +59,14 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): tts = ResembleAITTSService( api_key=os.getenv("RESEMBLE_API_KEY"), - settings=ResembleAITTSSettings( + settings=ResembleAITTSService.Settings( voice=os.getenv("RESEMBLE_VOICE_UUID"), ), ) llm = OpenAILLMService( api_key=os.getenv("OPENAI_API_KEY"), - settings=OpenAILLMSettings( + settings=OpenAILLMService.Settings( system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", ), ) diff --git a/examples/foundational/08-custom-frame-processor.py b/examples/foundational/08-custom-frame-processor.py index 507de6d41..b6b1ef42c 100644 --- a/examples/foundational/08-custom-frame-processor.py +++ b/examples/foundational/08-custom-frame-processor.py @@ -26,9 +26,9 @@ from pipecat.processors.aggregators.llm_response_universal import ( from pipecat.processors.frame_processor import FrameDirection, FrameProcessor from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport -from pipecat.services.cartesia.tts import CartesiaTTSService, CartesiaTTSSettings +from pipecat.services.cartesia.tts import CartesiaTTSService from pipecat.services.deepgram.stt import DeepgramSTTService -from pipecat.services.openai.llm import OpenAILLMService, OpenAILLMSettings +from pipecat.services.openai.llm import OpenAILLMService from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams @@ -95,14 +95,14 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): tts = CartesiaTTSService( api_key=os.getenv("CARTESIA_API_KEY"), - settings=CartesiaTTSSettings( + settings=CartesiaTTSService.Settings( voice="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady ), ) llm = OpenAILLMService( api_key=os.getenv("OPENAI_API_KEY"), - settings=OpenAILLMSettings( + settings=OpenAILLMService.Settings( system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", ), ) diff --git a/examples/foundational/10-wake-phrase.py b/examples/foundational/10-wake-phrase.py index 04a1e40b8..44b580ad5 100644 --- a/examples/foundational/10-wake-phrase.py +++ b/examples/foundational/10-wake-phrase.py @@ -22,9 +22,9 @@ from pipecat.processors.aggregators.llm_response_universal import ( from pipecat.processors.filters.wake_check_filter import WakeCheckFilter from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport -from pipecat.services.cartesia.tts import CartesiaTTSService, CartesiaTTSSettings +from pipecat.services.cartesia.tts import CartesiaTTSService from pipecat.services.deepgram.stt import DeepgramSTTService -from pipecat.services.openai.llm import OpenAILLMService, OpenAILLMSettings +from pipecat.services.openai.llm import OpenAILLMService from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams @@ -56,14 +56,14 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): tts = CartesiaTTSService( api_key=os.getenv("CARTESIA_API_KEY"), - settings=CartesiaTTSSettings( + settings=CartesiaTTSService.Settings( voice="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady ), ) llm = OpenAILLMService( api_key=os.getenv("OPENAI_API_KEY"), - settings=OpenAILLMSettings( + settings=OpenAILLMService.Settings( system_instruction="You are a helpful assistant. Respond to what the user said in a creative and helpful way. Keep your responses brief.", ), ) diff --git a/examples/foundational/11-sound-effects.py b/examples/foundational/11-sound-effects.py index 664bd122c..87cb3f333 100644 --- a/examples/foundational/11-sound-effects.py +++ b/examples/foundational/11-sound-effects.py @@ -30,9 +30,9 @@ from pipecat.processors.frame_processor import FrameDirection, FrameProcessor from pipecat.processors.logger import FrameLogger from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport -from pipecat.services.cartesia.tts import CartesiaTTSService, CartesiaTTSSettings +from pipecat.services.cartesia.tts import CartesiaTTSService from pipecat.services.deepgram.stt import DeepgramSTTService -from pipecat.services.openai.llm import OpenAILLMService, OpenAILLMSettings +from pipecat.services.openai.llm import OpenAILLMService from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams @@ -106,14 +106,14 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): llm = OpenAILLMService( api_key=os.getenv("OPENAI_API_KEY"), - settings=OpenAILLMSettings( + settings=OpenAILLMService.Settings( system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", ), ) tts = CartesiaTTSService( api_key=os.getenv("CARTESIA_API_KEY"), - settings=CartesiaTTSSettings( + settings=CartesiaTTSService.Settings( voice="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady ), ) diff --git a/examples/foundational/12-describe-image-openai.py b/examples/foundational/12-describe-image-openai.py index d9b0be871..0888fa6bf 100644 --- a/examples/foundational/12-describe-image-openai.py +++ b/examples/foundational/12-describe-image-openai.py @@ -23,9 +23,9 @@ from pipecat.processors.aggregators.llm_response_universal import ( ) from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport -from pipecat.services.cartesia.tts import CartesiaTTSService, CartesiaTTSSettings +from pipecat.services.cartesia.tts import CartesiaTTSService from pipecat.services.deepgram.stt import DeepgramSTTService -from pipecat.services.openai.llm import OpenAILLMService, OpenAILLMSettings +from pipecat.services.openai.llm import OpenAILLMService from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams @@ -53,14 +53,14 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): tts = CartesiaTTSService( api_key=os.getenv("CARTESIA_API_KEY"), - settings=CartesiaTTSSettings( + settings=CartesiaTTSService.Settings( voice="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady ), ) llm = OpenAILLMService( api_key=os.getenv("OPENAI_API_KEY"), - settings=OpenAILLMSettings( + settings=OpenAILLMService.Settings( system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way. You are also able to describe images.", ), ) diff --git a/examples/foundational/12a-describe-image-anthropic.py b/examples/foundational/12a-describe-image-anthropic.py index 5a10f24a5..086e282dc 100644 --- a/examples/foundational/12a-describe-image-anthropic.py +++ b/examples/foundational/12a-describe-image-anthropic.py @@ -23,8 +23,8 @@ from pipecat.processors.aggregators.llm_response_universal import ( ) from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport -from pipecat.services.anthropic.llm import AnthropicLLMService, AnthropicLLMSettings -from pipecat.services.cartesia.tts import CartesiaTTSService, CartesiaTTSSettings +from pipecat.services.anthropic.llm import AnthropicLLMService +from pipecat.services.cartesia.tts import CartesiaTTSService from pipecat.services.deepgram.stt import DeepgramSTTService from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams @@ -53,14 +53,14 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): tts = CartesiaTTSService( api_key=os.getenv("CARTESIA_API_KEY"), - settings=CartesiaTTSSettings( + settings=CartesiaTTSService.Settings( voice="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady ), ) llm = AnthropicLLMService( api_key=os.getenv("ANTHROPIC_API_KEY"), - settings=AnthropicLLMSettings( + settings=AnthropicLLMService.Settings( system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way. You are also able to describe images.", ), ) diff --git a/examples/foundational/12b-describe-image-aws.py b/examples/foundational/12b-describe-image-aws.py index 86ec2e66d..d42bc6ef0 100644 --- a/examples/foundational/12b-describe-image-aws.py +++ b/examples/foundational/12b-describe-image-aws.py @@ -23,8 +23,8 @@ from pipecat.processors.aggregators.llm_response_universal import ( ) from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport -from pipecat.services.aws.llm import AWSBedrockLLMService, AWSBedrockLLMSettings -from pipecat.services.cartesia.tts import CartesiaTTSService, CartesiaTTSSettings +from pipecat.services.aws.llm import AWSBedrockLLMService +from pipecat.services.cartesia.tts import CartesiaTTSService from pipecat.services.deepgram.stt import DeepgramSTTService from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams @@ -53,14 +53,14 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): tts = CartesiaTTSService( api_key=os.getenv("CARTESIA_API_KEY"), - settings=CartesiaTTSSettings( + settings=CartesiaTTSService.Settings( voice="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady ), ) llm = AWSBedrockLLMService( aws_region="us-west-2", - settings=AWSBedrockLLMSettings( + settings=AWSBedrockLLMService.Settings( model="us.anthropic.claude-sonnet-4-6", temperature=0.8, system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way. You are also able to describe images.", diff --git a/examples/foundational/12c-describe-image-gemini-flash.py b/examples/foundational/12c-describe-image-gemini-flash.py index 2e76eff19..acb481d3e 100644 --- a/examples/foundational/12c-describe-image-gemini-flash.py +++ b/examples/foundational/12c-describe-image-gemini-flash.py @@ -23,9 +23,9 @@ from pipecat.processors.aggregators.llm_response_universal import ( ) from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport -from pipecat.services.cartesia.tts import CartesiaTTSService, CartesiaTTSSettings +from pipecat.services.cartesia.tts import CartesiaTTSService from pipecat.services.deepgram.stt import DeepgramSTTService -from pipecat.services.google.llm import GoogleLLMService, GoogleLLMSettings +from pipecat.services.google.llm import GoogleLLMService from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams @@ -53,14 +53,14 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): tts = CartesiaTTSService( api_key=os.getenv("CARTESIA_API_KEY"), - settings=CartesiaTTSSettings( + settings=CartesiaTTSService.Settings( voice="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady ), ) llm = GoogleLLMService( api_key=os.getenv("GOOGLE_API_KEY"), - settings=GoogleLLMSettings( + settings=GoogleLLMService.Settings( system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way. You are also able to describe images.", ), ) diff --git a/examples/foundational/12d-describe-image-moondream.py b/examples/foundational/12d-describe-image-moondream.py index 21fc79ed5..6a73de7b3 100644 --- a/examples/foundational/12d-describe-image-moondream.py +++ b/examples/foundational/12d-describe-image-moondream.py @@ -17,7 +17,7 @@ from pipecat.pipeline.runner import PipelineRunner from pipecat.pipeline.task import PipelineParams, PipelineTask from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport -from pipecat.services.cartesia.tts import CartesiaTTSService, CartesiaTTSSettings +from pipecat.services.cartesia.tts import CartesiaTTSService from pipecat.services.moondream.vision import MoondreamService from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams @@ -42,7 +42,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): tts = CartesiaTTSService( api_key=os.getenv("CARTESIA_API_KEY"), - settings=CartesiaTTSSettings( + settings=CartesiaTTSService.Settings( voice="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady ), ) diff --git a/examples/foundational/13b-deepgram-transcription.py b/examples/foundational/13b-deepgram-transcription.py index 61ba5c266..04246d237 100644 --- a/examples/foundational/13b-deepgram-transcription.py +++ b/examples/foundational/13b-deepgram-transcription.py @@ -16,7 +16,7 @@ from pipecat.pipeline.task import PipelineTask from pipecat.processors.frame_processor import FrameDirection, FrameProcessor from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport -from pipecat.services.deepgram.stt import DeepgramSTTService, DeepgramSTTSettings, Language +from pipecat.services.deepgram.stt import DeepgramSTTService, Language from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams @@ -49,7 +49,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): stt = DeepgramSTTService( api_key=os.getenv("DEEPGRAM_API_KEY"), - settings=DeepgramSTTSettings( + settings=DeepgramSTTService.Settings( language=Language.EN, ), ) diff --git a/examples/foundational/13c-gladia-translation.py b/examples/foundational/13c-gladia-translation.py index 9f7b6a6da..e6557cd15 100644 --- a/examples/foundational/13c-gladia-translation.py +++ b/examples/foundational/13c-gladia-translation.py @@ -17,12 +17,11 @@ from pipecat.processors.frame_processor import FrameDirection, FrameProcessor from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport from pipecat.services.gladia.config import ( - GladiaInputParams, LanguageConfig, RealtimeProcessingConfig, TranslationConfig, ) -from pipecat.services.gladia.stt import GladiaSTTService, GladiaSTTSettings +from pipecat.services.gladia.stt import GladiaSTTService from pipecat.transcriptions.language import Language from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams @@ -59,7 +58,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): stt = GladiaSTTService( api_key=os.getenv("GLADIA_API_KEY"), region=os.getenv("GLADIA_REGION"), - settings=GladiaSTTSettings( + settings=GladiaSTTService.Settings( language_config=LanguageConfig( languages=[Language.EN], code_switching=False, diff --git a/examples/foundational/13d-assemblyai-transcription.py b/examples/foundational/13d-assemblyai-transcription.py index c4ca9cd6b..f50f63380 100644 --- a/examples/foundational/13d-assemblyai-transcription.py +++ b/examples/foundational/13d-assemblyai-transcription.py @@ -16,7 +16,7 @@ from pipecat.pipeline.task import PipelineTask from pipecat.processors.frame_processor import FrameDirection, FrameProcessor from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport -from pipecat.services.assemblyai.stt import AssemblyAISTTService, AssemblyAISTTSettings +from pipecat.services.assemblyai.stt import AssemblyAISTTService from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams @@ -49,7 +49,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): stt = AssemblyAISTTService( api_key=os.getenv("ASSEMBLYAI_API_KEY"), - settings=AssemblyAISTTSettings( + settings=AssemblyAISTTService.Settings( model="u3-rt-pro", ), ) diff --git a/examples/foundational/13e-whisper-mlx.py b/examples/foundational/13e-whisper-mlx.py index 0f11d4397..211695a3a 100644 --- a/examples/foundational/13e-whisper-mlx.py +++ b/examples/foundational/13e-whisper-mlx.py @@ -18,7 +18,7 @@ from pipecat.pipeline.task import PipelineParams, PipelineTask from pipecat.processors.frame_processor import FrameDirection, FrameProcessor from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport -from pipecat.services.whisper.stt import MLXModel, WhisperMLXSTTSettings, WhisperSTTServiceMLX +from pipecat.services.whisper.stt import MLXModel, WhisperSTTServiceMLX from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams @@ -78,7 +78,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): logger.info(f"Starting bot") stt = WhisperSTTServiceMLX( - settings=WhisperMLXSTTSettings( + settings=WhisperSTTServiceMLX.Settings( model=MLXModel.LARGE_V3_TURBO, ), ) diff --git a/examples/foundational/13g-sambanova-transcription.py b/examples/foundational/13g-sambanova-transcription.py index 1e399c38f..404c215fd 100644 --- a/examples/foundational/13g-sambanova-transcription.py +++ b/examples/foundational/13g-sambanova-transcription.py @@ -19,7 +19,7 @@ from pipecat.pipeline.task import PipelineParams, PipelineTask from pipecat.processors.frame_processor import FrameDirection, FrameProcessor from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport -from pipecat.services.sambanova.stt import SambaNovaSTTService, SambaNovaSTTSettings +from pipecat.services.sambanova.stt import SambaNovaSTTService from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams @@ -79,7 +79,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): logger.info(f"Starting bot") stt = SambaNovaSTTService( - settings=SambaNovaSTTSettings( + settings=SambaNovaSTTService.Settings( model="Whisper-Large-v3", ), api_key=os.getenv("SAMBANOVA_API_KEY"), diff --git a/examples/foundational/13h-speechmatics-transcription.py b/examples/foundational/13h-speechmatics-transcription.py index d013357f6..2df30f67b 100644 --- a/examples/foundational/13h-speechmatics-transcription.py +++ b/examples/foundational/13h-speechmatics-transcription.py @@ -16,7 +16,7 @@ from pipecat.pipeline.task import PipelineTask from pipecat.processors.frame_processor import FrameDirection, FrameProcessor from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport -from pipecat.services.speechmatics.stt import SpeechmaticsSTTService, SpeechmaticsSTTSettings +from pipecat.services.speechmatics.stt import SpeechmaticsSTTService from pipecat.transcriptions.language import Language from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams @@ -65,7 +65,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): stt = SpeechmaticsSTTService( api_key=os.getenv("SPEECHMATICS_API_KEY"), - settings=SpeechmaticsSTTSettings( + settings=SpeechmaticsSTTService.Settings( language=Language.EN, speaker_active_format="<{speaker_id}>{text}", ), diff --git a/examples/foundational/13l-gradium-transcription.py b/examples/foundational/13l-gradium-transcription.py index 84b23017c..59140466e 100644 --- a/examples/foundational/13l-gradium-transcription.py +++ b/examples/foundational/13l-gradium-transcription.py @@ -16,7 +16,7 @@ from pipecat.pipeline.task import PipelineTask from pipecat.processors.frame_processor import FrameDirection, FrameProcessor from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport -from pipecat.services.gradium.stt import GradiumSTTService, GradiumSTTSettings +from pipecat.services.gradium.stt import GradiumSTTService from pipecat.transcriptions.language import Language from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams @@ -52,7 +52,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): stt = GradiumSTTService( api_key=os.getenv("GRADIUM_API_KEY"), api_endpoint_base_url="wss://us.api.gradium.ai/api/speech/asr", - settings=GradiumSTTSettings( + settings=GradiumSTTService.Settings( language=Language.EN, delay_in_frames=8, ), diff --git a/examples/foundational/13m-openai-transcription.py b/examples/foundational/13m-openai-transcription.py index 8dc9e0101..fea5c2d97 100644 --- a/examples/foundational/13m-openai-transcription.py +++ b/examples/foundational/13m-openai-transcription.py @@ -18,7 +18,7 @@ from pipecat.pipeline.task import PipelineTask from pipecat.processors.frame_processor import FrameDirection, FrameProcessor from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport -from pipecat.services.openai.stt import OpenAIRealtimeSTTService, OpenAIRealtimeSTTSettings +from pipecat.services.openai.stt import OpenAIRealtimeSTTService from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams @@ -53,7 +53,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): stt = OpenAIRealtimeSTTService( api_key=os.getenv("OPENAI_API_KEY"), - settings=OpenAIRealtimeSTTSettings( + settings=OpenAIRealtimeSTTService.Settings( model="gpt-4o-transcribe", prompt="Expect words related to dogs, such as breed names.", ), diff --git a/examples/foundational/14-function-calling.py b/examples/foundational/14-function-calling.py index 81cddec90..7b7e11edf 100644 --- a/examples/foundational/14-function-calling.py +++ b/examples/foundational/14-function-calling.py @@ -23,10 +23,10 @@ from pipecat.processors.aggregators.llm_response_universal import ( ) from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport -from pipecat.services.cartesia.tts import CartesiaTTSService, CartesiaTTSSettings +from pipecat.services.cartesia.tts import CartesiaTTSService from pipecat.services.deepgram.stt import DeepgramSTTService from pipecat.services.llm_service import FunctionCallParams -from pipecat.services.openai.llm import OpenAILLMService, OpenAILLMSettings +from pipecat.services.openai.llm import OpenAILLMService from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams @@ -67,14 +67,14 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): tts = CartesiaTTSService( api_key=os.getenv("CARTESIA_API_KEY"), - settings=CartesiaTTSSettings( + settings=CartesiaTTSService.Settings( voice="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady ), ) llm = OpenAILLMService( api_key=os.getenv("OPENAI_API_KEY"), - settings=OpenAILLMSettings( + settings=OpenAILLMService.Settings( system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", ), ) diff --git a/examples/foundational/14a-function-calling-anthropic.py b/examples/foundational/14a-function-calling-anthropic.py index efcaba47e..c0ad9102d 100644 --- a/examples/foundational/14a-function-calling-anthropic.py +++ b/examples/foundational/14a-function-calling-anthropic.py @@ -24,8 +24,8 @@ from pipecat.processors.aggregators.llm_response_universal import ( ) from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport -from pipecat.services.anthropic.llm import AnthropicLLMService, AnthropicLLMSettings -from pipecat.services.cartesia.tts import CartesiaTTSService, CartesiaTTSSettings +from pipecat.services.anthropic.llm import AnthropicLLMService +from pipecat.services.cartesia.tts import CartesiaTTSService from pipecat.services.deepgram.stt import DeepgramSTTService from pipecat.services.llm_service import FunctionCallParams from pipecat.transports.base_transport import BaseTransport, TransportParams @@ -69,14 +69,14 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): tts = CartesiaTTSService( api_key=os.getenv("CARTESIA_API_KEY"), - settings=CartesiaTTSSettings( + settings=CartesiaTTSService.Settings( voice="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady ), ) llm = AnthropicLLMService( api_key=os.getenv("ANTHROPIC_API_KEY"), - settings=AnthropicLLMSettings( + settings=AnthropicLLMService.Settings( system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", ), ) diff --git a/examples/foundational/14c-function-calling-together.py b/examples/foundational/14c-function-calling-together.py index 66ed02c15..3d2034cb4 100644 --- a/examples/foundational/14c-function-calling-together.py +++ b/examples/foundational/14c-function-calling-together.py @@ -24,10 +24,10 @@ from pipecat.processors.aggregators.llm_response_universal import ( ) from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport -from pipecat.services.cartesia.tts import CartesiaTTSService, CartesiaTTSSettings +from pipecat.services.cartesia.tts import CartesiaTTSService from pipecat.services.deepgram.stt import DeepgramSTTService from pipecat.services.llm_service import FunctionCallParams -from pipecat.services.together.llm import TogetherLLMService, TogetherLLMSettings +from pipecat.services.together.llm import TogetherLLMService from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams @@ -64,14 +64,14 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): tts = CartesiaTTSService( api_key=os.getenv("CARTESIA_API_KEY"), - settings=CartesiaTTSSettings( + settings=CartesiaTTSService.Settings( voice="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady ), ) llm = TogetherLLMService( api_key=os.getenv("TOGETHER_API_KEY"), - settings=TogetherLLMSettings( + settings=TogetherLLMService.Settings( model="meta-llama/Meta-Llama-3.1-70B-Instruct-Turbo", system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", ), diff --git a/examples/foundational/14d-function-calling-anthropic-video.py b/examples/foundational/14d-function-calling-anthropic-video.py index 136a7f110..ce51ddb22 100644 --- a/examples/foundational/14d-function-calling-anthropic-video.py +++ b/examples/foundational/14d-function-calling-anthropic-video.py @@ -28,8 +28,8 @@ from pipecat.runner.utils import ( get_transport_client_id, maybe_capture_participant_camera, ) -from pipecat.services.anthropic.llm import AnthropicLLMService, AnthropicLLMSettings -from pipecat.services.cartesia.tts import CartesiaTTSService, CartesiaTTSSettings +from pipecat.services.anthropic.llm import AnthropicLLMService +from pipecat.services.cartesia.tts import CartesiaTTSService from pipecat.services.deepgram.stt import DeepgramSTTService from pipecat.services.llm_service import FunctionCallParams from pipecat.transports.base_transport import BaseTransport, TransportParams @@ -90,7 +90,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): tts = CartesiaTTSService( api_key=os.getenv("CARTESIA_API_KEY"), - settings=CartesiaTTSSettings( + settings=CartesiaTTSService.Settings( voice="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady ), ) @@ -98,7 +98,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): # Anthropic for vision analysis llm = AnthropicLLMService( api_key=os.getenv("ANTHROPIC_API_KEY"), - settings=AnthropicLLMSettings( + settings=AnthropicLLMService.Settings( system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way. You are able to describe images from the user camera.", ), ) diff --git a/examples/foundational/14d-function-calling-aws-video.py b/examples/foundational/14d-function-calling-aws-video.py index 75235bc01..2c54e83f4 100644 --- a/examples/foundational/14d-function-calling-aws-video.py +++ b/examples/foundational/14d-function-calling-aws-video.py @@ -28,8 +28,8 @@ from pipecat.runner.utils import ( get_transport_client_id, maybe_capture_participant_camera, ) -from pipecat.services.aws.llm import AWSBedrockLLMService, AWSBedrockLLMSettings -from pipecat.services.cartesia.tts import CartesiaTTSService, CartesiaTTSSettings +from pipecat.services.aws.llm import AWSBedrockLLMService +from pipecat.services.cartesia.tts import CartesiaTTSService from pipecat.services.deepgram.stt import DeepgramSTTService from pipecat.services.llm_service import FunctionCallParams from pipecat.transports.base_transport import BaseTransport, TransportParams @@ -90,7 +90,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): tts = CartesiaTTSService( api_key=os.getenv("CARTESIA_API_KEY"), - settings=CartesiaTTSSettings( + settings=CartesiaTTSService.Settings( voice="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady ), ) @@ -98,7 +98,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): # AWS for vision analysis llm = AWSBedrockLLMService( aws_region="us-west-2", - settings=AWSBedrockLLMSettings( + settings=AWSBedrockLLMService.Settings( model="us.anthropic.claude-sonnet-4-6", # Note: usually, prefer providing latency="optimized" param. # Here we can't because AWS Bedrock doesn't support it for Claude 3.7, diff --git a/examples/foundational/14d-function-calling-gemini-flash-video.py b/examples/foundational/14d-function-calling-gemini-flash-video.py index b261a8922..16d82e002 100644 --- a/examples/foundational/14d-function-calling-gemini-flash-video.py +++ b/examples/foundational/14d-function-calling-gemini-flash-video.py @@ -28,9 +28,9 @@ from pipecat.runner.utils import ( get_transport_client_id, maybe_capture_participant_camera, ) -from pipecat.services.cartesia.tts import CartesiaTTSService, CartesiaTTSSettings +from pipecat.services.cartesia.tts import CartesiaTTSService from pipecat.services.deepgram.stt import DeepgramSTTService -from pipecat.services.google.llm import GoogleLLMService, GoogleLLMSettings +from pipecat.services.google.llm import GoogleLLMService from pipecat.services.llm_service import FunctionCallParams from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams @@ -90,7 +90,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): tts = CartesiaTTSService( api_key=os.getenv("CARTESIA_API_KEY"), - settings=CartesiaTTSSettings( + settings=CartesiaTTSService.Settings( voice="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady ), ) @@ -98,7 +98,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): # Google Gemini model for vision analysis llm = GoogleLLMService( api_key=os.getenv("GOOGLE_API_KEY"), - settings=GoogleLLMSettings( + settings=GoogleLLMService.Settings( system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way. You are able to describe images from the user camera.", ), ) diff --git a/examples/foundational/14d-function-calling-moondream-video.py b/examples/foundational/14d-function-calling-moondream-video.py index 9de08ce05..df7fc6014 100644 --- a/examples/foundational/14d-function-calling-moondream-video.py +++ b/examples/foundational/14d-function-calling-moondream-video.py @@ -37,11 +37,11 @@ from pipecat.runner.utils import ( get_transport_client_id, maybe_capture_participant_camera, ) -from pipecat.services.cartesia.tts import CartesiaTTSService, CartesiaTTSSettings +from pipecat.services.cartesia.tts import CartesiaTTSService from pipecat.services.deepgram.stt import DeepgramSTTService from pipecat.services.llm_service import FunctionCallParams from pipecat.services.moondream.vision import MoondreamService -from pipecat.services.openai.llm import OpenAILLMService, OpenAILLMSettings +from pipecat.services.openai.llm import OpenAILLMService from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams @@ -121,14 +121,14 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): tts = CartesiaTTSService( api_key=os.getenv("CARTESIA_API_KEY"), - settings=CartesiaTTSSettings( + settings=CartesiaTTSService.Settings( voice="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady ), ) llm = OpenAILLMService( api_key=os.getenv("OPENAI_API_KEY"), - settings=OpenAILLMSettings( + settings=OpenAILLMService.Settings( system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way. You are able to describe images from the user camera.", ), ) diff --git a/examples/foundational/14d-function-calling-openai-video.py b/examples/foundational/14d-function-calling-openai-video.py index 8c6416617..1eac522e8 100644 --- a/examples/foundational/14d-function-calling-openai-video.py +++ b/examples/foundational/14d-function-calling-openai-video.py @@ -29,10 +29,10 @@ from pipecat.runner.utils import ( get_transport_client_id, maybe_capture_participant_camera, ) -from pipecat.services.cartesia.tts import CartesiaTTSService, CartesiaTTSSettings +from pipecat.services.cartesia.tts import CartesiaTTSService from pipecat.services.deepgram.stt import DeepgramSTTService from pipecat.services.llm_service import FunctionCallParams -from pipecat.services.openai.llm import OpenAILLMService, OpenAILLMSettings +from pipecat.services.openai.llm import OpenAILLMService from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams @@ -91,14 +91,14 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): tts = CartesiaTTSService( api_key=os.getenv("CARTESIA_API_KEY"), - settings=CartesiaTTSSettings( + settings=CartesiaTTSService.Settings( voice="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady ), ) llm = OpenAILLMService( api_key=os.getenv("OPENAI_API_KEY"), - settings=OpenAILLMSettings( + settings=OpenAILLMService.Settings( system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way. You are able to describe images from the user camera.", ), ) diff --git a/examples/foundational/14e-function-calling-google.py b/examples/foundational/14e-function-calling-google.py index 19a0392b9..e5a2cfb40 100644 --- a/examples/foundational/14e-function-calling-google.py +++ b/examples/foundational/14e-function-calling-google.py @@ -29,9 +29,9 @@ from pipecat.runner.utils import ( get_transport_client_id, maybe_capture_participant_camera, ) -from pipecat.services.cartesia.tts import CartesiaTTSService, CartesiaTTSSettings +from pipecat.services.cartesia.tts import CartesiaTTSService from pipecat.services.deepgram.stt import DeepgramSTTService -from pipecat.services.google.llm import GoogleLLMService, GoogleLLMSettings +from pipecat.services.google.llm import GoogleLLMService from pipecat.services.llm_service import FunctionCallParams from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams @@ -100,7 +100,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): tts = CartesiaTTSService( api_key=os.getenv("CARTESIA_API_KEY"), - settings=CartesiaTTSSettings( + settings=CartesiaTTSService.Settings( voice="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady ), ) @@ -126,7 +126,7 @@ indicate you should use the get_image tool are: llm = GoogleLLMService( api_key=os.getenv("GOOGLE_API_KEY"), - settings=GoogleLLMSettings( + settings=GoogleLLMService.Settings( system_instruction=system_prompt, ), ) diff --git a/examples/foundational/14f-function-calling-groq.py b/examples/foundational/14f-function-calling-groq.py index 1b66e7e90..a6f383a1f 100644 --- a/examples/foundational/14f-function-calling-groq.py +++ b/examples/foundational/14f-function-calling-groq.py @@ -24,8 +24,8 @@ from pipecat.processors.aggregators.llm_response_universal import ( ) from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport -from pipecat.services.cartesia.tts import CartesiaTTSService, CartesiaTTSSettings -from pipecat.services.groq.llm import GroqLLMService, GroqLLMSettings +from pipecat.services.cartesia.tts import CartesiaTTSService +from pipecat.services.groq.llm import GroqLLMService from pipecat.services.groq.stt import GroqSTTService from pipecat.services.llm_service import FunctionCallParams from pipecat.transports.base_transport import BaseTransport, TransportParams @@ -64,14 +64,14 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): tts = CartesiaTTSService( api_key=os.getenv("CARTESIA_API_KEY"), - settings=CartesiaTTSSettings( + settings=CartesiaTTSService.Settings( voice="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady ), ) llm = GroqLLMService( api_key=os.getenv("GROQ_API_KEY"), - settings=GroqLLMSettings( + settings=GroqLLMService.Settings( system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", ), ) diff --git a/examples/foundational/14g-function-calling-grok.py b/examples/foundational/14g-function-calling-grok.py index eb607a5b8..283fd40fd 100644 --- a/examples/foundational/14g-function-calling-grok.py +++ b/examples/foundational/14g-function-calling-grok.py @@ -24,9 +24,9 @@ from pipecat.processors.aggregators.llm_response_universal import ( ) from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport -from pipecat.services.cartesia.tts import CartesiaTTSService, CartesiaTTSSettings +from pipecat.services.cartesia.tts import CartesiaTTSService from pipecat.services.deepgram.stt import DeepgramSTTService -from pipecat.services.grok.llm import GrokLLMService, GrokLLMSettings +from pipecat.services.grok.llm import GrokLLMService from pipecat.services.llm_service import FunctionCallParams from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams @@ -64,14 +64,14 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): tts = CartesiaTTSService( api_key=os.getenv("CARTESIA_API_KEY"), - settings=CartesiaTTSSettings( + settings=CartesiaTTSService.Settings( voice="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady ), ) llm = GrokLLMService( api_key=os.getenv("GROK_API_KEY"), - settings=GrokLLMSettings( + settings=GrokLLMService.Settings( system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", ), ) diff --git a/examples/foundational/14h-function-calling-azure.py b/examples/foundational/14h-function-calling-azure.py index 7eb3cb9de..3aae0c490 100644 --- a/examples/foundational/14h-function-calling-azure.py +++ b/examples/foundational/14h-function-calling-azure.py @@ -24,8 +24,8 @@ from pipecat.processors.aggregators.llm_response_universal import ( ) from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport -from pipecat.services.azure.llm import AzureLLMService, AzureLLMSettings -from pipecat.services.cartesia.tts import CartesiaTTSService, CartesiaTTSSettings +from pipecat.services.azure.llm import AzureLLMService +from pipecat.services.cartesia.tts import CartesiaTTSService from pipecat.services.deepgram.stt import DeepgramSTTService from pipecat.services.llm_service import FunctionCallParams from pipecat.transports.base_transport import BaseTransport, TransportParams @@ -64,7 +64,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): tts = CartesiaTTSService( api_key=os.getenv("CARTESIA_API_KEY"), - settings=CartesiaTTSSettings( + settings=CartesiaTTSService.Settings( voice="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady ), ) @@ -72,7 +72,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): llm = AzureLLMService( api_key=os.getenv("AZURE_CHATGPT_API_KEY"), endpoint=os.getenv("AZURE_CHATGPT_ENDPOINT"), - settings=AzureLLMSettings( + settings=AzureLLMService.Settings( model=os.getenv("AZURE_CHATGPT_MODEL"), system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", ), diff --git a/examples/foundational/14i-function-calling-fireworks.py b/examples/foundational/14i-function-calling-fireworks.py index 23d971324..c82165b17 100644 --- a/examples/foundational/14i-function-calling-fireworks.py +++ b/examples/foundational/14i-function-calling-fireworks.py @@ -24,9 +24,9 @@ from pipecat.processors.aggregators.llm_response_universal import ( ) from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport -from pipecat.services.cartesia.tts import CartesiaTTSService, CartesiaTTSSettings +from pipecat.services.cartesia.tts import CartesiaTTSService from pipecat.services.deepgram.stt import DeepgramSTTService -from pipecat.services.fireworks.llm import FireworksLLMService, FireworksLLMSettings +from pipecat.services.fireworks.llm import FireworksLLMService from pipecat.services.llm_service import FunctionCallParams from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams @@ -64,14 +64,14 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): tts = CartesiaTTSService( api_key=os.getenv("CARTESIA_API_KEY"), - settings=CartesiaTTSSettings( + settings=CartesiaTTSService.Settings( voice="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady ), ) llm = FireworksLLMService( api_key=os.getenv("FIREWORKS_API_KEY"), - settings=FireworksLLMSettings( + settings=FireworksLLMService.Settings( model="accounts/fireworks/models/gpt-oss-20b", system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", ), diff --git a/examples/foundational/14j-function-calling-nvidia.py b/examples/foundational/14j-function-calling-nvidia.py index 87c6812e8..39b75b7ac 100644 --- a/examples/foundational/14j-function-calling-nvidia.py +++ b/examples/foundational/14j-function-calling-nvidia.py @@ -24,10 +24,10 @@ from pipecat.processors.aggregators.llm_response_universal import ( ) from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport -from pipecat.services.cartesia.tts import CartesiaTTSService, CartesiaTTSSettings +from pipecat.services.cartesia.tts import CartesiaTTSService from pipecat.services.deepgram.stt import DeepgramSTTService from pipecat.services.llm_service import FunctionCallParams -from pipecat.services.nvidia.llm import NvidiaLLMService, NvidiaLLMSettings +from pipecat.services.nvidia.llm import NvidiaLLMService from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams @@ -64,14 +64,14 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): tts = CartesiaTTSService( api_key=os.getenv("CARTESIA_API_KEY"), - settings=CartesiaTTSSettings( + settings=CartesiaTTSService.Settings( voice="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady ), ) llm = NvidiaLLMService( api_key=os.getenv("NVIDIA_API_KEY"), - settings=NvidiaLLMSettings( + settings=NvidiaLLMService.Settings( model="nvidia/llama-3.3-nemotron-super-49b-v1.5", # Recommended when turning thinking off temperature=0.0, diff --git a/examples/foundational/14k-function-calling-cerebras.py b/examples/foundational/14k-function-calling-cerebras.py index 4bbcf3f8e..51b9c9bf9 100644 --- a/examples/foundational/14k-function-calling-cerebras.py +++ b/examples/foundational/14k-function-calling-cerebras.py @@ -24,8 +24,8 @@ from pipecat.processors.aggregators.llm_response_universal import ( ) from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport -from pipecat.services.cartesia.tts import CartesiaTTSService, CartesiaTTSSettings -from pipecat.services.cerebras.llm import CerebrasLLMService, CerebrasLLMSettings +from pipecat.services.cartesia.tts import CartesiaTTSService +from pipecat.services.cerebras.llm import CerebrasLLMService from pipecat.services.deepgram.stt import DeepgramSTTService from pipecat.services.llm_service import FunctionCallParams from pipecat.transports.base_transport import BaseTransport, TransportParams @@ -64,14 +64,14 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): tts = CartesiaTTSService( api_key=os.getenv("CARTESIA_API_KEY"), - settings=CartesiaTTSSettings( + settings=CartesiaTTSService.Settings( voice="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady ), ) llm = CerebrasLLMService( api_key=os.getenv("CEREBRAS_API_KEY"), - settings=CerebrasLLMSettings( + settings=CerebrasLLMService.Settings( system_instruction="""You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. You have one functions available: diff --git a/examples/foundational/14l-function-calling-deepseek.py b/examples/foundational/14l-function-calling-deepseek.py index 425a58ec6..4af091b7a 100644 --- a/examples/foundational/14l-function-calling-deepseek.py +++ b/examples/foundational/14l-function-calling-deepseek.py @@ -24,9 +24,9 @@ from pipecat.processors.aggregators.llm_response_universal import ( ) from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport -from pipecat.services.cartesia.tts import CartesiaTTSService, CartesiaTTSSettings +from pipecat.services.cartesia.tts import CartesiaTTSService from pipecat.services.deepgram.stt import DeepgramSTTService -from pipecat.services.deepseek.llm import DeepSeekLLMService, DeepSeekLLMSettings +from pipecat.services.deepseek.llm import DeepSeekLLMService from pipecat.services.llm_service import FunctionCallParams from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams @@ -64,14 +64,14 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): tts = CartesiaTTSService( api_key=os.getenv("CARTESIA_API_KEY"), - settings=CartesiaTTSSettings( + settings=CartesiaTTSService.Settings( voice="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady ), ) llm = DeepSeekLLMService( api_key=os.getenv("DEEPSEEK_API_KEY"), - settings=DeepSeekLLMSettings( + settings=DeepSeekLLMService.Settings( model="deepseek-chat", system_instruction="""You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. diff --git a/examples/foundational/14m-function-calling-openrouter.py b/examples/foundational/14m-function-calling-openrouter.py index fd39ef7af..e23865435 100644 --- a/examples/foundational/14m-function-calling-openrouter.py +++ b/examples/foundational/14m-function-calling-openrouter.py @@ -24,10 +24,10 @@ from pipecat.processors.aggregators.llm_response_universal import ( ) from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport -from pipecat.services.azure.tts import AzureTTSService, AzureTTSSettings +from pipecat.services.azure.tts import AzureTTSService from pipecat.services.deepgram.stt import DeepgramSTTService from pipecat.services.llm_service import FunctionCallParams -from pipecat.services.openrouter.llm import OpenRouterLLMService, OpenRouterLLMSettings +from pipecat.services.openrouter.llm import OpenRouterLLMService from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams @@ -65,7 +65,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): tts = AzureTTSService( api_key=os.getenv("AZURE_SPEECH_API_KEY"), region=os.getenv("AZURE_SPEECH_REGION"), - settings=AzureTTSSettings( + settings=AzureTTSService.Settings( voice="en-US-JennyNeural", language="en-US", rate="1.1", @@ -75,7 +75,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): llm = OpenRouterLLMService( api_key=os.getenv("OPENROUTER_API_KEY"), - settings=OpenRouterLLMSettings( + settings=OpenRouterLLMService.Settings( model="openai/gpt-4o-2024-11-20", system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", ), diff --git a/examples/foundational/14n-function-calling-perplexity.py b/examples/foundational/14n-function-calling-perplexity.py index 78d397656..2c1ba9e00 100644 --- a/examples/foundational/14n-function-calling-perplexity.py +++ b/examples/foundational/14n-function-calling-perplexity.py @@ -28,9 +28,9 @@ from pipecat.processors.aggregators.llm_response_universal import ( ) from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport -from pipecat.services.cartesia.tts import CartesiaTTSService, CartesiaTTSSettings +from pipecat.services.cartesia.tts import CartesiaTTSService from pipecat.services.deepgram.stt import DeepgramSTTService -from pipecat.services.perplexity.llm import PerplexityLLMService, PerplexityLLMSettings +from pipecat.services.perplexity.llm import PerplexityLLMService from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams @@ -62,14 +62,14 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): tts = CartesiaTTSService( api_key=os.getenv("CARTESIA_API_KEY"), - settings=CartesiaTTSSettings( + settings=CartesiaTTSService.Settings( voice="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady ), ) llm = PerplexityLLMService( api_key=os.getenv("PERPLEXITY_API_KEY"), - settings=PerplexityLLMSettings( + settings=PerplexityLLMService.Settings( system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way, but try to be brief.", ), ) diff --git a/examples/foundational/14o-function-calling-gemini-openai-format.py b/examples/foundational/14o-function-calling-gemini-openai-format.py index 82a77e4bb..416e602bf 100644 --- a/examples/foundational/14o-function-calling-gemini-openai-format.py +++ b/examples/foundational/14o-function-calling-gemini-openai-format.py @@ -25,8 +25,8 @@ from pipecat.processors.aggregators.openai_llm_context import OpenAILLMContext from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport from pipecat.services.deepgram.stt import DeepgramSTTService -from pipecat.services.elevenlabs.tts import ElevenLabsTTSService, ElevenLabsTTSSettings -from pipecat.services.google.llm_openai import GoogleLLMOpenAIBetaService, OpenAILLMSettings +from pipecat.services.elevenlabs.tts import ElevenLabsTTSService +from pipecat.services.google.llm_openai import GoogleLLMOpenAIBetaService from pipecat.services.llm_service import FunctionCallParams from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams @@ -64,14 +64,14 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): tts = ElevenLabsTTSService( api_key=os.getenv("ELEVENLABS_API_KEY", ""), - settings=ElevenLabsTTSSettings( + settings=ElevenLabsTTSService.Settings( voice=os.getenv("ELEVENLABS_VOICE_ID", ""), ), ) llm = GoogleLLMOpenAIBetaService( api_key=os.getenv("GOOGLE_API_KEY"), - settings=OpenAILLMSettings( + settings=GoogleLLMOpenAIBetaService.Settings( system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", ), ) diff --git a/examples/foundational/14p-function-calling-gemini-vertex-ai.py b/examples/foundational/14p-function-calling-gemini-vertex-ai.py index 026e41e59..1f33efacf 100644 --- a/examples/foundational/14p-function-calling-gemini-vertex-ai.py +++ b/examples/foundational/14p-function-calling-gemini-vertex-ai.py @@ -25,8 +25,8 @@ from pipecat.processors.aggregators.llm_response_universal import ( from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport from pipecat.services.deepgram.stt import DeepgramSTTService -from pipecat.services.elevenlabs.tts import ElevenLabsTTSService, ElevenLabsTTSSettings -from pipecat.services.google.llm_vertex import GoogleVertexLLMService, GoogleVertexLLMSettings +from pipecat.services.elevenlabs.tts import ElevenLabsTTSService +from pipecat.services.google.llm_vertex import GoogleVertexLLMService from pipecat.services.llm_service import FunctionCallParams from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams @@ -64,7 +64,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): tts = ElevenLabsTTSService( api_key=os.getenv("ELEVENLABS_API_KEY", ""), - settings=ElevenLabsTTSSettings( + settings=ElevenLabsTTSService.Settings( voice=os.getenv("ELEVENLABS_VOICE_ID", ""), ), ) @@ -73,7 +73,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): credentials=os.getenv("GOOGLE_VERTEX_TEST_CREDENTIALS"), project_id=os.getenv("GOOGLE_CLOUD_PROJECT_ID"), location=os.getenv("GOOGLE_CLOUD_LOCATION"), - settings=GoogleVertexLLMSettings( + settings=GoogleVertexLLMService.Settings( system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", ), ) diff --git a/examples/foundational/14q-function-calling-qwen.py b/examples/foundational/14q-function-calling-qwen.py index 9aa1c3b91..bf866a519 100644 --- a/examples/foundational/14q-function-calling-qwen.py +++ b/examples/foundational/14q-function-calling-qwen.py @@ -24,10 +24,10 @@ from pipecat.processors.aggregators.llm_response_universal import ( ) from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport -from pipecat.services.cartesia.tts import CartesiaTTSService, CartesiaTTSSettings +from pipecat.services.cartesia.tts import CartesiaTTSService from pipecat.services.deepgram.stt import DeepgramSTTService from pipecat.services.llm_service import FunctionCallParams -from pipecat.services.qwen.llm import QwenLLMService, QwenLLMSettings +from pipecat.services.qwen.llm import QwenLLMService from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams @@ -64,7 +64,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): tts = CartesiaTTSService( api_key=os.getenv("CARTESIA_API_KEY"), - settings=CartesiaTTSSettings( + settings=CartesiaTTSService.Settings( voice="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady ), ) @@ -72,7 +72,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): llm = QwenLLMService( api_key=os.getenv("QWEN_API_KEY"), model="qwen2.5-72b-instruct", - settings=QwenLLMSettings( + settings=QwenLLMService.Settings( system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", ), ) diff --git a/examples/foundational/14r-function-calling-aws.py b/examples/foundational/14r-function-calling-aws.py index 2414e06f0..29591c80a 100644 --- a/examples/foundational/14r-function-calling-aws.py +++ b/examples/foundational/14r-function-calling-aws.py @@ -22,9 +22,9 @@ from pipecat.processors.aggregators.llm_response_universal import ( ) from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport -from pipecat.services.aws.llm import AWSBedrockLLMService, AWSBedrockLLMSettings +from pipecat.services.aws.llm import AWSBedrockLLMService from pipecat.services.aws.stt import AWSTranscribeSTTService -from pipecat.services.aws.tts import AWSPollyTTSService, AWSPollyTTSSettings +from pipecat.services.aws.tts import AWSPollyTTSService from pipecat.services.llm_service import FunctionCallParams from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams @@ -66,7 +66,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): tts = AWSPollyTTSService( region="us-west-2", # only specific regions support generative TTS - settings=AWSPollyTTSSettings( + settings=AWSPollyTTSService.Settings( voice="Joanna", engine="generative", rate="1.1", @@ -75,7 +75,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): llm = AWSBedrockLLMService( aws_region="us-west-2", - settings=AWSBedrockLLMSettings( + settings=AWSBedrockLLMService.Settings( model="us.anthropic.claude-sonnet-4-6", temperature=0.8, system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", diff --git a/examples/foundational/14s-function-calling-sambanova.py b/examples/foundational/14s-function-calling-sambanova.py index 46ae742f3..c329135f9 100644 --- a/examples/foundational/14s-function-calling-sambanova.py +++ b/examples/foundational/14s-function-calling-sambanova.py @@ -24,9 +24,9 @@ from pipecat.processors.aggregators.llm_response_universal import ( ) from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport -from pipecat.services.cartesia.tts import CartesiaTTSService, CartesiaTTSSettings +from pipecat.services.cartesia.tts import CartesiaTTSService from pipecat.services.llm_service import FunctionCallParams -from pipecat.services.sambanova.llm import SambaNovaLLMService, SambaNovaLLMSettings +from pipecat.services.sambanova.llm import SambaNovaLLMService from pipecat.services.sambanova.stt import SambaNovaSTTService from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams @@ -67,14 +67,14 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): tts = CartesiaTTSService( api_key=os.getenv("CARTESIA_API_KEY"), - settings=CartesiaTTSSettings( + settings=CartesiaTTSService.Settings( voice="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady ), ) llm = SambaNovaLLMService( api_key=os.getenv("SAMBANOVA_API_KEY"), - settings=SambaNovaLLMSettings( + settings=SambaNovaLLMService.Settings( system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", ), ) diff --git a/examples/foundational/14t-function-calling-direct.py b/examples/foundational/14t-function-calling-direct.py index 86a8d61b2..7b4485226 100644 --- a/examples/foundational/14t-function-calling-direct.py +++ b/examples/foundational/14t-function-calling-direct.py @@ -23,10 +23,10 @@ from pipecat.processors.aggregators.llm_response_universal import ( ) from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport -from pipecat.services.cartesia.tts import CartesiaTTSService, CartesiaTTSSettings +from pipecat.services.cartesia.tts import CartesiaTTSService from pipecat.services.deepgram.stt import DeepgramSTTService from pipecat.services.llm_service import FunctionCallParams -from pipecat.services.openai.llm import OpenAILLMService, OpenAILLMSettings +from pipecat.services.openai.llm import OpenAILLMService from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams @@ -80,14 +80,14 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): tts = CartesiaTTSService( api_key=os.getenv("CARTESIA_API_KEY"), - settings=CartesiaTTSSettings( + settings=CartesiaTTSService.Settings( voice="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady ), ) llm = OpenAILLMService( api_key=os.getenv("OPENAI_API_KEY"), - settings=OpenAILLMSettings( + settings=OpenAILLMService.Settings( system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", ), ) diff --git a/examples/foundational/14u-function-calling-ollama.py b/examples/foundational/14u-function-calling-ollama.py index 761bab4a4..a0c1ec33a 100644 --- a/examples/foundational/14u-function-calling-ollama.py +++ b/examples/foundational/14u-function-calling-ollama.py @@ -24,10 +24,10 @@ from pipecat.processors.aggregators.llm_response_universal import ( ) from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport -from pipecat.services.cartesia.tts import CartesiaTTSService, CartesiaTTSSettings +from pipecat.services.cartesia.tts import CartesiaTTSService from pipecat.services.deepgram.stt import DeepgramSTTService from pipecat.services.llm_service import FunctionCallParams -from pipecat.services.ollama.llm import OLLamaLLMService, OLLamaLLMSettings +from pipecat.services.ollama.llm import OLLamaLLMService from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams @@ -68,13 +68,13 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): tts = CartesiaTTSService( api_key=os.getenv("CARTESIA_API_KEY"), - settings=CartesiaTTSSettings( + settings=CartesiaTTSService.Settings( voice="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady ), ) llm = OLLamaLLMService( - settings=OLLamaLLMSettings( + settings=OLLamaLLMService.Settings( model="llama3.2", system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", ), diff --git a/examples/foundational/14v-function-calling-openai.py b/examples/foundational/14v-function-calling-openai.py index 5e86632ec..639d9bd23 100644 --- a/examples/foundational/14v-function-calling-openai.py +++ b/examples/foundational/14v-function-calling-openai.py @@ -24,9 +24,9 @@ from pipecat.processors.aggregators.llm_response_universal import ( from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport from pipecat.services.llm_service import FunctionCallParams -from pipecat.services.openai.llm import OpenAILLMService, OpenAILLMSettings -from pipecat.services.openai.stt import OpenAISTTService, OpenAISTTSettings -from pipecat.services.openai.tts import OpenAITTSService, OpenAITTSSettings +from pipecat.services.openai.llm import OpenAILLMService +from pipecat.services.openai.stt import OpenAISTTService +from pipecat.services.openai.tts import OpenAITTSService from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams @@ -65,7 +65,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): stt = OpenAISTTService( api_key=os.getenv("OPENAI_API_KEY"), - settings=OpenAISTTSettings( + settings=OpenAISTTService.Settings( model="gpt-4o-transcribe", prompt="Expect words related weather, such as temperature and conditions. And restaurant names.", ), @@ -73,7 +73,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): tts = OpenAITTSService( api_key=os.getenv("OPENAI_API_KEY"), - settings=OpenAITTSSettings( + settings=OpenAITTSService.Settings( voice="ballad", ), instructions="Please speak clearly and at a moderate pace.", @@ -82,7 +82,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): # model choices: gpt-4o, gpt-4.1, etc. llm = OpenAILLMService( api_key=os.getenv("OPENAI_API_KEY"), - settings=OpenAILLMSettings( + settings=OpenAILLMService.Settings( system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", ), ) diff --git a/examples/foundational/14w-function-calling-mistral.py b/examples/foundational/14w-function-calling-mistral.py index ce535c3ef..421a63b74 100644 --- a/examples/foundational/14w-function-calling-mistral.py +++ b/examples/foundational/14w-function-calling-mistral.py @@ -23,10 +23,10 @@ from pipecat.processors.aggregators.llm_response_universal import ( ) from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport -from pipecat.services.cartesia.tts import CartesiaTTSService, CartesiaTTSSettings +from pipecat.services.cartesia.tts import CartesiaTTSService from pipecat.services.deepgram.stt import DeepgramSTTService from pipecat.services.llm_service import FunctionCallParams -from pipecat.services.mistral.llm import MistralLLMService, MistralLLMSettings +from pipecat.services.mistral.llm import MistralLLMService from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams @@ -67,14 +67,14 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): tts = CartesiaTTSService( api_key=os.getenv("CARTESIA_API_KEY"), - settings=CartesiaTTSSettings( + settings=CartesiaTTSService.Settings( voice="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady ), ) llm = MistralLLMService( api_key=os.getenv("MISTRAL_API_KEY"), - settings=MistralLLMSettings( + settings=MistralLLMService.Settings( system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", ), ) diff --git a/examples/foundational/14x-function-calling-openpipe.py b/examples/foundational/14x-function-calling-openpipe.py index 4f6898f5c..e82062c16 100644 --- a/examples/foundational/14x-function-calling-openpipe.py +++ b/examples/foundational/14x-function-calling-openpipe.py @@ -24,10 +24,10 @@ from pipecat.processors.aggregators.llm_response_universal import ( ) from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport -from pipecat.services.cartesia.tts import CartesiaTTSService, CartesiaTTSSettings +from pipecat.services.cartesia.tts import CartesiaTTSService from pipecat.services.deepgram.stt import DeepgramSTTService from pipecat.services.llm_service import FunctionCallParams -from pipecat.services.openpipe.llm import OpenPipeLLMService, OpenPipeLLMSettings +from pipecat.services.openpipe.llm import OpenPipeLLMService from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams @@ -68,7 +68,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): tts = CartesiaTTSService( api_key=os.getenv("CARTESIA_API_KEY"), - settings=CartesiaTTSSettings( + settings=CartesiaTTSService.Settings( voice="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady ), ) @@ -78,7 +78,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): api_key=os.getenv("OPENAI_API_KEY"), openpipe_api_key=os.getenv("OPENPIPE_API_KEY"), tags={"conversation_id": f"pipecat-{timestamp}"}, - settings=OpenPipeLLMSettings( + settings=OpenPipeLLMService.Settings( system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", ), ) diff --git a/examples/foundational/15-switch-voices.py b/examples/foundational/15-switch-voices.py index 40f2202de..39918918b 100644 --- a/examples/foundational/15-switch-voices.py +++ b/examples/foundational/15-switch-voices.py @@ -26,10 +26,10 @@ from pipecat.processors.aggregators.llm_response_universal import ( from pipecat.processors.filters.function_filter import FunctionFilter from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport -from pipecat.services.cartesia.tts import CartesiaTTSService, CartesiaTTSSettings +from pipecat.services.cartesia.tts import CartesiaTTSService from pipecat.services.deepgram.stt import DeepgramSTTService from pipecat.services.llm_service import FunctionCallParams -from pipecat.services.openai.llm import OpenAILLMService, OpenAILLMSettings +from pipecat.services.openai.llm import OpenAILLMService from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams @@ -43,21 +43,21 @@ class SwitchVoices(ParallelPipeline): news_lady = CartesiaTTSService( api_key=os.getenv("CARTESIA_API_KEY"), - settings=CartesiaTTSSettings( + settings=CartesiaTTSService.Settings( voice="bf991597-6c13-47e4-8411-91ec2de5c466", # Newslady ), ) british_lady = CartesiaTTSService( api_key=os.getenv("CARTESIA_API_KEY"), - settings=CartesiaTTSSettings( + settings=CartesiaTTSService.Settings( voice="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady ), ) barbershop_man = CartesiaTTSService( api_key=os.getenv("CARTESIA_API_KEY"), - settings=CartesiaTTSSettings( + settings=CartesiaTTSService.Settings( voice="a0e99841-438c-4a64-b679-ae501e7d6091", # Barbershop Man ), ) @@ -120,7 +120,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): llm = OpenAILLMService( api_key=os.getenv("OPENAI_API_KEY"), - settings=OpenAILLMSettings( + settings=OpenAILLMService.Settings( system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities. Respond to what the user said in a creative and helpful way. Your output should not include non-alphanumeric characters. You can do the following voices: 'News Lady', 'British Lady' and 'Barbershop Man'.", ), ) diff --git a/examples/foundational/15a-switch-languages.py b/examples/foundational/15a-switch-languages.py index d1bfc2289..67d943a0a 100644 --- a/examples/foundational/15a-switch-languages.py +++ b/examples/foundational/15a-switch-languages.py @@ -26,10 +26,10 @@ from pipecat.processors.aggregators.llm_response_universal import ( from pipecat.processors.filters.function_filter import FunctionFilter from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport -from pipecat.services.cartesia.tts import CartesiaTTSService, CartesiaTTSSettings -from pipecat.services.deepgram.stt import DeepgramSTTService, DeepgramSTTSettings +from pipecat.services.cartesia.tts import CartesiaTTSService +from pipecat.services.deepgram.stt import DeepgramSTTService from pipecat.services.llm_service import FunctionCallParams -from pipecat.services.openai.llm import OpenAILLMService, OpenAILLMSettings +from pipecat.services.openai.llm import OpenAILLMService from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams @@ -43,14 +43,14 @@ class SwitchLanguage(ParallelPipeline): english_tts = CartesiaTTSService( api_key=os.getenv("CARTESIA_API_KEY"), - settings=CartesiaTTSSettings( + settings=CartesiaTTSService.Settings( voice="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady ), ) spanish_tts = CartesiaTTSService( api_key=os.getenv("CARTESIA_API_KEY"), - settings=CartesiaTTSSettings( + settings=CartesiaTTSService.Settings( voice="d4db5fb9-f44b-4bd1-85fa-192e0f0d75f9", # Spanish-speaking Lady ), ) @@ -102,7 +102,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): stt = DeepgramSTTService( api_key=os.getenv("DEEPGRAM_API_KEY"), - settings=DeepgramSTTSettings( + settings=DeepgramSTTService.Settings( language="multi", ), ) @@ -111,7 +111,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): llm = OpenAILLMService( api_key=os.getenv("OPENAI_API_KEY"), - settings=OpenAILLMSettings( + settings=OpenAILLMService.Settings( system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities. Respond to what the user said in a creative and helpful way. Your output should not include non-alphanumeric characters. You can speak the following languages: 'English' and 'Spanish'.", ), ) diff --git a/examples/foundational/16-gpu-container-local-bot.py b/examples/foundational/16-gpu-container-local-bot.py index c1d267df3..2b680eee1 100644 --- a/examples/foundational/16-gpu-container-local-bot.py +++ b/examples/foundational/16-gpu-container-local-bot.py @@ -23,8 +23,8 @@ from pipecat.processors.aggregators.llm_response_universal import ( from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport from pipecat.services.deepgram.stt import DeepgramSTTService -from pipecat.services.deepgram.tts import DeepgramTTSService, DeepgramTTSSettings -from pipecat.services.openai.llm import OpenAILLMService, OpenAILLMSettings +from pipecat.services.deepgram.tts import DeepgramTTSService +from pipecat.services.openai.llm import OpenAILLMService from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import ( DailyOutputTransportMessageFrame, @@ -60,7 +60,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): tts = DeepgramTTSService( api_key=os.getenv("DEEPGRAM_API_KEY"), - settings=DeepgramTTSSettings( + settings=DeepgramTTSService.Settings( voice="aura-asteria-en", ), base_url="http://0.0.0.0:8080", @@ -70,7 +70,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): # To use OpenAI # api_key=os.getenv("OPENAI_API_KEY"), # Or, to use a local vLLM (or similar) api server - settings=OpenAILLMSettings( + settings=OpenAILLMService.Settings( model="meta-llama/Meta-Llama-3-8B-Instruct", system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", ), diff --git a/examples/foundational/17-detect-user-idle.py b/examples/foundational/17-detect-user-idle.py index 90434c77b..a1ac00501 100644 --- a/examples/foundational/17-detect-user-idle.py +++ b/examples/foundational/17-detect-user-idle.py @@ -32,10 +32,10 @@ from pipecat.processors.aggregators.llm_response_universal import ( from pipecat.processors.frame_processor import FrameDirection from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport -from pipecat.services.cartesia.tts import CartesiaTTSService, CartesiaTTSSettings +from pipecat.services.cartesia.tts import CartesiaTTSService from pipecat.services.deepgram.stt import DeepgramSTTService from pipecat.services.llm_service import FunctionCallParams -from pipecat.services.openai.llm import OpenAILLMService, OpenAILLMSettings +from pipecat.services.openai.llm import OpenAILLMService from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams @@ -115,14 +115,14 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): tts = CartesiaTTSService( api_key=os.getenv("CARTESIA_API_KEY"), - settings=CartesiaTTSSettings( + settings=CartesiaTTSService.Settings( voice="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady ), ) llm = OpenAILLMService( api_key=os.getenv("OPENAI_API_KEY"), - settings=OpenAILLMSettings( + settings=OpenAILLMService.Settings( system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", ), ) diff --git a/examples/foundational/19-openai-realtime.py b/examples/foundational/19-openai-realtime.py index d10fbc129..8eeea9e02 100644 --- a/examples/foundational/19-openai-realtime.py +++ b/examples/foundational/19-openai-realtime.py @@ -37,10 +37,7 @@ from pipecat.services.openai.realtime.events import ( SemanticTurnDetection, SessionProperties, ) -from pipecat.services.openai.realtime.llm import ( - OpenAIRealtimeLLMService, - OpenAIRealtimeLLMSettings, -) +from pipecat.services.openai.realtime.llm import OpenAIRealtimeLLMService from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams @@ -142,7 +139,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): llm = OpenAIRealtimeLLMService( api_key=os.getenv("OPENAI_API_KEY"), - settings=OpenAIRealtimeLLMSettings( + settings=OpenAIRealtimeLLMService.Settings( system_instruction="""You are a helpful and friendly AI. Act like a human, but remember that you aren't a human and that you can't do human diff --git a/examples/foundational/19a-azure-realtime.py b/examples/foundational/19a-azure-realtime.py index 8d52a1c12..c98dc167a 100644 --- a/examples/foundational/19a-azure-realtime.py +++ b/examples/foundational/19a-azure-realtime.py @@ -30,7 +30,6 @@ from pipecat.services.openai.realtime.events import ( InputAudioTranscription, SessionProperties, ) -from pipecat.services.openai.realtime.llm import OpenAIRealtimeLLMSettings from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams @@ -115,7 +114,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): llm = AzureRealtimeLLMService( api_key=os.getenv("AZURE_REALTIME_API_KEY"), base_url=os.getenv("AZURE_REALTIME_BASE_URL"), - settings=OpenAIRealtimeLLMSettings( + settings=AzureRealtimeLLMService.Settings( system_instruction="""You are a helpful and friendly AI. Act like a human, but remember that you aren't a human and that you can't do human diff --git a/examples/foundational/19b-openai-realtime-beta-text.py b/examples/foundational/19b-openai-realtime-beta-text.py index 7a4ad3469..9e425537f 100644 --- a/examples/foundational/19b-openai-realtime-beta-text.py +++ b/examples/foundational/19b-openai-realtime-beta-text.py @@ -21,7 +21,7 @@ from pipecat.pipeline.task import PipelineParams, PipelineTask from pipecat.processors.aggregators.openai_llm_context import OpenAILLMContext from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport -from pipecat.services.cartesia.tts import CartesiaTTSService, CartesiaTTSSettings +from pipecat.services.cartesia.tts import CartesiaTTSService from pipecat.services.llm_service import FunctionCallParams from pipecat.services.openai_realtime_beta import ( InputAudioNoiseReduction, @@ -147,7 +147,7 @@ Remember, your responses should be short. Just one or two sentences, usually. Re tts = CartesiaTTSService( api_key=os.getenv("CARTESIA_API_KEY"), - settings=CartesiaTTSSettings( + settings=CartesiaTTSService.Settings( voice="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady ), ) diff --git a/examples/foundational/19b-openai-realtime-text.py b/examples/foundational/19b-openai-realtime-text.py index e03381642..deb50e805 100644 --- a/examples/foundational/19b-openai-realtime-text.py +++ b/examples/foundational/19b-openai-realtime-text.py @@ -22,7 +22,7 @@ from pipecat.processors.aggregators.llm_context import LLMContext from pipecat.processors.aggregators.llm_response_universal import LLMContextAggregatorPair from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport -from pipecat.services.cartesia.tts import CartesiaTTSService, CartesiaTTSSettings +from pipecat.services.cartesia.tts import CartesiaTTSService from pipecat.services.llm_service import FunctionCallParams from pipecat.services.openai.realtime.events import ( AudioConfiguration, @@ -157,7 +157,7 @@ Remember, your responses should be short. Just one or two sentences, usually. Re tts = CartesiaTTSService( api_key=os.getenv("CARTESIA_API_KEY"), - settings=CartesiaTTSSettings( + settings=CartesiaTTSService.Settings( voice="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady ), ) diff --git a/examples/foundational/19c-openai-realtime-live-video.py b/examples/foundational/19c-openai-realtime-live-video.py index 31088ff0f..3038a57bc 100644 --- a/examples/foundational/19c-openai-realtime-live-video.py +++ b/examples/foundational/19c-openai-realtime-live-video.py @@ -32,10 +32,7 @@ from pipecat.services.openai.realtime.events import ( SemanticTurnDetection, SessionProperties, ) -from pipecat.services.openai.realtime.llm import ( - OpenAIRealtimeLLMService, - OpenAIRealtimeLLMSettings, -) +from pipecat.services.openai.realtime.llm import OpenAIRealtimeLLMService from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams @@ -65,7 +62,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): llm = OpenAIRealtimeLLMService( api_key=os.getenv("OPENAI_API_KEY"), - settings=OpenAIRealtimeLLMSettings( + settings=OpenAIRealtimeLLMService.Settings( system_instruction="""You are a helpful and friendly AI. Act like a human, but remember that you aren't a human and that you can't do human diff --git a/examples/foundational/20a-persistent-context-openai.py b/examples/foundational/20a-persistent-context-openai.py index 691893336..d487133f5 100644 --- a/examples/foundational/20a-persistent-context-openai.py +++ b/examples/foundational/20a-persistent-context-openai.py @@ -26,7 +26,7 @@ from pipecat.processors.aggregators.llm_response_universal import ( ) from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport -from pipecat.services.cartesia.tts import CartesiaTTSService, CartesiaTTSSettings +from pipecat.services.cartesia.tts import CartesiaTTSService from pipecat.services.deepgram.stt import DeepgramSTTService from pipecat.services.llm_service import FunctionCallParams from pipecat.services.openai.llm import OpenAILLMService @@ -175,7 +175,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): tts = CartesiaTTSService( api_key=os.getenv("CARTESIA_API_KEY"), - settings=CartesiaTTSSettings( + settings=CartesiaTTSService.Settings( voice="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady ), ) diff --git a/examples/foundational/20b-persistent-context-openai-realtime.py b/examples/foundational/20b-persistent-context-openai-realtime.py index b85f8c319..2b9a8b6bf 100644 --- a/examples/foundational/20b-persistent-context-openai-realtime.py +++ b/examples/foundational/20b-persistent-context-openai-realtime.py @@ -33,10 +33,7 @@ from pipecat.services.openai.realtime.events import ( SessionProperties, TurnDetection, ) -from pipecat.services.openai.realtime.llm import ( - OpenAIRealtimeLLMService, - OpenAIRealtimeLLMSettings, -) +from pipecat.services.openai.realtime.llm import OpenAIRealtimeLLMService from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams @@ -178,7 +175,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): llm = OpenAIRealtimeLLMService( api_key=os.getenv("OPENAI_API_KEY"), - settings=OpenAIRealtimeLLMSettings( + settings=OpenAIRealtimeLLMService.Settings( system_instruction="""Your knowledge cutoff is 2023-10. You are a helpful and friendly AI. Act like a human, but remember that you aren't a human and that you can't do human diff --git a/examples/foundational/20c-persistent-context-anthropic.py b/examples/foundational/20c-persistent-context-anthropic.py index 78ab3a7bc..e7a8335ba 100644 --- a/examples/foundational/20c-persistent-context-anthropic.py +++ b/examples/foundational/20c-persistent-context-anthropic.py @@ -26,8 +26,8 @@ from pipecat.processors.aggregators.llm_response_universal import ( ) from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport -from pipecat.services.anthropic.llm import AnthropicLLMService, AnthropicLLMSettings -from pipecat.services.cartesia.tts import CartesiaTTSService, CartesiaTTSSettings +from pipecat.services.anthropic.llm import AnthropicLLMService +from pipecat.services.cartesia.tts import CartesiaTTSService from pipecat.services.deepgram.stt import DeepgramSTTService from pipecat.services.llm_service import FunctionCallParams from pipecat.transports.base_transport import BaseTransport, TransportParams @@ -174,14 +174,16 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): tts = CartesiaTTSService( api_key=os.getenv("CARTESIA_API_KEY"), - settings=CartesiaTTSSettings( + settings=CartesiaTTSService.Settings( voice="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady ), ) llm = AnthropicLLMService( api_key=os.getenv("ANTHROPIC_API_KEY"), - settings=AnthropicLLMSettings(system_instruction=system_instruction), + settings=AnthropicLLMService.Settings( + system_instruction=system_instruction, + ), ) # you can either register a single function for all function calls, or specific functions diff --git a/examples/foundational/20d-persistent-context-gemini.py b/examples/foundational/20d-persistent-context-gemini.py index 082e5f07f..638728331 100644 --- a/examples/foundational/20d-persistent-context-gemini.py +++ b/examples/foundational/20d-persistent-context-gemini.py @@ -31,7 +31,7 @@ from pipecat.runner.utils import ( get_transport_client_id, maybe_capture_participant_camera, ) -from pipecat.services.cartesia.tts import CartesiaTTSService, CartesiaTTSSettings +from pipecat.services.cartesia.tts import CartesiaTTSService from pipecat.services.deepgram.stt import DeepgramSTTService from pipecat.services.google.llm import GoogleLLMService from pipecat.services.llm_service import FunctionCallParams @@ -247,7 +247,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): tts = CartesiaTTSService( api_key=os.getenv("CARTESIA_API_KEY"), - settings=CartesiaTTSSettings( + settings=CartesiaTTSService.Settings( voice="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady ), ) diff --git a/examples/foundational/20e-persistent-context-aws-nova-sonic.py b/examples/foundational/20e-persistent-context-aws-nova-sonic.py index 16e00d4c2..9614328f2 100644 --- a/examples/foundational/20e-persistent-context-aws-nova-sonic.py +++ b/examples/foundational/20e-persistent-context-aws-nova-sonic.py @@ -24,7 +24,7 @@ from pipecat.processors.aggregators.llm_context import LLMContext from pipecat.processors.aggregators.llm_response_universal import LLMContextAggregatorPair from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport -from pipecat.services.aws.nova_sonic.llm import AWSNovaSonicLLMService, AWSNovaSonicLLMSettings +from pipecat.services.aws.nova_sonic.llm import AWSNovaSonicLLMService from pipecat.services.llm_service import FunctionCallParams from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams @@ -222,7 +222,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): secret_access_key=os.getenv("AWS_SECRET_ACCESS_KEY"), access_key_id=os.getenv("AWS_ACCESS_KEY_ID"), region=os.getenv("AWS_REGION"), # as of 2025-05-06, us-east-1 is the only supported region - settings=AWSNovaSonicLLMSettings( + settings=AWSNovaSonicLLMService.Settings( voice="tiffany", # matthew, tiffany, amy system_instruction=system_instruction, ), diff --git a/examples/foundational/21-tavus-transport.py b/examples/foundational/21-tavus-transport.py index 2da83463d..1ac54ff19 100644 --- a/examples/foundational/21-tavus-transport.py +++ b/examples/foundational/21-tavus-transport.py @@ -22,9 +22,9 @@ from pipecat.processors.aggregators.llm_response_universal import ( LLMContextAggregatorPair, LLMUserAggregatorParams, ) -from pipecat.services.cartesia.tts import CartesiaTTSService, CartesiaTTSSettings +from pipecat.services.cartesia.tts import CartesiaTTSService from pipecat.services.deepgram.stt import DeepgramSTTService -from pipecat.services.google.llm import GoogleLLMService, GoogleLLMSettings +from pipecat.services.google.llm import GoogleLLMService from pipecat.transports.tavus.transport import TavusParams, TavusTransport load_dotenv(override=True) @@ -51,14 +51,14 @@ async def main(): tts = CartesiaTTSService( api_key=os.getenv("CARTESIA_API_KEY"), - settings=CartesiaTTSSettings( + settings=CartesiaTTSService.Settings( voice="a167e0f3-df7e-4d52-a9c3-f949145efdab", ), ) llm = GoogleLLMService( api_key=os.getenv("GOOGLE_API_KEY"), - settings=GoogleLLMSettings( + settings=GoogleLLMService.Settings( system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", ), ) diff --git a/examples/foundational/21a-tavus-video-service.py b/examples/foundational/21a-tavus-video-service.py index 0b26961c2..f716d88d8 100644 --- a/examples/foundational/21a-tavus-video-service.py +++ b/examples/foundational/21a-tavus-video-service.py @@ -23,9 +23,9 @@ from pipecat.processors.aggregators.llm_response_universal import ( ) from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport -from pipecat.services.cartesia.tts import CartesiaTTSService, CartesiaTTSSettings +from pipecat.services.cartesia.tts import CartesiaTTSService from pipecat.services.deepgram.stt import DeepgramSTTService -from pipecat.services.google.llm import GoogleLLMService, GoogleLLMSettings +from pipecat.services.google.llm import GoogleLLMService from pipecat.services.tavus.video import TavusVideoService from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams @@ -61,14 +61,14 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): tts = CartesiaTTSService( api_key=os.getenv("CARTESIA_API_KEY"), - settings=CartesiaTTSSettings( + settings=CartesiaTTSService.Settings( voice="a167e0f3-df7e-4d52-a9c3-f949145efdab", ), ) llm = GoogleLLMService( api_key=os.getenv("GOOGLE_API_KEY"), - settings=GoogleLLMSettings( + settings=GoogleLLMService.Settings( system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", ), ) diff --git a/examples/foundational/22-filter-incomplete-turns.py b/examples/foundational/22-filter-incomplete-turns.py index 6d5af6be8..454e22722 100644 --- a/examples/foundational/22-filter-incomplete-turns.py +++ b/examples/foundational/22-filter-incomplete-turns.py @@ -35,9 +35,9 @@ from pipecat.processors.aggregators.llm_response_universal import ( ) from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport -from pipecat.services.cartesia.tts import CartesiaTTSService, CartesiaTTSSettings +from pipecat.services.cartesia.tts import CartesiaTTSService from pipecat.services.deepgram.stt import DeepgramSTTService -from pipecat.services.openai.llm import OpenAILLMService, OpenAILLMSettings +from pipecat.services.openai.llm import OpenAILLMService from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams @@ -70,14 +70,14 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): llm = OpenAILLMService( api_key=os.getenv("OPENAI_API_KEY"), - settings=OpenAILLMSettings( + settings=OpenAILLMService.Settings( system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", ), ) tts = CartesiaTTSService( api_key=os.getenv("CARTESIA_API_KEY"), - settings=CartesiaTTSSettings( + settings=CartesiaTTSService.Settings( voice="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady ), ) diff --git a/examples/foundational/23-bot-background-sound.py b/examples/foundational/23-bot-background-sound.py index 53544fdf6..6f6cf8eb7 100644 --- a/examples/foundational/23-bot-background-sound.py +++ b/examples/foundational/23-bot-background-sound.py @@ -24,9 +24,9 @@ from pipecat.processors.aggregators.llm_response_universal import ( ) from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport -from pipecat.services.cartesia.tts import CartesiaTTSService, CartesiaTTSSettings +from pipecat.services.cartesia.tts import CartesiaTTSService from pipecat.services.deepgram.stt import DeepgramSTTService -from pipecat.services.openai.llm import OpenAILLMService, OpenAILLMSettings +from pipecat.services.openai.llm import OpenAILLMService from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams @@ -75,14 +75,14 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): tts = CartesiaTTSService( api_key=os.getenv("CARTESIA_API_KEY"), - settings=CartesiaTTSSettings( + settings=CartesiaTTSService.Settings( voice="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady ), ) llm = OpenAILLMService( api_key=os.getenv("OPENAI_API_KEY"), - settings=OpenAILLMSettings( + settings=OpenAILLMService.Settings( system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", ), ) diff --git a/examples/foundational/24-user-mute-strategy.py b/examples/foundational/24-user-mute-strategy.py index fac86dae4..f7e29c171 100644 --- a/examples/foundational/24-user-mute-strategy.py +++ b/examples/foundational/24-user-mute-strategy.py @@ -26,9 +26,9 @@ from pipecat.processors.aggregators.llm_response_universal import ( from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport from pipecat.services.deepgram.stt import DeepgramSTTService -from pipecat.services.deepgram.tts import DeepgramTTSService, DeepgramTTSSettings +from pipecat.services.deepgram.tts import DeepgramTTSService from pipecat.services.llm_service import FunctionCallParams -from pipecat.services.openai.llm import OpenAILLMService, OpenAILLMSettings +from pipecat.services.openai.llm import OpenAILLMService from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams @@ -73,14 +73,14 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): tts = DeepgramTTSService( api_key=os.getenv("DEEPGRAM_API_KEY"), - settings=DeepgramTTSSettings( + settings=DeepgramTTSService.Settings( voice="aura-2-helena-en", ), ) llm = OpenAILLMService( api_key=os.getenv("OPENAI_API_KEY"), - settings=OpenAILLMSettings( + settings=OpenAILLMService.Settings( system_instruction="You are a helpful assistant who can check the weather. Always check the weather when a location is mentioned. Respond concisely and naturally. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points.", ), ) diff --git a/examples/foundational/25-google-audio-in.py b/examples/foundational/25-google-audio-in.py index 1a8d203cd..572e0e213 100644 --- a/examples/foundational/25-google-audio-in.py +++ b/examples/foundational/25-google-audio-in.py @@ -32,8 +32,8 @@ from pipecat.processors.aggregators.llm_response_universal import LLMContextAggr from pipecat.processors.frame_processor import FrameProcessor from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport -from pipecat.services.cartesia.tts import CartesiaTTSService, CartesiaTTSSettings -from pipecat.services.google.llm import GoogleLLMService, GoogleLLMSettings +from pipecat.services.cartesia.tts import CartesiaTTSService +from pipecat.services.google.llm import GoogleLLMService from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams @@ -290,14 +290,14 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): tts = CartesiaTTSService( api_key=os.getenv("CARTESIA_API_KEY"), - settings=CartesiaTTSSettings( + settings=CartesiaTTSService.Settings( voice="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady ), ) conversation_llm = GoogleLLMService( name="Conversation", - settings=GoogleLLMSettings( + settings=GoogleLLMService.Settings( model="gemini-2.5-flash", system_instruction=conversation_system_message, ), @@ -309,7 +309,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): input_transcription_llm = GoogleLLMService( name="Transcription", - settings=GoogleLLMSettings( + settings=GoogleLLMService.Settings( model="gemini-2.5-flash", system_instruction=transcriber_system_message, ), diff --git a/examples/foundational/26-gemini-live.py b/examples/foundational/26-gemini-live.py index 76287236c..e8ca05407 100644 --- a/examples/foundational/26-gemini-live.py +++ b/examples/foundational/26-gemini-live.py @@ -18,7 +18,7 @@ from pipecat.pipeline.task import PipelineParams, PipelineTask from pipecat.processors.audio.vad_processor import VADProcessor from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport -from pipecat.services.google.gemini_live.llm import GeminiLiveLLMService, GeminiLiveLLMSettings +from pipecat.services.google.gemini_live.llm import GeminiLiveLLMService from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams @@ -64,7 +64,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): llm = GeminiLiveLLMService( api_key=os.getenv("GOOGLE_API_KEY"), - settings=GeminiLiveLLMSettings( + settings=GeminiLiveLLMService.Settings( system_instruction=system_instruction, voice="Puck", # Aoede, Charon, Fenrir, Kore, Puck ), diff --git a/examples/foundational/26a-gemini-live-transcription.py b/examples/foundational/26a-gemini-live-transcription.py index eda8dde8b..5d9adbc7f 100644 --- a/examples/foundational/26a-gemini-live-transcription.py +++ b/examples/foundational/26a-gemini-live-transcription.py @@ -56,9 +56,11 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): llm = GeminiLiveLLMService( api_key=os.getenv("GOOGLE_API_KEY"), - voice_id="Aoede", # Puck, Charon, Kore, Fenrir, Aoede - # system_instruction="Talk like a pirate." - # inference_on_context_initialization=False, + settings=GeminiLiveLLMService.Settings( + voice="Aoede", # Puck, Charon, Kore, Fenrir, Aoede + # system_instruction="Talk like a pirate." + # inference_on_context_initialization=False, + ), ) context = LLMContext( diff --git a/examples/foundational/26b-gemini-live-function-calling.py b/examples/foundational/26b-gemini-live-function-calling.py index 850327924..75481c2cd 100644 --- a/examples/foundational/26b-gemini-live-function-calling.py +++ b/examples/foundational/26b-gemini-live-function-calling.py @@ -26,7 +26,7 @@ from pipecat.processors.aggregators.llm_response_universal import ( ) from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport -from pipecat.services.google.gemini_live.llm import GeminiLiveLLMService, GeminiLiveLLMSettings +from pipecat.services.google.gemini_live.llm import GeminiLiveLLMService from pipecat.services.llm_service import FunctionCallParams from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams @@ -120,7 +120,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): llm = GeminiLiveLLMService( api_key=os.getenv("GOOGLE_API_KEY"), - settings=GeminiLiveLLMSettings( + settings=GeminiLiveLLMService.Settings( system_instruction=system_instruction, ), tools=tools, diff --git a/examples/foundational/26c-gemini-live-video.py b/examples/foundational/26c-gemini-live-video.py index 5cde4d214..dc5044617 100644 --- a/examples/foundational/26c-gemini-live-video.py +++ b/examples/foundational/26c-gemini-live-video.py @@ -28,7 +28,7 @@ from pipecat.runner.utils import ( maybe_capture_participant_camera, maybe_capture_participant_screen, ) -from pipecat.services.google.gemini_live.llm import GeminiLiveLLMService, GeminiLiveLLMSettings +from pipecat.services.google.gemini_live.llm import GeminiLiveLLMService from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams @@ -53,7 +53,7 @@ transport_params = { async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): llm = GeminiLiveLLMService( api_key=os.getenv("GOOGLE_API_KEY"), - settings=GeminiLiveLLMSettings( + settings=GeminiLiveLLMService.Settings( voice="Aoede", # Puck, Charon, Kore, Fenrir, Aoede # system_instruction="Talk like a pirate." ), diff --git a/examples/foundational/26d-gemini-live-text.py b/examples/foundational/26d-gemini-live-text.py index dcaf617ac..29a4fd112 100644 --- a/examples/foundational/26d-gemini-live-text.py +++ b/examples/foundational/26d-gemini-live-text.py @@ -23,13 +23,8 @@ from pipecat.processors.aggregators.llm_response_universal import ( ) from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport -from pipecat.services.cartesia.tts import CartesiaTTSService, CartesiaTTSSettings -from pipecat.services.google.gemini_live.llm import ( - GeminiLiveLLMService, - GeminiLiveLLMSettings, - GeminiModalities, - InputParams, -) +from pipecat.services.cartesia.tts import CartesiaTTSService +from pipecat.services.google.gemini_live.llm import GeminiLiveLLMService, GeminiModalities from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams @@ -75,7 +70,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): # https://cloud.google.com/vertex-ai/generative-ai/docs/live-api/tools#native-audio). llm = GeminiLiveLLMService( api_key=os.getenv("GOOGLE_API_KEY"), - settings=GeminiLiveLLMSettings( + settings=GeminiLiveLLMService.Settings( system_instruction=SYSTEM_INSTRUCTION, modalities=GeminiModalities.TEXT, ), diff --git a/examples/foundational/26e-gemini-live-google-search.py b/examples/foundational/26e-gemini-live-google-search.py index 07c3a517d..28ab77c2a 100644 --- a/examples/foundational/26e-gemini-live-google-search.py +++ b/examples/foundational/26e-gemini-live-google-search.py @@ -23,7 +23,7 @@ from pipecat.processors.aggregators.llm_response_universal import ( ) from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport -from pipecat.services.google.gemini_live.llm import GeminiLiveLLMService, GeminiLiveLLMSettings +from pipecat.services.google.gemini_live.llm import GeminiLiveLLMService from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams @@ -73,7 +73,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): # Initialize the Gemini Multimodal Live model llm = GeminiLiveLLMService( api_key=os.getenv("GOOGLE_API_KEY"), - settings=GeminiLiveLLMSettings( + settings=GeminiLiveLLMService.Settings( voice="Puck", # Aoede, Charon, Fenrir, Kore, Puck system_instruction=system_instruction, ), diff --git a/examples/foundational/26f-gemini-live-files-api.py b/examples/foundational/26f-gemini-live-files-api.py index a35265e86..5abb50788 100644 --- a/examples/foundational/26f-gemini-live-files-api.py +++ b/examples/foundational/26f-gemini-live-files-api.py @@ -23,7 +23,7 @@ from pipecat.processors.aggregators.llm_response_universal import ( ) from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport -from pipecat.services.google.gemini_live.llm import GeminiLiveLLMService, GeminiLiveLLMSettings +from pipecat.services.google.gemini_live.llm import GeminiLiveLLMService from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams @@ -110,7 +110,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): # Initialize Gemini service with File API support llm = GeminiLiveLLMService( api_key=os.getenv("GOOGLE_API_KEY"), - settings=GeminiLiveLLMSettings( + settings=GeminiLiveLLMService.Settings( system_instruction=system_instruction, voice="Charon", # Aoede, Charon, Fenrir, Kore, Puck ), diff --git a/examples/foundational/26g-gemini-live-groundingMetadata.py b/examples/foundational/26g-gemini-live-groundingMetadata.py index 1dede44f2..0285483e5 100644 --- a/examples/foundational/26g-gemini-live-groundingMetadata.py +++ b/examples/foundational/26g-gemini-live-groundingMetadata.py @@ -19,7 +19,7 @@ from pipecat.processors.frame_processor import FrameDirection, FrameProcessor from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport from pipecat.services.google.frames import LLMSearchResponseFrame -from pipecat.services.google.gemini_live.llm import GeminiLiveLLMService, GeminiLiveLLMSettings +from pipecat.services.google.gemini_live.llm import GeminiLiveLLMService from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams @@ -107,7 +107,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): llm = GeminiLiveLLMService( api_key=os.getenv("GOOGLE_API_KEY"), - settings=GeminiLiveLLMSettings( + settings=GeminiLiveLLMService.Settings( system_instruction=SYSTEM_INSTRUCTION, voice="Charon", # Aoede, Charon, Fenrir, Kore, Puck ), diff --git a/examples/foundational/26h-gemini-live-vertex-function-calling.py b/examples/foundational/26h-gemini-live-vertex-function-calling.py index ba27bbc9d..18e417f22 100644 --- a/examples/foundational/26h-gemini-live-vertex-function-calling.py +++ b/examples/foundational/26h-gemini-live-vertex-function-calling.py @@ -26,7 +26,6 @@ from pipecat.processors.aggregators.llm_response_universal import ( ) from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport -from pipecat.services.google.gemini_live.llm import GeminiLiveLLMSettings from pipecat.services.google.gemini_live.llm_vertex import GeminiLiveVertexLLMService from pipecat.services.llm_service import FunctionCallParams from pipecat.transports.base_transport import BaseTransport, TransportParams @@ -118,7 +117,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): credentials=os.getenv("GOOGLE_VERTEX_TEST_CREDENTIALS"), project_id=os.getenv("GOOGLE_CLOUD_PROJECT_ID"), location=os.getenv("GOOGLE_CLOUD_LOCATION"), - settings=GeminiLiveLLMSettings( + settings=GeminiLiveVertexLLMService.Settings( system_instruction=system_instruction, voice="Puck", # Aoede, Charon, Fenrir, Kore, Puck ), diff --git a/examples/foundational/26i-gemini-live-graceful-end.py b/examples/foundational/26i-gemini-live-graceful-end.py index cfc09e19d..5359f431c 100644 --- a/examples/foundational/26i-gemini-live-graceful-end.py +++ b/examples/foundational/26i-gemini-live-graceful-end.py @@ -26,7 +26,7 @@ from pipecat.processors.aggregators.llm_response_universal import ( from pipecat.processors.frame_processor import FrameDirection from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport -from pipecat.services.google.gemini_live.llm import GeminiLiveLLMService, GeminiLiveLLMSettings +from pipecat.services.google.gemini_live.llm import GeminiLiveLLMService from pipecat.services.llm_service import FunctionCallParams from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams @@ -132,7 +132,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): llm = GeminiLiveLLMService( api_key=os.getenv("GOOGLE_API_KEY"), - settings=GeminiLiveLLMSettings( + settings=GeminiLiveLLMService.Settings( system_instruction=system_instruction, ), tools=tools, diff --git a/examples/foundational/27-simli-layer.py b/examples/foundational/27-simli-layer.py index 3120a1280..c8a9ad663 100644 --- a/examples/foundational/27-simli-layer.py +++ b/examples/foundational/27-simli-layer.py @@ -22,9 +22,9 @@ from pipecat.processors.aggregators.llm_response_universal import ( ) from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport -from pipecat.services.cartesia.tts import CartesiaTTSService, CartesiaTTSSettings +from pipecat.services.cartesia.tts import CartesiaTTSService from pipecat.services.deepgram.stt import DeepgramSTTService -from pipecat.services.openai.llm import OpenAILLMService, OpenAILLMSettings +from pipecat.services.openai.llm import OpenAILLMService from pipecat.services.simli.video import SimliVideoService from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams @@ -60,7 +60,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): tts = CartesiaTTSService( api_key=os.getenv("CARTESIA_API_KEY"), - settings=CartesiaTTSSettings( + settings=CartesiaTTSService.Settings( voice="71a7ad14-091c-4e8e-a314-022ece01c121", ), ) @@ -72,7 +72,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): llm = OpenAILLMService( api_key=os.getenv("OPENAI_API_KEY"), - settings=OpenAILLMSettings( + settings=OpenAILLMService.Settings( model="gpt-4o-mini", system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", ), diff --git a/examples/foundational/28-user-assistant-turns.py b/examples/foundational/28-user-assistant-turns.py index 6ff7ca9ec..b439794b5 100644 --- a/examples/foundational/28-user-assistant-turns.py +++ b/examples/foundational/28-user-assistant-turns.py @@ -24,9 +24,9 @@ from pipecat.processors.aggregators.llm_response_universal import ( ) from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport -from pipecat.services.cartesia.tts import CartesiaTTSService, CartesiaTTSSettings +from pipecat.services.cartesia.tts import CartesiaTTSService from pipecat.services.deepgram.stt import DeepgramSTTService -from pipecat.services.openai.llm import OpenAILLMService, OpenAILLMSettings +from pipecat.services.openai.llm import OpenAILLMService from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams @@ -122,14 +122,14 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): tts = CartesiaTTSService( api_key=os.getenv("CARTESIA_API_KEY"), - settings=CartesiaTTSSettings( + settings=CartesiaTTSService.Settings( voice="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady ), ) llm = OpenAILLMService( api_key=os.getenv("OPENAI_API_KEY"), - settings=OpenAILLMSettings( + settings=OpenAILLMService.Settings( system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative, helpful, and brief way.", ), ) diff --git a/examples/foundational/29-turn-tracking-observer.py b/examples/foundational/29-turn-tracking-observer.py index a73126936..f17dd0260 100644 --- a/examples/foundational/29-turn-tracking-observer.py +++ b/examples/foundational/29-turn-tracking-observer.py @@ -27,10 +27,10 @@ from pipecat.processors.aggregators.llm_response_universal import ( ) from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport -from pipecat.services.cartesia.tts import CartesiaTTSService, CartesiaTTSSettings +from pipecat.services.cartesia.tts import CartesiaTTSService from pipecat.services.deepgram.stt import DeepgramSTTService from pipecat.services.llm_service import FunctionCallParams -from pipecat.services.openai.llm import OpenAILLMService, OpenAILLMSettings +from pipecat.services.openai.llm import OpenAILLMService from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams @@ -73,14 +73,14 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): tts = CartesiaTTSService( api_key=os.getenv("CARTESIA_API_KEY"), - settings=CartesiaTTSSettings( + settings=CartesiaTTSService.Settings( voice="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady ), ) llm = OpenAILLMService( api_key=os.getenv("OPENAI_API_KEY"), - settings=OpenAILLMSettings( + settings=OpenAILLMService.Settings( system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", ), ) diff --git a/examples/foundational/30-observer.py b/examples/foundational/30-observer.py index 28a76059d..227a8978b 100644 --- a/examples/foundational/30-observer.py +++ b/examples/foundational/30-observer.py @@ -34,9 +34,9 @@ from pipecat.processors.aggregators.llm_response_universal import ( from pipecat.processors.frame_processor import FrameDirection from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport -from pipecat.services.cartesia.tts import CartesiaTTSService, CartesiaTTSSettings +from pipecat.services.cartesia.tts import CartesiaTTSService from pipecat.services.deepgram.stt import DeepgramSTTService -from pipecat.services.openai.llm import OpenAILLMService, OpenAILLMSettings +from pipecat.services.openai.llm import OpenAILLMService from pipecat.transports.base_input import BaseInputTransport from pipecat.transports.base_output import BaseOutputTransport from pipecat.transports.base_transport import BaseTransport, TransportParams @@ -104,14 +104,14 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): tts = CartesiaTTSService( api_key=os.getenv("CARTESIA_API_KEY"), - settings=CartesiaTTSSettings( + settings=CartesiaTTSService.Settings( voice="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady ), ) llm = OpenAILLMService( api_key=os.getenv("OPENAI_API_KEY"), - settings=OpenAILLMSettings( + settings=OpenAILLMService.Settings( system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", ), ) diff --git a/examples/foundational/32-gemini-grounding-metadata.py b/examples/foundational/32-gemini-grounding-metadata.py index 6c2b182f7..89afacfc3 100644 --- a/examples/foundational/32-gemini-grounding-metadata.py +++ b/examples/foundational/32-gemini-grounding-metadata.py @@ -25,9 +25,9 @@ from pipecat.processors.aggregators.llm_response_universal import ( ) from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport -from pipecat.services.cartesia.tts import CartesiaTTSService, CartesiaTTSSettings +from pipecat.services.cartesia.tts import CartesiaTTSService from pipecat.services.deepgram.stt import DeepgramSTTService -from pipecat.services.google.llm import GoogleLLMService, GoogleLLMSettings, LLMSearchResponseFrame +from pipecat.services.google.llm import GoogleLLMService, LLMSearchResponseFrame from pipecat.services.llm_service import LLMService from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams @@ -99,7 +99,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): tts = CartesiaTTSService( api_key=os.getenv("CARTESIA_API_KEY"), - settings=CartesiaTTSSettings( + settings=CartesiaTTSService.Settings( voice="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady ), ) @@ -107,7 +107,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): # Initialize the Gemini Multimodal Live model llm = GoogleLLMService( api_key=os.getenv("GOOGLE_API_KEY"), - settings=GoogleLLMSettings( + settings=GoogleLLMService.Settings( system_instruction=system_instruction, ), tools=tools, diff --git a/examples/foundational/33-gemini-rag.py b/examples/foundational/33-gemini-rag.py index cadb3fd92..4c107d35f 100644 --- a/examples/foundational/33-gemini-rag.py +++ b/examples/foundational/33-gemini-rag.py @@ -69,9 +69,9 @@ from pipecat.processors.aggregators.llm_response_universal import ( ) from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport -from pipecat.services.cartesia.tts import CartesiaTTSService, CartesiaTTSSettings +from pipecat.services.cartesia.tts import CartesiaTTSService from pipecat.services.deepgram.stt import DeepgramSTTService -from pipecat.services.google.llm import GoogleLLMService, GoogleLLMSettings +from pipecat.services.google.llm import GoogleLLMService from pipecat.services.llm_service import FunctionCallParams from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams @@ -183,7 +183,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): tts = CartesiaTTSService( api_key=os.getenv("CARTESIA_API_KEY"), - settings=CartesiaTTSSettings( + settings=CartesiaTTSService.Settings( voice="f9836c6e-a0bd-460e-9d3c-f7299fa60f94", # Southern Lady ), ) @@ -198,7 +198,7 @@ Your response will be turned into speech so use only simple words and punctuatio llm = GoogleLLMService( api_key=os.getenv("GOOGLE_API_KEY"), - settings=GoogleLLMSettings( + settings=GoogleLLMService.Settings( model=VOICE_MODEL, system_instruction=system_prompt, ), diff --git a/examples/foundational/34-audio-recording.py b/examples/foundational/34-audio-recording.py index 2bc413ec2..6ddfa6033 100644 --- a/examples/foundational/34-audio-recording.py +++ b/examples/foundational/34-audio-recording.py @@ -63,9 +63,9 @@ from pipecat.processors.aggregators.llm_response_universal import ( from pipecat.processors.audio.audio_buffer_processor import AudioBufferProcessor from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport -from pipecat.services.cartesia.tts import CartesiaTTSService, CartesiaTTSSettings +from pipecat.services.cartesia.tts import CartesiaTTSService from pipecat.services.deepgram.stt import DeepgramSTTService -from pipecat.services.openai.llm import OpenAILLMService, OpenAILLMSettings +from pipecat.services.openai.llm import OpenAILLMService from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams @@ -112,14 +112,14 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): tts = CartesiaTTSService( api_key=os.getenv("CARTESIA_API_KEY"), - settings=CartesiaTTSSettings( + settings=CartesiaTTSService.Settings( voice="71a7ad14-091c-4e8e-a314-022ece01c121", ), ) llm = OpenAILLMService( api_key=os.getenv("OPENAI_API_KEY"), - settings=OpenAILLMSettings( + settings=OpenAILLMService.Settings( system_instruction="You are a helpful assistant demonstrating audio recording capabilities. Keep your responses brief and clear.", ), ) diff --git a/examples/foundational/35-pattern-pair-voice-switching.py b/examples/foundational/35-pattern-pair-voice-switching.py index 0c5c6256c..ed9bb3973 100644 --- a/examples/foundational/35-pattern-pair-voice-switching.py +++ b/examples/foundational/35-pattern-pair-voice-switching.py @@ -56,9 +56,9 @@ from pipecat.processors.aggregators.llm_response_universal import ( ) from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport -from pipecat.services.cartesia.tts import CartesiaTTSService, CartesiaTTSSettings +from pipecat.services.cartesia.tts import CartesiaTTSService from pipecat.services.deepgram.stt import DeepgramSTTService -from pipecat.services.openai.llm import OpenAILLMService, OpenAILLMSettings +from pipecat.services.openai.llm import OpenAILLMService from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams @@ -129,7 +129,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): # Initialize TTS with narrator voice as default tts = CartesiaTTSService( api_key=os.getenv("CARTESIA_API_KEY"), - settings=CartesiaTTSSettings( + settings=CartesiaTTSService.Settings( voice=VOICE_IDS["narrator"], ), text_aggregator=pattern_aggregator, @@ -186,7 +186,7 @@ Remember: Use narrator voice for EVERYTHING except the actual quoted dialogue."" # Initialize LLM llm = OpenAILLMService( api_key=os.getenv("OPENAI_API_KEY"), - settings=OpenAILLMSettings( + settings=OpenAILLMService.Settings( system_instruction=system_prompt, ), ) diff --git a/examples/foundational/36-user-email-gathering.py b/examples/foundational/36-user-email-gathering.py index 2f9c04fd8..7e8a69011 100644 --- a/examples/foundational/36-user-email-gathering.py +++ b/examples/foundational/36-user-email-gathering.py @@ -24,10 +24,10 @@ from pipecat.processors.aggregators.llm_response_universal import ( ) from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport -from pipecat.services.cartesia.tts import CartesiaTTSService, CartesiaTTSSettings +from pipecat.services.cartesia.tts import CartesiaTTSService from pipecat.services.deepgram.stt import DeepgramSTTService from pipecat.services.llm_service import FunctionCallParams -from pipecat.services.openai.llm import OpenAILLMService, OpenAILLMSettings +from pipecat.services.openai.llm import OpenAILLMService from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams @@ -67,7 +67,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): # (see https://docs.cartesia.ai/build-with-sonic/formatting-text-for-sonic/spelling-out-input-text) tts = CartesiaTTSService( api_key=os.getenv("CARTESIA_API_KEY"), - settings=CartesiaTTSSettings( + settings=CartesiaTTSService.Settings( voice="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady ), ) @@ -85,7 +85,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): llm = OpenAILLMService( api_key=os.getenv("OPENAI_API_KEY"), - settings=OpenAILLMSettings( + settings=OpenAILLMService.Settings( system_instruction="You need to gather a valid email or emails from the user. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. If the user provides one or more email addresses confirm them with the user. Enclose all emails with tags, for example a@a.com.", ), ) diff --git a/examples/foundational/37-mem0.py b/examples/foundational/37-mem0.py index 5e9dc351d..06883a43e 100644 --- a/examples/foundational/37-mem0.py +++ b/examples/foundational/37-mem0.py @@ -60,9 +60,9 @@ from pipecat.processors.aggregators.llm_response_universal import ( from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport from pipecat.services.deepgram.stt import DeepgramSTTService -from pipecat.services.elevenlabs.tts import ElevenLabsTTSService, ElevenLabsTTSSettings +from pipecat.services.elevenlabs.tts import ElevenLabsTTSService from pipecat.services.mem0.memory import Mem0MemoryService -from pipecat.services.openai.llm import OpenAILLMService, OpenAILLMSettings +from pipecat.services.openai.llm import OpenAILLMService from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams @@ -166,7 +166,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): # Initialize text-to-speech service tts = ElevenLabsTTSService( api_key=os.getenv("ELEVENLABS_API_KEY"), - settings=ElevenLabsTTSSettings( + settings=ElevenLabsTTSService.Settings( voice="pNInz6obpgDQGcFmaJgB", ), ) @@ -225,7 +225,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): # Initialize LLM service llm = OpenAILLMService( api_key=os.getenv("OPENAI_API_KEY"), - settings=OpenAILLMSettings( + settings=OpenAILLMService.Settings( model="gpt-4o-mini", system_instruction="""You are a personal assistant. You can remember things about the person you are talking to. Some Guidelines: diff --git a/examples/foundational/38-smart-turn-fal.py b/examples/foundational/38-smart-turn-fal.py index 6ecc444f9..b2de247d7 100644 --- a/examples/foundational/38-smart-turn-fal.py +++ b/examples/foundational/38-smart-turn-fal.py @@ -24,9 +24,9 @@ from pipecat.processors.aggregators.llm_response_universal import ( ) from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport -from pipecat.services.cartesia.tts import CartesiaTTSService, CartesiaTTSSettings +from pipecat.services.cartesia.tts import CartesiaTTSService from pipecat.services.deepgram.stt import DeepgramSTTService -from pipecat.services.openai.llm import OpenAILLMService, OpenAILLMSettings +from pipecat.services.openai.llm import OpenAILLMService from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams @@ -61,14 +61,14 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): tts = CartesiaTTSService( api_key=os.getenv("CARTESIA_API_KEY"), - settings=CartesiaTTSSettings( + settings=CartesiaTTSService.Settings( voice="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady ), ) llm = OpenAILLMService( api_key=os.getenv("OPENAI_API_KEY"), - settings=OpenAILLMSettings( + settings=OpenAILLMService.Settings( system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", ), ) diff --git a/examples/foundational/38a-smart-turn-local-coreml.py b/examples/foundational/38a-smart-turn-local-coreml.py index 32cd507b8..3073ba0dd 100644 --- a/examples/foundational/38a-smart-turn-local-coreml.py +++ b/examples/foundational/38a-smart-turn-local-coreml.py @@ -23,9 +23,9 @@ from pipecat.processors.aggregators.llm_response_universal import ( ) from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport -from pipecat.services.cartesia.tts import CartesiaTTSService, CartesiaTTSSettings +from pipecat.services.cartesia.tts import CartesiaTTSService from pipecat.services.deepgram.stt import DeepgramSTTService -from pipecat.services.openai.llm import OpenAILLMService, OpenAILLMSettings +from pipecat.services.openai.llm import OpenAILLMService from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams @@ -76,14 +76,14 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): tts = CartesiaTTSService( api_key=os.getenv("CARTESIA_API_KEY"), - settings=CartesiaTTSSettings( + settings=CartesiaTTSService.Settings( voice="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady ), ) llm = OpenAILLMService( api_key=os.getenv("OPENAI_API_KEY"), - settings=OpenAILLMSettings( + settings=OpenAILLMService.Settings( system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", ), ) diff --git a/examples/foundational/38b-smart-turn-local.py b/examples/foundational/38b-smart-turn-local.py index 30849a71d..de8b214ea 100644 --- a/examples/foundational/38b-smart-turn-local.py +++ b/examples/foundational/38b-smart-turn-local.py @@ -24,9 +24,9 @@ from pipecat.processors.aggregators.llm_response_universal import ( ) from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport -from pipecat.services.cartesia.tts import CartesiaTTSService, CartesiaTTSSettings +from pipecat.services.cartesia.tts import CartesiaTTSService from pipecat.services.deepgram.stt import DeepgramSTTService -from pipecat.services.openai.llm import OpenAILLMService, OpenAILLMSettings +from pipecat.services.openai.llm import OpenAILLMService from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams @@ -58,14 +58,14 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): tts = CartesiaTTSService( api_key=os.getenv("CARTESIA_API_KEY"), - settings=CartesiaTTSSettings( + settings=CartesiaTTSService.Settings( voice="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady ), ) llm = OpenAILLMService( api_key=os.getenv("OPENAI_API_KEY"), - settings=OpenAILLMSettings( + settings=OpenAILLMService.Settings( system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", ), ) diff --git a/examples/foundational/39-mcp-stdio.py b/examples/foundational/39-mcp-stdio.py index b6f111044..0b2cfaabe 100644 --- a/examples/foundational/39-mcp-stdio.py +++ b/examples/foundational/39-mcp-stdio.py @@ -35,8 +35,8 @@ from pipecat.processors.aggregators.llm_response_universal import ( from pipecat.processors.frame_processor import FrameDirection, FrameProcessor from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport -from pipecat.services.anthropic.llm import AnthropicLLMService, AnthropicLLMSettings -from pipecat.services.cartesia.tts import CartesiaTTSService, CartesiaTTSSettings +from pipecat.services.anthropic.llm import AnthropicLLMService +from pipecat.services.cartesia.tts import CartesiaTTSService from pipecat.services.deepgram.stt import DeepgramSTTService from pipecat.services.mcp_service import MCPClient from pipecat.transports.base_transport import BaseTransport, TransportParams @@ -137,7 +137,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): tts = CartesiaTTSService( api_key=os.getenv("CARTESIA_API_KEY"), - settings=CartesiaTTSSettings( + settings=CartesiaTTSService.Settings( voice="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady ), ) @@ -157,7 +157,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): llm = AnthropicLLMService( api_key=os.getenv("ANTHROPIC_API_KEY"), - settings=AnthropicLLMSettings( + settings=AnthropicLLMService.Settings( system_instruction=system_prompt, ), ) diff --git a/examples/foundational/39a-mcp-streamable-http.py b/examples/foundational/39a-mcp-streamable-http.py index 38f52ff1c..b71938e43 100644 --- a/examples/foundational/39a-mcp-streamable-http.py +++ b/examples/foundational/39a-mcp-streamable-http.py @@ -23,7 +23,7 @@ from pipecat.processors.aggregators.llm_response_universal import ( ) from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport -from pipecat.services.cartesia.tts import CartesiaTTSService, CartesiaTTSSettings +from pipecat.services.cartesia.tts import CartesiaTTSService from pipecat.services.deepgram.stt import DeepgramSTTService from pipecat.services.google.llm import GoogleLLMService from pipecat.services.mcp_service import MCPClient @@ -58,7 +58,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): tts = CartesiaTTSService( api_key=os.getenv("CARTESIA_API_KEY"), - settings=CartesiaTTSSettings( + settings=CartesiaTTSService.Settings( voice="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady ), ) diff --git a/examples/foundational/39b-mcp-streamable-http-gemini-live.py b/examples/foundational/39b-mcp-streamable-http-gemini-live.py index 8a0ea57fd..19a5aa1b6 100644 --- a/examples/foundational/39b-mcp-streamable-http-gemini-live.py +++ b/examples/foundational/39b-mcp-streamable-http-gemini-live.py @@ -23,7 +23,7 @@ from pipecat.processors.aggregators.llm_response_universal import ( ) from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport -from pipecat.services.cartesia.tts import CartesiaTTSService, CartesiaTTSSettings +from pipecat.services.cartesia.tts import CartesiaTTSService from pipecat.services.deepgram.stt import DeepgramSTTService from pipecat.services.google.gemini_live.llm import GeminiLiveLLMService from pipecat.services.mcp_service import MCPClient @@ -58,7 +58,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): tts = CartesiaTTSService( api_key=os.getenv("CARTESIA_API_KEY"), - settings=CartesiaTTSSettings( + settings=CartesiaTTSService.Settings( voice="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady ), ) diff --git a/examples/foundational/39c-multiple-mcp.py b/examples/foundational/39c-multiple-mcp.py index 4c7bc27d9..b1ef3cb00 100644 --- a/examples/foundational/39c-multiple-mcp.py +++ b/examples/foundational/39c-multiple-mcp.py @@ -37,8 +37,8 @@ from pipecat.processors.aggregators.llm_response_universal import ( from pipecat.processors.frame_processor import FrameDirection, FrameProcessor from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport -from pipecat.services.anthropic.llm import AnthropicLLMService, AnthropicLLMSettings -from pipecat.services.cartesia.tts import CartesiaTTSService, CartesiaTTSSettings +from pipecat.services.anthropic.llm import AnthropicLLMService +from pipecat.services.cartesia.tts import CartesiaTTSService from pipecat.services.deepgram.stt import DeepgramSTTService from pipecat.services.mcp_service import MCPClient from pipecat.transports.base_transport import BaseTransport, TransportParams @@ -120,7 +120,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): tts = CartesiaTTSService( api_key=os.getenv("CARTESIA_API_KEY"), - settings=CartesiaTTSSettings( + settings=CartesiaTTSService.Settings( voice="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady ), ) @@ -141,7 +141,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): llm = AnthropicLLMService( api_key=os.getenv("ANTHROPIC_API_KEY"), - settings=AnthropicLLMSettings( + settings=AnthropicLLMService.Settings( system_instruction=system_prompt, ), ) diff --git a/examples/foundational/40-aws-nova-sonic.py b/examples/foundational/40-aws-nova-sonic.py index 327efaac5..79a3d168c 100644 --- a/examples/foundational/40-aws-nova-sonic.py +++ b/examples/foundational/40-aws-nova-sonic.py @@ -28,7 +28,7 @@ from pipecat.processors.aggregators.llm_response_universal import ( ) from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport -from pipecat.services.aws.nova_sonic.llm import AWSNovaSonicLLMService, AWSNovaSonicLLMSettings +from pipecat.services.aws.nova_sonic.llm import AWSNovaSonicLLMService from pipecat.services.llm_service import FunctionCallParams from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams @@ -130,7 +130,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): # - ap-northeast-1 region=os.getenv("AWS_REGION"), session_token=os.getenv("AWS_SESSION_TOKEN"), - settings=AWSNovaSonicLLMSettings( + settings=AWSNovaSonicLLMService.Settings( voice="tiffany", system_instruction=system_instruction, ), diff --git a/examples/foundational/42-interruption-config.py b/examples/foundational/42-interruption-config.py index a74b5cc7b..d690f60f0 100644 --- a/examples/foundational/42-interruption-config.py +++ b/examples/foundational/42-interruption-config.py @@ -22,9 +22,9 @@ from pipecat.processors.aggregators.llm_response_universal import ( ) from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport -from pipecat.services.cartesia.tts import CartesiaTTSService, CartesiaTTSSettings +from pipecat.services.cartesia.tts import CartesiaTTSService from pipecat.services.deepgram.stt import DeepgramSTTService -from pipecat.services.openai.llm import OpenAILLMService, OpenAILLMSettings +from pipecat.services.openai.llm import OpenAILLMService from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams @@ -59,14 +59,14 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): tts = CartesiaTTSService( api_key=os.getenv("CARTESIA_API_KEY"), - settings=CartesiaTTSSettings( + settings=CartesiaTTSService.Settings( voice="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady ), ) llm = OpenAILLMService( api_key=os.getenv("OPENAI_API_KEY"), - settings=OpenAILLMSettings( + settings=OpenAILLMService.Settings( system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", ), ) diff --git a/examples/foundational/43-heygen-transport.py b/examples/foundational/43-heygen-transport.py index 23b87a5bb..07190da16 100644 --- a/examples/foundational/43-heygen-transport.py +++ b/examples/foundational/43-heygen-transport.py @@ -22,9 +22,9 @@ from pipecat.processors.aggregators.llm_response_universal import ( LLMContextAggregatorPair, LLMUserAggregatorParams, ) -from pipecat.services.cartesia.tts import CartesiaTTSService, CartesiaTTSSettings +from pipecat.services.cartesia.tts import CartesiaTTSService from pipecat.services.deepgram.stt import DeepgramSTTService -from pipecat.services.google.llm import GoogleLLMService, GoogleLLMSettings +from pipecat.services.google.llm import GoogleLLMService from pipecat.services.heygen.api_liveavatar import LiveAvatarNewSessionRequest from pipecat.transports.heygen.transport import HeyGenParams, HeyGenTransport, ServiceType @@ -56,14 +56,14 @@ async def main(): tts = CartesiaTTSService( api_key=os.getenv("CARTESIA_API_KEY"), - settings=CartesiaTTSSettings( + settings=CartesiaTTSService.Settings( voice="00967b2f-88a6-4a31-8153-110a92134b9f", ), ) llm = GoogleLLMService( api_key=os.getenv("GOOGLE_API_KEY"), - settings=GoogleLLMSettings( + settings=GoogleLLMService.Settings( system_instruction="You are a helpful assistant. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Be succinct and respond to what the user said in a creative and helpful way.", ), ) diff --git a/examples/foundational/43a-heygen-video-service.py b/examples/foundational/43a-heygen-video-service.py index 5edeb6bc3..580aa52fc 100644 --- a/examples/foundational/43a-heygen-video-service.py +++ b/examples/foundational/43a-heygen-video-service.py @@ -22,9 +22,9 @@ from pipecat.processors.aggregators.llm_response_universal import ( ) from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport -from pipecat.services.cartesia.tts import CartesiaTTSService, CartesiaTTSSettings +from pipecat.services.cartesia.tts import CartesiaTTSService from pipecat.services.deepgram.stt import DeepgramSTTService -from pipecat.services.google.llm import GoogleLLMService, GoogleLLMSettings +from pipecat.services.google.llm import GoogleLLMService from pipecat.services.heygen.api_liveavatar import LiveAvatarNewSessionRequest from pipecat.services.heygen.client import ServiceType from pipecat.services.heygen.video import HeyGenVideoService @@ -63,14 +63,14 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): tts = CartesiaTTSService( api_key=os.getenv("CARTESIA_API_KEY"), - settings=CartesiaTTSSettings( + settings=CartesiaTTSService.Settings( voice="00967b2f-88a6-4a31-8153-110a92134b9f", ), ) llm = GoogleLLMService( api_key=os.getenv("GOOGLE_API_KEY"), - settings=GoogleLLMSettings( + settings=GoogleLLMService.Settings( system_instruction="You are a helpful assistant. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Be succinct and respond to what the user said in a creative and helpful way.", ), ) diff --git a/examples/foundational/44-voicemail-detection.py b/examples/foundational/44-voicemail-detection.py index ef7d73b38..df47bb945 100644 --- a/examples/foundational/44-voicemail-detection.py +++ b/examples/foundational/44-voicemail-detection.py @@ -22,9 +22,9 @@ from pipecat.processors.aggregators.llm_response_universal import ( ) from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport -from pipecat.services.cartesia.tts import CartesiaTTSService, CartesiaTTSSettings +from pipecat.services.cartesia.tts import CartesiaTTSService from pipecat.services.deepgram.stt import DeepgramSTTService -from pipecat.services.openai.llm import OpenAILLMService, OpenAILLMSettings +from pipecat.services.openai.llm import OpenAILLMService from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams @@ -56,14 +56,14 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): tts = CartesiaTTSService( api_key=os.getenv("CARTESIA_API_KEY"), - settings=CartesiaTTSSettings( + settings=CartesiaTTSService.Settings( voice="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady ), ) llm = OpenAILLMService( api_key=os.getenv("OPENAI_API_KEY"), - settings=OpenAILLMSettings( + settings=OpenAILLMService.Settings( system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", ), ) diff --git a/examples/foundational/45-before-and-after-events.py b/examples/foundational/45-before-and-after-events.py index e0e5604c6..3c583546f 100644 --- a/examples/foundational/45-before-and-after-events.py +++ b/examples/foundational/45-before-and-after-events.py @@ -22,9 +22,9 @@ from pipecat.processors.aggregators.llm_response_universal import ( ) from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport -from pipecat.services.cartesia.tts import CartesiaTTSService, CartesiaTTSSettings +from pipecat.services.cartesia.tts import CartesiaTTSService from pipecat.services.deepgram.stt import DeepgramSTTService -from pipecat.services.openai.llm import OpenAILLMService, OpenAILLMSettings +from pipecat.services.openai.llm import OpenAILLMService from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams @@ -67,14 +67,14 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): tts = CartesiaTTSService( api_key=os.getenv("CARTESIA_API_KEY"), - settings=CartesiaTTSSettings( + settings=CartesiaTTSService.Settings( voice="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady ), ) llm = OpenAILLMService( api_key=os.getenv("OPENAI_API_KEY"), - settings=OpenAILLMSettings( + settings=OpenAILLMService.Settings( system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", ), ) diff --git a/examples/foundational/47-sentry-metrics.py b/examples/foundational/47-sentry-metrics.py index a415fd975..9fe35d4c4 100644 --- a/examples/foundational/47-sentry-metrics.py +++ b/examples/foundational/47-sentry-metrics.py @@ -23,9 +23,9 @@ from pipecat.processors.aggregators.llm_response_universal import ( from pipecat.processors.metrics.sentry import SentryMetrics from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport -from pipecat.services.cartesia.tts import CartesiaTTSService, CartesiaTTSSettings +from pipecat.services.cartesia.tts import CartesiaTTSService from pipecat.services.deepgram.stt import DeepgramSTTService -from pipecat.services.openai.llm import OpenAILLMService, OpenAILLMSettings +from pipecat.services.openai.llm import OpenAILLMService from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams @@ -66,7 +66,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): tts = CartesiaTTSService( api_key=os.getenv("CARTESIA_API_KEY"), - settings=CartesiaTTSSettings( + settings=CartesiaTTSService.Settings( voice="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady ), metrics=SentryMetrics(), @@ -75,7 +75,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): llm = OpenAILLMService( api_key=os.getenv("OPENAI_API_KEY"), metrics=SentryMetrics(), - settings=OpenAILLMSettings( + settings=OpenAILLMService.Settings( system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", ), ) diff --git a/examples/foundational/48-service-switcher.py b/examples/foundational/48-service-switcher.py index 970e14839..e37925006 100644 --- a/examples/foundational/48-service-switcher.py +++ b/examples/foundational/48-service-switcher.py @@ -27,12 +27,12 @@ from pipecat.processors.aggregators.llm_response_universal import ( from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport from pipecat.services.cartesia.stt import CartesiaSTTService -from pipecat.services.cartesia.tts import CartesiaTTSService, CartesiaTTSSettings +from pipecat.services.cartesia.tts import CartesiaTTSService from pipecat.services.deepgram.stt import DeepgramSTTService -from pipecat.services.deepgram.tts import DeepgramTTSService, DeepgramTTSSettings -from pipecat.services.google.llm import GoogleLLMService, GoogleLLMSettings +from pipecat.services.deepgram.tts import DeepgramTTSService +from pipecat.services.google.llm import GoogleLLMService from pipecat.services.llm_service import FunctionCallParams -from pipecat.services.openai.llm import OpenAILLMService, OpenAILLMSettings +from pipecat.services.openai.llm import OpenAILLMService from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams @@ -102,13 +102,13 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): tts_cartesia = CartesiaTTSService( api_key=os.getenv("CARTESIA_API_KEY"), - settings=CartesiaTTSSettings( + settings=CartesiaTTSService.Settings( voice="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady ), ) tts_deepgram = DeepgramTTSService( api_key=os.getenv("DEEPGRAM_API_KEY"), - settings=DeepgramTTSSettings( + settings=DeepgramTTSService.Settings( voice="aura-2-helena-en", ), ) @@ -120,11 +120,11 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): llm_openai = OpenAILLMService( api_key=os.getenv("OPENAI_API_KEY"), - settings=OpenAILLMSettings(system_instruction=system_prompt), + settings=OpenAILLMService.Settings(system_instruction=system_prompt), ) llm_google = GoogleLLMService( api_key=os.getenv("GOOGLE_API_KEY"), - settings=GoogleLLMSettings(system_instruction=system_prompt), + settings=GoogleLLMService.Settings(system_instruction=system_prompt), ) llm_switcher = LLMSwitcher( llms=[llm_openai, llm_google], strategy_type=ServiceSwitcherStrategyManual diff --git a/examples/foundational/49a-thinking-anthropic.py b/examples/foundational/49a-thinking-anthropic.py index a222ad19f..8825ce7c5 100644 --- a/examples/foundational/49a-thinking-anthropic.py +++ b/examples/foundational/49a-thinking-anthropic.py @@ -22,12 +22,8 @@ from pipecat.processors.aggregators.llm_response_universal import ( ) from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport -from pipecat.services.anthropic.llm import ( - AnthropicLLMService, - AnthropicLLMSettings, - AnthropicThinkingConfig, -) -from pipecat.services.cartesia.tts import CartesiaTTSService, CartesiaTTSSettings +from pipecat.services.anthropic.llm import AnthropicLLMService, AnthropicThinkingConfig +from pipecat.services.cartesia.tts import CartesiaTTSService from pipecat.services.deepgram.stt import DeepgramSTTService from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams @@ -60,14 +56,14 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): tts = CartesiaTTSService( api_key=os.getenv("CARTESIA_API_KEY"), - settings=CartesiaTTSSettings( + settings=CartesiaTTSService.Settings( voice="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady ), ) llm = AnthropicLLMService( api_key=os.getenv("ANTHROPIC_API_KEY"), - settings=AnthropicLLMSettings( + settings=AnthropicLLMService.Settings( thinking=AnthropicThinkingConfig( type="enabled", budget_tokens=2048, diff --git a/examples/foundational/49b-thinking-google.py b/examples/foundational/49b-thinking-google.py index 05ec76f4c..ed7a393b0 100644 --- a/examples/foundational/49b-thinking-google.py +++ b/examples/foundational/49b-thinking-google.py @@ -22,9 +22,9 @@ from pipecat.processors.aggregators.llm_response_universal import ( ) from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport -from pipecat.services.cartesia.tts import CartesiaTTSService, CartesiaTTSSettings +from pipecat.services.cartesia.tts import CartesiaTTSService from pipecat.services.deepgram.stt import DeepgramSTTService -from pipecat.services.google.llm import GoogleLLMService, GoogleLLMSettings, GoogleThinkingConfig +from pipecat.services.google.llm import GoogleLLMService, GoogleThinkingConfig from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams @@ -56,7 +56,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): tts = CartesiaTTSService( api_key=os.getenv("CARTESIA_API_KEY"), - settings=CartesiaTTSSettings( + settings=CartesiaTTSService.Settings( voice="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady ), ) @@ -64,7 +64,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): llm = GoogleLLMService( api_key=os.getenv("GOOGLE_API_KEY"), # model="gemini-3-pro-preview", # A more powerful reasoning model, but slower - settings=GoogleLLMSettings( + settings=GoogleLLMService.Settings( thinking=GoogleThinkingConfig( thinking_budget=-1, # Dynamic thinking include_thoughts=True, diff --git a/examples/foundational/49c-thinking-functions-anthropic.py b/examples/foundational/49c-thinking-functions-anthropic.py index 977b49800..bc9f334c8 100644 --- a/examples/foundational/49c-thinking-functions-anthropic.py +++ b/examples/foundational/49c-thinking-functions-anthropic.py @@ -23,12 +23,8 @@ from pipecat.processors.aggregators.llm_response_universal import ( ) from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport -from pipecat.services.anthropic.llm import ( - AnthropicLLMService, - AnthropicLLMSettings, - AnthropicThinkingConfig, -) -from pipecat.services.cartesia.tts import CartesiaTTSService, CartesiaTTSSettings +from pipecat.services.anthropic.llm import AnthropicLLMService, AnthropicThinkingConfig +from pipecat.services.cartesia.tts import CartesiaTTSService from pipecat.services.deepgram.stt import DeepgramSTTService from pipecat.services.llm_service import FunctionCallParams from pipecat.transports.base_transport import BaseTransport, TransportParams @@ -81,14 +77,14 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): tts = CartesiaTTSService( api_key=os.getenv("CARTESIA_API_KEY"), - settings=CartesiaTTSSettings( + settings=CartesiaTTSService.Settings( voice="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady ), ) llm = AnthropicLLMService( api_key=os.getenv("ANTHROPIC_API_KEY"), - settings=AnthropicLLMSettings( + settings=AnthropicLLMService.Settings( thinking=AnthropicThinkingConfig( type="enabled", budget_tokens=2048, diff --git a/examples/foundational/49d-thinking-functions-google.py b/examples/foundational/49d-thinking-functions-google.py index 81b01f744..e8ecefcdd 100644 --- a/examples/foundational/49d-thinking-functions-google.py +++ b/examples/foundational/49d-thinking-functions-google.py @@ -23,9 +23,9 @@ from pipecat.processors.aggregators.llm_response_universal import ( ) from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport -from pipecat.services.cartesia.tts import CartesiaTTSService, CartesiaTTSSettings +from pipecat.services.cartesia.tts import CartesiaTTSService from pipecat.services.deepgram.stt import DeepgramSTTService -from pipecat.services.google.llm import GoogleLLMService, GoogleLLMSettings, GoogleThinkingConfig +from pipecat.services.google.llm import GoogleLLMService, GoogleThinkingConfig from pipecat.services.llm_service import FunctionCallParams from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams @@ -77,7 +77,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): tts = CartesiaTTSService( api_key=os.getenv("CARTESIA_API_KEY"), - settings=CartesiaTTSSettings( + settings=CartesiaTTSService.Settings( voice="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady ), ) @@ -85,7 +85,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): llm = GoogleLLMService( api_key=os.getenv("GOOGLE_API_KEY"), # model="gemini-3-pro-preview", # A more powerful reasoning model, but slower - settings=GoogleLLMSettings( + settings=GoogleLLMService.Settings( thinking=GoogleThinkingConfig( thinking_budget=-1, # Dynamic thinking include_thoughts=True, diff --git a/examples/foundational/51-grok-realtime.py b/examples/foundational/51-grok-realtime.py index 87486a0de..81a2c28c4 100644 --- a/examples/foundational/51-grok-realtime.py +++ b/examples/foundational/51-grok-realtime.py @@ -199,7 +199,9 @@ Always be helpful and proactive in offering assistance.""", # Create the Grok Realtime LLM service llm = GrokRealtimeLLMService( api_key=os.getenv("GROK_API_KEY"), - session_properties=session_properties, + settings=GrokRealtimeLLMService.Settings( + session_properties=session_properties, + ), ) # Register function handlers diff --git a/examples/foundational/52-live-translation.py b/examples/foundational/52-live-translation.py index a90eb3ce4..7a4a4b112 100644 --- a/examples/foundational/52-live-translation.py +++ b/examples/foundational/52-live-translation.py @@ -22,9 +22,9 @@ from pipecat.processors.aggregators.llm_response_universal import ( ) from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport -from pipecat.services.cartesia.tts import CartesiaTTSService, CartesiaTTSSettings +from pipecat.services.cartesia.tts import CartesiaTTSService from pipecat.services.deepgram.stt import DeepgramSTTService -from pipecat.services.openai.llm import OpenAILLMService, OpenAILLMSettings +from pipecat.services.openai.llm import OpenAILLMService from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams @@ -59,14 +59,14 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): tts = CartesiaTTSService( api_key=os.getenv("CARTESIA_API_KEY"), - settings=CartesiaTTSSettings( + settings=CartesiaTTSService.Settings( voice="d4db5fb9-f44b-4bd1-85fa-192e0f0d75f9", # Spanish-speaking Lady ), ) llm = OpenAILLMService( api_key=os.getenv("OPENAI_API_KEY"), - settings=OpenAILLMSettings( + settings=OpenAILLMService.Settings( system_instruction="You are a live translation assistant. Your sole purpose is to translate English text into Spanish. When you receive English text from the user, immediately translate it into natural, fluent Spanish. Do not add explanations, commentary, or extra information—only provide the Spanish translation of the text you receive.", ), ) diff --git a/examples/foundational/53-concurrent-llm-evaluation.py b/examples/foundational/53-concurrent-llm-evaluation.py index 0ae0afa18..46b2847e9 100644 --- a/examples/foundational/53-concurrent-llm-evaluation.py +++ b/examples/foundational/53-concurrent-llm-evaluation.py @@ -24,10 +24,10 @@ from pipecat.processors.aggregators.llm_response_universal import ( from pipecat.processors.audio.vad_processor import VADProcessor from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport -from pipecat.services.cartesia.tts import CartesiaTTSService, CartesiaTTSSettings +from pipecat.services.cartesia.tts import CartesiaTTSService from pipecat.services.deepgram.stt import DeepgramSTTService -from pipecat.services.groq.llm import GroqLLMService, GroqLLMSettings -from pipecat.services.openai.llm import OpenAILLMService, OpenAILLMSettings +from pipecat.services.groq.llm import GroqLLMService +from pipecat.services.openai.llm import OpenAILLMService from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams @@ -62,21 +62,21 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): tts = CartesiaTTSService( api_key=os.getenv("CARTESIA_API_KEY"), - settings=CartesiaTTSSettings( + settings=CartesiaTTSService.Settings( voice="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady ), ) openai_llm = OpenAILLMService( api_key=os.getenv("OPENAI_API_KEY"), - settings=OpenAILLMSettings( + settings=OpenAILLMService.Settings( system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", ), ) groq_llm = GroqLLMService( api_key=os.getenv("GROQ_API_KEY"), - settings=GroqLLMSettings( + settings=GroqLLMService.Settings( model="meta-llama/llama-4-maverick-17b-128e-instruct", system_instruction="You are a very helpful assistant. Your goal is to demonstrate your capabilities in detail in a creative and helpful way.", ), diff --git a/examples/foundational/53-concurrent-llm-rtvi-ignored-sources.py b/examples/foundational/53-concurrent-llm-rtvi-ignored-sources.py index d6b3feac3..d27bd86a1 100644 --- a/examples/foundational/53-concurrent-llm-rtvi-ignored-sources.py +++ b/examples/foundational/53-concurrent-llm-rtvi-ignored-sources.py @@ -31,9 +31,9 @@ from pipecat.processors.audio.vad_processor import VADProcessor from pipecat.processors.frameworks.rtvi import RTVIObserverParams from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport -from pipecat.services.cartesia.tts import CartesiaTTSService, CartesiaTTSSettings +from pipecat.services.cartesia.tts import CartesiaTTSService from pipecat.services.deepgram.stt import DeepgramSTTService -from pipecat.services.openai.llm import OpenAILLMService, OpenAILLMSettings +from pipecat.services.openai.llm import OpenAILLMService from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams @@ -67,7 +67,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): tts = CartesiaTTSService( api_key=os.getenv("CARTESIA_API_KEY"), - settings=CartesiaTTSSettings( + settings=CartesiaTTSService.Settings( voice="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady ), ) @@ -75,7 +75,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): # Main LLM — drives the conversation. Its RTVI events reach the client. main_llm = OpenAILLMService( api_key=os.getenv("OPENAI_API_KEY"), - settings=OpenAILLMSettings( + settings=OpenAILLMService.Settings( system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", ), ) @@ -85,7 +85,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): evaluator_llm = OpenAILLMService( api_key=os.getenv("OPENAI_API_KEY"), name="EvaluatorLLM", - settings=OpenAILLMSettings( + settings=OpenAILLMService.Settings( system_instruction="You are a silent quality evaluator. When given a user message, respond with a single JSON object: {'score': <1-5>, 'reason': ''}. Do not respond conversationally.", ), ) diff --git a/examples/foundational/54-context-summarization-openai.py b/examples/foundational/54-context-summarization-openai.py index 9c3f75fa5..0c0b72c17 100644 --- a/examples/foundational/54-context-summarization-openai.py +++ b/examples/foundational/54-context-summarization-openai.py @@ -34,10 +34,10 @@ from pipecat.processors.aggregators.llm_response_universal import ( ) from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport -from pipecat.services.cartesia.tts import CartesiaTTSService, CartesiaTTSSettings +from pipecat.services.cartesia.tts import CartesiaTTSService from pipecat.services.deepgram.stt import DeepgramSTTService from pipecat.services.llm_service import FunctionCallParams -from pipecat.services.openai.llm import OpenAILLMService, OpenAILLMSettings +from pipecat.services.openai.llm import OpenAILLMService from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams @@ -81,14 +81,14 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): tts = CartesiaTTSService( api_key=os.getenv("CARTESIA_API_KEY"), - settings=CartesiaTTSSettings( + settings=CartesiaTTSService.Settings( voice="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady ), ) llm = OpenAILLMService( api_key=os.getenv("OPENAI_API_KEY"), - settings=OpenAILLMSettings( + settings=OpenAILLMService.Settings( system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way. You have access to tools to get the current weather - use them when relevant.", ), ) diff --git a/examples/foundational/54a-context-summarization-google.py b/examples/foundational/54a-context-summarization-google.py index b9ce3d7c7..6c6315466 100644 --- a/examples/foundational/54a-context-summarization-google.py +++ b/examples/foundational/54a-context-summarization-google.py @@ -34,9 +34,9 @@ from pipecat.processors.aggregators.llm_response_universal import ( ) from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport -from pipecat.services.cartesia.tts import CartesiaTTSService, CartesiaTTSSettings +from pipecat.services.cartesia.tts import CartesiaTTSService from pipecat.services.deepgram.stt import DeepgramSTTService -from pipecat.services.google import GoogleLLMService, GoogleLLMSettings +from pipecat.services.google import GoogleLLMService from pipecat.services.llm_service import FunctionCallParams from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams @@ -81,14 +81,14 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): tts = CartesiaTTSService( api_key=os.getenv("CARTESIA_API_KEY"), - settings=CartesiaTTSSettings( + settings=CartesiaTTSService.Settings( voice="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady ), ) llm = GoogleLLMService( api_key=os.getenv("GOOGLE_API_KEY"), - settings=GoogleLLMSettings( + settings=GoogleLLMService.Settings( system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way. You have access to tools to get the current weather - use them when relevant.", ), ) diff --git a/examples/foundational/54b-context-summarization-manual-openai.py b/examples/foundational/54b-context-summarization-manual-openai.py index ae1e9bf14..520e1c996 100644 --- a/examples/foundational/54b-context-summarization-manual-openai.py +++ b/examples/foundational/54b-context-summarization-manual-openai.py @@ -34,15 +34,13 @@ from pipecat.processors.aggregators.llm_response_universal import ( ) from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport -from pipecat.services.cartesia.tts import CartesiaTTSService, CartesiaTTSSettings +from pipecat.services.cartesia.tts import CartesiaTTSService from pipecat.services.deepgram.stt import DeepgramSTTService from pipecat.services.llm_service import FunctionCallParams -from pipecat.services.openai.llm import OpenAILLMService, OpenAILLMSettings +from pipecat.services.openai.llm import OpenAILLMService from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams -from pipecat.turns.user_stop import TurnAnalyzerUserTurnStopStrategy -from pipecat.turns.user_turn_strategies import UserTurnStrategies load_dotenv(override=True) @@ -78,7 +76,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): tts = CartesiaTTSService( api_key=os.getenv("CARTESIA_API_KEY"), - settings=CartesiaTTSSettings( + settings=CartesiaTTSService.Settings( voice="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady ), ) @@ -94,7 +92,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): llm = OpenAILLMService( api_key=os.getenv("OPENAI_API_KEY"), - settings=OpenAILLMSettings( + settings=OpenAILLMService.Settings( system_instruction=system_prompt, ), ) diff --git a/examples/foundational/54c-context-summarization-dedicated-llm.py b/examples/foundational/54c-context-summarization-dedicated-llm.py index c3c4a0c2e..249368a68 100644 --- a/examples/foundational/54c-context-summarization-dedicated-llm.py +++ b/examples/foundational/54c-context-summarization-dedicated-llm.py @@ -36,11 +36,11 @@ from pipecat.processors.aggregators.llm_response_universal import ( ) from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport -from pipecat.services.cartesia.tts import CartesiaTTSService, CartesiaTTSSettings +from pipecat.services.cartesia.tts import CartesiaTTSService from pipecat.services.deepgram.stt import DeepgramSTTService -from pipecat.services.google.llm import GoogleLLMService, GoogleLLMSettings +from pipecat.services.google.llm import GoogleLLMService from pipecat.services.llm_service import FunctionCallParams -from pipecat.services.openai.llm import OpenAILLMService, OpenAILLMSettings +from pipecat.services.openai.llm import OpenAILLMService from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams @@ -93,7 +93,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): tts = CartesiaTTSService( api_key=os.getenv("CARTESIA_API_KEY"), - settings=CartesiaTTSSettings( + settings=CartesiaTTSService.Settings( voice="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady ), ) @@ -110,7 +110,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): # Primary LLM for conversation (could be any provider) llm = OpenAILLMService( api_key=os.getenv("OPENAI_API_KEY"), - settings=OpenAILLMSettings( + settings=OpenAILLMService.Settings( system_instruction=system_prompt, ), ) @@ -118,7 +118,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): # Dedicated cheap/fast LLM for summarization only summarization_llm = GoogleLLMService( api_key=os.getenv("GOOGLE_API_KEY"), - settings=GoogleLLMSettings( + settings=GoogleLLMService.Settings( model="gemini-2.5-flash", ), ) diff --git a/examples/foundational/55a-update-settings-deepgram-flux-stt.py b/examples/foundational/55a-update-settings-deepgram-flux-stt.py index 72d9b5638..fb0fbed72 100644 --- a/examples/foundational/55a-update-settings-deepgram-flux-stt.py +++ b/examples/foundational/55a-update-settings-deepgram-flux-stt.py @@ -22,9 +22,9 @@ from pipecat.processors.aggregators.llm_response_universal import ( ) from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport -from pipecat.services.cartesia.tts import CartesiaTTSService, CartesiaTTSSettings -from pipecat.services.deepgram.flux.stt import DeepgramFluxSTTService, DeepgramFluxSTTSettings -from pipecat.services.openai.llm import OpenAILLMService, OpenAILLMSettings +from pipecat.services.cartesia.tts import CartesiaTTSService +from pipecat.services.deepgram.flux.stt import DeepgramFluxSTTService +from pipecat.services.openai.llm import OpenAILLMService from pipecat.transcriptions.language import Language from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams @@ -55,14 +55,14 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): tts = CartesiaTTSService( api_key=os.getenv("CARTESIA_API_KEY"), - settings=CartesiaTTSSettings( + settings=CartesiaTTSService.Settings( voice="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady ), ) llm = OpenAILLMService( api_key=os.getenv("OPENAI_API_KEY"), - settings=OpenAILLMSettings( + settings=OpenAILLMService.Settings( system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", ), ) @@ -103,7 +103,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): await asyncio.sleep(10) logger.info("Updating Deepgram Flux STT settings: language=es") await task.queue_frame( - STTUpdateSettingsFrame(delta=DeepgramFluxSTTSettings(language=Language.ES)) + STTUpdateSettingsFrame(delta=DeepgramFluxSTTService.Settings(language=Language.ES)) ) @transport.event_handler("on_client_disconnected") diff --git a/examples/foundational/55a-update-settings-deepgram-sagemaker-stt.py b/examples/foundational/55a-update-settings-deepgram-sagemaker-stt.py index 30ce506a7..4b071d733 100644 --- a/examples/foundational/55a-update-settings-deepgram-sagemaker-stt.py +++ b/examples/foundational/55a-update-settings-deepgram-sagemaker-stt.py @@ -22,12 +22,9 @@ from pipecat.processors.aggregators.llm_response_universal import ( ) from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport -from pipecat.services.cartesia.tts import CartesiaTTSService, CartesiaTTSSettings -from pipecat.services.deepgram.sagemaker.stt import ( - DeepgramSageMakerSTTService, - DeepgramSageMakerSTTSettings, -) -from pipecat.services.openai.llm import OpenAILLMService, OpenAILLMSettings +from pipecat.services.cartesia.tts import CartesiaTTSService +from pipecat.services.deepgram.sagemaker.stt import DeepgramSageMakerSTTService +from pipecat.services.openai.llm import OpenAILLMService from pipecat.transcriptions.language import Language from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams @@ -61,14 +58,14 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): tts = CartesiaTTSService( api_key=os.getenv("CARTESIA_API_KEY"), - settings=CartesiaTTSSettings( + settings=CartesiaTTSService.Settings( voice="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady ), ) llm = OpenAILLMService( api_key=os.getenv("OPENAI_API_KEY"), - settings=OpenAILLMSettings( + settings=OpenAILLMService.Settings( system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", ), ) @@ -111,7 +108,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): logger.info("Updating Deepgram SageMaker STT settings: language=es, punctuate=False") await task.queue_frame( STTUpdateSettingsFrame( - delta=DeepgramSageMakerSTTSettings( + delta=DeepgramSageMakerSTTService.Settings( language=Language.ES, punctuate=False, ) diff --git a/examples/foundational/55a-update-settings-deepgram-stt.py b/examples/foundational/55a-update-settings-deepgram-stt.py index 100887f80..3c39c8cd5 100644 --- a/examples/foundational/55a-update-settings-deepgram-stt.py +++ b/examples/foundational/55a-update-settings-deepgram-stt.py @@ -22,9 +22,9 @@ from pipecat.processors.aggregators.llm_response_universal import ( ) from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport -from pipecat.services.cartesia.tts import CartesiaTTSService, CartesiaTTSSettings -from pipecat.services.deepgram.stt import DeepgramSTTService, DeepgramSTTSettings -from pipecat.services.openai.llm import OpenAILLMService, OpenAILLMSettings +from pipecat.services.cartesia.tts import CartesiaTTSService +from pipecat.services.deepgram.stt import DeepgramSTTService +from pipecat.services.openai.llm import OpenAILLMService from pipecat.transcriptions.language import Language from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams @@ -55,14 +55,14 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): tts = CartesiaTTSService( api_key=os.getenv("CARTESIA_API_KEY"), - settings=CartesiaTTSSettings( + settings=CartesiaTTSService.Settings( voice="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady ), ) llm = OpenAILLMService( api_key=os.getenv("OPENAI_API_KEY"), - settings=OpenAILLMSettings( + settings=OpenAILLMService.Settings( system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", ), ) @@ -105,7 +105,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): logger.info("Updating Deepgram STT settings: language=es, punctuate=False") await task.queue_frame( STTUpdateSettingsFrame( - delta=DeepgramSTTSettings( + delta=DeepgramSTTService.Settings( language=Language.ES, punctuate=False, ) diff --git a/examples/foundational/55b-update-settings-azure-stt.py b/examples/foundational/55b-update-settings-azure-stt.py index f93f907e7..59a411caf 100644 --- a/examples/foundational/55b-update-settings-azure-stt.py +++ b/examples/foundational/55b-update-settings-azure-stt.py @@ -22,9 +22,9 @@ from pipecat.processors.aggregators.llm_response_universal import ( ) from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport -from pipecat.services.azure.stt import AzureSTTService, AzureSTTSettings -from pipecat.services.cartesia.tts import CartesiaTTSService, CartesiaTTSSettings -from pipecat.services.openai.llm import OpenAILLMService, OpenAILLMSettings +from pipecat.services.azure.stt import AzureSTTService +from pipecat.services.cartesia.tts import CartesiaTTSService +from pipecat.services.openai.llm import OpenAILLMService from pipecat.transcriptions.language import Language from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams @@ -58,14 +58,14 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): tts = CartesiaTTSService( api_key=os.getenv("CARTESIA_API_KEY"), - settings=CartesiaTTSSettings( + settings=CartesiaTTSService.Settings( voice="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady ), ) llm = OpenAILLMService( api_key=os.getenv("OPENAI_API_KEY"), - settings=OpenAILLMSettings( + settings=OpenAILLMService.Settings( system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", ), ) @@ -105,7 +105,9 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): await asyncio.sleep(10) logger.info("Updating Azure STT settings: language=es") - await task.queue_frame(STTUpdateSettingsFrame(delta=AzureSTTSettings(language=Language.ES))) + await task.queue_frame( + STTUpdateSettingsFrame(delta=AzureSTTService.Settings(language=Language.ES)) + ) @transport.event_handler("on_client_disconnected") async def on_client_disconnected(transport, client): diff --git a/examples/foundational/55c-update-settings-google-stt.py b/examples/foundational/55c-update-settings-google-stt.py index e2b844c2e..c6d44da12 100644 --- a/examples/foundational/55c-update-settings-google-stt.py +++ b/examples/foundational/55c-update-settings-google-stt.py @@ -22,9 +22,9 @@ from pipecat.processors.aggregators.llm_response_universal import ( ) from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport -from pipecat.services.cartesia.tts import CartesiaTTSService, CartesiaTTSSettings -from pipecat.services.google.stt import GoogleSTTService, GoogleSTTSettings -from pipecat.services.openai.llm import OpenAILLMService, OpenAILLMSettings +from pipecat.services.cartesia.tts import CartesiaTTSService +from pipecat.services.google.stt import GoogleSTTService +from pipecat.services.openai.llm import OpenAILLMService from pipecat.transcriptions.language import Language from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams @@ -55,14 +55,14 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): tts = CartesiaTTSService( api_key=os.getenv("CARTESIA_API_KEY"), - settings=CartesiaTTSSettings( + settings=CartesiaTTSService.Settings( voice="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady ), ) llm = OpenAILLMService( api_key=os.getenv("OPENAI_API_KEY"), - settings=OpenAILLMSettings( + settings=OpenAILLMService.Settings( system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", ), ) @@ -103,7 +103,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): await asyncio.sleep(10) logger.info("Updating Google STT settings: language=es") await task.queue_frame( - STTUpdateSettingsFrame(delta=GoogleSTTSettings(language=Language.ES)) + STTUpdateSettingsFrame(delta=GoogleSTTService.Settings(language=Language.ES)) ) @transport.event_handler("on_client_disconnected") diff --git a/examples/foundational/55d-update-settings-assemblyai-stt.py b/examples/foundational/55d-update-settings-assemblyai-stt.py index 2a49da3e2..f62a968eb 100644 --- a/examples/foundational/55d-update-settings-assemblyai-stt.py +++ b/examples/foundational/55d-update-settings-assemblyai-stt.py @@ -22,9 +22,9 @@ from pipecat.processors.aggregators.llm_response_universal import ( ) from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport -from pipecat.services.assemblyai.stt import AssemblyAISTTService, AssemblyAISTTSettings -from pipecat.services.cartesia.tts import CartesiaTTSService, CartesiaTTSSettings -from pipecat.services.openai.llm import OpenAILLMService, OpenAILLMSettings +from pipecat.services.assemblyai.stt import AssemblyAISTTService +from pipecat.services.cartesia.tts import CartesiaTTSService +from pipecat.services.openai.llm import OpenAILLMService from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams @@ -52,21 +52,21 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): stt = AssemblyAISTTService( api_key=os.getenv("ASSEMBLYAI_API_KEY"), - settings=AssemblyAISTTSettings( + settings=AssemblyAISTTService.Settings( model="u3-rt-pro", ), ) tts = CartesiaTTSService( api_key=os.getenv("CARTESIA_API_KEY"), - settings=CartesiaTTSSettings( + settings=CartesiaTTSService.Settings( voice="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady ), ) llm = OpenAILLMService( api_key=os.getenv("OPENAI_API_KEY"), - settings=OpenAILLMSettings( + settings=OpenAILLMService.Settings( system_instruction="You are a helpful LLM in a WebRTC call demonstrating dynamic keyterms updates. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Try saying difficult names like 'Xiomara', 'Saoirse', or 'Krzystof' to test transcription accuracy.", ), ) @@ -111,7 +111,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): logger.info("🔄 Updating keyterms: Adding difficult names for boosting") await task.queue_frame( STTUpdateSettingsFrame( - delta=AssemblyAISTTSettings( + delta=AssemblyAISTTService.Settings( keyterms_prompt=["Xiomara", "Saoirse", "Krzystof", "Nguyen", "Pipecat"] ) ) diff --git a/examples/foundational/55e-update-settings-gladia-stt.py b/examples/foundational/55e-update-settings-gladia-stt.py index 885c78030..6ca8fa725 100644 --- a/examples/foundational/55e-update-settings-gladia-stt.py +++ b/examples/foundational/55e-update-settings-gladia-stt.py @@ -22,9 +22,9 @@ from pipecat.processors.aggregators.llm_response_universal import ( ) from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport -from pipecat.services.cartesia.tts import CartesiaTTSService, CartesiaTTSSettings -from pipecat.services.gladia.stt import GladiaSTTService, GladiaSTTSettings -from pipecat.services.openai.llm import OpenAILLMService, OpenAILLMSettings +from pipecat.services.cartesia.tts import CartesiaTTSService +from pipecat.services.gladia.stt import GladiaSTTService +from pipecat.services.openai.llm import OpenAILLMService from pipecat.transcriptions.language import Language from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams @@ -55,14 +55,14 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): tts = CartesiaTTSService( api_key=os.getenv("CARTESIA_API_KEY"), - settings=CartesiaTTSSettings( + settings=CartesiaTTSService.Settings( voice="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady ), ) llm = OpenAILLMService( api_key=os.getenv("OPENAI_API_KEY"), - settings=OpenAILLMSettings( + settings=OpenAILLMService.Settings( system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", ), ) @@ -103,7 +103,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): await asyncio.sleep(10) logger.info("Updating Gladia STT settings: language=es") await task.queue_frame( - STTUpdateSettingsFrame(delta=GladiaSTTSettings(language=Language.ES)) + STTUpdateSettingsFrame(delta=GladiaSTTService.Settings(language=Language.ES)) ) @transport.event_handler("on_client_disconnected") diff --git a/examples/foundational/55f-update-settings-elevenlabs-realtime-stt.py b/examples/foundational/55f-update-settings-elevenlabs-realtime-stt.py index 6598240cb..ee3244ffe 100644 --- a/examples/foundational/55f-update-settings-elevenlabs-realtime-stt.py +++ b/examples/foundational/55f-update-settings-elevenlabs-realtime-stt.py @@ -22,12 +22,9 @@ from pipecat.processors.aggregators.llm_response_universal import ( ) from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport -from pipecat.services.cartesia.tts import CartesiaTTSService, CartesiaTTSSettings -from pipecat.services.elevenlabs.stt import ( - ElevenLabsRealtimeSTTService, - ElevenLabsRealtimeSTTSettings, -) -from pipecat.services.openai.llm import OpenAILLMService, OpenAILLMSettings +from pipecat.services.cartesia.tts import CartesiaTTSService +from pipecat.services.elevenlabs.stt import ElevenLabsRealtimeSTTService +from pipecat.services.openai.llm import OpenAILLMService from pipecat.transcriptions.language import Language from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams @@ -58,14 +55,14 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): tts = CartesiaTTSService( api_key=os.getenv("CARTESIA_API_KEY"), - settings=CartesiaTTSSettings( + settings=CartesiaTTSService.Settings( voice="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady ), ) llm = OpenAILLMService( api_key=os.getenv("OPENAI_API_KEY"), - settings=OpenAILLMSettings( + settings=OpenAILLMService.Settings( system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", ), ) @@ -106,7 +103,9 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): await asyncio.sleep(10) logger.info("Updating ElevenLabs Realtime STT settings: language=es") await task.queue_frame( - STTUpdateSettingsFrame(delta=ElevenLabsRealtimeSTTSettings(language=Language.ES)) + STTUpdateSettingsFrame( + delta=ElevenLabsRealtimeSTTService.Settings(language=Language.ES) + ) ) @transport.event_handler("on_client_disconnected") diff --git a/examples/foundational/55g-update-settings-elevenlabs-stt.py b/examples/foundational/55g-update-settings-elevenlabs-stt.py index 50a160b2b..6307264fc 100644 --- a/examples/foundational/55g-update-settings-elevenlabs-stt.py +++ b/examples/foundational/55g-update-settings-elevenlabs-stt.py @@ -23,9 +23,9 @@ from pipecat.processors.aggregators.llm_response_universal import ( ) from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport -from pipecat.services.cartesia.tts import CartesiaTTSService, CartesiaTTSSettings -from pipecat.services.elevenlabs.stt import ElevenLabsSTTService, ElevenLabsSTTSettings -from pipecat.services.openai.llm import OpenAILLMService, OpenAILLMSettings +from pipecat.services.cartesia.tts import CartesiaTTSService +from pipecat.services.elevenlabs.stt import ElevenLabsSTTService +from pipecat.services.openai.llm import OpenAILLMService from pipecat.transcriptions.language import Language from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams @@ -60,14 +60,14 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): tts = CartesiaTTSService( api_key=os.getenv("CARTESIA_API_KEY"), - settings=CartesiaTTSSettings( + settings=CartesiaTTSService.Settings( voice="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady ), ) llm = OpenAILLMService( api_key=os.getenv("OPENAI_API_KEY"), - settings=OpenAILLMSettings( + settings=OpenAILLMService.Settings( system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", ), ) @@ -110,7 +110,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): await asyncio.sleep(10) logger.info("Updating ElevenLabs STT settings: language=es") await task.queue_frame( - STTUpdateSettingsFrame(delta=ElevenLabsSTTSettings(language=Language.ES)) + STTUpdateSettingsFrame(delta=ElevenLabsSTTService.Settings(language=Language.ES)) ) @transport.event_handler("on_client_disconnected") diff --git a/examples/foundational/55h-update-settings-speechmatics-stt.py b/examples/foundational/55h-update-settings-speechmatics-stt.py index 89b15c94c..df6d9575b 100644 --- a/examples/foundational/55h-update-settings-speechmatics-stt.py +++ b/examples/foundational/55h-update-settings-speechmatics-stt.py @@ -22,9 +22,9 @@ from pipecat.processors.aggregators.llm_response_universal import ( ) from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport -from pipecat.services.cartesia.tts import CartesiaTTSService, CartesiaTTSSettings -from pipecat.services.openai.llm import OpenAILLMService, OpenAILLMSettings -from pipecat.services.speechmatics.stt import SpeechmaticsSTTService, SpeechmaticsSTTSettings +from pipecat.services.cartesia.tts import CartesiaTTSService +from pipecat.services.openai.llm import OpenAILLMService +from pipecat.services.speechmatics.stt import SpeechmaticsSTTService from pipecat.transcriptions.language import Language from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams @@ -53,7 +53,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): stt = SpeechmaticsSTTService( api_key=os.getenv("SPEECHMATICS_API_KEY"), - settings=SpeechmaticsSTTSettings( + settings=SpeechmaticsSTTService.Settings( enable_diarization=True, speaker_active_format="<{speaker_id}>{text}", speaker_passive_format="<{speaker_id}>{text}", @@ -62,14 +62,14 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): tts = CartesiaTTSService( api_key=os.getenv("CARTESIA_API_KEY"), - settings=CartesiaTTSSettings( + settings=CartesiaTTSService.Settings( voice="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady ), ) llm = OpenAILLMService( api_key=os.getenv("OPENAI_API_KEY"), - settings=OpenAILLMSettings( + settings=OpenAILLMService.Settings( system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", ), ) @@ -110,13 +110,13 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): await asyncio.sleep(10) logger.info("Updating Speechmatics STT settings: language=es") await task.queue_frame( - STTUpdateSettingsFrame(delta=SpeechmaticsSTTSettings(language=Language.ES)) + STTUpdateSettingsFrame(delta=SpeechmaticsSTTService.Settings(language=Language.ES)) ) await asyncio.sleep(10) logger.info("Updating Speechmatics STT settings: focus_speakers=['S1']") await task.queue_frame( - STTUpdateSettingsFrame(delta=SpeechmaticsSTTSettings(focus_speakers=["S1"])) + STTUpdateSettingsFrame(delta=SpeechmaticsSTTService.Settings(focus_speakers=["S1"])) ) await asyncio.sleep(10) @@ -125,7 +125,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): ) await task.queue_frame( STTUpdateSettingsFrame( - delta=SpeechmaticsSTTSettings( + delta=SpeechmaticsSTTService.Settings( speaker_active_format="{text}" ) ) diff --git a/examples/foundational/55i-update-settings-whisper-api-stt.py b/examples/foundational/55i-update-settings-whisper-api-stt.py index 72674d7dd..e9ef61cce 100644 --- a/examples/foundational/55i-update-settings-whisper-api-stt.py +++ b/examples/foundational/55i-update-settings-whisper-api-stt.py @@ -22,8 +22,8 @@ from pipecat.processors.aggregators.llm_response_universal import ( ) from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport -from pipecat.services.cartesia.tts import CartesiaTTSService, CartesiaTTSSettings -from pipecat.services.openai.llm import OpenAILLMService, OpenAILLMSettings +from pipecat.services.cartesia.tts import CartesiaTTSService +from pipecat.services.openai.llm import OpenAILLMService from pipecat.services.openai.stt import OpenAISTTService from pipecat.services.whisper.base_stt import BaseWhisperSTTSettings from pipecat.transports.base_transport import BaseTransport, TransportParams @@ -61,14 +61,14 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): tts = CartesiaTTSService( api_key=os.getenv("CARTESIA_API_KEY"), - settings=CartesiaTTSSettings( + settings=CartesiaTTSService.Settings( voice="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady ), ) llm = OpenAILLMService( api_key=os.getenv("OPENAI_API_KEY"), - settings=OpenAILLMSettings( + settings=OpenAILLMService.Settings( system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", ), ) diff --git a/examples/foundational/55j-update-settings-sarvam-stt.py b/examples/foundational/55j-update-settings-sarvam-stt.py index b882c8a2b..529cf461d 100644 --- a/examples/foundational/55j-update-settings-sarvam-stt.py +++ b/examples/foundational/55j-update-settings-sarvam-stt.py @@ -22,9 +22,9 @@ from pipecat.processors.aggregators.llm_response_universal import ( ) from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport -from pipecat.services.cartesia.tts import CartesiaTTSService, CartesiaTTSSettings -from pipecat.services.openai.llm import OpenAILLMService, OpenAILLMSettings -from pipecat.services.sarvam.stt import SarvamSTTService, SarvamSTTSettings +from pipecat.services.cartesia.tts import CartesiaTTSService +from pipecat.services.openai.llm import OpenAILLMService +from pipecat.services.sarvam.stt import SarvamSTTService from pipecat.transcriptions.language import Language from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams @@ -55,14 +55,14 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): tts = CartesiaTTSService( api_key=os.getenv("CARTESIA_API_KEY"), - settings=CartesiaTTSSettings( + settings=CartesiaTTSService.Settings( voice="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady ), ) llm = OpenAILLMService( api_key=os.getenv("OPENAI_API_KEY"), - settings=OpenAILLMSettings( + settings=OpenAILLMService.Settings( system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", ), ) @@ -103,7 +103,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): await asyncio.sleep(10) logger.info("Updating Sarvam STT settings: language=en-IN") await task.queue_frame( - STTUpdateSettingsFrame(delta=SarvamSTTSettings(language=Language.EN_IN)) + STTUpdateSettingsFrame(delta=SarvamSTTService.Settings(language=Language.EN_IN)) ) @transport.event_handler("on_client_disconnected") diff --git a/examples/foundational/55k-update-settings-soniox-stt.py b/examples/foundational/55k-update-settings-soniox-stt.py index bf395aefc..07e33b4cd 100644 --- a/examples/foundational/55k-update-settings-soniox-stt.py +++ b/examples/foundational/55k-update-settings-soniox-stt.py @@ -22,9 +22,9 @@ from pipecat.processors.aggregators.llm_response_universal import ( ) from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport -from pipecat.services.cartesia.tts import CartesiaTTSService, CartesiaTTSSettings -from pipecat.services.openai.llm import OpenAILLMService, OpenAILLMSettings -from pipecat.services.soniox.stt import SonioxSTTService, SonioxSTTSettings +from pipecat.services.cartesia.tts import CartesiaTTSService +from pipecat.services.openai.llm import OpenAILLMService +from pipecat.services.soniox.stt import SonioxSTTService from pipecat.transcriptions.language import Language from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams @@ -55,14 +55,14 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): tts = CartesiaTTSService( api_key=os.getenv("CARTESIA_API_KEY"), - settings=CartesiaTTSSettings( + settings=CartesiaTTSService.Settings( voice="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady ), ) llm = OpenAILLMService( api_key=os.getenv("OPENAI_API_KEY"), - settings=OpenAILLMSettings( + settings=OpenAILLMService.Settings( system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", ), ) @@ -103,7 +103,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): await asyncio.sleep(10) logger.info("Updating Soniox STT settings: language=es") await task.queue_frame( - STTUpdateSettingsFrame(delta=SonioxSTTSettings(language=Language.ES)) + STTUpdateSettingsFrame(delta=SonioxSTTService.Settings(language=Language.ES)) ) @transport.event_handler("on_client_disconnected") diff --git a/examples/foundational/55l-update-settings-aws-transcribe-stt.py b/examples/foundational/55l-update-settings-aws-transcribe-stt.py index 9c37da430..e18833d8d 100644 --- a/examples/foundational/55l-update-settings-aws-transcribe-stt.py +++ b/examples/foundational/55l-update-settings-aws-transcribe-stt.py @@ -22,9 +22,9 @@ from pipecat.processors.aggregators.llm_response_universal import ( ) from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport -from pipecat.services.aws.stt import AWSTranscribeSTTService, AWSTranscribeSTTSettings -from pipecat.services.cartesia.tts import CartesiaTTSService, CartesiaTTSSettings -from pipecat.services.openai.llm import OpenAILLMService, OpenAILLMSettings +from pipecat.services.aws.stt import AWSTranscribeSTTService +from pipecat.services.cartesia.tts import CartesiaTTSService +from pipecat.services.openai.llm import OpenAILLMService from pipecat.transcriptions.language import Language from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams @@ -55,14 +55,14 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): tts = CartesiaTTSService( api_key=os.getenv("CARTESIA_API_KEY"), - settings=CartesiaTTSSettings( + settings=CartesiaTTSService.Settings( voice="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady ), ) llm = OpenAILLMService( api_key=os.getenv("OPENAI_API_KEY"), - settings=OpenAILLMSettings( + settings=OpenAILLMService.Settings( system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", ), ) @@ -103,7 +103,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): await asyncio.sleep(10) logger.info("Updating AWS Transcribe STT settings: language=es") await task.queue_frame( - STTUpdateSettingsFrame(delta=AWSTranscribeSTTSettings(language=Language.ES)) + STTUpdateSettingsFrame(delta=AWSTranscribeSTTService.Settings(language=Language.ES)) ) @transport.event_handler("on_client_disconnected") diff --git a/examples/foundational/55m-update-settings-cartesia-stt.py b/examples/foundational/55m-update-settings-cartesia-stt.py index 97d18f6fe..0599c9b56 100644 --- a/examples/foundational/55m-update-settings-cartesia-stt.py +++ b/examples/foundational/55m-update-settings-cartesia-stt.py @@ -22,9 +22,9 @@ from pipecat.processors.aggregators.llm_response_universal import ( ) from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport -from pipecat.services.cartesia.stt import CartesiaSTTService, CartesiaSTTSettings -from pipecat.services.cartesia.tts import CartesiaTTSService, CartesiaTTSSettings -from pipecat.services.openai.llm import OpenAILLMService, OpenAILLMSettings +from pipecat.services.cartesia.stt import CartesiaSTTService +from pipecat.services.cartesia.tts import CartesiaTTSService +from pipecat.services.openai.llm import OpenAILLMService from pipecat.transcriptions.language import Language from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams @@ -55,14 +55,14 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): tts = CartesiaTTSService( api_key=os.getenv("CARTESIA_API_KEY"), - settings=CartesiaTTSSettings( + settings=CartesiaTTSService.Settings( voice="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady ), ) llm = OpenAILLMService( api_key=os.getenv("OPENAI_API_KEY"), - settings=OpenAILLMSettings( + settings=OpenAILLMService.Settings( system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", ), ) @@ -103,7 +103,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): await asyncio.sleep(10) logger.info("Updating Cartesia STT settings: language=es") await task.queue_frame( - STTUpdateSettingsFrame(delta=CartesiaSTTSettings(language=Language.ES)) + STTUpdateSettingsFrame(delta=CartesiaSTTService.Settings(language=Language.ES)) ) @transport.event_handler("on_client_disconnected") diff --git a/examples/foundational/55n-update-settings-cartesia-http-tts.py b/examples/foundational/55n-update-settings-cartesia-http-tts.py index 7ec4155da..af4e8d5c1 100644 --- a/examples/foundational/55n-update-settings-cartesia-http-tts.py +++ b/examples/foundational/55n-update-settings-cartesia-http-tts.py @@ -22,13 +22,9 @@ from pipecat.processors.aggregators.llm_response_universal import ( ) from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport -from pipecat.services.cartesia.tts import ( - CartesiaHttpTTSService, - CartesiaTTSSettings, - GenerationConfig, -) +from pipecat.services.cartesia.tts import CartesiaHttpTTSService, GenerationConfig from pipecat.services.deepgram.stt import DeepgramSTTService -from pipecat.services.openai.llm import OpenAILLMService, OpenAILLMSettings +from pipecat.services.openai.llm import OpenAILLMService from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams @@ -58,14 +54,14 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): tts = CartesiaHttpTTSService( api_key=os.getenv("CARTESIA_API_KEY"), - settings=CartesiaTTSSettings( + settings=CartesiaHttpTTSService.Settings( voice="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady ), ) llm = OpenAILLMService( api_key=os.getenv("OPENAI_API_KEY"), - settings=OpenAILLMSettings( + settings=OpenAILLMService.Settings( system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", ), ) @@ -107,7 +103,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): logger.info("Updating Cartesia HTTP TTS settings: speed increased to 1.5") await task.queue_frame( TTSUpdateSettingsFrame( - delta=CartesiaTTSSettings(generation_config=GenerationConfig(speed=1.5)) + delta=CartesiaHttpTTSService.Settings(generation_config=GenerationConfig(speed=1.5)) ) ) diff --git a/examples/foundational/55n-update-settings-cartesia-tts.py b/examples/foundational/55n-update-settings-cartesia-tts.py index 3ecf6ba5a..64afeffc2 100644 --- a/examples/foundational/55n-update-settings-cartesia-tts.py +++ b/examples/foundational/55n-update-settings-cartesia-tts.py @@ -22,9 +22,9 @@ from pipecat.processors.aggregators.llm_response_universal import ( ) from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport -from pipecat.services.cartesia.tts import CartesiaTTSService, CartesiaTTSSettings, GenerationConfig +from pipecat.services.cartesia.tts import CartesiaTTSService, GenerationConfig from pipecat.services.deepgram.stt import DeepgramSTTService -from pipecat.services.openai.llm import OpenAILLMService, OpenAILLMSettings +from pipecat.services.openai.llm import OpenAILLMService from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams @@ -56,14 +56,14 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): tts = CartesiaTTSService( api_key=os.getenv("CARTESIA_API_KEY"), - settings=CartesiaTTSSettings( + settings=CartesiaTTSService.Settings( voice="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady ), ) llm = OpenAILLMService( api_key=os.getenv("OPENAI_API_KEY"), - settings=OpenAILLMSettings( + settings=OpenAILLMService.Settings( system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", ), ) @@ -106,7 +106,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): logger.info("Updating Cartesia TTS settings: speed increased to 1.5") await task.queue_frame( TTSUpdateSettingsFrame( - delta=CartesiaTTSSettings(generation_config=GenerationConfig(speed=1.5)) + delta=CartesiaTTSService.Settings(generation_config=GenerationConfig(speed=1.5)) ) ) diff --git a/examples/foundational/55o-update-settings-elevenlabs-http-tts.py b/examples/foundational/55o-update-settings-elevenlabs-http-tts.py index 58ef44010..8b6479edf 100644 --- a/examples/foundational/55o-update-settings-elevenlabs-http-tts.py +++ b/examples/foundational/55o-update-settings-elevenlabs-http-tts.py @@ -25,8 +25,8 @@ from pipecat.processors.aggregators.llm_response_universal import ( from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport from pipecat.services.deepgram.stt import DeepgramSTTService -from pipecat.services.elevenlabs.tts import ElevenLabsHttpTTSService, ElevenLabsHttpTTSSettings -from pipecat.services.openai.llm import OpenAILLMService, OpenAILLMSettings +from pipecat.services.elevenlabs.tts import ElevenLabsHttpTTSService +from pipecat.services.openai.llm import OpenAILLMService from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams @@ -58,13 +58,13 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): tts = ElevenLabsHttpTTSService( api_key=os.getenv("ELEVENLABS_API_KEY"), - settings=ElevenLabsHttpTTSSettings(voice=os.getenv("ELEVENLABS_VOICE_ID")), + settings=ElevenLabsHttpTTSService.Settings(voice=os.getenv("ELEVENLABS_VOICE_ID")), aiohttp_session=session, ) llm = OpenAILLMService( api_key=os.getenv("OPENAI_API_KEY"), - settings=OpenAILLMSettings( + settings=OpenAILLMService.Settings( system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", ), ) @@ -107,7 +107,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): await asyncio.sleep(10) logger.info("Updating ElevenLabs TTS settings: speed=0.7") await task.queue_frame( - TTSUpdateSettingsFrame(delta=ElevenLabsHttpTTSSettings(speed=0.7)) + TTSUpdateSettingsFrame(delta=ElevenLabsHttpTTSService.Settings(speed=0.7)) ) @transport.event_handler("on_client_disconnected") diff --git a/examples/foundational/55o-update-settings-elevenlabs-tts.py b/examples/foundational/55o-update-settings-elevenlabs-tts.py index dcab84af4..03a692324 100644 --- a/examples/foundational/55o-update-settings-elevenlabs-tts.py +++ b/examples/foundational/55o-update-settings-elevenlabs-tts.py @@ -23,9 +23,8 @@ from pipecat.processors.aggregators.llm_response_universal import ( from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport from pipecat.services.deepgram.stt import DeepgramSTTService -from pipecat.services.elevenlabs.tts import ElevenLabsTTSService, ElevenLabsTTSSettings -from pipecat.services.openai.llm import OpenAILLMService, OpenAILLMSettings -from pipecat.transcriptions.language import Language +from pipecat.services.elevenlabs.tts import ElevenLabsTTSService +from pipecat.services.openai.llm import OpenAILLMService from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams @@ -55,12 +54,12 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): tts = ElevenLabsTTSService( api_key=os.getenv("ELEVENLABS_API_KEY"), - settings=ElevenLabsTTSSettings(voice=os.getenv("ELEVENLABS_VOICE_ID")), + settings=ElevenLabsTTSService.Settings(voice=os.getenv("ELEVENLABS_VOICE_ID")), ) llm = OpenAILLMService( api_key=os.getenv("OPENAI_API_KEY"), - settings=OpenAILLMSettings( + settings=OpenAILLMService.Settings( system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", ), ) @@ -100,13 +99,15 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): await asyncio.sleep(10) logger.info("Updating ElevenLabs TTS settings: speed=0.7") - await task.queue_frame(TTSUpdateSettingsFrame(delta=ElevenLabsTTSSettings(speed=0.7))) + await task.queue_frame( + TTSUpdateSettingsFrame(delta=ElevenLabsTTSService.Settings(speed=0.7)) + ) await asyncio.sleep(10) logger.info("Updating ElevenLabs TTS settings: switching to a different voice") await task.queue_frame( TTSUpdateSettingsFrame( - delta=ElevenLabsTTSSettings(voice=os.getenv("ELEVENLABS_VOICE_ID_ALT")) + delta=ElevenLabsTTSService.Settings(voice=os.getenv("ELEVENLABS_VOICE_ID_ALT")) ) ) diff --git a/examples/foundational/55p-update-settings-openai-tts.py b/examples/foundational/55p-update-settings-openai-tts.py index 0a8c35cc2..110ee435b 100644 --- a/examples/foundational/55p-update-settings-openai-tts.py +++ b/examples/foundational/55p-update-settings-openai-tts.py @@ -23,8 +23,8 @@ from pipecat.processors.aggregators.llm_response_universal import ( from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport from pipecat.services.deepgram.stt import DeepgramSTTService -from pipecat.services.openai.llm import OpenAILLMService, OpenAILLMSettings -from pipecat.services.openai.tts import OpenAITTSService, OpenAITTSSettings +from pipecat.services.openai.llm import OpenAILLMService +from pipecat.services.openai.tts import OpenAITTSService from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams @@ -56,7 +56,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): llm = OpenAILLMService( api_key=os.getenv("OPENAI_API_KEY"), - settings=OpenAILLMSettings( + settings=OpenAILLMService.Settings( system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", ), ) @@ -97,7 +97,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): await asyncio.sleep(10) logger.info("Updating OpenAI TTS settings: speed=2.0") - await task.queue_frame(TTSUpdateSettingsFrame(delta=OpenAITTSSettings(speed=2.0))) + await task.queue_frame(TTSUpdateSettingsFrame(delta=OpenAITTSService.Settings(speed=2.0))) @transport.event_handler("on_client_disconnected") async def on_client_disconnected(transport, client): diff --git a/examples/foundational/55q-update-settings-deepgram-http-tts.py b/examples/foundational/55q-update-settings-deepgram-http-tts.py index bed83dfc3..877ec3f65 100644 --- a/examples/foundational/55q-update-settings-deepgram-http-tts.py +++ b/examples/foundational/55q-update-settings-deepgram-http-tts.py @@ -25,8 +25,8 @@ from pipecat.processors.aggregators.llm_response_universal import ( from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport from pipecat.services.deepgram.stt import DeepgramSTTService -from pipecat.services.deepgram.tts import DeepgramHttpTTSService, DeepgramTTSSettings -from pipecat.services.openai.llm import OpenAILLMService, OpenAILLMSettings +from pipecat.services.deepgram.tts import DeepgramHttpTTSService +from pipecat.services.openai.llm import OpenAILLMService from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams @@ -63,7 +63,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): llm = OpenAILLMService( api_key=os.getenv("OPENAI_API_KEY"), - settings=OpenAILLMSettings( + settings=OpenAILLMService.Settings( system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", ), ) @@ -106,13 +106,17 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): await asyncio.sleep(10) logger.info('Updating Deepgram TTS settings: voice="aura-2-aries-en"') await task.queue_frame( - TTSUpdateSettingsFrame(delta=DeepgramTTSSettings(voice="aura-2-aries-en")) + TTSUpdateSettingsFrame( + delta=DeepgramHttpTTSService.Settings(voice="aura-2-aries-en") + ) ) await asyncio.sleep(10) logger.info('Updating Deepgram TTS settings: voice="aura-2-luna-en"') await task.queue_frame( - TTSUpdateSettingsFrame(delta=DeepgramTTSSettings(voice="aura-2-luna-en")) + TTSUpdateSettingsFrame( + delta=DeepgramHttpTTSService.Settings(voice="aura-2-luna-en") + ) ) @transport.event_handler("on_client_disconnected") diff --git a/examples/foundational/55q-update-settings-deepgram-sagemaker-tts.py b/examples/foundational/55q-update-settings-deepgram-sagemaker-tts.py index 73a4ae365..270e00747 100644 --- a/examples/foundational/55q-update-settings-deepgram-sagemaker-tts.py +++ b/examples/foundational/55q-update-settings-deepgram-sagemaker-tts.py @@ -22,12 +22,9 @@ from pipecat.processors.aggregators.llm_response_universal import ( ) from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport -from pipecat.services.deepgram.sagemaker.tts import ( - DeepgramSageMakerTTSService, - DeepgramSageMakerTTSSettings, -) +from pipecat.services.deepgram.sagemaker.tts import DeepgramSageMakerTTSService from pipecat.services.deepgram.stt import DeepgramSTTService -from pipecat.services.openai.llm import OpenAILLMService, OpenAILLMSettings +from pipecat.services.openai.llm import OpenAILLMService from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams @@ -63,7 +60,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): llm = OpenAILLMService( api_key=os.getenv("OPENAI_API_KEY"), - settings=OpenAILLMSettings( + settings=OpenAILLMService.Settings( system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", ), ) @@ -104,13 +101,17 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): await asyncio.sleep(10) logger.info('Updating Deepgram SageMaker TTS settings: voice="aura-2-aries-en"') await task.queue_frame( - TTSUpdateSettingsFrame(delta=DeepgramSageMakerTTSSettings(voice="aura-2-aries-en")) + TTSUpdateSettingsFrame( + delta=DeepgramSageMakerTTSService.Settings(voice="aura-2-aries-en") + ) ) await asyncio.sleep(10) logger.info('Updating Deepgram SageMaker TTS settings: voice="aura-2-luna-en"') await task.queue_frame( - TTSUpdateSettingsFrame(delta=DeepgramSageMakerTTSSettings(voice="aura-2-luna-en")) + TTSUpdateSettingsFrame( + delta=DeepgramSageMakerTTSService.Settings(voice="aura-2-luna-en") + ) ) @transport.event_handler("on_client_disconnected") diff --git a/examples/foundational/55q-update-settings-deepgram-tts.py b/examples/foundational/55q-update-settings-deepgram-tts.py index f151f3d3f..335526768 100644 --- a/examples/foundational/55q-update-settings-deepgram-tts.py +++ b/examples/foundational/55q-update-settings-deepgram-tts.py @@ -23,8 +23,8 @@ from pipecat.processors.aggregators.llm_response_universal import ( from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport from pipecat.services.deepgram.stt import DeepgramSTTService -from pipecat.services.deepgram.tts import DeepgramTTSService, DeepgramTTSSettings -from pipecat.services.openai.llm import OpenAILLMService, OpenAILLMSettings +from pipecat.services.deepgram.tts import DeepgramTTSService +from pipecat.services.openai.llm import OpenAILLMService from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams @@ -56,7 +56,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): llm = OpenAILLMService( api_key=os.getenv("OPENAI_API_KEY"), - settings=OpenAILLMSettings( + settings=OpenAILLMService.Settings( system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", ), ) @@ -97,13 +97,13 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): await asyncio.sleep(10) logger.info('Updating Deepgram TTS settings: voice="aura-2-aries-en"') await task.queue_frame( - TTSUpdateSettingsFrame(delta=DeepgramTTSSettings(voice="aura-2-aries-en")) + TTSUpdateSettingsFrame(delta=DeepgramTTSService.Settings(voice="aura-2-aries-en")) ) await asyncio.sleep(10) logger.info('Updating Deepgram TTS settings: voice="aura-2-luna-en"') await task.queue_frame( - TTSUpdateSettingsFrame(delta=DeepgramTTSSettings(voice="aura-2-luna-en")) + TTSUpdateSettingsFrame(delta=DeepgramTTSService.Settings(voice="aura-2-luna-en")) ) @transport.event_handler("on_client_disconnected") diff --git a/examples/foundational/55r-update-settings-azure-http-tts.py b/examples/foundational/55r-update-settings-azure-http-tts.py index 56d144718..56cb23854 100644 --- a/examples/foundational/55r-update-settings-azure-http-tts.py +++ b/examples/foundational/55r-update-settings-azure-http-tts.py @@ -22,9 +22,9 @@ from pipecat.processors.aggregators.llm_response_universal import ( ) from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport -from pipecat.services.azure.tts import AzureHttpTTSService, AzureTTSSettings +from pipecat.services.azure.tts import AzureHttpTTSService from pipecat.services.deepgram.stt import DeepgramSTTService -from pipecat.services.openai.llm import OpenAILLMService, OpenAILLMSettings +from pipecat.services.openai.llm import OpenAILLMService from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams @@ -59,7 +59,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): llm = OpenAILLMService( api_key=os.getenv("OPENAI_API_KEY"), - settings=OpenAILLMSettings( + settings=OpenAILLMService.Settings( system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", ), ) @@ -100,7 +100,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): await asyncio.sleep(10) logger.info('Updating Azure TTS settings: rate="0.7", style="sad"') await task.queue_frame( - TTSUpdateSettingsFrame(delta=AzureTTSSettings(rate="0.7", style="sad")) + TTSUpdateSettingsFrame(delta=AzureHttpTTSService.Settings(rate="0.7", style="sad")) ) @transport.event_handler("on_client_disconnected") diff --git a/examples/foundational/55r-update-settings-azure-tts.py b/examples/foundational/55r-update-settings-azure-tts.py index de234fec9..5ccaa99bc 100644 --- a/examples/foundational/55r-update-settings-azure-tts.py +++ b/examples/foundational/55r-update-settings-azure-tts.py @@ -22,9 +22,9 @@ from pipecat.processors.aggregators.llm_response_universal import ( ) from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport -from pipecat.services.azure.tts import AzureTTSService, AzureTTSSettings +from pipecat.services.azure.tts import AzureTTSService from pipecat.services.deepgram.stt import DeepgramSTTService -from pipecat.services.openai.llm import OpenAILLMService, OpenAILLMSettings +from pipecat.services.openai.llm import OpenAILLMService from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams @@ -59,7 +59,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): llm = OpenAILLMService( api_key=os.getenv("OPENAI_API_KEY"), - settings=OpenAILLMSettings( + settings=OpenAILLMService.Settings( system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", ), ) @@ -100,7 +100,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): await asyncio.sleep(10) logger.info('Updating Azure TTS settings: rate="0.7", style="sad"') await task.queue_frame( - TTSUpdateSettingsFrame(delta=AzureTTSSettings(rate="0.7", style="sad")) + TTSUpdateSettingsFrame(delta=AzureTTSService.Settings(rate="0.7", style="sad")) ) @transport.event_handler("on_client_disconnected") diff --git a/examples/foundational/55s-update-settings-google-http-tts.py b/examples/foundational/55s-update-settings-google-http-tts.py index 79d3a3d42..fbe44ff07 100644 --- a/examples/foundational/55s-update-settings-google-http-tts.py +++ b/examples/foundational/55s-update-settings-google-http-tts.py @@ -23,8 +23,8 @@ from pipecat.processors.aggregators.llm_response_universal import ( from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport from pipecat.services.deepgram.stt import DeepgramSTTService -from pipecat.services.google.tts import GoogleHttpTTSService, GoogleHttpTTSSettings -from pipecat.services.openai.llm import OpenAILLMService, OpenAILLMSettings +from pipecat.services.google.tts import GoogleHttpTTSService +from pipecat.services.openai.llm import OpenAILLMService from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams @@ -56,7 +56,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): llm = OpenAILLMService( api_key=os.getenv("OPENAI_API_KEY"), - settings=OpenAILLMSettings( + settings=OpenAILLMService.Settings( system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", ), ) @@ -97,7 +97,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): await asyncio.sleep(10) logger.info("Updating Google HTTP TTS settings: speaking_rate=1.4") await task.queue_frame( - TTSUpdateSettingsFrame(delta=GoogleHttpTTSSettings(speaking_rate=1.4)) + TTSUpdateSettingsFrame(delta=GoogleHttpTTSService.Settings(speaking_rate=1.4)) ) @transport.event_handler("on_client_disconnected") diff --git a/examples/foundational/55s-update-settings-google-stream-tts.py b/examples/foundational/55s-update-settings-google-stream-tts.py index ca7e696af..b3310975a 100644 --- a/examples/foundational/55s-update-settings-google-stream-tts.py +++ b/examples/foundational/55s-update-settings-google-stream-tts.py @@ -23,8 +23,8 @@ from pipecat.processors.aggregators.llm_response_universal import ( from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport from pipecat.services.deepgram.stt import DeepgramSTTService -from pipecat.services.google.tts import GoogleStreamTTSSettings, GoogleTTSService -from pipecat.services.openai.llm import OpenAILLMService, OpenAILLMSettings +from pipecat.services.google.tts import GoogleTTSService +from pipecat.services.openai.llm import OpenAILLMService from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams @@ -56,7 +56,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): llm = OpenAILLMService( api_key=os.getenv("OPENAI_API_KEY"), - settings=OpenAILLMSettings( + settings=OpenAILLMService.Settings( system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", ), ) @@ -97,7 +97,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): await asyncio.sleep(10) logger.info("Updating Google Stream TTS settings: speaking_rate=1.4") await task.queue_frame( - TTSUpdateSettingsFrame(delta=GoogleStreamTTSSettings(speaking_rate=1.4)) + TTSUpdateSettingsFrame(delta=GoogleTTSService.Settings(speaking_rate=1.4)) ) @transport.event_handler("on_client_disconnected") diff --git a/examples/foundational/55u-update-settings-rime-http-tts.py b/examples/foundational/55u-update-settings-rime-http-tts.py index 6ecf61fce..07bb7e9a9 100644 --- a/examples/foundational/55u-update-settings-rime-http-tts.py +++ b/examples/foundational/55u-update-settings-rime-http-tts.py @@ -25,8 +25,8 @@ from pipecat.processors.aggregators.llm_response_universal import ( from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport from pipecat.services.deepgram.stt import DeepgramSTTService -from pipecat.services.openai.llm import OpenAILLMService, OpenAILLMSettings -from pipecat.services.rime.tts import RimeHttpTTSService, RimeTTSSettings +from pipecat.services.openai.llm import OpenAILLMService +from pipecat.services.rime.tts import RimeHttpTTSService from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams @@ -58,13 +58,13 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): tts = RimeHttpTTSService( api_key=os.getenv("RIME_API_KEY"), - settings=RimeTTSSettings(voice="eva"), + settings=RimeHttpTTSService.Settings(voice="eva"), aiohttp_session=session, ) llm = OpenAILLMService( api_key=os.getenv("OPENAI_API_KEY"), - settings=OpenAILLMSettings( + settings=OpenAILLMService.Settings( system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", ), ) @@ -106,7 +106,9 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): await asyncio.sleep(10) logger.info("Updating Rime TTS settings: voice=rex") - await task.queue_frame(TTSUpdateSettingsFrame(delta=RimeTTSSettings(voice="rex"))) + await task.queue_frame( + TTSUpdateSettingsFrame(delta=RimeHttpTTSService.Settings(voice="rex")) + ) @transport.event_handler("on_client_disconnected") async def on_client_disconnected(transport, client): diff --git a/examples/foundational/55u-update-settings-rime-tts.py b/examples/foundational/55u-update-settings-rime-tts.py index e8652d311..bbbdf534d 100644 --- a/examples/foundational/55u-update-settings-rime-tts.py +++ b/examples/foundational/55u-update-settings-rime-tts.py @@ -23,8 +23,8 @@ from pipecat.processors.aggregators.llm_response_universal import ( from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport from pipecat.services.deepgram.stt import DeepgramSTTService -from pipecat.services.openai.llm import OpenAILLMService, OpenAILLMSettings -from pipecat.services.rime.tts import RimeTTSService, RimeTTSSettings +from pipecat.services.openai.llm import OpenAILLMService +from pipecat.services.rime.tts import RimeTTSService from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams @@ -54,12 +54,12 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): tts = RimeTTSService( api_key=os.getenv("RIME_API_KEY"), - settings=RimeTTSSettings(voice="luna"), + settings=RimeTTSService.Settings(voice="luna"), ) llm = OpenAILLMService( api_key=os.getenv("OPENAI_API_KEY"), - settings=OpenAILLMSettings( + settings=OpenAILLMService.Settings( system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", ), ) @@ -99,7 +99,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): await asyncio.sleep(10) logger.info("Updating Rime TTS settings: voice=bond") - await task.queue_frame(TTSUpdateSettingsFrame(delta=RimeTTSSettings(voice="bond"))) + await task.queue_frame(TTSUpdateSettingsFrame(delta=RimeTTSService.Settings(voice="bond"))) @transport.event_handler("on_client_disconnected") async def on_client_disconnected(transport, client): diff --git a/examples/foundational/55v-update-settings-lmnt-tts.py b/examples/foundational/55v-update-settings-lmnt-tts.py index 55ab18a16..30f8135a0 100644 --- a/examples/foundational/55v-update-settings-lmnt-tts.py +++ b/examples/foundational/55v-update-settings-lmnt-tts.py @@ -23,8 +23,8 @@ from pipecat.processors.aggregators.llm_response_universal import ( from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport from pipecat.services.deepgram.stt import DeepgramSTTService -from pipecat.services.lmnt.tts import LmntTTSService, LmntTTSSettings -from pipecat.services.openai.llm import OpenAILLMService, OpenAILLMSettings +from pipecat.services.lmnt.tts import LmntTTSService +from pipecat.services.openai.llm import OpenAILLMService from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams @@ -54,12 +54,12 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): tts = LmntTTSService( api_key=os.getenv("LMNT_API_KEY"), - settings=LmntTTSSettings(voice="lily"), + settings=LmntTTSService.Settings(voice="lily"), ) llm = OpenAILLMService( api_key=os.getenv("OPENAI_API_KEY"), - settings=OpenAILLMSettings( + settings=OpenAILLMService.Settings( system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", ), ) @@ -99,7 +99,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): await asyncio.sleep(10) logger.info('Updating LMNT TTS settings: voice="tyler"') - await task.queue_frame(TTSUpdateSettingsFrame(delta=LmntTTSSettings(voice="tyler"))) + await task.queue_frame(TTSUpdateSettingsFrame(delta=LmntTTSService.Settings(voice="tyler"))) @transport.event_handler("on_client_disconnected") async def on_client_disconnected(transport, client): diff --git a/examples/foundational/55w-update-settings-fish-tts.py b/examples/foundational/55w-update-settings-fish-tts.py index 306f3e34d..f54d97684 100644 --- a/examples/foundational/55w-update-settings-fish-tts.py +++ b/examples/foundational/55w-update-settings-fish-tts.py @@ -23,8 +23,8 @@ from pipecat.processors.aggregators.llm_response_universal import ( from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport from pipecat.services.deepgram.stt import DeepgramSTTService -from pipecat.services.fish.tts import FishAudioTTSService, FishAudioTTSSettings -from pipecat.services.openai.llm import OpenAILLMService, OpenAILLMSettings +from pipecat.services.fish.tts import FishAudioTTSService +from pipecat.services.openai.llm import OpenAILLMService from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams @@ -54,12 +54,14 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): tts = FishAudioTTSService( api_key=os.getenv("FISH_API_KEY"), - settings=FishAudioTTSSettings(voice="4ce7e917cedd4bc2bb2e6ff3a46acaa1"), # Barack Obama + settings=FishAudioTTSService.Settings( + voice="4ce7e917cedd4bc2bb2e6ff3a46acaa1" + ), # Barack Obama ) llm = OpenAILLMService( api_key=os.getenv("OPENAI_API_KEY"), - settings=OpenAILLMSettings( + settings=OpenAILLMService.Settings( system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", ), ) @@ -100,7 +102,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): await asyncio.sleep(10) logger.info("Updating Fish Audio TTS settings: prosody_speed=1.5") await task.queue_frame( - TTSUpdateSettingsFrame(delta=FishAudioTTSSettings(prosody_speed=1.5)) + TTSUpdateSettingsFrame(delta=FishAudioTTSService.Settings(prosody_speed=1.5)) ) @transport.event_handler("on_client_disconnected") diff --git a/examples/foundational/55x-update-settings-minimax-tts.py b/examples/foundational/55x-update-settings-minimax-tts.py index 44ae6339d..53a120811 100644 --- a/examples/foundational/55x-update-settings-minimax-tts.py +++ b/examples/foundational/55x-update-settings-minimax-tts.py @@ -24,8 +24,8 @@ from pipecat.processors.aggregators.llm_response_universal import ( from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport from pipecat.services.deepgram.stt import DeepgramSTTService -from pipecat.services.minimax.tts import MiniMaxHttpTTSService, MiniMaxTTSSettings -from pipecat.services.openai.llm import OpenAILLMService, OpenAILLMSettings +from pipecat.services.minimax.tts import MiniMaxHttpTTSService +from pipecat.services.openai.llm import OpenAILLMService from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams @@ -62,7 +62,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): llm = OpenAILLMService( api_key=os.getenv("OPENAI_API_KEY"), - settings=OpenAILLMSettings( + settings=OpenAILLMService.Settings( system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", ), ) @@ -105,7 +105,9 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): await asyncio.sleep(10) logger.info('Updating MiniMax TTS settings: speed=1.5, emotion="happy"') await task.queue_frame( - TTSUpdateSettingsFrame(delta=MiniMaxTTSSettings(speed=1.5, emotion="happy")) + TTSUpdateSettingsFrame( + delta=MiniMaxHttpTTSService.Settings(speed=1.5, emotion="happy") + ) ) @transport.event_handler("on_client_disconnected") diff --git a/examples/foundational/55y-update-settings-groq-tts.py b/examples/foundational/55y-update-settings-groq-tts.py index 161c73ef0..c58b672c8 100644 --- a/examples/foundational/55y-update-settings-groq-tts.py +++ b/examples/foundational/55y-update-settings-groq-tts.py @@ -23,8 +23,8 @@ from pipecat.processors.aggregators.llm_response_universal import ( from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport from pipecat.services.deepgram.stt import DeepgramSTTService -from pipecat.services.groq.tts import GroqTTSService, GroqTTSSettings -from pipecat.services.openai.llm import OpenAILLMService, OpenAILLMSettings +from pipecat.services.groq.tts import GroqTTSService +from pipecat.services.openai.llm import OpenAILLMService from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams @@ -56,7 +56,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): llm = OpenAILLMService( api_key=os.getenv("OPENAI_API_KEY"), - settings=OpenAILLMSettings( + settings=OpenAILLMService.Settings( system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", ), ) @@ -96,7 +96,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): await asyncio.sleep(10) logger.info("Updating Groq TTS settings: voice=troy") - await task.queue_frame(TTSUpdateSettingsFrame(delta=GroqTTSSettings(voice="troy"))) + await task.queue_frame(TTSUpdateSettingsFrame(delta=GroqTTSService.Settings(voice="troy"))) @transport.event_handler("on_client_disconnected") async def on_client_disconnected(transport, client): diff --git a/examples/foundational/55z-update-settings-hume-tts.py b/examples/foundational/55z-update-settings-hume-tts.py index ea8f3b316..3af8b5fe7 100644 --- a/examples/foundational/55z-update-settings-hume-tts.py +++ b/examples/foundational/55z-update-settings-hume-tts.py @@ -23,8 +23,8 @@ from pipecat.processors.aggregators.llm_response_universal import ( from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport from pipecat.services.deepgram.stt import DeepgramSTTService -from pipecat.services.hume.tts import HumeTTSService, HumeTTSSettings -from pipecat.services.openai.llm import OpenAILLMService, OpenAILLMSettings +from pipecat.services.hume.tts import HumeTTSService +from pipecat.services.openai.llm import OpenAILLMService from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams @@ -54,12 +54,12 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): tts = HumeTTSService( api_key=os.getenv("HUME_API_KEY"), - settings=HumeTTSSettings(voice="f898a92e-685f-43fa-985b-a46920f0650b"), + settings=HumeTTSService.Settings(voice="f898a92e-685f-43fa-985b-a46920f0650b"), ) llm = OpenAILLMService( api_key=os.getenv("OPENAI_API_KEY"), - settings=OpenAILLMSettings( + settings=OpenAILLMService.Settings( system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", ), ) @@ -101,7 +101,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): logger.info('Updating Hume TTS settings: speed=2.0, description="Speak with excitement"') await task.queue_frame( TTSUpdateSettingsFrame( - delta=HumeTTSSettings(speed=2.0, description="Speak with excitement") + delta=HumeTTSService.Settings(speed=2.0, description="Speak with excitement") ) ) diff --git a/examples/foundational/55za-update-settings-neuphonic-http-tts.py b/examples/foundational/55za-update-settings-neuphonic-http-tts.py index 29de5281e..daaef4750 100644 --- a/examples/foundational/55za-update-settings-neuphonic-http-tts.py +++ b/examples/foundational/55za-update-settings-neuphonic-http-tts.py @@ -24,8 +24,8 @@ from pipecat.processors.aggregators.llm_response_universal import ( from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport from pipecat.services.deepgram.stt import DeepgramSTTService -from pipecat.services.neuphonic.tts import NeuphonicHttpTTSService, NeuphonicTTSSettings -from pipecat.services.openai.llm import OpenAILLMService, OpenAILLMSettings +from pipecat.services.neuphonic.tts import NeuphonicHttpTTSService +from pipecat.services.openai.llm import OpenAILLMService from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams @@ -61,7 +61,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): llm = OpenAILLMService( api_key=os.getenv("OPENAI_API_KEY"), - settings=OpenAILLMSettings( + settings=OpenAILLMService.Settings( system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", ), ) @@ -103,7 +103,9 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): await asyncio.sleep(10) logger.info("Updating Neuphonic HTTP TTS settings: speed=1.4") - await task.queue_frame(TTSUpdateSettingsFrame(delta=NeuphonicTTSSettings(speed=1.4))) + await task.queue_frame( + TTSUpdateSettingsFrame(delta=NeuphonicHttpTTSService.Settings(speed=1.4)) + ) @transport.event_handler("on_client_disconnected") async def on_client_disconnected(transport, client): diff --git a/examples/foundational/55za-update-settings-neuphonic-tts.py b/examples/foundational/55za-update-settings-neuphonic-tts.py index 58532eba0..dc9d3cb6f 100644 --- a/examples/foundational/55za-update-settings-neuphonic-tts.py +++ b/examples/foundational/55za-update-settings-neuphonic-tts.py @@ -23,8 +23,8 @@ from pipecat.processors.aggregators.llm_response_universal import ( from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport from pipecat.services.deepgram.stt import DeepgramSTTService -from pipecat.services.neuphonic.tts import NeuphonicTTSService, NeuphonicTTSSettings -from pipecat.services.openai.llm import OpenAILLMService, OpenAILLMSettings +from pipecat.services.neuphonic.tts import NeuphonicTTSService +from pipecat.services.openai.llm import OpenAILLMService from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams @@ -56,7 +56,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): llm = OpenAILLMService( api_key=os.getenv("OPENAI_API_KEY"), - settings=OpenAILLMSettings( + settings=OpenAILLMService.Settings( system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", ), ) @@ -96,7 +96,9 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): await asyncio.sleep(10) logger.info("Updating Neuphonic TTS settings: speed=1.4") - await task.queue_frame(TTSUpdateSettingsFrame(delta=NeuphonicTTSSettings(speed=1.4))) + await task.queue_frame( + TTSUpdateSettingsFrame(delta=NeuphonicTTSService.Settings(speed=1.4)) + ) @transport.event_handler("on_client_disconnected") async def on_client_disconnected(transport, client): diff --git a/examples/foundational/55zb-update-settings-inworld-http-tts.py b/examples/foundational/55zb-update-settings-inworld-http-tts.py index dc11afac5..bb031c231 100644 --- a/examples/foundational/55zb-update-settings-inworld-http-tts.py +++ b/examples/foundational/55zb-update-settings-inworld-http-tts.py @@ -25,8 +25,8 @@ from pipecat.processors.aggregators.llm_response_universal import ( from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport from pipecat.services.deepgram.stt import DeepgramSTTService -from pipecat.services.inworld.tts import InworldHttpTTSService, InworldTTSSettings -from pipecat.services.openai.llm import OpenAILLMService, OpenAILLMSettings +from pipecat.services.inworld.tts import InworldHttpTTSService +from pipecat.services.openai.llm import OpenAILLMService from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams @@ -60,7 +60,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): llm = OpenAILLMService( api_key=os.getenv("OPENAI_API_KEY"), - settings=OpenAILLMSettings( + settings=OpenAILLMService.Settings( system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", ), ) @@ -103,7 +103,9 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): await asyncio.sleep(10) logger.info("Updating Inworld TTS settings: speaking_rate=1.5, temperature=0.8") await task.queue_frame( - TTSUpdateSettingsFrame(delta=InworldTTSSettings(speaking_rate=1.5, temperature=0.8)) + TTSUpdateSettingsFrame( + delta=InworldHttpTTSService.Settings(speaking_rate=1.5, temperature=0.8) + ) ) @transport.event_handler("on_client_disconnected") diff --git a/examples/foundational/55zb-update-settings-inworld-tts.py b/examples/foundational/55zb-update-settings-inworld-tts.py index a1fb3a9f4..f1581bd44 100644 --- a/examples/foundational/55zb-update-settings-inworld-tts.py +++ b/examples/foundational/55zb-update-settings-inworld-tts.py @@ -23,8 +23,8 @@ from pipecat.processors.aggregators.llm_response_universal import ( from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport from pipecat.services.deepgram.stt import DeepgramSTTService -from pipecat.services.inworld.tts import InworldTTSService, InworldTTSSettings -from pipecat.services.openai.llm import OpenAILLMService, OpenAILLMSettings +from pipecat.services.inworld.tts import InworldTTSService +from pipecat.services.openai.llm import OpenAILLMService from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams @@ -56,7 +56,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): llm = OpenAILLMService( api_key=os.getenv("OPENAI_API_KEY"), - settings=OpenAILLMSettings( + settings=OpenAILLMService.Settings( system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", ), ) @@ -97,7 +97,9 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): await asyncio.sleep(10) logger.info("Updating Inworld TTS settings: speaking_rate=1.5, temperature=0.8") await task.queue_frame( - TTSUpdateSettingsFrame(delta=InworldTTSSettings(speaking_rate=1.5, temperature=0.8)) + TTSUpdateSettingsFrame( + delta=InworldTTSService.Settings(speaking_rate=1.5, temperature=0.8) + ) ) @transport.event_handler("on_client_disconnected") diff --git a/examples/foundational/55zc-update-settings-gemini-tts.py b/examples/foundational/55zc-update-settings-gemini-tts.py index 41c7dfd8b..0bf027f20 100644 --- a/examples/foundational/55zc-update-settings-gemini-tts.py +++ b/examples/foundational/55zc-update-settings-gemini-tts.py @@ -23,8 +23,8 @@ from pipecat.processors.aggregators.llm_response_universal import ( from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport from pipecat.services.deepgram.stt import DeepgramSTTService -from pipecat.services.google.tts import GeminiTTSService, GeminiTTSSettings -from pipecat.services.openai.llm import OpenAILLMService, OpenAILLMSettings +from pipecat.services.google.tts import GeminiTTSService +from pipecat.services.openai.llm import OpenAILLMService from pipecat.transcriptions.language import Language from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams @@ -55,7 +55,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): tts = GeminiTTSService( credentials=os.getenv("GOOGLE_TEST_CREDENTIALS"), - settings=GeminiTTSSettings( + settings=GeminiTTSService.Settings( model="gemini-2.5-flash-tts", voice="Charon", language=Language.EN_US, @@ -65,7 +65,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): llm = OpenAILLMService( api_key=os.getenv("OPENAI_API_KEY"), - settings=OpenAILLMSettings( + settings=OpenAILLMService.Settings( system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", ), ) @@ -106,7 +106,9 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): await asyncio.sleep(10) logger.info('Updating Gemini TTS settings: prompt="Speak slowly and dramatically"') await task.queue_frame( - TTSUpdateSettingsFrame(delta=GeminiTTSSettings(prompt="Speak slowly and dramatically")) + TTSUpdateSettingsFrame( + delta=GeminiTTSService.Settings(prompt="Speak slowly and dramatically") + ) ) @transport.event_handler("on_client_disconnected") diff --git a/examples/foundational/55zd-update-settings-aws-polly-tts.py b/examples/foundational/55zd-update-settings-aws-polly-tts.py index b1c632958..38a2544f2 100644 --- a/examples/foundational/55zd-update-settings-aws-polly-tts.py +++ b/examples/foundational/55zd-update-settings-aws-polly-tts.py @@ -22,9 +22,9 @@ from pipecat.processors.aggregators.llm_response_universal import ( ) from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport -from pipecat.services.aws.tts import AWSPollyTTSService, AWSPollyTTSSettings +from pipecat.services.aws.tts import AWSPollyTTSService from pipecat.services.deepgram.stt import DeepgramSTTService -from pipecat.services.openai.llm import OpenAILLMService, OpenAILLMSettings +from pipecat.services.openai.llm import OpenAILLMService from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams @@ -56,7 +56,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): llm = OpenAILLMService( api_key=os.getenv("OPENAI_API_KEY"), - settings=OpenAILLMSettings( + settings=OpenAILLMService.Settings( system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", ), ) @@ -96,7 +96,9 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): await asyncio.sleep(10) logger.info('Updating AWS Polly TTS settings: rate="fast"') - await task.queue_frame(TTSUpdateSettingsFrame(delta=AWSPollyTTSSettings(rate="fast"))) + await task.queue_frame( + TTSUpdateSettingsFrame(delta=AWSPollyTTSService.Settings(rate="fast")) + ) @transport.event_handler("on_client_disconnected") async def on_client_disconnected(transport, client): diff --git a/examples/foundational/55ze-update-settings-sarvam-http-tts.py b/examples/foundational/55ze-update-settings-sarvam-http-tts.py index 1bbd0886e..e00dfc621 100644 --- a/examples/foundational/55ze-update-settings-sarvam-http-tts.py +++ b/examples/foundational/55ze-update-settings-sarvam-http-tts.py @@ -25,8 +25,8 @@ from pipecat.processors.aggregators.llm_response_universal import ( from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport from pipecat.services.deepgram.stt import DeepgramSTTService -from pipecat.services.openai.llm import OpenAILLMService, OpenAILLMSettings -from pipecat.services.sarvam.tts import SarvamHttpTTSService, SarvamHttpTTSSettings +from pipecat.services.openai.llm import OpenAILLMService +from pipecat.services.sarvam.tts import SarvamHttpTTSService from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams @@ -60,7 +60,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): llm = OpenAILLMService( api_key=os.getenv("OPENAI_API_KEY"), - settings=OpenAILLMSettings( + settings=OpenAILLMService.Settings( system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", ), ) @@ -102,7 +102,9 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): await asyncio.sleep(10) logger.info("Updating Sarvam TTS settings: pace=1.5") - await task.queue_frame(TTSUpdateSettingsFrame(delta=SarvamHttpTTSSettings(pace=1.5))) + await task.queue_frame( + TTSUpdateSettingsFrame(delta=SarvamHttpTTSService.Settings(pace=1.5)) + ) @transport.event_handler("on_client_disconnected") async def on_client_disconnected(transport, client): diff --git a/examples/foundational/55ze-update-settings-sarvam-tts.py b/examples/foundational/55ze-update-settings-sarvam-tts.py index 52876c595..6b6a0709a 100644 --- a/examples/foundational/55ze-update-settings-sarvam-tts.py +++ b/examples/foundational/55ze-update-settings-sarvam-tts.py @@ -23,8 +23,8 @@ from pipecat.processors.aggregators.llm_response_universal import ( from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport from pipecat.services.deepgram.stt import DeepgramSTTService -from pipecat.services.openai.llm import OpenAILLMService, OpenAILLMSettings -from pipecat.services.sarvam.tts import SarvamTTSService, SarvamTTSSettings +from pipecat.services.openai.llm import OpenAILLMService +from pipecat.services.sarvam.tts import SarvamTTSService from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams @@ -56,7 +56,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): llm = OpenAILLMService( api_key=os.getenv("OPENAI_API_KEY"), - settings=OpenAILLMSettings( + settings=OpenAILLMService.Settings( system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", ), ) @@ -96,7 +96,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): await asyncio.sleep(10) logger.info("Updating Sarvam TTS settings: pace=1.5") - await task.queue_frame(TTSUpdateSettingsFrame(delta=SarvamTTSSettings(pace=1.5))) + await task.queue_frame(TTSUpdateSettingsFrame(delta=SarvamTTSService.Settings(pace=1.5))) @transport.event_handler("on_client_disconnected") async def on_client_disconnected(transport, client): diff --git a/examples/foundational/55zf-update-settings-camb-tts.py b/examples/foundational/55zf-update-settings-camb-tts.py index 5c9987dc9..5f0840857 100644 --- a/examples/foundational/55zf-update-settings-camb-tts.py +++ b/examples/foundational/55zf-update-settings-camb-tts.py @@ -22,9 +22,9 @@ from pipecat.processors.aggregators.llm_response_universal import ( ) from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport -from pipecat.services.camb.tts import CambTTSService, CambTTSSettings +from pipecat.services.camb.tts import CambTTSService from pipecat.services.deepgram.stt import DeepgramSTTService -from pipecat.services.openai.llm import OpenAILLMService, OpenAILLMSettings +from pipecat.services.openai.llm import OpenAILLMService from pipecat.transcriptions.language import Language from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams @@ -57,7 +57,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): llm = OpenAILLMService( api_key=os.getenv("OPENAI_API_KEY"), - settings=OpenAILLMSettings( + settings=OpenAILLMService.Settings( system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", ), ) @@ -97,7 +97,9 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): await asyncio.sleep(10) logger.info("Updating Camb TTS settings: language -> Spanish") - await task.queue_frame(TTSUpdateSettingsFrame(delta=CambTTSSettings(language=Language.ES))) + await task.queue_frame( + TTSUpdateSettingsFrame(delta=CambTTSService.Settings(language=Language.ES)) + ) @transport.event_handler("on_client_disconnected") async def on_client_disconnected(transport, client): diff --git a/examples/foundational/55zh-update-settings-resembleai-tts.py b/examples/foundational/55zh-update-settings-resembleai-tts.py index 192e5d868..befa0ce65 100644 --- a/examples/foundational/55zh-update-settings-resembleai-tts.py +++ b/examples/foundational/55zh-update-settings-resembleai-tts.py @@ -23,8 +23,8 @@ from pipecat.processors.aggregators.llm_response_universal import ( from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport from pipecat.services.deepgram.stt import DeepgramSTTService -from pipecat.services.openai.llm import OpenAILLMService, OpenAILLMSettings -from pipecat.services.resembleai.tts import ResembleAITTSService, ResembleAITTSSettings +from pipecat.services.openai.llm import OpenAILLMService +from pipecat.services.resembleai.tts import ResembleAITTSService from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams @@ -54,12 +54,12 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): tts = ResembleAITTSService( api_key=os.getenv("RESEMBLE_API_KEY"), - settings=ResembleAITTSSettings(voice=os.getenv("RESEMBLE_VOICE_UUID")), + settings=ResembleAITTSService.Settings(voice=os.getenv("RESEMBLE_VOICE_UUID")), ) llm = OpenAILLMService( api_key=os.getenv("OPENAI_API_KEY"), - settings=OpenAILLMSettings( + settings=OpenAILLMService.Settings( system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", ), ) @@ -101,7 +101,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): logger.info("Updating ResembleAI TTS settings: voice (changed)") await task.queue_frame( TTSUpdateSettingsFrame( - delta=ResembleAITTSSettings(voice=os.getenv("RESEMBLE_VOICE_UUID_ALT")) + delta=ResembleAITTSService.Settings(voice=os.getenv("RESEMBLE_VOICE_UUID_ALT")) ) ) diff --git a/examples/foundational/55zi-update-settings-azure-llm.py b/examples/foundational/55zi-update-settings-azure-llm.py index 21f65eabb..5fbd796ca 100644 --- a/examples/foundational/55zi-update-settings-azure-llm.py +++ b/examples/foundational/55zi-update-settings-azure-llm.py @@ -22,10 +22,9 @@ from pipecat.processors.aggregators.llm_response_universal import ( ) from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport -from pipecat.services.azure.llm import AzureLLMService, AzureLLMSettings -from pipecat.services.cartesia.tts import CartesiaTTSService, CartesiaTTSSettings +from pipecat.services.azure.llm import AzureLLMService +from pipecat.services.cartesia.tts import CartesiaTTSService from pipecat.services.deepgram.stt import DeepgramSTTService -from pipecat.services.openai.base_llm import OpenAILLMSettings from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams @@ -55,7 +54,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): tts = CartesiaTTSService( api_key=os.getenv("CARTESIA_API_KEY"), - settings=CartesiaTTSSettings( + settings=CartesiaTTSService.Settings( voice="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady ), ) @@ -63,7 +62,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): llm = AzureLLMService( api_key=os.getenv("AZURE_CHATGPT_API_KEY"), endpoint=os.getenv("AZURE_CHATGPT_ENDPOINT"), - settings=AzureLLMSettings( + settings=AzureLLMService.Settings( model=os.getenv("AZURE_CHATGPT_MODEL"), system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", ), @@ -104,7 +103,9 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): await asyncio.sleep(10) logger.info("Updating Azure LLM settings: temperature=0.1") - await task.queue_frame(LLMUpdateSettingsFrame(delta=OpenAILLMSettings(temperature=0.1))) + await task.queue_frame( + LLMUpdateSettingsFrame(delta=AzureLLMService.Settings(temperature=0.1)) + ) @transport.event_handler("on_client_disconnected") async def on_client_disconnected(transport, client): diff --git a/examples/foundational/55zi-update-settings-openai-llm.py b/examples/foundational/55zi-update-settings-openai-llm.py index 1eddc6bb4..76a14a3f0 100644 --- a/examples/foundational/55zi-update-settings-openai-llm.py +++ b/examples/foundational/55zi-update-settings-openai-llm.py @@ -22,9 +22,8 @@ from pipecat.processors.aggregators.llm_response_universal import ( ) from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport -from pipecat.services.cartesia.tts import CartesiaTTSService, CartesiaTTSSettings +from pipecat.services.cartesia.tts import CartesiaTTSService from pipecat.services.deepgram.stt import DeepgramSTTService -from pipecat.services.openai.base_llm import OpenAILLMSettings from pipecat.services.openai.llm import OpenAILLMService from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams @@ -55,14 +54,14 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): tts = CartesiaTTSService( api_key=os.getenv("CARTESIA_API_KEY"), - settings=CartesiaTTSSettings( + settings=CartesiaTTSService.Settings( voice="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady ), ) llm = OpenAILLMService( api_key=os.getenv("OPENAI_API_KEY"), - settings=OpenAILLMSettings( + settings=OpenAILLMService.Settings( system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", ), ) @@ -102,7 +101,9 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): await asyncio.sleep(10) logger.info("Updating OpenAI LLM settings: temperature=0.1") - await task.queue_frame(LLMUpdateSettingsFrame(delta=OpenAILLMSettings(temperature=0.1))) + await task.queue_frame( + LLMUpdateSettingsFrame(delta=OpenAILLMService.Settings(temperature=0.1)) + ) @transport.event_handler("on_client_disconnected") async def on_client_disconnected(transport, client): diff --git a/examples/foundational/55zj-update-settings-anthropic-llm.py b/examples/foundational/55zj-update-settings-anthropic-llm.py index c36ee758d..ba729bf4c 100644 --- a/examples/foundational/55zj-update-settings-anthropic-llm.py +++ b/examples/foundational/55zj-update-settings-anthropic-llm.py @@ -22,8 +22,8 @@ from pipecat.processors.aggregators.llm_response_universal import ( ) from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport -from pipecat.services.anthropic.llm import AnthropicLLMService, AnthropicLLMSettings -from pipecat.services.cartesia.tts import CartesiaTTSService, CartesiaTTSSettings +from pipecat.services.anthropic.llm import AnthropicLLMService +from pipecat.services.cartesia.tts import CartesiaTTSService from pipecat.services.deepgram.stt import DeepgramSTTService from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams @@ -54,14 +54,14 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): tts = CartesiaTTSService( api_key=os.getenv("CARTESIA_API_KEY"), - settings=CartesiaTTSSettings( + settings=CartesiaTTSService.Settings( voice="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady ), ) llm = AnthropicLLMService( api_key=os.getenv("ANTHROPIC_API_KEY"), - settings=AnthropicLLMSettings( + settings=AnthropicLLMService.Settings( system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", ), ) @@ -101,7 +101,9 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): await asyncio.sleep(10) logger.info("Updating Anthropic LLM settings: temperature=0.1") - await task.queue_frame(LLMUpdateSettingsFrame(delta=AnthropicLLMSettings(temperature=0.1))) + await task.queue_frame( + LLMUpdateSettingsFrame(delta=AnthropicLLMService.Settings(temperature=0.1)) + ) @transport.event_handler("on_client_disconnected") async def on_client_disconnected(transport, client): diff --git a/examples/foundational/55zk-update-settings-google-llm.py b/examples/foundational/55zk-update-settings-google-llm.py index 0eaa89d10..dc3e5917a 100644 --- a/examples/foundational/55zk-update-settings-google-llm.py +++ b/examples/foundational/55zk-update-settings-google-llm.py @@ -22,9 +22,9 @@ from pipecat.processors.aggregators.llm_response_universal import ( ) from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport -from pipecat.services.cartesia.tts import CartesiaTTSService, CartesiaTTSSettings +from pipecat.services.cartesia.tts import CartesiaTTSService from pipecat.services.deepgram.stt import DeepgramSTTService -from pipecat.services.google.llm import GoogleLLMService, GoogleLLMSettings +from pipecat.services.google.llm import GoogleLLMService from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams @@ -54,14 +54,14 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): tts = CartesiaTTSService( api_key=os.getenv("CARTESIA_API_KEY"), - settings=CartesiaTTSSettings( + settings=CartesiaTTSService.Settings( voice="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady ), ) llm = GoogleLLMService( api_key=os.getenv("GOOGLE_API_KEY"), - settings=GoogleLLMSettings( + settings=GoogleLLMService.Settings( system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", ), ) @@ -101,7 +101,9 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): await asyncio.sleep(10) logger.info("Updating Google LLM settings: temperature=0.1") - await task.queue_frame(LLMUpdateSettingsFrame(delta=GoogleLLMSettings(temperature=0.1))) + await task.queue_frame( + LLMUpdateSettingsFrame(delta=GoogleLLMService.Settings(temperature=0.1)) + ) @transport.event_handler("on_client_disconnected") async def on_client_disconnected(transport, client): diff --git a/examples/foundational/55zk-update-settings-google-vertex-llm.py b/examples/foundational/55zk-update-settings-google-vertex-llm.py index 95e84fec5..16cec654f 100644 --- a/examples/foundational/55zk-update-settings-google-vertex-llm.py +++ b/examples/foundational/55zk-update-settings-google-vertex-llm.py @@ -22,10 +22,10 @@ from pipecat.processors.aggregators.llm_response_universal import ( ) from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport -from pipecat.services.cartesia.tts import CartesiaTTSService, CartesiaTTSSettings +from pipecat.services.cartesia.tts import CartesiaTTSService from pipecat.services.deepgram.stt import DeepgramSTTService from pipecat.services.google.llm import GoogleLLMSettings -from pipecat.services.google.llm_vertex import GoogleVertexLLMService, GoogleVertexLLMSettings +from pipecat.services.google.llm_vertex import GoogleVertexLLMService from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams @@ -55,7 +55,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): tts = CartesiaTTSService( api_key=os.getenv("CARTESIA_API_KEY"), - settings=CartesiaTTSSettings( + settings=CartesiaTTSService.Settings( voice="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady ), ) @@ -64,7 +64,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): credentials=os.getenv("GOOGLE_VERTEX_TEST_CREDENTIALS"), project_id=os.getenv("GOOGLE_CLOUD_PROJECT_ID"), location=os.getenv("GOOGLE_CLOUD_LOCATION"), - settings=GoogleVertexLLMSettings( + settings=GoogleVertexLLMService.Settings( system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", ), ) @@ -104,7 +104,9 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): await asyncio.sleep(10) logger.info("Updating Google Vertex LLM settings: temperature=0.1") - await task.queue_frame(LLMUpdateSettingsFrame(delta=GoogleLLMSettings(temperature=0.1))) + await task.queue_frame( + LLMUpdateSettingsFrame(delta=GoogleVertexLLMService.Settings(temperature=0.1)) + ) @transport.event_handler("on_client_disconnected") async def on_client_disconnected(transport, client): diff --git a/examples/foundational/55zl-update-settings-azure-realtime.py b/examples/foundational/55zl-update-settings-azure-realtime.py index 247bde14b..fcfcdcfdd 100644 --- a/examples/foundational/55zl-update-settings-azure-realtime.py +++ b/examples/foundational/55zl-update-settings-azure-realtime.py @@ -24,7 +24,6 @@ from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport from pipecat.services.azure.realtime.llm import AzureRealtimeLLMService from pipecat.services.openai.realtime import events -from pipecat.services.openai.realtime.llm import OpenAIRealtimeLLMSettings from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams @@ -102,7 +101,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): logger.info("Updating Azure Realtime LLM settings: output_modalities=['text']") await task.queue_frame( LLMUpdateSettingsFrame( - delta=OpenAIRealtimeLLMSettings( + delta=AzureRealtimeLLMService.Settings( session_properties=events.SessionProperties(output_modalities=["text"]) ) ) @@ -112,7 +111,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): logger.info("Updating Azure Realtime LLM settings: output_modalities=['audio']") await task.queue_frame( LLMUpdateSettingsFrame( - delta=OpenAIRealtimeLLMSettings( + delta=AzureRealtimeLLMService.Settings( session_properties=events.SessionProperties(output_modalities=["audio"]) ) ) diff --git a/examples/foundational/55zl-update-settings-openai-realtime.py b/examples/foundational/55zl-update-settings-openai-realtime.py index f5c4afa26..372b1f1e6 100644 --- a/examples/foundational/55zl-update-settings-openai-realtime.py +++ b/examples/foundational/55zl-update-settings-openai-realtime.py @@ -23,10 +23,7 @@ from pipecat.processors.aggregators.llm_response_universal import ( from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport from pipecat.services.openai.realtime import events -from pipecat.services.openai.realtime.llm import ( - OpenAIRealtimeLLMService, - OpenAIRealtimeLLMSettings, -) +from pipecat.services.openai.realtime.llm import OpenAIRealtimeLLMService from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams @@ -101,7 +98,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): logger.info("Updating OpenAI Realtime LLM settings: output_modalities=['text']") await task.queue_frame( LLMUpdateSettingsFrame( - delta=OpenAIRealtimeLLMSettings( + delta=OpenAIRealtimeLLMService.Settings( session_properties=events.SessionProperties(output_modalities=["text"]) ) ) @@ -111,7 +108,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): logger.info("Updating OpenAI Realtime LLM settings: output_modalities=['audio']") await task.queue_frame( LLMUpdateSettingsFrame( - delta=OpenAIRealtimeLLMSettings( + delta=OpenAIRealtimeLLMService.Settings( session_properties=events.SessionProperties(output_modalities=["audio"]) ) ) diff --git a/examples/foundational/55zm-update-settings-gemini-live-vertex.py b/examples/foundational/55zm-update-settings-gemini-live-vertex.py index 715834f71..f69b94557 100644 --- a/examples/foundational/55zm-update-settings-gemini-live-vertex.py +++ b/examples/foundational/55zm-update-settings-gemini-live-vertex.py @@ -19,7 +19,6 @@ from pipecat.processors.aggregators.llm_context import LLMContext from pipecat.processors.aggregators.llm_response_universal import LLMContextAggregatorPair from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport -from pipecat.services.google.gemini_live.llm import GeminiLiveLLMSettings from pipecat.services.google.gemini_live.llm_vertex import GeminiLiveVertexLLMService from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams @@ -53,7 +52,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): credentials=os.getenv("GOOGLE_VERTEX_TEST_CREDENTIALS"), project_id=os.getenv("GOOGLE_CLOUD_PROJECT_ID"), location=os.getenv("GOOGLE_CLOUD_LOCATION"), - settings=GeminiLiveLLMSettings( + settings=GeminiLiveVertexLLMService.Settings( system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", ), ) @@ -88,7 +87,9 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): await asyncio.sleep(10) logger.info("Updating Gemini Live Vertex LLM settings: temperature=0.1") - await task.queue_frame(LLMUpdateSettingsFrame(delta=GeminiLiveLLMSettings(temperature=0.1))) + await task.queue_frame( + LLMUpdateSettingsFrame(delta=GeminiLiveVertexLLMService.Settings(temperature=0.1)) + ) @transport.event_handler("on_client_disconnected") async def on_client_disconnected(transport, client): diff --git a/examples/foundational/55zm-update-settings-gemini-live.py b/examples/foundational/55zm-update-settings-gemini-live.py index 172daae7c..0b88c45da 100644 --- a/examples/foundational/55zm-update-settings-gemini-live.py +++ b/examples/foundational/55zm-update-settings-gemini-live.py @@ -19,7 +19,7 @@ from pipecat.processors.aggregators.llm_context import LLMContext from pipecat.processors.aggregators.llm_response_universal import LLMContextAggregatorPair from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport -from pipecat.services.google.gemini_live.llm import GeminiLiveLLMService, GeminiLiveLLMSettings +from pipecat.services.google.gemini_live.llm import GeminiLiveLLMService from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams @@ -50,7 +50,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): llm = GeminiLiveLLMService( api_key=os.getenv("GOOGLE_API_KEY"), - settings=GeminiLiveLLMSettings( + settings=GeminiLiveLLMService.Settings( system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", ), ) @@ -85,7 +85,9 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): await asyncio.sleep(10) logger.info("Updating Gemini Live LLM settings: temperature=0.1") - await task.queue_frame(LLMUpdateSettingsFrame(delta=GeminiLiveLLMSettings(temperature=0.1))) + await task.queue_frame( + LLMUpdateSettingsFrame(delta=GeminiLiveLLMService.Settings(temperature=0.1)) + ) @transport.event_handler("on_client_disconnected") async def on_client_disconnected(transport, client): diff --git a/examples/foundational/55zn-update-settings-ultravox-realtime.py b/examples/foundational/55zn-update-settings-ultravox-realtime.py index 5bcbded6b..13ce6c1ae 100644 --- a/examples/foundational/55zn-update-settings-ultravox-realtime.py +++ b/examples/foundational/55zn-update-settings-ultravox-realtime.py @@ -24,11 +24,7 @@ from pipecat.processors.aggregators.llm_response_universal import ( ) from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport -from pipecat.services.ultravox.llm import ( - OneShotInputParams, - UltravoxRealtimeLLMService, - UltravoxRealtimeLLMSettings, -) +from pipecat.services.ultravox.llm import OneShotInputParams, UltravoxRealtimeLLMService from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams @@ -112,13 +108,13 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): await asyncio.sleep(10) logger.info("Updating Ultravox Realtime LLM settings: output_medium=text") await task.queue_frame( - LLMUpdateSettingsFrame(delta=UltravoxRealtimeLLMSettings(output_medium="text")) + LLMUpdateSettingsFrame(delta=UltravoxRealtimeLLMService.Settings(output_medium="text")) ) await asyncio.sleep(10) logger.info("Updating Ultravox Realtime LLM settings: output_medium=voice") await task.queue_frame( - LLMUpdateSettingsFrame(delta=UltravoxRealtimeLLMSettings(output_medium="voice")) + LLMUpdateSettingsFrame(delta=UltravoxRealtimeLLMService.Settings(output_medium="voice")) ) @transport.event_handler("on_client_disconnected") diff --git a/examples/foundational/55zo-update-settings-grok-realtime.py b/examples/foundational/55zo-update-settings-grok-realtime.py index 9444f126a..5ac425de4 100644 --- a/examples/foundational/55zo-update-settings-grok-realtime.py +++ b/examples/foundational/55zo-update-settings-grok-realtime.py @@ -23,10 +23,7 @@ from pipecat.processors.aggregators.llm_response_universal import ( from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport from pipecat.services.grok.realtime import events -from pipecat.services.grok.realtime.llm import ( - GrokRealtimeLLMService, - GrokRealtimeLLMSettings, -) +from pipecat.services.grok.realtime.llm import GrokRealtimeLLMService from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams @@ -101,7 +98,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): logger.info("Updating Grok Realtime LLM settings: voice='Rex'") await task.queue_frame( LLMUpdateSettingsFrame( - delta=GrokRealtimeLLMSettings( + delta=GrokRealtimeLLMService.Settings( session_properties=events.SessionProperties(voice="Rex") ) ) diff --git a/examples/foundational/55zp-update-settings-aws-bedrock-llm.py b/examples/foundational/55zp-update-settings-aws-bedrock-llm.py index 06a131814..2452ceada 100644 --- a/examples/foundational/55zp-update-settings-aws-bedrock-llm.py +++ b/examples/foundational/55zp-update-settings-aws-bedrock-llm.py @@ -22,8 +22,8 @@ from pipecat.processors.aggregators.llm_response_universal import ( ) from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport -from pipecat.services.aws.llm import AWSBedrockLLMService, AWSBedrockLLMSettings -from pipecat.services.cartesia.tts import CartesiaTTSService, CartesiaTTSSettings +from pipecat.services.aws.llm import AWSBedrockLLMService +from pipecat.services.cartesia.tts import CartesiaTTSService from pipecat.services.deepgram.stt import DeepgramSTTService from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams @@ -54,14 +54,14 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): tts = CartesiaTTSService( api_key=os.getenv("CARTESIA_API_KEY"), - settings=CartesiaTTSSettings( + settings=CartesiaTTSService.Settings( voice="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady ), ) llm = AWSBedrockLLMService( aws_region="us-west-2", - settings=AWSBedrockLLMSettings( + settings=AWSBedrockLLMService.Settings( model="us.anthropic.claude-sonnet-4-6", temperature=0.8, system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", @@ -103,7 +103,9 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): await asyncio.sleep(10) logger.info("Updating AWS Bedrock LLM settings: temperature=0.1") - await task.queue_frame(LLMUpdateSettingsFrame(delta=AWSBedrockLLMSettings(temperature=0.1))) + await task.queue_frame( + LLMUpdateSettingsFrame(delta=AWSBedrockLLMService.Settings(temperature=0.1)) + ) @transport.event_handler("on_client_disconnected") async def on_client_disconnected(transport, client): diff --git a/examples/foundational/55zq-update-settings-fal-stt.py b/examples/foundational/55zq-update-settings-fal-stt.py index 910b4d348..77d9bfd85 100644 --- a/examples/foundational/55zq-update-settings-fal-stt.py +++ b/examples/foundational/55zq-update-settings-fal-stt.py @@ -22,9 +22,9 @@ from pipecat.processors.aggregators.llm_response_universal import ( ) from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport -from pipecat.services.cartesia.tts import CartesiaTTSService, CartesiaTTSSettings -from pipecat.services.fal.stt import FalSTTService, FalSTTSettings -from pipecat.services.openai.llm import OpenAILLMService, OpenAILLMSettings +from pipecat.services.cartesia.tts import CartesiaTTSService +from pipecat.services.fal.stt import FalSTTService +from pipecat.services.openai.llm import OpenAILLMService from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams @@ -54,14 +54,14 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): tts = CartesiaTTSService( api_key=os.getenv("CARTESIA_API_KEY"), - settings=CartesiaTTSSettings( + settings=CartesiaTTSService.Settings( voice="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady ), ) llm = OpenAILLMService( api_key=os.getenv("OPENAI_API_KEY"), - settings=OpenAILLMSettings( + settings=OpenAILLMService.Settings( system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", ), ) @@ -101,7 +101,9 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): await asyncio.sleep(10) logger.info('Updating Fal STT settings: task="translate"') - await task.queue_frame(STTUpdateSettingsFrame(delta=FalSTTSettings(task="translate"))) + await task.queue_frame( + STTUpdateSettingsFrame(delta=FalSTTService.Settings(task="translate")) + ) @transport.event_handler("on_client_disconnected") async def on_client_disconnected(transport, client): diff --git a/examples/foundational/55zr-update-settings-gradium-stt.py b/examples/foundational/55zr-update-settings-gradium-stt.py index 9e76d3bec..e621cc89b 100644 --- a/examples/foundational/55zr-update-settings-gradium-stt.py +++ b/examples/foundational/55zr-update-settings-gradium-stt.py @@ -22,9 +22,9 @@ from pipecat.processors.aggregators.llm_response_universal import ( ) from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport -from pipecat.services.cartesia.tts import CartesiaTTSService, CartesiaTTSSettings -from pipecat.services.gradium.stt import GradiumSTTService, GradiumSTTSettings -from pipecat.services.openai.llm import OpenAILLMService, OpenAILLMSettings +from pipecat.services.cartesia.tts import CartesiaTTSService +from pipecat.services.gradium.stt import GradiumSTTService +from pipecat.services.openai.llm import OpenAILLMService from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams @@ -57,14 +57,14 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): tts = CartesiaTTSService( api_key=os.getenv("CARTESIA_API_KEY"), - settings=CartesiaTTSSettings( + settings=CartesiaTTSService.Settings( voice="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady ), ) llm = OpenAILLMService( api_key=os.getenv("OPENAI_API_KEY"), - settings=OpenAILLMSettings( + settings=OpenAILLMService.Settings( system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", ), ) @@ -104,7 +104,9 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): await asyncio.sleep(10) logger.info("Updating Gradium STT settings: delay_in_frames=5") - await task.queue_frame(STTUpdateSettingsFrame(delta=GradiumSTTSettings(delay_in_frames=16))) + await task.queue_frame( + STTUpdateSettingsFrame(delta=GradiumSTTService.Settings(delay_in_frames=16)) + ) @transport.event_handler("on_client_disconnected") async def on_client_disconnected(transport, client): diff --git a/examples/foundational/55zt-update-settings-nvidia-segmented-stt.py b/examples/foundational/55zt-update-settings-nvidia-segmented-stt.py index abec5cb7a..62d10d455 100644 --- a/examples/foundational/55zt-update-settings-nvidia-segmented-stt.py +++ b/examples/foundational/55zt-update-settings-nvidia-segmented-stt.py @@ -22,9 +22,9 @@ from pipecat.processors.aggregators.llm_response_universal import ( ) from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport -from pipecat.services.cartesia.tts import CartesiaTTSService, CartesiaTTSSettings -from pipecat.services.nvidia.stt import NvidiaSegmentedSTTService, NvidiaSegmentedSTTSettings -from pipecat.services.openai.llm import OpenAILLMService, OpenAILLMSettings +from pipecat.services.cartesia.tts import CartesiaTTSService +from pipecat.services.nvidia.stt import NvidiaSegmentedSTTService +from pipecat.services.openai.llm import OpenAILLMService from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams @@ -54,14 +54,14 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): tts = CartesiaTTSService( api_key=os.getenv("CARTESIA_API_KEY"), - settings=CartesiaTTSSettings( + settings=CartesiaTTSService.Settings( voice="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady ), ) llm = OpenAILLMService( api_key=os.getenv("OPENAI_API_KEY"), - settings=OpenAILLMSettings( + settings=OpenAILLMService.Settings( system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", ), ) @@ -102,7 +102,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): await asyncio.sleep(10) logger.info("Updating NVIDIA Segmented STT settings: profanity_filter=True") await task.queue_frame( - STTUpdateSettingsFrame(delta=NvidiaSegmentedSTTSettings(profanity_filter=True)) + STTUpdateSettingsFrame(delta=NvidiaSegmentedSTTService.Settings(profanity_filter=True)) ) @transport.event_handler("on_client_disconnected") diff --git a/examples/foundational/55zt-update-settings-nvidia-stt.py b/examples/foundational/55zt-update-settings-nvidia-stt.py index 116035aa2..612f12acf 100644 --- a/examples/foundational/55zt-update-settings-nvidia-stt.py +++ b/examples/foundational/55zt-update-settings-nvidia-stt.py @@ -22,9 +22,9 @@ from pipecat.processors.aggregators.llm_response_universal import ( ) from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport -from pipecat.services.cartesia.tts import CartesiaTTSService, CartesiaTTSSettings -from pipecat.services.nvidia.stt import NvidiaSTTService, NvidiaSTTSettings -from pipecat.services.openai.llm import OpenAILLMService, OpenAILLMSettings +from pipecat.services.cartesia.tts import CartesiaTTSService +from pipecat.services.nvidia.stt import NvidiaSTTService +from pipecat.services.openai.llm import OpenAILLMService from pipecat.transcriptions.language import Language from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams @@ -55,14 +55,14 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): tts = CartesiaTTSService( api_key=os.getenv("CARTESIA_API_KEY"), - settings=CartesiaTTSSettings( + settings=CartesiaTTSService.Settings( voice="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady ), ) llm = OpenAILLMService( api_key=os.getenv("OPENAI_API_KEY"), - settings=OpenAILLMSettings( + settings=OpenAILLMService.Settings( system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", ), ) @@ -103,7 +103,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): await asyncio.sleep(10) logger.info("Updating NVIDIA STT settings: language=es") await task.queue_frame( - STTUpdateSettingsFrame(delta=NvidiaSTTSettings(language=Language.ES)) + STTUpdateSettingsFrame(delta=NvidiaSTTService.Settings(language=Language.ES)) ) @transport.event_handler("on_client_disconnected") diff --git a/examples/foundational/55zu-update-settings-openai-realtime-stt.py b/examples/foundational/55zu-update-settings-openai-realtime-stt.py index 846775cd4..62cf902ed 100644 --- a/examples/foundational/55zu-update-settings-openai-realtime-stt.py +++ b/examples/foundational/55zu-update-settings-openai-realtime-stt.py @@ -22,9 +22,9 @@ from pipecat.processors.aggregators.llm_response_universal import ( ) from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport -from pipecat.services.cartesia.tts import CartesiaTTSService, CartesiaTTSSettings -from pipecat.services.openai.llm import OpenAILLMService, OpenAILLMSettings -from pipecat.services.openai.stt import OpenAIRealtimeSTTService, OpenAIRealtimeSTTSettings +from pipecat.services.cartesia.tts import CartesiaTTSService +from pipecat.services.openai.llm import OpenAILLMService +from pipecat.services.openai.stt import OpenAIRealtimeSTTService from pipecat.transcriptions.language import Language from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams @@ -55,14 +55,14 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): tts = CartesiaTTSService( api_key=os.getenv("CARTESIA_API_KEY"), - settings=CartesiaTTSSettings( + settings=CartesiaTTSService.Settings( voice="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady ), ) llm = OpenAILLMService( api_key=os.getenv("OPENAI_API_KEY"), - settings=OpenAILLMSettings( + settings=OpenAILLMService.Settings( system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", ), ) @@ -103,7 +103,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): await asyncio.sleep(10) logger.info("Updating OpenAI Realtime STT settings: language=es") await task.queue_frame( - STTUpdateSettingsFrame(delta=OpenAIRealtimeSTTSettings(language=Language.ES)) + STTUpdateSettingsFrame(delta=OpenAIRealtimeSTTService.Settings(language=Language.ES)) ) @transport.event_handler("on_client_disconnected") diff --git a/examples/foundational/55zv-update-settings-asyncai-http-tts.py b/examples/foundational/55zv-update-settings-asyncai-http-tts.py index cea5ab72f..639a28d7f 100644 --- a/examples/foundational/55zv-update-settings-asyncai-http-tts.py +++ b/examples/foundational/55zv-update-settings-asyncai-http-tts.py @@ -24,9 +24,9 @@ from pipecat.processors.aggregators.llm_response_universal import ( ) from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport -from pipecat.services.asyncai.tts import AsyncAIHttpTTSService, AsyncAITTSSettings +from pipecat.services.asyncai.tts import AsyncAIHttpTTSService from pipecat.services.deepgram.stt import DeepgramSTTService -from pipecat.services.openai.llm import OpenAILLMService, OpenAILLMSettings +from pipecat.services.openai.llm import OpenAILLMService from pipecat.transcriptions.language import Language from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams @@ -59,7 +59,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): tts = AsyncAIHttpTTSService( api_key=os.getenv("ASYNCAI_API_KEY", ""), - settings=AsyncAITTSSettings( + settings=AsyncAIHttpTTSService.Settings( voice=os.getenv("ASYNCAI_VOICE_ID", "e0f39dc4-f691-4e78-bba5-5c636692cc04") ), aiohttp_session=session, @@ -67,7 +67,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): llm = OpenAILLMService( api_key=os.getenv("OPENAI_API_KEY"), - settings=OpenAILLMSettings( + settings=OpenAILLMService.Settings( system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", ), ) @@ -110,7 +110,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): await asyncio.sleep(10) logger.info("Updating AsyncAI HTTP TTS settings: language=es") await task.queue_frame( - TTSUpdateSettingsFrame(delta=AsyncAITTSSettings(language=Language.ES)) + TTSUpdateSettingsFrame(delta=AsyncAIHttpTTSService.Settings(language=Language.ES)) ) @transport.event_handler("on_client_disconnected") diff --git a/examples/foundational/55zv-update-settings-asyncai-tts.py b/examples/foundational/55zv-update-settings-asyncai-tts.py index 947b5c852..cac3fde19 100644 --- a/examples/foundational/55zv-update-settings-asyncai-tts.py +++ b/examples/foundational/55zv-update-settings-asyncai-tts.py @@ -22,9 +22,9 @@ from pipecat.processors.aggregators.llm_response_universal import ( ) from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport -from pipecat.services.asyncai.tts import AsyncAITTSService, AsyncAITTSSettings +from pipecat.services.asyncai.tts import AsyncAITTSService from pipecat.services.deepgram.stt import DeepgramSTTService -from pipecat.services.openai.llm import OpenAILLMService, OpenAILLMSettings +from pipecat.services.openai.llm import OpenAILLMService from pipecat.transcriptions.language import Language from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams @@ -55,14 +55,14 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): tts = AsyncAITTSService( api_key=os.getenv("ASYNCAI_API_KEY", ""), - settings=AsyncAITTSSettings( + settings=AsyncAITTSService.Settings( voice=os.getenv("ASYNCAI_VOICE_ID", "e0f39dc4-f691-4e78-bba5-5c636692cc04") ), ) llm = OpenAILLMService( api_key=os.getenv("OPENAI_API_KEY"), - settings=OpenAILLMSettings( + settings=OpenAILLMService.Settings( system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", ), ) @@ -103,7 +103,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): await asyncio.sleep(10) logger.info("Updating AsyncAI TTS settings: language=es") await task.queue_frame( - TTSUpdateSettingsFrame(delta=AsyncAITTSSettings(language=Language.ES)) + TTSUpdateSettingsFrame(delta=AsyncAITTSService.Settings(language=Language.ES)) ) @transport.event_handler("on_client_disconnected") diff --git a/examples/foundational/55zw-update-settings-gradium-tts.py b/examples/foundational/55zw-update-settings-gradium-tts.py index f81267d1c..d2b3535c4 100644 --- a/examples/foundational/55zw-update-settings-gradium-tts.py +++ b/examples/foundational/55zw-update-settings-gradium-tts.py @@ -23,8 +23,8 @@ from pipecat.processors.aggregators.llm_response_universal import ( from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport from pipecat.services.deepgram.stt import DeepgramSTTService -from pipecat.services.gradium.tts import GradiumTTSService, GradiumTTSSettings -from pipecat.services.openai.llm import OpenAILLMService, OpenAILLMSettings +from pipecat.services.gradium.tts import GradiumTTSService +from pipecat.services.openai.llm import OpenAILLMService from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams @@ -54,13 +54,13 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): tts = GradiumTTSService( api_key=os.getenv("GRADIUM_API_KEY"), - settings=GradiumTTSSettings(voice="YTpq7expH9539ERJ"), + settings=GradiumTTSService.Settings(voice="YTpq7expH9539ERJ"), url="wss://us.api.gradium.ai/api/speech/tts", ) llm = OpenAILLMService( api_key=os.getenv("OPENAI_API_KEY"), - settings=OpenAILLMSettings( + settings=OpenAILLMService.Settings( system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", ), ) @@ -101,7 +101,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): await asyncio.sleep(10) logger.info('Updating Gradium TTS settings: voice="LFZvm12tW_z0xfGo"') await task.queue_frame( - TTSUpdateSettingsFrame(delta=GradiumTTSSettings(voice="LFZvm12tW_z0xfGo")) + TTSUpdateSettingsFrame(delta=GradiumTTSService.Settings(voice="LFZvm12tW_z0xfGo")) ) @transport.event_handler("on_client_disconnected") diff --git a/examples/foundational/55zx-update-settings-cerebras-llm.py b/examples/foundational/55zx-update-settings-cerebras-llm.py index 3a9bf5510..2d8e5a3d9 100644 --- a/examples/foundational/55zx-update-settings-cerebras-llm.py +++ b/examples/foundational/55zx-update-settings-cerebras-llm.py @@ -22,10 +22,9 @@ from pipecat.processors.aggregators.llm_response_universal import ( ) from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport -from pipecat.services.cartesia.tts import CartesiaTTSService, CartesiaTTSSettings -from pipecat.services.cerebras.llm import CerebrasLLMService, CerebrasLLMSettings +from pipecat.services.cartesia.tts import CartesiaTTSService +from pipecat.services.cerebras.llm import CerebrasLLMService from pipecat.services.deepgram.stt import DeepgramSTTService -from pipecat.services.openai.base_llm import OpenAILLMSettings from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams @@ -55,14 +54,14 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): tts = CartesiaTTSService( api_key=os.getenv("CARTESIA_API_KEY"), - settings=CartesiaTTSSettings( + settings=CartesiaTTSService.Settings( voice="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady ), ) llm = CerebrasLLMService( api_key=os.getenv("CEREBRAS_API_KEY"), - settings=CerebrasLLMSettings( + settings=CerebrasLLMService.Settings( system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", ), ) @@ -102,7 +101,9 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): await asyncio.sleep(10) logger.info("Updating Cerebras LLM settings: temperature=0.1") - await task.queue_frame(LLMUpdateSettingsFrame(delta=OpenAILLMSettings(temperature=0.1))) + await task.queue_frame( + LLMUpdateSettingsFrame(delta=CerebrasLLMService.Settings(temperature=0.1)) + ) @transport.event_handler("on_client_disconnected") async def on_client_disconnected(transport, client): diff --git a/examples/foundational/55zy-update-settings-deepseek-llm.py b/examples/foundational/55zy-update-settings-deepseek-llm.py index 3a2dd38a8..2a439f76d 100644 --- a/examples/foundational/55zy-update-settings-deepseek-llm.py +++ b/examples/foundational/55zy-update-settings-deepseek-llm.py @@ -22,10 +22,9 @@ from pipecat.processors.aggregators.llm_response_universal import ( ) from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport -from pipecat.services.cartesia.tts import CartesiaTTSService, CartesiaTTSSettings +from pipecat.services.cartesia.tts import CartesiaTTSService from pipecat.services.deepgram.stt import DeepgramSTTService -from pipecat.services.deepseek.llm import DeepSeekLLMService, DeepSeekLLMSettings -from pipecat.services.openai.base_llm import OpenAILLMSettings +from pipecat.services.deepseek.llm import DeepSeekLLMService from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams @@ -55,14 +54,14 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): tts = CartesiaTTSService( api_key=os.getenv("CARTESIA_API_KEY"), - settings=CartesiaTTSSettings( + settings=CartesiaTTSService.Settings( voice="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady ), ) llm = DeepSeekLLMService( api_key=os.getenv("DEEPSEEK_API_KEY"), - settings=DeepSeekLLMSettings( + settings=DeepSeekLLMService.Settings( system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", ), ) @@ -102,7 +101,9 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): await asyncio.sleep(10) logger.info("Updating DeepSeek LLM settings: temperature=0.1") - await task.queue_frame(LLMUpdateSettingsFrame(delta=OpenAILLMSettings(temperature=0.1))) + await task.queue_frame( + LLMUpdateSettingsFrame(delta=DeepSeekLLMService.Settings(temperature=0.1)) + ) @transport.event_handler("on_client_disconnected") async def on_client_disconnected(transport, client): diff --git a/examples/foundational/55zz-update-settings-fireworks-llm.py b/examples/foundational/55zz-update-settings-fireworks-llm.py index fceaadbc2..0b184974d 100644 --- a/examples/foundational/55zz-update-settings-fireworks-llm.py +++ b/examples/foundational/55zz-update-settings-fireworks-llm.py @@ -22,10 +22,9 @@ from pipecat.processors.aggregators.llm_response_universal import ( ) from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport -from pipecat.services.cartesia.tts import CartesiaTTSService, CartesiaTTSSettings +from pipecat.services.cartesia.tts import CartesiaTTSService from pipecat.services.deepgram.stt import DeepgramSTTService -from pipecat.services.fireworks.llm import FireworksLLMService, FireworksLLMSettings -from pipecat.services.openai.base_llm import OpenAILLMSettings +from pipecat.services.fireworks.llm import FireworksLLMService from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams @@ -55,14 +54,14 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): tts = CartesiaTTSService( api_key=os.getenv("CARTESIA_API_KEY"), - settings=CartesiaTTSSettings( + settings=CartesiaTTSService.Settings( voice="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady ), ) llm = FireworksLLMService( api_key=os.getenv("FIREWORKS_API_KEY"), - settings=FireworksLLMSettings( + settings=FireworksLLMService.Settings( model="accounts/fireworks/models/gpt-oss-20b", system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", ), @@ -103,7 +102,9 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): await asyncio.sleep(10) logger.info("Updating Fireworks LLM settings: temperature=0.1") - await task.queue_frame(LLMUpdateSettingsFrame(delta=OpenAILLMSettings(temperature=0.1))) + await task.queue_frame( + LLMUpdateSettingsFrame(delta=FireworksLLMService.Settings(temperature=0.1)) + ) @transport.event_handler("on_client_disconnected") async def on_client_disconnected(transport, client): diff --git a/examples/foundational/55zza-update-settings-grok-llm.py b/examples/foundational/55zza-update-settings-grok-llm.py index 6ea0cd3c3..c5caef791 100644 --- a/examples/foundational/55zza-update-settings-grok-llm.py +++ b/examples/foundational/55zza-update-settings-grok-llm.py @@ -22,10 +22,9 @@ from pipecat.processors.aggregators.llm_response_universal import ( ) from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport -from pipecat.services.cartesia.tts import CartesiaTTSService, CartesiaTTSSettings +from pipecat.services.cartesia.tts import CartesiaTTSService from pipecat.services.deepgram.stt import DeepgramSTTService -from pipecat.services.grok.llm import GrokLLMService, GrokLLMSettings -from pipecat.services.openai.base_llm import OpenAILLMSettings +from pipecat.services.grok.llm import GrokLLMService from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams @@ -55,14 +54,14 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): tts = CartesiaTTSService( api_key=os.getenv("CARTESIA_API_KEY"), - settings=CartesiaTTSSettings( + settings=CartesiaTTSService.Settings( voice="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady ), ) llm = GrokLLMService( api_key=os.getenv("GROK_API_KEY"), - settings=GrokLLMSettings( + settings=GrokLLMService.Settings( system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", ), ) @@ -102,7 +101,9 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): await asyncio.sleep(10) logger.info("Updating Grok LLM settings: temperature=0.1") - await task.queue_frame(LLMUpdateSettingsFrame(delta=OpenAILLMSettings(temperature=0.1))) + await task.queue_frame( + LLMUpdateSettingsFrame(delta=GrokLLMService.Settings(temperature=0.1)) + ) @transport.event_handler("on_client_disconnected") async def on_client_disconnected(transport, client): diff --git a/examples/foundational/55zzb-update-settings-groq-llm.py b/examples/foundational/55zzb-update-settings-groq-llm.py index 9f655f7fc..25d1b4019 100644 --- a/examples/foundational/55zzb-update-settings-groq-llm.py +++ b/examples/foundational/55zzb-update-settings-groq-llm.py @@ -22,10 +22,9 @@ from pipecat.processors.aggregators.llm_response_universal import ( ) from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport -from pipecat.services.cartesia.tts import CartesiaTTSService, CartesiaTTSSettings +from pipecat.services.cartesia.tts import CartesiaTTSService from pipecat.services.deepgram.stt import DeepgramSTTService -from pipecat.services.groq.llm import GroqLLMService, GroqLLMSettings -from pipecat.services.openai.base_llm import OpenAILLMSettings +from pipecat.services.groq.llm import GroqLLMService from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams @@ -55,14 +54,14 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): tts = CartesiaTTSService( api_key=os.getenv("CARTESIA_API_KEY"), - settings=CartesiaTTSSettings( + settings=CartesiaTTSService.Settings( voice="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady ), ) llm = GroqLLMService( api_key=os.getenv("GROQ_API_KEY"), - settings=GroqLLMSettings( + settings=GroqLLMService.Settings( model="meta-llama/llama-4-maverick-17b-128e-instruct", system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", ), @@ -103,7 +102,9 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): await asyncio.sleep(10) logger.info("Updating Groq LLM settings: temperature=0.1") - await task.queue_frame(LLMUpdateSettingsFrame(delta=OpenAILLMSettings(temperature=0.1))) + await task.queue_frame( + LLMUpdateSettingsFrame(delta=GroqLLMService.Settings(temperature=0.1)) + ) @transport.event_handler("on_client_disconnected") async def on_client_disconnected(transport, client): diff --git a/examples/foundational/55zzc-update-settings-mistral-llm.py b/examples/foundational/55zzc-update-settings-mistral-llm.py index a7cb56446..b3c5fa047 100644 --- a/examples/foundational/55zzc-update-settings-mistral-llm.py +++ b/examples/foundational/55zzc-update-settings-mistral-llm.py @@ -22,9 +22,9 @@ from pipecat.processors.aggregators.llm_response_universal import ( ) from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport -from pipecat.services.cartesia.tts import CartesiaTTSService, CartesiaTTSSettings +from pipecat.services.cartesia.tts import CartesiaTTSService from pipecat.services.deepgram.stt import DeepgramSTTService -from pipecat.services.mistral.llm import MistralLLMService, MistralLLMSettings +from pipecat.services.mistral.llm import MistralLLMService from pipecat.services.openai.base_llm import OpenAILLMSettings from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams @@ -55,14 +55,14 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): tts = CartesiaTTSService( api_key=os.getenv("CARTESIA_API_KEY"), - settings=CartesiaTTSSettings( + settings=CartesiaTTSService.Settings( voice="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady ), ) llm = MistralLLMService( api_key=os.getenv("MISTRAL_API_KEY"), - settings=MistralLLMSettings( + settings=MistralLLMService.Settings( system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", ), ) @@ -102,7 +102,9 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): await asyncio.sleep(10) logger.info("Updating Mistral LLM settings: temperature=0.1") - await task.queue_frame(LLMUpdateSettingsFrame(delta=OpenAILLMSettings(temperature=0.1))) + await task.queue_frame( + LLMUpdateSettingsFrame(delta=MistralLLMService.Settings(temperature=0.1)) + ) @transport.event_handler("on_client_disconnected") async def on_client_disconnected(transport, client): diff --git a/examples/foundational/55zzd-update-settings-nvidia-llm.py b/examples/foundational/55zzd-update-settings-nvidia-llm.py index 13593b57b..eb099e50c 100644 --- a/examples/foundational/55zzd-update-settings-nvidia-llm.py +++ b/examples/foundational/55zzd-update-settings-nvidia-llm.py @@ -22,10 +22,9 @@ from pipecat.processors.aggregators.llm_response_universal import ( ) from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport -from pipecat.services.cartesia.tts import CartesiaTTSService, CartesiaTTSSettings +from pipecat.services.cartesia.tts import CartesiaTTSService from pipecat.services.deepgram.stt import DeepgramSTTService -from pipecat.services.nvidia.llm import NvidiaLLMService, NvidiaLLMSettings -from pipecat.services.openai.base_llm import OpenAILLMSettings +from pipecat.services.nvidia.llm import NvidiaLLMService from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams @@ -55,14 +54,14 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): tts = CartesiaTTSService( api_key=os.getenv("CARTESIA_API_KEY"), - settings=CartesiaTTSSettings( + settings=CartesiaTTSService.Settings( voice="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady ), ) llm = NvidiaLLMService( api_key=os.getenv("NVIDIA_API_KEY"), - settings=NvidiaLLMSettings( + settings=NvidiaLLMService.Settings( model="meta/llama-3.1-405b-instruct", system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", ), @@ -103,7 +102,9 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): await asyncio.sleep(10) logger.info("Updating NVIDIA LLM settings: temperature=0.1") - await task.queue_frame(LLMUpdateSettingsFrame(delta=OpenAILLMSettings(temperature=0.1))) + await task.queue_frame( + LLMUpdateSettingsFrame(delta=NvidiaLLMService.Settings(temperature=0.1)) + ) @transport.event_handler("on_client_disconnected") async def on_client_disconnected(transport, client): diff --git a/examples/foundational/55zze-update-settings-ollama-llm.py b/examples/foundational/55zze-update-settings-ollama-llm.py index a6904895b..5625e188c 100644 --- a/examples/foundational/55zze-update-settings-ollama-llm.py +++ b/examples/foundational/55zze-update-settings-ollama-llm.py @@ -22,10 +22,9 @@ from pipecat.processors.aggregators.llm_response_universal import ( ) from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport -from pipecat.services.cartesia.tts import CartesiaTTSService, CartesiaTTSSettings +from pipecat.services.cartesia.tts import CartesiaTTSService from pipecat.services.deepgram.stt import DeepgramSTTService -from pipecat.services.ollama.llm import OLLamaLLMService, OllamaLLMSettings -from pipecat.services.openai.base_llm import OpenAILLMSettings +from pipecat.services.ollama.llm import OLLamaLLMService from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams @@ -55,13 +54,13 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): tts = CartesiaTTSService( api_key=os.getenv("CARTESIA_API_KEY"), - settings=CartesiaTTSSettings( + settings=CartesiaTTSService.Settings( voice="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady ), ) llm = OLLamaLLMService( - settings=OllamaLLMSettings( + settings=OLLamaLLMService.Settings( model="llama3.2", system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", ), @@ -102,7 +101,9 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): await asyncio.sleep(10) logger.info("Updating OLLama LLM settings: temperature=0.1") - await task.queue_frame(LLMUpdateSettingsFrame(delta=OpenAILLMSettings(temperature=0.1))) + await task.queue_frame( + LLMUpdateSettingsFrame(delta=OLLamaLLMService.Settings(temperature=0.1)) + ) @transport.event_handler("on_client_disconnected") async def on_client_disconnected(transport, client): diff --git a/examples/foundational/55zzf-update-settings-openrouter-llm.py b/examples/foundational/55zzf-update-settings-openrouter-llm.py index 124e5f04a..4745ae537 100644 --- a/examples/foundational/55zzf-update-settings-openrouter-llm.py +++ b/examples/foundational/55zzf-update-settings-openrouter-llm.py @@ -22,10 +22,9 @@ from pipecat.processors.aggregators.llm_response_universal import ( ) from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport -from pipecat.services.cartesia.tts import CartesiaTTSService, CartesiaTTSSettings +from pipecat.services.cartesia.tts import CartesiaTTSService from pipecat.services.deepgram.stt import DeepgramSTTService -from pipecat.services.openai.base_llm import OpenAILLMSettings -from pipecat.services.openrouter.llm import OpenRouterLLMService, OpenRouterLLMSettings +from pipecat.services.openrouter.llm import OpenRouterLLMService from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams @@ -55,14 +54,14 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): tts = CartesiaTTSService( api_key=os.getenv("CARTESIA_API_KEY"), - settings=CartesiaTTSSettings( + settings=CartesiaTTSService.Settings( voice="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady ), ) llm = OpenRouterLLMService( api_key=os.getenv("OPENROUTER_API_KEY"), - settings=OpenRouterLLMSettings( + settings=OpenRouterLLMService.Settings( system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", ), ) @@ -102,7 +101,9 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): await asyncio.sleep(10) logger.info("Updating OpenRouter LLM settings: temperature=0.1") - await task.queue_frame(LLMUpdateSettingsFrame(delta=OpenAILLMSettings(temperature=0.1))) + await task.queue_frame( + LLMUpdateSettingsFrame(delta=OpenRouterLLMService.Settings(temperature=0.1)) + ) @transport.event_handler("on_client_disconnected") async def on_client_disconnected(transport, client): diff --git a/examples/foundational/55zzg-update-settings-perplexity-llm.py b/examples/foundational/55zzg-update-settings-perplexity-llm.py index 5227c6063..b764e0ff7 100644 --- a/examples/foundational/55zzg-update-settings-perplexity-llm.py +++ b/examples/foundational/55zzg-update-settings-perplexity-llm.py @@ -22,9 +22,8 @@ from pipecat.processors.aggregators.llm_response_universal import ( ) from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport -from pipecat.services.cartesia.tts import CartesiaTTSService, CartesiaTTSSettings +from pipecat.services.cartesia.tts import CartesiaTTSService from pipecat.services.deepgram.stt import DeepgramSTTService -from pipecat.services.openai.base_llm import OpenAILLMSettings from pipecat.services.perplexity.llm import PerplexityLLMService from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams @@ -55,7 +54,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): tts = CartesiaTTSService( api_key=os.getenv("CARTESIA_API_KEY"), - settings=CartesiaTTSSettings( + settings=CartesiaTTSService.Settings( voice="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady ), ) @@ -103,7 +102,9 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): await asyncio.sleep(10) logger.info("Updating Perplexity LLM settings: temperature=0.1") - await task.queue_frame(LLMUpdateSettingsFrame(delta=OpenAILLMSettings(temperature=0.1))) + await task.queue_frame( + LLMUpdateSettingsFrame(delta=PerplexityLLMService.Settings(temperature=0.1)) + ) @transport.event_handler("on_client_disconnected") async def on_client_disconnected(transport, client): diff --git a/examples/foundational/55zzh-update-settings-qwen-llm.py b/examples/foundational/55zzh-update-settings-qwen-llm.py index 7a35fd124..2f56886b9 100644 --- a/examples/foundational/55zzh-update-settings-qwen-llm.py +++ b/examples/foundational/55zzh-update-settings-qwen-llm.py @@ -22,10 +22,9 @@ from pipecat.processors.aggregators.llm_response_universal import ( ) from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport -from pipecat.services.cartesia.tts import CartesiaTTSService, CartesiaTTSSettings +from pipecat.services.cartesia.tts import CartesiaTTSService from pipecat.services.deepgram.stt import DeepgramSTTService -from pipecat.services.openai.base_llm import OpenAILLMSettings -from pipecat.services.qwen.llm import QwenLLMService, QwenLLMSettings +from pipecat.services.qwen.llm import QwenLLMService from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams @@ -55,14 +54,14 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): tts = CartesiaTTSService( api_key=os.getenv("CARTESIA_API_KEY"), - settings=CartesiaTTSSettings( + settings=CartesiaTTSService.Settings( voice="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady ), ) llm = QwenLLMService( api_key=os.getenv("QWEN_API_KEY"), - settings=QwenLLMSettings( + settings=QwenLLMService.Settings( model="qwen2.5-72b-instruct", system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", ), @@ -103,7 +102,9 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): await asyncio.sleep(10) logger.info("Updating Qwen LLM settings: temperature=0.1") - await task.queue_frame(LLMUpdateSettingsFrame(delta=OpenAILLMSettings(temperature=0.1))) + await task.queue_frame( + LLMUpdateSettingsFrame(delta=QwenLLMService.Settings(temperature=0.1)) + ) @transport.event_handler("on_client_disconnected") async def on_client_disconnected(transport, client): diff --git a/examples/foundational/55zzi-update-settings-sambanova-llm.py b/examples/foundational/55zzi-update-settings-sambanova-llm.py index 73f3316db..46db2099f 100644 --- a/examples/foundational/55zzi-update-settings-sambanova-llm.py +++ b/examples/foundational/55zzi-update-settings-sambanova-llm.py @@ -22,10 +22,9 @@ from pipecat.processors.aggregators.llm_response_universal import ( ) from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport -from pipecat.services.cartesia.tts import CartesiaTTSService, CartesiaTTSSettings +from pipecat.services.cartesia.tts import CartesiaTTSService from pipecat.services.deepgram.stt import DeepgramSTTService -from pipecat.services.openai.base_llm import OpenAILLMSettings -from pipecat.services.sambanova.llm import SambaNovaLLMService, SambaNovaLLMSettings +from pipecat.services.sambanova.llm import SambaNovaLLMService from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams @@ -55,14 +54,14 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): tts = CartesiaTTSService( api_key=os.getenv("CARTESIA_API_KEY"), - settings=CartesiaTTSSettings( + settings=CartesiaTTSService.Settings( voice="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady ), ) llm = SambaNovaLLMService( api_key=os.getenv("SAMBANOVA_API_KEY"), - settings=SambaNovaLLMSettings( + settings=SambaNovaLLMService.Settings( system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", ), ) @@ -102,7 +101,9 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): await asyncio.sleep(10) logger.info("Updating SambaNova LLM settings: temperature=0.1") - await task.queue_frame(LLMUpdateSettingsFrame(delta=OpenAILLMSettings(temperature=0.1))) + await task.queue_frame( + LLMUpdateSettingsFrame(delta=SambaNovaLLMService.Settings(temperature=0.1)) + ) @transport.event_handler("on_client_disconnected") async def on_client_disconnected(transport, client): diff --git a/examples/foundational/55zzj-update-settings-together-llm.py b/examples/foundational/55zzj-update-settings-together-llm.py index 314b81223..e293613b1 100644 --- a/examples/foundational/55zzj-update-settings-together-llm.py +++ b/examples/foundational/55zzj-update-settings-together-llm.py @@ -22,10 +22,9 @@ from pipecat.processors.aggregators.llm_response_universal import ( ) from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport -from pipecat.services.cartesia.tts import CartesiaTTSService, CartesiaTTSSettings +from pipecat.services.cartesia.tts import CartesiaTTSService from pipecat.services.deepgram.stt import DeepgramSTTService -from pipecat.services.openai.base_llm import OpenAILLMSettings -from pipecat.services.together.llm import TogetherLLMService, TogetherLLMSettings +from pipecat.services.together.llm import TogetherLLMService from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams @@ -55,14 +54,14 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): tts = CartesiaTTSService( api_key=os.getenv("CARTESIA_API_KEY"), - settings=CartesiaTTSSettings( + settings=CartesiaTTSService.Settings( voice="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady ), ) llm = TogetherLLMService( api_key=os.getenv("TOGETHER_API_KEY"), - settings=TogetherLLMSettings( + settings=TogetherLLMService.Settings( model="meta-llama/Meta-Llama-3.1-70B-Instruct-Turbo", system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", ), @@ -103,7 +102,9 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): await asyncio.sleep(10) logger.info("Updating Together LLM settings: temperature=0.1") - await task.queue_frame(LLMUpdateSettingsFrame(delta=OpenAILLMSettings(temperature=0.1))) + await task.queue_frame( + LLMUpdateSettingsFrame(delta=TogetherLLMService.Settings(temperature=0.1)) + ) @transport.event_handler("on_client_disconnected") async def on_client_disconnected(transport, client): diff --git a/examples/foundational/55zzk-update-settings-aws-nova-sonic-llm.py b/examples/foundational/55zzk-update-settings-aws-nova-sonic-llm.py index de516baa8..bec1c4d86 100644 --- a/examples/foundational/55zzk-update-settings-aws-nova-sonic-llm.py +++ b/examples/foundational/55zzk-update-settings-aws-nova-sonic-llm.py @@ -22,7 +22,7 @@ from pipecat.processors.aggregators.llm_response_universal import ( ) from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport -from pipecat.services.aws.nova_sonic.llm import AWSNovaSonicLLMService, AWSNovaSonicLLMSettings +from pipecat.services.aws.nova_sonic.llm import AWSNovaSonicLLMService from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams @@ -52,7 +52,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): secret_access_key=os.getenv("AWS_SECRET_ACCESS_KEY"), access_key_id=os.getenv("AWS_ACCESS_KEY_ID"), region=os.getenv("AWS_REGION"), - settings=AWSNovaSonicLLMSettings( + settings=AWSNovaSonicLLMService.Settings( system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", ), ) @@ -91,7 +91,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): await asyncio.sleep(10) logger.info("Updating AWS Nova Sonic LLM settings: temperature=0.1") await task.queue_frame( - LLMUpdateSettingsFrame(delta=AWSNovaSonicLLMSettings(temperature=0.1)) + LLMUpdateSettingsFrame(delta=AWSNovaSonicLLMService.Settings(temperature=0.1)) ) @transport.event_handler("on_client_disconnected") diff --git a/examples/foundational/55zzl-update-settings-nvidia-tts.py b/examples/foundational/55zzl-update-settings-nvidia-tts.py index a6d26542a..5caaad3b4 100644 --- a/examples/foundational/55zzl-update-settings-nvidia-tts.py +++ b/examples/foundational/55zzl-update-settings-nvidia-tts.py @@ -23,8 +23,8 @@ from pipecat.processors.aggregators.llm_response_universal import ( from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport from pipecat.services.deepgram.stt import DeepgramSTTService -from pipecat.services.nvidia.tts import NvidiaTTSService, NvidiaTTSSettings -from pipecat.services.openai.llm import OpenAILLMService, OpenAILLMSettings +from pipecat.services.nvidia.tts import NvidiaTTSService +from pipecat.services.openai.llm import OpenAILLMService from pipecat.transcriptions.language import Language from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams @@ -57,7 +57,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): llm = OpenAILLMService( api_key=os.getenv("OPENAI_API_KEY"), - settings=OpenAILLMSettings( + settings=OpenAILLMService.Settings( system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", ), ) @@ -98,7 +98,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): await asyncio.sleep(10) logger.info('Updating NVIDIA TTS settings: language="ES_US"') await task.queue_frame( - TTSUpdateSettingsFrame(delta=NvidiaTTSSettings(language=Language.ES_US)) + TTSUpdateSettingsFrame(delta=NvidiaTTSService.Settings(language=Language.ES_US)) ) @transport.event_handler("on_client_disconnected") diff --git a/examples/foundational/55zzm-update-settings-speechmatics-tts.py b/examples/foundational/55zzm-update-settings-speechmatics-tts.py index 2cce46ebb..80a6c694c 100644 --- a/examples/foundational/55zzm-update-settings-speechmatics-tts.py +++ b/examples/foundational/55zzm-update-settings-speechmatics-tts.py @@ -24,8 +24,8 @@ from pipecat.processors.aggregators.llm_response_universal import ( from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport from pipecat.services.deepgram.stt import DeepgramSTTService -from pipecat.services.openai.llm import OpenAILLMService, OpenAILLMSettings -from pipecat.services.speechmatics.tts import SpeechmaticsTTSService, SpeechmaticsTTSSettings +from pipecat.services.openai.llm import OpenAILLMService +from pipecat.services.speechmatics.tts import SpeechmaticsTTSService from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams @@ -61,7 +61,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): llm = OpenAILLMService( api_key=os.getenv("OPENAI_API_KEY"), - settings=OpenAILLMSettings( + settings=OpenAILLMService.Settings( system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", ), ) @@ -104,7 +104,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): await asyncio.sleep(10) logger.info('Updating Speechmatics TTS settings: voice="theo"') await task.queue_frame( - TTSUpdateSettingsFrame(delta=SpeechmaticsTTSSettings(voice="theo")) + TTSUpdateSettingsFrame(delta=SpeechmaticsTTSService.Settings(voice="theo")) ) @transport.event_handler("on_client_disconnected") diff --git a/examples/foundational/55zzn-update-settings-groq-stt.py b/examples/foundational/55zzn-update-settings-groq-stt.py index dc7ba6d23..1b4e9b8ed 100644 --- a/examples/foundational/55zzn-update-settings-groq-stt.py +++ b/examples/foundational/55zzn-update-settings-groq-stt.py @@ -22,10 +22,9 @@ from pipecat.processors.aggregators.llm_response_universal import ( ) from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport -from pipecat.services.cartesia.tts import CartesiaTTSService, CartesiaTTSSettings +from pipecat.services.cartesia.tts import CartesiaTTSService from pipecat.services.groq.stt import GroqSTTService -from pipecat.services.openai.llm import OpenAILLMService, OpenAILLMSettings -from pipecat.services.whisper.base_stt import BaseWhisperSTTSettings +from pipecat.services.openai.llm import OpenAILLMService from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams @@ -57,14 +56,14 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): tts = CartesiaTTSService( api_key=os.getenv("CARTESIA_API_KEY"), - settings=CartesiaTTSSettings( + settings=CartesiaTTSService.Settings( voice="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady ), ) llm = OpenAILLMService( api_key=os.getenv("OPENAI_API_KEY"), - settings=OpenAILLMSettings( + settings=OpenAILLMService.Settings( system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", ), ) @@ -104,7 +103,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): await asyncio.sleep(10) logger.info('Updating Groq STT settings: language="es"') - await task.queue_frame(STTUpdateSettingsFrame(delta=BaseWhisperSTTSettings(language="es"))) + await task.queue_frame(STTUpdateSettingsFrame(delta=GroqSTTService.Settings(language="es"))) @transport.event_handler("on_client_disconnected") async def on_client_disconnected(transport, client): diff --git a/examples/foundational/56-lemonslice-transport.py b/examples/foundational/56-lemonslice-transport.py index aefa533e4..67f4e8ad1 100644 --- a/examples/foundational/56-lemonslice-transport.py +++ b/examples/foundational/56-lemonslice-transport.py @@ -23,8 +23,8 @@ from pipecat.processors.aggregators.llm_response_universal import ( LLMUserAggregatorParams, ) from pipecat.services.deepgram.stt import DeepgramSTTService -from pipecat.services.elevenlabs.tts import ElevenLabsTTSService, ElevenLabsTTSSettings -from pipecat.services.groq.llm import GroqLLMService, GroqLLMSettings +from pipecat.services.elevenlabs.tts import ElevenLabsTTSService +from pipecat.services.groq.llm import GroqLLMService from pipecat.transports.lemonslice.transport import ( LemonSliceNewSessionRequest, LemonSliceParams, @@ -57,14 +57,14 @@ async def main(): llm = GroqLLMService( api_key=os.getenv("GROQ_API_KEY"), - settings=GroqLLMSettings( + settings=GroqLLMService.Settings( system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", ), ) tts = ElevenLabsTTSService( api_key=os.getenv("ELEVENLABS_API_KEY", ""), - settings=ElevenLabsTTSSettings( + settings=ElevenLabsTTSService.Settings( voice="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady ), ) diff --git a/scripts/evals/eval.py b/scripts/evals/eval.py index 992eb43c7..ab4edad8d 100644 --- a/scripts/evals/eval.py +++ b/scripts/evals/eval.py @@ -48,8 +48,8 @@ from pipecat.processors.aggregators.llm_response_universal import ( from pipecat.processors.audio.audio_buffer_processor import AudioBufferProcessor from pipecat.processors.frame_processor import FrameDirection from pipecat.runner.types import RunnerArguments -from pipecat.services.cartesia.tts import CartesiaTTSService, CartesiaTTSSettings -from pipecat.services.deepgram.stt import DeepgramSTTService, DeepgramSTTSettings +from pipecat.services.cartesia.tts import CartesiaTTSService +from pipecat.services.deepgram.stt import DeepgramSTTService from pipecat.services.llm_service import FunctionCallParams from pipecat.services.openai.base_llm import OpenAILLMSettings from pipecat.services.openai.llm import OpenAILLMService @@ -244,7 +244,7 @@ async def run_eval_pipeline( # 5" (in audio) this can be converted to "32 is 5". stt = DeepgramSTTService( api_key=os.getenv("DEEPGRAM_API_KEY"), - settings=DeepgramSTTSettings( + settings=DeepgramSTTService.Settings( language="multi", smart_format=False, ), @@ -252,7 +252,7 @@ async def run_eval_pipeline( tts = CartesiaTTSService( api_key=os.getenv("CARTESIA_API_KEY"), - settings=CartesiaTTSSettings( + settings=CartesiaTTSService.Settings( voice="97f4b8fb-f2fe-444b-bb9a-c109783a857a", # Nathan ), ) @@ -302,7 +302,9 @@ async def run_eval_pipeline( llm = OpenAILLMService( api_key=os.getenv("OPENAI_API_KEY"), - settings=OpenAILLMSettings(system_instruction=system_prompt), + settings=OpenAILLMService.Settings( + system_instruction=system_prompt, + ), ) llm.register_function("eval_function", eval_runner.function_assert_eval) From 807759b8746201c294e011e3feebdab7ed363789 Mon Sep 17 00:00:00 2001 From: Mark Backman Date: Sat, 7 Mar 2026 15:43:52 -0500 Subject: [PATCH 0860/1060] Revert changes to quickstart --- examples/quickstart/bot.py | 6 ++---- 1 file changed, 2 insertions(+), 4 deletions(-) diff --git a/examples/quickstart/bot.py b/examples/quickstart/bot.py index 956331d50..fbe27d783 100644 --- a/examples/quickstart/bot.py +++ b/examples/quickstart/bot.py @@ -45,7 +45,7 @@ from pipecat.processors.aggregators.llm_response_universal import ( ) from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport -from pipecat.services.cartesia.tts import CartesiaTTSService, CartesiaTTSSettings +from pipecat.services.cartesia.tts import CartesiaTTSService from pipecat.services.deepgram.stt import DeepgramSTTService from pipecat.services.openai.llm import OpenAILLMService from pipecat.transports.base_transport import BaseTransport, TransportParams @@ -63,9 +63,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): tts = CartesiaTTSService( api_key=os.getenv("CARTESIA_API_KEY"), - settings=CartesiaTTSSettings( - voice="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady - ), + voice_id="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady ) llm = OpenAILLMService(api_key=os.getenv("OPENAI_API_KEY")) From 57f0b6d75bb9715167eaea15900786808eacb89f Mon Sep 17 00:00:00 2001 From: kigland Date: Sun, 8 Mar 2026 12:28:03 +0800 Subject: [PATCH 0861/1060] fix: address review feedback on exception handling - mcp_service.py: remove unnecessary try/except around debug log, use len(available_tools.tools) to match actual iteration target - bedrock_adapter.py, aws/llm.py: add AttributeError to except tuple to handle None content (previously caught by bare except) --- src/pipecat/adapters/services/bedrock_adapter.py | 2 +- src/pipecat/services/aws/llm.py | 2 +- src/pipecat/services/mcp_service.py | 5 +---- 3 files changed, 3 insertions(+), 6 deletions(-) diff --git a/src/pipecat/adapters/services/bedrock_adapter.py b/src/pipecat/adapters/services/bedrock_adapter.py index 8fd474cb6..d63c5cf0f 100644 --- a/src/pipecat/adapters/services/bedrock_adapter.py +++ b/src/pipecat/adapters/services/bedrock_adapter.py @@ -209,7 +209,7 @@ class AWSBedrockLLMAdapter(BaseLLMAdapter[AWSBedrockLLMInvocationParams]): tool_result_content = [{"json": content_json}] else: tool_result_content = [{"text": message["content"]}] - except (json.JSONDecodeError, ValueError): + except (json.JSONDecodeError, ValueError, AttributeError): tool_result_content = [{"text": message["content"]}] return { diff --git a/src/pipecat/services/aws/llm.py b/src/pipecat/services/aws/llm.py index 8f614cf8f..ea8a76b8f 100644 --- a/src/pipecat/services/aws/llm.py +++ b/src/pipecat/services/aws/llm.py @@ -369,7 +369,7 @@ class AWSBedrockLLMContext(OpenAILLMContext): tool_result_content = [{"json": content_json}] else: tool_result_content = [{"text": message["content"]}] - except (json.JSONDecodeError, ValueError): + except (json.JSONDecodeError, ValueError, AttributeError): tool_result_content = [{"text": message["content"]}] return { diff --git a/src/pipecat/services/mcp_service.py b/src/pipecat/services/mcp_service.py index 302185719..d4f0807b8 100644 --- a/src/pipecat/services/mcp_service.py +++ b/src/pipecat/services/mcp_service.py @@ -296,10 +296,7 @@ class MCPClient(BaseObject): available_tools = await session.list_tools() tool_schemas: List[FunctionSchema] = [] - try: - logger.debug(f"Found {len(available_tools)} available tools") - except Exception: - pass + logger.debug(f"Found {len(available_tools.tools)} available tools") for tool in available_tools.tools: tool_name = tool.name From b14c8e0e94a44accfec124f0787397736562cdbd Mon Sep 17 00:00:00 2001 From: radhikagpt1208 Date: Sun, 8 Mar 2026 13:01:59 +0530 Subject: [PATCH 0862/1060] Fix turn completion mixin not resetting state after each LLM response --- changelog/3956.fixed.md | 1 + .../turns/user_turn_completion_mixin.py | 19 +++++++++--- tests/test_user_turn_completion_mixin.py | 29 ++++++++++++++++++- 3 files changed, 44 insertions(+), 5 deletions(-) create mode 100644 changelog/3956.fixed.md diff --git a/changelog/3956.fixed.md b/changelog/3956.fixed.md new file mode 100644 index 000000000..c8af8db91 --- /dev/null +++ b/changelog/3956.fixed.md @@ -0,0 +1 @@ +- Fixed turn completion state not resetting at end of LLM responses. `LLMFullResponseEndFrame` is pushed (not received) by the LLM service, so the mixin now handles it in `push_frame` instead of `process_frame`. diff --git a/src/pipecat/turns/user_turn_completion_mixin.py b/src/pipecat/turns/user_turn_completion_mixin.py index 3aea01be9..40ae551b4 100644 --- a/src/pipecat/turns/user_turn_completion_mixin.py +++ b/src/pipecat/turns/user_turn_completion_mixin.py @@ -332,14 +332,25 @@ class UserTurnCompletionLLMServiceMixin: if isinstance(frame, InterruptionFrame): await self._cancel_incomplete_timeout() await self._turn_reset() - # Reset turn state at end of LLM response (but don't cancel timeout - - # incomplete timeouts should continue running) - elif isinstance(frame, LLMFullResponseEndFrame): - await self._turn_reset() # Pass frame to parent await super().process_frame(frame, direction) + async def push_frame(self, frame: Frame, direction: FrameDirection = FrameDirection.DOWNSTREAM): + """Push a frame downstream, resetting turn state at end of each LLM response. + + ``LLMFullResponseEndFrame`` is generated by the LLM service itself (pushed, + not received), so it must be handled here rather than in ``process_frame``. + + Args: + frame: The frame to push downstream. + direction: The direction of frame flow. Defaults to downstream. + """ + if isinstance(frame, LLMFullResponseEndFrame): + await self._turn_reset() + + await super().push_frame(frame, direction) + async def _push_turn_text(self, text: str): """Push LLM text with turn completion detection. diff --git a/tests/test_user_turn_completion_mixin.py b/tests/test_user_turn_completion_mixin.py index d258cff9a..273d8cc90 100644 --- a/tests/test_user_turn_completion_mixin.py +++ b/tests/test_user_turn_completion_mixin.py @@ -5,9 +5,10 @@ # import unittest +import unittest.mock from unittest.mock import AsyncMock -from pipecat.frames.frames import LLMTextFrame +from pipecat.frames.frames import LLMFullResponseEndFrame, LLMTextFrame from pipecat.processors.frame_processor import FrameProcessor from pipecat.turns.user_turn_completion_mixin import ( USER_TURN_COMPLETE_MARKER, @@ -112,6 +113,32 @@ class TestUserUserTurnCompletionLLMServiceMixin(unittest.IsolatedAsyncioTestCase # Now frames should be pushed self.assertEqual(len(pushed_frames), 2) + async def test_turn_state_reset_after_llm_full_response_end_frame(self): + """Test that _turn_complete_found is reset when LLMFullResponseEndFrame is pushed.""" + processor = MockProcessor() + + # Mock push_frame on the instance so _push_turn_text can call it without + # a live pipeline, but keep _turn_reset as the real implementation. + processor.push_frame = AsyncMock() + + # Simulate first LLM response: complete marker sets _turn_complete_found = True + await processor._push_turn_text(f"{USER_TURN_COMPLETE_MARKER} Hello!") + self.assertTrue(processor._turn_complete_found) + + # Restore the real push_frame so the mixin override runs, then call it + # with LLMFullResponseEndFrame as the LLM service would. + del processor.push_frame # removes instance mock, restores class method + + # Patch only the FrameProcessor-level send so no live pipeline is needed. + with unittest.mock.patch.object(FrameProcessor, "push_frame", AsyncMock()): + end_frame = LLMFullResponseEndFrame() + await processor.push_frame(end_frame) + + # _turn_complete_found must now be False — ready for the next response + self.assertFalse(processor._turn_complete_found) + self.assertEqual(processor._turn_text_buffer, "") + self.assertFalse(processor._turn_suppressed) + if __name__ == "__main__": unittest.main() From efda57de5c041e0912cd649869049f094d37d8b6 Mon Sep 17 00:00:00 2001 From: Mark Backman Date: Sun, 8 Mar 2026 10:41:40 -0400 Subject: [PATCH 0863/1060] Move turn completion instructions to system_instruction Turn completion instructions were being injected as a system message in the LLM context, which caused warning spam when system_instruction was also set, did not persist across full context updates, and broke LLMs that do not support consecutive system messages. Instead, compose the turn completion instructions into the LLM service system_instruction field. This is managed via _base_system_instruction which stores the original value for restoration when turn completion is disabled. --- .../aggregators/llm_response_universal.py | 6 - src/pipecat/services/llm_service.py | 33 +++++ tests/test_context_aggregators_universal.py | 11 +- tests/test_user_turn_completion_mixin.py | 117 ++++++++++++++++++ 4 files changed, 154 insertions(+), 13 deletions(-) diff --git a/src/pipecat/processors/aggregators/llm_response_universal.py b/src/pipecat/processors/aggregators/llm_response_universal.py index cf6c81e5f..db8ed4a3d 100644 --- a/src/pipecat/processors/aggregators/llm_response_universal.py +++ b/src/pipecat/processors/aggregators/llm_response_universal.py @@ -565,9 +565,6 @@ class LLMUserAggregator(LLMContextAggregator): ) ) - # Auto-inject turn completion instructions into context - self._context.add_message({"role": "system", "content": config.completion_instructions}) - async def _stop(self, frame: EndFrame): await self._maybe_emit_user_turn_stopped(on_session_end=True) await self._cleanup() @@ -636,9 +633,6 @@ class LLMUserAggregator(LLMContextAggregator): async def _handle_llm_messages_update(self, frame: LLMMessagesUpdateFrame): self.set_messages(frame.messages) - if self._params.filter_incomplete_user_turns: - config = self._params.user_turn_completion_config or UserTurnCompletionConfig() - self._context.add_message({"role": "system", "content": config.completion_instructions}) if frame.run_llm: await self.push_context_frame() diff --git a/src/pipecat/services/llm_service.py b/src/pipecat/services/llm_service.py index 909b555a2..44858038d 100644 --- a/src/pipecat/services/llm_service.py +++ b/src/pipecat/services/llm_service.py @@ -212,6 +212,7 @@ class LLMService(UserTurnCompletionLLMServiceMixin, AIService): self._run_in_parallel = run_in_parallel self._function_call_timeout_secs = function_call_timeout_secs self._filter_incomplete_user_turns: bool = False + self._base_system_instruction: Optional[str] = None self._start_callbacks = {} self._adapter = self.adapter_class() self._functions: Dict[Optional[str], FunctionCallRegistryItem] = {} @@ -326,6 +327,19 @@ class LLMService(UserTurnCompletionLLMServiceMixin, AIService): await self._cancel_sequential_runner_task() await self._cancel_summary_task() + def _compose_system_instruction(self): + """Compose system_instruction by appending turn completion instructions. + + Combines the base system instruction with turn completion instructions + and writes the result to ``self._settings.system_instruction``. + """ + base = self._base_system_instruction + completion_instructions = self._user_turn_completion_config.completion_instructions + if base: + self._settings.system_instruction = f"{base}\n\n{completion_instructions}" + else: + self._settings.system_instruction = completion_instructions + async def _update_settings(self, delta: LLMSettings) -> dict[str, Any]: """Apply a settings delta, handling turn-completion fields. @@ -345,9 +359,28 @@ class LLMService(UserTurnCompletionLLMServiceMixin, AIService): f"{self}: Incomplete turn filtering " f"{'enabled' if self._filter_incomplete_user_turns else 'disabled'}" ) + if self._filter_incomplete_user_turns: + # Save the current system_instruction before composing + self._base_system_instruction = self._settings.system_instruction + self._compose_system_instruction() + else: + # Restore original system_instruction + self._settings.system_instruction = self._base_system_instruction + self._base_system_instruction = None if "user_turn_completion_config" in changed and self._filter_incomplete_user_turns: self.set_user_turn_completion_config(self._settings.user_turn_completion_config) + self._compose_system_instruction() + + if ( + "system_instruction" in changed + and self._filter_incomplete_user_turns + and "filter_incomplete_user_turns" not in changed + ): + # system_instruction changed while turn completion is active. + # Treat the new value as the new base and recompose. + self._base_system_instruction = self._settings.system_instruction + self._compose_system_instruction() return changed diff --git a/tests/test_context_aggregators_universal.py b/tests/test_context_aggregators_universal.py index b22abf6c6..7d6f73f2d 100644 --- a/tests/test_context_aggregators_universal.py +++ b/tests/test_context_aggregators_universal.py @@ -50,7 +50,6 @@ from pipecat.turns.user_mute import ( MuteUntilFirstBotCompleteUserMuteStrategy, ) from pipecat.turns.user_stop import SpeechTimeoutUserTurnStopStrategy -from pipecat.turns.user_turn_completion_mixin import UserTurnCompletionConfig from pipecat.turns.user_turn_strategies import UserTurnStrategies USER_TURN_STOP_TIMEOUT = 0.2 @@ -156,7 +155,7 @@ class TestLLMUserAggregator(unittest.IsolatedAsyncioTestCase): ) assert context.messages[0]["content"] == "Hi there!" - async def test_llm_messages_update_reinjects_turn_completion_instructions(self): + async def test_llm_messages_update_does_not_inject_turn_completion_into_context(self): context = LLMContext() params = LLMUserAggregatorParams(filter_incomplete_user_turns=True) pipeline = Pipeline([LLMUserAggregator(context, params=params)]) @@ -170,13 +169,11 @@ class TestLLMUserAggregator(unittest.IsolatedAsyncioTestCase): pipeline, frames_to_send=frames_to_send, ) - config = UserTurnCompletionConfig() - # The context should contain the new messages plus the re-injected instructions - assert len(context.messages) == 3 + # Turn completion instructions are now set via system_instruction on the + # LLM service, not injected into context messages. + assert len(context.messages) == 2 assert context.messages[0]["content"] == "You are a helpful assistant." assert context.messages[1]["content"] == "Hello!" - assert context.messages[2]["role"] == "system" - assert context.messages[2]["content"] == config.completion_instructions async def test_default_user_turn_strategies(self): context = LLMContext() diff --git a/tests/test_user_turn_completion_mixin.py b/tests/test_user_turn_completion_mixin.py index 273d8cc90..e503ecbf2 100644 --- a/tests/test_user_turn_completion_mixin.py +++ b/tests/test_user_turn_completion_mixin.py @@ -10,10 +10,14 @@ from unittest.mock import AsyncMock from pipecat.frames.frames import LLMFullResponseEndFrame, LLMTextFrame from pipecat.processors.frame_processor import FrameProcessor +from pipecat.services.llm_service import LLMService +from pipecat.services.settings import LLMSettings from pipecat.turns.user_turn_completion_mixin import ( USER_TURN_COMPLETE_MARKER, + USER_TURN_COMPLETION_INSTRUCTIONS, USER_TURN_INCOMPLETE_LONG_MARKER, USER_TURN_INCOMPLETE_SHORT_MARKER, + UserTurnCompletionConfig, UserTurnCompletionLLMServiceMixin, ) @@ -140,5 +144,118 @@ class TestUserUserTurnCompletionLLMServiceMixin(unittest.IsolatedAsyncioTestCase self.assertFalse(processor._turn_suppressed) +class MockLLMService(LLMService): + """Minimal LLM service for testing system_instruction composition.""" + + def __init__(self, **kwargs): + settings = LLMSettings( + model="test-model", + system_instruction=kwargs.pop("system_instruction", None), + temperature=None, + max_tokens=None, + top_p=None, + top_k=None, + frequency_penalty=None, + presence_penalty=None, + seed=None, + filter_incomplete_user_turns=None, + user_turn_completion_config=None, + ) + super().__init__(settings=settings, **kwargs) + + +class TestSystemInstructionComposition(unittest.IsolatedAsyncioTestCase): + """Tests for turn completion system_instruction composition in LLMService.""" + + async def test_enable_turn_completion_sets_system_instruction(self): + """Enabling turn completion should set system_instruction to completion instructions.""" + service = MockLLMService() + self.assertIsNone(service._settings.system_instruction) + + delta = LLMSettings(filter_incomplete_user_turns=True) + await service._update_settings(delta) + + self.assertEqual(service._settings.system_instruction, USER_TURN_COMPLETION_INSTRUCTIONS) + self.assertIsNone(service._base_system_instruction) + + async def test_enable_turn_completion_appends_to_existing_system_instruction(self): + """Enabling turn completion should append instructions to existing system_instruction.""" + service = MockLLMService(system_instruction="You are a helpful assistant.") + + delta = LLMSettings(filter_incomplete_user_turns=True) + await service._update_settings(delta) + + expected = f"You are a helpful assistant.\n\n{USER_TURN_COMPLETION_INSTRUCTIONS}" + self.assertEqual(service._settings.system_instruction, expected) + self.assertEqual(service._base_system_instruction, "You are a helpful assistant.") + + async def test_disable_turn_completion_restores_system_instruction(self): + """Disabling turn completion should restore the original system_instruction.""" + service = MockLLMService(system_instruction="You are a helpful assistant.") + + # Enable + await service._update_settings(LLMSettings(filter_incomplete_user_turns=True)) + self.assertIn(USER_TURN_COMPLETION_INSTRUCTIONS, service._settings.system_instruction) + + # Disable + await service._update_settings(LLMSettings(filter_incomplete_user_turns=False)) + self.assertEqual(service._settings.system_instruction, "You are a helpful assistant.") + self.assertIsNone(service._base_system_instruction) + + async def test_disable_turn_completion_restores_none(self): + """Disabling turn completion when original was None should restore None.""" + service = MockLLMService() + + await service._update_settings(LLMSettings(filter_incomplete_user_turns=True)) + self.assertEqual(service._settings.system_instruction, USER_TURN_COMPLETION_INSTRUCTIONS) + + await service._update_settings(LLMSettings(filter_incomplete_user_turns=False)) + self.assertIsNone(service._settings.system_instruction) + + async def test_update_system_instruction_while_turn_completion_active(self): + """Changing system_instruction while turn completion is active should recompose.""" + service = MockLLMService(system_instruction="Original prompt.") + + await service._update_settings(LLMSettings(filter_incomplete_user_turns=True)) + expected = f"Original prompt.\n\n{USER_TURN_COMPLETION_INSTRUCTIONS}" + self.assertEqual(service._settings.system_instruction, expected) + + # Now update system_instruction + await service._update_settings(LLMSettings(system_instruction="New prompt.")) + expected = f"New prompt.\n\n{USER_TURN_COMPLETION_INSTRUCTIONS}" + self.assertEqual(service._settings.system_instruction, expected) + self.assertEqual(service._base_system_instruction, "New prompt.") + + async def test_update_config_recomposes_with_custom_instructions(self): + """Updating turn completion config should recompose with new instructions.""" + service = MockLLMService(system_instruction="Base prompt.") + + await service._update_settings(LLMSettings(filter_incomplete_user_turns=True)) + + custom_config = UserTurnCompletionConfig(instructions="Custom turn instructions.") + await service._update_settings(LLMSettings(user_turn_completion_config=custom_config)) + + expected = "Base prompt.\n\nCustom turn instructions." + self.assertEqual(service._settings.system_instruction, expected) + + async def test_simultaneous_enable_and_system_instruction_change(self): + """Enabling turn completion and changing system_instruction in the same delta + should use the new system_instruction as the base.""" + service = MockLLMService(system_instruction="Original prompt.") + + await service._update_settings( + LLMSettings( + filter_incomplete_user_turns=True, + system_instruction="New prompt.", + ) + ) + + # apply_update sets system_instruction to "New prompt." before _update_settings + # runs, so the base should be the new value the user explicitly set. + self.assertEqual(service._base_system_instruction, "New prompt.") + expected = f"New prompt.\n\n{USER_TURN_COMPLETION_INSTRUCTIONS}" + self.assertEqual(service._settings.system_instruction, expected) + + if __name__ == "__main__": unittest.main() From 64155e8f0638721df82ebaf56582750d020bf071 Mon Sep 17 00:00:00 2001 From: Mark Backman Date: Sun, 8 Mar 2026 10:44:45 -0400 Subject: [PATCH 0864/1060] Add changelog for #3957 --- changelog/3957.fixed.md | 1 + 1 file changed, 1 insertion(+) create mode 100644 changelog/3957.fixed.md diff --git a/changelog/3957.fixed.md b/changelog/3957.fixed.md new file mode 100644 index 000000000..a501aecb1 --- /dev/null +++ b/changelog/3957.fixed.md @@ -0,0 +1 @@ +- Fixed turn completion instructions being injected as a context system message instead of using `system_instruction`. This caused warning spam when `system_instruction` was also set and didn't persist across full context updates. From 57c4d72bf016d215e85eff04eb18cd9fc30604c0 Mon Sep 17 00:00:00 2001 From: ajmeraharsh Date: Mon, 9 Mar 2026 02:51:35 +0400 Subject: [PATCH 0865/1060] fix(livekit): remove redundant self arg in on_call_state_updated event _on_call_state_updated passes (self, state) to _call_event_handler, but _run_handler already prepends self when invoking the handler. This causes handlers to receive 3 positional arguments instead of 2, making the on_call_state_updated event unusable. This aligns with how _on_first_participant_joined correctly passes only the data arg without self. --- src/pipecat/transports/livekit/transport.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/src/pipecat/transports/livekit/transport.py b/src/pipecat/transports/livekit/transport.py index 7e9c1de35..3fb3d1694 100644 --- a/src/pipecat/transports/livekit/transport.py +++ b/src/pipecat/transports/livekit/transport.py @@ -1244,7 +1244,7 @@ class LiveKitTransport(BaseTransport): async def _on_call_state_updated(self, state: str): """Handle call state update events.""" - await self._call_event_handler("on_call_state_updated", self, state) + await self._call_event_handler("on_call_state_updated", state) async def _on_first_participant_joined(self, participant_id: str): """Handle first participant joined events.""" From 1f8cc3d216b75d582f2ddc04b2ea968dc49d8b38 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Aleix=20Conchillo=20Flaqu=C3=A9?= Date: Fri, 6 Mar 2026 20:55:32 -0800 Subject: [PATCH 0866/1060] Expose on_summary_applied event on LLMAssistantAggregator Forward the on_summary_applied event from the internal summarizer to the aggregator so users can listen for it without accessing private members. Update summarization examples to use the new public event. --- .../54-context-summarization-openai.py | 19 ++++++-------- .../54a-context-summarization-google.py | 19 ++++++-------- ...54c-context-summarization-dedicated-llm.py | 19 ++++++-------- .../aggregators/llm_response_universal.py | 25 ++++++++++++++++++- 4 files changed, 48 insertions(+), 34 deletions(-) diff --git a/examples/foundational/54-context-summarization-openai.py b/examples/foundational/54-context-summarization-openai.py index 9c3f75fa5..4c3e10359 100644 --- a/examples/foundational/54-context-summarization-openai.py +++ b/examples/foundational/54-context-summarization-openai.py @@ -138,17 +138,14 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): ) # Listen for summarization events - summarizer = assistant_aggregator._summarizer - if summarizer: - - @summarizer.event_handler("on_summary_applied") - async def on_summary_applied(summarizer, event: SummaryAppliedEvent): - logger.info( - f"Context summarized: {event.original_message_count} messages -> " - f"{event.new_message_count} messages " - f"({event.summarized_message_count} summarized, " - f"{event.preserved_message_count} preserved)" - ) + @assistant_aggregator.event_handler("on_summary_applied") + async def on_summary_applied(aggregator, summarizer, event: SummaryAppliedEvent): + logger.info( + f"Context summarized: {event.original_message_count} messages -> " + f"{event.new_message_count} messages " + f"({event.summarized_message_count} summarized, " + f"{event.preserved_message_count} preserved)" + ) pipeline = Pipeline( [ diff --git a/examples/foundational/54a-context-summarization-google.py b/examples/foundational/54a-context-summarization-google.py index b9ce3d7c7..531708748 100644 --- a/examples/foundational/54a-context-summarization-google.py +++ b/examples/foundational/54a-context-summarization-google.py @@ -138,17 +138,14 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): ) # Listen for summarization events - summarizer = assistant_aggregator._summarizer - if summarizer: - - @summarizer.event_handler("on_summary_applied") - async def on_summary_applied(summarizer, event: SummaryAppliedEvent): - logger.info( - f"Context summarized: {event.original_message_count} messages -> " - f"{event.new_message_count} messages " - f"({event.summarized_message_count} summarized, " - f"{event.preserved_message_count} preserved)" - ) + @assistant_aggregator.event_handler("on_summary_applied") + async def on_summary_applied(aggregator, summarizer, event: SummaryAppliedEvent): + logger.info( + f"Context summarized: {event.original_message_count} messages -> " + f"{event.new_message_count} messages " + f"({event.summarized_message_count} summarized, " + f"{event.preserved_message_count} preserved)" + ) pipeline = Pipeline( [ diff --git a/examples/foundational/54c-context-summarization-dedicated-llm.py b/examples/foundational/54c-context-summarization-dedicated-llm.py index c3c4a0c2e..01b4e0862 100644 --- a/examples/foundational/54c-context-summarization-dedicated-llm.py +++ b/examples/foundational/54c-context-summarization-dedicated-llm.py @@ -177,17 +177,14 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): ) # Listen for summarization events - summarizer = assistant_aggregator._summarizer - if summarizer: - - @summarizer.event_handler("on_summary_applied") - async def on_summary_applied(summarizer, event: SummaryAppliedEvent): - logger.info( - f"Context summarized: {event.original_message_count} messages -> " - f"{event.new_message_count} messages " - f"({event.summarized_message_count} summarized, " - f"{event.preserved_message_count} preserved)" - ) + @assistant_aggregator.event_handler("on_summary_applied") + async def on_summary_applied(aggregator, summarizer, event: SummaryAppliedEvent): + logger.info( + f"Context summarized: {event.original_message_count} messages -> " + f"{event.new_message_count} messages " + f"({event.summarized_message_count} summarized, " + f"{event.preserved_message_count} preserved)" + ) pipeline = Pipeline( [ diff --git a/src/pipecat/processors/aggregators/llm_response_universal.py b/src/pipecat/processors/aggregators/llm_response_universal.py index cf6c81e5f..ca25650b4 100644 --- a/src/pipecat/processors/aggregators/llm_response_universal.py +++ b/src/pipecat/processors/aggregators/llm_response_universal.py @@ -70,7 +70,10 @@ from pipecat.processors.aggregators.llm_context import ( LLMSpecificMessage, NotGiven, ) -from pipecat.processors.aggregators.llm_context_summarizer import LLMContextSummarizer +from pipecat.processors.aggregators.llm_context_summarizer import ( + LLMContextSummarizer, + SummaryAppliedEvent, +) from pipecat.processors.frame_processor import FrameCallback, FrameDirection, FrameProcessor from pipecat.turns.user_idle_controller import UserIdleController from pipecat.turns.user_mute import BaseUserMuteStrategy @@ -796,6 +799,7 @@ class LLMAssistantAggregator(LLMContextAggregator): - on_assistant_turn_started: Called when the assistant turn starts - on_assistant_turn_stopped: Called when the assistant turn ends - on_assistant_thought: Called when an assistant thought is available + - on_summary_applied: Called when a context summarization is applied Example:: @@ -811,6 +815,10 @@ class LLMAssistantAggregator(LLMContextAggregator): async def on_assistant_thought(aggregator, message: AssistantThoughtMessage): ... + @aggregator.event_handler("on_summary_applied") + async def on_summary_applied(aggregator, summarizer, event: SummaryAppliedEvent): + ... + """ def __init__( @@ -873,10 +881,12 @@ class LLMAssistantAggregator(LLMContextAggregator): self._summarizer.add_event_handler( "on_request_summarization", self._on_request_summarization ) + self._summarizer.add_event_handler("on_summary_applied", self._on_summary_applied) self._register_event_handler("on_assistant_turn_started") self._register_event_handler("on_assistant_turn_stopped") self._register_event_handler("on_assistant_thought") + self._register_event_handler("on_summary_applied") @property def has_function_calls_in_progress(self) -> bool: @@ -1294,6 +1304,19 @@ class LLMAssistantAggregator(LLMContextAggregator): """ await self.push_frame(frame, FrameDirection.UPSTREAM) + async def _on_summary_applied( + self, summarizer: LLMContextSummarizer, event: SummaryAppliedEvent + ): + """Handle summary applied event from the summarizer. + + Forwards the event to any registered `on_summary_applied` handlers. + + Args: + summarizer: The summarizer that applied the summary. + event: The summary applied event. + """ + await self._call_event_handler("on_summary_applied", summarizer, event) + class LLMContextAggregatorPair: """Pair of LLM context aggregators for updating context with user and assistant messages.""" From 3b947b7844a110f09260d1f3b7185de3037b32e7 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Aleix=20Conchillo=20Flaqu=C3=A9?= Date: Fri, 6 Mar 2026 20:56:02 -0800 Subject: [PATCH 0867/1060] Add changelog for #3947 --- changelog/3947.added.md | 1 + 1 file changed, 1 insertion(+) create mode 100644 changelog/3947.added.md diff --git a/changelog/3947.added.md b/changelog/3947.added.md new file mode 100644 index 000000000..175cb87bd --- /dev/null +++ b/changelog/3947.added.md @@ -0,0 +1 @@ +- Exposed `on_summary_applied` event on `LLMAssistantAggregator`, allowing users to listen for context summarization events without accessing private members. From ae6f159b182932f92c5fbe21c79422249df407f9 Mon Sep 17 00:00:00 2001 From: ajmeraharsh Date: Mon, 9 Mar 2026 09:15:03 +0400 Subject: [PATCH 0868/1060] chore: add changelog entry for #3959 --- changelog/3959.fixed.md | 1 + 1 file changed, 1 insertion(+) create mode 100644 changelog/3959.fixed.md diff --git a/changelog/3959.fixed.md b/changelog/3959.fixed.md new file mode 100644 index 000000000..a10521d92 --- /dev/null +++ b/changelog/3959.fixed.md @@ -0,0 +1 @@ +- Fixed `on_call_state_updated` event handler in LiveKit transport receiving incorrect number of arguments due to redundant `self` passed to `_call_event_handler`. From 25165d6e2b221d0ca9b181ccac50c48650ef98ee Mon Sep 17 00:00:00 2001 From: filipi87 Date: Mon, 9 Mar 2026 09:47:45 -0300 Subject: [PATCH 0869/1060] Queuing the messages received before the data channel is ready to send them. --- src/pipecat/transports/smallwebrtc/connection.py | 13 +++++++++++-- 1 file changed, 11 insertions(+), 2 deletions(-) diff --git a/src/pipecat/transports/smallwebrtc/connection.py b/src/pipecat/transports/smallwebrtc/connection.py index b9b6538f1..bc990d736 100644 --- a/src/pipecat/transports/smallwebrtc/connection.py +++ b/src/pipecat/transports/smallwebrtc/connection.py @@ -283,6 +283,7 @@ class SmallWebRTCConnection(BaseObject): self._data_channel = None self._renegotiation_in_progress = False self._last_received_time = None + self._message_queue = [] self._pending_app_messages = [] self._connecting_timeout_task = None @@ -297,6 +298,7 @@ class SmallWebRTCConnection(BaseObject): @channel.on("open") async def on_open(): logger.debug("Data channel is open!") + self._flush_message_queue() @channel.on("message") async def on_message(message): @@ -499,6 +501,7 @@ class SmallWebRTCConnection(BaseObject): self._track_map.clear() if self._pc: await self._pc.close() + self._message_queue.clear() self._pending_app_messages.clear() self._track_map = {} self._cancel_monitoring_connecting_state() @@ -664,8 +667,14 @@ class SmallWebRTCConnection(BaseObject): if self._data_channel and self._data_channel.readyState == "open": self._data_channel.send(json_message) else: - # The client might choose never to create a data channel. - logger.trace("Data channel not ready, discarding message!") + logger.debug("Data channel not ready, queuing message") + self._message_queue.append(json_message) + + def _flush_message_queue(self): + logger.debug("Data channel is open, flushing queued messages") + while self._message_queue: + message = self._message_queue.pop(0) + self._data_channel.send(message) def ask_to_renegotiate(self): """Request renegotiation of the WebRTC connection.""" From 322e317a003ae162a5134f4287504bbcfa42fffa Mon Sep 17 00:00:00 2001 From: filipi87 Date: Mon, 9 Mar 2026 10:04:33 -0300 Subject: [PATCH 0870/1060] Adding guardrails in case the data channel is never established. --- .../transports/smallwebrtc/connection.py | 87 +++++++++++++++++-- 1 file changed, 81 insertions(+), 6 deletions(-) diff --git a/src/pipecat/transports/smallwebrtc/connection.py b/src/pipecat/transports/smallwebrtc/connection.py index bc990d736..0dcdd0eed 100644 --- a/src/pipecat/transports/smallwebrtc/connection.py +++ b/src/pipecat/transports/smallwebrtc/connection.py @@ -41,6 +41,11 @@ AUDIO_TRANSCEIVER_INDEX = 0 VIDEO_TRANSCEIVER_INDEX = 1 SCREEN_VIDEO_TRANSCEIVER_INDEX = 2 +# Maximum number of messages to queue while the data channel is not yet open. +MAX_MESSAGE_QUEUE_SIZE = 50 +# Seconds to wait for the data channel to open after the peer connection is established. +DATA_CHANNEL_TIMEOUT_SECS = 10 + class TrackStatusMessage(BaseModel): """Message for updating track enabled/disabled status. @@ -283,9 +288,11 @@ class SmallWebRTCConnection(BaseObject): self._data_channel = None self._renegotiation_in_progress = False self._last_received_time = None - self._message_queue = [] + self._outgoing_messages_queue = [] + self._data_channel_enabled = True self._pending_app_messages = [] self._connecting_timeout_task = None + self._data_channel_timeout_task = None def _setup_listeners(self): """Set up event listeners for the peer connection.""" @@ -501,10 +508,12 @@ class SmallWebRTCConnection(BaseObject): self._track_map.clear() if self._pc: await self._pc.close() - self._message_queue.clear() + self._outgoing_messages_queue.clear() + self._data_channel_enabled = True self._pending_app_messages.clear() self._track_map = {} self._cancel_monitoring_connecting_state() + self._cancel_data_channel_timeout() def get_answer(self): """Get the SDP answer for the current connection. @@ -553,6 +562,44 @@ class SmallWebRTCConnection(BaseObject): self._connecting_timeout_task.cancel() self._connecting_timeout_task = None + def _start_data_channel_timeout(self) -> None: + """Start a timeout to detect if the data channel fails to open after connection. + + Schedules a background task that fires ``DATA_CHANNEL_TIMEOUT_SECS`` seconds after + the peer connection reaches the *connected* state. If the data channel has not + opened by then, the queued messages are discarded, a warning is logged, and future + calls to :meth:`send_app_message` will silently drop messages instead of queuing + them (fall-back to "discard" mode). + + The task is automatically cancelled when the data channel opens successfully (see + :meth:`_flush_message_queue`) or when the connection is closed (see + :meth:`_close`). + """ + + async def timeout_handler(): + await asyncio.sleep(DATA_CHANNEL_TIMEOUT_SECS) + if not self._data_channel or self._data_channel.readyState != "open": + logger.warning( + f"Data channel not established within {DATA_CHANNEL_TIMEOUT_SECS}s after " + "connection. Clearing message queue and disabling future queueing." + ) + self._outgoing_messages_queue.clear() + self._data_channel_enabled = False + + self._data_channel_timeout_task = asyncio.create_task(timeout_handler()) + + def _cancel_data_channel_timeout(self) -> None: + """Cancel the data-channel open timeout task, if any. + + Should be called when the data channel opens successfully (the timeout is no longer + needed) or when the connection is being torn down. If the task is still pending it + will be cancelled and the reference cleared. + """ + if self._data_channel_timeout_task and not self._data_channel_timeout_task.done(): + logger.debug("Cancelling the data channel timeout task") + self._data_channel_timeout_task.cancel() + self._data_channel_timeout_task = None + async def _handle_new_connection_state(self): """Handle changes in the peer connection state.""" state = self._pc.connectionState @@ -561,6 +608,9 @@ class SmallWebRTCConnection(BaseObject): else: self._cancel_monitoring_connecting_state() + if state == "connected" and not self._data_channel_timeout_task: + self._start_data_channel_timeout() + if state == "connected" and not self._connect_invoked: # We are going to wait until the pipeline is ready before triggering the event return @@ -660,20 +710,45 @@ class SmallWebRTCConnection(BaseObject): def send_app_message(self, message: Any): """Send an application message through the data channel. + If the data channel is open the message is sent immediately. Otherwise, + the message is placed in an in-memory queue so it can be flushed once the + channel opens, subject to the following constraints: + + * Queueing is only attempted when ``_data_channel_enabled`` is ``True``. It is + set to ``False`` when the data-channel open timeout fires (see + :meth:`_start_data_channel_timeout`), after which messages are silently + discarded. + * The queue will not grow beyond ``MAX_MESSAGE_QUEUE_SIZE`` entries. + Messages that arrive when the queue is full are discarded with a warning. + Args: message: The message to send (will be JSON serialized). """ json_message = json.dumps(message) if self._data_channel and self._data_channel.readyState == "open": self._data_channel.send(json_message) + elif self._data_channel_enabled: + if len(self._outgoing_messages_queue) < MAX_MESSAGE_QUEUE_SIZE: + logger.debug("Data channel not ready, queuing message") + self._outgoing_messages_queue.append(json_message) + else: + logger.warning( + f"Message queue is full ({MAX_MESSAGE_QUEUE_SIZE} messages). Discarding message." + ) else: - logger.debug("Data channel not ready, queuing message") - self._message_queue.append(json_message) + logger.trace("Data channel unavailable and queueing disabled. Discarding message.") def _flush_message_queue(self): + """Flush all queued messages through the now-open data channel. + + Called when the data channel transitions to the *open* state. Cancels + the data-channel open timeout (it is no longer needed) and sends every + message that was buffered while the channel was unavailable. + """ + self._cancel_data_channel_timeout() logger.debug("Data channel is open, flushing queued messages") - while self._message_queue: - message = self._message_queue.pop(0) + while self._outgoing_messages_queue: + message = self._outgoing_messages_queue.pop(0) self._data_channel.send(message) def ask_to_renegotiate(self): From 74a06a6968bb7b1e992ececd5c1bc658c06a5211 Mon Sep 17 00:00:00 2001 From: filipi87 Date: Mon, 9 Mar 2026 10:06:38 -0300 Subject: [PATCH 0871/1060] Adding extra comment. --- src/pipecat/transports/smallwebrtc/connection.py | 1 + 1 file changed, 1 insertion(+) diff --git a/src/pipecat/transports/smallwebrtc/connection.py b/src/pipecat/transports/smallwebrtc/connection.py index 0dcdd0eed..3f0d6a9ee 100644 --- a/src/pipecat/transports/smallwebrtc/connection.py +++ b/src/pipecat/transports/smallwebrtc/connection.py @@ -736,6 +736,7 @@ class SmallWebRTCConnection(BaseObject): f"Message queue is full ({MAX_MESSAGE_QUEUE_SIZE} messages). Discarding message." ) else: + # The client might choose never to create a data channel. logger.trace("Data channel unavailable and queueing disabled. Discarding message.") def _flush_message_queue(self): From aa693bb5ee4057245402dab550426c99f1341579 Mon Sep 17 00:00:00 2001 From: filipi87 Date: Mon, 9 Mar 2026 10:11:40 -0300 Subject: [PATCH 0872/1060] Adding changelog entry for the SmallWebRTCConnection fix. --- changelog/3962.fixed.md | 1 + 1 file changed, 1 insertion(+) create mode 100644 changelog/3962.fixed.md diff --git a/changelog/3962.fixed.md b/changelog/3962.fixed.md new file mode 100644 index 000000000..1d326cd05 --- /dev/null +++ b/changelog/3962.fixed.md @@ -0,0 +1 @@ +- Fixed `SmallWebRTCConnection` silently discarding messages sent before the data channel is open by queuing them and flushing once the channel is ready. A bounded queue (`MAX_MESSAGE_QUEUE_SIZE = 50`) prevents unbounded memory growth, and a 10-second timeout after connection clears the queue and falls back to discard mode if the data channel never opens. From 4557ef8c42f3ba02cde1d48b0093995a7fd16337 Mon Sep 17 00:00:00 2001 From: filipi87 Date: Mon, 9 Mar 2026 10:16:02 -0300 Subject: [PATCH 0873/1060] Renaming method to _get_earliest_function_call_not_resolved_in_range --- src/pipecat/utils/context/llm_context_summarization.py | 8 +++++--- tests/test_context_summarization.py | 2 +- 2 files changed, 6 insertions(+), 4 deletions(-) diff --git a/src/pipecat/utils/context/llm_context_summarization.py b/src/pipecat/utils/context/llm_context_summarization.py index f7536cbaf..259d0bae5 100644 --- a/src/pipecat/utils/context/llm_context_summarization.py +++ b/src/pipecat/utils/context/llm_context_summarization.py @@ -382,7 +382,7 @@ class LLMContextSummarizationUtil: return total @staticmethod - def _get_function_calls_in_progress_index( + def _get_earliest_function_call_not_resolved_in_range( messages: List[dict], start_idx: int, summary_end: int ) -> int: """Find the earliest message index with incomplete function calls. @@ -491,8 +491,10 @@ class LLMContextSummarizationUtil: return LLMMessagesToSummarize(messages=[], last_summarized_index=-1) # Check for function calls in progress in the range we want to summarize - function_call_start = LLMContextSummarizationUtil._get_function_calls_in_progress_index( - messages, summary_start, summary_end + function_call_start = ( + LLMContextSummarizationUtil._get_earliest_function_call_not_resolved_in_range( + messages, summary_start, summary_end + ) ) if function_call_start >= 0 and function_call_start < summary_end: # Stop summarization before the function call diff --git a/tests/test_context_summarization.py b/tests/test_context_summarization.py index 454535bc0..f0d4ffc19 100644 --- a/tests/test_context_summarization.py +++ b/tests/test_context_summarization.py @@ -1168,7 +1168,7 @@ class TestLLMSpecificMessageHandling(unittest.TestCase): {"role": "tool", "tool_call_id": "call_123", "content": '{"time": "10:30 AM"}'}, ] - result = LLMContextSummarizationUtil._get_function_calls_in_progress_index( + result = LLMContextSummarizationUtil._get_earliest_function_call_not_resolved_in_range( messages, 0, len(messages) ) self.assertEqual(result, -1) From 097f9c089681738b67f1671ed828a1854ffde5e6 Mon Sep 17 00:00:00 2001 From: filipi87 Date: Mon, 9 Mar 2026 11:04:09 -0300 Subject: [PATCH 0874/1060] Fixed to push LLMAssistantPushAggregationFrame when the base TTSService class is responsible for pushing the TTSStoppedFrame. --- changelog/3936.fixed.md | 1 + src/pipecat/services/tts_service.py | 15 +++++---------- 2 files changed, 6 insertions(+), 10 deletions(-) create mode 100644 changelog/3936.fixed.md diff --git a/changelog/3936.fixed.md b/changelog/3936.fixed.md new file mode 100644 index 000000000..2d186ffd7 --- /dev/null +++ b/changelog/3936.fixed.md @@ -0,0 +1 @@ +- Fixed `TTSService` to push `LLMAssistantPushAggregationFrame` when the base class is responsible for pushing `TTSStoppedFrame`. diff --git a/src/pipecat/services/tts_service.py b/src/pipecat/services/tts_service.py index db695fd52..731b71581 100644 --- a/src/pipecat/services/tts_service.py +++ b/src/pipecat/services/tts_service.py @@ -768,6 +768,8 @@ class TTSService(AIService): # Clean up context when we see TTSStoppedFrame if isinstance(frame, TTSStoppedFrame) and frame.context_id: if frame.context_id in self._tts_contexts: + if self._tts_contexts[frame.context_id].push_assistant_aggregation: + await self.push_frame(LLMAssistantPushAggregationFrame()) logger.debug(f"{self} cleaning up TTS context {frame.context_id}") del self._tts_contexts[frame.context_id] @@ -1009,14 +1011,8 @@ class TTSService(AIService): # For services using the audio context we are appending to the context, so it preserves the ordering. if self.audio_context_available(context_id): await self.append_to_audio_context(context_id, frame) - if push_assistant_aggregation: - await self.append_to_audio_context( - context_id, LLMAssistantPushAggregationFrame() - ) else: await self.push_frame(frame) - if push_assistant_aggregation: - await self.push_frame(LLMAssistantPushAggregationFrame()) async def tts_process_generator( self, context_id: str, generator: AsyncGenerator[Frame | None, None] @@ -1047,18 +1043,20 @@ class TTSService(AIService): async def _stop_frame_handler(self): has_started = False + context_id = None while True: try: frame = await asyncio.wait_for( self._stop_frame_queue.get(), timeout=self._stop_frame_timeout_s ) + context_id = frame.context_id if isinstance(frame, TTSStartedFrame): has_started = True elif isinstance(frame, (TTSStoppedFrame, InterruptionFrame)): has_started = False except asyncio.TimeoutError: if has_started: - await self.push_frame(TTSStoppedFrame()) + await self.push_frame(TTSStoppedFrame(context_id=context_id)) has_started = False # @@ -1142,9 +1140,6 @@ class TTSService(AIService): frame.pts = self._word_last_pts frame.context_id = context_id await self.push_frame(frame) - if context_id in self._tts_contexts: - if self._tts_contexts[context_id].push_assistant_aggregation: - await self.push_frame(LLMAssistantPushAggregationFrame()) else: ts_ns = seconds_to_nanoseconds(timestamp) if self._initial_word_timestamp == -1: From c5ce667387b110f02bb856d9e5e492ef3e66bb53 Mon Sep 17 00:00:00 2001 From: filipi87 Date: Mon, 9 Mar 2026 11:10:42 -0300 Subject: [PATCH 0875/1060] Retrieving the context_id from the TTSStartedFrame --- src/pipecat/services/tts_service.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/src/pipecat/services/tts_service.py b/src/pipecat/services/tts_service.py index 731b71581..25a4c2735 100644 --- a/src/pipecat/services/tts_service.py +++ b/src/pipecat/services/tts_service.py @@ -1049,8 +1049,8 @@ class TTSService(AIService): frame = await asyncio.wait_for( self._stop_frame_queue.get(), timeout=self._stop_frame_timeout_s ) - context_id = frame.context_id if isinstance(frame, TTSStartedFrame): + context_id = frame.context_id has_started = True elif isinstance(frame, (TTSStoppedFrame, InterruptionFrame)): has_started = False From f7dc13c0ded43eeca63ae32de1ef849e95be5fd6 Mon Sep 17 00:00:00 2001 From: Mark Backman Date: Mon, 9 Mar 2026 10:24:24 -0400 Subject: [PATCH 0876/1060] Update COMMUNITY_INTEGRATIONS.md for Settings alias class --- COMMUNITY_INTEGRATIONS.md | 9 ++++++--- 1 file changed, 6 insertions(+), 3 deletions(-) diff --git a/COMMUNITY_INTEGRATIONS.md b/COMMUNITY_INTEGRATIONS.md index e17c72bc7..f6f92a5d3 100644 --- a/COMMUNITY_INTEGRATIONS.md +++ b/COMMUNITY_INTEGRATIONS.md @@ -271,12 +271,15 @@ The rule of thumb: if a caller might send an update frame to change it at runtim #### Wiring settings into `__init__` -Accept an **optional** `settings` parameter. Build a `default_settings` object with all fields set to real values, then merge any caller overrides with `apply_update`: +Accept an **optional** `settings` parameter. Build a `default_settings` object with all fields set to real values, then merge any caller overrides with `apply_update`. + +Add a `Settings` **class attribute** that points to your settings dataclass. This lets callers access the settings class through the service itself (e.g. `MyTTSService.Settings(...)`) without a separate import: ```python from typing import Optional class MyTTSService(TTSService): + Settings = MyTTSSettings _settings: MyTTSSettings def __init__( @@ -311,10 +314,10 @@ This pattern lets callers override only what they care about: # Uses all defaults svc = MyTTSService(api_key="sk-xxx") -# Overrides just the voice +# Overrides just the voice — access Settings through the service class svc = MyTTSService( api_key="sk-xxx", - settings=MyTTSSettings(voice="custom-voice"), + settings=MyTTSService.Settings(voice="custom-voice"), ) ``` From ba87d1609cce06ba3b3ced10c16feebf76d2b241 Mon Sep 17 00:00:00 2001 From: filipi87 Date: Mon, 9 Mar 2026 11:24:36 -0300 Subject: [PATCH 0877/1060] Only marking self._is_yielding_frames_synchronously if receiving TTSAudioRawFrame --- src/pipecat/services/tts_service.py | 4 +++- 1 file changed, 3 insertions(+), 1 deletion(-) diff --git a/src/pipecat/services/tts_service.py b/src/pipecat/services/tts_service.py index 25a4c2735..6a04062e5 100644 --- a/src/pipecat/services/tts_service.py +++ b/src/pipecat/services/tts_service.py @@ -1038,7 +1038,9 @@ class TTSService(AIService): async for frame in generator: if frame: await self.append_to_audio_context(context_id, frame) - is_yielding_frames = True + if isinstance(frame, TTSAudioRawFrame): + is_yielding_frames = True + self._is_yielding_frames_synchronously = is_yielding_frames async def _stop_frame_handler(self): From 8ec160f71e36a9f25a65db8528950d41f7a2f9ed Mon Sep 17 00:00:00 2001 From: filipi87 Date: Mon, 9 Mar 2026 11:37:11 -0300 Subject: [PATCH 0878/1060] Making the changelog more user friendly. --- changelog/3936.fixed.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/changelog/3936.fixed.md b/changelog/3936.fixed.md index 2d186ffd7..27e48815c 100644 --- a/changelog/3936.fixed.md +++ b/changelog/3936.fixed.md @@ -1 +1 @@ -- Fixed `TTSService` to push `LLMAssistantPushAggregationFrame` when the base class is responsible for pushing `TTSStoppedFrame`. +- Fixed TTS context not being appended to the assistant message history when using `TTSSpeakFrame` with `append_to_context=True` with some TTS providers. From 7f9169269c0d465fc562c0fe65d3ded7f4c5b9cb Mon Sep 17 00:00:00 2001 From: Paul Kompfner Date: Mon, 9 Mar 2026 10:45:33 -0400 Subject: [PATCH 0879/1060] Improve changelog skill: prioritize user-facing language and update example changelog --- .claude/skills/changelog/SKILL.md | 16 +++++++++++++++- changelog/3953.added.md | 2 +- 2 files changed, 16 insertions(+), 2 deletions(-) diff --git a/.claude/skills/changelog/SKILL.md b/.claude/skills/changelog/SKILL.md index 1ef8f324e..4ef6a8dc2 100644 --- a/.claude/skills/changelog/SKILL.md +++ b/.claude/skills/changelog/SKILL.md @@ -32,6 +32,20 @@ Create changelog files for the important commits in this PR. The PR number is pr 6. Use ⚠️ emoji prefix for breaking changes. +7. **Write changes in user-facing terms first.** Lead with what users of the framework will notice: new APIs, changed behavior, new parameters, fixed bugs they might have hit, etc. Implementation details (internal refactoring, how something is wired up under the hood) can be included as secondary context after the user-facing description, but should never be the *only* content of a changelog entry when there is a user-visible effect. + + **Good** (user-facing first, implementation detail as context): + ``` + - Turn completion instructions now persist correctly across full context updates when using `system_instruction`. Previously they were injected as a context system message, which caused warning spam and didn't survive context updates. + ``` + + **Bad** (implementation detail only, no user-facing framing): + ``` + - Fixed turn completion instructions being injected as a context system message instead of using `system_instruction`. + ``` + + Ask yourself: "If I'm a developer building on Pipecat, what would I notice changed?" Start there. + ## Example For PR #3519 with a new feature and a bug fix: @@ -43,5 +57,5 @@ For PR #3519 with a new feature and a bug fix: `changelog/3519.fixed.md`: ``` -- Fixed an issue where something was not working correctly. +- Fixed an issue where something was not working correctly in some user-visible scenario. The root cause was an internal implementation detail. ``` diff --git a/changelog/3953.added.md b/changelog/3953.added.md index d540ff125..f30c31733 100644 --- a/changelog/3953.added.md +++ b/changelog/3953.added.md @@ -1 +1 @@ -- Added on-the-fly `Configure` support for `DeepgramFluxSTTService`. The `keyterm`, `eot_threshold`, `eager_eot_threshold`, and `eot_timeout_ms` settings can now be updated mid-stream via `STTUpdateSettingsFrame` without requiring a WebSocket reconnect. +- Deepgram Flux STT settings (`keyterm`, `eot_threshold`, `eager_eot_threshold`, `eot_timeout_ms`) can now be updated mid-stream via `STTUpdateSettingsFrame` without triggering a reconnect. The new values are sent to Deepgram as a Configure WebSocket message on the existing connection. From f0c5925a79bcdfead695fad126a22c956edd5a06 Mon Sep 17 00:00:00 2001 From: filipi87 Date: Mon, 9 Mar 2026 12:07:45 -0300 Subject: [PATCH 0880/1060] Fixing Piper test. --- src/pipecat/services/piper/tts.py | 2 ++ tests/test_piper_tts.py | 2 +- 2 files changed, 3 insertions(+), 1 deletion(-) diff --git a/src/pipecat/services/piper/tts.py b/src/pipecat/services/piper/tts.py index fb7b627cd..53990ff2e 100644 --- a/src/pipecat/services/piper/tts.py +++ b/src/pipecat/services/piper/tts.py @@ -17,6 +17,7 @@ from loguru import logger from pipecat.frames.frames import ( ErrorFrame, Frame, + TTSStoppedFrame, ) from pipecat.services.settings import TTSSettings, _warn_deprecated_param from pipecat.services.tts_service import TTSService @@ -287,6 +288,7 @@ class PiperHttpTTSService(TTSService): yield ErrorFrame( error=f"Error getting audio (status: {response.status}, error: {error})" ) + yield TTSStoppedFrame(context_id=context_id) return await self.start_tts_usage_metrics(text) diff --git a/tests/test_piper_tts.py b/tests/test_piper_tts.py index 2b1dae577..3b822f07c 100644 --- a/tests/test_piper_tts.py +++ b/tests/test_piper_tts.py @@ -136,7 +136,7 @@ async def test_run_piper_tts_error(aiohttp_client): TTSSpeakFrame(text="Error case.", append_to_context=False), ] - expected_down_frames = [AggregatedTextFrame, TTSStartedFrame, TTSTextFrame, TTSStoppedFrame] + expected_down_frames = [AggregatedTextFrame, TTSStartedFrame, TTSStoppedFrame, TTSTextFrame] expected_up_frames = [ErrorFrame] From f1bb065823366c8ca89726ea884e8523308ec1bc Mon Sep 17 00:00:00 2001 From: Paul Kompfner Date: Mon, 9 Mar 2026 11:52:10 -0400 Subject: [PATCH 0881/1060] Add missing 55-* update-settings examples for Piper TTS, Kokoro TTS, Whisper STT, and Whisper MLX STT Also fix 13e-whisper-mlx.py to pass MLXModel.LARGE_V3_TURBO.value instead of the enum directly. --- examples/foundational/13e-whisper-mlx.py | 2 +- .../55t-update-settings-piper-http-tts.py | 133 +++++++++++++++++ .../55t-update-settings-piper-tts.py | 129 +++++++++++++++++ .../55zg-update-settings-kokoro-tts.py | 126 ++++++++++++++++ .../55zs-update-settings-whisper-mlx-stt.py | 137 ++++++++++++++++++ .../55zs-update-settings-whisper-stt.py | 136 +++++++++++++++++ 6 files changed, 662 insertions(+), 1 deletion(-) create mode 100644 examples/foundational/55t-update-settings-piper-http-tts.py create mode 100644 examples/foundational/55t-update-settings-piper-tts.py create mode 100644 examples/foundational/55zg-update-settings-kokoro-tts.py create mode 100644 examples/foundational/55zs-update-settings-whisper-mlx-stt.py create mode 100644 examples/foundational/55zs-update-settings-whisper-stt.py diff --git a/examples/foundational/13e-whisper-mlx.py b/examples/foundational/13e-whisper-mlx.py index 211695a3a..f4721a86a 100644 --- a/examples/foundational/13e-whisper-mlx.py +++ b/examples/foundational/13e-whisper-mlx.py @@ -79,7 +79,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): stt = WhisperSTTServiceMLX( settings=WhisperSTTServiceMLX.Settings( - model=MLXModel.LARGE_V3_TURBO, + model=MLXModel.LARGE_V3_TURBO.value, ), ) diff --git a/examples/foundational/55t-update-settings-piper-http-tts.py b/examples/foundational/55t-update-settings-piper-http-tts.py new file mode 100644 index 000000000..0b208ccbc --- /dev/null +++ b/examples/foundational/55t-update-settings-piper-http-tts.py @@ -0,0 +1,133 @@ +# +# Copyright (c) 2024-2026, Daily +# +# SPDX-License-Identifier: BSD 2-Clause License +# + +import asyncio +import os + +import aiohttp +from dotenv import load_dotenv +from loguru import logger + +from pipecat.audio.vad.silero import SileroVADAnalyzer +from pipecat.frames.frames import LLMRunFrame, TTSUpdateSettingsFrame +from pipecat.pipeline.pipeline import Pipeline +from pipecat.pipeline.runner import PipelineRunner +from pipecat.pipeline.task import PipelineParams, PipelineTask +from pipecat.processors.aggregators.llm_context import LLMContext +from pipecat.processors.aggregators.llm_response_universal import ( + LLMContextAggregatorPair, + LLMUserAggregatorParams, +) +from pipecat.runner.types import RunnerArguments +from pipecat.runner.utils import create_transport +from pipecat.services.deepgram.stt import DeepgramSTTService +from pipecat.services.openai.llm import OpenAILLMService +from pipecat.services.piper.tts import PiperHttpTTSService +from pipecat.transports.base_transport import BaseTransport, TransportParams +from pipecat.transports.daily.transport import DailyParams +from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams + +load_dotenv(override=True) + + +transport_params = { + "daily": lambda: DailyParams( + audio_in_enabled=True, + audio_out_enabled=True, + ), + "twilio": lambda: FastAPIWebsocketParams( + audio_in_enabled=True, + audio_out_enabled=True, + ), + "webrtc": lambda: TransportParams( + audio_in_enabled=True, + audio_out_enabled=True, + ), +} + + +async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): + logger.info(f"Starting bot") + + async with aiohttp.ClientSession() as session: + stt = DeepgramSTTService(api_key=os.getenv("DEEPGRAM_API_KEY")) + + tts = PiperHttpTTSService( + base_url=os.getenv("PIPER_BASE_URL"), + aiohttp_session=session, + settings=PiperHttpTTSService.Settings(voice="en_US-ryan-high"), + ) + + llm = OpenAILLMService( + api_key=os.getenv("OPENAI_API_KEY"), + settings=OpenAILLMService.Settings( + system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + ), + ) + + context = LLMContext() + user_aggregator, assistant_aggregator = LLMContextAggregatorPair( + context, + user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()), + ) + + pipeline = Pipeline( + [ + transport.input(), + stt, + user_aggregator, + llm, + tts, + transport.output(), + assistant_aggregator, + ] + ) + + task = PipelineTask( + pipeline, + params=PipelineParams( + enable_metrics=True, + enable_usage_metrics=True, + ), + idle_timeout_secs=runner_args.pipeline_idle_timeout_secs, + ) + + @transport.event_handler("on_client_connected") + async def on_client_connected(transport, client): + logger.info(f"Client connected") + context.add_message( + {"role": "user", "content": "Please introduce yourself to the user."} + ) + await task.queue_frames([LLMRunFrame()]) + + await asyncio.sleep(10) + logger.info('Updating Piper HTTP TTS settings: voice="en_US-lessac-medium"') + await task.queue_frame( + TTSUpdateSettingsFrame( + delta=PiperHttpTTSService.Settings(voice="en_US-lessac-medium") + ) + ) + + @transport.event_handler("on_client_disconnected") + async def on_client_disconnected(transport, client): + logger.info(f"Client disconnected") + await task.cancel() + + runner = PipelineRunner(handle_sigint=runner_args.handle_sigint) + + await runner.run(task) + + +async def bot(runner_args: RunnerArguments): + """Main bot entry point compatible with Pipecat Cloud.""" + transport = await create_transport(runner_args, transport_params) + await run_bot(transport, runner_args) + + +if __name__ == "__main__": + from pipecat.runner.run import main + + main() diff --git a/examples/foundational/55t-update-settings-piper-tts.py b/examples/foundational/55t-update-settings-piper-tts.py new file mode 100644 index 000000000..6e9d79a72 --- /dev/null +++ b/examples/foundational/55t-update-settings-piper-tts.py @@ -0,0 +1,129 @@ +# +# Copyright (c) 2024-2026, Daily +# +# SPDX-License-Identifier: BSD 2-Clause License +# + +import asyncio +import os + +from dotenv import load_dotenv +from loguru import logger + +from pipecat.audio.vad.silero import SileroVADAnalyzer +from pipecat.frames.frames import LLMRunFrame, TTSUpdateSettingsFrame +from pipecat.pipeline.pipeline import Pipeline +from pipecat.pipeline.runner import PipelineRunner +from pipecat.pipeline.task import PipelineParams, PipelineTask +from pipecat.processors.aggregators.llm_context import LLMContext +from pipecat.processors.aggregators.llm_response_universal import ( + LLMContextAggregatorPair, + LLMUserAggregatorParams, +) +from pipecat.runner.types import RunnerArguments +from pipecat.runner.utils import create_transport +from pipecat.services.deepgram.stt import DeepgramSTTService +from pipecat.services.openai.llm import OpenAILLMService +from pipecat.services.piper.tts import PiperTTSService +from pipecat.transports.base_transport import BaseTransport, TransportParams +from pipecat.transports.daily.transport import DailyParams +from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams + +load_dotenv(override=True) + +transport_params = { + "daily": lambda: DailyParams( + audio_in_enabled=True, + audio_out_enabled=True, + ), + "twilio": lambda: FastAPIWebsocketParams( + audio_in_enabled=True, + audio_out_enabled=True, + ), + "webrtc": lambda: TransportParams( + audio_in_enabled=True, + audio_out_enabled=True, + ), +} + + +async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): + logger.info(f"Starting bot") + + stt = DeepgramSTTService(api_key=os.getenv("DEEPGRAM_API_KEY")) + + tts = PiperTTSService( + settings=PiperTTSService.Settings( + voice="en_US-ryan-high", + ), + ) + + llm = OpenAILLMService( + api_key=os.getenv("OPENAI_API_KEY"), + settings=OpenAILLMService.Settings( + system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + ), + ) + + context = LLMContext() + user_aggregator, assistant_aggregator = LLMContextAggregatorPair( + context, + user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()), + ) + + pipeline = Pipeline( + [ + transport.input(), + stt, + user_aggregator, + llm, + tts, + transport.output(), + assistant_aggregator, + ] + ) + + task = PipelineTask( + pipeline, + params=PipelineParams( + enable_metrics=True, + enable_usage_metrics=True, + ), + idle_timeout_secs=runner_args.pipeline_idle_timeout_secs, + ) + + @transport.event_handler("on_client_connected") + async def on_client_connected(transport, client): + logger.info(f"Client connected") + context.add_message({"role": "user", "content": "Please introduce yourself to the user."}) + await task.queue_frames([LLMRunFrame()]) + + # NOTE: Local Piper loads the voice model once at init, so runtime voice + # changes are not applied. This update will log an "unhandled settings" + # warning. Use PiperHttpTTSService for dynamic voice switching. + await asyncio.sleep(10) + logger.info('Updating Piper TTS settings: voice="en_US-lessac-medium"') + await task.queue_frame( + TTSUpdateSettingsFrame(delta=PiperTTSService.Settings(voice="en_US-lessac-medium")) + ) + + @transport.event_handler("on_client_disconnected") + async def on_client_disconnected(transport, client): + logger.info(f"Client disconnected") + await task.cancel() + + runner = PipelineRunner(handle_sigint=runner_args.handle_sigint) + + await runner.run(task) + + +async def bot(runner_args: RunnerArguments): + """Main bot entry point compatible with Pipecat Cloud.""" + transport = await create_transport(runner_args, transport_params) + await run_bot(transport, runner_args) + + +if __name__ == "__main__": + from pipecat.runner.run import main + + main() diff --git a/examples/foundational/55zg-update-settings-kokoro-tts.py b/examples/foundational/55zg-update-settings-kokoro-tts.py new file mode 100644 index 000000000..69fb14512 --- /dev/null +++ b/examples/foundational/55zg-update-settings-kokoro-tts.py @@ -0,0 +1,126 @@ +# +# Copyright (c) 2024-2026, Daily +# +# SPDX-License-Identifier: BSD 2-Clause License +# + +import asyncio +import os + +from dotenv import load_dotenv +from loguru import logger + +from pipecat.audio.vad.silero import SileroVADAnalyzer +from pipecat.frames.frames import LLMRunFrame, TTSUpdateSettingsFrame +from pipecat.pipeline.pipeline import Pipeline +from pipecat.pipeline.runner import PipelineRunner +from pipecat.pipeline.task import PipelineParams, PipelineTask +from pipecat.processors.aggregators.llm_context import LLMContext +from pipecat.processors.aggregators.llm_response_universal import ( + LLMContextAggregatorPair, + LLMUserAggregatorParams, +) +from pipecat.runner.types import RunnerArguments +from pipecat.runner.utils import create_transport +from pipecat.services.deepgram.stt import DeepgramSTTService +from pipecat.services.kokoro.tts import KokoroTTSService +from pipecat.services.openai.llm import OpenAILLMService +from pipecat.transports.base_transport import BaseTransport, TransportParams +from pipecat.transports.daily.transport import DailyParams +from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams + +load_dotenv(override=True) + +transport_params = { + "daily": lambda: DailyParams( + audio_in_enabled=True, + audio_out_enabled=True, + ), + "twilio": lambda: FastAPIWebsocketParams( + audio_in_enabled=True, + audio_out_enabled=True, + ), + "webrtc": lambda: TransportParams( + audio_in_enabled=True, + audio_out_enabled=True, + ), +} + + +async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): + logger.info(f"Starting bot") + + stt = DeepgramSTTService(api_key=os.getenv("DEEPGRAM_API_KEY")) + + tts = KokoroTTSService( + settings=KokoroTTSService.Settings( + voice="af_heart", + ), + ) + + llm = OpenAILLMService( + api_key=os.getenv("OPENAI_API_KEY"), + settings=OpenAILLMService.Settings( + system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + ), + ) + + context = LLMContext() + user_aggregator, assistant_aggregator = LLMContextAggregatorPair( + context, + user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()), + ) + + pipeline = Pipeline( + [ + transport.input(), + stt, + user_aggregator, + llm, + tts, + transport.output(), + assistant_aggregator, + ] + ) + + task = PipelineTask( + pipeline, + params=PipelineParams( + enable_metrics=True, + enable_usage_metrics=True, + ), + idle_timeout_secs=runner_args.pipeline_idle_timeout_secs, + ) + + @transport.event_handler("on_client_connected") + async def on_client_connected(transport, client): + logger.info(f"Client connected") + context.add_message({"role": "user", "content": "Please introduce yourself to the user."}) + await task.queue_frames([LLMRunFrame()]) + + await asyncio.sleep(10) + logger.info('Updating Kokoro TTS settings: voice="am_adam"') + await task.queue_frame( + TTSUpdateSettingsFrame(delta=KokoroTTSService.Settings(voice="am_adam")) + ) + + @transport.event_handler("on_client_disconnected") + async def on_client_disconnected(transport, client): + logger.info(f"Client disconnected") + await task.cancel() + + runner = PipelineRunner(handle_sigint=runner_args.handle_sigint) + + await runner.run(task) + + +async def bot(runner_args: RunnerArguments): + """Main bot entry point compatible with Pipecat Cloud.""" + transport = await create_transport(runner_args, transport_params) + await run_bot(transport, runner_args) + + +if __name__ == "__main__": + from pipecat.runner.run import main + + main() diff --git a/examples/foundational/55zs-update-settings-whisper-mlx-stt.py b/examples/foundational/55zs-update-settings-whisper-mlx-stt.py new file mode 100644 index 000000000..a3ca78f8c --- /dev/null +++ b/examples/foundational/55zs-update-settings-whisper-mlx-stt.py @@ -0,0 +1,137 @@ +# +# Copyright (c) 2024-2026, Daily +# +# SPDX-License-Identifier: BSD 2-Clause License +# + +import asyncio +import os + +from dotenv import load_dotenv +from loguru import logger + +from pipecat.audio.vad.silero import SileroVADAnalyzer +from pipecat.frames.frames import LLMRunFrame, STTUpdateSettingsFrame +from pipecat.pipeline.pipeline import Pipeline +from pipecat.pipeline.runner import PipelineRunner +from pipecat.pipeline.task import PipelineParams, PipelineTask +from pipecat.processors.aggregators.llm_context import LLMContext +from pipecat.processors.aggregators.llm_response_universal import ( + LLMContextAggregatorPair, + LLMUserAggregatorParams, +) +from pipecat.runner.types import RunnerArguments +from pipecat.runner.utils import create_transport +from pipecat.services.cartesia.tts import CartesiaTTSService +from pipecat.services.openai.llm import OpenAILLMService +from pipecat.services.whisper.stt import MLXModel, WhisperSTTServiceMLX +from pipecat.transcriptions.language import Language +from pipecat.transports.base_transport import BaseTransport, TransportParams +from pipecat.transports.daily.transport import DailyParams +from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams + +load_dotenv(override=True) + +transport_params = { + "daily": lambda: DailyParams( + audio_in_enabled=True, + audio_out_enabled=True, + ), + "twilio": lambda: FastAPIWebsocketParams( + audio_in_enabled=True, + audio_out_enabled=True, + ), + "webrtc": lambda: TransportParams( + audio_in_enabled=True, + audio_out_enabled=True, + ), +} + + +async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): + logger.info(f"Starting bot") + + stt = WhisperSTTServiceMLX( + settings=WhisperSTTServiceMLX.Settings( + model=MLXModel.LARGE_V3_TURBO.value, + ), + ) + + tts = CartesiaTTSService( + api_key=os.getenv("CARTESIA_API_KEY"), + settings=CartesiaTTSService.Settings( + voice="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady + ), + ) + + llm = OpenAILLMService( + api_key=os.getenv("OPENAI_API_KEY"), + settings=OpenAILLMService.Settings( + system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + ), + ) + + context = LLMContext() + user_aggregator, assistant_aggregator = LLMContextAggregatorPair( + context, + user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()), + ) + + pipeline = Pipeline( + [ + transport.input(), + stt, + user_aggregator, + llm, + tts, + transport.output(), + assistant_aggregator, + ] + ) + + task = PipelineTask( + pipeline, + params=PipelineParams( + enable_metrics=True, + enable_usage_metrics=True, + ), + idle_timeout_secs=runner_args.pipeline_idle_timeout_secs, + ) + + @transport.event_handler("on_client_connected") + async def on_client_connected(transport, client): + logger.info(f"Client connected") + context.add_message({"role": "user", "content": "Please introduce yourself to the user."}) + await task.queue_frames([LLMRunFrame()]) + + # NOTE: after this change, the bot will only respond if you speak Spanish + await asyncio.sleep(10) + logger.info("Updating Whisper MLX STT settings: model=TINY") + await task.queue_frame( + STTUpdateSettingsFrame( + delta=WhisperSTTServiceMLX.Settings( + model=MLXModel.TINY.value, + ) + ) + ) + + @transport.event_handler("on_client_disconnected") + async def on_client_disconnected(transport, client): + logger.info(f"Client disconnected") + await task.cancel() + + runner = PipelineRunner(handle_sigint=runner_args.handle_sigint) + + await runner.run(task) + + +async def bot(runner_args: RunnerArguments): + """Main bot entry point compatible with Pipecat Cloud.""" + transport = await create_transport(runner_args, transport_params) + await run_bot(transport, runner_args) + + +if __name__ == "__main__": + from pipecat.runner.run import main + + main() diff --git a/examples/foundational/55zs-update-settings-whisper-stt.py b/examples/foundational/55zs-update-settings-whisper-stt.py new file mode 100644 index 000000000..b58e86dbf --- /dev/null +++ b/examples/foundational/55zs-update-settings-whisper-stt.py @@ -0,0 +1,136 @@ +# +# Copyright (c) 2024-2026, Daily +# +# SPDX-License-Identifier: BSD 2-Clause License +# + +import asyncio +import os + +from dotenv import load_dotenv +from loguru import logger + +from pipecat.audio.vad.silero import SileroVADAnalyzer +from pipecat.frames.frames import LLMRunFrame, STTUpdateSettingsFrame +from pipecat.pipeline.pipeline import Pipeline +from pipecat.pipeline.runner import PipelineRunner +from pipecat.pipeline.task import PipelineParams, PipelineTask +from pipecat.processors.aggregators.llm_context import LLMContext +from pipecat.processors.aggregators.llm_response_universal import ( + LLMContextAggregatorPair, + LLMUserAggregatorParams, +) +from pipecat.runner.types import RunnerArguments +from pipecat.runner.utils import create_transport +from pipecat.services.cartesia.tts import CartesiaTTSService +from pipecat.services.openai.llm import OpenAILLMService +from pipecat.services.whisper.stt import Model, WhisperSTTService +from pipecat.transcriptions.language import Language +from pipecat.transports.base_transport import BaseTransport, TransportParams +from pipecat.transports.daily.transport import DailyParams +from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams + +load_dotenv(override=True) + +transport_params = { + "daily": lambda: DailyParams( + audio_in_enabled=True, + audio_out_enabled=True, + ), + "twilio": lambda: FastAPIWebsocketParams( + audio_in_enabled=True, + audio_out_enabled=True, + ), + "webrtc": lambda: TransportParams( + audio_in_enabled=True, + audio_out_enabled=True, + ), +} + + +async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): + logger.info(f"Starting bot") + + stt = WhisperSTTService( + settings=WhisperSTTService.Settings( + model=Model.DISTIL_MEDIUM_EN.value, + ), + ) + + tts = CartesiaTTSService( + api_key=os.getenv("CARTESIA_API_KEY"), + settings=CartesiaTTSService.Settings( + voice="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady + ), + ) + + llm = OpenAILLMService( + api_key=os.getenv("OPENAI_API_KEY"), + settings=OpenAILLMService.Settings( + system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + ), + ) + + context = LLMContext() + user_aggregator, assistant_aggregator = LLMContextAggregatorPair( + context, + user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()), + ) + + pipeline = Pipeline( + [ + transport.input(), + stt, + user_aggregator, + llm, + tts, + transport.output(), + assistant_aggregator, + ] + ) + + task = PipelineTask( + pipeline, + params=PipelineParams( + enable_metrics=True, + enable_usage_metrics=True, + ), + idle_timeout_secs=runner_args.pipeline_idle_timeout_secs, + ) + + @transport.event_handler("on_client_connected") + async def on_client_connected(transport, client): + logger.info(f"Client connected") + context.add_message({"role": "user", "content": "Please introduce yourself to the user."}) + await task.queue_frames([LLMRunFrame()]) + + await asyncio.sleep(10) + logger.info("Updating Whisper STT settings: model=LARGE") + await task.queue_frame( + STTUpdateSettingsFrame( + delta=WhisperSTTService.Settings( + model=Model.LARGE.value, + ) + ) + ) + + @transport.event_handler("on_client_disconnected") + async def on_client_disconnected(transport, client): + logger.info(f"Client disconnected") + await task.cancel() + + runner = PipelineRunner(handle_sigint=runner_args.handle_sigint) + + await runner.run(task) + + +async def bot(runner_args: RunnerArguments): + """Main bot entry point compatible with Pipecat Cloud.""" + transport = await create_transport(runner_args, transport_params) + await run_bot(transport, runner_args) + + +if __name__ == "__main__": + from pipecat.runner.run import main + + main() From 9423d22051ee522d84168480ca6211d8ab432521 Mon Sep 17 00:00:00 2001 From: Paul Kompfner Date: Mon, 9 Mar 2026 12:07:18 -0400 Subject: [PATCH 0882/1060] Fix broken `test_unified_function_calling_anthropic` due to use of an unsupported/deprecated model. Update the tests in test_integration_unified_function_calling.py to not specify particular models but instead just use service defaults (the tests shouldn't be model-dependent anyway) --- .../test_integration_unified_function_calling.py | 6 ++---- 1 file changed, 2 insertions(+), 4 deletions(-) diff --git a/tests/integration/test_integration_unified_function_calling.py b/tests/integration/test_integration_unified_function_calling.py index 552c839a5..a282ba611 100644 --- a/tests/integration/test_integration_unified_function_calling.py +++ b/tests/integration/test_integration_unified_function_calling.py @@ -88,7 +88,7 @@ async def test_unified_function_calling_openai(): @pytest.mark.skipif(os.getenv("GOOGLE_API_KEY") is None, reason="GOOGLE_API_KEY is not set") @pytest.mark.asyncio async def test_unified_function_calling_gemini(): - llm = GoogleLLMService(api_key=os.getenv("GOOGLE_API_KEY"), model="gemini-2.0-flash-001") + llm = GoogleLLMService(api_key=os.getenv("GOOGLE_API_KEY")) # This will fail if an exception is raised await _test_llm_function_calling(llm) @@ -96,8 +96,6 @@ async def test_unified_function_calling_gemini(): @pytest.mark.skipif(os.getenv("ANTHROPIC_API_KEY") is None, reason="ANTHROPIC_API_KEY is not set") @pytest.mark.asyncio async def test_unified_function_calling_anthropic(): - llm = AnthropicLLMService( - api_key=os.getenv("ANTHROPIC_API_KEY"), model="claude-3-5-sonnet-20240620" - ) + llm = AnthropicLLMService(api_key=os.getenv("ANTHROPIC_API_KEY")) # This will fail if an exception is raised await _test_llm_function_calling(llm) From 786279f143bb6683cf9f4bdda3c5307a2a129403 Mon Sep 17 00:00:00 2001 From: Mark Backman Date: Sat, 7 Mar 2026 07:56:35 -0500 Subject: [PATCH 0883/1060] Remove unused imports, 2026-03-07 --- examples/foundational/07-interruptible.py | 1 - examples/foundational/10-wake-phrase.py | 2 +- examples/foundational/13k-elevenlabs-transcription.py | 1 - examples/foundational/13m-openai-transcription.py | 1 - examples/foundational/50-ultravox-realtime.py | 1 - .../foundational/55zk-update-settings-google-vertex-llm.py | 1 - examples/foundational/55zzc-update-settings-mistral-llm.py | 1 - scripts/evals/eval.py | 1 - src/pipecat/audio/filters/aic_filter.py | 1 - src/pipecat/serializers/base_serializer.py | 2 +- src/pipecat/serializers/exotel.py | 1 - src/pipecat/serializers/genesys.py | 1 - src/pipecat/serializers/plivo.py | 1 - src/pipecat/serializers/twilio.py | 1 - src/pipecat/serializers/vonage.py | 1 - src/pipecat/services/google/gemini_live/llm.py | 2 +- src/pipecat/services/google/llm.py | 3 +-- src/pipecat/services/google/tts.py | 2 +- src/pipecat/services/openai/realtime/llm.py | 1 - src/pipecat/services/speechmatics/tts.py | 2 +- tests/test_context_summarization.py | 2 +- tests/test_settings.py | 2 -- 22 files changed, 7 insertions(+), 24 deletions(-) diff --git a/examples/foundational/07-interruptible.py b/examples/foundational/07-interruptible.py index 6fa80d838..17aec31e1 100644 --- a/examples/foundational/07-interruptible.py +++ b/examples/foundational/07-interruptible.py @@ -24,7 +24,6 @@ from pipecat.runner.utils import create_transport from pipecat.services.cartesia.tts import CartesiaTTSService from pipecat.services.deepgram.stt import DeepgramSTTService from pipecat.services.openai.llm import OpenAILLMService -from pipecat.services.tts_service import TextAggregationMode from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams diff --git a/examples/foundational/10-wake-phrase.py b/examples/foundational/10-wake-phrase.py index 44b580ad5..df74e4be4 100644 --- a/examples/foundational/10-wake-phrase.py +++ b/examples/foundational/10-wake-phrase.py @@ -10,7 +10,7 @@ from dotenv import load_dotenv from loguru import logger from pipecat.audio.vad.silero import SileroVADAnalyzer -from pipecat.frames.frames import LLMRunFrame, TTSSpeakFrame +from pipecat.frames.frames import LLMRunFrame from pipecat.pipeline.pipeline import Pipeline from pipecat.pipeline.runner import PipelineRunner from pipecat.pipeline.task import PipelineParams, PipelineTask diff --git a/examples/foundational/13k-elevenlabs-transcription.py b/examples/foundational/13k-elevenlabs-transcription.py index 2b0b8143f..f801944e5 100644 --- a/examples/foundational/13k-elevenlabs-transcription.py +++ b/examples/foundational/13k-elevenlabs-transcription.py @@ -6,7 +6,6 @@ import os -import aiohttp from dotenv import load_dotenv from loguru import logger diff --git a/examples/foundational/13m-openai-transcription.py b/examples/foundational/13m-openai-transcription.py index fea5c2d97..0fb595881 100644 --- a/examples/foundational/13m-openai-transcription.py +++ b/examples/foundational/13m-openai-transcription.py @@ -6,7 +6,6 @@ import os -import aiohttp from dotenv import load_dotenv from loguru import logger diff --git a/examples/foundational/50-ultravox-realtime.py b/examples/foundational/50-ultravox-realtime.py index 0908c518c..7aaacdeaf 100644 --- a/examples/foundational/50-ultravox-realtime.py +++ b/examples/foundational/50-ultravox-realtime.py @@ -13,7 +13,6 @@ from loguru import logger from pipecat.adapters.schemas.function_schema import FunctionSchema from pipecat.adapters.schemas.tools_schema import ToolsSchema from pipecat.audio.vad.silero import SileroVADAnalyzer -from pipecat.audio.vad.vad_analyzer import VADParams from pipecat.pipeline.pipeline import Pipeline from pipecat.pipeline.runner import PipelineRunner from pipecat.pipeline.task import PipelineParams, PipelineTask diff --git a/examples/foundational/55zk-update-settings-google-vertex-llm.py b/examples/foundational/55zk-update-settings-google-vertex-llm.py index 16cec654f..6b2babb7f 100644 --- a/examples/foundational/55zk-update-settings-google-vertex-llm.py +++ b/examples/foundational/55zk-update-settings-google-vertex-llm.py @@ -24,7 +24,6 @@ from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport from pipecat.services.cartesia.tts import CartesiaTTSService from pipecat.services.deepgram.stt import DeepgramSTTService -from pipecat.services.google.llm import GoogleLLMSettings from pipecat.services.google.llm_vertex import GoogleVertexLLMService from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams diff --git a/examples/foundational/55zzc-update-settings-mistral-llm.py b/examples/foundational/55zzc-update-settings-mistral-llm.py index b3c5fa047..94ee3f29a 100644 --- a/examples/foundational/55zzc-update-settings-mistral-llm.py +++ b/examples/foundational/55zzc-update-settings-mistral-llm.py @@ -25,7 +25,6 @@ from pipecat.runner.utils import create_transport from pipecat.services.cartesia.tts import CartesiaTTSService from pipecat.services.deepgram.stt import DeepgramSTTService from pipecat.services.mistral.llm import MistralLLMService -from pipecat.services.openai.base_llm import OpenAILLMSettings from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams diff --git a/scripts/evals/eval.py b/scripts/evals/eval.py index ab4edad8d..925853981 100644 --- a/scripts/evals/eval.py +++ b/scripts/evals/eval.py @@ -51,7 +51,6 @@ from pipecat.runner.types import RunnerArguments from pipecat.services.cartesia.tts import CartesiaTTSService from pipecat.services.deepgram.stt import DeepgramSTTService from pipecat.services.llm_service import FunctionCallParams -from pipecat.services.openai.base_llm import OpenAILLMSettings from pipecat.services.openai.llm import OpenAILLMService from pipecat.transports.daily.transport import DailyParams, DailyTransport diff --git a/src/pipecat/audio/filters/aic_filter.py b/src/pipecat/audio/filters/aic_filter.py index 91f0356d0..e33899aae 100644 --- a/src/pipecat/audio/filters/aic_filter.py +++ b/src/pipecat/audio/filters/aic_filter.py @@ -23,7 +23,6 @@ from typing import List, Optional, Tuple import numpy as np from aic_sdk import ( Model, - ParameterFixedError, ProcessorAsync, ProcessorConfig, ProcessorParameter, diff --git a/src/pipecat/serializers/base_serializer.py b/src/pipecat/serializers/base_serializer.py index c7b32dccc..d9414e43d 100644 --- a/src/pipecat/serializers/base_serializer.py +++ b/src/pipecat/serializers/base_serializer.py @@ -6,7 +6,7 @@ """Frame serialization interfaces for Pipecat.""" -from abc import ABC, abstractmethod +from abc import abstractmethod from typing import Optional from pydantic import BaseModel diff --git a/src/pipecat/serializers/exotel.py b/src/pipecat/serializers/exotel.py index 74e3f28b0..abf170d65 100644 --- a/src/pipecat/serializers/exotel.py +++ b/src/pipecat/serializers/exotel.py @@ -11,7 +11,6 @@ import json from typing import Optional from loguru import logger -from pydantic import BaseModel from pipecat.audio.dtmf.types import KeypadEntry from pipecat.audio.utils import create_stream_resampler diff --git a/src/pipecat/serializers/genesys.py b/src/pipecat/serializers/genesys.py index a25287b5c..2cc3c32db 100644 --- a/src/pipecat/serializers/genesys.py +++ b/src/pipecat/serializers/genesys.py @@ -27,7 +27,6 @@ from enum import Enum from typing import Any, Dict, List, Optional from loguru import logger -from pydantic import BaseModel from pipecat.audio.dtmf.types import KeypadEntry from pipecat.audio.resamplers.soxr_stream_resampler import SOXRStreamAudioResampler diff --git a/src/pipecat/serializers/plivo.py b/src/pipecat/serializers/plivo.py index 3341e5ffa..b6346d542 100644 --- a/src/pipecat/serializers/plivo.py +++ b/src/pipecat/serializers/plivo.py @@ -11,7 +11,6 @@ import json from typing import Optional from loguru import logger -from pydantic import BaseModel from pipecat.audio.dtmf.types import KeypadEntry from pipecat.audio.utils import create_stream_resampler, pcm_to_ulaw, ulaw_to_pcm diff --git a/src/pipecat/serializers/twilio.py b/src/pipecat/serializers/twilio.py index bf92a9043..4d4b5344a 100644 --- a/src/pipecat/serializers/twilio.py +++ b/src/pipecat/serializers/twilio.py @@ -11,7 +11,6 @@ import json from typing import Optional from loguru import logger -from pydantic import BaseModel from pipecat.audio.dtmf.types import KeypadEntry from pipecat.audio.utils import create_stream_resampler, pcm_to_ulaw, ulaw_to_pcm diff --git a/src/pipecat/serializers/vonage.py b/src/pipecat/serializers/vonage.py index 01fed08f8..c14ae4025 100644 --- a/src/pipecat/serializers/vonage.py +++ b/src/pipecat/serializers/vonage.py @@ -10,7 +10,6 @@ import json from typing import Optional from loguru import logger -from pydantic import BaseModel from pipecat.audio.dtmf.types import KeypadEntry from pipecat.audio.utils import create_stream_resampler diff --git a/src/pipecat/services/google/gemini_live/llm.py b/src/pipecat/services/google/gemini_live/llm.py index c25caafdd..07f185f99 100644 --- a/src/pipecat/services/google/gemini_live/llm.py +++ b/src/pipecat/services/google/gemini_live/llm.py @@ -19,7 +19,7 @@ import uuid import warnings from dataclasses import dataclass, field from enum import Enum -from typing import Any, ClassVar, Dict, List, Optional, Union +from typing import Any, Dict, List, Optional, Union from loguru import logger from PIL import Image diff --git a/src/pipecat/services/google/llm.py b/src/pipecat/services/google/llm.py index 198e612f0..7f4f8caae 100644 --- a/src/pipecat/services/google/llm.py +++ b/src/pipecat/services/google/llm.py @@ -16,7 +16,7 @@ import json import os import uuid from dataclasses import dataclass, field -from typing import Any, AsyncIterator, ClassVar, Dict, List, Literal, Optional +from typing import Any, AsyncIterator, Dict, List, Literal, Optional from loguru import logger from PIL import Image @@ -35,7 +35,6 @@ from pipecat.frames.frames import ( LLMFullResponseStartFrame, LLMMessagesAppendFrame, LLMMessagesFrame, - LLMTextFrame, LLMThoughtEndFrame, LLMThoughtStartFrame, LLMThoughtTextFrame, diff --git a/src/pipecat/services/google/tts.py b/src/pipecat/services/google/tts.py index d3f7879ad..a9394028b 100644 --- a/src/pipecat/services/google/tts.py +++ b/src/pipecat/services/google/tts.py @@ -24,7 +24,7 @@ from pipecat.utils.tracing.service_decorators import traced_tts os.environ["GRPC_ENABLE_FORK_SUPPORT"] = "false" from dataclasses import dataclass, field -from typing import Any, AsyncGenerator, Dict, List, Literal, Optional +from typing import Any, AsyncGenerator, List, Literal, Optional from loguru import logger from pydantic import BaseModel diff --git a/src/pipecat/services/openai/realtime/llm.py b/src/pipecat/services/openai/realtime/llm.py index 4fa3ab604..d1a90779e 100644 --- a/src/pipecat/services/openai/realtime/llm.py +++ b/src/pipecat/services/openai/realtime/llm.py @@ -37,7 +37,6 @@ from pipecat.frames.frames import ( LLMMessagesAppendFrame, LLMSetToolsFrame, LLMTextFrame, - LLMUpdateSettingsFrame, StartFrame, TranscriptionFrame, TTSAudioRawFrame, diff --git a/src/pipecat/services/speechmatics/tts.py b/src/pipecat/services/speechmatics/tts.py index 5f0aed7f3..20a3212ff 100644 --- a/src/pipecat/services/speechmatics/tts.py +++ b/src/pipecat/services/speechmatics/tts.py @@ -8,7 +8,7 @@ import asyncio from dataclasses import dataclass, field -from typing import Any, AsyncGenerator, Optional +from typing import AsyncGenerator, Optional from urllib.parse import urlencode import aiohttp diff --git a/tests/test_context_summarization.py b/tests/test_context_summarization.py index f0d4ffc19..26d26614e 100644 --- a/tests/test_context_summarization.py +++ b/tests/test_context_summarization.py @@ -10,7 +10,7 @@ import asyncio import unittest from unittest.mock import AsyncMock -from pipecat.frames.frames import LLMContextSummaryRequestFrame, LLMContextSummaryResultFrame +from pipecat.frames.frames import LLMContextSummaryRequestFrame from pipecat.processors.aggregators.llm_context import LLMContext, LLMSpecificMessage from pipecat.services.llm_service import LLMService from pipecat.utils.context.llm_context_summarization import ( diff --git a/tests/test_settings.py b/tests/test_settings.py index 973dd7815..8ffe355ad 100644 --- a/tests/test_settings.py +++ b/tests/test_settings.py @@ -8,8 +8,6 @@ from unittest.mock import patch -import pytest - from pipecat.services.deepgram.stt import DeepgramSTTService, DeepgramSTTSettings from pipecat.services.deepgram.stt_sagemaker import DeepgramSageMakerSTTSettings from pipecat.services.grok.realtime import events as grok_events From 20c3f553b2a88de49eb6870a7906d756961c56e7 Mon Sep 17 00:00:00 2001 From: Paul Kompfner Date: Mon, 9 Mar 2026 14:36:15 -0400 Subject: [PATCH 0884/1060] Add missing 55-* update-settings examples for OpenPipe LLM and XTTS TTS --- .../55zzo-update-settings-openpipe-llm.py | 131 +++++++++++++++++ .../55zzp-update-settings-xtts-tts.py | 133 ++++++++++++++++++ 2 files changed, 264 insertions(+) create mode 100644 examples/foundational/55zzo-update-settings-openpipe-llm.py create mode 100644 examples/foundational/55zzp-update-settings-xtts-tts.py diff --git a/examples/foundational/55zzo-update-settings-openpipe-llm.py b/examples/foundational/55zzo-update-settings-openpipe-llm.py new file mode 100644 index 000000000..669a35cd5 --- /dev/null +++ b/examples/foundational/55zzo-update-settings-openpipe-llm.py @@ -0,0 +1,131 @@ +# +# Copyright (c) 2024-2026, Daily +# +# SPDX-License-Identifier: BSD 2-Clause License +# + +import asyncio +import os +import time + +from dotenv import load_dotenv +from loguru import logger + +from pipecat.audio.vad.silero import SileroVADAnalyzer +from pipecat.frames.frames import LLMRunFrame, LLMUpdateSettingsFrame +from pipecat.pipeline.pipeline import Pipeline +from pipecat.pipeline.runner import PipelineRunner +from pipecat.pipeline.task import PipelineParams, PipelineTask +from pipecat.processors.aggregators.llm_context import LLMContext +from pipecat.processors.aggregators.llm_response_universal import ( + LLMContextAggregatorPair, + LLMUserAggregatorParams, +) +from pipecat.runner.types import RunnerArguments +from pipecat.runner.utils import create_transport +from pipecat.services.cartesia.tts import CartesiaTTSService +from pipecat.services.deepgram.stt import DeepgramSTTService +from pipecat.services.openpipe.llm import OpenPipeLLMService +from pipecat.transports.base_transport import BaseTransport, TransportParams +from pipecat.transports.daily.transport import DailyParams +from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams + +load_dotenv(override=True) + +transport_params = { + "daily": lambda: DailyParams( + audio_in_enabled=True, + audio_out_enabled=True, + ), + "twilio": lambda: FastAPIWebsocketParams( + audio_in_enabled=True, + audio_out_enabled=True, + ), + "webrtc": lambda: TransportParams( + audio_in_enabled=True, + audio_out_enabled=True, + ), +} + + +async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): + logger.info(f"Starting bot") + + stt = DeepgramSTTService(api_key=os.getenv("DEEPGRAM_API_KEY")) + + tts = CartesiaTTSService( + api_key=os.getenv("CARTESIA_API_KEY"), + settings=CartesiaTTSService.Settings( + voice="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady + ), + ) + + timestamp = int(time.time()) + llm = OpenPipeLLMService( + api_key=os.getenv("OPENAI_API_KEY"), + openpipe_api_key=os.getenv("OPENPIPE_API_KEY"), + tags={"conversation_id": f"pipecat-{timestamp}"}, + settings=OpenPipeLLMService.Settings( + system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + ), + ) + + context = LLMContext() + user_aggregator, assistant_aggregator = LLMContextAggregatorPair( + context, + user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()), + ) + + pipeline = Pipeline( + [ + transport.input(), + stt, + user_aggregator, + llm, + tts, + transport.output(), + assistant_aggregator, + ] + ) + + task = PipelineTask( + pipeline, + params=PipelineParams( + enable_metrics=True, + enable_usage_metrics=True, + ), + idle_timeout_secs=runner_args.pipeline_idle_timeout_secs, + ) + + @transport.event_handler("on_client_connected") + async def on_client_connected(transport, client): + logger.info(f"Client connected") + context.add_message({"role": "user", "content": "Please introduce yourself to the user."}) + await task.queue_frames([LLMRunFrame()]) + + await asyncio.sleep(10) + logger.info("Updating OpenPipe LLM settings: temperature=0.1") + await task.queue_frame( + LLMUpdateSettingsFrame(delta=OpenPipeLLMService.Settings(temperature=0.1)) + ) + + @transport.event_handler("on_client_disconnected") + async def on_client_disconnected(transport, client): + logger.info(f"Client disconnected") + await task.cancel() + + runner = PipelineRunner(handle_sigint=runner_args.handle_sigint) + + await runner.run(task) + + +async def bot(runner_args: RunnerArguments): + """Main bot entry point compatible with Pipecat Cloud.""" + transport = await create_transport(runner_args, transport_params) + await run_bot(transport, runner_args) + + +if __name__ == "__main__": + from pipecat.runner.run import main + + main() diff --git a/examples/foundational/55zzp-update-settings-xtts-tts.py b/examples/foundational/55zzp-update-settings-xtts-tts.py new file mode 100644 index 000000000..8a7667036 --- /dev/null +++ b/examples/foundational/55zzp-update-settings-xtts-tts.py @@ -0,0 +1,133 @@ +# +# Copyright (c) 2024-2026, Daily +# +# SPDX-License-Identifier: BSD 2-Clause License +# + +import asyncio +import os + +import aiohttp +from dotenv import load_dotenv +from loguru import logger + +from pipecat.audio.vad.silero import SileroVADAnalyzer +from pipecat.frames.frames import LLMRunFrame, TTSUpdateSettingsFrame +from pipecat.pipeline.pipeline import Pipeline +from pipecat.pipeline.runner import PipelineRunner +from pipecat.pipeline.task import PipelineParams, PipelineTask +from pipecat.processors.aggregators.llm_context import LLMContext +from pipecat.processors.aggregators.llm_response_universal import ( + LLMContextAggregatorPair, + LLMUserAggregatorParams, +) +from pipecat.runner.types import RunnerArguments +from pipecat.runner.utils import create_transport +from pipecat.services.deepgram.stt import DeepgramSTTService +from pipecat.services.openai.llm import OpenAILLMService +from pipecat.services.xtts.tts import XTTSService +from pipecat.transports.base_transport import BaseTransport, TransportParams +from pipecat.transports.daily.transport import DailyParams +from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams + +load_dotenv(override=True) + + +transport_params = { + "daily": lambda: DailyParams( + audio_in_enabled=True, + audio_out_enabled=True, + ), + "twilio": lambda: FastAPIWebsocketParams( + audio_in_enabled=True, + audio_out_enabled=True, + ), + "webrtc": lambda: TransportParams( + audio_in_enabled=True, + audio_out_enabled=True, + ), +} + + +async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): + logger.info(f"Starting bot") + + async with aiohttp.ClientSession() as session: + stt = DeepgramSTTService(api_key=os.getenv("DEEPGRAM_API_KEY")) + + tts = XTTSService( + aiohttp_session=session, + settings=XTTSService.Settings( + voice="Claribel Dervla", + ), + base_url="http://localhost:8000", + ) + + llm = OpenAILLMService( + api_key=os.getenv("OPENAI_API_KEY"), + settings=OpenAILLMService.Settings( + system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + ), + ) + + context = LLMContext() + user_aggregator, assistant_aggregator = LLMContextAggregatorPair( + context, + user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()), + ) + + pipeline = Pipeline( + [ + transport.input(), + stt, + user_aggregator, + llm, + tts, + transport.output(), + assistant_aggregator, + ] + ) + + task = PipelineTask( + pipeline, + params=PipelineParams( + enable_metrics=True, + enable_usage_metrics=True, + ), + idle_timeout_secs=runner_args.pipeline_idle_timeout_secs, + ) + + @transport.event_handler("on_client_connected") + async def on_client_connected(transport, client): + logger.info(f"Client connected") + context.add_message( + {"role": "user", "content": "Please introduce yourself to the user."} + ) + await task.queue_frames([LLMRunFrame()]) + + await asyncio.sleep(10) + logger.info('Updating XTTS TTS settings: voice="Ana Florence"') + await task.queue_frame( + TTSUpdateSettingsFrame(delta=XTTSService.Settings(voice="Ana Florence")) + ) + + @transport.event_handler("on_client_disconnected") + async def on_client_disconnected(transport, client): + logger.info(f"Client disconnected") + await task.cancel() + + runner = PipelineRunner(handle_sigint=runner_args.handle_sigint) + + await runner.run(task) + + +async def bot(runner_args: RunnerArguments): + """Main bot entry point compatible with Pipecat Cloud.""" + transport = await create_transport(runner_args, transport_params) + await run_bot(transport, runner_args) + + +if __name__ == "__main__": + from pipecat.runner.run import main + + main() From f533dc320304a691c98f7e7ab826bf16e39bd686 Mon Sep 17 00:00:00 2001 From: Mark Backman Date: Mon, 9 Mar 2026 14:59:09 -0400 Subject: [PATCH 0885/1060] Fix Azure STT SpeechConfig failing when private_endpoint is provided MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit SpeechConfig does not accept both `region` and `endpoint` simultaneously — they are mutually exclusive. The previous code always passed both, which raises ValueError when a user supplies a private_endpoint URL. Now we conditionally pass either `endpoint` or `region`, never both. --- src/pipecat/services/azure/stt.py | 22 +++++++++++++++------- 1 file changed, 15 insertions(+), 7 deletions(-) diff --git a/src/pipecat/services/azure/stt.py b/src/pipecat/services/azure/stt.py index 0588cc6cc..72388b370 100644 --- a/src/pipecat/services/azure/stt.py +++ b/src/pipecat/services/azure/stt.py @@ -94,7 +94,7 @@ class AzureSTTService(STTService): sample_rate: Audio sample rate in Hz. If None, uses service default. private_endpoint: Private endpoint for STT behind firewall. - See https://docs.azure.cn/en-us/ai-services/speech-service/speech-services-private-link?tabs=portal + See https://learn.microsoft.com/en-us/azure/ai-services/speech-service/speech-services-private-link?tabs=portal endpoint_id: Custom model endpoint id. settings: Runtime-updatable settings. When provided alongside deprecated parameters, ``settings`` values take precedence. @@ -126,13 +126,21 @@ class AzureSTTService(STTService): **kwargs, ) - self._speech_config = SpeechConfig( - subscription=api_key, - region=region, - speech_recognition_language=default_settings.language + speech_config_kwargs: dict[str, Any] = { + "subscription": api_key, + "speech_recognition_language": default_settings.language or language_to_azure_language(Language.EN_US), - endpoint=private_endpoint, - ) + } + if private_endpoint: + if region: + logger.warning( + "Both 'region' and 'private_endpoint' provided; 'region' will be ignored." + ) + speech_config_kwargs["endpoint"] = private_endpoint + else: + speech_config_kwargs["region"] = region + + self._speech_config = SpeechConfig(**speech_config_kwargs) if endpoint_id: self._speech_config.endpoint_id = endpoint_id From 07b901c2a5b8deaa55b4bdce18cfb0e8695de8cc Mon Sep 17 00:00:00 2001 From: Mark Backman Date: Mon, 9 Mar 2026 15:00:24 -0400 Subject: [PATCH 0886/1060] Add changelog for #3967 --- changelog/3967.fixed.md | 1 + 1 file changed, 1 insertion(+) create mode 100644 changelog/3967.fixed.md diff --git a/changelog/3967.fixed.md b/changelog/3967.fixed.md new file mode 100644 index 000000000..dff880c2c --- /dev/null +++ b/changelog/3967.fixed.md @@ -0,0 +1 @@ +- Fixed `AzureSTTService` failing to initialize when `private_endpoint` is provided. The Azure Speech SDK's `SpeechConfig` does not accept both `region` and `endpoint` simultaneously, so they are now passed conditionally. From 00eb190424755b39246571a345f93b59a1fa88f6 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Aleix=20Conchillo=20Flaqu=C3=A9?= Date: Mon, 9 Mar 2026 20:47:13 -0700 Subject: [PATCH 0887/1060] Update daily-python to 0.24.0 --- pyproject.toml | 2 +- uv.lock | 778 +++++++++++++++++++++++++------------------------ 2 files changed, 398 insertions(+), 382 deletions(-) diff --git a/pyproject.toml b/pyproject.toml index d52e8af07..d2ff8ec85 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -62,7 +62,7 @@ azure = [ "azure-cognitiveservices-speech>=1.47.0,<2"] cartesia = [ "pipecat-ai[websockets-base]" ] camb = [ "camb-sdk>=1.5.4,<2" ] cerebras = [] -daily = [ "daily-python~=0.23.0" ] +daily = [ "daily-python~=0.24.0" ] deepgram = [ "deepgram-sdk>=6.0.1,<7", "pipecat-ai[websockets-base]" ] deepseek = [] elevenlabs = [ "pipecat-ai[websockets-base]" ] diff --git a/uv.lock b/uv.lock index 9d27b1c3a..eae25a805 100644 --- a/uv.lock +++ b/uv.lock @@ -16,7 +16,7 @@ source = { registry = 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= "2026-03-09T17:24:35.378Z" }, ] [[package]] From d79e35d84fa84245b6899f91c60f25d5f4164955 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Aleix=20Conchillo=20Flaqu=C3=A9?= Date: Mon, 9 Mar 2026 20:47:42 -0700 Subject: [PATCH 0888/1060] Add changelog for #3970 --- changelog/3970.changed.md | 1 + 1 file changed, 1 insertion(+) create mode 100644 changelog/3970.changed.md diff --git a/changelog/3970.changed.md b/changelog/3970.changed.md new file mode 100644 index 000000000..f420a7e73 --- /dev/null +++ b/changelog/3970.changed.md @@ -0,0 +1 @@ +- Updated `daily-python` dependency from `~=0.23.0` to `~=0.24.0`. From 9cc264471918e4622a98b8be4b3103cd4e6947f1 Mon Sep 17 00:00:00 2001 From: Kinshuk Bairagi Date: Wed, 14 Jan 2026 21:46:58 +0530 Subject: [PATCH 0889/1060] Improve system message extraction in traced_llm Enhanced the logic for extracting the system message in the traced_llm decorator to support LLMContext via adapter and handle exceptions gracefully. This improves compatibility with different context types and ensures better tracing information. --- changelog/3449.fixed.md | 1 + .../utils/tracing/service_decorators.py | 19 ++++++++++++++++++- 2 files changed, 19 insertions(+), 1 deletion(-) create mode 100644 changelog/3449.fixed.md diff --git a/changelog/3449.fixed.md b/changelog/3449.fixed.md new file mode 100644 index 000000000..a8663e004 --- /dev/null +++ b/changelog/3449.fixed.md @@ -0,0 +1 @@ +- Fixed telemetry record correct system_instruction in span for LLM services diff --git a/src/pipecat/utils/tracing/service_decorators.py b/src/pipecat/utils/tracing/service_decorators.py index 304ecb5e8..6f772aa88 100644 --- a/src/pipecat/utils/tracing/service_decorators.py +++ b/src/pipecat/utils/tracing/service_decorators.py @@ -500,7 +500,24 @@ def traced_llm(func: Optional[Callable] = None, *, name: Optional[str] = None) - # Handle system message for different services system_message = None - if hasattr(context, "system"): + # Handle system message for different services + if isinstance(context, LLMContext): + # Universal LLMContext - use adapter to convert and get system message + if hasattr(self, "get_llm_adapter"): + adapter = self.get_llm_adapter() + try: + # Get LLM invocation params which includes system_instruction + params = adapter.get_llm_invocation_params(context) + if ( + isinstance(params, dict) + and "system_instruction" in params + ): + system_message = params["system_instruction"] + except Exception as e: + logging.debug( + f"Could not extract system instruction from adapter: {e}" + ) + elif hasattr(context, "system"): system_message = context.system elif hasattr(context, "system_message"): system_message = context.system_message From c7ef23dd2253000b4c842a17606ed43494d752ab Mon Sep 17 00:00:00 2001 From: yukiobata1 Date: Tue, 10 Mar 2026 18:22:20 +0900 Subject: [PATCH 0890/1060] Update Fish Audio default model from s1 to s2-pro --- src/pipecat/services/fish/tts.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/src/pipecat/services/fish/tts.py b/src/pipecat/services/fish/tts.py index 4974dfa37..f21b42b97 100644 --- a/src/pipecat/services/fish/tts.py +++ b/src/pipecat/services/fish/tts.py @@ -172,7 +172,7 @@ class FishAudioTTSService(InterruptibleTTSService): # 1. Initialize default_settings with hardcoded defaults default_settings = FishAudioTTSSettings( - model="s1", + model="s2-pro", voice=None, language=None, latency="balanced", From ceb53e044b0407b9cfa58a0510a9b5dccee4758e Mon Sep 17 00:00:00 2001 From: yukiobata1 Date: Tue, 10 Mar 2026 19:29:47 +0900 Subject: [PATCH 0891/1060] Add changelog for #3973 --- changelog/3973.changed.md | 1 + 1 file changed, 1 insertion(+) create mode 100644 changelog/3973.changed.md diff --git a/changelog/3973.changed.md b/changelog/3973.changed.md new file mode 100644 index 000000000..d6834ce8e --- /dev/null +++ b/changelog/3973.changed.md @@ -0,0 +1 @@ +- Updated `FishAudioTTSService` default model from `s1` to `s2-pro`, matching Fish Audio's latest recommended model for improved quality and speed. From 233867fdfb626c2eb0dcd4a6d0b11304bd1a3594 Mon Sep 17 00:00:00 2001 From: Mark Backman Date: Tue, 10 Mar 2026 07:40:55 -0400 Subject: [PATCH 0892/1060] Make region optional and validate Azure STT config Make `region` optional so users can provide only `private_endpoint`. Raise ValueError if neither is provided, and warn if both are given (private_endpoint takes priority). --- src/pipecat/services/azure/stt.py | 31 ++++++++++++++++++++----------- 1 file changed, 20 insertions(+), 11 deletions(-) diff --git a/src/pipecat/services/azure/stt.py b/src/pipecat/services/azure/stt.py index 72388b370..169b055f2 100644 --- a/src/pipecat/services/azure/stt.py +++ b/src/pipecat/services/azure/stt.py @@ -73,7 +73,7 @@ class AzureSTTService(STTService): self, *, api_key: str, - region: str, + region: Optional[str] = None, language: Optional[Language] = Language.EN_US, sample_rate: Optional[int] = None, private_endpoint: Optional[str] = None, @@ -87,6 +87,7 @@ class AzureSTTService(STTService): Args: api_key: Azure Cognitive Services subscription key. region: Azure region for the Speech service (e.g., 'eastus'). + Required unless ``private_endpoint`` is provided. language: Language for speech recognition. Defaults to English (US). .. deprecated:: 0.0.105 @@ -94,7 +95,7 @@ class AzureSTTService(STTService): sample_rate: Audio sample rate in Hz. If None, uses service default. private_endpoint: Private endpoint for STT behind firewall. - See https://learn.microsoft.com/en-us/azure/ai-services/speech-service/speech-services-private-link?tabs=portal + See https://docs.azure.cn/en-us/ai-services/speech-service/speech-services-private-link?tabs=portal endpoint_id: Custom model endpoint id. settings: Runtime-updatable settings. When provided alongside deprecated parameters, ``settings`` values take precedence. @@ -126,21 +127,29 @@ class AzureSTTService(STTService): **kwargs, ) - speech_config_kwargs: dict[str, Any] = { - "subscription": api_key, - "speech_recognition_language": default_settings.language - or language_to_azure_language(Language.EN_US), - } + recognition_language = default_settings.language or language_to_azure_language( + Language.EN_US + ) + + if not region and not private_endpoint: + raise ValueError("Either 'region' or 'private_endpoint' must be provided.") + if private_endpoint: if region: logger.warning( "Both 'region' and 'private_endpoint' provided; 'region' will be ignored." ) - speech_config_kwargs["endpoint"] = private_endpoint + self._speech_config = SpeechConfig( + subscription=api_key, + endpoint=private_endpoint, + speech_recognition_language=recognition_language, + ) else: - speech_config_kwargs["region"] = region - - self._speech_config = SpeechConfig(**speech_config_kwargs) + self._speech_config = SpeechConfig( + subscription=api_key, + region=region, + speech_recognition_language=recognition_language, + ) if endpoint_id: self._speech_config.endpoint_id = endpoint_id From edc65fc45e3e2e67eee899a5caa18a2733f0c79a Mon Sep 17 00:00:00 2001 From: Mark Backman Date: Tue, 10 Mar 2026 07:44:42 -0400 Subject: [PATCH 0893/1060] Add changelog for #3974 --- changelog/3974.changed.md | 1 + src/pipecat/services/azure/stt.py | 2 +- 2 files changed, 2 insertions(+), 1 deletion(-) create mode 100644 changelog/3974.changed.md diff --git a/changelog/3974.changed.md b/changelog/3974.changed.md new file mode 100644 index 000000000..7c4c360d5 --- /dev/null +++ b/changelog/3974.changed.md @@ -0,0 +1 @@ +- `AzureSTTService` `region` parameter is now optional when `private_endpoint` is provided. A `ValueError` is raised if neither is given, and a warning is logged if both are provided (`private_endpoint` takes priority). diff --git a/src/pipecat/services/azure/stt.py b/src/pipecat/services/azure/stt.py index 169b055f2..6abe52db1 100644 --- a/src/pipecat/services/azure/stt.py +++ b/src/pipecat/services/azure/stt.py @@ -95,7 +95,7 @@ class AzureSTTService(STTService): sample_rate: Audio sample rate in Hz. If None, uses service default. private_endpoint: Private endpoint for STT behind firewall. - See https://docs.azure.cn/en-us/ai-services/speech-service/speech-services-private-link?tabs=portal + See https://learn.microsoft.com/en-us/azure/ai-services/speech-service/speech-services-private-link?tabs=portal endpoint_id: Custom model endpoint id. settings: Runtime-updatable settings. When provided alongside deprecated parameters, ``settings`` values take precedence. From df64f3f94397a65d95d8b1f373be5e89be0101f9 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?G=C3=B6kmen=20G=C3=B6rgen?= Date: Mon, 9 Mar 2026 12:44:27 +0100 Subject: [PATCH 0894/1060] add enhancement_level support to `AICFilter`. # Conflicts: # src/pipecat/audio/filters/aic_filter.py --- src/pipecat/audio/filters/aic_filter.py | 45 ++++-- tests/test_aic_filter.py | 179 +++++++++++++++++------- 2 files changed, 163 insertions(+), 61 deletions(-) diff --git a/src/pipecat/audio/filters/aic_filter.py b/src/pipecat/audio/filters/aic_filter.py index e33899aae..5e8c5bc41 100644 --- a/src/pipecat/audio/filters/aic_filter.py +++ b/src/pipecat/audio/filters/aic_filter.py @@ -23,6 +23,7 @@ from typing import List, Optional, Tuple import numpy as np from aic_sdk import ( Model, + ParameterOutOfRangeError, ProcessorAsync, ProcessorConfig, ProcessorParameter, @@ -220,6 +221,7 @@ class AICFilter(BaseAudioFilter): model_id: Optional[str] = None, model_path: Optional[Path] = None, model_download_dir: Optional[Path] = None, + enhancement_level: Optional[float] = None, ) -> None: """Initialize the AIC filter. @@ -231,9 +233,12 @@ class AICFilter(BaseAudioFilter): model_id is ignored and no download occurs. model_download_dir: Directory for downloading models as a Path object. Defaults to a cache directory in user's home folder. + enhancement_level: Optional overall enhancement strength (0.0..1.0). + If None, the model default is used. Raises: - ValueError: If neither model_id nor model_path is provided. + ValueError: If neither model_id nor model_path is provided, or if + enhancement_level is out of range. """ # Set SDK ID for telemetry identification (6 = pipecat) set_sdk_id(6) @@ -244,14 +249,18 @@ class AICFilter(BaseAudioFilter): "See https://artifacts.ai-coustics.io/ for available models." ) + if enhancement_level is not None and not 0.0 <= enhancement_level <= 1.0: + raise ValueError("'enhancement_level' must be between 0.0 and 1.0.") + self._license_key = license_key self._model_id = model_id self._model_path = model_path self._model_download_dir = model_download_dir or ( Path.home() / ".cache" / "pipecat" / "aic-models" ) + self._enhancement_level = enhancement_level + self._is_filter_enabled = True - self._bypass = False self._sample_rate = 0 self._aic_ready = False self._frames_per_block = 0 @@ -325,6 +334,20 @@ class AICFilter(BaseAudioFilter): sensitivity=sensitivity, ) + def _apply_enhancement_level(self): + """Apply enhancement_level if configured and supported by the active model.""" + if self._enhancement_level is None or self._processor_ctx is None: + return + + level = float(self._enhancement_level if self._is_filter_enabled else 0.0) + + try: + self._processor_ctx.set_parameter(ProcessorParameter.EnhancementLevel, level) + except ParameterOutOfRangeError as e: + logger.warning("AIC enhancement_level was rejected as out-of-range; ignoring it.") + logger.debug(f"AIC EnhancementLevel set_parameter out-of-range: {e}") + self._enhancement_level = None + async def start(self, sample_rate: int): """Initialize the filter with the transport's sample rate. @@ -373,14 +396,19 @@ class AICFilter(BaseAudioFilter): self._processor_ctx = self._processor.get_processor_context() self._vad_ctx = self._processor.get_vad_context() - # Apply initial parameters - self._processor_ctx.set_parameter(ProcessorParameter.Bypass, 1.0 if self._bypass else 0.0) + # Apply initial enhancement settings (if configured) + self._apply_enhancement_level() # Log processor information logger.debug(f"ai-coustics filter started:") logger.debug(f" Model ID: {self._model.get_id()}") logger.debug(f" Sample rate: {self._sample_rate} Hz") logger.debug(f" Frames per chunk: {self._frames_per_block}") + if self._enhancement_level is not None: + level = self._enhancement_level if self._is_filter_enabled else 0.0 + logger.debug(f" Enhancement strength: {int(level * 100)}%") + else: + logger.debug(" Enhancement level not configured; using the model's default behavior.") logger.debug(f" Optimal sample rate: {self._model.get_optimal_sample_rate()} Hz") logger.debug( f" Optimal number of frames for {self._sample_rate} Hz: " @@ -422,14 +450,9 @@ class AICFilter(BaseAudioFilter): None """ if isinstance(frame, FilterEnableFrame): - self._bypass = not frame.enable + self._is_filter_enabled = frame.enable if self._processor_ctx is not None: - try: - self._processor_ctx.set_parameter( - ProcessorParameter.Bypass, 1.0 if self._bypass else 0.0 - ) - except Exception as e: # noqa: BLE001 - logger.error(f"AIC set_parameter failed: {e}") + self._apply_enhancement_level() async def filter(self, audio: bytes) -> bytes: """Apply AIC enhancement to audio data. diff --git a/tests/test_aic_filter.py b/tests/test_aic_filter.py index 08c702986..3dc284f32 100644 --- a/tests/test_aic_filter.py +++ b/tests/test_aic_filter.py @@ -8,16 +8,19 @@ import asyncio import time import unittest from pathlib import Path +from typing import Any from unittest.mock import AsyncMock, MagicMock, patch import numpy as np # Check if aic_sdk is available +aic_sdk: Any try: import aic_sdk HAS_AIC_SDK = True except ImportError: + aic_sdk = None HAS_AIC_SDK = False # Module path for patching @@ -67,6 +70,22 @@ class MockProcessorContext: self.reset_called = True +class UnsupportedEnhancementProcessorContext(MockProcessorContext): + """Processor context mock that rejects EnhancementLevel updates.""" + + def __init__(self, enhancement_parameter, error_type): + super().__init__() + self._enhancement_parameter = enhancement_parameter + self._error_type = error_type + self.enhancement_attempts = 0 + + def set_parameter(self, param, value): + if param == self._enhancement_parameter: + self.enhancement_attempts += 1 + raise self._error_type("EnhancementLevel out of range") + super().set_parameter(param, value) + + class MockVadContext: """A lightweight mock for AIC VadContext.""" @@ -157,7 +176,8 @@ class TestAICFilter(unittest.IsolatedAsyncioTestCase): self.assertEqual(filter_instance._license_key, "test-key") self.assertEqual(filter_instance._model_id, "test-model") self.assertIsNone(filter_instance._model_path) - self.assertFalse(filter_instance._bypass) + self.assertIsNone(filter_instance._enhancement_level) + self.assertTrue(filter_instance._is_filter_enabled) async def test_initialization_with_model_path(self): """Test filter initialization with model_path.""" @@ -174,6 +194,29 @@ class TestAICFilter(unittest.IsolatedAsyncioTestCase): self.assertEqual(filter_instance._model_download_dir, download_dir) + async def test_initialization_with_valid_enhancement_level(self): + """Test filter initialization with a valid enhancement_level.""" + filter_instance = self._create_filter_with_mocks(enhancement_level=0.75) + + self.assertEqual(filter_instance._enhancement_level, 0.75) + + async def test_initialization_with_none_enhancement_level(self): + """Test filter initialization with enhancement_level set to None.""" + filter_instance = self._create_filter_with_mocks(enhancement_level=None) + + self.assertIsNone(filter_instance._enhancement_level) + + async def test_initialization_invalid_enhancement_level_raises(self): + """Test initialization rejects enhancement_level outside 0.0..1.0.""" + with patch(f"{AIC_FILTER_MODULE}.set_sdk_id"): + with self.assertRaises(ValueError) as context: + self.AICFilter( + license_key="test-key", + model_id="test-model", + enhancement_level=1.5, + ) + self.assertIn("enhancement_level", str(context.exception)) + async def test_start_with_model_path(self): """Test starting filter with a local model path.""" model_path = Path("/tmp/test.aicmodel") @@ -241,19 +284,61 @@ class TestAICFilter(unittest.IsolatedAsyncioTestCase): self.assertIsNotNone(filter_instance._processor_ctx) self.assertIsNotNone(filter_instance._vad_ctx) - async def test_start_applies_initial_bypass_parameter(self): - """Test that start applies bypass parameter.""" + async def test_start_does_not_apply_bypass_parameter(self): + """Test that start does not set SDK Bypass parameter.""" filter_instance = self._create_filter_with_mocks() await self._start_filter_with_mocks(filter_instance) - # Check that bypass was set to 0.0 (enabled) bypass_params = [ (p, v) for p, v in self.mock_processor.processor_ctx.parameters_set if p == aic_sdk.ProcessorParameter.Bypass ] - self.assertTrue(len(bypass_params) > 0) - self.assertEqual(bypass_params[-1][1], 0.0) + self.assertEqual(bypass_params, []) + + async def test_start_applies_enhancement_level_when_supported(self): + """Test that start applies enhancement_level when supported by model.""" + filter_instance = self._create_filter_with_mocks(enhancement_level=0.65) + await self._start_filter_with_mocks(filter_instance) + + enhancement_params = [ + (p, v) + for p, v in self.mock_processor.processor_ctx.parameters_set + if p == aic_sdk.ProcessorParameter.EnhancementLevel + ] + self.assertTrue(len(enhancement_params) > 0) + self.assertEqual(enhancement_params[-1][1], 0.65) + + async def test_start_ignores_enhancement_level_when_unsupported(self): + """Test unsupported enhancement_level logs warning and keeps filter ready.""" + filter_instance = self._create_filter_with_mocks(enhancement_level=0.65) + + with patch(f"{AIC_FILTER_MODULE}.ParameterOutOfRangeError", ValueError): + unsupported_ctx = UnsupportedEnhancementProcessorContext( + aic_sdk.ProcessorParameter.EnhancementLevel, ValueError + ) + self.mock_processor.processor_ctx = unsupported_ctx + await self._start_filter_with_mocks(filter_instance) + + self.assertTrue(filter_instance._aic_ready) + self.assertIsNone(filter_instance._enhancement_level) + self.assertEqual(unsupported_ctx.enhancement_attempts, 1) + + async def test_start_does_not_set_enhancement_level_when_none(self): + """Test start does not attempt enhancement_level when not configured.""" + filter_instance = self._create_filter_with_mocks(enhancement_level=None) + with patch(f"{AIC_FILTER_MODULE}.logger.debug") as mock_debug: + await self._start_filter_with_mocks(filter_instance) + + enhancement_params = [ + (p, v) + for p, v in self.mock_processor.processor_ctx.parameters_set + if p == aic_sdk.ProcessorParameter.EnhancementLevel + ] + self.assertEqual(enhancement_params, []) + self.assertTrue( + any("default behavior" in str(call.args[0]) for call in mock_debug.call_args_list) + ) async def test_stop_cleans_up_resources(self): """Test that stop properly cleans up resources and releases model reference.""" @@ -420,57 +505,52 @@ class TestAICFilter(unittest.IsolatedAsyncioTestCase): self.assertIsNone(filter_instance._processor) self.assertFalse(filter_instance._aic_ready) - async def test_start_parameter_fixed_error_logged(self): - """Test start() when set_parameter raises ParameterFixedError: logged, no raise.""" - filter_instance = self._create_filter_with_mocks() - self.mock_processor.processor_ctx.set_parameter = MagicMock( - side_effect=aic_sdk.ParameterFixedError("fixed") - ) + async def test_start_skips_unsupported_enhancement_level_after_first_attempt(self): + """Test unsupported enhancement_level is attempted once and then skipped.""" + filter_instance = self._create_filter_with_mocks(enhancement_level=0.9) - with ( - patch(f"{AIC_FILTER_MODULE}.AICModelManager") as mock_manager_cls, - patch(f"{AIC_FILTER_MODULE}.ProcessorConfig") as mock_config_cls, - patch(f"{AIC_FILTER_MODULE}.ProcessorAsync", return_value=self.mock_processor), - ): - mock_manager_cls.acquire = AsyncMock(return_value=(self.mock_model, "test-key")) - mock_config_cls.optimal.return_value = MagicMock() + with patch(f"{AIC_FILTER_MODULE}.ParameterOutOfRangeError", ValueError): + unsupported_ctx = UnsupportedEnhancementProcessorContext( + aic_sdk.ProcessorParameter.EnhancementLevel, ValueError + ) + self.mock_processor.processor_ctx = unsupported_ctx - await filter_instance.start(16000) + await self._start_filter_with_mocks(filter_instance) + await filter_instance.stop() + await self._start_filter_with_mocks(filter_instance) - self.assertTrue(filter_instance._aic_ready) + self.assertEqual(unsupported_ctx.enhancement_attempts, 1) - async def test_process_frame_set_parameter_exception_logged(self): - """Test process_frame when set_parameter raises: exception logged, no raise.""" - filter_instance = self._create_filter_with_mocks() + async def test_process_frame_disable_sets_enhancement_to_zero(self): + """Test disable frame sets enhancement level to 0.0.""" + filter_instance = self._create_filter_with_mocks(enhancement_level=0.7) await self._start_filter_with_mocks(filter_instance) - filter_instance._processor_ctx.set_parameter = MagicMock( - side_effect=ValueError("param error") - ) + await filter_instance.process_frame(self.FilterEnableFrame(enable=False)) + + enhancement_params = [ + (p, v) + for p, v in self.mock_processor.processor_ctx.parameters_set + if p == aic_sdk.ProcessorParameter.EnhancementLevel + ] + self.assertFalse(filter_instance._is_filter_enabled) + self.assertEqual(enhancement_params[-1][1], 0.0) + + async def test_process_frame_enable_restores_configured_enhancement(self): + """Test enable frame restores configured enhancement level.""" + filter_instance = self._create_filter_with_mocks(enhancement_level=0.7) + await self._start_filter_with_mocks(filter_instance) + + await filter_instance.process_frame(self.FilterEnableFrame(enable=False)) await filter_instance.process_frame(self.FilterEnableFrame(enable=True)) - self.assertFalse(filter_instance._bypass) - - async def test_process_frame_enable(self): - """Test processing FilterEnableFrame to enable filtering.""" - filter_instance = self._create_filter_with_mocks() - await self._start_filter_with_mocks(filter_instance) - filter_instance._bypass = True - - enable_frame = self.FilterEnableFrame(enable=True) - await filter_instance.process_frame(enable_frame) - - self.assertFalse(filter_instance._bypass) - - async def test_process_frame_disable(self): - """Test processing FilterEnableFrame to disable filtering.""" - filter_instance = self._create_filter_with_mocks() - await self._start_filter_with_mocks(filter_instance) - - disable_frame = self.FilterEnableFrame(enable=False) - await filter_instance.process_frame(disable_frame) - - self.assertTrue(filter_instance._bypass) + enhancement_params = [ + (p, v) + for p, v in self.mock_processor.processor_ctx.parameters_set + if p == aic_sdk.ProcessorParameter.EnhancementLevel + ] + self.assertTrue(filter_instance._is_filter_enabled) + self.assertEqual(enhancement_params[-1][1], 0.7) async def test_filter_when_not_ready(self): """Test that filter returns audio unchanged when not ready.""" @@ -678,7 +758,6 @@ class TestAICFilter(unittest.IsolatedAsyncioTestCase): BufferError: Existing exports of data: object cannot be re-sized - This is the exact error path reported in production (line 414). The fix removes the memoryview by snapshotting data into immutable bytes before any await. """ From 0c87fcc48cbeeb0fcd266ca0b65096fa48838acc Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?G=C3=B6kmen=20G=C3=B6rgen?= Date: Mon, 9 Mar 2026 13:47:50 +0100 Subject: [PATCH 0895/1060] re-add bypass parameter support to `AICFilter` and update related unit tests. --- src/pipecat/audio/filters/aic_filter.py | 18 ++++++++++++++++-- tests/test_aic_filter.py | 22 +++++++++++++++++++--- 2 files changed, 35 insertions(+), 5 deletions(-) diff --git a/src/pipecat/audio/filters/aic_filter.py b/src/pipecat/audio/filters/aic_filter.py index 5e8c5bc41..fd4e927c2 100644 --- a/src/pipecat/audio/filters/aic_filter.py +++ b/src/pipecat/audio/filters/aic_filter.py @@ -260,6 +260,7 @@ class AICFilter(BaseAudioFilter): ) self._enhancement_level = enhancement_level self._is_filter_enabled = True + self._bypass = False self._sample_rate = 0 self._aic_ready = False @@ -348,6 +349,13 @@ class AICFilter(BaseAudioFilter): logger.debug(f"AIC EnhancementLevel set_parameter out-of-range: {e}") self._enhancement_level = None + def _apply_bypass(self): + """Apply bypass parameter to the active processor.""" + if self._processor_ctx is None: + return + + self._processor_ctx.set_parameter(ProcessorParameter.Bypass, 1.0 if self._bypass else 0.0) + async def start(self, sample_rate: int): """Initialize the filter with the transport's sample rate. @@ -396,7 +404,8 @@ class AICFilter(BaseAudioFilter): self._processor_ctx = self._processor.get_processor_context() self._vad_ctx = self._processor.get_vad_context() - # Apply initial enhancement settings (if configured) + # Apply initial control parameters + self._apply_bypass() self._apply_enhancement_level() # Log processor information @@ -451,8 +460,13 @@ class AICFilter(BaseAudioFilter): """ if isinstance(frame, FilterEnableFrame): self._is_filter_enabled = frame.enable + self._bypass = not frame.enable if self._processor_ctx is not None: - self._apply_enhancement_level() + try: + self._apply_bypass() + self._apply_enhancement_level() + except Exception as e: # noqa: BLE001 + logger.error(f"AIC set_parameter failed: {e}") async def filter(self, audio: bytes) -> bytes: """Apply AIC enhancement to audio data. diff --git a/tests/test_aic_filter.py b/tests/test_aic_filter.py index 3dc284f32..f47b38233 100644 --- a/tests/test_aic_filter.py +++ b/tests/test_aic_filter.py @@ -178,6 +178,7 @@ class TestAICFilter(unittest.IsolatedAsyncioTestCase): self.assertIsNone(filter_instance._model_path) self.assertIsNone(filter_instance._enhancement_level) self.assertTrue(filter_instance._is_filter_enabled) + self.assertFalse(filter_instance._bypass) async def test_initialization_with_model_path(self): """Test filter initialization with model_path.""" @@ -284,8 +285,8 @@ class TestAICFilter(unittest.IsolatedAsyncioTestCase): self.assertIsNotNone(filter_instance._processor_ctx) self.assertIsNotNone(filter_instance._vad_ctx) - async def test_start_does_not_apply_bypass_parameter(self): - """Test that start does not set SDK Bypass parameter.""" + async def test_start_applies_initial_bypass_parameter(self): + """Test that start applies SDK Bypass parameter.""" filter_instance = self._create_filter_with_mocks() await self._start_filter_with_mocks(filter_instance) @@ -294,7 +295,8 @@ class TestAICFilter(unittest.IsolatedAsyncioTestCase): for p, v in self.mock_processor.processor_ctx.parameters_set if p == aic_sdk.ProcessorParameter.Bypass ] - self.assertEqual(bypass_params, []) + self.assertTrue(len(bypass_params) > 0) + self.assertEqual(bypass_params[-1][1], 0.0) async def test_start_applies_enhancement_level_when_supported(self): """Test that start applies enhancement_level when supported by model.""" @@ -533,8 +535,15 @@ class TestAICFilter(unittest.IsolatedAsyncioTestCase): for p, v in self.mock_processor.processor_ctx.parameters_set if p == aic_sdk.ProcessorParameter.EnhancementLevel ] + bypass_params = [ + (p, v) + for p, v in self.mock_processor.processor_ctx.parameters_set + if p == aic_sdk.ProcessorParameter.Bypass + ] self.assertFalse(filter_instance._is_filter_enabled) + self.assertTrue(filter_instance._bypass) self.assertEqual(enhancement_params[-1][1], 0.0) + self.assertEqual(bypass_params[-1][1], 1.0) async def test_process_frame_enable_restores_configured_enhancement(self): """Test enable frame restores configured enhancement level.""" @@ -549,8 +558,15 @@ class TestAICFilter(unittest.IsolatedAsyncioTestCase): for p, v in self.mock_processor.processor_ctx.parameters_set if p == aic_sdk.ProcessorParameter.EnhancementLevel ] + bypass_params = [ + (p, v) + for p, v in self.mock_processor.processor_ctx.parameters_set + if p == aic_sdk.ProcessorParameter.Bypass + ] self.assertTrue(filter_instance._is_filter_enabled) + self.assertFalse(filter_instance._bypass) self.assertEqual(enhancement_params[-1][1], 0.7) + self.assertEqual(bypass_params[-1][1], 0.0) async def test_filter_when_not_ready(self): """Test that filter returns audio unchanged when not ready.""" From 82b300298a302fc487bbd3606686ae459bfc5750 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?G=C3=B6kmen=20G=C3=B6rgen?= Date: Mon, 9 Mar 2026 15:35:10 +0100 Subject: [PATCH 0896/1060] add changelog. --- changelog/3961.changed.md | 1 + 1 file changed, 1 insertion(+) create mode 100644 changelog/3961.changed.md diff --git a/changelog/3961.changed.md b/changelog/3961.changed.md new file mode 100644 index 000000000..19c2780e3 --- /dev/null +++ b/changelog/3961.changed.md @@ -0,0 +1 @@ +- Re-added `enhancement_level` support to `AICFilter` with runtime `FilterEnableFrame` control, applying `ProcessorParameter.Bypass` and `ProcessorParameter.EnhancementLevel` together. From bc11bf96731342a236bb2322190a48aa425395be Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?G=C3=B6kmen=20G=C3=B6rgen?= Date: Tue, 10 Mar 2026 13:48:32 +0100 Subject: [PATCH 0897/1060] remove `_is_filter_enabled` from `AICFilter` and refactor related logic and tests. --- src/pipecat/audio/filters/aic_filter.py | 6 ++---- tests/test_aic_filter.py | 3 --- 2 files changed, 2 insertions(+), 7 deletions(-) diff --git a/src/pipecat/audio/filters/aic_filter.py b/src/pipecat/audio/filters/aic_filter.py index fd4e927c2..fc1fe008d 100644 --- a/src/pipecat/audio/filters/aic_filter.py +++ b/src/pipecat/audio/filters/aic_filter.py @@ -259,7 +259,6 @@ class AICFilter(BaseAudioFilter): Path.home() / ".cache" / "pipecat" / "aic-models" ) self._enhancement_level = enhancement_level - self._is_filter_enabled = True self._bypass = False self._sample_rate = 0 @@ -340,7 +339,7 @@ class AICFilter(BaseAudioFilter): if self._enhancement_level is None or self._processor_ctx is None: return - level = float(self._enhancement_level if self._is_filter_enabled else 0.0) + level = float(self._enhancement_level if not self._bypass else 0.0) try: self._processor_ctx.set_parameter(ProcessorParameter.EnhancementLevel, level) @@ -414,7 +413,7 @@ class AICFilter(BaseAudioFilter): logger.debug(f" Sample rate: {self._sample_rate} Hz") logger.debug(f" Frames per chunk: {self._frames_per_block}") if self._enhancement_level is not None: - level = self._enhancement_level if self._is_filter_enabled else 0.0 + level = self._enhancement_level if not self._bypass else 0.0 logger.debug(f" Enhancement strength: {int(level * 100)}%") else: logger.debug(" Enhancement level not configured; using the model's default behavior.") @@ -459,7 +458,6 @@ class AICFilter(BaseAudioFilter): None """ if isinstance(frame, FilterEnableFrame): - self._is_filter_enabled = frame.enable self._bypass = not frame.enable if self._processor_ctx is not None: try: diff --git a/tests/test_aic_filter.py b/tests/test_aic_filter.py index f47b38233..8403f3711 100644 --- a/tests/test_aic_filter.py +++ b/tests/test_aic_filter.py @@ -177,7 +177,6 @@ class TestAICFilter(unittest.IsolatedAsyncioTestCase): self.assertEqual(filter_instance._model_id, "test-model") self.assertIsNone(filter_instance._model_path) self.assertIsNone(filter_instance._enhancement_level) - self.assertTrue(filter_instance._is_filter_enabled) self.assertFalse(filter_instance._bypass) async def test_initialization_with_model_path(self): @@ -540,7 +539,6 @@ class TestAICFilter(unittest.IsolatedAsyncioTestCase): for p, v in self.mock_processor.processor_ctx.parameters_set if p == aic_sdk.ProcessorParameter.Bypass ] - self.assertFalse(filter_instance._is_filter_enabled) self.assertTrue(filter_instance._bypass) self.assertEqual(enhancement_params[-1][1], 0.0) self.assertEqual(bypass_params[-1][1], 1.0) @@ -563,7 +561,6 @@ class TestAICFilter(unittest.IsolatedAsyncioTestCase): for p, v in self.mock_processor.processor_ctx.parameters_set if p == aic_sdk.ProcessorParameter.Bypass ] - self.assertTrue(filter_instance._is_filter_enabled) self.assertFalse(filter_instance._bypass) self.assertEqual(enhancement_params[-1][1], 0.7) self.assertEqual(bypass_params[-1][1], 0.0) From 483f6689ed97c7dcd233ddf424bcf90d411ba94f Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?G=C3=B6kmen=20G=C3=B6rgen?= Date: Tue, 10 Mar 2026 13:52:13 +0100 Subject: [PATCH 0898/1060] address feedback, use one logging. --- src/pipecat/audio/filters/aic_filter.py | 3 +-- 1 file changed, 1 insertion(+), 2 deletions(-) diff --git a/src/pipecat/audio/filters/aic_filter.py b/src/pipecat/audio/filters/aic_filter.py index fc1fe008d..3762d49f6 100644 --- a/src/pipecat/audio/filters/aic_filter.py +++ b/src/pipecat/audio/filters/aic_filter.py @@ -344,8 +344,7 @@ class AICFilter(BaseAudioFilter): try: self._processor_ctx.set_parameter(ProcessorParameter.EnhancementLevel, level) except ParameterOutOfRangeError as e: - logger.warning("AIC enhancement_level was rejected as out-of-range; ignoring it.") - logger.debug(f"AIC EnhancementLevel set_parameter out-of-range: {e}") + logger.warning(f"AIC EnhancementLevel set_parameter out-of-range: {e}") self._enhancement_level = None def _apply_bypass(self): From 8e1c8a38e487d12272b09eedd1d8726be326f5a2 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?G=C3=B6kmen=20G=C3=B6rgen?= Date: Tue, 10 Mar 2026 14:17:21 +0100 Subject: [PATCH 0899/1060] don't change enhancement level if bypass toggled. --- src/pipecat/audio/filters/aic_filter.py | 8 ++++---- 1 file changed, 4 insertions(+), 4 deletions(-) diff --git a/src/pipecat/audio/filters/aic_filter.py b/src/pipecat/audio/filters/aic_filter.py index 3762d49f6..d4f0b37de 100644 --- a/src/pipecat/audio/filters/aic_filter.py +++ b/src/pipecat/audio/filters/aic_filter.py @@ -336,13 +336,13 @@ class AICFilter(BaseAudioFilter): def _apply_enhancement_level(self): """Apply enhancement_level if configured and supported by the active model.""" - if self._enhancement_level is None or self._processor_ctx is None: + if self._processor_ctx is None or self._enhancement_level is None: return - level = float(self._enhancement_level if not self._bypass else 0.0) - try: - self._processor_ctx.set_parameter(ProcessorParameter.EnhancementLevel, level) + self._processor_ctx.set_parameter( + ProcessorParameter.EnhancementLevel, self._enhancement_level + ) except ParameterOutOfRangeError as e: logger.warning(f"AIC EnhancementLevel set_parameter out-of-range: {e}") self._enhancement_level = None From 780559dc32a771db0462cb2efe9614f32afa550f Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?G=C3=B6kmen=20G=C3=B6rgen?= Date: Tue, 10 Mar 2026 14:23:00 +0100 Subject: [PATCH 0900/1060] address feedback. --- src/pipecat/audio/filters/aic_filter.py | 3 +-- 1 file changed, 1 insertion(+), 2 deletions(-) diff --git a/src/pipecat/audio/filters/aic_filter.py b/src/pipecat/audio/filters/aic_filter.py index d4f0b37de..752f6f3fa 100644 --- a/src/pipecat/audio/filters/aic_filter.py +++ b/src/pipecat/audio/filters/aic_filter.py @@ -412,8 +412,7 @@ class AICFilter(BaseAudioFilter): logger.debug(f" Sample rate: {self._sample_rate} Hz") logger.debug(f" Frames per chunk: {self._frames_per_block}") if self._enhancement_level is not None: - level = self._enhancement_level if not self._bypass else 0.0 - logger.debug(f" Enhancement strength: {int(level * 100)}%") + logger.debug(f" Enhancement level: {self._enhancement_level}") else: logger.debug(" Enhancement level not configured; using the model's default behavior.") logger.debug(f" Optimal sample rate: {self._model.get_optimal_sample_rate()} Hz") From a96702acfcbfc33bd219f127d268ea83318393d3 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?G=C3=B6kmen=20G=C3=B6rgen?= Date: Tue, 10 Mar 2026 14:41:18 +0100 Subject: [PATCH 0901/1060] fix test. --- tests/test_aic_filter.py | 8 ++++---- 1 file changed, 4 insertions(+), 4 deletions(-) diff --git a/tests/test_aic_filter.py b/tests/test_aic_filter.py index 8403f3711..fb9d38457 100644 --- a/tests/test_aic_filter.py +++ b/tests/test_aic_filter.py @@ -522,11 +522,10 @@ class TestAICFilter(unittest.IsolatedAsyncioTestCase): self.assertEqual(unsupported_ctx.enhancement_attempts, 1) - async def test_process_frame_disable_sets_enhancement_to_zero(self): - """Test disable frame sets enhancement level to 0.0.""" + async def test_process_frame_disable_sets_bypass(self): + """Test disable frame toggles bypass.""" filter_instance = self._create_filter_with_mocks(enhancement_level=0.7) await self._start_filter_with_mocks(filter_instance) - await filter_instance.process_frame(self.FilterEnableFrame(enable=False)) enhancement_params = [ @@ -539,8 +538,9 @@ class TestAICFilter(unittest.IsolatedAsyncioTestCase): for p, v in self.mock_processor.processor_ctx.parameters_set if p == aic_sdk.ProcessorParameter.Bypass ] + self.assertTrue(filter_instance._bypass) - self.assertEqual(enhancement_params[-1][1], 0.0) + self.assertEqual(enhancement_params[-1][1], 0.7) self.assertEqual(bypass_params[-1][1], 1.0) async def test_process_frame_enable_restores_configured_enhancement(self): From 3a6f848a5b5b7006a95bb0bdba98e81ffa2f081c Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?G=C3=B6kmen=20G=C3=B6rgen?= Date: Tue, 10 Mar 2026 14:54:49 +0100 Subject: [PATCH 0902/1060] update test description. --- tests/test_aic_filter.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/tests/test_aic_filter.py b/tests/test_aic_filter.py index fb9d38457..b04054180 100644 --- a/tests/test_aic_filter.py +++ b/tests/test_aic_filter.py @@ -285,7 +285,7 @@ class TestAICFilter(unittest.IsolatedAsyncioTestCase): self.assertIsNotNone(filter_instance._vad_ctx) async def test_start_applies_initial_bypass_parameter(self): - """Test that start applies SDK Bypass parameter.""" + """Test that start applies bypass parameter.""" filter_instance = self._create_filter_with_mocks() await self._start_filter_with_mocks(filter_instance) From ba0ebd5525f5bd93afff41fc18292c0822f28234 Mon Sep 17 00:00:00 2001 From: sysradium Date: Mon, 9 Mar 2026 00:38:14 +0100 Subject: [PATCH 0903/1060] Treat conversation_already_has_active_response as non-fatal in Realtime API --- changelog/3960.fixed.md | 1 + src/pipecat/services/grok/realtime/llm.py | 5 ++++- src/pipecat/services/openai/realtime/llm.py | 5 ++++- src/pipecat/services/openai_realtime_beta/openai.py | 5 ++++- 4 files changed, 13 insertions(+), 3 deletions(-) create mode 100644 changelog/3960.fixed.md diff --git a/changelog/3960.fixed.md b/changelog/3960.fixed.md new file mode 100644 index 000000000..404569234 --- /dev/null +++ b/changelog/3960.fixed.md @@ -0,0 +1 @@ +- Fixed OpenAI Realtime, OpenAI Realtime Beta, and Grok realtime services treating `conversation_already_has_active_response` as a fatal error. These services now log it as a non-fatal debug event when a response is already in progress. diff --git a/src/pipecat/services/grok/realtime/llm.py b/src/pipecat/services/grok/realtime/llm.py index 7e252ebf5..39cf06a10 100644 --- a/src/pipecat/services/grok/realtime/llm.py +++ b/src/pipecat/services/grok/realtime/llm.py @@ -676,7 +676,10 @@ class GrokRealtimeLLMService(LLMService): elif evt.type == "response.function_call_arguments.done": await self._handle_evt_function_call_arguments_done(evt) elif evt.type == "error": - if evt.error.code == "response_cancel_not_active": + if evt.error.code in ( + "response_cancel_not_active", + "conversation_already_has_active_response", + ): logger.debug(f"{self} {evt.error.message}") else: await self._handle_evt_error(evt) diff --git a/src/pipecat/services/openai/realtime/llm.py b/src/pipecat/services/openai/realtime/llm.py index c25181dd1..25afc0ef1 100644 --- a/src/pipecat/services/openai/realtime/llm.py +++ b/src/pipecat/services/openai/realtime/llm.py @@ -747,7 +747,10 @@ class OpenAIRealtimeLLMService(LLMService): await self._handle_evt_function_call_arguments_done(evt) elif evt.type == "error": if not await self._maybe_handle_evt_retrieve_conversation_item_error(evt): - if evt.error.code == "response_cancel_not_active": + if evt.error.code in ( + "response_cancel_not_active", + "conversation_already_has_active_response", + ): logger.debug(f"{self} {evt.error.message}") else: await self._handle_evt_error(evt) diff --git a/src/pipecat/services/openai_realtime_beta/openai.py b/src/pipecat/services/openai_realtime_beta/openai.py index 689ca91a5..d603eda83 100644 --- a/src/pipecat/services/openai_realtime_beta/openai.py +++ b/src/pipecat/services/openai_realtime_beta/openai.py @@ -555,7 +555,10 @@ class OpenAIRealtimeBetaLLMService(LLMService): await self._handle_evt_audio_transcript_delta(evt) elif evt.type == "error": if not await self._maybe_handle_evt_retrieve_conversation_item_error(evt): - if evt.error.code == "response_cancel_not_active": + if evt.error.code in ( + "response_cancel_not_active", + "conversation_already_has_active_response", + ): logger.debug(f"{self} {evt.error.message}") else: await self._handle_evt_error(evt) From 92b5185165fded60cb4a3b6c9ca02df79997dd0b Mon Sep 17 00:00:00 2001 From: Mark Backman Date: Sun, 8 Mar 2026 13:16:42 -0400 Subject: [PATCH 0904/1060] Route Deepgram WebSocket TTS audio through audio context queue The Deepgram TTS service was bypassing pipecats audio context management system, pushing audio frames directly via push_frame() instead of routing them through append_to_audio_context(). This caused stale audio to leak into the pipeline after interruptions and missed ordered playback guarantees. - Route audio frames through append_to_audio_context() with context availability checks to discard stale post-interruption frames - Handle Flushed responses by appending TTSStoppedFrame and removing the audio context to signal completion - Replace _handle_interruption override with on_audio_context_interrupted hook (the recommended pattern used by ElevenLabs and Cartesia) - Remove redundant process_frame override that caused double-flush (base class already flushes via on_turn_context_completed) - Remove redundant start_tts_usage_metrics call (base class handles aggregated usage metrics) --- src/pipecat/services/deepgram/tts.py | 54 ++++++++++------------------ 1 file changed, 19 insertions(+), 35 deletions(-) diff --git a/src/pipecat/services/deepgram/tts.py b/src/pipecat/services/deepgram/tts.py index 5d6e5ffdc..ae064fffd 100644 --- a/src/pipecat/services/deepgram/tts.py +++ b/src/pipecat/services/deepgram/tts.py @@ -22,12 +22,10 @@ from pipecat.frames.frames import ( EndFrame, ErrorFrame, Frame, - InterruptionFrame, - LLMFullResponseEndFrame, StartFrame, TTSAudioRawFrame, + TTSStoppedFrame, ) -from pipecat.processors.frame_processor import FrameDirection from pipecat.services.settings import TTSSettings, _warn_deprecated_param from pipecat.services.tts_service import TTSService, WebsocketTTSService from pipecat.utils.tracing.service_decorators import traced_tts @@ -119,7 +117,7 @@ class DeepgramTTSService(WebsocketTTSService): super().__init__( sample_rate=sample_rate, pause_frame_processing=True, - push_stop_frames=True, + push_stop_frames=False, push_start_frame=True, append_trailing_space=True, settings=default_settings, @@ -167,19 +165,6 @@ class DeepgramTTSService(WebsocketTTSService): await super().cancel(frame) await self._disconnect() - async def process_frame(self, frame: Frame, direction: FrameDirection): - """Process frames with special handling for LLM response end. - - Args: - frame: The frame to process. - direction: The direction of frame processing. - """ - await super().process_frame(frame, direction) - - # When the LLM finishes responding, flush any remaining text in Deepgram's buffer - if isinstance(frame, (LLMFullResponseEndFrame, EndFrame)): - await self.flush_audio() - async def _connect(self): """Connect to Deepgram WebSocket and start receive task.""" await super()._connect() @@ -276,19 +261,19 @@ class DeepgramTTSService(WebsocketTTSService): return self._websocket raise Exception("Websocket not connected") - async def _handle_interruption(self, frame: InterruptionFrame, direction: FrameDirection): - """Handle interruption by sending Clear message to Deepgram. + async def on_audio_context_interrupted(self, context_id: str): + """Send Clear message to Deepgram when an audio context is interrupted. The Clear message will clear Deepgram's internal text buffer and stop sending audio, allowing for a new response to be generated. - """ - await super()._handle_interruption(frame, direction) - # Send Clear message to stop current audio generation + Args: + context_id: The ID of the audio context that was interrupted. + """ + await self.stop_all_metrics() if self._websocket: try: - clear_msg = {"type": "Clear"} - await self._websocket.send(json.dumps(clear_msg)) + await self._websocket.send(json.dumps({"type": "Clear"})) except Exception as e: logger.error(f"{self} error sending Clear message: {e}") @@ -297,11 +282,9 @@ class DeepgramTTSService(WebsocketTTSService): async for message in self._get_websocket(): if isinstance(message, bytes): # Binary message contains audio data - await self.stop_ttfb_metrics() - frame = TTSAudioRawFrame( - message, self.sample_rate, 1, context_id=self.get_active_audio_context_id() - ) - await self.push_frame(frame) + ctx_id = self.get_active_audio_context_id() + frame = TTSAudioRawFrame(message, self.sample_rate, 1, context_id=ctx_id) + await self.append_to_audio_context(ctx_id, frame) elif isinstance(message, str): # Text message contains metadata or control messages try: @@ -312,12 +295,15 @@ class DeepgramTTSService(WebsocketTTSService): logger.trace(f"Received metadata: {msg}") elif msg_type == "Flushed": logger.trace(f"Received Flushed: {msg}") - # Flushed indicates the end of audio generation for the current buffer - # This happens after flush_audio() is called + ctx_id = self.get_active_audio_context_id() + await self.append_to_audio_context( + ctx_id, TTSStoppedFrame(context_id=ctx_id) + ) + await self.remove_audio_context(ctx_id) elif msg_type == "Cleared": logger.trace(f"Received Cleared: {msg}") - # Buffer has been cleared after interruption - # TTSStoppedFrame will be sent by the interruption handler + # Buffer has been cleared after interruption. + # The on_audio_context_interrupted handler already cleaned up. elif msg_type == "Warning": logger.warning( f"{self} warning: {msg.get('description', 'Unknown warning')}" @@ -358,8 +344,6 @@ class DeepgramTTSService(WebsocketTTSService): if not self._websocket or self._websocket.state is State.CLOSED: await self._connect() - await self.start_tts_usage_metrics(text) - # Send text message to Deepgram # Note: We don't send Flush here - that should only be sent when the # LLM finishes a complete response via flush_audio() From d5c0789ab585efc43b836a25f55b5216a9c60c17 Mon Sep 17 00:00:00 2001 From: Mark Backman Date: Sun, 8 Mar 2026 13:18:02 -0400 Subject: [PATCH 0905/1060] Add changelog for #3958 --- changelog/3958.changed.md | 1 + changelog/3958.fixed.md | 1 + 2 files changed, 2 insertions(+) create mode 100644 changelog/3958.changed.md create mode 100644 changelog/3958.fixed.md diff --git a/changelog/3958.changed.md b/changelog/3958.changed.md new file mode 100644 index 000000000..dbeabd0f2 --- /dev/null +++ b/changelog/3958.changed.md @@ -0,0 +1 @@ +- Changed `DeepgramTTSService` to send a Clear message on interruption instead of disconnecting and reconnecting the WebSocket, allowing the connection to persist throughout the session. diff --git a/changelog/3958.fixed.md b/changelog/3958.fixed.md new file mode 100644 index 000000000..8bc21dffe --- /dev/null +++ b/changelog/3958.fixed.md @@ -0,0 +1 @@ +- Fixed `TTSService` audio context queue getting blocked when `append_to_audio_context()` was called with a `None` context ID, which prevented subsequent audio from being delivered. From 50cc01a578c0f66f478eaf1a7c2f97dad315df25 Mon Sep 17 00:00:00 2001 From: Mark Backman Date: Tue, 10 Mar 2026 11:25:59 -0400 Subject: [PATCH 0906/1060] Guard against None context ID in append_to_audio_context After interruption, both _playing_context_id and _turn_context_id are None. If a subclass calls append_to_audio_context(None, frame), the recovery path matches (None == None) and creates a bogus audio context that blocks the handler from ever processing the real context. Early-return when context_id is falsy to prevent this. --- src/pipecat/services/tts_service.py | 3 +++ 1 file changed, 3 insertions(+) diff --git a/src/pipecat/services/tts_service.py b/src/pipecat/services/tts_service.py index db695fd52..3c0161fa5 100644 --- a/src/pipecat/services/tts_service.py +++ b/src/pipecat/services/tts_service.py @@ -1182,6 +1182,9 @@ class TTSService(AIService): context_id: The context to append audio to. frame: The audio or control frame to append. """ + if not context_id: + logger.debug(f"{self} unable to append audio to context: no context ID provided") + return if self.audio_context_available(context_id): logger.trace(f"{self} appending audio {frame} to audio context {context_id}") await self._audio_contexts[context_id].put(frame) From 153705f05ba4ea6474e282f5d73e8374e413e957 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Aleix=20Conchillo=20Flaqu=C3=A9?= Date: Tue, 10 Mar 2026 09:25:42 -0700 Subject: [PATCH 0907/1060] Fix Google LLM system instruction priority Constructor/settings system_instruction now takes priority over the context system message. Previously the context value would overwrite the constructor value on every call. Warn when both are set. --- src/pipecat/services/google/llm.py | 18 +++++++++++------- 1 file changed, 11 insertions(+), 7 deletions(-) diff --git a/src/pipecat/services/google/llm.py b/src/pipecat/services/google/llm.py index 7f4f8caae..d14795d29 100644 --- a/src/pipecat/services/google/llm.py +++ b/src/pipecat/services/google/llm.py @@ -997,12 +997,16 @@ class GoogleLLMService(LLMService): self, params_from_context: GeminiLLMInvocationParams ) -> AsyncIterator[GenerateContentResponse]: messages = params_from_context["messages"] - if ( - params_from_context["system_instruction"] - and self._settings.system_instruction != params_from_context["system_instruction"] - ): - logger.debug(f"System instruction changed: {params_from_context['system_instruction']}") - self._settings.system_instruction = params_from_context["system_instruction"] + + # Constructor/settings system instruction takes priority over context. + if self._settings.system_instruction and params_from_context["system_instruction"]: + logger.warning( + f"{self}: Both system_instruction and a system message in context are" + " set. Using system_instruction." + ) + system_instruction = ( + self._settings.system_instruction or params_from_context["system_instruction"] + ) tools = [] if params_from_context["tools"]: @@ -1015,7 +1019,7 @@ class GoogleLLMService(LLMService): # Build generation parameters generation_params = self._build_generation_params( - system_instruction=self._settings.system_instruction, + system_instruction=system_instruction, tools=tools, tool_config=tool_config, ) From db27aaa7903c3697a426dc6add1be6f3ef8321fe Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Aleix=20Conchillo=20Flaqu=C3=A9?= Date: Tue, 10 Mar 2026 09:26:26 -0700 Subject: [PATCH 0908/1060] Add changelog for #3976 --- changelog/3976.fixed.md | 1 + 1 file changed, 1 insertion(+) create mode 100644 changelog/3976.fixed.md diff --git a/changelog/3976.fixed.md b/changelog/3976.fixed.md new file mode 100644 index 000000000..3153cdcbe --- /dev/null +++ b/changelog/3976.fixed.md @@ -0,0 +1 @@ +- Fixed `GoogleLLMService` ignoring the `system_instruction` set via constructor or `GoogleLLMSettings` when a system message was also present in the context. The settings value now correctly takes priority, and a warning is logged when both are set. From 912f1be31c78f63e3b1777ec12f7e9b3b809dbb2 Mon Sep 17 00:00:00 2001 From: Mark Backman Date: Tue, 10 Mar 2026 12:57:23 -0400 Subject: [PATCH 0909/1060] Add system_instruction parameter to run_inference (#3968) * Add system_instruction parameter to run_inference Allow callers to provide a custom system instruction directly when calling run_inference, without having to construct provider-specific context objects. For OpenAI, the instruction is prepended as a system message (preserving existing messages). For Anthropic, Google, and AWS Bedrock, it overrides the single system field with a warning when an existing system instruction is present in the context. * Use system_instruction parameter in _generate_summary Pass the summarization prompt via run_inference's system_instruction parameter instead of embedding it as a system message in the context. * Add changelog for #3968 --- changelog/3968.added.md | 1 + src/pipecat/pipeline/llm_switcher.py | 6 +- src/pipecat/services/anthropic/llm.py | 16 +- src/pipecat/services/aws/llm.py | 16 +- src/pipecat/services/google/llm.py | 16 +- src/pipecat/services/llm_service.py | 25 ++- src/pipecat/services/openai/base_llm.py | 17 +- tests/test_run_inference.py | 256 +++++++++++++++++++++++- 8 files changed, 332 insertions(+), 21 deletions(-) create mode 100644 changelog/3968.added.md diff --git a/changelog/3968.added.md b/changelog/3968.added.md new file mode 100644 index 000000000..cd9be5996 --- /dev/null +++ b/changelog/3968.added.md @@ -0,0 +1 @@ +- Added `system_instruction` parameter to `run_inference` across all LLM services, allowing callers to override the system prompt for one-shot inference calls. Used by `_generate_summary` to pass the summarization prompt cleanly. diff --git a/src/pipecat/pipeline/llm_switcher.py b/src/pipecat/pipeline/llm_switcher.py index f9f53c066..281bedc65 100644 --- a/src/pipecat/pipeline/llm_switcher.py +++ b/src/pipecat/pipeline/llm_switcher.py @@ -52,17 +52,19 @@ class LLMSwitcher(ServiceSwitcher[StrategyType]): """ return self.strategy.active_service - async def run_inference(self, context: LLMContext) -> Optional[str]: + async def run_inference(self, context: LLMContext, **kwargs) -> Optional[str]: """Run a one-shot, out-of-band (i.e. out-of-pipeline) inference with the given LLM context, using the currently active LLM. Args: context: The LLM context containing conversation history. + **kwargs: Additional arguments forwarded to the active LLM's run_inference + (e.g. max_tokens, system_instruction). Returns: The LLM's response as a string, or None if no response is generated. """ if self.active_llm: - return await self.active_llm.run_inference(context=context) + return await self.active_llm.run_inference(context=context, **kwargs) return None def register_function( diff --git a/src/pipecat/services/anthropic/llm.py b/src/pipecat/services/anthropic/llm.py index 7abcec3e0..6bf7bf180 100644 --- a/src/pipecat/services/anthropic/llm.py +++ b/src/pipecat/services/anthropic/llm.py @@ -346,7 +346,10 @@ class AnthropicLLMService(LLMService): return response async def run_inference( - self, context: LLMContext | OpenAILLMContext, max_tokens: Optional[int] = None + self, + context: LLMContext | OpenAILLMContext, + max_tokens: Optional[int] = None, + system_instruction: Optional[str] = None, ) -> Optional[str]: """Run a one-shot, out-of-band (i.e. out-of-pipeline) inference with the given LLM context. @@ -354,6 +357,8 @@ class AnthropicLLMService(LLMService): context: The LLM context containing conversation history. max_tokens: Optional maximum number of tokens to generate. If provided, overrides the service's default max_tokens setting. + system_instruction: Optional system instruction to use for this inference. + If provided, overrides any system instruction in the context. Returns: The LLM's response as a string, or None if no response is generated. @@ -375,6 +380,15 @@ class AnthropicLLMService(LLMService): system = getattr(context, "system", NOT_GIVEN) tools = context.tools or [] + # Override system instruction if provided + if system_instruction is not None: + if system and system is not NOT_GIVEN: + logger.warning( + f"{self}: Both system_instruction and a system message in context are set." + " Using system_instruction." + ) + system = system_instruction + # Build params using the same method as streaming completions params = { "model": self._settings.model, diff --git a/src/pipecat/services/aws/llm.py b/src/pipecat/services/aws/llm.py index 434011f1f..c77321ead 100644 --- a/src/pipecat/services/aws/llm.py +++ b/src/pipecat/services/aws/llm.py @@ -923,7 +923,10 @@ class AWSBedrockLLMService(LLMService): return inference_config async def run_inference( - self, context: LLMContext | OpenAILLMContext, max_tokens: Optional[int] = None + self, + context: LLMContext | OpenAILLMContext, + max_tokens: Optional[int] = None, + system_instruction: Optional[str] = None, ) -> Optional[str]: """Run a one-shot, out-of-band (i.e. out-of-pipeline) inference with the given LLM context. @@ -931,6 +934,8 @@ class AWSBedrockLLMService(LLMService): context: The LLM context containing conversation history. max_tokens: Optional maximum number of tokens to generate. If provided, overrides the service's default max_tokens setting. + system_instruction: Optional system instruction to use for this inference. + If provided, overrides any system instruction in the context. Returns: The LLM's response as a string, or None if no response is generated. @@ -947,6 +952,15 @@ class AWSBedrockLLMService(LLMService): messages = context.messages system = getattr(context, "system", None) # [{"text": "system message"}] + # Override system instruction if provided + if system_instruction is not None: + if system: + logger.warning( + f"{self}: Both system_instruction and a system message in context are set." + " Using system_instruction." + ) + system = [{"text": system_instruction}] + # Prepare request parameters using the same method as streaming inference_config = self._build_inference_config() diff --git a/src/pipecat/services/google/llm.py b/src/pipecat/services/google/llm.py index 7f4f8caae..85f8c0ce3 100644 --- a/src/pipecat/services/google/llm.py +++ b/src/pipecat/services/google/llm.py @@ -881,7 +881,10 @@ class GoogleLLMService(LLMService): self._client = genai.Client(api_key=self._api_key, http_options=self._http_options) async def run_inference( - self, context: LLMContext | OpenAILLMContext, max_tokens: Optional[int] = None + self, + context: LLMContext | OpenAILLMContext, + max_tokens: Optional[int] = None, + system_instruction: Optional[str] = None, ) -> Optional[str]: """Run a one-shot, out-of-band (i.e. out-of-pipeline) inference with the given LLM context. @@ -889,6 +892,8 @@ class GoogleLLMService(LLMService): context: The LLM context containing conversation history. max_tokens: Optional maximum number of tokens to generate. If provided, overrides the service's default max_tokens setting. + system_instruction: Optional system instruction to use for this inference. + If provided, overrides any system instruction in the context. Returns: The LLM's response as a string, or None if no response is generated. @@ -908,6 +913,15 @@ class GoogleLLMService(LLMService): system = getattr(context, "system_message", None) tools = context.tools or [] + # Override system instruction if provided + if system_instruction is not None: + if system: + logger.warning( + f"{self}: Both system_instruction and a system message in context are set." + " Using system_instruction." + ) + system = system_instruction + # Build generation config using the same method as streaming generation_params = self._build_generation_params( system_instruction=system, tools=tools if tools else None diff --git a/src/pipecat/services/llm_service.py b/src/pipecat/services/llm_service.py index 44858038d..7944f413a 100644 --- a/src/pipecat/services/llm_service.py +++ b/src/pipecat/services/llm_service.py @@ -244,7 +244,10 @@ class LLMService(UserTurnCompletionLLMServiceMixin, AIService): return self.get_llm_adapter().create_llm_specific_message(message) async def run_inference( - self, context: LLMContext | OpenAILLMContext, max_tokens: Optional[int] = None + self, + context: LLMContext | OpenAILLMContext, + max_tokens: Optional[int] = None, + system_instruction: Optional[str] = None, ) -> Optional[str]: """Run a one-shot, out-of-band (i.e. out-of-pipeline) inference with the given LLM context. @@ -254,6 +257,8 @@ class LLMService(UserTurnCompletionLLMServiceMixin, AIService): context: The LLM context containing conversation history. max_tokens: Optional maximum number of tokens to generate. If provided, overrides the service's default max_tokens/max_completion_tokens setting. + system_instruction: Optional system instruction to use for this inference. + If provided, overrides any system instruction in the context. Returns: The LLM's response as a string, or None if no response is generated. @@ -535,23 +540,17 @@ class LLMService(UserTurnCompletionLLMServiceMixin, AIService): # Create summary context transcript = LLMContextSummarizationUtil.format_messages_for_summary(result.messages) - prompt_messages = [ - { - "role": "system", - "content": frame.summarization_prompt, - }, - { - "role": "user", - "content": f"Conversation history:\n{transcript}", - }, - ] - summary_context = LLMContext(messages=prompt_messages) + summary_context = LLMContext( + messages=[{"role": "user", "content": f"Conversation history:\n{transcript}"}] + ) # Generate summary using run_inference # This will be overridden by each LLM service implementation try: summary_text = await self.run_inference( - summary_context, max_tokens=frame.target_context_tokens + summary_context, + max_tokens=frame.target_context_tokens, + system_instruction=frame.summarization_prompt, ) except NotImplementedError: raise RuntimeError( diff --git a/src/pipecat/services/openai/base_llm.py b/src/pipecat/services/openai/base_llm.py index 5466c75a5..c62147c3d 100644 --- a/src/pipecat/services/openai/base_llm.py +++ b/src/pipecat/services/openai/base_llm.py @@ -342,7 +342,10 @@ class BaseOpenAILLMService(LLMService): return params async def run_inference( - self, context: LLMContext | OpenAILLMContext, max_tokens: Optional[int] = None + self, + context: LLMContext | OpenAILLMContext, + max_tokens: Optional[int] = None, + system_instruction: Optional[str] = None, ) -> Optional[str]: """Run a one-shot, out-of-band (i.e. out-of-pipeline) inference with the given LLM context. @@ -350,6 +353,8 @@ class BaseOpenAILLMService(LLMService): context: The LLM context containing conversation history. max_tokens: Optional maximum number of tokens to generate. If provided, overrides the service's default max_tokens/max_completion_tokens setting. + system_instruction: Optional system instruction to use for this inference. + If provided, overrides any system instruction in the context. Returns: The LLM's response as a string, or None if no response is generated. @@ -371,6 +376,16 @@ class BaseOpenAILLMService(LLMService): params["stream"] = False params.pop("stream_options", None) + # Prepend system instruction if provided + if system_instruction is not None: + messages = params.get("messages", []) + if messages and messages[0].get("role") == "system": + logger.warning( + f"{self}: Both system_instruction and a system message in context are set." + " Using system_instruction." + ) + params["messages"] = [{"role": "system", "content": system_instruction}] + messages + # Override max_tokens if provided if max_tokens is not None: # Use max_completion_tokens for newer models, fallback to max_tokens diff --git a/tests/test_run_inference.py b/tests/test_run_inference.py index eb18a5fda..4f4021b5d 100644 --- a/tests/test_run_inference.py +++ b/tests/test_run_inference.py @@ -511,5 +511,257 @@ async def test_aws_bedrock_run_inference_client_exception(): await service.run_inference(mock_context) -if __name__ == "__main__": - unittest.main() +# --- system_instruction parameter tests --- + + +@pytest.mark.asyncio +async def test_openai_run_inference_system_instruction_overrides_context(): + """Test that system_instruction overrides the system message from context.""" + with patch.object(OpenAILLMService, "create_client"): + service = OpenAILLMService(model="gpt-4") + service._client = AsyncMock() + + mock_context = MagicMock(spec=LLMContext) + mock_adapter = MagicMock() + test_messages = [ + {"role": "system", "content": "Original system message"}, + {"role": "user", "content": "Hello"}, + ] + mock_adapter.get_llm_invocation_params.return_value = OpenAILLMInvocationParams( + messages=test_messages, tools=OPENAI_NOT_GIVEN, tool_choice=OPENAI_NOT_GIVEN + ) + service.get_llm_adapter = MagicMock(return_value=mock_adapter) + + mock_response = MagicMock() + mock_response.choices = [MagicMock()] + mock_response.choices[0].message.content = "Response" + service._client.chat.completions.create.return_value = mock_response + + result = await service.run_inference( + mock_context, system_instruction="New system instruction" + ) + + assert result == "Response" + call_kwargs = service._client.chat.completions.create.call_args.kwargs + messages = call_kwargs["messages"] + # system_instruction should be prepended as the first message + assert messages[0] == {"role": "system", "content": "New system instruction"} + # Original system message should still be present + assert messages[1] == {"role": "system", "content": "Original system message"} + # User message should still be present + assert messages[2] == {"role": "user", "content": "Hello"} + assert len(messages) == 3 + + +@pytest.mark.asyncio +async def test_openai_run_inference_system_instruction_none_unchanged(): + """Test that when system_instruction is None, behavior is unchanged.""" + with patch.object(OpenAILLMService, "create_client"): + service = OpenAILLMService(model="gpt-4") + service._client = AsyncMock() + + mock_context = MagicMock(spec=LLMContext) + mock_adapter = MagicMock() + test_messages = [ + {"role": "system", "content": "Original system message"}, + {"role": "user", "content": "Hello"}, + ] + mock_adapter.get_llm_invocation_params.return_value = OpenAILLMInvocationParams( + messages=test_messages, tools=OPENAI_NOT_GIVEN, tool_choice=OPENAI_NOT_GIVEN + ) + service.get_llm_adapter = MagicMock(return_value=mock_adapter) + + mock_response = MagicMock() + mock_response.choices = [MagicMock()] + mock_response.choices[0].message.content = "Response" + service._client.chat.completions.create.return_value = mock_response + + result = await service.run_inference(mock_context) + + assert result == "Response" + call_kwargs = service._client.chat.completions.create.call_args.kwargs + messages = call_kwargs["messages"] + assert messages[0] == {"role": "system", "content": "Original system message"} + assert messages[1] == {"role": "user", "content": "Hello"} + + +@pytest.mark.asyncio +async def test_anthropic_run_inference_system_instruction_overrides_context(): + """Test that system_instruction overrides the system message for Anthropic.""" + service = AnthropicLLMService(api_key="test-key", model="claude-3-sonnet-20240229") + service._client = AsyncMock() + + mock_context = MagicMock(spec=LLMContext) + mock_adapter = MagicMock() + test_messages = [{"role": "user", "content": "Hello"}] + mock_adapter.get_llm_invocation_params.return_value = AnthropicLLMInvocationParams( + messages=test_messages, system="Original system", tools=[] + ) + service.get_llm_adapter = MagicMock(return_value=mock_adapter) + + mock_response = MagicMock() + mock_response.content = [MagicMock()] + mock_response.content[0].text = "Response" + service._client.beta.messages.create.return_value = mock_response + + result = await service.run_inference(mock_context, system_instruction="New system instruction") + + assert result == "Response" + call_kwargs = service._client.beta.messages.create.call_args.kwargs + assert call_kwargs["system"] == "New system instruction" + assert call_kwargs["messages"] == test_messages + + +@pytest.mark.asyncio +async def test_anthropic_run_inference_system_instruction_none_unchanged(): + """Test that when system_instruction is None, Anthropic behavior is unchanged.""" + service = AnthropicLLMService(api_key="test-key", model="claude-3-sonnet-20240229") + service._client = AsyncMock() + + mock_context = MagicMock(spec=LLMContext) + mock_adapter = MagicMock() + test_messages = [{"role": "user", "content": "Hello"}] + mock_adapter.get_llm_invocation_params.return_value = AnthropicLLMInvocationParams( + messages=test_messages, system="Original system", tools=[] + ) + service.get_llm_adapter = MagicMock(return_value=mock_adapter) + + mock_response = MagicMock() + mock_response.content = [MagicMock()] + mock_response.content[0].text = "Response" + service._client.beta.messages.create.return_value = mock_response + + result = await service.run_inference(mock_context) + + assert result == "Response" + call_kwargs = service._client.beta.messages.create.call_args.kwargs + assert call_kwargs["system"] == "Original system" + + +@pytest.mark.asyncio +async def test_google_run_inference_system_instruction_overrides_context(): + """Test that system_instruction overrides the system message for Google.""" + service = GoogleLLMService(api_key="test-key", model="gemini-2.0-flash") + service._client = AsyncMock() + + mock_context = MagicMock(spec=LLMContext) + mock_adapter = MagicMock() + test_messages = [{"role": "user", "content": "Hello"}] + mock_adapter.get_llm_invocation_params.return_value = GeminiLLMInvocationParams( + messages=test_messages, system_instruction="Original system", tools=NotGiven() + ) + service.get_llm_adapter = MagicMock(return_value=mock_adapter) + + mock_response = MagicMock() + mock_response.candidates = [MagicMock()] + mock_response.candidates[0].content = MagicMock() + mock_response.candidates[0].content.parts = [MagicMock()] + mock_response.candidates[0].content.parts[0].text = "Response" + service._client.aio = AsyncMock() + service._client.aio.models = AsyncMock() + service._client.aio.models.generate_content = AsyncMock(return_value=mock_response) + + result = await service.run_inference(mock_context, system_instruction="New system instruction") + + assert result == "Response" + call_kwargs = service._client.aio.models.generate_content.call_args.kwargs + config = call_kwargs["config"] + assert config.system_instruction == "New system instruction" + + +@pytest.mark.asyncio +async def test_google_run_inference_system_instruction_none_unchanged(): + """Test that when system_instruction is None, Google behavior is unchanged.""" + service = GoogleLLMService(api_key="test-key", model="gemini-2.0-flash") + service._client = AsyncMock() + + mock_context = MagicMock(spec=LLMContext) + mock_adapter = MagicMock() + test_messages = [{"role": "user", "content": "Hello"}] + mock_adapter.get_llm_invocation_params.return_value = GeminiLLMInvocationParams( + messages=test_messages, system_instruction="Original system", tools=NotGiven() + ) + service.get_llm_adapter = MagicMock(return_value=mock_adapter) + + mock_response = MagicMock() + mock_response.candidates = [MagicMock()] + mock_response.candidates[0].content = MagicMock() + mock_response.candidates[0].content.parts = [MagicMock()] + mock_response.candidates[0].content.parts[0].text = "Response" + service._client.aio = AsyncMock() + service._client.aio.models = AsyncMock() + service._client.aio.models.generate_content = AsyncMock(return_value=mock_response) + + result = await service.run_inference(mock_context) + + assert result == "Response" + call_kwargs = service._client.aio.models.generate_content.call_args.kwargs + config = call_kwargs["config"] + assert config.system_instruction == "Original system" + + +@pytest.mark.asyncio +async def test_aws_bedrock_run_inference_system_instruction_overrides_context(): + """Test that system_instruction overrides the system message for AWS Bedrock.""" + service = AWSBedrockLLMService(model="anthropic.claude-3-sonnet-20240229-v1:0") + + mock_context = MagicMock(spec=LLMContext) + mock_adapter = MagicMock() + test_messages = [{"role": "user", "content": [{"text": "Hello"}]}] + mock_adapter.get_llm_invocation_params.return_value = AWSBedrockLLMInvocationParams( + messages=test_messages, + system=[{"text": "Original system"}], + tools=[], + tool_choice=None, + ) + service.get_llm_adapter = MagicMock(return_value=mock_adapter) + + mock_client = AsyncMock() + mock_response = {"output": {"message": {"content": [{"text": "Response"}]}}} + mock_client.converse.return_value = mock_response + + mock_context_manager = AsyncMock() + mock_context_manager.__aenter__ = AsyncMock(return_value=mock_client) + mock_context_manager.__aexit__ = AsyncMock(return_value=None) + + with patch.object(service._aws_session, "client", return_value=mock_context_manager): + result = await service.run_inference( + mock_context, system_instruction="New system instruction" + ) + + assert result == "Response" + call_kwargs = mock_client.converse.call_args.kwargs + assert call_kwargs["system"] == [{"text": "New system instruction"}] + assert call_kwargs["messages"] == test_messages + + +@pytest.mark.asyncio +async def test_aws_bedrock_run_inference_system_instruction_none_unchanged(): + """Test that when system_instruction is None, AWS Bedrock behavior is unchanged.""" + service = AWSBedrockLLMService(model="anthropic.claude-3-sonnet-20240229-v1:0") + + mock_context = MagicMock(spec=LLMContext) + mock_adapter = MagicMock() + test_messages = [{"role": "user", "content": [{"text": "Hello"}]}] + mock_adapter.get_llm_invocation_params.return_value = AWSBedrockLLMInvocationParams( + messages=test_messages, + system=[{"text": "Original system"}], + tools=[], + tool_choice=None, + ) + service.get_llm_adapter = MagicMock(return_value=mock_adapter) + + mock_client = AsyncMock() + mock_response = {"output": {"message": {"content": [{"text": "Response"}]}}} + mock_client.converse.return_value = mock_response + + mock_context_manager = AsyncMock() + mock_context_manager.__aenter__ = AsyncMock(return_value=mock_client) + mock_context_manager.__aexit__ = AsyncMock(return_value=None) + + with patch.object(service._aws_session, "client", return_value=mock_context_manager): + result = await service.run_inference(mock_context) + + assert result == "Response" + call_kwargs = mock_client.converse.call_args.kwargs + assert call_kwargs["system"] == [{"text": "Original system"}] From 37906403225adde7276fbab7c1cfce90cf82d6ad Mon Sep 17 00:00:00 2001 From: Paul Kompfner Date: Tue, 10 Mar 2026 13:59:01 -0400 Subject: [PATCH 0910/1060] Fix an out-of-date comment for accuracy. In the OpenAI LLM service, we *don't* replace any context system messages with system instructions from the constructor. --- src/pipecat/services/openai/base_llm.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/src/pipecat/services/openai/base_llm.py b/src/pipecat/services/openai/base_llm.py index c62147c3d..9e3b6a282 100644 --- a/src/pipecat/services/openai/base_llm.py +++ b/src/pipecat/services/openai/base_llm.py @@ -327,7 +327,7 @@ class BaseOpenAILLMService(LLMService): params.update(self._settings.extra) - # Prepend system instruction from constructor, replacing any context system message + # Prepend system instruction from constructor if self._settings.system_instruction: messages = params.get("messages", []) if messages and messages[0].get("role") == "system": From 18e99123af3f171b43623f621101470fc0e24f89 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Aleix=20Conchillo=20Flaqu=C3=A9?= Date: Mon, 9 Mar 2026 23:55:24 -0700 Subject: [PATCH 0911/1060] Replace VirtualCameraDevice with CustomVideoTrack and add custom video track support Use CustomVideoSource/CustomVideoTrack for the default camera output instead of VirtualCameraDevice, mirroring how audio already uses CustomAudioSource/CustomAudioTrack. Add support for custom video destinations (register_video_destination, add/remove custom video tracks, routing in write_video_frame) so multiple video tracks can be published simultaneously. --- src/pipecat/transports/daily/transport.py | 197 +++++++++++++++++++--- 1 file changed, 173 insertions(+), 24 deletions(-) diff --git a/src/pipecat/transports/daily/transport.py b/src/pipecat/transports/daily/transport.py index 421e5db8e..1ded5ded7 100644 --- a/src/pipecat/transports/daily/transport.py +++ b/src/pipecat/transports/daily/transport.py @@ -57,10 +57,11 @@ try: CallClient, CustomAudioSource, CustomAudioTrack, + CustomVideoSource, + CustomVideoTrack, Daily, EventHandler, VideoFrame, - VirtualCameraDevice, VirtualSpeakerDevice, ) from daily import LogLevel as DailyLogLevel @@ -304,6 +305,44 @@ class DailyTranscriptionSettings(BaseModel): extra: Mapping[str, Any] = {"interim_results": True} +class DailyCustomVideoTrackParams(BaseModel): + """Configuration for a custom video track. + + If ``send_settings`` is not provided, the track will use the default video + publishing settings (framerate, bitrate, codec, etc.). + + Parameters: + width: Video width in pixels. + height: Video height in pixels. + color_format: Video color format (e.g., "RGB", "RGBA", "BGRA"). + send_settings: Optional Daily sendSettings dict for this track. + See https://reference-python.daily.co/types.html#videopublishingsettings + """ + + width: int = 1024 + height: int = 768 + color_format: str = "RGB" + send_settings: Optional[Dict[str, Any]] = None + + +class DailyCustomAudioTrackParams(BaseModel): + """Configuration for a custom audio track. + + If ``send_settings`` is not provided, the track will use the default audio + publishing settings (bitrate, channel config, etc.). + + Parameters: + sample_rate: Audio sample rate in Hz. Defaults to transport's output sample rate. + channels: Number of audio channels. + send_settings: Optional Daily sendSettings dict for this track. + See https://reference-python.daily.co/types.html#audiopublishingsettings + """ + + sample_rate: Optional[int] = None + channels: int = 1 + send_settings: Optional[Dict[str, Any]] = None + + class DailyParams(TransportParams): """Configuration parameters for Daily transport. @@ -311,8 +350,10 @@ class DailyParams(TransportParams): api_url: Daily API base URL. api_key: Daily API authentication key. audio_in_user_tracks: Receive users' audio in separate tracks - dialin_settings: Optional settings for dial-in functionality. camera_out_enabled: Whether to enable the main camera output track. + custom_audio_track_params: Per-destination configuration for custom audio tracks. + custom_video_track_params: Per-destination configuration for custom video tracks. + dialin_settings: Optional settings for dial-in functionality. microphone_out_enabled: Whether to enable the main microphone track. transcription_enabled: Whether to enable speech transcription. transcription_settings: Configuration for transcription service. @@ -321,8 +362,10 @@ class DailyParams(TransportParams): api_url: str = "https://api.daily.co/v1" api_key: str = "" audio_in_user_tracks: bool = True - dialin_settings: Optional[DailyDialinSettings] = None camera_out_enabled: bool = True + custom_audio_track_params: Optional[Mapping[str, DailyCustomAudioTrackParams]] = None + custom_video_track_params: Optional[Mapping[str, DailyCustomVideoTrackParams]] = None + dialin_settings: Optional[DailyDialinSettings] = None microphone_out_enabled: bool = True transcription_enabled: bool = False transcription_settings: DailyTranscriptionSettings = DailyTranscriptionSettings() @@ -430,6 +473,19 @@ class DailyAudioTrack: track: CustomAudioTrack +@dataclass +class DailyVideoTrack: + """Container for Daily video track components. + + Parameters: + source: The custom video source for the track. + track: The custom video track instance. + """ + + source: CustomVideoSource + track: CustomVideoTrack + + # This is just a type alias for the errors returned by daily-python. Right now # they are just a string. CallClientError = str @@ -519,14 +575,11 @@ class DailyTransportClient(EventHandler): self._in_sample_rate = 0 self._out_sample_rate = 0 - self._camera: Optional[VirtualCameraDevice] = None self._speaker: Optional[VirtualSpeakerDevice] = None + self._camera_track: Optional[DailyVideoTrack] = None self._microphone_track: Optional[DailyAudioTrack] = None self._custom_audio_tracks: Dict[str, DailyAudioTrack] = {} - - def _camera_name(self): - """Generate a unique virtual camera name for this client instance.""" - return f"camera-{self}" + self._custom_video_tracks: Dict[str, DailyVideoTrack] = {} def _speaker_name(self): """Generate a unique virtual speaker name for this client instance.""" @@ -625,8 +678,29 @@ class DailyTransportClient(EventHandler): Args: destination: The destination identifier to register. """ - self._custom_audio_tracks[destination] = await self.add_custom_audio_track(destination) - self._client.update_publishing({"customAudio": {destination: True}}) + params = (self._params.custom_audio_track_params or {}).get(destination) + self._custom_audio_tracks[destination] = await self.add_custom_audio_track( + destination, params=params + ) + publishing: Dict[str, Any] = {"customAudio": {destination: True}} + if params and params.send_settings: + publishing["customAudio"][destination] = {"sendSettings": params.send_settings} + self._client.update_publishing(publishing) + + async def register_video_destination(self, destination: str): + """Register a custom video destination for multi-track output. + + Args: + destination: The destination identifier to register. + """ + params = (self._params.custom_video_track_params or {}).get(destination) + self._custom_video_tracks[destination] = await self.add_custom_video_track( + destination, params=params + ) + publishing: Dict[str, Any] = {"customVideo": {destination: True}} + if params and params.send_settings: + publishing["customVideo"][destination] = {"sendSettings": params.send_settings} + self._client.update_publishing(publishing) async def write_audio_frame(self, frame: OutputAudioRawFrame) -> bool: """Write an audio frame to the appropriate audio track. @@ -657,7 +731,7 @@ class DailyTransportClient(EventHandler): return num_frames > 0 async def write_video_frame(self, frame: OutputImageRawFrame) -> bool: - """Write a video frame to the camera device. + """Write a video frame to the appropriate video track. Args: frame: The image frame to write. @@ -665,10 +739,20 @@ class DailyTransportClient(EventHandler): Returns: True if the video frame was written successfully, False otherwise. """ - if not frame.transport_destination and self._camera: - self._camera.write_frame(frame.image) + destination = frame.transport_destination + video_source: Optional[CustomVideoSource] = None + if not destination and self._camera_track: + video_source = self._camera_track.source + elif destination and destination in self._custom_video_tracks: + track = self._custom_video_tracks[destination] + video_source = track.source + + if video_source: + video_source.write_frame(frame.image) return True - return False + else: + logger.warning(f"{self} unable to write video frames to destination [{destination}]") + return False async def setup(self, setup: FrameProcessorSetup): """Setup the client with task manager and event queues. @@ -733,13 +817,14 @@ class DailyTransportClient(EventHandler): self._callback_task_handler(self._video_queue), f"{self}::video_callback_task", ) - if self._params.video_out_enabled and not self._camera: - self._camera = Daily.create_camera_device( - self._camera_name(), - width=self._params.video_out_width, - height=self._params.video_out_height, - color_format=self._params.video_out_color_format, + if self._params.video_out_enabled and not self._camera_track: + video_source = CustomVideoSource( + self._params.video_out_width, + self._params.video_out_height, + self._params.video_out_color_format, ) + video_track = CustomVideoTrack(video_source) + self._camera_track = DailyVideoTrack(source=video_source, track=video_track) if self._params.audio_out_enabled and not self._microphone_track: audio_source = CustomAudioSource(self._out_sample_rate, self._params.audio_out_channels) @@ -809,7 +894,11 @@ class DailyTransportClient(EventHandler): "camera": { "isEnabled": camera_enabled, "settings": { - "deviceId": self._camera_name(), + "customTrack": { + "id": self._camera_track.track.id + if self._camera_track + else "no-camera-track" + } }, }, "microphone": { @@ -874,6 +963,8 @@ class DailyTransportClient(EventHandler): # Remove any custom tracks, if any. for track_name, _ in self._custom_audio_tracks.items(): await self.remove_custom_audio_track(track_name) + for track_name, _ in self._custom_video_tracks.items(): + await self.remove_custom_video_track(track_name) error = await self._leave() if not error: @@ -1173,18 +1264,26 @@ class DailyTransportClient(EventHandler): color_format=color_format, ) - async def add_custom_audio_track(self, track_name: str) -> DailyAudioTrack: + async def add_custom_audio_track( + self, + track_name: str, + params: Optional[DailyCustomAudioTrackParams] = None, + ) -> DailyAudioTrack: """Add a custom audio track for multi-stream output. Args: track_name: Name for the custom audio track. + params: Optional per-track configuration for sample rate, channels, and sendSettings. Returns: The created DailyAudioTrack instance. """ future = self._get_event_loop().create_future() - audio_source = CustomAudioSource(self._out_sample_rate, 1) + sample_rate = params.sample_rate if params and params.sample_rate else self._out_sample_rate + channels = params.channels if params else 1 + + audio_source = CustomAudioSource(sample_rate, channels) audio_track = CustomAudioTrack(audio_source) @@ -1217,6 +1316,56 @@ class DailyTransportClient(EventHandler): ) return await future + async def add_custom_video_track( + self, + track_name: str, + params: Optional[DailyCustomVideoTrackParams] = None, + ) -> DailyVideoTrack: + """Add a custom video track for multi-stream output. + + Args: + track_name: Name for the custom video track. + params: Optional per-track configuration for dimensions, color format, and sendSettings. + + Returns: + The created DailyVideoTrack instance. + """ + future = self._get_event_loop().create_future() + + width = params.width if params else self._params.video_out_width + height = params.height if params else self._params.video_out_height + color_format = params.color_format if params else self._params.video_out_color_format + + video_source = CustomVideoSource(width, height, color_format) + + video_track = CustomVideoTrack(video_source) + + self._client.add_custom_video_track( + track_name=track_name, + video_track=video_track, + completion=completion_callback(future), + ) + + await future + + return DailyVideoTrack(source=video_source, track=video_track) + + async def remove_custom_video_track(self, track_name: str) -> Optional[CallClientError]: + """Remove a custom video track. + + Args: + track_name: Name of the custom video track to remove. + + Returns: + error: An error description or None. + """ + future = self._get_event_loop().create_future() + self._client.remove_custom_video_track( + track_name=track_name, + completion=completion_callback(future), + ) + return await future + async def update_transcription( self, participants=None, instance_id=None ) -> Optional[CallClientError]: @@ -1985,7 +2134,7 @@ class DailyOutputTransport(BaseOutputTransport): Args: destination: The destination identifier to register. """ - logger.warning(f"{self} registering video destinations is not supported yet") + await self._client.register_video_destination(destination) async def register_audio_destination(self, destination: str): """Register an audio output destination. From 14dd028b8f0a751135bfcd490ad5af83398766e7 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Aleix=20Conchillo=20Flaqu=C3=A9?= Date: Mon, 9 Mar 2026 23:55:28 -0700 Subject: [PATCH 0912/1060] Add custom video track example with per-track params --- .../foundational/56-custom-video-track.py | 210 ++++++++++++++++++ 1 file changed, 210 insertions(+) create mode 100644 examples/foundational/56-custom-video-track.py diff --git a/examples/foundational/56-custom-video-track.py b/examples/foundational/56-custom-video-track.py new file mode 100644 index 000000000..274ab6a5e --- /dev/null +++ b/examples/foundational/56-custom-video-track.py @@ -0,0 +1,210 @@ +# +# Copyright (c) 2024-2026, Daily +# +# SPDX-License-Identifier: BSD 2-Clause License +# + +"""Example demonstrating custom video tracks output with Daily transport. + +This example outputs two video track simultaneously: + - The default camera track with an animated color gradient pattern. + - A custom "blue" track with the same pattern but with a blue tint applied. + +The pattern generator pushes frames to the default camera. A second processor +(BlueTintProcessor) duplicates each frame, applies a blue tint, and pushes it +to the "blue" custom video destination. + +Run with: python examples/foundational/56-custom-video-track.py -t daily +""" + +import asyncio +import math +import time + +import numpy as np +from loguru import logger + +from pipecat.frames.frames import ( + CancelFrame, + EndFrame, + Frame, + OutputImageRawFrame, + StartFrame, + SystemFrame, +) +from pipecat.pipeline.pipeline import Pipeline +from pipecat.pipeline.runner import PipelineRunner +from pipecat.pipeline.task import PipelineTask +from pipecat.processors.frame_processor import FrameDirection, FrameProcessor +from pipecat.runner.types import RunnerArguments +from pipecat.runner.utils import create_transport +from pipecat.transports.base_transport import BaseTransport +from pipecat.transports.daily.transport import DailyCustomVideoTrackParams, DailyParams + +WIDTH = 320 +HEIGHT = 240 +FPS = 30 + +transport_params = { + "daily": lambda: DailyParams( + video_out_enabled=True, + video_out_width=WIDTH, + video_out_height=HEIGHT, + video_out_framerate=FPS, + video_out_destinations=["blue"], + custom_video_track_params={ + "blue": DailyCustomVideoTrackParams( + width=WIDTH, + height=HEIGHT, + send_settings={ + "maxQuality": "low", + "encodings": { + "low": { + "maxBitrate": 500_000, + "maxFramerate": FPS, + } + }, + }, + ), + }, + ), +} + + +def generate_gradient_frame(width: int, height: int, t: float) -> np.ndarray: + """Generate an animated gradient pattern. + + Creates a smooth color gradient that shifts over time using sine waves + for each RGB channel at different frequencies. + """ + x = np.linspace(0, 1, width) + y = np.linspace(0, 1, height) + xv, yv = np.meshgrid(x, y) + + r = ((np.sin(2 * math.pi * (xv + t * 0.3)) + 1) / 2 * 255).astype(np.uint8) + g = ((np.sin(2 * math.pi * (yv + t * 0.5)) + 1) / 2 * 255).astype(np.uint8) + b = ((np.sin(2 * math.pi * (xv + yv + t * 0.7)) + 1) / 2 * 255).astype(np.uint8) + + return np.stack([r, g, b], axis=-1) + + +class VideoPatternGenerator(FrameProcessor): + """Generates an animated gradient pattern and pushes it as video frames.""" + + def __init__(self, width: int, height: int, fps: int): + super().__init__() + self._width = width + self._height = height + self._fps = fps + self._generate_task = None + + async def process_frame(self, frame: Frame, direction: FrameDirection): + await super().process_frame(frame, direction) + + if isinstance(frame, StartFrame): + await self.push_frame(frame, direction) + await self._start() + elif isinstance(frame, (EndFrame, CancelFrame)): + await self._stop() + await self.push_frame(frame, direction) + else: + await self.push_frame(frame, direction) + + async def _start(self): + self._generate_task = self.create_task(self._generate_loop(), "video_generate_loop") + + async def _stop(self): + if self._generate_task: + await self.cancel_task(self._generate_task) + self._generate_task = None + + async def _generate_loop(self): + interval = 1.0 / self._fps + start = time.monotonic() + + while True: + t = time.monotonic() - start + + pattern = generate_gradient_frame(self._width, self._height, t) + + frame = OutputImageRawFrame( + image=pattern.tobytes(), + size=(self._width, self._height), + format="RGB", + ) + await self.push_frame(frame) + + elapsed = time.monotonic() - start - t + await asyncio.sleep(max(0, interval - elapsed)) + + +class BlueTintProcessor(FrameProcessor): + """Duplicates OutputImageRawFrames with a blue tint for a custom video destination.""" + + def __init__(self, destination: str): + super().__init__() + self._destination = destination + + async def process_frame(self, frame: Frame, direction: FrameDirection): + await super().process_frame(frame, direction) + + if isinstance(frame, OutputImageRawFrame): + # Pass through the original frame. + await self.push_frame(frame, direction) + + # Create a blue-tinted copy for the custom destination. + img = np.frombuffer(frame.image, dtype=np.uint8).reshape( + (frame.size[1], frame.size[0], 3) + ) + tinted = img.copy() + tinted[:, :, 0] = (tinted[:, :, 0] * 0.3).astype(np.uint8) # R + tinted[:, :, 1] = (tinted[:, :, 1] * 0.3).astype(np.uint8) # G + tinted[:, :, 2] = np.clip(tinted[:, :, 2].astype(np.uint16) + 80, 0, 255).astype( + np.uint8 + ) # B + + blue_frame = OutputImageRawFrame( + image=tinted.tobytes(), + size=frame.size, + format=frame.format, + ) + blue_frame.transport_destination = self._destination + await self.push_frame(blue_frame) + else: + await self.push_frame(frame, direction) + + +async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): + logger.info("Starting dual video track bot") + + generator = VideoPatternGenerator(WIDTH, HEIGHT, FPS) + blue_tint = BlueTintProcessor(destination="blue") + + task = PipelineTask( + Pipeline([generator, blue_tint, transport.output()]), + idle_timeout_secs=runner_args.pipeline_idle_timeout_secs, + ) + + @transport.event_handler("on_client_connected") + async def on_client_connected(transport, client): + logger.info("Client connected") + + @transport.event_handler("on_client_disconnected") + async def on_client_disconnected(transport, client): + logger.info("Client disconnected") + await task.queue_frame(EndFrame()) + + runner = PipelineRunner(handle_sigint=runner_args.handle_sigint) + await runner.run(task) + + +async def bot(runner_args: RunnerArguments): + """Main bot entry point compatible with Pipecat Cloud.""" + transport = await create_transport(runner_args, transport_params) + await run_bot(transport, runner_args) + + +if __name__ == "__main__": + from pipecat.runner.run import main + + main() From 86597cc9ec296fd3f4a23c5bb20d6936af22e6dd Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Aleix=20Conchillo=20Flaqu=C3=A9?= Date: Mon, 9 Mar 2026 23:55:31 -0700 Subject: [PATCH 0913/1060] Add changelog entries for PR #3831 --- changelog/3831.added.md | 1 + changelog/3831.changed.md | 1 + 2 files changed, 2 insertions(+) create mode 100644 changelog/3831.added.md create mode 100644 changelog/3831.changed.md diff --git a/changelog/3831.added.md b/changelog/3831.added.md new file mode 100644 index 000000000..7c3f7f4df --- /dev/null +++ b/changelog/3831.added.md @@ -0,0 +1 @@ +- Added custom video track support to Daily transport. Use `video_out_destinations` in `DailyParams` to publish multiple video tracks simultaneously, mirroring the existing `audio_out_destinations` feature. diff --git a/changelog/3831.changed.md b/changelog/3831.changed.md new file mode 100644 index 000000000..bb4d7df83 --- /dev/null +++ b/changelog/3831.changed.md @@ -0,0 +1 @@ +- Daily transport now uses `CustomVideoSource`/`CustomVideoTrack` instead of `VirtualCameraDevice` for the default camera output, mirroring how audio already works with `CustomAudioSource`/`CustomAudioTrack`. From 4a2d57511d0cb1c1f70ca110cb0eca6cde9d663b Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Aleix=20Conchillo=20Flaqu=C3=A9?= Date: Tue, 10 Mar 2026 11:55:38 -0700 Subject: [PATCH 0914/1060] Make DailyParams.transcription_settings optional Change transcription_settings to Optional[DailyTranscriptionSettings] defaulting to None. The default settings are now applied at the call site when transcription is started, and start_transcription receives the serialized settings dict directly. --- src/pipecat/transports/daily/transport.py | 12 +++++------- 1 file changed, 5 insertions(+), 7 deletions(-) diff --git a/src/pipecat/transports/daily/transport.py b/src/pipecat/transports/daily/transport.py index 1ded5ded7..06fbc9540 100644 --- a/src/pipecat/transports/daily/transport.py +++ b/src/pipecat/transports/daily/transport.py @@ -356,7 +356,7 @@ class DailyParams(TransportParams): dialin_settings: Optional settings for dial-in functionality. microphone_out_enabled: Whether to enable the main microphone track. transcription_enabled: Whether to enable speech transcription. - transcription_settings: Configuration for transcription service. + transcription_settings: Optional configuration for transcription service. """ api_url: str = "https://api.daily.co/v1" @@ -368,7 +368,7 @@ class DailyParams(TransportParams): dialin_settings: Optional[DailyDialinSettings] = None microphone_out_enabled: bool = True transcription_enabled: bool = False - transcription_settings: DailyTranscriptionSettings = DailyTranscriptionSettings() + transcription_settings: Optional[DailyTranscriptionSettings] = None class DailyCallbacks(BaseModel): @@ -1134,10 +1134,7 @@ class DailyTransportClient(EventHandler): return "Transcription can't be started without a room token" future = self._get_event_loop().create_future() - self._client.start_transcription( - settings=self._params.transcription_settings.model_dump(exclude_none=True), - completion=completion_callback(future), - ) + self._client.start_transcription(settings=settings, completion=completion_callback(future)) return await future async def stop_transcription(self) -> Optional[CallClientError]: @@ -2727,7 +2724,8 @@ class DailyTransport(BaseTransport): if self._params.transcription_enabled: # We report an error because we are starting transcription # internally and if it fails we need to know. - error = await self.start_transcription(self._params.transcription_settings) + settings = self._params.transcription_settings or DailyTranscriptionSettings() + error = await self.start_transcription(settings.model_dump(exclude_none=True)) if error: await self._on_error(f"Unable to start transcription: {error}") await self._call_event_handler("on_joined", data) From 11a0c1105028d4561794fdfa4205708d5222c8b2 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Aleix=20Conchillo=20Flaqu=C3=A9?= Date: Tue, 10 Mar 2026 11:56:11 -0700 Subject: [PATCH 0915/1060] Fix start_transcription ignoring its settings argument DailyTransportClient.start_transcription() accepted a settings parameter but always used self._params.transcription_settings instead, silently discarding any custom settings passed by callers. --- src/pipecat/transports/daily/transport.py | 8 ++++---- 1 file changed, 4 insertions(+), 4 deletions(-) diff --git a/src/pipecat/transports/daily/transport.py b/src/pipecat/transports/daily/transport.py index 06fbc9540..4626f9f53 100644 --- a/src/pipecat/transports/daily/transport.py +++ b/src/pipecat/transports/daily/transport.py @@ -356,7 +356,7 @@ class DailyParams(TransportParams): dialin_settings: Optional settings for dial-in functionality. microphone_out_enabled: Whether to enable the main microphone track. transcription_enabled: Whether to enable speech transcription. - transcription_settings: Optional configuration for transcription service. + transcription_settings: Configuration for transcription service. """ api_url: str = "https://api.daily.co/v1" @@ -368,7 +368,7 @@ class DailyParams(TransportParams): dialin_settings: Optional[DailyDialinSettings] = None microphone_out_enabled: bool = True transcription_enabled: bool = False - transcription_settings: Optional[DailyTranscriptionSettings] = None + transcription_settings: DailyTranscriptionSettings = DailyTranscriptionSettings() class DailyCallbacks(BaseModel): @@ -2724,8 +2724,8 @@ class DailyTransport(BaseTransport): if self._params.transcription_enabled: # We report an error because we are starting transcription # internally and if it fails we need to know. - settings = self._params.transcription_settings or DailyTranscriptionSettings() - error = await self.start_transcription(settings.model_dump(exclude_none=True)) + settings = self._params.transcription_settings.model_dump(exclude_none=True) + error = await self.start_transcription(settings) if error: await self._on_error(f"Unable to start transcription: {error}") await self._call_event_handler("on_joined", data) From 80bd935c196ca625e5fbb5ca82d9b7119196522e Mon Sep 17 00:00:00 2001 From: kollaikal-rupesh Date: Tue, 10 Mar 2026 12:37:30 -0700 Subject: [PATCH 0916/1060] Add ServiceSwitcherStrategyFailover for automatic failover on service errors (#3870) MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit * Add ServiceSwitcherStrategyFailover for automatic error-based service switching Introduce a strategy hierarchy: ServiceSwitcherStrategy (base) → ServiceSwitcherStrategyManual (handles ManuallySwitchServiceFrame) → ServiceSwitcherStrategyFailover (adds error-based failover). ServiceSwitcher now defaults to ServiceSwitcherStrategyManual with strategy_type optional. Non-fatal ErrorFrames are forwarded to the strategy via handle_error(). * Move metadata request into _set_active_if_available Requesting metadata is part of making a service active, so it belongs alongside setting _active_service and firing on_service_switched. This removes the duplicate queue_frame calls from ServiceSwitcher push_frame and process_frame. --- changelog/3861.added.md | 1 + changelog/3861.changed.md | 1 + examples/foundational/48-service-switcher.py | 17 +- src/pipecat/pipeline/llm_switcher.py | 18 +- src/pipecat/pipeline/service_switcher.py | 121 +++++++++--- tests/test_service_switcher.py | 192 ++++++++++++++----- 6 files changed, 264 insertions(+), 86 deletions(-) create mode 100644 changelog/3861.added.md create mode 100644 changelog/3861.changed.md diff --git a/changelog/3861.added.md b/changelog/3861.added.md new file mode 100644 index 000000000..c0a6f6aee --- /dev/null +++ b/changelog/3861.added.md @@ -0,0 +1 @@ +- Added `ServiceSwitcherStrategyFailover` that automatically switches to the next service when the active service reports a non-fatal error. Recovery policies can be implemented via the `on_service_switched` event handler. diff --git a/changelog/3861.changed.md b/changelog/3861.changed.md new file mode 100644 index 000000000..41c577dcd --- /dev/null +++ b/changelog/3861.changed.md @@ -0,0 +1 @@ +- `ServiceSwitcherStrategy` base class now provides a `handle_error()` hook for subclasses to implement error-based switching. `ServiceSwitcher` defaults to `ServiceSwitcherStrategyManual` and `strategy_type` is now optional. diff --git a/examples/foundational/48-service-switcher.py b/examples/foundational/48-service-switcher.py index e37925006..0947bc6c2 100644 --- a/examples/foundational/48-service-switcher.py +++ b/examples/foundational/48-service-switcher.py @@ -17,7 +17,7 @@ from pipecat.frames.frames import LLMRunFrame, ManuallySwitchServiceFrame from pipecat.pipeline.llm_switcher import LLMSwitcher from pipecat.pipeline.pipeline import Pipeline from pipecat.pipeline.runner import PipelineRunner -from pipecat.pipeline.service_switcher import ServiceSwitcher, ServiceSwitcherStrategyManual +from pipecat.pipeline.service_switcher import ServiceSwitcher from pipecat.pipeline.task import PipelineParams, PipelineTask from pipecat.processors.aggregators.llm_context import LLMContext from pipecat.processors.aggregators.llm_response_universal import ( @@ -96,9 +96,8 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): stt_cartesia = CartesiaSTTService(api_key=os.getenv("CARTESIA_API_KEY")) stt_deepgram = DeepgramSTTService(api_key=os.getenv("DEEPGRAM_API_KEY")) - stt_switcher = ServiceSwitcher( - services=[stt_cartesia, stt_deepgram], strategy_type=ServiceSwitcherStrategyManual - ) + # Uses ServiceSwitcherStrategyManual by default + stt_switcher = ServiceSwitcher(services=[stt_cartesia, stt_deepgram]) tts_cartesia = CartesiaTTSService( api_key=os.getenv("CARTESIA_API_KEY"), @@ -112,9 +111,8 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): voice="aura-2-helena-en", ), ) - tts_switcher = ServiceSwitcher( - services=[tts_cartesia, tts_deepgram], strategy_type=ServiceSwitcherStrategyManual - ) + # Uses ServiceSwitcherStrategyManual by default + tts_switcher = ServiceSwitcher(services=[tts_cartesia, tts_deepgram]) system_prompt = "You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way." @@ -126,9 +124,8 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): api_key=os.getenv("GOOGLE_API_KEY"), settings=GoogleLLMService.Settings(system_instruction=system_prompt), ) - llm_switcher = LLMSwitcher( - llms=[llm_openai, llm_google], strategy_type=ServiceSwitcherStrategyManual - ) + # Uses ServiceSwitcherStrategyManual by default + llm_switcher = LLMSwitcher(llms=[llm_openai, llm_google]) # Register a "classic" function llm_switcher.register_function("get_current_weather", fetch_weather_from_api) # Register a "direct" function diff --git a/src/pipecat/pipeline/llm_switcher.py b/src/pipecat/pipeline/llm_switcher.py index 281bedc65..47147dba2 100644 --- a/src/pipecat/pipeline/llm_switcher.py +++ b/src/pipecat/pipeline/llm_switcher.py @@ -9,7 +9,11 @@ from typing import Any, List, Optional, Type from pipecat.adapters.schemas.direct_function import DirectFunction -from pipecat.pipeline.service_switcher import ServiceSwitcher, StrategyType +from pipecat.pipeline.service_switcher import ( + ServiceSwitcher, + ServiceSwitcherStrategyManual, + StrategyType, +) from pipecat.processors.aggregators.llm_context import LLMContext from pipecat.services.llm_service import LLMService @@ -19,18 +23,20 @@ class LLMSwitcher(ServiceSwitcher[StrategyType]): Example:: - llm_switcher = LLMSwitcher( - llms=[openai_llm, anthropic_llm], - strategy_type=ServiceSwitcherStrategyManual - ) + llm_switcher = LLMSwitcher(llms=[openai_llm, anthropic_llm]) """ - def __init__(self, llms: List[LLMService], strategy_type: Type[StrategyType]): + def __init__( + self, + llms: List[LLMService], + strategy_type: Type[StrategyType] = ServiceSwitcherStrategyManual, + ): """Initialize the service switcher with a list of LLMs and a switching strategy. Args: llms: List of LLM services to switch between. strategy_type: The strategy class to use for switching between LLMs. + Defaults to ``ServiceSwitcherStrategyManual``. """ super().__init__(llms, strategy_type) diff --git a/src/pipecat/pipeline/service_switcher.py b/src/pipecat/pipeline/service_switcher.py index d18f00e7c..76b703681 100644 --- a/src/pipecat/pipeline/service_switcher.py +++ b/src/pipecat/pipeline/service_switcher.py @@ -6,10 +6,12 @@ """Service switcher for switching between different services at runtime, with different switching strategies.""" -from abc import abstractmethod from typing import Any, Generic, List, Optional, Type, TypeVar +from loguru import logger + from pipecat.frames.frames import ( + ErrorFrame, Frame, ManuallySwitchServiceFrame, ServiceMetadataFrame, @@ -69,13 +71,13 @@ class ServiceSwitcherStrategy(BaseObject): """Return the currently active service.""" return self._active_service - @abstractmethod async def handle_frame( self, frame: ServiceSwitcherFrame, direction: FrameDirection ) -> Optional[FrameProcessor]: """Handle a frame that controls service switching. - Subclasses implement this to decide whether a switch should occur. + The base implementation returns ``None`` for all frames. Subclasses + override this to implement specific switching behaviors. Args: frame: The frame to handle. @@ -84,7 +86,41 @@ class ServiceSwitcherStrategy(BaseObject): Returns: The newly active service if a switch occurred, or None otherwise. """ - pass + return None + + async def handle_error(self, error: ErrorFrame) -> Optional[FrameProcessor]: + """Handle an error from the active service. + + Called by ``ServiceSwitcher`` when a non-fatal ``ErrorFrame`` is pushed + upstream by the currently active service. Subclasses can override this + to implement automatic failover. + + Args: + error: The error frame pushed by the active service. + + Returns: + The newly active service if a switch occurred, or None otherwise. + """ + return None + + async def _set_active_if_available(self, service: FrameProcessor) -> Optional[FrameProcessor]: + """Set the active service to the given one, if it is in the list of available services. + + If it's not in the list, the request is ignored, as it may have been + intended for another ServiceSwitcher in the pipeline. + + Args: + service: The service to set as active. + + Returns: + The newly active service, or None if the service was not found. + """ + if service in self.services: + self._active_service = service + await service.queue_frame(ServiceSwitcherRequestMetadataFrame(service=service)) + await self._call_event_handler("on_service_switched", service) + return service + return None class ServiceSwitcherStrategyManual(ServiceSwitcherStrategy): @@ -118,23 +154,54 @@ class ServiceSwitcherStrategyManual(ServiceSwitcherStrategy): return None - async def _set_active_if_available(self, service: FrameProcessor) -> Optional[FrameProcessor]: - """Set the active service to the given one, if it is in the list of available services. - If it's not in the list, the request is ignored, as it may have been - intended for another ServiceSwitcher in the pipeline. +class ServiceSwitcherStrategyFailover(ServiceSwitcherStrategyManual): + """A strategy that automatically switches to a backup service on failure. + + When the active service produces a non-fatal error, this strategy switches + to the next available service in the list. Recovery and fallback policies + are left to application code via the ``on_service_switched`` event. + + Event handlers available: + + - on_service_switched: Called when the active service changes. + + Example:: + + switcher = ServiceSwitcher( + services=[primary_stt, backup_stt], + strategy_type=ServiceSwitcherStrategyFailover, + ) + + @switcher.strategy.event_handler("on_service_switched") + async def on_switched(strategy, service): + # App decides when/how to recover the failed service + ... + """ + + async def handle_error(self, error: ErrorFrame) -> Optional[FrameProcessor]: + """Handle an error from the active service by failing over. + + Switches to the next service in the list. The failed service remains + in the list and can be switched back to manually or via application + logic in the ``on_service_switched`` event handler. Args: - service: The service to set as active. + error: The error frame pushed by the active service. Returns: - The newly active service, or None if the service was not found. + The newly active service if a switch occurred, or None if no + other service is available. """ - if service in self.services: - self._active_service = service - await self._call_event_handler("on_service_switched", service) - return service - return None + logger.warning(f"Service {self._active_service.name} reported an error: {error.error}") + + if len(self._services) <= 1: + logger.error("No other service available to switch to") + return None + + current_idx = self._services.index(self._active_service) + next_idx = (current_idx + 1) % len(self._services) + return await self._set_active_if_available(self._services[next_idx]) StrategyType = TypeVar("StrategyType", bound=ServiceSwitcherStrategy) @@ -150,18 +217,20 @@ class ServiceSwitcher(ParallelPipeline, Generic[StrategyType]): Example:: - switcher = ServiceSwitcher( - services=[stt_1, stt_2], - strategy_type=ServiceSwitcherStrategyManual, - ) + switcher = ServiceSwitcher(services=[stt_1, stt_2]) """ - def __init__(self, services: List[FrameProcessor], strategy_type: Type[StrategyType]): + def __init__( + self, + services: List[FrameProcessor], + strategy_type: Type[StrategyType] = ServiceSwitcherStrategyManual, + ): """Initialize the service switcher with a list of services and a switching strategy. Args: services: List of frame processors to switch between. strategy_type: The strategy class to use for switching between services. + Defaults to ``ServiceSwitcherStrategyManual``. """ _strategy = strategy_type(services) super().__init__(*self._make_pipeline_definitions(services, _strategy)) @@ -227,6 +296,10 @@ class ServiceSwitcher(ParallelPipeline, Generic[StrategyType]): all the filters let it pass, and `StartFrame` causes the service to generate `ServiceMetadataFrame`. + Non-fatal ``ErrorFrame`` instances are forwarded to the strategy via + ``handle_error`` so strategies like ``ServiceSwitcherStrategyFailover`` + can perform failover. The error frame is still propagated upstream so + that application-level error handlers can observe it. """ # Consume ServiceSwitcherRequestMetadataFrame once the targeted service # has handled it (i.e. the active service). @@ -239,6 +312,10 @@ class ServiceSwitcher(ParallelPipeline, Generic[StrategyType]): if frame.service_name != self.strategy.active_service.name: return + # Let the strategy react to non-fatal errors from the active service. + if isinstance(frame, ErrorFrame) and not frame.fatal: + await self.strategy.handle_error(frame) + await super().push_frame(frame, direction) async def process_frame(self, frame: Frame, direction: FrameDirection): @@ -255,9 +332,5 @@ class ServiceSwitcher(ParallelPipeline, Generic[StrategyType]): # frame. If we switched, we just swallow the frame. if not service: await super().process_frame(frame, direction) - - # If we switched to a new service, request its metadata. - if service: - await service.queue_frame(ServiceSwitcherRequestMetadataFrame(service=service)) else: await super().process_frame(frame, direction) diff --git a/tests/test_service_switcher.py b/tests/test_service_switcher.py index 4df6696af..4cdf38f1a 100644 --- a/tests/test_service_switcher.py +++ b/tests/test_service_switcher.py @@ -11,6 +11,7 @@ import unittest from dataclasses import dataclass from pipecat.frames.frames import ( + ErrorFrame, Frame, ManuallySwitchServiceFrame, ServiceMetadataFrame, @@ -20,7 +21,12 @@ from pipecat.frames.frames import ( TextFrame, ) from pipecat.pipeline.pipeline import Pipeline -from pipecat.pipeline.service_switcher import ServiceSwitcher, ServiceSwitcherStrategyManual +from pipecat.pipeline.service_switcher import ( + ServiceSwitcher, + ServiceSwitcherStrategy, + ServiceSwitcherStrategyFailover, + ServiceSwitcherStrategyManual, +) from pipecat.processors.frame_processor import FrameDirection, FrameProcessor from pipecat.tests.utils import run_test @@ -106,8 +112,8 @@ class DummySystemFrame(SystemFrame): text: str = "" -class TestServiceSwitcherStrategyManual(unittest.IsolatedAsyncioTestCase): - """Test cases for ServiceSwitcherStrategyManual.""" +class TestServiceSwitcherStrategy(unittest.IsolatedAsyncioTestCase): + """Test cases for the base ServiceSwitcherStrategy.""" def setUp(self): """Set up test fixtures.""" @@ -118,10 +124,54 @@ class TestServiceSwitcherStrategyManual(unittest.IsolatedAsyncioTestCase): def test_init_with_services(self): """Test initialization with a list of services.""" - strategy = ServiceSwitcherStrategyManual(self.services) + strategy = ServiceSwitcherStrategy(self.services) self.assertEqual(strategy.services, self.services) - self.assertEqual(strategy.active_service, self.service1) # First service should be active + self.assertEqual(strategy.active_service, self.service1) + + async def test_handle_frame_returns_none_for_manual_switch(self): + """Test that base strategy does not handle ManuallySwitchServiceFrame.""" + strategy = ServiceSwitcherStrategy(self.services) + + switch_frame = ManuallySwitchServiceFrame(service=self.service2) + result = await strategy.handle_frame(switch_frame, FrameDirection.DOWNSTREAM) + + self.assertIsNone(result) + self.assertEqual(strategy.active_service, self.service1) + + async def test_handle_frame_returns_none_for_unsupported_frame(self): + """Test that unsupported frame types return None.""" + strategy = ServiceSwitcherStrategy(self.services) + unsupported_frame = TextFrame(text="test") + + result = await strategy.handle_frame(unsupported_frame, FrameDirection.DOWNSTREAM) + + self.assertIsNone(result) + + async def test_handle_error_returns_none(self): + """Test that handle_error returns None by default.""" + strategy = ServiceSwitcherStrategy(self.services) + + result = await strategy.handle_error(ErrorFrame(error="error")) + + self.assertIsNone(result) + self.assertEqual(strategy.active_service, self.service1) + + +class TestServiceSwitcherStrategyManual(unittest.IsolatedAsyncioTestCase): + """Test cases for ServiceSwitcherStrategyManual.""" + + def setUp(self): + """Set up test fixtures.""" + self.service1 = MockFrameProcessor("service1") + self.service2 = MockFrameProcessor("service2") + self.service3 = MockFrameProcessor("service3") + self.services = [self.service1, self.service2, self.service3] + + def test_is_subclass_of_base_strategy(self): + """Test that ServiceSwitcherStrategyManual is a subclass of ServiceSwitcherStrategy.""" + strategy = ServiceSwitcherStrategyManual(self.services) + self.assertIsInstance(strategy, ServiceSwitcherStrategy) async def test_handle_manually_switch_service_frame(self): """Test manual service switching with ManuallySwitchServiceFrame.""" @@ -129,22 +179,15 @@ class TestServiceSwitcherStrategyManual(unittest.IsolatedAsyncioTestCase): # Initially service1 should be active self.assertEqual(strategy.active_service, self.service1) - self.assertNotEqual(strategy.active_service, self.service2) # Switch to service2 switch_frame = ManuallySwitchServiceFrame(service=self.service2) await strategy.handle_frame(switch_frame, FrameDirection.DOWNSTREAM) - - self.assertNotEqual(strategy.active_service, self.service1) self.assertEqual(strategy.active_service, self.service2) - self.assertNotEqual(strategy.active_service, self.service3) # Switch to service3 switch_frame = ManuallySwitchServiceFrame(service=self.service3) await strategy.handle_frame(switch_frame, FrameDirection.DOWNSTREAM) - - self.assertNotEqual(strategy.active_service, self.service1) - self.assertNotEqual(strategy.active_service, self.service2) self.assertEqual(strategy.active_service, self.service3) async def test_on_service_switched_event(self): @@ -157,25 +200,16 @@ class TestServiceSwitcherStrategyManual(unittest.IsolatedAsyncioTestCase): async def on_service_switched(strategy, service): switched_events.append((strategy, service)) - # Switch to service2 switch_frame = ManuallySwitchServiceFrame(service=self.service2) await strategy.handle_frame(switch_frame, FrameDirection.DOWNSTREAM) - await asyncio.sleep(0) # Let async event task run + await asyncio.sleep(0) self.assertEqual(len(switched_events), 1) self.assertIsInstance(switched_events[0][0], ServiceSwitcherStrategyManual) self.assertEqual(switched_events[0][1], self.service2) - # Switch to service3 - switch_frame = ManuallySwitchServiceFrame(service=self.service3) - await strategy.handle_frame(switch_frame, FrameDirection.DOWNSTREAM) - await asyncio.sleep(0) - - self.assertEqual(len(switched_events), 2) - self.assertEqual(switched_events[1][1], self.service3) - - async def test_on_service_switched_event_not_fired_for_unknown_service(self): - """Test that on_service_switched event does not fire for services not in the list.""" + async def test_unknown_service_ignored(self): + """Test that switching to an unknown service is ignored.""" strategy = ServiceSwitcherStrategyManual(self.services) switched_events = [] @@ -184,23 +218,14 @@ class TestServiceSwitcherStrategyManual(unittest.IsolatedAsyncioTestCase): async def on_service_switched(strategy, service): switched_events.append(service) - # Try switching to a service not in the list unknown_service = MockFrameProcessor("unknown") switch_frame = ManuallySwitchServiceFrame(service=unknown_service) - await strategy.handle_frame(switch_frame, FrameDirection.DOWNSTREAM) + result = await strategy.handle_frame(switch_frame, FrameDirection.DOWNSTREAM) await asyncio.sleep(0) - self.assertEqual(len(switched_events), 0) - self.assertEqual(strategy.active_service, self.service1) # Unchanged - - async def test_handle_frame_unsupported_frame_type(self): - """Test that unsupported frame types raise an error.""" - strategy = ServiceSwitcherStrategyManual(self.services) - unsupported_frame = TextFrame(text="test") # Not a ServiceSwitcherFrame - - result = await strategy.handle_frame(unsupported_frame, FrameDirection.DOWNSTREAM) - self.assertIsNone(result) + self.assertEqual(len(switched_events), 0) + self.assertEqual(strategy.active_service, self.service1) class TestServiceSwitcher(unittest.IsolatedAsyncioTestCase): @@ -213,9 +238,9 @@ class TestServiceSwitcher(unittest.IsolatedAsyncioTestCase): self.service3 = MockFrameProcessor("service3") self.services = [self.service1, self.service2, self.service3] - def test_init_with_manual_strategy(self): - """Test initialization with manual strategy.""" - switcher = ServiceSwitcher(self.services, ServiceSwitcherStrategyManual) + def test_init_with_default_strategy(self): + """Test initialization with default strategy.""" + switcher = ServiceSwitcher(self.services) self.assertEqual(switcher.services, self.services) self.assertIsInstance(switcher.strategy, ServiceSwitcherStrategyManual) @@ -223,7 +248,7 @@ class TestServiceSwitcher(unittest.IsolatedAsyncioTestCase): async def test_default_active_service(self): """Test that the initially-active service receives frames while others don't.""" - switcher = ServiceSwitcher(self.services, ServiceSwitcherStrategyManual) + switcher = ServiceSwitcher(self.services) # Reset counters for service in self.services: @@ -292,7 +317,7 @@ class TestServiceSwitcher(unittest.IsolatedAsyncioTestCase): async def test_service_switching(self): """Test that after service switching using ManuallySwitchServiceFrame, the new active service receives frames while others don't.""" - switcher = ServiceSwitcher(self.services, ServiceSwitcherStrategyManual) + switcher = ServiceSwitcher(self.services) # Reset counters for service in self.services: @@ -341,8 +366,8 @@ class TestServiceSwitcher(unittest.IsolatedAsyncioTestCase): switcher2_services = [switcher2_service1, switcher2_service2] # Create two service switchers - switcher1 = ServiceSwitcher(switcher1_services, ServiceSwitcherStrategyManual) - switcher2 = ServiceSwitcher(switcher2_services, ServiceSwitcherStrategyManual) + switcher1 = ServiceSwitcher(switcher1_services) + switcher2 = ServiceSwitcher(switcher2_services) # Create a pipeline with both switchers: switcher1 -> switcher2 pipeline = Pipeline([switcher1, switcher2]) @@ -428,7 +453,7 @@ class TestServiceSwitcherMetadata(unittest.IsolatedAsyncioTestCase): async def test_only_active_service_metadata_at_startup(self): """Test that only the active service's metadata leaves the ServiceSwitcher at startup.""" - switcher = ServiceSwitcher(self.services, ServiceSwitcherStrategyManual) + switcher = ServiceSwitcher(self.services) # Run the pipeline (StartFrame triggers metadata emission) output_frames = [] @@ -450,7 +475,7 @@ class TestServiceSwitcherMetadata(unittest.IsolatedAsyncioTestCase): async def test_metadata_emitted_on_service_switch(self): """Test that switching services triggers metadata emission from the new active service.""" - switcher = ServiceSwitcher(self.services, ServiceSwitcherStrategyManual) + switcher = ServiceSwitcher(self.services) # Reset counters after startup self.service1.reset_counters() @@ -482,7 +507,7 @@ class TestServiceSwitcherMetadata(unittest.IsolatedAsyncioTestCase): async def test_inactive_service_metadata_blocked(self): """Test that metadata from inactive services is blocked.""" - switcher = ServiceSwitcher(self.services, ServiceSwitcherStrategyManual) + switcher = ServiceSwitcher(self.services) # Run and collect output frames await run_test( @@ -497,5 +522,80 @@ class TestServiceSwitcherMetadata(unittest.IsolatedAsyncioTestCase): # Only one MockMetadataFrame should have left (from service1) +class TestServiceSwitcherStrategyFailover(unittest.IsolatedAsyncioTestCase): + """Test cases for ServiceSwitcherStrategyFailover.""" + + def setUp(self): + """Set up test fixtures.""" + self.service1 = MockFrameProcessor("service1") + self.service2 = MockFrameProcessor("service2") + self.service3 = MockFrameProcessor("service3") + self.services = [self.service1, self.service2, self.service3] + + def test_init_defaults(self): + """Test that default values are set correctly.""" + strategy = ServiceSwitcherStrategyFailover(self.services) + self.assertEqual(strategy.active_service, self.service1) + + async def test_error_switches_to_next_service(self): + """Test that an error on the active service switches to the next one.""" + strategy = ServiceSwitcherStrategyFailover(self.services) + + error = ErrorFrame(error="connection lost") + result = await strategy.handle_error(error) + + self.assertEqual(result, self.service2) + self.assertEqual(strategy.active_service, self.service2) + + async def test_consecutive_errors_cycle_through_services(self): + """Test that repeated errors cycle through all services.""" + strategy = ServiceSwitcherStrategyFailover(self.services) + + # First error: service1 -> service2 + await strategy.handle_error(ErrorFrame(error="error 1")) + self.assertEqual(strategy.active_service, self.service2) + + # Second error: service2 -> service3 + await strategy.handle_error(ErrorFrame(error="error 2")) + self.assertEqual(strategy.active_service, self.service3) + + # Third error: service3 -> service1 (wraps around) + await strategy.handle_error(ErrorFrame(error="error 3")) + self.assertEqual(strategy.active_service, self.service1) + + async def test_single_service_returns_none(self): + """Test that handle_error returns None with only one service.""" + strategy = ServiceSwitcherStrategyFailover([self.service1]) + + result = await strategy.handle_error(ErrorFrame(error="error")) + self.assertIsNone(result) + + async def test_manual_switch_still_works(self): + """Test that ManuallySwitchServiceFrame is still handled.""" + strategy = ServiceSwitcherStrategyFailover(self.services) + + frame = ManuallySwitchServiceFrame(service=self.service3) + result = await strategy.handle_frame(frame, FrameDirection.DOWNSTREAM) + + self.assertEqual(result, self.service3) + self.assertEqual(strategy.active_service, self.service3) + + async def test_on_service_switched_event_fires_on_error(self): + """Test that on_service_switched event fires when an error triggers a switch.""" + strategy = ServiceSwitcherStrategyFailover(self.services) + + switched_events = [] + + @strategy.event_handler("on_service_switched") + async def on_service_switched(strategy, service): + switched_events.append(service) + + await strategy.handle_error(ErrorFrame(error="error")) + await asyncio.sleep(0) + + self.assertEqual(len(switched_events), 1) + self.assertEqual(switched_events[0], self.service2) + + if __name__ == "__main__": unittest.main() From 0df421de9cebb64beea59b02c94cd319ef10c41e Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Aleix=20Conchillo=20Flaqu=C3=A9?= Date: Tue, 10 Mar 2026 12:53:13 -0700 Subject: [PATCH 0917/1060] Move google/llm_vertex.py to google/vertex/llm.py --- src/pipecat/services/google/vertex/__init__.py | 5 +++++ src/pipecat/services/google/{llm_vertex.py => vertex/llm.py} | 0 2 files changed, 5 insertions(+) create mode 100644 src/pipecat/services/google/vertex/__init__.py rename src/pipecat/services/google/{llm_vertex.py => vertex/llm.py} (100%) diff --git a/src/pipecat/services/google/vertex/__init__.py b/src/pipecat/services/google/vertex/__init__.py new file mode 100644 index 000000000..c4d243b97 --- /dev/null +++ b/src/pipecat/services/google/vertex/__init__.py @@ -0,0 +1,5 @@ +# +# Copyright (c) 2024-2026, Daily +# +# SPDX-License-Identifier: BSD 2-Clause License +# diff --git a/src/pipecat/services/google/llm_vertex.py b/src/pipecat/services/google/vertex/llm.py similarity index 100% rename from src/pipecat/services/google/llm_vertex.py rename to src/pipecat/services/google/vertex/llm.py From b159d02b0cc3d690bc375961e7677bbea22e81e3 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Aleix=20Conchillo=20Flaqu=C3=A9?= Date: Tue, 10 Mar 2026 12:54:05 -0700 Subject: [PATCH 0918/1060] Add deprecation stub for google/llm_vertex.py --- src/pipecat/services/google/__init__.py | 4 ++-- src/pipecat/services/google/llm_vertex.py | 18 ++++++++++++++++++ 2 files changed, 20 insertions(+), 2 deletions(-) create mode 100644 src/pipecat/services/google/llm_vertex.py diff --git a/src/pipecat/services/google/__init__.py b/src/pipecat/services/google/__init__.py index 032cf0eb8..009f71f08 100644 --- a/src/pipecat/services/google/__init__.py +++ b/src/pipecat/services/google/__init__.py @@ -13,11 +13,11 @@ from .gemini_live import * from .image import * from .llm import * from .llm_openai import * -from .llm_vertex import * from .rtvi import * from .stt import * from .tts import * +from .vertex import * sys.modules[__name__] = DeprecatedModuleProxy( - globals(), "google", "google.[frames,image,llm,llm_openai,llm_vertex,rtvi,stt,tts]" + globals(), "google", "google.[frames,image,llm,openai,vertex,rtvi,stt,tts]" ) diff --git a/src/pipecat/services/google/llm_vertex.py b/src/pipecat/services/google/llm_vertex.py new file mode 100644 index 000000000..54d338ad7 --- /dev/null +++ b/src/pipecat/services/google/llm_vertex.py @@ -0,0 +1,18 @@ +# +# Copyright (c) 2024-2026, Daily +# +# SPDX-License-Identifier: BSD 2-Clause License +# + +"""Deprecated: use ``pipecat.services.google.vertex.llm`` instead.""" + +import warnings + +warnings.warn( + "Module `pipecat.services.google.llm_vertex` is deprecated, " + "use `pipecat.services.google.vertex.llm` instead.", + DeprecationWarning, + stacklevel=2, +) + +from pipecat.services.google.vertex.llm import * # noqa: E402, F401, F403 From 8ea006739c2f1cd52b1614ac16354420a7d55e6a Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Aleix=20Conchillo=20Flaqu=C3=A9?= Date: Tue, 10 Mar 2026 12:54:37 -0700 Subject: [PATCH 0919/1060] Move google/llm_openai.py to google/openai/llm.py --- src/pipecat/services/google/openai/__init__.py | 5 +++++ src/pipecat/services/google/{llm_openai.py => openai/llm.py} | 0 2 files changed, 5 insertions(+) create mode 100644 src/pipecat/services/google/openai/__init__.py rename src/pipecat/services/google/{llm_openai.py => openai/llm.py} (100%) diff --git a/src/pipecat/services/google/openai/__init__.py b/src/pipecat/services/google/openai/__init__.py new file mode 100644 index 000000000..c4d243b97 --- /dev/null +++ b/src/pipecat/services/google/openai/__init__.py @@ -0,0 +1,5 @@ +# +# Copyright (c) 2024-2026, Daily +# +# SPDX-License-Identifier: BSD 2-Clause License +# diff --git a/src/pipecat/services/google/llm_openai.py b/src/pipecat/services/google/openai/llm.py similarity index 100% rename from src/pipecat/services/google/llm_openai.py rename to src/pipecat/services/google/openai/llm.py From 4fa3890cec1706701da12651740d753d5f8a7af2 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Aleix=20Conchillo=20Flaqu=C3=A9?= Date: Tue, 10 Mar 2026 12:55:16 -0700 Subject: [PATCH 0920/1060] Add deprecation stub for google/llm_openai.py --- src/pipecat/services/google/__init__.py | 2 +- src/pipecat/services/google/llm_openai.py | 18 ++++++++++++++++++ 2 files changed, 19 insertions(+), 1 deletion(-) create mode 100644 src/pipecat/services/google/llm_openai.py diff --git a/src/pipecat/services/google/__init__.py b/src/pipecat/services/google/__init__.py index 009f71f08..32b12e367 100644 --- a/src/pipecat/services/google/__init__.py +++ b/src/pipecat/services/google/__init__.py @@ -12,7 +12,7 @@ from .frames import * from .gemini_live import * from .image import * from .llm import * -from .llm_openai import * +from .openai import * from .rtvi import * from .stt import * from .tts import * diff --git a/src/pipecat/services/google/llm_openai.py b/src/pipecat/services/google/llm_openai.py new file mode 100644 index 000000000..f9d182e78 --- /dev/null +++ b/src/pipecat/services/google/llm_openai.py @@ -0,0 +1,18 @@ +# +# Copyright (c) 2024-2026, Daily +# +# SPDX-License-Identifier: BSD 2-Clause License +# + +"""Deprecated: use ``pipecat.services.google.openai.llm`` instead.""" + +import warnings + +warnings.warn( + "Module `pipecat.services.google.llm_openai` is deprecated, " + "use `pipecat.services.google.openai.llm` instead.", + DeprecationWarning, + stacklevel=2, +) + +from pipecat.services.google.openai.llm import * # noqa: E402, F401, F403 From b23652caa68c757adbd0a8ce2e35d62a6813424a Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Aleix=20Conchillo=20Flaqu=C3=A9?= Date: Tue, 10 Mar 2026 12:58:04 -0700 Subject: [PATCH 0921/1060] Update imports to use new google.vertex and google.openai paths --- .../14o-function-calling-gemini-openai-format.py | 2 +- .../foundational/14p-function-calling-gemini-vertex-ai.py | 2 +- .../foundational/55zk-update-settings-google-vertex-llm.py | 2 +- src/pipecat/services/google/google.py | 6 +++--- tests/test_google_llm_openai.py | 2 +- 5 files changed, 7 insertions(+), 7 deletions(-) diff --git a/examples/foundational/14o-function-calling-gemini-openai-format.py b/examples/foundational/14o-function-calling-gemini-openai-format.py index 416e602bf..8ab53d9cf 100644 --- a/examples/foundational/14o-function-calling-gemini-openai-format.py +++ b/examples/foundational/14o-function-calling-gemini-openai-format.py @@ -26,7 +26,7 @@ from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport from pipecat.services.deepgram.stt import DeepgramSTTService from pipecat.services.elevenlabs.tts import ElevenLabsTTSService -from pipecat.services.google.llm_openai import GoogleLLMOpenAIBetaService +from pipecat.services.google.openai.llm import GoogleLLMOpenAIBetaService from pipecat.services.llm_service import FunctionCallParams from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams diff --git a/examples/foundational/14p-function-calling-gemini-vertex-ai.py b/examples/foundational/14p-function-calling-gemini-vertex-ai.py index 1f33efacf..c6259b992 100644 --- a/examples/foundational/14p-function-calling-gemini-vertex-ai.py +++ b/examples/foundational/14p-function-calling-gemini-vertex-ai.py @@ -26,7 +26,7 @@ from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport from pipecat.services.deepgram.stt import DeepgramSTTService from pipecat.services.elevenlabs.tts import ElevenLabsTTSService -from pipecat.services.google.llm_vertex import GoogleVertexLLMService +from pipecat.services.google.vertex.llm import GoogleVertexLLMService from pipecat.services.llm_service import FunctionCallParams from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams diff --git a/examples/foundational/55zk-update-settings-google-vertex-llm.py b/examples/foundational/55zk-update-settings-google-vertex-llm.py index 6b2babb7f..7f7a34cba 100644 --- a/examples/foundational/55zk-update-settings-google-vertex-llm.py +++ b/examples/foundational/55zk-update-settings-google-vertex-llm.py @@ -24,7 +24,7 @@ from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport from pipecat.services.cartesia.tts import CartesiaTTSService from pipecat.services.deepgram.stt import DeepgramSTTService -from pipecat.services.google.llm_vertex import GoogleVertexLLMService +from pipecat.services.google.vertex.llm import GoogleVertexLLMService from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams diff --git a/src/pipecat/services/google/google.py b/src/pipecat/services/google/google.py index 3d1814cf0..b2fc88b23 100644 --- a/src/pipecat/services/google/google.py +++ b/src/pipecat/services/google/google.py @@ -13,12 +13,12 @@ from pipecat.services import DeprecatedModuleProxy from .frames import * from .image import * from .llm import * -from .llm_openai import * -from .llm_vertex import * +from .openai import * from .rtvi import * from .stt import * from .tts import * +from .vertex import * sys.modules[__name__] = DeprecatedModuleProxy( - globals(), "google", "google.[frames,image,llm,llm_openai,llm_vertex,rtvi,stt,tts]" + globals(), "google", "google.[frames,image,llm,openai,vertex,rtvi,stt,tts]" ) diff --git a/tests/test_google_llm_openai.py b/tests/test_google_llm_openai.py index 2940bf7d7..5e6cee6f8 100644 --- a/tests/test_google_llm_openai.py +++ b/tests/test_google_llm_openai.py @@ -15,7 +15,7 @@ import pytest from pipecat.processors.aggregators.openai_llm_context import OpenAILLMContext try: - from pipecat.services.google.llm_openai import GoogleLLMOpenAIBetaService + from pipecat.services.google.openai.llm import GoogleLLMOpenAIBetaService google_available = True except Exception: From d086b9f138e460523e1bddbb2c6b1ccbcc57b61c Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Aleix=20Conchillo=20Flaqu=C3=A9?= Date: Tue, 10 Mar 2026 12:59:36 -0700 Subject: [PATCH 0922/1060] Move google/gemini_live/llm_vertex.py to google/gemini_live/vertex/llm.py --- src/pipecat/services/google/gemini_live/vertex/__init__.py | 5 +++++ .../google/gemini_live/{llm_vertex.py => vertex/llm.py} | 0 2 files changed, 5 insertions(+) create mode 100644 src/pipecat/services/google/gemini_live/vertex/__init__.py rename src/pipecat/services/google/gemini_live/{llm_vertex.py => vertex/llm.py} (100%) diff --git a/src/pipecat/services/google/gemini_live/vertex/__init__.py b/src/pipecat/services/google/gemini_live/vertex/__init__.py new file mode 100644 index 000000000..c4d243b97 --- /dev/null +++ b/src/pipecat/services/google/gemini_live/vertex/__init__.py @@ -0,0 +1,5 @@ +# +# Copyright (c) 2024-2026, Daily +# +# SPDX-License-Identifier: BSD 2-Clause License +# diff --git a/src/pipecat/services/google/gemini_live/llm_vertex.py b/src/pipecat/services/google/gemini_live/vertex/llm.py similarity index 100% rename from src/pipecat/services/google/gemini_live/llm_vertex.py rename to src/pipecat/services/google/gemini_live/vertex/llm.py From ea09586db633a4b8c815d2f3ac9458a937562c48 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Aleix=20Conchillo=20Flaqu=C3=A9?= Date: Tue, 10 Mar 2026 13:00:02 -0700 Subject: [PATCH 0923/1060] Add deprecation stub for google/gemini_live/llm_vertex.py --- .../services/google/gemini_live/__init__.py | 2 +- .../services/google/gemini_live/llm_vertex.py | 18 ++++++++++++++++++ 2 files changed, 19 insertions(+), 1 deletion(-) create mode 100644 src/pipecat/services/google/gemini_live/llm_vertex.py diff --git a/src/pipecat/services/google/gemini_live/__init__.py b/src/pipecat/services/google/gemini_live/__init__.py index f4bfbb5c8..4afeb99ce 100644 --- a/src/pipecat/services/google/gemini_live/__init__.py +++ b/src/pipecat/services/google/gemini_live/__init__.py @@ -1,6 +1,6 @@ from .file_api import GeminiFileAPI from .llm import GeminiLiveLLMService -from .llm_vertex import GeminiLiveVertexLLMService +from .vertex.llm import GeminiLiveVertexLLMService __all__ = [ "GeminiFileAPI", diff --git a/src/pipecat/services/google/gemini_live/llm_vertex.py b/src/pipecat/services/google/gemini_live/llm_vertex.py new file mode 100644 index 000000000..038d72e57 --- /dev/null +++ b/src/pipecat/services/google/gemini_live/llm_vertex.py @@ -0,0 +1,18 @@ +# +# Copyright (c) 2024-2026, Daily +# +# SPDX-License-Identifier: BSD 2-Clause License +# + +"""Deprecated: use ``pipecat.services.google.gemini_live.vertex.llm`` instead.""" + +import warnings + +warnings.warn( + "Module `pipecat.services.google.gemini_live.llm_vertex` is deprecated, " + "use `pipecat.services.google.gemini_live.vertex.llm` instead.", + DeprecationWarning, + stacklevel=2, +) + +from pipecat.services.google.gemini_live.vertex.llm import * # noqa: E402, F401, F403 From 7be2c43e1d56e5400637b4a7526ffc95d367c290 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Aleix=20Conchillo=20Flaqu=C3=A9?= Date: Tue, 10 Mar 2026 13:00:31 -0700 Subject: [PATCH 0924/1060] Update imports to use new google.gemini_live.vertex path --- .../foundational/26h-gemini-live-vertex-function-calling.py | 2 +- .../foundational/55zm-update-settings-gemini-live-vertex.py | 2 +- 2 files changed, 2 insertions(+), 2 deletions(-) diff --git a/examples/foundational/26h-gemini-live-vertex-function-calling.py b/examples/foundational/26h-gemini-live-vertex-function-calling.py index 18e417f22..7dd894fd1 100644 --- a/examples/foundational/26h-gemini-live-vertex-function-calling.py +++ b/examples/foundational/26h-gemini-live-vertex-function-calling.py @@ -26,7 +26,7 @@ from pipecat.processors.aggregators.llm_response_universal import ( ) from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport -from pipecat.services.google.gemini_live.llm_vertex import GeminiLiveVertexLLMService +from pipecat.services.google.gemini_live.vertex.llm import GeminiLiveVertexLLMService from pipecat.services.llm_service import FunctionCallParams from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams diff --git a/examples/foundational/55zm-update-settings-gemini-live-vertex.py b/examples/foundational/55zm-update-settings-gemini-live-vertex.py index f69b94557..8ff18e1eb 100644 --- a/examples/foundational/55zm-update-settings-gemini-live-vertex.py +++ b/examples/foundational/55zm-update-settings-gemini-live-vertex.py @@ -19,7 +19,7 @@ from pipecat.processors.aggregators.llm_context import LLMContext from pipecat.processors.aggregators.llm_response_universal import LLMContextAggregatorPair from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport -from pipecat.services.google.gemini_live.llm_vertex import GeminiLiveVertexLLMService +from pipecat.services.google.gemini_live.vertex.llm import GeminiLiveVertexLLMService from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams From 23218aaed707903f620d0329aacc69f7b582c167 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Aleix=20Conchillo=20Flaqu=C3=A9?= Date: Tue, 10 Mar 2026 13:04:16 -0700 Subject: [PATCH 0925/1060] Add changelog for #3980 --- changelog/3980.deprecated.md | 1 + 1 file changed, 1 insertion(+) create mode 100644 changelog/3980.deprecated.md diff --git a/changelog/3980.deprecated.md b/changelog/3980.deprecated.md new file mode 100644 index 000000000..f69964b62 --- /dev/null +++ b/changelog/3980.deprecated.md @@ -0,0 +1 @@ +- Deprecated `pipecat.services.google.llm_vertex`, `pipecat.services.google.llm_openai`, and `pipecat.services.google.gemini_live.llm_vertex` modules. Use `pipecat.services.google.vertex.llm`, `pipecat.services.google.openai.llm`, and `pipecat.services.google.gemini_live.vertex.llm` instead. The old import paths still work but will emit a `DeprecationWarning`. From 4c19337d890f6462a0565927caa1f432e2e5eb4d Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Aleix=20Conchillo=20Flaqu=C3=A9?= Date: Tue, 10 Mar 2026 15:29:52 -0700 Subject: [PATCH 0926/1060] Fix examples: Groq model, Google settings class, Nvidia system instruction --- examples/foundational/07l-interruptible-groq.py | 2 +- examples/foundational/07n-interruptible-google-http.py | 2 +- examples/foundational/14j-function-calling-nvidia.py | 2 +- 3 files changed, 3 insertions(+), 3 deletions(-) diff --git a/examples/foundational/07l-interruptible-groq.py b/examples/foundational/07l-interruptible-groq.py index 208d39c2d..a4bfee8dc 100644 --- a/examples/foundational/07l-interruptible-groq.py +++ b/examples/foundational/07l-interruptible-groq.py @@ -57,7 +57,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): llm = GroqLLMService( api_key=os.getenv("GROQ_API_KEY"), settings=GroqLLMService.Settings( - model="meta-llama/llama-4-maverick-17b-128e-instruct", + model="llama-3.1-8b-instant", system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", ), ) diff --git a/examples/foundational/07n-interruptible-google-http.py b/examples/foundational/07n-interruptible-google-http.py index 91e822ec0..35c80a972 100644 --- a/examples/foundational/07n-interruptible-google-http.py +++ b/examples/foundational/07n-interruptible-google-http.py @@ -73,7 +73,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): llm = GoogleLLMService( api_key=os.getenv("GOOGLE_API_KEY"), - settings=GoogleLLMService.GoogleLLMSettings( + settings=GoogleLLMService.Settings( model="gemini-2.5-flash", # force a certain amount of thinking if you want it # thinking=GoogleLLMService.ThinkingConfig(thinking_budget=4096) diff --git a/examples/foundational/14j-function-calling-nvidia.py b/examples/foundational/14j-function-calling-nvidia.py index 39b75b7ac..7dd772c03 100644 --- a/examples/foundational/14j-function-calling-nvidia.py +++ b/examples/foundational/14j-function-calling-nvidia.py @@ -75,7 +75,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): model="nvidia/llama-3.3-nemotron-super-49b-v1.5", # Recommended when turning thinking off temperature=0.0, - system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + system_instruction="/no_think You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", ), ) # You can also register a function_name of None to get all functions From 610dc25fb16c3c87f93c817dd9819d11d8af11bc Mon Sep 17 00:00:00 2001 From: aconchillo <951761+aconchillo@users.noreply.github.com> Date: Wed, 11 Mar 2026 00:50:01 +0000 Subject: [PATCH 0927/1060] Update changelog for version 0.0.105 --- CHANGELOG.md | 265 +++++++++++++++++++++++++++++++++++ changelog/3804.added.md | 1 - changelog/3804.changed.md | 1 - changelog/3804.deprecated.md | 2 - changelog/3804.removed.md | 1 - changelog/3831.added.md | 1 - changelog/3831.changed.md | 1 - changelog/3848.changed.md | 1 - changelog/3848.fixed.md | 1 - changelog/3861.added.md | 1 - changelog/3861.changed.md | 1 - changelog/3889.changed.md | 3 - changelog/3889.fixed.md | 1 - changelog/3914.changed.md | 1 - changelog/3915.added.md | 1 - changelog/3916.added.md | 1 - changelog/3918.added.md | 15 -- changelog/3918.other.md | 1 - changelog/3927.added.md | 1 - changelog/3927.changed.md | 1 - changelog/3929.other.md | 1 - changelog/3930.added.md | 1 - changelog/3931.other.md | 1 - changelog/3932.added.md | 1 - changelog/3936.fixed.md | 1 - changelog/3937.fixed.md | 1 - changelog/3946.added.md | 1 - changelog/3947.added.md | 1 - changelog/3953.added.md | 1 - changelog/3956.fixed.md | 1 - changelog/3957.fixed.md | 1 - changelog/3958.changed.md | 1 - changelog/3958.fixed.md | 1 - changelog/3959.fixed.md | 1 - changelog/3960.fixed.md | 1 - changelog/3961.changed.md | 1 - changelog/3962.fixed.md | 1 - changelog/3967.fixed.md | 1 - changelog/3968.added.md | 1 - changelog/3970.changed.md | 1 - changelog/3973.changed.md | 1 - changelog/3974.changed.md | 1 - changelog/3976.fixed.md | 1 - changelog/3980.deprecated.md | 1 - 44 files changed, 265 insertions(+), 60 deletions(-) delete mode 100644 changelog/3804.added.md delete mode 100644 changelog/3804.changed.md delete mode 100644 changelog/3804.deprecated.md delete mode 100644 changelog/3804.removed.md delete mode 100644 changelog/3831.added.md delete mode 100644 changelog/3831.changed.md delete mode 100644 changelog/3848.changed.md delete mode 100644 changelog/3848.fixed.md delete mode 100644 changelog/3861.added.md delete mode 100644 changelog/3861.changed.md delete mode 100644 changelog/3889.changed.md delete mode 100644 changelog/3889.fixed.md delete mode 100644 changelog/3914.changed.md delete mode 100644 changelog/3915.added.md delete mode 100644 changelog/3916.added.md delete mode 100644 changelog/3918.added.md delete mode 100644 changelog/3918.other.md delete mode 100644 changelog/3927.added.md delete mode 100644 changelog/3927.changed.md delete mode 100644 changelog/3929.other.md delete mode 100644 changelog/3930.added.md delete mode 100644 changelog/3931.other.md delete mode 100644 changelog/3932.added.md delete mode 100644 changelog/3936.fixed.md delete mode 100644 changelog/3937.fixed.md delete mode 100644 changelog/3946.added.md delete mode 100644 changelog/3947.added.md delete mode 100644 changelog/3953.added.md delete mode 100644 changelog/3956.fixed.md delete mode 100644 changelog/3957.fixed.md delete mode 100644 changelog/3958.changed.md delete mode 100644 changelog/3958.fixed.md delete mode 100644 changelog/3959.fixed.md delete mode 100644 changelog/3960.fixed.md delete mode 100644 changelog/3961.changed.md delete mode 100644 changelog/3962.fixed.md delete mode 100644 changelog/3967.fixed.md delete mode 100644 changelog/3968.added.md delete mode 100644 changelog/3970.changed.md delete mode 100644 changelog/3973.changed.md delete mode 100644 changelog/3974.changed.md delete mode 100644 changelog/3976.fixed.md delete mode 100644 changelog/3980.deprecated.md diff --git a/CHANGELOG.md b/CHANGELOG.md index 39dd6c194..71938516a 100644 --- a/CHANGELOG.md +++ b/CHANGELOG.md @@ -7,6 +7,271 @@ and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0 +## [0.0.105] - 2026-03-10 + +### Added + +- Added concurrent audio context support: `CartesiaTTSService` can now + synthesize the next sentence while the previous one is still playing, by + setting `pause_frame_processing=False` and routing each sentence through its + own audio context queue. + (PR [#3804](https://github.com/pipecat-ai/pipecat/pull/3804)) + +- Added custom video track support to Daily transport. Use + `video_out_destinations` in `DailyParams` to publish multiple video tracks + simultaneously, mirroring the existing `audio_out_destinations` feature. + (PR [#3831](https://github.com/pipecat-ai/pipecat/pull/3831)) + +- Added `ServiceSwitcherStrategyFailover` that automatically switches to the + next service when the active service reports a non-fatal error. Recovery + policies can be implemented via the `on_service_switched` event handler. + (PR [#3861](https://github.com/pipecat-ai/pipecat/pull/3861)) + +- Added optional `timeout_secs` parameter to `register_function()` and + `register_direct_function()` for per-tool function call timeout control, + overriding the global `function_call_timeout_secs` default. + (PR [#3915](https://github.com/pipecat-ai/pipecat/pull/3915)) + +- Added `cloud-audio-only` recording option to Daily transport's + `enable_recording` property. + (PR [#3916](https://github.com/pipecat-ai/pipecat/pull/3916)) + +- Wired up `system_instruction` in `BaseOpenAILLMService`, + `AnthropicLLMService`, and `AWSBedrockLLMService` so it works as a default + system prompt, matching the behavior of the Google services. This enables + sharing a single `LLMContext` across multiple LLM services, where each + service provides its own system instruction independently. + + ```python + llm = OpenAILLMService( + api_key=os.getenv("OPENAI_API_KEY"), + system_instruction="You are a helpful assistant.", + ) + + context = LLMContext() + + @transport.event_handler("on_client_connected") + async def on_client_connected(transport, client): + context.add_message({"role": "user", "content": "Please introduce yourself."}) + await task.queue_frames([LLMRunFrame()]) + ``` + (PR [#3918](https://github.com/pipecat-ai/pipecat/pull/3918)) + +- Added `vad_threshold` parameter to `AssemblyAIConnectionParams` for + configuring voice activity detection sensitivity in U3 Pro. Aligning this + with external VAD thresholds (e.g., Silero VAD) prevents the "dead zone" + where AssemblyAI transcribes speech that VAD hasn't detected yet. + (PR [#3927](https://github.com/pipecat-ai/pipecat/pull/3927)) + +- Added `push_empty_transcripts` parameter to `BaseWhisperSTTService` and + `OpenAISTTService` to allow empty transcripts to be pushed downstream as + `TranscriptionFrame` instead of discarding them (the default behavior). This + is intended for situations where VAD fires even though the user did not + speak. In these cases, it is useful to know that nothing was transcribed so + that the agent can resume speaking, instead of waiting longer for a + transcription. + (PR [#3930](https://github.com/pipecat-ai/pipecat/pull/3930)) + +- LLM services (`BaseOpenAILLMService`, `AnthropicLLMService`, + `AWSBedrockLLMService`) now log a warning when both `system_instruction` and + a system message in the context are set. The constructor's + `system_instruction` takes precedence. + (PR [#3932](https://github.com/pipecat-ai/pipecat/pull/3932)) + +- Runtime settings updates (via `STTUpdateSettingsFrame`) now work for AWS + Transcribe, Azure, Cartesia, Deepgram, ElevenLabs Realtime, Gradium, and + Soniox STT services. Previously, changing settings at runtime only stored the + new values without reconnecting. + (PR [#3946](https://github.com/pipecat-ai/pipecat/pull/3946)) + +- Exposed `on_summary_applied` event on `LLMAssistantAggregator`, allowing + users to listen for context summarization events without accessing private + members. + (PR [#3947](https://github.com/pipecat-ai/pipecat/pull/3947)) + +- Deepgram Flux STT settings (`keyterm`, `eot_threshold`, + `eager_eot_threshold`, `eot_timeout_ms`) can now be updated mid-stream via + `STTUpdateSettingsFrame` without triggering a reconnect. The new values are + sent to Deepgram as a Configure WebSocket message on the existing connection. + (PR [#3953](https://github.com/pipecat-ai/pipecat/pull/3953)) + +- Added `system_instruction` parameter to `run_inference` across all LLM + services, allowing callers to override the system prompt for one-shot + inference calls. Used by `_generate_summary` to pass the summarization prompt + cleanly. + (PR [#3968](https://github.com/pipecat-ai/pipecat/pull/3968)) + +### Changed + +- Audio context management (previously in `AudioContextTTSService`) is now + built into `TTSService`. All WebSocket providers (`cartesia`, `elevenlabs`, + `asyncai`, `inworld`, `rime`, `gradium`, `resembleai`) now inherit from + `WebsocketTTSService` directly. Word-timestamp baseline is set automatically + on the first audio chunk of each context instead of requiring each provider + to call `start_word_timestamps()` in their receive loop. + (PR [#3804](https://github.com/pipecat-ai/pipecat/pull/3804)) + +- Daily transport now uses `CustomVideoSource`/`CustomVideoTrack` instead of + `VirtualCameraDevice` for the default camera output, mirroring how audio + already works with `CustomAudioSource`/`CustomAudioTrack`. + (PR [#3831](https://github.com/pipecat-ai/pipecat/pull/3831)) + +- ⚠️ Updated `DeepgramSTTService` to use `deepgram-sdk` v6. The `LiveOptions` + class was removed from the SDK and is now provided by pipecat directly; + import it from `pipecat.services.deepgram.stt` instead of `deepgram`. + (PR [#3848](https://github.com/pipecat-ai/pipecat/pull/3848)) + +- `ServiceSwitcherStrategy` base class now provides a `handle_error()` hook for + subclasses to implement error-based switching. `ServiceSwitcher` defaults to + `ServiceSwitcherStrategyManual` and `strategy_type` is now optional. + (PR [#3861](https://github.com/pipecat-ai/pipecat/pull/3861)) + +- Support for Voice Focus 2.0 models. + - Updated `aic-sdk` to `~=2.1.0` to support Voice Focus 2.0 models. + - Cleaned unused `ParameterFixedError` exception handling in `AICFilter` + parameter setup. + (PR [#3889](https://github.com/pipecat-ai/pipecat/pull/3889)) + +- `max_context_tokens` and `max_unsummarized_messages` in + `LLMAutoContextSummarizationConfig` (and deprecated + `LLMContextSummarizationConfig`) can now be set to `None` independently to + disable that summarization threshold. At least one must remain set. + (PR [#3914](https://github.com/pipecat-ai/pipecat/pull/3914)) + +- ⚠️ Removed `formatted_finals` and `word_finalization_max_wait_time` from + `AssemblyAIConnectionParams` as these were v2 API parameters not supported in + v3. Clarified that `format_turns` only applies to Universal-Streaming models; + U3 Pro has automatic formatting built-in. + (PR [#3927](https://github.com/pipecat-ai/pipecat/pull/3927)) + +- Changed `DeepgramTTSService` to send a Clear message on interruption instead + of disconnecting and reconnecting the WebSocket, allowing the connection to + persist throughout the session. + (PR [#3958](https://github.com/pipecat-ai/pipecat/pull/3958)) + +- Re-added `enhancement_level` support to `AICFilter` with runtime + `FilterEnableFrame` control, applying `ProcessorParameter.Bypass` and + `ProcessorParameter.EnhancementLevel` together. + (PR [#3961](https://github.com/pipecat-ai/pipecat/pull/3961)) + +- Updated `daily-python` dependency from `~=0.23.0` to `~=0.24.0`. + (PR [#3970](https://github.com/pipecat-ai/pipecat/pull/3970)) + +- Updated `FishAudioTTSService` default model from `s1` to `s2-pro`, matching + Fish Audio's latest recommended model for improved quality and speed. + (PR [#3973](https://github.com/pipecat-ai/pipecat/pull/3973)) + +- `AzureSTTService` `region` parameter is now optional when `private_endpoint` + is provided. A `ValueError` is raised if neither is given, and a warning is + logged if both are provided (`private_endpoint` takes priority). + (PR [#3974](https://github.com/pipecat-ai/pipecat/pull/3974)) + +### Deprecated + +- Deprecated `AudioContextTTSService` and `AudioContextWordTTSService`. + Subclass `WebsocketTTSService` directly instead; audio context management is + now part of the base `TTSService`. + - Deprecated `WordTTSService`, `WebsocketWordTTSService`, and + `InterruptibleWordTTSService`. Word timestamp logic is now always active in + `TTSService` and no longer needs to be opted into via a subclass. + (PR [#3804](https://github.com/pipecat-ai/pipecat/pull/3804)) + +- Deprecated `pipecat.services.google.llm_vertex`, + `pipecat.services.google.llm_openai`, and + `pipecat.services.google.gemini_live.llm_vertex` modules. Use + `pipecat.services.google.vertex.llm`, `pipecat.services.google.openai.llm`, + and `pipecat.services.google.gemini_live.vertex.llm` instead. The old import + paths still work but will emit a `DeprecationWarning`. + (PR [#3980](https://github.com/pipecat-ai/pipecat/pull/3980)) + +### Removed + +- ⚠️ Removed `supports_word_timestamps` parameter from `TTSService.__init__()`. + Word timestamp logic is now always active. Remove this argument from any + custom subclass `super().__init__()` calls. + (PR [#3804](https://github.com/pipecat-ai/pipecat/pull/3804)) + +### Fixed + +- Fixed `DeepgramSTTService` keepalive ping timeout disconnections. The + deepgram-sdk v6 removed automatic keepalive; pipecat now sends explicit + `KeepAlive` messages every 5 seconds, within the recommended 3–5 second + interval before Deepgram's 10-second inactivity timeout. + (PR [#3848](https://github.com/pipecat-ai/pipecat/pull/3848)) + +- Fixed `BufferError: Existing exports of data: object cannot be re-sized` in + `AICFilter` caused by holding a `memoryview` on the mutable audio buffer + across async yield points. + (PR [#3889](https://github.com/pipecat-ai/pipecat/pull/3889)) + +- Fixed TTS context not being appended to the assistant message history when + using `TTSSpeakFrame` with `append_to_context=True` with some TTS providers. + (PR [#3936](https://github.com/pipecat-ai/pipecat/pull/3936)) + +- Fixed context summarization leaving orphaned tool responses in the kept + context when tool calls were moved to the summarized portion. + (PR [#3937](https://github.com/pipecat-ai/pipecat/pull/3937)) + +- Fixed turn completion state not resetting at end of LLM responses. + `LLMFullResponseEndFrame` is pushed (not received) by the LLM service, so the + mixin now handles it in `push_frame` instead of `process_frame`. + (PR [#3956](https://github.com/pipecat-ai/pipecat/pull/3956)) + +- Fixed turn completion instructions being injected as a context system message + instead of using `system_instruction`. This caused warning spam when + `system_instruction` was also set and didn't persist across full context + updates. + (PR [#3957](https://github.com/pipecat-ai/pipecat/pull/3957)) + +- Fixed `TTSService` audio context queue getting blocked when + `append_to_audio_context()` was called with a `None` context ID, which + prevented subsequent audio from being delivered. + (PR [#3958](https://github.com/pipecat-ai/pipecat/pull/3958)) + +- Fixed `on_call_state_updated` event handler in LiveKit transport receiving + incorrect number of arguments due to redundant `self` passed to + `_call_event_handler`. + (PR [#3959](https://github.com/pipecat-ai/pipecat/pull/3959)) + +- Fixed OpenAI Realtime, OpenAI Realtime Beta, and Grok realtime services + treating `conversation_already_has_active_response` as a fatal error. These + services now log it as a non-fatal debug event when a response is already in + progress. + (PR [#3960](https://github.com/pipecat-ai/pipecat/pull/3960)) + +- Fixed `SmallWebRTCConnection` silently discarding messages sent before the + data channel is open by queuing them and flushing once the channel is ready. + A bounded queue (`MAX_MESSAGE_QUEUE_SIZE = 50`) prevents unbounded memory + growth, and a 10-second timeout after connection clears the queue and falls + back to discard mode if the data channel never opens. + (PR [#3962](https://github.com/pipecat-ai/pipecat/pull/3962)) + +- Fixed `AzureSTTService` failing to initialize when `private_endpoint` is + provided. The Azure Speech SDK's `SpeechConfig` does not accept both `region` + and `endpoint` simultaneously, so they are now passed conditionally. + (PR [#3967](https://github.com/pipecat-ai/pipecat/pull/3967)) + +- Fixed `GoogleLLMService` ignoring the `system_instruction` set via + constructor or `GoogleLLMSettings` when a system message was also present in + the context. The settings value now correctly takes priority, and a warning + is logged when both are set. + (PR [#3976](https://github.com/pipecat-ai/pipecat/pull/3976)) + +### Other + +- Updated foundational examples to use `system_instruction` on LLM services + instead of adding system messages to `LLMContext`. + (PR [#3918](https://github.com/pipecat-ai/pipecat/pull/3918)) + +- Updated AssemblyAI turn detection example to use `keyterms_prompt` list + format instead of `prompt` string for improved clarity. + (PR [#3929](https://github.com/pipecat-ai/pipecat/pull/3929)) + +- Updated foundational examples and eval scripts to use `"user"` role instead + of `"system"` when adding messages to `LLMContext`, since system prompts + should be set via `system_instruction` on the LLM service. + (PR [#3931](https://github.com/pipecat-ai/pipecat/pull/3931)) + ## [0.0.104] - 2026-03-02 ### Added diff --git a/changelog/3804.added.md b/changelog/3804.added.md deleted file mode 100644 index 0ad7676c9..000000000 --- a/changelog/3804.added.md +++ /dev/null @@ -1 +0,0 @@ -- Added concurrent audio context support: `CartesiaTTSService` can now synthesize the next sentence while the previous one is still playing, by setting `pause_frame_processing=False` and routing each sentence through its own audio context queue. diff --git a/changelog/3804.changed.md b/changelog/3804.changed.md deleted file mode 100644 index 9caae491f..000000000 --- a/changelog/3804.changed.md +++ /dev/null @@ -1 +0,0 @@ -- Audio context management (previously in `AudioContextTTSService`) is now built into `TTSService`. All WebSocket providers (`cartesia`, `elevenlabs`, `asyncai`, `inworld`, `rime`, `gradium`, `resembleai`) now inherit from `WebsocketTTSService` directly. Word-timestamp baseline is set automatically on the first audio chunk of each context instead of requiring each provider to call `start_word_timestamps()` in their receive loop. diff --git a/changelog/3804.deprecated.md b/changelog/3804.deprecated.md deleted file mode 100644 index 0babfe7d4..000000000 --- a/changelog/3804.deprecated.md +++ /dev/null @@ -1,2 +0,0 @@ -- Deprecated `AudioContextTTSService` and `AudioContextWordTTSService`. Subclass `WebsocketTTSService` directly instead; audio context management is now part of the base `TTSService`. -- Deprecated `WordTTSService`, `WebsocketWordTTSService`, and `InterruptibleWordTTSService`. Word timestamp logic is now always active in `TTSService` and no longer needs to be opted into via a subclass. diff --git a/changelog/3804.removed.md b/changelog/3804.removed.md deleted file mode 100644 index 1813b5999..000000000 --- a/changelog/3804.removed.md +++ /dev/null @@ -1 +0,0 @@ -- ⚠️ Removed `supports_word_timestamps` parameter from `TTSService.__init__()`. Word timestamp logic is now always active. Remove this argument from any custom subclass `super().__init__()` calls. diff --git a/changelog/3831.added.md b/changelog/3831.added.md deleted file mode 100644 index 7c3f7f4df..000000000 --- a/changelog/3831.added.md +++ /dev/null @@ -1 +0,0 @@ -- Added custom video track support to Daily transport. Use `video_out_destinations` in `DailyParams` to publish multiple video tracks simultaneously, mirroring the existing `audio_out_destinations` feature. diff --git a/changelog/3831.changed.md b/changelog/3831.changed.md deleted file mode 100644 index bb4d7df83..000000000 --- a/changelog/3831.changed.md +++ /dev/null @@ -1 +0,0 @@ -- Daily transport now uses `CustomVideoSource`/`CustomVideoTrack` instead of `VirtualCameraDevice` for the default camera output, mirroring how audio already works with `CustomAudioSource`/`CustomAudioTrack`. diff --git a/changelog/3848.changed.md b/changelog/3848.changed.md deleted file mode 100644 index 1590e284a..000000000 --- a/changelog/3848.changed.md +++ /dev/null @@ -1 +0,0 @@ -- ⚠️ Updated `DeepgramSTTService` to use `deepgram-sdk` v6. The `LiveOptions` class was removed from the SDK and is now provided by pipecat directly; import it from `pipecat.services.deepgram.stt` instead of `deepgram`. diff --git a/changelog/3848.fixed.md b/changelog/3848.fixed.md deleted file mode 100644 index a6651b763..000000000 --- a/changelog/3848.fixed.md +++ /dev/null @@ -1 +0,0 @@ -- Fixed `DeepgramSTTService` keepalive ping timeout disconnections. The deepgram-sdk v6 removed automatic keepalive; pipecat now sends explicit `KeepAlive` messages every 5 seconds, within the recommended 3–5 second interval before Deepgram's 10-second inactivity timeout. diff --git a/changelog/3861.added.md b/changelog/3861.added.md deleted file mode 100644 index c0a6f6aee..000000000 --- a/changelog/3861.added.md +++ /dev/null @@ -1 +0,0 @@ -- Added `ServiceSwitcherStrategyFailover` that automatically switches to the next service when the active service reports a non-fatal error. Recovery policies can be implemented via the `on_service_switched` event handler. diff --git a/changelog/3861.changed.md b/changelog/3861.changed.md deleted file mode 100644 index 41c577dcd..000000000 --- a/changelog/3861.changed.md +++ /dev/null @@ -1 +0,0 @@ -- `ServiceSwitcherStrategy` base class now provides a `handle_error()` hook for subclasses to implement error-based switching. `ServiceSwitcher` defaults to `ServiceSwitcherStrategyManual` and `strategy_type` is now optional. diff --git a/changelog/3889.changed.md b/changelog/3889.changed.md deleted file mode 100644 index c04aa0080..000000000 --- a/changelog/3889.changed.md +++ /dev/null @@ -1,3 +0,0 @@ -- Support for Voice Focus 2.0 models. - - Updated `aic-sdk` to `~=2.1.0` to support Voice Focus 2.0 models. - - Cleaned unused `ParameterFixedError` exception handling in `AICFilter` parameter setup. diff --git a/changelog/3889.fixed.md b/changelog/3889.fixed.md deleted file mode 100644 index babe3eb35..000000000 --- a/changelog/3889.fixed.md +++ /dev/null @@ -1 +0,0 @@ -- Fixed `BufferError: Existing exports of data: object cannot be re-sized` in `AICFilter` caused by holding a `memoryview` on the mutable audio buffer across async yield points. diff --git a/changelog/3914.changed.md b/changelog/3914.changed.md deleted file mode 100644 index 22d4ff94e..000000000 --- a/changelog/3914.changed.md +++ /dev/null @@ -1 +0,0 @@ -- `max_context_tokens` and `max_unsummarized_messages` in `LLMAutoContextSummarizationConfig` (and deprecated `LLMContextSummarizationConfig`) can now be set to `None` independently to disable that summarization threshold. At least one must remain set. diff --git a/changelog/3915.added.md b/changelog/3915.added.md deleted file mode 100644 index 66d4fb383..000000000 --- a/changelog/3915.added.md +++ /dev/null @@ -1 +0,0 @@ -- Added optional `timeout_secs` parameter to `register_function()` and `register_direct_function()` for per-tool function call timeout control, overriding the global `function_call_timeout_secs` default. diff --git a/changelog/3916.added.md b/changelog/3916.added.md deleted file mode 100644 index 05c3f124f..000000000 --- a/changelog/3916.added.md +++ /dev/null @@ -1 +0,0 @@ -- Added `cloud-audio-only` recording option to Daily transport's `enable_recording` property. diff --git a/changelog/3918.added.md b/changelog/3918.added.md deleted file mode 100644 index 6b4d4446f..000000000 --- a/changelog/3918.added.md +++ /dev/null @@ -1,15 +0,0 @@ -- Wired up `system_instruction` in `BaseOpenAILLMService`, `AnthropicLLMService`, and `AWSBedrockLLMService` so it works as a default system prompt, matching the behavior of the Google services. This enables sharing a single `LLMContext` across multiple LLM services, where each service provides its own system instruction independently. - - ```python - llm = OpenAILLMService( - api_key=os.getenv("OPENAI_API_KEY"), - system_instruction="You are a helpful assistant.", - ) - - context = LLMContext() - - @transport.event_handler("on_client_connected") - async def on_client_connected(transport, client): - context.add_message({"role": "user", "content": "Please introduce yourself."}) - await task.queue_frames([LLMRunFrame()]) - ``` diff --git a/changelog/3918.other.md b/changelog/3918.other.md deleted file mode 100644 index 6caa1ba05..000000000 --- a/changelog/3918.other.md +++ /dev/null @@ -1 +0,0 @@ -- Updated foundational examples to use `system_instruction` on LLM services instead of adding system messages to `LLMContext`. diff --git a/changelog/3927.added.md b/changelog/3927.added.md deleted file mode 100644 index 378815fc3..000000000 --- a/changelog/3927.added.md +++ /dev/null @@ -1 +0,0 @@ -- Added `vad_threshold` parameter to `AssemblyAIConnectionParams` for configuring voice activity detection sensitivity in U3 Pro. Aligning this with external VAD thresholds (e.g., Silero VAD) prevents the "dead zone" where AssemblyAI transcribes speech that VAD hasn't detected yet. diff --git a/changelog/3927.changed.md b/changelog/3927.changed.md deleted file mode 100644 index b397e86a2..000000000 --- a/changelog/3927.changed.md +++ /dev/null @@ -1 +0,0 @@ -- ⚠️ Removed `formatted_finals` and `word_finalization_max_wait_time` from `AssemblyAIConnectionParams` as these were v2 API parameters not supported in v3. Clarified that `format_turns` only applies to Universal-Streaming models; U3 Pro has automatic formatting built-in. diff --git a/changelog/3929.other.md b/changelog/3929.other.md deleted file mode 100644 index c1d9f8dda..000000000 --- a/changelog/3929.other.md +++ /dev/null @@ -1 +0,0 @@ -- Updated AssemblyAI turn detection example to use `keyterms_prompt` list format instead of `prompt` string for improved clarity. diff --git a/changelog/3930.added.md b/changelog/3930.added.md deleted file mode 100644 index dd799f9ec..000000000 --- a/changelog/3930.added.md +++ /dev/null @@ -1 +0,0 @@ -- Added `push_empty_transcripts` parameter to `BaseWhisperSTTService` and `OpenAISTTService` to allow empty transcripts to be pushed downstream as `TranscriptionFrame` instead of discarding them (the default behavior). This is intended for situations where VAD fires even though the user did not speak. In these cases, it is useful to know that nothing was transcribed so that the agent can resume speaking, instead of waiting longer for a transcription. \ No newline at end of file diff --git a/changelog/3931.other.md b/changelog/3931.other.md deleted file mode 100644 index a1ebef414..000000000 --- a/changelog/3931.other.md +++ /dev/null @@ -1 +0,0 @@ -- Updated foundational examples and eval scripts to use `"user"` role instead of `"system"` when adding messages to `LLMContext`, since system prompts should be set via `system_instruction` on the LLM service. diff --git a/changelog/3932.added.md b/changelog/3932.added.md deleted file mode 100644 index e97690d44..000000000 --- a/changelog/3932.added.md +++ /dev/null @@ -1 +0,0 @@ -- LLM services (`BaseOpenAILLMService`, `AnthropicLLMService`, `AWSBedrockLLMService`) now log a warning when both `system_instruction` and a system message in the context are set. The constructor's `system_instruction` takes precedence. diff --git a/changelog/3936.fixed.md b/changelog/3936.fixed.md deleted file mode 100644 index 27e48815c..000000000 --- a/changelog/3936.fixed.md +++ /dev/null @@ -1 +0,0 @@ -- Fixed TTS context not being appended to the assistant message history when using `TTSSpeakFrame` with `append_to_context=True` with some TTS providers. diff --git a/changelog/3937.fixed.md b/changelog/3937.fixed.md deleted file mode 100644 index eda9d27f6..000000000 --- a/changelog/3937.fixed.md +++ /dev/null @@ -1 +0,0 @@ -- Fixed context summarization leaving orphaned tool responses in the kept context when tool calls were moved to the summarized portion. diff --git a/changelog/3946.added.md b/changelog/3946.added.md deleted file mode 100644 index 6aabfefb2..000000000 --- a/changelog/3946.added.md +++ /dev/null @@ -1 +0,0 @@ -- Runtime settings updates (via `STTUpdateSettingsFrame`) now work for AWS Transcribe, Azure, Cartesia, Deepgram, ElevenLabs Realtime, Gradium, and Soniox STT services. Previously, changing settings at runtime only stored the new values without reconnecting. diff --git a/changelog/3947.added.md b/changelog/3947.added.md deleted file mode 100644 index 175cb87bd..000000000 --- a/changelog/3947.added.md +++ /dev/null @@ -1 +0,0 @@ -- Exposed `on_summary_applied` event on `LLMAssistantAggregator`, allowing users to listen for context summarization events without accessing private members. diff --git a/changelog/3953.added.md b/changelog/3953.added.md deleted file mode 100644 index f30c31733..000000000 --- a/changelog/3953.added.md +++ /dev/null @@ -1 +0,0 @@ -- Deepgram Flux STT settings (`keyterm`, `eot_threshold`, `eager_eot_threshold`, `eot_timeout_ms`) can now be updated mid-stream via `STTUpdateSettingsFrame` without triggering a reconnect. The new values are sent to Deepgram as a Configure WebSocket message on the existing connection. diff --git a/changelog/3956.fixed.md b/changelog/3956.fixed.md deleted file mode 100644 index c8af8db91..000000000 --- a/changelog/3956.fixed.md +++ /dev/null @@ -1 +0,0 @@ -- Fixed turn completion state not resetting at end of LLM responses. `LLMFullResponseEndFrame` is pushed (not received) by the LLM service, so the mixin now handles it in `push_frame` instead of `process_frame`. diff --git a/changelog/3957.fixed.md b/changelog/3957.fixed.md deleted file mode 100644 index a501aecb1..000000000 --- a/changelog/3957.fixed.md +++ /dev/null @@ -1 +0,0 @@ -- Fixed turn completion instructions being injected as a context system message instead of using `system_instruction`. This caused warning spam when `system_instruction` was also set and didn't persist across full context updates. diff --git a/changelog/3958.changed.md b/changelog/3958.changed.md deleted file mode 100644 index dbeabd0f2..000000000 --- a/changelog/3958.changed.md +++ /dev/null @@ -1 +0,0 @@ -- Changed `DeepgramTTSService` to send a Clear message on interruption instead of disconnecting and reconnecting the WebSocket, allowing the connection to persist throughout the session. diff --git a/changelog/3958.fixed.md b/changelog/3958.fixed.md deleted file mode 100644 index 8bc21dffe..000000000 --- a/changelog/3958.fixed.md +++ /dev/null @@ -1 +0,0 @@ -- Fixed `TTSService` audio context queue getting blocked when `append_to_audio_context()` was called with a `None` context ID, which prevented subsequent audio from being delivered. diff --git a/changelog/3959.fixed.md b/changelog/3959.fixed.md deleted file mode 100644 index a10521d92..000000000 --- a/changelog/3959.fixed.md +++ /dev/null @@ -1 +0,0 @@ -- Fixed `on_call_state_updated` event handler in LiveKit transport receiving incorrect number of arguments due to redundant `self` passed to `_call_event_handler`. diff --git a/changelog/3960.fixed.md b/changelog/3960.fixed.md deleted file mode 100644 index 404569234..000000000 --- a/changelog/3960.fixed.md +++ /dev/null @@ -1 +0,0 @@ -- Fixed OpenAI Realtime, OpenAI Realtime Beta, and Grok realtime services treating `conversation_already_has_active_response` as a fatal error. These services now log it as a non-fatal debug event when a response is already in progress. diff --git a/changelog/3961.changed.md b/changelog/3961.changed.md deleted file mode 100644 index 19c2780e3..000000000 --- a/changelog/3961.changed.md +++ /dev/null @@ -1 +0,0 @@ -- Re-added `enhancement_level` support to `AICFilter` with runtime `FilterEnableFrame` control, applying `ProcessorParameter.Bypass` and `ProcessorParameter.EnhancementLevel` together. diff --git a/changelog/3962.fixed.md b/changelog/3962.fixed.md deleted file mode 100644 index 1d326cd05..000000000 --- a/changelog/3962.fixed.md +++ /dev/null @@ -1 +0,0 @@ -- Fixed `SmallWebRTCConnection` silently discarding messages sent before the data channel is open by queuing them and flushing once the channel is ready. A bounded queue (`MAX_MESSAGE_QUEUE_SIZE = 50`) prevents unbounded memory growth, and a 10-second timeout after connection clears the queue and falls back to discard mode if the data channel never opens. diff --git a/changelog/3967.fixed.md b/changelog/3967.fixed.md deleted file mode 100644 index dff880c2c..000000000 --- a/changelog/3967.fixed.md +++ /dev/null @@ -1 +0,0 @@ -- Fixed `AzureSTTService` failing to initialize when `private_endpoint` is provided. The Azure Speech SDK's `SpeechConfig` does not accept both `region` and `endpoint` simultaneously, so they are now passed conditionally. diff --git a/changelog/3968.added.md b/changelog/3968.added.md deleted file mode 100644 index cd9be5996..000000000 --- a/changelog/3968.added.md +++ /dev/null @@ -1 +0,0 @@ -- Added `system_instruction` parameter to `run_inference` across all LLM services, allowing callers to override the system prompt for one-shot inference calls. Used by `_generate_summary` to pass the summarization prompt cleanly. diff --git a/changelog/3970.changed.md b/changelog/3970.changed.md deleted file mode 100644 index f420a7e73..000000000 --- a/changelog/3970.changed.md +++ /dev/null @@ -1 +0,0 @@ -- Updated `daily-python` dependency from `~=0.23.0` to `~=0.24.0`. diff --git a/changelog/3973.changed.md b/changelog/3973.changed.md deleted file mode 100644 index d6834ce8e..000000000 --- a/changelog/3973.changed.md +++ /dev/null @@ -1 +0,0 @@ -- Updated `FishAudioTTSService` default model from `s1` to `s2-pro`, matching Fish Audio's latest recommended model for improved quality and speed. diff --git a/changelog/3974.changed.md b/changelog/3974.changed.md deleted file mode 100644 index 7c4c360d5..000000000 --- a/changelog/3974.changed.md +++ /dev/null @@ -1 +0,0 @@ -- `AzureSTTService` `region` parameter is now optional when `private_endpoint` is provided. A `ValueError` is raised if neither is given, and a warning is logged if both are provided (`private_endpoint` takes priority). diff --git a/changelog/3976.fixed.md b/changelog/3976.fixed.md deleted file mode 100644 index 3153cdcbe..000000000 --- a/changelog/3976.fixed.md +++ /dev/null @@ -1 +0,0 @@ -- Fixed `GoogleLLMService` ignoring the `system_instruction` set via constructor or `GoogleLLMSettings` when a system message was also present in the context. The settings value now correctly takes priority, and a warning is logged when both are set. diff --git a/changelog/3980.deprecated.md b/changelog/3980.deprecated.md deleted file mode 100644 index f69964b62..000000000 --- a/changelog/3980.deprecated.md +++ /dev/null @@ -1 +0,0 @@ -- Deprecated `pipecat.services.google.llm_vertex`, `pipecat.services.google.llm_openai`, and `pipecat.services.google.gemini_live.llm_vertex` modules. Use `pipecat.services.google.vertex.llm`, `pipecat.services.google.openai.llm`, and `pipecat.services.google.gemini_live.vertex.llm` instead. The old import paths still work but will emit a `DeprecationWarning`. From 087abc9bb901687403c2f4f0bbdd9bfedca648fc Mon Sep 17 00:00:00 2001 From: Paul Kompfner Date: Wed, 11 Mar 2026 09:56:32 -0400 Subject: [PATCH 0928/1060] Fix outdated CambTTSService docstring example --- src/pipecat/services/camb/tts.py | 13 ++++++++++--- 1 file changed, 10 insertions(+), 3 deletions(-) diff --git a/src/pipecat/services/camb/tts.py b/src/pipecat/services/camb/tts.py index 9918b2320..f458fa2e4 100644 --- a/src/pipecat/services/camb/tts.py +++ b/src/pipecat/services/camb/tts.py @@ -158,13 +158,20 @@ class CambTTSService(TTSService): Example:: # Basic usage with mars-flash (fast) - tts = CambTTSService(api_key="your-api-key", model="mars-flash") + tts = CambTTSService( + api_key="your-api-key", + settings=CambTTSService.Settings( + model="mars-flash" + ) + ) # High quality with mars-pro tts = CambTTSService( api_key="your-api-key", - voice_id=12345, - model="mars-pro", + settings=CambTTSService.Settings( + voice=12345, + model="mars-pro", + ) ) """ From 916936d3ee33c0df5d92fe2dda0d96f8516b27ab Mon Sep 17 00:00:00 2001 From: Paul Kompfner Date: Wed, 11 Mar 2026 10:07:07 -0400 Subject: [PATCH 0929/1060] Fix outdated Sarvam TTS docstring examples --- src/pipecat/services/sarvam/tts.py | 40 +++++++++++++++--------------- 1 file changed, 20 insertions(+), 20 deletions(-) diff --git a/src/pipecat/services/sarvam/tts.py b/src/pipecat/services/sarvam/tts.py index 639a860ac..0d6a872eb 100644 --- a/src/pipecat/services/sarvam/tts.py +++ b/src/pipecat/services/sarvam/tts.py @@ -326,28 +326,28 @@ class SarvamHttpTTSService(TTSService): # Using bulbul:v2 (default) tts = SarvamHttpTTSService( api_key="your-api-key", - voice_id="anushka", - model="bulbul:v2", aiohttp_session=session, - params=SarvamHttpTTSService.InputParams( + settings=SarvamHttpTTSService.Settings( + voice="anushka", + model="bulbul:v2", language=Language.HI, pitch=0.1, pace=1.2, - loudness=1.5 - ) + loudness=1.5, + ), ) # Using bulbul:v3-beta with temperature control tts_v3 = SarvamHttpTTSService( api_key="your-api-key", - voice_id="aditya", # Use v3 speaker - model="bulbul:v3-beta", aiohttp_session=session, - params=SarvamHttpTTSService.InputParams( + settings=SarvamHttpTTSService.Settings( + voice="aditya", # Use v3 speaker + model="bulbul:v3-beta", language=Language.HI, pace=1.2, # Range: 0.5-2.0 for v3 - temperature=0.8 - ) + temperature=0.8, + ), ) """ @@ -693,26 +693,26 @@ class SarvamTTSService(InterruptibleTTSService): # Using bulbul:v2 (default) tts = SarvamTTSService( api_key="your-api-key", - voice_id="anushka", - model="bulbul:v2", - params=SarvamTTSService.InputParams( + settings=SarvamTTSService.Settings( + voice="anushka", + model="bulbul:v2", language=Language.HI, pitch=0.1, pace=1.2, - loudness=1.5 - ) + loudness=1.5, + ), ) # Using bulbul:v3-beta with temperature control tts_v3 = SarvamTTSService( api_key="your-api-key", - voice_id="aditya", # Use v3 speaker - model="bulbul:v3-beta", - params=SarvamTTSService.InputParams( + settings=SarvamTTSService.Settings( + voice="aditya", # Use v3 speaker + model="bulbul:v3-beta", language=Language.HI, pace=1.2, # Range: 0.5-2.0 for v3 - temperature=0.8 - ) + temperature=0.8, + ), ) See https://docs.sarvam.ai/api-reference-docs/text-to-speech/stream for API details. From 264ce681f7f017c4dc735ba0a51cd34d64f15920 Mon Sep 17 00:00:00 2001 From: Paul Kompfner Date: Wed, 11 Mar 2026 10:10:15 -0400 Subject: [PATCH 0930/1060] Fix outdated DeepgramSageMakerSTTService docstring example --- src/pipecat/services/deepgram/sagemaker/stt.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/src/pipecat/services/deepgram/sagemaker/stt.py b/src/pipecat/services/deepgram/sagemaker/stt.py index 812a2701e..f6093a630 100644 --- a/src/pipecat/services/deepgram/sagemaker/stt.py +++ b/src/pipecat/services/deepgram/sagemaker/stt.py @@ -69,7 +69,7 @@ class DeepgramSageMakerSTTService(STTService): stt = DeepgramSageMakerSTTService( endpoint_name="my-deepgram-endpoint", region="us-east-2", - settings=DeepgramSageMakerSTTSettings( + settings=DeepgramSageMakerSTTService.Settings( model="nova-3", language="en", interim_results=True, From 0ebcb555829c73103f15810b90f133accdc60c43 Mon Sep 17 00:00:00 2001 From: Paul Kompfner Date: Wed, 11 Mar 2026 10:11:26 -0400 Subject: [PATCH 0931/1060] Fix outdated DeepgramSageMakerTTSService docstring example --- src/pipecat/services/deepgram/sagemaker/tts.py | 4 +++- 1 file changed, 3 insertions(+), 1 deletion(-) diff --git a/src/pipecat/services/deepgram/sagemaker/tts.py b/src/pipecat/services/deepgram/sagemaker/tts.py index a40f56713..d315b9e01 100644 --- a/src/pipecat/services/deepgram/sagemaker/tts.py +++ b/src/pipecat/services/deepgram/sagemaker/tts.py @@ -63,7 +63,9 @@ class DeepgramSageMakerTTSService(TTSService): tts = DeepgramSageMakerTTSService( endpoint_name="my-deepgram-tts-endpoint", region="us-east-2", - voice="aura-2-helena-en", + settings=DeepgramSageMakerTTSService.Settings( + voice="aura-2-helena-en", + ) ) """ From df82df8e39ac5f3a4353734ce7ff0abf8646f7ba Mon Sep 17 00:00:00 2001 From: Paul Kompfner Date: Wed, 11 Mar 2026 10:14:18 -0400 Subject: [PATCH 0932/1060] Fix outdated Google + Gemini TTS service docstring examples --- src/pipecat/services/google/tts.py | 10 +++++----- 1 file changed, 5 insertions(+), 5 deletions(-) diff --git a/src/pipecat/services/google/tts.py b/src/pipecat/services/google/tts.py index a9394028b..9d92c91ea 100644 --- a/src/pipecat/services/google/tts.py +++ b/src/pipecat/services/google/tts.py @@ -1014,8 +1014,8 @@ class GoogleTTSService(GoogleBaseTTSService): tts = GoogleTTSService( credentials_path="/path/to/service-account.json", - voice_id="en-US-Chirp3-HD-Charon", - params=GoogleTTSService.InputParams( + settings=GoogleTTSService.Settings( + voice="en-US-Chirp3-HD-Charon", language=Language.EN_US, ) ) @@ -1191,9 +1191,9 @@ class GeminiTTSService(GoogleBaseTTSService): tts = GeminiTTSService( credentials_path="/path/to/service-account.json", - model="gemini-2.5-flash-tts", - voice_id="Kore", - params=GeminiTTSService.InputParams( + settings=GeminiTTSService.Settings( + model="gemini-2.5-flash-tts", + voice="Kore", language=Language.EN_US, prompt="Say this in a friendly and helpful tone" ) From 42262d10bbe0908cfa1cf52d8237c84e28676757 Mon Sep 17 00:00:00 2001 From: Paul Kompfner Date: Wed, 11 Mar 2026 10:17:24 -0400 Subject: [PATCH 0933/1060] Move OpenAIRealtimeSTTService's noise_reduction into its Settings object, as it might be useful to update it at runtime, and fix outdated OpenAIRealtimeSTTService docstring example --- src/pipecat/services/openai/stt.py | 24 +++++++++++++++++++----- 1 file changed, 19 insertions(+), 5 deletions(-) diff --git a/src/pipecat/services/openai/stt.py b/src/pipecat/services/openai/stt.py index e2f9ec0ee..473b23637 100644 --- a/src/pipecat/services/openai/stt.py +++ b/src/pipecat/services/openai/stt.py @@ -187,9 +187,15 @@ class OpenAIRealtimeSTTSettings(STTSettings): Parameters: prompt: Optional prompt text to guide transcription style. + noise_reduction: Noise reduction mode. ``"near_field"`` for close + microphones, ``"far_field"`` for distant microphones, or ``None`` + to disable. """ prompt: str | None | _NotGiven = field(default_factory=lambda: NOT_GIVEN) + noise_reduction: Literal["near_field", "far_field"] | None | _NotGiven = field( + default_factory=lambda: NOT_GIVEN + ) class OpenAIRealtimeSTTService(WebsocketSTTService): @@ -220,8 +226,10 @@ class OpenAIRealtimeSTTService(WebsocketSTTService): stt = OpenAIRealtimeSTTService( api_key="sk-...", - model="gpt-4o-transcribe", - noise_reduction="near_field", + settings=OpenAIRealtimeSTTService.Settings( + model="gpt-4o-transcribe", + noise_reduction="near_field", + ), ) """ @@ -274,6 +282,9 @@ class OpenAIRealtimeSTTService(WebsocketSTTService): noise_reduction: Noise reduction mode. ``"near_field"`` for close microphones, ``"far_field"`` for distant microphones, or ``None`` to disable. + + .. deprecated:: 0.0.106 + Use ``settings=OpenAIRealtimeSTTSettings(noise_reduction=...)`` instead. should_interrupt: Whether to interrupt bot output when speech is detected by server-side VAD. Only applies when turn detection is enabled. Defaults to True. @@ -295,6 +306,7 @@ class OpenAIRealtimeSTTService(WebsocketSTTService): model="gpt-4o-transcribe", language=Language.EN, prompt=None, + noise_reduction=None, ) # --- 2. Deprecated direct-arg overrides --- @@ -307,6 +319,9 @@ class OpenAIRealtimeSTTService(WebsocketSTTService): if prompt is not None: _warn_deprecated_param("prompt", OpenAIRealtimeSTTSettings, "prompt") default_settings.prompt = prompt + if noise_reduction is not None: + _warn_deprecated_param("noise_reduction", OpenAIRealtimeSTTSettings, "noise_reduction") + default_settings.noise_reduction = noise_reduction # --- 3. (no params object for this service) --- @@ -324,7 +339,6 @@ class OpenAIRealtimeSTTService(WebsocketSTTService): self._base_url = base_url self._turn_detection = turn_detection - self._noise_reduction = noise_reduction self._should_interrupt = should_interrupt self._receive_task = None @@ -544,9 +558,9 @@ class OpenAIRealtimeSTTService(WebsocketSTTService): input_audio["turn_detection"] = self._turn_detection # Noise reduction - if self._noise_reduction: + if self._settings.noise_reduction: input_audio["noise_reduction"] = { - "type": self._noise_reduction, + "type": self._settings.noise_reduction, } await self._ws_send( From 3cbd27d20235dc90b6b60d6b37a24f70cb1ac4fe Mon Sep 17 00:00:00 2001 From: Paul Kompfner Date: Wed, 11 Mar 2026 10:34:00 -0400 Subject: [PATCH 0934/1060] Add changelog for PR #3991 --- changelog/3991.changed.md | 1 + 1 file changed, 1 insertion(+) create mode 100644 changelog/3991.changed.md diff --git a/changelog/3991.changed.md b/changelog/3991.changed.md new file mode 100644 index 000000000..5767dc8aa --- /dev/null +++ b/changelog/3991.changed.md @@ -0,0 +1 @@ +- `OpenAIRealtimeSTTService`'s `noise_reduction` parameter is now part of `OpenAIRealtimeSTTSettings`, making it runtime-updatable via `STTUpdateSettingsFrame`. The direct `noise_reduction` init argument is deprecated as of 0.0.106. From 6b168d6bbbbc67444e9a23e9aeb1c992cc4eddc5 Mon Sep 17 00:00:00 2001 From: Paul Kompfner Date: Wed, 11 Mar 2026 12:15:00 -0400 Subject: [PATCH 0935/1060] Prefer Service.Settings over raw settings class names across all services Replace direct references to settings class names (e.g. `FooSettings`) with the nested `Settings` alias form throughout all 87 service files: - Type annotations: `Settings` - Runtime code: `self.Settings` - Docstrings: `ServiceClass.Settings` - Cross-file inheritance: `ParentService.Settings` This makes the `Settings` alias the canonical way to reference a service's settings, keeping only the class definition and alias assignment as the remaining hits for each raw settings class name. --- src/pipecat/services/anthropic/llm.py | 16 ++--- src/pipecat/services/assemblyai/models.py | 2 +- src/pipecat/services/assemblyai/stt.py | 18 +++--- src/pipecat/services/asyncai/tts.py | 40 ++++++------- src/pipecat/services/aws/llm.py | 20 +++---- src/pipecat/services/aws/nova_sonic/llm.py | 28 ++++----- src/pipecat/services/aws/stt.py | 10 ++-- src/pipecat/services/aws/tts.py | 16 ++--- src/pipecat/services/azure/image.py | 14 ++--- src/pipecat/services/azure/llm.py | 12 ++-- src/pipecat/services/azure/realtime/llm.py | 6 +- src/pipecat/services/azure/stt.py | 10 ++-- src/pipecat/services/azure/tts.py | 29 ++++----- src/pipecat/services/camb/tts.py | 20 +++---- src/pipecat/services/cartesia/stt.py | 14 ++--- src/pipecat/services/cartesia/tts.py | 36 +++++------ src/pipecat/services/cerebras/llm.py | 14 ++--- src/pipecat/services/deepgram/flux/stt.py | 20 +++---- .../services/deepgram/sagemaker/stt.py | 20 +++---- .../services/deepgram/sagemaker/tts.py | 10 ++-- src/pipecat/services/deepgram/stt.py | 16 ++--- src/pipecat/services/deepgram/tts.py | 22 +++---- src/pipecat/services/deepseek/llm.py | 14 ++--- src/pipecat/services/elevenlabs/stt.py | 34 +++++------ src/pipecat/services/elevenlabs/tts.py | 56 ++++++++--------- src/pipecat/services/fal/image.py | 18 +++--- src/pipecat/services/fal/stt.py | 12 ++-- src/pipecat/services/fireworks/llm.py | 14 ++--- src/pipecat/services/fish/tts.py | 22 +++---- src/pipecat/services/gladia/config.py | 2 +- src/pipecat/services/gladia/stt.py | 16 ++--- .../services/google/gemini_live/llm.py | 20 +++---- .../services/google/gemini_live/vertex/llm.py | 21 ++++--- src/pipecat/services/google/image.py | 12 ++-- src/pipecat/services/google/llm.py | 20 +++---- src/pipecat/services/google/openai/llm.py | 14 ++--- src/pipecat/services/google/stt.py | 30 +++++----- src/pipecat/services/google/tts.py | 58 +++++++++--------- src/pipecat/services/google/vertex/llm.py | 24 ++++---- src/pipecat/services/gradium/stt.py | 14 ++--- src/pipecat/services/gradium/tts.py | 22 +++---- src/pipecat/services/grok/llm.py | 14 ++--- src/pipecat/services/grok/realtime/llm.py | 20 +++---- src/pipecat/services/groq/llm.py | 14 ++--- src/pipecat/services/groq/stt.py | 25 ++++---- src/pipecat/services/groq/tts.py | 20 +++---- src/pipecat/services/heygen/video.py | 4 +- src/pipecat/services/hume/tts.py | 22 +++---- src/pipecat/services/inworld/tts.py | 40 ++++++------- src/pipecat/services/kokoro/tts.py | 16 ++--- src/pipecat/services/lmnt/tts.py | 16 ++--- src/pipecat/services/minimax/tts.py | 20 +++---- src/pipecat/services/mistral/llm.py | 14 ++--- src/pipecat/services/moondream/vision.py | 10 ++-- src/pipecat/services/neuphonic/tts.py | 32 +++++----- src/pipecat/services/nvidia/llm.py | 14 ++--- src/pipecat/services/nvidia/stt.py | 26 ++++---- src/pipecat/services/nvidia/tts.py | 18 +++--- src/pipecat/services/ollama/llm.py | 14 ++--- src/pipecat/services/openai/base_llm.py | 12 ++-- src/pipecat/services/openai/image.py | 14 ++--- src/pipecat/services/openai/llm.py | 16 ++--- src/pipecat/services/openai/realtime/llm.py | 24 ++++---- src/pipecat/services/openai/stt.py | 47 +++++++-------- src/pipecat/services/openai/tts.py | 28 ++++----- .../services/openai_realtime_beta/azure.py | 6 +- .../services/openai_realtime_beta/openai.py | 10 ++-- src/pipecat/services/openpipe/llm.py | 14 ++--- src/pipecat/services/openrouter/llm.py | 14 ++--- src/pipecat/services/perplexity/llm.py | 14 ++--- src/pipecat/services/piper/tts.py | 22 +++---- src/pipecat/services/qwen/llm.py | 14 ++--- src/pipecat/services/resembleai/tts.py | 10 ++-- src/pipecat/services/rime/tts.py | 60 +++++++++---------- src/pipecat/services/sambanova/llm.py | 14 ++--- src/pipecat/services/sambanova/stt.py | 23 ++++--- src/pipecat/services/sarvam/stt.py | 28 ++++----- src/pipecat/services/sarvam/tts.py | 42 ++++++------- src/pipecat/services/soniox/stt.py | 18 +++--- src/pipecat/services/speechmatics/stt.py | 28 ++++----- src/pipecat/services/speechmatics/tts.py | 16 ++--- src/pipecat/services/tavus/video.py | 4 +- src/pipecat/services/together/llm.py | 14 ++--- src/pipecat/services/ultravox/llm.py | 8 +-- src/pipecat/services/whisper/base_stt.py | 22 +++---- src/pipecat/services/whisper/stt.py | 40 ++++++------- src/pipecat/services/xtts/tts.py | 10 ++-- 87 files changed, 859 insertions(+), 868 deletions(-) diff --git a/src/pipecat/services/anthropic/llm.py b/src/pipecat/services/anthropic/llm.py index 6bf7bf180..0c6d436e1 100644 --- a/src/pipecat/services/anthropic/llm.py +++ b/src/pipecat/services/anthropic/llm.py @@ -160,7 +160,7 @@ class AnthropicLLMService(LLMService): """ Settings = AnthropicLLMSettings - _settings: AnthropicLLMSettings + _settings: Settings # Overriding the default adapter to use the Anthropic one. adapter_class = AnthropicLLMAdapter @@ -172,7 +172,7 @@ class AnthropicLLMService(LLMService): """Input parameters for Anthropic model inference. .. deprecated:: 0.0.105 - Use ``AnthropicLLMSettings`` instead. Pass settings directly via the + Use ``AnthropicLLMService.Settings`` instead. Pass settings directly via the ``settings`` parameter of :class:`AnthropicLLMService`. Parameters: @@ -220,7 +220,7 @@ class AnthropicLLMService(LLMService): api_key: str, model: Optional[str] = None, params: Optional[InputParams] = None, - settings: Optional[AnthropicLLMSettings] = None, + settings: Optional[Settings] = None, client=None, retry_timeout_secs: Optional[float] = 5.0, retry_on_timeout: Optional[bool] = False, @@ -233,12 +233,12 @@ class AnthropicLLMService(LLMService): model: Model name to use. .. deprecated:: 0.0.105 - Use ``settings=AnthropicLLMSettings(model=...)`` instead. + Use ``settings=AnthropicLLMService.Settings(model=...)`` instead. params: Optional model parameters for inference. .. deprecated:: 0.0.105 - Use ``settings=AnthropicLLMSettings(...)`` instead. + Use ``settings=AnthropicLLMService.Settings(...)`` instead. settings: Runtime-updatable settings for this service. When both deprecated parameters and *settings* are provided, *settings* @@ -249,7 +249,7 @@ class AnthropicLLMService(LLMService): **kwargs: Additional arguments passed to parent LLMService. """ # 1. Initialize default_settings with hardcoded defaults - default_settings = AnthropicLLMSettings( + default_settings = self.Settings( model="claude-sonnet-4-6", system_instruction=None, max_tokens=4096, @@ -268,12 +268,12 @@ class AnthropicLLMService(LLMService): # 2. Apply direct init arg overrides (deprecated) if model is not None: - _warn_deprecated_param("model", AnthropicLLMSettings, "model") + _warn_deprecated_param("model", self.Settings, "model") default_settings.model = model # 3. Apply params overrides — only if settings not provided if params is not None: - _warn_deprecated_param("params", AnthropicLLMSettings) + _warn_deprecated_param("params", self.Settings) if not settings: default_settings.max_tokens = params.max_tokens default_settings.temperature = params.temperature diff --git a/src/pipecat/services/assemblyai/models.py b/src/pipecat/services/assemblyai/models.py index efc13d482..cffebcf06 100644 --- a/src/pipecat/services/assemblyai/models.py +++ b/src/pipecat/services/assemblyai/models.py @@ -125,7 +125,7 @@ class AssemblyAIConnectionParams(BaseModel): """Configuration parameters for AssemblyAI WebSocket connection. .. deprecated:: 0.0.105 - Use ``settings=AssemblyAISTTSettings(foo=...)`` instead. + Use ``settings=AssemblyAISTTService.Settings(foo=...)`` instead. Parameters: sample_rate: Audio sample rate in Hz. Defaults to 16000. diff --git a/src/pipecat/services/assemblyai/stt.py b/src/pipecat/services/assemblyai/stt.py index ddfcb4a47..e7a2854b0 100644 --- a/src/pipecat/services/assemblyai/stt.py +++ b/src/pipecat/services/assemblyai/stt.py @@ -129,7 +129,7 @@ class AssemblyAISTTService(WebsocketSTTService): """ Settings = AssemblyAISTTSettings - _settings: AssemblyAISTTSettings + _settings: Settings def __init__( self, @@ -143,7 +143,7 @@ class AssemblyAISTTService(WebsocketSTTService): vad_force_turn_endpoint: bool = True, should_interrupt: bool = True, speaker_format: Optional[str] = None, - settings: Optional[AssemblyAISTTSettings] = None, + settings: Optional[Settings] = None, ttfs_p99_latency: Optional[float] = ASSEMBLYAI_TTFS_P99, **kwargs, ): @@ -154,7 +154,7 @@ class AssemblyAISTTService(WebsocketSTTService): language: Language code for transcription. Defaults to English (Language.EN). .. deprecated:: 0.0.105 - Use ``settings=AssemblyAISTTSettings(language=...)`` instead. + Use ``settings=AssemblyAISTTService.Settings(language=...)`` instead. api_endpoint_base_url: WebSocket endpoint URL. Defaults to AssemblyAI's streaming endpoint. sample_rate: Audio sample rate in Hz. Defaults to 16000. @@ -162,7 +162,7 @@ class AssemblyAISTTService(WebsocketSTTService): connection_params: Connection configuration parameters. .. deprecated:: 0.0.105 - Use ``settings=AssemblyAISTTSettings(...)`` instead. + Use ``settings=AssemblyAISTTService.Settings(...)`` instead. vad_force_turn_endpoint: Controls turn detection mode. When True (Pipecat mode, default): Forces AssemblyAI to return finals ASAP @@ -190,7 +190,7 @@ class AssemblyAISTTService(WebsocketSTTService): **kwargs: Additional arguments passed to parent STTService class. """ # 1. Initialize default_settings with hardcoded defaults - default_settings = AssemblyAISTTSettings( + default_settings = self.Settings( model="u3-rt-pro", language=Language.EN, formatted_finals=True, @@ -208,12 +208,12 @@ class AssemblyAISTTService(WebsocketSTTService): # 2. Apply direct init arg overrides (deprecated) if language is not None: - _warn_deprecated_param("language", AssemblyAISTTSettings, "language") + _warn_deprecated_param("language", self.Settings, "language") default_settings.language = language # 3. Apply connection_params overrides (deprecated) — only if settings not provided if connection_params is not None: - _warn_deprecated_param("connection_params", AssemblyAISTTSettings) + _warn_deprecated_param("connection_params", self.Settings) if not settings: sample_rate = connection_params.sample_rate encoding = connection_params.encoding @@ -299,7 +299,7 @@ class AssemblyAISTTService(WebsocketSTTService): self._user_speaking = False - def _configure_pipecat_turn_mode(self, settings: AssemblyAISTTSettings, is_u3_pro: bool): + def _configure_pipecat_turn_mode(self, settings: Settings, is_u3_pro: bool): """Configure settings for Pipecat turn detection mode. When vad_force_turn_endpoint is enabled, force AssemblyAI to return @@ -353,7 +353,7 @@ class AssemblyAISTTService(WebsocketSTTService): """ return True - async def _update_settings(self, delta: AssemblyAISTTSettings) -> dict[str, Any]: + async def _update_settings(self, delta: Settings) -> dict[str, Any]: """Apply a settings delta and reconnect to apply changes. Args: diff --git a/src/pipecat/services/asyncai/tts.py b/src/pipecat/services/asyncai/tts.py index 67f79dbfd..2cecb2d5b 100644 --- a/src/pipecat/services/asyncai/tts.py +++ b/src/pipecat/services/asyncai/tts.py @@ -86,13 +86,13 @@ class AsyncAITTSService(WebsocketTTSService): """ Settings = AsyncAITTSSettings - _settings: AsyncAITTSSettings + _settings: Settings class InputParams(BaseModel): """Input parameters for Async TTS configuration. .. deprecated:: 0.0.105 - Use ``AsyncAITTSSettings`` directly via the ``settings`` parameter instead. + Use ``AsyncAITTSService.Settings`` directly via the ``settings`` parameter instead. Parameters: language: Language to use for synthesis. @@ -112,7 +112,7 @@ class AsyncAITTSService(WebsocketTTSService): encoding: str = "pcm_s16le", container: str = "raw", params: Optional[InputParams] = None, - settings: Optional[AsyncAITTSSettings] = None, + settings: Optional[Settings] = None, aggregate_sentences: Optional[bool] = None, text_aggregation_mode: Optional[TextAggregationMode] = None, **kwargs, @@ -125,14 +125,14 @@ class AsyncAITTSService(WebsocketTTSService): https://docs.async.com/list-voices-16699698e0 .. deprecated:: 0.0.105 - Use ``settings=AsyncAITTSSettings(voice=...)`` instead. + Use ``settings=AsyncAITTSService.Settings(voice=...)`` instead. version: Async API version. url: WebSocket URL for Async TTS API. model: TTS model to use (e.g., "async_flash_v1.0"). .. deprecated:: 0.0.105 - Use ``settings=AsyncAITTSSettings(model=...)`` instead. + Use ``settings=AsyncAITTSService.Settings(model=...)`` instead. sample_rate: Audio sample rate. encoding: Audio encoding format. @@ -140,7 +140,7 @@ class AsyncAITTSService(WebsocketTTSService): params: Additional input parameters for voice customization. .. deprecated:: 0.0.105 - Use ``settings=AsyncAITTSSettings(...)`` instead. + Use ``settings=AsyncAITTSService.Settings(...)`` instead. settings: Runtime-updatable settings. When provided alongside deprecated parameters, ``settings`` values take precedence. @@ -153,7 +153,7 @@ class AsyncAITTSService(WebsocketTTSService): **kwargs: Additional arguments passed to the parent service. """ # 1. Initialize default_settings with hardcoded defaults - default_settings = AsyncAITTSSettings( + default_settings = self.Settings( model="async_flash_v1.0", voice=None, language=None, @@ -161,15 +161,15 @@ class AsyncAITTSService(WebsocketTTSService): # 2. Apply direct init arg overrides (deprecated) if voice_id is not None: - _warn_deprecated_param("voice_id", AsyncAITTSSettings, "voice") + _warn_deprecated_param("voice_id", self.Settings, "voice") default_settings.voice = voice_id if model is not None: - _warn_deprecated_param("model", AsyncAITTSSettings, "model") + _warn_deprecated_param("model", self.Settings, "model") default_settings.model = model # 3. Apply params overrides — only if settings not provided if params is not None: - _warn_deprecated_param("params", AsyncAITTSSettings) + _warn_deprecated_param("params", self.Settings) if not settings: default_settings.language = ( self.language_to_service_language(params.language) if params.language else None @@ -487,13 +487,13 @@ class AsyncAIHttpTTSService(TTSService): """ Settings = AsyncAITTSSettings - _settings: AsyncAITTSSettings + _settings: Settings class InputParams(BaseModel): """Input parameters for Async API. .. deprecated:: 0.0.105 - Use ``AsyncAITTSSettings`` directly via the ``settings`` parameter instead. + Use ``AsyncAIHttpTTSService.Settings`` directly via the ``settings`` parameter instead. Parameters: language: Language to use for synthesis. @@ -514,7 +514,7 @@ class AsyncAIHttpTTSService(TTSService): encoding: str = "pcm_s16le", container: str = "raw", params: Optional[InputParams] = None, - settings: Optional[AsyncAITTSSettings] = None, + settings: Optional[Settings] = None, **kwargs, ): """Initialize the Async TTS service. @@ -524,13 +524,13 @@ class AsyncAIHttpTTSService(TTSService): voice_id: ID of the voice to use for synthesis. .. deprecated:: 0.0.105 - Use ``settings=AsyncAITTSSettings(voice=...)`` instead. + Use ``settings=AsyncAIHttpTTSService.Settings(voice=...)`` instead. aiohttp_session: An aiohttp session for making HTTP requests. model: TTS model to use (e.g., "async_flash_v1.0"). .. deprecated:: 0.0.105 - Use ``settings=AsyncAITTSSettings(model=...)`` instead. + Use ``settings=AsyncAIHttpTTSService.Settings(model=...)`` instead. url: Base URL for Async API. version: API version string for Async API. @@ -540,14 +540,14 @@ class AsyncAIHttpTTSService(TTSService): params: Additional input parameters for voice customization. .. deprecated:: 0.0.105 - Use ``settings=AsyncAITTSSettings(...)`` instead. + Use ``settings=AsyncAIHttpTTSService.Settings(...)`` instead. settings: Runtime-updatable settings. When provided alongside deprecated parameters, ``settings`` values take precedence. **kwargs: Additional arguments passed to the parent TTSService. """ # 1. Initialize default_settings with hardcoded defaults - default_settings = AsyncAITTSSettings( + default_settings = self.Settings( model="async_flash_v1.0", voice=None, language=None, @@ -555,15 +555,15 @@ class AsyncAIHttpTTSService(TTSService): # 2. Apply direct init arg overrides (deprecated) if voice_id is not None: - _warn_deprecated_param("voice_id", AsyncAITTSSettings, "voice") + _warn_deprecated_param("voice_id", self.Settings, "voice") default_settings.voice = voice_id if model is not None: - _warn_deprecated_param("model", AsyncAITTSSettings, "model") + _warn_deprecated_param("model", self.Settings, "model") default_settings.model = model # 3. Apply params overrides — only if settings not provided if params is not None: - _warn_deprecated_param("params", AsyncAITTSSettings) + _warn_deprecated_param("params", self.Settings) if not settings: default_settings.language = ( self.language_to_service_language(params.language) if params.language else None diff --git a/src/pipecat/services/aws/llm.py b/src/pipecat/services/aws/llm.py index c77321ead..9a2ebfdcf 100644 --- a/src/pipecat/services/aws/llm.py +++ b/src/pipecat/services/aws/llm.py @@ -747,7 +747,7 @@ class AWSBedrockLLMService(LLMService): """ Settings = AWSBedrockLLMSettings - _settings: AWSBedrockLLMSettings + _settings: Settings # Overriding the default adapter to use the Anthropic one. adapter_class = AWSBedrockLLMAdapter @@ -756,7 +756,7 @@ class AWSBedrockLLMService(LLMService): """Input parameters for AWS Bedrock LLM service. .. deprecated:: 0.0.105 - Use ``AWSBedrockLLMSettings`` instead. Pass settings directly via the + Use ``AWSBedrockLLMService.Settings`` instead. Pass settings directly via the ``settings`` parameter of :class:`AWSBedrockLLMService`. Parameters: @@ -784,7 +784,7 @@ class AWSBedrockLLMService(LLMService): aws_session_token: Optional[str] = None, aws_region: Optional[str] = None, params: Optional[InputParams] = None, - settings: Optional[AWSBedrockLLMSettings] = None, + settings: Optional[Settings] = None, stop_sequences: Optional[List[str]] = None, client_config: Optional[Config] = None, retry_timeout_secs: Optional[float] = 5.0, @@ -797,7 +797,7 @@ class AWSBedrockLLMService(LLMService): model: The AWS Bedrock model identifier to use. .. deprecated:: 0.0.105 - Use ``settings=AWSBedrockLLMSettings(model=...)`` instead. + Use ``settings=AWSBedrockLLMService.Settings(model=...)`` instead. aws_access_key: AWS access key ID. If None, uses default credentials. aws_secret_key: AWS secret access key. If None, uses default credentials. @@ -806,7 +806,7 @@ class AWSBedrockLLMService(LLMService): params: Model parameters and configuration. .. deprecated:: 0.0.105 - Use ``settings=AWSBedrockLLMSettings(...)`` instead. + Use ``settings=AWSBedrockLLMService.Settings(...)`` instead. settings: Runtime-updatable settings for this service. When both deprecated parameters and *settings* are provided, *settings* @@ -814,7 +814,7 @@ class AWSBedrockLLMService(LLMService): stop_sequences: List of strings that stop generation. .. deprecated:: 0.0.105 - Use ``settings=AWSBedrockLLMSettings(stop_sequences=...)`` instead. + Use ``settings=AWSBedrockLLMService.Settings(stop_sequences=...)`` instead. client_config: Custom boto3 client configuration. retry_timeout_secs: Request timeout in seconds for retry logic. @@ -822,7 +822,7 @@ class AWSBedrockLLMService(LLMService): **kwargs: Additional arguments passed to parent LLMService. """ # 1. Initialize default_settings with hardcoded defaults - default_settings = AWSBedrockLLMSettings( + default_settings = self.Settings( model="us.amazon.nova-lite-v1:0", system_instruction=None, max_tokens=None, @@ -841,15 +841,15 @@ class AWSBedrockLLMService(LLMService): # 2. Apply direct init arg overrides (deprecated) if model is not None: - _warn_deprecated_param("model", AWSBedrockLLMSettings, "model") + _warn_deprecated_param("model", self.Settings, "model") default_settings.model = model if stop_sequences is not None: - _warn_deprecated_param("stop_sequences", AWSBedrockLLMSettings, "stop_sequences") + _warn_deprecated_param("stop_sequences", self.Settings, "stop_sequences") default_settings.stop_sequences = stop_sequences # 3. Apply params overrides — only if settings not provided if params is not None: - _warn_deprecated_param("params", AWSBedrockLLMSettings) + _warn_deprecated_param("params", self.Settings) if not settings: default_settings.max_tokens = params.max_tokens default_settings.temperature = params.temperature diff --git a/src/pipecat/services/aws/nova_sonic/llm.py b/src/pipecat/services/aws/nova_sonic/llm.py index 8e4633544..0309c0fad 100644 --- a/src/pipecat/services/aws/nova_sonic/llm.py +++ b/src/pipecat/services/aws/nova_sonic/llm.py @@ -150,7 +150,7 @@ class Params(BaseModel): """Configuration parameters for AWS Nova Sonic. .. deprecated:: 0.0.105 - Use ``settings=AWSNovaSonicLLMSettings(...)`` for inference settings + Use ``settings=AWSNovaSonicLLMService.Settings(...)`` for inference settings and ``audio_config=AudioConfig(...)`` for audio configuration. Parameters: @@ -247,7 +247,7 @@ class AWSNovaSonicLLMService(LLMService): """ Settings = AWSNovaSonicLLMSettings - _settings: AWSNovaSonicLLMSettings + _settings: Settings # Override the default adapter to use the AWSNovaSonicLLMAdapter one adapter_class = AWSNovaSonicLLMAdapter @@ -263,7 +263,7 @@ class AWSNovaSonicLLMService(LLMService): voice_id: str = "matthew", params: Optional[Params] = None, audio_config: Optional[AudioConfig] = None, - settings: Optional[AWSNovaSonicLLMSettings] = None, + settings: Optional[Settings] = None, system_instruction: Optional[str] = None, tools: Optional[ToolsSchema] = None, send_transcription_frames: bool = True, @@ -282,7 +282,7 @@ class AWSNovaSonicLLMService(LLMService): model: Model identifier. Defaults to "amazon.nova-2-sonic-v1:0". .. deprecated:: 0.0.105 - Use ``settings=AWSNovaSonicLLMSettings(model=...)`` instead. + Use ``settings=AWSNovaSonicLLMService.Settings(model=...)`` instead. voice_id: Voice ID for speech synthesis. Note that some voices are designed for use with a specific language. @@ -291,12 +291,12 @@ class AWSNovaSonicLLMService(LLMService): - Nova Sonic (the older model): see https://docs.aws.amazon.com/nova/latest/userguide/available-voices.html. .. deprecated:: 0.0.105 - Use ``settings=AWSNovaSonicLLMSettings(voice=...)`` instead. + Use ``settings=AWSNovaSonicLLMService.Settings(voice=...)`` instead. params: Model parameters for audio configuration and inference. .. deprecated:: 0.0.105 - Use ``settings=AWSNovaSonicLLMSettings(...)`` for inference + Use ``settings=AWSNovaSonicLLMService.Settings(...)`` for inference settings and ``audio_config=AudioConfig(...)`` for audio configuration. @@ -308,7 +308,7 @@ class AWSNovaSonicLLMService(LLMService): system_instruction: System-level instruction for the model. .. deprecated:: 0.0.105 - Use ``settings=AWSNovaSonicLLMSettings(system_instruction=...)`` instead. + Use ``settings=AWSNovaSonicLLMService.Settings(system_instruction=...)`` instead. tools: Available tools/functions for the model to use. send_transcription_frames: Whether to emit transcription frames. @@ -319,7 +319,7 @@ class AWSNovaSonicLLMService(LLMService): **kwargs: Additional arguments passed to the parent LLMService. """ # 1. Initialize default_settings with hardcoded defaults - default_settings = AWSNovaSonicLLMSettings( + default_settings = self.Settings( model="amazon.nova-2-sonic-v1:0", system_instruction=None, voice="matthew", @@ -337,15 +337,13 @@ class AWSNovaSonicLLMService(LLMService): # 2. Apply direct init arg overrides (deprecated) if model != "amazon.nova-2-sonic-v1:0": - _warn_deprecated_param("model", AWSNovaSonicLLMSettings, "model") + _warn_deprecated_param("model", self.Settings, "model") default_settings.model = model if voice_id != "matthew": - _warn_deprecated_param("voice_id", AWSNovaSonicLLMSettings, "voice") + _warn_deprecated_param("voice_id", self.Settings, "voice") default_settings.voice = voice_id if system_instruction is not None: - _warn_deprecated_param( - "system_instruction", AWSNovaSonicLLMSettings, "system_instruction" - ) + _warn_deprecated_param("system_instruction", self.Settings, "system_instruction") default_settings.system_instruction = system_instruction # 3. Apply params overrides — only if settings not provided @@ -356,7 +354,7 @@ class AWSNovaSonicLLMService(LLMService): warnings.simplefilter("always") warnings.warn( "The `params` parameter is deprecated. " - "Use `settings=AWSNovaSonicLLMSettings(...)` for inference settings " + "Use `settings=self.Settings(...)` for inference settings " "(temperature, max_tokens, top_p, endpointing_sensitivity) " "and `audio_config=AudioConfig(...)` for audio configuration " "(sample rates, sample sizes, channel counts).", @@ -447,7 +445,7 @@ class AWSNovaSonicLLMService(LLMService): # settings # - async def _update_settings(self, delta: AWSNovaSonicLLMSettings) -> dict[str, Any]: + async def _update_settings(self, delta: Settings) -> dict[str, Any]: """Apply a settings delta. Settings are stored but not applied to the active connection. diff --git a/src/pipecat/services/aws/stt.py b/src/pipecat/services/aws/stt.py index 8b28c006a..0a648759c 100644 --- a/src/pipecat/services/aws/stt.py +++ b/src/pipecat/services/aws/stt.py @@ -61,7 +61,7 @@ class AWSTranscribeSTTService(WebsocketSTTService): """ Settings = AWSTranscribeSTTSettings - _settings: AWSTranscribeSTTSettings + _settings: Settings def __init__( self, @@ -72,7 +72,7 @@ class AWSTranscribeSTTService(WebsocketSTTService): region: Optional[str] = None, sample_rate: Optional[int] = None, language: Optional[Language] = None, - settings: Optional[AWSTranscribeSTTSettings] = None, + settings: Optional[Settings] = None, ttfs_p99_latency: Optional[float] = AWS_TRANSCRIBE_TTFS_P99, **kwargs, ): @@ -89,7 +89,7 @@ class AWSTranscribeSTTService(WebsocketSTTService): language: Language for transcription. .. deprecated:: 0.0.105 - Use ``settings=AWSTranscribeSTTSettings(language=...)`` instead. + Use ``settings=AWSTranscribeSTTService.Settings(language=...)`` instead. settings: Runtime-updatable settings. When provided alongside deprecated parameters, ``settings`` values take precedence. @@ -98,14 +98,14 @@ class AWSTranscribeSTTService(WebsocketSTTService): **kwargs: Additional arguments passed to parent STTService class. """ # 1. Initialize default_settings with hardcoded defaults - default_settings = AWSTranscribeSTTSettings( + default_settings = self.Settings( model=None, language=self.language_to_service_language(Language.EN), ) # 2. Apply direct init arg overrides (deprecated) if language is not None: - _warn_deprecated_param("language", AWSTranscribeSTTSettings, "language") + _warn_deprecated_param("language", self.Settings, "language") default_settings.language = self.language_to_service_language(language) # 3. (No step 3, as there's no params object to apply) diff --git a/src/pipecat/services/aws/tts.py b/src/pipecat/services/aws/tts.py index 47b12429a..1e16958fe 100644 --- a/src/pipecat/services/aws/tts.py +++ b/src/pipecat/services/aws/tts.py @@ -149,13 +149,13 @@ class AWSPollyTTSService(TTSService): """ Settings = AWSPollyTTSSettings - _settings: AWSPollyTTSSettings + _settings: Settings class InputParams(BaseModel): """Input parameters for AWS Polly TTS configuration. .. deprecated:: 0.0.105 - Use ``AWSPollyTTSSettings`` directly via the ``settings`` parameter instead. + Use ``AWSPollyTTSService.Settings`` directly via the ``settings`` parameter instead. Parameters: engine: TTS engine to use ('standard', 'neural', etc.). @@ -183,7 +183,7 @@ class AWSPollyTTSService(TTSService): voice_id: Optional[str] = None, sample_rate: Optional[int] = None, params: Optional[InputParams] = None, - settings: Optional[AWSPollyTTSSettings] = None, + settings: Optional[Settings] = None, **kwargs, ): """Initializes the AWS Polly TTS service. @@ -196,20 +196,20 @@ class AWSPollyTTSService(TTSService): voice_id: Voice ID to use for synthesis. Defaults to 'Joanna'. .. deprecated:: 0.0.105 - Use ``settings=AWSPollyTTSSettings(voice=...)`` instead. + Use ``settings=AWSPollyTTSService.Settings(voice=...)`` instead. sample_rate: Audio sample rate. If None, uses service default. params: Additional input parameters for voice customization. .. deprecated:: 0.0.105 - Use ``settings=AWSPollyTTSSettings(...)`` instead. + Use ``settings=AWSPollyTTSService.Settings(...)`` instead. settings: Runtime-updatable settings. When provided alongside deprecated parameters, ``settings`` values take precedence. **kwargs: Additional arguments passed to parent TTSService class. """ # 1. Initialize default_settings with hardcoded defaults - default_settings = AWSPollyTTSSettings( + default_settings = self.Settings( model=None, voice="Joanna", language="en-US", @@ -222,12 +222,12 @@ class AWSPollyTTSService(TTSService): # 2. Apply direct init arg overrides (deprecated) if voice_id is not None: - _warn_deprecated_param("voice_id", AWSPollyTTSSettings, "voice") + _warn_deprecated_param("voice_id", self.Settings, "voice") default_settings.voice = voice_id # 3. Apply params overrides — only if settings not provided if params is not None: - _warn_deprecated_param("params", AWSPollyTTSSettings) + _warn_deprecated_param("params", self.Settings) if not settings: default_settings.engine = params.engine default_settings.language = ( diff --git a/src/pipecat/services/azure/image.py b/src/pipecat/services/azure/image.py index 1b62fbfe4..a80496599 100644 --- a/src/pipecat/services/azure/image.py +++ b/src/pipecat/services/azure/image.py @@ -44,7 +44,7 @@ class AzureImageGenServiceREST(ImageGenService): """ Settings = AzureImageGenSettings - _settings: AzureImageGenSettings + _settings: Settings def __init__( self, @@ -55,7 +55,7 @@ class AzureImageGenServiceREST(ImageGenService): model: Optional[str] = None, aiohttp_session: aiohttp.ClientSession, api_version="2023-06-01-preview", - settings: Optional[AzureImageGenSettings] = None, + settings: Optional[Settings] = None, ): """Initialize the AzureImageGenServiceREST. @@ -63,14 +63,14 @@ class AzureImageGenServiceREST(ImageGenService): image_size: Size specification for generated images (e.g., "1024x1024"). .. deprecated:: 0.0.105 - Use ``settings=AzureImageGenSettings(image_size=...)`` instead. + Use ``settings=AzureImageGenServiceREST.Settings(image_size=...)`` instead. api_key: Azure OpenAI API key for authentication. endpoint: Azure OpenAI endpoint URL. model: The image generation model to use. .. deprecated:: 0.0.105 - Use ``settings=AzureImageGenSettings(model=...)`` instead. + Use ``settings=AzureImageGenServiceREST.Settings(model=...)`` instead. aiohttp_session: Shared aiohttp session for HTTP requests. api_version: Azure API version string. Defaults to "2023-06-01-preview". @@ -78,18 +78,18 @@ class AzureImageGenServiceREST(ImageGenService): parameters, ``settings`` values take precedence. """ # 1. Initialize default_settings with hardcoded defaults - default_settings = AzureImageGenSettings( + default_settings = self.Settings( model=None, image_size=None, ) # 2. Apply direct init arg overrides (deprecated) if model is not None: - _warn_deprecated_param("model", AzureImageGenSettings, "model") + _warn_deprecated_param("model", self.Settings, "model") default_settings.model = model if image_size is not None: - _warn_deprecated_param("image_size", AzureImageGenSettings, "image_size") + _warn_deprecated_param("image_size", self.Settings, "image_size") default_settings.image_size = image_size # 4. Apply settings delta (canonical API, always wins) diff --git a/src/pipecat/services/azure/llm.py b/src/pipecat/services/azure/llm.py index 322ff0b3e..b4f2de5dc 100644 --- a/src/pipecat/services/azure/llm.py +++ b/src/pipecat/services/azure/llm.py @@ -12,13 +12,13 @@ from typing import Optional from loguru import logger from openai import AsyncAzureOpenAI -from pipecat.services.openai.base_llm import OpenAILLMSettings +from pipecat.services.openai.base_llm import BaseOpenAILLMService from pipecat.services.openai.llm import OpenAILLMService from pipecat.services.settings import _warn_deprecated_param @dataclass -class AzureLLMSettings(OpenAILLMSettings): +class AzureLLMSettings(BaseOpenAILLMService.Settings): """Settings for AzureLLMService.""" pass @@ -40,7 +40,7 @@ class AzureLLMService(OpenAILLMService): endpoint: str, model: Optional[str] = None, api_version: str = "2024-09-01-preview", - settings: Optional[AzureLLMSettings] = None, + settings: Optional[Settings] = None, **kwargs, ): """Initialize the Azure LLM service. @@ -51,7 +51,7 @@ class AzureLLMService(OpenAILLMService): model: The model identifier to use. Defaults to "gpt-4o". .. deprecated:: 0.0.105 - Use ``settings=OpenAILLMSettings(model=...)`` instead. + Use ``settings=AzureLLMService.Settings(model=...)`` instead. api_version: Azure API version. Defaults to "2024-09-01-preview". settings: Runtime-updatable settings. When provided alongside deprecated @@ -59,11 +59,11 @@ class AzureLLMService(OpenAILLMService): **kwargs: Additional keyword arguments passed to OpenAILLMService. """ # 1. Initialize default_settings with hardcoded defaults - default_settings = AzureLLMSettings(model="gpt-4o") + default_settings = self.Settings(model="gpt-4o") # 2. Apply direct init arg overrides (deprecated) if model is not None: - _warn_deprecated_param("model", AzureLLMSettings, "model") + _warn_deprecated_param("model", self.Settings, "model") default_settings.model = model # 3. (No step 3, as there's no params object to apply) diff --git a/src/pipecat/services/azure/realtime/llm.py b/src/pipecat/services/azure/realtime/llm.py index c791af94d..e6bc05478 100644 --- a/src/pipecat/services/azure/realtime/llm.py +++ b/src/pipecat/services/azure/realtime/llm.py @@ -10,7 +10,7 @@ from dataclasses import dataclass from loguru import logger -from pipecat.services.openai.realtime.llm import OpenAIRealtimeLLMService, OpenAIRealtimeLLMSettings +from pipecat.services.openai.realtime.llm import OpenAIRealtimeLLMService try: from websockets.asyncio.client import connect as websocket_connect @@ -21,7 +21,7 @@ except ModuleNotFoundError as e: @dataclass -class AzureRealtimeLLMSettings(OpenAIRealtimeLLMSettings): +class AzureRealtimeLLMSettings(OpenAIRealtimeLLMService.Settings): """Settings for AzureRealtimeLLMService.""" pass @@ -36,7 +36,7 @@ class AzureRealtimeLLMService(OpenAIRealtimeLLMService): """ Settings = AzureRealtimeLLMSettings - _settings: AzureRealtimeLLMSettings + _settings: Settings def __init__( self, diff --git a/src/pipecat/services/azure/stt.py b/src/pipecat/services/azure/stt.py index 6abe52db1..7309a4a4e 100644 --- a/src/pipecat/services/azure/stt.py +++ b/src/pipecat/services/azure/stt.py @@ -67,7 +67,7 @@ class AzureSTTService(STTService): """ Settings = AzureSTTSettings - _settings: AzureSTTSettings + _settings: Settings def __init__( self, @@ -78,7 +78,7 @@ class AzureSTTService(STTService): sample_rate: Optional[int] = None, private_endpoint: Optional[str] = None, endpoint_id: Optional[str] = None, - settings: Optional[AzureSTTSettings] = None, + settings: Optional[Settings] = None, ttfs_p99_latency: Optional[float] = AZURE_TTFS_P99, **kwargs, ): @@ -91,7 +91,7 @@ class AzureSTTService(STTService): language: Language for speech recognition. Defaults to English (US). .. deprecated:: 0.0.105 - Use ``settings=AzureSTTSettings(language=...)`` instead. + Use ``settings=AzureSTTService.Settings(language=...)`` instead. sample_rate: Audio sample rate in Hz. If None, uses service default. private_endpoint: Private endpoint for STT behind firewall. @@ -104,14 +104,14 @@ class AzureSTTService(STTService): **kwargs: Additional arguments passed to parent STTService. """ # 1. Initialize default_settings with hardcoded defaults - default_settings = AzureSTTSettings( + default_settings = self.Settings( model=None, language=language_to_azure_language(Language.EN_US), ) # 2. Apply direct init arg overrides (deprecated) if language is not None and language != Language.EN_US: - _warn_deprecated_param("language", AzureSTTSettings, "language") + _warn_deprecated_param("language", self.Settings, "language") default_settings.language = language_to_azure_language(language) # 3. (No step 3, as there's no params object to apply) diff --git a/src/pipecat/services/azure/tts.py b/src/pipecat/services/azure/tts.py index 1c74c7655..d33937d52 100644 --- a/src/pipecat/services/azure/tts.py +++ b/src/pipecat/services/azure/tts.py @@ -97,7 +97,8 @@ class AzureBaseTTSService: This is a mixin class and should be used alongside TTSService or its subclasses. """ - _settings: AzureTTSSettings + Settings = AzureTTSSettings + _settings: Settings # Define SSML escape mappings based on SSML reserved characters # See - https://learn.microsoft.com/en-us/azure/ai-services/speech-service/speech-synthesis-markup-structure @@ -113,7 +114,7 @@ class AzureBaseTTSService: """Input parameters for Azure TTS voice configuration. .. deprecated:: 0.0.105 - Use ``settings=AzureTTSSettings(...)`` instead. + Use ``settings=AzureBaseTTSService.Settings(...)`` instead. Parameters: emphasis: Emphasis level for speech ("strong", "moderate", "reduced"). @@ -256,7 +257,7 @@ class AzureTTSService(TTSService, AzureBaseTTSService): voice: Optional[str] = None, sample_rate: Optional[int] = None, params: Optional[AzureBaseTTSService.InputParams] = None, - settings: Optional[AzureTTSSettings] = None, + settings: Optional[Settings] = None, aggregate_sentences: Optional[bool] = None, text_aggregation_mode: Optional[TextAggregationMode] = None, **kwargs, @@ -269,13 +270,13 @@ class AzureTTSService(TTSService, AzureBaseTTSService): voice: Voice name to use for synthesis. .. deprecated:: 0.0.105 - Use ``settings=AzureTTSSettings(voice=...)`` instead. + Use ``settings=AzureTTSService.Settings(voice=...)`` instead. sample_rate: Audio sample rate in Hz. If None, uses service default. params: Voice and synthesis parameters configuration. .. deprecated:: 0.0.105 - Use ``settings=AzureTTSSettings(...)`` instead. + Use ``settings=AzureTTSService.Settings(...)`` instead. settings: Runtime-updatable settings. When provided alongside deprecated parameters, ``settings`` values take precedence. @@ -288,7 +289,7 @@ class AzureTTSService(TTSService, AzureBaseTTSService): **kwargs: Additional arguments passed to parent WordTTSService. """ # 1. Initialize default_settings with hardcoded defaults - default_settings = AzureTTSSettings( + default_settings = self.Settings( model=None, voice="en-US-SaraNeural", language="en-US", @@ -303,12 +304,12 @@ class AzureTTSService(TTSService, AzureBaseTTSService): # 2. Apply direct init arg overrides (deprecated) if voice is not None: - _warn_deprecated_param("voice", AzureTTSSettings, "voice") + _warn_deprecated_param("voice", self.Settings, "voice") default_settings.voice = voice # 3. Apply params overrides — only if settings not provided if params is not None: - _warn_deprecated_param("params", AzureTTSSettings) + _warn_deprecated_param("params", self.Settings) if not settings: default_settings.emphasis = params.emphasis default_settings.language = ( @@ -761,7 +762,7 @@ class AzureHttpTTSService(TTSService, AzureBaseTTSService): voice: Optional[str] = None, sample_rate: Optional[int] = None, params: Optional[AzureBaseTTSService.InputParams] = None, - settings: Optional[AzureTTSSettings] = None, + settings: Optional[Settings] = None, **kwargs, ): """Initialize the Azure HTTP TTS service. @@ -772,20 +773,20 @@ class AzureHttpTTSService(TTSService, AzureBaseTTSService): voice: Voice name to use for synthesis. .. deprecated:: 0.0.105 - Use ``settings=AzureTTSSettings(voice=...)`` instead. + Use ``settings=AzureHttpTTSService.Settings(voice=...)`` instead. sample_rate: Audio sample rate in Hz. If None, uses service default. params: Voice and synthesis parameters configuration. .. deprecated:: 0.0.105 - Use ``settings=AzureTTSSettings(...)`` instead. + Use ``settings=AzureHttpTTSService.Settings(...)`` instead. settings: Runtime-updatable settings. When provided alongside deprecated parameters, ``settings`` values take precedence. **kwargs: Additional arguments passed to parent TTSService. """ # 1. Initialize default_settings with hardcoded defaults - default_settings = AzureTTSSettings( + default_settings = self.Settings( model=None, voice="en-US-SaraNeural", language="en-US", @@ -800,12 +801,12 @@ class AzureHttpTTSService(TTSService, AzureBaseTTSService): # 2. Apply direct init arg overrides (deprecated) if voice is not None: - _warn_deprecated_param("voice", AzureTTSSettings, "voice") + _warn_deprecated_param("voice", self.Settings, "voice") default_settings.voice = voice # 3. Apply params overrides — only if settings not provided if params is not None: - _warn_deprecated_param("params", AzureTTSSettings) + _warn_deprecated_param("params", self.Settings) if not settings: default_settings.emphasis = params.emphasis default_settings.language = ( diff --git a/src/pipecat/services/camb/tts.py b/src/pipecat/services/camb/tts.py index f458fa2e4..7586644ce 100644 --- a/src/pipecat/services/camb/tts.py +++ b/src/pipecat/services/camb/tts.py @@ -176,13 +176,13 @@ class CambTTSService(TTSService): """ Settings = CambTTSSettings - _settings: CambTTSSettings + _settings: Settings class InputParams(BaseModel): """Input parameters for Camb.ai TTS configuration. .. deprecated:: 0.0.105 - Use ``settings=CambTTSSettings(...)`` instead. + Use ``settings=CambTTSService.Settings(...)`` instead. Parameters: language: Language for synthesis (BCP-47 format). Defaults to English. @@ -207,7 +207,7 @@ class CambTTSService(TTSService): timeout: float = 60.0, sample_rate: Optional[int] = None, params: Optional[InputParams] = None, - settings: Optional[CambTTSSettings] = None, + settings: Optional[Settings] = None, **kwargs, ): """Initialize the Camb.ai TTS service. @@ -217,12 +217,12 @@ class CambTTSService(TTSService): voice_id: Voice ID to use. .. deprecated:: 0.0.105 - Use ``settings=CambTTSSettings(voice=...)`` instead. + Use ``settings=CambTTSService.Settings(voice=...)`` instead. model: TTS model to use. Options: "mars-flash" (fast), "mars-pro" (high quality). .. deprecated:: 0.0.105 - Use ``settings=CambTTSSettings(model=...)`` instead. + Use ``settings=CambTTSService.Settings(model=...)`` instead. timeout: Request timeout in seconds. Defaults to 60.0 (minimum recommended by Camb.ai). @@ -230,14 +230,14 @@ class CambTTSService(TTSService): params: Additional voice parameters. If None, uses defaults. .. deprecated:: 0.0.105 - Use ``settings=CambTTSSettings(...)`` instead. + Use ``settings=CambTTSService.Settings(...)`` instead. settings: Runtime-updatable settings. When provided alongside deprecated parameters, ``settings`` values take precedence. **kwargs: Additional arguments passed to parent TTSService. """ # 1. Initialize default_settings with hardcoded defaults - default_settings = CambTTSSettings( + default_settings = self.Settings( model="mars-flash", voice=147320, language="en-us", @@ -246,15 +246,15 @@ class CambTTSService(TTSService): # 2. Apply direct init arg overrides (deprecated) if model is not None: - _warn_deprecated_param("model", CambTTSSettings, "model") + _warn_deprecated_param("model", self.Settings, "model") default_settings.model = model if voice_id is not None: - _warn_deprecated_param("voice_id", CambTTSSettings, "voice") + _warn_deprecated_param("voice_id", self.Settings, "voice") default_settings.voice = voice_id # 3. Apply params overrides — only if settings not provided if params is not None: - _warn_deprecated_param("params", CambTTSSettings) + _warn_deprecated_param("params", self.Settings) if not settings: if params.language is not None: default_settings.language = ( diff --git a/src/pipecat/services/cartesia/stt.py b/src/pipecat/services/cartesia/stt.py index 9c0924827..e094ef044 100644 --- a/src/pipecat/services/cartesia/stt.py +++ b/src/pipecat/services/cartesia/stt.py @@ -55,7 +55,7 @@ class CartesiaLiveOptions: """Configuration options for Cartesia Live STT service. .. deprecated:: 0.0.105 - Use ``settings=CartesiaSTTSettings(...)`` for model/language and + Use ``settings=CartesiaSTTService.Settings(...)`` for model/language and direct ``__init__`` parameters for encoding/sample_rate instead. """ @@ -147,7 +147,7 @@ class CartesiaSTTService(WebsocketSTTService): """ Settings = CartesiaSTTSettings - _settings: CartesiaSTTSettings + _settings: Settings def __init__( self, @@ -157,7 +157,7 @@ class CartesiaSTTService(WebsocketSTTService): encoding: str = "pcm_s16le", sample_rate: Optional[int] = None, live_options: Optional[CartesiaLiveOptions] = None, - settings: Optional[CartesiaSTTSettings] = None, + settings: Optional[Settings] = None, ttfs_p99_latency: Optional[float] = CARTESIA_TTFS_P99, **kwargs, ): @@ -172,7 +172,7 @@ class CartesiaSTTService(WebsocketSTTService): live_options: Configuration options for transcription service. .. deprecated:: 0.0.105 - Use ``settings=CartesiaSTTSettings(...)`` for model/language + Use ``settings=CartesiaSTTService.Settings(...)`` for model/language and direct init parameters for encoding/sample_rate instead. settings: Runtime-updatable settings. When provided alongside deprecated @@ -182,14 +182,14 @@ class CartesiaSTTService(WebsocketSTTService): **kwargs: Additional arguments passed to parent STTService. """ # 1. Initialize default_settings with hardcoded defaults - default_settings = CartesiaSTTSettings( + default_settings = self.Settings( model="ink-whisper", language=Language.EN.value, ) # 2. Apply live_options overrides — only if settings not provided if live_options is not None: - _warn_deprecated_param("live_options", CartesiaSTTSettings) + _warn_deprecated_param("live_options", self.Settings) if not settings: if live_options.sample_rate and sample_rate is None: sample_rate = live_options.sample_rate @@ -313,7 +313,7 @@ class CartesiaSTTService(WebsocketSTTService): """Apply a settings delta. Args: - delta: A :class:`STTSettings` (or ``CartesiaSTTSettings``) delta. + delta: A :class:`STTSettings` (or ``CartesiaSTTService.Settings``) delta. Returns: Dict mapping changed field names to their previous values. diff --git a/src/pipecat/services/cartesia/tts.py b/src/pipecat/services/cartesia/tts.py index d41f341ca..90497eb1d 100644 --- a/src/pipecat/services/cartesia/tts.py +++ b/src/pipecat/services/cartesia/tts.py @@ -211,7 +211,7 @@ class CartesiaTTSService(WebsocketTTSService): """ Settings = CartesiaTTSSettings - _settings: CartesiaTTSSettings + _settings: Settings class InputParams(BaseModel): """Input parameters for Cartesia TTS configuration. @@ -239,7 +239,7 @@ class CartesiaTTSService(WebsocketTTSService): encoding: str = "pcm_s16le", container: str = "raw", params: Optional[InputParams] = None, - settings: Optional[CartesiaTTSSettings] = None, + settings: Optional[Settings] = None, text_aggregator: Optional[BaseTextAggregator] = None, text_aggregation_mode: Optional[TextAggregationMode] = None, aggregate_sentences: Optional[bool] = None, @@ -252,14 +252,14 @@ class CartesiaTTSService(WebsocketTTSService): voice_id: ID of the voice to use for synthesis. .. deprecated:: 0.0.105 - Use ``settings=CartesiaTTSSettings(voice=...)`` instead. + Use ``settings=CartesiaTTSService.Settings(voice=...)`` instead. cartesia_version: API version string for Cartesia service. url: WebSocket URL for Cartesia TTS API. model: TTS model to use (e.g., "sonic-3"). .. deprecated:: 0.0.105 - Use ``settings=CartesiaTTSSettings(model=...)`` instead. + Use ``settings=CartesiaTTSService.Settings(model=...)`` instead. sample_rate: Audio sample rate. If None, uses default. encoding: Audio encoding format. @@ -267,7 +267,7 @@ class CartesiaTTSService(WebsocketTTSService): params: Additional input parameters for voice customization. .. deprecated:: 0.0.105 - Use ``settings=CartesiaTTSSettings(...)`` instead. + Use ``settings=CartesiaTTSService.Settings(...)`` instead. settings: Runtime-updatable settings. When provided alongside deprecated parameters, ``settings`` values take precedence. @@ -299,7 +299,7 @@ class CartesiaTTSService(WebsocketTTSService): # playout timing of the audio! # 1. Initialize default_settings with hardcoded defaults - default_settings = CartesiaTTSSettings( + default_settings = self.Settings( model="sonic-3", voice=None, language=language_to_cartesia_language(Language.EN), @@ -309,15 +309,15 @@ class CartesiaTTSService(WebsocketTTSService): # 2. Apply direct init arg overrides (deprecated) if voice_id is not None: - _warn_deprecated_param("voice_id", CartesiaTTSSettings, "voice") + _warn_deprecated_param("voice_id", self.Settings, "voice") default_settings.voice = voice_id if model is not None: - _warn_deprecated_param("model", CartesiaTTSSettings, "model") + _warn_deprecated_param("model", self.Settings, "model") default_settings.model = model # 3. Apply params overrides — only if settings not provided if params is not None: - _warn_deprecated_param("params", CartesiaTTSSettings) + _warn_deprecated_param("params", self.Settings) if not settings: if params.language is not None: default_settings.language = self.language_to_service_language(params.language) @@ -683,7 +683,7 @@ class CartesiaHttpTTSService(TTSService): """ Settings = CartesiaTTSSettings - _settings: CartesiaTTSSettings + _settings: Settings class InputParams(BaseModel): """Input parameters for Cartesia HTTP TTS configuration. @@ -712,7 +712,7 @@ class CartesiaHttpTTSService(TTSService): encoding: str = "pcm_s16le", container: str = "raw", params: Optional[InputParams] = None, - settings: Optional[CartesiaTTSSettings] = None, + settings: Optional[Settings] = None, **kwargs, ): """Initialize the Cartesia HTTP TTS service. @@ -722,12 +722,12 @@ class CartesiaHttpTTSService(TTSService): voice_id: ID of the voice to use for synthesis. .. deprecated:: 0.0.105 - Use ``settings=CartesiaTTSSettings(voice=...)`` instead. + Use ``settings=CartesiaHttpTTSService.Settings(voice=...)`` instead. model: TTS model to use (e.g., "sonic-3"). .. deprecated:: 0.0.105 - Use ``settings=CartesiaTTSSettings(model=...)`` instead. + Use ``settings=CartesiaHttpTTSService.Settings(model=...)`` instead. base_url: Base URL for Cartesia HTTP API. cartesia_version: API version string for Cartesia service. @@ -739,14 +739,14 @@ class CartesiaHttpTTSService(TTSService): params: Additional input parameters for voice customization. .. deprecated:: 0.0.105 - Use ``settings=CartesiaTTSSettings(...)`` instead. + Use ``settings=CartesiaHttpTTSService.Settings(...)`` instead. settings: Runtime-updatable settings. When provided alongside deprecated parameters, ``settings`` values take precedence. **kwargs: Additional arguments passed to the parent TTSService. """ # 1. Initialize default_settings with hardcoded defaults - default_settings = CartesiaTTSSettings( + default_settings = self.Settings( model="sonic-3", voice=None, language=language_to_cartesia_language(Language.EN), @@ -756,15 +756,15 @@ class CartesiaHttpTTSService(TTSService): # 2. Apply direct init arg overrides (deprecated) if voice_id is not None: - _warn_deprecated_param("voice_id", CartesiaTTSSettings, "voice") + _warn_deprecated_param("voice_id", self.Settings, "voice") default_settings.voice = voice_id if model is not None: - _warn_deprecated_param("model", CartesiaTTSSettings, "model") + _warn_deprecated_param("model", self.Settings, "model") default_settings.model = model # 3. Apply params overrides — only if settings not provided if params is not None: - _warn_deprecated_param("params", CartesiaTTSSettings) + _warn_deprecated_param("params", self.Settings) if not settings: if params.language is not None: default_settings.language = self.language_to_service_language(params.language) diff --git a/src/pipecat/services/cerebras/llm.py b/src/pipecat/services/cerebras/llm.py index 5d4bc2d14..e2a15f4e5 100644 --- a/src/pipecat/services/cerebras/llm.py +++ b/src/pipecat/services/cerebras/llm.py @@ -12,13 +12,13 @@ from typing import Optional from loguru import logger from pipecat.adapters.services.open_ai_adapter import OpenAILLMInvocationParams -from pipecat.services.openai.base_llm import OpenAILLMSettings +from pipecat.services.openai.base_llm import BaseOpenAILLMService from pipecat.services.openai.llm import OpenAILLMService from pipecat.services.settings import _warn_deprecated_param @dataclass -class CerebrasLLMSettings(OpenAILLMSettings): +class CerebrasLLMSettings(BaseOpenAILLMService.Settings): """Settings for CerebrasLLMService.""" pass @@ -32,7 +32,7 @@ class CerebrasLLMService(OpenAILLMService): """ Settings = CerebrasLLMSettings - _settings: CerebrasLLMSettings + _settings: Settings def __init__( self, @@ -40,7 +40,7 @@ class CerebrasLLMService(OpenAILLMService): api_key: str, base_url: str = "https://api.cerebras.ai/v1", model: Optional[str] = None, - settings: Optional[CerebrasLLMSettings] = None, + settings: Optional[Settings] = None, **kwargs, ): """Initialize the Cerebras LLM service. @@ -51,18 +51,18 @@ class CerebrasLLMService(OpenAILLMService): model: The model identifier to use. Defaults to "gpt-oss-120b". .. deprecated:: 0.0.105 - Use ``settings=OpenAILLMSettings(model=...)`` instead. + Use ``settings=CerebrasLLMService.Settings(model=...)`` instead. settings: Runtime-updatable settings. When provided alongside deprecated parameters, ``settings`` values take precedence. **kwargs: Additional keyword arguments passed to OpenAILLMService. """ # 1. Initialize default_settings with hardcoded defaults - default_settings = CerebrasLLMSettings(model="gpt-oss-120b") + default_settings = self.Settings(model="gpt-oss-120b") # 2. Apply direct init arg overrides (deprecated) if model is not None: - _warn_deprecated_param("model", CerebrasLLMSettings, "model") + _warn_deprecated_param("model", self.Settings, "model") default_settings.model = model # 3. (No step 3, as there's no params object to apply) diff --git a/src/pipecat/services/deepgram/flux/stt.py b/src/pipecat/services/deepgram/flux/stt.py index 3227bd0a6..085d1ed2c 100644 --- a/src/pipecat/services/deepgram/flux/stt.py +++ b/src/pipecat/services/deepgram/flux/stt.py @@ -116,14 +116,14 @@ class DeepgramFluxSTTService(WebsocketSTTService): """ Settings = DeepgramFluxSTTSettings - _settings: DeepgramFluxSTTSettings + _settings: Settings _CONFIGURE_FIELDS = {"keyterm", "eot_threshold", "eager_eot_threshold", "eot_timeout_ms"} class InputParams(BaseModel): """Configuration parameters for Deepgram Flux API. .. deprecated:: 0.0.105 - Use ``settings=DeepgramFluxSTTSettings(...)`` instead. + Use ``settings=DeepgramFluxSTTService.Settings(...)`` instead. Parameters: eager_eot_threshold: Optional. EagerEndOfTurn/TurnResumed are off by default. @@ -162,7 +162,7 @@ class DeepgramFluxSTTService(WebsocketSTTService): tag: Optional[list] = None, params: Optional[InputParams] = None, should_interrupt: bool = True, - settings: Optional[DeepgramFluxSTTSettings] = None, + settings: Optional[Settings] = None, **kwargs, ): """Initialize the Deepgram Flux STT service. @@ -176,7 +176,7 @@ class DeepgramFluxSTTService(WebsocketSTTService): model: Deepgram Flux model to use for transcription. .. deprecated:: 0.0.105 - Use ``settings=DeepgramFluxSTTSettings(model=...)`` instead. + Use ``settings=DeepgramFluxSTTService.Settings(model=...)`` instead. flux_encoding: Audio encoding format required by Flux API. Must be "linear16". Raw signed little-endian 16-bit PCM encoding. @@ -184,7 +184,7 @@ class DeepgramFluxSTTService(WebsocketSTTService): params: InputParams instance containing detailed API configuration options. .. deprecated:: 0.0.105 - Use ``settings=DeepgramFluxSTTSettings(...)`` instead. + Use ``settings=DeepgramFluxSTTService.Settings(...)`` instead. should_interrupt: Determine whether the bot should be interrupted when Flux detects that the user is speaking. settings: Runtime-updatable settings. When provided alongside deprecated @@ -200,7 +200,7 @@ class DeepgramFluxSTTService(WebsocketSTTService): stt = DeepgramFluxSTTService( api_key="your-api-key", - settings=DeepgramFluxSTTSettings( + settings=DeepgramFluxSTTService.Settings( model="flux-general-en", eager_eot_threshold=0.5, eot_threshold=0.8, @@ -221,7 +221,7 @@ class DeepgramFluxSTTService(WebsocketSTTService): # already try to reconnect if needed. # 1. Initialize default_settings with hardcoded defaults - default_settings = DeepgramFluxSTTSettings( + default_settings = self.Settings( model="flux-general-en", language=Language.EN, eager_eot_threshold=None, @@ -233,12 +233,12 @@ class DeepgramFluxSTTService(WebsocketSTTService): # 2. Apply direct init arg overrides (deprecated) if model is not None: - _warn_deprecated_param("model", DeepgramFluxSTTSettings, "model") + _warn_deprecated_param("model", self.Settings, "model") default_settings.model = model # 3. Apply params overrides — only if settings not provided if params is not None: - _warn_deprecated_param("params", DeepgramFluxSTTSettings) + _warn_deprecated_param("params", self.Settings) if not settings: default_settings.eager_eot_threshold = params.eager_eot_threshold default_settings.eot_threshold = params.eot_threshold @@ -448,7 +448,7 @@ class DeepgramFluxSTTService(WebsocketSTTService): """ return True - async def _update_settings(self, delta: DeepgramFluxSTTSettings) -> dict[str, Any]: + async def _update_settings(self, delta: Settings) -> dict[str, Any]: """Apply a settings delta. Configure-able fields (keyterm, eot_threshold, eager_eot_threshold, diff --git a/src/pipecat/services/deepgram/sagemaker/stt.py b/src/pipecat/services/deepgram/sagemaker/stt.py index f6093a630..98b3556cc 100644 --- a/src/pipecat/services/deepgram/sagemaker/stt.py +++ b/src/pipecat/services/deepgram/sagemaker/stt.py @@ -32,7 +32,7 @@ from pipecat.frames.frames import ( ) from pipecat.processors.frame_processor import FrameDirection from pipecat.services.aws.sagemaker.bidi_client import SageMakerBidiClient -from pipecat.services.deepgram.stt import DeepgramSTTSettings, LiveOptions +from pipecat.services.deepgram.stt import DeepgramSTTService, LiveOptions from pipecat.services.settings import STTSettings, _warn_deprecated_param, is_given from pipecat.services.stt_latency import DEEPGRAM_SAGEMAKER_TTFS_P99 from pipecat.services.stt_service import STTService @@ -42,10 +42,10 @@ from pipecat.utils.tracing.service_decorators import traced_stt @dataclass -class DeepgramSageMakerSTTSettings(DeepgramSTTSettings): +class DeepgramSageMakerSTTSettings(DeepgramSTTService.Settings): """Settings for the Deepgram SageMaker STT service. - Inherits all fields from :class:`DeepgramSTTSettings`. + Inherits all fields from :class:`DeepgramSTTService.Settings`. """ pass @@ -79,7 +79,7 @@ class DeepgramSageMakerSTTService(STTService): """ Settings = DeepgramSageMakerSTTSettings - _settings: DeepgramSageMakerSTTSettings + _settings: Settings def __init__( self, @@ -92,7 +92,7 @@ class DeepgramSageMakerSTTService(STTService): sample_rate: Optional[int] = None, mip_opt_out: Optional[bool] = None, live_options: Optional[LiveOptions] = None, - settings: Optional[DeepgramSageMakerSTTSettings] = None, + settings: Optional[Settings] = None, ttfs_p99_latency: Optional[float] = DEEPGRAM_SAGEMAKER_TTFS_P99, **kwargs, ): @@ -112,7 +112,7 @@ class DeepgramSageMakerSTTService(STTService): live_options: Legacy configuration options. .. deprecated:: 0.0.105 - Use ``settings=DeepgramSageMakerSTTSettings(...)`` for + Use ``settings=DeepgramSageMakerSTTService.Settings(...)`` for runtime-updatable fields and direct init parameters for connection-level config. @@ -124,7 +124,7 @@ class DeepgramSageMakerSTTService(STTService): **kwargs: Additional arguments passed to the parent STTService. """ # 1. Initialize default_settings with hardcoded defaults - default_settings = DeepgramSageMakerSTTSettings( + default_settings = self.Settings( model="nova-3", language=Language.EN, detect_entities=False, @@ -147,7 +147,7 @@ class DeepgramSageMakerSTTService(STTService): # 2. Apply live_options overrides — only if settings not provided if live_options is not None: - _warn_deprecated_param("live_options", DeepgramSageMakerSTTSettings) + _warn_deprecated_param("live_options", self.Settings) if not settings: # Extract init-only fields from live_options if live_options.sample_rate is not None and sample_rate is None: @@ -170,7 +170,7 @@ class DeepgramSageMakerSTTService(STTService): "mip_opt_out", } lo_dict = {k: v for k, v in live_options.to_dict().items() if k not in init_only} - delta = DeepgramSageMakerSTTSettings.from_mapping(lo_dict) + delta = self.Settings.from_mapping(lo_dict) default_settings.apply_update(delta) # 3. Apply settings delta (canonical API, always wins) @@ -216,7 +216,7 @@ class DeepgramSageMakerSTTService(STTService): return changed # Sync extra to fields after the update so self._settings stays unambiguous - if isinstance(self._settings, DeepgramSTTSettings): + if isinstance(self._settings, self.Settings): self._settings._sync_extra_to_fields() # TODO: someday we could reconnect here to apply updated settings. diff --git a/src/pipecat/services/deepgram/sagemaker/tts.py b/src/pipecat/services/deepgram/sagemaker/tts.py index d315b9e01..f2c55c882 100644 --- a/src/pipecat/services/deepgram/sagemaker/tts.py +++ b/src/pipecat/services/deepgram/sagemaker/tts.py @@ -70,7 +70,7 @@ class DeepgramSageMakerTTSService(TTSService): """ Settings = DeepgramSageMakerTTSSettings - _settings: DeepgramSageMakerTTSSettings + _settings: Settings def __init__( self, @@ -80,7 +80,7 @@ class DeepgramSageMakerTTSService(TTSService): voice: Optional[str] = None, sample_rate: Optional[int] = None, encoding: str = "linear16", - settings: Optional[DeepgramSageMakerTTSSettings] = None, + settings: Optional[Settings] = None, **kwargs, ): """Initialize the Deepgram SageMaker TTS service. @@ -92,7 +92,7 @@ class DeepgramSageMakerTTSService(TTSService): voice: Voice model to use for synthesis. Defaults to "aura-2-helena-en". .. deprecated:: 0.0.105 - Use ``settings=DeepgramSageMakerTTSSettings(voice=...)`` instead. + Use ``settings=DeepgramSageMakerTTSService.Settings(voice=...)`` instead. sample_rate: Audio sample rate in Hz. If None, uses the value from StartFrame. encoding: Audio encoding format. Defaults to "linear16". @@ -101,11 +101,11 @@ class DeepgramSageMakerTTSService(TTSService): **kwargs: Additional arguments passed to the parent TTSService. """ if voice is not None: - _warn_deprecated_param("voice", DeepgramSageMakerTTSSettings, "voice") + _warn_deprecated_param("voice", self.Settings, "voice") voice = voice or "aura-2-helena-en" - default_settings = DeepgramSageMakerTTSSettings( + default_settings = self.Settings( model=None, voice=voice, language=None, diff --git a/src/pipecat/services/deepgram/stt.py b/src/pipecat/services/deepgram/stt.py index d8f782f5d..e84964dce 100644 --- a/src/pipecat/services/deepgram/stt.py +++ b/src/pipecat/services/deepgram/stt.py @@ -59,7 +59,7 @@ class LiveOptions: deepgram-sdk v6. .. deprecated:: 0.0.105 - Use ``settings=DeepgramSTTSettings(...)`` for runtime-updatable fields + Use ``settings=DeepgramSTTService.Settings(...)`` for runtime-updatable fields and direct ``__init__`` parameters for connection-level config instead. """ @@ -267,7 +267,7 @@ class DeepgramSTTService(STTService): """ Settings = DeepgramSTTSettings - _settings: DeepgramSTTSettings + _settings: Settings def __init__( self, @@ -286,7 +286,7 @@ class DeepgramSTTService(STTService): live_options: Optional[LiveOptions] = None, addons: Optional[dict] = None, should_interrupt: bool = True, - settings: Optional[DeepgramSTTSettings] = None, + settings: Optional[Settings] = None, ttfs_p99_latency: Optional[float] = DEEPGRAM_TTFS_P99, **kwargs, ): @@ -313,7 +313,7 @@ class DeepgramSTTService(STTService): live_options: Legacy configuration options. .. deprecated:: 0.0.105 - Use ``settings=DeepgramSTTSettings(...)`` for runtime-updatable + Use ``settings=DeepgramSTTService.Settings(...)`` for runtime-updatable fields and direct init parameters for connection-level config. addons: Additional Deepgram features to enable. @@ -345,7 +345,7 @@ class DeepgramSTTService(STTService): base_url = url # 1. Initialize default_settings with hardcoded defaults - default_settings = DeepgramSTTSettings( + default_settings = self.Settings( model="nova-3-general", language=Language.EN, detect_entities=False, @@ -370,7 +370,7 @@ class DeepgramSTTService(STTService): # 3. Apply live_options overrides — only if settings not provided if live_options is not None: - _warn_deprecated_param("live_options", DeepgramSTTSettings) + _warn_deprecated_param("live_options", self.Settings) if not settings: # Extract init-only fields from live_options if live_options.sample_rate is not None and sample_rate is None: @@ -402,7 +402,7 @@ class DeepgramSTTService(STTService): "mip_opt_out", } lo_dict = {k: v for k, v in live_options.to_dict().items() if k not in init_only} - delta = DeepgramSTTSettings.from_mapping(lo_dict) + delta = self.Settings.from_mapping(lo_dict) default_settings.apply_update(delta) # 4. Apply settings delta (canonical API, always wins) @@ -494,7 +494,7 @@ class DeepgramSTTService(STTService): return changed # Sync extra to fields after the update so self._settings stays unambiguous - if isinstance(self._settings, DeepgramSTTSettings): + if isinstance(self._settings, self.Settings): self._settings._sync_extra_to_fields() if self._connection: diff --git a/src/pipecat/services/deepgram/tts.py b/src/pipecat/services/deepgram/tts.py index 791462a91..5fdbeb700 100644 --- a/src/pipecat/services/deepgram/tts.py +++ b/src/pipecat/services/deepgram/tts.py @@ -57,7 +57,7 @@ class DeepgramTTSService(WebsocketTTSService): """ Settings = DeepgramTTSSettings - _settings: DeepgramTTSSettings + _settings: Settings SUPPORTED_ENCODINGS = ("linear16", "mulaw", "alaw") @@ -69,7 +69,7 @@ class DeepgramTTSService(WebsocketTTSService): base_url: str = "wss://api.deepgram.com", sample_rate: Optional[int] = None, encoding: str = "linear16", - settings: Optional[DeepgramTTSSettings] = None, + settings: Optional[Settings] = None, **kwargs, ): """Initialize the Deepgram WebSocket TTS service. @@ -79,7 +79,7 @@ class DeepgramTTSService(WebsocketTTSService): voice: Voice model to use for synthesis. .. deprecated:: 0.0.105 - Use ``settings=DeepgramTTSSettings(voice=...)`` instead. + Use ``settings=DeepgramTTSService.Settings(voice=...)`` instead. base_url: WebSocket base URL for Deepgram API. Defaults to "wss://api.deepgram.com". sample_rate: Audio sample rate in Hz. If None, uses service default. @@ -97,7 +97,7 @@ class DeepgramTTSService(WebsocketTTSService): ) # 1. Initialize default_settings with hardcoded defaults - default_settings = DeepgramTTSSettings( + default_settings = self.Settings( model=None, voice="aura-2-helena-en", language=None, @@ -105,7 +105,7 @@ class DeepgramTTSService(WebsocketTTSService): # 2. Apply direct init arg overrides (deprecated) if voice is not None: - _warn_deprecated_param("voice", DeepgramTTSSettings, "voice") + _warn_deprecated_param("voice", self.Settings, "voice") default_settings.model = voice default_settings.voice = voice @@ -189,7 +189,7 @@ class DeepgramTTSService(WebsocketTTSService): """Apply a settings delta. Args: - delta: A :class:`TTSSettings` (or ``DeepgramTTSSettings``) delta. + delta: A :class:`TTSSettings` (or ``DeepgramTTSService.Settings``) delta. Returns: Dict mapping changed field names to their previous values. @@ -367,7 +367,7 @@ class DeepgramHttpTTSService(TTSService): """ Settings = DeepgramTTSSettings - _settings: DeepgramTTSSettings + _settings: Settings def __init__( self, @@ -378,7 +378,7 @@ class DeepgramHttpTTSService(TTSService): base_url: str = "https://api.deepgram.com", sample_rate: Optional[int] = None, encoding: str = "linear16", - settings: Optional[DeepgramTTSSettings] = None, + settings: Optional[Settings] = None, **kwargs, ): """Initialize the Deepgram TTS service. @@ -388,7 +388,7 @@ class DeepgramHttpTTSService(TTSService): voice: Voice model to use for synthesis. .. deprecated:: 0.0.105 - Use ``settings=DeepgramTTSSettings(voice=...)`` instead. + Use ``settings=DeepgramHttpTTSService.Settings(voice=...)`` instead. aiohttp_session: Shared aiohttp session for HTTP requests with connection pooling. base_url: Custom base URL for Deepgram API. Defaults to "https://api.deepgram.com". @@ -399,7 +399,7 @@ class DeepgramHttpTTSService(TTSService): **kwargs: Additional arguments passed to parent TTSService class. """ # 1. Initialize default_settings with hardcoded defaults - default_settings = DeepgramTTSSettings( + default_settings = self.Settings( model=None, voice="aura-2-helena-en", language=None, @@ -407,7 +407,7 @@ class DeepgramHttpTTSService(TTSService): # 2. Apply direct init arg overrides (deprecated) if voice is not None: - _warn_deprecated_param("voice", DeepgramTTSSettings, "voice") + _warn_deprecated_param("voice", self.Settings, "voice") default_settings.model = voice default_settings.voice = voice diff --git a/src/pipecat/services/deepseek/llm.py b/src/pipecat/services/deepseek/llm.py index 8fc4b5db8..abb0d56bb 100644 --- a/src/pipecat/services/deepseek/llm.py +++ b/src/pipecat/services/deepseek/llm.py @@ -12,13 +12,13 @@ from typing import Optional from loguru import logger from pipecat.adapters.services.open_ai_adapter import OpenAILLMInvocationParams -from pipecat.services.openai.base_llm import OpenAILLMSettings +from pipecat.services.openai.base_llm import BaseOpenAILLMService from pipecat.services.openai.llm import OpenAILLMService from pipecat.services.settings import _warn_deprecated_param @dataclass -class DeepSeekLLMSettings(OpenAILLMSettings): +class DeepSeekLLMSettings(BaseOpenAILLMService.Settings): """Settings for DeepSeekLLMService.""" pass @@ -32,7 +32,7 @@ class DeepSeekLLMService(OpenAILLMService): """ Settings = DeepSeekLLMSettings - _settings: DeepSeekLLMSettings + _settings: Settings def __init__( self, @@ -40,7 +40,7 @@ class DeepSeekLLMService(OpenAILLMService): api_key: str, base_url: str = "https://api.deepseek.com/v1", model: Optional[str] = None, - settings: Optional[DeepSeekLLMSettings] = None, + settings: Optional[Settings] = None, **kwargs, ): """Initialize the DeepSeek LLM service. @@ -51,18 +51,18 @@ class DeepSeekLLMService(OpenAILLMService): model: The model identifier to use. Defaults to "deepseek-chat". .. deprecated:: 0.0.105 - Use ``settings=OpenAILLMSettings(model=...)`` instead. + Use ``settings=DeepSeekLLMService.Settings(model=...)`` instead. settings: Runtime-updatable settings. When provided alongside deprecated parameters, ``settings`` values take precedence. **kwargs: Additional keyword arguments passed to OpenAILLMService. """ # 1. Initialize default_settings with hardcoded defaults - default_settings = DeepSeekLLMSettings(model="deepseek-chat") + default_settings = self.Settings(model="deepseek-chat") # 2. Apply direct init arg overrides (deprecated) if model is not None: - _warn_deprecated_param("model", DeepSeekLLMSettings, "model") + _warn_deprecated_param("model", self.Settings, "model") default_settings.model = model # 3. (No step 3, as there's no params object to apply) diff --git a/src/pipecat/services/elevenlabs/stt.py b/src/pipecat/services/elevenlabs/stt.py index 76e854ade..7247241d3 100644 --- a/src/pipecat/services/elevenlabs/stt.py +++ b/src/pipecat/services/elevenlabs/stt.py @@ -217,13 +217,13 @@ class ElevenLabsSTTService(SegmentedSTTService): """ Settings = ElevenLabsSTTSettings - _settings: ElevenLabsSTTSettings + _settings: Settings class InputParams(BaseModel): """Configuration parameters for ElevenLabs STT API. .. deprecated:: 0.0.105 - Use ``settings=ElevenLabsSTTSettings(...)`` instead. + Use ``settings=ElevenLabsSTTService.Settings(...)`` instead. Parameters: language: Target language for transcription. @@ -242,7 +242,7 @@ class ElevenLabsSTTService(SegmentedSTTService): model: Optional[str] = None, sample_rate: Optional[int] = None, params: Optional[InputParams] = None, - settings: Optional[ElevenLabsSTTSettings] = None, + settings: Optional[Settings] = None, ttfs_p99_latency: Optional[float] = ELEVENLABS_TTFS_P99, **kwargs, ): @@ -255,13 +255,13 @@ class ElevenLabsSTTService(SegmentedSTTService): model: Model ID for transcription. .. deprecated:: 0.0.105 - Use ``settings=ElevenLabsSTTSettings(model=...)`` instead. + Use ``settings=ElevenLabsSTTService.Settings(model=...)`` instead. sample_rate: Audio sample rate in Hz. If not provided, uses the pipeline's rate. params: Configuration parameters for the STT service. .. deprecated:: 0.0.105 - Use ``settings=ElevenLabsSTTSettings(...)`` instead. + Use ``settings=ElevenLabsSTTService.Settings(...)`` instead. settings: Runtime-updatable settings. When provided alongside deprecated parameters, ``settings`` values take precedence. @@ -270,7 +270,7 @@ class ElevenLabsSTTService(SegmentedSTTService): **kwargs: Additional arguments passed to SegmentedSTTService. """ # 1. Initialize default_settings with hardcoded defaults - default_settings = ElevenLabsSTTSettings( + default_settings = self.Settings( model="scribe_v2", language=language_to_elevenlabs_language(Language.EN), tag_audio_events=None, @@ -278,12 +278,12 @@ class ElevenLabsSTTService(SegmentedSTTService): # 2. Apply direct init arg overrides (deprecated) if model is not None: - _warn_deprecated_param("model", ElevenLabsSTTSettings, "model") + _warn_deprecated_param("model", self.Settings, "model") default_settings.model = model # 3. Apply params overrides — only if settings not provided if params is not None: - _warn_deprecated_param("params", ElevenLabsSTTSettings) + _warn_deprecated_param("params", self.Settings) if not settings: if params.language is not None: default_settings.language = language_to_elevenlabs_language(params.language) @@ -450,13 +450,13 @@ class ElevenLabsRealtimeSTTService(WebsocketSTTService): """ Settings = ElevenLabsRealtimeSTTSettings - _settings: ElevenLabsRealtimeSTTSettings + _settings: Settings class InputParams(BaseModel): """Configuration parameters for ElevenLabs Realtime STT API. .. deprecated:: 0.0.105 - Use ``settings=ElevenLabsRealtimeSTTSettings(...)`` instead. + Use ``settings=ElevenLabsRealtimeSTTService.Settings(...)`` instead. Parameters: language_code: ISO-639-1 or ISO-639-3 language code. Leave None for auto-detection. @@ -496,7 +496,7 @@ class ElevenLabsRealtimeSTTService(WebsocketSTTService): enable_logging: bool = False, include_language_detection: bool = False, params: Optional[InputParams] = None, - settings: Optional[ElevenLabsRealtimeSTTSettings] = None, + settings: Optional[Settings] = None, ttfs_p99_latency: Optional[float] = ELEVENLABS_REALTIME_TTFS_P99, **kwargs, ): @@ -511,7 +511,7 @@ class ElevenLabsRealtimeSTTService(WebsocketSTTService): model: Model ID for transcription. .. deprecated:: 0.0.105 - Use ``settings=ElevenLabsRealtimeSTTSettings(model=...)`` instead. + Use ``settings=ElevenLabsRealtimeSTTService.Settings(model=...)`` instead. sample_rate: Audio sample rate in Hz. If not provided, uses the pipeline's rate. include_timestamps: Whether to include word-level timestamps in transcripts. @@ -520,7 +520,7 @@ class ElevenLabsRealtimeSTTService(WebsocketSTTService): params: Configuration parameters for the STT service. .. deprecated:: 0.0.105 - Use ``settings=ElevenLabsRealtimeSTTSettings(...)`` instead. + Use ``settings=ElevenLabsRealtimeSTTService.Settings(...)`` instead. settings: Runtime-updatable settings. When provided alongside deprecated parameters, ``settings`` values take precedence. @@ -529,7 +529,7 @@ class ElevenLabsRealtimeSTTService(WebsocketSTTService): **kwargs: Additional arguments passed to WebsocketSTTService. """ # 1. Initialize default_settings with hardcoded defaults - default_settings = ElevenLabsRealtimeSTTSettings( + default_settings = self.Settings( model="scribe_v2_realtime", language=None, vad_silence_threshold_secs=None, @@ -540,12 +540,12 @@ class ElevenLabsRealtimeSTTService(WebsocketSTTService): # 2. Apply direct init arg overrides (deprecated) if model is not None: - _warn_deprecated_param("model", ElevenLabsRealtimeSTTSettings, "model") + _warn_deprecated_param("model", self.Settings, "model") default_settings.model = model # 3. Apply params overrides — only if settings not provided if params is not None: - _warn_deprecated_param("params", ElevenLabsRealtimeSTTSettings) + _warn_deprecated_param("params", self.Settings) if not settings: default_settings.language = params.language_code if params.commit_strategy != CommitStrategy.MANUAL: @@ -597,7 +597,7 @@ class ElevenLabsRealtimeSTTService(WebsocketSTTService): """Apply a settings delta and reconnect if anything changed. Args: - delta: A :class:`STTSettings` (or ``ElevenLabsRealtimeSTTSettings``) delta. + delta: A :class:`STTSettings` (or ``ElevenLabsRealtimeSTTService.Settings``) delta. Returns: Dict mapping changed field names to their previous values. diff --git a/src/pipecat/services/elevenlabs/tts.py b/src/pipecat/services/elevenlabs/tts.py index 01f3cd516..46acc2f1c 100644 --- a/src/pipecat/services/elevenlabs/tts.py +++ b/src/pipecat/services/elevenlabs/tts.py @@ -317,13 +317,13 @@ class ElevenLabsTTSService(WebsocketTTSService): """ Settings = ElevenLabsTTSSettings - _settings: ElevenLabsTTSSettings + _settings: Settings class InputParams(BaseModel): """Input parameters for ElevenLabs TTS configuration. .. deprecated:: 0.0.105 - Use ``settings=ElevenLabsTTSSettings(...)`` instead. + Use ``settings=ElevenLabsTTSService.Settings(...)`` instead. Parameters: language: Language to use for synthesis. @@ -364,7 +364,7 @@ class ElevenLabsTTSService(WebsocketTTSService): enable_logging: Optional[bool] = None, pronunciation_dictionary_locators: Optional[List[PronunciationDictionaryLocator]] = None, params: Optional[InputParams] = None, - settings: Optional[ElevenLabsTTSSettings] = None, + settings: Optional[Settings] = None, text_aggregation_mode: Optional[TextAggregationMode] = None, aggregate_sentences: Optional[bool] = None, **kwargs, @@ -376,12 +376,12 @@ class ElevenLabsTTSService(WebsocketTTSService): voice_id: ID of the voice to use for synthesis. .. deprecated:: 0.0.105 - Use ``settings=ElevenLabsTTSSettings(voice=...)`` instead. + Use ``settings=ElevenLabsTTSService.Settings(voice=...)`` instead. model: TTS model to use (e.g., "eleven_turbo_v2_5"). .. deprecated:: 0.0.105 - Use ``settings=ElevenLabsTTSSettings(model=...)`` instead. + Use ``settings=ElevenLabsTTSService.Settings(model=...)`` instead. url: WebSocket URL for ElevenLabs TTS API. sample_rate: Audio sample rate. If None, uses default. @@ -393,7 +393,7 @@ class ElevenLabsTTSService(WebsocketTTSService): params: Additional input parameters for voice customization. .. deprecated:: 0.0.105 - Use ``settings=ElevenLabsTTSSettings(...)`` instead. + Use ``settings=ElevenLabsTTSService.Settings(...)`` instead. settings: Runtime-updatable settings. When provided alongside deprecated parameters, ``settings`` values take precedence. @@ -423,7 +423,7 @@ class ElevenLabsTTSService(WebsocketTTSService): # after a short period not receiving any audio. # 1. Initialize default_settings with hardcoded defaults - default_settings = ElevenLabsTTSSettings( + default_settings = self.Settings( model="eleven_turbo_v2_5", voice=None, language=None, @@ -437,16 +437,16 @@ class ElevenLabsTTSService(WebsocketTTSService): # 2. Apply direct init arg overrides (deprecated) if voice_id is not None: - _warn_deprecated_param("voice_id", ElevenLabsTTSSettings, "voice") + _warn_deprecated_param("voice_id", self.Settings, "voice") default_settings.voice = voice_id if model is not None: - _warn_deprecated_param("model", ElevenLabsTTSSettings, "model") + _warn_deprecated_param("model", self.Settings, "model") default_settings.model = model # 3. Apply params overrides — only if settings not provided _pronunciation_dictionary_locators = pronunciation_dictionary_locators if params is not None: - _warn_deprecated_param("params", ElevenLabsTTSSettings) + _warn_deprecated_param("params", self.Settings) if not settings: if params.language is not None: default_settings.language = self.language_to_service_language(params.language) @@ -533,11 +533,11 @@ class ElevenLabsTTSService(WebsocketTTSService): """Apply a settings delta, reconnecting as needed. Uses the declarative ``URL_FIELDS`` and ``VOICE_SETTINGS_FIELDS`` - sets on :class:`ElevenLabsTTSSettings` to decide whether to + sets on :class:`ElevenLabsTTSService.Settings` to decide whether to reconnect the WebSocket or close the current audio context. Args: - delta: A :class:`TTSSettings` (or ``ElevenLabsTTSSettings``) delta. + delta: A :class:`TTSSettings` (or ``ElevenLabsTTSService.Settings``) delta. Returns: Dict mapping changed field names to their previous values. @@ -550,19 +550,19 @@ class ElevenLabsTTSService(WebsocketTTSService): # Rebuild voice settings for next context self._voice_settings = self._set_voice_settings() - url_changed = bool(changed.keys() & ElevenLabsTTSSettings.URL_FIELDS) - voice_settings_changed = bool(changed.keys() & ElevenLabsTTSSettings.VOICE_SETTINGS_FIELDS) + url_changed = bool(changed.keys() & self.Settings.URL_FIELDS) + voice_settings_changed = bool(changed.keys() & self.Settings.VOICE_SETTINGS_FIELDS) if url_changed: logger.debug( - f"URL-level setting changed ({changed.keys() & ElevenLabsTTSSettings.URL_FIELDS}), " + f"URL-level setting changed ({changed.keys() & self.Settings.URL_FIELDS}), " f"reconnecting WebSocket" ) await self._disconnect() await self._connect() elif voice_settings_changed: logger.debug( - f"Voice settings changed ({changed.keys() & ElevenLabsTTSSettings.VOICE_SETTINGS_FIELDS}), " + f"Voice settings changed ({changed.keys() & self.Settings.VOICE_SETTINGS_FIELDS}), " f"closing current context to apply changes" ) audio_contexts = self.get_audio_contexts() @@ -573,7 +573,7 @@ class ElevenLabsTTSService(WebsocketTTSService): if not url_changed: # Reconnect applies all settings; only warn about fields not handled # by voice settings or URL changes. - handled = ElevenLabsTTSSettings.URL_FIELDS | ElevenLabsTTSSettings.VOICE_SETTINGS_FIELDS + handled = self.Settings.URL_FIELDS | self.Settings.VOICE_SETTINGS_FIELDS self._warn_unhandled_updated_settings(changed.keys() - handled) return changed @@ -906,13 +906,13 @@ class ElevenLabsHttpTTSService(TTSService): """ Settings = ElevenLabsHttpTTSSettings - _settings: ElevenLabsHttpTTSSettings + _settings: Settings class InputParams(BaseModel): """Input parameters for ElevenLabs HTTP TTS configuration. .. deprecated:: 0.0.105 - Use ``settings=ElevenLabsHttpTTSSettings(...)`` instead. + Use ``settings=ElevenLabsHttpTTSService.Settings(...)`` instead. Parameters: language: Language to use for synthesis. @@ -947,7 +947,7 @@ class ElevenLabsHttpTTSService(TTSService): sample_rate: Optional[int] = None, pronunciation_dictionary_locators: Optional[List[PronunciationDictionaryLocator]] = None, params: Optional[InputParams] = None, - settings: Optional[ElevenLabsHttpTTSSettings] = None, + settings: Optional[Settings] = None, text_aggregation_mode: Optional[TextAggregationMode] = None, aggregate_sentences: Optional[bool] = None, **kwargs, @@ -959,13 +959,13 @@ class ElevenLabsHttpTTSService(TTSService): voice_id: ID of the voice to use for synthesis. .. deprecated:: 0.0.105 - Use ``settings=ElevenLabsHttpTTSSettings(voice=...)`` instead. + Use ``settings=ElevenLabsHttpTTSService.Settings(voice=...)`` instead. aiohttp_session: aiohttp ClientSession for HTTP requests. model: TTS model to use (e.g., "eleven_turbo_v2_5"). .. deprecated:: 0.0.105 - Use ``settings=ElevenLabsHttpTTSSettings(model=...)`` instead. + Use ``settings=ElevenLabsHttpTTSService.Settings(model=...)`` instead. base_url: Base URL for ElevenLabs HTTP API. sample_rate: Audio sample rate. If None, uses default. @@ -974,7 +974,7 @@ class ElevenLabsHttpTTSService(TTSService): params: Additional input parameters for voice customization. .. deprecated:: 0.0.105 - Use ``settings=ElevenLabsHttpTTSSettings(...)`` instead. + Use ``settings=ElevenLabsHttpTTSService.Settings(...)`` instead. settings: Runtime-updatable settings. When provided alongside deprecated parameters, ``settings`` values take precedence. @@ -987,7 +987,7 @@ class ElevenLabsHttpTTSService(TTSService): **kwargs: Additional arguments passed to the parent service. """ # 1. Initialize default_settings with hardcoded defaults - default_settings = ElevenLabsHttpTTSSettings( + default_settings = self.Settings( model="eleven_turbo_v2_5", voice=None, language=None, @@ -1002,16 +1002,16 @@ class ElevenLabsHttpTTSService(TTSService): # 2. Apply direct init arg overrides (deprecated) if voice_id is not None: - _warn_deprecated_param("voice_id", ElevenLabsHttpTTSSettings, "voice") + _warn_deprecated_param("voice_id", self.Settings, "voice") default_settings.voice = voice_id if model is not None: - _warn_deprecated_param("model", ElevenLabsHttpTTSSettings, "model") + _warn_deprecated_param("model", self.Settings, "model") default_settings.model = model # 3. Apply params overrides — only if settings not provided _pronunciation_dictionary_locators = pronunciation_dictionary_locators if params is not None: - _warn_deprecated_param("params", ElevenLabsHttpTTSSettings) + _warn_deprecated_param("params", self.Settings) if not settings: if params.language is not None: default_settings.language = self.language_to_service_language(params.language) @@ -1091,7 +1091,7 @@ class ElevenLabsHttpTTSService(TTSService): """Apply a settings delta and rebuild voice settings. Args: - delta: A :class:`TTSSettings` (or ``ElevenLabsHttpTTSSettings``) delta. + delta: A :class:`TTSSettings` (or ``ElevenLabsHttpTTSService.Settings``) delta. Returns: Dict mapping changed field names to their previous values. diff --git a/src/pipecat/services/fal/image.py b/src/pipecat/services/fal/image.py index cb4d646ba..3c15a918a 100644 --- a/src/pipecat/services/fal/image.py +++ b/src/pipecat/services/fal/image.py @@ -71,13 +71,13 @@ class FalImageGenService(ImageGenService): """ Settings = FalImageGenSettings - _settings: FalImageGenSettings + _settings: Settings class InputParams(BaseModel): """Input parameters for Fal.ai image generation. .. deprecated:: 0.0.105 - Use ``settings=FalImageGenSettings(...)`` instead. + Use ``settings=FalImageGenService.Settings(...)`` instead. Parameters: seed: Random seed for reproducible generation. If None, uses random seed. @@ -97,7 +97,7 @@ class FalImageGenService(ImageGenService): enable_safety_checker: bool = True format: str = "png" - _settings: FalImageGenSettings + _settings: Settings def __init__( self, @@ -106,7 +106,7 @@ class FalImageGenService(ImageGenService): aiohttp_session: aiohttp.ClientSession, model: Optional[str] = None, key: Optional[str] = None, - settings: Optional[FalImageGenSettings] = None, + settings: Optional[Settings] = None, **kwargs, ): """Initialize the FalImageGenService. @@ -115,13 +115,13 @@ class FalImageGenService(ImageGenService): params: Input parameters for image generation configuration. .. deprecated:: 0.0.105 - Use ``settings=FalImageGenSettings(...)`` instead. + Use ``settings=FalImageGenService.Settings(...)`` instead. aiohttp_session: HTTP client session for downloading generated images. model: The Fal.ai model to use for generation. Defaults to "fal-ai/fast-sdxl". .. deprecated:: 0.0.105 - Use ``settings=FalImageGenSettings(model=...)`` instead. + Use ``settings=FalImageGenService.Settings(model=...)`` instead. key: Optional API key for Fal.ai. If provided, sets FAL_KEY environment variable. settings: Runtime-updatable settings. When provided alongside deprecated @@ -129,7 +129,7 @@ class FalImageGenService(ImageGenService): **kwargs: Additional arguments passed to parent ImageGenService. """ # 1. Initialize default_settings with hardcoded defaults - default_settings = FalImageGenSettings( + default_settings = self.Settings( model="fal-ai/fast-sdxl", seed=None, num_inference_steps=8, @@ -142,11 +142,11 @@ class FalImageGenService(ImageGenService): # 2. Apply direct init arg overrides (deprecated) if model is not None: - _warn_deprecated_param("model", FalImageGenSettings, "model") + _warn_deprecated_param("model", self.Settings, "model") default_settings.model = model if params is not None: - _warn_deprecated_param("params", FalImageGenSettings) + _warn_deprecated_param("params", self.Settings) if not settings: default_settings.seed = params.seed default_settings.num_inference_steps = params.num_inference_steps diff --git a/src/pipecat/services/fal/stt.py b/src/pipecat/services/fal/stt.py index 692878bf6..c1aae24b7 100644 --- a/src/pipecat/services/fal/stt.py +++ b/src/pipecat/services/fal/stt.py @@ -156,13 +156,13 @@ class FalSTTService(SegmentedSTTService): """ Settings = FalSTTSettings - _settings: FalSTTSettings + _settings: Settings class InputParams(BaseModel): """Configuration parameters for Fal's Wizper API. .. deprecated:: 0.0.105 - Use ``settings=FalSTTSettings(...)`` instead. + Use ``settings=FalSTTService.Settings(...)`` instead. Parameters: language: Language of the audio input. Defaults to English. @@ -186,7 +186,7 @@ class FalSTTService(SegmentedSTTService): version: str = "3", sample_rate: Optional[int] = None, params: Optional[InputParams] = None, - settings: Optional[FalSTTSettings] = None, + settings: Optional[Settings] = None, ttfs_p99_latency: Optional[float] = FAL_TTFS_P99, **kwargs, ): @@ -204,7 +204,7 @@ class FalSTTService(SegmentedSTTService): params: Configuration parameters for the Wizper API. .. deprecated:: 0.0.105 - Use ``settings=FalSTTSettings(...)`` for model/language and + Use ``settings=FalSTTService.Settings(...)`` for model/language and direct init parameters for task/chunk_level/version instead. settings: Runtime-updatable settings. When provided alongside deprecated @@ -214,7 +214,7 @@ class FalSTTService(SegmentedSTTService): **kwargs: Additional arguments passed to SegmentedSTTService. """ # 1. Initialize default_settings with hardcoded defaults - default_settings = FalSTTSettings( + default_settings = self.Settings( model=None, language=language_to_fal_language(Language.EN), ) @@ -223,7 +223,7 @@ class FalSTTService(SegmentedSTTService): # 3. Apply params overrides — only if settings not provided if params is not None: - _warn_deprecated_param("params", FalSTTSettings) + _warn_deprecated_param("params", self.Settings) if not settings: if params.language is not None: default_settings.language = language_to_fal_language(params.language) diff --git a/src/pipecat/services/fireworks/llm.py b/src/pipecat/services/fireworks/llm.py index 118090be9..fdd688149 100644 --- a/src/pipecat/services/fireworks/llm.py +++ b/src/pipecat/services/fireworks/llm.py @@ -12,13 +12,13 @@ from typing import Optional from loguru import logger from pipecat.adapters.services.open_ai_adapter import OpenAILLMInvocationParams -from pipecat.services.openai.base_llm import OpenAILLMSettings +from pipecat.services.openai.base_llm import BaseOpenAILLMService from pipecat.services.openai.llm import OpenAILLMService from pipecat.services.settings import _warn_deprecated_param @dataclass -class FireworksLLMSettings(OpenAILLMSettings): +class FireworksLLMSettings(BaseOpenAILLMService.Settings): """Settings for FireworksLLMService.""" pass @@ -32,7 +32,7 @@ class FireworksLLMService(OpenAILLMService): """ Settings = FireworksLLMSettings - _settings: FireworksLLMSettings + _settings: Settings def __init__( self, @@ -40,7 +40,7 @@ class FireworksLLMService(OpenAILLMService): api_key: str, model: Optional[str] = None, base_url: str = "https://api.fireworks.ai/inference/v1", - settings: Optional[FireworksLLMSettings] = None, + settings: Optional[Settings] = None, **kwargs, ): """Initialize the Fireworks LLM service. @@ -50,7 +50,7 @@ class FireworksLLMService(OpenAILLMService): model: The model identifier to use. Defaults to "accounts/fireworks/models/firefunction-v2". .. deprecated:: 0.0.105 - Use ``settings=OpenAILLMSettings(model=...)`` instead. + Use ``settings=FireworksLLMService.Settings(model=...)`` instead. base_url: The base URL for Fireworks API. Defaults to "https://api.fireworks.ai/inference/v1". settings: Runtime-updatable settings. When provided alongside deprecated @@ -58,11 +58,11 @@ class FireworksLLMService(OpenAILLMService): **kwargs: Additional keyword arguments passed to OpenAILLMService. """ # 1. Initialize default_settings with hardcoded defaults - default_settings = FireworksLLMSettings(model="accounts/fireworks/models/firefunction-v2") + default_settings = self.Settings(model="accounts/fireworks/models/firefunction-v2") # 2. Apply direct init arg overrides (deprecated) if model is not None: - _warn_deprecated_param("model", FireworksLLMSettings, "model") + _warn_deprecated_param("model", self.Settings, "model") default_settings.model = model # 3. (No step 3, as there's no params object to apply) diff --git a/src/pipecat/services/fish/tts.py b/src/pipecat/services/fish/tts.py index f21b42b97..39669574a 100644 --- a/src/pipecat/services/fish/tts.py +++ b/src/pipecat/services/fish/tts.py @@ -85,13 +85,13 @@ class FishAudioTTSService(InterruptibleTTSService): """ Settings = FishAudioTTSSettings - _settings: FishAudioTTSSettings + _settings: Settings class InputParams(BaseModel): """Input parameters for Fish Audio TTS configuration. .. deprecated:: 0.0.105 - Use ``settings=FishAudioTTSSettings(...)`` instead. + Use ``settings=FishAudioTTSService.Settings(...)`` instead. Parameters: language: Language for synthesis. Defaults to English. @@ -117,7 +117,7 @@ class FishAudioTTSService(InterruptibleTTSService): output_format: FishAudioOutputFormat = "pcm", sample_rate: Optional[int] = None, params: Optional[InputParams] = None, - settings: Optional[FishAudioTTSSettings] = None, + settings: Optional[Settings] = None, **kwargs, ): """Initialize the Fish Audio TTS service. @@ -127,7 +127,7 @@ class FishAudioTTSService(InterruptibleTTSService): reference_id: Reference ID of the voice model to use for synthesis. .. deprecated:: 0.0.105 - Use ``settings=FishAudioTTSSettings(voice=...)`` instead. + Use ``settings=FishAudioTTSService.Settings(voice=...)`` instead. model: Deprecated. Reference ID of the voice model to use for synthesis. @@ -138,14 +138,14 @@ class FishAudioTTSService(InterruptibleTTSService): model_id: Specify which Fish Audio TTS model to use (e.g. "s1"). .. deprecated:: 0.0.105 - Use ``settings=FishAudioTTSSettings(model=...)`` instead. + Use ``settings=FishAudioTTSService.Settings(model=...)`` instead. output_format: Audio output format. Defaults to "pcm". sample_rate: Audio sample rate. If None, uses default. params: Additional input parameters for voice customization. .. deprecated:: 0.0.105 - Use ``settings=FishAudioTTSSettings(...)`` instead. + Use ``settings=FishAudioTTSService.Settings(...)`` instead. settings: Runtime-updatable settings. When provided alongside deprecated parameters, ``settings`` values take precedence. @@ -171,7 +171,7 @@ class FishAudioTTSService(InterruptibleTTSService): reference_id = model # 1. Initialize default_settings with hardcoded defaults - default_settings = FishAudioTTSSettings( + default_settings = self.Settings( model="s2-pro", voice=None, language=None, @@ -185,15 +185,15 @@ class FishAudioTTSService(InterruptibleTTSService): # 2. Apply direct init arg overrides (deprecated) if reference_id is not None: - _warn_deprecated_param("reference_id", FishAudioTTSSettings, "voice") + _warn_deprecated_param("reference_id", self.Settings, "voice") default_settings.voice = reference_id if model_id is not None: - _warn_deprecated_param("model_id", FishAudioTTSSettings, "model") + _warn_deprecated_param("model_id", self.Settings, "model") default_settings.model = model_id # 3. Apply params overrides — only if settings not provided if params is not None: - _warn_deprecated_param("params", FishAudioTTSSettings) + _warn_deprecated_param("params", self.Settings) if not settings: if params.latency is not None: default_settings.latency = params.latency @@ -240,7 +240,7 @@ class FishAudioTTSService(InterruptibleTTSService): Any change to voice or model triggers a WebSocket reconnect. Args: - delta: A :class:`TTSSettings` (or ``FishAudioTTSSettings``) delta. + delta: A :class:`TTSSettings` (or ``FishAudioTTSService.Settings``) delta. Returns: Dict mapping changed field names to their previous values. diff --git a/src/pipecat/services/gladia/config.py b/src/pipecat/services/gladia/config.py index ec8997d7c..c492a04a1 100644 --- a/src/pipecat/services/gladia/config.py +++ b/src/pipecat/services/gladia/config.py @@ -153,7 +153,7 @@ class GladiaInputParams(BaseModel): """Configuration parameters for the Gladia STT service. .. deprecated:: 0.0.105 - Use ``settings=GladiaSTTSettings(...)`` for runtime-updatable + Use ``settings=GladiaSTTService.Settings(...)`` for runtime-updatable fields and direct init parameters for encoding/bit_depth/channels. Parameters: diff --git a/src/pipecat/services/gladia/stt.py b/src/pipecat/services/gladia/stt.py index fc09d94fc..a68bf78b3 100644 --- a/src/pipecat/services/gladia/stt.py +++ b/src/pipecat/services/gladia/stt.py @@ -231,7 +231,7 @@ class GladiaSTTService(WebsocketSTTService): """ Settings = GladiaSTTSettings - _settings: GladiaSTTSettings + _settings: Settings # Maintain backward compatibility InputParams = _InputParamsDescriptor() @@ -251,7 +251,7 @@ class GladiaSTTService(WebsocketSTTService): params: Optional[GladiaInputParams] = None, max_buffer_size: int = 1024 * 1024 * 20, # 20MB default buffer should_interrupt: bool = True, - settings: Optional[GladiaSTTSettings] = None, + settings: Optional[Settings] = None, ttfs_p99_latency: Optional[float] = GLADIA_TTFS_P99, **kwargs, ): @@ -274,12 +274,12 @@ class GladiaSTTService(WebsocketSTTService): model: Model to use for transcription. .. deprecated:: 0.0.105 - Use ``settings=GladiaSTTSettings(model=...)`` instead. + Use ``settings=GladiaSTTService.Settings(model=...)`` instead. params: Additional configuration parameters for Gladia service. .. deprecated:: 0.0.105 - Use ``settings=GladiaSTTSettings(...)`` for runtime-updatable + Use ``settings=GladiaSTTService.Settings(...)`` for runtime-updatable fields and direct init parameters for encoding/bit_depth/channels. max_buffer_size: Maximum size of audio buffer in bytes. Defaults to 20MB. @@ -302,7 +302,7 @@ class GladiaSTTService(WebsocketSTTService): ) # 1. Initialize default_settings with hardcoded defaults - default_settings = GladiaSTTSettings( + default_settings = self.Settings( model="solaria-1", language=None, language_config=None, @@ -317,12 +317,12 @@ class GladiaSTTService(WebsocketSTTService): # 2. Apply direct init arg overrides (deprecated) if model is not None: - _warn_deprecated_param("model", GladiaSTTSettings, "model") + _warn_deprecated_param("model", self.Settings, "model") default_settings.model = model # 3. Apply params overrides — only if settings not provided if params is not None: - _warn_deprecated_param("params", GladiaSTTSettings) + _warn_deprecated_param("params", self.Settings) if params.language is not None: with warnings.catch_warnings(): warnings.simplefilter("always") @@ -469,7 +469,7 @@ class GladiaSTTService(WebsocketSTTService): await super().start(frame) await self._connect() - async def _update_settings(self, delta: GladiaSTTSettings) -> dict[str, Any]: + async def _update_settings(self, delta: Settings) -> dict[str, Any]: """Apply settings delta. Settings are stored but not applied to the active session. diff --git a/src/pipecat/services/google/gemini_live/llm.py b/src/pipecat/services/google/gemini_live/llm.py index 07f185f99..167abb938 100644 --- a/src/pipecat/services/google/gemini_live/llm.py +++ b/src/pipecat/services/google/gemini_live/llm.py @@ -553,7 +553,7 @@ class InputParams(BaseModel): """Input parameters for Gemini Live generation. .. deprecated:: 0.0.105 - Use ``GeminiLiveLLMSettings`` instead. + Use ``GeminiLiveLLMService.Settings`` instead. Parameters: frequency_penalty: Frequency penalty for generation (0.0-2.0). Defaults to None. @@ -643,7 +643,7 @@ class GeminiLiveLLMService(LLMService): """ Settings = GeminiLiveLLMSettings - _settings: GeminiLiveLLMSettings + _settings: Settings # Overriding the default adapter to use the Gemini one. adapter_class = GeminiLLMAdapter @@ -660,7 +660,7 @@ class GeminiLiveLLMService(LLMService): system_instruction: Optional[str] = None, tools: Optional[Union[List[dict], ToolsSchema]] = None, params: Optional[InputParams] = None, - settings: Optional[GeminiLiveLLMSettings] = None, + settings: Optional[Settings] = None, inference_on_context_initialization: bool = True, file_api_base_url: str = "https://generativelanguage.googleapis.com/v1beta/files", http_options: Optional[HttpOptions] = None, @@ -680,12 +680,12 @@ class GeminiLiveLLMService(LLMService): model: Model identifier to use. .. deprecated:: 0.0.105 - Use ``settings=GeminiLiveLLMSettings(model=...)`` instead. + Use ``settings=GeminiLiveLLMService.Settings(model=...)`` instead. voice_id: TTS voice identifier. Defaults to "Charon". .. deprecated:: 0.0.105 - Use ``settings=GeminiLiveLLMSettings(voice=...)`` instead. + Use ``settings=GeminiLiveLLMService.Settings(voice=...)`` instead. start_audio_paused: Whether to start with audio input paused. Defaults to False. start_video_paused: Whether to start with video input paused. Defaults to False. system_instruction: System prompt for the model. Defaults to None. @@ -693,7 +693,7 @@ class GeminiLiveLLMService(LLMService): params: Configuration parameters for the model. .. deprecated:: 0.0.105 - Use ``settings=GeminiLiveLLMSettings(...)`` instead. + Use ``settings=GeminiLiveLLMService.Settings(...)`` instead. settings: Gemini Live LLM settings. If provided together with deprecated top-level parameters, the ``settings`` values take precedence. @@ -716,7 +716,7 @@ class GeminiLiveLLMService(LLMService): ) # 1. Initialize default_settings with hardcoded defaults - default_settings = GeminiLiveLLMSettings( + default_settings = self.Settings( model="models/gemini-2.5-flash-native-audio-preview-12-2025", system_instruction=system_instruction, voice="Charon", @@ -742,15 +742,15 @@ class GeminiLiveLLMService(LLMService): # 2. Apply direct init arg overrides (deprecated) if model is not None: - _warn_deprecated_param("model", GeminiLiveLLMSettings, "model") + _warn_deprecated_param("model", self.Settings, "model") default_settings.model = model if voice_id != "Charon": - _warn_deprecated_param("voice_id", GeminiLiveLLMSettings, "voice") + _warn_deprecated_param("voice_id", self.Settings, "voice") default_settings.voice = voice_id # 3. Apply params overrides — only if settings not provided if params is not None: - _warn_deprecated_param("params", GeminiLiveLLMSettings) + _warn_deprecated_param("params", self.Settings) if not settings: default_settings.frequency_penalty = params.frequency_penalty default_settings.max_tokens = params.max_tokens diff --git a/src/pipecat/services/google/gemini_live/vertex/llm.py b/src/pipecat/services/google/gemini_live/vertex/llm.py index cdfde1660..c610b4cdb 100644 --- a/src/pipecat/services/google/gemini_live/vertex/llm.py +++ b/src/pipecat/services/google/gemini_live/vertex/llm.py @@ -20,7 +20,6 @@ from loguru import logger from pipecat.adapters.schemas.tools_schema import ToolsSchema from pipecat.services.google.gemini_live.llm import ( GeminiLiveLLMService, - GeminiLiveLLMSettings, GeminiMediaResolution, GeminiModalities, HttpOptions, @@ -43,7 +42,7 @@ except ModuleNotFoundError as e: @dataclass -class GeminiLiveVertexLLMSettings(GeminiLiveLLMSettings): +class GeminiLiveVertexLLMSettings(GeminiLiveLLMService.Settings): """Settings for GeminiLiveVertexLLMService.""" pass @@ -58,7 +57,7 @@ class GeminiLiveVertexLLMService(GeminiLiveLLMService): """ Settings = GeminiLiveVertexLLMSettings - _settings: GeminiLiveVertexLLMSettings + _settings: Settings def __init__( self, @@ -74,7 +73,7 @@ class GeminiLiveVertexLLMService(GeminiLiveLLMService): system_instruction: Optional[str] = None, tools: Optional[Union[List[dict], ToolsSchema]] = None, params: Optional[InputParams] = None, - settings: Optional[GeminiLiveVertexLLMSettings] = None, + settings: Optional[Settings] = None, inference_on_context_initialization: bool = True, file_api_base_url: str = "https://generativelanguage.googleapis.com/v1beta/files", http_options: Optional[HttpOptions] = None, @@ -90,12 +89,12 @@ class GeminiLiveVertexLLMService(GeminiLiveLLMService): model: Model identifier to use. .. deprecated:: 0.0.105 - Use ``settings=GeminiLiveLLMSettings(model=...)`` instead. + Use ``settings=GeminiLiveVertexLLMService.Settings(model=...)`` instead. voice_id: TTS voice identifier. Defaults to "Charon". .. deprecated:: 0.0.105 - Use ``settings=GeminiLiveVertexLLMSettings(voice=...)`` instead. + Use ``settings=GeminiLiveVertexLLMService.Settings(voice=...)`` instead. start_audio_paused: Whether to start with audio input paused. Defaults to False. start_video_paused: Whether to start with video input paused. Defaults to False. system_instruction: System prompt for the model. Defaults to None. @@ -104,7 +103,7 @@ class GeminiLiveVertexLLMService(GeminiLiveLLMService): location and project ID. .. deprecated:: 0.0.105 - Use ``settings=GeminiLiveLLMSettings(...)`` instead. + Use ``settings=GeminiLiveVertexLLMService.Settings(...)`` instead. settings: Gemini Live LLM settings. If provided together with deprecated top-level parameters, the ``settings`` values take precedence. @@ -136,7 +135,7 @@ class GeminiLiveVertexLLMService(GeminiLiveLLMService): # double deprecation warnings from the parent. # 1. Initialize default_settings with hardcoded defaults - default_settings = GeminiLiveVertexLLMSettings( + default_settings = self.Settings( model="google/gemini-live-2.5-flash-native-audio", voice="Charon", frequency_penalty=None, @@ -161,15 +160,15 @@ class GeminiLiveVertexLLMService(GeminiLiveLLMService): # 2. Apply direct init arg overrides (deprecated) if model is not None: - _warn_deprecated_param("model", GeminiLiveVertexLLMSettings, "model") + _warn_deprecated_param("model", self.Settings, "model") default_settings.model = model if voice_id != "Charon": - _warn_deprecated_param("voice_id", GeminiLiveVertexLLMSettings, "voice") + _warn_deprecated_param("voice_id", self.Settings, "voice") default_settings.voice = voice_id # 3. Apply params overrides — only if settings not provided if params is not None: - _warn_deprecated_param("params", GeminiLiveVertexLLMSettings) + _warn_deprecated_param("params", self.Settings) if not settings: default_settings.frequency_penalty = params.frequency_penalty default_settings.max_tokens = params.max_tokens diff --git a/src/pipecat/services/google/image.py b/src/pipecat/services/google/image.py index 5cf37aa4e..40706ad50 100644 --- a/src/pipecat/services/google/image.py +++ b/src/pipecat/services/google/image.py @@ -60,13 +60,13 @@ class GoogleImageGenService(ImageGenService): """ Settings = GoogleImageGenSettings - _settings: GoogleImageGenSettings + _settings: Settings class InputParams(BaseModel): """Configuration parameters for Google image generation. .. deprecated:: 0.0.105 - Use ``settings=GoogleImageGenSettings(...)`` instead. + Use ``settings=GoogleImageGenService.Settings(...)`` instead. Parameters: number_of_images: Number of images to generate (1-8). Defaults to 1. @@ -84,7 +84,7 @@ class GoogleImageGenService(ImageGenService): api_key: str, params: Optional[InputParams] = None, http_options: Optional[Any] = None, - settings: Optional[GoogleImageGenSettings] = None, + settings: Optional[Settings] = None, **kwargs, ): """Initialize the GoogleImageGenService with API key and parameters. @@ -94,7 +94,7 @@ class GoogleImageGenService(ImageGenService): params: Configuration parameters for image generation. .. deprecated:: 0.0.105 - Use ``settings=GoogleImageGenSettings(...)`` instead. + Use ``settings=GoogleImageGenService.Settings(...)`` instead. http_options: HTTP options for the client. settings: Runtime-updatable settings. When provided alongside deprecated @@ -102,7 +102,7 @@ class GoogleImageGenService(ImageGenService): **kwargs: Additional arguments passed to the parent ImageGenService. """ # 1. Initialize default_settings with hardcoded defaults - default_settings = GoogleImageGenSettings( + default_settings = self.Settings( model="imagen-3.0-generate-002", number_of_images=1, negative_prompt=None, @@ -110,7 +110,7 @@ class GoogleImageGenService(ImageGenService): # 2. Apply params overrides (deprecated) if params is not None: - _warn_deprecated_param("params", GoogleImageGenSettings) + _warn_deprecated_param("params", self.Settings) if not settings: default_settings.model = params.model default_settings.number_of_images = params.number_of_images diff --git a/src/pipecat/services/google/llm.py b/src/pipecat/services/google/llm.py index cf9e91b53..2ade23906 100644 --- a/src/pipecat/services/google/llm.py +++ b/src/pipecat/services/google/llm.py @@ -743,7 +743,7 @@ class GoogleLLMService(LLMService): """ Settings = GoogleLLMSettings - _settings: GoogleLLMSettings + _settings: Settings # Overriding the default adapter to use the Gemini one. adapter_class = GeminiLLMAdapter @@ -755,7 +755,7 @@ class GoogleLLMService(LLMService): """Input parameters for Google AI models. .. deprecated:: 0.0.105 - Use ``settings=GoogleLLMSettings(...)`` instead. + Use ``settings=GoogleLLMService.Settings(...)`` instead. Parameters: max_tokens: Maximum number of tokens to generate. @@ -784,7 +784,7 @@ class GoogleLLMService(LLMService): api_key: str, model: Optional[str] = None, params: Optional[InputParams] = None, - settings: Optional[GoogleLLMSettings] = None, + settings: Optional[Settings] = None, system_instruction: Optional[str] = None, tools: Optional[List[Dict[str, Any]]] = None, tool_config: Optional[Dict[str, Any]] = None, @@ -798,12 +798,12 @@ class GoogleLLMService(LLMService): model: Model name to use. .. deprecated:: 0.0.105 - Use ``settings=GoogleLLMSettings(model=...)`` instead. + Use ``settings=GoogleLLMService.Settings(model=...)`` instead. params: Optional model parameters for inference. .. deprecated:: 0.0.105 - Use ``settings=GoogleLLMSettings(...)`` instead. + Use ``settings=GoogleLLMService.Settings(...)`` instead. settings: Runtime-updatable settings for this service. When both deprecated parameters and *settings* are provided, *settings* @@ -811,14 +811,14 @@ class GoogleLLMService(LLMService): system_instruction: System instruction/prompt for the model. .. deprecated:: 0.0.105 - Use ``settings=GoogleLLMSettings(system_instruction=...)`` instead. + Use ``settings=GoogleLLMService.Settings(system_instruction=...)`` instead. tools: List of available tools/functions. tool_config: Configuration for tool usage. http_options: HTTP options for the client. **kwargs: Additional arguments passed to parent class. """ # 1. Initialize default_settings with hardcoded defaults - default_settings = GoogleLLMSettings( + default_settings = self.Settings( model="gemini-2.5-flash", system_instruction=None, max_tokens=4096, @@ -836,15 +836,15 @@ class GoogleLLMService(LLMService): # 2. Apply direct init arg overrides (deprecated) if model is not None: - _warn_deprecated_param("model", GoogleLLMSettings, "model") + _warn_deprecated_param("model", self.Settings, "model") default_settings.model = model if system_instruction is not None: - _warn_deprecated_param("system_instruction", GoogleLLMSettings, "system_instruction") + _warn_deprecated_param("system_instruction", self.Settings, "system_instruction") default_settings.system_instruction = system_instruction # 3. Apply params overrides — only if settings not provided if params is not None: - _warn_deprecated_param("params", GoogleLLMSettings) + _warn_deprecated_param("params", self.Settings) if not settings: default_settings.max_tokens = params.max_tokens default_settings.temperature = params.temperature diff --git a/src/pipecat/services/google/openai/llm.py b/src/pipecat/services/google/openai/llm.py index cd5e0f060..717c1e379 100644 --- a/src/pipecat/services/google/openai/llm.py +++ b/src/pipecat/services/google/openai/llm.py @@ -28,13 +28,13 @@ from loguru import logger from pipecat.frames.frames import LLMTextFrame from pipecat.metrics.metrics import LLMTokenUsage from pipecat.processors.aggregators.openai_llm_context import OpenAILLMContext -from pipecat.services.openai.base_llm import OpenAILLMSettings +from pipecat.services.openai.base_llm import BaseOpenAILLMService from pipecat.services.openai.llm import OpenAILLMService from pipecat.services.settings import _warn_deprecated_param @dataclass -class GoogleOpenAILLMSettings(OpenAILLMSettings): +class GoogleOpenAILLMSettings(BaseOpenAILLMService.Settings): """Settings for GoogleLLMOpenAIBetaService.""" pass @@ -59,7 +59,7 @@ class GoogleLLMOpenAIBetaService(OpenAILLMService): """ Settings = GoogleOpenAILLMSettings - _settings: GoogleOpenAILLMSettings + _settings: Settings def __init__( self, @@ -67,7 +67,7 @@ class GoogleLLMOpenAIBetaService(OpenAILLMService): api_key: str, base_url: str = "https://generativelanguage.googleapis.com/v1beta/openai/", model: Optional[str] = None, - settings: Optional[GoogleOpenAILLMSettings] = None, + settings: Optional[Settings] = None, **kwargs, ): """Initialize the Google LLM service. @@ -78,7 +78,7 @@ class GoogleLLMOpenAIBetaService(OpenAILLMService): model: Google model name to use (e.g., "gemini-2.0-flash"). .. deprecated:: 0.0.105 - Use ``settings=OpenAILLMSettings(model=...)`` instead. + Use ``settings=GoogleLLMOpenAIBetaService.Settings(model=...)`` instead. settings: Runtime-updatable settings. When provided alongside deprecated parameters, ``settings`` values take precedence. @@ -96,11 +96,11 @@ class GoogleLLMOpenAIBetaService(OpenAILLMService): ) # 1. Initialize default_settings with hardcoded defaults - default_settings = GoogleOpenAILLMSettings(model="gemini-2.0-flash") + default_settings = self.Settings(model="gemini-2.0-flash") # 2. Apply direct init arg overrides (deprecated) if model is not None: - _warn_deprecated_param("model", GoogleOpenAILLMSettings, "model") + _warn_deprecated_param("model", self.Settings, "model") default_settings.model = model # 3. (No step 3, as there's no params object to apply) diff --git a/src/pipecat/services/google/stt.py b/src/pipecat/services/google/stt.py index 70e51ac3c..cab176668 100644 --- a/src/pipecat/services/google/stt.py +++ b/src/pipecat/services/google/stt.py @@ -415,7 +415,7 @@ class GoogleSTTService(STTService): """ Settings = GoogleSTTSettings - _settings: GoogleSTTSettings + _settings: Settings # Google Cloud's STT service has a connection time limit of 5 minutes per stream. # They've shared an "endless streaming" example that guided this implementation: @@ -427,7 +427,7 @@ class GoogleSTTService(STTService): """Configuration parameters for Google Speech-to-Text. .. deprecated:: 0.0.105 - Use ``settings=GoogleSTTSettings(...)`` instead. + Use ``settings=GoogleSTTService.Settings(...)`` instead. Parameters: languages: Single language or list of recognition languages. First language is primary. @@ -488,7 +488,7 @@ class GoogleSTTService(STTService): location: str = "global", sample_rate: Optional[int] = None, params: Optional[InputParams] = None, - settings: Optional[GoogleSTTSettings] = None, + settings: Optional[Settings] = None, ttfs_p99_latency: Optional[float] = GOOGLE_TTFS_P99, **kwargs, ): @@ -502,7 +502,7 @@ class GoogleSTTService(STTService): params: Configuration parameters for the service. .. deprecated:: 0.0.105 - Use ``settings=GoogleSTTSettings(...)`` instead. + Use ``settings=GoogleSTTService.Settings(...)`` instead. settings: Runtime-updatable settings. When provided alongside deprecated ``params``, ``settings`` values take precedence. @@ -511,7 +511,7 @@ class GoogleSTTService(STTService): **kwargs: Additional arguments passed to STTService. """ # 1. Initialize default_settings with hardcoded defaults - default_settings = GoogleSTTSettings( + default_settings = self.Settings( language=None, languages=[Language.EN_US], language_codes=None, @@ -531,7 +531,7 @@ class GoogleSTTService(STTService): # 3. Apply params overrides — only if settings not provided if params is not None: - _warn_deprecated_param("params", GoogleSTTSettings) + _warn_deprecated_param("params", self.Settings) if not settings: default_settings.languages = list(params.language_list) default_settings.model = params.model @@ -655,7 +655,7 @@ class GoogleSTTService(STTService): """Update the service's recognition languages. .. deprecated:: 0.0.104 - Use ``STTUpdateSettingsFrame`` with ``GoogleSTTSettings(languages=...)`` + Use ``STTUpdateSettingsFrame`` with ``GoogleSTTService.Settings(languages=...)`` instead. Args: @@ -665,13 +665,13 @@ class GoogleSTTService(STTService): warnings.simplefilter("always") warnings.warn( "set_languages() is deprecated. Use STTUpdateSettingsFrame with " - "GoogleSTTSettings(languages=...) instead.", + "self.Settings(languages=...) instead.", DeprecationWarning, ) logger.debug(f"Switching STT languages to: {languages}") - await self._update_settings(GoogleSTTSettings(languages=list(languages))) + await self._update_settings(self.Settings(languages=list(languages))) - async def _update_settings(self, delta: GoogleSTTSettings) -> dict[str, Any]: + async def _update_settings(self, delta: Settings) -> dict[str, Any]: """Apply settings delta and reconnect if anything changed. Handles ``language`` from base ``set_language`` by converting it to @@ -698,8 +698,8 @@ class GoogleSTTService(STTService): with warnings.catch_warnings(): warnings.simplefilter("always") warnings.warn( - "GoogleSTTSettings.language_codes is deprecated. " - "Use GoogleSTTSettings.languages (List[Language]) instead.", + "self.Settings.language_codes is deprecated. " + "Use self.Settings.languages (List[Language]) instead.", DeprecationWarning, stacklevel=2, ) @@ -756,7 +756,7 @@ class GoogleSTTService(STTService): """Update service options dynamically. .. deprecated:: - Use ``STTUpdateSettingsFrame`` with ``GoogleSTTSettings(...)`` + Use ``STTUpdateSettingsFrame`` with ``GoogleSTTService.Settings(...)`` instead. Args: @@ -780,11 +780,11 @@ class GoogleSTTService(STTService): warnings.simplefilter("always") warnings.warn( "update_options() is deprecated. Use STTUpdateSettingsFrame with " - "GoogleSTTSettings(...) instead.", + "self.Settings(...) instead.", DeprecationWarning, ) # Build a settings delta from the provided options - delta = GoogleSTTSettings() + delta = self.Settings() if languages is not None: delta.languages = list(languages) diff --git a/src/pipecat/services/google/tts.py b/src/pipecat/services/google/tts.py index 9d92c91ea..c2e32ad3c 100644 --- a/src/pipecat/services/google/tts.py +++ b/src/pipecat/services/google/tts.py @@ -523,7 +523,7 @@ class GoogleTTSSettings(TTSSettings): #: .. deprecated:: 0.0.105 -#: Use ``GoogleTTSSettings`` instead. +#: Use ``GoogleTTSService.Settings`` instead. GoogleStreamTTSSettings = GoogleTTSSettings @@ -559,13 +559,13 @@ class GoogleHttpTTSService(TTSService): """ Settings = GoogleHttpTTSSettings - _settings: GoogleHttpTTSSettings + _settings: Settings class InputParams(BaseModel): """Input parameters for Google HTTP TTS voice customization. .. deprecated:: 0.0.105 - Use ``GoogleHttpTTSSettings`` directly via the ``settings`` parameter instead. + Use ``GoogleHttpTTSService.Settings`` directly via the ``settings`` parameter instead. Parameters: pitch: Voice pitch adjustment (e.g., "+2st", "-50%"). @@ -596,7 +596,7 @@ class GoogleHttpTTSService(TTSService): voice_id: Optional[str] = None, sample_rate: Optional[int] = None, params: Optional[InputParams] = None, - settings: Optional[GoogleHttpTTSSettings] = None, + settings: Optional[Settings] = None, **kwargs, ): """Initializes the Google HTTP TTS service. @@ -608,20 +608,20 @@ class GoogleHttpTTSService(TTSService): voice_id: Google TTS voice identifier (e.g., "en-US-Standard-A"). .. deprecated:: 0.0.105 - Use ``settings=GoogleHttpTTSSettings(voice=...)`` instead. + Use ``settings=GoogleHttpTTSService.Settings(voice=...)`` instead. sample_rate: Audio sample rate in Hz. If None, uses default. params: Voice customization parameters including pitch, rate, volume, etc. .. deprecated:: 0.0.105 - Use ``settings=GoogleHttpTTSSettings(...)`` instead. + Use ``settings=GoogleHttpTTSService.Settings(...)`` instead. settings: Runtime-updatable settings. When provided alongside deprecated parameters, ``settings`` values take precedence. **kwargs: Additional arguments passed to parent TTSService. """ # 1. Initialize default_settings with hardcoded defaults - default_settings = GoogleHttpTTSSettings( + default_settings = self.Settings( model=None, voice="en-US-Chirp3-HD-Charon", language="en-US", @@ -636,12 +636,12 @@ class GoogleHttpTTSService(TTSService): # 2. Apply direct init arg overrides (deprecated) if voice_id is not None: - _warn_deprecated_param("voice_id", GoogleHttpTTSSettings, "voice") + _warn_deprecated_param("voice_id", self.Settings, "voice") default_settings.voice = voice_id # 3. Apply params overrides — only if settings not provided if params is not None: - _warn_deprecated_param("params", GoogleHttpTTSSettings) + _warn_deprecated_param("params", self.Settings) if not settings: if params.pitch is not None: default_settings.pitch = params.pitch @@ -747,7 +747,7 @@ class GoogleHttpTTSService(TTSService): Args: delta: Settings delta. Can include 'speaking_rate' (float). """ - if isinstance(delta, GoogleHttpTTSSettings) and is_given(delta.speaking_rate): + if isinstance(delta, self.Settings) and is_given(delta.speaking_rate): rate_value = float(delta.speaking_rate) if not (0.25 <= rate_value <= 2.0): logger.warning( @@ -1022,13 +1022,13 @@ class GoogleTTSService(GoogleBaseTTSService): """ Settings = GoogleTTSSettings - _settings: GoogleTTSSettings + _settings: Settings class InputParams(BaseModel): """Input parameters for Google streaming TTS configuration. .. deprecated:: 0.0.105 - Use ``GoogleTTSSettings`` directly via the ``settings`` parameter instead. + Use ``GoogleTTSService.Settings`` directly via the ``settings`` parameter instead. Parameters: language: Language for synthesis. Defaults to English. @@ -1048,7 +1048,7 @@ class GoogleTTSService(GoogleBaseTTSService): voice_cloning_key: Optional[str] = None, sample_rate: Optional[int] = None, params: Optional[InputParams] = None, - settings: Optional[GoogleTTSSettings] = None, + settings: Optional[Settings] = None, **kwargs, ): """Initializes the Google streaming TTS service. @@ -1060,21 +1060,21 @@ class GoogleTTSService(GoogleBaseTTSService): voice_id: Google TTS voice identifier (e.g., "en-US-Chirp3-HD-Charon"). .. deprecated:: 0.0.105 - Use ``settings=GoogleTTSSettings(voice=...)`` instead. + Use ``settings=GoogleTTSService.Settings(voice=...)`` instead. voice_cloning_key: The voice cloning key for Chirp 3 custom voices. sample_rate: Audio sample rate in Hz. If None, uses default. params: Language configuration parameters. .. deprecated:: 0.0.105 - Use ``settings=GoogleTTSSettings(...)`` instead. + Use ``settings=GoogleTTSService.Settings(...)`` instead. settings: Runtime-updatable settings. When provided alongside deprecated parameters, ``settings`` values take precedence. **kwargs: Additional arguments passed to parent TTSService. """ # 1. Initialize default_settings with hardcoded defaults - default_settings = GoogleTTSSettings( + default_settings = self.Settings( model=None, voice="en-US-Chirp3-HD-Charon", language="en-US", @@ -1083,12 +1083,12 @@ class GoogleTTSService(GoogleBaseTTSService): # 2. Apply direct init arg overrides (deprecated) if voice_id is not None: - _warn_deprecated_param("voice_id", GoogleTTSSettings, "voice") + _warn_deprecated_param("voice_id", self.Settings, "voice") default_settings.voice = voice_id # 3. Apply params overrides — only if settings not provided if params is not None: - _warn_deprecated_param("params", GoogleTTSSettings) + _warn_deprecated_param("params", self.Settings) if not settings: if params.language is not None: default_settings.language = self.language_to_service_language(params.language) @@ -1119,7 +1119,7 @@ class GoogleTTSService(GoogleBaseTTSService): Args: delta: Settings delta. Can include 'speaking_rate' (float). """ - if isinstance(delta, GoogleTTSSettings) and is_given(delta.speaking_rate): + if isinstance(delta, self.Settings) and is_given(delta.speaking_rate): rate_value = float(delta.speaking_rate) if not (0.25 <= rate_value <= 2.0): logger.warning( @@ -1201,7 +1201,7 @@ class GeminiTTSService(GoogleBaseTTSService): """ Settings = GeminiTTSSettings - _settings: GeminiTTSSettings + _settings: Settings GOOGLE_SAMPLE_RATE = 24000 # Google TTS always outputs at 24kHz @@ -1243,7 +1243,7 @@ class GeminiTTSService(GoogleBaseTTSService): """Input parameters for Gemini TTS configuration. .. deprecated:: 0.0.105 - Use ``GeminiTTSSettings`` directly via the ``settings`` parameter instead. + Use ``GeminiTTSService.Settings`` directly via the ``settings`` parameter instead. Parameters: language: Language for synthesis. Defaults to English. @@ -1268,7 +1268,7 @@ class GeminiTTSService(GoogleBaseTTSService): voice_id: Optional[str] = None, sample_rate: Optional[int] = None, params: Optional[InputParams] = None, - settings: Optional[GeminiTTSSettings] = None, + settings: Optional[Settings] = None, **kwargs, ): """Initializes the Gemini TTS service. @@ -1284,7 +1284,7 @@ class GeminiTTSService(GoogleBaseTTSService): "gemini-2.5-flash-tts" or "gemini-2.5-pro-tts". .. deprecated:: 0.0.105 - Use ``settings=GeminiTTSSettings(model=...)`` instead. + Use ``settings=GeminiTTSService.Settings(model=...)`` instead. credentials: JSON string containing Google Cloud service account credentials. credentials_path: Path to Google Cloud service account JSON file. @@ -1292,13 +1292,13 @@ class GeminiTTSService(GoogleBaseTTSService): voice_id: Voice name from the available Gemini voices. .. deprecated:: 0.0.105 - Use ``settings=GeminiTTSSettings(voice=...)`` instead. + Use ``settings=GeminiTTSService.Settings(voice=...)`` instead. sample_rate: Audio sample rate in Hz. If None, uses Google's default 24kHz. params: TTS configuration parameters. .. deprecated:: 0.0.105 - Use ``settings=GeminiTTSSettings(...)`` instead. + Use ``settings=GeminiTTSService.Settings(...)`` instead. settings: Runtime-updatable settings. When provided alongside deprecated parameters, ``settings`` values take precedence. @@ -1320,7 +1320,7 @@ class GeminiTTSService(GoogleBaseTTSService): ) # 1. Initialize default_settings with hardcoded defaults - default_settings = GeminiTTSSettings( + default_settings = self.Settings( model="gemini-2.5-flash-tts", voice="Kore", language="en-US", @@ -1331,10 +1331,10 @@ class GeminiTTSService(GoogleBaseTTSService): # 2. Apply direct init arg overrides (deprecated) if model is not None: - _warn_deprecated_param("model", GeminiTTSSettings, "model") + _warn_deprecated_param("model", self.Settings, "model") default_settings.model = model if voice_id is not None: - _warn_deprecated_param("voice_id", GeminiTTSSettings, "voice") + _warn_deprecated_param("voice_id", self.Settings, "voice") default_settings.voice = voice_id if default_settings.voice not in self.AVAILABLE_VOICES: @@ -1344,7 +1344,7 @@ class GeminiTTSService(GoogleBaseTTSService): # 3. Apply params overrides — only if settings not provided if params is not None: - _warn_deprecated_param("params", GeminiTTSSettings) + _warn_deprecated_param("params", self.Settings) if not settings: if params.language is not None: default_settings.language = self.language_to_service_language(params.language) diff --git a/src/pipecat/services/google/vertex/llm.py b/src/pipecat/services/google/vertex/llm.py index 3901b5d50..014dea405 100644 --- a/src/pipecat/services/google/vertex/llm.py +++ b/src/pipecat/services/google/vertex/llm.py @@ -21,7 +21,7 @@ from typing import Optional from loguru import logger -from pipecat.services.google.llm import GoogleLLMService, GoogleLLMSettings +from pipecat.services.google.llm import GoogleLLMService from pipecat.services.settings import _warn_deprecated_param try: @@ -41,7 +41,7 @@ except ModuleNotFoundError as e: @dataclass -class GoogleVertexLLMSettings(GoogleLLMSettings): +class GoogleVertexLLMSettings(GoogleLLMService.Settings): """Settings for GoogleVertexLLMService.""" pass @@ -60,7 +60,7 @@ class GoogleVertexLLMService(GoogleLLMService): """ Settings = GoogleVertexLLMSettings - _settings: GoogleVertexLLMSettings + _settings: Settings class InputParams(GoogleLLMService.InputParams): """Input parameters specific to Vertex AI. @@ -115,7 +115,7 @@ class GoogleVertexLLMService(GoogleLLMService): location: Optional[str] = None, project_id: Optional[str] = None, params: Optional[GoogleLLMService.InputParams] = None, - settings: Optional[GoogleVertexLLMSettings] = None, + settings: Optional[Settings] = None, system_instruction: Optional[str] = None, tools: Optional[list] = None, tool_config: Optional[dict] = None, @@ -130,14 +130,14 @@ class GoogleVertexLLMService(GoogleLLMService): model: Model identifier (e.g., "gemini-2.5-flash"). .. deprecated:: 0.0.105 - Use ``settings=GoogleLLMSettings(model=...)`` instead. + Use ``settings=GoogleVertexLLMService.Settings(model=...)`` instead. location: GCP region for Vertex AI endpoint (e.g., "us-east4"). project_id: Google Cloud project ID. params: Input parameters for the model. .. deprecated:: 0.0.105 - Use ``settings=GoogleLLMSettings(...)`` instead. + Use ``settings=GoogleVertexLLMService.Settings(...)`` instead. settings: Runtime-updatable settings for this service. When both deprecated parameters and *settings* are provided, *settings* @@ -145,7 +145,7 @@ class GoogleVertexLLMService(GoogleLLMService): system_instruction: System instruction/prompt for the model. .. deprecated:: 0.0.105 - Use ``settings=GoogleVertexLLMSettings(system_instruction=...)`` instead. + Use ``settings=GoogleVertexLLMService.Settings(system_instruction=...)`` instead. tools: List of available tools/functions. tool_config: Configuration for tool usage. http_options: HTTP options for the client. @@ -197,7 +197,7 @@ class GoogleVertexLLMService(GoogleLLMService): self._location = location # 1. Initialize default_settings with hardcoded defaults - default_settings = GoogleVertexLLMSettings( + default_settings = self.Settings( model="gemini-2.5-flash", system_instruction=None, max_tokens=4096, @@ -215,17 +215,15 @@ class GoogleVertexLLMService(GoogleLLMService): # 2. Apply direct init arg overrides (deprecated) if model is not None: - _warn_deprecated_param("model", GoogleVertexLLMSettings, "model") + _warn_deprecated_param("model", self.Settings, "model") default_settings.model = model if system_instruction is not None: - _warn_deprecated_param( - "system_instruction", GoogleVertexLLMSettings, "system_instruction" - ) + _warn_deprecated_param("system_instruction", self.Settings, "system_instruction") default_settings.system_instruction = system_instruction # 3. Apply params overrides — only if settings not provided if params is not None: - _warn_deprecated_param("params", GoogleVertexLLMSettings) + _warn_deprecated_param("params", self.Settings) if not settings: default_settings.max_tokens = params.max_tokens default_settings.temperature = params.temperature diff --git a/src/pipecat/services/gradium/stt.py b/src/pipecat/services/gradium/stt.py index 3fddf0470..90d1e800f 100644 --- a/src/pipecat/services/gradium/stt.py +++ b/src/pipecat/services/gradium/stt.py @@ -89,13 +89,13 @@ class GradiumSTTService(WebsocketSTTService): """ Settings = GradiumSTTSettings - _settings: GradiumSTTSettings + _settings: Settings class InputParams(BaseModel): """Configuration parameters for Gradium STT API. .. deprecated:: 0.0.105 - Use ``settings=GradiumSTTSettings(...)`` instead. + Use ``settings=GradiumSTTService.Settings(...)`` instead. Parameters: language: Expected language of the audio (e.g., "en", "es", "fr"). @@ -117,7 +117,7 @@ class GradiumSTTService(WebsocketSTTService): api_endpoint_base_url: str = "wss://eu.api.gradium.ai/api/speech/asr", params: Optional[InputParams] = None, json_config: Optional[str] = None, - settings: Optional[GradiumSTTSettings] = None, + settings: Optional[Settings] = None, ttfs_p99_latency: Optional[float] = GRADIUM_TTFS_P99, **kwargs, ): @@ -129,7 +129,7 @@ class GradiumSTTService(WebsocketSTTService): params: Configuration parameters for language and delay settings. .. deprecated:: 0.0.105 - Use ``settings=GradiumSTTSettings(...)`` instead. + Use ``settings=GradiumSTTService.Settings(...)`` instead. json_config: Optional JSON configuration string for additional model settings. @@ -152,7 +152,7 @@ class GradiumSTTService(WebsocketSTTService): ) # 1. Initialize default_settings with hardcoded defaults - default_settings = GradiumSTTSettings( + default_settings = self.Settings( model=None, language=None, delay_in_frames=None, @@ -162,7 +162,7 @@ class GradiumSTTService(WebsocketSTTService): # 3. Apply params overrides — only if settings not provided if params is not None: - _warn_deprecated_param("params", GradiumSTTSettings) + _warn_deprecated_param("params", self.Settings) if not settings: default_settings.language = params.language if params.delay_in_frames is not None: @@ -207,7 +207,7 @@ class GradiumSTTService(WebsocketSTTService): """Apply a settings delta, sync params, and reconnect. Args: - delta: A :class:`STTSettings` (or ``GradiumSTTSettings``) delta. + delta: A :class:`STTSettings` (or ``GradiumSTTService.Settings``) delta. Returns: Dict mapping changed field names to their previous values. diff --git a/src/pipecat/services/gradium/tts.py b/src/pipecat/services/gradium/tts.py index 03b4d7008..43114b193 100644 --- a/src/pipecat/services/gradium/tts.py +++ b/src/pipecat/services/gradium/tts.py @@ -48,13 +48,13 @@ class GradiumTTSService(WebsocketTTSService): """Text-to-Speech service using Gradium's websocket API.""" Settings = GradiumTTSSettings - _settings: GradiumTTSSettings + _settings: Settings class InputParams(BaseModel): """Configuration parameters for Gradium TTS service. .. deprecated:: 0.0.105 - Use ``GradiumTTSSettings`` directly via the ``settings`` parameter instead. + Use ``GradiumTTSService.Settings`` directly via the ``settings`` parameter instead. Parameters: temp: Temperature to be used for generation, defaults to 0.6. @@ -71,7 +71,7 @@ class GradiumTTSService(WebsocketTTSService): model: Optional[str] = None, json_config: Optional[str] = None, params: Optional[InputParams] = None, - settings: Optional[GradiumTTSSettings] = None, + settings: Optional[Settings] = None, **kwargs, ): """Initialize the Gradium TTS service. @@ -81,26 +81,26 @@ class GradiumTTSService(WebsocketTTSService): voice_id: the voice identifier. .. deprecated:: 0.0.105 - Use ``settings=GradiumTTSSettings(voice=...)`` instead. + Use ``settings=GradiumTTSService.Settings(voice=...)`` instead. url: Gradium websocket API endpoint. model: Model ID to use for synthesis. .. deprecated:: 0.0.105 - Use ``settings=GradiumTTSSettings(model=...)`` instead. + Use ``settings=GradiumTTSService.Settings(model=...)`` instead. json_config: Optional JSON configuration string for additional model settings. params: Additional configuration parameters. .. deprecated:: 0.0.105 - Use ``settings=GradiumTTSSettings(...)`` instead. + Use ``settings=GradiumTTSService.Settings(...)`` instead. settings: Runtime-updatable settings. When provided alongside deprecated parameters, ``settings`` values take precedence. **kwargs: Additional arguments passed to parent class. """ # 1. Initialize default_settings with hardcoded defaults - default_settings = GradiumTTSSettings( + default_settings = self.Settings( model="default", voice="YTpq7expH9539ERJ", language=None, @@ -108,15 +108,15 @@ class GradiumTTSService(WebsocketTTSService): # 2. Apply direct init arg overrides (deprecated) if model is not None: - _warn_deprecated_param("model", GradiumTTSSettings, "model") + _warn_deprecated_param("model", self.Settings, "model") default_settings.model = model if voice_id is not None: - _warn_deprecated_param("voice_id", GradiumTTSSettings, "voice") + _warn_deprecated_param("voice_id", self.Settings, "voice") default_settings.voice = voice_id # 3. Apply params overrides — only if settings not provided if params is not None: - _warn_deprecated_param("params", GradiumTTSSettings) + _warn_deprecated_param("params", self.Settings) # Note: params.temp has no corresponding settings field # 4. Apply settings delta (canonical API, always wins) @@ -153,7 +153,7 @@ class GradiumTTSService(WebsocketTTSService): """Apply a settings delta and reconnect if voice changed. Args: - delta: A :class:`TTSSettings` (or ``GradiumTTSSettings``) delta. + delta: A :class:`TTSSettings` (or ``GradiumTTSService.Settings``) delta. Returns: Dict mapping changed field names to their previous values. diff --git a/src/pipecat/services/grok/llm.py b/src/pipecat/services/grok/llm.py index 255ee2cf5..3eaf0646a 100644 --- a/src/pipecat/services/grok/llm.py +++ b/src/pipecat/services/grok/llm.py @@ -23,7 +23,7 @@ from pipecat.processors.aggregators.llm_response import ( LLMUserAggregatorParams, ) from pipecat.processors.aggregators.openai_llm_context import OpenAILLMContext -from pipecat.services.openai.base_llm import OpenAILLMSettings +from pipecat.services.openai.base_llm import BaseOpenAILLMService from pipecat.services.openai.llm import ( OpenAIAssistantContextAggregator, OpenAILLMService, @@ -71,7 +71,7 @@ class GrokContextAggregatorPair: @dataclass -class GrokLLMSettings(OpenAILLMSettings): +class GrokLLMSettings(BaseOpenAILLMService.Settings): """Settings for GrokLLMService.""" pass @@ -87,7 +87,7 @@ class GrokLLMService(OpenAILLMService): """ Settings = GrokLLMSettings - _settings: GrokLLMSettings + _settings: Settings def __init__( self, @@ -95,7 +95,7 @@ class GrokLLMService(OpenAILLMService): api_key: str, base_url: str = "https://api.x.ai/v1", model: Optional[str] = None, - settings: Optional[GrokLLMSettings] = None, + settings: Optional[Settings] = None, **kwargs, ): """Initialize the GrokLLMService with API key and model. @@ -106,18 +106,18 @@ class GrokLLMService(OpenAILLMService): model: The model identifier to use. Defaults to "grok-3-beta". .. deprecated:: 0.0.105 - Use ``settings=OpenAILLMSettings(model=...)`` instead. + Use ``settings=GrokLLMService.Settings(model=...)`` instead. settings: Runtime-updatable settings. When provided alongside deprecated parameters, ``settings`` values take precedence. **kwargs: Additional keyword arguments passed to OpenAILLMService. """ # 1. Initialize default_settings with hardcoded defaults - default_settings = GrokLLMSettings(model="grok-3-beta") + default_settings = self.Settings(model="grok-3-beta") # 2. Apply direct init arg overrides (deprecated) if model is not None: - _warn_deprecated_param("model", GrokLLMSettings, "model") + _warn_deprecated_param("model", self.Settings, "model") default_settings.model = model # 3. (No step 3, as there's no params object to apply) diff --git a/src/pipecat/services/grok/realtime/llm.py b/src/pipecat/services/grok/realtime/llm.py index 9063ac22c..dcd7ac59e 100644 --- a/src/pipecat/services/grok/realtime/llm.py +++ b/src/pipecat/services/grok/realtime/llm.py @@ -109,7 +109,7 @@ class GrokRealtimeLLMSettings(LLMSettings): # -- Bidirectional sync helpers ------------------------------------------ @staticmethod - def _sync_top_level_to_sp(settings: "GrokRealtimeLLMSettings"): + def _sync_top_level_to_sp(settings: "GrokRealtimeLLMService.Settings"): """Push top-level ``system_instruction`` into ``session_properties``.""" if not is_given(settings.session_properties): return @@ -119,7 +119,7 @@ class GrokRealtimeLLMSettings(LLMSettings): # -- apply_update override ----------------------------------------------- - def apply_update(self, delta: "GrokRealtimeLLMSettings") -> Dict[str, Any]: + def apply_update(self, delta: "GrokRealtimeLLMService.Settings") -> Dict[str, Any]: """Merge a delta, keeping ``system_instruction`` in sync with SP. When the delta contains ``session_properties``, it **replaces** the @@ -151,8 +151,8 @@ class GrokRealtimeLLMSettings(LLMSettings): @classmethod def from_mapping( - cls: Type["GrokRealtimeLLMSettings"], settings: Mapping[str, Any] - ) -> "GrokRealtimeLLMSettings": + cls: Type["GrokRealtimeLLMService.Settings"], settings: Mapping[str, Any] + ) -> "GrokRealtimeLLMService.Settings": """Build a delta from a plain dict, routing SP keys into ``session_properties``. Keys that correspond to ``SessionProperties`` fields are collected into @@ -203,7 +203,7 @@ class GrokRealtimeLLMService(LLMService): """ Settings = GrokRealtimeLLMSettings - _settings: GrokRealtimeLLMSettings + _settings: Settings # Use the Grok-specific adapter adapter_class = GrokRealtimeLLMAdapter @@ -214,7 +214,7 @@ class GrokRealtimeLLMService(LLMService): api_key: str, base_url: str = "wss://api.x.ai/v1/realtime", session_properties: Optional[events.SessionProperties] = None, - settings: Optional[GrokRealtimeLLMSettings] = None, + settings: Optional[Settings] = None, start_audio_paused: bool = False, **kwargs, ): @@ -228,7 +228,7 @@ class GrokRealtimeLLMService(LLMService): If None, uses default SessionProperties with voice "Ara". .. deprecated:: 0.0.105 - Use ``settings=GrokRealtimeLLMSettings(session_properties=...)`` + Use ``settings=GrokRealtimeLLMService.Settings(session_properties=...)`` instead. To set a different voice, configure it in session_properties: @@ -241,7 +241,7 @@ class GrokRealtimeLLMService(LLMService): **kwargs: Additional arguments passed to parent LLMService. """ # 1. Initialize default_settings with hardcoded defaults - default_settings = GrokRealtimeLLMSettings( + default_settings = self.Settings( model=None, system_instruction=None, temperature=None, @@ -260,7 +260,7 @@ class GrokRealtimeLLMService(LLMService): if session_properties is not None: _warn_deprecated_param( "session_properties", - GrokRealtimeLLMSettings, + self.Settings, "session_properties", ) default_settings.session_properties = session_properties @@ -269,7 +269,7 @@ class GrokRealtimeLLMService(LLMService): default_settings.system_instruction = session_properties.instructions # Sync top-level system_instruction back into session_properties - GrokRealtimeLLMSettings._sync_top_level_to_sp(default_settings) + self.Settings._sync_top_level_to_sp(default_settings) # 3. Apply settings delta (canonical API, always wins) if settings is not None: diff --git a/src/pipecat/services/groq/llm.py b/src/pipecat/services/groq/llm.py index 6669c385a..8b6bdc3bc 100644 --- a/src/pipecat/services/groq/llm.py +++ b/src/pipecat/services/groq/llm.py @@ -11,13 +11,13 @@ from typing import Optional from loguru import logger -from pipecat.services.openai.base_llm import OpenAILLMSettings +from pipecat.services.openai.base_llm import BaseOpenAILLMService from pipecat.services.openai.llm import OpenAILLMService from pipecat.services.settings import _warn_deprecated_param @dataclass -class GroqLLMSettings(OpenAILLMSettings): +class GroqLLMSettings(BaseOpenAILLMService.Settings): """Settings for GroqLLMService.""" pass @@ -31,7 +31,7 @@ class GroqLLMService(OpenAILLMService): """ Settings = GroqLLMSettings - _settings: GroqLLMSettings + _settings: Settings def __init__( self, @@ -39,7 +39,7 @@ class GroqLLMService(OpenAILLMService): api_key: str, base_url: str = "https://api.groq.com/openai/v1", model: Optional[str] = None, - settings: Optional[GroqLLMSettings] = None, + settings: Optional[Settings] = None, **kwargs, ): """Initialize Groq LLM service. @@ -50,18 +50,18 @@ class GroqLLMService(OpenAILLMService): model: The model identifier to use. Defaults to "llama-3.3-70b-versatile". .. deprecated:: 0.0.105 - Use ``settings=OpenAILLMSettings(model=...)`` instead. + Use ``settings=GroqLLMService.Settings(model=...)`` instead. settings: Runtime-updatable settings. When provided alongside deprecated parameters, ``settings`` values take precedence. **kwargs: Additional keyword arguments passed to OpenAILLMService. """ # 1. Initialize default_settings with hardcoded defaults - default_settings = GroqLLMSettings(model="llama-3.3-70b-versatile") + default_settings = self.Settings(model="llama-3.3-70b-versatile") # 2. Apply direct init arg overrides (deprecated) if model is not None: - _warn_deprecated_param("model", GroqLLMSettings, "model") + _warn_deprecated_param("model", self.Settings, "model") default_settings.model = model # 3. (No step 3, as there's no params object to apply) diff --git a/src/pipecat/services/groq/stt.py b/src/pipecat/services/groq/stt.py index b5d59181a..6a234cc27 100644 --- a/src/pipecat/services/groq/stt.py +++ b/src/pipecat/services/groq/stt.py @@ -13,14 +13,13 @@ from pipecat.services.settings import _warn_deprecated_param from pipecat.services.stt_latency import GROQ_TTFS_P99 from pipecat.services.whisper.base_stt import ( BaseWhisperSTTService, - BaseWhisperSTTSettings, Transcription, ) from pipecat.transcriptions.language import Language @dataclass -class GroqSTTSettings(BaseWhisperSTTSettings): +class GroqSTTSettings(BaseWhisperSTTService.Settings): """Settings for the Groq STT service. Parameters: @@ -38,7 +37,7 @@ class GroqSTTService(BaseWhisperSTTService): """ Settings = GroqSTTSettings - _settings: GroqSTTSettings + _settings: Settings def __init__( self, @@ -49,7 +48,7 @@ class GroqSTTService(BaseWhisperSTTService): language: Optional[Language] = None, prompt: Optional[str] = None, temperature: Optional[float] = None, - settings: Optional[GroqSTTSettings] = None, + settings: Optional[Settings] = None, ttfs_p99_latency: Optional[float] = GROQ_TTFS_P99, **kwargs, ): @@ -59,24 +58,24 @@ class GroqSTTService(BaseWhisperSTTService): model: Whisper model to use. .. deprecated:: 0.0.105 - Use ``settings=GroqSTTSettings(model=...)`` instead. + Use ``settings=GroqSTTService.Settings(model=...)`` instead. api_key: Groq API key. Defaults to None. base_url: API base URL. Defaults to "https://api.groq.com/openai/v1". language: Language of the audio input. .. deprecated:: 0.0.105 - Use ``settings=GroqSTTSettings(language=...)`` instead. + Use ``settings=GroqSTTService.Settings(language=...)`` instead. prompt: Optional text to guide the model's style or continue a previous segment. .. deprecated:: 0.0.105 - Use ``settings=GroqSTTSettings(prompt=...)`` instead. + Use ``settings=GroqSTTService.Settings(prompt=...)`` instead. temperature: Optional sampling temperature between 0 and 1. .. deprecated:: 0.0.105 - Use ``settings=GroqSTTSettings(temperature=...)`` instead. + Use ``settings=GroqSTTService.Settings(temperature=...)`` instead. settings: Runtime-updatable settings. When provided alongside deprecated parameters, ``settings`` values take precedence. @@ -85,7 +84,7 @@ class GroqSTTService(BaseWhisperSTTService): **kwargs: Additional arguments passed to BaseWhisperSTTService. """ # --- 1. Hardcoded defaults --- - default_settings = GroqSTTSettings( + default_settings = self.Settings( model="whisper-large-v3-turbo", language=self.language_to_service_language(Language.EN), prompt=None, @@ -94,16 +93,16 @@ class GroqSTTService(BaseWhisperSTTService): # --- 2. Deprecated direct-arg overrides --- if model is not None: - _warn_deprecated_param("model", GroqSTTSettings, "model") + _warn_deprecated_param("model", self.Settings, "model") default_settings.model = model if language is not None: - _warn_deprecated_param("language", GroqSTTSettings, "language") + _warn_deprecated_param("language", self.Settings, "language") default_settings.language = self.language_to_service_language(language) if prompt is not None: - _warn_deprecated_param("prompt", GroqSTTSettings, "prompt") + _warn_deprecated_param("prompt", self.Settings, "prompt") default_settings.prompt = prompt if temperature is not None: - _warn_deprecated_param("temperature", GroqSTTSettings, "temperature") + _warn_deprecated_param("temperature", self.Settings, "temperature") default_settings.temperature = temperature # --- 3. (no params object for this service) --- diff --git a/src/pipecat/services/groq/tts.py b/src/pipecat/services/groq/tts.py index bb39a9067..714ecdeb1 100644 --- a/src/pipecat/services/groq/tts.py +++ b/src/pipecat/services/groq/tts.py @@ -52,13 +52,13 @@ class GroqTTSService(TTSService): """ Settings = GroqTTSSettings - _settings: GroqTTSSettings + _settings: Settings class InputParams(BaseModel): """Input parameters for Groq TTS configuration. .. deprecated:: 0.0.105 - Use ``settings=GroqTTSSettings(...)`` instead. + Use ``settings=GroqTTSService.Settings(...)`` instead. Parameters: language: Language for speech synthesis. Defaults to English. @@ -79,7 +79,7 @@ class GroqTTSService(TTSService): model_name: Optional[str] = None, voice_id: Optional[str] = None, sample_rate: Optional[int] = GROQ_SAMPLE_RATE, - settings: Optional[GroqTTSSettings] = None, + settings: Optional[Settings] = None, **kwargs, ): """Initialize Groq TTS service. @@ -90,17 +90,17 @@ class GroqTTSService(TTSService): params: Additional input parameters for voice customization. .. deprecated:: 0.0.105 - Use ``settings=GroqTTSSettings(...)`` instead. + Use ``settings=GroqTTSService.Settings(...)`` instead. model_name: TTS model to use. .. deprecated:: 0.0.105 - Use ``settings=GroqTTSSettings(model=...)`` instead. + Use ``settings=GroqTTSService.Settings(model=...)`` instead. voice_id: Voice identifier to use. .. deprecated:: 0.0.105 - Use ``settings=GroqTTSSettings(voice=...)`` instead. + Use ``settings=GroqTTSService.Settings(voice=...)`` instead. sample_rate: Audio sample rate. Must be 48000 Hz for Groq TTS. settings: Runtime-updatable settings. When provided alongside deprecated @@ -111,7 +111,7 @@ class GroqTTSService(TTSService): logger.warning(f"Groq TTS only supports {self.GROQ_SAMPLE_RATE}Hz sample rate. ") # 1. Initialize default_settings with hardcoded defaults - default_settings = GroqTTSSettings( + default_settings = self.Settings( model="canopylabs/orpheus-v1-english", voice="autumn", language="en", @@ -120,15 +120,15 @@ class GroqTTSService(TTSService): # 2. Apply direct init arg overrides (deprecated) if model_name is not None: - _warn_deprecated_param("model_name", GroqTTSSettings, "model") + _warn_deprecated_param("model_name", self.Settings, "model") default_settings.model = model_name if voice_id is not None: - _warn_deprecated_param("voice_id", GroqTTSSettings, "voice") + _warn_deprecated_param("voice_id", self.Settings, "voice") default_settings.voice = voice_id # 3. Apply params overrides — only if settings not provided if params is not None: - _warn_deprecated_param("params", GroqTTSSettings) + _warn_deprecated_param("params", self.Settings) if not settings: default_settings.language = str(params.language) if params.language else "en" default_settings.speed = params.speed diff --git a/src/pipecat/services/heygen/video.py b/src/pipecat/services/heygen/video.py index 2c42dfc6b..9a20f35ef 100644 --- a/src/pipecat/services/heygen/video.py +++ b/src/pipecat/services/heygen/video.py @@ -83,7 +83,7 @@ class HeyGenVideoService(AIService): """ Settings = HeyGenVideoSettings - _settings: HeyGenVideoSettings + _settings: Settings def __init__( self, @@ -92,7 +92,7 @@ class HeyGenVideoService(AIService): session: aiohttp.ClientSession, session_request: Optional[Union[LiveAvatarNewSessionRequest, NewSessionRequest]] = None, service_type: Optional[ServiceType] = None, - settings: Optional[HeyGenVideoSettings] = None, + settings: Optional[Settings] = None, **kwargs, ) -> None: """Initialize the HeyGen video service. diff --git a/src/pipecat/services/hume/tts.py b/src/pipecat/services/hume/tts.py index 5eb2db646..9fa1cd46c 100644 --- a/src/pipecat/services/hume/tts.py +++ b/src/pipecat/services/hume/tts.py @@ -79,13 +79,13 @@ class HumeTTSService(TTSService): """ Settings = HumeTTSSettings - _settings: HumeTTSSettings + _settings: Settings class InputParams(BaseModel): """Optional synthesis parameters for Hume TTS. .. deprecated:: 0.0.105 - Use ``settings=HumeTTSSettings(...)`` instead. + Use ``settings=HumeTTSService.Settings(...)`` instead. Parameters: description: Natural-language acting directions (up to 100 characters). @@ -104,7 +104,7 @@ class HumeTTSService(TTSService): voice_id: Optional[str] = None, params: Optional[InputParams] = None, sample_rate: Optional[int] = HUME_SAMPLE_RATE, - settings: Optional[HumeTTSSettings] = None, + settings: Optional[Settings] = None, **kwargs, ) -> None: """Initialize the HumeTTSService. @@ -114,12 +114,12 @@ class HumeTTSService(TTSService): voice_id: ID of the voice to use. Only voice IDs are supported; voice names are not. .. deprecated:: 0.0.105 - Use ``settings=HumeTTSSettings(voice=...)`` instead. + Use ``settings=HumeTTSService.Settings(voice=...)`` instead. params: Optional synthesis controls (acting instructions, speed, trailing silence). .. deprecated:: 0.0.105 - Use ``settings=HumeTTSSettings(...)`` instead. + Use ``settings=HumeTTSService.Settings(...)`` instead. sample_rate: Output sample rate for emitted PCM frames. Defaults to 48_000 (Hume). settings: Runtime-updatable settings. When provided alongside deprecated @@ -136,7 +136,7 @@ class HumeTTSService(TTSService): ) # 1. Initialize default_settings with hardcoded defaults - default_settings = HumeTTSSettings( + default_settings = self.Settings( model=None, voice=None, language=None, # Not applicable here @@ -147,12 +147,12 @@ class HumeTTSService(TTSService): # 2. Apply direct init arg overrides (deprecated) if voice_id is not None: - _warn_deprecated_param("voice_id", HumeTTSSettings, "voice") + _warn_deprecated_param("voice_id", self.Settings, "voice") default_settings.voice = voice_id # 3. Apply params overrides — only if settings not provided if params is not None: - _warn_deprecated_param("params", HumeTTSSettings) + _warn_deprecated_param("params", self.Settings) if not settings: default_settings.description = params.description default_settings.speed = params.speed @@ -242,7 +242,7 @@ class HumeTTSService(TTSService): """Runtime updates via key/value pair. .. deprecated:: 0.0.104 - Use ``TTSUpdateSettingsFrame(delta=HumeTTSSettings(...))`` instead. + Use ``TTSUpdateSettingsFrame(delta=HumeTTSService.Settings(...))`` instead. Args: key: The name of the setting to update. Recognized keys are: @@ -256,7 +256,7 @@ class HumeTTSService(TTSService): warnings.simplefilter("always") warnings.warn( "'update_setting' is deprecated, use " - "'TTSUpdateSettingsFrame(delta=HumeTTSSettings(...))' instead.", + "'TTSUpdateSettingsFrame(delta=self.Settings(...))' instead.", DeprecationWarning, stacklevel=2, ) @@ -274,7 +274,7 @@ class HumeTTSService(TTSService): kwargs["speed"] = None if value is None else float(value) elif key_l == "trailing_silence": kwargs["trailing_silence"] = None if value is None else float(value) - await self._update_settings(HumeTTSSettings(**kwargs)) + await self._update_settings(self.Settings(**kwargs)) @traced_tts async def run_tts(self, text: str, context_id: str) -> AsyncGenerator[Frame, None]: diff --git a/src/pipecat/services/inworld/tts.py b/src/pipecat/services/inworld/tts.py index dc09c0481..f24e9dcf6 100644 --- a/src/pipecat/services/inworld/tts.py +++ b/src/pipecat/services/inworld/tts.py @@ -101,13 +101,13 @@ class InworldHttpTTSService(TTSService): """ Settings = InworldTTSSettings - _settings: InworldTTSSettings + _settings: Settings class InputParams(BaseModel): """Input parameters for Inworld TTS configuration. .. deprecated:: 0.0.105 - Use ``InworldTTSSettings`` directly via the ``settings`` parameter instead. + Use ``InworldHttpTTSService.Settings`` directly via the ``settings`` parameter instead. Parameters: temperature: Temperature for speech synthesis. @@ -131,7 +131,7 @@ class InworldHttpTTSService(TTSService): encoding: str = "LINEAR16", timestamp_transport_strategy: Optional[Literal["ASYNC", "SYNC"]] = "ASYNC", params: Optional[InputParams] = None, - settings: Optional[InworldTTSSettings] = None, + settings: Optional[Settings] = None, **kwargs, ): """Initialize the Inworld TTS service. @@ -142,12 +142,12 @@ class InworldHttpTTSService(TTSService): voice_id: ID of the voice to use for synthesis. .. deprecated:: 0.0.105 - Use ``settings=InworldTTSSettings(voice=...)`` instead. + Use ``settings=InworldHttpTTSService.Settings(voice=...)`` instead. model: ID of the model to use for synthesis. .. deprecated:: 0.0.105 - Use ``settings=InworldTTSSettings(model=...)`` instead. + Use ``settings=InworldHttpTTSService.Settings(model=...)`` instead. streaming: Whether to use streaming mode. sample_rate: Audio sample rate in Hz. @@ -157,14 +157,14 @@ class InworldHttpTTSService(TTSService): params: Input parameters for Inworld TTS configuration. .. deprecated:: 0.0.105 - Use ``settings=InworldTTSSettings(...)`` instead. + Use ``settings=InworldHttpTTSService.Settings(...)`` instead. settings: Runtime-updatable settings. When provided alongside deprecated parameters, ``settings`` values take precedence. **kwargs: Additional arguments passed to the parent class. """ # 1. Initialize default_settings with hardcoded defaults - default_settings = InworldTTSSettings( + default_settings = self.Settings( model="inworld-tts-1.5-max", voice="Ashley", language=None, @@ -174,15 +174,15 @@ class InworldHttpTTSService(TTSService): # 2. Apply direct init arg overrides (deprecated) if voice_id is not None: - _warn_deprecated_param("voice_id", InworldTTSSettings, "voice") + _warn_deprecated_param("voice_id", self.Settings, "voice") default_settings.voice = voice_id if model is not None: - _warn_deprecated_param("model", InworldTTSSettings, "model") + _warn_deprecated_param("model", self.Settings, "model") default_settings.model = model # 3. Apply params overrides — only if settings not provided if params is not None: - _warn_deprecated_param("params", InworldTTSSettings) + _warn_deprecated_param("params", self.Settings) if not settings: if params.speaking_rate is not None: default_settings.speaking_rate = params.speaking_rate @@ -489,13 +489,13 @@ class InworldTTSService(WebsocketTTSService): """ Settings = InworldTTSSettings - _settings: InworldTTSSettings + _settings: Settings class InputParams(BaseModel): """Input parameters for Inworld WebSocket TTS configuration. .. deprecated:: 0.0.105 - Use ``InworldTTSSettings`` directly via the ``settings`` parameter instead. + Use ``InworldTTSService.Settings`` directly via the ``settings`` parameter instead. Parameters: temperature: Temperature for speech synthesis. @@ -532,7 +532,7 @@ class InworldTTSService(WebsocketTTSService): apply_text_normalization: Optional[str] = None, timestamp_transport_strategy: Optional[Literal["ASYNC", "SYNC"]] = "ASYNC", params: Optional[InputParams] = None, - settings: Optional[InworldTTSSettings] = None, + settings: Optional[Settings] = None, aggregate_sentences: Optional[bool] = None, text_aggregation_mode: Optional[TextAggregationMode] = None, append_trailing_space: bool = True, @@ -545,12 +545,12 @@ class InworldTTSService(WebsocketTTSService): voice_id: ID of the voice to use for synthesis. .. deprecated:: 0.0.105 - Use ``settings=InworldTTSSettings(voice=...)`` instead. + Use ``settings=InworldTTSService.Settings(voice=...)`` instead. model: ID of the model to use for synthesis. .. deprecated:: 0.0.105 - Use ``settings=InworldTTSSettings(model=...)`` instead. + Use ``settings=InworldTTSService.Settings(model=...)`` instead. url: URL of the Inworld WebSocket API. sample_rate: Audio sample rate in Hz. @@ -564,7 +564,7 @@ class InworldTTSService(WebsocketTTSService): params: Input parameters for Inworld WebSocket TTS configuration. .. deprecated:: 0.0.105 - Use ``settings=InworldTTSSettings(...)`` instead. + Use ``settings=InworldTTSService.Settings(...)`` instead. settings: Runtime-updatable settings. When provided alongside deprecated parameters, ``settings`` values take precedence. @@ -582,7 +582,7 @@ class InworldTTSService(WebsocketTTSService): auto_mode = True if aggregate_sentences is None else aggregate_sentences # 1. Initialize default_settings with hardcoded defaults - default_settings = InworldTTSSettings( + default_settings = self.Settings( model="inworld-tts-1.5-max", voice="Ashley", language=None, @@ -592,17 +592,17 @@ class InworldTTSService(WebsocketTTSService): # 2. Apply direct init arg overrides (deprecated) if voice_id is not None: - _warn_deprecated_param("voice_id", InworldTTSSettings, "voice") + _warn_deprecated_param("voice_id", self.Settings, "voice") default_settings.voice = voice_id if model is not None: - _warn_deprecated_param("model", InworldTTSSettings, "model") + _warn_deprecated_param("model", self.Settings, "model") default_settings.model = model # 3. Apply params overrides — only if settings not provided _buffer_max_delay_ms = None _buffer_char_threshold = None if params is not None: - _warn_deprecated_param("params", InworldTTSSettings) + _warn_deprecated_param("params", self.Settings) if not settings: if params.speaking_rate is not None: default_settings.speaking_rate = params.speaking_rate diff --git a/src/pipecat/services/kokoro/tts.py b/src/pipecat/services/kokoro/tts.py index 98f181c6f..fd7f15c27 100644 --- a/src/pipecat/services/kokoro/tts.py +++ b/src/pipecat/services/kokoro/tts.py @@ -102,13 +102,13 @@ class KokoroTTSService(TTSService): """ Settings = KokoroTTSSettings - _settings: KokoroTTSSettings + _settings: Settings class InputParams(BaseModel): """Input parameters for Kokoro TTS configuration. .. deprecated:: 0.0.105 - Use ``KokoroTTSSettings`` directly via the ``settings`` parameter instead. + Use ``KokoroTTSService.Settings`` directly via the ``settings`` parameter instead. Parameters: language: Language to use for synthesis. @@ -123,7 +123,7 @@ class KokoroTTSService(TTSService): model_path: Optional[str] = None, voices_path: Optional[str] = None, params: Optional[InputParams] = None, - settings: Optional[KokoroTTSSettings] = None, + settings: Optional[Settings] = None, **kwargs, ): """Initialize the Kokoro TTS service. @@ -132,14 +132,14 @@ class KokoroTTSService(TTSService): voice_id: Voice identifier to use for synthesis. .. deprecated:: 0.0.105 - Use ``settings=KokoroTTSSettings(voice=...)`` instead. + Use ``settings=KokoroTTSService.Settings(voice=...)`` instead. model_path: Path to the kokoro ONNX model file. Defaults to auto-downloaded file. voices_path: Path to the voices binary file. Defaults to auto-downloaded file. params: Configuration parameters for synthesis. .. deprecated:: 0.0.105 - Use ``settings=KokoroTTSSettings(...)`` instead. + Use ``settings=KokoroTTSService.Settings(...)`` instead. settings: Runtime-updatable settings. When provided alongside deprecated parameters, ``settings`` values take precedence. @@ -147,7 +147,7 @@ class KokoroTTSService(TTSService): """ # 1. Initialize default_settings with hardcoded defaults - default_settings = KokoroTTSSettings( + default_settings = self.Settings( model=None, voice=None, language=language_to_kokoro_language(Language.EN), @@ -155,12 +155,12 @@ class KokoroTTSService(TTSService): # 2. Apply direct init arg overrides (deprecated) if voice_id is not None: - _warn_deprecated_param("voice_id", KokoroTTSSettings, "voice") + _warn_deprecated_param("voice_id", self.Settings, "voice") default_settings.voice = voice_id # 3. Apply params overrides — only if settings not provided if params is not None: - _warn_deprecated_param("params", KokoroTTSSettings) + _warn_deprecated_param("params", self.Settings) if not settings: default_settings.language = language_to_kokoro_language(params.language) diff --git a/src/pipecat/services/lmnt/tts.py b/src/pipecat/services/lmnt/tts.py index 46e5e4697..ea5986ffc 100644 --- a/src/pipecat/services/lmnt/tts.py +++ b/src/pipecat/services/lmnt/tts.py @@ -89,7 +89,7 @@ class LmntTTSService(InterruptibleTTSService): """ Settings = LmntTTSSettings - _settings: LmntTTSSettings + _settings: Settings def __init__( self, @@ -100,7 +100,7 @@ class LmntTTSService(InterruptibleTTSService): language: Language = Language.EN, output_format: str = "pcm_s16le", model: Optional[str] = None, - settings: Optional[LmntTTSSettings] = None, + settings: Optional[Settings] = None, **kwargs, ): """Initialize the LMNT TTS service. @@ -110,7 +110,7 @@ class LmntTTSService(InterruptibleTTSService): voice_id: ID of the voice to use for synthesis. .. deprecated:: 0.0.105 - Use ``settings=LmntTTSSettings(voice=...)`` instead. + Use ``settings=LmntTTSService.Settings(voice=...)`` instead. sample_rate: Audio sample rate. If None, uses default. language: Language for synthesis. Defaults to English. @@ -119,14 +119,14 @@ class LmntTTSService(InterruptibleTTSService): model: TTS model to use. .. deprecated:: 0.0.105 - Use ``settings=LmntTTSSettings(model=...)`` instead. + Use ``settings=LmntTTSService.Settings(model=...)`` instead. settings: Runtime-updatable settings. When provided alongside deprecated parameters, ``settings`` values take precedence. **kwargs: Additional arguments passed to parent InterruptibleTTSService. """ # 1. Initialize default_settings with hardcoded defaults - default_settings = LmntTTSSettings( + default_settings = self.Settings( model="aurora", voice=None, language=self.language_to_service_language(language), @@ -134,10 +134,10 @@ class LmntTTSService(InterruptibleTTSService): # 2. Apply direct init arg overrides (deprecated) if voice_id is not None: - _warn_deprecated_param("voice_id", LmntTTSSettings, "voice") + _warn_deprecated_param("voice_id", self.Settings, "voice") default_settings.voice = voice_id if model is not None: - _warn_deprecated_param("model", LmntTTSSettings, "model") + _warn_deprecated_param("model", self.Settings, "model") default_settings.model = model # 3. (No step 3, as there's no params object to apply) @@ -237,7 +237,7 @@ class LmntTTSService(InterruptibleTTSService): """Apply a settings delta. Args: - delta: A :class:`TTSSettings` (or ``LmntTTSSettings``) delta. + delta: A :class:`TTSSettings` (or ``LmntTTSService.Settings``) delta. Returns: Dict mapping changed field names to their previous values. diff --git a/src/pipecat/services/minimax/tts.py b/src/pipecat/services/minimax/tts.py index f62e8d46b..173c1ea05 100644 --- a/src/pipecat/services/minimax/tts.py +++ b/src/pipecat/services/minimax/tts.py @@ -141,13 +141,13 @@ class MiniMaxHttpTTSService(TTSService): """ Settings = MiniMaxTTSSettings - _settings: MiniMaxTTSSettings + _settings: Settings class InputParams(BaseModel): """Configuration parameters for MiniMax TTS. .. deprecated:: 0.0.105 - Use ``MiniMaxTTSSettings`` directly via the ``settings`` parameter instead. + Use ``MiniMaxHttpTTSService.Settings`` directly via the ``settings`` parameter instead. Parameters: language: Language for TTS generation. Supports 40 languages. @@ -190,7 +190,7 @@ class MiniMaxHttpTTSService(TTSService): sample_rate: Optional[int] = None, stream: bool = True, params: Optional[InputParams] = None, - settings: Optional[MiniMaxTTSSettings] = None, + settings: Optional[Settings] = None, **kwargs, ): """Initialize the MiniMax TTS service. @@ -208,12 +208,12 @@ class MiniMaxHttpTTSService(TTSService): "speech-01-hd", "speech-01-turbo". .. deprecated:: 0.0.105 - Use ``settings=MiniMaxTTSSettings(model=...)`` instead. + Use ``settings=MiniMaxHttpTTSService.Settings(model=...)`` instead. voice_id: Voice identifier. Defaults to "Calm_Woman". .. deprecated:: 0.0.105 - Use ``settings=MiniMaxTTSSettings(voice=...)`` instead. + Use ``settings=MiniMaxHttpTTSService.Settings(voice=...)`` instead. aiohttp_session: aiohttp.ClientSession for API communication. sample_rate: Output audio sample rate in Hz. If None, uses pipeline default. @@ -221,14 +221,14 @@ class MiniMaxHttpTTSService(TTSService): params: Additional configuration parameters. .. deprecated:: 0.0.105 - Use ``settings=MiniMaxTTSSettings(...)`` instead. + Use ``settings=MiniMaxHttpTTSService.Settings(...)`` instead. settings: Runtime-updatable settings. When provided alongside deprecated parameters, ``settings`` values take precedence. **kwargs: Additional arguments passed to parent TTSService. """ # 1. Initialize default_settings with hardcoded defaults - default_settings = MiniMaxTTSSettings( + default_settings = self.Settings( model="speech-02-turbo", voice="Calm_Woman", language=None, @@ -243,15 +243,15 @@ class MiniMaxHttpTTSService(TTSService): # 2. Apply direct init arg overrides (deprecated) if model is not None: - _warn_deprecated_param("model", MiniMaxTTSSettings, "model") + _warn_deprecated_param("model", self.Settings, "model") default_settings.model = model if voice_id is not None: - _warn_deprecated_param("voice_id", MiniMaxTTSSettings, "voice") + _warn_deprecated_param("voice_id", self.Settings, "voice") default_settings.voice = voice_id # 3. Apply params overrides — only if settings not provided if params is not None: - _warn_deprecated_param("params", MiniMaxTTSSettings) + _warn_deprecated_param("params", self.Settings) if not settings: default_settings.speed = params.speed default_settings.volume = params.volume diff --git a/src/pipecat/services/mistral/llm.py b/src/pipecat/services/mistral/llm.py index 9e01a76b5..4b74695ef 100644 --- a/src/pipecat/services/mistral/llm.py +++ b/src/pipecat/services/mistral/llm.py @@ -14,13 +14,13 @@ from openai.types.chat import ChatCompletionMessageParam from pipecat.adapters.services.open_ai_adapter import OpenAILLMInvocationParams from pipecat.frames.frames import FunctionCallFromLLM -from pipecat.services.openai.base_llm import OpenAILLMSettings +from pipecat.services.openai.base_llm import BaseOpenAILLMService from pipecat.services.openai.llm import OpenAILLMService from pipecat.services.settings import _warn_deprecated_param @dataclass -class MistralLLMSettings(OpenAILLMSettings): +class MistralLLMSettings(BaseOpenAILLMService.Settings): """Settings for MistralLLMService.""" pass @@ -34,7 +34,7 @@ class MistralLLMService(OpenAILLMService): """ Settings = MistralLLMSettings - _settings: MistralLLMSettings + _settings: Settings def __init__( self, @@ -42,7 +42,7 @@ class MistralLLMService(OpenAILLMService): api_key: str, base_url: str = "https://api.mistral.ai/v1", model: Optional[str] = None, - settings: Optional[MistralLLMSettings] = None, + settings: Optional[Settings] = None, **kwargs, ): """Initialize the Mistral LLM service. @@ -53,18 +53,18 @@ class MistralLLMService(OpenAILLMService): model: The model identifier to use. Defaults to "mistral-small-latest". .. deprecated:: 0.0.105 - Use ``settings=OpenAILLMSettings(model=...)`` instead. + Use ``settings=MistralLLMService.Settings(model=...)`` instead. settings: Runtime-updatable settings. When provided alongside deprecated parameters, ``settings`` values take precedence. **kwargs: Additional keyword arguments passed to OpenAILLMService. """ # 1. Initialize default_settings with hardcoded defaults - default_settings = MistralLLMSettings(model="mistral-small-latest") + default_settings = self.Settings(model="mistral-small-latest") # 2. Apply direct init arg overrides (deprecated) if model is not None: - _warn_deprecated_param("model", MistralLLMSettings, "model") + _warn_deprecated_param("model", self.Settings, "model") default_settings.model = model # 3. (No step 3, as there's no params object to apply) diff --git a/src/pipecat/services/moondream/vision.py b/src/pipecat/services/moondream/vision.py index abc344fc5..b8ab5a270 100644 --- a/src/pipecat/services/moondream/vision.py +++ b/src/pipecat/services/moondream/vision.py @@ -80,7 +80,7 @@ class MoondreamService(VisionService): """ Settings = MoondreamSettings - _settings: MoondreamSettings + _settings: Settings def __init__( self, @@ -88,7 +88,7 @@ class MoondreamService(VisionService): model: Optional[str] = None, revision="2025-01-09", use_cpu=False, - settings: Optional[MoondreamSettings] = None, + settings: Optional[Settings] = None, **kwargs, ): """Initialize the Moondream service. @@ -97,7 +97,7 @@ class MoondreamService(VisionService): model: Hugging Face model identifier for the Moondream model. .. deprecated:: 0.0.105 - Use ``settings=MoondreamSettings(model=...)`` instead. + Use ``settings=MoondreamService.Settings(model=...)`` instead. revision: Specific model revision to use. use_cpu: Whether to force CPU usage instead of hardware acceleration. @@ -106,11 +106,11 @@ class MoondreamService(VisionService): **kwargs: Additional arguments passed to the parent VisionService. """ # 1. Initialize default_settings with hardcoded defaults - default_settings = MoondreamSettings(model="vikhyatk/moondream2") + default_settings = self.Settings(model="vikhyatk/moondream2") # 2. Apply direct init arg overrides (deprecated) if model is not None: - _warn_deprecated_param("model", MoondreamSettings, "model") + _warn_deprecated_param("model", self.Settings, "model") default_settings.model = model # 4. Apply settings delta (canonical API, always wins) diff --git a/src/pipecat/services/neuphonic/tts.py b/src/pipecat/services/neuphonic/tts.py index abc33c37e..5c0605293 100644 --- a/src/pipecat/services/neuphonic/tts.py +++ b/src/pipecat/services/neuphonic/tts.py @@ -92,13 +92,13 @@ class NeuphonicTTSService(InterruptibleTTSService): """ Settings = NeuphonicTTSSettings - _settings: NeuphonicTTSSettings + _settings: Settings class InputParams(BaseModel): """Input parameters for Neuphonic TTS configuration. .. deprecated:: 0.0.105 - Use ``settings=NeuphonicTTSSettings(...)`` instead. + Use ``settings=NeuphonicTTSService.Settings(...)`` instead. Parameters: language: Language for synthesis. Defaults to English. @@ -117,7 +117,7 @@ class NeuphonicTTSService(InterruptibleTTSService): sample_rate: Optional[int] = 22050, encoding: str = "pcm_linear", params: Optional[InputParams] = None, - settings: Optional[NeuphonicTTSSettings] = None, + settings: Optional[Settings] = None, aggregate_sentences: Optional[bool] = None, text_aggregation_mode: Optional[TextAggregationMode] = None, **kwargs, @@ -129,7 +129,7 @@ class NeuphonicTTSService(InterruptibleTTSService): voice_id: ID of the voice to use for synthesis. .. deprecated:: 0.0.105 - Use ``settings=NeuphonicTTSSettings(voice=...)`` instead. + Use ``settings=NeuphonicTTSService.Settings(voice=...)`` instead. url: WebSocket URL for the Neuphonic API. sample_rate: Audio sample rate in Hz. Defaults to 22050. @@ -137,7 +137,7 @@ class NeuphonicTTSService(InterruptibleTTSService): params: Additional input parameters for TTS configuration. .. deprecated:: 0.0.105 - Use ``settings=NeuphonicTTSSettings(...)`` instead. + Use ``settings=NeuphonicTTSService.Settings(...)`` instead. settings: Runtime-updatable settings. When provided alongside deprecated parameters, ``settings`` values take precedence. @@ -150,7 +150,7 @@ class NeuphonicTTSService(InterruptibleTTSService): **kwargs: Additional arguments passed to parent InterruptibleTTSService. """ # 1. Initialize default_settings with hardcoded defaults - default_settings = NeuphonicTTSSettings( + default_settings = self.Settings( model=None, voice=None, language=self.language_to_service_language(Language.EN), @@ -159,12 +159,12 @@ class NeuphonicTTSService(InterruptibleTTSService): # 2. Apply direct init arg overrides (deprecated) if voice_id is not None: - _warn_deprecated_param("voice_id", NeuphonicTTSSettings, "voice") + _warn_deprecated_param("voice_id", self.Settings, "voice") default_settings.voice = voice_id # 3. Apply params overrides — only if settings not provided if params is not None: - _warn_deprecated_param("params", NeuphonicTTSSettings) + _warn_deprecated_param("params", self.Settings) if not settings: if params.language is not None: default_settings.language = self.language_to_service_language(params.language) @@ -432,13 +432,13 @@ class NeuphonicHttpTTSService(TTSService): """ Settings = NeuphonicTTSSettings - _settings: NeuphonicTTSSettings + _settings: Settings class InputParams(BaseModel): """Input parameters for Neuphonic HTTP TTS configuration. .. deprecated:: 0.0.105 - Use ``settings=NeuphonicTTSSettings(...)`` instead. + Use ``settings=NeuphonicHttpTTSService.Settings(...)`` instead. Parameters: language: Language for synthesis. Defaults to English. @@ -458,7 +458,7 @@ class NeuphonicHttpTTSService(TTSService): sample_rate: Optional[int] = 22050, encoding: Optional[str] = "pcm_linear", params: Optional[InputParams] = None, - settings: Optional[NeuphonicTTSSettings] = None, + settings: Optional[Settings] = None, **kwargs, ): """Initialize the Neuphonic HTTP TTS service. @@ -468,7 +468,7 @@ class NeuphonicHttpTTSService(TTSService): voice_id: ID of the voice to use for synthesis. .. deprecated:: 0.0.105 - Use ``settings=NeuphonicTTSSettings(voice=...)`` instead. + Use ``settings=NeuphonicHttpTTSService.Settings(voice=...)`` instead. aiohttp_session: Shared aiohttp session for HTTP requests. url: Base URL for the Neuphonic HTTP API. @@ -477,14 +477,14 @@ class NeuphonicHttpTTSService(TTSService): params: Additional input parameters for TTS configuration. .. deprecated:: 0.0.105 - Use ``settings=NeuphonicTTSSettings(...)`` instead. + Use ``settings=NeuphonicHttpTTSService.Settings(...)`` instead. settings: Runtime-updatable settings. When provided alongside deprecated parameters, ``settings`` values take precedence. **kwargs: Additional arguments passed to parent TTSService. """ # 1. Initialize default_settings with hardcoded defaults - default_settings = NeuphonicTTSSettings( + default_settings = self.Settings( model=None, voice=None, language=self.language_to_service_language(Language.EN), @@ -493,12 +493,12 @@ class NeuphonicHttpTTSService(TTSService): # 2. Apply direct init arg overrides (deprecated) if voice_id is not None: - _warn_deprecated_param("voice_id", NeuphonicTTSSettings, "voice") + _warn_deprecated_param("voice_id", self.Settings, "voice") default_settings.voice = voice_id # 3. Apply params overrides — only if settings not provided if params is not None: - _warn_deprecated_param("params", NeuphonicTTSSettings) + _warn_deprecated_param("params", self.Settings) if not settings: if params.language is not None: default_settings.language = self.language_to_service_language(params.language) diff --git a/src/pipecat/services/nvidia/llm.py b/src/pipecat/services/nvidia/llm.py index 17490f513..b40190bec 100644 --- a/src/pipecat/services/nvidia/llm.py +++ b/src/pipecat/services/nvidia/llm.py @@ -16,13 +16,13 @@ from typing import Optional from pipecat.metrics.metrics import LLMTokenUsage from pipecat.processors.aggregators.llm_context import LLMContext from pipecat.processors.aggregators.openai_llm_context import OpenAILLMContext -from pipecat.services.openai.base_llm import OpenAILLMSettings +from pipecat.services.openai.base_llm import BaseOpenAILLMService from pipecat.services.openai.llm import OpenAILLMService from pipecat.services.settings import _warn_deprecated_param @dataclass -class NvidiaLLMSettings(OpenAILLMSettings): +class NvidiaLLMSettings(BaseOpenAILLMService.Settings): """Settings for NvidiaLLMService.""" pass @@ -37,7 +37,7 @@ class NvidiaLLMService(OpenAILLMService): """ Settings = NvidiaLLMSettings - _settings: NvidiaLLMSettings + _settings: Settings def __init__( self, @@ -45,7 +45,7 @@ class NvidiaLLMService(OpenAILLMService): api_key: str, base_url: str = "https://integrate.api.nvidia.com/v1", model: Optional[str] = None, - settings: Optional[NvidiaLLMSettings] = None, + settings: Optional[Settings] = None, **kwargs, ): """Initialize the NvidiaLLMService. @@ -57,18 +57,18 @@ class NvidiaLLMService(OpenAILLMService): "nvidia/llama-3.1-nemotron-70b-instruct". .. deprecated:: 0.0.105 - Use ``settings=OpenAILLMSettings(model=...)`` instead. + Use ``settings=NvidiaLLMService.Settings(model=...)`` instead. settings: Runtime-updatable settings. When provided alongside deprecated parameters, ``settings`` values take precedence. **kwargs: Additional keyword arguments passed to OpenAILLMService. """ # 1. Initialize default_settings with hardcoded defaults - default_settings = NvidiaLLMSettings(model="nvidia/llama-3.1-nemotron-70b-instruct") + default_settings = self.Settings(model="nvidia/llama-3.1-nemotron-70b-instruct") # 2. Apply direct init arg overrides (deprecated) if model is not None: - _warn_deprecated_param("model", NvidiaLLMSettings, "model") + _warn_deprecated_param("model", self.Settings, "model") default_settings.model = model # 3. (No step 3, as there's no params object to apply) diff --git a/src/pipecat/services/nvidia/stt.py b/src/pipecat/services/nvidia/stt.py index 5935e7846..3c8004baa 100644 --- a/src/pipecat/services/nvidia/stt.py +++ b/src/pipecat/services/nvidia/stt.py @@ -126,13 +126,13 @@ class NvidiaSTTService(STTService): """ Settings = NvidiaSTTSettings - _settings: NvidiaSTTSettings + _settings: Settings class InputParams(BaseModel): """Configuration parameters for NVIDIA Riva STT service. .. deprecated:: 0.0.105 - Use ``settings=NvidiaSTTSettings(...)`` instead. + Use ``settings=NvidiaSTTService.Settings(...)`` instead. Parameters: language: Target language for transcription. Defaults to EN_US. @@ -152,7 +152,7 @@ class NvidiaSTTService(STTService): sample_rate: Optional[int] = None, params: Optional[InputParams] = None, use_ssl: bool = True, - settings: Optional[NvidiaSTTSettings] = None, + settings: Optional[Settings] = None, ttfs_p99_latency: Optional[float] = NVIDIA_TTFS_P99, **kwargs, ): @@ -166,7 +166,7 @@ class NvidiaSTTService(STTService): params: Additional configuration parameters for NVIDIA Riva. .. deprecated:: 0.0.105 - Use ``settings=NvidiaSTTSettings(...)`` instead. + Use ``settings=NvidiaSTTService.Settings(...)`` instead. use_ssl: Whether to use SSL for the NVIDIA Riva server. Defaults to True. settings: Runtime-updatable settings. When provided alongside deprecated @@ -176,7 +176,7 @@ class NvidiaSTTService(STTService): **kwargs: Additional arguments passed to STTService. """ # 1. Initialize default_settings with hardcoded defaults - default_settings = NvidiaSTTSettings( + default_settings = self.Settings( model=model_function_map.get("model_name"), language=Language.EN_US, ) @@ -185,7 +185,7 @@ class NvidiaSTTService(STTService): # 3. Apply params overrides — only if settings not provided if params is not None: - _warn_deprecated_param("params", NvidiaSTTSettings) + _warn_deprecated_param("params", self.Settings) if not settings: default_settings.language = params.language @@ -441,13 +441,13 @@ class NvidiaSegmentedSTTService(SegmentedSTTService): """ Settings = NvidiaSegmentedSTTSettings - _settings: NvidiaSegmentedSTTSettings + _settings: Settings class InputParams(BaseModel): """Configuration parameters for NVIDIA Riva segmented STT service. .. deprecated:: 0.0.105 - Use ``settings=NvidiaSegmentedSTTSettings(...)`` instead. + Use ``settings=NvidiaSegmentedSTTService.Settings(...)`` instead. Parameters: language: Target language for transcription. Defaults to EN_US. @@ -477,7 +477,7 @@ class NvidiaSegmentedSTTService(SegmentedSTTService): sample_rate: Optional[int] = None, params: Optional[InputParams] = None, use_ssl: bool = True, - settings: Optional[NvidiaSegmentedSTTSettings] = None, + settings: Optional[Settings] = None, ttfs_p99_latency: Optional[float] = NVIDIA_TTFS_P99, **kwargs, ): @@ -491,7 +491,7 @@ class NvidiaSegmentedSTTService(SegmentedSTTService): params: Additional configuration parameters for NVIDIA Riva .. deprecated:: 0.0.105 - Use ``settings=NvidiaSegmentedSTTSettings(...)`` instead. + Use ``settings=NvidiaSegmentedSTTService.Settings(...)`` instead. use_ssl: Whether to use SSL for the NVIDIA Riva server. Defaults to True. settings: Runtime-updatable settings. When provided alongside deprecated @@ -501,7 +501,7 @@ class NvidiaSegmentedSTTService(SegmentedSTTService): **kwargs: Additional arguments passed to SegmentedSTTService """ # 1. Initialize default_settings with hardcoded defaults - default_settings = NvidiaSegmentedSTTSettings( + default_settings = self.Settings( model=model_function_map.get("model_name"), language=language_to_nvidia_riva_language(Language.EN_US) or "en-US", profanity_filter=False, @@ -515,7 +515,7 @@ class NvidiaSegmentedSTTService(SegmentedSTTService): # 3. Apply params overrides — only if settings not provided if params is not None: - _warn_deprecated_param("params", NvidiaSegmentedSTTSettings) + _warn_deprecated_param("params", self.Settings) if not settings: default_settings.language = ( language_to_nvidia_riva_language(params.language or Language.EN_US) or "en-US" @@ -641,7 +641,7 @@ class NvidiaSegmentedSTTService(SegmentedSTTService): """Apply a settings delta and sync internal state. Args: - delta: A :class:`STTSettings` (or ``NvidiaSegmentedSTTSettings``) delta. + delta: A :class:`STTSettings` (or ``NvidiaSegmentedSTTService.Settings``) delta. Returns: Dict mapping changed field names to their previous values. diff --git a/src/pipecat/services/nvidia/tts.py b/src/pipecat/services/nvidia/tts.py index ad39d505b..b41de8b47 100644 --- a/src/pipecat/services/nvidia/tts.py +++ b/src/pipecat/services/nvidia/tts.py @@ -62,13 +62,13 @@ class NvidiaTTSService(TTSService): """ Settings = NvidiaTTSSettings - _settings: NvidiaTTSSettings + _settings: Settings class InputParams(BaseModel): """Input parameters for Riva TTS configuration. .. deprecated:: 0.0.105 - Use ``NvidiaTTSSettings`` directly via the ``settings`` parameter instead. + Use ``NvidiaTTSService.Settings`` directly via the ``settings`` parameter instead. Parameters: language: Language code for synthesis. Defaults to US English. @@ -90,7 +90,7 @@ class NvidiaTTSService(TTSService): "model_name": "magpie-tts-multilingual", }, params: Optional[InputParams] = None, - settings: Optional[NvidiaTTSSettings] = None, + settings: Optional[Settings] = None, use_ssl: bool = True, **kwargs, ): @@ -102,14 +102,14 @@ class NvidiaTTSService(TTSService): voice_id: Voice model identifier. Defaults to multilingual Aria voice. .. deprecated:: 0.0.105 - Use ``settings=NvidiaTTSSettings(voice=...)`` instead. + Use ``settings=NvidiaTTSService.Settings(voice=...)`` instead. sample_rate: Audio sample rate. If None, uses service default. model_function_map: Dictionary containing function_id and model_name for the TTS model. params: Additional configuration parameters for TTS synthesis. .. deprecated:: 0.0.105 - Use ``settings=NvidiaTTSSettings(...)`` instead. + Use ``settings=NvidiaTTSService.Settings(...)`` instead. settings: Runtime-updatable settings. When provided alongside deprecated parameters, ``settings`` values take precedence. @@ -117,7 +117,7 @@ class NvidiaTTSService(TTSService): **kwargs: Additional arguments passed to parent TTSService. """ # 1. Initialize default_settings with hardcoded defaults - default_settings = NvidiaTTSSettings( + default_settings = self.Settings( model=model_function_map.get("model_name"), voice="Magpie-Multilingual.EN-US.Aria", language=Language.EN_US, @@ -126,12 +126,12 @@ class NvidiaTTSService(TTSService): # 2. Apply direct init arg overrides (deprecated) if voice_id is not None: - _warn_deprecated_param("voice_id", NvidiaTTSSettings, "voice") + _warn_deprecated_param("voice_id", self.Settings, "voice") default_settings.voice = voice_id # 3. Apply params overrides — only if settings not provided if params is not None: - _warn_deprecated_param("params", NvidiaTTSSettings) + _warn_deprecated_param("params", self.Settings) if not settings: if params.language is not None: default_settings.language = params.language @@ -186,7 +186,7 @@ class NvidiaTTSService(TTSService): stacklevel=2, ) - async def _update_settings(self, delta: NvidiaTTSSettings) -> dict[str, Any]: + async def _update_settings(self, delta: Settings) -> dict[str, Any]: """Apply a settings delta. Settings are stored but not applied to the active connection. diff --git a/src/pipecat/services/ollama/llm.py b/src/pipecat/services/ollama/llm.py index f4d138d78..3b15049a4 100644 --- a/src/pipecat/services/ollama/llm.py +++ b/src/pipecat/services/ollama/llm.py @@ -11,13 +11,13 @@ from typing import Optional from loguru import logger -from pipecat.services.openai.base_llm import OpenAILLMSettings +from pipecat.services.openai.base_llm import BaseOpenAILLMService from pipecat.services.openai.llm import OpenAILLMService from pipecat.services.settings import _warn_deprecated_param @dataclass -class OllamaLLMSettings(OpenAILLMSettings): +class OllamaLLMSettings(BaseOpenAILLMService.Settings): """Settings for OLLamaLLMService.""" pass @@ -31,14 +31,14 @@ class OLLamaLLMService(OpenAILLMService): """ Settings = OllamaLLMSettings - _settings: OllamaLLMSettings + _settings: Settings def __init__( self, *, model: Optional[str] = None, base_url: str = "http://localhost:11434/v1", - settings: Optional[OllamaLLMSettings] = None, + settings: Optional[Settings] = None, **kwargs, ): """Initialize OLLama LLM service. @@ -47,7 +47,7 @@ class OLLamaLLMService(OpenAILLMService): model: The OLLama model to use. Defaults to "llama2". .. deprecated:: 0.0.105 - Use ``settings=OpenAILLMSettings(model=...)`` instead. + Use ``settings=OLLamaLLMService.Settings(model=...)`` instead. base_url: The base URL for the OLLama API endpoint. Defaults to "http://localhost:11434/v1". @@ -56,11 +56,11 @@ class OLLamaLLMService(OpenAILLMService): **kwargs: Additional keyword arguments passed to OpenAILLMService. """ # 1. Initialize default_settings with hardcoded defaults - default_settings = OllamaLLMSettings(model="llama2") + default_settings = self.Settings(model="llama2") # 2. Apply direct init arg overrides (deprecated) if model is not None: - _warn_deprecated_param("model", OllamaLLMSettings, "model") + _warn_deprecated_param("model", self.Settings, "model") default_settings.model = model # 3. (No step 3, as there's no params object to apply) diff --git a/src/pipecat/services/openai/base_llm.py b/src/pipecat/services/openai/base_llm.py index 9e3b6a282..d1d695ef6 100644 --- a/src/pipecat/services/openai/base_llm.py +++ b/src/pipecat/services/openai/base_llm.py @@ -69,13 +69,13 @@ class BaseOpenAILLMService(LLMService): """ Settings = OpenAILLMSettings - _settings: OpenAILLMSettings + _settings: Settings class InputParams(BaseModel): """Input parameters for OpenAI model configuration. .. deprecated:: 0.0.105 - Use ``settings=OpenAILLMSettings(...)`` instead of + Use ``settings=BaseOpenAILLMService.Settings(...)`` instead of ``params=InputParams(...)``. Parameters: @@ -119,7 +119,7 @@ class BaseOpenAILLMService(LLMService): default_headers: Optional[Mapping[str, str]] = None, service_tier: Optional[str] = None, params: Optional[InputParams] = None, - settings: Optional[OpenAILLMSettings] = None, + settings: Optional[Settings] = None, retry_timeout_secs: Optional[float] = 5.0, retry_on_timeout: Optional[bool] = False, **kwargs, @@ -130,7 +130,7 @@ class BaseOpenAILLMService(LLMService): model: The OpenAI model name to use (e.g., "gpt-4.1", "gpt-4o"). .. deprecated:: 0.0.105 - Use ``settings=OpenAILLMSettings(model=...)`` instead. + Use ``settings=BaseOpenAILLMService.Settings(model=...)`` instead. api_key: OpenAI API key. If None, uses environment variable. base_url: Custom base URL for OpenAI API. If None, uses default. @@ -141,7 +141,7 @@ class BaseOpenAILLMService(LLMService): params: Input parameters for model configuration and behavior. .. deprecated:: 0.0.105 - Use ``settings=OpenAILLMSettings(...)`` instead. + Use ``settings=BaseOpenAILLMService.Settings(...)`` instead. settings: Runtime-updatable settings. When provided alongside deprecated parameters, ``settings`` values take precedence. @@ -150,7 +150,7 @@ class BaseOpenAILLMService(LLMService): **kwargs: Additional arguments passed to the parent LLMService. """ # 1. Initialize default_settings with hardcoded defaults - default_settings = OpenAILLMSettings( + default_settings = self.Settings( model="gpt-4o", system_instruction=None, frequency_penalty=NOT_GIVEN, diff --git a/src/pipecat/services/openai/image.py b/src/pipecat/services/openai/image.py index 6091863f3..31f9949b8 100644 --- a/src/pipecat/services/openai/image.py +++ b/src/pipecat/services/openai/image.py @@ -49,7 +49,7 @@ class OpenAIImageGenService(ImageGenService): """ Settings = OpenAIImageGenSettings - _settings: OpenAIImageGenSettings + _settings: Settings def __init__( self, @@ -61,7 +61,7 @@ class OpenAIImageGenService(ImageGenService): Literal["256x256", "512x512", "1024x1024", "1792x1024", "1024x1792"] ] = None, model: Optional[str] = None, - settings: Optional[OpenAIImageGenSettings] = None, + settings: Optional[Settings] = None, ): """Initialize the OpenAI image generation service. @@ -72,29 +72,29 @@ class OpenAIImageGenService(ImageGenService): image_size: Target size for generated images. Defaults to "1024x1024". .. deprecated:: 0.0.105 - Use ``settings=OpenAIImageGenSettings(image_size=...)`` instead. + Use ``settings=OpenAIImageGenService.Settings(image_size=...)`` instead. model: DALL-E model to use for generation. Defaults to "dall-e-3". .. deprecated:: 0.0.105 - Use ``settings=OpenAIImageGenSettings(model=...)`` instead. + Use ``settings=OpenAIImageGenService.Settings(model=...)`` instead. settings: Runtime-updatable settings. When provided alongside deprecated parameters, ``settings`` values take precedence. """ # 1. Initialize default_settings with hardcoded defaults - default_settings = OpenAIImageGenSettings( + default_settings = self.Settings( model="dall-e-3", image_size=None, ) # 2. Apply direct init arg overrides (deprecated) if model is not None: - _warn_deprecated_param("model", OpenAIImageGenSettings, "model") + _warn_deprecated_param("model", self.Settings, "model") default_settings.model = model if image_size is not None: - _warn_deprecated_param("image_size", OpenAIImageGenSettings, "image_size") + _warn_deprecated_param("image_size", self.Settings, "image_size") default_settings.image_size = image_size # 4. Apply settings delta (canonical API, always wins) diff --git a/src/pipecat/services/openai/llm.py b/src/pipecat/services/openai/llm.py index ab1384a4c..032d4dfa4 100644 --- a/src/pipecat/services/openai/llm.py +++ b/src/pipecat/services/openai/llm.py @@ -25,7 +25,7 @@ from pipecat.processors.aggregators.llm_response import ( LLMUserContextAggregator, ) from pipecat.processors.aggregators.openai_llm_context import OpenAILLMContext -from pipecat.services.openai.base_llm import BaseOpenAILLMService, OpenAILLMSettings +from pipecat.services.openai.base_llm import BaseOpenAILLMService from pipecat.services.settings import _warn_deprecated_param @@ -72,13 +72,15 @@ class OpenAILLMService(BaseOpenAILLMService): context aggregator creation. """ + Settings = BaseOpenAILLMService.Settings + def __init__( self, *, model: Optional[str] = None, service_tier: Optional[str] = None, params: Optional[BaseOpenAILLMService.InputParams] = None, - settings: Optional[OpenAILLMSettings] = None, + settings: Optional[Settings] = None, **kwargs, ): """Initialize OpenAI LLM service. @@ -87,20 +89,20 @@ class OpenAILLMService(BaseOpenAILLMService): model: The OpenAI model name to use. Defaults to "gpt-4.1". .. deprecated:: 0.0.105 - Use ``settings=OpenAILLMSettings(model=...)`` instead. + Use ``settings=OpenAILLMService.Settings(model=...)`` instead. service_tier: Service tier to use (e.g., "auto", "flex", "priority"). params: Input parameters for model configuration. .. deprecated:: 0.0.105 - Use ``settings=OpenAILLMSettings(...)`` instead. + Use ``settings=OpenAILLMService.Settings(...)`` instead. settings: Runtime-updatable settings. When provided alongside deprecated parameters, ``settings`` values take precedence. **kwargs: Additional arguments passed to the parent BaseOpenAILLMService. """ # 1. Initialize default_settings with hardcoded defaults - default_settings = OpenAILLMSettings( + default_settings = self.Settings( model="gpt-4.1", system_instruction=None, frequency_penalty=NOT_GIVEN, @@ -118,7 +120,7 @@ class OpenAILLMService(BaseOpenAILLMService): # 2. Apply direct init arg overrides (deprecated) if model is not None: - _warn_deprecated_param("model", OpenAILLMSettings, "model") + _warn_deprecated_param("model", self.Settings, "model") default_settings.model = model # Handle service_tier from deprecated params @@ -127,7 +129,7 @@ class OpenAILLMService(BaseOpenAILLMService): # 3. Apply params overrides — only if settings not provided if params is not None: - _warn_deprecated_param("params", OpenAILLMSettings) + _warn_deprecated_param("params", self.Settings) if not settings: default_settings.frequency_penalty = params.frequency_penalty default_settings.presence_penalty = params.presence_penalty diff --git a/src/pipecat/services/openai/realtime/llm.py b/src/pipecat/services/openai/realtime/llm.py index 23d044c5f..300792cbd 100644 --- a/src/pipecat/services/openai/realtime/llm.py +++ b/src/pipecat/services/openai/realtime/llm.py @@ -115,7 +115,7 @@ class OpenAIRealtimeLLMSettings(LLMSettings): # -- Bidirectional sync helpers ------------------------------------------ @staticmethod - def _sync_top_level_to_sp(settings: "OpenAIRealtimeLLMSettings"): + def _sync_top_level_to_sp(settings: "OpenAIRealtimeLLMService.Settings"): """Push top-level ``model``/``system_instruction`` into ``session_properties``.""" if not is_given(settings.session_properties): return @@ -127,7 +127,7 @@ class OpenAIRealtimeLLMSettings(LLMSettings): # -- apply_update override ----------------------------------------------- - def apply_update(self, delta: "OpenAIRealtimeLLMSettings") -> Dict[str, Any]: + def apply_update(self, delta: "OpenAIRealtimeLLMService.Settings") -> Dict[str, Any]: """Merge a delta, keeping ``model``/``system_instruction`` in sync with SP. When the delta contains ``session_properties``, it **replaces** the @@ -165,8 +165,8 @@ class OpenAIRealtimeLLMSettings(LLMSettings): @classmethod def from_mapping( - cls: Type["OpenAIRealtimeLLMSettings"], settings: Mapping[str, Any] - ) -> "OpenAIRealtimeLLMSettings": + cls: Type["OpenAIRealtimeLLMService.Settings"], settings: Mapping[str, Any] + ) -> "OpenAIRealtimeLLMService.Settings": """Build a delta from a plain dict, routing SP keys into ``session_properties``. Keys that correspond to ``SessionProperties`` fields (except ``model``) @@ -211,7 +211,7 @@ class OpenAIRealtimeLLMService(LLMService): """ Settings = OpenAIRealtimeLLMSettings - _settings: OpenAIRealtimeLLMSettings + _settings: Settings # Overriding the default adapter to use the OpenAIRealtimeLLMAdapter one. adapter_class = OpenAIRealtimeLLMAdapter @@ -223,7 +223,7 @@ class OpenAIRealtimeLLMService(LLMService): model: Optional[str] = None, base_url: str = "wss://api.openai.com/v1/realtime", session_properties: Optional[events.SessionProperties] = None, - settings: Optional[OpenAIRealtimeLLMSettings] = None, + settings: Optional[Settings] = None, start_audio_paused: bool = False, start_video_paused: bool = False, video_frame_detail: str = "auto", @@ -237,7 +237,7 @@ class OpenAIRealtimeLLMService(LLMService): model: OpenAI model name. .. deprecated:: 0.0.105 - Use ``settings=OpenAIRealtimeLLMSettings(model=...)`` instead. + Use ``settings=OpenAIRealtimeLLMService.Settings(model=...)`` instead. This is a connection-level parameter set via the WebSocket URL query parameter and cannot be changed during the session. @@ -247,7 +247,7 @@ class OpenAIRealtimeLLMService(LLMService): If None, uses default SessionProperties. .. deprecated:: 0.0.105 - Use ``settings=OpenAIRealtimeLLMSettings(session_properties=...)`` + Use ``settings=OpenAIRealtimeLLMService.Settings(session_properties=...)`` instead. settings: Runtime-updatable settings for this service. start_audio_paused: Whether to start with audio input paused. Defaults to False. @@ -277,7 +277,7 @@ class OpenAIRealtimeLLMService(LLMService): ) # 1. Initialize default_settings with hardcoded defaults - default_settings = OpenAIRealtimeLLMSettings( + default_settings = self.Settings( model="gpt-realtime-1.5", system_instruction=None, temperature=None, @@ -294,13 +294,13 @@ class OpenAIRealtimeLLMService(LLMService): # 2. Apply direct init arg overrides (deprecated) if model is not None: - _warn_deprecated_param("model", OpenAIRealtimeLLMSettings, "model") + _warn_deprecated_param("model", self.Settings, "model") default_settings.model = model if session_properties is not None: _warn_deprecated_param( "session_properties", - OpenAIRealtimeLLMSettings, + self.Settings, "session_properties", ) default_settings.session_properties = session_properties @@ -312,7 +312,7 @@ class OpenAIRealtimeLLMService(LLMService): default_settings.system_instruction = session_properties.instructions # Sync top-level model back into session_properties - OpenAIRealtimeLLMSettings._sync_top_level_to_sp(default_settings) + self.Settings._sync_top_level_to_sp(default_settings) # 3. Apply settings delta (canonical API, always wins) if settings is not None: diff --git a/src/pipecat/services/openai/stt.py b/src/pipecat/services/openai/stt.py index 473b23637..943be17de 100644 --- a/src/pipecat/services/openai/stt.py +++ b/src/pipecat/services/openai/stt.py @@ -40,7 +40,6 @@ from pipecat.services.stt_latency import OPENAI_REALTIME_TTFS_P99, OPENAI_TTFS_P from pipecat.services.stt_service import WebsocketSTTService from pipecat.services.whisper.base_stt import ( BaseWhisperSTTService, - BaseWhisperSTTSettings, Transcription, ) from pipecat.transcriptions.language import Language @@ -56,7 +55,7 @@ except ModuleNotFoundError: @dataclass -class OpenAISTTSettings(BaseWhisperSTTSettings): +class OpenAISTTSettings(BaseWhisperSTTService.Settings): """Settings for the OpenAI STT service.""" pass @@ -70,7 +69,7 @@ class OpenAISTTService(BaseWhisperSTTService): """ Settings = OpenAISTTSettings - _settings: OpenAISTTSettings + _settings: Settings def __init__( self, @@ -81,7 +80,7 @@ class OpenAISTTService(BaseWhisperSTTService): language: Optional[Language] = Language.EN, prompt: Optional[str] = None, temperature: Optional[float] = None, - settings: Optional[OpenAISTTSettings] = None, + settings: Optional[Settings] = None, ttfs_p99_latency: Optional[float] = OPENAI_TTFS_P99, **kwargs, ): @@ -91,24 +90,24 @@ class OpenAISTTService(BaseWhisperSTTService): model: Model to use — either gpt-4o or Whisper. .. deprecated:: 0.0.105 - Use ``settings=OpenAISTTSettings(model=...)`` instead. + Use ``settings=OpenAISTTService.Settings(model=...)`` instead. api_key: OpenAI API key. Defaults to None. base_url: API base URL. Defaults to None. language: Language of the audio input. Defaults to English. .. deprecated:: 0.0.105 - Use ``settings=OpenAISTTSettings(language=...)`` instead. + Use ``settings=OpenAISTTService.Settings(language=...)`` instead. prompt: Optional text to guide the model's style or continue a previous segment. .. deprecated:: 0.0.105 - Use ``settings=OpenAISTTSettings(prompt=...)`` instead. + Use ``settings=OpenAISTTService.Settings(prompt=...)`` instead. temperature: Optional sampling temperature between 0 and 1. Defaults to 0.0. .. deprecated:: 0.0.105 - Use ``settings=OpenAISTTSettings(temperature=...)`` instead. + Use ``settings=OpenAISTTService.Settings(temperature=...)`` instead. settings: Runtime-updatable settings. When provided alongside deprecated parameters, ``settings`` values take precedence. @@ -118,7 +117,7 @@ class OpenAISTTService(BaseWhisperSTTService): """ # --- 1. Hardcoded defaults --- _language = language or Language.EN - default_settings = OpenAISTTSettings( + default_settings = self.Settings( model="gpt-4o-transcribe", language=self.language_to_service_language(_language), prompt=None, @@ -127,13 +126,13 @@ class OpenAISTTService(BaseWhisperSTTService): # --- 2. Deprecated direct-arg overrides --- if model is not None: - _warn_deprecated_param("model", OpenAISTTSettings, "model") + _warn_deprecated_param("model", self.Settings, "model") default_settings.model = model if prompt is not None: - _warn_deprecated_param("prompt", OpenAISTTSettings, "prompt") + _warn_deprecated_param("prompt", self.Settings, "prompt") default_settings.prompt = prompt if temperature is not None: - _warn_deprecated_param("temperature", OpenAISTTSettings, "temperature") + _warn_deprecated_param("temperature", self.Settings, "temperature") default_settings.temperature = temperature # --- 3. (no params object for this service) --- @@ -234,7 +233,7 @@ class OpenAIRealtimeSTTService(WebsocketSTTService): """ Settings = OpenAIRealtimeSTTSettings - _settings: OpenAIRealtimeSTTSettings + _settings: Settings def __init__( self, @@ -247,7 +246,7 @@ class OpenAIRealtimeSTTService(WebsocketSTTService): turn_detection: Optional[Union[dict, Literal[False]]] = False, noise_reduction: Optional[Literal["near_field", "far_field"]] = None, should_interrupt: bool = True, - settings: Optional[OpenAIRealtimeSTTSettings] = None, + settings: Optional[Settings] = None, ttfs_p99_latency: Optional[float] = OPENAI_REALTIME_TTFS_P99, **kwargs, ): @@ -259,20 +258,20 @@ class OpenAIRealtimeSTTService(WebsocketSTTService): ``"gpt-4o-transcribe"`` and ``"gpt-4o-mini-transcribe"``. .. deprecated:: 0.0.105 - Use ``settings=OpenAIRealtimeSTTSettings(model=...)`` instead. + Use ``settings=OpenAIRealtimeSTTService.Settings(model=...)`` instead. base_url: WebSocket base URL for the Realtime API. Defaults to ``"wss://api.openai.com/v1/realtime"``. language: Language of the audio input. Defaults to English. .. deprecated:: 0.0.105 - Use ``settings=OpenAIRealtimeSTTSettings(language=...)`` instead. + Use ``settings=OpenAIRealtimeSTTService.Settings(language=...)`` instead. prompt: Optional prompt text to guide transcription style or provide keyword hints. .. deprecated:: 0.0.105 - Use ``settings=OpenAIRealtimeSTTSettings(prompt=...)`` instead. + Use ``settings=OpenAIRealtimeSTTService.Settings(prompt=...)`` instead. turn_detection: Server-side VAD configuration. Defaults to ``False`` (disabled), which relies on a local VAD @@ -284,7 +283,7 @@ class OpenAIRealtimeSTTService(WebsocketSTTService): microphones, or ``None`` to disable. .. deprecated:: 0.0.106 - Use ``settings=OpenAIRealtimeSTTSettings(noise_reduction=...)`` instead. + Use ``settings=OpenAIRealtimeSTTService.Settings(noise_reduction=...)`` instead. should_interrupt: Whether to interrupt bot output when speech is detected by server-side VAD. Only applies when turn detection is enabled. Defaults to True. @@ -302,7 +301,7 @@ class OpenAIRealtimeSTTService(WebsocketSTTService): ) # --- 1. Hardcoded defaults --- - default_settings = OpenAIRealtimeSTTSettings( + default_settings = self.Settings( model="gpt-4o-transcribe", language=Language.EN, prompt=None, @@ -311,16 +310,16 @@ class OpenAIRealtimeSTTService(WebsocketSTTService): # --- 2. Deprecated direct-arg overrides --- if model is not None: - _warn_deprecated_param("model", OpenAIRealtimeSTTSettings, "model") + _warn_deprecated_param("model", self.Settings, "model") default_settings.model = model if language is not None and language != Language.EN: - _warn_deprecated_param("language", OpenAIRealtimeSTTSettings, "language") + _warn_deprecated_param("language", self.Settings, "language") default_settings.language = language if prompt is not None: - _warn_deprecated_param("prompt", OpenAIRealtimeSTTSettings, "prompt") + _warn_deprecated_param("prompt", self.Settings, "prompt") default_settings.prompt = prompt if noise_reduction is not None: - _warn_deprecated_param("noise_reduction", OpenAIRealtimeSTTSettings, "noise_reduction") + _warn_deprecated_param("noise_reduction", self.Settings, "noise_reduction") default_settings.noise_reduction = noise_reduction # --- 3. (no params object for this service) --- @@ -376,7 +375,7 @@ class OpenAIRealtimeSTTService(WebsocketSTTService): Sends a ``session.update`` to the server when the session is active. Args: - delta: A :class:`STTSettings` (or ``OpenAIRealtimeSTTSettings``) delta. + delta: A :class:`STTSettings` (or ``OpenAIRealtimeSTTService.Settings``) delta. Returns: Dict mapping changed field names to their previous values. diff --git a/src/pipecat/services/openai/tts.py b/src/pipecat/services/openai/tts.py index 264475113..7eb80cd1e 100644 --- a/src/pipecat/services/openai/tts.py +++ b/src/pipecat/services/openai/tts.py @@ -82,7 +82,7 @@ class OpenAITTSService(TTSService): """ Settings = OpenAITTSSettings - _settings: OpenAITTSSettings + _settings: Settings OPENAI_SAMPLE_RATE = 24000 # OpenAI TTS always outputs at 24kHz @@ -90,7 +90,7 @@ class OpenAITTSService(TTSService): """Input parameters for OpenAI TTS configuration. .. deprecated:: 0.0.105 - Use ``settings=OpenAITTSSettings(...)`` instead. + Use ``settings=OpenAITTSService.Settings(...)`` instead. Parameters: instructions: Instructions to guide voice synthesis behavior. @@ -111,7 +111,7 @@ class OpenAITTSService(TTSService): instructions: Optional[str] = None, speed: Optional[float] = None, params: Optional[InputParams] = None, - settings: Optional[OpenAITTSSettings] = None, + settings: Optional[Settings] = None, **kwargs, ): """Initialize OpenAI TTS service. @@ -122,28 +122,28 @@ class OpenAITTSService(TTSService): voice: Voice ID to use for synthesis. Defaults to "alloy". .. deprecated:: 0.0.105 - Use ``settings=OpenAITTSSettings(voice=...)`` instead. + Use ``settings=OpenAITTSService.Settings(voice=...)`` instead. model: TTS model to use. Defaults to "gpt-4o-mini-tts". .. deprecated:: 0.0.105 - Use ``settings=OpenAITTSSettings(model=...)`` instead. + Use ``settings=OpenAITTSService.Settings(model=...)`` instead. sample_rate: Output audio sample rate in Hz. If None, uses OpenAI's default 24kHz. instructions: Optional instructions to guide voice synthesis behavior. .. deprecated:: 0.0.105 - Use ``settings=OpenAITTSSettings(instructions=...)`` instead. + Use ``settings=OpenAITTSService.Settings(instructions=...)`` instead. speed: Voice speed control (0.25 to 4.0, default 1.0). .. deprecated:: 0.0.105 - Use ``settings=OpenAITTSSettings(speed=...)`` instead. + Use ``settings=OpenAITTSService.Settings(speed=...)`` instead. params: Optional synthesis controls (acting instructions, speed, ...). .. deprecated:: 0.0.105 - Use ``settings=OpenAITTSSettings(...)`` instead. + Use ``settings=OpenAITTSService.Settings(...)`` instead. settings: Runtime-updatable settings. When provided alongside deprecated parameters, ``settings`` values take precedence. @@ -156,7 +156,7 @@ class OpenAITTSService(TTSService): ) # 1. Initialize default_settings with hardcoded defaults - default_settings = OpenAITTSSettings( + default_settings = self.Settings( model="gpt-4o-mini-tts", voice="alloy", language=None, @@ -166,21 +166,21 @@ class OpenAITTSService(TTSService): # 2. Apply direct init arg overrides (deprecated) if voice is not None: - _warn_deprecated_param("voice", OpenAITTSSettings, "voice") + _warn_deprecated_param("voice", self.Settings, "voice") default_settings.voice = voice if model is not None: - _warn_deprecated_param("model", OpenAITTSSettings, "model") + _warn_deprecated_param("model", self.Settings, "model") default_settings.model = model if instructions is not None: - _warn_deprecated_param("instructions", OpenAITTSSettings, "instructions") + _warn_deprecated_param("instructions", self.Settings, "instructions") default_settings.instructions = instructions if speed is not None: - _warn_deprecated_param("speed", OpenAITTSSettings, "speed") + _warn_deprecated_param("speed", self.Settings, "speed") default_settings.speed = speed # 3. Apply params overrides — only if settings not provided if params is not None: - _warn_deprecated_param("params", OpenAITTSSettings) + _warn_deprecated_param("params", self.Settings) if not settings: if params.instructions is not None: default_settings.instructions = params.instructions diff --git a/src/pipecat/services/openai_realtime_beta/azure.py b/src/pipecat/services/openai_realtime_beta/azure.py index 6497e1266..b590f2c29 100644 --- a/src/pipecat/services/openai_realtime_beta/azure.py +++ b/src/pipecat/services/openai_realtime_beta/azure.py @@ -11,7 +11,7 @@ from dataclasses import dataclass from loguru import logger -from .openai import OpenAIRealtimeBetaLLMService, OpenAIRealtimeBetaLLMSettings +from .openai import OpenAIRealtimeBetaLLMService try: from websockets.asyncio.client import connect as websocket_connect @@ -24,7 +24,7 @@ except ModuleNotFoundError as e: @dataclass -class AzureRealtimeBetaLLMSettings(OpenAIRealtimeBetaLLMSettings): +class AzureRealtimeBetaLLMSettings(OpenAIRealtimeBetaLLMService.Settings): """Settings for AzureRealtimeBetaLLMService.""" pass @@ -43,7 +43,7 @@ class AzureRealtimeBetaLLMService(OpenAIRealtimeBetaLLMService): """ Settings = AzureRealtimeBetaLLMSettings - _settings: AzureRealtimeBetaLLMSettings + _settings: Settings def __init__( self, diff --git a/src/pipecat/services/openai_realtime_beta/openai.py b/src/pipecat/services/openai_realtime_beta/openai.py index d8f817ffc..209ff3122 100644 --- a/src/pipecat/services/openai_realtime_beta/openai.py +++ b/src/pipecat/services/openai_realtime_beta/openai.py @@ -112,7 +112,7 @@ class OpenAIRealtimeBetaLLMService(LLMService): """ Settings = OpenAIRealtimeBetaLLMSettings - _settings: OpenAIRealtimeBetaLLMSettings + _settings: Settings # Overriding the default adapter to use the OpenAIRealtimeLLMAdapter one. adapter_class = OpenAIRealtimeLLMAdapter @@ -124,7 +124,7 @@ class OpenAIRealtimeBetaLLMService(LLMService): model: Optional[str] = None, base_url: str = "wss://api.openai.com/v1/realtime", session_properties: Optional[events.SessionProperties] = None, - settings: Optional[OpenAIRealtimeBetaLLMSettings] = None, + settings: Optional[Settings] = None, start_audio_paused: bool = False, send_transcription_frames: bool = True, **kwargs, @@ -136,7 +136,7 @@ class OpenAIRealtimeBetaLLMService(LLMService): model: OpenAI model name. .. deprecated:: 0.0.105 - Use ``settings=OpenAIRealtimeBetaLLMSettings(model=...)`` instead. + Use ``settings=OpenAIRealtimeBetaLLMService.Settings(model=...)`` instead. base_url: WebSocket base URL for the realtime API. Defaults to "wss://api.openai.com/v1/realtime". @@ -157,7 +157,7 @@ class OpenAIRealtimeBetaLLMService(LLMService): ) # 1. Initialize default_settings with hardcoded defaults - default_settings = OpenAIRealtimeBetaLLMSettings( + default_settings = self.Settings( model="gpt-4o-realtime-preview-2025-06-03", system_instruction=None, temperature=None, @@ -173,7 +173,7 @@ class OpenAIRealtimeBetaLLMService(LLMService): # 2. Apply direct init arg overrides (deprecated) if model is not None: - _warn_deprecated_param("model", OpenAIRealtimeBetaLLMSettings, "model") + _warn_deprecated_param("model", self.Settings, "model") default_settings.model = model # 3. Apply settings delta (canonical API, always wins) if settings is not None: diff --git a/src/pipecat/services/openpipe/llm.py b/src/pipecat/services/openpipe/llm.py index 3fef1e3af..a2198eb74 100644 --- a/src/pipecat/services/openpipe/llm.py +++ b/src/pipecat/services/openpipe/llm.py @@ -16,7 +16,7 @@ from typing import Dict, Optional from loguru import logger from pipecat.adapters.services.open_ai_adapter import OpenAILLMInvocationParams -from pipecat.services.openai.base_llm import OpenAILLMSettings +from pipecat.services.openai.base_llm import BaseOpenAILLMService from pipecat.services.openai.llm import OpenAILLMService from pipecat.services.settings import _warn_deprecated_param @@ -29,7 +29,7 @@ except ModuleNotFoundError as e: @dataclass -class OpenPipeLLMSettings(OpenAILLMSettings): +class OpenPipeLLMSettings(BaseOpenAILLMService.Settings): """Settings for OpenPipeLLMService.""" pass @@ -44,7 +44,7 @@ class OpenPipeLLMService(OpenAILLMService): """ Settings = OpenPipeLLMSettings - _settings: OpenPipeLLMSettings + _settings: Settings def __init__( self, @@ -55,7 +55,7 @@ class OpenPipeLLMService(OpenAILLMService): openpipe_api_key: Optional[str] = None, openpipe_base_url: str = "https://app.openpipe.ai/api/v1", tags: Optional[Dict[str, str]] = None, - settings: Optional[OpenPipeLLMSettings] = None, + settings: Optional[Settings] = None, **kwargs, ): """Initialize OpenPipe LLM service. @@ -64,7 +64,7 @@ class OpenPipeLLMService(OpenAILLMService): model: The model name to use. Defaults to "gpt-4.1". .. deprecated:: 0.0.105 - Use ``settings=OpenAILLMSettings(model=...)`` instead. + Use ``settings=OpenPipeLLMService.Settings(model=...)`` instead. api_key: OpenAI API key for authentication. If None, reads from environment. base_url: Custom OpenAI API endpoint URL. Uses default if None. @@ -76,11 +76,11 @@ class OpenPipeLLMService(OpenAILLMService): **kwargs: Additional arguments passed to parent OpenAILLMService. """ # 1. Initialize default_settings with hardcoded defaults - default_settings = OpenPipeLLMSettings(model="gpt-4.1") + default_settings = self.Settings(model="gpt-4.1") # 2. Apply direct init arg overrides (deprecated) if model is not None: - _warn_deprecated_param("model", OpenPipeLLMSettings, "model") + _warn_deprecated_param("model", self.Settings, "model") default_settings.model = model # 3. (No step 3, as there's no params object to apply) diff --git a/src/pipecat/services/openrouter/llm.py b/src/pipecat/services/openrouter/llm.py index d57c5cf24..84647890f 100644 --- a/src/pipecat/services/openrouter/llm.py +++ b/src/pipecat/services/openrouter/llm.py @@ -15,13 +15,13 @@ from typing import Any, Dict, Optional from loguru import logger -from pipecat.services.openai.base_llm import OpenAILLMSettings +from pipecat.services.openai.base_llm import BaseOpenAILLMService from pipecat.services.openai.llm import OpenAILLMService from pipecat.services.settings import _warn_deprecated_param @dataclass -class OpenRouterLLMSettings(OpenAILLMSettings): +class OpenRouterLLMSettings(BaseOpenAILLMService.Settings): """Settings for OpenRouterLLMService.""" pass @@ -35,7 +35,7 @@ class OpenRouterLLMService(OpenAILLMService): """ Settings = OpenRouterLLMSettings - _settings: OpenRouterLLMSettings + _settings: Settings def __init__( self, @@ -43,7 +43,7 @@ class OpenRouterLLMService(OpenAILLMService): api_key: Optional[str] = None, model: Optional[str] = None, base_url: str = "https://openrouter.ai/api/v1", - settings: Optional[OpenRouterLLMSettings] = None, + settings: Optional[Settings] = None, **kwargs, ): """Initialize the OpenRouter LLM service. @@ -54,7 +54,7 @@ class OpenRouterLLMService(OpenAILLMService): model: The model identifier to use. Defaults to "openai/gpt-4o-2024-11-20". .. deprecated:: 0.0.105 - Use ``settings=OpenAILLMSettings(model=...)`` instead. + Use ``settings=OpenRouterLLMService.Settings(model=...)`` instead. base_url: The base URL for OpenRouter API. Defaults to "https://openrouter.ai/api/v1". settings: Runtime-updatable settings. When provided alongside deprecated @@ -62,11 +62,11 @@ class OpenRouterLLMService(OpenAILLMService): **kwargs: Additional keyword arguments passed to OpenAILLMService. """ # 1. Initialize default_settings with hardcoded defaults - default_settings = OpenRouterLLMSettings(model="openai/gpt-4o-2024-11-20") + default_settings = self.Settings(model="openai/gpt-4o-2024-11-20") # 2. Apply direct init arg overrides (deprecated) if model is not None: - _warn_deprecated_param("model", OpenRouterLLMSettings, "model") + _warn_deprecated_param("model", self.Settings, "model") default_settings.model = model # 3. (No step 3, as there's no params object to apply) diff --git a/src/pipecat/services/perplexity/llm.py b/src/pipecat/services/perplexity/llm.py index b13fb20f0..c93a77c16 100644 --- a/src/pipecat/services/perplexity/llm.py +++ b/src/pipecat/services/perplexity/llm.py @@ -18,13 +18,13 @@ from pipecat.adapters.services.open_ai_adapter import OpenAILLMInvocationParams from pipecat.metrics.metrics import LLMTokenUsage from pipecat.processors.aggregators.llm_context import LLMContext from pipecat.processors.aggregators.openai_llm_context import OpenAILLMContext -from pipecat.services.openai.base_llm import OpenAILLMSettings +from pipecat.services.openai.base_llm import BaseOpenAILLMService from pipecat.services.openai.llm import OpenAILLMService from pipecat.services.settings import _warn_deprecated_param @dataclass -class PerplexityLLMSettings(OpenAILLMSettings): +class PerplexityLLMSettings(BaseOpenAILLMService.Settings): """Settings for PerplexityLLMService.""" pass @@ -39,7 +39,7 @@ class PerplexityLLMService(OpenAILLMService): """ Settings = PerplexityLLMSettings - _settings: PerplexityLLMSettings + _settings: Settings def __init__( self, @@ -47,7 +47,7 @@ class PerplexityLLMService(OpenAILLMService): api_key: str, base_url: str = "https://api.perplexity.ai", model: Optional[str] = None, - settings: Optional[PerplexityLLMSettings] = None, + settings: Optional[Settings] = None, **kwargs, ): """Initialize the Perplexity LLM service. @@ -58,18 +58,18 @@ class PerplexityLLMService(OpenAILLMService): model: The model identifier to use. Defaults to "sonar". .. deprecated:: 0.0.105 - Use ``settings=OpenAILLMSettings(model=...)`` instead. + Use ``settings=PerplexityLLMService.Settings(model=...)`` instead. settings: Runtime-updatable settings. When provided alongside deprecated parameters, ``settings`` values take precedence. **kwargs: Additional keyword arguments passed to OpenAILLMService. """ # 1. Initialize default_settings with hardcoded defaults - default_settings = PerplexityLLMSettings(model="sonar") + default_settings = self.Settings(model="sonar") # 2. Apply direct init arg overrides (deprecated) if model is not None: - _warn_deprecated_param("model", PerplexityLLMSettings, "model") + _warn_deprecated_param("model", self.Settings, "model") default_settings.model = model # 3. (No step 3, as there's no params object to apply) diff --git a/src/pipecat/services/piper/tts.py b/src/pipecat/services/piper/tts.py index 3cafd2dcd..0d56d377e 100644 --- a/src/pipecat/services/piper/tts.py +++ b/src/pipecat/services/piper/tts.py @@ -48,7 +48,7 @@ class PiperTTSService(TTSService): """ Settings = PiperTTSSettings - _settings: PiperTTSSettings + _settings: Settings def __init__( self, @@ -57,7 +57,7 @@ class PiperTTSService(TTSService): download_dir: Optional[Path] = None, force_redownload: bool = False, use_cuda: bool = False, - settings: Optional[PiperTTSSettings] = None, + settings: Optional[Settings] = None, **kwargs, ): """Initialize the Piper TTS service. @@ -66,7 +66,7 @@ class PiperTTSService(TTSService): voice_id: Piper voice model identifier (e.g. `en_US-ryan-high`). .. deprecated:: 0.0.105 - Use ``settings=PiperTTSSettings(voice=...)`` instead. + Use ``settings=PiperTTSService.Settings(voice=...)`` instead. download_dir: Directory for storing voice model files. Defaults to the current working directory. @@ -77,11 +77,11 @@ class PiperTTSService(TTSService): **kwargs: Additional arguments passed to the parent `TTSService`. """ # 1. Initialize default_settings with hardcoded defaults - default_settings = PiperTTSSettings(model=None, voice=None, language=None) + default_settings = self.Settings(model=None, voice=None, language=None) # 2. Apply direct init arg overrides (deprecated) if voice_id is not None: - _warn_deprecated_param("voice_id", PiperTTSSettings, "voice") + _warn_deprecated_param("voice_id", self.Settings, "voice") default_settings.voice = voice_id # 3. (No step 3, as there's no params object to apply) @@ -121,7 +121,7 @@ class PiperTTSService(TTSService): """ return True - async def _update_settings(self, delta: PiperTTSSettings) -> dict[str, Any]: + async def _update_settings(self, delta: Settings) -> dict[str, Any]: """Apply a settings delta. Settings are stored but not applied to the active connection. @@ -202,7 +202,7 @@ class PiperHttpTTSService(TTSService): """ Settings = PiperHttpTTSSettings - _settings: PiperHttpTTSSettings + _settings: Settings def __init__( self, @@ -210,7 +210,7 @@ class PiperHttpTTSService(TTSService): base_url: str, aiohttp_session: aiohttp.ClientSession, voice_id: Optional[str] = None, - settings: Optional[PiperHttpTTSSettings] = None, + settings: Optional[Settings] = None, **kwargs, ): """Initialize the Piper TTS service. @@ -221,18 +221,18 @@ class PiperHttpTTSService(TTSService): voice_id: Piper voice model identifier (e.g. `en_US-ryan-high`). .. deprecated:: 0.0.105 - Use ``settings=PiperHttpTTSSettings(voice=...)`` instead. + Use ``settings=PiperHttpTTSService.Settings(voice=...)`` instead. settings: Runtime-updatable settings. When provided alongside deprecated parameters, ``settings`` values take precedence. **kwargs: Additional arguments passed to the parent TTSService. """ # 1. Initialize default_settings with hardcoded defaults - default_settings = PiperHttpTTSSettings(model=None, voice=None, language=None) + default_settings = self.Settings(model=None, voice=None, language=None) # 2. Apply direct init arg overrides (deprecated) if voice_id is not None: - _warn_deprecated_param("voice_id", PiperHttpTTSSettings, "voice") + _warn_deprecated_param("voice_id", self.Settings, "voice") default_settings.voice = voice_id # 3. (No step 3, as there's no params object to apply) diff --git a/src/pipecat/services/qwen/llm.py b/src/pipecat/services/qwen/llm.py index d145f8339..4c3d7015c 100644 --- a/src/pipecat/services/qwen/llm.py +++ b/src/pipecat/services/qwen/llm.py @@ -11,13 +11,13 @@ from typing import Optional from loguru import logger -from pipecat.services.openai.base_llm import OpenAILLMSettings +from pipecat.services.openai.base_llm import BaseOpenAILLMService from pipecat.services.openai.llm import OpenAILLMService from pipecat.services.settings import _warn_deprecated_param @dataclass -class QwenLLMSettings(OpenAILLMSettings): +class QwenLLMSettings(BaseOpenAILLMService.Settings): """Settings for QwenLLMService.""" pass @@ -31,7 +31,7 @@ class QwenLLMService(OpenAILLMService): """ Settings = QwenLLMSettings - _settings: QwenLLMSettings + _settings: Settings def __init__( self, @@ -39,7 +39,7 @@ class QwenLLMService(OpenAILLMService): api_key: str, base_url: str = "https://dashscope-intl.aliyuncs.com/compatible-mode/v1", model: Optional[str] = None, - settings: Optional[QwenLLMSettings] = None, + settings: Optional[Settings] = None, **kwargs, ): """Initialize the Qwen LLM service. @@ -50,18 +50,18 @@ class QwenLLMService(OpenAILLMService): model: The model identifier to use. Defaults to "qwen-plus". .. deprecated:: 0.0.105 - Use ``settings=OpenAILLMSettings(model=...)`` instead. + Use ``settings=QwenLLMService.Settings(model=...)`` instead. settings: Runtime-updatable settings. When provided alongside deprecated parameters, ``settings`` values take precedence. **kwargs: Additional keyword arguments passed to OpenAILLMService. """ # 1. Initialize default_settings with hardcoded defaults - default_settings = QwenLLMSettings(model="qwen-plus") + default_settings = self.Settings(model="qwen-plus") # 2. Apply direct init arg overrides (deprecated) if model is not None: - _warn_deprecated_param("model", QwenLLMSettings, "model") + _warn_deprecated_param("model", self.Settings, "model") default_settings.model = model # 3. (No step 3, as there's no params object to apply) diff --git a/src/pipecat/services/resembleai/tts.py b/src/pipecat/services/resembleai/tts.py index 31977ca0b..7375b9a1b 100644 --- a/src/pipecat/services/resembleai/tts.py +++ b/src/pipecat/services/resembleai/tts.py @@ -52,7 +52,7 @@ class ResembleAITTSService(WebsocketTTSService): """ Settings = ResembleAITTSSettings - _settings: ResembleAITTSSettings + _settings: Settings def __init__( self, @@ -63,7 +63,7 @@ class ResembleAITTSService(WebsocketTTSService): precision: Optional[str] = "PCM_16", output_format: Optional[str] = "wav", sample_rate: Optional[int] = 22050, - settings: Optional[ResembleAITTSSettings] = None, + settings: Optional[Settings] = None, **kwargs, ): """Initialize the Resemble AI TTS service. @@ -73,7 +73,7 @@ class ResembleAITTSService(WebsocketTTSService): voice_id: Voice UUID to use for synthesis. .. deprecated:: 0.0.105 - Use ``settings=ResembleAITTSSettings(voice=...)`` instead. + Use ``settings=ResembleAITTSService.Settings(voice=...)`` instead. url: WebSocket URL for Resemble AI TTS API. precision: PCM bit depth (PCM_32, PCM_24, PCM_16, or MULAW). @@ -84,7 +84,7 @@ class ResembleAITTSService(WebsocketTTSService): **kwargs: Additional arguments passed to the parent service. """ # 1. Initialize default_settings with hardcoded defaults - default_settings = ResembleAITTSSettings( + default_settings = self.Settings( model=None, voice=None, language=None, @@ -92,7 +92,7 @@ class ResembleAITTSService(WebsocketTTSService): # 2. Apply direct init arg overrides (deprecated) if voice_id is not None: - _warn_deprecated_param("voice_id", ResembleAITTSSettings, "voice") + _warn_deprecated_param("voice_id", self.Settings, "voice") default_settings.voice = voice_id # 3. (No step 3, as there's no params object to apply) diff --git a/src/pipecat/services/rime/tts.py b/src/pipecat/services/rime/tts.py index 15cc8b88a..df1b269cd 100644 --- a/src/pipecat/services/rime/tts.py +++ b/src/pipecat/services/rime/tts.py @@ -132,13 +132,13 @@ class RimeTTSService(WebsocketTTSService): """ Settings = RimeTTSSettings - _settings: RimeTTSSettings + _settings: Settings class InputParams(BaseModel): """Configuration parameters for Rime TTS service. .. deprecated:: 0.0.105 - Use ``settings=RimeTTSSettings(...)`` instead. + Use ``settings=RimeTTSService.Settings(...)`` instead. Parameters: language: Language for synthesis. Defaults to English. @@ -177,7 +177,7 @@ class RimeTTSService(WebsocketTTSService): model: Optional[str] = None, sample_rate: Optional[int] = None, params: Optional[InputParams] = None, - settings: Optional[RimeTTSSettings] = None, + settings: Optional[Settings] = None, text_aggregator: Optional[BaseTextAggregator] = None, text_aggregation_mode: Optional[TextAggregationMode] = None, aggregate_sentences: Optional[bool] = None, @@ -190,19 +190,19 @@ class RimeTTSService(WebsocketTTSService): voice_id: ID of the voice to use. .. deprecated:: 0.0.105 - Use ``settings=RimeTTSSettings(voice=...)`` instead. + Use ``settings=RimeTTSService.Settings(voice=...)`` instead. url: Rime websocket API endpoint. model: Model ID to use for synthesis. .. deprecated:: 0.0.105 - Use ``settings=RimeTTSSettings(model=...)`` instead. + Use ``settings=RimeTTSService.Settings(model=...)`` instead. sample_rate: Audio sample rate in Hz. params: Additional configuration parameters. .. deprecated:: 0.0.105 - Use ``settings=RimeTTSSettings(...)`` instead. + Use ``settings=RimeTTSService.Settings(...)`` instead. settings: Runtime-updatable settings. When provided alongside deprecated parameters, ``settings`` values take precedence. @@ -220,7 +220,7 @@ class RimeTTSService(WebsocketTTSService): **kwargs: Additional arguments passed to parent class. """ # 1. Initialize default_settings with hardcoded defaults - default_settings = RimeTTSSettings( + default_settings = self.Settings( model="arcana", voice=None, language=None, @@ -241,15 +241,15 @@ class RimeTTSService(WebsocketTTSService): # 2. Apply direct init arg overrides (deprecated) if voice_id is not None: - _warn_deprecated_param("voice_id", RimeTTSSettings, "voice") + _warn_deprecated_param("voice_id", self.Settings, "voice") default_settings.voice = voice_id if model is not None: - _warn_deprecated_param("model", RimeTTSSettings, "model") + _warn_deprecated_param("model", self.Settings, "model") default_settings.model = model # 3. Apply params overrides — only if settings not provided if params is not None: - _warn_deprecated_param("params", RimeTTSSettings) + _warn_deprecated_param("params", self.Settings) if not settings: default_settings.language = ( self.language_to_service_language(params.language) if params.language else None @@ -663,13 +663,13 @@ class RimeHttpTTSService(TTSService): """ Settings = RimeTTSSettings - _settings: RimeTTSSettings + _settings: Settings class InputParams(BaseModel): """Configuration parameters for Rime HTTP TTS service. .. deprecated:: 0.0.105 - Use ``settings=RimeTTSSettings(...)`` instead. + Use ``settings=RimeHttpTTSService.Settings(...)`` instead. Parameters: language: Language for synthesis. Defaults to English. @@ -696,7 +696,7 @@ class RimeHttpTTSService(TTSService): model: Optional[str] = None, sample_rate: Optional[int] = None, params: Optional[InputParams] = None, - settings: Optional[RimeTTSSettings] = None, + settings: Optional[Settings] = None, **kwargs, ): """Initialize Rime HTTP TTS service. @@ -706,26 +706,26 @@ class RimeHttpTTSService(TTSService): voice_id: ID of the voice to use. .. deprecated:: 0.0.105 - Use ``settings=RimeTTSSettings(voice=...)`` instead. + Use ``settings=RimeHttpTTSService.Settings(voice=...)`` instead. aiohttp_session: Shared aiohttp session for HTTP requests. model: Model ID to use for synthesis. .. deprecated:: 0.0.105 - Use ``settings=RimeTTSSettings(model=...)`` instead. + Use ``settings=RimeHttpTTSService.Settings(model=...)`` instead. sample_rate: Audio sample rate in Hz. params: Additional configuration parameters. .. deprecated:: 0.0.105 - Use ``settings=RimeTTSSettings(...)`` instead. + Use ``settings=RimeHttpTTSService.Settings(...)`` instead. settings: Runtime-updatable settings. When provided alongside deprecated parameters, ``settings`` values take precedence. **kwargs: Additional arguments passed to parent TTSService. """ # 1. Initialize default_settings with hardcoded defaults - default_settings = RimeTTSSettings( + default_settings = self.Settings( model="mistv2", voice=None, language="eng", @@ -744,15 +744,15 @@ class RimeHttpTTSService(TTSService): # 2. Apply direct init arg overrides (deprecated) if voice_id is not None: - _warn_deprecated_param("voice_id", RimeTTSSettings, "voice") + _warn_deprecated_param("voice_id", self.Settings, "voice") default_settings.voice = voice_id if model is not None: - _warn_deprecated_param("model", RimeTTSSettings, "model") + _warn_deprecated_param("model", self.Settings, "model") default_settings.model = model # 3. Apply params overrides — only if settings not provided if params is not None: - _warn_deprecated_param("params", RimeTTSSettings) + _warn_deprecated_param("params", self.Settings) if not settings: default_settings.language = ( self.language_to_service_language(params.language) if params.language else "eng" @@ -888,13 +888,13 @@ class RimeNonJsonTTSService(InterruptibleTTSService): """ Settings = RimeNonJsonTTSSettings - _settings: RimeNonJsonTTSSettings + _settings: Settings class InputParams(BaseModel): """Configuration parameters for Rime Non-JSON WebSocket TTS service. .. deprecated:: 0.0.105 - Use ``settings=RimeNonJsonTTSSettings(...)`` instead. + Use ``settings=RimeNonJsonTTSService.Settings(...)`` instead. Args: language: Language for synthesis. Defaults to English. @@ -922,7 +922,7 @@ class RimeNonJsonTTSService(InterruptibleTTSService): audio_format: str = "pcm", sample_rate: Optional[int] = None, params: Optional[InputParams] = None, - settings: Optional[RimeNonJsonTTSSettings] = None, + settings: Optional[Settings] = None, aggregate_sentences: Optional[bool] = None, text_aggregation_mode: Optional[TextAggregationMode] = None, **kwargs, @@ -934,20 +934,20 @@ class RimeNonJsonTTSService(InterruptibleTTSService): voice_id: ID of the voice to use. .. deprecated:: 0.0.105 - Use ``settings=RimeNonJsonTTSSettings(voice=...)`` instead. + Use ``settings=RimeNonJsonTTSService.Settings(voice=...)`` instead. url: Rime websocket API endpoint. model: Model ID to use for synthesis. .. deprecated:: 0.0.105 - Use ``settings=RimeNonJsonTTSSettings(model=...)`` instead. + Use ``settings=RimeNonJsonTTSService.Settings(model=...)`` instead. audio_format: Audio format to use. sample_rate: Audio sample rate in Hz. params: Additional configuration parameters. .. deprecated:: 0.0.105 - Use ``settings=RimeNonJsonTTSSettings(...)`` instead. + Use ``settings=RimeNonJsonTTSService.Settings(...)`` instead. settings: Runtime-updatable settings. When provided alongside deprecated parameters, ``settings`` values take precedence. @@ -962,7 +962,7 @@ class RimeNonJsonTTSService(InterruptibleTTSService): **kwargs: Additional arguments passed to parent class. """ # 1. Initialize default_settings with hardcoded defaults - default_settings = RimeNonJsonTTSSettings( + default_settings = self.Settings( voice=None, model="arcana", language=None, @@ -974,15 +974,15 @@ class RimeNonJsonTTSService(InterruptibleTTSService): # 2. Apply direct init arg overrides (deprecated) if voice_id is not None: - _warn_deprecated_param("voice_id", RimeNonJsonTTSSettings, "voice") + _warn_deprecated_param("voice_id", self.Settings, "voice") default_settings.voice = voice_id if model is not None: - _warn_deprecated_param("model", RimeNonJsonTTSSettings, "model") + _warn_deprecated_param("model", self.Settings, "model") default_settings.model = model # 3. Apply params overrides — only if settings not provided if params is not None: - _warn_deprecated_param("params", RimeNonJsonTTSSettings) + _warn_deprecated_param("params", self.Settings) if not settings: default_settings.language = ( self.language_to_service_language(params.language) if params.language else None diff --git a/src/pipecat/services/sambanova/llm.py b/src/pipecat/services/sambanova/llm.py index 629c3d4c5..a77252ff8 100644 --- a/src/pipecat/services/sambanova/llm.py +++ b/src/pipecat/services/sambanova/llm.py @@ -22,14 +22,14 @@ from pipecat.metrics.metrics import LLMTokenUsage from pipecat.processors.aggregators.llm_context import LLMContext from pipecat.processors.aggregators.openai_llm_context import OpenAILLMContext from pipecat.services.llm_service import FunctionCallFromLLM -from pipecat.services.openai.base_llm import OpenAILLMSettings +from pipecat.services.openai.base_llm import BaseOpenAILLMService from pipecat.services.openai.llm import OpenAILLMService from pipecat.services.settings import _warn_deprecated_param from pipecat.utils.tracing.service_decorators import traced_llm @dataclass -class SambaNovaLLMSettings(OpenAILLMSettings): +class SambaNovaLLMSettings(BaseOpenAILLMService.Settings): """Settings for SambaNovaLLMService.""" pass @@ -43,7 +43,7 @@ class SambaNovaLLMService(OpenAILLMService): # type: ignore """ Settings = SambaNovaLLMSettings - _settings: SambaNovaLLMSettings + _settings: Settings def __init__( self, @@ -51,7 +51,7 @@ class SambaNovaLLMService(OpenAILLMService): # type: ignore api_key: str, model: Optional[str] = None, base_url: str = "https://api.sambanova.ai/v1", - settings: Optional[SambaNovaLLMSettings] = None, + settings: Optional[Settings] = None, **kwargs: Dict[Any, Any], ) -> None: """Initialize SambaNova LLM service. @@ -61,7 +61,7 @@ class SambaNovaLLMService(OpenAILLMService): # type: ignore model: The model identifier to use. Defaults to "Llama-4-Maverick-17B-128E-Instruct". .. deprecated:: 0.0.105 - Use ``settings=OpenAILLMSettings(model=...)`` instead. + Use ``settings=SambaNovaLLMService.Settings(model=...)`` instead. base_url: The base URL for SambaNova API. Defaults to "https://api.sambanova.ai/v1". settings: Runtime-updatable settings. When provided alongside deprecated @@ -69,11 +69,11 @@ class SambaNovaLLMService(OpenAILLMService): # type: ignore **kwargs: Additional keyword arguments passed to OpenAILLMService. """ # 1. Initialize default_settings with hardcoded defaults - default_settings = SambaNovaLLMSettings(model="Llama-4-Maverick-17B-128E-Instruct") + default_settings = self.Settings(model="Llama-4-Maverick-17B-128E-Instruct") # 2. Apply direct init arg overrides (deprecated) if model is not None: - _warn_deprecated_param("model", SambaNovaLLMSettings, "model") + _warn_deprecated_param("model", self.Settings, "model") default_settings.model = model # 3. (No step 3, as there's no params object to apply) diff --git a/src/pipecat/services/sambanova/stt.py b/src/pipecat/services/sambanova/stt.py index c273b67eb..c42a491e1 100644 --- a/src/pipecat/services/sambanova/stt.py +++ b/src/pipecat/services/sambanova/stt.py @@ -15,14 +15,13 @@ from pipecat.services.settings import _warn_deprecated_param from pipecat.services.stt_latency import SAMBANOVA_TTFS_P99 from pipecat.services.whisper.base_stt import ( BaseWhisperSTTService, - BaseWhisperSTTSettings, Transcription, ) from pipecat.transcriptions.language import Language @dataclass -class SambaNovaSTTSettings(BaseWhisperSTTSettings): +class SambaNovaSTTSettings(BaseWhisperSTTService.Settings): """Settings for the SambaNova STT service.""" pass @@ -46,7 +45,7 @@ class SambaNovaSTTService(BaseWhisperSTTService): # type: ignore language: Optional[Language] = None, prompt: Optional[str] = None, temperature: Optional[float] = None, - settings: Optional[SambaNovaSTTSettings] = None, + settings: Optional[Settings] = None, ttfs_p99_latency: Optional[float] = SAMBANOVA_TTFS_P99, **kwargs: Any, ) -> None: @@ -56,24 +55,24 @@ class SambaNovaSTTService(BaseWhisperSTTService): # type: ignore model: Whisper model to use. .. deprecated:: 0.0.105 - Use ``settings=SambaNovaSTTSettings(model=...)`` instead. + Use ``settings=SambaNovaSTTService.Settings(model=...)`` instead. api_key: SambaNova API key. Defaults to None. base_url: API base URL. Defaults to "https://api.sambanova.ai/v1". language: Language of the audio input. .. deprecated:: 0.0.105 - Use ``settings=SambaNovaSTTSettings(language=...)`` instead. + Use ``settings=SambaNovaSTTService.Settings(language=...)`` instead. prompt: Optional text to guide the model's style or continue a previous segment. .. deprecated:: 0.0.105 - Use ``settings=SambaNovaSTTSettings(prompt=...)`` instead. + Use ``settings=SambaNovaSTTService.Settings(prompt=...)`` instead. temperature: Optional sampling temperature between 0 and 1. .. deprecated:: 0.0.105 - Use ``settings=SambaNovaSTTSettings(temperature=...)`` instead. + Use ``settings=SambaNovaSTTService.Settings(temperature=...)`` instead. settings: Runtime-updatable settings. When provided alongside deprecated parameters, ``settings`` values take precedence. @@ -82,7 +81,7 @@ class SambaNovaSTTService(BaseWhisperSTTService): # type: ignore **kwargs: Additional arguments passed to `pipecat.services.whisper.base_stt.BaseWhisperSTTService`. """ # --- 1. Hardcoded defaults --- - default_settings = SambaNovaSTTSettings( + default_settings = self.Settings( model="Whisper-Large-v3", language=self.language_to_service_language(Language.EN), prompt=None, @@ -91,16 +90,16 @@ class SambaNovaSTTService(BaseWhisperSTTService): # type: ignore # --- 2. Deprecated direct-arg overrides --- if model is not None: - _warn_deprecated_param("model", SambaNovaSTTSettings, "model") + _warn_deprecated_param("model", self.Settings, "model") default_settings.model = model if language is not None: - _warn_deprecated_param("language", SambaNovaSTTSettings, "language") + _warn_deprecated_param("language", self.Settings, "language") default_settings.language = self.language_to_service_language(language) if prompt is not None: - _warn_deprecated_param("prompt", SambaNovaSTTSettings, "prompt") + _warn_deprecated_param("prompt", self.Settings, "prompt") default_settings.prompt = prompt if temperature is not None: - _warn_deprecated_param("temperature", SambaNovaSTTSettings, "temperature") + _warn_deprecated_param("temperature", self.Settings, "temperature") default_settings.temperature = temperature # --- 3. (no params object for this service) --- diff --git a/src/pipecat/services/sarvam/stt.py b/src/pipecat/services/sarvam/stt.py index 429973838..b2c02f7cd 100644 --- a/src/pipecat/services/sarvam/stt.py +++ b/src/pipecat/services/sarvam/stt.py @@ -172,13 +172,13 @@ class SarvamSTTService(STTService): """ Settings = SarvamSTTSettings - _settings: SarvamSTTSettings + _settings: Settings class InputParams(BaseModel): """Configuration parameters for Sarvam STT service. .. deprecated:: 0.0.105 - Use ``settings=SarvamSTTSettings(...)`` instead. + Use ``settings=SarvamSTTService.Settings(...)`` instead. Parameters: language: Target language for transcription. @@ -210,7 +210,7 @@ class SarvamSTTService(STTService): sample_rate: Optional[int] = None, input_audio_codec: str = "wav", params: Optional[InputParams] = None, - settings: Optional[SarvamSTTSettings] = None, + settings: Optional[Settings] = None, ttfs_p99_latency: Optional[float] = SARVAM_TTFS_P99, keepalive_timeout: Optional[float] = None, keepalive_interval: float = 5.0, @@ -223,7 +223,7 @@ class SarvamSTTService(STTService): model: Sarvam model to use for transcription. .. deprecated:: 0.0.105 - Use ``settings=SarvamSTTSettings(model=...)`` instead. + Use ``settings=SarvamSTTService.Settings(model=...)`` instead. mode: Mode of operation. Options: transcribe, translate, verbatim, translit, codemix. Only applicable to models that support it @@ -233,7 +233,7 @@ class SarvamSTTService(STTService): params: Configuration parameters for Sarvam STT service. .. deprecated:: 0.0.105 - Use ``settings=SarvamSTTSettings(...)`` instead. + Use ``settings=SarvamSTTService.Settings(...)`` instead. settings: Runtime-updatable settings. When provided alongside deprecated parameters, ``settings`` values take precedence. @@ -245,7 +245,7 @@ class SarvamSTTService(STTService): **kwargs: Additional arguments passed to the parent STTService. """ # --- 1. Hardcoded defaults --- - default_settings = SarvamSTTSettings( + default_settings = self.Settings( model="saarika:v2.5", language=None, prompt=None, @@ -255,12 +255,12 @@ class SarvamSTTService(STTService): # --- 2. Deprecated direct-arg overrides --- if model is not None: - _warn_deprecated_param("model", SarvamSTTSettings, "model") + _warn_deprecated_param("model", self.Settings, "model") default_settings.model = model # --- 3. Deprecated params overrides --- if params is not None: - _warn_deprecated_param("params", SarvamSTTSettings) + _warn_deprecated_param("params", self.Settings) if not settings: default_settings.language = params.language default_settings.prompt = params.prompt @@ -374,7 +374,7 @@ class SarvamSTTService(STTService): """Apply a settings delta, validate, sync state, and reconnect. Args: - delta: A :class:`STTSettings` (or ``SarvamSTTSettings``) delta. + delta: A :class:`STTSettings` (or ``SarvamSTTService.Settings``) delta. Returns: Dict mapping changed field names to their previous values. @@ -389,11 +389,7 @@ class SarvamSTTService(STTService): f"Model '{self._settings.model}' does not support language parameter " "(auto-detects language)." ) - if ( - isinstance(delta, SarvamSTTSettings) - and is_given(delta.prompt) - and delta.prompt is not None - ): + if isinstance(delta, self.Settings) and is_given(delta.prompt) and delta.prompt is not None: if not self._config.supports_prompt: raise ValueError( f"Model '{self._settings.model}' does not support prompt parameter." @@ -417,7 +413,7 @@ class SarvamSTTService(STTService): """Set the transcription/translation prompt and reconnect. .. deprecated:: 0.0.104 - Use ``STTUpdateSettingsFrame(SarvamSTTSettings(prompt=...))`` instead. + Use ``STTUpdateSettingsFrame(SarvamSTTService.Settings(prompt=...))`` instead. Args: prompt: Prompt text to guide transcription/translation style/context. @@ -430,7 +426,7 @@ class SarvamSTTService(STTService): warnings.simplefilter("always") warnings.warn( f"{self.__class__.__name__}.set_prompt() is deprecated. " - "Use STTUpdateSettingsFrame(SarvamSTTSettings(prompt=...)) instead.", + "Use STTUpdateSettingsFrame(self.Settings(prompt=...)) instead.", DeprecationWarning, stacklevel=2, ) diff --git a/src/pipecat/services/sarvam/tts.py b/src/pipecat/services/sarvam/tts.py index 0d6a872eb..a469dbf33 100644 --- a/src/pipecat/services/sarvam/tts.py +++ b/src/pipecat/services/sarvam/tts.py @@ -284,7 +284,7 @@ class SarvamHttpTTSSettings(TTSSettings): class SarvamTTSSettings(SarvamHttpTTSSettings): """Settings for SarvamTTSService. - Extends :class:`SarvamHttpTTSSettings` with WebSocket-specific buffering parameters. + Extends :class:`SarvamHttpTTSService.Settings` with WebSocket-specific buffering parameters. Parameters: min_buffer_size: Minimum characters to buffer before generating audio. @@ -352,13 +352,13 @@ class SarvamHttpTTSService(TTSService): """ Settings = SarvamHttpTTSSettings - _settings: SarvamHttpTTSSettings + _settings: Settings class InputParams(BaseModel): """Input parameters for Sarvam TTS configuration. .. deprecated:: 0.0.105 - Use ``SarvamHttpTTSSettings`` directly via the ``settings`` parameter instead. + Use ``SarvamHttpTTSService.Settings`` directly via the ``settings`` parameter instead. Parameters: language: Language for synthesis. Defaults to English (India). @@ -416,7 +416,7 @@ class SarvamHttpTTSService(TTSService): base_url: str = "https://api.sarvam.ai", sample_rate: Optional[int] = None, params: Optional[InputParams] = None, - settings: Optional[SarvamHttpTTSSettings] = None, + settings: Optional[Settings] = None, **kwargs, ): """Initialize the Sarvam TTS service. @@ -427,14 +427,14 @@ class SarvamHttpTTSService(TTSService): voice_id: Speaker voice ID. If None, uses model-appropriate default. .. deprecated:: 0.0.105 - Use ``settings=SarvamHttpTTSSettings(voice=...)`` instead. + Use ``settings=SarvamHttpTTSService.Settings(voice=...)`` instead. model: TTS model to use. Options: - "bulbul:v2" (default): Standard model with pitch/loudness support - "bulbul:v3-beta": Advanced model with temperature control .. deprecated:: 0.0.105 - Use ``settings=SarvamHttpTTSSettings(model=...)`` instead. + Use ``settings=SarvamHttpTTSService.Settings(model=...)`` instead. base_url: Sarvam AI API base URL. Defaults to "https://api.sarvam.ai". sample_rate: Audio sample rate in Hz (8000, 16000, 22050, 24000). @@ -442,14 +442,14 @@ class SarvamHttpTTSService(TTSService): params: Additional voice and preprocessing parameters. If None, uses defaults. .. deprecated:: 0.0.105 - Use ``settings=SarvamHttpTTSSettings(...)`` instead. + Use ``settings=SarvamHttpTTSService.Settings(...)`` instead. settings: Runtime-updatable settings. When provided alongside deprecated parameters, ``settings`` values take precedence. **kwargs: Additional arguments passed to parent TTSService. """ # 1. Initialize default_settings with hardcoded defaults - default_settings = SarvamHttpTTSSettings( + default_settings = self.Settings( model="bulbul:v2", voice="anushka", language="en-IN", @@ -462,15 +462,15 @@ class SarvamHttpTTSService(TTSService): # 2. Apply direct init arg overrides (deprecated) if model is not None: - _warn_deprecated_param("model", SarvamHttpTTSSettings, "model") + _warn_deprecated_param("model", self.Settings, "model") default_settings.model = model if voice_id is not None: - _warn_deprecated_param("voice_id", SarvamHttpTTSSettings, "voice") + _warn_deprecated_param("voice_id", self.Settings, "voice") default_settings.voice = voice_id # 3. Apply params overrides — only if settings not provided if params is not None: - _warn_deprecated_param("params", SarvamHttpTTSSettings) + _warn_deprecated_param("params", self.Settings) if not settings: if params.language is not None: default_settings.language = ( @@ -719,13 +719,13 @@ class SarvamTTSService(InterruptibleTTSService): """ Settings = SarvamTTSSettings - _settings: SarvamTTSSettings + _settings: Settings class InputParams(BaseModel): """Configuration parameters for Sarvam TTS WebSocket service. .. deprecated:: 0.0.105 - Use ``SarvamTTSSettings`` directly via the ``settings`` parameter instead. + Use ``SarvamTTSService.Settings`` directly via the ``settings`` parameter instead. Parameters: pitch: Voice pitch adjustment (-0.75 to 0.75). Defaults to 0.0. @@ -819,7 +819,7 @@ class SarvamTTSService(InterruptibleTTSService): text_aggregation_mode: Optional[TextAggregationMode] = None, sample_rate: Optional[int] = None, params: Optional[InputParams] = None, - settings: Optional[SarvamTTSSettings] = None, + settings: Optional[Settings] = None, **kwargs, ): """Initialize the Sarvam TTS service with voice and transport configuration. @@ -831,12 +831,12 @@ class SarvamTTSService(InterruptibleTTSService): - "bulbul:v3-beta": Advanced model with temperature control .. deprecated:: 0.0.105 - Use ``settings=SarvamTTSSettings(model=...)`` instead. + Use ``settings=SarvamTTSService.Settings(model=...)`` instead. voice_id: Speaker voice ID. If None, uses model-appropriate default. .. deprecated:: 0.0.105 - Use ``settings=SarvamTTSSettings(voice=...)`` instead. + Use ``settings=SarvamTTSService.Settings(voice=...)`` instead. url: WebSocket URL for the TTS backend (default production URL). aggregate_sentences: Deprecated. Use text_aggregation_mode instead. @@ -850,7 +850,7 @@ class SarvamTTSService(InterruptibleTTSService): params: Optional input parameters to override defaults. .. deprecated:: 0.0.105 - Use ``settings=SarvamTTSSettings(...)`` instead. + Use ``settings=SarvamTTSService.Settings(...)`` instead. settings: Runtime-updatable settings. When provided alongside deprecated parameters, ``settings`` values take precedence. @@ -859,7 +859,7 @@ class SarvamTTSService(InterruptibleTTSService): See https://docs.sarvam.ai/api-reference-docs/text-to-speech/stream """ # 1. Initialize default_settings with hardcoded defaults - default_settings = SarvamTTSSettings( + default_settings = self.Settings( model="bulbul:v2", voice="anushka", language="en-IN", @@ -874,10 +874,10 @@ class SarvamTTSService(InterruptibleTTSService): # 2. Apply direct init arg overrides (deprecated) if model is not None: - _warn_deprecated_param("model", SarvamTTSSettings, "model") + _warn_deprecated_param("model", self.Settings, "model") default_settings.model = model if voice_id is not None: - _warn_deprecated_param("voice_id", SarvamTTSSettings, "voice") + _warn_deprecated_param("voice_id", self.Settings, "voice") default_settings.voice = voice_id # Init-only audio format fields (not runtime-updatable) @@ -886,7 +886,7 @@ class SarvamTTSService(InterruptibleTTSService): # 3. Apply params overrides — only if settings not provided if params is not None: - _warn_deprecated_param("params", SarvamTTSSettings) + _warn_deprecated_param("params", self.Settings) if not settings: if params.language is not None: default_settings.language = ( diff --git a/src/pipecat/services/soniox/stt.py b/src/pipecat/services/soniox/stt.py index 6e5a8f62c..abf42dcdc 100644 --- a/src/pipecat/services/soniox/stt.py +++ b/src/pipecat/services/soniox/stt.py @@ -80,7 +80,7 @@ class SonioxInputParams(BaseModel): """Real-time transcription settings. .. deprecated:: 0.0.105 - Use ``settings=SonioxSTTSettings(...)`` instead. + Use ``settings=SonioxSTTService.Settings(...)`` instead. See Soniox WebSocket API documentation for more details: https://soniox.com/docs/speech-to-text/api-reference/websocket-api#configuration-parameters @@ -175,7 +175,7 @@ class SonioxSTTService(WebsocketSTTService): """ Settings = SonioxSTTSettings - _settings: SonioxSTTSettings + _settings: Settings def __init__( self, @@ -188,7 +188,7 @@ class SonioxSTTService(WebsocketSTTService): num_channels: int = 1, params: Optional[SonioxInputParams] = None, vad_force_turn_endpoint: bool = True, - settings: Optional[SonioxSTTSettings] = None, + settings: Optional[Settings] = None, ttfs_p99_latency: Optional[float] = SONIOX_TTFS_P99, **kwargs, ): @@ -201,7 +201,7 @@ class SonioxSTTService(WebsocketSTTService): model: Soniox model to use for transcription. .. deprecated:: 0.0.105 - Use ``settings=SonioxSTTSettings(model=...)`` instead. + Use ``settings=SonioxSTTService.Settings(model=...)`` instead. audio_format: Audio format for transcription. Defaults to ``"pcm_s16le"``. num_channels: Number of audio channels. Defaults to 1. @@ -209,7 +209,7 @@ class SonioxSTTService(WebsocketSTTService): speaker diarization. .. deprecated:: 0.0.105 - Use ``settings=SonioxSTTSettings(...)`` instead. + Use ``settings=SonioxSTTService.Settings(...)`` instead. vad_force_turn_endpoint: Listen to `VADUserStoppedSpeakingFrame` to send finalize message to Soniox. If disabled, Soniox will detect the end of the speech. Defaults to True. @@ -220,7 +220,7 @@ class SonioxSTTService(WebsocketSTTService): **kwargs: Additional arguments passed to the STTService. """ # --- 1. Hardcoded defaults --- - default_settings = SonioxSTTSettings( + default_settings = self.Settings( model="stt-rt-v4", language=None, language_hints=None, @@ -233,12 +233,12 @@ class SonioxSTTService(WebsocketSTTService): # --- 2. Deprecated direct-arg overrides --- if model is not None: - _warn_deprecated_param("model", SonioxSTTSettings, "model") + _warn_deprecated_param("model", self.Settings, "model") default_settings.model = model # --- 3. Deprecated params overrides --- if params is not None: - _warn_deprecated_param("params", SonioxSTTSettings) + _warn_deprecated_param("params", self.Settings) if not settings: default_settings.model = params.model if params.audio_format is not None: @@ -297,7 +297,7 @@ class SonioxSTTService(WebsocketSTTService): await super().start(frame) await self._connect() - async def _update_settings(self, delta: SonioxSTTSettings) -> dict[str, Any]: + async def _update_settings(self, delta: Settings) -> dict[str, Any]: """Apply settings delta and reconnect if anything changed. Args: diff --git a/src/pipecat/services/speechmatics/stt.py b/src/pipecat/services/speechmatics/stt.py index aaff90900..2a54b2b08 100644 --- a/src/pipecat/services/speechmatics/stt.py +++ b/src/pipecat/services/speechmatics/stt.py @@ -176,7 +176,7 @@ class SpeechmaticsSTTService(STTService): """ Settings = SpeechmaticsSTTSettings - _settings: SpeechmaticsSTTSettings + _settings: Settings # Export related classes as class attributes TurnDetectionMode = TurnDetectionMode @@ -343,7 +343,7 @@ class SpeechmaticsSTTService(STTService): """Update parameters for Speechmatics STT service. .. deprecated:: 0.0.104 - Use ``SpeechmaticsSTTSettings`` with ``STTUpdateSettingsFrame`` instead. + Use ``SpeechmaticsSTTService.Settings`` with ``STTUpdateSettingsFrame`` instead. Parameters: focus_speakers: List of speaker IDs to focus on. When enabled, only these speakers are @@ -380,7 +380,7 @@ class SpeechmaticsSTTService(STTService): encoding: AudioEncoding = AudioEncoding.PCM_S16LE, params: InputParams | None = None, should_interrupt: bool = True, - settings: SpeechmaticsSTTSettings | None = None, + settings: Settings | None = None, ttfs_p99_latency: float | None = SPEECHMATICS_TTFS_P99, **kwargs, ): @@ -396,7 +396,7 @@ class SpeechmaticsSTTService(STTService): params: Input parameters for the service. .. deprecated:: 0.0.105 - Use ``settings=SpeechmaticsSTTSettings(...)`` instead. + Use ``settings=SpeechmaticsSTTService.Settings(...)`` instead. should_interrupt: Determine whether the bot should be interrupted when Speechmatics turn_detection_mode is configured to detect user speech. settings: Runtime-updatable settings. When provided alongside deprecated @@ -424,7 +424,7 @@ class SpeechmaticsSTTService(STTService): self._check_deprecated_args(kwargs, _params) # --- 1. Hardcoded defaults --- - default_settings = SpeechmaticsSTTSettings( + default_settings = self.Settings( model=None, # Will be resolved from operating_point after config is built language=Language.EN, domain=None, @@ -454,7 +454,7 @@ class SpeechmaticsSTTService(STTService): # --- 3. Deprecated params overrides --- if params is not None: - _warn_deprecated_param("params", SpeechmaticsSTTSettings) + _warn_deprecated_param("params", self.Settings) if not settings: default_settings.language = _params.language default_settings.domain = _params.domain @@ -537,11 +537,11 @@ class SpeechmaticsSTTService(STTService): await super().start(frame) await self._connect() - async def _update_settings(self, delta: SpeechmaticsSTTSettings) -> dict[str, Any]: + async def _update_settings(self, delta: Settings) -> dict[str, Any]: """Apply settings delta, reconnecting only when necessary. Fields are classified into three categories (see - ``SpeechmaticsSTTSettings``): + ``SpeechmaticsSTTService.Settings``): * **HOT_FIELDS** – diarization speaker settings that can be pushed to a live Speechmatics connection without reconnecting. @@ -561,7 +561,7 @@ class SpeechmaticsSTTService(STTService): if not changed: return changed - no_reconnect = SpeechmaticsSTTSettings.HOT_FIELDS | SpeechmaticsSTTSettings.LOCAL_FIELDS + no_reconnect = self.Settings.HOT_FIELDS | self.Settings.LOCAL_FIELDS needs_reconnect = bool(changed.keys() - no_reconnect) if needs_reconnect: @@ -571,7 +571,7 @@ class SpeechmaticsSTTService(STTService): self._config = self._build_config(self._settings) await self._disconnect() await self._connect() - elif changed.keys() & SpeechmaticsSTTSettings.HOT_FIELDS: + elif changed.keys() & self.Settings.HOT_FIELDS: logger.debug(f"{self} applying hot settings update: {changed.keys()}") if self._config.enable_diarization: # Only hot-updatable fields changed — push to the live session. @@ -586,7 +586,7 @@ class SpeechmaticsSTTService(STTService): ) # Diarization not enabled — the new settings will take effect # if/when diarization is enabled, which does require a reconnect. - elif changed.keys() & SpeechmaticsSTTSettings.LOCAL_FIELDS: + elif changed.keys() & self.Settings.LOCAL_FIELDS: logger.debug( f"{self} local settings update, no special action required: {changed.keys()}" ) @@ -705,7 +705,7 @@ class SpeechmaticsSTTService(STTService): # CONFIGURATION # ============================================================================ - def _build_config(self, settings: SpeechmaticsSTTSettings) -> VoiceAgentConfig: + def _build_config(self, settings: Settings) -> VoiceAgentConfig: """Build a ``VoiceAgentConfig`` from the given settings. Used both at init time (with explicit settings, before @@ -778,7 +778,7 @@ class SpeechmaticsSTTService(STTService): .. deprecated:: 0.0.104 Use ``STTUpdateSettingsFrame`` with - ``SpeechmaticsSTTSettings(...)`` instead. + ``SpeechmaticsSTTService.Settings(...)`` instead. This can update the speakers to listen to or ignore during an in-flight transcription. Only available if diarization is enabled. @@ -790,7 +790,7 @@ class SpeechmaticsSTTService(STTService): warnings.simplefilter("always") warnings.warn( "update_params() is deprecated. Use STTUpdateSettingsFrame with " - "SpeechmaticsSTTSettings(...) instead.", + "self.Settings(...) instead.", DeprecationWarning, ) # Check possible diff --git a/src/pipecat/services/speechmatics/tts.py b/src/pipecat/services/speechmatics/tts.py index 20a3212ff..243437cb3 100644 --- a/src/pipecat/services/speechmatics/tts.py +++ b/src/pipecat/services/speechmatics/tts.py @@ -54,7 +54,7 @@ class SpeechmaticsTTSService(TTSService): """ Settings = SpeechmaticsTTSSettings - _settings: SpeechmaticsTTSSettings + _settings: Settings SPEECHMATICS_SAMPLE_RATE = 16000 @@ -62,7 +62,7 @@ class SpeechmaticsTTSService(TTSService): """Optional input parameters for Speechmatics TTS configuration. .. deprecated:: 0.0.105 - Use ``settings=SpeechmaticsTTSSettings(...)`` instead. + Use ``settings=SpeechmaticsTTSService.Settings(...)`` instead. Parameters: max_retries: Maximum number of retries for TTS requests. Defaults to 5. @@ -79,7 +79,7 @@ class SpeechmaticsTTSService(TTSService): aiohttp_session: aiohttp.ClientSession, sample_rate: Optional[int] = SPEECHMATICS_SAMPLE_RATE, params: Optional[InputParams] = None, - settings: Optional[SpeechmaticsTTSSettings] = None, + settings: Optional[Settings] = None, **kwargs, ): """Initialize the Speechmatics TTS service. @@ -90,14 +90,14 @@ class SpeechmaticsTTSService(TTSService): voice_id: Voice model to use for synthesis. .. deprecated:: 0.0.105 - Use ``settings=SpeechmaticsTTSSettings(voice=...)`` instead. + Use ``settings=SpeechmaticsTTSService.Settings(voice=...)`` instead. aiohttp_session: Shared aiohttp session for HTTP requests. sample_rate: Audio sample rate in Hz. params: Input parameters for the service. .. deprecated:: 0.0.105 - Use ``settings=SpeechmaticsTTSSettings(...)`` instead. + Use ``settings=SpeechmaticsTTSService.Settings(...)`` instead. settings: Runtime-updatable settings. When provided alongside deprecated parameters, ``settings`` values take precedence. @@ -110,7 +110,7 @@ class SpeechmaticsTTSService(TTSService): ) # 1. Initialize default_settings with hardcoded defaults - default_settings = SpeechmaticsTTSSettings( + default_settings = self.Settings( model=None, voice="sarah", language=None, @@ -119,12 +119,12 @@ class SpeechmaticsTTSService(TTSService): # 2. Apply direct init arg overrides (deprecated) if voice_id is not None: - _warn_deprecated_param("voice_id", SpeechmaticsTTSSettings, "voice") + _warn_deprecated_param("voice_id", self.Settings, "voice") default_settings.voice = voice_id # 3. Apply params overrides — only if settings not provided if params is not None: - _warn_deprecated_param("params", SpeechmaticsTTSSettings) + _warn_deprecated_param("params", self.Settings) if not settings: default_settings.max_retries = params.max_retries diff --git a/src/pipecat/services/tavus/video.py b/src/pipecat/services/tavus/video.py index 3d5946e54..9043710c8 100644 --- a/src/pipecat/services/tavus/video.py +++ b/src/pipecat/services/tavus/video.py @@ -60,7 +60,7 @@ class TavusVideoService(AIService): """ Settings = TavusVideoSettings - _settings: TavusVideoSettings + _settings: Settings def __init__( self, @@ -69,7 +69,7 @@ class TavusVideoService(AIService): replica_id: str, persona_id: str = "pipecat-stream", session: aiohttp.ClientSession, - settings: Optional[TavusVideoSettings] = None, + settings: Optional[Settings] = None, **kwargs, ) -> None: """Initialize the Tavus video service. diff --git a/src/pipecat/services/together/llm.py b/src/pipecat/services/together/llm.py index 21663206e..b1eb83d26 100644 --- a/src/pipecat/services/together/llm.py +++ b/src/pipecat/services/together/llm.py @@ -11,13 +11,13 @@ from typing import Optional from loguru import logger -from pipecat.services.openai.base_llm import OpenAILLMSettings +from pipecat.services.openai.base_llm import BaseOpenAILLMService from pipecat.services.openai.llm import OpenAILLMService from pipecat.services.settings import _warn_deprecated_param @dataclass -class TogetherLLMSettings(OpenAILLMSettings): +class TogetherLLMSettings(BaseOpenAILLMService.Settings): """Settings for TogetherLLMService.""" pass @@ -31,7 +31,7 @@ class TogetherLLMService(OpenAILLMService): """ Settings = TogetherLLMSettings - _settings: TogetherLLMSettings + _settings: Settings def __init__( self, @@ -39,7 +39,7 @@ class TogetherLLMService(OpenAILLMService): api_key: str, base_url: str = "https://api.together.xyz/v1", model: Optional[str] = None, - settings: Optional[TogetherLLMSettings] = None, + settings: Optional[Settings] = None, **kwargs, ): """Initialize Together.ai LLM service. @@ -50,18 +50,18 @@ class TogetherLLMService(OpenAILLMService): model: The model identifier to use. Defaults to "meta-llama/Meta-Llama-3.1-8B-Instruct-Turbo". .. deprecated:: 0.0.105 - Use ``settings=OpenAILLMSettings(model=...)`` instead. + Use ``settings=TogetherLLMService.Settings(model=...)`` instead. settings: Runtime-updatable settings. When provided alongside deprecated parameters, ``settings`` values take precedence. **kwargs: Additional keyword arguments passed to OpenAILLMService. """ # 1. Initialize default_settings with hardcoded defaults - default_settings = TogetherLLMSettings(model="meta-llama/Meta-Llama-3.1-8B-Instruct-Turbo") + default_settings = self.Settings(model="meta-llama/Meta-Llama-3.1-8B-Instruct-Turbo") # 2. Apply direct init arg overrides (deprecated) if model is not None: - _warn_deprecated_param("model", TogetherLLMSettings, "model") + _warn_deprecated_param("model", self.Settings, "model") default_settings.model = model # 3. (No step 3, as there's no params object to apply) diff --git a/src/pipecat/services/ultravox/llm.py b/src/pipecat/services/ultravox/llm.py index bfd34ceae..fe8a97549 100644 --- a/src/pipecat/services/ultravox/llm.py +++ b/src/pipecat/services/ultravox/llm.py @@ -167,13 +167,13 @@ class UltravoxRealtimeLLMService(LLMService): """ Settings = UltravoxRealtimeLLMSettings - _settings: UltravoxRealtimeLLMSettings + _settings: Settings def __init__( self, *, params: Union[AgentInputParams, OneShotInputParams, JoinUrlInputParams], - settings: Optional[UltravoxRealtimeLLMSettings] = None, + settings: Optional[Settings] = None, one_shot_selected_tools: Optional[ToolsSchema] = None, **kwargs, ): @@ -188,7 +188,7 @@ class UltravoxRealtimeLLMService(LLMService): **kwargs: Additional arguments passed to parent LLMService. """ # 1. Initialize default_settings with hardcoded defaults - default_settings = UltravoxRealtimeLLMSettings( + default_settings = self.Settings( model=None, system_instruction=None, temperature=None, @@ -383,7 +383,7 @@ class UltravoxRealtimeLLMService(LLMService): await self.cancel_task(self._receive_task, timeout=1.0) self._receive_task = None - async def _update_settings(self, delta: UltravoxRealtimeLLMSettings): + async def _update_settings(self, delta: Settings): changed = await super()._update_settings(delta) if "output_medium" in changed: await self._update_output_medium(self._settings.output_medium) diff --git a/src/pipecat/services/whisper/base_stt.py b/src/pipecat/services/whisper/base_stt.py index 869f92a55..d045eafc7 100644 --- a/src/pipecat/services/whisper/base_stt.py +++ b/src/pipecat/services/whisper/base_stt.py @@ -123,7 +123,7 @@ class BaseWhisperSTTService(SegmentedSTTService): """ Settings = BaseWhisperSTTSettings - _settings: BaseWhisperSTTSettings + _settings: Settings def __init__( self, @@ -136,7 +136,7 @@ class BaseWhisperSTTService(SegmentedSTTService): temperature: Optional[float] = None, include_prob_metrics: bool = False, push_empty_transcripts: bool = False, - settings: Optional[BaseWhisperSTTSettings] = None, + settings: Optional[Settings] = None, ttfs_p99_latency: Optional[float] = WHISPER_TTFS_P99, **kwargs, ): @@ -146,24 +146,24 @@ class BaseWhisperSTTService(SegmentedSTTService): model: Name of the Whisper model to use. .. deprecated:: 0.0.105 - Use ``settings=BaseWhisperSTTSettings(model=...)`` instead. + Use ``settings=BaseWhisperSTTService.Settings(model=...)`` instead. api_key: Service API key. Defaults to None. base_url: Service API base URL. Defaults to None. language: Language of the audio input. .. deprecated:: 0.0.105 - Use ``settings=BaseWhisperSTTSettings(language=...)`` instead. + Use ``settings=BaseWhisperSTTService.Settings(language=...)`` instead. prompt: Optional text to guide the model's style or continue a previous segment. .. deprecated:: 0.0.105 - Use ``settings=BaseWhisperSTTSettings(prompt=...)`` instead. + Use ``settings=BaseWhisperSTTService.Settings(prompt=...)`` instead. temperature: Sampling temperature between 0 and 1. .. deprecated:: 0.0.105 - Use ``settings=BaseWhisperSTTSettings(temperature=...)`` instead. + Use ``settings=BaseWhisperSTTService.Settings(temperature=...)`` instead. include_prob_metrics: If True, enables probability metrics in API response. Each service implements this differently (see child classes). @@ -181,7 +181,7 @@ class BaseWhisperSTTService(SegmentedSTTService): **kwargs: Additional arguments passed to SegmentedSTTService. """ # --- 1. Hardcoded defaults --- - default_settings = BaseWhisperSTTSettings( + default_settings = self.Settings( model=None, language=None, prompt=None, @@ -190,16 +190,16 @@ class BaseWhisperSTTService(SegmentedSTTService): # --- 2. Deprecated direct-arg overrides --- if model is not None: - _warn_deprecated_param("model", BaseWhisperSTTSettings, "model") + _warn_deprecated_param("model", self.Settings, "model") default_settings.model = model if language is not None: - _warn_deprecated_param("language", BaseWhisperSTTSettings, "language") + _warn_deprecated_param("language", self.Settings, "language") default_settings.language = self.language_to_service_language(language) if prompt is not None: - _warn_deprecated_param("prompt", BaseWhisperSTTSettings, "prompt") + _warn_deprecated_param("prompt", self.Settings, "prompt") default_settings.prompt = prompt if temperature is not None: - _warn_deprecated_param("temperature", BaseWhisperSTTSettings, "temperature") + _warn_deprecated_param("temperature", self.Settings, "temperature") default_settings.temperature = temperature # --- 3. (no params object for this service) --- diff --git a/src/pipecat/services/whisper/stt.py b/src/pipecat/services/whisper/stt.py index b5971ce9a..29574007a 100644 --- a/src/pipecat/services/whisper/stt.py +++ b/src/pipecat/services/whisper/stt.py @@ -208,7 +208,7 @@ class WhisperSTTService(SegmentedSTTService): """ Settings = WhisperSTTSettings - _settings: WhisperSTTSettings + _settings: Settings def __init__( self, @@ -218,7 +218,7 @@ class WhisperSTTService(SegmentedSTTService): compute_type: str = "default", no_speech_prob: Optional[float] = None, language: Optional[Language] = None, - settings: Optional[WhisperSTTSettings] = None, + settings: Optional[Settings] = None, **kwargs, ): """Initialize the Whisper STT service. @@ -227,7 +227,7 @@ class WhisperSTTService(SegmentedSTTService): model: The Whisper model to use for transcription. Can be a Model enum or string. .. deprecated:: 0.0.105 - Use ``settings=WhisperSTTSettings(model=...)`` instead. + Use ``settings=WhisperSTTService.Settings(model=...)`` instead. device: The device to run inference on ('cpu', 'cuda', or 'auto'). Defaults to ``"auto"``. @@ -236,19 +236,19 @@ class WhisperSTTService(SegmentedSTTService): no_speech_prob: Probability threshold for filtering out non-speech segments. .. deprecated:: 0.0.105 - Use ``settings=WhisperSTTSettings(no_speech_prob=...)`` instead. + Use ``settings=WhisperSTTService.Settings(no_speech_prob=...)`` instead. language: The default language for transcription. .. deprecated:: 0.0.105 - Use ``settings=WhisperSTTSettings(language=...)`` instead. + Use ``settings=WhisperSTTService.Settings(language=...)`` instead. settings: Runtime-updatable settings. When provided alongside deprecated parameters, ``settings`` values take precedence. **kwargs: Additional arguments passed to SegmentedSTTService. """ # --- 1. Hardcoded defaults --- - default_settings = WhisperSTTSettings( + default_settings = self.Settings( model=Model.DISTIL_MEDIUM_EN.value, language=Language.EN, no_speech_prob=0.4, @@ -256,13 +256,13 @@ class WhisperSTTService(SegmentedSTTService): # --- 2. Deprecated direct-arg overrides --- if model is not None: - _warn_deprecated_param("model", WhisperSTTSettings, "model") + _warn_deprecated_param("model", self.Settings, "model") default_settings.model = model if isinstance(model, str) else model.value if no_speech_prob is not None: - _warn_deprecated_param("no_speech_prob", WhisperSTTSettings, "no_speech_prob") + _warn_deprecated_param("no_speech_prob", self.Settings, "no_speech_prob") default_settings.no_speech_prob = no_speech_prob if language is not None: - _warn_deprecated_param("language", WhisperSTTSettings, "language") + _warn_deprecated_param("language", self.Settings, "language") default_settings.language = language # --- 3. (no params object for this service) --- @@ -382,7 +382,7 @@ class WhisperSTTServiceMLX(WhisperSTTService): """ Settings = WhisperMLXSTTSettings - _settings: WhisperMLXSTTSettings + _settings: Settings def __init__( self, @@ -391,7 +391,7 @@ class WhisperSTTServiceMLX(WhisperSTTService): no_speech_prob: Optional[float] = None, language: Optional[Language] = None, temperature: Optional[float] = None, - settings: Optional[WhisperMLXSTTSettings] = None, + settings: Optional[Settings] = None, **kwargs, ): """Initialize the MLX Whisper STT service. @@ -400,29 +400,29 @@ class WhisperSTTServiceMLX(WhisperSTTService): model: The MLX Whisper model to use for transcription. Can be an MLXModel enum or string. .. deprecated:: 0.0.105 - Use ``settings=WhisperMLXSTTSettings(model=...)`` instead. + Use ``settings=WhisperSTTServiceMLX.Settings(model=...)`` instead. no_speech_prob: Probability threshold for filtering out non-speech segments. .. deprecated:: 0.0.105 - Use ``settings=WhisperMLXSTTSettings(no_speech_prob=...)`` instead. + Use ``settings=WhisperSTTServiceMLX.Settings(no_speech_prob=...)`` instead. language: The default language for transcription. .. deprecated:: 0.0.105 - Use ``settings=WhisperMLXSTTSettings(language=...)`` instead. + Use ``settings=WhisperSTTServiceMLX.Settings(language=...)`` instead. temperature: Temperature for sampling. Can be a float or tuple of floats. .. deprecated:: 0.0.105 - Use ``settings=WhisperMLXSTTSettings(temperature=...)`` instead. + Use ``settings=WhisperSTTServiceMLX.Settings(temperature=...)`` instead. settings: Runtime-updatable settings. When provided alongside deprecated parameters, ``settings`` values take precedence. **kwargs: Additional arguments passed to SegmentedSTTService. """ # --- 1. Hardcoded defaults --- - default_settings = WhisperMLXSTTSettings( + default_settings = self.Settings( model=MLXModel.TINY.value, language=Language.EN, no_speech_prob=0.6, @@ -432,16 +432,16 @@ class WhisperSTTServiceMLX(WhisperSTTService): # --- 2. Deprecated direct-arg overrides --- if model is not None: - _warn_deprecated_param("model", WhisperMLXSTTSettings, "model") + _warn_deprecated_param("model", self.Settings, "model") default_settings.model = model if isinstance(model, str) else model.value if no_speech_prob is not None: - _warn_deprecated_param("no_speech_prob", WhisperMLXSTTSettings, "no_speech_prob") + _warn_deprecated_param("no_speech_prob", self.Settings, "no_speech_prob") default_settings.no_speech_prob = no_speech_prob if language is not None: - _warn_deprecated_param("language", WhisperMLXSTTSettings, "language") + _warn_deprecated_param("language", self.Settings, "language") default_settings.language = language if temperature is not None: - _warn_deprecated_param("temperature", WhisperMLXSTTSettings, "temperature") + _warn_deprecated_param("temperature", self.Settings, "temperature") default_settings.temperature = temperature # --- 3. (no params object for this service) --- diff --git a/src/pipecat/services/xtts/tts.py b/src/pipecat/services/xtts/tts.py index 32c2781f2..b769742f3 100644 --- a/src/pipecat/services/xtts/tts.py +++ b/src/pipecat/services/xtts/tts.py @@ -84,7 +84,7 @@ class XTTSService(TTSService): """ Settings = XTTSTTSSettings - _settings: XTTSTTSSettings + _settings: Settings def __init__( self, @@ -94,7 +94,7 @@ class XTTSService(TTSService): aiohttp_session: aiohttp.ClientSession, language: Language = Language.EN, sample_rate: Optional[int] = None, - settings: Optional[XTTSTTSSettings] = None, + settings: Optional[Settings] = None, **kwargs, ): """Initialize the XTTS service. @@ -103,7 +103,7 @@ class XTTSService(TTSService): voice_id: ID of the voice/speaker to use for synthesis. .. deprecated:: 0.0.105 - Use ``settings=XTTSTTSSettings(voice=...)`` instead. + Use ``settings=XTTSService.Settings(voice=...)`` instead. base_url: Base URL of the XTTS streaming server. aiohttp_session: HTTP session for making requests to the server. @@ -114,7 +114,7 @@ class XTTSService(TTSService): **kwargs: Additional arguments passed to parent TTSService. """ # 1. Initialize default_settings with hardcoded defaults - default_settings = XTTSTTSSettings( + default_settings = self.Settings( model=None, voice=None, language=self.language_to_service_language(language), @@ -122,7 +122,7 @@ class XTTSService(TTSService): # 2. Apply direct init arg overrides (deprecated) if voice_id is not None: - _warn_deprecated_param("voice_id", XTTSTTSSettings, "voice") + _warn_deprecated_param("voice_id", self.Settings, "voice") default_settings.voice = voice_id # 3. (No step 3, as there's no params object to apply) From 51a8a28a991be8e3ae8d651f03abc0c97537730c Mon Sep 17 00:00:00 2001 From: Paul Kompfner Date: Wed, 11 Mar 2026 12:34:10 -0400 Subject: [PATCH 0936/1060] Prefer Service.ThinkingConfig over raw ThinkingConfig class names in Anthropic and Google services and examples --- examples/foundational/49a-thinking-anthropic.py | 4 ++-- examples/foundational/49b-thinking-google.py | 4 ++-- .../foundational/49c-thinking-functions-anthropic.py | 4 ++-- .../foundational/49d-thinking-functions-google.py | 4 ++-- src/pipecat/services/anthropic/llm.py | 12 ++++++++---- src/pipecat/services/google/llm.py | 12 +++++++----- 6 files changed, 23 insertions(+), 17 deletions(-) diff --git a/examples/foundational/49a-thinking-anthropic.py b/examples/foundational/49a-thinking-anthropic.py index 8825ce7c5..727e8e0a7 100644 --- a/examples/foundational/49a-thinking-anthropic.py +++ b/examples/foundational/49a-thinking-anthropic.py @@ -22,7 +22,7 @@ from pipecat.processors.aggregators.llm_response_universal import ( ) from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport -from pipecat.services.anthropic.llm import AnthropicLLMService, AnthropicThinkingConfig +from pipecat.services.anthropic.llm import AnthropicLLMService from pipecat.services.cartesia.tts import CartesiaTTSService from pipecat.services.deepgram.stt import DeepgramSTTService from pipecat.transports.base_transport import BaseTransport, TransportParams @@ -64,7 +64,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): llm = AnthropicLLMService( api_key=os.getenv("ANTHROPIC_API_KEY"), settings=AnthropicLLMService.Settings( - thinking=AnthropicThinkingConfig( + thinking=AnthropicLLMService.ThinkingConfig( type="enabled", budget_tokens=2048, ), diff --git a/examples/foundational/49b-thinking-google.py b/examples/foundational/49b-thinking-google.py index ed7a393b0..b2b44d59a 100644 --- a/examples/foundational/49b-thinking-google.py +++ b/examples/foundational/49b-thinking-google.py @@ -24,7 +24,7 @@ from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport from pipecat.services.cartesia.tts import CartesiaTTSService from pipecat.services.deepgram.stt import DeepgramSTTService -from pipecat.services.google.llm import GoogleLLMService, GoogleThinkingConfig +from pipecat.services.google.llm import GoogleLLMService from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams @@ -65,7 +65,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): api_key=os.getenv("GOOGLE_API_KEY"), # model="gemini-3-pro-preview", # A more powerful reasoning model, but slower settings=GoogleLLMService.Settings( - thinking=GoogleThinkingConfig( + thinking=GoogleLLMService.ThinkingConfig( thinking_budget=-1, # Dynamic thinking include_thoughts=True, ), diff --git a/examples/foundational/49c-thinking-functions-anthropic.py b/examples/foundational/49c-thinking-functions-anthropic.py index bc9f334c8..d6b2749e1 100644 --- a/examples/foundational/49c-thinking-functions-anthropic.py +++ b/examples/foundational/49c-thinking-functions-anthropic.py @@ -23,7 +23,7 @@ from pipecat.processors.aggregators.llm_response_universal import ( ) from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport -from pipecat.services.anthropic.llm import AnthropicLLMService, AnthropicThinkingConfig +from pipecat.services.anthropic.llm import AnthropicLLMService from pipecat.services.cartesia.tts import CartesiaTTSService from pipecat.services.deepgram.stt import DeepgramSTTService from pipecat.services.llm_service import FunctionCallParams @@ -85,7 +85,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): llm = AnthropicLLMService( api_key=os.getenv("ANTHROPIC_API_KEY"), settings=AnthropicLLMService.Settings( - thinking=AnthropicThinkingConfig( + thinking=AnthropicLLMService.ThinkingConfig( type="enabled", budget_tokens=2048, ), diff --git a/examples/foundational/49d-thinking-functions-google.py b/examples/foundational/49d-thinking-functions-google.py index e8ecefcdd..f5b9a1d20 100644 --- a/examples/foundational/49d-thinking-functions-google.py +++ b/examples/foundational/49d-thinking-functions-google.py @@ -25,7 +25,7 @@ from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport from pipecat.services.cartesia.tts import CartesiaTTSService from pipecat.services.deepgram.stt import DeepgramSTTService -from pipecat.services.google.llm import GoogleLLMService, GoogleThinkingConfig +from pipecat.services.google.llm import GoogleLLMService from pipecat.services.llm_service import FunctionCallParams from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams @@ -86,7 +86,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): api_key=os.getenv("GOOGLE_API_KEY"), # model="gemini-3-pro-preview", # A more powerful reasoning model, but slower settings=GoogleLLMService.Settings( - thinking=GoogleThinkingConfig( + thinking=GoogleLLMService.ThinkingConfig( thinking_budget=-1, # Dynamic thinking include_thoughts=True, ), diff --git a/src/pipecat/services/anthropic/llm.py b/src/pipecat/services/anthropic/llm.py index 0c6d436e1..2f77e1665 100644 --- a/src/pipecat/services/anthropic/llm.py +++ b/src/pipecat/services/anthropic/llm.py @@ -98,18 +98,20 @@ class AnthropicLLMSettings(LLMSettings): """ enable_prompt_caching: bool | _NotGiven = field(default_factory=lambda: _NOT_GIVEN) - thinking: AnthropicThinkingConfig | _NotGiven = field(default_factory=lambda: _NOT_GIVEN) + thinking: Union["AnthropicLLMService.ThinkingConfig", _NotGiven] = field( + default_factory=lambda: _NOT_GIVEN + ) @classmethod def from_mapping(cls, settings): """Convert a plain dict to settings, coercing thinking dicts. For backward compatibility, a ``thinking`` value that is a plain dict - is converted to a :class:`AnthropicThinkingConfig`. + is converted to a :class:`AnthropicLLMService.ThinkingConfig`. """ instance = super().from_mapping(settings) if is_given(instance.thinking) and isinstance(instance.thinking, dict): - instance.thinking = AnthropicThinkingConfig(**instance.thinking) + instance.thinking = AnthropicLLMService.ThinkingConfig(**instance.thinking) return instance @@ -199,7 +201,9 @@ class AnthropicLLMService(LLMService): temperature: Optional[float] = Field(default_factory=lambda: NOT_GIVEN, ge=0.0, le=1.0) top_k: Optional[int] = Field(default_factory=lambda: NOT_GIVEN, ge=0) top_p: Optional[float] = Field(default_factory=lambda: NOT_GIVEN, ge=0.0, le=1.0) - thinking: Optional[AnthropicThinkingConfig] = Field(default_factory=lambda: NOT_GIVEN) + thinking: Optional["AnthropicLLMService.ThinkingConfig"] = Field( + default_factory=lambda: NOT_GIVEN + ) extra: Optional[Dict[str, Any]] = Field(default_factory=dict) def model_post_init(self, __context): diff --git a/src/pipecat/services/google/llm.py b/src/pipecat/services/google/llm.py index 2ade23906..02b5a5c19 100644 --- a/src/pipecat/services/google/llm.py +++ b/src/pipecat/services/google/llm.py @@ -16,7 +16,7 @@ import json import os import uuid from dataclasses import dataclass, field -from typing import Any, AsyncIterator, Dict, List, Literal, Optional +from typing import Any, AsyncIterator, Dict, List, Literal, Optional, Union from loguru import logger from PIL import Image @@ -719,18 +719,20 @@ class GoogleLLMSettings(LLMSettings): thinking: Thinking configuration. """ - thinking: GoogleThinkingConfig | _NotGiven = field(default_factory=lambda: NOT_GIVEN) + thinking: Union["GoogleLLMService.ThinkingConfig", _NotGiven] = field( + default_factory=lambda: NOT_GIVEN + ) @classmethod def from_mapping(cls, settings): """Convert a plain dict to settings, coercing thinking dicts. For backward compatibility, a ``thinking`` value that is a plain dict - is converted to a :class:`GoogleThinkingConfig`. + is converted to a :class:`GoogleLLMService.ThinkingConfig`. """ instance = super().from_mapping(settings) if is_given(instance.thinking) and isinstance(instance.thinking, dict): - instance.thinking = GoogleThinkingConfig(**instance.thinking) + instance.thinking = GoogleLLMService.ThinkingConfig(**instance.thinking) return instance @@ -775,7 +777,7 @@ class GoogleLLMService(LLMService): temperature: Optional[float] = Field(default=None, ge=0.0, le=2.0) top_k: Optional[int] = Field(default=None, ge=0) top_p: Optional[float] = Field(default=None, ge=0.0, le=1.0) - thinking: Optional[GoogleThinkingConfig] = Field(default=None) + thinking: Optional["GoogleLLMService.ThinkingConfig"] = Field(default=None) extra: Optional[Dict[str, Any]] = Field(default_factory=dict) def __init__( From eb9212f152a8e08575103ec2ee33cd1cecc8deb4 Mon Sep 17 00:00:00 2001 From: Paul Kompfner Date: Wed, 11 Mar 2026 12:37:43 -0400 Subject: [PATCH 0937/1060] Update COMMUNITY_INTEGRATIONS.md code sample to prefer Settings alias over raw settings class name --- COMMUNITY_INTEGRATIONS.md | 6 +++--- 1 file changed, 3 insertions(+), 3 deletions(-) diff --git a/COMMUNITY_INTEGRATIONS.md b/COMMUNITY_INTEGRATIONS.md index f6f92a5d3..c7e4c8e90 100644 --- a/COMMUNITY_INTEGRATIONS.md +++ b/COMMUNITY_INTEGRATIONS.md @@ -280,17 +280,17 @@ from typing import Optional class MyTTSService(TTSService): Settings = MyTTSSettings - _settings: MyTTSSettings + _settings: Settings def __init__( self, *, api_key: str, - settings: Optional[MyTTSSettings] = None, + settings: Optional[Settings] = None, **kwargs, ): # 1. Defaults — every field has a real value (store mode). - default_settings = MyTTSSettings( + default_settings = self.Settings( model="my-model-v1", voice="default-voice", language="en", From e5b60ba0957b060abb962322111d0e44fd662217 Mon Sep 17 00:00:00 2001 From: Paul Kompfner Date: Wed, 11 Mar 2026 13:04:15 -0400 Subject: [PATCH 0938/1060] Make deprecated-init-param warnings recommend the preferred Service.Settings(...) pattern Move the warning helper into AIService as _warn_init_param_moved_to_settings. It now uses type(self).__name__ to produce messages like "Use settings=AnthropicLLMService.Settings(model=...)" instead of the raw settings class name "AnthropicLLMSettings(model=...)". Callers no longer need to pass the settings class explicitly. --- src/pipecat/services/ai_service.py | 38 ++++++++++++++++++ src/pipecat/services/anthropic/llm.py | 6 +-- src/pipecat/services/assemblyai/stt.py | 6 +-- src/pipecat/services/asyncai/tts.py | 14 +++---- src/pipecat/services/aws/llm.py | 8 ++-- src/pipecat/services/aws/nova_sonic/llm.py | 8 ++-- src/pipecat/services/aws/stt.py | 4 +- src/pipecat/services/aws/tts.py | 6 +-- src/pipecat/services/azure/image.py | 6 +-- src/pipecat/services/azure/llm.py | 3 +- src/pipecat/services/azure/stt.py | 4 +- src/pipecat/services/azure/tts.py | 10 ++--- src/pipecat/services/camb/tts.py | 8 ++-- src/pipecat/services/cartesia/stt.py | 4 +- src/pipecat/services/cartesia/tts.py | 14 +++---- src/pipecat/services/cerebras/llm.py | 3 +- src/pipecat/services/deepgram/flux/stt.py | 6 +-- .../services/deepgram/sagemaker/stt.py | 4 +- .../services/deepgram/sagemaker/tts.py | 4 +- src/pipecat/services/deepgram/stt.py | 3 +- src/pipecat/services/deepgram/tts.py | 6 +-- src/pipecat/services/deepseek/llm.py | 3 +- src/pipecat/services/elevenlabs/stt.py | 10 ++--- src/pipecat/services/elevenlabs/tts.py | 14 +++---- src/pipecat/services/fal/image.py | 6 +-- src/pipecat/services/fal/stt.py | 4 +- src/pipecat/services/fireworks/llm.py | 3 +- src/pipecat/services/fish/tts.py | 8 ++-- src/pipecat/services/gladia/stt.py | 6 +-- .../services/google/gemini_live/llm.py | 8 ++-- .../services/google/gemini_live/vertex/llm.py | 7 ++-- src/pipecat/services/google/image.py | 4 +- src/pipecat/services/google/llm.py | 7 ++-- src/pipecat/services/google/openai/llm.py | 3 +- src/pipecat/services/google/stt.py | 4 +- src/pipecat/services/google/tts.py | 15 ++++--- src/pipecat/services/google/vertex/llm.py | 7 ++-- src/pipecat/services/gradium/stt.py | 4 +- src/pipecat/services/gradium/tts.py | 8 ++-- src/pipecat/services/grok/llm.py | 3 +- src/pipecat/services/grok/realtime/llm.py | 1 - src/pipecat/services/groq/llm.py | 3 +- src/pipecat/services/groq/stt.py | 9 ++--- src/pipecat/services/groq/tts.py | 8 ++-- src/pipecat/services/hume/tts.py | 6 +-- src/pipecat/services/inworld/tts.py | 14 +++---- src/pipecat/services/kokoro/tts.py | 6 +-- src/pipecat/services/lmnt/tts.py | 6 +-- src/pipecat/services/minimax/tts.py | 8 ++-- src/pipecat/services/mistral/llm.py | 3 +- src/pipecat/services/moondream/vision.py | 4 +- src/pipecat/services/neuphonic/tts.py | 10 ++--- src/pipecat/services/nvidia/llm.py | 3 +- src/pipecat/services/nvidia/stt.py | 6 +-- src/pipecat/services/nvidia/tts.py | 6 +-- src/pipecat/services/ollama/llm.py | 3 +- src/pipecat/services/openai/image.py | 6 +-- src/pipecat/services/openai/llm.py | 5 +-- src/pipecat/services/openai/realtime/llm.py | 3 +- src/pipecat/services/openai/stt.py | 16 ++++---- src/pipecat/services/openai/tts.py | 12 +++--- .../services/openai_realtime_beta/openai.py | 4 +- src/pipecat/services/openpipe/llm.py | 3 +- src/pipecat/services/openrouter/llm.py | 3 +- src/pipecat/services/perplexity/llm.py | 3 +- src/pipecat/services/piper/tts.py | 6 +-- src/pipecat/services/qwen/llm.py | 3 +- src/pipecat/services/resembleai/tts.py | 4 +- src/pipecat/services/rime/tts.py | 20 +++++----- src/pipecat/services/sambanova/llm.py | 3 +- src/pipecat/services/sambanova/stt.py | 9 ++--- src/pipecat/services/sarvam/stt.py | 5 +-- src/pipecat/services/sarvam/tts.py | 14 +++---- src/pipecat/services/settings.py | 40 ------------------- src/pipecat/services/soniox/stt.py | 6 +-- src/pipecat/services/speechmatics/stt.py | 4 +- src/pipecat/services/speechmatics/tts.py | 6 +-- src/pipecat/services/together/llm.py | 3 +- src/pipecat/services/whisper/base_stt.py | 10 ++--- src/pipecat/services/whisper/stt.py | 16 ++++---- src/pipecat/services/xtts/tts.py | 4 +- 81 files changed, 282 insertions(+), 311 deletions(-) diff --git a/src/pipecat/services/ai_service.py b/src/pipecat/services/ai_service.py index c4e45a417..dd9ef1dba 100644 --- a/src/pipecat/services/ai_service.py +++ b/src/pipecat/services/ai_service.py @@ -10,6 +10,7 @@ Provides the foundation for all AI services in the Pipecat framework, including model management, settings handling, and frame processing lifecycle methods. """ +import warnings from typing import Any, AsyncGenerator, Dict from loguru import logger @@ -130,6 +131,43 @@ class AIService(FrameProcessor): return changed + def _warn_init_param_moved_to_settings( + self, + param_name: str, + settings_field: str | None = None, + stacklevel: int = 3, + ): + """Warn that an ``__init__`` param has moved to ``Settings``. + + Emits a ``DeprecationWarning`` directing users to the canonical + ``settings=ServiceClass.Settings(field=...)`` API. + + Args: + param_name: Name of the deprecated ``__init__`` parameter. + settings_field: The corresponding field on the ``Settings`` + dataclass, if different from *param_name*. When ``None`` + the message omits the field hint. + stacklevel: Stack depth for the warning. Default ``3`` targets + the caller's caller (i.e. user code that instantiated the + service). + """ + label = f"{type(self).__name__}.Settings" + if settings_field: + msg = ( + f"The `{param_name}` parameter is deprecated. " + f"Use `settings={label}({settings_field}=...)` instead. " + f"If both are provided, `settings` takes precedence." + ) + else: + msg = ( + f"The `{param_name}` parameter is deprecated. " + f"Use `settings={label}(...)` instead. " + f"If both are provided, `settings` takes precedence." + ) + with warnings.catch_warnings(): + warnings.simplefilter("always") + warnings.warn(msg, DeprecationWarning, stacklevel=stacklevel) + def _warn_unhandled_updated_settings(self, unhandled): """Log a warning for settings changes that won't take effect at runtime. diff --git a/src/pipecat/services/anthropic/llm.py b/src/pipecat/services/anthropic/llm.py index 2f77e1665..fcaed1dfe 100644 --- a/src/pipecat/services/anthropic/llm.py +++ b/src/pipecat/services/anthropic/llm.py @@ -58,7 +58,7 @@ from pipecat.processors.aggregators.openai_llm_context import ( from pipecat.processors.frame_processor import FrameDirection from pipecat.services.llm_service import FunctionCallFromLLM, LLMService from pipecat.services.settings import NOT_GIVEN as _NOT_GIVEN -from pipecat.services.settings import LLMSettings, _NotGiven, _warn_deprecated_param, is_given +from pipecat.services.settings import LLMSettings, _NotGiven, is_given from pipecat.utils.tracing.service_decorators import traced_llm try: @@ -272,12 +272,12 @@ class AnthropicLLMService(LLMService): # 2. Apply direct init arg overrides (deprecated) if model is not None: - _warn_deprecated_param("model", self.Settings, "model") + self._warn_init_param_moved_to_settings("model", "model") default_settings.model = model # 3. Apply params overrides — only if settings not provided if params is not None: - _warn_deprecated_param("params", self.Settings) + self._warn_init_param_moved_to_settings("params") if not settings: default_settings.max_tokens = params.max_tokens default_settings.temperature = params.temperature diff --git a/src/pipecat/services/assemblyai/stt.py b/src/pipecat/services/assemblyai/stt.py index e7a2854b0..f52c1d935 100644 --- a/src/pipecat/services/assemblyai/stt.py +++ b/src/pipecat/services/assemblyai/stt.py @@ -32,7 +32,7 @@ from pipecat.frames.frames import ( VADUserStoppedSpeakingFrame, ) from pipecat.processors.frame_processor import FrameDirection -from pipecat.services.settings import NOT_GIVEN, STTSettings, _NotGiven, _warn_deprecated_param +from pipecat.services.settings import NOT_GIVEN, STTSettings, _NotGiven from pipecat.services.stt_latency import ASSEMBLYAI_TTFS_P99 from pipecat.services.stt_service import WebsocketSTTService from pipecat.transcriptions.language import Language @@ -208,12 +208,12 @@ class AssemblyAISTTService(WebsocketSTTService): # 2. Apply direct init arg overrides (deprecated) if language is not None: - _warn_deprecated_param("language", self.Settings, "language") + self._warn_init_param_moved_to_settings("language", "language") default_settings.language = language # 3. Apply connection_params overrides (deprecated) — only if settings not provided if connection_params is not None: - _warn_deprecated_param("connection_params", self.Settings) + self._warn_init_param_moved_to_settings("connection_params") if not settings: sample_rate = connection_params.sample_rate encoding = connection_params.encoding diff --git a/src/pipecat/services/asyncai/tts.py b/src/pipecat/services/asyncai/tts.py index 2cecb2d5b..42c0a09a4 100644 --- a/src/pipecat/services/asyncai/tts.py +++ b/src/pipecat/services/asyncai/tts.py @@ -26,7 +26,7 @@ from pipecat.frames.frames import ( TTSStoppedFrame, ) from pipecat.processors.frame_processor import FrameDirection -from pipecat.services.settings import TTSSettings, _warn_deprecated_param +from pipecat.services.settings import TTSSettings from pipecat.services.tts_service import TextAggregationMode, TTSService, WebsocketTTSService from pipecat.transcriptions.language import Language, resolve_language from pipecat.utils.tracing.service_decorators import traced_tts @@ -161,15 +161,15 @@ class AsyncAITTSService(WebsocketTTSService): # 2. Apply direct init arg overrides (deprecated) if voice_id is not None: - _warn_deprecated_param("voice_id", self.Settings, "voice") + self._warn_init_param_moved_to_settings("voice_id", "voice") default_settings.voice = voice_id if model is not None: - _warn_deprecated_param("model", self.Settings, "model") + self._warn_init_param_moved_to_settings("model", "model") default_settings.model = model # 3. Apply params overrides — only if settings not provided if params is not None: - _warn_deprecated_param("params", self.Settings) + self._warn_init_param_moved_to_settings("params") if not settings: default_settings.language = ( self.language_to_service_language(params.language) if params.language else None @@ -555,15 +555,15 @@ class AsyncAIHttpTTSService(TTSService): # 2. Apply direct init arg overrides (deprecated) if voice_id is not None: - _warn_deprecated_param("voice_id", self.Settings, "voice") + self._warn_init_param_moved_to_settings("voice_id", "voice") default_settings.voice = voice_id if model is not None: - _warn_deprecated_param("model", self.Settings, "model") + self._warn_init_param_moved_to_settings("model", "model") default_settings.model = model # 3. Apply params overrides — only if settings not provided if params is not None: - _warn_deprecated_param("params", self.Settings) + self._warn_init_param_moved_to_settings("params") if not settings: default_settings.language = ( self.language_to_service_language(params.language) if params.language else None diff --git a/src/pipecat/services/aws/llm.py b/src/pipecat/services/aws/llm.py index 9a2ebfdcf..59859abf7 100644 --- a/src/pipecat/services/aws/llm.py +++ b/src/pipecat/services/aws/llm.py @@ -55,7 +55,7 @@ from pipecat.processors.aggregators.openai_llm_context import ( ) from pipecat.processors.frame_processor import FrameDirection from pipecat.services.llm_service import LLMService -from pipecat.services.settings import NOT_GIVEN, LLMSettings, _NotGiven, _warn_deprecated_param +from pipecat.services.settings import NOT_GIVEN, LLMSettings, _NotGiven from pipecat.utils.tracing.service_decorators import traced_llm try: @@ -841,15 +841,15 @@ class AWSBedrockLLMService(LLMService): # 2. Apply direct init arg overrides (deprecated) if model is not None: - _warn_deprecated_param("model", self.Settings, "model") + self._warn_init_param_moved_to_settings("model", "model") default_settings.model = model if stop_sequences is not None: - _warn_deprecated_param("stop_sequences", self.Settings, "stop_sequences") + self._warn_init_param_moved_to_settings("stop_sequences", "stop_sequences") default_settings.stop_sequences = stop_sequences # 3. Apply params overrides — only if settings not provided if params is not None: - _warn_deprecated_param("params", self.Settings) + self._warn_init_param_moved_to_settings("params") if not settings: default_settings.max_tokens = params.max_tokens default_settings.temperature = params.temperature diff --git a/src/pipecat/services/aws/nova_sonic/llm.py b/src/pipecat/services/aws/nova_sonic/llm.py index 0309c0fad..b1f56dbbd 100644 --- a/src/pipecat/services/aws/nova_sonic/llm.py +++ b/src/pipecat/services/aws/nova_sonic/llm.py @@ -60,7 +60,7 @@ from pipecat.processors.aggregators.openai_llm_context import ( ) from pipecat.processors.frame_processor import FrameDirection from pipecat.services.llm_service import LLMService -from pipecat.services.settings import NOT_GIVEN, LLMSettings, _NotGiven, _warn_deprecated_param +from pipecat.services.settings import NOT_GIVEN, LLMSettings, _NotGiven from pipecat.utils.time import time_now_iso8601 try: @@ -337,13 +337,13 @@ class AWSNovaSonicLLMService(LLMService): # 2. Apply direct init arg overrides (deprecated) if model != "amazon.nova-2-sonic-v1:0": - _warn_deprecated_param("model", self.Settings, "model") + self._warn_init_param_moved_to_settings("model", "model") default_settings.model = model if voice_id != "matthew": - _warn_deprecated_param("voice_id", self.Settings, "voice") + self._warn_init_param_moved_to_settings("voice_id", "voice") default_settings.voice = voice_id if system_instruction is not None: - _warn_deprecated_param("system_instruction", self.Settings, "system_instruction") + self._warn_init_param_moved_to_settings("system_instruction", "system_instruction") default_settings.system_instruction = system_instruction # 3. Apply params overrides — only if settings not provided diff --git a/src/pipecat/services/aws/stt.py b/src/pipecat/services/aws/stt.py index 0a648759c..eed1a321d 100644 --- a/src/pipecat/services/aws/stt.py +++ b/src/pipecat/services/aws/stt.py @@ -29,7 +29,7 @@ from pipecat.frames.frames import ( TranscriptionFrame, ) from pipecat.services.aws.utils import build_event_message, decode_event, get_presigned_url -from pipecat.services.settings import STTSettings, _warn_deprecated_param +from pipecat.services.settings import STTSettings from pipecat.services.stt_latency import AWS_TRANSCRIBE_TTFS_P99 from pipecat.services.stt_service import WebsocketSTTService from pipecat.transcriptions.language import Language, resolve_language @@ -105,7 +105,7 @@ class AWSTranscribeSTTService(WebsocketSTTService): # 2. Apply direct init arg overrides (deprecated) if language is not None: - _warn_deprecated_param("language", self.Settings, "language") + self._warn_init_param_moved_to_settings("language", "language") default_settings.language = self.language_to_service_language(language) # 3. (No step 3, as there's no params object to apply) diff --git a/src/pipecat/services/aws/tts.py b/src/pipecat/services/aws/tts.py index 1e16958fe..9648c45c8 100644 --- a/src/pipecat/services/aws/tts.py +++ b/src/pipecat/services/aws/tts.py @@ -23,7 +23,7 @@ from pipecat.frames.frames import ( Frame, TTSAudioRawFrame, ) -from pipecat.services.settings import NOT_GIVEN, TTSSettings, _NotGiven, _warn_deprecated_param +from pipecat.services.settings import NOT_GIVEN, TTSSettings, _NotGiven from pipecat.services.tts_service import TTSService from pipecat.transcriptions.language import Language, resolve_language from pipecat.utils.tracing.service_decorators import traced_tts @@ -222,12 +222,12 @@ class AWSPollyTTSService(TTSService): # 2. Apply direct init arg overrides (deprecated) if voice_id is not None: - _warn_deprecated_param("voice_id", self.Settings, "voice") + self._warn_init_param_moved_to_settings("voice_id", "voice") default_settings.voice = voice_id # 3. Apply params overrides — only if settings not provided if params is not None: - _warn_deprecated_param("params", self.Settings) + self._warn_init_param_moved_to_settings("params") if not settings: default_settings.engine = params.engine default_settings.language = ( diff --git a/src/pipecat/services/azure/image.py b/src/pipecat/services/azure/image.py index a80496599..fc50d710a 100644 --- a/src/pipecat/services/azure/image.py +++ b/src/pipecat/services/azure/image.py @@ -20,7 +20,7 @@ from PIL import Image from pipecat.frames.frames import ErrorFrame, Frame, URLImageRawFrame from pipecat.services.image_service import ImageGenService -from pipecat.services.settings import NOT_GIVEN, ImageGenSettings, _NotGiven, _warn_deprecated_param +from pipecat.services.settings import NOT_GIVEN, ImageGenSettings, _NotGiven @dataclass @@ -85,11 +85,11 @@ class AzureImageGenServiceREST(ImageGenService): # 2. Apply direct init arg overrides (deprecated) if model is not None: - _warn_deprecated_param("model", self.Settings, "model") + self._warn_init_param_moved_to_settings("model", "model") default_settings.model = model if image_size is not None: - _warn_deprecated_param("image_size", self.Settings, "image_size") + self._warn_init_param_moved_to_settings("image_size", "image_size") default_settings.image_size = image_size # 4. Apply settings delta (canonical API, always wins) diff --git a/src/pipecat/services/azure/llm.py b/src/pipecat/services/azure/llm.py index b4f2de5dc..ea705eec6 100644 --- a/src/pipecat/services/azure/llm.py +++ b/src/pipecat/services/azure/llm.py @@ -14,7 +14,6 @@ from openai import AsyncAzureOpenAI from pipecat.services.openai.base_llm import BaseOpenAILLMService from pipecat.services.openai.llm import OpenAILLMService -from pipecat.services.settings import _warn_deprecated_param @dataclass @@ -63,7 +62,7 @@ class AzureLLMService(OpenAILLMService): # 2. Apply direct init arg overrides (deprecated) if model is not None: - _warn_deprecated_param("model", self.Settings, "model") + self._warn_init_param_moved_to_settings("model", "model") default_settings.model = model # 3. (No step 3, as there's no params object to apply) diff --git a/src/pipecat/services/azure/stt.py b/src/pipecat/services/azure/stt.py index 7309a4a4e..857b166cb 100644 --- a/src/pipecat/services/azure/stt.py +++ b/src/pipecat/services/azure/stt.py @@ -26,7 +26,7 @@ from pipecat.frames.frames import ( TranscriptionFrame, ) from pipecat.services.azure.common import language_to_azure_language -from pipecat.services.settings import STTSettings, _warn_deprecated_param +from pipecat.services.settings import STTSettings from pipecat.services.stt_latency import AZURE_TTFS_P99 from pipecat.services.stt_service import STTService from pipecat.transcriptions.language import Language @@ -111,7 +111,7 @@ class AzureSTTService(STTService): # 2. Apply direct init arg overrides (deprecated) if language is not None and language != Language.EN_US: - _warn_deprecated_param("language", self.Settings, "language") + self._warn_init_param_moved_to_settings("language", "language") default_settings.language = language_to_azure_language(language) # 3. (No step 3, as there's no params object to apply) diff --git a/src/pipecat/services/azure/tts.py b/src/pipecat/services/azure/tts.py index d33937d52..0130ef5cb 100644 --- a/src/pipecat/services/azure/tts.py +++ b/src/pipecat/services/azure/tts.py @@ -25,7 +25,7 @@ from pipecat.frames.frames import ( ) from pipecat.processors.frame_processor import FrameDirection from pipecat.services.azure.common import language_to_azure_language -from pipecat.services.settings import NOT_GIVEN, TTSSettings, _NotGiven, _warn_deprecated_param +from pipecat.services.settings import NOT_GIVEN, TTSSettings, _NotGiven from pipecat.services.tts_service import TextAggregationMode, TTSService from pipecat.transcriptions.language import Language from pipecat.utils.tracing.service_decorators import traced_tts @@ -304,12 +304,12 @@ class AzureTTSService(TTSService, AzureBaseTTSService): # 2. Apply direct init arg overrides (deprecated) if voice is not None: - _warn_deprecated_param("voice", self.Settings, "voice") + self._warn_init_param_moved_to_settings("voice", "voice") default_settings.voice = voice # 3. Apply params overrides — only if settings not provided if params is not None: - _warn_deprecated_param("params", self.Settings) + self._warn_init_param_moved_to_settings("params") if not settings: default_settings.emphasis = params.emphasis default_settings.language = ( @@ -801,12 +801,12 @@ class AzureHttpTTSService(TTSService, AzureBaseTTSService): # 2. Apply direct init arg overrides (deprecated) if voice is not None: - _warn_deprecated_param("voice", self.Settings, "voice") + self._warn_init_param_moved_to_settings("voice", "voice") default_settings.voice = voice # 3. Apply params overrides — only if settings not provided if params is not None: - _warn_deprecated_param("params", self.Settings) + self._warn_init_param_moved_to_settings("params") if not settings: default_settings.emphasis = params.emphasis default_settings.language = ( diff --git a/src/pipecat/services/camb/tts.py b/src/pipecat/services/camb/tts.py index 7586644ce..b0c237165 100644 --- a/src/pipecat/services/camb/tts.py +++ b/src/pipecat/services/camb/tts.py @@ -30,7 +30,7 @@ from pipecat.frames.frames import ( StartFrame, TTSAudioRawFrame, ) -from pipecat.services.settings import NOT_GIVEN, TTSSettings, _NotGiven, _warn_deprecated_param +from pipecat.services.settings import NOT_GIVEN, TTSSettings, _NotGiven from pipecat.services.tts_service import TTSService from pipecat.transcriptions.language import Language, resolve_language from pipecat.utils.tracing.service_decorators import traced_tts @@ -246,15 +246,15 @@ class CambTTSService(TTSService): # 2. Apply direct init arg overrides (deprecated) if model is not None: - _warn_deprecated_param("model", self.Settings, "model") + self._warn_init_param_moved_to_settings("model", "model") default_settings.model = model if voice_id is not None: - _warn_deprecated_param("voice_id", self.Settings, "voice") + self._warn_init_param_moved_to_settings("voice_id", "voice") default_settings.voice = voice_id # 3. Apply params overrides — only if settings not provided if params is not None: - _warn_deprecated_param("params", self.Settings) + self._warn_init_param_moved_to_settings("params") if not settings: if params.language is not None: default_settings.language = ( diff --git a/src/pipecat/services/cartesia/stt.py b/src/pipecat/services/cartesia/stt.py index e094ef044..85d43bcd3 100644 --- a/src/pipecat/services/cartesia/stt.py +++ b/src/pipecat/services/cartesia/stt.py @@ -28,7 +28,7 @@ from pipecat.frames.frames import ( VADUserStoppedSpeakingFrame, ) from pipecat.processors.frame_processor import FrameDirection -from pipecat.services.settings import STTSettings, _warn_deprecated_param +from pipecat.services.settings import STTSettings from pipecat.services.stt_latency import CARTESIA_TTFS_P99 from pipecat.services.stt_service import WebsocketSTTService from pipecat.transcriptions.language import Language @@ -189,7 +189,7 @@ class CartesiaSTTService(WebsocketSTTService): # 2. Apply live_options overrides — only if settings not provided if live_options is not None: - _warn_deprecated_param("live_options", self.Settings) + self._warn_init_param_moved_to_settings("live_options") if not settings: if live_options.sample_rate and sample_rate is None: sample_rate = live_options.sample_rate diff --git a/src/pipecat/services/cartesia/tts.py b/src/pipecat/services/cartesia/tts.py index 90497eb1d..aca5c46c6 100644 --- a/src/pipecat/services/cartesia/tts.py +++ b/src/pipecat/services/cartesia/tts.py @@ -25,7 +25,7 @@ from pipecat.frames.frames import ( TTSAudioRawFrame, TTSStoppedFrame, ) -from pipecat.services.settings import NOT_GIVEN, TTSSettings, _NotGiven, _warn_deprecated_param +from pipecat.services.settings import NOT_GIVEN, TTSSettings, _NotGiven from pipecat.services.tts_service import TextAggregationMode, TTSService, WebsocketTTSService from pipecat.transcriptions.language import Language, resolve_language from pipecat.utils.text.base_text_aggregator import BaseTextAggregator @@ -309,15 +309,15 @@ class CartesiaTTSService(WebsocketTTSService): # 2. Apply direct init arg overrides (deprecated) if voice_id is not None: - _warn_deprecated_param("voice_id", self.Settings, "voice") + self._warn_init_param_moved_to_settings("voice_id", "voice") default_settings.voice = voice_id if model is not None: - _warn_deprecated_param("model", self.Settings, "model") + self._warn_init_param_moved_to_settings("model", "model") default_settings.model = model # 3. Apply params overrides — only if settings not provided if params is not None: - _warn_deprecated_param("params", self.Settings) + self._warn_init_param_moved_to_settings("params") if not settings: if params.language is not None: default_settings.language = self.language_to_service_language(params.language) @@ -756,15 +756,15 @@ class CartesiaHttpTTSService(TTSService): # 2. Apply direct init arg overrides (deprecated) if voice_id is not None: - _warn_deprecated_param("voice_id", self.Settings, "voice") + self._warn_init_param_moved_to_settings("voice_id", "voice") default_settings.voice = voice_id if model is not None: - _warn_deprecated_param("model", self.Settings, "model") + self._warn_init_param_moved_to_settings("model", "model") default_settings.model = model # 3. Apply params overrides — only if settings not provided if params is not None: - _warn_deprecated_param("params", self.Settings) + self._warn_init_param_moved_to_settings("params") if not settings: if params.language is not None: default_settings.language = self.language_to_service_language(params.language) diff --git a/src/pipecat/services/cerebras/llm.py b/src/pipecat/services/cerebras/llm.py index e2a15f4e5..7c31a6857 100644 --- a/src/pipecat/services/cerebras/llm.py +++ b/src/pipecat/services/cerebras/llm.py @@ -14,7 +14,6 @@ from loguru import logger from pipecat.adapters.services.open_ai_adapter import OpenAILLMInvocationParams from pipecat.services.openai.base_llm import BaseOpenAILLMService from pipecat.services.openai.llm import OpenAILLMService -from pipecat.services.settings import _warn_deprecated_param @dataclass @@ -62,7 +61,7 @@ class CerebrasLLMService(OpenAILLMService): # 2. Apply direct init arg overrides (deprecated) if model is not None: - _warn_deprecated_param("model", self.Settings, "model") + self._warn_init_param_moved_to_settings("model", "model") default_settings.model = model # 3. (No step 3, as there's no params object to apply) diff --git a/src/pipecat/services/deepgram/flux/stt.py b/src/pipecat/services/deepgram/flux/stt.py index 085d1ed2c..64d4e87b9 100644 --- a/src/pipecat/services/deepgram/flux/stt.py +++ b/src/pipecat/services/deepgram/flux/stt.py @@ -28,7 +28,7 @@ from pipecat.frames.frames import ( UserStartedSpeakingFrame, UserStoppedSpeakingFrame, ) -from pipecat.services.settings import NOT_GIVEN, STTSettings, _NotGiven, _warn_deprecated_param +from pipecat.services.settings import NOT_GIVEN, STTSettings, _NotGiven from pipecat.services.stt_service import WebsocketSTTService from pipecat.transcriptions.language import Language from pipecat.utils.time import time_now_iso8601 @@ -233,12 +233,12 @@ class DeepgramFluxSTTService(WebsocketSTTService): # 2. Apply direct init arg overrides (deprecated) if model is not None: - _warn_deprecated_param("model", self.Settings, "model") + self._warn_init_param_moved_to_settings("model", "model") default_settings.model = model # 3. Apply params overrides — only if settings not provided if params is not None: - _warn_deprecated_param("params", self.Settings) + self._warn_init_param_moved_to_settings("params") if not settings: default_settings.eager_eot_threshold = params.eager_eot_threshold default_settings.eot_threshold = params.eot_threshold diff --git a/src/pipecat/services/deepgram/sagemaker/stt.py b/src/pipecat/services/deepgram/sagemaker/stt.py index 98b3556cc..1087b124f 100644 --- a/src/pipecat/services/deepgram/sagemaker/stt.py +++ b/src/pipecat/services/deepgram/sagemaker/stt.py @@ -33,7 +33,7 @@ from pipecat.frames.frames import ( from pipecat.processors.frame_processor import FrameDirection from pipecat.services.aws.sagemaker.bidi_client import SageMakerBidiClient from pipecat.services.deepgram.stt import DeepgramSTTService, LiveOptions -from pipecat.services.settings import STTSettings, _warn_deprecated_param, is_given +from pipecat.services.settings import STTSettings, is_given from pipecat.services.stt_latency import DEEPGRAM_SAGEMAKER_TTFS_P99 from pipecat.services.stt_service import STTService from pipecat.transcriptions.language import Language @@ -147,7 +147,7 @@ class DeepgramSageMakerSTTService(STTService): # 2. Apply live_options overrides — only if settings not provided if live_options is not None: - _warn_deprecated_param("live_options", self.Settings) + self._warn_init_param_moved_to_settings("live_options") if not settings: # Extract init-only fields from live_options if live_options.sample_rate is not None and sample_rate is None: diff --git a/src/pipecat/services/deepgram/sagemaker/tts.py b/src/pipecat/services/deepgram/sagemaker/tts.py index f2c55c882..70be4a00e 100644 --- a/src/pipecat/services/deepgram/sagemaker/tts.py +++ b/src/pipecat/services/deepgram/sagemaker/tts.py @@ -33,7 +33,7 @@ from pipecat.frames.frames import ( ) from pipecat.processors.frame_processor import FrameDirection from pipecat.services.aws.sagemaker.bidi_client import SageMakerBidiClient -from pipecat.services.settings import TTSSettings, _warn_deprecated_param +from pipecat.services.settings import TTSSettings from pipecat.services.tts_service import TTSService from pipecat.utils.tracing.service_decorators import traced_tts @@ -101,7 +101,7 @@ class DeepgramSageMakerTTSService(TTSService): **kwargs: Additional arguments passed to the parent TTSService. """ if voice is not None: - _warn_deprecated_param("voice", self.Settings, "voice") + self._warn_init_param_moved_to_settings("voice", "voice") voice = voice or "aura-2-helena-en" diff --git a/src/pipecat/services/deepgram/stt.py b/src/pipecat/services/deepgram/stt.py index e84964dce..7d849a160 100644 --- a/src/pipecat/services/deepgram/stt.py +++ b/src/pipecat/services/deepgram/stt.py @@ -29,7 +29,6 @@ from pipecat.services.settings import ( NOT_GIVEN, STTSettings, _NotGiven, - _warn_deprecated_param, is_given, ) from pipecat.services.stt_latency import DEEPGRAM_TTFS_P99 @@ -370,7 +369,7 @@ class DeepgramSTTService(STTService): # 3. Apply live_options overrides — only if settings not provided if live_options is not None: - _warn_deprecated_param("live_options", self.Settings) + self._warn_init_param_moved_to_settings("live_options") if not settings: # Extract init-only fields from live_options if live_options.sample_rate is not None and sample_rate is None: diff --git a/src/pipecat/services/deepgram/tts.py b/src/pipecat/services/deepgram/tts.py index 5fdbeb700..9f2dc3976 100644 --- a/src/pipecat/services/deepgram/tts.py +++ b/src/pipecat/services/deepgram/tts.py @@ -26,7 +26,7 @@ from pipecat.frames.frames import ( TTSAudioRawFrame, TTSStoppedFrame, ) -from pipecat.services.settings import TTSSettings, _warn_deprecated_param +from pipecat.services.settings import TTSSettings from pipecat.services.tts_service import TTSService, WebsocketTTSService from pipecat.utils.tracing.service_decorators import traced_tts @@ -105,7 +105,7 @@ class DeepgramTTSService(WebsocketTTSService): # 2. Apply direct init arg overrides (deprecated) if voice is not None: - _warn_deprecated_param("voice", self.Settings, "voice") + self._warn_init_param_moved_to_settings("voice", "voice") default_settings.model = voice default_settings.voice = voice @@ -407,7 +407,7 @@ class DeepgramHttpTTSService(TTSService): # 2. Apply direct init arg overrides (deprecated) if voice is not None: - _warn_deprecated_param("voice", self.Settings, "voice") + self._warn_init_param_moved_to_settings("voice", "voice") default_settings.model = voice default_settings.voice = voice diff --git a/src/pipecat/services/deepseek/llm.py b/src/pipecat/services/deepseek/llm.py index abb0d56bb..cfb69cb9a 100644 --- a/src/pipecat/services/deepseek/llm.py +++ b/src/pipecat/services/deepseek/llm.py @@ -14,7 +14,6 @@ from loguru import logger from pipecat.adapters.services.open_ai_adapter import OpenAILLMInvocationParams from pipecat.services.openai.base_llm import BaseOpenAILLMService from pipecat.services.openai.llm import OpenAILLMService -from pipecat.services.settings import _warn_deprecated_param @dataclass @@ -62,7 +61,7 @@ class DeepSeekLLMService(OpenAILLMService): # 2. Apply direct init arg overrides (deprecated) if model is not None: - _warn_deprecated_param("model", self.Settings, "model") + self._warn_init_param_moved_to_settings("model", "model") default_settings.model = model # 3. (No step 3, as there's no params object to apply) diff --git a/src/pipecat/services/elevenlabs/stt.py b/src/pipecat/services/elevenlabs/stt.py index 7247241d3..daca9be3d 100644 --- a/src/pipecat/services/elevenlabs/stt.py +++ b/src/pipecat/services/elevenlabs/stt.py @@ -35,7 +35,7 @@ from pipecat.frames.frames import ( VADUserStoppedSpeakingFrame, ) from pipecat.processors.frame_processor import FrameDirection -from pipecat.services.settings import NOT_GIVEN, STTSettings, _NotGiven, _warn_deprecated_param +from pipecat.services.settings import NOT_GIVEN, STTSettings, _NotGiven from pipecat.services.stt_latency import ELEVENLABS_REALTIME_TTFS_P99, ELEVENLABS_TTFS_P99 from pipecat.services.stt_service import SegmentedSTTService, WebsocketSTTService from pipecat.transcriptions.language import Language, resolve_language @@ -278,12 +278,12 @@ class ElevenLabsSTTService(SegmentedSTTService): # 2. Apply direct init arg overrides (deprecated) if model is not None: - _warn_deprecated_param("model", self.Settings, "model") + self._warn_init_param_moved_to_settings("model", "model") default_settings.model = model # 3. Apply params overrides — only if settings not provided if params is not None: - _warn_deprecated_param("params", self.Settings) + self._warn_init_param_moved_to_settings("params") if not settings: if params.language is not None: default_settings.language = language_to_elevenlabs_language(params.language) @@ -540,12 +540,12 @@ class ElevenLabsRealtimeSTTService(WebsocketSTTService): # 2. Apply direct init arg overrides (deprecated) if model is not None: - _warn_deprecated_param("model", self.Settings, "model") + self._warn_init_param_moved_to_settings("model", "model") default_settings.model = model # 3. Apply params overrides — only if settings not provided if params is not None: - _warn_deprecated_param("params", self.Settings) + self._warn_init_param_moved_to_settings("params") if not settings: default_settings.language = params.language_code if params.commit_strategy != CommitStrategy.MANUAL: diff --git a/src/pipecat/services/elevenlabs/tts.py b/src/pipecat/services/elevenlabs/tts.py index 46acc2f1c..8cfd1abe2 100644 --- a/src/pipecat/services/elevenlabs/tts.py +++ b/src/pipecat/services/elevenlabs/tts.py @@ -44,7 +44,7 @@ from pipecat.frames.frames import ( TTSStoppedFrame, ) from pipecat.processors.frame_processor import FrameDirection -from pipecat.services.settings import NOT_GIVEN, TTSSettings, _NotGiven, _warn_deprecated_param +from pipecat.services.settings import NOT_GIVEN, TTSSettings, _NotGiven from pipecat.services.tts_service import ( TextAggregationMode, TTSService, @@ -437,16 +437,16 @@ class ElevenLabsTTSService(WebsocketTTSService): # 2. Apply direct init arg overrides (deprecated) if voice_id is not None: - _warn_deprecated_param("voice_id", self.Settings, "voice") + self._warn_init_param_moved_to_settings("voice_id", "voice") default_settings.voice = voice_id if model is not None: - _warn_deprecated_param("model", self.Settings, "model") + self._warn_init_param_moved_to_settings("model", "model") default_settings.model = model # 3. Apply params overrides — only if settings not provided _pronunciation_dictionary_locators = pronunciation_dictionary_locators if params is not None: - _warn_deprecated_param("params", self.Settings) + self._warn_init_param_moved_to_settings("params") if not settings: if params.language is not None: default_settings.language = self.language_to_service_language(params.language) @@ -1002,16 +1002,16 @@ class ElevenLabsHttpTTSService(TTSService): # 2. Apply direct init arg overrides (deprecated) if voice_id is not None: - _warn_deprecated_param("voice_id", self.Settings, "voice") + self._warn_init_param_moved_to_settings("voice_id", "voice") default_settings.voice = voice_id if model is not None: - _warn_deprecated_param("model", self.Settings, "model") + self._warn_init_param_moved_to_settings("model", "model") default_settings.model = model # 3. Apply params overrides — only if settings not provided _pronunciation_dictionary_locators = pronunciation_dictionary_locators if params is not None: - _warn_deprecated_param("params", self.Settings) + self._warn_init_param_moved_to_settings("params") if not settings: if params.language is not None: default_settings.language = self.language_to_service_language(params.language) diff --git a/src/pipecat/services/fal/image.py b/src/pipecat/services/fal/image.py index 3c15a918a..31af55440 100644 --- a/src/pipecat/services/fal/image.py +++ b/src/pipecat/services/fal/image.py @@ -23,7 +23,7 @@ from pydantic import BaseModel from pipecat.frames.frames import ErrorFrame, Frame, URLImageRawFrame from pipecat.services.image_service import ImageGenService -from pipecat.services.settings import NOT_GIVEN, ImageGenSettings, _NotGiven, _warn_deprecated_param +from pipecat.services.settings import NOT_GIVEN, ImageGenSettings, _NotGiven @dataclass @@ -142,11 +142,11 @@ class FalImageGenService(ImageGenService): # 2. Apply direct init arg overrides (deprecated) if model is not None: - _warn_deprecated_param("model", self.Settings, "model") + self._warn_init_param_moved_to_settings("model", "model") default_settings.model = model if params is not None: - _warn_deprecated_param("params", self.Settings) + self._warn_init_param_moved_to_settings("params") if not settings: default_settings.seed = params.seed default_settings.num_inference_steps = params.num_inference_steps diff --git a/src/pipecat/services/fal/stt.py b/src/pipecat/services/fal/stt.py index c1aae24b7..7bfcfbcfd 100644 --- a/src/pipecat/services/fal/stt.py +++ b/src/pipecat/services/fal/stt.py @@ -20,7 +20,7 @@ from loguru import logger from pydantic import BaseModel from pipecat.frames.frames import ErrorFrame, Frame, TranscriptionFrame -from pipecat.services.settings import STTSettings, _warn_deprecated_param +from pipecat.services.settings import STTSettings from pipecat.services.stt_latency import FAL_TTFS_P99 from pipecat.services.stt_service import SegmentedSTTService from pipecat.transcriptions.language import Language, resolve_language @@ -223,7 +223,7 @@ class FalSTTService(SegmentedSTTService): # 3. Apply params overrides — only if settings not provided if params is not None: - _warn_deprecated_param("params", self.Settings) + self._warn_init_param_moved_to_settings("params") if not settings: if params.language is not None: default_settings.language = language_to_fal_language(params.language) diff --git a/src/pipecat/services/fireworks/llm.py b/src/pipecat/services/fireworks/llm.py index fdd688149..bf141fac1 100644 --- a/src/pipecat/services/fireworks/llm.py +++ b/src/pipecat/services/fireworks/llm.py @@ -14,7 +14,6 @@ from loguru import logger from pipecat.adapters.services.open_ai_adapter import OpenAILLMInvocationParams from pipecat.services.openai.base_llm import BaseOpenAILLMService from pipecat.services.openai.llm import OpenAILLMService -from pipecat.services.settings import _warn_deprecated_param @dataclass @@ -62,7 +61,7 @@ class FireworksLLMService(OpenAILLMService): # 2. Apply direct init arg overrides (deprecated) if model is not None: - _warn_deprecated_param("model", self.Settings, "model") + self._warn_init_param_moved_to_settings("model", "model") default_settings.model = model # 3. (No step 3, as there's no params object to apply) diff --git a/src/pipecat/services/fish/tts.py b/src/pipecat/services/fish/tts.py index 39669574a..92cb54701 100644 --- a/src/pipecat/services/fish/tts.py +++ b/src/pipecat/services/fish/tts.py @@ -27,7 +27,7 @@ from pipecat.frames.frames import ( TTSStoppedFrame, ) from pipecat.processors.frame_processor import FrameDirection -from pipecat.services.settings import NOT_GIVEN, TTSSettings, _NotGiven, _warn_deprecated_param +from pipecat.services.settings import NOT_GIVEN, TTSSettings, _NotGiven from pipecat.services.tts_service import InterruptibleTTSService from pipecat.transcriptions.language import Language from pipecat.utils.tracing.service_decorators import traced_tts @@ -185,15 +185,15 @@ class FishAudioTTSService(InterruptibleTTSService): # 2. Apply direct init arg overrides (deprecated) if reference_id is not None: - _warn_deprecated_param("reference_id", self.Settings, "voice") + self._warn_init_param_moved_to_settings("reference_id", "voice") default_settings.voice = reference_id if model_id is not None: - _warn_deprecated_param("model_id", self.Settings, "model") + self._warn_init_param_moved_to_settings("model_id", "model") default_settings.model = model_id # 3. Apply params overrides — only if settings not provided if params is not None: - _warn_deprecated_param("params", self.Settings) + self._warn_init_param_moved_to_settings("params") if not settings: if params.latency is not None: default_settings.latency = params.latency diff --git a/src/pipecat/services/gladia/stt.py b/src/pipecat/services/gladia/stt.py index a68bf78b3..2ce2a15b5 100644 --- a/src/pipecat/services/gladia/stt.py +++ b/src/pipecat/services/gladia/stt.py @@ -39,7 +39,7 @@ from pipecat.services.gladia.config import ( PreProcessingConfig, RealtimeProcessingConfig, ) -from pipecat.services.settings import NOT_GIVEN, STTSettings, _NotGiven, _warn_deprecated_param +from pipecat.services.settings import NOT_GIVEN, STTSettings, _NotGiven from pipecat.services.stt_latency import GLADIA_TTFS_P99 from pipecat.services.stt_service import WebsocketSTTService from pipecat.transcriptions.language import Language, resolve_language @@ -317,12 +317,12 @@ class GladiaSTTService(WebsocketSTTService): # 2. Apply direct init arg overrides (deprecated) if model is not None: - _warn_deprecated_param("model", self.Settings, "model") + self._warn_init_param_moved_to_settings("model", "model") default_settings.model = model # 3. Apply params overrides — only if settings not provided if params is not None: - _warn_deprecated_param("params", self.Settings) + self._warn_init_param_moved_to_settings("params") if params.language is not None: with warnings.catch_warnings(): warnings.simplefilter("always") diff --git a/src/pipecat/services/google/gemini_live/llm.py b/src/pipecat/services/google/gemini_live/llm.py index 167abb938..5c9e5f8b3 100644 --- a/src/pipecat/services/google/gemini_live/llm.py +++ b/src/pipecat/services/google/gemini_live/llm.py @@ -76,7 +76,7 @@ from pipecat.services.openai.llm import ( OpenAIAssistantContextAggregator, OpenAIUserContextAggregator, ) -from pipecat.services.settings import NOT_GIVEN, LLMSettings, _NotGiven, _warn_deprecated_param +from pipecat.services.settings import NOT_GIVEN, LLMSettings, _NotGiven from pipecat.transcriptions.language import Language, resolve_language from pipecat.utils.string import match_endofsentence from pipecat.utils.time import time_now_iso8601 @@ -742,15 +742,15 @@ class GeminiLiveLLMService(LLMService): # 2. Apply direct init arg overrides (deprecated) if model is not None: - _warn_deprecated_param("model", self.Settings, "model") + self._warn_init_param_moved_to_settings("model", "model") default_settings.model = model if voice_id != "Charon": - _warn_deprecated_param("voice_id", self.Settings, "voice") + self._warn_init_param_moved_to_settings("voice_id", "voice") default_settings.voice = voice_id # 3. Apply params overrides — only if settings not provided if params is not None: - _warn_deprecated_param("params", self.Settings) + self._warn_init_param_moved_to_settings("params") if not settings: default_settings.frequency_penalty = params.frequency_penalty default_settings.max_tokens = params.max_tokens diff --git a/src/pipecat/services/google/gemini_live/vertex/llm.py b/src/pipecat/services/google/gemini_live/vertex/llm.py index c610b4cdb..cb9d74c62 100644 --- a/src/pipecat/services/google/gemini_live/vertex/llm.py +++ b/src/pipecat/services/google/gemini_live/vertex/llm.py @@ -26,7 +26,6 @@ from pipecat.services.google.gemini_live.llm import ( InputParams, language_to_gemini_language, ) -from pipecat.services.settings import _warn_deprecated_param try: from google.auth import default @@ -160,15 +159,15 @@ class GeminiLiveVertexLLMService(GeminiLiveLLMService): # 2. Apply direct init arg overrides (deprecated) if model is not None: - _warn_deprecated_param("model", self.Settings, "model") + self._warn_init_param_moved_to_settings("model", "model") default_settings.model = model if voice_id != "Charon": - _warn_deprecated_param("voice_id", self.Settings, "voice") + self._warn_init_param_moved_to_settings("voice_id", "voice") default_settings.voice = voice_id # 3. Apply params overrides — only if settings not provided if params is not None: - _warn_deprecated_param("params", self.Settings) + self._warn_init_param_moved_to_settings("params") if not settings: default_settings.frequency_penalty = params.frequency_penalty default_settings.max_tokens = params.max_tokens diff --git a/src/pipecat/services/google/image.py b/src/pipecat/services/google/image.py index 40706ad50..6a2919986 100644 --- a/src/pipecat/services/google/image.py +++ b/src/pipecat/services/google/image.py @@ -26,7 +26,7 @@ from pydantic import BaseModel, Field from pipecat.frames.frames import ErrorFrame, Frame, URLImageRawFrame from pipecat.services.google.utils import update_google_client_http_options from pipecat.services.image_service import ImageGenService -from pipecat.services.settings import NOT_GIVEN, ImageGenSettings, _NotGiven, _warn_deprecated_param +from pipecat.services.settings import NOT_GIVEN, ImageGenSettings, _NotGiven try: from google import genai @@ -110,7 +110,7 @@ class GoogleImageGenService(ImageGenService): # 2. Apply params overrides (deprecated) if params is not None: - _warn_deprecated_param("params", self.Settings) + self._warn_init_param_moved_to_settings("params") if not settings: default_settings.model = params.model default_settings.number_of_images = params.number_of_images diff --git a/src/pipecat/services/google/llm.py b/src/pipecat/services/google/llm.py index 02b5a5c19..698b9f97f 100644 --- a/src/pipecat/services/google/llm.py +++ b/src/pipecat/services/google/llm.py @@ -61,7 +61,6 @@ from pipecat.services.settings import ( NOT_GIVEN, LLMSettings, _NotGiven, - _warn_deprecated_param, is_given, ) from pipecat.utils.tracing.service_decorators import traced_llm @@ -838,15 +837,15 @@ class GoogleLLMService(LLMService): # 2. Apply direct init arg overrides (deprecated) if model is not None: - _warn_deprecated_param("model", self.Settings, "model") + self._warn_init_param_moved_to_settings("model", "model") default_settings.model = model if system_instruction is not None: - _warn_deprecated_param("system_instruction", self.Settings, "system_instruction") + self._warn_init_param_moved_to_settings("system_instruction", "system_instruction") default_settings.system_instruction = system_instruction # 3. Apply params overrides — only if settings not provided if params is not None: - _warn_deprecated_param("params", self.Settings) + self._warn_init_param_moved_to_settings("params") if not settings: default_settings.max_tokens = params.max_tokens default_settings.temperature = params.temperature diff --git a/src/pipecat/services/google/openai/llm.py b/src/pipecat/services/google/openai/llm.py index 717c1e379..da5d1be7a 100644 --- a/src/pipecat/services/google/openai/llm.py +++ b/src/pipecat/services/google/openai/llm.py @@ -30,7 +30,6 @@ from pipecat.metrics.metrics import LLMTokenUsage from pipecat.processors.aggregators.openai_llm_context import OpenAILLMContext from pipecat.services.openai.base_llm import BaseOpenAILLMService from pipecat.services.openai.llm import OpenAILLMService -from pipecat.services.settings import _warn_deprecated_param @dataclass @@ -100,7 +99,7 @@ class GoogleLLMOpenAIBetaService(OpenAILLMService): # 2. Apply direct init arg overrides (deprecated) if model is not None: - _warn_deprecated_param("model", self.Settings, "model") + self._warn_init_param_moved_to_settings("model", "model") default_settings.model = model # 3. (No step 3, as there's no params object to apply) diff --git a/src/pipecat/services/google/stt.py b/src/pipecat/services/google/stt.py index cab176668..173b201fe 100644 --- a/src/pipecat/services/google/stt.py +++ b/src/pipecat/services/google/stt.py @@ -36,7 +36,7 @@ from pipecat.frames.frames import ( StartFrame, TranscriptionFrame, ) -from pipecat.services.settings import NOT_GIVEN, STTSettings, _NotGiven, _warn_deprecated_param +from pipecat.services.settings import NOT_GIVEN, STTSettings, _NotGiven from pipecat.services.stt_latency import GOOGLE_TTFS_P99 from pipecat.services.stt_service import STTService from pipecat.transcriptions.language import Language, resolve_language @@ -531,7 +531,7 @@ class GoogleSTTService(STTService): # 3. Apply params overrides — only if settings not provided if params is not None: - _warn_deprecated_param("params", self.Settings) + self._warn_init_param_moved_to_settings("params") if not settings: default_settings.languages = list(params.language_list) default_settings.model = params.model diff --git a/src/pipecat/services/google/tts.py b/src/pipecat/services/google/tts.py index c2e32ad3c..3455a8125 100644 --- a/src/pipecat/services/google/tts.py +++ b/src/pipecat/services/google/tts.py @@ -39,7 +39,6 @@ from pipecat.services.settings import ( NOT_GIVEN, TTSSettings, _NotGiven, - _warn_deprecated_param, is_given, ) from pipecat.services.tts_service import TTSService @@ -636,12 +635,12 @@ class GoogleHttpTTSService(TTSService): # 2. Apply direct init arg overrides (deprecated) if voice_id is not None: - _warn_deprecated_param("voice_id", self.Settings, "voice") + self._warn_init_param_moved_to_settings("voice_id", "voice") default_settings.voice = voice_id # 3. Apply params overrides — only if settings not provided if params is not None: - _warn_deprecated_param("params", self.Settings) + self._warn_init_param_moved_to_settings("params") if not settings: if params.pitch is not None: default_settings.pitch = params.pitch @@ -1083,12 +1082,12 @@ class GoogleTTSService(GoogleBaseTTSService): # 2. Apply direct init arg overrides (deprecated) if voice_id is not None: - _warn_deprecated_param("voice_id", self.Settings, "voice") + self._warn_init_param_moved_to_settings("voice_id", "voice") default_settings.voice = voice_id # 3. Apply params overrides — only if settings not provided if params is not None: - _warn_deprecated_param("params", self.Settings) + self._warn_init_param_moved_to_settings("params") if not settings: if params.language is not None: default_settings.language = self.language_to_service_language(params.language) @@ -1331,10 +1330,10 @@ class GeminiTTSService(GoogleBaseTTSService): # 2. Apply direct init arg overrides (deprecated) if model is not None: - _warn_deprecated_param("model", self.Settings, "model") + self._warn_init_param_moved_to_settings("model", "model") default_settings.model = model if voice_id is not None: - _warn_deprecated_param("voice_id", self.Settings, "voice") + self._warn_init_param_moved_to_settings("voice_id", "voice") default_settings.voice = voice_id if default_settings.voice not in self.AVAILABLE_VOICES: @@ -1344,7 +1343,7 @@ class GeminiTTSService(GoogleBaseTTSService): # 3. Apply params overrides — only if settings not provided if params is not None: - _warn_deprecated_param("params", self.Settings) + self._warn_init_param_moved_to_settings("params") if not settings: if params.language is not None: default_settings.language = self.language_to_service_language(params.language) diff --git a/src/pipecat/services/google/vertex/llm.py b/src/pipecat/services/google/vertex/llm.py index 014dea405..946a8f1bb 100644 --- a/src/pipecat/services/google/vertex/llm.py +++ b/src/pipecat/services/google/vertex/llm.py @@ -22,7 +22,6 @@ from typing import Optional from loguru import logger from pipecat.services.google.llm import GoogleLLMService -from pipecat.services.settings import _warn_deprecated_param try: from google.auth import default @@ -215,15 +214,15 @@ class GoogleVertexLLMService(GoogleLLMService): # 2. Apply direct init arg overrides (deprecated) if model is not None: - _warn_deprecated_param("model", self.Settings, "model") + self._warn_init_param_moved_to_settings("model", "model") default_settings.model = model if system_instruction is not None: - _warn_deprecated_param("system_instruction", self.Settings, "system_instruction") + self._warn_init_param_moved_to_settings("system_instruction", "system_instruction") default_settings.system_instruction = system_instruction # 3. Apply params overrides — only if settings not provided if params is not None: - _warn_deprecated_param("params", self.Settings) + self._warn_init_param_moved_to_settings("params") if not settings: default_settings.max_tokens = params.max_tokens default_settings.temperature = params.temperature diff --git a/src/pipecat/services/gradium/stt.py b/src/pipecat/services/gradium/stt.py index 90d1e800f..c328dceab 100644 --- a/src/pipecat/services/gradium/stt.py +++ b/src/pipecat/services/gradium/stt.py @@ -28,7 +28,7 @@ from pipecat.frames.frames import ( VADUserStoppedSpeakingFrame, ) from pipecat.processors.frame_processor import FrameDirection -from pipecat.services.settings import NOT_GIVEN, STTSettings, _NotGiven, _warn_deprecated_param +from pipecat.services.settings import NOT_GIVEN, STTSettings, _NotGiven from pipecat.services.stt_latency import GRADIUM_TTFS_P99 from pipecat.services.stt_service import WebsocketSTTService from pipecat.transcriptions.language import Language, resolve_language @@ -162,7 +162,7 @@ class GradiumSTTService(WebsocketSTTService): # 3. Apply params overrides — only if settings not provided if params is not None: - _warn_deprecated_param("params", self.Settings) + self._warn_init_param_moved_to_settings("params") if not settings: default_settings.language = params.language if params.delay_in_frames is not None: diff --git a/src/pipecat/services/gradium/tts.py b/src/pipecat/services/gradium/tts.py index 43114b193..f63f931ad 100644 --- a/src/pipecat/services/gradium/tts.py +++ b/src/pipecat/services/gradium/tts.py @@ -21,7 +21,7 @@ from pipecat.frames.frames import ( TTSAudioRawFrame, TTSStoppedFrame, ) -from pipecat.services.settings import TTSSettings, _warn_deprecated_param +from pipecat.services.settings import TTSSettings from pipecat.services.tts_service import WebsocketTTSService from pipecat.utils.tracing.service_decorators import traced_tts @@ -108,15 +108,15 @@ class GradiumTTSService(WebsocketTTSService): # 2. Apply direct init arg overrides (deprecated) if model is not None: - _warn_deprecated_param("model", self.Settings, "model") + self._warn_init_param_moved_to_settings("model", "model") default_settings.model = model if voice_id is not None: - _warn_deprecated_param("voice_id", self.Settings, "voice") + self._warn_init_param_moved_to_settings("voice_id", "voice") default_settings.voice = voice_id # 3. Apply params overrides — only if settings not provided if params is not None: - _warn_deprecated_param("params", self.Settings) + self._warn_init_param_moved_to_settings("params") # Note: params.temp has no corresponding settings field # 4. Apply settings delta (canonical API, always wins) diff --git a/src/pipecat/services/grok/llm.py b/src/pipecat/services/grok/llm.py index 3eaf0646a..160ad3331 100644 --- a/src/pipecat/services/grok/llm.py +++ b/src/pipecat/services/grok/llm.py @@ -29,7 +29,6 @@ from pipecat.services.openai.llm import ( OpenAILLMService, OpenAIUserContextAggregator, ) -from pipecat.services.settings import _warn_deprecated_param @dataclass @@ -117,7 +116,7 @@ class GrokLLMService(OpenAILLMService): # 2. Apply direct init arg overrides (deprecated) if model is not None: - _warn_deprecated_param("model", self.Settings, "model") + self._warn_init_param_moved_to_settings("model", "model") default_settings.model = model # 3. (No step 3, as there's no params object to apply) diff --git a/src/pipecat/services/grok/realtime/llm.py b/src/pipecat/services/grok/realtime/llm.py index dcd7ac59e..bfa192aad 100644 --- a/src/pipecat/services/grok/realtime/llm.py +++ b/src/pipecat/services/grok/realtime/llm.py @@ -60,7 +60,6 @@ from pipecat.services.settings import ( NOT_GIVEN, LLMSettings, _NotGiven, - _warn_deprecated_param, is_given, ) from pipecat.utils.time import time_now_iso8601 diff --git a/src/pipecat/services/groq/llm.py b/src/pipecat/services/groq/llm.py index 8b6bdc3bc..d36b52ab8 100644 --- a/src/pipecat/services/groq/llm.py +++ b/src/pipecat/services/groq/llm.py @@ -13,7 +13,6 @@ from loguru import logger from pipecat.services.openai.base_llm import BaseOpenAILLMService from pipecat.services.openai.llm import OpenAILLMService -from pipecat.services.settings import _warn_deprecated_param @dataclass @@ -61,7 +60,7 @@ class GroqLLMService(OpenAILLMService): # 2. Apply direct init arg overrides (deprecated) if model is not None: - _warn_deprecated_param("model", self.Settings, "model") + self._warn_init_param_moved_to_settings("model", "model") default_settings.model = model # 3. (No step 3, as there's no params object to apply) diff --git a/src/pipecat/services/groq/stt.py b/src/pipecat/services/groq/stt.py index 6a234cc27..6ff4075ae 100644 --- a/src/pipecat/services/groq/stt.py +++ b/src/pipecat/services/groq/stt.py @@ -9,7 +9,6 @@ from dataclasses import dataclass from typing import Optional -from pipecat.services.settings import _warn_deprecated_param from pipecat.services.stt_latency import GROQ_TTFS_P99 from pipecat.services.whisper.base_stt import ( BaseWhisperSTTService, @@ -93,16 +92,16 @@ class GroqSTTService(BaseWhisperSTTService): # --- 2. Deprecated direct-arg overrides --- if model is not None: - _warn_deprecated_param("model", self.Settings, "model") + self._warn_init_param_moved_to_settings("model", "model") default_settings.model = model if language is not None: - _warn_deprecated_param("language", self.Settings, "language") + self._warn_init_param_moved_to_settings("language", "language") default_settings.language = self.language_to_service_language(language) if prompt is not None: - _warn_deprecated_param("prompt", self.Settings, "prompt") + self._warn_init_param_moved_to_settings("prompt", "prompt") default_settings.prompt = prompt if temperature is not None: - _warn_deprecated_param("temperature", self.Settings, "temperature") + self._warn_init_param_moved_to_settings("temperature", "temperature") default_settings.temperature = temperature # --- 3. (no params object for this service) --- diff --git a/src/pipecat/services/groq/tts.py b/src/pipecat/services/groq/tts.py index 714ecdeb1..00ff3ef84 100644 --- a/src/pipecat/services/groq/tts.py +++ b/src/pipecat/services/groq/tts.py @@ -19,7 +19,7 @@ from pipecat.frames.frames import ( Frame, TTSAudioRawFrame, ) -from pipecat.services.settings import NOT_GIVEN, TTSSettings, _NotGiven, _warn_deprecated_param +from pipecat.services.settings import NOT_GIVEN, TTSSettings, _NotGiven from pipecat.services.tts_service import TTSService from pipecat.transcriptions.language import Language from pipecat.utils.tracing.service_decorators import traced_tts @@ -120,15 +120,15 @@ class GroqTTSService(TTSService): # 2. Apply direct init arg overrides (deprecated) if model_name is not None: - _warn_deprecated_param("model_name", self.Settings, "model") + self._warn_init_param_moved_to_settings("model_name", "model") default_settings.model = model_name if voice_id is not None: - _warn_deprecated_param("voice_id", self.Settings, "voice") + self._warn_init_param_moved_to_settings("voice_id", "voice") default_settings.voice = voice_id # 3. Apply params overrides — only if settings not provided if params is not None: - _warn_deprecated_param("params", self.Settings) + self._warn_init_param_moved_to_settings("params") if not settings: default_settings.language = str(params.language) if params.language else "en" default_settings.speed = params.speed diff --git a/src/pipecat/services/hume/tts.py b/src/pipecat/services/hume/tts.py index 9fa1cd46c..e591ebec2 100644 --- a/src/pipecat/services/hume/tts.py +++ b/src/pipecat/services/hume/tts.py @@ -25,7 +25,7 @@ from pipecat.frames.frames import ( TTSStoppedFrame, ) from pipecat.processors.frame_processor import FrameDirection -from pipecat.services.settings import NOT_GIVEN, TTSSettings, _NotGiven, _warn_deprecated_param +from pipecat.services.settings import NOT_GIVEN, TTSSettings, _NotGiven from pipecat.services.tts_service import TTSService from pipecat.utils.tracing.service_decorators import traced_tts @@ -147,12 +147,12 @@ class HumeTTSService(TTSService): # 2. Apply direct init arg overrides (deprecated) if voice_id is not None: - _warn_deprecated_param("voice_id", self.Settings, "voice") + self._warn_init_param_moved_to_settings("voice_id", "voice") default_settings.voice = voice_id # 3. Apply params overrides — only if settings not provided if params is not None: - _warn_deprecated_param("params", self.Settings) + self._warn_init_param_moved_to_settings("params") if not settings: default_settings.description = params.description default_settings.speed = params.speed diff --git a/src/pipecat/services/inworld/tts.py b/src/pipecat/services/inworld/tts.py index f24e9dcf6..334c3c617 100644 --- a/src/pipecat/services/inworld/tts.py +++ b/src/pipecat/services/inworld/tts.py @@ -40,7 +40,7 @@ from pipecat import version as pipecat_version USER_AGENT = f"pipecat/{pipecat_version()}" from pydantic import BaseModel -from pipecat.services.settings import NOT_GIVEN, TTSSettings, _NotGiven, _warn_deprecated_param +from pipecat.services.settings import NOT_GIVEN, TTSSettings, _NotGiven try: from websockets.asyncio.client import connect as websocket_connect @@ -174,15 +174,15 @@ class InworldHttpTTSService(TTSService): # 2. Apply direct init arg overrides (deprecated) if voice_id is not None: - _warn_deprecated_param("voice_id", self.Settings, "voice") + self._warn_init_param_moved_to_settings("voice_id", "voice") default_settings.voice = voice_id if model is not None: - _warn_deprecated_param("model", self.Settings, "model") + self._warn_init_param_moved_to_settings("model", "model") default_settings.model = model # 3. Apply params overrides — only if settings not provided if params is not None: - _warn_deprecated_param("params", self.Settings) + self._warn_init_param_moved_to_settings("params") if not settings: if params.speaking_rate is not None: default_settings.speaking_rate = params.speaking_rate @@ -592,17 +592,17 @@ class InworldTTSService(WebsocketTTSService): # 2. Apply direct init arg overrides (deprecated) if voice_id is not None: - _warn_deprecated_param("voice_id", self.Settings, "voice") + self._warn_init_param_moved_to_settings("voice_id", "voice") default_settings.voice = voice_id if model is not None: - _warn_deprecated_param("model", self.Settings, "model") + self._warn_init_param_moved_to_settings("model", "model") default_settings.model = model # 3. Apply params overrides — only if settings not provided _buffer_max_delay_ms = None _buffer_char_threshold = None if params is not None: - _warn_deprecated_param("params", self.Settings) + self._warn_init_param_moved_to_settings("params") if not settings: if params.speaking_rate is not None: default_settings.speaking_rate = params.speaking_rate diff --git a/src/pipecat/services/kokoro/tts.py b/src/pipecat/services/kokoro/tts.py index fd7f15c27..34e703dab 100644 --- a/src/pipecat/services/kokoro/tts.py +++ b/src/pipecat/services/kokoro/tts.py @@ -21,7 +21,7 @@ from pipecat.frames.frames import ( Frame, TTSAudioRawFrame, ) -from pipecat.services.settings import TTSSettings, _warn_deprecated_param +from pipecat.services.settings import TTSSettings from pipecat.services.tts_service import TTSService from pipecat.transcriptions.language import Language, resolve_language from pipecat.utils.tracing.service_decorators import traced_tts @@ -155,12 +155,12 @@ class KokoroTTSService(TTSService): # 2. Apply direct init arg overrides (deprecated) if voice_id is not None: - _warn_deprecated_param("voice_id", self.Settings, "voice") + self._warn_init_param_moved_to_settings("voice_id", "voice") default_settings.voice = voice_id # 3. Apply params overrides — only if settings not provided if params is not None: - _warn_deprecated_param("params", self.Settings) + self._warn_init_param_moved_to_settings("params") if not settings: default_settings.language = language_to_kokoro_language(params.language) diff --git a/src/pipecat/services/lmnt/tts.py b/src/pipecat/services/lmnt/tts.py index ea5986ffc..0ca91a107 100644 --- a/src/pipecat/services/lmnt/tts.py +++ b/src/pipecat/services/lmnt/tts.py @@ -22,7 +22,7 @@ from pipecat.frames.frames import ( TTSStoppedFrame, ) from pipecat.processors.frame_processor import FrameDirection -from pipecat.services.settings import TTSSettings, _warn_deprecated_param +from pipecat.services.settings import TTSSettings from pipecat.services.tts_service import InterruptibleTTSService from pipecat.transcriptions.language import Language, resolve_language from pipecat.utils.tracing.service_decorators import traced_tts @@ -134,10 +134,10 @@ class LmntTTSService(InterruptibleTTSService): # 2. Apply direct init arg overrides (deprecated) if voice_id is not None: - _warn_deprecated_param("voice_id", self.Settings, "voice") + self._warn_init_param_moved_to_settings("voice_id", "voice") default_settings.voice = voice_id if model is not None: - _warn_deprecated_param("model", self.Settings, "model") + self._warn_init_param_moved_to_settings("model", "model") default_settings.model = model # 3. (No step 3, as there's no params object to apply) diff --git a/src/pipecat/services/minimax/tts.py b/src/pipecat/services/minimax/tts.py index 173c1ea05..d41fb6255 100644 --- a/src/pipecat/services/minimax/tts.py +++ b/src/pipecat/services/minimax/tts.py @@ -24,7 +24,7 @@ from pipecat.frames.frames import ( StartFrame, TTSAudioRawFrame, ) -from pipecat.services.settings import NOT_GIVEN, TTSSettings, _NotGiven, _warn_deprecated_param +from pipecat.services.settings import NOT_GIVEN, TTSSettings, _NotGiven from pipecat.services.tts_service import TTSService from pipecat.transcriptions.language import Language, resolve_language from pipecat.utils.tracing.service_decorators import traced_tts @@ -243,15 +243,15 @@ class MiniMaxHttpTTSService(TTSService): # 2. Apply direct init arg overrides (deprecated) if model is not None: - _warn_deprecated_param("model", self.Settings, "model") + self._warn_init_param_moved_to_settings("model", "model") default_settings.model = model if voice_id is not None: - _warn_deprecated_param("voice_id", self.Settings, "voice") + self._warn_init_param_moved_to_settings("voice_id", "voice") default_settings.voice = voice_id # 3. Apply params overrides — only if settings not provided if params is not None: - _warn_deprecated_param("params", self.Settings) + self._warn_init_param_moved_to_settings("params") if not settings: default_settings.speed = params.speed default_settings.volume = params.volume diff --git a/src/pipecat/services/mistral/llm.py b/src/pipecat/services/mistral/llm.py index 4b74695ef..3ee1b2623 100644 --- a/src/pipecat/services/mistral/llm.py +++ b/src/pipecat/services/mistral/llm.py @@ -16,7 +16,6 @@ from pipecat.adapters.services.open_ai_adapter import OpenAILLMInvocationParams from pipecat.frames.frames import FunctionCallFromLLM from pipecat.services.openai.base_llm import BaseOpenAILLMService from pipecat.services.openai.llm import OpenAILLMService -from pipecat.services.settings import _warn_deprecated_param @dataclass @@ -64,7 +63,7 @@ class MistralLLMService(OpenAILLMService): # 2. Apply direct init arg overrides (deprecated) if model is not None: - _warn_deprecated_param("model", self.Settings, "model") + self._warn_init_param_moved_to_settings("model", "model") default_settings.model = model # 3. (No step 3, as there's no params object to apply) diff --git a/src/pipecat/services/moondream/vision.py b/src/pipecat/services/moondream/vision.py index b8ab5a270..6eeff19cd 100644 --- a/src/pipecat/services/moondream/vision.py +++ b/src/pipecat/services/moondream/vision.py @@ -25,7 +25,7 @@ from pipecat.frames.frames import ( VisionFullResponseStartFrame, VisionTextFrame, ) -from pipecat.services.settings import VisionSettings, _warn_deprecated_param +from pipecat.services.settings import VisionSettings from pipecat.services.vision_service import VisionService try: @@ -110,7 +110,7 @@ class MoondreamService(VisionService): # 2. Apply direct init arg overrides (deprecated) if model is not None: - _warn_deprecated_param("model", self.Settings, "model") + self._warn_init_param_moved_to_settings("model", "model") default_settings.model = model # 4. Apply settings delta (canonical API, always wins) diff --git a/src/pipecat/services/neuphonic/tts.py b/src/pipecat/services/neuphonic/tts.py index 5c0605293..b345a0ff4 100644 --- a/src/pipecat/services/neuphonic/tts.py +++ b/src/pipecat/services/neuphonic/tts.py @@ -33,7 +33,7 @@ from pipecat.frames.frames import ( TTSStoppedFrame, ) from pipecat.processors.frame_processor import FrameDirection -from pipecat.services.settings import NOT_GIVEN, TTSSettings, _NotGiven, _warn_deprecated_param +from pipecat.services.settings import NOT_GIVEN, TTSSettings, _NotGiven from pipecat.services.tts_service import InterruptibleTTSService, TextAggregationMode, TTSService from pipecat.transcriptions.language import Language, resolve_language from pipecat.utils.tracing.service_decorators import traced_tts @@ -159,12 +159,12 @@ class NeuphonicTTSService(InterruptibleTTSService): # 2. Apply direct init arg overrides (deprecated) if voice_id is not None: - _warn_deprecated_param("voice_id", self.Settings, "voice") + self._warn_init_param_moved_to_settings("voice_id", "voice") default_settings.voice = voice_id # 3. Apply params overrides — only if settings not provided if params is not None: - _warn_deprecated_param("params", self.Settings) + self._warn_init_param_moved_to_settings("params") if not settings: if params.language is not None: default_settings.language = self.language_to_service_language(params.language) @@ -493,12 +493,12 @@ class NeuphonicHttpTTSService(TTSService): # 2. Apply direct init arg overrides (deprecated) if voice_id is not None: - _warn_deprecated_param("voice_id", self.Settings, "voice") + self._warn_init_param_moved_to_settings("voice_id", "voice") default_settings.voice = voice_id # 3. Apply params overrides — only if settings not provided if params is not None: - _warn_deprecated_param("params", self.Settings) + self._warn_init_param_moved_to_settings("params") if not settings: if params.language is not None: default_settings.language = self.language_to_service_language(params.language) diff --git a/src/pipecat/services/nvidia/llm.py b/src/pipecat/services/nvidia/llm.py index b40190bec..66bbd4402 100644 --- a/src/pipecat/services/nvidia/llm.py +++ b/src/pipecat/services/nvidia/llm.py @@ -18,7 +18,6 @@ from pipecat.processors.aggregators.llm_context import LLMContext from pipecat.processors.aggregators.openai_llm_context import OpenAILLMContext from pipecat.services.openai.base_llm import BaseOpenAILLMService from pipecat.services.openai.llm import OpenAILLMService -from pipecat.services.settings import _warn_deprecated_param @dataclass @@ -68,7 +67,7 @@ class NvidiaLLMService(OpenAILLMService): # 2. Apply direct init arg overrides (deprecated) if model is not None: - _warn_deprecated_param("model", self.Settings, "model") + self._warn_init_param_moved_to_settings("model", "model") default_settings.model = model # 3. (No step 3, as there's no params object to apply) diff --git a/src/pipecat/services/nvidia/stt.py b/src/pipecat/services/nvidia/stt.py index 3c8004baa..fcca14741 100644 --- a/src/pipecat/services/nvidia/stt.py +++ b/src/pipecat/services/nvidia/stt.py @@ -23,7 +23,7 @@ from pipecat.frames.frames import ( StartFrame, TranscriptionFrame, ) -from pipecat.services.settings import NOT_GIVEN, STTSettings, _NotGiven, _warn_deprecated_param +from pipecat.services.settings import NOT_GIVEN, STTSettings, _NotGiven from pipecat.services.stt_latency import NVIDIA_TTFS_P99 from pipecat.services.stt_service import SegmentedSTTService, STTService from pipecat.transcriptions.language import Language, resolve_language @@ -185,7 +185,7 @@ class NvidiaSTTService(STTService): # 3. Apply params overrides — only if settings not provided if params is not None: - _warn_deprecated_param("params", self.Settings) + self._warn_init_param_moved_to_settings("params") if not settings: default_settings.language = params.language @@ -515,7 +515,7 @@ class NvidiaSegmentedSTTService(SegmentedSTTService): # 3. Apply params overrides — only if settings not provided if params is not None: - _warn_deprecated_param("params", self.Settings) + self._warn_init_param_moved_to_settings("params") if not settings: default_settings.language = ( language_to_nvidia_riva_language(params.language or Language.EN_US) or "en-US" diff --git a/src/pipecat/services/nvidia/tts.py b/src/pipecat/services/nvidia/tts.py index b41de8b47..5e7a20a3c 100644 --- a/src/pipecat/services/nvidia/tts.py +++ b/src/pipecat/services/nvidia/tts.py @@ -29,7 +29,7 @@ from pipecat.frames.frames import ( StartFrame, TTSAudioRawFrame, ) -from pipecat.services.settings import NOT_GIVEN, TTSSettings, _NotGiven, _warn_deprecated_param +from pipecat.services.settings import NOT_GIVEN, TTSSettings, _NotGiven from pipecat.services.tts_service import TTSService from pipecat.transcriptions.language import Language @@ -126,12 +126,12 @@ class NvidiaTTSService(TTSService): # 2. Apply direct init arg overrides (deprecated) if voice_id is not None: - _warn_deprecated_param("voice_id", self.Settings, "voice") + self._warn_init_param_moved_to_settings("voice_id", "voice") default_settings.voice = voice_id # 3. Apply params overrides — only if settings not provided if params is not None: - _warn_deprecated_param("params", self.Settings) + self._warn_init_param_moved_to_settings("params") if not settings: if params.language is not None: default_settings.language = params.language diff --git a/src/pipecat/services/ollama/llm.py b/src/pipecat/services/ollama/llm.py index 3b15049a4..a24ebfcaf 100644 --- a/src/pipecat/services/ollama/llm.py +++ b/src/pipecat/services/ollama/llm.py @@ -13,7 +13,6 @@ from loguru import logger from pipecat.services.openai.base_llm import BaseOpenAILLMService from pipecat.services.openai.llm import OpenAILLMService -from pipecat.services.settings import _warn_deprecated_param @dataclass @@ -60,7 +59,7 @@ class OLLamaLLMService(OpenAILLMService): # 2. Apply direct init arg overrides (deprecated) if model is not None: - _warn_deprecated_param("model", self.Settings, "model") + self._warn_init_param_moved_to_settings("model", "model") default_settings.model = model # 3. (No step 3, as there's no params object to apply) diff --git a/src/pipecat/services/openai/image.py b/src/pipecat/services/openai/image.py index 31f9949b8..de010247b 100644 --- a/src/pipecat/services/openai/image.py +++ b/src/pipecat/services/openai/image.py @@ -25,7 +25,7 @@ from pipecat.frames.frames import ( URLImageRawFrame, ) from pipecat.services.image_service import ImageGenService -from pipecat.services.settings import NOT_GIVEN, ImageGenSettings, _NotGiven, _warn_deprecated_param +from pipecat.services.settings import NOT_GIVEN, ImageGenSettings, _NotGiven @dataclass @@ -90,11 +90,11 @@ class OpenAIImageGenService(ImageGenService): # 2. Apply direct init arg overrides (deprecated) if model is not None: - _warn_deprecated_param("model", self.Settings, "model") + self._warn_init_param_moved_to_settings("model", "model") default_settings.model = model if image_size is not None: - _warn_deprecated_param("image_size", self.Settings, "image_size") + self._warn_init_param_moved_to_settings("image_size", "image_size") default_settings.image_size = image_size # 4. Apply settings delta (canonical API, always wins) diff --git a/src/pipecat/services/openai/llm.py b/src/pipecat/services/openai/llm.py index 032d4dfa4..abb3e7eec 100644 --- a/src/pipecat/services/openai/llm.py +++ b/src/pipecat/services/openai/llm.py @@ -26,7 +26,6 @@ from pipecat.processors.aggregators.llm_response import ( ) from pipecat.processors.aggregators.openai_llm_context import OpenAILLMContext from pipecat.services.openai.base_llm import BaseOpenAILLMService -from pipecat.services.settings import _warn_deprecated_param @dataclass @@ -120,7 +119,7 @@ class OpenAILLMService(BaseOpenAILLMService): # 2. Apply direct init arg overrides (deprecated) if model is not None: - _warn_deprecated_param("model", self.Settings, "model") + self._warn_init_param_moved_to_settings("model", "model") default_settings.model = model # Handle service_tier from deprecated params @@ -129,7 +128,7 @@ class OpenAILLMService(BaseOpenAILLMService): # 3. Apply params overrides — only if settings not provided if params is not None: - _warn_deprecated_param("params", self.Settings) + self._warn_init_param_moved_to_settings("params") if not settings: default_settings.frequency_penalty = params.frequency_penalty default_settings.presence_penalty = params.presence_penalty diff --git a/src/pipecat/services/openai/realtime/llm.py b/src/pipecat/services/openai/realtime/llm.py index 300792cbd..faaa19884 100644 --- a/src/pipecat/services/openai/realtime/llm.py +++ b/src/pipecat/services/openai/realtime/llm.py @@ -63,7 +63,6 @@ from pipecat.services.settings import ( NOT_GIVEN, LLMSettings, _NotGiven, - _warn_deprecated_param, is_given, ) from pipecat.transcriptions.language import Language @@ -294,7 +293,7 @@ class OpenAIRealtimeLLMService(LLMService): # 2. Apply direct init arg overrides (deprecated) if model is not None: - _warn_deprecated_param("model", self.Settings, "model") + self._warn_init_param_moved_to_settings("model", "model") default_settings.model = model if session_properties is not None: diff --git a/src/pipecat/services/openai/stt.py b/src/pipecat/services/openai/stt.py index 943be17de..39ca60b25 100644 --- a/src/pipecat/services/openai/stt.py +++ b/src/pipecat/services/openai/stt.py @@ -35,7 +35,7 @@ from pipecat.frames.frames import ( VADUserStoppedSpeakingFrame, ) from pipecat.processors.frame_processor import FrameDirection -from pipecat.services.settings import NOT_GIVEN, STTSettings, _NotGiven, _warn_deprecated_param +from pipecat.services.settings import NOT_GIVEN, STTSettings, _NotGiven from pipecat.services.stt_latency import OPENAI_REALTIME_TTFS_P99, OPENAI_TTFS_P99 from pipecat.services.stt_service import WebsocketSTTService from pipecat.services.whisper.base_stt import ( @@ -126,13 +126,13 @@ class OpenAISTTService(BaseWhisperSTTService): # --- 2. Deprecated direct-arg overrides --- if model is not None: - _warn_deprecated_param("model", self.Settings, "model") + self._warn_init_param_moved_to_settings("model", "model") default_settings.model = model if prompt is not None: - _warn_deprecated_param("prompt", self.Settings, "prompt") + self._warn_init_param_moved_to_settings("prompt", "prompt") default_settings.prompt = prompt if temperature is not None: - _warn_deprecated_param("temperature", self.Settings, "temperature") + self._warn_init_param_moved_to_settings("temperature", "temperature") default_settings.temperature = temperature # --- 3. (no params object for this service) --- @@ -310,16 +310,16 @@ class OpenAIRealtimeSTTService(WebsocketSTTService): # --- 2. Deprecated direct-arg overrides --- if model is not None: - _warn_deprecated_param("model", self.Settings, "model") + self._warn_init_param_moved_to_settings("model", "model") default_settings.model = model if language is not None and language != Language.EN: - _warn_deprecated_param("language", self.Settings, "language") + self._warn_init_param_moved_to_settings("language", "language") default_settings.language = language if prompt is not None: - _warn_deprecated_param("prompt", self.Settings, "prompt") + self._warn_init_param_moved_to_settings("prompt", "prompt") default_settings.prompt = prompt if noise_reduction is not None: - _warn_deprecated_param("noise_reduction", self.Settings, "noise_reduction") + self._warn_init_param_moved_to_settings("noise_reduction", "noise_reduction") default_settings.noise_reduction = noise_reduction # --- 3. (no params object for this service) --- diff --git a/src/pipecat/services/openai/tts.py b/src/pipecat/services/openai/tts.py index 7eb80cd1e..074792b33 100644 --- a/src/pipecat/services/openai/tts.py +++ b/src/pipecat/services/openai/tts.py @@ -23,7 +23,7 @@ from pipecat.frames.frames import ( StartFrame, TTSAudioRawFrame, ) -from pipecat.services.settings import NOT_GIVEN, TTSSettings, _NotGiven, _warn_deprecated_param +from pipecat.services.settings import NOT_GIVEN, TTSSettings, _NotGiven from pipecat.services.tts_service import TTSService from pipecat.utils.tracing.service_decorators import traced_tts @@ -166,21 +166,21 @@ class OpenAITTSService(TTSService): # 2. Apply direct init arg overrides (deprecated) if voice is not None: - _warn_deprecated_param("voice", self.Settings, "voice") + self._warn_init_param_moved_to_settings("voice", "voice") default_settings.voice = voice if model is not None: - _warn_deprecated_param("model", self.Settings, "model") + self._warn_init_param_moved_to_settings("model", "model") default_settings.model = model if instructions is not None: - _warn_deprecated_param("instructions", self.Settings, "instructions") + self._warn_init_param_moved_to_settings("instructions", "instructions") default_settings.instructions = instructions if speed is not None: - _warn_deprecated_param("speed", self.Settings, "speed") + self._warn_init_param_moved_to_settings("speed", "speed") default_settings.speed = speed # 3. Apply params overrides — only if settings not provided if params is not None: - _warn_deprecated_param("params", self.Settings) + self._warn_init_param_moved_to_settings("params") if not settings: if params.instructions is not None: default_settings.instructions = params.instructions diff --git a/src/pipecat/services/openai_realtime_beta/openai.py b/src/pipecat/services/openai_realtime_beta/openai.py index 209ff3122..0a6315986 100644 --- a/src/pipecat/services/openai_realtime_beta/openai.py +++ b/src/pipecat/services/openai_realtime_beta/openai.py @@ -54,7 +54,7 @@ from pipecat.processors.aggregators.openai_llm_context import ( from pipecat.processors.frame_processor import FrameDirection from pipecat.services.llm_service import FunctionCallFromLLM, LLMService from pipecat.services.openai.llm import OpenAIContextAggregatorPair -from pipecat.services.settings import LLMSettings, _warn_deprecated_param +from pipecat.services.settings import LLMSettings from pipecat.transcriptions.language import Language from pipecat.utils.time import time_now_iso8601 from pipecat.utils.tracing.service_decorators import traced_openai_realtime, traced_stt @@ -173,7 +173,7 @@ class OpenAIRealtimeBetaLLMService(LLMService): # 2. Apply direct init arg overrides (deprecated) if model is not None: - _warn_deprecated_param("model", self.Settings, "model") + self._warn_init_param_moved_to_settings("model", "model") default_settings.model = model # 3. Apply settings delta (canonical API, always wins) if settings is not None: diff --git a/src/pipecat/services/openpipe/llm.py b/src/pipecat/services/openpipe/llm.py index a2198eb74..0a8fd9044 100644 --- a/src/pipecat/services/openpipe/llm.py +++ b/src/pipecat/services/openpipe/llm.py @@ -18,7 +18,6 @@ from loguru import logger from pipecat.adapters.services.open_ai_adapter import OpenAILLMInvocationParams from pipecat.services.openai.base_llm import BaseOpenAILLMService from pipecat.services.openai.llm import OpenAILLMService -from pipecat.services.settings import _warn_deprecated_param try: from openpipe import AsyncOpenAI as OpenPipeAI @@ -80,7 +79,7 @@ class OpenPipeLLMService(OpenAILLMService): # 2. Apply direct init arg overrides (deprecated) if model is not None: - _warn_deprecated_param("model", self.Settings, "model") + self._warn_init_param_moved_to_settings("model", "model") default_settings.model = model # 3. (No step 3, as there's no params object to apply) diff --git a/src/pipecat/services/openrouter/llm.py b/src/pipecat/services/openrouter/llm.py index 84647890f..f92fb5e3b 100644 --- a/src/pipecat/services/openrouter/llm.py +++ b/src/pipecat/services/openrouter/llm.py @@ -17,7 +17,6 @@ from loguru import logger from pipecat.services.openai.base_llm import BaseOpenAILLMService from pipecat.services.openai.llm import OpenAILLMService -from pipecat.services.settings import _warn_deprecated_param @dataclass @@ -66,7 +65,7 @@ class OpenRouterLLMService(OpenAILLMService): # 2. Apply direct init arg overrides (deprecated) if model is not None: - _warn_deprecated_param("model", self.Settings, "model") + self._warn_init_param_moved_to_settings("model", "model") default_settings.model = model # 3. (No step 3, as there's no params object to apply) diff --git a/src/pipecat/services/perplexity/llm.py b/src/pipecat/services/perplexity/llm.py index c93a77c16..6c2ceba35 100644 --- a/src/pipecat/services/perplexity/llm.py +++ b/src/pipecat/services/perplexity/llm.py @@ -20,7 +20,6 @@ from pipecat.processors.aggregators.llm_context import LLMContext from pipecat.processors.aggregators.openai_llm_context import OpenAILLMContext from pipecat.services.openai.base_llm import BaseOpenAILLMService from pipecat.services.openai.llm import OpenAILLMService -from pipecat.services.settings import _warn_deprecated_param @dataclass @@ -69,7 +68,7 @@ class PerplexityLLMService(OpenAILLMService): # 2. Apply direct init arg overrides (deprecated) if model is not None: - _warn_deprecated_param("model", self.Settings, "model") + self._warn_init_param_moved_to_settings("model", "model") default_settings.model = model # 3. (No step 3, as there's no params object to apply) diff --git a/src/pipecat/services/piper/tts.py b/src/pipecat/services/piper/tts.py index 0d56d377e..1b0037abb 100644 --- a/src/pipecat/services/piper/tts.py +++ b/src/pipecat/services/piper/tts.py @@ -19,7 +19,7 @@ from pipecat.frames.frames import ( Frame, TTSStoppedFrame, ) -from pipecat.services.settings import TTSSettings, _warn_deprecated_param +from pipecat.services.settings import TTSSettings from pipecat.services.tts_service import TTSService from pipecat.utils.tracing.service_decorators import traced_tts @@ -81,7 +81,7 @@ class PiperTTSService(TTSService): # 2. Apply direct init arg overrides (deprecated) if voice_id is not None: - _warn_deprecated_param("voice_id", self.Settings, "voice") + self._warn_init_param_moved_to_settings("voice_id", "voice") default_settings.voice = voice_id # 3. (No step 3, as there's no params object to apply) @@ -232,7 +232,7 @@ class PiperHttpTTSService(TTSService): # 2. Apply direct init arg overrides (deprecated) if voice_id is not None: - _warn_deprecated_param("voice_id", self.Settings, "voice") + self._warn_init_param_moved_to_settings("voice_id", "voice") default_settings.voice = voice_id # 3. (No step 3, as there's no params object to apply) diff --git a/src/pipecat/services/qwen/llm.py b/src/pipecat/services/qwen/llm.py index 4c3d7015c..857c89bea 100644 --- a/src/pipecat/services/qwen/llm.py +++ b/src/pipecat/services/qwen/llm.py @@ -13,7 +13,6 @@ from loguru import logger from pipecat.services.openai.base_llm import BaseOpenAILLMService from pipecat.services.openai.llm import OpenAILLMService -from pipecat.services.settings import _warn_deprecated_param @dataclass @@ -61,7 +60,7 @@ class QwenLLMService(OpenAILLMService): # 2. Apply direct init arg overrides (deprecated) if model is not None: - _warn_deprecated_param("model", self.Settings, "model") + self._warn_init_param_moved_to_settings("model", "model") default_settings.model = model # 3. (No step 3, as there's no params object to apply) diff --git a/src/pipecat/services/resembleai/tts.py b/src/pipecat/services/resembleai/tts.py index 7375b9a1b..fc70d814b 100644 --- a/src/pipecat/services/resembleai/tts.py +++ b/src/pipecat/services/resembleai/tts.py @@ -23,7 +23,7 @@ from pipecat.frames.frames import ( TTSStartedFrame, TTSStoppedFrame, ) -from pipecat.services.settings import TTSSettings, _warn_deprecated_param +from pipecat.services.settings import TTSSettings from pipecat.services.tts_service import WebsocketTTSService from pipecat.utils.tracing.service_decorators import traced_tts @@ -92,7 +92,7 @@ class ResembleAITTSService(WebsocketTTSService): # 2. Apply direct init arg overrides (deprecated) if voice_id is not None: - _warn_deprecated_param("voice_id", self.Settings, "voice") + self._warn_init_param_moved_to_settings("voice_id", "voice") default_settings.voice = voice_id # 3. (No step 3, as there's no params object to apply) diff --git a/src/pipecat/services/rime/tts.py b/src/pipecat/services/rime/tts.py index df1b269cd..24a5d152b 100644 --- a/src/pipecat/services/rime/tts.py +++ b/src/pipecat/services/rime/tts.py @@ -31,7 +31,7 @@ from pipecat.frames.frames import ( TTSStoppedFrame, ) from pipecat.processors.frame_processor import FrameDirection -from pipecat.services.settings import NOT_GIVEN, TTSSettings, _NotGiven, _warn_deprecated_param +from pipecat.services.settings import NOT_GIVEN, TTSSettings, _NotGiven from pipecat.services.tts_service import ( InterruptibleTTSService, TextAggregationMode, @@ -241,15 +241,15 @@ class RimeTTSService(WebsocketTTSService): # 2. Apply direct init arg overrides (deprecated) if voice_id is not None: - _warn_deprecated_param("voice_id", self.Settings, "voice") + self._warn_init_param_moved_to_settings("voice_id", "voice") default_settings.voice = voice_id if model is not None: - _warn_deprecated_param("model", self.Settings, "model") + self._warn_init_param_moved_to_settings("model", "model") default_settings.model = model # 3. Apply params overrides — only if settings not provided if params is not None: - _warn_deprecated_param("params", self.Settings) + self._warn_init_param_moved_to_settings("params") if not settings: default_settings.language = ( self.language_to_service_language(params.language) if params.language else None @@ -744,15 +744,15 @@ class RimeHttpTTSService(TTSService): # 2. Apply direct init arg overrides (deprecated) if voice_id is not None: - _warn_deprecated_param("voice_id", self.Settings, "voice") + self._warn_init_param_moved_to_settings("voice_id", "voice") default_settings.voice = voice_id if model is not None: - _warn_deprecated_param("model", self.Settings, "model") + self._warn_init_param_moved_to_settings("model", "model") default_settings.model = model # 3. Apply params overrides — only if settings not provided if params is not None: - _warn_deprecated_param("params", self.Settings) + self._warn_init_param_moved_to_settings("params") if not settings: default_settings.language = ( self.language_to_service_language(params.language) if params.language else "eng" @@ -974,15 +974,15 @@ class RimeNonJsonTTSService(InterruptibleTTSService): # 2. Apply direct init arg overrides (deprecated) if voice_id is not None: - _warn_deprecated_param("voice_id", self.Settings, "voice") + self._warn_init_param_moved_to_settings("voice_id", "voice") default_settings.voice = voice_id if model is not None: - _warn_deprecated_param("model", self.Settings, "model") + self._warn_init_param_moved_to_settings("model", "model") default_settings.model = model # 3. Apply params overrides — only if settings not provided if params is not None: - _warn_deprecated_param("params", self.Settings) + self._warn_init_param_moved_to_settings("params") if not settings: default_settings.language = ( self.language_to_service_language(params.language) if params.language else None diff --git a/src/pipecat/services/sambanova/llm.py b/src/pipecat/services/sambanova/llm.py index a77252ff8..3c7d76737 100644 --- a/src/pipecat/services/sambanova/llm.py +++ b/src/pipecat/services/sambanova/llm.py @@ -24,7 +24,6 @@ from pipecat.processors.aggregators.openai_llm_context import OpenAILLMContext from pipecat.services.llm_service import FunctionCallFromLLM from pipecat.services.openai.base_llm import BaseOpenAILLMService from pipecat.services.openai.llm import OpenAILLMService -from pipecat.services.settings import _warn_deprecated_param from pipecat.utils.tracing.service_decorators import traced_llm @@ -73,7 +72,7 @@ class SambaNovaLLMService(OpenAILLMService): # type: ignore # 2. Apply direct init arg overrides (deprecated) if model is not None: - _warn_deprecated_param("model", self.Settings, "model") + self._warn_init_param_moved_to_settings("model", "model") default_settings.model = model # 3. (No step 3, as there's no params object to apply) diff --git a/src/pipecat/services/sambanova/stt.py b/src/pipecat/services/sambanova/stt.py index c42a491e1..d3a77b4eb 100644 --- a/src/pipecat/services/sambanova/stt.py +++ b/src/pipecat/services/sambanova/stt.py @@ -11,7 +11,6 @@ from typing import Any, Optional from loguru import logger -from pipecat.services.settings import _warn_deprecated_param from pipecat.services.stt_latency import SAMBANOVA_TTFS_P99 from pipecat.services.whisper.base_stt import ( BaseWhisperSTTService, @@ -90,16 +89,16 @@ class SambaNovaSTTService(BaseWhisperSTTService): # type: ignore # --- 2. Deprecated direct-arg overrides --- if model is not None: - _warn_deprecated_param("model", self.Settings, "model") + self._warn_init_param_moved_to_settings("model", "model") default_settings.model = model if language is not None: - _warn_deprecated_param("language", self.Settings, "language") + self._warn_init_param_moved_to_settings("language", "language") default_settings.language = self.language_to_service_language(language) if prompt is not None: - _warn_deprecated_param("prompt", self.Settings, "prompt") + self._warn_init_param_moved_to_settings("prompt", "prompt") default_settings.prompt = prompt if temperature is not None: - _warn_deprecated_param("temperature", self.Settings, "temperature") + self._warn_init_param_moved_to_settings("temperature", "temperature") default_settings.temperature = temperature # --- 3. (no params object for this service) --- diff --git a/src/pipecat/services/sarvam/stt.py b/src/pipecat/services/sarvam/stt.py index b2c02f7cd..8d0a38810 100644 --- a/src/pipecat/services/sarvam/stt.py +++ b/src/pipecat/services/sarvam/stt.py @@ -36,7 +36,6 @@ from pipecat.services.settings import ( NOT_GIVEN, STTSettings, _NotGiven, - _warn_deprecated_param, is_given, ) from pipecat.services.stt_latency import SARVAM_TTFS_P99 @@ -255,12 +254,12 @@ class SarvamSTTService(STTService): # --- 2. Deprecated direct-arg overrides --- if model is not None: - _warn_deprecated_param("model", self.Settings, "model") + self._warn_init_param_moved_to_settings("model", "model") default_settings.model = model # --- 3. Deprecated params overrides --- if params is not None: - _warn_deprecated_param("params", self.Settings) + self._warn_init_param_moved_to_settings("params") if not settings: default_settings.language = params.language default_settings.prompt = params.prompt diff --git a/src/pipecat/services/sarvam/tts.py b/src/pipecat/services/sarvam/tts.py index a469dbf33..91ee088cf 100644 --- a/src/pipecat/services/sarvam/tts.py +++ b/src/pipecat/services/sarvam/tts.py @@ -60,7 +60,7 @@ from pipecat.frames.frames import ( ) from pipecat.processors.frame_processor import FrameDirection from pipecat.services.sarvam._sdk import sdk_headers -from pipecat.services.settings import NOT_GIVEN, TTSSettings, _NotGiven, _warn_deprecated_param +from pipecat.services.settings import NOT_GIVEN, TTSSettings, _NotGiven from pipecat.services.tts_service import InterruptibleTTSService, TextAggregationMode, TTSService from pipecat.transcriptions.language import Language, resolve_language from pipecat.utils.tracing.service_decorators import traced_tts @@ -462,15 +462,15 @@ class SarvamHttpTTSService(TTSService): # 2. Apply direct init arg overrides (deprecated) if model is not None: - _warn_deprecated_param("model", self.Settings, "model") + self._warn_init_param_moved_to_settings("model", "model") default_settings.model = model if voice_id is not None: - _warn_deprecated_param("voice_id", self.Settings, "voice") + self._warn_init_param_moved_to_settings("voice_id", "voice") default_settings.voice = voice_id # 3. Apply params overrides — only if settings not provided if params is not None: - _warn_deprecated_param("params", self.Settings) + self._warn_init_param_moved_to_settings("params") if not settings: if params.language is not None: default_settings.language = ( @@ -874,10 +874,10 @@ class SarvamTTSService(InterruptibleTTSService): # 2. Apply direct init arg overrides (deprecated) if model is not None: - _warn_deprecated_param("model", self.Settings, "model") + self._warn_init_param_moved_to_settings("model", "model") default_settings.model = model if voice_id is not None: - _warn_deprecated_param("voice_id", self.Settings, "voice") + self._warn_init_param_moved_to_settings("voice_id", "voice") default_settings.voice = voice_id # Init-only audio format fields (not runtime-updatable) @@ -886,7 +886,7 @@ class SarvamTTSService(InterruptibleTTSService): # 3. Apply params overrides — only if settings not provided if params is not None: - _warn_deprecated_param("params", self.Settings) + self._warn_init_param_moved_to_settings("params") if not settings: if params.language is not None: default_settings.language = ( diff --git a/src/pipecat/services/settings.py b/src/pipecat/services/settings.py index c9a120972..a0bf3cd58 100644 --- a/src/pipecat/services/settings.py +++ b/src/pipecat/services/settings.py @@ -37,7 +37,6 @@ Key helpers: from __future__ import annotations import copy -import warnings from dataclasses import dataclass, field, fields from typing import TYPE_CHECKING, Any, ClassVar, Dict, Mapping, Optional, Type, TypeVar @@ -49,45 +48,6 @@ if TYPE_CHECKING: from pipecat.turns.user_turn_completion_mixin import UserTurnCompletionConfig -# --------------------------------------------------------------------------- -# Deprecation helper -# --------------------------------------------------------------------------- - - -def _warn_deprecated_param( - param_name: str, - settings_class: type, - settings_field: str | None = None, - stacklevel: int = 3, -): - """Emit DeprecationWarning for a deprecated init parameter. - - Args: - param_name: Name of the deprecated parameter. - settings_class: The settings class to use instead. - settings_field: Specific field on the settings class, if different - from *param_name*. - stacklevel: Stack depth for the warning. Default ``3`` targets - the caller's caller (i.e. user code that instantiated the service). - """ - settings_class_name = settings_class.__name__ - if settings_field: - msg = ( - f"The `{param_name}` parameter is deprecated. " - f"Use `settings={settings_class_name}({settings_field}=...)` instead. " - f"If both are provided, `settings` takes precedence." - ) - else: - msg = ( - f"The `{param_name}` parameter is deprecated. " - f"Use `settings={settings_class_name}(...)` instead. " - f"If both are provided, `settings` takes precedence." - ) - with warnings.catch_warnings(): - warnings.simplefilter("always") - warnings.warn(msg, DeprecationWarning, stacklevel=stacklevel) - - # --------------------------------------------------------------------------- # NOT_GIVEN sentinel # --------------------------------------------------------------------------- diff --git a/src/pipecat/services/soniox/stt.py b/src/pipecat/services/soniox/stt.py index abf42dcdc..f123d850c 100644 --- a/src/pipecat/services/soniox/stt.py +++ b/src/pipecat/services/soniox/stt.py @@ -24,7 +24,7 @@ from pipecat.frames.frames import ( VADUserStoppedSpeakingFrame, ) from pipecat.processors.frame_processor import FrameDirection -from pipecat.services.settings import NOT_GIVEN, STTSettings, _NotGiven, _warn_deprecated_param +from pipecat.services.settings import NOT_GIVEN, STTSettings, _NotGiven from pipecat.services.stt_latency import SONIOX_TTFS_P99 from pipecat.services.stt_service import WebsocketSTTService from pipecat.transcriptions.language import Language @@ -233,12 +233,12 @@ class SonioxSTTService(WebsocketSTTService): # --- 2. Deprecated direct-arg overrides --- if model is not None: - _warn_deprecated_param("model", self.Settings, "model") + self._warn_init_param_moved_to_settings("model", "model") default_settings.model = model # --- 3. Deprecated params overrides --- if params is not None: - _warn_deprecated_param("params", self.Settings) + self._warn_init_param_moved_to_settings("params") if not settings: default_settings.model = params.model if params.audio_format is not None: diff --git a/src/pipecat/services/speechmatics/stt.py b/src/pipecat/services/speechmatics/stt.py index 2a54b2b08..ae8e35850 100644 --- a/src/pipecat/services/speechmatics/stt.py +++ b/src/pipecat/services/speechmatics/stt.py @@ -33,7 +33,7 @@ from pipecat.frames.frames import ( VADUserStoppedSpeakingFrame, ) from pipecat.processors.frame_processor import FrameDirection -from pipecat.services.settings import NOT_GIVEN, STTSettings, _NotGiven, _warn_deprecated_param +from pipecat.services.settings import NOT_GIVEN, STTSettings, _NotGiven from pipecat.services.stt_latency import SPEECHMATICS_TTFS_P99 from pipecat.services.stt_service import STTService from pipecat.transcriptions.language import Language, resolve_language @@ -454,7 +454,7 @@ class SpeechmaticsSTTService(STTService): # --- 3. Deprecated params overrides --- if params is not None: - _warn_deprecated_param("params", self.Settings) + self._warn_init_param_moved_to_settings("params") if not settings: default_settings.language = _params.language default_settings.domain = _params.domain diff --git a/src/pipecat/services/speechmatics/tts.py b/src/pipecat/services/speechmatics/tts.py index 243437cb3..64f64378a 100644 --- a/src/pipecat/services/speechmatics/tts.py +++ b/src/pipecat/services/speechmatics/tts.py @@ -20,7 +20,7 @@ from pipecat.frames.frames import ( Frame, TTSAudioRawFrame, ) -from pipecat.services.settings import NOT_GIVEN, TTSSettings, _NotGiven, _warn_deprecated_param +from pipecat.services.settings import NOT_GIVEN, TTSSettings, _NotGiven from pipecat.services.tts_service import TTSService from pipecat.utils.network import exponential_backoff_time from pipecat.utils.tracing.service_decorators import traced_tts @@ -119,12 +119,12 @@ class SpeechmaticsTTSService(TTSService): # 2. Apply direct init arg overrides (deprecated) if voice_id is not None: - _warn_deprecated_param("voice_id", self.Settings, "voice") + self._warn_init_param_moved_to_settings("voice_id", "voice") default_settings.voice = voice_id # 3. Apply params overrides — only if settings not provided if params is not None: - _warn_deprecated_param("params", self.Settings) + self._warn_init_param_moved_to_settings("params") if not settings: default_settings.max_retries = params.max_retries diff --git a/src/pipecat/services/together/llm.py b/src/pipecat/services/together/llm.py index b1eb83d26..4ec2f8244 100644 --- a/src/pipecat/services/together/llm.py +++ b/src/pipecat/services/together/llm.py @@ -13,7 +13,6 @@ from loguru import logger from pipecat.services.openai.base_llm import BaseOpenAILLMService from pipecat.services.openai.llm import OpenAILLMService -from pipecat.services.settings import _warn_deprecated_param @dataclass @@ -61,7 +60,7 @@ class TogetherLLMService(OpenAILLMService): # 2. Apply direct init arg overrides (deprecated) if model is not None: - _warn_deprecated_param("model", self.Settings, "model") + self._warn_init_param_moved_to_settings("model", "model") default_settings.model = model # 3. (No step 3, as there's no params object to apply) diff --git a/src/pipecat/services/whisper/base_stt.py b/src/pipecat/services/whisper/base_stt.py index d045eafc7..93bb5de34 100644 --- a/src/pipecat/services/whisper/base_stt.py +++ b/src/pipecat/services/whisper/base_stt.py @@ -18,7 +18,7 @@ from openai import AsyncOpenAI from openai.types.audio import Transcription from pipecat.frames.frames import ErrorFrame, Frame, TranscriptionFrame -from pipecat.services.settings import NOT_GIVEN, STTSettings, _NotGiven, _warn_deprecated_param +from pipecat.services.settings import NOT_GIVEN, STTSettings, _NotGiven from pipecat.services.stt_latency import WHISPER_TTFS_P99 from pipecat.services.stt_service import SegmentedSTTService from pipecat.transcriptions.language import Language, resolve_language @@ -190,16 +190,16 @@ class BaseWhisperSTTService(SegmentedSTTService): # --- 2. Deprecated direct-arg overrides --- if model is not None: - _warn_deprecated_param("model", self.Settings, "model") + self._warn_init_param_moved_to_settings("model", "model") default_settings.model = model if language is not None: - _warn_deprecated_param("language", self.Settings, "language") + self._warn_init_param_moved_to_settings("language", "language") default_settings.language = self.language_to_service_language(language) if prompt is not None: - _warn_deprecated_param("prompt", self.Settings, "prompt") + self._warn_init_param_moved_to_settings("prompt", "prompt") default_settings.prompt = prompt if temperature is not None: - _warn_deprecated_param("temperature", self.Settings, "temperature") + self._warn_init_param_moved_to_settings("temperature", "temperature") default_settings.temperature = temperature # --- 3. (no params object for this service) --- diff --git a/src/pipecat/services/whisper/stt.py b/src/pipecat/services/whisper/stt.py index 29574007a..ac5d90c30 100644 --- a/src/pipecat/services/whisper/stt.py +++ b/src/pipecat/services/whisper/stt.py @@ -20,7 +20,7 @@ from loguru import logger from typing_extensions import TYPE_CHECKING, override from pipecat.frames.frames import ErrorFrame, Frame, TranscriptionFrame -from pipecat.services.settings import NOT_GIVEN, STTSettings, _NotGiven, _warn_deprecated_param +from pipecat.services.settings import NOT_GIVEN, STTSettings, _NotGiven from pipecat.services.stt_service import SegmentedSTTService from pipecat.transcriptions.language import Language, resolve_language from pipecat.utils.time import time_now_iso8601 @@ -256,13 +256,13 @@ class WhisperSTTService(SegmentedSTTService): # --- 2. Deprecated direct-arg overrides --- if model is not None: - _warn_deprecated_param("model", self.Settings, "model") + self._warn_init_param_moved_to_settings("model", "model") default_settings.model = model if isinstance(model, str) else model.value if no_speech_prob is not None: - _warn_deprecated_param("no_speech_prob", self.Settings, "no_speech_prob") + self._warn_init_param_moved_to_settings("no_speech_prob", "no_speech_prob") default_settings.no_speech_prob = no_speech_prob if language is not None: - _warn_deprecated_param("language", self.Settings, "language") + self._warn_init_param_moved_to_settings("language", "language") default_settings.language = language # --- 3. (no params object for this service) --- @@ -432,16 +432,16 @@ class WhisperSTTServiceMLX(WhisperSTTService): # --- 2. Deprecated direct-arg overrides --- if model is not None: - _warn_deprecated_param("model", self.Settings, "model") + self._warn_init_param_moved_to_settings("model", "model") default_settings.model = model if isinstance(model, str) else model.value if no_speech_prob is not None: - _warn_deprecated_param("no_speech_prob", self.Settings, "no_speech_prob") + self._warn_init_param_moved_to_settings("no_speech_prob", "no_speech_prob") default_settings.no_speech_prob = no_speech_prob if language is not None: - _warn_deprecated_param("language", self.Settings, "language") + self._warn_init_param_moved_to_settings("language", "language") default_settings.language = language if temperature is not None: - _warn_deprecated_param("temperature", self.Settings, "temperature") + self._warn_init_param_moved_to_settings("temperature", "temperature") default_settings.temperature = temperature # --- 3. (no params object for this service) --- diff --git a/src/pipecat/services/xtts/tts.py b/src/pipecat/services/xtts/tts.py index b769742f3..099fce65c 100644 --- a/src/pipecat/services/xtts/tts.py +++ b/src/pipecat/services/xtts/tts.py @@ -23,7 +23,7 @@ from pipecat.frames.frames import ( StartFrame, TTSAudioRawFrame, ) -from pipecat.services.settings import TTSSettings, _warn_deprecated_param +from pipecat.services.settings import TTSSettings from pipecat.services.tts_service import TTSService from pipecat.transcriptions.language import Language, resolve_language from pipecat.utils.tracing.service_decorators import traced_tts @@ -122,7 +122,7 @@ class XTTSService(TTSService): # 2. Apply direct init arg overrides (deprecated) if voice_id is not None: - _warn_deprecated_param("voice_id", self.Settings, "voice") + self._warn_init_param_moved_to_settings("voice_id", "voice") default_settings.voice = voice_id # 3. (No step 3, as there's no params object to apply) From a9e124b84f845b02a67637ffccf45db3dde6751a Mon Sep 17 00:00:00 2001 From: Mark Backman Date: Wed, 11 Mar 2026 14:17:40 -0400 Subject: [PATCH 0939/1060] Update sarvamai dependency from 0.1.26a2 to 0.1.26 Bump the Sarvam AI SDK to the stable release version. --- pyproject.toml | 2 +- uv.lock | 21 +++++++++++++++++---- 2 files changed, 18 insertions(+), 5 deletions(-) diff --git a/pyproject.toml b/pyproject.toml index d2ff8ec85..48226b14f 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -109,7 +109,7 @@ riva = [ "pipecat-ai[nvidia]" ] runner = [ "python-dotenv>=1.0.0,<2.0.0", "uvicorn>=0.32.0,<1.0.0", "fastapi>=0.115.6,<1", "pipecat-ai-small-webrtc-prebuilt>=2.3.0"] sagemaker = ["aws_sdk_sagemaker_runtime_http2; python_version>='3.12'"] sambanova = [] -sarvam = [ "sarvamai==0.1.26a2", "pipecat-ai[websockets-base]" ] +sarvam = [ "sarvamai==0.1.26", "pipecat-ai[websockets-base]" ] sentry = [ "sentry-sdk>=2.28.0,<3" ] silero = [] simli 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create mode 100644 changelog/3997.changed.md diff --git a/changelog/3997.changed.md b/changelog/3997.changed.md new file mode 100644 index 000000000..7d626a5fe --- /dev/null +++ b/changelog/3997.changed.md @@ -0,0 +1 @@ +- Updated `sarvamai` dependency from `0.1.26a2` (alpha) to `0.1.26` (stable release). From 080ed22ff5cf1caaf53625f884386ec4d2c17e9c Mon Sep 17 00:00:00 2001 From: Paul Kompfner Date: Wed, 11 Mar 2026 15:44:05 -0400 Subject: [PATCH 0941/1060] Override CambTTSSettings.voice type from str to int to match Camb.ai's integer voice IDs --- examples/foundational/55zf-update-settings-camb-tts.py | 6 ++++-- src/pipecat/services/camb/tts.py | 3 +++ 2 files changed, 7 insertions(+), 2 deletions(-) diff --git a/examples/foundational/55zf-update-settings-camb-tts.py b/examples/foundational/55zf-update-settings-camb-tts.py index 5f0840857..37b845ab4 100644 --- a/examples/foundational/55zf-update-settings-camb-tts.py +++ b/examples/foundational/55zf-update-settings-camb-tts.py @@ -96,9 +96,11 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): await task.queue_frames([LLMRunFrame()]) await asyncio.sleep(10) - logger.info("Updating Camb TTS settings: language -> Spanish") + logger.info("Updating Camb TTS settings: language -> Spanish, voice -> Pirate Captain") await task.queue_frame( - TTSUpdateSettingsFrame(delta=CambTTSService.Settings(language=Language.ES)) + TTSUpdateSettingsFrame( + delta=CambTTSService.Settings(language=Language.ES, voice=147319) + ) ) @transport.event_handler("on_client_disconnected") diff --git a/src/pipecat/services/camb/tts.py b/src/pipecat/services/camb/tts.py index b0c237165..9c360ed37 100644 --- a/src/pipecat/services/camb/tts.py +++ b/src/pipecat/services/camb/tts.py @@ -138,10 +138,13 @@ class CambTTSSettings(TTSSettings): """Settings for CambTTSService. Parameters: + voice: Camb.ai voice ID. Overrides ``TTSSettings.voice`` (str) because + Camb.ai uses integer voice IDs. user_instructions: Custom instructions for mars-instruct model only. Ignored for other models. Max 1000 characters. """ + voice: int | _NotGiven = field(default_factory=lambda: NOT_GIVEN) user_instructions: str | None | _NotGiven = field(default_factory=lambda: NOT_GIVEN) From 4a45145cbaf379e1aedeb1ca1acb902d8a3ec045 Mon Sep 17 00:00:00 2001 From: Mark Backman Date: Wed, 11 Mar 2026 15:51:09 -0400 Subject: [PATCH 0942/1060] Restored the default model to gpt-4.1 for OpenAI and Azure LLM services The default model for OpenAILLMService and AzureLLMService was still set to gpt-4o. Restored it to gpt-4.1. Also, removed hardcoded gpt-4o/gpt-4o-mini model references from examples so they pick up the new default. --- changelog/4000.fixed.md | 1 + examples/foundational/04a-transports-daily.py | 1 - examples/foundational/14v-function-calling-openai.py | 1 - examples/foundational/27-simli-layer.py | 1 - examples/foundational/35-pattern-pair-voice-switching.py | 2 +- examples/foundational/37-mem0.py | 3 +-- src/pipecat/services/azure/llm.py | 4 ++-- src/pipecat/services/openai/base_llm.py | 2 +- 8 files changed, 6 insertions(+), 9 deletions(-) create mode 100644 changelog/4000.fixed.md diff --git a/changelog/4000.fixed.md b/changelog/4000.fixed.md new file mode 100644 index 000000000..871d71135 --- /dev/null +++ b/changelog/4000.fixed.md @@ -0,0 +1 @@ +- Fixed an issue where the default model for `OpenAILLMService` and `AzureLLMService` was mistakenly reverted to `gpt-4o`. The defaults are now restored to `gpt-4.1`. diff --git a/examples/foundational/04a-transports-daily.py b/examples/foundational/04a-transports-daily.py index ab986c22f..b73b7bdfe 100644 --- a/examples/foundational/04a-transports-daily.py +++ b/examples/foundational/04a-transports-daily.py @@ -58,7 +58,6 @@ async def main(): llm = OpenAILLMService( api_key=os.getenv("OPENAI_API_KEY"), settings=OpenAILLMService.Settings( - model="gpt-4o", system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", ), ) diff --git a/examples/foundational/14v-function-calling-openai.py b/examples/foundational/14v-function-calling-openai.py index 639d9bd23..db759b186 100644 --- a/examples/foundational/14v-function-calling-openai.py +++ b/examples/foundational/14v-function-calling-openai.py @@ -79,7 +79,6 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): instructions="Please speak clearly and at a moderate pace.", ) - # model choices: gpt-4o, gpt-4.1, etc. llm = OpenAILLMService( api_key=os.getenv("OPENAI_API_KEY"), settings=OpenAILLMService.Settings( diff --git a/examples/foundational/27-simli-layer.py b/examples/foundational/27-simli-layer.py index c8a9ad663..b2cbb6837 100644 --- a/examples/foundational/27-simli-layer.py +++ b/examples/foundational/27-simli-layer.py @@ -73,7 +73,6 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): llm = OpenAILLMService( api_key=os.getenv("OPENAI_API_KEY"), settings=OpenAILLMService.Settings( - model="gpt-4o-mini", system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", ), ) diff --git a/examples/foundational/35-pattern-pair-voice-switching.py b/examples/foundational/35-pattern-pair-voice-switching.py index ed9bb3973..c246ce599 100644 --- a/examples/foundational/35-pattern-pair-voice-switching.py +++ b/examples/foundational/35-pattern-pair-voice-switching.py @@ -24,7 +24,7 @@ The PatternPairAggregator: - Returns processed text at sentence boundaries Requirements: - - OpenAI API key (for GPT-4o) + - OpenAI API key - Cartesia API key (for text-to-speech) - Daily API key (for video/audio transport) diff --git a/examples/foundational/37-mem0.py b/examples/foundational/37-mem0.py index 06883a43e..e572d2dbe 100644 --- a/examples/foundational/37-mem0.py +++ b/examples/foundational/37-mem0.py @@ -24,7 +24,7 @@ Example usage (run from pipecat root directory): $ python examples/foundational/37-mem0.py Requirements: - - OpenAI API key (for GPT-4o-mini) + - OpenAI API key - ElevenLabs API key (for text-to-speech) - Daily API key (for video/audio transport) - Mem0 API key (for cloud-based memory storage) @@ -226,7 +226,6 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): llm = OpenAILLMService( api_key=os.getenv("OPENAI_API_KEY"), settings=OpenAILLMService.Settings( - model="gpt-4o-mini", system_instruction="""You are a personal assistant. You can remember things about the person you are talking to. Some Guidelines: - Make sure your responses are friendly yet short and concise. diff --git a/src/pipecat/services/azure/llm.py b/src/pipecat/services/azure/llm.py index ea705eec6..8b5050e5b 100644 --- a/src/pipecat/services/azure/llm.py +++ b/src/pipecat/services/azure/llm.py @@ -47,7 +47,7 @@ class AzureLLMService(OpenAILLMService): Args: api_key: The API key for accessing Azure OpenAI. endpoint: The Azure endpoint URL. - model: The model identifier to use. Defaults to "gpt-4o". + model: The model identifier to use. Defaults to "gpt-4.1". .. deprecated:: 0.0.105 Use ``settings=AzureLLMService.Settings(model=...)`` instead. @@ -58,7 +58,7 @@ class AzureLLMService(OpenAILLMService): **kwargs: Additional keyword arguments passed to OpenAILLMService. """ # 1. Initialize default_settings with hardcoded defaults - default_settings = self.Settings(model="gpt-4o") + default_settings = self.Settings(model="gpt-4.1") # 2. Apply direct init arg overrides (deprecated) if model is not None: diff --git a/src/pipecat/services/openai/base_llm.py b/src/pipecat/services/openai/base_llm.py index d1d695ef6..41b26bd20 100644 --- a/src/pipecat/services/openai/base_llm.py +++ b/src/pipecat/services/openai/base_llm.py @@ -151,7 +151,7 @@ class BaseOpenAILLMService(LLMService): """ # 1. Initialize default_settings with hardcoded defaults default_settings = self.Settings( - model="gpt-4o", + model="gpt-4.1", system_instruction=None, frequency_penalty=NOT_GIVEN, presence_penalty=NOT_GIVEN, From a54aa2d1f879990826a99b3adaf1fddb1cf40322 Mon Sep 17 00:00:00 2001 From: Mark Backman Date: Wed, 11 Mar 2026 16:56:41 -0400 Subject: [PATCH 0943/1060] Migrate SimliVideoService to AIService with Settings pattern Align Simli with HeyGen/Tavus by extending AIService instead of FrameProcessor and using a ServiceSettings dataclass. InputParams is preserved but deprecated; its fields are promoted to direct init params. Lifecycle handling moves to start()/stop()/cancel() methods. --- src/pipecat/services/simli/video.py | 105 +++++++++++++++++++++++----- 1 file changed, 86 insertions(+), 19 deletions(-) diff --git a/src/pipecat/services/simli/video.py b/src/pipecat/services/simli/video.py index 880b40428..8345c0b86 100644 --- a/src/pipecat/services/simli/video.py +++ b/src/pipecat/services/simli/video.py @@ -8,6 +8,7 @@ import asyncio import warnings +from dataclasses import dataclass from typing import Optional import numpy as np @@ -20,11 +21,14 @@ from pipecat.frames.frames import ( Frame, InterruptionFrame, OutputImageRawFrame, + StartFrame, TTSAudioRawFrame, TTSStoppedFrame, UserStartedSpeakingFrame, ) -from pipecat.processors.frame_processor import FrameDirection, FrameProcessor, StartFrame +from pipecat.processors.frame_processor import FrameDirection +from pipecat.services.ai_service import AIService +from pipecat.services.settings import ServiceSettings try: from av.audio.frame import AudioFrame @@ -36,7 +40,14 @@ except ModuleNotFoundError as e: raise Exception(f"Missing module: {e}") -class SimliVideoService(FrameProcessor): +@dataclass +class SimliVideoSettings(ServiceSettings): + """Settings for the Simli video service.""" + + pass + + +class SimliVideoService(AIService): """Simli video service for real-time avatar generation. Provides real-time avatar video generation by processing audio frames @@ -44,9 +55,15 @@ class SimliVideoService(FrameProcessor): audio resampling, video frame processing, and connection management. """ + Settings = SimliVideoSettings + _settings: Settings + class InputParams(BaseModel): """Input parameters for Simli video configuration. + .. deprecated:: 0.0.105 + Use ``SimliVideoService.Settings(...)`` instead. + Parameters: enable_logging: Whether to enable Simli logging. max_session_length: Absolute maximum session duration in seconds. @@ -66,10 +83,13 @@ class SimliVideoService(FrameProcessor): face_id: Optional[str] = None, simli_config: Optional[SimliConfig] = None, use_turn_server: bool = False, - latency_interval: int = 0, simli_url: str = "https://api.simli.ai", is_trinity_avatar: bool = False, params: Optional[InputParams] = None, + max_session_length: Optional[int] = None, + max_idle_time: Optional[int] = None, + enable_logging: Optional[bool] = None, + settings: Optional[Settings] = None, **kwargs, ): """Initialize the Simli video service. @@ -90,18 +110,42 @@ class SimliVideoService(FrameProcessor): .. deprecated:: 0.0.95 The 'use_turn_server' parameter is deprecated and will be removed in a future version. - latency_interval: Latency interval setting for sending health checks to check - the latency to Simli Servers. Defaults to 0. simli_url: URL of the simli servers. Can be changed for custom deployments of enterprise users. is_trinity_avatar: Boolean to tell simli client that this is a Trinity avatar which reduces latency when using Trinity. params: Additional input parameters for session configuration. - **kwargs: Additional arguments passed to the parent FrameProcessor. - """ - super().__init__(**kwargs) - params = params or SimliVideoService.InputParams() + .. deprecated:: 0.0.105 + Use ``settings=SimliVideoService.Settings(...)`` instead. + + max_session_length: Absolute maximum session duration in seconds. + Avatar will disconnect after this time even if it's speaking. + max_idle_time: Maximum duration in seconds the avatar is not speaking + before the avatar disconnects. + enable_logging: Whether to enable Simli logging. + settings: Service settings. + **kwargs: Additional arguments passed to the parent AIService. + """ + # 1. Default settings + default_settings = ServiceSettings(model=None) + + # 2. Apply deprecated params overrides + if params is not None: + self._warn_init_param_moved_to_settings("params") + if max_session_length is None and hasattr(params, "max_session_length"): + max_session_length = params.max_session_length + if max_idle_time is None and hasattr(params, "max_idle_time"): + max_idle_time = params.max_idle_time + if enable_logging is None and hasattr(params, "enable_logging"): + enable_logging = params.enable_logging + + # 3. Apply settings delta + if settings is not None: + default_settings.apply_update(settings) + + # 4. Call super + super().__init__(settings=default_settings, **kwargs) # Handle deprecated simli_config parameter if simli_config is not None: @@ -133,10 +177,10 @@ class SimliVideoService(FrameProcessor): config_kwargs = { "faceId": face_id, } - if params.max_session_length is not None: - config_kwargs["maxSessionLength"] = params.max_session_length - if params.max_idle_time is not None: - config_kwargs["maxIdleTime"] = params.max_idle_time + if max_session_length is not None: + config_kwargs["maxSessionLength"] = max_session_length + if max_idle_time is not None: + config_kwargs["maxIdleTime"] = max_idle_time config = SimliConfig(**config_kwargs) @@ -168,6 +212,33 @@ class SimliVideoService(FrameProcessor): self._previously_interrupted = is_trinity_avatar self._audio_buffer = bytearray() + async def start(self, frame: StartFrame): + """Start the Simli video service. + + Args: + frame: The start frame containing initialization parameters. + """ + await super().start(frame) + await self._start_connection() + + async def stop(self, frame: EndFrame): + """Stop the Simli video service. + + Args: + frame: The end frame. + """ + await super().stop(frame) + await self._stop_connection() + + async def cancel(self, frame: CancelFrame): + """Cancel the Simli video service. + + Args: + frame: The cancel frame. + """ + await super().cancel(frame) + await self._stop_connection() + async def _start_connection(self): """Start the connection to Simli service and begin processing tasks.""" try: @@ -222,9 +293,7 @@ class SimliVideoService(FrameProcessor): direction: The direction of frame processing. """ await super().process_frame(frame, direction) - if isinstance(frame, StartFrame): - await self._start_connection() - elif isinstance(frame, TTSAudioRawFrame): + if isinstance(frame, TTSAudioRawFrame): # Send audio frame to Simli try: old_frame = AudioFrame.from_ndarray( @@ -268,8 +337,6 @@ class SimliVideoService(FrameProcessor): except Exception as e: await self.push_error(error_msg=f"Error stopping TTS: {e}", exception=e) return - elif isinstance(frame, (EndFrame, CancelFrame)): - await self._stop() elif isinstance(frame, (InterruptionFrame, UserStartedSpeakingFrame)): if not self._previously_interrupted: await self._simli_client.clearBuffer() @@ -277,7 +344,7 @@ class SimliVideoService(FrameProcessor): await self.push_frame(frame, direction) - async def _stop(self): + async def _stop_connection(self): """Stop the Simli client and cancel processing tasks.""" await self._simli_client.stop() if self._audio_task: From 2d9dc2fa1c8c89c155ac4404fad9cd8601ef862d Mon Sep 17 00:00:00 2001 From: Mark Backman Date: Wed, 11 Mar 2026 17:12:59 -0400 Subject: [PATCH 0944/1060] Update quickstart example for 0.0.105 --- examples/quickstart/bot.py | 24 +++++++++++++----------- 1 file changed, 13 insertions(+), 11 deletions(-) diff --git a/examples/quickstart/bot.py b/examples/quickstart/bot.py index fbe27d783..c201edeb3 100644 --- a/examples/quickstart/bot.py +++ b/examples/quickstart/bot.py @@ -63,19 +63,19 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): tts = CartesiaTTSService( api_key=os.getenv("CARTESIA_API_KEY"), - voice_id="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady + settings=CartesiaTTSService.Settings( + voice="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady + ), ) - llm = OpenAILLMService(api_key=os.getenv("OPENAI_API_KEY")) + llm = OpenAILLMService( + api_key=os.getenv("OPENAI_API_KEY"), + settings=OpenAILLMService.Settings( + system_instruction="You are a friendly AI assistant. Respond naturally and keep your answers conversational.", + ), + ) - messages = [ - { - "role": "system", - "content": "You are a friendly AI assistant. Respond naturally and keep your answers conversational.", - }, - ] - - context = LLMContext(messages) + context = LLMContext() user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()), @@ -105,7 +105,9 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): async def on_client_connected(transport, client): logger.info(f"Client connected") # Kick off the conversation. - messages.append({"role": "system", "content": "Say hello and briefly introduce yourself."}) + context.add_message( + {"role": "user", "content": "Say hello and briefly introduce yourself."} + ) await task.queue_frames([LLMRunFrame()]) @transport.event_handler("on_client_disconnected") From e456a6bb233f0e67db800f05aa906f233e2acaeb Mon Sep 17 00:00:00 2001 From: Paul Kompfner Date: Wed, 11 Mar 2026 17:17:40 -0400 Subject: [PATCH 0945/1060] Move away from remaining deprecated `TransportParams.vad_analyzer` usage in example files. Skip updates to deprecated services. --- .../foundational/07zk-interruptible-resemble.py | 8 ++------ examples/foundational/13-whisper-transcription.py | 7 +++---- examples/foundational/13a-whisper-local.py | 5 +++-- examples/foundational/13e-whisper-mlx.py | 9 +++++---- .../foundational/13g-sambanova-transcription.py | 9 +++++---- examples/foundational/13i-soniox-transcription.py | 7 +++---- examples/foundational/13j-azure-transcription.py | 7 +++---- .../foundational/13k-elevenlabs-transcription.py | 12 ++++++------ examples/foundational/13m-openai-transcription.py | 12 ++++++------ examples/foundational/19-openai-realtime.py | 9 +++++---- examples/foundational/19a-azure-realtime.py | 13 ++++++++----- examples/foundational/19b-openai-realtime-text.py | 13 ++++++++----- .../foundational/19c-openai-realtime-live-video.py | 12 ++++++++---- .../20b-persistent-context-openai-realtime.py | 13 ++++++++----- .../20e-persistent-context-aws-nova-sonic.py | 13 ++++++++----- examples/foundational/25-google-audio-in.py | 13 ++++++++----- examples/foundational/40-aws-nova-sonic.py | 9 +++++---- .../55zl-update-settings-azure-realtime.py | 9 +++++---- .../55zl-update-settings-openai-realtime.py | 9 +++++---- .../55zm-update-settings-gemini-live-vertex.py | 13 ++++++++----- .../55zm-update-settings-gemini-live.py | 13 ++++++++----- .../55zn-update-settings-ultravox-realtime.py | 9 +++++---- .../55zo-update-settings-grok-realtime.py | 9 +++++---- 23 files changed, 130 insertions(+), 103 deletions(-) diff --git a/examples/foundational/07zk-interruptible-resemble.py b/examples/foundational/07zk-interruptible-resemble.py index 88bcb724e..a62387815 100644 --- a/examples/foundational/07zk-interruptible-resemble.py +++ b/examples/foundational/07zk-interruptible-resemble.py @@ -30,24 +30,20 @@ from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams load_dotenv(override=True) -# We store functions so objects (e.g. SileroVADAnalyzer) don't get -# instantiated. The function will be called when the desired transport gets -# selected. +# We use lambdas to defer transport parameter creation until the transport +# type is selected at runtime. transport_params = { "daily": lambda: DailyParams( audio_in_enabled=True, audio_out_enabled=True, - vad_analyzer=SileroVADAnalyzer(), ), "twilio": lambda: FastAPIWebsocketParams( audio_in_enabled=True, audio_out_enabled=True, - vad_analyzer=SileroVADAnalyzer(), ), "webrtc": lambda: TransportParams( audio_in_enabled=True, audio_out_enabled=True, - vad_analyzer=SileroVADAnalyzer(), ), } diff --git a/examples/foundational/13-whisper-transcription.py b/examples/foundational/13-whisper-transcription.py index e2f0f61e0..f61cec132 100644 --- a/examples/foundational/13-whisper-transcription.py +++ b/examples/foundational/13-whisper-transcription.py @@ -13,6 +13,7 @@ from pipecat.frames.frames import Frame, TranscriptionFrame from pipecat.pipeline.pipeline import Pipeline from pipecat.pipeline.runner import PipelineRunner from pipecat.pipeline.task import PipelineTask +from pipecat.processors.audio.vad_processor import VADProcessor from pipecat.processors.frame_processor import FrameDirection, FrameProcessor from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport @@ -40,15 +41,12 @@ class TranscriptionLogger(FrameProcessor): transport_params = { "daily": lambda: DailyParams( audio_in_enabled=True, - vad_analyzer=SileroVADAnalyzer(), ), "twilio": lambda: FastAPIWebsocketParams( audio_in_enabled=True, - vad_analyzer=SileroVADAnalyzer(), ), "webrtc": lambda: TransportParams( audio_in_enabled=True, - vad_analyzer=SileroVADAnalyzer(), ), } @@ -59,8 +57,9 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): stt = WhisperSTTService() tl = TranscriptionLogger() + vad_processor = VADProcessor(vad_analyzer=SileroVADAnalyzer()) - pipeline = Pipeline([transport.input(), stt, tl]) + pipeline = Pipeline([transport.input(), vad_processor, stt, tl]) task = PipelineTask( pipeline, diff --git a/examples/foundational/13a-whisper-local.py b/examples/foundational/13a-whisper-local.py index ec9ddb603..0882542fc 100644 --- a/examples/foundational/13a-whisper-local.py +++ b/examples/foundational/13a-whisper-local.py @@ -15,6 +15,7 @@ from pipecat.frames.frames import Frame, TranscriptionFrame from pipecat.pipeline.pipeline import Pipeline from pipecat.pipeline.runner import PipelineRunner from pipecat.pipeline.task import PipelineTask +from pipecat.processors.audio.vad_processor import VADProcessor from pipecat.processors.frame_processor import FrameDirection, FrameProcessor from pipecat.services.whisper.stt import WhisperSTTService from pipecat.transports.local.audio import LocalAudioTransport, LocalAudioTransportParams @@ -40,15 +41,15 @@ async def main(): transport = LocalAudioTransport( LocalAudioTransportParams( audio_in_enabled=True, - vad_analyzer=SileroVADAnalyzer(), ) ) stt = WhisperSTTService() tl = TranscriptionLogger() + vad_processor = VADProcessor(vad_analyzer=SileroVADAnalyzer()) - pipeline = Pipeline([transport.input(), stt, tl]) + pipeline = Pipeline([transport.input(), vad_processor, stt, tl]) task = PipelineTask(pipeline) diff --git a/examples/foundational/13e-whisper-mlx.py b/examples/foundational/13e-whisper-mlx.py index f4721a86a..af7d2d79e 100644 --- a/examples/foundational/13e-whisper-mlx.py +++ b/examples/foundational/13e-whisper-mlx.py @@ -15,6 +15,7 @@ from pipecat.frames.frames import Frame, TranscriptionFrame, UserStoppedSpeaking from pipecat.pipeline.pipeline import Pipeline from pipecat.pipeline.runner import PipelineRunner from pipecat.pipeline.task import PipelineParams, PipelineTask +from pipecat.processors.audio.vad_processor import VADProcessor from pipecat.processors.frame_processor import FrameDirection, FrameProcessor from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport @@ -61,15 +62,12 @@ class TranscriptionLogger(FrameProcessor): transport_params = { "daily": lambda: DailyParams( audio_in_enabled=True, - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=STOP_SECS)), ), "twilio": lambda: FastAPIWebsocketParams( audio_in_enabled=True, - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=STOP_SECS)), ), "webrtc": lambda: TransportParams( audio_in_enabled=True, - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=STOP_SECS)), ), } @@ -84,8 +82,11 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): ) tl = TranscriptionLogger() + vad_processor = VADProcessor( + vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=STOP_SECS)) + ) - pipeline = Pipeline([transport.input(), stt, tl]) + pipeline = Pipeline([transport.input(), vad_processor, stt, tl]) task = PipelineTask( pipeline, diff --git a/examples/foundational/13g-sambanova-transcription.py b/examples/foundational/13g-sambanova-transcription.py index 404c215fd..26e961c5e 100644 --- a/examples/foundational/13g-sambanova-transcription.py +++ b/examples/foundational/13g-sambanova-transcription.py @@ -16,6 +16,7 @@ from pipecat.frames.frames import Frame, TranscriptionFrame, UserStoppedSpeaking from pipecat.pipeline.pipeline import Pipeline from pipecat.pipeline.runner import PipelineRunner from pipecat.pipeline.task import PipelineParams, PipelineTask +from pipecat.processors.audio.vad_processor import VADProcessor from pipecat.processors.frame_processor import FrameDirection, FrameProcessor from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport @@ -62,15 +63,12 @@ class TranscriptionLogger(FrameProcessor): transport_params = { "daily": lambda: DailyParams( audio_in_enabled=True, - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=STOP_SECS)), ), "twilio": lambda: FastAPIWebsocketParams( audio_in_enabled=True, - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=STOP_SECS)), ), "webrtc": lambda: TransportParams( audio_in_enabled=True, - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=STOP_SECS)), ), } @@ -86,8 +84,11 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): ) tl = TranscriptionLogger() + vad_processor = VADProcessor( + vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=STOP_SECS)) + ) - pipeline = Pipeline([transport.input(), stt, tl]) + pipeline = Pipeline([transport.input(), vad_processor, stt, tl]) task = PipelineTask( pipeline, diff --git a/examples/foundational/13i-soniox-transcription.py b/examples/foundational/13i-soniox-transcription.py index d8d46dfc3..9476e9441 100644 --- a/examples/foundational/13i-soniox-transcription.py +++ b/examples/foundational/13i-soniox-transcription.py @@ -14,6 +14,7 @@ from pipecat.frames.frames import Frame, TranscriptionFrame from pipecat.pipeline.pipeline import Pipeline from pipecat.pipeline.runner import PipelineRunner from pipecat.pipeline.task import PipelineTask +from pipecat.processors.audio.vad_processor import VADProcessor from pipecat.processors.frame_processor import FrameDirection, FrameProcessor from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport @@ -39,15 +40,12 @@ class TranscriptionLogger(FrameProcessor): transport_params = { "daily": lambda: DailyParams( audio_in_enabled=True, - vad_analyzer=SileroVADAnalyzer(), ), "twilio": lambda: FastAPIWebsocketParams( audio_in_enabled=True, - vad_analyzer=SileroVADAnalyzer(), ), "webrtc": lambda: TransportParams( audio_in_enabled=True, - vad_analyzer=SileroVADAnalyzer(), ), } @@ -60,8 +58,9 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): ) tl = TranscriptionLogger() + vad_processor = VADProcessor(vad_analyzer=SileroVADAnalyzer()) - pipeline = Pipeline([transport.input(), stt, tl]) + pipeline = Pipeline([transport.input(), vad_processor, stt, tl]) task = PipelineTask( pipeline, diff --git a/examples/foundational/13j-azure-transcription.py b/examples/foundational/13j-azure-transcription.py index d3df106bd..301c6effd 100644 --- a/examples/foundational/13j-azure-transcription.py +++ b/examples/foundational/13j-azure-transcription.py @@ -14,6 +14,7 @@ from pipecat.frames.frames import Frame, TranscriptionFrame from pipecat.pipeline.pipeline import Pipeline from pipecat.pipeline.runner import PipelineRunner from pipecat.pipeline.task import PipelineTask +from pipecat.processors.audio.vad_processor import VADProcessor from pipecat.processors.frame_processor import FrameDirection, FrameProcessor from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport @@ -39,15 +40,12 @@ class TranscriptionLogger(FrameProcessor): transport_params = { "daily": lambda: DailyParams( audio_in_enabled=True, - vad_analyzer=SileroVADAnalyzer(), ), "twilio": lambda: FastAPIWebsocketParams( audio_in_enabled=True, - vad_analyzer=SileroVADAnalyzer(), ), "webrtc": lambda: TransportParams( audio_in_enabled=True, - vad_analyzer=SileroVADAnalyzer(), ), } @@ -61,8 +59,9 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): ) tl = TranscriptionLogger() + vad_processor = VADProcessor(vad_analyzer=SileroVADAnalyzer()) - pipeline = Pipeline([transport.input(), stt, tl]) + pipeline = Pipeline([transport.input(), vad_processor, stt, tl]) task = PipelineTask( pipeline, diff --git a/examples/foundational/13k-elevenlabs-transcription.py b/examples/foundational/13k-elevenlabs-transcription.py index f801944e5..dbfd32ec6 100644 --- a/examples/foundational/13k-elevenlabs-transcription.py +++ b/examples/foundational/13k-elevenlabs-transcription.py @@ -14,6 +14,7 @@ from pipecat.frames.frames import Frame, TranscriptionFrame from pipecat.pipeline.pipeline import Pipeline from pipecat.pipeline.runner import PipelineRunner from pipecat.pipeline.task import PipelineTask +from pipecat.processors.audio.vad_processor import VADProcessor from pipecat.processors.frame_processor import FrameDirection, FrameProcessor from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport @@ -39,11 +40,9 @@ class TranscriptionLogger(FrameProcessor): # We use lambdas to defer transport parameter creation until the transport # type is selected at runtime. transport_params = { - "daily": lambda: DailyParams(audio_in_enabled=True, vad_analyzer=SileroVADAnalyzer()), - "twilio": lambda: FastAPIWebsocketParams( - audio_in_enabled=True, vad_analyzer=SileroVADAnalyzer() - ), - "webrtc": lambda: TransportParams(audio_in_enabled=True, vad_analyzer=SileroVADAnalyzer()), + "daily": lambda: DailyParams(audio_in_enabled=True), + "twilio": lambda: FastAPIWebsocketParams(audio_in_enabled=True), + "webrtc": lambda: TransportParams(audio_in_enabled=True), } @@ -53,8 +52,9 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): stt = ElevenLabsRealtimeSTTService(api_key=os.getenv("ELEVENLABS_API_KEY")) tl = TranscriptionLogger() + vad_processor = VADProcessor(vad_analyzer=SileroVADAnalyzer()) - pipeline = Pipeline([transport.input(), stt, tl]) + pipeline = Pipeline([transport.input(), vad_processor, stt, tl]) task = PipelineTask( pipeline, diff --git a/examples/foundational/13m-openai-transcription.py b/examples/foundational/13m-openai-transcription.py index 0fb595881..cbbf0e13d 100644 --- a/examples/foundational/13m-openai-transcription.py +++ b/examples/foundational/13m-openai-transcription.py @@ -14,6 +14,7 @@ from pipecat.frames.frames import Frame, TranscriptionFrame from pipecat.pipeline.pipeline import Pipeline from pipecat.pipeline.runner import PipelineRunner from pipecat.pipeline.task import PipelineTask +from pipecat.processors.audio.vad_processor import VADProcessor from pipecat.processors.frame_processor import FrameDirection, FrameProcessor from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport @@ -39,11 +40,9 @@ class TranscriptionLogger(FrameProcessor): # We use lambdas to defer transport parameter creation until the transport # type is selected at runtime. transport_params = { - "daily": lambda: DailyParams(audio_in_enabled=True, vad_analyzer=SileroVADAnalyzer()), - "twilio": lambda: FastAPIWebsocketParams( - audio_in_enabled=True, vad_analyzer=SileroVADAnalyzer() - ), - "webrtc": lambda: TransportParams(audio_in_enabled=True, vad_analyzer=SileroVADAnalyzer()), + "daily": lambda: DailyParams(audio_in_enabled=True), + "twilio": lambda: FastAPIWebsocketParams(audio_in_enabled=True), + "webrtc": lambda: TransportParams(audio_in_enabled=True), } @@ -59,8 +58,9 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): ) tl = TranscriptionLogger() + vad_processor = VADProcessor(vad_analyzer=SileroVADAnalyzer()) - pipeline = Pipeline([transport.input(), stt, tl]) + pipeline = Pipeline([transport.input(), vad_processor, stt, tl]) task = PipelineTask( pipeline, diff --git a/examples/foundational/19-openai-realtime.py b/examples/foundational/19-openai-realtime.py index 8eeea9e02..cb3abf953 100644 --- a/examples/foundational/19-openai-realtime.py +++ b/examples/foundational/19-openai-realtime.py @@ -24,6 +24,7 @@ from pipecat.processors.aggregators.llm_context import LLMContext from pipecat.processors.aggregators.llm_response_universal import ( AssistantTurnStoppedMessage, LLMContextAggregatorPair, + LLMUserAggregatorParams, UserTurnStoppedMessage, ) from pipecat.runner.types import RunnerArguments @@ -119,17 +120,14 @@ transport_params = { "daily": lambda: DailyParams( audio_in_enabled=True, audio_out_enabled=True, - vad_analyzer=SileroVADAnalyzer(), ), "twilio": lambda: FastAPIWebsocketParams( audio_in_enabled=True, audio_out_enabled=True, - vad_analyzer=SileroVADAnalyzer(), ), "webrtc": lambda: TransportParams( audio_in_enabled=True, audio_out_enabled=True, - vad_analyzer=SileroVADAnalyzer(), ), } @@ -187,7 +185,10 @@ Remember, your responses should be short. Just one or two sentences, usually. Re tools, ) - user_aggregator, assistant_aggregator = LLMContextAggregatorPair(context) + user_aggregator, assistant_aggregator = LLMContextAggregatorPair( + context, + user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()), + ) pipeline = Pipeline( [ diff --git a/examples/foundational/19a-azure-realtime.py b/examples/foundational/19a-azure-realtime.py index c98dc167a..ffba20f5d 100644 --- a/examples/foundational/19a-azure-realtime.py +++ b/examples/foundational/19a-azure-realtime.py @@ -19,7 +19,10 @@ from pipecat.pipeline.pipeline import Pipeline from pipecat.pipeline.runner import PipelineRunner from pipecat.pipeline.task import PipelineParams, PipelineTask from pipecat.processors.aggregators.llm_context import LLMContext -from pipecat.processors.aggregators.llm_response_universal import LLMContextAggregatorPair +from pipecat.processors.aggregators.llm_response_universal import ( + LLMContextAggregatorPair, + LLMUserAggregatorParams, +) from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport from pipecat.services.azure.realtime.llm import AzureRealtimeLLMService @@ -93,17 +96,14 @@ transport_params = { "daily": lambda: DailyParams( audio_in_enabled=True, audio_out_enabled=True, - vad_analyzer=SileroVADAnalyzer(), ), "twilio": lambda: FastAPIWebsocketParams( audio_in_enabled=True, audio_out_enabled=True, - vad_analyzer=SileroVADAnalyzer(), ), "webrtc": lambda: TransportParams( audio_in_enabled=True, audio_out_enabled=True, - vad_analyzer=SileroVADAnalyzer(), ), } @@ -172,7 +172,10 @@ Remember, your responses should be short. Just one or two sentences, usually. Re tools, ) - user_aggregator, assistant_aggregator = LLMContextAggregatorPair(context) + user_aggregator, assistant_aggregator = LLMContextAggregatorPair( + context, + user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()), + ) pipeline = Pipeline( [ diff --git a/examples/foundational/19b-openai-realtime-text.py b/examples/foundational/19b-openai-realtime-text.py index deb50e805..1fa6ea545 100644 --- a/examples/foundational/19b-openai-realtime-text.py +++ b/examples/foundational/19b-openai-realtime-text.py @@ -19,7 +19,10 @@ from pipecat.pipeline.pipeline import Pipeline from pipecat.pipeline.runner import PipelineRunner from pipecat.pipeline.task import PipelineParams, PipelineTask from pipecat.processors.aggregators.llm_context import LLMContext -from pipecat.processors.aggregators.llm_response_universal import LLMContextAggregatorPair +from pipecat.processors.aggregators.llm_response_universal import ( + LLMContextAggregatorPair, + LLMUserAggregatorParams, +) from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport from pipecat.services.cartesia.tts import CartesiaTTSService @@ -98,17 +101,14 @@ transport_params = { "daily": lambda: DailyParams( audio_in_enabled=True, audio_out_enabled=True, - vad_analyzer=SileroVADAnalyzer(), ), "twilio": lambda: FastAPIWebsocketParams( audio_in_enabled=True, audio_out_enabled=True, - vad_analyzer=SileroVADAnalyzer(), ), "webrtc": lambda: TransportParams( audio_in_enabled=True, audio_out_enabled=True, - vad_analyzer=SileroVADAnalyzer(), ), } @@ -175,7 +175,10 @@ Remember, your responses should be short. Just one or two sentences, usually. Re tools, ) - user_aggregator, assistant_aggregator = LLMContextAggregatorPair(context) + user_aggregator, assistant_aggregator = LLMContextAggregatorPair( + context, + user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()), + ) pipeline = Pipeline( [ diff --git a/examples/foundational/19c-openai-realtime-live-video.py b/examples/foundational/19c-openai-realtime-live-video.py index 3038a57bc..f862b5511 100644 --- a/examples/foundational/19c-openai-realtime-live-video.py +++ b/examples/foundational/19c-openai-realtime-live-video.py @@ -17,7 +17,10 @@ from pipecat.pipeline.pipeline import Pipeline from pipecat.pipeline.runner import PipelineRunner from pipecat.pipeline.task import PipelineParams, PipelineTask from pipecat.processors.aggregators.llm_context import LLMContext -from pipecat.processors.aggregators.llm_response_universal import LLMContextAggregatorPair +from pipecat.processors.aggregators.llm_response_universal import ( + LLMContextAggregatorPair, + LLMUserAggregatorParams, +) from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import ( create_transport, @@ -46,13 +49,11 @@ transport_params = { audio_in_enabled=True, audio_out_enabled=True, video_in_enabled=True, - vad_analyzer=SileroVADAnalyzer(), ), "webrtc": lambda: TransportParams( audio_in_enabled=True, audio_out_enabled=True, video_in_enabled=True, - vad_analyzer=SileroVADAnalyzer(), ), } @@ -103,7 +104,10 @@ Remember, your responses should be short. Just one or two sentences, usually. Re [{"role": "user", "content": "Say hello!"}], ) - user_aggregator, assistant_aggregator = LLMContextAggregatorPair(context) + user_aggregator, assistant_aggregator = LLMContextAggregatorPair( + context, + user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()), + ) pipeline = Pipeline( [ diff --git a/examples/foundational/20b-persistent-context-openai-realtime.py b/examples/foundational/20b-persistent-context-openai-realtime.py index 2b9a8b6bf..de4215ab8 100644 --- a/examples/foundational/20b-persistent-context-openai-realtime.py +++ b/examples/foundational/20b-persistent-context-openai-realtime.py @@ -21,7 +21,10 @@ from pipecat.pipeline.pipeline import Pipeline from pipecat.pipeline.runner import PipelineRunner from pipecat.pipeline.task import PipelineParams, PipelineTask from pipecat.processors.aggregators.llm_context import LLMContext -from pipecat.processors.aggregators.llm_response_universal import LLMContextAggregatorPair +from pipecat.processors.aggregators.llm_response_universal import ( + LLMContextAggregatorPair, + LLMUserAggregatorParams, +) from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport from pipecat.services.deepgram.stt import DeepgramSTTService @@ -153,17 +156,14 @@ transport_params = { "daily": lambda: DailyParams( audio_in_enabled=True, audio_out_enabled=True, - vad_analyzer=SileroVADAnalyzer(), ), "twilio": lambda: FastAPIWebsocketParams( audio_in_enabled=True, audio_out_enabled=True, - vad_analyzer=SileroVADAnalyzer(), ), "webrtc": lambda: TransportParams( audio_in_enabled=True, audio_out_enabled=True, - vad_analyzer=SileroVADAnalyzer(), ), } @@ -214,7 +214,10 @@ Remember, your responses should be short. Just one or two sentences, usually.""" llm.register_function("load_conversation", load_conversation) context = LLMContext([{"role": "user", "content": "Say hello!"}], tools) - user_aggregator, assistant_aggregator = LLMContextAggregatorPair(context) + user_aggregator, assistant_aggregator = LLMContextAggregatorPair( + context, + user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()), + ) pipeline = Pipeline( [ diff --git a/examples/foundational/20e-persistent-context-aws-nova-sonic.py b/examples/foundational/20e-persistent-context-aws-nova-sonic.py index 9614328f2..3d1043d18 100644 --- a/examples/foundational/20e-persistent-context-aws-nova-sonic.py +++ b/examples/foundational/20e-persistent-context-aws-nova-sonic.py @@ -21,7 +21,10 @@ from pipecat.pipeline.pipeline import Pipeline from pipecat.pipeline.runner import PipelineRunner from pipecat.pipeline.task import PipelineParams, PipelineTask from pipecat.processors.aggregators.llm_context import LLMContext -from pipecat.processors.aggregators.llm_response_universal import LLMContextAggregatorPair +from pipecat.processors.aggregators.llm_response_universal import ( + LLMContextAggregatorPair, + LLMUserAggregatorParams, +) from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport from pipecat.services.aws.nova_sonic.llm import AWSNovaSonicLLMService @@ -189,17 +192,14 @@ transport_params = { "daily": lambda: DailyParams( audio_in_enabled=True, audio_out_enabled=True, - vad_analyzer=SileroVADAnalyzer(), ), "twilio": lambda: FastAPIWebsocketParams( audio_in_enabled=True, audio_out_enabled=True, - vad_analyzer=SileroVADAnalyzer(), ), "webrtc": lambda: TransportParams( audio_in_enabled=True, audio_out_enabled=True, - vad_analyzer=SileroVADAnalyzer(), ), } @@ -236,7 +236,10 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): llm.register_function("load_conversation", load_conversation) context = LLMContext(tools=tools) - user_aggregator, assistant_aggregator = LLMContextAggregatorPair(context) + user_aggregator, assistant_aggregator = LLMContextAggregatorPair( + context, + user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()), + ) pipeline = Pipeline( [ diff --git a/examples/foundational/25-google-audio-in.py b/examples/foundational/25-google-audio-in.py index 572e0e213..6b549a7fe 100644 --- a/examples/foundational/25-google-audio-in.py +++ b/examples/foundational/25-google-audio-in.py @@ -28,7 +28,10 @@ from pipecat.pipeline.pipeline import Pipeline from pipecat.pipeline.runner import PipelineRunner from pipecat.pipeline.task import PipelineParams, PipelineTask from pipecat.processors.aggregators.llm_context import LLMContext -from pipecat.processors.aggregators.llm_response_universal import LLMContextAggregatorPair +from pipecat.processors.aggregators.llm_response_universal import ( + LLMContextAggregatorPair, + LLMUserAggregatorParams, +) from pipecat.processors.frame_processor import FrameProcessor from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport @@ -270,17 +273,14 @@ transport_params = { "daily": lambda: DailyParams( audio_in_enabled=True, audio_out_enabled=True, - vad_analyzer=SileroVADAnalyzer(), ), "twilio": lambda: FastAPIWebsocketParams( audio_in_enabled=True, audio_out_enabled=True, - vad_analyzer=SileroVADAnalyzer(), ), "webrtc": lambda: TransportParams( audio_in_enabled=True, audio_out_enabled=True, - vad_analyzer=SileroVADAnalyzer(), ), } @@ -324,7 +324,10 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): ] context = LLMContext(messages) - context_aggregator = LLMContextAggregatorPair(context) + context_aggregator = LLMContextAggregatorPair( + context, + user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()), + ) audio_collector = UserAudioCollector(context, context_aggregator.user()) input_transcription_context_filter = InputTranscriptionContextFilter() transcription_frames_emitter = InputTranscriptionFrameEmitter() diff --git a/examples/foundational/40-aws-nova-sonic.py b/examples/foundational/40-aws-nova-sonic.py index 79a3d168c..6f7c745ce 100644 --- a/examples/foundational/40-aws-nova-sonic.py +++ b/examples/foundational/40-aws-nova-sonic.py @@ -24,6 +24,7 @@ from pipecat.processors.aggregators.llm_context import LLMContext from pipecat.processors.aggregators.llm_response_universal import ( AssistantTurnStoppedMessage, LLMContextAggregatorPair, + LLMUserAggregatorParams, UserTurnStoppedMessage, ) from pipecat.runner.types import RunnerArguments @@ -87,17 +88,14 @@ transport_params = { "daily": lambda: DailyParams( audio_in_enabled=True, audio_out_enabled=True, - vad_analyzer=SileroVADAnalyzer(), ), "twilio": lambda: FastAPIWebsocketParams( audio_in_enabled=True, audio_out_enabled=True, - vad_analyzer=SileroVADAnalyzer(), ), "webrtc": lambda: TransportParams( audio_in_enabled=True, audio_out_enabled=True, - vad_analyzer=SileroVADAnalyzer(), ), } @@ -147,7 +145,10 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): # Set up context and context management. context = LLMContext(tools=tools) - user_aggregator, assistant_aggregator = LLMContextAggregatorPair(context) + user_aggregator, assistant_aggregator = LLMContextAggregatorPair( + context, + user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()), + ) # Build the pipeline pipeline = Pipeline( diff --git a/examples/foundational/55zl-update-settings-azure-realtime.py b/examples/foundational/55zl-update-settings-azure-realtime.py index fcfcdcfdd..a977ea60c 100644 --- a/examples/foundational/55zl-update-settings-azure-realtime.py +++ b/examples/foundational/55zl-update-settings-azure-realtime.py @@ -19,6 +19,7 @@ from pipecat.processors.aggregators.llm_context import LLMContext from pipecat.processors.aggregators.llm_response_universal import ( AssistantTurnStoppedMessage, LLMContextAggregatorPair, + LLMUserAggregatorParams, ) from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport @@ -34,17 +35,14 @@ transport_params = { "daily": lambda: DailyParams( audio_in_enabled=True, audio_out_enabled=True, - vad_analyzer=SileroVADAnalyzer(), ), "twilio": lambda: FastAPIWebsocketParams( audio_in_enabled=True, audio_out_enabled=True, - vad_analyzer=SileroVADAnalyzer(), ), "webrtc": lambda: TransportParams( audio_in_enabled=True, audio_out_enabled=True, - vad_analyzer=SileroVADAnalyzer(), ), } @@ -65,7 +63,10 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): ] context = LLMContext(messages) - user_aggregator, assistant_aggregator = LLMContextAggregatorPair(context) + user_aggregator, assistant_aggregator = LLMContextAggregatorPair( + context, + user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()), + ) pipeline = Pipeline( [ diff --git a/examples/foundational/55zl-update-settings-openai-realtime.py b/examples/foundational/55zl-update-settings-openai-realtime.py index 372b1f1e6..9f7281a72 100644 --- a/examples/foundational/55zl-update-settings-openai-realtime.py +++ b/examples/foundational/55zl-update-settings-openai-realtime.py @@ -19,6 +19,7 @@ from pipecat.processors.aggregators.llm_context import LLMContext from pipecat.processors.aggregators.llm_response_universal import ( AssistantTurnStoppedMessage, LLMContextAggregatorPair, + LLMUserAggregatorParams, ) from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport @@ -34,17 +35,14 @@ transport_params = { "daily": lambda: DailyParams( audio_in_enabled=True, audio_out_enabled=True, - vad_analyzer=SileroVADAnalyzer(), ), "twilio": lambda: FastAPIWebsocketParams( audio_in_enabled=True, audio_out_enabled=True, - vad_analyzer=SileroVADAnalyzer(), ), "webrtc": lambda: TransportParams( audio_in_enabled=True, audio_out_enabled=True, - vad_analyzer=SileroVADAnalyzer(), ), } @@ -62,7 +60,10 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): ] context = LLMContext(messages) - user_aggregator, assistant_aggregator = LLMContextAggregatorPair(context) + user_aggregator, assistant_aggregator = LLMContextAggregatorPair( + context, + user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()), + ) pipeline = Pipeline( [ diff --git a/examples/foundational/55zm-update-settings-gemini-live-vertex.py b/examples/foundational/55zm-update-settings-gemini-live-vertex.py index 8ff18e1eb..c6a04347a 100644 --- a/examples/foundational/55zm-update-settings-gemini-live-vertex.py +++ b/examples/foundational/55zm-update-settings-gemini-live-vertex.py @@ -16,7 +16,10 @@ from pipecat.pipeline.pipeline import Pipeline from pipecat.pipeline.runner import PipelineRunner from pipecat.pipeline.task import PipelineParams, PipelineTask from pipecat.processors.aggregators.llm_context import LLMContext -from pipecat.processors.aggregators.llm_response_universal import LLMContextAggregatorPair +from pipecat.processors.aggregators.llm_response_universal import ( + LLMContextAggregatorPair, + LLMUserAggregatorParams, +) from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport from pipecat.services.google.gemini_live.vertex.llm import GeminiLiveVertexLLMService @@ -30,17 +33,14 @@ transport_params = { "daily": lambda: DailyParams( audio_in_enabled=True, audio_out_enabled=True, - vad_analyzer=SileroVADAnalyzer(), ), "twilio": lambda: FastAPIWebsocketParams( audio_in_enabled=True, audio_out_enabled=True, - vad_analyzer=SileroVADAnalyzer(), ), "webrtc": lambda: TransportParams( audio_in_enabled=True, audio_out_enabled=True, - vad_analyzer=SileroVADAnalyzer(), ), } @@ -58,7 +58,10 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): ) context = LLMContext() - user_aggregator, assistant_aggregator = LLMContextAggregatorPair(context) + user_aggregator, assistant_aggregator = LLMContextAggregatorPair( + context, + user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()), + ) pipeline = Pipeline( [ diff --git a/examples/foundational/55zm-update-settings-gemini-live.py b/examples/foundational/55zm-update-settings-gemini-live.py index 0b88c45da..beb7f0c1c 100644 --- a/examples/foundational/55zm-update-settings-gemini-live.py +++ b/examples/foundational/55zm-update-settings-gemini-live.py @@ -16,7 +16,10 @@ from pipecat.pipeline.pipeline import Pipeline from pipecat.pipeline.runner import PipelineRunner from pipecat.pipeline.task import PipelineParams, PipelineTask from pipecat.processors.aggregators.llm_context import LLMContext -from pipecat.processors.aggregators.llm_response_universal import LLMContextAggregatorPair +from pipecat.processors.aggregators.llm_response_universal import ( + LLMContextAggregatorPair, + LLMUserAggregatorParams, +) from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport from pipecat.services.google.gemini_live.llm import GeminiLiveLLMService @@ -30,17 +33,14 @@ transport_params = { "daily": lambda: DailyParams( audio_in_enabled=True, audio_out_enabled=True, - vad_analyzer=SileroVADAnalyzer(), ), "twilio": lambda: FastAPIWebsocketParams( audio_in_enabled=True, audio_out_enabled=True, - vad_analyzer=SileroVADAnalyzer(), ), "webrtc": lambda: TransportParams( audio_in_enabled=True, audio_out_enabled=True, - vad_analyzer=SileroVADAnalyzer(), ), } @@ -56,7 +56,10 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): ) context = LLMContext() - user_aggregator, assistant_aggregator = LLMContextAggregatorPair(context) + user_aggregator, assistant_aggregator = LLMContextAggregatorPair( + context, + user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()), + ) pipeline = Pipeline( [ diff --git a/examples/foundational/55zn-update-settings-ultravox-realtime.py b/examples/foundational/55zn-update-settings-ultravox-realtime.py index 13ce6c1ae..ccf2d2003 100644 --- a/examples/foundational/55zn-update-settings-ultravox-realtime.py +++ b/examples/foundational/55zn-update-settings-ultravox-realtime.py @@ -21,6 +21,7 @@ from pipecat.processors.aggregators.llm_context import LLMContext from pipecat.processors.aggregators.llm_response_universal import ( AssistantTurnStoppedMessage, LLMContextAggregatorPair, + LLMUserAggregatorParams, ) from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport @@ -35,17 +36,14 @@ transport_params = { "daily": lambda: DailyParams( audio_in_enabled=True, audio_out_enabled=True, - vad_analyzer=SileroVADAnalyzer(), ), "twilio": lambda: FastAPIWebsocketParams( audio_in_enabled=True, audio_out_enabled=True, - vad_analyzer=SileroVADAnalyzer(), ), "webrtc": lambda: TransportParams( audio_in_enabled=True, audio_out_enabled=True, - vad_analyzer=SileroVADAnalyzer(), ), } @@ -73,7 +71,10 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): ] context = LLMContext(messages) - user_aggregator, assistant_aggregator = LLMContextAggregatorPair(context) + user_aggregator, assistant_aggregator = LLMContextAggregatorPair( + context, + user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()), + ) pipeline = Pipeline( [ diff --git a/examples/foundational/55zo-update-settings-grok-realtime.py b/examples/foundational/55zo-update-settings-grok-realtime.py index 5ac425de4..60ba18755 100644 --- a/examples/foundational/55zo-update-settings-grok-realtime.py +++ b/examples/foundational/55zo-update-settings-grok-realtime.py @@ -19,6 +19,7 @@ from pipecat.processors.aggregators.llm_context import LLMContext from pipecat.processors.aggregators.llm_response_universal import ( AssistantTurnStoppedMessage, LLMContextAggregatorPair, + LLMUserAggregatorParams, ) from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport @@ -34,17 +35,14 @@ transport_params = { "daily": lambda: DailyParams( audio_in_enabled=True, audio_out_enabled=True, - vad_analyzer=SileroVADAnalyzer(), ), "twilio": lambda: FastAPIWebsocketParams( audio_in_enabled=True, audio_out_enabled=True, - vad_analyzer=SileroVADAnalyzer(), ), "webrtc": lambda: TransportParams( audio_in_enabled=True, audio_out_enabled=True, - vad_analyzer=SileroVADAnalyzer(), ), } @@ -62,7 +60,10 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): ] context = LLMContext(messages) - user_aggregator, assistant_aggregator = LLMContextAggregatorPair(context) + user_aggregator, assistant_aggregator = LLMContextAggregatorPair( + context, + user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()), + ) pipeline = Pipeline( [ From ccc2549c0cebed0ad65a8b13b978b7b7768161b8 Mon Sep 17 00:00:00 2001 From: Paul Kompfner Date: Wed, 11 Mar 2026 17:22:11 -0400 Subject: [PATCH 0946/1060] Broaden the `vad_analyzer` deprecation warning in `BaseInputTransport` to account for use-cases where there is no `LLMUserAggregator` at play --- src/pipecat/transports/base_input.py | 5 +++-- src/pipecat/transports/base_transport.py | 5 +++-- 2 files changed, 6 insertions(+), 4 deletions(-) diff --git a/src/pipecat/transports/base_input.py b/src/pipecat/transports/base_input.py index 1da672ab7..bcd457564 100644 --- a/src/pipecat/transports/base_input.py +++ b/src/pipecat/transports/base_input.py @@ -150,8 +150,9 @@ class BaseInputTransport(FrameProcessor): with warnings.catch_warnings(): warnings.simplefilter("always") warnings.warn( - "Parameter 'vad_analyzer' is deprecated, use `LLMUserAggregator`'s new " - "`vad_analyzer` parameter instead.", + "Parameter 'vad_analyzer' is deprecated. Use `LLMUserAggregator`'s " + "`vad_analyzer` parameter, or `VADProcessor` if no `LLMUserAggregator` " + "is needed.", DeprecationWarning, ) diff --git a/src/pipecat/transports/base_transport.py b/src/pipecat/transports/base_transport.py index 7879976ba..a78e1046c 100644 --- a/src/pipecat/transports/base_transport.py +++ b/src/pipecat/transports/base_transport.py @@ -115,8 +115,9 @@ class TransportParams(BaseModel): vad_analyzer: Voice Activity Detection analyzer instance. .. deprecated:: 0.0.101 - The `vad_analyzer` parameter is deprecated, use `LLMUSerAggregator`'s - new `vad_analyzer` parameter instead. + The `vad_analyzer` parameter is deprecated. Use `LLMUserAggregator`'s + `vad_analyzer` parameter, or `VADProcessor` if no `LLMUserAggregator` + is needed. turn_analyzer: Turn-taking analyzer instance for conversation management. From 9a0568e6fe1e3b5afb56304c3067139fc3d152b3 Mon Sep 17 00:00:00 2001 From: Paul Kompfner Date: Wed, 11 Mar 2026 17:32:39 -0400 Subject: [PATCH 0947/1060] Add changelog for #4003 --- changelog/4003.changed.md | 1 + 1 file changed, 1 insertion(+) create mode 100644 changelog/4003.changed.md diff --git a/changelog/4003.changed.md b/changelog/4003.changed.md new file mode 100644 index 000000000..26269ba68 --- /dev/null +++ b/changelog/4003.changed.md @@ -0,0 +1 @@ +- The `TransportParams.vad_analyzer` deprecation warning now also suggests `VADProcessor` as an alternative for pipelines that don't use an `LLMUserAggregator`. From 69e7677f4f477e39d8c7257443d664e1a0dee089 Mon Sep 17 00:00:00 2001 From: Paul Kompfner Date: Wed, 11 Mar 2026 17:33:20 -0400 Subject: [PATCH 0948/1060] Remove changelog for #4003 --- changelog/4003.changed.md | 1 - 1 file changed, 1 deletion(-) delete mode 100644 changelog/4003.changed.md diff --git a/changelog/4003.changed.md b/changelog/4003.changed.md deleted file mode 100644 index 26269ba68..000000000 --- a/changelog/4003.changed.md +++ /dev/null @@ -1 +0,0 @@ -- The `TransportParams.vad_analyzer` deprecation warning now also suggests `VADProcessor` as an alternative for pipelines that don't use an `LLMUserAggregator`. From 11b14b7857a86b920aeb16dc1b83897695fde2df Mon Sep 17 00:00:00 2001 From: Mark Backman Date: Wed, 11 Mar 2026 17:01:19 -0400 Subject: [PATCH 0949/1060] Add changelog for PR #4001 --- changelog/4001.changed.md | 1 + changelog/4001.deprecated.md | 1 + src/pipecat/services/simli/video.py | 4 ++-- 3 files changed, 4 insertions(+), 2 deletions(-) create mode 100644 changelog/4001.changed.md create mode 100644 changelog/4001.deprecated.md diff --git a/changelog/4001.changed.md b/changelog/4001.changed.md new file mode 100644 index 000000000..1d0d4e4ef --- /dev/null +++ b/changelog/4001.changed.md @@ -0,0 +1 @@ +- `SimliVideoService` now extends `AIService` instead of `FrameProcessor`, aligning it with the HeyGen and Tavus video services. It supports `SimliVideoService.Settings(...)` for configuration and uses `start()`/`stop()`/`cancel()` lifecycle methods. Existing constructor usage (`api_key`, `face_id`, etc.) remains unchanged. diff --git a/changelog/4001.deprecated.md b/changelog/4001.deprecated.md new file mode 100644 index 000000000..749e7eea5 --- /dev/null +++ b/changelog/4001.deprecated.md @@ -0,0 +1 @@ +- `SimliVideoService.InputParams` is deprecated. Use the direct constructor parameters `max_session_length`, `max_idle_time`, and `enable_logging` instead. diff --git a/src/pipecat/services/simli/video.py b/src/pipecat/services/simli/video.py index 8345c0b86..f994ef0dc 100644 --- a/src/pipecat/services/simli/video.py +++ b/src/pipecat/services/simli/video.py @@ -61,7 +61,7 @@ class SimliVideoService(AIService): class InputParams(BaseModel): """Input parameters for Simli video configuration. - .. deprecated:: 0.0.105 + .. deprecated:: 0.0.106 Use ``SimliVideoService.Settings(...)`` instead. Parameters: @@ -116,7 +116,7 @@ class SimliVideoService(AIService): which reduces latency when using Trinity. params: Additional input parameters for session configuration. - .. deprecated:: 0.0.105 + .. deprecated:: 0.0.106 Use ``settings=SimliVideoService.Settings(...)`` instead. max_session_length: Absolute maximum session duration in seconds. From 65e4e365dcc5e451d6ffbc7d89d4686f399604d4 Mon Sep 17 00:00:00 2001 From: Paul Kompfner Date: Wed, 11 Mar 2026 21:32:39 -0400 Subject: [PATCH 0950/1060] Add optional `service` field to `ServiceUpdateSettingsFrame` for targeting a specific service instance When `service` is set and doesn't match, the service forwards the frame instead of consuming it. This allows targeting a specific service when multiple services of the same type exist in the pipeline. --- src/pipecat/frames/frames.py | 5 +++++ src/pipecat/services/llm_service.py | 4 +++- src/pipecat/services/openai_realtime_beta/openai.py | 6 +++++- src/pipecat/services/stt_service.py | 4 +++- src/pipecat/services/tts_service.py | 4 +++- 5 files changed, 19 insertions(+), 4 deletions(-) diff --git a/src/pipecat/frames/frames.py b/src/pipecat/frames/frames.py index 390eb93dd..f58dc957f 100644 --- a/src/pipecat/frames/frames.py +++ b/src/pipecat/frames/frames.py @@ -2154,10 +2154,15 @@ class ServiceUpdateSettingsFrame(ControlFrame, UninterruptibleFrame): delta: :class:`~pipecat.services.settings.ServiceSettings` delta-mode object describing the fields to change. + + service: Optional target service instance. When provided, only that + service will apply the settings; other services will forward the + frame unchanged. """ settings: Mapping[str, Any] = field(default_factory=dict) delta: Optional["ServiceSettings"] = None + service: Optional["FrameProcessor"] = None @dataclass diff --git a/src/pipecat/services/llm_service.py b/src/pipecat/services/llm_service.py index 7944f413a..a479fcfc6 100644 --- a/src/pipecat/services/llm_service.py +++ b/src/pipecat/services/llm_service.py @@ -403,7 +403,9 @@ class LLMService(UserTurnCompletionLLMServiceMixin, AIService): elif isinstance(frame, LLMConfigureOutputFrame): self._skip_tts = frame.skip_tts elif isinstance(frame, LLMUpdateSettingsFrame): - if frame.delta is not None: + if frame.service is not None and frame.service is not self: + await self.push_frame(frame, direction) + elif frame.delta is not None: await self._update_settings(frame.delta) elif frame.settings: # Backward-compatible path: convert legacy dict to settings object. diff --git a/src/pipecat/services/openai_realtime_beta/openai.py b/src/pipecat/services/openai_realtime_beta/openai.py index 0a6315986..cacf8debd 100644 --- a/src/pipecat/services/openai_realtime_beta/openai.py +++ b/src/pipecat/services/openai_realtime_beta/openai.py @@ -386,7 +386,11 @@ class OpenAIRealtimeBetaLLMService(LLMService): # fields, not our Settings fields, so we construct SessionProperties # directly. The frame.delta path falls through to super, which calls # _update_settings → our override handles the rest. - if isinstance(frame, LLMUpdateSettingsFrame) and frame.delta is None: + if ( + isinstance(frame, LLMUpdateSettingsFrame) + and frame.delta is None + and (frame.service is None or frame.service is self) + ): self._session_properties = events.SessionProperties(**frame.settings) await self._send_session_update() await self.push_frame(frame, direction) diff --git a/src/pipecat/services/stt_service.py b/src/pipecat/services/stt_service.py index ebf007f6f..a16aa0eaa 100644 --- a/src/pipecat/services/stt_service.py +++ b/src/pipecat/services/stt_service.py @@ -357,7 +357,9 @@ class STTService(AIService): await self._handle_vad_user_stopped_speaking(frame) await self.push_frame(frame, direction) elif isinstance(frame, STTUpdateSettingsFrame): - if frame.delta is not None: + if frame.service is not None and frame.service is not self: + await self.push_frame(frame, direction) + elif frame.delta is not None: await self._update_settings(frame.delta) elif frame.settings: # Backward-compatible path: convert legacy dict to settings object. diff --git a/src/pipecat/services/tts_service.py b/src/pipecat/services/tts_service.py index da1bcaf87..a79156018 100644 --- a/src/pipecat/services/tts_service.py +++ b/src/pipecat/services/tts_service.py @@ -738,7 +738,9 @@ class TTSService(AIService): self._turn_context_id = saved_turn_context_id self._processing_text = processing_text elif isinstance(frame, TTSUpdateSettingsFrame): - if frame.delta is not None: + if frame.service is not None and frame.service is not self: + await self.push_frame(frame, direction) + elif frame.delta is not None: await self._update_settings(frame.delta) elif frame.settings: # Backward-compatible path: convert legacy dict to settings object. From 36b57252b4d6807e38ddf443343cb579f2239d13 Mon Sep 17 00:00:00 2001 From: Paul Kompfner Date: Wed, 11 Mar 2026 21:47:51 -0400 Subject: [PATCH 0951/1060] Add changelog for PR #4004 --- changelog/4004.added.md | 1 + 1 file changed, 1 insertion(+) create mode 100644 changelog/4004.added.md diff --git a/changelog/4004.added.md b/changelog/4004.added.md new file mode 100644 index 000000000..f0fd28767 --- /dev/null +++ b/changelog/4004.added.md @@ -0,0 +1 @@ +- Added optional `service` field to `ServiceUpdateSettingsFrame` (and its subclasses `LLMUpdateSettingsFrame`, `TTSUpdateSettingsFrame`, `STTUpdateSettingsFrame`) to target a specific service instance. When `service` is set, only the matching service applies the settings; others forward the frame unchanged. This enables updating a single service when multiple services of the same type exist in the pipeline. From 7a7d600985d09f642d80e04fe4853426b7d93399 Mon Sep 17 00:00:00 2001 From: Varun Singh <382354+vr000m@users.noreply.github.com> Date: Wed, 11 Mar 2026 21:50:10 -0700 Subject: [PATCH 0952/1060] Add sip_provider and room_geo parameters to configure() Add convenience parameters to configure() so callers don't need to manually construct DailyRoomProperties/DailyRoomSipParams for common SIP provider and geo configuration. --- src/pipecat/runner/daily.py | 12 ++++++++++++ 1 file changed, 12 insertions(+) diff --git a/src/pipecat/runner/daily.py b/src/pipecat/runner/daily.py index b2090b094..cfb754dfd 100644 --- a/src/pipecat/runner/daily.py +++ b/src/pipecat/runner/daily.py @@ -85,6 +85,8 @@ async def configure( sip_enable_video: Optional[bool] = False, sip_num_endpoints: Optional[int] = 1, sip_codecs: Optional[Dict[str, List[str]]] = None, + sip_provider: Optional[str] = None, + room_geo: Optional[str] = None, room_properties: Optional[DailyRoomProperties] = None, token_properties: Optional["DailyMeetingTokenProperties"] = None, ) -> DailyRoomConfig: @@ -105,6 +107,10 @@ async def configure( sip_num_endpoints: Number of allowed SIP endpoints. sip_codecs: Codecs to support for audio and video. If None, uses Daily defaults. Example: {"audio": ["OPUS"], "video": ["H264"]} + sip_provider: SIP provider name (e.g., "daily"). Only used when + sip_caller_phone is provided and room_properties is not. + room_geo: Daily room geographic region (e.g., "us-east-1"). Only used + when room_properties is not provided. room_properties: Optional DailyRoomProperties to use instead of building from individual parameters. When provided, this overrides room_exp_duration and SIP-related parameters. If not provided, properties are built from the @@ -154,6 +160,8 @@ async def configure( sip_enable_video is not False, sip_num_endpoints != 1, sip_codecs is not None, + sip_provider is not None, + room_geo is not None, ] ) if individual_params_provided: @@ -207,6 +215,9 @@ async def configure( eject_at_room_exp=True, ) + if room_geo: + room_properties.geo = room_geo + # Add SIP configuration if enabled if sip_enabled: sip_params = DailyRoomSipParams( @@ -215,6 +226,7 @@ async def configure( sip_mode="dial-in", num_endpoints=sip_num_endpoints, codecs=sip_codecs, + provider=sip_provider, ) room_properties.sip = sip_params room_properties.enable_dialout = True # Enable outbound calls if needed From bf66ae7e46db3eb384eddbdc17e8bda02a0f81ce Mon Sep 17 00:00:00 2001 From: Mark Backman Date: Thu, 12 Mar 2026 09:22:31 -0400 Subject: [PATCH 0953/1060] Add changelog for #4005 --- changelog/4005.added.md | 1 + 1 file changed, 1 insertion(+) create mode 100644 changelog/4005.added.md diff --git a/changelog/4005.added.md b/changelog/4005.added.md new file mode 100644 index 000000000..0a023f104 --- /dev/null +++ b/changelog/4005.added.md @@ -0,0 +1 @@ +- Added `sip_provider` and `room_geo` parameters to `configure()` in the Daily runner. These convenience parameters let callers specify a SIP provider name and geographic region directly without manually constructing `DailyRoomProperties` and `DailyRoomSipParams`. From 84538b0ca89bb6770bc97246dd2dfbe83d83b631 Mon Sep 17 00:00:00 2001 From: Ali Alhoshaiyan Date: Thu, 15 Jan 2026 09:52:44 +0300 Subject: [PATCH 0954/1060] Reduce Call Tool Result Context Size by Allowing UTF-8 in JSON Serialization --- src/pipecat/services/anthropic/llm.py | 2 +- src/pipecat/services/aws/llm.py | 2 +- src/pipecat/services/openai/llm.py | 2 +- src/pipecat/services/openai_realtime_beta/openai.py | 2 +- 4 files changed, 4 insertions(+), 4 deletions(-) diff --git a/src/pipecat/services/anthropic/llm.py b/src/pipecat/services/anthropic/llm.py index fcaed1dfe..2f375df82 100644 --- a/src/pipecat/services/anthropic/llm.py +++ b/src/pipecat/services/anthropic/llm.py @@ -1246,7 +1246,7 @@ class AnthropicAssistantContextAggregator(LLMAssistantContextAggregator): frame: Frame containing function call result. """ if frame.result: - result = json.dumps(frame.result) + result = json.dumps(frame.result, ensure_ascii=False) await self._update_function_call_result(frame.function_name, frame.tool_call_id, result) else: await self._update_function_call_result( diff --git a/src/pipecat/services/aws/llm.py b/src/pipecat/services/aws/llm.py index 59859abf7..92049dffb 100644 --- a/src/pipecat/services/aws/llm.py +++ b/src/pipecat/services/aws/llm.py @@ -691,7 +691,7 @@ class AWSBedrockAssistantContextAggregator(LLMAssistantContextAggregator): frame: The function call result frame to handle. """ if frame.result: - result = json.dumps(frame.result) + result = json.dumps(frame.result, ensure_ascii=False) await self._update_function_call_result(frame.function_name, frame.tool_call_id, result) else: await self._update_function_call_result( diff --git a/src/pipecat/services/openai/llm.py b/src/pipecat/services/openai/llm.py index abb3e7eec..553733922 100644 --- a/src/pipecat/services/openai/llm.py +++ b/src/pipecat/services/openai/llm.py @@ -255,7 +255,7 @@ class OpenAIAssistantContextAggregator(LLMAssistantContextAggregator): frame: Frame containing the function call result. """ if frame.result: - result = json.dumps(frame.result) + result = json.dumps(frame.result, ensure_ascii=False) await self._update_function_call_result(frame.function_name, frame.tool_call_id, result) else: await self._update_function_call_result( diff --git a/src/pipecat/services/openai_realtime_beta/openai.py b/src/pipecat/services/openai_realtime_beta/openai.py index 0a6315986..0d20039b1 100644 --- a/src/pipecat/services/openai_realtime_beta/openai.py +++ b/src/pipecat/services/openai_realtime_beta/openai.py @@ -441,7 +441,7 @@ class OpenAIRealtimeBetaLLMService(LLMService): item = events.ConversationItem( type="function_call_output", call_id=frame.tool_call_id, - output=json.dumps(frame.result), + output=json.dumps(frame.result, ensure_ascii=False), ) await self.send_client_event(events.ConversationItemCreateEvent(item=item)) From 765fbeec630ef9ed2bf70bc8becdd80443aef4c8 Mon Sep 17 00:00:00 2001 From: Ali Alhoshaiyan Date: Thu, 15 Jan 2026 10:11:20 +0300 Subject: [PATCH 0955/1060] Add changelog --- changelog/3457.changed.md | 16 ++++++++++++++++ 1 file changed, 16 insertions(+) create mode 100644 changelog/3457.changed.md diff --git a/changelog/3457.changed.md b/changelog/3457.changed.md new file mode 100644 index 000000000..afd607d7a --- /dev/null +++ b/changelog/3457.changed.md @@ -0,0 +1,16 @@ +# Reduce Call Tool Result Context Size by Allowing UTF-8 in JSON Serialization + +This PR changes tool result serialization to prevent UTF-8 code points from being escaped during serialization. This drastically reduces the context size when returning a response that contains languages other than English. + +We have been running a monkey-patched version in production and it helped us improve the agent accuracy and control cost better. + +``` +>>> data = { "message": "أهلًا بالعالم" } +>>> json.dumps(data) +'{"message": "\\u0623\\u0647\\u0644\\u064b\\u0627 \\u0628\\u0627\\u0644\\u0639\\u0627\\u0644\\u0645"}' +>>> +>>> +>>> +>>> json.dumps(data, ensure_ascii=False) +'{"message": "أهلًا بالعالم"}' +``` From 1fe1f0f43929892c47379985ea854010ebd25e4a Mon Sep 17 00:00:00 2001 From: Mark Backman Date: Thu, 12 Mar 2026 10:34:29 -0400 Subject: [PATCH 0956/1060] Apply ensure_ascii=False to remaining LLM services and fix changelog format --- changelog/3457.changed.md | 17 +---------------- src/pipecat/services/aws/nova_sonic/llm.py | 4 +++- src/pipecat/services/google/llm.py | 4 +++- src/pipecat/services/grok/realtime/llm.py | 2 +- src/pipecat/services/openai/realtime/llm.py | 2 +- 5 files changed, 9 insertions(+), 20 deletions(-) diff --git a/changelog/3457.changed.md b/changelog/3457.changed.md index afd607d7a..d0d82ad2d 100644 --- a/changelog/3457.changed.md +++ b/changelog/3457.changed.md @@ -1,16 +1 @@ -# Reduce Call Tool Result Context Size by Allowing UTF-8 in JSON Serialization - -This PR changes tool result serialization to prevent UTF-8 code points from being escaped during serialization. This drastically reduces the context size when returning a response that contains languages other than English. - -We have been running a monkey-patched version in production and it helped us improve the agent accuracy and control cost better. - -``` ->>> data = { "message": "أهلًا بالعالم" } ->>> json.dumps(data) -'{"message": "\\u0623\\u0647\\u0644\\u064b\\u0627 \\u0628\\u0627\\u0644\\u0639\\u0627\\u0644\\u0645"}' ->>> ->>> ->>> ->>> json.dumps(data, ensure_ascii=False) -'{"message": "أهلًا بالعالم"}' -``` +- Changed tool result JSON serialization to use `ensure_ascii=False`, preserving UTF-8 characters instead of escaping them. This reduces context size and token usage for non-English languages. diff --git a/src/pipecat/services/aws/nova_sonic/llm.py b/src/pipecat/services/aws/nova_sonic/llm.py index b1f56dbbd..0947ba1d7 100644 --- a/src/pipecat/services/aws/nova_sonic/llm.py +++ b/src/pipecat/services/aws/nova_sonic/llm.py @@ -1044,7 +1044,9 @@ class AWSNovaSonicLLMService(LLMService): "toolResult": { "promptName": self._prompt_name, "contentName": content_name, - "content": json.dumps(result) if isinstance(result, dict) else result, + "content": json.dumps(result, ensure_ascii=False) + if isinstance(result, dict) + else result, } } } diff --git a/src/pipecat/services/google/llm.py b/src/pipecat/services/google/llm.py index 698b9f97f..26ad46311 100644 --- a/src/pipecat/services/google/llm.py +++ b/src/pipecat/services/google/llm.py @@ -200,7 +200,9 @@ class GoogleAssistantContextAggregator(OpenAIAssistantContextAggregator): if message.role == "user": for part in message.parts: if part.function_response and part.function_response.id == tool_call_id: - part.function_response.response = {"value": json.dumps(result)} + part.function_response.response = { + "value": json.dumps(result, ensure_ascii=False) + } @dataclass diff --git a/src/pipecat/services/grok/realtime/llm.py b/src/pipecat/services/grok/realtime/llm.py index bfa192aad..6e37d21d2 100644 --- a/src/pipecat/services/grok/realtime/llm.py +++ b/src/pipecat/services/grok/realtime/llm.py @@ -939,7 +939,7 @@ class GrokRealtimeLLMService(LLMService): item = events.ConversationItem( type="function_call_output", call_id=tool_call_id, - output=json.dumps(result), + output=json.dumps(result, ensure_ascii=False), ) await self.send_client_event(events.ConversationItemCreateEvent(item=item)) diff --git a/src/pipecat/services/openai/realtime/llm.py b/src/pipecat/services/openai/realtime/llm.py index faaa19884..bd31369ae 100644 --- a/src/pipecat/services/openai/realtime/llm.py +++ b/src/pipecat/services/openai/realtime/llm.py @@ -1128,7 +1128,7 @@ class OpenAIRealtimeLLMService(LLMService): item = events.ConversationItem( type="function_call_output", call_id=tool_call_id, - output=json.dumps(result), + output=json.dumps(result, ensure_ascii=False), ) await self.send_client_event(events.ConversationItemCreateEvent(item=item)) From 27b686db8c6369ead5b28fc9b3f572351caba890 Mon Sep 17 00:00:00 2001 From: Paul Kompfner Date: Thu, 12 Mar 2026 11:04:49 -0400 Subject: [PATCH 0957/1060] Don't bother honoring the new `LLMUpdateSettingsFrame.service` field in the deprecated `OpenAIRealtimeBetaLLMService` --- src/pipecat/services/openai_realtime_beta/openai.py | 6 +----- 1 file changed, 1 insertion(+), 5 deletions(-) diff --git a/src/pipecat/services/openai_realtime_beta/openai.py b/src/pipecat/services/openai_realtime_beta/openai.py index cacf8debd..0a6315986 100644 --- a/src/pipecat/services/openai_realtime_beta/openai.py +++ b/src/pipecat/services/openai_realtime_beta/openai.py @@ -386,11 +386,7 @@ class OpenAIRealtimeBetaLLMService(LLMService): # fields, not our Settings fields, so we construct SessionProperties # directly. The frame.delta path falls through to super, which calls # _update_settings → our override handles the rest. - if ( - isinstance(frame, LLMUpdateSettingsFrame) - and frame.delta is None - and (frame.service is None or frame.service is self) - ): + if isinstance(frame, LLMUpdateSettingsFrame) and frame.delta is None: self._session_properties = events.SessionProperties(**frame.settings) await self._send_session_update() await self.push_frame(frame, direction) From 73a56f5d81b84bbc5442c60cffe6ffb500d4ff80 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Aleix=20Conchillo=20Flaqu=C3=A9?= Date: Thu, 12 Mar 2026 00:15:01 -0700 Subject: [PATCH 0958/1060] Fix ParallelPipeline flush ordering and buffered frame handling Flush buffered frames before pushing the synchronization frame so downstream processors see the buffered frames first. Switch to a while-loop with pop(0) so frames added to the buffer during flush are also drained. --- src/pipecat/pipeline/parallel_pipeline.py | 27 ++++++++++++++++++----- 1 file changed, 22 insertions(+), 5 deletions(-) diff --git a/src/pipecat/pipeline/parallel_pipeline.py b/src/pipecat/pipeline/parallel_pipeline.py index 88ea04638..1e2e03a8f 100644 --- a/src/pipecat/pipeline/parallel_pipeline.py +++ b/src/pipecat/pipeline/parallel_pipeline.py @@ -143,6 +143,19 @@ class ParallelPipeline(BasePipeline): await super().process_frame(frame, direction) # Parallel pipeline synchronized frames. + # + # - StartFrame: If a fast branch completes first, processors in + # other branches that haven't received StartFrame yet could + # receive other frames before it, causing errors. + # + # - EndFrame: If EndFrame escapes from a fast branch, downstream + # processors (e.g. output transport) begin shutting down while + # other branches still have frames to flush, causing lost output. + # + # - CancelFrame: PipelineTask waits for CancelFrame to reach the + # pipeline sink. If it escapes from a fast branch while slower + # branches are still running, the task considers cancellation + # complete prematurely. if isinstance(frame, (StartFrame, EndFrame, CancelFrame)): self._frame_counter[frame.id] = len(self._pipelines) self._synchronizing = True @@ -179,8 +192,13 @@ class ParallelPipeline(BasePipeline): # Only push the frame when all pipelines have processed it. if frame_counter == 0: self._synchronizing = False - await self._parallel_push_frame(frame, direction) - await self._flush_buffered_frames() + # StartFrame should always go before any other frame. + if isinstance(frame, StartFrame): + await self._parallel_push_frame(frame, direction) + await self._flush_buffered_frames() + else: + await self._flush_buffered_frames() + await self._parallel_push_frame(frame, direction) await self.resume_processing_system_frames() await self.resume_processing_frames() else: @@ -188,7 +206,6 @@ class ParallelPipeline(BasePipeline): async def _flush_buffered_frames(self): """Flush frames that were buffered during lifecycle frame synchronization.""" - frames = self._buffered_frames - self._buffered_frames = [] - for frame, direction in frames: + while len(self._buffered_frames) > 0: + frame, direction = self._buffered_frames.pop(0) await self.push_frame(frame, direction) From 1a66bdef8ed36722169752041051a62d844f85a1 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Aleix=20Conchillo=20Flaqu=C3=A9?= Date: Thu, 12 Mar 2026 00:15:03 -0700 Subject: [PATCH 0959/1060] Fix TTS stop ordering to drain audio contexts before canceling Wait for _audio_context_task to finish draining the contexts queue before canceling _stop_frame_task, ensuring all pending audio contexts are processed during shutdown. --- src/pipecat/services/tts_service.py | 6 +++--- 1 file changed, 3 insertions(+), 3 deletions(-) diff --git a/src/pipecat/services/tts_service.py b/src/pipecat/services/tts_service.py index da1bcaf87..7cfb9d738 100644 --- a/src/pipecat/services/tts_service.py +++ b/src/pipecat/services/tts_service.py @@ -536,15 +536,15 @@ class TTSService(AIService): frame: The end frame. """ await super().stop(frame) - if self._stop_frame_task: - await self.cancel_task(self._stop_frame_task) - self._stop_frame_task = None if self._audio_context_task: # Indicate no more audio contexts are available; this will end the # task cleanly after all contexts have been processed. await self._contexts_queue.put(None) await self._audio_context_task self._audio_context_task = None + if self._stop_frame_task: + await self.cancel_task(self._stop_frame_task) + self._stop_frame_task = None async def cancel(self, frame: CancelFrame): """Cancel the TTS service. From a461b2b9e6bb7306596d15b921e3753de2ffc717 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Aleix=20Conchillo=20Flaqu=C3=A9?= Date: Thu, 12 Mar 2026 00:16:26 -0700 Subject: [PATCH 0960/1060] Add changelog entries for PR #4007 --- changelog/4007.fixed.2.md | 1 + changelog/4007.fixed.md | 1 + 2 files changed, 2 insertions(+) create mode 100644 changelog/4007.fixed.2.md create mode 100644 changelog/4007.fixed.md diff --git a/changelog/4007.fixed.2.md b/changelog/4007.fixed.2.md new file mode 100644 index 000000000..0c50b83e9 --- /dev/null +++ b/changelog/4007.fixed.2.md @@ -0,0 +1 @@ +- Fixed `TTSService` potentially canceling in-flight audio during shutdown. The stop sequence now waits for all queued audio contexts to finish processing before canceling the stop frame task. diff --git a/changelog/4007.fixed.md b/changelog/4007.fixed.md new file mode 100644 index 000000000..8a90aea43 --- /dev/null +++ b/changelog/4007.fixed.md @@ -0,0 +1 @@ +- Fixed `ParallelPipeline` dropping or misordering frames during lifecycle synchronization. Buffered frames are now flushed in the correct order relative to synchronization frames (`StartFrame` goes first, `EndFrame`/`CancelFrame` go after), and frames added to the buffer during flush are also drained. From 2eccd28cf0aaa6362ff117dd3b6de7539b809d4e Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Aleix=20Conchillo=20Flaqu=C3=A9?= Date: Wed, 11 Mar 2026 23:16:15 -0700 Subject: [PATCH 0961/1060] handle EndTaskFrame, StopTaskFrame and CancelTaskFrame downstream EndTaskFrame and StopTaskFrame are now ControlFrames instead of SystemFrames, so they flow through the pipeline and queue behind pending work. This prevents races where EndFrame could overtake in-flight frames (e.g. function call responses). CancelTaskFrame and InterruptionTaskFrame remain SystemFrames (via new TaskSystemFrame base): since they need immediate propagation. The sink now catches EndTaskFrame, StopTaskFrame and CancelTaskFrame downstream and re-queues it upstream to the task, ensuring the full pipeline drains before shutdown begins. --- src/pipecat/frames/frames.py | 48 +++++++++++++++++++++++------------- src/pipecat/pipeline/task.py | 20 ++++++++++++--- 2 files changed, 47 insertions(+), 21 deletions(-) diff --git a/src/pipecat/frames/frames.py b/src/pipecat/frames/frames.py index f58dc957f..1ef7bdb4a 100644 --- a/src/pipecat/frames/frames.py +++ b/src/pipecat/frames/frames.py @@ -1742,7 +1742,7 @@ class ServiceSwitcherRequestMetadataFrame(ControlFrame): @dataclass -class TaskFrame(SystemFrame): +class TaskFrame(ControlFrame): """Base frame for task frames. This is a base class for frames that are meant to be sent and handled @@ -1756,7 +1756,21 @@ class TaskFrame(SystemFrame): @dataclass -class EndTaskFrame(TaskFrame): +class TaskSystemFrame(SystemFrame): + """Base frame for task system frames. + + This is a base class for frames that are meant to be sent and handled + upstream by the pipeline task. This might result in a corresponding frame + sent downstream (e.g. `InterruptionTaskFrame` / `InterruptionFrame` or + `EndTaskFrame` / `EndFrame`). + + """ + + pass + + +@dataclass +class EndTaskFrame(TaskFrame, UninterruptibleFrame): """Frame to request graceful pipeline task closure. This is used to notify the pipeline task that the pipeline should be @@ -1774,7 +1788,20 @@ class EndTaskFrame(TaskFrame): @dataclass -class CancelTaskFrame(TaskFrame): +class StopTaskFrame(TaskFrame, UninterruptibleFrame): + """Frame to request pipeline task stop while keeping processors running. + + This is used to notify the pipeline task that it should be stopped as + soon as possible (flushing all the queued frames) but that the pipeline + processors should be kept in a running state. This frame should be pushed + upstream. + """ + + pass + + +@dataclass +class CancelTaskFrame(TaskSystemFrame): """Frame to request immediate pipeline task cancellation. This is used to notify the pipeline task that the pipeline should be @@ -1792,20 +1819,7 @@ class CancelTaskFrame(TaskFrame): @dataclass -class StopTaskFrame(TaskFrame): - """Frame to request pipeline task stop while keeping processors running. - - This is used to notify the pipeline task that it should be stopped as - soon as possible (flushing all the queued frames) but that the pipeline - processors should be kept in a running state. This frame should be pushed - upstream. - """ - - pass - - -@dataclass -class InterruptionTaskFrame(TaskFrame): +class InterruptionTaskFrame(TaskSystemFrame): """Frame indicating the pipeline should be interrupted. This frame should be pushed upstream to indicate the pipeline should be diff --git a/src/pipecat/pipeline/task.py b/src/pipecat/pipeline/task.py index e795961a1..56df719d5 100644 --- a/src/pipecat/pipeline/task.py +++ b/src/pipecat/pipeline/task.py @@ -876,22 +876,22 @@ class PipelineTask(BasePipelineTask): if isinstance(frame, EndTaskFrame): # Tell the task we should end nicely. - logger.debug(f"{self}: received end task frame {frame}") + logger.debug(f"{self}: received end task frame upstream {frame}") await self.queue_frame(EndFrame(reason=frame.reason)) elif isinstance(frame, CancelTaskFrame): # Tell the task we should end right away. - logger.debug(f"{self}: received cancel task frame {frame}") + logger.debug(f"{self}: received cancel task frame upstream {frame}") await self.queue_frame(CancelFrame(reason=frame.reason)) elif isinstance(frame, StopTaskFrame): # Tell the task we should stop nicely. - logger.debug(f"{self}: received stop task frame {frame}") + logger.debug(f"{self}: received stop task frame upstream {frame}") await self.queue_frame(StopFrame()) elif isinstance(frame, InterruptionTaskFrame): # Tell the task we should interrupt the pipeline. Note that we are # bypassing the push queue and directly queue into the # pipeline. This is in case the push task is blocked waiting for a # pipeline-ending frame to finish traversing the pipeline. - logger.debug(f"{self}: received interruption task frame {frame}") + logger.debug(f"{self}: received interruption task frame upstream {frame}") await self._pipeline.queue_frame(InterruptionFrame()) elif isinstance(frame, ErrorFrame): await self._call_event_handler("on_pipeline_error", frame) @@ -934,6 +934,18 @@ class PipelineTask(BasePipelineTask): self._pipeline_end_event.set() elif isinstance(frame, HeartbeatFrame): await self._heartbeat_queue.put(frame) + elif isinstance(frame, EndTaskFrame): + logger.debug(f"{self}: received end task frame downstream {frame}") + await self.queue_frame(EndTaskFrame(reason=frame.reason), FrameDirection.UPSTREAM) + elif isinstance(frame, StopTaskFrame): + logger.debug(f"{self}: received stop task frame downstream {frame}") + await self.queue_frame(StopTaskFrame(), FrameDirection.UPSTREAM) + elif isinstance(frame, CancelTaskFrame): + logger.debug(f"{self}: received cancel task frame downstream {frame}") + await self.queue_frame(CancelTaskFrame(reason=frame.reason), FrameDirection.UPSTREAM) + elif isinstance(frame, InterruptionTaskFrame): + logger.debug(f"{self}: received interruption task frame downstream {frame}") + await self.queue_frame(InterruptionTaskFrame(), FrameDirection.UPSTREAM) async def _heartbeat_push_handler(self): """Push heartbeat frames at regular intervals.""" From f6f08d19a86acb72b1c984810a9b2038b6174f5c Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Aleix=20Conchillo=20Flaqu=C3=A9?= Date: Wed, 11 Mar 2026 23:16:45 -0700 Subject: [PATCH 0962/1060] Add changelog for #4006 --- changelog/4006.fixed.md | 1 + 1 file changed, 1 insertion(+) create mode 100644 changelog/4006.fixed.md diff --git a/changelog/4006.fixed.md b/changelog/4006.fixed.md new file mode 100644 index 000000000..ba12beea7 --- /dev/null +++ b/changelog/4006.fixed.md @@ -0,0 +1 @@ +- Fixed a race condition where `EndTaskFrame` could cause the pipeline to shut down before in-flight frames (e.g. LLM function call responses) finished processing. `EndTaskFrame` and `StopTaskFrame` now flow through the pipeline as `ControlFrame`s, ensuring all pending work is flushed before shutdown begins. `CancelTaskFrame` and `InterruptionTaskFrame` remain immediate (`SystemFrame`). From 38a4d4ff239c6a629c0eeb2677f50530eac4341d Mon Sep 17 00:00:00 2001 From: Mark Backman Date: Thu, 12 Mar 2026 14:46:49 -0400 Subject: [PATCH 0963/1060] Update quickstart to use cloud builds --- examples/quickstart/README.md | 28 +++++----------------------- examples/quickstart/pcc-deploy.toml | 9 ++------- 2 files changed, 7 insertions(+), 30 deletions(-) diff --git a/examples/quickstart/README.md b/examples/quickstart/README.md index 91a3fd888..6374d622c 100644 --- a/examples/quickstart/README.md +++ b/examples/quickstart/README.md @@ -81,23 +81,12 @@ Transform your local bot into a production-ready service. Pipecat Cloud handles > 💡 Tip: You can run the `pipecat` CLI using the `pc` alias. -3. Set up Docker for building your bot image: - - - **Install [Docker](https://www.docker.com/)** on your system - - **Create a [Docker Hub](https://hub.docker.com/) account** - - **Login to Docker Hub:** - - ```bash - docker login - ``` - ### Configure your deployment -The `pcc-deploy.toml` file tells Pipecat Cloud how to run your bot. **Update the image field** with your Docker Hub username by editing `pcc-deploy.toml`. +The `pcc-deploy.toml` file tells Pipecat Cloud how to run your bot. ```ini agent_name = "quickstart" -image = "YOUR_DOCKERHUB_USERNAME/quickstart:0.1" # 👈 Update this line secret_set = "quickstart-secrets" [scaling] @@ -107,12 +96,9 @@ secret_set = "quickstart-secrets" **Understanding the TOML file settings:** - `agent_name`: Your bot's name in Pipecat Cloud -- `image`: The Docker image to deploy (format: `username/image:version`) - `secret_set`: Where your API keys are stored securely - `min_agents`: Number of bot instances to keep ready (1 = instant start) -> 💡 Tip: [Set up `image_credentials`](https://docs.pipecat.ai/deployment/pipecat-cloud/fundamentals/secrets#image-pull-secrets) in your TOML file for authenticated image pulls - ### Log in to Pipecat Cloud To start using the CLI, authenticate to Pipecat Cloud: @@ -121,7 +107,7 @@ To start using the CLI, authenticate to Pipecat Cloud: pipecat cloud auth login ``` -You'll be presented with a link that you can click to authenticate your client. +You'll be presented with a link and six-digit code that you can click to authenticate your client. ### Configure secrets @@ -133,13 +119,7 @@ pipecat cloud secrets set quickstart-secrets --file .env This creates a secret set called `quickstart-secrets` (matching your TOML file) and uploads all your API keys from `.env`. -### Build and deploy - -Build your Docker image and push to Docker Hub: - -```bash -pipecat cloud docker build-push -``` +### Deploy Deploy to Pipecat Cloud: @@ -147,6 +127,8 @@ Deploy to Pipecat Cloud: pipecat cloud deploy ``` +This pushes your project files to Pipecat Cloud where a docker image is built and deployed into production. + ### Connect to your agent 1. Open your [Pipecat Cloud dashboard](https://pipecat.daily.co/) diff --git a/examples/quickstart/pcc-deploy.toml b/examples/quickstart/pcc-deploy.toml index f08e8a624..5562f117e 100644 --- a/examples/quickstart/pcc-deploy.toml +++ b/examples/quickstart/pcc-deploy.toml @@ -1,11 +1,6 @@ -agent_name = "quickstart-test" -image = "your_username/quickstart-test:latest" -secret_set = "quickstart-test-secrets" +agent_name = "quickstart" +secret_set = "quickstart-secrets" agent_profile = "agent-1x" -# RECOMMENDED: Set an image pull secret: -# https://docs.pipecat.ai/deployment/pipecat-cloud/fundamentals/secrets#image-pull-secrets -image_credentials = "dockerhub-access" - [scaling] min_agents = 1 From 0373f85b85c92d31f252971f1c10c899412a6750 Mon Sep 17 00:00:00 2001 From: Paul Kompfner Date: Thu, 12 Mar 2026 14:56:30 -0400 Subject: [PATCH 0964/1060] Add PerplexityLLMAdapter to enforce Perplexity's message ordering constraints Perplexity's API is stricter than OpenAI about conversation history: - Requires strict alternation between user/tool and assistant messages - Disallows system messages except as the initial message - Requires the last message to be user or tool The new adapter transforms messages before sending to satisfy all three constraints: merging consecutive initial system messages, converting non-initial system to user, merging consecutive same-role messages, and removing trailing assistant messages. Also adds dual-system-instruction warnings to Cerebras, Fireworks, Mistral, Perplexity, and SambaNova services (matching the existing BaseOpenAILLMService pattern), and updates the warning text in BaseOpenAILLMService to be more descriptive. --- .../adapters/services/perplexity_adapter.py | 169 +++++++++++++++ src/pipecat/services/cerebras/llm.py | 4 + src/pipecat/services/fireworks/llm.py | 4 + src/pipecat/services/mistral/llm.py | 4 + src/pipecat/services/openai/base_llm.py | 6 +- src/pipecat/services/perplexity/llm.py | 9 + src/pipecat/services/sambanova/llm.py | 4 + tests/test_get_llm_invocation_params.py | 197 ++++++++++++++++++ 8 files changed, 393 insertions(+), 4 deletions(-) create mode 100644 src/pipecat/adapters/services/perplexity_adapter.py diff --git a/src/pipecat/adapters/services/perplexity_adapter.py b/src/pipecat/adapters/services/perplexity_adapter.py new file mode 100644 index 000000000..0c5de9a63 --- /dev/null +++ b/src/pipecat/adapters/services/perplexity_adapter.py @@ -0,0 +1,169 @@ +# +# Copyright (c) 2024-2026, Daily +# +# SPDX-License-Identifier: BSD 2-Clause License +# + +"""Perplexity LLM adapter for Pipecat. + +Perplexity's API uses an OpenAI-compatible interface but enforces stricter +constraints on conversation history structure: + +1. **Strict role alternation** — Messages must alternate between "user"/"tool" + and "assistant" roles. Consecutive messages with the same role (e.g. two + "user" messages in a row) are rejected with: + ``"messages must be an alternating sequence of user/tool and assistant messages"`` + +2. **No non-initial system messages** — "system" messages are only allowed as + the very first message. A system message anywhere else causes: + ``"only the initial message can have the system role"`` + +3. **Last message must be user/tool** — The final message in the conversation + must have role "user" or "tool". A trailing "assistant" message causes: + ``"the last message must have the user or tool role"`` + +This adapter transforms the message list to satisfy all three constraints before +the messages are sent to Perplexity's API. +""" + +import copy +from typing import List + +from openai.types.chat import ChatCompletionMessageParam + +from pipecat.adapters.services.open_ai_adapter import OpenAILLMAdapter, OpenAILLMInvocationParams +from pipecat.processors.aggregators.llm_context import LLMContext + + +class PerplexityLLMAdapter(OpenAILLMAdapter): + """Adapter that transforms messages to satisfy Perplexity's API constraints. + + Perplexity's API is stricter than standard OpenAI about message structure. + This adapter extends ``OpenAILLMAdapter`` and applies message transformations + to ensure compliance with Perplexity's three constraints (role alternation, + no non-initial system messages, last message must be user/tool). + + The transformations are applied in ``get_llm_invocation_params`` after the + parent adapter extracts messages from the LLM context, and before + ``build_chat_completion_params`` prepends ``system_instruction``. + """ + + def get_llm_invocation_params(self, context: LLMContext) -> OpenAILLMInvocationParams: + """Get OpenAI-compatible invocation parameters with Perplexity message fixes applied. + + Args: + context: The LLM context containing messages, tools, etc. + + Returns: + Dictionary of parameters for Perplexity's ChatCompletion API, with + messages transformed to satisfy Perplexity's constraints. + """ + params = super().get_llm_invocation_params(context) + params["messages"] = self._transform_messages(list(params["messages"])) + return params + + def _transform_messages( + self, messages: List[ChatCompletionMessageParam] + ) -> List[ChatCompletionMessageParam]: + """Transform messages to satisfy Perplexity's API constraints. + + Applies four transformation steps in order: + + 1. **Merge consecutive initial system messages** — If the conversation + starts with multiple system messages, merge them into a single system + message using list-of-dicts content format. This addresses + Perplexity's constraint that only the initial message can be system. + + 2. **Convert non-initial system messages to user** — Any system message + after the initial position is converted to role "user", since + Perplexity rejects non-initial system messages. + + 3. **Merge consecutive same-role messages** — After the above + conversions, adjacent messages with the same role are merged using + list-of-dicts content format. This ensures strict role alternation + (e.g. a converted system→user message adjacent to an existing user + message gets merged). + + 4. **Remove trailing assistant messages** — If the last message is + "assistant", remove it. OpenAI appears to silently ignore trailing + assistant messages server-side, so removing them preserves equivalent + behavior while satisfying Perplexity's "last message must be + user/tool" constraint. If the only remaining message is "system" + (possible when the context contains just a single system message), + convert it to "user" since Perplexity requires the last message to + be "user" or "tool". + + Args: + messages: List of message dicts with "role" and "content" keys. + + Returns: + Transformed list of message dicts satisfying Perplexity's constraints. + """ + if not messages: + return messages + + messages = copy.deepcopy(messages) + + # Step 1: Merge consecutive system messages at the start into one. + # Perplexity only allows a single initial system message, so if there + # are multiple consecutive system messages at the start, we merge them. + if messages[0].get("role") == "system": + system_end = 1 + while system_end < len(messages) and messages[system_end].get("role") == "system": + system_end += 1 + + if system_end > 1: + # Merge all initial system messages into a single message using + # list-of-dicts content format (same approach as Anthropic adapter). + merged_content = [] + for msg in messages[:system_end]: + content = msg.get("content", "") + if isinstance(content, str): + merged_content.append({"type": "text", "text": content}) + elif isinstance(content, list): + merged_content.extend(content) + messages = [{"role": "system", "content": merged_content}] + messages[system_end:] + + # Step 2: Convert non-initial system messages to "user". + # Perplexity only allows system role for the very first message. + for i in range(1, len(messages)): + if messages[i].get("role") == "system": + messages[i]["role"] = "user" + + # Step 3: Merge consecutive same-role messages. + # After system→user conversions above, we may have adjacent same-role + # messages that violate Perplexity's strict alternation requirement. + i = 0 + while i < len(messages) - 1: + current = messages[i] + next_msg = messages[i + 1] + if current["role"] == next_msg["role"]: + # Convert string content to list-of-dicts format for merging + if isinstance(current.get("content"), str): + current["content"] = [{"type": "text", "text": current["content"]}] + if isinstance(next_msg.get("content"), str): + next_msg["content"] = [{"type": "text", "text": next_msg["content"]}] + # Merge content from next message into current + if isinstance(current.get("content"), list) and isinstance( + next_msg.get("content"), list + ): + current["content"].extend(next_msg["content"]) + messages.pop(i + 1) + else: + i += 1 + + # Step 4: Handle trailing messages. + # Perplexity requires the last message to be "user" or "tool". + if messages: + # Remove trailing assistant messages. OpenAI appears to silently + # ignore trailing assistant messages server-side, so removing them + # preserves equivalent behavior. + while messages and messages[-1].get("role") == "assistant": + messages.pop() + + # If the only remaining message is "system" (single system message + # in the context), convert it to "user". + if messages and len(messages) == 1 and messages[0].get("role") == "system": + messages[0]["role"] = "user" + + return messages diff --git a/src/pipecat/services/cerebras/llm.py b/src/pipecat/services/cerebras/llm.py index 7c31a6857..dfb62baf8 100644 --- a/src/pipecat/services/cerebras/llm.py +++ b/src/pipecat/services/cerebras/llm.py @@ -117,6 +117,10 @@ class CerebrasLLMService(OpenAILLMService): # Prepend system instruction if set if self._settings.system_instruction: messages = params.get("messages", []) + if messages and messages[0].get("role") == "system": + logger.warning( + f"{self}: Both system_instruction and an initial system message in context are set. This may be unintended." + ) params["messages"] = [ {"role": "system", "content": self._settings.system_instruction} ] + messages diff --git a/src/pipecat/services/fireworks/llm.py b/src/pipecat/services/fireworks/llm.py index bf141fac1..5efa60793 100644 --- a/src/pipecat/services/fireworks/llm.py +++ b/src/pipecat/services/fireworks/llm.py @@ -118,6 +118,10 @@ class FireworksLLMService(OpenAILLMService): # Prepend system instruction if set if self._settings.system_instruction: messages = params.get("messages", []) + if messages and messages[0].get("role") == "system": + logger.warning( + f"{self}: Both system_instruction and an initial system message in context are set. This may be unintended." + ) params["messages"] = [ {"role": "system", "content": self._settings.system_instruction} ] + messages diff --git a/src/pipecat/services/mistral/llm.py b/src/pipecat/services/mistral/llm.py index 3ee1b2623..063dac3aa 100644 --- a/src/pipecat/services/mistral/llm.py +++ b/src/pipecat/services/mistral/llm.py @@ -236,6 +236,10 @@ class MistralLLMService(OpenAILLMService): # Prepend system instruction if set if self._settings.system_instruction: messages = params.get("messages", []) + if messages and messages[0].get("role") == "system": + logger.warning( + f"{self}: Both system_instruction and an initial system message in context are set. This may be unintended." + ) params["messages"] = [ {"role": "system", "content": self._settings.system_instruction} ] + messages diff --git a/src/pipecat/services/openai/base_llm.py b/src/pipecat/services/openai/base_llm.py index 41b26bd20..eb8ce3cc6 100644 --- a/src/pipecat/services/openai/base_llm.py +++ b/src/pipecat/services/openai/base_llm.py @@ -332,8 +332,7 @@ class BaseOpenAILLMService(LLMService): messages = params.get("messages", []) if messages and messages[0].get("role") == "system": logger.warning( - f"{self}: Both system_instruction and a system message in context are set." - " Using system_instruction." + f"{self}: Both system_instruction and an initial system message in context are set. This may be unintended." ) params["messages"] = [ {"role": "system", "content": self._settings.system_instruction} @@ -381,8 +380,7 @@ class BaseOpenAILLMService(LLMService): messages = params.get("messages", []) if messages and messages[0].get("role") == "system": logger.warning( - f"{self}: Both system_instruction and a system message in context are set." - " Using system_instruction." + f"{self}: Both system_instruction and an initial system message in context are set. This may be unintended." ) params["messages"] = [{"role": "system", "content": system_instruction}] + messages diff --git a/src/pipecat/services/perplexity/llm.py b/src/pipecat/services/perplexity/llm.py index 6c2ceba35..9ea323c5d 100644 --- a/src/pipecat/services/perplexity/llm.py +++ b/src/pipecat/services/perplexity/llm.py @@ -14,7 +14,10 @@ reporting patterns while maintaining compatibility with the Pipecat framework. from dataclasses import dataclass from typing import Optional +from loguru import logger + from pipecat.adapters.services.open_ai_adapter import OpenAILLMInvocationParams +from pipecat.adapters.services.perplexity_adapter import PerplexityLLMAdapter from pipecat.metrics.metrics import LLMTokenUsage from pipecat.processors.aggregators.llm_context import LLMContext from pipecat.processors.aggregators.openai_llm_context import OpenAILLMContext @@ -37,6 +40,8 @@ class PerplexityLLMService(OpenAILLMService): in token usage reporting between Perplexity (incremental) and OpenAI (final summary). """ + adapter_class = PerplexityLLMAdapter + Settings = PerplexityLLMSettings _settings: Settings @@ -119,6 +124,10 @@ class PerplexityLLMService(OpenAILLMService): # Prepend system instruction if set if self._settings.system_instruction: messages = params.get("messages", []) + if messages and messages[0].get("role") == "system": + logger.warning( + f"{self}: Both system_instruction and an initial system message in context are set. This may be unintended." + ) params["messages"] = [ {"role": "system", "content": self._settings.system_instruction} ] + messages diff --git a/src/pipecat/services/sambanova/llm.py b/src/pipecat/services/sambanova/llm.py index 3c7d76737..710a22db2 100644 --- a/src/pipecat/services/sambanova/llm.py +++ b/src/pipecat/services/sambanova/llm.py @@ -134,6 +134,10 @@ class SambaNovaLLMService(OpenAILLMService): # type: ignore # Prepend system instruction if set if self._settings.system_instruction: messages = params.get("messages", []) + if messages and messages[0].get("role") == "system": + logger.warning( + f"{self}: Both system_instruction and an initial system message in context are set. This may be unintended." + ) params["messages"] = [ {"role": "system", "content": self._settings.system_instruction} ] + messages diff --git a/tests/test_get_llm_invocation_params.py b/tests/test_get_llm_invocation_params.py index c93275b67..f534d7109 100644 --- a/tests/test_get_llm_invocation_params.py +++ b/tests/test_get_llm_invocation_params.py @@ -48,6 +48,7 @@ from pipecat.adapters.services.anthropic_adapter import AnthropicLLMAdapter from pipecat.adapters.services.bedrock_adapter import AWSBedrockLLMAdapter from pipecat.adapters.services.gemini_adapter import GeminiLLMAdapter from pipecat.adapters.services.open_ai_adapter import OpenAILLMAdapter +from pipecat.adapters.services.perplexity_adapter import PerplexityLLMAdapter from pipecat.processors.aggregators.llm_context import ( LLMContext, LLMStandardMessage, @@ -992,5 +993,201 @@ class TestAWSBedrockGetLLMInvocationParams(unittest.TestCase): self.assertEqual(len(params["messages"]), 0) +class TestPerplexityGetLLMInvocationParams(unittest.TestCase): + def setUp(self) -> None: + """Sets up a common adapter instance for all tests.""" + self.adapter = PerplexityLLMAdapter() + + def test_standard_messages_pass_through(self): + """Test that a valid [user, assistant, user] sequence passes through unchanged.""" + messages: list[LLMStandardMessage] = [ + {"role": "user", "content": "Hello"}, + {"role": "assistant", "content": "Hi there!"}, + {"role": "user", "content": "How are you?"}, + ] + + context = LLMContext(messages=messages) + params = self.adapter.get_llm_invocation_params(context) + + self.assertEqual(len(params["messages"]), 3) + self.assertEqual(params["messages"][0]["role"], "user") + self.assertEqual(params["messages"][0]["content"], "Hello") + self.assertEqual(params["messages"][1]["role"], "assistant") + self.assertEqual(params["messages"][1]["content"], "Hi there!") + self.assertEqual(params["messages"][2]["role"], "user") + self.assertEqual(params["messages"][2]["content"], "How are you?") + + def test_initial_system_message_preserved(self): + """Test that a valid [system, user, assistant, user] sequence passes through unchanged.""" + messages: list[LLMStandardMessage] = [ + {"role": "system", "content": "You are a helpful assistant."}, + {"role": "user", "content": "Hello"}, + {"role": "assistant", "content": "Hi!"}, + {"role": "user", "content": "Bye"}, + ] + + context = LLMContext(messages=messages) + params = self.adapter.get_llm_invocation_params(context) + + self.assertEqual(len(params["messages"]), 4) + self.assertEqual(params["messages"][0]["role"], "system") + self.assertEqual(params["messages"][0]["content"], "You are a helpful assistant.") + self.assertEqual(params["messages"][1]["role"], "user") + self.assertEqual(params["messages"][2]["role"], "assistant") + self.assertEqual(params["messages"][3]["role"], "user") + + def test_consecutive_same_role_messages_merged(self): + """Test that consecutive user messages are merged into list-of-dicts content.""" + messages: list[LLMStandardMessage] = [ + {"role": "user", "content": "First message"}, + {"role": "user", "content": "Second message"}, + {"role": "assistant", "content": "Response"}, + {"role": "user", "content": "Third message"}, + ] + + context = LLMContext(messages=messages) + params = self.adapter.get_llm_invocation_params(context) + + self.assertEqual(len(params["messages"]), 3) + + # First message should be merged users + merged = params["messages"][0] + self.assertEqual(merged["role"], "user") + self.assertIsInstance(merged["content"], list) + self.assertEqual(len(merged["content"]), 2) + self.assertEqual(merged["content"][0]["type"], "text") + self.assertEqual(merged["content"][0]["text"], "First message") + self.assertEqual(merged["content"][1]["type"], "text") + self.assertEqual(merged["content"][1]["text"], "Second message") + + self.assertEqual(params["messages"][1]["role"], "assistant") + self.assertEqual(params["messages"][2]["role"], "user") + + def test_non_initial_system_converted_to_user(self): + """Test that non-initial system messages are converted to user and merged with adjacent user.""" + messages: list[LLMStandardMessage] = [ + {"role": "system", "content": "You are helpful."}, + {"role": "user", "content": "Hello"}, + {"role": "assistant", "content": "Hi!"}, + {"role": "system", "content": "Be concise."}, + {"role": "user", "content": "Tell me about Python."}, + ] + + context = LLMContext(messages=messages) + params = self.adapter.get_llm_invocation_params(context) + + # system(initial), user, assistant, merged(system→user + user) + self.assertEqual(len(params["messages"]), 4) + self.assertEqual(params["messages"][0]["role"], "system") + self.assertEqual(params["messages"][1]["role"], "user") + self.assertEqual(params["messages"][2]["role"], "assistant") + + # The converted system→user and the following user should be merged + merged = params["messages"][3] + self.assertEqual(merged["role"], "user") + self.assertIsInstance(merged["content"], list) + self.assertEqual(len(merged["content"]), 2) + self.assertEqual(merged["content"][0]["text"], "Be concise.") + self.assertEqual(merged["content"][1]["text"], "Tell me about Python.") + + def test_multiple_system_messages_at_start_merged(self): + """Test that multiple consecutive system messages at start are merged into one.""" + messages: list[LLMStandardMessage] = [ + {"role": "system", "content": "You are a helpful assistant."}, + {"role": "system", "content": "Always be polite."}, + {"role": "user", "content": "Hello"}, + ] + + context = LLMContext(messages=messages) + params = self.adapter.get_llm_invocation_params(context) + + self.assertEqual(len(params["messages"]), 2) + + # First message should be merged system + system_msg = params["messages"][0] + self.assertEqual(system_msg["role"], "system") + self.assertIsInstance(system_msg["content"], list) + self.assertEqual(len(system_msg["content"]), 2) + self.assertEqual(system_msg["content"][0]["text"], "You are a helpful assistant.") + self.assertEqual(system_msg["content"][1]["text"], "Always be polite.") + + self.assertEqual(params["messages"][1]["role"], "user") + self.assertEqual(params["messages"][1]["content"], "Hello") + + def test_trailing_assistant_removed(self): + """Test that a trailing assistant message is removed.""" + messages: list[LLMStandardMessage] = [ + {"role": "user", "content": "Hello"}, + {"role": "assistant", "content": "Hi there!"}, + ] + + context = LLMContext(messages=messages) + params = self.adapter.get_llm_invocation_params(context) + + self.assertEqual(len(params["messages"]), 1) + self.assertEqual(params["messages"][0]["role"], "user") + self.assertEqual(params["messages"][0]["content"], "Hello") + + def test_only_system_message_converted_to_user(self): + """Test that a single system message is converted to user role.""" + messages: list[LLMStandardMessage] = [ + {"role": "system", "content": "You are a helpful assistant."}, + ] + + context = LLMContext(messages=messages) + params = self.adapter.get_llm_invocation_params(context) + + self.assertEqual(len(params["messages"]), 1) + self.assertEqual(params["messages"][0]["role"], "user") + self.assertEqual(params["messages"][0]["content"], "You are a helpful assistant.") + + def test_consecutive_assistants_merged_then_trailing_removed(self): + """Test that consecutive assistant messages are merged, then trailing assistant is removed.""" + messages: list[LLMStandardMessage] = [ + {"role": "user", "content": "Hello"}, + {"role": "assistant", "content": "First response"}, + {"role": "assistant", "content": "Second response"}, + ] + + context = LLMContext(messages=messages) + params = self.adapter.get_llm_invocation_params(context) + + # After merging assistants we get [user, assistant(merged)], then trailing + # assistant is removed, leaving just [user] + self.assertEqual(len(params["messages"]), 1) + self.assertEqual(params["messages"][0]["role"], "user") + self.assertEqual(params["messages"][0]["content"], "Hello") + + def test_tool_messages_preserved(self): + """Test that tool messages pass through without modification.""" + messages: list[LLMStandardMessage] = [ + {"role": "user", "content": "What's the weather?"}, + { + "role": "assistant", + "content": "Let me check.", + "tool_calls": [{"id": "1", "function": {"name": "get_weather", "arguments": "{}"}}], + }, + {"role": "tool", "content": "Sunny, 72F", "tool_call_id": "1"}, + {"role": "user", "content": "Thanks!"}, + ] + + context = LLMContext(messages=messages) + params = self.adapter.get_llm_invocation_params(context) + + self.assertEqual(len(params["messages"]), 4) + self.assertEqual(params["messages"][0]["role"], "user") + self.assertEqual(params["messages"][1]["role"], "assistant") + self.assertEqual(params["messages"][2]["role"], "tool") + self.assertEqual(params["messages"][2]["content"], "Sunny, 72F") + self.assertEqual(params["messages"][3]["role"], "user") + + def test_empty_messages(self): + """Test that empty messages list returns empty.""" + context = LLMContext(messages=[]) + params = self.adapter.get_llm_invocation_params(context) + + self.assertEqual(params["messages"], []) + + if __name__ == "__main__": unittest.main() From e4bf6281c6fb136cbed12dfdf7ca6f671caae718 Mon Sep 17 00:00:00 2001 From: Paul Kompfner Date: Thu, 12 Mar 2026 14:56:37 -0400 Subject: [PATCH 0965/1060] Add changelog for #4009 --- changelog/4009.added.md | 1 + 1 file changed, 1 insertion(+) create mode 100644 changelog/4009.added.md diff --git a/changelog/4009.added.md b/changelog/4009.added.md new file mode 100644 index 000000000..9ebbec7dd --- /dev/null +++ b/changelog/4009.added.md @@ -0,0 +1 @@ +- Added `PerplexityLLMAdapter` that automatically transforms conversation messages to satisfy Perplexity's stricter API constraints (strict role alternation, no non-initial system messages, last message must be user/tool). Previously, certain conversation histories could cause Perplexity API errors that didn't occur with OpenAI (`PerplexityLLMService` subclasses `OpenAILLMService` since Perplexity uses an OpenAI-compatible API). From 7f98cc9921fe7fe44f1e64ffb71524e592b16ceb Mon Sep 17 00:00:00 2001 From: Paul Kompfner Date: Thu, 12 Mar 2026 15:14:56 -0400 Subject: [PATCH 0966/1060] Remove initial system message merging, handle trailing system messages Perplexity allows multiple initial system messages, so don't merge them. Instead, skip system-system pairs during the consecutive same-role merge step. Broaden the trailing message fix to convert any trailing system message to user (not just a lone system message), so contexts with only system messages don't fail. --- .../adapters/services/perplexity_adapter.py | 85 ++++++++----------- tests/test_get_llm_invocation_params.py | 39 ++++++--- 2 files changed, 59 insertions(+), 65 deletions(-) diff --git a/src/pipecat/adapters/services/perplexity_adapter.py b/src/pipecat/adapters/services/perplexity_adapter.py index 0c5de9a63..754716a19 100644 --- a/src/pipecat/adapters/services/perplexity_adapter.py +++ b/src/pipecat/adapters/services/perplexity_adapter.py @@ -14,8 +14,9 @@ constraints on conversation history structure: "user" messages in a row) are rejected with: ``"messages must be an alternating sequence of user/tool and assistant messages"`` -2. **No non-initial system messages** — "system" messages are only allowed as - the very first message. A system message anywhere else causes: +2. **No non-initial system messages** — "system" messages are only allowed at + the start of the conversation. A system message after a non-system message + causes: ``"only the initial message can have the system role"`` 3. **Last message must be user/tool** — The final message in the conversation @@ -38,9 +39,9 @@ from pipecat.processors.aggregators.llm_context import LLMContext class PerplexityLLMAdapter(OpenAILLMAdapter): """Adapter that transforms messages to satisfy Perplexity's API constraints. - Perplexity's API is stricter than standard OpenAI about message structure. - This adapter extends ``OpenAILLMAdapter`` and applies message transformations - to ensure compliance with Perplexity's three constraints (role alternation, + Perplexity's API is stricter than OpenAI about message structure. This + adapter extends ``OpenAILLMAdapter`` and applies message transformations + to ensure compliance with Perplexity's constraints (role alternation, no non-initial system messages, last message must be user/tool). The transformations are applied in ``get_llm_invocation_params`` after the @@ -67,31 +68,24 @@ class PerplexityLLMAdapter(OpenAILLMAdapter): ) -> List[ChatCompletionMessageParam]: """Transform messages to satisfy Perplexity's API constraints. - Applies four transformation steps in order: + Applies three transformation steps in order: - 1. **Merge consecutive initial system messages** — If the conversation - starts with multiple system messages, merge them into a single system - message using list-of-dicts content format. This addresses - Perplexity's constraint that only the initial message can be system. + 1. **Convert non-initial system messages to user** — Any system message + after the initial system message block is converted to role "user", + since Perplexity rejects system messages after a non-system message. - 2. **Convert non-initial system messages to user** — Any system message - after the initial position is converted to role "user", since - Perplexity rejects non-initial system messages. - - 3. **Merge consecutive same-role messages** — After the above + 2. **Merge consecutive same-role messages** — After the above conversions, adjacent messages with the same role are merged using list-of-dicts content format. This ensures strict role alternation (e.g. a converted system→user message adjacent to an existing user message gets merged). - 4. **Remove trailing assistant messages** — If the last message is + 3. **Ensure last message is user/tool** — If the last message is "assistant", remove it. OpenAI appears to silently ignore trailing assistant messages server-side, so removing them preserves equivalent behavior while satisfying Perplexity's "last message must be - user/tool" constraint. If the only remaining message is "system" - (possible when the context contains just a single system message), - convert it to "user" since Perplexity requires the last message to - be "user" or "tool". + user/tool" constraint. If the last message is "system" (e.g. the + context only contains system messages), convert it to "user". Args: messages: List of message dicts with "role" and "content" keys. @@ -104,40 +98,29 @@ class PerplexityLLMAdapter(OpenAILLMAdapter): messages = copy.deepcopy(messages) - # Step 1: Merge consecutive system messages at the start into one. - # Perplexity only allows a single initial system message, so if there - # are multiple consecutive system messages at the start, we merge them. - if messages[0].get("role") == "system": - system_end = 1 - while system_end < len(messages) and messages[system_end].get("role") == "system": - system_end += 1 - - if system_end > 1: - # Merge all initial system messages into a single message using - # list-of-dicts content format (same approach as Anthropic adapter). - merged_content = [] - for msg in messages[:system_end]: - content = msg.get("content", "") - if isinstance(content, str): - merged_content.append({"type": "text", "text": content}) - elif isinstance(content, list): - merged_content.extend(content) - messages = [{"role": "system", "content": merged_content}] + messages[system_end:] - - # Step 2: Convert non-initial system messages to "user". - # Perplexity only allows system role for the very first message. - for i in range(1, len(messages)): + # Step 1: Convert non-initial system messages to "user". + # Perplexity allows system messages at the start, but rejects them + # after any non-system message. + in_initial_system_block = True + for i in range(len(messages)): if messages[i].get("role") == "system": - messages[i]["role"] = "user" + if not in_initial_system_block: + messages[i]["role"] = "user" + else: + in_initial_system_block = False - # Step 3: Merge consecutive same-role messages. + # Step 2: Merge consecutive same-role messages. # After system→user conversions above, we may have adjacent same-role # messages that violate Perplexity's strict alternation requirement. + # Skip consecutive system messages at the start — Perplexity allows those. i = 0 while i < len(messages) - 1: current = messages[i] next_msg = messages[i + 1] - if current["role"] == next_msg["role"]: + if current["role"] == next_msg["role"] == "system": + # Perplexity allows multiple initial system messages, don't merge + i += 1 + elif current["role"] == next_msg["role"]: # Convert string content to list-of-dicts format for merging if isinstance(current.get("content"), str): current["content"] = [{"type": "text", "text": current["content"]}] @@ -152,7 +135,7 @@ class PerplexityLLMAdapter(OpenAILLMAdapter): else: i += 1 - # Step 4: Handle trailing messages. + # Step 3: Handle trailing messages. # Perplexity requires the last message to be "user" or "tool". if messages: # Remove trailing assistant messages. OpenAI appears to silently @@ -161,9 +144,9 @@ class PerplexityLLMAdapter(OpenAILLMAdapter): while messages and messages[-1].get("role") == "assistant": messages.pop() - # If the only remaining message is "system" (single system message - # in the context), convert it to "user". - if messages and len(messages) == 1 and messages[0].get("role") == "system": - messages[0]["role"] = "user" + # If the last message is "system" (e.g. the context only contains + # system messages), convert it to "user". + if messages and messages[-1].get("role") == "system": + messages[-1]["role"] = "user" return messages diff --git a/tests/test_get_llm_invocation_params.py b/tests/test_get_llm_invocation_params.py index f534d7109..6e37873d4 100644 --- a/tests/test_get_llm_invocation_params.py +++ b/tests/test_get_llm_invocation_params.py @@ -1090,8 +1090,8 @@ class TestPerplexityGetLLMInvocationParams(unittest.TestCase): self.assertEqual(merged["content"][0]["text"], "Be concise.") self.assertEqual(merged["content"][1]["text"], "Tell me about Python.") - def test_multiple_system_messages_at_start_merged(self): - """Test that multiple consecutive system messages at start are merged into one.""" + def test_multiple_system_messages_at_start_preserved(self): + """Test that multiple consecutive system messages at start pass through unchanged.""" messages: list[LLMStandardMessage] = [ {"role": "system", "content": "You are a helpful assistant."}, {"role": "system", "content": "Always be polite."}, @@ -1101,18 +1101,13 @@ class TestPerplexityGetLLMInvocationParams(unittest.TestCase): context = LLMContext(messages=messages) params = self.adapter.get_llm_invocation_params(context) - self.assertEqual(len(params["messages"]), 2) - - # First message should be merged system - system_msg = params["messages"][0] - self.assertEqual(system_msg["role"], "system") - self.assertIsInstance(system_msg["content"], list) - self.assertEqual(len(system_msg["content"]), 2) - self.assertEqual(system_msg["content"][0]["text"], "You are a helpful assistant.") - self.assertEqual(system_msg["content"][1]["text"], "Always be polite.") - - self.assertEqual(params["messages"][1]["role"], "user") - self.assertEqual(params["messages"][1]["content"], "Hello") + self.assertEqual(len(params["messages"]), 3) + self.assertEqual(params["messages"][0]["role"], "system") + self.assertEqual(params["messages"][0]["content"], "You are a helpful assistant.") + self.assertEqual(params["messages"][1]["role"], "system") + self.assertEqual(params["messages"][1]["content"], "Always be polite.") + self.assertEqual(params["messages"][2]["role"], "user") + self.assertEqual(params["messages"][2]["content"], "Hello") def test_trailing_assistant_removed(self): """Test that a trailing assistant message is removed.""" @@ -1141,6 +1136,22 @@ class TestPerplexityGetLLMInvocationParams(unittest.TestCase): self.assertEqual(params["messages"][0]["role"], "user") self.assertEqual(params["messages"][0]["content"], "You are a helpful assistant.") + def test_only_system_messages_last_converted_to_user(self): + """Test that when only system messages exist, the last one is converted to user.""" + messages: list[LLMStandardMessage] = [ + {"role": "system", "content": "You are a helpful assistant."}, + {"role": "system", "content": "Always be polite."}, + ] + + context = LLMContext(messages=messages) + params = self.adapter.get_llm_invocation_params(context) + + self.assertEqual(len(params["messages"]), 2) + self.assertEqual(params["messages"][0]["role"], "system") + self.assertEqual(params["messages"][0]["content"], "You are a helpful assistant.") + self.assertEqual(params["messages"][1]["role"], "user") + self.assertEqual(params["messages"][1]["content"], "Always be polite.") + def test_consecutive_assistants_merged_then_trailing_removed(self): """Test that consecutive assistant messages are merged, then trailing assistant is removed.""" messages: list[LLMStandardMessage] = [ From e69f5a76e1e596bb4ebfac7f93bcb0151dab04f0 Mon Sep 17 00:00:00 2001 From: Paul Kompfner Date: Thu, 12 Mar 2026 15:24:17 -0400 Subject: [PATCH 0967/1060] Add test for trailing assistant+system ordering, improve docstring Add test exercising the step 3 ordering where stripping a trailing assistant exposes a system message that then gets converted to user. Move the reasoning about when a trailing system message can occur into the docstring. --- .../adapters/services/perplexity_adapter.py | 10 ++++++---- tests/test_get_llm_invocation_params.py | 19 +++++++++++++++++++ 2 files changed, 25 insertions(+), 4 deletions(-) diff --git a/src/pipecat/adapters/services/perplexity_adapter.py b/src/pipecat/adapters/services/perplexity_adapter.py index 754716a19..b55696893 100644 --- a/src/pipecat/adapters/services/perplexity_adapter.py +++ b/src/pipecat/adapters/services/perplexity_adapter.py @@ -84,8 +84,11 @@ class PerplexityLLMAdapter(OpenAILLMAdapter): "assistant", remove it. OpenAI appears to silently ignore trailing assistant messages server-side, so removing them preserves equivalent behavior while satisfying Perplexity's "last message must be - user/tool" constraint. If the last message is "system" (e.g. the - context only contains system messages), convert it to "user". + user/tool" constraint. If the last message is "system", convert it + to "user". A trailing system message can only occur when the context + consists entirely of system messages (possibly followed by assistant + messages that were just removed), because step 1 converts any system + message that appears after a non-system message to "user". Args: messages: List of message dicts with "role" and "content" keys. @@ -144,8 +147,7 @@ class PerplexityLLMAdapter(OpenAILLMAdapter): while messages and messages[-1].get("role") == "assistant": messages.pop() - # If the last message is "system" (e.g. the context only contains - # system messages), convert it to "user". + # If the last message is "system", convert it to "user". if messages and messages[-1].get("role") == "system": messages[-1]["role"] = "user" diff --git a/tests/test_get_llm_invocation_params.py b/tests/test_get_llm_invocation_params.py index 6e37873d4..08710d77d 100644 --- a/tests/test_get_llm_invocation_params.py +++ b/tests/test_get_llm_invocation_params.py @@ -1152,6 +1152,25 @@ class TestPerplexityGetLLMInvocationParams(unittest.TestCase): self.assertEqual(params["messages"][1]["role"], "user") self.assertEqual(params["messages"][1]["content"], "Always be polite.") + def test_trailing_assistant_removed_then_system_converted(self): + """Test that trailing assistant is removed, exposing a system message that becomes user. + + This exercises the ordering of step 3: strip trailing assistants first, + then convert a trailing system to user. + """ + messages: list[LLMStandardMessage] = [ + {"role": "system", "content": "You are helpful."}, + {"role": "assistant", "content": "Sure thing."}, + ] + + context = LLMContext(messages=messages) + params = self.adapter.get_llm_invocation_params(context) + + # Trailing assistant removed → [system] → system converted to user → [user] + self.assertEqual(len(params["messages"]), 1) + self.assertEqual(params["messages"][0]["role"], "user") + self.assertEqual(params["messages"][0]["content"], "You are helpful.") + def test_consecutive_assistants_merged_then_trailing_removed(self): """Test that consecutive assistant messages are merged, then trailing assistant is removed.""" messages: list[LLMStandardMessage] = [ From 99f28120b70b5a295ad2f7dd659023764e8075f3 Mon Sep 17 00:00:00 2001 From: Paul Kompfner Date: Thu, 12 Mar 2026 16:04:46 -0400 Subject: [PATCH 0968/1060] =?UTF-8?q?Remove=20trailing=20system=E2=86=92us?= =?UTF-8?q?er=20conversion=20for=20cross-call=20stability?= MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit Perplexity appears to have statefulness within a conversation, so converting a system message to "user" in one call and then back to "system" in the next (after more messages are appended) causes API errors. Remove the trailing system→user conversion entirely — if the context only has system messages, the API call will fail but the mistake will be caught right away. --- .../adapters/services/perplexity_adapter.py | 32 +++++++-------- tests/test_get_llm_invocation_params.py | 41 ++++++++----------- 2 files changed, 31 insertions(+), 42 deletions(-) diff --git a/src/pipecat/adapters/services/perplexity_adapter.py b/src/pipecat/adapters/services/perplexity_adapter.py index b55696893..a8fbe3c18 100644 --- a/src/pipecat/adapters/services/perplexity_adapter.py +++ b/src/pipecat/adapters/services/perplexity_adapter.py @@ -80,15 +80,19 @@ class PerplexityLLMAdapter(OpenAILLMAdapter): (e.g. a converted system→user message adjacent to an existing user message gets merged). - 3. **Ensure last message is user/tool** — If the last message is + 3. **Remove trailing assistant messages** — If the last message is "assistant", remove it. OpenAI appears to silently ignore trailing assistant messages server-side, so removing them preserves equivalent behavior while satisfying Perplexity's "last message must be - user/tool" constraint. If the last message is "system", convert it - to "user". A trailing system message can only occur when the context - consists entirely of system messages (possibly followed by assistant - messages that were just removed), because step 1 converts any system - message that appears after a non-system message to "user". + user/tool" constraint. + + Note: we intentionally do *not* convert a trailing system message to + "user". That would make the transformation unstable across calls — + Perplexity appears to have statefulness/caching within a conversation, + so a message that was sent as "user" in one call but becomes "system" + in the next (once more messages are appended) causes errors. If the + context consists entirely of system messages, the Perplexity API call + will fail, but that mistake will be caught right away. Args: messages: List of message dicts with "role" and "content" keys. @@ -138,17 +142,11 @@ class PerplexityLLMAdapter(OpenAILLMAdapter): else: i += 1 - # Step 3: Handle trailing messages. + # Step 3: Remove trailing assistant messages. # Perplexity requires the last message to be "user" or "tool". - if messages: - # Remove trailing assistant messages. OpenAI appears to silently - # ignore trailing assistant messages server-side, so removing them - # preserves equivalent behavior. - while messages and messages[-1].get("role") == "assistant": - messages.pop() - - # If the last message is "system", convert it to "user". - if messages and messages[-1].get("role") == "system": - messages[-1]["role"] = "user" + # OpenAI appears to silently ignore trailing assistant messages + # server-side, so removing them preserves equivalent behavior. + while messages and messages[-1].get("role") == "assistant": + messages.pop() return messages diff --git a/tests/test_get_llm_invocation_params.py b/tests/test_get_llm_invocation_params.py index 08710d77d..9cfeb8933 100644 --- a/tests/test_get_llm_invocation_params.py +++ b/tests/test_get_llm_invocation_params.py @@ -1123,8 +1123,14 @@ class TestPerplexityGetLLMInvocationParams(unittest.TestCase): self.assertEqual(params["messages"][0]["role"], "user") self.assertEqual(params["messages"][0]["content"], "Hello") - def test_only_system_message_converted_to_user(self): - """Test that a single system message is converted to user role.""" + def test_only_system_messages_preserved(self): + """Test that system-only contexts are left unchanged (no system→user conversion). + + We intentionally do not convert trailing system messages to "user" + because that would make the transformation unstable across calls — + Perplexity has statefulness within a conversation, so a message that + was "user" in one call but becomes "system" in the next causes errors. + """ messages: list[LLMStandardMessage] = [ {"role": "system", "content": "You are a helpful assistant."}, ] @@ -1133,30 +1139,15 @@ class TestPerplexityGetLLMInvocationParams(unittest.TestCase): params = self.adapter.get_llm_invocation_params(context) self.assertEqual(len(params["messages"]), 1) - self.assertEqual(params["messages"][0]["role"], "user") - self.assertEqual(params["messages"][0]["content"], "You are a helpful assistant.") - - def test_only_system_messages_last_converted_to_user(self): - """Test that when only system messages exist, the last one is converted to user.""" - messages: list[LLMStandardMessage] = [ - {"role": "system", "content": "You are a helpful assistant."}, - {"role": "system", "content": "Always be polite."}, - ] - - context = LLMContext(messages=messages) - params = self.adapter.get_llm_invocation_params(context) - - self.assertEqual(len(params["messages"]), 2) self.assertEqual(params["messages"][0]["role"], "system") - self.assertEqual(params["messages"][0]["content"], "You are a helpful assistant.") - self.assertEqual(params["messages"][1]["role"], "user") - self.assertEqual(params["messages"][1]["content"], "Always be polite.") - def test_trailing_assistant_removed_then_system_converted(self): - """Test that trailing assistant is removed, exposing a system message that becomes user. + def test_system_exposed_after_trailing_assistant_removed(self): + """Test that a system message exposed by trailing assistant removal stays system. - This exercises the ordering of step 3: strip trailing assistants first, - then convert a trailing system to user. + It's important that initial system messages are never converted to + "user", because Perplexity has statefulness within a conversation — if + a message was sent as "system" in one call and then becomes "user" in a + later call (after more messages are appended), the API rejects it. """ messages: list[LLMStandardMessage] = [ {"role": "system", "content": "You are helpful."}, @@ -1166,9 +1157,9 @@ class TestPerplexityGetLLMInvocationParams(unittest.TestCase): context = LLMContext(messages=messages) params = self.adapter.get_llm_invocation_params(context) - # Trailing assistant removed → [system] → system converted to user → [user] + # Trailing assistant removed → [system], system stays as-is self.assertEqual(len(params["messages"]), 1) - self.assertEqual(params["messages"][0]["role"], "user") + self.assertEqual(params["messages"][0]["role"], "system") self.assertEqual(params["messages"][0]["content"], "You are helpful.") def test_consecutive_assistants_merged_then_trailing_removed(self): From de38ca626d6b11d6d11c90e88145fc8d23133da0 Mon Sep 17 00:00:00 2001 From: Mark Backman Date: Thu, 12 Mar 2026 17:19:32 -0400 Subject: [PATCH 0969/1060] Deprecate LocalSmartTurnAnalyzerV2 and LocalCoreMLSmartTurnAnalyzer Both analyzers are superseded by LocalSmartTurnAnalyzerV3. Added deprecation warnings and docstring notices following the existing pattern from LocalSmartTurnAnalyzer. --- .../turn/smart_turn/local_coreml_smart_turn.py | 14 ++++++++++++++ .../audio/turn/smart_turn/local_smart_turn.py | 2 +- .../audio/turn/smart_turn/local_smart_turn_v2.py | 14 ++++++++++++++ 3 files changed, 29 insertions(+), 1 deletion(-) diff --git a/src/pipecat/audio/turn/smart_turn/local_coreml_smart_turn.py b/src/pipecat/audio/turn/smart_turn/local_coreml_smart_turn.py index be4744c27..18310c386 100644 --- a/src/pipecat/audio/turn/smart_turn/local_coreml_smart_turn.py +++ b/src/pipecat/audio/turn/smart_turn/local_coreml_smart_turn.py @@ -10,6 +10,7 @@ This module provides a smart turn analyzer that uses CoreML models for local end-of-turn detection without requiring network connectivity. """ +import warnings from typing import Any, Dict import numpy as np @@ -35,6 +36,10 @@ class LocalCoreMLSmartTurnAnalyzer(BaseSmartTurn): Provides end-of-turn detection using locally-stored CoreML models, enabling offline operation without network dependencies. Optimized for Apple Silicon and other CoreML-compatible hardware. + + .. deprecated:: 0.0.106 + LocalCoreMLSmartTurnAnalyzer is deprecated and will be removed in a future version. + Use LocalSmartTurnAnalyzerV3 instead. """ def __init__(self, *, smart_turn_model_path: str, **kwargs): @@ -50,6 +55,15 @@ class LocalCoreMLSmartTurnAnalyzer(BaseSmartTurn): """ super().__init__(**kwargs) + with warnings.catch_warnings(): + warnings.simplefilter("always") + warnings.warn( + "LocalCoreMLSmartTurnAnalyzer is deprecated and will be removed in a future " + "version. Use LocalSmartTurnAnalyzerV3 instead.", + DeprecationWarning, + stacklevel=2, + ) + if not smart_turn_model_path: logger.error("smart_turn_model_path is not set.") raise Exception("smart_turn_model_path must be provided.") diff --git a/src/pipecat/audio/turn/smart_turn/local_smart_turn.py b/src/pipecat/audio/turn/smart_turn/local_smart_turn.py index e98c345a1..791b63af1 100644 --- a/src/pipecat/audio/turn/smart_turn/local_smart_turn.py +++ b/src/pipecat/audio/turn/smart_turn/local_smart_turn.py @@ -36,7 +36,7 @@ class LocalSmartTurnAnalyzer(BaseSmartTurn): enabling offline operation without network dependencies. Uses Wav2Vec2-BERT architecture for audio sequence classification. - .. deprecated:: 0.98.0 + .. deprecated:: 0.0.98 LocalSmartTurnAnalyzer is deprecated and will be removed in a future version. Use LocalSmartTurnAnalyzerV3 instead. """ diff --git a/src/pipecat/audio/turn/smart_turn/local_smart_turn_v2.py b/src/pipecat/audio/turn/smart_turn/local_smart_turn_v2.py index 0b2f21cba..8d584ecd2 100644 --- a/src/pipecat/audio/turn/smart_turn/local_smart_turn_v2.py +++ b/src/pipecat/audio/turn/smart_turn/local_smart_turn_v2.py @@ -10,6 +10,7 @@ This module provides a smart turn analyzer that uses PyTorch models for local end-of-turn detection without requiring network connectivity. """ +import warnings from typing import Any, Dict import numpy as np @@ -41,6 +42,10 @@ class LocalSmartTurnAnalyzerV2(BaseSmartTurn): Provides end-of-turn detection using locally-stored PyTorch models, enabling offline operation without network dependencies. Uses Wav2Vec2 architecture for audio sequence classification. + + .. deprecated:: 0.0.106 + LocalSmartTurnAnalyzerV2 is deprecated and will be removed in a future version. + Use LocalSmartTurnAnalyzerV3 instead. """ def __init__(self, *, smart_turn_model_path: str, **kwargs): @@ -53,6 +58,15 @@ class LocalSmartTurnAnalyzerV2(BaseSmartTurn): """ super().__init__(**kwargs) + with warnings.catch_warnings(): + warnings.simplefilter("always") + warnings.warn( + "LocalSmartTurnAnalyzerV2 is deprecated and will be removed in a future version. " + "Use LocalSmartTurnAnalyzerV3 instead.", + DeprecationWarning, + stacklevel=2, + ) + if not smart_turn_model_path: # Define the path to the pretrained model on Hugging Face smart_turn_model_path = "pipecat-ai/smart-turn-v2" From ed0b8dadb51dfe6a95feff693d5f8073451aa118 Mon Sep 17 00:00:00 2001 From: Mark Backman Date: Thu, 12 Mar 2026 17:22:13 -0400 Subject: [PATCH 0970/1060] Add changelog for #4012 --- changelog/4012.deprecated.md | 1 + 1 file changed, 1 insertion(+) create mode 100644 changelog/4012.deprecated.md diff --git a/changelog/4012.deprecated.md b/changelog/4012.deprecated.md new file mode 100644 index 000000000..4310b8aba --- /dev/null +++ b/changelog/4012.deprecated.md @@ -0,0 +1 @@ +- Deprecated `LocalSmartTurnAnalyzerV2` and `LocalCoreMLSmartTurnAnalyzer`. Use `LocalSmartTurnAnalyzerV3` instead. Instantiating these analyzers will now emit a `DeprecationWarning`. From 1064482ade2340549fe1d90030f783472c8dff4f Mon Sep 17 00:00:00 2001 From: Mark Backman Date: Fri, 13 Mar 2026 10:20:51 -0400 Subject: [PATCH 0971/1060] Update pipecat-ai-small-webrtc-prebuilt to 2.4.0 --- pyproject.toml | 2 +- uv.lock | 8 ++++---- 2 files changed, 5 insertions(+), 5 deletions(-) diff --git a/pyproject.toml b/pyproject.toml index 48226b14f..5a4b45646 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -106,7 +106,7 @@ remote-smart-turn = [] resembleai = [ "pipecat-ai[websockets-base]" ] rime = [ "pipecat-ai[websockets-base]" ] riva = [ "pipecat-ai[nvidia]" ] -runner = [ "python-dotenv>=1.0.0,<2.0.0", "uvicorn>=0.32.0,<1.0.0", "fastapi>=0.115.6,<1", "pipecat-ai-small-webrtc-prebuilt>=2.3.0"] +runner = [ "python-dotenv>=1.0.0,<2.0.0", "uvicorn>=0.32.0,<1.0.0", "fastapi>=0.115.6,<1", "pipecat-ai-small-webrtc-prebuilt>=2.4.0"] sagemaker = ["aws_sdk_sagemaker_runtime_http2; python_version>='3.12'"] sambanova = [] sarvam = [ "sarvamai==0.1.26", "pipecat-ai[websockets-base]" ] diff --git a/uv.lock b/uv.lock index b68216261..079d7df2a 100644 --- a/uv.lock +++ b/uv.lock @@ -4855,7 +4855,7 @@ requires-dist = [ { name = "pipecat-ai", extras = ["websockets-base"], marker = "extra == 'ultravox'" }, { name = "pipecat-ai", extras = ["websockets-base"], marker = "extra == 'websocket'" }, { name = "pipecat-ai-krisp", marker = "extra == 'krisp'", specifier = "~=0.4.0" }, - { name = "pipecat-ai-small-webrtc-prebuilt", marker = "extra == 'runner'", specifier = ">=2.3.0" }, + { name = "pipecat-ai-small-webrtc-prebuilt", marker = "extra == 'runner'", specifier = ">=2.4.0" }, { name = "piper-tts", marker = "extra == 'piper'", specifier = ">=1.3.0,<2" }, { name = "protobuf", specifier = "~=5.29.6" }, { name = "pvkoala", marker = "extra == 'koala'", specifier = "~=2.0.3" }, @@ -4927,14 +4927,14 @@ sdist = { url = "https://files.pythonhosted.org/packages/1d/37/0f1d11d1dc33234a3 [[package]] name = "pipecat-ai-small-webrtc-prebuilt" -version = "2.3.0" +version = "2.4.0" source = { registry = "https://pypi.org/simple" } dependencies = [ { name = "fastapi", extra = ["all"] }, ] -sdist = { url = "https://files.pythonhosted.org/packages/2e/5f/b0f73bbc6997c22655f0495ce21a4cb176e192df1b5407f66fad8101c697/pipecat_ai_small_webrtc_prebuilt-2.3.0.tar.gz", hash = "sha256:10dc31db9978d68001ae941066fe460c533412a8984df71e5416d4ebeb9c0371", size = 469001, upload-time = "2026-02-25T17:18:43.316Z" } +sdist = { url = "https://files.pythonhosted.org/packages/ba/02/1e6e90f084ebb1fc954f37661c4614219e4c9fec3d305c8abe5141707b0c/pipecat_ai_small_webrtc_prebuilt-2.4.0.tar.gz", hash = "sha256:c5eddca4e061afb7c5f98cf52ccb85511978a8c834447f6c6d662029e02950c4", size = 472449, upload-time = "2026-03-13T14:17:08.164Z" } wheels = [ - { url = "https://files.pythonhosted.org/packages/5a/bc/6193b639a53f4bac1c0fe29b1f8e0d49085c60e457b02a01e725eb7c093f/pipecat_ai_small_webrtc_prebuilt-2.3.0-py3-none-any.whl", hash = "sha256:b3ddaff8bbd56746fe3c58a2d721d3ccc94d17a33c16d78dcbce73d7526c1a05", size = 468881, upload-time = "2026-02-25T17:18:41.869Z" }, + { url = "https://files.pythonhosted.org/packages/25/77/8f6f67142a153943fff31530d51dcf7a2374c39dfa9aba6ef163bf0c622f/pipecat_ai_small_webrtc_prebuilt-2.4.0-py3-none-any.whl", hash = "sha256:9e9a3aa24231b1bf4101a6a2b42c4164a186c0c3d3e49bd51f77280eaa402d12", size = 472792, upload-time = "2026-03-13T14:17:06.556Z" }, ] [[package]] From 7365ebfdf937832986395191e6d5f3a62585221c Mon Sep 17 00:00:00 2001 From: Mark Backman Date: Fri, 13 Mar 2026 10:22:58 -0400 Subject: [PATCH 0972/1060] Add changelog for #4023 --- changelog/4023.changed.md | 1 + 1 file changed, 1 insertion(+) create mode 100644 changelog/4023.changed.md diff --git a/changelog/4023.changed.md b/changelog/4023.changed.md new file mode 100644 index 000000000..7756f20b8 --- /dev/null +++ b/changelog/4023.changed.md @@ -0,0 +1 @@ +- Update `pipecat-ai-small-webrtc-prebuilt` to `2.4.0`. From 8467058e48e8206961598b1e5f991cb20cd19d33 Mon Sep 17 00:00:00 2001 From: Mark Backman Date: Fri, 13 Mar 2026 10:56:33 -0400 Subject: [PATCH 0973/1060] Fix Language enum conversion at init time in base TTS/STT services When a Language enum (e.g. Language.ES) is passed via settings=Service.Settings(language=Language.ES), it gets stored as-is without conversion to the service-specific code. The base _update_settings() handles this for runtime updates, but at init time apply_update() copies the raw enum. This causes API errors because services send the unconverted enum value. Add language conversion in TTSService.__init__ and STTService.__init__ after super().__init__(), using the subclass language_to_service_language() via normal method resolution. --- src/pipecat/services/stt_service.py | 9 +++++++++ src/pipecat/services/tts_service.py | 8 ++++++++ 2 files changed, 17 insertions(+) diff --git a/src/pipecat/services/stt_service.py b/src/pipecat/services/stt_service.py index a16aa0eaa..c442c41eb 100644 --- a/src/pipecat/services/stt_service.py +++ b/src/pipecat/services/stt_service.py @@ -120,6 +120,15 @@ class STTService(AIService): or STTSettings(), **kwargs, ) + + # Convert Language enum to service-specific format at init time. + # Runtime updates are handled by _update_settings(), but init-time + # settings bypass that path and need explicit conversion. + if isinstance(self._settings.language, Language): + converted = self.language_to_service_language(self._settings.language) + if converted is not None: + self._settings.language = converted + self._audio_passthrough = audio_passthrough self._init_sample_rate = sample_rate self._sample_rate = 0 diff --git a/src/pipecat/services/tts_service.py b/src/pipecat/services/tts_service.py index 44fb98826..e2a9190ab 100644 --- a/src/pipecat/services/tts_service.py +++ b/src/pipecat/services/tts_service.py @@ -245,6 +245,14 @@ class TTSService(AIService): **kwargs, ) + # Convert Language enum to service-specific format at init time. + # Runtime updates are handled by _update_settings(), but init-time + # settings bypass that path and need explicit conversion. + if isinstance(self._settings.language, Language): + converted = self.language_to_service_language(self._settings.language) + if converted is not None: + self._settings.language = converted + # Resolve text_aggregation_mode from the new param or deprecated aggregate_sentences if aggregate_sentences is not None: import warnings From 9f2f73b6b4a14af8ab077a464d8d9bab6f211eec Mon Sep 17 00:00:00 2001 From: Mark Backman Date: Fri, 13 Mar 2026 10:57:04 -0400 Subject: [PATCH 0974/1060] Remove redundant per-service language conversion from subclasses Now that the base TTSService and STTService handle Language enum conversion at init time, subclasses no longer need to convert in their own __init__ methods. Remove conversion calls from hardcoded defaults, params paths, and deprecated direct arg paths across 22 service files. Services just pass raw Language enums and let the base class convert via language_to_service_language() polymorphic dispatch. --- src/pipecat/services/asyncai/tts.py | 8 ++------ src/pipecat/services/aws/stt.py | 4 ++-- src/pipecat/services/aws/tts.py | 6 +----- src/pipecat/services/azure/stt.py | 4 ++-- src/pipecat/services/azure/tts.py | 12 ++---------- src/pipecat/services/camb/tts.py | 4 +--- src/pipecat/services/cartesia/tts.py | 8 ++++---- src/pipecat/services/elevenlabs/stt.py | 4 ++-- src/pipecat/services/elevenlabs/tts.py | 4 ++-- src/pipecat/services/fal/stt.py | 4 ++-- src/pipecat/services/google/tts.py | 6 +++--- src/pipecat/services/groq/stt.py | 4 ++-- src/pipecat/services/kokoro/tts.py | 4 ++-- src/pipecat/services/lmnt/tts.py | 2 +- src/pipecat/services/neuphonic/tts.py | 8 ++++---- src/pipecat/services/nvidia/stt.py | 6 ++---- src/pipecat/services/openai/stt.py | 2 +- src/pipecat/services/rime/tts.py | 12 +++--------- src/pipecat/services/sambanova/stt.py | 4 ++-- src/pipecat/services/sarvam/tts.py | 16 ++-------------- src/pipecat/services/whisper/base_stt.py | 2 +- src/pipecat/services/xtts/tts.py | 2 +- 22 files changed, 44 insertions(+), 82 deletions(-) diff --git a/src/pipecat/services/asyncai/tts.py b/src/pipecat/services/asyncai/tts.py index 42c0a09a4..d2ac74445 100644 --- a/src/pipecat/services/asyncai/tts.py +++ b/src/pipecat/services/asyncai/tts.py @@ -171,9 +171,7 @@ class AsyncAITTSService(WebsocketTTSService): if params is not None: self._warn_init_param_moved_to_settings("params") if not settings: - default_settings.language = ( - self.language_to_service_language(params.language) if params.language else None - ) + default_settings.language = params.language # 4. Apply settings delta (canonical API, always wins) if settings is not None: @@ -565,9 +563,7 @@ class AsyncAIHttpTTSService(TTSService): if params is not None: self._warn_init_param_moved_to_settings("params") if not settings: - default_settings.language = ( - self.language_to_service_language(params.language) if params.language else None - ) + default_settings.language = params.language # 4. Apply settings delta (canonical API, always wins) if settings is not None: diff --git a/src/pipecat/services/aws/stt.py b/src/pipecat/services/aws/stt.py index eed1a321d..ace05090d 100644 --- a/src/pipecat/services/aws/stt.py +++ b/src/pipecat/services/aws/stt.py @@ -100,13 +100,13 @@ class AWSTranscribeSTTService(WebsocketSTTService): # 1. Initialize default_settings with hardcoded defaults default_settings = self.Settings( model=None, - language=self.language_to_service_language(Language.EN), + language=Language.EN, ) # 2. Apply direct init arg overrides (deprecated) if language is not None: self._warn_init_param_moved_to_settings("language", "language") - default_settings.language = self.language_to_service_language(language) + default_settings.language = language # 3. (No step 3, as there's no params object to apply) diff --git a/src/pipecat/services/aws/tts.py b/src/pipecat/services/aws/tts.py index 9648c45c8..32266886e 100644 --- a/src/pipecat/services/aws/tts.py +++ b/src/pipecat/services/aws/tts.py @@ -230,11 +230,7 @@ class AWSPollyTTSService(TTSService): self._warn_init_param_moved_to_settings("params") if not settings: default_settings.engine = params.engine - default_settings.language = ( - self.language_to_service_language(params.language) - if params.language - else "en-US" - ) + default_settings.language = params.language if params.language else "en-US" default_settings.pitch = params.pitch default_settings.rate = params.rate default_settings.volume = params.volume diff --git a/src/pipecat/services/azure/stt.py b/src/pipecat/services/azure/stt.py index 857b166cb..57306e06a 100644 --- a/src/pipecat/services/azure/stt.py +++ b/src/pipecat/services/azure/stt.py @@ -106,13 +106,13 @@ class AzureSTTService(STTService): # 1. Initialize default_settings with hardcoded defaults default_settings = self.Settings( model=None, - language=language_to_azure_language(Language.EN_US), + language=Language.EN_US, ) # 2. Apply direct init arg overrides (deprecated) if language is not None and language != Language.EN_US: self._warn_init_param_moved_to_settings("language", "language") - default_settings.language = language_to_azure_language(language) + default_settings.language = language # 3. (No step 3, as there's no params object to apply) diff --git a/src/pipecat/services/azure/tts.py b/src/pipecat/services/azure/tts.py index 0130ef5cb..a9491e9aa 100644 --- a/src/pipecat/services/azure/tts.py +++ b/src/pipecat/services/azure/tts.py @@ -312,11 +312,7 @@ class AzureTTSService(TTSService, AzureBaseTTSService): self._warn_init_param_moved_to_settings("params") if not settings: default_settings.emphasis = params.emphasis - default_settings.language = ( - self.language_to_service_language(params.language) - if params.language - else "en-US" - ) + default_settings.language = params.language if params.language else "en-US" default_settings.pitch = params.pitch default_settings.rate = params.rate default_settings.role = params.role @@ -809,11 +805,7 @@ class AzureHttpTTSService(TTSService, AzureBaseTTSService): self._warn_init_param_moved_to_settings("params") if not settings: default_settings.emphasis = params.emphasis - default_settings.language = ( - self.language_to_service_language(params.language) - if params.language - else "en-US" - ) + default_settings.language = params.language if params.language else "en-US" default_settings.pitch = params.pitch default_settings.rate = params.rate default_settings.role = params.role diff --git a/src/pipecat/services/camb/tts.py b/src/pipecat/services/camb/tts.py index 9c360ed37..b6b83a928 100644 --- a/src/pipecat/services/camb/tts.py +++ b/src/pipecat/services/camb/tts.py @@ -260,9 +260,7 @@ class CambTTSService(TTSService): self._warn_init_param_moved_to_settings("params") if not settings: if params.language is not None: - default_settings.language = ( - self.language_to_service_language(params.language) or "en-us" - ) + default_settings.language = params.language if params.user_instructions is not None: default_settings.user_instructions = params.user_instructions diff --git a/src/pipecat/services/cartesia/tts.py b/src/pipecat/services/cartesia/tts.py index aca5c46c6..b713a0d9a 100644 --- a/src/pipecat/services/cartesia/tts.py +++ b/src/pipecat/services/cartesia/tts.py @@ -302,7 +302,7 @@ class CartesiaTTSService(WebsocketTTSService): default_settings = self.Settings( model="sonic-3", voice=None, - language=language_to_cartesia_language(Language.EN), + language=Language.EN, generation_config=None, pronunciation_dict_id=None, ) @@ -320,7 +320,7 @@ class CartesiaTTSService(WebsocketTTSService): self._warn_init_param_moved_to_settings("params") if not settings: if params.language is not None: - default_settings.language = self.language_to_service_language(params.language) + default_settings.language = params.language if params.generation_config is not None: default_settings.generation_config = params.generation_config if params.pronunciation_dict_id is not None: @@ -749,7 +749,7 @@ class CartesiaHttpTTSService(TTSService): default_settings = self.Settings( model="sonic-3", voice=None, - language=language_to_cartesia_language(Language.EN), + language=Language.EN, generation_config=None, pronunciation_dict_id=None, ) @@ -767,7 +767,7 @@ class CartesiaHttpTTSService(TTSService): self._warn_init_param_moved_to_settings("params") if not settings: if params.language is not None: - default_settings.language = self.language_to_service_language(params.language) + default_settings.language = params.language if params.generation_config is not None: default_settings.generation_config = params.generation_config if params.pronunciation_dict_id is not None: diff --git a/src/pipecat/services/elevenlabs/stt.py b/src/pipecat/services/elevenlabs/stt.py index daca9be3d..aa7fd0659 100644 --- a/src/pipecat/services/elevenlabs/stt.py +++ b/src/pipecat/services/elevenlabs/stt.py @@ -272,7 +272,7 @@ class ElevenLabsSTTService(SegmentedSTTService): # 1. Initialize default_settings with hardcoded defaults default_settings = self.Settings( model="scribe_v2", - language=language_to_elevenlabs_language(Language.EN), + language=Language.EN, tag_audio_events=None, ) @@ -286,7 +286,7 @@ class ElevenLabsSTTService(SegmentedSTTService): self._warn_init_param_moved_to_settings("params") if not settings: if params.language is not None: - default_settings.language = language_to_elevenlabs_language(params.language) + default_settings.language = params.language default_settings.tag_audio_events = params.tag_audio_events # 4. Apply settings delta (canonical API, always wins) diff --git a/src/pipecat/services/elevenlabs/tts.py b/src/pipecat/services/elevenlabs/tts.py index 8cfd1abe2..866d0405f 100644 --- a/src/pipecat/services/elevenlabs/tts.py +++ b/src/pipecat/services/elevenlabs/tts.py @@ -449,7 +449,7 @@ class ElevenLabsTTSService(WebsocketTTSService): self._warn_init_param_moved_to_settings("params") if not settings: if params.language is not None: - default_settings.language = self.language_to_service_language(params.language) + default_settings.language = params.language if params.stability is not None: default_settings.stability = params.stability if params.similarity_boost is not None: @@ -1014,7 +1014,7 @@ class ElevenLabsHttpTTSService(TTSService): self._warn_init_param_moved_to_settings("params") if not settings: if params.language is not None: - default_settings.language = self.language_to_service_language(params.language) + default_settings.language = params.language if params.optimize_streaming_latency is not None: default_settings.optimize_streaming_latency = params.optimize_streaming_latency if params.stability is not None: diff --git a/src/pipecat/services/fal/stt.py b/src/pipecat/services/fal/stt.py index 7bfcfbcfd..65df7e3ab 100644 --- a/src/pipecat/services/fal/stt.py +++ b/src/pipecat/services/fal/stt.py @@ -216,7 +216,7 @@ class FalSTTService(SegmentedSTTService): # 1. Initialize default_settings with hardcoded defaults default_settings = self.Settings( model=None, - language=language_to_fal_language(Language.EN), + language=Language.EN, ) # 2. (no deprecated direct args for this service) @@ -226,7 +226,7 @@ class FalSTTService(SegmentedSTTService): self._warn_init_param_moved_to_settings("params") if not settings: if params.language is not None: - default_settings.language = language_to_fal_language(params.language) + default_settings.language = params.language if params.task != "transcribe": task = params.task if params.chunk_level != "segment": diff --git a/src/pipecat/services/google/tts.py b/src/pipecat/services/google/tts.py index 3455a8125..93053cc94 100644 --- a/src/pipecat/services/google/tts.py +++ b/src/pipecat/services/google/tts.py @@ -653,7 +653,7 @@ class GoogleHttpTTSService(TTSService): if params.emphasis is not None: default_settings.emphasis = params.emphasis if params.language is not None: - default_settings.language = self.language_to_service_language(params.language) + default_settings.language = params.language if params.gender is not None: default_settings.gender = params.gender if params.google_style is not None: @@ -1090,7 +1090,7 @@ class GoogleTTSService(GoogleBaseTTSService): self._warn_init_param_moved_to_settings("params") if not settings: if params.language is not None: - default_settings.language = self.language_to_service_language(params.language) + default_settings.language = params.language if params.speaking_rate is not None: default_settings.speaking_rate = params.speaking_rate @@ -1346,7 +1346,7 @@ class GeminiTTSService(GoogleBaseTTSService): self._warn_init_param_moved_to_settings("params") if not settings: if params.language is not None: - default_settings.language = self.language_to_service_language(params.language) + default_settings.language = params.language if params.prompt is not None: default_settings.prompt = params.prompt if params.multi_speaker is not None: diff --git a/src/pipecat/services/groq/stt.py b/src/pipecat/services/groq/stt.py index 6ff4075ae..3f6c23774 100644 --- a/src/pipecat/services/groq/stt.py +++ b/src/pipecat/services/groq/stt.py @@ -85,7 +85,7 @@ class GroqSTTService(BaseWhisperSTTService): # --- 1. Hardcoded defaults --- default_settings = self.Settings( model="whisper-large-v3-turbo", - language=self.language_to_service_language(Language.EN), + language=Language.EN, prompt=None, temperature=None, ) @@ -96,7 +96,7 @@ class GroqSTTService(BaseWhisperSTTService): default_settings.model = model if language is not None: self._warn_init_param_moved_to_settings("language", "language") - default_settings.language = self.language_to_service_language(language) + default_settings.language = language if prompt is not None: self._warn_init_param_moved_to_settings("prompt", "prompt") default_settings.prompt = prompt diff --git a/src/pipecat/services/kokoro/tts.py b/src/pipecat/services/kokoro/tts.py index 34e703dab..4756d4e74 100644 --- a/src/pipecat/services/kokoro/tts.py +++ b/src/pipecat/services/kokoro/tts.py @@ -150,7 +150,7 @@ class KokoroTTSService(TTSService): default_settings = self.Settings( model=None, voice=None, - language=language_to_kokoro_language(Language.EN), + language=Language.EN, ) # 2. Apply direct init arg overrides (deprecated) @@ -162,7 +162,7 @@ class KokoroTTSService(TTSService): if params is not None: self._warn_init_param_moved_to_settings("params") if not settings: - default_settings.language = language_to_kokoro_language(params.language) + default_settings.language = params.language # 4. Apply settings delta (canonical API, always wins) if settings is not None: diff --git a/src/pipecat/services/lmnt/tts.py b/src/pipecat/services/lmnt/tts.py index 0ca91a107..5fe574c5a 100644 --- a/src/pipecat/services/lmnt/tts.py +++ b/src/pipecat/services/lmnt/tts.py @@ -129,7 +129,7 @@ class LmntTTSService(InterruptibleTTSService): default_settings = self.Settings( model="aurora", voice=None, - language=self.language_to_service_language(language), + language=language, ) # 2. Apply direct init arg overrides (deprecated) diff --git a/src/pipecat/services/neuphonic/tts.py b/src/pipecat/services/neuphonic/tts.py index b345a0ff4..6fb9d3e28 100644 --- a/src/pipecat/services/neuphonic/tts.py +++ b/src/pipecat/services/neuphonic/tts.py @@ -153,7 +153,7 @@ class NeuphonicTTSService(InterruptibleTTSService): default_settings = self.Settings( model=None, voice=None, - language=self.language_to_service_language(Language.EN), + language=Language.EN, speed=1.0, ) @@ -167,7 +167,7 @@ class NeuphonicTTSService(InterruptibleTTSService): self._warn_init_param_moved_to_settings("params") if not settings: if params.language is not None: - default_settings.language = self.language_to_service_language(params.language) + default_settings.language = params.language if params.speed is not None: default_settings.speed = params.speed @@ -487,7 +487,7 @@ class NeuphonicHttpTTSService(TTSService): default_settings = self.Settings( model=None, voice=None, - language=self.language_to_service_language(Language.EN), + language=Language.EN, speed=1.0, ) @@ -501,7 +501,7 @@ class NeuphonicHttpTTSService(TTSService): self._warn_init_param_moved_to_settings("params") if not settings: if params.language is not None: - default_settings.language = self.language_to_service_language(params.language) + default_settings.language = params.language if params.speed is not None: default_settings.speed = params.speed diff --git a/src/pipecat/services/nvidia/stt.py b/src/pipecat/services/nvidia/stt.py index fcca14741..50a654191 100644 --- a/src/pipecat/services/nvidia/stt.py +++ b/src/pipecat/services/nvidia/stt.py @@ -503,7 +503,7 @@ class NvidiaSegmentedSTTService(SegmentedSTTService): # 1. Initialize default_settings with hardcoded defaults default_settings = self.Settings( model=model_function_map.get("model_name"), - language=language_to_nvidia_riva_language(Language.EN_US) or "en-US", + language=Language.EN_US, profanity_filter=False, automatic_punctuation=True, verbatim_transcripts=False, @@ -517,9 +517,7 @@ class NvidiaSegmentedSTTService(SegmentedSTTService): if params is not None: self._warn_init_param_moved_to_settings("params") if not settings: - default_settings.language = ( - language_to_nvidia_riva_language(params.language or Language.EN_US) or "en-US" - ) + default_settings.language = params.language or Language.EN_US default_settings.profanity_filter = params.profanity_filter default_settings.automatic_punctuation = params.automatic_punctuation default_settings.verbatim_transcripts = params.verbatim_transcripts diff --git a/src/pipecat/services/openai/stt.py b/src/pipecat/services/openai/stt.py index 39ca60b25..68ab7e067 100644 --- a/src/pipecat/services/openai/stt.py +++ b/src/pipecat/services/openai/stt.py @@ -119,7 +119,7 @@ class OpenAISTTService(BaseWhisperSTTService): _language = language or Language.EN default_settings = self.Settings( model="gpt-4o-transcribe", - language=self.language_to_service_language(_language), + language=_language, prompt=None, temperature=None, ) diff --git a/src/pipecat/services/rime/tts.py b/src/pipecat/services/rime/tts.py index 24a5d152b..aec5630b6 100644 --- a/src/pipecat/services/rime/tts.py +++ b/src/pipecat/services/rime/tts.py @@ -251,9 +251,7 @@ class RimeTTSService(WebsocketTTSService): if params is not None: self._warn_init_param_moved_to_settings("params") if not settings: - default_settings.language = ( - self.language_to_service_language(params.language) if params.language else None - ) + default_settings.language = params.language default_settings.segment = params.segment default_settings.speedAlpha = params.speed_alpha # Arcana params @@ -754,9 +752,7 @@ class RimeHttpTTSService(TTSService): if params is not None: self._warn_init_param_moved_to_settings("params") if not settings: - default_settings.language = ( - self.language_to_service_language(params.language) if params.language else "eng" - ) + default_settings.language = params.language default_settings.speedAlpha = params.speed_alpha default_settings.reduceLatency = params.reduce_latency default_settings.pauseBetweenBrackets = params.pause_between_brackets @@ -984,9 +980,7 @@ class RimeNonJsonTTSService(InterruptibleTTSService): if params is not None: self._warn_init_param_moved_to_settings("params") if not settings: - default_settings.language = ( - self.language_to_service_language(params.language) if params.language else None - ) + default_settings.language = params.language default_settings.segment = params.segment default_settings.repetition_penalty = params.repetition_penalty default_settings.temperature = params.temperature diff --git a/src/pipecat/services/sambanova/stt.py b/src/pipecat/services/sambanova/stt.py index d3a77b4eb..5cf12d771 100644 --- a/src/pipecat/services/sambanova/stt.py +++ b/src/pipecat/services/sambanova/stt.py @@ -82,7 +82,7 @@ class SambaNovaSTTService(BaseWhisperSTTService): # type: ignore # --- 1. Hardcoded defaults --- default_settings = self.Settings( model="Whisper-Large-v3", - language=self.language_to_service_language(Language.EN), + language=Language.EN, prompt=None, temperature=None, ) @@ -93,7 +93,7 @@ class SambaNovaSTTService(BaseWhisperSTTService): # type: ignore default_settings.model = model if language is not None: self._warn_init_param_moved_to_settings("language", "language") - default_settings.language = self.language_to_service_language(language) + default_settings.language = language if prompt is not None: self._warn_init_param_moved_to_settings("prompt", "prompt") default_settings.prompt = prompt diff --git a/src/pipecat/services/sarvam/tts.py b/src/pipecat/services/sarvam/tts.py index 91ee088cf..c926270de 100644 --- a/src/pipecat/services/sarvam/tts.py +++ b/src/pipecat/services/sarvam/tts.py @@ -473,9 +473,7 @@ class SarvamHttpTTSService(TTSService): self._warn_init_param_moved_to_settings("params") if not settings: if params.language is not None: - default_settings.language = ( - self.language_to_service_language(params.language) or "en-IN" - ) + default_settings.language = params.language if params.enable_preprocessing is not None: default_settings.enable_preprocessing = params.enable_preprocessing if params.pace is not None: @@ -491,10 +489,6 @@ class SarvamHttpTTSService(TTSService): if settings is not None: default_settings.apply_update(settings) - # Convert Language enum to service-specific string - if isinstance(default_settings.language, Language): - default_settings.language = self.language_to_service_language(default_settings.language) - # Get model configuration (validates model exists) resolved_model = default_settings.model if resolved_model not in TTS_MODEL_CONFIGS: @@ -889,9 +883,7 @@ class SarvamTTSService(InterruptibleTTSService): self._warn_init_param_moved_to_settings("params") if not settings: if params.language is not None: - default_settings.language = ( - self.language_to_service_language(params.language) or "en-IN" - ) + default_settings.language = params.language if params.enable_preprocessing is not None: default_settings.enable_preprocessing = params.enable_preprocessing if params.min_buffer_size is not None: @@ -915,10 +907,6 @@ class SarvamTTSService(InterruptibleTTSService): if settings is not None: default_settings.apply_update(settings) - # Convert Language enum to service-specific string - if isinstance(default_settings.language, Language): - default_settings.language = self.language_to_service_language(default_settings.language) - # Get model configuration (validates model exists) resolved_model = default_settings.model if resolved_model not in TTS_MODEL_CONFIGS: diff --git a/src/pipecat/services/whisper/base_stt.py b/src/pipecat/services/whisper/base_stt.py index 93bb5de34..33d19b0aa 100644 --- a/src/pipecat/services/whisper/base_stt.py +++ b/src/pipecat/services/whisper/base_stt.py @@ -194,7 +194,7 @@ class BaseWhisperSTTService(SegmentedSTTService): default_settings.model = model if language is not None: self._warn_init_param_moved_to_settings("language", "language") - default_settings.language = self.language_to_service_language(language) + default_settings.language = language if prompt is not None: self._warn_init_param_moved_to_settings("prompt", "prompt") default_settings.prompt = prompt diff --git a/src/pipecat/services/xtts/tts.py b/src/pipecat/services/xtts/tts.py index 099fce65c..1c3feedb6 100644 --- a/src/pipecat/services/xtts/tts.py +++ b/src/pipecat/services/xtts/tts.py @@ -117,7 +117,7 @@ class XTTSService(TTSService): default_settings = self.Settings( model=None, voice=None, - language=self.language_to_service_language(language), + language=language, ) # 2. Apply direct init arg overrides (deprecated) From 1ea23ad362ea264f6b7a1f34a3e7fc90089496cd Mon Sep 17 00:00:00 2001 From: Mark Backman Date: Fri, 13 Mar 2026 10:58:51 -0400 Subject: [PATCH 0975/1060] Add changelog for #4024 --- changelog/4024.fixed.md | 1 + 1 file changed, 1 insertion(+) create mode 100644 changelog/4024.fixed.md diff --git a/changelog/4024.fixed.md b/changelog/4024.fixed.md new file mode 100644 index 000000000..7654cbdf5 --- /dev/null +++ b/changelog/4024.fixed.md @@ -0,0 +1 @@ +- Fixed `Language` enum values (e.g. `Language.ES`) not being converted to service-specific codes when passed via `settings=Service.Settings(language=Language.ES)` at init time. This caused API errors (e.g. 400 from Rime) because the raw enum was sent instead of the expected language code (e.g. `"spa"`). Runtime updates via `UpdateSettingsFrame` were unaffected. The fix centralizes conversion in the base `TTSService` and `STTService` classes so all services handle this consistently. From 0ec5f5e5ac528c89872c49a5fb9c8a3fde8fd72c Mon Sep 17 00:00:00 2001 From: Mark Backman Date: Fri, 13 Mar 2026 11:33:59 -0400 Subject: [PATCH 0976/1060] Add missing language deprecations for XTTSService, LmntTTSService --- src/pipecat/services/lmnt/tts.py | 9 ++++++++- src/pipecat/services/xtts/tts.py | 9 ++++++++- 2 files changed, 16 insertions(+), 2 deletions(-) diff --git a/src/pipecat/services/lmnt/tts.py b/src/pipecat/services/lmnt/tts.py index 5fe574c5a..29d0b60ca 100644 --- a/src/pipecat/services/lmnt/tts.py +++ b/src/pipecat/services/lmnt/tts.py @@ -114,6 +114,10 @@ class LmntTTSService(InterruptibleTTSService): sample_rate: Audio sample rate. If None, uses default. language: Language for synthesis. Defaults to English. + + .. deprecated:: 0.0.106 + Use ``settings=LmntTTSService.Settings(language=...)`` instead. + output_format: Audio output format. One of "pcm_s16le", "pcm_f32le", "mp3", "ulaw", "webm". Defaults to "pcm_s16le". model: TTS model to use. @@ -129,13 +133,16 @@ class LmntTTSService(InterruptibleTTSService): default_settings = self.Settings( model="aurora", voice=None, - language=language, + language=Language.EN, ) # 2. Apply direct init arg overrides (deprecated) if voice_id is not None: self._warn_init_param_moved_to_settings("voice_id", "voice") default_settings.voice = voice_id + if language is not None: + self._warn_init_param_moved_to_settings("language", "language") + default_settings.language = language if model is not None: self._warn_init_param_moved_to_settings("model", "model") default_settings.model = model diff --git a/src/pipecat/services/xtts/tts.py b/src/pipecat/services/xtts/tts.py index 1c3feedb6..b164f8945 100644 --- a/src/pipecat/services/xtts/tts.py +++ b/src/pipecat/services/xtts/tts.py @@ -108,6 +108,10 @@ class XTTSService(TTSService): base_url: Base URL of the XTTS streaming server. aiohttp_session: HTTP session for making requests to the server. language: Language for synthesis. Defaults to English. + + .. deprecated:: 0.0.106 + Use ``settings=XTTSService.Settings(language=...)`` instead. + sample_rate: Audio sample rate. If None, uses default. settings: Runtime-updatable settings. When provided alongside deprecated parameters, ``settings`` values take precedence. @@ -117,13 +121,16 @@ class XTTSService(TTSService): default_settings = self.Settings( model=None, voice=None, - language=language, + language=Language.EN, ) # 2. Apply direct init arg overrides (deprecated) if voice_id is not None: self._warn_init_param_moved_to_settings("voice_id", "voice") default_settings.voice = voice_id + if language is not None: + self._warn_init_param_moved_to_settings("language", "language") + default_settings.language = language # 3. (No step 3, as there's no params object to apply) From 978a1a2083bb5ee3e29342522e7580cd97be108a Mon Sep 17 00:00:00 2001 From: Mark Backman Date: Fri, 13 Mar 2026 12:22:10 -0400 Subject: [PATCH 0977/1060] Update the system_instruction wording in the foundational examples to not mention WebRTC call --- examples/foundational/02-llm-say-one-thing.py | 2 +- examples/foundational/04-transports-small-webrtc.py | 2 +- examples/foundational/04a-transports-daily.py | 2 +- examples/foundational/04b-transports-livekit.py | 2 +- examples/foundational/06-listen-and-respond.py | 2 +- examples/foundational/06a-image-sync.py | 2 +- examples/foundational/07-interruptible-cartesia-http.py | 2 +- examples/foundational/07-interruptible.py | 2 +- examples/foundational/07a-interruptible-speechmatics-vad.py | 2 +- examples/foundational/07a-interruptible-speechmatics.py | 2 +- examples/foundational/07b-interruptible-langchain.py | 3 +-- examples/foundational/07c-interruptible-deepgram-flux.py | 2 +- examples/foundational/07c-interruptible-deepgram-http.py | 2 +- examples/foundational/07c-interruptible-deepgram-sagemaker.py | 2 +- examples/foundational/07c-interruptible-deepgram-vad.py | 2 +- examples/foundational/07c-interruptible-deepgram.py | 2 +- examples/foundational/07d-interruptible-elevenlabs-http.py | 2 +- examples/foundational/07d-interruptible-elevenlabs.py | 2 +- examples/foundational/07f-interruptible-azure-http.py | 2 +- examples/foundational/07f-interruptible-azure.py | 2 +- examples/foundational/07h-interruptible-openpipe.py | 2 +- examples/foundational/07i-interruptible-xtts.py | 2 +- examples/foundational/07j-interruptible-gladia-vad.py | 2 +- examples/foundational/07j-interruptible-gladia.py | 2 +- examples/foundational/07k-interruptible-lmnt.py | 2 +- examples/foundational/07l-interruptible-groq.py | 2 +- examples/foundational/07m-interruptible-aws.py | 2 +- examples/foundational/07n-interruptible-gemini-image.py | 2 +- examples/foundational/07n-interruptible-gemini.py | 4 ++-- examples/foundational/07n-interruptible-google-http.py | 2 +- examples/foundational/07n-interruptible-google.py | 2 +- .../07o-interruptible-assemblyai-turn-detection.py | 2 +- examples/foundational/07o-interruptible-assemblyai.py | 2 +- examples/foundational/07p-interruptible-krisp-viva.py | 2 +- examples/foundational/07p-interruptible-krisp.py | 2 +- examples/foundational/07q-interruptible-rime-http.py | 2 +- examples/foundational/07q-interruptible-rime.py | 2 +- examples/foundational/07r-interruptible-nvidia.py | 2 +- examples/foundational/07s-interruptible-google-audio-in.py | 2 +- examples/foundational/07t-interruptible-fish.py | 2 +- examples/foundational/07v-interruptible-neuphonic-http.py | 2 +- examples/foundational/07v-interruptible-neuphonic.py | 2 +- examples/foundational/07w-interruptible-fal.py | 2 +- examples/foundational/07x-interruptible-local.py | 2 +- examples/foundational/07y-interruptible-minimax.py | 2 +- examples/foundational/07z-interruptible-sarvam-http.py | 2 +- examples/foundational/07z-interruptible-sarvam.py | 2 +- examples/foundational/07za-interruptible-soniox.py | 2 +- examples/foundational/07zc-interruptible-asyncai-http.py | 2 +- examples/foundational/07zc-interruptible-asyncai.py | 2 +- examples/foundational/07zd-interruptible-aicoustics.py | 2 +- examples/foundational/07ze-interruptible-hume.py | 2 +- examples/foundational/07zf-interruptible-gradium.py | 2 +- examples/foundational/07zg-interruptible-camb.py | 2 +- examples/foundational/07zi-interruptible-piper.py | 2 +- examples/foundational/07zj-interruptible-kokoro.py | 2 +- examples/foundational/07zk-interruptible-resemble.py | 2 +- examples/foundational/08-custom-frame-processor.py | 2 +- examples/foundational/10-wake-phrase.py | 2 +- examples/foundational/11-sound-effects.py | 2 +- examples/foundational/12-describe-image-openai.py | 2 +- examples/foundational/12a-describe-image-anthropic.py | 2 +- examples/foundational/12b-describe-image-aws.py | 2 +- examples/foundational/12c-describe-image-gemini-flash.py | 2 +- examples/foundational/14-function-calling.py | 2 +- examples/foundational/14a-function-calling-anthropic.py | 2 +- examples/foundational/14c-function-calling-together.py | 2 +- examples/foundational/14d-function-calling-anthropic-video.py | 2 +- examples/foundational/14d-function-calling-aws-video.py | 2 +- .../foundational/14d-function-calling-gemini-flash-video.py | 2 +- examples/foundational/14d-function-calling-moondream-video.py | 2 +- examples/foundational/14d-function-calling-openai-video.py | 2 +- examples/foundational/14f-function-calling-groq.py | 2 +- examples/foundational/14g-function-calling-grok.py | 2 +- examples/foundational/14h-function-calling-azure.py | 2 +- examples/foundational/14i-function-calling-fireworks.py | 2 +- examples/foundational/14j-function-calling-nvidia.py | 2 +- examples/foundational/14k-function-calling-cerebras.py | 2 +- examples/foundational/14l-function-calling-deepseek.py | 2 +- examples/foundational/14m-function-calling-openrouter.py | 2 +- examples/foundational/14n-function-calling-perplexity.py | 2 +- .../foundational/14o-function-calling-gemini-openai-format.py | 2 +- .../foundational/14p-function-calling-gemini-vertex-ai.py | 2 +- examples/foundational/14q-function-calling-qwen.py | 2 +- examples/foundational/14r-function-calling-aws.py | 2 +- examples/foundational/14s-function-calling-sambanova.py | 2 +- examples/foundational/14t-function-calling-direct.py | 2 +- examples/foundational/14u-function-calling-ollama.py | 2 +- examples/foundational/14v-function-calling-openai.py | 2 +- examples/foundational/14w-function-calling-mistral.py | 2 +- examples/foundational/14x-function-calling-openpipe.py | 2 +- examples/foundational/15-switch-voices.py | 2 +- examples/foundational/15a-switch-languages.py | 2 +- examples/foundational/16-gpu-container-local-bot.py | 2 +- examples/foundational/17-detect-user-idle.py | 2 +- examples/foundational/20a-persistent-context-openai.py | 2 +- examples/foundational/20c-persistent-context-anthropic.py | 2 +- examples/foundational/20d-persistent-context-gemini.py | 4 ++-- examples/foundational/21-tavus-transport.py | 2 +- examples/foundational/21a-tavus-video-service.py | 2 +- examples/foundational/22-filter-incomplete-turns.py | 2 +- examples/foundational/23-bot-background-sound.py | 2 +- examples/foundational/25-google-audio-in.py | 2 +- examples/foundational/27-simli-layer.py | 2 +- examples/foundational/28-user-assistant-turns.py | 2 +- examples/foundational/29-turn-tracking-observer.py | 2 +- examples/foundational/30-observer.py | 2 +- examples/foundational/34-audio-recording.py | 2 +- examples/foundational/38-smart-turn-fal.py | 2 +- examples/foundational/38a-smart-turn-local-coreml.py | 2 +- examples/foundational/38b-smart-turn-local.py | 2 +- examples/foundational/39-mcp-stdio.py | 2 +- examples/foundational/39a-mcp-streamable-http.py | 2 +- examples/foundational/39b-mcp-streamable-http-gemini-live.py | 2 +- examples/foundational/39c-multiple-mcp.py | 2 +- examples/foundational/42-interruption-config.py | 2 +- examples/foundational/44-voicemail-detection.py | 2 +- examples/foundational/45-before-and-after-events.py | 2 +- examples/foundational/47-sentry-metrics.py | 2 +- examples/foundational/48-service-switcher.py | 2 +- examples/foundational/49a-thinking-anthropic.py | 2 +- examples/foundational/49b-thinking-google.py | 2 +- examples/foundational/49c-thinking-functions-anthropic.py | 2 +- examples/foundational/49d-thinking-functions-google.py | 2 +- examples/foundational/53-concurrent-llm-evaluation.py | 2 +- .../foundational/53-concurrent-llm-rtvi-ignored-sources.py | 2 +- examples/foundational/54-context-summarization-openai.py | 2 +- examples/foundational/54a-context-summarization-google.py | 2 +- .../foundational/54b-context-summarization-manual-openai.py | 2 +- .../foundational/54c-context-summarization-dedicated-llm.py | 2 +- .../foundational/55a-update-settings-deepgram-flux-stt.py | 2 +- .../55a-update-settings-deepgram-sagemaker-stt.py | 2 +- examples/foundational/55a-update-settings-deepgram-stt.py | 2 +- examples/foundational/55b-update-settings-azure-stt.py | 2 +- examples/foundational/55c-update-settings-google-stt.py | 2 +- examples/foundational/55d-update-settings-assemblyai-stt.py | 2 +- examples/foundational/55e-update-settings-gladia-stt.py | 2 +- .../55f-update-settings-elevenlabs-realtime-stt.py | 2 +- examples/foundational/55g-update-settings-elevenlabs-stt.py | 2 +- examples/foundational/55h-update-settings-speechmatics-stt.py | 2 +- examples/foundational/55i-update-settings-whisper-api-stt.py | 2 +- examples/foundational/55j-update-settings-sarvam-stt.py | 2 +- examples/foundational/55k-update-settings-soniox-stt.py | 2 +- .../foundational/55l-update-settings-aws-transcribe-stt.py | 2 +- examples/foundational/55m-update-settings-cartesia-stt.py | 2 +- .../foundational/55n-update-settings-cartesia-http-tts.py | 2 +- examples/foundational/55n-update-settings-cartesia-tts.py | 2 +- .../foundational/55o-update-settings-elevenlabs-http-tts.py | 2 +- examples/foundational/55o-update-settings-elevenlabs-tts.py | 2 +- examples/foundational/55p-update-settings-openai-tts.py | 2 +- .../foundational/55q-update-settings-deepgram-http-tts.py | 2 +- .../55q-update-settings-deepgram-sagemaker-tts.py | 2 +- examples/foundational/55q-update-settings-deepgram-tts.py | 2 +- examples/foundational/55r-update-settings-azure-http-tts.py | 2 +- examples/foundational/55r-update-settings-azure-tts.py | 2 +- examples/foundational/55s-update-settings-google-http-tts.py | 2 +- .../foundational/55s-update-settings-google-stream-tts.py | 2 +- examples/foundational/55t-update-settings-piper-http-tts.py | 2 +- examples/foundational/55t-update-settings-piper-tts.py | 2 +- examples/foundational/55u-update-settings-rime-http-tts.py | 2 +- examples/foundational/55u-update-settings-rime-tts.py | 2 +- examples/foundational/55v-update-settings-lmnt-tts.py | 2 +- examples/foundational/55w-update-settings-fish-tts.py | 2 +- examples/foundational/55x-update-settings-minimax-tts.py | 2 +- examples/foundational/55y-update-settings-groq-tts.py | 2 +- examples/foundational/55z-update-settings-hume-tts.py | 2 +- .../foundational/55za-update-settings-neuphonic-http-tts.py | 2 +- examples/foundational/55za-update-settings-neuphonic-tts.py | 2 +- .../foundational/55zb-update-settings-inworld-http-tts.py | 2 +- examples/foundational/55zb-update-settings-inworld-tts.py | 2 +- examples/foundational/55zc-update-settings-gemini-tts.py | 2 +- examples/foundational/55zd-update-settings-aws-polly-tts.py | 2 +- examples/foundational/55ze-update-settings-sarvam-http-tts.py | 2 +- examples/foundational/55ze-update-settings-sarvam-tts.py | 2 +- examples/foundational/55zf-update-settings-camb-tts.py | 2 +- examples/foundational/55zg-update-settings-kokoro-tts.py | 2 +- examples/foundational/55zh-update-settings-resembleai-tts.py | 2 +- examples/foundational/55zi-update-settings-azure-llm.py | 2 +- examples/foundational/55zi-update-settings-openai-llm.py | 2 +- examples/foundational/55zj-update-settings-anthropic-llm.py | 2 +- examples/foundational/55zk-update-settings-google-llm.py | 2 +- .../foundational/55zk-update-settings-google-vertex-llm.py | 2 +- examples/foundational/55zl-update-settings-azure-realtime.py | 2 +- examples/foundational/55zl-update-settings-openai-realtime.py | 2 +- .../foundational/55zm-update-settings-gemini-live-vertex.py | 2 +- examples/foundational/55zm-update-settings-gemini-live.py | 2 +- .../foundational/55zn-update-settings-ultravox-realtime.py | 2 +- examples/foundational/55zo-update-settings-grok-realtime.py | 2 +- examples/foundational/55zp-update-settings-aws-bedrock-llm.py | 2 +- examples/foundational/55zq-update-settings-fal-stt.py | 2 +- examples/foundational/55zr-update-settings-gradium-stt.py | 2 +- examples/foundational/55zs-update-settings-whisper-mlx-stt.py | 2 +- examples/foundational/55zs-update-settings-whisper-stt.py | 2 +- .../foundational/55zt-update-settings-nvidia-segmented-stt.py | 2 +- examples/foundational/55zt-update-settings-nvidia-stt.py | 2 +- .../foundational/55zu-update-settings-openai-realtime-stt.py | 2 +- .../foundational/55zv-update-settings-asyncai-http-tts.py | 2 +- examples/foundational/55zv-update-settings-asyncai-tts.py | 2 +- examples/foundational/55zw-update-settings-gradium-tts.py | 2 +- examples/foundational/55zx-update-settings-cerebras-llm.py | 2 +- examples/foundational/55zy-update-settings-deepseek-llm.py | 2 +- examples/foundational/55zz-update-settings-fireworks-llm.py | 2 +- examples/foundational/55zza-update-settings-grok-llm.py | 2 +- examples/foundational/55zzb-update-settings-groq-llm.py | 2 +- examples/foundational/55zzc-update-settings-mistral-llm.py | 2 +- examples/foundational/55zzd-update-settings-nvidia-llm.py | 2 +- examples/foundational/55zze-update-settings-ollama-llm.py | 2 +- examples/foundational/55zzf-update-settings-openrouter-llm.py | 2 +- examples/foundational/55zzg-update-settings-perplexity-llm.py | 2 +- examples/foundational/55zzh-update-settings-qwen-llm.py | 2 +- examples/foundational/55zzi-update-settings-sambanova-llm.py | 2 +- examples/foundational/55zzj-update-settings-together-llm.py | 2 +- .../foundational/55zzk-update-settings-aws-nova-sonic-llm.py | 2 +- examples/foundational/55zzl-update-settings-nvidia-tts.py | 2 +- .../foundational/55zzm-update-settings-speechmatics-tts.py | 2 +- examples/foundational/55zzn-update-settings-groq-stt.py | 2 +- examples/foundational/55zzo-update-settings-openpipe-llm.py | 2 +- examples/foundational/55zzp-update-settings-xtts-tts.py | 2 +- examples/foundational/56-lemonslice-transport.py | 2 +- 219 files changed, 221 insertions(+), 222 deletions(-) diff --git a/examples/foundational/02-llm-say-one-thing.py b/examples/foundational/02-llm-say-one-thing.py index cebea9dcf..d699277ce 100644 --- a/examples/foundational/02-llm-say-one-thing.py +++ b/examples/foundational/02-llm-say-one-thing.py @@ -47,7 +47,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): llm = OpenAILLMService( api_key=os.getenv("OPENAI_API_KEY"), settings=OpenAILLMService.Settings( - system_instruction="You are an LLM in a WebRTC session, and this is a 'hello world' demo.", + system_instruction="You are a helpful assistant in a voice conversation. Your responses will be spoken aloud, so avoid emojis, bullet points, or other formatting that can't be spoken. Respond to what the user said in a creative, helpful, and brief way.", ), ) diff --git a/examples/foundational/04-transports-small-webrtc.py b/examples/foundational/04-transports-small-webrtc.py index ba4749919..cc768a751 100644 --- a/examples/foundational/04-transports-small-webrtc.py +++ b/examples/foundational/04-transports-small-webrtc.py @@ -75,7 +75,7 @@ async def run_example(webrtc_connection: SmallWebRTCConnection): llm = OpenAILLMService( api_key=os.getenv("OPENAI_API_KEY"), settings=OpenAILLMService.Settings( - system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + system_instruction="You are a helpful assistant in a voice conversation. Your responses will be spoken aloud, so avoid emojis, bullet points, or other formatting that can't be spoken. Respond to what the user said in a creative, helpful, and brief way.", ), ) diff --git a/examples/foundational/04a-transports-daily.py b/examples/foundational/04a-transports-daily.py index b73b7bdfe..83bc27aca 100644 --- a/examples/foundational/04a-transports-daily.py +++ b/examples/foundational/04a-transports-daily.py @@ -58,7 +58,7 @@ async def main(): llm = OpenAILLMService( api_key=os.getenv("OPENAI_API_KEY"), settings=OpenAILLMService.Settings( - system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + system_instruction="You are a helpful assistant in a voice conversation. Your responses will be spoken aloud, so avoid emojis, bullet points, or other formatting that can't be spoken. Respond to what the user said in a creative, helpful, and brief way.", ), ) diff --git a/examples/foundational/04b-transports-livekit.py b/examples/foundational/04b-transports-livekit.py index 09262f767..b2ec6b49c 100644 --- a/examples/foundational/04b-transports-livekit.py +++ b/examples/foundational/04b-transports-livekit.py @@ -58,7 +58,7 @@ async def main(): llm = OpenAILLMService( api_key=os.getenv("OPENAI_API_KEY"), settings=OpenAILLMService.Settings( - system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + system_instruction="You are a helpful assistant in a voice conversation. Your responses will be spoken aloud, so avoid emojis, bullet points, or other formatting that can't be spoken. Respond to what the user said in a creative, helpful, and brief way.", ), ) diff --git a/examples/foundational/06-listen-and-respond.py b/examples/foundational/06-listen-and-respond.py index 7a73ad876..769975b9a 100644 --- a/examples/foundational/06-listen-and-respond.py +++ b/examples/foundational/06-listen-and-respond.py @@ -91,7 +91,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): llm = OpenAILLMService( api_key=os.getenv("OPENAI_API_KEY"), settings=OpenAILLMService.Settings( - system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + system_instruction="You are a helpful assistant in a voice conversation. Your responses will be spoken aloud, so avoid emojis, bullet points, or other formatting that can't be spoken. Respond to what the user said in a creative, helpful, and brief way.", ), ) diff --git a/examples/foundational/06a-image-sync.py b/examples/foundational/06a-image-sync.py index 3f80380dc..473441fac 100644 --- a/examples/foundational/06a-image-sync.py +++ b/examples/foundational/06a-image-sync.py @@ -108,7 +108,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): llm = OpenAILLMService( api_key=os.getenv("OPENAI_API_KEY"), settings=OpenAILLMService.Settings( - system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + system_instruction="You are a helpful assistant in a voice conversation. Your responses will be spoken aloud, so avoid emojis, bullet points, or other formatting that can't be spoken. Respond to what the user said in a creative, helpful, and brief way.", ), ) diff --git a/examples/foundational/07-interruptible-cartesia-http.py b/examples/foundational/07-interruptible-cartesia-http.py index be6bc07a6..6b3daecf0 100644 --- a/examples/foundational/07-interruptible-cartesia-http.py +++ b/examples/foundational/07-interruptible-cartesia-http.py @@ -67,7 +67,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): llm = OpenAILLMService( api_key=os.getenv("OPENAI_API_KEY"), settings=OpenAILLMService.Settings( - system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + system_instruction="You are a helpful assistant in a voice conversation. Your responses will be spoken aloud, so avoid emojis, bullet points, or other formatting that can't be spoken. Respond to what the user said in a creative, helpful, and brief way.", ), ) diff --git a/examples/foundational/07-interruptible.py b/examples/foundational/07-interruptible.py index 17aec31e1..c0b410f50 100644 --- a/examples/foundational/07-interruptible.py +++ b/examples/foundational/07-interruptible.py @@ -63,7 +63,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): llm = OpenAILLMService( api_key=os.getenv("OPENAI_API_KEY"), settings=OpenAILLMService.Settings( - system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + system_instruction="You are a helpful assistant in a voice conversation. Your responses will be spoken aloud, so avoid emojis, bullet points, or other formatting that can't be spoken. Respond to what the user said in a creative, helpful, and brief way.", ), ) diff --git a/examples/foundational/07a-interruptible-speechmatics-vad.py b/examples/foundational/07a-interruptible-speechmatics-vad.py index cece246d8..327701ff2 100644 --- a/examples/foundational/07a-interruptible-speechmatics-vad.py +++ b/examples/foundational/07a-interruptible-speechmatics-vad.py @@ -113,7 +113,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): api_key=os.getenv("OPENAI_API_KEY"), settings=OpenAILLMService.Settings( temperature=0.75, - system_instruction="You are a helpful British assistant called Sarah. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Always include punctuation in your responses. Give very short replies - do not give longer replies unless strictly necessary. Respond to what the user said in a concise, funny, creative and helpful way. Use `` tags to identify different speakers - do not use tags in your replies. Do not respond to speakers within `` tags unless explicitly asked to.", + system_instruction="You are a helpful British assistant called Sarah in a voice conversation. Your responses will be spoken aloud, so avoid emojis, bullet points, or other formatting that can't be spoken. Always include punctuation in your responses. Give very short replies - do not give longer replies unless strictly necessary. Respond to what the user said in a concise, funny, creative and helpful way. Use `` tags to identify different speakers - do not use tags in your replies. Do not respond to speakers within `` tags unless explicitly asked to.", ), ) diff --git a/examples/foundational/07a-interruptible-speechmatics.py b/examples/foundational/07a-interruptible-speechmatics.py index 3d6395f73..5181bf36f 100644 --- a/examples/foundational/07a-interruptible-speechmatics.py +++ b/examples/foundational/07a-interruptible-speechmatics.py @@ -93,7 +93,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): api_key=os.getenv("OPENAI_API_KEY"), settings=OpenAILLMService.Settings( temperature=0.75, - system_instruction="You are a helpful British assistant called Sarah. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Always include punctuation in your responses. Give very short replies - do not give longer replies unless strictly necessary. Respond to what the user said in a concise, funny, creative and helpful way. Use `` tags to identify different speakers - do not use tags in your replies. Do not respond to speakers within `` tags unless explicitly asked to.", + system_instruction="You are a helpful British assistant called Sarah in a voice conversation. Your responses will be spoken aloud, so avoid emojis, bullet points, or other formatting that can't be spoken. Always include punctuation in your responses. Give very short replies - do not give longer replies unless strictly necessary. Respond to what the user said in a concise, funny, creative and helpful way. Use `` tags to identify different speakers - do not use tags in your replies. Do not respond to speakers within `` tags unless explicitly asked to.", ), ) diff --git a/examples/foundational/07b-interruptible-langchain.py b/examples/foundational/07b-interruptible-langchain.py index 1a85bf7ad..d78e678a2 100644 --- a/examples/foundational/07b-interruptible-langchain.py +++ b/examples/foundational/07b-interruptible-langchain.py @@ -80,8 +80,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): [ ( "system", - "Be nice and helpful. Answer very briefly and without special characters like `#` or `*`. " - "Your response will be synthesized to voice and those characters will create unnatural sounds.", + "You are a helpful assistant in a voice conversation. Your responses will be spoken aloud, so avoid emojis, bullet points, or other formatting that can't be spoken. Respond to what the user said in a creative, helpful, and brief way.", ), MessagesPlaceholder("chat_history"), ("human", "{input}"), diff --git a/examples/foundational/07c-interruptible-deepgram-flux.py b/examples/foundational/07c-interruptible-deepgram-flux.py index da027b4f8..2c4e63bb7 100644 --- a/examples/foundational/07c-interruptible-deepgram-flux.py +++ b/examples/foundational/07c-interruptible-deepgram-flux.py @@ -71,7 +71,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): llm = OpenAILLMService( api_key=os.getenv("OPENAI_API_KEY"), settings=OpenAILLMService.Settings( - system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + system_instruction="You are a helpful assistant in a voice conversation. Your responses will be spoken aloud, so avoid emojis, bullet points, or other formatting that can't be spoken. Respond to what the user said in a creative, helpful, and brief way.", ), ) diff --git a/examples/foundational/07c-interruptible-deepgram-http.py b/examples/foundational/07c-interruptible-deepgram-http.py index ee6733165..cb1026d7f 100644 --- a/examples/foundational/07c-interruptible-deepgram-http.py +++ b/examples/foundational/07c-interruptible-deepgram-http.py @@ -68,7 +68,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): llm = OpenAILLMService( api_key=os.getenv("OPENAI_API_KEY"), settings=OpenAILLMService.Settings( - system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + system_instruction="You are a helpful assistant in a voice conversation. Your responses will be spoken aloud, so avoid emojis, bullet points, or other formatting that can't be spoken. Respond to what the user said in a creative, helpful, and brief way.", ), ) diff --git a/examples/foundational/07c-interruptible-deepgram-sagemaker.py b/examples/foundational/07c-interruptible-deepgram-sagemaker.py index 91b1c95aa..b3b53b3db 100644 --- a/examples/foundational/07c-interruptible-deepgram-sagemaker.py +++ b/examples/foundational/07c-interruptible-deepgram-sagemaker.py @@ -79,7 +79,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): settings=AWSBedrockLLMSettings( model="us.amazon.nova-pro-v1:0", temperature=0.8, - system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + system_instruction="You are a helpful assistant in a voice conversation. Your responses will be spoken aloud, so avoid emojis, bullet points, or other formatting that can't be spoken. Respond to what the user said in a creative, helpful, and brief way.", ), ) diff --git a/examples/foundational/07c-interruptible-deepgram-vad.py b/examples/foundational/07c-interruptible-deepgram-vad.py index 0a4dc0125..420ec795b 100644 --- a/examples/foundational/07c-interruptible-deepgram-vad.py +++ b/examples/foundational/07c-interruptible-deepgram-vad.py @@ -71,7 +71,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): llm = OpenAILLMService( api_key=os.getenv("OPENAI_API_KEY"), settings=OpenAILLMService.Settings( - system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + system_instruction="You are a helpful assistant in a voice conversation. Your responses will be spoken aloud, so avoid emojis, bullet points, or other formatting that can't be spoken. Respond to what the user said in a creative, helpful, and brief way.", ), ) diff --git a/examples/foundational/07c-interruptible-deepgram.py b/examples/foundational/07c-interruptible-deepgram.py index e00a9f191..a4d94f915 100644 --- a/examples/foundational/07c-interruptible-deepgram.py +++ b/examples/foundational/07c-interruptible-deepgram.py @@ -65,7 +65,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): llm = OpenAILLMService( api_key=os.getenv("OPENAI_API_KEY"), settings=OpenAILLMService.Settings( - system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + system_instruction="You are a helpful assistant in a voice conversation. Your responses will be spoken aloud, so avoid emojis, bullet points, or other formatting that can't be spoken. Respond to what the user said in a creative, helpful, and brief way.", ), ) diff --git a/examples/foundational/07d-interruptible-elevenlabs-http.py b/examples/foundational/07d-interruptible-elevenlabs-http.py index cf60ac3e7..a83df1465 100644 --- a/examples/foundational/07d-interruptible-elevenlabs-http.py +++ b/examples/foundational/07d-interruptible-elevenlabs-http.py @@ -72,7 +72,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): llm = OpenAILLMService( api_key=os.getenv("OPENAI_API_KEY"), settings=OpenAILLMService.Settings( - system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + system_instruction="You are a helpful assistant in a voice conversation. Your responses will be spoken aloud, so avoid emojis, bullet points, or other formatting that can't be spoken. Respond to what the user said in a creative, helpful, and brief way.", ), ) diff --git a/examples/foundational/07d-interruptible-elevenlabs.py b/examples/foundational/07d-interruptible-elevenlabs.py index d14bc71cd..ad1873788 100644 --- a/examples/foundational/07d-interruptible-elevenlabs.py +++ b/examples/foundational/07d-interruptible-elevenlabs.py @@ -65,7 +65,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): llm = OpenAILLMService( api_key=os.getenv("OPENAI_API_KEY"), settings=OpenAILLMService.Settings( - system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + system_instruction="You are a helpful assistant in a voice conversation. Your responses will be spoken aloud, so avoid emojis, bullet points, or other formatting that can't be spoken. Respond to what the user said in a creative, helpful, and brief way.", ), ) diff --git a/examples/foundational/07f-interruptible-azure-http.py b/examples/foundational/07f-interruptible-azure-http.py index 38a2410fc..c372c7c7e 100644 --- a/examples/foundational/07f-interruptible-azure-http.py +++ b/examples/foundational/07f-interruptible-azure-http.py @@ -67,7 +67,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): endpoint=os.getenv("AZURE_CHATGPT_ENDPOINT"), settings=AzureLLMService.Settings( model=os.getenv("AZURE_CHATGPT_MODEL"), - system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + system_instruction="You are a helpful assistant in a voice conversation. Your responses will be spoken aloud, so avoid emojis, bullet points, or other formatting that can't be spoken. Respond to what the user said in a creative, helpful, and brief way.", ), ) diff --git a/examples/foundational/07f-interruptible-azure.py b/examples/foundational/07f-interruptible-azure.py index b7ace8548..6a0b39bb5 100644 --- a/examples/foundational/07f-interruptible-azure.py +++ b/examples/foundational/07f-interruptible-azure.py @@ -67,7 +67,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): endpoint=os.getenv("AZURE_CHATGPT_ENDPOINT"), settings=AzureLLMService.Settings( model=os.getenv("AZURE_CHATGPT_MODEL"), - system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + system_instruction="You are a helpful assistant in a voice conversation. Your responses will be spoken aloud, so avoid emojis, bullet points, or other formatting that can't be spoken. Respond to what the user said in a creative, helpful, and brief way.", ), ) diff --git a/examples/foundational/07h-interruptible-openpipe.py b/examples/foundational/07h-interruptible-openpipe.py index eaaa6fedd..8d31125f2 100644 --- a/examples/foundational/07h-interruptible-openpipe.py +++ b/examples/foundational/07h-interruptible-openpipe.py @@ -68,7 +68,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): openpipe_api_key=os.getenv("OPENPIPE_API_KEY"), tags={"conversation_id": f"pipecat-{timestamp}"}, settings=OpenPipeLLMService.Settings( - system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + system_instruction="You are a helpful assistant in a voice conversation. Your responses will be spoken aloud, so avoid emojis, bullet points, or other formatting that can't be spoken. Respond to what the user said in a creative, helpful, and brief way.", ), ) diff --git a/examples/foundational/07i-interruptible-xtts.py b/examples/foundational/07i-interruptible-xtts.py index 3246d5da9..0f51ff03e 100644 --- a/examples/foundational/07i-interruptible-xtts.py +++ b/examples/foundational/07i-interruptible-xtts.py @@ -68,7 +68,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): llm = OpenAILLMService( api_key=os.getenv("OPENAI_API_KEY"), settings=OpenAILLMService.Settings( - system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + system_instruction="You are a helpful assistant in a voice conversation. Your responses will be spoken aloud, so avoid emojis, bullet points, or other formatting that can't be spoken. Respond to what the user said in a creative, helpful, and brief way.", ), ) diff --git a/examples/foundational/07j-interruptible-gladia-vad.py b/examples/foundational/07j-interruptible-gladia-vad.py index b25ab7275..ec3cc80e1 100644 --- a/examples/foundational/07j-interruptible-gladia-vad.py +++ b/examples/foundational/07j-interruptible-gladia-vad.py @@ -76,7 +76,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): llm = OpenAILLMService( api_key=os.getenv("OPENAI_API_KEY", ""), settings=OpenAILLMService.Settings( - system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + system_instruction="You are a helpful assistant in a voice conversation. Your responses will be spoken aloud, so avoid emojis, bullet points, or other formatting that can't be spoken. Respond to what the user said in a creative, helpful, and brief way.", ), ) diff --git a/examples/foundational/07j-interruptible-gladia.py b/examples/foundational/07j-interruptible-gladia.py index d1fee759b..5ab2e16a3 100644 --- a/examples/foundational/07j-interruptible-gladia.py +++ b/examples/foundational/07j-interruptible-gladia.py @@ -74,7 +74,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): llm = OpenAILLMService( api_key=os.getenv("OPENAI_API_KEY", ""), settings=OpenAILLMService.Settings( - system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + system_instruction="You are a helpful assistant in a voice conversation. Your responses will be spoken aloud, so avoid emojis, bullet points, or other formatting that can't be spoken. Respond to what the user said in a creative, helpful, and brief way.", ), ) diff --git a/examples/foundational/07k-interruptible-lmnt.py b/examples/foundational/07k-interruptible-lmnt.py index a41f1ae2e..c6f931413 100644 --- a/examples/foundational/07k-interruptible-lmnt.py +++ b/examples/foundational/07k-interruptible-lmnt.py @@ -64,7 +64,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): llm = OpenAILLMService( api_key=os.getenv("OPENAI_API_KEY"), settings=OpenAILLMService.Settings( - system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + system_instruction="You are a helpful assistant in a voice conversation. Your responses will be spoken aloud, so avoid emojis, bullet points, or other formatting that can't be spoken. Respond to what the user said in a creative, helpful, and brief way.", ), ) diff --git a/examples/foundational/07l-interruptible-groq.py b/examples/foundational/07l-interruptible-groq.py index a4bfee8dc..59e1a7fca 100644 --- a/examples/foundational/07l-interruptible-groq.py +++ b/examples/foundational/07l-interruptible-groq.py @@ -58,7 +58,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): api_key=os.getenv("GROQ_API_KEY"), settings=GroqLLMService.Settings( model="llama-3.1-8b-instant", - system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + system_instruction="You are a helpful assistant in a voice conversation. Your responses will be spoken aloud, so avoid emojis, bullet points, or other formatting that can't be spoken. Respond to what the user said in a creative, helpful, and brief way.", ), ) diff --git a/examples/foundational/07m-interruptible-aws.py b/examples/foundational/07m-interruptible-aws.py index ff3b6a789..ca44fb448 100644 --- a/examples/foundational/07m-interruptible-aws.py +++ b/examples/foundational/07m-interruptible-aws.py @@ -66,7 +66,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): settings=AWSBedrockLLMService.Settings( model="us.anthropic.claude-sonnet-4-6", temperature=0.8, - system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + system_instruction="You are a helpful assistant in a voice conversation. Your responses will be spoken aloud, so avoid emojis, bullet points, or other formatting that can't be spoken. Respond to what the user said in a creative, helpful, and brief way.", ), ) diff --git a/examples/foundational/07n-interruptible-gemini-image.py b/examples/foundational/07n-interruptible-gemini-image.py index ad292ab03..461e2d8fa 100644 --- a/examples/foundational/07n-interruptible-gemini-image.py +++ b/examples/foundational/07n-interruptible-gemini-image.py @@ -89,7 +89,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): settings=GoogleLLMService.Settings( model="gemini-2.5-flash-image", # model="gemini-3-pro-image-preview", # A more powerful model, but slower, - system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + system_instruction="You are a helpful assistant in a voice conversation. Your responses will be spoken aloud, so avoid emojis, bullet points, or other formatting that can't be spoken. Respond to what the user said in a creative, helpful, and brief way.", ), ) diff --git a/examples/foundational/07n-interruptible-gemini.py b/examples/foundational/07n-interruptible-gemini.py index 3d8857708..00290bd3a 100644 --- a/examples/foundational/07n-interruptible-gemini.py +++ b/examples/foundational/07n-interruptible-gemini.py @@ -74,7 +74,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): api_key=os.getenv("GOOGLE_API_KEY"), model="gemini-2.5-flash", settings=GoogleLLMService.Settings( - system_instruction="""You are a helpful AI assistant in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. + system_instruction="""You are a helpful assistant in a voice conversation. IMPORTANT: You're using Gemini TTS which supports expressive markup tags. You can use these tags in your responses: - [sigh] - Insert a sigh sound @@ -91,7 +91,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): - "[whispering] Let me tell you a secret." - "The answer is... [long pause] ...42!" - Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.""", + Your responses will be spoken aloud, so avoid emojis, bullet points, or other formatting that can't be spoken. Keep responses concise. Respond to what the user said in a creative and helpful way.""", ), ) diff --git a/examples/foundational/07n-interruptible-google-http.py b/examples/foundational/07n-interruptible-google-http.py index 35c80a972..d627f431f 100644 --- a/examples/foundational/07n-interruptible-google-http.py +++ b/examples/foundational/07n-interruptible-google-http.py @@ -77,7 +77,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): model="gemini-2.5-flash", # force a certain amount of thinking if you want it # thinking=GoogleLLMService.ThinkingConfig(thinking_budget=4096) - system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + system_instruction="You are a helpful assistant in a voice conversation. Your responses will be spoken aloud, so avoid emojis, bullet points, or other formatting that can't be spoken. Respond to what the user said in a creative, helpful, and brief way.", ), ) diff --git a/examples/foundational/07n-interruptible-google.py b/examples/foundational/07n-interruptible-google.py index 2f148bb13..f8ec7b037 100644 --- a/examples/foundational/07n-interruptible-google.py +++ b/examples/foundational/07n-interruptible-google.py @@ -77,7 +77,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): model="gemini-2.5-flash", # force a certain amount of thinking if you want it # thinking=GoogleLLMService.ThinkingConfig(thinking_budget=4096), - system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + system_instruction="You are a helpful assistant in a voice conversation. Your responses will be spoken aloud, so avoid emojis, bullet points, or other formatting that can't be spoken. Respond to what the user said in a creative, helpful, and brief way.", ), ) diff --git a/examples/foundational/07o-interruptible-assemblyai-turn-detection.py b/examples/foundational/07o-interruptible-assemblyai-turn-detection.py index 7f8c8169e..14ec1af21 100644 --- a/examples/foundational/07o-interruptible-assemblyai-turn-detection.py +++ b/examples/foundational/07o-interruptible-assemblyai-turn-detection.py @@ -115,7 +115,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): llm = OpenAILLMService( api_key=os.getenv("OPENAI_API_KEY"), settings=OpenAILLMService.Settings( - system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + system_instruction="You are a helpful assistant in a voice conversation. Your responses will be spoken aloud, so avoid emojis, bullet points, or other formatting that can't be spoken. Respond to what the user said in a creative, helpful, and brief way.", ), ) diff --git a/examples/foundational/07o-interruptible-assemblyai.py b/examples/foundational/07o-interruptible-assemblyai.py index 700ec404e..dc8ecee12 100644 --- a/examples/foundational/07o-interruptible-assemblyai.py +++ b/examples/foundational/07o-interruptible-assemblyai.py @@ -67,7 +67,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): llm = OpenAILLMService( api_key=os.getenv("OPENAI_API_KEY"), settings=OpenAILLMService.Settings( - system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + system_instruction="You are a helpful assistant in a voice conversation. Your responses will be spoken aloud, so avoid emojis, bullet points, or other formatting that can't be spoken. Respond to what the user said in a creative, helpful, and brief way.", ), ) diff --git a/examples/foundational/07p-interruptible-krisp-viva.py b/examples/foundational/07p-interruptible-krisp-viva.py index b9eda804c..2b8e7f2f0 100644 --- a/examples/foundational/07p-interruptible-krisp-viva.py +++ b/examples/foundational/07p-interruptible-krisp-viva.py @@ -93,7 +93,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): llm = OpenAILLMService( api_key=os.getenv("OPENAI_API_KEY"), settings=OpenAILLMService.Settings( - system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + system_instruction="You are a helpful assistant in a voice conversation. Your responses will be spoken aloud, so avoid emojis, bullet points, or other formatting that can't be spoken. Respond to what the user said in a creative, helpful, and brief way.", ), ) diff --git a/examples/foundational/07p-interruptible-krisp.py b/examples/foundational/07p-interruptible-krisp.py index 800bc6fbc..229d50d17 100644 --- a/examples/foundational/07p-interruptible-krisp.py +++ b/examples/foundational/07p-interruptible-krisp.py @@ -68,7 +68,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): llm = OpenAILLMService( api_key=os.getenv("OPENAI_API_KEY"), settings=OpenAILLMService.Settings( - system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + system_instruction="You are a helpful assistant in a voice conversation. Your responses will be spoken aloud, so avoid emojis, bullet points, or other formatting that can't be spoken. Respond to what the user said in a creative, helpful, and brief way.", ), ) diff --git a/examples/foundational/07q-interruptible-rime-http.py b/examples/foundational/07q-interruptible-rime-http.py index f143ee287..f661c112b 100644 --- a/examples/foundational/07q-interruptible-rime-http.py +++ b/examples/foundational/07q-interruptible-rime-http.py @@ -71,7 +71,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): llm = OpenAILLMService( api_key=os.getenv("OPENAI_API_KEY"), settings=OpenAILLMService.Settings( - system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + system_instruction="You are a helpful assistant in a voice conversation. Your responses will be spoken aloud, so avoid emojis, bullet points, or other formatting that can't be spoken. Respond to what the user said in a creative, helpful, and brief way.", ), ) diff --git a/examples/foundational/07q-interruptible-rime.py b/examples/foundational/07q-interruptible-rime.py index dde507ee1..694f25c25 100644 --- a/examples/foundational/07q-interruptible-rime.py +++ b/examples/foundational/07q-interruptible-rime.py @@ -64,7 +64,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): llm = OpenAILLMService( api_key=os.getenv("OPENAI_API_KEY"), settings=OpenAILLMService.Settings( - system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + system_instruction="You are a helpful assistant in a voice conversation. Your responses will be spoken aloud, so avoid emojis, bullet points, or other formatting that can't be spoken. Respond to what the user said in a creative, helpful, and brief way.", ), ) diff --git a/examples/foundational/07r-interruptible-nvidia.py b/examples/foundational/07r-interruptible-nvidia.py index 2e69dd50f..ed0918ec1 100644 --- a/examples/foundational/07r-interruptible-nvidia.py +++ b/examples/foundational/07r-interruptible-nvidia.py @@ -58,7 +58,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): api_key=os.getenv("NVIDIA_API_KEY"), settings=NvidiaLLMService.Settings( model="meta/llama-3.3-70b-instruct", - system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + system_instruction="You are a helpful assistant in a voice conversation. Your responses will be spoken aloud, so avoid emojis, bullet points, or other formatting that can't be spoken. Respond to what the user said in a creative, helpful, and brief way.", ), ) diff --git a/examples/foundational/07s-interruptible-google-audio-in.py b/examples/foundational/07s-interruptible-google-audio-in.py index 6de7e1966..3f92872f0 100644 --- a/examples/foundational/07s-interruptible-google-audio-in.py +++ b/examples/foundational/07s-interruptible-google-audio-in.py @@ -48,7 +48,7 @@ load_dotenv(override=True) marker = "|----|" system_message = f""" -You are a helpful LLM in a WebRTC call. Your goals are to be helpful and brief in your responses. +You are a helpful LLM in a voice call. Your goals are to be helpful and brief in your responses. You are expert at transcribing audio to text. You will receive a mixture of audio and text input. When asked to transcribe what the user said, output an exact, word-for-word transcription. diff --git a/examples/foundational/07t-interruptible-fish.py b/examples/foundational/07t-interruptible-fish.py index d51e3a71e..13612a887 100644 --- a/examples/foundational/07t-interruptible-fish.py +++ b/examples/foundational/07t-interruptible-fish.py @@ -65,7 +65,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): llm = OpenAILLMService( api_key=os.getenv("OPENAI_API_KEY"), settings=OpenAILLMService.Settings( - system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + system_instruction="You are a helpful assistant in a voice conversation. Your responses will be spoken aloud, so avoid emojis, bullet points, or other formatting that can't be spoken. Respond to what the user said in a creative, helpful, and brief way.", ), ) diff --git a/examples/foundational/07v-interruptible-neuphonic-http.py b/examples/foundational/07v-interruptible-neuphonic-http.py index bc2bbe983..ad5b7e996 100644 --- a/examples/foundational/07v-interruptible-neuphonic-http.py +++ b/examples/foundational/07v-interruptible-neuphonic-http.py @@ -69,7 +69,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): llm = OpenAILLMService( api_key=os.getenv("OPENAI_API_KEY"), settings=OpenAILLMService.Settings( - system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + system_instruction="You are a helpful assistant in a voice conversation. Your responses will be spoken aloud, so avoid emojis, bullet points, or other formatting that can't be spoken. Respond to what the user said in a creative, helpful, and brief way.", ), ) diff --git a/examples/foundational/07v-interruptible-neuphonic.py b/examples/foundational/07v-interruptible-neuphonic.py index b44632286..ba3350754 100644 --- a/examples/foundational/07v-interruptible-neuphonic.py +++ b/examples/foundational/07v-interruptible-neuphonic.py @@ -64,7 +64,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): llm = OpenAILLMService( api_key=os.getenv("OPENAI_API_KEY"), settings=OpenAILLMService.Settings( - system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + system_instruction="You are a helpful assistant in a voice conversation. Your responses will be spoken aloud, so avoid emojis, bullet points, or other formatting that can't be spoken. Respond to what the user said in a creative, helpful, and brief way.", ), ) diff --git a/examples/foundational/07w-interruptible-fal.py b/examples/foundational/07w-interruptible-fal.py index 89a38d23c..08f24fd79 100644 --- a/examples/foundational/07w-interruptible-fal.py +++ b/examples/foundational/07w-interruptible-fal.py @@ -70,7 +70,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): llm = OpenAILLMService( api_key=os.getenv("OPENAI_API_KEY"), settings=OpenAILLMService.Settings( - system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + system_instruction="You are a helpful assistant in a voice conversation. Your responses will be spoken aloud, so avoid emojis, bullet points, or other formatting that can't be spoken. Respond to what the user said in a creative, helpful, and brief way.", ), ) diff --git a/examples/foundational/07x-interruptible-local.py b/examples/foundational/07x-interruptible-local.py index e0ace854b..28e970403 100644 --- a/examples/foundational/07x-interruptible-local.py +++ b/examples/foundational/07x-interruptible-local.py @@ -52,7 +52,7 @@ async def main(): llm = OpenAILLMService( api_key=os.getenv("OPENAI_API_KEY"), settings=OpenAILLMService.Settings( - system_instruction="You are a helpful LLM. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + system_instruction="You are a helpful assistant in a voice conversation. Your responses will be spoken aloud, so avoid emojis, bullet points, or other formatting that can't be spoken. Respond to what the user said in a creative, helpful, and brief way.", ), ) diff --git a/examples/foundational/07y-interruptible-minimax.py b/examples/foundational/07y-interruptible-minimax.py index d9bcef371..f8323369e 100644 --- a/examples/foundational/07y-interruptible-minimax.py +++ b/examples/foundational/07y-interruptible-minimax.py @@ -71,7 +71,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): llm = OpenAILLMService( api_key=os.getenv("OPENAI_API_KEY"), settings=OpenAILLMService.Settings( - system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + system_instruction="You are a helpful assistant in a voice conversation. Your responses will be spoken aloud, so avoid emojis, bullet points, or other formatting that can't be spoken. Respond to what the user said in a creative, helpful, and brief way.", ), ) diff --git a/examples/foundational/07z-interruptible-sarvam-http.py b/examples/foundational/07z-interruptible-sarvam-http.py index 76c892fd9..f8a806493 100644 --- a/examples/foundational/07z-interruptible-sarvam-http.py +++ b/examples/foundational/07z-interruptible-sarvam-http.py @@ -75,7 +75,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): llm = OpenAILLMService( api_key=os.getenv("OPENAI_API_KEY"), settings=OpenAILLMService.Settings( - system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + system_instruction="You are a helpful assistant in a voice conversation. Your responses will be spoken aloud, so avoid emojis, bullet points, or other formatting that can't be spoken. Respond to what the user said in a creative, helpful, and brief way.", ), ) diff --git a/examples/foundational/07z-interruptible-sarvam.py b/examples/foundational/07z-interruptible-sarvam.py index 915ea2c3d..5f144f73f 100644 --- a/examples/foundational/07z-interruptible-sarvam.py +++ b/examples/foundational/07z-interruptible-sarvam.py @@ -69,7 +69,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): llm = OpenAILLMService( api_key=os.getenv("OPENAI_API_KEY"), settings=OpenAILLMService.Settings( - system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + system_instruction="You are a helpful assistant in a voice conversation. Your responses will be spoken aloud, so avoid emojis, bullet points, or other formatting that can't be spoken. Respond to what the user said in a creative, helpful, and brief way.", ), ) diff --git a/examples/foundational/07za-interruptible-soniox.py b/examples/foundational/07za-interruptible-soniox.py index d425be966..c29fea9fb 100644 --- a/examples/foundational/07za-interruptible-soniox.py +++ b/examples/foundational/07za-interruptible-soniox.py @@ -71,7 +71,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): llm = OpenAILLMService( api_key=os.getenv("OPENAI_API_KEY"), settings=OpenAILLMService.Settings( - system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + system_instruction="You are a helpful assistant in a voice conversation. Your responses will be spoken aloud, so avoid emojis, bullet points, or other formatting that can't be spoken. Respond to what the user said in a creative, helpful, and brief way.", ), ) diff --git a/examples/foundational/07zc-interruptible-asyncai-http.py b/examples/foundational/07zc-interruptible-asyncai-http.py index e95bd60b2..96964f5e8 100644 --- a/examples/foundational/07zc-interruptible-asyncai-http.py +++ b/examples/foundational/07zc-interruptible-asyncai-http.py @@ -69,7 +69,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): llm = OpenAILLMService( api_key=os.getenv("OPENAI_API_KEY"), settings=OpenAILLMService.Settings( - system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + system_instruction="You are a helpful assistant in a voice conversation. Your responses will be spoken aloud, so avoid emojis, bullet points, or other formatting that can't be spoken. Respond to what the user said in a creative, helpful, and brief way.", ), ) diff --git a/examples/foundational/07zc-interruptible-asyncai.py b/examples/foundational/07zc-interruptible-asyncai.py index 40cdcf7ab..39052720c 100644 --- a/examples/foundational/07zc-interruptible-asyncai.py +++ b/examples/foundational/07zc-interruptible-asyncai.py @@ -65,7 +65,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): llm = OpenAILLMService( api_key=os.getenv("OPENAI_API_KEY"), settings=OpenAILLMService.Settings( - system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + system_instruction="You are a helpful assistant in a voice conversation. Your responses will be spoken aloud, so avoid emojis, bullet points, or other formatting that can't be spoken. Respond to what the user said in a creative, helpful, and brief way.", ), ) diff --git a/examples/foundational/07zd-interruptible-aicoustics.py b/examples/foundational/07zd-interruptible-aicoustics.py index 923530943..eeb45a4c7 100644 --- a/examples/foundational/07zd-interruptible-aicoustics.py +++ b/examples/foundational/07zd-interruptible-aicoustics.py @@ -85,7 +85,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): llm = OpenAILLMService( api_key=os.getenv("OPENAI_API_KEY"), settings=OpenAILLMService.Settings( - system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + system_instruction="You are a helpful assistant in a voice conversation. Your responses will be spoken aloud, so avoid emojis, bullet points, or other formatting that can't be spoken. Respond to what the user said in a creative, helpful, and brief way.", ), ) diff --git a/examples/foundational/07ze-interruptible-hume.py b/examples/foundational/07ze-interruptible-hume.py index ef19e3619..a5e4253f6 100644 --- a/examples/foundational/07ze-interruptible-hume.py +++ b/examples/foundational/07ze-interruptible-hume.py @@ -67,7 +67,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): llm = OpenAILLMService( api_key=os.getenv("OPENAI_API_KEY"), settings=OpenAILLMService.Settings( - system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + system_instruction="You are a helpful assistant in a voice conversation. Your responses will be spoken aloud, so avoid emojis, bullet points, or other formatting that can't be spoken. Respond to what the user said in a creative, helpful, and brief way.", ), ) diff --git a/examples/foundational/07zf-interruptible-gradium.py b/examples/foundational/07zf-interruptible-gradium.py index 4b7e2f32b..1a067d1b2 100644 --- a/examples/foundational/07zf-interruptible-gradium.py +++ b/examples/foundational/07zf-interruptible-gradium.py @@ -71,7 +71,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): llm = OpenAILLMService( api_key=os.getenv("OPENAI_API_KEY"), settings=OpenAILLMService.Settings( - system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + system_instruction="You are a helpful assistant in a voice conversation. Your responses will be spoken aloud, so avoid emojis, bullet points, or other formatting that can't be spoken. Respond to what the user said in a creative, helpful, and brief way.", ), ) diff --git a/examples/foundational/07zg-interruptible-camb.py b/examples/foundational/07zg-interruptible-camb.py index e0f764f4e..ff9b7162d 100644 --- a/examples/foundational/07zg-interruptible-camb.py +++ b/examples/foundational/07zg-interruptible-camb.py @@ -64,7 +64,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): llm = OpenAILLMService( api_key=os.getenv("OPENAI_API_KEY"), settings=OpenAILLMService.Settings( - system_instruction="You are a helpful voice assistant powered by Camb AI text-to-speech. ", + system_instruction="You are a helpful voice assistant powered by Camb AI text-to-speech. Your responses will be spoken aloud, so avoid emojis, bullet points, or other formatting that can't be spoken. Keep responses concise.", ), ) diff --git a/examples/foundational/07zi-interruptible-piper.py b/examples/foundational/07zi-interruptible-piper.py index 44b7d0efd..53f21811c 100644 --- a/examples/foundational/07zi-interruptible-piper.py +++ b/examples/foundational/07zi-interruptible-piper.py @@ -63,7 +63,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): llm = OpenAILLMService( api_key=os.getenv("OPENAI_API_KEY"), settings=OpenAILLMService.Settings( - system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + system_instruction="You are a helpful assistant in a voice conversation. Your responses will be spoken aloud, so avoid emojis, bullet points, or other formatting that can't be spoken. Respond to what the user said in a creative, helpful, and brief way.", ), ) diff --git a/examples/foundational/07zj-interruptible-kokoro.py b/examples/foundational/07zj-interruptible-kokoro.py index 0978ba720..5fb0ca55b 100644 --- a/examples/foundational/07zj-interruptible-kokoro.py +++ b/examples/foundational/07zj-interruptible-kokoro.py @@ -63,7 +63,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): llm = OpenAILLMService( api_key=os.getenv("OPENAI_API_KEY"), settings=OpenAILLMService.Settings( - system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + system_instruction="You are a helpful assistant in a voice conversation. Your responses will be spoken aloud, so avoid emojis, bullet points, or other formatting that can't be spoken. Respond to what the user said in a creative, helpful, and brief way.", ), ) diff --git a/examples/foundational/07zk-interruptible-resemble.py b/examples/foundational/07zk-interruptible-resemble.py index a62387815..60d1d8495 100644 --- a/examples/foundational/07zk-interruptible-resemble.py +++ b/examples/foundational/07zk-interruptible-resemble.py @@ -63,7 +63,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): llm = OpenAILLMService( api_key=os.getenv("OPENAI_API_KEY"), settings=OpenAILLMService.Settings( - system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + system_instruction="You are a helpful assistant in a voice conversation. Your responses will be spoken aloud, so avoid emojis, bullet points, or other formatting that can't be spoken. Respond to what the user said in a creative, helpful, and brief way.", ), ) diff --git a/examples/foundational/08-custom-frame-processor.py b/examples/foundational/08-custom-frame-processor.py index b6b1ef42c..f07711657 100644 --- a/examples/foundational/08-custom-frame-processor.py +++ b/examples/foundational/08-custom-frame-processor.py @@ -103,7 +103,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): llm = OpenAILLMService( api_key=os.getenv("OPENAI_API_KEY"), settings=OpenAILLMService.Settings( - system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + system_instruction="You are a helpful assistant in a voice conversation. Your responses will be spoken aloud, so avoid emojis, bullet points, or other formatting that can't be spoken. Respond to what the user said in a creative, helpful, and brief way.", ), ) diff --git a/examples/foundational/10-wake-phrase.py b/examples/foundational/10-wake-phrase.py index df74e4be4..0a4244c33 100644 --- a/examples/foundational/10-wake-phrase.py +++ b/examples/foundational/10-wake-phrase.py @@ -64,7 +64,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): llm = OpenAILLMService( api_key=os.getenv("OPENAI_API_KEY"), settings=OpenAILLMService.Settings( - system_instruction="You are a helpful assistant. Respond to what the user said in a creative and helpful way. Keep your responses brief.", + system_instruction="You are a helpful assistant in a voice conversation. Your responses will be spoken aloud, so avoid emojis, bullet points, or other formatting that can't be spoken. Respond to what the user said in a creative, helpful, and brief way.", ), ) diff --git a/examples/foundational/11-sound-effects.py b/examples/foundational/11-sound-effects.py index 87cb3f333..1f7fdd339 100644 --- a/examples/foundational/11-sound-effects.py +++ b/examples/foundational/11-sound-effects.py @@ -107,7 +107,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): llm = OpenAILLMService( api_key=os.getenv("OPENAI_API_KEY"), settings=OpenAILLMService.Settings( - system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + system_instruction="You are a helpful assistant in a voice conversation. Your responses will be spoken aloud, so avoid emojis, bullet points, or other formatting that can't be spoken. Respond to what the user said in a creative, helpful, and brief way.", ), ) diff --git a/examples/foundational/12-describe-image-openai.py b/examples/foundational/12-describe-image-openai.py index 0888fa6bf..8c8af6352 100644 --- a/examples/foundational/12-describe-image-openai.py +++ b/examples/foundational/12-describe-image-openai.py @@ -61,7 +61,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): llm = OpenAILLMService( api_key=os.getenv("OPENAI_API_KEY"), settings=OpenAILLMService.Settings( - system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way. You are also able to describe images.", + system_instruction="You are a helpful assistant in a voice conversation. Your responses will be spoken aloud, so avoid emojis, bullet points, or other formatting that can't be spoken. Respond to what the user said in a creative, helpful, and brief way. You are also able to describe images.", ), ) diff --git a/examples/foundational/12a-describe-image-anthropic.py b/examples/foundational/12a-describe-image-anthropic.py index 086e282dc..642885dcf 100644 --- a/examples/foundational/12a-describe-image-anthropic.py +++ b/examples/foundational/12a-describe-image-anthropic.py @@ -61,7 +61,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): llm = AnthropicLLMService( api_key=os.getenv("ANTHROPIC_API_KEY"), settings=AnthropicLLMService.Settings( - system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way. You are also able to describe images.", + system_instruction="You are a helpful assistant in a voice conversation. Your responses will be spoken aloud, so avoid emojis, bullet points, or other formatting that can't be spoken. Respond to what the user said in a creative, helpful, and brief way. You are also able to describe images.", ), ) diff --git a/examples/foundational/12b-describe-image-aws.py b/examples/foundational/12b-describe-image-aws.py index d42bc6ef0..47d2b7970 100644 --- a/examples/foundational/12b-describe-image-aws.py +++ b/examples/foundational/12b-describe-image-aws.py @@ -63,7 +63,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): settings=AWSBedrockLLMService.Settings( model="us.anthropic.claude-sonnet-4-6", temperature=0.8, - system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way. You are also able to describe images.", + system_instruction="You are a helpful assistant in a voice conversation. Your responses will be spoken aloud, so avoid emojis, bullet points, or other formatting that can't be spoken. Respond to what the user said in a creative, helpful, and brief way. You are also able to describe images.", ), ) diff --git a/examples/foundational/12c-describe-image-gemini-flash.py b/examples/foundational/12c-describe-image-gemini-flash.py index acb481d3e..248bc08a7 100644 --- a/examples/foundational/12c-describe-image-gemini-flash.py +++ b/examples/foundational/12c-describe-image-gemini-flash.py @@ -61,7 +61,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): llm = GoogleLLMService( api_key=os.getenv("GOOGLE_API_KEY"), settings=GoogleLLMService.Settings( - system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way. You are also able to describe images.", + system_instruction="You are a helpful assistant in a voice conversation. Your responses will be spoken aloud, so avoid emojis, bullet points, or other formatting that can't be spoken. Respond to what the user said in a creative, helpful, and brief way. You are also able to describe images.", ), ) diff --git a/examples/foundational/14-function-calling.py b/examples/foundational/14-function-calling.py index 7b7e11edf..5001d5dad 100644 --- a/examples/foundational/14-function-calling.py +++ b/examples/foundational/14-function-calling.py @@ -75,7 +75,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): llm = OpenAILLMService( api_key=os.getenv("OPENAI_API_KEY"), settings=OpenAILLMService.Settings( - system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + system_instruction="You are a helpful assistant in a voice conversation. Your responses will be spoken aloud, so avoid emojis, bullet points, or other formatting that can't be spoken. Respond to what the user said in a creative, helpful, and brief way.", ), ) diff --git a/examples/foundational/14a-function-calling-anthropic.py b/examples/foundational/14a-function-calling-anthropic.py index c0ad9102d..6cf1e228f 100644 --- a/examples/foundational/14a-function-calling-anthropic.py +++ b/examples/foundational/14a-function-calling-anthropic.py @@ -77,7 +77,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): llm = AnthropicLLMService( api_key=os.getenv("ANTHROPIC_API_KEY"), settings=AnthropicLLMService.Settings( - system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + system_instruction="You are a helpful assistant in a voice conversation. Your responses will be spoken aloud, so avoid emojis, bullet points, or other formatting that can't be spoken. Respond to what the user said in a creative, helpful, and brief way.", ), ) llm.register_function("get_weather", get_weather) diff --git a/examples/foundational/14c-function-calling-together.py b/examples/foundational/14c-function-calling-together.py index 3d2034cb4..5bd176237 100644 --- a/examples/foundational/14c-function-calling-together.py +++ b/examples/foundational/14c-function-calling-together.py @@ -73,7 +73,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): api_key=os.getenv("TOGETHER_API_KEY"), settings=TogetherLLMService.Settings( model="meta-llama/Meta-Llama-3.1-70B-Instruct-Turbo", - system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + system_instruction="You are a helpful assistant in a voice conversation. Your responses will be spoken aloud, so avoid emojis, bullet points, or other formatting that can't be spoken. Respond to what the user said in a creative, helpful, and brief way.", ), ) # You can also register a function_name of None to get all functions diff --git a/examples/foundational/14d-function-calling-anthropic-video.py b/examples/foundational/14d-function-calling-anthropic-video.py index ce51ddb22..f2653101e 100644 --- a/examples/foundational/14d-function-calling-anthropic-video.py +++ b/examples/foundational/14d-function-calling-anthropic-video.py @@ -99,7 +99,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): llm = AnthropicLLMService( api_key=os.getenv("ANTHROPIC_API_KEY"), settings=AnthropicLLMService.Settings( - system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way. You are able to describe images from the user camera.", + system_instruction="You are a helpful assistant in a voice conversation. Your responses will be spoken aloud, so avoid emojis, bullet points, or other formatting that can't be spoken. Respond to what the user said in a creative, helpful, and brief way. You are able to describe images from the user camera.", ), ) llm.register_function("fetch_user_image", fetch_user_image) diff --git a/examples/foundational/14d-function-calling-aws-video.py b/examples/foundational/14d-function-calling-aws-video.py index 2c54e83f4..9fccdecdf 100644 --- a/examples/foundational/14d-function-calling-aws-video.py +++ b/examples/foundational/14d-function-calling-aws-video.py @@ -104,7 +104,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): # Here we can't because AWS Bedrock doesn't support it for Claude 3.7, # which we need for image input. temperature=0.8, - system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way. You are able to describe images from the user camera.", + system_instruction="You are a helpful assistant in a voice conversation. Your responses will be spoken aloud, so avoid emojis, bullet points, or other formatting that can't be spoken. Respond to what the user said in a creative, helpful, and brief way. You are able to describe images from the user camera.", ), ) llm.register_function("fetch_user_image", fetch_user_image) diff --git a/examples/foundational/14d-function-calling-gemini-flash-video.py b/examples/foundational/14d-function-calling-gemini-flash-video.py index 16d82e002..ba76de44b 100644 --- a/examples/foundational/14d-function-calling-gemini-flash-video.py +++ b/examples/foundational/14d-function-calling-gemini-flash-video.py @@ -99,7 +99,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): llm = GoogleLLMService( api_key=os.getenv("GOOGLE_API_KEY"), settings=GoogleLLMService.Settings( - system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way. You are able to describe images from the user camera.", + system_instruction="You are a helpful assistant in a voice conversation. Your responses will be spoken aloud, so avoid emojis, bullet points, or other formatting that can't be spoken. Respond to what the user said in a creative, helpful, and brief way. You are able to describe images from the user camera.", ), ) llm.register_function("fetch_user_image", fetch_user_image) diff --git a/examples/foundational/14d-function-calling-moondream-video.py b/examples/foundational/14d-function-calling-moondream-video.py index df7fc6014..2bbfbd426 100644 --- a/examples/foundational/14d-function-calling-moondream-video.py +++ b/examples/foundational/14d-function-calling-moondream-video.py @@ -129,7 +129,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): llm = OpenAILLMService( api_key=os.getenv("OPENAI_API_KEY"), settings=OpenAILLMService.Settings( - system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way. You are able to describe images from the user camera.", + system_instruction="You are a helpful assistant in a voice conversation. Your responses will be spoken aloud, so avoid emojis, bullet points, or other formatting that can't be spoken. Respond to what the user said in a creative, helpful, and brief way. You are able to describe images from the user camera.", ), ) llm.register_function("fetch_user_image", fetch_user_image) diff --git a/examples/foundational/14d-function-calling-openai-video.py b/examples/foundational/14d-function-calling-openai-video.py index 1eac522e8..59bef64b6 100644 --- a/examples/foundational/14d-function-calling-openai-video.py +++ b/examples/foundational/14d-function-calling-openai-video.py @@ -99,7 +99,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): llm = OpenAILLMService( api_key=os.getenv("OPENAI_API_KEY"), settings=OpenAILLMService.Settings( - system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way. You are able to describe images from the user camera.", + system_instruction="You are a helpful assistant in a voice conversation. Your responses will be spoken aloud, so avoid emojis, bullet points, or other formatting that can't be spoken. Respond to what the user said in a creative, helpful, and brief way. You are able to describe images from the user camera.", ), ) llm.register_function("fetch_user_image", fetch_user_image) diff --git a/examples/foundational/14f-function-calling-groq.py b/examples/foundational/14f-function-calling-groq.py index a6f383a1f..1e6e84338 100644 --- a/examples/foundational/14f-function-calling-groq.py +++ b/examples/foundational/14f-function-calling-groq.py @@ -72,7 +72,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): llm = GroqLLMService( api_key=os.getenv("GROQ_API_KEY"), settings=GroqLLMService.Settings( - system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + system_instruction="You are a helpful assistant in a voice conversation. Your responses will be spoken aloud, so avoid emojis, bullet points, or other formatting that can't be spoken. Respond to what the user said in a creative, helpful, and brief way.", ), ) # You can also register a function_name of None to get all functions diff --git a/examples/foundational/14g-function-calling-grok.py b/examples/foundational/14g-function-calling-grok.py index 283fd40fd..4de1f6528 100644 --- a/examples/foundational/14g-function-calling-grok.py +++ b/examples/foundational/14g-function-calling-grok.py @@ -72,7 +72,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): llm = GrokLLMService( api_key=os.getenv("GROK_API_KEY"), settings=GrokLLMService.Settings( - system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + system_instruction="You are a helpful assistant in a voice conversation. Your responses will be spoken aloud, so avoid emojis, bullet points, or other formatting that can't be spoken. Respond to what the user said in a creative, helpful, and brief way.", ), ) # You can also register a function_name of None to get all functions diff --git a/examples/foundational/14h-function-calling-azure.py b/examples/foundational/14h-function-calling-azure.py index 3aae0c490..23c156da4 100644 --- a/examples/foundational/14h-function-calling-azure.py +++ b/examples/foundational/14h-function-calling-azure.py @@ -74,7 +74,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): endpoint=os.getenv("AZURE_CHATGPT_ENDPOINT"), settings=AzureLLMService.Settings( model=os.getenv("AZURE_CHATGPT_MODEL"), - system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + system_instruction="You are a helpful assistant in a voice conversation. Your responses will be spoken aloud, so avoid emojis, bullet points, or other formatting that can't be spoken. Respond to what the user said in a creative, helpful, and brief way.", ), ) # You can also register a function_name of None to get all functions diff --git a/examples/foundational/14i-function-calling-fireworks.py b/examples/foundational/14i-function-calling-fireworks.py index c82165b17..f58ef73d9 100644 --- a/examples/foundational/14i-function-calling-fireworks.py +++ b/examples/foundational/14i-function-calling-fireworks.py @@ -73,7 +73,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): api_key=os.getenv("FIREWORKS_API_KEY"), settings=FireworksLLMService.Settings( model="accounts/fireworks/models/gpt-oss-20b", - system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + system_instruction="You are a helpful assistant in a voice conversation. Your responses will be spoken aloud, so avoid emojis, bullet points, or other formatting that can't be spoken. Respond to what the user said in a creative, helpful, and brief way.", ), ) # You can also register a function_name of None to get all functions diff --git a/examples/foundational/14j-function-calling-nvidia.py b/examples/foundational/14j-function-calling-nvidia.py index 7dd772c03..e3db6db8d 100644 --- a/examples/foundational/14j-function-calling-nvidia.py +++ b/examples/foundational/14j-function-calling-nvidia.py @@ -75,7 +75,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): model="nvidia/llama-3.3-nemotron-super-49b-v1.5", # Recommended when turning thinking off temperature=0.0, - system_instruction="/no_think You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + system_instruction="/no_think You are a helpful assistant in a voice conversation. Your responses will be spoken aloud, so avoid emojis, bullet points, or other formatting that can't be spoken. Respond to what the user said in a creative, helpful, and brief way.", ), ) # You can also register a function_name of None to get all functions diff --git a/examples/foundational/14k-function-calling-cerebras.py b/examples/foundational/14k-function-calling-cerebras.py index 51b9c9bf9..ad8475185 100644 --- a/examples/foundational/14k-function-calling-cerebras.py +++ b/examples/foundational/14k-function-calling-cerebras.py @@ -72,7 +72,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): llm = CerebrasLLMService( api_key=os.getenv("CEREBRAS_API_KEY"), settings=CerebrasLLMService.Settings( - system_instruction="""You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. + system_instruction="""You are a helpful assistant in a voice conversation. Your responses will be spoken aloud, so avoid emojis, bullet points, or other formatting that can't be spoken. Respond to what the user said in a creative, helpful, and brief way. You have one functions available: diff --git a/examples/foundational/14l-function-calling-deepseek.py b/examples/foundational/14l-function-calling-deepseek.py index 4af091b7a..f115299e2 100644 --- a/examples/foundational/14l-function-calling-deepseek.py +++ b/examples/foundational/14l-function-calling-deepseek.py @@ -73,7 +73,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): api_key=os.getenv("DEEPSEEK_API_KEY"), settings=DeepSeekLLMService.Settings( model="deepseek-chat", - system_instruction="""You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. + system_instruction="""You are a helpful assistant in a voice conversation. Your responses will be spoken aloud, so avoid emojis, bullet points, or other formatting that can't be spoken. Respond to what the user said in a creative, helpful, and brief way. You have one functions available: diff --git a/examples/foundational/14m-function-calling-openrouter.py b/examples/foundational/14m-function-calling-openrouter.py index e23865435..b341ca71c 100644 --- a/examples/foundational/14m-function-calling-openrouter.py +++ b/examples/foundational/14m-function-calling-openrouter.py @@ -77,7 +77,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): api_key=os.getenv("OPENROUTER_API_KEY"), settings=OpenRouterLLMService.Settings( model="openai/gpt-4o-2024-11-20", - system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + system_instruction="You are a helpful assistant in a voice conversation. Your responses will be spoken aloud, so avoid emojis, bullet points, or other formatting that can't be spoken. Respond to what the user said in a creative, helpful, and brief way.", ), ) # You can also register a function_name of None to get all functions diff --git a/examples/foundational/14n-function-calling-perplexity.py b/examples/foundational/14n-function-calling-perplexity.py index 2c1ba9e00..a67e93ab8 100644 --- a/examples/foundational/14n-function-calling-perplexity.py +++ b/examples/foundational/14n-function-calling-perplexity.py @@ -70,7 +70,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): llm = PerplexityLLMService( api_key=os.getenv("PERPLEXITY_API_KEY"), settings=PerplexityLLMService.Settings( - system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way, but try to be brief.", + system_instruction="You are a helpful assistant in a voice conversation. Your responses will be spoken aloud, so avoid emojis, bullet points, or other formatting that can't be spoken. Respond to what the user said in a creative, helpful, and brief way.", ), ) diff --git a/examples/foundational/14o-function-calling-gemini-openai-format.py b/examples/foundational/14o-function-calling-gemini-openai-format.py index 8ab53d9cf..70e8af3d3 100644 --- a/examples/foundational/14o-function-calling-gemini-openai-format.py +++ b/examples/foundational/14o-function-calling-gemini-openai-format.py @@ -72,7 +72,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): llm = GoogleLLMOpenAIBetaService( api_key=os.getenv("GOOGLE_API_KEY"), settings=GoogleLLMOpenAIBetaService.Settings( - system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + system_instruction="You are a helpful assistant in a voice conversation. Your responses will be spoken aloud, so avoid emojis, bullet points, or other formatting that can't be spoken. Respond to what the user said in a creative, helpful, and brief way.", ), ) # You can aslo register a function_name of None to get all functions diff --git a/examples/foundational/14p-function-calling-gemini-vertex-ai.py b/examples/foundational/14p-function-calling-gemini-vertex-ai.py index c6259b992..fb3910ed3 100644 --- a/examples/foundational/14p-function-calling-gemini-vertex-ai.py +++ b/examples/foundational/14p-function-calling-gemini-vertex-ai.py @@ -74,7 +74,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): project_id=os.getenv("GOOGLE_CLOUD_PROJECT_ID"), location=os.getenv("GOOGLE_CLOUD_LOCATION"), settings=GoogleVertexLLMService.Settings( - system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + system_instruction="You are a helpful assistant in a voice conversation. Your responses will be spoken aloud, so avoid emojis, bullet points, or other formatting that can't be spoken. Respond to what the user said in a creative, helpful, and brief way.", ), ) # You can aslo register a function_name of None to get all functions diff --git a/examples/foundational/14q-function-calling-qwen.py b/examples/foundational/14q-function-calling-qwen.py index bf866a519..9a6bf6d8b 100644 --- a/examples/foundational/14q-function-calling-qwen.py +++ b/examples/foundational/14q-function-calling-qwen.py @@ -73,7 +73,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): api_key=os.getenv("QWEN_API_KEY"), model="qwen2.5-72b-instruct", settings=QwenLLMService.Settings( - system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + system_instruction="You are a helpful assistant in a voice conversation. Your responses will be spoken aloud, so avoid emojis, bullet points, or other formatting that can't be spoken. Respond to what the user said in a creative, helpful, and brief way.", ), ) diff --git a/examples/foundational/14r-function-calling-aws.py b/examples/foundational/14r-function-calling-aws.py index 29591c80a..86ee0f0dc 100644 --- a/examples/foundational/14r-function-calling-aws.py +++ b/examples/foundational/14r-function-calling-aws.py @@ -78,7 +78,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): settings=AWSBedrockLLMService.Settings( model="us.anthropic.claude-sonnet-4-6", temperature=0.8, - system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + system_instruction="You are a helpful assistant in a voice conversation. Your responses will be spoken aloud, so avoid emojis, bullet points, or other formatting that can't be spoken. Respond to what the user said in a creative, helpful, and brief way.", ), ) diff --git a/examples/foundational/14s-function-calling-sambanova.py b/examples/foundational/14s-function-calling-sambanova.py index c329135f9..3854d2d6e 100644 --- a/examples/foundational/14s-function-calling-sambanova.py +++ b/examples/foundational/14s-function-calling-sambanova.py @@ -75,7 +75,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): llm = SambaNovaLLMService( api_key=os.getenv("SAMBANOVA_API_KEY"), settings=SambaNovaLLMService.Settings( - system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + system_instruction="You are a helpful assistant in a voice conversation. Your responses will be spoken aloud, so avoid emojis, bullet points, or other formatting that can't be spoken. Respond to what the user said in a creative, helpful, and brief way.", ), ) # You can also register a function_name of None to get all functions diff --git a/examples/foundational/14t-function-calling-direct.py b/examples/foundational/14t-function-calling-direct.py index 7b4485226..1c6ebe072 100644 --- a/examples/foundational/14t-function-calling-direct.py +++ b/examples/foundational/14t-function-calling-direct.py @@ -88,7 +88,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): llm = OpenAILLMService( api_key=os.getenv("OPENAI_API_KEY"), settings=OpenAILLMService.Settings( - system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + system_instruction="You are a helpful assistant in a voice conversation. Your responses will be spoken aloud, so avoid emojis, bullet points, or other formatting that can't be spoken. Respond to what the user said in a creative, helpful, and brief way.", ), ) diff --git a/examples/foundational/14u-function-calling-ollama.py b/examples/foundational/14u-function-calling-ollama.py index a0c1ec33a..87491f3d6 100644 --- a/examples/foundational/14u-function-calling-ollama.py +++ b/examples/foundational/14u-function-calling-ollama.py @@ -76,7 +76,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): llm = OLLamaLLMService( settings=OLLamaLLMService.Settings( model="llama3.2", - system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + system_instruction="You are a helpful assistant in a voice conversation. Your responses will be spoken aloud, so avoid emojis, bullet points, or other formatting that can't be spoken. Respond to what the user said in a creative, helpful, and brief way.", ), ) # Update to the model you're running locally diff --git a/examples/foundational/14v-function-calling-openai.py b/examples/foundational/14v-function-calling-openai.py index db759b186..2b59d7072 100644 --- a/examples/foundational/14v-function-calling-openai.py +++ b/examples/foundational/14v-function-calling-openai.py @@ -82,7 +82,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): llm = OpenAILLMService( api_key=os.getenv("OPENAI_API_KEY"), settings=OpenAILLMService.Settings( - system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + system_instruction="You are a helpful assistant in a voice conversation. Your responses will be spoken aloud, so avoid emojis, bullet points, or other formatting that can't be spoken. Respond to what the user said in a creative, helpful, and brief way.", ), ) diff --git a/examples/foundational/14w-function-calling-mistral.py b/examples/foundational/14w-function-calling-mistral.py index 421a63b74..c52d46c03 100644 --- a/examples/foundational/14w-function-calling-mistral.py +++ b/examples/foundational/14w-function-calling-mistral.py @@ -75,7 +75,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): llm = MistralLLMService( api_key=os.getenv("MISTRAL_API_KEY"), settings=MistralLLMService.Settings( - system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + system_instruction="You are a helpful assistant in a voice conversation. Your responses will be spoken aloud, so avoid emojis, bullet points, or other formatting that can't be spoken. Respond to what the user said in a creative, helpful, and brief way.", ), ) diff --git a/examples/foundational/14x-function-calling-openpipe.py b/examples/foundational/14x-function-calling-openpipe.py index e82062c16..5074bda2f 100644 --- a/examples/foundational/14x-function-calling-openpipe.py +++ b/examples/foundational/14x-function-calling-openpipe.py @@ -79,7 +79,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): openpipe_api_key=os.getenv("OPENPIPE_API_KEY"), tags={"conversation_id": f"pipecat-{timestamp}"}, settings=OpenPipeLLMService.Settings( - system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + system_instruction="You are a helpful assistant in a voice conversation. Your responses will be spoken aloud, so avoid emojis, bullet points, or other formatting that can't be spoken. Respond to what the user said in a creative, helpful, and brief way.", ), ) diff --git a/examples/foundational/15-switch-voices.py b/examples/foundational/15-switch-voices.py index 39918918b..daf77ecde 100644 --- a/examples/foundational/15-switch-voices.py +++ b/examples/foundational/15-switch-voices.py @@ -121,7 +121,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): llm = OpenAILLMService( api_key=os.getenv("OPENAI_API_KEY"), settings=OpenAILLMService.Settings( - system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities. Respond to what the user said in a creative and helpful way. Your output should not include non-alphanumeric characters. You can do the following voices: 'News Lady', 'British Lady' and 'Barbershop Man'.", + system_instruction="You are a helpful assistant in a voice conversation. Your responses will be spoken aloud, so avoid emojis, bullet points, or other formatting that can't be spoken. Respond to what the user said in a creative and helpful way. You can do the following voices: 'News Lady', 'British Lady' and 'Barbershop Man'.", ), ) llm.register_function("switch_voice", tts.switch_voice) diff --git a/examples/foundational/15a-switch-languages.py b/examples/foundational/15a-switch-languages.py index 67d943a0a..0ff13df1a 100644 --- a/examples/foundational/15a-switch-languages.py +++ b/examples/foundational/15a-switch-languages.py @@ -112,7 +112,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): llm = OpenAILLMService( api_key=os.getenv("OPENAI_API_KEY"), settings=OpenAILLMService.Settings( - system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities. Respond to what the user said in a creative and helpful way. Your output should not include non-alphanumeric characters. You can speak the following languages: 'English' and 'Spanish'.", + system_instruction="You are a helpful assistant in a voice conversation. Your responses will be spoken aloud, so avoid emojis, bullet points, or other formatting that can't be spoken. Respond to what the user said in a creative, helpful, and brief way. You can speak the following languages: 'English' and 'Spanish'.", ), ) llm.register_function("switch_language", tts.switch_language) diff --git a/examples/foundational/16-gpu-container-local-bot.py b/examples/foundational/16-gpu-container-local-bot.py index 2b680eee1..b12d85dff 100644 --- a/examples/foundational/16-gpu-container-local-bot.py +++ b/examples/foundational/16-gpu-container-local-bot.py @@ -72,7 +72,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): # Or, to use a local vLLM (or similar) api server settings=OpenAILLMService.Settings( model="meta-llama/Meta-Llama-3-8B-Instruct", - system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + system_instruction="You are a helpful assistant in a voice conversation. Your responses will be spoken aloud, so avoid emojis, bullet points, or other formatting that can't be spoken. Respond to what the user said in a creative, helpful, and brief way.", ), base_url="http://0.0.0.0:8000/v1", ) diff --git a/examples/foundational/17-detect-user-idle.py b/examples/foundational/17-detect-user-idle.py index a1ac00501..1cd772af2 100644 --- a/examples/foundational/17-detect-user-idle.py +++ b/examples/foundational/17-detect-user-idle.py @@ -123,7 +123,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): llm = OpenAILLMService( api_key=os.getenv("OPENAI_API_KEY"), settings=OpenAILLMService.Settings( - system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + system_instruction="You are a helpful assistant in a voice conversation. Your responses will be spoken aloud, so avoid emojis, bullet points, or other formatting that can't be spoken. Respond to what the user said in a creative, helpful, and brief way.", ), ) diff --git a/examples/foundational/20a-persistent-context-openai.py b/examples/foundational/20a-persistent-context-openai.py index d487133f5..f6a4dc937 100644 --- a/examples/foundational/20a-persistent-context-openai.py +++ b/examples/foundational/20a-persistent-context-openai.py @@ -95,7 +95,7 @@ async def load_conversation(params: FunctionCallParams): await params.result_callback({"success": False, "error": str(e)}) -system_instruction = "You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way." +system_instruction = "You are a helpful assistant in a voice conversation. Your responses will be spoken aloud, so avoid emojis, bullet points, or other formatting that can't be spoken. Respond to what the user said in a creative, helpful, and brief way." weather_function = FunctionSchema( name="get_current_weather", diff --git a/examples/foundational/20c-persistent-context-anthropic.py b/examples/foundational/20c-persistent-context-anthropic.py index e7a8335ba..1b74c87e1 100644 --- a/examples/foundational/20c-persistent-context-anthropic.py +++ b/examples/foundational/20c-persistent-context-anthropic.py @@ -94,7 +94,7 @@ async def load_conversation(params: FunctionCallParams): await params.result_callback({"success": False, "error": str(e)}) -system_instruction = "You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a succinct, creative and helpful way. Prefer responses that are one sentence long unless you are asked for a longer or more detailed response." +system_instruction = "You are a helpful assistant in a voice conversation. Your responses will be spoken aloud, so avoid emojis, bullet points, or other formatting that can't be spoken. Respond to what the user said in a succinct, creative and helpful way. Prefer responses that are one sentence long unless you are asked for a longer or more detailed response." weather_function = FunctionSchema( name="get_current_weather", diff --git a/examples/foundational/20d-persistent-context-gemini.py b/examples/foundational/20d-persistent-context-gemini.py index 638728331..ae37e19ce 100644 --- a/examples/foundational/20d-persistent-context-gemini.py +++ b/examples/foundational/20d-persistent-context-gemini.py @@ -122,8 +122,8 @@ async def load_conversation(params: FunctionCallParams): await params.result_callback({"success": False, "error": str(e)}) -system_instruction = """You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your -capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that +system_instruction = """You are a helpful assistant in a voice conversation. Your goal is to demonstrate your +capabilities in a succinct way. Your responses will be spoken aloud, so avoid emojis, bullet points, or other formatting that can't be spoken. Keep responses concise. Respond to what the user said in a creative can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way. diff --git a/examples/foundational/21-tavus-transport.py b/examples/foundational/21-tavus-transport.py index 1ac54ff19..f09902fcd 100644 --- a/examples/foundational/21-tavus-transport.py +++ b/examples/foundational/21-tavus-transport.py @@ -59,7 +59,7 @@ async def main(): llm = GoogleLLMService( api_key=os.getenv("GOOGLE_API_KEY"), settings=GoogleLLMService.Settings( - system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + system_instruction="You are a helpful assistant in a voice conversation. Your responses will be spoken aloud, so avoid emojis, bullet points, or other formatting that can't be spoken. Respond to what the user said in a creative, helpful, and brief way.", ), ) diff --git a/examples/foundational/21a-tavus-video-service.py b/examples/foundational/21a-tavus-video-service.py index f716d88d8..6e03a2418 100644 --- a/examples/foundational/21a-tavus-video-service.py +++ b/examples/foundational/21a-tavus-video-service.py @@ -69,7 +69,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): llm = GoogleLLMService( api_key=os.getenv("GOOGLE_API_KEY"), settings=GoogleLLMService.Settings( - system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + system_instruction="You are a helpful assistant in a voice conversation. Your responses will be spoken aloud, so avoid emojis, bullet points, or other formatting that can't be spoken. Respond to what the user said in a creative, helpful, and brief way.", ), ) diff --git a/examples/foundational/22-filter-incomplete-turns.py b/examples/foundational/22-filter-incomplete-turns.py index 454e22722..8a3001366 100644 --- a/examples/foundational/22-filter-incomplete-turns.py +++ b/examples/foundational/22-filter-incomplete-turns.py @@ -71,7 +71,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): llm = OpenAILLMService( api_key=os.getenv("OPENAI_API_KEY"), settings=OpenAILLMService.Settings( - system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + system_instruction="You are a helpful assistant in a voice conversation. Your responses will be spoken aloud, so avoid emojis, bullet points, or other formatting that can't be spoken. Respond to what the user said in a creative, helpful, and brief way.", ), ) diff --git a/examples/foundational/23-bot-background-sound.py b/examples/foundational/23-bot-background-sound.py index 6f6cf8eb7..0229db419 100644 --- a/examples/foundational/23-bot-background-sound.py +++ b/examples/foundational/23-bot-background-sound.py @@ -83,7 +83,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): llm = OpenAILLMService( api_key=os.getenv("OPENAI_API_KEY"), settings=OpenAILLMService.Settings( - system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + system_instruction="You are a helpful assistant in a voice conversation. Your responses will be spoken aloud, so avoid emojis, bullet points, or other formatting that can't be spoken. Respond to what the user said in a creative, helpful, and brief way.", ), ) diff --git a/examples/foundational/25-google-audio-in.py b/examples/foundational/25-google-audio-in.py index 6b549a7fe..7a6c910e7 100644 --- a/examples/foundational/25-google-audio-in.py +++ b/examples/foundational/25-google-audio-in.py @@ -47,7 +47,7 @@ load_dotenv(override=True) # The system prompt for the main conversation. # conversation_system_message = """ -You are a helpful LLM in a WebRTC call. Your goals are to be helpful and brief in your responses. Respond with one or two sentences at most, unless you are asked to +You are a helpful LLM in a voice call. Your goals are to be helpful and brief in your responses. Respond with one or two sentences at most, unless you are asked to respond at more length. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. """ diff --git a/examples/foundational/27-simli-layer.py b/examples/foundational/27-simli-layer.py index b2cbb6837..76c2dd99d 100644 --- a/examples/foundational/27-simli-layer.py +++ b/examples/foundational/27-simli-layer.py @@ -73,7 +73,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): llm = OpenAILLMService( api_key=os.getenv("OPENAI_API_KEY"), settings=OpenAILLMService.Settings( - system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + system_instruction="You are a helpful assistant in a voice conversation. Your responses will be spoken aloud, so avoid emojis, bullet points, or other formatting that can't be spoken. Respond to what the user said in a creative, helpful, and brief way.", ), ) diff --git a/examples/foundational/28-user-assistant-turns.py b/examples/foundational/28-user-assistant-turns.py index b439794b5..d1c053710 100644 --- a/examples/foundational/28-user-assistant-turns.py +++ b/examples/foundational/28-user-assistant-turns.py @@ -130,7 +130,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): llm = OpenAILLMService( api_key=os.getenv("OPENAI_API_KEY"), settings=OpenAILLMService.Settings( - system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative, helpful, and brief way.", + system_instruction="You are a helpful assistant in a voice conversation. Your responses will be spoken aloud, so avoid emojis, bullet points, or other formatting that can't be spoken. Respond to what the user said in a creative, helpful, and brief way.", ), ) diff --git a/examples/foundational/29-turn-tracking-observer.py b/examples/foundational/29-turn-tracking-observer.py index f17dd0260..e4c33a379 100644 --- a/examples/foundational/29-turn-tracking-observer.py +++ b/examples/foundational/29-turn-tracking-observer.py @@ -81,7 +81,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): llm = OpenAILLMService( api_key=os.getenv("OPENAI_API_KEY"), settings=OpenAILLMService.Settings( - system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + system_instruction="You are a helpful assistant in a voice conversation. Your responses will be spoken aloud, so avoid emojis, bullet points, or other formatting that can't be spoken. Respond to what the user said in a creative, helpful, and brief way.", ), ) diff --git a/examples/foundational/30-observer.py b/examples/foundational/30-observer.py index 227a8978b..523e09583 100644 --- a/examples/foundational/30-observer.py +++ b/examples/foundational/30-observer.py @@ -112,7 +112,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): llm = OpenAILLMService( api_key=os.getenv("OPENAI_API_KEY"), settings=OpenAILLMService.Settings( - system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + system_instruction="You are a helpful assistant in a voice conversation. Your responses will be spoken aloud, so avoid emojis, bullet points, or other formatting that can't be spoken. Respond to what the user said in a creative, helpful, and brief way.", ), ) diff --git a/examples/foundational/34-audio-recording.py b/examples/foundational/34-audio-recording.py index 6ddfa6033..68354e0dd 100644 --- a/examples/foundational/34-audio-recording.py +++ b/examples/foundational/34-audio-recording.py @@ -120,7 +120,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): llm = OpenAILLMService( api_key=os.getenv("OPENAI_API_KEY"), settings=OpenAILLMService.Settings( - system_instruction="You are a helpful assistant demonstrating audio recording capabilities. Keep your responses brief and clear.", + system_instruction="You are a helpful assistant in a voice conversation. Your responses will be spoken aloud, so avoid emojis, bullet points, or other formatting that can't be spoken. Respond to what the user said in a creative, helpful, and brief way.", ), ) diff --git a/examples/foundational/38-smart-turn-fal.py b/examples/foundational/38-smart-turn-fal.py index b2de247d7..b8a62626a 100644 --- a/examples/foundational/38-smart-turn-fal.py +++ b/examples/foundational/38-smart-turn-fal.py @@ -69,7 +69,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): llm = OpenAILLMService( api_key=os.getenv("OPENAI_API_KEY"), settings=OpenAILLMService.Settings( - system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + system_instruction="You are a helpful assistant in a voice conversation. Your responses will be spoken aloud, so avoid emojis, bullet points, or other formatting that can't be spoken. Respond to what the user said in a creative, helpful, and brief way.", ), ) diff --git a/examples/foundational/38a-smart-turn-local-coreml.py b/examples/foundational/38a-smart-turn-local-coreml.py index 3073ba0dd..fc2f1d14d 100644 --- a/examples/foundational/38a-smart-turn-local-coreml.py +++ b/examples/foundational/38a-smart-turn-local-coreml.py @@ -84,7 +84,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): llm = OpenAILLMService( api_key=os.getenv("OPENAI_API_KEY"), settings=OpenAILLMService.Settings( - system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + system_instruction="You are a helpful assistant in a voice conversation. Your responses will be spoken aloud, so avoid emojis, bullet points, or other formatting that can't be spoken. Respond to what the user said in a creative, helpful, and brief way.", ), ) diff --git a/examples/foundational/38b-smart-turn-local.py b/examples/foundational/38b-smart-turn-local.py index de8b214ea..7e4a0abd8 100644 --- a/examples/foundational/38b-smart-turn-local.py +++ b/examples/foundational/38b-smart-turn-local.py @@ -66,7 +66,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): llm = OpenAILLMService( api_key=os.getenv("OPENAI_API_KEY"), settings=OpenAILLMService.Settings( - system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + system_instruction="You are a helpful assistant in a voice conversation. Your responses will be spoken aloud, so avoid emojis, bullet points, or other formatting that can't be spoken. Respond to what the user said in a creative, helpful, and brief way.", ), ) diff --git a/examples/foundational/39-mcp-stdio.py b/examples/foundational/39-mcp-stdio.py index d46c034d1..48382046d 100644 --- a/examples/foundational/39-mcp-stdio.py +++ b/examples/foundational/39-mcp-stdio.py @@ -143,7 +143,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): ) system_prompt = f""" - You are a helpful LLM in a WebRTC call. + You are a helpful LLM in a voice call. Your goal is to demonstrate your capabilities in a succinct way. You have access to tools to search the Rijksmuseum collection. Offer, for example, to show a floral still life, use the `search_artwork` tool. diff --git a/examples/foundational/39a-mcp-streamable-http.py b/examples/foundational/39a-mcp-streamable-http.py index b71938e43..5ddf53264 100644 --- a/examples/foundational/39a-mcp-streamable-http.py +++ b/examples/foundational/39a-mcp-streamable-http.py @@ -64,7 +64,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): ) system_prompt = f""" - You are a helpful LLM in a WebRTC call. + You are a helpful LLM in a voice call. Your goal is to answer questions about the user's GitHub repositories and account. You have access to a number of tools provided by Github. Use any and all tools to help users. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. diff --git a/examples/foundational/39b-mcp-streamable-http-gemini-live.py b/examples/foundational/39b-mcp-streamable-http-gemini-live.py index 19a5aa1b6..eb276a91a 100644 --- a/examples/foundational/39b-mcp-streamable-http-gemini-live.py +++ b/examples/foundational/39b-mcp-streamable-http-gemini-live.py @@ -86,7 +86,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): logger.exception("error trace:") system = f""" - You are a helpful LLM in a WebRTC call. + You are a helpful LLM in a voice call. Your goal is to answer questions about the user's GitHub repositories and account. You have access to a number of tools provided by Github. Use any and all tools to help users. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. diff --git a/examples/foundational/39c-multiple-mcp.py b/examples/foundational/39c-multiple-mcp.py index eabfeccab..9d449251d 100644 --- a/examples/foundational/39c-multiple-mcp.py +++ b/examples/foundational/39c-multiple-mcp.py @@ -126,7 +126,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): ) system_prompt = f""" - You are a helpful LLM in a WebRTC call. + You are a helpful LLM in a voice call. Your goal is to demonstrate your capabilities in a succinct way. You have access to tools to search the Rijksmuseum collection and the user's GitHub repositories and account. Offer, for example, to show a floral still life, use the `search_artwork` tool. diff --git a/examples/foundational/42-interruption-config.py b/examples/foundational/42-interruption-config.py index d690f60f0..64ea2cee0 100644 --- a/examples/foundational/42-interruption-config.py +++ b/examples/foundational/42-interruption-config.py @@ -67,7 +67,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): llm = OpenAILLMService( api_key=os.getenv("OPENAI_API_KEY"), settings=OpenAILLMService.Settings( - system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + system_instruction="You are a helpful assistant in a voice conversation. Your responses will be spoken aloud, so avoid emojis, bullet points, or other formatting that can't be spoken. Respond to what the user said in a creative, helpful, and brief way.", ), ) diff --git a/examples/foundational/44-voicemail-detection.py b/examples/foundational/44-voicemail-detection.py index df47bb945..854e546ec 100644 --- a/examples/foundational/44-voicemail-detection.py +++ b/examples/foundational/44-voicemail-detection.py @@ -64,7 +64,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): llm = OpenAILLMService( api_key=os.getenv("OPENAI_API_KEY"), settings=OpenAILLMService.Settings( - system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + system_instruction="You are a helpful assistant in a voice conversation. Your responses will be spoken aloud, so avoid emojis, bullet points, or other formatting that can't be spoken. Respond to what the user said in a creative, helpful, and brief way.", ), ) classifier_llm = OpenAILLMService(api_key=os.getenv("OPENAI_API_KEY")) diff --git a/examples/foundational/45-before-and-after-events.py b/examples/foundational/45-before-and-after-events.py index 3c583546f..3a36a626a 100644 --- a/examples/foundational/45-before-and-after-events.py +++ b/examples/foundational/45-before-and-after-events.py @@ -75,7 +75,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): llm = OpenAILLMService( api_key=os.getenv("OPENAI_API_KEY"), settings=OpenAILLMService.Settings( - system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + system_instruction="You are a helpful assistant in a voice conversation. Your responses will be spoken aloud, so avoid emojis, bullet points, or other formatting that can't be spoken. Respond to what the user said in a creative, helpful, and brief way.", ), ) diff --git a/examples/foundational/47-sentry-metrics.py b/examples/foundational/47-sentry-metrics.py index 9fe35d4c4..3294727dc 100644 --- a/examples/foundational/47-sentry-metrics.py +++ b/examples/foundational/47-sentry-metrics.py @@ -76,7 +76,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): api_key=os.getenv("OPENAI_API_KEY"), metrics=SentryMetrics(), settings=OpenAILLMService.Settings( - system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + system_instruction="You are a helpful assistant in a voice conversation. Your responses will be spoken aloud, so avoid emojis, bullet points, or other formatting that can't be spoken. Respond to what the user said in a creative, helpful, and brief way.", ), ) diff --git a/examples/foundational/48-service-switcher.py b/examples/foundational/48-service-switcher.py index 0947bc6c2..9225963f7 100644 --- a/examples/foundational/48-service-switcher.py +++ b/examples/foundational/48-service-switcher.py @@ -114,7 +114,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): # Uses ServiceSwitcherStrategyManual by default tts_switcher = ServiceSwitcher(services=[tts_cartesia, tts_deepgram]) - system_prompt = "You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way." + system_prompt = "You are a helpful assistant in a voice conversation. Your responses will be spoken aloud, so avoid emojis, bullet points, or other formatting that can't be spoken. Respond to what the user said in a creative, helpful, and brief way." llm_openai = OpenAILLMService( api_key=os.getenv("OPENAI_API_KEY"), diff --git a/examples/foundational/49a-thinking-anthropic.py b/examples/foundational/49a-thinking-anthropic.py index 727e8e0a7..0495d5e97 100644 --- a/examples/foundational/49a-thinking-anthropic.py +++ b/examples/foundational/49a-thinking-anthropic.py @@ -68,7 +68,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): type="enabled", budget_tokens=2048, ), - system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + system_instruction="You are a helpful assistant in a voice conversation. Your responses will be spoken aloud, so avoid emojis, bullet points, or other formatting that can't be spoken. Respond to what the user said in a creative, helpful, and brief way.", ), ) diff --git a/examples/foundational/49b-thinking-google.py b/examples/foundational/49b-thinking-google.py index b2b44d59a..1cfeba456 100644 --- a/examples/foundational/49b-thinking-google.py +++ b/examples/foundational/49b-thinking-google.py @@ -69,7 +69,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): thinking_budget=-1, # Dynamic thinking include_thoughts=True, ), - system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + system_instruction="You are a helpful assistant in a voice conversation. Your responses will be spoken aloud, so avoid emojis, bullet points, or other formatting that can't be spoken. Respond to what the user said in a creative, helpful, and brief way.", ), ) diff --git a/examples/foundational/49c-thinking-functions-anthropic.py b/examples/foundational/49c-thinking-functions-anthropic.py index d6b2749e1..1ce5832fc 100644 --- a/examples/foundational/49c-thinking-functions-anthropic.py +++ b/examples/foundational/49c-thinking-functions-anthropic.py @@ -89,7 +89,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): type="enabled", budget_tokens=2048, ), - system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + system_instruction="You are a helpful assistant in a voice conversation. Your responses will be spoken aloud, so avoid emojis, bullet points, or other formatting that can't be spoken. Respond to what the user said in a creative, helpful, and brief way.", ), ) diff --git a/examples/foundational/49d-thinking-functions-google.py b/examples/foundational/49d-thinking-functions-google.py index f5b9a1d20..0b62fbf2e 100644 --- a/examples/foundational/49d-thinking-functions-google.py +++ b/examples/foundational/49d-thinking-functions-google.py @@ -90,7 +90,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): thinking_budget=-1, # Dynamic thinking include_thoughts=True, ), - system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + system_instruction="You are a helpful assistant in a voice conversation. Your responses will be spoken aloud, so avoid emojis, bullet points, or other formatting that can't be spoken. Respond to what the user said in a creative, helpful, and brief way.", ), ) diff --git a/examples/foundational/53-concurrent-llm-evaluation.py b/examples/foundational/53-concurrent-llm-evaluation.py index 46b2847e9..69cebd0ac 100644 --- a/examples/foundational/53-concurrent-llm-evaluation.py +++ b/examples/foundational/53-concurrent-llm-evaluation.py @@ -70,7 +70,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): openai_llm = OpenAILLMService( api_key=os.getenv("OPENAI_API_KEY"), settings=OpenAILLMService.Settings( - system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + system_instruction="You are a helpful assistant in a voice conversation. Your responses will be spoken aloud, so avoid emojis, bullet points, or other formatting that can't be spoken. Respond to what the user said in a creative, helpful, and brief way.", ), ) diff --git a/examples/foundational/53-concurrent-llm-rtvi-ignored-sources.py b/examples/foundational/53-concurrent-llm-rtvi-ignored-sources.py index d27bd86a1..481d865e1 100644 --- a/examples/foundational/53-concurrent-llm-rtvi-ignored-sources.py +++ b/examples/foundational/53-concurrent-llm-rtvi-ignored-sources.py @@ -76,7 +76,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): main_llm = OpenAILLMService( api_key=os.getenv("OPENAI_API_KEY"), settings=OpenAILLMService.Settings( - system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + system_instruction="You are a helpful assistant in a voice conversation. Your responses will be spoken aloud, so avoid emojis, bullet points, or other formatting that can't be spoken. Respond to what the user said in a creative, helpful, and brief way.", ), ) diff --git a/examples/foundational/54-context-summarization-openai.py b/examples/foundational/54-context-summarization-openai.py index a536fc813..060eda8f7 100644 --- a/examples/foundational/54-context-summarization-openai.py +++ b/examples/foundational/54-context-summarization-openai.py @@ -89,7 +89,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): llm = OpenAILLMService( api_key=os.getenv("OPENAI_API_KEY"), settings=OpenAILLMService.Settings( - system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way. You have access to tools to get the current weather - use them when relevant.", + system_instruction="You are a helpful assistant in a voice conversation. Your responses will be spoken aloud, so avoid emojis, bullet points, or other formatting that can't be spoken. Respond to what the user said in a creative, helpful, and brief way. You have access to tools to get the current weather - use them when relevant.", ), ) diff --git a/examples/foundational/54a-context-summarization-google.py b/examples/foundational/54a-context-summarization-google.py index 942567c83..2727d34a8 100644 --- a/examples/foundational/54a-context-summarization-google.py +++ b/examples/foundational/54a-context-summarization-google.py @@ -89,7 +89,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): llm = GoogleLLMService( api_key=os.getenv("GOOGLE_API_KEY"), settings=GoogleLLMService.Settings( - system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way. You have access to tools to get the current weather - use them when relevant.", + system_instruction="You are a helpful assistant in a voice conversation. Your responses will be spoken aloud, so avoid emojis, bullet points, or other formatting that can't be spoken. Respond to what the user said in a creative, helpful, and brief way. You have access to tools to get the current weather - use them when relevant.", ), ) diff --git a/examples/foundational/54b-context-summarization-manual-openai.py b/examples/foundational/54b-context-summarization-manual-openai.py index 520e1c996..e6bdcaf00 100644 --- a/examples/foundational/54b-context-summarization-manual-openai.py +++ b/examples/foundational/54b-context-summarization-manual-openai.py @@ -81,7 +81,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): ), ) - system_prompt = """You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your + system_prompt = """You are a helpful LLM in a voice call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way. diff --git a/examples/foundational/54c-context-summarization-dedicated-llm.py b/examples/foundational/54c-context-summarization-dedicated-llm.py index 9f8f0b35d..ed56e343e 100644 --- a/examples/foundational/54c-context-summarization-dedicated-llm.py +++ b/examples/foundational/54c-context-summarization-dedicated-llm.py @@ -98,7 +98,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): ), ) - system_prompt = """You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your + system_prompt = """You are a helpful LLM in a voice call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way. diff --git a/examples/foundational/55a-update-settings-deepgram-flux-stt.py b/examples/foundational/55a-update-settings-deepgram-flux-stt.py index 237e5c3f7..d710015bd 100644 --- a/examples/foundational/55a-update-settings-deepgram-flux-stt.py +++ b/examples/foundational/55a-update-settings-deepgram-flux-stt.py @@ -63,7 +63,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): llm = OpenAILLMService( api_key=os.getenv("OPENAI_API_KEY"), settings=OpenAILLMService.Settings( - system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + system_instruction="You are a helpful assistant in a voice conversation. Your responses will be spoken aloud, so avoid emojis, bullet points, or other formatting that can't be spoken. Respond to what the user said in a creative, helpful, and brief way.", ), ) diff --git a/examples/foundational/55a-update-settings-deepgram-sagemaker-stt.py b/examples/foundational/55a-update-settings-deepgram-sagemaker-stt.py index 4b071d733..ebe3d4cce 100644 --- a/examples/foundational/55a-update-settings-deepgram-sagemaker-stt.py +++ b/examples/foundational/55a-update-settings-deepgram-sagemaker-stt.py @@ -66,7 +66,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): llm = OpenAILLMService( api_key=os.getenv("OPENAI_API_KEY"), settings=OpenAILLMService.Settings( - system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + system_instruction="You are a helpful assistant in a voice conversation. Your responses will be spoken aloud, so avoid emojis, bullet points, or other formatting that can't be spoken. Respond to what the user said in a creative, helpful, and brief way.", ), ) diff --git a/examples/foundational/55a-update-settings-deepgram-stt.py b/examples/foundational/55a-update-settings-deepgram-stt.py index 3c39c8cd5..46adaad6b 100644 --- a/examples/foundational/55a-update-settings-deepgram-stt.py +++ b/examples/foundational/55a-update-settings-deepgram-stt.py @@ -63,7 +63,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): llm = OpenAILLMService( api_key=os.getenv("OPENAI_API_KEY"), settings=OpenAILLMService.Settings( - system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + system_instruction="You are a helpful assistant in a voice conversation. Your responses will be spoken aloud, so avoid emojis, bullet points, or other formatting that can't be spoken. Respond to what the user said in a creative, helpful, and brief way.", ), ) diff --git a/examples/foundational/55b-update-settings-azure-stt.py b/examples/foundational/55b-update-settings-azure-stt.py index 59a411caf..8e5d3bfe3 100644 --- a/examples/foundational/55b-update-settings-azure-stt.py +++ b/examples/foundational/55b-update-settings-azure-stt.py @@ -66,7 +66,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): llm = OpenAILLMService( api_key=os.getenv("OPENAI_API_KEY"), settings=OpenAILLMService.Settings( - system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + system_instruction="You are a helpful assistant in a voice conversation. Your responses will be spoken aloud, so avoid emojis, bullet points, or other formatting that can't be spoken. Respond to what the user said in a creative, helpful, and brief way.", ), ) diff --git a/examples/foundational/55c-update-settings-google-stt.py b/examples/foundational/55c-update-settings-google-stt.py index c6d44da12..be62d90ad 100644 --- a/examples/foundational/55c-update-settings-google-stt.py +++ b/examples/foundational/55c-update-settings-google-stt.py @@ -63,7 +63,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): llm = OpenAILLMService( api_key=os.getenv("OPENAI_API_KEY"), settings=OpenAILLMService.Settings( - system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + system_instruction="You are a helpful assistant in a voice conversation. Your responses will be spoken aloud, so avoid emojis, bullet points, or other formatting that can't be spoken. Respond to what the user said in a creative, helpful, and brief way.", ), ) diff --git a/examples/foundational/55d-update-settings-assemblyai-stt.py b/examples/foundational/55d-update-settings-assemblyai-stt.py index f62a968eb..213873ab5 100644 --- a/examples/foundational/55d-update-settings-assemblyai-stt.py +++ b/examples/foundational/55d-update-settings-assemblyai-stt.py @@ -67,7 +67,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): llm = OpenAILLMService( api_key=os.getenv("OPENAI_API_KEY"), settings=OpenAILLMService.Settings( - system_instruction="You are a helpful LLM in a WebRTC call demonstrating dynamic keyterms updates. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Try saying difficult names like 'Xiomara', 'Saoirse', or 'Krzystof' to test transcription accuracy.", + system_instruction="You are a helpful assistant in a voice conversation. Your responses will be spoken aloud, so avoid emojis, bullet points, or other formatting that can't be spoken. Try saying difficult names like 'Xiomara', 'Saoirse', or 'Krzystof' to test transcription accuracy.", ), ) diff --git a/examples/foundational/55e-update-settings-gladia-stt.py b/examples/foundational/55e-update-settings-gladia-stt.py index 6ca8fa725..307ea2954 100644 --- a/examples/foundational/55e-update-settings-gladia-stt.py +++ b/examples/foundational/55e-update-settings-gladia-stt.py @@ -63,7 +63,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): llm = OpenAILLMService( api_key=os.getenv("OPENAI_API_KEY"), settings=OpenAILLMService.Settings( - system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + system_instruction="You are a helpful assistant in a voice conversation. Your responses will be spoken aloud, so avoid emojis, bullet points, or other formatting that can't be spoken. Respond to what the user said in a creative, helpful, and brief way.", ), ) diff --git a/examples/foundational/55f-update-settings-elevenlabs-realtime-stt.py b/examples/foundational/55f-update-settings-elevenlabs-realtime-stt.py index ee3244ffe..4fc351de0 100644 --- a/examples/foundational/55f-update-settings-elevenlabs-realtime-stt.py +++ b/examples/foundational/55f-update-settings-elevenlabs-realtime-stt.py @@ -63,7 +63,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): llm = OpenAILLMService( api_key=os.getenv("OPENAI_API_KEY"), settings=OpenAILLMService.Settings( - system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + system_instruction="You are a helpful assistant in a voice conversation. Your responses will be spoken aloud, so avoid emojis, bullet points, or other formatting that can't be spoken. Respond to what the user said in a creative, helpful, and brief way.", ), ) diff --git a/examples/foundational/55g-update-settings-elevenlabs-stt.py b/examples/foundational/55g-update-settings-elevenlabs-stt.py index 6307264fc..d610acea6 100644 --- a/examples/foundational/55g-update-settings-elevenlabs-stt.py +++ b/examples/foundational/55g-update-settings-elevenlabs-stt.py @@ -68,7 +68,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): llm = OpenAILLMService( api_key=os.getenv("OPENAI_API_KEY"), settings=OpenAILLMService.Settings( - system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + system_instruction="You are a helpful assistant in a voice conversation. Your responses will be spoken aloud, so avoid emojis, bullet points, or other formatting that can't be spoken. Respond to what the user said in a creative, helpful, and brief way.", ), ) diff --git a/examples/foundational/55h-update-settings-speechmatics-stt.py b/examples/foundational/55h-update-settings-speechmatics-stt.py index df6d9575b..eaa1874f6 100644 --- a/examples/foundational/55h-update-settings-speechmatics-stt.py +++ b/examples/foundational/55h-update-settings-speechmatics-stt.py @@ -70,7 +70,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): llm = OpenAILLMService( api_key=os.getenv("OPENAI_API_KEY"), settings=OpenAILLMService.Settings( - system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + system_instruction="You are a helpful assistant in a voice conversation. Your responses will be spoken aloud, so avoid emojis, bullet points, or other formatting that can't be spoken. Respond to what the user said in a creative, helpful, and brief way.", ), ) diff --git a/examples/foundational/55i-update-settings-whisper-api-stt.py b/examples/foundational/55i-update-settings-whisper-api-stt.py index e9ef61cce..179a65f83 100644 --- a/examples/foundational/55i-update-settings-whisper-api-stt.py +++ b/examples/foundational/55i-update-settings-whisper-api-stt.py @@ -69,7 +69,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): llm = OpenAILLMService( api_key=os.getenv("OPENAI_API_KEY"), settings=OpenAILLMService.Settings( - system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + system_instruction="You are a helpful assistant in a voice conversation. Your responses will be spoken aloud, so avoid emojis, bullet points, or other formatting that can't be spoken. Respond to what the user said in a creative, helpful, and brief way.", ), ) diff --git a/examples/foundational/55j-update-settings-sarvam-stt.py b/examples/foundational/55j-update-settings-sarvam-stt.py index 529cf461d..b65401dc5 100644 --- a/examples/foundational/55j-update-settings-sarvam-stt.py +++ b/examples/foundational/55j-update-settings-sarvam-stt.py @@ -63,7 +63,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): llm = OpenAILLMService( api_key=os.getenv("OPENAI_API_KEY"), settings=OpenAILLMService.Settings( - system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + system_instruction="You are a helpful assistant in a voice conversation. Your responses will be spoken aloud, so avoid emojis, bullet points, or other formatting that can't be spoken. Respond to what the user said in a creative, helpful, and brief way.", ), ) diff --git a/examples/foundational/55k-update-settings-soniox-stt.py b/examples/foundational/55k-update-settings-soniox-stt.py index 07e33b4cd..2a2548888 100644 --- a/examples/foundational/55k-update-settings-soniox-stt.py +++ b/examples/foundational/55k-update-settings-soniox-stt.py @@ -63,7 +63,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): llm = OpenAILLMService( api_key=os.getenv("OPENAI_API_KEY"), settings=OpenAILLMService.Settings( - system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + system_instruction="You are a helpful assistant in a voice conversation. Your responses will be spoken aloud, so avoid emojis, bullet points, or other formatting that can't be spoken. Respond to what the user said in a creative, helpful, and brief way.", ), ) diff --git a/examples/foundational/55l-update-settings-aws-transcribe-stt.py b/examples/foundational/55l-update-settings-aws-transcribe-stt.py index e18833d8d..cd9cfec11 100644 --- a/examples/foundational/55l-update-settings-aws-transcribe-stt.py +++ b/examples/foundational/55l-update-settings-aws-transcribe-stt.py @@ -63,7 +63,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): llm = OpenAILLMService( api_key=os.getenv("OPENAI_API_KEY"), settings=OpenAILLMService.Settings( - system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + system_instruction="You are a helpful assistant in a voice conversation. Your responses will be spoken aloud, so avoid emojis, bullet points, or other formatting that can't be spoken. Respond to what the user said in a creative, helpful, and brief way.", ), ) diff --git a/examples/foundational/55m-update-settings-cartesia-stt.py b/examples/foundational/55m-update-settings-cartesia-stt.py index 0599c9b56..acd7fb972 100644 --- a/examples/foundational/55m-update-settings-cartesia-stt.py +++ b/examples/foundational/55m-update-settings-cartesia-stt.py @@ -63,7 +63,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): llm = OpenAILLMService( api_key=os.getenv("OPENAI_API_KEY"), settings=OpenAILLMService.Settings( - system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + system_instruction="You are a helpful assistant in a voice conversation. Your responses will be spoken aloud, so avoid emojis, bullet points, or other formatting that can't be spoken. Respond to what the user said in a creative, helpful, and brief way.", ), ) diff --git a/examples/foundational/55n-update-settings-cartesia-http-tts.py b/examples/foundational/55n-update-settings-cartesia-http-tts.py index af4e8d5c1..328940bb5 100644 --- a/examples/foundational/55n-update-settings-cartesia-http-tts.py +++ b/examples/foundational/55n-update-settings-cartesia-http-tts.py @@ -62,7 +62,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): llm = OpenAILLMService( api_key=os.getenv("OPENAI_API_KEY"), settings=OpenAILLMService.Settings( - system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + system_instruction="You are a helpful assistant in a voice conversation. Your responses will be spoken aloud, so avoid emojis, bullet points, or other formatting that can't be spoken. Respond to what the user said in a creative, helpful, and brief way.", ), ) diff --git a/examples/foundational/55n-update-settings-cartesia-tts.py b/examples/foundational/55n-update-settings-cartesia-tts.py index 64afeffc2..67e0c599b 100644 --- a/examples/foundational/55n-update-settings-cartesia-tts.py +++ b/examples/foundational/55n-update-settings-cartesia-tts.py @@ -64,7 +64,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): llm = OpenAILLMService( api_key=os.getenv("OPENAI_API_KEY"), settings=OpenAILLMService.Settings( - system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + system_instruction="You are a helpful assistant in a voice conversation. Your responses will be spoken aloud, so avoid emojis, bullet points, or other formatting that can't be spoken. Respond to what the user said in a creative, helpful, and brief way.", ), ) diff --git a/examples/foundational/55o-update-settings-elevenlabs-http-tts.py b/examples/foundational/55o-update-settings-elevenlabs-http-tts.py index 8b6479edf..d819f2bdf 100644 --- a/examples/foundational/55o-update-settings-elevenlabs-http-tts.py +++ b/examples/foundational/55o-update-settings-elevenlabs-http-tts.py @@ -65,7 +65,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): llm = OpenAILLMService( api_key=os.getenv("OPENAI_API_KEY"), settings=OpenAILLMService.Settings( - system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + system_instruction="You are a helpful assistant in a voice conversation. Your responses will be spoken aloud, so avoid emojis, bullet points, or other formatting that can't be spoken. Respond to what the user said in a creative, helpful, and brief way.", ), ) diff --git a/examples/foundational/55o-update-settings-elevenlabs-tts.py b/examples/foundational/55o-update-settings-elevenlabs-tts.py index 03a692324..9afa33252 100644 --- a/examples/foundational/55o-update-settings-elevenlabs-tts.py +++ b/examples/foundational/55o-update-settings-elevenlabs-tts.py @@ -60,7 +60,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): llm = OpenAILLMService( api_key=os.getenv("OPENAI_API_KEY"), settings=OpenAILLMService.Settings( - system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + system_instruction="You are a helpful assistant in a voice conversation. Your responses will be spoken aloud, so avoid emojis, bullet points, or other formatting that can't be spoken. Respond to what the user said in a creative, helpful, and brief way.", ), ) diff --git a/examples/foundational/55p-update-settings-openai-tts.py b/examples/foundational/55p-update-settings-openai-tts.py index 110ee435b..a6f2b40c7 100644 --- a/examples/foundational/55p-update-settings-openai-tts.py +++ b/examples/foundational/55p-update-settings-openai-tts.py @@ -57,7 +57,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): llm = OpenAILLMService( api_key=os.getenv("OPENAI_API_KEY"), settings=OpenAILLMService.Settings( - system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + system_instruction="You are a helpful assistant in a voice conversation. Your responses will be spoken aloud, so avoid emojis, bullet points, or other formatting that can't be spoken. Respond to what the user said in a creative, helpful, and brief way.", ), ) diff --git a/examples/foundational/55q-update-settings-deepgram-http-tts.py b/examples/foundational/55q-update-settings-deepgram-http-tts.py index 877ec3f65..706dcc357 100644 --- a/examples/foundational/55q-update-settings-deepgram-http-tts.py +++ b/examples/foundational/55q-update-settings-deepgram-http-tts.py @@ -64,7 +64,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): llm = OpenAILLMService( api_key=os.getenv("OPENAI_API_KEY"), settings=OpenAILLMService.Settings( - system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + system_instruction="You are a helpful assistant in a voice conversation. Your responses will be spoken aloud, so avoid emojis, bullet points, or other formatting that can't be spoken. Respond to what the user said in a creative, helpful, and brief way.", ), ) diff --git a/examples/foundational/55q-update-settings-deepgram-sagemaker-tts.py b/examples/foundational/55q-update-settings-deepgram-sagemaker-tts.py index 270e00747..76c67095f 100644 --- a/examples/foundational/55q-update-settings-deepgram-sagemaker-tts.py +++ b/examples/foundational/55q-update-settings-deepgram-sagemaker-tts.py @@ -61,7 +61,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): llm = OpenAILLMService( api_key=os.getenv("OPENAI_API_KEY"), settings=OpenAILLMService.Settings( - system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + system_instruction="You are a helpful assistant in a voice conversation. Your responses will be spoken aloud, so avoid emojis, bullet points, or other formatting that can't be spoken. Respond to what the user said in a creative, helpful, and brief way.", ), ) diff --git a/examples/foundational/55q-update-settings-deepgram-tts.py b/examples/foundational/55q-update-settings-deepgram-tts.py index 335526768..39a6ea7b7 100644 --- a/examples/foundational/55q-update-settings-deepgram-tts.py +++ b/examples/foundational/55q-update-settings-deepgram-tts.py @@ -57,7 +57,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): llm = OpenAILLMService( api_key=os.getenv("OPENAI_API_KEY"), settings=OpenAILLMService.Settings( - system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + system_instruction="You are a helpful assistant in a voice conversation. Your responses will be spoken aloud, so avoid emojis, bullet points, or other formatting that can't be spoken. Respond to what the user said in a creative, helpful, and brief way.", ), ) diff --git a/examples/foundational/55r-update-settings-azure-http-tts.py b/examples/foundational/55r-update-settings-azure-http-tts.py index 56cb23854..c75ba5ff4 100644 --- a/examples/foundational/55r-update-settings-azure-http-tts.py +++ b/examples/foundational/55r-update-settings-azure-http-tts.py @@ -60,7 +60,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): llm = OpenAILLMService( api_key=os.getenv("OPENAI_API_KEY"), settings=OpenAILLMService.Settings( - system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + system_instruction="You are a helpful assistant in a voice conversation. Your responses will be spoken aloud, so avoid emojis, bullet points, or other formatting that can't be spoken. Respond to what the user said in a creative, helpful, and brief way.", ), ) diff --git a/examples/foundational/55r-update-settings-azure-tts.py b/examples/foundational/55r-update-settings-azure-tts.py index 5ccaa99bc..851e16de3 100644 --- a/examples/foundational/55r-update-settings-azure-tts.py +++ b/examples/foundational/55r-update-settings-azure-tts.py @@ -60,7 +60,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): llm = OpenAILLMService( api_key=os.getenv("OPENAI_API_KEY"), settings=OpenAILLMService.Settings( - system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + system_instruction="You are a helpful assistant in a voice conversation. Your responses will be spoken aloud, so avoid emojis, bullet points, or other formatting that can't be spoken. Respond to what the user said in a creative, helpful, and brief way.", ), ) diff --git a/examples/foundational/55s-update-settings-google-http-tts.py b/examples/foundational/55s-update-settings-google-http-tts.py index fbe44ff07..bb9b1862b 100644 --- a/examples/foundational/55s-update-settings-google-http-tts.py +++ b/examples/foundational/55s-update-settings-google-http-tts.py @@ -57,7 +57,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): llm = OpenAILLMService( api_key=os.getenv("OPENAI_API_KEY"), settings=OpenAILLMService.Settings( - system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + system_instruction="You are a helpful assistant in a voice conversation. Your responses will be spoken aloud, so avoid emojis, bullet points, or other formatting that can't be spoken. Respond to what the user said in a creative, helpful, and brief way.", ), ) diff --git a/examples/foundational/55s-update-settings-google-stream-tts.py b/examples/foundational/55s-update-settings-google-stream-tts.py index b3310975a..68cfd2aaa 100644 --- a/examples/foundational/55s-update-settings-google-stream-tts.py +++ b/examples/foundational/55s-update-settings-google-stream-tts.py @@ -57,7 +57,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): llm = OpenAILLMService( api_key=os.getenv("OPENAI_API_KEY"), settings=OpenAILLMService.Settings( - system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + system_instruction="You are a helpful assistant in a voice conversation. Your responses will be spoken aloud, so avoid emojis, bullet points, or other formatting that can't be spoken. Respond to what the user said in a creative, helpful, and brief way.", ), ) diff --git a/examples/foundational/55t-update-settings-piper-http-tts.py b/examples/foundational/55t-update-settings-piper-http-tts.py index 0b208ccbc..57770cc91 100644 --- a/examples/foundational/55t-update-settings-piper-http-tts.py +++ b/examples/foundational/55t-update-settings-piper-http-tts.py @@ -64,7 +64,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): llm = OpenAILLMService( api_key=os.getenv("OPENAI_API_KEY"), settings=OpenAILLMService.Settings( - system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + system_instruction="You are a helpful assistant in a voice conversation. Your responses will be spoken aloud, so avoid emojis, bullet points, or other formatting that can't be spoken. Respond to what the user said in a creative, helpful, and brief way.", ), ) diff --git a/examples/foundational/55t-update-settings-piper-tts.py b/examples/foundational/55t-update-settings-piper-tts.py index 6e9d79a72..5416b7e58 100644 --- a/examples/foundational/55t-update-settings-piper-tts.py +++ b/examples/foundational/55t-update-settings-piper-tts.py @@ -61,7 +61,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): llm = OpenAILLMService( api_key=os.getenv("OPENAI_API_KEY"), settings=OpenAILLMService.Settings( - system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + system_instruction="You are a helpful assistant in a voice conversation. Your responses will be spoken aloud, so avoid emojis, bullet points, or other formatting that can't be spoken. Respond to what the user said in a creative, helpful, and brief way.", ), ) diff --git a/examples/foundational/55u-update-settings-rime-http-tts.py b/examples/foundational/55u-update-settings-rime-http-tts.py index 07bb7e9a9..1d7154107 100644 --- a/examples/foundational/55u-update-settings-rime-http-tts.py +++ b/examples/foundational/55u-update-settings-rime-http-tts.py @@ -65,7 +65,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): llm = OpenAILLMService( api_key=os.getenv("OPENAI_API_KEY"), settings=OpenAILLMService.Settings( - system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + system_instruction="You are a helpful assistant in a voice conversation. Your responses will be spoken aloud, so avoid emojis, bullet points, or other formatting that can't be spoken. Respond to what the user said in a creative, helpful, and brief way.", ), ) diff --git a/examples/foundational/55u-update-settings-rime-tts.py b/examples/foundational/55u-update-settings-rime-tts.py index bbbdf534d..33a811228 100644 --- a/examples/foundational/55u-update-settings-rime-tts.py +++ b/examples/foundational/55u-update-settings-rime-tts.py @@ -60,7 +60,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): llm = OpenAILLMService( api_key=os.getenv("OPENAI_API_KEY"), settings=OpenAILLMService.Settings( - system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + system_instruction="You are a helpful assistant in a voice conversation. Your responses will be spoken aloud, so avoid emojis, bullet points, or other formatting that can't be spoken. Respond to what the user said in a creative, helpful, and brief way.", ), ) diff --git a/examples/foundational/55v-update-settings-lmnt-tts.py b/examples/foundational/55v-update-settings-lmnt-tts.py index 30f8135a0..1a6c9bd07 100644 --- a/examples/foundational/55v-update-settings-lmnt-tts.py +++ b/examples/foundational/55v-update-settings-lmnt-tts.py @@ -60,7 +60,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): llm = OpenAILLMService( api_key=os.getenv("OPENAI_API_KEY"), settings=OpenAILLMService.Settings( - system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + system_instruction="You are a helpful assistant in a voice conversation. Your responses will be spoken aloud, so avoid emojis, bullet points, or other formatting that can't be spoken. Respond to what the user said in a creative, helpful, and brief way.", ), ) diff --git a/examples/foundational/55w-update-settings-fish-tts.py b/examples/foundational/55w-update-settings-fish-tts.py index f54d97684..6ba018d0e 100644 --- a/examples/foundational/55w-update-settings-fish-tts.py +++ b/examples/foundational/55w-update-settings-fish-tts.py @@ -62,7 +62,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): llm = OpenAILLMService( api_key=os.getenv("OPENAI_API_KEY"), settings=OpenAILLMService.Settings( - system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + system_instruction="You are a helpful assistant in a voice conversation. Your responses will be spoken aloud, so avoid emojis, bullet points, or other formatting that can't be spoken. Respond to what the user said in a creative, helpful, and brief way.", ), ) diff --git a/examples/foundational/55x-update-settings-minimax-tts.py b/examples/foundational/55x-update-settings-minimax-tts.py index 53a120811..c91e728a4 100644 --- a/examples/foundational/55x-update-settings-minimax-tts.py +++ b/examples/foundational/55x-update-settings-minimax-tts.py @@ -63,7 +63,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): llm = OpenAILLMService( api_key=os.getenv("OPENAI_API_KEY"), settings=OpenAILLMService.Settings( - system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + system_instruction="You are a helpful assistant in a voice conversation. Your responses will be spoken aloud, so avoid emojis, bullet points, or other formatting that can't be spoken. Respond to what the user said in a creative, helpful, and brief way.", ), ) diff --git a/examples/foundational/55y-update-settings-groq-tts.py b/examples/foundational/55y-update-settings-groq-tts.py index c58b672c8..2e1a7a09d 100644 --- a/examples/foundational/55y-update-settings-groq-tts.py +++ b/examples/foundational/55y-update-settings-groq-tts.py @@ -57,7 +57,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): llm = OpenAILLMService( api_key=os.getenv("OPENAI_API_KEY"), settings=OpenAILLMService.Settings( - system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + system_instruction="You are a helpful assistant in a voice conversation. Your responses will be spoken aloud, so avoid emojis, bullet points, or other formatting that can't be spoken. Respond to what the user said in a creative, helpful, and brief way.", ), ) diff --git a/examples/foundational/55z-update-settings-hume-tts.py b/examples/foundational/55z-update-settings-hume-tts.py index 3af8b5fe7..4a1fc061b 100644 --- a/examples/foundational/55z-update-settings-hume-tts.py +++ b/examples/foundational/55z-update-settings-hume-tts.py @@ -60,7 +60,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): llm = OpenAILLMService( api_key=os.getenv("OPENAI_API_KEY"), settings=OpenAILLMService.Settings( - system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + system_instruction="You are a helpful assistant in a voice conversation. Your responses will be spoken aloud, so avoid emojis, bullet points, or other formatting that can't be spoken. Respond to what the user said in a creative, helpful, and brief way.", ), ) diff --git a/examples/foundational/55za-update-settings-neuphonic-http-tts.py b/examples/foundational/55za-update-settings-neuphonic-http-tts.py index daaef4750..12d44aa02 100644 --- a/examples/foundational/55za-update-settings-neuphonic-http-tts.py +++ b/examples/foundational/55za-update-settings-neuphonic-http-tts.py @@ -62,7 +62,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): llm = OpenAILLMService( api_key=os.getenv("OPENAI_API_KEY"), settings=OpenAILLMService.Settings( - system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + system_instruction="You are a helpful assistant in a voice conversation. Your responses will be spoken aloud, so avoid emojis, bullet points, or other formatting that can't be spoken. Respond to what the user said in a creative, helpful, and brief way.", ), ) diff --git a/examples/foundational/55za-update-settings-neuphonic-tts.py b/examples/foundational/55za-update-settings-neuphonic-tts.py index dc9d3cb6f..f3b2970a6 100644 --- a/examples/foundational/55za-update-settings-neuphonic-tts.py +++ b/examples/foundational/55za-update-settings-neuphonic-tts.py @@ -57,7 +57,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): llm = OpenAILLMService( api_key=os.getenv("OPENAI_API_KEY"), settings=OpenAILLMService.Settings( - system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + system_instruction="You are a helpful assistant in a voice conversation. Your responses will be spoken aloud, so avoid emojis, bullet points, or other formatting that can't be spoken. Respond to what the user said in a creative, helpful, and brief way.", ), ) diff --git a/examples/foundational/55zb-update-settings-inworld-http-tts.py b/examples/foundational/55zb-update-settings-inworld-http-tts.py index bb031c231..fb96a8eeb 100644 --- a/examples/foundational/55zb-update-settings-inworld-http-tts.py +++ b/examples/foundational/55zb-update-settings-inworld-http-tts.py @@ -61,7 +61,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): llm = OpenAILLMService( api_key=os.getenv("OPENAI_API_KEY"), settings=OpenAILLMService.Settings( - system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + system_instruction="You are a helpful assistant in a voice conversation. Your responses will be spoken aloud, so avoid emojis, bullet points, or other formatting that can't be spoken. Respond to what the user said in a creative, helpful, and brief way.", ), ) diff --git a/examples/foundational/55zb-update-settings-inworld-tts.py b/examples/foundational/55zb-update-settings-inworld-tts.py index f1581bd44..07ee4d674 100644 --- a/examples/foundational/55zb-update-settings-inworld-tts.py +++ b/examples/foundational/55zb-update-settings-inworld-tts.py @@ -57,7 +57,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): llm = OpenAILLMService( api_key=os.getenv("OPENAI_API_KEY"), settings=OpenAILLMService.Settings( - system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + system_instruction="You are a helpful assistant in a voice conversation. Your responses will be spoken aloud, so avoid emojis, bullet points, or other formatting that can't be spoken. Respond to what the user said in a creative, helpful, and brief way.", ), ) diff --git a/examples/foundational/55zc-update-settings-gemini-tts.py b/examples/foundational/55zc-update-settings-gemini-tts.py index 0bf027f20..fd7a8a5f7 100644 --- a/examples/foundational/55zc-update-settings-gemini-tts.py +++ b/examples/foundational/55zc-update-settings-gemini-tts.py @@ -66,7 +66,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): llm = OpenAILLMService( api_key=os.getenv("OPENAI_API_KEY"), settings=OpenAILLMService.Settings( - system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + system_instruction="You are a helpful assistant in a voice conversation. Your responses will be spoken aloud, so avoid emojis, bullet points, or other formatting that can't be spoken. Respond to what the user said in a creative, helpful, and brief way.", ), ) diff --git a/examples/foundational/55zd-update-settings-aws-polly-tts.py b/examples/foundational/55zd-update-settings-aws-polly-tts.py index 38a2544f2..d293e12ed 100644 --- a/examples/foundational/55zd-update-settings-aws-polly-tts.py +++ b/examples/foundational/55zd-update-settings-aws-polly-tts.py @@ -57,7 +57,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): llm = OpenAILLMService( api_key=os.getenv("OPENAI_API_KEY"), settings=OpenAILLMService.Settings( - system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + system_instruction="You are a helpful assistant in a voice conversation. Your responses will be spoken aloud, so avoid emojis, bullet points, or other formatting that can't be spoken. Respond to what the user said in a creative, helpful, and brief way.", ), ) diff --git a/examples/foundational/55ze-update-settings-sarvam-http-tts.py b/examples/foundational/55ze-update-settings-sarvam-http-tts.py index e00dfc621..5bc5da404 100644 --- a/examples/foundational/55ze-update-settings-sarvam-http-tts.py +++ b/examples/foundational/55ze-update-settings-sarvam-http-tts.py @@ -61,7 +61,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): llm = OpenAILLMService( api_key=os.getenv("OPENAI_API_KEY"), settings=OpenAILLMService.Settings( - system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + system_instruction="You are a helpful assistant in a voice conversation. Your responses will be spoken aloud, so avoid emojis, bullet points, or other formatting that can't be spoken. Respond to what the user said in a creative, helpful, and brief way.", ), ) diff --git a/examples/foundational/55ze-update-settings-sarvam-tts.py b/examples/foundational/55ze-update-settings-sarvam-tts.py index 6b6a0709a..8df7f781b 100644 --- a/examples/foundational/55ze-update-settings-sarvam-tts.py +++ b/examples/foundational/55ze-update-settings-sarvam-tts.py @@ -57,7 +57,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): llm = OpenAILLMService( api_key=os.getenv("OPENAI_API_KEY"), settings=OpenAILLMService.Settings( - system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + system_instruction="You are a helpful assistant in a voice conversation. Your responses will be spoken aloud, so avoid emojis, bullet points, or other formatting that can't be spoken. Respond to what the user said in a creative, helpful, and brief way.", ), ) diff --git a/examples/foundational/55zf-update-settings-camb-tts.py b/examples/foundational/55zf-update-settings-camb-tts.py index 37b845ab4..66a90b6a8 100644 --- a/examples/foundational/55zf-update-settings-camb-tts.py +++ b/examples/foundational/55zf-update-settings-camb-tts.py @@ -58,7 +58,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): llm = OpenAILLMService( api_key=os.getenv("OPENAI_API_KEY"), settings=OpenAILLMService.Settings( - system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + system_instruction="You are a helpful assistant in a voice conversation. Your responses will be spoken aloud, so avoid emojis, bullet points, or other formatting that can't be spoken. Respond to what the user said in a creative, helpful, and brief way.", ), ) diff --git a/examples/foundational/55zg-update-settings-kokoro-tts.py b/examples/foundational/55zg-update-settings-kokoro-tts.py index 69fb14512..2ef247f66 100644 --- a/examples/foundational/55zg-update-settings-kokoro-tts.py +++ b/examples/foundational/55zg-update-settings-kokoro-tts.py @@ -61,7 +61,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): llm = OpenAILLMService( api_key=os.getenv("OPENAI_API_KEY"), settings=OpenAILLMService.Settings( - system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + system_instruction="You are a helpful assistant in a voice conversation. Your responses will be spoken aloud, so avoid emojis, bullet points, or other formatting that can't be spoken. Respond to what the user said in a creative, helpful, and brief way.", ), ) diff --git a/examples/foundational/55zh-update-settings-resembleai-tts.py b/examples/foundational/55zh-update-settings-resembleai-tts.py index befa0ce65..45f8785a0 100644 --- a/examples/foundational/55zh-update-settings-resembleai-tts.py +++ b/examples/foundational/55zh-update-settings-resembleai-tts.py @@ -60,7 +60,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): llm = OpenAILLMService( api_key=os.getenv("OPENAI_API_KEY"), settings=OpenAILLMService.Settings( - system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + system_instruction="You are a helpful assistant in a voice conversation. Your responses will be spoken aloud, so avoid emojis, bullet points, or other formatting that can't be spoken. Respond to what the user said in a creative, helpful, and brief way.", ), ) diff --git a/examples/foundational/55zi-update-settings-azure-llm.py b/examples/foundational/55zi-update-settings-azure-llm.py index 5fbd796ca..20bae3aac 100644 --- a/examples/foundational/55zi-update-settings-azure-llm.py +++ b/examples/foundational/55zi-update-settings-azure-llm.py @@ -64,7 +64,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): endpoint=os.getenv("AZURE_CHATGPT_ENDPOINT"), settings=AzureLLMService.Settings( model=os.getenv("AZURE_CHATGPT_MODEL"), - system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + system_instruction="You are a helpful assistant in a voice conversation. Your responses will be spoken aloud, so avoid emojis, bullet points, or other formatting that can't be spoken. Respond to what the user said in a creative, helpful, and brief way.", ), ) diff --git a/examples/foundational/55zi-update-settings-openai-llm.py b/examples/foundational/55zi-update-settings-openai-llm.py index 76a14a3f0..5862e3cab 100644 --- a/examples/foundational/55zi-update-settings-openai-llm.py +++ b/examples/foundational/55zi-update-settings-openai-llm.py @@ -62,7 +62,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): llm = OpenAILLMService( api_key=os.getenv("OPENAI_API_KEY"), settings=OpenAILLMService.Settings( - system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + system_instruction="You are a helpful assistant in a voice conversation. Your responses will be spoken aloud, so avoid emojis, bullet points, or other formatting that can't be spoken. Respond to what the user said in a creative, helpful, and brief way.", ), ) diff --git a/examples/foundational/55zj-update-settings-anthropic-llm.py b/examples/foundational/55zj-update-settings-anthropic-llm.py index ba729bf4c..437769643 100644 --- a/examples/foundational/55zj-update-settings-anthropic-llm.py +++ b/examples/foundational/55zj-update-settings-anthropic-llm.py @@ -62,7 +62,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): llm = AnthropicLLMService( api_key=os.getenv("ANTHROPIC_API_KEY"), settings=AnthropicLLMService.Settings( - system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + system_instruction="You are a helpful assistant in a voice conversation. Your responses will be spoken aloud, so avoid emojis, bullet points, or other formatting that can't be spoken. Respond to what the user said in a creative, helpful, and brief way.", ), ) diff --git a/examples/foundational/55zk-update-settings-google-llm.py b/examples/foundational/55zk-update-settings-google-llm.py index dc3e5917a..a9fbfd093 100644 --- a/examples/foundational/55zk-update-settings-google-llm.py +++ b/examples/foundational/55zk-update-settings-google-llm.py @@ -62,7 +62,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): llm = GoogleLLMService( api_key=os.getenv("GOOGLE_API_KEY"), settings=GoogleLLMService.Settings( - system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + system_instruction="You are a helpful assistant in a voice conversation. Your responses will be spoken aloud, so avoid emojis, bullet points, or other formatting that can't be spoken. Respond to what the user said in a creative, helpful, and brief way.", ), ) diff --git a/examples/foundational/55zk-update-settings-google-vertex-llm.py b/examples/foundational/55zk-update-settings-google-vertex-llm.py index 7f7a34cba..c2c8ea2bf 100644 --- a/examples/foundational/55zk-update-settings-google-vertex-llm.py +++ b/examples/foundational/55zk-update-settings-google-vertex-llm.py @@ -64,7 +64,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): project_id=os.getenv("GOOGLE_CLOUD_PROJECT_ID"), location=os.getenv("GOOGLE_CLOUD_LOCATION"), settings=GoogleVertexLLMService.Settings( - system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + system_instruction="You are a helpful assistant in a voice conversation. Your responses will be spoken aloud, so avoid emojis, bullet points, or other formatting that can't be spoken. Respond to what the user said in a creative, helpful, and brief way.", ), ) diff --git a/examples/foundational/55zl-update-settings-azure-realtime.py b/examples/foundational/55zl-update-settings-azure-realtime.py index a977ea60c..fde633912 100644 --- a/examples/foundational/55zl-update-settings-azure-realtime.py +++ b/examples/foundational/55zl-update-settings-azure-realtime.py @@ -58,7 +58,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): messages = [ { "role": "system", - "content": "You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + "content": "You are a helpful assistant in a voice conversation. Your responses will be spoken aloud, so avoid emojis, bullet points, or other formatting that can't be spoken. Respond to what the user said in a creative, helpful, and brief way.", }, ] diff --git a/examples/foundational/55zl-update-settings-openai-realtime.py b/examples/foundational/55zl-update-settings-openai-realtime.py index 9f7281a72..83cdb9fa7 100644 --- a/examples/foundational/55zl-update-settings-openai-realtime.py +++ b/examples/foundational/55zl-update-settings-openai-realtime.py @@ -55,7 +55,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): messages = [ { "role": "system", - "content": "You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + "content": "You are a helpful assistant in a voice conversation. Your responses will be spoken aloud, so avoid emojis, bullet points, or other formatting that can't be spoken. Respond to what the user said in a creative, helpful, and brief way.", }, ] diff --git a/examples/foundational/55zm-update-settings-gemini-live-vertex.py b/examples/foundational/55zm-update-settings-gemini-live-vertex.py index c6a04347a..59b9a5a41 100644 --- a/examples/foundational/55zm-update-settings-gemini-live-vertex.py +++ b/examples/foundational/55zm-update-settings-gemini-live-vertex.py @@ -53,7 +53,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): project_id=os.getenv("GOOGLE_CLOUD_PROJECT_ID"), location=os.getenv("GOOGLE_CLOUD_LOCATION"), settings=GeminiLiveVertexLLMService.Settings( - system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + system_instruction="You are a helpful assistant in a voice conversation. Your responses will be spoken aloud, so avoid emojis, bullet points, or other formatting that can't be spoken. Respond to what the user said in a creative, helpful, and brief way.", ), ) diff --git a/examples/foundational/55zm-update-settings-gemini-live.py b/examples/foundational/55zm-update-settings-gemini-live.py index beb7f0c1c..fd5ef213a 100644 --- a/examples/foundational/55zm-update-settings-gemini-live.py +++ b/examples/foundational/55zm-update-settings-gemini-live.py @@ -51,7 +51,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): llm = GeminiLiveLLMService( api_key=os.getenv("GOOGLE_API_KEY"), settings=GeminiLiveLLMService.Settings( - system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + system_instruction="You are a helpful assistant in a voice conversation. Your responses will be spoken aloud, so avoid emojis, bullet points, or other formatting that can't be spoken. Respond to what the user said in a creative, helpful, and brief way.", ), ) diff --git a/examples/foundational/55zn-update-settings-ultravox-realtime.py b/examples/foundational/55zn-update-settings-ultravox-realtime.py index ccf2d2003..f77aa4252 100644 --- a/examples/foundational/55zn-update-settings-ultravox-realtime.py +++ b/examples/foundational/55zn-update-settings-ultravox-realtime.py @@ -51,7 +51,7 @@ transport_params = { async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): logger.info(f"Starting bot") - system_prompt = "You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way." + system_prompt = "You are a helpful assistant in a voice conversation. Your responses will be spoken aloud, so avoid emojis, bullet points, or other formatting that can't be spoken. Respond to what the user said in a creative, helpful, and brief way." llm = UltravoxRealtimeLLMService( params=OneShotInputParams( diff --git a/examples/foundational/55zo-update-settings-grok-realtime.py b/examples/foundational/55zo-update-settings-grok-realtime.py index 60ba18755..0d44470e5 100644 --- a/examples/foundational/55zo-update-settings-grok-realtime.py +++ b/examples/foundational/55zo-update-settings-grok-realtime.py @@ -55,7 +55,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): messages = [ { "role": "system", - "content": "You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + "content": "You are a helpful assistant in a voice conversation. Your responses will be spoken aloud, so avoid emojis, bullet points, or other formatting that can't be spoken. Respond to what the user said in a creative, helpful, and brief way.", }, ] diff --git a/examples/foundational/55zp-update-settings-aws-bedrock-llm.py b/examples/foundational/55zp-update-settings-aws-bedrock-llm.py index 2452ceada..96f151463 100644 --- a/examples/foundational/55zp-update-settings-aws-bedrock-llm.py +++ b/examples/foundational/55zp-update-settings-aws-bedrock-llm.py @@ -64,7 +64,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): settings=AWSBedrockLLMService.Settings( model="us.anthropic.claude-sonnet-4-6", temperature=0.8, - system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + system_instruction="You are a helpful assistant in a voice conversation. Your responses will be spoken aloud, so avoid emojis, bullet points, or other formatting that can't be spoken. Respond to what the user said in a creative, helpful, and brief way.", ), ) diff --git a/examples/foundational/55zq-update-settings-fal-stt.py b/examples/foundational/55zq-update-settings-fal-stt.py index 77d9bfd85..8047c04e3 100644 --- a/examples/foundational/55zq-update-settings-fal-stt.py +++ b/examples/foundational/55zq-update-settings-fal-stt.py @@ -62,7 +62,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): llm = OpenAILLMService( api_key=os.getenv("OPENAI_API_KEY"), settings=OpenAILLMService.Settings( - system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + system_instruction="You are a helpful assistant in a voice conversation. Your responses will be spoken aloud, so avoid emojis, bullet points, or other formatting that can't be spoken. Respond to what the user said in a creative, helpful, and brief way.", ), ) diff --git a/examples/foundational/55zr-update-settings-gradium-stt.py b/examples/foundational/55zr-update-settings-gradium-stt.py index e621cc89b..b906306b4 100644 --- a/examples/foundational/55zr-update-settings-gradium-stt.py +++ b/examples/foundational/55zr-update-settings-gradium-stt.py @@ -65,7 +65,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): llm = OpenAILLMService( api_key=os.getenv("OPENAI_API_KEY"), settings=OpenAILLMService.Settings( - system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + system_instruction="You are a helpful assistant in a voice conversation. Your responses will be spoken aloud, so avoid emojis, bullet points, or other formatting that can't be spoken. Respond to what the user said in a creative, helpful, and brief way.", ), ) diff --git a/examples/foundational/55zs-update-settings-whisper-mlx-stt.py b/examples/foundational/55zs-update-settings-whisper-mlx-stt.py index a3ca78f8c..c60cd072b 100644 --- a/examples/foundational/55zs-update-settings-whisper-mlx-stt.py +++ b/examples/foundational/55zs-update-settings-whisper-mlx-stt.py @@ -67,7 +67,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): llm = OpenAILLMService( api_key=os.getenv("OPENAI_API_KEY"), settings=OpenAILLMService.Settings( - system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + system_instruction="You are a helpful assistant in a voice conversation. Your responses will be spoken aloud, so avoid emojis, bullet points, or other formatting that can't be spoken. Respond to what the user said in a creative, helpful, and brief way.", ), ) diff --git a/examples/foundational/55zs-update-settings-whisper-stt.py b/examples/foundational/55zs-update-settings-whisper-stt.py index b58e86dbf..5af0049ea 100644 --- a/examples/foundational/55zs-update-settings-whisper-stt.py +++ b/examples/foundational/55zs-update-settings-whisper-stt.py @@ -67,7 +67,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): llm = OpenAILLMService( api_key=os.getenv("OPENAI_API_KEY"), settings=OpenAILLMService.Settings( - system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + system_instruction="You are a helpful assistant in a voice conversation. Your responses will be spoken aloud, so avoid emojis, bullet points, or other formatting that can't be spoken. Respond to what the user said in a creative, helpful, and brief way.", ), ) diff --git a/examples/foundational/55zt-update-settings-nvidia-segmented-stt.py b/examples/foundational/55zt-update-settings-nvidia-segmented-stt.py index 62d10d455..28717e035 100644 --- a/examples/foundational/55zt-update-settings-nvidia-segmented-stt.py +++ b/examples/foundational/55zt-update-settings-nvidia-segmented-stt.py @@ -62,7 +62,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): llm = OpenAILLMService( api_key=os.getenv("OPENAI_API_KEY"), settings=OpenAILLMService.Settings( - system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + system_instruction="You are a helpful assistant in a voice conversation. Your responses will be spoken aloud, so avoid emojis, bullet points, or other formatting that can't be spoken. Respond to what the user said in a creative, helpful, and brief way.", ), ) diff --git a/examples/foundational/55zt-update-settings-nvidia-stt.py b/examples/foundational/55zt-update-settings-nvidia-stt.py index 612f12acf..c2ad7c813 100644 --- a/examples/foundational/55zt-update-settings-nvidia-stt.py +++ b/examples/foundational/55zt-update-settings-nvidia-stt.py @@ -63,7 +63,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): llm = OpenAILLMService( api_key=os.getenv("OPENAI_API_KEY"), settings=OpenAILLMService.Settings( - system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + system_instruction="You are a helpful assistant in a voice conversation. Your responses will be spoken aloud, so avoid emojis, bullet points, or other formatting that can't be spoken. Respond to what the user said in a creative, helpful, and brief way.", ), ) diff --git a/examples/foundational/55zu-update-settings-openai-realtime-stt.py b/examples/foundational/55zu-update-settings-openai-realtime-stt.py index 62cf902ed..5ddea6181 100644 --- a/examples/foundational/55zu-update-settings-openai-realtime-stt.py +++ b/examples/foundational/55zu-update-settings-openai-realtime-stt.py @@ -63,7 +63,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): llm = OpenAILLMService( api_key=os.getenv("OPENAI_API_KEY"), settings=OpenAILLMService.Settings( - system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + system_instruction="You are a helpful assistant in a voice conversation. Your responses will be spoken aloud, so avoid emojis, bullet points, or other formatting that can't be spoken. Respond to what the user said in a creative, helpful, and brief way.", ), ) diff --git a/examples/foundational/55zv-update-settings-asyncai-http-tts.py b/examples/foundational/55zv-update-settings-asyncai-http-tts.py index 639a28d7f..caaba5ff2 100644 --- a/examples/foundational/55zv-update-settings-asyncai-http-tts.py +++ b/examples/foundational/55zv-update-settings-asyncai-http-tts.py @@ -68,7 +68,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): llm = OpenAILLMService( api_key=os.getenv("OPENAI_API_KEY"), settings=OpenAILLMService.Settings( - system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + system_instruction="You are a helpful assistant in a voice conversation. Your responses will be spoken aloud, so avoid emojis, bullet points, or other formatting that can't be spoken. Respond to what the user said in a creative, helpful, and brief way.", ), ) diff --git a/examples/foundational/55zv-update-settings-asyncai-tts.py b/examples/foundational/55zv-update-settings-asyncai-tts.py index cac3fde19..6aa678df7 100644 --- a/examples/foundational/55zv-update-settings-asyncai-tts.py +++ b/examples/foundational/55zv-update-settings-asyncai-tts.py @@ -63,7 +63,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): llm = OpenAILLMService( api_key=os.getenv("OPENAI_API_KEY"), settings=OpenAILLMService.Settings( - system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + system_instruction="You are a helpful assistant in a voice conversation. Your responses will be spoken aloud, so avoid emojis, bullet points, or other formatting that can't be spoken. Respond to what the user said in a creative, helpful, and brief way.", ), ) diff --git a/examples/foundational/55zw-update-settings-gradium-tts.py b/examples/foundational/55zw-update-settings-gradium-tts.py index d2b3535c4..71f19dc98 100644 --- a/examples/foundational/55zw-update-settings-gradium-tts.py +++ b/examples/foundational/55zw-update-settings-gradium-tts.py @@ -61,7 +61,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): llm = OpenAILLMService( api_key=os.getenv("OPENAI_API_KEY"), settings=OpenAILLMService.Settings( - system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + system_instruction="You are a helpful assistant in a voice conversation. Your responses will be spoken aloud, so avoid emojis, bullet points, or other formatting that can't be spoken. Respond to what the user said in a creative, helpful, and brief way.", ), ) diff --git a/examples/foundational/55zx-update-settings-cerebras-llm.py b/examples/foundational/55zx-update-settings-cerebras-llm.py index 2d8e5a3d9..6e03a1d8b 100644 --- a/examples/foundational/55zx-update-settings-cerebras-llm.py +++ b/examples/foundational/55zx-update-settings-cerebras-llm.py @@ -62,7 +62,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): llm = CerebrasLLMService( api_key=os.getenv("CEREBRAS_API_KEY"), settings=CerebrasLLMService.Settings( - system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + system_instruction="You are a helpful assistant in a voice conversation. Your responses will be spoken aloud, so avoid emojis, bullet points, or other formatting that can't be spoken. Respond to what the user said in a creative, helpful, and brief way.", ), ) diff --git a/examples/foundational/55zy-update-settings-deepseek-llm.py b/examples/foundational/55zy-update-settings-deepseek-llm.py index 2a439f76d..4d34cf67b 100644 --- a/examples/foundational/55zy-update-settings-deepseek-llm.py +++ b/examples/foundational/55zy-update-settings-deepseek-llm.py @@ -62,7 +62,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): llm = DeepSeekLLMService( api_key=os.getenv("DEEPSEEK_API_KEY"), settings=DeepSeekLLMService.Settings( - system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + system_instruction="You are a helpful assistant in a voice conversation. Your responses will be spoken aloud, so avoid emojis, bullet points, or other formatting that can't be spoken. Respond to what the user said in a creative, helpful, and brief way.", ), ) diff --git a/examples/foundational/55zz-update-settings-fireworks-llm.py b/examples/foundational/55zz-update-settings-fireworks-llm.py index 0b184974d..85d83097e 100644 --- a/examples/foundational/55zz-update-settings-fireworks-llm.py +++ b/examples/foundational/55zz-update-settings-fireworks-llm.py @@ -63,7 +63,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): api_key=os.getenv("FIREWORKS_API_KEY"), settings=FireworksLLMService.Settings( model="accounts/fireworks/models/gpt-oss-20b", - system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + system_instruction="You are a helpful assistant in a voice conversation. Your responses will be spoken aloud, so avoid emojis, bullet points, or other formatting that can't be spoken. Respond to what the user said in a creative, helpful, and brief way.", ), ) diff --git a/examples/foundational/55zza-update-settings-grok-llm.py b/examples/foundational/55zza-update-settings-grok-llm.py index c5caef791..0a793d58e 100644 --- a/examples/foundational/55zza-update-settings-grok-llm.py +++ b/examples/foundational/55zza-update-settings-grok-llm.py @@ -62,7 +62,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): llm = GrokLLMService( api_key=os.getenv("GROK_API_KEY"), settings=GrokLLMService.Settings( - system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + system_instruction="You are a helpful assistant in a voice conversation. Your responses will be spoken aloud, so avoid emojis, bullet points, or other formatting that can't be spoken. Respond to what the user said in a creative, helpful, and brief way.", ), ) diff --git a/examples/foundational/55zzb-update-settings-groq-llm.py b/examples/foundational/55zzb-update-settings-groq-llm.py index 25d1b4019..896f5d6ab 100644 --- a/examples/foundational/55zzb-update-settings-groq-llm.py +++ b/examples/foundational/55zzb-update-settings-groq-llm.py @@ -63,7 +63,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): api_key=os.getenv("GROQ_API_KEY"), settings=GroqLLMService.Settings( model="meta-llama/llama-4-maverick-17b-128e-instruct", - system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + system_instruction="You are a helpful assistant in a voice conversation. Your responses will be spoken aloud, so avoid emojis, bullet points, or other formatting that can't be spoken. Respond to what the user said in a creative, helpful, and brief way.", ), ) diff --git a/examples/foundational/55zzc-update-settings-mistral-llm.py b/examples/foundational/55zzc-update-settings-mistral-llm.py index 94ee3f29a..6a03b9e8c 100644 --- a/examples/foundational/55zzc-update-settings-mistral-llm.py +++ b/examples/foundational/55zzc-update-settings-mistral-llm.py @@ -62,7 +62,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): llm = MistralLLMService( api_key=os.getenv("MISTRAL_API_KEY"), settings=MistralLLMService.Settings( - system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + system_instruction="You are a helpful assistant in a voice conversation. Your responses will be spoken aloud, so avoid emojis, bullet points, or other formatting that can't be spoken. Respond to what the user said in a creative, helpful, and brief way.", ), ) diff --git a/examples/foundational/55zzd-update-settings-nvidia-llm.py b/examples/foundational/55zzd-update-settings-nvidia-llm.py index eb099e50c..c34d45a2a 100644 --- a/examples/foundational/55zzd-update-settings-nvidia-llm.py +++ b/examples/foundational/55zzd-update-settings-nvidia-llm.py @@ -63,7 +63,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): api_key=os.getenv("NVIDIA_API_KEY"), settings=NvidiaLLMService.Settings( model="meta/llama-3.1-405b-instruct", - system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + system_instruction="You are a helpful assistant in a voice conversation. Your responses will be spoken aloud, so avoid emojis, bullet points, or other formatting that can't be spoken. Respond to what the user said in a creative, helpful, and brief way.", ), ) diff --git a/examples/foundational/55zze-update-settings-ollama-llm.py b/examples/foundational/55zze-update-settings-ollama-llm.py index 5625e188c..666f96e6b 100644 --- a/examples/foundational/55zze-update-settings-ollama-llm.py +++ b/examples/foundational/55zze-update-settings-ollama-llm.py @@ -62,7 +62,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): llm = OLLamaLLMService( settings=OLLamaLLMService.Settings( model="llama3.2", - system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + system_instruction="You are a helpful assistant in a voice conversation. Your responses will be spoken aloud, so avoid emojis, bullet points, or other formatting that can't be spoken. Respond to what the user said in a creative, helpful, and brief way.", ), ) # Update to the model you're running locally diff --git a/examples/foundational/55zzf-update-settings-openrouter-llm.py b/examples/foundational/55zzf-update-settings-openrouter-llm.py index 4745ae537..2647848bc 100644 --- a/examples/foundational/55zzf-update-settings-openrouter-llm.py +++ b/examples/foundational/55zzf-update-settings-openrouter-llm.py @@ -62,7 +62,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): llm = OpenRouterLLMService( api_key=os.getenv("OPENROUTER_API_KEY"), settings=OpenRouterLLMService.Settings( - system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + system_instruction="You are a helpful assistant in a voice conversation. Your responses will be spoken aloud, so avoid emojis, bullet points, or other formatting that can't be spoken. Respond to what the user said in a creative, helpful, and brief way.", ), ) diff --git a/examples/foundational/55zzg-update-settings-perplexity-llm.py b/examples/foundational/55zzg-update-settings-perplexity-llm.py index b764e0ff7..c495830dd 100644 --- a/examples/foundational/55zzg-update-settings-perplexity-llm.py +++ b/examples/foundational/55zzg-update-settings-perplexity-llm.py @@ -64,7 +64,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): messages = [ { "role": "user", - "content": "You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way. Start by introducing yourself.", + "content": "You are a helpful assistant in a voice conversation. Your responses will be spoken aloud, so avoid emojis, bullet points, or other formatting that can't be spoken. Respond to what the user said in a creative, helpful, and brief way. Start by introducing yourself.", }, ] diff --git a/examples/foundational/55zzh-update-settings-qwen-llm.py b/examples/foundational/55zzh-update-settings-qwen-llm.py index 2f56886b9..6cfcfc97d 100644 --- a/examples/foundational/55zzh-update-settings-qwen-llm.py +++ b/examples/foundational/55zzh-update-settings-qwen-llm.py @@ -63,7 +63,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): api_key=os.getenv("QWEN_API_KEY"), settings=QwenLLMService.Settings( model="qwen2.5-72b-instruct", - system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + system_instruction="You are a helpful assistant in a voice conversation. Your responses will be spoken aloud, so avoid emojis, bullet points, or other formatting that can't be spoken. Respond to what the user said in a creative, helpful, and brief way.", ), ) diff --git a/examples/foundational/55zzi-update-settings-sambanova-llm.py b/examples/foundational/55zzi-update-settings-sambanova-llm.py index 46db2099f..46a6561ae 100644 --- a/examples/foundational/55zzi-update-settings-sambanova-llm.py +++ b/examples/foundational/55zzi-update-settings-sambanova-llm.py @@ -62,7 +62,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): llm = SambaNovaLLMService( api_key=os.getenv("SAMBANOVA_API_KEY"), settings=SambaNovaLLMService.Settings( - system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + system_instruction="You are a helpful assistant in a voice conversation. Your responses will be spoken aloud, so avoid emojis, bullet points, or other formatting that can't be spoken. Respond to what the user said in a creative, helpful, and brief way.", ), ) diff --git a/examples/foundational/55zzj-update-settings-together-llm.py b/examples/foundational/55zzj-update-settings-together-llm.py index e293613b1..3ffbe9c3e 100644 --- a/examples/foundational/55zzj-update-settings-together-llm.py +++ b/examples/foundational/55zzj-update-settings-together-llm.py @@ -63,7 +63,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): api_key=os.getenv("TOGETHER_API_KEY"), settings=TogetherLLMService.Settings( model="meta-llama/Meta-Llama-3.1-70B-Instruct-Turbo", - system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + system_instruction="You are a helpful assistant in a voice conversation. Your responses will be spoken aloud, so avoid emojis, bullet points, or other formatting that can't be spoken. Respond to what the user said in a creative, helpful, and brief way.", ), ) diff --git a/examples/foundational/55zzk-update-settings-aws-nova-sonic-llm.py b/examples/foundational/55zzk-update-settings-aws-nova-sonic-llm.py index bec1c4d86..0d03efe58 100644 --- a/examples/foundational/55zzk-update-settings-aws-nova-sonic-llm.py +++ b/examples/foundational/55zzk-update-settings-aws-nova-sonic-llm.py @@ -53,7 +53,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): access_key_id=os.getenv("AWS_ACCESS_KEY_ID"), region=os.getenv("AWS_REGION"), settings=AWSNovaSonicLLMService.Settings( - system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + system_instruction="You are a helpful assistant in a voice conversation. Your responses will be spoken aloud, so avoid emojis, bullet points, or other formatting that can't be spoken. Respond to what the user said in a creative, helpful, and brief way.", ), ) diff --git a/examples/foundational/55zzl-update-settings-nvidia-tts.py b/examples/foundational/55zzl-update-settings-nvidia-tts.py index 5caaad3b4..3282c981d 100644 --- a/examples/foundational/55zzl-update-settings-nvidia-tts.py +++ b/examples/foundational/55zzl-update-settings-nvidia-tts.py @@ -58,7 +58,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): llm = OpenAILLMService( api_key=os.getenv("OPENAI_API_KEY"), settings=OpenAILLMService.Settings( - system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + system_instruction="You are a helpful assistant in a voice conversation. Your responses will be spoken aloud, so avoid emojis, bullet points, or other formatting that can't be spoken. Respond to what the user said in a creative, helpful, and brief way.", ), ) diff --git a/examples/foundational/55zzm-update-settings-speechmatics-tts.py b/examples/foundational/55zzm-update-settings-speechmatics-tts.py index 80a6c694c..908ff9918 100644 --- a/examples/foundational/55zzm-update-settings-speechmatics-tts.py +++ b/examples/foundational/55zzm-update-settings-speechmatics-tts.py @@ -62,7 +62,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): llm = OpenAILLMService( api_key=os.getenv("OPENAI_API_KEY"), settings=OpenAILLMService.Settings( - system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + system_instruction="You are a helpful assistant in a voice conversation. Your responses will be spoken aloud, so avoid emojis, bullet points, or other formatting that can't be spoken. Respond to what the user said in a creative, helpful, and brief way.", ), ) diff --git a/examples/foundational/55zzn-update-settings-groq-stt.py b/examples/foundational/55zzn-update-settings-groq-stt.py index 1b4e9b8ed..e5c903753 100644 --- a/examples/foundational/55zzn-update-settings-groq-stt.py +++ b/examples/foundational/55zzn-update-settings-groq-stt.py @@ -64,7 +64,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): llm = OpenAILLMService( api_key=os.getenv("OPENAI_API_KEY"), settings=OpenAILLMService.Settings( - system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + system_instruction="You are a helpful assistant in a voice conversation. Your responses will be spoken aloud, so avoid emojis, bullet points, or other formatting that can't be spoken. Respond to what the user said in a creative, helpful, and brief way.", ), ) diff --git a/examples/foundational/55zzo-update-settings-openpipe-llm.py b/examples/foundational/55zzo-update-settings-openpipe-llm.py index 669a35cd5..89a94d61f 100644 --- a/examples/foundational/55zzo-update-settings-openpipe-llm.py +++ b/examples/foundational/55zzo-update-settings-openpipe-llm.py @@ -66,7 +66,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): openpipe_api_key=os.getenv("OPENPIPE_API_KEY"), tags={"conversation_id": f"pipecat-{timestamp}"}, settings=OpenPipeLLMService.Settings( - system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + system_instruction="You are a helpful assistant in a voice conversation. Your responses will be spoken aloud, so avoid emojis, bullet points, or other formatting that can't be spoken. Respond to what the user said in a creative, helpful, and brief way.", ), ) diff --git a/examples/foundational/55zzp-update-settings-xtts-tts.py b/examples/foundational/55zzp-update-settings-xtts-tts.py index 8a7667036..adb90247b 100644 --- a/examples/foundational/55zzp-update-settings-xtts-tts.py +++ b/examples/foundational/55zzp-update-settings-xtts-tts.py @@ -66,7 +66,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): llm = OpenAILLMService( api_key=os.getenv("OPENAI_API_KEY"), settings=OpenAILLMService.Settings( - system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + system_instruction="You are a helpful assistant in a voice conversation. Your responses will be spoken aloud, so avoid emojis, bullet points, or other formatting that can't be spoken. Respond to what the user said in a creative, helpful, and brief way.", ), ) diff --git a/examples/foundational/56-lemonslice-transport.py b/examples/foundational/56-lemonslice-transport.py index 67f4e8ad1..667b317f8 100644 --- a/examples/foundational/56-lemonslice-transport.py +++ b/examples/foundational/56-lemonslice-transport.py @@ -58,7 +58,7 @@ async def main(): llm = GroqLLMService( api_key=os.getenv("GROQ_API_KEY"), settings=GroqLLMService.Settings( - system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + system_instruction="You are a helpful assistant in a voice conversation. Your responses will be spoken aloud, so avoid emojis, bullet points, or other formatting that can't be spoken. Respond to what the user said in a creative, helpful, and brief way.", ), ) From 79b7a0f969e5c8946fcd51fa794c8690929e3301 Mon Sep 17 00:00:00 2001 From: Mark Backman Date: Fri, 13 Mar 2026 13:53:06 -0400 Subject: [PATCH 0978/1060] Fix DeepgramSTTService base_url forcing HTTPS/WSS schemes The base_url parameter previously forced wss:// and https:// schemes, breaking air-gapped or private deployments that need ws:// or http://. Extract URL derivation into _derive_deepgram_urls() helper that respects the developers scheme choice while deriving the paired WebSocket and HTTP URLs the Deepgram SDK requires. Closes #4019 --- src/pipecat/services/deepgram/stt.py | 42 +++++++++++++++++++++-- tests/test_deepgram_stt.py | 51 ++++++++++++++++++++++++++++ 2 files changed, 91 insertions(+), 2 deletions(-) create mode 100644 tests/test_deepgram_stt.py diff --git a/src/pipecat/services/deepgram/stt.py b/src/pipecat/services/deepgram/stt.py index 7d849a160..32710d00c 100644 --- a/src/pipecat/services/deepgram/stt.py +++ b/src/pipecat/services/deepgram/stt.py @@ -247,6 +247,45 @@ class DeepgramSTTSettings(STTSettings): del self.extra[key] +def _derive_deepgram_urls(base_url: str) -> tuple[str, str]: + """Derive paired WebSocket and HTTP URLs from a single base URL. + + The Deepgram SDK client requires both a WebSocket URL (for streaming) + and an HTTP URL (for REST calls). This helper lets developers provide + a single ``base_url`` and consistently derives both, preserving the + security level they chose. Useful for air-gapped or private deployments + where insecure schemes (ws:// / http://) are acceptable. + + Accepted inputs: + - ``wss://`` or ``https://`` — secure (paired as wss + https) + - ``ws://`` or ``http://`` — insecure (paired as ws + http) + - Bare hostname (no scheme) — defaults to secure + - Unrecognized scheme — logs a warning, defaults to secure + + Args: + base_url: Host with optional scheme, port, and path. + + Returns: + A (ws_url, http_url) tuple with consistent schemes. + """ + known_schemes = ("wss://", "https://", "ws://", "http://") + if "://" in base_url: + scheme, host = base_url.split("://", 1) + scheme += "://" + if scheme not in known_schemes: + logger.warning( + f"Unrecognized scheme in base_url '{base_url}', defaulting to wss:// / https://" + ) + else: + scheme = "" + host = base_url + + insecure = scheme in ("ws://", "http://") + ws_url = f"{'ws' if insecure else 'wss'}://{host}" + http_url = f"{'http' if insecure else 'https'}://{host}" + return ws_url, http_url + + class DeepgramSTTService(STTService): """Deepgram speech-to-text service. @@ -445,8 +484,7 @@ class DeepgramSTTService(STTService): try: from deepgram import DeepgramClientEnvironment - ws_url = base_url if base_url.startswith("wss://") else f"wss://{base_url}" - http_url = base_url if base_url.startswith("https://") else f"https://{base_url}" + ws_url, http_url = _derive_deepgram_urls(base_url) environment = DeepgramClientEnvironment( base=http_url, production=ws_url, diff --git a/tests/test_deepgram_stt.py b/tests/test_deepgram_stt.py new file mode 100644 index 000000000..eb8036237 --- /dev/null +++ b/tests/test_deepgram_stt.py @@ -0,0 +1,51 @@ +# +# Copyright (c) 2024-2026, Daily +# +# SPDX-License-Identifier: BSD 2-Clause License +# + +import io + +import pytest +from loguru import logger + +from pipecat.services.deepgram.stt import _derive_deepgram_urls + + +@pytest.mark.parametrize( + "base_url, expected_ws, expected_http", + [ + # Secure schemes + ("wss://mydeepgram.com", "wss://mydeepgram.com", "https://mydeepgram.com"), + ("https://mydeepgram.com", "wss://mydeepgram.com", "https://mydeepgram.com"), + # Insecure schemes (air-gapped deployments) + ("ws://mydeepgram.com", "ws://mydeepgram.com", "http://mydeepgram.com"), + ("http://mydeepgram.com", "ws://mydeepgram.com", "http://mydeepgram.com"), + # Bare hostname defaults to secure + ("mydeepgram.com", "wss://mydeepgram.com", "https://mydeepgram.com"), + # With port + ("ws://localhost:8080", "ws://localhost:8080", "http://localhost:8080"), + ("wss://localhost:443", "wss://localhost:443", "https://localhost:443"), + ("localhost:8080", "wss://localhost:8080", "https://localhost:8080"), + # With path + ("wss://host/v1/listen", "wss://host/v1/listen", "https://host/v1/listen"), + ("http://host/v1/listen", "ws://host/v1/listen", "http://host/v1/listen"), + ], +) +def test_derive_deepgram_urls(base_url, expected_ws, expected_http): + ws_url, http_url = _derive_deepgram_urls(base_url) + assert ws_url == expected_ws + assert http_url == expected_http + + +def test_derive_deepgram_urls_unknown_scheme_warns(): + sink = io.StringIO() + handler_id = logger.add(sink, format="{message}") + try: + ws_url, http_url = _derive_deepgram_urls("ftp://mydeepgram.com") + # Falls back to secure + assert ws_url == "wss://mydeepgram.com" + assert http_url == "https://mydeepgram.com" + assert "Unrecognized scheme" in sink.getvalue() + finally: + logger.remove(handler_id) From 2f7c441c1ce94947e39ff3ede49b10d02b75318b Mon Sep 17 00:00:00 2001 From: Mark Backman Date: Fri, 13 Mar 2026 13:55:27 -0400 Subject: [PATCH 0979/1060] Add changelog for #4026 --- changelog/4026.fixed.md | 1 + 1 file changed, 1 insertion(+) create mode 100644 changelog/4026.fixed.md diff --git a/changelog/4026.fixed.md b/changelog/4026.fixed.md new file mode 100644 index 000000000..a12321ab4 --- /dev/null +++ b/changelog/4026.fixed.md @@ -0,0 +1 @@ +- Fixed `DeepgramSTTService` ignoring the `base_url` scheme when using `ws://` or `http://`. Previously these were silently overwritten with `wss://` / `https://`, breaking air-gapped or private deployments that don't use TLS. All scheme choices (`wss://`, `https://`, `ws://`, `http://`, or bare hostname) are now respected. From 24c3d23229b3b78582a8597c0f6d21c56fa9a030 Mon Sep 17 00:00:00 2001 From: Mark Backman Date: Sun, 15 Mar 2026 08:53:06 -0400 Subject: [PATCH 0980/1060] Bump PyJWT minimum version to 2.12.0 for CVE-2026-32597 Addresses Dependabot alert #165 (GHSA-752w-5fwx-jx9f) where PyJWT <= 2.11.0 accepts unknown `crit` header extensions. --- pyproject.toml | 2 +- uv.lock | 11 +++++++---- 2 files changed, 8 insertions(+), 5 deletions(-) diff --git a/pyproject.toml b/pyproject.toml index 48226b14f..6c47ea8b4 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -83,7 +83,7 @@ kokoro = [ "kokoro-onnx>=0.5.0,<1", "requests>=2.32.5,<3" ] krisp = [ "pipecat-ai-krisp~=0.4.0" ] langchain = [ "langchain~=0.3.20", "langchain-community~=0.3.20", "langchain-openai~=0.3.9" ] lemonslice = [ "pipecat-ai[daily]" ] -livekit = [ "livekit>=1.0.13,<2", "livekit-api>=1.0.5,<2", "tenacity>=8.2.3,<10.0.0", "pyjwt>=2.10.1,<3" ] +livekit = [ "livekit>=1.0.13,<2", "livekit-api>=1.0.5,<2", "tenacity>=8.2.3,<10.0.0", "pyjwt>=2.12.0,<3" ] lmnt = [ "pipecat-ai[websockets-base]" ] local = [ "pyaudio~=0.2.14" ] local-smart-turn = [ "coremltools>=8.0", "transformers>=4.48.0,<6", "torch>=2.5.0,<3", "torchaudio>=2.5.0,<3" ] diff --git a/uv.lock b/uv.lock index b68216261..b11a51bb2 100644 --- a/uv.lock +++ b/uv.lock @@ -4862,7 +4862,7 @@ requires-dist = [ { name = "pyaudio", marker = "extra == 'local'", specifier = "~=0.2.14" }, { name = "pydantic", specifier = ">=2.10.6,<3" }, { name = "pygobject", marker = "extra == 'gstreamer'", specifier = "~=3.50.0" }, - { name = "pyjwt", marker = "extra == 'livekit'", specifier = ">=2.10.1,<3" }, + { name = "pyjwt", marker = "extra == 'livekit'", specifier = ">=2.12.0,<3" }, { name = "pyloudnorm", specifier = "~=0.2.0" }, { name = "pyrnnoise", marker = "extra == 'rnnoise'", specifier = "~=0.4.1" }, { name = "python-dotenv", marker = "extra == 'runner'", specifier = ">=1.0.0,<2.0.0" }, @@ -5473,11 +5473,14 @@ sdist = { url = "https://files.pythonhosted.org/packages/a7/5d/f2946cc6c1baf56de [[package]] name = "pyjwt" -version = "2.11.0" +version = "2.12.1" source = { registry = "https://pypi.org/simple" } -sdist = { url = "https://files.pythonhosted.org/packages/5c/5a/b46fa56bf322901eee5b0454a34343cdbdae202cd421775a8ee4e42fd519/pyjwt-2.11.0.tar.gz", hash = "sha256:35f95c1f0fbe5d5ba6e43f00271c275f7a1a4db1dab27bf708073b75318ea623", size = 98019, upload-time = "2026-01-30T19:59:55.694Z" } +dependencies = [ + { name = "typing-extensions", marker = "python_full_version < '3.11'" }, +] +sdist = { url = "https://files.pythonhosted.org/packages/c2/27/a3b6e5bf6ff856d2509292e95c8f57f0df7017cf5394921fc4e4ef40308a/pyjwt-2.12.1.tar.gz", hash = "sha256:c74a7a2adf861c04d002db713dd85f84beb242228e671280bf709d765b03672b", size = 102564, upload-time = "2026-03-13T19:27:37.25Z" } wheels = [ - { url = "https://files.pythonhosted.org/packages/6f/01/c26ce75ba460d5cd503da9e13b21a33804d38c2165dec7b716d06b13010c/pyjwt-2.11.0-py3-none-any.whl", hash = "sha256:94a6bde30eb5c8e04fee991062b534071fd1439ef58d2adc9ccb823e7bcd0469", size = 28224, upload-time = "2026-01-30T19:59:54.539Z" }, + { url = "https://files.pythonhosted.org/packages/e5/7a/8dd906bd22e79e47397a61742927f6747fe93242ef86645ee9092e610244/pyjwt-2.12.1-py3-none-any.whl", hash = "sha256:28ca37c070cad8ba8cd9790cd940535d40274d22f80ab87f3ac6a713e6e8454c", size = 29726, upload-time = "2026-03-13T19:27:35.677Z" }, ] [package.optional-dependencies] From e8415b745162d269867d6c07c0b5298fa8175e16 Mon Sep 17 00:00:00 2001 From: Mark Backman Date: Sun, 15 Mar 2026 08:56:54 -0400 Subject: [PATCH 0981/1060] Add changelog for #4035 --- changelog/4035.security.md | 1 + 1 file changed, 1 insertion(+) create mode 100644 changelog/4035.security.md diff --git a/changelog/4035.security.md b/changelog/4035.security.md new file mode 100644 index 000000000..9ffc17305 --- /dev/null +++ b/changelog/4035.security.md @@ -0,0 +1 @@ +- Bumped PyJWT minimum version from 2.10.1 to 2.12.0 in the `livekit` extra to address CVE-2026-32597 (GHSA-752w-5fwx-jx9f), where PyJWT <= 2.11.0 accepted unknown `crit` header extensions. From a6ad8a355b8878bdc47b5ada12eece476469bb9a Mon Sep 17 00:00:00 2001 From: Om Chauhan Date: Sun, 15 Mar 2026 19:10:32 +0530 Subject: [PATCH 0982/1060] forward timeout_secs in LLMSwitcher register methods --- src/pipecat/pipeline/llm_switcher.py | 6 ++++++ 1 file changed, 6 insertions(+) diff --git a/src/pipecat/pipeline/llm_switcher.py b/src/pipecat/pipeline/llm_switcher.py index 47147dba2..cfee6b2b0 100644 --- a/src/pipecat/pipeline/llm_switcher.py +++ b/src/pipecat/pipeline/llm_switcher.py @@ -80,6 +80,7 @@ class LLMSwitcher(ServiceSwitcher[StrategyType]): start_callback=None, *, cancel_on_interruption: bool = True, + timeout_secs: Optional[float] = None, ): """Register a function handler for LLM function calls, on all LLMs, active or not. @@ -96,6 +97,7 @@ class LLMSwitcher(ServiceSwitcher[StrategyType]): cancel_on_interruption: Whether to cancel this function call when an interruption occurs. Defaults to True. + timeout_secs: Optional timeout in seconds for the function call. """ for llm in self.llms: llm.register_function( @@ -103,6 +105,7 @@ class LLMSwitcher(ServiceSwitcher[StrategyType]): handler=handler, start_callback=start_callback, cancel_on_interruption=cancel_on_interruption, + timeout_secs=timeout_secs, ) def register_direct_function( @@ -110,6 +113,7 @@ class LLMSwitcher(ServiceSwitcher[StrategyType]): handler: DirectFunction, *, cancel_on_interruption: bool = True, + timeout_secs: Optional[float] = None, ): """Register a direct function handler for LLM function calls, on all LLMs, active or not. @@ -117,9 +121,11 @@ class LLMSwitcher(ServiceSwitcher[StrategyType]): handler: The direct function to register. Must follow DirectFunction protocol. cancel_on_interruption: Whether to cancel this function call when an interruption occurs. Defaults to True. + timeout_secs: Optional timeout in seconds for the function call. """ for llm in self.llms: llm.register_direct_function( handler=handler, cancel_on_interruption=cancel_on_interruption, + timeout_secs=timeout_secs, ) From ed0f5ab09b6187fac7a2ed9b68de2f215464280c Mon Sep 17 00:00:00 2001 From: Om Chauhan Date: Sun, 15 Mar 2026 19:15:18 +0530 Subject: [PATCH 0983/1060] added changelog --- changelog/4037.fixed.md | 1 + 1 file changed, 1 insertion(+) create mode 100644 changelog/4037.fixed.md diff --git a/changelog/4037.fixed.md b/changelog/4037.fixed.md new file mode 100644 index 000000000..e55b6f998 --- /dev/null +++ b/changelog/4037.fixed.md @@ -0,0 +1 @@ +- Fixed `LLMSwitcher.register_function()` and `register_direct_function()` not accepting or forwarding the `timeout_secs` parameter. From 538b9fa2d928e52434a50fc282d2ea0064ed5b6d Mon Sep 17 00:00:00 2001 From: Mark Backman Date: Mon, 16 Mar 2026 17:58:44 -0400 Subject: [PATCH 0984/1060] Bump pyopenssl in uv.lock to 26.0.0 --- uv.lock | 6 +++--- 1 file changed, 3 insertions(+), 3 deletions(-) diff --git a/uv.lock b/uv.lock index b68216261..b91380198 100644 --- a/uv.lock +++ b/uv.lock @@ -5524,15 +5524,15 @@ wheels = [ [[package]] name = "pyopenssl" -version = "25.3.0" +version = "26.0.0" source = { registry = "https://pypi.org/simple" } dependencies = [ { name = "cryptography" }, { name = "typing-extensions", marker = "python_full_version < '3.13'" }, ] -sdist = { url = "https://files.pythonhosted.org/packages/80/be/97b83a464498a79103036bc74d1038df4a7ef0e402cfaf4d5e113fb14759/pyopenssl-25.3.0.tar.gz", hash = "sha256:c981cb0a3fd84e8602d7afc209522773b94c1c2446a3c710a75b06fe1beae329", size = 184073, upload-time = "2025-09-17T00:32:21.037Z" } +sdist = { url = "https://files.pythonhosted.org/packages/8e/11/a62e1d33b373da2b2c2cd9eb508147871c80f12b1cacde3c5d314922afdd/pyopenssl-26.0.0.tar.gz", hash = "sha256:f293934e52936f2e3413b89c6ce36df66a0b34ae1ea3a053b8c5020ff2f513fc", size = 185534, upload-time = "2026-03-15T14:28:26.353Z" } wheels = [ - { url = "https://files.pythonhosted.org/packages/d1/81/ef2b1dfd1862567d573a4fdbc9f969067621764fbb74338496840a1d2977/pyopenssl-25.3.0-py3-none-any.whl", hash = "sha256:1fda6fc034d5e3d179d39e59c1895c9faeaf40a79de5fc4cbbfbe0d36f4a77b6", size = 57268, upload-time = "2025-09-17T00:32:19.474Z" }, + { url = "https://files.pythonhosted.org/packages/fb/7d/d4f7d908fa8415571771b30669251d57c3cf313b36a856e6d7548ae01619/pyopenssl-26.0.0-py3-none-any.whl", hash = "sha256:df94d28498848b98cc1c0ffb8ef1e71e40210d3b0a8064c9d29571ed2904bf81", size = 57969, upload-time = "2026-03-15T14:28:24.864Z" }, ] [[package]] From 3b8d040e41781a5bcfe8a9a569e2fe853cbadd20 Mon Sep 17 00:00:00 2001 From: Mark Backman Date: Mon, 16 Mar 2026 19:45:03 -0400 Subject: [PATCH 0985/1060] Fix SonioxSTTService crash when language_hints contains plain strings (#4045) Refactor language_to_soniox_language to use resolve_language + LANGUAGE_MAP pattern consistent with other services. Fix resolve_language fallback to use str(language) instead of language.value so plain strings don't crash. --- changelog/4045.fixed.md | 1 + src/pipecat/services/soniox/stt.py | 75 +++++++++++++++++++++++--- src/pipecat/transcriptions/language.py | 6 +-- 3 files changed, 72 insertions(+), 10 deletions(-) create mode 100644 changelog/4045.fixed.md diff --git a/changelog/4045.fixed.md b/changelog/4045.fixed.md new file mode 100644 index 000000000..ecae78969 --- /dev/null +++ b/changelog/4045.fixed.md @@ -0,0 +1 @@ +Fixed `SonioxSTTService` crash when `language_hints` contains plain strings instead of `Language` enum values. diff --git a/src/pipecat/services/soniox/stt.py b/src/pipecat/services/soniox/stt.py index f123d850c..5163ef113 100644 --- a/src/pipecat/services/soniox/stt.py +++ b/src/pipecat/services/soniox/stt.py @@ -27,7 +27,7 @@ from pipecat.processors.frame_processor import FrameDirection from pipecat.services.settings import NOT_GIVEN, STTSettings, _NotGiven from pipecat.services.stt_latency import SONIOX_TTFS_P99 from pipecat.services.stt_service import WebsocketSTTService -from pipecat.transcriptions.language import Language +from pipecat.transcriptions.language import Language, resolve_language from pipecat.utils.time import time_now_iso8601 from pipecat.utils.tracing.service_decorators import traced_stt @@ -118,14 +118,75 @@ def is_end_token(token: dict) -> bool: def language_to_soniox_language(language: Language) -> str: - """Pipecat Language enum uses same ISO 2-letter codes as Soniox, except with added regional variants. + """Convert a Pipecat Language to a Soniox language code. - For a list of all supported languages, see: https://soniox.com/docs/speech-to-text/core-concepts/supported-languages + For a list of all supported languages, see: + https://soniox.com/docs/speech-to-text/core-concepts/supported-languages """ - lang_str = str(language.value).lower() - if "-" in lang_str: - return lang_str.split("-")[0] - return lang_str + LANGUAGE_MAP = { + Language.AF: "af", + Language.AR: "ar", + Language.AZ: "az", + Language.BE: "be", + Language.BG: "bg", + Language.BN: "bn", + Language.BS: "bs", + Language.CA: "ca", + Language.CS: "cs", + Language.CY: "cy", + Language.DA: "da", + Language.DE: "de", + Language.EL: "el", + Language.EN: "en", + Language.ES: "es", + Language.ET: "et", + Language.EU: "eu", + Language.FA: "fa", + Language.FI: "fi", + Language.FR: "fr", + Language.GL: "gl", + Language.GU: "gu", + Language.HE: "he", + Language.HI: "hi", + Language.HR: "hr", + Language.HU: "hu", + Language.ID: "id", + Language.IT: "it", + Language.JA: "ja", + Language.KA: "ka", + Language.KK: "kk", + Language.KN: "kn", + Language.KO: "ko", + Language.LT: "lt", + Language.LV: "lv", + Language.MK: "mk", + Language.ML: "ml", + Language.MR: "mr", + Language.MS: "ms", + Language.NL: "nl", + Language.NO: "no", + Language.PA: "pa", + Language.PL: "pl", + Language.PT: "pt", + Language.RO: "ro", + Language.RU: "ru", + Language.SK: "sk", + Language.SL: "sl", + Language.SQ: "sq", + Language.SR: "sr", + Language.SV: "sv", + Language.SW: "sw", + Language.TA: "ta", + Language.TE: "te", + Language.TH: "th", + Language.TL: "tl", + Language.TR: "tr", + Language.UK: "uk", + Language.UR: "ur", + Language.VI: "vi", + Language.ZH: "zh", + } + return resolve_language(language, LANGUAGE_MAP, use_base_code=True) def _prepare_language_hints( diff --git a/src/pipecat/transcriptions/language.py b/src/pipecat/transcriptions/language.py index a79a85166..1980590e3 100644 --- a/src/pipecat/transcriptions/language.py +++ b/src/pipecat/transcriptions/language.py @@ -631,13 +631,13 @@ def resolve_language( return result # Not in map - fall back with warning - lang_str = str(language.value) + lang_str = str(language) if use_base_code: # Extract base code (e.g., "en" from "en-US") base_code = lang_str.split("-")[0].lower() - logger.warning(f"Language {language.value} not verified. Using base code '{base_code}'.") + logger.warning(f"Language {language} not verified. Using base code '{base_code}'.") return base_code else: - logger.warning(f"Language {language.value} not verified. Using '{lang_str}'.") + logger.warning(f"Language {language} not verified. Using '{lang_str}'.") return lang_str From 2801439e489eb4511521758210ae465754df6f72 Mon Sep 17 00:00:00 2001 From: Mark Backman Date: Mon, 16 Mar 2026 19:48:49 -0400 Subject: [PATCH 0986/1060] Fix OpenAI STT crash when language is a plain string instead of Language enum --- src/pipecat/services/openai/stt.py | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/src/pipecat/services/openai/stt.py b/src/pipecat/services/openai/stt.py index 39ca60b25..35ec0350c 100644 --- a/src/pipecat/services/openai/stt.py +++ b/src/pipecat/services/openai/stt.py @@ -358,8 +358,8 @@ class OpenAIRealtimeSTTService(WebsocketSTTService): Returns: Two-letter ISO-639-1 language code. """ - # Language.value is e.g. "en", "en-US", "fr", "zh". - return language.value.split("-")[0].lower() + # Language value is e.g. "en", "en-US", "fr", "zh". + return str(language).split("-")[0].lower() def can_generate_metrics(self) -> bool: """Check if the service can generate processing metrics. From abb8bae6f7b4bd9085393d7e14da9a9979e6ae13 Mon Sep 17 00:00:00 2001 From: Mark Backman Date: Mon, 16 Mar 2026 19:49:23 -0400 Subject: [PATCH 0987/1060] Add changelog for #4046 --- changelog/4045.fixed.md | 1 - changelog/4046.fixed.md | 1 + 2 files changed, 1 insertion(+), 1 deletion(-) delete mode 100644 changelog/4045.fixed.md create mode 100644 changelog/4046.fixed.md diff --git a/changelog/4045.fixed.md b/changelog/4045.fixed.md deleted file mode 100644 index ecae78969..000000000 --- a/changelog/4045.fixed.md +++ /dev/null @@ -1 +0,0 @@ -Fixed `SonioxSTTService` crash when `language_hints` contains plain strings instead of `Language` enum values. diff --git a/changelog/4046.fixed.md b/changelog/4046.fixed.md new file mode 100644 index 000000000..0f147e04e --- /dev/null +++ b/changelog/4046.fixed.md @@ -0,0 +1 @@ +Fixed `SonioxSTTService` and `OpenAIRealtimeSTTService` crash when language parameters contain plain strings instead of `Language` enum values. 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=?UTF-8?q?Aleix=20Conchillo=20Flaqu=C3=A9?= Date: Mon, 16 Mar 2026 17:57:39 -0700 Subject: [PATCH 0989/1060] Add DTMF input event support to Daily transport Handle Daily's on_dtmf_event callback, convert it to an InputDTMFFrame pushed into the input transport. Also add __str__ methods to InputDTMFFrame and OutputDTMFFrame for better logging. --- src/pipecat/frames/frames.py | 6 ++++-- src/pipecat/transports/daily/transport.py | 23 +++++++++++++++++++++++ 2 files changed, 27 insertions(+), 2 deletions(-) diff --git a/src/pipecat/frames/frames.py b/src/pipecat/frames/frames.py index 1ef7bdb4a..fbc01c488 100644 --- a/src/pipecat/frames/frames.py +++ b/src/pipecat/frames/frames.py @@ -1001,7 +1001,8 @@ class OutputDTMFFrame(DTMFFrame, DataFrame): specify where the DTMF keypress should be sent. """ - pass + def __str__(self): + return f"{self.name}(tone: {self.button})" # @@ -1658,7 +1659,8 @@ class AssistantImageRawFrame(OutputImageRawFrame): class InputDTMFFrame(DTMFFrame, SystemFrame): """DTMF keypress input frame from transport.""" - pass + def __str__(self): + return f"{self.name}(tone: {self.button.value})" @dataclass diff --git a/src/pipecat/transports/daily/transport.py b/src/pipecat/transports/daily/transport.py index 4626f9f53..2798f6d5e 100644 --- a/src/pipecat/transports/daily/transport.py +++ b/src/pipecat/transports/daily/transport.py @@ -22,6 +22,7 @@ import aiohttp from loguru import logger from pydantic import BaseModel +from pipecat.audio.dtmf.types import KeypadEntry from pipecat.audio.vad.vad_analyzer import VADAnalyzer, VADParams from pipecat.frames.frames import ( BotConnectedFrame, @@ -31,6 +32,7 @@ from pipecat.frames.frames import ( EndFrame, Frame, InputAudioRawFrame, + InputDTMFFrame, InputTransportMessageFrame, InterimTranscriptionFrame, OutputAudioRawFrame, @@ -394,6 +396,7 @@ class DailyCallbacks(BaseModel): on_dialout_stopped: Called when dial-out is stopped. on_dialout_error: Called when dial-out encounters an error. on_dialout_warning: Called when dial-out has a warning. + on_dtmf_event: Called when a DTMF tone happens. on_participant_joined: Called when a participant joins. on_participant_left: Called when a participant leaves. on_participant_updated: Called when participant info is updated. @@ -424,6 +427,7 @@ class DailyCallbacks(BaseModel): on_dialout_stopped: Callable[[Any], Awaitable[None]] on_dialout_error: Callable[[Any], Awaitable[None]] on_dialout_warning: Callable[[Any], Awaitable[None]] + on_dtmf_event: Callable[[Any], Awaitable[None]] on_participant_joined: Callable[[Mapping[str, Any]], Awaitable[None]] on_participant_left: Callable[[Mapping[str, Any], str], Awaitable[None]] on_participant_updated: Callable[[Mapping[str, Any]], Awaitable[None]] @@ -1560,6 +1564,14 @@ class DailyTransportClient(EventHandler): """ self._call_event_callback(self._callbacks.on_dialout_warning, data) + def on_dtmf_event(self, data: Any): + """Handle incoming DTMF events. + + Args: + data: DTMF data. + """ + self._call_event_callback(self._callbacks.on_dtmf_event, data) + def on_participant_joined(self, participant): """Handle participant joined events. @@ -2313,6 +2325,7 @@ class DailyTransport(BaseTransport): on_dialout_stopped=self._on_dialout_stopped, on_dialout_error=self._on_dialout_error, on_dialout_warning=self._on_dialout_warning, + on_dtmf_event=self._on_dtmf_event, on_participant_joined=self._on_participant_joined, on_participant_left=self._on_participant_left, on_participant_updated=self._on_participant_updated, @@ -2354,6 +2367,7 @@ class DailyTransport(BaseTransport): self._register_event_handler("on_dialout_stopped") self._register_event_handler("on_dialout_error") self._register_event_handler("on_dialout_warning") + self._register_event_handler("on_dtmf_event") self._register_event_handler("on_first_participant_joined") self._register_event_handler("on_participant_joined") self._register_event_handler("on_participant_left") @@ -2864,6 +2878,15 @@ class DailyTransport(BaseTransport): logger.warning(f"{self} dial-out warning: {data}") await self._call_event_handler("on_dialout_warning", data) + async def _on_dtmf_event(self, data): + """Handle incoming DTMF events.""" + logger.debug(f"{self} DTMF event: {data}") + await self._call_event_handler("on_dtmf_event", data) + + if self._input: + frame = InputDTMFFrame(button=KeypadEntry(data["tone"])) + await self._input.push_frame(frame) + async def _on_participant_joined(self, participant): """Handle participant joined events.""" id = participant["id"] From 59486d5abfbb2b70ff1748612b3e31898c4d8c29 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Aleix=20Conchillo=20Flaqu=C3=A9?= Date: Mon, 16 Mar 2026 17:58:12 -0700 Subject: [PATCH 0990/1060] Add changelog entries for PR #4047 --- changelog/4047.added.md | 1 + changelog/4047.changed.md | 1 + 2 files changed, 2 insertions(+) create mode 100644 changelog/4047.added.md create mode 100644 changelog/4047.changed.md diff --git a/changelog/4047.added.md b/changelog/4047.added.md new file mode 100644 index 000000000..b0bda2ed4 --- /dev/null +++ b/changelog/4047.added.md @@ -0,0 +1 @@ +- Added DTMF input event support to the Daily transport. Incoming DTMF tones are now received via Daily's `on_dtmf_event` callback and pushed into the pipeline as `InputDTMFFrame`, enabling bots to react to keypad presses from phone callers. diff --git a/changelog/4047.changed.md b/changelog/4047.changed.md new file mode 100644 index 000000000..c93e95f76 --- /dev/null +++ b/changelog/4047.changed.md @@ -0,0 +1 @@ +- Updated `daily-python` dependency to 0.25.0. From e5b4403ed4f6c5234bec080e7febf54db7c9797a Mon Sep 17 00:00:00 2001 From: Julien Vantyghem Date: Mon, 16 Mar 2026 19:54:04 -0600 Subject: [PATCH 0991/1060] update docstring following https://github.com/pipecat-ai/pipecat/pull/3916 --- src/pipecat/transports/daily/utils.py | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/src/pipecat/transports/daily/utils.py b/src/pipecat/transports/daily/utils.py index 8719cfe7d..8c7526357 100644 --- a/src/pipecat/transports/daily/utils.py +++ b/src/pipecat/transports/daily/utils.py @@ -89,7 +89,7 @@ class DailyRoomProperties(BaseModel): enable_emoji_reactions: Whether emoji reactions are enabled. eject_at_room_exp: Whether to remove participants when room expires. enable_dialout: Whether SIP dial-out is enabled. - enable_recording: Recording settings ('cloud', 'local', 'raw-tracks'). + enable_recording: Recording settings ('cloud', 'cloud-audio-only', 'local', 'raw-tracks'). enable_transcription_storage: Whether transcription storage is enabled. geo: Geographic region for room. max_participants: Maximum number of participants allowed in the room. @@ -185,7 +185,7 @@ class DailyMeetingTokenProperties(BaseModel): enable_screenshare: If True, the user will be able to share their screen. start_video_off: If True, the user's video will be turned off when they join the room. start_audio_off: If True, the user's audio will be turned off when they join the room. - enable_recording: Recording settings for the token. Must be one of 'cloud', 'local' or 'raw-tracks'. + enable_recording: Recording settings for the token. Must be one of 'cloud', 'cloud-audio-only', 'local' or 'raw-tracks'. enable_prejoin_ui: If True, the user will see the prejoin UI before joining the room. start_cloud_recording: Start cloud recording when the user joins the room. permissions: Specifies the initial default permissions for a non-meeting-owner participant. From 89cb0f089e128a6192d0de90b751e3537da0b1c4 Mon Sep 17 00:00:00 2001 From: "copilot-swe-agent[bot]" <198982749+Copilot@users.noreply.github.com> Date: Tue, 17 Mar 2026 04:01:00 +0000 Subject: [PATCH 0992/1060] Initial plan From 7e60320a746184391233630489c53ffa69ce0637 Mon Sep 17 00:00:00 2001 From: "copilot-swe-agent[bot]" <198982749+Copilot@users.noreply.github.com> Date: Tue, 17 Mar 2026 04:04:11 +0000 Subject: [PATCH 0993/1060] fix: set enable_dialout to False in PSTN runner to prevent room creation failures Co-authored-by: jamsea <614910+jamsea@users.noreply.github.com> --- src/pipecat/runner/daily.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/src/pipecat/runner/daily.py b/src/pipecat/runner/daily.py index cfb754dfd..d61f14381 100644 --- a/src/pipecat/runner/daily.py +++ b/src/pipecat/runner/daily.py @@ -229,7 +229,7 @@ async def configure( provider=sip_provider, ) room_properties.sip = sip_params - room_properties.enable_dialout = True # Enable outbound calls if needed + room_properties.enable_dialout = False # Requires dialout entitlement on Daily plan room_properties.start_video_off = not sip_enable_video # Voice-only by default # Create room parameters From e11b48631230fe5affd0dbaf9aaf6598f3c6e4aa Mon Sep 17 00:00:00 2001 From: Mark Backman Date: Tue, 17 Mar 2026 08:54:07 -0400 Subject: [PATCH 0994/1060] fix: clean up configure() type hints, deduplicate token expiry, and improve comment Narrow misleading Optional type hints on parameters that never accept None, extract the duplicated token_exp_duration * 60 * 60 calculation, remove unnecessary forward-reference quotes on DailyMeetingTokenProperties, and clarify why enable_dialout is explicitly set to False. --- changelog/4048.changed.md | 1 + src/pipecat/runner/daily.py | 23 ++++++++++++++--------- 2 files changed, 15 insertions(+), 9 deletions(-) create mode 100644 changelog/4048.changed.md diff --git a/changelog/4048.changed.md b/changelog/4048.changed.md new file mode 100644 index 000000000..e5b9aab06 --- /dev/null +++ b/changelog/4048.changed.md @@ -0,0 +1 @@ +- Narrowed misleading `Optional` type hints and deduplicated token expiry calculation in `configure()` (`pipecat.runner.daily`). diff --git a/src/pipecat/runner/daily.py b/src/pipecat/runner/daily.py index d61f14381..099d931a4 100644 --- a/src/pipecat/runner/daily.py +++ b/src/pipecat/runner/daily.py @@ -79,16 +79,16 @@ async def configure( aiohttp_session: aiohttp.ClientSession, *, api_key: Optional[str] = None, - room_exp_duration: Optional[float] = 2.0, - token_exp_duration: Optional[float] = 2.0, + room_exp_duration: float = 2.0, + token_exp_duration: float = 2.0, sip_caller_phone: Optional[str] = None, - sip_enable_video: Optional[bool] = False, - sip_num_endpoints: Optional[int] = 1, + sip_enable_video: bool = False, + sip_num_endpoints: int = 1, sip_codecs: Optional[Dict[str, List[str]]] = None, sip_provider: Optional[str] = None, room_geo: Optional[str] = None, room_properties: Optional[DailyRoomProperties] = None, - token_properties: Optional["DailyMeetingTokenProperties"] = None, + token_properties: Optional[DailyMeetingTokenProperties] = None, ) -> DailyRoomConfig: """Configure Daily room URL and token with optional SIP capabilities. @@ -184,6 +184,8 @@ async def configure( aiohttp_session=aiohttp_session, ) + token_expiry_seconds: float = token_exp_duration * 60 * 60 + # Check for existing room URL (only in standard mode) existing_room_url = os.getenv("DAILY_ROOM_URL") if existing_room_url and not sip_enabled: @@ -192,11 +194,12 @@ async def configure( room_url = existing_room_url # Create token and return standard format - expiry_time: float = token_exp_duration * 60 * 60 token_params = None if token_properties: token_params = DailyMeetingTokenParams(properties=token_properties) - token = await daily_rest_helper.get_token(room_url, expiry_time, params=token_params) + token = await daily_rest_helper.get_token( + room_url, token_expiry_seconds, params=token_params + ) return DailyRoomConfig(room_url=room_url, token=token) # Create a new room @@ -229,7 +232,10 @@ async def configure( provider=sip_provider, ) room_properties.sip = sip_params - room_properties.enable_dialout = False # Requires dialout entitlement on Daily plan + # Explicitly disable dialout to prevent room creation failures on + # accounts where dialout defaults to enabled but the plan lacks the + # required dialout entitlement. + room_properties.enable_dialout = False room_properties.start_video_off = not sip_enable_video # Voice-only by default # Create room parameters @@ -241,7 +247,6 @@ async def configure( logger.info(f"Created Daily room: {room_url}") # Create meeting token - token_expiry_seconds = token_exp_duration * 60 * 60 token_params = None if token_properties: token_params = DailyMeetingTokenParams(properties=token_properties) From 091f88e42e4b8456dde672acfbcc4a3677fb4ef5 Mon Sep 17 00:00:00 2001 From: Mark Backman Date: Tue, 17 Mar 2026 09:03:50 -0400 Subject: [PATCH 0995/1060] feat: add enable_dialout parameter to configure() for dial-out rooms Expose enable_dialout as a configure() parameter (default False) so dial-out examples can opt in without needing to build DailyRoomProperties manually. --- changelog/4048.changed.md | 2 +- src/pipecat/runner/daily.py | 9 +++++---- 2 files changed, 6 insertions(+), 5 deletions(-) diff --git a/changelog/4048.changed.md b/changelog/4048.changed.md index e5b9aab06..edef83283 100644 --- a/changelog/4048.changed.md +++ b/changelog/4048.changed.md @@ -1 +1 @@ -- Narrowed misleading `Optional` type hints and deduplicated token expiry calculation in `configure()` (`pipecat.runner.daily`). +- Added `enable_dialout` parameter to `configure()` in `pipecat.runner.daily` to support dial-out rooms. Also narrowed misleading `Optional` type hints and deduplicated token expiry calculation. diff --git a/src/pipecat/runner/daily.py b/src/pipecat/runner/daily.py index 099d931a4..b9bcb6e3d 100644 --- a/src/pipecat/runner/daily.py +++ b/src/pipecat/runner/daily.py @@ -84,6 +84,7 @@ async def configure( sip_caller_phone: Optional[str] = None, sip_enable_video: bool = False, sip_num_endpoints: int = 1, + enable_dialout: bool = False, sip_codecs: Optional[Dict[str, List[str]]] = None, sip_provider: Optional[str] = None, room_geo: Optional[str] = None, @@ -105,6 +106,8 @@ async def configure( When provided, enables SIP functionality and returns SipRoomConfig. sip_enable_video: Whether video is enabled for SIP. sip_num_endpoints: Number of allowed SIP endpoints. + enable_dialout: Whether to enable outbound dialing (PSTN or SIP) on the room. + Requires dial-out entitlement on your Daily account. sip_codecs: Codecs to support for audio and video. If None, uses Daily defaults. Example: {"audio": ["OPUS"], "video": ["H264"]} sip_provider: SIP provider name (e.g., "daily"). Only used when @@ -159,6 +162,7 @@ async def configure( sip_caller_phone is not None, sip_enable_video is not False, sip_num_endpoints != 1, + enable_dialout is not False, sip_codecs is not None, sip_provider is not None, room_geo is not None, @@ -232,10 +236,7 @@ async def configure( provider=sip_provider, ) room_properties.sip = sip_params - # Explicitly disable dialout to prevent room creation failures on - # accounts where dialout defaults to enabled but the plan lacks the - # required dialout entitlement. - room_properties.enable_dialout = False + room_properties.enable_dialout = enable_dialout room_properties.start_video_off = not sip_enable_video # Voice-only by default # Create room parameters From 024e2ebd4e63f0efb8334a4ff3a27b86b6aba1e7 Mon Sep 17 00:00:00 2001 From: Mark Backman Date: Tue, 17 Mar 2026 10:51:01 -0400 Subject: [PATCH 0996/1060] Fix deprecation warning when using filter_incomplete_user_turns --- .../processors/aggregators/llm_response_universal.py | 9 +++++---- 1 file changed, 5 insertions(+), 4 deletions(-) diff --git a/src/pipecat/processors/aggregators/llm_response_universal.py b/src/pipecat/processors/aggregators/llm_response_universal.py index e1e356007..b8a7061d8 100644 --- a/src/pipecat/processors/aggregators/llm_response_universal.py +++ b/src/pipecat/processors/aggregators/llm_response_universal.py @@ -75,6 +75,7 @@ from pipecat.processors.aggregators.llm_context_summarizer import ( SummaryAppliedEvent, ) from pipecat.processors.frame_processor import FrameCallback, FrameDirection, FrameProcessor +from pipecat.services.settings import LLMSettings from pipecat.turns.user_idle_controller import UserIdleController from pipecat.turns.user_mute import BaseUserMuteStrategy from pipecat.turns.user_start import BaseUserTurnStartStrategy, UserTurnStartedParams @@ -561,10 +562,10 @@ class LLMUserAggregator(LLMContextAggregator): # Enable the feature on the LLM with config await self.push_frame( LLMUpdateSettingsFrame( - settings={ - "filter_incomplete_user_turns": True, - "user_turn_completion_config": config, - } + delta=LLMSettings( + filter_incomplete_user_turns=True, + user_turn_completion_config=config, + ) ) ) From 5000b040ddd5aa10eac3239b87fbbded0362075e Mon Sep 17 00:00:00 2001 From: Mark Backman Date: Tue, 17 Mar 2026 11:31:08 -0400 Subject: [PATCH 0997/1060] Fix stale state in user turn stop strategies between turns Reset stop strategies at turn start (not just turn stop) so that late transcriptions arriving between turns do not leave stale _text that causes premature stops on the next turn. Also cancel pending timeout tasks in reset() for both SpeechTimeout and TurnAnalyzer strategies. --- .../speech_timeout_user_turn_stop_strategy.py | 3 + .../turn_analyzer_user_turn_stop_strategy.py | 3 + src/pipecat/turns/user_turn_controller.py | 4 ++ tests/test_user_turn_controller.py | 68 +++++++++++++++++++ tests/test_user_turn_stop_strategy.py | 44 ++++++++++++ 5 files changed, 122 insertions(+) diff --git a/src/pipecat/turns/user_stop/speech_timeout_user_turn_stop_strategy.py b/src/pipecat/turns/user_stop/speech_timeout_user_turn_stop_strategy.py index 66d6fa703..ec94d9176 100644 --- a/src/pipecat/turns/user_stop/speech_timeout_user_turn_stop_strategy.py +++ b/src/pipecat/turns/user_stop/speech_timeout_user_turn_stop_strategy.py @@ -64,6 +64,9 @@ class SpeechTimeoutUserTurnStopStrategy(BaseUserTurnStopStrategy): self._vad_user_speaking = False self._transcript_finalized = False self._vad_stopped_time = None + if self._timeout_task: + await self.task_manager.cancel_task(self._timeout_task) + self._timeout_task = None async def setup(self, task_manager: BaseTaskManager): """Initialize the strategy with the given task manager. diff --git a/src/pipecat/turns/user_stop/turn_analyzer_user_turn_stop_strategy.py b/src/pipecat/turns/user_stop/turn_analyzer_user_turn_stop_strategy.py index f141a75b7..232bde223 100644 --- a/src/pipecat/turns/user_stop/turn_analyzer_user_turn_stop_strategy.py +++ b/src/pipecat/turns/user_stop/turn_analyzer_user_turn_stop_strategy.py @@ -68,6 +68,9 @@ class TurnAnalyzerUserTurnStopStrategy(BaseUserTurnStopStrategy): self._vad_user_speaking = False self._vad_stopped_time = None self._transcript_finalized = False + if self._timeout_task: + await self.task_manager.cancel_task(self._timeout_task) + self._timeout_task = None async def setup(self, task_manager: BaseTaskManager): """Initialize the strategy with the given task manager. diff --git a/src/pipecat/turns/user_turn_controller.py b/src/pipecat/turns/user_turn_controller.py index adaafd298..a064fc47b 100644 --- a/src/pipecat/turns/user_turn_controller.py +++ b/src/pipecat/turns/user_turn_controller.py @@ -256,6 +256,10 @@ class UserTurnController(BaseObject): for s in self._user_turn_strategies.start or []: await s.reset() + # Reset all user turn stop strategies to start fresh for the new turn. + for s in self._user_turn_strategies.stop or []: + await s.reset() + await self._call_event_handler("on_user_turn_started", strategy, params) async def _trigger_user_turn_stop( diff --git a/tests/test_user_turn_controller.py b/tests/test_user_turn_controller.py index 72a04a519..2883d39bd 100644 --- a/tests/test_user_turn_controller.py +++ b/tests/test_user_turn_controller.py @@ -15,6 +15,7 @@ from pipecat.frames.frames import ( VADUserStartedSpeakingFrame, VADUserStoppedSpeakingFrame, ) +from pipecat.turns.user_start import VADUserTurnStartStrategy from pipecat.turns.user_start.min_words_user_turn_start_strategy import ( MinWordsUserTurnStartStrategy, ) @@ -199,6 +200,73 @@ class TestUserTurnController(unittest.IsolatedAsyncioTestCase): self.assertTrue(should_stop) self.assertTrue(timeout) + async def test_late_transcription_between_turns_no_premature_stop(self): + """Test that a late transcription arriving between turns does not cause a premature stop. + + Reproduces the bug from issue #4053: after turn 1 completes and reset() + clears state, a late TranscriptionFrame sets _text to stale content. On + the next turn, that stale _text gates a premature turn stop via timeout(0) + before the current turn's transcript arrives. + + Uses only VADUserTurnStartStrategy (no TranscriptionUserTurnStartStrategy) + so the late transcription doesn't trigger a spurious turn start. + """ + controller = UserTurnController( + user_turn_strategies=UserTurnStrategies( + start=[VADUserTurnStartStrategy()], + stop=[SpeechTimeoutUserTurnStopStrategy(user_speech_timeout=TRANSCRIPTION_TIMEOUT)], + ), + user_turn_stop_timeout=USER_TURN_STOP_TIMEOUT, + ) + + await controller.setup(self.task_manager) + + start_count = 0 + stop_count = 0 + + @controller.event_handler("on_user_turn_started") + async def on_user_turn_started(controller, strategy, params): + nonlocal start_count + start_count += 1 + + @controller.event_handler("on_user_turn_stopped") + async def on_user_turn_stopped(controller, strategy, params): + nonlocal stop_count + stop_count += 1 + + # === Turn 1: S-T-E === + await controller.process_frame(VADUserStartedSpeakingFrame()) + self.assertEqual(start_count, 1) + + await controller.process_frame( + TranscriptionFrame(text="Hello!", user_id="", timestamp="now") + ) + + await controller.process_frame(VADUserStoppedSpeakingFrame()) + await asyncio.sleep(TRANSCRIPTION_TIMEOUT + 0.1) + self.assertEqual(stop_count, 1) + + # === Between turns: late transcription arrives === + # This sets _text on the stop strategy while _user_turn is False. + await controller.process_frame( + TranscriptionFrame(text="Hello!", user_id="", timestamp="now") + ) + + # === Turn 2: S-T-E (transcription arrives during turn) === + # The fix resets stop strategies at turn start, clearing stale _text. + await controller.process_frame(VADUserStartedSpeakingFrame()) + self.assertEqual(start_count, 2) + + await controller.process_frame( + TranscriptionFrame(text="How are you?", user_id="", timestamp="now") + ) + + await controller.process_frame(VADUserStoppedSpeakingFrame()) + + # Wait for user_speech_timeout to elapse — should get turn 2 stop + await asyncio.sleep(TRANSCRIPTION_TIMEOUT + 0.1) + self.assertEqual(stop_count, 2) + if __name__ == "__main__": unittest.main() diff --git a/tests/test_user_turn_stop_strategy.py b/tests/test_user_turn_stop_strategy.py index 80fb98efc..85f9f2752 100644 --- a/tests/test_user_turn_stop_strategy.py +++ b/tests/test_user_turn_stop_strategy.py @@ -493,6 +493,50 @@ class TestSpeechTimeoutUserTurnStopStrategy(unittest.IsolatedAsyncioTestCase): # Finalized transcript received after timeout, triggers immediately self.assertTrue(should_start) + async def test_reset_clears_stale_text_no_premature_stop(self): + """Test that reset() clears stale text and cancels timeout, preventing premature stop. + + Reproduces the bug from issue #4053: after turn 1 completes and + reset() is called, a late transcription sets _text. If reset() is + called again at turn 2 start, the stale _text should be cleared + so no premature stop occurs on VAD stop. + """ + strategy = await self._create_strategy() + + stop_count = 0 + + @strategy.event_handler("on_user_turn_stopped") + async def on_user_turn_stopped(strategy, params): + nonlocal stop_count + stop_count += 1 + + # === Turn 1: S-T-E === + await strategy.process_frame(VADUserStartedSpeakingFrame()) + await strategy.process_frame(TranscriptionFrame(text="Hello!", user_id="cat", timestamp="")) + await strategy.process_frame(VADUserStoppedSpeakingFrame()) + await asyncio.sleep(AGGREGATION_TIMEOUT + 0.1) + self.assertEqual(stop_count, 1) + + # Reset after turn 1 (as controller would do at turn stop) + await strategy.reset() + + # === Late transcription arrives between turns === + await strategy.process_frame(TranscriptionFrame(text="Hello!", user_id="cat", timestamp="")) + + # Reset at turn 2 start (the fix: controller now resets stop strategies at turn start) + await strategy.reset() + + # === Turn 2: S-T-E (transcription arrives during turn) === + await strategy.process_frame(VADUserStartedSpeakingFrame()) + await strategy.process_frame( + TranscriptionFrame(text="How are you?", user_id="cat", timestamp="") + ) + await strategy.process_frame(VADUserStoppedSpeakingFrame()) + + # Wait for timeout — should get turn 2 stop with the real transcription + await asyncio.sleep(AGGREGATION_TIMEOUT + 0.1) + self.assertEqual(stop_count, 2) + class TestExternalUserTurnStopStrategy(unittest.IsolatedAsyncioTestCase): async def test_external_strategy(self): From d70df1d8b0cd1a11ce524617dc2a25a9266c06e3 Mon Sep 17 00:00:00 2001 From: Mark Backman Date: Tue, 17 Mar 2026 11:35:38 -0400 Subject: [PATCH 0998/1060] Add changelog for #4057 --- changelog/4057.fixed.md | 1 + 1 file changed, 1 insertion(+) create mode 100644 changelog/4057.fixed.md diff --git a/changelog/4057.fixed.md b/changelog/4057.fixed.md new file mode 100644 index 000000000..b63b8540e --- /dev/null +++ b/changelog/4057.fixed.md @@ -0,0 +1 @@ +- Fixed premature user turn stops caused by late transcriptions arriving between turns. A stale transcript from the previous turn could persist into the next turn and trigger a stop before the current turn's real transcript arrived. Stop strategies are now reset at both turn start and turn stop to prevent state from leaking across turn boundaries. From 790a23d2e569957923f49bc790f82be26477900c Mon Sep 17 00:00:00 2001 From: Mark Backman Date: Tue, 17 Mar 2026 12:00:28 -0400 Subject: [PATCH 0999/1060] fix: resolve raw language strings through Language enum for proper service conversion Raw strings like "de-DE" passed as the language parameter to TTS/STT services were bypassing the Language enum resolution logic, causing silent failures (e.g. ElevenLabs expects "de" not "de-DE"). Now raw strings are first converted to Language enums so they go through the same resolve_language() path, with a warning logged for unrecognized strings. --- src/pipecat/services/stt_service.py | 27 ++- src/pipecat/services/tts_service.py | 27 ++- tests/test_service_language.py | 251 ++++++++++++++++++++++++++++ 3 files changed, 303 insertions(+), 2 deletions(-) create mode 100644 tests/test_service_language.py diff --git a/src/pipecat/services/stt_service.py b/src/pipecat/services/stt_service.py index c442c41eb..ecfec7b9b 100644 --- a/src/pipecat/services/stt_service.py +++ b/src/pipecat/services/stt_service.py @@ -124,6 +124,18 @@ class STTService(AIService): # Convert Language enum to service-specific format at init time. # Runtime updates are handled by _update_settings(), but init-time # settings bypass that path and need explicit conversion. + # Raw strings (e.g. "de-DE") are first converted to Language enums + # so they go through the same resolution logic. + if isinstance(self._settings.language, str) and not isinstance( + self._settings.language, Language + ): + try: + self._settings.language = Language(self._settings.language) + except ValueError: + logger.warning( + f"Language string '{self._settings.language}' is not a recognized " + f"Language code. It will be passed to the service as-is." + ) if isinstance(self._settings.language, Language): converted = self.language_to_service_language(self._settings.language) if converted is not None: @@ -294,7 +306,20 @@ class STTService(AIService): Returns: Dict mapping changed field names to their previous values. """ - # Translate language *before* applying so the stored value is canonical + # Translate language *before* applying so the stored value is canonical. + # Raw strings are first converted to Language enums for proper resolution. + if ( + is_given(delta.language) + and isinstance(delta.language, str) + and not isinstance(delta.language, Language) + ): + try: + delta.language = Language(delta.language) + except ValueError: + logger.warning( + f"Language string '{delta.language}' is not a recognized " + f"Language code. It will be passed to the service as-is." + ) if is_given(delta.language) and isinstance(delta.language, Language): converted = self.language_to_service_language(delta.language) if converted is not None: diff --git a/src/pipecat/services/tts_service.py b/src/pipecat/services/tts_service.py index e2a9190ab..7583339c8 100644 --- a/src/pipecat/services/tts_service.py +++ b/src/pipecat/services/tts_service.py @@ -248,6 +248,18 @@ class TTSService(AIService): # Convert Language enum to service-specific format at init time. # Runtime updates are handled by _update_settings(), but init-time # settings bypass that path and need explicit conversion. + # Raw strings (e.g. "de-DE") are first converted to Language enums + # so they go through the same resolution logic. + if isinstance(self._settings.language, str) and not isinstance( + self._settings.language, Language + ): + try: + self._settings.language = Language(self._settings.language) + except ValueError: + logger.warning( + f"Language string '{self._settings.language}' is not a recognized " + f"Language code. It will be passed to the service as-is." + ) if isinstance(self._settings.language, Language): converted = self.language_to_service_language(self._settings.language) if converted is not None: @@ -610,7 +622,20 @@ class TTSService(AIService): Returns: Dict mapping changed field names to their previous values. """ - # Translate language *before* applying so the stored value is canonical + # Translate language *before* applying so the stored value is canonical. + # Raw strings are first converted to Language enums for proper resolution. + if ( + is_given(delta.language) + and isinstance(delta.language, str) + and not isinstance(delta.language, Language) + ): + try: + delta.language = Language(delta.language) + except ValueError: + logger.warning( + f"Language string '{delta.language}' is not a recognized " + f"Language code. It will be passed to the service as-is." + ) if is_given(delta.language) and isinstance(delta.language, Language): converted = self.language_to_service_language(delta.language) if converted is not None: diff --git a/tests/test_service_language.py b/tests/test_service_language.py new file mode 100644 index 000000000..6ac23c823 --- /dev/null +++ b/tests/test_service_language.py @@ -0,0 +1,251 @@ +# +# Copyright (c) 2024-2026, Daily +# +# SPDX-License-Identifier: BSD 2-Clause License +# + +"""Tests for language parameter handling in TTS and STT services. + +Verifies that Language enums, raw strings (e.g. "de-DE"), and unrecognized +strings are all resolved correctly at both init time and runtime update time. +""" + +from typing import AsyncGenerator, Optional +from unittest.mock import patch + +import pytest + +from pipecat.frames.frames import Frame +from pipecat.services.settings import STTSettings, TTSSettings +from pipecat.services.stt_service import STTService +from pipecat.services.tts_service import TTSService +from pipecat.transcriptions.language import Language, resolve_language + +# --------------------------------------------------------------------------- +# Minimal concrete subclasses for testing +# --------------------------------------------------------------------------- + +# A simple language map using only base codes (like ElevenLabs does). +_LANGUAGE_MAP = { + Language.DE: "de", + Language.EN: "en", + Language.FR: "fr", +} + + +class _TestTTSService(TTSService): + """Minimal concrete TTS service for testing language resolution.""" + + class Settings(TTSSettings): + pass + + def __init__(self, **kwargs): + super().__init__(**kwargs) + + async def run_tts(self, text: str, context_id: str) -> AsyncGenerator[Frame, None]: + yield # pragma: no cover + + def language_to_service_language(self, language: Language) -> Optional[str]: + return resolve_language(language, _LANGUAGE_MAP, use_base_code=True) + + +class _TestSTTService(STTService): + """Minimal concrete STT service for testing language resolution.""" + + class Settings(STTSettings): + pass + + def __init__(self, **kwargs): + super().__init__(**kwargs) + + async def run_stt(self, audio: bytes) -> AsyncGenerator[Frame, None]: + yield # pragma: no cover + + async def process_audio_frame(self, frame, direction): + pass # pragma: no cover + + def language_to_service_language(self, language: Language) -> Optional[str]: + return resolve_language(language, _LANGUAGE_MAP, use_base_code=True) + + +# --------------------------------------------------------------------------- +# TTS init tests +# --------------------------------------------------------------------------- + + +class TestTTSLanguageInit: + """Test language resolution at TTS service init time.""" + + def test_language_enum_base_code(self): + """Language.DE (base code in map) resolves to 'de'.""" + svc = _TestTTSService(settings=_TestTTSService.Settings(language=Language.DE)) + assert svc._settings.language == "de" + + def test_language_enum_regional_code(self): + """Language.DE_DE (regional, not in map) falls back to base code 'de'.""" + svc = _TestTTSService(settings=_TestTTSService.Settings(language=Language.DE_DE)) + assert svc._settings.language == "de" + + def test_raw_string_base_code(self): + """Raw string 'de' is converted to Language.DE then resolved to 'de'.""" + svc = _TestTTSService(settings=_TestTTSService.Settings(language="de")) + assert svc._settings.language == "de" + + def test_raw_string_regional_code(self): + """Raw string 'de-DE' is converted to Language.DE_DE then resolved to 'de'.""" + svc = _TestTTSService(settings=_TestTTSService.Settings(language="de-DE")) + assert svc._settings.language == "de" + + def test_raw_string_other_regional(self): + """Raw string 'en-US' is converted to Language.EN_US then resolved to 'en'.""" + svc = _TestTTSService(settings=_TestTTSService.Settings(language="en-US")) + assert svc._settings.language == "en" + + def test_raw_string_unrecognized(self): + """Unrecognized raw string logs a warning and is passed through as-is.""" + with patch("pipecat.services.tts_service.logger") as mock_logger: + svc = _TestTTSService(settings=_TestTTSService.Settings(language="klingon")) + assert svc._settings.language == "klingon" + mock_logger.warning.assert_called_once() + assert "klingon" in mock_logger.warning.call_args[0][0] + + def test_language_none(self): + """None language is left as None.""" + svc = _TestTTSService(settings=_TestTTSService.Settings(language=None)) + assert svc._settings.language is None + + +# --------------------------------------------------------------------------- +# STT init tests +# --------------------------------------------------------------------------- + + +class TestSTTLanguageInit: + """Test language resolution at STT service init time.""" + + def test_language_enum_base_code(self): + """Language.FR (base code in map) resolves to 'fr'.""" + svc = _TestSTTService(settings=_TestSTTService.Settings(language=Language.FR)) + assert svc._settings.language == "fr" + + def test_language_enum_regional_code(self): + """Language.FR_FR (regional, not in map) falls back to base code 'fr'.""" + svc = _TestSTTService(settings=_TestSTTService.Settings(language=Language.FR_FR)) + assert svc._settings.language == "fr" + + def test_raw_string_base_code(self): + """Raw string 'fr' is converted to Language.FR then resolved to 'fr'.""" + svc = _TestSTTService(settings=_TestSTTService.Settings(language="fr")) + assert svc._settings.language == "fr" + + def test_raw_string_regional_code(self): + """Raw string 'de-DE' is converted to Language.DE_DE then resolved to 'de'.""" + svc = _TestSTTService(settings=_TestSTTService.Settings(language="de-DE")) + assert svc._settings.language == "de" + + def test_raw_string_unrecognized(self): + """Unrecognized raw string logs a warning and is passed through as-is.""" + with patch("pipecat.services.stt_service.logger") as mock_logger: + svc = _TestSTTService(settings=_TestSTTService.Settings(language="klingon")) + assert svc._settings.language == "klingon" + mock_logger.warning.assert_called_once() + assert "klingon" in mock_logger.warning.call_args[0][0] + + def test_language_none(self): + """None language is left as None.""" + svc = _TestSTTService(settings=_TestSTTService.Settings(language=None)) + assert svc._settings.language is None + + +# --------------------------------------------------------------------------- +# TTS runtime update tests +# --------------------------------------------------------------------------- + + +class TestTTSLanguageUpdate: + """Test language resolution during runtime settings updates.""" + + @pytest.mark.asyncio + async def test_update_language_enum_base_code(self): + """Updating with Language.EN resolves to 'en'.""" + svc = _TestTTSService(settings=_TestTTSService.Settings(language=None)) + await svc._update_settings(_TestTTSService.Settings(language=Language.EN)) + assert svc._settings.language == "en" + + @pytest.mark.asyncio + async def test_update_language_enum_regional_code(self): + """Updating with Language.DE_DE falls back to base code 'de'.""" + svc = _TestTTSService(settings=_TestTTSService.Settings(language=None)) + await svc._update_settings(_TestTTSService.Settings(language=Language.DE_DE)) + assert svc._settings.language == "de" + + @pytest.mark.asyncio + async def test_update_raw_string_base_code(self): + """Updating with raw string 'de' resolves to 'de'.""" + svc = _TestTTSService(settings=_TestTTSService.Settings(language=None)) + await svc._update_settings(_TestTTSService.Settings(language="de")) + assert svc._settings.language == "de" + + @pytest.mark.asyncio + async def test_update_raw_string_regional_code(self): + """Updating with raw string 'de-DE' resolves to 'de'.""" + svc = _TestTTSService(settings=_TestTTSService.Settings(language=None)) + await svc._update_settings(_TestTTSService.Settings(language="de-DE")) + assert svc._settings.language == "de" + + @pytest.mark.asyncio + async def test_update_raw_string_unrecognized(self): + """Updating with unrecognized string logs warning and passes through.""" + svc = _TestTTSService(settings=_TestTTSService.Settings(language=None)) + with patch("pipecat.services.tts_service.logger") as mock_logger: + await svc._update_settings(_TestTTSService.Settings(language="klingon")) + assert svc._settings.language == "klingon" + mock_logger.warning.assert_called_once() + assert "klingon" in mock_logger.warning.call_args[0][0] + + +# --------------------------------------------------------------------------- +# STT runtime update tests +# --------------------------------------------------------------------------- + + +class TestSTTLanguageUpdate: + """Test language resolution during runtime settings updates.""" + + @pytest.mark.asyncio + async def test_update_language_enum_base_code(self): + """Updating with Language.EN resolves to 'en'.""" + svc = _TestSTTService(settings=_TestSTTService.Settings(language=None)) + await svc._update_settings(_TestSTTService.Settings(language=Language.EN)) + assert svc._settings.language == "en" + + @pytest.mark.asyncio + async def test_update_language_enum_regional_code(self): + """Updating with Language.FR_FR falls back to base code 'fr'.""" + svc = _TestSTTService(settings=_TestSTTService.Settings(language=None)) + await svc._update_settings(_TestSTTService.Settings(language=Language.FR_FR)) + assert svc._settings.language == "fr" + + @pytest.mark.asyncio + async def test_update_raw_string_base_code(self): + """Updating with raw string 'fr' resolves to 'fr'.""" + svc = _TestSTTService(settings=_TestSTTService.Settings(language=None)) + await svc._update_settings(_TestSTTService.Settings(language="fr")) + assert svc._settings.language == "fr" + + @pytest.mark.asyncio + async def test_update_raw_string_regional_code(self): + """Updating with raw string 'fr-FR' resolves to 'fr'.""" + svc = _TestSTTService(settings=_TestSTTService.Settings(language=None)) + await svc._update_settings(_TestSTTService.Settings(language="fr-FR")) + assert svc._settings.language == "fr" + + @pytest.mark.asyncio + async def test_update_raw_string_unrecognized(self): + """Updating with unrecognized string logs warning and passes through.""" + svc = _TestSTTService(settings=_TestSTTService.Settings(language=None)) + with patch("pipecat.services.stt_service.logger") as mock_logger: + await svc._update_settings(_TestSTTService.Settings(language="klingon")) + assert svc._settings.language == "klingon" + mock_logger.warning.assert_called_once() + assert "klingon" in mock_logger.warning.call_args[0][0] From 18e654b3f03e294d6c6b4ca5d813530c4dffbc96 Mon Sep 17 00:00:00 2001 From: Mark Backman Date: Tue, 17 Mar 2026 12:01:50 -0400 Subject: [PATCH 1000/1060] docs: add changelog for #4058 --- changelog/4058.fixed.md | 1 + 1 file changed, 1 insertion(+) create mode 100644 changelog/4058.fixed.md diff --git a/changelog/4058.fixed.md b/changelog/4058.fixed.md new file mode 100644 index 000000000..4b5baed82 --- /dev/null +++ b/changelog/4058.fixed.md @@ -0,0 +1 @@ +- Fixed raw language strings like `"de-DE"` silently failing when passed to TTS/STT services (e.g. ElevenLabs producing no audio). Raw strings now go through the same `Language` enum resolution as enum values, so regional codes like `"de-DE"` are properly converted to service-expected formats like `"de"`. Unrecognized strings log a warning instead of failing silently. 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keywords, search, redact, and replace were being converted to strings before being passed to the SDK connect() method. The SDK expects lists so its encode_query can produce repeated query params (keyterm=a&keyterm=b). --- changelog/4063.fixed.md | 1 + src/pipecat/services/deepgram/stt.py | 17 +++++++++++++++-- 2 files changed, 16 insertions(+), 2 deletions(-) create mode 100644 changelog/4063.fixed.md diff --git a/changelog/4063.fixed.md b/changelog/4063.fixed.md new file mode 100644 index 000000000..ea703078a --- /dev/null +++ b/changelog/4063.fixed.md @@ -0,0 +1 @@ +- Fixed Deepgram STT list-type settings (`keyterm`, `keywords`, `search`, `redact`, `replace`) being stringified instead of passed as lists to the SDK, which caused them to be sent as literal strings (e.g. `"['pipecat']"`) in the WebSocket query params. diff --git a/src/pipecat/services/deepgram/stt.py b/src/pipecat/services/deepgram/stt.py index 7d849a160..85dfc059c 100644 --- a/src/pipecat/services/deepgram/stt.py +++ b/src/pipecat/services/deepgram/stt.py @@ -554,7 +554,15 @@ class DeepgramSTTService(STTService): value = getattr(s, f.name) if not is_given(value) or value is None: continue - kwargs[f.name] = str(value).lower() if isinstance(value, bool) else str(value) + # Lists (e.g. keyterm, keywords, search, redact, replace) must be + # passed through as-is so the SDK's encode_query produces repeated + # query params (keyterm=a&keyterm=b) instead of a stringified list. + if isinstance(value, list): + kwargs[f.name] = value + elif isinstance(value, bool): + kwargs[f.name] = str(value).lower() + else: + kwargs[f.name] = str(value) # model and language if is_given(s.model) and s.model is not None: @@ -580,7 +588,12 @@ class DeepgramSTTService(STTService): # Any remaining values in extra (that didn't map to declared fields) for key, value in s.extra.items(): if value is not None: - kwargs[key] = str(value).lower() if isinstance(value, bool) else str(value) + if isinstance(value, list): + kwargs[key] = value + elif isinstance(value, bool): + kwargs[key] = str(value).lower() + else: + kwargs[key] = str(value) if self._addons: for key, value in self._addons.items(): From 0378fb0d9194e0a6206671d283a965e899f2258e Mon Sep 17 00:00:00 2001 From: joachimchauvet Date: Wed, 18 Mar 2026 16:04:42 +0200 Subject: [PATCH 1003/1060] fix(livekit): suppress InvalidState log spam from audio mixer during interruptions --- src/pipecat/transports/livekit/transport.py | 11 ++++++++++- 1 file changed, 10 insertions(+), 1 deletion(-) diff --git a/src/pipecat/transports/livekit/transport.py b/src/pipecat/transports/livekit/transport.py index 3fb3d1694..18163cf8e 100644 --- a/src/pipecat/transports/livekit/transport.py +++ b/src/pipecat/transports/livekit/transport.py @@ -388,7 +388,16 @@ class LiveKitTransportClient: await self._audio_source.capture_frame(audio_frame) return True except Exception as e: - logger.error(f"Error publishing audio: {e}") + # When using an audio mixer, the base output transport's + # with_mixer() generator continuously yields frames (mixed with + # background audio) even when no TTS audio is queued. During + # interruptions, the audio task is cancelled and recreated, but + # there is a brief window where the native LiveKit AudioSource + # rejects capture_frame() with an InvalidState error. This is a + # transient condition — the mixer will produce a new frame within + # milliseconds, so we silently drop these frames. + if "InvalidState" not in str(e): + logger.error(f"Error publishing audio: {e}") return False def get_participants(self) -> List[str]: From 45186cc4ce0024c414216d79ce8f5681f1a5f7b5 Mon Sep 17 00:00:00 2001 From: Paul Kompfner Date: Wed, 18 Mar 2026 11:45:23 -0400 Subject: [PATCH 1004/1060] feat: add OpenAI Responses API LLM service MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit Add OpenAIResponsesLLMService using the Responses API, with a dedicated adapter that converts LLMContext messages to Responses API input items (system→developer, tool_calls→function_call, tool→function_call_output, multimodal content conversion, and tools schema flattening). - New adapter: open_ai_responses_adapter.py - New service: openai/responses/llm.py - Examples: 07-interruptible and 14-function-calling variants - 19 unit tests for adapter conversion logic - Eval entries for both examples --- .../07-interruptible-openai-responses.py | 125 ++++++ .../14-function-calling-openai-responses.py | 175 ++++++++ scripts/evals/run-release-evals.py | 3 + .../services/open_ai_responses_adapter.py | 240 +++++++++++ src/pipecat/services/openai/__init__.py | 1 + .../services/openai/responses/__init__.py | 5 + src/pipecat/services/openai/responses/llm.py | 393 ++++++++++++++++++ tests/test_openai_responses_adapter.py | 349 ++++++++++++++++ 8 files changed, 1291 insertions(+) create mode 100644 examples/foundational/07-interruptible-openai-responses.py create mode 100644 examples/foundational/14-function-calling-openai-responses.py create mode 100644 src/pipecat/adapters/services/open_ai_responses_adapter.py create mode 100644 src/pipecat/services/openai/responses/__init__.py create mode 100644 src/pipecat/services/openai/responses/llm.py create mode 100644 tests/test_openai_responses_adapter.py diff --git a/examples/foundational/07-interruptible-openai-responses.py b/examples/foundational/07-interruptible-openai-responses.py new file mode 100644 index 000000000..baae3754a --- /dev/null +++ b/examples/foundational/07-interruptible-openai-responses.py @@ -0,0 +1,125 @@ +# +# Copyright (c) 2024-2026, Daily +# +# SPDX-License-Identifier: BSD 2-Clause License +# + +import os + +from dotenv import load_dotenv +from loguru import logger + +from pipecat.audio.vad.silero import SileroVADAnalyzer +from pipecat.frames.frames import LLMRunFrame +from pipecat.pipeline.pipeline import Pipeline +from pipecat.pipeline.runner import PipelineRunner +from pipecat.pipeline.task import PipelineParams, PipelineTask +from pipecat.processors.aggregators.llm_context import LLMContext +from pipecat.processors.aggregators.llm_response_universal import ( + LLMContextAggregatorPair, + LLMUserAggregatorParams, +) +from pipecat.runner.types import RunnerArguments +from pipecat.runner.utils import create_transport +from pipecat.services.cartesia.tts import CartesiaTTSService +from pipecat.services.deepgram.stt import DeepgramSTTService +from pipecat.services.openai.responses.llm import OpenAIResponsesLLMService +from pipecat.transports.base_transport import BaseTransport, TransportParams +from pipecat.transports.daily.transport import DailyParams +from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams + +load_dotenv(override=True) + +# We use lambdas to defer transport parameter creation until the transport +# type is selected at runtime. +transport_params = { + "daily": lambda: DailyParams( + audio_in_enabled=True, + audio_out_enabled=True, + ), + "twilio": lambda: FastAPIWebsocketParams( + audio_in_enabled=True, + audio_out_enabled=True, + ), + "webrtc": lambda: TransportParams( + audio_in_enabled=True, + audio_out_enabled=True, + ), +} + + +async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): + logger.info(f"Starting bot") + + stt = DeepgramSTTService(api_key=os.getenv("DEEPGRAM_API_KEY")) + + tts = CartesiaTTSService( + api_key=os.getenv("CARTESIA_API_KEY"), + settings=CartesiaTTSService.Settings( + voice="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady + ), + ) + + llm = OpenAIResponsesLLMService( + api_key=os.getenv("OPENAI_API_KEY"), + settings=OpenAIResponsesLLMService.Settings( + system_instruction="You are a helpful assistant in a voice conversation. Your responses will be spoken aloud, so avoid emojis, bullet points, or other formatting that can't be spoken. Respond to what the user said in a creative, helpful, and brief way.", + ), + ) + + context = LLMContext() + user_aggregator, assistant_aggregator = LLMContextAggregatorPair( + context, + user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()), + ) + + pipeline = Pipeline( + [ + transport.input(), # Transport user input + stt, + user_aggregator, # User responses + llm, # LLM + tts, # TTS + transport.output(), # Transport bot output + assistant_aggregator, # Assistant spoken responses + ] + ) + + task = PipelineTask( + pipeline, + params=PipelineParams( + enable_metrics=True, + enable_usage_metrics=True, + ), + idle_timeout_secs=runner_args.pipeline_idle_timeout_secs, + ) + + @transport.event_handler("on_client_connected") + async def on_client_connected(transport, client): + logger.info(f"Client connected") + # Kick off the conversation. + context.add_message( + {"role": "developer", "content": "Please introduce yourself to the user."} + ) + await task.queue_frames([LLMRunFrame()]) + + @transport.event_handler("on_client_disconnected") + async def on_client_disconnected(transport, client): + logger.info(f"Client disconnected") + await task.cancel() + + runner = PipelineRunner(handle_sigint=runner_args.handle_sigint) + + await runner.run(task) + + +async def bot(runner_args: RunnerArguments): + """Main bot entry point compatible with Pipecat Cloud.""" + transport = await create_transport(runner_args, transport_params) + await run_bot(transport, runner_args) + + +if __name__ == "__main__": + from pipecat.runner.run import main + + main() diff --git a/examples/foundational/14-function-calling-openai-responses.py b/examples/foundational/14-function-calling-openai-responses.py new file mode 100644 index 000000000..58cac774a --- /dev/null +++ b/examples/foundational/14-function-calling-openai-responses.py @@ -0,0 +1,175 @@ +# +# Copyright (c) 2024-2026, Daily +# +# SPDX-License-Identifier: BSD 2-Clause License +# + +import os + +from dotenv import load_dotenv +from loguru import logger + +from pipecat.adapters.schemas.function_schema import FunctionSchema +from pipecat.adapters.schemas.tools_schema import ToolsSchema +from pipecat.audio.vad.silero import SileroVADAnalyzer +from pipecat.frames.frames import LLMRunFrame, TTSSpeakFrame +from pipecat.pipeline.pipeline import Pipeline +from pipecat.pipeline.runner import PipelineRunner +from pipecat.pipeline.task import PipelineParams, PipelineTask +from pipecat.processors.aggregators.llm_context import LLMContext +from pipecat.processors.aggregators.llm_response_universal import ( + LLMContextAggregatorPair, + LLMUserAggregatorParams, +) +from pipecat.runner.types import RunnerArguments +from pipecat.runner.utils import create_transport +from pipecat.services.cartesia.tts import CartesiaTTSService +from pipecat.services.deepgram.stt import DeepgramSTTService +from pipecat.services.llm_service import FunctionCallParams +from pipecat.services.openai.responses.llm import OpenAIResponsesLLMService +from pipecat.transports.base_transport import BaseTransport, TransportParams +from pipecat.transports.daily.transport import DailyParams +from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams + +load_dotenv(override=True) + + +async def fetch_weather_from_api(params: FunctionCallParams): + await params.result_callback({"conditions": "nice", "temperature": "75"}) + + +async def fetch_restaurant_recommendation(params: FunctionCallParams): + await params.result_callback({"name": "The Golden Dragon"}) + + +# We use lambdas to defer transport parameter creation until the transport +# type is selected at runtime. +transport_params = { + "daily": lambda: DailyParams( + audio_in_enabled=True, + audio_out_enabled=True, + ), + "twilio": lambda: FastAPIWebsocketParams( + audio_in_enabled=True, + audio_out_enabled=True, + ), + "webrtc": lambda: TransportParams( + audio_in_enabled=True, + audio_out_enabled=True, + ), +} + + +async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): + logger.info(f"Starting bot") + + stt = DeepgramSTTService(api_key=os.getenv("DEEPGRAM_API_KEY")) + + tts = CartesiaTTSService( + api_key=os.getenv("CARTESIA_API_KEY"), + settings=CartesiaTTSService.Settings( + voice="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady + ), + ) + + llm = OpenAIResponsesLLMService( + api_key=os.getenv("OPENAI_API_KEY"), + settings=OpenAIResponsesLLMService.Settings( + system_instruction="You are a helpful assistant in a voice conversation. Your responses will be spoken aloud, so avoid emojis, bullet points, or other formatting that can't be spoken. Respond to what the user said in a creative, helpful, and brief way.", + ), + ) + + # You can also register a function_name of None to get all functions + # sent to the same callback with an additional function_name parameter. + llm.register_function("get_current_weather", fetch_weather_from_api) + llm.register_function("get_restaurant_recommendation", fetch_restaurant_recommendation) + + @llm.event_handler("on_function_calls_started") + async def on_function_calls_started(service, function_calls): + await tts.queue_frame(TTSSpeakFrame("Let me check on that.")) + + weather_function = FunctionSchema( + name="get_current_weather", + description="Get the current weather", + properties={ + "location": { + "type": "string", + "description": "The city and state, e.g. San Francisco, CA", + }, + "format": { + "type": "string", + "enum": ["celsius", "fahrenheit"], + "description": "The temperature unit to use. Infer this from the user's location.", + }, + }, + required=["location", "format"], + ) + restaurant_function = FunctionSchema( + name="get_restaurant_recommendation", + description="Get a restaurant recommendation", + properties={ + "location": { + "type": "string", + "description": "The city and state, e.g. San Francisco, CA", + }, + }, + required=["location"], + ) + tools = ToolsSchema(standard_tools=[weather_function, restaurant_function]) + + context = LLMContext(tools=tools) + user_aggregator, assistant_aggregator = LLMContextAggregatorPair( + context, + user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()), + ) + + pipeline = Pipeline( + [ + transport.input(), + stt, + user_aggregator, + llm, + tts, + transport.output(), + assistant_aggregator, + ] + ) + + task = PipelineTask( + pipeline, + params=PipelineParams( + enable_metrics=True, + enable_usage_metrics=True, + ), + idle_timeout_secs=runner_args.pipeline_idle_timeout_secs, + ) + + @transport.event_handler("on_client_connected") + async def on_client_connected(transport, client): + logger.info(f"Client connected") + # Kick off the conversation. + context.add_message( + {"role": "developer", "content": "Please introduce yourself to the user."} + ) + await task.queue_frames([LLMRunFrame()]) + + @transport.event_handler("on_client_disconnected") + async def on_client_disconnected(transport, client): + logger.info(f"Client disconnected") + await task.cancel() + + runner = PipelineRunner(handle_sigint=runner_args.handle_sigint) + + await runner.run(task) + + +async def bot(runner_args: RunnerArguments): + """Main bot entry point compatible with Pipecat Cloud.""" + transport = await create_transport(runner_args, transport_params) + await run_bot(transport, runner_args) + + +if __name__ == "__main__": + from pipecat.runner.run import main + + main() diff --git a/scripts/evals/run-release-evals.py b/scripts/evals/run-release-evals.py index 625f33564..9671703ba 100644 --- a/scripts/evals/run-release-evals.py +++ b/scripts/evals/run-release-evals.py @@ -147,6 +147,7 @@ TESTS_07 = [ ("07zi-interruptible-piper.py", EVAL_SIMPLE_MATH), ("07zj-interruptible-kokoro.py", EVAL_SIMPLE_MATH), ("07zk-interruptible-resembleai.py", EVAL_SIMPLE_MATH), + ("07-interruptible-openai-responses.py", EVAL_SIMPLE_MATH), # Needs a local XTTS docker instance running. # ("07i-interruptible-xtts.py", EVAL_SIMPLE_MATH), ] @@ -184,6 +185,8 @@ TESTS_14 = [ ("14v-function-calling-openai.py", EVAL_WEATHER), ("14w-function-calling-mistral.py", EVAL_WEATHER), ("14x-function-calling-openpipe.py", EVAL_WEATHER), + ("14-function-calling-openai-responses.py", EVAL_WEATHER), + ("14-function-calling-openai-responses.py", EVAL_WEATHER_AND_RESTAURANT), # Video ("14d-function-calling-anthropic-video.py", EVAL_VISION_CAMERA), ("14d-function-calling-aws-video.py", EVAL_VISION_CAMERA), diff --git a/src/pipecat/adapters/services/open_ai_responses_adapter.py b/src/pipecat/adapters/services/open_ai_responses_adapter.py new file mode 100644 index 000000000..f55ba6435 --- /dev/null +++ b/src/pipecat/adapters/services/open_ai_responses_adapter.py @@ -0,0 +1,240 @@ +# +# Copyright (c) 2024-2026, Daily +# +# SPDX-License-Identifier: BSD 2-Clause License +# + +"""OpenAI Responses API adapter for Pipecat.""" + +import copy +from typing import Any, Dict, List, Optional, TypedDict + +from loguru import logger +from openai._types import NotGiven as OpenAINotGiven +from openai.types.responses import FunctionToolParam, ResponseInputItemParam + +from pipecat.adapters.base_llm_adapter import BaseLLMAdapter +from pipecat.adapters.schemas.tools_schema import ToolsSchema +from pipecat.processors.aggregators.llm_context import ( + LLMContext, + LLMContextMessage, + LLMSpecificMessage, + NotGiven, +) + + +class OpenAIResponsesLLMInvocationParams(TypedDict, total=False): + """Context-based parameters for invoking OpenAI Responses API.""" + + input: List[ResponseInputItemParam] + tools: List[FunctionToolParam] | OpenAINotGiven + instructions: str + + +class OpenAIResponsesLLMAdapter(BaseLLMAdapter[OpenAIResponsesLLMInvocationParams]): + """OpenAI Responses API adapter for Pipecat. + + Handles: + + - Converting LLMContext messages to Responses API input items + - Converting Pipecat's standardized tools schema to Responses API function tool format + - Extracting and sanitizing messages from the LLM context for logging + """ + + def __init__(self): + """Initialize the adapter.""" + super().__init__() + self._warned_system_instruction = False + + @property + def id_for_llm_specific_messages(self) -> str: + """Get the identifier used in LLMSpecificMessage instances.""" + return "openai_responses" + + def get_llm_invocation_params( + self, + context: LLMContext, + *, + system_instruction: Optional[str] = None, + ) -> OpenAIResponsesLLMInvocationParams: + """Get Responses API invocation parameters from a universal LLM context. + + Args: + context: The LLM context containing messages, tools, etc. + system_instruction: Optional system instruction from service settings. + + Returns: + Dictionary of parameters for the Responses API. + """ + messages = self.get_messages(context) + input_items = self._convert_messages_to_input(messages) + + params: OpenAIResponsesLLMInvocationParams = { + "input": input_items, + "tools": self.from_standard_tools(context.tools), + } + + if system_instruction: + # Compatibility: The Responses API requires at least one input + # message when instructions are provided. Contexts that worked with + # OpenAILLMService (system_instruction + empty messages) need the + # instructions converted to an initial developer message. + if not input_items: + params["input"] = [{"role": "developer", "content": system_instruction}] + else: + params["instructions"] = system_instruction + + return params + + def to_provider_tools_format(self, tools_schema: ToolsSchema) -> List[FunctionToolParam]: + """Convert function schemas to Responses API function tool format. + + Args: + tools_schema: The Pipecat tools schema to convert. + + Returns: + List of Responses API function tool definitions. + """ + functions_schema = tools_schema.standard_tools + result = [] + for func in functions_schema: + d = func.to_default_dict() + tool: FunctionToolParam = { + "type": "function", + "name": d["name"], + "parameters": d.get("parameters", {}), + "strict": d.get("strict", None), + } + if "description" in d: + tool["description"] = d["description"] + result.append(tool) + return result + + def get_messages_for_logging(self, context: LLMContext) -> List[Dict[str, Any]]: + """Get messages from context in a format ready for logging. + + Removes or truncates sensitive data like image content for safe logging. + + Args: + context: The LLM context containing messages. + + Returns: + List of messages in a format ready for logging. + """ + msgs = [] + for message in self.get_messages(context): + msg = copy.deepcopy(message) + if "content" in msg: + if isinstance(msg["content"], list): + for item in msg["content"]: + if item.get("type") == "image_url": + if item["image_url"]["url"].startswith("data:image/"): + item["image_url"]["url"] = "data:image/..." + if item.get("type") == "input_audio": + item["input_audio"]["data"] = "..." + msgs.append(msg) + return msgs + + def _convert_messages_to_input( + self, messages: List[LLMContextMessage] + ) -> List[ResponseInputItemParam]: + """Convert LLMContext messages to Responses API input items. + + Args: + messages: Messages from the LLMContext. + + Returns: + List of Responses API input items. + """ + result: List[ResponseInputItemParam] = [] + is_first = True + + for message in messages: + if isinstance(message, LLMSpecificMessage): + result.append(message.message) + is_first = False + continue + + role = message.get("role") + + if role == "system": + if is_first and not self._warned_system_instruction: + logger.warning( + "System messages in LLMContext are converted to 'developer' role for the " + "Responses API. Consider using settings.system_instruction instead, which " + "maps to the 'instructions' parameter." + ) + self._warned_system_instruction = True + content = message.get("content", "") + if isinstance(content, list): + content = self._convert_multimodal_content(content) + result.append({"role": "developer", "content": content}) + + elif role == "user": + content = message.get("content", "") + if isinstance(content, list): + content = self._convert_multimodal_content(content) + result.append({"role": "user", "content": content}) + + elif role == "assistant": + tool_calls = message.get("tool_calls") + if tool_calls: + for tc in tool_calls: + func = tc.get("function", {}) + result.append( + { + "type": "function_call", + "call_id": tc.get("id", ""), + "name": func.get("name", ""), + "arguments": func.get("arguments", ""), + } + ) + else: + content = message.get("content", "") + if isinstance(content, list): + content = self._convert_multimodal_content(content) + result.append({"role": "assistant", "content": content}) + + elif role == "tool": + content = message.get("content", "") + if not isinstance(content, str): + content = str(content) + result.append( + { + "type": "function_call_output", + "call_id": message.get("tool_call_id", ""), + "output": content, + } + ) + + is_first = False + + return result + + def _convert_multimodal_content(self, content: list) -> list: + """Convert multimodal content parts to Responses API format. + + Args: + content: List of content parts from the LLMContext message. + + Returns: + List of content parts in Responses API format. + """ + result = [] + for part in content: + part_type = part.get("type") + if part_type == "text": + result.append({"type": "input_text", "text": part.get("text", "")}) + elif part_type == "image_url": + image_url_obj = part.get("image_url", {}) + result.append( + { + "type": "input_image", + "image_url": image_url_obj.get("url", ""), + "detail": image_url_obj.get("detail", "auto"), + } + ) + else: + # Pass through unknown types as-is + result.append(part) + return result diff --git a/src/pipecat/services/openai/__init__.py b/src/pipecat/services/openai/__init__.py index e182264b1..3caa3c3cb 100644 --- a/src/pipecat/services/openai/__init__.py +++ b/src/pipecat/services/openai/__init__.py @@ -11,6 +11,7 @@ from pipecat.services import DeprecatedModuleProxy from .image import * from .llm import * from .realtime import * +from .responses.llm import * from .stt import * from .tts import * diff --git a/src/pipecat/services/openai/responses/__init__.py b/src/pipecat/services/openai/responses/__init__.py new file mode 100644 index 000000000..c4d243b97 --- /dev/null +++ b/src/pipecat/services/openai/responses/__init__.py @@ -0,0 +1,5 @@ +# +# Copyright (c) 2024-2026, Daily +# +# SPDX-License-Identifier: BSD 2-Clause License +# diff --git a/src/pipecat/services/openai/responses/llm.py b/src/pipecat/services/openai/responses/llm.py new file mode 100644 index 000000000..e72b8acdb --- /dev/null +++ b/src/pipecat/services/openai/responses/llm.py @@ -0,0 +1,393 @@ +# +# Copyright (c) 2024-2026, Daily +# +# SPDX-License-Identifier: BSD 2-Clause License +# + +"""OpenAI Responses API LLM service implementation.""" + +import json +from contextlib import asynccontextmanager +from dataclasses import dataclass, field +from typing import Any, Dict, List, Mapping, Optional + +import httpx +from loguru import logger +from openai import NOT_GIVEN, AsyncOpenAI, AsyncStream, DefaultAsyncHttpxClient +from openai.types.responses import ( + ResponseCompletedEvent, + ResponseFunctionCallArgumentsDeltaEvent, + ResponseFunctionCallArgumentsDoneEvent, + ResponseOutputItemAddedEvent, + ResponseOutputItemDoneEvent, + ResponseStreamEvent, + ResponseTextDeltaEvent, +) + +from pipecat.adapters.services.open_ai_responses_adapter import ( + OpenAIResponsesLLMAdapter, + OpenAIResponsesLLMInvocationParams, +) +from pipecat.frames.frames import ( + Frame, + LLMContextFrame, + LLMFullResponseEndFrame, + LLMFullResponseStartFrame, +) +from pipecat.metrics.metrics import LLMTokenUsage +from pipecat.processors.aggregators.llm_context import LLMContext +from pipecat.processors.frame_processor import FrameDirection +from pipecat.services.llm_service import FunctionCallFromLLM, LLMService +from pipecat.services.settings import NOT_GIVEN as _NOT_GIVEN +from pipecat.services.settings import LLMSettings, _NotGiven +from pipecat.utils.tracing.service_decorators import traced_llm + + +@dataclass +class OpenAIResponsesLLMSettings(LLMSettings): + """Settings for OpenAIResponsesLLMService. + + Parameters: + max_completion_tokens: Maximum completion tokens to generate. + """ + + max_completion_tokens: int | _NotGiven = field(default_factory=lambda: _NOT_GIVEN) + + +class OpenAIResponsesLLMService(LLMService): + """OpenAI Responses API LLM service. + + This service works with the universal LLMContext and LLMContextAggregatorPair. + + Example:: + + llm = OpenAIResponsesLLMService( + api_key=os.getenv("OPENAI_API_KEY"), + settings=OpenAIResponsesLLMService.Settings( + model="gpt-4.1", + system_instruction="You are a helpful assistant.", + ), + ) + """ + + Settings = OpenAIResponsesLLMSettings + _settings: Settings + + adapter_class = OpenAIResponsesLLMAdapter + + def __init__( + self, + *, + model: Optional[str] = None, + api_key=None, + base_url=None, + organization=None, + project=None, + default_headers: Optional[Mapping[str, str]] = None, + settings: Optional[Settings] = None, + **kwargs, + ): + """Initialize the OpenAI Responses API LLM service. + + Args: + model: The OpenAI model name to use. Defaults to "gpt-4.1". + api_key: OpenAI API key. If None, uses environment variable. + base_url: Custom base URL for OpenAI API. If None, uses default. + organization: OpenAI organization ID. + project: OpenAI project ID. + default_headers: Additional HTTP headers to include in requests. + settings: Runtime-updatable settings. When provided alongside + other parameters, ``settings`` values take precedence. + **kwargs: Additional arguments passed to the parent LLMService. + """ + default_settings = self.Settings( + model="gpt-4.1", + system_instruction=None, + frequency_penalty=None, + presence_penalty=None, + seed=None, + temperature=NOT_GIVEN, + top_p=NOT_GIVEN, + top_k=None, + max_tokens=None, + max_completion_tokens=NOT_GIVEN, + filter_incomplete_user_turns=False, + user_turn_completion_config=None, + extra={}, + ) + + if model is not None: + default_settings.model = model + + if settings is not None: + default_settings.apply_update(settings) + + super().__init__( + settings=default_settings, + **kwargs, + ) + + self._client = self._create_client( + api_key=api_key, + base_url=base_url, + organization=organization, + project=project, + default_headers=default_headers, + ) + + if self._settings.system_instruction: + logger.debug(f"{self}: Using system instruction: {self._settings.system_instruction}") + + def _create_client( + self, + api_key=None, + base_url=None, + organization=None, + project=None, + default_headers=None, + ) -> AsyncOpenAI: + """Create an AsyncOpenAI client instance. + + Args: + api_key: OpenAI API key. + base_url: Custom base URL for the API. + organization: OpenAI organization ID. + project: OpenAI project ID. + default_headers: Additional HTTP headers. + + Returns: + Configured AsyncOpenAI client instance. + """ + return AsyncOpenAI( + api_key=api_key, + base_url=base_url, + organization=organization, + project=project, + http_client=DefaultAsyncHttpxClient( + limits=httpx.Limits( + max_keepalive_connections=100, max_connections=1000, keepalive_expiry=None + ) + ), + default_headers=default_headers, + ) + + def can_generate_metrics(self) -> bool: + """Check if this service can generate processing metrics.""" + return True + + async def process_frame(self, frame: Frame, direction: FrameDirection): + """Process frames for LLM completion requests. + + Args: + frame: The frame to process. + direction: The direction of frame processing. + """ + await super().process_frame(frame, direction) + + context = None + if isinstance(frame, LLMContextFrame): + context = frame.context + else: + await self.push_frame(frame, direction) + + if context: + try: + await self.push_frame(LLMFullResponseStartFrame()) + await self.start_processing_metrics() + await self._process_context(context) + except httpx.TimeoutException as e: + await self._call_event_handler("on_completion_timeout") + await self.push_error(error_msg="LLM completion timeout", exception=e) + except Exception as e: + await self.push_error(error_msg=f"Error during completion: {e}", exception=e) + finally: + await self.stop_processing_metrics() + await self.push_frame(LLMFullResponseEndFrame()) + + @traced_llm + async def _process_context(self, context: LLMContext): + adapter = self.get_llm_adapter() + logger.debug( + f"{self}: Generating response from universal context " + f"{adapter.get_messages_for_logging(context)}" + ) + + invocation_params: OpenAIResponsesLLMInvocationParams = adapter.get_llm_invocation_params( + context, system_instruction=self._settings.system_instruction + ) + + params = self._build_response_params(invocation_params) + + await self.start_ttfb_metrics() + + stream: AsyncStream[ResponseStreamEvent] = await self._client.responses.create(**params) + + # Track function calls across stream events + function_calls: Dict[str, Dict[str, str]] = {} # item_id -> {name, call_id, arguments} + current_arguments: Dict[str, str] = {} # item_id -> accumulated arguments + + @asynccontextmanager + async def _closing(stream): + chunk_iter = stream.__aiter__() + try: + yield chunk_iter + finally: + if hasattr(chunk_iter, "aclose"): + await chunk_iter.aclose() + if hasattr(stream, "close"): + await stream.close() + elif hasattr(stream, "aclose"): + await stream.aclose() + + async with _closing(stream) as event_iter: + async for event in event_iter: + if isinstance(event, ResponseTextDeltaEvent): + await self.stop_ttfb_metrics() + await self._push_llm_text(event.delta) + + elif isinstance(event, ResponseOutputItemAddedEvent): + await self.stop_ttfb_metrics() + item = event.item + if getattr(item, "type", None) == "function_call": + item_id = getattr(item, "id", "") or "" + function_calls[item_id] = { + "name": getattr(item, "name", ""), + "call_id": getattr(item, "call_id", ""), + "arguments": "", + } + current_arguments[item_id] = "" + + elif isinstance(event, ResponseFunctionCallArgumentsDeltaEvent): + item_id = event.item_id + if item_id in current_arguments: + current_arguments[item_id] += event.delta + + elif isinstance(event, ResponseFunctionCallArgumentsDoneEvent): + item_id = event.item_id + if item_id in function_calls: + function_calls[item_id]["arguments"] = event.arguments + + elif isinstance(event, ResponseOutputItemDoneEvent): + item = event.item + if getattr(item, "type", None) == "function_call": + item_id = getattr(item, "id", "") or "" + if item_id in function_calls: + function_calls[item_id]["name"] = getattr(item, "name", "") + function_calls[item_id]["call_id"] = getattr(item, "call_id", "") + function_calls[item_id]["arguments"] = getattr(item, "arguments", "") + + elif isinstance(event, ResponseCompletedEvent): + response = event.response + usage = getattr(response, "usage", None) + if usage: + tokens = LLMTokenUsage( + prompt_tokens=getattr(usage, "input_tokens", 0), + completion_tokens=getattr(usage, "output_tokens", 0), + total_tokens=getattr(usage, "total_tokens", 0), + ) + await self.start_llm_usage_metrics(tokens) + + model = getattr(response, "model", None) + if model: + self._full_model_name = model + + # Process any function calls + if function_calls: + fc_list: List[FunctionCallFromLLM] = [] + for item_id, fc in function_calls.items(): + try: + arguments = json.loads(fc["arguments"]) if fc["arguments"] else {} + except json.JSONDecodeError: + logger.warning( + f"{self}: Failed to parse function call arguments: {fc['arguments']}" + ) + arguments = {} + fc_list.append( + FunctionCallFromLLM( + context=context, + tool_call_id=fc["call_id"], + function_name=fc["name"], + arguments=arguments, + ) + ) + await self.run_function_calls(fc_list) + + def _build_response_params(self, invocation_params: OpenAIResponsesLLMInvocationParams) -> dict: + """Build parameters for the responses.create() call. + + Args: + invocation_params: Parameters derived from the LLM context. + + Returns: + Dictionary of parameters for the Responses API call. + """ + params: Dict[str, Any] = { + "model": self._settings.model, + "stream": True, + "input": invocation_params["input"], + } + + # instructions (set by the adapter when input is non-empty) + if "instructions" in invocation_params: + params["instructions"] = invocation_params["instructions"] + + # Optional parameters - only include if given + if isinstance(self._settings.temperature, (int, float)): + params["temperature"] = self._settings.temperature + + if isinstance(self._settings.top_p, (int, float)): + params["top_p"] = self._settings.top_p + + if isinstance(self._settings.max_completion_tokens, int): + params["max_output_tokens"] = self._settings.max_completion_tokens + + # Tools + tools = invocation_params.get("tools") + if tools is not None and not isinstance(tools, type(NOT_GIVEN)): + params["tools"] = tools + + # Extra settings + params.update(self._settings.extra) + + return params + + async def run_inference( + self, + context: LLMContext, + max_tokens: Optional[int] = None, + system_instruction: Optional[str] = None, + ) -> Optional[str]: + """Run a one-shot, out-of-band inference with the given LLM context. + + Args: + context: The LLM context containing conversation history. + max_tokens: Optional maximum number of tokens to generate. + system_instruction: Optional system instruction for this inference. + + Returns: + The LLM's response as a string, or None if no response is generated. + """ + adapter = self.get_llm_adapter() + effective_instruction = system_instruction or self._settings.system_instruction + invocation_params = adapter.get_llm_invocation_params( + context, system_instruction=effective_instruction + ) + + params = self._build_response_params(invocation_params) + + # Override for non-streaming + params["stream"] = False + + # Override instructions if caller provided one explicitly + if system_instruction is not None: + params["instructions"] = system_instruction + + if max_tokens is not None: + params["max_output_tokens"] = max_tokens + + response = await self._client.responses.create(**params) + + return response.output_text + + +__all__ = ["OpenAIResponsesLLMService", "OpenAIResponsesLLMSettings"] diff --git a/tests/test_openai_responses_adapter.py b/tests/test_openai_responses_adapter.py new file mode 100644 index 000000000..973c05c8c --- /dev/null +++ b/tests/test_openai_responses_adapter.py @@ -0,0 +1,349 @@ +# +# Copyright (c) 2024-2026, Daily +# +# SPDX-License-Identifier: BSD 2-Clause License +# + +"""Unit tests for the OpenAI Responses API adapter. + +Tests the conversion from LLMContext messages to Responses API input items, including: + +1. Simple user/assistant text messages pass through (with correct role) +2. System role converted to developer role +3. First-message system role triggers a warning +4. Assistant messages with tool_calls produce function_call input items +5. Tool messages produce function_call_output input items +6. Mixed conversations with text + function calls convert correctly +7. Multimodal content conversion (text -> input_text, image_url -> input_image) +8. Tools schema flattening (nested function dict -> flat format) +9. Empty messages list +10. LLMSpecificMessage with llm="openai_responses" passes through +""" + +import unittest +from unittest.mock import patch + +from pipecat.adapters.schemas.function_schema import FunctionSchema +from pipecat.adapters.schemas.tools_schema import ToolsSchema +from pipecat.adapters.services.open_ai_responses_adapter import OpenAIResponsesLLMAdapter +from pipecat.processors.aggregators.llm_context import LLMContext, LLMStandardMessage + + +class TestOpenAIResponsesAdapter(unittest.TestCase): + def setUp(self): + self.adapter = OpenAIResponsesLLMAdapter() + + def test_simple_user_assistant_messages(self): + """Simple user/assistant text messages are converted correctly.""" + messages: list[LLMStandardMessage] = [ + {"role": "user", "content": "Hello"}, + {"role": "assistant", "content": "Hi there!"}, + ] + context = LLMContext(messages=messages) + params = self.adapter.get_llm_invocation_params(context) + + self.assertEqual(len(params["input"]), 2) + self.assertEqual(params["input"][0], {"role": "user", "content": "Hello"}) + self.assertEqual(params["input"][1], {"role": "assistant", "content": "Hi there!"}) + + def test_system_role_converted_to_developer(self): + """System role messages are converted to developer role.""" + messages: list[LLMStandardMessage] = [ + {"role": "system", "content": "You are helpful."}, + {"role": "user", "content": "Hello"}, + ] + context = LLMContext(messages=messages) + params = self.adapter.get_llm_invocation_params(context) + + self.assertEqual(params["input"][0]["role"], "developer") + self.assertEqual(params["input"][0]["content"], "You are helpful.") + + def test_first_system_message_triggers_warning(self): + """First system message triggers a warning about using system_instruction.""" + # Use a fresh adapter so the warning hasn't been emitted yet + adapter = OpenAIResponsesLLMAdapter() + messages: list[LLMStandardMessage] = [ + {"role": "system", "content": "You are helpful."}, + {"role": "user", "content": "Hello"}, + ] + context = LLMContext(messages=messages) + + with patch("pipecat.adapters.services.open_ai_responses_adapter.logger") as mock_logger: + adapter.get_llm_invocation_params(context) + mock_logger.warning.assert_called_once() + warning_msg = mock_logger.warning.call_args[0][0] + self.assertIn("system_instruction", warning_msg) + + def test_non_initial_system_message_no_warning(self): + """Non-initial system messages are converted without a warning.""" + messages: list[LLMStandardMessage] = [ + {"role": "user", "content": "Hello"}, + {"role": "system", "content": "New instruction"}, + ] + context = LLMContext(messages=messages) + + adapter = OpenAIResponsesLLMAdapter() + with patch("pipecat.adapters.services.open_ai_responses_adapter.logger") as mock_logger: + params = adapter.get_llm_invocation_params(context) + mock_logger.warning.assert_not_called() + + self.assertEqual(params["input"][1]["role"], "developer") + self.assertEqual(params["input"][1]["content"], "New instruction") + + def test_first_system_message_warning_fires_only_once(self): + """The first-system-message warning fires only once per adapter instance.""" + messages: list[LLMStandardMessage] = [ + {"role": "system", "content": "You are helpful."}, + {"role": "user", "content": "Hello"}, + ] + context = LLMContext(messages=messages) + + adapter = OpenAIResponsesLLMAdapter() + with patch("pipecat.adapters.services.open_ai_responses_adapter.logger") as mock_logger: + adapter.get_llm_invocation_params(context) + adapter.get_llm_invocation_params(context) + # Warning should have been emitted exactly once, not twice + mock_logger.warning.assert_called_once() + + def test_assistant_tool_calls_to_function_call(self): + """Assistant messages with tool_calls produce function_call input items.""" + messages = [ + { + "role": "assistant", + "tool_calls": [ + { + "id": "call_123", + "function": { + "name": "get_weather", + "arguments": '{"location": "SF"}', + }, + "type": "function", + } + ], + } + ] + context = LLMContext(messages=messages) + params = self.adapter.get_llm_invocation_params(context) + + self.assertEqual(len(params["input"]), 1) + fc = params["input"][0] + self.assertEqual(fc["type"], "function_call") + self.assertEqual(fc["call_id"], "call_123") + self.assertEqual(fc["name"], "get_weather") + self.assertEqual(fc["arguments"], '{"location": "SF"}') + + def test_multiple_tool_calls(self): + """Multiple tool calls in one assistant message produce multiple function_call items.""" + messages = [ + { + "role": "assistant", + "tool_calls": [ + { + "id": "call_1", + "function": {"name": "get_weather", "arguments": '{"location": "SF"}'}, + "type": "function", + }, + { + "id": "call_2", + "function": {"name": "get_restaurant", "arguments": '{"location": "SF"}'}, + "type": "function", + }, + ], + } + ] + context = LLMContext(messages=messages) + params = self.adapter.get_llm_invocation_params(context) + + self.assertEqual(len(params["input"]), 2) + self.assertEqual(params["input"][0]["name"], "get_weather") + self.assertEqual(params["input"][1]["name"], "get_restaurant") + + def test_tool_message_to_function_call_output(self): + """Tool role messages produce function_call_output input items.""" + messages = [ + { + "role": "tool", + "content": '{"temperature": "72"}', + "tool_call_id": "call_123", + } + ] + context = LLMContext(messages=messages) + params = self.adapter.get_llm_invocation_params(context) + + self.assertEqual(len(params["input"]), 1) + fco = params["input"][0] + self.assertEqual(fco["type"], "function_call_output") + self.assertEqual(fco["call_id"], "call_123") + self.assertEqual(fco["output"], '{"temperature": "72"}') + + def test_mixed_conversation(self): + """Mixed conversation with text + function calls converts correctly.""" + messages = [ + {"role": "user", "content": "What's the weather in SF?"}, + { + "role": "assistant", + "tool_calls": [ + { + "id": "call_abc", + "function": {"name": "get_weather", "arguments": '{"location": "SF"}'}, + "type": "function", + } + ], + }, + { + "role": "tool", + "content": '{"temp": "72"}', + "tool_call_id": "call_abc", + }, + {"role": "assistant", "content": "It's 72 degrees in SF."}, + ] + context = LLMContext(messages=messages) + params = self.adapter.get_llm_invocation_params(context) + + self.assertEqual(len(params["input"]), 4) + self.assertEqual(params["input"][0]["role"], "user") + self.assertEqual(params["input"][1]["type"], "function_call") + self.assertEqual(params["input"][2]["type"], "function_call_output") + self.assertEqual(params["input"][3]["role"], "assistant") + + def test_multimodal_text_conversion(self): + """Multimodal text content parts are converted to input_text.""" + messages = [ + { + "role": "user", + "content": [ + {"type": "text", "text": "What's in this image?"}, + ], + } + ] + context = LLMContext(messages=messages) + params = self.adapter.get_llm_invocation_params(context) + + content = params["input"][0]["content"] + self.assertEqual(len(content), 1) + self.assertEqual(content[0]["type"], "input_text") + self.assertEqual(content[0]["text"], "What's in this image?") + + def test_multimodal_image_conversion(self): + """Multimodal image_url content parts are converted to input_image.""" + messages = [ + { + "role": "user", + "content": [ + {"type": "text", "text": "Describe this:"}, + { + "type": "image_url", + "image_url": {"url": "data:image/jpeg;base64,abc123"}, + }, + ], + } + ] + context = LLMContext(messages=messages) + params = self.adapter.get_llm_invocation_params(context) + + content = params["input"][0]["content"] + self.assertEqual(len(content), 2) + self.assertEqual(content[0]["type"], "input_text") + self.assertEqual(content[1]["type"], "input_image") + self.assertEqual(content[1]["image_url"], "data:image/jpeg;base64,abc123") + self.assertEqual(content[1]["detail"], "auto") + + def test_multimodal_image_with_detail(self): + """Image content parts preserve the detail setting when provided.""" + messages = [ + { + "role": "user", + "content": [ + { + "type": "image_url", + "image_url": {"url": "https://example.com/img.png", "detail": "high"}, + }, + ], + } + ] + context = LLMContext(messages=messages) + params = self.adapter.get_llm_invocation_params(context) + + content = params["input"][0]["content"] + self.assertEqual(content[0]["detail"], "high") + + def test_tools_schema_flattening(self): + """Tools schema with nested function dict is flattened to Responses API format.""" + weather_fn = FunctionSchema( + name="get_weather", + description="Get the current weather", + properties={ + "location": {"type": "string", "description": "The city"}, + }, + required=["location"], + ) + tools = ToolsSchema(standard_tools=[weather_fn]) + context = LLMContext(tools=tools) + params = self.adapter.get_llm_invocation_params(context) + + tool_list = params["tools"] + self.assertEqual(len(tool_list), 1) + tool = tool_list[0] + self.assertEqual(tool["type"], "function") + self.assertEqual(tool["name"], "get_weather") + self.assertEqual(tool["description"], "Get the current weather") + self.assertIn("properties", tool["parameters"]) + + def test_empty_messages(self): + """Empty messages list produces empty input list.""" + context = LLMContext(messages=[]) + params = self.adapter.get_llm_invocation_params(context) + self.assertEqual(params["input"], []) + + def test_llm_specific_message_passthrough(self): + """LLMSpecificMessage with llm='openai_responses' passes through.""" + specific_msg = self.adapter.create_llm_specific_message( + {"type": "function_call", "call_id": "x", "name": "foo", "arguments": "{}"} + ) + messages = [ + {"role": "user", "content": "Hello"}, + specific_msg, + ] + context = LLMContext(messages=messages) + params = self.adapter.get_llm_invocation_params(context) + + self.assertEqual(len(params["input"]), 2) + self.assertEqual(params["input"][0]["role"], "user") + self.assertEqual(params["input"][1]["type"], "function_call") + + def test_id_for_llm_specific_messages(self): + """Adapter identifier is 'openai_responses'.""" + self.assertEqual(self.adapter.id_for_llm_specific_messages, "openai_responses") + + def test_system_instruction_with_messages_sets_instructions(self): + """When system_instruction is provided and input is non-empty, sets instructions.""" + messages: list[LLMStandardMessage] = [ + {"role": "user", "content": "Hello"}, + ] + context = LLMContext(messages=messages) + params = self.adapter.get_llm_invocation_params(context, system_instruction="Be helpful.") + + self.assertEqual(params["instructions"], "Be helpful.") + self.assertEqual(len(params["input"]), 1) + self.assertEqual(params["input"][0]["role"], "user") + + def test_system_instruction_with_empty_input_becomes_developer_message(self): + """When system_instruction is provided but input is empty, it becomes a developer message.""" + context = LLMContext(messages=[]) + params = self.adapter.get_llm_invocation_params(context, system_instruction="Be helpful.") + + self.assertNotIn("instructions", params) + self.assertEqual(len(params["input"]), 1) + self.assertEqual(params["input"][0]["role"], "developer") + self.assertEqual(params["input"][0]["content"], "Be helpful.") + + def test_no_system_instruction_omits_instructions(self): + """When no system_instruction is provided, instructions key is absent.""" + context = LLMContext(messages=[{"role": "user", "content": "Hi"}]) + params = self.adapter.get_llm_invocation_params(context) + + self.assertNotIn("instructions", params) + + +if __name__ == "__main__": + unittest.main() From eaccb964541d19496970557b732461a51667c706 Mon Sep 17 00:00:00 2001 From: Paul Kompfner Date: Wed, 18 Mar 2026 11:46:49 -0400 Subject: [PATCH 1005/1060] docs: add changelog for OpenAI Responses API service --- changelog/4074.added.md | 1 + 1 file changed, 1 insertion(+) create mode 100644 changelog/4074.added.md diff --git a/changelog/4074.added.md b/changelog/4074.added.md new file mode 100644 index 000000000..c27a8e3cf --- /dev/null +++ b/changelog/4074.added.md @@ -0,0 +1 @@ +- Added `OpenAIResponsesLLMService`, a new LLM service that uses the OpenAI Responses API. Supports streaming text, function calling, usage metrics, and out-of-band inference. Works with the universal `LLMContext` and `LLMContextAggregatorPair`. See `examples/foundational/07-interruptible-openai-responses.py` and `14-function-calling-openai-responses.py`. From a7167ad121f206ebb97f1ae120015d6254ab85b7 Mon Sep 17 00:00:00 2001 From: Paul Kompfner Date: Wed, 18 Mar 2026 14:09:17 -0400 Subject: [PATCH 1006/1060] test: add run_inference tests for OpenAIResponsesLLMService Tests cover basic inference, client exception propagation, system_instruction override, and max_tokens override. --- src/pipecat/services/openai/responses/llm.py | 6 +- tests/test_run_inference.py | 148 +++++++++++++++++++ 2 files changed, 151 insertions(+), 3 deletions(-) diff --git a/src/pipecat/services/openai/responses/llm.py b/src/pipecat/services/openai/responses/llm.py index e72b8acdb..e0a3e4428 100644 --- a/src/pipecat/services/openai/responses/llm.py +++ b/src/pipecat/services/openai/responses/llm.py @@ -206,13 +206,13 @@ class OpenAIResponsesLLMService(LLMService): @traced_llm async def _process_context(self, context: LLMContext): - adapter = self.get_llm_adapter() + adapter: OpenAIResponsesLLMAdapter = self.get_llm_adapter() logger.debug( f"{self}: Generating response from universal context " f"{adapter.get_messages_for_logging(context)}" ) - invocation_params: OpenAIResponsesLLMInvocationParams = adapter.get_llm_invocation_params( + invocation_params = adapter.get_llm_invocation_params( context, system_instruction=self._settings.system_instruction ) @@ -367,7 +367,7 @@ class OpenAIResponsesLLMService(LLMService): Returns: The LLM's response as a string, or None if no response is generated. """ - adapter = self.get_llm_adapter() + adapter: OpenAIResponsesLLMAdapter = self.get_llm_adapter() effective_instruction = system_instruction or self._settings.system_instruction invocation_params = adapter.get_llm_invocation_params( context, system_instruction=effective_instruction diff --git a/tests/test_run_inference.py b/tests/test_run_inference.py index 4f4021b5d..4b35aee2b 100644 --- a/tests/test_run_inference.py +++ b/tests/test_run_inference.py @@ -15,11 +15,13 @@ from pipecat.adapters.services.anthropic_adapter import AnthropicLLMInvocationPa from pipecat.adapters.services.bedrock_adapter import AWSBedrockLLMInvocationParams from pipecat.adapters.services.gemini_adapter import GeminiLLMInvocationParams from pipecat.adapters.services.open_ai_adapter import OpenAILLMInvocationParams +from pipecat.adapters.services.open_ai_responses_adapter import OpenAIResponsesLLMInvocationParams from pipecat.processors.aggregators.llm_context import LLMContext from pipecat.services.anthropic.llm import AnthropicLLMService from pipecat.services.aws.llm import AWSBedrockLLMService from pipecat.services.google.llm import GoogleLLMService from pipecat.services.openai.llm import OpenAILLMService +from pipecat.services.openai.responses.llm import OpenAIResponsesLLMService @pytest.mark.asyncio @@ -765,3 +767,149 @@ async def test_aws_bedrock_run_inference_system_instruction_none_unchanged(): assert result == "Response" call_kwargs = mock_client.converse.call_args.kwargs assert call_kwargs["system"] == [{"text": "Original system"}] + + +# --- OpenAI Responses API tests --- + + +@pytest.mark.asyncio +async def test_openai_responses_run_inference_with_llm_context(): + """Test run_inference with LLMContext returns expected response.""" + with patch.object(OpenAIResponsesLLMService, "_create_client"): + service = OpenAIResponsesLLMService( + settings=OpenAIResponsesLLMService.Settings( + model="gpt-4.1", + system_instruction="You are a helpful assistant", + temperature=0.7, + max_completion_tokens=100, + ), + ) + service._client = AsyncMock() + + # Setup mocks + mock_context = MagicMock(spec=LLMContext) + mock_adapter = MagicMock() + test_input = [ + {"role": "developer", "content": "You are a helpful assistant"}, + {"role": "user", "content": "Hello, world!"}, + ] + mock_adapter.get_llm_invocation_params.return_value = OpenAIResponsesLLMInvocationParams( + input=test_input, + tools=OPENAI_NOT_GIVEN, + instructions="You are a helpful assistant", + ) + service.get_llm_adapter = MagicMock(return_value=mock_adapter) + + # Mock response + mock_response = MagicMock() + mock_response.output_text = "Hello! How can I help you today?" + service._client.responses.create = AsyncMock(return_value=mock_response) + + # Execute + result = await service.run_inference(mock_context) + + # Verify + assert result == "Hello! How can I help you today?" + service.get_llm_adapter.assert_called_once() + mock_adapter.get_llm_invocation_params.assert_called_once_with( + mock_context, system_instruction="You are a helpful assistant" + ) + service._client.responses.create.assert_called_once_with( + model="gpt-4.1", + stream=False, + input=test_input, + instructions="You are a helpful assistant", + temperature=0.7, + max_output_tokens=100, + ) + + +@pytest.mark.asyncio +async def test_openai_responses_run_inference_client_exception(): + """Test that exceptions from the client are propagated.""" + with patch.object(OpenAIResponsesLLMService, "_create_client"): + service = OpenAIResponsesLLMService() + service._client = AsyncMock() + + mock_context = MagicMock(spec=LLMContext) + mock_adapter = MagicMock() + mock_adapter.get_llm_invocation_params.return_value = OpenAIResponsesLLMInvocationParams( + input=[], tools=OPENAI_NOT_GIVEN + ) + service.get_llm_adapter = MagicMock(return_value=mock_adapter) + service._client.responses.create = AsyncMock(side_effect=Exception("API Error")) + + with pytest.raises(Exception, match="API Error"): + await service.run_inference(mock_context) + + +@pytest.mark.asyncio +async def test_openai_responses_run_inference_system_instruction_overrides(): + """Test that system_instruction parameter overrides the settings instruction.""" + with patch.object(OpenAIResponsesLLMService, "_create_client"): + service = OpenAIResponsesLLMService( + settings=OpenAIResponsesLLMService.Settings( + model="gpt-4.1", + system_instruction="Original instruction", + ), + ) + service._client = AsyncMock() + + mock_context = MagicMock(spec=LLMContext) + mock_adapter = MagicMock() + test_input = [{"role": "user", "content": "Hello"}] + mock_adapter.get_llm_invocation_params.return_value = OpenAIResponsesLLMInvocationParams( + input=test_input, + tools=OPENAI_NOT_GIVEN, + instructions="New system instruction", + ) + service.get_llm_adapter = MagicMock(return_value=mock_adapter) + + mock_response = MagicMock() + mock_response.output_text = "Response" + service._client.responses.create = AsyncMock(return_value=mock_response) + + result = await service.run_inference( + mock_context, system_instruction="New system instruction" + ) + + assert result == "Response" + # The adapter should have been called with the override instruction + mock_adapter.get_llm_invocation_params.assert_called_once_with( + mock_context, system_instruction="New system instruction" + ) + # The final API call should have the override instruction + call_kwargs = service._client.responses.create.call_args.kwargs + assert call_kwargs["instructions"] == "New system instruction" + + +@pytest.mark.asyncio +async def test_openai_responses_run_inference_max_tokens_override(): + """Test that max_tokens parameter overrides max_output_tokens.""" + with patch.object(OpenAIResponsesLLMService, "_create_client"): + service = OpenAIResponsesLLMService( + settings=OpenAIResponsesLLMService.Settings( + model="gpt-4.1", + max_completion_tokens=500, + ), + ) + service._client = AsyncMock() + + mock_context = MagicMock(spec=LLMContext) + mock_adapter = MagicMock() + test_input = [{"role": "user", "content": "Summarize this"}] + mock_adapter.get_llm_invocation_params.return_value = OpenAIResponsesLLMInvocationParams( + input=test_input, tools=OPENAI_NOT_GIVEN + ) + service.get_llm_adapter = MagicMock(return_value=mock_adapter) + + mock_response = MagicMock() + mock_response.output_text = "Summary" + service._client.responses.create = AsyncMock(return_value=mock_response) + + result = await service.run_inference(mock_context, max_tokens=200) + + assert result == "Summary" + call_kwargs = service._client.responses.create.call_args.kwargs + # max_tokens override should take precedence + assert call_kwargs["max_output_tokens"] == 200 From c4f21ef76ba9d15b6fae045f6870cf1d789b6b2a Mon Sep 17 00:00:00 2001 From: Paul Kompfner Date: Wed, 18 Mar 2026 14:17:21 -0400 Subject: [PATCH 1007/1060] test: add run_inference tests for OpenAIResponsesLLMService Uses real LLMContext and adapter (only HTTP client is mocked) to test basic inference, client exception propagation, system_instruction override, empty context fallback, and max_tokens override. --- tests/test_run_inference.py | 108 ++++++++++++++++-------------------- 1 file changed, 48 insertions(+), 60 deletions(-) diff --git a/tests/test_run_inference.py b/tests/test_run_inference.py index 4b35aee2b..e01d7b36d 100644 --- a/tests/test_run_inference.py +++ b/tests/test_run_inference.py @@ -15,7 +15,6 @@ from pipecat.adapters.services.anthropic_adapter import AnthropicLLMInvocationPa from pipecat.adapters.services.bedrock_adapter import AWSBedrockLLMInvocationParams from pipecat.adapters.services.gemini_adapter import GeminiLLMInvocationParams from pipecat.adapters.services.open_ai_adapter import OpenAILLMInvocationParams -from pipecat.adapters.services.open_ai_responses_adapter import OpenAIResponsesLLMInvocationParams from pipecat.processors.aggregators.llm_context import LLMContext from pipecat.services.anthropic.llm import AnthropicLLMService from pipecat.services.aws.llm import AWSBedrockLLMService @@ -786,42 +785,26 @@ async def test_openai_responses_run_inference_with_llm_context(): ) service._client = AsyncMock() - # Setup mocks - mock_context = MagicMock(spec=LLMContext) - mock_adapter = MagicMock() - test_input = [ - {"role": "developer", "content": "You are a helpful assistant"}, - {"role": "user", "content": "Hello, world!"}, - ] - mock_adapter.get_llm_invocation_params.return_value = OpenAIResponsesLLMInvocationParams( - input=test_input, - tools=OPENAI_NOT_GIVEN, - instructions="You are a helpful assistant", + context = LLMContext( + messages=[ + {"role": "user", "content": "Hello, world!"}, + ] ) - service.get_llm_adapter = MagicMock(return_value=mock_adapter) - # Mock response mock_response = MagicMock() mock_response.output_text = "Hello! How can I help you today?" service._client.responses.create = AsyncMock(return_value=mock_response) - # Execute - result = await service.run_inference(mock_context) + result = await service.run_inference(context) - # Verify assert result == "Hello! How can I help you today?" - service.get_llm_adapter.assert_called_once() - mock_adapter.get_llm_invocation_params.assert_called_once_with( - mock_context, system_instruction="You are a helpful assistant" - ) - service._client.responses.create.assert_called_once_with( - model="gpt-4.1", - stream=False, - input=test_input, - instructions="You are a helpful assistant", - temperature=0.7, - max_output_tokens=100, - ) + call_kwargs = service._client.responses.create.call_args.kwargs + assert call_kwargs["model"] == "gpt-4.1" + assert call_kwargs["stream"] is False + assert call_kwargs["input"] == [{"role": "user", "content": "Hello, world!"}] + assert call_kwargs["instructions"] == "You are a helpful assistant" + assert call_kwargs["temperature"] == 0.7 + assert call_kwargs["max_output_tokens"] == 100 @pytest.mark.asyncio @@ -831,16 +814,11 @@ async def test_openai_responses_run_inference_client_exception(): service = OpenAIResponsesLLMService() service._client = AsyncMock() - mock_context = MagicMock(spec=LLMContext) - mock_adapter = MagicMock() - mock_adapter.get_llm_invocation_params.return_value = OpenAIResponsesLLMInvocationParams( - input=[], tools=OPENAI_NOT_GIVEN - ) - service.get_llm_adapter = MagicMock(return_value=mock_adapter) + context = LLMContext(messages=[{"role": "user", "content": "Hello"}]) service._client.responses.create = AsyncMock(side_effect=Exception("API Error")) with pytest.raises(Exception, match="API Error"): - await service.run_inference(mock_context) + await service.run_inference(context) @pytest.mark.asyncio @@ -855,32 +833,47 @@ async def test_openai_responses_run_inference_system_instruction_overrides(): ) service._client = AsyncMock() - mock_context = MagicMock(spec=LLMContext) - mock_adapter = MagicMock() - test_input = [{"role": "user", "content": "Hello"}] - mock_adapter.get_llm_invocation_params.return_value = OpenAIResponsesLLMInvocationParams( - input=test_input, - tools=OPENAI_NOT_GIVEN, - instructions="New system instruction", + context = LLMContext( + messages=[{"role": "user", "content": "Hello"}], ) - service.get_llm_adapter = MagicMock(return_value=mock_adapter) mock_response = MagicMock() mock_response.output_text = "Response" service._client.responses.create = AsyncMock(return_value=mock_response) - result = await service.run_inference( - mock_context, system_instruction="New system instruction" - ) + result = await service.run_inference(context, system_instruction="New system instruction") assert result == "Response" - # The adapter should have been called with the override instruction - mock_adapter.get_llm_invocation_params.assert_called_once_with( - mock_context, system_instruction="New system instruction" - ) - # The final API call should have the override instruction call_kwargs = service._client.responses.create.call_args.kwargs assert call_kwargs["instructions"] == "New system instruction" + assert call_kwargs["input"] == [{"role": "user", "content": "Hello"}] + + +@pytest.mark.asyncio +async def test_openai_responses_run_inference_empty_context_with_instruction(): + """Test that system_instruction becomes a developer message when context is empty.""" + with patch.object(OpenAIResponsesLLMService, "_create_client"): + service = OpenAIResponsesLLMService( + settings=OpenAIResponsesLLMService.Settings( + model="gpt-4.1", + system_instruction="You are helpful", + ), + ) + service._client = AsyncMock() + + context = LLMContext(messages=[]) + + mock_response = MagicMock() + mock_response.output_text = "Response" + service._client.responses.create = AsyncMock(return_value=mock_response) + + result = await service.run_inference(context) + + assert result == "Response" + call_kwargs = service._client.responses.create.call_args.kwargs + # With empty context, instruction should become a developer message + assert call_kwargs["input"] == [{"role": "developer", "content": "You are helpful"}] + assert "instructions" not in call_kwargs @pytest.mark.asyncio @@ -895,21 +888,16 @@ async def test_openai_responses_run_inference_max_tokens_override(): ) service._client = AsyncMock() - mock_context = MagicMock(spec=LLMContext) - mock_adapter = MagicMock() - test_input = [{"role": "user", "content": "Summarize this"}] - mock_adapter.get_llm_invocation_params.return_value = OpenAIResponsesLLMInvocationParams( - input=test_input, tools=OPENAI_NOT_GIVEN + context = LLMContext( + messages=[{"role": "user", "content": "Summarize this"}], ) - service.get_llm_adapter = MagicMock(return_value=mock_adapter) mock_response = MagicMock() mock_response.output_text = "Summary" service._client.responses.create = AsyncMock(return_value=mock_response) - result = await service.run_inference(mock_context, max_tokens=200) + result = await service.run_inference(context, max_tokens=200) assert result == "Summary" call_kwargs = service._client.responses.create.call_args.kwargs - # max_tokens override should take precedence assert call_kwargs["max_output_tokens"] == 200 From 21b1812c71413cabdb7f2a836024d16e0e345d24 Mon Sep 17 00:00:00 2001 From: Paul Kompfner Date: Wed, 18 Mar 2026 14:26:51 -0400 Subject: [PATCH 1008/1060] chore: add note about previous_response_id and empty input handling --- src/pipecat/adapters/services/open_ai_responses_adapter.py | 3 +++ 1 file changed, 3 insertions(+) diff --git a/src/pipecat/adapters/services/open_ai_responses_adapter.py b/src/pipecat/adapters/services/open_ai_responses_adapter.py index f55ba6435..01e6a7503 100644 --- a/src/pipecat/adapters/services/open_ai_responses_adapter.py +++ b/src/pipecat/adapters/services/open_ai_responses_adapter.py @@ -79,6 +79,9 @@ class OpenAIResponsesLLMAdapter(BaseLLMAdapter[OpenAIResponsesLLMInvocationParam # message when instructions are provided. Contexts that worked with # OpenAILLMService (system_instruction + empty messages) need the # instructions converted to an initial developer message. + # NOTE: once we support `previous_response_id`, we need to revisit + # this logic, as it'll be legit to provide instructions without input + # items if `previous_response_id` is provided. if not input_items: params["input"] = [{"role": "developer", "content": system_instruction}] else: From 951bb0c1a724712e03757f2315f76571bb8d378a Mon Sep 17 00:00:00 2001 From: Paul Kompfner Date: Wed, 18 Mar 2026 14:47:12 -0400 Subject: [PATCH 1009/1060] feat: set store=False and add run_inference tests Set store=False in Responses API calls since we send full conversation history as input items and don't use previous_response_id. Add 5 run_inference tests for OpenAIResponsesLLMService using real LLMContext and adapter (only HTTP client mocked). --- .../adapters/services/open_ai_responses_adapter.py | 14 ++++++++++++-- src/pipecat/services/openai/responses/llm.py | 1 + tests/test_run_inference.py | 1 + 3 files changed, 14 insertions(+), 2 deletions(-) diff --git a/src/pipecat/adapters/services/open_ai_responses_adapter.py b/src/pipecat/adapters/services/open_ai_responses_adapter.py index 01e6a7503..4f88e028d 100644 --- a/src/pipecat/adapters/services/open_ai_responses_adapter.py +++ b/src/pipecat/adapters/services/open_ai_responses_adapter.py @@ -79,9 +79,19 @@ class OpenAIResponsesLLMAdapter(BaseLLMAdapter[OpenAIResponsesLLMInvocationParam # message when instructions are provided. Contexts that worked with # OpenAILLMService (system_instruction + empty messages) need the # instructions converted to an initial developer message. - # NOTE: once we support `previous_response_id`, we need to revisit + # + # NOTE: if/when we support `previous_response_id`, we'll need to revisit # this logic, as it'll be legit to provide instructions without input - # items if `previous_response_id` is provided. + # items if `previous_response_id` is provided. Though...OpenAI's docs + + # ChatGPT suggests that `previous_response_id` is primarily for + # development convenience, not performance (other than minor bandwidth + # savings from not transferring the full context), as the model still + # processes the full context from the previous response. The tradeoff + # of using `previous_response_id` is that it requires enabling OpenAI-side + # 30-day conversation storage (meaning we couldn't do `store=False` + # in the API call), which may not be desirable for all users. So, + # my guess is we won't need to support `previous_response_id` in the + # immediate future. if not input_items: params["input"] = [{"role": "developer", "content": system_instruction}] else: diff --git a/src/pipecat/services/openai/responses/llm.py b/src/pipecat/services/openai/responses/llm.py index e0a3e4428..fd1d711cc 100644 --- a/src/pipecat/services/openai/responses/llm.py +++ b/src/pipecat/services/openai/responses/llm.py @@ -324,6 +324,7 @@ class OpenAIResponsesLLMService(LLMService): params: Dict[str, Any] = { "model": self._settings.model, "stream": True, + "store": False, "input": invocation_params["input"], } diff --git a/tests/test_run_inference.py b/tests/test_run_inference.py index e01d7b36d..f67c725ae 100644 --- a/tests/test_run_inference.py +++ b/tests/test_run_inference.py @@ -801,6 +801,7 @@ async def test_openai_responses_run_inference_with_llm_context(): call_kwargs = service._client.responses.create.call_args.kwargs assert call_kwargs["model"] == "gpt-4.1" assert call_kwargs["stream"] is False + assert call_kwargs["store"] is False assert call_kwargs["input"] == [{"role": "user", "content": "Hello, world!"}] assert call_kwargs["instructions"] == "You are a helpful assistant" assert call_kwargs["temperature"] == 0.7 From 0449df828cf6ae0959e36cf2e3374fe527fa81d0 Mon Sep 17 00:00:00 2001 From: Paul Kompfner Date: Wed, 18 Mar 2026 15:06:54 -0400 Subject: [PATCH 1010/1060] chore: update previous_response_id comment --- .../services/open_ai_responses_adapter.py | 22 +++++++++---------- 1 file changed, 10 insertions(+), 12 deletions(-) diff --git a/src/pipecat/adapters/services/open_ai_responses_adapter.py b/src/pipecat/adapters/services/open_ai_responses_adapter.py index 4f88e028d..0d586fb12 100644 --- a/src/pipecat/adapters/services/open_ai_responses_adapter.py +++ b/src/pipecat/adapters/services/open_ai_responses_adapter.py @@ -80,18 +80,16 @@ class OpenAIResponsesLLMAdapter(BaseLLMAdapter[OpenAIResponsesLLMInvocationParam # OpenAILLMService (system_instruction + empty messages) need the # instructions converted to an initial developer message. # - # NOTE: if/when we support `previous_response_id`, we'll need to revisit - # this logic, as it'll be legit to provide instructions without input - # items if `previous_response_id` is provided. Though...OpenAI's docs + - # ChatGPT suggests that `previous_response_id` is primarily for - # development convenience, not performance (other than minor bandwidth - # savings from not transferring the full context), as the model still - # processes the full context from the previous response. The tradeoff - # of using `previous_response_id` is that it requires enabling OpenAI-side - # 30-day conversation storage (meaning we couldn't do `store=False` - # in the API call), which may not be desirable for all users. So, - # my guess is we won't need to support `previous_response_id` in the - # immediate future. + # NOTE: if/when we support `previous_response_id` and/or + # `conversation_id`, we'll need to revisit this logic, as it'll + # be legit to provide instructions without input items. Worth + # noting that OpenAI's docs suggest these parameters are primarily + # for development convenience rather than performance (the model + # still processes the full context), and come with the tradeoff + # of requiring OpenAI-side 30-day conversation storage, which may + # not be desirable for many users. But it could give folks an easy + # way to store/switch between conversations without needing to + # manage that storage themselves. if not input_items: params["input"] = [{"role": "developer", "content": system_instruction}] else: From 2001ab4577df414bf26128678b5980a8b0976e56 Mon Sep 17 00:00:00 2001 From: Paul Kompfner Date: Wed, 18 Mar 2026 15:14:28 -0400 Subject: [PATCH 1011/1060] feat: add 20a persistent context example for OpenAI Responses --- ...20a-persistent-context-openai-responses.py | 249 ++++++++++++++++++ 1 file changed, 249 insertions(+) create mode 100644 examples/foundational/20a-persistent-context-openai-responses.py diff --git a/examples/foundational/20a-persistent-context-openai-responses.py b/examples/foundational/20a-persistent-context-openai-responses.py new file mode 100644 index 000000000..730e90197 --- /dev/null +++ b/examples/foundational/20a-persistent-context-openai-responses.py @@ -0,0 +1,249 @@ +# +# Copyright (c) 2024-2026, Daily +# +# SPDX-License-Identifier: BSD 2-Clause License +# + +import glob +import json +import os +from datetime import datetime + +from dotenv import load_dotenv +from loguru import logger + +from pipecat.adapters.schemas.function_schema import FunctionSchema +from pipecat.adapters.schemas.tools_schema import ToolsSchema +from pipecat.audio.vad.silero import SileroVADAnalyzer +from pipecat.frames.frames import LLMRunFrame, TTSSpeakFrame +from pipecat.pipeline.pipeline import Pipeline +from pipecat.pipeline.runner import PipelineRunner +from pipecat.pipeline.task import PipelineParams, PipelineTask +from pipecat.processors.aggregators.llm_context import LLMContext +from pipecat.processors.aggregators.llm_response_universal import ( + LLMContextAggregatorPair, + LLMUserAggregatorParams, +) +from pipecat.runner.types import RunnerArguments +from pipecat.runner.utils import create_transport +from pipecat.services.cartesia.tts import CartesiaTTSService +from pipecat.services.deepgram.stt import DeepgramSTTService +from pipecat.services.llm_service import FunctionCallParams +from pipecat.services.openai.responses.llm import OpenAIResponsesLLMService +from pipecat.transports.base_transport import BaseTransport, TransportParams +from pipecat.transports.daily.transport import DailyParams +from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams + +load_dotenv(override=True) + + +BASE_FILENAME = "/tmp/pipecat_conversation_" + + +async def fetch_weather_from_api(params: FunctionCallParams): + temperature = 75 if params.arguments["format"] == "fahrenheit" else 24 + await params.result_callback( + { + "conditions": "nice", + "temperature": temperature, + "format": params.arguments["format"], + "timestamp": datetime.now().strftime("%Y%m%d_%H%M%S"), + } + ) + + +async def get_saved_conversation_filenames(params: FunctionCallParams): + # Construct the full pattern including the BASE_FILENAME + full_pattern = f"{BASE_FILENAME}*.json" + + # Use glob to find all matching files + matching_files = glob.glob(full_pattern) + logger.debug(f"matching files: {matching_files}") + + await params.result_callback({"filenames": matching_files}) + + +async def save_conversation(params: FunctionCallParams): + timestamp = datetime.now().strftime("%Y-%m-%d_%H:%M:%S") + filename = f"{BASE_FILENAME}{timestamp}.json" + logger.debug( + f"writing conversation to {filename}\n{json.dumps(params.context.get_messages(), indent=4)}" + ) + try: + with open(filename, "w") as file: + messages = params.context.get_messages() + # remove the last message, which is the instruction we just gave to save the conversation + messages.pop() + json.dump(messages, file, indent=2) + await params.result_callback({"success": True}) + except Exception as e: + await params.result_callback({"success": False, "error": str(e)}) + + +async def load_conversation(params: FunctionCallParams): + global tts + filename = params.arguments["filename"] + logger.debug(f"loading conversation from {filename}") + try: + with open(filename, "r") as file: + params.context.set_messages(json.load(file)) + logger.debug( + f"loaded conversation from {filename}\n{json.dumps(params.context.get_messages(), indent=4)}" + ) + await params.llm.queue_frame(TTSSpeakFrame("Ok, I've loaded that conversation.")) + except Exception as e: + await params.result_callback({"success": False, "error": str(e)}) + + +system_instruction = "You are a helpful assistant in a voice conversation. Your responses will be spoken aloud, so avoid emojis, bullet points, or other formatting that can't be spoken. Respond to what the user said in a creative, helpful, and brief way." + +weather_function = FunctionSchema( + name="get_current_weather", + description="Get the current weather", + properties={ + "location": { + "type": "string", + "description": "The city and state, e.g. San Francisco, CA", + }, + "format": { + "type": "string", + "enum": ["celsius", "fahrenheit"], + "description": "The temperature unit to use. Infer this from the users location.", + }, + }, + required=["location", "format"], +) + +save_conversation_function = FunctionSchema( + name="save_conversation", + description="Save the current conversatione. Use this function to persist the current conversation to external storage.", + properties={}, + required=[], +) + +get_filenames_function = FunctionSchema( + name="get_saved_conversation_filenames", + description="Get a list of saved conversation histories. Returns a list of filenames. Each filename includes a date and timestamp. Each file is conversation history that can be loaded into this session.", + properties={}, + required=[], +) + +load_conversation_function = FunctionSchema( + name="load_conversation", + description="Load a conversation history. Use this function to load a conversation history into the current session.", + properties={ + "filename": { + "type": "string", + "description": "The filename of the conversation history to load.", + } + }, + required=["filename"], +) + +tools = ToolsSchema( + standard_tools=[ + weather_function, + save_conversation_function, + get_filenames_function, + load_conversation_function, + ] +) + + +# We use lambdas to defer transport parameter creation until the transport +# type is selected at runtime. +transport_params = { + "daily": lambda: DailyParams( + audio_in_enabled=True, + audio_out_enabled=True, + ), + "twilio": lambda: FastAPIWebsocketParams( + audio_in_enabled=True, + audio_out_enabled=True, + ), + "webrtc": lambda: TransportParams( + audio_in_enabled=True, + audio_out_enabled=True, + ), +} + + +async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): + logger.info(f"Starting bot") + + stt = DeepgramSTTService(api_key=os.getenv("DEEPGRAM_API_KEY")) + + tts = CartesiaTTSService( + api_key=os.getenv("CARTESIA_API_KEY"), + settings=CartesiaTTSService.Settings( + voice="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady + ), + ) + + llm = OpenAIResponsesLLMService( + api_key=os.getenv("OPENAI_API_KEY"), + settings=OpenAIResponsesLLMService.Settings( + system_instruction=system_instruction, + ), + ) + + # you can either register a single function for all function calls, or specific functions + # llm.register_function(None, fetch_weather_from_api) + llm.register_function("get_current_weather", fetch_weather_from_api) + llm.register_function("save_conversation", save_conversation) + llm.register_function("get_saved_conversation_filenames", get_saved_conversation_filenames) + llm.register_function("load_conversation", load_conversation) + + context = LLMContext(tools=tools) + user_aggregator, assistant_aggregator = LLMContextAggregatorPair( + context, + user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()), + ) + + pipeline = Pipeline( + [ + transport.input(), # Transport user input + stt, # STT + user_aggregator, + llm, # LLM + tts, + transport.output(), # Transport bot output + assistant_aggregator, + ] + ) + + task = PipelineTask( + pipeline, + params=PipelineParams( + enable_metrics=True, + enable_usage_metrics=True, + ), + idle_timeout_secs=runner_args.pipeline_idle_timeout_secs, + ) + + @transport.event_handler("on_client_connected") + async def on_client_connected(transport, client): + logger.info(f"Client connected") + # Kick off the conversation. + await task.queue_frames([LLMRunFrame()]) + + @transport.event_handler("on_client_disconnected") + async def on_client_disconnected(transport, client): + logger.info(f"Client disconnected") + await task.cancel() + + runner = PipelineRunner(handle_sigint=runner_args.handle_sigint) + + await runner.run(task) + + +async def bot(runner_args: RunnerArguments): + """Main bot entry point compatible with Pipecat Cloud.""" + transport = await create_transport(runner_args, transport_params) + await run_bot(transport, runner_args) + + +if __name__ == "__main__": + from pipecat.runner.run import main + + main() From 891966346ca88443f33b61921dd2a466d78f897b Mon Sep 17 00:00:00 2001 From: Paul Kompfner Date: Wed, 18 Mar 2026 15:17:16 -0400 Subject: [PATCH 1012/1060] feat: add 55zi update-settings example for OpenAI Responses --- ...zi-update-settings-openai-responses-llm.py | 127 ++++++++++++++++++ 1 file changed, 127 insertions(+) create mode 100644 examples/foundational/55zi-update-settings-openai-responses-llm.py diff --git a/examples/foundational/55zi-update-settings-openai-responses-llm.py b/examples/foundational/55zi-update-settings-openai-responses-llm.py new file mode 100644 index 000000000..61bd8329e --- /dev/null +++ b/examples/foundational/55zi-update-settings-openai-responses-llm.py @@ -0,0 +1,127 @@ +# +# Copyright (c) 2024-2026, Daily +# +# SPDX-License-Identifier: BSD 2-Clause License +# + +import asyncio +import os + +from dotenv import load_dotenv +from loguru import logger + +from pipecat.audio.vad.silero import SileroVADAnalyzer +from pipecat.frames.frames import LLMRunFrame, LLMUpdateSettingsFrame +from pipecat.pipeline.pipeline import Pipeline +from pipecat.pipeline.runner import PipelineRunner +from pipecat.pipeline.task import PipelineParams, PipelineTask +from pipecat.processors.aggregators.llm_context import LLMContext +from pipecat.processors.aggregators.llm_response_universal import ( + LLMContextAggregatorPair, + LLMUserAggregatorParams, +) +from pipecat.runner.types import RunnerArguments +from pipecat.runner.utils import create_transport +from pipecat.services.cartesia.tts import CartesiaTTSService +from pipecat.services.deepgram.stt import DeepgramSTTService +from pipecat.services.openai.responses.llm import OpenAIResponsesLLMService +from pipecat.transports.base_transport import BaseTransport, TransportParams +from pipecat.transports.daily.transport import DailyParams +from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams + +load_dotenv(override=True) + +transport_params = { + "daily": lambda: DailyParams( + audio_in_enabled=True, + audio_out_enabled=True, + ), + "twilio": lambda: FastAPIWebsocketParams( + audio_in_enabled=True, + audio_out_enabled=True, + ), + "webrtc": lambda: TransportParams( + audio_in_enabled=True, + audio_out_enabled=True, + ), +} + + +async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): + logger.info(f"Starting bot") + + stt = DeepgramSTTService(api_key=os.getenv("DEEPGRAM_API_KEY")) + + tts = CartesiaTTSService( + api_key=os.getenv("CARTESIA_API_KEY"), + settings=CartesiaTTSService.Settings( + voice="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady + ), + ) + + llm = OpenAIResponsesLLMService( + api_key=os.getenv("OPENAI_API_KEY"), + settings=OpenAIResponsesLLMService.Settings( + system_instruction="You are a helpful assistant in a voice conversation. Your responses will be spoken aloud, so avoid emojis, bullet points, or other formatting that can't be spoken. Respond to what the user said in a creative, helpful, and brief way.", + ), + ) + + context = LLMContext() + user_aggregator, assistant_aggregator = LLMContextAggregatorPair( + context, + user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()), + ) + + pipeline = Pipeline( + [ + transport.input(), + stt, + user_aggregator, + llm, + tts, + transport.output(), + assistant_aggregator, + ] + ) + + task = PipelineTask( + pipeline, + params=PipelineParams( + enable_metrics=True, + enable_usage_metrics=True, + ), + idle_timeout_secs=runner_args.pipeline_idle_timeout_secs, + ) + + @transport.event_handler("on_client_connected") + async def on_client_connected(transport, client): + logger.info(f"Client connected") + context.add_message({"role": "user", "content": "Please introduce yourself to the user."}) + await task.queue_frames([LLMRunFrame()]) + + await asyncio.sleep(10) + logger.info("Updating OpenAI LLM settings: temperature=0.1") + await task.queue_frame( + LLMUpdateSettingsFrame(delta=OpenAIResponsesLLMService.Settings(temperature=0.1)) + ) + + @transport.event_handler("on_client_disconnected") + async def on_client_disconnected(transport, client): + logger.info(f"Client disconnected") + await task.cancel() + + runner = PipelineRunner(handle_sigint=runner_args.handle_sigint) + + await runner.run(task) + + +async def bot(runner_args: RunnerArguments): + """Main bot entry point compatible with Pipecat Cloud.""" + transport = await create_transport(runner_args, transport_params) + await run_bot(transport, runner_args) + + +if __name__ == "__main__": + from pipecat.runner.run import main + + main() From 5de794e1da5389005d2d155c8311a1191b93479e Mon Sep 17 00:00:00 2001 From: Paul Kompfner Date: Wed, 18 Mar 2026 15:29:04 -0400 Subject: [PATCH 1013/1060] feat: add service_tier support to OpenAIResponsesLLMService --- src/pipecat/services/openai/responses/llm.py | 6 ++++++ 1 file changed, 6 insertions(+) diff --git a/src/pipecat/services/openai/responses/llm.py b/src/pipecat/services/openai/responses/llm.py index fd1d711cc..f62c6e758 100644 --- a/src/pipecat/services/openai/responses/llm.py +++ b/src/pipecat/services/openai/responses/llm.py @@ -84,6 +84,7 @@ class OpenAIResponsesLLMService(LLMService): organization=None, project=None, default_headers: Optional[Mapping[str, str]] = None, + service_tier: Optional[str] = None, settings: Optional[Settings] = None, **kwargs, ): @@ -96,6 +97,7 @@ class OpenAIResponsesLLMService(LLMService): organization: OpenAI organization ID. project: OpenAI project ID. default_headers: Additional HTTP headers to include in requests. + service_tier: Service tier to use (e.g., "auto", "flex", "priority"). settings: Runtime-updatable settings. When provided alongside other parameters, ``settings`` values take precedence. **kwargs: Additional arguments passed to the parent LLMService. @@ -127,6 +129,7 @@ class OpenAIResponsesLLMService(LLMService): **kwargs, ) + self._service_tier = service_tier self._client = self._create_client( api_key=api_key, base_url=base_url, @@ -342,6 +345,9 @@ class OpenAIResponsesLLMService(LLMService): if isinstance(self._settings.max_completion_tokens, int): params["max_output_tokens"] = self._settings.max_completion_tokens + if self._service_tier is not None: + params["service_tier"] = self._service_tier + # Tools tools = invocation_params.get("tools") if tools is not None and not isinstance(tools, type(NOT_GIVEN)): From b1a8588209d407feebbffd1b7c40998bcfe8a33b Mon Sep 17 00:00:00 2001 From: Paul Kompfner Date: Wed, 18 Mar 2026 15:39:06 -0400 Subject: [PATCH 1014/1060] feat: add 12- and 14d- image/video examples for OpenAI Responses --- .../12-describe-image-openai-responses.py | 139 +++++++++++++ ...function-calling-openai-responses-video.py | 195 ++++++++++++++++++ scripts/evals/run-release-evals.py | 2 + 3 files changed, 336 insertions(+) create mode 100644 examples/foundational/12-describe-image-openai-responses.py create mode 100644 examples/foundational/14d-function-calling-openai-responses-video.py diff --git a/examples/foundational/12-describe-image-openai-responses.py b/examples/foundational/12-describe-image-openai-responses.py new file mode 100644 index 000000000..a3c113cb2 --- /dev/null +++ b/examples/foundational/12-describe-image-openai-responses.py @@ -0,0 +1,139 @@ +# +# Copyright (c) 2024-2026, Daily +# +# SPDX-License-Identifier: BSD 2-Clause License +# + + +import os + +from dotenv import load_dotenv +from loguru import logger +from PIL import Image + +from pipecat.audio.vad.silero import SileroVADAnalyzer +from pipecat.frames.frames import LLMRunFrame +from pipecat.pipeline.pipeline import Pipeline +from pipecat.pipeline.runner import PipelineRunner +from pipecat.pipeline.task import PipelineParams, PipelineTask +from pipecat.processors.aggregators.llm_context import LLMContext +from pipecat.processors.aggregators.llm_response_universal import ( + LLMContextAggregatorPair, + LLMUserAggregatorParams, +) +from pipecat.runner.types import RunnerArguments +from pipecat.runner.utils import create_transport +from pipecat.services.cartesia.tts import CartesiaTTSService +from pipecat.services.deepgram.stt import DeepgramSTTService +from pipecat.services.openai.responses.llm import OpenAIResponsesLLMService +from pipecat.transports.base_transport import BaseTransport, TransportParams +from pipecat.transports.daily.transport import DailyParams + +load_dotenv(override=True) + + +# We use lambdas to defer transport parameter creation until the transport +# type is selected at runtime. +transport_params = { + "daily": lambda: DailyParams( + audio_in_enabled=True, + audio_out_enabled=True, + ), + "webrtc": lambda: TransportParams( + audio_in_enabled=True, + audio_out_enabled=True, + ), +} + + +async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): + logger.info(f"Starting bot") + + stt = DeepgramSTTService(api_key=os.getenv("DEEPGRAM_API_KEY")) + + tts = CartesiaTTSService( + api_key=os.getenv("CARTESIA_API_KEY"), + settings=CartesiaTTSService.Settings( + voice="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady + ), + ) + + llm = OpenAIResponsesLLMService( + api_key=os.getenv("OPENAI_API_KEY"), + settings=OpenAIResponsesLLMService.Settings( + system_instruction="You are a helpful assistant in a voice conversation. Your responses will be spoken aloud, so avoid emojis, bullet points, or other formatting that can't be spoken. Respond to what the user said in a creative, helpful, and brief way. You are also able to describe images.", + ), + ) + + context = LLMContext() + user_aggregator, assistant_aggregator = LLMContextAggregatorPair( + context, + user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()), + ) + + pipeline = Pipeline( + [ + transport.input(), # Transport user input + stt, # STT + user_aggregator, # User responses + llm, # LLM + tts, # TTS + transport.output(), # Transport bot output + assistant_aggregator, # Assistant spoken responses + ] + ) + + task = PipelineTask( + pipeline, + params=PipelineParams( + enable_metrics=True, + enable_usage_metrics=True, + ), + idle_timeout_secs=runner_args.pipeline_idle_timeout_secs, + ) + + @transport.event_handler("on_client_connected") + async def on_client_connected(transport, client): + logger.info(f"Client connected") + + if not runner_args.body: + script_dir = os.path.dirname(__file__) + runner_args.body = { + "image_path": os.path.join(script_dir, "assets", "cat.jpg"), + "question": "Describe this image", + } + + image_path = runner_args.body["image_path"] + question = runner_args.body["question"] + + # Kick off the conversation. + image = Image.open(image_path) + message = await LLMContext.create_image_message( + image=image.tobytes(), + format="RGB", + size=image.size, + text=question, + ) + context.add_message(message) + await task.queue_frames([LLMRunFrame()]) + + @transport.event_handler("on_client_disconnected") + async def on_client_disconnected(transport, client): + logger.info(f"Client disconnected") + await task.cancel() + + runner = PipelineRunner(handle_sigint=runner_args.handle_sigint) + + await runner.run(task) + + +async def bot(runner_args: RunnerArguments): + """Main bot entry point compatible with Pipecat Cloud.""" + transport = await create_transport(runner_args, transport_params) + await run_bot(transport, runner_args) + + +if __name__ == "__main__": + from pipecat.runner.run import main + + main() diff --git a/examples/foundational/14d-function-calling-openai-responses-video.py b/examples/foundational/14d-function-calling-openai-responses-video.py new file mode 100644 index 000000000..440c51cc1 --- /dev/null +++ b/examples/foundational/14d-function-calling-openai-responses-video.py @@ -0,0 +1,195 @@ +# +# Copyright (c) 2024-2026, Daily +# +# SPDX-License-Identifier: BSD 2-Clause License +# + + +import os + +from dotenv import load_dotenv +from loguru import logger + +from pipecat.adapters.schemas.function_schema import FunctionSchema +from pipecat.adapters.schemas.tools_schema import ToolsSchema +from pipecat.audio.vad.silero import SileroVADAnalyzer +from pipecat.frames.frames import LLMRunFrame, TTSSpeakFrame, UserImageRequestFrame +from pipecat.pipeline.pipeline import Pipeline +from pipecat.pipeline.runner import PipelineRunner +from pipecat.pipeline.task import PipelineParams, PipelineTask +from pipecat.processors.aggregators.llm_context import LLMContext +from pipecat.processors.aggregators.llm_response_universal import ( + LLMContextAggregatorPair, + LLMUserAggregatorParams, +) +from pipecat.processors.frame_processor import FrameDirection +from pipecat.runner.types import RunnerArguments +from pipecat.runner.utils import ( + create_transport, + get_transport_client_id, + maybe_capture_participant_camera, +) +from pipecat.services.cartesia.tts import CartesiaTTSService +from pipecat.services.deepgram.stt import DeepgramSTTService +from pipecat.services.llm_service import FunctionCallParams +from pipecat.services.openai.responses.llm import OpenAIResponsesLLMService +from pipecat.transports.base_transport import BaseTransport, TransportParams +from pipecat.transports.daily.transport import DailyParams + +load_dotenv(override=True) + + +async def fetch_user_image(params: FunctionCallParams): + """Fetch the user image and push it to the LLM. + + When called, this function pushes a UserImageRequestFrame upstream to the + transport. As a result, the transport will request the user image and push a + UserImageRawFrame downstream which will be added to the context by the LLM + assistant aggregator. The result_callback will be invoked once the image is + retrieved and processed. + """ + user_id = params.arguments["user_id"] + question = params.arguments["question"] + logger.debug(f"Requesting image with user_id={user_id}, question={question}") + + # Request a user image frame and indicate that it should be added to the + # context. Also associate it to the function call. Pass the result_callback + # so it can be invoked when the image is actually retrieved. + await params.llm.push_frame( + UserImageRequestFrame( + user_id=user_id, + text=question, + append_to_context=True, + function_name=params.function_name, + tool_call_id=params.tool_call_id, + result_callback=params.result_callback, + ), + FrameDirection.UPSTREAM, + ) + + +# We use lambdas to defer transport parameter creation until the transport +# type is selected at runtime. +transport_params = { + "daily": lambda: DailyParams( + audio_in_enabled=True, + audio_out_enabled=True, + video_in_enabled=True, + ), + "webrtc": lambda: TransportParams( + audio_in_enabled=True, + audio_out_enabled=True, + video_in_enabled=True, + ), +} + + +async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): + logger.info(f"Starting bot") + + stt = DeepgramSTTService(api_key=os.getenv("DEEPGRAM_API_KEY")) + + tts = CartesiaTTSService( + api_key=os.getenv("CARTESIA_API_KEY"), + settings=CartesiaTTSService.Settings( + voice="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady + ), + ) + + llm = OpenAIResponsesLLMService( + api_key=os.getenv("OPENAI_API_KEY"), + settings=OpenAIResponsesLLMService.Settings( + system_instruction="You are a helpful assistant in a voice conversation. Your responses will be spoken aloud, so avoid emojis, bullet points, or other formatting that can't be spoken. Respond to what the user said in a creative, helpful, and brief way. You are able to describe images from the user camera.", + ), + ) + llm.register_function("fetch_user_image", fetch_user_image) + + @llm.event_handler("on_function_calls_started") + async def on_function_calls_started(service, function_calls): + await tts.queue_frame(TTSSpeakFrame("Let me check on that.", append_to_context=False)) + + fetch_image_function = FunctionSchema( + name="fetch_user_image", + description="Called when the user requests a description of their camera feed", + properties={ + "user_id": { + "type": "string", + "description": "The ID of the user to grab the image from", + }, + "question": { + "type": "string", + "description": "The question that the user is asking about the image", + }, + }, + required=["user_id", "question"], + ) + tools = ToolsSchema(standard_tools=[fetch_image_function]) + + context = LLMContext(tools=tools) + user_aggregator, assistant_aggregator = LLMContextAggregatorPair( + context, + user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()), + ) + + pipeline = Pipeline( + [ + transport.input(), # Transport user input + stt, # STT + user_aggregator, # User responses + llm, # LLM + tts, # TTS + transport.output(), # Transport bot output + assistant_aggregator, # Assistant spoken responses + ] + ) + + task = PipelineTask( + pipeline, + params=PipelineParams( + enable_metrics=True, + enable_usage_metrics=True, + ), + idle_timeout_secs=runner_args.pipeline_idle_timeout_secs, + ) + + @transport.event_handler("on_client_connected") + async def on_client_connected(transport, client): + logger.info(f"Client connected") + + await maybe_capture_participant_camera(transport, client) + + client_id = get_transport_client_id(transport, client) + + # Kick off the conversation. + context.add_message( + { + "role": "user", + "content": f"Please introduce yourself to the user. Use '{client_id}' as the user ID during function calls.", + } + ) + await task.queue_frames([LLMRunFrame()]) + + @transport.event_handler("on_client_disconnected") + async def on_client_disconnected(transport, client): + logger.info(f"Client disconnected") + await task.cancel() + + @tts.event_handler("on_tts_request") + async def on_tts_request(tts, context_id: str, text: str): + logger.debug(f"On TTS request: {context_id}: {text}") + + runner = PipelineRunner(handle_sigint=runner_args.handle_sigint) + + await runner.run(task) + + +async def bot(runner_args: RunnerArguments): + """Main bot entry point compatible with Pipecat Cloud.""" + transport = await create_transport(runner_args, transport_params) + await run_bot(transport, runner_args) + + +if __name__ == "__main__": + from pipecat.runner.run import main + + main() diff --git a/scripts/evals/run-release-evals.py b/scripts/evals/run-release-evals.py index 9671703ba..19492ba62 100644 --- a/scripts/evals/run-release-evals.py +++ b/scripts/evals/run-release-evals.py @@ -154,6 +154,7 @@ TESTS_07 = [ TESTS_12 = [ ("12-describe-image-openai.py", EVAL_VISION_IMAGE(eval_speaks_first=True)), + ("12-describe-image-openai-responses.py", EVAL_VISION_IMAGE(eval_speaks_first=True)), ("12a-describe-image-anthropic.py", EVAL_VISION_IMAGE(eval_speaks_first=True)), ("12b-describe-image-aws.py", EVAL_VISION_IMAGE(eval_speaks_first=True)), ("12c-describe-image-gemini-flash.py", EVAL_VISION_IMAGE(eval_speaks_first=True)), @@ -193,6 +194,7 @@ TESTS_14 = [ ("14d-function-calling-gemini-flash-video.py", EVAL_VISION_CAMERA), ("14d-function-calling-moondream-video.py", EVAL_VISION_CAMERA), ("14d-function-calling-openai-video.py", EVAL_VISION_CAMERA), + ("14d-function-calling-openai-responses-video.py", EVAL_VISION_CAMERA), # Currently not working. # ("14c-function-calling-together.py", EVAL_WEATHER), # ("14l-function-calling-deepseek.py", EVAL_WEATHER), From 4b704e6d3a5bbe509f1b435df04da4aaf08f04ad Mon Sep 17 00:00:00 2001 From: Mark Backman Date: Wed, 18 Mar 2026 15:57:34 -0400 Subject: [PATCH 1015/1060] GradiumSTTService improvements (#4066) * Remove duplicate reconnection logic from Gradium STT The _receive_messages method had its own while-True reconnect loop, duplicating the reconnection handling already provided by WebsocketService._receive_task_handler (exponential backoff, max retries, error reporting). Flatten to just the inner message loop and let the base class handle reconnection. * Align Gradium STT VAD handling with base class patterns Replace the process_frame override with a _handle_vad_user_stopped_speaking override, which is the proper hook provided by STTService. Move start_processing_metrics() into run_stt (matching Gladia's pattern). Remove unused FrameDirection and VADUserStartedSpeakingFrame imports. * Add transcript aggregation delay after flushed to capture trailing tokens Gradium flushed response can arrive before all text tokens have been delivered. Instead of finalizing immediately on flushed, start a short timer (100ms) that allows trailing tokens to accumulate before pushing the final TranscriptionFrame. * Add changelog for PR #4066 * Change default encoding to pcm_16000 * Decouple encoding from sample_rate in Gradium STT The encoding parameter now takes just the base type (pcm, wav, opus) and the sample rate is derived from the pipeline audio_in_sample_rate, assembled dynamically via input_format_from_encoding(). This fixes the mismatch where SAMPLE_RATE=24000 was passed to the base class while encoding defaulted to pcm_16000. --- changelog/4066.changed.2.md | 1 + changelog/4066.changed.md | 1 + src/pipecat/services/gradium/stt.py | 216 ++++++++++++++++++---------- 3 files changed, 144 insertions(+), 74 deletions(-) create mode 100644 changelog/4066.changed.2.md create mode 100644 changelog/4066.changed.md diff --git a/changelog/4066.changed.2.md b/changelog/4066.changed.2.md new file mode 100644 index 000000000..751961f10 --- /dev/null +++ b/changelog/4066.changed.2.md @@ -0,0 +1 @@ +- `GradiumSTTService` now takes both an `encoding` and `sample_rate` constructor argument which is assmebled in the class to form the `input_format`. PCM accepts `8000`, `16000`, and `24000` Hz sample rates. diff --git a/changelog/4066.changed.md b/changelog/4066.changed.md new file mode 100644 index 000000000..65e95ff2c --- /dev/null +++ b/changelog/4066.changed.md @@ -0,0 +1 @@ +- Improved `GradiumSTTService` transcription accuracy by reworking how text fragments are accumulated and finalized. Previously, trailing words could be dropped when the server's `flushed` response arrived before all text tokens were delivered. The service now uses a short aggregation delay after flush to capture trailing tokens, producing complete utterances. diff --git a/src/pipecat/services/gradium/stt.py b/src/pipecat/services/gradium/stt.py index c328dceab..5dea2c824 100644 --- a/src/pipecat/services/gradium/stt.py +++ b/src/pipecat/services/gradium/stt.py @@ -10,6 +10,7 @@ This module provides integration with Gradium's real-time speech-to-text WebSocket API for streaming audio transcription. """ +import asyncio import base64 import json from dataclasses import dataclass, field @@ -22,6 +23,7 @@ from pipecat.frames.frames import ( CancelFrame, EndFrame, Frame, + InterimTranscriptionFrame, StartFrame, TranscriptionFrame, VADUserStartedSpeakingFrame, @@ -43,7 +45,37 @@ except ModuleNotFoundError as e: logger.error('In order to use Gradium, you need to `pip install "pipecat-ai[gradium]"`.') raise Exception(f"Missing module: {e}") -SAMPLE_RATE = 24000 +# Seconds to wait after a "flushed" message for trailing text tokens to arrive +# before finalizing the transcription. +TRANSCRIPT_AGGREGATION_DELAY = 0.1 + + +def _input_format_from_encoding(encoding: str, sample_rate: int) -> str: + """Build Gradium input_format from encoding type and sample rate. + + For PCM encoding, appends the sample rate (e.g., "pcm_16000"). + For other encodings (wav, opus), returns the encoding as-is. + + Args: + encoding: Base encoding type ("pcm", "wav", or "opus"). + sample_rate: Audio sample rate in Hz. + + Returns: + The full input_format string for the Gradium API. + """ + if encoding == "pcm": + match sample_rate: + case 8000: + return "pcm_8000" + case 16000: + return "pcm_16000" + case 24000: + return "pcm_24000" + logger.warning( + f"GradiumSTTService: unsupported sample rate {sample_rate} for PCM encoding, using pcm_16000" + ) + return "pcm_16000" + return encoding def language_to_gradium_language(language: Language) -> Optional[str]: @@ -115,6 +147,8 @@ class GradiumSTTService(WebsocketSTTService): *, api_key: str, api_endpoint_base_url: str = "wss://eu.api.gradium.ai/api/speech/asr", + encoding: str = "pcm", + sample_rate: Optional[int] = None, params: Optional[InputParams] = None, json_config: Optional[str] = None, settings: Optional[Settings] = None, @@ -126,6 +160,12 @@ class GradiumSTTService(WebsocketSTTService): Args: api_key: Gradium API key for authentication. api_endpoint_base_url: WebSocket endpoint URL. Defaults to Gradium's streaming endpoint. + encoding: Base audio encoding type. One of "pcm", "wav", or "opus". + For PCM, the sample rate is appended automatically from the + pipeline's audio_in_sample_rate (e.g., "pcm" becomes "pcm_16000"). + Defaults to "pcm". + sample_rate: Audio sample rate in Hz. If None, uses the pipeline + sample rate. params: Configuration parameters for language and delay settings. .. deprecated:: 0.0.105 @@ -153,7 +193,7 @@ class GradiumSTTService(WebsocketSTTService): # 1. Initialize default_settings with hardcoded defaults default_settings = self.Settings( - model=None, + model="default", language=None, delay_in_frames=None, ) @@ -173,7 +213,7 @@ class GradiumSTTService(WebsocketSTTService): default_settings.apply_update(settings) super().__init__( - sample_rate=SAMPLE_RATE, + sample_rate=sample_rate, ttfs_p99_latency=ttfs_p99_latency, settings=default_settings, **kwargs, @@ -181,19 +221,25 @@ class GradiumSTTService(WebsocketSTTService): self._api_key = api_key self._api_endpoint_base_url = api_endpoint_base_url + self._encoding = encoding self._websocket = None self._json_config = json_config self._receive_task = None + self._input_format = "" + self._audio_buffer = bytearray() self._chunk_size_ms = 80 self._chunk_size_bytes = 0 - # Set from the ready message when connecting to the service. - # These values are used for flushing transcription. - self._delay_in_frames = 0 - self._frame_size = 0 + # Accumulates text fragments within a turn. Each "text" message + # appends to this list. On "flushed" a short aggregation delay + # allows trailing tokens to arrive before the full text is joined + # and pushed as a TranscriptionFrame. + self._accumulated_text: list[str] = [] + self._flush_counter = 0 + self._transcript_aggregation_task: Optional[asyncio.Task] = None def can_generate_metrics(self) -> bool: """Check if the service can generate metrics. @@ -228,6 +274,7 @@ class GradiumSTTService(WebsocketSTTService): frame: Start frame to begin processing. """ await super().start(frame) + self._input_format = _input_format_from_encoding(self._encoding, self.sample_rate) self._chunk_size_bytes = int(self._chunk_size_ms * self.sample_rate * 2 / 1000) await self._connect() @@ -249,56 +296,41 @@ class GradiumSTTService(WebsocketSTTService): await super().cancel(frame) await self._disconnect() - async def process_frame(self, frame: Frame, direction: FrameDirection): - """Process frames with VAD-specific handling. + async def _start_metrics(self): + """Start performance metrics collection for transcription processing.""" + await self.start_processing_metrics() - When VAD detects the user has stopped speaking, we flush the transcription - by sending silence frames. This makes the system more reactive by getting - the final transcription faster without closing the connection. + async def process_frame(self, frame: Frame, direction: FrameDirection): + """Process incoming frames and handle speech events. Args: frame: The frame to process. - direction: The direction of frame processing. + direction: Direction of frame flow in the pipeline. """ await super().process_frame(frame, direction) if isinstance(frame, VADUserStartedSpeakingFrame): - await self.start_processing_metrics() + await self._start_metrics() elif isinstance(frame, VADUserStoppedSpeakingFrame): - await self._flush_transcription() + await self._send_flush() - async def _flush_transcription(self): - """Flush the transcription by sending silence frames. + async def _send_flush(self): + """Send a flush request to process any buffered audio immediately. - When VAD detects the user stopped speaking, we send delay_in_frames - chunks of silence (zeros) to flush the remaining audio from the model's - buffer. This allows for faster turn-around without closing the connection. - - From Gradium docs: "feed in delay_in_frames chunks of silence (vectors - of zeros). If those are fed in faster than realtime, the API also has - a possibility to process them faster." + Sends a flush message to tell the server to process buffered audio. + The server responds with text fragments followed by a "flushed" + acknowledgment, which triggers finalization. """ if not self._websocket or self._websocket.state is not State.OPEN: return - if self._delay_in_frames <= 0: - logger.debug("No delay_in_frames set, skipping flush") - return - - # Create a silence chunk (zeros) of frame_size samples - # Each sample is 2 bytes (16-bit PCM) - silence_bytes = bytes(self._frame_size * 2) - silence_b64 = base64.b64encode(silence_bytes).decode("utf-8") - - logger.debug(f"Flushing Gradium STT with {self._delay_in_frames} silence frames") - - for _ in range(self._delay_in_frames): - msg = {"type": "audio", "audio": silence_b64} - try: - await self._websocket.send(json.dumps(msg)) - except Exception as e: - logger.warning(f"Failed to send silence frame: {e}") - break + self._flush_counter += 1 + flush_id = str(self._flush_counter) + msg = {"type": "flush", "flush_id": flush_id} + try: + await self._websocket.send(json.dumps(msg)) + except Exception as e: + logger.warning(f"Failed to send flush: {e}") async def run_stt(self, audio: bytes) -> AsyncGenerator[Frame, None]: """Process audio data for speech-to-text conversion. @@ -353,7 +385,8 @@ class GradiumSTTService(WebsocketSTTService): await self._call_event_handler("on_connected") setup_msg = { "type": "setup", - "input_format": "pcm", + "model_name": self._settings.model, + "input_format": self._input_format, } # Build json_config: start with deprecated json_config, then override with params json_config = {} @@ -375,13 +408,7 @@ class GradiumSTTService(WebsocketSTTService): if ready_msg["type"] != "ready": raise Exception(f"unexpected first message type {ready_msg['type']}") - # Store delay_in_frames and frame_size for silence flushing - self._delay_in_frames = ready_msg.get("delay_in_frames", 0) - self._frame_size = ready_msg.get("frame_size", 1920) - logger.debug( - f"Connected to Gradium STT (delay_in_frames={self._delay_in_frames}, " - f"frame_size={self._frame_size})" - ) + logger.debug("Connected to Gradium STT") except Exception as e: await self.push_error(error_msg=f"Unknown error occurred: {e}", exception=e) @@ -390,6 +417,13 @@ class GradiumSTTService(WebsocketSTTService): async def _disconnect(self): await super()._disconnect() + if self._transcript_aggregation_task: + await self.cancel_task(self._transcript_aggregation_task) + self._transcript_aggregation_task = None + + self._accumulated_text.clear() + self._flush_counter = 0 + if self._receive_task: await self.cancel_task(self._receive_task) self._receive_task = None @@ -412,41 +446,75 @@ class GradiumSTTService(WebsocketSTTService): return self._websocket raise Exception("Websocket not connected") - async def _process_messages(self): + async def _receive_messages(self): async for message in self._get_websocket(): try: - data = json.loads(message) - await self._process_response(data) + msg = json.loads(message) except json.JSONDecodeError: logger.warning(f"Received non-JSON message: {message}") + continue - async def _receive_messages(self): - while True: - await self._process_messages() - logger.debug(f"{self} Gradium connection was disconnected (timeout?), reconnecting") - await self._connect_websocket() - - async def _process_response(self, msg): - type_ = msg.get("type", "") - if type_ == "text": - await self._handle_text(msg["text"]) - elif type_ == "end_of_stream": - await self._handle_end_of_stream() - elif type_ == "error": - await self.push_error(error_msg=f"Error: {msg}") - - async def _handle_end_of_stream(self): - """Handle termination message.""" - logger.debug("Received end_of_stream message from server") + type_ = msg.get("type", "") + if type_ == "text": + await self._handle_text(msg["text"]) + elif type_ == "flushed": + await self._handle_flushed() + elif type_ == "end_of_stream": + logger.debug("Received end_of_stream message from server") + elif type_ == "error": + await self.push_error(error_msg=f"Error: {msg}") async def _handle_text(self, text: str): - """Handle transcription results.""" + """Handle streaming transcription fragment. + + Accumulates text and pushes an InterimTranscriptionFrame with the + full accumulated text so far. + """ + self._accumulated_text.append(text) + accumulated = " ".join(self._accumulated_text) + await self.push_frame( + InterimTranscriptionFrame( + text=accumulated, + user_id=self._user_id, + timestamp=time_now_iso8601(), + language=self._settings.language, + ) + ) + await self.stop_processing_metrics() + + async def _handle_flushed(self): + """Handle flush completion by starting a transcript aggregation timer. + + The "flushed" message confirms that buffered audio has been processed, + but text tokens may still arrive after this point. A short timer allows + trailing tokens to accumulate before finalizing the transcription. + """ + if self._transcript_aggregation_task: + await self.cancel_task(self._transcript_aggregation_task) + self._transcript_aggregation_task = self.create_task( + self._transcript_aggregation_handler(), "transcript_aggregation" + ) + + async def _transcript_aggregation_handler(self): + """Wait for trailing tokens then finalize the accumulated transcription.""" + await asyncio.sleep(TRANSCRIPT_AGGREGATION_DELAY) + await self._finalize_accumulated_text() + + async def _finalize_accumulated_text(self): + """Join accumulated text, push TranscriptionFrame, and clear state.""" + if not self._accumulated_text: + return + self._transcript_aggregation_task = None + + text = " ".join(self._accumulated_text) + self._accumulated_text.clear() + logger.debug(f"Final transcription: [{text}]") await self.push_frame( TranscriptionFrame( text, self._user_id, time_now_iso8601(), + self._settings.language, ) ) - await self._trace_transcription(text, is_final=True, language=None) - await self.stop_processing_metrics() + await self._trace_transcription(text, is_final=True, language=self._settings.language) From c4be51304437d5958156f4f62e0261299eed49cf Mon Sep 17 00:00:00 2001 From: Mark Backman Date: Wed, 18 Mar 2026 16:04:12 -0400 Subject: [PATCH 1016/1060] Improvements for Nova Sonic LLM and TTS output frames (#4042) MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit * Fix empty user transcription causing spurious interruption in Nova Sonic Skip _report_user_transcription_ended() when _user_text_buffer is empty, which happens when the initial prompt is text-only. Previously, an empty TranscriptionFrame was pushed upstream, triggering a chain reaction: on_user_turn_stopped → UserStartedSpeakingFrame → interruption → premature BotStoppedSpeaking → multiple response start/stop cycles. * Improve TextFrame and assistant end of turn logic Now, SPECULATIVE text results are used to push the LLMTextFrame, AggregatedTextFrame, and TTSTextFrame. Additionally, the TTSTextFrames are push at the end of the corresponding audio segment. * Remove BotStoppedSpeakingFrame fallback from Nova Sonic Now that assistant response end is detected directly from Nova Sonic contentEnd events (END_TURN and INTERRUPTED), the BotStoppedSpeakingFrame handler is no longer needed. Inline the cleanup logic in reset_conversation. --- changelog/4042.changed.md | 1 + changelog/4042.fixed.md | 1 + src/pipecat/services/aws/nova_sonic/llm.py | 185 +++++++-------------- 3 files changed, 66 insertions(+), 121 deletions(-) create mode 100644 changelog/4042.changed.md create mode 100644 changelog/4042.fixed.md diff --git a/changelog/4042.changed.md b/changelog/4042.changed.md new file mode 100644 index 000000000..f83c32f59 --- /dev/null +++ b/changelog/4042.changed.md @@ -0,0 +1 @@ +- Nova Sonic assistant text transcripts are now delivered in real-time using speculative text events instead of delayed final text events. Previously, assistant text only arrived after all audio had finished playing, causing laggy transcripts in client UIs. Speculative text arrives before each audio chunk, providing text synchronized with what the bot is saying. This also simplifies the internal text handling by removing the interruption re-push hack and assistant text buffer. diff --git a/changelog/4042.fixed.md b/changelog/4042.fixed.md new file mode 100644 index 000000000..a48996208 --- /dev/null +++ b/changelog/4042.fixed.md @@ -0,0 +1 @@ +- Fixed empty user transcriptions in Nova Sonic causing spurious interruptions. Previously, an empty transcription could trigger an interruption of the assistant's response even though the user hadn't actually spoken. diff --git a/src/pipecat/services/aws/nova_sonic/llm.py b/src/pipecat/services/aws/nova_sonic/llm.py index 0947ba1d7..ffcbb5e5d 100644 --- a/src/pipecat/services/aws/nova_sonic/llm.py +++ b/src/pipecat/services/aws/nova_sonic/llm.py @@ -27,8 +27,8 @@ from pydantic import BaseModel, Field from pipecat.adapters.schemas.tools_schema import ToolsSchema from pipecat.adapters.services.aws_nova_sonic_adapter import AWSNovaSonicLLMAdapter, Role from pipecat.frames.frames import ( + AggregatedTextFrame, AggregationType, - BotStoppedSpeakingFrame, CancelFrame, EndFrame, Frame, @@ -424,18 +424,16 @@ class AWSNovaSonicLLMService(LLMService): self._input_audio_content_name: Optional[str] = None self._content_being_received: Optional[CurrentContent] = None self._assistant_is_responding = False - self._may_need_repush_assistant_text = False self._ready_to_send_context = False - self._handling_bot_stopped_speaking = False self._triggering_assistant_response = False self._waiting_for_trigger_transcription = False self._disconnecting = False self._connected_time: Optional[float] = None self._wants_connection = False self._user_text_buffer = "" - self._assistant_text_buffer = "" self._completed_tool_calls = set() self._audio_input_started = False + self._pending_speculative_text: Optional[str] = None file_path = files("pipecat.services.aws.nova_sonic").joinpath("ready.wav") with wave.open(file_path.open("rb"), "rb") as wav_file: @@ -505,11 +503,13 @@ class AWSNovaSonicLLMService(LLMService): async def reset_conversation(self): """Reset the conversation state while preserving context. - Handles bot stopped speaking event, disconnects from the service, - and reconnects with the preserved context. + Cleans up any in-progress assistant response, disconnects from the + service, and reconnects with the preserved context. """ logger.debug("Resetting conversation") - await self._handle_bot_stopped_speaking(delay_to_catch_trailing_assistant_text=False) + if self._assistant_is_responding: + self._assistant_is_responding = False + await self._report_assistant_response_ended() # Grab context to carry through disconnect/reconnect context = self._context @@ -540,8 +540,6 @@ class AWSNovaSonicLLMService(LLMService): await self._handle_context(context) elif isinstance(frame, InputAudioRawFrame): await self._handle_input_audio_frame(frame) - elif isinstance(frame, BotStoppedSpeakingFrame): - await self._handle_bot_stopped_speaking(delay_to_catch_trailing_assistant_text=True) elif isinstance(frame, InterruptionFrame): await self._handle_interruption_frame() @@ -569,49 +567,8 @@ class AWSNovaSonicLLMService(LLMService): await self._send_user_audio_event(frame.audio) - async def _handle_bot_stopped_speaking(self, delay_to_catch_trailing_assistant_text: bool): - # Protect against back-to-back BotStoppedSpeaking calls, which I've observed - if self._handling_bot_stopped_speaking: - return - self._handling_bot_stopped_speaking = True - - async def finalize_assistant_response(): - if self._assistant_is_responding: - # Consider the assistant finished with their response (possibly after a short delay, - # to allow for any trailing FINAL assistant text block to come in that need to make - # it into context). - # - # TODO: ideally we could base this solely on the LLM output events, but I couldn't - # figure out a reliable way to determine when we've gotten our last FINAL text block - # after the LLM is done talking. - # - # First I looked at stopReason, but it doesn't seem like the last FINAL text block - # is reliably marked END_TURN (sometimes the *first* one is, but not the last... - # bug?) - # - # Then I considered schemes where we tally or match up SPECULATIVE text blocks with - # FINAL text blocks to know how many or which FINAL blocks to expect, but user - # interruptions throw a wrench in these schemes: depending on the exact timing of - # the interruption, we should or shouldn't expect some FINAL blocks. - if delay_to_catch_trailing_assistant_text: - # This delay length is a balancing act between "catching" trailing assistant - # text that is quite delayed but not waiting so long that user text comes in - # first and results in a bit of context message order scrambling. - await asyncio.sleep(1.25) - self._assistant_is_responding = False - await self._report_assistant_response_ended() - - self._handling_bot_stopped_speaking = False - - # Finalize the assistant response, either now or after a delay - if delay_to_catch_trailing_assistant_text: - self.create_task(finalize_assistant_response()) - else: - await finalize_assistant_response() - async def _handle_interruption_frame(self): - if self._assistant_is_responding: - self._may_need_repush_assistant_text = True + pass # # LLM communication: lifecycle @@ -771,17 +728,15 @@ class AWSNovaSonicLLMService(LLMService): self._input_audio_content_name = None self._content_being_received = None self._assistant_is_responding = False - self._may_need_repush_assistant_text = False self._ready_to_send_context = False - self._handling_bot_stopped_speaking = False self._triggering_assistant_response = False self._waiting_for_trigger_transcription = False self._disconnecting = False self._connected_time = None self._user_text_buffer = "" - self._assistant_text_buffer = "" self._completed_tool_calls = set() self._audio_input_started = False + self._pending_speculative_text = None logger.info("Finished disconnecting") except Exception as e: @@ -1153,10 +1108,11 @@ class AWSNovaSonicLLMService(LLMService): self._content_being_received = content if content.role == Role.ASSISTANT: - if content.type == ContentType.AUDIO: - # Note that an assistant response can comprise of multiple audio blocks - if not self._assistant_is_responding: - # The assistant has started responding. + if content.type == ContentType.TEXT: + if ( + content.text_stage == TextStage.SPECULATIVE + and not self._assistant_is_responding + ): self._assistant_is_responding = True await self._report_user_transcription_ended() # Consider user turn over await self._report_assistant_response_started() @@ -1232,18 +1188,30 @@ class AWSNovaSonicLLMService(LLMService): if content.role == Role.ASSISTANT: if content.type == ContentType.TEXT: - # Ignore non-final text, and the "interrupted" message (which isn't meaningful text) - if content.text_stage == TextStage.FINAL and stop_reason != "INTERRUPTED": - if self._assistant_is_responding: - # Text added to the ongoing assistant response - await self._report_assistant_response_text_added(content.text_content) + if stop_reason != "INTERRUPTED": + if content.text_stage == TextStage.SPECULATIVE: + await self._report_llm_text(content.text_content) + elif self._assistant_is_responding: + # TEXT INTERRUPTED with no audio means the user interrupted + # before audio started. End the response here since no AUDIO + # contentEnd will arrive. + self._assistant_is_responding = False + await self._report_assistant_response_ended() + elif content.type == ContentType.AUDIO: + # Emit deferred TTSTextFrame after all audio chunks have been sent + await self._report_tts_text() + if stop_reason in ("END_TURN", "INTERRUPTED"): + # END_TURN: normal completion. INTERRUPTED: user interrupted + # mid-audio. Both mean no more audio for this turn. + self._assistant_is_responding = False + await self._report_assistant_response_ended() elif content.role == Role.USER: if content.type == ContentType.TEXT: if content.text_stage == TextStage.FINAL: # User transcription text added await self._report_user_transcription_text_added(content.text_content) - async def _handle_completion_end_event(self, event_json): + async def _handle_completion_end_event(self, _): pass # @@ -1256,29 +1224,40 @@ class AWSNovaSonicLLMService(LLMService): async def _report_assistant_response_started(self): logger.debug("Assistant response started") - - # Report the start of the assistant response. await self.push_frame(LLMFullResponseStartFrame()) # Report that equivalent of TTS (this is a speech-to-speech model) started await self.push_frame(TTSStartedFrame()) - async def _report_assistant_response_text_added(self, text): - if not self._context: # should never happen - return + async def _report_llm_text(self, text): + """Push speculative assistant text and defer TTSTextFrame. - logger.debug(f"Assistant response text added: {text}") + Speculative text arrives before each audio chunk, providing real-time + text that is synchronized with what the bot is saying. LLMTextFrame and + AggregatedTextFrame are pushed immediately for real-time text display. + TTSTextFrame emission is deferred to audio contentEnd so it aligns with + audio playout timing. + """ + logger.debug(f"Assistant speculative text: {text}") - # Report the text of the assistant response. - await self._push_assistant_response_text_frames(text) + llm_text_frame = LLMTextFrame(text) + llm_text_frame.append_to_context = False + await self.push_frame(llm_text_frame) - # HACK: here we're also buffering the assistant text ourselves as a - # backup rather than relying solely on the assistant context aggregator - # to do it, because the text arrives from Nova Sonic only after all the - # assistant audio frames have been pushed, meaning that if an - # interruption frame were to arrive we would lose all of it (the text - # frames sitting in the queue would be wiped). - self._assistant_text_buffer += text + aggregated_text_frame = AggregatedTextFrame(text, aggregated_by=AggregationType.SENTENCE) + aggregated_text_frame.append_to_context = False + await self.push_frame(aggregated_text_frame) + + self._pending_speculative_text = text + + async def _report_tts_text(self): + if self._pending_speculative_text: + tts_text_frame = TTSTextFrame( + self._pending_speculative_text, aggregated_by=AggregationType.SENTENCE + ) + tts_text_frame.includes_inter_frame_spaces = True + await self.push_frame(tts_text_frame) + self._pending_speculative_text = None async def _report_assistant_response_ended(self): if not self._context: # should never happen @@ -1286,54 +1265,12 @@ class AWSNovaSonicLLMService(LLMService): logger.debug("Assistant response ended") - # If an interruption frame arrived while the assistant was responding - # we may have lost all of the assistant text (see HACK, above), so - # re-push it downstream to the aggregator now. - if self._may_need_repush_assistant_text: - # Just in case, check that assistant text hasn't already made it - # into the context (sometimes it does, despite the interruption). - messages = self._context.get_messages() - last_message = messages[-1] if messages else None - if ( - not last_message - or last_message.get("role") != "assistant" - or last_message.get("content") != self._assistant_text_buffer - ): - # We also need to re-push the LLMFullResponseStartFrame since the - # TTSTextFrame would be ignored otherwise (the interruption frame - # would have cleared the assistant aggregator state). - await self.push_frame(LLMFullResponseStartFrame()) - await self._push_assistant_response_text_frames(self._assistant_text_buffer) - self._may_need_repush_assistant_text = False - # Report the end of the assistant response. await self.push_frame(LLMFullResponseEndFrame()) # Report that equivalent of TTS (this is a speech-to-speech model) stopped. await self.push_frame(TTSStoppedFrame()) - # Clear out the buffered assistant text - self._assistant_text_buffer = "" - - async def _push_assistant_response_text_frames(self, text: str): - # In a typical "cascade" LLM + TTS setup, LLMTextFrames would not - # proceed beyond the TTS service. Therefore, since a speech-to-speech - # service like Nova Sonic combines both LLM and TTS functionality, you - # would think we wouldn't need to push LLMTextFrames at all. However, - # RTVI relies on LLMTextFrames being pushed to trigger its - # "bot-llm-text" event. So here we push an LLMTextFrame, too, but avoid - # appending it to context to avoid context message duplication. - - # Push LLMTextFrame - llm_text_frame = LLMTextFrame(text) - llm_text_frame.append_to_context = False - await self.push_frame(llm_text_frame) - - # Push TTSTextFrame - tts_text_frame = TTSTextFrame(text, aggregated_by=AggregationType.SENTENCE) - tts_text_frame.includes_inter_frame_spaces = True - await self.push_frame(tts_text_frame) - # # user transcription reporting # @@ -1363,6 +1300,12 @@ class AWSNovaSonicLLMService(LLMService): if not self._context: # should never happen return + # Nothing to report if no user speech was transcribed (e.g. the prompt + # was text-only, which is the case on the first user turn when the bot + # starts the conversation). + if not self._user_text_buffer: + return + logger.debug(f"User transcription ended") # Report to the upstream user context aggregator that some new user From bad10177d426c99c07c7fa4d3a5d6ddf6fbab457 Mon Sep 17 00:00:00 2001 From: Mark Backman Date: Wed, 18 Mar 2026 16:47:17 -0400 Subject: [PATCH 1017/1060] Add WakePhraseUserTurnStartStrategy (#4064) - Add WakePhraseUserTurnStartStrategy for gating interaction behind wake phrase detection, with timeout and single_activation modes - Add default_user_turn_start_strategies() and default_user_turn_stop_strategies() helper functions - Deprecate WakeCheckFilter in favor of the new strategy - Extend ProcessFrameResult to stop strategies for short-circuit evaluation - Fix MinWordsUserTurnStartStrategy including filtered text in output --- changelog/4064.added.2.md | 1 + changelog/4064.added.md | 1 + changelog/4064.changed.md | 1 + changelog/4064.deprecated.md | 1 + changelog/4064.fixed.md | 1 + examples/foundational/10-wake-phrase.py | 39 +- .../aggregators/llm_response_universal.py | 9 + .../processors/filters/wake_check_filter.py | 18 + src/pipecat/turns/types.py | 24 ++ src/pipecat/turns/user_start/__init__.py | 2 + .../base_user_turn_start_strategy.py | 12 +- .../external_user_turn_start_strategy.py | 11 +- .../min_words_user_turn_start_strategy.py | 27 +- .../transcription_user_turn_start_strategy.py | 12 +- .../vad_user_turn_start_strategy.py | 11 +- .../wake_phrase_user_turn_start_strategy.py | 281 ++++++++++++++ .../user_stop/base_user_turn_stop_strategy.py | 7 +- .../external_user_turn_stop_strategy.py | 7 +- .../speech_timeout_user_turn_stop_strategy.py | 7 +- .../turn_analyzer_user_turn_stop_strategy.py | 8 +- src/pipecat/turns/user_turn_controller.py | 19 +- src/pipecat/turns/user_turn_strategies.py | 29 +- ...st_wake_phrase_user_turn_start_strategy.py | 346 ++++++++++++++++++ 23 files changed, 835 insertions(+), 39 deletions(-) create mode 100644 changelog/4064.added.2.md create mode 100644 changelog/4064.added.md create mode 100644 changelog/4064.changed.md create mode 100644 changelog/4064.deprecated.md create mode 100644 changelog/4064.fixed.md create mode 100644 src/pipecat/turns/types.py create mode 100644 src/pipecat/turns/user_start/wake_phrase_user_turn_start_strategy.py create mode 100644 tests/test_wake_phrase_user_turn_start_strategy.py diff --git a/changelog/4064.added.2.md b/changelog/4064.added.2.md new file mode 100644 index 000000000..f2dc79a16 --- /dev/null +++ b/changelog/4064.added.2.md @@ -0,0 +1 @@ +- Added `default_user_turn_start_strategies()` and `default_user_turn_stop_strategies()` helper functions for composing custom strategy lists. diff --git a/changelog/4064.added.md b/changelog/4064.added.md new file mode 100644 index 000000000..5c28bde94 --- /dev/null +++ b/changelog/4064.added.md @@ -0,0 +1 @@ +- Added `WakePhraseUserTurnStartStrategy` for triggering user turns based on wake phrases, with support for `single_activation` mode. Deprecates `WakeCheckFilter`. diff --git a/changelog/4064.changed.md b/changelog/4064.changed.md new file mode 100644 index 000000000..c66263fbe --- /dev/null +++ b/changelog/4064.changed.md @@ -0,0 +1 @@ +- Extended `ProcessFrameResult` to stop strategies, allowing a stop strategy to short-circuit evaluation of subsequent strategies by returning `STOP`. diff --git a/changelog/4064.deprecated.md b/changelog/4064.deprecated.md new file mode 100644 index 000000000..b5f42c215 --- /dev/null +++ b/changelog/4064.deprecated.md @@ -0,0 +1 @@ +- Deprecated `WakeCheckFilter` in favor of `WakePhraseUserTurnStartStrategy`. diff --git a/changelog/4064.fixed.md b/changelog/4064.fixed.md new file mode 100644 index 000000000..6824ce26f --- /dev/null +++ b/changelog/4064.fixed.md @@ -0,0 +1 @@ +- Fixed `MinWordsUserTurnStartStrategy` including text below the word threshold in the output by resetting aggregation when the minimum word count is not met. diff --git a/examples/foundational/10-wake-phrase.py b/examples/foundational/10-wake-phrase.py index 0a4244c33..5b93efb0e 100644 --- a/examples/foundational/10-wake-phrase.py +++ b/examples/foundational/10-wake-phrase.py @@ -19,7 +19,6 @@ from pipecat.processors.aggregators.llm_response_universal import ( LLMContextAggregatorPair, LLMUserAggregatorParams, ) -from pipecat.processors.filters.wake_check_filter import WakeCheckFilter from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport from pipecat.services.cartesia.tts import CartesiaTTSService @@ -28,6 +27,11 @@ from pipecat.services.openai.llm import OpenAILLMService from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams +from pipecat.turns.user_start import WakePhraseUserTurnStartStrategy +from pipecat.turns.user_turn_strategies import ( + UserTurnStrategies, + default_user_turn_start_strategies, +) load_dotenv(override=True) @@ -52,7 +56,12 @@ transport_params = { async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): logger.info(f"Starting bot") - stt = DeepgramSTTService(api_key=os.getenv("DEEPGRAM_API_KEY")) + stt = DeepgramSTTService( + api_key=os.getenv("DEEPGRAM_API_KEY"), + settings=DeepgramSTTService.Settings( + keyterm=["pipecat"], + ), + ) tts = CartesiaTTSService( api_key=os.getenv("CARTESIA_API_KEY"), @@ -68,19 +77,28 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): ), ) - hey_robot_filter = WakeCheckFilter(["hey robot", "hey, robot"]) - context = LLMContext() user_aggregator, assistant_aggregator = LLMContextAggregatorPair( context, - user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()), + user_params=LLMUserAggregatorParams( + user_turn_strategies=UserTurnStrategies( + start=[ + WakePhraseUserTurnStartStrategy( + phrases=["pipecat"], + # Timeout before wake phrase must be spoken again + timeout=5.0, + ), + *default_user_turn_start_strategies(), + ] + ), + vad_analyzer=SileroVADAnalyzer(), + ), ) pipeline = Pipeline( [ transport.input(), # Transport user input - stt, # STT - hey_robot_filter, # Filter out speech not directed at the robot + stt, user_aggregator, # User responses llm, # LLM tts, # TTS @@ -102,12 +120,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): async def on_client_connected(transport, client): logger.info(f"Client connected") # Kick off the conversation. - context.add_message( - { - "role": "user", - "content": "Please introduce yourself. Tell the user they should say 'Hey Robot' before talking to you.", - } - ) + context.add_message({"role": "user", "content": "Please introduce yourself to the user."}) await task.queue_frames([LLMRunFrame()]) @transport.event_handler("on_client_disconnected") diff --git a/src/pipecat/processors/aggregators/llm_response_universal.py b/src/pipecat/processors/aggregators/llm_response_universal.py index b8a7061d8..605db31f6 100644 --- a/src/pipecat/processors/aggregators/llm_response_universal.py +++ b/src/pipecat/processors/aggregators/llm_response_universal.py @@ -447,6 +447,9 @@ class LLMUserAggregator(LLMContextAggregator): self._user_turn_controller.add_event_handler( "on_user_turn_stop_timeout", self._on_user_turn_stop_timeout ) + self._user_turn_controller.add_event_handler( + "on_reset_aggregation", self._on_reset_aggregation + ) self._user_idle_controller = UserIdleController( user_idle_timeout=self._params.user_idle_timeout @@ -748,6 +751,12 @@ class LLMUserAggregator(LLMContextAggregator): await self._maybe_emit_user_turn_stopped(strategy) + async def _on_reset_aggregation( + self, controller: UserTurnController, strategy: BaseUserTurnStartStrategy + ): + logger.debug(f"{self}: Resetting aggregation (strategy: {strategy})") + await self.reset() + async def _on_user_turn_stop_timeout(self, controller): await self._call_event_handler("on_user_turn_stop_timeout") diff --git a/src/pipecat/processors/filters/wake_check_filter.py b/src/pipecat/processors/filters/wake_check_filter.py index ec8f31f53..6a9e524e6 100644 --- a/src/pipecat/processors/filters/wake_check_filter.py +++ b/src/pipecat/processors/filters/wake_check_filter.py @@ -6,6 +6,9 @@ """Wake phrase detection filter for Pipecat transcription processing. +.. deprecated:: 0.0.106 + Use :class:`~pipecat.turns.user_start.WakePhraseUserTurnStartStrategy` instead. + This module provides a frame processor that filters transcription frames, only allowing them through after wake phrases have been detected. Includes keepalive functionality to maintain conversation flow after wake detection. @@ -13,6 +16,7 @@ keepalive functionality to maintain conversation flow after wake detection. import re import time +import warnings from enum import Enum from typing import List @@ -25,6 +29,11 @@ from pipecat.processors.frame_processor import FrameDirection, FrameProcessor class WakeCheckFilter(FrameProcessor): """Frame processor that filters transcription frames based on wake phrase detection. + .. deprecated:: 0.0.106 + Use :class:`~pipecat.turns.user_start.WakePhraseUserTurnStartStrategy` instead, + which integrates with the user turn strategy system and supports configurable + timeouts and single-activation mode. + This filter monitors transcription frames for configured wake phrases and only passes frames through after a wake phrase has been detected. Maintains a keepalive timeout to allow continued conversation after wake detection. @@ -65,12 +74,21 @@ class WakeCheckFilter(FrameProcessor): def __init__(self, wake_phrases: List[str], keepalive_timeout: float = 3): """Initialize the wake phrase filter. + .. deprecated:: 0.0.106 + Use :class:`~pipecat.turns.user_start.WakePhraseUserTurnStartStrategy` instead. + Args: wake_phrases: List of wake phrases to detect in transcriptions. keepalive_timeout: Duration in seconds to keep passing frames after wake detection. Defaults to 3 seconds. """ super().__init__() + warnings.warn( + "WakeCheckFilter is deprecated since v0.0.106. " + "Use WakePhraseUserTurnStartStrategy instead.", + DeprecationWarning, + stacklevel=2, + ) self._participant_states = {} self._keepalive_timeout = keepalive_timeout self._wake_patterns = [] diff --git a/src/pipecat/turns/types.py b/src/pipecat/turns/types.py new file mode 100644 index 000000000..5ebdf20a3 --- /dev/null +++ b/src/pipecat/turns/types.py @@ -0,0 +1,24 @@ +# +# Copyright (c) 2024-2026, Daily +# +# SPDX-License-Identifier: BSD 2-Clause License +# + +"""Shared result type for user turn strategy frame processing.""" + +from enum import Enum + + +class ProcessFrameResult(Enum): + """Result of processing a frame in a user turn strategy. + + Controls whether the strategy loop in the controller continues to the + next strategy or stops early. + + Attributes: + CONTINUE: Continue to the next strategy in the loop. + STOP: Stop evaluating further strategies for this frame. + """ + + CONTINUE = "continue" + STOP = "stop" diff --git a/src/pipecat/turns/user_start/__init__.py b/src/pipecat/turns/user_start/__init__.py index fb84f62ed..94d12708d 100644 --- a/src/pipecat/turns/user_start/__init__.py +++ b/src/pipecat/turns/user_start/__init__.py @@ -9,6 +9,7 @@ from .external_user_turn_start_strategy import ExternalUserTurnStartStrategy from .min_words_user_turn_start_strategy import MinWordsUserTurnStartStrategy from .transcription_user_turn_start_strategy import TranscriptionUserTurnStartStrategy from .vad_user_turn_start_strategy import VADUserTurnStartStrategy +from .wake_phrase_user_turn_start_strategy import WakePhraseUserTurnStartStrategy __all__ = [ "BaseUserTurnStartStrategy", @@ -17,4 +18,5 @@ __all__ = [ "TranscriptionUserTurnStartStrategy", "UserTurnStartedParams", "VADUserTurnStartStrategy", + "WakePhraseUserTurnStartStrategy", ] diff --git a/src/pipecat/turns/user_start/base_user_turn_start_strategy.py b/src/pipecat/turns/user_start/base_user_turn_start_strategy.py index 25f5c8303..fd928a8a7 100644 --- a/src/pipecat/turns/user_start/base_user_turn_start_strategy.py +++ b/src/pipecat/turns/user_start/base_user_turn_start_strategy.py @@ -11,6 +11,7 @@ from typing import Optional, Type from pipecat.frames.frames import Frame from pipecat.processors.frame_processor import FrameDirection +from pipecat.turns.types import ProcessFrameResult from pipecat.utils.asyncio.task_manager import BaseTaskManager from pipecat.utils.base_object import BaseObject @@ -76,6 +77,7 @@ class BaseUserTurnStartStrategy(BaseObject): self._register_event_handler("on_push_frame", sync=True) self._register_event_handler("on_broadcast_frame", sync=True) self._register_event_handler("on_user_turn_started", sync=True) + self._register_event_handler("on_reset_aggregation", sync=True) @property def task_manager(self) -> BaseTaskManager: @@ -100,7 +102,7 @@ class BaseUserTurnStartStrategy(BaseObject): """Reset the strategy to its initial state.""" pass - async def process_frame(self, frame: Frame): + async def process_frame(self, frame: Frame) -> ProcessFrameResult: """Process an incoming frame. Subclasses should override this to implement logic that decides whether @@ -108,6 +110,10 @@ class BaseUserTurnStartStrategy(BaseObject): Args: frame: The frame to be processed. + + Returns: + A ProcessFrameResult indicating the outcome. Subclasses that return + None are treated as CONTINUE for backward compatibility. """ pass @@ -138,3 +144,7 @@ class BaseUserTurnStartStrategy(BaseObject): enable_user_speaking_frames=self._enable_user_speaking_frames, ), ) + + async def trigger_reset_aggregation(self): + """Trigger the `on_reset_aggregation` event.""" + await self._call_event_handler("on_reset_aggregation") diff --git a/src/pipecat/turns/user_start/external_user_turn_start_strategy.py b/src/pipecat/turns/user_start/external_user_turn_start_strategy.py index 9a85cad6d..1031a6b46 100644 --- a/src/pipecat/turns/user_start/external_user_turn_start_strategy.py +++ b/src/pipecat/turns/user_start/external_user_turn_start_strategy.py @@ -7,6 +7,7 @@ """User turn start strategy triggered by externally emitted frames.""" from pipecat.frames.frames import Frame, UserStartedSpeakingFrame +from pipecat.turns.types import ProcessFrameResult from pipecat.turns.user_start.base_user_turn_start_strategy import BaseUserTurnStartStrategy @@ -27,13 +28,17 @@ class ExternalUserTurnStartStrategy(BaseUserTurnStartStrategy): """ super().__init__(enable_interruptions=False, enable_user_speaking_frames=False, **kwargs) - async def process_frame(self, frame: Frame): + async def process_frame(self, frame: Frame) -> ProcessFrameResult: """Process an incoming frame to detect user turn start. Args: frame: The frame to be analyzed. - """ - await super().process_frame(frame) + Returns: + STOP if a user started speaking frame was received, CONTINUE otherwise. + """ if isinstance(frame, UserStartedSpeakingFrame): await self.trigger_user_turn_started() + return ProcessFrameResult.STOP + + return ProcessFrameResult.CONTINUE diff --git a/src/pipecat/turns/user_start/min_words_user_turn_start_strategy.py b/src/pipecat/turns/user_start/min_words_user_turn_start_strategy.py index 57a0ca0d8..10bcfcdad 100644 --- a/src/pipecat/turns/user_start/min_words_user_turn_start_strategy.py +++ b/src/pipecat/turns/user_start/min_words_user_turn_start_strategy.py @@ -15,6 +15,7 @@ from pipecat.frames.frames import ( InterimTranscriptionFrame, TranscriptionFrame, ) +from pipecat.turns.types import ProcessFrameResult from pipecat.turns.user_start.base_user_turn_start_strategy import BaseUserTurnStartStrategy @@ -47,7 +48,7 @@ class MinWordsUserTurnStartStrategy(BaseUserTurnStartStrategy): await super().reset() self._bot_speaking = False - async def process_frame(self, frame: Frame): + async def process_frame(self, frame: Frame) -> ProcessFrameResult: """Process an incoming frame to detect the start of a user turn. This method updates internal state based on transcription frames and @@ -55,17 +56,20 @@ class MinWordsUserTurnStartStrategy(BaseUserTurnStartStrategy): Args: frame: The frame to be analyzed. - """ - await super().process_frame(frame) + Returns: + STOP if the minimum word count was reached, CONTINUE otherwise. + """ if isinstance(frame, BotStartedSpeakingFrame): await self._handle_bot_started_speaking(frame) elif isinstance(frame, BotStoppedSpeakingFrame): await self._handle_bot_stopped_speaking(frame) elif isinstance(frame, TranscriptionFrame): - await self._handle_transcription(frame) + return await self._handle_transcription(frame) elif isinstance(frame, InterimTranscriptionFrame) and self._use_interim: - await self._handle_transcription(frame) + return await self._handle_transcription(frame) + + return ProcessFrameResult.CONTINUE async def _handle_bot_started_speaking(self, frame: BotStartedSpeakingFrame): """Handle bot started speaking frame. @@ -87,11 +91,16 @@ class MinWordsUserTurnStartStrategy(BaseUserTurnStartStrategy): """ self._bot_speaking = False - async def _handle_transcription(self, frame: TranscriptionFrame | InterimTranscriptionFrame): - """Handle a completed transcription frame and check word count. + async def _handle_transcription( + self, frame: TranscriptionFrame | InterimTranscriptionFrame + ) -> ProcessFrameResult: + """Handle a transcription frame and check word count. Args: frame: The transcription frame to be processed. + + Returns: + STOP if the minimum word count was reached, CONTINUE otherwise. """ min_words = self._min_words if self._bot_speaking else 1 @@ -106,3 +115,7 @@ class MinWordsUserTurnStartStrategy(BaseUserTurnStartStrategy): if should_trigger: await self.trigger_user_turn_started() + return ProcessFrameResult.STOP + await self.trigger_reset_aggregation() + + return ProcessFrameResult.CONTINUE diff --git a/src/pipecat/turns/user_start/transcription_user_turn_start_strategy.py b/src/pipecat/turns/user_start/transcription_user_turn_start_strategy.py index b69b127ea..34a3e83e6 100644 --- a/src/pipecat/turns/user_start/transcription_user_turn_start_strategy.py +++ b/src/pipecat/turns/user_start/transcription_user_turn_start_strategy.py @@ -7,6 +7,7 @@ """User turn start strategy based on transcriptions.""" from pipecat.frames.frames import Frame, InterimTranscriptionFrame, TranscriptionFrame +from pipecat.turns.types import ProcessFrameResult from pipecat.turns.user_start.base_user_turn_start_strategy import BaseUserTurnStartStrategy @@ -25,15 +26,20 @@ class TranscriptionUserTurnStartStrategy(BaseUserTurnStartStrategy): super().__init__(**kwargs) self._use_interim = use_interim - async def process_frame(self, frame: Frame): + async def process_frame(self, frame: Frame) -> ProcessFrameResult: """Process an incoming frame to detect the start of a user turn. Args: frame: The frame to be processed. - """ - await super().process_frame(frame) + Returns: + STOP if a transcription was received, CONTINUE otherwise. + """ if isinstance(frame, InterimTranscriptionFrame) and self._use_interim: await self.trigger_user_turn_started() + return ProcessFrameResult.STOP elif isinstance(frame, TranscriptionFrame): await self.trigger_user_turn_started() + return ProcessFrameResult.STOP + + return ProcessFrameResult.CONTINUE diff --git a/src/pipecat/turns/user_start/vad_user_turn_start_strategy.py b/src/pipecat/turns/user_start/vad_user_turn_start_strategy.py index 4bdf48594..2bc3875e0 100644 --- a/src/pipecat/turns/user_start/vad_user_turn_start_strategy.py +++ b/src/pipecat/turns/user_start/vad_user_turn_start_strategy.py @@ -7,6 +7,7 @@ """User turn start strategy based on VAD events.""" from pipecat.frames.frames import Frame, VADUserStartedSpeakingFrame +from pipecat.turns.types import ProcessFrameResult from pipecat.turns.user_start.base_user_turn_start_strategy import BaseUserTurnStartStrategy @@ -18,13 +19,17 @@ class VADUserTurnStartStrategy(BaseUserTurnStartStrategy): """ - async def process_frame(self, frame: Frame): + async def process_frame(self, frame: Frame) -> ProcessFrameResult: """Process an incoming frame to detect user turn start. Args: frame: The frame to be analyzed. - """ - await super().process_frame(frame) + Returns: + STOP if the user started speaking, CONTINUE otherwise. + """ if isinstance(frame, VADUserStartedSpeakingFrame): await self.trigger_user_turn_started() + return ProcessFrameResult.STOP + + return ProcessFrameResult.CONTINUE diff --git a/src/pipecat/turns/user_start/wake_phrase_user_turn_start_strategy.py b/src/pipecat/turns/user_start/wake_phrase_user_turn_start_strategy.py new file mode 100644 index 000000000..bcc069ad7 --- /dev/null +++ b/src/pipecat/turns/user_start/wake_phrase_user_turn_start_strategy.py @@ -0,0 +1,281 @@ +# +# Copyright (c) 2024-2026, Daily +# +# SPDX-License-Identifier: BSD 2-Clause License +# + +"""User turn start strategy that gates interaction behind wake phrase detection.""" + +import asyncio +import enum +import re +from typing import List, Optional + +from loguru import logger + +from pipecat.frames.frames import ( + BotSpeakingFrame, + Frame, + TranscriptionFrame, + UserSpeakingFrame, + VADUserStartedSpeakingFrame, +) +from pipecat.turns.types import ProcessFrameResult +from pipecat.turns.user_start.base_user_turn_start_strategy import BaseUserTurnStartStrategy +from pipecat.utils.asyncio.task_manager import BaseTaskManager + + +class _WakeState(enum.Enum): + """Internal state for wake phrase detection.""" + + IDLE = "idle" + AWAKE = "awake" + + +class WakePhraseUserTurnStartStrategy(BaseUserTurnStartStrategy): + """User turn start strategy that requires a wake phrase before interaction. + + Blocks subsequent strategies until a wake phrase is detected in a final + transcription. After detection, allows interaction for a configurable + timeout period before requiring the wake phrase again. Use + ``single_activation=True`` to require the wake phrase before every turn. + + This strategy should be placed first in the start strategies list. + + Event handlers available: + + - on_wake_phrase_detected: Called when a wake phrase is matched. + - on_wake_phrase_timeout: Called when the inactivity timeout expires + (timeout mode only). + + Example:: + + # Timeout mode (default): wake phrase unlocks interaction for 10s + strategy = WakePhraseUserTurnStartStrategy( + phrases=["hey pipecat", "ok pipecat"], + timeout=10.0, + ) + + # Single activation: wake phrase required before every turn + strategy = WakePhraseUserTurnStartStrategy( + phrases=["hey pipecat"], + single_activation=True, + ) + + @strategy.event_handler("on_wake_phrase_detected") + async def on_wake_phrase_detected(strategy, phrase): + ... + + @strategy.event_handler("on_wake_phrase_timeout") + async def on_wake_phrase_timeout(strategy): + ... + + Args: + phrases: List of wake phrases to detect. + timeout: Inactivity timeout in seconds before returning to IDLE. + In timeout mode, the timer resets on activity (user, bot speech). + In single activation mode, acts as a keepalive window — the strategy + stays AWAKE for this duration after wake phrase detection, allowing + the current turn to complete before returning to IDLE. + single_activation: If True, the wake phrase is required before every + turn. The strategy returns to IDLE after each turn completes. + **kwargs: Additional keyword arguments passed to parent. + """ + + def __init__( + self, + *, + phrases: List[str], + timeout: float = 10.0, + single_activation: bool = False, + **kwargs, + ): + """Initialize the wake phrase user turn start strategy. + + Args: + phrases: List of wake phrases to detect. + timeout: Inactivity timeout in seconds before returning to IDLE. + In timeout mode, the timer resets on activity. In single activation + mode, acts as a keepalive window after wake phrase detection. + single_activation: If True, the wake phrase is required before every + turn. The strategy returns to IDLE after each turn completes. + **kwargs: Additional keyword arguments passed to parent. + """ + super().__init__(**kwargs) + self._phrases = phrases + self._timeout = timeout + self._single_activation = single_activation + + self._patterns: List[re.Pattern] = [] + for phrase in phrases: + pattern = re.compile( + r"\b" + r"\s*".join(re.escape(word) for word in phrase.split()) + r"\b", + re.IGNORECASE, + ) + self._patterns.append(pattern) + + self._state = _WakeState.IDLE + self._accumulated_text = "" + + self._timeout_event = asyncio.Event() + self._timeout_task: Optional[asyncio.Task] = None + + self._register_event_handler("on_wake_phrase_detected") + self._register_event_handler("on_wake_phrase_timeout") + + @property + def state(self) -> _WakeState: + """Returns the current wake state.""" + return self._state + + async def setup(self, task_manager: BaseTaskManager): + """Initialize the strategy with the given task manager. + + Args: + task_manager: The task manager to be associated with this instance. + """ + await super().setup(task_manager) + if not self._timeout_task: + self._timeout_task = self.task_manager.create_task( + self._timeout_task_handler(), + f"{self}::_timeout_task_handler", + ) + + async def cleanup(self): + """Cleanup the strategy.""" + await super().cleanup() + if self._timeout_task: + await self.task_manager.cancel_task(self._timeout_task) + self._timeout_task = None + + async def reset(self): + """Reset the strategy. + + In timeout mode, preserves state and refreshes timeout since reset + means a turn started (activity). In single activation mode, does + nothing — the keepalive timeout (started when the wake phrase was + detected) handles the transition back to IDLE. + """ + await super().reset() + if self._state == _WakeState.AWAKE: + if not self._single_activation: + self._refresh_timeout() + + async def process_frame(self, frame: Frame) -> ProcessFrameResult: + """Process an incoming frame for wake phrase detection or passthrough. + + Args: + frame: The frame to be processed. + + Returns: + STOP when the wake phrase is detected or when in IDLE state + (blocks subsequent strategies), CONTINUE when in AWAKE state + (allows subsequent strategies to proceed). + """ + await super().process_frame(frame) + + if self._state == _WakeState.IDLE: + return await self._process_idle(frame) + else: + return await self._process_awake(frame) + + async def _process_idle(self, frame: Frame) -> ProcessFrameResult: + """Process a frame while in IDLE state. + + Only final ``TranscriptionFrame`` instances are checked for wake phrase + matches. When a match is found, a user turn start is triggered. + Transcription frames that don't match have their text cleared so that + pre-wake-phrase speech is not added to the LLM context. All frames + return STOP to block subsequent strategies. + """ + if isinstance(frame, TranscriptionFrame): + if self._check_wake_phrase(frame.text): + await self.trigger_user_turn_started() + return ProcessFrameResult.STOP + await self.trigger_reset_aggregation() + + return ProcessFrameResult.STOP + + async def _process_awake(self, frame: Frame) -> ProcessFrameResult: + """Process a frame while in AWAKE state. + + Refreshes the timeout on activity frames (timeout mode only). Returns + CONTINUE so subsequent strategies can process the frame. + """ + if not self._single_activation: + if isinstance(frame, (UserSpeakingFrame, BotSpeakingFrame)): + self._refresh_timeout() + elif isinstance(frame, TranscriptionFrame): + self._refresh_timeout() + elif isinstance(frame, VADUserStartedSpeakingFrame): + self._refresh_timeout() + + return ProcessFrameResult.CONTINUE + + @staticmethod + def _strip_punctuation(text: str) -> str: + """Strip punctuation from text, keeping only letters, digits, and whitespace.""" + return re.sub(r"[^\w\s]", "", text) + + def _check_wake_phrase(self, text: str) -> bool: + """Check if the accumulated text contains a wake phrase. + + Punctuation is stripped before matching so that STT output like + "Hey, Pipecat!" still matches the phrase "hey pipecat". + + Args: + text: New transcription text to append and check. + + Returns: + True if a wake phrase was found, False otherwise. + """ + self._accumulated_text += " " + self._strip_punctuation(text) + # Cap accumulated text to prevent unbounded growth. + if len(self._accumulated_text) > 250: + self._accumulated_text = self._accumulated_text[-250:] + + for i, pattern in enumerate(self._patterns): + if pattern.search(self._accumulated_text): + phrase = self._phrases[i] + logger.debug(f"{self} wake phrase detected: {phrase!r}") + self._transition_to_awake(phrase) + return True + + return False + + def _transition_to_awake(self, phrase: str): + """Transition from IDLE to AWAKE state.""" + self._state = _WakeState.AWAKE + self._accumulated_text = "" + self._refresh_timeout() + self.task_manager.create_task( + self._call_event_handler("on_wake_phrase_detected", phrase), + f"{self}::on_wake_phrase_detected", + ) + + def _transition_to_idle(self): + """Transition from AWAKE to IDLE state.""" + logger.debug(f"{self} wake phrase timeout, returning to IDLE") + self._state = _WakeState.IDLE + self._accumulated_text = "" + self.task_manager.create_task( + self._call_event_handler("on_wake_phrase_timeout"), + f"{self}::on_wake_phrase_timeout", + ) + + def _refresh_timeout(self): + """Refresh the inactivity timeout.""" + self._timeout_event.set() + + async def _timeout_task_handler(self): + """Background task that monitors inactivity timeout.""" + while True: + try: + await asyncio.wait_for( + self._timeout_event.wait(), + timeout=self._timeout, + ) + self._timeout_event.clear() + except asyncio.TimeoutError: + if self._state == _WakeState.AWAKE: + self._transition_to_idle() diff --git a/src/pipecat/turns/user_stop/base_user_turn_stop_strategy.py b/src/pipecat/turns/user_stop/base_user_turn_stop_strategy.py index c0042f902..7c493475e 100644 --- a/src/pipecat/turns/user_stop/base_user_turn_stop_strategy.py +++ b/src/pipecat/turns/user_stop/base_user_turn_stop_strategy.py @@ -11,6 +11,7 @@ from typing import Optional, Type from pipecat.frames.frames import Frame from pipecat.processors.frame_processor import FrameDirection +from pipecat.turns.types import ProcessFrameResult from pipecat.utils.asyncio.task_manager import BaseTaskManager from pipecat.utils.base_object import BaseObject @@ -89,7 +90,7 @@ class BaseUserTurnStopStrategy(BaseObject): """Reset the strategy to its initial state.""" pass - async def process_frame(self, frame: Frame): + async def process_frame(self, frame: Frame) -> ProcessFrameResult: """Process an incoming frame to decide whether the user stopped speaking. Subclasses should override this to implement logic that decides whether @@ -97,6 +98,10 @@ class BaseUserTurnStopStrategy(BaseObject): Args: frame: The frame to be analyzed. + + Returns: + A ProcessFrameResult indicating the outcome. Subclasses that return + None are treated as CONTINUE for backward compatibility. """ pass diff --git a/src/pipecat/turns/user_stop/external_user_turn_stop_strategy.py b/src/pipecat/turns/user_stop/external_user_turn_stop_strategy.py index 58e037fbf..4ffa3360b 100644 --- a/src/pipecat/turns/user_stop/external_user_turn_stop_strategy.py +++ b/src/pipecat/turns/user_stop/external_user_turn_stop_strategy.py @@ -16,6 +16,7 @@ from pipecat.frames.frames import ( UserStartedSpeakingFrame, UserStoppedSpeakingFrame, ) +from pipecat.turns.types import ProcessFrameResult from pipecat.turns.user_stop.base_user_turn_stop_strategy import BaseUserTurnStopStrategy from pipecat.utils.asyncio.task_manager import BaseTaskManager @@ -69,7 +70,7 @@ class ExternalUserTurnStopStrategy(BaseUserTurnStopStrategy): await self.task_manager.cancel_task(self._task) self._task = None - async def process_frame(self, frame: Frame): + async def process_frame(self, frame: Frame) -> ProcessFrameResult: """Process an incoming frame to update strategy state. Updates internal transcription text and VAD state. The user end turn @@ -78,6 +79,8 @@ class ExternalUserTurnStopStrategy(BaseUserTurnStopStrategy): Args: frame: The frame to be analyzed. + Returns: + Always returns CONTINUE so subsequent stop strategies are evaluated. """ if isinstance(frame, UserStartedSpeakingFrame): await self._handle_user_started_speaking(frame) @@ -88,6 +91,8 @@ class ExternalUserTurnStopStrategy(BaseUserTurnStopStrategy): elif isinstance(frame, TranscriptionFrame): await self._handle_transcription(frame) + return ProcessFrameResult.CONTINUE + async def _handle_user_started_speaking(self, _: UserStartedSpeakingFrame): """Handle when the external service indicates the user is speaking.""" self._user_speaking = True diff --git a/src/pipecat/turns/user_stop/speech_timeout_user_turn_stop_strategy.py b/src/pipecat/turns/user_stop/speech_timeout_user_turn_stop_strategy.py index ec94d9176..341a4c1e3 100644 --- a/src/pipecat/turns/user_stop/speech_timeout_user_turn_stop_strategy.py +++ b/src/pipecat/turns/user_stop/speech_timeout_user_turn_stop_strategy.py @@ -17,6 +17,7 @@ from pipecat.frames.frames import ( VADUserStartedSpeakingFrame, VADUserStoppedSpeakingFrame, ) +from pipecat.turns.types import ProcessFrameResult from pipecat.turns.user_stop.base_user_turn_stop_strategy import BaseUserTurnStopStrategy from pipecat.utils.asyncio.task_manager import BaseTaskManager @@ -83,7 +84,7 @@ class SpeechTimeoutUserTurnStopStrategy(BaseUserTurnStopStrategy): await self.task_manager.cancel_task(self._timeout_task) self._timeout_task = None - async def process_frame(self, frame: Frame): + async def process_frame(self, frame: Frame) -> ProcessFrameResult: """Process an incoming frame to update strategy state. Updates internal transcription text and VAD state. The user end turn @@ -92,6 +93,8 @@ class SpeechTimeoutUserTurnStopStrategy(BaseUserTurnStopStrategy): Args: frame: The frame to be analyzed. + Returns: + Always returns CONTINUE so subsequent stop strategies are evaluated. """ if isinstance(frame, STTMetadataFrame): self._stt_timeout = frame.ttfs_p99_latency @@ -102,6 +105,8 @@ class SpeechTimeoutUserTurnStopStrategy(BaseUserTurnStopStrategy): elif isinstance(frame, TranscriptionFrame): await self._handle_transcription(frame) + return ProcessFrameResult.CONTINUE + async def _handle_vad_user_started_speaking(self, _: VADUserStartedSpeakingFrame): """Handle when the VAD indicates the user is speaking.""" self._vad_user_speaking = True diff --git a/src/pipecat/turns/user_stop/turn_analyzer_user_turn_stop_strategy.py b/src/pipecat/turns/user_stop/turn_analyzer_user_turn_stop_strategy.py index 232bde223..a0df2efbb 100644 --- a/src/pipecat/turns/user_stop/turn_analyzer_user_turn_stop_strategy.py +++ b/src/pipecat/turns/user_stop/turn_analyzer_user_turn_stop_strategy.py @@ -22,6 +22,7 @@ from pipecat.frames.frames import ( VADUserStoppedSpeakingFrame, ) from pipecat.metrics.metrics import MetricsData +from pipecat.turns.types import ProcessFrameResult from pipecat.turns.user_stop.base_user_turn_stop_strategy import BaseUserTurnStopStrategy from pipecat.utils.asyncio.task_manager import BaseTaskManager @@ -88,11 +89,14 @@ class TurnAnalyzerUserTurnStopStrategy(BaseUserTurnStopStrategy): await self.task_manager.cancel_task(self._timeout_task) self._timeout_task = None - async def process_frame(self, frame: Frame): + async def process_frame(self, frame: Frame) -> ProcessFrameResult: """Process an incoming frame to update the turn analyzer and strategy state. Args: frame: The frame to be analyzed. + + Returns: + Always returns CONTINUE so subsequent stop strategies are evaluated. """ await super().process_frame(frame) @@ -109,6 +113,8 @@ class TurnAnalyzerUserTurnStopStrategy(BaseUserTurnStopStrategy): elif isinstance(frame, TranscriptionFrame): await self._handle_transcription(frame) + return ProcessFrameResult.CONTINUE + async def _start(self, frame: StartFrame): """Process the start frame to configure the turn analyzer.""" self._turn_analyzer.set_sample_rate(frame.audio_in_sample_rate) diff --git a/src/pipecat/turns/user_turn_controller.py b/src/pipecat/turns/user_turn_controller.py index a064fc47b..9abed3932 100644 --- a/src/pipecat/turns/user_turn_controller.py +++ b/src/pipecat/turns/user_turn_controller.py @@ -19,7 +19,11 @@ from pipecat.frames.frames import ( VADUserStoppedSpeakingFrame, ) from pipecat.processors.frame_processor import FrameDirection -from pipecat.turns.user_start import BaseUserTurnStartStrategy, UserTurnStartedParams +from pipecat.turns.types import ProcessFrameResult +from pipecat.turns.user_start import ( + BaseUserTurnStartStrategy, + UserTurnStartedParams, +) from pipecat.turns.user_stop import BaseUserTurnStopStrategy, UserTurnStoppedParams from pipecat.turns.user_turn_strategies import UserTurnStrategies from pipecat.utils.asyncio.task_manager import BaseTaskManager @@ -94,6 +98,7 @@ class UserTurnController(BaseObject): self._register_event_handler("on_user_turn_started", sync=True) self._register_event_handler("on_user_turn_stopped", sync=True) self._register_event_handler("on_user_turn_stop_timeout", sync=True) + self._register_event_handler("on_reset_aggregation", sync=True) @property def task_manager(self) -> BaseTaskManager: @@ -161,10 +166,14 @@ class UserTurnController(BaseObject): await self._handle_transcription(frame) for strategy in self._user_turn_strategies.start or []: - await strategy.process_frame(frame) + result = await strategy.process_frame(frame) + if result == ProcessFrameResult.STOP: + break for strategy in self._user_turn_strategies.stop or []: - await strategy.process_frame(frame) + result = await strategy.process_frame(frame) + if result == ProcessFrameResult.STOP: + break async def _setup_strategies(self): for s in self._user_turn_strategies.start or []: @@ -172,6 +181,7 @@ class UserTurnController(BaseObject): s.add_event_handler("on_push_frame", self._on_push_frame) s.add_event_handler("on_broadcast_frame", self._on_broadcast_frame) s.add_event_handler("on_user_turn_started", self._on_user_turn_started) + s.add_event_handler("on_reset_aggregation", self._on_reset_aggregation) for s in self._user_turn_strategies.stop or []: await s.setup(self.task_manager) @@ -242,6 +252,9 @@ class UserTurnController(BaseObject): ): await self._trigger_user_turn_stop(strategy, params) + async def _on_reset_aggregation(self, strategy: BaseUserTurnStartStrategy): + await self._call_event_handler("on_reset_aggregation", strategy) + async def _trigger_user_turn_start( self, strategy: Optional[BaseUserTurnStartStrategy], params: UserTurnStartedParams ): diff --git a/src/pipecat/turns/user_turn_strategies.py b/src/pipecat/turns/user_turn_strategies.py index 0435f141c..5789c6328 100644 --- a/src/pipecat/turns/user_turn_strategies.py +++ b/src/pipecat/turns/user_turn_strategies.py @@ -23,6 +23,31 @@ from pipecat.turns.user_stop import ( ) +def default_user_turn_start_strategies() -> List[BaseUserTurnStartStrategy]: + """Return the default user turn start strategies. + + Returns ``[VADUserTurnStartStrategy, TranscriptionUserTurnStartStrategy]``. + Useful when building a custom strategy list that extends the defaults. + + Example:: + + start_strategies = [ + WakePhraseUserTurnStartStrategy(phrases=["hey pipecat"]), + *default_user_turn_start_strategies(), + ] + """ + return [VADUserTurnStartStrategy(), TranscriptionUserTurnStartStrategy()] + + +def default_user_turn_stop_strategies() -> List[BaseUserTurnStopStrategy]: + """Return the default user turn stop strategies. + + Returns ``[TurnAnalyzerUserTurnStopStrategy(LocalSmartTurnAnalyzerV3)]``. + Useful when building a custom strategy list that extends the defaults. + """ + return [TurnAnalyzerUserTurnStopStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3())] + + @dataclass class UserTurnStrategies: """Container for user turn start and stop strategies. @@ -45,9 +70,9 @@ class UserTurnStrategies: def __post_init__(self): if not self.start: - self.start = [VADUserTurnStartStrategy(), TranscriptionUserTurnStartStrategy()] + self.start = default_user_turn_start_strategies() if not self.stop: - self.stop = [TurnAnalyzerUserTurnStopStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3())] + self.stop = default_user_turn_stop_strategies() @dataclass diff --git a/tests/test_wake_phrase_user_turn_start_strategy.py b/tests/test_wake_phrase_user_turn_start_strategy.py new file mode 100644 index 000000000..e79b9ab99 --- /dev/null +++ b/tests/test_wake_phrase_user_turn_start_strategy.py @@ -0,0 +1,346 @@ +# +# Copyright (c) 2024-2026, Daily +# +# SPDX-License-Identifier: BSD 2-Clause License +# + +import asyncio +import unittest + +from pipecat.frames.frames import ( + BotSpeakingFrame, + InterimTranscriptionFrame, + TranscriptionFrame, + UserSpeakingFrame, + VADUserStartedSpeakingFrame, +) +from pipecat.turns.types import ProcessFrameResult +from pipecat.turns.user_start.wake_phrase_user_turn_start_strategy import ( + WakePhraseUserTurnStartStrategy, + _WakeState, +) +from pipecat.utils.asyncio.task_manager import TaskManager, TaskManagerParams + + +class TestWakePhraseUserTurnStartStrategy(unittest.IsolatedAsyncioTestCase): + def _create_strategy(self, **kwargs) -> WakePhraseUserTurnStartStrategy: + kwargs.setdefault("phrases", ["hey pipecat"]) + kwargs.setdefault("timeout", 10.0) + return WakePhraseUserTurnStartStrategy(**kwargs) + + async def _setup_strategy(self, strategy: WakePhraseUserTurnStartStrategy): + task_manager = TaskManager() + loop = asyncio.get_running_loop() + task_manager.setup(TaskManagerParams(loop=loop)) + await strategy.setup(task_manager) + return task_manager + + async def test_wake_phrase_in_final_transcription(self): + strategy = self._create_strategy() + await self._setup_strategy(strategy) + + result = await strategy.process_frame( + TranscriptionFrame(text="hey pipecat", user_id="user1", timestamp="") + ) + self.assertEqual(result, ProcessFrameResult.STOP) + self.assertEqual(strategy.state, _WakeState.AWAKE) + + await strategy.cleanup() + + async def test_interim_transcription_ignored(self): + """Interim transcriptions are never used for wake phrase matching.""" + strategy = self._create_strategy() + await self._setup_strategy(strategy) + + result = await strategy.process_frame( + InterimTranscriptionFrame(text="hey pipecat", user_id="user1", timestamp="") + ) + self.assertEqual(result, ProcessFrameResult.STOP) + self.assertEqual(strategy.state, _WakeState.IDLE) + + await strategy.cleanup() + + async def test_no_wake_phrase_returns_stop(self): + strategy = self._create_strategy() + await self._setup_strategy(strategy) + + result = await strategy.process_frame( + TranscriptionFrame(text="hello world", user_id="user1", timestamp="") + ) + self.assertEqual(result, ProcessFrameResult.STOP) + self.assertEqual(strategy.state, _WakeState.IDLE) + + await strategy.cleanup() + + async def test_non_matching_text_resets_aggregation(self): + """Non-matching transcription triggers aggregation reset to prevent LLM context pollution.""" + strategy = self._create_strategy() + await self._setup_strategy(strategy) + + reset_called = False + + @strategy.event_handler("on_reset_aggregation") + async def on_reset_aggregation(strategy): + nonlocal reset_called + reset_called = True + + await strategy.process_frame( + TranscriptionFrame(text="hello world", user_id="user1", timestamp="") + ) + self.assertTrue(reset_called) + + await strategy.cleanup() + + async def test_vad_frame_returns_stop_in_listening(self): + strategy = self._create_strategy() + await self._setup_strategy(strategy) + + result = await strategy.process_frame(VADUserStartedSpeakingFrame()) + self.assertEqual(result, ProcessFrameResult.STOP) + self.assertEqual(strategy.state, _WakeState.IDLE) + + await strategy.cleanup() + + async def test_inactive_returns_continue(self): + strategy = self._create_strategy() + await self._setup_strategy(strategy) + + # Trigger wake phrase first. + await strategy.process_frame( + TranscriptionFrame(text="hey pipecat", user_id="user1", timestamp="") + ) + self.assertEqual(strategy.state, _WakeState.AWAKE) + + # Subsequent frames should return CONTINUE. + result = await strategy.process_frame(VADUserStartedSpeakingFrame()) + self.assertEqual(result, ProcessFrameResult.CONTINUE) + + result = await strategy.process_frame( + TranscriptionFrame(text="what is the weather", user_id="user1", timestamp="") + ) + self.assertEqual(result, ProcessFrameResult.CONTINUE) + + await strategy.cleanup() + + async def test_accumulation_across_frames(self): + strategy = self._create_strategy() + await self._setup_strategy(strategy) + + result = await strategy.process_frame( + TranscriptionFrame(text="hey", user_id="user1", timestamp="") + ) + self.assertEqual(result, ProcessFrameResult.STOP) + self.assertEqual(strategy.state, _WakeState.IDLE) + + result = await strategy.process_frame( + TranscriptionFrame(text="pipecat", user_id="user1", timestamp="") + ) + self.assertEqual(result, ProcessFrameResult.STOP) + self.assertEqual(strategy.state, _WakeState.AWAKE) + + await strategy.cleanup() + + async def test_multiple_phrases(self): + strategy = self._create_strategy(phrases=["hey pipecat", "ok computer"]) + await self._setup_strategy(strategy) + + result = await strategy.process_frame( + TranscriptionFrame(text="ok computer", user_id="user1", timestamp="") + ) + self.assertEqual(result, ProcessFrameResult.STOP) + self.assertEqual(strategy.state, _WakeState.AWAKE) + + await strategy.cleanup() + + async def test_punctuation_stripped(self): + """STT punctuation like 'Hey, Pipecat!' should still match.""" + strategy = self._create_strategy() + await self._setup_strategy(strategy) + + result = await strategy.process_frame( + TranscriptionFrame(text="Hey, Pipecat!", user_id="user1", timestamp="") + ) + self.assertEqual(result, ProcessFrameResult.STOP) + self.assertEqual(strategy.state, _WakeState.AWAKE) + + await strategy.cleanup() + + async def test_reset_preserves_inactive_state(self): + strategy = self._create_strategy() + await self._setup_strategy(strategy) + + await strategy.process_frame( + TranscriptionFrame(text="hey pipecat", user_id="user1", timestamp="") + ) + self.assertEqual(strategy.state, _WakeState.AWAKE) + + await strategy.reset() + self.assertEqual(strategy.state, _WakeState.AWAKE) + + await strategy.cleanup() + + async def test_timeout_returns_to_listening(self): + strategy = self._create_strategy(timeout=0.1) + await self._setup_strategy(strategy) + + # Trigger wake phrase. + await strategy.process_frame( + TranscriptionFrame(text="hey pipecat", user_id="user1", timestamp="") + ) + self.assertEqual(strategy.state, _WakeState.AWAKE) + + # Wait for timeout to expire. + await asyncio.sleep(0.3) + + self.assertEqual(strategy.state, _WakeState.IDLE) + + await strategy.cleanup() + + async def test_activity_refreshes_timeout(self): + strategy = self._create_strategy(timeout=0.2) + await self._setup_strategy(strategy) + + # Trigger wake phrase. + await strategy.process_frame( + TranscriptionFrame(text="hey pipecat", user_id="user1", timestamp="") + ) + self.assertEqual(strategy.state, _WakeState.AWAKE) + + # Send activity before timeout. + await asyncio.sleep(0.1) + await strategy.process_frame(UserSpeakingFrame()) + self.assertEqual(strategy.state, _WakeState.AWAKE) + + # Send more activity. + await asyncio.sleep(0.1) + await strategy.process_frame(BotSpeakingFrame()) + self.assertEqual(strategy.state, _WakeState.AWAKE) + + # Wait for timeout to expire after last activity. + await asyncio.sleep(0.3) + self.assertEqual(strategy.state, _WakeState.IDLE) + + await strategy.cleanup() + + async def test_wake_phrase_detected_event(self): + strategy = self._create_strategy() + await self._setup_strategy(strategy) + + detected_phrase = None + + @strategy.event_handler("on_wake_phrase_detected") + async def on_wake_phrase_detected(strategy, phrase): + nonlocal detected_phrase + detected_phrase = phrase + + await strategy.process_frame( + TranscriptionFrame(text="hey pipecat", user_id="user1", timestamp="") + ) + + # Event fires in a background task, give it a moment. + await asyncio.sleep(0.05) + self.assertEqual(detected_phrase, "hey pipecat") + + await strategy.cleanup() + + async def test_wake_phrase_timeout_event(self): + strategy = self._create_strategy(timeout=0.1) + await self._setup_strategy(strategy) + + timeout_fired = False + + @strategy.event_handler("on_wake_phrase_timeout") + async def on_wake_phrase_timeout(strategy): + nonlocal timeout_fired + timeout_fired = True + + await strategy.process_frame( + TranscriptionFrame(text="hey pipecat", user_id="user1", timestamp="") + ) + + # Wait for timeout. + await asyncio.sleep(0.3) + self.assertTrue(timeout_fired) + + await strategy.cleanup() + + async def test_single_activation_stays_inactive_after_reset(self): + """In single activation mode, reset() keeps INACTIVE so the current turn can finish.""" + strategy = self._create_strategy(single_activation=True, timeout=0.5) + await self._setup_strategy(strategy) + + # Trigger wake phrase. + result = await strategy.process_frame( + TranscriptionFrame(text="hey pipecat", user_id="user1", timestamp="") + ) + self.assertEqual(result, ProcessFrameResult.STOP) + self.assertEqual(strategy.state, _WakeState.AWAKE) + + # Simulate turn start (controller calls reset on all start strategies). + await strategy.reset() + # State remains INACTIVE so frames continue to flow. + self.assertEqual(strategy.state, _WakeState.AWAKE) + + # Subsequent frames should pass through (CONTINUE). + result = await strategy.process_frame(VADUserStartedSpeakingFrame()) + self.assertEqual(result, ProcessFrameResult.CONTINUE) + + result = await strategy.process_frame( + TranscriptionFrame(text="what is the weather", user_id="user1", timestamp="") + ) + self.assertEqual(result, ProcessFrameResult.CONTINUE) + + await strategy.cleanup() + + async def test_single_activation_timeout_returns_to_listening(self): + """In single activation mode, the keepalive timeout returns to LISTENING.""" + strategy = self._create_strategy(single_activation=True, timeout=0.1) + await self._setup_strategy(strategy) + + # Trigger wake phrase. + await strategy.process_frame( + TranscriptionFrame(text="hey pipecat", user_id="user1", timestamp="") + ) + self.assertEqual(strategy.state, _WakeState.AWAKE) + + # Wait for keepalive timeout to expire. + await asyncio.sleep(0.3) + self.assertEqual(strategy.state, _WakeState.IDLE) + + # Frames should now be blocked again. + result = await strategy.process_frame(VADUserStartedSpeakingFrame()) + self.assertEqual(result, ProcessFrameResult.STOP) + + await strategy.cleanup() + + async def test_single_activation_requires_wake_phrase_after_timeout(self): + """Single activation mode requires wake phrase again after keepalive timeout.""" + strategy = self._create_strategy(single_activation=True, timeout=0.1) + await self._setup_strategy(strategy) + + # First turn: wake phrase -> INACTIVE -> timeout -> LISTENING. + await strategy.process_frame( + TranscriptionFrame(text="hey pipecat", user_id="user1", timestamp="") + ) + self.assertEqual(strategy.state, _WakeState.AWAKE) + await asyncio.sleep(0.3) + self.assertEqual(strategy.state, _WakeState.IDLE) + + # Without wake phrase, frames are blocked. + result = await strategy.process_frame( + TranscriptionFrame(text="what is the weather", user_id="user1", timestamp="") + ) + self.assertEqual(result, ProcessFrameResult.STOP) + + # Second turn: wake phrase again. + result = await strategy.process_frame( + TranscriptionFrame(text="hey pipecat", user_id="user1", timestamp="") + ) + self.assertEqual(result, ProcessFrameResult.STOP) + self.assertEqual(strategy.state, _WakeState.AWAKE) + + await strategy.cleanup() + + +if __name__ == "__main__": + unittest.main() From 4aea7784c98d4b80c3cf96eec4b98f066cd65355 Mon Sep 17 00:00:00 2001 From: Filipi da Silva Fuchter Date: Wed, 18 Mar 2026 16:55:59 -0400 Subject: [PATCH 1018/1060] Fixed the ordering of `_maybe_pause_frame_processing` call in `TTSService` (#4071) * Fixing the invocation of pause_frame_processing at the correct time when receiving LLMFullResponseEndFrame and EndFrame. --- changelog/4071.fixed.md | 1 + src/pipecat/services/tts_service.py | 10 +++++----- 2 files changed, 6 insertions(+), 5 deletions(-) create mode 100644 changelog/4071.fixed.md diff --git a/changelog/4071.fixed.md b/changelog/4071.fixed.md new file mode 100644 index 000000000..0938127c3 --- /dev/null +++ b/changelog/4071.fixed.md @@ -0,0 +1 @@ +- Fixed audio overlap and potential dropped TTS content when multiple assistant turns occur in quick succession. `TTSService` now flushes remaining text before pausing frame processing on `LLMFullResponseEndFrame`/`EndFrame`, instead of pausing first. diff --git a/src/pipecat/services/tts_service.py b/src/pipecat/services/tts_service.py index 7583339c8..f93c13d79 100644 --- a/src/pipecat/services/tts_service.py +++ b/src/pipecat/services/tts_service.py @@ -720,11 +720,6 @@ class TTSService(AIService): self._turn_context_id = self.create_context_id() await self.push_frame(frame, direction) elif isinstance(frame, (LLMFullResponseEndFrame, EndFrame)): - # We pause processing incoming frames if the LLM response included - # text (it might be that it's only a function calling response). We - # pause to avoid audio overlapping. - await self._maybe_pause_frame_processing() - # Flush any remaining text (including text waiting for lookahead) remaining = await self._text_aggregator.flush() # Stop the aggregation metric (no-op if already stopped on first sentence). @@ -732,6 +727,11 @@ class TTSService(AIService): if remaining: await self._push_tts_frames(AggregatedTextFrame(remaining.text, remaining.type)) + # We pause processing incoming frames if the LLM response included + # text (it might be that it's only a function calling response). We + # pause to avoid audio overlapping. + await self._maybe_pause_frame_processing() + # Log accumulated streamed text and emit aggregated usage metric. if self._streamed_text: logger.debug(f"{self}: Generating TTS [{self._streamed_text}]") From 7dfcaf8096b057d4108998ec6b63c7d7571c0585 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Aleix=20Conchillo=20Flaqu=C3=A9?= Date: Wed, 18 Mar 2026 21:46:06 -0700 Subject: [PATCH 1019/1060] Add missing on_dtmf_event callback to Tavus transport The on_dtmf_event callback was added to DailyCallbacks in #4047 but the Tavus transport was not updated, causing a missing argument error. --- src/pipecat/transports/tavus/transport.py | 1 + 1 file changed, 1 insertion(+) diff --git a/src/pipecat/transports/tavus/transport.py b/src/pipecat/transports/tavus/transport.py index 79be070c5..872e6eefc 100644 --- a/src/pipecat/transports/tavus/transport.py +++ b/src/pipecat/transports/tavus/transport.py @@ -241,6 +241,7 @@ class TavusTransportClient: on_dialout_stopped=partial(self._on_handle_callback, "on_dialout_stopped"), on_dialout_error=partial(self._on_handle_callback, "on_dialout_error"), on_dialout_warning=partial(self._on_handle_callback, "on_dialout_warning"), + on_dtmf_event=partial(self._on_handle_callback, "on_dtmf_event"), on_participant_joined=self._callbacks.on_participant_joined, on_participant_left=self._callbacks.on_participant_left, on_participant_updated=partial(self._on_handle_callback, "on_participant_updated"), From 3e0c536fe784e3ff252f138ff2ddda9b582d2ec5 Mon Sep 17 00:00:00 2001 From: aconchillo <951761+aconchillo@users.noreply.github.com> Date: Thu, 19 Mar 2026 04:48:16 +0000 Subject: [PATCH 1020/1060] Update changelog for version 0.0.106 --- CHANGELOG.md | 212 +++++++++++++++++++++++++++++++++++ changelog/3457.changed.md | 1 - changelog/3991.changed.md | 1 - changelog/3997.changed.md | 1 - changelog/4000.fixed.md | 1 - changelog/4001.changed.md | 1 - changelog/4001.deprecated.md | 1 - changelog/4004.added.md | 1 - changelog/4005.added.md | 1 - changelog/4006.fixed.md | 1 - changelog/4007.fixed.2.md | 1 - changelog/4007.fixed.md | 1 - changelog/4009.added.md | 1 - changelog/4012.deprecated.md | 1 - changelog/4023.changed.md | 1 - changelog/4024.fixed.md | 1 - changelog/4026.fixed.md | 1 - changelog/4035.security.md | 1 - changelog/4037.fixed.md | 1 - changelog/4042.changed.md | 1 - changelog/4042.fixed.md | 1 - changelog/4046.fixed.md | 1 - changelog/4047.added.md | 1 - changelog/4047.changed.md | 1 - changelog/4048.changed.md | 1 - changelog/4057.fixed.md | 1 - changelog/4058.fixed.md | 1 - changelog/4063.fixed.md | 1 - changelog/4064.added.2.md | 1 - changelog/4064.added.md | 1 - changelog/4064.changed.md | 1 - changelog/4064.deprecated.md | 1 - changelog/4064.fixed.md | 1 - changelog/4066.changed.2.md | 1 - changelog/4066.changed.md | 1 - changelog/4071.fixed.md | 1 - 36 files changed, 212 insertions(+), 35 deletions(-) delete mode 100644 changelog/3457.changed.md delete mode 100644 changelog/3991.changed.md delete mode 100644 changelog/3997.changed.md delete mode 100644 changelog/4000.fixed.md delete mode 100644 changelog/4001.changed.md delete mode 100644 changelog/4001.deprecated.md delete mode 100644 changelog/4004.added.md delete mode 100644 changelog/4005.added.md delete mode 100644 changelog/4006.fixed.md delete mode 100644 changelog/4007.fixed.2.md delete mode 100644 changelog/4007.fixed.md delete mode 100644 changelog/4009.added.md delete mode 100644 changelog/4012.deprecated.md delete mode 100644 changelog/4023.changed.md delete mode 100644 changelog/4024.fixed.md delete mode 100644 changelog/4026.fixed.md delete mode 100644 changelog/4035.security.md delete mode 100644 changelog/4037.fixed.md delete mode 100644 changelog/4042.changed.md delete mode 100644 changelog/4042.fixed.md delete mode 100644 changelog/4046.fixed.md delete mode 100644 changelog/4047.added.md delete mode 100644 changelog/4047.changed.md delete mode 100644 changelog/4048.changed.md delete mode 100644 changelog/4057.fixed.md delete mode 100644 changelog/4058.fixed.md delete mode 100644 changelog/4063.fixed.md delete mode 100644 changelog/4064.added.2.md delete mode 100644 changelog/4064.added.md delete mode 100644 changelog/4064.changed.md delete mode 100644 changelog/4064.deprecated.md delete mode 100644 changelog/4064.fixed.md delete mode 100644 changelog/4066.changed.2.md delete mode 100644 changelog/4066.changed.md delete mode 100644 changelog/4071.fixed.md diff --git a/CHANGELOG.md b/CHANGELOG.md index 71938516a..dfd42c6c9 100644 --- a/CHANGELOG.md +++ b/CHANGELOG.md @@ -7,6 +7,218 @@ and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0 +## [0.0.106] - 2026-03-18 + +### Added + +- Added optional `service` field to `ServiceUpdateSettingsFrame` (and its + subclasses `LLMUpdateSettingsFrame`, `TTSUpdateSettingsFrame`, + `STTUpdateSettingsFrame`) to target a specific service instance. When + `service` is set, only the matching service applies the settings; others + forward the frame unchanged. This enables updating a single service when + multiple services of the same type exist in the pipeline. + (PR [#4004](https://github.com/pipecat-ai/pipecat/pull/4004)) + +- Added `sip_provider` and `room_geo` parameters to `configure()` in the Daily + runner. These convenience parameters let callers specify a SIP provider name + and geographic region directly without manually constructing + `DailyRoomProperties` and `DailyRoomSipParams`. + (PR [#4005](https://github.com/pipecat-ai/pipecat/pull/4005)) + +- Added `PerplexityLLMAdapter` that automatically transforms conversation + messages to satisfy Perplexity's stricter API constraints (strict role + alternation, no non-initial system messages, last message must be user/tool). + Previously, certain conversation histories could cause Perplexity API errors + that didn't occur with OpenAI (`PerplexityLLMService` subclasses + `OpenAILLMService` since Perplexity uses an OpenAI-compatible API). + (PR [#4009](https://github.com/pipecat-ai/pipecat/pull/4009)) + +- Added DTMF input event support to the Daily transport. Incoming DTMF tones + are now received via Daily's `on_dtmf_event` callback and pushed into the + pipeline as `InputDTMFFrame`, enabling bots to react to keypad presses from + phone callers. + (PR [#4047](https://github.com/pipecat-ai/pipecat/pull/4047)) + +- Added `WakePhraseUserTurnStartStrategy` for triggering user turns based on + wake phrases, with support for `single_activation` mode. Deprecates + `WakeCheckFilter`. + (PR [#4064](https://github.com/pipecat-ai/pipecat/pull/4064)) + +- Added `default_user_turn_start_strategies()` and + `default_user_turn_stop_strategies()` helper functions for composing custom + strategy lists. + (PR [#4064](https://github.com/pipecat-ai/pipecat/pull/4064)) + +### Changed + +- Changed tool result JSON serialization to use `ensure_ascii=False`, + preserving UTF-8 characters instead of escaping them. This reduces context + size and token usage for non-English languages. + (PR [#3457](https://github.com/pipecat-ai/pipecat/pull/3457)) + +- `OpenAIRealtimeSTTService`'s `noise_reduction` parameter is now part of + `OpenAIRealtimeSTTSettings`, making it runtime-updatable via + `STTUpdateSettingsFrame`. The direct `noise_reduction` init argument is + deprecated as of 0.0.106. + (PR [#3991](https://github.com/pipecat-ai/pipecat/pull/3991)) + +- Updated `sarvamai` dependency from `0.1.26a2` (alpha) to `0.1.26` (stable + release). + (PR [#3997](https://github.com/pipecat-ai/pipecat/pull/3997)) + +- `SimliVideoService` now extends `AIService` instead of `FrameProcessor`, + aligning it with the HeyGen and Tavus video services. It supports + `SimliVideoService.Settings(...)` for configuration and uses + `start()`/`stop()`/`cancel()` lifecycle methods. Existing constructor usage + (`api_key`, `face_id`, etc.) remains unchanged. + (PR [#4001](https://github.com/pipecat-ai/pipecat/pull/4001)) + +- Update `pipecat-ai-small-webrtc-prebuilt` to `2.4.0`. + (PR [#4023](https://github.com/pipecat-ai/pipecat/pull/4023)) + +- Nova Sonic assistant text transcripts are now delivered in real-time using + speculative text events instead of delayed final text events. Previously, + assistant text only arrived after all audio had finished playing, causing + laggy transcripts in client UIs. Speculative text arrives before each audio + chunk, providing text synchronized with what the bot is saying. This also + simplifies the internal text handling by removing the interruption re-push + hack and assistant text buffer. + (PR [#4042](https://github.com/pipecat-ai/pipecat/pull/4042)) + +- Updated `daily-python` dependency to 0.25.0. + (PR [#4047](https://github.com/pipecat-ai/pipecat/pull/4047)) + +- Added `enable_dialout` parameter to `configure()` in `pipecat.runner.daily` + to support dial-out rooms. Also narrowed misleading `Optional` type hints and + deduplicated token expiry calculation. + (PR [#4048](https://github.com/pipecat-ai/pipecat/pull/4048)) + +- Extended `ProcessFrameResult` to stop strategies, allowing a stop strategy to + short-circuit evaluation of subsequent strategies by returning `STOP`. + (PR [#4064](https://github.com/pipecat-ai/pipecat/pull/4064)) + +- `GradiumSTTService` now takes both an `encoding` and `sample_rate` + constructor argument which is assmebled in the class to form the + `input_format`. PCM accepts `8000`, `16000`, and `24000` Hz sample rates. + (PR [#4066](https://github.com/pipecat-ai/pipecat/pull/4066)) + +- Improved `GradiumSTTService` transcription accuracy by reworking how text + fragments are accumulated and finalized. Previously, trailing words could be + dropped when the server's `flushed` response arrived before all text tokens + were delivered. The service now uses a short aggregation delay after flush to + capture trailing tokens, producing complete utterances. + (PR [#4066](https://github.com/pipecat-ai/pipecat/pull/4066)) + +### Deprecated + +- `SimliVideoService.InputParams` is deprecated. Use the direct constructor + parameters `max_session_length`, `max_idle_time`, and `enable_logging` + instead. + (PR [#4001](https://github.com/pipecat-ai/pipecat/pull/4001)) + +- Deprecated `LocalSmartTurnAnalyzerV2` and `LocalCoreMLSmartTurnAnalyzer`. Use + `LocalSmartTurnAnalyzerV3` instead. Instantiating these analyzers will now + emit a `DeprecationWarning`. + (PR [#4012](https://github.com/pipecat-ai/pipecat/pull/4012)) + +- Deprecated `WakeCheckFilter` in favor of `WakePhraseUserTurnStartStrategy`. + (PR [#4064](https://github.com/pipecat-ai/pipecat/pull/4064)) + +### Fixed + +- Fixed an issue where the default model for `OpenAILLMService` and + `AzureLLMService` was mistakenly reverted to `gpt-4o`. The defaults are now + restored to `gpt-4.1`. + (PR [#4000](https://github.com/pipecat-ai/pipecat/pull/4000)) + +- Fixed a race condition where `EndTaskFrame` could cause the pipeline to shut + down before in-flight frames (e.g. LLM function call responses) finished + processing. `EndTaskFrame` and `StopTaskFrame` now flow through the pipeline + as `ControlFrame`s, ensuring all pending work is flushed before shutdown + begins. `CancelTaskFrame` and `InterruptionTaskFrame` remain immediate + (`SystemFrame`). + (PR [#4006](https://github.com/pipecat-ai/pipecat/pull/4006)) + +- Fixed `ParallelPipeline` dropping or misordering frames during lifecycle + synchronization. Buffered frames are now flushed in the correct order + relative to synchronization frames (`StartFrame` goes first, + `EndFrame`/`CancelFrame` go after), and frames added to the buffer during + flush are also drained. + (PR [#4007](https://github.com/pipecat-ai/pipecat/pull/4007)) + +- Fixed `TTSService` potentially canceling in-flight audio during shutdown. The + stop sequence now waits for all queued audio contexts to finish processing + before canceling the stop frame task. + (PR [#4007](https://github.com/pipecat-ai/pipecat/pull/4007)) + +- Fixed `Language` enum values (e.g. `Language.ES`) not being converted to + service-specific codes when passed via + `settings=Service.Settings(language=Language.ES)` at init time. This caused + API errors (e.g. 400 from Rime) because the raw enum was sent instead of the + expected language code (e.g. `"spa"`). Runtime updates via + `UpdateSettingsFrame` were unaffected. The fix centralizes conversion in the + base `TTSService` and `STTService` classes so all services handle this + consistently. + (PR [#4024](https://github.com/pipecat-ai/pipecat/pull/4024)) + +- Fixed `DeepgramSTTService` ignoring the `base_url` scheme when using `ws://` + or `http://`. Previously these were silently overwritten with `wss://` / + `https://`, breaking air-gapped or private deployments that don't use TLS. + All scheme choices (`wss://`, `https://`, `ws://`, `http://`, or bare + hostname) are now respected. + (PR [#4026](https://github.com/pipecat-ai/pipecat/pull/4026)) + +- Fixed `LLMSwitcher.register_function()` and `register_direct_function()` not + accepting or forwarding the `timeout_secs` parameter. + (PR [#4037](https://github.com/pipecat-ai/pipecat/pull/4037)) + +- Fixed empty user transcriptions in Nova Sonic causing spurious interruptions. + Previously, an empty transcription could trigger an interruption of the + assistant's response even though the user hadn't actually spoken. + (PR [#4042](https://github.com/pipecat-ai/pipecat/pull/4042)) + +- Fixed `SonioxSTTService` and `OpenAIRealtimeSTTService` crash when language + parameters contain plain strings instead of `Language` enum values. + (PR [#4046](https://github.com/pipecat-ai/pipecat/pull/4046)) + +- Fixed premature user turn stops caused by late transcriptions arriving + between turns. A stale transcript from the previous turn could persist into + the next turn and trigger a stop before the current turn's real transcript + arrived. Stop strategies are now reset at both turn start and turn stop to + prevent state from leaking across turn boundaries. + (PR [#4057](https://github.com/pipecat-ai/pipecat/pull/4057)) + +- Fixed raw language strings like `"de-DE"` silently failing when passed to + TTS/STT services (e.g. ElevenLabs producing no audio). Raw strings now go + through the same `Language` enum resolution as enum values, so regional codes + like `"de-DE"` are properly converted to service-expected formats like + `"de"`. Unrecognized strings log a warning instead of failing silently. + (PR [#4058](https://github.com/pipecat-ai/pipecat/pull/4058)) + +- Fixed Deepgram STT list-type settings (`keyterm`, `keywords`, `search`, + `redact`, `replace`) being stringified instead of passed as lists to the SDK, + which caused them to be sent as literal strings (e.g. `"['pipecat']"`) in the + WebSocket query params. + (PR [#4063](https://github.com/pipecat-ai/pipecat/pull/4063)) + +- Fixed `MinWordsUserTurnStartStrategy` including text below the word threshold + in the output by resetting aggregation when the minimum word count is not + met. + (PR [#4064](https://github.com/pipecat-ai/pipecat/pull/4064)) + +- Fixed audio overlap and potential dropped TTS content when multiple assistant + turns occur in quick succession. `TTSService` now flushes remaining text + before pausing frame processing on `LLMFullResponseEndFrame`/`EndFrame`, + instead of pausing first. + (PR [#4071](https://github.com/pipecat-ai/pipecat/pull/4071)) + +### Security + +- Bumped PyJWT minimum version from 2.10.1 to 2.12.0 in the `livekit` extra to + address CVE-2026-32597 (GHSA-752w-5fwx-jx9f), where PyJWT <= 2.11.0 accepted + unknown `crit` header extensions. + (PR [#4035](https://github.com/pipecat-ai/pipecat/pull/4035)) + ## [0.0.105] - 2026-03-10 ### Added diff --git a/changelog/3457.changed.md b/changelog/3457.changed.md deleted file mode 100644 index d0d82ad2d..000000000 --- a/changelog/3457.changed.md +++ /dev/null @@ -1 +0,0 @@ -- Changed tool result JSON serialization to use `ensure_ascii=False`, preserving UTF-8 characters instead of escaping them. This reduces context size and token usage for non-English languages. diff --git a/changelog/3991.changed.md b/changelog/3991.changed.md deleted file mode 100644 index 5767dc8aa..000000000 --- a/changelog/3991.changed.md +++ /dev/null @@ -1 +0,0 @@ -- `OpenAIRealtimeSTTService`'s `noise_reduction` parameter is now part of `OpenAIRealtimeSTTSettings`, making it runtime-updatable via `STTUpdateSettingsFrame`. The direct `noise_reduction` init argument is deprecated as of 0.0.106. diff --git a/changelog/3997.changed.md b/changelog/3997.changed.md deleted file mode 100644 index 7d626a5fe..000000000 --- a/changelog/3997.changed.md +++ /dev/null @@ -1 +0,0 @@ -- Updated `sarvamai` dependency from `0.1.26a2` (alpha) to `0.1.26` (stable release). diff --git a/changelog/4000.fixed.md b/changelog/4000.fixed.md deleted file mode 100644 index 871d71135..000000000 --- a/changelog/4000.fixed.md +++ /dev/null @@ -1 +0,0 @@ -- Fixed an issue where the default model for `OpenAILLMService` and `AzureLLMService` was mistakenly reverted to `gpt-4o`. The defaults are now restored to `gpt-4.1`. diff --git a/changelog/4001.changed.md b/changelog/4001.changed.md deleted file mode 100644 index 1d0d4e4ef..000000000 --- a/changelog/4001.changed.md +++ /dev/null @@ -1 +0,0 @@ -- `SimliVideoService` now extends `AIService` instead of `FrameProcessor`, aligning it with the HeyGen and Tavus video services. It supports `SimliVideoService.Settings(...)` for configuration and uses `start()`/`stop()`/`cancel()` lifecycle methods. Existing constructor usage (`api_key`, `face_id`, etc.) remains unchanged. diff --git a/changelog/4001.deprecated.md b/changelog/4001.deprecated.md deleted file mode 100644 index 749e7eea5..000000000 --- a/changelog/4001.deprecated.md +++ /dev/null @@ -1 +0,0 @@ -- `SimliVideoService.InputParams` is deprecated. Use the direct constructor parameters `max_session_length`, `max_idle_time`, and `enable_logging` instead. diff --git a/changelog/4004.added.md b/changelog/4004.added.md deleted file mode 100644 index f0fd28767..000000000 --- a/changelog/4004.added.md +++ /dev/null @@ -1 +0,0 @@ -- Added optional `service` field to `ServiceUpdateSettingsFrame` (and its subclasses `LLMUpdateSettingsFrame`, `TTSUpdateSettingsFrame`, `STTUpdateSettingsFrame`) to target a specific service instance. When `service` is set, only the matching service applies the settings; others forward the frame unchanged. This enables updating a single service when multiple services of the same type exist in the pipeline. diff --git a/changelog/4005.added.md b/changelog/4005.added.md deleted file mode 100644 index 0a023f104..000000000 --- a/changelog/4005.added.md +++ /dev/null @@ -1 +0,0 @@ -- Added `sip_provider` and `room_geo` parameters to `configure()` in the Daily runner. These convenience parameters let callers specify a SIP provider name and geographic region directly without manually constructing `DailyRoomProperties` and `DailyRoomSipParams`. diff --git a/changelog/4006.fixed.md b/changelog/4006.fixed.md deleted file mode 100644 index ba12beea7..000000000 --- a/changelog/4006.fixed.md +++ /dev/null @@ -1 +0,0 @@ -- Fixed a race condition where `EndTaskFrame` could cause the pipeline to shut down before in-flight frames (e.g. LLM function call responses) finished processing. `EndTaskFrame` and `StopTaskFrame` now flow through the pipeline as `ControlFrame`s, ensuring all pending work is flushed before shutdown begins. `CancelTaskFrame` and `InterruptionTaskFrame` remain immediate (`SystemFrame`). diff --git a/changelog/4007.fixed.2.md b/changelog/4007.fixed.2.md deleted file mode 100644 index 0c50b83e9..000000000 --- a/changelog/4007.fixed.2.md +++ /dev/null @@ -1 +0,0 @@ -- Fixed `TTSService` potentially canceling in-flight audio during shutdown. The stop sequence now waits for all queued audio contexts to finish processing before canceling the stop frame task. diff --git a/changelog/4007.fixed.md b/changelog/4007.fixed.md deleted file mode 100644 index 8a90aea43..000000000 --- a/changelog/4007.fixed.md +++ /dev/null @@ -1 +0,0 @@ -- Fixed `ParallelPipeline` dropping or misordering frames during lifecycle synchronization. Buffered frames are now flushed in the correct order relative to synchronization frames (`StartFrame` goes first, `EndFrame`/`CancelFrame` go after), and frames added to the buffer during flush are also drained. diff --git a/changelog/4009.added.md b/changelog/4009.added.md deleted file mode 100644 index 9ebbec7dd..000000000 --- a/changelog/4009.added.md +++ /dev/null @@ -1 +0,0 @@ -- Added `PerplexityLLMAdapter` that automatically transforms conversation messages to satisfy Perplexity's stricter API constraints (strict role alternation, no non-initial system messages, last message must be user/tool). Previously, certain conversation histories could cause Perplexity API errors that didn't occur with OpenAI (`PerplexityLLMService` subclasses `OpenAILLMService` since Perplexity uses an OpenAI-compatible API). diff --git a/changelog/4012.deprecated.md b/changelog/4012.deprecated.md deleted file mode 100644 index 4310b8aba..000000000 --- a/changelog/4012.deprecated.md +++ /dev/null @@ -1 +0,0 @@ -- Deprecated `LocalSmartTurnAnalyzerV2` and `LocalCoreMLSmartTurnAnalyzer`. Use `LocalSmartTurnAnalyzerV3` instead. Instantiating these analyzers will now emit a `DeprecationWarning`. diff --git a/changelog/4023.changed.md b/changelog/4023.changed.md deleted file mode 100644 index 7756f20b8..000000000 --- a/changelog/4023.changed.md +++ /dev/null @@ -1 +0,0 @@ -- Update `pipecat-ai-small-webrtc-prebuilt` to `2.4.0`. diff --git a/changelog/4024.fixed.md b/changelog/4024.fixed.md deleted file mode 100644 index 7654cbdf5..000000000 --- a/changelog/4024.fixed.md +++ /dev/null @@ -1 +0,0 @@ -- Fixed `Language` enum values (e.g. `Language.ES`) not being converted to service-specific codes when passed via `settings=Service.Settings(language=Language.ES)` at init time. This caused API errors (e.g. 400 from Rime) because the raw enum was sent instead of the expected language code (e.g. `"spa"`). Runtime updates via `UpdateSettingsFrame` were unaffected. The fix centralizes conversion in the base `TTSService` and `STTService` classes so all services handle this consistently. diff --git a/changelog/4026.fixed.md b/changelog/4026.fixed.md deleted file mode 100644 index a12321ab4..000000000 --- a/changelog/4026.fixed.md +++ /dev/null @@ -1 +0,0 @@ -- Fixed `DeepgramSTTService` ignoring the `base_url` scheme when using `ws://` or `http://`. Previously these were silently overwritten with `wss://` / `https://`, breaking air-gapped or private deployments that don't use TLS. All scheme choices (`wss://`, `https://`, `ws://`, `http://`, or bare hostname) are now respected. diff --git a/changelog/4035.security.md b/changelog/4035.security.md deleted file mode 100644 index 9ffc17305..000000000 --- a/changelog/4035.security.md +++ /dev/null @@ -1 +0,0 @@ -- Bumped PyJWT minimum version from 2.10.1 to 2.12.0 in the `livekit` extra to address CVE-2026-32597 (GHSA-752w-5fwx-jx9f), where PyJWT <= 2.11.0 accepted unknown `crit` header extensions. diff --git a/changelog/4037.fixed.md b/changelog/4037.fixed.md deleted file mode 100644 index e55b6f998..000000000 --- a/changelog/4037.fixed.md +++ /dev/null @@ -1 +0,0 @@ -- Fixed `LLMSwitcher.register_function()` and `register_direct_function()` not accepting or forwarding the `timeout_secs` parameter. diff --git a/changelog/4042.changed.md b/changelog/4042.changed.md deleted file mode 100644 index f83c32f59..000000000 --- a/changelog/4042.changed.md +++ /dev/null @@ -1 +0,0 @@ -- Nova Sonic assistant text transcripts are now delivered in real-time using speculative text events instead of delayed final text events. Previously, assistant text only arrived after all audio had finished playing, causing laggy transcripts in client UIs. Speculative text arrives before each audio chunk, providing text synchronized with what the bot is saying. This also simplifies the internal text handling by removing the interruption re-push hack and assistant text buffer. diff --git a/changelog/4042.fixed.md b/changelog/4042.fixed.md deleted file mode 100644 index a48996208..000000000 --- a/changelog/4042.fixed.md +++ /dev/null @@ -1 +0,0 @@ -- Fixed empty user transcriptions in Nova Sonic causing spurious interruptions. Previously, an empty transcription could trigger an interruption of the assistant's response even though the user hadn't actually spoken. diff --git a/changelog/4046.fixed.md b/changelog/4046.fixed.md deleted file mode 100644 index 0f147e04e..000000000 --- a/changelog/4046.fixed.md +++ /dev/null @@ -1 +0,0 @@ -Fixed `SonioxSTTService` and `OpenAIRealtimeSTTService` crash when language parameters contain plain strings instead of `Language` enum values. diff --git a/changelog/4047.added.md b/changelog/4047.added.md deleted file mode 100644 index b0bda2ed4..000000000 --- a/changelog/4047.added.md +++ /dev/null @@ -1 +0,0 @@ -- Added DTMF input event support to the Daily transport. Incoming DTMF tones are now received via Daily's `on_dtmf_event` callback and pushed into the pipeline as `InputDTMFFrame`, enabling bots to react to keypad presses from phone callers. diff --git a/changelog/4047.changed.md b/changelog/4047.changed.md deleted file mode 100644 index c93e95f76..000000000 --- a/changelog/4047.changed.md +++ /dev/null @@ -1 +0,0 @@ -- Updated `daily-python` dependency to 0.25.0. diff --git a/changelog/4048.changed.md b/changelog/4048.changed.md deleted file mode 100644 index edef83283..000000000 --- a/changelog/4048.changed.md +++ /dev/null @@ -1 +0,0 @@ -- Added `enable_dialout` parameter to `configure()` in `pipecat.runner.daily` to support dial-out rooms. Also narrowed misleading `Optional` type hints and deduplicated token expiry calculation. diff --git a/changelog/4057.fixed.md b/changelog/4057.fixed.md deleted file mode 100644 index b63b8540e..000000000 --- a/changelog/4057.fixed.md +++ /dev/null @@ -1 +0,0 @@ -- Fixed premature user turn stops caused by late transcriptions arriving between turns. A stale transcript from the previous turn could persist into the next turn and trigger a stop before the current turn's real transcript arrived. Stop strategies are now reset at both turn start and turn stop to prevent state from leaking across turn boundaries. diff --git a/changelog/4058.fixed.md b/changelog/4058.fixed.md deleted file mode 100644 index 4b5baed82..000000000 --- a/changelog/4058.fixed.md +++ /dev/null @@ -1 +0,0 @@ -- Fixed raw language strings like `"de-DE"` silently failing when passed to TTS/STT services (e.g. ElevenLabs producing no audio). Raw strings now go through the same `Language` enum resolution as enum values, so regional codes like `"de-DE"` are properly converted to service-expected formats like `"de"`. Unrecognized strings log a warning instead of failing silently. diff --git a/changelog/4063.fixed.md b/changelog/4063.fixed.md deleted file mode 100644 index ea703078a..000000000 --- a/changelog/4063.fixed.md +++ /dev/null @@ -1 +0,0 @@ -- Fixed Deepgram STT list-type settings (`keyterm`, `keywords`, `search`, `redact`, `replace`) being stringified instead of passed as lists to the SDK, which caused them to be sent as literal strings (e.g. `"['pipecat']"`) in the WebSocket query params. diff --git a/changelog/4064.added.2.md b/changelog/4064.added.2.md deleted file mode 100644 index f2dc79a16..000000000 --- a/changelog/4064.added.2.md +++ /dev/null @@ -1 +0,0 @@ -- Added `default_user_turn_start_strategies()` and `default_user_turn_stop_strategies()` helper functions for composing custom strategy lists. diff --git a/changelog/4064.added.md b/changelog/4064.added.md deleted file mode 100644 index 5c28bde94..000000000 --- a/changelog/4064.added.md +++ /dev/null @@ -1 +0,0 @@ -- Added `WakePhraseUserTurnStartStrategy` for triggering user turns based on wake phrases, with support for `single_activation` mode. Deprecates `WakeCheckFilter`. diff --git a/changelog/4064.changed.md b/changelog/4064.changed.md deleted file mode 100644 index c66263fbe..000000000 --- a/changelog/4064.changed.md +++ /dev/null @@ -1 +0,0 @@ -- Extended `ProcessFrameResult` to stop strategies, allowing a stop strategy to short-circuit evaluation of subsequent strategies by returning `STOP`. diff --git a/changelog/4064.deprecated.md b/changelog/4064.deprecated.md deleted file mode 100644 index b5f42c215..000000000 --- a/changelog/4064.deprecated.md +++ /dev/null @@ -1 +0,0 @@ -- Deprecated `WakeCheckFilter` in favor of `WakePhraseUserTurnStartStrategy`. diff --git a/changelog/4064.fixed.md b/changelog/4064.fixed.md deleted file mode 100644 index 6824ce26f..000000000 --- a/changelog/4064.fixed.md +++ /dev/null @@ -1 +0,0 @@ -- Fixed `MinWordsUserTurnStartStrategy` including text below the word threshold in the output by resetting aggregation when the minimum word count is not met. diff --git a/changelog/4066.changed.2.md b/changelog/4066.changed.2.md deleted file mode 100644 index 751961f10..000000000 --- a/changelog/4066.changed.2.md +++ /dev/null @@ -1 +0,0 @@ -- `GradiumSTTService` now takes both an `encoding` and `sample_rate` constructor argument which is assmebled in the class to form the `input_format`. PCM accepts `8000`, `16000`, and `24000` Hz sample rates. diff --git a/changelog/4066.changed.md b/changelog/4066.changed.md deleted file mode 100644 index 65e95ff2c..000000000 --- a/changelog/4066.changed.md +++ /dev/null @@ -1 +0,0 @@ -- Improved `GradiumSTTService` transcription accuracy by reworking how text fragments are accumulated and finalized. Previously, trailing words could be dropped when the server's `flushed` response arrived before all text tokens were delivered. The service now uses a short aggregation delay after flush to capture trailing tokens, producing complete utterances. diff --git a/changelog/4071.fixed.md b/changelog/4071.fixed.md deleted file mode 100644 index 0938127c3..000000000 --- a/changelog/4071.fixed.md +++ /dev/null @@ -1 +0,0 @@ -- Fixed audio overlap and potential dropped TTS content when multiple assistant turns occur in quick succession. `TTSService` now flushes remaining text before pausing frame processing on `LLMFullResponseEndFrame`/`EndFrame`, instead of pausing first. From 5fd98e13910eb42a377d5f0dbe1e94ad6c26248c Mon Sep 17 00:00:00 2001 From: filipi87 Date: Thu, 19 Mar 2026 09:43:40 -0300 Subject: [PATCH 1021/1060] Fixing TTS frame order. --- src/pipecat/services/tts_service.py | 56 +++-- tests/test_tts_frame_ordering.py | 315 ++++++++++++++++++++++++++++ 2 files changed, 359 insertions(+), 12 deletions(-) create mode 100644 tests/test_tts_frame_ordering.py diff --git a/src/pipecat/services/tts_service.py b/src/pipecat/services/tts_service.py index f93c13d79..303072373 100644 --- a/src/pipecat/services/tts_service.py +++ b/src/pipecat/services/tts_service.py @@ -43,6 +43,7 @@ from pipecat.frames.frames import ( LLMFullResponseEndFrame, LLMFullResponseStartFrame, StartFrame, + SystemFrame, TextFrame, TranscriptionFrame, TTSAudioRawFrame, @@ -557,9 +558,9 @@ class TTSService(AIService): """ await super().stop(frame) if self._audio_context_task: - # Indicate no more audio contexts are available; this will end the - # task cleanly after all contexts have been processed. - await self._contexts_queue.put(None) + # Sentinel None shuts down the serialization queue once all + # pending contexts and frames have been processed. + await self._serialization_queue.put(None) await self._audio_context_task self._audio_context_task = None if self._stop_frame_task: @@ -791,7 +792,15 @@ class TTSService(AIService): await self._maybe_resume_frame_processing() await self.push_frame(frame, direction) else: - await self.push_frame(frame, direction) + if direction == FrameDirection.DOWNSTREAM and not isinstance(frame, SystemFrame): + # Route non-system downstream frames through the serialization queue so they + # are emitted in the same order they arrive relative to any audio contexts that + # are already queued (e.g. a FooFrame sent right after a TTSSpeakFrame must + # not overtake the TTSStartedFrame / TTSAudioRawFrame / TTSStoppedFrame + # sequence from that speak frame). + await self._serialization_queue.put(frame) + else: + await self.push_frame(frame, direction) async def push_frame(self, frame: Frame, direction: FrameDirection = FrameDirection.DOWNSTREAM): """Push a frame downstream with TTS-specific handling. @@ -994,7 +1003,10 @@ class TTSService(AIService): # is spoken, so we set append_to_context to False. src_frame.append_to_context = False src_frame.context_id = context_id - await self.push_frame(src_frame) + # Route AggregatedTextFrame through the serialization queue so it is emitted + # immediately before the TTSStartedFrame of the audio context it describes, + # rather than racing ahead of audio frames from a previous context. + await self._serialization_queue.put(src_frame) # Note: Text transformations are meant to only affect the text sent to the TTS for # TTS-specific purposes. This allows for explicit TTS modifications (e.g., inserting @@ -1203,7 +1215,7 @@ class TTSService(AIService): Args: context_id: Unique identifier for the audio context. """ - await self._contexts_queue.put(context_id) + await self._serialization_queue.put(context_id) self._audio_contexts[context_id] = asyncio.Queue() logger.trace(f"{self} created audio context {context_id}") @@ -1295,7 +1307,14 @@ class TTSService(AIService): def _create_audio_context_task(self): if not self._audio_context_task: - self._contexts_queue: asyncio.Queue = asyncio.Queue() + # Single FIFO queue that serializes everything the TTS service emits downstream. + # Items can be: + # str – an audio context ID: process the per-context audio queue in full before + # moving on (see _handle_audio_context). + # Frame – a non-system downstream frame (e.g. AggregatedTextFrame, FooFrame) that + # must be emitted in-order relative to surrounding audio contexts. + # None – shutdown sentinel (sent by stop()). + self._serialization_queue: asyncio.Queue = asyncio.Queue() self._audio_contexts: Dict[str, asyncio.Queue] = {} self._audio_context_task = self.create_task(self._audio_context_task_handler()) @@ -1305,13 +1324,26 @@ class TTSService(AIService): self._audio_context_task = None async def _audio_context_task_handler(self): - """In this task we process audio contexts in order.""" + """Drain the serialization queue, preserving downstream frame order. + + The queue carries three kinds of items (see _create_audio_context_task): + + * str – audio context ID: block until all audio for that context has been + pushed downstream, then call on_audio_context_completed(). + * Frame – a non-system downstream frame that must be emitted at this exact + position in the output stream (e.g. AggregatedTextFrame preceding + its audio, or an arbitrary frame that arrived between two speak frames). + * None – shutdown sentinel; exit the loop once reached. + """ running = True while running: - context_id = await self._contexts_queue.get() - self._playing_context_id = context_id + context_value = await self._serialization_queue.get() + if isinstance(context_value, Frame): + await self.push_frame(context_value) + elif isinstance(context_value, str): + context_id = context_value + self._playing_context_id = context_id - if context_id: # Process the audio context until the context doesn't have more # audio available (i.e. we find None). await self._handle_audio_context(context_id) @@ -1323,7 +1355,7 @@ class TTSService(AIService): else: running = False - self._contexts_queue.task_done() + self._serialization_queue.task_done() async def _handle_audio_context(self, context_id: str): """Process items from an audio context queue until it is exhausted.""" diff --git a/tests/test_tts_frame_ordering.py b/tests/test_tts_frame_ordering.py new file mode 100644 index 000000000..52d3df4e7 --- /dev/null +++ b/tests/test_tts_frame_ordering.py @@ -0,0 +1,315 @@ +# +# Copyright (c) 2024-2026, Daily +# +# SPDX-License-Identifier: BSD 2-Clause License +# + +"""Tests for frame ordering across TTS service types. + +Covers three patterns: +- HTTP TTS services (e.g. CartesiaHttpTTSService): yield audio frames synchronously. +- WebSocket TTS services without pause (e.g. CartesiaTTSService): deliver audio via + append_to_audio_context from a background receive loop, no frame-processing pause. +- WebSocket TTS services with pause (e.g. ElevenLabsTTSService): same delivery + mechanism, but pause downstream frame processing while audio is in flight. + +For all three patterns we verify: + AggregatedTextFrame → TTSStartedFrame → TTSAudioRawFrame (1+) → TTSStoppedFrame → FooFrame + +repeated for each TTSSpeakFrame, with no cross-group contamination. +""" + +import asyncio +import unittest +from dataclasses import dataclass +from typing import AsyncGenerator, List, Sequence, Tuple + +import pytest + +from pipecat.frames.frames import ( + AggregatedTextFrame, + DataFrame, + Frame, + TTSAudioRawFrame, + TTSSpeakFrame, + TTSStartedFrame, + TTSStoppedFrame, +) +from pipecat.services.tts_service import TTSService +from pipecat.tests.utils import run_test + +# --------------------------------------------------------------------------- +# Test-only frame +# --------------------------------------------------------------------------- + +_FAKE_AUDIO = b"\x00\x01" * 320 # 320 bytes of silence +_SAMPLE_RATE = 16000 + + +@dataclass +class FooFrame(DataFrame): + """Marker frame used to verify relative ordering against TTS audio frames.""" + + label: str = "" + + +# --------------------------------------------------------------------------- +# Mock TTS services +# --------------------------------------------------------------------------- + + +class MockHttpTTSService(TTSService): + """Simulates an HTTP TTS service (e.g. CartesiaHttpTTSService). + + Audio frames are yielded synchronously from run_tts(), so the audio context + is fully populated before the next downstream frame is processed. + TTSStoppedFrame is appended by the base class in on_turn_context_completed() + once it detects _is_yielding_frames_synchronously is True. + """ + + def __init__(self, **kwargs): + super().__init__( + push_start_frame=True, + push_stop_frames=True, + push_text_frames=False, + sample_rate=_SAMPLE_RATE, + **kwargs, + ) + + def can_generate_metrics(self) -> bool: + return False + + async def run_tts(self, text: str, context_id: str) -> AsyncGenerator[Frame, None]: + yield TTSAudioRawFrame( + audio=_FAKE_AUDIO, + sample_rate=_SAMPLE_RATE, + num_channels=1, + context_id=context_id, + ) + + +class MockWebSocketTTSService(TTSService): + """Simulates a WebSocket TTS service without frame-processing pause (e.g. CartesiaTTSService). + + run_tts() is an empty async generator (signals async delivery). A background + task appends audio frames and the TTSStoppedFrame to the audio context after a + short delay, mimicking real WebSocket receive-loop behaviour. + pause_frame_processing=False means downstream frames (FooFrame) are NOT held. + """ + + def __init__(self, **kwargs): + super().__init__( + push_start_frame=True, + push_text_frames=False, + pause_frame_processing=False, + sample_rate=_SAMPLE_RATE, + **kwargs, + ) + + def can_generate_metrics(self) -> bool: + return False + + async def run_tts(self, text: str, context_id: str) -> AsyncGenerator[Frame, None]: + async def _deliver_audio(): + await asyncio.sleep(0.01) + await self.append_to_audio_context( + context_id, + TTSAudioRawFrame( + audio=_FAKE_AUDIO, + sample_rate=_SAMPLE_RATE, + num_channels=1, + context_id=context_id, + ), + ) + await self.append_to_audio_context(context_id, TTSStoppedFrame(context_id=context_id)) + await self.remove_audio_context(context_id) + + self.create_task(_deliver_audio(), name=f"mock_ws_deliver_{context_id}") + if False: + yield # make this an async generator without yielding anything + + +class MockWebSocketPauseTTSService(TTSService): + """Simulates a WebSocket TTS service WITH frame-processing pause (e.g. ElevenLabsTTSService). + + Identical to MockWebSocketTTSService except pause_frame_processing=True. + on_audio_context_completed() resumes downstream processing once the full + audio context has been pushed, guaranteeing FooFrame arrives after TTSStoppedFrame. + """ + + def __init__(self, **kwargs): + super().__init__( + push_start_frame=True, + push_text_frames=False, + pause_frame_processing=True, + sample_rate=_SAMPLE_RATE, + **kwargs, + ) + + def can_generate_metrics(self) -> bool: + return False + + async def on_audio_context_completed(self, context_id: str): + # Resume frame processing after the audio context is fully played out. + await self._maybe_resume_frame_processing() + + async def run_tts(self, text: str, context_id: str) -> AsyncGenerator[Frame, None]: + async def _deliver_audio(): + await asyncio.sleep(0.01) + await self.append_to_audio_context( + context_id, + TTSAudioRawFrame( + audio=_FAKE_AUDIO, + sample_rate=_SAMPLE_RATE, + num_channels=1, + context_id=context_id, + ), + ) + await self.append_to_audio_context(context_id, TTSStoppedFrame(context_id=context_id)) + await self.remove_audio_context(context_id) + + self.create_task(_deliver_audio(), name=f"mock_ws_pause_deliver_{context_id}") + if False: + yield + + +# --------------------------------------------------------------------------- +# Assertion helper +# --------------------------------------------------------------------------- + + +def _assert_group_ordering( + down_frames: Sequence[Frame], + expected_groups: List[Tuple[str, str]], +) -> None: + """Assert two (or more) TTS+FooFrame groups are in strict order. + + Args: + down_frames: All downstream frames received by the test sink. + expected_groups: List of (tts_text, foo_label) pairs, one per TTSSpeakFrame. + tts_text is unused in assertions today but included for readability. + """ + relevant = [ + f + for f in down_frames + if isinstance( + f, (AggregatedTextFrame, TTSStartedFrame, TTSAudioRawFrame, TTSStoppedFrame, FooFrame) + ) + ] + + # Locate the FooFrames that delimit groups. + foo_indices = [i for i, f in enumerate(relevant) if isinstance(f, FooFrame)] + assert len(foo_indices) == len(expected_groups), ( + f"Expected {len(expected_groups)} FooFrames, got {len(foo_indices)}.\n" + f"Relevant frames: {[type(f).__name__ for f in relevant]}" + ) + + # Build groups: everything up to and including each FooFrame. + groups: List[List[Frame]] = [] + prev = 0 + for idx in foo_indices: + groups.append(relevant[prev : idx + 1]) + prev = idx + 1 + + for group, (_, foo_label) in zip(groups, expected_groups): + types = [type(f) for f in group] + type_names = [t.__name__ for t in types] + + assert AggregatedTextFrame in types, ( + f"Group {foo_label!r}: missing AggregatedTextFrame. Got: {type_names}" + ) + assert TTSStartedFrame in types, ( + f"Group {foo_label!r}: missing TTSStartedFrame. Got: {type_names}" + ) + assert TTSAudioRawFrame in types, ( + f"Group {foo_label!r}: missing TTSAudioRawFrame. Got: {type_names}" + ) + assert TTSStoppedFrame in types, ( + f"Group {foo_label!r}: missing TTSStoppedFrame. Got: {type_names}" + ) + + started_idx = types.index(TTSStartedFrame) + stopped_idx = types.index(TTSStoppedFrame) + foo_idx = types.index(FooFrame) + + assert started_idx < stopped_idx, ( + f"Group {foo_label!r}: TTSStartedFrame (pos {started_idx}) must precede " + f"TTSStoppedFrame (pos {stopped_idx}). Got: {type_names}" + ) + assert stopped_idx < foo_idx, ( + f"Group {foo_label!r}: TTSStoppedFrame (pos {stopped_idx}) must precede " + f"FooFrame (pos {foo_idx}). Got: {type_names}" + ) + + # All frames between TTSStartedFrame and TTSStoppedFrame must be audio. + mid_types = types[started_idx + 1 : stopped_idx] + for t in mid_types: + assert t is TTSAudioRawFrame, ( + f"Group {foo_label!r}: unexpected frame {t.__name__!r} between " + f"TTSStartedFrame and TTSStoppedFrame. Got: {type_names}" + ) + + # Check the FooFrame label. + actual_label = group[foo_idx].label + assert actual_label == foo_label, ( + f"Expected FooFrame(label={foo_label!r}), got label={actual_label!r}" + ) + + +# --------------------------------------------------------------------------- +# Tests +# --------------------------------------------------------------------------- + +_GROUPS = [("test 1", "1"), ("test 2", "2")] + + +def _make_frames_no_sleep() -> List[Frame]: + """Return two TTSSpeakFrame+FooFrame pairs sent back-to-back. + + Only correct for services that pause downstream processing until the audio + context is fully consumed (pause_frame_processing=True + on_audio_context_completed). + """ + return [ + TTSSpeakFrame(text="test 1", append_to_context=False), + FooFrame(label="1"), + TTSSpeakFrame(text="test 2", append_to_context=False), + FooFrame(label="2"), + ] + + +def _print_frames_received(frames_received) -> None: + print("FRAMES RECEIVED:") + for frame in frames_received[0]: + print(frame.name) + + +@pytest.mark.asyncio +async def test_http_tts_frame_ordering(): + """HTTP TTS services yield audio synchronously.""" + tts = MockHttpTTSService() + frames_received = await run_test(tts, frames_to_send=_make_frames_no_sleep()) + + # only for debugging + _print_frames_received(frames_received) + + _assert_group_ordering(frames_received[0], _GROUPS) + + +@pytest.mark.asyncio +async def test_websocket_tts_no_pause_frame_ordering(): + """WebSocket TTS services without pause_frame_processing.""" + tts = MockWebSocketTTSService() + frames_received = await run_test(tts, frames_to_send=_make_frames_no_sleep()) + _assert_group_ordering(frames_received[0], _GROUPS) + + +@pytest.mark.asyncio +async def test_websocket_tts_with_pause_frame_ordering(): + """WebSocket TTS services with pause_frame_processing=True.""" + tts = MockWebSocketPauseTTSService() + frames_received = await run_test(tts, frames_to_send=_make_frames_no_sleep()) + _assert_group_ordering(frames_received[0], _GROUPS) + + +if __name__ == "__main__": + unittest.main() From 2836b1ea7e7e6bc70e61c63551c8a3f526871f02 Mon Sep 17 00:00:00 2001 From: filipi87 Date: Thu, 19 Mar 2026 10:07:25 -0300 Subject: [PATCH 1022/1060] Fixing the frame ordering of the AggregatedTextFrame. --- src/pipecat/services/tts_service.py | 7 ++++++- 1 file changed, 6 insertions(+), 1 deletion(-) diff --git a/src/pipecat/services/tts_service.py b/src/pipecat/services/tts_service.py index 303072373..dd27314f5 100644 --- a/src/pipecat/services/tts_service.py +++ b/src/pipecat/services/tts_service.py @@ -1006,7 +1006,12 @@ class TTSService(AIService): # Route AggregatedTextFrame through the serialization queue so it is emitted # immediately before the TTSStartedFrame of the audio context it describes, # rather than racing ahead of audio frames from a previous context. - await self._serialization_queue.put(src_frame) + if not self.audio_context_available(context_id): + await self._serialization_queue.put(src_frame) + # Otherwise, if the context already exists, we append the AggregatedTextFrame + # to the existing context queue. + else: + await self.append_to_audio_context(context_id, src_frame) # Note: Text transformations are meant to only affect the text sent to the TTS for # TTS-specific purposes. This allows for explicit TTS modifications (e.g., inserting From 6841c0719bc2fc416c96879f92b8a6a25b40c06a Mon Sep 17 00:00:00 2001 From: filipi87 Date: Thu, 19 Mar 2026 10:12:01 -0300 Subject: [PATCH 1023/1060] Always appending TTSTextFrame to the audio context. --- src/pipecat/services/tts_service.py | 7 ++----- 1 file changed, 2 insertions(+), 5 deletions(-) diff --git a/src/pipecat/services/tts_service.py b/src/pipecat/services/tts_service.py index dd27314f5..f16c66191 100644 --- a/src/pipecat/services/tts_service.py +++ b/src/pipecat/services/tts_service.py @@ -1060,11 +1060,8 @@ class TTSService(AIService): # Only override append_to_context if explicitly set if append_tts_text_to_context is not None: frame.append_to_context = append_tts_text_to_context - # For services using the audio context we are appending to the context, so it preserves the ordering. - if self.audio_context_available(context_id): - await self.append_to_audio_context(context_id, frame) - else: - await self.push_frame(frame) + # Appending to the context, so it preserves the ordering. + await self.append_to_audio_context(context_id, frame) async def tts_process_generator( self, context_id: str, generator: AsyncGenerator[Frame | None, None] From 8f6dfc477731b1ca0122795b0ab19ac798dfd058 Mon Sep 17 00:00:00 2001 From: filipi87 Date: Thu, 19 Mar 2026 10:26:58 -0300 Subject: [PATCH 1024/1060] Mentioning the frame order fix in the changelog. --- changelog/4075.fixed.md | 1 + 1 file changed, 1 insertion(+) create mode 100644 changelog/4075.fixed.md diff --git a/changelog/4075.fixed.md b/changelog/4075.fixed.md new file mode 100644 index 000000000..97870d4bb --- /dev/null +++ b/changelog/4075.fixed.md @@ -0,0 +1 @@ +- Fixed TTS frame ordering so that non-system frames always arrive in correct order relative to the `TTSStartedFrame`/`TTSAudioRawFrame`/`TTSStoppedFrame` sequence. Previously these frames could race ahead of or behind audio context frames, producing out-of-order output downstream. From 0be40846834d8937f04712ca7a2348d800fdb90d Mon Sep 17 00:00:00 2001 From: Paul Kompfner Date: Fri, 13 Mar 2026 12:29:32 -0400 Subject: [PATCH 1025/1060] Fix bug resulting in `SyncParallelPipeline` breaking the Whisker debugger --- src/pipecat/pipeline/sync_parallel_pipeline.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/src/pipecat/pipeline/sync_parallel_pipeline.py b/src/pipecat/pipeline/sync_parallel_pipeline.py index cb3f1bbe0..48d66d3b8 100644 --- a/src/pipecat/pipeline/sync_parallel_pipeline.py +++ b/src/pipecat/pipeline/sync_parallel_pipeline.py @@ -184,7 +184,7 @@ class SyncParallelPipeline(BasePipeline): Returns: The list of entry processors. """ - return self._sources + return [s["processor"] for s in self._sources] def processors_with_metrics(self) -> List[FrameProcessor]: """Collect processors that can generate metrics from all parallel pipelines. From 463db59bb5b1cda95cc697b0b2aabd2d70240571 Mon Sep 17 00:00:00 2001 From: Paul Kompfner Date: Fri, 13 Mar 2026 13:40:26 -0400 Subject: [PATCH 1026/1060] Minor comment typo fix --- src/pipecat/pipeline/sync_parallel_pipeline.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/src/pipecat/pipeline/sync_parallel_pipeline.py b/src/pipecat/pipeline/sync_parallel_pipeline.py index 48d66d3b8..3597b0e9e 100644 --- a/src/pipecat/pipeline/sync_parallel_pipeline.py +++ b/src/pipecat/pipeline/sync_parallel_pipeline.py @@ -225,7 +225,7 @@ class SyncParallelPipeline(BasePipeline): # this element won't work. Since, we know it should be synchronous we # push a SyncFrame. Since frames are ordered we know this frame will be # pushed after the synchronous processor has pushed its data allowing us - # to synchrnonize all the internal pipelines by waiting for the + # to synchronize all the internal pipelines by waiting for the # SyncFrame in all of them. async def wait_for_sync( obj, main_queue: asyncio.Queue, frame: Frame, direction: FrameDirection From 1ede8460a2d775ea9580f53af0f7a772b39c7df6 Mon Sep 17 00:00:00 2001 From: Paul Kompfner Date: Fri, 13 Mar 2026 14:17:35 -0400 Subject: [PATCH 1027/1060] Fix SyncParallelPipeline race condition with concurrent SystemFrame processing MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit The FrameProcessor two-queue architecture processes SystemFrames and non-SystemFrames on separate concurrent async tasks. Both paths called SyncParallelPipeline.process_frame(), which used the same per-pipeline sink queues. A SystemFrame's wait_for_sync could steal frames from a concurrent non-SystemFrame's wait_for_sync, corrupting synchronization and stalling the pipeline. This was triggered by the auto-embedded RTVI processor (added in v0.0.101) which floods OutputTransportMessageUrgentFrame SystemFrames through the pipeline during LLM responses. Fix: SystemFrames (except EndFrame) now take a fast path — passed through internal pipelines and pushed downstream directly without touching the sink queues or drain logic. EndFrame retains the full drain behavior as a lifecycle frame. --- .../pipeline/sync_parallel_pipeline.py | 20 ++++++++++++++++--- 1 file changed, 17 insertions(+), 3 deletions(-) diff --git a/src/pipecat/pipeline/sync_parallel_pipeline.py b/src/pipecat/pipeline/sync_parallel_pipeline.py index 3597b0e9e..00af35bbf 100644 --- a/src/pipecat/pipeline/sync_parallel_pipeline.py +++ b/src/pipecat/pipeline/sync_parallel_pipeline.py @@ -221,6 +221,20 @@ class SyncParallelPipeline(BasePipeline): """ await super().process_frame(frame, direction) + # SystemFrames (but not EndFrame) are simply passed through all + # internal pipelines without draining queued output. This avoids + # the race condition where a SystemFrame's wait_for_sync steals + # frames from a concurrent non-SystemFrame's wait_for_sync. + if isinstance(frame, SystemFrame) and not isinstance(frame, EndFrame): + if direction == FrameDirection.UPSTREAM: + for s in self._sinks: + await s["processor"].process_frame(frame, direction) + elif direction == FrameDirection.DOWNSTREAM: + for s in self._sources: + await s["processor"].process_frame(frame, direction) + await self.push_frame(frame, direction) + return + # The last processor of each pipeline needs to be synchronous otherwise # this element won't work. Since, we know it should be synchronous we # push a SyncFrame. Since frames are ordered we know this frame will be @@ -235,12 +249,12 @@ class SyncParallelPipeline(BasePipeline): await processor.process_frame(frame, direction) - if isinstance(frame, (SystemFrame, EndFrame)): + if isinstance(frame, EndFrame): new_frame = await queue.get() - if isinstance(new_frame, (SystemFrame, EndFrame)): + if isinstance(new_frame, EndFrame): await main_queue.put(new_frame) else: - while not isinstance(new_frame, (SystemFrame, EndFrame)): + while not isinstance(new_frame, EndFrame): await main_queue.put(new_frame) queue.task_done() new_frame = await queue.get() From 0f1ff16af12e26e9cf05e4c6b2add398ff6f96b5 Mon Sep 17 00:00:00 2001 From: Paul Kompfner Date: Fri, 13 Mar 2026 15:15:45 -0400 Subject: [PATCH 1028/1060] Add sync_with_audio support for OutputImageRawFrame Add a `sync_with_audio` field to `OutputImageRawFrame` that routes image frames through the audio queue in the output transport, ensuring images are only displayed after all preceding audio has been sent. This enables proper audio/image synchronization in pipelines like the calendar month narration example. Update the 05-sync-speech-and-image example to use an `ImageAudioSync` processor that sets this flag on image frames. --- .../foundational/05-sync-speech-and-image.py | 18 +++++++++++++++++- src/pipecat/frames/frames.py | 8 ++++++++ src/pipecat/transports/base_output.py | 6 +++++- 3 files changed, 30 insertions(+), 2 deletions(-) diff --git a/examples/foundational/05-sync-speech-and-image.py b/examples/foundational/05-sync-speech-and-image.py index 1e4cf34a4..35f8f411c 100644 --- a/examples/foundational/05-sync-speech-and-image.py +++ b/examples/foundational/05-sync-speech-and-image.py @@ -16,6 +16,7 @@ from pipecat.frames.frames import ( Frame, LLMContextFrame, LLMFullResponseStartFrame, + OutputImageRawFrame, TextFrame, ) from pipecat.pipeline.pipeline import Pipeline @@ -44,6 +45,18 @@ class MonthFrame(DataFrame): return f"{self.name}(month: {self.month})" +class ImageAudioSync(FrameProcessor): + """Marks output image frames to be synchronized with audio playback.""" + + async def process_frame(self, frame: Frame, direction: FrameDirection): + await super().process_frame(frame, direction) + + if isinstance(frame, OutputImageRawFrame): + frame.sync_with_audio = True + + await self.push_frame(frame, direction) + + class MonthPrepender(FrameProcessor): def __init__(self): super().__init__() @@ -129,7 +142,10 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): sentence_aggregator, # Aggregates LLM output into full sentences SyncParallelPipeline( # Run pipelines in parallel aggregating the result [month_prepender, tts], # Create "Month: sentence" and output audio - [imagegen], # Generate image + [ + imagegen, # Generate image + ImageAudioSync(), # Mark image as needing sync output w/audio + ], ), transport.output(), # Transport output ] diff --git a/src/pipecat/frames/frames.py b/src/pipecat/frames/frames.py index fbc01c488..7107cfd97 100644 --- a/src/pipecat/frames/frames.py +++ b/src/pipecat/frames/frames.py @@ -274,8 +274,16 @@ class OutputImageRawFrame(DataFrame, ImageRawFrame): An image that will be shown by the transport. If the transport supports multiple video destinations (e.g. multiple video tracks) the destination name can be specified in transport_destination. + + Parameters: + sync_with_audio: If True, the image is queued with audio frames so + it is only displayed after all preceding audio has been sent. + Defaults to False (image is displayed immediately when the output + transport receives it). """ + sync_with_audio: bool = field(default=False, init=False) + def __str__(self): pts = format_pts(self.pts) return f"{self.name}(pts: {pts}, destination: {self.transport_destination}, size: {self.size}, format: {self.format})" diff --git a/src/pipecat/transports/base_output.py b/src/pipecat/transports/base_output.py index e14ae3828..01af97be8 100644 --- a/src/pipecat/transports/base_output.py +++ b/src/pipecat/transports/base_output.py @@ -569,7 +569,11 @@ class BaseOutputTransport(FrameProcessor): if not self._params.video_out_enabled: return - if self._params.video_out_is_live and isinstance(frame, OutputImageRawFrame): + if isinstance(frame, OutputImageRawFrame) and frame.sync_with_audio: + # Route through the audio queue so the image is only + # displayed after all preceding audio has been sent. + await self._audio_queue.put(frame) + elif self._params.video_out_is_live and isinstance(frame, OutputImageRawFrame): await self._video_queue.put(frame) elif isinstance(frame, OutputImageRawFrame): await self._set_video_image(frame) From c3d6e965d80f10f491d0cf62bec7a57663c79fd5 Mon Sep 17 00:00:00 2001 From: Paul Kompfner Date: Fri, 13 Mar 2026 18:43:54 -0400 Subject: [PATCH 1029/1060] Use TextAggregationMode.TOKEN in the 05-sync-speech-and-image example since the SentenceAggregator already provides complete sentences. --- examples/foundational/05-sync-speech-and-image.py | 5 +++++ src/pipecat/processors/frame_processor.py | 4 ++-- 2 files changed, 7 insertions(+), 2 deletions(-) diff --git a/examples/foundational/05-sync-speech-and-image.py b/examples/foundational/05-sync-speech-and-image.py index 35f8f411c..b896261ae 100644 --- a/examples/foundational/05-sync-speech-and-image.py +++ b/examples/foundational/05-sync-speech-and-image.py @@ -31,6 +31,7 @@ from pipecat.runner.utils import create_transport from pipecat.services.cartesia.tts import CartesiaHttpTTSService from pipecat.services.fal.image import FalImageGenService from pipecat.services.openai.llm import OpenAILLMService +from pipecat.services.tts_service import TextAggregationMode from pipecat.transports.base_transport import BaseTransport, TransportParams from pipecat.transports.daily.transport import DailyParams @@ -114,6 +115,10 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): settings=CartesiaHttpTTSService.Settings( voice="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady ), + # No need to aggregate by sentences (the default), as we already know we're getting full sentences + # (Otherwise the service will unnecessarily wait for follow-up input to confirm the sentence is complete, + # which, sadly, actually breaks the synchronization mechanism) + text_aggregation_mode=TextAggregationMode.TOKEN, ) imagegen = FalImageGenService( diff --git a/src/pipecat/processors/frame_processor.py b/src/pipecat/processors/frame_processor.py index f3d9fbdea..a74ee4f81 100644 --- a/src/pipecat/processors/frame_processor.py +++ b/src/pipecat/processors/frame_processor.py @@ -633,7 +633,7 @@ class FrameProcessor(BaseObject): async def pause_processing_frames(self): """Pause processing of queued frames.""" - logger.trace(f"{self}: pausing frame processing") + logger.debug(f"{self}: pausing frame processing") self.__should_block_frames = True if self.__process_event: self.__process_event.clear() @@ -647,7 +647,7 @@ class FrameProcessor(BaseObject): async def resume_processing_frames(self): """Resume processing of queued frames.""" - logger.trace(f"{self}: resuming frame processing") + logger.debug(f"{self}: resuming frame processing") if self.__process_event: self.__process_event.set() From ba779f920fcd2f7a3f8f48218299911ed782785d Mon Sep 17 00:00:00 2001 From: Paul Kompfner Date: Fri, 13 Mar 2026 21:04:16 -0400 Subject: [PATCH 1030/1060] Revert a couple of logs that were changed from `trace` to `debug` just for debugging --- src/pipecat/processors/frame_processor.py | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/src/pipecat/processors/frame_processor.py b/src/pipecat/processors/frame_processor.py index a74ee4f81..f3d9fbdea 100644 --- a/src/pipecat/processors/frame_processor.py +++ b/src/pipecat/processors/frame_processor.py @@ -633,7 +633,7 @@ class FrameProcessor(BaseObject): async def pause_processing_frames(self): """Pause processing of queued frames.""" - logger.debug(f"{self}: pausing frame processing") + logger.trace(f"{self}: pausing frame processing") self.__should_block_frames = True if self.__process_event: self.__process_event.clear() @@ -647,7 +647,7 @@ class FrameProcessor(BaseObject): async def resume_processing_frames(self): """Resume processing of queued frames.""" - logger.debug(f"{self}: resuming frame processing") + logger.trace(f"{self}: resuming frame processing") if self.__process_event: self.__process_event.set() From 5e7639812aee582ab9f1435cfdfa5b25ba318706 Mon Sep 17 00:00:00 2001 From: Paul Kompfner Date: Fri, 13 Mar 2026 22:09:44 -0400 Subject: [PATCH 1031/1060] Add ImageBeforeAudioReorderer to sync-speech-and-image example Add a processor after SyncParallelPipeline that ensures each image frame precedes its corresponding TTS audio frames. SyncParallelPipeline batches them together but doesn't guarantee branch ordering. The reorderer detects when TTS frames arrive before their image (via context_id tracking) and holds them until the image arrives. Also rename ImageAudioSync to MarkImageForPlaybackSync for clarity. --- .../foundational/05-sync-speech-and-image.py | 65 ++++++++++++++++++- 1 file changed, 63 insertions(+), 2 deletions(-) diff --git a/examples/foundational/05-sync-speech-and-image.py b/examples/foundational/05-sync-speech-and-image.py index b896261ae..646235e7c 100644 --- a/examples/foundational/05-sync-speech-and-image.py +++ b/examples/foundational/05-sync-speech-and-image.py @@ -12,12 +12,17 @@ from dotenv import load_dotenv from loguru import logger from pipecat.frames.frames import ( + AggregatedTextFrame, DataFrame, Frame, LLMContextFrame, LLMFullResponseStartFrame, OutputImageRawFrame, TextFrame, + TTSAudioRawFrame, + TTSStartedFrame, + TTSStoppedFrame, + TTSTextFrame, ) from pipecat.pipeline.pipeline import Pipeline from pipecat.pipeline.runner import PipelineRunner @@ -46,7 +51,7 @@ class MonthFrame(DataFrame): return f"{self.name}(month: {self.month})" -class ImageAudioSync(FrameProcessor): +class MarkImageForPlaybackSync(FrameProcessor): """Marks output image frames to be synchronized with audio playback.""" async def process_frame(self, frame: Frame, direction: FrameDirection): @@ -58,6 +63,61 @@ class ImageAudioSync(FrameProcessor): await self.push_frame(frame, direction) +class ImageBeforeAudioReorderer(FrameProcessor): + """Ensures each image frame precedes its corresponding TTS audio frames. + + SyncParallelPipeline guarantees that each image is in the same synchronized + batch as its audio, but doesn't guarantee which branch's output comes first. + This processor detects when TTS frames arrive before their image and holds + them until the image arrives. + + All frames pass through immediately unless we detect an ordering problem: + TTS frames arrived without a preceding image for the current batch (identified + by context_id). In that case, the TTS frames are held until the next image + frame, which is pushed first. + """ + + def __init__(self): + super().__init__() + self._held_tts_frames = [] + self._seen_image = False + self._current_context_id = None + + async def process_frame(self, frame: Frame, direction: FrameDirection): + await super().process_frame(frame, direction) + + if isinstance(frame, OutputImageRawFrame): + self._seen_image = True + if self._held_tts_frames: + # Image arrived after TTS frames — push image first, then release held frames. + logger.debug("ImageBeforeAudioReorderer: reordered — moved image before audio") + await self.push_frame(frame, direction) + for f in self._held_tts_frames: + await self.push_frame(f, direction) + self._held_tts_frames = [] + else: + logger.debug( + "ImageBeforeAudioReorderer: no reorder needed — image was already first" + ) + await self.push_frame(frame, direction) + elif isinstance( + frame, + (AggregatedTextFrame, TTSStartedFrame, TTSAudioRawFrame, TTSStoppedFrame, TTSTextFrame), + ): + # A new context_id means a new batch — reset image tracking. + context_id = frame.context_id + if context_id and context_id != self._current_context_id: + self._current_context_id = context_id + self._seen_image = False + + if self._seen_image: + await self.push_frame(frame, direction) + else: + self._held_tts_frames.append(frame) + else: + await self.push_frame(frame, direction) + + class MonthPrepender(FrameProcessor): def __init__(self): super().__init__() @@ -149,9 +209,10 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): [month_prepender, tts], # Create "Month: sentence" and output audio [ imagegen, # Generate image - ImageAudioSync(), # Mark image as needing sync output w/audio + MarkImageForPlaybackSync(), # Mark image as needing sync w/audio during playback ], ), + ImageBeforeAudioReorderer(), # Ensure each image precedes its audio (important for playback) transport.output(), # Transport output ] ) From 61ff53f2b968c8acc435c8492e2027fa8035ab0e Mon Sep 17 00:00:00 2001 From: Paul Kompfner Date: Fri, 13 Mar 2026 22:15:32 -0400 Subject: [PATCH 1032/1060] Add changelog entries for PR #4029 --- changelog/4029.added.md | 1 + changelog/4029.fixed.2.md | 1 + changelog/4029.fixed.md | 1 + 3 files changed, 3 insertions(+) create mode 100644 changelog/4029.added.md create mode 100644 changelog/4029.fixed.2.md create mode 100644 changelog/4029.fixed.md diff --git a/changelog/4029.added.md b/changelog/4029.added.md new file mode 100644 index 000000000..ba3714483 --- /dev/null +++ b/changelog/4029.added.md @@ -0,0 +1 @@ +- Added `sync_with_audio` field to `OutputImageRawFrame`. When set to `True`, the output transport queues image frames with audio so they are displayed only after all preceding audio has been sent, enabling synchronized audio/image playback. diff --git a/changelog/4029.fixed.2.md b/changelog/4029.fixed.2.md new file mode 100644 index 000000000..faf54592e --- /dev/null +++ b/changelog/4029.fixed.2.md @@ -0,0 +1 @@ +- Fixed TTS frame ordering when an audio context is active. Pass-through frames are now routed through the audio context queue so they stay properly ordered with TTS audio frames. Previously, a frame that preceded some incoming text to a TTS service could "jump the queue", getting ahead of the outgoing audio. diff --git a/changelog/4029.fixed.md b/changelog/4029.fixed.md new file mode 100644 index 000000000..57930a997 --- /dev/null +++ b/changelog/4029.fixed.md @@ -0,0 +1 @@ +- Fixed `SyncParallelPipeline` race condition where concurrent SystemFrame processing (e.g. from RTVI) could corrupt sink queues and cause deadlocks. SystemFrames now take a fast path that passes them through without draining queued output. From 26fc238eb7e558ee414e3faf00bb0b3456b3d546 Mon Sep 17 00:00:00 2001 From: Paul Kompfner Date: Fri, 13 Mar 2026 22:20:53 -0400 Subject: [PATCH 1033/1060] Add changelog entry for Whisker debugger fix --- changelog/4029.fixed.3.md | 1 + 1 file changed, 1 insertion(+) create mode 100644 changelog/4029.fixed.3.md diff --git a/changelog/4029.fixed.3.md b/changelog/4029.fixed.3.md new file mode 100644 index 000000000..3c812d590 --- /dev/null +++ b/changelog/4029.fixed.3.md @@ -0,0 +1 @@ +- Fixed `SyncParallelPipeline` breaking the Whisker debugger. From d702ebd6a29519af2ea50f5a6b8d208901342139 Mon Sep 17 00:00:00 2001 From: Paul Kompfner Date: Mon, 16 Mar 2026 09:59:13 -0400 Subject: [PATCH 1034/1060] Add frame_order parameter to SyncParallelPipeline MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit Adds a FrameOrder enum with ARRIVAL (default, existing behavior) and PIPELINE (pushes frames in pipeline definition order). This lets callers guarantee output ordering between parallel pipelines — e.g. ensuring image frames precede audio frames — without needing a separate reordering processor downstream. Updates the 05-sync-speech-and-image example to use FrameOrder.PIPELINE, removing the ImageBeforeAudioReorderer class entirely. --- changelog/4029.added.2.md | 1 + .../foundational/05-sync-speech-and-image.py | 73 ++--------- .../pipeline/sync_parallel_pipeline.py | 111 +++++++++++++---- tests/test_sync_parallel_pipeline.py | 117 ++++++++++++++++++ 4 files changed, 214 insertions(+), 88 deletions(-) create mode 100644 changelog/4029.added.2.md create mode 100644 tests/test_sync_parallel_pipeline.py diff --git a/changelog/4029.added.2.md b/changelog/4029.added.2.md new file mode 100644 index 000000000..1ae691442 --- /dev/null +++ b/changelog/4029.added.2.md @@ -0,0 +1 @@ +- Added `frame_order` parameter to `SyncParallelPipeline`. Set `frame_order=FrameOrder.PIPELINE` to push synchronized output frames in pipeline definition order (all frames from the first pipeline, then the second, etc.) instead of the default arrival order. diff --git a/examples/foundational/05-sync-speech-and-image.py b/examples/foundational/05-sync-speech-and-image.py index 646235e7c..f0e2ff9c7 100644 --- a/examples/foundational/05-sync-speech-and-image.py +++ b/examples/foundational/05-sync-speech-and-image.py @@ -12,21 +12,16 @@ from dotenv import load_dotenv from loguru import logger from pipecat.frames.frames import ( - AggregatedTextFrame, DataFrame, Frame, LLMContextFrame, LLMFullResponseStartFrame, OutputImageRawFrame, TextFrame, - TTSAudioRawFrame, - TTSStartedFrame, - TTSStoppedFrame, - TTSTextFrame, ) from pipecat.pipeline.pipeline import Pipeline from pipecat.pipeline.runner import PipelineRunner -from pipecat.pipeline.sync_parallel_pipeline import SyncParallelPipeline +from pipecat.pipeline.sync_parallel_pipeline import FrameOrder, SyncParallelPipeline from pipecat.pipeline.task import PipelineTask from pipecat.processors.aggregators.llm_context import LLMContext from pipecat.processors.aggregators.sentence import SentenceAggregator @@ -63,61 +58,6 @@ class MarkImageForPlaybackSync(FrameProcessor): await self.push_frame(frame, direction) -class ImageBeforeAudioReorderer(FrameProcessor): - """Ensures each image frame precedes its corresponding TTS audio frames. - - SyncParallelPipeline guarantees that each image is in the same synchronized - batch as its audio, but doesn't guarantee which branch's output comes first. - This processor detects when TTS frames arrive before their image and holds - them until the image arrives. - - All frames pass through immediately unless we detect an ordering problem: - TTS frames arrived without a preceding image for the current batch (identified - by context_id). In that case, the TTS frames are held until the next image - frame, which is pushed first. - """ - - def __init__(self): - super().__init__() - self._held_tts_frames = [] - self._seen_image = False - self._current_context_id = None - - async def process_frame(self, frame: Frame, direction: FrameDirection): - await super().process_frame(frame, direction) - - if isinstance(frame, OutputImageRawFrame): - self._seen_image = True - if self._held_tts_frames: - # Image arrived after TTS frames — push image first, then release held frames. - logger.debug("ImageBeforeAudioReorderer: reordered — moved image before audio") - await self.push_frame(frame, direction) - for f in self._held_tts_frames: - await self.push_frame(f, direction) - self._held_tts_frames = [] - else: - logger.debug( - "ImageBeforeAudioReorderer: no reorder needed — image was already first" - ) - await self.push_frame(frame, direction) - elif isinstance( - frame, - (AggregatedTextFrame, TTSStartedFrame, TTSAudioRawFrame, TTSStoppedFrame, TTSTextFrame), - ): - # A new context_id means a new batch — reset image tracking. - context_id = frame.context_id - if context_id and context_id != self._current_context_id: - self._current_context_id = context_id - self._seen_image = False - - if self._seen_image: - await self.push_frame(frame, direction) - else: - self._held_tts_frames.append(frame) - else: - await self.push_frame(frame, direction) - - class MonthPrepender(FrameProcessor): def __init__(self): super().__init__() @@ -197,22 +137,27 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): # that, each pipeline runs concurrently and `SyncParallelPipeline` will # wait for the input frame to be processed. # + # We use `FrameOrder.PIPELINE` so that each synchronized batch of output + # frames is pushed in the order the pipelines are listed: image first, + # then audio. This ensures the transport receives the image before the + # audio frames it should accompany. + # # Note that `SyncParallelPipeline` requires the last processor in each # of the pipelines to be synchronous. In this case, we use - # `CartesiaHttpTTSService` and `FalImageGenService` which make HTTP + # `FalImageGenService` and `CartesiaHttpTTSService` which make HTTP # requests and wait for the response. pipeline = Pipeline( [ llm, # LLM sentence_aggregator, # Aggregates LLM output into full sentences SyncParallelPipeline( # Run pipelines in parallel aggregating the result - [month_prepender, tts], # Create "Month: sentence" and output audio [ imagegen, # Generate image MarkImageForPlaybackSync(), # Mark image as needing sync w/audio during playback ], + [month_prepender, tts], # Create "Month: sentence" and output audio + frame_order=FrameOrder.PIPELINE, ), - ImageBeforeAudioReorderer(), # Ensure each image precedes its audio (important for playback) transport.output(), # Transport output ] ) diff --git a/src/pipecat/pipeline/sync_parallel_pipeline.py b/src/pipecat/pipeline/sync_parallel_pipeline.py index 00af35bbf..9870f03f3 100644 --- a/src/pipecat/pipeline/sync_parallel_pipeline.py +++ b/src/pipecat/pipeline/sync_parallel_pipeline.py @@ -13,6 +13,7 @@ and prevent duplicate processing. import asyncio from dataclasses import dataclass +from enum import Enum from itertools import chain from typing import List @@ -24,6 +25,25 @@ from pipecat.pipeline.pipeline import Pipeline from pipecat.processors.frame_processor import FrameDirection, FrameProcessor, FrameProcessorSetup +class FrameOrder(Enum): + """Controls the order in which synchronized frames are pushed downstream. + + When multiple parallel pipelines produce output for the same input frame, + this setting determines the order in which those output frames are pushed. + + Attributes: + ARRIVAL: Frames are pushed in the order they arrive from any pipeline. + This is the default and matches the behavior of prior versions. + PIPELINE: Frames are pushed in pipeline definition order — all frames + from the first pipeline are pushed, then all frames from the second + pipeline, and so on. Useful when the relative ordering between + pipelines matters (e.g. ensuring image frames precede audio frames). + """ + + ARRIVAL = "arrival" + PIPELINE = "pipeline" + + @dataclass class SyncFrame(ControlFrame): """Control frame used to synchronize parallel pipeline processing. @@ -109,20 +129,30 @@ class SyncParallelPipeline(BasePipeline): The pipeline uses SyncFrame control frames to coordinate between parallel paths and ensure all paths have completed processing before moving to the next frame. + + By default, output frames are pushed in the order they arrive from any pipeline + (``FrameOrder.ARRIVAL``). Set ``frame_order=FrameOrder.PIPELINE`` to push frames + in pipeline definition order instead — all output from the first pipeline, then + the second, and so on. """ - def __init__(self, *args): + def __init__(self, *args, frame_order: FrameOrder = FrameOrder.ARRIVAL): """Initialize the synchronous parallel pipeline. Args: - *args: Variable number of processor lists, each representing a parallel pipeline path. - Each argument should be a list of FrameProcessor instances. + *args: Variable number of processor lists, each representing a parallel + pipeline path. Each argument should be a list of FrameProcessor instances. + frame_order: Controls the order in which synchronized output frames are + pushed. ``FrameOrder.ARRIVAL`` (default) pushes frames in the order they arrive. + ``FrameOrder.PIPELINE`` pushes all frames from the first pipeline + before the second, and so on. Raises: Exception: If no arguments are provided. TypeError: If any argument is not a list of processors. """ super().__init__() + self._frame_order = frame_order if len(args) == 0: raise Exception(f"SyncParallelPipeline needs at least one argument") @@ -215,6 +245,11 @@ class SyncParallelPipeline(BasePipeline): to maintain proper ordering and prevent duplicate processing. Uses SyncFrame control frames to coordinate between parallel paths. + When ``frame_order`` is ``FrameOrder.ARRIVAL``, output frames are pushed in + the order they arrive from any pipeline (via a shared queue). When it is + ``FrameOrder.PIPELINE``, each pipeline collects its output into a separate + list and the lists are drained in pipeline definition order. + Args: frame: The frame to process. direction: The direction of frame flow. @@ -235,60 +270,88 @@ class SyncParallelPipeline(BasePipeline): await self.push_frame(frame, direction) return + use_pipeline_order = self._frame_order == FrameOrder.PIPELINE + # The last processor of each pipeline needs to be synchronous otherwise - # this element won't work. Since, we know it should be synchronous we + # this element won't work. Since we know it should be synchronous we # push a SyncFrame. Since frames are ordered we know this frame will be # pushed after the synchronous processor has pushed its data allowing us # to synchronize all the internal pipelines by waiting for the # SyncFrame in all of them. + # + # In ARRIVAL mode, output frames are put onto a shared main_queue as + # they arrive. In PIPELINE mode, they are accumulated in a per-pipeline + # list and returned so the caller can drain them in definition order. async def wait_for_sync( obj, main_queue: asyncio.Queue, frame: Frame, direction: FrameDirection - ): + ) -> list[Frame]: processor = obj["processor"] queue = obj["queue"] + output_frames: list[Frame] = [] await processor.process_frame(frame, direction) if isinstance(frame, EndFrame): new_frame = await queue.get() if isinstance(new_frame, EndFrame): - await main_queue.put(new_frame) + if use_pipeline_order: + output_frames.append(new_frame) + else: + await main_queue.put(new_frame) else: while not isinstance(new_frame, EndFrame): - await main_queue.put(new_frame) + if use_pipeline_order: + output_frames.append(new_frame) + else: + await main_queue.put(new_frame) queue.task_done() new_frame = await queue.get() else: await processor.process_frame(SyncFrame(), direction) new_frame = await queue.get() while not isinstance(new_frame, SyncFrame): - await main_queue.put(new_frame) + if use_pipeline_order: + output_frames.append(new_frame) + else: + await main_queue.put(new_frame) queue.task_done() new_frame = await queue.get() + return output_frames + if direction == FrameDirection.UPSTREAM: # If we get an upstream frame we process it in each sink. - await asyncio.gather( + frames_per_pipeline = await asyncio.gather( *[wait_for_sync(s, self._up_queue, frame, direction) for s in self._sinks] ) elif direction == FrameDirection.DOWNSTREAM: # If we get a downstream frame we process it in each source. - await asyncio.gather( + frames_per_pipeline = await asyncio.gather( *[wait_for_sync(s, self._down_queue, frame, direction) for s in self._sources] ) - seen_ids = set() - while not self._up_queue.empty(): - frame = await self._up_queue.get() - if frame.id not in seen_ids: - await self.push_frame(frame, FrameDirection.UPSTREAM) - seen_ids.add(frame.id) - self._up_queue.task_done() + if use_pipeline_order: + # Push frames in pipeline definition order, deduplicating by id. + seen_ids = set() + for pipeline_frames in frames_per_pipeline: + for f in pipeline_frames: + if f.id not in seen_ids: + await self.push_frame(f, direction) + seen_ids.add(f.id) + else: + # ARRIVAL mode: drain the shared queues in the order frames arrived. + seen_ids = set() + while not self._up_queue.empty(): + frame = await self._up_queue.get() + if frame.id not in seen_ids: + await self.push_frame(frame, FrameDirection.UPSTREAM) + seen_ids.add(frame.id) + self._up_queue.task_done() - seen_ids = set() - while not self._down_queue.empty(): - frame = await self._down_queue.get() - if frame.id not in seen_ids: - await self.push_frame(frame, FrameDirection.DOWNSTREAM) - seen_ids.add(frame.id) - self._down_queue.task_done() + seen_ids = set() + while not self._down_queue.empty(): + frame = await self._down_queue.get() + if frame.id not in seen_ids: + await self.push_frame(frame, FrameDirection.DOWNSTREAM) + seen_ids.add(frame.id) + self._down_queue.task_done() diff --git a/tests/test_sync_parallel_pipeline.py b/tests/test_sync_parallel_pipeline.py new file mode 100644 index 000000000..6c6faf7c7 --- /dev/null +++ b/tests/test_sync_parallel_pipeline.py @@ -0,0 +1,117 @@ +# +# Copyright (c) 2024-2026, Daily +# +# SPDX-License-Identifier: BSD 2-Clause License +# + +import asyncio +import unittest +from dataclasses import dataclass + +from pipecat.frames.frames import Frame, TextFrame +from pipecat.pipeline.sync_parallel_pipeline import FrameOrder, SyncParallelPipeline +from pipecat.processors.filters.identity_filter import IdentityFilter +from pipecat.processors.frame_processor import FrameDirection, FrameProcessor +from pipecat.tests.utils import run_test + + +@dataclass +class TaggedFrame(Frame): + """A simple tagged frame for testing pipeline ordering.""" + + tag: str = "" + + def __str__(self): + return f"{self.name}(tag: {self.tag})" + + +class EmitTaggedFrameProcessor(FrameProcessor): + """Emits a TaggedFrame for every TextFrame it receives. + + Used to produce distinguishable output from different pipelines so tests + can verify ordering. + """ + + def __init__(self, tag: str, *, delay: float = 0, **kwargs): + super().__init__(**kwargs) + self._tag = tag + self._delay = delay + + async def process_frame(self, frame: Frame, direction: FrameDirection): + await super().process_frame(frame, direction) + + if isinstance(frame, TextFrame): + if self._delay > 0: + await asyncio.sleep(self._delay) + await self.push_frame(TaggedFrame(tag=self._tag)) + else: + await self.push_frame(frame, direction) + + +class TestSyncParallelPipeline(unittest.IsolatedAsyncioTestCase): + async def test_dedup_multiple_frames(self): + """Identical frames from multiple paths should be deduplicated.""" + pipeline = SyncParallelPipeline([IdentityFilter()], [IdentityFilter()]) + + frames_to_send = [TextFrame(text="one"), TextFrame(text="two")] + expected_down_frames = [TextFrame, TextFrame] + await run_test( + pipeline, + frames_to_send=frames_to_send, + expected_down_frames=expected_down_frames, + ) + + async def test_arrival_order(self): + """With FrameOrder.ARRIVAL, a slow first pipeline's frames should + arrive after a fast second pipeline's frames.""" + pipeline = SyncParallelPipeline( + [EmitTaggedFrameProcessor("slow", delay=0.05)], + [EmitTaggedFrameProcessor("fast")], + frame_order=FrameOrder.ARRIVAL, + ) + + frames_to_send = [TextFrame(text="one"), TextFrame(text="two")] + (down_frames, _) = await run_test( + pipeline, + frames_to_send=frames_to_send, + ) + + tags = [f.tag for f in down_frames if isinstance(f, TaggedFrame)] + assert tags == [ + "fast", + "slow", + "fast", + "slow", + ], f"Expected fast before slow in each batch, got {tags}" + + async def test_pipeline_order(self): + """With FrameOrder.PIPELINE and multiple input frames, each batch + should follow pipeline definition order regardless of processing speed.""" + pipeline = SyncParallelPipeline( + [EmitTaggedFrameProcessor("slow", delay=0.05)], + [EmitTaggedFrameProcessor("fast")], + frame_order=FrameOrder.PIPELINE, + ) + + frames_to_send = [TextFrame(text="one"), TextFrame(text="two")] + (down_frames, _) = await run_test( + pipeline, + frames_to_send=frames_to_send, + ) + + tags = [f.tag for f in down_frames if isinstance(f, TaggedFrame)] + assert tags == [ + "slow", + "fast", + "slow", + "fast", + ], f"Expected pipeline definition order (slow, fast) in each batch, got {tags}" + + async def test_default_is_arrival(self): + """The default frame_order should be ARRIVAL.""" + pipeline = SyncParallelPipeline([IdentityFilter()]) + assert pipeline._frame_order == FrameOrder.ARRIVAL + + +if __name__ == "__main__": + unittest.main() From 06f7da44f19b8fa949b8335273df3d3a970aabd8 Mon Sep 17 00:00:00 2001 From: Paul Kompfner Date: Wed, 18 Mar 2026 16:39:20 -0400 Subject: [PATCH 1035/1060] Clarify SyncParallelPipeline docstrings Rewrite docstrings to more clearly explain what SyncParallelPipeline does: hold all output until every parallel branch finishes, so frames produced in response to a single input are released together. --- .../pipeline/sync_parallel_pipeline.py | 65 ++++++++++--------- 1 file changed, 36 insertions(+), 29 deletions(-) diff --git a/src/pipecat/pipeline/sync_parallel_pipeline.py b/src/pipecat/pipeline/sync_parallel_pipeline.py index 9870f03f3..148d29b25 100644 --- a/src/pipecat/pipeline/sync_parallel_pipeline.py +++ b/src/pipecat/pipeline/sync_parallel_pipeline.py @@ -4,11 +4,16 @@ # SPDX-License-Identifier: BSD 2-Clause License # -"""Synchronous parallel pipeline implementation for concurrent frame processing. +"""Synchronized parallel pipeline that holds output until all branches finish. -This module provides a pipeline that processes frames through multiple parallel -pipelines simultaneously, synchronizing their output to maintain frame ordering -and prevent duplicate processing. +A SyncParallelPipeline fans each inbound frame out to multiple parallel pipelines +and waits for every pipeline to finish processing before releasing any of the +resulting output frames. This ensures that all frames produced in response to a +single input frame are emitted together. + +System frames (except EndFrame) are exempt from this synchronization — they pass +straight through without waiting, since they are expected to race ahead of +regular data frames. """ import asyncio @@ -46,20 +51,21 @@ class FrameOrder(Enum): @dataclass class SyncFrame(ControlFrame): - """Control frame used to synchronize parallel pipeline processing. + """Sentinel frame used to detect when a parallel pipeline has finished processing. - This frame is sent through parallel pipelines to determine when the - internal pipelines have finished processing a batch of frames. + After sending a real frame into a parallel pipeline, a SyncFrame is sent + behind it. When the SyncFrame emerges from the pipeline's output, we know + all output frames for the preceding input have been produced. """ pass class SyncParallelPipelineSource(FrameProcessor): - """Source processor for synchronous parallel pipeline processing. + """Bookend processor placed at the start of each parallel pipeline. - Routes frames to parallel pipelines and collects upstream responses - for synchronization purposes. + Forwards downstream frames into the pipeline and captures upstream frames + into a queue so the parent SyncParallelPipeline can release them later. """ def __init__(self, upstream_queue: asyncio.Queue): @@ -88,10 +94,11 @@ class SyncParallelPipelineSource(FrameProcessor): class SyncParallelPipelineSink(FrameProcessor): - """Sink processor for synchronous parallel pipeline processing. + """Bookend processor placed at the end of each parallel pipeline. - Collects downstream frames from parallel pipelines and routes - upstream frames back through the pipeline. + Captures downstream output frames into a queue so the parent + SyncParallelPipeline can release them later, and forwards upstream + frames back through the pipeline. """ def __init__(self, downstream_queue: asyncio.Queue): @@ -120,15 +127,20 @@ class SyncParallelPipelineSink(FrameProcessor): class SyncParallelPipeline(BasePipeline): - """Pipeline that processes frames through multiple parallel pipelines synchronously. + """Fans each input frame to parallel pipelines then holds output until every pipeline finishes. - Creates multiple parallel processing paths that all receive the same input frames - and produces synchronized output. Each parallel path is a separate pipeline that - processes frames independently, with synchronization points to ensure consistent - ordering and prevent duplicate frame processing. + For each inbound frame the pipeline: - The pipeline uses SyncFrame control frames to coordinate between parallel paths - and ensure all paths have completed processing before moving to the next frame. + 1. Sends the frame into every parallel pipeline. + 2. Sends a ``SyncFrame`` sentinel behind it in each pipeline. + 3. Waits until every pipeline has produced its ``SyncFrame``, meaning all + output for that input is ready. + 4. Releases the collected output frames (deduplicating by frame id, since + the same frame may emerge from more than one branch). + + System frames (except ``EndFrame``) bypass this mechanism entirely — they are + forwarded through each pipeline and pushed immediately, since system frames + are expected to race ahead of regular data frames. By default, output frames are pushed in the order they arrive from any pipeline (``FrameOrder.ARRIVAL``). Set ``frame_order=FrameOrder.PIPELINE`` to push frames @@ -239,16 +251,11 @@ class SyncParallelPipeline(BasePipeline): await asyncio.gather(*[p.cleanup() for p in self._pipelines]) async def process_frame(self, frame: Frame, direction: FrameDirection): - """Process frames through all parallel pipelines with synchronization. + """Send a frame through all parallel pipelines and release output once all finish. - Distributes frames to all parallel pipelines and synchronizes their output - to maintain proper ordering and prevent duplicate processing. Uses SyncFrame - control frames to coordinate between parallel paths. - - When ``frame_order`` is ``FrameOrder.ARRIVAL``, output frames are pushed in - the order they arrive from any pipeline (via a shared queue). When it is - ``FrameOrder.PIPELINE``, each pipeline collects its output into a separate - list and the lists are drained in pipeline definition order. + System frames (except EndFrame) skip synchronization and pass straight + through. All other frames are fanned out to every pipeline, and output is + held until every pipeline signals completion (via SyncFrame). Args: frame: The frame to process. From 57fd29f0c4204ca5df58468108325394cb211a95 Mon Sep 17 00:00:00 2001 From: Paul Kompfner Date: Thu, 19 Mar 2026 09:57:26 -0400 Subject: [PATCH 1036/1060] Remove changelog fragment that no longer applies after a rebase --- changelog/4029.fixed.2.md | 1 - 1 file changed, 1 deletion(-) delete mode 100644 changelog/4029.fixed.2.md diff --git a/changelog/4029.fixed.2.md b/changelog/4029.fixed.2.md deleted file mode 100644 index faf54592e..000000000 --- a/changelog/4029.fixed.2.md +++ /dev/null @@ -1 +0,0 @@ -- Fixed TTS frame ordering when an audio context is active. Pass-through frames are now routed through the audio context queue so they stay properly ordered with TTS audio frames. Previously, a frame that preceded some incoming text to a TTS service could "jump the queue", getting ahead of the outgoing audio. From fd8c6c88bb76e1b7ab541eea9937679f2a23cfe1 Mon Sep 17 00:00:00 2001 From: filipi87 Date: Thu, 19 Mar 2026 11:13:17 -0300 Subject: [PATCH 1037/1060] Improvements to SarvamTTSService. --- src/pipecat/services/sarvam/tts.py | 25 ++++--------------------- 1 file changed, 4 insertions(+), 21 deletions(-) diff --git a/src/pipecat/services/sarvam/tts.py b/src/pipecat/services/sarvam/tts.py index c926270de..0478f8faf 100644 --- a/src/pipecat/services/sarvam/tts.py +++ b/src/pipecat/services/sarvam/tts.py @@ -1031,23 +1031,6 @@ class SarvamTTSService(InterruptibleTTSService): except Exception as e: await self.push_error(error_msg=f"Error sending flush to Sarvam: {e}", exception=e) - async def push_frame(self, frame: Frame, direction: FrameDirection = FrameDirection.DOWNSTREAM): - """Push a frame downstream with special handling for stop conditions. - - Args: - frame: The frame to push. - direction: The direction to push the frame. - """ - await super().push_frame(frame, direction) - - async def process_frame(self, frame: Frame, direction: FrameDirection): - """Process a frame and flush audio if it's the end of a full response.""" - await super().process_frame(frame, direction) - - # When the LLM finishes responding, flush any remaining text in Sarvam's buffer - if isinstance(frame, (LLMFullResponseEndFrame, EndFrame)): - await self.flush_audio() - async def _update_settings(self, delta: TTSSettings) -> dict[str, Any]: """Apply a settings delta and resend config if voice changed.""" changed = await super()._update_settings(delta) @@ -1168,14 +1151,15 @@ class SarvamTTSService(InterruptibleTTSService): async for message in self._get_websocket(): if isinstance(message, str): msg = json.loads(message) + context_id = self.get_active_audio_context_id() if msg.get("type") == "audio": # Check for interruption before processing audio await self.stop_ttfb_metrics() audio = base64.b64decode(msg["data"]["audio"]) frame = TTSAudioRawFrame( - audio, self.sample_rate, 1, context_id=self.get_active_audio_context_id() + audio, self.sample_rate, 1, context_id=context_id ) - await self.push_frame(frame) + await self.append_to_audio_context(context_id, frame) elif msg.get("type") == "error": error_msg = msg["data"]["message"] await self.push_error(error_msg=f"TTS Error: {error_msg}") @@ -1183,8 +1167,7 @@ class SarvamTTSService(InterruptibleTTSService): # If it's a timeout error, the connection might need to be reset if "too long" in error_msg.lower() or "timeout" in error_msg.lower(): logger.warning("Connection timeout detected, service may need restart") - - await self.push_frame(ErrorFrame(error=f"TTS Error: {error_msg}")) + await self.append_to_audio_context(context_id, ErrorFrame(error=f"TTS Error: {error_msg}")) async def _keepalive_task_handler(self): """Handle keepalive messages to maintain WebSocket connection.""" From c4d1b89049c02ca1e61c91a469ea600b667bbe22 Mon Sep 17 00:00:00 2001 From: filipi87 Date: Thu, 19 Mar 2026 11:17:39 -0300 Subject: [PATCH 1038/1060] Adding changelog entry for the Sarvam fixes. --- changelog/4082.fixed.md | 1 + src/pipecat/services/sarvam/tts.py | 8 ++++---- 2 files changed, 5 insertions(+), 4 deletions(-) create mode 100644 changelog/4082.fixed.md diff --git a/changelog/4082.fixed.md b/changelog/4082.fixed.md new file mode 100644 index 000000000..e17e84fea --- /dev/null +++ b/changelog/4082.fixed.md @@ -0,0 +1 @@ +- Fixed `SarvamTTSService` audio and error frames now route through `append_to_audio_context()` instead of `push_frame()`, ensuring correct behavior with audio contexts and interruptions. diff --git a/src/pipecat/services/sarvam/tts.py b/src/pipecat/services/sarvam/tts.py index 0478f8faf..8bfeea8c6 100644 --- a/src/pipecat/services/sarvam/tts.py +++ b/src/pipecat/services/sarvam/tts.py @@ -1156,9 +1156,7 @@ class SarvamTTSService(InterruptibleTTSService): # Check for interruption before processing audio await self.stop_ttfb_metrics() audio = base64.b64decode(msg["data"]["audio"]) - frame = TTSAudioRawFrame( - audio, self.sample_rate, 1, context_id=context_id - ) + frame = TTSAudioRawFrame(audio, self.sample_rate, 1, context_id=context_id) await self.append_to_audio_context(context_id, frame) elif msg.get("type") == "error": error_msg = msg["data"]["message"] @@ -1167,7 +1165,9 @@ class SarvamTTSService(InterruptibleTTSService): # If it's a timeout error, the connection might need to be reset if "too long" in error_msg.lower() or "timeout" in error_msg.lower(): logger.warning("Connection timeout detected, service may need restart") - await self.append_to_audio_context(context_id, ErrorFrame(error=f"TTS Error: {error_msg}")) + await self.append_to_audio_context( + context_id, ErrorFrame(error=f"TTS Error: {error_msg}") + ) async def _keepalive_task_handler(self): """Handle keepalive messages to maintain WebSocket connection.""" From 39425a675a60bbffc8de1fc50cc485baafd7d344 Mon Sep 17 00:00:00 2001 From: filipi87 Date: Thu, 19 Mar 2026 11:32:56 -0300 Subject: [PATCH 1039/1060] Improvements to DeepgramSageMakerTTSService. --- .../services/deepgram/sagemaker/tts.py | 47 +++---------------- 1 file changed, 7 insertions(+), 40 deletions(-) diff --git a/src/pipecat/services/deepgram/sagemaker/tts.py b/src/pipecat/services/deepgram/sagemaker/tts.py index 70be4a00e..6add3f951 100644 --- a/src/pipecat/services/deepgram/sagemaker/tts.py +++ b/src/pipecat/services/deepgram/sagemaker/tts.py @@ -20,18 +20,13 @@ from typing import Any, AsyncGenerator, Optional from loguru import logger from pipecat.frames.frames import ( - BotStoppedSpeakingFrame, CancelFrame, EndFrame, ErrorFrame, Frame, - InterruptionFrame, - LLMFullResponseEndFrame, StartFrame, TTSAudioRawFrame, - TTSStartedFrame, ) -from pipecat.processors.frame_processor import FrameDirection from pipecat.services.aws.sagemaker.bidi_client import SageMakerBidiClient from pipecat.services.settings import TTSSettings from pipecat.services.tts_service import TTSService @@ -115,6 +110,7 @@ class DeepgramSageMakerTTSService(TTSService): super().__init__( sample_rate=sample_rate, + push_start_frame=True, push_stop_frames=True, pause_frame_processing=True, append_trailing_space=True, @@ -128,8 +124,6 @@ class DeepgramSageMakerTTSService(TTSService): self._client: Optional[SageMakerBidiClient] = None self._response_task: Optional[asyncio.Task] = None - self._context_id: Optional[str] = None - self._ttfb_started: bool = False def can_generate_metrics(self) -> bool: """Check if this service can generate processing metrics. @@ -166,20 +160,6 @@ class DeepgramSageMakerTTSService(TTSService): await super().cancel(frame) await self._disconnect() - async def process_frame(self, frame: Frame, direction: FrameDirection): - """Process frames with special handling for LLM response end. - - Args: - frame: The frame to process. - direction: The direction of frame processing. - """ - await super().process_frame(frame, direction) - - if isinstance(frame, (LLMFullResponseEndFrame, EndFrame)): - await self.flush_audio() - elif isinstance(frame, BotStoppedSpeakingFrame): - self._ttfb_started = False - async def _connect(self): """Connect to the SageMaker endpoint and start the BiDi session. @@ -305,7 +285,7 @@ class DeepgramSageMakerTTSService(TTSService): payload, self.sample_rate, 1, - context_id=self._context_id, + context_id=self.get_active_audio_context_id(), ) await self.push_frame(frame) @@ -316,15 +296,13 @@ class DeepgramSageMakerTTSService(TTSService): finally: logger.debug("TTS response processor stopped") - async def _handle_interruption(self, frame: InterruptionFrame, direction: FrameDirection): - """Handle interruption by sending Clear message to Deepgram. + async def on_audio_context_interrupted(self, context_id: str): + """Called when an audio context is cancelled due to an interruption. - The Clear message will clear Deepgram's internal text buffer and stop - sending audio, allowing for a new response to be generated. + Args: + context_id: The ID of the audio context that was interrupted, or + ``None`` if no context was active at the time. """ - await super()._handle_interruption(frame, direction) - self._ttfb_started = False - if self._client and self._client.is_active: try: await self._client.send_json({"type": "Clear"}) @@ -356,19 +334,8 @@ class DeepgramSageMakerTTSService(TTSService): the response processor). """ logger.debug(f"{self}: Generating TTS [{text}]") - try: - if not self.audio_context_available(context_id): - await self.create_audio_context(context_id) - if not self._ttfb_started: - await self.start_ttfb_metrics() - self._ttfb_started = True - yield TTSStartedFrame(context_id=context_id) - self._context_id = context_id - await self._client.send_json({"type": "Speak", "text": text}) - yield None - except Exception as e: yield ErrorFrame(error=f"Unknown error occurred: {e}") From d3ca034c4f14b2a138c68586e54275e89114263c Mon Sep 17 00:00:00 2001 From: filipi87 Date: Thu, 19 Mar 2026 11:40:43 -0300 Subject: [PATCH 1040/1060] Routing the audio through the audio context queue. --- src/pipecat/services/deepgram/sagemaker/tts.py | 5 +++-- 1 file changed, 3 insertions(+), 2 deletions(-) diff --git a/src/pipecat/services/deepgram/sagemaker/tts.py b/src/pipecat/services/deepgram/sagemaker/tts.py index 6add3f951..36541b4be 100644 --- a/src/pipecat/services/deepgram/sagemaker/tts.py +++ b/src/pipecat/services/deepgram/sagemaker/tts.py @@ -281,13 +281,14 @@ class DeepgramSageMakerTTSService(TTSService): except (UnicodeDecodeError, json.JSONDecodeError): # Not JSON — treat as raw audio bytes await self.stop_ttfb_metrics() + context_id = self.get_active_audio_context_id() frame = TTSAudioRawFrame( payload, self.sample_rate, 1, - context_id=self.get_active_audio_context_id(), + context_id=context_id, ) - await self.push_frame(frame) + await self.append_to_audio_context(context_id, frame) except asyncio.CancelledError: logger.debug("TTS response processor cancelled") From a0f311158dd70ab3ddd683a5f6ac530432bfff99 Mon Sep 17 00:00:00 2001 From: filipi87 Date: Thu, 19 Mar 2026 11:46:49 -0300 Subject: [PATCH 1041/1060] Changelog entry for the DeepgramSageMakerTTSService improvements. --- changelog/4083.changed.md | 1 + 1 file changed, 1 insertion(+) create mode 100644 changelog/4083.changed.md diff --git a/changelog/4083.changed.md b/changelog/4083.changed.md new file mode 100644 index 000000000..d9d46957a --- /dev/null +++ b/changelog/4083.changed.md @@ -0,0 +1 @@ +- `DeepgramSageMakerTTSService` now correctly routes audio through the base `TTSService` audio context queue. Audio frames are delivered via `append_to_audio_context()` instead of being pushed directly, enabling proper ordering, interruption handling, and start/stop frame lifecycle management. Interruptions now trigger a `Clear` message to Deepgram (flushing its text buffer) at the right time via `on_audio_context_interrupted`. From 348df9d4ced25de0f6c36fb0fb38e1b31743d28b Mon Sep 17 00:00:00 2001 From: Paul Kompfner Date: Thu, 19 Mar 2026 13:34:41 -0400 Subject: [PATCH 1042/1060] fix: remove redundant instructions override in run_inference The override would re-add `instructions` after the adapter had intentionally converted it to a developer message for empty contexts. Added a regression test. --- src/pipecat/services/openai/responses/llm.py | 4 --- tests/test_run_inference.py | 33 ++++++++++++++++++++ 2 files changed, 33 insertions(+), 4 deletions(-) diff --git a/src/pipecat/services/openai/responses/llm.py b/src/pipecat/services/openai/responses/llm.py index f62c6e758..4f0c81dc7 100644 --- a/src/pipecat/services/openai/responses/llm.py +++ b/src/pipecat/services/openai/responses/llm.py @@ -385,10 +385,6 @@ class OpenAIResponsesLLMService(LLMService): # Override for non-streaming params["stream"] = False - # Override instructions if caller provided one explicitly - if system_instruction is not None: - params["instructions"] = system_instruction - if max_tokens is not None: params["max_output_tokens"] = max_tokens diff --git a/tests/test_run_inference.py b/tests/test_run_inference.py index f67c725ae..cef13fb27 100644 --- a/tests/test_run_inference.py +++ b/tests/test_run_inference.py @@ -902,3 +902,36 @@ async def test_openai_responses_run_inference_max_tokens_override(): assert result == "Summary" call_kwargs = service._client.responses.create.call_args.kwargs assert call_kwargs["max_output_tokens"] == 200 + + +@pytest.mark.asyncio +async def test_openai_responses_run_inference_system_instruction_param_with_empty_context(): + """Test that system_instruction param becomes a developer message when context is empty. + + The Responses API rejects requests with instructions but no input items. + When run_inference is called with an explicit system_instruction and an + empty context, the instruction must become a developer message — not be + sent as the instructions parameter. + """ + with patch.object(OpenAIResponsesLLMService, "_create_client"): + service = OpenAIResponsesLLMService( + settings=OpenAIResponsesLLMService.Settings(model="gpt-4.1"), + ) + service._client = AsyncMock() + + context = LLMContext(messages=[]) + + mock_response = MagicMock() + mock_response.output_text = "Response" + service._client.responses.create = AsyncMock(return_value=mock_response) + + result = await service.run_inference( + context, system_instruction="Summarize the conversation" + ) + + assert result == "Response" + call_kwargs = service._client.responses.create.call_args.kwargs + assert call_kwargs["input"] == [ + {"role": "developer", "content": "Summarize the conversation"} + ] + assert "instructions" not in call_kwargs From a3431d3b0176c4740dc5f27fe5f59977ae1d54bc Mon Sep 17 00:00:00 2001 From: Paul Kompfner Date: Thu, 19 Mar 2026 13:55:26 -0400 Subject: [PATCH 1043/1060] fix: prefer _full_model_name over _settings.model in tracing The API-provided full model name is more specific than the user-provided model name (e.g. includes version/snapshot details). Reorder the lookup in _get_model_name and add a comment where the Responses service sets the field. --- src/pipecat/services/openai/responses/llm.py | 2 ++ src/pipecat/utils/tracing/service_decorators.py | 6 ++++-- 2 files changed, 6 insertions(+), 2 deletions(-) diff --git a/src/pipecat/services/openai/responses/llm.py b/src/pipecat/services/openai/responses/llm.py index 4f0c81dc7..8c7269323 100644 --- a/src/pipecat/services/openai/responses/llm.py +++ b/src/pipecat/services/openai/responses/llm.py @@ -292,6 +292,8 @@ class OpenAIResponsesLLMService(LLMService): model = getattr(response, "model", None) if model: + # This field is used by @traced_llm for more detailed + # model name in tracing spans self._full_model_name = model # Process any function calls diff --git a/src/pipecat/utils/tracing/service_decorators.py b/src/pipecat/utils/tracing/service_decorators.py index f4764d248..5292a5d3f 100644 --- a/src/pipecat/utils/tracing/service_decorators.py +++ b/src/pipecat/utils/tracing/service_decorators.py @@ -51,8 +51,10 @@ def _get_model_name(service) -> str: check all the places we used to store it. """ return ( - getattr(getattr(service, "_settings", None), "model", None) - or getattr(service, "_full_model_name", None) + # Some services store an API-response-provided detailed "full" name, + # which is distinct from the user-provided model name + getattr(service, "_full_model_name", None) + or getattr(getattr(service, "_settings", None), "model", None) or getattr(service, "model_name", None) or getattr(service, "_model_name", None) or "unknown" From 0533ea7b7fdd45a906cc05349109606b3314f236 Mon Sep 17 00:00:00 2001 From: Paul Kompfner Date: Thu, 19 Mar 2026 14:19:10 -0400 Subject: [PATCH 1044/1060] refactor: use direct attribute access for typed stream events Replace getattr() calls with direct attribute access and isinstance() checks on the strongly-typed OpenAI SDK event models. --- src/pipecat/services/openai/responses/llm.py | 36 +++++++++----------- 1 file changed, 17 insertions(+), 19 deletions(-) diff --git a/src/pipecat/services/openai/responses/llm.py b/src/pipecat/services/openai/responses/llm.py index 8c7269323..a412d9627 100644 --- a/src/pipecat/services/openai/responses/llm.py +++ b/src/pipecat/services/openai/responses/llm.py @@ -18,6 +18,7 @@ from openai.types.responses import ( ResponseCompletedEvent, ResponseFunctionCallArgumentsDeltaEvent, ResponseFunctionCallArgumentsDoneEvent, + ResponseFunctionToolCall, ResponseOutputItemAddedEvent, ResponseOutputItemDoneEvent, ResponseStreamEvent, @@ -251,11 +252,11 @@ class OpenAIResponsesLLMService(LLMService): elif isinstance(event, ResponseOutputItemAddedEvent): await self.stop_ttfb_metrics() item = event.item - if getattr(item, "type", None) == "function_call": - item_id = getattr(item, "id", "") or "" + if isinstance(item, ResponseFunctionToolCall): + item_id = item.id or "" function_calls[item_id] = { - "name": getattr(item, "name", ""), - "call_id": getattr(item, "call_id", ""), + "name": item.name, + "call_id": item.call_id, "arguments": "", } current_arguments[item_id] = "" @@ -272,29 +273,26 @@ class OpenAIResponsesLLMService(LLMService): elif isinstance(event, ResponseOutputItemDoneEvent): item = event.item - if getattr(item, "type", None) == "function_call": - item_id = getattr(item, "id", "") or "" + if isinstance(item, ResponseFunctionToolCall): + item_id = item.id or "" if item_id in function_calls: - function_calls[item_id]["name"] = getattr(item, "name", "") - function_calls[item_id]["call_id"] = getattr(item, "call_id", "") - function_calls[item_id]["arguments"] = getattr(item, "arguments", "") + function_calls[item_id]["name"] = item.name + function_calls[item_id]["call_id"] = item.call_id + function_calls[item_id]["arguments"] = item.arguments elif isinstance(event, ResponseCompletedEvent): response = event.response - usage = getattr(response, "usage", None) - if usage: + if response.usage: tokens = LLMTokenUsage( - prompt_tokens=getattr(usage, "input_tokens", 0), - completion_tokens=getattr(usage, "output_tokens", 0), - total_tokens=getattr(usage, "total_tokens", 0), + prompt_tokens=response.usage.input_tokens, + completion_tokens=response.usage.output_tokens, + total_tokens=response.usage.total_tokens, ) await self.start_llm_usage_metrics(tokens) - model = getattr(response, "model", None) - if model: - # This field is used by @traced_llm for more detailed - # model name in tracing spans - self._full_model_name = model + # This field is used by @traced_llm for more detailed + # model name in tracing spans + self._full_model_name = response.model # Process any function calls if function_calls: From 4ec7be88507eaae006d41c283d80ce1f805de920 Mon Sep 17 00:00:00 2001 From: Paul Kompfner Date: Thu, 19 Mar 2026 14:23:39 -0400 Subject: [PATCH 1045/1060] feat: include cached_tokens and reasoning_tokens in usage metrics --- src/pipecat/services/openai/responses/llm.py | 2 ++ 1 file changed, 2 insertions(+) diff --git a/src/pipecat/services/openai/responses/llm.py b/src/pipecat/services/openai/responses/llm.py index a412d9627..bcc6274b4 100644 --- a/src/pipecat/services/openai/responses/llm.py +++ b/src/pipecat/services/openai/responses/llm.py @@ -287,6 +287,8 @@ class OpenAIResponsesLLMService(LLMService): prompt_tokens=response.usage.input_tokens, completion_tokens=response.usage.output_tokens, total_tokens=response.usage.total_tokens, + cache_read_input_tokens=response.usage.input_tokens_details.cached_tokens, + reasoning_tokens=response.usage.output_tokens_details.reasoning_tokens, ) await self.start_llm_usage_metrics(tokens) From 05e344b9ec67fe94ab22f5fe8047bd9a41b40ed6 Mon Sep 17 00:00:00 2001 From: Paul Kompfner Date: Thu, 19 Mar 2026 14:30:34 -0400 Subject: [PATCH 1046/1060] docs: port _closing comments from BaseOpenAILLMService --- src/pipecat/services/openai/responses/llm.py | 8 ++++++++ 1 file changed, 8 insertions(+) diff --git a/src/pipecat/services/openai/responses/llm.py b/src/pipecat/services/openai/responses/llm.py index bcc6274b4..b12a33510 100644 --- a/src/pipecat/services/openai/responses/llm.py +++ b/src/pipecat/services/openai/responses/llm.py @@ -230,14 +230,22 @@ class OpenAIResponsesLLMService(LLMService): function_calls: Dict[str, Dict[str, str]] = {} # item_id -> {name, call_id, arguments} current_arguments: Dict[str, str] = {} # item_id -> accumulated arguments + # Ensure stream and its async iterator are closed on cancellation/exception + # to prevent socket leaks and uvloop crashes. Closing the iterator first + # cascades cleanup through nested async generators (httpx/httpcore internals), + # preventing uvloop's broken asyncgen finalizer from firing on Python 3.12+ + # (MagicStack/uvloop#699). @asynccontextmanager async def _closing(stream): chunk_iter = stream.__aiter__() try: yield chunk_iter finally: + # Close the iterator first to cascade cleanup through + # nested async generators (httpx/httpcore internals). if hasattr(chunk_iter, "aclose"): await chunk_iter.aclose() + # Then close the stream to release HTTP resources. if hasattr(stream, "close"): await stream.close() elif hasattr(stream, "aclose"): From 6424c36666bd7755c7fe5c26d342e5431bb5d3c4 Mon Sep 17 00:00:00 2001 From: Paul Kompfner Date: Thu, 19 Mar 2026 14:37:46 -0400 Subject: [PATCH 1047/1060] refactor: remove model init param from OpenAIResponsesLLMService Model is only configurable via settings, matching the canonical API. --- src/pipecat/services/openai/responses/llm.py | 8 +------- 1 file changed, 1 insertion(+), 7 deletions(-) diff --git a/src/pipecat/services/openai/responses/llm.py b/src/pipecat/services/openai/responses/llm.py index b12a33510..e9e5d3a1f 100644 --- a/src/pipecat/services/openai/responses/llm.py +++ b/src/pipecat/services/openai/responses/llm.py @@ -79,7 +79,6 @@ class OpenAIResponsesLLMService(LLMService): def __init__( self, *, - model: Optional[str] = None, api_key=None, base_url=None, organization=None, @@ -92,15 +91,13 @@ class OpenAIResponsesLLMService(LLMService): """Initialize the OpenAI Responses API LLM service. Args: - model: The OpenAI model name to use. Defaults to "gpt-4.1". api_key: OpenAI API key. If None, uses environment variable. base_url: Custom base URL for OpenAI API. If None, uses default. organization: OpenAI organization ID. project: OpenAI project ID. default_headers: Additional HTTP headers to include in requests. service_tier: Service tier to use (e.g., "auto", "flex", "priority"). - settings: Runtime-updatable settings. When provided alongside - other parameters, ``settings`` values take precedence. + settings: Runtime-updatable settings. **kwargs: Additional arguments passed to the parent LLMService. """ default_settings = self.Settings( @@ -119,9 +116,6 @@ class OpenAIResponsesLLMService(LLMService): extra={}, ) - if model is not None: - default_settings.model = model - if settings is not None: default_settings.apply_update(settings) From ea1534f9f8e757ee0fa86c46aea79eafdcb86a95 Mon Sep 17 00:00:00 2001 From: Paul Kompfner Date: Thu, 19 Mar 2026 15:36:23 -0400 Subject: [PATCH 1048/1060] docs: note input_audio coming soon, no conversion needed The LLMContext format already matches the expected Responses API shape for input_audio, so no adapter conversion will be needed once OpenAI enables support. --- src/pipecat/adapters/services/open_ai_responses_adapter.py | 5 ++++- 1 file changed, 4 insertions(+), 1 deletion(-) diff --git a/src/pipecat/adapters/services/open_ai_responses_adapter.py b/src/pipecat/adapters/services/open_ai_responses_adapter.py index 0d586fb12..70627fe5d 100644 --- a/src/pipecat/adapters/services/open_ai_responses_adapter.py +++ b/src/pipecat/adapters/services/open_ai_responses_adapter.py @@ -246,6 +246,9 @@ class OpenAIResponsesLLMAdapter(BaseLLMAdapter[OpenAIResponsesLLMInvocationParam } ) else: - # Pass through unknown types as-is + # Pass through other types as-is. Note: "input_audio" is not + # yet supported by the Responses API (coming soon per OpenAI + # docs) but the LLMContext format already matches the expected + # shape, so it should work once support is enabled. result.append(part) return result From dafbb2eb6628692b3cba8e7659c99abdf124e97d Mon Sep 17 00:00:00 2001 From: Paul Kompfner Date: Thu, 19 Mar 2026 15:38:38 -0400 Subject: [PATCH 1049/1060] =?UTF-8?q?fix:=20typo=20"conversatione"=20?= =?UTF-8?q?=E2=86=92=20"conversation"=20in=2020-=20examples?= MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit --- .../foundational/20a-persistent-context-openai-responses.py | 2 +- examples/foundational/20a-persistent-context-openai.py | 2 +- .../foundational/20b-persistent-context-openai-realtime-beta.py | 2 +- examples/foundational/20b-persistent-context-openai-realtime.py | 2 +- 4 files changed, 4 insertions(+), 4 deletions(-) diff --git a/examples/foundational/20a-persistent-context-openai-responses.py b/examples/foundational/20a-persistent-context-openai-responses.py index 730e90197..5fd9c7657 100644 --- a/examples/foundational/20a-persistent-context-openai-responses.py +++ b/examples/foundational/20a-persistent-context-openai-responses.py @@ -116,7 +116,7 @@ weather_function = FunctionSchema( save_conversation_function = FunctionSchema( name="save_conversation", - description="Save the current conversatione. Use this function to persist the current conversation to external storage.", + description="Save the current conversation. Use this function to persist the current conversation to external storage.", properties={}, required=[], ) diff --git a/examples/foundational/20a-persistent-context-openai.py b/examples/foundational/20a-persistent-context-openai.py index f6a4dc937..7f744fd46 100644 --- a/examples/foundational/20a-persistent-context-openai.py +++ b/examples/foundational/20a-persistent-context-openai.py @@ -116,7 +116,7 @@ weather_function = FunctionSchema( save_conversation_function = FunctionSchema( name="save_conversation", - description="Save the current conversatione. Use this function to persist the current conversation to external storage.", + description="Save the current conversation. Use this function to persist the current conversation to external storage.", properties={}, required=[], ) diff --git a/examples/foundational/20b-persistent-context-openai-realtime-beta.py b/examples/foundational/20b-persistent-context-openai-realtime-beta.py index fa59e1674..4b05db618 100644 --- a/examples/foundational/20b-persistent-context-openai-realtime-beta.py +++ b/examples/foundational/20b-persistent-context-openai-realtime-beta.py @@ -119,7 +119,7 @@ tools = [ { "type": "function", "name": "save_conversation", - "description": "Save the current conversatione. Use this function to persist the current conversation to external storage.", + "description": "Save the current conversation. Use this function to persist the current conversation to external storage.", "parameters": { "type": "object", "properties": {}, diff --git a/examples/foundational/20b-persistent-context-openai-realtime.py b/examples/foundational/20b-persistent-context-openai-realtime.py index de4215ab8..bceca410d 100644 --- a/examples/foundational/20b-persistent-context-openai-realtime.py +++ b/examples/foundational/20b-persistent-context-openai-realtime.py @@ -125,7 +125,7 @@ tools = ToolsSchema( ), FunctionSchema( name="save_conversation", - description="Save the current conversatione. Use this function to persist the current conversation to external storage.", + description="Save the current conversation. Use this function to persist the current conversation to external storage.", properties={}, required=[], ), From 4c456ada0411509c1c22d2182d2bb4009973780a Mon Sep 17 00:00:00 2001 From: Paul Kompfner Date: Thu, 19 Mar 2026 15:52:48 -0400 Subject: [PATCH 1050/1060] Remove 05a example, which was broken and isn't currently a priority to fix --- .../05a-local-sync-speech-and-image.py | 202 ------------------ 1 file changed, 202 deletions(-) delete mode 100644 examples/foundational/05a-local-sync-speech-and-image.py diff --git a/examples/foundational/05a-local-sync-speech-and-image.py b/examples/foundational/05a-local-sync-speech-and-image.py deleted file mode 100644 index d0c5a103a..000000000 --- a/examples/foundational/05a-local-sync-speech-and-image.py +++ /dev/null @@ -1,202 +0,0 @@ -# -# Copyright (c) 2024-2026, Daily -# -# SPDX-License-Identifier: BSD 2-Clause License -# - -import asyncio -import os -import sys -import tkinter as tk - -import aiohttp -from dotenv import load_dotenv -from loguru import logger - -from pipecat.frames.frames import ( - Frame, - LLMContextFrame, - OutputAudioRawFrame, - TextFrame, - TTSAudioRawFrame, - URLImageRawFrame, -) -from pipecat.pipeline.pipeline import Pipeline -from pipecat.pipeline.runner import PipelineRunner -from pipecat.pipeline.sync_parallel_pipeline import SyncParallelPipeline -from pipecat.pipeline.task import PipelineTask -from pipecat.processors.aggregators.llm_context import LLMContext -from pipecat.processors.aggregators.sentence import SentenceAggregator -from pipecat.processors.frame_processor import FrameDirection, FrameProcessor -from pipecat.services.cartesia.tts import CartesiaHttpTTSService -from pipecat.services.fal.image import FalImageGenService -from pipecat.services.openai.llm import OpenAILLMService -from pipecat.transports.local.tk import TkLocalTransport, TkTransportParams - -load_dotenv(override=True) - -logger.remove(0) -logger.add(sys.stderr, level="DEBUG") - - -async def main(): - async with aiohttp.ClientSession() as session: - tk_root = tk.Tk() - tk_root.title("Calendar") - - runner = PipelineRunner() - - async def get_month_data(month): - messages = [ - { - "role": "user", - "content": f"Describe a nature photograph suitable for use in a calendar, for the month of {month}. Include only the image description with no preamble. Limit the description to one sentence, please.", - } - ] - - class ImageDescription(FrameProcessor): - def __init__(self): - super().__init__() - self.text = "" - - async def process_frame(self, frame: Frame, direction: FrameDirection): - await super().process_frame(frame, direction) - - if isinstance(frame, TextFrame): - self.text = frame.text - await self.push_frame(frame, direction) - - class AudioGrabber(FrameProcessor): - def __init__(self): - super().__init__() - self.audio = bytearray() - self.frame = None - - async def process_frame(self, frame: Frame, direction: FrameDirection): - await super().process_frame(frame, direction) - - if isinstance(frame, TTSAudioRawFrame): - self.audio.extend(frame.audio) - self.frame = OutputAudioRawFrame( - bytes(self.audio), frame.sample_rate, frame.num_channels - ) - await self.push_frame(frame, direction) - - class ImageGrabber(FrameProcessor): - def __init__(self): - super().__init__() - self.frame = None - - async def process_frame(self, frame: Frame, direction: FrameDirection): - await super().process_frame(frame, direction) - - if isinstance(frame, URLImageRawFrame): - self.frame = frame - await self.push_frame(frame, direction) - - llm = OpenAILLMService(api_key=os.getenv("OPENAI_API_KEY")) - - tts = CartesiaHttpTTSService( - api_key=os.getenv("CARTESIA_API_KEY"), - settings=CartesiaHttpTTSService.Settings( - voice="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady - ), - ) - - imagegen = FalImageGenService( - settings=FalImageGenService.Settings( - image_size="square_hd", - ), - aiohttp_session=session, - key=os.getenv("FAL_KEY"), - ) - - sentence_aggregator = SentenceAggregator() - - description = ImageDescription() - - audio_grabber = AudioGrabber() - - image_grabber = ImageGrabber() - - # With `SyncParallelPipeline` we synchronize audio and images by - # pushing them basically in order (e.g. I1 A1 A1 A1 I2 A2 A2 A2 A2 - # I3 A3). To do that, each pipeline runs concurrently and - # `SyncParallelPipeline` will wait for the input frame to be - # processed. - # - # Note that `SyncParallelPipeline` requires the last processor in - # each of the pipelines to be synchronous. In this case, we use - # `CartesiaHttpTTSService` and `FalImageGenService` which make HTTP - # requests and wait for the response. - pipeline = Pipeline( - [ - llm, # LLM - sentence_aggregator, # Aggregates LLM output into full sentences - description, # Store sentence - SyncParallelPipeline( - [tts, audio_grabber], # Generate and store audio for the given sentence - [imagegen, image_grabber], # Generate and storeimage for the given sentence - ), - ] - ) - - task = PipelineTask(pipeline) - await task.queue_frame(LLMContextFrame(LLMContext(messages))) - await task.stop_when_done() - - await runner.run(task) - - return { - "month": month, - "text": description.text, - "image": image_grabber.frame, - "audio": audio_grabber.frame, - } - - transport = TkLocalTransport( - tk_root, - TkTransportParams( - audio_out_enabled=True, - video_out_enabled=True, - video_out_width=1024, - video_out_height=1024, - ), - ) - - pipeline = Pipeline([transport.output()]) - - task = PipelineTask(pipeline) - - # We only specify a few months as we create tasks all at once and we - # might get rate limited otherwise. - months: list[str] = [ - "January", - "February", - ] - - # We create one task per month. This will be executed concurrently. - month_tasks = [asyncio.create_task(get_month_data(month)) for month in months] - - # Now we wait for each month task in the order they're completed. The - # benefit is we'll have as little delay as possible before the first - # month, and likely no delay between months, but the months won't - # display in order. - async def show_images(month_tasks): - for month_data_task in asyncio.as_completed(month_tasks): - data = await month_data_task - await task.queue_frames([data["image"], data["audio"]]) - - await runner.stop_when_done() - - async def run_tk(): - while not task.has_finished(): - tk_root.update() - tk_root.update_idletasks() - await asyncio.sleep(0.1) - - await asyncio.gather(runner.run(task), show_images(month_tasks), run_tk()) - - -if __name__ == "__main__": - asyncio.run(main()) From a11c48d5b04f6c592b9f69c5d19b76280adda32e Mon Sep 17 00:00:00 2001 From: Mark Backman Date: Fri, 20 Mar 2026 10:09:58 -0400 Subject: [PATCH 1051/1060] Add community integrations to README --- README.md | 5 +++++ 1 file changed, 5 insertions(+) diff --git a/README.md b/README.md index 8af4f942c..1afc7f7a0 100644 --- a/README.md +++ b/README.md @@ -65,6 +65,10 @@ claude plugin marketplace add pipecat-ai/skills and install any of the available plugins. +### 🧩 Community Integrations + +Build and share your own Pipecat service integrations! Browse existing [community integrations](https://docs.pipecat.ai/server/services/community-integrations) or check out our [guide](COMMUNITY_INTEGRATIONS.md) to create your own. + ### 📺️ Pipecat TV Channel Catch new features, interviews, and how-tos on our [Pipecat TV](https://www.youtube.com/playlist?list=PLzU2zoMTQIHjqC3v4q2XVSR3hGSzwKFwH) channel. @@ -94,6 +98,7 @@ Catch new features, interviews, and how-tos on our [Pipecat TV](https://www.yout | Vision & Image | [fal](https://docs.pipecat.ai/server/services/image-generation/fal), [Google Imagen](https://docs.pipecat.ai/server/services/image-generation/google-imagen), [Moondream](https://docs.pipecat.ai/server/services/vision/moondream) | | Audio Processing | [Silero VAD](https://docs.pipecat.ai/server/utilities/audio/silero-vad-analyzer), [Krisp](https://docs.pipecat.ai/server/utilities/audio/krisp-filter), [Koala](https://docs.pipecat.ai/server/utilities/audio/koala-filter), [ai-coustics](https://docs.pipecat.ai/server/utilities/audio/aic-filter) | | Analytics & Metrics | [OpenTelemetry](https://docs.pipecat.ai/server/utilities/opentelemetry), [Sentry](https://docs.pipecat.ai/server/services/analytics/sentry) | +| Community | [Browse community integrations →](https://docs.pipecat.ai/server/services/community-integrations) | 📚 [View full services documentation →](https://docs.pipecat.ai/server/services/supported-services) From b98ad7fb64efb8b91f992d1bfe112c5a63a8461e Mon Sep 17 00:00:00 2001 From: Mark Backman Date: Fri, 20 Mar 2026 10:41:43 -0400 Subject: [PATCH 1052/1060] fix: route TTS audio through audio context queue in Fish, LMNT, Neuphonic, Rime NonJson These services were pushing audio frames directly via push_frame() in their WebSocket receive loops, bypassing the base TTSService audio context serialization queue. This causes incorrect frame ordering and broken interruption handling. Changes per service: - Fish Audio: use append_to_audio_context(), replace _handle_interruption with on_audio_context_interrupted() - LMNT: use append_to_audio_context(), remove redundant push_frame override - Neuphonic: use append_to_audio_context(), remove redundant push_frame and process_frame overrides (base class handles pause/resume) - Rime NonJson: use append_to_audio_context(), remove redundant push_frame override --- src/pipecat/services/fish/tts.py | 16 +++++++---- src/pipecat/services/lmnt/tts.py | 20 +++++-------- src/pipecat/services/neuphonic/tts.py | 41 +++++---------------------- src/pipecat/services/rime/tts.py | 14 ++------- 4 files changed, 27 insertions(+), 64 deletions(-) diff --git a/src/pipecat/services/fish/tts.py b/src/pipecat/services/fish/tts.py index 92cb54701..ab57522d4 100644 --- a/src/pipecat/services/fish/tts.py +++ b/src/pipecat/services/fish/tts.py @@ -21,12 +21,10 @@ from pipecat.frames.frames import ( EndFrame, ErrorFrame, Frame, - InterruptionFrame, StartFrame, TTSAudioRawFrame, TTSStoppedFrame, ) -from pipecat.processors.frame_processor import FrameDirection from pipecat.services.settings import NOT_GIVEN, TTSSettings, _NotGiven from pipecat.services.tts_service import InterruptibleTTSService from pipecat.transcriptions.language import Language @@ -362,8 +360,8 @@ class FishAudioTTSService(InterruptibleTTSService): return self._websocket raise Exception("Websocket not connected") - async def _handle_interruption(self, frame: InterruptionFrame, direction: FrameDirection): - await super()._handle_interruption(frame, direction) + async def on_audio_context_interrupted(self, context_id: str): + """Stop all metrics when audio context is interrupted.""" await self.stop_all_metrics() async def _receive_messages(self): @@ -377,8 +375,14 @@ class FishAudioTTSService(InterruptibleTTSService): audio_data = msg.get("audio") # Only process larger chunks to remove msgpack overhead if audio_data and len(audio_data) > 1024: - frame = TTSAudioRawFrame(audio_data, self.sample_rate, 1) - await self.push_frame(frame) + context_id = self.get_active_audio_context_id() + frame = TTSAudioRawFrame( + audio_data, + self.sample_rate, + 1, + context_id=context_id, + ) + await self.append_to_audio_context(context_id, frame) await self.stop_ttfb_metrics() elif event == "finish": reason = msg.get("reason", "unknown") diff --git a/src/pipecat/services/lmnt/tts.py b/src/pipecat/services/lmnt/tts.py index 29d0b60ca..0df70fd19 100644 --- a/src/pipecat/services/lmnt/tts.py +++ b/src/pipecat/services/lmnt/tts.py @@ -21,7 +21,6 @@ from pipecat.frames.frames import ( TTSAudioRawFrame, TTSStoppedFrame, ) -from pipecat.processors.frame_processor import FrameDirection from pipecat.services.settings import TTSSettings from pipecat.services.tts_service import InterruptibleTTSService from pipecat.transcriptions.language import Language, resolve_language @@ -212,15 +211,6 @@ class LmntTTSService(InterruptibleTTSService): await super().cancel(frame) await self._disconnect() - async def push_frame(self, frame: Frame, direction: FrameDirection = FrameDirection.DOWNSTREAM): - """Push a frame downstream with special handling for stop conditions. - - Args: - frame: The frame to push. - direction: The direction to push the frame. - """ - await super().push_frame(frame, direction) - async def _connect(self): """Connect to LMNT WebSocket and start receive task.""" await super()._connect() @@ -322,18 +312,22 @@ class LmntTTSService(InterruptibleTTSService): if isinstance(message, bytes): # Raw audio data await self.stop_ttfb_metrics() + context_id = self.get_active_audio_context_id() frame = TTSAudioRawFrame( audio=message, sample_rate=self.sample_rate, num_channels=1, - context_id=self.get_active_audio_context_id(), + context_id=context_id, ) - await self.push_frame(frame) + await self.append_to_audio_context(context_id, frame) else: try: msg = json.loads(message) if "error" in msg: - await self.push_frame(TTSStoppedFrame()) + context_id = self.get_active_audio_context_id() + await self.append_to_audio_context( + context_id, TTSStoppedFrame(context_id=context_id) + ) await self.stop_all_metrics() await self.push_error(error_msg=f"Error: {msg['error']}") return diff --git a/src/pipecat/services/neuphonic/tts.py b/src/pipecat/services/neuphonic/tts.py index 6fb9d3e28..1fad281d8 100644 --- a/src/pipecat/services/neuphonic/tts.py +++ b/src/pipecat/services/neuphonic/tts.py @@ -21,18 +21,14 @@ from loguru import logger from pydantic import BaseModel from pipecat.frames.frames import ( - BotStoppedSpeakingFrame, CancelFrame, EndFrame, ErrorFrame, Frame, - LLMFullResponseEndFrame, StartFrame, TTSAudioRawFrame, - TTSSpeakFrame, TTSStoppedFrame, ) -from pipecat.processors.frame_processor import FrameDirection from pipecat.services.settings import NOT_GIVEN, TTSSettings, _NotGiven from pipecat.services.tts_service import InterruptibleTTSService, TextAggregationMode, TTSService from pipecat.transcriptions.language import Language, resolve_language @@ -180,6 +176,7 @@ class NeuphonicTTSService(InterruptibleTTSService): text_aggregation_mode=text_aggregation_mode, push_stop_frames=True, push_start_frame=True, + pause_frame_processing=True, stop_frame_timeout_s=2.0, sample_rate=sample_rate, settings=default_settings, @@ -254,34 +251,6 @@ class NeuphonicTTSService(InterruptibleTTSService): msg = {"text": ""} await self._websocket.send(json.dumps(msg)) - async def push_frame(self, frame: Frame, direction: FrameDirection = FrameDirection.DOWNSTREAM): - """Push a frame downstream with special handling for stop conditions. - - Args: - frame: The frame to push. - direction: The direction to push the frame. - """ - await super().push_frame(frame, direction) - - async def process_frame(self, frame: Frame, direction: FrameDirection): - """Process frames with special handling for speech control. - - Args: - frame: The frame to process. - direction: The direction of frame processing. - """ - await super().process_frame(frame, direction) - - # If we received a TTSSpeakFrame and the LLM response included text (it - # might be that it's only a function calling response) we pause - # processing more frames until we receive a BotStoppedSpeakingFrame. - if isinstance(frame, TTSSpeakFrame): - await self.pause_processing_frames() - elif isinstance(frame, LLMFullResponseEndFrame): - await self.pause_processing_frames() - elif isinstance(frame, BotStoppedSpeakingFrame): - await self.resume_processing_frames() - async def _connect(self): """Connect to Neuphonic WebSocket and start background tasks.""" await super()._connect() @@ -366,10 +335,14 @@ class NeuphonicTTSService(InterruptibleTTSService): await self.stop_ttfb_metrics() audio = base64.b64decode(msg["data"]["audio"]) + context_id = self.get_active_audio_context_id() frame = TTSAudioRawFrame( - audio, self.sample_rate, 1, context_id=self.get_active_audio_context_id() + audio, + self.sample_rate, + 1, + context_id=context_id, ) - await self.push_frame(frame) + await self.append_to_audio_context(context_id, frame) async def _keepalive_task_handler(self): """Handle keepalive messages to maintain WebSocket connection.""" diff --git a/src/pipecat/services/rime/tts.py b/src/pipecat/services/rime/tts.py index aec5630b6..4dca789e5 100644 --- a/src/pipecat/services/rime/tts.py +++ b/src/pipecat/services/rime/tts.py @@ -1054,15 +1054,6 @@ class RimeNonJsonTTSService(InterruptibleTTSService): await super().cancel(frame) await self._disconnect() - async def push_frame(self, frame: Frame, direction: FrameDirection = FrameDirection.DOWNSTREAM): - """Push a frame downstream with special handling for stop conditions. - - Args: - frame: The frame to push. - direction: The direction to push the frame. - """ - await super().push_frame(frame, direction) - async def _connect(self): """Establish WebSocket connection and start receive task.""" await super()._connect() @@ -1153,13 +1144,14 @@ class RimeNonJsonTTSService(InterruptibleTTSService): if isinstance(message, bytes): await self.stop_ttfb_metrics() + context_id = self.get_active_audio_context_id() frame = TTSAudioRawFrame( audio=message, sample_rate=self.sample_rate, num_channels=1, - context_id=self.get_active_audio_context_id(), + context_id=context_id, ) - await self.push_frame(frame) + await self.append_to_audio_context(context_id, frame) except Exception as e: await self.push_error(error_msg=f"Error: {e}", exception=e) From da8070e98e9bd9d07da7f671cafcd33ae00b3b40 Mon Sep 17 00:00:00 2001 From: Mark Backman Date: Fri, 20 Mar 2026 10:46:36 -0400 Subject: [PATCH 1053/1060] Add changelog entry for #4090 --- changelog/4090.fixed.md | 1 + 1 file changed, 1 insertion(+) create mode 100644 changelog/4090.fixed.md diff --git a/changelog/4090.fixed.md b/changelog/4090.fixed.md new file mode 100644 index 000000000..ff42f09fe --- /dev/null +++ b/changelog/4090.fixed.md @@ -0,0 +1 @@ +- Fixed audio frame ordering and interruption handling in Fish Audio, LMNT, Neuphonic, and Rime NonJson TTS services. These services were bypassing the base `TTSService` audio context serialization queue by pushing audio frames directly, which could cause out-of-order frames and broken interruptions during speech. From a12ad273482fdaa1a59793a0cf154ea098e510af Mon Sep 17 00:00:00 2001 From: Varun Singh <382354+vr000m@users.noreply.github.com> Date: Fri, 20 Mar 2026 10:01:31 -0700 Subject: [PATCH 1054/1060] enable_dialout should not depend on sip_caller_phone being set (#4087) * enable_dialout should not depend on SIP being set * we still need room_prefix to have pipecat-sip, s/sip/telephony in room prefix --- src/pipecat/runner/daily.py | 6 ++++-- 1 file changed, 4 insertions(+), 2 deletions(-) diff --git a/src/pipecat/runner/daily.py b/src/pipecat/runner/daily.py index b9bcb6e3d..a60b84a6a 100644 --- a/src/pipecat/runner/daily.py +++ b/src/pipecat/runner/daily.py @@ -207,7 +207,7 @@ async def configure( return DailyRoomConfig(room_url=room_url, token=token) # Create a new room - room_prefix = "pipecat-sip" if sip_enabled else "pipecat" + room_prefix = "pipecat-telephony" if (sip_enabled or enable_dialout) else "pipecat" room_name = f"{room_prefix}-{uuid.uuid4().hex[:8]}" logger.info(f"Creating new Daily room: {room_name}") @@ -225,6 +225,9 @@ async def configure( if room_geo: room_properties.geo = room_geo + if enable_dialout: + room_properties.enable_dialout = True + # Add SIP configuration if enabled if sip_enabled: sip_params = DailyRoomSipParams( @@ -236,7 +239,6 @@ async def configure( provider=sip_provider, ) room_properties.sip = sip_params - room_properties.enable_dialout = enable_dialout room_properties.start_video_off = not sip_enable_video # Voice-only by default # Create room parameters From e5aaa4c4ebc6eda8d297140587cfaadd95498afb Mon Sep 17 00:00:00 2001 From: Mark Backman Date: Fri, 20 Mar 2026 13:12:40 -0400 Subject: [PATCH 1055/1060] fix: read system_instruction from _settings instead of removed attribute Replace adapter-based extraction in traced_llm with direct reads from _settings.system_instruction (priority) and context messages (fallback). The old approach had three bugs: signature mismatch with Anthropic adapter, key name inconsistency, and unnecessary overhead from full message/tools conversion. Also deduplicate the system instruction in spans -- it was appearing as both "system" and "param.system_instruction". --- changelog/3449.fixed.md | 2 +- .../utils/tracing/service_decorators.py | 42 ++++++++++++------- 2 files changed, 27 insertions(+), 17 deletions(-) diff --git a/changelog/3449.fixed.md b/changelog/3449.fixed.md index a8663e004..7cf01c0cb 100644 --- a/changelog/3449.fixed.md +++ b/changelog/3449.fixed.md @@ -1 +1 @@ -- Fixed telemetry record correct system_instruction in span for LLM services +- Fixed stale `system_instruction` in LLM tracing spans by reading from `_settings.system_instruction` instead of the removed `_system_instruction` attribute. diff --git a/src/pipecat/utils/tracing/service_decorators.py b/src/pipecat/utils/tracing/service_decorators.py index 0b63989ea..2b189feb5 100644 --- a/src/pipecat/utils/tracing/service_decorators.py +++ b/src/pipecat/utils/tracing/service_decorators.py @@ -502,35 +502,45 @@ def traced_llm(func: Optional[Callable] = None, *, name: Optional[str] = None) - # Handle system message for different services system_message = None - # Handle system message for different services if isinstance(context, LLMContext): - # Universal LLMContext - use adapter to convert and get system message - if hasattr(self, "get_llm_adapter"): - adapter = self.get_llm_adapter() - try: - # Get LLM invocation params which includes system_instruction - params = adapter.get_llm_invocation_params(context) + # settings.system_instruction takes priority (matches service behavior) + if hasattr(self, "_settings") and getattr( + self._settings, "system_instruction", None + ): + system_message = self._settings.system_instruction + else: + # Fall back to extracting from context messages + ctx_messages = context.get_messages() + if ctx_messages: + first = ctx_messages[0] if ( - isinstance(params, dict) - and "system_instruction" in params + isinstance(first, dict) + and first.get("role") == "system" ): - system_message = params["system_instruction"] - except Exception as e: - logging.debug( - f"Could not extract system instruction from adapter: {e}" - ) + content = first.get("content") + if isinstance(content, str): + system_message = content + elif isinstance(content, list): + system_message = " ".join( + part.get("text", "") + for part in content + if isinstance(part, dict) + and part.get("type") == "text" + ) elif hasattr(context, "system"): system_message = context.system elif hasattr(context, "system_message"): system_message = context.system_message - elif hasattr(self, "_system_instruction"): - system_message = self._system_instruction # Use given_fields() defensively in case a service doesn't # initialize all settings. params = {} if hasattr(self, "_settings"): for key, value in self._settings.given_fields().items(): + # system_instruction is already captured as the + # "system" span attribute above. + if key == "system_instruction": + continue if isinstance(value, (int, float, bool, str)): params[key] = value elif value is None: From b5c362d6e61afaa0d2ac1dc958ef68da5be78241 Mon Sep 17 00:00:00 2001 From: Mark Backman Date: Fri, 20 Mar 2026 13:20:03 -0400 Subject: [PATCH 1056/1060] refactor: rename tracing span attribute "system" to "system_instructions" Align with the OpenTelemetry GenAI semantic convention gen_ai.system_instructions for system prompts. The old "system" attribute name was unrelated to gen_ai.system (which is for provider name). --- changelog/3449.changed.md | 1 + src/pipecat/utils/tracing/service_attributes.py | 8 ++++---- src/pipecat/utils/tracing/service_decorators.py | 4 ++-- 3 files changed, 7 insertions(+), 6 deletions(-) create mode 100644 changelog/3449.changed.md diff --git a/changelog/3449.changed.md b/changelog/3449.changed.md new file mode 100644 index 000000000..d06ad37c4 --- /dev/null +++ b/changelog/3449.changed.md @@ -0,0 +1 @@ +- Renamed tracing span attribute `system` to `system_instructions` to align with the OpenTelemetry GenAI semantic conventions. diff --git a/src/pipecat/utils/tracing/service_attributes.py b/src/pipecat/utils/tracing/service_attributes.py index 21a22341f..1a6537f2b 100644 --- a/src/pipecat/utils/tracing/service_attributes.py +++ b/src/pipecat/utils/tracing/service_attributes.py @@ -193,7 +193,7 @@ def add_llm_span_attributes( tools: Optional[str] = None, tool_count: Optional[int] = None, tool_choice: Optional[str] = None, - system: Optional[str] = None, + system_instructions: Optional[str] = None, parameters: Optional[Dict[str, Any]] = None, extra_parameters: Optional[Dict[str, Any]] = None, ttfb: Optional[float] = None, @@ -211,7 +211,7 @@ def add_llm_span_attributes( tools: JSON-serialized tools configuration. tool_count: Number of tools available. tool_choice: Tool selection configuration. - system: System message. + system_instructions: System instructions. parameters: Service parameters. extra_parameters: Additional parameters. ttfb: Time to first byte in seconds. @@ -240,8 +240,8 @@ def add_llm_span_attributes( if tool_choice: span.set_attribute("tool_choice", tool_choice) - if system: - span.set_attribute("system", system) + if system_instructions: + span.set_attribute("system_instructions", system_instructions) if ttfb is not None: span.set_attribute("metrics.ttfb", ttfb) diff --git a/src/pipecat/utils/tracing/service_decorators.py b/src/pipecat/utils/tracing/service_decorators.py index 2b189feb5..2e54732f1 100644 --- a/src/pipecat/utils/tracing/service_decorators.py +++ b/src/pipecat/utils/tracing/service_decorators.py @@ -538,7 +538,7 @@ def traced_llm(func: Optional[Callable] = None, *, name: Optional[str] = None) - if hasattr(self, "_settings"): for key, value in self._settings.given_fields().items(): # system_instruction is already captured as the - # "system" span attribute above. + # "system_instructions" span attribute above. if key == "system_instruction": continue if isinstance(value, (int, float, bool, str)): @@ -561,7 +561,7 @@ def traced_llm(func: Optional[Callable] = None, *, name: Optional[str] = None) - attribute_kwargs["tools"] = serialized_tools attribute_kwargs["tool_count"] = tool_count if system_message: - attribute_kwargs["system"] = system_message + attribute_kwargs["system_instructions"] = system_message # Add all gathered attributes to the span add_llm_span_attributes(span=current_span, **attribute_kwargs) From c89e36673912839fb2c5262ac6ecf2d231591545 Mon Sep 17 00:00:00 2001 From: Mark Backman Date: Fri, 20 Mar 2026 13:36:20 -0400 Subject: [PATCH 1057/1060] refactor: align tracing attributes with OpenTelemetry GenAI conventions - gen_ai.system -> gen_ai.provider.name (deprecated) - system / system_instructions -> gen_ai.system_instructions - gen_ai.usage.cache_read_input_tokens -> gen_ai.usage.cache_read.input_tokens - gen_ai.usage.cache_creation_input_tokens -> gen_ai.usage.cache_creation.input_tokens --- changelog/3449.changed.md | 2 +- .../utils/tracing/service_attributes.py | 22 +++++++++---------- .../utils/tracing/service_decorators.py | 8 +++---- 3 files changed, 16 insertions(+), 16 deletions(-) diff --git a/changelog/3449.changed.md b/changelog/3449.changed.md index d06ad37c4..d5ea2f6d7 100644 --- a/changelog/3449.changed.md +++ b/changelog/3449.changed.md @@ -1 +1 @@ -- Renamed tracing span attribute `system` to `system_instructions` to align with the OpenTelemetry GenAI semantic conventions. +- Renamed tracing span attributes to align with OpenTelemetry GenAI semantic conventions: `gen_ai.system` to `gen_ai.provider.name`, `system` to `gen_ai.system_instructions`, `gen_ai.usage.cache_read_input_tokens` to `gen_ai.usage.cache_read.input_tokens`, and `gen_ai.usage.cache_creation_input_tokens` to `gen_ai.usage.cache_creation.input_tokens`. diff --git a/src/pipecat/utils/tracing/service_attributes.py b/src/pipecat/utils/tracing/service_attributes.py index 1a6537f2b..e5cf4a83f 100644 --- a/src/pipecat/utils/tracing/service_attributes.py +++ b/src/pipecat/utils/tracing/service_attributes.py @@ -25,20 +25,20 @@ if is_tracing_available(): from opentelemetry.trace import Span -def _get_gen_ai_system_from_service_name(service_name: str) -> str: - """Extract the standardized gen_ai.system value from a service class name. +def _get_provider_name_from_service_name(service_name: str) -> str: + """Extract the standardized gen_ai.provider.name value from a service class name. Source: - https://opentelemetry.io/docs/specs/semconv/attributes-registry/gen-ai/#gen-ai-system + https://opentelemetry.io/docs/specs/semconv/attributes-registry/gen-ai/ Uses standard OTel names where possible, with special case mappings for service names that don't follow the pattern. Args: - service_name: The service class name to extract system name from. + service_name: The service class name to extract provider name from. Returns: - The standardized gen_ai.system value. + The standardized gen_ai.provider.name value. """ SPECIAL_CASE_MAPPINGS = { # AWS @@ -91,7 +91,7 @@ def add_tts_span_attributes( **kwargs: Additional attributes to add. """ # Add standard attributes - span.set_attribute("gen_ai.system", service_name.replace("TTSService", "").lower()) + span.set_attribute("gen_ai.provider.name", service_name.replace("TTSService", "").lower()) span.set_attribute("gen_ai.request.model", model) span.set_attribute("gen_ai.operation.name", operation_name) span.set_attribute("gen_ai.output.type", "speech") @@ -150,7 +150,7 @@ def add_stt_span_attributes( **kwargs: Additional attributes to add. """ # Add standard attributes - span.set_attribute("gen_ai.system", service_name.replace("STTService", "").lower()) + span.set_attribute("gen_ai.provider.name", service_name.replace("STTService", "").lower()) span.set_attribute("gen_ai.request.model", model) span.set_attribute("gen_ai.operation.name", operation_name) span.set_attribute("vad_enabled", vad_enabled) @@ -218,7 +218,7 @@ def add_llm_span_attributes( **kwargs: Additional attributes to add. """ # Add standard attributes - span.set_attribute("gen_ai.system", _get_gen_ai_system_from_service_name(service_name)) + span.set_attribute("gen_ai.provider.name", _get_provider_name_from_service_name(service_name)) span.set_attribute("gen_ai.request.model", model) span.set_attribute("gen_ai.operation.name", "chat") span.set_attribute("gen_ai.output.type", "text") @@ -241,7 +241,7 @@ def add_llm_span_attributes( span.set_attribute("tool_choice", tool_choice) if system_instructions: - span.set_attribute("system_instructions", system_instructions) + span.set_attribute("gen_ai.system_instructions", system_instructions) if ttfb is not None: span.set_attribute("metrics.ttfb", ttfb) @@ -313,7 +313,7 @@ def add_gemini_live_span_attributes( **kwargs: Additional attributes to add. """ # Add standard attributes - span.set_attribute("gen_ai.system", "gcp.gemini") + span.set_attribute("gen_ai.provider.name", "gcp.gemini") span.set_attribute("gen_ai.request.model", model) span.set_attribute("gen_ai.operation.name", operation_name) span.set_attribute("service.operation", operation_name) @@ -414,7 +414,7 @@ def add_openai_realtime_span_attributes( **kwargs: Additional attributes to add. """ # Add standard attributes - span.set_attribute("gen_ai.system", "openai") + span.set_attribute("gen_ai.provider.name", "openai") span.set_attribute("gen_ai.request.model", model) span.set_attribute("gen_ai.operation.name", operation_name) span.set_attribute("service.operation", operation_name) diff --git a/src/pipecat/utils/tracing/service_decorators.py b/src/pipecat/utils/tracing/service_decorators.py index 2e54732f1..cc353e1a3 100644 --- a/src/pipecat/utils/tracing/service_decorators.py +++ b/src/pipecat/utils/tracing/service_decorators.py @@ -137,14 +137,14 @@ def _add_token_usage_to_span(span, token_usage): and token_usage["cache_read_input_tokens"] is not None ): span.set_attribute( - "gen_ai.usage.cache_read_input_tokens", token_usage["cache_read_input_tokens"] + "gen_ai.usage.cache_read.input_tokens", token_usage["cache_read_input_tokens"] ) if ( "cache_creation_input_tokens" in token_usage and token_usage["cache_creation_input_tokens"] is not None ): span.set_attribute( - "gen_ai.usage.cache_creation_input_tokens", + "gen_ai.usage.cache_creation.input_tokens", token_usage["cache_creation_input_tokens"], ) if "reasoning_tokens" in token_usage and token_usage["reasoning_tokens"] is not None: @@ -159,11 +159,11 @@ def _add_token_usage_to_span(span, token_usage): # Add cached token metrics for LLMTokenUsage object cache_read_tokens = getattr(token_usage, "cache_read_input_tokens", None) if cache_read_tokens is not None: - span.set_attribute("gen_ai.usage.cache_read_input_tokens", cache_read_tokens) + span.set_attribute("gen_ai.usage.cache_read.input_tokens", cache_read_tokens) cache_creation_tokens = getattr(token_usage, "cache_creation_input_tokens", None) if cache_creation_tokens is not None: - span.set_attribute("gen_ai.usage.cache_creation_input_tokens", cache_creation_tokens) + span.set_attribute("gen_ai.usage.cache_creation.input_tokens", cache_creation_tokens) reasoning_tokens = getattr(token_usage, "reasoning_tokens", None) if reasoning_tokens is not None: From bc0e7130b8c6b6365e4ff73c5de66c2d9d38f700 Mon Sep 17 00:00:00 2001 From: Pablo Ois Lagarde Date: Fri, 20 Mar 2026 16:37:53 -0300 Subject: [PATCH 1058/1060] fix: always include parameters field in Genesys AudioHook messages The AudioHook protocol requires every message to carry a `parameters` object. `_create_message` conditionally included it only when parameters were truthy, so pong responses and closed responses without outputVariables were sent without the field. Clients that validate message structure (including the Genesys reference implementation) rejected these messages, which broke server sequence tracking and prevented outputVariables from reaching the Architect flow. Co-Authored-By: Claude Opus 4.6 (1M context) --- changelog/0000.fixed.md | 7 +++++++ src/pipecat/serializers/genesys.py | 3 +-- tests/genesys/test_genesys_serializer.py | 3 ++- 3 files changed, 10 insertions(+), 3 deletions(-) create mode 100644 changelog/0000.fixed.md diff --git a/changelog/0000.fixed.md b/changelog/0000.fixed.md new file mode 100644 index 000000000..39fabc029 --- /dev/null +++ b/changelog/0000.fixed.md @@ -0,0 +1,7 @@ +- Fixed Genesys AudioHook serializer to always include the `parameters` field in + protocol messages. The AudioHook protocol requires every message to carry a + `parameters` object (even if empty), but `_create_message` omitted it when no + parameters were provided. This caused clients that validate message structure + (including the Genesys reference implementation) to reject `pong` and + parameter-less `closed` responses, breaking server sequence tracking and + preventing `outputVariables` from reaching the Architect flow. diff --git a/src/pipecat/serializers/genesys.py b/src/pipecat/serializers/genesys.py index 2cc3c32db..4e0c11504 100644 --- a/src/pipecat/serializers/genesys.py +++ b/src/pipecat/serializers/genesys.py @@ -336,8 +336,7 @@ class GenesysAudioHookSerializer(FrameSerializer): if include_position: msg["position"] = self._format_position(self._position) - if parameters: - msg["parameters"] = parameters + msg["parameters"] = parameters if parameters is not None else {} return msg diff --git a/tests/genesys/test_genesys_serializer.py b/tests/genesys/test_genesys_serializer.py index 03132d7cb..1f63ae94e 100644 --- a/tests/genesys/test_genesys_serializer.py +++ b/tests/genesys/test_genesys_serializer.py @@ -76,6 +76,7 @@ class TestGenesysAudioHookSerializer: assert msg["type"] == "pong" assert msg["id"] == serializer.session_id + assert msg["parameters"] == {} def test_create_closed_response(self): """Test creating a closed response message.""" @@ -86,7 +87,7 @@ class TestGenesysAudioHookSerializer: assert msg["type"] == "closed" assert serializer.is_open is False - assert "parameters" not in msg # No parameters when no output_variables + assert msg["parameters"] == {} # Empty parameters when no output_variables def test_create_closed_response_with_output_variables(self): """Test creating a closed response with custom output variables.""" From 53e0136366eed70d84dafa707054e02e12a9c3d1 Mon Sep 17 00:00:00 2001 From: Pablo Ois Lagarde Date: Fri, 20 Mar 2026 16:46:35 -0300 Subject: [PATCH 1059/1060] chore: rename changelog fragment to PR #4093 Co-Authored-By: Claude Opus 4.6 (1M context) --- changelog/{0000.fixed.md => 4093.fixed.md} | 0 1 file changed, 0 insertions(+), 0 deletions(-) rename changelog/{0000.fixed.md => 4093.fixed.md} (100%) diff --git a/changelog/0000.fixed.md b/changelog/4093.fixed.md similarity index 100% rename from changelog/0000.fixed.md rename to changelog/4093.fixed.md From 622ebd5d74bcbc43c909d72e27d43de2a25bab64 Mon Sep 17 00:00:00 2001 From: Mark Backman Date: Sat, 21 Mar 2026 07:02:06 -0400 Subject: [PATCH 1060/1060] Update MiniMaxHttpTTSService platform docs link --- src/pipecat/services/minimax/tts.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/src/pipecat/services/minimax/tts.py b/src/pipecat/services/minimax/tts.py index d41fb6255..46502409d 100644 --- a/src/pipecat/services/minimax/tts.py +++ b/src/pipecat/services/minimax/tts.py @@ -137,7 +137,7 @@ class MiniMaxHttpTTSService(TTSService): Supports real-time audio streaming with configurable voice parameters. Platform documentation: - https://www.minimax.io/platform/document/T2A%20V2?key=66719005a427f0c8a5701643 + https://platform.minimax.io/docs/api-reference/speech-t2a-http """ Settings = MiniMaxTTSSettings